diff --git a/layer3/data/tmp.json b/layer3/data/tmp.json new file mode 100644 index 0000000..292919a --- /dev/null +++ b/layer3/data/tmp.json @@ -0,0 +1,9378 @@ +[ + { + "id": "10.1126_science.aaa9272", + "DOI": "10.1126/science.aaa9272", + "DOI Link": "http://dx.doi.org/10.1126/science.aaa9272", + "Relative Dir Path": "mds/10.1126_science.aaa9272", + "Article Title": "High-performance photovoltaic perovskite layers fabricated through intramolecular exchange", + "Authors": "Yang, WS; Noh, JH; Jeon, NJ; Kim, YC; Ryu, S; Seo, J; Seok, SI", + "Source Title": "SCIENCE", + "Abstract": "The band gap of formamidinium lead iodide (FAPbI(3)) perovskites allows broader absorption of the solar spectrum relative to conventional methylammonium lead iodide (MAPbI(3)). Because the optoelectronic properties of perovskite films are closely related to film quality, deposition of dense and uniform films is crucial for fabricating high-performance perovskite solar cells (PSCs). We report an approach for depositing high-quality FAPbI(3) films, involving FAPbI(3) crystallization by the direct intramolecular exchange of dimethylsulfoxide (DMSO) molecules intercalated in PbI2 with formamidinium iodide. This process produces FAPbI(3) films with (111)-preferred crystallographic orientation, large-grained dense microstructures, and flat surfaces without residual PbI2. Using films prepared by this technique, we fabricated FAPbI(3)-based PSCs with maximum power conversion efficiency greater than 20%.", + "Times Cited, WoS Core": 5584, + "Times Cited, All Databases": 5939, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000356011500049", + "Markdown": "14. A. S. Aricò, P. Bruce, B. Scrosati, J. M. Tarascon, W. van Schalkwijk, Nat. Mater. 4, 366–377 (2005). \n15. S. Guo, S. Zhang, S. Sun, Angew. Chem. Int. Ed. Engl. 52, 8526–8544 (2013). \n16. J. Wu, A. Gross, H. Yang, Nano Lett. 11, 798–802 (2011). \n17. J. Zhang, J. Fang, J. Am. Chem. Soc. 131, 18543–18547 (2009). \n18. Y. Kang, C. B. Murray, J. Am. Chem. Soc. 132, 7568–7569 (2010). \n19. Y. Wu, S. Cai, D. Wang, W. He, Y. Li, J. Am. Chem. Soc. 134, 8975–8981 (2012). \n20. D. Wang et al., Nat. Mater. 12, 81–87 (2013). \n21. S. I. Choi et al., Nano Lett. 13, 3420–3425 (2013). \n22. J. Zhang, H. Yang, J. Fang, S. Zou, Nano Lett. 10, 638–644 (2010). \n23. X. Huang et al., Adv. Mater. 25, 2974–2979 (2013). \n24. C. Cui, L. Gan, M. Heggen, S. Rudi, P. Strasser, Nat. Mater. 12, 765–771 (2013). \n25. M. K. Carpenter, T. E. Moylan, R. S. Kukreja, M. H. Atwan, M. M. Tessema, J. Am. Chem. Soc. 134, 8535–8542 (2012). \n26. J. Snyder, I. McCue, K. Livi, J. Erlebacher, J. Am. Chem. Soc. 134, 8633–8645 (2012). \n27. H. Zhu, S. Zhang, S. Guo, D. Su, S. Sun, J. Am. Chem. Soc. 135, 7130–7133 (2013). \n28. C. Chen et al., Science 343, 1339–1343 (2014). \n29. K. Ahrenstorf et al., Small 3, 271–274 (2007). \n30. Y. Wu et al., Angew. Chem. Int. Ed. Engl. 51, 12524–12528 (2012). \n31. Z. Liu et al., J. Am. Chem. Soc. 131, 6924–6925 (2009). \n32. B. Lim et al., Science 324, 1302–1305 (2009). \n33. J. M. Sanchez, F. Ducastelle, D. Gratias, Physica A 128, 334–350 (1984). \n34. N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, E. Teller, J. Chem. Phys. 21, 1087–1092 (1953). \n35. T. Mueller, G. Ceder, Phys. Rev. B 80, 024103 (2009). \n36. W. Kohn, L. J. Sham, Phys. Rev. 140 (4A), A1133–A1138 (1965). \n37. J. Rossmeisl, G. S. Karlberg, T. Jaramillo, J. K. Nørskov, Faraday Discuss. 140, 337–346 (2009). \n38. K. Momma, F. Izumi, J. Appl. Cryst. 41, 653–658 (2008). \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge support from the National Science Foundation (NSF) through award DMR-1437263 on catalysis studies and the Office of Naval Research (ONR) under award N00014-15-1-2146 for synthesis efforts. Computational studies were supported by the NSF through award DMR-1352373 and using computationa resources provided by Extreme Science and Engineering Development Environment (XSEDE) through awards DMR130056 and DMR140068. Atomic-scale structural images were generated by using VESTA (38). We thank the Director, Office of Energy Research, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, of the U.S. Department of Energy under contract DE-AC02-05CH11231, under the $\\boldsymbol{s p^{2}}$ -bonded materials program, for TEM analytical measurements performed at the National Center for Electron Microscopy at the Lawrence Berkeley National Laboratory. X.D. acknowledges support from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Science and Engineering through award DE-SC0008055. The work at LLNL was performed under the auspices of the U.S. Department of Energy under contract DE-AC52-07NA27344. A.Y. and A.Z. received additional support from NSF grant EEC-083219 within the Center of Integrated Nanomechanical Systems. We also thank the Electron Imaging Center of Nanomachines at CNSI for TEM support. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/348/6240/1230/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S17 \nTables S1 to S2 \nReferences (39–53) \n\n# SOLAR CELLS \n\n# High-performance photovoltaic perovskite layers fabricated through intramolecular exchange \n\nWoon Seok Yang,1\\* Jun Hong Noh,1\\* Nam Joong Jeon,1 Young Chan Kim,1 Seungchan Ryu,1 Jangwon Seo,1 Sang Il Seok1,2† \n\nThe band gap of formamidinium lead iodide $(F A P b l_{3})$ perovskites allows broader absorption of the solar spectrum relative to conventional methylammonium lead iodide $(M A P b\\mathsf{I}_{3})$ . Because the optoelectronic properties of perovskite films are closely related to film quality, deposition of dense and uniform films is crucial for fabricating high-performance perovskite solar cells (PSCs). We report an approach for depositing high-quality $\\mathsf{F A P b l}_{3}$ films, involving $\\mathsf{F A P b l}_{3}$ crystallization by the direct intramolecular exchange of dimethylsulfoxide (DMSO) molecules intercalated in $\\mathsf{P b l}_{2}$ with formamidinium iodide. This process produces $\\mathsf{F A P b l}_{3}$ films with (111)-preferred crystallographic orientation, large-grained dense microstructures, and flat surfaces without residual $\\mathsf{P b l}_{2}$ . Using films prepared by this technique, we fabricated $\\mathsf{F A P b l}_{3}$ -based PSCs with maximum power conversion efficiency greater than $20\\%$ . \n\nT cheitreectmureen(d1o–u3s),ihmigphr-oqvueamlietyntfislimn fdoervmicaetiaorn- methodologies (4–6), and compositional engineering of perovskite materials (7–9) over the past 3 years have led to rapid improvements in the power conversion efficiency (PCE) of perovskite solar cells (PSCs). Although solarto-electric PCEs of up to $18\\%$ have been reported for PSCs (10), developing technologies further to achieve PCEs near theoretical values $(>30\\%)$ ) continues to be an important challenge in making the solar cell industry economically competitive. \n\nFormamidinium lead iodide $\\mathrm{(FAPbI_{3})}$ is a perovskite material that can potentially provide better performance than methylammonium lead iodide $\\mathrm{(MAPbI_{3})}$ ) because of its broad absorption of the solar spectrum. In addition, $\\mathrm{FAPbI_{3}}$ with the n-i-p architecture (the n-side is illuminated with solar radiation) exhibits negligible hysteresis with sweep direction during current-voltage measurements (8–13). However, it is more difficult to form stable perovskite phases and highquality films with $\\mathrm{FAPbI_{3}}$ than with $\\mathbf{MAPbI_{3}}$ . \n\nVarious methodologies such as sequential deposition $\\left(4\\right)$ , solvent engineering (5), vapor-assisted deposition $(I4),$ additive-assisted deposition $(I5,I6),$ , and vacuum evaporation $\\textcircled{6}$ can now produce high-quality films of $\\mathbf{MAPbI_{3}}$ with flat surfaces and complete surface coverage by controlling its rapid crystallization behavior and have led to substantial improvements in the PCE of $\\mathbf{MAPbI_{3}}$ - based PSCs. \n\nAmong these methodologies, two-step sequential deposition and solvent engineering are representative wet processes that can yield perovskite films for high-performance PSCs. In the sequential deposition process, a thin layer of $\\mathrm{PbI_{2}}$ is deposited on the substrate; methylammonium iodide (MAI) or formamidinium iodide (FAI) is then applied to the predeposited $\\mathrm{PbI_{2}}$ to enable conversion to the perovskite phase. This process involves crystal nucleation and growth of the perovskite phase because of solution-phase or solidstate reaction between $\\mathrm{PbI_{2}}$ and an organic iodide such as MAI or FAI (4, 13, 17, 18). However, the sequential reaction of organic iodides with $\\mathrm{PbI_{2}}$ that occurs from the surface to the inner crystalline regions of $\\mathrm{PbI_{2}}$ has been ineffective in producing high-performance perovskite films that are ${>}500\\ \\mathrm{nm}$ in thickness because of incomplete conversion of $\\mathrm{PbI_{2}},$ peeling off of the perovskite film in solution, and uncontrolled surface roughness. In contrast, the solvent-engineering process uses the formation of intermediate phases to retard the rapid reaction between $\\mathrm{PbI_{2}}$ and organic iodide in the solution. Although this process has been successfully used to form dense and uniform $\\mathbf{MAPbI_{3}}$ layers, it has not been explored for $\\mathrm{FAPbI_{3}}$ (5). \n\nTable 1. Comparison of layer thickness before and after $\\mathsf{F A P b l}_{3}$ phase is formed by conventional and intramolecular exchange process (IEP). The thin $\\mathsf{P b l}_{2}$ and $\\mathsf{P b l}_{2}(\\mathsf{D M S O})$ layers were deposited on a fused quartz glass, and their layer thickness was measured by alpha-step IQ surface profiler. \n\n\n
MethodBeforeAfter
Conventional process (Pbl2)290 nm570 nm
IEP [Pbl2(DMSO)]510 nm560 nm
\n\nTo deposit a uniform and dense $\\mathrm{FAPbI_{3}}$ layer, Snaith et al. added a small amount of aqueous hydrogen iodide (HI) to a solution mixture containing $\\mathrm{PbI_{2}}$ , FAI, and dimethylformamide (DMF) (11). Very recently, Zhao et al. reported the deposition of highly uniform and fully covered $\\mathrm{FAPbI_{3}}$ films using FAI and $\\mathrm{\\cdot_{HPbl_{3}}},$ which is formed by the reaction of $\\mathrm{PbI_{2}}$ and HI in DMF (19). The HI in the $\\mathrm{PbI_{2}}$ layers retards the rapid reaction between FAI and $\\mathrm{PbI_{2}}$ . In addition, the release of HI from $\\mathrm{PbI_{2}}$ at high temperatures allows the formation of a $\\mathrm{FAPbI_{3}}$ layer by solid-state reaction with the neighboring FAI molecules. Stated differently, this process can be regarded as the transformation of $\\mathrm{PbI_{2}\\mathrm{-HI\\mathrm{-FAI}}}$ into $\\mathrm{FAPbI_{3}},$ similar to the formation of $\\mathbf{MAPbI_{3}}$ via the $\\mathrm{PbI_{2}}$ –dimethylsulfoxide (DMSO)–MAI phase in the solvent-engineering process (5). \n\nHowever, we observed that the solventengineering process, which is effective for depositing dense and uniform $\\mathbf{MAPbI_{3}}$ layers, yields $\\mathrm{FAPbI_{3}}$ layers with pinholes and a rough surface. Although aspects of $\\mathrm{FAPbI_{3}}$ film quality, including coverage and uniformity on the substrate, have been improved, the performance of $\\mathrm{FAPbI_{3}}$ solar cells still lags behind that of $\\mathrm{\\mathbf{MAPbI_{3}}}$ -based PSCs (8), implying that more sophisticated deposition techniques are necessary for fabricating highquality, thick $\\mathrm{FAPbI_{3}}$ films ${\\bf\\zeta}>500{\\bf n m}),$ that would enable sufficient absorption up to a wavelength of $840~\\mathrm{{nm}}$ . \n\n![](images/d705e11b0d6cfa8f47714d14145b60c7558d988f71f716d21bd4e1b2f8723b7a.jpg) \nperovskite crys$\\mathsf{P b l}_{2}$ complex soluby IEP, \nFig. 2. SEM observations and J-V and EQE measurements. (A) Cross-sectional FESEM image of the device consisting of FTO-glass/bl-TiO2/mp-TiO2/ perovskite/PTAA/Au. (B) The comparison of FESEM surface images of $\\mathsf{F A P b l}_{3}$ -based layer formed on mp- $\\mathsf{T i O}_{2}$ by IEP and conventional method. (C) (a) J-V curves of best device measured with a $40-m s$ scanning delay in reverse (from $1.2\\ V$ to $0\\veebar$ ) and forward (from 0 V to $1.2\\ V.$ ) modes under standard AM 1.5G illumination, and (b) EQE spectra for best device and integrated $J_{\\mathsf{S C}}$ . \n\nAs expected from the conversion of $\\mathrm{PbI_{2}(D M S O)-}$ MAI to $\\mathbf{MAPbI_{3}}$ (5), the DMSO molecules intercalated in $\\mathrm{PbI_{2}}$ can be easily replaced by external FAIs because of their higher affinity toward $\\mathrm{PbI_{2}}$ relative to DMSO; the FAI molecules experience ionic interactions, whereas DMSO participates in van der Waals interactions $(5,20)$ . Highly uniform and dense predeposited $\\mathrm{PbI_{2}}.$ DMSO layers could be directly converted to $\\mathrm{FAPbI_{3}}$ because the inorganic $\\mathrm{PbI_{2}}$ framework would be retained. $\\mathrm{FAPbI_{3}}$ crystallization by the intramolecular exchange process (IEP) of DMSO intercalated in $\\mathrm{PbI_{2}}$ with FAI was schematically shown in Fig. 1A. The intramolecular exchange between DMSO and FAI can be described as \n\n$$\n\\begin{array}{r}{\\mathrm{\\bI_{2}\\mathrm{-DMSO+FAI\\rightarrow}}}\\\\ {\\mathrm{\\PbI_{2}\\mathrm{-FAI+DMSO\\uparrow\\(removal)}}}\\end{array}\n$$ \n\nand does not induce volume expansion, unlike the $\\mathrm{FAPbI_{3}}$ formed with FAI intercalating into pristine $\\mathrm{PbI_{2}}$ (discussed below), because the molecular sizes of DMSO and FAI are similar. \n\nIn this work, we report on the synthesis of a $\\mathrm{PbI_{2}(D M S O)}$ precursor with excellent capabilities for molecular exchange with FAI at low temperatures during the spinning process, as well as the fabrication of highly efficient $\\mathrm{FAPbI_{3}}$ - based PSCs with certified PCEs exceeding $20\\%$ . To synthesize the $\\mathrm{PbI_{2}(D M S O)}$ precursors, we obtained precipitates by pouring toluene as a nonsolvent into $\\mathbf{1.0\\:M\\:PbI_{2}}$ solution dissolved in DMSO. The x-ray diffraction (XRD) pattern of the resulting complex [Fig. 1B(a)] matched that of the $\\mathrm{PbI_{2}(D M S O)_{2}}$ phase (5, 20). The as-prepared $\\mathrm{PbI_{2}(D M S O)_{2}}$ was then annealed at $60^{\\circ}\\mathrm{C}$ for 24 hours in vacuum to obtain $\\mathrm{PbI_{2}(D M S O)}$ by removal of 1 mol DMSO. The XRD pattern of the vacuum-annealed powder [Fig. 1B(b)] did not match that of $\\mathrm{PbI_{2}(D M S O)_{2}}$ , implying that the $\\mathrm{PbI_{2}(D M S O)_{2}}$ transformed into a different phase by releasing some DMSO molecules. The content of DMSO in the as-annealed powder was estimated by thermogravimetric analysis (TGA). TGA was suitable for this purpose because the only volatile species in the powder was DMSO. The TGA results of the $\\mathrm{PbI_{2}(D M S O)_{2}}$ and $\\mathrm{PbI_{2}(D M S O)}$ complexes are shown in Fig. 1C. The $\\mathrm{PbI_{2}(D M S O)_{2}}$ complex exhibited a two-step decomposition process with weight loss of $12.6\\%$ at each step, whereas the vacuumannealed $\\mathrm{PbI_{2}(D M S O)}$ complex showed a singlestep decomposition. The decomposition of both the complexes was completed at the same temperature $(\\mathrm{138.6^{\\circ}C})$ . The powders obtained by vacuum-annealing $\\mathrm{PbI_{2}(D M S O)_{2}}$ complex at $60^{\\circ}\\mathrm{C}$ can be regarded as one of the most thermodynamically stable forms among the various crystalline $\\mathrm{PbI_{2}(D M S O)}$ -based complexes, which are similar to those of $\\mathrm{PbBr_{2}(D M S O)}$ and $\\mathrm{PbCl_{2}(D M S O)}$ (21). The DMSO content of the vacuum-annealed $\\mathrm{PbI_{2}(D M S O)}$ ) complex was also checked by elemental analysis, which yielded $\\mathrm{H}=1.0\\%$ $(1.1\\%)$ ; and $\\mathrm{C}=4.1\\%$ $(4.4\\%)$ , where the values expressed in parentheses indicate the theoretical mass percent for a given element in $\\mathrm{C_{2}H_{6}S O P b I_{2}}$ . \n\nTo fabricate $\\mathrm{FAPbI_{3}}$ -based PSCs through IEP between DMSO and FAI (MABr) using predeposited $\\mathrm{PbI_{2}(D M S O)}$ ) layers and a FAI (MABr) solution, we first confirmed that the $\\mathrm{PbI_{2}(D M S O)}$ phase was retained even after spin-coating with the $\\mathrm{PbI_{2}(D M S O)}$ precursor dissolved in DMF. The XRD pattern for film coated on a fused silica substrate was compared with that of the initial precursor. As seen in Fig. 1B(c), the \n\nXRD pattern for the as-coated film was consistent with that of the $\\mathrm{PbI_{2}(D M S O)}$ complex powder, although its crystallinity was lower. The as-coated $\\mathrm{PbI_{2}(D M S O)}$ film also had a flat and dense surface, as shown in the field emission scanning electron microscopy (FESEM) image in fig. S1 (22). Next, we investigated the formation of mixed $\\mathrm{FAPbI_{3}/M A P b B r_{3}}$ by IEP. We recently reported that the coexistence of MA/FA/I/Br in the $\\mathrm{PbI_{2}}$ skeleton improved the phase stability of $\\mathrm{FAPbI_{3}}$ (10). The formation of mixed $\\mathrm{FAPbI_{3}/M A P b B r_{3}}$ layers via IEP was controlled by coating the solution mixture with different weight ratios of MABr to FAI, dissolved in isopropyl alcohol, on the predeposited $\\mathrm{PbI_{2}(D M S O)}$ layers (see below). It is evident from Fig. 1D(a) that well-crystallized $\\mathrm{FAPbI_{3}}$ -based films were formed by IEP. The XRD pattern for the $\\mathrm{FAPbI_{3}}$ film derived from the $\\mathrm{PbI_{2}(D M S O)}$ complex film exhibits dominant (–111) and (–222) diffraction peaks at $13.9^{\\circ}$ and 28.1°, respectively, corresponding to the $\\mathrm{FAPbI_{3}}$ trigonal perovskite phase $(P3m1)$ , in contrast with the XRD patterns of the $\\mathrm{FAPbI_{3}}$ powder [Fig. 1D(b)] (13). The intensity ratio of the (–123) peak at $31.5^{\\circ}$ to the (–222) peak at $28.1^{\\circ}$ was 0.05. This value was much smaller than the corresponding intensity ratios (0.8) for the $\\mathrm{FAPbI_{3}}$ powder. Thus, IEP leads to high-quality pure $\\mathrm{FAPbI_{3^{-}}}$ based films with preferred orientation along the [111] axis. \n\nFigure S2 (22) presents the current density− voltage $\\left(J\\mathbf{-}V\\right)$ curves measured under standard AM 1.5G (air mass 1.5 global) illumination, as well as the external quantum efficiency (EQE) spectra of the fabricated cells with $\\mathrm{FAPbI_{3}}$ - based layers fabricated with various amounts of MABr (0 to $20~\\mathrm{wt\\%}$ ). The onset wavelength in the EQE spectra near $830\\ \\mathrm{nm}$ showed a nonlinear blue shift with increasing amounts of MABr, indicating that there is unsymmetrical competition between FAI and MABr in forming the $\\mathrm{FAPbI_{3}\\mathrm{-MAPbBr_{3}}}$ perovskite phase through an intramolecular exchange reaction. Nonetheless, the highest PCE of $19.2\\%$ was achieved for the film fabricated from a FAI solution containing $15\\mathrm{\\mt{\\%}}$ MABr. To accurately determine the composition of the $\\mathrm{FAPbI_{3}}$ -based layer, we investigated the lattice parameter using XRD and the band gap using the EQE for the film showing the best performance. Figure S3 (22) shows the pseudocubic lattice parameter for $\\mathbf{(FAPbI_{3})_{1-x}(M A P b B r_{3})}_{x}$ as a function of $x$ , in which the composition was controlled by a previously reported method (10). In this study, the pseudocubic lattice parameter of the $\\mathrm{FAPbI_{3}}/$ $\\mathbf{MAPbBr_{3}}$ film fabricated by IEP with a FAI solution containing $15\\ \\mathrm{wt\\%}$ MABr is $6.348\\mathrm{~\\AA~}$ . As indicated in fig. S4 (22), the lattice parameter can be assigned as $x={\\sim}5$ , corresponding to $(\\mathrm{FAPbI_{3}})_{0.95}(\\mathrm{MAPbBr_{3}})_{0.05}$ . This result is in agreement with the value estimated using the band gap $\\left(1.49\\ \\mathrm{eV}\\right)$ from EQE [fig. S3 (22)], because pure $\\mathrm{FAPbI_{3}}$ has a band gap of 1.47 eV and $\\mathrm{(FAPbI_{3})_{0.85}(M A P b B r_{3})_{0.15}}$ has a band gap of 1.55 eV (10). Fortunately, the simultaneous introduction of both $\\mathrm{MA}^{+}$ cations and $\\mathrm{Br}^{-}$ anions in $\\mathrm{FAPbI_{3}}$ even after incorporating $5\\mathrm{mol\\%}$ of $\\mathbf{MAPbBr_{3}}$ serves to stabilize the perovskite phase (10). \n\n![](images/2834a9ec7828b3183680b0b92e7a015a593e4e3ddca341c9abddb080ea18461c.jpg) \nFig. 3. Comparison of x-ray diffractions, performance, and reproducibility between IEP and conventional process. (A) XRD patterns of asformed and annealed film for $\\mathsf{F A P b}\\mathsf{l}_{3}$ -based layers formed by IEP (red line) and conventional (blue line) process. a, #, and \\* denote the identified diffraction peaks corresponding to the $\\mathsf{F A P b l}_{3}$ perovskite phase, $\\mathsf{P b l}_{2}$ , and FAI, respectively. (B) Representative $J-V$ curves for $\\mathsf{F A P b l}_{3}$ -based cells fabricated by IEP and \nconventional process. (C) Histogram of solar cell efficiencies for each 66 $\\mathsf{F A P b l}_{3}$ -based cells fabricated by IEP and conventional process. \n\nAfter comparing the absorption coefficients of $\\mathrm{FAPbI_{3}}$ and $\\mathbf{MAPbI_{3}}$ at wavelengths beyond $800\\mathrm{nm}$ , we noted that the thickness of a $\\mathrm{FAPbI_{3}}$ layer needed to be higher than the optimal thickness of a typical perovskite layer with a band gap of \\~1.55 eV (300 to $400~\\mathrm{nm}$ ) to guarantee full light harvesting around $800\\mathrm{nm}$ (21, 23). We deposited $\\mathrm{FAPbI_{3}}$ -based layers with thickness of ${\\sim}500~\\mathrm{nm}$ , and fabricated devices consisting of fluorine-doped tin oxide (FTO)–glass/barrier layer (bl)- $\\cdot\\mathrm{{TiO}_{2}}/$ /mesoporous $\\mathrm{(mp){\\cdot}T i O_{2}}$ /perovskite/ polytriarylamine (PTAA)/Au (n-i-p architecture), as shown in the cross-sectional FESEM image of Fig. 2A. FESEM plane-view images of the device with film derived from $\\mathrm{PbI_{2}(D M S O)}$ complex and $\\mathrm{PbI_{2}}$ films are shown in Fig. 2B. The $\\mathrm{FAPbI_{3}}$ film derived from $\\mathrm{PbI_{2}(D M S O)}$ exhibited a dense and well-developed grain structure with larger grains than the $\\mathrm{FAPbI_{3}}$ film derived from $\\mathrm{PbI_{2}}$ . Figure 2C(a) shows the $J_{-}V$ curves measured via reverse and forward bias sweep for one of the best-performing solar cells. The devices we fabricated also showed no hysteresis. Here, we believe that the hysteresis is highly dependent on the perovskite materials $\\mathrm{(FAPbI_{3}}$ or $\\mathrm{\\mathbf{MAPbI_{3}}}.$ ) and cell architecture (n-i-p or p-i-n), although the ferroelectric properties of the perovskite itself are more likely to be the origin of the hysteresis in PSCs (24, 25). Thus, $\\mathrm{FAPbI_{3}}$ -based PSCs with n-i-p architecture show negligible hysteresis between the reverse and the forward scan in the $I{-}V$ characteristics. In contrast, $\\mathrm{FAPbI_{3}}.$ - based cells consisting of FTO/NiO/perovskite/ PCBM/LiF/Al (p-i-n architecture) showed very strong hysteresis [fig. S4 (22)]. Values of shortcircuit current density $(J_{\\mathrm{SC}})$ , open-circuit voltage $(V_{\\mathrm{OC}})$ , and fill factor $(F F)$ determined from the $J.$ -V curves were $24.7\\mathrm{mAcm^{-2}}$ , $\\boldsymbol{\\mathrm{1.06V}}$ , and $77.5\\%$ , respectively, and correspond to a PCE of $20.2\\%$ under standard AM 1.5G illumination. Figure 2C(b) shows the EQE spectrum and integrated $J_{\\mathrm{SC}}$ for one of the best-performing solar cell. The high $J_{\\mathrm{SC}}$ is attributed to a very broad EQE plateau of ${>}85\\%$ in the illumination wavelength range of 400 to $780~\\mathrm{{\\nm}}$ and broad lightharvesting up to a long wavelength of $840\\mathrm{nm}$ , owing to the relatively low band gap (1.47 eV) of $\\mathrm{FAPbI_{3}}$ . The $J_{\\mathrm{SC}}$ value $(24.4~\\mathrm{mA~cm^{-2}},$ ) obtained by integrating EQE spectrum agreed well with that derived from the $J_{-}V$ measurement. The PCE of the best-performing cell $(20.2\\%)$ was certified by the standardized method in the PV calibration laboratory, which confirmed a PCE of $20.1\\%$ under AM 1.5 G full-Sun illuminations [fig. S5 (22)]. \n\nTo gain more insight into the enhanced performance of the $\\mathrm{FAPbI_{3}}$ -based PSCs, we compared the properties of the films fabricated by IEP with those obtained from a conventional sequential process. A sequential reaction such as interdiffusion between FAI/MAI and $\\mathrm{PbI_{2}}$ through thermal annealing in organic iodide $\\mathrm{\\DeltaPbI_{2}}$ multilayer films has been used to form perovskite $\\mathrm{FAPbI_{3}}/$ $\\mathbf{MAPbI_{3}}$ films from inorganic $\\mathrm{PbI_{2}}$ films in the conventional process (17, 18). Thus, considerable volume expansion occurs in the sequential deposition process based on $\\mathrm{PbI_{2}}$ because of the growth of perovskite crystals with the insertion of organic iodides into $\\mathrm{PbI_{2}}$ skeleton (14, 23). As expected, an initial $\\mathrm{PbI_{2}}$ film with thickness of ${\\sim}290~\\mathrm{nm}$ was doubled to $570~\\mathrm{nm}$ for the film formed by the reaction of $\\mathrm{PbI_{2}}$ with FAI [Table 1 and fig. S6 (22)]. \n\nIn contrast, the change in thickness observed by the application of the FAI (MABr) solution to the predeposited $\\mathrm{PbI_{2}(D M S O)}$ film was negligible. In fact, the reaction between FAI (MABr) and $\\mathrm{PbI_{2}(D M S O)}$ was completed within 1 min during spin-coating and the $\\mathrm{FAPbI_{3}}$ perovskite phase was formed without sequential annealing. However, in a conventional process using $\\mathrm{PbI_{2}}$ films, annealing at high temperature is required to achieve interdiffusion. Figure 3A compares XRD patterns for as-formed and annealed films by IEP and conventional process from $\\mathrm{PbI_{2}(D M S O)}$ complex film and $\\mathrm{PbI_{2}}$ film, respectively; there is no appreciable difference in XRD patterns between as-formed and annealed film. This result confirms that the $\\mathrm{FAPbI_{3}}$ -based layer is formed by the IEP of DMSO and FAI (MABr) without additional annealing process. In addition, such an exchange can considerably favor crystallization into perovskite, compared to conventional interdiffusion from $\\mathrm{PbI_{2}}$ , and led to an increase in the XRD peaks intensity after annealing at $\\mathrm{150^{\\circ}C}$ for $20~\\mathrm{{min}}$ . However, the asformed film with $\\mathrm{PbI_{2}}$ showed XRD patterns assigned to $\\mathrm{PbI_{2}}$ , FAI, and $\\mathrm{FAPbI_{3}}$ , and a (002) peak at $12.5^{\\circ}$ corresponding to the $\\mathrm{PbI_{2}}$ still remained after annealing at same temperature and time with IEP. In particular, the $\\mathrm{FAPbI_{3}}$ film prepared by IEP shows preferred orientation in the (111) direction compared to $\\mathrm{FAPbI_{3}}$ film annealed after preparing it by conventional process. \n\nThe advantages of IEP become further apparent upon comparing the $J_{-}V$ curves and PCEs of $\\mathrm{FAPbI_{3}}$ -based devices derived from $\\mathrm{PbI_{2}(D M S O)}$ complex films and conventional $\\mathrm{PbI_{2}}$ films (Fig. 3, B and C). The devices based on $\\mathrm{FAPbI_{3}}$ fabricated from $\\mathrm{PbI_{2}(D M S O)}$ showed superior PCEs with smaller deviations in the value, compared to those prepared from conventional $\\mathrm{PbI_{2}}$ films. High-efficiency solar cells with average PCEs of ${>}19\\%$ could be produced with a high degree of reproducibility by using the IEP. This study provides an effective protocol for fabricating efficient and cost-effective inorganic-organic hybrid heterojunction solar cells. \n\n1. J. H. Heo et al., Nat. Photonics 7, 486–491 (2013). \n2. H.-S. Kim et al., Sci. Rep. 2, 591 (2012). \n3. M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami, H. J. Snaith, Science 338, 643–647 (2012). \n4. J. Burschka et al., Nature 499, 316–319 (2013). \n5. N. J. Jeon et al., Nat. Mater. 13, 897–903 (2014). \n6. M. Liu, M. B. Johnston, H. J. Snaith, Nature 501, 395–398 (2013). \n7. J. H. Noh, S. H. Im, J. H. Heo, T. N. Mandal, S. I. Seok, Nano Lett. 13, 1764–1769 (2013). \n8. J. W. Lee, D. J. Seol, A. N. Cho, N. G. Park, Adv. Mater. 26, 4991–4998 (2014). \n9. N. Pellet et al., Angew. Chem. Int. Ed. 53, 3151–3157 (2014). \n10. N. J. Jeon et al., Nature 517, 476–480 (2015). \n11. G. E. Eperon et al., Energy Environ. Sci. 7, 982–988 (2014). \n12. T. M. Koh et al., J. Phys. Chem. C 118, 16458–16462 (2014). \n13. S. Pang et al., Chem. Mater. 26, 1485–1491 (2014). \n14. Q. Chen et al., J. Am. Chem. Soc. 136, 622–625 (2014). \n15. P. W. Liang et al., Adv. Mater. 26, 3748–3754 (2014). \n16. Y.-J. Jeon et al., Sci. Rep. 4, 6953 (2014). \n17. J. H. Im, I. H. Jang, N. Pellet, M. Grätzel, N. G. Park, Nat. Nanotechnol. 9, 927–932 (2014). \n18. Y. Wu et al., Energy Environ. Sci. 7, 2934–2938 (2014). \n19. F. Wang, H. Yu, H. Xu, N. Zhao, Adv. Funct. Mater. 25, 1120–1126 (2015). \n20. H. Miyamae, Y. Numahata, M. Nagata, Chem. Lett. 9, 663–664 (1980). \n21. J. Selbin, W. Bull, L. Holmes Jr., J. Inorg. Nucl. Chem. 16, 219–224 (1961). \n22. See supplementary materials on Science Online. \n23. L. Hu et al., ACS Photonics 1, 547–553 (2014). \n24. H. J. Snaith et al., J. Phys. Chem. Lett. 5, 1511–1515 (2014). \n25. J. M. Frost et al., Nano Lett. 14, 2584–2590 (2014). \n\n# REFERENCES AND NOTES \n\n# ACKNOWLEDGMENTS \n\nSupported by the Global Research Laboratory Program, the Global Frontier R&D Program on Center for Multiscale Energy System funded by the National Research Foundation in Korea, and a grant from the KRICT 2020 Program for Future Technology of the Korea Research Institute of Chemical Technology and SKKU-KRICT DRC program. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/348/6240/1234/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S6 \n\n14 February 2015; accepted 30 April 2015 Published online 21 May 2015; 10.1126/science.aaa9272 \n\n# Science \n\n# High-performance photovoltaic perovskite layers fabricated through intramolecular exchange \n\nWoon Seok Yang, Jun Hong Noh, Nam Joong Jeon, Young Chan Kim, Seungchan Ryu, Jangwon Seo and Sang Il Seok \n\nScience 348 (6240), 1234-1237. DOI: 10.1126/science.aaa9272originally published online May 21, 2015 \n\n# Taking in more sun \n\nMost efforts to grow superior films of organic-inorganic perovskites for solar cells have focused on methylammonium lead iodide $(\\mathsf{M A P b l}_{3})$ . However, formamidinium lead iodide $(\\mathsf{F A P b}\\mathsf{b}_{3})$ has a broader solar absorption spectrum that could ultimately lead to better performance. Yang et al. grew high-quality $\\mathsf{F A P b l}_{3}$ films by starting with a film of lead iodide and dimethylsulfoxide (DMSO) and then exchanging the DMSO with formamidinium iodide. Their best devices achieved power conversion efficiencies exceeding $20\\%$ . \n\nScience, this issue p. 1234 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1021_nl5048779", + "DOI": "10.1021/nl5048779", + "DOI Link": "http://dx.doi.org/10.1021/nl5048779", + "Relative Dir Path": "mds/10.1021_nl5048779", + "Article Title": "nullocrystals of Cesium Lead Halide Perovskites (CsPbX3, X = Cl, Br, and I): Novel Optoelectronic Materials Showing Bright Emission with Wide Color Gamut", + "Authors": "Protesescu, L; Yakunin, S; Bodnarchuk, MI; Krieg, F; Caputo, R; Hendon, CH; Yang, RX; Walsh, A; Kovalenko, MV", + "Source Title": "nullO LETTERS", + "Abstract": "Metal halides perovskites, such as hybrid organic-inorganic CH3NH3PbI3, are newcomer optoelectronic materials that have attracted enormous attention as solution-deposited absorbing layers in solar cells with power conversion efficiencies reaching 20%. Herein we demonstrate a new avenue for halide perovskites by designing highly luminescent perovskite-based colloidal quantum dot materials. We have synthesized monodisperse colloidal nullocubes (4-15 nm edge lengths) of fully inorganic cesium lead halide perovskites (CsPbX3, X = Cl, Br, and I or mixed halide systems Cl/Br and Br/I) using inexpensive commercial precursors. Through compositional modulations and quantum size-effects, the bandgap energies and emission spectra are readily tunable over the entire visible spectral region of 410-700 nm. The photoluminescence of CsPbX3 nullocrystals is characterized by narrow emission line-widths of 12-42 nm, wide color gamut covering up to 140% of the NTSC color standard, high quantum yields of up to 90%, and radiative lifetimes in the range of 1-29 ns. The compelling combination of enhanced optical properties and chemical robustness makes CsPbX3 nullocrystals appealing for optoelectronic applications, particularly for blue and green spectral regions (410-530 nm), where typical metal chalcogenide-based quantum dots suffer from photodegradation.", + "Times Cited, WoS Core": 7392, + "Times Cited, All Databases": 7899, + "Publication Year": 2015, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000356316900006", + "Markdown": "# Nanocrystals of Cesium Lead Halide Perovskites $(C s P b)_{3},$ $\\mathbf{\\boldsymbol{X}}=\\mathbf{\\boldsymbol{C}}\\mathbf{\\boldsymbol{l}},$ , Br, and I): Novel Optoelectronic Materials Showing Bright Emission with Wide Color Gamut \n\nLoredana Protesescu,†,‡ Sergii Yakunin,†,‡ Maryna I. Bodnarchuk,†,‡ Franziska Krieg,†,‡ Riccarda Caputo,† Christopher H. Hendon,§ Ruo Xi Yang,§ Aron Walsh,§ and Maksym V. Kovalenko\\*,†,‡ \n\n†Institute of Inorganic Chemistry, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir Prelog Weg 1, CH-8093 \nZürich, Switzerland \n‡Laboratory for Thin Films and Photovoltaics, Empa − Swiss Federal Laboratories for Materials Science and Technology, \nÜ berlandstrasse 129, CH-8600 Dübendorf, Switzerland \n§Centre for Sustainable Chemical Technologies and Department of Chemistry, University of Bath, Bath BA2 7AY, United Kingdom \n\nSupporting Information \n\nABSTRACT: Metal halides perovskites, such as hybrid organic−inorganic $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ , are newcomer optoelectronic materials that have attracted enormous attention as solution-deposited absorbing layers in solar cells with power conversion efficiencies reaching $20\\%$ . Herein we demonstrate a new avenue for halide perovskites by designing highly luminescent perovskite-based colloidal quantum dot materials. We have synthesized monodisperse colloidal nanocubes $(4-15~\\mathrm{~nm}$ edge lengths) of fully inorganic cesium lead halide perovskites $(\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3},$ $\\mathrm{\\DeltaX=\\dot{C}l}$ , Br, and I or mixed halide systems $\\mathrm{Cl/Br}$ and $\\mathbf{Br/I}\\dot{}$ ) using inexpensive commercial precursors. Through compositional modulations and quantum size-effects, the bandgap energies and emission spectra are readily tunable over the entire visible spectral region of $410{-}700~\\mathrm{nm}$ . The photoluminescence of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ nanocrystals is characterized by narrow emission line-widths of $12{-}42\\ \\mathrm{nm}$ , wide color gamut covering up to $140\\%$ of the NTSC color standard, high quantum yields of up to $90\\%$ , and radiative lifetimes in the range of $1-29~\\mathrm{ns}$ . The compelling combination of enhanced optical properties and chemical robustness makes $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ nanocrystals appealing for optoelectronic applications, particularly for blue and green spectral regions $\\left(410-530\\ \\mathrm{nm}\\right)$ , where typical metal chalcogenide-based quantum dots suffer from photodegradation. \n\n![](images/ebdb71d2bb930498389bc3674e955ce6244a24696dcc1df14cb4b9e308f09596.jpg) \n\nKEYWORDS: Perovskites, halides, quantum dots, nanocrystals, optoelectronics \n\nolloidal semiconductor nanocrystals (NCs, typically 2−20 nm large), also known as nanocrystal quantum dots (QDs), are being studied intensively as future optoelectronic materials.1−4 These QD materials feature a very favorable combination of quantum-size effects, enhancing their optical properties with respect to their bulk counterparts, versatile surface chemistry, and a “free” colloidal state, allowing their dispersion into a variety of solvents and matrices and eventual incorporation into various devices. To date, the best developed optoelectronic NCs in terms of size, shape, and composition are binary and multinary (ternary, quaternary) metal chalcogenide NCs.1,5−9 In contrast, the potential of semiconducting metal halides in the form of colloidal NCs remains rather unexplored. In this regard, recent reports on highly efficient photovoltaic devices with certified power conversion efficiencies approaching $20\\%$ using hybrid organic−inorganic lead halides $\\mathbf{MAPb}\\mathrm{X}_{3}$ $\\mathrm{{'}M A=C H_{3}N H_{3},}$ $\\mathrm{\\DeltaX=Cl}_{\\mathrm{\\Delta}}$ , Br, and I) as semiconducting absorber layers are highly encouraging.10−14 \n\nIn this study, we turn readers’ attention to a closely related family of materials: all-inorganic cesium lead halide perovskites $\\left(\\mathrm{CsPb}{\\mathrm{X}}_{3},\\right.$ , $\\mathrm{\\DeltaX=Cl}$ , Br, I, and mixed $\\mathrm{Cl/Br}$ and $\\mathrm{Br/I}$ systems; isostructural to perovskite $\\mathrm{CaTiO}_{3}$ and related oxides). These ternary compounds are far less soluble in common solvents (contrary to $\\begin{array}{r}{\\mathbf{MAPb}\\mathbf{X}_{3},}\\end{array}$ ), which is a shortcoming for direct solution processing but a necessary attribute for obtaining these compounds in the form of colloidal NCs. Although the synthesis, crystallography, and photoconductivity of direct bandgap $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ have been reported more than 50 years ago,15 they have never been explored in the form of colloidal nanomaterials. \n\nHere we report a facile colloidal synthesis of monodisperse, $4{-}15\\ \\mathrm{nm}\\ \\mathrm{CsPb}\\mathrm{X}_{3}$ NCs with cubic shape and cubic perovskite crystal structure. $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs exhibit not only compositional bandgap engineering, but owing to the exciton Bohr diameter of up to $12\\ \\mathrm{nm},$ , also exhibit size-tunability of their bandgap energies through the entire visible spectral region of 410−700 nm. Photoluminescence (PL) of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs is characterized by narrow emission line widths of $12{-}42~\\mathrm{nm}$ , high quantum yields of $50-90\\%$ , and short radiative lifetimes of $1-29~\\mathrm{ns}$ . \n\n![](images/18f3aa00132fa044ccf81bd001ce2a0a65b0bc472037b9dd96e99cc1db1e3b9c.jpg) \nFigure 1. Monodisperse $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs and their structural characterization. (a) Schematic of the cubic perovskite lattice; $^{(\\mathrm{b,c})}$ typical transmission electron microscopy (TEM) images of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs; (d) X-ray diffraction patterns for typical ternary and mixed-halide NCs. \n\n![](images/cb02d1a9d9b38a07f2d1a56f63833abc2e9c99a3935c5648df1de045af188429.jpg) \nFigure 2. Colloidal perovskite $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs ( $\\mathrm{\\DeltaX=Cl},$ Br, I) exhibit size- and composition-tunable bandgap energies covering the entire visible spectral region with narrow and bright emission: (a) colloidal solutions in toluene under UV lamp $\\dot{\\lambda}=365\\mathrm{\\scriptsize~nm}$ ); (b) representative PL spectra $\\left\\langle\\lambda_{\\mathrm{exc}}\\right.$ $=400\\ \\mathrm{nm}$ for all but $350\\mathrm{nm}$ for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ samples); (c) typical optical absorption and $\\mathrm{PL}$ spectra; (d) time-resolved PL decays for all samples shown in (c) except $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ . \n\nSynthesis of Monodisperse $\\mathsf{C s P b}\\mathsf{X}_{3}$ NCs. Our solutionphase synthesis of monodisperse $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs (Figure 1) takes advantage of the ionic nature of the chemical bonding in these compounds. Controlled arrested precipitation of ${\\mathrm{C}}s^{+}.$ , $\\mathrm{Pb}^{2+}$ , and $\\mathrm{X}^{-}$ ions into $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs is obtained by reacting Cs-oleate with a $\\operatorname{Pb}(\\operatorname{II})$ -halide in a high boiling solvent (octadecene) at $140{-}200\\ ^{\\circ}\\mathrm{C}$ (for details, see the Supporting Information). A 1:1 mixture of oleylamine and oleic acid are added into octadecene to solubilize $\\mathrm{Pb}X_{2}$ and to colloidally stabilize the NCs. As one would expect for an ionic metathesis reaction, the nucleation and growth kinetics are very fast. In situ PL measurements with a CCD-array detector (Supporting Information Figure S1) indicate that the majority of growth occurs within the first 1−3 s (faster for heavier halides). Consequently, the size of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs can be most conveniently tuned in the range of $4{-}15\\ \\mathrm{nm}$ by the reaction temperature $(140-200~^{\\circ}\\mathrm{C})$ rather than by the growth time. \n\nMixed-halide perovskites, that is, $\\mathrm{Cs}\\mathrm{Pb}(\\mathrm{Cl}/\\mathrm{Br})_{3}$ and $\\mathrm{CsPb(Br/}$ $\\mathrm{I})_{3},$ can be readily produced by combining appropriate ratios of $\\mathrm{Pb}{\\mathrm{X}}_{2}$ salts. Note that $\\mathrm{Cl/I}$ perovskites cannot be obtained due to the large difference in ionic radii, which is in good agreement with the phase diagram for bulk materials.16 Elemental analyses by energy dispersive X-ray (EDX) spectroscopy and by Ratherford backscattering spectrometry (RBS) confirmed the 1:1:3 atomic ratio for all samples of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs, including mixed-halide systems. \n\n$\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ are known to crystallize in orthorhombic, tetragonal, and cubic polymorphs of the perovskite lattice with the cubic phase being the high-temperature state for all compounds.16−18 Interestingly, we find that all $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs crystallize in the cubic phase (Figure 1d), which can be attributed to the combined effect of the high synthesis temperature and contributions from the surface energy. For $\\mathrm{CsPbI}_{3}$ NCs, this is very much a metastable state, because bulk material converts into cubic polymorph only above $315~^{\\circ}\\mathrm{C}$ . At room temperature, an exclusively PL-inactive orthorhombic phase has been reported for bulk $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ (a yellow phase).16−19 Our firstprinciples total energy calculations (density functional theory, Figure S2, Table S1 in Supporting Information) confirm the bulk cubic $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ phase to have $17\\mathrm{\\kJ/mol}$ higher internal energy than the orthorhombic polymorph $(7~\\mathrm{kJ/mol}$ difference for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ ). Weak emission centered at ${\\sim}710~\\mathrm{nm}$ has been observed from melt-spun bulk $\\mathrm{Cs}\\mathrm{Pb}\\ensuremath{\\mathrm{I}_{3}}.$ , shortly before recrystallization into the yellow phase.18 Similarly, our solution synthesis of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ at $305~^{\\circ}\\mathrm{C}$ yields cubic-phase $100{-}200~\\mathrm{nm}$ NCs with weak, short-lived emission at $714~\\mathrm{nm}$ (1.74 eV), highlighting the importance of size reduction for stabilizing the cubic phase and indicating that all $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ NCs in Figure 2b 1 $\\scriptstyle5-15\\ {\\mathrm{~nm}}$ in size) exhibit quantum-size effects (i.e., higher band gap energies due to quantum confinement, as discussed below). Cubic $4{-}15\\ \\mathrm{\\nm}\\ C s\\mathrm{PbI}_{3}$ NCs recrystallize into the yellow phase only upon extended storage (months), whereas all other compositions of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs appear fully stable in a cubic phase. \n\nOptical Properties of Colloidal $\\mathsf{c s P b}\\mathsf{x}_{3}$ NCs. Optical absorption and emission spectra of colloidal $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs (Figure $2\\mathrm{b},\\mathrm{c}$ ) can be tuned over the entire visible spectral region by adjusting their composition (ratio of halides in mixed halide NCs) and particle size (quantum-size effects). Remarkably bright PL of all NCs is characterized by high QY of $50\\mathrm{-}90\\%$ and narrow emission line widths of $12{-}42\\ \\mathrm{nm}$ . The combination of these two characteristics had been previously achieved only for core−shell chalcogenide-based QDs such as CdSe/CdS due to the narrow size distributions of the luminescent CdSe cores, combined with an epitaxially grown, electronically passivating CdS shell.5,20 Time-resolved photoluminescence decays of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs (Figure 2d) indicate radiative lifetimes in the range of $_{1-29}$ ns with faster emission for wider-gap NCs. For comparison, decay times of several 100 ns are typically observed in $\\mathbf{MAPbI}_{3}$ (PL peak at $765\\ \\mathrm{nm}$ , fwhm $=50\\ \\mathrm{nm}\\big)^{21}$ and 40−400 ns for $\\mathbf{MAPbBr}_{3-x}\\mathbf{Cl}_{\\mathrm{x}}$ $(x=0.6-2)$ .22 \n\nVery bright emission of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs indicates that contrary to uncoated chalcogenide NCs surface dangling bonds do not impart severe midgap trap states. This observation is also in good agreement with the high photophysical quality of hybrid organic−inorganic perovskites $\\left(\\mathrm{MAPb}\\mathrm{X}_{3}\\right)$ , despite their lowtemperature solution-processing, which is generally considered to cause a high density of structural defects and trap states. In particular, thin-films of $\\mathbf{MAPb}\\mathrm{X}_{3}$ exhibit relatively high PL QYs of $20-40\\%$ at room temperature23,24 and afford inexpensive photovoltaic devices approaching $20\\%$ in power conversion efficiency10−12 and also electrically driven light-emitting devices. \n\nTernary $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs compare favorably to common multinary chalcogenide NCs: both ternary $\\left(\\mathrm{CuIn}{\\cal S}_{2},\\right.$ ${\\mathrm{CuInSe}}_{2},$ $\\mathrm{AgInS}_{2},$ and $\\mathrm{AgInSe}_{2}$ ) and quaternary $\\mathrm{'CuZnSnS}_{2}$ and similar) compounds. $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ materials are highly ionic and thus are rather stoichiometric and ordered due to the distinct size and charge of the $C s$ and $\\mathrm{Pb}$ ions. This is different from multinary chalcogenide materials that exhibit significant disorder and inhomogeneity in the distribution of cations and anions owing to little difference between the different cationic and anionic sites (all are essentially tetrahedral). In addition, considerable stoichiometric deviations lead to a large density of donor− acceptor states due to various point defects (vacancies, interstitials, etc.) within the band gap, both shallow and deep. \n\nThese effects eventually lead to absent or weak and broad emission spectra and long multiexponent lifetimes.7,26−29 \n\nFor a colloidal semiconductor NC to exhibit quantum-dotlike properties (shown in Figures 2b and 3), the NC diameter must be comparable or smaller than that of the natural delocalization lengths of an exciton in a bulk semiconductor (i.e., the exciton Bohr diameter, $a_{0,}$ ). The electronic structure of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ $\\mathrm{\\langleX=Cl,}$ Br, and I), including scalar relativistic and spin−orbit interactions, was calculated using VASP code30 and confirms that the upper valence band is formed predominately by the halide p-orbitals and the lower conduction band is formed by the overlap of the Pb p-orbitals (Figures S3 and S4 and Tables S2 and S3 in Supporting Information). Effective masses of the electrons and holes were estimated from the band dispersion, while the high-frequency dielectric constants were calculated by using density functional perturbation theory. 31 Within the effective mass approximation (EMA),32 we have estimated the effective Bohr diameters of Wannier−Mott excitons and the binding energies for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ $\\langle s_{\\mathrm{\\scriptsize~nm},75}\\mathrm{\\meV}\\rangle$ , $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ $(7\\ \\mathrm{nm},\\ 40\\ \\mathrm{meV}).$ , and $\\mathrm{CsPbI}_{3}$ ( $12\\ \\mathrm{nm}$ , $20\\mathrm{\\meV})$ . Similarly, in closely related hybrid perovskite $\\mathbf{MAPbI}_{3}$ small exciton binding energies of $\\leq25\\mathrm{\\meV}$ have been suggested computationally33−35 and found experimentally.36 For comparison, the typical exciton binding energies in organic semiconductors are above $100\\ \\mathrm{meV}$ . The confinement energy ( $\\Delta E$ $=\\hbar^{2}\\pi^{2}/2m^{*}r^{2}$ , where $r$ is the particle radius and $m^{*}$ is the reduced mass of the exciton) provides an estimate for the blue shift of the emission peak and absorption edge and is in good agreement with the experimental observations (Figure 3b). \n\n![](images/b88ccf6a28e01baab877004132635636b2cc17e4df47d42d2aa34367741122ab.jpg) \nFigure 3. (a) Quantum-size effects in the absorption and emission spectra of $5{-}12\\ \\mathrm{nm}\\ C s\\mathrm{Pb}\\mathrm{Br}_{3}\\ \\mathrm{NCs}$ . (b) Experimental versus theoretical (effective mass approximation, EMA) size dependence of the band gap energy. \n\nRecently, highly luminescent semiconductor NCs based on Cd-chalcogenides have inspired innovative optoelectronic applications such as color-conversion LEDs, color-enhancers in backlight applications (e.g., Sony’s 2013 Triluminos LCD displays), and solid-state lightin g.4,37,38 Compared to conventional rare-earth phosphors or organic polymers and dyes, NCs often show superior quantum efficiency and narrower PL spectra with fine-size tuning of the emission peaks and hence can produce saturated colors. A CIE chromaticity diagram (introduced by the Commision Internationale de l’Eclairage)39 allows the comparison of the quality of colors by mapping colors visible to the human eye in terms of hue and saturation. For instance, well-optimized core−shell CdSe-based NCs cover $\\geq100\\%$ of the NTSC TV color standard (introduced in 1951 by the National Television System Committee).39 Figure 4a shows that $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs allow a wide gamut of pure colors as well. Namely, a selected triangle of red, green, and blue emitting $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs encompasses $140\\%$ of the NTSC standard, extending mainly into red and green regions. \n\nLight-emission applications, discussed above, and also luminescent solar concentrators40,41 require solution-processability and miscibility of NC-emitters with organic and inorganic matrix materials. To demonstrate such robustness for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs, we embedded them into poly(methylmetacrylate) (PMMA), yielding composites of excellent optical clarity and with bright emission (Figure 4b). To accomplish this, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs were first dispersed in a liquid monomer (methylmetacrylate, MMA) as a solvent. Besides using known heat-induced polymerization with radical initiators,41 we also performed polymerization already at room-temperature by adding a photoinitiator Irgacure 819 (bis(2,4,6-trimethylbenzoyl)-phenylphosphineoxide),42 followed by 1h of UV-curing. We find that the presence of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs increases the rate of photopolymerization, compared to a control experiment with pure MMA. This can be explained by the fact that the luminescence from $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs may be reabsorbed by the photoinitiator that has a strong absorption band in the visible spectral region, increasing the rate of polymerization. \n\n![](images/e6319c8bc349c8800f6aeb9a2c57b359076b5ea8bd7338780a71775499bc712d.jpg) \nFigure 4. (a) Emission from $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs (black data points) plotted on CEI chromaticity coordinates and compared to most common color standards (LCD TV, dashed white triangle, and NTSC TV, solid white triangle). Radiant Imaging Color Calculator software from Radiant Zemax (http://www.radiantzemax.com) was used to map the colors. (b) Photograph ${}^{\\prime}\\lambda_{\\mathrm{exc}}=365~\\mathrm{nm},$ of highly luminescent $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs-PMMA polymer monoliths obtained with Irgacure 819 as photoinitiator for polymerization. \n\nConclusions. In summary, we have presented highly luminescent colloidal $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs $\\mathrm{{\\overset{\\triangledown}{X}=C l},}$ Br, I, and mixed $\\mathrm{Cl/Br}$ and $\\mathrm{Br/I}$ systems) with bright $\\mathrm{(QY=50{-}90\\%)}$ , stable, spectrally narrow, and broadly tunable photoluminescence. Particularly appealing are highly stable blue and green emitting $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs $(410-530\\mathrm{nm})$ , because the corresponding metalchalcogenide QDs show reduced chemical and photostability at these wavelengths. In our ongoing experiments, we find that this simple synthesis methodology is also applicable to other metal halides with related crystal structures (e.g., ${\\mathrm{CsGeI}}_{3},$ $\\mathrm{Cs}_{3}\\mathrm{Bi}_{2}\\mathrm{I}_{9},$ , and $\\mathrm{Cs}_{2}\\mathrm{SnI}_{6},$ to be published elsewhere). Future studies with these novel QD-materials will concentrate on optoelectronic applications such as lasing, light-emitting diodes, photovoltaics, and photon detection. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nSynthesis details, calculations, and additional figures. This material is available free of charge via the Internet at http:// pubs.acs.org. \n\n# AUTHOR INFORMATION \n\n# Corresponding Author \n\n$^{*}\\mathrm{E}$ -mail: mvkovalenko@ethz.ch. \n\n# Author Contributions \n\nThe manuscript was prepared through the contribution of all coauthors. All authors have given approval to the final version of the manuscript. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work was financially supported by the European Research Council (ERC) via Starting Grant (306733). The work at Bath was supported by the ERC Starting Grant (277757) and by the EPSRC (Grants EP/M009580/1 and EP/K016288/1). Calculations at Bath were performed on ARCHER via the U.K.’s HPC Materials Chemistry Consortium (Grant EP/L000202). Calculations at ETH Zürich were performed on the central HPC cluster BRUTUS. We thank Nadia Schwitz for a help with photography, Professor Dr. H. Grützmacher and Dr. G. Müller for a sample of Irgacure 819 photoinitiator, Dr. F. Krumeich for EDX measurements, Dr. M. Döbeli for RBS measurements (ETH Laboratory of Ion Beam Physics), and Dr. N. Stadie for reading the manuscript. We gratefully acknowledge the support of the Electron Microscopy Center at Empa and the Scientific Center for Optical and Electron Microscopy (ScopeM) at ETH Zürich. \n\n# REFERENCES \n\n(1) Talapin, D. V.; Lee, J.-S.; Kovalenko, M. V.; Shevchenko, E. V. Chem. Rev. 2009, 110, 389−458. \n(2) Lan, X.; Masala, S.; Sargent, E. H. Nat. Mater. 2014, 13, 233−240. (3) Hetsch, F.; Zhao, N.; Kershaw, S. V.; Rogach, A. L. Mater. Today 2013, 16, 312−325. \n(4) Shirasaki, Y.; Supran, G. J.; Bawendi, M. G.; Bulovic, V. Nat. Photonics 2013, 7, 13−23. \n(5) Chen, O.; Zhao, J.; Chauhan, V. P.; Cui, J.; Wong, C.; Harris, D. K.; Wei, H.; Han, H.-S.; Fukumura, D.; Jain, R. K.; Bawendi, M. G. Nat. Mater. 2013, 12, 445−451. \n(6) Murray, C. B.; Norris, D. J.; Bawendi, M. G. J. Am. Chem. Soc. 1993, 115, 8706−8715. \n(7) Aldakov, D.; Lefrancois, A.; Reiss, P. J. Mater. Chem. C 2013, 1, 3756−3776. \n(8) Fan, F.-J.; Wu, L.; Yu, S.-H. Energy Environ. Sci. 2014, 7, 190− 208. \n(9) Yu, X.; Shavel, A.; An, X.; Luo, Z.; Ibáñez, M.; Cabot, A. J. Am. Chem. Soc. 2014, 136, 9236−9239. \n(10) Gratzel, M. Nat. Mater. 2014, 13, 838−842. \n(11) Green, M. A.; Ho-Baillie, A.; Snaith, H. J. Nat. Photonics 2014, 8, 506−514. \n(12) Park, N.-G. J. Phys. Chem. Lett. 2013, 4, 2423−2429. \n(13) Zhou, H.; Chen, Q.; Li, G.; Luo, S.; Song, T.-b.; Duan, H.-S.; Hong, Z.; You, J.; Liu, Y.; Yang, Y. Science 2014, 345, 542−546. (14) Chung, I.; Lee, B.; He, J.; Chang, R. P. H.; Kanatzidis, M. G. Nature 2012, 485, 486−489. \n(15) Moller, C. K. Nature 1958, 182, 1436−1436. \n(16) Sharma, S.; Weiden, N.; Weiss, A. Z. Phys. Chem. 1992, 175, 63−80. \n(17) Trots, D. M.; Myagkota, S. V. J. Phys. Chem. Solids 2008, 69, 2520−2526. \n(18) Stoumpos, C. C.; Malliakas, C. D.; Kanatzidis, M. G. Inorg. Chem. 2013, 52, 9019−9038. \n(19) Babin, V.; Fabeni, P.; Nikl, M.; Nitsch, K.; Pazzi, G. P.; Zazubovich, S. Phys. Status Solidi B 2001, 226, 419−428. \n(20) Christodoulou, S.; Vaccaro, G.; Pinchetti, V.; De Donato, F.; Grim, J. $\\mathrm{\\Q.;}$ Casu, A.; Genovese, A.; Vicidomini, G.; Diaspro, A.; Brovelli, S.; Manna, L.; Moreels, I. J. Mater. Chem. C 2014, 2, 3439− 3447. \n(21) Wehrenfennig, C.; Liu, M.; Snaith, H. J.; Johnston, M. B.; Herz, L. M. J. Phys. Chem. Lett. 2014, 5, 1300−1306. \n(22) Zhang, M.; Yu, H.; Lyu, M.; Wang, Q.; Yun, J.-H.; Wang, L. Chem. Commun. 2014, 50, 11727−11730. \n(23) Xing, G.; Mathews, N.; Lim, S. S.; Yantara, N.; Liu, X.; Sabba, D.; Grätzel, M.; Mhaisalkar, S.; Sum, T. C. Nat. Mater. 2014, 13, 476− 480. \n(24) Deschler, F.; Price, M.; Pathak, S.; Klintberg, L. E.; Jarausch, D.- D.; Higler, R.; Hüttner, S.; Leijtens, T.; Stranks, S. D.; Snaith, H. J.; Atatüre, M.; Phillips, R. T.; Friend, R. H. J. Phys. Chem. Lett. 2014, 5, 1421−1426. \n(25) Tan, Z.-K.; Moghaddam, R. S.; Lai, M. L.; Docampo, P.; Higler, R.; Deschler, F.; Price, M.; Sadhanala, A.; Pazos, L. M.; Credgington, D.; Hanusch, F.; Bein, T.; Snaith, H. J.; Friend, R. H. Nat. Nanotechnol. 2014, 9, 687−692. \n(26) Ueng, H. Y.; Hwang, H. L. J. Phys. Chem. Solids 1989, 50, 1297− 1305. \n(27) Huang, L.; Zhu, X.; Publicover, N. G.; Hunter, K. W.; Ahmadiantehrani, M.; de Bettencourt-Dias, A.; Bell, T. W. J. Nanopart. Res. 2013, 15, 2056. \n(28) De Trizio, L.; Prato, M.; Genovese, A.; Casu, A.; Povia, M.; Simonutti, R.; Alcocer, M. J. P.; D’Andrea, C.; Tassone, F.; Manna, L. Chem. Mater. 2012, 24, 2400−2406. (29) Zhang, W.; Zhong, X. Inorg. Chem. 2011, 50, 4065−4072. \n(30) Kresse, G.; Joubert, D. Phys. Rev. B 1999, 59, 1758. \n(31) Baroni, S.; de Gironcoli, S.; Dal Corso, A.; Giannozzi, P. Rev. \nMod. Phys. 2001, 73, 515. \n(32) Yu, P. Y.; Cardona, M. Fundamentals of Semiconductors; \nSpringer: New York, 1996. \n(33) Even, J.; Pedesseau, L.; Katan, C. J. Phys. Chem. C 2014, 118, 11566−11572. \n(34) Frost, J. M.; Butler, K. T.; Brivio, F.; Hendon, C. H.; van Schilfgaarde, M.; Walsh, A. Nano Lett. 2014, 14, 2584−2590. \n(35) Menéndez-Proupin, E.; Palacios, P.; Wahnón, P.; Conesa, J. \nPhys. Rev. B 2014, 90, 045207. \n(36) Saba, M.; Cadelano, M.; Marongiu, D.; Chen, F.; Sarritzu, V.; \nSestu, N.; Figus, C.; Aresti, M.; Piras, R.; Geddo Lehmann, A.; Cannas, C.; Musinu, A.; Quochi, F.; Mura, A.; Bongiovanni, G. Nat. Commun. \n2014, 5, 5049. \n(37) Kim, T.-H.; Jun, S.; Cho, K.-S.; Choi, B. L.; Jang, E. MRS Bull. \n2013, 38, 712−720. \n(38) Supran, G. J.; Shirasaki, Y.; Song, K. W.; Caruge, J.-M.; Kazlas, P. \nT.; Coe-Sullivan, S.; Andrew, T. L.; Bawendi, M. G.; Bulović, V. MRS Bull. 2013, 38, 703−711. \n(39) Ye, S.; Xiao, F.; Pan, Y. X.; Ma, Y. Y.; Zhang, Q. Y. Mater. Sci. \nEng. R 2010, 71, 1−34. \n(40) Bomm, J.; Buechtemann, A.; Chatten, A. J.; Bose, R.; Farrell, D. \nJ.; Chan, N. L. A.; Xiao, Y.; Slooff, L. H.; Meyer, T.; Meyer, A.; van Sark, W. G. J. H. M.; Koole, R. Sol. Energy Mater. Sol. Cells 2011, 95, 2087−2094. \n(41) Meinardi, F.; Colombo, A.; Velizhanin, K. A.; Simonutti, R.; \nLorenzon, M.; Beverina, L.; Viswanatha, R.; Klimov, V. I.; Brovelli, S. \nNat. Photonics 2014, 8, 392−399. \n(42) Gruetzmacher, H.; Geier, J.; Stein, D.; Ott, T.; Schoenberg, H.; \nSommerlade, R. H.; Boulmaaz, S.; Wolf, J.-P.; Murer, P.; Ulrich, T. \nChimia 2008, 62, 18−22. \n\n# NOTE ADDED AFTER ASAP PUBLICATION \n\nThis paper was published on the Web on February 2, 2015. The discussion of the preparation of Cs-oleate and synthesis of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs in the Supporting Information has been corrected, and the paper was reposted on April 14, 2015. " + }, + { + "id": "10.1016_j.scriptamat.2015.07.021", + "DOI": "10.1016/j.scriptamat.2015.07.021", + "DOI Link": "http://dx.doi.org/10.1016/j.scriptamat.2015.07.021", + "Relative Dir Path": "mds/10.1016_j.scriptamat.2015.07.021", + "Article Title": "First principles phonon calculations in materials science", + "Authors": "Togo, A; Tanaka, I", + "Source Title": "SCRIPTA MATERIALIA", + "Abstract": "Phonon plays essential roles in dynamical behaviors and thermal properties, which are central topics in fundamental issues of materials science. The importance of first principles phonon calculations cannot be overly emphasized. Phonopy is an open source code for such calculations launched by the present authors, which has been world-widely used. Here we demonstrate phonon properties with fundamental equations and show examples how the phonon calculations are applied in materials science. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.orgilicenses/by/4.0/).", + "Times Cited, WoS Core": 8499, + "Times Cited, All Databases": 8915, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000360250700001", + "Markdown": "Viewpoint Paper \n\n# First principles phonon calculations in materials science \n\nAtsushi Togo a,b, Isao Tanaka a,b,c,⇑ \n\na Center for Elements Strategy Initiative for Structure Materials (ESISM), Kyoto University, Sakyo, Kyoto 606-8501, Japan b Department of Materials Science and Engineering, Kyoto University, Sakyo, Kyoto 606-8501, Japan c Nanostructures Research Laboratory, Japan Fine Ceramics Center, Atsuta, Nagoya 456-8587, Japan \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: \nReceived 30 June 2015 \nRevised 17 July 2015 \nAccepted 18 July 2015 \nAvailable online 29 July 2015 \n\nKeywords: \nFirst principles phonon calculation \nThermal ellipsoid \nThermal expansion \n\nPhonon plays essential roles in dynamical behaviors and thermal properties, which are central topics in fundamental issues of materials science. The importance of first principles phonon calculations cannot be overly emphasized. Phonopy is an open source code for such calculations launched by the present authors, which has been world-widely used. Here we demonstrate phonon properties with fundamental equations and show examples how the phonon calculations are applied in materials science. \n\n$\\circledcirc$ 2015 Acta Materialia Inc. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). \n\n# 1. Introduction \n\nApplication of first principles calculations in condensed matter physics and materials science has greatly expanded when phonon calculations became routine in the last decade. Thanks to the progress of high performance computers and development of accurate and efficient density functional theory (DFT) codes, a large set of first principles calculations are now practical with the accuracy comparable to experiments using ordinary PC clusters. In addition to electronic structure information, a DFT calculation for solids provides energy and stress of the system as well as the force on each atom. Equilibrium crystal structures can be obtained by minimizing residual forces and optimizing stress tensors. When an atom in a crystal is displaced from its equilibrium position, the forces on all atoms in the crystal raise. Analysis of the forces associated with a systematic set of displacements provides a series of phonon frequencies. First principles phonon calculations with a finite displacement method (FDM) [1,2] can be made in this way. An alternative approach for phonon calculations is the density functional perturbation theory (DFPT) [3,4]. The present authors have launched a robust and easy-to-use open-source code for first principles phonon calculations, phonopy [5–20]. This can handle force constants obtained both by FDM and DFPT. The number of users is rapidly growing world-wide, since the information of phonon is very useful for accounting variety of properties and behavior of crystalline materials, such as thermal properties, mechanical properties, phase transition, and superconductivity. In this article, we show examples of applications of the first principles phonon calculations. \n\nIn Sections 2–4, we take FCC-Al as examples of applications of first principles phonon calculations. For the electronic structure calculations, we employed the plane-wave basis projector augmented wave method [21] in the framework of DFT within the generalized gradient approximation in the Perdew–Burke–Ernzer hof form [22] as implemented in the VASP code [23–25]. A plane-wave energy cutoff of $300\\mathrm{eV}$ and an energy convergence criteria of $10^{-8}\\mathrm{eV}$ were used. A $30\\times30\\times30~k$ -point sampling mesh was used for the unit cell and the equivalent density mesh was used for the supercells together with a $0.2\\mathrm{eV}$ smearing width of the Methfessel–Paxton scheme [26]. For the phonon calculations, supercell and finite displacement approaches were used with $3\\times3\\times3$ supercell of the conventional unit cell (108 atoms) and the atomic displacement distance of $0.01\\mathring{\\mathsf{A}}.$ \n\n# 2. Harmonic approximation \n\nIn crystals, it is presumed that atoms move around their equilibrium positions ${\\bf r}(l\\kappa)$ with displacements ${\\bf u}(l\\kappa)$ , where $l$ and $\\kappa$ are the labels of unit cells and atoms in each unit cell, respectively. Crystal potential energy $\\Phi$ is presumed to be an analytic function of the displacements of the atoms, and $\\Phi$ is expanded as \n\n$$\n\\begin{array}{l}{{\\Phi=\\Phi_{0}+\\displaystyle\\sum_{l k}\\displaystyle\\sum_{\\alpha}\\Phi_{\\alpha}(l\\kappa)u_{\\alpha}(l\\kappa)}}\\\\ {{\\mathrm{}+\\displaystyle\\frac{1}{2}\\displaystyle\\sum_{l l^{\\prime}\\kappa\\kappa^{\\prime}}\\displaystyle\\sum_{\\alpha\\beta}\\Phi_{\\alpha\\beta}(l\\kappa,l^{\\prime}\\kappa^{\\prime})u_{\\alpha}(l\\kappa)u_{\\beta}(l^{\\prime}\\kappa^{\\prime})}}\\\\ {{\\mathrm{}+\\displaystyle\\frac{1}{3!}\\displaystyle\\sum_{l l^{\\prime\\prime}\\kappa\\kappa^{\\prime}\\kappa^{\\prime\\prime}}\\displaystyle\\sum_{\\alpha\\beta\\gamma}\\Phi_{\\alpha\\beta\\gamma}(l\\kappa,l^{\\prime}\\kappa^{\\prime},l^{\\prime\\prime}\\kappa^{\\prime\\prime})\\times u_{\\alpha}(l\\kappa)u_{\\beta}(l^{\\prime}\\kappa^{\\prime})u_{\\gamma}(l^{\\prime\\prime}\\kappa^{\\prime\\prime})+\\cdots}}\\end{array}\n$$ \n\nwhere $\\alpha,\\beta,\\cdots$ are the Cartesian indices. The coefficients of the series expansion, $\\Phi_{0},\\ \\Phi_{\\alpha}(l\\kappa),\\ \\Phi_{\\alpha\\beta}(l\\kappa,l^{\\prime}\\kappa^{\\prime})$ , and, $\\Phi_{\\alpha\\beta\\gamma}(l\\kappa,l^{\\prime}\\kappa^{\\prime},l^{\\prime\\prime}\\kappa^{\\prime\\prime})$ , are the zeroth, first, second, and third order force constants, respectively. With small displacements at constant volume, the problem of atomic vibrations is solved with the second-order terms as the harmonic approximation, and the higher order terms are treated by the perturbation theory. \n\nWith a force $\\begin{array}{r}{F_{\\alpha}(l\\kappa)=-\\frac{\\partial\\Phi}{\\partial u_{\\alpha}(l\\kappa)},}\\end{array}$ an element of second-order force constants $\\Phi_{\\alpha\\beta}(l\\kappa,l^{\\prime}\\kappa^{\\prime})$ is obtained by \n\n$$\n\\frac{\\partial^{2}{\\Phi}}{\\partial u_{\\alpha}(l\\kappa)\\partial u_{\\beta}(l^{\\prime}\\kappa^{\\prime})}=-\\frac{\\partial F_{\\beta}(l^{\\prime}\\kappa^{\\prime})}{\\partial u_{\\alpha}(l\\kappa)}.\n$$ \n\nCrystal symmetry is utilized to improve the numerical accuracy of the force constants and to reduce the computational cost. The more details on the calculation of force constants are found in Refs. [8,9]. \n\nAs found in text books [27–30], dynamical property of atoms in the harmonic approximation is obtained by solving eigenvalue problem of dynamical matrix $\\mathbf{D(\\pmbq)}$ , \n\n$$\n\\mathrm{D}(\\mathbf{q})\\mathbf{e}_{\\mathbf{q}j}=\\omega_{\\mathbf{q}j}^{2}\\mathbf{e}_{\\mathbf{q}j},\\quad\\mathrm{or}\\quad\\sum_{\\beta\\kappa^{\\prime}}D_{\\kappa\\kappa^{\\prime}}^{\\alpha\\beta}(\\mathbf{q})e_{\\mathbf{q}j}^{\\beta\\kappa^{\\prime}}=\\omega_{\\mathbf{q}j}^{2}e_{\\mathbf{q}j}^{\\alpha\\kappa},\n$$ \n\nwith \n\n$$\nD_{\\kappa\\kappa^{\\prime}}^{\\alpha\\beta}(\\mathbf{q})=\\sum_{l^{\\prime}}\\frac{\\Phi_{z\\beta}(0\\kappa,l^{\\prime}\\kappa^{\\prime})}{\\sqrt{m_{\\kappa}m_{\\kappa^{\\prime}}}}e^{i\\mathbf{q}\\cdot[\\mathbf{r}(l^{\\prime}\\kappa^{\\prime})-\\mathbf{r}(0\\kappa)]},\n$$ \n\nwhere $m_{\\kappa}$ is the mass of the atom $\\kappa$ ; $\\pmb q$ is the wave vector, and $j$ is the band index. $\\omega_{\\mathbf{q}j}$ and ${\\bf e_{q}}_{j}$ give the phonon frequency and polarization vector of the phonon mode labeled by a set $\\{\\mathbf{q},j\\}$ , respectively. Since DðqÞ is an Hermitian matrix, its eigenvalues, $\\omega_{\\mathbf{q}j}^{2}$ , are real. Usually DðqÞ is arranged to be a $3n_{\\mathrm{a}}\\times3n_{\\mathrm{a}}$ matrix [30], where 3 comes from the freedom of the Cartesian indices for crystal and $n_{\\mathrm{a}}$ is the number of atoms in a unit cell. Then ${\\mathbf{e_{q}}}_{j}$ becomes a complex column vector with $3n_{\\mathrm{a}}$ elements, and usually ${\\bf e_{q}}_{j}$ is normalized to be 1, i.e., $\\begin{array}{r}{\\sum_{\\alpha\\kappa}|e_{\\mathbf q_{j}}^{\\alpha\\kappa}|^{2}=1}\\end{array}$ . ${\\bf e_{q}}_{j}$ contains information of collective motion of atoms. This may be understood as a set of atomic displacement vectors, \n\n$$\n[\\mathbf{u}(l1),\\dots,\\mathbf{u}(l\\kappa)]=\\left[{\\frac{A}{\\sqrt{m_{1}}}}\\mathbf{e_{qj}^{1}}e^{i\\mathbf{q}\\cdot\\mathbf{r}(l1)},\\dots,{\\frac{A}{\\sqrt{m_{n}}}}\\mathbf{e_{qj}^{n_{\\mathrm{{a}}}}}e^{i\\mathbf{q}\\cdot\\mathbf{r}(l\\kappa)}\\right],\n$$ \n\nwhere $A$ is the complex constant undetermined by Eq. (3), and $\\mathbf{e_{q}^{\\kappa}}{}^{\\mathrm{T}}=\\left(e_{\\mathbf{q}j}^{x\\kappa},e_{\\mathbf{q}j}^{y\\kappa},e_{\\mathbf{q}j}^{z\\kappa}\\right)$ \n\nAs a typical example, the phonon band structure and phonon density of states (DOS) of Al are shown in Fig. 1. The phonon DOS is defined as \n\n$$\ng(\\omega)=\\frac{1}{N}\\sum_{\\mathbf{q}j}\\delta(\\omega-\\omega_{\\mathbf{q}j}),\n$$ \n\nwhere $N$ is the number of unit cells in crystal. Divided by N, $g(\\omega)$ is normalized so that the integral over frequency becomes $3n_{\\mathrm{a}}$ . The phonon band structure can be directly comparable with experimental data by neutron or $\\mathsf{X}.$ -ray inelastic scattering. They often show reasonable agreements [20,31,32]. Frequency data by Raman and infrared (IR) spectroscopy can also be well reproduced [12,33]. \n\n![](images/cd061426c3952aaa5959eeb84741e94d2ec790b892981826c6acf8337ee2be6a.jpg) \nFig. 1. Phonon band structure and DOS of Al. \n\nIrreducible representations of phonon modes, which can be used to assign Raman or IR active modes, are calculated from polarization vectors [12,34]. Atom specific phonon DOS projected along a unit direction vector $\\hat{\\bf n}$ is defined as \n\n$$\ng_{\\kappa}(\\omega,\\hat{\\mathbf{n}})=\\frac{1}{N}{\\sum_{\\mathbf{q}j}\\delta{(\\omega-\\omega_{\\mathbf{q}j})}\\left|\\hat{\\mathbf{n}}\\cdot\\mathbf{e}_{\\mathbf{q}j}^{\\kappa}\\right|}^{2}.\n$$ \n\nThis $g_{\\kappa}(\\omega,\\hat{\\mathbf n})$ can be directly compared with that measured by means of nuclear-resonant inelastic scattering using synchrotron radiation. In Ref. [17], phonon calculations of $\\mathtt{L1}_{0}$ -type FePt projected along the $c$ -axis and basal plane are well comparable to experimental $^{57}\\mathrm{Fe}$ nuclear-resonant inelastic scattering spectra measured at $10\\mathrm{K}$ in the parallel and perpendicular geometries, respectively. \n\nOnce phonon frequencies over Brillouin zone are known, from the canonical distribution in statistical mechanics for phonons under the harmonic approximation, the energy $E$ of phonon system is given as \n\n$$\nE=\\sum_{\\mathbf{q}j}\\hbar\\omega_{\\mathbf{q}j}\\left[\\frac{1}{2}+\\frac{1}{\\exp(\\hbar\\omega_{\\mathbf{q}j}/k_{\\mathrm{B}}T)-1}\\right],\n$$ \n\nwhere $T,\\ k_{\\mathrm{B}}$ , and $\\hbar$ are the temperature, the Boltzmann constant, and the reduced Planck constant, respectively. Using the thermodynamic relations, a number of thermal properties, such as constant volume heat capacity $C_{V}$ , Helmholtz free energy $F_{\\ast}$ and entropy S, can be computed as functions of temperature [30]: \n\n$$\nC_{V}=\\sum_{{\\bf{q}}j}C_{{\\bf{q}}j}=\\sum_{{\\bf{q}}j}k_{\\mathrm{{B}}}\\left(\\frac{\\hbar\\omega_{{\\bf{q}}j}}{k_{\\mathrm{{B}}}T}\\right)^{2}\\frac{\\exp(\\hbar\\omega_{{\\bf{q}}j}/k_{\\mathrm{B}}T)}{\\left[{\\exp(\\hbar\\omega_{{\\bf{q}}j}/k_{\\mathrm{{B}}}T)-1}\\right]^{2}},\n$$ \n\n$$\n\\boldsymbol{F}=\\frac{1}{2}\\sum_{\\mathbf{q}j}\\hbar\\omega_{\\mathbf{q}j}+k_{\\mathrm{B}}T\\sum_{\\mathbf{q}j}\\ln{\\left[1-\\exp(-\\hbar\\omega_{\\mathbf{q}j}/k_{\\mathrm{B}}T)\\right]},\n$$ \n\nand \n\n$$\n\\begin{array}{c}{{S{=}\\displaystyle\\frac{1}{2T}\\sum_{{\\bf{q}}i}{\\hbar\\omega_{{\\bf{q}}i}\\coth\\left[{\\hbar\\omega_{{\\bf{q}}i}\\o{T}}\\right]}}}\\\\ {{{-}k_{\\mathrm{B}}\\displaystyle\\sum_{{\\bf{q}}i}{\\ln\\left[{2\\sinh({\\hbar\\omega_{{\\bf{q}}i}\\o{T}})}\\right]}.}}\\end{array}\n$$ \n\nThe calculated $F,\\ C_{V}$ , and $S$ for Al are shown in Fig. 2. \n\n# 3. Mean square atomic displacements \n\nWith the phase factor convention of the dynamical matrix used in Eq. (4), an atomic displacement operator is written as, \n\n$$\n\\hat{u}_{\\alpha}({l}\\kappa)=\\sqrt{\\frac{\\hbar}{2N m_{\\kappa}}}{\\sum_{{\\bf q}j}}\\frac{\\hat{a}_{{\\bf q}j}+\\hat{a}_{-{\\bf q}j}^{\\dagger}}{\\sqrt{\\omega_{{\\bf q}j}}}e_{{\\bf q}j}^{\\alpha\\kappa}e^{i{\\bf q}\\cdot{\\bf r}(l\\kappa)},\n$$ \n\n![](images/dec8bb0351bd980087eeb19aefeaf2c4c6798d64c1e999a439e35cb7439f9ed8.jpg) \nFig. 2. Thermal properties of Al. Entropy, $C_{V}$ , and Helmholtz free energy were calculated with harmonic approximation (Section 2). QHA was employed to obtain $C_{P}$ (Section 4). Physical units are shown with labels of the physical properties, and the value of the vertical axis is shared by them. Dotted curve depicts the experiment of $C_{P}$ [35]. \n\nwhere $\\hat{\\boldsymbol{a}}^{\\dagger}$ and $\\hat{\\boldsymbol{a}}$ are the creation and annihilation operators, respectively. Distributions of atoms around their equilibrium positions are then obtained as the expectation values of Eq. (12). The mean square atomic displacement projected along $\\hat{\\bf n}$ is obtained as \n\n$$\n\\left\\langle\\left|\\widehat{u}_{\\widehat{\\mathbf{n}}}(\\kappa)\\right|^{2}\\right\\rangle=\\frac{\\hbar}{2\\mathrm{N}\\mathrm{m}_{\\kappa}}\\sum_{\\mathbf{q}j}\\frac{1+2n_{\\mathbf{q}j}}{\\omega_{\\mathbf{q}j}}\\left|\\widehat{\\mathbf{n}}\\cdot\\mathbf{e}_{\\mathbf{q}j}^{\\kappa}\\right|^{2},\n$$ \n\nwhere $n_{\\mathbf q{j}}=\\left[\\exp({\\hbar\\omega_{\\mathbf q{j}}}/{k_{\\mathrm{B}}T})-1\\right]^{-1}$ is the phonon occupation number. Eq. (13) is lattice-point $(l)$ independent since the phase factor disappears. Anisotropic atomic displacement parameters (ADPs) to estimate the atom positions during thermal motion can also be computed and compared with experimental neutron diffraction data. Thermal ellipsoids may be discussed using mean square displacement matrix $\\mathsf{B}(\\kappa)$ defined by \n\n$$\n\\mathbf{B}(\\kappa)=\\frac{\\hbar}{2N m_{\\kappa}}\\sum_{\\mathbf{q}j}\\frac{1+2n_{\\mathbf{q}j}}{\\omega_{\\mathbf{q}j}}\\mathbf{e}_{\\mathbf{q}j}^{\\kappa}\\otimes\\mathbf{e}_{\\mathbf{q}j}^{\\kappa*}.\n$$ \n\nThe shape and orientation of an ellipsoid is obtained solving eigenvalue problem of this matrix. The method has been applied to show the ORTEP (Oak Ridge Thermal Ellipsoid Plot)-style drawing of ADPs [18]. Ref. [11] shows an example for a ternary carbide $\\mathrm{Ti}_{3}\\mathrm{SiC}_{2}$ having a layered structure known as MAX phases, in which we can see good agreement between calculated and experimental ADPs. \n\n# 4. Quasi-harmonic approximation \n\nBy changing volume, phonon properties vary since the crystal potential is an anharmonic function of volume. In this article, the term ‘‘quasi-harmonic approximation (QHA)’’ means this volume dependence of phonon properties, but the harmonic approximation is simply applied at each volume. Fig. 3a shows calculated phonon frequencies of Al at $X$ and $L$ points with respect to ten different unit-cell volumes. Typically phonon frequency decreases by increasing volume, and the slope of each phonon mode is nearly constant in the wide volume range. The normalized slope is called mode-Grüneisen parameter that is defined as \n\n$$\n\\gamma_{\\mathbf{q}j}(V)=-\\frac{V}{\\omega_{\\mathbf{q}j}(V)}\\frac{\\partial\\omega_{\\mathbf{q}j}(V)}{\\partial V}.\n$$ \n\nOnce dynamical matrix is known, $\\gamma_{\\mathbf{q}j}$ is easily calculated from the volume derivative of the dynamical matrix [29], \n\n$$\n\\gamma_{\\mathbf q{j}}(V)=-\\frac{V}{2{(\\omega_{\\mathbf q{j}})}^{2}}\\sum_{\\alpha\\beta\\kappa\\kappa^{\\prime}}e_{\\mathbf q{j}}^{\\alpha\\kappa*}\\frac{\\partial D_{\\kappa\\kappa^{\\prime}}^{\\alpha\\beta}(V,\\mathbf q)}{\\partial V}e_{\\mathbf q{j}}^{\\beta\\kappa^{\\prime}}.\n$$ \n\n![](images/6ccd8dee3e6368110724c1f477226865f5a7d1bc24477b106a3e37d5d342c52a.jpg) \nFig. 3. (a) Phonon frequencies of Al at $X$ and L points with respect to unit cell volume are shown by filled and open circles, respectively. The solid and dotted lines are guides to the eye. (b) $U_{\\mathrm{el}}+F_{\\mathrm{ph}}$ of Al with respect to volume at temperatures from 0 to $800\\mathrm{K}$ with $100\\mathrm{K}$ step are depicted by filled circles and the values are fit by the solid curves. Cross symbols show the energy bottoms of the respective curves and simultaneously the equilibrium volumes. Lines connecting the cross symbols are guides to the eye. (c) Volumetric thermal expansion coefficient of Al. Calculation is shown with solid curve and experiments are depicted by filled circle symbols [36] and dotted curve [37]. \n\nThe quantity can be related to macroscopic Grüneisen parameter $\\gamma$ using mode contributions to the heat capacity $C_{\\mathbf{q}j}$ found in Eq. (9), $\\begin{array}{r}{\\gamma=\\sum_{\\mathbf{q}j}\\gamma_{\\mathbf{q}j}C_{\\mathbf{q}j}/C_{V}}\\end{array}$ [28,30]. \n\nSilicon is known as a famous exception to have large negative mode-Grüneisen parameters. Mode-Grüneisen parameter is a measure of anharmonicity of phonon modes and is related to third-order force constants directly [29]. Therefore crystals that possess large anharmonic terms beyond third-order terms in Eq. (1) can show non-linear change of phonon frequency with respect to volume. This is often observed in crystals that exhibit second- or higher-order structural phase transitions [6]. \n\nThe phonon frequency influences the phonon energy through Eq. (8). The thermal properties are thereby affected. Using thermodynamics definition, thermodynamic variables at constant volume is transformed to those at constant pressure that is often more easily measurable in experiments. Gibbs free energy $G(T,p)$ at given temperature $T$ and pressure $p$ is obtained from Helmholtz free energy $F(T;V)$ through the transformation, \n\n$$\nG(T,p)=\\operatorname*{min}_{V}[F(T;V)+p V],\n$$ \n\nwhere the right hand side of this equation means finding a minimum value in the square bracket by changing volume $V.$ We may approximate $F(T;V)$ by the sum of electronic internal energy $U_{\\mathrm{el}}(V)$ and phonon Helmholtz free energy $F_{\\mathrm{ph}}(T;V)$ , i.e., $F(T;V)\\simeq U_{\\mathrm{el}}(V)+F_{\\mathrm{ph}}(T;V).\\ U_{\\mathrm{el}}(V)$ is obtained as total energy of electronic structure from the first principles calculation, and the first principles phonon calculation at $T$ and $V$ gives $F_{\\mathrm{ph}}(T;V)$ . The calculated $U_{\\mathrm{el}}(V)+F_{\\mathrm{ph}}(T;V)$ are depicted by the filled circle symbols in Fig. 3b, where the ten volume points chosen are the same as those in Fig. 3a. The nine curves are the fits to equation of states (EOS) at temperatures from 0 to $800\\mathrm{K}$ with $100\\mathrm{K}$ step. Here the Vinet EOS [38] was used to fit the points to the curves though any other functions can be used for the fitting. The minimum values at the temperatures are depicted by the cross symbols in Fig. 3b and are the Gibbs free energies at the temperatures and the respective equilibrium volumes are simultaneously given. Volumetric thermal expansion coefficient, bðTÞ ¼ V1T @V@ðT , is obtained from the calculated equilibrium volumes $V(T)$ at dense temperature points. $\\beta(T)$ for Al is shown in Fig. 3c, where we can see that the calculation shows reasonable agreements with the experiments. In thermodynamics, heat capacity at constant pressure $C_{P}$ is given by \n\n$$\nC_{P}(T,p)=-T{\\frac{\\partial^{2}G(T,p)}{\\partial T^{2}}}=C_{V}(T,V(T,p))+T{\\frac{\\partial V(T,p)}{\\partial T}}{\\frac{\\partial S(T;V)}{\\partial V}}\\Bigg|_{V=V(T,p)}.\n$$ \n\nIn Eq. (18), the second term of the second equation is understood as the contribution to heat capacity from thermal expansion. $C_{P}$ for Al is shown in Fig. 2. The agreement of the calculation with the experiment is excellent. At high temperatures, the difference between $C_{P}$ and $C_{V}$ is not negligible in Al. Therefore it is essential to consider thermal expansion for heat capacity. \n\nQHA is known as a reasonable approximation in a wide temperature range below melting point except for temperatures very close to melting point where higher-order terms in Eq. (1) become evident [39]. \n\n# 5. Stability condition and imaginary mode \n\nAt equilibrium, $\\begin{array}{r}{\\frac{\\partial\\Phi}{\\partial r_{\\alpha}(l\\kappa)}=0}\\end{array}$ , a crystal is dynamically (mechanically) stable if its potential energy always increases against any combinations of atomic displacements. In the harmonic approximation, this is equivalent to the condition that all phonons have real and positive frequencies [29]. However under virtual thermodynamic conditions, imaginary frequency or negative eigenvalue can appear in the solution of Eq. (3). This indicates dynamical instability of the system, which means that the corrective atomic displacements of Eq. (5) reduce the potential energy in the vicinity of the equilibrium atomic positions. \n\nImaginary mode provides useful information to study displacive phase transition. A typical example is shown in Fig. 4a to c [16]. Imaginary modes can be found only for $\\beta$ -Ti, that has BCC structure, at both $P$ and $N$ points. This indicates that $\\beta$ -Ti is unstable at low temperature. Such imaginary modes cannot be seen for either $\\omega$ -Ti whose crystal structure is shown in Fig. 4d or $\\alpha$ -Ti (HCP). Experimentally $\\beta$ -Ti is known to occur above 1155 K. At such high temperatures, large atomic displacements can stabilize the BCC structure. In such a case, the perturbation approach is invalid. Phonons with large atomic displacements may be treated by self-consistent phonon method [29,40] or by a combination of molecular dynamics and lattice dynamics calculation [41–43], which is not discussed in this article. \n\nA given structure having imaginary phonon modes can be led to alternative structures through continuous atomic displacements and lattice deformations. The present authors systematically investigated the evolution of crystal structures from the simple cubic (SC) structure [10]. The inset of Fig. 5 shows the phonon band structure of SC-Cu $(P m\\bar{3}m)$ . Imaginary modes can be found at $M(1/2,1/2,0)$ and $X(1/2,0,0)$ points. Then the SC structure is deformed along these directions. In order to accommodate the deformation in the calculation model with the periodic boundary condition, the unit cells are expanded by $2\\times2\\times1$ for the $M$ point and $2\\times1\\times1$ for the $X$ point. The $M$ point deformation breaks the crystal symmetry of SC $(P m\\bar{3}m)$ to $P4/n m m$ . The doubly degenerated instability at the $X$ point leads to Pmma and Cmcm as highest possible symmetries. The deformed crystal structures are relaxed by first principles calculations imposing the corresponding space-group operations. After these procedures, body-centered tetragonal (BCT), simple hexagonal (SH), and FCC are respectively formed. The whole procedure finishes when all crystal structures at the end-points are found to be dynamically stable. Finally a treelike structure of crystal structure relationships was drawn as shown in Fig. 5, where thick lines indicate phase transition pathways (PTPs). The space-group type written near a line is a common subgroup of initial and final structures. The presence of the line indicates that the energy decreases monotonically with the phase transition. In other words, the transition can take place spontaneously without any energy barrier. The line is terminated when the final structure is dynamically stable. \n\n![](images/fe2c36d9cbdd59049f066f0e814795640c96365d35a97052ec31da0100fb5812.jpg) \nFig. 4. Phonon band structures of (a) $\\alpha$ -Ti (HCP), (b) $\\beta$ -Ti (BCC), and (c) $\\omega$ -Ti. The figure (d) shows the hexagonal crystal structure of $\\omega$ -Ti. \n\nIn the line diagram, $\\omega$ is located at the junction of two pathways, i.e., $\\omega\\rightarrow\\mathsf{B C C}\\rightarrow\\mathsf{H C P}$ and $\\omega\\rightarrow{\\sf F C C}$ . The instability of $\\omega$ at the $\\Gamma$ point leads to BCC, which is still dynamically unstable and eventually leads to HCP. Another instability at the $M$ point leads to FCC. The other instability at the $K$ point, which is doubly degenerate, leads to FCC. On the path from $\\omega$ to BCC, the crystal symmetry of $\\omega$ having the space-group type of P6=mmm is once lowered to $P\\bar{3}m{1}$ and then becomes $I m\\bar{3}m$ (BCC) after the geometry optimization. Both x- and BCC-Cu are dynamically unstable, which can be formed only under crystal symmetry constraints. FCC-Cu is, of course, dynamically stable. Several PTPs between BCC and FCC have been proposed in literature. However, they are mostly based only upon investigation of continuous lattice deformation. For example in the classical Bain path, formation of BCT in between BCC and FCC is considered. Formation of SC is taken into account in the ‘‘trigonal Bain path’’. Normal modes of phonon, which should be most adequate to describe the collective atomic displacements, have not been considered. The presence of $\\omega$ as the lowest energy barrier in the BCC–FCC pathway had not been reported before Ref. [10]. The situation is the same for the BCC–HCP transition, known as the Burgers path. The Burgers path was thought to be quite complicated from the viewpoint of the lattice continuity. On the basis of the present study, it can be easily pointed out that the BCC– HCP transition pathway is along the space-group type of Cmcm. \n\n![](images/f0299d5b318b08b2c4cc1c7bca668af8ca3183e7c759caf1948a1f1f11ebf698.jpg) \nFig. 5. Line diagram of structural transition pathways in Cu. The inset shows phonon band structure of simple cubic (SC) Cu. Open and filled symbols represent dynamically unstable and stable crystal structures, respectively. Lines connecting these symbols are the phase transition pathways for which space-group types are shown near the lines. \n\nEvolution diagram was constructed in the same way for $\\mathsf{N a}R\\mathsf{T i O}_{4}$ (R: rare-earth metal) with Ruddlesden–Popper type structure [13]. Inversion symmetry breaking by oxygen octahedral rotations was unambiguously demonstrated. The mechanism is expected to lead to many more families of acentric oxides. \n\n# 6. Interactions among phonons and lattice thermal conductivity \n\nUsing the harmonic phonon coordinates, anharmonic terms in Eq. (1) are transformed to a picture of phonon–phonon interactions [8,28]. Lattice thermal conductivity can be accurately calculated by solving linearized Boltzmann transport equation with the phonon– phonon interaction strength obtained using first principles calculation [9,44,45]. Although the computational cost for such calculations is many orders of magnitudes higher than the ordinary DFT calculations of primitive cells, such calculations have already been applied for many simple compounds and computed lattice thermal conductivities show good agreements with experimental data [9,45]. Calculations with special focus on searching thermoelectric materials have also been made [14,20,45]. \n\n# Acknowledgments \n\nThe research leading to these results was supported by Grant-in-Aid for Scientific Research on Innovative Areas ‘‘Nano Informatics’’ (Grant No. 25106005) and for Young Scientists (B) (Grant No. 26820284) both from JSPS. Support from MEXT through ESISM is also acknowledged. \n\n# References \n\n[1] G. Kresse, J. Furthmüller, J. Hafner, Europhys. Lett. 32 (1995) 729. \n[2] K. Parlinski, Z.Q. Li, Y. Kawazoe, Phys. Rev. Lett. 78 (1997) 4063. \n[3] P. Giannozzi, S. de Gironcoli, P. Pavone, S. Baroni, Phys. Rev. B 43 (1991) 7231. \n[4] X. Gonze, C. Lee, Phys. Rev. B 55 (1997) 10355. \n[5] A. Togo, Phonopy, http://phonopy.sourceforge.net/. \n[6] A. Togo, F. Oba, I. Tanaka, Phys. Rev. B 78 (2008) 134106. \n[7] A. Togo, L. Chaput, I. Tanaka, G. Hug, Phys. Rev. B 81 (2010) 174301. [8] L. Chaput, A. Togo, I. Tanaka, G. Hug, Phys. Rev. B 84 (2011) 094302. [9] A. Togo, L. Chaput, I. Tanaka, Phys. Rev. B 91 (2015) 094306. \n[10] A. Togo, I. Tanaka, Phys. Rev. B 87 (2013) 184104. \n[11] N.J. Lane, S.C. Vogel, G. Hug, A. Togo, L. Chaput, L. Hultman, M.W. Barsoum, Phys. Rev. B 86 (2012) 214301. \n[12] A. Togo, F. Oba, I. Tanaka, Phys. Rev. B 77 (2008) 184101. \n[13] H. Akamatsu, K. Fujita, T. Kuge, A. Sen Gupta, A. Togo, S. Lei, F. Xue, G. Stone, J.M. Rondinelli, L.-Q. Chen, I. Tanaka, V. Gopalan, K. Tanaka, Phys. Rev. Lett. 112 (2014) 187602. \n[14] J.M. Skelton, S.C. Parker, A. Togo, I. Tanaka, A. Walsh, Phys. Rev. B 89 (2014) 205203. \n[15] A. Matsumoto, Y. Koyama, A. Togo, M. Choi, I. Tanaka, Phys. Rev. B 83 (2011) 214110. \n[16] K. Edalati, T. Daio, M. Arita, S. Lee, Z. Horita, A. Togo, I. Tanaka, Acta Mater. 68 (2014) 207. \n[17] Y. Tamada, R. Masuda, A. Togo, S. Yamamoto, Y. Yoda, I. Tanaka, M. Seto, S. Nasu, T. Ono, Phys. Rev. B 81 (2010) 132302. \n[18] V.L. Deringer, R.P. Stoffel, A. Togo, B. Eck, M. Meven, R. Dronskowski, CrystEngComm 16 (2014) 10907. \n[19] Y. Ikeda, . Seko, A. Togo, I. Tanaka, Phys. Rev. B 90 (2014) 134106. \n[20] Tanaka, G.K.H. Madsen, J. Appl. Phys. 117 (2015) 045102. 2 B 50 (1994) 17953. 2 erdew Burk Ernzerhof, Phys. Rev. Lett. 77 (1996) 3865. Kresse, Solids 193 (1995) 222. \n[24] Kresse Comput. Mater. Sci. 6 (1996) 15. 25 Kresse . Rev. B 59 (1999) 1758. \n[26] M. Methfess Phys. Rev. B 40 (1989) 3616. \n[27] . Ziman on Phonons, Oxford University Press, 2001. \n[28] .P. Srivastava ysics of Phonons, CRC Press, 1990. \n[29] D.C. Wallace, Thermodynamics of Crystals, Dover Publications, 1998. \n[30] M.T. Dove, Introduction to Lattice Dynamics, Cambridge University Press, 1993. \n[31] F. Körmann, A. Dick, B. Grabowski, T. Hickel, J. Neugebauer, Phys. Rev. B 85 (2012) 125104. \n[32] F. Körmann, B. Grabowski, B. Dutta, T. Hickel, L. Mauger, B. Fultz, J. Neugebauer, Phys. Rev. Lett. 113 (2014) 165503. \n[33] A. Kuwabara, T. Tohei, T. Yamamoto, I. Tanaka, Phys. Rev. B 71 (2005) 064301. \n[34] G. Venkataraman, L.A. Feldkamp, V.C. Sahni, Dynamics of Perfect Crystals, MIT press, 1975. \n[35] M.W. Chase, Jr., NIST-JANAF Thermochemical Tables, Journal of Physical and Chemical Reference Data Monographs, American Inst. of Physics, 1998. \n[36] A.J.C. Wilson, Proc. Phys. Soc. 53 (1941) 235. \n[37] F.C. Nix, D. MacNair, Phys. Rev. 60 (1941) 597. \n[38] P. Vinet, J.H. Rose, J. Ferrante, J.R. Smith, J. Phys.: Condens. Matter 1 (1989) 1941. \n[39] B. Grabowski, . Ismer, T. Hickel, J. Neugebauer, Phys. Rev. B 79 (2009) 134106. \n[40] I. Errea, Calandra, F. Mauri, Phys. Rev. B 89 (2014) 064302. \n[41] C.Z Wang, Chan, K.M. Ho, Phys. Rev. B 42 (1990) 11276. \n[42] C. Lee, D. Vanderbilt, K. Laasonen, R. Car, M. Parrinello, Phys. Rev. B 47 (1993) 4863. \n[43] T. Sun, D.-B. Zhang, R.M. Wentzcovitch, Phys. Rev. B 89 (2014) 094109. \n[44] Chaput, Phys. Rev. Lett. 110 (2013) 265506. \n[45] A. Seko, A. Togo, H. Hayashi, K. Tsuda, L. Chaput, I. Tanaka, ArXiv e-prints: . " + }, + { + "id": "10.1126_science.aad1080", + "DOI": "10.1126/science.aad1080", + "DOI Link": "http://dx.doi.org/10.1126/science.aad1080", + "Relative Dir Path": "mds/10.1126_science.aad1080", + "Article Title": "Synthesis of borophenes: Anisotropic, two-dimensional boron polymorphs", + "Authors": "Mannix, AJ; Zhou, XF; Kiraly, B; Wood, JD; Alducin, D; Myers, BD; Liu, XL; Fisher, BL; Santiago, U; Guest, JR; Yacaman, MJ; Ponce, A; Oganov, AR; Hersam, MC; Guisinger, NP", + "Source Title": "SCIENCE", + "Abstract": "At the atomic-cluster scale, pure boron is markedly similar to carbon, forming simple planar molecules and cage-like fullerenes. Theoretical studies predict that two-dimensional (2D) boron sheets will adopt an atomic configuration similar to that of boron atomic clusters. We synthesized atomically thin, crystalline 2D boron sheets (i.e., borophene) on silver surfaces under ultrahigh-vacuum conditions. Atomic-scale characterization, supported by theoretical calculations, revealed structures reminiscent of fused boron clusters with multiple scales of anisotropic, out-of-plane buckling. Unlike bulk boron allotropes, borophene shows metallic characteristics that are consistent with predictions of a highly anisotropic, 2D metal.", + "Times Cited, WoS Core": 2187, + "Times Cited, All Databases": 2304, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000366591100055", + "Markdown": "25. Q. Gao, L. Demarconnay, E. Raymundo-Piñero, F. Béguin, Energy Environ. Sci. 5, 9611–9617 (2012). \n26. A. F. Burke, Advanced batteries for vehicle applications. In Encyclopedia of Automotive Engineering, D. Crolla, D. E. Foster, T. Kobayashi, N. Vaughan, Eds. (Wiley, New York, 2014), pp. 1–20. \n27. A. Burke, M. Miller, J. Power Sources 196, 514–522 (2011). \n28. D. Linden, T. B. Reddy, Handbook of Batteries (McGraw-Hill, New York, ed. 3, 2001). \n\n# ACKNOWLEDGMENTS \n\nSupported by National Natural Science Foundation of China grants 51125006, 91122034, 61376056, and 51402336 and Science and Technology Commission of Shanghai grant 14YF1406500. \n\n# NANOMATERIALS \n\n# Synthesis of borophenes: Anisotropic, two-dimensional boron polymorphs \n\nAndrew J. Mannix,1,2 Xiang-Feng Zhou,3,4 Brian Kiraly,1,2 Joshua D. Wood,2 Diego Alducin,5 Benjamin D. Myers,2,6 Xiaolong Liu,7 Brandon L. Fisher,1 Ulises Santiago,5 Jeffrey R. Guest,1 Miguel Jose Yacaman,5 Arturo Ponce,5 Artem R. Oganov,8,9,3\\* Mark C. Hersam,2,7,10\\* Nathan P. Guisinger1\\* \n\nAt the atomic-cluster scale, pure boron is markedly similar to carbon, forming simple planar molecules and cage-like fullerenes.Theoretical studies predict that two-dimensional (2D) boron sheets will adopt an atomic configuration similar to that of boron atomic clusters. We synthesized atomically thin, crystalline 2D boron sheets (i.e., borophene) on silver surfaces under ultrahigh-vacuum conditions. Atomic-scale characterization, supported by theoretical calculations, revealed structures reminiscent of fused boron clusters with multiple scales of anisotropic, out-of-plane buckling. Unlike bulk boron allotropes, borophene shows metallic characteristics that are consistent with predictions of a highly anisotropic, 2D metal. \n\nB onding between boron atoms is more complex than in carbon; for example, both twoand three-center B-B bonds can form $(I)$ . The interaction between these bonding configurations results in as many as 16 bulk allotropes of boron (1–3), composed of icosahedral $\\mathbf{B}_{12}$ units, small interstitial clusters, and fused supericosahedra. In contrast, small $(n<15)$ boron clusters form simple covalent, quasiplanar molecules with carbon-like aromatic or anti-aromatic electronic structure (4–7). Recently, Zhai et al. have shown that $\\mathbf{B}_{40}$ clusters form a cage-like fullerene $\\scriptstyle(6),$ further extending the parallels between boron and carbon cluster chemistry. \n\nTo date, experimental investigations of nanostructured boron allotropes are notably sparse, partly owing to the costly and toxic precursors (e.g., diborane) typically used. However, numerous theoretical studies have examined twodimensional (2D) boron sheets [i.e., borophene (7)]. Although these studies propose various structures, we refer to the general class of 2D boron sheets as borophene. Based upon the quasiplanar $\\mathbf{B}_{7}$ cluster (Fig. 1A), Boustani proposed an Aufbau principle (8) to construct nanostructures, including puckered monolayer sheets (analogous to the relation between graphene and the aromatic ring). The stability of these sheets is enhanced by vacancy superstructures $(7,9)$ or out-of-plane distortions (10, 11). Typically, borophene is predicted to be metallic (7, 9–12) or semimetallic (10) and is expected to exhibit weak binding (13) and anisotropic growth (14) when adsorbed on noble-metal substrates. Early reports of multiwall boron nanotubes suggested a layered structure (15), but their atomic-scale structure remains unresolved. It is therefore unknown whether borophene is experimentally stable and whether the borophene \n\nI.W.C. was supported by U.S. Department of Energy BES grant DE-FG02-11ER46814 and used the facilities (Laboratory for Research on the Structure of Matter) supported by NSF grant DMR-11-20901. \n\nstructure would reflect the simplicity of planar boron clusters or the complexity of bulk boron phases. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/350/6267/1508/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S14 \nTables S1 and S2 \nReferences (29–32) \n\n20 April 2015; accepted 13 November 2015 \n10.1126/science.aab3798 \n\nWe have grown atomically thin, borophene sheets under ultrahigh-vacuum (UHV) conditions (Fig. 1B), using a solid boron atomic source $(99.9999\\%$ purity) to avoid the difficulties posed by toxic precursors. An atomically clean Ag(111) substrate provided a well-defined and inert surface for borophene growth (13, 16). In situ scanning tunneling microscopy (STM) images show the emergence of planar structures exhibiting anisotropic corrugation, which is consistent with first-principles structure prediction. We further verify the planar, chemically distinct, and atomically thin nature of these sheets via a suite of characterization techniques. In situ electronic characterization supports theoretical predictions that borophene sheets are metallic with highly anisotropic electronic properties. This anisotropy is predicted to result in mechanical stiffness comparable to that of graphene along one axis. Such properties are complementary to those of existing 2D materials and distinct from those of the metallic boron previously observable only at ultrahigh pressures $(I7)$ . \n\nDuring growth, the substrate was maintained between $450^{\\circ}$ and $700^{\\circ}\\mathrm{C}$ under a boron flux between ${\\sim}0.01$ to ${\\sim}0.1$ monolayer (ML) per minute [see supplementary materials for details (18)]. After deposition, in situ Auger electron spectroscopy (AES; Fig. 1C) revealed a boron KLL peak at the standard position $\\mathrm{(180~eV)}$ superimposed on the clean Ag(111) spectrum. We observed no peaks due to contaminants, and none of the distinctive peak shifts or satellite features characteristic of compound or alloy formation (fig. S1). \n\nAfter boron deposition at a substrate temperature of $550^{\\circ}\\mathrm{C},$ , STM topography images (Fig. 1D) revealed two distinct boron phases: a homogeneous phase and a more corrugated “striped” phase (highlighted with red and white arrows, respectively). Simultaneously acquired dI/dV maps (where $I$ and $V$ are the tunneling current and voltage, respectively) of the electronic density of states (DOS), given in Fig. 1E, showed strong electronic contrast between boron sheets and the $\\mathbf{Ag}(\\mathrm{{111}})$ substrate and increased differentiation between homogeneous and striped islands. The relative concentration of these phases depends upon the deposition rate. Low deposition rates favored the striped phase and resulted in the corrugation. The rectangular structure (inset) is defined by vectors a and $\\mathbf{b}$ of lengths $0.51\\ \\mathrm{nm}$ $_{\\pm0.02\\mathrm{nm}})$ and $0.29\\mathrm{nm}$ ${\\bf\\chi}_{\\pm0.02\\ n m},$ , respectively. Within the striped regions, the in-plane periodicity parallel to the a vector is reduced by the increased out-of-plane corrugation associated with the stripes. However, the periodicities along the stripes match those of the rectangular lattice in the b direction. Further analysis [see supplementary text (18)] shows that the striped regions are simple distortions of the rectangular lattice that maximize the number of ideal boron adsorption sites (fig. S5). The formation of these stripes was temperature-dependent, with fewer stripes observed at $450^{\\circ}\\mathrm{C}$ and almost complete stripe coverage at $700^{\\circ}\\mathrm{C}$ . This is consistent with a progressive, thermally driven relaxation of the rectangular lattice into more favorable adsorption sites. \n\n![](images/4f8dd44e1dcb4c3f28c7903ad36c5274144fe7ab895d700a698d85de8333100b.jpg) \n\n![](images/000d18a5f85909fa3910e8a7f58a3f726642c69111755605cb9f5c523d4f1a80.jpg) \nFig. 1. Growth and atomic-scale characterization of borophene sheets. Schematics of (A) distorted $\\mathsf{B}_{7}$ cluster and (B) growth 20 nm setup with atomic structure model and STM topography rendering. (C) AES spectra of clean Ag(111) before and after boron deposition. (D to I) Series of large-scale STM topography (left) and closed-loop dI/dV (right) images of borophene sheets, showing (D and E) low coverage $(V_{\\mathrm{sample}}=2.0$ V, $I_{t}=100~\\mathsf{p A};$ , (F and $\\mathsf{G}$ ) medium coverage $\\langle V_{\\mathrm{sample}}=3.5\\$ V, $I_{t}=100$ pA), and (H and I) high coverage $(V_{\\mathrm{sample}}=$ $3.5~\\lor,$ $I_{\\mathrm{t}}=100~\\mathsf{p A})$ . Regions of homogeneous-phase, striped-phase island, and striped-phase nanoribbon are indicated with red, white, and bl respectively. (J to L) STM topography images showing (J) striped-phase atomic-scale structure $\\ensuremath{\\langle V_{\\mathrm{sample}}=0.1V}$ , $I_{t}=1.0$ nA). Inset shows rectangular lattice with overlaid lattice vectors. (K) Striped phase with rhombohedral (indicated by white rhombus) and honeycomb (indicated by purple arrow) Moiré patterns $(\\mathsf{V}_{\\mathsf{s a m p l e}}=$ $3.5~\\mathrm{V},$ $\\mathsf{I}_{\\mathrm{t}}=100$ pA). (L) Striped-phase island, demonstrating carpet-mode growth $(V_{\\mathrm{sample}}=3.5\\ V$ , $I_{t}=100~\\mathsf{p A}.$ ). Inset shows atomic continuity across $\\mathsf{A g}(\\mathtt{l}\\mathtt{l}\\mathtt{l})$ step $(V_{\\mathrm{sample}}=-0.5$ V, $I_{t}=700~\\mathsf{p A},$ ). \n\ngrowth of striped-phase nanoribbons (blue arrow, also fig. S2). At higher deposition rates, we observed more of the homogeneous islands (Fig. 1, F and G). Increasing growth temperatures favored the striped phase, suggesting that the homogeneous phase is metastable relative to the striped phase. Both phases exhibited threefold orientation degeneracy with respect to the substrate, as confirmed by low-energy electron diffraction (fig. S3). The island size for both phases resembles that of graphene grown on Ag(111) (19). \n\nAt boron coverage approaching $1.0\\mathrm{ML}$ , the substrate is completely covered by boron sheets and sparse clusters (Fig. 1, H and I). \n\nHigh-resolution STM images show anisotropic atomic-scale features for both phases. The homogeneous phase (fig. S4) appears as atomic chains $\\mathrm{0.30nm}$ periodicity) with periodic vertical buckling, a short-range rhombohedral Moiré pattern, and a longer-range 1D Moiré pattern (fig. S4). The striped phase (Fig. 1J) consists of a rectangular lattice commensurate with regions of striped \n\nRotationally misaligned striped-phase islands coalesce via defects that accommodate the anisotropic corrugations to form a complete monolayer (fig. S5). As shown in Fig. 1K, the striped regions exhibited Moiré patterns with rhombohedral ${\\cdot}8\\mathrm{nm}$ period, marked by white rhombus) or, far less commonly, honeycomb (indicated by purple arrow) symmetry. These observations indicate the possibility of at least two well-defined long-range structural relationships between borophene and $\\mathrm{Ag(111)}$ . The borophene superstructure is evidently more complex than planar 2D materials such as BN, which forms a well-defined nanomesh on transition metals (20, 21) due to substrate interactions. The mildly attractive B-Ag interactions, (21) result in enhanced corrugation and substrate-stabilized structural variation in borophene, providing additional degrees of freedom for functionality beyond those of conventional 2D materials. \n\n![](images/c75deff4ad2e2b79f517b390aa288f3da47e0865757c76d36fb8ed9c1f7ea445.jpg) \nFig. 3. Borophene structural and chemical characterization. Cross-sectional AC-STEM images from (A) HAADF and (B) ABF detectors. (C) Juxtaposition (left to right) of Si-capped borophene structure model, simulated ABF image, and magnified ABF image. (D) XPS B 1s core–level spectra and fitted components for samples with and without Si capping layers. (E) Angle-resolved XPS data acquired on Si-capped samples. Inset: schematic showing measurement angle and sample structure determined by angle-resolved XPS. \n\nFrequently, borophene growth over the substrate step edges is observed [i.e., “carpet mode” growth (22)], as in Fig. 1L. This continuity of the atomic-scale structure over the step (inset) suggests that the borophene is structurally distinct from the underlying substrate. \n\nThese experimental results are further elucidated by ab initio evolutionary structure prediction with the USPEX algorithm (23, 24), which minimizes the thermodynamic potential of the system using density functional theory (DFT). Structures calculated with varying concentrations of Ag and B atoms on the Ag(111) substrate show surface segregation of B (fig. S6), indicating that the formation of a B-Ag surface alloy or boride is highly improbable (16, 25). Additional calculations predict likely monolayer (fig. S7) and bilayer (fig. S8) borophene structures on Ag(111), although height measurements (see following discussion) supported a monolayer model. \n\nThe lowest-energy monolayer structure is shown in Fig. 2, A and B, and is constructible from distorted $\\mathbf{B}_{7}$ clusters using the Aufbau principle proposed by Boustani (8). The symmetry (space group Pmmn) and calculated lattice constants agree well with the STM data, with a and b equal to $0.500\\ \\mathrm{nm}$ and $0.289~\\mathrm{nm}$ , respectively. Comparison between simulated (Fig. 2C) and experimental STM topography images (Fig. 2D, also fig. S7) gives excellent agreement, as do electron diffraction data (fig. S3). Freestanding relaxation of this structure removes the slight corrugations along the a direction, but preserves the buckling along the b direction (fig. S7). The freestanding sheet may exhibit instability against longwavelength transversal thermal vibrations (fig. S7), which may contribute to the observed stripe formation and would likely distort the structure of the borophene sheet upon removal from the growth substrate. This substrate-induced stability frames borophene as an intermediate class of templated, covalently bound sheets with properties distinct from those of conventional 2D materials and more consistent structure than that of supported silicon phases (26). \n\n![](images/d06c74682e32669dbf5fc5d7978a180a79966c7a9b6ef7c9de9f39164426e1a9.jpg) \nFig. 4. Scanning tunneling spectroscopy of borophene. (A) STS I-V curves and (B) STS dI/dV spectra [inset: clean Ag(111) dI/dV spectrum] from the borophene sheets, which demonstrate metallic characteristics (feedback loop opened at $V_{\\mathrm{sample}}=1.0$ V, $I_{t}=1.0$ nA). \n\nElectronic band structure calculations (Fig. 2E) within the 2D Brillouin zone of the relaxed, freestanding monolayer (inset) predict metallic conduction (i.e., bands crossing the Fermi level) along the $\\scriptstyle{F-X}$ and Y-S directions (parallel to the uncorrugated a direction). However, the out-of-plane corrugation along the b direction opens a band gap along the $\\boldsymbol{{\\cal T}}$ -Y and $s{-}X$ directions. As a result, borophene is a highly anisotropic metal, where electrical conductivity is confined along the chains. The calculated DOS (Fig. 2F) is likewise metallic $(9,{\\cal I I})$ . \n\nThis structure also results in substantial mechanical anisotropy (fig. S7). Owing to the strong, highly coordinated B-B bonds, the in-plane Young’s modulus (a measure of stiffness) is equal to 170 GPa·nm along the b direction, and 398 GPa·nm along the a direction, which potentially rivals graphene, at 340 GPa·nm (27). Furthermore, the out-of-plane buckling results in negative values for the in-plane Poisson’s ratio (equal to $-0.04$ along a and $-0.02$ along b), resulting in unusual properties, such as in-plane expansion under tensile strain. \n\nThe apparent topographic height of the boron islands in STM depended upon scanning parameters, with the islands appearing as depressions for sample biases $<3.2\\mathrm{V}$ (compare the images in Fig. 1, D and F). This observation is attributed to the inherent convolution between topography and electronic structure in STM measurements. Similar inversion is observed for NaCl islands (28) and graphene (19) on Ag(111). However, crosssectional, aberration-corrected scanning transmission electron microscopy (AC-STEM) unambiguously shows that the boron phase is atomically thin and structurally distinct from the Ag(111) growth substrate. AC-STEM sample preparation is detailed in fig. S9. Images acquired with the highangle annular dark field (HAADF) detector (Fig. 3A) are sensitive to the atomic number $Z$ (contrast \\~ $Z^{3/2},$ ) and show minimal contrast at the interface between the $\\mathbf{Ag}(\\mathrm{{111}})$ substrate and amorphous $\\mathrm{SiO}_{x}$ capping layer, which is consistent with the lack of electron scattering from the low-Z boron. Nevertheless, electron energyloss spectra confirm that the boron lies at the Ag(111) surface (fig. S11). Annular bright field (ABF) images (Fig. 3B and fig. S10), which are sensitive to light elements such as boron (29), revealed a planar structure (indicated by a purple arrow) at this interface. The observed contrast and structure are consistent with a simulated ABF image of the borophene structure model (Fig. 3C). Measured sheet thicknesses of ${\\sim}0.27$ to ${\\sim}0.31\\ \\mathrm{nm}$ match both the monolayer structure model and multiwalled boron nanotubes (15). \n\nX-ray photoelectron spectroscopy (XPS) measures both sample composition and the oxidation state of the species present. Although the borophene islands persisted under ambient conditions (fig. S12), the emergence of higher–binding energy features in the XPS B 1s core-level spectra (Fig. 3D) demonstrate that bare samples (black curve) were partially oxidized within several hours in ambient conditions. However, this oxidation was impeded by an amorphous silicon/silicon oxide capping layer (red curve), which delayed oxidation for several weeks (blue curve). The unoxidized, capped sample is fit by two Voigt components, which reflect the differences in chemical environment between the low- and highbuckled atoms. Increasing the photoelectron detector angle from the sample normal enhances XPS surface sensitivity, thereby selectively probing the surface and subsurface. The normalized, integrated components of angle-resolved XPS spectra on silicon-capped borophene are plotted in Fig. 3E. With increasing emission angle, the relative intensities of the carbon, silicon, and boron peaks increased, whereas the silver peak diminished. These results confirm the structure shown in the inset schematic, corroborating our AES, STM, and STEM results. Additional XPS data are given in fig. S13. \n\nAs shown above, theoretical predictions of the borophene structure forecast metallic characteristics. However, all known bulk boron allotropes are semiconductors at standard conditions, only becoming metallic at extremely high pressures $(I7)$ . Scanning tunneling spectroscopy (STS) confirms the metallic characteristics of borophene through $I{-}V$ curves (Fig. 4A) and dI/dV spectra (which measure the local electronic DOS, Fig. 4B). These show gapless (i.e., metallic) behavior consistent with the superposition between the Ag(111) surface (30) and the predicted filledstate population in borophene (Fig. 2G). These observations are likely to motivate and inform further studies of metallicity and related phenomena in 2D boron polymorphs. \n\n# REFERENCES AND NOTES \n\n1. T. Ogitsu, E. Schwegler, G. Galli, Chem. Rev. 113, 3425–3449 (2013). \n2. B. Douglas, S.-M. Ho, Structure and Chemistry of Crystalline Solids (Springer Science & Business Media, New York, 2007). \n3. A. R. Oganov et al., Nature 457, 863–867 (2009). \n4. H.-J. Zhai, B. Kiran, J. Li, L.-S. Wang, Nat. Mater. 2, 827–833 (2003). \n5. A. P. Sergeeva et al., Acc. Chem. Res. 47, 1349–1358 (2014). \n6. H.-J. Zhai et al., Nat. Chem. 6, 727–731 (2014). \n7. Z. A. Piazza et al., Nat. Commun. 5, 3113 (2014). \n8. I. Boustani, Phys. Rev. B 55, 16426–16438 (1997). \n9. H. Tang, S. Ismail-Beigi, Phys. Rev. Lett. 99, 115501 (2007). \n10. X.-F. Zhou et al., Phys. Rev. Lett. 112, 085502 (2014). \n11. K. C. Lau, R. Pandey, J. Phys. Chem. C 111, 2906–2912 (2007). \n12. E. S. Penev, S. Bhowmick, A. Sadrzadeh, B. I. Yakobson, Nano Lett. 12, 2441–2445 (2012). \n13. Y. Liu, E. S. Penev, B. I. Yakobson, Angew. Chem. Int. Ed. 52, 3156–3159 (2013). \n14. H. Liu, J. Gao, J. Zhao, Sci. Rep. 3, 3238 (2013). \n15. F. Liu et al., J. Mater. Chem. 20, 2197 (2010). \n16. H. Okamoto, J. Phase Equilibria 13, 211–212 (1992). \n17. M. I. Eremets, V. V. Struzhkin, H. Mao, R. J. Hemley, Science 293, 272–274 (2001). \n18. Additional supplementary text and data are available on Science Online. \n19. B. Kiraly et al., Nat. Commun. 4, 2804 (2013). \n20. S. Berner et al., Angew. Chem. 46, 5115–5119 (2007). \n21. F. Müller et al., Phys. Rev. B 82, 113406 (2010). \n22. H. I. Rasool et al., J. Am. Chem. Soc. 133, 12536–12543 (2011). \n23. A. R. Oganov, C. W. Glass, J. Chem. Phys. 124, 244704–244716 (2006). \n24. Q. Zhu, L. Li, A. R. Oganov, P. B. Allen, Phys. Rev. B 87, 195317 (2013). \n25. A. Kolmogorov, S. Curtarolo, Phys. Rev. B 74, 224507 (2006). \n26. B. Feng et al., Nano Lett. 12, 3507–3511 (2012). \n27. C. Lee, X. Wei, J. W. Kysar, J. Hone, Science 321, 385–388 (2008). \n28. Q. Guo et al., Surf. Sci. 604, 1820–1824 (2010). \n29. R. Ishikawa et al., Nat. Mater. 10, 278–281 (2011). \n30. J. Kliewer et al., Science 288, 1399–1402 (2000). \n\n# ACKNOWLEDGMENTS \n\nThis work was performed, in part, at the Center for Nanoscale Materials, a U.S. Department of Energy Office of Science User Facility under Contract No. DE-AC02-06CH11357. This work was also performed, in part, at the NUANCE Center, supported by the \n\nInternational Institute for Nanotechnology, Materials Research Science and Engineering Centers (NSF DMR-1121262), the Keck Foundation, the State of Illinois, and Northwestern University. A.J.M., B.K., J.D.W., X.L., J.R.G, M.C.H., and N.P.G acknowledge support by the U.S. Department of Energy SISGR (contract no. DE-FG02-09ER16109), the Office of Naval Research (grant no. N00014-14-1-0669), and the National Science Foundation Graduate Fellowship Program (DGE-1324585 and DGE-0824162). X.-F.Z thanks the National Science Foundation of China (grant no. 11174152), the National 973 Program of China (grant no. 2012CB921900), and the Program for New Century Excellent Talents in University (grant no. NCET-12-0278). U.S. thanks the National Council of Science and Technology, CONACyT (proposal no. 250836). A.R.O acknowledges support fromthe Defense Advanced Research Projects Agency (grant no. W31P4Q1210008) and the Government of Russian Federation (no. 14.A12.31.0003). D.A., M.J.Y, and A.P. acknowledge support by the National Institute on Minority Health and Health Disparities (NIMHD) in the program Research Centers in Minority Institutions Program (RCMI) Nanotechnology and Human Health Core (grant G12MD007591), the NSF PREM DMR (grant no. DMR-0934218), the Welch Foundation (grant no. AX-1615), and the Department of Defense (grant no. 64756-RT-REP). \n\n# BATTERIES \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/350/6267/1513/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S13 \nReferences (31–57) \n27 July 2015; accepted 28 October 2015 \n10.1126/science.aad1080 \n\n# Visualization of O-O peroxo-like dimers in high-capacity layered oxides for Li-ion batteries \n\nEric McCalla,1,2,3,4 Artem M. Abakumov,5,6 Matthieu Saubanère,2,3,7 \nDominique Foix,2,3,8 Erik J. Berg,9 Gwenaelle Rousse,1,3,10 Marie-Liesse Doublet,2,3,7 \nDanielle Gonbeau,2,3,8 Petr Novák,9 Gustaaf Van Tendeloo,5 \nRobert Dominko,4 Jean-Marie Tarascon1,2,3,10\\* \n\nLithium-ion (Li-ion) batteries that rely on cationic redox reactions are the primary energy source for portable electronics. One pathway toward greater energy density is through the use of Li-rich layered oxides. The capacity of this class of materials $(>270$ milliampere hours per gram) has been shown to be nested in anionic redox reactions, which are thought to form peroxo-like species. However, the oxygen-oxygen (O-O) bonding pattern has not been observed in previous studies, nor has there been a satisfactory explanation for the irreversible changes that occur during first delithiation. By using $\\mathsf{L i}_{2}\\mathsf{I r O}_{3}$ as a model compound, we visualize the O-O dimers via transmission electron microscopy and neutron diffraction. Our findings establish the fundamental relation between the anionic redox process and the evolution of the O-O bonding in layered oxides. \n\nB tcpihoaelwlhyergamvhaeoislta ebclonenersbguaytmtdererinelsie,cytrhoefnyaclalsr ecaonamdblhmeaetvroepowering electric vehicles. Li-ion batteries may also be used for grid storage and load-leveling for renewable energy. Current state-of-the-art positive electrodes use layered rock salt oxides $\\mathrm{(LiCoO_{2}}$ and its derivatives), spinel $\\mathrm{(LiMn_{2}O_{4})}$ , or polyanionic compounds such as olivine-type $\\mathrm{LiFePO}_{4}(I)$ . One push to increase the practical capacity limit of $\\mathrm{LiCoO_{2}}$ is via chemical substitution aimed at stabilizing the layered framework. The partial replacement of ${\\mathrm{Co}}^{3+}$ with $\\mathrm{Ni^{2+}}$ and $\\mathrm{{Mn}^{4+}}$ has led to the $\\mathrm{Li}(\\mathrm{Ni}_{x}\\mathrm{Mn}_{y}\\mathrm{Co}_{1-x-y})\\mathrm{O}_{2}$ layered oxides being coined as stoichiometric nickel manganese cobalt (NMC) oxides. These compounds have improved safety and capacities approaching 200 mA·hour/g. Further substitution of the transition metals by Li results in capacities exceeding $270\\mathrm{mA}{\\cdot}\\mathrm{hour}/\\mathrm{g}$ . These materials are referred to as Li-rich layered \n\nSynthesis of borophenes: Anisotropic, two-dimensional boron polymorphs \nAndrew J. Mannix, Xiang-Feng Zhou, Brian Kiraly, Joshua D. Wood, Diego Alducin, Benjamin D. Myers, Xiaolong Liu, Brandon L. Fisher, Ulises Santiago, Jeffrey R. Guest, Miguel Jose Yacaman, Arturo Ponce, Artem R. Oganov, Mark C. Hersam and Nathan P. Guisinger (December 17, 2015) \nScience 350 (6267), 1513-1516. [doi: 10.1126/science.aad1080] \n\nEditor's Summary \n\n# Borophene: Boron in two dimensions \n\nAlthough bulk allotropes of carbon and boron differ greatly, small clusters of these elements show remarkable similarities. Boron analogs of two-dimensional carbon allotropes such as graphene have been predicted. Now Mannix et al. report the formation of two-dimensional boron by depositing the elemental boron onto a silver surface under ultrahigh-vacuum conditions (see the Perspective by Sachdev). The graphene-like structure was buckled, weakly bonded to the substrate, and metallic. \n\nScience, this issue p. 1513; see also p. 1468 \n\nThis copy is for your personal, non-commercial use only. \n\n# Article Tools \n\n# Permissions \n\nObtain information about reproducing this article: http://www.sciencemag.org/about/permissions.dtl " + }, + { + "id": "10.1126_science.aaa9297", + "DOI": "10.1126/science.aaa9297", + "DOI Link": "http://dx.doi.org/10.1126/science.aaa9297", + "Relative Dir Path": "mds/10.1126_science.aaa9297", + "Article Title": "Discovery of a Weyl fermion semimetal and topological Fermi arcs", + "Authors": "Xu, SY; Belopolski, I; Alidoust, N; Neupane, M; Bian, G; Zhang, CL; Sankar, R; Chang, GQ; Yuan, ZJ; Lee, CC; Huang, SM; Zheng, H; Ma, J; Sanchez, DS; Wang, BK; Bansil, A; Chou, FC; Shibayev, PP; Lin, H; Jia, S; Hasan, MZ", + "Source Title": "SCIENCE", + "Abstract": "A Weyl semimetal is a new state of matter that hosts Weyl fermions as emergent quasiparticles and admits a topological classification that protects Fermi arc surface states on the boundary of a bulk sample. This unusual electronic structure has deep analogies with particle physics and leads to unique topological properties. We report the experimental discovery of a Weyl semimetal, tantalum arsenide (TaAs). Using photoemission spectroscopy, we directly observe Fermi arcs on the surface, as well as the Weyl fermion cones and Weyl nodes in the bulk of TaAs single crystals. We find that Fermi arcs terminate on the Weyl fermion nodes, consistent with their topological character. Our work opens the field for the experimental study of Weyl fermions in physics and materials science.", + "Times Cited, WoS Core": 2782, + "Times Cited, All Databases": 2968, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000359092900034", + "Markdown": "# Discovery of a Weyl Fermion semimetal and topological Fermi arcs \n\n# Su-Yang Xu,1,2\\* Ilya Belopolski,1\\* Nasser Alidoust,1,2\\* Madhab Neupane,1,3\\* Guang Bian,1 Chenglong Zhang,4 Raman Sankar,5 Guoqing Chang,6,7 Zhujun Yuan,4 Chi-Cheng Lee,6,7 Shin-Ming Huang,6,7 Hao Zheng,1 Jie Ma,8 Daniel S. Sanchez,1 BaoKai Wang,6,7,9 Arun Bansil,9 Fangcheng Chou,5 Pavel P. Shibayev,1,10 Hsin Lin,6,7 Shuang Jia,4,11 M. Zahid Hasan1,2† \n\n1Laboratory for Topological Quantum Matter and Spectroscopy (B7), Department of Physics, Princeton University, Princeton, NJ 08544, USA. 2Princeton Center for Complex Materials, Princeton Institute for Science and Technology of Materials, Princeton University, Princeton, NJ 08544, USA. 3Condensed Matter and Magnet Science Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. 4International Center for Quantum Materials, School of Physics, Peking University, China. 5Center for Condensed Matter Sciences, National Taiwan University, Taipei 10617, Taiwan. 6Centre for Advanced 2D Materials and Graphene Research Centre National University of Singapore, 6 Science Drive 2, Singapore 117546. 7Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117542. 8Quantum Condensed Matter Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. 9Department of Physics, Northeastern University, Boston, MA 02115, USA. 10Princeton Institute for Science and Technology of Materials, Princeton University, Princeton, New Jersey 08544, USA. 11Collaborative Innovation Center of Quantum Matter, Beijing, 100871, China. \n\n\\*These authors contributed equally to this work. †Corresponding author. E-mail: mzhasan@princeton.edu \n\nA Weyl semimetal is a crystal which hosts Weyl fermions as emergent quasiparticles and admits a topological classification that protects Fermi arc surface states on the boundary of a bulk sample. This unusual electronic structure has deep analogies with particle physics and leads to unique topological properties. We report the experimental discovery of a Weyl semimetal, TaAs. Using photoemission spectroscopy, we directly observe Fermi arcs on the surface, as well as the Weyl fermion cones and Weyl nodes in the bulk of TaAs single crystals. We find that Fermi arcs terminate on the Weyl nodes, consistent with their topological character. Our work opens the field for the experimental study of Weyl fermions in physics and materials science. \n\nWeyl fermions have long been known in quantum field theory, but have not been observed as a fundamental particle in nature (1–3). Recently, it was understood that a Weyl fermion can emerge as a quasiparticle in certain crystals, Weyl fermion semimetals (1–22). Despite being a gapless metal, a Weyl semimetal is characterized by topological invariants, broadening the classification of topological phases of matter beyond insulators. Specifically, Weyl fermions at zero energy correspond to points of bulk band degeneracy, Weyl nodes, which are associated with a chiral charge that protects gapless surface states on the boundary of a bulk sample. These surface states take the form of Fermi arcs connecting the projection of bulk Weyl nodes in the surface Brillouin zone (BZ) (6). A band structure like the Fermi arc surface states would violate basic band theory in an isolated two-dimensional system and can only arise on the boundary of a three-dimensional sample, providing a dramatic example of the bulk-boundary correspondence in a topological phase. In contrast to topological insulators where only the surface states are interesting (21, 22), a Weyl semimetal features unusual band structure in the bulk and on the surface. The Weyl fermions in the bulk are predicted to provide a condensed matter realization of the chiral anomaly, giving rise to a negative magnetoresistance under parallel electric and magnetic fields, unusual optical conductivity, non-local transport and local non-conservation of ordinary current (5, 12–16). At the same time, the Fermi arc surface states are predicted to show unconventional quantum oscillations in magnetotransport, as well as unusual quantum interference effects in tunneling spectroscopy (17–19). The prospect of the realization of these phenomena has inspired much experimental and theoretical work. (1–22). \n\nHere we report the experimental realization of a Weyl semimetal in a single crystalline material tantalum arsenide, TaAs. Utilizing the combination of the vacuum ultraviolet (lowphoton-energy) and soft X-ray (SX) angle-resolved photoemission spectroscopy (ARPES), we systematically and differentially study the surface and bulk electronic structure of TaAs. Our ultraviolet (low-photon-energy) ARPES measurements, which are highly surface sensitive, demonstrate the existence of the Fermi arc surface states, consistent with our band calculations presented here. Moreover, our SX-ARPES measurements, which are reasonably bulk sensitive, reveal the three-dimensional linearly dispersive bulk Weyl cones and Weyl nodes. Furthermore, by combining the lowphoton-energy and SX-ARPES data, we show that the locations of the projected bulk Weyl nodes correspond to the terminations of the Fermi arcs within our experimental resolution. These systematic measurements demonstrate TaAs as a Weyl semimetal. \n\nThe material system and theoretical considerations Tantalum arsenide, TaAs, is a semimetallic material that crystalizes in a body-centered tetragonal lattice system (Fig. \n\n1A) (23). The lattice constants are $a=3.437\\mathrm{A}$ and $c=11.656\\mathrm{A}$ , and the space group is $I4_{1}m d(\\#109,C_{4\\nu})$ , as consistently reported in previous structural studies (23–25). The crystal consists of interpenetrating Ta and As sublattices, where the two sub-lattices are shifted by $(\\frac{a}{2},\\frac{a}{2},\\delta)$ , $\\delta\\approx\\frac{c}{12}$ . Our diffraction data matches well with the lattice parameters and the space group $I4_{1}m d$ (26). The scanning tunneling microscopic (STM) topography (Fig. 1B) clearly resolves the (001) square lattice without any obvious defect. From the topography, we obtain a lattice constant $a=3.45\\mathrm{{\\dot{A}}}$ . Electrical transport measurements on TaAs confirmed its semimetallic transport properties and reported negative magnetoresistance suggesting the anomalies due to Weyl fermions (23). \n\nWe discuss the essential aspects of the theoretically calculated bulk band structure $(9,\\ I O)$ that predicts TaAs as a Weyl semimetal candidate. Without spin-orbit coupling, calculations $(9,\\ I O)$ show that the conduction and valence bands interpenetrate (dip into) each other to form four 1D line nodes (closed loops) located on the $k_{x}$ and $k_{y}$ planes (shaded blue in Figs. 1, C and E). Upon the inclusion of spinorbit coupling, each line node loop is gapped out and shrinks into six Weyl nodes that are away from the $k_{x}=0$ and $k_{y}=0$ mirror planes (Fig. 1E, small filled circles). In our calculation, in total there are 24 bulk Weyl cones $(9,10)$ , all of which are linearly dispersive and are associated with a single chiral charge of $\\pm1$ (Fig. 1E). We denote the 8 Weyl nodes that are located on the brown plane $(k_{z}=\\frac{2\\pi}{c})$ as W1 and the other 16 nodes that are away from this plane as W2. At the (001) surface BZ (Fig. 1F), the 8 W1 Weyl nodes are projected in the vicinity of the surface BZ edges, $\\overline{{\\boldsymbol X}}$ and $\\overline{{Y}}$ . More interestingly, pairs of W2 Weyl nodes with the same chiral charge are projected onto the same point on the surface BZ. Therefore, in total there are 8 projected W2 Weyl nodes with a projected chiral charge of $\\pm2$ , which are located near the midpoints of the $\\overline{{\\Gamma}}-\\overline{{X}}$ and the $\\overline{{\\Gamma}}-\\overline{{Y}}$ lines. Because the $\\pm2$ chiral charge is a projected value, the Weyl cone is still linear $(9)$ . The number of Fermi arcs terminating on a projected Weyl node must equal its projected chiral charge. Therefore, in TaAs, two Fermi arc surface states must terminate on each projected W2 Weyl node. \n\n# Surface electronic structure of TaAs \n\nWe carried out low-photon-energy ARPES measurements to explore surface electronic structure of TaAs. Figure 1H presents an overview of the (001) Fermi surface map. We observe three types of dominant features, namely a crescentshaped feature in the vicinity of the midpoint of each $\\overline{{\\Gamma}}-\\overline{{X}}$ or $\\overline{{\\Gamma}}-\\overline{{Y}}$ line, a bowtie-like feature centered at the $\\overline{{\\boldsymbol{X}}}$ point, and an extended feature centered at the $\\overline{{Y}}$ point. We find that the Fermi surface and the constant energy contours at shallow binding energies (Fig. 2A) violate the $C_{4}$ symmetry, considering the features at $\\overline{{\\boldsymbol X}}$ and $\\overline{{Y}}$ points. In the crystal structure of TaAs, where the rotational symmetry is implemented as a screw axis that sends the crystal back into itself after a $C_{4}$ rotation and a translation by $\\frac{c}{2}$ along the rotation axis, such an asymmetry is expected in calculation. The crystallinity of (001) surface in fact breaks the rotational symmetry. We now focus on the crescent-shaped features. Their peculiar shape suggests the existence of two arcs and their termination points in $k$ -space seem to coincide with the surface projection of the W2 Weyl nodes. Because the crescent feature consists of two non-closed curves, it can either arise from two Fermi arcs or a closed contour, however, the decisive property that clearly distinguishes one case from the other is the way in which the constant energy contour evolves as a function of energy. As shown in Fig. 2F, in order for the crescent feature to be Fermi arcs, the two non-closed curves have to move (disperse) in the same direction as one varies the energy (26). We now provide ARPES data to show that the crescent features in TaAs indeed exhibit this “co-propagating” property. To do so, we single out a crescent feature as shown in Figs. 2, B and E and show the band dispersions at representative momentum space cuts, Cut I and Cut II, as defined in Fig. 2E. The corresponding $E-k$ dispersions are shown in Figs. 2, C and D. The evolution (dispersive “movement”) of the bands as a function of binding energy can be clearly read from the slope of the bands in the dispersion maps, and is indicated in Fig. 2E by the white arrows. It can be seen that the evolution of the two non-closed curves are consistent with the copropagating property. In order to further visualize the evolution of the constant energy contour throughout $k_{x},k_{y}$ space, we use surface state constant energy contours at two slightly different binding energies, namely $E_{\\mathrm{{B}}}=0=E_{\\mathrm{{F}}}$ and $E_{\\mathrm{B}}=20~\\mathrm{meV}$ . Figure 2G shows the difference between these two constant energy contours, namely $\\Delta I(k_{x},k_{y})=I(E_{\\mathrm{B}}=20\\mathrm{meV},k_{x},k_{y})-I(E_{\\mathrm{B}}=0\\mathrm{meV},k_{x},k_{y})$ , where $I$ is the ARPES intensity. The $k$ -space regions in Fig. 2G that have negative spectral weight (red) correspond to the constant energy contour at $E_{\\mathrm{B}}=0~\\mathrm{meV}$ , whereas those regions with positive spectral weight (blue) corresponds to the contour at $E_{\\mathrm{B}}=20~\\mathrm{meV}$ . Thus one can visualize the two contours in a single $k_{x},k_{y}$ map. The alternating “red - blue - red - blue” sequence for each crescent feature in Fig. 2G shows the co-propagating property, consistent with Fig. 2F. Furthermore, we note that there are two crescent features, one located near the $k_{x}=0$ axis and the other near the $k_{y}=0$ axis, in Fig. 2G. The fact that we observe the copropagating property for two independent crescent features which are $90^{\\circ}$ rotated with respect to each other further shows that this observation is not due to artifacts, such as a $k$ misalignment while performing the subtraction. The above systematic data reveal the existence of Fermi arcs on the (001) surface of TaAs. Just like one can identify a crystal as a topological insulator by observing an odd number of Dirac cone surface states, we emphasize that our data here are sufficient to identify TaAs as a Weyl semimetal because of bulk-boundary correspondence in topology. \n\nTheoretically, the co-propagating property of the Fermi arcs is unique to Weyl semimetals because it arises from the nonzero chiral charge of the projected bulk Weyl nodes (26), which in this case is $\\pm2$ . Therefore, this property distinguishes the crescent Fermi arcs not only from any closed contour but also from the double Fermi arcs in Dirac semimetals (27, 28) because the bulk Dirac nodes do not carry any net chiral charges (26). After observing the surface electronic structure containing Fermi arcs in our ARPES data, we are able to slightly tune the free parameters of our surface calculation and obtain a calculated surface Fermi surface that reproduces and explains our ARPES data (Fig. 1G). This serves as an important cross-check that our data and interpretation are self consistent. Specifically, our surface calculation indeed also reveals the crescent Fermi arcs that connect the projected W2 Weyl nodes near the midpoints of each $\\overline{{\\Gamma}}-\\overline{{X}}$ or $\\overline{{\\Gamma}}-\\overline{{Y}}$ line (Fig. 1G). In addition, our calculation shows the bowtie surface states centered at the $\\overline{{\\boldsymbol{X}}}$ point, also consistent with our ARPES data. According to our calculation, these bowtie surface states are in fact Fermi arcs (26) associated with the W1 Weyl nodes near the BZ boundaries. However, our ARPES data cannot resolve the arc character since the W1 Weyl nodes are too close to each other in momentum space compared to the experimental resolution. Additionally, we note that the agreement between the ARPES data and the surface calculation upon the contour at the $\\overline{{Y}}$ point can be further improved by fineoptimizing the surface parameters. In order to establish the topology, it is not necessary for the data to have a perfect correspondence with the details of calculation because some changes in the choice of the surface potential allowed by the free parameters do not change the topology of the materials, as is the case in topological insulators (21, 22). In principle, Fermi arcs can coexist with additional closed contours in a Weyl semimetal $(6,9)$ , just as Dirac cones can coexist with additional trivial surface states in a topological insulator (21, 22). Particularly, establishing one set of Weyl Fermi arcs is sufficient to prove a Weyl semimetal (6). This is achieved by observing the crescent Fermi arcs as we show here by our ARPES data in Fig. 2, which is further consistent with our surface calculations. \n\n# Bulk measurements \n\nWe now present bulk-sensitive SX-ARPES (29) data, which reveal the existence of bulk Weyl cones and Weyl nodes. This serves as an independent proof of the Weyl semimetal state in TaAs. Figure 3B shows the SX-ARPES measured $k_{x}-k_{z}$ Fermi surface at $k_{y}=0$ (note that none of the Weyl nodes are located on the $k_{y}=0$ plane). We emphasize that the clear dispersion along the $k_{z}$ direction (Fig. 3B) firmly shows that our SX-ARPES predominantly images the bulk bands. SX-ARPES boosts the bulk-surface contrast in favor of the bulk band structure, which can be further tested by measuring the band dispersion along the $k_{z}$ axis in the SXARPES setting. This is confirmed by the agreement between the ARPES data (Fig. 3B) and the corresponding bulk band calculation (Fig. 3A). We now choose an incident photon energy (i.e., a $k_{z}$ value) that corresponds to the $k$ -space location of W2 Weyl nodes and map the corresponding $k_{x}-k_{y}$ Fermi surface. As shown in Fig. 3C, the Fermi points that are located away from the $k_{x}$ or $k_{y}$ axes are the W2 Weyl nodes. In Fig. 3D, we clearly observe two linearly dispersive cones that correspond to the two nearby W2 Weyl nodes along Cut 1. The $k$ -space separation between the two W2 −1 Weyl nodes is measured to be 0.08 A , which is consistent with both the bulk calculation and the separation of the two terminations of the crescent Fermi arcs measured in Fig. 2. The linear dispersion along the out-of-plane direction for the W2 Weyl nodes is shown by our data in Fig. 3E. Additionally, we also observe the W1 Weyl cones in Figs. 3G-I. Notably, our data shows that the energy of the bulk W1 Weyl nodes is lower than that of the bulk W2 Weyl nodes, which agrees well with our calculation shown in Fig. 3J and an independent modeling of the bulk transport data on TaAs (23). \n\nIn general, in a spin-orbit coupled bulk crystal, point-like linear band crossings can either be Weyl cones or Dirac cones. Because the observed bulk cones in Figs. 3C,D are located neither at Kramers' points nor on a rotational axis, they cannot be identified as bulk Dirac cones and have to be Weyl cones according to topological theories (6, 28). Therefore, our SX-ARPES data alone, proves the existence of bulk Weyl nodes. The agreement between the SX-ARPES data and our bulk calculation, which only requires the crystal structure and the lattice constants as inputs, provides further cross-check. \n\n# Bulk-surface correspondence \n\nFinally, we show that the $k$ -space locations of the surface Fermi arc terminations match with the projection of the bulk Weyl nodes on the surface BZ. We superimpose the SXARPES measured bulk Fermi surface containing W2 Weyl nodes (Fig. 3C) onto the low-photon-energy ARPES Fermi surface containing the surface Fermi arcs (Fig. 2A) to-scale. \n\nFrom Fig. 4A we see that all the arc terminations and projected Weyl nodes match with each other within the $k$ - space region that is covered in our measurements. To establish this point quantitatively, in Fig. 4C, we show the zoomed-in map near the crescent Fermi arc terminations, from which we obtain the $k$ -space location of the termina$^{-1}$  −1 \ntions to be at $\\vec{k}_{\\mathrm{arc}}=(0.04\\pm0.01\\mathrm{\\check{A}}$ , $0.51{\\pm}0.01\\mathrm{A}$ ) . Figure 4D shows the zoomed-in map of two nearby W2 Weyl nodes, from which we obtain the $k$ -space location of the W2 Weyl  −1 nodes to be at $\\vec{k}_{\\mathrm{W}2}=(0.04\\pm0.015\\mathrm{\\check{A}}$ , $0.53\\pm0.015\\mathrm{A}\\ \\mathrm{~\\Omega~}$ ) . In our bulk calculation, the $k$ -space location of the W2 Weyl $^{-1}$ \nnodes is found to be at (0.035A ,0.518A ) . Since the SXARPES bulk data and the low-photon-energy ARPES surface data are completely independent measurements using two different beamlines, the fact that they match well provides another piece of evidence of the topological nature (the surface-bulk correspondence) of the Weyl semimetal state in TaAs. In figs. S5-S7, we further show that the bulk Weyl cones can also be observed in our low-photon-energy ARPES data, although their spectral weight is much lower than the surface state intensities that dominate the data. Our demonstration of the Weyl fermion semimetal state in and Fermi arc surface metals paves the way (30) for the realization of many fascinating topological quantum phenomena.. \n\n# REFERENCES AND NOTES \n\n1. H. Weyl, Elektron und gravitation. I. Z. Phys. 56, 330–352 (1929). doi:10.1007/BF01339504 \n2. L. Balents, Weyl electrons kiss. Physics 4, 36 (2011). doi:10.1103/Physics.4.36 \n3. F. Wilczek, Why are there Analogies between Condensed Matter and Particle Theory? Phys. Today 51, 11 (1998). \n4. M. Z. Hasan, S.-Y. Xu, M. Neupane, Topological Insulators, Topological Crystalline Insulators, Topological Kondo Insulators, and Topological Semimetals. in Topological Insulators: Fundamentals and Perspectives edited by F. Ortmann, S. Roche, S. O. Valenzuela (John Wiley & Sons, 2015). \n5. H. B. Nielsen, M. Ninomiya, The Adler-Bell-Jackiw anomaly and Weyl fermions in a crystal. Phys. Lett. B 130, 389–396 (1983). doi:10.1016/0370-2693(83)91529-0 \n6. X. Wan, A. M. Turner, A. Vishwanath, S. Y. Savrasov, Topological Semimetal and Fermi-arc surface states in the electronic structure of pyrochlore iridates. Phys. Rev. B 83, 205101 (2011). doi:10.1103/PhysRevB.83.205101 \n7. B. Singh, A. Sharma, H. Lin, M. Z. Hasan, R. Prasad, A. Bansil, Topological electronic structure and Weyl semimetal in the TlBiSe2 class of semiconductors. Phys. Rev. B 86, 115208 (2012). doi:10.1103/PhysRevB.86.115208 \n8. S.-Y. Xu, Y. Xia, L. A. Wray, S. Jia, F. Meier, J. H. Dil, J. Osterwalder, B. Slomski, A. Bansil, H. Lin, R. J. Cava, M. Z. Hasan, Topological phase transition and texture inversion in a tunable topological insulator. Science 332, 560–564 (2011). Medline doi:10.1126/science.1201607 \n9. S.-M. Huang, S.-Y. Xu, I. Belopolski, C.-C. Lee, G. Chang, B. K. Wang, N. Alidoust, G. Bian, M. Neupane, C. Zhang, S. Jia, A. Bansil, H. Lin, M. Z. Hasan, A Weyl Fermion semimetal with surface Fermi arcs in the transition metal monopnictide TaAs class. Nat. Commun. 6, 7373 (2015). Medline doi:10.1038/ncomms8373 \n10. H. Weng, C. Fang, Z. Fang, F. B. Andrei Bernevig, X. Dai, Weyl semimetal phase in non-centrosymmetric transition metal monophosphides. Phys. Rev. X 5, 011029 (2015) doi:10.1103/PhysRevX.5.011029. \n11. J. Liu, D. Vanderbilt, Weyl semimetals from noncentrosymmetric topological insulators. Phys. Rev. B 90, 155316 (2014). doi:10.1103/PhysRevB.90.155316 \n12. A. A. Zyuzin, A. A. Burkov, Topological response in Weyl semimetals and the chiral anomaly. Phys. Rev. B 86, 115133 (2012). doi:10.1103/PhysRevB.86.115133 \n13. D. T. Son, B. Z. Spivak, Chiral anomaly and classical negative magnetoresistance of Weyl metals. Phys. Rev. B 88, 104412 (2013). doi:10.1103/PhysRevB.88.104412 \n14. C.-X. Liu, P. Ye, X.-L. Qi, Chiral gauge field and axial anomaly in a Weyl semimetal. Phys. Rev. B 87, 235306 (2013). doi:10.1103/PhysRevB.87.235306 \n15. H. Wei, S.-P. Chao, V. Aji, Excitonic phases from Weyl semimetals. Phys. Rev. Lett. 109, 196403 (2012). Medline doi:10.1103/PhysRevLett.109.196403 \n16. P. E. C. Ashby, J. P. Carbotte, Magneto-optical conductivity of Weyl semimetals. Phys. Rev. B 87, 245131 (2013). doi:10.1103/PhysRevB.87.245131 \n17. P. Hosur, Friedel oscillations due to Fermi arcs in Weyl semimetals. Phys. Rev. B 86, 195102 (2012). doi:10.1103/PhysRevB.86.195102 \n18. T. Ojanen, Helical Fermi arcs and surface states in time-reversal invariant Weyl semimetals. Phys. Rev. B 87, 245112 (2013). doi:10.1103/PhysRevB.87.245112 \n19. A. C. Potter, I. Kimchi, A. Vishwanath, Quantum oscillations from surface Fermi arcs in Weyl and Dirac semimetals. Nat. Commun. 5, 5161 (2014). Medline doi:10.1038/ncomms6161 \n20. S. Murakami, Phase transition between the quantum spin Hall and insulator phases in 3D: Emergence of a topological gapless phase. New J. Phys. 9, 356 (2007). doi:10.1088/1367-2630/9/9/356 \n21. M. Z. Hasan, C. L. Kane, Topological Insulators. Rev. Mod. Phys. 82, 3045–3067 (2010). doi:10.1103/RevModPhys.82.3045 \n22. X.-L. Qi, S.-C. Zhang, Topological insulators and superconductors. Rev. Mod. Phys. 83, 1057–1110 (2011). doi:10.1103/RevModPhys.83.1057 \n23. C.-L. Zhang et al., Observation of the Adler-Bell-Jackiw chiral anomaly in a Weyl semimetal. http://arxiv.org/abs/1503.02630 (2015). \n24. J. J. Murray, J. B. Taylor, L. D. Calvert, Y. Wang, E. J. Gabe, J. G. Despault, Phase relationships and thermodynamics of refractory metal pnictides: The metal-rich tantalum arsenides. J. Less Common Met. 46, 311–320 (1976). doi:10.1016/0022-5088(76)90220-4 \n25. S. Furuseth, K. Selte, A. Kjekshus, S. Gronowitz, R. A. Hoffman, A. Westerdahl, On the Arsenides and Antimonides of Tantalum. Acta Chem. Scand. 19, 95–106 (1965). doi:10.3891/acta.chem.scand.19-0095 \n26. Materials and methods are available as supplementary materials on Science Online. \n27. S.-Y. Xu, C. Liu, S. K. Kushwaha, R. Sankar, J. W. Krizan, I. Belopolski, M. Neupane, G. Bian, N. Alidoust, T. R. Chang, H. T. Jeng, C. Y. Huang, W. F. Tsai, H. Lin, P. P. Shibayev, F. C. Chou, R. J. Cava, M. Z. Hasan, Observation of Fermi arc surface states in a topological metal. Science 347, 294–298 (2015). Medline doi:10.1126/science.1256742 \n28. B.-J. Yang, N. Nagaosa, Classification of stable three-dimensional Dirac semimetals with nontrivial topology. Nat. Commun. 5, 4898 (2014). Medline doi:10.1038/ncomms5898 \n29. V. N. Strocov, X. Wang, M. Shi, M. Kobayashi, J. Krempasky, C. Hess, T. Schmitt, L. Patthey, Soft-X-ray ARPES facility at the ADRESS beamline of the SLS: Concepts, technical realisation and scientific applications. J. Synchrotron Radiat. 21, 32–44 (2014). Medline doi:10.1107/S1600577513019085 \n30. M. Z. Hasan, “Topological Insulators: A New Form of Quantum Matter,” presentation at 2014 Nobel Symposium on New Forms of Matter http://www.fysik.su.se/\\~ardonne/nobel/ns156-program.pdf (2014). \n31. J. P. Perdew, K. Burke, M. Ernzerhof, Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 77, 3865–3868 (1996). Medline doi:10.1103/PhysRevLett.77.3865 \n32. H. Weng, T. Ozaki, K. Terakura, Revisiting magnetic coupling in transition-metalbenzene complexes with maximally localized Wannier functions. Phys. Rev. B 79, 235118 (2009). doi:10.1103/PhysRevB.79.235118 \n\n# ACKNOWLEDGMENTS \n\nWork at Princeton University and Princeton-led synchrotron-based ARPES measurements were supported by the Gordon and Betty Moore Foundations EPiQS Initiative through Grant GBMF4547 (Hasan). First-principles band structure calculations at National University of Singapore were supported by the National Research Foundation, Prime Minister's Office, Singapore under its NRF fellowship (NRF Award No. NRF-NRFF2013-03). Single crystal growth was supported by National Basic Research Program of China (Grant Nos. 2013CB921901 and 2014CB239302) and characterization by U.S. DOE DE-FG02-05ER46200. F.C.C acknowledges the support provided by MOST-Taiwan under project number 102-2119-M-002-004. We gratefully acknowledge J. D. Denlinger, S. K. Mo, A. V. Fedorov, M. Hashimoto, M. Hoesch, T. Kim, and V. N. Strocov for their beamline assistance at the Advanced Light Source, the \n\nStanford Synchrotron Radiation Lightsource, the Diamond Light Source, and the Swiss Light Source. We also thank D. Huse, I. Klebanov, T. Neupert, A. Polyakov, P. Steinhardt, H. Verlinde, and A. Vishwanath for discussions. R.S. and H.L. acknowledge visiting scientist support from Princeton University. A patent application is being prepared on behalf of the authors on the discovery of a Weyl semimetal. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/cgi/content/full/science.aaa9297/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S10 \nReferences (31, 32) \n\n15 February 2015; accepted 6 July 2015 \nPublished online 16 July 2015 \n10.1126/science.aaa9297 \n\n![](images/18e5d9090eb0e2bc09ae53552e8c460a7d8abf4b2a8ce6b1cd9931df145a31f0.jpg) \nFig. 1. Crystal structure and electronic structure of TaAs. (A) Body-centered tetragonal structure of TaAs, shown as stacked Ta and As layers. The lattice of TaAs does not have space inversion symmetry. (B) STM topographic image of TaAs's (001) surface taken at the bias voltage $-300~\\mathrm{mV}$ , revealing the surface lattice constant. (C) First-principles band structure calculations of TaAs without spin-orbit coupling. The blue box highlights the locations where bulk bands touch in the BZ. (D) Illustration of the simplest Weyl semimetal state that has two single Weyl nodes with the opposite $(\\pm1)$ chiral charges in the bulk. (E) In the absence of spin-orbit coupling, there are two line nodes on the $k_{x}$ mirror plane and two line nodes on the $k_{y}$ mirror plane (red loops). In the presence of spin-orbit coupling, each line node reduces into six Weyl nodes (small black and white circles). Black and white show the opposite chiral charges of the Weyl nodes. (F) A schematic (not to-scale) showing the projected Weyl nodes and their projected chiral charges. (G) Theoretically calculated band structure (26) of the Fermi surface on the (001) surface of TaAs. (H) The ARPES measured Fermi surface of the (001) cleaving plane of TaAs. The high symmetry points of the surface BZ are noted. \n\n![](images/b3019c55c6f36325cc4e3583a52715c9090aa5567db340309022b970433c0d1e.jpg) \n\nFig. 2. Observation of topological Fermi arc surface states on the (001) surface of TaAs. (A) ARPES Fermi surface map and constant binding energy contours measured using incident photon energy of $90\\ \\mathrm{eV}$ . (B) High-resolution ARPES Fermi surface map of the crescent Fermi arcs. The $k$ - space range of this map is defined by the blue box in panel A. (C,D) Energy dispersion maps along Cuts I and II. (E) Same Fermi surface map as in panel B. The dotted lines define the $k$ - space direction for Cuts I and II. The numbers 1-6 note the Fermi crossings that are located on Cuts I and II. The white arrows show the evolution of the constant energy contours as one varies the binding energy, which is obtained from the dispersion maps in panels C and D. (F) A schematic showing the evolution of the Fermi arcs as a function of energy, which clearly distinguish between two Fermi arcs and a closed contour. (G) The difference between the constant energy contours at the binding energy $E_{\\mathrm{B}}=20~\\mathrm{meV}$ and the binding energy $E_{\\mathrm{B}}=0~\\mathrm{meV}$ , from which one can visualize the evolution of the constant energy contours through $k_{x}-k_{y}$ space. The range of this map is shown by the white dotted box in panel A. \n\n![](images/d6067e679ac19a8762ce9180b362a8b3e1eed13fd083113a2fb52b85fddd08b2.jpg) \n\nFig. 3. Observation of bulk Weyl Fermion cones and Weyl nodes in TaAs. (A,B) First-principles calculated and ARPES measured $k_{z}-k_{x}$ Fermi surface maps at $k_{y}=0$ , respectively. (C) ARPES measured and firstprinciples calculated $k_{x}-k_{y}$ Fermi surface maps at the $k_{z}$ value that corresponds to the W2 Weyl nodes. The dotted line defines the $k$ -space cut direction for Cut 1, which goes through two nearby W2 Weyl nodes along the $k_{y}$ direction. The black cross defines Cut 2, which means that the $k_{x},k_{y}$ values are fixed at the location of a W2 Weyl node and one varies the $k_{z}$ value. (D) ARPES $E-k_{y}$ dispersion map along the Cut 1 direction, which clearly shows the two linearly dispersive W2 Weyl cones. (E) ARPES $E-k_{z}$ dispersion map along the Cut 2 direction, showing that the W2 Weyl cone also disperses linearly along the out-of-plane $k_{z}$ direction. (F) First-principles calculated $E-k_{z}$ dispersion that corresponds to the Cut 2 shown in panel E. (G) ARPES measured $k_{x}-k_{y}$ Fermi surface maps at the $k_{z}$ value that corresponds to the W1 Weyl nodes. The dotted line defines the $k$ -space cut direction for Cut 3, which goes through the W1 Weyl nodes along the $k_{y}$ direction. (H,I) ARPES $E-k_{y}$ dispersion map and its zoomed-in version along the Cut 3 direction, revealing the linearly dispersive W1 Weyl cone. (J) First-principles calculation shows a $14~\\mathrm{meV}$ energy difference between the W1 and W2 Weyl nodes. \n\n# Weyl Fermion nodes and Topological Fermi arcs \n\n![](images/2f934d23e69b7f996fb8b6f93565ca3f0e7bab3ef594b8d20c8338c7b3ba1434.jpg) \nFig. 4. Surface-bulk correspondence and the topologically nontrivial state in TaAs. (A) Low-photon-energy ARPES Fermi surface map ( $h\\upsilon=90~\\mathrm{eV}$ ) from Fig. 2A, with the $\\mathsf{S X}$ - ARPES map ( $h\\upsilon=650~\\mathrm{eV}$ ) from Fig. 3C overlaid on top of it to-scale, showing that the locations of the projected bulk Weyl nodes correspond to the terminations of the surface Fermi arcs. (B) The bottom shows a rectangular tube in the bulk BZ that encloses four W2 Weyl nodes. These four W2 Weyl nodes project onto two points at the (001) surface BZ with projected chiral charges of $\\pm2$ , shown by the brown circles. The top surface shows the ARPES measured crescent surface Fermi arcs that connect these two projected Weyl nodes. (C) Surface state Fermi surface map at the $k$ -space region corresponding to the terminations of the crescent Fermi arcs. The $k$ -space region is defined by the black dotted box in panel E. (D) Bulk Fermi surface map at the $k$ -space region corresponding to the W2 Weyl nodes. The $k$ -space region is defined by the black dotted box in Fig. 3C. (E) ARPES and schematic of the crescent-shaped co-propagating Fermi arcs. " + }, + { + "id": "10.1021_acs.nullolett.5b02404", + "DOI": "10.1021/acs.nullolett.5b02404", + "DOI Link": "http://dx.doi.org/10.1021/acs.nullolett.5b02404", + "Relative Dir Path": "mds/10.1021_acs.nullolett.5b02404", + "Article Title": "Fast Anion-Exchange in Highly Luminescent nullocrystals of Cesium Lead Halide Perovskites (CsPbX3, X = Cl, Br, I)", + "Authors": "Nedelcu, G; Protesescu, L; Yakunin, S; Bodnarchuk, MI; Grotevent, MJ; Kovalenko, MV", + "Source Title": "nullO LETTERS", + "Abstract": "Postsynthetic chemical transformations of colloidal nullocrystals, such as ion-exchange reactions, provide an avenue to compositional fine-tuning or to otherwise inaccessible materials and morphologies. While cation-exchange is facile and commonplace, anion-exchange reactions have not received substantial deployment. Here we report fast, low-temperature, deliberately partial, or complete anionexchange in highly luminescent semiconductor nullocrystals of cesium lead halide perovskites (CsPbX3, X = Cl, Br, I). By adjusting the halide ratios in the colloidal nullocrystal solution, the bright photoluminescence can be tuned over the entire visible spectral region (410-700 nm) while maintaining high quantum yields of 20 80% and narrow emission line widths of 10-40 nm (from blue to red). Furthermore, fast internullocrystal anion-exchange is demonstrated, leading to uniform CsPb(Cl/Br)(3) or CsPb(Br/I)(3) compositions simply by mixing CsPbCl3, CsPbBr3, and CsPbI3 nullo crystals in appropriate ratios.", + "Times Cited, WoS Core": 2047, + "Times Cited, All Databases": 2199, + "Publication Year": 2015, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000359613700119", + "Markdown": "# Fast Anion-Exchange in Highly Luminescent Nanocrystals of Cesium Lead Halide Perovskites $(\\mathsf{C s P b}\\mathsf{X}_{3},$ $\\pmb{X}=\\pmb{C}\\pmb{l},$ , Br, I) \n\nGeorgian Nedelcu,†,‡ Loredana Protesescu,†,‡ Sergii Yakunin,†,‡ Maryna I. Bodnarchuk,†,‡ Matthias J. Grotevent,† and Maksym V. Kovalenko\\*,†,‡ \n\n†Institute of Inorganic Chemistry, Department of Chemistry and Applied Bioscience, ETH Zürich, CH-8093 Zürich, Switzerland ‡Laboratory for Thin Films and Photovoltaics, Empa − Swiss Federal Laboratories for Materials Science and Technology, CH-8600 Dübendorf, Switzerland \n\nSupporting Information \n\nABSTRACT: Postsynthetic chemical transformations of colloidal nanocrystals, such as ion-exchange reactions, provide an avenue to compositional fine-tuning or to otherwise inaccessible materials and morphologies. While cation-exchange is facile and commonplace, anion-exchange reactions have not received substantial deployment. Here we report fast, low-temperature, deliberately partial, or complete anionexchange in highly luminescent semiconductor nanocrystals of cesium lead halide perovskites $\\mathrm{\\'{CsPb}}X_{3},$ $\\mathrm{\\DeltaX=Cl}_{\\mathrm{\\Delta}}$ Br, I). By adjusting the halide ratios in the colloidal nanocrystal solution, the bright photoluminescence can be tuned over the entire visible spectral region $(410-700~\\mathrm{nm})$ while maintaining high quantum yields of $20-$ $80\\%$ and narrow emission line widths of $10{-}40~\\mathrm{nm}$ (from blue to red). Furthermore, fast internanocrystal anion-exchange is demonstrated, leading to uniform $\\mathrm{CsPb(Cl/}$ $\\left|\\mathtt{B r}\\right\\rangle_{3}$ or $\\mathrm{Cs}\\mathrm{Pb}\\big(\\mathrm{Br/I}\\big)_{3}$ compositions simply by mixing $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3},$ $\\mathbf{CsPbBr}_{3},$ and $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ nanocrystals in appropriate ratios. \n\n![](images/d5c1cf433a3b6cf533b19096153df1872d5b61bd92520f8e7330e51f3ee7d726.jpg) \n\nKEYWORDS: Nanocrystals, perovskites, metal halides, cation exchange, anion exchange, photoluminescence \n\nR aptairoanmal snytnitmhepsoisr onf cionl oNidCal sneaanrocrhysdtuales ( tNhCesg) isw ogf demand for compositional diversity, shape engineering, and new optical, electronic, magnetic, or catalytic functionalities of NCs.1,2 In this regard, postsynthetic chemical transformations of metallic, semiconducting, and magnetic NCs are increasingly useful, such as by galvanic replacement,3,4 cation-exchange reactions,5−10 or the nanoscale Kirkendall effect.11−13 These transformation routes, particularly suited to NCs due to their high surface-to-volume ratios and short diffusion path lengths, give access to a myriad of structures that are difficult or impossible to synthesize directly. The initial (parent) NC serves as a template whose size, shape, and composition can be independently modified. \n\nFor semiconductor NCs, typically metal chalcogenides, cation-exchange reactions are particularly powerful, resulting in a partial or complete replacement of cations while maintaining an uninterrupted anionic sublattice and often preserving the pre-existing shape as well.5−7 A partial list of notable examples includes (with the parent NC in parentheses) the following: the first report on cation exchange leading to $\\mathrm{Ag}_{2}\\mathrm{Se}$ (from CdSe NCs),14 CdS- ${\\cdot\\mathrm{Ag}_{2}S}$ nanorod superlattices (from CdS nanorods),15 core−shell PbTe/CdTe, PbSe/CdSe and PbS/CdS NCs (from PbTe, PbSe and PbS NCs),16,17 PbSe/PbS core−shell and dot-in-rod NCs (from respective CdSe/CdS nanomorphologies),18 PbS nanorods (from CdS nanorods),19 disk-shaped CdTe NCs (from $\\mathrm{Cu}_{2}\\mathrm{Te}$ nanodisks),20 $\\mathrm{CuIn}{\\mathrm{S}}_{2}$ NCs (from $\\mathrm{Cu}_{2\\cdot\\mathrm{x}}\\mathrm{S}\\ \\mathrm{NCs},$ ),21 InP nanoplatelets (from $\\mathrm{Cu}_{3\\cdot\\mathrm{x}}\\mathrm{P}$ nanoplatelets),22 and sequential multiple cation exchanges for obtaining metastable phases.5 In contrast to the facile extraction and replacement of cations, anion-exchange in NCs has remained elusive. Taking CdSe as an example, where $\\operatorname{Cd}^{2+}$ has at most half the radius of $S\\mathrm{e}^{2-}$ , cations are much easier to manipulate within the voids of the anionic sublattice than vice versa. The scarcity of reported examples of successful anion-exchange post-treatments in NCs is reflective of both the typical difficulties encountered (e.g., substantial resturcturing or fracturing) and the demanding reaction conditions necessary (e.g., high reaction temperatures of $160{-}450\\ ^{\\circ}\\mathrm{C}$ for $\\mathrm{{znO}}$ to $Z\\mathrm{n}\\bar{\\bf S}({\\bf S}\\mathrm{e})$ conversions23−25) or the incomplete nature of the process (e.g., partial or limited to only a few surface atomic layers26−29). In this work, we report a shift in the status quo; halide anions in metal halide semiconductor NCs can be easily extracted and replaced with another halide, owing to their single ionic charge, the rigid nature of the cationic sublattice, and an efficient vacancy-assisted diffusion mechanism. \n\nWe recently reported a simple one-step synthesis of cesium lead halide perovskites $\\mathrm{'Cs}\\mathrm{Pb}{\\mathrm{X}}_{3},$ $\\mathbf{X}=\\mathbf{Cl},$ Br, I) in the form of monodisperse colloidal nanocubes $_{4-15\\ \\mathrm{nm}}$ edge lengths).30 Through compositional modulations and quantum size-effects, the bandgap energies and photoluminescence (PL) spectra are readily tunable over the entire visible spectral region of $410-$ $700~\\mathrm{{nm}}$ . A peculiar feature of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs is that, contrary to uncoated chalcogenide NCs, dangling bonds on the surface do not impart severe midgap trap states and the as-synthesized NCs exhibit bright emission with quantum efficiencies of up to $90\\%$ in green-to-red spectral region. The fact that metal halides are significantly different from metal chalcogenides (for example, from a structural standpoint, they consist of singly charged anions and exhibit highly ionic bonding) led us to explore postsynthetic chemical transformations of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs, the subject of this work. Cation- and anion-exchange reactions of $\\mathrm{ABX}_{3}$ perovskite structures offer a very promising avenue to a plethora of optoelectronic materials. \n\n![](images/c12057e349d82842f1f203b9dd454072342a94853aa80a9f9f28eff19b546af0.jpg) \nFigure 1. (a) Schematic of the anion-exchange within the cubic perovskite crystal structure of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ along with a list of suitable reagents for each reaction when performed in organic media. A three-dimensional network is formed by corner-sharing $\\mathrm{PbX}_{6}$ octahedra with ${\\mathrm{Cs}}^{+}$ (purple spheres) occupying the interstitial voids. Ionic radii: ${\\mathrm{C}}s_{\\mathrm{~;~}}^{+}$ , 1.88 Å; ${\\mathrm{Pb}}^{2+}$ , $1.16\\ \\mathring{\\mathrm{A}};$ : $\\mathrm{Cl}^{-}.$ , 1.81 ${\\hat{\\mathrm{A}}};$ $\\mathrm{Br}^{-},$ , $1.96\\ \\mathring{\\mathrm{A}};$ and ${\\mathrm{I}}^{-}.$ $^{-},2.2\\mathrm{~\\AA~}^{35-37}$ (b) Powder X-ray diffraction (XRD) patterns of the parent $\\mathrm{CsPbBr}_{3}\\mathrm{NCs}$ and anion-exchanged samples (using $\\mathrm{Pb}{\\mathrm{Cl}}_{2}$ and $\\mathrm{PbI}_{2}$ as halide sources), showing the retention of phasepure cubic perovskite structure and an average (Scherrer) crystallite size of $8{-}10~\\mathrm{nm}$ . The shift of the XRD reflections is linearly dependent on the composition (Vegard’s law), indicating the formation of uniform solid solutions. Equivalent behaviors were also observed for $\\mathrm{CsPbCl}_{3}+\\mathrm{Br}^{-}$ and $\\mathrm{CsPbI}_{3}+\\mathrm{Br}^{-}$ systems. Formation of solid solutions has been also confirmed by energy dispersive X-ray spectroscopy (EDX) and Rutherford backscattering spectrometry (RBS). \n\n![](images/8c9a7cf332409ec663693992a6954f51ea6811dace968c7a7305c0bb062b8cad.jpg) \nFigure 2. Transmission electron microscopy (TEM) images of ${\\sim}10\\ \\mathrm{nm}\\ C s\\mathrm{Pb}X_{3}$ NCs after treatment with various quantities of (a) chloride and (b) iodide anions. The insets show the evolution of emission colors (under a UV lamp, $\\lambda=365~\\mathrm{{nm}}$ ) upon forming mixed-halide $\\mathrm{CsPb}\\big(\\mathrm{Br/Cl}\\big)_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}(\\mathbf{Br}/\\mathrm{I})_{3}$ to fully exchanged $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ NCs. \n\nWith this motivation in mind, various attempts to exchange either ${\\mathrm{C}}s^{+}$ cations (with $\\mathrm{{Rb}^{+}}$ , ${\\mathbf{A}}{\\mathbf{g}}^{+}$ , $\\mathrm{Cu}^{+}$ , or ${\\mathrm{Ba}}^{2+}$ ) or $\\mathrm{Pb}^{2+}$ cations (with $S\\mathrm{n}^{2+}$ , ${\\mathrm{Ge}}^{2+}$ , or $\\mathbf{Bi}^{3+}$ ) in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs were undertaken, though unfortunately leading to the decomposition of the parent $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs in every case. To this end, most common outcome was the formation of a new halide such as $\\operatorname{AgX}.$ . In stark contrast, fast (for example, in several seconds), lowtemperature, deliberately partial, or complete anion-exchange (Figure 1a) could easily be performed in the cases of Cl-to-Br, Br-to-Cl, Br-to-I, and I-to-Br anion-exchanges, via the formation of homogeneous solid solutions. Because of the large difference in ionic radii between $\\mathrm{Cl}^{-}$ and $\\mathrm{I}^{-}$ causing the instability of $\\mathrm{Cl/I}$ solid solutions, no mixed-halide solid solutions could be obtained in $\\mathrm{CsPbCl_{3}}+\\mathrm{I}^{-}$ or $\\mathrm{CsPbI_{3}+C l^{-}}$ systems, but rather slow and complete exchange occurred. \n\nThe anion-exchange reactions reported herein were conducted in dry octadecene (ODE) as a solvent by mixing a specific ratio of the desired halide source and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}{\\mathrm{NCs}}$ (see Supporting Information file SI2 and, for experimental details, Table S1). The concentrations of capping ligands (oleylamine and oleic acid) were adjusted to be similar to those used for the synthesis of the parent $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs. All tested halide sources, from organometallic Grignard reagents $\\left({\\mathrm{MeMg}}\\mathrm{X}\\right)$ to oleylammonium halides (OAmX) and simple $\\mathrm{Pb}X_{2}$ salts, afforded fast anion-exchange at $40\\ {}^{\\circ}\\mathrm{C};$ ; at this temperature, the solubility of all reagents and NCs could be maintained. \n\nIt is well-known that bulk $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ crystallize in orthorhombic, tetragonal, and cubic polymorphs of the perovskite lattice with the cubic phase being the high-temperature state for all compounds.31−33 By direct synthesis at $160{-}200~^{\\circ}\\mathrm{C},$ $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs are formed in the cubic phase.30 Interestingly, the subsequent anion-exchange manipulations of the halide ions do not seem to affect the cationic sublattice and the cubic perovskite crystal structure is maintained (Figure 1b) despite the low temperature of the anion-exchange reaction. The size and shape of the parent NCs are also preserved in the course of the anion-exchange (Figure 2). The direct synthesis of singleor mixed-halide $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ at such low temperatures yields either exclusively large and polydisperse crystallites of poorly or nonluminescent, wider-bandgap orthorhombic phases or simply no crystalline products at all. $\\mathrm{Cs}\\mathrm{PbI}_{3},$ for example, is highly luminescent and red in its three-dimensional cubic phase, yet yellow and nonluminescent upon conversion into its orthorhombic polymorph.31−34 \n\nAlong with the cubic crystal structure, bright PL (with quantum yields of $10\\mathrm{-}80\\%$ , the lowest values for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}_{3}},$ ) is retained in anion-exchanged $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs, with fwhm peak widths ranging from $12\\ \\mathrm{nm}$ for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ to $40\\ \\mathrm{nm}$ for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ (Figure 3), comparable to directly synthesized CsPbX3 NCs.30 \n\n![](images/80977cc00a38fd664663bfd7f090d66ba12509c9e2503d1a8cf0de5f7a698c24.jpg) \nFigure 3. Evolution of the optical absorption (solid lines) and PL (dashed lines) spectra of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs with increasing quantities of $\\mathrm{Pb}{\\mathrm{Cl}}_{2}$ or $\\mathrm{PbI}_{2},$ added as exchanging halide sources. \n\nThe PL spectra of such exchanged NCs are Stokes-shifted with respect to the optical absorption spectra. As in our previous report on the direct synthesis of mixed-halide $\\mathrm{NCs},^{30}$ the resulting composition of anion-exchanged NCs follows the overall halide ratio in the system, which is $[\\mathrm{X}]_{\\mathrm{parent}}/[\\mathrm{X}]_{\\mathrm{incoming}}$ for anion-exchange or simply the precursor ratio in direct synthesis. The $[\\bar{\\mathrm{X}}]_{\\mathrm{parent}}/[\\mathrm{X}]_{\\mathrm{incoming}}^{-}$ ratio in Cl-to-Br, Br-to-Cl, Br-to-I, and I-to-Br anion-exchanges was varied continuously from 3:1 to 1:3 for three tested halide sources to cover the entire visible spectral region (Table S1 and Figure S1). In general, the distribution of two halide ions between the solution and the crystal is governed by the balance of the crystal energies of the mixed solid-solution and single-halide perovskites on the one side and the solvation energies of halide ions in solution on the other side. The lack of a strong preference toward one of the halides either indicates that the crystal energies are similar for all halides, or that the preferred halide is also preferably solvated, thereby maintaining balance. Eventually, also an entropy of mixing should favor the formation of solid-solutions in the absence of strong enthalpic factors (crystal energy). A different picture is found for I-to-Cl or Cl-to-I exchanges. Treatment of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ NCs with a large excess of $\\mathrm{PbI}_{2}$ (or OAmI and MeMgI) transforms the PL color from blue (410 nm) directly to red $\\left(690\\ \\mathrm{nm}\\right)$ in ca. $30{-}60\\ \\mathrm{~s~}$ The rate for backward transition is similar, also lacking any intermediate color. This can be explained by the larger difference in ionic radii between $\\mathrm{Cl}^{-}$ and $\\mathrm{I}^{-}$ , leading to the higher stability of the single-halide crystals as compared to the solid-solutions. \n\nThe high speed of anion-exchange in perovskite NCs is rooted in the ionic properties of perovskite metal halide crystals. The high ionic conductivity of halides in bulk $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ has been known for 30 years.38 The primary conduction mechanism is the diffusion of halide vacancies, $V_{\\mathrm{X}}^{\\ast}$ $\\mathrm{(X=Br,Cl)},$ , where the activation energy is $0.29\\ \\mathrm{eV}$ for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ and $0.25\\ \\mathrm{eV}$ for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ . Recently, methylammonium hybrid organic− inorganic perovskite analogues $\\mathrm{\\CH_{3}N H_{3}P b I_{3}}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3},$ ) have been the subject of numerous studies due to their unprecedented (for solution-processed absorber materials) photovoltaic power conversion efficiencies of up to $20\\%$ .39−44 Also here understanding the ionics of perovskite halides holds a potential key to explaining a range of important observations such as the hysteresis of current−voltage characteristics45 or the self-compensating mechanism of electrical conductivity.46 Density functional theory calculations point to a prevalence of ionic versus electronic disorder with the charged vacancy concentration exceeding $0.4\\%$ at room temperature,46 and electron and hole traps being rather shallow with respect to hole and conduction bands.47−49 In an elegant study using specially designed ion-selective galvanic cells, Maier et al. have confirmed that of the three ions in the lattice 1 $\\mathrm{^{CH_{3}N H_{3}}}^{+}$ , $\\mathrm{Pb}^{2+}$ , and ${\\mathrm{I}}^{-}$ ), only the latest $\\mathrm{I}^{-}$ is responsible for ionic conductivity, via the vacancy diffusion mechanism.50 \n\nAn in situ PL study of the Br-to-I exchange in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ is presented in Figure 4. Most of the anion-exchange occurs within the first several seconds. The gradual shift of the PL color is consistent with the continuous formation of homogeneous $\\mathrm{Cs}\\mathrm{Pb}\\mathbf{Br}_{x}\\mathrm{I}_{3-x}$ solid solutions because compositional inhomogeneities or preferred compositions within the NC ensemble would lead to broad or multiple peaks. Supporting Information file SI1 presents video of the same reaction, again with clearly observed gradual change of PL colors. Importantly, the integrated intensities of the PL spectra of each exchanged sample remain comparable to that of the parent sample, indicating high PL quantum yields throughout the process. In the course of this work, rapid anion-exchange in thin films of hybrid perovskites of $\\mathrm{CH_{3}N H_{3}P b}X_{3}$ was reported,51 along with in situ optical measurements. In such 2D extended films, $\\mathrm{CH_{3}N H_{3}P b B\\bar{r}_{3}\\mathrm{\\cdotto-CH_{3}N H_{3}P b I_{3}}}$ conversion was determined to progress via the formation of iodine-rich domains within the first seconds with the immediate appearance of red-emission closer to the PL of pure $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ followed by a slower homogenization of the composition over the entire sample. In accord with our study, $\\mathrm{CH_{3}N H_{3}P b C l_{3}}{\\leftrightarrow}\\mathrm{CH_{3}N H_{3}P b I_{3}}$ conversions do not involve solid solutions due to the lattice mismatch between the parent and fully exchanged phases. Another study on the anionexchange in the films of plate-type $\\mathrm{CH_{3}N H_{3}P b}X_{3}$ NCs has appeared during the revision of our manuscript,52 where again $\\mathrm{Br-Cl}$ and $\\mathrm{Br-I}$ systems showed tunable solid solutions, while mixed $\\mathrm{Cl-I}$ systems were not obtained. \n\n![](images/cf524bb934844ccf074fdc4aab42ee730f1cab64fd87e9645b6350fe16febc0e.jpg) \nFigure 4. In-situ PL measurements during a $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ to $\\mathrm{CsPbI}_{3}$ NC conversion at $40~^{\\circ}\\mathrm{C}$ with $\\mathrm{\\big[Br\\big]_{parent}/[I]_{i n c o m i n g}=1:3,}$ (a) plotted at specific times during conversion and (b) throughout the complete process (with three spectra acquired per second). \n\n![](images/19be17600cc54c44006e7974370c20d824dc65bd88dd37a439d60064a01aeaa8.jpg) \nFigure 5. Inter-NC anion-exchange reactions in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NC systems. (a) An overview of the PL spectra of samples obtained by mixing $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs with either $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ or $\\mathrm{CsPbI}_{3}$ NCs in various ratios. (b) Time-dependent PL spectra showing an intermediate stage formed during inter-NC anion-exchange between $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ and $\\mathrm{CsPbI}_{3}$ in which two distinct NC species coexist with altered compositions. \n\nIn addition to fast halide motion within the perovskite lattice, the ease of anion-exchange in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs is in part also due to fast exchange dynamics of the halide ions in solution. Even in the absence of added halide source, we find that the NCs themselves can serve as halide sources for each other (Figure 5a). For example, the mixing of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ in colloidal solution is followed by fast cross-exchange and homogenization of their compositions, forming $\\mathrm{\\bar{c}s P b\\bar{(B r/I)}}_{3}$ solid solutions. Shuttling of halide ions between NCs is facilitated by the small concentration of the solvated halide ions in the colloidal dispersion, present as a residue of $\\mathrm{\\Gamma_{OAmX}}$ or similar species after the isolation of NCs or due to desorption from the NC surface. Only one PL peak is measured after the completion of ionic exchange. The time taken to reach full homogeneity in this case is $10{-}20~\\mathrm{min}$ , much longer than for direct anion-exchange. Investigations of intermediate stages of this process indicate that exchange occurs simultaneously in both kinds of particles; the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ PL peaks shift to longer wavelengths and the $\\mathrm{CsPbI}_{3}$ PL moves to shorter wavelengths (Figure 5b and detailed in situ PL study in Figure S2). The tunability of the PL peaks, emission line widths, and quantum yields after full homogenization are equivalent to those obtained from direct synthesis or via direct ion-exchange as discussed above. \n\nIn summary, remarkably fast anion-exchange was observed in perovskite $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs. Overall, the behavior of perovskite halides with respect to anion-exchange is orthogonal to common metal chalcogenide NCs, namely since the cationic sublattice is substantially rigid and the singly charged halide ions are highly mobile. In metal chalcogenides, ion-exchange has been observed with such ease only for cations. Semiconducting properties of lead halide perovskites are highly defect-tolerant, maintaining bright excitonic emission throughout and upon completion of the anion-exchange. Of practical note, the herein demonstrated fine-tuning of the spectrally narrow and bright PL of anion-exchanged $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs over the entire visible spectral region can be conveniently accomplished from numerous halide sources at low temperatures. In addition, fast anion-exchange between $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs of different compositions can also be readily achieved. Future investigations of halide-exchange reactions in other nanoscale metal halide systems are clearly warranted, as high ionic conductivity may not be strictly necessary due to the short diffusion paths within the NCs. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.5b02404. \n\nAnion-exchange reactions. (MPG) Experimental details and additional figures. (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Author \n\n$^*\\mathrm{E}$ -mail: mvkovalenko@ethz.ch. \n\n# Author Contributions \n\nThe manuscript was prepared through the contribution of all coauthors. All authors have given approval to the final version of the manuscript. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work was financially supported by the European Union via FP7 European Research Council Starting Grant (306733) and Horizon2020 MSCA-ETN phonsi (642656), by the Swiss National Science Foundation (Grant 200021_143638). M.B. is grateful to Swiss National Science Foundation for Ambizione Energy fellowship (Grant PZENP2_154287). All authors thank Nadia Schwitz for a help with producing the photographs and the video of anion-exchange reactions, Dr. M. Döbeli for RBS measurements (ETH Laboratory of Ion Beam Physics), Dr. F. Krumeich and M. Walter for EDX measurements, and Dr. N. Stadie for reading the manuscript. We also acknowledge the support of the Scientific Center for Optical and Electron Microscopy (ETH Zurich) and Empa Electron Microscopy Center. \n\n# REFERENCES \n\n(1) Schaak, R. E.; Williams, M. E. ACS Nano 2012, 6, 8492−8497. (2) Kovalenko, M. V.; Manna, L.; Cabot, A.; Hens, Z.; Talapin, D. V.; Kagan, C. R.; Klimov, V. I.; Rogach, A. L.; Reiss, P.; Milliron, D. J.; Guyot-Sionnnest, P.; Konstantatos, G.; Parak, W. J.; Hyeon, T.; Korgel, B. A.; Murray, C. B.; Heiss, W. ACS Nano 2015, 9, 1012− 1057. (3) Oh, M. H.; Yu, T.; Yu, S.-H.; Lim, B.; Ko, K.-T.; Willinger, M.-G.; Seo, D.-H.; Kim, B. H.; Cho, M. G.; Park, J.-H.; Kang, K.; Sung, Y.-E.; Pinna, N.; Hyeon, T. Science 2013, 340, 964−968. (4) Xia, X.; Wang, Y.; Ruditskiy, A.; Xia, Y. Adv. Mater. 2013, 25, 6313−6333. (5) Li, H. B.; Zanella, M.; Genovese, A.; Povia, M.; Falqui, A.; Giannini, C.; Manna, L. Nano Lett. 2011, 11, 4964−4970. (6) Gupta, S.; Kershaw, S. V.; Rogach, A. L. Adv. Mater. 2013, 25, 6923−6944. (7) Rivest, J. B.; Jain, P. K. Chem. Soc. Rev. 2013, 42, 89−96. (8) Sytnyk, M.; Kirchschlager, R.; Bodnarchuk, M. I.; Primetzhofer, D.; Kriegner, D.; Enser, H.; Stangl, J.; Bauer, P.; Voith, M.; Hassel, A. W.; Krumeich, F.; Ludwig, F.; Meingast, A.; Kothleitner, G.; Kovalenko, M. V.; Heiss, W. Nano Lett. 2013, 13, 586−593. (9) Beberwyck, B. J.; Surendranath, Y.; Alivisatos, A. P. J. Phys. Chem. C 2013, 117, 19759−19770. (10) Ott, F. D.; Spiegel, L. L.; Norris, D. J.; Erwin, S. C. Phys. Rev. Lett. 2014, 113, 156803. (11) Wang, W. S.; Dahl, M.; Yin, Y. D. Chem. Mater. 2013, 25, 1179− 1189. (12) El Mel, A. A.; Buffiere, M.; Tessier, P. Y.; Konstantinidis, S.; Xu, W.; Du, K.; Wathuthanthri, I.; Choi, C. H.; Bittencourt, C.; Snyders, R. Small 2013, 9, 2838−2843. \n\n(13) Yin, Y.; Rioux, R. M.; Erdonmez, C. K.; Hughes, S.; Somorjai, G. \nA.; Alivisatos, A. P. Science 2004, 304, 711−714. \n(14) Son, D. H.; Hughes, S. M.; Yin, Y.; Alivisatos, A. P. Science 2004, 306, 1009−1012. \n(15) Robinson, R. D.; Sadtler, B.; Demchenko, D. O.; Erdonmez, C. \nK.; Wang, L.-W.; Alivisatos, A. P. Science 2007, 317, 355−358. \n(16) Pietryga, J. M.; Werder, D. J.; Williams, D. J.; Casson, J. L.; \nSchaller, R. D.; Klimov, V. I.; Hollingsworth, J. A. J. Am. Chem. Soc. \n2008, 130, 4879−4885. \n(17) Lambert, K.; Geyter, B. D.; Moreels, I.; Hens, Z. Chem. Mater. \n2009, 21, 778−780. \n(18) Jain, P. K.; Amirav, L.; Aloni, S.; Alivisatos, A. P. J. Am. Chem. \nSoc. 2010, 132, 9997−9999. \n(19) Rivest, J. B.; Swisher, S. L.; Fong, L.-K.; Zheng, H.; Alivisatos, A. \nP. ACS Nano 2011, 5, 3811−3816. \n(20) Li, H. B.; Brescia, R.; Povia, M.; Prato, M.; Bertoni, G.; Manna, L.; Moreels, I. J. Am. Chem. Soc. 2013, 135, 12270−12278. \n(21) van der Stam, W.; Berends, A. C.; Rabouw, F. T.; Willhammar, T.; Ke, X.; Meeldijk, J. D.; Bals, S.; de Mello Donega, C. Chem. Mater. \n2015, 27, 621−628. \n(22) De Trizio, L.; Gaspari, R.; Bertoni, G.; Kriegel, I.; Moretti, L.; \nScotognella, F.; Maserati, L.; Zhang, Y.; Messina, G. C.; Prato, M.; \nMarras, S.; Cavalli, A.; Manna, L. Chem. Mater. 2015, 27, 1120−1128. \n(23) Park, J.; Zheng, H.; Jun, Y.-w.; Alivisatos, A. P. J. Am. Chem. Soc. \n2009, 131, 13943−13945. \n(24) Dloczik, L.; Könenkamp, R. Nano Lett. 2003, 3, 651−653. \n(25) Dawood, F.; Schaak, R. E. J. Am. Chem. Soc. 2009, 131, 424− 425. \n(26) Brumer, M.; Kigel, A.; Amirav, L.; Sashchiuk, A.; Solomesch, O.; \nTessler, N.; Lifshitz, E. Adv. Funct. Mater. 2005, 15, 1111−1116. \n(27) Saruyama, M.; So, Y.-G.; Kimoto, K.; Taguchi, S.; Kanemitsu, Y.; \nTeranishi, T. J. Am. Chem. Soc. 2011, 133, 17598−17601. \n(28) Bailey, R. E.; Nie, S. J. Am. Chem. Soc. 2003, 125, 7100−7106. \n(29) Choi, D.; Lee, S.; Lee, J.; Cho, K.-S.; Kim, S.-W. Chem. Commun. \n2015, 51, 899−902. \n(30) Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Krieg, F.; \nCaputo, R.; Hendon, C. H.; Yang, R. X.; Walsh, A.; Kovalenko, M. V. \nNano Lett. 2015, 15, 3692−3696. \n(31) Sharma, S.; Weiden, N.; Weiss, A. Z. Phys. Chem. 1992, 175, 63−80. \n(32) Trots, D. M.; Myagkota, S. V. J. Phys. Chem. Solids 2008, 69, 2520−2526. \n(33) Stoumpos, C. C.; Malliakas, C. D.; Kanatzidis, M. G. Inorg. \nChem. 2013, 52, 9019−9038. \n(34) Babin, V.; Fabeni, P.; Nikl, M.; Nitsch, K.; Pazzi, G. P.; \nZazubovich, S. Phys. Status Solidi B 2001, 226, 419−428. \n(35) Verma, A. S.; Jindal, V. K. J. Alloys Compd. 2009, 485, 514−518. \n(36) Verma, A. S.; Kumar, A.; Bhardwaj, S. R. Phys. Status Solidi B 2008, 245, 1520−1526. \n(37) Ida, Y. Phys. Earth Planet. Inter. 1976, 13, 97−104. \n(38) Mizusaki, J.; Arai, K.; Fueki, K. Solid State Ionics 1983, 11, 203− 211. \n(39) Gratzel, M. Nat. Mater. 2014, 13, 838−842. \n(40) Green, M. A.; Ho-Baillie, A.; Snaith, H. J. Nat. Photonics 2014, 8, 506−514. \n(41) Park, N.-G. J. Phys. Chem. Lett. 2013, 4, 2423−2429. \n(42) Zhou, H.; Chen, Q.; Li, G.; Luo, S.; Song, T.-b.; Duan, H.-S.; \nHong, Z.; You, J.; Liu, Y.; Yang, Y. Science 2014, 345, 542−546. \n(43) Chung, I.; Lee, B.; He, J.; Chang, R. P. H.; Kanatzidis, M. G. \nNature 2012, 485, 486−489. \n(44) Stranks, S. D.; Snaith, H. J. Nat. Nanotechnol. 2015, 10, 391− 402. \n(45) Xiao, Z.; Yuan, Y.; Shao, Y.; Wang, $\\mathrm{Q.;}$ Dong, $\\mathrm{Q.;}$ Bi, C.; \nSharma, P.; Gruverman, A.; Huang, J. Nat. Mater. 2014, 14, 193−198. \n(46) Walsh, A.; Scanlon, D. O.; Chen, S.; Gong, X. G.; Wei, S.-H. \nAngew. Chem., Int. Ed. 2015, 54, 1791−1794. \n(47) Buin, A.; Pietsch, P.; Xu, J.; Voznyy, O.; Ip, A. H.; Comin, R.; \nSargent, E. H. Nano Lett. 2014, 14, 6281−6286. (48) Agiorgousis, M. L.; Sun, Y.-Y.; Zeng, H.; Zhang, S. J. Am. Chem. \nSoc. 2014, 136, 14570−14575. \n(49) Yin, W.-J.; Shi, T.; Yan, Y. Appl. Phys. Lett. 2014, 104, 063903. \n(50) Yang, T.-Y.; Gregori, G.; Pellet, N.; Grätzel, M.; Maier, J. Angew. \nChem., Int. Ed. 2015, DOI: 10.1002/anie.201500014. \n(51) Pellet, N.; Teuscher, J.; Maier, J.; Grätzel, M. Chem. Mater. \n2015, 27, 2181−2188. \n(52) Jang, D. M.; Park, K.; Kim, D. H.; Park, J.; Shojaei, F.; Kang, H. \nS.; Ahn, J.-P.; Lee, J. W.; Song, J. K. Nano Lett. 2015, DOI: 10.1021/ acs.nanolett.5b01430. " + }, + { + "id": "10.1038_ncomms9485", + "DOI": "10.1038/ncomms9485", + "DOI Link": "http://dx.doi.org/10.1038/ncomms9485", + "Relative Dir Path": "mds/10.1038_ncomms9485", + "Article Title": "Entropy-stabilized oxides", + "Authors": "Rost, CM; Sachet, E; Borman, T; Moballegh, A; Dickey, EC; Hou, D; Jones, JL; Curtarolo, S; Maria, JP", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Configurational disorder can be compositionally engineered into mixed oxide by populating a single sublattice with many distinct cations. The formulations promote novel and entropy-stabilized forms of crystalline matter where metal cations are incorporated in new ways. Here, through rigorous experiments, a simple thermodynamic model, and a five-component oxide formulation, we demonstrate beyond reasonable doubt that entropy predominates the thermodynamic landscape, and drives a reversible solid-state transformation between a multiphase and single-phase state. In the latter, cation distributions are proven to be random and homogeneous. The findings validate the hypothesis that deliberate configurational disorder provides an orthogonal strategy to imagine and discover new phases of crystalline matter and untapped opportunities for property engineering.", + "Times Cited, WoS Core": 2203, + "Times Cited, All Databases": 2351, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000363146400003", + "Markdown": "# Entropy-stabilized oxides \n\nChristina M. Rost1, Edward Sachet1, Trent Borman1, Ali Moballegh1, Elizabeth C. Dickey1, Dong Hou1, Jacob L. Jones1, Stefano Curtarolo2 & Jon-Paul Maria1 \n\nConfigurational disorder can be compositionally engineered into mixed oxide by populating a single sublattice with many distinct cations. The formulations promote novel and entropystabilized forms of crystalline matter where metal cations are incorporated in new ways. Here, through rigorous experiments, a simple thermodynamic model, and a five-component oxide formulation, we demonstrate beyond reasonable doubt that entropy predominates the thermodynamic landscape, and drives a reversible solid-state transformation between a multiphase and single-phase state. In the latter, cation distributions are proven to be random and homogeneous. The findings validate the hypothesis that deliberate configurational disorder provides an orthogonal strategy to imagine and discover new phases of crystalline matter and untapped opportunities for property engineering. \n\ngrand challenge facing materials science is the continuous hunt for advanced materials with properties that satisfy the demands of rapidly evolving technology needs. The materials research community has been addressing this problem since the early 1900s when Goldschmidt reported the ‘the method of chemical substitution’1 that combined a tabulation of cationic and anionic radii with geometric principles of ion packing and ion radius ratios. Despite its simplicity, this model enabled a surprising capability to predict stable phases and structures. As early as 1926 many of the technologically important materials that remain subjects of contemporary research were identified (though their properties were not known); ${\\mathrm{BaTiO}}_{3}$ , AlN, GaP, $\\mathrm{{}}Z\\mathrm{{nO}}$ and GaAs are among that list. \n\nThese methods are based on overarching natural tendencies for binary, ternary and quaternary structures to minimize polyhedral distortions, maximize space filling and adopt polyhedral linkages that preserve electroneutrality1–3. The structure-field maps compiled by Muller and Roy catalogue the crystallographic diversity in the context of these largely geometry-based predictions4. There are, however, limitations to the predictive power, particularly when factors like partial covalency and heterodesmic bonding are considered. \n\nTo further expand the library of advanced materials and property opportunities, our community explores possibilities based on mechanical strain5, artificial layering6, external fields7, combinatorial screening8, interface engineering9,10 and structuring at the nanoscale6,11. In many of these efforts, computation and experiment are important companions. \n\nMost recently, high-throughput methods emerged as a powerful engine to assess huge sections of composition space12–17 and identified rapidly new Heusler alloys, extensive ion substitution schemes18,19, new 18-electron ABX compounds20 and new ferroic semiconductors21. \n\nWhile these methods offer tremendous predictive power and an assessment of composition space intractable to experiment, they often utilize density functional theory calculations conducted at $0\\mathrm{K}$ . Consequently, the predicted stabilities are based on enthalpies of formation. As such, there remains a potential section of discovery space at elevated temperatures where entropy predominates the free-energy landscape. \n\nThis landscape was explored recently by incorporating deliberately five or more elemental species into a single lattice with random occupancy. In such crystals, entropic contributions to the free energy, rather than the cohesive energy, promote thermodynamic stability at finite temperatures. The approach is being explored within the high-entropy-alloy family of materials (HEAs)22, in which extremely attractive properties continue to be found23,24. In HEAs, however, discussion remains regarding the true role of configurational entropy25–28, as samples often contain second phases, and there are uncertainties regarding short-range order. In response to these open discussions, HEAs have been referred to recently as multiple-principle-element alloys29. \n\nIt is compelling to consider similar phenomena in non-metallic systems, particularly considering existing information from entropy studies in mixed oxides. In 1967 Navrotsky and Kleppa showed how configurational entropy regulates the normal-to-inverse transformation in spinels, where cations transition between ordered and disordered site occupancy among the available sublattices30,31. These fundamental thermodynamic studies lead one to hypothesize that in principle, sufficient temperature would promote an additional transition to a structure containing only one sublattice with random cation occupancy. From experiment we know that before such transitions, normal materials melt, however, it is conceivable that synthetic formulations exist, which exhibit them. \n\nInspired by research activities in the metal alloy communities and fundamental principles of thermodynamics we extend the entropy concept to five-component oxides. With unambiguous experiments we demonstrate the existence of a new class of mixed oxides that not only contains high configurational entropy but also is indeed truly entropy stabilized. In addition, we present a hypothesis suggesting that entropy stabilization is particularly effective in a compound with ionic character. \n\n# Results \n\nChoosing an appropriate experimental candidate. The candidate system is an equimolar mixture of MgO, CoO, NiO, CuO and $\\mathrm{{}}Z\\mathrm{{nO}}$ , (which we label as ‘E1’) so chosen to provide the appropriate diversity in structures, coordination and cationic radii to test directly the entropic ansatz. The rationale for selection is as follows: the ensemble of binary oxides should not exhibit uniform crystal structure, electronegativity or cation coordination, and there should exist pairs, for example, $\\mathrm{MgO-ZnO}$ and $\\mathrm{{CuO-NiO}}$ , that do not exhibit extensive solubility. Furthermore, the entire collection should be isovalent such that relative cation ratios can be varied continuously with electroneutrality preserved at the net cation to anion ration of unity. Tabulated reference data for each component, including structure and ionic radius, can be found in Supplementary Table 1. \n\nTesting reversibility. In the first experiment, ceramic pellets of E1 are equilibrated in an air furnace and quenched to room temperature. The temperature spanned a range from 700 to $1{,}10\\bar{0}^{\\circ}\\mathrm{C},$ in $50\\mathrm{-}^{\\circ}\\mathrm{C}$ increments. X-ray diffraction patterns showing the phase evolution are depicted in Fig. 1. After $700^{\\circ}\\mathrm{C},$ two prominent phases are observed, rocksalt and tenorite. The tenorite phase fraction reduces with increasing equilibration temperature. Full conversion to single-phase rocksalt occurs between 850 and ${}^{900^{\\circ}\\mathrm{C},}$ after which there are no additional peaks, the background is low and flat, and peak widths are narrow in two-theta (2y) space. \n\nReversibility is a requirement of entropy-driven transitions. Consequently, low-temperature equilibration should transform homogeneous $1{,}000^{\\circ}\\mathrm{C}$ -equilibrated E1 back to its multiphase state (and vice versa on heating). Figure 1 also shows a sequence of X-ray diffraction patterns for such a thermal excursion; initial equilibration at $1{,}00\\bar{0}^{\\circ}\\mathrm{C},$ a second anneal at $750^{\\circ}\\mathrm{C},$ and finally a return to $1,000^{\\circ}\\mathrm{C}$ . The transformation from single phase, to multiphase, to single phase is evident by the $\\mathrm{\\DeltaX}$ -ray patterns and demonstrates an enantiotropic (that is, reversible with temperature32) phase transition. \n\nTesting entropy though composition variation. A composition experiment is conducted to further characterize this phase transition to the random solid solution state. If the driving force is entropy, altering the relative cation ratios will influence the transition temperature. Any deviation from equimolarity will reduce the number of possible configurations $\\Omega$ $(S_{c}=k_{\\mathrm{B}}\\mathrm{log}(\\Omega))$ , thus increasing the transition temperature. Because $S_{c}(x_{i})$ is logarithmically linked to mole fraction via $\\sim x_{i}\\mathrm{log}(x_{i})$ , the compositional dependence is substantial. \n\nThis dependency underpins our gedankenexperiment where the role of entropy can be tested by measuring the dependency of transition temperature as a function of the total number of components present, and of the composition of a single component about the equimolar formulation. \n\nThe calculated entropy trends for an ideal mixture are illustrated in Fig. 2b, which plots configurational entropy for a set of mixtures having $N$ species where the composition of an individual species is changed and the others $(N-1)$ are kept equimolar. Two dependencies become apparent: the entropy increases as new species are added and the maximum entropy is achieved when all the species have the same fraction. Both dependencies assume ideal random mixing. Two series of composition-varying experiments investigate the existence of these trends in formulation E1. \n\n![](images/65618867d517582fc56de1dfcc2f8bfa201dcdc871eb0216c177e8dbcf02ae7a.jpg) \nFigure 1 | X-ray diffraction patterns for entropy-stabilized oxide formulation E1. E1 consists of an equimolar mixture of $M g O,$ NiO, ZnO, CuO and CoO. The patterns were collected from a single pellet. The pellet was equilibrated for $2h$ at each temperature in air, then air quenched to room temperature by direct extraction from the furnace. X-ray intensity is plotted on a logarthimic scale and arrows indicate peaks associated with non-rocksalt phases, peaks indexed with (T) and with (RS) correspond to tenorite and rocksalt phases, respectively. The two X-ray patterns for $1,000^{\\circ}\\mathsf{C}$ annealed samples are offset in 2y for clarity. \n\n![](images/d4348e57802329fbca9a029d9bbf66d10f49f3e4d76f32314f9e850ed8a54ae7.jpg) \nFigure 2 | Compositional analysis. (a) X-ray diffraction analysis for a composition series where individual components are removed from the parent composition E1 and heat treated to the conditions that would otherwise produce full solid solution. Asterisks identify peaks from rocksalt while carrots identify peaks from other crystal structures. (b) Calculated configurational entropy in an N-component solid solutions as a function of $m o l\\%$ of the $N^{\\mathrm{th}}$ component, and $(\\pmb{\\mathsf{c}}\\pmb{\\mathsf{g}})$ partial phase diagrams showing the transition temperature to single phase as a function of composition (solvus) in the vicinity of the equimolar composition where maximum configurational entropy is expected. Error bars account for uncertainty between temperature intervals. Each phase diagram varies systematically the concentration of one element. \n\nThe first experiment monitors phase evolution in five compounds, each related to the parent E1 by the extraction of a single component. The sets are equilibrated at $875^{\\circ}\\mathrm{C}$ (the threshold temperature for complete solubility) for $12\\mathrm{h}$ . The diffraction patterns in Fig. 2a show that removing any component oxide results in material with multiple phases. A four-species set equilibrated under these conditions never yields a single-phase material. \n\nThe second experiment uses five individual phase diagrams to explore the configurational entropy versus composition trend. In each, the composition of a single component is varied by $\\pm2$ , $\\pm6$ and $\\pm10\\%$ increments about the equimolar composition while the others are kept even. Since any departure from equimolarity reduces the configurational entropy, it should increase transition temperatures to single phase, if that transition is in fact entropy driven. The specific formulations used are given in Supplementary Table 2. \n\nFigure $2\\mathrm{c-g}$ are phase diagrams of composition versus transformation temperature for the five sample sets that varied mole fraction of a single component. The diagrams were produced by equilibrating and quenching individual samples in $25^{\\circ}\\mathrm{C}$ intervals between 825 and $1,125^{\\circ}\\mathrm{C}$ to obtain the $T_{\\mathrm{trans}}{\\cdot}$ composition solvus. In all cases equimolarity always leads to the lowest transformation temperatures. This is in agreement with entropic promotion, and consistent with the ideal model shown in Fig. 2b. One set of raw X-ray patterns used to identify $T_{\\mathrm{trans}}$ for $10\\%$ MgO is given as an example in Supplementary Fig. 1. \n\nTesting endothermicity. Reversibility and compositionally dependent solvus lines indicate an entropy-driven process. As such, the excursion from polyphase to single phase should be endothermic. An entropy-driven solid–solid transformation is similar to melting, thus requires heat from an external source33. To test this possibility, the phase transformation in formulation E1 can be co-analysed with differential scanning calorimetry and in situ temperature-dependent X-ray diffraction using identical heating rates. The data for both measurements are shown in Fig. 3. Figure 3a is a map of diffracted intensity versus diffraction angle (abscissa) as a function of temperature. It covers $\\sim4^{\\circ}$ of $2\\theta$ space centred about the 111 reflection for E1. At a temperature interval between 825 and ${875}^{\\circ}{\\mathrm{C}},$ there is a distinct transition to single-phase rocksalt structure—all diffraction events in that range collapse into an intense $<111>$ rocksalt peak. \n\nFigure 3b contains the companion calorimetric result where one finds a pronounced endotherm in the identical temperature window. The endothermic response only occurs when the system adds heat to the sample, uniquely consistent with an entropydriven transformation33. We note the small mass loss $(\\sim1.5\\%)$ at the endothermic transition. This mass loss results from the conversion of some spinel (an intermediate phase seen by $\\mathrm{\\DeltaX}$ -ray diffraction) to rocksalt, which requires reduction of ${{3}^{+}}$ to $2^{+}$ cations and release of oxygen to maintain stoichiometry. To address concerns regarding CuO reduction, Supplementary Fig. 2 shows a differential scanning calorimetry and thermal gravimetric analysis curve for pure $\\mathtt{C u O}$ collected under the same conditions. There is no oxygen loss in the vicinity of $875^{\\circ}\\mathrm{C}$ . \n\n![](images/8c1c6c0728228c587a2827e982ad80b36485a1f0d64826ac5f5edd6942e522d7.jpg) \nFigure 3 | Demonstrating endothermicity. (a) In situ X-ray diffraction intensity map as a function of $2\\theta$ and temperature; and (b) differential scanning calorimetry trace for formulation ‘E1’. Note that the conversion to single phase is accompanied by an endotherm. Both experiments were conducted at a heating rate of $5^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ . \n\nTesting homogeneity. All experimental results shown so far support the entropic stabilization hypothesis. However, all assume that homogeneous cation mixing occurs above the transition temperature. It is conceivable that local composition fluctuations produce coherent clustering or phase separation events that are difficult to discern by diffraction using a laboratory sealed tube diffractometer. The solvus lines of Fig. $2\\mathrm{c-g}$ support random mixing, as the most stable composition is equimolar (a condition only expected for ideal/regular solutions), but it is appropriate to ensure self-consistency with direct measurements. To characterize the cation distributions, extended X-ray absorption fine structure (EXAFS) and scanning transmission electron microscopy with energy dispersive X-ray spectroscopy (STEM EDS) is used to analyse structure and chemistry on the local scale. \n\nEXAFS data were collected for $Z\\mathrm{n}$ , Ni, Cu and $\\scriptstyle{\\mathrm{Co}}$ at the Advanced Photon Source 12-BM- $\\cdot\\mathrm{B}^{34,35}$ . The fitted data are shown in Fig. 4, the raw data are given in Supplementary Fig. 3. The fitted data for each element provide two conclusions: the cation-to-anion first-near-neighbour distances are identical (within experimental error of $\\dot{\\pm}0.01\\mathring\\mathrm{A}.$ ) and the local structures for each element to approximately seven near-neighbour distances are similar. Both observations are only consistent with a random cation distribution. \n\nAs a corroborating measure of local homogeneity, chemical analysis was conducted using a probe-corrected FEI Titan STEM with EDS detection. Thin film samples of E1, prepared by pulsed laser deposition, are the most suitable samples to make the assessment. Details of preparation are given in the methods, and X-ray and electron diffraction analysis for the film are provided in Supplementary Figs 4 and 5. The sample was thinned by mechanical polishing and ion milling. Figure 5 shows a collection of images including Fig. 5a, the high-angle annular dark-field signal (HAADF). \n\nIn Fig. 5b–f, the EDS signals for the $\\mathsf{K}\\mathsf{\\mathfrak{a}}$ emission energies of Mg, Co, Ni, Cu and Zn are shown (additional lower magnification images are included in Supplementary Fig. 6). All magnifications reveal chemically and structurally homogeneous material. \n\n![](images/dbf0ac6b0feae69daba30f0f743084fec5805460016b96c1b096d1537aa2fd3e.jpg) \nFigure 4 | Extended X-ray absorption fine structure. EXAFS measured at Advanced Photon Source beamlime 12-BM after energy normalization and fitting. Note that the oscillations for each element occur with similar relative intensity and at similar reciprocal spacing. This suggests a similar local structural and chemical environment for each. \n\n![](images/3366d953e369c2554e930ddb2231b8b8892b0bbfc9143a0ebdaafec4a41a01e9.jpg) \nFigure 5 | STEM–EDS analysis of E1. (a) HAADF image. Panels labelled as Zn, Ni, Cu, Mg and Co are intensity maps for the respective characteristic X-rays. The individual EDS maps show uniform spatial distributions for each element and are atomically resolved. \n\nX-ray diffraction, EXAFS and STEM–EDS probes are sensitive to 10 s of nm, 10 s of $\\mathring\\mathrm{A}$ and $1\\mathring\\mathrm{A}$ length scales, respectively. While any single technique could be misinterpreted to conclude homogenous mixing, the combination of $\\mathrm{\\DeltaX}$ -ray diffraction, EXAFS and STEM–EDS provide very strong evidence. We note, in particular, the similarity in EXAFS oscillations (both in amplitude and position) out to 12 inverse angstroms. This similarly would be lost if local ordering or clustering were present. Consequently, we conclude with certainty that the cations are uniformly dispersed. \n\n# Discussion \n\nThe set of experimental outcomes show that the transition from multiple-phase to single phase in E1 is driven by configurational entropy. To complete our thermodynamic understanding of this system, it is important to understand and appreciate the enthalpic penalties that establish the transition temperature. In so doing, the data set can be tested for self-consistency, and the present data are brought into the context of prior research on oxide solubility. \n\nFirst, we consider an equation relating the initial and final states of the proposed phase transition: \n\n$$\n\\mathrm{MgO_{(RS)}+N i O_{(R S)}+C o O_{(R S)}+C u O_{(T)}+Z n O_{(W)}=(M g,N i,C o,C u,Z n)O_{(R S)}}\n$$ \n\nFor MgO, NiO and $\\mathrm{CoO}$ , the crystal structures of the initial and final states are identical. If we assume that solution of each into the E1 rocksalt phase is ideal, the enthalpy for mixing is zero. For $\\mathtt{C u O}$ and $\\mathrm{{}}Z\\mathrm{{nO}}$ , there must be a structural transition to rocksalt on dissolution from tenorite and wurtzite, respectively. If we again assume (for simplicity) that the solution is ideal, the mixing energy is zero, but there is an enthalpic penalty associated with the structure transition. From Davies et al. and Bularzik et al., we know the reference chemical potential changes for the wurtzite-to-rocksalt and the tenorite-to-rocksalt transitions of $\\mathrm{znO}$ and CuO; they are 25 and $22\\mathrm{kJ}\\mathrm{mol}^{-1}$ , respectively36,37. If we make the assumption that the transition enthalpies of $\\mathrm{znO}$ (wurtzite) to ZnO(rocksalt E1) and $\\mathtt{C u O}$ (tenorite) to $\\mathtt{C u O}$ (rocksalt E1) are comparable, then the enthalpic penalty for solution into E1 can be estimated. For $\\mathrm{znO}$ and $\\mathtt{C u O}$ , the transition to solid solution in a rocksalt structure involves an enthalpy change of $(0.2)\\cdot(25\\mathrm{kJmol}^{-1})+(0.2)\\cdot(22\\mathrm{kJmol}^{-1})$ , a total of $+10\\dot{\\mathrm{kJ}}\\mathrm{mol}^{-1}$ . This calculation is based on the product of the mol fraction of each multiplied by the reference transition enthalpy. \n\nThis assumption is consistent with the report of Davies et al. who showed that the chemical potential of a particular cation in a particular structure is associated with the molar volume of that structure36. Since the rocksalt phases of $\\mathrm{{}}Z\\mathrm{{nO}}$ and $\\mathtt{C u O}$ have molar volumes comparable to E1, their reference transition enthalpy values are considered suitable proxies. \n\nIn comparison, the maximum theoretically expected configurational entropy difference at $875^{\\circ}\\mathrm{C}$ (the temperature were we observe the transition experimentally) between the single species and the random five-species solid solution is $\\sim15\\mathrm{\\check{k}J\\ m o l^{-1}}$ , $5\\mathrm{kJmol}^{-1}$ larger than the calculated enthalpy of transition. It is possible that the origins of this difference are related to mixing energy as the reference energy values for structural transitions to rocksalt do not capture that aspect. \n\nWhile the present phase diagrams that monitor $T_{\\mathrm{trans}}$ as a function of composition demonstrate rather symmetric behaviour about the temperature minima, it is unlikely that mixing enthalpies are zero for all constituents. Indeed, literature reports show that enthalpies of mixing between the constituent oxides in E1 are finite and of mixed sign, and their magnitudes are on the same order as the $5\\mathrm{kJmol^{-1}}$ difference between our calculated predictions36. This energy difference may be accounted for by finite and positive mixing enthalpies. \n\nFollowing this argument, we can achieve a self-consistent appreciation for the entropic driving force and the enthalpic penalties for solution formation in E1 by considering enthalpies of the associated structural transitions and expected entropy values for ideal cation mixing. \n\nAs a final test, these predictions can be compared with experiment, specifically by calculating the magnitude of the endotherm observed by DSC at the transition from multiplephase to single-phase states. Doing so we find a value $\\stackrel{\\bullet}{\\sim}12\\mathrm{kJ}\\mathrm{mol}^{-1}$ (with an uncertainty of $\\pm2\\mathrm{kJ}\\mathrm{mol}^{-1}.$ ). While we acknowledge the challenge of quantitative calorimetry, we note that this experimental result is intermediate to and in close agreement with the predicted values. \n\nCompared with metallic alloys, the pronounced impact of entropy in oxides may be surprising given that on a per-atom basis the total disorder per volume of an oxide seems be lower than in a high-entropy alloy, as the anion sublattice is ordered (apart from point defects). The chemically uniform sublattice is perhaps the key factor that retains cation configurational entropy. As an illustration, consider a comparison between random metal alloys and random metal oxide alloys. \n\nBegin by reviewing the case of a two-component metallic mixture A–B. If the mixture is ideal, the energy of interaction $E_{\\mathrm{A-B}}=(E_{\\mathrm{A-A}}+E_{\\mathrm{B-B}})/2$ , there is no enthalpic preference for bonding, and entropy regulates solution formation. In this scenario, all lattice sites are equivalent and configurational entropy is maximized. This situation, however, never occurs as no two elements have identical electronegativity and radii values. Figure 6a illustrates a two-component alloy scenario A–B where species B is more electronegative than A. Consequently, the interaction energies $E_{\\mathrm{A-A}},\\ E_{\\mathrm{B-B}}$ and $E_{\\mathrm{A-B}}$ will be different. A random mixture of $_\\mathrm{A-B}$ will produce lattice sites with a distribution of first near neighbours, that is, species A coordinated to 4-B atoms, 2-A and 2-B atoms, etcy Different coordinations will have different energy values and the sites are no longer indistinguishable. Reducing the number of equivalent sites reduces the number of possible configurations and S. \n\nNow consider the same two metallic ions co-populating a cation sublattice, as in Fig. 6b. In this case, there is always an intermediate anion separating neighbouring cation lattice sites. Again, in the limiting case where only first near neighbours are considered, every cation lattice site is ‘identical’ because each has the same immediate surroundings: the interior of an oxygen octahedron. Differentiation between sites is only apparent when the second near neighbours are considered. From the configurational disorder perspective, if each cation lattice site is identical, and thus energetically similar to all others, the number of microstates possible within the macrostate will approach the maximum value. \n\n![](images/c52461e9db2ece62aed18c22248759087538057f69c5e304c42a8820885b9f2b.jpg) \nFigure 6 | Binary metallic compared with a ternary oxide. A schematic representation of two lattices illustrating how the first-near-neighbour environments between species having different electronegativity (the darker the more negative charge localized) for (a) a random binary metal alloy and (b) a random pseudo-binary mixed oxide. In the latter, nearneighbour cations are interrupted by intermediate common anions. \n\nThis crystallographic argument is based on the limiting case where first-near-neighbour interactions predominate the energy landscape, which is an imperfect approximation. Second and third near neighbours will influence the distribution of lattice site energies and the number of equivalent microstates— but the impact will be the same in both scenarios. A larger number of equivalent sites in a crystal with an intermediate sublattice will increase S and expand the elemental diversity containable in a single solid solution and to lower the temperature at which the transition to entropic stabilization occurs. We acknowledge the hypothesis nature of this model at this time, and the need for a rigorous theoretical exploration. It is presented currently as a possibility and suggestion for future consideration and testing. \n\nWe demonstrate that configurational disorder can promote reversible transformations between a poly-phase mixture and a homogeneous solid solution of five binary oxides, which do not form solid solutions when any of the constituents are removed provided the same thermal budget. The outcome is representative of a new class of materials called ‘entropy-stabilized oxides’. While entropic effects are known for oxide systems, for example, random cation occupancy in spinels30, order–disorder transformations in feldspar38, and oxygen nonstoichiometry in layered perovskites39, the capacity to actively engineer configurational entropy by composition, to stabilize a quinternary oxide with a single cation sublattice, and to stabilize unusual cation coordination values is new. Furthermore, these systems provide a unique opportunity to explore the thermodynamics and structure–property relationships in systems with extreme configurational disorder. \n\nExperimental efforts exploring this composition space are important considering that such compounds will be challenging to characterize with computational approaches minimizing formation energy (for example, genetic algorithms) or with adhoc thermodynamic models (for example, CALPHAD, cluster expansion) . \n\nWe expect entropic stabilization in systems where nearneighbour cations are interrupted by a common intermediate anion (or vice versa), which includes broad classes of chalcogenides, nitrides and halides; particularly when covalent character is modest. The entropic driving force—engineered by cation composition— provides a departure from traditional crystal-chemical principles that elegantly predict structural trends in the major ternary and quaternary systems. A companion set of structure–property relationships that predict new entropy-stabilized structures with novel cation incorporation await discovery and exploitation. \n\n# Methods \n\nSolid-state synthesis of bulk materials. MgO (Alfa Aesar, $99.99\\%$ ), NiO (Sigma Aldrich, $99\\%$ ), CuO (Alfa Aesar, $99.9\\%$ ), CoO (Alfa Aesar, $99\\%$ ) and $\\mathrm{znO}$ (Alfa Aesar $99.9\\%$ ) are massed and combined using a shaker mill and $3\\mathrm{-mm}$ diameter yttrium-stabilized zirconia milling media. To ensure adequate mixing, all batches are milled for at least $^{2\\mathrm{h}}$ Mixed powders are then separated into $_{0.500-\\mathrm{g}}$ samples and pressed into $1.27\\mathrm{-cm}$ diameter pellets using a uniaxial hydraulic press at $31,000\\mathrm{N}$ . The pellets are fired in air using a Protherm PC442 tube furnace. \n\nTemperature evolution of phases. Ceramic pellets of E1 are equilibrated in an air furnace and quenched to room temperature by direct extraction from the hot zone. Phase analysis is monitored by X-ray diffraction using a PANalytical Empyrean X-ray diffractometer with Bragg-Brentano optics including programmable divergence and receiving slits to ensure constant illumination area, a Ni filter, and a 1-D 128 element strip detector. The equivalent counting time for a conventional point detector would be $30\\mathrm{s}$ per point at $0.01^{\\circ}2\\theta$ increments. Note that all X-ray are collected using substantial counting times and are plotted on a logarithmic scale. To the extent knowable using a laboratory diffractometer, the high-temperature samples are homogeneous and single phase: there are no additional minor peaks, the background is low and flat, and peak widths are sharp in two-theta (2y) space. \n\nTemperature-dependent diffraction data are collected with PANalytical Empyrean X-ray diffractometer with Bragg-Brentano optics including programmable divergence and receiving slits to ensure constant illumination area, a Ni filter, and a 1-D 256 element strip detector. The samples are placed in a resistively heated HTK-1200N hot stage in air. The samples are ramped at a constant rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ with a theta–two theta pattern captured every $1.5\\mathrm{min}$ . Calorimetry data are collected using a Netzsch STA 449 F1 Jupiter system in a $\\mathrm{Pt}$ crucible at $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ in flowing air. \n\nDetermining solvus lines. Five series of powders are mixed where the amount of one constituent oxide is varied from the parent mixture E1. Supplementary Table 2 lists the full set of samples synthesized for this experiment. Each individual sample is cycled through a heat-soak-quench sequence at $25^{\\circ}\\mathrm{C}$ increments from $850^{\\circ}\\mathrm{C}$ up to $1,150^{\\circ}\\mathrm{C}$ . The soak time for each cycle is $^{2\\mathrm{h}}$ , and samples are then quenched to room temperature in $<1\\mathrm{min}$ . \n\nAfter the quenching step for each cycle, samples are immediately analysed for phase identification using a PANalytical Empyrean X-ray diffractometer using the conditions identified above. If more than one phase is present, the sample would be put through the next temperature cycle. The temperature at which the structure is determined to be pure rocksalt, with no discernable evidence of peak splitting or secondary phases, is deemed the transition temperature as a function of composition. Supplementary Fig. 1 shows an example of the collected X-ray patterns after each cycle using the E1L series with $+10\\%$ MgO. Once single phase is achieved, the sample is removed from the sequence. \n\nNote that this entire experiment is conducted two times. Initially in $50^{\\circ}\\mathrm{C}$ increments and longer anneals, and to ensure accuracy of temperature values and reproducibility, a second time using shorter increments and $25^{\\circ}\\mathrm{C}$ anneals. Findings in both sets are identical to within experimental error bar values. In the latter case, error bars correspond to the annealing interval value of $25^{\\circ}\\mathrm{C}$ . \n\nIn the main text relating to Fig. 2a we note that in addition to small peaks from second phases, X-ray spectra for $N=4$ samples with either NiO or MgO removed show anisotropic peak broadening in 2y and skewed relative intensities where $I_{(200)}/I_{(111)}$ is less than unity. This ratio is not possible for the rocksalt structure. Supplementary Table 3 shows the result of calculations of structure factors for a random equimolar rocksalt oxide with composition E1. Calculations show that the 200 reflection is the strongest, and that the experimentally measured relative intensities of 111/200 are consistent with calculations. We use this information as a means too best assess when the transition to single phase occurs since the most likely reason for the skewed relative intensity is an incomplete conversion to the single-phase state. This dependency is highlighted in Supplementary Fig. 1. \n\nX-ray absorption fine structure. X-ray absorption fine structure (XAFS) is made possible through the general user programme at the Advanced Photon Source in Lemont, IL (GUP-38672). This technique provides a unique way to probe the local environment of a specific element based on the interference between an emitted core electron and the backscattering from surrounding species. XAFS makes no assumption of structure symmetry or elemental periodicity, making it an ideal means to study disordered materials. During the absorption process, core electrons will absorb incident X-ray energies equal to or greater than their respective binding energies. The emitted photoelectron wave interacts with neighbouring species, and the resulting absorption spectrum, displayed as absorption intensity versus incident energy, shows characteristic modulations unique to the target atom and its environment. \n\nEquimolar amounts of the constituent oxides $\\mathrm{\\Delta}\\mathrm{MgO}$ , NiO, CuO, CoO and $z_{\\mathrm{{nO}}}$ ) are mixed and pre-reacted at $1{,}000^{\\circ}\\mathrm{C}$ in air for $12\\mathrm{{h}}$ with intermittent stirring during calcination. The product is mixed into an isopropyl alcohol slurry and ball milled using yttrium-stabilized media for $24\\mathrm{h}$ . The powder is then dried in a fume hood at room temperature then re-fired at $1{,}000^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ , then checked via X-ray diffraction to ensure phase purity and that peaks remain narrow and intense. Milled grain size is measured using scanning electron microscopy and determined to average $\\sim10\\upmu\\mathrm{m}$ . \n\nA 2:1 powder to $10\\%$ $\\mathrm{PVA}/\\mathrm{H}_{2}\\mathrm{O}$ suspension is mixed continuously to disperse particles within the solution as well as aid in breaking up any agglomerates. Using a Cookson Electronics P-6000 spin coater, thin layers are spun onto $2\\times2\\mathrm{cm}$ square pieces of $25\\mathrm{-}\\upmu\\mathrm{m}$ thick Kapton. By trial and observation, it is determined that spinning at $2{,}000\\mathrm{r.p.m}$ . for 1 min makes a homogenous thin film with the appropriate quantity of particles for XAFS analysis. \n\nAdvanced Photon Source beamline 12-BM is utilized for its energy range of $4.5\\mathrm{-}23\\mathrm{keV}$ , which can probe all cation species except magnesium. Absorption spectra are recorded as a function of energy using a fluorescence set- $\\mathrm{up}^{4\\dot{0}}$ with a Canberra 13-element Ge detector. The energies per measurement range from $150\\mathrm{eV}$ before the known K absorption edge of the target element to $\\mathrm{\\sim1,000eV}$ past the edge onset. Supplementary Table 3 lists the cation species of interest and their respective K edges. Simultaneously to the sample fluorescence, reference foils are measured in transmission mode. This enables the energy calibration of the data relative to the theoretical edge of the metal, since compounds tend to have a slight variation in their absorption-edge energies. Each measurement is repeated three times to check for systematic error and to improve signal to noise ratio. \n\nThe raw data shown in Supplementary Fig. 2a plots the absorption edge and modulations on the post edge background. In order to isolate the EXAFS from these spectra, a background function is fit and subtracted. Energy space is transformed into $k$ -space via the equation25: \n\n$$\nk={\\sqrt{\\frac{2m(E-E_{0})}{\\hbar^{2}}}}\n$$ \n\nwhere $m$ is electron mass, $\\hbar$ is the reduced Planck’s constant, and $E_{0}$ is the absorption-edge energy. Supplementary Fig. 2b shows the isolated EXAFS from the measurement. With this data, qualitative conclusions can be made pertaining to the degree of randomness of the cation species. If there were ordering within the system, these spectra would not demonstrate such consistent oscillatory structure and the scattering pathways for individual species would be unique. We limit our current conclusions at this somewhat conservative level as it provides the evidence needed to support a random solid solution. \n\nScanning transmission electron microscopy. To best facilitate sample preparation and atomic-resolution analysis in STEM, a single crystal E1 thin film is grown on a {100} MgO substrate using pulsed laser deposition and thinned to electron transparency. The deposition process used a KrF $248\\mathrm{nm}$ excimer laser; with an energy density of $3\\mathrm{J}\\mathrm{cm}^{-2}$ , substrate temperature of $600^{\\circ}\\mathrm{C},$ an oxygen pressure of 50 mtorr and target to substrate distance of $4c m$ . A deposition rate of $6\\mathrm{Hz}$ and 40,000 pulses resulted in an $\\sim400–\\mathrm{nm}$ -thick film. The thin film sample was used for two reasons: (1) an edge-oriented substrate facilitates imaging along a low index zone axis perpendicular to the thinnest portion of the sample (this can be challenging for random powder specimens); and (2) by capping the thin film with a conductor, one can provide a conductive pathway to mitigate the sample charging that ultimately manifests in image drift. To do so, E1 films were coated with $50\\mathrm{nm}$ of indium tin oxide (ITO) at room temperature using radio frequency-magnetron sputtering. Indium tin oxide is the preferred conductor as it is mechanically similar to a halide oxide and thus responds comparably to mechanical polishing. \n\nLaser ablated samples were examined by four-circle diffraction to assess crystallinity and epitaxy. Supplementary Fig. 4 shows a theta–two theta and an omega scan for E1 prepared at $600^{\\circ}\\mathrm{C}$ . The films are epitaxial to the $\\mathrm{MgO}$ substrate (expected since the lattice mismatch is below $1\\%$ ), and the mosaicity observed in the omega circle is consistent with that present in the $\\mathbf{MgO}$ substrate. MgO substrates are known to have limited crystal quality $\\cdot\\sim0.02^{\\circ}$ in omega) due to the flame-fusion technique used to grow them. \n\nAn Allied Multiprep polishing system is utilized to prepare a cross-sectional electron microscopy sample by wedge polishing technique41. To achieve electron transparency, the polished sample is ion milled with a Fischione Model 1050 Ion Mill while cooling with liquid nitrogen. \n\nA JEOL 2000 S/TEM is used to collect selected area diffraction patterns from the E1 thin film. An aberration corrected FEI Titan G260–300 kV S/TEM equipped with an X-FEG source and an advanced Super-XTM EDS detector system is used to analyse the structure and chemistry of E1. The Titan is operated at $200\\mathrm{kV}$ for HAADF STEM imaging and EDS mapping with the convergence semi-angle set to 15 mrad. The atomic-resolution EDS map indicating the position and the arrangement of the ions in the unit cell can be explained by corresponding HAADF–STEM images in which the atomic columns containing heavier elements are observed brighter. \n\nWe note that STEM analysis is also performed on cryogenically fractured E1 powder samples, and epitaxial thin films along [001] and [110] zone axes. In all cases STEM EDS analysis revealed no second phases and homogeneous and random elemental distributions within the E1 crystals. The STEM data featured in Fig. 5 of the main text was chosen since the thin film configuration coated with a capping layer of ITO mitigated charging most effectively and allowed access to near-atomic resolution with channelling conditions. \n\nSupplementary Fig. 5 is a selected area diffraction pattern for E1 taken along ${\\<}001>$ , the pattern contains no diffraction events that are attributable to second phases or to cation ordering. As such, we conclude single phase on the local scale. Supplementary Fig. 6 is a lower magnification STEM image showing a wider area view as compared with STEM EDS data in the main text. Two observations are of particular note: (1) the HAADF-STEM image on the left suggests high crystallinity; and (2) the STEM–EDS analysis shows no evidence for chemical segregation or phase separation over a lager range. \n\nConfigurational entropy in the ideal model. The following derivation describes the method to determine the composition dependence of configurational entropy shown in Fig. 2b of the main text. An $N.$ species system having composition $\\{x_{i}\\}$ has ideal entropy equal to: \n\n$$\nS=-k_{\\mathrm{B}}\\sum_{i=1}^{N}x_{i}\\mathrm{log}(x_{i}).\n$$ \n\nThe maximum S is reached at equicomposition $x_{i}=1/N$ for each $i,$ so: \n\n$$\nS_{\\mathrm{max}}=-k_{\\mathrm{B}}\\mathrm{log}(N)\n$$ \n\nIf only one species is varied, composition $x_{1}=x$ for instance, while leaving the other $N-1$ species at equicomposition: \n\n$$\nx_{i\\neq1}={\\frac{1-x}{N-1}}\n$$ \n\nthe ideal entropy becomes: \n\n$$\n\\begin{array}{l}{S=-k_{\\mathrm{B}}\\left[x\\mathrm{log}(x)+(N-1)\\displaystyle\\frac{1-x}{N-1}\\mathrm{log}\\left(\\displaystyle\\frac{1-x}{N-1}\\right)\\right]}\\\\ {=-k_{\\mathrm{B}}\\left[x\\mathrm{log}(x)+(1-x)\\mathrm{log}\\left(\\displaystyle\\frac{1-x}{N-1}\\right)\\right].}\\end{array}\n$$ \n\nAn expanded plot of entropy versus $N$ for the entire series is shown in the Supplementary Fig. 7. \n\n# References \n\n1. Goldschmidt, V. M. The laws of crystal chemistry. Naturwissenschaften 14, 477–485 (1926). \n2. Hume-Rothery, W. & Powell, H. M. On the theory of super-lattice structures in alloys. Z. Kristallogr. 91, 23–47 (1935). \n3. Pauling, L. The sizes of ions and the structure of ionic crystals. J. Am. Chem. Soc. 49, 765–790 (1927). \n4. Muller, O. & Roy, R. The Major Ternary Structural Families (Springer, 1974). \n5. Choi, K. et al. Enhancement of ferroelectricity in strained BaTiO3 thin films. Science 306, 1005–1009 (2004). \n6. Gudiksen, M., Lauhon, L., Wang, J., Smith, D. & Lieber, C. Growth of nanowire superlattice structures for nanoscale photonics and electronics. Nature 415, 617–620 (2002). \n7. Park, S. & Shrout, T. Ultrahigh strain and piezoelectric behavior in relaxor based ferroelectric single crystals. J. Appl. Phys. 82, 1804 (1997). \n8. Xiang, X. et al. A combinatorial approach to materials discovery. Science 268, 1738–1740 (1995). \n9. Rijnders, G. & Blank, D. Materials science: build your own superlattice. Nature 433, 369–370 (2005). \n10. Paisley, E. et al. Surfactant assisted growth of MgO films on GaN. Appl. Phys. Lett. 101, 092904 (2012). \n11. Gao, P. et al. Conversion of zinc oxide nanobelts into superlattice-structured nanohelices. Science 309, 1700–1704 (2005). \n12. Wang, Y. et al. Ab initio lattice stability in comparison with CALPHAD lattice stability. Calphad 28, 79–90 (2004). \n13. Curtarolo, S. et al. AFLOW: An automatic framework for high-throughput materials discovery. Comput. Mater. Sci. 58, 218–226 (2012). \n14. Curtarolo, S. et al. AFLOWLIB.ORG: a distributed materials properties repository from high-throughput ab initio calculations. Comput. Mater. Sci. 58, 227–235 (2012). \n15. Potyrailo, R. et al. Combinatorial and high-throughput screening of materials libraries: review of state of the art. ACS Comb. Sci. 13, 579–633 (2011). \n16. Curtarolo, S., Morgan, D., Persson, K., Rodgers, J. & Ceder, G. Predicting crystal structures with data mining of quantum calculations. Phys. Rev. Lett. 91 (2003). \n17. Curtarolo, S. et al. The high-throughput highway to computational materials design. Nat. Mater. 12, 191–201 (2013). \n18. Hautier, G., Fischer, C., Ehrlacher, V., Jain, A. & Ceder, G. Data mined ionic substitutions for the discovery of new compounds. Inorg. Chem. 50, 656–663 (2011). \n19. Carrete, J., Mingo, N. & Wang, S. et al. Nanograined half-Heusler semiconductors as advanced thermoelectrics: an ab-initio high-throughput statistical study. Adv. Funct. Mater. 24, 7427–7432 (2014). \n20. Gautier, R. et al. Prediction and accelerated laboratory discovery of previously unknown 18-electron ABX compounds. Nat. Chem. 7, 308–316 (2015). \n21. Bennet, J., Garrity, K., Rabe, K. & Vanderbilt, D. Orthorhombic A BC semiconductors as antiferroelectrics. Phys. Rev. Lett. 110, 017603 (2013). \n22. Cantor, B., Chang, I., Knight, P. & Vincent, A. Microstructural development in equiatomic multicomponent alloys. Mater. Sci. Eng. A 375, 213–218 (2004). \n23. Gludovatz, B. et al. A fracture-resistant high-entropy alloy for cryogenic applications. Science 345, 1153–1158 (2014). \n24. Gali, A. & George, E. Tensile properties of high- and medium-entropy alloys. Intermetallics 39, 74–78 (2013). \n25. Jones, N., Aveson, J., Bhowmik, A., Conduit, B. & Stone, H. On the entropic stabilisation of an Al0.5CrFeCoNiCu high entropy alloy. Intermetallics 54, \n148–153 (2014). \n26. Otto, F., Yang, Y., Bei, H. & George, E. Relative effects of enthalpy and entropy on the phase stability of equiatomic high-entropy alloys. Acta Mater. 61, \n2628–2638 (2013). \n27. Wu, Z., Bei, H., Otto, F., Pharr, G. & George, E. Recovery, recrystallization, grain growth and phase stability of a family of FCC-structured multicomponent equiatomic solid solution alloys. Intermetallics 46, 131–140 (2014). \n28. Zhang, F. et al. An understanding of high entropy alloys from phase diagram calculations. Calphad 45, 1–10 (2014). \n29. Santodonato, L. et al. Deviation from high-entropy configurations in the atomic distributions of a multi-principal-element alloy. Nat. Commun. 6, 5964 (2015). \n30. Navrotsky, A. & Kleppa, O. The thermodynamics of cation distributions in simple spinels. J. Inorg. Nucl. Chem. 29, 2701–2714 (1967). \n31. Navrotsky, A. & Kleppa, O. Thermodynamics of formation of simple spinels. J. Inorg. Nucl. Chem. 30, 479–498 (1968). \n32. Jones, S., Fenerty, J. & Pearce, J. The enantiotropic phase transition of antimony(III) oxide. Thermochim. Acta 114, 61–66 (1987). \n33. Bragg, W. & Williams, E. The effect of thermal agitation on atomic arrangement in alloys. II. Proc. R. Soc. Lond. A 151, 540–566 (1935). \n34. Knapp, G., Nevitt, M., Aldred, A. & Klippert, T. An EXAFS study of interionic distances in complex lanthanide oxides. J. Phys. Chem. Solids 46, 1321–1325 (1985). \n35. Antonioli, G., Lottici, P., Parisini, A. & Razzetti, C. EXAFS study of mixed crystals of the AIIBIII2XVI4 family. Prog. Cryst. Growth Charact. 10, 9–18 (1984). \n36. Davies, P. & Navrotsky, A. Thermodynamics of solid solution formation in NiO-MgO and NiO-ZnO. J. Solid State Chem. 38, 264–276 (1981). \n37. Bularzik, J., Davies, P. & Navrotsky, A. Thermodynamics of solid-solution formation in NiO-CuO. J. Am. Ceram. Soc. 69, 453–457 (1986). \n38. Megaw, H. Crystal Structures: A Working Approach (Saunders, 1973). \n39. Navrotsky, A. Thermochemistry of perovskite-related oxides with high oxidation states: superconductors, sensors, fuel cell materials. Pure Appl. Chem. \n66, 1759–1764 (1994). \n\n40. Calvin, S. XAFS for Everyone (CRC, 2013). 41. Voyles, P., Grazul, J. & Muller, D. Imaging individual atoms inside crystals with ADF-STEM. Ultramicroscopy 96, 251–273 (2003). \n\n# Acknowledgements \n\nJ-P.M., E.C.D. and C.M.R. acknowledge support from ARO under contract W911NF-14- 0285. J-P.M. and C.M.R. acknowledge the Advanced Photon Source (supported by proposal 38672) for access to synchrotron experiments. S.C. acknowledges partial support by DOD (ONR-MURI- N000141310635), DOE (DE-AC02-05CH11231, BES #EDCBEE) and the Duke Center for Materials Genomics and the aflowlib.org consortium. J-P.M. and S.C. acknowledge support from DOD (ONR-MURI-N00014-15-1- 2863). The authors acknowledge the use of the Analytical Instrumentation facility at North Carolina State University who provided access to X-ray diffraction and electron microscopy facilities. AIF is supported by the State of North Carolina and the National Science Foundation. J-P.M. and C.M.R. acknowledge useful discussions with Dr Sungsik Lee at the Advanced Photon Source regarding collection and interpretation of XAFS data. \n\n# Author contributions \n\nC.M.R., E.S., T.B. and J-P.M. designed the experimental plan, performed sample synthesis and ex situ sample characterization; J-P.M. and S.C. envisioned and implemented the experiments to test the entropy hypothesis; S.C. performed thermodynamic calculations for composition dependence of entropy; D.H. and J.L.J. performed temperature dependent X-ray diffraction experiments, and E.C.D. and A.M. conducted TEM investigations. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Rost, C. M. et al. Entropy-stabilized oxides. Nat. Commun. \n6:8485 doi: 10.1038/ncomms9485 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1126_science.aaa0472", + "DOI": "10.1126/science.aaa0472", + "DOI Link": "http://dx.doi.org/10.1126/science.aaa0472", + "Relative Dir Path": "mds/10.1126_science.aaa0472", + "Article Title": "High-efficiency solution-processed perovskite solar cells with millimeter-scale grains", + "Authors": "Nie, WY; Tsai, HH; Asadpour, R; Blancon, JC; Neukirch, AJ; Gupta, G; Crochet, JJ; Chhowalla, M; Tretiak, S; Alam, MA; Wang, HL; Mohite, AD", + "Source Title": "SCIENCE", + "Abstract": "State-of-the-art photovoltaics use high-purity, large-area, wafer-scale single-crystalline semiconductors grown by sophisticated, high-temperature crystal growth processes. We demonstrate a solution-based hot-casting technique to grow continuous, pinhole-free thin films of organometallic perovskites with millimeter-scale crystalline grains. We fabricated planar solar cells with efficiencies approaching 18%, with little cell-to-cell variability. The devices show hysteresis-free photovoltaic response, which had been a fundamental bottleneck for the stable operation of perovskite devices. Characterization and modeling attribute the improved performance to reduced bulk defects and improved charge carrier mobility in large-grain devices. We anticipate that this technique will lead the field toward synthesis of wafer-scale crystalline perovskites, necessary for the fabrication of high-efficiency solar cells, and will be applicable to several other material systems plagued by polydispersity, defects, and grain boundary recombination in solution-processed thin films.", + "Times Cited, WoS Core": 2941, + "Times Cited, All Databases": 3159, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000348639300046", + "Markdown": "ultrahigh-quality crystalline silicon, grown at high temperatures, offers comparable or better deep trap densities $(10^{8}}10^{3}\\upmu\\mathrm{m}^{2})$ were observed at 1.627 eV and $1.653\\mathrm{eV}$ , respectively (Fig. 4A). As the grain size decreased, two concomitant effects were observed: (i) a blue shift of the band-edge photoluminescence by $\\mathrm{\\sim25meV}$ (Fig. 4B), and (ii) linewidth broadening of ${\\sim}20\\mathrm{meV}$ (Fig. 4C). Such blue shifts were predicted by our density functional theory (DFT) simulations (24) (fig. S12) and are possibly attributed to the composition change at the grain boundaries. The increase of emission line width at grain boundaries can be attributed to disorder and defects. We observed a bimolecular recombination process of free electrons and holes for the largegrain crystals by means of time-resolved photoluminescence spectroscopy (Fig. 4D), which is a strong indicator of good crystalline quality (24) (fig. S13). This is in contrast to a monoexponential decay observed in previous reports for small grain size or mesoporous structures (11, 12, 32) and with our measurements on small grains, and is representative of nonradiative decay due to trap states. These results are also consistent with our earlier measurements of $V_{\\mathrm{OC}}$ as a function of light intensity, which suggest reduced trap-assisted recombination in largearea grains. \n\nBeyond our results described above, further enhancements in efficiency can be expected by improving the interface between perovskite and PCBM, obtaining better band alignment, and using an inverted structure. From the perspective of the global photovoltaics community, these results are expected to lead the field toward the reproducible synthesis of wafer-scale crystalline perovskites, which are necessary for the fabrication of high-efficiency single-junction and hybrid (semiconductor and perovskite) planar cells. \n\n# REFERENCES AND NOTES \n\n1. J. Burschka et al., Nature 499, 316–319 (2013). \n2. M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami, \nH. J. Snaith, Science 338, 643–647 (2012). \n3. A. Mei et al., Science 345, 295–298 (2014). \n4. H. Zhou et al., Science 345, 542–546 (2014). \n5. H.-S. Kim et al., Sci. Rep. 2, 591 (2012). \n6. M. Liu, M. B. Johnston, H. J. Snaith, Nature 501, 395–398 (2013). \n7. N. J. Jeon et al., Nat. Mater. 13, 897–903 (2014). \n8. P. Docampo, J. M. Ball, M. Darwich, G. E. Eperon, H. J. Snaith, \nNat. Commun. 4, 2761 (2013). \n9. O. Malinkiewicz et al., Nat. Photonics 8, 128–132 (2014). \n10. J. Seo et al., Energy Environ. Sci. 7, 2642–2646 (2014). \n11. S. D. Stranks et al., Science 342, 341–344 (2013). \n12. G. Xing et al., Science 342, 344–347 (2013). \n13. J. S. Manser, P. V. Kamat, Nat. Photonics 8, 737–743 (2014). \n14. M. Grätzel, Nat. Mater. 13, 838–842 (2014). \n15. M. D. McGehee, Nat. Mater. 13, 845–846 (2014). \n16. R. S. Sanchez et al., J. Phys. Chem. Lett. 5, 2357–2363 (2014). \n17. H. J. Snaith et al., J. Phys. Chem. Lett 5, 1511–1515 (2014). \n18. G. E. Eperon, V. M. Burlakov, P. Docampo, A. Goriely, \nH. J. Snaith, Adv. Funct. Mater. 24, 151–157 (2014). \n19. M. Xiao et al., Angew. Chem. Int. Ed. 53, 9898–9903 (2014). \n20. B. Conings et al., Adv. Mater. 26, 2041–2046 (2014). \n21. A. Dualeh et al., Adv. Funct. Mater. 24, 3250–3258 (2014). \n22. Q. Wang et al., Energy Environ. Sci. 7, 2359–2365 (2014). \n23. H.-B. Kim et al., Nanoscale 6, 6679–6683 (2014). \n24. See supplementary materials on Science Online. \n25. [Editorial] Nat. Photonics 8, 665 (2014). \n26. Q. Chen et al., J. Am. Chem. Soc. 136, 622–625 (2014). \n27. G. Grancini et al., J. Phys. Chem. Lett. 5, 3836–3842 (2014). \n28. Z. Xiao et al., Adv. Mater. 26, 6503–6509 (2014). \n29. S. R. Cowan, A. Roy, A. J. Heeger, Phys. Rev. B 82, 245207 (2010). \n30. C. M. Proctor, C. Kim, D. Neher, T.-Q. Nguyen, Adv. Funct. \nMater. 23, 3584–3594 (2013). \n31. C. M. Proctor, M. Kuik, T.-Q. Nguyen, Prog. Polym. Sci. 38, \n1941–1960 (2013). \n32. C. Wehrenfennig et al., Adv. Mater. 26, 1584–1589 (2014). \n\n![](images/6b98f22eb6ab79e616b683aa17ff0d882710b2bac30a72fdc469c519aa050211.jpg) \nFig. 4. Spectrally, spatially, and temporally resolved microphotoluminescence spectroscopy. (A) Normalized absorbance (black) and microscopically resolved PL emission spectra (red) obtained for a large-grain sample. (B) Normalized, microscopically resolved emission spectra for different grain sizes. (C) Relative shift and linewidth broadening of the band-edge emission as a function of grain area (with respect to the largest grain). (D) Normalized, microscopically resolved timecorrelated single-photon histograms of both a large and a small grain (black). The red and blue lines are fits to the intensity decay considering interband relaxation, radiative bimolecular recombination, and nonradiative decay into states below the gap (see figs. S13 and S14). \n\n# ACKNOWLEDGMENTS \n\nWork at Los Alamos National Laboratory (LANL) was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Work Proposal 08SPCE973 (W.N., G.G., and A.D.M.) and by the LANL LDRD program XW11 (A.D.M., H.-L.W., and S.T.). This work was done in part at the Center for Integrated Nanotechnologies, an Office of Science User Facility. Work at Purdue University was supported by the U.S. Department of Energy under DOE Cooperative Agreement no. DE-EE0004946 (“PVMI Bay Area PV Consortium”). We thank C. Sheehan for the high-resolution cross-sectional SEM images. A.J.N. and S.T. thank C. Katan, J. Even, L. Pedesseau, and M. Kepenekian for useful discussions as well as starting coordinates for bulk perovskites. Author contributions: A.D.M. conceived the idea, designed and supervised experiments, analyzed data, and wrote the manuscript. H.-L.W. and H.T. designed the synthesis chemistry for perovskite thin-film growth and analyzed data. W.N. developed the hot-casting, slow-quenching method for large-area crystal growth along with H.T. and also performed device fabrication and solar cell testing, x-ray diffraction and analyzed the data. J.-C.B. performed optical spectroscopy measurements, analyzed the data under the supervision of J.J.C. R.A. performed device modeling simulations. M.A.A. conceived the device modeling, supervised the device modeling, analyzed crystal growth mechanisms, and co-wrote the paper. A.J.N. performed DFT calculations under the guidance of S.T., who designed the DFT calculations, analyzed the data, and provided guidance to the project. G.G. and M.C. conceived the XRD measurements and analyzed the data, co-designed the experiments, and contributed to the organization of the manuscript. All authors have read the manuscript and agree to its contents. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/347/6221/522/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S21 \nTables S1 to S5 \nReferences (33–64) \n9 October 2014; accepted 23 December 2014 \n10.1126/science.aaa0472 \n\n# Science \n\n# High-efficiency solution-processed perovskite solar cells with millimeter-scale grains \n\nWanyi Nie, Hsinhan Tsai, Reza Asadpour, Jean-Christophe Blancon, Amanda J. Neukirch, Gautam Gupta, Jared J. Crochet, Manish Chhowalla, Sergei Tretiak, Muhammad A. Alam, Hsing-Lin Wang and Aditya D. Mohite \n\nScience 347 (6221), 522-525. DOI: 10.1126/science.aaa0472 \n\n# Large-crystal perovskite films \n\nThe performance of organic-inorganic hybrid perovskite planar solar cells has steadily improved. One outstanding issue is that grain boundaries and defects in polycrystalline films degrade their output. Now, two studies report the growth of millimeter-scale single crystals. Nie et al. grew continuous, pinhole-free, thin iodochloride films with a hot-casting technique and report device efficiencies of $18\\%$ . Shi et al. used antisolvent vapor-assisted crystallization to grow millimeter-scale bromide and iodide cubic crystals with charge-carrier diffusion lengths exceeding $10\\mathsf{m m}$ . \n\nScience, this issue p. 522, p. 519 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/347/6221/522 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2015/01/28/347.6221.522.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/347/6221/519.full http://science.sciencemag.org/content/sci/347/6225/967.full \n\nREFERENCES \n\nThis article cites 60 articles, 5 of which you can access for free http://science.sciencemag.org/content/347/6221/522#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1021_ja511559d", + "DOI": "10.1021/ja511559d", + "DOI Link": "http://dx.doi.org/10.1021/ja511559d", + "Relative Dir Path": "mds/10.1021_ja511559d", + "Article Title": "Identification of Highly Active Fe Sites in (Ni,Fe)OOH for Electrocatalytic Water Splitting", + "Authors": "Friebel, D; Louie, MW; Bajdich, M; Sanwald, KE; Cai, Y; Wise, AM; Cheng, MJ; Sokaras, D; Weng, TC; Alonso-Mori, R; Davis, RC; Bargar, JR; Norskov, JK; Nilsson, A; Bell, AT", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Highly active catalysts for the oxygen evolution reaction (OER) are required for the development of photoelectrochemical devices that generate hydrogen efficiently from water using solar energy. Here, we identify the origin of a 500-fold OER activity enhancement that can be achieved with mixed (Ni,Fe)oxyhydroxides (Ni1-xFexOOH) over their pure Ni and Fe parent compounds, resulting in one of the most active currently known OER catalysts in alkaline electrolyte. Operando X-ray absorption spectroscopy (XAS) using high energy resolution fluorescence detection (HERFD) reveals that Fe3+ in Ni1-xFexOOH occupies octahedral sites with unusually short Fe-O bond distances, induced by edge-sharing with surrounding [NiO6] octahedra. Using computational methods, we establish that this structural motif results in near optimal adsorption energies of OER intermediates and low overpotentials at Fe sites. By contrast, Ni sites in Ni1-xFexOOH are not active sites for the oxidation of water.", + "Times Cited, WoS Core": 2153, + "Times Cited, All Databases": 2270, + "Publication Year": 2015, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000348690100042", + "Markdown": "# Identification of Highly Active Fe Sites in (Ni,Fe)OOH for Electrocatalytic Water Splitting \n\nDaniel Friebel,\\*,†,§,¶ Mary W. Louie,†,‡,¶ Michal Bajdich,§,¶ Kai E. Sanwald,§,∥ Yun Cai,†,‡ Anna M. Wise,⊥ Mu-Jeng Cheng,†,‡ Dimosthenis Sokaras,⊥ Tsu-Chien Weng,⊥ Roberto Alonso-Mori,# Ryan C. Davis,⊥ John R. Bargar,⊥ Jens K. Nørskov,§ Anders Nilsson,†,§,⊥ and Alexis T. Bell\\*,†,‡ \n\n†Joint Center for Artificial Photosynthesis, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mail Stop 976, Berkeley, \nCalifornia 94720, United States \n‡Department of Chemical and Biomolecular Engineering, University of California at Berkeley, 107 Gilman Hall, Berkeley, California \n94720, United States \n§SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, \nCalifornia 94025, United States \n∥Department of Chemistry, Technische Universität München, Lichtenbergstraße 4, 85749 Garching, Germany \n⊥Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California \n94025, United States \n#Linac Coherent Lightsource, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United \nStates \n\n# Supporting Information \n\nABSTRACT: Highly active catalysts for the oxygen evolution reaction (OER) are required for the development of photoelectrochemical devices that generate hydrogen efficiently from water using solar energy. Here, we identify the origin of a 500-fold OER activity enhancement that can be achieved with mixed (Ni,Fe)oxyhydroxides $(\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH})$ over their pure Ni and Fe parent compounds, resulting in one of the most active currently known OER catalysts in alkaline electrolyte. Operando X-ray absorption spectroscopy (XAS) using high energy resolution fluorescence detection (HERFD) reveals that $\\mathrm{Fe}^{\\tilde{3}+}$ in $\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH}$ occupies octahedral sites \n\n![](images/a2c0786b2e6ef5ccc0c3c38133575ac14aa7ada7fa10411c594bcef84c12b829.jpg) \n\nwith unusually short Fe−O bond distances, induced by edge-sharing with surrounding $\\left[\\mathrm{NiO}_{6}\\right]$ octahedra. Using computational methods, we establish that this structural motif results in near optimal adsorption energies of OER intermediates and low overpotentials at Fe sites. By contrast, $\\mathrm{\\DeltaNi}$ sites in $\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH}$ are not active sites for the oxidation of water. \n\n# INTRODUCTION \n\nThe conversion of solar energy to renewable fuels is an important and scientifically challenging issue. A critical requirement for achieving this goal is an efficient means for photoelectrochemically splitting water to hydrogen and oxygen. The hydrogen can be used to provide fuel for a fuel cell, as a green, carbon-free reducing agent for upgrading of biomass to fuels, or, in the future, for reducing $\\mathrm{CO}_{2}$ to fuels. Prior work has shown that one of the most significant performance losses of electrochemical and photoelectrochemical cells used for the water splitting is due to the high overpotential $\\left(>0.35\\mathrm{~V}\\right)$ of existing water oxidation catalysts required for the anode of such cells.1−11 If the overpotential for the oxygen evolution reaction (OER) cannot be reduced, then high band gap photoabsorbers or high catalyst loadings will be needed in order to match geometric photocurrent and catalytic current densities.1,12 Increased catalyst loading is undesirable since light absorption in the catalyst will reduce the photon flux to the photoabsorber.13,14 To overcome this limitation, it is necessary to understand what limits the OER activity of existing OER catalysts. \n\nThe most promising OER catalysts based on earth-abundant elements are mixed Ni−Fe compounds, which perform best in alkaline eletrolytes.15−27 While there is consensus that the coexistence of Ni and Fe is required to achieve high activity, a variety of views have been reported regarding the structure of the active phase and whether Fe or Ni constitutes the active center, and only a few studies have examined the energetics of intermediates involved in the OER.26,28 In an effort to identify the structure of active Ni−Fe OER catalysts, we have used in situ Raman spectroscopy to characterize electrochemically grown Ni−Fe films.23 This work has shown that NiOOH is present for films containing up to ${\\sim}50\\%$ Fe, and at higher Fe concentrations there is increasing evidence for a mixture of FeOOH and ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ . However, neither this work nor other studies have identified the local structure of the Fe sites unambiguously.29−32 It is, therefore, desirable to obtain a fundamental understanding of the interactions of Ni and Fe and how they contribute to the high OER activity of $_\\mathrm{Ni-Fe}$ catalysts. A question of particular interest is whether the substitution of Fe cations into NiOOH enhance the OER activity of Ni, Fe, or both, and whether the substitution of Ni into FeOOH can enhance the activity of this phase and if so, how. Answers to these questions would not only explain the unusually high activity of Ni−Fe OER catalysts but should also provide guidance for the design of new catalysts. \n\nHere, we probe the short-range structure at Fe and Ni sites in electrodeposited (Ni,Fe) oxyhydroxide catalysts, across the entire composition range, in 0.1 M KOH with element-sensitive operando $\\mathrm{x}$ -ray absorption spectroscopy (XAS) in the high energy resolution fluorescence detection (HERFD) mode. The HERFD technique provides detailed electronic structure information through spectra with partially removed core-hole lifetime broadening 33,34 and enhanced pre-edge features.35,36 XAS analysis, reinforced by density-functional theory with Hubbard U $\\mathrm{\\DeltaDFT+U},$ calculations conducted on model catalysts, leads to the conclusion that electrodeposited (Ni,Fe) oxyhydroxide catalysts contain two phases, Fecontaining $\\gamma{\\mathrm{-NiOOH}}$ and $\\gamma{\\mathrm{-FeOOH}}$ containing little or no Ni (see Figure 1). $\\tt D F T+U$ calculations reveal the effects of catalyst composition on the OER overpotential: the active sites in $\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH}$ are Fe cations; the alteration of their electronic properties due to incorporation into γ-NiOOH dramatically changes the chemical bonding of these cations with intermediates involved in the OER, resulting a lower OER overpotential and, correspondingly, increased OER activity. \n\n![](images/514e7165fdcd9cb5b6c57a3ba72baee7d2751ce3ac07f4441ed0e517d96a87ad.jpg) \nFigure 1. Measured OER activity of mixed Ni−Fe catalysts as a function of Fe content in $0.1\\mathrm{~M~}$ KOH. For $0\\%$ Fe, measurements were performed in electrolyte which was carefully purified to remove any Fe contamination. Top: a schematic illustrating the influence of Fe content on the competing formation of highly active Fe sites in $\\gamma-$ NiOOH and of phase-separated low-activity γ-FeOOH. \n\n# EXPERIMENTAL SECTION \n\nAll operando XAS measurements were carried out using custom-made spectroelectrochemical cells. Each working electrode consisted of a 1 $\\mu\\mathrm{m}$ thin silicon nitride window ( $\\mathsf{S}\\times\\mathsf{S}\\ \\mathrm{mm}^{2}$ on a $10\\times10~\\mathrm{mm}^{2}.$ 200 $\\mu\\mathrm{m}$ thick silicon supporting frame) onto which a Ti adhesion layer (4 nm) followed by the Au layer $\\left(10\\mathrm{\\nm}\\right)$ were evaporated (see Supporting Information S1 for details). Ni−Fe catalysts were electrodeposited using the procedure described previously23 except with a shorter deposition time of $20~\\mathrm{s};$ ; this prevented the formation of metallic Ni and Fe byproducts that were detected in thicker films (see Supporting Information S2). An intermediate film thickness was prepared for the complementary EXAFS characterization of the catalyst containing $25\\%$ Fe; in this case, sputter deposition was used instead of electrodeposition, and the resulting ${\\sim}2~\\mathrm{nm}$ thick metallic film was subsequently oxidized in 0.1 M KOH by cycling the potential between 0.92 and $1.62\\mathrm{V}$ for ${\\sim}17\\mathrm{h}$ at a sweep rate of $\\mathrm{i}0\\mathrm{mV}/s$ . After this treatment no metallic Fe or Ni was detected, and the thickness of the oxidized film ( $\\mathrm{\\sim}10~\\mathrm{nm},$ estimated using the density of the $\\mathrm{{Ni}(\\mathrm{{II})/}}$ $\\mathrm{Fe(III)}$ layered double hydroxide structure31 at low potential) was sufficient for conventional EXAFS measurements. \n\nDuring operando XAS measurements, a three-electrode setup using a Pt counter electrode (DOE Business Center for Precious Metals Sales and Recovery, USA) and a $\\mathrm{Hg/HgO/1}$ M KOH reference electrode (ET072, CH Instruments, USA) was controlled with a potentiostat $(\\mathrm{VSP/Z{-}01}$ , BioLogic, France). All potentials were corrected at $95\\%$ for the ohmic drop, which was determined using an AC impedance measurement, and are converted and reported with respect to the reversible hydrogen electrode (RHE). \n\nAll XAS measurements were carried out at the Stanford Synchrotron Radiation Lightsource (SSRL). The sample cells were aligned such that both incident beam and fluorescence would enter and exit through the silicon nitride window at the back of the Au electrode at an angle of ${\\sim}45^{\\circ}$ , with no penetration of electrolyte necessary. HERFD XAS measurements were made with the highresolution spectrometer at SSRL beamline 6−2.37 The incident energy was selected using a double-crystal monochromator with Si(311) and Si(111) crystals for measurements at the Fe and Ni K-edge, respectively. A Rowland circle spectrometer ${\\bf\\ddot{\\phi}}R=1{\\bf\\phi}\\mathrm{m})$ was aligned to the peaks of the Fe and Ni $\\mathrm{K}\\alpha$ lines. To collect the Fe $\\mathrm{K}\\alpha$ emission, four spherically bent ${\\mathrm{Ge}}(440)$ crystals were aligned to the peak at 6404 eV, corresponding to a Bragg angle of $75.5^{\\circ}$ . The Ni Kα emission at $7478\\ \\mathrm{eV}$ was collected using three spherically bent Si(620) crystals at a Bragg angle of $74.9^{\\circ}$ . The combined resolution of spectrometer and monochromator was determined to be 1.0 and $1.3~\\mathrm{{\\eV}}$ for measurements at the Fe and Ni K-edge, respectively. \n\nHERFD XAS scans were treated by subtracting a constant background (typically ${\\sim}25$ counts/s) and normalized to an edgejump of 1. Complementary operando EXAFS measurements were carried out at SSRL beamline $_{4-1}$ , using a 32-element Ge array detector. In these conventional fluorescence detection measurements the background from elastic and Compton scattering was reduced using a combination of Z-1 filters (3 absorption lengths of Mn (Co) for Fe (Ni) K-edge spectra) with Soller slits. EXAFS data were averaged and normalized using $S_{ Ḋ }\\mathrm{IXPack}^{38}$ and spline-fitted using IFEFFIT39 through the Athena graphical user interface.40 EXAFS scattering paths were calculated with $\\mathrm{FEFF}6^{41}$ through the Artemis graphical user interface,40 using published crystallographic information for $\\gamma{\\mathrm{-FeOOH}}^{42}$ and $\\gamma{\\mathrm{-NiOOH}}$ .43 Least-squares fitting of the Fouriertransformed EXAFS signals was carried out using IFEFFIT39 through the SIXPack graphical user interface.38 All EXAFS data were fitted to the Fourier transforms of $\\chi(\\boldsymbol{k})$ using $k$ -weights of 1, 2, and 3 simultaneously. \n\n# COMPUTATIONAL METHODS \n\nBulk and surface properties and energetics of NiFe-oxides were obtained using the GGA-DFT plus Hubbard- $U$ framework (GGA $+\\mathrm{U})$ .44−46 The $\\mathrm{RPBE}^{47}$ parametrization of GGA was chosen together with rotationally invariant implemetation48 of Hubbard- $U$ term fixed at $U_{\\mathrm{Hub}}(\\mathrm{Ni})=6.6~\\mathrm{eV}$ and $U_{\\mathrm{Hub}}\\mathbf{\\bar{(Fe)}}=3.5~\\mathrm{eV}$ as obtained within linear response theory49 on respective pure systems. Furthermore, ultrasoft pseudopotentials50 and plane-wave basis set cutoff of 40 and $400~\\mathrm{Ry}$ for density were employed within the PWscf program of the Quantum Espresso package.51 For periodic slab calculations, slabs of four metal− oxygen layers, separated by at least $16\\mathring{\\mathrm{A}}$ of vacuum and containing 4 metal sites per surface unit mesh and a $4\\times4\\times1$ Monkhorst−Pack Kpoint grid were constructed. The atomic positions within the topmost two layers of the slabs were allowed to relax below a maximum threshold force of $0.05\\mathrm{eV}/{\\hat{\\mathrm{A}}}.$ Additional computational details are given in the Supporting Information (S3−S5). \n\n# RESULTS AND DISCUSSION \n\nCatalyst layers, ${\\sim}1.8\\ \\mathrm{\\nm}$ thick, were electrodeposited from $\\mathrm{FeSO}_{4}$ and $\\mathrm{NiSO}_{4}$ solutions (Supporting Information S1). Figure 1 shows that the addition of Fe to NiOOH results in up to 500-fold higher OER current density compared to pure Ni and Fe oxyhydroxide films (see Supporting Information S6 for details of OER activity measurements). The trend is very similar to results presented earlier;23 however, a notable exception is the point for no added Fe. Previous measurements of relatively high OER activity for “pure” $\\mathrm{NiOOH}^{27}$ were due to unintentional contamination with trace amounts of Fe present in the electrolyte.21 After eliminating these impurities (see Supporting Information S7), pure NiOOH films exhibited similar or lower OER activity than pure FeOOH. \n\nIn order to understand how the composition-dependent trend in Figure 1 correlates with the local structure at Fe and Ni sites within the catalysts, we acquired Fe and Ni K-edge HERFD XAS over the full range of Fe/Ni ratios and potentials both below and well within conditions where significant OER activity can be observed. The spectra were examined using an analysis of (i) local symmetry induced multiplet structure and relative intensity of the $1s\\rightarrow3d$ transitions in the pre-edge region,35,52 (ii) oxidation-state sensitive energy positions of the pre-edge centroid35,52 and photoionization threshold, (iii) structure (bond length) sensitive energy positions of peaks and dips in the high energy range that can be understood in the context of extended X-ray absorption fine structure (EXAFS) and (iv) spectral fingerprinting using literature data and own measurements of well-defined reference compounds. The key results are shown in Figure 2 and Figure 3 (see Supporting Information S8 for the complete set of spectra). \n\nIn an OER catalyst containing only Fe sites, the short-range structure closely resembles $\\gamma{\\mathrm{-FeOOH}}$ (Figure 2a); however, a small discrepancy can be seen in the pre-edge region at ${\\sim}7115$ eV, where $\\bar{\\mathrm{Fe}}^{3+}$ in octahedral coordination is expected to give rise to a characteristic double-peak structure, as observed with $\\gamma\\mathrm{-FeOOH.}^{35,52}$ A small amount ( $10~\\pm~3\\%$ of tetrahedrally coordinated $\\mathrm{Fe}^{3+}$ may therefore exist in addition to a majority species $(90\\pm3\\%)$ of $\\mathrm{Fe}^{3+}$ in an octahedral environment (see Supporting Information S9 for a more detailed analysis). \n\nHERFD XAS measurements at potentials (vs reversible hydrogen electrode, RHE) of 1.12, 1.52, 1.62, and $1.72\\mathrm{~V~}$ (Figure 2a) do not indicate any potential-induced phase transformation in the pure FeOOH sample. By contrast, the Fe $K$ -edge HERFD XAS for a sample containing $25\\%$ Fe and $75\\%$ Ni shows strong potential-induced changes (Figure 2b), which coincide with changes in complementary Ni K-edge HERFD XAS measurements. The latter can be identified with the wellknown spectral signatures of $\\alpha{\\mathrm{-Ni(OH)}}_{2}$ at low potentials and γ-NiOOH at high potentials. $^{9,32,53-56}$ Both $\\alpha{\\mathrm{-Ni\\bar{(OH)}}_{2}}$ and $\\gamma-$ \n\n![](images/ab940be1d15f75d5f9debc3b3631ad3c033872ad63046d91f2634116f0276b24.jpg) \nFigure 2. Comparison of $100\\%$ Fe-containing sample with OER catalyst containing $25\\%$ Fe and $75\\%$ Ni using operando HERFD XAS. (a) Catalyst containing $100\\%$ Fe. The spectrum of $\\gamma{\\mathrm{-FeOOH}}$ is also shown for comparison. Plots of both pre-edge (enlarged) and the full spectra are shown. $({\\mathsf{b}}{-}{\\mathsf{e}})$ Catalyst containing $25\\%$ Fe and $75\\%$ Ni. (b) Fe K-edge. While the potential increase does not influence the oxidation-state-sensitive energy of the main absorption threshold $\\left(7125\\mathrm{~\\eV}\\right)$ , significant $\\mathrm{Fe-O}$ bond contraction with increasing potential is clearly indicated by the changes of the photoelectron scattering features (energy range above $7140~\\mathrm{eV},$ ). (c) Complementary operando EXAFS measurement confirming the potential-induced bond contraction at both Fe and Ni sites. (d) Structure model of Fedoped $\\gamma{\\mathrm{-NiOOH}}$ . (e) Ni K-edge XAS showing shifts in both oxidationstate-sensitive and structure-sensitive features due to oxidation of $\\mathrm{Ni}^{2+}$ sites. \n\nNiOOH form layered structures in which sheets of edgesharing $\\left[\\mathrm{NiO}_{6}\\right]$ octahedra are separated by intercalated water molecules and hydrated ions (Figure 2d).56 The Ni−O bond lengths $^{9,32,53-56}$ differ significantly between 2.05 Å in $\\mathrm{{Ni}(\\mathrm{{II})}}$ - containing $\\alpha\\mathrm{-Ni(OH)}_{2},$ and 1.88 Å in $\\gamma{\\mathrm{-NiOOH}}$ , which is nonstoichiometric $\\left(\\mathrm{NiOOH}_{1-x}\\right)$ and contains a mixture of $\\operatorname{Ni}(\\operatorname{III})$ and $\\mathrm{{Ni}(\\mathrm{{IV})}}$ sites.57 The significant shift of both the preedge peak and the main absorption edge in the Ni K-edge spectra (Figure 2e) shows nearly complete oxidation of Ni sites when the potential is increased from 1.12 to $1.52\\mathrm{~V};$ the features of the oxidized component then approach saturation with further potential increase. A more detailed analysis (Supporting Information S10) confirms that the observed redox transition is indeed that between $\\alpha{\\mathrm{-Ni(OH)}}_{2}$ and $\\gamma-$ NiOOH; the presence of $\\beta{\\mathrm{-Ni}}(\\mathrm{OH})_{2}$ or $\\beta_{\\mathrm{-NiOOH}}$ can be ruled out. Both the Fe and Ni K-edge spectra exhibit shifts of the structure-sensitive EXAFS dips and peaks to higher energy, indicating significant bond contraction. Using the “bond length with a ruler” relationship $(E_{\\mathrm{peak}}-E_{0})d^{2}=\\mathrm{cons}$ st.,58,59 which is equivalent to an EXAFS analysis with a strongly reduced number of independent fitting parameters (see Supporting Information S11), we estimate a bond length contraction of (7 $\\pm1)\\%$ at both Fe and Ni sites. This result was further refined with EXAFS measurements over a much larger energy range for a $\\mathrm{Fe/Ni}$ (25:75) sample in the fully reduced and fully oxidized state. EXAFS confirms that the $\\mathrm{Fe-O}$ and $\\mathrm{{Ni-O}}$ bond lengths contract from 2.01 and $2.06\\mathring{\\mathrm{A}}$ at $1.12\\mathrm{V}$ to 1.90 and $1.89\\breve{\\mathrm{~A~}}$ at $1.92{\\mathrm{~V}}_{\\ }$ , respectively (Figure 2c, Table 1), and the result in Figure 2c was not affected by the catalyst preparation method (sputter deposition followed by electrochemical oxidation, see Supporting Information S2 for results with an electrodeposited film). A strong correlation was found not only between $\\mathrm{Fe-O}$ and $\\mathrm{{Ni-O}}$ bond lengths but also between nearest metal−metal distances, indicating that Fe substitutes for Ni in both $\\alpha\\cdot$ - $\\mathrm{\\Ni(OH)}_{2}$ and γ-NiOOH. Moreover, the identical appearance in both Fe and Ni K-edge EXAFS of a peak at approximately twice the nearest $\\mathrm{{Ni-Ni}}$ and Fe−Ni distance, predominantly from multiple-scattering in collinear Fe−Ni−Ni, Ni−Fe−Ni and aThis catalyst sample was made by sputter-deposition followed by electrochemical oxidation. Values shown without error bars were not allowed to vary in the fit. $S_{0}^{\\ 2}$ was fixed at 0.90. \n\n![](images/a07758880fb2850a5b953243940cf21705048750d1f6e8b502d7123f015735cc.jpg) \nFigure 3. Identification of the most likely structural motif for mixed Ni,Fe catalysts by comparison of experimentally obtained metal−oxygen bond lengths with optimized theoretical model structures. (a) Bond lengths extracted from HERFD XAS measurements at 1.12 and $1.62\\mathrm{V},$ plotted as a function of Fe content. (b) Examples of unit cells for Fe-substituted $\\gamma{\\mathrm{-NiOOH}}$ and Ni-substituted γ-FeOOH model structures. (c) Theoretically predicted bond lengths, corrected by a factor of 0.97 for comparison with experimental data. The dashed lines represent experimental bond lengths from literature (see Supporting Information S12). (d) Löwdin charges in Fe-substituted $\\gamma{\\mathrm{-NiOOH}}$ and Ni-substituted $\\gamma$ -FeOOH model structures, plotted as a function of Fe content. All dashed lines are guides to the eye. \n\nTable 1. EXAFS Fit Results for Catalyst Containing $75\\%$ Ni/ 25% Fea \n\n\n
E= 1.12 VNi K-edgeFe K-edge
Ni-ONi-NiFe-OFe-Ni
CN6.5 ±0.65.5 ±0.66.5 ±0.65.9 ±0.7
distance (A)2.06 ± 0.013.10 ± 0.012.01 ± 0.013.10 ± 0.01
² (A-2)0.0050.0050.0050.007
(A-1) k-range2.0-11.72.0-11.5
r range (A)0.6-3.40.6-3.5
R factor0.050.015
Eo (eV)-1.6 ± 1.9-1.6 ±1.8
E = 1.62 VNi K-edgeFe K-edge
Ni-ONi-NiFe-OFe-Ni
CN6.1 ± 0.95.4 ±0.75.4 ± 0.95.2 ±0.7
distance (A)1.89 ± 0.022.82 ± 0.011.90 ± 0.022.84 ± 0.02
² (A-2)0.0050.0050.0050.005
k-range (A-1)2.0 to 11.72.0-11.5
r range (A)0.6-3.00.6-3.0
R factor0.0940.028
E (eV)-2.4 ±2.4-4.8 ±2.9
\n\n$\\mathrm{\\DeltaNi-Ni-Ni}$ arrangements, clearly shows that Fe is not intercalated between the hexagonal $\\left[\\mathrm{NiO}_{2}\\right]$ sheets but instead substitutes for Ni within the sheets. \n\nFurther examination of the HERFD XAS reveals important information about the oxidation states of Fe and Ni in Fesubstituted $\\alpha{\\mathrm{-Ni(OH)}}_{2}$ and $\\gamma{\\mathrm{-NiOOH}}$ . Contracted bond distances are commonly associated with an increased oxidation state, and such oxidation state increase can be clearly seen in the Ni K-edge spectra where the pre-edge centroid and the photoionization threshold both shift to significantly higher energy. In contrast, an intriguing discrepancy can be seen in the Fe K-edge spectra. Comparison of the short $\\mathrm{Fe-O}$ distance of $(1.90\\pm\\mathrm{{0.0\\bar{1}}}{},$ ) $\\mathring\\mathrm{A}$ at $1.62\\mathrm{~V~}$ with bond lengths for different Fe oxides reported in the literature (Supporting Information S12) suggests that all Fe sites should have increased their oxidation state from $+3$ to $+4$ . However, if such a significant oxidation state increase occurred at all Fe sites, we would have expected more noticeable shifts to higher energies of both the pre-edge centroid as well as the photoionization threshold. In XANES spectra of the $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{FeO}_{4}$ series,60−62 in which Fe has the formal oxidation states of $+3$ and $+4$ for the end members $x=0$ and $x=1$ , respectively, the pre-edge centroid shifts by ${\\sim}0.7\\ \\mathrm{eV}$ and the multiplet structure changes significantly from the characteristic doublet for $\\mathrm{Fe}^{3+}$ in octahedral coordination to a much more intense single peak for $\\mathrm{Fe^{4+}}$ . Main edge shifts up to $1.26~\\mathrm{eV}$ have been reported in the same series. In the present study, such changes are much less pronounced; furthermore, two additional characteristics of $\\bar{\\mathrm{Fe}}^{4+}$ in $\\mathrm{SrFeO}_{4}$ due to increased $\\mathrm{Fe-O}$ covalency, i.e., a ligand-to-metal charge transfer (LMCT) shakedown feature near the main edge and a strong decrease of the white line intensity, are not observed for Fe-containing $\\gamma{\\mathrm{-NiOOH}}$ . Subtle changes in the pre-edge region might suggest a small fraction of $\\mathrm{\\bar{F}e^{4+}}$ sites, but this cannot account for the bond contraction, which clearly affects all Fe sites and is imposed through the edge-sharing of $\\left[\\mathrm{FeO}_{6}\\right]$ and surrounding $[\\mathrm{NiO}_{6}]$ octahedra. \n\nFor all other $\\mathrm{Fe/Ni}$ ratios, average $\\mathrm{{Ni-O}}$ and Fe−O bond lengths at different potentials can be obtained by applying either the same relation $[(E_{\\mathrm{peak}}-E_{0})d^{2}=\\mathrm{const.}]$ as above, or linear combination fits using the two spectra of the $\\mathrm{Ni}/\\mathrm{Fe}$ (75:25) sample at 1.12 and $1.92\\mathrm{~V~}$ as components, which sufficiently reproduce all other spectra (Supporting Information S10). The results are shown in Figure 3a for two potentials, the resting state at $1.12\\mathrm{~V~}$ as well as OER operating conditions at $1.62~\\mathrm{V}.$ . Irrespective of the presence and concentration of Fe, the $\\mathrm{{Ni-O}}$ bond lengths correspond to $\\alpha{\\mathrm{-Ni(OH)}}_{2}$ and $\\gamma-$ NiOOH at low and high potentials, respectively. Conversely, the average $\\mathrm{Fe-O}$ bond length completely follows the $\\mathrm{{Ni-O}}$ bond contraction only at low Fe content (10 and $25\\%$ ). With increasing Fe content, the $\\mathrm{Fe-O}$ distance at $1.62\\mathrm{~V~}$ gradually increases toward that of pure $\\gamma{\\mathrm{-FeOOH}}$ . We propose that two different $\\mathrm{Fe}^{3+}$ species are present, i.e., $\\mathrm{Fe}^{3\\hat{+}}$ dopants in $\\alpha\\cdot$ - $\\mathrm{Ni(OH)}_{2}/\\gamma$ -NiOOH and $\\mathrm{Fe}^{\\bar{3}+}$ sites within a separate $\\gamma{\\mathrm{-FeOOH}}$ phase. While a single $\\mathrm{Ni}/\\mathrm{Fe}$ phase exists at low Fe content, FeOOH increasingly contributes to the Fe K-edge spectra with increasing overall Fe content, due to limited solubility of $\\mathrm{Fe}^{3+}$ in $\\alpha{\\mathrm{-}}\\mathrm{Ni}(\\mathrm{OH})_{2}$ . A more recent study of Fe uptake into $\\mathrm{\\Ni(OH)}_{2}$ from Fe-containing KOH solution indicates such a solubility limit near 25% Fe.63 \n\nSince we do not observe $\\mathrm{{Ni-O}}$ bond expansion even at $75\\%$ Fe content, we estimate based on experimental uncertainty in the $\\mathrm{{Ni-O}}$ bond distance, that Ni doping into $\\gamma{\\mathrm{-FeOOH}},$ , if any, does not exceed $3\\%$ . The proposed interpretation is illustrated schematically in Figure 1 (top). The different solubility limits for Fe in $\\mathrm{Ni(OH)_{2}/N i O O H}$ and Ni in FeOOH could be attributed to differences in the capability of the host structures to compensate the charge difference between $\\mathrm{Ni}^{2+}$ and $\\mathrm{Fe}^{3+}$ that are present at low potential and, presumably, during catalyst electrodeposition. The $\\alpha{\\mathrm{-Ni(OH)}}_{2}$ structure contains intercalated $_\\mathrm{H}_{2}\\mathrm{O}$ between the hexagonal $\\left[\\mathrm{NiO}_{2}\\right]$ sheets, and can accommodate electrolyte anions (e.g., $S O_{4}^{2-}\\big)$ . In the resulting charge-neutral $\\mathrm{Ni(II)_{1-\\itx}F e(I I I)_{\\it x}(O H)_{2}(S O_{4})_{\\it x/2}(H_{2}O)_{\\it y}}$ layered double hydroxide structure,31 Fe uptake will be enabled by closely matching $\\mathrm{Fe}^{3+}{-}\\mathrm{O}$ and $\\mathrm{Ni^{2+}{-}\\bar{O}}$ distances but limited by steric hindrance and repulsion between partially hydrated anions. Conversely, there is no obvious pathway for the $\\gamma-$ FeOOH structure to allow intercalation of cations $(\\mathrm{e.g.,K^{\\prime}})$ or protonation of $\\mathrm{~o~}$ or OH ligands without a significant distortion of linkages between $\\mathrm{\\Delta}[\\mathrm{MO}_{6}]$ octahedra. Correspondingly, the absence of intercalation in $\\beta{\\mathrm{-Ni}}(\\mathrm{OH})_{2}$ could explain why the presence of $\\mathrm{Fe}^{3+}$ appears to prevent the transformation $\\bar{(}^{\\alpha}\\mathrm{aging^{\\prime\\prime}})$ of $\\alpha{\\mathrm{-}}\\mathrm{Ni}(\\mathrm{OH})_{2}$ into $\\beta{\\mathrm{-Ni}}(\\mathrm{OH})_{2}$ .21 \n\n$\\mathrm{\\DeltaDFT+U}$ calculations were carried out in order to further understand the effects of Fe substitution into $\\gamma$ -NiOOH and Ni substitution into γ-FeOOH (see Supporting Information $\\$3-$ S5 for details). The model structures shown in Figure 3b capture the known oxidation states and local binding environment of metal sites but neglect the role of intercalated species that have not been well characterized experimentally (Supporting Information S3). The $\\tt D F T+U$ method offers an improved description of correlated transition metal oxides over commonly used DFT at minimal additional cost,64,65 which makes this approach optimal for materials screening and optimization; however some deficiencies of DFT remain.66 A comparison of theoretically predicted metal−oxygen bond lengths (Figure 3c and Supporting Information S4) with the experimental values from our measurements (Figure 3a) and literature (Supporting Information S12) supports our hypothesis that only Fe-doped $\\gamma$ -NiOOH and pure FeOOH, but very little, if any, Ni-doped γ-FeOOH, exist under OER conditions. \n\nLöwdin charges of Ni, Fe, O, and H relative to the free atoms were obtained from the $\\mathrm{\\DeltaDFT+U}$ results in order to provide a measure of the apparent oxidation states of these elements. Figure 3d shows that the Löwdin charges for both Fe and Ni remain approximately constant for all model structures investigated. This finding agrees with our experimental observation that Fe and Ni oxidation states under OER conditions are $+3$ and $+3.6$ (average), respectively, independent of the ${\\mathrm{Ni}}/{\\mathrm{Fe}}$ ratio. We also note that the Löwdin charge for Fe is significantly higher than for Ni despite the opposite order of formal oxidation states of both cations. This difference reflects the nature of the metal−oxygen bonds, which are more ionic and less covalent for Fe than for Ni. Likewise, the linear increase in negative charge on the $\\mathrm{~o~}$ atoms with increasing Fe content is attributable to the replacement of the more covalent $\\mathrm{{Ni-O}}$ bonds with the more ionic $\\mathrm{Fe-O}$ bonds. \n\nIn summary, our operando HERFD-XAS data demonstrate that for Fe contents lower than ${\\sim}25\\%$ , $\\mathrm{Fe}^{3+}$ cations substitute for $\\mathrm{Ni}^{3+}$ cations into the lattice of $\\gamma$ -NiOOH. This modification has no effect on the oxidation state of the Ni cations. We observe, however, that the $\\mathrm{Fe-O}$ bond distance in $\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH}$ is $6\\%$ shorter than that found in $\\gamma{\\mathrm{-FeOOH}},$ and, for small Fe content up to $25\\%$ , is almost identical to that of $\\mathrm{{Ni-O}}$ . With increasing Fe content the $\\mathrm{{Ni-O}}$ bond distance remains nearly constant, whereas the average $\\mathrm{Fe-O}$ bond distance increases steadily, becoming comparable to that for $\\gamma-$ \n\nFeOOH at Fe contents above $75\\%$ . $\\tt D F T+U$ calculations confirm that a $\\mathrm{Fe-O}$ bond distance similar to that for $\\mathrm{{Ni-O}}$ should be observed when $\\mathrm{Fe}^{3+}$ cations substitute for $\\mathrm{Ni}^{3+}$ cations in $\\gamma{\\mathrm{-Ni}_{1-x}}\\mathrm{Fe}_{x}\\mathrm{OOH}$ . The absence of any experimental evidence for $\\mathrm{{Ni-O}}$ bond expansion in materials prepared with Fe contents above $50\\%$ suggests that for Fe contents in excess of ${\\sim}25\\%$ , a γ-FeOOH phase is nucleated that does not contain a large amount of Ni in it. \n\nWe note that our conclusions concerning the oxidation state of Fe and the $\\mathrm{Fe-O}$ bond distance for Fe cations present in Fesubstituted $\\gamma$ -NiOOH differ from those reported earlier.30,32 Previous XANES and EXAFS studies of Fe-doped NiOOH yielded contradictory results regarding the local structure and oxidation state of Fe. Kim et al. reported that Fe in $\\gamma$ -NiOOH remains as $\\mathrm{Fe}^{3+}$ ;30 the Fe−O bond length was found to be 1.92 $\\mathring\\mathrm{A}$ independent of applied potential and was stated to be “essentially identical” to that in $\\beta{\\mathrm{-FeOOH}}$ and $\\gamma{\\mathrm{-FeOOH}},$ although both sources cited for this value actually reported average bond lengths of 2.05 and $2.03\\mathrm{~\\AA},$ respectively.67,68 By contrast, Balasubramanian et al. reported oxidation of $\\mathrm{Fe}^{3+}$ to $\\mathrm{Fe}^{4+}$ and an $\\mathrm{Fe-O}$ distance of $1.94{\\hat{\\mathrm{A}}}^{32}$ We suggest that in both refs 30 and 32, Ni oxidation could have been incomplete, since measurements under OER conditions were not carried out. We note further that HERFD XAS measurements and supporting $\\tt D F T+U$ calculations rule out the formation of significant concentrations of $\\mathrm{Fe^{4+}}$ cations in Fe-doped $\\gamma{\\mathrm{-NiOOH}}$ . It is important to note that energy shifts of the $1s\\rightarrow4p$ resonance, reported by Balasubramanian et al. as an indication for $\\mathrm{Fe}^{4+}$ formation, can arise not only from oxidation state changes, which shift the 1s core level, but also energy shifts in the $4p$ unoccupied pDOS due to altered bond lengths. In the present case, the energy shift of ${\\sim}1\\ \\mathrm{eV}$ can be explained with the Fe−O bond contraction alone and is too small to account for an additional core level shift, as shown in our more detailed analysis given in Figure S5. \n\nOur interpretation of the changes in the structure of $\\gamma-$ $\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH}$ with increasing Fe content suggests that the observed changes in OER activity shown in Figure 1 can be explained in the following manner. Addition of Fe to $\\gamma$ -NiOOH initially increases the OER activity to due to the substitution of $\\mathrm{Fe}^{3+}$ cations in the framework of $\\gamma{\\mathrm{-NiOOH}}$ . A plateau in activity is reached at ${\\sim}25\\%$ Fe content, beyond which further increases in the catalyst content of Fe results in the growth of catalytically inactive $\\gamma{\\mathrm{-FeOOH}},$ , with the net effect that the catalyst activity declines as the fraction of the less active to the more active catalyst increases. \n\nNot addressed to this point, though, is why the substitution of $\\mathrm{Fe}^{3+}$ into the lattice of $\\gamma{\\mathrm{-NiOOH}}$ increases the OER activity of the catalyst. Two options exist: one is that the substituted $\\mathrm{Fe}^{3+}$ sites become more active when hosted in the lattice of $\\gamma-$ NiOOH due to a change in their electronic environment, and the other is that the activity of $\\mathrm{Ni}^{3+}$ sites increases as a consequence of their electronic properties being altered by the substitution of $\\mathrm{Fe}^{3+}$ cations into the $\\gamma{\\mathrm{-NiOOH}}$ lattice. Another question to ask is whether the small amount of $\\mathrm{Ni}^{3+}$ that can substitute into $\\gamma{\\mathrm{-FeOOH}}$ has an effect on the OER activity of this phase, and if so how so. As we will next show, both sets of questions can be addressed by $\\tt D F T+U$ calculations of the overpotential for the OER. This will be done using standard procedures, which have been demonstrated to give solid basis for interpreting the relationship between catalyst composition and OER overpotential.28,69−71 \n\nIn acidic conditions, the OER is taken to occur via four elementary steps: \n\n$$\n\\begin{array}{r l}&{\\mathrm{H}_{2}\\mathrm{O}+^{\\ast}\\rightarrow\\mathrm{OH}^{\\ast}+\\mathrm{e}^{-}+\\mathrm{H}^{+}}\\\\ &{\\mathrm{OH}^{\\ast}\\rightarrow\\mathrm{O}^{\\ast}+\\mathrm{e}^{-}+\\mathrm{H}^{+}}\\\\ &{\\mathrm{O}^{\\ast}+\\mathrm{H}_{2}\\mathrm{O}\\rightarrow\\mathrm{OOH}^{\\ast}+\\mathrm{e}^{-}+\\mathrm{H}^{+}}\\\\ &{\\mathrm{OOH}^{\\ast}\\rightarrow\\mathrm{O}_{2}+\\mathrm{e}^{-}+\\mathrm{H}^{+}}\\end{array}\n$$ \n\nwith $*$ indicating an oxygen vacancy site at the surface. The computational hydrogen electrode69 was used to express the chemical potentials of protons and electrons at any given $\\mathrm{\\tt{pH}}$ and applied potential $U.$ . As a result, the theoretical overpotential $\\eta$ obtained from Gibbs free energy differences $\\Delta G_{i}$ (i $=1,...,4,$ ) at each step as \n\n$$\n\\eta=\\operatorname*{max}[\\Delta G_{1},\\Delta G_{2},\\Delta G_{3},\\Delta G_{4}]/e-1.23[\\mathrm{V}]\n$$ \n\nis independent of $\\mathrm{\\ttpH}$ and is therefore applicable to alkaline conditions. Further details of the computational methodology are given in the Supporting Information S5. \n\nFigure 4 compares predicted overpotentials for the OER occurring at Ni and Fe surface sites in pure and doped $\\gamma-$ NiOOH and γ-FeOOH. The choice of surface terminations for γ-NiOOH was influenced by previous works for structurally similar $\\mathrm{CoOOH},^{72}$ were it was found that the natural (0001) facet leads to low OER activity, while higher index surfaces such as (011̅2) or (011̅4), which contain under-coordinated metal sites similar to step or edge have more active sites. The results can be rationalized in terms of the overall affinity of surface sites for adsorbed intermediates and the relative stability of ${\\boldsymbol{\\mathrm{O}}}^{*}$ with respect to $\\mathrm{OH^{*}}$ and $\\scriptstyle{\\mathrm{OOH^{*}}}$ . Generally much weaker adsorption is found for the on-top position of a single 5-fold coordinated metal atom than for the bridge site between two 5- fold coordinated metal atoms, and Fe sites have significantly higher OH affinity than Ni sites. While the difference between adsorption energies of ${\\mathrm{OH}}^{*}$ and ${\\mathrm{OOH^{*}}}$ is nearly constant, $\\Delta E_{\\mathrm{OOH}}=0.8\\Delta E_{\\mathrm{OH}}+3.3~\\mathrm{eV},$ the $\\boldsymbol{\\mathrm{O^{*}}}$ binding energy increases as a function of $\\Delta E_{\\mathrm{OH}}$ (see Figure S14). Under the optimum condition $\\Delta E_{\\mathrm{O}}-\\Delta E_{\\mathrm{OH}}=0.5\\big(\\mathrm{\\'Delta}E_{\\mathrm{OOH}}-\\Delta E_{\\mathrm{OH}}\\big),^{71}\\eta$ reaches a minimum value of $0.4~\\mathrm{V}$ . In the absence of doping, all OER intermediates adsorb too strongly on pure $\\gamma{\\mathrm{-FeOOH}}$ and too weakly on pure $\\gamma{\\mathrm{-NiOOH}}$ . The calculated overpotentials for Fe-free $\\gamma{\\mathrm{-NiOOH}}$ are larger than that for pure γ-FeOOH, in very good agreement with the results presented in Figure 1. \n\nCompared to pure $\\gamma{\\mathrm{-FeOOH}}$ , Fe sites surrounded by Ni next-nearest neighbors in either $\\gamma{\\mathrm{-NiOOH}}$ or γ-FeOOH host structures exhibit decreased affinity for OER intermediates, resulting in a shift in their binding energies toward optimal values. The origin of these trends can be rationalized based on the results in Figure 3d, which show that $\\mathrm{Ni}^{3+/4+}$ cations, due to their higher electron affinity compared to $\\mathrm{Fe}^{3+}$ , withdraw electron density from oxygen sites. During OER, the formation of $\\mathrm{HO^{*}}$ and ${{\\mathrm{O}}^{*}}$ requires an oxidation state increase at the active Fe site, which becomes evident, for example, in the notably short bond distance of $1.62\\mathring{\\mathrm{A}}$ between ${{\\mathrm{O}}^{*}}$ and a highly charged Fe site in Fe-doped $\\gamma{\\mathrm{-NiOOH}}(01{\\overline{{1}}}2)$ (Figure 4a). The oxidation of the Fe surface site will be less favorable energetically in γ-NiOOH than in $\\gamma{\\mathrm{-FeOOH}}$ , because neighboring Ni sites induce lower negative charge density on adsorbed O and OH. We propose that this effect is mostly determined by the local arrangement of neighboring Fe and Ni sites. Computational results for structurally similar Ni-doped hematite indicate the same mechanism for the catalytic enhancement, further supporting our hypothesis.28 \n\n![](images/86b0ab6a78c422f4eafa5cb665b8dcbe6b730010894df078aeaeb2cd77cdbb97.jpg) \nFigure 4. Theoretical OER overpotentials at Ni and Fe surface sites in pure and doped $\\gamma{\\mathrm{-NiOOH}}$ and $\\gamma{\\mathrm{-FeOOH}}$ model structures. (a) Proposed OER pathway with intermediates $\\mathrm{HO^{*}}$ , $\\boldsymbol{\\mathrm{O^{*}}}$ and $\\mathrm{HOO^{*}}$ , illustrated using the example of the on-top site at a substituted Fe surface atom in $\\gamma{\\mathrm{-NiOO}}\\bar{\\mathrm{H}}(01\\bar{1}2)$ . The binding energies of these species are used to estimate the OER overpotential. (b) OER activity volcano showing the overpotential as a function of Gibbs free energies of the reaction intermediates. Computed overpotentials are shown for the OER at $\\mathrm{{Ni-Ni}}$ bridge and Fe on-top sites located in pure $\\gamma-$ NiOOH(011̅2) and in $\\gamma{\\mathrm{-NiOOH}}(01{\\overline{{1}}}{\\bar{2}})$ with Fe surface and subsurface doping, at a Ni on-top site in pure $\\gamma\\mathrm{-NiOOH}(01\\overline{{1}}2)$ , and at Fe−Fe bridge sites in pure and Ni-doped $\\gamma{\\mathrm{-FeOOH}}(010)$ ( $25\\%$ Ni in bulk unit cell). All corresponding model structures are shown with the intermediate whose formation is the potential limiting step (PLS) $\\mathrm{\\tilde{HOO^{*}}}$ in all cases except for the on-top Ni site in $\\gamma{\\mathrm{-NiOOH}}(01{\\overline{{1}}}2)$ and $\\gamma{\\mathrm{-NiOOH}}(01{\\overline{{1}}}2)$ with subsurface Fe, where formation of ${{\\mathrm{O}}^{*}}$ determines the overpotential). \n\nFurther calculations comparing the overpotentials for the OER occurring over Ni or Fe sites confirm that Fe rather than Ni constitutes the active site for the OER at mixed $\\mathrm{Fe-Ni}$ oxyhydroxides. Subsurface Fe sites in $\\gamma{\\mathrm{-NiOOH}}$ (Figure 4b) increase the OER overpotential at Ni surface sites because the already too weak oxygen affinity of Ni further decreases. This finding is consistent with the experimentally observed shift of the $\\alpha{\\mathrm{-Ni}}(\\mathrm{OH})_{2}/\\gamma{\\mathrm{-NiOOH}}$ redox potential to higher values with increasing Fe content.23 \n\nIt is important at this stage to compare and contrast our theoretical results with those of Li and Selloni,26 who report $\\tt D F T+U$ calculations of the OER overpotentials for $\\beta\\mathrm{.}$ and $\\gamma-$ NiOOH and for Fe substituted into the surface of both NiOOH phases. While there are substantial differences in the catalyst structure, the sequence of steps leading to the oxidation of water, and the computational approach used in this study and the present one, both studies agree that the OER overpotential for Fe-doped $\\gamma{\\mathrm{-NiOOH}}$ is lower than that for pure γ-NiOOH. Thus, Li and Selloni find that $\\eta=0.48\\mathrm{~V~}$ for Fe-doped $\\gamma$ -NiOOH and $\\eta\\ =\\ 0.52\\mathrm{~V~}$ for pure $\\gamma{\\mathrm{-NiOOH}}$ , whereas we find that $\\eta=0.43\\:\\mathrm{V}$ for Fe-doped $\\gamma{\\mathrm{-NiOOH}}$ and $\\eta$ $=0.56\\mathrm{V}$ for pure $\\gamma{\\mathrm{-NiOOH}}$ . Li and Selloni also predict that an even lower overpotential for the OER can be achieved on Fedoped $\\beta{\\mathrm{-NiOOH}}$ $(\\eta=0.26\\:\\mathrm{V})$ and that the overpotential for pure $\\beta$ -NiOOH should be lower than that for $\\gamma$ -NiOOH $(\\eta=$ 0.46 for $\\beta$ -NiOOH versus $\\eta=0.52$ for $\\gamma{\\mathrm{-NiOOH}},$ . While we note that these are interesting findings, we did not observe any evidence for the $\\beta$ phase of NiOOH in our experiments, and recent work by Trotochaud et al. indicates that the presence of Fe in the active phase of Ni−Fe oxides inhibits the formation of this phase.21 \n\nIt is significant to note that the conclusions regarding the influence of Fe on the overpotential for the OER deduced from the present work differ from those that would have been made in the absence of this effort. Prior to this study and based on the observation that addition of Fe to NiOOH results in an increase of the redox potential for the equilibrium between $\\alpha\\cdot$ - $\\mathrm{\\Ni(OH)}_{2}$ and $\\gamma{\\mathrm{-NiOOH}},$ we had speculated that the altered relative stability of $\\mathrm{Ni}^{2+}$ , $\\mathrm{Ni}^{3+}$ and $\\mathrm{Ni^{4+}}$ sites could be the dominant factor affecting the activation barriers for the OER. This reasoning was based on the assumption that an OERactive metal site would undergo oxidation state changes during the elementary steps of the OER. Furthermore, measurements of the charge required to reduce $\\mathrm{Fe-Ni}$ OER catalysts from their operating state to $\\alpha{\\mathrm{-Ni(OH)}}_{2}$ seemed to indicate a lower average Ni oxidation state in Fe-doped NiOOH compared to pure NiOOH.23 On the basis of these observations, “chemical intuition” suggested that the most active site in (Fe,Ni)OOH would be a Ni cation. In contrast to previous coulometric analysis,23 our XAS results indicate that under OER conditions Ni sites have the same average oxidation state, independent of Fe content. This finding does not contradict the anodic shift of the $\\alpha{\\mathrm{-Ni}}(\\mathrm{OH})_{2}/\\gamma$ -NiOOH redox potential but merely indicates that the redox potential, although it increases, does not exceed the onset potential for the OER. What we must conclude, therefore, is that the local electronic structure of Ni cations in Fe-doped NiOOH during OER cannot be distinguished by XAS from that in pure NiOOH. Nevertheless, XAS does reveal a strong influence of the Ni host structure on the local structure at Fe cations. \n\nWhile it might still be argued that XAS only captures bulkaveraged electronic structure information and therefore may not be representative of minority Ni species at the surface, the $\\tt D F T+U$ results reveal unambiguously how the reactivity of surface Ni and Fe sites is altered. We conclude that “chemical intuition” was actually correct insofar as Ni surface sites were assumed to bind OER intermediates more weakly in $\\gamma-$ $\\mathrm{Fe}_{x}\\mathrm{Ni}_{1-x}\\mathrm{OOH}$ than in $\\gamma{\\mathrm{-NiOOH}};$ ; however, the calculation also reveal that the resulting adsorption at Ni surface sites is much weaker than what is required for an “optimal” catalyst and therefore cannot account for the significant reduction in the OER overpotential observed experimentally. By contrast, nearly optimal adsorption energies are achieved at Fe sites in $\\mathrm{Fe}_{x}\\mathrm{Ni}_{1-x}\\mathrm{OOH}$ . \n\n# CONCLUSIONS \n\nIn situ HERFD XAS data were acquired in order to establish the local electronic environment of $\\mathrm{\\DeltaNi}$ and Fe cations in Fedoped $\\mathrm{NiO}_{x}$ catalysts used for the OER. Changes in the oxidation and metal-to-oxygen bond distance were observed with increasing applied potential. At potentials well below the onset of the OER, the Ni is present as $\\alpha{\\mathrm{-Ni(OH)}}_{2}$ in the absence of Fe, and as $\\mathrm{Ni(II)_{1-x}\\mathrm{\\bar{F}e(I I I)_{\\it x}(O H)_{2}(S O_{4})_{\\it x/2}(H_{2}O)_{\\it y},}}$ a layered double hydroxide structure, in the presence of Fe. While Ni is present in the double hydroxide as $\\mathrm{Ni}^{2+}$ , Fe is present as $\\mathrm{Fe}^{\\hat{3}+}$ , in both cases independent of the amount of Fe added. As the potential is raised, but still below that for the onset of the OER, the Ni cations undergo oxidation to $\\mathrm{Ni}^{3+}$ ; however, the Fe cations remain as $\\mathrm{Fe}^{3+}$ . For Fe levels below about $25\\%$ , the oxidized catalyst can be described as $\\gamma-$ $\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH},$ reflecting the substitution of Ni by Fe cations. What is notable in this material is that the $\\mathrm{{Ni-O}}$ and $\\mathrm{Fe-O}$ bond distances are very similar and both are comparable to the $\\mathrm{{Ni-O}}$ bond distance in $\\gamma{\\mathrm{-NiOOH}}$ . It is also notable that the Fe−O bond distance is ${\\sim}6\\%$ shorter than that in γ-FeOOH. As the Fe level rises above $25\\%$ , the XAS data suggest that a γ- FeOOH phase nucleates, which contains either no or $<3\\%$ Ni. The conclusions drawn about the effects of Fe on the composition and structure of the oxidized catalyst are supported by DFT $+\\boldsymbol{\\mathrm{U}}$ calculations. Insights into the cause for the rapid increase in OER activity of $\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{x}\\mathrm{OOH}$ with increasing Fe content can also be obtained from $\\tt D F T+U$ calculations of the OER overpotential. What is found is that $\\mathrm{Fe}^{3+}$ cations in $\\gamma{\\mathrm{-Ni}_{1-x}}\\mathrm{Fe}_{x}\\mathrm{OOH}$ exhibit a significantly lower overpotential than do $\\mathrm{Ni}^{3+}$ cations in either $\\gamma{\\mathrm{-Ni}_{1-x}}\\mathrm{Fe}_{x}\\mathrm{OOH}$ or γ-NiOOH. Such calculations and those by others28 also reveal that, in addition to $\\gamma{\\mathrm{-Ni}_{1-x}}\\mathrm{Fe}_{x}\\mathrm{OOH},$ , a variety of other materials with edge-sharing $\\left[\\mathrm{FeO}_{6}\\right]$ and $\\left[\\mathrm{NiO}_{6}\\right]$ octahedra, such as Nidoped $\\gamma{\\mathrm{-FeOOH}}$ and Ni-doped hematite28 are predicted to have superior OER activity at Fe sites. \n\n# ASSOCIATED CONTENT \n\n# $\\bullet$ Supporting Information \n\nCatalyst preparation, additional EXAFS measurements on electrodeposited catalyst layers, choice of model $(\\mathrm{Ni,Fe})\\mathrm{OOH}$ structures for $\\mathrm{DFT+U}$ , optimized bulk structures and their density of states, calculation of OER overpotentials, OER activity measurements, purification of KOH electrolyte, complete set of operando HERFD XAS measurements, HERFD XAS of Fe and Ni reference compounds, linear combination fitting of operando HERFD XAS, bond contraction from HERFD XAS, comparison of structure information from HERFD XAS and EXAFS. This material is available free of charge via the Internet at http://pubs.acs.org. \n\n# AUTHOR INFORMATION \n\nCorresponding Authors \ndfriebel@slac.stanford.edu \nalexbell@berkeley.edu \nAuthor Contributions \n¶D.F., M.W.L., and M.B. contributed equally. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis material is based upon work performed by the Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award Number DE-SC0004993. This research was partly carried out at the Stanford Synchrotron Radiation Lightsource, a National User Facility operated by Stanford University on behalf of the U.S. Department of Energy, Office of Basic Energy Sciences. We thank Lena Trotochaud, Harri Ali-Löytti and Lin Li for their assistance with data collection. We are grateful to Uwe Bergmann, Thomas Bligaard, Aleksandra Vojvodic and Lena Trotochaud for helpful discussions. We thank Tyler Matthews for assistance with sample preparation. M.W.L. was partially supported by the University of California President’s Postdoctoral Fellowship. K.E.S. gratefully acknowledges the Ernest-Solvay-Stiftung for financial support. This research employed NERSC computational resources under DOE Contract No. DE-AC02-05CH11231. \n\n# REFERENCES \n\n(1) Walter, M. G.; Warren, E. L.; McKone, J. R.; Boettcher, S. W.; Mi, $\\mathrm{Q.;}$ Santori, E. A.; Lewis, N. S. Chem. Rev. 2010, 110, 6446. \n(2) Trasatti, S. Electrochim. Acta 1984, 29, 1503. \n(3) Lee, S. W.; Carlton, C.; Risch, M.; Surendranath, Y.; Chen, S.; \nFurutsuki, S.; Yamada, A.; Nocera, D. G.; Shao-Horn, Y. J. Am. Chem. \nSoc. 2012, 134, 16959. \n(4) Risch, $\\mathbf{M}.;$ Grimaud, A.; May, K. J.; Stoerzinger, K. A.; Chen, T. J.; \nMansour, A. N.; Shao-Horn, Y. J. Phys. Chem. C 2013, 117, 8628. \n(5) Suntivich, J.; May, K. J.; Gasteiger, H. A.; Goodenough, J. B.; \nShao-Horn, Y. Science 2011, 334, 1383. \n(6) Subbaraman, R.; Tripkovic, D.; Chang, K.-C.; Strmcnik, D.; \nPaulikas, A. P.; Hirunsit, P.; Chan, M.; Greeley, J.; Stamenkovic, V.; \nMarkovic, N. M. Nat. Mater. 2012, 11, 550. \n(7) McCrory, C. C. L.; Jung, S.; Peters, J. C.; Jaramillo, T. F. J. Am. \nChem. Soc. 2013, 135, 16977. \n(8) Kanan, M. W.; Nocera, D. G. Science 2008, 321, 1072. \n(9) Bediako, D. K.; Lassalle-Kaiser, B.; Surendranath, Y.; Yano, J.; \nYachandra, V. K.; Nocera, D. G. J. Am. Chem. Soc. 2012, 134, 6801. \n(10) Khaselev, O.; Turner, J. A. Science 1998, 280, 425. \n(11) Jin, J.; Walczak, K.; Singh, M. R.; Karp, C.; Lewis, N. S.; Xiang, C. Energy Environ. Sci. 2014, 7, 3371. \n(12) Hu, S.; Xiang, C.; Haussener, S.; Berger, A. D.; Lewis, N. S. \nEnergy Environ. Sci. 2013, 6, 2984. \n(13) Gregoire, J. M.; Xiang, C.; Mitrovic, S.; Liu, X.; Marcin, M.; \nCornell, E. W.; Fan, J.; Jin, J. J. Electrochem. Soc. 2013, 160, F337. \n(14) Trotochaud, L.; Mills, T. J.; Boettcher, S. W. J. Phys. Chem. Lett. \n2013, 4, 931. \n(15) Młynarek, G.; Paszkiewicz, M.; Radniecka, A. J. Appl. \nElectrochem. 1984, 14, 145. \n(16) Corrigan, D. A. J. Electrochem. Soc. 1987, 134, 377. \n(17) Miller, E. L.; Rocheleau, R. E. J. Electrochem. Soc. 1997, 144, 3072. \n(18) Li, X.; Walsh, F. C.; Pletcher, D. Phys. Chem. Chem. Phys. 2010, 13, 1162. \n(19) Landon, J.; Demeter, E.; İnoğlu, N.; Keturakis, C.; Wachs, I. E.; \nVasić, R.; Frenkel, A. I.; Kitchin, J. R. ACS Catal. 2012, 2, 1793. \n(20) Trotochaud, L.; Ranney, J. K.; Williams, K. N.; Boettcher, S. W. \nJ. Am. Chem. Soc. 2012, 134, 17253. \n(21) Trotochaud, L.; Young, S. L.; Ranney, J. K.; Boettcher, S. W. J. \nAm. Chem. Soc. 2014, 136, 6744. \n(22) Gong, M.; Li, Y.; Wang, H.; Liang, Y.; Wu, J. Z.; Zhou, J.; Wang, J.; Regier, T.; Wei, F.; Dai, H. J. Am. Chem. Soc. 2013, 135, 8452. (23) Louie, M. W.; Bell, A. T. J. Am. Chem. Soc. 2013, 135, 12329. (24) Smith, R. D. L.; Prévot, M. S.; Fagan, R. D.; Trudel, S.; \nBerlinguette, C. P. J. Am. Chem. Soc. 2013, 135, 11580. (25) Smith, R. D. L.; Prévot, M. S.; Fagan, R. D.; Zhang, Z.; Sedach, \nP. A.; Siu, M. K. J.; Trudel, S.; Berlinguette, C. P. Science 2013, 340, 60. (26) Li, Y.-F.; Selloni, A. ACS Catal. 2014, 1148. (27) Gao, M.; Sheng, W.; Zhuang, Z.; Fang, Q.; Gu, S.; Jiang, J.; Yan, \nY. J. Am. Chem. Soc. 2014, 136, 7077. (28) Liao, P.; Keith, J. A.; Carter, E. A. J. Am. Chem. Soc. 2012, 134, \n13296. (29) Corrigan, D. A.; Conell, R. S.; Fierro, C. A.; Scherson, D. A. J. \nPhys. Chem. 1987, 91, 5009. (30) Kim, S.; Tryk, D. A.; Antonio, M. R.; Carr, R.; Scherson, D. J. \nPhys. Chem. 1994, 98, 10269. (31) Guerlou-Demourgues, L.; Fournès, L.; Delmas, C. J. Electrochem. \nSoc. 1996, 143, 3083. (32) Balasubramanian, M.; Melendres, C. A.; Mini, S. J. Phys. Chem. B \n2000, 104, 4300. (33) Eisenberger, P.; Platzman, P. M.; Winick, H. Phys. Rev. Lett. \n1976, 36, 623. (34) Hämäläinen, K.; Siddons, D. P.; Hastings, J. B.; Berman, L. E. \nPhys. Rev. Lett. 1991, 67, 2850. (35) Heijboer, W. M.; Glatzel, P.; Sawant, K. R.; Lobo, R. F.; \nBergmann, U.; Barrea, R. A.; Koningsberger, D. C.; Weckhuysen, B. \nM.; de Groot, F. M. F. J. Phys. Chem. B 2004, 108, 10002. (36) Friebel, D.; Bajdich, M.; Yeo, B. S.; Louie, M. W.; Miller, D. J.; \nCasalongue, H. S.; Mbuga, F.; Weng, T.-C.; Nordlund, D.; Sokaras, D.; \nAlonso-Mori, R.; Bell, A. T.; Nilsson, A. Phys. Chem. Chem. Phys. 2013, \n15, 17460. \n(37) Sokaras, D.; Weng, T.-C.; Nordlund, D.; Alonso-Mori, R.; \nVelikov, P.; Wenger, D.; Garachtchenko, A.; George, M.; Borzenets, \nV.; Johnson, B.; Rabedeau, T.; Bergmann, U. Rev. Sci. Instrum. 2013, \n84, 053102. (38) Webb, S. M. Phys. Scr. 2005, T115, 1011. (39) Newville, M. J. Synchrotron Radiat. 2001, 8, 322. (40) Ravel, B.; Newville, M. J. Synchrotron Radiat. 2005, 12, 537. (41) Zabinsky, S. I.; Rehr, J. J.; Ankudinov, A.; Albers, R. C.; Eller, M. \nJ. Phys. Rev. B: Condens. Matter Mater. Phys. 1995, 52, 2995. (42) Christensen, H.; Christensen, A. Acta Chem. Scand., Ser. A 1978, \n32, 87. (43) Bartl, H.; Bode, H.; Sterr, G.; Witte, J. Electrochim. Acta 1971, \n16, 615. (44) Anisimov, V. I.; Aryasetiawan, F.; Lichtenstein, A. I. J. Phys.: \nCondens. Matter 1997, 9, 767. (45) Anisimov, V. I.; Zaanen, J.; Andersen, O. K. Phys. Rev. B: \nCondens. Matter Mater. Phys. 1991, 44, 943. (46) Bacq, O. L.; Pasturel, A.; Bengone, O. Phys. Rev. B: Condens. \nMatter Mater. Phys. 2004, 69, 245107. (47) Hammer, B.; Hansen, L. B.; Nørskov, J. K. Phys. Rev. B: Condens. \nMatter Mater. Phys. 1999, 59, 7413. \n(48) Dudarev, S. L.; Botton, G. A.; Savrasov, S. Y.; Humphreys, C. J.; \nSutton, A. P. Phys. Rev. B: Condens. Matter Mater. Phys. 1998, 57, 1505. (49) Cococcioni, M.; de Gironcoli, S. Phys. Rev. B: Condens. Matter \nMater. Phys. 2005, 71, 035105. \n(50) Vanderbilt, D. Phys. Rev. B: Condens. Matter Mater. Phys. 1990, \n41, 7892. (51) Giannozzi, P.; Baroni, S.; Bonini, N.; Calandra, M.; Car, R.; \nCavazzoni, C.; Ceresoli, D.; Chiarotti, G. L.; Cococcioni, M.; Dabo, I.; \nDal Corso, A.; de Gironcoli, S.; Fabris, S.; Fratesi, G.; Gebauer, R.; \nGerstmann, U.; Gougoussis, C.; Kokalj, A.; Lazzeri, M.; Martin-Samos, \nL.; Marzari, N.; Mauri, F.; Mazzarello, R.; Paolini, S.; Pasquarello, A.; \nPaulatto, L.; Sbraccia, C.; Scandolo, S.; Sclauzero, G.; Seitsonen, A. P.; \nSmogunov, A.; Umari, P.; Wentzcovitch, R. M. J. Phys.: Condens. \nMatter 2009, 21, 395502. (52) Westre, T. E.; Kennepohl, P.; DeWitt, J. G.; Hedman, B.; \nHodgson, K. O.; Solomon, E. I. J. Am. Chem. Soc. 1997, 119, 6297. (53) Capehart, T. W.; Corrigan, D. A.; Conell, R. S.; Pandya, K. I.; \nHoffman, R. W. Appl. Phys. Lett. 1991, 58, 865. (54) Mansour, A. N.; Melendres, C. A. Phys. B 1995, 208−209, 583. \n\n(55) Hu, Y.; Bae, I. T.; Mo, Y.; Scherson, D. A.; Antonio, M. R. Can. J. Chem. 1997, 75, 1721. (56) Morishita, M.; Ochiai, S.; Kakeya, T.; Ozaki, T.; Kawabe, Y.; Watada, M.; Tanase, S.; Sakai, T. Electrochemistry 2008, 76, 802. (57) Yang, X.; Takada, K.; Itose, M.; Ebina, Y.; Ma, R.; Fukuda, K.; Sasaki, T. Chem. Mater. 2008, 20, 479. (58) Bianconi, A.; Garcia, J.; Benfatto, M. In Synchrotron Radiation in Chemistry and Biology I; Topics in Current Chemistry; Springer: Berlin, 1988; pp 29−67. (59) Stöhr, J.; Sette, F.; Johnson, A. L. Phys. Rev. Lett. 1984, 53, 1684. (60) Haas, O.; Vogt, U. F.; Soltmann, C.; Braun, A.; Yoon, W.-S.; Yang, X. $\\mathrm{Q.;}$ Graule, T. Mater. Res. Bull. 2009, 44, 1397. (61) Haas, O.; Ludwig, C.; Bergmann, U.; Singh, R. N.; Braun, A.; Graule, T. J. Solid State Chem. 2011, 184, 3163. (62) Blasco, J.; Aznar, B.; García, J.; Subías, G.; Herrero-Martín, J.; Stankiewicz, J. Phys. Rev. B: Condens. Matter Mater. Phys. 2008, 77, 054107. (63) Klaus, S.; Cai, Y.; Louie, M. W.; Trotochaud, L.; Bell, A. T. manuscript in preparation, 2015. (64) Wang, L.; Maxisch, T.; Ceder, G. Phys. Rev. B: Condens. Matter Mater. Phys. 2006, 73, 195107. (65) García-Mota, M.; Bajdich, M.; Viswanathan, V.; Vojvodic, A.; Bell, A. T.; Nørskov, J. K. J. Phys. Chem. C 2012, 116, 21077. (66) Himmetoglu, B.; Floris, A.; de Gironcoli, S.; Cococcioni, M. Int. J. Quantum Chem. 2014, 114, 14. (67) Szytula, A.; Balanda, M.; Dimitrijevi, Ž. Phys. Status Solidi A 1970, 3, 1033. (68) Oleś, A.; Szytuła, A.; Wanic, A. Phys. Status Solidi B 1970, 41, 173. (69) Nørskov, J. K.; Rossmeisl, J.; Logadottir, A.; Lindqvist, L.; Kitchin, J. R.; Bligaard, T.; Jónsson, H. J. Phys. Chem. B 2004, 108, 17886. (70) Man, I. C.; Su, H.; Calle-Vallejo, F.; Hansen, H. A.; Martínez, J. I.; Inoglu, N. G.; Kitchin, J.; Jaramillo, T. F.; Nørskov, J. K.; Rossmeisl, J. ChemCatChem 2011, 3, 1159. (71) Koper, M. T. M. J. Electroanal. Chem. 2011, 660, 254. (72) Bajdich, M.; García-Mota, M.; Vojvodic, A.; Nørskov, J. K.; Bell, A. T. J. Am. Chem. Soc. 2013, 135, 13521. " + }, + { + "id": "10.1038_NMAT4113", + "DOI": "10.1038/NMAT4113", + "DOI Link": "http://dx.doi.org/10.1038/NMAT4113", + "Relative Dir Path": "mds/10.1038_NMAT4113", + "Article Title": "Metal-organic framework nullosheets in polymer composite materials for gas separation", + "Authors": "Rodenas, T; Luz, I; Prieto, G; Seoane, B; Miro, H; Corma, A; Kapteijn, F; Xamena, FXLI; Gascon, J", + "Source Title": "NATURE MATERIALS", + "Abstract": "Composites incorporating two-dimensional nullostructures within polymeric matrices have potential as functional components for several technologies, including gas separation. Prospectively, employing metal-organic frameworks (MOFs) as versatile nullofillers would notably broaden the scope of functionalities. However, synthesizing MOFs in the form of freestanding nullosheets has proved challenging. We present a bottom-up synthesis strategy for dispersible copper 1,4-benzenedicarboxylate MOF lamellae of micrometre lateral dimensions and nullometre thickness. Incorporating MOF nullosheets into polymer matrices endows the resultant composites with outstanding CO2 separation performance from CO2/CH4 gas mixtures, together with an unusual and highly desired increase in the separation selectivity with pressure. As revealed by tomographic focused ion beam scanning electron microscopy, the unique separation behaviour stems from a superior occupation of the membrane cross-section by the MOF nullosheets as compared with isotropic crystals, which improves the efficiency of molecular discrimination and eliminates unselective permeation pathways. This approach opens the door to ultrathin MOF-polymer composites for various applications.", + "Times Cited, WoS Core": 1787, + "Times Cited, All Databases": 1899, + "Publication Year": 2015, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000346430100013", + "Markdown": "# Metal–organic framework nanosheets in polymer composite materials for gas separation \n\nTania Rodenas1†, Ignacio $\\mathsf{L}\\mathsf{u}\\mathsf{z}^{2\\dagger}$ , Gonzalo Prieto3†, Beatriz Seoane1, Hozanna Miro4, Avelino Corma2, Freek Kapteijn1, Francesc X. Llabrés i Xamena2\\* and Jorge Gascon1\\* \n\nComposites incorporating two-dimensional nanostructures within polymeric matrices have potential as functional components for several technologies, including gas separation. Prospectively, employing metal–organic frameworks (MOFs) as versatile nanofillers would notably broaden the scope of functionalities. However, synthesizing MOFs in the form of freestanding nanosheets has proved challenging. We present a bottom-up synthesis strategy for dispersible copper 1,4-benzenedicarboxylate MOF lamellae of micrometre lateral dimensions and nanometre thickness. Incorporating MOF nanosheets into polymer matrices endows the resultant composites with outstanding $\\mathbf{co}_{2}$ separation performance from $\\mathsf{c o}_{2}/\\mathsf{c h}_{4}$ gas mixtures, together with an unusual and highly desired increase in the separation selectivity with pressure. As revealed by tomographic focused ion beam scanning electron microscopy, the unique separation behaviour stems from a superior occupation of the membrane cross-section by the MOF nanosheets as compared with isotropic crystals, which improves the efciency of molecular discrimination and eliminates unselective permeation pathways. This approach opens the door to ultrathin MOF–polymer composites for various applications. \n\nHigh-aspect-ratio nanostructured materials with extended lateral dimensions and (sub)nanometre thickness often exhibit exotic physicochemical properties radically different from those of their isotropic (bulk) counterparts. As a result, two-dimensional (2D) nanostructures are highly interesting components for advanced structures1 and functional materials for applications including (opto)electronics2, energy storage and gas separation3,4. This has stimulated keen interest in devising innovative synthesis routes towards 2D nanostructured materials. Essentially, these methodologies can be grouped into two categories. On one hand, top-down exfoliation approaches rely on the disintegration of 3D layered solids5–7. However, shortcomings such as fragmentation, morphological damage4 and re-aggregation of the detached sheets are often associated with these methods. On the other hand, although scarce, bottom-up strategies which produce ultrathin materials at their genesis are preferred. In this case, 2D nanostructures might be achieved by either imposing anisotropic crystal growth8 or restricting thermodynamically favoured layer stacking processes9. \n\nMetal–organic frameworks are crystalline coordination polymers in which a hybrid array of metallic nodes interconnected by organic linkers defines a regular and porous structure10–12. MOFs exhibit pores and cavities in the range of molecular dimensions whose size, connectivity and dynamic interaction with target guest molecules can be regulated by the judicious selection of the organic and inorganic building blocks among a virtually unlimited number of possibilities13,14. These properties endow MOFs with great potential for applications in which molecule discrimination via preferential adsorption or molecular sieving is important: for example, drug delivery, catalysis and gas separation15–17. In particular, the use of MOF-based membranes to selectively remove specific components from gas mixtures has the promise of giving a breakthrough in several processes of economic and environmental significance17,18. \n\nAll-MOF membranes built on the packing of discrete crystals19 face challenges which limit their applicability—for example, complex manufacture and processing, often alongside suboptimal mechanical stability20. As a trade-off between the selective hostmolecule interactions of MOFs and the mechano-chemical stability and easy processing of polymers, MOF–polymer composite materials have been proposed for gas separation processes21,22. However, conventional MOF synthesis procedures yield agglomerated powders consisting of isotropic micrometre-sized crystals or barely dispersible nanoparticles. This complicates their subsequent incorporation within a polymer matrix and restricts the integration of the two components in the ultimate composite—for example, by promoting phase segregation. As a result, the benefits of incorporating MOF fillers within polymer matrices for gas separation applications have remained modest and manifested at relatively high MOF loadings, where the mechanical integrity of the composite is often compromised23. Encouraging results have been recently reported using submicrometre-sized MOF filler crystals24,25. Intuitively, the availability of high-aspect-ratio, ideally ultrathin, MOF nanostructures would represent an advanced solution to improve the integration between both components in the composite materials, thereby circumventing the aforementioned hurdles. Two-dimensional MOF structures have been manufactured on solid substrates via layer-bylayer or epitaxial growth approaches18,26. However, the synthesis of freestanding MOF nanosheets, which is central to intimately blend them into polymers and produce spatially uniform composites, has as yet remained a challenge. Here we present a bottom-up synthesis strategy leading to highly crystalline, intact MOF nanosheets that can be readily dispersed into a polymer matrix, yielding composite materials with superior performance when applied as membranes in gas separation. \n\n![](images/f4aa281dd54527195f9ae3ea0283a88e61abb58d9d01d146658c0b7e85ceb460.jpg) \nFigure 1 | Synthesis and structure of the metal–organic framework nanostructures. a, 3D crystalline structure of CuBDC MOF. Copper, oxygen and carbon atoms are shown in blue, red and grey, respectively. The insets on the right-hand side show views along the $b$ (top) and c (bottom) crystallographic axes showing the stacking direction and the pore system, respectively. Hydrogen atoms and $N,N$ -dimethyl formamide solvate molecules coordinated to ${\\mathsf{C u}}^{2+}$ ions have been omitted for clarity. b, Scanning electron micrograph of bulk-type CuBDC MOF crystals. c, Picture showing the spatial arrangement of diferent liquid layers during the synthesis of CuBDC MOF nanosheets. Layers labelled as i, ii and iii correspond to a benzene 1,4-dicarboxylic acid (BDCA) solution, the solvent spacer layer and the solution of $\\mathsf{C u}^{2+}$ ions, respectively. To enhance visualization, 2-amino 1,4-benzenedicarboxylic acid, which shows a yellow colour shade, has been employed as phase i to produce the illustrative picture presented. A close-up schematic representation of the concentration gradients established for $\\mathsf{C u}^{2+}$ and linker precursors at the spacer layer is also depicted on the right. d, X-ray difractograms (Cu Kα radiation) for the bulk-type and nanosheet CuBDC MOF. e,f, Scanning electron micrograph and atomic-force micrograph (with corresponding height profiles), respectively, for CuBDC MOF nanosheets synthesized as illustrated in c. The height profiles, colour-coded red and blue, are measured along the corresponding tracks shown in the atomic-force micrograph. \n\n# Synthesis of freestanding MOF nanosheets \n\nTo illustrate our synthesis approach we have selected the copper 1,4-benzenedicarboxylate (CuBDC) MOF as a showcase. This material, initially synthesized by Mori et al.27, exhibits a layered crystalline structure and looks promising for the separation of polar gas molecules, such as $\\mathrm{CO}_{2}$ , via selective adsorption28,29. Its crystalline structure consists of ${\\mathrm{Cu}}^{\\mathrm{{II}}}$ dimers with a square-pyramidal coordination geometry interconnected by benzenedicarboxylate anions, constituting layers which stack along the [2¯01] crystallographic direction (Fig. 1a)30. The network of metal nodes and organic linkers defines nanopores which run along the stacking direction. The conventional solvothermal synthesis protocol yields predominantly well-defined cubic MOF crystals with edge dimensions ranging from 2 to $10\\upmu\\mathrm{m}$ (Supplementary Fig. 1). Close-up inspection of the crystals reveals that they actually consist of multiple, closely packed lamellae (Fig. 1b). \n\nOur bottom-up synthesis strategy to produce MOF nanosheets relies on the diffusion-mediated modulation of the MOF growth kinetics. As schematically illustrated in Fig. 1c, the synthesis medium consists of three liquid layers composed of mixtures of $^{N,N}$ -dimethyl formamide (DMF) and a suitable miscible co-solvent in appropriate ratios, which are vertically arranged according to their different densities—namely, a topmost solution of $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}$ and a bottom solution of 1,4-benzenedicarboxylic acid (BDCA), separated by an intermediate solvent layer. Under static conditions, diffusion of ${\\mathrm{Cu}}^{2+}$ cations and BDCA linker precursors into the spacer segment causes a slow supply of the MOF nutrients to an intermediate region where the growth of MOF crystals occurs locally in a highly diluted medium. No immiscible liquid phases are involved in the proposed synthesis method, as opposed to interfacial reaction strategies where the extent of an organic/aqueous interface determines the surface available for MOF growth31. The nascent MOF crystals are naturally removed from the reactive front by sedimentation, after which further growth is inhibited in the ${\\mathrm{Cu}}^{2+}$ - depleted underlying organic phase. X-ray diffraction of the solid product showed only three reflections, which can be indexed as the (¯201), (¯402) and (¯804) crystallographic planes of the CuBDC structure, all perpendicular to the stacking direction of the layers in the bulk MOF crystals and to the pore openings (Fig. 1d). None of the additional Bragg diffractions of the bulk counterpart were detected, indicative of the successful synthesis of MOF structures showing a strong preferential orientation along the basal plane. Scanning electron microscopy and atomic-force microscopy showed square lamellae exhibiting lateral dimensions of $0.5\\mathrm{-}4\\upmu\\mathrm{m}$ and thicknesses in the range $5-25\\mathrm{nm}$ —that is, aspect ratios exceeding 20 (Fig. 1e,f and Supplementary Fig. 1). Transmission electron microscopy (Supplementary Fig. 2) verified the highly regular morphology and the absence of internal structural defects in the obtained MOF nanosheets. \n\n![](images/e7cc6798ba6a2b8d7bcabae0ed1e4e85ab50f6b38ceec32f0a82ea48b6b13aeb.jpg) \nFigure 2 | Versatility and scope of the three-layer synthesis strategy to produce 2D MOF nanocrystals. a–d, Scanning electron microscopy (SEM) images of CuBDC crystals synthesized via the three-layer approach at $298\\mathsf{K}$ (a), 313 K (b), $3231$ (c) and $333\\mathsf{K}$ (d). e–h, SEM micrographs of 2D crystals obtained by extending the same synthesis strategy to other MOFs: cobalt 1,4-benzenedicarboxylate or CoBDC (e), zinc 1,4-benzenedicarboxylate or ZnBDC (f), copper 1,4-naphthalenedicarboxylate or Cu(1,4-NDC) $\\mathbf{\\sigma}(\\mathbf{g})$ and copper 2,6-naphthalenedicarboxylate or Cu(2,6-NDC) (h). Insets in e–h show the corresponding X-ray difractograms recorded for the 2D MOF crystals. \n\nThe versatility and scope of the MOF nanosheet synthesis strategy was further investigated by assessing the impact of the relevant reaction parameters and exploring alternative MOF building units. Under otherwise identical synthesis conditions, omission of the intermediate buffer layer resulted in CuBDC crystals exhibiting notably smaller aspect ratios as a result of having up to micrometre-scale thickness along the stacking direction (Supplementary Fig. 3). As illustrated in Fig. 2, control of the crystal growth kinetics, via adjustment of the synthesis temperature, enables variation of the thickness of the CuBDC MOF nanosheets. On increasing the synthesis temperature, the MOF crystal morphology evolved from ultrathin nanosheets (with average thickness ${<}10\\mathrm{nm}$ ) at $298\\mathrm{K}$ to thicker platelets at $323\\mathrm{K}.$ At a higher temperature of $333\\mathrm{K},$ the anisotropic crystal growth was not preserved, and the synthesis yielded primarily CuBDC nanometric crystals, with aspect ratios close to unity and sizes in the range $30{-}500\\mathrm{nm}$ , coexisting with a few bulkier crystals and platelets. The nature of the co-solvent employed serves also to modify the crystal growth behaviour to obtain CuBDC crystals with different aspect ratios (Supplementary Fig. 4). Furthermore, the same synthesis methodology can be successfully extended to produce high-aspectratio sheet crystals of a variety of layered MOF structures via either substitution of ${\\mathrm{Cu}}^{2+}$ for alternative metal nodes, for example, ${\\mathrm{Co}}^{2+}$ and $Z\\mathrm{n}^{2+}$ (Fig. 2e,f), or BDC for alternative dicarboxylate linkers (Fig. $^{2\\mathrm{g},\\mathrm{h}}$ ), which represent powerful strategies to tune the MOF porosity and functionality. No surfactants or tensioactive additives are employed to modify the crystal growth pattern. Thus, application of the three-layer synthesis strategy to MOFs with a propensity for more isotropic growth modes essentially preserved their crystal morphology, although modulation of the crystal growth resulted in submicrometre-sized MOF crystals (Supplementary Fig. 5). Collectively, these results underscore the versatility of the synthesis methodology to produce freestanding, 2D nanocrystals of several metal–organic frameworks. \n\nMicroporous MOFs containing coordinatively unsaturated (cus) copper sites, including CuBDC (ref. 28), but also related frameworks such as copper hydroxyterephthalate $\\left(\\mathrm{Cu}(\\mathrm{OH}{\\cdot}\\mathrm{BDC})\\right)$ (ref. 32), and copper 1,3,5-benzenetricarboxylate $\\mathrm{(Cu(BTC))}$ (refs 33,34), show the potential for gas separation applications owing to their preferential $\\mathrm{CO}_{2}$ adsorption over apolar molecules such as $\\mathrm{CH_{4}}$ and $\\Nu_{2}$ . Figure 3a shows the $\\Nu_{2}$ sorption isotherms (77 K) for the herein synthesized bulk-type and nanosheet CuBDC MOFs. \n\nThe MOF nanosheets feature a specific surface area $(S_{\\mathrm{BET}})$ of $53\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , which is mostly external, as deduced from the corresponding $t$ -plot analysis, and is about five times higher than that of the bulk material $(S_{\\mathrm{BET}}\\ 11\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}.$ ). Effective blockage of $\\mathrm{N}_{2}$ and Ar from the microporous structure in both cases indicates that effective pore apertures smaller than the crystallographic value of $5.2\\mathring\\mathrm{A}$ (refs 35,36) are obtained following the herein adopted synthesis and activation procedures. The $\\mathrm{N}_{2}$ uptake observed at high relative pressures $(P/P_{0}>0.7)$ in the nanosheet material, featuring a H1-type hysteresis loop, and which is totally absent in the bulk solid, is characteristic of the ‘house-of-cards’ interparticle porosity previously described for other delaminated materials5,8,37,38. Figure 3b shows the $\\mathrm{CO}_{2}$ and $\\mathrm{CH}_{4}$ adsorption isotherms for CuBDC in both crystal morphologies. The isotherms exhibit a type I shape, characteristic of microporous materials39, with $\\mathrm{CO}_{2}$ uptakes at 1 bar (750 torr) of 1.29 and $0.82\\mathrm{mmol}\\mathrm{g}^{-1}$ for $b$ -CuBDC and nsCuBDC, respectively. The obtained values are in good agreement with previous reports on the bulk material28,36. The slightly higher gas uptake determined for $b$ -CuBDC over ns-CuBDC might be ascribed to the contribution of interlamella voids to adsorption in the former. Analysis of the $\\mathrm{CO}_{2}$ adsorption isotherms with the Dubinin–Radushkevich formalism40 revealed analogous micropore specific surface areas of 288 and $267\\mathrm{m}^{2}\\mathrm{g}^{-1}$ for the bulk and nanosheet MOF crystals, respectively. Irrespective of the crystal morphology, the materials show a significant preference for $\\mathrm{CO}_{2}$ adsorption over $\\mathrm{CH_{4}}$ . Ideal $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ selectivities, determined as the ratio of the single-component sorption capacities at every pressure, are similar for both crystal morphologies $(3.9\\pm0.5)\\$ , comparable to those reported for related MOF structures comprising cus copper sites such as $\\mathrm{Cu(BTC)}$ (ref. 34) and $\\mathrm{Cu(OH\\mathrm{-BDC)}}$ (ref. 32). The obtained results for ns- and $b$ -CuBDC demonstrate the similar intrinsic sorption properties of both MOF crystal morphologies and demonstrate the suitability of the CuBDC framework for the selective removal of $\\mathrm{CO}_{2}$ from $\\mathrm{CO_{2}/C H_{4}}$ gas mixtures. \n\n![](images/071593e3c4b20d180d9d8fb2897499b49f8f1345326d7e070c237f7222d1e935.jpg) \nFigure 3 | Sorption properties of CuBDC MOF crystals. a, ${\\sf N}_{2}$ sorption isotherms at $77\\mathsf{K}.$ b, $\\mathsf{C O}_{2}$ (circles) and $C H_{4}$ (diamonds) sorption isotherms at $273\\mathsf{K};$ for bulk-like (red) and nanosheet (blue) CuBDC crystals after washing and evacuation at $453\\mathsf{K}$ . The inset to a shows the Ar sorption isotherm at $87\\mathsf{K}$ for the nanosheet crystals. Open symbols correspond to adsorption branches while closed symbols correspond to desorption branches. \n\n# MOF–polymer composites assembly and structure \n\nThe structural and physicochemical properties of the CuBDC MOF nanosheets, alongside their freestanding and dispersible nature, represent promising features for their integration in advanced composites for gas separation applications. To test this potential, MOF–polymer composites were prepared by incorporating CuBDC nanosheets within a polyimide (PI) matrix at different filler loadings $(2-12\\mathrm{wt\\%})$ . The nanosheets were dispersed in a solution of commercially available PI. Next, the composites were cast as thin membranes with a thickness of $30{-}50\\upmu\\mathrm{m}$ (Supplementary Fig. 7) and activated under dynamic vacuum at $453\\mathrm{K}$ . The same procedure was employed to prepare comparative composites incorporating either bulk-type or submicrometre-sized (nanoparticle) isotropic CuBDC MOF crystals as fillers, as well as a MOF-free polymeric film. The resulting composites are hereafter labelled as $x$ - $\\mathrm{CuBDC}(y)@\\mathrm{PI}.$ where $x$ is ns, $b$ or nc for CuBDC nanosheet, bulk and nanoparticle crystals, respectively, and $y$ indicates the MOF weight loading. The internal structure of the composite membranes was studied with tomographic focused ion beam scanning electron microscopy (FIB–SEM; refs 41,42), as illustrated in Fig. 4 for $n s\\mathrm{-}\\mathrm{CuBDC}(\\&)@\\mathrm{PI}$ and $b{\\mathrm{-}}\\mathrm{CuBDC}(8)\\ @\\mathrm{PI}$ A trench was carved on the upper surface of the membranes using a FIB (Fig. 4a) and a series of SEM micrographs were recorded of crosssections exposed on successive FIB milling of thin slices (Fig. $^\\mathrm{4b,c}$ ). After alignment of the stack of micrographs, the imaged volumes were reconstructed in 3D. The full tomograms are provided as Supplementary Movies 1 and 2, while Fig. 4e,f shows surfacerendered views after segmentation of different phases. The MOF content in the examined volume was very close to the overall loading (Supplementary Methods). Despite the identical filler content, striking differences in the nanostructure were immediately evident. Whereas the regular MOF crystals leave a significant fraction of the composite volume unoccupied in $\\begin{array}{r}{b\\mathrm{-CuBDC}(8)@\\mathrm{PI}_{\\mathit{i}}}\\end{array}$ , owing to their bulky nature, the MOF lamellae are uniformly distributed over the inspected volume for ns- $-\\mathrm{CuBDC}(8)\\textcircled{a}\\mathrm{PI}$ \n\nImage analysis of the FIB–SEM tomograms allowed quantification of a number of structural parameters of the composite membranes (Fig. 5). The MOF nanosheets in ns$\\mathrm{CuBDC(}8)@\\mathrm{PI}$ exposed about one order of magnitude larger surface area than the bulk-type crystals incorporated in $b$ - $\\mathrm{CuBDC(8)}\\ @\\mathrm{PI}$ $(2.2\\times10^{-3}$ versus $2.{\\dot{9}}\\times10^{-4}\\mathrm{nm}^{\\dot{2}}\\mathrm{nm}^{-3}$ MOF), enormously increasing their interaction with gas molecules. Of particular relevance for the separation performance is the extent to which the MOF filler occupies the membrane cross-section perpendicular to the gas flux—that is, perpendicular to the pressure gradient established over the membrane during the separation process. Such a flux direction is normal to the basal plane of the membranes, corresponding to the y axis in the tomograms depicted in Fig. 4. Figure 5 shows the 2D projections of the reconstructed FIB–SEM tomograms as well as the evolution of the MOF surface coverage as a function of the membrane depth along the $y$ axis. \n\nSignificant variations in the local MOF coverage at different membrane depths are observed for $b{\\mathrm{-}}\\mathrm{CuBDC}({\\bar{8}}){\\textcircled{\\omega}}\\mathrm{PI}$ , corresponding to alternating regions with high and low MOF content owing to the bulky character of the crystals. In sharp contrast, the MOF nanosheets very uniformly occupy the membrane cross-section at all depths. As a result, the effective MOF surface occupation, accumulated over an identical sampled depth of ${5\\upmu\\mathrm{m}}$ , is almost three times higher—that is, $94\\%$ versus $36\\%$ —for the composite membrane incorporating CuBDC nanosheets. An intermediate case, with $51\\%$ accumulated coverage, is realized with CuBDC isotropic nanocrystals as fillers at the same MOF loading (Supplementary Fig. 8). The statistical orientation of the MOF nanosheets in $n s\\mathrm{-}\\mathrm{CuBDC}(\\boldsymbol{8})@\\mathrm{PI}$ was also investigated. Notably deviating from a random orientation, the histogram shows a strong prevalence of lamellae oriented at angles close to $90^{\\circ}$ with respect to the gas flux direction (Fig. 5e). Similar preferential orientations of nanosized 2D objects within viscous matrices have been previously encountered under external shear forces43 to those applied during the casting of the membranes investigated here, suggesting their relevance for the ultimate nanosheet orientation in the MOF nanosheet–polymer composite films. The preferential orientation of the MOF nanosheets means that the efficiency with which the lamellae cover the membrane cross-section, exposing their pore system in the direction of the gas flux, is close to maximum (Fig. 5f), thereby minimizing the filler content and the membrane thickness required for an effective coverage. In summary, image analysis results directly prove how the incorporation of CuBDC nanosheets results in a notably superior occupation of the membrane crosssection perpendicular to the gas flux by the molecular sieve, increasing the likelihood of repeated molecule discrimination events and efficiently eliminating MOF-free diffusion pathways. \n\n![](images/b5091680d920cb503dd95c3411f906b3ecb8418a025493c5d1021acb4accc7f4.jpg) \nFigure 4 | Tomographic FIB–SEM analysis of MOF–polymer composite membranes. a, Overview scanning electron micrograph of the trench carved with a FIB on the surface of an $8w t\\%$ MOF–polymer composite membrane. The yellow frame indicates a central region within the imaged cross-section that was selected for further analysis. b,c, Representative SEM micrographs of cross-sections of composite membranes containing bulk-type (b) and nanosheet (c) CuBDC MOF embedded in polyimide. MOF species appear as bright motifs on the dark grey polymer matrix. Cubic MOF crystals are seen in b, whereas ultrathin MOF nanosheets are evident in c. d, Orthogonal cross-sections through the 3D reconstructed FIB–SEM tomogram of a MOF–polymer composite. e,f, Surface-rendered views of the segmented FIB–SEM tomograms for composite membranes containing bulk-type (e) and nanosheet (f) CuBDC MOF embedded in polyimide. MOF particles are shown in blue, while voids are shown in red. Given the diferent magnification required to image the features of interest for diferent composite membranes, the dimensions of the boxes shown in e and f along the x:y:z directions are 11.2:11.2:7.6 and $4.9{:}4.9{:}6.6\\upmu\\mathrm{m}$ , respectively. \n\n# Gas separation application \n\nTo assess their technological relevance, the MOF–polymer composite membranes were tested in the separation of $\\mathrm{CO}_{2}$ from $\\mathrm{CO_{2}/C H_{4}}$ mixtures. The selective recovery of $\\mathrm{CO}_{2}$ from gas mixtures is central to a number of energy-related processes as well as to reduce the emissions of greenhouse gases to the atmosphere44. For example, $\\mathrm{CO}_{2}$ is a main impurity in most natural and shale gas wells. Its separation from $\\mathrm{CH_{4}}$ is mandatory for the processing and transport of these carbon resources, as it significantly decreases the calorific power and contributes to pipeline corrosion. Whereas conventional amine absorption technologies are energy intensive and employ hazardous chemicals, the development of membranes for the selective separation of $\\mathrm{CO}_{2}$ has the promise of giving an energy-efficient and environmentally benign alternative45,46. As shown in Fig. 6, the incorporation of bulktype CuBDC crystals into the polyimide matrix slightly worsens the separation selectivity as compared with a neat polyimide reference membrane. This result is illustrative of the discouraging separation performances previously encountered for composite membranes incorporating bulky, isotropic filler crystals23. It can be attributed to the disruption of the polymer chains due to the presence of the bulky filler particles, which worsens the intrinsic separation properties of the polymeric matrix and favours the generation of unselective nano- or microvoids at the filler–matrix boundary. The use of smaller, submicrometre-sized CuBDC crystals results in a slight improvement in the separation selectivity, which nevertheless underperforms the neat polymeric membrane. However, the beneficial role of the MOF nanosheets as filler material is immediately apparent. At every studied transmembrane pressure difference, the separation selectivity for $n s\\mathrm{-CuBDC}(8)@\\mathrm{PI}$ is $30\\mathrm{-}80\\%$ higher than for the polymeric membrane and $75\\%$ to eight times higher than for the $\\scriptstyle{\\dot{b}}\\mathbf{-CuBDC}(8)@\\operatorname{PI}$ counterpart in the range of operating conditions investigated. The similar intrinsic sorption properties of bulk-type and nanosheet CuBDC crystals cannot account for such remarkable differences in separation performance, which are therefore attributed to the different MOF crystal morphology, which is in turn key for the filler–polymer integration and the occupation of the gas permeation pathways by the molecular sieve. Most remarkably, the selectivity achieved with $n s\\mathrm{-}\\mathrm{CuBDC}(\\&)@\\mathrm{PI}$ is retained or even increases slightly on increasing the upstream pressure. This significant finding is completely opposite to the general observation for both polymeric and conventional MOF–polymer membranes47, that the separation selectivity drops on incrementing the partial pressure of $\\mathrm{CO}_{2}$ . Such classical behaviour is exemplified here by the performance of the neat polymer (PI), but also composites containing isotropic filler particles such as $n c\\mathrm{-CuBDC(8)@PI}$ and, most notably, $b{\\mathrm{-}}\\mathrm{CuBDC}(8)\\ @\\mathrm{PI}$ , incorporating bulkier MOF crystals. This phenomenon, which represents a serious challenge to the state-of-the-art membranes, has been associated with the swelling of the polymer matrix on increasing the uptake of the highly sorbing $\\mathrm{CO}_{2}$ , which promotes the formation of less selective pathways for the permeating gases. \n\n![](images/213bb351047cded33180f4d070cf7960f97ba4553420a45af0e5e3bf8f714cbb.jpg) \nFigure 5 | Image analysis of FIB–SEM tomograms for MOF–polymer composite membranes. a,c, Full projections along the y direction of the reconstructed volumes for composite membranes containing bulk-type (a) and nanosheet (c) CuBDC MOF embedded in polyimide. The MOF particles are depicted as partially transparent to better perceive overlaps in the direction of the projection. b,d, Evolution of the coverage of the membrane xz cross-section by MOF particles for composite membranes containing bulk-type (b) and nanosheet (d) CuBDC MOF embedded in polyimide. Error bars in b,d correspond to the standard deviation $(\\%)$ . e, Angular histogram showing the orientation of MOF lamellae with respect to the gas flux direction (y axis) for a composite material containing MOF nanosheets embedded in polyimide. f, Histogram of the efciency with which the individual MOF nanosheets cover the membrane cross-section, defined as the ratio between the area of the MOF lamellae $(A_{|a m})$ and that projected on the plane perpendicular to the gas flux $(A_{\\mathsf{p r o j}})$ , as schematically depicted in the inset. In the same inset figure, $\\alpha$ represents the angle of inclination of each MOF lamellae with respect to the y axis. Green bars correspond to experimental data while the red line shows the exponential fit. See experimental methods in the Supplementary Information for more details on the tomogram image analysis procedures. \n\nThe superior occupation of the membrane cross-section by the nanosheet filler, uniformly at different depth levels, has two positive effects on the separation performance. First, it results in repeated gas discrimination events, contributing to higher separation selectivity, albeit at lower gas permeabilities. This is exemplified by a relationship found for $n s\\mathrm{-CuBDC}(x)@\\mathrm{PI}$ membranes between the filler cross-section coverage and the selectivity increment—and $\\mathrm{CO}_{2}$ permeability decrease—with respect to the neat polymer (Supplementary Fig. 9). Second, and most remarkably, it effectively counteracts the undesired plasticization effect, as the depletion of MOF-free permeation pathways enables the intrinsic separation properties of the MOF nanosheets to sustain the separation performance at higher operation pressures, when the separation capacity of the polymeric matrix deteriorates. Furthermore, the near-optimal orientation of the ultrathin nanofiller permits a reduction in the MOF content and membrane thickness, resulting in increased $\\mathrm{CO}_{2}$ permeability without significant penalties in the separation selectivity (Supplementary Table 1). Preliminary results indicate that a further approach to increase gas permeability, although at the expense of separation selectivity, is to employ nanosheets of a wider-pore MOF as filler material (Supplementary Fig. 10). Overall, these results emphasize the potential technological significance of the MOF nanosheet–polymer composite materials. \n\nOur findings underline the relevance of structuring the metal– organic framework component in the form of high-aspect-ratio nanosheets to design advanced composite membranes, providing a direction to reduce the thickness required to meet a given separation performance. Apart from gas separation, we envisage the versatile synthesis route and the advanced structural diagnostics strategy presented here enabling the rational development of a variety of MOF-based and other composite materials for technological applications where integrating a functional component in ultrathin devices is essential, such as light-emitting diodes, solar-light harvesting, sensing, food packaging and functional coatings and textiles. \n\n![](images/d2304f8d794eebdb4ac60d767dd7ba3aa8ec450713673067779674023a8db813.jpg) \nFigure 6 | Application of the MOF–polymer composites in a gas separation process. Separation selectivity, defined as the ratio between the permeability of $\\mathsf{C O}_{2}$ and $C H_{4}$ , as a function of the pressure diference over the membrane for the MOF–polymer composites when employed as membranes in the separation of ${\\mathsf{C O}}_{2}$ from an equimolar ${\\mathsf{C O}}_{2}/{\\mathsf{C H}}_{4}$ mixture at $298\\mathsf{K}.$ For comparison purposes, results for a neat polyimide membrane (PI) are also presented. The data correspond to steady operation conditions, after at least $^{8\\mathfrak{h}}$ on stream. ${\\mathsf{C O}}_{2}$ permeabilities spanned in the range of 2.8–5.8 Barrer, whereas $C H_{4}$ permeabilities were lower than 0.3 Barrer in all cases (Supplementary Table 1). 1 Barrer $\\c=$ $10^{-10}{\\mathsf{c m}}^{3}({\\mathsf{S T P}}){\\mathsf{c m}}^{-1}{\\mathsf{s}}^{-1}{\\mathsf{c m}}{\\mathsf{H}}{\\mathsf{g}}$ . Error bars correspond to the standard deviations, as determined from three independent tests with selected membranes. When not shown, error bars are smaller than the symbols. \n\n# Methods \n\nSynthesis of CuBDC MOF nanosheets. CuBDC MOF nanosheets were synthesized in a glass test tube. A linker solution composed of $30\\mathrm{mg}$ of $\\mathrm{H}_{2}\\mathrm{BDC}$ dissolved in a mixture of $2\\mathrm{ml}$ of DMF and $\\mathrm{1ml}$ of $\\mathrm{CH}_{3}\\mathrm{CN}$ was poured into the bottom of the tube. Over this solution, a mixture of $1\\mathrm{ml}$ of DMF and $1\\mathrm{ml}$ of $\\mathrm{CH}_{3}\\mathrm{CN}$ was carefully added to prevent premature mixing of the two solutions containing the precursors. Finally, a metal precursor solution composed of $30\\mathrm{mg}$ of $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ dissolved in a mixture of $\\mathrm{1ml}$ of DMF and $2\\mathrm{ml}$ of $\\mathrm{CH}_{3}\\mathrm{CN}$ was also carefully added to the tube as the top layer. The synthesis proceeded at $313\\mathrm{K}$ for $24\\mathrm{h}$ in static conditions, and the resulting precipitate was collected by centrifugation and washed consecutively three times with DMF (1 ml each step) followed by another three times with $\\mathrm{CHCl}_{3}$ (1 ml each step). The resulting material was left suspended in $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}$ until the synthesis of the composite materials. \n\nSynthesis of MOF–polymer composites and thin membrane casting. The polymer Matrimid 5218 (0.4 g), was stepwise added to the MOF suspension to obtain a final mass ratio solvent/(MOF+polymer) of 90/10. The MOF/polymer mass ratio was selected to achieve the desired final MOF loading in the composite materials. For the casting of membranes, the viscous suspension was poured on a flat surface and shaped as a thin film under shear forces by a doctor blade knife. Next, the solvent was removed by evaporation, first by natural convection at room temperature for $^{8\\mathrm{h}}$ , followed by a treatment in a vacuum oven at $453\\mathrm{K}$ (75.01 torr) for $12\\mathrm{h}$ . \n\nGas separation experiments. Gas permeation experiments were performed with an equimolar $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ mixture as feed. In all cases, separation selectivity and gas permeability values are reported after a steady operating regime was reached (Supplementary Fig. 11). \n\nFIB–SEM tomography. Focused ion beam scanning electron microscopy (FIB–SEM) experiments were performed in DualBeam Strata 235 (FEI) and AURIGA Compact (Zeiss) microscopes. Slices with a nominal thickness of $52\\mathrm{nm}$ were milled away by the FIB, operating at $30\\mathrm{kV}$ and $7\\times10^{3}\\mathrm{pA}$ Between 124 and 150 individual SEM micrographs of the consecutive cross-sections exposed on milling were recorded, at magnifications of 12,000–25,000, with a secondary electron detector operated at $5\\mathrm{kV.}$ The stack of images was aligned to an external feature on the membrane surface using a cross-correlation algorithm, and a stretching operation in the y direction was performed to correct the foreshortening caused by the tilt angle between the specimen cross-section and the SEM detector. To quantify parameters of interest from the reconstructed FIB–SEM tomograms, segmentation of the different phases—that is, the polymer matrix, MOF particles and internal voids—was performed in Avizo (FEI Visualization Sciences Group). \n\nFurther details on the experimental methods can be found in the Supplementary Information. \n\n# Received 24 October 2013; accepted 12 September 2014; published online 2 November 2014 \n\n# References \n\n1. Stankovich, S. et al. Graphene-based composite materials. Nature 442, 282–286 (2006). \n2. Wang, Q. H., Kalantar-Zadeh, K., Kis, A., Coleman, J. N. & Strano, M. S. Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. Nature Nanotech. 7, 699–712 (2012). \n3. Choi, S. et al. Layered silicates by swelling of AMH-3 and nanocomposite membranes. Angew. Chem. Int. Ed. 47, 552–555 (2008). \n4. Varoon, K. et al. Dispersible exfoliated zeolite nanosheets and their application as a selective membrane. Science 334, 72–75 (2011). \n5. Corma, A., Fornes, V., Pergher, S. B., Maesen, Th. L. M. & Buglass, J. G. Delaminated zeolite precursors as selective acidic catalysts. Nature 396, 353–356 (1998). \n6. Hernandez, Y. et al. High-yield production of graphene by liquid-phase exfoliation of graphite. Nature Nanotech. 3, 563–568 (2008). \n7. Li, P-Z., Maeda, Y. & Xu, Q. Top-down fabrication of crystalline metal-organic framework nanosheets. Chem. Commun. 47, 8436–8438 (2011). \n8. Choi, M. et al. Stable single-unit-cell nanosheets of zeolite MFI as active and long-lived catalysts. Nature 461, 246–249 (2009). \n9. Hu, G., Wang, N., O’Hare, D. & Davis, J. One-step synthesis and AFM imaging of hydrophobic LDH monolayers. Chem. Commun. 287–289 (2006). \n10. Yamamoto, K., Sakata, Y., Nohara, Y., Takahashi, Y. & Tatsumi, T. Organic-inorganic hybrid zeolites containing organic frameworks. Science 300, 470–472 (2003). \n11. Yaghi, O. M. et al. Reticular synthesis and the design of new materials. Nature 423, 705–714 (2003). \n12. Férey, G. Hybrid porous solids: Past, present, future. Chem. Soc. Rev. 37, 191–214 (2008). \n13. Gücüyener, C., Bergh, J., Gascon, J. & Kapteijn, F. Ethane/ethene separation turned on its head: Selective ethane adsorption on the metal-organic framework ZIF-7 through a gate-opening mechanism. J. Am. Chem. Soc. 132, 17704–17706 (2010). \n14. Deng, H. et al. Multiple functional groups of varying ratios in metal-organic frameworks. Science 12, 846–850 (2010). \n15. Khaletskaya, K. et al. Integration of porous coordination polymers and gold nanorods into core-shell mesoscopic composites toward light-induced molecular release. J. Am. Chem. Soc. 135, 10998–11005 (2013). \n16. Corma, A., Garcia, H. & Llabrés i Xamena, F. X. Engineering metal organic frameworks for heterogeneous catalysis. Chem. Rev. 110, 4606–4655 (2010). \n17. Mueller, U. et al. Metal-organic frameworks-prospective industrial applications. J. Mater. Chem. 16, 626–636 (2006). \n18. Gascon, J. & Kapteijn, F. Metal-organic framework membranes-high potential, bright future? Angew. Chem. Int. Ed. 49, 1530–1532 (2010). \n19. Li, Y. S. et al. Controllable synthesis of metal-organic frameworks: From MOF nanorods to oriented MOF membranes. Adv. Mater. 22, 3322–3326 (2010). \n20. Gascon, J. et al. Practical approach to zeolitic membranes and coatings: State of the art, opportunities, barriers, and future perspectives. Chem. Mater. 24, 2829–2844 (2012). \n21. Bae, T-H. et al. A high-performance gas-separation membrane containing submicrometer-sized metal-organic framework crystals. Angew. Chem. Int. Ed. 49, 9863–9866 (2010). \n22. Zornoza, B. et al. Functionalized flexible MOFs as fillers in mixed matrix membranes for highly selective separation of $\\mathrm{CO}_{2}$ from $\\mathrm{CH}_{4}$ at elevated pressures. Chem. Commun. 47, 9522–9524 (2011). \n23. Zornoza, B., Tellez, C., Coronas, J., Gascon, J. & Kapteijn, F. Metal organic frameworks based mixed matrix membranes: An increasingly important field of research with a large application potential. Microp. Mesop. Mater. 166, 67–78 (2013). \n24. Zhang, C., Dai, Y., Johnson, J. R., Karvan, O. & Koros, W. High performance ZIF-8/6FDA-DAM mixed matrix membrane for propylene/propane separations. J. Mem. Sci. 389, 34–42 (2012). \n25. Li, T., Pan, Y., Peinemann, K-V. & Lai, Z. Carbon dioxide selective mixed matrix composite membrane containing ZIF-7 nano-fillers. J. Mem. Sci. 425–426, 235–242 (2013). \n26. Makiura, R. et al. Surface nano-architecture of a metal-organic framework. Nature Mater. 9, 565–571 (2010). \n27. Mori, W. et al. Synthesis of new adsorbent copper(II) terephthalate. Chem. Lett. 26, 1219–1220 (1997). \n28. Xin, Z., Bai, J., Shen, Y. & Pan, Y. Hierarchically micro- and mesoporous coordination polymer nanostructures with high adsorption performance. Cryst. Growth Des. 10, 2451–2454 (2010). \n29. Adams, R., Carson, C., Ward, J., Tannenbaum, R. & Koros, W. Metal organic framework mixed matrix membranes for gas separations. Micropor. Mesopor. Mater. 131, 13–20 (2010). \n30. Carson, C. G. et al. Synthesis and structure characterization of copper terephthalate metal-organic framework. Eur. J. Inorg. Chem. 2009, 2338–2343 (2009). \n31. Ameloot, R. et al. Interfacial synthesis of hollow metal-organic framework capsules demonstrating selective permeability. Nature Chem. 3, 382–387 (2011). \n32. Chen, Z. et al. Microporous metal-organic framework with immobilized -OH functional groups within the pore surfaces for selective gas sorption. Eur. J. Inorg. Chem. 2010, 3745–3749 (2010). \n33. Karra, J. R. & Walton, K. S. Molecular simulations and experimental studies of $\\mathrm{CO}_{2}$ , CO, and $\\mathrm{N}_{2}$ adsorption in metal-organic frameworks. J. Phys. Chem. C 114, 15735–15740 (2010). \n34. Liu, J., Thallapally, P. K., McGrail, B. P., Brown, D. R. & Liu, J. Progress in adsorption-based $\\mathrm{CO}_{2}$ capture by metal-organic frameworks. Chem. Soc. Rev. 41, 2308–2322 (2012). \n35. Seki, K., Takamizawa, S. & Mori, W. Characterization of microporous copper(II) dicarboxylates (fumarate, terephthalate, and trans-1,4-cyclohexanedicarboxylate) by gas adsorption. Chem. Lett. 30, 122–123 (2001). \n36. Carson, C. G. et al. Structure solution from powder diffraction of copper 1,4-benzenedicarboxylate. Eur. J. Inorg. Chem. 2014, 2140–2145 (2014). \n37. Corma, A., Diaz, U., Domine, M. E. & Fornes, V. AlITQ-6 and TiITQ-6: Synthesis, characterization, and catalytic activity. Angew. Chem. Int. Ed. 39, 1499–1501 (2000). \n38. Corma, A., Fornes, V. & Diaz, U. ITQ-18 a new delaminated stable zeolite. Chem. Commun. 2642–2643 (2001). \n39. Rouquerol, F., Rouquerol, J. & Sing, K. Adsorption by Powders and Porous Solids (Academic, 1999). \n40. Dubinin, M. M. The potential theory of adsorption of gases and vapors for adsorbents with energetically nonuniform surfaces. Chem. Rev. 60, \n235–241 (1960). \n41. Uchic, M. D., Holzer, L., Inkson, B. J., Principe, E. L. & Munroe, P. Three-dimensional microstructural characterization using focused ion beam tomography. Mater. Res. Soc. Bull. 32, 408–416 (2007). \n42. Rodenas, T. et al. Visualizing MOF mixed matrix membranes at the nanoscale: Towards structure-performance relationships in $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ separation over $\\mathrm{NH}_{2}$ -MIL-53(Al) ${\\mathcal{Q}}\\mathrm{PI}$ Adv. Funct. Mater. 24, 249–256 (2013). \n43. Wang, X. et al. Unusual rheological behaviour of liquid polybutadiene rubber/clay nanocomposite gels: The role of polymer-clay interaction, clay exfoliation, and clay orientation and disorientation. Macromology 39, \n6653–6660 (2006). \n44. Yang, Y. et al. Progress in carbon dioxide separation and capture: A review. J. Environ. Sci. 20, 14–27 (2008). \n45. Yeo, Z. Y., Chew, T. L., Zhu, P. W., Mohamed, A. R. & Chai, S-P. Conventional processes and membrane technology for carbon dioxide removal from natural gas: A review. J. Nature Gas Chem. 21, 282–298 (2012). \n46. McKeown, N. B. & Budd, P. M. Polymers of intrinsic microporosity (PIMs): Organic materials for membrane separations, heterogeneous catalysis and hydrogen storage. Chem. Soc. Rev. 35, 675–683 (2006). \n47. Vinh-Thang, H. & Kaliaguine, S. Predictive models for mixed-matrix membrane performance: A review. Chem. Rev. 113, 4980–5028 (2013). \n\n# Acknowledgements \n\nThe Kavli Institute of Nanoscience (TUDelft) and the Microscopy Service of the Polytechnic University of Valencia (UPV) are acknowledged for access to their microscopy facilities. P. Alkemade (TUDelft) and J.L. Moya (UPV) are acknowledged for their guidance and assistance in the acquisition of FIB–SEM data sets. The research leading to these results has received funding (J.G., B.S.) from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 335746, CrystEng-MOF-MMM. T.R. is grateful to TUDelft for funding. G.P. acknowledges the A. von Humboldt Foundation for a research grant. A.C., I.L. and F.X.L.i.X. thank Consolider-Ingenio 2010 (project MULTICAT) and the ‘Severo Ochoa’ programme for support. I.L. also thanks CSIC for a JAE doctoral grant. \n\n# Author contributions \n\nA.C., F.K., F.X.L.i.X. and J.G. conceived the research. F.X.L.i.X. and J.G. designed the experiments and coordinated the research. I.L. synthesized and characterized the MOF materials. T.R. and B.S. synthesized and characterized the MOF–polymer composites. H.M. and T.R. recorded the FIB–SEM data sets. G.P. contributed conception and execution of FIB–SEM data reconstruction and image analysis, with the assistance of T.R. All authors contributed to analysis and discussion on the data. The manuscript was primarily written by T.R., G.P., F.X.L.i.X. and J.G., with input from all authors. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to F.X.L.i.X. or J.G. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. " + }, + { + "id": "10.1126_science.aad1818", + "DOI": "10.1126/science.aad1818", + "DOI Link": "http://dx.doi.org/10.1126/science.aad1818", + "Relative Dir Path": "mds/10.1126_science.aad1818", + "Article Title": "Overcoming the electroluminescence efficiency limitations of perovskite light-emitting diodes", + "Authors": "Cho, HC; Jeong, SH; Park, MH; Kim, YH; Wolf, C; Lee, CL; Heo, JH; Sadhanala, A; Myoung, N; Yoo, S; Im, SH; Friend, RH; Lee, TW", + "Source Title": "SCIENCE", + "Abstract": "Organic-inorganic hybrid perovskites are emerging low-cost emitters with very high color purity, but their low luminescent efficiency is a critical drawback. We boosted the current efficiency (CE) of perovskite light-emitting diodes with a simple bilayer structure to 42.9 candela per ampere, similar to the CE of phosphorescent organic light-emitting diodes, with two modifications: We prevented the formation of metallic lead (Pb) atoms that cause strong exciton quenching through a small increase in methylammonium bromide (MABr) molar proportion, and we spatially confined the exciton in uniform MAPbBr3 nullograins (average diameter = 99.7 nullometers) formed by a nullocrystal pinning process and concomitant reduction of exciton diffusion length to 67 nullometers. These changes caused substantial increases in steady-state photoluminescence intensity and efficiency of MAPbBr(3) nullograin layers.", + "Times Cited, WoS Core": 2512, + "Times Cited, All Databases": 2659, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000365700500069", + "Markdown": "# PEROVSKITE LEDS \n\n# Overcoming the electroluminescence efficiency limitations of perovskite light-emitting diodes \n\nHimchan Cho,1\\* Su-Hun Jeong,1\\* Min-Ho Park,1\\* Young-Hoon Kim,1 Christoph Wolf,1 Chang-Lyoul Lee,2 Jin Hyuck Heo,3 Aditya Sadhanala,4 NoSoung Myoung,2 Seunghyup Yoo,5 Sang Hyuk Im,3 Richard H. Friend,4 Tae-Woo Lee1,6† \n\nOrganic-inorganic hybrid perovskites are emerging low-cost emitters with very high color purity, but their low luminescent efficiency is a critical drawback. We boosted the current efficiency (CE) of perovskite light-emitting diodes with a simple bilayer structure to 42.9 candela per ampere, similar to the CE of phosphorescent organic light-emitting diodes, with two modifications: We prevented the formation of metallic lead (Pb) atoms that cause strong exciton quenching through a small increase in methylammonium bromide (MABr) molar proportion, and we spatially confined the exciton in uniform $\\mathsf{M A P b B r}_{3}$ nanograins (average diameter $=99.7\\$ nanometers) formed by a nanocrystal pinning process and concomitant reduction of exciton diffusion length to 67 nanometers. These changes caused substantial increases in steady-state photoluminescence intensity and efficiency of $\\mathsf{M A P b B r}_{3}$ nanograin layers. \n\nO rhgavne cr-eicneonrtglaynbiceehnybersitdapbleirsohvesdkitaessa(nOIiPms)- portant class of materials in photovoltaic devices, and there has been rapid progress in increasing their power conversion efficiency (1–5). OIPs are emerging also as promising light emitters because they can provide very high color purity (full width at half maximum $\\sim20\\mathrm{nm}\\cdot$ ) irrespective of the crystal size, unlike conventional inorganic quantum dots, because their intrinsic crystal structure is similar to a multiple quantum well $(6,7)$ . Also, OIPs have low material cost and a simply tunable band gap, with a reasonable ionization energy (IE) comparable to that of common hole-injection materials (7–11). Thus, OIPs are attractive materials as alternative emitters that can overcome the disadvantages of organic light-emitting diodes (OLEDs) (e.g., complex synthesis, high cost, and poor color purity) and inorganic quantum dot LEDs (e.g., complex synthesis, high cost, and high IE). \n\nBright electroluminescence (EL) $\\mathrm{(>100~cd~m^{-2})}$ at room temperature from perovskite light-emitting diodes (PeLEDs) with a methylammonium lead halide $\\mathrm{(MAPbX_{3},}$ where X is I, Br, or Cl) emission layer was demonstrated recently $(6,7,I2\\ –I8)$ . As an emission layer, $\\mathbf{MAPbBr_{3}}$ has higher air stability (7, 19) and exciton binding energy (76 or $150\\mathrm{meV})$ than does $\\mathbf{MAPbI_{3}}$ (30 or $50\\mathrm{meV},$ (20, 21). However, PeLEDs have much lower current efficiency (CE) at room temperature than do OLEDs or quantum dot LEDs. Existing methods have not overcome the substantial luminescence quenching in $\\mathrm{MAPbX_{3}}$ caused by facile thermal ionization of excitons generated in the OIP layer, which has a low exciton binding energy. Spincoating of $\\mathbf{MAPbBr_{3}}$ solution creates a rough, nonuniform surface with many cuboids of large grain size (22), which leads to a substantial leakage current and large exciton diffusion length, $\\scriptstyle L_{\\mathrm{D}},$ that reduces CE in PeLEDs. To improve the CE of PeLEDs, the OIP grain size must be decreased, and OIP films should be flat and uniform. Smaller grains can spatially limit the $L_{\\mathrm{D}}$ of excitons or charge carriers and reduce the possibility of exciton dissociation into carriers. This fabrication goal differs from that of the OIP layers in solar cells, which should be dense films with large grain size to achieve facile exciton diffusion and dissociation. Thus, processes designed to achieve uniform OIP film morphology with large grain size in solar cells, such as solvent engineering (23, 24), are not applicable to PeLEDs, which require a small $L_{\\mathrm{D}}$ . \n\nHere, we report a systematic approach for achieving highly bright and efficient green PeLEDs with $\\mathrm{CE}=42.9\\$ cd $\\mathbf{A}^{-1}$ and external quantum efficiency $(\\mathrm{EQE})=8.53\\%$ , even in a simplified bilayer structure. These high efficiencies represent a ${\\tt>}20{,}000$ -fold increase compared with that of the control devices and are higher than the best EQEs of a previous report regarding visible PeLEDs using OIP films by factors of $>10.6$ (table S1 and fig. S1) (15). The high-efficiency PeLEDs were constructed on the basis of effective management of exciton quenching by a modified $\\mathbf{MAPbBr_{3}}$ emission layer that was achieved with (i) fine and controllable stoichiometry modification and (ii) optimized nanograin engineering by nanocrystal pinning (NCP) (fig. S2). Furthermore, we demonstrated a flexible PeLED using a self-organized conducting polymer (SOCP) anode and the first large-area PeLED (2 cm by 2 cm pixel). A fundamental problem that must be solved to achieve high CE in PeLEDs is minimizing the presence of metallic Pb atoms in $\\mathbf{MAPbBr_{3}}$ that limits the efficiency of PeLEDs. Metallic Pb atoms can emerge in $\\mathbf{MAPbBr_{3}}$ even if MABr and $\\mathrm{PbBr_{2}}$ are mixed in 1:1 (mol:mol) ratios because of the unintended losses of Br atoms or incomplete reaction between MABr and $\\mathrm{PbBr_{2}}$ (25). Excess $\\mathrm{\\Pb}$ atoms degrade luminescence by increasing the nonradiative decay rate and decreasing the radiative decay rate (26). Preventing the formation of metallic $\\mathrm{Pb}$ atoms was achieved by finely increasing the molar proportion of MABr by 2 to $7\\%$ in $\\mathbf{MAPbBr_{3}}$ solution (fig. S2A). Use of excess MABr suppressed exciton quenching and reduced the hole-injection barrier from SOCP layers (table S2) to $\\mathbf{MAPbBr_{3}}$ layers with decreased IE and greatly increased the steady-state photoluminescence (PL) intensity and PL lifetime of $\\mathbf{MAPbBr_{3}}$ films. We propose that the PL process in $\\mathbf{MAPbBr_{3}}$ nanograins depends on trap-assisted recombination at grain boundaries and radiative recombination inside the grains. Second, the CE in PeLEDs can be increased by decreasing $\\mathbf{MAPbBr_{3}}$ grain sizes, which improves uniformity and coverage of $\\mathbf{MAPbBr_{3}}$ nanograin layers and radiative recombination by confining the excitons in the nanograins (leading to small $\\scriptstyle L_{\\mathrm{D}},$ . An optimized NCP process (fig. S3) helped to change the morphology of $\\mathbf{MAPbBr_{3}}$ layers from scattered micrometer-sized cuboids to wellpacked nanograins with uniform coverage, which greatly reduced leakage current and increased CE. \n\nWe fabricated $\\mathbf{MAPbBr_{3}}$ films by spin-coating with stoichiometrically modified perovskite solutions on prepared glass/SOCPs or silicon wafer/ SOCPs substrates later used in devices (Fig. 1, A and B), and then characterized the films’ morphologies and optoelectronic properties. The solutions had different molar ratios of MABr to $\\mathrm{PbBr_{2}}$ (MABr: $\\mathrm{PbBr_{2}}~=~1.05{:}1$ , 1:1, or 1:1.05). To achieve uniform surface coverage and reduced grain size, we used NCP instead of normal spin coating (fig. S3). This process washed out the “good” solvents [dimethylformamide or dimethyl sulfoxide (DMSO)] and causes pinning of NCs by inducing fast crystallization. Chloroform was chosen as the solvent for NCP because a highly volatile nonpolar solvent is suitable to reduce the size and increase the uniformity of $\\mathbf{MAPbBr_{3}}$ grains by reducing solvent evaporation time. In addition, to further reduce grain size, we devised additive-based NCP (A-NCP), which uses an organic small molecule, $^{2,2^{\\prime},2^{\\prime\\prime}}$ -(1,3,5-benzinetriyl)-tris (1-phenyl-1-H-benzimidazole) (TPBI), as an additive to chloroform, whereas pure chloroform is used in solvent-based NCP (S-NCP). \n\nThe use of NCP affected film morphology (Fig. 2). Without NCP, micrometer-sized $\\mathbf{MAPbBr_{3}}$ cuboids were scattered on the SOCP layer (Fig. 2A). They were only interconnected with a few other cuboids, so a large amount of space remained uncovered. This high surface roughness and the formation of pinholes in OIP films result in formation of a bad interface with the electron transport layer and electrical shunt paths, and thus severely limit CE in PeLEDs. In contrast, when NCP was used, perfect surface coverage was obtained, and the $\\mathbf{MAPbBr_{3}}$ crystal morphology changed to a well-packed assembly of tiny grains ranging from 100 to $250\\mathrm{nm}$ (Fig. 2, B to E, and fig. S4). $\\mathbf{MAPbBr_{3}}$ grain size was very slightly affected by the stoichiometric modification of $\\mathbf{MAPbBr_{3}}$ solutions (Fig. 2, B to D, and fig. S4, A to C). Furthermore, $\\mathbf{MAPbBr_{3}}$ grain size was greatly reduced to 50 to $150~\\mathrm{nm}$ (average $\\mathbf{\\varepsilon}=99.7\\mathrm{nm}$ ) by A-NCP (Fig. 2E and fig. S4D). This reduction can be attributed to hindrance of crystal growth by TPBI molecules during crystal pinning. The thickness of $\\mathbf{MAPbBr_{3}}$ layer was ${\\sim}400~\\mathrm{nm}$ (Fig. 1B). \n\nThe crystal structures of $\\mathbf{MAPbBr_{3}}$ films were analyzed by measuring x-ray diffraction (XRD) patterns (Fig. 2F, fig. S5, and table S3). The XRD patterns of $\\mathbf{MAPbBr_{3}}$ films (1:1) exhibit peaks at $15.02^{\\circ};$ , 21.3°, $30.28^{\\circ};$ $33.92^{\\circ}$ , $37.24^{\\circ},$ , $43.28^{\\circ};$ and $46.00^{\\circ}$ that can be assigned to (100), (110), (200), (210), (211), (220), and (300) planes, respectively, by using Bragg’s law to convert the peak positions to interplanar spacings (Fig. 2F). The lattice parameter is in accordance with a previous report (19) and demonstrates that $\\mathbf{MAPbBr_{3}}$ films had a stable cubic $P m\\overline{{3}}m$ phase. Using the Scherrer equation, we calculated the crystallite size to be $24.4\\pm2.4\\mathrm{nm}$ , and the variation with stoichiometric change was not large (table S3). Because the crystallite sizes were much smaller than the apparent grain sizes (Fig. 2, A to E), we conclude that all grains consisted of many crystallites. The stoichiometric changes had very little effect on the peak positions (fig. S5A). Furthermore, ANCP did not change the peak positions when compared to S-NCP (fig. S5); this stability in positions indicates that the stoichiometric changes of $\\mathbf{MAPbBr_{3}}$ solution and the use of TPBI additive did not affect the crystal structure of $\\mathbf{MAPbBr_{3}}$ films. \n\nTo study chemical changes in the $\\mathbf{MAPbBr_{3}}$ layers fabricated with perovskite solutions of different stoichiometries, we conducted x-ray photoelectron spectroscopy (XPS). The survey spectra showed strong peaks of Br $\\mathrm{\\sim68~eV,}$ ), Pb (\\~138 and $\\mathrm{143\\:eV},$ , C $:(\\sim285\\mathrm{eV})$ , and $\\mathrm{~N~}(\\sim413\\ \\mathrm{eV})$ ; these results agree with values in previous reports (fig. S6A) (7, 25, 27, 28). Systematic deconvolution of Pb4f, Br3d, and N1s spectra into summations of Gaussian-Lorentzian curves revealed the nature of chemical bonds in $\\mathbf{MAPbBr_{3}}$ (figs. S6, B to D, and S7). We confirmed the gradual increase in MABr molar proportion in the films by observing the gradual increase in N1s peak intensities as MABr: $\\mathrm{PbBr_{2}}$ increased from 1:1.05 to 1.05:1 (fig. S7, C and D) and the gradual decrease in Br:Pb atomic ratio (supplementary text F). In the Pb4f spectra (fig. S6, B to F), large peaks were observed at ${\\sim}138.8\\$ and ${\\sim}143.6\\mathrm{eV}$ (caused by the spin orbit split) that correspond to $\\mathrm{Pb4f_{7/2}}$ and $\\mathrm{Pb}4\\mathrm{f}_{5/2}$ levels, respectively (25, 27, 28). Each of these peaks was associated with a smaller peak that was shifted to 1.8-eV lower binding energy; these small peaks can be assigned to metallic Pb (25, 27, 28). The height of peaks that represent metallic Pb decreased as MABr: $\\mathrm{PbBr_{2}}$ increased from 1:1.05 to 1:1 (fig. S6, E and F); this peak was absent in the film with MABr: $\\mathrm{PbBr_{2}}=1.05{:}1$ (fig. S6F). This trend indicates that the presence of metallic Pb atoms on the films was successfully prevented by fine stoichiometry control. In contrast, the high peak intensity of the metallic Pb peak in the films with MABr: $\\mathrm{PbBr_{2}=1:1}$ and 1:1.05 suggests that numerous metallic $\\mathrm{\\Pb}$ atoms were formed on the film surfaces. \n\n![](images/1e92cf94468df149104d625f4479e02eafbda00b71e77ab8a7411244a6ab3478.jpg) \nFig. 1. Schematic illustrations of device structure and its cross-sectional scanning electron microscope (SEM) image, and energy band structure. (A) The device structure. (B) Crosssectional SEM image of PeLEDs. (C) Energy band diagram of PeLEDs, showing a decrease in IE with increasing MABr molar proportion. \nFig. 2. SEM images and XRD patterns of $\\mathsf{M A P b B r}_{3}$ layers. SEM images of MAPbBr3 layers of (A) MABr: $\\mathsf{P b B r}_{2}=1{:}1$ without NCP, (B) 1:1.05, (C) 1:1, (D) 1.05:1 with S-NCP, and (E) 1.05:1 with A-NCP. (F) XRD patterns of ${\\mathsf{M A P b}}{\\mathsf{B}}{\\mathsf{r}}_{3}$ nanograin layers with MABr: ${\\tt b b r}_{2}=1:1.05$ , 1:1, and 1.05:1. \n\nWe measured the work functions (WFs) and IEs of the $\\mathbf{MAPbBr_{3}}$ films using ultraviolet photoelectron spectroscopy (UPS) (fig. S8). The WFs were obtained by subtracting the energies at secondary cut-offs of the UPS spectra from the ultraviolet radiation energy of $21.2\\ \\mathrm{eV}$ when a Fermi level of $0\\:\\mathrm{eV}$ was the common reference for all energies. The IEs were determined by adding the WF (fig. S8A) to the energy offset between WFs and IEs of $\\mathbf{MAPbBr_{3}}$ (fig. S8B) (29). The IE gradually decreased with increasing MABr molar proportion from 6.01 eV in the film with MABr: $\\mathrm{\\cdotPbBr_{2}}=1{:}1.05$ to $5.86\\mathrm{eV}$ in the film with MABr $\\mathrm{\\cdotPbBr_{2}=1.1{:}1}$ (Fig. 1C and table S4). \n\nThe gradual decrease in IEs with decreasing $\\mathrm{PbBr_{2}}$ molar proportion can be understood on the basis of the IE being greater in $\\mathrm{PbBr_{2}}$ than in $\\mathbf{MAPbBr_{3}}$ (30). In PeLEDs, this decrease can help alleviate hole-injection barriers from SOCP layers to $\\mathbf{MAPbBr_{3}}$ layers (Fig. 1C). \n\nThe luminescent properties of the $\\mathbf{MAPbBr_{3}}$ films were investigated by steady-state PL measurement (Fig. 3A). We carried out the measurement using a spectrofluorometer with excitation from monochromatic light with a wavelength of $405~\\mathrm{nm}$ (xenon lamp). The $\\mathbf{MAPbBr_{3}}$ films fabricated from MABr: $\\mathrm{\\cdotPbBr_{2}}=1.05{:}1$ had $\\iota\\sim5.8$ times increase in PL intensity (Fig. 3A) compared with 1:1 films and had much higher PL quantum efficiency (PLQE; $36\\%$ versus $3\\%$ ). In addition, the reduction in grain size with A-NCP versus S-NCP increased the PL intensity by ${\\sim}2.8$ times. The PL intensity of the films with MABr: ${\\mathrm{Pb}}{\\mathrm{Br}}_{2}=$ 1:1.05 was greater than in those with MABr: $\\mathrm{PbBr_{2}=1:1}$ , although the $\\mathrm{PbBr_{2}}$ molar proportion had increased in the former. We suspect that this departure from the expected trend is due to $\\mathrm{Pb}\\mathrm{Br}_{2}$ -induced surface passivation of the film, which reduces nonradiative recombination at the trap sites (31). \n\nTable 1. Maximum CE of PeLEDs depending on NCP and the molar ratio of MABr:PbBr2. \n\n\n
MABr:PbBr2 NCP type Max. CE (cd A-1)
1.05:1 A-NCP42.9
1.07:1 S-NCP19.3
1.05:1 S-NCP21.4
1.03:1 S-NCP4.03
1.02:1 S-NCP0.457
1:1 S-NCP0.183
1:1.05 S-NCP4.87 ×10-2
1:1 WithoutNCP2.03 ×10-3
\n\nTo understand the kinetics of excitons and free carriers in $\\mathbf{MAPbBr_{3}}$ films and how the presence of metallic $\\mathrm{\\Pb}$ atoms affects the PL lifetime, we conducted time-correlated single-photon counting measurements (Fig. 3B). The PL decay curves were fitted with a bi-exponential decay model, in which the PL lifetime is considered as the summation of fast- and slow-decay components that give a short lifetime $\\uptau_{1}$ and a long lifetime $\\tau_{2},$ , respectively. To investigate the quality of quenching sites, we prepared the layers (MABr: $\\mathrm{Pb}{\\bf B}\\mathrm{r_{2}}=1.05{\\mathrm{:1)}}$ with and without sealing with a $50\\mathrm{-nm}$ -thick poly(methyl methacrylate) (PMMA) layer. The fraction $f_{2}$ of $\\tau_{2}$ decreased from 91 to $77\\%$ in the film without sealing (table S5). Oxygen and moisture can diffuse quickly into grain boundaries when the top \n\n![](images/3082e9bb4262f227559cd128bc36490531de8a64388a71d28c9121c3ef78cbe4.jpg) \nFig. 3. Steady-state PL spectra and lifetime. (A) Steady-state PL spectra of ${\\mathsf{M A P b}}{\\mathsf{B}}{\\mathsf{r}}_{3}$ nanograin layers with NCP type and varying molar ratio of MABr: $\\mathsf{P b B r}_{2}$ . (B) PL lifetime curves of ${\\mathsf{M A P b}}{\\mathsf{B}}{\\mathsf{r}}_{3}$ nanograin layers with varying molar ratio of MABr:PbB $\\boldsymbol{\\mathrm{r}}_{2}$ . Black line: instrument response function (IRF). \n\n![](images/cb59fd922398a4a66b19e8661995e9a6149e838762a93799cbf1454c611e755b.jpg) \nFig. 4. PeLED characteristics, EL spectra, and photograph of PeLED. (A and B) CE and luminance of PeLEDs based on S-NCP and MAPbBr3 nanograin emission layers with varying molar ratio of MABr:PbBr2 (■ 1.07:1, $\\cdot$ 1.05:1, ▲1.03:1, ▼1.02:1, ◀1:1, ▶1:1.05, ◆1:1 without NCP). (C and D) CE and luminance of PeLEDs based on A-NCP and MAPbBr3 nanograin emission layers. (E) EL spectra of PeLEDs. (F) Photograph of a flexible PeLED, and (G) its device structure. \n\nPMMA layer is not used; oxygen or moisture at grain boundaries provides quenching sites. The fast decay is related to trap-assisted recombination at grain boundaries, whereas the slow decay is related to radiative recombination inside the grains (fig. S9) (32). \n\nThis proposition was supported by analyzing the change in $\\boldsymbol{\\tau}$ and $f$ of $\\mathbf{MAPbBr_{3}}$ films with varying stoichiometric ratio. As MABr: $\\mathrm{PbBr_{2}}$ increased from 1:1 to 1.05:1, the average lifetime $\\tau_{\\mathrm{avg}}$ gradually increased from 12.2 to 51.0 ns (table S5). The short $\\tau_{\\mathrm{avg}}$ (12.2 ns) in the film with $\\mathrm{MABr{:}P b B r_{2}=1{:}1}$ originated from the substantial reduction in $\\tau_{2}$ . This implies that uncoordinated metallic $\\mathrm{\\Pb}$ atoms at grain boundaries inhibit radiative recombination and cause strong nonradiative recombination (fig. S9). The $\\mathbf{MAPbBr_{3}}$ films fabricated with $\\mathrm{PbBr_{2}}$ -rich perovskite solution (M $\\mathrm{\\DeltaLABr{:}P b B r_{2}=1{:}1.05}$ ) had a longer lifetime than films with MABr: $\\mathrm{PbBr_{2}=1:1,}$ possibly through $\\mathrm{PbBr_{2}}$ -induced surface passivation (31). We calculated the average $L_{\\mathrm{D}}$ using a model similar to that in a previous report (fig. S10) (33). The films ( $\\mathrm{\\backslash{uBr}:\\mathrm{{PbBr}_{2}=1.05:1}})$ underneath a PMMA layer exhibited a much smaller $L_{\\mathrm{D}}$ $\\mathrm{\\langle67nm\\rangle}$ than those previously reported $({\\mathrm{>}}1\\upmu\\mathrm{m})$ (34). We attribute this reduction in $L_{\\mathrm{D}}$ to the reduced grain sizes in which excitons are under stronger spatial confinement, thereby reducing dissociation and enhancing radiative recombination; this compensates the plausible adverse effect of larger grain boundary area $\\textcircled{6}$ . \n\nThe PeLED fabricated from the $\\mathbf{MAPbBr_{3}}$ solution (MABr: $\\mathrm{PbBr_{2}=1:1},$ without using NCP showed poor luminous characteristics (maximum $\\mathrm{CE}=2.03~\\times\\$ $10^{-3}\\mathrm{cd}\\mathrm{A}^{-1})$ , mainly owing to high leakage current (fig. S11). In contrast, maximum CE was substantially increased $(0.183\\mathrm{~cd~A}^{-1})$ when a fullcoverage uniform $\\mathbf{MAPbBr_{3}}$ nanograin layer $(\\mathrm{MABr{:}P b B r_{2}=1{:}1)}$ with decreased grain size was achieved with S-NCP, without stoichiometric modifications to avoid metallic Pb atoms (Fig. 4, A and B, and Table 1). The maximum CE was boosted to 21.4 cd $\\mathbf{A}^{-1}$ in the PeLEDs fabricated with perovskite solutions with excess MABr (1.07:1, 1.05:1, 1.03:1 and 1.02:1) (Fig. 4A and Table 1). As MABr: $\\mathrm{PbBr_{2}}$ increased from 1:1 to 1.05:1, the maximum CE varied from 0.183 to 21.4 cd $\\mathbf{A}^{-1}$ . \n\nWe further increased the CE of PeLEDs by using A-NCP. The PeLEDs based on A-NCP had a maximum CE of $42.9\\operatorname{cd}\\mathrm{A}^{-1}$ (Fig. 4, C and D, and Table 1), which represents an EQE of $8.53\\%$ when the angular emission profile is considered (fig. S12). The EL spectra of PeLEDs were very narrow; full width at half maximum was ${\\sim}20\\mathrm{nm}$ for all spectra. This high color purity of OIP emitters shows great potential when used in displays (Fig. 4E). A pixel of the PeLED based on MABr: ${\\mathrm{Pb}}\\mathbf{B}\\mathbf{r}_{2}=$ 1.05:1 exhibited strong green-light emission (fig. S13A). Furthermore, the proposed processes and materials used therein are compatible with flexible and large-area devices; a high-brightness flexible PeLED (Fig. 4, F and G) and a large-area (2 cm by $2\\mathrm{cm}$ pixel) PeLED (fig. S13B) were fabricated. Our study reduces the technical gap between PeLEDs and OLEDs or quantum dot LEDs and is a big step toward the development of efficient next-generation emitters with high color purity and low fabrication cost based on perovskites. \n\n# REFERENCES AND NOTES \n\n1. W. S. Yang et al., Science 348, 1234–1237 (2015). \n2. M. Liu, M. B. Johnston, H. J. Snaith, Nature 501, 395–398 (2013). \n3. N. J. Jeon et al., Nature 517, 476–480 (2015). \n4. J.-H. Im, I.-H. Jang, N. Pellet, M. Grätzel, N.-G. Park, Nat. Nanotechnol. 9, 927–932 (2014). \n5. H. Kim, K.-G. Lim, T.-W. Lee, Energy Environ. Sci. 10.1039/ c5ee02194d (2015) \n6. Z.-K. Tan et al., Nat. Nanotechnol. 9, 687–692 (2014). \n7. Y.-H. Kim et al., Adv. Mater. 27, 1248–1254 (2015). \n8. D. B. Mitzi, Chem. Mater. 8, 791–800 (1996). \n9. M. R. Filip, G. E. Eperon, H. J. Snaith, F. Giustino, Nat. Commun. \n5, 5757 (2014). \n10. T. M. Koh et al., J. Phys. Chem. C 118, 16458–16462 (2014). \n11. G. E. Eperon et al., Energy Environ. Sci. 7, 982–988 (2014). \n12. R. L. Z. Hoye et al., Adv. Mater. 27, 1414–1419 (2015). \n13. N. K. Kumawat, A. Dey, K. L. Narasimhan, D. Kabra, ACS Photonics 2, 349–354 (2015). \n14. G. Li et al., Nano Lett. 15, 2640–2644 (2015). \n15. J. Wang et al., Adv. Mater. 27, 2311–2316 (2015). \n16. A. Sadhanala et al., Adv. Electron. Mater. 1, 1500008 (2015). \n17. J. C. Yu et al., Adv. Mater. 27, 3492–3500 (2015). \n18. N. K. Kumawat et al., ACS Appl. Mater. Interfaces 7, \n13119–13124 (2015). \n19. J. H. Noh, S. H. Im, J. H. Heo, T. N. Mandal, S. I. Seok, Nano Lett. 13, 1764–1769 (2013). \n20. I. B. Koutselas, L. Ducasse, G. C. Papavassiliou, J. Phys. Condens. Matter 8, 1217–1227 (1996). \n21. K. Tanaka et al., Solid State Commun. 127, 619–623 (2003). \n22. J. H. Heo, D. H. Song, S. H. Im, Adv. Mater. 26, 8179–8183 (2014). \n\n23. Z. Xiao et al., Adv. Mater. 26, 6503–6509 (2014). \n24. N. J. Jeon et al., Nat. Mater. 13, 897–903 (2014). \n25. R. Lindblad et al., J. Phys. Chem. C 119, 1818–1825 \n(2015). \n26. E. Dulkeith et al., Nano Lett. 5, 585–589 (2005). \n27. S. Gonzalez-Carrero, R. E. Galian, J. Pérez-Prieto, J. Mater. \nChem. A 3, 9187–9193 (2015). \n28. I. A. Shkrob, T. W. Marin, J. Phys. Chem. Lett. 5, 1066–1071 \n(2014). \n29. P. Schulz et al., Energy Environ. Sci. 7, 1377–1381 (2014). \n30. J. Kanbe, H. Onuki, R. Onaka, J. Phys. Soc. Jpn. 43, 1280–1285 (1977). \n31. Q. Chen et al., Nano Lett. 14, 4158–4163 (2014). \n32. D. Shi et al., Science 347, 519–522 (2015). \n33. S. D. Stranks et al., Science 342, 341–344 (2013). \n34. R. Sheng et al., J. Phys. Chem. C 119, 3545–3549 (2015). \n\n# ACKNOWLEDGMENTS \n\nThis work was partially supported by Samsung Research Funding Center of Samsung Electronics under Project Number SRFC-MA-1402-07. A.S. was partially supported by the Engineering and Physical Sciences Research Council (UK). All data are available in the main text and the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/350/6265/1222/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S13 \nTables S1 to S5 \nReferences (35–43) \n\n4 August 2015; accepted 22 October 2015 \n10.1126/science.aad1818 \n\n# LASER PHYSICS \n\n# Ultraviolet surprise: Efficient soft x-ray high-harmonic generation in multiply ionized plasmas \n\nDimitar Popmintchev,1 Carlos Hernández-García,1,2 Franklin Dollar,1 \nChristopher Mancuso,1 Jose A. Pérez-Hernández,3 Ming-Chang Chen,4 Amelia Hankla,1 \nXiaohui Gao,5 Bonggu Shim,5 Alexander L. Gaeta,5 Maryam Tarazkar,6 \nDmitri A. Romanov,7 Robert J. Levis,6 Jim A. Gaffney,8 Mark Foord,8 \nStephen B. Libby,8 Agnieszka Jaron-Becker,1 Andreas Becker,1 Luis Plaja,2 \nMargaret M. Murnane,1 Henry C. Kapteyn,1 Tenio Popmintchev1\\* \n\nHigh-harmonic generation is a universal response of matter to strong femtosecond laser fields, coherently upconverting light to much shorter wavelengths. Optimizing the conversion of laser light into soft x-rays typically demands a trade-off between two competing factors. Because of reduced quantum diffusion of the radiating electron wave function, the emission from each species is highest when a short-wavelength ultraviolet driving laser is used. However, phase matching—the constructive addition of $\\boldsymbol{\\mathsf{x}}$ -ray waves from a large number of atoms—favors longer-wavelength mid-infrared lasers. We identified a regime of high-harmonic generation driven by 40-cycle ultraviolet lasers in waveguides that can generate bright beams in the soft x-ray region of the spectrum, up to photon energies of 280 electron volts. Surprisingly, the high ultraviolet refractive indices of both neutral atoms and ions enabled effective phase matching, even in a multiply ionized plasma. We observed harmonics with very narrow linewidths, while calculations show that the $\\boldsymbol{\\mathsf{x}}$ -rays emerge as nearly time-bandwidth–limited pulse trains of \\~100 attoseconds. \n\nigh-order harmonic generation (HHG) results from the extreme quantum nonlinear response of atoms to intense laser fields: Atoms in the process of being ionized by an intense femtosecond laser pulse coherently emit short-wavelength light that can extend well into the soft x-ray region (1–6). When implemented in a phase-matched geometry to ensure that the laser and HHG fields both propagate at the same speed ${\\sim}c$ , HHG from \n\n# Overcoming the electroluminescence efficiency limitations of perovskite light-emitting diodes Himchan Cho et al. Science 350, 1222 (2015); DOI: 10.1126/science.aad1818 \n\nThis copy is for your personal, non-commercial use only. \n\nIf you wish to distribute this article to others, you can order high-quality copies for your colleagues, clients, or customers by clicking here. \n\nPermission to republish or repurpose articles or portions of articles can be obtained by following the guidelines here. \n\nThe following resources related to this article are available online at www.sciencemag.org (this information is current as of December 3, 2015 ): \n\nUpdated information and services, including high-resolution figures, can be found in the online \nversion of this article at: \nhttp://www.sciencemag.org/content/350/6265/1222.full.html \n\nSupporting Online Material can be found at: http://www.sciencemag.org/content/suppl/2015/12/02/350.6265.1222.DC1.html \n\nThis article cites 41 articles, 3 of which can be accessed free: http://www.sciencemag.org/content/350/6265/1222.full.html#ref-list-1 \n\nThis article appears in the following subject collections: Physics http://www.sciencemag.org/cgi/collection/physics " + }, + { + "id": "10.1103_PhysRevX.5.011029", + "DOI": "10.1103/PhysRevX.5.011029", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevX.5.011029", + "Relative Dir Path": "mds/10.1103_PhysRevX.5.011029", + "Article Title": "Weyl Semimetal Phase in Noncentrosymmetric Transition-Metal Monophosphides", + "Authors": "Weng, HM; Fang, C; Fang, Z; Bernevig, BA; Dai, X", + "Source Title": "PHYSICAL REVIEW X", + "Abstract": "Based on first-principle calculations, we show that a family of nonmagnetic materials including TaAs, TaP, NbAs, and NbP are Weyl semimetals (WSM) without inversion centers. We find twelve pairs of Weyl points in the whole Brillouin zone (BZ) for each of them. In the absence of spin-orbit coupling (SOC), band inversions in mirror-invariant planes lead to gapless nodal rings in the energy-momentum dispersion. The strong SOC in these materials then opens full gaps in the mirror planes, generating nonzero mirror Chern numbers and Weyl points off the mirror planes. The resulting surface-state Fermi arc structures on both (001) and (100) surfaces are also obtained, and they show interesting shapes, pointing to fascinating playgrounds for future experimental studies.", + "Times Cited, WoS Core": 1901, + "Times Cited, All Databases": 2042, + "Publication Year": 2015, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000351507700001", + "Markdown": "# Weyl Semimetal Phase in Noncentrosymmetric Transition-Metal Monophosphides \n\nHongming Weng,1,2,\\* Chen Fang,3 Zhong Fang,1,2 B. Andrei Bernevig,4 and Xi Dai1,2 1Beijing National Laboratory for Condensed Matter Physics, and Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China 2Collaborative Innovation Center of Quantum Matter, Beijing 100084, China 3Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA 4Department of Physics, Princeton University, Princeton, New Jersey 08544, USA (Received 12 January 2015; published 17 March 2015) \n\nBased on first-principle calculations, we show that a family of nonmagnetic materials including TaAs, TaP, NbAs, and NbP are Weyl semimetals (WSM) without inversion centers. We find twelve pairs of Weyl points in the whole Brillouin zone (BZ) for each of them. In the absence of spin-orbit coupling (SOC), band inversions in mirror-invariant planes lead to gapless nodal rings in the energy-momentum dispersion. The strong SOC in these materials then opens full gaps in the mirror planes, generating nonzero mirror Chern numbers and Weyl points off the mirror planes. The resulting surface-state Fermi arc structures on both (001) and (100) surfaces are also obtained, and they show interesting shapes, pointing to fascinating playgrounds for future experimental studies. \n\nDOI: 10.1103/PhysRevX.5.011029 \n\nSubject Areas: Condensed Matter Physics, Materials Science, Topological Insulators \n\n# I. INTRODUCTION \n\nMost topological invariants in condensed-matter noninteracting phases are defined on closed manifolds in momentum space. For gapped systems, both the Chern insulator and $Z_{2}$ topological insulator phases can be defined using the Berry phase and curvature in either the entire or half of the two-dimensional (2D) Brillouin zone (BZ), respectively [1,2]. A similar idea can be generalized to gapless metallic systems. In three-dimensional (3D) systems, besides the BZ, an important closed manifold in momentum space is a 2D Fermi surface (FS). Topological metals can be defined by Chern numbers of the singleparticle wave functions at the Fermi surface energies [3–5]. Such nonzero FS Chern numbers appear when the FS encloses a band-crossing point—the Weyl point—which can be viewed as a singular point of Berry curvature or “magnetic monopole” in momentum space [6–9]. Materials with such Weyl points near the Fermi level are called Weyl semimetals (WSM) [7–10]. \n\nWeyl points can only appear when the spin-doublet degeneracy of the bands is removed by breaking either time reversal $T$ or spacial inversion symmetry $P$ (in fact, Weyl points exist if the system does not respect $T\\cdot P$ ). In these cases, the low-energy single-particle Hamiltonian around a \n\nWeyl point can be written as a $2\\times2$ “Weyl equation,” which is half of the Dirac equation in three dimensions. According to the “no-go theorem” [11,12], for any lattice model, the Weyl points always appear in pairs of opposite chirality or monopole charge. The conservation of chirality is one of the many ways to understand the topological stability of the WSM against any perturbation that preserves translational symmetry: The only way to annihilate a pair of Weyl points with opposite chirality is to move them to the same point in BZ. Since generically the Weyls can sit far away from each other in the BZ, this requires large changes of Hamiltonian parameters, and the WSM is stable. The existence of Weyl points near the Fermi level will lead to several unique physical properties, including the appearance of discontinuous Fermi surfaces (Fermi arcs) on the surface [7–9], the Adler-Bell-Jackiw anomaly [10,13–15], and others [16,17]. \n\nThe first proposal to realize WSM in condensed-matter materials was suggested in Ref. [7] for ${\\mathrm{Rn}}_{2}{\\mathrm{Ir}}_{2}{\\mathrm{O}}_{7}$ pyrochlore with all-in/all-out magnetic structure, where 24 pairs of Weyl points emerge as the system undergoes the magnetic ordering transition. A relatively simpler system $\\mathrm{Hg}\\mathrm{Cr}_{2}\\mathrm{Se}_{4}$ [9] was then proposed by some of the present authors, where a pair of double-Weyl points due to quadratic band crossing appear when the system is in a ferromagnetic phase. Another proposal involves a finetuned multilayer structure of normal insulators and magnetically doped topological insulators [18]. These proposed WSM systems involve magnetic materials, where the spin degeneracy of the bands is removed by breaking timereversal symmetry. As mentioned, the WSM can also be generated by breaking the spatial inversion symmetry only, a method which has the following advantages. First, compared with magnetic materials, nonmagnetic WSM are much more easily studied experimentally using angle-resolved photo emission spectroscopy (ARPES) as alignment of magnetic domains is no longer required. Second, without the spin exchange field, the unique structure of Berry curvature leads to very unusual transport properties under a strong magnetic field, unspoiled by the magnetism of the sample. \n\nCurrently, there are several representative proposals for WSM generated by inversion symmetry breaking. The first one is a superlattice system formed by alternatively stacking normal and topological insulators [19,20]. The second one involves tellurium or selenium crystals under pressure [21]. The third one is the solid solutions of $A\\mathbf{B}\\mathbf{i}_{1-x}\\mathbf{S}\\mathbf{b}_{x}\\mathrm{Te}_{3}$ $\\boldsymbol{\\mathrm{\\acute{A}}}=\\mathrm{La}$ and Lu) [22] and $\\mathrm{TlBi}(\\mathrm{S}_{1-x}R_{x})_{2}$ $R={\\mathrm{Se}}$ or Te) [23] tuned around the topological transition points [24]. The fourth one is a model based on zinc-blende structure [25] with the fine-tuning of the relative strength between SOC and the inversion symmetry-breaking term. But none of the above proposals has been realized experimentally. In the present study, we predict that TaAs, TaP, NbAs, and \n\nNbP single crystals are natural WSM, and each of them possesses a total of 12 pairs of Weyl points. Compared with the existing proposals, this family of materials is completely stoichiometric and, therefore, are easier to grow and measure. Unlike in the case of pyrochlore iridates and $\\mathrm{Hg}\\mathrm{Cr}_{2}\\mathrm{Se}_{4}$ , where inversion is still a good symmetry and the appearance of Weyl points can be immediately inferred from the product of the parities at all the time-reversal invariant momenta (TRIM) [26–28], in the TaAs, family parity is no longer a good quantum number. However, the appearance of Weyl points can still be inferred by analyzing the mirror Chern numbers (MCN) [29,30] and $Z_{2}$ indices [26,31] for the four mirror and time-reversal invariant planes in the BZ. Similar to many other topological materials, the WSM phase in this family is also induced by a type of band-inversion phenomena, which, in the absence of spin-orbit coupling (SOC), leads to nodal rings in the mirror plane. Once the SOC is turned on, each nodal ring will be gapped with the exception of three pairs of Weyl points leading to fascinating physical properties which include complicated Fermi arc structures on the surfaces. \n\n![](images/10fd52540d289115c425964baa785d26fa831fe9443955c50c5922c2a8ceaef6.jpg) \nFIG. 1. Crystal structure and Brillouin zone (BZ). (a) The crystal symmetry of TaAs. (b) The bulk BZ and the projected surface BZ for both (001) and (100) surfaces. (c) The band structure of TaAs calculated by GGA without including the spin-orbit coupling. (d) The band structure of TaAs calculated by GGA with the spin-orbit coupling. \n\n# II. CRYSTAL STRUCTURE AND CALCULATION METHODS \n\nAs all four mentioned materials share very similar band structures, in the rest of the paper, we will choose TaAs as the representative material to introduce the electronic structures of the whole family. The experimental crystal structure of TaAs [32] is shown in Fig. 1(a). It crystalizes in body-centered-tetragonal structure with nonsymmorphic space group $I4_{1}m d$ (No. 109), which lacks inversion symmetry. The measured lattice constants are $a=b=$ $3.4348\\mathrm{~\\AA~}$ and $c=11.641\\mathrm{~\\AA~}$ . Both Ta and As are at $4a$ Wyckoff position $(0,0,u)$ with $u=0$ and 0.417 for Ta and As, respectively. We have employed the software package OpenMX [33] for the first-principles calculation. It is based on norm-conserving pseudopotential and pseudo-atomic localized basis functions. The choice of pseudopotentials, pseudo-atomic orbital basis sets $(\\mathrm{Ta9.0}\\cdotp$ - $\\mathrm{s2p2d2f1}$ and $\\mathrm{As9.0-s2p}2\\mathrm{d}1\\rrangle$ ), and the sampling of BZ with a $10\\times10\\times10$ grid have been carefully checked. The exchange-correlation functional within a generalized gradient approximation (GGA) parametrized by Perdew, Burke, and Ernzerhof has been used [34]. After full structural relaxation, we obtain the lattice constants $a=b=$ $3.4824\\mathring\\mathrm{A}$ , $c=11.8038\\mathrm{~\\AA~}$ and optimized $u=0.4176$ for the As site, in very good agreement with the experimental values. To calculate the topological invariant such as MCN and surface states of TaAs, we have generated atomiclike Wannier functions for $\\mathrm{Ta}~5d$ and As ${4p}$ orbitals using the scheme described in Ref. [35]. \n\n# III. RESULTS \n\n# A. Band structures with and without spin-orbit coupling \n\nWe first obtain the band structure of TaAs without SOC by GGA and plot it along the high-symmetry directions in Fig. 1(c). We find clear band inversion and multiple band crossing features near the Fermi level along the ZN, ZS, and ΣS lines. The space group of the TaAs family contains two mirror planes, namely, $M_{x}$ and $M_{y}$ [shaded planes in Fig. 1(b)] and two glide mirror planes, namely, $M_{x y}$ and $M_{-x y}$ [illustrated by the dashed lines in Fig. 1(b)]. The plane spanned by $Z,\\ \\mathrm{N}.$ , and $\\Gamma$ points is invariant under mirror $M_{y}$ , and the energy bands within the plane can be labeled by mirror eigenvalues $\\pm1$ . Further symmetry analysis shows that the two bands that cross along the $Z$ to $\\mathbf{N}$ line belong to opposite mirror eigenvalues, and hence, the crossing between them is protected by mirror symmetry. Similar band crossings can also be found along other high-symmetry lines in the ZNΓ plane, i.e., the ZS and NS lines. Altogether, these band crossing points form a “nodal ring” in the ZNΓ plane as shown in Fig. 2(b). Unlike for the situation in the ZNΓ plane, in the two glide mirror planes \n\n$M_{x y}$ and $M_{-x y.}$ ), the band structure is fully gapped, with a minimum gap of roughly $0.5\\ \\mathrm{eV}.$ \n\nThe analysis of orbital character shows that the bands near the Fermi energy are mainly formed by Ta $5d$ orbitals, which have large SOC. Including SOC in the first-principle calculation leads to a dramatic change of the band structure near the Fermi level, as plotted in Fig. 1(d). At first glance, it seems that the previous band crossings in the ZNΓ plane are all gapped, with the exception of one point along the ZN line. Detailed symmetry analysis reveals that the bands $^{66}2^{,9}$ and “3” in Fig. 1(d) belong to opposite mirror eigenvalues, indicating the almost-touching point along the ZN line is completely accidental. In fact, there is a small gap of roughly $3\\mathrm{meV}$ between bands “2” and “3” as illustrated by the inset of Fig. 1(d). The ZNΓ plane then becomes fully gapped once SOC is turned on. \n\n# B. Topological invariants for mirror plane and Weyl points \n\nSince the material has no inversion center, the usual parity condition [26–28] cannot be applied to predict the existence of WSM. We then resort to another strategy. As previously mentioned, the space group of the material provides two mirror planes $M_{x}$ and $M_{y.}$ ), where the MCN can be defined. If a full gap exists for the entire BZ, the MCN would directly reveal whether this system is a topological crystalline insulator or not. Interestingly, as shown below, if the system is not fully gapped, we can still use the MCN to find out whether the material hosts Weyl points in the BZ or not. Besides the two mirror planes, we have two additional glide mirror planes $(M_{x y}$ and $M_{-x y})$ . Although the MCN is not well defined for the glide mirror planes, the $Z_{2}$ index is still well defined here as these planes are time-reversal invariant. We then apply the Wilson-loop method to calculate the MCNs for the two mirror planes and $Z_{2}$ indices for the two glide mirror planes. Here, we just briefly describe the essence of this method. For a more detailed explanation of the method, please refer to Refs. [5,37]. A Wilson loop is an arbitrary closed $k$ -point loop in BZ, evaluated around which, the occupied Bloch functions acquire a total Berry phase $\\theta(w)$ , with $w$ being the loop index. One can define a series of parallel Wilson loops $w$ to fully cover a closed 2D manifold in 3D momentum space, such as a cut plane in BZ or a closed FS as stated in the beginning of this paper. Then, the evolution of $\\theta(\\boldsymbol{w})$ along these parallel Wilson loops (it turns out to be a 1D problem) gives information on the band-structure topology on the closed 2D manifold. For example, to determine the MCNs for the mirror plane $M_{x}$ , we define Wilson loops along the $k_{x}$ direction with fixed $k_{z}$ . All the occupied bands at $k$ points in this plane can be classified into two groups according to their eigenvalues under mirror operation, $i$ or $-i$ . Taking those having eigenvalue $i$ , the evolution of Berry phases along the periodic $k_{z}$ direction can be obtained, and the MCN is simply its winding number. \n\nThe results are plotted in Fig. 2(d), which shows that MCN is 1 for the ZNΓ plane $(M_{y})$ and the $Z_{2}$ index is even or trivial for the ZXΓ plane $(M_{x y})$ . Then, if we consider the (001) surface, which is invariant under the $M_{y}$ mirror. The nontrivial helical surface modes will appear because of the nonzero MCN in the ZNΓ plane, which generates a single pair of FS cuts along the projective line of the ZNΓ plane [the $x$ axis in Fig. 2(c)]. Whether these Fermi cuts will eventually form a single closed Fermi circle or not depends on the $Z_{2}$ index for the two glide mirror planes, which are projected to the dashed blue lines in Fig. 2(c). Since the $Z_{2}$ indices for the glide mirror planes are trivial, as confirmed by our Wilson-loop calculation plotted in Fig. 2(d), there are no protected helical edge modes along the projective lines of the glide mirror planes [dashed blue lines in Fig. 2(c)], and the Fermi cuts along the $x$ axis in Fig. 2(c) must end somewhere between the $x$ axis and the diagonal lines [dashed blue lines in Fig. 2(c)]. In other words, they must be Fermi arcs, indicating the existence of Weyl points in the bulk band structure of TaAs. \n\nFrom the above analysis of the MCN and $Z_{2}$ index of several high-symmetry planes, we can conclude that Weyl points exist in the TaAs band structure. We now determine the total number of Weyl points and their exact positions. This is a hard task, as the Weyl points are located at generic $k$ points without any little-group symmetry. For this purpose, we calculate the integral of the Berry curvature on a closed surface in $k$ space, which equals the total chirality of the Weyl points enclosed by the given surface. Because of the fourfold rotational symmetry and mirror planes that characterize TaAs, we only need to search for the Weyl points within the reduced BZ—one-eighth of the whole BZ. We first calculate the total chirality or monopole charge enclosed in the reduced BZ. The result is 1, which guarantees the existence of, and odd number of, Weyl points. To determine precisely the location of each Weyl point, we divide the reduced BZ into a very dense $k$ -point mesh and compute the Berry curvature or the “magnetic field in momentum space” [35,38] on that mesh, as shown in Fig. 3. From this, we can easily identify the precise position of the Weyl points by searching for the “source” and “drain” points of the “magnetic field.” The Weyl points in TaAs are illustrated in Fig. 2(a), where we find 12 pairs of Weyl points in the vicinity of what used to be, in the SOC-free case, the nodal rings on two of the mirrorinvariant planes. For each of the mirror-invariant planes, after turning on SOC, the nodal rings will be fully gapped within the plane, but isolated gapless nodes slightly off plane appear, as illustrated in Fig. 2(b). Two pairs of Weyl points are located exactly in the $k_{z}=0$ plane, and another four pairs of Weyl points are located off the $k_{z}=0$ plane. Considering the fourfold rotational symmetry, it is then easy to understand that there are a total of 12 pairs of Weyl points in the whole BZ. The Weyl points in the $k_{z}=0$ plane are about $2{\\mathrm{~meV}}$ above the Fermi energy and form eight tiny hole pockets, while the others are about $21\\mathrm{\\meV}$ below the Fermi level to form 16 electron pockets. The appearance of Weyl points can also be derived from a $k\\cdot p$ model with different types of mass terms induced by SOC, which will be introduced in detail in the Appendix. The band structures for the other three materials—TaP, NbAs, and NbP—are very similar. The precise positions of the Weyl points for all these materials are summarized in Table. I. \n\n![](images/fef6470d5f0297e632f09663b597f002d2cbdc0455ec010f52ca66d4df89485e.jpg) \nFIG. 2. Nodal rings and Weyl points distribution, as well as $Z_{2}$ and MCN for mirror planes. (a) 3D view of the nodal rings (in the absence of SOC) and Weyl points (with SOC) in the BZ. (b) Side view from [100] and (c) top view from [001] directions for the nodal rings and Weyl points. Once the SOC is turned on, the nodal rings are gapped and give rise to Weyl points off the mirror planes (see movie in Supplemental Material [36]). (d) Top panel: Flow chart of the average position of the Wannier centers obtained by Wilson-loop calculation for bands with mirror eigenvalue $i$ in the mirror plane ZNΓ. (d) Bottom panel: The flow chart of the Wannier centers obtained by Wilson-loop calculation for bands in the glide mirror plane ZXΓ. There is no crossing along the reference line (the dashed line), indicating the $Z_{2}$ index is even. \n\n![](images/f39ad2bc7f01821023e7054a3d1af6623dc5b6f80d44635a04afffb84554ca9d.jpg) \nFIG. 3. Berry curvature from pairs of Weyl points. (a) The distribution of the Berry curvature for the $k_{z}=0$ plane, where the blue and red dots denote the Weyl points with chirality of $+1$ and $^{-1}$ , respectively; (b) same as (a) but for the $k_{z}=0.592\\pi$ plane. The insets show the 3D view of hedgehoglike Berry curvature near the two selected Weyl points. \n\nTABLE I. The two nonequivalent Weyl points in the xyz coordinates shown in Fig. 1(b). The position is given in units of the length of $\\Gamma{-}\\Sigma$ for $x$ and $y$ and of the length of Γ-Z for z. \n\n\n
Weyl node 1Weyl node 2
TaAs(0.949, 0.014, 0.0)(0.520, 0.037, 0.592)
TaP(0.955, 0.025, 0.0)(0.499, 0.045, 0.578)
NbAs(0.894, 0.007, 0.0)(0.510, 0.011, 0.593)
NbP(0.914, 0.006, 0.0)(0.494, 0.010, 0.579)
\n\n# C. Fermi arcs and surface states \n\nUnique surface states with unconnected Fermi arcs can be found on the surface of a WSM. These can be understood in the following way: For any surface of a WSM, we can consider small cylinders in the momentum space parallel to the surface normal. In the 3D BZ, these cylinders will be cut by the zone boundary, and their topology is equivalent to that of a closed torus rather than that of open cylinders. If a cylinder encloses a Weyl point, by Stokes theorem, the total integral of the Berry curvature (Chern number) of this closed torus must equal the total “monopole charge” carried by the Weyl point(s) enclosed inside. On the surface of the material, such a cylinder will be projected to a cycle surrounding the projection point of the Weyl point, and a single Fermi surface cut stemming from the chiral edge model of the 2D manifold with Chern number 1 (or $^{-1}$ ) must be found on that circle. By varying the radius of the cylinder, it is easy to show that such FSs must start and end at the projection of two (or more) Weyl points with different “monopole charge”; i.e., they must be “Fermi arcs” [7,9,16]. In the TaAs materials family, on most of the common surfaces, multiple Weyl points will be projected on top of each other, and we must generalize the above argument to multiple projections of Weyl points. It is easy to prove that the total number of surface modes at the Fermi level crossing a closed circle in surface BZ must equal the sum of the “monopole charge” of the Weyl points inside the 3D cylinder that projects to the given circle. Another fact controlling the behavior of the surface states is the MCN introduced in the previous discussion, which limits the number of FSs cutting certain projection lines of the mirror plane (when the corresponding mirror symmetries are still preserved on the surface). \n\nBy using the Green’s function method [5] based on the tight-binding (TB) Hamiltonian generated by the previously obtained Wannier functions, we have computed the surface states for both (001) and (100) surfaces. They are plotted in Fig. 4 together with the FS plots. On the (001) surface, the crystal symmetry is reduced to $C_{2v}$ , leading to different behavior for the surface bands around the $\\bar{X}$ and $\\bar{Y}$ points, respectively. Along the $\\bar{\\Gamma}\\bar{-}\\bar{X}$ or $\\bar{\\Gamma}{-}\\bar{Y}$ lines, there are two FS cuts with the opposite Fermi velocity satisfying the constraint from the MCN for the ΓZN plane. In addition to the MCN, the possible “connectivity pattern” of the Fermi arcs on the surface has to link different projection points of the Weyl nodes in a way that obeys the chirality condition discussed in the above paragraph. For the (001) surface of TaAs, the connectivity pattern of the Fermi arcs that satisfy all the conditions discussed is not unique. However, due to the fact that all the projective points on the (001) surface are generated either by a single Weyl point or by two Weyl points with the same chirality, the appearance of “Fermi arcs” on the (001) surface is guaranteed. The actual Fermiarc connectivity pattern for the (001) surface is shown in Fig. 4(b), obtained by our ab initio calculation on a nonrelaxed surface described by the TB model. Changes of surface potentials or the simple relaxation of the surface charge density might lead to transitions of the Fermi-arc connectivity pattern and may result in topological Fermiarc phase transitions on the surface. A very interesting point of the (001) surface states are the extremely long Fermi arcs that cross the zone boundary along the $\\bar{X}$ to $\\bar{M}$ line. \n\n![](images/d33590a1f21ce2e9071b70329d3cd5d1c09f05a6f25acb778bebd305c49e5595.jpg) \nFIG. 4. Fermi arcs in the surface states. (a) The Surface states for (001) surface; (b) the corresponding fermi surfaces on (001) surfaces; (c) The Surface states for (100) surface. The dots illustrate the projective points of the bulk Weyl points on the surfaces, where the color represents the chirality of the Weyl points (blue for positive and green for negative), small dot represents the single projected Wely point, and large dot represents two Weyl points with same chirality projecting on top of each other. (d) the corresponding fermi surfaces on (100) surfaces. All the dots here are the projective points for a pair of Weyl points with opposite chirality. \n\nCompared to other proposed WSM materials, the Fermi arcs in TaAs families are much longer, which greatly facilitates their detection in experiments. \n\nCompared to the (001) surface, the (100) surface states of TaAs are much more complicated, as shown in Figs. 4(c) and 4(d). The biggest difference between the (100) and (001) surfaces is that all the projected Weyl points on the (100) surface are formed by a pair of Weyl points with opposite chirality, which does not guarantee (but does not disallow) the existence of the Fermi arcs. The only constraint for the (100) surface states is the nonzero MCN of the ΓZN plane, which generates a pair of chiral modes along the $\\bar{\\Gamma}\\bar{Y}$ line, the projection of the mirror plane, as illustrated in Fig. 4(d). \n\n# IV. DISCUSSION \n\nIn summary, a family of nonmagnetic WSM materials is proposed in the present paper. Each material in this family contains 12 pairs of Weyl points, which appear because of the lack of an inversion center in the crystal structure and can be derived from the nonzero MCN for two of the mirror-invariant planes in the BZ. The surface states of these materials form quite complicated patterns for the Fermi surfaces, which are determined by both the chirality distribution of the Weyl points and the MCNs for the mirror-invariant planes. \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge helpful discussions with A. Alexandradinata and N. P. Ong, and thank Rui Yu for help in plotting Fig. 3. This work was supported by the National Natural Science Foundation of China, the 973 program of China (No. 2011CBA00108 and No. 2013CB921700), and the “Strategic Priority Research Program (B)” of the Chinese Academy of Sciences (No. XDB07020100). The calculations were preformed on TianHe-1(A), the National Supercomputer Center in Tianjin, China. B. A. B. acknowledges support from ARO MURI on topological insulators, Grant No. W911NF-12-1-0461, along with NSF CAREER DMR-0952428, ONR-N00014-11-1-0635, and the Packard Foundation. \n\n# APPENDIX: $\\pmb{k}\\cdot\\pmb{p}$ MODEL OF A NODAL RING AND THE APPEARANCE OF WEYL POINTS DUE TO SPIN-ORBIT COUPLING \n\nWe perform a $k\\cdot p$ analysis in the vicinity of the $\\Sigma$ point in the 3D BZ. We show that (1) a nodal ring (a closed line of band-touching points) is protected in the presence of a mirror-reflection symmetry and SU(2) spin-rotation symmetry (when spin-orbit coupling is absent), and (2) when SOC is turned on and all crystalline symmetries are preserved, the nodal ring may be partially gapped with several distinct possibilities: (i) Weyl nodes on the (001) plane, (ii) Weyl nodes away from the (001) plane, and (iii) nodal rings on the (010) plane and (iv) full gap. The realization of these different possibilities strongly depends on the specific form of the SOC terms. \n\nThe nodal ring around the $\\Sigma$ point can be modeled by a two-band $k\\cdot p$ theory, in the absence of SOC: \n\n$$\nH_{0}(\\mathbf{k})=\\sum_{i=x,y,z}d_{i}(\\mathbf{k})\\sigma_{i},\n$$ \n\nwhere $d_{i}(\\mathbf{k})$ are real functions and $\\mathbf{k}=\\left(k_{x},k_{y},k_{z}\\right)$ are three components of the momentum $\\mathbf{k}$ relative to the $\\Sigma$ point along [100], [010], and [001] axes, respectively. In Eq. (A1), we have ignored the kinetic term proportional to the identity matrix, as it is irrelevant in studying the band touching. The mirror-reflection symmetry, denoted by $M_{010}$ , is represented by $M=\\sigma_{z}$ : In the absence of SOC, we can choose a mirror symmetry that squares to unity. The form of the mirror operator is chosen such that the two bands have opposite mirror eigenvalues, information obtained from the ab initio calculation. The mirror reflection dictates that \n\n$$\nM H_{0}(k_{x},k_{y},k_{z})M^{-1}=H_{0}(k_{x},-k_{y},k_{z}),\n$$ \n\nwhich translates into \n\n$$\nd_{x,y}(k_{x},k_{y},k_{z})=-d_{x,y}(k_{x},-k_{y},k_{z}),\n$$ \n\n$$\nd_{z}(k_{x},k_{y},k_{z})=d_{z}(k_{x},-k_{y},k_{z}).\n$$ \n\nEquation (A3) states that on the plane $k_{y}=0$ , only $d_{z}$ is nonzero, and hence, generically, the equation $\\bar{d_{z}}(k_{x},0,k_{z})=0$ will have codimension one, i.e., a nodal line solution. Symmetry-preserving perturbations involve gradually changing the forms of the $d_{i}$ ’s without violating Eq. (A3), so the nodal ring is robust against them. \n\nAnother symmetry is present at the $\\Sigma$ point: a twofold rotation $C_{2}$ about the [001] axis followed by time-reversal symmetry. The symmetry is present because the rotation sends the $\\Sigma$ point to its time-reversal partner, and a further time-reversal operation sends it back. This symmetry may be represented by $C_{2T}=U_{T}K_{\\sun}$ , where $U_{T}$ is any symmetric and unitary matrix and $K$ is complex conjugation. Without SOC, the rotation about the [001] axis and the reflection about the (010) plane commute with each other, so we require \n\n$$\n\\left[\\sigma_{z},K U_{T}\\right]=0,\n$$ \n\nand we may choose $U_{T}=\\sigma_{z}$ . This symmetry places additional constraints on the $d_{i}$ ’s: \n\n$$\nH_{0}(k_{x},k_{y},k_{z})=\\sigma_{z}H_{0}^{*}(k_{x},k_{y},-k_{z})\\sigma_{z}\n$$ \n\nor \n\n$$\n\\begin{array}{r}{d_{y,z}(k_{x},k_{y},k_{z})=d_{y,z}(k_{x},k_{y},-k_{z}),}\\\\ {d_{x}(k_{x},k_{y},k_{z})=-d_{x}(k_{x},k_{y},-k_{z}).}\\end{array}\n$$ \n\nEquations (A3) and (A7) determine the general form of our $k\\cdot p$ model. \n\nNow we consider adding spin-orbit coupling terms while respecting the symmetries at the $\\Sigma$ point. We first need to determine the matrix representations of the generators of the little group, i.e., $M_{010}$ and $C_{2}*T$ . Considering spin degrees of freedom, we know that (i) a mirror reflection consists of a spatial reflection and a twofold spin rotation about the axis perpendicular to the reflection plane, (ii) a twofold rotation involves a spatial twofold rotation and a twofold spin rotation about the same axis, and (iii) timereversal symmetry involves complex conjugation and a flipping of the spin. Following these facts, we obtain the matrix representations \n\n$$\n\\begin{array}{c}{{M=i\\sigma_{z}\\otimes s_{y},}}\\\\ {{{}}}\\\\ {{C_{2T}=K\\sigma_{z}\\otimes s_{x}.}}\\end{array}\n$$ \n\nNotice that now $M^{2}=-1$ and $C_{2T}^{2}=1$ , as needed. With spin degrees of freedom, each band in the previous spinorbit coupling free model in Eq. (A1) becomes two bands, and the nodal ring becomes a four-band crossing. In the vicinity of the nodal ring, the addition of SOC is equivalent to adding coupling between different spin components, i.e., “mass terms,” to the previous model. Here, the name mass term simply means that these terms are not required to vanish at the nodal ring by any symmetry. \n\nThe symmetry of the nodal ring is just a mirror reflection. The mass terms hence must commute with mirror symmetry, and a generic term on the $k_{y}=0$ plane is given by \n\n$$\n\\begin{array}{c}{{H_{m}=m_{1}({\\bf k})s_{y}+m_{2}({\\bf k})\\sigma_{z}s_{y}+m_{3}({\\bf k})\\sigma_{x}s_{x}+m_{4}({\\bf k})\\sigma_{x}s_{z}}}\\\\ {{{}}}\\\\ {{+m_{5}({\\bf k})\\sigma_{y}s_{z}+m_{6}({\\bf k})\\sigma_{y}s_{x}.}}\\end{array}\n$$ \n\nNote that these mass terms are, in general, $\\mathbf{k}$ dependent, as their values may change as $\\mathbf{k}$ moves along the nodal ring, but the $C_{2}*T$ symmetry makes them satisfy (on the $k_{y}=0$ plane) \n\n$$\n\\begin{array}{r l}&{m_{1,2,4,6}(k_{x},0,k_{z})=m_{1,2,4,6}(k_{x},0,-k_{z})=m_{1,2,4,6}(k_{x},0,k_{z}),}\\\\ &{\\quad m_{3,5}(k_{x},0,k_{z})=-m_{3,5}(k_{x},0,-k_{z})=m_{3,5}(k_{x},0,k_{z}).}\\end{array}\n$$ \n\nA complete analysis of the band crossing in the presence of all six mass terms is unavailable as the analytic expressions for the dispersion are involved. However, one may see the qualitative role played by each mass term by analyzing them separately. From Eq. (A10), we see that $m_{3,5}$ are odd under $k_{z}\\rightarrow-k_{z}$ , while the others are even. This indicates that only $m_{1,2,4,6}$ terms are responsible for band crossings appearing on the $k_{z}=0$ plane, while the band crossings away from that plane are attributed mainly to the presence of $m_{3,5}$ terms. \n\nAt the $k_{y}=0$ plane, $m_{1,2}$ terms commute with $H_{0}$ , so these terms, if of small strength, will split the doubly degenerate nodal ring into two singly degenerate rings but not open gaps. The equations for the two new rings are given by \n\n$$\nd_{z}(k_{x},0,k_{z})\\pm m_{1,2}=0.\n$$ \n\nOne should note that when the $m_{1}$ term ( $\\cdot m_{2}$ term) is added, the two rings are the crossing between two bands with the same (opposite) mirror eigenvalues. Therefore, the two rings from adding the $m_{1}$ term are purely accidental, and the two rings from adding the $m_{2}$ term are protected by mirror symmetry. \n\nNext, we discuss the effect of the $m_{4,6}$ terms, which should, in combination, give rise to the pair of Weyl nodes on the $k_{z}=0$ plane shown in Fig. 2. The dispersion after adding the $m_{4,6}$ terms is \n\n$$\nE({\\bf k})=\\sqrt{d^{2}+m_{4}^{2}+m_{6}^{2}\\pm2\\sqrt{m_{4}^{2}d_{x}^{2}+m_{6}^{2}d_{y}^{2}+m_{4}^{2}m_{6}^{2}}},\n$$ \n\nwhere $d^{2}=d_{x}^{2}+d_{y}^{2}+d_{z}^{2}.$ . With some straightforward algebraic work, it can be shown that the equation $E({\\bf k})=0$ (band touching) is equivalent to the following equations: \n\n$$\n\\begin{array}{l}{{d_{x}=d_{z}=0,}}\\\\ {{d_{y}^{2}=m_{6}^{2}-m_{4}^{2}.}}\\end{array}\n$$ \n\nWhen $\\vert m_{6}\\vert>\\vert m_{4}\\vert$ , these equations have at least one pair of solutions on the $k_{z}=0$ plane symmetric about $k_{y}=0$ with codimension zero: They are Weyl nodes on the $k_{z}=0$ plane. In our simulation, we found only one pair of Weyl nodes appearing on this plane, which can only be understood if $m_{4,6}$ are $\\mathbf{k}$ dependent. The equations $d_{x}=0$ and $d_{z}=0$ determine a closed loop on the $k_{z}=0$ plane. At the same time, $d_{y}(k_{x},k_{y},0)=\\pm\\sqrt{m_{6}^{2}-m_{4}^{2}}$ has solutions that are symmetric about $k_{y}=0$ . Since $d_{y}(k_{x},0,0)=0$ , the solutions do not cross the $k_{y}=0$ line if $m_{4,6}$ are constants. Therefore, the solutions must be two lines, which make four crossings in total with the solution to $d_{z}=0$ . However, let us recall that all mass terms can also contain a linear function in $k_{x}$ , so it is possible that $m_{6}-m_{4}$ vanishes for a particular $k_{x}$ . At that $k_{c}$ , the solution to $d_{y}=\\sqrt{m_{6}^{2}-m_{4}^{2}}=0$ is satisfied at $k_{y}=0$ . If the point $(k_{c},0,0)$ is inside the loop that solves $d_{z}(k_{x},k_{y},0)=0$ , then there must be an odd number of crossings of $d_{y}={\\sqrt{m_{6}^{2}-m_{4}^{2}}}$ and $d_{z}=0$ . \n\nWe can also understand the pairs of Weyl nodes that are away from the $k_{z}=0$ plane. Consider a coexistence of both $m_{4}$ and $m_{5}$ terms. The dispersion is given by \n\n$$\nE(\\mathbf{k})=\\sqrt{(d_{x}\\pm m_{4})^{2}+(d_{y}\\pm m_{5})^{2}+d_{z}^{2}}.\n$$ \n\nSolving $E({\\bf k})=0$ is equivalent to solving \n\n$$\n\\begin{array}{l}{d_{z}=0,}\\\\ {d_{x}=\\pm m_{4},}\\\\ {d_{y}=\\pm m_{5}.}\\end{array}\n$$ \n\nThe last two equations together give \n\n$$\n\\begin{array}{r}{k_{z}^{2}=\\sqrt{v m_{4}/\\lambda},}\\\\ {k_{y}^{2}=\\sqrt{m_{4}\\lambda/v},}\\end{array}\n$$ \n\nwhere $d_{x}\\equiv u k_{y}k_{z}$ , $m_{5}\\equiv\\lambda k_{z}$ , and $d_{y}\\equiv v k_{y}$ . \n\nWhen $v m_{4}\\lambda<0$ , there is no solution. When $v m_{4}\\lambda<0$ , there are four sets of solutions for $(k_{y},k_{z})$ . We can substitute them into $d_{z}=0$ to obtain the four Weyl nodes observed in our simulation. When $m_{4}$ is small, the four Weyl nodes are close to the crossing point of the nodal ring and the $k_{z}=0$ plane. \n\nWe summarize the roles played by different mass terms: $m_{1,2}$ terms split the nodal ring into two nondegenerate rings. With the $m_{1}$ $\\mathbf{\\dot{\\Gamma}}m_{2})$ term alone, the ring is the crossing of two bands with the same (opposite) mirror eigenvalues. $m_{3,5}$ terms gap the nodal ring except at $k_{y}=k_{z}=0$ . The $m_{4}$ term alone or coexisting with the $m_{3}$ term fully gaps the ring. The $m_{4}$ term coexisting with $m_{5}$ produces four Weyl nodes away from the $k_{z}=0$ plane. The $m_{6}$ term creates a pair of Weyl nodes on the $k_{z}=0$ plane, symmetric about $k_{y}=0$ . \n\n[1] M. Z. Hasan and C. L. Kane, Colloquium: Topological Insulators, Rev. Mod. Phys. 82, 3045 (2010). \n[2] X. L. Qi and S. C. Zhang, Topological Insulators and Superconductors, Rev. Mod. Phys. 83, 1057 (2011). \n[3] Z. Wang, Y. Sun, X.-Q. Chen, C. Franchini, G. Xu, H. Weng, X. Dai, and Z. Fang, Dirac Semimetal and Topological Phase Transitions in $A_{3}\\mathrm{Bi}$ $\\mathrm{{\\hat{A}=N a,}}$ , K, Rb), Phys. Rev. B 85, 195320 (2012). \n[4] Z. Wang, H. Weng, Q. Wu, X. Dai, and Z. Fang, ThreeDimensional Dirac Semimetal and Quantum Transport in $\\mathrm{Cd}_{3}\\mathrm{As}_{2}$ , Phys. Rev. B 88, 125427 (2013). \n[5] H. Weng, X. Dai, and Z. Fang, Exploration and Prediction of Topological Electronic Materials Based on FirstPrinciples Calculations, MRS Bull. 39, 849 (2014). \n[6] Z. Fang, N. Nagaosa, K. S. Takahashi, A. Asamitsu, R. Mathieu, T. Ogasawara, H. Yamada, M. Kawasaki, Y. Tokura, and K. Terakura, The Anomalous Hall Effect and Magnetic Monopoles in Momentum Space, Science 302, 92 (2003). \n[7] X. Wan, A. M. Turner, A. Vishwanath, and S. Y. Savrasov, Topological Semimetal and Fermi-Arc Surface States in the Electronic Structure of Pyrochlore Iridates, Phys. Rev. B 83, 205101 (2011). \n[8] L. Balents, Weyl Electrons Kiss, Physics 4, 36 (2011). \n[9] G. Xu, H. Weng, Z. Wang, X. Dai, and Z. Fang, Chern Semimetal and the Quantized Anomalous Hall Effect in ${\\mathrm{Hg}}{\\mathrm{Cr}}_{2}{\\mathrm{Se}}_{4}$ , Phys. Rev. Lett. 107, 186806 (2011). \n[10] H. B. Nielsen and M. Ninomiya, The Adler-Bell-Jackiw Anomaly and Weyl Fermions in a Crystal, Phys. Lett. B 130, 389 (1983). \n[11] H. B. Nielsen and M. Ninomiya, Absence of Neutrinos on a Lattice: (I). Proof by Homotopy Theory, Nucl. Phys. B185, 20 (1981). \n[12] H. B. Nielsen and M. Ninomiya, Absence of Neutrinos on a Lattice: (II). Intuitive Topological Proof, Nucl. Phys. B193, 173 (1981). \n[13] H.-J. Kim, K.-S. Kim, J.-F. Wang, M. Sasaki, N. Satoh, A. Ohnishi, M. Kitaura, M. Yang, and L. Li, Dirac Versus Weyl Fermions in Topological Insulators: Adler-BellJackiw Anomaly in Transport Phenomena, Phys. Rev. Lett. 111, 246603 (2013). \n[14] P. Hosur, S. Parameswaran, and A. Vishwanath, Charge Transport in Weyl Semimetals, Phys. Rev. Lett. 108, 046602 (2012). \n[15] S. A. Parameswaran, T. Grover, D. A. Abanin, D. A. Pesin, and A. Vishwanath, Probing the Chiral Anomaly with Nonlocal Transport in Three-Dimensional Topological Semimetals, Phys. Rev. X 4, 031035 (2014). \n[16] P. Hosur and X. Qi, Recent Developments in Transport Phenomena in Weyl Semimetals, Comp. Rend. Phys. 14, 857 (2013). \n[17] G. E. Volovik, From Standard Model of Particle Physics to Room-Temperature Superconductivity, arXiv:1409.3944. \n[18] A. A. Burkov and L. Balents, Weyl Semimetal in a Topological Insulator Multilayer, Phys. Rev. Lett. 107, 127205 (2011). \n[19] G. B. Halász and L. Balents, Time-Reversal Invariant Realization of the Weyl Semimetal Phase, Phys. Rev. B 85, 035103 (2012). \n[20] A. A. Zyuzin, S. Wu, and A. A. Burkov, Weyl Semimetal with Broken Time Reversal and Inversion Symmetries, Phys. Rev. B 85, 165110 (2012); T. Das, Weyl Semimetal and Superconductor Designed in an Orbital-Selective Superlattice, Phys. Rev. B 88, 035444 (2013). \n[21] M. Hirayama, R. Okugawa, S. Ishibashi, S. Murakami, and T. Miyake, Weyl Node and Spin Texture in Trigonal Tellurium and Selenium, arXiv:1409.7517. \n[22] J. Liu and D. Vanderbilt, Weyl Semimetals from Noncentrosymmetric Topological Insulators, Phys. Rev. B 90, 155316 (2014). \n[23] B. Singh, A. Sharma, H. Lin, M. Z. Hasan, R. Prasad, and A. Bansil, Topological Electronic Structure and Weyl Semimetal in the TlBiSe $_2$ Class of Semiconductors, Phys. Rev. B 86, 115208 (2012). \n[24] S. Murakami, Phase Transition between the Quantum Spin Hall and Insulator Phases in 3D: Emergence of a Topological Gapless Phase, New J. Phys. 9, 356 (2007). \n[25] T. Ojanen, Helical Fermi Arcs and Surface States in Time-Reversal Invariant Weyl Semimetals, Phys. Rev. B 87, 245112 (2013). \n[26] L. Fu, C. Kane, and E. Mele, Topological Insulators in Three Dimensions, Phys. Rev. Lett. 98, 106803 (2007). \n[27] A. M. Turner, Y. Zhang, R. S. K. Mong, and A. Vishwanath, Quantized Response and Topology of Magnetic Insulators with Inversion Symmetry, Phys. Rev. B 85, 165120 (2012). \n[28] T. L. Hughes, E. Prodan, and B. A. Bernevig, InversionSymmetric Topological Insulators, Phys. Rev. B 83, 245132 (2011). \n[29] T. H. Hsieh, H. Lin, J. Liu, W. Duan, A. Bansil, and L. Fu, Topological Crystalline Insulators in the SnTe Material Class, Nat. Commun. 3, 982 (2012). \n[30] H. Weng, J. Zhao, Z. Wang, Z. Fang, and X. Dai, Topological Crystalline Kondo Insulator in Mixed Valence Ytterbium Borides, Phys. Rev. Lett. 112, 016403 (2014). \n[31] C. L. Kane and E. J. Mele, $Z_{2}$ Topological Order and the Quantum Spin Hall Effect, Phys. Rev. Lett. 95, 146802 (2005). \n[32] S. Furuseth, K. Selte, and A. Kjekshus, On the Arsenides and Antimonides of Tantalum, Acta Chem. Scand. 19, 95 (1965). \n[33] See http://www.openmx‑square.org. \n[34] J. P. Perdew, K. Burke, and M. Ernzerhof, Generalized Gradient Approximation Made Simple, Phys. Rev. Lett. 77, 3865 (1996). \n[35] H. Weng, T. Ozaki, and K. Terakura, Revisiting Magnetic Coupling in Transition-Metal-Benzene Complexes with Maximally Localized Wannier Functions, Phys. Rev. B 79, 235118 (2009). \n[36] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevX.5.011029 for a movie demonstrating the distribution of nodal rings and Weyl points in the crystal momentum space. \n[37] R. Yu, X. L. Qi, A. Bernevig, Z. Fang, and X. Dai, Equivalent Expression of $\\mathbb{Z}_{2}$ Topological Invariant for Band Insulators Using the Non-Abelian Berry Connection, Phys. Rev. B 84, 075119 (2011). \n[38] X. Wang, J. Yates, I. Souza, and D. Vanderbilt, Ab initio Calculation of the Anomalous Hall Conductivity by Wannier Interpolation, Phys. Rev. B 74, 195118 (2006). " + }, + { + "id": "10.1038_nature14964", + "DOI": "10.1038/nature14964", + "DOI Link": "http://dx.doi.org/10.1038/nature14964", + "Relative Dir Path": "mds/10.1038_nature14964", + "Article Title": "Conventional superconductivity at 203 kelvin at high pressures in the sulfur hydride system", + "Authors": "Drozdov, AP; Eremets, MI; Troyan, IA; Ksenofontov, V; Shylin, SI", + "Source Title": "NATURE", + "Abstract": "A superconductor is a material that can conduct electricity without resistance below a superconducting transition temperature, T-c. The highest T-c that has been achieved to date is in the copper oxide system(1): 133 kelvin at ambient pressure(2) and 164 kelvin at high pressures(3). As the nature of superconductivity in these materials is still not fully understood (they are not conventional superconductors), the prospects for achieving still higher transition temperatures by this route are not clear. In contrast, the Bardeen-Cooper-Schrieffer theory of conventional superconductivity gives a guide for achieving high T-c with no theoretical upper bound-all that is needed is a favourable combination of high-frequency phonons, strong electron-phonon coupling, and a high density of states(4). These conditions can in principle be fulfilled for metallic hydrogen and covalent compounds dominated by hydrogen(5,6), as hydrogen atoms provide the necessary high-frequency phonon modes as well as the strong electron-phonon coupling. Numerous calculations support this idea and have predicted transition temperatures in the range 50-235 kelvin for many hydrides(7), but only a moderate T-c of 17 kelvin has been observed experimentally(8). Here we investigate sulfur hydride(9), where a T-c of 80 kelvin has been predicted(10). We find that this system transforms to a metal at a pressure of approximately 90 gigapascals. On cooling, we see signatures of superconductivity: a sharp drop of the resistivity to zero and a decrease of the transition temperature with magnetic field, with magnetic susceptibility measurements confirming a T-c of 203 kelvin. Moreover, a pronounced isotope shift of T-c in sulfur deuteride is suggestive of an electron-phonon mechanism of superconductivity that is consistent with the Bardeen-Cooper-Schrieffer scenario. We argue that the phase responsible for high-T-c superconductivity in this system is likely to be H3S, formed from H2S by decomposition under pressure. These findings raise hope for the prospects for achieving room-temperature superconductivity in other hydrogen-based materials.", + "Times Cited, WoS Core": 1830, + "Times Cited, All Databases": 1999, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000360594100027", + "Markdown": "# Conventional superconductivity at 203 kelvin at high pressures in the sulfur hydride system \n\nA. P. Drozdov1\\*, M. I. Eremets1\\*, I. A. Troyan1, V. Ksenofontov2 & S. I. Shylin2 \n\nA superconductor is a material that can conduct electricity without resistance below a superconducting transition temperature, $T_{\\mathrm{c}}$ The highest $T_{\\mathrm{c}}$ that has been achieved to date is in the copper oxide system1: 133 kelvin at ambient pressure2 and 164 kelvin at high pressures3. As the nature of superconductivity in these materials is still not fully understood (they are not conventional superconductors), the prospects for achieving still higher transition temperatures by this route are not clear. In contrast, the Bardeen–Cooper– Schrieffer theory of conventional superconductivity gives a guide for achieving high $T_{\\mathrm{c}}$ with no theoretical upper bound—all that is needed is a favourable combination of high-frequency phonons, strong electron–phonon coupling, and a high density of states4. These conditions can in principle be fulfilled for metallic hydrogen and covalent compounds dominated by hydrogen5,6, as hydrogen atoms provide the necessary high-frequency phonon modes as well as the strong electron–phonon coupling. Numerous calculations support this idea and have predicted transition temperatures in the range 50–235 kelvin for many hydrides7, but only a moderate $T_{\\mathrm{c}}$ of 17 kelvin has been observed experimentally8. Here we investigate sulfur hydride9, where a $T_{\\mathrm{c}}$ of 80 kelvin has been predicted10. We find that this system transforms to a metal at a pressure of approximately 90 gigapascals. On cooling, we see signatures of superconductivity: a sharp drop of the resistivity to zero and a decrease of the transition temperature with magnetic field, with magnetic susceptibility measurements confirming a $T_{\\mathrm{c}}$ of 203 kelvin. Moreover, a pronounced isotope shift of $T_{\\mathrm{c}}$ in sulfur deuteride is suggestive of an electron–phonon mechanism of superconductivity that is consistent with the Bardeen–Cooper–Schrieffer scenario. We argue that the phase responsible for high- $T_{\\mathrm{c}}$ superconductivity in this system is likely to be $\\mathbf{H}_{3}\\mathbf{S}$ , formed from $\\mathbf{H}_{2}\\mathbf{S}$ by decomposition under pressure. These findings raise hope for the prospects for achieving room-temperature superconductivity in other hydrogen-based materials. \n\nA search for high- (room)-temperature conventional superconductivity is likely to be fruitful, as the Bardeen–Cooper–Schrieffer (BCS) theory in the Eliashberg formulation puts no apparent limits on $T_{\\mathrm{c}}$ Materials with light elements are especially favourable as they provide high frequencies in the phonon spectrum. Indeed, many superconductive materials have been found in this way, but only a moderately high $T_{\\mathrm{c}}=39\\:\\mathrm{K}$ has been found in this search (in $\\mathrm{MgB}_{2}$ ; ref. 11). \n\nAshcroft5 turned attention to hydrogen, which has very high vibrational frequencies due to the light hydrogen atom and provides a strong electron–phonon interaction. Further calculations showed that metallic hydrogen should be a superconductor with a very high $T_{\\mathrm{c}}$ of about $100{-}240\\ \\mathrm{K}$ for molecular hydrogen, and of $300{-}350\\ \\mathrm{K}$ in the atomic phase at $500\\mathrm{GPa}$ (ref. 12). However, superconductivity in pure hydrogen has not yet been found, even though a conductive and probably semimetallic state of hydrogen has been recently produced13. Hydrogen-dominated materials such as covalent hydrides $\\mathrm{SiH_{4}},$ $\\mathrm{SnH_{4}}$ , and so on might also be good candidates for showing high- $T_{\\mathrm{c}}$ superconductivity6. Similarly to pure hydrogen, they have high Debye temperatures. Moreover, heavier elements might be beneficial as they contribute to the low frequencies that enhance electron–phonon coupling. Importantly, lower pressures are required to metallize hydrides in comparison to pure hydrogen. Ashcroft’s general idea was supported in numerous calculations7,10 predicting high values of $T_{\\mathrm{c}}$ for many hydrides. So far only a low $T_{\\mathrm{c}}(\\sim17\\:\\mathrm{K})$ has been observed experimentally8. \n\nFor the present study we selected $\\mathrm{H}_{2}\\mathrm{S}$ , because it is relatively easy to handle and is predicted to transform to a metal and a superconductor at a low pressure $P\\approx100$ GPa with a high $T_{\\mathrm{c}}\\approx80$ K (ref. 10). Experimentally, $\\mathrm{H}_{2}\\mathrm{S}$ is known as a typical molecular compound with a rich phase diagram14. At about $96\\mathrm{GPa}$ , hydrogen sulphide transforms to a metal15. The transformation is complicated by the partial dissociation of $\\mathrm{H}_{2}S$ and the appearance of elemental sulfur at $P>27$ GPa at room temperature, and at higher pressures at lower temperatures14. Therefore, the metallization of hydrogen sulphide can be explained by elemental sulfur, which is known to become metallic above $95\\mathrm{GPa}$ (ref. 16). No experimental studies of hydrogen sulphide are known above $100\\mathrm{GPa}$ . \n\nIn a typical experiment, we performed loading and the initial pressure increase at temperatures of ${\\sim}200\\mathrm{K};$ this is essential for obtaining a good sample (Methods). The Raman spectra of $\\mathrm{H}_{2}\\mathrm{S}$ and $\\mathrm{D}_{2}S$ were measured as the pressure was increased, and were in general agreement with the literature data17,18 (Extended Data Fig. 1). The sample starts to conduct at $P\\approx50$ GPa. At this pressure it is a semiconductor, as shown by the temperature dependence of the resistance and pronounced photoconductivity. At 90–100 GPa the resistance drops further, and the temperature dependence becomes metallic. No photoconductive response is observed in this state. It is a poor metal—its resistivity at ${\\sim}100\\mathrm{K}$ is $\\rho\\approx3\\times{10}^{-5}$ ohm m at $110\\mathrm{GPa}$ and $\\rho\\approx3\\times{10}^{-7}$ ohm m at ${\\sim}200$ GPa. \n\nDuring the cooling of the metal at pressures of about $100~\\mathrm{GPa}$ (Fig. 1a) the resistance abruptly drops by three to four orders of magnitude, indicating a transition to the superconducting state. At the next increase of pressure at low temperatures of $T<100~\\mathrm{K},~T_{\\mathrm{c}}$ steadily increases with pressure. However, at pressures of ${>}160$ GPa, $T_{c}$ increases sharply (Fig. 1b). As higher temperatures of $150–250\\mathrm{~K~}$ were involved in this pressure range, we supposed that the increase of $T_{c}$ and the decrease of sample resistance during warming (Fig. 1a) could indicate a possible kinetic-controlled phase transformation. Therefore in further experiments, after loading and after the initial pressure increase at $200~\\mathrm{K},$ we annealed all samples by heating them to room temperature (or above) at pressures of $>\\sim150\\ \\mathrm{GPa}$ (Fig. 2a, see also Extended Data Fig. 2). This allowed us to obtain stable results, to compare different isotopes, to obtain the dependence of $T_{\\mathrm{c}}$ on pressure and magnetic field, and to prove the existence of superconductivity in our samples as follows. (We note that additional information on experimental conditions are given in the appropriate figure legends.) \n\n![](images/1268cb6ccf067a223573148d898c7bc0426955541cc65a06286ec72e28389b10.jpg) \nFigure 1 | Temperature dependence of the resistance of sulfur hydride measured at different pressures, and the pressure dependence of $T_{\\mathrm{c}}.$ a, Main panel, temperature dependence of the resistance (R) of sulfur hydride at different pressures. The pressure values are indicated near the corresponding plots. At first, the sample was loaded at $T\\approx200~\\mathrm{K}$ and the pressure was increased to ${\\sim}100\\mathrm{GPa}$ ; the sample was then cooled down to $4\\mathrm{K}.$ . After warming to ${\\sim}100\\mathrm{K},$ pressure was further increased. Plots at pressures ${<}135$ GPa have been scaled (reduced) as follows—105 GPa, by 10 times; 115 GPa and $122\\mathrm{GPa}$ , by 5 times; and 129 GPa by 2 times—for easier comparison with the higher pressure steps. The resistance was measured with a current of $10~\\upmu\\mathrm{A}$ . Bottom panel, the resistance plots near zero. The resistance was measured with four electrodes deposited on a diamond anvil that touched the sample (top panel inset). The diameters of the samples were ${\\sim}25\\upmu\\mathrm{m}$ and the thickness was \n\n(1) There is a sharp drop in resistivity with cooling, indicating a phase transformation. The measured minimum resistance is at least as low, $\\sim{10}^{-11}$ ohm m—about two orders of magnitude less than for pure copper (Fig. 1, Extended Data Fig. 3e) measured at the same temperature19. (2) A strong isotope effect is observed: $T_{c}$ shifts to lower ${\\sim}1\\upmu\\mathrm{m}$ . b, Blue round points represent values of $T_{c}$ determined from a. Other blue points (triangles and half circles) were obtained in similar runs. Measurements at $P{>}{\\sim}160$ GPa revealed a sharp increase of $T_{c}$ . In this pressure range the $R(T)$ measurements were performed over a larger temperature range up to $260~\\mathrm{K},$ , the corresponding experimental points for two samples are indicated by adding a pink colour to half circles and a centred dot to filled circles. These points probably reflect a transient state for these particular $P/T$ conditions. Further annealing of the sample at room temperature would require stabilizing the sample (Fig. 2a). Black stars are calculations from ref. 10. Dark yellow points are $T_{c}$ values of pure sulfur obtained with the same four-probe electrical measurement method. They are consistent with literature data30 (susceptibility measurements) but have higher values at $P>200\\mathrm{GPa}$ . \n\ntemperatures for sulfur deuteride, indicating phonon-assisted superconductivity (Fig. 2b, c). The BCS theory gives the dependence of $T_{c}$ on atomic mass $m$ as $T_{\\mathrm{c}}\\propto m^{-\\alpha};$ where $\\alpha\\approx0.5$ . Comparison of $T_{c}$ values in the pressure range $P>170\\mathrm{GPa}$ (Fig. 2c) gives $\\alpha\\approx0.3$ . (3) $T_{\\mathrm{c}}$ shifts to lower temperatures with available magnetic field $(B)$ up to $7\\mathrm{~T~}$ temperatures (Fig. 4c) revealed a pronounced hysteresis indicating type II superconductivity with the first critical field $H_{\\mathrm{c1}}\\approx30~\\mathrm{mT}$ . The magnetization decreases sharply at temperatures above $200\\mathrm{~K~}$ showing the onset of superconductivity at $203.5\\mathrm{K},$ in agreement with the susceptibility measurements (Fig. 4a). A list of key properties of the new superconductor is given in Methods. \n\n![](images/fccf33eb397790e0a283034c25ddbe614be7beec2c5e8ab0b97d2fc69f2e2dc9.jpg) \nFigure 2 | Pressure and temperature effects on $T_{\\mathrm{c}}$ of sulfur hydride and sulfur deuteride. a, Changes of resistance and $T_{c}$ of sulfur hydride with temperature at constant pressure—the annealing process. The sample was pressurized to $145\\mathrm{GPa}$ at $220\\mathrm{K}$ and then cooled to $100\\mathrm{K}.$ It was then slowly warmed at ${\\sim}1\\mathrm{K}\\operatorname*{min}^{-1}$ ; $T_{\\mathrm{c}}=170\\mathrm{K}$ was determined. At temperatures above $-250\\mathrm{K}$ the resistance dropped sharply, and during the next temperature run $T_{c}$ increased to ${\\sim}195\\mathrm{K}$ . This $T_{\\mathrm{c}}$ remained nearly the same for the next two runs. (We note that the only point for sulfur deuteride presented in ref. 9 was determined without sample annealing, and $T_{c}$ would increase after annealing at room temperature.) $\\mathbf{b}$ , Typical superconductive steps for sulfur hydride \n(blue trace) and sulfur deuteride (red trace). The data were acquired during slow warming over a time of several hours. $T_{c}$ is defined here as the sharp kink in the transition to normal metallic behaviour. These curves were obtained after annealing at room temperature as shown in a. c, Dependence of $T_{c}$ on pressure; data on annealed samples are presented. Open coloured points refer to sulfur deuteride, and filled points to sulfur hydride. Data shown as the magenta point were obtained in magnetic susceptibility measurements (Fig. 4a). The lines indicate that the plots are parallel at pressures above ${\\sim}170\\mathrm{GPa}$ (the isotope shift is constant) but strongly deviate at lower pressures. \n\n![](images/6e9ec9e62f80b83b4892938bfe201a5e400ed1ff7eca1193b304b32868be0d24.jpg) \nFigure 3 | Temperature dependence of the resistance of sulfur hydride in same measurements but for the $185\\mathrm{K}$ superconducting transition. c, The different magnetic fields. a, The shift of the ${\\sim}60\\mathrm{K}$ superconducting transition temperature dependence of the critical magnetic field strengths of sulfur in magnetic fields of $0{-}7\\mathrm{T}$ (colour coded). The upper and lower parts of the hydride. $T_{c}$ (black points deduced from a, b) are plotted for the corresponding transition are shown enlarged in the insets (axes as in main panel). The magnetic fields. To estimate the critical magnetic field $H_{c},$ the plots were temperature dependence of the resistance without an applied magnetic field extrapolated to high magnetic fields using the formula $H_{c}(T)=H_{c0}(1-(T/$ was measured three times: before applying the field, after applying 1, 3, 5, 7 T ${T_{c}})^{2}.$ ). The extrapolation has been done with $95\\%$ confidence (band shown as and finally after applying 2, 4, 6 T (black, grey and dark grey colours). b, The grey lines). \n\n![](images/b4d8e69e44871e1206bfd158db0f146f75d80307eaacdf0a186fbdf585461478.jpg) \n(Fig. 3). Much higher fields are required to destroy the superconductivity: extrapolation of $T_{\\mathrm{c}}(B)$ gives an estimate of a critical magnetic field as high as $70~\\mathrm{T}$ (Fig. 3). (4) Finally, in magnetic susceptibility measurements (Fig. 4) a sharp transition from the diamagnetic to the paramagnetic state (Fig. 4a) was observed for zero-field-cooled (ZFC) material. The onset temperature of the superconducting state $T_{\\mathrm{onset}}=203(1)\\:\\mathrm{K},$ and the width of the superconducting transition is nearly the same as in electrical measurements (Fig. 4a). Magnetization measurements $M(H)$ , where $H$ is magnetic field, at different \n\nWe have presented purely experimental evidence of superconductivity in sulfur hydride. However the particular compound responsible for the high $T_{c}$ is not obvious. The superconductivity measured in the \n\nFigure 4 | Magnetization measurements. a, Temperature dependence of the magnetization of sulfur hydride at a pressure of $155\\mathrm{GPa}$ in zero-field cooled (ZFC) and $20\\mathrm{Oe}$ field cooled (FC) modes (black circles). The onset temperature is $T_{\\mathrm{onset}}=203(1)\\:\\mathrm{{K}}$ . For comparison, the superconducting step obtained for sulfur hydride from electrical measurements at 145 GPa is shown by red circles. Resistivity data $\\mathrm{\\Delta}T_{\\mathrm{onset}}=195\\mathrm{\\:K}$ were scaled and moved vertically to compare with the magnetization data. Inset, optical micrograph of a sulfur hydride sample at $155\\mathrm{GPa}$ in a $\\mathrm{CaSO_{4}}$ gasket (scale bar $100\\upmu\\mathrm{m}$ ). The high $T_{\\mathrm{onset}}=203\\mathrm{K}$ measured from the susceptibility can be explained by a significant input to the signal from the periphery of the sample which expanded beyond the culet where pressure is smaller than in the culet centre $\\cdot T_{c}$ increases with decreasing pressure (Fig. 2b)). b, Non-magnetic diamond anvil cell (DAC) of diameter $8.8~\\mathrm{mm}$ . c, Magnetization measurements $M(H)$ of sulfur hydride at a pressure of $155\\mathrm{GPa}$ at different temperatures (given as curve labels). The magnetization curves show hysteresis, indicating a type II superconductor. The magnetization curves are however distorted by obvious paramagnetic input (which is also observed in other superconductors31). In our case, the paramagnetic signal is probably from the DAC, but further study of the origin of this input is required. The paramagnetic background increases when temperature is decreased. The minima of the magnetization curves $(\\sim35\\mathrm{mT})$ are the result of the diamagnetic input from superconductivity and the paramagnetic background. The first critical field $H_{\\mathrm{c1}}\\approx30\\:\\mathrm{mT}$ can be roughly estimated as the point where magnetization deviates from linear behaviour. At higher fields, magnetization increases due to the penetration of magnetic vortexes. As the sign of the field change reverses, the magnetic flux in the Shubnikov phase remains trapped and therefore the back run (that is, with decreasing field) is irreversible—the returning branch of the magnetic cycle (shown by filled points) runs above the direct one. Hysteretic behaviour of the magnetization becomes more clearly visible as the temperature decreases. d, At high temperatures $T>200\\mathrm{K},$ the magnetization decreases sharply. e, Extrapolation of the pronounced minima at the magnetization curves to higher temperatures gives the onset of superconductivity at $T=203.5\\:\\bar{\\mathrm{K}}$ \n\nlow-temperature runs (Fig. 1) possibly relates to $\\mathrm{H}_{2}\\mathrm{S},$ as it is generally consistent with calculations10 for $\\mathrm{H}_{2}S$ : both the value of $T_{\\mathrm{c}}\\approx80\\mathrm{K}$ and its pressure behaviour. However superconductivity with $T_{\\mathrm{c}}\\approx200~\\mathrm{K}$ (Fig. 2) does not follow from these calculations. We suppose that it relates to the decomposition of $\\mathrm{\\ddot{H}}_{2}\\mathrm{S}$ , as high temperatures are required to reach the high $T_{c}$ (Fig. 2b). Precipitation of elemental sulfur on decomposition could be expected (which is well known at low pressures of $P{<}100\\mathrm{GPa}$ ; ref. 14); however the superconducting transition in elemental sulfur occurs at significantly lower temperatures (Fig. 1b). Another expected product of decomposition of $\\mathrm{H}_{2}S$ is hydrogen. However, the strong characteristic vibrational stretching mode from the $\\mathrm{H}_{2}$ molecule was never observed in our Raman spectra (nor was it observed in ref. 14). Therefore we suppose that the dissociation of $\\mathrm{H}_{2}S$ is different and involves the creation of higher hydrides, such as $3\\mathrm{H}_{2}\\mathrm{S}$ $\\rightarrow\\mathrm{H}_{6}\\mathrm{S}+2\\mathrm{S}$ or $2\\mathrm{H}_{2}\\mathrm{S}\\longrightarrow\\mathrm{H}_{4}\\mathrm{S}+\\mathrm{S}.$ It is natural to expect these reactions, as sulfur can be not only divalent, but also exhibits higher valencies. In fact, calculations10 indirectly support this hypothesis, as the dissociation $\\mathrm{H}_{2}S\\rightarrow\\mathrm{H}_{2}+S$ was shown to be energetically very unfavourable. We found further theoretical support in ref. 20. In that work, the van der Waals compound21 $(\\mathrm{H}_{2}\\mathrm{S})_{2}\\mathrm{H}_{2}$ was considered, and it was shown that at pressures above $180\\mathrm{GPa}$ it forms an Im- $\\cdot3m$ structure with $\\mathrm{H}_{3}S$ stoichiometry. The predicted $T_{\\mathrm{c}}\\approx190\\mathrm{K}$ and its pressure dependences are close to our experimental values (Fig. 2c). Our hypothesis of the transformation of $\\mathrm{H}_{2}\\mathrm{S}$ to higher hydrides (in the $\\mathrm{H}_{3}\\mathrm{S}$ stoichiometry each S atom is surrounded by 6 hydrogen atoms) is strongly supported by further calculations22,23. All the numerous works based on the Im$3m$ structure23–27 are consistent in their prediction of $T_{\\mathrm{c}}>\\sim200~\\mathrm{K},$ which decreases with pressure. The hydrogen sublattice gives the main contribution to superconductivity20,25,26. Inclusion of zero point vibrations and anharmonicity in the calculations24 corrected the calculated $T_{\\mathrm{c}}$ to ${\\sim}190\\mathrm{K},$ and the isotope coefficient from $\\alpha=0.5$ to $\\alpha=0.35-$ both in agreement with the present work. \n\nThe highest $T_{c}$ of $203\\mathrm{K}$ that we report here has been achieved most probably in $\\mathrm{H}_{3}S$ having the Im- $\\cdot3m$ structure. It is a good metal; interestingly, there is also strong covalent bonding between H and S atoms in this compound20. This is in agreement with the general assumption (see for instance ref. 28) that a metal with high $T_{\\mathrm{c}}$ should have strong covalent bonding (as is realized in $\\begin{array}{r}{\\mathbf{MgB}_{2};}\\end{array}$ ; ref. 29) together with highfrequency modes in the phonon spectrum. This particular combination of bonding type and phonon spectrum would probably provide a good criterion when searching for the materials with high $T_{\\mathrm{c}}$ at ambient pressure that are required for applications. There are many hydrogen-containing materials with strong covalent bonding (such as organics) but typically they are insulators. In principle, they could be tuned to a metallic state by doping or gating. Modern methods of structure prediction could facilitate exploration for the desired materials. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# Received 25 June; accepted 22 July 2015. Published online 17 August 2015. \n\n1. Bednorz, J. G. & Mueller, K. A. Possible high TC superconductivity in the Ba-La-CuO system. Z. Phys. B 64, 189–193 (1986). \n2. Schilling, A., Cantoni, M., Guo, J. D. &. Ott, H. R. Superconductivity above $130\\mathsf{K}$ in the Hg-Ba-Ca-Cu-O system. Nature 363, 56–58 (1993). \n3. Gao, L. et al. Superconductivity up to $164\\mathsf{K}$ in $\\mathsf{H g B a}_{2}\\mathsf{C a}_{m-1}\\mathsf{C u}_{m}\\mathsf{O}_{2m+2+\\delta}(m{=}1,2$ , and 3) under quasihydrostatic pressures. Phys. Rev. B 50, 4260–4263 (1994). \n4. Ginzburg, V. L. Once again about high-temperature superconductivity. Contemp. Phys. 33, 15–23 (1992). \n5. Ashcroft, N. W. Metallic hydrogen: A high-temperature superconductor? Phys. Rev. Lett. 21, 1748–1750 (1968). \n6. Ashcroft, N. W. Hydrogen dominant metallic alloys: high temperature superconductors? Phys. Rev. Lett. 92, 187002 (2004). \n7. Wang, Y. & Ma, Y. Perspective: Crystal structure prediction at high pressures. J. Chem. Phys. 140, 040901 (2014). \n8. Eremets, M. I., Trojan, I. A., Medvedev, S. A., Tse, J. S. & Yao, Y. Superconductivity in hydrogen dominant materials: silane. Science 319, 1506–1509 (2008). \n9. Drozdov, A. P., Eremets, M. I. & Troyan, I. A. Conventional superconductivity at 190 K at high pressures. Preprint at http://arXiv.org/abs/1412.0460 (2014). \n10. Li, Y., Hao, J., Li, Y. & Ma, Y. The metallization and superconductivity of dense hydrogen sulfide. J. Chem. Phys. 140, 174712 (2014). \n11. Nagamatsu, J., Nakagawa, N., Muranaka, T., Zenitani, Y. & Akimitsu, J. Superconductivity at $39\\mathsf{K}$ in magnesium diboride. Nature 410, 63–64 (2001). \n12. McMahon, J. M., Morales, M. A., Pierleoni, C. & Ceperley, D. M. The properties of hydrogen and helium under extreme conditions. Rev. Mod. Phys. 84, 1607–1653 (2012). \n13. Eremets, M. I. & Troyan, I. A. Conductive dense hydrogen. Nature Mater. 10, 927–931 (2011). \n14. Fujihisa, H. et al. Molecular dissociation and two low-temperature high-pressure phases of ${\\sf H}_{2}{\\sf S}$ . Phys. Rev. B 69, 214102 (2004). \n15. Sakashita, M. et al. Pressure-induced molecular dissociation and metallization in hydrogen-bonded ${\\sf H}_{2}{\\sf S}$ solid. Phys. Rev. Lett. 79, 1082–1085 (1997). \n16. Kometani, S., Eremets, M., Shimizu, K., Kobayashi, M. & Amaya, K. Observation of pressure-induced superconductivity of sulfur. J. Phys. Soc. Jpn. 66, 2564–2565 (1997). \n17. Shimizu, H. et al. Pressure-temperature phase diagram of solid hydrogen sulfide determined by Raman spectroscopy. Phys. Rev. B 51, 9391–9394 (1995). \n18. Shimizu, H., Murashima, H. & Sasaki, S. High-pressure Raman study of solid deuterium sulfide up to 17 GPa. J. Chem. Phys. 97, 7137–7139 (1992). \n19. Matula, R. A. Electrical resistivity of copper, gold, palladium, and silver. J. Phys. Chem. Ref. 8, 1147–1298 (1979). \n20. Duan, D. et al. Pressure-induced metallization of dense $(H_{2}S)_{2}H_{2}$ with high- $\\cdot T_{\\mathrm{c}}$ superconductivity. Sci. Rep. 4, 6968 (2014). \n21. Strobel, T. A., Ganesh, P., Somayazulu, M., Kent, P. R. C. & Hemley, R. J. Novel cooperative interactions and structural ordering in $H_{2}S_{-}\\Hat{H}_{2}$ . Phys. Rev. Lett. 107, 255503 (2011). \n22. Duan, D. et al. Pressure-induced decomposition of solid hydrogen sulfide. Phys. Rev. B 91, 180502(R) (2015). \n23. Bernstein, N., Hellberg, C. S., Johannes, M. D., Mazin, I. I. & Mehl, M. J. What superconducts in sulfur hydrides under pressure, and why. Phys. Rev. B 91, 060511(R) (2015). \n24. Errea, I. et al. Hydrogen sulfide at high pressure: a strongly-anharmonic phononmediated superconductor. Phys. Rev. Lett. 114, 157004 (2015). \n25. Flores-Livas, J. A., Sanna, A. & Gross, E. K. U. High temperature superconductivity in sulfur and selenium hydrides at high pressure. Preprint at http://arXiv.org/abs/ 1501.06336v1 (2015). \n26. Papaconstantopoulos, D. A., Klein, B. M., Mehl, M. J. & Pickett, W. E. Cubic H3S around 200 GPa: an atomic hydrogen superconductor stabilized by sulfur. Phys. Rev. B. 91, 184511 (2015). \n27. Akashi, R., Kawamura, M., Tsuneyuki, S., Nomura, Y. & Arita, R. Fully non-empirical study on superconductivity in compressed sulfur hydrides. Preprint at http:// arXiv.org/abs/1502.00936v1 (2015). \n28. Cohen, M. L. in BCS: 50 years (eds Cooper, L. N. & Feldman, D.) 375–389 (World Scientific, 2011). \n29. An, J. M. & Pickett, W. E. Superconductivity of ${\\mathsf{M g B}}_{2}$ : covalent bonds driven metallic. Phys. Rev. Lett. 86, 4366–4369 (2001). \n30. Gregoryanz, E. et al. Superconductivity in the chalcogens up to multimegabar pressures. Phys. Rev. B 65, 064504 (2002). \n31. Senoussi, S., Sastry, P., Yakhmi, J. V. & Campbell, I. Magnetic hysteresis of superconducting $\\mathsf{G d B a}_{2}\\mathsf{C u}_{3}0_{7}$ down to 1.8 K. J. Phys. 49, 2163–2164 (1988). \n\nAcknowledgements Support provided by the European Research Council under the 2010 Advanced Grant 267777 is acknowledged. We appreciate help provided in MPI Chemie by U. P¨oschl. We thank P. Alireza and G. Lonzarich for help with samples of CuTi; J. Kamarad, S. Toser and C. Q. Jin for sharing their experience on SQUID measurements; K. Shimizu and his group for cooperation; P. Chu and his group for many discussions and collaboration, and L. Pietronero, M. Calandra and T. Timusk for discussions. V.K. and S.I.S. acknowledge the DFG (Priority Program No. 1458) for support. M.I.E. thanks H. Musshof and R. Wittkowski for precision machining of the DACs. \n\nAuthor Contributions A.P.D. performed the most of the experiments and contributed to the data interpretation and writing the manuscript. M.I.E. designed the study, wrote the major part of the manuscript, developed the DAC for SQUID measurements, and participated in the experiments. I.A.T. participated in experiments. V.K. and S.I.S. performed the magnetic susceptibility measurements and contributed to writing the manuscript. M.I.E. and A.P.D. contributed equally to this paper. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Correspondence and requests for materials should be addressed to M.I.E. (m.eremets@mpic.de). \n\n# METHODS \n\nExperimental procedure. For electrical measurements we used diamond anvil cells (DACs) with anvils of the following shape: tip diameter of $200{-}300~{\\upmu\\mathrm{m}}$ bevelled at $7{-}8^{\\circ}$ to a culet of $40{-}80\\upmu\\mathrm{m}$ . An insulating gasket is required to separate the metallic gasket from the electrodes. It was prepared in the following way (Extended Data Fig. 3). First a metallic gasket of T301 stainless steel (or Re) 250 $\\upmu\\mathrm{m}$ thick was indented with about $17-20\\mathrm{GPa}$ pressure. Then the bottom of the imprint of diameter ${\\sim}200~\\upmu\\mathrm{m}$ was drilled out, and a powder insulating material was put in the imprint and pressed between the anvils to form a layer. The insulating layer was made of either Teflon, $\\mathrm{\\DeltaNaCl}$ or $\\mathrm{CaSO_{4}}$ as these materials do not react with $\\mathrm{H}_{2}S$ . The layer was pressed to obtain a thickness in the centre of ${\\sim}3{\\ensuremath-}5~{\\upmu}\\mathrm{m}$ to provide stable clamping. A larger thickness leads to instability in the sample—it shifts or escapes under pressure—while with a thinner gasket it is difficult to reach high pressures. A hole of diameter ${\\sim}10{-}30\\upmu\\mathrm{m}$ was then drilled in the insulating layer. Four Ti electrodes were sputtered on the diamond anvil. The electrodes were capped with Au to prevent oxidation of the Ti. (To check a possible contribution of the diamond surface to the conductivity, we prepared a different configuration of electrodes for a once-only experiment: two electrodes were sputtered on one anvil and another two on another anvil, similar to ref. 13). After preparation of the electrodes the gasket was put back on the anvil and the DAC was assembled so that the separation between the anvils was about $20{-}100~{\\upmu\\mathrm{m}}$ (measured by interference fringes). The DAC was placed into a cryostat and cooled down to ${\\sim}200\\mathrm{K}$ (within the temperature range of liquid $\\mathrm{H}_{2}S$ ) and then $\\mathrm{H}_{2}\\mathrm{S}$ gas was put through a capillary into a rim around the diamond anvil where it liquefied (Extended Data Fig. 4). $\\mathrm{H}_{2}\\mathrm{S}$ of $99.5\\%$ and $\\mathrm{D}_{2}\\mathrm{S}$ of $97\\%$ purity were been used. The filling was monitored visually (Extended Data Figs 4, 5) and the sample was identified by measuring Raman spectra. Then liquid $\\mathrm{H}_{2}\\mathrm{S}$ was clamped in the gasket hole by pushing the piston of the DAC with the aid of screws outside the cryostat. The thickness of the sample can be estimated to be few micrometres, as measured from interference spectra through the clamped transparent sample. The thickness might be ${\\sim}1\\upmu\\mathrm{m}$ if the sample expanded over the culet (Fig. 4). After the clamping, the DAC was heated to ${\\sim}220\\mathrm{K}$ to evaporate the rest of the $\\mathrm{H}_{2}\\mathrm{S},$ and then the pressure was further increased at this temperature. The pressure remained stable during the cooling within $\\pm5\\mathrm{{GPa}}$ . The pressure was determined by a diamond edge scale at room temperature and low temperatures32. For optical measurements a Raman spectrometer was equipped with a nitrogen-cooled CCD and notch filters. The $632.8\\mathrm{nm}$ line of a He–Ne laser was used to excite the Raman spectra and to determine pressure. \n\nThe low temperature loading seems to be required to prepare samples with high $T_{c}.$ If $\\mathrm{H}_{2}\\mathrm{S}$ was loaded at room temperature in the gas loader, for example, only sulfur was detected in Raman and $\\mathrm{\\DeltaX}$ -ray scattering. Apparently in this route the sample decomposes before reaching the required high-pressure phase of $\\mathrm{H}_{3}\\mathrm{S}$ . We did not explore all (P,T) paths to reach the state with high $T_{c}$ . We found however that superconductivity is not observed in sample loaded at ${\\sim}200\\mathrm{K}$ but heated to room temperature at low pressure $<\\sim100\\ \\mathrm{GPa}$ . \n\nThe resistance and Raman spectra were measured during the pressurizing using the four-probe van der Pauw method (Extended Data Fig. 3) with a current of $10{-}10{,}000\\upmu\\mathrm{A}.$ The temperature was reliably determined by using a slow warming rate $(\\sim1\\mathrm{\\K\\min}^{-1}),$ ) and allowing the DAC to equilibrate with attached thermometer. The determined $T_{c}$ was well reproduced in measurements with the PPMS6000 (Physical Property Measurement System from Quantum Design) \n\nand other set-ups. $T_{\\mathrm{c}}$ was determined as the point of steepest change of resistance from the normal state (Fig. 2b). \n\nThe influence of the magnetic field on superconducting transitions has been measured with a non-magnetic DAC (diameter $25\\mathrm{mm}$ ) in a PPMS6000 in a 4–300 K temperature range and fields up to $7\\mathrm{T}$ . \n\nMagnetic susceptibility measurements were performed in an MPMS (Magnetic Property Measurement System) from Quantum Design. For these measurements a miniature non-magnetic cell made of $\\mathrm{{Cu}\\mathrm{{:Ti}}}$ alloy working up to $200~\\mathrm{GPa}$ was designed (Fig. 4b). Samples of diameter ${\\sim}50{\\mathrm{-}}100~\\upmu\\mathrm{m}$ and a thickness of a few micrometres were prepared to provide a sufficient signal. Magnetic susceptibility measurements using a high-pressure cell were performed using a background subtraction feature of the MPMS software of the SQUID magnetometer (Extended Data Fig. 6). \n\nResults. We present here some important key features of our new high- $T_{c}$ sulfur hydride superconductor: \n\n(1) The new superconductor is of type II. This fact is clearly supported by (i) a difference in temperature-dependent ZFC and FC magnetization (Fig. 4a), which is due to the Meissner effect (ZFC) and magnetic flux capture when the sample is cooled down from its normal state (FC); and (ii) the magnetic hysteresis curves (Fig. 4c, d). The magnetic hysteresis curves also have all the features of typical type II superconductors with a mixed state between $\\mathrm{H}_{\\mathrm{c1}}$ and $\\mathrm{H}_{\\mathrm{c}2}$ . \n\n(2) A typical value of the coherence length $\\xi_{\\mathrm{GL}}$ in the framework of the Ginzburg– Landau theory can be estimated on the basis of the measured upper critical fields from conductivity measurements (Fig. 3c). Using the experimental estimation 60 $\\mathrm{T}\\xi_{\\mathrm{GL}}>2.0\\mathrm{nm}.$ We note that this relatively short coherence length is of the same order as, for instance, the values for superconducting $\\mathrm{YBa}_{2}\\mathrm{Cu}_{3}\\mathrm{O}_{7}$ $(1.3\\ \\mathrm{nm})$ ) and $\\mathrm{Nb}_{3}\\mathrm{Sn}$ $3.5\\mathrm{nm}\\cdot$ ). (3) The London penetration depth $\\lambda_{\\mathrm{L}}$ can be estimated from the known relation of the lower critical field $H_{\\mathrm{c1}}$ to the upper critical field $H_{c2}$ for a type II superconductor \n\n$$\n\\frac{H_{\\mathrm{c1}}}{H_{\\mathrm{c2}}}\\approx\\frac{\\ln{\\kappa}}{2\\sqrt{2}\\kappa^{2}}\n$$ \n\nin the limit $\\kappa>>1$ of the Ginzburg–Landau parameter $\\begin{array}{r}{\\kappa=\\frac{\\lambda_{\\mathrm{L}}}{\\xi_{\\mathrm{GL}}}}\\end{array}$ Considering the experimental value of the first critical field of $3\\times{10}^{-2}$ T (Fig. 4c) and the abovementioned relation $60\\ \\mathrm{T}1 square centimeter that have a PCE >15%, as certified by an accredited photovoltaic calibration laboratory. Hysteresis in the current-voltage characteristics was eliminated; the PSCs were stable, with >90% of the initial PCE remaining after 1000 hours of light soaking.", + "Times Cited, WoS Core": 2031, + "Times Cited, All Databases": 2126, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000364955200041", + "Markdown": "# Efficient and stable large-area perovskite solar cells with inorganic charge extraction layers \n\nWei Chen,1, 2\\* Yongzhen Wu,1\\* Youfeng Yue,1 Jian Liu,1 Wenjun Zhang,2 Xudong Yang,3 Han Chen,3 Enbing Bi,3 Islam Ashraful,1 Michael Grätzel,4† Liyuan Han1,3† \n\n1Photovoltaic Materials Unit, National Institute for Materials Science, Tsukuba, Ibaraki 305-0047, Japan. 2Michael Grätzel Centre for Mesoscopic Solar Cells, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China. 3State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, 800 Dong Chuan Road, Minhang District, Shanghai 200240, China. 4Laboratory of Photonics and Interfaces, Department of Chemistry and Chemical Engineering, Swiss Federal Institute of Technology, Station 6, CH-1015 Lausanne, Switzerland. \\*These authors contributed equally to this work. \n\n# †Corresponding author. E-mail: michael.graetzel@epfl.ch (M.G.); han.liyuan@nims.go.jp (L.H.) \n\nThe recent stunning rise in power conversion efficiencies (PCEs) of perovskite solar cells (PSCs) has triggered worldwide intense research. However, high PCEvalues have often been reached with poor stability at an illuminated area of typically less than $0.1\\mathsf{c m}^{2}$ . We used heavily doped inorganic charge extraction layers in planar PSCs to achieve very rapid carrier extraction even with 10-20 nm thick layers avoiding pinholes and eliminating local structural defects over large areas. This robust inorganic nature allowed for the fabrication of PSCs with an aperture area $\\scriptstyle>1\\ c m^{2}$ showing a power conversion efficiency $(P C E)>15\\%$ certified by an accredited photovoltaic calibration laboratory. Hysteresis in the currentvoltage characteristics was eliminated; the PSCs were stable: $590\\%$ of the initial PCEremained after 1000 hours light soaking. \n\nOrganic–inorganic metal halide perovskite solar cells (PSCs) have attracted large attention due to the meteoric rise in their solar to electric power conversion efficiency $(P C E)$ over the last few years $(I)$ . In particular, methylammoniun $\\mathrm{(CH_{3}N H_{3}P b I_{3}}$ , denoted as $\\mathbf{MAPbI_{3}},$ ) and formamidinium lead iodide $\\mathrm{(CH(NH_{2})_{2}P b I_{3})}$ emerged as a highly attractive solar light harvesting materials because of their intense broad–band absorption, high charge carrier mobility, low–cost precursor materials and simple solution processing (2, 3). Their ambipolar semiconducting characteristics further enable variable device architectures, ranging from mesoscopic to planar structures with $\\scriptstyle\\mathbf{n-i-p}$ or p–i–n layouts (4). Mesoporous $\\mathrm{TiO_{2}}$ -based PSCs have reached the highest performance $(5-7)$ ; their certified PCE attaining presently $20.1\\%$ (8). However, there is growing interest in inverted $(\\mathsf{p-i-n})$ planar device architectures typically employing a $\\mathbf{MAPbI_{3}}$ –PCBM ([6,6]–phenyl– $\\mathrm{.c_{61}}^{\\mathrm{}}\\mathrm{.}$ – butyric acid methyl ester) bilayer junction, because of their simple fabrication and relatively small hysteresis (9–11). A key question that remains open to date is the true power conversion efficiency and stability of planar PSCs as none of the devices has been certified so far and their stability remains largely unexplored. Only hole–conductor–free mesoscopic PSCs using carbon as a back contact have shown so far promising stability under long term light soaking and long term heat exposure, but their certified PCE remains relatively low at $12.8\\%$ (12, 13). \n\nRegardless of their architectures, all high efficiency PSCs so far employed small areas, their device size being often $\\mathrm{<0.1\\cm^{2}}$ (Table S1) $(I4)$ . As such a small device size is prone to induce measurement errors, an obligatory minimum cell area of ${>}1$ $\\mathrm{cm^{2}}$ is required for certified PCEs to be recorded in the standard “Solar Cell Efficiency Tables” edited by public test centers, such as National Renewable Energy Laboratory (NREL) in the US and the National Institute of Advanced Industrial Science and Technology (AIST) in Japan (15). It has been recommended that the record efficiencies should be recorded with cell size of ideally 1 to $\\mathrm{2\\cm^{2}}$ or larger to allow comparison of competing technologies (16–19). Although a few works reported attempts of fabricating centimeter-scale PSCs, for example by using vacuum evaporation system (20) or modified two-step approach (21) to produce large area $\\mathbf{MAPbI_{3}}$ films, the PCEs obtained for these devices reached only $10.9\\%\\sim12.6\\%$ . Apart from the small device areas, the widely recognized hysteresis and stability issues of PSCs have raised doubts on the reliability of previously claimed high efficiencies (22, 23). \n\nThe poor reproducibility and lack of uniformity of PSCs render it challenging to obtain high efficiencies with large devices. It is difficult to control the formation of cracks and pinholes in the selective carrier extraction layers over large areas. As small size PSCs typically show a wide spread in their PCEs, previous work has focused on improving the uniformity of perovskite layer by varying its deposition methods (3, 6, 10). However, fewer studies have aimed at identifying selective extraction layers for photogenerated charge carriers placed over the current collector to prevent their recombination at its surface (24–26); event though such selective contacts have turned out to be equally important to developing efficient solar light harvesters (27). The dilemma with optimizing of such charge carrier extraction layers in solar cells is that the film should be thin to mimimize resistive losses while at the same time it should cover the whole collector area in a contiguous and uniform manner. Meeting these requirement becomes increasingly difficult as the device area increases. \n\nHere we present a strategy that addresses simultaneously the scale up and stability issues facing current PSC embodiments. We develop heavily p–doped $(\\mathfrak{p}^{+})$ $\\mathrm{Ni_{x}M g_{\\mathrm{1-x}}O}$ and n–doped $(\\mathbf{n}^{+})$ $\\mathrm{TiO_{x}}$ contacts to extract selectively photogenerated charge carriers from an inverted planar $\\mathbf{MAPbI_{3}}\\mathbf{-}$ PCBM film architecture. We implement the $\\mathbf{p}^{+}$ and $\\mathfrak{n}^{+}$ doping by substituting $\\mathrm{{Ni(Mg)^{2+}}}$ ions and $\\mathrm{Ti^{4+}}$ ions on the $\\mathrm{Ni_{x}M g_{\\mathrm{1-x}}O}$ lattice and $\\mathrm{TiO_{x}}$ matrix by $\\mathbf{Li}^{+}$ and $\\mathbf{Nb^{5+}}$ ions, respectively. The resulting dramatic increase in the electrical conductivity enables $10{-}20~\\mathrm{nm}$ thick oxide layers to be used for selective extraction of one type of charge carriers while improving their electronic blocking effect for the other type by reducing the density of pinholes and cracks over large areas. Accordingly, the series resistance $(R_{s})$ of the oxides decreased and the shunt resistance $(R_{\\mathrm{sh}})$ greatly increased with respect to the undoped ones, allowing excellent fill factor $(F F)$ with values exceeding 0.8 and hysteresis–free behavior to be achieved. With this strategy, we successfully fabricated large size $\\mathrm{(>1\\cm^{2})}$ PSCs with an efficiency of up to $16.2\\%$ . A $P C E$ of $15\\%$ was certified by a public test center (Calibration, Standards and Measurement Team at the Research Center for Photovoltaics, National Institute of Advanced Industrial Science and Technology, AIST, Japan). This is listed as the first official efficiency entry for PSCs in the most recent edition of the “Solar Cell Efficiency Tables” (28). Moreover, the devices based on these stable $\\boldsymbol{\\mathrm{p}}^{+}$ and $\\mathfrak{n}^{+}$ doped inorganic metal oxides charge extraction layers show high stability rendering them attractive for future practical deployment of PSCs. \n\nWe fabricated PSCs with an inverted planar device architecture (Fig. 1A); a cross sectional scanning electron microscopy (SEM) image of the device is shown in Fig. 1B. We first deposited the NiO based hole extraction layer onto fluorinedoped tin oxide (FTO) glass using spray pyrolysis. The precursor solution was composed of nickel (II) acetylacetonate alone or together with doping cations $\\mathrm{\\cdot}\\mathrm{Mg^{2+}}$ from magnesium acetate tetrahydrate, $\\mathbf{Li}^{+}$ from lithium acetate) in super– dehydrated acetonitrile/ethanol mixture. The $\\mathbf{MAPbI_{3}}$ perovskite layer with thickness of ${\\sim}300~\\mathrm{nm}$ was deposited by a reported method $\\left(6\\right)$ , which was followed by the deposition of a thin PCBM layer $(80\\ \\mathrm{nm})$ via spin–coating its chlorobenzol solution $(20\\mathrm{mg}\\mathrm{ml^{-1}})$ at $1000~\\mathrm{rpm}$ for 30 s. An n–type $\\mathrm{TiO_{x}}$ based electron extraction layer with and without $\\mathrm{Nb}^{5+}$ doping was further deposited on the PCBM by spin–coating a diluted methanol solution of titanium isopropoxide (or mixed with niobium ethoxide), followed by controlled hydrolysis and condensation (14). Finally, the device was completed by thermal evaporation of a $100~\\mathrm{{nm}}$ thick Ag cathode. The band alignments of relevant functional layers are shown in Fig. 1C, based on the energy levels determined by ultraviolet (UV) photoelectron spectroscopy (UPS) and ultraviolet–visible (UV–Vis) absorption spectroscopy measurements (fig. S1) (14). The uniformity of the perovskite and PCBM layers was examined by cross sectional SEM observation (fig. S2) (14). The full XPS spectra of the NiO and $\\mathrm{TiO_{x}}$ based charge carrier extraction layers are shown in fig. S3 (14), revealing the designated compositions for the target materials. The close–up observation on the morphology of the charge carrier extraction layers are depicted in fig. S4 $(I4)$ , while their pin–hole densities were examined by electrical measurement as discussed below. \n\nThe stoichiometric form of NiO is a wide band gap semiconductor with a very low intrinsic conductivity of $10^{-13}$ S $\\mathrm{cm^{-1}}$ (29). Self–doping by introducing $\\mathrm{Ni^{3+}}$ acceptors into the NiO crystal lattice renders the crystals more conductive, depending on the film deposition techniques and conditions (11, 30–32). The room temperature specific conductivity of our NiO films from Hall effect measurements was $1.66~\\times$ $10^{-4}~\\mathrm{{S}~c m^{-1}}$ . This value is much lower than the typically used p–type contact layer of PEDOT: PSS that shows a conductivity of 1 to $1000\\mathrm{~S~cm^{-1}}$ (33). The low conductivity of NiO will lead to a high $R_{s}$ resulting in a low $F F$ of the solar cells (34). Substitutional doping by $\\mathbf{Li^{+}}$ is an effective way to increase the p-conductivity of NiO (35). Values of heavily $(\\mathbf{p}^{+})$ –doped NiO films can reach 1 to $10\\ \\mathrm{S\\cm^{-1}}$ at room temperature under optimal conditions (36). For our $\\mathrm{Li^{+}}$ doped $\\mathrm{Ni_{x}M g_{\\mathrm{1-x}}O}$ films the conductivity is $2.32\\times10^{-3}\\mathrm{~S~cm^{-1}}$ , ${\\sim}12$ times greater than that of the undoped reference. \n\nA $\\mathbf{Mg^{2+}}$ content of $15\\mathrm{~mol\\%~}$ was alloyed in the $\\mathbf{Li^{+}}$ doped nickel oxide film, to compensate the undesirable positive shift of its valence band $(E_{\\mathrm{VB}})$ caused by $\\mathbf{Li}^{+}$ incorporation into the lattice (fig. S1) (14, 35, 37, 38). As the $\\mathbf{Li^{+}}$ content was adjusted to $5\\mathrm{mol\\%}$ , the doped oxide has the formula of $\\mathrm{Li}_{0.05}\\mathrm{Mg}_{0.15}\\ \\mathrm{Ni}_{0.8}\\mathrm{O}$ if one assumes that the molar ratio of the three different cations in the spray pyrolyses solution is maintained in the mixed oxide. This co–doping strategy is feasible because the mismatch of the ionic radii of $\\mathbf{Li}^{+}$ (0.76Å), $\\mathbf{Mg^{2+}}$ (0.71Å) and $\\mathrm{Ni^{2+}}$ (0.69Å) is quite small, conferring good lattice stability to the $\\mathrm{Li_{x}M g_{y}N i_{1-x-y}O}$ ternary oxides. We compared conductivity of NiO and $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ films by using contact–current mode of a scanning probe microscope (SPM) and show the results in Fig. 2, A and B. At a bias potential of $1.0\\mathrm{V}_{\\cdot}$ , the electric current increased by a factor of ${\\sim}10$ (from ${\\sim}0.3\\ \\mathrm{nA}$ to ${\\sim}3\\ \\mathrm{nA})$ upon replacing undoped NiO by a $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ film. The XPS spectra in fig. S6 (14) reveal that the doping increased the relative content of $\\mathrm{Ni^{3+}}$ acceptors in the $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ sample. These findings are consistent with reports on $\\mathbf{Li}^{+}$ doped NiO films in (32) and explains the increase in carrier concentration from $2.66\\times10^{17}\\mathrm{~cm^{-3}}$ of the undoped NiO film to $6.46\\times10^{18}$ $\\mathrm{cm}^{-3}$ for $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ film that we derived from Hall effect measurements. \n\nThe electron specific n–type $\\mathrm{TiO_{x}}$ contact used commonly for organic PV is normally fabricated by hydrolysis and condensation of titanium alkoxides at temperature below $\\mathrm{150^{\\circ}C}$ (39, 40), where the crystallization of $\\mathrm{TiO_{2}}$ is slow. In order to prevent heat-induced degradation of the perovskite layer and the adjacent interfaces, we kept the annealing temperature of $\\mathrm{TiO_{x}}$ films below $70^{\\circ}\\mathrm{C}.$ . While such $\\mathrm{TiO_{x}}$ films have been used extensively in organic PVs, details on their structure and mechanism of electric conduction have so far not been elucidated (41). One commonly recognized problem is that the amorphous nature of $\\mathrm{TiO_{x}}$ leads to extremely low specific conductivities that are in the range of $10^{-8}–10^{-6}$ S $\\mathrm{cm^{-1}}$ (42). $\\mathbf{N}\\mathbf{b}^{5+}$ doping has proved to be effective for enhancing the conductivity of crystalline anatase $\\mathrm{TiO_{2}}$ films to ${\\sim}10^{4}$ $\\mathrm{\\sf~s~cm^{-1}}$ , enabling its use as a transparent conducting oxide similar to conventional indium tin oxide (43). By analogy, this dopant is expected to improve also the conductivity of the amorphous $\\mathrm{TiO_{x}}$ via substitution of $\\mathrm{Ti^{4+}}$ by $\\mathrm{Nb^{5+}}$ which is expected to create donor centers. From the current-voltage $\\left(I/V\\right)$ curves obtained by SPM measurement shown in Fig. 2B, the conductivity of $\\mathrm{TiO_{x}}$ film was estimated to increase from about $10^{-6}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1}$ to $10^{-5}\\ \\mathrm{S\\cm^{-1}}$ upon adding $5\\ \\mathrm{mol\\%}$ $\\mathrm{Nb^{5+}}$ to the precursor solution. By resolving the XPS spectra in fig. S6 $(I4)$ , the relative content of $\\mathrm{Ti^{3+}}$ in comparison to $\\mathrm{Ti^{4+}}$ , i.e., the donor species in the $\\mathrm{TiO_{x}}$ film responsible for its n–type conductivity, has increased via $\\mathrm{Nb^{5+}}$ doping. \n\nWe derived the optimal thickness of the NiO- and $\\mathrm{TiO_{x}}.$ based charge-extraction layers from the electrical measurements shown in fig. S7 (14). A complete layer with no pinholes of NiO and $\\mathrm{TiO_{x}}$ requires at least thickness of $20\\ \\mathrm{nm}$ and $10\\ \\mathrm{nm}$ , respectively, regardless of the presence of dopants. These minimum thicknesses should depend on the underlayers’ (FTO for NiO, or PCBM for $\\mathrm{TiO_{x}}^{\\cdot}$ ) surface chemistry and morphology, as well as the fabrication methods used for the NiO and $\\mathrm{TiO_{x}}$ films. We compared small solar cells with size of $0.09\\ \\mathrm{cm^{2}}$ and varied the NiO layer thickness from 10, 20 to $40\\ \\mathrm{nm}$ , keeping that of the $\\mathrm{Ti}_{0.95}\\mathrm{Nb}_{0.05}\\mathrm{O}_{\\mathrm{x}}$ fixed at $10\\ \\mathrm{nm}$ . Conversely, we fixed the $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ layer thickness at $20~\\mathrm{{nm}}$ and varied that of the $\\mathrm{TiO_{x}}$ films from 5 to $30\\ \\mathrm{nm}$ . For each condition, 20 cells were made and measured to establish any underlying trends. As shown in fig. S8 $(I4)$ , although high performance can be occasionally achieved from devices with very thin charge carrier extraction layers $[\\sim]0\\ \\mathrm{nm\\NiO}$ or ${\\sim}5\\ \\mathrm{nm}\\ \\mathrm{TiO_{x}},$ , most devices showed lower PCEs because of lower $F F$ and open–circuit voltage $(V_{\\mathrm{oc}})$ (fig. S9) $(I4)$ , which can be attributed to the presence of substantial levels of pinholes. The reproducibility of device performance was greatly enhanced as the thickness of charge extraction layers increased, while the optimal performance was attained with $20\\ \\mathrm{nm\\NiO}$ and 10 nm $\\mathrm{TiO_{x}}$ film, in agreement with the electrical measurement. Further increasing the film thickness of the two charge extraction layers can lead to a large efficiency decline caused by increased internal resistance, larger optical loss, or both (fig. S10) $(I4)$ . Thus, we fixed the thickness of NiO and $\\mathrm{TiO_{x}}$ at $20\\ \\mathrm{nm}$ and $10\\ \\mathrm{nm}$ , respectively for the following studies of doping effect on device performance. \n\nFigure 3A shows the effect of doping the NiO and $\\mathrm{TiO_{x}}$ charge extraction layers on the photocurrent density– voltage $\\left(J{-}V\\right)$ curves of PSCs measured under simulated AM 1.5 sunlight with forward scanning direction. The short circuit current $(J_{\\mathrm{sc}})$ , $V_{\\mathrm{oc}},F F_{\\mathrm{i}}$ , and $P C E$ data are listed in Table S2 $(I4)$ . Both doping of NiO and $\\mathrm{TiO_{x}}$ reduced $R_{\\mathrm{s}}$ and improved the $F F_{:}$ and to a lesser extent $J_{\\mathrm{sc}}$ and $V_{\\mathrm{{oc}}}$ . The $\\mathrm{TiO_{x}}$ electron extraction layers mainly affect the shape of $J{-}V$ curves in the forward bias range from 0.7 to $1.0\\mathrm{~V~}$ , where a Schottkybarrier type contact between PCBM and Ag strongly restricted efficient electron collection (fig. S9A) (14, 44). The $\\mathbf{N}\\mathbf{b}^{5+}$ doping of $\\mathrm{TiO_{x}}$ reduced the interfacial electron transfer resistance and facilitated electron transport, increasing the photocurrent especially in the 0.7 to $1.0\\mathrm{~V~}$ forward bias region. The NiMg(Li)O-based hole extraction layer promoted ohmic contact formation at the FTO–MAPbI3 interface by decreasing the barrier height through the staircase energy level alignment shown in Fig. 1C. $\\mathbf{P}^{+}$ –doping increased the electrical conductivity by decreasing the charge transport resistance and hence enhancing hole extraction. \n\nDoping of both NiO and $\\mathrm{TiO_{x}}$ improves the cell performance by increasing the values of $F F$ and $V_{\\mathrm{{oc}}}$ to 0.827 and $1.083\\mathrm{~V~}$ , respectively, leading to $P C E$ of $18.3\\%$ for this planar PSC with MAPbI3. In comparison to PEDOT:PSS based PSCs, the $V_{\\mathrm{{oc}}}$ increased by ${\\sim}100~\\mathrm{~mV}$ , indicating that with $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ , the holes can be extracted at a higher energy level (10). Furthermore, the $F F$ of 0.83 is one of the highest values for reported PSCs $(8,\\ 9,\\ 23)$ , demonstrating the key role of the charge extraction layers in minimizing resistive losses and improving the photovoltaic performance. \n\nTo gain further insight into the reasons for the performance enhancement by the doping, we characterized the charge carrier extraction, transportation and recombination by nanosecond time–resolved photoluminescence (PL) decay using a picosecond laser flash as excitation source and by measuring transient photocurrent/photovoltage decays on the microsecond scale. The charge extraction involved in our cells include the electron transfer from the $\\mathbf{MAPbI_{3}}$ absorber layer to PCBM/ $\\mathrm{\\DeltaTiO_{x}}$ and hole transfer to NiO as well as the carrier transport in the TiOx and $\\mathrm{{NiMg(Li)O}}$ layers. The perovskite/PCBM interface has been demonstrated to be very efficient for electron extraction (9–11). Doping of the $\\mathrm{TiO_{x}}$ extraction layer is unlikely to have a direct impact on the electron injection rate because of it physical separation from the MAPbI3 by $80\\ \\mathrm{nm}$ -thick PCBM layer. Nevertheless, it greatly accelerates the electron extraction by decreasing the electron transport time as shown in Fig. 3C. Figure 3B shows the PL decays of the MAPbI3 films on different substrates, including a glass slide, and NiO and $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ deposited on FTO glass. The MAPbI3 itself showed a long PL lifetime of $>100~\\mathrm{ns}$ , indicating slow carrier recombination in the perovskite layer (10). When contacted with the p–type hole extraction layers, the PL lifetimes were shortened to a similar degree for both doped and undoped NiO–MAPbI3 contacts. Thus, doping has a negligible influence on the hole injection. \n\nWe derived the charge transport and recombination time constants ( $\\overline{{\\tau}}_{\\mathrm{t}}$ and $\\mathrm{\\Delta\\tau_{r})}$ from the transient photocurrent and photovoltage decays measured at short and open circuit, respectively (Fig. 3C). The $\\tau_{\\mathrm{t}}$ decreased by ${\\sim}5$ fold from 4.41 μs for undoped cell to 0.88 μs for doped cell, confirming the much faster charge transport through the doped charge carrier extraction layers compared to the undpoed ones. However, the $\\mathrm{~\\tt~{~T~r~}~}$ of a doped cell is substantially longer than that of an undoped one (84.8 vs. 50.5 μs, Fig. 3D), which we attribute to slower interfacial charge recombination since the very rapid carrier collection prevents charge accumulation at the interface of the pervovskite with the charge extraction layer. The doping-induced difference in charge transport/recombination kinetics should be the main reason responsible for their performance enhancement. \n\nThe hysteresis of our cells was examined by using different scan rates and directions. By decreasing the step width from $70~\\mathrm{mV}$ to $\\mathrm{~5~mV}$ , the PCEs determined from the forward scan slightly increased from $18.14\\%$ to $18.35\\%$ . However, the reverse scan PCEs decreased substantially from $22.35\\%$ at 70 mV/step (fig. S11A and table S3 (14)) to $18.40\\%$ at $5\\mathrm{mV}/$ step. The steady power outputs measurements (fig. S11D) $(I4)$ indicate that the $P C E\\mathbf{s}$ obtained in forward scans and at small step widths $(5{-}10~\\mathrm{mV})$ are near the real performance. The $V_{\\mathrm{{oc}}}$ and $P C E$ obtained at a fast reverse scan, i.e., 1.273 V and $22.35\\%$ at $70\\mathrm{\\mV/}$ step, are largely overestimated. With the step widths of $\\mathrm{5-10~mV}$ , the $P C E$ deviations between forward and reverse scans are very small, i.e., within $0.3\\%$ in absolute $P C E$ values reflecting negligible hysteresis. A histogram comparing the difference in the PCEs obtained from scanning in the forward and reverse bias directions is shown in fig. S11C $(I4)$ , supporting the absence of hysteresis for the optimized device architecture. In stark contrast, for undoped charge extraction layers, a pronounced hysteresis was observed even for slow scan rates (fig. S11E) $(I4)$ , which is likely to arise from unbalanced charge accumulation at the two interfaces (45). Thus, the $\\mathrm{Li_{0.05}M g_{0.15}N i_{0.8}O}$ and $\\mathrm{Ti}_{0.95}\\mathrm{Nb}_{0.05}\\mathrm{O}_{\\mathrm{x}}$ charge extraction layer create a robust low impedance interface that can mitigate the $J{-}V$ hysteresis under a routine scanning condition. \n\nWe fabricate cells with active area $\\mathrm{>}1\\ \\mathrm{cm}^{2}$ as a first step toward scale up of the photovoltaic devices. Figure 4A shows the $J{-}V$ curve of such cell with aperture area of 1.02 $\\mathrm{cm^{2}}$ . It shows excellent performance, with $J_{\\mathrm{sc}},\\ V_{\\mathrm{oc}},$ and $F F$ reaching values of $20.21\\mathrm{mAcm^{-2}}$ , $\\boldsymbol{\\mathrm{1.072~V}}$ and 0.748, respectively, corresponding to a $P C E$ of $16.2\\%$ . Hysteresis for these large area devices is also small (fig. S12) $(I4)$ . The corresponding IPCE (Fig. 4B) shows a broad plateau with maximum value of $90.1\\%$ over practically the whole visible range. The integrated $J_{\\mathrm{sc}}$ from $I P C E$ matches well with the measured value. Compared to small size cells $\\left(0.09\\ \\mathrm{cm^{2}}\\right)$ , a ${\\sim}10\\%$ decrease in $P C E$ was observed in large size cells $(1.02\\ \\mathrm{cm^{2}})$ , which is mainly caused by the large sheet resistance of the FTO. We sent one of our best large cells to a public test center (AIST, Japan) for certification. A PCE of $15.0\\%$ for a 1.017 $\\mathrm{cm^{2}}$ device was certified (fig. S13) $(I4)$ . \n\nTo demonstrate the superiority of the solution processible $\\mathrm{Ti}_{0.95}\\mathrm{Nb}_{0.05}\\mathrm{O}_{\\mathrm{x}}$ charge carrier extraction layer, two references, i.e., Ca $(4\\mathrm{nm})/\\mathrm{Ag},$ , LiF $(1.5\\mathrm{nm})/\\mathrm{Ag}$ that were deposited by thermal evaporation, were compared with our best interfacial condition. As shown in Fig. 4C, without sealing, the $\\mathrm{Ti(Nb)O_{x}}$ based PSC shows the best stability since its $P C E$ only decreased by $\\sim5\\%$ of its initial value after 1 week. The $\\mathrm{Ca/Ag}$ based PSC showed the fastest degradation, which lost its initial $P C E$ by ${>}30\\%$ after 1 day and by $\\sim45\\%$ within 1 week. This difference is attributed to the fast oxidization of very reactive Ca, leading to dramatic loss on $J_{\\mathrm{sc}}$ and $F F.$ . The LiF/Ag based PSC lost $15\\%$ of its initial $P C E$ within 1 week. The extremely thin LiF layer $(<2.5~\\mathrm{nm}$ , as required by efficient tunneling) $(46)$ and the high sensitivity of LiF to moisture is likely to be responsible for the corresponding cell’s inferior stability. It is possible that the stability of Ca or LiF based devices can be improved if they are thoroughly sealed. However, the requirement on sealing quality will be much more critical in comparison to the air–stable interface of $\\mathrm{Ti}_{0.95}\\mathrm{Nb}_{0.05}\\mathrm{O}_{\\mathrm{x}}$ (39). \n\nThe $\\mathrm{Ti}_{0.95}\\mathrm{Nb}_{0.05}\\mathrm{O}_{\\mathrm{x}}$ layer also shields the perovskite from the intrusion of humidity. It assumes a similar role in OPVs (39). We exposed bare $\\mathbf{MAPbI_{3}},$ , MAPbI3/PCBM and MAP$\\mathrm{bI_{3}/P C B M/T i(N b)O_{x}}$ , to ambient air under room light for 3 weeks. A striking difference in color degradation associated with perovskite decomposition became clearly visible (fig. S14) (14). Thus it appears that the hydrophobic nature of PCBM may protect the perovskite from reaction with water, while the coating of $\\mathrm{Ti(Nb)O_{x}}$ could further enhance the stability. \n\nFigure 4D also shows the long–term stability of PSCs using the optimized inorganic charge extraction layers. The silver back contact was protected by a covering glass which was separated from the front FTO glass by a UV-activated glue used as a sealant. The cells maintained $97\\%$ of their initial $P C E$ after keeping them in the dark for 1000 hours. Exposing the cells for 1000 hours at short–circuit condition to full sunlight from a solar simulator, resulted in a $P C E$ degradation of less than $10\\%$ . This degradation is consistent with the general tendency among 10 devices, as shown in fig. S15 (14), indicative of their good long-term stability. During this time, an electric charge of around $72^{\\circ}000\\mathrm{~C~}$ $(4.49\\times$ $10^{23}$ electrons) passed through the device. This result shows that the planar cell structure and the metal oxides extraction layers, as well as the organo–metal halide perovskite material, are robust enough to sustain continued current flow under light exposure for 1000 hours. A further increase in the $P C E$ without sacrificing stability could be expected from varying the composition of the pervoskite, e.g., replacing part of the methylammonium cations in the $\\mathbf{MAPbI_{3}}$ pervovskite by formamidinium (47) and a small fraction of the iodide by bromide anions. \n\n# REFERENCES AND NOTES \n\n1. G. Hodes, Perovskite-based solar cells. Science 342, 317–318 (2013). Medline \n\ndoi:10.1126/science.1245473 \n2. G. Xing, N. Mathews, S. Sun, S. S. Lim, Y. M. Lam, M. Grätzel, S. Mhaisalkar, T. C. Sum, Long-range balanced electron- and hole-transport lengths in organicinorganic CH3NH3PbI3. Science 342, 344–347 (2013). Medline \n3. Q. Dong, Y. Fang, Y. Shao, P. Mulligan, J. Qiu, L. Cao, J. Huang, Electron-hole diffusion lengths $>175\\upmu\\mathrm{m}$ in solution-grown CH3NH3PbI3 single crystals. Science 347, 967–970 (2015). Medline doi:10.1126/science.aaa5760 \n4. M. Liu, M. B. Johnston, H. J. Snaith, Efficient planar heterojunction perovskite solar cells by vapour deposition. Nature 501, 395–398 (2013). Medline doi:10.1038/nature12509 \n5. J. Burschka, N. Pellet, S. J. Moon, R. Humphry-Baker, P. Gao, M. K. Nazeeruddin, M. Grätzel, Sequential deposition as a route to high-performance perovskitesensitized solar cells. Nature 499, 316–319 (2013). Medline doi:10.1038/nature12340 \n6. N. J. Jeon, J. H. Noh, Y. C. Kim, W. S. Yang, S. Ryu, S. I. Seok, Solvent engineering for high-performance inorganic-organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). Medline doi:10.1038/nmat4014 \n7. N. J. Jeon, J. H. Noh, W. S. Yang, Y. C. Kim, S. Ryu, J. Seo, S. I. Seok, Compositional engineering of perovskite materials for high-performance solar cells. Nature 517, 476–480 (2015). Medline doi:10.1038/nature14133 \n8. W. S. Yang, J. H. Noh, N. J. Jeon, Y. C. Kim, S. Ryu, J. Seo, S. I. Seok, Highperformance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237 (2015). Medline doi:10.1126/science.aaa9272 \n9. J. H. Heo, H. J. Han, D. Kim, T. K. Ahn, S. H. Im, Stable semi-transparent CH3NH3PbI3 planar sandwich solar cells. Energy Environ. Sci. 8, 1602–1608 (2015). \n10. W. Nie, H. Tsai, R. Asadpour, J. C. Blancon, A. J. Neukirch, G. Gupta, J. J. Crochet, M. Chhowalla, S. Tretiak, M. A. Alam, H. L. Wang, A. D. Mohite, High-efficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 347, 522–525 (2015). Medline doi:10.1126/science.aaa0472 \n11. J. H. Park, J. Seo, S. Park, S. S. Shin, Y. C. Kim, N. J. Jeon, H. W. Shin, T. K. Ahn, J. H. Noh, S. C. Yoon, C. S. Hwang, S. I. Seok, Efficient CH3NH3PbI3 perovskite solar cells employing nanostructured p-type NiO electrode formed by a pulsed laser deposition. Adv. Mater. 27, 4013–4019 (2015). Medline doi:10.1002/adma.201500523 \n12. A. Mei, X. Li, L. Liu, Z. Ku, T. Liu, Y. Rong, M. Xu, M. Hu, J. Chen, Y. Yang, M. Grätzel, H. Han, A hole-conductor–free, fully printable mesoscopic perovskite solar cell with high stability. Science 345, 295–298 (2014). Medline \n13. X. Li, M. Tschumi, H. Han, S. S. Babkair, R. A. Alzubaydi, A. A. Ansari, S. S. Habib, M. K. Nazeeruddin, S. M. Zakeeruddin, M. Grätzel, Outdoor performance and stability under elevated temperatures and long-term light soaking of triple-layer mesoporous perovskite photovoltaics. Energy Technol. 3, 551–555 (2015). doi:10.1002/ente.201500045 \n14. Materials and methods are available as supplementary materials on Science Online. \n15. M. A. Green, K. Emery, Y. Hishikawa, W. Warta, E. D. Dunlop, Solar cell efficiency tables (Version 45). Prog. Photovolt. Res. Appl. 23, 1–9 (2015). doi:10.1002/pip.2573 \n16. M. C. Beard, J. M. Luther, A. J. Nozik, The promise and challenge of nanostructured solar cells. Nat. Nanotechnol. 9, 951–954 (2014). Medline doi:10.1038/nnano.2014.292 \n17. E. Zimmermann, P. Ehrenreich, T. Pfadler, J. A. Dorman, J. Weickert, L. SchmidtMende, Erroneous efficiency reports harm organic solar cell research. Nat. Photonics 8, 669–672 (2014). doi:10.1038/nphoton.2014.210 \n18. K. D. G. I. Jayawardena, L. J. Rozanski, C. A. Mills, S. R. P. Silva, The true status of solar cell technology. Nat. Photonics 9, 207–208 (2015). doi:10.1038/nphoton.2015.45 \n19. Bringing solar cell efficiencies into the light. Nat. Nanotechnol. 9, 657 (2014). \n20. O. Malinkiewicz, C. Roldán-Carmona, A. Soriano, E. Bandiello, L. Camacho, M. K. Nazeeruddin, H. J. Bolink, Metal-oxide-free methylammonium lead iodide perovskite-based solar cells: The influence of organic charge transport layers. Adv. Energy Mater. 4, 1400345 (2014). doi:10.1002/aenm.201400345 \n21. Z. Yang, B. Cai, B. Zhou, T. Yao, W. Yu, S. F. Liu, W.-H. Zhang, C. Li, An up-scalable approach to CH3NH3PbI3 compact films for high-performance perovskite solar cells. Nano Energy 15, 670–678 (2015). doi:10.1016/j.nanoen.2015.05.027 \n22. M. Grätzel, The light and shade of perovskite solar cells. Nat. Mater. 13, 838–842 (2014). Medline doi:10.1038/nmat4065 \n23. M. Gunther, “Meteoritic rise of perovskite solar cells under scrutiny over efficiencies,” Chemistry World, 2 March 2015; www.rsc.org/chemistryworld/2015/02/meteoritic-rise-perovskite-solar-cellsunder-scrutiny-over-efficiencies. \n24. H. Zhou, Q. Chen, G. Li, S. Luo, T. B. Song, H. S. Duan, Z. Hong, J. You, Y. Liu, Y. Yang, Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). Medline doi:10.1126/science.1254050 \n25. O. Malinkiewicz, A. Yella, Y. H. Lee, G. M. Espallargas, M. Graetzel, M. K. Nazeeruddin, H. J. Bolink, Perovskite solar cells employing organic chargetransport layers. Nat. Photonics 8, 128–132 (2014). doi:10.1038/nphoton.2013.341 \n26. Q. Lin, A. Armin, R. C. R. Nagiri, P. L. Burn, P. Meredith, Electro-optics of perovskite solar cells. Nat. Photonics 9, 106–112 (2015). doi:10.1038/nphoton.2014.284 \n27. A. G. Aberle, Surface passivation of crystalline silicon solar cells: A review. Prog. Photovolt. Res. Appl. 8, 473–487 (2000). doi:10.1002/1099- 159X(200009/10)8:5<473::AID-PIP337>3.0.CO;2-D \n28. M. A. Green, K. Emery, Y. Hishikawa, W. Warta, E. D. Dunlop, Solar cell efficiency tables (version 46). Prog. Photovolt. Res. Appl. 23, 805–812 (2015). doi:10.1002/pip.2637 \n29. M. A. Wittenauer, L. L. Van Zandt, Surface conduction versus bulk conduction in pure stoichiometric NiO crystals. Philos. Mag. B 46, 659–667 (1982). doi:10.1080/01418638208223551 \n30. J. H. Kim, P. W. Liang, S. T. Williams, N. Cho, C. C. Chueh, M. S. Glaz, D. S. Ginger, A. K. Jen, High-performance and environmentally stable planar heterojunction perovskite solar cells based on a solution-processed copper-doped nickel oxide hole-transporting layer. Adv. Mater. 27, 695–701 (2015). Medline doi:10.1002/adma.201404189 \n31. Z. Zhu, Y. Bai, T. Zhang, Z. Liu, X. Long, Z. Wei, Z. Wang, L. Zhang, J. Wang, F. Yan, S. Yang, High-performance hole-extraction layer of sol–gel-processed $N i O_{x}$ nanocrystals for inverted planar perovskite solar cells. Angew. Chem. Int. Ed. 53, 12571–12575 (2014). \n32. C. Wu, C. Yang, Effect of annealing temperature on the characteristics of the modified spray deposited Li-doped NiO films and their applications in transparent heterojunction diode. Sol. Energy Mater. Sol. Cells 132, 492–498 (2015). doi:10.1016/j.solmat.2014.09.017 \n33. Y. H. Kim, C. Sachse, M. L. Machala, C. May, L. Müller-Meskamp, K. Leo, Highly conductive PEDOT:PSS electrode with optimized solvent and thermal posttreatment for ITO-free organic solar cells. Adv. Funct. Mater. 21, 1076–1081 (2011). doi:10.1002/adfm.201002290 \n34. X. F. Chen, H. M. Huang, X. L. Li, G. J. Liu, H. Zhang, Slightly focused high-energy shockwave therapy: A potential adjuvant treatment for osteoporotic fracture. Int. J. Clin. Exp. Med. 8, 5044–5054 (2015). Medline \n35. N. Alidoust, M. C. Toroker, J. A. Keith, E. A. Carter, Significant reduction in NiO band gap upon formation of LixNi1– $_{\\mathbf{\\nabla}\\cdot\\mathbf{\\vec{x}}}0$ alloys: Applications to solar energy conversion. ChemSusChem 7, 195–201 (2014). Medline doi:10.1002/cssc.201300595 \n36. U. S. Joshi, Y. Matsumoto, K. Itaka, M. Sumiya, H. Koinuma, Combinatorial synthesis of Li-doped NiO thin films and their transparent conducting properties. Appl. Surf. Sci. 252, 2524–2528 (2006). doi:10.1016/j.apsusc.2005.03.239 \n37. Z. Huang, X. Zeng, H. Wang, W. Zhang, Y. Li, M. Wang, Y.-B. Cheng, W. Chen, Enhanced performance of $\\mathsf{p}$ -type dye sensitized solar cells based on mesoporous Ni1 $-x$ $_\\mathrm{{\\times}}\\mathsf{M g}_{\\mathrm{{\\times}}}0$ ternary oxide films. RSC Adv. 4, 60670–60674 (2014). doi:10.1039/C4RA09727K \n38. J. Deng, M. Mortazavi, N. V. Medhekar, J. Zhe Liu, Band engineering of Ni1−xMgxO alloys for photocathodes of high efficiency dye-sensitized solar cells. J. Appl. Phys. 112, 123703 (2012). doi:10.1063/1.4769210 \n39. K. Lee, J. Y. Kim, S. H. Park, S. H. Kim, S. Cho, A. J. Heeger, Air-stable polymer electronic devices. Adv. Mater. 19, 2445–2449 (2007). doi:10.1002/adma.200602653 \n40. T. Kuwabara, T. Nakayama, K. Uozumi, T. Yamaguchi, K. Takahashi, Highly durable inverted-type organic solar cell using amorphous titanium oxide as electron collection electrode inserted between ITO and organic layer. Sol. Energy Mater. Sol. Cells 92, 1476–1482 (2008). doi:10.1016/j.solmat.2008.06.012 \n41. T. Kuwabara, H. Sugiyama, T. Yamaguchi, K. Takahashi, Inverted type bulkheterojunction organic solar cell using electrodeposited titanium oxide thin films as electron collector electrode. Thin Solid Films 517, 3766–3769 (2009). doi:10.1016/j.tsf.2008.12.039 \n42. K. Wojciechowski, M. Saliba, T. Leijtens, A. Abate, H. J. Snaith, Sub-150 °C processed meso-superstructured perovskite solar cells with enhanced efficiency. Energy Environ. Sci. 7, 1142–1147 (2014). \n43. Y. Furubayashi, T. Hitosugi, Y. Yamamoto, K. Inaba, G. Kinoda, Y. Hirose, T. Shimada, T. Hasegawa, A transparent metal: Nb-doped anatase TiO2. Appl. Phys. Lett. 86, 252101–252103 (2005). doi:10.1063/1.1949728 \n44. S. Braun, W. R. Salaneck, M. Fahlman, Energy-level alignment at organic/metal and organic/organic interfaces. Adv. Mater. 21, 1450–1472 (2009). doi:10.1002/adma.200802893 \n45. J. H. Heo, D. H. Song, H. J. Han, S. Y. Kim, J. H. Kim, D. Kim, H. W. Shin, T. K. Ahn, C. Wolf, T. W. Lee, S. H. Im, Planar CH3NH3PbI3 perovskite solar cells with constant $17.2\\%$ average power conversion efficiency irrespective of the scan rate. Adv. Mater. 27, 3424–3430 (2015). Medline doi:10.1002/adma.201500048 \n46. X. Liu, H. Yu, L. Yan, Q. Dong, Q. Wan, Y. Zhou, B. Song, Y. Li, Triple cathode buffer layers composed of PCBM, $\\mathsf{C}_{60}$ , and LiF for high-performance planar perovskite solar cells. ACS Appl. Mater. Interfaces 7, 6230–6237 (2015). Medline doi:10.1021/acsami.5b00468 \n47. J. Liu, Y. Shirai, X. Yang, Y. Yue, W. Chen, Y. Wu, A. Islam, L. Han, High-quality mixed-organic-cation perovskites from a phase-pure non-stoichiometric intermediate (FAI)1– $-x^{.}$ -PbI2 for solar cells. Adv. Mater. 27, 4918–4923 (2015). Medline doi:10.1002/adma.201501489 \n48. P. Puspharajah, S. Radhakrishna, A. K. Arof, Transparent conducting lithiumdoped nickel oxide thin films by spray pyrolysis technique. J. Mater. Sci. 32, 3001–3006 (1997). doi:10.1023/A:1018657424566 \n49. T. Dutta, P. Gupta, A. Gupta, J. Narayan, Effect of Li doping in NiO thin films on its transparent and conducting properties and its application in heteroepitaxial p-n junctions. J. Appl. Phys. 108, 083715 (2010). doi:10.1063/1.3499276 \n50. T. Moehl, J. H. Im, Y. H. Lee, K. Domanski, F. Giordano, S. M. Zakeeruddin, M. I. Dar, L. P. Heiniger, M. K. Nazeeruddin, N. G. Park, M. Grätzel, Strong photocurrent amplification in perovskite solar cells with a porous TiO2 blocking layer under reverse bias. J. Phys. Chem. Lett. 5, 3931–3936 (2014). Medline \n\n# ACKNOWLEDGMENTS \n\nThis work was partially supported by the Core Research for Evolutional Science and Technology of the Japan Science and Technology Agency. The authors thank Dr. H. Kanai at Materials Analysis Station of NIMS, Japan for high resolution SEM image measurement, and Mr. T. Shimizu, Mr. T. Ishikawa for technical support. The author, L. Han, thanks for Prof. Hiroyoshi Naito of Osaka Prefecture University and Dr. Masafumi Shimizu of Institute of Advanced Energy, Kyoto University for their useful discussions. The author, M. Grätzel thanks for financial support of this work under the Swiss Nanotera and Swiss National Science Foundation PV2050 program and acknowledges his affiliation as a visiting faculty member with Nanyang Technological University (NTU) Singapore and the Advanced Institute for Nanotechnology at Sungkyunkwan University (SKKU), Suwon, Korea. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/cgi/content/full/science.aad1015/DC1 \nMaterials and Methods \nFigs. S1 to S15 \nTables S1 to S3 \nReferences (48–50) \n\n![](images/eb70af8805096da2eb3e5b4de4faa1bb638fdf9c7010b8d839aedc5dca137ea7.jpg) \n\nFig. 1. Structure and band alignments of the PSC. (A) Scheme of the cell configuration highlighting the doped charge carrier extraction layers. The right insets shows the composition of $T i(N b)0_{x}$ and the crystal structure of lithium doped ${\\sf N i}_{\\sf x}{\\sf M g}_{\\mathrm{1-x}}\\mathrm{O}$ , denoted as ${\\mathsf{N i M g}}(\\mathsf{L i})0$ . (B) A high resolution $\\mathsf{c r o s s-}$ sectional SEM image of a complete solar cell (the corresponding EDX analysis results are shown in fig. S5 (14), demonstrating the presence of the ${\\mathsf{p}}^{+}$ –doped ${\\sf N i}_{\\mathrm{{x}}}{\\sf M g}_{\\mathrm{1-x}}\\mathrm{O}$ and ${\\mathfrak{n}}^{+}$ –doped $T_{\\mathrm{iO_{x}}}$ charge extraction layers). (C) Band alignments of the solar cell. The data of ${\\mathsf{M A P b}}{\\mathsf{b}}{\\mathsf{l}}_{3}$ and PCBM are taken from (11). \n\n![](images/a392d71f9a124cad7fcda01abac9b49f5c061f787ef2de6aa8bc4ad4b5a6bcf8.jpg) \nFig. 2. Dopant enhanced conductivity of NiO and $T_{\\mathrm{iO_{x}}}$ . (A) Comparison of the conductivity mapping results for NiO (Left) and $\\mathsf{L i}_{0.05}\\mathsf{M g}_{0.15}\\mathsf{N i}_{0.8}\\mathsf{O}$ (Right) films. (B) Left: Comparison of the $I{-}V$ curves of NiO and $\\mathsf{L i}_{0.05}\\mathsf{M g}_{0.15}\\mathsf{N i}_{0.8}\\mathsf{O}$ films deposited on FTO glass and Right: Comparison of the $I{-}V$ curves for $T_{\\mathrm{iO_{x}}}$ and $\\mathsf{T i}_{0.95}\\mathsf{N b}_{0.05}\\mathsf{O}_{\\mathsf{x}}$ films deposited on PCBM/ITO glass, obtained by SPM measurements. Thickness was 20 nm for both NiO and $T_{\\mathrm{iO_{x}}}$ based films. \n\n![](images/73966dbd3876e167b8943e640de78d256cf130289213c6837f98bb7929c1dfe0.jpg) \nFig. 3. Doping enhanced photovoltaic performance. (A) $J-V$ curves of solar cells based on different combinations of charge extraction layers with standard thickness (NiO, $\\mathsf{N i M g}(\\mathsf{L i})0=20~\\mathsf{n m}$ ; $T i O_{x}$ , $\\mathsf{T i}(\\mathsf{N b})\\mathsf{O}_{\\mathsf{x}}=10$ nm). (B) Normalized PL transient decay curves of perovskite and perovskite at the controlled interfaces of NiO and ${\\mathsf{N i M g}}(\\mathsf{L i})0$ , solid lines are fitted results with a double exponential decay. The time interval during which the PL decays to $1/\\mathsf{e}$ of the initial intensity is defined as the characteristic lifetime (τ) of free carriers after photoexcitation. (C) and (D) show normalized transient photocurrent and photovoltage decay curves, respectibely based on undoped and doped charge carrier extraction layers. The charge transport $\\left(\\uptau_{\\mathrm{t}}\\right)$ and recombination time $\\left(\\uptau_{\\mathsf{r}}\\right)$ are again defined as the time interval during which the photocurrent or photovoltage decays to $1/\\mathsf{e}$ of the their initial value immediately after excitation. \n\n![](images/fbd9955f1b5d0a14775a7c7d0192e5fa98219f7c99af4c8bb4d2842f99a4a285.jpg) \nFig. 4. Performance and stability of large size cells. (A) $J{-}V$ curve of the best large cell endowed with anti–reflection film, (B) the corresponding IPCE spectrum and integrated $J_{\\mathsf{s c}}$ , (C) the stability of the cells without sealing, based on different electron extraction layers of Ca (4 nm), LiF $(1.5\\ \\mathsf{n m})$ and $\\mathsf{T i}(\\mathsf{N b})\\mathsf{O}_{\\mathsf{x}}$ $(10\\ \\mathsf{n m})$ between PCBM and the Ag contact, the cells were kept in a dry cabinet ( $\\mathit{\\Pi}_{<}^{\\cdot}$ $20\\%$ humidity) in the dark and measured in ambient air, (D) stability of sealed cells kept in the dark or under simulated solar light (AM 1.5, $100\\mathrm{\\mW\\cm^{-2}}$ , using a $420\\mathsf{n m}\\mathsf{U V}$ light cut–off filter, surface temperature of the cell: $45^{\\circ}$ to $50^{\\circ}\\mathrm{C}$ , bias potential $=0\\vee$ ). " + }, + { + "id": "10.1039_c4sc03141e", + "DOI": "10.1039/c4sc03141e", + "DOI Link": "http://dx.doi.org/10.1039/c4sc03141e", + "Relative Dir Path": "mds/10.1039_c4sc03141e", + "Article Title": "Reversible photo-induced trap formation in mixed-halide hybrid perovskites for photovoltaics", + "Authors": "Hoke, ET; Slotcavage, DJ; Dohner, ER; Bowring, AR; Karunadasa, HI; McGehee, MD", + "Source Title": "CHEMICAL SCIENCE", + "Abstract": "We report on reversible, light-induced transformations in (CH3NH3) Pb(BrxI1-x) 3. Photoluminescence (PL) spectra of these perovskites develop a new, red-shifted peak at 1.68 eV that grows in intensity under constant, 1-sun illumination in less than a minute. This is accompanied by an increase in sub-bandgap absorption at similar to 1.7 eV, indicating the formation of luminescent trap states. Light soaking causes a splitting of X-ray diffraction (XRD) peaks, suggesting segregation into two crystalline phases. Surprisingly, these photo-induced changes are fully reversible; the XRD patterns and the PL and absorption spectra revert to their initial states after the materials are left for a few minutes in the dark. We speculate that photoexcitation may cause halide segregation into iodide-rich minority and bromide-enriched majority domains, the former acting as a recombination center trap. This instability may limit achievable voltages from some mixed-halide perovskite solar cells and could have implications for the photostability of halide perovskites used in optoelectronics.", + "Times Cited, WoS Core": 1783, + "Times Cited, All Databases": 1947, + "Publication Year": 2015, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000345901600072", + "Markdown": "View Article Online View Journal \n\n# Chemical Science \n\nAccepted Manuscript \n\nThis article can be cited before page numbers have been issued, to do this please use: E. T. Hoke, D. J. Slotcavage, E. R. Dohner, A. R. Bowring, H. I. Karunadasa and M. D. McGehee, Chem. Sci., 2014, DOI: \n\n![](images/327da28dc256783fce91220ada3cc665030ae92b48a96587d6b4504e0b053411.jpg) \n\nThis is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication. \n\nAccepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof reading. Using this free service, authors can make their results available to the community, in citable form, before we publish the edited article. We will replace this Accepted Manuscript with the edited and formatted Advance Article as soon as it is available. \n\nYou can find more information about Accepted Manuscripts in the Information for Authors. \n\nPlease note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. \n\n# Chemical Science \n\n# Reversible photo-induced trap formation in mixedhalide hybrid perovskites for photovoltaics† \n\nReceived Ooth January 2012, Accepted Ooth January 2012 \n\nDOI:10.1039/x0xx00000x \n\nEric. T. Hoke,a Daniel J. Slotcavage,a Emma R. Dohner,b Andrea R. Bowring,a Hemamala I. Karunadasa,b\\* and Michael D. McGeheea\\* \n\nwww.rsc.org/ \n\nWe report on reversible, light-induced transformations in $(\\mathbf{CH}_{3}\\mathbf{NH}_{3})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ . Photoluminescence (PL) spectra of these perovskites develop a new, red-shifted peak at $1.68\\mathrm{eV}$ that grows in intensity under constant, 1-sun illumination in less than a minute. This is accompanied by an increase in sub-bandgap absorption at $\\mathord{\\sim}1.7\\ \\mathrm{eV}$ , indicating the formation of luminescent trap states. Light soaking causes a splitting of $\\mathbf{x}$ -ray diffraction (XRD) peaks, suggesting segregation into two crystalline phases. Surprisingly, these photo-induced changes are fully reversible; the XRD patterns and the PL and absorption spectra revert to their initial states after the materials are left for a few minutes in the dark. We speculate that photoexcitation may cause halide segregation into iodide-rich minority and bromide-enriched majority domains, the former acting as a recombination center trap. This instability may limit achievable voltages from some mixed-halide perovskite solar cells and could have implications for the photostability of halide perovskites used in optoelectronics. \n\n# Introduction \n\nHybrid perovskites have attracted significant attention over the past few years as absorbers for solar cells1–4 with power conversion efficiencies (PCEs) exceeding $15\\%$ .5–8 One attractive attribute of hybrid perovskites as photovoltaic absorbers is the ability to continuously tune the absorption onset by alloying different halides into the structure. For example, the bandgap of $(\\mathbf{MA})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x}){_{3}}$ $\\mathbf{\\left(MA_{\\lambda}=C H_{3}N H_{3}\\right)}$ can be continuously tuned over the range $1.6{-}2.3\\ \\mathrm{eV}$ ,9 making these materials suitable both for single-junction solar cells and for the larger bandgap absorber of tandem solar cells. Photovoltaic devices containing $(\\mathbf{MA})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ have demonstrated PCEs of $4\\%$ for a wide range of halide ratios,8–12 and an open circuit voltage $(V_{\\mathrm{OC}})$ of 1.5 V has been achieved using the largest bandgap perovskite of this family: $(\\mathbf{MA})\\mathbf{Pb}\\mathbf{B}\\mathbf{r}_{3}$ .13 Although solar cells containing $(\\mathbf{MA})\\mathbf{Pb}\\mathbf{I}_{3}$ have obtained VOC’s of up to $1.15~\\mathrm{V},{}^{14}$ solar cells with mixedhalide perovskites have so far not produced the larger VOC’s that may be expected from their larger bandgaps. Several groups have reported a decrease in $V_{\\mathrm{OC}}$ , despite the increase in optical band gap, in $(\\mathbf{R})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ $\\mathrm{\\bf{R}}=\\mathrm{\\bf{C}}\\mathrm{\\bf{H}}_{3}\\mathrm{\\bf{N}}\\mathrm{\\bf{H}}_{3}$ or ${\\mathrm{HC}}({\\mathrm{NH}}_{2})_{2}$ ) absorbers for x > 0.25.9–11,15 \n\nWe examined the optical properties of $(\\mathbf{MA})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ thin films to understand the poor voltage performance of solar cells with the bromide-rich alloys. We find that the photoluminescence (PL) spectra of these materials discretely red-shift to ${\\sim}1.68~\\mathrm{eV}$ under illumination intensities of less than 1 sun in less than a minute at room temperature. This red-shift is accompanied by an increase in absorption between $1.68\\ \\mathrm{eV}$ and the bandgap. X-ray diffraction (XRD) patterns of the thin films show that the original peaks split upon illumination and revert back to their original line shape after a few minutes in the dark. Our observations so far are consistent with light-induced segregation of the mixed-halide alloy. We hypothesize that photoexcitation induces halide migration, which results in lowerbandgap, iodide-rich domains that pin the PL and $V_{\\mathrm{OC}}$ at a lower energy compared to the alloy. \n\n# Results and discussion \n\nWe measured the absorption coefficients of $(\\mathbf{MA})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ over the full range of compositions to characterize band-edge states and optical bandgaps (Figure 1). Thin films of $(\\mathbf{MA})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ were spun from equimolar mixtures of $0.55{\\bf M}$ $\\mathrm{PbI}_{2}~+~\\mathrm{(MA)I}$ and $\\mathbf{PbBr}_{2}~+~(\\mathbf{MA})\\mathbf{Br}$ solutions in dimethyl formamide and annealed for 5 minutes at $100~^{\\circ}\\mathrm{C}$ in dry air. The phase purity of the films was confirmed with XRD; their pseudocubic lattice parameters agree with previous reports (Supplementary Figure S1).9 Photocurrent spectroscopy (i.e., external quantum efficiency) measurements were performed on $(\\mathbf{MA})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ photovoltaic devices using a lock-in amplifier to measure weak absorption from band-edge states. At these weakly absorbed wavelengths, the photocurrent is proportional to the perovskite layer absorption coefficient. We combined these measurements with diffuse transmission and reflection measurements on films of varying thickness to obtain the full absorption spectra. These spectra continuously blue-shift upon increasing bromide content as previously reported.9 All perovskites in this family (except for $x\\:=\\:0.5$ ) have strong absorption onsets, yielding absorption coefficients above $1\\times10^{4}$ $\\mathrm{cm}^{-1}$ at energies only $0.1\\ \\mathrm{eV}$ above the bandgap. This property is highly desirable for thin-film photovoltaic absorbers. These absorption onsets correspond to Urbach energies in the range $12-$ $17\\mathrm{meV}$ . These values are similar to the reported value of $15\\mathrm{meV}$ for $(\\mathbf{MA})\\mathbf{Pb}\\mathbf{I}_{3}$ ,16,17 indicating that mixed halide films are homogeneous in composition. In contrast, the $x=0.5$ thin films exhibit a more gradual absorption onset, suggesting the presence of minority, iodide-rich domains $(x{\\sim}0.2)$ . Photothermal deflection spectroscopy (PDS) measurements corroborate the sharp absorption onset for all compositions except for $x=0.5$ . (Figure S2) \n\n![](images/bc310484a2debfc58c9fae884276ed1ce2e8160cf57e29313b179867ff2cc05a.jpg) \nFigure 1. Absorption coefficient of ( $\\J{\\sf A})\\mathsf{P b}(\\mathsf{B r}_{x}|_{1-x})_{3}$ measured by diffuse spectral reflection and transmission measurements on thin films and photocurrent spectroscopy of solar cells. Inset: photograph of $(\\mathsf{M A})\\mathsf{P b}(\\mathsf{B r}_{x}\\vert_{1-x})_{3}$ photovoltaic devices from $x=0$ to $x=1$ (left to right). \n\n![](images/2e61f585d187871e67d0cd9fb4952c789f703b4eb9d2c7710ead69f986d4ffb4.jpg) \nFigure 2. (a) Photoluminescence (PL) spectra of an $x=0.4$ thin film over $45s$ in $5-5$ increments under $457{\\mathsf{n m}}$ , $15\\mathrm{mW/cm}^{2}$ light at $300\\mathsf{K}.$ Inset: temperature dependence of initial PL growth rate. (b) Normalized PL spectra of $\\mathsf{M A})\\mathsf{P b}(\\mathsf{B r}_{x}|_{1-x})_{3}$ thin films after illuminating for 510 minutes with $10{-}100\\mathrm{m}\\mathsf{W}/\\mathsf{c m}^{2}$ , $457\\mathsf{n m}$ light. (c) PL spectra of an $x=0.6$ thin film after sequential cycles of illumination for 2 minutes $457\\mathsf{n m}$ , $15\\mathrm{\\mw/cm}^{2})$ followed by 5 minutes in the dark. \n\nThe initial PL spectra for $(\\mathbf{MA})\\mathbf{Pb}(\\mathbf{Br}_{x}\\mathbf{I}_{1-x})_{3}$ at low illumination intensities also continuously blue-shift upon increasing bromide content (Figure S3). However, for perovskites with $0.2$ , parallel to the boundary. The misfit between the two planes is ${\\sim}0.15$ Å $(\\sim4.5\\%)$ , which compensates the misfit spacing of ${\\sim}6~\\mathsf{n m}$ and is identical to the periodic patterns ${\\cdot-}6\\mathsf{n m}$ spacing) in (F) and (G). (F) Enlarged view of boxed region in (B). A view of tilted zone axis from (C), showing periodic Moiré patterns along GBs. (G) Enlarged views of boxed region in (F). (H) Enlarged view of boxed region in (B). (I) Enlarged view of boxed region in (H). The insets are FFT images of adjacent grains crossing a tilt-type GB. Enlarged high-resolution TEM image of boxed region dislocation arrays is shown in fig. S18C. (J) FFT image of (0 1 5) atomic planes in the inset of (I). Burgers vectors of the each dislocation is $\\mathsf{B}_{\\mathsf{D}}=<\\bar{2}\\mathrm{~1~}0>$ , perpendicular to the boundary. The misfit spacing of ${\\sim}2.5\\mathsf{n m}$ was obtained. Insets of (E) and (J) are the IFFT images of boxed areas, respectively, clearly identifying the dislocations. Other arrays of dislocations embedded in the low-angle grain boundary are shown in figs. S17 and S18. \n\nIn a typical solid-phase sintering, the grain boundaries have random alignment due to a limited diffusion length of atoms/dislocations, and so the chance of low-angle boundary $(<{\\bf l}{\\bf l}^{\\circ})_{\\mathrm{~}}$ ) is very low (19). In contrast, in liquid-phase sintering, the wetting liquid penetrates into the grain boundaries (21). Atoms in a liquid have much higher diffusivities and also dislocations at the grain boundaries have much higher diffusion lengths (22). The high solubility of Bi and Sb in the Te liquid and insignificant solubility of Te in the solid phase contributes to the very rapid mass transport (over 100 times faster than in solids) and rapid rearrangement of the grains (21). In addition, the capillary force of the liquid at the grain boundary exerts a force facilitating grain rearrangement (21, 23). \n\nHowever, the liquid phase becomes absorbed in the matrix of the grain in a typical transient liquid-phase sintering, leading to compositional variation of the matrix. This prohibits the application of traditional liquid-phase sintering for thermoelectric Bi-Sb-Te because compositional variation will degrade the TE properties. In contrast, the liquidified excess Te in the eutectic phase is expelled during the high-pressure–assisted liquidphase compacting processing. Any slight amount of Te remaining is nearly insoluble in $\\mathrm{Bi_{0.5}S b_{1.5}T e_{3}}$ and does not as dramatically affect the carrier concentration. Furthermore, the applied pressure \n\nFrom the thermal and electrical transport properties, it appears that the semicoherent grain boundaries of Te-MS material do maintain high charge-carrier mobility $(I7)$ but provide sufficient atomic strain to scatter heat-carrying phonons. The small increase in the Seebeck coefficient is due to a slight decrease in carrier concentration for S-MS and Te-MS materials compared with the ingot material (Fig. 2B). The reduced grain size of the S-MS and Te-MS materials leads to lower carrier mobility. This decrease is less dramatic for Te-MS indicating that the semicoherent grain boundaries in Te-MS are less disruptive to charge carriers than those in the S-MS material (Fig. 2A). Low-energy grain boundaries in Bi-Sb-Te are likely formed when atomic displacements are primarily in the Te-Te van der Waals layer, which have been observed experimentally (24). Displacements in this layer are also likely to be least disruptive to the charge carriers and maintain high mobility. Although the dense dislocation arrays embedded in grain boundaries do little to scatter charge carriers, they are remarkably efficient at scattering phonons and greatly reducing thermal conductivity in the Te-MS material (Fig. 2D). The $\\upkappa_{\\mathrm{lat}}$ values were extracted from $\\upkappa_{\\mathrm{tot}}$ by subtracting the electronic thermal conductivity $(\\upkappa_{\\mathrm{ele}})_{:}$ , which was estimated using the Wiedemann-Franz relation. We calculated the Lorenz number $(L_{0})$ using the reduced Fermi energy obtained from measured $s$ values at different temperatures $(I7)$ . The calculations indicate that dislocation arrays embedded in grain boundaries cause the reduction of $\\upkappa_{\\mathrm{lat}}.$ . The $\\upkappa_{\\mathrm{lat}}$ value at 320 $\\mathrm{K(0.33W{m}^{-1}{K}^{-1})}$ of the TeMS sample is comparable to the reported value $(0.29\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1})$ in highly deformed $\\mathrm{Bi_{0.2}S b_{1.8}T e_{3}}$ with high-density lattice defects (25), indicating that dense dislocation arrays at grain boundaries are effective to reduce the $\\boldsymbol{\\kappa}_{\\mathrm{lat}}.$ . \n\ninduces additional stresses, which helps create dislocations (23) and accelerate grain rearrangement (21). As a result, the grain interfaces rearrange to allow low-energy grain boundaries, which results in dislocation arrays within much of the grain boundary. \n\nWe have modeled the temperature-dependent $\\upkappa_{\\mathrm{lat}}$ of BM, S-MS and Te-MS materials based on the Debye-Callaway model (26) using parameters derived from independently measured physical properties (Fig. 1B) $(I7)$ . The total phonon relaxation time $:\\tau_{\\mathrm{tot}})$ was estimated by including scattering from Umklapp processes $(\\uptau_{\\mathrm{U}})$ and point defects $\\scriptstyle\\left(\\tau_{\\mathrm{PD}}\\right)$ using parameters based on bulk alloys (9, 27, 28). We used microscopy to determine the parameter of average grain size $(d)$ for the grain boundary scattering $(\\uptau_{\\mathrm{B}})$ (17, 18). The calculated $\\upkappa_{\\mathrm{lat}}$ $_\\mathrm{at}\\left(0.66\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}\\right.$ at $300\\mathrm{K})$ for BM matches the measured data well, verifying the values used for Umklapp processes $(\\uptau_{\\mathrm{U}})$ and point defects $\\scriptstyle(\\tau_{\\mathrm{PD}})$ of $\\mathrm{Bi_{0.5}S b_{1.5}T e_{3}}$ alloys. The $18\\%$ reduction in $\\upkappa_{\\mathrm{lat}}$ observed in S-MS material relative to BM material at $300\\mathrm{~K~}$ is explained by a grain size reduction from $50\\upmu\\mathrm{m}$ to ${300}\\mathrm{nm}$ . The additional $29\\%$ reduction in $\\upkappa_{\\mathrm{lat}}$ for Te-MS material is explained by introducing phonon relaxation times associated with additional scattering from dislocation cores $(\\tau_{\\mathrm{DC}})$ and strain $\\mathrm{(\\tau_{DS})}$ (29–31), using the experimentally determined dislocation density $(\\sim2\\mathrm{~\\times~}10^{11}\\mathrm{~cm^{-2}})$ and the effective Burgers vector $(B_{\\mathrm{D}}$ of ${\\sim}12.7\\mathrm{\\AA})$ . \n\nThis analysis shows that the periodic spacing of dislocation arrays plays a vital role for reducing $\\upkappa_{\\mathrm{lat}}.$ When the spacing between dislocation cores is small, as observed in Te-MS material, the scattering from dislocation strain is reinforced (32). This effect was experimentally observed in $\\mathrm{\\Ag-Cd}$ alloys with the large scattering effect as due to the dislocation pile-up (10). When dislocations are closely spaced, the effective Burgers vector $(B_{\\mathrm{D}})$ is the sum of the individual Burgers vectors involved (33). As the scattering rate is proportional to ${B_{\\mathrm{D}}}^{2}$ $(I7),$ , this pile-up of dislocation strain leads to a nonlinear increase in scattering. The exact amount of reinforcement is not precisely specified in the theory and leads to the only adjustable parameter in the model. Nevertheless, the Burgers vector that precisely fits the data is well within the range observed experimentally (24). \n\nThe dislocation scattering mechanism is particularly effective because it targets phonons not scattered sufficiently by the other mechanisms providing a full-spectrum solution to scatter phonons. Compared with Umklapp scattering (Fig. 1A), boundary scattering from grain boundaries ${({\\uptau_{\\mathrm{B}}}^{-1}\\sim\\infty^{0})}$ is efficient at scattering low-frequency phonons but quickly becomes ineffective at higher frequencies. Conversely, point defects scatter mostly high-frequency phonons ${({\\tau_{\\mathrm{PD}}}^{-1}\\sim\\omega^{4})}$ . However, most of the remaining heat-carrying phonons have intermediate frequency around 0.63 THz (Fig. 1A) and avoid scattering from boundaries and point defects. The $0.63\\mathrm{THz}$ phonons still carry $74\\%$ of the heat that they would have carried without any scattering from boundaries or point defects in the S-MS material. Including the dislocation scattering as found in the Te-MS material, the $\\upkappa_{\\mathrm{s}}$ of $0.63\\mathrm{THz}$ phonons drops to less than $45\\%$ of the heat that they would have carried with only Umklapp scattering (Fig. 1A). \n\nThe low thermal conductivity while maintaining high mobility results in a dimensionless figure of merit $(z T)$ for Te-MS that reaches a maximum value of 2.01 at $320\\mathrm{~K~}$ within the range of $1.86\\pm$ 0.15 at $320\\mathrm{K}$ for 30 samples (Fig. 1C and fig. S9F), a much higher value than for S-MS or ingot materials. Most importantly, for cooling applications, the $z T$ at $300\\mathrm{~K~}$ is high $(1.72\\pm0.12)\\$ , suggesting that it should provide superior refrigeration than other materials. For example, the $z T$ is higher than that of nanograined $\\mathrm{Bi_{0.5}S b_{1.5}T e_{3}}$ alloy (dotted line in Fig. 1C) $(7)$ near room temperature. This results from the ability of dislocation arrays to enable a full-spectrum scattering of phonons due to a compounding effect not found in randomly dispersed dislocations inside grains. The present liquidphase compaction method assisted with a transient liquid flow is highly scalable for commercial use and generally applicable to other thermoelectric systems such as PbTe, $\\mathrm{CoSb_{3}}$ , and Si-Ge alloys, and even engineer thermal properties of other thermal materials such as thermal barrier coatings (34). This may accelerate practical applications of thermoelectric systems in refrigeration and beyond to waste heat recovery and power generation. \n\nThe ultimate verification of the exceptional $z T$ comes from testing the performance of a Peltier cooler (Fig. 1D) made using Te-MS materials. A state-of-the-art Peltier device using the Te-MS as the p-type material and an n-type ingot material made cutting-edge commercial methods $(I7)$ . The device not only greatly outperforms a similar device made with the p- and n-type ingot materials (Fig. 1E) but also outperforms all commercial Peltier devices (16). We determined the coefficient of performance (COP) (cooling power divided by input power) to assess the cooling performance of both Peltier devices. A key characteristic performance metric of a Peltier cooler is $\\Delta T_{\\mathrm{max}},$ which is directly related to the $z T$ of materials. The $\\Delta T_{\\mathrm{max}}$ values are easily extracted from the COP measurements as the temperature difference reached when the cooling power vanishes. Although the $\\Delta T_{\\mathrm{max}}$ of the Peltier cooler made from the ingot materials falls within the range of current commercial devices, $64\\mathrm{K}<\\Delta T_{\\mathrm{max}}<72$ K for $T_{\\mathrm{h}}$ of $300\\mathrm{K},$ the Peltier cooler made with the Te-MS p-type material exhibits a $\\Delta T_{\\mathrm{max}}$ of 81 K for $T_{\\mathrm{h}}$ of 300 K (Fig. 1E) (17). \n\n1. L. E. Bell, Science 321, 1457–1461 (2008). \n2. H. Scherrer, S. Scherrer, in Thermoelectrics Handbook Macro to Nano, D. M. Rowe, Ed. (CRC, Boca Raton, FL, 2006), chap. 27. \n3. R. J. Buist, in 3rd International Conference on Thermoelectric Energy Conversion, Arlington, Texas, 12 to 14 May 1980 (IEEE, New York, 1980), pp. 130–134. \n4. H. J. Goldsmid, in Electronic Refrigeration (Pion, London, 1986), chaps. 2 and 7. \n5. M. S. Dresselhaus et al., Adv. Mater. 19, 1043–1053 (2007). \n6. D. L. Medlin, G. J. Snyder, Curr. Opin. Colloid Interface Sci. 14, 226–235 (2009). \n7. B. Poudel et al., Science 320, 634–638 (2008). \n8. S. Fan et al., Appl. Phys. Lett. 96, 182104 (2010). \n9. E. S. Toberer, A. Zevalkink, G. J. Snyder, J. Mater. Chem. 21, 15843–15852 (2011). \n10. P. G. Klemens, Proc. Phys. Soc. A 68, 1113–1128 (1955). \n11. P. Kim, L. Shi, A. Majumdar, P. L. McEuen, Phys. Rev. Lett. 87, 215502 (2001). \n12. H. Wang, A. D. LaLonde, Y. Pei, G. J. Snyder, Adv. Funct. Mater. 23, 1586–1596 (2013). \n13. M. Nader, F. Aldinger, M. J. Hoffmann, J. Mater. Sci. 34, 1197–1204 (1999). \n14. P. J. Jorgensen, R. W. Bartlett, J. Appl. Phys. 44, 2876–2880 (1973). \n15. S. Nazaré, G. Ondracek, F. Thümmler, in Relations Between Stereometric Microstructure and Properties of Cermets and Porous Materials, H. H. Hausner, Ed. (Springer, New York, 1971), pp. 171–186. \n16. D. Zhao, G. Tan, Appl. Therm. Eng. 66, 15–24 (2014). \n17. Materials and methods are available as supplementary materials on Science Online. \n18. D. B. Williams, C. B. Carter, Transmission Electron Microscopy (Springer, New York, 1996). \n19. F. J. Humphreys, M. Hatherly, Recrystallization and Related Annealing Phenomena (Elsevier, Oxford, ed. 2, 2004). \n20. N. Peranio, O. Eibl, Phys. Status Solidi A 206, 42–49 (2009). \n21. R. M. German, P. Suri, S. J. Park, J. Mater. Sci. 44, 1–39 (2009). \n22. C. Herzig, Y. Mishin, in Diffusion in Condensed Matter, P. Heitjans, J. Kärger, Eds. (Springer, Berlin, Heidelberg, 2005), chap. 8. \n23. J. W. Cahn, Y. Mishin, A. Suzuki, Acta Mater. 54, 4953–4975 (2006). \n24. D. L. Medlin, K. J. Erickson, S. J. Limmer, W. G. Yelton, M. P. Siegal, J. Mater. Sci. 49, 3970–3979 (2014). \n25. L. P. Hu et al., NPG Asia Mater. 6, e88 (2014). \n26. J. Callaway, H. C. von Baeyer, Phys. Rev. 120, 1149–1154 (1960). \n\n# REFERENCES AND NOTES \n\n27. G. A. Slack, S. Galginaitis, Phys. Rev. 133 (1A), A253–A268 (1964). \n28. M. Roufosse, P. G. Klemens, Phys. Rev. B 7, 5379–5386 (1973). \n29. J. He, S. N. Girard, M. G. Kanatzidis, V. P. Dravid, Adv. Funct. Mater. 20, 764–772 (2010). \n30. B. Abeles, Phys. Rev. 131, 1906–1911 (1963). \n31. D. T. Morelli, J. P. Heremans, G. A. Slack, Phys. Rev. B 66, 195304 (2002). \n32. D. J. H. Cockayne, I. L. F. Ray, M. J. Whelan, Philos. Mag. 20, 1265–1270 (1969). \n\n# STELLAR PHYSICS \n\n33. N. F. Mott, Philos. Mag. 43, 1151–1178 (1952). \n34. D. R. Clarke, S. R. Phillpot, Mater. Today 8, 22–29 (2005). \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by IBS-R011-D1, the National Research Foundation of Korea (2013R1A1A1008025), the Human Resources Development program (no. 20124010203270) of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Trade, Industry, and Energy, and AFOSR MURI FA9550-10-1-0533. \n\n# Observing the onset of outflow collimation in a massive protostar \n\nC. Carrasco-González,1\\* J. M. Torrelles,2 J. Cantó,3 S. Curiel,3 G. Surcis,4 \nW. H. T. Vlemmings,5 H. J. van Langevelde,4,6 C. Goddi,4,7 G. Anglada,8 \nS.-W. Kim,9,10 J.-S. Kim,11 J. F. Gómez8 \n\nThe current paradigm of star formation through accretion disks, and magnetohydrodynamically driven gas ejections, predicts the development of collimated outflows, rather than expansion without any preferential direction. We present radio continuum observations of the massive protostar W75N(B)-VLA 2, showing that it is a thermal, collimated ionized wind and that it has evolved in 18 years from a compact source into an elongated one. This is consistent with the evolution of the associated expanding water-vapor maser shell, which changed from a nearly circular morphology, tracing an almost isotropic outflow, to an elliptical one outlining collimated motions. We model this behavior in terms of an episodic, short-lived, originally isotropic ionized wind whose morphology evolves as it moves within a toroidal density stratification. \n\nater-vapor masers at $22~\\mathrm{{GHz}}$ are commonly found in star-forming regions, arising in the shocked regions created by powerful outflows from protostars in their earliest phases of evolution $(I)$ . Ob \nservations of these masers with very long base \nline interferometry (VLBI) indicate that at the \nearly life of massive stars, there may exist episodic, \nshort-lived (tens of years) events associated with \nvery poorly collimated outflows (2–5). These re \nsults are surprising because, according to the \ncore-accretion model for the formation of mas \nsive stars $({\\gtrsim}8M_{\\odot})$ , which is a scaled-up version of \nlow-mass star formation, collimated outflows are \nalready expected at their very early phases (6–8). \n\nA unique case of a short-lived, poorly collimated outflow is the one found in the highmass star-forming region W75N(B). This region contains two massive protostars, VLA 1 and VLA 2, separated by ${\\lesssim}0.7$ arc sec [projected separation of ${\\lesssim}910$ astronomical units (AU) at the source distance of $1.3{\\mathrm{~kpc}};{\\mathrm{~}}$ ; (9)], both associated with strong water-vapor maser emission at 22 GHz (10, 11), and with a markedly different outflow geometry. At epoch 1996, VLA 1 shows an elongated radio continuum emission consistent with a thermal radio jet, as well as water maser emission tracing a collimated outflow of ∼1300 AU along its major axis. In contrast, in VLA 2, the water masers traced a shock-excited shell of ${\\sim}185$ AU diameter radially expanding with respect to a central, compact radio continuum source ${\\lesssim}0.12$ arc sec; ${\\lesssim}160$ AU of unknown nature (12). A monitoring of the water masers toward these two objects from 1996 to 2012 shows that the masers in VLA 1 display a persistent linear distribution along the major axis of the radio jet. In the case of VLA 2, we observe that the water maser shell continues its expansion at ${\\sim}30\\mathrm{kms^{-1}}$ 16 years after its first detection. More important, the shell has evolved from an almost circular structure (∼185 AU) to an elliptical one ${\\sim}354\\times190$ AU) oriented northeast-southwest, along a direction similar to that of the nearby VLA 1 radio jet (13, 14) (fig. S1) and of the ordered large-scale (2000 AU) magnetic field observed in the region (15). The estimated kinematic age for the expanding shell is ${\\sim}25$ years, indicating that it is driven by a short-lived, episodic outflow \n\n4 December 2014; accepted 13 February 2015 \n10.1126/science.aaa4166 \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/348/6230/109/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S21 \nTables S1 to S4 \nReferences (35–56) \n\nevent. Moreover, our polarization measurements of the water maser emission show that whereas the magnetic field around VLA 1 has not changed over time, the magnetic field around VLA 2 changed its orientation, following the direction of the major axis of the water maser elliptical structure. That is, it now shares a similar northeastsouthwest orientation with those of both the magnetic field around VLA 1 and the large-scale magnetic field in the region (14, 15) (fig. S1). \n\nAll these observations suggest that we are observing in “real time” the transition from an uncollimated outflow to a collimated outflow during the early life of a massive star. This scenario predicts that, within the same time span of the evolution of the shell, VLA 2 must have also evolved from a compact radio continuum source to an extended elongated source along the major axis of the water maser shell. Furthermore, the radio continuum emission of VLA 2 should have physical properties (e.g., spectral energy distribution, size of the source as a function of frequency) characteristic of free-free emission from a thermal, collimated ionized wind (16, 17). This can be tested through continuum observations at centimeter wavelengths that usually trace the emission from collimated, ionized winds (17, 18). \n\nTaking advantage of the high sensitivity and high angular resolution of the Jansky Very Large Array (VLA) at centimeter wavelengths, we obtained new observations in 2014 at several bands in the frequency range from 4 to 48 GHz (19). These highly sensitive observations confirmed the expected scenario proposed above. The source VLA 2 is detected at all bands. In the images of higher-frequency bands [U $_{\\cdot\\sim15}$ GHz), K (∼23 GHz), and $\\mathrm{Q\\left({\\sim}44~G H z\\right)]}$ , which have higher angular resolutions $_{\\ \\sim0.1}$ to 0.2 arc sec), the source VLA 2 appears clearly elongated in the northeast-southwest direction (Fig. 1). Water maser emission was also observed simultaneously with the K band continuum emission (19), allowing a very accurate alignment (better than ${\\boldsymbol{\\sim}}1$ milli–arc sec) between the masers and the continuum emission. We find that the elongation of the continuum emission is in good agreement with that of the water maser distribution (Fig. 1). \n\nComparison of the radio continuum emission of VLA 2 at K band between epochs 1996 (10) and 2014 is shown in Fig. 2. Whereas in 1996 the emission was compact, in 2014 we observed extended emission in the northeast-southwest direction. In particular, the core of the radio continuum emission of VLA 2 has evolved from a compact source in 1996 ${\\ \\stackrel{\\cdot}{\\ s u o}}$ AU to an elongated core with a full width at half-maximum (FWHM) of \n\n# Science \n\n# Dense dislocation arrays embedded in grain boundaries for high-performance bulk thermoelectrics \n\nSang Il Kim, Kyu Hyoung Lee, Hyeon A Mun, Hyun Sik Kim, Sung Woo Hwang, Jong Wook Roh, Dae Jin Yang, Weon Ho Shin, Xiang Shu Li, Young Hee Lee, G. Jeffrey Snyder and Sung Wng Kim \n\nScience 348 (6230), 109-114. DOI: 10.1126/science.aaa4166 \n\n# Squeezing out efficient thermoelectrics \n\nThermoelectric materials hold the promise of converting waste heat into electricity. The challenge is to develop high-efficiency materials that are not too expensive. Kim et al. suggest a pathway for developing inexpensive thermoelectrics. They show a dramatic improvement of efficiency in bismuth telluride samples by quickly squeezing out excess liquid during compaction. This method introduces grain boundary dislocations in a way that avoids degrading electrical conductivity, which makes a better thermoelectric material. With the potential for scale-up and application to cheaper materials, this discovery presents an attractive path forward for thermoelectrics. \n\nScience, this issue p. 109 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.aab3798", + "DOI": "10.1126/science.aab3798", + "DOI Link": "http://dx.doi.org/10.1126/science.aab3798", + "Relative Dir Path": "mds/10.1126_science.aab3798", + "Article Title": "Nitrogen-doped mesoporous carbon of extraordinary capacitance for electrochemical energy storage", + "Authors": "Lin, TQ; Chen, IW; Liu, FX; Yang, CY; Bi, H; Xu, FF; Huang, FQ", + "Source Title": "SCIENCE", + "Abstract": "Carbon-based supercapacitors can provide high electrical power, but they do not have sufficient energy density to directly compete with batteries. We found that a nitrogen-doped ordered mesoporous few-layer carbon has a capacitance of 855 farads per gram in aqueous electrolytes and can be bipolarly charged or discharged at a fast, carbon-like speed. The improvement mostly stems from robust redox reactions at nitrogen-associated defects that transform inert graphene-like layered carbon into an electrochemically active substance without affecting its electric conductivity. These bipolar aqueous-electrolyte electrochemical cells offer power densities and lifetimes similar to those of carbon-based supercapacitors and can store a specific energy of 41 watt-hours per kilogram (19.5 watt-hours per liter).", + "Times Cited, WoS Core": 1835, + "Times Cited, All Databases": 1899, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000366591100054", + "Markdown": "the superfluid bulk, before annihilation. The propagation of the vortex through the superfluid bulk acts as a dissipative channel that gives rise to a resistive flow, which leads to an exponential decay of $\\ensuremath{\\boldsymbol{z}}(t)$ . This mechanism can occur in our crossover superfluids: The three-dimensional character of our junction, combined with the coupling to the transverse modes favored by the strong interparticle interactions, may facilitate the leakage of vortices from the barrier region (33). \n\nBy performing a statistical study over several time-of-flight images recorded after some time evolution in the trap (22), we detected with nonzero probability the presence of topological defects, which appear as density depletions in the expanded clouds (Fig. 4B, inset). By measuring their oscillation period in the trap after switching off the barrier, we identified them as solitonic vortices (22, 34). The intimate connection between the breakdown of the Josephson oscillations and the appearance of vortices is further confirmed by the data shown in Fig. 4B. This figure shows the behavior of the Josephson frequency ${\\mathfrak{o}}_{\\mathrm{J}}$ at unitarity as a function of $V_{0},$ together with the occurrence of defects observed for each $V_{0}$ value over a statistical ensemble of 40 images. Vortices appear only in the regime where coherent oscillations are absent $(V_{0}/E_{\\mathrm{F}}>$ 1.5). The interconnection between the quench of the coherent dynamics and the vortex nucleation is not peculiar to the unitary point; it extends over the entire BEC-BCS crossover region. This can be observed by comparing Fig. 4C and 4D, where the measured ${\\mathfrak{o}}_{\\mathbf{J}}$ is contrasted with the vortex occurrence probability, as a function of $V_{0}/E_{\\mathrm{F}}$ and $1/k_{\\mathrm{F}}a$ . The trend of the first observable is inversely correlated with the behavior of the second one for all interaction regimes. Figure 4D highlights the robustness of the crossover superfluid, which resists the formation of topological defects while maintaining the highest Josephson frequency. Our results differ from those reported in a study of the limit of vanishingly low barriers $(V_{0}\\ll\\upmu)$ , where phononic excitations and pair-breaking effects, rather than vortices, respectively cause the breakdown of superfluidity in the BEC and BCS sides (30). \n\n# REFERENCES AND NOTES \n\nOur work paves the way for studies of the interplay between elementary and topological excitations in the dissipative dynamics created by varying the height and width of the interwell barrier, and to the measurement of the superfluid gap, in close analogy with tunneling experiments in superconductors (3, 18). Moreover, extending our studies of the tunneling dynamics above the condensation temperature $T_{\\mathrm{C}}$ may provide insight into the role of phase fluctuations in the regime where preformed noncondensed pairs appear in the system (17). \n\n1. B. D. Josephson, Phys. Lett. 1, 251–253 (1962). \n2. P. W. Anderson, Rev. Mod. Phys. 38, 298–310 (1966). \n3. A. Barone, G. Paternò, Physics and Applications of the Josephson Effect (Wiley, New York, 1982). \n4. K. Sukhatme, Y. Mukharsky, T. Chui, D. Pearson, Nature 411 280–283 (2001). \n5. E. Hoskinson, Y. Sato, I. Hahn, R. E. Packard, Nat. Phys. 2, 23–26 (2006). \n6. F. S. Cataliotti et al., Science 293, 843–846 (2001). \n7. M. Albiez et al., Phys. Rev. Lett. 95, 010402 (2005). \n8. T. Schumm et al., Nat. Phys. 1, 57–62 (2005). \n9. S. Levy, E. Lahoud, I. Shomroni, J. Steinhauer, Nature 449, 579–583 (2007). \n10. L. J. LeBlanc et al., Phys. Rev. Lett. 106, 025302 (2011). \n11. M. Abbarchi et al., Nat. Phys. 9, 275–279 (2013). \n12. J. C. Davis, R. E. Packard, Rev. Mod. Phys. 74, 741–773 (2002). \n13. A. J. Leggett, Quantum Liquids: Bose Condensation and Cooper Pairing in Condensed-Matter Systems (Oxford Univ. Press, Oxford, 2006). \n14. W. Zwerger, Ed., The BCS-BEC Crossover and the Unitary Fermi Gas (Springer, Heidelberg, Germany, 2012). \n15. M. Inguscio, W. Ketterle, C. Salomon, Eds., Proceedings of the International School of Physics “Enrico Fermi”, Course CLXIV, Varenna, Italy, 20 to 30 June 2006 (IOS Press, Amsterdam, 2008). \n16. M. W. Zwierlein, in Novel Superfluids, Volume 2, K. H. Bennemann, J. B. Ketterson, Eds. (International Series of Monographs on Physics 157, Oxford Univ. Press, Oxford, 2014), pp. 269–422, and references therein. \n17. Q. Chen, J. Stajic, S. Tan, K. Levin, Phys. Rep. 412, 1–88 (2005). \n18. S. Hüfner, M. A. Hossain, A. Damascelli, G. A. Sawatzky, Rep. Prog. Phys. 71, 062501 (2008). \n19. E. Varoquaux, Rev. Mod. Phys. 87, 803–854 (2015), and references therein. \n20. F. Piazza, L. A. Collins, A. Smerzi, New J. Phys. 13, 043008 (2011). \n21. A. Burchianti et al., Phys. Rev. A 90, 043408 (2014). \n22. Materials and methods are available as supplementary materials on Science Online. \n23. D. Stadler, S. Krinner, J. Meineke, J. P. Brantut, T. Esslinger, Nature 491, 736–739 (2012). \n24. A. Smerzi, S. Fantoni, S. Giovanazzi, S. R. Shenoy, Phys. Rev. Lett. 79, 4950–4953 (1997). \n25. I. Zapata, F. Sols, A. J. Leggett, Phys. Rev. A 57, R28–R31 (1998). \n26. J. K. Chin et al., Nature 443, 961–964 (2006). \n27. C. Kohstall et al., New J. Phys. 13, 065027 (2011). \n28. P. Zou, F. Dalfovo, J. Low Temp. Phys. 177, 240–256 (2014). \n29. A. Spuntarelli, P. Pieri, G. C. Strinati, Phys. Rev. Lett. 99, \n040401 (2007). \n30. D. E. Miller et al., Phys. Rev. Lett. 99, 070402 (2007). \n31. F. Meier, W. Zwerger, Phys. Rev. A 64, 033610 (2001). \n32. G. E. Astrakharchik, J. Boronat, J. Casulleras, S. Giorgini, Phys. Rev. Lett. 95, 230405 (2005). \n33. K. C. Wright, R. B. Blakestad, C. J. Lobb, W. D. Phillips, G. K. Campbell, Phys. Rev. Lett. 110, 025302 (2013). \n34. M. J. Ku et al., Phys. Rev. Lett. 113, 065301 (2014). \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge inspiring discussions with F. Dalfovo, A. Recati, and W. Zwerger. We thank C. Fort, A. Trenkwalder, A. Morales, and T. Macrì for collaboration at the initial stage of this work. We especially acknowledge the LENS Quantum Gases group. This work was supported under European Research Council grant no. 307032 QuFerm2D. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/350/6267/1505/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S7 \nReferences (35–49) \n7 July 2015; accepted 13 November 2015 \n10.1126/science.aac9725 \n\n# ENERGY STORAGE \n\n# Nitrogen-doped mesoporous carbon of extraordinary capacitance for electrochemical energy storage \n\nTianquan Lin,1,2 I-Wei Chen,3 Fengxin Liu,1 Chongyin Yang,1 Hui Bi,1 Fangfang Xu,1 Fuqiang Huang1,2\\* \n\nCarbon-based supercapacitors can provide high electrical power, but they do not have sufficient energy density to directly compete with batteries. We found that a nitrogen-doped ordered mesoporous few-layer carbon has a capacitance of 855 farads per gram in aqueous electrolytes and can be bipolarly charged or discharged at a fast, carbon-like speed. The improvement mostly stems from robust redox reactions at nitrogen-associated defects that transform inert graphene-like layered carbon into an electrochemically active substance without affecting its electric conductivity. These bipolar aqueous-electrolyte electrochemical cells offer power densities and lifetimes similar to those of carbon-based supercapacitors and can store a specific energy of 41 watt-hours per kilogram (19.5 watt-hours per liter). \n\nC arbon supercapacitors have outstanding attributes of low weight, very fast charging/ discharging kinetics, and bipolar operational flexibility. For carbon-based materials, only electrical double-layer capacitance (EDLC) is available; thus, surface area is the key concern. But even at a very large surface area (\\~2180 to $\\mathrm{3100\\m^{2}\\ g^{-1})}$ , their specific capacitance is still relatively low $(\\sim250\\mathrm{~F~g^{-1}})$ , which has limited their appeal (1–4). Meanwhile, graphene has a theoretical EDLC of $\\sim550\\mathrm{Fg}^{-1}(5,6)$ because of its extraordinary conductivity and specific surface area $({\\sim}2630\\mathrm{m}^{2}\\mathrm{g}^{-1})$ . In practice, however, its capacitance has also been limited to ${\\sim}300\\mathrm{~F~g^{-1}}$ , about the same as the best carbon-based EDLC (2, $5\\mathrm{-}7)$ . Therefore, efforts have been made to enable redox reactions in ordered mesoporous carbon (OMC) $(\\delta,g)$ and conducting polymers by N doping, which via proton incorporation can theoretically endow a capacitance of ${\\sim}2000\\mathrm{Fg^{-1}}$ to conducting polymer polyaniline (10). Nevertheless, such efforts have failed because conducting polymers are too unstable for practical electrochemical cells, while stable OMC is too resistive to deliver a high capacitance or power. \n\nWe demonstrate that N doping can turn inert graphene-like layered carbon into an electrochemically active substance. The preparation method is described in the supplementary materials, starting with a sacrificial mesoporous silica template, which contains self-assembled tubes $(I I)$ later covered by few-layer carbon. After etching away silica, a self-supported ordered mesoporous few-layer carbon (OMFLC) superstructure in Fig. 1A remained. Various N-doped OMFLC (OMFLC-N) having N incorporated at several OMFLC locations in Fig. 1B were also obtained, some further modified by a $\\mathrm{{HNO}_{3}}$ oxidation treatment that partially converted N into $_{\\mathrm{N-O}}$ . This set of OMFLC-N samples (table S1) includes 8.2 atomic percent $(\\mathrm{at\\%})\\$ ) N before and after oxidation treatment (samples S1 and S2) and $11.9\\mathrm{at\\%}$ N before and after treatment (samples S3 and S4). For comparison, an ordered mesoporous (amorphous) carbon and a commercial activated carbon (YP-50, Kuraray Chemical) were also studied. To demonstrate the relevance to practical applications, we further implemented the idea using a simplified, template-free, scalable method producing essentially the same N-doped mesoporous few-layer carbon materials with the same overall performance. \n\nThe ordered mesoporous nature of OMC (Fig. 1C) and OMFLC (Fig. 1D) was confirmed by electron microscopy. In both, OMFLC tubes appear as bright strips 4 to $6\\mathrm{nm}$ wide. The tubes are porous, containing pores 1 to $2\\mathrm{nm}$ in diameter (dark regions in strips), and are separated by aligned pore channels (dark regions between strips) of about the same size or diameter. Highresolution imaging of OMFLC’s tube walls further revealed graphene-like sheets with $\\leq5$ layers (Fig. 1E). These relatively homogeneous and uniform mesoporous textures were largely preserved in OMFLC-N (fig. S1). The silica tubes in the template are known to form a two-dimensional (2D) hexagonal “crystal” with space group p6mm $(I I)$ . The same superstructure was confirmed in OMC, OMFLC, and OMFLC-N by their diffraction patterns (Fig. 1F), which show decreasing peak intensities in the above order, indicating a progressive distortion of the superstructure. \n\nNitrogen adsorption-desorption suggests a bimodal pore size distribution (Fig. 1G) centered around $1.8~\\mathrm{nm}$ and 3.5 to $4.0\\ \\mathrm{nm}$ in all three mesoporous structures. They share similar $\\mathrm{N}_{2}$ adsorption-desorption isotherms with a Langmuir hysteresis (fig. S2A) typical of well-defined mesopores. Among them, OMFLC-N (S1) has the largest surface area $(\\mathrm{1580~m^{2}~g^{-1}})$ , the largest total pore volume $(2.20\\mathrm{cm}^{3}\\mathrm{g}^{-1})$ , the smallest average pore width $(2.25\\mathrm{nm})$ , and the most prominent pores smaller than $2\\ \\mathrm{nm}$ (Fig. 1G). The characteristic Raman 2D band (fig. S2B) verified the formation of local graphene-like structure with $\\leq5$ layers in OMFLC and OMFLC-N. \n\n![](images/61c1951210f29fbb2e02855a26fb203c9baa3bed72d306c7c64326c55bf7fbd2.jpg) \nFig. 1. Structure of N-doped ordered mesoporous few-layer carbon and resolution TEM image of OMFLC; nanoporous walls consist of few-layered carbon related materials. (A) Fabrication schematic of ordered mesoporous few- sheets. (F) Low-angle x-ray diffraction patterns of OMC, OMFLC, and OMFLC-N layer carbon (OMFLC). (B) Possible locations for N incorporation into a few- (S1), showing characteristic (100), (110), and (200) peaks of hexagonal packlayer carbon network. (C and D) High-angle annular dark-field transmission ing. (G) Pore size distributions of OMC, OMFLC, and OMFLC-N (S1). (H) Wetting electron microscopy (TEM) images of ordered mesoporous carbon (OMC) angles of $0.5~\\mathsf{M}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ droplet on OMFLC $(85^{\\circ})$ ) and OMFLC-N (S1) (21°) (C) and OMFLC (D); dark regions indicate connected pore channels. (E) High- substrates. \n\nLocal graphene-like structure formation and N doping profoundly altered other physical properties as well. Whereas OMC is clearly an insulator, OMFLC and OMFLC-N display much lower room-temperature resistance with much weaker temperature dependence (fig. S2C), indicating an improvement in the structural order of carbon (12). Meanwhile, whereas both OMC and OMFLC are hydrophobic, OMFLC-N is hydrophilic, wetting a 0.5 M $\\mathrm{H_{2}S O_{4}}$ droplet in Fig. 1H. This is consistent with the zeta potential: Nearly neutral OMFLC (zeta potential $\\mathrm{\\Omega}=-6\\mathrm{mV},$ almost the same as OMC’s $-4~\\mathrm{mV})$ becomes more nucleophilic OMFLC-N $(-20\\mathrm{mV})$ as a result of lone-pair $\\mathrm{\\DeltaN2p_{z}}$ electrons; these improved physical properties of OMFLC-N are generally conducive to the supercapacitive performance (see below). \n\nSpectroscopy studies identified C-bonding and N-C locations in the carbon network. The presence of $\\mathbf{sp}^{2}$ bonding expected for graphene and local graphene-like structure was evident from the high ratio of $\\pi^{*}$ bonding to $\\pi^{*}+\\upsigma^{*}$ bonding (fig. S3A), giving $98\\%$ $(\\pm2\\%)$ $\\mathrm{sp}^{2}$ bonding in OMFLC versus $86\\%$ $(\\pm2\\%)$ in OMFLC-N, with reference to graphite $(100\\%)$ ). Evidence for N substitution in OMFLC-N was also detected (fig. S3B), and the $\\mathrm{{N/O}}$ content and bonding of OMFLC-N quantified by x-ray photoelectron spectroscopy (XPS) (fig. S3, C to F, and table S1) provided the following picture: (i) Deconvoluted N 1s XPS contains three characteristic peaks at 398, 400, and 401 eV, corresponding to pyridinic (N-6), pyrrolic (N-5), and graphitic (N-Q) nitrogen, respectively, as shown in Fig. 1B $(I3,I4)$ . (ii) As the N content increases from ${\\sim}8.2\\ \\mathrm{at\\%}$ in sample S1 to 11.9 $a t\\%$ in S3, N substitution at “regular” graphitic C sites (N-Q) instead of defective sites (N-5 and N-6) becomes more abundant. (iii) Oxidative $\\mathrm{HNO_{3}}$ treatment caused the least stable N-5 to substantially convert to N−O (N associated with an O, shown in fig. S3D at $403.2\\mathrm{eV},$ ) (15) without affecting the most stable $\\mathrm{N}{\\cdot}Q,$ as suggested by the correlation of N-O percentage (%N-O) to the decrement of N-5 percentage $(\\%\\mathrm{N}.5)$ , denoted by $\\Delta\\%\\mathrm{N}{-}5$ in table S1. (iv) Non–N- $Q$ fractions (i.e., $\\%\\mathrm{N}{-}5+$ $\\%\\mathrm{N}_{\\cdot}-6$ in table S1) decrease in the order of samples S3, S1, S2, and S4; their redox potentials also increase in the same order. \n\nThese redox potentials in aqueous electrolytes were determined in three-electrode electrochemical cells in $0.5{\\bf M}$ $\\mathrm{H_{2}S O_{4}}$ $\\left(\\mathrm{pH}0\\right.$ ) electrolyte using an $\\mathrm{{Ag/AgCl}}$ reference electrode and a Pt counterelectrode. The working electrode was prepared by pressing together active-material powders (at a mass loading of $0.5\\mathrm{~mg\\cm^{-2}}.$ ) and an inactive, highly compressible graphene foam (3D-graphene, specific capacitance $=30\\mathrm{Fg^{-1}}\\cdot$ ) without any other additive. In cyclic voltammetry (CV) at $2\\mathrm{mVs}^{-1}$ (Fig. 2A), cells with both OMC and OMFLC working electrodes have nearly rectangular CV curves representative of an ideal efficient EDLC. With OMFLC-N electrodes, the curves may be deconvoluted into (i) a nearly rectangular EDLC-like curve, albeit with a substantially higher charging/ discharging current not seen with OMC and OMFLC, and (ii) a set of symmetric Faradaic charging/discharging peaks. In (ii), the charging peaks are located at ${\\sim}0.25\\mathrm{V}$ to ${\\sim}0.5\\mathrm{V}$ , increasing in the order of S3, S1, S2, and S4 (S4 data omitted in Fig. 2A but listed in table S1), which is exactly the same order that non–N-Q fractions decrease, thus strongly suggesting that the redox potential is related to N-5 and/or N-6. The above shape and symmetry features were maintained when the scan rate increased to $\\mathrm{100~mV~s^{-1}}$ , as shown for S1 in fig. S4A. This indicates that both EDLClike and redox reactions have fast charging/ discharging kinetics. \n\nTo proceed further, we note that pseudocapacitive materials with a pronounced redox peak are usually inefficient electrodes in a symmetric electrochemical cell, which renders the effort of incorporating faradaic capacitance ineffective. This is because a symmetric cell is electrically equivalent to two serial capacitors, $C_{1}$ and $C_{2},$ so its total capacitance $C_{1}C_{2}/(C_{1}+C_{2})$ is optimized when $C_{1}=C_{2}$ . This condition is usually impossible to satisfy at all potentials unless the CV curve is rectangular. We found that the following simple method can overcome this problem, however. \n\n![](images/9f329cc4ac8957c7ef08024f7b8125821647ee1a73abefd17d7b14ae9c7b2202.jpg) \nFig. 2. Electrochemical evaluation. (A) Cyclic voltammetry (CV test, at independent capacitance $k_{1}$ , the remainder diffusion-controlled capaci$2\\mathsf{m V s}^{-1})$ from the first cycle for OMC, OMFLC, and OMFLC-N (S1 to S3) tance. (E) Tafel plots of electrode potential against pH at steady-state and for mixed OMFLC- $\\cdot\\mathsf{N}$ (SM). (B) Galvanostatic charge/discharge (CC current density of $10\\upmu\\mathsf{A}\\mathsf{c m}^{-2}$ . (F) Tafel plots of electrode potential against test at $1.0\\mathsf{A g}^{-1}\\dot{}\\varepsilon$ ) from the first cycle for OMC, OMFLC, and OMFLC-N (S1 current $\\boldsymbol{{j}}$ at $\\mathsf{p H}6.8$ for OMFLC-N (S1 and SM). All potentials are relative to and SM). (C) Complex-plane plots of AC impedance. Inset shows phase $\\mathsf{A g/A g C l}$ reference electrode; all electrolytes except (E) and (F) are $0.5\\mathsf{M}$ angle versus frequency. (D) Capacity versus square root of half-cycle time. ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ aqueous solution. In (E) and (F), theoretical slope (–59.2 mV/decade) Solid symbols, CV test data from 2 to $500\\mathrm{mVs^{-1}}$ ; open symbols, CC test is shown as a straight line to suggest reasonable agreement with the data data from 1 to 40 A $\\mathrm{g}^{-1}$ . Extrapolated intercept capacitance is rate- (see text). \n\nBy mixing three OMFLC-N powders at the ratio of S1 $:\\mathrm{S2}{:\\mathrm{S3}}=0.3{:0.3}{:0.4}$ to form another OMFLCN powder (SM), we obtain a new material that is capable of supporting multiple faradaic peaks. It exhibits a rectangular EDLC-like CV curve at a very large current (Fig. 2A)—a feature that should prove useful for constructing high-performance symmetric electrochemical cells. Because this is a qualitatively different CV curve from those of other OMFLC-N electrodes as well as OMC and OMFLC, we made further performance comparisons between SM, S1, OMC, OMFLC, and YP-50. \n\nConsistent with the CV results, all galvanostatic charge/discharge tests (the CC test in Fig. 2B) show symmetric features with a fairly linear slope. A specific capacitance as high as $855\\mathrm{Fg^{-1}}$ at a current density of $\\mathrm{\\bar{1}A g^{-1}}$ was obtained for SM, versus $\\ensuremath{\\mathrm{715~F~g^{-1}}}$ for S1 (fig. S4, C and D) and $\\boldsymbol{175}\\mathrm{~F~g^{-1}}$ for YP-50 (fig. S5). Over a wide range of current densities, SM continued to provide a well-behaving CC curve and high capacitance (fig. S4, E and F), achieving $615\\mathrm{Fg}^{-1}$ at $40\\mathrm{Ag^{-1}}$ , which is much higher than known EDLC and quite comparable to the capacitance of transition metal–oxide faradaic pseudocapacitors (16–18). \n\nElectrochemical impedance spectroscopy (Fig. 2C, enlarged in fig. S6A) found OMFLC-N (S1) to have the lowest equivalent series resistance of ${\\sim}0.8$ ohms, better than that of OMFLC and OMC. \n\nThis may be attributed to better wetting on OMFLC-N, which lowers the interface resistance, because OMFLC has at least comparable, if not lower, resistivity than OMFLC-N (fig. S2C). The ${>}45^{\\circ}$ (negative) phase angle of both OMFLC-N (S1 and SM; inset of Fig. 2C) at relatively high frequencies confirms their capacitive behavior at fast rates. Specifically, the frequency (of $-45^{\\mathrm{o}}$ ) when the resistance and reactance have equal magnitudes is $0.48~\\mathrm{Hz}$ for OMFLC-N, giving a relaxation time ${\\bf\\zeta}_{\\tau_{0}}=1/f_{0})$ of 2.1 s. \n\nThe CV and CC tests are in broad agreement with each other when compared at the same half-cycle time $T$ as seen in Fig. 2D, which also provides insight into the charging/discharging kinetics. (In the CV test, $T$ is the time to sweep over the voltage window. In the CC test, it is the time to discharge.) In general, the capacitance $c$ may contain a rate-independent component $k_{1}$ (classically attributed to EDLC) and a diffusionlimited component controlled by the scanning rate, $\\mathrm{v}=T^{-1}$ , taking the form (19, 20) \n\n$$\nC=k_{1}+k_{2}v^{-1/2}\n$$ \n\nIn Fig. 2D, the $k_{2}v^{-1/2}$ term represents the long- $T$ data, which extrapolate to $k_{1}$ at the $\\boldsymbol{T}^{\\mathrm{{1}/2}}=\\boldsymbol{v}^{-\\mathrm{{1}/2}}=0$ intercept. (In the CV test, Fig. 2D reduces to the standard $\\dot{C}–v^{-1/2}$ plot in fig. S6B, from which one can also obtain $k_{1}.$ ) Apparently, $k_{1}$ dominates in OMFLC-N, exceeding ${700}\\mathrm{Fg^{-1}}$ in SM and $545\\mathrm{~F~g^{-1}}$ in S1. Dominance of rate-independent capacitances is common for EDLC, but it nevertheless holds here in redox reactions of the above materials because (i) OMFLC is a lowdimensional, fast-conducting, high-surface-area, few-layered material, and (ii) OMFLC-N is mesoporous (fig. S1) and hydrophilic (Fig. 1H). Therefore, they allow facile reactions both outside and inside the few-layer carbon tubes, as well as across the tube thickness. \n\nThe data from the slowest, near-equilibrium tests allowed us to construct the Tafel plots in Fig. 2, E and F, to compare the energetics of faradaic reactions and reveal a fundamental difference between OMFLC-N and OMC or OMFLC. For both S1 and SM, the potential required to sustain a constant current density of $10\\upmu\\mathrm{Acm}^{-2}$ from $\\mathrm{pH}~4.0$ to 7.0 (Fig. 2E) lies close to the theoretical Tafel line with a slope of $2.3\\times R T/F$ $(-59.2\\ \\mathrm{mV/pH})$ (21). Likewise, measuring the potential required for different current densities (Fig. 2F) at $\\mathrm{pH}~6.8$ gives again a slope in close coincidence with $2.3\\times R T/F.$ . Because both sets of Tafel lines imply a one-electron reaction, the pH dependence must arise from the concurrent incorporation of one proton and one electron. In contrast, for OMC and OMFLC, the slope is very flat, suggesting little redox activity. Recalling that the redox potential decreases with increasing concentration of nongraphitic N (Fig. 2A and table S1), we believe the redox reaction previously proposed for pseudocapacitance in N-containing polypyrrole (22) and carbon nanotubes $(8,9)-$ that each pyrrolic (N-5) and pyridine (N-6) nitrogen can incorporate an electron and a proton—is also operational here: It fits all of the above descriptions. According to N 1s XPS that can “see” through tubes less than $2\\mathrm{nm}$ thick, there is 8.2 $a t\\%$ N in OMFLC-N (S1), which may store an additional faradaic charge of $660\\mathrm{~F~g^{-1}}$ . This is more than enough to account for the storage difference $(390\\mathrm{~F~g~}^{-1})$ between OMFLC-N (S1) and OMFLC. \n\n![](images/de969c7155032ac778366fcce0e1864a86141ad6ba996d9316a23ef7797bac1d.jpg) \nFig. 3. Electrochemical performance of symmetric cells. OMFLC-N SM cathode and anode were used in two aqueous electrolytes, $0.5~\\mathsf{M}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ $\\left(\\mathsf{p}\\mathsf{H}\\mathsf{O}\\right)$ and 2 M $\\mathsf{L i}_{2}\\mathsf{S O}_{4}$ $\\mathsf{\\Pi}_{\\mathsf{p H1.8}}\\mathsf{\\Pi},$ ). (A) Cyclic voltammetry from the first cycle at $2{\\sf m}{\\sf V}{\\sf s}^{-1}$ scan rate. (B) Galvanostatic charge/discharge curves from the first cycle at $\\mathsf{1}\\mathsf{A}\\mathsf{g}^{-1}$ . (C) Symmetric electrochemical cell devices retain ${>}92\\%$ after 100 hours of sustained loading (blue symbols, upper scale) at $1.2\\:\\vee$ (in 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ ) and $1.6\\:\\vee$ (in 2 M $\\mathsf{L i}_{2}\\mathsf{S O}_{4}.$ ), and retain ${>}80\\%$ of their initial response after 50,000 cycles (black symbols, lower scale) from 0 to same peak voltages in two electrolytes. (D) Gravimetric (left) and volumetric (right) capacitance (at $1\\mathsf{A}\\mathsf{g}^{-1})$ ) of symmetric electrochemical cell device (counting electrode weight and volume only) versus areal mass loading of OMFLC-N SM in two aqueous electrolytes. (E) Ragone plot of \nspecific energy versus specific power for OMFLC-N SM symmetric devices (counting all-device weight) using 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ (solid squares) and $2\\mathsf{M}$ $\\mathsf{L i}_{2}\\mathsf{S O}_{4}$ (solid circles) electrolytes, as well as several standard devices: electrochemical capacitors (EC) (2, 28), lead-acid batteries (1, 26), nickel metal-hydride batteries $(27)$ , and lithium-ion batteries $(28)$ . Data counting electrode mass only are shown as open symbols. (F) Ragone plots of energy density versus power density for OMFLC-N SM packaged symmetric devices (counting all-device volume) using 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ (solid squares) and 2 M $\\mathsf{L i}_{2}\\mathsf{S O}_{4}$ (solid circles) electrolytes, as well as several standard devices as in (E). Data counting electrode volume only are shown as open symbols. Dotted lines in (E) and (F) are current drain time, calculated by dividing specific energy by specific power. \n\nThe proposed N-H mechanism dictates that an acidic condition is more favorable for redox reactions. This was verified for S1 in the threeelectrode CC test at $\\mathrm{1Ag^{-1}}$ : It has a larger capacitance in $0.5{\\bf M}$ $\\mathrm{H_{2}S O_{4}}(715\\mathrm{Fg^{-1}}$ , Fig. 2B) than in 1 M KOH (pH 14) electrolyte $(405\\mathrm{F}\\mathrm{g}^{-1}$ ; fig. S7, A to D, also confirmed by the CV tests). In contrast, OMFLC, which solely relies on EDLC, has very similar capacitances in the two electrolytes (fig. S7E). These results lend further support to the proposed N-H redox mechanism that makes OMFLC-N a superior supercapacitor. \n\nHoping to reduce these new mechanisms into practice, we investigated whether the threeelectrode performance of OMFLC-N can be translated to electrochemical cells. Carbon-based electrodes are special in that they can be used as both cathodes and anodes in symmetric electrochemical cells, with a per-electrode specific capacitance nearly the same as that measured in the three-electrode test. This was confirmed for YP-50, OMC, and OMFLC (table S2). Here, we multiply the nominal specific capacitance of a symmetric EC by 4 to obtain the per-electrode specific capacitance (23). In contrast, as mentioned before, pseudocapacitive materials with a pronounced redox peak are usually inefficient electrodes in symmetric electrochemical cells (23, 24) because their two differential capacitances at the two electrodes, $C_{1}$ and $C_{2}$ , are different. (Under the normal circumstance when one electrode has a suitable potential for the major redox peak and thus a larger differential capacitance, the other electrode is at a potential away from the major redox peak, hence having a smaller differential capacitance.) So their total capacitance ${C_{1}C_{2}}/$ $(C_{1}+C_{2})$ is lower than the maximum, which is $\\gamma_{2}C_{1}=\\gamma_{2}C_{2}$ when $C_{1}=C_{2}$ . In contrast, despite predominant contributions of redox reactions, our SM electrode maintains a nearly rectangular CV curve (Fig. 2A)—that is, a constant differential capacitance—in the three-electrode test. So we expect its symmetric electrochemical cell to satisfy ${\\cal C}_{1}={\\cal C}_{2},$ thus to provide a per-electrode specific capacitance identical to that measured in the three-electrode test. Indeed, its symmetriccell CV curve (Fig. 3A) in 0.5 M $\\mathrm{H_{2}S O_{4}}$ electrolyte is rectangular and rather symmetric, and its symmetric-cell CC test (Fig. 3B) gives a perelectrode capacitance of $840\\mathrm{~F~g^{-1}}$ at $\\textrm{1A g^{-1}-}$ within $2\\%$ of the three-electrode capacitance of \n\n$855\\mathrm{~F~g^{-1}}$ (see table S2). In comparison, other OMFLC-N electrodes (S1 to S3) each having a distinct redox peak in the CV curve all suffered from capacitance losses of 10 to $15\\%$ when used in a symmetric electrochemical cell (table S2). All the symmetric-cell electrochemical measurements were conducted in $0.5{\\bf M}$ $\\mathrm{H_{2}S O_{4}}$ electrolyte using an operating voltage of $1.2\\mathrm{V}$ , which did not cause any detectable $\\mathrm{{H_{2}}}$ or $\\mathrm{O}_{2}$ evolution (fig. S8A). \n\nThe performance of OMFLC-N SM electrodes in symmetric aqueous electrochemical cells was further confirmed using another electrolyte, $\\mathrm{Li_{2}S O_{4}}$ , which helps prevent carbon-electrode corroding and allows a higher operating voltage up to $1.9\\mathrm{V}$ (25). Indeed, in 2 M $\\mathrm{Li_{2}S O_{4}}$ electrolyte at pH 1.8, a symmetric electrochemical cell with SM electrodes had a threshold water-splitting voltage of $1.8\\mathrm{V}$ ; at $1.6\\mathrm{V}$ there was no detectable $\\mathrm{H}_{2}$ or $\\mathrm{O}_{2}$ evolution after 24 hours (fig. S8B). In acidic $\\mathrm{(pH~1.8)}$ but not basic $\\left(\\mathrm{pH}\\ 9.2\\right)$ ) $\\mathrm{Li_{2}S O_{4},}$ pronounced redox was confirmed by the CV test (fig. S9). With this electrolyte, symmetric electrochemical cells obtained a specific capacitance of $740\\mathrm{Fg}^{-1}$ at $\\mathbf{1}\\mathbf{A}\\mathbf{g}^{-1}$ from the CV and CC tests (Fig. 3, A and B), just $5\\%$ below the three-electrode capacitance of $780\\mathrm{F}\\mathrm{g}^{-1}$ (table S2). \n\nTo pack more energy and power into the device, we increased the mass loading to the limit of not sacrificing full electrochemical efficiency. (To aid electrode formation at $>2.0\\mathrm{mgcm^{-2}}$ OMFLC-N SM loading, we added $5\\mathrm{wt\\%}$ PVDF to the OMFLC-N powders.) Up to $6.0\\mathrm{~mg\\cm^{-2}}$ $(\\sim0.69\\mathrm{g}\\mathrm{cm}^{-3})$ , the gravimetric specific capacitance of the symmetric electrochemical cell changed minimally (Fig. 3D), indicating that OMFLC-N powders had full access to the electrolyte without geometric or electric hindrance or diffusion limitation. Such increased loading benefits the volumetric capacitance, which is important for practical applications. Peaking at $6.0~\\mathrm{{mg}~\\mathrm{{cm}^{-2}}}$ , the volumetric capacitance increases by more than a factor of 8, so that OMFLC-N SM can reach $560~\\mathrm{F~cm^{-3}}$ and $810\\mathrm{~F~g^{-1}}$ in $0.5{\\mathrm{~M~}}$ $\\mathrm{H_{2}S O_{4}},$ and $490\\ensuremath{\\mathrm{F}}\\ensuremath{\\mathrm{cm}}^{-3}$ and $\\mathrm{710~F~g^{-1}}$ in 2 M $\\mathrm{Li_{2}S O_{4}}$ (pH 1.8). The merit of our material relative to existing battery and supercapacitor materials was evaluated using Ragone plots (specific power versus specific energy) for symmetric electrochemical cells on both the device gravimetric basis (Fig. 3E) and the device volumetric basis (Fig. 3F). In 0.5 M $\\mathrm{H_{2}S O_{4}}$ electrolyte, our device has a specific energy $E$ of $24.5~\\mathrm{Wh~kg^{-1}}$ based on the device weight (corresponding to $39.5\\mathrm{Wh}$ \n\nHaving established the robust redox bipolar activities of OMFLC-N SM as both cathode and anode, we further evaluated its suitability for practical applications, starting with their stability in sustained and cyclic loading (Fig. 3C). After 100 hours of sustained loading, the capacitance retention was $93\\%$ at $1.2\\mathrm{V}$ in 0.5 M $\\mathrm{H_{2}S O_{4}}$ electrolyte and $92\\%$ at $1.6\\mathrm{V}$ in 2 M $\\mathrm{Li_{2}S O_{4}}$ electrolyte. The symmetric electrochemical cell withstood 50,000 cycles between 0 and $1.2\\mathrm{V}$ in $0.5{\\bf M}$ $\\mathrm{H_{2}S O_{4}}$ electrolyte with $82\\%$ of the capacitance remaining; a similarly cycled device between 0 and $1.6\\mathrm{\\:V}$ in 2 M $\\mathrm{Li_{2}S O_{4}}$ $\\mathrm{(pH1.8}$ ) electrolyte retained $80\\%$ . \n\n$\\mathrm{kg_{OMFLC-N}}^{-1}$ based on the active-material weight) or 12.0 Wh liter−1 based on the device volume (or 27.0 Wh literOMFLC-N−1 based on the electrode volume). The specific power $P$ is $26.5\\mathrm{kW}\\mathrm{kg}^{-1}$ $(42.5\\mathrm{kW}\\mathrm{kg}_{\\mathrm{OMFLC-N}}^{-1})$ or $13.0\\mathrm{kW}\\mathrm{liter}^{-1}(29.0\\mathrm{kW}$ $\\mathrm{liter_{OMFLC-N}}^{-1\\setminus}$ , with a current-drain time $(E/P)$ of $3.4~\\mathrm{s}.$ . In 2 M $\\mathrm{Li_{2}S O_{4}}$ electrolyte, $E$ increases to $\\mathrm{4.0Wh\\kg^{-1}(63.0W h\\ k g_{O M F L C-N})^{-1}}$ and $19.5\\mathrm{Wh}$ liter−1 (43.5 Wh literOMFLC-N−1) and $P$ stays at $26.0\\mathrm{kW}\\mathrm{kg}^{-1}$ $44.0\\mathrm{kW}\\mathrm{kg}_{\\mathrm{OMFLC-N}}-$ 1) and $12.5\\mathrm{kW}$ liter−1 $(30.0\\mathrm{\\kW\\liter_{OMFLC-N}}^{-1},$ , with a drain time of 5.7 s. For supercapacitor applications, these properties are notable in that high specific power can be simultaneously achieved along with high specific energy, thus making carbonbased supercapacitors potentially competitive against batteries, such as lead-acid batteries (3, 26), nickel metahydride batteries (27), and perhaps even lithium batteries (28) on a gravimetric basis. \n\nSimplified fabrication of N-doped mesoporous few-layer carbon (omitting the sacrificial silica template and post–carbon deposition etching as described in supplementary materials) was finally implemented by combining chemical vapor deposition with a sol-gel process of inexpensive, environmentally friendly, Si-free precursors/ catalysts. The material obtained is made of highly conductive $(\\upsigma=360\\mathrm{S}/\\mathrm{cm})$ mesoscopically ordered few-layer carbon with a large surface area $(1900\\mathrm{~m}^{2}\\mathrm{~g}^{-1})$ . In $0.5\\mathrm{~M~}$ $\\mathrm{H_{2}S O_{4}}$ electrolyte, its electrode has a specific capacitance of $790\\mathrm{F}\\mathrm{g}^{-1}$ at $\\mathrm{1Ag^{-1}}$ , and its packaged device has a specific energy of $23.0~\\mathrm{Wh~kg^{-1}}$ and a specific power of $18.5\\mathrm{kW}\\mathrm{kg}^{-1}$ based on the device weight; in $^{2\\mathrm{{M}}}$ $\\mathrm{Li_{2}S O_{4}}$ $\\mathrm{(pH~1.8)}$ ) electrolyte, the corresponding values are $720\\ \\mathrm{F\\g^{-1}}$ , $38.5\\mathrm{Wh\\kg^{-1}}$ , and $22.5\\mathrm{kW}$ $\\mathbf{kg^{-1}}$ . Indeed, in all important respects (figs. S10 to S13), this material behaves within ${\\sim}10\\%$ of the best OMFLC-N SM described above, thus providing an outstanding low-cost carbon-based material for electrochemical cells for electric power applications. \n\n# REFERENCES AND NOTES \n\n1. J. Chmiola et al., Science 313, 1760–1763 (2006). \n2. Y. Zhu et al., Science 332, 1537–1541 (2011). \n3. P. Simon, Y. Gogotsi, Nat. Mater. 7, 845–854 (2008). \n4. X. Yang, C. Cheng, Y. Wang, L. Qiu, D. Li, Science 341, 534–537 (2013). \n5. J. Xia, F. Chen, J. Li, N. Tao, Nat. Nanotechnol. 4, 505–509 (2009). \n6. M. F. El-Kady, V. Strong, S. Dubin, R. B. Kaner, Science 335, 1326–1330 (2012). \n7. J. Huang, B. G. Sumpter, V. Meunier, Angew. Chem. Int. Ed. 47, 520–524 (2008). \n8. L. L. Zhang et al., Energy Environ. Sci. 5, 9618–9625 (2012). \n9. G. Lota, B. Grzyb, H. Machnikowska, J. Machnikowski, E. Frackowiak, Chem. Phys. Lett. 404, 53–58 (2005). \n10. H. Li et al., J. Power Sources 190, 578–586 (2009). \n11. D. Zhao et al., Science 279, 548–552 (1998). \n12. P. M. Vora et al., Phys. Rev. B 84, 155114 (2011). \n13. J. Casanovas, J. M. Ricart, J. Rubio, F. Illas, J. M. Jiménez-Mateos, J. Am. Chem. Soc. 118, 8071–8076 (1996). \n14. D. Wei et al., Nano Lett. 9, 1752–1758 (2009). \n15. D. W. Wang et al., Chem. Eur. J. 18, 5345–5351 (2012). \n25. Q. Gao, L. Demarconnay, E. Raymundo-Piñero, F. Béguin, Energy Environ. Sci. 5, 9611–9617 (2012). \n26. A. F. Burke, Advanced batteries for vehicle applications. In Encyclopedia of Automotive Engineering, D. Crolla, D. E. Foster, T. Kobayashi, N. Vaughan, Eds. (Wiley, New York, 2014), pp. 1–20. \n27. A. Burke, M. Miller, J. Power Sources 196, 514–522 (2011). \n28. D. Linden, T. B. Reddy, Handbook of Batteries (McGraw-Hill, New York, ed. 3, 2001). \n\n# ACKNOWLEDGMENTS \n\nSupported by National Natural Science Foundation of China grants 51125006, 91122034, 61376056, and 51402336 and Science and Technology Commission of Shanghai grant 14YF1406500. \n\n# NANOMATERIALS \n\n# Synthesis of borophenes: Anisotropic, two-dimensional boron polymorphs \n\nAndrew J. Mannix,1,2 Xiang-Feng Zhou,3,4 Brian Kiraly,1,2 Joshua D. Wood,2 Diego Alducin,5 Benjamin D. Myers,2,6 Xiaolong Liu,7 Brandon L. Fisher,1 Ulises Santiago,5 Jeffrey R. Guest,1 Miguel Jose Yacaman,5 Arturo Ponce,5 Artem R. Oganov,8,9,3\\* Mark C. Hersam,2,7,10\\* Nathan P. Guisinger1\\* \n\nAt the atomic-cluster scale, pure boron is markedly similar to carbon, forming simple planar molecules and cage-like fullerenes.Theoretical studies predict that two-dimensional (2D) boron sheets will adopt an atomic configuration similar to that of boron atomic clusters. We synthesized atomically thin, crystalline 2D boron sheets (i.e., borophene) on silver surfaces under ultrahigh-vacuum conditions. Atomic-scale characterization, supported by theoretical calculations, revealed structures reminiscent of fused boron clusters with multiple scales of anisotropic, out-of-plane buckling. Unlike bulk boron allotropes, borophene shows metallic characteristics that are consistent with predictions of a highly anisotropic, 2D metal. \n\nB onding between boron atoms is more complex than in carbon; for example, both twoand three-center B-B bonds can form $(I)$ . The interaction between these bonding configurations results in as many as 16 bulk allotropes of boron (1–3), composed of icosahedral $\\mathbf{B}_{12}$ units, small interstitial clusters, and fused supericosahedra. In contrast, small $(n<15)$ boron clusters form simple covalent, quasiplanar molecules with carbon-like aromatic or anti-aromatic electronic structure (4–7). Recently, Zhai et al. have shown that $\\mathbf{B}_{40}$ clusters form a cage-like fullerene $\\scriptstyle(6),$ further extending the parallels between boron and carbon cluster chemistry. \n\nTo date, experimental investigations of nanostructured boron allotropes are notably sparse, partly owing to the costly and toxic precursors (e.g., diborane) typically used. However, numerous theoretical studies have examined twodimensional (2D) boron sheets [i.e., borophene (7)]. Although these studies propose various structures, we refer to the general class of 2D boron sheets as borophene. Based upon the quasiplanar $\\mathbf{B}_{7}$ cluster (Fig. 1A), Boustani proposed an Aufbau principle (8) to construct nanostructures, including puckered monolayer sheets (analogous to the relation between graphene and the aromatic ring). The stability of these sheets is enhanced by vacancy superstructures $(7,9)$ or out-of-plane distortions (10, 11). Typically, borophene is predicted to be metallic (7, 9–12) or semimetallic (10) and is expected to exhibit weak binding (13) and anisotropic growth (14) when adsorbed on noble-metal substrates. Early reports of multiwall boron nanotubes suggested a layered structure (15), but their atomic-scale structure remains unresolved. It is therefore unknown whether borophene is experimentally stable and whether the borophene structure would reflect the simplicity of planar boron clusters or the complexity of bulk boron phases. \n\nI.W.C. was supported by U.S. Department of Energy BES grant DE-FG02-11ER46814 and used the facilities (Laboratory for Research on the Structure of Matter) supported by NSF grant DMR-11-20901. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/350/6267/1508/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S14 \nTables S1 and S2 \nReferences (29–32) \n\n20 April 2015; accepted 13 November 2015 \n10.1126/science.aab3798 \n\nWe have grown atomically thin, borophene sheets under ultrahigh-vacuum (UHV) conditions (Fig. 1B), using a solid boron atomic source $(99.9999\\%$ purity) to avoid the difficulties posed by toxic precursors. An atomically clean Ag(111) substrate provided a well-defined and inert surface for borophene growth (13, 16). In situ scanning tunneling microscopy (STM) images show the emergence of planar structures exhibiting anisotropic corrugation, which is consistent with first-principles structure prediction. We further verify the planar, chemically distinct, and atomically thin nature of these sheets via a suite of characterization techniques. In situ electronic characterization supports theoretical predictions that borophene sheets are metallic with highly anisotropic electronic properties. This anisotropy is predicted to result in mechanical stiffness comparable to that of graphene along one axis. Such properties are complementary to those of existing 2D materials and distinct from those of the metallic boron previously observable only at ultrahigh pressures $(I7)$ . \n\nDuring growth, the substrate was maintained between $450^{\\circ}$ and $700^{\\circ}\\mathrm{C}$ under a boron flux between ${\\sim}0.01$ to ${\\sim}0.1$ monolayer (ML) per minute [see supplementary materials for details (18)]. After deposition, in situ Auger electron spectroscopy (AES; Fig. 1C) revealed a boron KLL peak at the standard position $\\mathrm{(180~eV)}$ superimposed on the clean Ag(111) spectrum. We observed no peaks due to contaminants, and none of the distinctive peak shifts or satellite features characteristic of compound or alloy formation (fig. S1). \n\nAfter boron deposition at a substrate temperature of $550^{\\circ}\\mathrm{C},$ , STM topography images (Fig. 1D) revealed two distinct boron phases: a homogeneous phase and a more corrugated “striped” phase (highlighted with red and white arrows, respectively). Simultaneously acquired dI/dV maps (where $I$ and $V$ are the tunneling current and voltage, respectively) of the electronic density of states (DOS), given in Fig. 1E, showed strong electronic contrast between boron sheets and the $\\mathbf{Ag}(\\mathrm{{111}})$ substrate and increased differentiation between homogeneous and striped islands. The relative concentration of these phases depends upon the deposition rate. Low deposition rates favored the striped phase and resulted in the \n\nEditor's Summary \n\n# Store more energy with a touch of nitrogen \n\nIn contrast to batteries, capacitors typically can store less power, but they can capture and release that power much more quickly. Lin et al. fabricated a porous carbon material that was then doped with nitrogen. This raised the energy density of the carbon more than threefold−−an increase that was retained in full capacitors, without losing their ability to deliver power quickly. \n\nScience, this issue p. 1508 \n\nThis copy is for your personal, non-commercial use only. \n\n# Article Tools \n\n# Permissions \n\nObtain information about reproducing this article: http://www.sciencemag.org/about/permissions.dtl " + }, + { + "id": "10.1126_science.aaa8765", + "DOI": "10.1126/science.aaa8765", + "DOI Link": "http://dx.doi.org/10.1126/science.aaa8765", + "Relative Dir Path": "mds/10.1126_science.aaa8765", + "Article Title": "High-performance transition metal-doped Pt3Ni octahedra for oxygen reduction reaction", + "Authors": "Huang, XQ; Zhao, ZP; Cao, L; Chen, Y; Zhu, EB; Lin, ZY; Li, MF; Yan, AM; Zettl, A; Wang, YM; Duan, XF; Mueller, T; Huang, Y", + "Source Title": "SCIENCE", + "Abstract": "Bimetallic platinum-nickel (Pt-Ni) nullostructures represent an emerging class of electrocatalysts for oxygen reduction reaction (ORR) in fuel cells, but practical applications have been limited by catalytic activity and durability. We surface-doped Pt3Ni octahedra supported on carbon with transition metals, termed M-Pt3Ni/C, where M is vanadium, chromium, manganese, iron, cobalt, molybdenum (Mo), tungsten, or rhenium. The Mo-Pt3Ni/C showed the best ORR performance, with a specific activity of 10.3 mA/cm(2) and mass activity of 6.98 A/mg(Pt), which are 81- and 73-fold enhancements compared with the commercial Pt/C catalyst (0.127 mA/cm(2) and 0.096 A/mg(Pt)). Theoretical calculations suggest that Mo prefers subsurface positions near the particle edges in vacuum and surface vertex/edge sites in oxidizing conditions, where it enhances both the performance and the stability of the Pt3Ni catalyst.", + "Times Cited, WoS Core": 1665, + "Times Cited, All Databases": 1783, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000356011500048", + "Markdown": "8. J. Y. Rempel, M. G. Bawendi, K. F. Jensen, J. Am. Chem. Soc. 131, 4479–4489 (2009). \n9. R. García-Rodríguez, M. P. Hendricks, B. M. Cossairt, H. Liu, J. S. Owen, Chem. Mater. 25, 1233–1249 (2013). \n10. T. P. A. Ruberu et al., ACS Nano 6, 5348–5359 (2012). \n11. Y. Guo, S. R. Alvarado, J. D. Barclay, J. Vela, ACS Nano 7, 3616–3626 (2013). \n12. I. Moreels et al., ACS Nano 3, 3023–3030 (2009). \n13. M. C. Weidman, M. E. Beck, R. S. Hoffman, F. Prins, W. A. Tisdale, ACS Nano 8, 6363–6371 (2014). \n14. C.-H. M. Chuang, P. R. Brown, V. Bulović, M. G. Bawendi, Nat. Mater. 13, 796–801 (2014). \n15. C. D. Ritchie, W. F. Sager, Prog. Phys. Org. Chem. 2, 323–400 (1964). \n16. G. Marcotrigiano, G. Peyronel, R. Battistuzzi, J. Chem. Soc. Perkin Trans. 2 1972, 1539 (1972). \n17. F. Wang, W. Buhro, J. Am. Chem. Soc. 134, 5369–5380 (2012). \n18. G. G. Yordanov, C. D. Dushkin, E. Adachi, Colloids Surf. A Physicochem. Eng. Asp. 316, 37–45 (2008). \n\n19. D. Zherebetskyy et al., Science 344, 1380–1384 (2014). 20. N. C. Anderson, M. P. Hendricks, J. J. Choi, J. S. Owen, J. Am. Chem. Soc. 135, 18536–18548 (2013). \n\n# ACKNOWLEDGMENTS \n\nPrecursor design and kinetics studies were supported by the Center for Re-Defining Photovoltaic Efficiency Through Molecule Scale Control, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under award no. DE-SC0001085. Large-scale syntheses and surface chemistry measurements were supported by the Department of Energy under grant no. DE-SC0006410. The authors thank A. N. Beecher and E. Auyeung for assistance with transmission electron microscopy, which was carried out in part at the New York Structural Biology Center, supported by Empire State Development’s Division of Science, Technology and Innovation and the National Center for Research Resources, NIH, grant no. C06 \n\nRR017528-01-CEM. We also thank E. Busby and M. Sfier for assistance with near-infrared (NIR) photoluminescence, which was carried out in part at the Center for Functional Nanomaterials, Brookhaven National Laboratory, Office of Basic Energy Sciences, under contract no. DE-AC02-98CH10886. Z. M. Norman is thanked for assistance with Fourier transform–infrared spectroscopy studies and A. S. R. Chesman for helpful advice concerning the synthesis and characterization of copper zinc tin sulfide. A series of patent applications on this subject have been filed. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/348/6240/1226/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S20 \nReferences (21–27) \n\n13 November 2014; accepted 1 May 2015 \n10.1126/science.aaa2951 \n\n# ELECTROCHEMISTRY \n\n# High-performance transition metal–doped Pt Ni octahedra for oxygen reduction reaction \n\nXiaoqing Huang, $^{1,2*}\\dag$ Zipeng Zhao,1,2\\* Liang Cao,3 Yu Chen,1,2 Enbo Zhu,1,2 Zhaoyang Lin,4 Mufan Li,4 Aiming Yan,5,6,7 Alex Zettl, ${\\bf5,6,7_{\\bf\\delta Y.}}$ Morris Wang,8 Xiangfeng Duan,2,4 Tim Mueller, $^{9}\\ddag$ Yu Huang1,2‡ \n\nBimetallic platinum-nickel (Pt-Ni) nanostructures represent an emerging class of electrocatalysts for oxygen reduction reaction (ORR) in fuel cells, but practical applications have been limited by catalytic activity and durability. We surface-doped $\\mathsf{P t}_{3}\\mathsf{N i}$ octahedra supported on carbon with transition metals, termed $M\\mathrm{-}P t_{3}\\mathsf{N i/C}$ , where M is vanadium, chromium, manganese, iron, cobalt, molybdenum (Mo), tungsten, or rhenium. The Mo ${\\cdot}\\mathsf{P t}_{3}\\mathsf{N i}/\\mathsf{C}$ showed the best ORR performance, with a specific activity of $10.3\\:\\mathsf{m A}/\\mathsf{c m}^{2}$ and mass activity of 6.98 $\\mathsf{\\Delta}\\mathsf{\\/m g_{P t}}$ , which are 81- and 73‐fold enhancements compared with the commercial Pt/C catalyst $(0.127\\mathrm{\\mA}/\\mathrm{cm}^{2}$ and $0.096\\mathrm{\\A/mg_{Pt})}$ . Theoretical calculations suggest that Mo prefers subsurface positions near the particle edges in vacuum and surface vertex/edge sites in oxidizing conditions, where it enhances both the performance and the stability of the $\\mathsf{P t}_{3}\\mathsf{N i}$ catalyst. \n\nP ouhxsyiedraroengatec(ntimoornlsae buoelhatrowloes)exynatg ethn)e aftnutoehlde(csauntcdhohdaes need catalysts to lower their electrochemical overpotential for high-voltage output, and so far, platinum $\\mathbf{\\Psi}(\\mathrm{Pt})$ has been the universal choice (4–6). To fully realize the commercial viability of fuel cells, the following challenges, which may not be strictly independent of one another, need to be simultaneously addressed: the high cost of Pt, the sluggish kinetics of the oxygen reduction reaction (ORR), and the low durability of the catalysts (7–11). \n\nAlloying Pt with a secondary metal reduces the usage of scarce Pt metal while at the same time improving performance as compared with that of pure Pt on mass activity (12–15), which has led to the development of active and durable Ptbased electrocatalysts with a wide range of compositions (16–20). However, although studies so far have led to a considerable increase in ORR activity, the champion activity as observed on bulk $\\mathrm{Pt_{3}N i(111)}$ surface has not been matched in nanocatalyts (21–25), indicating room for further improvement. At the same time, one noted major limitation of Pt-Ni nanostructures is their low durability. The Ni element in these nanostructures leaches away gradually under detrimental corrosive ORR conditions, resulting in rapid performance losses (23–27). Thus, synthesizing Pt‐based nanostructures with simultaneously high catalytic activity and durability remains an important open challenge (28). \n\nBecause surface and near-surface features of a catalyst have a strong influence on its catalytic performance, we adopted a surface engineering strategy to further explore and enhance the performance of $\\mathrm{Pt_{3}N i(\\mathbf{\\bar{1}}\\mathbf{1}\\mathbf{1})}$ nanocatalysts. We specifically focused our efforts on $\\mathrm{Pt_{3}N i}$ -based nanocatalysts because the bulk extended $\\mathrm{Pt_{3}N i(\\mathrm{111})}$ surface has been shown to be one of the most efficient catalytic surfaces for the ORR. On the basis of the control over dopant incorporation of various transition metals onto the surface of dispersive and octahedral $\\mathrm{Pt_{3}N i/C}$ (termed as M $\\mathrm{\\bar{-Pt}_{3}N i/C,}$ where $M=\\mathbb{V}$ , Cr, Mn, Fe, Co, Mo, W, or Re), we have developed ORR catalysts that exhibit both high activity and stability. In particular, our $\\mathrm{Mo{-}P t_{3}N i/C}$ catalyst has high specific activity $(10.3\\mathrm{mA/cm^{2}})$ ), high mass activity $(6.98\\ \\mathrm{A/mg_{Pt}})$ , and substantially improved stability for 8000 potential cycles. \n\nWe prepared highly dispersed $\\mathrm{Pt_{3}N i}$ octahedra on commercial carbon black by means of an efficient one‐pot approach without using any bulky capping agents, which used platinum(II) acetylacetonate $\\mathrm{[Pt(acac)_{2}]}$ and nickel(II) acetylacetonate $\\mathrm{[Ni(acac)_{2}]}$ as metal precursors, carbon black as support, $N\\mathcal{N}$ -dimethylformamide (DMF) as solvent and reducing agent, and benzoic acid as the structure-directing agent (fig. S1A). The surface doping for the $\\mathrm{Pt_{3}N i/C}$ catalyst was initiated by the addition of dopant precursors, $\\mathrm{Mo(CO)_{6}},$ together with $\\mathrm{Pt}(\\mathrm{acac})_{2}$ and $\\mathrm{Ni(acac)_{2}}$ into a suspension of $\\mathrm{Pt_{3}N i/C}$ in DMF, and the subsequent reaction at $\\mathrm{170^{\\circ}C}$ for 48 hours (fig. S1B). The transmission electron microscopy (TEM) and high‐angle annular dark‐field scanning TEM (HAADF‐STEM) images of the $\\mathrm{Pt_{3}N i/C}$ and Mo$\\mathrm{Pt_{3}N i/C}$ catalysts (Fig. 1, A and B, and fig. S2) revealed highly dispersive octahedral nanocrystals (NCs) in both samples, which were substantially uniform in size, averaging $4.2\\pm0.2\\ \\mathrm{nm}$ in edge length. High-resolution TEM (HRTEM) images taken from individual octahedra showed a single-crystal structure with well‐defined fringes (Fig. 1, C and D) and an edge lattice spacing of $0.22~\\mathrm{nm}$ , which is consistent with that expected for face-centered cubic (fcc) $\\mathrm{Pt_{3}N i}.$ \n\n![](images/208c0f66804fd50d6451209d76d4db174e5cb53c8943c5597b4c889abadf442d.jpg) \nFig. 1. Schematic illustration of the fabrication process and the structure analyses for the transition metal–doped $\\mathsf{P t}_{3}\\mathsf{N i}/{\\mathsf{C}}$ catalysts. (A and B) Representative HAADF‐STEM images of the (A) $\\mathsf{P t}_{3}\\mathsf{N i/C}$ and (B) Mo- $\\cdot\\mathsf{P t}_{3}\\mathsf{N i}/\\mathsf{C}$ catalysts. (C and D) HRTEM images on individual octahedral (C) $\\mathsf{P t}_{3}\\mathsf{N i}/\\mathsf{C}$ and (D) Mo-Pt3Ni/C nanocrystals. (E and F) EDS line‐scanning profile across individual (E) $\\mathsf{P t}_{3}\\mathsf{N i/C}$ and (F) Mo-Pt3Ni/C octahedral nanocrystals. (G) Pt, Ni, and Mo XPS spectra for the octahedral Mo‐Pt3Ni/C catalyst. \n\nFor $\\mathrm{Pt_{3}N i},$ powder x‐ray diffraction (PXRD) patterns of the colloidal products displayed typical peaks that could be indexed as those of fcc $\\mathrm{Pt_{3}N i}$ (fig. S3) (29, 30), and the $\\mathrm{{Pt/Ni}}$ composition of 74/26 was confirmed by means of both inductively coupled plasma atomic emission spectroscopy (ICP‐AES) and TEM energy‐dispersive x‐ray spectroscopy (TEM‐EDS) (fig. S4 and table S1). Composition line-scan profiles across octahedra obtained by means of HAADF‐STEM‐EDS for $\\mathrm{Pt_{3}N i/C}$ (Fig. 1E) and Mo- $\\mathrm{\\cdotPt_{3}N i/C}$ (Fig. 1F) showed that all elements were distributed throughout the NCs (Fig. 1, E and F). For the doped NCs, x‐ray photoelectron spectroscopy (XPS) shows the presence of Pt, Ni, and Mo in the catalyst (Fig. 1G). The Ni 2p and Pt 4f XPS spectra of the $\\mathrm{{Mo-Pt_{3}N i/C}}$ catalyst showed that the majority of the surface Ni was in the oxidized state and that the surface Pt was mainly in the metallic state, which were consistent with a recent Pt-Ni catalysts–based study (28). Mo exhibits mainly ${\\mathrm{Mo}}^{6+}$ and ${\\mathrm{Mo}}^{4+}$ states, which is in agreement with previous studies of PtMo nanoparticles (31). The overall molar ratio for Pt, Ni, and Mo obtained from ICP-AES was 73.4:25.0:1.6. \n\n![](images/c236eba66c20e1431033032d807b5a9299e6e1c3aa9c7334bc91bae9a0cf351e.jpg) \nFig. 2. Electrocatalytic properties of high‐performance transition metal–doped octahedral $\\mathsf{P t}_{3}\\mathsf{N i}/\\mathsf{c}$ catalysts and a commercial Pt/C catalyst. (A) Cyclic voltammograms of octahedral ${\\mathsf{M o-P t}}_{3}{\\mathsf{N i/C}}$ , octahedral $\\mathsf{P t}_{3}\\mathsf{N i/C}$ , and commercial Pt/C catalysts recorded at room temperature in ${\\sf N}_{2}$ ‐purged ${0.1\\:\\mathsf{M}}$ ${\\mathsf{H C l O}}_{4}$ solution with a sweep rate of $100~\\mathsf{m V}/\\mathsf{s}$ . (B) ORR polarization curves of octahedral ${\\mathsf{M o-P t}}_{3}{\\mathsf{N i/C}}$ , octahedral $\\mathsf{P t}_{3}\\mathsf{N i}/\\mathsf{C}$ , and commercial $\\mathsf{P t/C}$ catalysts recorded at room temperature in an ${{\\mathsf O}_{2}}$ ‐saturated $0.1\\mathsf{M}$ $H C l O_{4}$ aqueous solution with a sweep rate of $10\\mathrm{mV/s}$ and a rotation rate of 1600 rotations per min (rpm). (C) The electrochemically active surface area (ECSA, top), specific activity (middle), and mass activity (bottom) at $0.9~\\mathsf{V}$ versus RHE for these transition metal–doped ${\\mathsf{P t}}_{3}{\\mathsf{N i/C}}$ catalysts, which are given as kinetic current densities normalized to the ECSA and the loading amount of Pt, respectively. In (A) and (B), current densities were normalized in reference to the geometric area of the RDE (0.196 cm2). \n\nTo assess ORR catalytic activity, we used cyclic voltammetry (CV) to evaluate the electrochemically active surface areas (ECSAs). Our catalysts were loaded (with the same Pt mass loading) onto glassy carbon electrodes. A commercial $\\mathrm{Pt/C}$ catalyst [20 weight percent (wt $\\%$ ) Pt on carbon black; Pt particle size, 2 to $5\\mathrm{nm}]$ obtained from Alfa-Aesar was used as a baseline catalyst for comparison (fig. S5). The CV curves on these different catalysts are compared in Fig. 2A. We calculated the ECSA by measuring the charge collected in the hydrogen adsorption/desorption region (between 0.05 and 0.35 V) after double‐layer correction and assuming a value of $210~\\upmu\\mathrm{C/cm^{2}}$ for the adsorption of a hydrogen monolayer. The octahedral $\\mathrm{Pt_{3}N i/C}$ and $\\mathrm{{Mo-Pt_{3}N i/C}}$ catalysts display similar and high ECSAs of 66.6 and $67.5\\mathrm{{m}^{2}/g_{P t},}$ respectively, which is comparable with that of the commercial $\\mathrm{Pt/C}$ catalyst $(75.6~\\mathrm{m^{2}/g_{P t})}$ (Fig. 2C, top). \n\nThe ORR polarization curves for the different catalysts, which were normalized by the area of the glassy carbon area $\\mathrm{(0.196~cm^{2})}$ ), are shown in Fig. 2B. The polarization curves display two distinguishable potential regions: the diffusion‐ limiting current region below $0.6\\mathrm{V}$ and the mixed kinetic‐diffusion control region between 0.6 and 1.1 V. We calculated the kinetic currents from the ORR polarization curves by considering the mass‐ transport correction (32). In order to compare the activity for different catalysts, the kinetic currents were normalized with respect to both ECSA and the loading amount of metal Pt. As shown in Fig. 2C, the octahedral Mo $\\mathrm{\\cdotPt_{3}N i/C}$ exhibits a specific activity of $\\mathrm{10.3\\mA/cm^{2}}$ at $0.9{\\mathrm{V}}$ versus a reversible hydrogen electrode (RHE). In contrast, the specific activity of the undoped $\\mathrm{Pt_{3}N i/C}$ catalyst is $\\mathrm{\\sim2.7\\mA/cm^{2}}$ . On the basis of the mass loading of Pt, the mass activity of the Mo $\\mathrm{\\cdotPt_{3}N i/C}$ catalyst was calculated to be $6.98~\\mathrm{{A/mg_{Pt}}}$ . The specific activity of the $\\mathrm{{Mo-Pt_{3}N i/C}}$ catalyst represents an improvement by a factor of 81 relative to the commercial $\\mathrm{Pt/C}$ catalyst, whereas the mass activity of the Mo $\\mathrm{\\cdotPt_{3}N i/C}$ catalyst achieved a 73‐fold enhancement. To compare the activities of our catalysts with the state-of-the-art reported Pt-Ni catalysts, we also calculated the catalytic activities of our catalysts at $0.95\\mathrm{V}$ and with the ECSA calculated with the CO stripping method. Whether we calculated at 0.90 or $0.95\\mathrm{V}$ or used the ECSA based on Hupd and/or CO stripping, both the specific activity and the mass activity of the Mo $\\mathrm{\\cdotPt_{3}N i/C}$ (fig. S6) are higher than those of the state‐of‐the-art Pt-Ni catalysts (21, 24), including the recently reported Pt-Ni nanoframes catalyst (Table 1 and table S2) (28). \n\nBecause Mo $\\mathrm{\\cdotPt_{3}N i/C}$ exhibited an exceptional activity toward ORR, we further examined the doping effects for $\\mathrm{Pt_{3}N i/C}$ modified by other transition metals. $\\mathrm{Pt_{3}N i/C}$ catalysts doped with seven other transition metals—V, Cr, Mn, Fe, Co, W, or Re—were synthesized in a similar fashion with metal carbonyls (figs. S7 and S8 and table S1; details are available in the supplementary materials), and their catalytic activity toward the ORR was tested under the same conditions (Fig. 2C; individual sample measurements are available in fig. S9). The ECSAs of these transition metal– doped $\\mathrm{Pt_{3}N i/C}$ catalysts were all similar (Fig. 2C, top), but variable ORR activities were observed for differently doped $\\mathrm{Pt_{3}N i/C}$ catalysts. None of the other dopants resulted in a catalyst with activity as high as that of the Mo $\\mathrm{\\cdotPt_{3}N i/C}$ (Fig. 2C, middle). The change of mass activities in various $M_{\\sun}$ -doped $\\mathrm{Pt_{3}N i/C}$ catalysts was also similar to that of the specific activities (Fig. 2C, bottom), with Mo- $\\mathrm{\\cdotPt_{3}N i/C}$ showing the highest activity. \n\nWe further evaluated the electrochemical durability of the $\\mathrm{{Mo-Pt_{3}N i/C}}$ catalyst using the accelerated durability test (ADT) between 0.6 and 1.1 V (versus RHE, 4000 and 800 cycles) in $\\mathrm{O_{2}}$ ‐saturated 0.1 M $\\mathrm{HClO}_{4}$ at a scan rate of $50\\ \\mathrm{mV/s}$ . The $\\mathrm{Pt_{3}N i/C}$ catalyst was used as a baseline catalyst for comparison. After 4000 and 8000 potential cycles, the $\\mathrm{{Mo-Pt_{3}N i/C}}$ catalyst largely retained its ECSA and activity (Fig. 3A), exhibiting only 1- and $\\ensuremath{\\mathrm{3-mV}}$ shifts for its half‐wave potential, respectively. And after 8000 cycles, the activity of the $\\mathrm{{Mo-Pt_{3}N i/C}}$ catalyst was still as high as $9.7\\mathrm{mA}/\\mathrm{cm}^{2}$ and $6.6~\\mathrm{A/mg_{Pt}}$ (Fig. 3C), showing only 6.2 and $5.5\\%$ decreases from the initial specific activity and mass activity, respectively. On the other hand, the undoped $\\mathrm{Pt_{3}N i/C}$ catalyst was unstable under the same reaction conditions. Its polarization curve showed a $33\\mathrm{-mV}$ negative shift after durability tests (Fig. 3B), and the $\\mathrm{Pt_{3}N i/C}$ retained only 33 and $41\\%$ of the initial specific activity and mass activity, respectively, after 8000 cycles (Fig. 3C). The morphology and the composition of the electrocatalysts after the durability change were further examined. As shown in fig. S4, although the size of the $\\mathrm{Pt_{3}N i/C}$ octahedra were largely maintained, their morphologies became more spherical. This change of the morphology likely resulted from the Ni loss after the potential cycles, as confirmed by means of EDS and XPS analyses (the Pt/Ni composition ratio changed from 74.3/25.7 to 88.1/11.9) (figs. S4 and S10). In contrast, the corresponding morphology of the Mo $\\mathrm{\\cdotPt_{3}N i/C}$ catalyst largely maintained the octahedral shape, and the composition change was negligible (from 73.4/25.0/1.6 to 74.5/24.0/1.5). \n\nTable 1. Performance of M $\\mathsf{l o}\\mathsf{-P t}_{3}\\mathsf{N i}/\\mathsf{c}$ catalyst and several representative results with high performance from recent published works. NA, not availlable. \n\n\n
CatalystBased on Hupd SpecificBased on CO stripping Specific
ECSA (m² / gpt) @(activit) @@Mass activity (A/mgpt) @ECSA (m²/gpt)(activit2) @@
This67.70.9 V 10.30.95 V 2.080.9 V0.95 V0.9 V 8.20.95 V 1.74
work ThisMo-Pt3Ni/C Pt3Ni/C66.62.70.556.98 1.801.4183.90.45
work0.3781.92.2
(53) (24)PtNi/C PtNi/C50 483.14 3.8NA 1.45 NA 1.65NA NANA NANA NANA NA
(21)PtNi2.5/C21NANA 3.3NA31NANA
(28)Pt3Ni/C nanoframesNANANA 5.70.97NANA1.48
\n\n![](images/bf0480cb36e611baf89c6705ce2b155e87a6b4ada821ed5dc04ee6cc479a8138.jpg) \nFig. 3. Electrochemical durability of the high-performance octahedral Mo-Pt3NiCo/C catalyst and octahedral $\\mathsf{P t}_{3}\\mathsf{N i}/\\mathsf{c}$ catalyst. (A and B) ORR polarization curves and (inset) corresponding cyclic voltammograms of (A) the octahedral ${\\mathsf{M o-P t}}_{3}{\\mathsf{N i/C}}$ catalyst and (B) the octahedral $\\mathsf{P t}_{3}\\mathsf{N i}/\\mathsf{C}$ catalyst before, after 4000, and after 8000 potential cycles between 0.6 and 1.1 V versus RHE. (C) The changes of ECSAs (left), specific activities (middle), and mass activities (right) of the octahedral Mo‐Pt3Ni/C catalyst and octahedral $\\mathsf{P t}_{3}\\mathsf{N i/C}$ catalyst before, after 4000, and after 8000 potential cycles. The durability tests were carried out at room temperature in ${{\\mathsf O}_{2}}$ ‐saturated 0.1 M $H C l O_{4}$ at a scan rate of $50\\mathrm{mV/s}$ . \n\nTo investigate the cause of the enhanced durability of the Mo $\\mathrm{\\cdotPt_{3}N i/C}$ catalysts, cluster expansions of Pt‐Ni‐Mo NCs were used in Monte Carlo simulations (33–35) to identify low‐energy NC and (111) surface structures for computational analysis (details of our calculations are provided in the supplementary materials). In vacuum, the equilibrium structures predicted by the cluster expansion have a Pt skin, with Mo atoms preferring sites in the second atomic layer along the edges connecting two different (111) facets (Fig. 4, A and B, and fig. S11). Density functional theory (DFT) (36) calculations indicate that in vacuum, the subsurface site is preferable to the lowest‐energy neighboring surface site, but in the presence of adsorbed oxygen, there is a strong driving force for Mo to segregate to the surface, where it was found to be most stable on a vertex site. This suggests the formation of surface Mo‐oxide species, which is consistent with our XPS measurements. Our calculations indicate that the formation of surface Mo-oxide species may contribute to improved stability by “crowding out” surface Ni. Our computational prediction that Mo favors sites near the particle edges and vertices is consistent with the dopant distributions for Fe shown in our STEM electron energy loss spectroscopy (EELS) line scan results (fig. S12). \n\nOur calculations suggest that doping the NCs with Mo directly stabilizes both Ni and Pt atoms against dissolution and may inhibit diffusion through the formation of relatively strong Mo‐Pt and Mo‐Ni bonds. Calculations on a representative nanoparticle with dimensions and composition comparable with those observed experimentally (fig. S13) indicate that a Mo on an edge or vertex site increases the energy required to remove a Pt atom from a neighboring edge or vertex site by an average of $362\\mathrm{meV}$ , with values ranging from 346 to $444\\mathrm{meV}$ , and to remove a Ni atom by an average of $201~\\mathrm{meV}$ , with values ranging from 160 to $214{\\mathrm{meV}}$ . These predictions are consistent with our ADT results (fig. S14). The evidence that Mo may have a stabilizing effect on undercoordinated sites suggests that Mo atoms may also pin step edges on the surface, inhibiting the dissolution process. \n\n![](images/3a0d11cccc1703dc92abead8864b105aceb64c76c29b0c782b48f6dbfcd5fa24.jpg) \nFig. 4. Computational results. (A and B) The average site occupancies of the second layer of (A) the Ni1175Pt3398 NC and (B) the $\\mathsf{M o}_{73}\\mathsf{N i}_{1143}\\mathsf{P t}_{3357}\\mathsf{N}($ C at $170^{\\circ}\\mathrm{C}$ as determined by means of a Monte Carlo simulation. Occupancies are indicated by the color triangle on the right. Small spheres represent the atoms in the outer layer. (C) The calculated binding energies for a single oxygen atom on all fcc and hcp sites on the (111) facet of the $\\mathsf{M o}_{6}\\mathsf{N i}_{41}\\mathsf{P t}_{178}$ NC, relative to the lowest binding energy. Gray spheres represent Pt, and colored spheres represent oxygen sites. Three binding energies are provided for reference: the calculated binding energy on the fcc site of a pure Pt (111) surface, the binding energy corresponding to the peak of the Sabatier volcano $(37)$ , and the binding energy on a Pt3Ni(111) surface. (D) The change in binding energies when a $\\mathsf{N i}_{47}\\mathsf{P t}_{178}\\mathsf{N C}$ is transformed to a $\\mathsf{M o}_{6}\\mathsf{N i}_{41}\\mathsf{P t}_{178}$ NC by the substitution of Mo on its energetically favored sites in the second layer below the vertices. \n\nAlthough the exact mechanisms by which the surface-doped $\\mathrm{Pt_{3}N i}$ shows exceptional catalytic performance demand more detailed studies, local changes in oxygen binding energies provide a possible explanation for some of the observed increase in specific activity. A Sabatier volcano of ORR catalysts predicts that ORR activity will be maximized when the oxygen binding energy is ${\\sim}0.2\\ \\mathrm{eV}$ less than the binding energy on $\\mathrm{Pt}(\\mathrm{111})$ (37). Our calculations indicate that sites near the particle edge bind oxygenated species too strongly, such as in $\\mathrm{Pt}(\\mathrm{111})$ , and sites near the facets of the particles bind oxygenated species too weakly, such as in $\\mathrm{Pt_{3}N i(111)}$ (Fig. 4C). However, compared with the undoped NC, the oxygen binding energies in the doped NC near the Mo atoms are decreased by up to $154~\\mathrm{meV};$ , and binding energies at sites closer to the center of the (111) facet are increased by up to 102 meV (Fig. 4D). Thus, if Mo migrates to the thermodynamically favored sites near the particle edges, it may shift the oxygen binding energies at these sites closer to the peak of the volcano plot. Similarly, Mo doping may increase the oxygen binding energies at sites closer to the center of the (111) facet that bind oxygen too weakly. As a result of these shifts, some sites may become highly active for catalysis. Together, our studies demonstrate that by engineering the surface structure of the octahedral $\\mathrm{Pt_{3}N i}$ nanocrystal, it is possible to fine-tune the chemical and electronic properties of the surface layer and hence modulate its catalytic activity. \n\n# REFERENCES AND NOTES \n\n1. Y. Bing, H. Liu, L. Zhang, D. Ghosh, J. Zhang, Chem. Soc. Rev. 39, 2184–2202 (2010). \n2. D. S. Su, G. Sun, Angew. Chem. Int. Ed. Engl. 50, 11570–11572 (2011). \n3. Z. W. Chen, D. Higgins, A. P. Yu, L. Zhang, J. J. Zhang, Energy Environ. Sci. 4, 3167–3192 (2011). \n4. J. Y. Chen, B. Lim, E. P. Lee, Y. N. Xia, Nano Today 4, 81–95 (2009). \n5. J. Wu, H. Yang, Acc. Chem. Res. 46, 1848–1857 (2013). \n6. N. S. Porter, H. Wu, Z. Quan, J. Fang, Acc. Chem. Res. 46, 1867–1877 (2013). \n7. H. A. Gasteiger, S. S. Kocha, B. Sompalli, F. T. Wagner, Appl. Catal. B 56, 9–35 (2005). \n8. F. A. de Bruijn, V. A. T. Dam, G. J. M. Janssen, Fuel Cells 8, 3–22 (2008). \n9. J. Greeley et al., Nat. Chem. 1, 552–556 (2009). \n10. H. A. Gasteiger, N. M. Marković, Science 324, 48–49 (2009). \n11. J. K. Nørskov, T. Bligaard, J. Rossmeisl, C. H. Christensen, Nat. Chem. 1, 37–46 (2009). \n12. V. R. Stamenkovic et al., Nat. Mater. 6, 241–247 (2007). \n13. V. R. Stamenkovic et al., Science 315, 493–497 (2007). \n14. A. S. Aricò, P. Bruce, B. Scrosati, J. M. Tarascon, W. van Schalkwijk, Nat. Mater. 4, 366–377 (2005). \n15. S. Guo, S. Zhang, S. Sun, Angew. Chem. Int. Ed. Engl. 52, 8526–8544 (2013). \n16. J. Wu, A. Gross, H. Yang, Nano Lett. 11, 798–802 (2011). \n17. J. Zhang, J. Fang, J. Am. Chem. Soc. 131, 18543–18547 (2009). \n18. Y. Kang, C. B. Murray, J. Am. Chem. Soc. 132, 7568–7569 (2010). \n19. Y. Wu, S. Cai, D. Wang, W. He, Y. Li, J. Am. Chem. Soc. 134, 8975–8981 (2012). \n20. D. Wang et al., Nat. Mater. 12, 81–87 (2013). \n21. S. I. Choi et al., Nano Lett. 13, 3420–3425 (2013). \n22. J. Zhang, H. Yang, J. Fang, S. Zou, Nano Lett. 10, 638–644 (2010). \n23. X. Huang et al., Adv. Mater. 25, 2974–2979 (2013). \n24. C. Cui, L. Gan, M. Heggen, S. Rudi, P. Strasser, Nat. Mater. 12, 765–771 (2013). \n25. M. K. Carpenter, T. E. Moylan, R. S. Kukreja, M. H. Atwan, M. M. Tessema, J. Am. Chem. Soc. 134, 8535–8542 (2012). \n26. J. Snyder, I. McCue, K. Livi, J. Erlebacher, J. Am. Chem. Soc. 134, 8633–8645 (2012). \n27. H. Zhu, S. Zhang, S. Guo, D. Su, S. Sun, J. Am. Chem. Soc. 135, 7130–7133 (2013). \n28. C. Chen et al., Science 343, 1339–1343 (2014). \n29. K. Ahrenstorf et al., Small 3, 271–274 (2007). \n30. Y. Wu et al., Angew. Chem. Int. Ed. Engl. 51, 12524–12528 (2012). \n31. Z. Liu et al., J. Am. Chem. Soc. 131, 6924–6925 (2009). \n32. B. Lim et al., Science 324, 1302–1305 (2009). \n33. J. M. Sanchez, F. Ducastelle, D. Gratias, Physica A 128, 334–350 (1984). \n34. N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, E. Teller, J. Chem. Phys. 21, 1087–1092 (1953). \n35. T. Mueller, G. Ceder, Phys. Rev. B 80, 024103 (2009). \n36. W. Kohn, L. J. Sham, Phys. Rev. 140 (4A), A1133–A1138 (1965). \n37. J. Rossmeisl, G. S. Karlberg, T. Jaramillo, J. K. Nørskov, Faraday Discuss. 140, 337–346 (2009). \n38. K. Momma, F. Izumi, J. Appl. Cryst. 41, 653–658 (2008). \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge support from the National Science Foundation (NSF) through award DMR-1437263 on catalysis studies and the Office of Naval Research (ONR) under award N00014-15-1-2146 for synthesis efforts. Computational studies were supported by the NSF through award DMR-1352373 and using computationa resources provided by Extreme Science and Engineering Development Environment (XSEDE) through awards DMR130056 and DMR140068. Atomic-scale structural images were generated by using VESTA (38). We thank the Director, Office of Energy Research, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, of the U.S. Department of Energy under contract DE-AC02-05CH11231, under the $\\boldsymbol{s p^{2}}$ -bonded materials program, for TEM analytical measurements performed at the National Center for Electron Microscopy at the Lawrence Berkeley National Laboratory. X.D. acknowledges support from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Science and Engineering through award DE-SC0008055. The work at LLNL was performed under the auspices of the U.S. Department of Energy under contract DE-AC52-07NA27344. A.Y. and A.Z. received additional support from NSF grant EEC-083219 within the Center of Integrated Nanomechanical Systems. We also thank the Electron Imaging Center of Nanomachines at CNSI for TEM support. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/348/6240/1230/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S17 \nTables S1 to S2 \nReferences (39–53) \n\n# SOLAR CELLS \n\n# High-performance photovoltaic perovskite layers fabricated through intramolecular exchange \n\nWoon Seok Yang,1\\* Jun Hong Noh,1\\* Nam Joong Jeon,1 Young Chan Kim,1 Seungchan Ryu,1 Jangwon Seo,1 Sang Il Seok1,2† \n\nThe band gap of formamidinium lead iodide $(F A P b l_{3})$ perovskites allows broader absorption of the solar spectrum relative to conventional methylammonium lead iodide $(M A P b\\mathsf{I}_{3})$ . Because the optoelectronic properties of perovskite films are closely related to film quality, deposition of dense and uniform films is crucial for fabricating high-performance perovskite solar cells (PSCs). We report an approach for depositing high-quality $\\mathsf{F A P b l}_{3}$ films, involving $\\mathsf{F A P b l}_{3}$ crystallization by the direct intramolecular exchange of dimethylsulfoxide (DMSO) molecules intercalated in $\\mathsf{P b l}_{2}$ with formamidinium iodide. This process produces $\\mathsf{F A P b l}_{3}$ films with (111)-preferred crystallographic orientation, large-grained dense microstructures, and flat surfaces without residual $\\mathsf{P b l}_{2}$ . Using films prepared by this technique, we fabricated $\\mathsf{F A P b l}_{3}$ -based PSCs with maximum power conversion efficiency greater than $20\\%$ . \n\nT cheitreectmureen(d1o–u3s),ihmigphr-oqvueamlietyntfislimn fdoervmicaetiaorn- methodologies (4–6), and compositional engineering of perovskite materials (7–9) over the past 3 years have led to rapid improvements in the power conversion efficiency (PCE) of perovskite solar cells (PSCs). Although solarto-electric PCEs of up to $18\\%$ have been reported for PSCs (10), developing technologies further to achieve PCEs near theoretical values $(>30\\%)$ ) continues to be an important challenge in making the solar cell industry economically competitive. \n\nFormamidinium lead iodide $\\mathrm{(FAPbI_{3})}$ is a perovskite material that can potentially provide better performance than methylammonium lead iodide $\\mathrm{(MAPbI_{3})}$ ) because of its broad absorption of the solar spectrum. In addition, $\\mathrm{FAPbI_{3}}$ with the n-i-p architecture (the n-side is illuminated with solar radiation) exhibits negligible hysteresis with sweep direction during current-voltage measurements (8–13). However, it is more difficult to form stable perovskite phases and highquality films with $\\mathrm{FAPbI_{3}}$ than with $\\mathbf{MAPbI_{3}}$ . \n\nVarious methodologies such as sequential deposition $\\left(4\\right)$ , solvent engineering (5), vapor-assisted deposition $(I4),$ additive-assisted deposition $(I5,I6),$ , and vacuum evaporation $\\textcircled{6}$ can now produce high-quality films of $\\mathbf{MAPbI_{3}}$ with flat surfaces and complete surface coverage by controlling its rapid crystallization behavior and have led to substantial improvements in the PCE of $\\mathbf{MAPbI_{3}}$ - based PSCs. \n\nAmong these methodologies, two-step sequential deposition and solvent engineering are representative wet processes that can yield perovskite films for high-performance PSCs. In the sequential deposition process, a thin layer of $\\mathrm{PbI_{2}}$ is deposited on the substrate; methylammonium iodide (MAI) or formamidinium iodide (FAI) is then applied to the predeposited $\\mathrm{PbI_{2}}$ to enable conversion to the perovskite phase. This process involves crystal nucleation and growth of the perovskite phase because of solution-phase or solidstate reaction between $\\mathrm{PbI_{2}}$ and an organic iodide such as MAI or FAI (4, 13, 17, 18). However, the sequential reaction of organic iodides with $\\mathrm{PbI_{2}}$ that occurs from the surface to the inner crystalline regions of $\\mathrm{PbI_{2}}$ has been ineffective in producing high-performance perovskite films that are ${>}500\\ \\mathrm{nm}$ in thickness because of incomplete conversion of $\\mathrm{PbI_{2}},$ peeling off of the perovskite film in solution, and uncontrolled surface roughness. In contrast, the solvent-engineering process uses the formation of intermediate phases to \n\nTable 1. Comparison of layer thickness before and after $\\mathsf{F A P b l}_{3}$ phase is formed by conventional and intramolecular exchange process (IEP). The thin $\\mathsf{P b l}_{2}$ and $\\mathsf{P b l}_{2}(\\mathsf{D M S O})$ layers were deposited on a fused quartz glass, and their layer thickness was measured by alpha-step IQ surface profiler. \n\n\n
MethodBeforeAfter
Conventional process (Pbl2)290 nm570 nm
IEP [Pbl2(DMSO)]510 nm560 nm
\n\nHigh-performance transition metal−doped $\\mathsf{P t}_{3}\\mathsf{N i}$ octahedra for oxygen reduction reaction \nXiaoqing Huang et al. \nScience 348, 1230 (2015); \nDOI: 10.1126/science.aaa8765 \n\nThis copy is for your personal, non-commercial use only. \n\nIf you wish to distribute this article to others, you can order high-quality copies for your colleagues, clients, or customers by clicking here. \n\nPermission to republish or repurpose articles or portions of articles can be obtained by following the guidelines here. \n\nThe following resources related to this article are available online at www.sciencemag.org (this information is current as of June 11, 2015 ): \n\nUpdated information and services, including high-resolution figures, can be found in the online \nversion of this article at: \nhttp://www.sciencemag.org/content/348/6240/1230.full.html \n\nSupporting Online Material can be found at: http://www.sciencemag.org/content/suppl/2015/06/10/348.6240.1230.DC1.html \n\nThis article cites 52 articles, 4 of which can be accessed free: http://www.sciencemag.org/content/348/6240/1230.full.html#ref-list-1 " + }, + { + "id": "10.1021_jacs.5b00281", + "DOI": "10.1021/jacs.5b00281", + "DOI Link": "http://dx.doi.org/10.1021/jacs.5b00281", + "Relative Dir Path": "mds/10.1021_jacs.5b00281", + "Article Title": "Cobalt-Iron (Oxy)hydroxide Oxygen Evolution Electrocatalysts: The Role of Structure and Composition on Activity, Stability, and Mechanism", + "Authors": "Burke, MS; Kast, MG; Trotochaud, L; Smith, AM; Boettcher, SW", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Cobalt oxides and (oxy)hydroxides have been widely studied as electrocatalysts for the oxygen evolution reaction (OER). For related Ni-based materials, the addition of Fe dramatically enhances OER activity. The role of Fe in Co-based materials is not well-documented. We show that the intrinsic OER activity of Co1-xFex(OOH) is similar to 100-fold higher for x approximate to 0.6-0.7 than for x = 0 on a per-metal turnover frequency basis. Fe-free CoOOH absorbs Fe from electrolyte impurities if the electrolyte is not rigorously purified. Fe incorporation and increased activity correlate with an anodic shift in the nominally Co2+/3+ redox wave, indicating strong electronic interactions between the two elements and likely substitutional doping of Fe for Co. In situ electrical measurements show that Co1-xFex(OOH) is conductive under OER conditions (similar to 0.7-4 mS cm(-1) at similar to 300 mV overpotential), but that FeOOH is an insulator with measurable conductivity (2.2 x 10(-2) mS cm(-1)) only at high overpotentials >400 mV. The apparent OER activity of FeOOH is thus limited by low conductivity. Microbalance measurements show that films with x >= 0.54 (i.e., Fe-rich) dissolve in 1 M KOH electrolyte under OER conditions. For x < 0.54, the films appear chemically stable, but the OER activity decreases by 16-62% over 2 h, likely due to conversion into denser, oxide-like phases. We thus hypothesize that Fe is the most-active site in the catalyst, while CoOOH primarily provides a conductive, high-surface area, chemically stabilizing host. These results are important as Fe-containing Co- and Ni-(oxy)hydroxides are the fastest OER catalysts known.", + "Times Cited, WoS Core": 1655, + "Times Cited, All Databases": 1743, + "Publication Year": 2015, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000351420800034", + "Markdown": "# Cobalt−Iron (Oxy)hydroxide Oxygen Evolution Electrocatalysts: The Role of Structure and Composition on Activity, Stability, and Mechanism \n\nMichaela S. Burke,† Matthew G. Kast,†,‡ Lena Trotochaud,† Adam M. Smith,† and Shannon W. Boettcher\\*,†,‡ \n\n†Department of Chemistry and Biochemistry and ‡Center for Sustainable Materials Chemistry, University of Oregon Eugene, Oregon 97403, United States \n\nSupporting Information \n\nABSTRACT: Cobalt oxides and (oxy)hydroxides have been widely studied as electrocatalysts for the oxygen evolution reaction (OER). For related Ni-based materials, the addition of Fe dramatically enhances OER activity. The role of Fe in Co-based materials is not well-documented. We show that the intrinsic OER activity of $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OOH)}$ is ${\\sim}100$ -fold higher for $x\\approx0.6\\mathrm{-}0.7$ than for $x=0$ on a per-metal turnover frequency basis. Fe-free $\\mathrm{CoOOH}$ absorbs Fe from electrolyte impurities if the electrolyte is not rigorously purified. Fe incorporation and increased activity correlate with an anodic shift in the nominally $\\mathbf{Co}^{2+/3+}$ redox wave, indicating strong electronic interactions between the two elements and likely substitutional doping of Fe for Co. In situ electrical measurements show that $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})$ is conductive under OER conditions $(\\sim0.7–4$ $\\mathrm{m}S\\mathrm{cm}^{-1}$ at ${\\sim}300\\mathrm{mV}$ overpotential), but that FeOOH is an insulator with measurable conductivity $(\\hat{2.2}\\times10^{-2}\\mathrm{mS}\\mathrm{cm}^{-1})$ only at high overpotentials ${>}400~\\mathrm{mV}.$ . The apparent OER activity of FeOOH is thus limited by low conductivity. Microbalance measurements show that films with $x\\ge0.54$ (i.e., Fe-rich) dissolve in 1 M KOH electrolyte under OER conditions. For $x<0.54.$ , the films appear chemically stable, but the OER activity decreases by $16\\mathrm{-}62\\%$ over $^{2\\mathrm{h},}$ likely due to conversion into denser, oxide-like phases. We thus hypothesize that Fe is the most-active site in the catalyst, while CoOOH primarily provides a conductive, high-surface area, chemically stabilizing host. These results are important as Fe-containing $\\mathrm{Co-}$ and Ni-(oxy)hydroxides are the fastest OER catalysts known. \n\n![](images/1197014d5039bebcc27eb7ec3b31ae6530c0e798cf0a6c13b8c3c5a85c0ee6c6.jpg) \n\n# 1. INTRODUCTION \n\nWater splitting by direct or photodriven electrolysis $\\mathrm{\\Omega}2\\mathrm{H}_{2}\\mathrm{O}\\rightarrow$ $\\mathrm{O}_{2}\\ +\\ 2\\mathrm{H}_{2})$ provides a potential path for the production of clean, renewable $\\mathrm{H}_{2}$ fuel to power human civilization.1−5 The efficiency of water electrolysis is limited, in part, by the high kinetic overpotential associated with driving the oxygen evolution reaction (OER). $^{3,6-12}$ In addition to facilitating fast kinetics (i.e., low overpotential), ideal OER catalysts are composed of nontoxic earth-abundant elements, economical to manufacture, chemically and mechanically stable, and sufficiently electrically conductive to facilitate integration with water-splitting (photo)anodes.13−17 \n\nAlthough water electrolysis can, in principle, be performed in conductive electrolytes of any $\\mathrm{\\tt{pH}},$ , alkaline conditions are perhaps best suited to meet the above requirements. In neutral electrolytes, the slow transport of buffer ions and the formation of a $\\mathrm{\\tt{pH}}$ gradient (particularly when membranes to separate $\\mathrm{H}_{2}$ from $\\mathrm{O}_{2}$ are used) increase the cell resistance and lower efficiency. 2,18 Membranes with high $\\mathbf{H}^{+}$ mobility (e.g., Nafion)19 are used for commercial water electrolyzers in acidic conditions.20,21 Unfortunately, the scarce and expensive $\\mathrm{IrO}_{2}$ - based catalysts used are the only known acid-insoluble OER catalysts with reasonable activity.17,22 \n\nIn contrast, many inexpensive, earth-abundant, first-row transition metals are OER active and largely insoluble in alkaline electrolytes.3,13,14,16,17,23,24 Independent of synthetic method, transition metals and their oxides often form (oxy)hydroxides at their surfaces in alkaline solutions during OER. These surface structures are different than those of the bulk crystalline oxide phases.3,25−27 Such structural transformations under catalytically relevant conditions make mechanistic studies at these surfaces challenging. \n\nCo-based OER catalysts, e.g. $\\mathrm{Co-P_{i}}$ (electrodeposited ${\\mathrm{CoO}}_{x}$ films in a phosphate electrolyte),28 have been of recent interest due to reasonable activity and catalyst “self-repair” in neutral electrolyte.29 Substantial work has aimed to understand the relation between structure, mechanism, and activity. $^{30-37}\\mathrm{Co-}$ $\\mathrm{{P_{i}}}$ and related catalysts are composed of small fragments/layers of CoOOH during $\\mathrm{OER},$ independent of initial deposition conditions or the electrolyte used.27,38−41 Klingan et al. showed that the “bulk” material is active for catalysis because it consists of a mixture of electrolyte-accessible CoOOH nanosheets, counterions, and electrolyte.39 Risch et al. complemented this analysis using X-ray absorption spectroscopy to follow the Co oxidation state and local structure during the OER.42 \n\nMixed-metal systems containing both Co and Fe have also been studied in basic media. There are conflicting reports as to whether the addition of Fe into ${\\mathrm{CoO}}_{x}$ increases OER activity, due to the difficultly in quantifying the number of active sites, the surface/local structures under which OER occurs, and the catalyst stability as a function of Fe content. Several studies show that the addition of Fe to polycrystalline $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ decreased the Tafel slope.43−46 Kishi et al. concluded that the addition of Fe in $\\mathrm{Fe}_{x}\\mathrm{Co}_{3-x}\\mathrm{O}_{4}$ $\\left(0\\leq x\\leq2\\right)$ decreased OER actvitiy.47 Smith et al. report little difference in Tafel slope between photochemically deposited porous/amorphous $\\mathrm{CoO}_{x},\\mathrm{FeO}_{x},$ and $\\mathrm{FeCoO}_{x}^{4\\dot{8}}$ (likely a mix of oxides and (oxy)hydroxides). In a later study, they showed that the $\\mathrm{FeCoO}_{x}$ and ${\\mathrm{CoO}}_{x}$ films have the same overpotential $\\left(0.27\\pm0.02\\mathrm{\\V}\\right)$ at $1\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ anodic current density.49 McCrory et al. benchmarked different OER catalysts and found that the overpotential at $10~\\mathrm{\\mA}~\\mathrm{cm}^{-2}$ (geometric surface area) for ${\\mathrm{CoO}}_{x}$ and $\\mathrm{CoFeO}_{x}$ was statistically indistinguishable $\\mathit{\\check{(0.39~\\pm~0.04~}}$ and $\\begin{array}{c c c c}{0.37}&{\\pm}&{0.02}&{\\mathrm{~V~}}\\end{array}$ , respectively).17 At lower overpotentials $(350~\\mathrm{\\mV})$ , however, McCrory et al. note that $\\mathrm{CoFeO}_{x}$ has ${\\sim}7$ -fold higher current density than $\\mathrm{CoO}_{x}$ . Suntivich et al. reported high activity from a $\\mathrm{Ba}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{Co}_{0.8}\\mathrm{Fe}_{0.2}\\mathrm{O}_{x}$ perovskite catalyst optimized based on molecular orbital principles.50 Further work from the same group showed that $\\mathbf{\\hat{B}}\\mathbf{a}^{2+}$ and $\\mathrm{Sr}^{2+}$ leached at the surface, leaving behind amorphous $\\scriptstyle\\mathrm{Fe-Co}$ phases, likely (oxy)hydroxides, which were responsible for the measured OER activity.51 \n\nFe is known to have a dramatic effect on the OER activity of Ni-based materials by substituting for Ni in NiOOH.52,53 This is intriguing as alone, NiOOH is a very poor OER catalyst,53 while $\\mathrm{FeO}_{x}$ is also traditionally considered to have low OER activity.54 Evidence from our group53 and others $^{52,55-57}$ shows that Fe affects the local electronic structure of the NiOOH, suggesting the possibility that Fe (or Ni substantially modified by the presence of Fe) is the active site. Unaccounted for Fe impurities have also complicated attempts to elucidate the OER mechanism on Ni-based materials. An improved understanding of the role that Fe (and other) additives/impurities play in OER catalysis is thus important for implementing new approaches to enhance catalytic activity. Given the volume of work on ${\\mathrm{CoO}}_{x}$ electrocatalysis and the record-high OER activity of the related $\\mathrm{{Ni}(F e)O O H}$ materials, it is particularly important to clarify the role of Fe in OER on $_\\mathrm{Co(Fe)OOH}$ . \n\nHere, we probe the role of structure and composition in $\\mathbf{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})$ films electrodeposited on quartz-crystal microbalance (QCM) electrodes in alkaline media. We follow the activity, voltammetry, stability, conductivity, morphology, and chemical changes that occur during OER catalysis. We use total film mass to calculate approximations of intrinsic activity for the different possible active cations. We discover that Fe incorporation increases the intrinsic activity of CoOOH by ${\\sim}100$ -fold, with peak activity for $40{-}60\\%$ Fe. Based on in situ mass measurements, we find that Fe also affects chemical and structural stability. $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})$ films with $x>0.54$ slowly dissolve under anodic polarization, while those with lower $x$ appear insoluble. In situ measurements of electrocatalyst film conductivity show that while $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OOH)}\\ \\mathrm{~(}x\\ \\stackrel{\\cdot}{>}\\ 1\\mathrm{)}$ is conductive under OER conditions, FeOOH only has measurable conductivity at overpotentials ${>}400~\\mathrm{~mV}$ . The intrinsic activity of FeOOH at low overpotentials is thus masked by high electrical resistance. This may indicate that the CoOOH (and similarly NiOOH) serves primarily as electrically conductive and chemically stable host that enhances the activity of Fe-based active sites in the most-active mixed-cation phases. These results thus shed light onto the role of Fe in high-activity $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})$ OER catalysts and provide further basis for the rational development of new catalysts with improved activity. \n\n# 2. EXPERIMENTAL SECTION \n\n2.1. Solution Preparation. A stock solution of $0.1\\mathrm{~M~Co}(\\mathrm{NO}_{3})_{2}$ · $\\mathsf{\\Pi}^{6\\mathrm{H}_{2}\\mathrm{O}}$ (Strem Chemicals, $99.999\\%$ trace metal basis) was prepared in 18.2 MΩ·cm water. Individual solutions of mixed $\\mathrm{Co}\\big(\\mathrm{NO}_{3}\\big)_{2}$ and $\\mathrm{FeCl}_{2}$ (total $0.1\\mathrm{~M~}$ metal ion concentration) for $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OH)}_{2}$ films of $x>0$ and $0.1\\mathrm{~M~FeCl}_{2}$ (Sigma-Aldrich, $>98\\%$ ) and $0.05\\mathrm{M}\\mathrm{NaNO}_{3}$ (Mallinckrodt Chemicals, $>98\\%$ ) for $x=1$ were freshly prepared in $18.2~\\mathrm{M}\\Omega\\cdot\\mathrm{cm}$ water for each deposition session ( $<10$ film depositions per session). The $\\mathrm{FeCl}_{2}$ solutions are air sensitive and form FeOOH precipitates in the presence of oxygen.53 All solutions containing $\\mathrm{FeCl}_{2}$ were covered in Parafilm and purged with ${\\bf N}_{2}$ for ${\\sim}20$ min prior to $\\mathrm{FeCl}_{2}$ addition and between depositions. ${\\mathrm{NaNO}}_{3}$ was added to $\\mathrm{FeCl}_{2}$ solutions to facilitate the cathodic deposition via reduction of NO3−.53,58 \n\n2.2. Film Electrodeposition. $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OH)}_{2}$ was cathodically deposited onto $\\mathbf{Au}/\\mathrm{Ti}$ -coated 5 MHz QCM crystals (Stanford Research Systems QCM200) using a two-electrode cell with a carbon-cloth counter electrode (Fuel Cell Earth, untreated).53 Deposition was accomplished by applying between $-0.1$ and $-4.0$ mA $\\mathrm{cm}^{-2}$ (cathodic) until the desired mass was registered on the $\\mathrm{QCM.}^{52,58-\\dot{6}0}$ Deposition rates vary for optimal substrate coverage and are indicated in Table S1. The film masses $\\left(\\sim10~\\mu\\mathrm{g}\\ c m^{-2}\\right)$ ) were calculated based on the Sauerbrey equation $\\left(\\Delta f=-C_{f}\\times\\Delta m,\\right.$ where $\\Delta f$ is the experimental frequency change, $C_{f}$ is the sensitivity factor, $6\\dot{4}.5\\ \\mathrm{Hz\\cm^{2}}^{*}\\mu\\mathrm{g^{-1}}.$ , of the 5 MHz AT-cut quartz crystal in solution, and $\\Delta m$ is the change in mass per area, see Figure S1 and corresponding example mass calculations).16,61 Mass is lost during the first cycle, which we attribute to residual ion (e.g., nitrate, chloride) loss to the solution (Figure S2). The film mass was thus determined from the difference between the measured QCM resonance frequency in 18 ${\\bf{M}}{\\bf{\\Omega}}^{}.{\\bf{c m}}$ water prior to deposition and that after the first voltammetry cycle (Figure S1 and supporting calculations). Prior to deposition, all QCM crystals were cleaned in 1 M $\\mathrm{H}_{2}S\\mathrm{O}_{4}$ (Sigma-Aldrich) via potential cycling (2 cycles, 2.5 to $-2.5\\mathrm{~V~}$ at $200~\\mathrm{mV~s^{-1}}$ ). The $\\mathrm{{Au/Ti}}$ QCM crystals were then cycled in 1 M KOH to check for the appropriate Au redox features and confirm the absence of any redox features or OER current associated with residual impurities or Co from previous measurements (see Figure S3), rinsed in $18.2~\\mathrm{M}\\Omega\\cdot\\mathrm{cm}$ water, and transferred to the deposition solution. It was also found that Co (and Fe) from the deposition solution readily adsorbed to the Teflon QCM holder and would contaminate the electrolyte when transferred to the electrochemical testing cell, resulting in inconsistent experimental results. To prevent this, the QCM holder was quickly removed after deposition from the acidic deposition solution (which slowly dissolves the film) and submerged into three consecutive 18.2 $\\mathbf{M}\\Omega\\cdot\\mathbf{cm}$ water baths to rinse off excess deposition solution. The crystal was then transferred to a second, acid-cleaned Teflon QCM holder for use in the electrochemical testing cell. Films characterized ex situ prior to further electrochemical measurements are referred to as “asdeposited” samples (Table S1). \n\n2.3. Electrochemical Characterization. Measurements were made with a potentiostat (BioLogic SP300 or SP200) using a three electrode (voltammetry and steady-state studies) or four electrode (through-film conductivity studies) cell with a coiled $\\mathrm{Pt}$ -wire counter electrode contained in a plastic fritted compartment and a $\\mathrm{Hg/HgO}$ reference electrode (CH Instruments) filled with 1 M KOH. For activity measurements the electrolyte was saturated with ultrahigh purity $\\mathrm{O}_{2}$ (sparged ${\\sim}20~\\mathrm{min}$ prior to the experiment and continuously bubbled during the data collection). Magnetic stirring was used to eliminate bubble accumulation. Through-film conductivity measurements were made using ${\\bf A u}/\\mathrm{Ti}/$ quartz interdigitated array (IDA) electrodes (CH instruments, $2\\ \\mu\\mathrm{m}$ electrode width, $2\\ \\mu\\mathrm{m}$ gap, $2~\\mathrm{mm}$ length, 65 pairs). The conductivity was extracted from the steady-state current between the two working electrodes with a $10\\ \\mathrm{mV}$ offset during which the potential of both were stepped between 0 and $0.65\\mathrm{V}$ $(2-5\\mathrm{\\min}$ per step). The conductivity of the FeOOH was not sufficient to measure in this way due to low effective conductivity at low overpotentials and the interference from the comparatively large OER current at high overpotentials. Alternatively, we first poised both working electrodes at the same potential until a steady-state OER current was reached. We then stepped the potential of the first electrode by $10~\\mathrm{mV},$ causing a significant change in OER current on that electrode. The change in current on the second electrode was assumed to be only due to electrical transport through the FeOOH from one working electrode to the other, because the potential of the second electrode was not changed. We confirmed this by measuring a number of different positive and negative potential step combinations (see Figure S4 for details). This method allows for measurement of the small conductance current on top of the large OER background current. \n\nAll electrochemical measurements were made in polytetrafluoroethylene (PTFE) or Nalgene containers. No glass components were used as they are etched in 1 M KOH and contaminate the electrolyte with Fe and other impurities. All plastic components were cleaned with 1 M $\\mathrm{H}_{2}S\\mathrm{O}_{4}$ prior to use. Pt counter electrodes were regularly cleaned by dipping briefly $(\\sim5~\\mathrm{~s~})$ in aqua regia. The $\\mathrm{Hg/HgO}$ reference electrode was calibrated against a reversible hydrogen electrode (RHE) at $\\mathrm{pH}14$ ( $0.93{\\mathrm{~V~}}$ vs RHE), fabricated by bubbling $\\mathrm{H}_{2}(\\mathbf{g})$ over a freshly cleaned Pt electrode. When indicated, measurements were corrected for uncompensated series resistance $\\left(R_{\\mathrm{u}}\\right)$ . $R_{\\mathrm{u}}$ was determined by equating $R_{\\mathrm{u}}$ to the minimum impedance between $10\\ \\mathrm{kHz}$ and $^{1}\\mathrm{\\:MHz},$ where the phase angle was closest to zero. $R_{\\mathrm{u}}$ was between 2 and $6~\\Omega$ for QCM electrodes. Current densities were calculated using the geometric surface area of the QCM crystal $\\left(1.38\\ \\mathrm{cm}^{2}\\right)$ . The overpotential $(\\eta)$ was calculated where $\\eta=$ $E_{\\mathrm{measured}}-E_{\\mathrm{rev}}-i R_{\\mathrm{u}}.\\ E_{\\mathrm{measured}}$ is the recorded potential vs $\\mathrm{Hg/HgO}$ and $E_{\\mathrm{rev}}$ is the reversible potential ( $\\mathrm{\\Delta}0.30\\mathrm{\\DeltaV}$ vs $\\mathrm{Hg/HgO)}$ for the OER.1 All three-electrode steady-state potentiostatic experiments were corrected for $i R_{\\mathrm{u}}$ in real time using a manual $i R$ compensation based on the full value of $R_{\\mathrm{u}}$ derived from the impedance measurements. \n\n2.4. Purification of KOH Electrolyte. As-received KOH (Sigma TraceSelect or Semiconductor grade), diluted to $^{1\\mathrm{~M~}}$ , was used for all measurements made on films already containing Fe because these films did not absorb a discernible amount of Fe from solution. Electrochemical measurements performed on Fe-free samples used purified 1 M KOH, unless the film was being tested for Fe accumulation in the as-received electrolyte. The 1 M KOH was purified as follows. ${\\mathrm{Co}}({\\mathrm{OH}})_{2}$ was precipitated from $\\mathrm{Co}\\big(\\mathrm{NO}_{3}\\big)_{2}$ $(0.5-1~\\mathrm{g},\\ 99.999\\%)$ with ${\\sim}0.1$ M KOH and washed three times via mechanical agitation, centrifugation, and decanting. The triple-washed ${\\mathrm{Co}}{\\left(\\mathrm{OH}\\right)}_{2}$ was then added to the $^{1\\mathrm{~M~}}$ KOH electrolyte and mechanically agitated for 10 min to absorb Fe impurities (the affinity for Fe by $\\mathrm{Co}(\\mathrm{OH})_{2}$ is demonstrated below). The resultant brown suspension was centrifuged for $^{\\mathrm{~1~h,~}}$ and the Fe-free electrolyte decanted into a clean PTFE electrochemical test cell for use. This procedure is analogous to the KOH cleaning procedure developed using $\\mathrm{Ni}(\\mathrm{OH})_{2},^{53}$ however, it eliminates the possibility of Ni contamination by using ${\\mathrm{Co}}{\\left(\\mathrm{OH}\\right)}_{2}$ . \n\n2.5. Materials Characterization. Scanning electron microscope (SEM) images were taken using a Zeiss Ultra 55 SEM operating at 5 $\\mathbf{keV}.$ . Compositional information (Fe/Co ratio) was determined by Xray photoelectron spectroscopy (XPS) with an ESCALAB 250 (ThermoScientific) using a $\\mathbf{Mg}\\ \\mathrm{K}\\alpha$ nonmonochromated flood source (400 W, $75~\\mathrm{eV}$ pass energy). An Al $\\mathrm{K}\\alpha$ monochromated source (150 W, $20~\\mathrm{eV}$ pass energy, $500\\mu\\mathrm{m}$ spot size) was used to collect oxidation state information. All samples were charge neutralized using an in-lens electron source and grounded to the stage with a conductive clip to minimize charging. The resulting spectra were analyzed with a Shirley background, calibrated using the substrate Au 4f peaks $(84.0\\ \\mathrm{eV})$ , and peak fit using ThermoScientific Avantage 4.75 software. The $\\mathbf{Mg}\\ \\mathrm{K}\\alpha$ source was used for determining the $\\mathrm{Fe/Co}$ ratio because the Al $\\mathrm{K}\\alpha$ source yields large Co or Fe Auger (LMM Co at $713\\mathrm{eV}$ and Fe at 784 $\\mathrm{eV})^{62}$ peaks that overshadow smaller Fe 2p or Co 2p peaks, respectively. Grazing incidence X-ray diffraction (GIXRD) patterns were taken on thick films using a Rigaku SmartLab diffractometer ( $0.4^{\\circ}$ incident angle, $0.1^{\\circ}$ step size, and $120\\ s$ per step integration time) with parallel beam optics, diffracted-beam monochromator (to remove Fe fluorescence), knife edge, and $\\operatorname{K}\\mathcal{\\beta}$ filter. Thick films for GIXRD of $x=0.$ , 0.54, and 1.0 were deposited for 15, 10, and $20~\\mathrm{min},$ respectively, onto $\\mathrm{{Au/Ti}}$ /glass slides at a specified current density $(-2,$ $^{-4,}$ and $-\\mathrm{\\dot{1}}\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ , respectively). All glass components in premade electrodes were covered with hot glue to eliminate Fe contamination we found from Hysol 1C epoxy that is typically used in our laboratory. \n\n# 3. RESULTS AND DISCUSSION \n\n3.1. Film Preparation and Structural Characterization. The study of OER electrocatalysts has been hampered by difficulties in accurately identifying the catalytically active phases. When oxides prepared at high-temperature are used as OER catalysts in base, a surface layer that is the active catalyst usually forms that is composed of (oxy)hydroxides, as predicted by equilibrium Pourbaix diagrams63 and as has been observed directly in several case s.16,51,64,65 Measurements of chemical structure and composition of this surface layer can be challenging, however, as the underlying bulk crystalline phase often dominates the signal for many analysis techniques. \n\nTo address this, we directly electrodeposited hydrated $\\scriptstyle\\mathbf{Co-}$ Fe (oxy)hydroxides at room temperature and studied them electrochemically without dehydration or heating. The deposition proceeds via the cathodic reduction of ${\\bar{\\bf N O}_{3}}^{-}$ at the electrode surface which increases the $\\mathsf{p H}$ to drive metal hydroxide precipitation at the electrode surface.58,66,67 Although the $\\mathrm{Fe/Co}$ ratio in solution was typically higher than that of the deposited material, films deposited from the same solutions had similar Fe content within $2\\%$ (Table S1). \n\nGIXRD patterns of as-deposited $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OH)}_{2}$ with $x=0,$ , 0.54, and 1.0 are plotted in Figure 1a. No reflections from the Au−Ti substrates are observed in the range shown (reference patterns can be found in Figure S5). The diffraction pattern for the $x=0$ sample (as deposited) has a broad peak centered at $d$ $=5.1$ Å corresponding roughly to the 001 reflection of $\\beta\\mathrm{.}$ - ${\\mathrm{Co}}{\\left(\\mathrm{OH}\\right)}_{2}$ . The sharp peak at $\\overset{\\cdot}{d}=4.2\\ \\overset{\\cdot}{\\mathrm{A}}$ and the collection of peaks at ${\\sim}2.7{-}2.6$ Å suggest also the presence of $\\alpha$ - $\\mathsf{\\bar{C}o}(\\mathrm{OH})_{2}$ .60 The broadness of the peak between $7.5\\mathrm{-}4.4\\mathrm{~\\AA~}$ suggests variation in the local $d$ -spacing associated with nonhomogeneous intercalation of water and/or ions in a somewhat disordered $\\alpha{\\mathrm{-}}{\\mathrm{Co}}({\\mathrm{OH}})_{2}$ material.60,68 The pattern for the $x=0.54$ sample has two distinct low-angle peaks ( $\\dot{\\boldsymbol{d}}=7.7$ and 4.2 Å) consistent with the (003) and (006) reflections from a Co−Fe fougèrite-analogue phase in which $\\mathrm{Fe}^{3+}$ substitutes for ${\\mathrm{Co}}^{2+}$ . The pattern for the $x=1$ sample (Fe-only) has a number of peaks that can be well-indexed to a mix of $\\alpha,\\beta,$ and γ FeOOH (Figure S5). \n\nSEM imaging shows that the as-deposited films consist of platelets roughly $100~\\mathrm{{nm}}$ in diameter that tend to be vertically oriented and randomly distributed on the electrode surface (Figure 1b, top row and Figure S6). This morphology is consistent with that typically observed for layered double hydroxides or oxyhydroxides adopting a brucite-like structure with octahedrally coordinated metal cations hexagonally packed in sheets that are separated by water and charge-balancing ions. $^{58,67-73}$ The morphology is not substantially altered by addition of Fe, suggesting a solid solution. The $\\mathrm{~O~}$ 1s XPS spectra of the film as-deposited from pure $\\mathrm{Co}(\\mathrm{NO}_{3})_{2}$ show a single peak in a region between ${\\sim}531.5{-}530.0~\\mathrm{eV} $ , indicating the O is in a hydroxide-like environment and thus a ${\\mathrm{Co}}{\\mathrm{(OH)}}_{2}^{\\mathrm{-}}$ local structure (Figure 1c; see Figure S7 for full range of films studied).69,74,75 Upon addition of Fe, the $\\mathrm{~O~}$ 1s spectra develop a shoulder at lower binding energy indicating O in a moreoxide-like environment (see arrow $\\dot{(\\boldsymbol{s})}$ in Figures 1c and S7), consistent with the presence of $\\mathrm{Fe}^{3+}$ and thus more oxide bridges in the mixed-metal (oxy)hydroxide. $\\mathrm{Fe}^{3+}$ is expected after exposure to oxygen in air. \n\n![](images/c71eabfa956057938c194645e43b196eb5b51f558aecae5a412eca7c2c298775.jpg) \nFigure 1. Materials characterization of electrodeposited $\\mathrm{Co_{1-x}F e_{x}(O H)_{2}/C o_{1-x}F e_{x}O O H}$ films. (a) GIXRD of as-deposited films (see Figure S5 for indexed patterns) where $x=0.$ 0.54, 1 (left), and crystal structure for layered double hydroxide $x=0.54$ (fougèrite, ICSD 159700, all Fe analog) along the [100] direction (right). The unit cell is indicated by dotted lines, red $\\mathbf{\\Lambda}=\\mathrm{OH}.$ ; blue $=\\mathrm{Fe}^{3+}/\\bar{\\mathrm{C}}\\mathrm{o}^{2+}$ ; gray $\\mathbf{\\Sigma}=\\mathbf{\\Sigma}$ water. (b) SEM images of samples as-deposited (top) and after $^{2\\mathrm{~h~}}$ of anodic polarization at $\\eta=350\\:\\mathrm{mV}$ (bottom). The scale bars are 100 nm (see Figures S6 and S8 for full composition set). (c) O 1s XP spectra of samples as-deposited (top) and after $^{2\\mathrm{~h~}}$ anodic polarization (bottom). Gray shading indicates the peak for hydroxide phases (see Figure S7 for full composition set). \n\nAfter evolving $\\mathrm{O}_{2}$ from the electrodes at an iR-corrected overpotential of $350\\mathrm{mV}$ for $^{2\\mathrm{h}}$ in 1 M KOH, the samples were re-examined by SEM and XPS (Figures $^{\\mathrm{1b,c}}$ bottom row). For $x=0$ the nanoplatelet structures appear less defined after conditioning. For $\\ x\\ =\\ 0.54$ the structures remain largely unaffected. For $x=1$ the structures appear to have largely dissolved as the bare Au substrate appears visible (see also Figure S8 for full range of compositions studied). The $\\dot{\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})}$ films with $x>{\\sim}0.5$ also lost a portion of the film mass and showed decreased Fe:Co ratios (see Section 3.7). The $\\mathrm{~o~}$ 1s XPS spectra of the anodically polarized films showed an increase in the size of the oxide-like shoulder at lower binding energies. This is consistent with an increase in the oxide character of the films due to the formation of CoOOH, FeOOH, and/or other Fe/Co-oxide phases. In situ measurements would be needed to determine the oxidation state under OER conditions. We discuss these structural and compositional changes in more detail when we address the electrocatalyst stability in Section 3.7. \n\n3.2. Voltammetric Analysis of $\\mathbf{Co}_{1-x}\\mathsf{F e}_{x}(00\\mathsf{H})$ . The first CV cycle of all $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OH)}_{2}$ films for $x<1$ has an anodic peak with a larger integrated area than either the corresponding cathodic peak or subsequent anodic peaks (Figures 2a and S9). \n\n![](images/0150aa7d0b76cd69e6b959b2e71d5d7162ffb0f3175a2fda8e9f9d09c01c7ded.jpg) \nFigure 2. (a) Voltammetry of ${\\mathrm{Co}}(\\mathrm{OOH})$ in purified KOH showing the difference between the first and second CV cycle after deposition. (b) Voltammetry of $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OOH)}$ showing systematic anodic shift of the (nominally) $\\mathbf{Co}^{2+/3+}$ wave with increasing Fe content. The second CV cycle of each film is shown for clarity. \n\nThis peak has been seen in other ${\\mathrm{Co}}(\\mathrm{OH})_{2}$ and ${\\mathrm{CoO}}_{x}$ films and it has been attributed to an irreversible oxidation of ${\\mathrm{Co}}({\\mathrm{OH}})_{2}$ to CoOOH.49,76 We also observe a decrease in film mass $(\\sim8\\%)$ only during this first anodic wave of the first CV cycle. It is likely that during the initial oxidation of the film, the mass decreases as ${\\mathrm{NO}}_{3}{}^{-}$ ions exchange with $\\mathrm{OH^{-}}$ (Figure S2).73 This large anodic peak is not recovered during anodic cycling, anodic polarization, or after sitting in base with no applied potential for $120\\mathrm{min}$ (Figure S10a). However, the peak does reappear upon cathodic cycling to $-0.9\\mathrm{~V~}$ vs $\\mathrm{Hg/HgO}$ (Figure S10b). Such partial irreversible oxidation has been previously observed for $\\bar{\\mathrm{Ni}}(\\mathrm{OH})_{2}$ oxidation to NiOOH and attributed to the trapping of the outer portion of the NiOOH film by electrically insulating $\\mathrm{{Ni}(O H)}_{2}$ formed at the underlying interface between the conductive electrode and film.77 The conductivity switching behavior of $\\mathrm{Co(OH)_{2}/C o O O H}$ is further discussed below. \n\nAs the Fe content in $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})$ films increases, the $\\mathbf{Co}^{2+/3+}$ wave shifts anodically (Figure 2b). This shift indicates a strong electronic interaction between the Co and Fe that modifies the electronic structure of the catalyst thus making ${\\mathrm{Co}}^{2+}$ oxidation more difficult. This is consistent with the substitution of Fe onto Co sites in $\\mathrm{Co(OH)_{2}/C o O O H}$ . We note that the Fe does not have any redox features in this potential range and remains nominally $\\mathrm{Fe}^{3+}$ .78 A similar effect on the $\\mathrm{\\DeltaNi}$ voltammetry is observed in Ni−Fe (oxy)- hydroxides,53,55 and there have been related observations in various ${\\mathrm{Co}}{\\mathrm{-}}{\\mathrm{Fe}}$ systems. Smith et al. noted a small redox wave in photochemically prepared $\\mathrm{Fe}_{0.4}\\mathrm{Co}_{0.60}\\mathrm{O}_{x}$ that was shifted ${\\sim}0.4\\mathrm{V}$ anodic relative to the wave assigned to $\\mathrm{CoO}_{x}^{4\\mathfrak{s}}$ 9 Laouini et al. added Fe to nanocrystalline $\\mathrm{Co}_{3}\\mathrm{\\bar{O}}_{4}$ films and observed a decrease in the integrated charge in the $\\mathrm{Co}^{2+/3+}$ wave with an increased lattice constant that was consistent with Fe incorporation into the nanocrystalline $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ .44 An anodic shift in the $\\mathbf{Co}^{2+/3+}$ wave was observed with Ti incorporation into Co-based oxides; however, no increase in activity was reported.79 The latter point is interesting, as it suggests that an anodic shift in the $\\mathbf{Co}^{\\hat{2}+/3+}$ wave alone is perhaps not sufficient to cause increased activity, an observation that will be discussed further in Section 3.6 with regard to the mechanistic role of Fe on the OER. \n\n3.3. Intrinsic Activity via Turnover Frequency (TOF) Calculation. In order to make meaningful comparisons of activity trends and understand their fundamental origin, it is critical to compare intrinsic activities either on a TOF basis or normalized by real surface area.6,16 The TOF is defined as the number of $\\mathrm{O}_{2}$ molecules produced per second per active site. A substantial challenge in measuring TOF is the difficulty in accurately measuring the number of active sites. Normalizing the current to the “real” surface area is also challenging as the real surface area is extremely difficult to measure, as has been discussed in detail by Trasatti.80 McCory et al. suggested a standard protocol for assessing electrochemically active surface area by measurement of the double-layer capacitance in a potential region with no faradaic response.17 This method, while suitable for electrodes consisting of conductive crystalline oxides without hydrated surface phases, fails for electrodeposited (oxy)hydroxide films. The electrode capacitance is nearly independent of the catalyst loading because ions polarize through the hydrated, electrolyte-permeated films against the underlying metallic electrode.11,39,81,82 \n\nTo avoid the challenge in directly measuring active-site density, we have calculated TOF using the catalyst mass and composition provided from in situ QCM and ex situ XPS measurements, respectively. Figure 3a shows $\\mathrm{TOF}_{\\mathrm{mass}},$ which is calculated based on the total number of ${\\mathrm{Co~}}+{\\mathrm{~Fe}}$ atoms from the steady-state current (assuming unity faradaic efficiency) at an $i R_{\\mathrm{u}}$ -corrected $\\eta=350~\\mathrm{mV}$ (Table S1 contains the complete data set). As some of the films are changing (i.e., losing Fe and/ or chemically restructuring) the TOFs represent “snapshots” of activity after 1 and $120~\\mathrm{\\min}$ of steady-state polarization. $\\mathrm{TOF}_{\\mathrm{mass}}$ is a lower limit for the TOF, as both Fe and Co sites are unlikely to be equally active and some cations are not electrochemically accessible. It is, however, the most practically relevant metric. \n\nThe CoOOH films (measured in a rigorously Fe-free electrolyte) showed $\\mathrm{TOF}_{\\mathrm{mass}}~=~0.007~\\pm~0.001~s^{-1}$ . The FeOOH films had a slightly higher $\\mathrm{TOF}_{\\mathrm{mass}}=0.016\\pm0.003$ $\\ensuremath{\\mathbf{s}}^{-1}$ . $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OOH)}$ with $x$ between 0.4 and 0.6 had $\\mathrm{TOF}_{\\mathrm{mass}}$ $\\sim~100$ -fold higher, peaking at $0.61~\\pm~0.10~\\mathrm{{s^{-1}}}$ for $\\mathrm{Co}_{0.54}\\mathrm{Fe}_{0.46}(\\mathrm{OOH})$ . These data unequivocally demonstrate the synergistic role of Fe and $C_{0}$ for OER catalysis. We note that $\\mathrm{Ni}_{0.9}\\mathrm{Fe}_{0.1}\\mathrm{OOH}$ had a $\\mathrm{TOF}_{\\mathrm{mass}}$ at $\\eta=350~\\mathrm{mV}$ of $2.8\\pm0.4$ $s^{-1},^{16}$ larger by a factor of $^{>4}$ than for $\\mathbf{Co}_{0.54}\\mathrm{Fe}_{0.46}(\\mathrm{OOH})$ Given the observation that the TOF can range over many orders of magnitude, these numbers are comparatively similar. \n\n![](images/e62daea7d045335ccd7ded445940bdd953285c4465b079349347bb93d2865176.jpg) \nFigure 3. TOF data depicted based on the total film mass and composition assuming (a) all metal sites are available for catalysis $(\\mathrm{TOF}_{\\mathrm{mass}},$ triangles), (b) only $C_{0}$ -sites are available for catalysis $(\\mathrm{TOF}_{\\mathrm{mass,Co}}^{\\mathrm{app}},$ circles), and (c) only Fe-sites are available for catalysis $/\\mathrm{TOF}_{\\mathrm{mass,Fe}}^{\\mathrm{app}},$ diamonds) during steady-state polarization at $\\eta=350~\\mathrm{mV}$ after $1~\\mathrm{min}$ (closed symbols) and $120~\\mathrm{{min}}$ (open symbols). Dot-dash lines $\\left(\\mathsf{a}-\\mathsf{c}\\right)$ are calculations based on the model described in the text. Shaded regions indicate the region where the model no longer applies (see Section 3.6.2). (d) The fraction of electrochemically accessible Co is calculated from the ratio of the integrated charge of the cathodic Co2+/3+ wave relative to the total Co deposited from mass measurements. Different symbols indicate integration of the oxidative peak (closed black squares) from the first CV cycle and the oxidative (open colored squares) and reductive peak from the second CV cycle (closed colored squares). Some data for $x>0.54$ is omitted due to a lack of a distinct oxidation wave. Uncertainties $(\\mathsf{a}\\mathrm{-}\\mathsf{d})$ are standard deviations of three identically prepared samples (see Figure S1 for TOF determination and calculation). Some error bars are smaller than the symbols. \n\nTo better identify the metal centers responsible for catalysis, we separate $\\mathrm{TOF}_{\\mathrm{mass}}$ into apparent TOFs for each element $(\\mathrm{TOF_{mass,Co}^{a p p}}$ and $\\mathrm{TOF}_{\\mathrm{mass,Fe},}^{\\mathrm{app}}$ ) by dividing by the relative Fe or Co atomic fraction, respectively (Figure 3b, c). \n\n$$\n\\mathrm{TOF}_{\\mathrm{mass,Fe}}^{\\mathrm{app}}=\\frac{\\mathrm{TOF}_{\\mathrm{mass}}}{x}\n$$ \n\n$$\n\\mathrm{TOF_{mass,Co}^{a p p}=\\frac{T O F_{m a s s}}{(1-\\it{\\Delta}x)}}\n$$ \n\nThese apparent TOF values thus implicitly assume that only one of the metal ions is active (e.g., Fe or Co). \n\nTo understand the activity trends of the various TOFs, we further analyzed the data under the simple assumption that both Co and Fe (within the $\\mathrm{CoOOH}$ host-structure) have a constant intrinsic activity $(\\mathrm{TOF}_{\\mathrm{Co}}^{*}$ and $\\mathrm{TOF_{Fe}^{*}},$ respectively) for all $x_{\\cdot}$ . To estimate $\\mathrm{TOF}_{\\mathrm{Co}}^{*},$ we take the average activity of pure CoOOH $(\\sim0.006~s^{-1})$ as representative of the activity of Cosites for all $x$ . Due to the low electrical conductivity of FeOOH (see section 3.6.2), a reliable estimate of $\\mathrm{TOF_{Fe}^{*}}$ cannot be taken from the pure FeOOH activity. From Figure 3c, we observe that $\\mathrm{TOF}_{\\mathrm{mass,Fe}}^{\\mathrm{app}}$ is nearly constant, within error, for $x\\leq$ 0.79, with an average value of $0.8\\ s^{-1}\\pm\\:0.3$ . We take this average TOFampapss, Fe as TOFF\\*e. \n\nUsing these intrinsic TOFs estimates, we then calculate the expected values for $\\mathrm{TOF}_{\\mathrm{mass}}$ : \n\n$$\n\\mathrm{TOF}_{\\mathrm{mass}}=(1-x){\\cdot}\\mathrm{TOF}_{\\mathrm{Co}}^{\\ast}+x{\\cdot}\\mathrm{TOF}_{\\mathrm{Fe}}^{\\ast}\n$$ \n\nas well as for TOFampapss, Fe and TOFampapss, Co, using eqs 1 - 3. The calculated TOF data, assuming constant intrinsic activity $\\mathrm{TOF}_{\\mathrm{Co}}^{*}$ and $\\mathrm{TOF_{Fe}^{*}}$ with $x,$ are overlaid as the dashed lines on the experimental data in Figure $_{3\\mathsf{a}-\\mathsf{c}}$ . The agreement between the results of the simple model using experimentally derived $\\mathrm{TOF}_{\\mathrm{Co}}^{*}$ and $\\mathrm{TOF_{Fe}^{*}}$ as the only parameters for $x<0.79$ suggests that the assumption of constant intrinsic activity for each cation is reasonable over this range. The substantial deviation from the model data for higher $x>0.79$ (Figure $_{\\mathrm{1a-c,}}$ gray regions) can be explained by the formation of phase-separated FeOOH (that is electrically insulating, as discussed below) within the active $\\mathrm{Co(Fe)OO\\dot{H},}$ similar to that recently described for $\\mathrm{{Ni}(\\mathrm{{Fe})}}$ - OOH.57 More work would be needed to confirm this. \n\nA separate method to estimate active site density is to integrate the total charge in a well-defined redox feature, for example associated with the $\\mathbf{Co}^{2+/3+}$ redox wave shown in Figure 2, and assume each electron is associated with a single surface-active metal ion. Counting active sites in this way, however, implicitly assumes the reaction occurs only on the metal exhibiting the redox feature (e.g., here Co), which we do not believe to be true. Furthermore, as discussed above, the size of the integrated redox wave is influenced by the scan cycle. Figure 3d shows the apparent fraction of electrochemically accessible Co centers (relative to the total number of Co from the mass measurement) as a function of Fe content and measurement cycle. The integrated charge in the Co oxidation measured on the first cycle represents $50\\mathrm{-}100\\%$ of the total $\\scriptstyle{\\mathrm{Co}}$ in the film. On subsequent cycles, less of the film is apparently electrochemically active $(\\sim20\\mathrm{-}60\\%)$ . As discussed above, this is likely due to trapping of a portion of the film in the oxidized state by an insulating Co−Fe hydroxide layer at the electrode surface. Because the oxidized film is conductive (see below) this portion of the film nevertheless remains OER active under operating conditions. These data confirm that a significant portion of the total number of Co sites is electrochemically accessible and thus indicate that the $\\mathrm{TOF}_{\\mathrm{mass}}$ -based analysis presented above (which assumes all cations accessible) is reasonable. \n\n3.4. Tafel Electrokinetics Analysis As a Function of Fe Content. Tafel analysis was performed on voltammetry data collected at $10\\ \\mathrm{mV}\\ \\mathrm{{\\dot{s}}^{-1}}$ . This was used instead of steady-state measurements, because the $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OOH)}$ films change composition/activity with time. To minimize the contribution of noncatalytic current (i.e., faradaic and capacitive charging currents) we averaged the forward and reverse voltammetry sweeps prior to finding the Tafel slope (see Figure S12). The pure Co films have Tafel slopes of ${\\bar{\\sim}}62~\\mathrm{mV~d{\\bar{e}}c^{-1}}$ . The films with moderately high Fe content $(0.33~x~>~0.5$ slowly dissolve during the stability test, losing $18-38\\%$ of their mass during the $^{2\\mathrm{h}}$ . FeOOH ${\\bf\\Psi}(x=1)$ ) is the least stable, losing ${\\sim}44\\%$ of it mass. The OER current at $\\eta=350~\\mathrm{mV}$ thus decreases over time for samples with $x>0.5$ . The $\\mathrm{TOF}_{\\mathrm{mass}}$ for films with $x>0.43$ (calculated with the mass measured in situ), however, increases over the $^{2\\mathrm{h}}$ stability test (Figure 8b). Further, the $\\mathrm{Co}^{2+/3+}$ wave potential is unchanged before and after conditioning, suggesting the composition of the electroactive Co−Fe (oxy)hydroxides is not changing. These data are consistent with the hypothesis that for $\\bar{\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})}$ with $x>0.5$ there are regions of FeOOH that have low activity (as they are electrically insulating). These regions then dissolve during stability testing leading to a larger fraction of the film mass contributing to the OER. The data also demonstrate that CoOOH is responsible for chemically stabilizing Fe under OER conditions that would otherwise be soluble as FeOOH. \n\n![](images/df4c5cc2d69ff8e7cb7e468f2bb80179186e3cece8ecdf2557e7e8dc3ddd82f7.jpg) \nFigure 8. (a) In situ mass change as a function of time from films with the different Fe contents listed, and (b) semilog plot of activity normalized by the mass measured in situ with initial Fe content listed. The data are from the same representative sample for each film composition. \n\nIt is further interesting to consider the balance between stability and activity. Danilovic et al. compared the OER activity and stability of five different noble metal oxides in acid. They found that the most active metals were those with the least stability (i.e., high solubility in acid). The best catalysts, they argue, must balance stability and activity.22 It is interesting to note that FeOOH is also unstable (i.e., soluble) unless incorporated into NiOOH or CoOOH, which are insoluble. This could indicate that the electronic/bonding effects that stabilize Fe within the Co matrix are the same as those that increase the activity of Fe-sites within mixed Co−Fe (oxy)- hydroxide systems above that of pure FeOOH. \n\n# 4. CONCLUSION \n\nWe studied electrodeposited Co−Fe (oxy)hydroxides and discovered that Fe incorporation enhances the OER activity by ${\\sim}100$ -fold over that of pure CoOOH. We observed that Fe impurities incorporate into CoOOH unless test electrolytes are rigorously cleaned; of significance for the numerous mechanistic studies of Co-based OER catalysts. We combined in situ measurements of catalyst electrical conductivity and stability, along with ex situ diffraction and XPS measurements, to identify the roles of Fe and Co in $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}(\\mathrm{OOH})$ OER catalysis. FeOOH has a higher intrinsic OER activity than CoOOH but is an electrical insulator and is chemically unstable to dissolution under OER conditions in base. CoOOH is a good electrical conductor at OER potentials and chemically stable to dissolution. The voltammetry of $\\mathrm{Co}_{1-x}\\mathrm{Fe}_{x}\\mathrm{(OOH)}$ shows a strong dependence of the $\\mathbf{Co}^{\\dot{2}+/3+}$ potential on the Fe content, suggesting strong electronic coupling between Fe and Co in the solid. These data thus support a hypothesis where CoOOH provides a conductive, chemically stable, and intrinsically porous/electrolyte-permeable host for Fe, which substitutes for Co and serves as the (most) active site for OER catalysis. This work thus provides a new framework for understanding OER catalysis on transition metal (oxy)hydroxides and will aid in the design of improved OER catalysts. \n\n# ASSOCIATED CONTENT \n\n# Supporting Information \n\nTable S1, Figures S1S14, and calculations for associated figures are included in the Supporting Information. This material is available free of charge via the Internet at http:// pubs.acs.org. \n\n# AUTHOR INFORMATION \n\nCorresponding Author \\*swb@uoregon.edu \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the National Science Foundation through CHE-1301461. M.G.K. and the thin-film X-ray diffraction analysis portion of this study were supported by the Center for Sustainable Materials Chemistry through the National Science Foundation grant CHE-1102637. The authors thank Lisa Enman and Adam Batchellor from the University of Oregon and Kathy Ayers, Julie Renner, and Nemanja Danilovic from Proton OnSite for insightful discussion. We acknowledge Stephen Golledge for help with XPS data interpretation. The project made use of CAMCOR facilities supported by grants from the W. M. Keck Foundation, the M. J. Murdock Charitable Trust, ONAMI, the Air Force Research Laboratory (FA8650-05-1-5041), the National Science Foundation (0923577 and 0421086), and the University of Oregon. S.W.B. thanks the Research Corporation for Science Advancement for support as a Cottrell Scholar. \n\n# REFERENCES \n\n(1) Walter, M. G.; Warren, E. L.; McKone, J. R.; Boettcher, S. W.; Mi, \n$\\mathrm{Q.;}$ Santori, E. a; Lewis, N. S. Chem. Rev. 2010, 110, 6446. \n(2) Mckone, J. R.; Lewis, N. S.; Gray, H. B. Chem. Mater. 2013, 26, \n407. (3) Pletcher, D.; Li, X. Int. J. Hydrogen Energy 2011, 36, 15089. (4) Armaroli, N.; Balzani, V. Angew. Chem., Int. Ed. Engl. 2007, 46, 52. (5) Lewis, N. S.; Nocera, D. G. Proc. Natl. Acad. Sci. U. S. A. 2006, \n104, 15729. (6) Trotochaud, L.; Boettcher, S. W. Scr. Mater. 2014, 74, 25. (7) Rossmeisl, J.; Qu, Z.-W.; Zhu, H.; Kroes, G.-J.; Nørskov, J. K. J. \nElectroanal. Chem. 2007, 607, 83. (8) Koper, M. T. M. J. Electroanal. Chem. 2011, 660, 254. (9) Zeng, K.; Zhang, D. Prog. Energy Combust. Sci. 2010, 36, 307. \n(10) Appleby, a; Crepy, G.; Jacquelin, J. Int. J. Hydrogen Energy 1978, \n3, 21. \n(11) Lin, F.; Boettcher, S. W. Nat. Mater. 2014, 13, 81. (12) Trotochaud, L.; Mills, T. J.; Boettcher, S. W. J. Phys. Chem. Lett. \n2013, 4, 931. (13) Trasatti, S. Electrochim. Acta 1984, 29, 1503. (14) Merrill, M. D.; Dougherty, R. C. J. Phys. Chem. C 2008, 112, \n3655. \n(15) Singh, A.; Spiccia, L. Coord. Chem. Rev. 2013, 257, 2607. (16) Trotochaud, L.; Ranney, J. K.; Williams, K. N.; Boettcher, S. W. \nJ. Am. Chem. Soc. 2012, 134, 17253. \n(17) McCrory, C. C. L.; Jung, S.; Peters, J. C.; Jaramillo, T. F. J. Am. \nChem. Soc. 2013, 135, 16977. \n(18) Hernández-Pagán, E. a.; Vargas-Barbosa, N. M.; Wang, T.; \nZhao, Y.; Smotkin, E. S.; Mallouk, T. E. Energy Environ. Sci. 2012, 5, \n7582. \n(19) Okada, T.; Xie, G.; Gorseth, O.; Kjelstrup, S. Electrochim. Acta \n1998, 43, 3741. (20) Ayers, K. E.; Anderson, E. B.; Capuano, C. B.; Carter, B. D.; \nDalton, L. T.; Hanlon, G.; Manco, J.; Niedzwiecki, M. ECS Trans. \n2010, 33, 3. \n(21) Ayers, K. E.; Capuano, C. B.; Anderson, E. B. ECS Trans. 2012, 41, 15. \n(22) Danilovic, N.; Subbaraman, R.; Chang, K.; Chang, S. H.; Kang, Y. J.; Snyder, J.; Paulikas, A. P.; Strmcnik, D.; Kim, Y.; Myers, D.; \nStamenkovic, V. R.; Markovic, N. M. J. Phys. Chem. Lett. 2014, 5, 2474. \n(23) Galán-Mascarós, J. R. ChemElectroChem 2014, 4, 1637. \n(24) Subbaraman, R.; Tripkovic, D.; Chang, K.-C.; Strmcnik, D.; \nPaulikas, A. P.; Hirunsit, P.; Chan, M.; Greeley, J.; Stamenkovic, V.; \nMarkovic, N. M. Nat. Mater. 2012, 11, 550. \n(25) Doyle, R. L.; Godwin, I. J.; Brandon, M. P.; Lyons, M. E. G. \nPhys. Chem. Chem. Phys. 2013, 15, 13737. \n(26) Ardizzone, S.; Trasatti, S. Adv. Colloid Interface Sci. 1996, 64, 173. \n(27) Gerken, J. B.; McAlpin, J. G.; Chen, J. Y. C.; Rigsby, M. L.; \nCasey, W. H.; Britt, R. D.; Stahl, S. S. J. Am. Chem. Soc. 2011, 133, 14431. \n(28) Kanan, M. W.; Nocera, D. G. Science 2008, 321, 1072. \n(29) Lutterman, D. a; Surendranath, Y.; Nocera, D. G. J. Am. Chem. \nSoc. 2009, 131, 3838. \n(30) Farrow, C. L.; Bediako, D. K.; Surendranath, Y.; Nocera, D. G.; \nBillinge, S. J. L. J. Am. Chem. Soc. 2013, 135, 6403. \n(31) Mattioli, G.; Giannozzi, P.; Amore Bonapasta, A.; Guidoni, L. J. \nAm. Chem. Soc. 2013, 135, 15353. \n(32) Bediako, D. K.; Costentin, C.; Jones, E. C.; Nocera, D. G.; \nSavéant, J.-M. J. Am. Chem. Soc. 2013, 135, 10492. \n(33) García-Mota, M.; Bajdich, M.; Viswanathan, V.; Vojvodic, A.; \nBell, A. T.; Nørskov, J. K. J. Phys. Chem. C 2012, 116, 21077. \n(34) Bajdich, M.; García-Mota, M.; Vojvodic, A.; Nørskov, J. K.; Bell, A. T. J. Am. Chem. Soc. 2013, 135, 13521. \n(35) Friebel, D.; Bajdich, M.; Yeo, B. S.; Louie, M. W.; Miller, D. J.; \nSanchez Casalongue, H.; Mbuga, F.; Weng, T.-C.; Nordlund, D.; \nSokaras, D.; Alonso-Mori, R.; Bell, A. T.; Nilsson, A. Phys. Chem. \nChem. Phys. 2013, 15, 17460. \n(36) Li, X.; Siegbahn, P. E. M. J. Am. Chem. Soc. 2013, 135, 13804. \n(37) Chen, J.; Selloni, A. J. Phys. Chem. C 2013, 117, 20002. \n(38) Risch, M.; Khare, V.; Zaharieva, I.; Gerencser, L.; Chernev, P.; \nDau, H. J. Am. Chem. Soc. 2009, 131, 6936. \n(39) Klingan, K.; Ringleb, F.; Zaharieva, I.; Heidkamp, J.; Chernev, P.; Gonzalez-Flores, D.; Risch, M.; Fischer, A.; Dau, H. ChemSusChem 2014, 7, 1301. \n(40) McAlpin, J. G.; Surendranath, Y.; Dinca, M.; Stich, T. A.; Stoian, S. A.; Casey, W. H.; Nocera, D. G.; Britt, R. D. J. Am. Chem. Soc. 2010, 132, 6882. \n(41) $\\mathrm{Du},$ P.; Kokhan, O.; Chapman, K. W.; Chupas, P. J.; Tiede, D. \nM. J. Am. Chem. Soc. 2012, 134, 11096. \n(42) Risch, M.; Ringleb, F.; Kohlhoff, M.; Bogdanoff, P.; Chernev, P.; \nZaharieva, I.; Dau, H. Energy Environ. Sci. 2015, 8, 661. \n(43) Iwakura, C.; Honji, A.; Tamura, H. Electrochim. Acta 1980, 26, 1319. \n(44) Laouini, E.; Hamdani, M.; Pereira, M. I. S.; Douch, J.; \nMendonça, M. H.; Berghoute, Y.; Singh, R. N. Int. J. Hydrogen Energy 2008, 33, 4936. \n(45) Grewe, T.; Deng, X.; Tuysuz, H. Chem. Mater. 2014, 26, 3162. \n(46) Xiao, C.; Lu, X.; Zhao, C. Chem. Commun. 2014, 50, 10122. \n(47) Kishi, T.; Takahashi, S.; Nagai, T. Surf. Coat. Technol. 1986, 27, 351. \n(48) Smith, R. D. L.; Prévot, M. S.; Fagan, R. D.; Zhang, Z.; Sedach, P. a; Siu, M. K. J.; Trudel, S.; Berlinguette, C. P. Science 2013, 340, 60. \n(49) Smith, R. D. L.; Prévot, M. S.; Fagan, R. D.; Trudel, S.; \nBerlinguette, C. P. J. Am. Chem. Soc. 2013, 135, 11580. \n(50) Suntivich, J.; May, K. J.; Gasteiger, H. a; Goodenough, J. B.; \nShao-Horn, Y. Science 2011, 334, 1383. \n(51) May, K. J.; Carlton, C.; Stoerzinter; Kelsey, A.; Risch, M.; \nSuntivich, J.; Lee, Y.; Grimaud, A.; Shao-horn, Y. J. Phys. Chem. Lett. \n2012, 3, 3264. \n(52) Corrigan, D. A. J. Electrochem. Soc. 1987, 134, 377. (53) Trotochaud, L.; Young, S. L.; Ranney, J. K.; Boettcher, S. W. J. Am. Chem. Soc. 2014, 136, 6744. \n(54) Trasatti, S.; Lodi, G. Electrodes of Conductive Metallic Oxides; Elsevier: Amsterdam, 1981; Vol. B, pp 521−626. \n(55) Louie, M. W.; Bell, A. T. J. Am. Chem. Soc. 2013, 135, 12329. (56) Corrigan, D. A.; Conell, R. S.; Fierro, C. A.; Scherson, D. A. J. Phys. Chem. 1987, 91, 5009. \n(57) Friebel, D.; Louie, M. W.; Bajdich, M.; Sanwald, K. E.; Cai, Y.; Wise, A. M.; Cheng, M.-J.; Sokaras, D.; Weng, T.-C.; Alonso-Mori, R.; Davis, R. C.; Bargar, J. R.; Norskov, J. K.; Nilsson, A.; Bell, A. T. J. Am. Chem. Soc. 2015, 137, 1305. \n(58) Brownson, J. R. S.; Lévy-Clément, C. Phys. Status Solidi 2008, 245, 1785. \n(59) Hu, C.-C.; Chen, J.-C.; Chang, K.-H. J. Power Sources 2013, 221, 128. \n(60) Liu, Z.; Ma, R.; Osada, M.; Takada, K.; Sasaki, T. J. Am. Chem. Soc. 2005, 127, 13869. \n(61) Sauerbrey, G. Z. Z. Phys. A Hadron. Nucl. 1959, 155, 206. (62) Moulder, J. F.; Stickle, W. F.; Sobol, P. E.; Bomben, K. D. Handbook of X-ray Potoelectron Spectroscopy; Chastain, J., Ed.; PerkinElmer Corporation: Waltham, MA, 1992; pp 254−257. \n(63) Schweitzer, G. K.; Pesterfield, L. L. The Aqueous Chemistry of the Elements; Oxford University Press: Oxford, 2010. \n(64) Risch, M.; Grimaud, A.; May, K. J.; Stoerzinger, K. a.; Chen, T. J.; Mansour, A. N.; Shao-Horn, Y. J. Phys. Chem. C 2013, 117, 8628. (65) Grimaud, A.; Carlton, C. E.; Risch, M.; Hong, W. T.; May, K. J.; Shao-horn, Y. J. Phys. Chem. C 2013, 117, 25926. \n(66) Zhang, J.; Wang, X.; Ma, J.; Liu, S.; Yi, X. Electrochim. Acta 2013, 104, 110. \n(67) Therese, G. H. A.; Kamath, P. V. Chem. Mater. 2000, 12, 1195. (68) Ma, R.; Liu, Z.; Takada, K.; Fukuda, K.; Ebina, Y.; Bando, Y.; Sasaki, T. Inorg. Chem. 2006, 45, 3964. \n(69) Yang, J.; Liu, H.; Martens, W. N.; Frost, R. L. J. Phys. Chem. C 2010, 111. \n(70) Liang, J.; Ma, R.; Iyi, N.; Ebina, Y.; Takada, K.; Sasaki, T. Chem. Mater. 2010, 22, 371. \n(71) El-Batlouni, H.; El-Rassy, H.; Al-Ghoul, M. J. Phys. Chem. A 2008, 112, 7755. \n(72) Ma, R.; Sasaki, T. Adv. Mater. 2010, 22, 5082. \n(73) Rahbani, J.; Ammar, M.; Al-Ghoul, M. J. Phys. Chem. A 2013, 117, 1685. \n(74) Mclntyre, N. S.; Cook, M. G. Anal. Chem. 1975, 47, 2208. (75) Biesinger, M. C.; Payne, B. P.; Grosvenor, A. P.; Lau, L. W. M.; Gerson, A. R.; Smart, R. S. C. Appl. Surf. Sci. 2011, 257, 2717. (76) Koza, J. A.; Hull, C. M.; Liu, Y.; Switzer, J. A. Chem. Mater. 2013, 25, 1922. \n(77) Corrigan, D. A.; Bendert, R. M. J. Electrochem. Soc. 1989, 136, 723. \n(78) Lyons, M. E. G.; Brandon, M. P. Phys. Chem. Chem. Phys. 2009, 11, 2203. \n(79) Seitz, L.; Pinaud, B.; Norclund, D.; Jaramillo, T. F. Materials for Photoelectrochemical and Photocatalytic Solar-Energy Harvesting and Storage. Proceedings from the Materials Research Society Spring Symposium, San Francisco, CA, April 21−25, 2014; Materials Research Society: Warrendale, PA, 2014. \n(80) Trasatti, S.; Petrii, O. A. J. Electroanal. Chem. 1993, 321, 353. (81) Burke, L. D.; Sullivan, E. J. M. O. J. Electroanal. Chem. 1981, 117, 155. \n(82) Mills, T. J.; Lin, F.; Boettcher, S. W. Phys. Rev. Lett. 2014, 112, 148304. \n(83) Bard, A. J.; Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications; 2nd ed.; John Wiley and Sons, Inc.: New York, 2001; p 115. \n(84) Surendranath, Y.; Kanan, M. W.; Nocera, D. G. J. Am. Chem. Soc. 2010, 132, 16501. \n(85) Smith, A. M.; Trotochaud, L.; Burke, M. S.; Boettcher, S. Chem. Commun. 2014, advance article. DOI: 10.1039/C4CC08670H. \n(86) Viswanathan, V.; Pickrahn, K. L.; Luntz, A. C.; Bent, S. F.; Nørskov, J. K. Nano Lett. 2014, 14, 5853. (87) Wuelfing, W. P.; Green, S. J.; Pietron, J. J.; Cliffel, D. E.; Murray, R. W.; Hill, C.; Carolina, N.; June, R. V.; Re, V.; Recei, M.; September, V. J. Am. Chem. Soc. 2000, 122, 11465. \n(88) Katz, J. E.; Zhang, X.; Attenkofer, K.; Chapman, K. W.; Frandsen, C.; Zarzycki, P.; Rosso, K. M.; Falcone, R. W.; Waychunas, G. A.; Gilbert, B. Science 2012, 337, 1200. \n(89) Liao, P.; Keith, J. A.; Carter, E. A. J. Am. Chem. Soc. 2012, 134, 13296. \n(90) Frydendal, R.; Paoli, E. a.; Knudsen, B. P.; Wickman, B.; Malacrida, P.; Stephens, I. E. L.; Chorkendorff, I. ChemElectroChem 2014, 1, 2075. " + }, + { + "id": "10.1021_acsnullo.5b03591", + "DOI": "10.1021/acsnullo.5b03591", + "DOI Link": "http://dx.doi.org/10.1021/acsnullo.5b03591", + "Relative Dir Path": "mds/10.1021_acsnullo.5b03591", + "Article Title": "Two-Dimensional, Ordered, Double Transition Metals Carbides (MXenes)", + "Authors": "Anasori, B; Xie, Y; Beidaghi, M; Lu, J; Hosler, BC; Hultman, L; Kent, PRC; Gogotsi, Y; Barsoum, MW", + "Source Title": "ACS nullO", + "Abstract": "The higher the chemical diversity and structural complexity of two-dimensional (2D) materials, the higher the likelihood they possess unique and useful properties. Herein, density functional theory (DFT) is used to predict the existence of two new families of 2D ordered, carbides (MXenes), M'M-2 '' C-2 and M'M-2 '' C-2(3), where M' and M '' are two different early transition metals. In these solids, M' layers sandwich M carbide layers. By synthesizing Mo2TiC2Tx, Mo2Ti2C3Tx, and Cr2TiC2Tx (where T is a surface termination), we validated the DFT predictions. Since the Mo and Cr atoms are on the outside, they control the 2D flakes' chemical and electrochemical properties. The latter was proven by showing quite different electrochemical behavior of Mo2TiC2Tx and Ti3C2Tx. This work further expands the family of 2D materials, offering additional choices of structures, chemistries, and ultimately useful properties.", + "Times Cited, WoS Core": 1476, + "Times Cited, All Databases": 1593, + "Publication Year": 2015, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000363915300009", + "Markdown": "# Two-Dimensional, Ordered, Double Transition Metals Carbides (MXenes) \n\nBabak Anasori,†,‡,# Yu Xie,\\*,§,# Majid Beidaghi,†,‡,# Jun Lu, Brian C. Hosler,† Lars Hultman, Paul R. C. Kent,§,^ Yury Gogotsi,\\*,†,‡ and Michel W. Barsoum\\*,† \n\n†Department of Materials Science & Engineering, Drexel University, Philadelphia, Pennsylvania 19104, United States, $^{\\ddagger}\\mathtt{A}.\\mathsf{J}.$ . Drexel Nanomaterials Institute, Drexel University, Philadelphia, Pennsylvania 19104, United States, §Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37381, United States, Thin Film Physics Division, Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-581 83 Linköping, Sweden, and ^Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37381, United States. #Contributed equally to this work. \n\nABSTRACT The higher the chemical diversity and structural complexity of two-dimensional (2D) materials, the higher the likelihood they possess unique and useful properties. Herein, density functional theory (DFT) is used to predict the existence of two new families of 2D ordered, carbides (MXenes), $\\mathsf{M}^{\\prime}{}_{2}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}$ and $M^{\\prime}{}_{2}M^{\\prime\\prime}{}_{2}C_{3},$ where $M^{\\prime}$ and $M^{\\prime\\prime}$ are two different early transition metals. In these solids, $M^{\\prime}$ layers sandwich $M^{\\prime\\prime}$ carbide layers. By synthesizing \n\n![](images/71905126db5f07877b197b1b22fa00ac8e3cd95d13946196c5c84e2453e5696d.jpg) \n\n$\\begin{array}{r}{\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x},\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}\\mathsf{T}_{x},}\\end{array}$ and $\\mathsf{C r}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ (where T is a surface termination), we validated the DFT predictions. Since the Mo and Cr atoms are on the outside, they control the 2D flakes' chemical and electrochemical properties. The latter was proven by showing quite different electrochemical behavior of $\\mathsf{M o}_{2}\\bar{\\mathsf{I i C}}_{2}\\bar{\\mathsf{I}}_{x}$ and $\\bar{\\mathsf{I i}}_{3}\\mathsf{C}_{2}\\bar{\\mathsf{I}}_{x}.$ . This work further expands the family of 2D materials, offering additional choices of structures, chemistries, and ultimately useful properties. \n\nKEYWORDS: MXene $\\cdot$ 2D materials $\\cdot$ DFT calculations $\\cdot$ electrochemical properties \n\nThigh specific surface areas, as well as that differ from their bulk counterparts. They also provide easy-to-assemble building blocks for nanoscale architectures.1,2 Graphene is the most studied 2D material,3\u00015 but other 2D solids, such as metal oxides and hydroxides, dichalcogenides, hexagonal boron nitride, silicene, and others are garnering increasing attention.1,2,6\u000110 2D transition metal oxides (TMO) are promising for many applications varying from electron$\\mathsf{i c s}^{11}$ to electrochemical energy storage.12,13 By moving toward increasing complexity and diversity, unique combinations of properties can be achieved. \n\nAbout 4 years ago, we discovered a new class of 2D transition metal carbides and nitrides (Figure 1a) we labeled MXenes,14\u000116 because they are obtained by selectively etching the A-layers from their 3D layered, parent compounds the $\\mathsf{M}_{n+1}\\mathsf{A X}_{n},$ or MAX, phases, where M is an early transition metal, A is an A-group element, such as Al or Si, X is carbon and/or nitrogen, and $\\boldsymbol{n}$ is $1-3.^{17}$ The MXenes synthesized to date include $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x},\\mathsf{T i}_{2}\\mathsf{C T}_{x},\\mathsf{V}_{2}\\mathsf{C T}_{x},\\mathsf{N b}_{2}\\mathsf{C T}_{x},\\mathsf{N b}_{4}\\mathsf{C}_{3}\\mathsf{T}_{x},$ and $\\mathsf{T a}_{4}\\mathsf{C}_{3}\\mathsf{T}_{x}$ .16 In this notation, $\\daleth_{x}$ represents surface groups, mostly $\\circ,$ , $\\mathsf{\\Gamma}_{\\mathsf{O H}}$ , and F. Solid solutions, such as $\\mathrm{Ti}_{3}\\mathsf{C N T}_{x},$ $(\\mathsf{T i}_{0.5},\\mathsf{N b}_{0.5})_{2}\\mathsf{C T}_{x},$ and $(\\mathsf{V}_{0.5},\\mathsf{C r}_{0.5})_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ have been reported, in which the two transition elements are believed to randomly occupy the M-sites.16 MXenes with other M elements such as Sc, Zr, Hf and Mo have been predicted.18\u000120 \n\nMXenes offer a unique combination of metallic conductivity and hydrophilicity, and have already showed promise as electrodes for supercapacitors,21 Li S batteries,22 and Li-, Na- and K-ion batteries,14,17,23,24 partially due to a low metal diffusion barrier on their surfaces.25,26 MXenes are also predicted to have high capacities for multivalent ions such as ${\\mathsf{C a}}^{2+},{\\mathsf{\\Lambda}}^{24,27}{\\mathsf{M}}{\\mathsf{g}}^{2+}$ and $A l^{3+24}$ and are being explored in many other applications. \n\nIn 2014, Liu et al. discovered an ordered $M_{3}A X_{2}$ structure, $\\mathsf{C r}_{2}\\mathsf{T i A l C}_{2},^{28}$ in which a Ti-layer is sandwiched between two outer Cr carbide layers in a $M_{3}A X_{2}$ structure. Very recently, we synthesized the first MAX phase with Mo\u0001Al bonds, viz. $\\mathsf{M o}_{2}\\mathsf{T i A l C}_{2},^{29}$ wherein Mo-layers sandwiched $\\mathsf{T i C}_{2}$ layers. In short, a new class of ordered MAX phases $^*$ Address correspondence to gogotsi@drexel.edu, barsoumw@drexel.edu, yxe@ornl.gov. \n\nReceived for review June 12, 2015 and accepted July 24, 2015. \n\nPublished online July 24, 2015 \n10.1021/acsnano.5b03591 \n\n# ARTICLE \n\n![](images/b89aaeb05dbd4fc167f2693a00c63c8bef74ab9ce44265d41c59515a34f83336.jpg) \nFigure 1. Schematics of the new MXene structures. (a) Currently available MXenes, where M can be Ti, V, Nb, Ta, forming either monatomic M layers or intermixing between two different M elements to make solid solutions. (b) Discovering the new families of double transition metals MXenes, with two structures as $\\pmb{M}^{\\prime}{}_{2}\\pmb{M}^{\\prime\\prime}\\pmb{C}_{2}$ and $M^{\\prime}{}_{2}M^{\\prime\\prime}{}_{2}C_{3},$ adds more than 20 new MXene carbides, in which the surface $\\pmb{M}^{\\prime}$ atoms can be different from the inner $\\pmb{M}^{\\prime\\prime}$ atoms. $\\pmb{M}^{\\prime}$ and $\\pmb{M}^{\\prime\\prime}$ atoms can be Ti, V, Nb, Ta, Cr, Mo. (c) Each MXene can have at least three different surface termination groups (OH, O, and F), adding to the variety of the newly discovered MXenes. \n\nis emerging. Their discovery is crucial for the potential expansion of MXene family since they can result in numerous ordered layered 2D structures and MXene chemistries that were not possible previously. However, this discovery does not automatically imply that the corresponding MXenes are realizable because it is not known if the carbide layers are stable in the 2D state when released from the parent MAX phase. Even if the ordered compounds are structurally and energetically stable, they need to survive the etching process. The goal of this article is to demonstrate the existence of ordered double-transition metal 2D carbides. \n\nHerein, we use density functional theory (DFT) to predict the stability of over 20 new, ordered, double-M MXenes, viz. $\\mathsf{M}^{\\prime}{}_{2}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}$ and $M^{\\prime}{}_{2}M^{\\prime\\prime}{}_{2}C_{3}$ (Figure 1b), where $M^{\\prime}$ (outer layer metal) and $M^{\\prime\\prime}$ (inner layer metal) are Ti, V, Nb, Ta, Cr or Mo. In all cases, the C atoms occupy the octahedral sites between the $\\mathsf{{\\Omega}}M^{\\prime}{-}M^{\\prime\\prime}$ layers. Each $\\mathsf{M}^{\\prime}\\mathsf{M}^{\\prime\\prime}$ Xene can, in turn, have multiple surface termination groups, T;such as F, O, or OH;greatly expanding their varieties (Figure 1c). Of these, we synthesized $\\mathsf{M o}_{2}\\mathsf{T i C}_{2},\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}$ and $\\mathsf{C r}_{2}\\mathsf{T i C}_{2},$ , and showed them to be ordered directly in high-resolution scanning transmission electron microscope (HR STEM) images. We also explored the potential of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2},$ in electrochemical energy storage and showed that its electrochemical behavior is quite different from $\\mathrm{Ti}_{3}C_{2}\\mathsf{T}_{x}$ . \n\n# RESULTS AND DISCUSSION \n\nTheoretical Prediction of Double Transition Metal MXenes. We begin by presenting the results of our DFT calculations (see Materials and Methods section for details). Using Mo Ti containing phases as a case study, we start with $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ . The energy differences between a fully ordered ${M O}_{2}{\\mathrm{TiC}}_{2}$ configuration (inset on far left in Figure 2a) and partially ordered configurations (middle and right insets in Figure 2a and Supporting Information, Figure S1) are plotted in Figure 2a. These results unequivocally show that the ordered $\\mathsf{M o}_{2}\\mathsf{T i C}_{2},$ with a Mo\u0001Ti\u0001Mo stacking, has the lowest energy. Moreover, the total energy of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ increases almost linearly as the fraction of Mo atoms in the middle layer increases. \n\nThe same calculations were repeated for several other $M^{\\prime}$ and $M^{\\prime\\prime}$ elements in various $\\mathsf{M}^{\\prime}{}_{2}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}$ compositions and select results are shown in Figure 2b. Supporting Information, Figure S2 plots the entire set. On the basis of these figures, it is clear that the stability depends on the elements chosen. Thus, at $0\\mathsf{K},$ the following MXenes prefer to be in a fully ordered state: $\\mathsf{M o}_{2}\\mathsf{T i C}_{2},$ $\\mathsf{M o}_{2}\\mathsf{V C}_{2},$ ${M O}_{2}{\\mathsf{T a C}}_{2},$ ${\\mathsf{M o}}_{2}{\\mathsf{N b}}{\\mathsf{C}}_{2},$ $\\mathsf{C r}_{2}\\mathsf{T i C}_{2},$ $\\mathsf{C r}_{2}\\mathsf{V C}_{2},\\mathsf{C r}_{2}\\mathsf{T a C}_{2},\\mathsf{C r}_{2}\\mathsf{N b C}_{2},\\mathsf{T i}_{2}\\mathsf{N b C}_{2},\\mathsf{T i}_{2}\\mathsf{T a C}_{2},\\mathsf{V}_{2}\\mathsf{T a C}_{2}$ and $\\mathsf{V}_{2}\\mathsf{T i C}_{2}$ . The following four MXenes, $\\mathsf{N b}_{2}\\mathsf{V C}_{2},$ $\\mathsf{T a}_{2}\\mathsf{T i C}_{2},$ $\\mathsf{T a}_{2}\\mathsf{V C}_{2}$ and ${\\mathsf{N b}}_{2}{\\mathsf{T i C}}_{2},$ are more stable in their partially ordered, than in their fully ordered, state (Figure 2b). \n\nFor the $M_{2}^{'}M_{2}^{'\\prime}C_{3}$ compositions, there are two fully ordered structures, $M_{2}^{'}M_{2}^{'\\prime}C_{3}$ and $M_{2}^{'\\prime}M_{2}^{'}C_{3}$ (see Supporting Information, Figure S3). The energy differences between select pairs of fully ordered structures are plotted in Figure $\\mathsf{2c},$ in such a way that the more stable MXene is at $100\\%$ (for the full set, see Supporting Information, Figure S2b). Here again, the energy of the system increases monotonically from one ordered configuration to the other. On the basis of these results, we predict that, at $0\\mathsf{K}$ in the absence of terminations, ${M O}_{2}{\\mathrm{Ti}}_{2}{\\mathrm{C}}_{3},$ $\\mathsf{M o}_{2}\\mathsf{V}_{2}\\mathsf{C}_{3}$ , ${\\mathsf{M o}}_{2}{\\mathsf{N b}}_{2}{\\mathsf{C}}_{3},$ ${M O}_{2}\\mathsf{T a}_{2}\\mathsf{C}_{3},$ , ${\\mathsf{C r}}_{2}{\\mathsf{T i}}_{2}{\\mathsf{C}}_{3},$ ${\\mathsf{C r}}_{2}{\\mathsf{V}}_{2}{\\mathsf{C}}_{3},$ ${\\mathsf{C r}}_{2}{\\mathsf{N b}}_{2}{\\mathsf{C}}_{3},$ ${\\mathsf{C r}}_{2}{\\mathsf{T a}}_{2}{\\mathsf{C}}_{3},$ ${\\mathsf{N b}}_{2}{\\mathsf{T a}}_{2}{\\mathsf{C}}_{3},$ $\\bar{\\mathsf{T i}}_{2}\\mathsf{N b}_{2}\\mathsf{C}_{3},$ $\\mathsf{T i}_{2}\\mathsf{T a}_{2}\\mathsf{C}_{3},\\mathsf{V}_{2}\\mathsf{T a}_{2}\\mathsf{C}_{3},\\mathsf{V}_{2}\\mathsf{N b}_{2}\\mathsf{C}_{3}$ and $V_{2}T_{1_{2}}C_{3}$ are ordered. Since, by our definition the first element in the formula is on the surface, their opposite configurations (e.g., ${\\sf T i}_{2}{\\sf M o}_{2}{\\sf C}_{3},{\\sf V}_{2}{\\sf C r}_{2}{\\sf C}_{3},$ etc.) are higher in energy. From the totality of these results one can infer two important generalization concerning ordering. The Mo and $\\mathsf{C r}$ atoms avoid the middle layers, whereas the Ta and ${\\mathsf{N b}},$ when given the chance, avoid the outer ones. It is important to know that the inclusion of entropy30 and/ or surface terminations in these calculations could affect the degree of order. \n\nTo further explore the driving forces for ordering, we calculated the formation energies of various single M $M_{3}C_{2}$ and $M_{4}C_{3}$ structures, from their elements (Table 1). These results indicate that $M O_{3}C_{2}$ and \n\n# ARTICLE \n\n![](images/7a8a8b0460116c4fad905daa1be9e630f0c365633957193351f9dadf37a0e478.jpg) \nFigure 2. Predicted stability of $M^{\\prime}M^{\\prime\\prime}$ Xenes based on DFT calculations. (a) Total energy diagram of $\\ensuremath{\\mathsf{M o}}_{2}\\ensuremath{\\mathsf{T i C}}_{2}$ monolayer as a function of Ti concentration in the middle layer, relative to fully ordered ${M O}_{2}{\\mathsf{T i C}}_{2}$ . The open symbols are the calculated total energies for both ordered and disordered ${\\mathsf{M o}}_{2}{\\mathsf{T i C}}_{2}$ configurations. For all concentrations, the lowest energy configurations (squares) correspond to the most ordered configuration calculated. The black line is a guide for the eye for the lowest energy configuration of each composition. Insets show the stable structures of ${M O}_{2}{\\mathsf{T i C}}_{2}$ monolayers with $100\\%$ , $50\\%$ , and $0\\%$ Ti in the middle layer (Ti atoms are green, Mo atoms are red, and C atoms are black). The stable structure of ${M\\circ}_{2}\\bar{\\Pi}_{1_{2}}\\bar{\\mathsf{C}}_{3}$ monolayers is shown in Figure 4d. (b and c) Total energy diagrams of calculated $\\pmb{M}_{2}^{\\prime}\\pmb{M}^{\\prime\\prime}\\pmb{C}_{2}$ (b) and $M^{\\prime}{}_{2}M^{\\prime\\prime}{}_{2}C_{3}$ (c) $\\pmb{M}^{\\prime}\\pmb{M}^{\\prime\\prime}$ Xenes. \n\nTABLE 1. Formation Energies (eV/atom) from Their Elements of Select $M_{3}C_{2}$ and $M_{4}C_{3}$ Unterminated MXenes \n\n\n
formation energy (eV/atom)
transition metal (M)
unterminated MXenesTiVNbTaCrMo
M3C2-0.365-0.2540.039-0.0170.0120.328
M4C3-0.594-0.582-0.236-0.259-0.0920.258
\n\n$M o_{4}C_{3}$ are highly unstable and are thus unlikely to be synthesized. These results do not mean that Mo C bonds are unstable but rather that the Mo and C atoms avoid, at all costs, to stack in a face centered cubic (fcc) arrangement characteristic of the $\\boldsymbol{{\\mathsf{M}}}_{n+1}\\boldsymbol{\\mathsf{X}}_{n}$ layers. DFT calculations have shown that hexagonal molybdenum carbides are more stable than their rock salt counterparts.31 Consequently, if $M O_{3}C_{2}$ and $M o_{4}C_{3}$ are formed, Mo and C would be in fcc arrangement, which makes them energetically less preferable. By adding an element that favors the fcc arrangement with C, viz. Ti, the Mo layers avoid the fcc arrangement with the C atoms, forming $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ or $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}$ instead. Consistent with this notion is that most binary Mo-carbide phases are hexagonal.31 The same notion explains why the Cr atoms (Table 1) also prefer the outside of the $\\textstyle{\\boldsymbol{M}}_{n+1}{\\boldsymbol{C}}_{n}$ layers. \n\nTo shed light on effects of chemistry on the electronic properties of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x},$ and its end members as a function of T where ${\\sf T}=\\sf{O H}$ , O and F, we carried out further DFT calculations and plotted the projected and total density of states (DOS) (Figure 3). In all cases and regardless of termination, the DOS at Fermi level $(E_{\\mathsf{f}})$ is dominated by the M M d-orbitals and is substantial. In the $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ case (Figure $_{3a-c)}$ , the DOS at $E_{\\mathsf{f}}$ is dominated by the Mo Mo d-orbitals and not the Ti orbitals. Thus, the Mo layers should control its electronic properties. \n\nSynthesis of Double Transition Metal MXenes. On the basis of these predictions, we chose to synthesize $\\mathsf{M o}_{2}\\mathsf{T i C}_{2},$ $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}$ and $\\mathsf{C r}_{2}\\mathsf{T i C}_{2}$ not only because they would serve as typical examples of ordered $\\mathsf{M}^{\\prime}{}_{2}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}$ and $M^{\\prime}{}_{2}M^{\\prime\\prime}{}_{2}C_{3},$ but also because neither Mo- nor Cr-based single-transition metal MXenes exist to date. Synthesis of the MXenes followed published protocols (see Materials and Methods). \n\nIn agreement with the disappearance of the MAX phase peaks in the X-ray diffraction (XRD) patterns after etching (Figure 4a,b), energy dispersive X-ray spectroscopy (EDX) confirmed a significant drop in the Al signals and concomitant increases in the F and O signals (see Supporting Information, Table S2), implying that our MXene surfaces are O, OH and F terminated.16,32 The MXene yield was close to $100\\%$ . \n\nA comparison of the XRD patterns of $\\mathsf{M o}_{2}\\mathsf{T i A l C}_{2}$ before;lower red pattern, Figure 4a;and after etching and delamination (middle green and top blue patterns, respectively, in Figure 4a) clearly shows that all peaks belonging to ${M o}_{2}\\mathsf{T i A l C}_{2}$ were replaced by (000l) peaks belonging to ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ . These peaks broaden and downshift to lower angles, which is due to an increase in the $c$ lattice parameter, $\\mathsf{L P S},$ from $18.6\\mathring{\\mathsf{A}}$ in ${M o}_{2}\\mathrm{TiAlC}_{2}$ to 25.8 and $30.5\\mathring{\\mathsf{A}}$ after etching and delamination, respectively (Figure 4a). Consistent with our previous results on $\\mathsf{V}_{2}\\mathsf{C T}_{x},\\mathsf{N b}_{2}\\mathsf{C T}_{x},\\mathsf{\\Omega}^{17}$ and $\\mathsf{N b}_{4}\\mathsf{C}_{3}\\mathsf{T}_{x},^{33}$ the large $C{\\cdot}\\mathsf{L P S},$ increases upon etching are due to the presence of intercalated water and, quite possibly, cations between the MXene sheets. The widening of the (000l) peaks is related to domain size reduction along [0001] due to the etching process. That the $c$ -LP increases further after delamination (compare middle and top patterns in Figure 4a) most probably reflects the presence of additional water layers between the MXene sheets, like in $N b_{4}C_{3}\\mathsf{T}_{x}$ .33 \n\nIt is important to note here that the (1120) peak, around $62^{\\circ}$ , is present after etching (compare green and red in Figure 4a), but disappears after delamination (top blue pattern in Figure 4a). On the basis of our previous work, this indicates that etching alone does not necessarily disrupt the stacking along nonbasal directions.21 The disappearance of this peak upon delamination proves that when the delaminated layers \n\n# ARTICLE \n\n![](images/547c99e2b8dbe86f31fb505e2069aab601d33c443930d84ac1234fa23be858a3.jpg) \nFigure 3. Electronic structures of selected MXenes. $(\\mathsf{a}-\\mathsf{i})$ Total and projected densities of states for OH-, O-, and F-terminated $\\ensuremath{\\mathsf{M o}}_{2}\\ensuremath{\\mathsf{T i C}}_{2}$ (a c), $M O_{3}C_{2}$ (d f), and $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ (g i) MXenes. \n\nare restacked they do so randomly, while still maintaining crystallographic ordered along [000l]. The exact same conclusions can be reached for $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}$ (Figure 4b). In this case, the c-LP of the starting $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3}$ powder is about $23.6\\mathring{\\mathsf{A}}$ (bottom pattern in Figure 4b) and increases to $34.6\\mathring{\\mathsf{A}}$ after delamination (top pattern in Figure 4b), with that of the etched sample (middle pattern in Figure 4b) in between. \n\nScanning electron microscope (SEM) images of the parent MAX phases (Figure 4e,j), and their MXenes (Figure $4\\mathsf{f},\\mathsf{k})$ confirm the 3D to 2D transformation in both materials, as schematically shown in Figure 4c,d. So do HR STEM images of ${M o}_{2}\\mathrm{TiAlC}_{2}$ and $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ shown in Figure 4, panels g and $\\boldsymbol{\\mathsf{h}}$ , respectively. In the former, the Mo\u0001Ti layers are interleaved with Al layers; in the latter, the Al is absent. The atomic ordering of the Mo and Ti layers was confirmed by EDX mapping (Supporting Information, Figure S4), in which a layer of Ti (green) is sandwiched between two Mo layers (red). Lower magnification TEM image of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ flakes (Figure 4i) clearly shows its layered nature, even after etching. It is this order that gives rise to peaks ${\\approx}62^{\\circ}$ in the XRD patterns. A TEM image of a $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ flake and a low-magnification image of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ layers are shown in Supporting Information Figures S5 and S6a, respectively. \n\nA comparison of the HR STEM images of ${M o}_{2}{\\sf T i}_{2}{\\sf A l C}_{3}$ (Figure 4l) and $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}\\mathsf{T}_{x}$ (Figure $4\\mathsf{m},\\mathsf{n}$ ) again clearly evidence the removal of the Al layers by etching. The ordering of the Mo and Ti atoms, confirmed by EDX mapping (Supporting Information, Figure S4), is highlighted by red and green circles, respectively, in \n\nFigure $^{41,\\mathrm{m}}$ . After etching, the gaps between the MXene layers along [0001] are no longer as evenly spaced as they were in the parent phase (compare Figure ${49,\\mathsf{h}}$ , or Figure $^{41,\\mathfrak{n}}$ ). A low-magnification TEM image of the $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}$ layers is shown in Supporting Information, Figure S6b. \n\nWhen $\\mathsf{C r}_{2}\\mathsf{T i A l C}_{2}$ powders were etched in 6 M HCl with 5 mol equiv of LiF, for $42\\mathsf{h}$ at $55^{\\circ}\\mathsf{C},$ a characteristic MXene peak emerged (Supporting Information, Figure S7), presumably that of $\\mathsf{C r}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ . The c-LP was $24.3\\mathring{\\mathsf{A}}$ . However, in contrast to ${M o}_{2}{\\mathrm{TiC}}_{2}{\\mathrm{T}}_{X}$ (Figure 4a), we were not able to achieve $100\\%$ yield (see Supporting Information, Table S2), and completely rid the etched powders of the parent MAX phase. The same was true of $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3}$ (Figure 4b). Consequently, we focused the electrochemical work described below on the purest of the three, viz. $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}.$ . \n\nPrevious studies have shown that MXenes multilayers could be delaminated to single, or few-layer, MXene flakes by intercalation and sonication.23 Here, ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ was delaminated by first intercalating dimethyl sulfoxide (DMSO) between the layers, followed by sonication in water,23 as shown schematically in Figure 5a. After delamination, a stable ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ colloidal solution was obtained (Figure 5b), which, in turn, was used to form freestanding conductive $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ 'paper'23 (Figure 5c,d) by vacuum-assisted filtration. \n\nElectrochemistry of $\\mathsf{M o}_{2}\\bar{\\mathsf{I i C}}_{2}\\bar{\\mathsf{I}}_{x}.$ Since $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x},\\mathsf{T i}_{2}\\mathsf{C T}_{x}$ and other MXenes have previously shown promising performance in energy storage devices,17,23,34 we tested $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ 'paper' as electrodes for Li-ion batteries (LIBs). To prove that the Mo-layers are at the surface \n\n# ARTICLE \n\n![](images/6e179dc10edde37fec5e93d3b31c187b1f5260b71e71fba394e80be552908f4e.jpg) \nFigure 4. Synthesis and structure of ${M O}_{2}{\\mathsf{T i C}}_{2}$ and $M O_{2}\\mathsf{T i}_{2}C_{3}$ . (a) XRD patterns of ${\\mathsf{M o}}_{2}{\\mathsf{T i A l C}}_{2}$ before (red) and after (green) HF treatment and after delamination (blue). In the delaminated sample, only $\\cdot$ -direction peaks, (00l) peaks, are visible, corresponding to a $\\boldsymbol{\\mathsf{\\Sigma}}_{c}$ lattice parameter of $30.44\\mathring{A};$ the (110) peak is no longer observed, showing loss of order in nonbasal directions. (b) XRD patterns of $M O_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3}$ before (pink) and after (purple) HF treatment and after delamination (black). (c and d) Schematics of ${M o}_{2}\\mathsf{T i A l C}_{2}$ to $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ and $M\\circ_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3}$ to $\\pmb{M_{0}}_{2}\\pmb{\\top_{1}}_{2}\\pmb{\\subset_{3}}\\pmb{\\top_{x}}$ transformations, respectively; red, green, blue, and black circles represent Mo, Ti, Al, and C atoms, respectively. (e and $\\pmb{\\uparrow})$ SEM images of $\\mathsf{M o}_{2}\\mathsf{T i A l C}_{2}$ and $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x},$ respectively. Note the layers become open after etching in $\\ensuremath{M_{0}}_{2}\\ensuremath{\\mathrm{TiC}_{2}}\\ensuremath{\\mathsf{T}}_{x}$ . (g and h) HRSTEM of $\\mathsf{M o}_{2}\\mathsf{T i A l C}_{2}$ and $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x},$ respectively. Atoms are shown with the same colors as (c). Atomic ordering is confirmed by EDX mapping. No Al was observed in EDX of $\\ensuremath{M_{0}}_{2}\\ensuremath{\\mathsf{T i C}}_{2}\\ensuremath{\\mathsf{T}}_{x}$ . (i) Lower magnification TEM image of $(\\pmb{\\mathsf{f}})$ showing the layered structure throughout the sample. $\\mathfrak{j}$ and $\\mathbf{k})$ SEM images of $M\\circ_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3}$ and $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}\\mathsf{T}_{x},$ respectively. HRSTEM images of (l) ${\\mathsf{M o}}_{2}{\\mathsf{T i}}_{2}{\\mathsf{A l C}}_{3}$ and (m and n) $M O_{2}\\mathsf{T i}_{2}C_{3}$ . Atoms are shown with the same colors as (d). \n\n![](images/69358e01c031a89fb925b8f61578d506b0370b753beaa386eaa7f5b4501562a9.jpg) \nFigure 5. Delamination of $\\ensuremath{\\mathsf{M o}}_{2}\\ensuremath{\\mathsf{T i C}}_{2}$ . (a) Schematic showing delamination process used to produce single or few-layered ${M O}_{2}{\\mathsf{T i C}}_{2}$ sheets. (b) Photograph shows the Tyndall effect on a stable colloidal solution of ${\\mathsf{M o}}_{2}{\\mathsf{T i C}}_{2}$ in water. Low (c) and high (d) magnification cross-sectional SEM image of freestanding ${M O}_{2}{\\mathsf{T i C}}_{2}$ 'paper' fabricated by filtration of a stable colloidal solution; dotted lines in (c) show the film's cross section. MXene flakes are well aligned, but not too tightly packed in the 'paper'. \n\nand dictate the surface properties, we compared the electrochemical properties of ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ to those of \n\n$\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ . The cyclic voltammetry (CV) curves (Supporting Information, Figure 8a) show that much of the lithiation \n\n# ARTICLE \n\n![](images/17b78539512ad00356c6238c6cf914add14338a6d3e10149358f2442365d759d.jpg) \nFigure 6. Electrochemical performance of ${M O}_{2}{\\mathsf{T i C}}_{2}$ in LIB and supercapacitor electrodes. (a) Voltage profiles between 0.02 and 3 V vs ${\\mathsf{L i}}/{\\mathsf{L i}}^{+}$ at $\\mathsf{C}/10$ rate for the first 10 cycles. (b) Specific lithiation (squares) and delithiation (circles) capacities versus cycle number at 1 C and $\\mathsf{C}/10$ rates. Right axis in panel (b) shows the Columbic efficacies for cells tested at these rates. (c) Cyclic voltammograms, at different scan rates, for a freestanding electrode in 1 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ . (d) Capacitance retention test of ${M O}_{2}{\\mathsf{T i C}}_{2}$ 'paper' in 1 M ${\\sf H}_{2}\\mathsf{S}\\mathsf{O}_{4}$ . Inset shows galvanostatic cycling data collected at a current density of $1\\ A/{\\mathfrak{g}}$ . \n\nhappens at voltages less than ${\\sim}0.6\\lor v s\\lor\\mathrm{i}/\\mathrm{Li}^{+}$ . However, and although there is a broad peak at ${\\sim}1.3~\\mathsf{V}$ during charging, delithiation continues up to a voltage of $3\\vee$ A crucial and important distinction between previous and current results is the fact that here $85\\%$ of the total capacity is below $\\boldsymbol{1}\\lor$ compared to $<66\\%$ for $\\mathsf{N b}_{2}\\mathsf{C T}_{x}$ .17 \n\nThe discharge profile for a sample tested at a rate of $C/10$ (Figure 6a) shows a voltage plateau starting at about $0.6~\\mathsf{V}_{\\iota}$ , consistent with the appearance a discharge peak in the CVs (Supporting Information, Figure S8a). The first cycle discharge and charge capacities, at $C/10$ , are about 311 and $269\\ m A\\cdot h\\ g^{-1}$ , respectively, which translates to a Coulombic efficiency of $86\\%$ . The reason for this initial irreversible capacity is to be studied. After a few cycles, however, the Coulombic efficiency approaches $100\\%$ (Figure 6b). The first cycle irreversible capacities reported here ( $14\\%$ at $\\mathsf{C}/10$ and $27\\%$ at 1 C) are significantly lower than the $45-60\\%$ reported for other MXenes. ${14,17,23}_{\\mathsf{A t1}}\\mathsf{C},$ the ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ electrode showed a stable capacity of about $176\\mathrm{\\:mA}\\cdot\\mathrm{h}$ ${\\mathfrak{g}}^{-1}$ at the second cycle and retains about $82\\%$ of this capacity after 160 cycles (Figure 6b). About $92\\%$ of the capacity of $260\\mathsf{m A}{\\cdot}\\mathsf{h}\\mathsf{g}^{-1}$ is retained after 25 cycles at C/10. At both rates, Coulombic efficiencies higher than $97\\%$ were observed after the first cycle. \n\nTABLE 2. Calculated Li Adsorption Energies (eV/atom) of OH- and O-Terminated $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}_{2}\\ensuremath{\\mathsf{T i C}}_{2},$ , $M O_{3}C_{2},$ and $\\bar{\\mathsf{T i}}_{3}{\\mathsf{C}_{2}}^{a}$ \n\n\n
Li adsorption energy (eV/atom)
MXene composition
surface terminationMoTiCMoC2TiC2
OH0.070.030.17
-1.63-1.68-1.40
\n\na Note similarity between the two Mo-containing MXenes. \n\nThe fact that ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ and $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ are isostructural and only differ in the nature of their surface atoms, and yet exhibit significantly difference electrochemical behavior, is indirect evidence that the Ti atoms do not play a major role in the electrochemical behavior of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ and the latter acts as a pure Mo MXene. \n\nTo understand why $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ and $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ behave differently, we compared Li adsorption on $0H-$ and O-terminated $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{\\boldsymbol{x}},\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\boldsymbol{x}}$ and $\\mathsf{M o}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ (Table 2) and show that Li would rather adsorb onto the O terminations than the OH-ones. The fact that the adsorption energies for $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ and $\\mathsf{M o}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ surfaces are comparable and lower than those for $\\mathrm{Ti}_{3}C_{2}\\mathsf{T}_{x}$ confirms that the Mo-outer layers dominate the surface properties. Given that $\\mathsf{M o}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ is unstable (Table 1), the utility of having the ordered phases becomes clear. \n\nThe estimated theoretical Li capacity is 43 and 181 mA 3 h ${\\mathfrak{g}}^{-1}$ for OH- and O-terminated $\\mathsf{M o}_{2}\\mathsf{T i C}_{2},$ respectively. Since the capacity of the OH-terminated $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ is much smaller than the measured one ${\\sim}150\\ m\\mathsf{A}\\cdot\\mathsf{h}\\ \\mathsf{g}^{-1}$ , the lithiation should occur on the O terminations. Previous studies26,35 have shown that OH termination on MXene surfaces can be converted to O termination with metal ion adsorption. Therefore, the following lithiation reaction can be envisioned after the first cycle: \n\n$$\n\\mathsf{M}_{2}^{\\prime}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}\\mathsf{O}_{2}+2\\mathsf{L}\\mathsf{i}^{+}+2\\mathsf{e}^{-}{\\Longrightarrow}\\mathsf{L}\\mathsf{i}_{2}\\mathsf{M}_{2}^{\\prime}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}\\mathsf{O}_{2}\n$$ \n\nAlthough the predicted Li capacity of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{O}_{2}$ is close to experiments ${\\sim}150\\ m\\mathsf{A}\\cdot\\mathsf{h}\\ \\mathsf{g}^{-1}$ , the lithium insertion into interlayer spacing of MXene sheets should occur at ${\\sim}1.6\\lor v s\\lor\\lor\\lor\\cdots$ , which is much higher than the voltage where much of the lithiation happens $(\\sim0.6~\\lor~v s~\\mathsf{L i}/\\mathsf{L i}^{+})$ . Further simulations suggest that a conversion reaction: \n\n$$\n\\mathsf{L i}_{2}\\mathsf{M}_{2}^{\\prime}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}\\mathsf{O}_{2}+2\\mathsf{L i}^{+}+2\\mathsf{e}^{-}{\\Longrightarrow}\\mathsf{M}_{2}^{\\prime}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}+2\\mathsf{L i}_{2}\\mathsf{O}\n$$ \n\nmay also be possible. The enthalpy changes for eq 2 are $-0.74,-0.87,$ , and $+0.54$ eV/formula unit for ${\\cal M}\\circ_{2}\\mathsf{T i C}_{2}\\mathsf{O}_{2},$ $M\\circ_{3}{\\mathsf C}_{2}{\\mathsf O}_{2},$ and $\\Gamma_{1_{3}}C_{2}\\mathrm{O}_{2},$ , respectively. Clearly, the reaction is energetically favorable for Mo-based MXenes, but not for $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\mathsf{O}_{2}$ . Thus, below $0.7\\lor v s\\bot\\mathrm{i}/\\mathrm{Li}^{+}$ , reaction eq 2 should occur in $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{O}_{2}$ . The behavior of Mo-based MXenes resembles that of other Mo-based materials.36\u000138 The lithiation in Mo-based MXenes can be described by a two-step mechanism: stage I happens up to a potential of $1.6{\\sf V}$ and stage II corresponds to potentials below $0.6~\\mathsf{V}.$ . This mechanism may well explain why: (i) a voltage plateau is obtained in the Mocase, and (ii) the voltage profiles of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ are different from ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ . With the extra Li ions, the theoretical Li capacity of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{O}_{2}$ increases to $356\\mathsf{m A}{\\cdot}\\mathsf{h}\\mathsf{g}^{-1}$ . The latter value assumes that only one Li layer intercalates between the MXene layers. If more than one layer can intercalate,26 the theoretical capacity could be significantly higher (e.g., doubled, if a double-layer of Li formed between the MXene sheets, etc.).26 \n\nSimilar to other MXenes, adsorption is not limited to $\\mathsf{L i}^{+}$ .24 The adsorption energies of ${\\mathsf{L i}}^{+}$ , $\\mathsf{N a}^{+}$ , $\\mathsf{K}^{+}$ , ${\\mathsf{C}}{\\mathsf{s}}^{+}$ , $\\mathsf{M}\\mathsf{g}^{2+}$ , ${\\mathsf{C a}}^{2+}$ and $\\mathsf{A l}^{3+}$ ions on $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}({\\mathsf{O H}})_{2},\\mathsf{M o}_{3}\\mathsf{C}_{2}.$ $(\\mathsf{O H})_{2}$ and $T\\mathfrak{i}_{3}C_{2}(\\mathsf{O H})_{2}$ surfaces were computationally investigated. For the OH terminated surfaces, only ${\\mathsf{C}}{\\mathsf{s}}^{+}$ is stable (Supporting Information, Figure S9a). The rest presumably react with the OH terminations releasing ${\\sf H}_{2}$ and converting to O-terminated flakes.26 When the same cations were absorbed onto ${\\sf M o}_{2}{\\sf T i C}_{2}{\\sf O}_{2},$ $\\mathsf{M o}_{3}\\mathsf{C}_{2}\\mathsf{O}_{2}$ and $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\mathsf{O}_{2}$ surfaces (i.e., assuming eq 1 was operative), the opposite was observed (Supporting Information, Figure 9b): ${\\mathsf{C}}{\\mathsf{s}}^{+}$ was unstable, all the rest (with the exception of $\\mathsf{A l}^{3+}$ on $\\bar{\\mathsf{I i}}_{3}\\mathsf{C}_{2}\\mathsf{O}_{2})$ were stable. \n\nLastly, the enthalpy changes, at $0\\mathsf{K},$ assuming eq 2 is operative, for the various cations on the ${\\sf M o}_{2}{\\sf T i C}_{2}{\\sf O}_{2},$ ${M O}_{3}{C}_{2}{O}_{2}$ and $\\mathsf{T i}_{3}\\mathsf C_{2}\\mathsf O_{2}$ surfaces (Supporting Information, Figure $\\mathsf{S9c}$ ) suggest that reaction 2 is operative for $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{O}_{2}$ for all cations except ${\\mathsf{N a}}^{+}$ and $\\mathsf{K}^{+}$ . Said otherwise, ${\\sf M o}_{2}{\\sf T i C}_{2}{\\sf O}_{2},$ could, in principle, be used as an electrode in $\\mathsf{M}\\mathsf{g}^{2+}$ , ${\\mathsf{C a}}^{2+}$ , and $\\mathsf{A l}^{3+}$ -ion batteries. \n\nBecause $\\mathrm{Ti}_{3}C_{2}\\mathsf{T}_{x}$ has shown exceptional capacitance in aqueous electrolytes,21 we tested the capacitive behavior of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ 'paper' in 1 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ . While Mo is heavier than Ti and a lower gravimetric capacitance is expected, this difference in atomic weights should not significantly affect the volumetric capacitances. At potentials between $-0.1$ and $0.4~\\mathsf{V},$ the CV curves obtained (Figure 6c) were more rectangular compared to those previously reported for $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ .39 The working potential window also shifted by about $0.2\\:\\forall$ to more positive potentials. The charge is expected to be stored by intercalated cations and possibly redox contributions from changes in the Mo oxidation state, similar to $M\\circ{\\cal O}_{3}$ .40 At a scan rate of $2\\mathsf{m}\\mathsf{v}\\mathsf{s}^{-1}$ , the volumetric capacitance was calculated to be $413\\mathsf{F c m}^{-3}$ and $78\\%$ of this capacitance was retained at $100\\mathrm{\\mV\\}\\mathsf{s}^{-1}$ for a $3\\mu\\mathsf{m}$ thick film (Supporting Information, Figure S10a). Increasing the film thickness to $12\\ \\mu\\mathsf{m}$ reduced the volumetric capacitance to $342\\mathsf{F c m}^{-3}$ at a scan rate of $2\\mathsf{m}\\mathsf{v}\\mathsf{s}^{-1}$ and $167\\mathsf{F c m}^{-3}$ at a scan rate of $100\\mathrm{mV}\\mathsf{s}^{-1}$ . Galvanostatic charge discharge (GCD) tests at a $1\\mathsf{A}\\mathsf{g}^{1-}$ current density showed perfect triangular shapes with negligible IR drops at the beginning of the charge and discharge cycles (inset in Figure 6d). GCD tests also showed no degradation in performance of the electrodes after 10 000 cycles (Figure 6d). Electrochemical impedance spectroscopy (EIS) tests show a near ideal behavior of the electrodes at low frequencies, with close to vertical slope of the Nyquist plots (Supporting Information, Figure S10b). There is no reason to believe that the high values reported in this work cannot be further improved by selecting other MXenes. \n\n# CONCLUSIONS \n\nIn summary, we predict that at $0\\ \\mathsf{K},$ at least 26 ordered, double-M 2D carbides $(\\mathsf{M}^{\\prime}\\mathsf{M}^{\\prime\\prime}\\mathsf{X e n e})$ should be stable. On the basis of the DFT calculations, we identified two general trends for the stabilities of these ordered MXenes. The first is that M-elements whose binary carbides do not crystallize in the rock salt structure, like Mo and $C\\mathsf{r},$ avoid the center layers. The opposite is true for Nb and Ta; they prefer the middle layers. The relative stabilities of these compounds and their ordering could shift when entropy and surface terminations are taken into account. To verify DFT predictions, we synthesized $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x},$ $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{C}_{3}\\mathsf{T}_{x}$ and $\\mathsf{C r}_{2}\\mathsf{T i C}_{x}\\mathsf{T}_{x},$ and showed the electrochemical response of ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ to be dominated by the surface Mo layers. \n\n# ARTICLE \n\nLastly, we also expect nitrides and carbonitrides to show similar self-organizational behavior, further increasing the number of MXenes. It is reasonable to assume that the layering due to different sizes of M atoms will be even more pronounced in theoretically predicted MXene nanotubes,41 where placing smaller atoms in the inner layer will decrease strain and stress, increasing nanotube stability. Thus, numerous new structures with different transition metals in outer and inner layers and various surface terminations are possible, greatly expanding the family MXenes in particular and 2D materials in general. \n\n# ARTICLE \n\n# MATERIALS AND METHODS \n\nSynthesis of MAX Phases. The Mo-based MAX phases were synthesized by ball milling Mo, Ti, Al and graphite powders (all from Alfa Aesar, Ward Hill, MA), with mesh sizes of $-250,$ , $-325,-325$ , and $-300$ , respectively, for $18\\mathsf{h}$ using zirconia balls in plastic jars. The Mo/Ti/Al/C molar ratios were 2:1:1.1:2 and 2:2:1.3:2.7 for the ${M o}_{2}\\mathsf{T i A l C}_{2}$ and $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3},$ respectively. Powder mixtures were heated in covered alumina crucibles at $5^{\\circ}C/\\mathsf{m i n}$ to $1600^{\\circ}\\mathsf C$ and held for $4h$ under flowing argon. After cooling, the porous compacts were milled using a TiN-coated milling bit and sieved through a 400 mesh sieve, producing powders with a particle size $<38\\ \\mu\\mathsf{m}$ . Notably, this is the first report on the existence of the $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3}$ phase. $\\mathsf{C r}_{2}\\mathsf{T i A l C}_{2}$ was synthesized by heating an elemental mixture of Cr, Ti, Al and C at $1500^{\\circ}{\\mathsf{C}}$ for $1\\mathfrak{h}$ under Ar flow. Further details can be found in Supporting Information. \n\nSynthesis of MXenes. Two grams of ${M o}_{2}\\mathrm{TiAlC}_{2}$ or ${M o}_{2}{\\sf T i}_{2}{\\sf A l C}_{3}$ powders was added, over ${\\approx}60~5,$ to $20~\\mathrm{ml}$ of $48-51\\%$ aqueous HF solution and held at ambient temperature $(55~^{\\circ}C$ for $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3})$ for $48\\mathrm{~h~}$ $90\\mathsf{h}$ for $\\mathsf{M o}_{2}\\mathsf{T i}_{2}\\mathsf{A l C}_{3})$ while stirring with a magnetic Teflon coated bar, rotating at 200 rpm. The mixtures were washed 5 times by adding distilled water, shaking for 1 min, centrifuging at 3500 rpm for 120 s for each cycle and finally decanted. After the last centrifugation, the pH of the supernatant was $^{>6}$ . The final product was mixed with distilled water and filtered on a membrane (3501 Coated PP, Celgard, Charlotte, NC). $\\mathsf{C r}_{2}\\mathsf{T i C}_{2}$ synthesis is described in Supporting Information. \n\nPreparation and Testing of LIB Electrodes. Electrodes were prepared by mixing the MXene powders, carbon black and $10\\mathsf{w t}\\%$ polyvinylidene fluoride dissolved in 1-methyl-2-pyrrolidinone (all from Alfa Aesar, Ward Hill, MA) in a 80:10:10 ratio by weight. The mixture was coated onto a copper foil using a doctor blade and dried under vacuum at $140~^{\\circ}\\mathsf{C}$ for $24~\\mathsf{h}$ . Coin cells were assembled using Li foil and two layers of Celgard separators. The electrolyte was 1 M solution of $\\mathsf{L i P F}_{6}$ in a 1:1 mixture of ethylene carbonate and diethyl carbonate. Electrochemical studies were performed using a potentiostat (VMP3, Biologic, France). \n\nDelamination of ${M O}_{2}\\bar{\\Pi}\\mathbf{C}_{2}\\bar{\\Pi}_{X}$ and Preparation of MXene 'Paper'. About 1 g of multilayered $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ powder was mixed with $10\\mathrm{ml}$ of DMSO and the mixture was stirred for $24\\mathsf{h}$ at room temperature. The resulting colloidal suspension was centrifuged to separate the intercalated powder from the liquid DMSO. After decantation of the supernatant, $100\\mathsf{m l}$ of deionized water was added to the residue and the mixture was sonicated for $1\\ h,$ before centrifuging it for $1\\mathrm{~h~}$ at 3500 rpm. Lastly, the supernatant was decanted and filtered, using a Celgard membrane, and dried under vacuum. \n\nElectrochemical Capacitor Fabrication and Testing. Electrodes based on multilayered ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ were prepared by rolling a mixture of ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ powders, acetylene carbon black (Alfa Aesar) and polytetrafluoroethylene (PTFE) binder (60 wt $\\%$ solution in water, Aldrich, St. Louis MO). Rolled films, $\\sim80\\mu\\mathrm{m}$ thick, were punched into $10~\\mathsf{m m}$ discs. The delaminated ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ 'paper' was tested in 1 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ electrolyte using 3-electrode Swagelok cells, where the MXene served as working electrode, an overcapacitive activated carbon film was used as a counter electrode, and $\\mathsf{A g/A g C l}$ in 1 M KCl was the reference electrode.39 \n\nMicrostructural Characterization. XRD was carried out on a Rigaku Smartlab (Tokyo, Japan) diffractometer using Cu KR radiation $(40\\up k\\upnu$ and $44\\mathsf{m A}$ ); step scan $0.02^{\\circ},3^{\\circ}-80^{\\circ}2\\theta$ range, step time of 7 s, $10\\times10\\mathsf{m m}^{2}$ window slit. Ten wt $\\%$ of silicon powder was added to the MAX powders as an internal standard. A SEM (Zeiss Supra 50VP, Germany) equipped with EDX (Oxford Inca X-Sight, Oxfordshire, U.K.) was used. HR STEM and EDX analyses were carried out with a double corrected FEI Titan 3 operated at $300\\mathsf{k V},$ equipped with the Super-X EDX system. Selected area electron diffraction (SAED) characterization was performed using a FEI Tecnai G2 TF20 UT field emission microscope at $200\\mathsf{k V}$ and a point resolution of $0.19\\mathsf{n m}$ . The specimens were prepared by embedding the powder in a Ti grid, reducing the Ti-grid thickness down to $50\\mu\\mathsf{m}$ via mechanical polishing and finally $\\mathsf{A}\\mathsf{r}^{+}$ ion milling to reach electron transparency. \n\nDensity Functional Theory Simulations. First-principles calculations were carried out using ${\\mathsf{D F T}}^{42}$ and the all-electron projected augmented wave $\\left(\\mathsf{P A W}\\right)^{43}$ method as implemented in the Vienna ab initio simulation package (VASP).44 A plane-wave cutoff energy of $580~\\mathrm{eV}$ is sufficient to ensure convergence of the total energies to 1 meV per primitive cell. For the exchangecorrelation energy, we used the Perdue-Burke-Ernzerhof (PBE) version of the generalized gradient approximation (GGA).45 Considering the strong correlation effects in transition metals, electronic structure calculations and structural relaxations were performed using a spin-dependent GGA plus Hubbard U $(\\mathsf{G G A}\\ +\\ \\mathsf{U})^{46}$ method. More details can be found in the Supporting Information. \n\nConflict of Interest: The authors declare no competing financial interest. \n\nAcknowledgment. Synthesis of MAX phases and MXenes at Drexel University was funded by a grant from the U.S. Army Research Office under Grant Number W911NF-14-1-0568. We thank the Centralized Research Facility of Drexel University for access to XRD and SEM equipment. Electrochemical studies and DFT work were supported as part of the Fluid Interface Reactions, Structures and Transport (FIRST) Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The Linköping Electron Microscopy Laboratory was supported by the Knut and Alice Wallenberg Foundation. L.H., J.L., and M.W.B. acknowledge support from the Swedish Research Council. Crystal structures schematics were produced using VESTA.47 \n\nSupporting Information Available: The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.5b03591. \n\nComputational details and full range of $\\mathsf{M}^{\\prime}{}_{2}\\mathsf{M}^{\\prime\\prime}\\mathsf{C}_{2}$ and $M^{\\prime}{}_{2}M^{\\prime\\prime}{}_{2}C_{3}$ configurations and complete energy profiles for all unterminated $M^{\\prime}M^{\\prime\\prime}$ Xenes, EDX results of all the MAX and MXenes phases synthesized in this study, HR STEM with EDX of both $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ and ${M O}_{2}{\\mathrm{Ti}}_{2}{\\mathrm{C}}_{3}$ , TEM images of a $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}$ sheet and low-magnification TEM images of ${M O}_{2}{\\mathrm{TiC}}_{2}$ and ${M O}_{2}{\\mathrm{Ti}}_{2}{\\mathrm{C}}_{3},$ synthesis method of $\\mathsf{C r}_{2}\\mathsf{T i C}_{2},$ electrochemical performance of ${M o}_{2}{\\sf T i C}_{2}{\\sf T}_{X}$ as LIB and supercapacitor electrodes, and ions adsorption energies on different MXenes (PDF) \n\n# REFERENCES AND NOTES \n\n1. Nicolosi, $\\mathsf{v}.,$ Chhowalla, M.; Kanatzidis, M. G.; Strano, M. S.; Coleman, J. N. Liquid Exfoliation of Layered Materials. Science 2013, 340, 1226419. \n\n2. Geim, A.; Grigorieva, I. Van der Waals Heterostructures. Nature 2013, 499, 419–425. 3. Berger, C.; Song, Z.; Li, T.; Li, X.; Ogbazghi, A. Y.; Feng, R.; Dai, Z.; Marchenkov, A. N.; Conrad, E. H.; First, P. N.; et al. Ultrathin Epitaxial Graphite: 2D Electron Gas Properties and a Route toward Graphene-based Nanoelectronics. J. Phys. Chem. B 2004, 108, 19912–19916. 4. Allen, M. J.; Tung, V. C.; Kaner, R. B. Honeycomb Carbon: A Review of Graphene. Chem. Rev. 2010, 110, 132–145. 5. Geim, A. K. Graphene: Status and Prospects. Science 2009, 324, 1530–1534. 6. Lv, R.; Robinson, J. A.; Schaak, R. E.; Sun, D.; Sun, Y.; Mallouk, T. E.; Terrones, M. Transition Metal Dichalcogenides and Beyond: Synthesis, Properties, and Applications of Singleand Few-Layer Nanosheets. Acc. Chem. Res. 2015, 48, 56–64. \n7. Gong, Y.; Liu, Z.; Lupini, A. R.; Shi, G.; Lin, J.; Najmaei, S.; Lin, Z.; Elías, A. L.; Berkdemir, A.; You, G.; et al. Band Gap Engineering and Layer-by-Layer Mapping of SeleniumDoped Molybdenum Disulfide. Nano Lett. 2014, 14, 442– 449. 8. Butler, S. Z.; Hollen, S. M.; Cao, L.; Cui, Y.; Gupta, J. A.; Gutiérrez, H. R.; Heinz, T. F.; Hong, S. S.; Huang, J.; Ismach, A. F.; et al. Progress, Challenges, and Opportunities in Two-Dimensional Materials Beyond Graphene. ACS Nano 2013, 7, 2898–2926. 9. Taha-Tijerina, J.; Narayanan, T. N.; Gao, G.; Rohde, M.; Tsentalovich, D. A.; Pasquali, M.; Ajayan, P. M. Electrically Insulating Thermal Nano-Oils Using 2D Fillers. ACS Nano 2012, 6, 1214–1220. \n10. Wang, Q. H.; Kalantar-Zadeh, K.; Kis, A.; Coleman, J. N.; Strano, M. S. Electronics and Optoelectronics of Two-Dimensional Transition Metal Dichalcogenides. Nat. Nanotechnol. 2012, 7, 699–712. \n11. Osada, M.; Sasaki, T. Exfoliated Oxide Nanosheets: New Solution to Nanoelectronics. J. Mater. Chem. 2009, 19, 2503–2511. \n12. Sugimoto, W.; Iwata, H.; Yasunaga, Y.; Murakami, Y.; Takasu, Y. Preparation of Ruthenic Acid Nanosheets and Utilization of Its Interlayer Surface for Electrochemical Energy Storage. Angew. Chem., Int. Ed. 2003, 42, 4092–4096. \n13. Rui, X.; Lu, Z.; Yu, H.; Yang, D.; Hng, H. H.; Lim, T. M.; Yan, Q. Ultrathin $V_{2}O_{5}$ Nanosheet Cathodes: Realizing Ultrafast Reversible Lithium Storage. Nanoscale 2013, 5, 556–560. \n14. Naguib, ${\\sf M}_{\\dot{\\cdot}\\dot{\\prime}}$ Come, J.; Dyatkin, B.; Presser, V.; Taberna, P.-L.; Simon, P.; Barsoum, M. W.; Gogotsi, Y. MXene: A Promising Transition Metal Carbide Anode for Lithium-Ion Batteries. Electrochem. Commun. 2012, 16, 61–64. \n15. Naguib, M.; Kurtoglu, M.; Presser, V.; Lu, J.; Niu, J.; Heon, M.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Nanocrystals Produced by Exfoliation of $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ . Adv. Mater. 2011, 23, 4248–4253. \n16. Naguib, M.; Mochalin, V. N.; Barsoum, M. W.; Gogotsi, Y. MXenes: A New Family of Two-Dimensional Materials. Adv. Mater. 2014, 26, 982–982. \n17. Naguib, M.; Halim, J.; Lu, J.; Cook, K. M.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. New Two-Dimensional Niobium and Vanadium Carbides as Promising Materials for Li-ion Batteries. J. Am. Chem. Soc. 2013, 135, 15966–15969. \n18. Kurtoglu, M.; Naguib, M.; Gogotsi, Y.; Barsoum, M. W. First Principles Study of Two-Dimensional Early Transition Metal Carbides. MRS Commun. 2012, 2, 133–137. \n19. Hu, Q.; Wang, H.; Wu, $\\mathsf{Q}.$ ; Ye, X.; Zhou, A.; Sun, D.; Wang, L.; Liu, B.; He, J. Two-Dimensional $\\mathsf{S c}_{2}\\mathsf{C}:$ A Reversible and High-Capacity Hydrogen Storage Material Predicted by First-Principles Calculations. Int. J. Hydrogen Energy 2014, 39, 10606–10612. \n20. Khazaei, M.; Arai, M.; Sasaki, T.; Chung, C.-Y.; Venkataramanan, N. S.; Estili, M.; Sakka, Y.; Kawazoe, Y. Novel Electronic and Magnetic Properties of Two-Dimensional Transition Metal Carbides and Nitrides. Adv. Funct. Mater. 2013, 23, 2185–2192. \n21. Ghidiu, M.; Lukatskaya, M. R.; Zhao, M.-Q.; Gogotsi, Y.; Barsoum, M. W. Conductive Two-Dimensional Titanium Carbide 'Clay' with High Volumetric Capacitance. Nature 2014, 516, 78–81. \n22. Liang, X.; Garsuch, A.; Nazar, L. F. Sulfur Cathodes Based on Conductive MXene Nanosheets for High-Performance Lithium\u0001Sulfur Batteries. Angew. Chem., Int. Ed. 2015, 54, 3907–3911. \n23. Mashtalir, O.; Naguib, M.; Mochalin, V. N.; Dall'Agnese, Y.; Heon, M.; Barsoum, M. W.; Gogotsi, Y. Intercalation and Delamination of Layered Carbides and Carbonitrides. Nat. Commun. 2013, 4, 1716. \n24. Xie, Y.; Dall'Agnese, Y.; Naguib, M.; Gogotsi, Y.; Barsoum, M. W.; Zhuang, H. L.; Kent, P. R. C. Prediction and Characterization of MXene Nanosheet Anodes for NonLithium-Ion Batteries. ACS Nano 2014, 8, 9606–9615. \n25. Tang, Q.; Zhou, Z.; Shen, P. Are MXenes Promising Anode Materials for Li Ion Batteries? Computational Studies on Electronic Properties and Li Storage Capability of $\\mathsf{T i}_{3}\\mathsf{C}_{2}$ and $\\bar{\\Pi}_{1_{3}}\\mathsf C_{2}\\mathsf X_{2}$ ${\\mathrm{X}}={\\mathsf{F}},$ , OH) Monolayer. J. Am. Chem. Soc. 2012, 134, 16909–16916. \n26. Xie, Y.; Naguib, M.; Mochalin, V. N.; Barsoum, M. W.; Gogotsi, Y.; Yu, X.; Nam, K.-W.; Yang, $x.-\\mathsf{Q}.;$ Kolesnikov, A. I.; Kent, P. R. C. Role of Surface Structure on Li-Ion Energy Storage Capacity of Two-Dimensional Transition-Metal Carbides. J. Am. Chem. Soc. 2014, 136, 6385–6394. \n27. Er, D.; Li, J.; Naguib, M.; Gogotsi, Y.; Shenoy, V. B. $\\mathsf{T i}_{3}\\mathsf{C}_{2}$ MXene as a High Capacity Electrode Material for Metal (Li, Na, K, Ca) Ion Batteries. ACS Appl. Mater. Interfaces 2014, 6, 11173–11179. \n28. Liu, Z.; Zheng, L.; Sun, $\\mathsf{L}.\\mathsf{\\Omega}$ Qian, Y.; Wang, J.; Li, M. $(\\mathsf{C r}_{2/3}\\mathsf{T i}_{1/3})_{3}$ - ${\\mathsf{A l C}}_{2}$ and $(C r_{5/8}\\mathsf{T i}_{3/8})_{4}\\mathsf{A l C}_{3}$ : New MAX-phase Compounds in $T i-C r-A l-C$ System. J. Am. Ceram. Soc. 2014, 97, 67–69. \n29. Anasori, $\\mathsf{B}_{\\cdot,\\prime}$ Halim, J.; Lu, J.; Voigt, C. A.; Hultman, L.; Barsoum, M. W. ${M o}_{2}\\mathsf{T i A l C}_{2}$ : A New Ordered Layered Ternary Carbide. Scr. Mater. 2015, 101, 5–7. \n30. Anasori, B.; Dahlqvist, M.; Halim, J.; Moon, E. J.; Lu, J.; Hosler, B. C.; Caspi, E. N.; May, S.; Hultman, L.; Eklund, P.; Rose\u0001n, J.; Barsoum, M. W. Experimental and Theoretical Characterization of Ordered MAX Phases ${M o}_{2}\\mathrm{TiAlC}_{2}$ and ${M o}_{2}{\\mathrm{Ti}}_{2}{\\mathsf{A l C}}_{3}$ . J. Appl. Phys. 2015, In Press. \n31. Hugosson, H. W.; Eriksson, O.; Nordström, L.; Jansson, U.; Fast, L.; Delin, A.; Wills, J. M.; Johansson, B. Theory of Phase Stabilities and Bonding Mechanisms in Stoichiometric and Substoichiometric Molybdenum Carbide. J. Appl. Phys. 1999, 86, 3758–3767. \n32. Enyashin, A. N.; Ivanovskii, A. L. Two-Dimensional Titanium Carbonitrides and Their Hydroxylated Derivatives: Structural, Electronic Properties and Stability of MXenes $T\\mathsf{i}_{3}C_{2-\\times}\\mathsf{N}_{\\times}(\\mathsf{O H})_{2}$ from DFTB Calculations. J. Solid State Chem. 2013, 207, 42–48. \n33. Ghidiu, M.; Naguib, M.; Shi, C.; Mashtalir, O.; Pan, L. M.; Zhang, B.; Yang, J.; Gogotsi, Y.; Billinge, S. J. L.; Barsoum, M. W. Synthesis and Characterization of Two-Dimensional $N b_{4}C_{3}$ (MXene). Chem. Commun. 2014, 50, 9517–9520. \n34. Wang, X.; Kajiyama, S.; Iinuma, H.; Hosono, E.; Oro, S.; Moriguchi, I.; Okubo, M.; Yamada, A. Pseudocapacitance of MXene Nanosheets for High-Power Sodium-Ion Hybrid Capacitors. Nat. Commun. 2015, 6, 6544. \n35. Peng, Q.; Guo, J.; Zhang, $\\mathsf{Q}.;$ Xiang, J.; Liu, B.; Zhou, A.; Liu, R.; Tian, Y. Unique Lead Adsorption Behavior of Activated Hydroxyl Group in Two-Dimensional Titanium Carbide. J. Am. Chem. Soc. 2014, 136, 4113–4116. \n36. Meduri, P.; Clark, E.; Kim, J. H.; Dayalan, E.; Sumanasekera, G. $\\mathsf{u}_{\\cdot}$ Sunkara, M. K. $\\mathsf{M o O}_{3-\\mathsf{x}}$ Nanowire Arrays As Stable and High-Capacity Anodes for Lithium Ion Batteries. Nano Lett. 2012, 12, 1784–1788. \n37. Stephenson, T.; Li, Z.; Olsen, B.; Mitlin, D. Lithium Ion Battery Applications of Molybdenum Disulfide $(M\\circ S_{2})$ ) Nanocomposites. Energy Environ. Sci. 2014, 7, 209–231. \n38. Liu, Y.; Zhang, H.; Ouyang, P.; Chen, W.; Wang, Y.; Li, Z. High Electrochemical Performance and Phase Evolution of Magnetron Sputtered $M\\circ\\mathsf{O}_{2}$ Thin Films with Hierarchical Structure for Li-Ion Battery Electrodes. J. Mater. Chem. A 2014, 2, 4714–4721. \n39. Lukatskaya, M. R.; Mashtalir, O.; Ren, C. E.; Dall'Agnese, Y.; Rozier, P.; Taberna, P. L.; Naguib, M.; Simon, P.; Barsoum, M. W.; Gogotsi, Y. Cation Intercalation and High Volumetric \n\n# ARTICLE \n\n# ARTICLE \n\nCapacitance of Two-Dimensional Titanium Carbide. Science 2013, 341, 1502–1505. \n40. Brezesinski, T.; Wang, J.; Tolbert, S. H.; Dunn, B. Ordered Mesoporous [alpha]- ${\\cdot}M\\circ{\\mathsf{O}}_{3}$ with Iso-Oriented Nanocrystalline Walls for Thin-Film Pseudocapacitors. Nat. Mater. 2010, 9, 146–151. \n41. Enyashin, A.; Ivanovskii, A. Atomic Structure, Comparative Stability and Electronic Properties of Hydroxylated $\\pi_{1_{2}}C$ and $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ Nanotubes. Comput. Theor. Chem. 2012, 989, 27–32. \n42. Kohn, W.; Sham, L. J. Self-Consistent Equations Including Exchange and Correlation Effects. Phys. Rev. 1965, 140, A1133. \n43. Blöchl, P. E. Projector Augmented-Wave Method. Phys. Rev. B: Condens. Matter Mater. Phys. 1994, 50, 17953. \n44. Kresse, G.; Furthmüller, J. Efficient Iterative Schemes for Ab Initio Total-Energy Calculations Using a Plane-Wave Basis Set. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 11169. \n45. Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865. \n46. Dudarev, S.; Botton, G.; Savrasov, S.; Humphreys, C.; Sutton, A. Electron-Energy-Loss Spectra and the Structural Stability of Nickel Oxide: An $\\mathsf{L S D A+}$ U Study. Phys. Rev. B: Condens. Matter Mater. Phys. 1998, 57, 1505. \n47. Momma, K.; Izumi, F. VESTA 3 for Three-Dimensional Visualization of Crystal, Volumetric and Morphology Data. J. Appl. Crystallogr. 2011, 44, 1272–1276. " + }, + { + "id": "10.1038_nmat4205", + "DOI": "10.1038/nmat4205", + "DOI Link": "http://dx.doi.org/10.1038/nmat4205", + "Relative Dir Path": "mds/10.1038_nmat4205", + "Article Title": "Light-emitting diodes by band-structure engineering in van der Waals heterostructures", + "Authors": "Withers, F; Del Pozo-Zamudio, O; Mishchenko, A; Rooney, AP; Gholinia, A; Watanabe, K; Taniguchi, T; Haigh, SJ; Geim, AK; Tartakovskii, AI; Novoselov, KS", + "Source Title": "NATURE MATERIALS", + "Abstract": "The advent of graphene and related 2D materials1,2 has recently led to a new technology: heterostructures based on these atomically thin crystals(3). The paradigm proved itself extremely versatile and led to rapid demonstration of tunnelling diodes with negative differential resistance(4), tunnelling transistors(5), photovoltaic devices(6,7) and so on. Here, we take the complexity and functionality of such van der Waals heterostructures to the next level by introducing quantum wells (QWs) engineered with one atomic plane precision. We describe light-emitting diodes (LEDs) made by stacking metallic graphene, insulating hexagonal boron nitride and various semiconducting monolayers into complex but carefully designed sequences. Our first devices already exhibit an extrinsic quantum efficiency of nearly 10% and the emission can be tuned over a wide range of frequencies by appropriately choosing and combining 2D semiconductors (monolayers of transition metal dichalcogenides). By preparing the heterostructures on elastic and transparent substrates, we show that they can also provide the basis for flexible and semi-transparent electronics. The range of functionalities for the demonstrated heterostructures is expected to grow further on increasing the number of available 2D crystals and improving their electronic quality.", + "Times Cited, WoS Core": 1407, + "Times Cited, All Databases": 1559, + "Publication Year": 2015, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000350136400017", + "Markdown": "# Light-emitting diodes by band-structure engineering in van der Waals heterostructures \n\nF. Withers1, O. Del Pozo-Zamudio2, A. Mishchenko1, A. P. Rooney3, A. Gholinia3, K. Watanabe4, T. Taniguchi4, S. J. Haigh3, A. K. Geim5, A. I. Tartakovskii2 and K. S. Novoselov1\\* \n\nThe advent of graphene and related 2D materials1,2 has recently led to a new technology: heterostructures based on these atomically thin crystals3. The paradigm proved itself extremely versatile and led to rapid demonstration of tunnelling diodes with negative diferential resistance4, tunnelling transistors5, photovoltaic devices6,7 and so on. Here, we take the complexity and functionality of such van der Waals heterostructures to the next level by introducing quantum wells (QWs) engineered with one atomic plane precision. We describe light-emitting diodes (LEDs) made by stacking metallic graphene, insulating hexagonal boron nitride and various semiconducting monolayers into complex but carefully designed sequences. Our first devices already exhibit an extrinsic quantum efciency of nearly $10\\%$ and the emission can be tuned over a wide range of frequencies by appropriately choosing and combining 2D semiconductors (monolayers of transition metal dichalcogenides). By preparing the heterostructures on elastic and transparent substrates, we show that they can also provide the basis for flexible and semi-transparent electronics. The range of functionalities for the demonstrated heterostructures is expected to grow further on increasing the number of available 2D crystals and improving their electronic quality. \n\nThe class of two-dimensional (2D) atomic crystals1, which started with graphene2, now includes a large variety of materials. However, even larger diversity can be achieved if one starts to combine several such crystals in van der Waals heterostructures3,8. Most attractive and powerful is the idea of band-structure engineering, where by combining several different 2D crystals one can create a designer potential landscape for electrons to live in. Rendering the band structure with atomic precision allows tunnel barriers, QWs and other structures, based on the broad choice of 2D materials. \n\nSuch band-structure engineering has previously been exploited to create LEDs and lasers based on semiconductor heterostructures grown by molecular beam epitaxy9. Here we demonstrate that using graphene as a transparent conductive layer, hexagonal boron nitride (hBN) as tunnel barriers and different transition metal dichalcogenides1,10 (TMDCs) as the materials for QWs, we can create efficient LEDs (Fig. 1f). In our devices, electrons and holes are injected into a layer of TMDC from the two graphene electrodes. As a result of the long lifetime of the quasiparticles in the QWs (determined by the height and thickness of the neighbouring hBN barriers), electrons and holes recombine, emitting a photon. The emission wavelength can be fine-tuned by the appropriate selection of TMDC and quantum efficiency (QE) can be enhanced by using multiple QWs (MQWs). \n\nWe chose TMDCs because of wide choice of such materials and the fact that monolayers of many TMDCs are direct-bandgap semiconductors11–15. Until now, electroluminescence (EL) in TMDC devices has been reported only for lateral monolayer devices and attributed to thermally assisted processes arising from impact ionization across a Schottky barrier16 and formation of $\\mathtt{p-n}$ junctions15,17,18. The use of vertical heterostructures allows us to improve the performance of LEDs in many respects: reduced contact resistance, higher current densities allowing brighter LEDs, luminescence from the whole device area (Fig. 1e,f) and wider choice of TMDCs and their combinations allowed in designing such heterostructures. The same technology can be extended to create other QW-based devices such as indirect excitonic devices19, LEDs based on several different QWs and lasers. \n\nFigure 1 schematically shows the architecture of singlequantum-well (SQW) and MQW structures along with optical images of a typical device (Fig. 1e). We used a peel/lift van der Waals technique20 to produce our devices (see Methods and Supplementary Information for further details on device fabrication). In total we measured more than a dozen of such QW structures comprising single and multiple layers of TMDC flakes from different materials: $\\mathbf{MoS}_{2}$ , $\\mathrm{WS}_{2}$ and ${\\mathrm{WSe}}_{2}$ . The yield was $100\\%$ with every device showing strong EL that remains unchanged after months of periodic measurements, which demonstrates the robustness of the technology and materials involved. \n\nCross-sectional bright-field scanning transmission electron microscope (STEM) images of our SQW and MQW devices demonstrate that the heterostructures are atomically flat and free from interlayer contamination21 (Fig. $^{1\\mathrm{b,d}},$ ). The large atomic numbers for TMDCs allow the semiconductor crystals to be clearly identified owing to strong electron-beam scattering (dark contrast observed in Fig. $^{1\\mathrm{b,d}}.$ ). Other layers were identified by energy-dispersive X-ray spectroscopy. The large intensity variation partially obscures the lattice contrast between adjacent layers but, despite this, the hBN lattice fringes can clearly be seen in Fig. $^{1\\mathrm{b,d}}$ . The different contrast of the four $\\mathbf{MoS}_{2}$ monolayers in the MQW of Fig. 1d is attributed to their different crystallographic orientations (confirmed by rotating the sample around the heterostructure’s vertical direction, which changes the relative intensity of different layers). \n\nFor brevity we concentrate on current–voltage $(I-V)$ characteristics, photoluminescence (PL) and EL spectra from symmetric devices based on $\\mathbf{MoS}_{2}$ (Fig. 2a–c). Devices based on $\\mathrm{WS}_{2}$ and devices with asymmetric barriers are considered in the Supplementary Information. \n\n![](images/091c049e494445d50e2db16d98ae1c9da378502ed4c900d18e4d1a84c55ad6ef.jpg) \nFigure 1 | Heterostructure devices with a SQW and MQWs. a, Schematic of the SQW heterostructure hBN/GrB/2hBN/WS2/2hBN/GrT/hBN. b, Cross-sectional bright-field STEM image of the type of heterostructure presented in a. Scale bar, 5 nm. c,d, Schematic and STEM image of the MQW heterostructure hBN/GrB/2hBN/MoS2/2hBN/MoS2/2hBN/MoS2/2hBN/MoS2/2hBN/GrT/hBN. The number of hBN layers between ${M o S}_{2}$ QWs in d varies. Scale bar, $5\\mathsf{n m}$ . e, Optical image of an operational device (hBN/GrB/3hBN/MoS2/3hBN/GrT/hBN). The dashed curve outlines the heterostructure area. Scale bar, $10\\upmu\\mathrm{m}$ . f, Optical image of EL from the same device. $V_{\\flat}=2.5\\:\\vee,$ , ${\\bar{T}}=3001$ . 2hBN and 3hBN stand for bi- and trilayer hBN, respectively. g, Schematic of our heterostructure consisting of Si/SiO2/hBN/GrB/3hBN/MoS2/3hBN/GrT/hBN. h–j, Band diagrams for the case of zero applied bias ${\\bf\\Pi}({\\bf h})$ , intermediate applied bias (i) and high bias (j) for the heterostructure presented in g. \n\nAt low $V_{\\mathrm{b}}$ , the PL in Fig. 2a is dominated by the neutral A exciton, $\\mathrm{X}^{0}$ , peak12 at $1.93\\mathrm{eV.}$ We attribute the two weaker and broader peaks at 1.87 and $1.79\\mathrm{eV}$ to bound excitons22,23. At a certain $V_{\\mathrm{b}}$ , the PL spectrum changes abruptly with another peak emerging at $1.90\\mathrm{eV}.$ This transition is correlated with an increase in the differential conductivity (Fig. 2a). We explain this transition as being due to the fact that at this voltage the Fermi level in the bottom graphene electrode $\\displaystyle\\left(\\mathrm{Gr_{B}}\\right)$ ) rises above the conduction band in $\\mathbf{MoS}_{2}$ , allowing injection of electrons into the QW (Fig. 1i). This allows us to determine the band alignment between the Dirac point in graphene and the bottom of the conductance band in $\\mathbf{MoS}_{2}$ : the offset equals half of the bias voltage at which the tunnelling through states in the conductance band of $\\mathbf{MoS}_{2}$ is first observed. To take into account the effects of possible variance in the thickness of hBN barriers and small intrinsic doping of graphene, we average the onset of tunnelling through $\\mathbf{MoS}_{2}$ for positive and negative bias voltages (Fig. 2a), which yields the offset to be ${\\sim}0.5\\mathrm{eV}$ —in agreement with theoretical prediction24,25. Note, that the alignment of graphene’s Dirac point with respect to the valence band in hBN has been measured in tunnelling experiments previously5,26,27. \n\n![](images/22dba1ba06751412c699406ce9139511d13b3842036087b76c94064d62dae219.jpg) \nFigure 2 | Optical and transport characterization of our SQW devices, ${\\boldsymbol{\\tau}}=7{\\boldsymbol{\\upkappa}}.$ a, Colour map of the PL spectra as a function of $V_{\\mathrm{b}}$ for a ${M o S}_{2}$ -based SQW. The white curve is the ${\\mathsf{d}}I/{\\mathsf{d}}V_{\\flat}$ of the device. Excitation energy $E_{\\mathrm{l}}=2.33\\mathrm{eV}.$ b, EL spectra as a function of $V_{\\mathfrak{b}}$ for the same device as in a. White curve: its $j-V_{\\mathrm{b}}$ characteristic $(j$ is the current density). c, Comparison of the PL and EL spectra for the same device. As PL and EL occur in the same spectral range, we measured them separately. $\\mathbf{d}\\mathbf{-g},$ The same as in b,c but for the bilayer (d,e) and monolayer $\\mathbf{\\Gamma}(\\mathbf{f},\\mathbf{g})$ ${\\mathsf{W S}}_{2}$ QWs. The PL curves were taken at $V_{\\mathrm{b}}{=}2.4\\:\\forall$ (c), $2.5\\mathsf{V}$ (e) and 2 V $\\mathbf{\\sigma}(\\mathbf{g})$ ; the EL curves were taken at $V_{\\mathrm{b}}=2.5\\:\\forall$ (c), $2.5\\mathsf{V}$ (e) and $2.3\\lor(\\mathbf{g})$ . \n\nInjection of electrons into the conduction band of $\\mathbf{MoS}_{2}$ leads not only to an increase in tunnelling conductivity but, also, to accumulation of electrons in $\\mathbf{MoS}_{2}$ and results in formation of negatively charged excitons12, $\\mathrm{X^{-}}$ . The $\\mathrm{X}^{-}$ peak is positioned at a lower energy compared with the $\\mathrm{X}^{0}$ peak owing to the binding energy, $E_{\\mathrm{B}}$ , of $\\mathrm{X}^{-}$ . In the case of $\\mathbf{MoS}_{2}$ we estimate $\\boldsymbol{E_{\\mathrm{B}}}$ as ${\\approx}36\\mathrm{meV}$ near the onset of $\\mathrm{X}^{-}$ . As the bias increases, the energy of the $\\mathrm{X}^{-}$ peak shifts to lower values, which can be attributed either to the Stark effect or to the increase in the Fermi energy in $\\mathbf{MoS}_{2}$ (ref. 12). \n\nIn contrast to PL, EL starts only at $V_{\\mathrm{b}}$ above a certain threshold (Fig. 2b). We associate such behaviour with the Fermi level of the top graphene $(\\mathrm{Gr_{T}})$ being brought below the edge of the valence band so that holes can be injected into $\\mathrm{MoS}_{2}$ from $\\mathrm{Gr}_{\\mathrm{T}}$ (in addition to electrons already injected from $\\mathrm{Gr_{B}}$ ) as sketched in Fig. 1j. This creates conditions for exciton formation inside the QW and their radiative recombination. We find that the EL frequency is close to that of PL at $V_{\\mathrm{b}}{\\approx}2.4\\:\\mathrm{V}$ (Fig. 2a–c), which allows us to attribute the EL to radiative recombination of $\\mathrm{X}^{-}$ . Qualitatively similar behaviour is observed for $\\mathrm{WS}_{2}$ QWs (Fig. 2d–g). \n\nAn important parameter for any light-emission device is the QE defined as $\\eta=N2e/I$ (here $e$ is the electron charge, and $N$ is the number of the emitted photons). For SQWs we obtain quantum efficiencies of ${\\sim}1\\%$ —this value by itself is ten times larger than that of planar p–n diodes15,17,18 and 100 times larger than EL from Schottky barrier devices16. Our rough estimations show that the external QE (EQE) for PL is lower than that for EL. Relatively low EQE found in PL indicates that the crystal quality itself requires improvement and that even higher EQE in EL may then be achieved28. \n\nTo enhance QE even further, we have employed multiple QWs stacked in series, which increases the overall thickness of the tunnel barrier and enhances the probability for injected carriers to recombine radiatively. Figure 3 shows results for one of such MQW structures with three $\\mathbf{MoS}_{2}$ QWs (layer sequence: Si/SiO2/hBN/GrB/3hBN/MoS2/3hBN/MoS2/3hBN/MoS2/ $3\\mathrm{hBN/Gr_{\\mathrm{T}}/h B N)}$ and another MQW with four asymmetric $\\mathbf{MoS}_{2}$ QWs (Fig. $^{1\\mathrm{c},\\mathrm{d}},$ ) is described in the Supplementary Information. The current increases with $V_{\\mathrm{b}}$ in a step-like manner, which is attributed to sequential switching of the tunnelling current through individual $\\mathbf{MoS}_{2}$ QWs. PL for the MQW device is qualitatively similar to that of SQW devices but the $\\mathrm{X}^{0}$ peak is replaced with a $\\mathrm{X}^{-}$ peak at $V_{\\mathrm{b}}=0.4\\:\\mathrm{V}$ (Fig. 3c). The $\\mathrm{X}^{0}$ peak reappears again at \n\n![](images/2a6878a4fb878aa3d188f974e19494350f1da5ac85a19ab10f2e908c985094c5.jpg) \nFigure 3 | Optical and transport characteristics of MQW devices, ${\\boldsymbol{\\tau}}=7{\\mathsf{K}}.$ a, Modulus of the current density through a triple QW structure based on ${\\mathsf{M o S}}_{2}$ . b, Its schematic structure. c,d, Maps of $\\mathsf{P L}$ and EL spectra for this device. $E_{\\mathrm{L}}{=}2.33\\mathrm{eV}.\\mathrm{\\}$ , Individual EL spectra plotted on a logarithmic scale show the onset of EL at $1.8\\mathsf{n A}\\upmu\\mathsf{m}^{-2}$ (blue curve). Olive and red: $j=18$ and $130\\mathsf{n A}\\mathsf{\\upmu m}^{-2}$ , respectively. f, Comparison of the EL (taken at $V_{\\mathrm{b}}=8.3\\:\\forall.$ ) and PL (taken at $V_{\\flat}=4.5\\vee$ ) spectra. \n\n$V_{\\mathrm{b}}>1.2\\:\\mathrm{V}.$ This can be explained by charge redistribution between different QWs. The EL first becomes observable at $V_{\\mathrm{b}}>3.9\\mathrm{V}$ and $j$ of $1.8\\mathrm{nA}\\upmu\\mathrm{m}^{-2}$ (Fig. 3d,e). This current density is nearly 2 orders of magnitude smaller than the threshold current required to see EL in similar SQWs. Importantly, the increased probability of radiative recombination is reflected in higher QE, reaching values of ${\\sim}8.4\\%$ (for the device with quadruple QW, $6\\%$ for triple). This high QE is comparable to the efficiencies of the best modern-day organic LEDs (ref. 29). \n\nThe described technology of making designer MQWs offers the possibility of combining various semiconductor QWs in one device. Figure $4\\mathsf{a}-\\mathsf{c}$ describes an LED made from ${\\mathrm{WSe}}_{2}$ and $\\mathbf{MoS}_{2}$ QWs: $\\mathrm{Si/SiO_{2}/h B N/G r_{\\it B}/3h B N/W S e_{2}/3h B N/M o S_{2}/3h B N/G r_{\\it T}/h B N}$ . EL and PL occur here in the low- $E$ part of the spectra and can be associated with excitons and charged excitons in $\\mathrm{WSe}_{2}$ . However, in comparison with SQW devices, the combinational device in Fig. 4 exhibits intensities more than an order of magnitude stronger for both PL and $\\mathrm{EL},$ yielding ${\\sim}5\\%$ QE. We associate this with charge transfer between the $\\mathbf{MoS}_{2}$ and $\\mathrm{WSe}_{2}$ layers such that electron–hole pairs are created in both layers but transfer to and recombine in the material with the smaller bandgap30. Such a process is expected to depend strongly on band alignment, which is controlled by bias and gate voltages. This explains the complex, asymmetric $V_{\\mathrm{b}}$ dependence of PL and EL in Fig. 4. \n\nGenerally, the fine control over the tunnelling barriers allows a reduction in the number of electrons and holes escaping from the quantum well, thus enhancing EQE. EQE generally demonstrates a peak at $T$ around $50\\mathrm{-}150\\mathrm{K}.$ , depending on the material. Depending on the particular structure we found that typical values of EQE for $\\mathrm{MoS}_{2}$ - and $\\mathrm{WS}_{2}$ -based devices at room $T$ are close or a factor of 2–3 lower than those at low $T$ (Fig. 4d). \n\nFinally, we note that because our typical stacks are only 10–40 atoms thick, they are flexible and bendable and, accordingly, can be used for making flexible and semi-transparent devices. To prove this concept experimentally, we have fabricated a $\\mathbf{MoS}_{2}$ SQW on a thin PET (polyethylene terephthalate) film (Fig. 4e,f). The device shows PL and EL very similar to those in Fig. 2a–c. We also tested the device’s performance under uniaxial strain of up to $1\\%$ (using bending) and found no changes in the EL spectrum (Fig. 4g). \n\nIn summary, we have demonstrated band-structure engineering with one atomic layer precision by creating QW heterostructures from various 2D crystals including several TMDCs, hBN and graphene. Our LEDs based on a single QW already exhibit QE of above $1\\%$ and line widths down to $18\\mathrm{meV},$ despite the relatively poor quality of available TMDC layers. This EQE can be improved significantly by using multiple QWs. Consisting of 3 to 4 QWs, these devices show EQEs up to $8.4\\%$ . Combining different 2D semiconductor materials allows fine-tuning of the emission spectra and also an enhanced EL with a quantum yield of $5\\%$ . These values of QE are comparable to modern-day organic LED lighting and the concept is compatible with the popular idea of flexible and transparent electronics. The rapid progress in technology of chemical vapour deposition growth will allow scaling up of production of such heterostructures. \n\n![](images/52d430da0b44a4401e474d8dec41f932862c56454b2780c3360a93019d2368fa.jpg) \nFigure 4 | Devices combining diferent QW materials and on flexible substrates. a–c, EL at negative (a) and positive (c) bias voltages for the device with two QWs made from $M\\circ\\mathsf{S}_{2}$ and ${\\mathsf{W S e}}_{2}$ schematically shown in the inset in d. Its PL bias dependence is shown in b, for laser excitation $E_{\\mathrm{L}}=2.33\\mathrm{eV},$ ${\\cal T}=7\\sf K$ . White curve: |j|– $V_{\\mathrm{b}}$ characteristics of the device. d, Temperature dependence of EQE for a device with two QWs made from ${M o S}_{2}$ and ${\\mathsf{W S e}}_{2}$ . Inset: schematic representation of a device with two QWs produced from diferent materials. e, Optical micrograph taken in reflection mode of a SQW $(M\\circ\\mathsf{S}_{2}$ ) device on PET. f, Optical micrograph of the same device as in e taken in transmission mode. For e,f the area of the stack is marked by red rectangles; scale bars are $10\\upmu\\mathrm{m}$ . g, EL spectra for the device in e,f at zero (blue dots) and $1\\%$ (red dots) strain. $V_{\\mathrm{b}}{=}{-}2.3\\lor,I{=}{-}40\\upmu\\mathrm{A}$ at room T. \n\n# Methods \n\nSample fabrication. Flakes of graphene, hBN and TMDCs are prepared by micromechanical exfoliation of bulk crystals. Single- or few-layer flakes are identified by optical contrast and Raman spectroscopy. Heterostructures are assembled using the dry peel/lift method described in detail in the Supplementary Methods. Electrical contacts to the top and bottom graphene electrodes are patterned using electron-beam lithography followed by evaporation of $5\\mathrm{nm}\\mathrm{Cr}/60\\mathrm{nm}$ Au. \n\nElectrical and optical measurements. Samples are mounted within a liquid helium flow cryostat with a base temperature of $T=6\\mathrm{K}$ Electrical injection is performed using a Keithley 2400 source meter. To measure PL the samples were excited with a continuous wave $532\\mathrm{nm}$ laser, focused to a spot size of ${\\sim}1\\upmu\\mathrm{m}$ through a $\\times50$ objective $(\\mathrm{NA}=0.55)$ at a power less than required to modify the spectral line shape. The signal was collected and analysed using a single spectrometer and a nitrogen cooled CCD (charge-coupled device). \n\nScanning transmission electron microscopy. STEM imaging was carried out using a Titan G2 probe-side aberration-corrected STEM operating at $200\\mathrm{kV}$ and equipped with a high-efficiency ChemiSTEM energy-dispersive X-ray detector. The convergence angle was 19 mrad and the third-order spherical aberration \n\nwas set to zero $(\\pm5\\upmu\\mathrm{m})$ . The multilayer structures were oriented along the ⟨hkl0⟩ crystallographic direction by taking advantage of the Kikuchi bands of the silicon substrate. (See Supplementary Information and ref. 21 for more detailed description.) \n\n# Received 19 November 2014; accepted 23 December 2014; published online 2 February 2015 \n\n# References \n\n1. Novoselov, K. S. et al. Two-dimensional atomic crystals. Proc. Natl Acad. Sci. USA 102, 10451–10453 (2005). \n2. Novoselov, K. S. et al. Electric field effect in atomically thin carbon films. Science 306, 666–669 (2004). \n3. Geim, A. K. & Grigorieva, I. V. Van der Waals heterostructures. Nature 499, \n419–425 (2013). \n4. Britnell, L. et al. Resonant tunnelling and negative differential conductance in graphene transistors. Nature Commun. 4, 1794 (2013). \n5. Britnell, L. et al. Field-effect tunneling transistor based on vertical graphene heterostructures. Science 335, 947–950 (2012). \n6. Britnell, L. et al. Strong light–matter interactions in heterostructures of atomically thin films. Science 340, 1311–1314 (2013). \n7. Yu, W. J. et al. Highly efficient gate-tunable photocurrent generation in vertical heterostructures of layered materials. Nature Nanotech. 8, \n952–958 (2013). \n8. Novoselov, K. S. Nobel lecture: Graphene: Materials in the flatland. Rev. Mod. Phys. 83, 837–849 (2011). \n9. Yao, Y., Hoffman, A. J. & Gmachl, C. F. Mid-infrared quantum cascade lasers. Nature Photon. 6, 432–439 (2012). \n10. Wang, Q. H., Kalantar-Zadeh, K., Kis, A., Coleman, J. N. & Strano, M. S. Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. Nature Nanotech. 7, 699–712 (2012). \n11. Mak, K. F., Lee, C., Hone, J., Shan, J. & Heinz, T. F. Atomically thin $\\mathbf{MoS}_{2}$ : A new direct-gap semiconductor. Phys. Rev. Lett. 105, 136805 (2010). \n12. Mak, K. F. et al. Tightly bound trions in monolayer $\\mathbf{MoS}_{2}$ . Nature Mater. 12, \n207–211 (2013). \n13. Xiao, D., Liu, G-B., Feng, W., Xu, X. & Yao, W. Coupled spin and valley physics in monolayers of $\\mathrm{MoS}_{2}$ and other group-VI dichalcogenides. Phys. Rev. Lett. \n108, 196802 (2012). \n14. Ross, J. S. et al. Electrical control of neutral and charged excitons in a monolayer semiconductor. Nature Commun. 4, 1474 (2013). \n15. Ross, J. S. et al. Electrically tunable excitonic light-emitting diodes based on monolayer ${\\mathrm{WSe}}_{2}\\ {\\mathrm{p-n}}$ junctions. Nature Nanotech. 9, 268–272 (2014). \n16. Sundaram, R. S. et al. Electroluminescence in single layer $\\mathbf{MoS}_{2}$ . Nano Lett. 13, \n1416–1421 (2013). \n17. Pospischil, A., Furchi, M. M. & Mueller, T. Solar-energy conversion and light emission in an atomic monolayer p–n diode. Nature Nanotech. 9, \n257–261 (2014). \n18. Baugher, B. W. H., Churchill, H. O. H., Yang, Y. & Jarillo-Herrero, P. Optoelectronic devices based on electrically tunable p–n diodes in a monolayer dichalcogenide. Nature Nanotech. 9, 262–267 (2014). \n19. Rivera, P. et al. Observation of long-lived interlayer excitons in monolayer ${\\mathrm{MoSe}}_{2}{\\mathrm{-}}{\\mathrm{WSe}}_{2}$ heterostructures. Preprint at http://arXiv.org/abs/1403.4985 (2014). \n20. Wang, L. et al. One-dimensional electrical contact to a two-dimensional material. Science 342, 614–617 (2013). \n21. Haigh, S. J. et al. Cross-sectional imaging of individual layers and buried interfaces of graphene-based heterostructures and superlattices. Nature Mater. \n11, 764–767 (2012). \n22. Tongay, S. et al. Defects activated photoluminescence in two-dimensional semiconductors: Interplay between bound, charged, and free excitons. Sci. Rep. \n3, 2657 (2013). \n23. Sercombe, D. et al. Optical investigation of the natural electron doping in thin $\\mathbf{MoS}_{2}$ films deposited on dielectric substrates. Sci. Rep. 3, 3489 (2013). \n24. Kang, J., Tongay, S., Zhou, J., Li, J. B. & Wu, J. Q. Band offsets and heterostructures of two-dimensional semiconductors. Appl. Phys. Lett. 102, \n012111 (2013). \n25. Sachs, B. et al. Doping mechanisms in graphene- ${\\cdot\\mathrm{Mo}}S_{2}$ hybrids. Appl. Phys. Lett. \n103, 251607 (2013). \n26. Lee, G. H. et al. Electron tunneling through atomically flat and ultrathin hexagonal boron nitride. Appl. Phys. Lett. 99, 243114 (2011). \n27. Britnell, L. et al. Electron tunneling through ultrathin boron nitride crystalline barriers. Nano Lett. 12, 1707–1710 (2012). \n28. Gutierrez, H. R. et al. Extraordinary room-temperature photoluminescence in triangular $\\mathrm{WS}_{2}$ monolayers. Nano Lett. 13, 3447–3454 (2013). \n29. Reineke, S. et al. White organic light-emitting diodes with fluorescent tube efficiency. Nature 459, 234–238 (2009). \n30. Lee, C. H. et al. Atomically thin p–n junctions with van der Waals heterointerfaces. Nature Nanotech. 9, 676–681 (2014). \n\n# Acknowledgements \n\nThis work was supported by The Royal Society, Royal Academy of Engineering, US Army, European Science Foundation (ESF) under the EUROCORES Programme EuroGRAPHENE (GOSPEL), European Research Council, EC-FET European Graphene Flagship, Engineering and Physical Sciences Research Council (UK), the Leverhulme Trust (UK), US Office of Naval Research, US Defence Threat Reduction Agency, US Air Force Office of Scientific Research, FP7 ITN $S^{3}$ NANO, SEP-Mexico and CONACYT. \n\n# Author contributions \n\nF.W. produced experimental devices, led the experimental part of the project, analysed experimental data, participated in discussions, contributed to writing the manuscript; O.D.P-Z. measured device characteristics, participated in discussions, analysed experimental data; A.M. measured transport properties of the devices, participated in discussions; A.P.R. and A.G. produced samples for TEM study, analysed TEM results, participated in discussions; K.W. and T.T. grew high-quality hBN, participated in discussions; S.J.H. analysed TEM results, participated in discussions; A.K.G. analysed experimental data, participated in discussions, contributed to writing the manuscript; A.I.T. analysed experimental data, participated in discussions, contributed to writing the manuscript; K.S.N. initiated the project, analysed experimental data, participated in discussions, contributed to writing the manuscript. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to K.S.N. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. " + }, + { + "id": "10.1039_c5ta06398a", + "DOI": "10.1039/c5ta06398a", + "DOI Link": "http://dx.doi.org/10.1039/c5ta06398a", + "Relative Dir Path": "mds/10.1039_c5ta06398a", + "Article Title": "Inorganic caesium lead iodide perovskite solar cells", + "Authors": "Eperon, GE; Paternò, GM; Sutton, RJ; Zampetti, A; Haghighirad, AA; Cacialli, F; Snaith, HJ", + "Source Title": "JOURNAL OF MATERIALS CHEMISTRY A", + "Abstract": "The vast majority of perovskite solar cell research has focused on organic-inorganic lead trihalide perovskites. Herein, we present working inorganic CsPbI3 perovskite solar cells for the first time. CsPbI3 normally resides in a yellow non-perovskite phase at room temperature, but by careful processing control and development of a low-temperature phase transition route we have stabilised the material in the black perovskite phase at room temperature. As such, we have fabricated solar cell devices in a variety of architectures, with current-voltage curve measured efficiency up to 2.9% for a planar heterojunction architecture, and stabilised power conversion efficiency of 1.7%. The well-functioning planar junction devices demonstrate long-range electron and hole transport in this material. Importantly, this work identifies that the organic cation is not essential, but simply a convenience for forming lead triiodide perovskites with good photovoltaic properties. We additionally observe significant rate-dependent current-voltage hysteresis in CsPbI3 devices, despite the absence of the organic polar molecule previously thought to be a candidate for inducing hysteresis via ferroelectric polarisation. Due to its space group, CsPbI3 cannot be a ferroelectric material, and thus we can conclude that ferroelectricity is not required to explain current-voltage hysteresis in perovskite solar cells. Our report of working inorganic perovskite solar cells paves the way for further developments likely to lead to much more thermally stable perovskite solar cells and other optoelectronic devices.", + "Times Cited, WoS Core": 1534, + "Times Cited, All Databases": 1626, + "Publication Year": 2015, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000362041300009", + "Markdown": "# Inorganic caesium lead iodide perovskite solar cells† \n\nGiles E. Eperon,a Giuseppe M. Patern\\`o,bc Rebecca J. Sutton,a Andrea Zampetti,bc Amir Abbas Haghighirad,a Franco Caciallibc and Henry J. Snaith\\*a \n\nReceived 14th August 2015 \nAccepted 4th September 2015 \n\nDOI: 10.1039/c5ta06398a www.rsc.org/MaterialsA \n\nThe vast majority of perovskite solar cell research has focused on organic–inorganic lead trihalide perovskites. Herein, we present working inorganic $\\mathsf{C s P b l}_{3}$ perovskite solar cells for the first time. $\\mathsf{C s P b l}_{3}$ normally resides in a yellow non-perovskite phase at room temperature, but by careful processing control and development of a low-temperature phase transition route we have stabilised the material in the black perovskite phase at room temperature. As such, we have fabricated solar cell devices in a variety of architectures, with current–voltage curve measured efficiency up to $2.9\\%$ for a planar heterojunction architecture, and stabilised power conversion efficiency of $1.7\\%$ . The well-functioning planar junction devices demonstrate long-range electron and hole transport in this material. Importantly, this work identifies that the organic cation is not essential, but simply a convenience for forming lead triiodide perovskites with good photovoltaic properties. We additionally observe significant rate-dependent current–voltage hysteresis in $\\mathsf{C s P b l}_{3}$ devices, despite the absence of the organic polar molecule previously thought to be a candidate for inducing hysteresis via ferroelectric polarisation. Due to its space group, $\\mathsf{C s P b l}_{3}$ cannot be a ferroelectric material, and thus we can conclude that ferroelectricity is not required to explain current–voltage hysteresis in perovskite solar cells. Our report of working inorganic perovskite solar cells paves the way for further developments likely to lead to much more thermally stable perovskite solar cells and other optoelectronic devices. \n\n# Introduction \n\nThe meteoric rise of hybrid organic–inorganic perovskite solar cells has seen power conversion efficiencies rise from $3.8\\%$ to over $20\\%$ in merely a couple of years, with more than 1000 scientic publications on the topic.1–6 The most studied materials are methylammonium lead triiodide $\\left(\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}\\right.$ or $\\mathbf{MAPbI}_{3_{.}}^{\\cdot}$ and formamidinium lead triiodide $\\mathrm{\\bfNH_{2}C H N H_{2}P b I_{3}}$ or $\\mathrm{FAPbI}_{3,}$ , which are 3-dimensional hybrid organic–inorganic perovskite semiconductors with the generic chemical formula $\\mathbf{ABX}_{3}$ .7,8 These materials exhibit long-range electron and hole diffusion lengths, low exciton binding energies, high carrier mobilities and suitable bandgaps for making solar cells and other optoelectronic devices.7,9–12 Whilst the organic cation enables stabilised $\\mathbf{ABX}_{3}$ perovskites which could not be formed by simply employing elements (ions) within the periodic table, one concern of these hybrid perovskites, when compared to conventional thin lm compound semiconductors, is the inclusion of the organic cation: the hybrid perovskites have considerably lower thermal decomposition temperatures ${\\bf\\omega}_{\\sim300}^{\\circ}{\\bf C}$ in bulk and between 150 to $200~^{\\circ}\\mathrm{C}$ in thin lm) than conventional inorganic semiconductors. A poignant question to ask is whether the organic cation is an essential component in high efficiency metal halide perovskite solar cells, or can all inorganic metal halide perovskite solar cells be developed to match the hybrid materials on efficiency, and simultaneously match conventional PV materials on fundamental thermal stability? In addition, whilst these hybrid perovskites form high quality thin lm semiconductors and subsequently high efficiency solar cells, in certain congurations they exhibit a current–voltage hysteresis on the timescale of seconds, inhibiting the maximum performance being achieved.13–15 Recently there has been much speculation about the origin of this hysteresis, with the two main suggestions being (1) that it is due to the motion of charged defects in solar cells under operating conditions, leading to benecial or detrimental bias-dependent charge extraction efficiency,16–19 or (2) that it is due to a ferroelectric polarisation, originating from aligned dipolar organic molecules in the lattice.20–24 There is evidence for both theories and thus far no studies have conclusively ruled out either possibility. Replacement of the polar organic molecule with a non-polar component would be an ideal test for the ferroelectric \n\ntheory, sin city of the perovski though to arise from alignment of the MA molecular dipoles throughout the lattice. If the polar organic molecule is responsible for the hysteretic effect, replacing it with a nonpolar component should result in hysteresis-free devices. There have been reports of all inorganic caesium tin iodide perovskite solar cells, which do replace the organic component and also the lead cation.25,26 However, the efficiencies are very low and these are fabricated on mesoporous titania, a structure that is known to mitigate hysteretic effects.13 Additionally, fabrication of Sn-based devices remains challenging due to susceptibility for the $\\mathrm{Sn}^{2+}$ ion to oxidize to $\\sin^{4^{+}}$ .27 Caesium lead bromide, a wide bandgap perovskite material, hence not well suited for efficient solar energy conversion, has been recently reported in working solar cells by Cahen and co-workers. They show that $\\mathbf{CsPbBr}_{3}$ devices work effectively as well as $\\mathbf{MAPbB}\\mathbf{r}_{3}$ devices, going some way to solve the debate over the role of the organic cation.28 However, these devices too are fabricated on mesoporous titania, mitigating hysteresis. Caesium lead iodide, the perovskite formed by substituting the organic cation in $\\mathbf{MAPbI}_{3}$ with caesium, has not yet been reported in functioning solar cells, likely due to the fact that the desired black $(\\sim1.73\\ \\mathrm{eV}$ bandgap) cubic perovskite phase is not stable at room temperature at ambient conditions, making fabrication challenging.8 The material generally transforms to the yellow $\\mathbf{NH}_{3}\\mathbf{CdCl}_{3}$ nonperovskite structure at room temperature.29 Solar cells with this yellow phase have been reported, but did not function at more than $0.09\\%$ PCE.30 Herein, we develop a route to form the black phase at much lower temperatures than would normally be necessary. Furthermore, we nd that by processing the material in a totally air-free environment, it is stable in its black phase. In this way we fabricate working black phase caesium lead iodide solar cells for the rst time. These inorganic perovskites offer the promise of high thermal stability from a material with bandgap suited for solar energy conversion, with a potentially attractive application being in tandem devices. We show that such fully inorganic devices do display signicant hysteresis in current–voltage measurements. Therefore, we can comprehensively conclude that the presence of a polar organic component is not necessary for inducing current–voltage hysteresis. Moreover, the respectable starting performance of these inorganic perovskite devices shows that the hybrid nature of the previously explored perovskites is not critical to fabrication of working solar cells. The solar cells function even in a thin-lm planar heterojunction architecture, demonstrating that this material has good ambipolar transport properties and a signicant diffusion length. \n\n# Results and discussion \n\nCaesium lead iodide $\\mathrm{(CsPbI_{3})}$ has been previously synthesised as single crystals and as nanocrystals, and as a dopant in methylammonium lead iodide lms in solar cells.8,30–34 It can be solution-processed in a similar manner to the hybrid lead halide perovskites; upon formation at room temperature it exhibits a yellow orthorhombic phase with wide bandgap, unsuitable for solar cell applications.8 Upon heating, it can form a black cubic perovskite phase with an optical bandgap of ${\\sim}1.73$ eV.34 The phase transition has been reported to occur at temperatures of ${\\sim}310\\ ^{\\circ}\\mathbf{C}.^{8,33}$ However, upon cooling, this phase is unstable in ambient conditions at room temperature, returning to the yellow non-perovskite phase in a matter of minutes. Practically, we found that when spin-coating a thin lm of material, heating at temperatures of $\\scriptstyle\\geq335^{\\circ}\\mathbf{C}$ was necessary to form the black phase, and that aer returning to the yellow phase when exposed to ambient conditions, reheating would return it to the black phase. Notably, we found that when the lm was never exposed to ambient air, it remained ‘frozen’ in the black phase even at room temperature, for a matter of weeks at least. Thus, by processing full devices in completely air-free systems, we were able to fabricate thin lms and full solar cell devices. We were able to form smooth and uniform thin lms of black phase $\\mathbf{CsPbI}_{3}$ by spin-coating a $1:1$ $\\mathbf{CsI}:\\mathbf{PbI}_{2}$ solution in N,N-dimethylformamide (DMF) and heating to $335\\ ^{\\circ}\\mathbf{C}.$ . However, $335~^{\\circ}\\mathrm{C}$ is still a relatively high temperature, rendering the conversion impractical for a number of device architectures and substrates, such as temperature sensitive c-Si solar cells and hence relevant for tandem cell applications. We found that by adding a small amount of hydroiodic acid to the precursor solution prior to spin-coating, an additive commonly employed to enhance the solubility of perovskite precursors allowing uniform lm formation,7,35 we were able to convert from the yellow to the black phase at only $100~^{\\circ}\\mathbf{C}.$ Using this additive route, we were able to form uniform and smooth thin lms of black $\\mathbf{CsPbI}_{3}$ by spin-coating the precursor solution plus additive and annealing at only $100^{\\circ}\\mathrm{C}$ for 10 minutes. \n\nIn Fig. 1 we show the material properties of $\\mathbf{CsPbI}_{3}$ yellow and black phase thin lms. The crystal structures of the yellow and black phases are shown in Fig. 1a. Absorbance spectra (Fig. 1b) agree with previous observations and indicate a material with bandgap of ${\\sim}1.73\\ \\mathrm{eV}$ for the black phase, and a material absorbing only below ${\\sim}440~\\mathrm{nm}\\left(2.82~\\mathrm{eV}\\right)$ in the yellow phase. Renement of X-ray diffraction data for the black phase (Fig. 1c) indicates a cubic perovskite structure with lattice constant $a=6.1769(3)\\mathring{\\mathrm{A}}$ and space group $P m\\bar{3}m$ (no. 221).8,31 We note that this is not a polar space group, so this material cannot sustain ferroelectricity in the classical manner, by distortion of the lattice. \n\nThe addition of HI did not result in any obvious changes to the optical properties of the material, as we show in Fig. 2a; the absorption spectrum is essentially identical for the low and high temperature processed material. However, we noticed that in addition to forming the black phase at lower temperature, the lms processed with HI at low temperature were stable in the black phase for signicantly longer when exposed to air than the high-temperature processed lms – hours rather than minutes. This implies that the lms processed with HI are producing a material with a more energetically favourable black phase – it requires less energy input to form it and it is more stable once formed. Considering the role of HI, and the mechanism by which it allows us to form the black phase at a lower temperature, we carried out a more in-depth characterisation of the material formed with and without HI. \n\n![](images/71a0f293c46e4b8cdfc43a07eaf5d3a9deced9566732a5f5a38ed448a0083c0f.jpg) \nFig. 1 Material properties of $\\mathsf{C s P b l}_{3}$ (a) diagrammatic structure of $\\mathsf{C s P b l}_{3}$ phases.8,31 (b) Absorbance spectra of black and yellow phases of $\\mathsf{C s P b l}_{3}$ thin films. (c) $\\mathsf{X}$ -ray diffraction spectra (XRD) of $\\mathsf{C s P b l}_{3}$ thin film in black phase, with peaks assigned to a cubic $(P m\\bar{3}m)$ lattice with $a=6.1769(3)\\AA$ . Peaks marked with \\* are those assigned to the FTO substrate. The XRD was performed in air, with the perovskite film coated with polymethylmethacrylate (PMMA) to minimise exposure to air and inhibit the transformation into the yellow phase. \n\nAs we show in Fig. 2b, scanning electron microscope characterisation of the surface of black phase lms formed with and without HI (annealed at low and high temperature respectively), indicate a signicant difference. Both lms appear very uniform and smooth, but the grain size of the lms formed without HI is very large, whereas with HI, the grains are signicantly smaller – only on the scale of ${\\sim}100~\\mathrm{nm}$ , compared to almost microns in the lm processed without HI. Comparing the X-ray diffraction spectra (Fig. 2c and d), we notice that although the overall majority crystal structure appears identical in the two lms, there is a different degree of orientation (comparing the magnitude of the (100) and (200) peaks with the other peaks observed) – the lm processed with HI has a more pronounced orientation. Moreover, looking closely at the (110) and (200) peaks (Fig. 2d), a further difference becomes evident. The (110) peak is in fact split in the lm processed with HI, appearing as a single peak only in the lm processed without HI. This second peak cannot be assigned to any possible impurity, nor degradation to the yellow phase (spectrum in SI). The (200) peak exhibits a small shoulder in the HI processed lm, and is a clear single peak in the lm without HI. Peak splitting such as this is oen related to the presence of strain in a crystal; as such we propose that the lm processed with HI has a slightly strained crystal lattice.36 This strain could then be responsible for allowing the lower temperature phase transition; strain has previously been observed to induce crystal phase transitions, and serves to completely shi the phase diagram for a material.37–40 The role of HI in creating this lattice strain is likely related to formation of the smaller grains, causing the strain in the lattice. The small crystals presumably result from faster crystallisation from the solution containing HI, which could be due to the HI being driven off more rapidly than pure DMF, or reduced solubility of the Cs precursor in a solution containing HI. We note that this would be opposite to the behaviour normally observed for $\\mathbf{MAPbI}_{3}$ or $\\mathbf{FAPbI}_{3}$ , but given the replacement of the organic component with Cs would not be unprecedented. In either case though, HI clearly induces the formation of smaller grains, and this is likely responsible for stabilising the black phase at lower temperature. We note that in the previous report of $\\mathrm{CsPbI}_{3}$ nanocrystals, Protesescu et al. observed that the smaller the nanocrystals, the more stable they were in the black phase, with the smallest nanocrystals being stable in the black phase for months.31 This ts well with our observations and reinforces our hypothesis, suggesting that the grain size is of critical importance for stabilisation of the black phase at low temperature. As an aside, this points towards controlling grain boundaries and surface states being of critical importance for these inorganic perovskites, if small grains are a prerequisite of stable crystal phase. \n\n![](images/23a195e6a3843868067957defd013745faac99062596a259c4f87ec959ad399f.jpg) \nFig. 2 (a) Comparison of absorbance spectra of films fabricated at low and high temperatures (with and without the hydroiodic acid additive) on FTO/compact $\\mathsf{T i O}_{2}$ substrate, which is representative of the morphology on all substrates. Inset: magnification of onset. (b) Scanning electron micrographs of films fabricated without and with HI additive, annealed at high and low temperature respectively. Inset: magnification of film fabricated with HI showing small grain size. (c) Comparison of XRD spectra of films processed with and without HI. Assigned peaks are marked; peaks labelled with a # are assigned to some yellow phase present due to degradation in the film without HI (full spectrum of yellow phase in SI). (d) Magnification of the (110) and (200) peaks to show peak splitting and shoulder in film processed with HI. \n\nHaving ascertained that we have indeed formed $\\mathbf{CsPbI}_{3}$ stably in the black cubic phase, and that we can maintain it in this phase for a long period of time by processing in air-free environments, we fabricated solar cell devices. We made solar cells in both the planar heterojunction and inltrated mesoporous $\\mathrm{TiO}_{2}$ architectures, as planar heterojunctions will function only if the material is such that photoexcitation generates free carriers which are able to reach the opposite sides of the device before recombining. Inltrating the perovskite into mesoporous titania allows materials with worse transport properties to function effectively, with the material acting as a “sensitizer”, and transferring photoexcited carriers rapidly into the mesoporous titania and hole transporting layer as appropriate. Additionally, the low temperature processing route allowed us to fabricate ‘inverted’ planar heterojunction devices, based on a poly(3,4-ethylene dioxythiophene) doped with poly(styrene sulfonate) (PEDOT : PSS) coated substrate with the n-type phenyl-C61-butyric-acid-methyl ester (PCBM) collection layer on top. We show diagrammatic representations of the different architectures employed in Fig. 3a. \n\nThe perovskite, optionally inltrated within a $400\\ \\mathrm{nm}$ thick layer of mesoporous $\\mathrm{TiO}_{2}$ , is sandwiched between electronselective and hole-selective contacts of compact $\\mathrm{TiO}_{2}$ and spiroOMeTAD respectively for the ‘regular’ n-i-p devices and PCBM and PEDOT : PSS for the ‘inverted’ p-i-n devices. When not inltrated, the perovskite has thickness of ${\\sim}220~\\mathrm{nm}$ . The spiroOMeTAD is doped with spiro $(\\mathrm{TFSI})_{2}$ and tert-butylpyridine; the spiro $(\\mathrm{TFSI})_{2}$ negates the normal requirement for doping via air exposure.41 We show the current–voltage $(J V)$ characteristics, measured under AM1.5 illumination and scanning from forward to reverse bias, in Fig. 3b–d. We observe that the regular architecture planar perovskite solar cells generate up to $12~\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ short-circuit current density, and an open-circuit voltage of ${\\sim}0.8\\mathrm{V}$ . This results in $2.9\\%$ power conversion efficiency (PCE) for this fast $J V$ scan. The mesoporous titania devices however do not perform as effectively, generating lower open-circuit voltage, ll factor, and short-circuit current. This results in only $1.3\\%$ PCE. The planar inverted devices generate a lower current, but a good ll factor and open-circuit voltage, resulting in $1.7\\%$ PCE. We note that we also fabricated high-temperature processed $\\mathbf{CsPbI}_{3}$ devices in the regular planar and mesoporous structures; these devices behaved very similarly to the low-temperature processed lms. The planar regular devices and the mesoporous devices are clearly subject to imperfect shunt and series resistances, and possibly non-optimal interface contacts causing the s-shape of the planar device. Clearly, they are not optimised devices, but they do function. Further work will be necessary to understand the limitations of these initial devices, and fabricate highefficiency solar cells. These will likely be enabled by optimising deposition techniques and annealing protocols, as has been responsible for the current high efficiencies of the more studied MAPbI3 and FAPbI3 devices.35,42,43 \n\n![](images/4605e47d28f954a27e977a72a22fab2524e4da24e8b8edb03ec4769dc083ef67.jpg) \nFig. 3 Solar cell properties. (a) Schematic of the architectures used. Current–voltage characteristics measured under simulated AM1.5G illumination, scanning from forward to reverse bias at $0.1\\lor{\\mathsf{s}}^{-1}.$ , for regular planar heterojunctions (b), mesoporous titania based devices (c), and inverted planar heterojunctions (d). Devices were unencapsulated and were measured in vacuum conditions. \n\nThe fact that the planar devices function is integral to the understanding of this material. A functioning planar device means that because charges are extracted and a signicant short-circuit current generated, carriers must be able to travel across the lm before recombining. This implies that both electrons and holes must have a signicant diffusion length in caesium lead triiodide. Moreover, it implies that the exciton binding energy is low enough that most excited carriers in the lm are present as free carriers as opposed to excitons. The fact that the planar devices outperform the mesoporous devices indicates that transport in the perovskite is likely superior to transport in the mesoporous titania, and indicates that there is no need for the mesostructured approach for this all inorganic perovskite. \n\nAs previously discussed, the issue of current–voltage hysteresis, exhibiting different $J V$ characteristics at different scan speeds, is a critical issue in the hybrid organic–inorganic perovskite solar cells. Typically regular n-i-p structured planar devices display most hysteresis, with mesoporous titania-based devices and inverted devices mitigating the effects of hysteresis. The extent of hysteresis can be ascertained by measuring steadystate power output of the cell, which at maximum power point gives the real sustainable efficiency of the device. Comparing this to the current–voltage sweeps allows us to quantify to what extent the PCE is articially inated in the $J V$ scan due to the hysteretic effect. As such, we measured current–voltage characteristics for these fully inorganic perovskite solar cells at different rates, and also measured the steady-state power output. \n\nIn Fig. 4, we plot current–voltage characteristics measured at different scan rates on the le, and stabilised power measurements (holding at maximum power point) on the right hand side. We observe that the regular structure planar device (Fig. 4a) shows large differences in its $J V$ scans depending on scan rate. Faster scans appear to show in particular a superior ll factor (FF), and more similar forward going (SC-FB) and reverse going (FB-SC) scans. At the slower scan speed, there is a very large difference in the forward and reverse scans. Measuring the stabilised power output (Fig. 4b), we show that the stabilised value is signicantly below that estimated from the JV scans; indeed, it is lower than any of the scans, no matter the rate or direction. As such, we can conclude that the perovskite device in this architecture does display signicant hysteresis, with the $J V$ scans overestimating the PCE by a factor of more than 2. The mesoporous titania devices (Fig. 4c and d) do also display some variation in hysteresis with scan rate, though not as notable as the planar devices. The stabilised power output rises to a value very similar to the estimated PCE from the $J V$ scan, so we can conclude that while there is some hysteresis in the current–voltage characteristics, it does not critically affect the steady-state response. In the case of the inverted devices, we observe little hysteresis in the $J V$ curves. However, the scans at a very fast rate give a slightly lower shortcircuit current density. The stabilised power output of these devices rises to almost exactly the same as the PCE estimated from the best $J V$ curves, so there appears to be no articial ination of the PCE value in this case; hysteresis does not seem to affect these inverted devices detrimentally. We note that there was a similar degree of hysteresis observed in high- and low-temperature processed devices. \n\n![](images/bfe46513e45abe839eda37e487f54f52c4ae82546703bfcdaa2820ba7220a66d.jpg) \nFig. 4 Hysteresis in inorganic perovskite solar cells. Current–voltage characteristics measured at different sweep rates for (a) regular planar devices, (c) mesoporous titania devices, and (e) inverted planar devices. FB-SC $\\c=$ scanning from forward bias to short circuit, SC-FB vice versa. (b), (d) and (f) show stabilisation of current density and hence PCE measured at the maximum power point determined from FB-SC scan at $0.1\\vee{\\mathsf{s}}^{-1}$ , compared to the PCE extracted from that $\\boldsymbol{\\mathcal{I}V}$ curve. The final stabilised power output (SPO) is marked on the $\\boldsymbol{\\mathcal{I}V}$ plots as a red circle. \n\nFrom these measurements we can conclude several things. Firstly, current–voltage hysteresis is present in $\\mathbf{CsPbI}_{3}$ devices. This effect is therefore not unique to the hybrid materials with a dipolar organic molecule. $\\mathbf{CsPbI}_{3}$ cannot be ferroelectric, either via dipole alignment or by classical lattice distortion, as it does not have a polar space group. Thus, the current–voltage hysteresis displayed here, and likely in other perovskite solar cells, is not resultant from the ferroelectric nature of the material. \n\nSecondly, we observe that the planar regular device shows very signicant hysteresis, and over-estimation of the PCE from the $J V$ scans. On the other hand, the mesoporous titania based and inverted planar devices show little overestimation of the PCE, and a much reduced hysteresis in the $J V$ scans. This is in keeping with what has been observed previously for $\\mathbf{MAPbI}_{3}$ devices.13,14 It is now generally thought that the hysteresis arises due to compensation of an applied bias with an internal built-in eld.16,44,45 This built-in eld acts to reduce recombination aer the device has been held at forward bias (i.e. scanning FB-SC); it can allow even devices with poorly selective contacts to function well temporarily by biasing.16 This allows carriers to be extracted before recombination, making the solar cell ‘better’ – this is the reverse scan with the higher efficiency. Devices with contacts that already rapidly extract charge before it recombines will not be so affected by the temporary built-in eld, as it is not necessary for efficient extraction of charge. This is likely to be the case for the mesoporous and inverted devices. The large surface area of mesoporous titania allows rapid extraction of electrons, as does the PCBM in the inverted devices. However, the compact titania in the regular planar n-i-p device is not as effective at extracting charge – there is even some evidence for an energy barrier that must be overcome by the temporary builtin eld.46 Thus, it requires the temporary enhancement gained by the device previously being at open-circuit conditions to function well (FB-SC in Fig. 4a). Upon going back to shortcircuit, or holding at the maximum power point, the device behaves poorly again (SC-FB in Fig. 4a). \n\nThe SPO measurements take tens of seconds to reach steady state. Furthermore, hysteresis is most severe in $J V$ curves scanned at the slowest rate; the faster scans maintain the device in the benecial state during scanning. As such, we can conclude that the hysteretic effect takes place on the timescale of seconds. \n\nThe main alternative to ferroelectricity proposed as a cause for the hysteretic effect is ion motion within the perovskite lm. Charged defect ions could move to compensate an applied eld, resulting in the built-in eld via charge accumulation at the interfaces or doping of the lm at either side. It has been shown that ions can move under bias in perovskite lms, and there is mounting evidence that this is also the cause of the current– voltage hysteresis.16,17,45 The results presented here agree well with this theory; the timescale of hysteresis observed is as expected for ionic motion. Because here we observe hysteresis with no organic component present, we can rule out the organic component as the only mobile ion in the hybrid devices. \n\nWe note that although the devices presented here are not the most efficient, with further optimisation it is likely that they could perform as well as the hybrid organic–inorganic materials. The fact that we have fabricated working $\\mathbf{CsPbI}_{3}$ devices suggests that there is no fundamental property of the hybrid materials that allows them to work as efficient solar cells. We do note however that the maximum open-circuit voltage we have generated here under full sun illumination is $0.85{\\mathrm{~V~}}$ and the material has an optical band gap of $1.73\\ \\mathrm{eV}.$ . Therefore the loss in potential or voltage-decit, i.e. the difference in energy between the band gap and the open-circuit voltage, is relatively large at $0.88\\:\\mathrm{eV}.$ It remains to be seen if we can achieve similarly small voltage decits as achieved with the organic–inorganic perovskites $(<0.4\\ \\mathrm{eV})$ , at which point we would conclusively demonstrate that the inorganic perovskites are as effective PV materials. To motivate such effort, these inorganic materials do not suffer from some limitations of the hybrid materials; notably the thermal stability of $\\mathbf{CsPbI}_{3}$ is much greater than that of the organic containing materials, where the organic component becomes volatile and easily removed at elevated temperatures. Whilst $\\mathbf{MAPbI}_{3}$ is known to degrade even when held at $85\\ ^{\\circ}\\mathrm{C}$ for long periods of time,47 rendering it ultimately unsuitable for commercialisation, the black phase of $\\mathbf{CsPbI}_{3}$ is stable up to well over $300^{\\circ}\\mathrm{C}$ – this is clearly a signicantly more thermally stable material. If the ambient instability problems of these inorganic materials could be overcome, they could allow long-term efficient operation due to the higher thermal stability. As such, we expect signicant further research into inorganic perovskite solar cells to take place, likely to be accompanied by enhanced efficiencies and stability. \n\n# Conclusion \n\nIn summary, we have fabricated working inorganic $\\mathbf{CsPbI}_{3}$ solar cells for the rst time. By carrying out all processing in a totally inert atmosphere, and developing a low temperature phase transition route, we are able to stabilise $\\mathbf{CsPbI}_{3}$ lms in the black phase at room temperature, and fabricate solar cells in a variety of architectures. This highlights that the organic cation is unlikely to be essential for efficient perovskite solar cells. Despite the fact that $\\mathbf{CsPbI}_{3}$ cannot be ferroelectric in any way, we observe signicant current–voltage hysteresis in such devices, pointing towards other non-ferroelectric phenomena being the cause of current–voltage hysteresis. These results pave the way for further optimisation and stabilisation of the inorganic perovskite materials, with potential for even more stable devices than the hybrid organic–inorganic materials currently displaying the highest efficiencies. \n\n# Acknowledgements \n\nThis work was in part funded by UCL, EPSRC and the European Commission through the ERC-Stg2011 grant HYPER. GE thanks Oxford Photovoltaics Ltd and the EPSRC for his CASE studentship award through the Nanotechnology KTN. We also thank the EC Seventh Framework Programme (FP7/2007-2013) under Grant Agreement No. 607585 (OSNIRO). R.S. is a Commonwealth Scholar, funded by the UK government. F.C. is a Royal Society Wolfson Research Merit Award Holder. The research leading to these results has received funding from the Office of Naval Research long-range scientic projects framework. \n\n# Notes and references \n\n1 A. Kojima, K. Teshima, Y. Shirai and T. Miyasaka, J. Am. Chem. Soc., 2009, 131, 6050–6051. \n2 M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami and H. J. Snaith, Science, 2012, 338, 643–647. \n3 J. Burschka, N. Pellet, S.-J. J. Moon, R. Humphry-Baker, P. Gao, M. K. Nazeeruddin, M. Gra¨tzel and M. Gratzel, Nature, 2013, 499, 316–319. \n4 N. J. Jeon, J. H. Noh, W. S. Yang, Y. C. Kim, S. Ryu, J. Seo and S. Il Seok, Nature, 2015, 517, 476–480. \n5 H. Zhou, Q. Chen, G. Li, S. Luo, T.-B. Song, H.-S. Duan, Z. Hong, J. You, Y. Liu and Y. Yang, Science, 2014, 345, 542–546. \n6 NREL, Best Research-Cell Efficiencies, http://www.nrel.gov/ ncpv/images/efficiency_chart.jpg, 2015. \n7 G. E. Eperon, S. D. Stranks, C. Menelaou, M. B. Johnston, L. M. Herz and H. J. Snaith, Energy Environ. Sci., 2014, 7, 982–988. \n8 C. C. Stoumpos, C. D. Malliakas and M. G. Kanatzidis, Inorg. Chem., 2013, 52, 9019–9038. \n9 S. D. Stranks, G. E. Eperon, G. Grancini, C. Menelaou, M. J. P. Alcocer, T. Leijtens, L. M. Herz, A. Petrozza and H. J. Snaith, Science, 2013, 342, 341–344. \n10 V. D'Innocenzo, G. Grancini, M. J. P. Alcocer, A. R. S. Kandada, S. D. Stranks, M. M. Lee, G. Lanzani, H. J. Snaith and A. Petrozza, Nat. Commun., 2014, 5, 3586. \n11 C. Wehrenfennig, G. E. Eperon, M. B. Johnston, H. J. Snaith and L. M. Herz, Adv. Mater., 2014, 26, 1584–1589. \n$12\\mathrm{~T~}$ . Leijtens, S. D. Stranks, G. E. Eperon, R. Lindblad, E. M. J. Johansson, J. M. Ball, M. M. Lee, H. J. Snaith, I. J. McPherson, H. Rensmo, J. M. Ball, M. M. Lee and H. J. Snaith, ACS Nano, 2014, 8, 7155–7174. \n13 E. L. Unger, E. T. Hoke, C. D. Bailie, W. H. Nguyen, A. R. Bowring, T. Heumuller, M. G. Christoforo and M. D. McGehee, Energy Environ. Sci., 2014, 7, 3690–3698. \n14 H. J. Snaith, A. Abate, J. M. Ball, G. E. Eperon, T. Leijtens, N. K. Noel, S. D. Stranks, J. T. Wang, K. Wojciechowski and W. Zhang, J. Phys. Chem. Lett., 2014, 5, 1511–1515. \n15 J. A. Christians, J. S. Manser and P. V. Kamat, J. Phys. Chem. Lett., 2015, 6, 852–857. \n16 Y. Zhang, M. Liu, G. E. Eperon, T. C. Leijtens, D. McMeekin, M. Saliba, W. Zhang, M. de Bastiani, A. Petrozza, L. M. Herz, M. B. Johnston, H. Lin and H. J. Snaith, Mater. Horiz., 2015, 2, 315–322. \n17 Z. Xiao, Y. Yuan, Y. Shao, Q. Wang, Q. Dong, C. Bi, P. Sharma, A. Gruverman and J. Huang, Nat. Mater., 2015, 14, 193–198. \n18 H. Min Zhang, C. Liang, Y. Zhao, M. Sun, H. Liu, J. Liang, D. Li, F. Zhang and Z. He, Phys. Chem. Chem. Phys., 2015, 17, 9613–9618. \n19 J. Beilsten-Edmands, G. E. Eperon, R. D. Johnson, H. J. Snaith and P. G. Radaelli, Appl. Phys. Lett., 2015, 106, 173502. \n20 R. S. Sanchez, V. Gonzalez-Pedro, J. Lee, N. Park, Y. S. Kang, I. Mora-Sero and J. Bisquert, J. Phys. Chem. Lett., 2014, 5, 2357–2363. \n21 J. M. Frost, K. T. Butler and A. Walsh, APL Mater., 2014, 2, 81506. \n22 Y. Kutes, L. Ye, Y. Zhou, S. Pang, B. D. Huey and N. P. Padture, J. Phys. Chem. Lett., 2014, 5, 3335–3339. \n23 S. Liu, F. Zheng, N. Z. Koocher, H. Takenaka, F. Wang and A. M. Rappe, J. Phys. Chem. Lett., 2015, 6, 693–699. \n24 H.-W. Chen, N. Sakai, M. Ikegami and T. Miyasaka, J. Phys. Chem. Lett., 2014, 6, 164–169. \n25 Z. Chen, J. J. Wang, Y. Ren, C. Yu and K. Shum, Appl. Phys. Lett., 2012, 101, 093901. \n26 M. H. Kumar, S. Dharani, W. L. Leong, P. P. Boix, R. R. Prabhakar, T. Baikie, C. Shi, H. Ding, R. Ramesh, M. Asta, M. Graetzel, S. G. Mhaisalkar and N. Mathews, Adv. Mater., 2014, 26, 7122–7127. \n27 N. K. Noel, S. D. Stranks, A. Abate, C. Wehrenfennig, S. Guarnera, A. Haghighirad, A. Sadhanala, G. E. Eperon, S. K. Pathak, M. B. Johnston, A. Petrozza, L. Herz and H. Snaith, Energy Environ. Sci., 2014, 7, 3061–3068. \n28 M. Kulbak, D. Cahen and G. Hodes, J. Phys. Chem. Lett., 2015, 6, 2452–2456. \n29 C. K. Møller, Mat.-Fys. Medd. - K. Dan. Vidensk. Selsk., 1959, 32, 3–18. \n30 H. Choi, J. Jeong, H.-B. Kim, S. Kim, B. Walker, G.-H. Kim and J. Y. Kim, Nano Energy, 2014, 7, 80–85. \n31 L. Protesescu, S. Yakunin, M. I. Bodnarchuk, F. Krieg, R. Caputo, C. H. Hendon, R. X. Yang, A. Walsh and M. V. Kovalenko, Nano Lett., 2015, 15, 3692–3696. \n32 O. N. Yunakova, V. K. Miloslavskii and E. N. Kovalenko, Opt. Spectrosc., 2012, 112, 91–96. \n33 C. K. Moller, Nature, 1958, 182, 1436. \n34 G. E. Eperon, S. D. Stranks, C. Menelaou, M. B. Johnston, L. M. Herz and H. J. Snaith, Energy Environ. Sci., 2014, 7, 982. \n35 J. H. Heo, H. J. Han, D. Kim, T. K. Ahn and S. H. Im, Energy Environ. Sci., 2015, 8, 1602–1608. \n36 H. W. Jang, S. H. Baek, D. Ortiz, C. M. Folkman, R. R. Das, Y. H. Chu, P. Shafer, J. X. Zhang, S. Choudhury, V. Vaithyanathan, Y. B. Chen, D. A. Felker, M. D. Biegalski, M. S. Rzchowski, X. Q. Pan, D. G. Schlom, L. Q. Chen, R. Ramesh and C. B. Eom, Phys. Rev. Lett., 2008, 101, 3–6. \n37 A. J. Hatt, N. A. Spaldin and C. Ederer, Phys. Rev. B: Condens. Matter Mater. Phys., 2010, 81, 1–5. \n38 Y. Tokura, Science, 2000, 288, 462–468. \n39 F. Tsui, M. C. Smoak, T. K. Nath and C. B. Eom, Appl. Phys. Lett., 2000, 76, 2421–2423. \n40 Y. L. Li and L. Q. Chen, Appl. Phys. Lett., 2006, 88, 3–5. \n41 W. H. Nguyen, C. D. Bailie, E. L. Unger and M. D. McGehee, J. Am. Chem. Soc., 2014, 136, 10996–11001. \n42 N. J. Jeon, J. H. Noh, W. S. Yang, Y. C. Kim, S. Ryu, J. Seo and S. Il Seok, Nature, 2015, 517, 476–480. \n43 W. S. Yang, J. H. Noh, N. J. Jeon, Y. C. Kim, S. Ryu, J. Seo and S. I. Seok, Science, 2015, 348, 1234–1237. \n44 W. Tress, N. Marinova, T. Moehl, S. M. Zakeeruddin, M. K. Nazeeruddin and M. Gra¨tzel, Energy Environ. Sci., 2015, 8, 995–1004. \n45 Y. Zhao, C. Liang, H. Min Zhang, D. Li, D. Tian, G. Li, X. Jing, W. Zhang, W. Xiao, Q. Liu, F. Zhang and Z. He, Energy Environ. Sci., 2015, 8, 1256–1260. \n46 K. Wojciechowski, S. D. Stranks, A. Abate, G. Sadoughi, A. Sadhanala, N. Kopidakis, G. Rumbles, C. Li, R. H. Friend, A. K.-Y. Jen and H. J. Snaith, ACS Nano, 2014, 8, 12701–12709. \n47 B. Conings, J. Drijkoningen, N. Gauquelin, A. Babayigit, J. D'Haen, L. D'Olieslaeger, A. Ethirajan, J. Verbeeck, J. Manca, E. Mosconi, F. de Angelis and H. Boyen, Adv. Energy Mater., 2015, 5, DOI: 10.1002/aenm.201500477. " + }, + { + "id": "10.1038_ncomms9668", + "DOI": "10.1038/ncomms9668", + "DOI Link": "http://dx.doi.org/10.1038/ncomms9668", + "Relative Dir Path": "mds/10.1038_ncomms9668", + "Article Title": "Atomic cobalt on nitrogen-doped graphene for hydrogen generation", + "Authors": "Fei, HL; Dong, JC; Arellano-Jiménez, MJ; Ye, GL; Kim, ND; Samuel, ELG; Peng, ZW; Zhu, Z; Qin, F; Bao, JM; Yacaman, MJ; Ajayan, PM; Chen, DL; Tour, JM", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Reduction of water to hydrogen through electrocatalysis holds great promise for clean energy, but its large-scale application relies on the development of inexpensive and efficient catalysts to replace precious platinum catalysts. Here we report an electrocatalyst for hydrogen generation based on very small amounts of cobalt dispersed as individual atoms on nitrogen-doped graphene. This catalyst is robust and highly active in aqueous media with very low overpotentials (30 mV). A variety of analytical techniques and electrochemical measurements suggest that the catalytically active sites are associated with the metal centres coordinated to nitrogen. This unusual atomic constitution of supported metals is suggestive of a new approach to preparing extremely efficient single-atom catalysts.", + "Times Cited, WoS Core": 1468, + "Times Cited, All Databases": 1527, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000364936200011", + "Markdown": "# Atomic cobalt on nitrogen-doped graphene for hydrogen generation \n\nHuilong Fei1, Juncai Dong2, M. Josefina Arellano-Jime´nez3, Gonglan Ye4, Nam Dong Kim1, Errol L.G. Samuel1, Zhiwei Peng1, Zhuan Zhu5, Fan $\\mathsf{Q i n}^{5}.$ , Jiming ${\\mathsf{B a o}}^{5}$ , Miguel Jose Yacaman3, Pulickel M. Ajayan4, Dongliang Chen2 & James M. Tour1,4,6 \n\nReduction of water to hydrogen through electrocatalysis holds great promise for clean energy, but its large-scale application relies on the development of inexpensive and efficient catalysts to replace precious platinum catalysts. Here we report an electrocatalyst for hydrogen generation based on very small amounts of cobalt dispersed as individual atoms on nitrogen-doped graphene. This catalyst is robust and highly active in aqueous media with very low overpotentials $30\\mathsf{m V})$ . A variety of analytical techniques and electrochemical measurements suggest that the catalytically active sites are associated with the metal centres coordinated to nitrogen. This unusual atomic constitution of supported metals is suggestive of a new approach to preparing extremely efficient single-atom catalysts. \n\nElevcotlruotcihoenmirceal rieodn (tiHonERo) iws ae ctlheraon $\\left(\\operatorname{H}_{2}\\right)$ e uhsytadirnoagbelne been proposed as a future energy carrier1,2. Catalysts are needed to improve HER efficiency by minimizing reaction kinetic barriers, which manifest themselves as overpotentials $(\\eta)$ Although platinum $\\mathrm{(Pt)}$ is the most active HER catalyst, its scarcity and high cost limit its widespread use. Thus, the transition to a hydrogen economy calls for alternative electrocatalysts based on earth-abundant elements, such as nonprecious metal oxides3,4, sulfides5, phosphides6,7, carbides8 and borides9. In spite of their low $\\eta$ for HER, the active sites of these inorganic-solid catalysts, like other heterogeneous catalysts, are sparsely distributed at selective sites (that is, surface sites or edges sites)10,11. To expose more active sites, these catalysts are generally downsized into nanoparticulate form and stabilized onto certain substrates12,13. Graphene is such a substrate that has a large specific surface area (high catalyst loading), good stability (tolerance to harsh operational conditions) as well as a high electrical conductivity (facilitated electron transfer) and therefore has been widely used to disperse nanoparticles for advanced electrocatalysis14–16. \n\nThe dispersing ability of graphene is, however, far from being fulfilled unless single-atom catalysis (SAC) is achieved. SAC represents the lowest size limit to obtain full atom utility in a catalyst and has recently emerged as a new research frontier17. Although an increasing number of SAC systems have been reported, most have been focusing on supporting noble metal atoms (for example, $\\mathrm{Pt,}$ Au, Pd) on metal oxide or metal surfaces with a limited number of applications demonstrated18–23. Wide employment of SAC is hampered mainly due to the lack of readily available synthetic approaches originated from the aggregation tendency of single atoms. Here, we report an inexpensive, concise and scalable method to disperse the earth-abundant metal, cobalt, onto nitrogen-doped graphene (denoted as Co-NG) by simply heat-treating graphene oxide (GO) and small amounts of cobalt salts in a gaseous $\\mathrm{NH}_{3}$ atmosphere. These small amounts of cobalt atoms, coordinated to nitrogen atoms on the graphene, can work as extraordinary catalysts towards HER in both acidic and basic water. \n\n# Results \n\nSynthesis and characterization of the Co-NG catalyst. To prepare the Co-NG catalyst, a precursor solution was first prepared by sonicating GO and cobalt salts $(\\mathrm{CoCl}_{2}{\\bullet6}\\mathrm{H}_{2}\\mathrm{O};$ weight ratio ${\\mathrm{GO}}/{\\mathrm{Co}}=135{:}1{\\cdot}$ ) in water. The well-mixed precursor solution, as depicted in Fig. 1a, was then freeze-dried to minimize re-stacking of the GO sheets. The Co-NG catalyst was finally obtained by heating the dried sample under a $\\mathrm{NH}_{3}$ atmosphere to dope the GO with nitrogen. Control samples of nitrogen-doped graphene (NG) and Co-containing graphene (Co-G, with no $\\mathrm{~N~}$ doping) were also prepared. A detailed preparation procedure is described in the Methods section. The morphology of the Co-NG was examined by scanning electron microscopy (SEM); Fig. 1b reveals that the Co-NG has similar morphologic features to graphene with sheet-like structures. Transmission electron microscopy (TEM; Fig. 1c) shows Co-NG nanosheets with ripples observed on the surface. No cobalt-derived particles were found by SEM or TEM on the Co-NG nanosheets, underscoring the smallness in size of the Co. The Co-NG could be formed into a paper by filtration of Co-containing GO suspension and subsequent $\\mathrm{NH}_{3}$ treatment (Fig. 1d). \n\nTo probe the compositions of Co-NG, X-ray photoelectron spectroscopy (XPS; Fig. 2a) showed the presence of C, N and O peaks in the samples of Co-NG and NG, whereas the $\\mathrm{\\DeltaN}$ peak was absent in Co-G. No significant signals were found at the $\\scriptstyle{\\mathrm{Co}}$ region in the Co-NG. To determine the Co content, inductively coupled plasma optical emission spectrometry (ICP-OES) was performed after digesting the powdered sample in ${\\mathrm{HNO}}_{3}$ . By combined use of XPS and ICP-OES, the Co-NG was determined to be $0.57\\ \\mathrm{at\\%}$ Co, $8.5\\ \\mathrm{at\\%}$ N, $2.9\\ \\mathrm{at\\%}$ O and $88.2\\ \\mathrm{at\\%}$ C, as summarized in Fig. 2b. The Co content in NG with no intentional addition of Co is negligible ( $\\mathit{\\Omega}^{'}<0.005\\ \\mathrm{at\\%}$ by ICP-OES). The XPS detailed scan in the $\\scriptstyle{\\mathrm{Co}}$ region (Fig. 2c) of Co-NG shows two peaks at a binding energy of 781.1 and $796.2\\mathrm{eV}$ , corresponding to the $2p_{3/2}$ and $2p_{1/2}$ levels, respectively. The peak positions and the separation of $15.1\\mathrm{eV}$ between these two peaks indicates the presence of $\\mathrm{Co}(\\mathrm{III})^{24}$ . The N 1s (Fig. 2d) can be deconvoluted into different types of nitrogen $^{25,26}$ , namely pyridinic and N-Co $(398.4\\mathrm{eV})$ , pyrrolic $(399.{\\dot{8}}\\mathrm{eV})$ , graphitic $(401.2\\mathrm{eV})$ and N-oxide (402.8). The small difference in the binding energies between pyridinic $\\mathrm{~N~}$ and N-Co prevents further deconvolution27. From the peak intensity, the $\\mathrm{\\DeltaN}$ was dominated by the pyridinic/N-Co species. The C 1s and O 1s XPS were shown in Supplementary Fig. 1. The presence of $\\scriptstyle{\\mathrm{Co}}$ and $\\mathrm{~N~}$ was further confirmed by the energy-dispersive X-ray spectroscopy (EDS) spectrum (Supplementary Fig. 2) taken in the area shown in Fig. 2e of the scanning transmission electron microscopy (STEM) image. The EDS line scan in Fig. 2e reveals the close-proximity distributions of the Co and N elements. \n\n![](images/32706297e7ed8a29467dcc416fc94c69ac57527306e936368f4d0f17551b5ddc.jpg) \nFigure 1 | Preparation and morphology characterizations. (a) Schematic illustration of the synthetic procedure of the Co-NG catalyst. (b) SEM image of the Co-NG nanosheets. Scale bar, $2\\upmu\\mathrm{m}$ . (c) TEM image of the Co-NG nanosheets atop a lacey carbon TEM grid. Scale bar, $50\\mathsf{n m}$ . (d) SEM image showing the cross-section view of the Co-NG paper with thickness of $15\\upmu\\mathrm{m}$ , prepared by filtration of Co-containing GO suspension followed by $N H_{3}$ annealing. Scale bar, $20\\upmu\\mathrm{m}$ . The inset shows the optical image of a $2\\times1\\mathsf{c m}^{2}$ Co-NG paper. \n\n![](images/36ceb1f6322037db52a27222aafb679f39efa6904600c6fe09bc4f1b123f3673.jpg) \nFigure 2 | Compositional characterizations on the Co-NG. (a) XPS survey spectra of the Co-NG, NG and Co-G. (b) Chart showing the percentages of cobalt, nitrogen, oxygen and carbon in the Co-NG measured by XPS and ICP-OES. (c,d) High-resolution ${\\mathsf{X P S}}\\mathsf{C o2p}$ and N 1s spectra, respectively. (e) STEM image of the Co-NG nanosheet. Scale bar, $20\\mathsf{n m}$ . Inset is the EDS elemental line scan from A to B showing the presence of C, N and Co elements. \n\nAtomic structure analysis by HAADF and EXAFS. To investigate the atomic structure of the Co-NG nanosheet, we used highangle annular dark field (HAADF) imaging in an aberrationcorrected STEM. The bright-field STEM image (Fig. 3a) shows the defective structures of the GO-derived graphitic carbon. The corresponding HAADF image (Fig. 3b) clearly shows that several bright dots, corresponding to heavy atoms (Co in this case), are well dispersed in the carbon matrix. The size of these dots is in the range of $2-3\\mathring{\\mathrm{A}}$ , indicating that each bright dot corresponds to one individual Co atom. The enlarged view of the selected region (Fig. 3c) reveals that each Co atom is centred by the light elements (C, N and/or O). Additional STEM images are provided in Supplementary Fig. 3. To probe the possible bonding between the cobalt and the light elements in the Co-NG, we performed extended X-ray absorption fine structure (EXAFS) analysis at the Co $K\\mathrm{\\Omega}$ -edge, using both a wavelet transform (WT) and Fourier transform. WT-EXAFS analysis is a powerful method for separating backscattering atoms that provides not only a radial distance resolution, but also resolution in the $k$ -space28. The discrimination of atoms can be identified even when these atoms overlap substantially in $R$ -space. The $k^{2}$ -weighted $\\chi(\\boldsymbol{k})$ signals (Fig. 3d) and the corresponding Fourier transforms (Fig. 3e) of the Co-NG and Co-G samples show quite similar profiles, suggesting no substantial differences in the coordination environments of the $\\scriptstyle{\\mathrm{Co}}$ atoms. The existence of only one single strong shell, which is usually characteristic of amorphous or poorly crystalline materials, at $\\mathrm{\\sim}1.5\\mathrm{\\AA}$ in $R$ -space (Fig. 3e) is indicative of a large structural disorder around Co sites, consistent with the abundant misplacement and voids observed in the aberration-corrected STEM images. Figure 3f shows the WT contour plots of the two signals based on Morlet wavelets $\\stackrel{\\prime}{\\kappa}=3,\\ \\sigma=1;$ with optimum resolution at the first shell29. The intensity maximum A is well-resolved for the Co-NG $(3.4\\mathring\\mathrm{A}^{-1})$ and Co-G $(3.2\\mathring{\\mathrm{A}}^{-1})$ . Since the locations of the WT maxima are highly predictable, they allow qualitative interpretation of the scattering path origins. The WT maximum is known to be affected by the path length $R,$ Debye–Waller factors $\\sigma^{2}$ , energy shift $\\Delta E$ and atomic number $Z$ , and this corresponds to the same location of the maximum in the $q$ -space magnitude30. For an isolated $_{\\mathrm{Co-C}}$ path $(R=2\\mathring\\mathrm{A})$ , the WT maximum at $3.2\\mathring\\mathrm{A}^{-1}$ in the $q$ -space magnitude showed little dependence on R, $\\sigma^{2}$ and $\\Delta E$ , but it is largely affected by different $\\bar{Z}$ $(3.5\\mathring{\\mathrm{A}}^{-1}$ for Co-N path, $4.3\\mathring\\mathrm{A}^{-1}$ for Co-O path, and $6.8\\mathring{\\mathrm{A}}^{-1}$ for Co-Co path; \n\n![](images/e92f1a4a1b1233356f82b172049fe4c599c1774455cceba67e77a14018ec88c2.jpg) \nFigure 3 | Structural characterizations on the Co-NG. (a) Bright-field aberration-corrected STEM image of the Co-NG showing the defective and disordered graphitic carbon structures. Scale bar, $1\\mathsf{n m}$ . (b) HAADF-STEM image of the Co-NG, showing many Co atoms well-dispersed in the carbon matrix. Scale bar, 1 nm. (c) The enlarged view of the selected area in b. Scale bar, $0.5\\mathsf{n m}$ . (d,e) The $k^{2}$ -weighted EXAFS in $k\\mathrm{.}$ space and their Fourier transforms in $R$ space for the Co-NG and Co-G, respectively. (f) Wavelet transforms for the Co-NG and Co-G. The location of the maximum A shifts from $3.2\\mathring{\\mathsf{A}}^{-1}$ for Co-G to $3.4\\mathring{\\mathsf{A}}^{-1}$ for Co-NG, indicating the presence of Co-N bonding in Co-NG. The vertical dashed lines are provided to guide the eye. \n\nSupplementary Fig. 4). As a result, by comparison, the WT maximum A at $3.2\\mathring\\mathrm{A}^{-1}$ for the Co-G can be associated with the Co-C path, and $3.4\\mathring\\mathrm{A}^{-1}$ for the Co-N path within the Co-NG. A small difference of $\\sim0.1\\mathring\\mathrm{A}^{-1}$ between the maxima A for the Co-NG $(3.4\\mathring{\\mathrm{A}}^{-1})$ and the calculated ${\\mathrm{Co-N}}$ path $(3.5\\mathring\\mathrm{A}^{-1})$ might arise from the much shorter length of the actual Co-N path than $2\\mathring\\mathrm{A}$ . The maximum feature $\\mathbf{B}$ at $9.0\\mathring{\\mathrm{A}}^{-1}$ might result from the effect of side lobes and the multiple scattering paths between the light atoms, instead of from the Co–Co path, which exhibits a maximum at $6.8\\mathring{\\mathrm{A}}^{-1}$ . The validity of the above WT-EXAFS interpretation was confirmed by a least-squares curve fitting analysis carried out for the first coordination shell of $\\scriptstyle\\mathrm{Co}$ (Supplementary Figs 5 and 6 and Supplementary Note 1). \n\nTaken together, the data indicate that in the Co-NG the Co is atomically dispersed in the nitrogen-doped graphene matrix and it is in the ionic state with nitrogen atoms in the cobalt’s first coordination sphere. Hence, nitrogen doping of the graphene provides sites for $\\scriptstyle{\\mathrm{Co}}$ incorporation. \n\nHER activity evaluation. The HER catalytic activity of the CoNG was evaluated using a standard three-electrode electrochemical cell. The catalyst mass loading on a glassy carbon electrode was $285\\upmu\\mathrm{gcm}^{-2}$ . Figure 4a shows the linear-sweep voltammograms (LSVs) at a scan rate of $2\\mathrm{m}\\mathrm{V}\\thinspace\\mathsf{s}^{-1}$ in $0.5\\dot{\\bf M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ after iR-compensation for the $\\mathrm{Co}$ -NG electrode along with the two control samples of NG and Co-G. The commercial $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%}$ platinum on Vulcan carbon black, Alfa Aesar) with the same mass loading was also included as a reference point. As expected, the $\\mathrm{Pt/C}$ exhibits superior HER catalytic activity with a near zero onset $\\eta$ . The Co-NG catalyst shows excellent HER activity, as evidenced by the very small onset $\\eta$ of $\\sim30\\mathrm{mV}$ (inset in Fig. 4a), beyond which the current density increases sharply. The onset $\\eta$ is defined here as the potential at a current density of $-0.3\\mathrm{mAcm}^{-2}$ , which is chosen to match the onset $\\eta$ determined by the Tafel plot (shown later). The $\\eta$ needed to deliver 1 and $10\\dot{\\mathrm{mA}}\\mathrm{cm}^{-2}$ were determined to be $\\sim70$ and $\\sim147\\mathrm{mV}$ respectively. The Faradaic efficiency of the Co-NG catalyst was determined to be $\\sim100\\%$ by gas chromatography (Fig. 4b, Supplementary Fig. 7 and Supplementary Note 2), confirming the cathode current is due to the generation of $\\mathrm{H}_{2}$ . It should be noted that these $\\eta$ values are much smaller than those of $C\\mathrm{{o}}$ -based molecular complexes31–33, and further suggesting that the Co-NG system is one of the best solid-state earth-abundant catalysts, including $\\ensuremath{\\mathrm{MoS}}_{2}$ (refs 15,34), $\\mathrm{WS}_{2}$ (ref. 35), $\\mathrm{CoP}^{36}$ and $\\mathrm{Mo}\\mathbf{\\dot{P}}^{37}$ . Also, this ‘pseudo-metal-free’ catalyst (which contains only 0.57 $a t\\%$ metal) shows much higher activity than all the recently reported metal-free catalysts (Supplementary Table 1 and Supplementary Note 3). As control samples, the NG and Co-G show poor activity towards HER with onset $\\eta$ larger than $200\\mathrm{mV}$ , indicating that the active sites in Co-NG are associated with the Co and N. Tafel analysis (Fig. 4c) gives Tafel slope values of 31, 82, 117 and $144\\mathrm{mV}$ decade ${\\check{-}}1$ for $\\mathrm{Pt/C,}$ Co-NG, NG and Co-G, respectively. Notably, the Tafel plot for the Co-NG catalyst becomes linear at low $\\eta$ of $\\sim30\\mathrm{mV}$ . \n\n![](images/5d8eef1ff1fba58e2530071b83691ef27bb4e48a6163649c4f4b2fea873cd9ac.jpg) \nFigure 4 | HER activity characterizations. (a) LSV of NG, Co-G, Co-NG and $\\mathsf{P t/C}$ in $0.5{\\ensuremath{\\mathsf{M}}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at scan rate of $2{\\mathsf{m}}{\\mathsf{V}}{\\mathsf{s}}^{-1}$ . The inset shows the enlarged view of the LSV for the Co-NG near the onset region. (b) Plot showing the molar number of ${\\sf H}_{2}$ produced as a function of time. The straight line represents the theoretically calculated amounts of ${\\sf H}_{2}$ assuming $100\\%$ Faradaic efficiency, and the scattered dots represent the produced ${\\sf H}_{2}$ measured by gas chromatography. The overlapping of these two sets of data indicates that nearly all the current is due to ${\\sf H}_{2}$ evolution. The error bars arise from instrument uncertainty. $\\mathbf{\\eta}(\\bullet)$ Tafel plots of the polarization curves in a. (d) TOF values of the Co-NG catalyst (black line) along with TOF values for other recently reported catalysts. \n\nWhen tested in alkaline media $\\mathrm{(1M\\NaOH)}$ , the Co-NG catalyst also exhibits improved activity compared with the NG and Co-G (Supplementary Fig. 8 and Supplementary Note 4). This distinguishes the Co-NG catalyst from the $\\mathbf{MoS}_{2}$ and some metal phosphide (for example, ${\\mathrm{Ni}}_{2}{\\mathrm{P}}$ ) catalysts, which are highly active in acid, but are unstable in base and thus their application in alkaline electrolysis is limited2,7. More interestingly, as the precursor suspension of GO containing small amounts of Co is highly stable, it can be formed into a paper (Fig. 1d), which can work as a free-standing electrode for $\\mathrm{H}_{2}$ generation (Supplementary Movie 1). Alternatively, the precursor solution can be readily coated onto a conductive substrate (Supplementary Fig. 9 and and Supplementary Note 5) that can be used as a binder-free electrode (Supplementary Fig. 10) after postannealing in $\\mathrm{NH}_{3}$ . The straightforward and convenient synthetic approach to achieve the Co-NG catalyst adds versatility in the design and construction of electrodes and thus enables easy integration of the catalytic layer with other components in electrochemical devices. \n\n# Discussion \n\nTo investigate the effects of Co content on the catalytic activity, Co-NG catalysts with different Co content (from $0.03\\mathrm{\\at\\%}$ to 1.23 $a t\\%$ , Supplementary Table 2 and Supplementary Note 6) were prepared and their HER activity were evaluated by LSV. The results (Supplementary Fig. 11 and Supplementary Fig. 12) show that HER activity does not increase linearly with the Co content, but instead there is a saturation point for Co content, beyond which the HER activity starts to decrease. This trend might be due to excess Co content; the extra Co atoms would not be able to be incorporated into the C-N lattices in graphene. Instead, the excessive Co would form Co-containing particles or clusters, such as cobalt oxide, as evidenced by the much higher oxygen content in the Co-NG sample with the highest Co content (Supplementary Table 2 and Supplementary Fig. 13). To study the effects of nitrogen doping level on the HER activity, samples with different N doping concentration were prepared by varying the annealing time (Supplementary Figs 14 and 15). The electrochemical measurements (Supplementary Fig. 16 and Supplementary Note 7) show that higher N doping level results in higher HER activity, suggesting the critical role of nitrogen in forming the catalytically active site. The influence of nitrogen doping temperature on HER activity was also studied. The results (Supplementary Fig. 17 and Supplementary Note 8) show that doping temperature above $550^{\\circ}\\mathrm{C}$ is necessary to observe appreciably improved HER activity, which implies that the high temperature was necessary to induce $_{\\mathrm{Co-N}}$ interaction and thus to create Co-N-active sites. The optimized doping temperature was $750^{\\circ}\\mathrm{C}$ with the highest N-doping level (Supplementary Table 3 and Supplementary Fig. 18). These optimizations further suggest that the HER-active sites involve the coupling effects between Co and N. \n\nThe most important figure of merit to evaluate in the intrinsic activity of a catalyst is its turnover frequency (TOF), which gives its activity on a per-site basis. To quantify the number of active sites in Co-NG, each Co centre is considered to account for one active site (see Supplementary Note 9). The contribution from the $\\mathrm{C-N}$ matrix can be ignored as the exchange current density $(i_{0})$ , determined from the Tafel plot by an extrapolation method, for the NG $(8.34\\times10^{-7}\\mathrm{Acm}^{\\div2})$ is much smaller than that of the Co-NG $(1.25\\times10^{-4}\\mathrm{Acm}^{-2})$ . Figure 4d shows the TOF values for the Co-NG catalyst against applied $\\eta$ together with those of eight recently reported non-precious-metal HER catalyst at specific $\\eta$ , including ultra-high vacuum (UHV)-deposited $\\ensuremath{\\mathrm{MoS}}_{2}$ nanocrystals on a Au substrate10, $[\\mathrm{Mo}_{3}\\mathrm{S}_{13}]^{2-}$ nanoclusters supported on graphite paper38, amorphous $\\ensuremath{\\mathrm{MoS}}_{3}$ (ref. 39), Ni-Mo nanopowders40, $\\mathrm{Ni}_{2}\\mathrm{\\dot{P}^{7}}$ , CoP36, MoP41 and MoP|S nanoparticles41. \n\n![](images/40a6224217a4d5566245e2738aa8d3971dc0df5855bc64a7bcaa928175439c11.jpg) \nFigure 5 | HER stability tests. (a) Accelerated stability measurements by recording the polarization curves for the Co-NG catalyst before and after 1,000 cyclic voltammograms at a scan rate of $50\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ under acidic (black curves) and basic conditions (red curves). (b) Plot of $\\eta$ vs t for the $C o{\\tt-N G}$ catalyst at a constant cathodic current density of $10\\mathsf{m A c m}^{-2}$ under acidic and basic conditions. \n\nAt $\\eta$ of 50, 100, 150 and $200\\mathrm{mV}$ , the TOF values of the Co-NG are 0.022, 0.101, 0.386 and $1.189\\mathrm{H}_{2}\\thinspace s^{-1}$ , respectively. These values reveal that the Co-NG is higher than or similar in activity to other reported catalysts, apart from the UHV-deposited $\\mathbf{MoS}_{2}$ nanocrystals and the $[\\dot{\\mathrm{Mo}}_{3}\\dot{\\mathrm{S}}_{13}]^{2-}$ nanoclusters. The TOF value of the Co-NG at thermodynamic potential ( $\\operatorname{\\mathrm{~\\sc~0~V~}}$ vs reversible hydrogen electrode) was also calculated using the exchange current density, which gives a TOF value of $0.0\\dot{0}54\\mathrm{H}_{2}\\thinspace s^{-1}$ . This value is approximately three times smaller than that $(0.0164\\mathrm{H}_{2}\\thinspace s^{-1})$ of the UHV-deposited $\\ensuremath{\\mathrm{MoS}}_{2}$ nanocrystals (the benchmark catalyst on $\\mathrm{MoS}_{2}.$ ). However, it should be noted that unlike the active site selectivity on the edge sites for $\\ensuremath{\\mathrm{MoS}}_{2}$ and on the surface sites for nanoparticulate catalysts including the amorphous $\\mathrm{MoS}_{3}$ , Ni-Mo nanopowders, ${\\mathrm{Ni}}_{2}{\\dot{\\mathrm{P}}}$ , CoP, MoP and $\\mathrm{MoP}|\\bar{\\mathsf{S}}$ , each Co centre in our Co-NG is presumably catalytically active. To estimate the active site density (sites per $\\mathrm{cm}^{2}.$ ), the electrochemically active surface areas were measured (Supplementary Fig. 19), which yields an active site density of $\\sim\\dot{9.7}\\times10^{13}$ sites per $\\mathrm{cm}^{2}$ (see Supplementary Note 10 for details). For comparison, $\\mathrm{Pt}(111)$ has an active site density10 of $1.5\\times10^{15}$ sites per $\\mathrm{cm}^{2}$ . \n\nTo evaluate the stability of the Co-NG catalyst, accelerated degradation studies were performed in both acid and base. As shown in Fig. 5a, the cathodic polarization curves obtained after 1,000 continuous cyclic voltammograms (scan rate: $50\\mathrm{mVs}^{-1}.$ ) shows a negligible decrease in current density compared with the initial curve, indicating the excellent stability of Co-NG in both the acid and base. In addition to the cycling tests, galvanostatic measurements at a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ were performed and the results (Fig. 5b) show that after $\\mathrm{10h}$ of continuous operation the $\\eta$ increased by $35\\mathrm{mV}$ in acid and $17\\mathrm{mV}$ in base, which might be associated with the desorption of some catalysts from the glassy carbon substrate during operation. The catalysts after accelerated cycling were characterized by XPS (Supplementary Figs 20 and 21), $\\mathrm{\\DeltaX}$ -ray diffraction analysis (Supplementary Fig. 22) and HAADF-STEM (Supplementary Fig. 23), which suggest that cycling operation did not change the atomic Co dispersion and the chemical states of Co and $\\mathrm{\\DeltaN}$ (see Supplementary Note 11 for details). The excellent stability of the Co-NG with active sites at the atomic scale can be attributed to the high-temperature-induced strong coordination between the Co and N. \n\nIn conclusion, nitrogen-doped graphene, with negligible intrinsic $\\mathrm{H}_{2}$ -evolving activity, when incorporated with very small amounts of Co as individual atoms can function as a highly active and robust HER catalyst in both acid and base media. This catalyst represents the first example of SAC achieved in inorganic solid-state catalysts for HER. This excellent catalytic performance, maximal efficiency of atomic utility, scalability and low-cost for the preparation makes this catalyst a promising candidate to replace Pt for water splitting applications. In addition, the approach demonstrated in this work in obtaining individual metal atoms that are supported on graphene may be a harbinger for broad applicability of this methodology for other atomic-scale catalytic systems. \n\n# Methods \n\nMaterials synthesis. All chemicals were purchased from Sigma-Aldrich unless otherwise specified. GO was synthesized from graphite flakes $\\cdot\\sim150\\upmu\\mathrm{m}$ flakes) using the improved Hummers method42. \n\nSynthesis of Co-NG. An aqueous suspension of GO $(2\\mathrm{mg}\\mathrm{ml}^{-1},$ was first prepared by adding $100\\mathrm{mg}$ GO into $50\\mathrm{ml}$ deionized water and sonicating (Cole Parmer, model 08849–00) for $^{2\\mathrm{h}}$ . One millilitre $\\mathrm{CoCl}_{2}{\\bullet}6\\mathrm{H}_{2}\\mathrm{O}$ $(3\\mathrm{mg}\\mathrm{ml}^{-1}),$ aqueous solution was added into the GO suspension and sonicated for another $10\\mathrm{min}$ . This precursor solution was freeze-dried for at least $24\\mathrm{h}$ to produce a brownish powder. The dried sample was then placed in the centre of a standard 1-inch quartz tube furnace. After pumping and purging the system with Ar three times, the temperature was ramped at $\\bar{2}0^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ up to $750^{\\circ}\\mathrm{C}$ with the feeding of Ar (150 s.c.c.m.) and $\\mathrm{NH}_{3}$ (50 s.c.c.m.) at ambient pressure (s.c.c.m., standard cubic centimeters per minute). The reaction was allowed to proceed for $^{\\textrm{1h}}$ and the final product Co-NG with a blackish colour was obtained after the furnace was permitted to cool to room temperature under Ar protection. The control sample of Co-G was prepared with the same treatment except $\\mathrm{NH}_{3}$ was not introduced during the annealing process. The control sample of NG was prepared with the same treatment except that the $\\mathrm{CoCl}_{2}{\\bullet}6\\mathrm{H}_{2}\\mathrm{O}$ was not added into the precursor solution. The Co-NG paper was fabricated by first filtering a $25\\mathrm{-ml}$ precursor solution $(2\\mathrm{mg}\\mathrm{ml}^{-1}\\dot{\\mathrm{GO}}$ and $0.06\\mathrm{{mg}m l^{-1}\\dot{C}o C l_{2}\\bullet6H_{2}O\\dot{)}}$ through a $0.22\\mathrm{-}\\upmu\\mathrm{m}$ polytetrafluoroethylene membrane (Whatman). After peeling off the paper from the membrane, the cobalt-containing GO paper was annealed at $750^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ under Ar (150 s.c.c.m.) and ${\\mathrm{NH}}_{3}$ (50 s.c.c.m.) atmosphere in a tube furnace. \n\nCharacterizations. A JEOL 6500F SEM was used to examine the sample morphology. A JEOL 2,100 field emission gun TEM was used to observe the morphologic and structural characteristics of the samples. Aberration-corrected scanning TEM images were taken using an $80\\mathrm{-KeV}$ JEOL ARM200F equipped with a spherical aberration corrector. Chemical compositions and elemental oxidation states of the samples were investigated by XPS spectra with a base pressure of $5\\times10^{-9}$ Torr. The survey spectra were recorded in a $0.5–\\mathrm{eV}$ step size with a pass energy of $140\\mathrm{eV}$ . Detailed scans were recorded in $0.1\\mathrm{eV}$ step sizes with a pass energy of $140\\mathrm{eV}$ . The elemental spectra were all corrected with respect to C1s peaks at $284.8\\mathrm{eV}$ . Cobalt quantitative analysis was carried using a PerkinElmer Optima 4,300 DV ICP-OES. X-ray diffraction) analysis was performed by a Rigaku D/Max Ultima II (Rigaku Corporation) configured with a $\\operatorname{CuK}\\alpha$ radiation, graphite monoichrometer and scintillation counter. The Co $K$ -edge EXAFS spectra were acquired at beamline 1W2B of the Beijing Synchrotron Radiation Facility in fluorescence mode using a fixed-exit Si(111) double crystal monochromator. The incident X-ray beam was monitored by an ionization chamber filled with ${\\bf N}_{2},$ and the X-ray fluorescence detection was performed using a Lytle-type detector filled with Ar. The EXAFS raw data were then background-subtracted, normalized and Fourier transformed by the standard procedures with the IFEFFIT package43. \n\nElectrochemical measurements. The electrochemical measurements were carried out in a three-electrode setup using a CHI 608D workstation (US version). To prepare the working electrode, $4\\mathrm{mg}$ of the catalyst and ${80\\upmu\\mathrm{l}}$ of $5\\mathrm{wt\\%}$ Nafion solution were dispersed in $\\mathrm{1ml}$ of $4{:}1(\\mathrm{v/v})$ water/ethanol with $1{-}2\\mathrm{h}$ bath-sonication (Cole Parmer, model 08849–00) to form a homogeneous suspension. Five microlitres of the catalyst suspension were loaded onto a $3\\mathrm{-mm}$ -diameter glassy carbon electrode (mass loading $\\sim0.285\\mathrm{mgcm}^{-2}$ ). For the counter electrode, a $\\mathrm{\\Pt}$ wire was used. The reference electrode was $\\mathrm{Hg/HgSO_{4}}$ , $\\mathrm{K}_{2}\\mathrm{SO}_{4}(\\mathrm{sat})$ for measurements in 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4},$ and $\\mathrm{Hg/HgO}$ , NaOH (1 M) for measurements in $1\\mathrm{M}\\mathrm{NaOH}$ . Both of these two reference electrodes were calibrated against a reversible hydrogen electrode under the same testing conditions immediately before the catalytic characterizations (Supplementary Figs 24 and 25, and Supplementary Note 12). A scan rate of $2\\mathrm{m}\\mathrm{V}\\mathrm{s}^{-1}$ was used in the cyclic voltammograms of the HER activity unless otherwise noted. The electrolyte solution was sparged with $\\mathrm{H}_{2}$ for $20\\mathrm{min}$ before each test. \n\n# References \n\n1. Walter, M. G. et al. Solar water splitting cells. Chem. Rev. 110, 6446–6473 (2010). \n2. Luo, J. et al. Water photolysis at $12.3\\%$ efficiency via perovskite photovoltaics and earth-abundant catalysts. Science 345, 1593–1596 (2014). \n3. Jin, H. et al. In situ cobalt–cobalt oxide/N-doped carbon hybrids as superior bifunctional electrocatalysts for hydrogen and oxygen evolution. J. Am. Chem. Soc. 137, 2688–2694 (2015). \n4. Gong, M. et al. Nanoscale nickel oxide/nickel heterostructures for active hydrogen evolution electrocatalysis. Nat. Commun 5, 4695 (2014). \n5. Merki, D. & Hu, X. Recent developments of molybdenum and tungsten sulfides as hydrogen evolution catalysts. Energy Environ. Sci. 4, 3878–3888 (2011). \n6. Tian, J., Liu, Q., Asiri, A. M. & Sun, X. Self-supported nanoporous cobalt phosphide nanowire arrays: an efficient 3D hydrogen-evolving cathode over the wide range of pH 0–14. J. Am. Chem. Soc. 136, 7587–7590 (2014). \n7. Popczun, E. J. et al. Nanostructured nickel phosphide as an electrocatalyst for the hydrogen evolution reaction. J. Am. Chem. Soc. 135, 9267–9270 (2013). \n8. Chen, W. F., Muckerman, J. T. & Fujita, E. Recent developments in transition metal carbides and nitrides as hydrogen evolution electrocatalysts. Chem. Commun. 49, 8896–8909 (2013). \n9. Vrubel, H. & Hu, X. Molybdenum boride and carbide catalyze hydrogen evolution in both acidic and basic solutions. Angew. Chem. 124, 12875–12878 (2012). \n10. Jaramillo, T. F. et al. Identification of active edge sites for electrochemical $\\mathrm{H}_{2}$ evolution from $\\ensuremath{\\mathrm{MoS}}_{2}$ nanocatalysts. Science 317, 100–102 (2007). \n11. Chen, C. et al. Highly crystalline multimetallic nanoframes with threedimensional electrocatalytic surfaces. Science 343, 1339–1343 (2014). \n12. Bell, A. T. The impact of nanoscience on heterogeneous catalysis. Science 299, \n1688–1691 (2003). \n13. Jiang, H., Zhu, L., Moon, K. & Wong, C. P. The preparation of stable metal nanoparticles on carbon nanotubes whose surfaces were modified during production. Carbon 45, 655–661 (2007). \n14. Liang, Y., Li, Y., Wang, H. & Dai, H. Strongly coupled inorganic/nanocarbon hybrid materials for advanced electrocatalysis. J. Am. Chem. Soc. 135, \n2013–2036 (2013). \n15. Li, Y. et al. $\\ensuremath{\\mathbf{MoS}}_{2}$ nanoparticles grown on graphene: an advanced catalyst for the hydrogen evolution reaction. J. Am. Chem. Soc. 133, 7296–7299 (2011). \n16. Liu, Q. et al. Carbon nanotubes decorated with CoP nanocrystals: a highly active non-noble-metal nanohybrid electrocatalyst for hydrogen evolution. Angew. Chem. Int. Ed. 53, 6710–6714 (2014). \n17. Yang, X. F. et al. Single-atom catalysts: a new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748 (2013). \n18. Kyriakou, G. et al. Isolated metal atom geometries as a strategy for selective heterogeneous hydrogenations. Science 335, 1209–1212 (2012). \n19. Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}/F e O_{x}}$ . Nat. Chem \n3, 634–641 (2011). \n20. Lin, J. et al. Remarkable performance of $\\mathrm{Ir_{1}/F e O_{x}}$ single-atom catalyst in water gas shift reaction. J. Am. Chem. Soc. 135, 15314–15317 (2013). \n21. Wei, H. et al. $\\mathrm{FeO_{x}}$ -supported platinum single-atom and pseudo-single-atom catalysts for chemoselective hydrogenation of functionalized nitroarenes. Nat. Commun 5, 5634 (2014). \n22. Yang, M., Allard, L. F. & Flytzani-Stephanopoulos, M. Atomically dispersed Au– $\\mathrm{(OH)_{x}}$ species bound on titania catalyze the low-temperature water-gas shift reaction. J. Am. Chem. Soc. 135, 3768–3771 (2013). \n23. Moses-DeBusk, M. et al. CO oxidation on supported single Pt atoms: experimental and ab initio density functional studies of CO interaction with Pt atom on $\\Theta\\mathrm{-}\\mathrm{Al}_{2}\\mathrm{O}_{3}(010)$ surface. J. Am. Chem. Soc. 135, 12634–12645 (2013). \n24. Andreiadis, E. S. et al. Molecular engineering of a cobalt-based electrocatalytic nanomaterial for $\\mathrm{H}_{2}$ evolution under fully aqueous conditions. Nat. Chem 5, \n48–53 (2013). \n25. Xue, Y. et al. Low temperature growth of highly nitrogen-doped single crystal graphene arrays by chemical vapor deposition. J. Am. Chem. Soc. 134, 11060–11063 (2012). \n26. Ferrandon, M. et al. Multitechnique characterization of a polyaniline– iron–carbon oxygen reduction catalyst. J. Phys. Chem. C 116, 16001–16013 (2012). \n27. Wu, G. et al. Synthesis-structure-performance correlation for polyaniline-Me-C non-precious metal cathode catalysts for oxygen reduction in fuel cells. J. Mater. Chem. 21, 11392–11405 (2011). \n28. Funke, H., Scheinost, A. C. & Chukalina, M. Wavelet analysis of extended x-ray absorption fine structure data. Phys. Rev. B 71, 094110 (2005). \n29. Funke, H., Chukalina, M. & Scheinost, A. C. A new FEFF-based wavelet for EXAFS data analysis. J. Synchrotron Radiat. 14, 426–432 (2007). \n30. Savinelli, R. O. & Scott, S. L. Wavelet transform EXAFS analysis of mono- and dimolybdate model compounds and a Mo/HZSM-5 dehydroaromatization catalyst. Phys. Chem. Chem. Phys 12, 5660–5667 (2010). \n31. Sun, Y. et al. Molecular cobalt pentapyridine catalysts for generating hydrogen from water. J. Am. Chem. Soc. 133, 9212–9215 (2011). \n32. Artero, V., Chavarot-Kerlidou, M. & Fontecave, M. Splitting water with cobalt. Angew. Chem. Int. Ed. 50, 7238–7266 (2011). \n33. Cobo, S. et al. A Janus cobalt-based catalytic material for electro-splitting of water. Nat. Mater 11, 802–807 (2012). \n34. Xie, J. et al. Controllable disorder engineering in oxygen-incorporated $\\ensuremath{\\mathrm{MoS}}_{2}$ ultrathin nanosheets for efficient hydrogen evolution. J. Am. Chem. Soc. 135, 17881–17888 (2013). \n35. Cheng, L. et al. Ultrathin $\\mathrm{WS}_{2}$ nanoflakes as a high-performance electrocatalyst for the hydrogen evolution reaction. Angew. Chem. Int. Ed. 53, 7860–7863 (2014). \n36. Popczun, E. J. et al. Highly active electrocatalysis of the hydrogen evolution reaction by cobalt phosphide nanoparticles. Angew. Chem. Int. Ed. 126, 5531–5534 (2014). \n37. Wang, X. et al. Molybdenum phosphide as an efficient electrocatalyst for hydrogen evolution reaction. Energy Environ. Sci 7, 2624–2629 (2014). \n38. Kibsgaard, J., Jaramillo, T. F. & Besenbacher, F. Building an appropriate activesite motif into a hydrogen-evolution catalyst with thiomolybdate $\\mathrm{[Mo}_{3}S_{13}]^{2-}$ clusters. Nat. Chem. 6, 248–253 (2014). \n39. Merki, D., Fierro, S., Vrubel, H. & Hu, X. Amorphous molybdenum sulfide films as catalysts for electrochemical hydrogen production in water. Chem. Sci. 2, 1262–1267 (2011). \n40. McKone, J. R., Sadtler, B. F., Werlang, C. A., Lewis, N. S. & Gray, H. B. Ni–Mo nanopowders for efficient electrochemical hydrogen evolution. ACS Catal 3, 166–169 (2012). \n41. Kibsgaard, J. & Jaramillo, T. F. Molybdenum phosphosulfide: an active, acidstable, earth-abundant catalyst for the hydrogen evolution reaction. Angew. Chem. Int. Ed. 53, 14433–14437 (2014). \n42. Marcano, D. C. et al. Improved synthesis of graphene oxide. ACS Nano 4, 4806–4814 (2010). \n43. Newville, M. IFEFFIT: interactive XAFS analysis and FEFF fitting. J. Synchrotron Radiat. 8, 322–324 (2001). \n\n# Acknowledgements \n\nWe thank Ye Wu from Peking University for insightful discussions on the EXAFS analysis. Funding was provided by the AFOSR MURI program (FA9550-12-1-0035) and the AFOSR (FA9550-14-1-0111). This work was partially supported by a grant from the National Institute on Minority Health and Health Disparities (G12MD007591) from the National Institutes of Health, the Welch Foundation Grant (AX-1615). J.D. and D.C. acknowledge support from the National Natural Science Foundation of China (Grant No. 11475212). J.M.B. acknowledges support from the Robert A. Welch Foundation (E-1728). We also thank China Scholarship Council for partial financial support (to H.F.). \n\n# Author contributions \n\nH.F. discovered the procedure, performed the syntheses, part of the structural characterization and electrochemical tests. J.D. and D.C. performed the EXAFS measurements. M.J.A.-J. conducted the aberration-corrected STEM. G.Y assisted in material synthesis and electrochemical measurements. E.L.G.S. drew the scheme, took photographs and videos, and performed ICP-OES measurements. N.D.K. assisted in HER measurements as well as editing the manuscript. Z.W.P performed the GO synthesis. Z.Z. and F.Q. attained the Faradaic efficiency measurements. J.M.T. oversaw the research in different phases and provided regular guidance and suggestions throughout the research. H.F., J.D., J.B., M.J.Y., P.M.A. and J.M.T. analysed the results and co-wrote the paper. All authors had an opportunity to comment on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Fei, H. et al. Atomic cobalt on nitrogen-doped graphene for hydrogen generation. Nat. Commun. 6:8668 doi: 10.1038/ncomms9668 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.3762_bjnullo.6.181", + "DOI": "10.3762/bjnullo.6.181", + "DOI Link": "http://dx.doi.org/10.3762/bjnullo.6.181", + "Relative Dir Path": "mds/10.3762_bjnullo.6.181", + "Article Title": "nullotechnology in the real world: Redeveloping the nullomaterial consumer products inventory", + "Authors": "Vance, ME; Kuiken, T; Vejerano, EP; McGinnis, SP; Hochella, MF; Rejeski, D; Hull, MS", + "Source Title": "BEILSTEIN JOURNAL OF nullOTECHNOLOGY", + "Abstract": "To document the marketing and distribution of nullo-enabled products into the commercial marketplace, the Woodrow Wilson International Center for Scholars and the Project on Emerging nullotechnologies created the nullotechnology Consumer Products Inventory (CPI) in 2005. The objective of this present work is to redevelop the CPI by leading a research effort to increase the usefulness and reliability of this inventory. We created eight new descriptors for consumer products, including information pertaining to the nullomaterials contained in each product. The project was motivated by the recognition that a diverse group of stakeholders from academia, industry, and state/ federal government had become highly dependent on the inventory as an important resource and bellweather of the pervasiveness of nullotechnology in society. We interviewed 68 nullotechnology experts to assess key information needs. Their answers guided inventory modifications by providing a clear conceptual framework best suited for user expectations. The revised inventory was released in October 2013. It currently lists 1814 consumer products from 622 companies in 32 countries. The Health and Fitness category contains the most products (762, or 42% of the total). Silver is the most frequently used nullomaterial (435 products, or 24%); however, 49% of the products (889) included in the CPI do not provide the composition of the nullomaterial used in them. About 29% of the CPI (528 products) contain nullomaterials suspended in a variety of liquid media and dermal contact is the most likely exposure scenario from their use. The majority (1288 products, or 71%) of the products do not present enough supporting information to corroborate the claim that nullomaterials are used. The modified CPI has enabled crowdsourcing capabilities, which allow users to suggest edits to any entry and permits researchers to upload new findings ranging from human and environmental exposure data to complete life cycle assessments. There are inherent limitations to this type of database, but these modifications to the inventory addressed the majority of criticisms raised in published literature and in surveys of nullotechnology stakeholders and experts. The development of standardized methods and metrics for nullomaterial characterization and labelling in consumer products can lead to greater understanding between the key stakeholders in nullotechnology, especially consumers, researchers, regulators, and industry.", + "Times Cited, WoS Core": 1345, + "Times Cited, All Databases": 1533, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000359834400001", + "Markdown": "# Nanotechnology in the real world: Redeveloping the nanomaterial consumer products inventory \n\nMarina E. Vance\\*1, Todd Kuiken2, Eric P. Vejerano3, Sean P. McGinnis4, Michael F. Hochella Jr.5, David Rejeski2 and Matthew S. Hull1 \n\n# Full Research Paper \n\nAddress: \n\n1Institute for Critical Technology and Applied Science, Virginia Tech, 410 Kelly Hall (0194), 235 Stanger St., Blacksburg, VA 24061, United States, 2Woodrow Wilson International Center for Scholars, One Woodrow Wilson Plaza - 1300 Pennsylvania Ave., NW, Washington, DC 20004, United States, 3Department of Civil & Environmental Engineering, Virginia Tech, 418 Durham Hall (0246), Blacksburg, VA 24061, United States, 4Department of Materials Science and Engineering, Virginia Tech, Holden Hall (0237), Blacksburg, VA 24061, United States and 5Department of Geosciences, Virginia Tech, 4044 Derring Hall (0420), Blacksburg, VA 24061, United States \n\nEmail: Marina E. Vance\\* - marinaeq@vt.edu \n\nBeilstein J. Nanotechnol. 2015, 6, 1769–1780. doi:10.3762/bjnano.6.181 \n\nReceived: 28 March 2015 \nAccepted: 07 August 2015 \nPublished: 21 August 2015 \n\nThis article is part of the Thematic Series \"Nanoinformatics for environmental health and biomedicine\". \n\nGuest Editor: R. Liu \n\n$\\circledcirc$ 2015 Vance et al; licensee Beilstein-Institut. \nLicense and terms: see end of document. \n\n\\* Corresponding author \n\n# Abstract \n\nTo document the marketing and distribution of nano-enabled products into the commercial marketplace, the Woodrow Wilson International Center for Scholars and the Project on Emerging Nanotechnologies created the Nanotechnology Consumer Products Inventory (CPI) in 2005. The objective of this present work is to redevelop the CPI by leading a research effort to increase the usefulness and reliability of this inventory. We created eight new descriptors for consumer products, including information pertaining to the nanomaterials contained in each product. The project was motivated by the recognition that a diverse group of stakeholders from academia, industry, and state/federal government had become highly dependent on the inventory as an important resource and bellweather of the pervasiveness of nanotechnology in society. We interviewed 68 nanotechnology experts to assess key information needs. Their answers guided inventory modifications by providing a clear conceptual framework best suited for user expectations. The revised inventory was released in October 2013. It currently lists 1814 consumer products from 622 companies in 32 countries. The Health and Fitness category contains the most products (762, or $42\\%$ of the total). Silver is the most frequently used nanomaterial (435 products, or $24\\%$ ); however, $49\\%$ of the products (889) included in the CPI do not provide the composition of the nanomaterial used in them. About $29\\%$ of the CPI (528 products) contain nanomaterials suspended in a variety of liquid media and dermal contact is the most likely exposure scenario from their use. The majority (1288 products, or $71\\%$ ) of the products do not present enough supporting information to corroborate the claim that nanomaterials are used. The modified CPI has enabled crowdsourcing capabilities, which allow users to suggest edits to any entry and permits researchers to upload new findings ranging from human and environmental exposure data to complete life cycle assessments. There are inherent limitations to this type of database, but these modifications to the inventory addressed the majority of criticisms raised in published literature and in surveys of nanotechnology stakeholders and experts. The development of standardized methods and metrics for nanomaterial characterization and labelling in consumer products can lead to greater understanding between the key stakeholders in nanotechnology, especially consumers, researchers, regulators, and industry. \n\n# Introduction \n\nAdvancements in the fields of nanoscience and nanotechnology have resulted in myriad possibilities for consumer product applications, many of which have already migrated from laboratory benches into store shelves and e-commerce websites. Nanomaterials have been increasingly incorporated into consumer products, although research is still ongoing on their potential effects to the environment and human health. This research will continue long into the future. \n\nTo document the penetration of nanotechnology in the consumer marketplace, the Woodrow Wilson International Center for Scholars and the Project on Emerging Nanotechnology created the Nanotechnology Consumer Product Inventory (CPI) in 2005, listing 54 products [1]. This first-of-its-kind inventory has become one of the most frequently cited resources showcasing the widespread applications of nanotechnology in consumer products. In 2010, the CPI listed 1012 products from 409 companies in 24 countries. Even though it did not go through substantial updates in the period between 2010 and 2013, it continued being heavily cited in government reports [2] and the scientific literature – the website http://www.nanotechproject.org has been cited over 2,580 times in articles according to Google Scholar – and became a popular indicator of the prevalence of nanotechnology in everyday life and the need to further study its potential social, economical, and environmental impacts [3-6]. The CPI has also been criticized due to its lack of science-based data to support manufacturer claims. Other longstanding suggestions for improvement included: more frequent updates, indications when products were no longer available for purchase by consumers, and the inclusion of more product categories to improve the searchability of the CPI database [7]. \n\nSince the creation of the CPI, other nanotechnology-related inventories have been developed around the world. In 2006, a German company launched a freely accessible internet database of nanotechnology products [8]. The website associated with this database was not accessible at the time of this writing and its last available record is from May 2014, when 586 products were listed. In 2007, Japan’s National Institute of Advanced Industrial Science and Technology created an inventory of “nanotechnology-claimed consumer products” available in Japan [2]. This inventory is freely accessible online and it acknowledges the CPI in its website. At the time of this writing, the inventory listed 541 product lines and 1241 products; its last update occurred in 2010 [9]. In 2009, two European consumer organizations, the European Consumers Organization (BEUC) and the European Consumer Voice in Standardization (ANEC), joined efforts to develop an inventory of “consumer products with nano-claims” available to consumers in Europe [10]. A new inventory was generated annually from 2009 to 2012, but the 2011 and 2012 versions focused exclusively on products containing silver nanoparticles (nanosilver); the latest version in 2012 listed 141 nanosilver products. This inventory does not provide a searchable online database, but it can be downloaded for free as an Excel spreadsheet. In 2012, the Danish Consumer Council and Ecological Council and the Technical University of Denmark’s Department of Environmental Engineering launched “The Nanodatabase”, an inventory of products available for purchase that are claimed to contain nanomaterials and are available in the European consumer market [11]. This inventory has been continually updated and it currently lists 1423 products. \n\nThese worldwide efforts to understand the transition of nanotechnology from the laboratory bench to the commercial marketplace substantiate the need for applying the concept of nanoinformatics to a nanotechnology-enabled consumer products database, which is to determine the most relevant and useful information needed by a variety of stakeholders and to develop tools for its most effective use [12]. Databases such as the CPI offer information useful and relevant to a variety of stakeholders who are interested in a) understanding which consumer products incorporate nanotechnology and b) developing strategies, tools, and policies that may be needed to ensure safe and responsible use of those products. \n\nNanomaterials are regulated without specific provisions in the U.S. as hazardous chemical substances and pesticides, under the EPA’s Toxic Substances Control Act (TSCA) [13] and the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) [14]. When used as food additives, drugs, or cosmetics, nanomaterials are regulated under the Federal Food, Drug, and Cosmetic Act (FFDCA). \n\nIn the European Union, nanomaterials are regulated under the Concerning the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) and the Classification, Labeling, and Packaging (CLP) regulations when those are classified by the Commission as hazardous chemical substances [15]. The Biocidal Products Regulation (BPR) has special provisions for biocidal materials that consist of nanoparticles, aggregates, or agglomerates in which at least $50\\%$ of primary particles have at least one dimension between 1 and $100~\\mathrm{{nm}}$ , with no provisions for “novel properties” stemming from their small size [16]. Cosmetics that contain nanomaterials are also regulated by the European Commission, and although the use of nanoscale titanium dioxide is permitted, zinc oxide is not [17]. The German Federal Environment Agency performed an Impact Assessment of a European Register of Products Containing Nanomaterials and determined that when compared to the implementation of a variety of national registries, an unified European registry would bring many advantages, including a lower cost for industries and, ultimately, a registry would benefit consumers, companies, and governments [18]. \n\nThe objective of this work was to modify the CPI to improve its functionality, reliability, and utility to the diverse group of stakeholders who have come to depend on it as a critical resource for current information on nano-enabled consumer products. Specific objectives were (1) to update the CPI data to gain an insight into the penetration of nanotechnology in the consumer products market over the past decade; (2) to determine and implement improvements to the CPI based on the scientific literature and a survey of nanotechnology experts and CPI users; and to (3) develop a sustainable model to facilitate future CPI maintenance using crowdsourcing tools. \n\nBelow, we present a brief history of this inventory over a decade of existence. We also describe the specific changes made in the inventory during this project (referred here as CPI 2.0). Finally, we present an overview of the current data present in the CPI after the completion of this project. \n\n# Results and Discussion CPI growth over time \n\nTable 1 lists the growth of the CPI since 2005. In 2011, before this current project, the CPI described 1314 products. Since then, 489 products that are no longer available or marketed as containing nanotechnology have been archived and 500 products have been added. The new total of 1814 products as of March 2015 represents a thirty-fold increase over the 54 products originally listed in 2005 – which is not a complete representation of the growth of this market, as our methodology has also evolved over time. Based on our review, the CPI is the largest online inventory of nanotechnology consumer products available. Products come from 622 companies located in 32 countries (Supporting Information File 1, Table S1). \n\nThe products listed on the $\\mathrm{CPI}2.0$ satisfy three criteria: (1) they can be readily purchased by consumers; (2) they are claimed to contain nanomaterials by the manufacturer or another source; and (3) their claim to contain nanomaterials appears reasonable to CPI curatorial staff. \n\nAlthough the steady growth of the inventory indicates that the popularity of products claimed to incorporate nanotechnology is continually increasing, not all products have persisted in the consumer market. In the past seven years, $34\\%$ of the entries in the inventory have been archived because the product is not currently available in the market or their claim to contain nanotechnology can no longer be verified. One example of a claim that can no longer be verified is a product that is still available for purchase on a manufacturer’s website but no longer references, explicitly, the incorporation of nanotechnology into that product. Even after archiving, a product can return to the main inventory listing if a third party makes the claim that the product indeed contains nanomaterials or if the manufacturer restates their nanomaterial claim. \n\n
Table 1: Number of products in the CPl over time.
YearTotal products Products addedProducts archivedData collection notes
200554540Beginning of CPl as a static pdf document.
20063563020Launch of the online CPl.
20075802780Nanoscale silver emerged as most cited nanomaterial.
20088032230Health and fitness products represented 6o% of the inventory.
20091015212107Added archiving function to the CPl.
2010101500No data collected.
2011101500No data collected.
201214384260Beginning of CPl 2.0 project, focus on adding new products.
20131628190288Launch of crowdsourcing component. Extensive effort put into adding and archiving products.
20141814a238a223aExtensive effort put into adding and archiving products.
\n\naThe CPI now has crowdsourcing capabilities, so these numbers are a snapshot in time and will not represent the CPI at the time of reading. \n\nIn the CPI, entries are grouped under eight generally accepted consumer goods categories that are loosely based on publicly available consumer product classification systems (Figure 1) [19]. The Health and Fitness category includes the largest listing of products in the CPI, comprising $42\\%$ of listed products (excluding archived products). Within the Health and Fitness category, Personal Care products (e.g., toothbrushes, lotions, and hairstyling tools and products) comprise the largest subcategory $39\\%$ of products). Starting in 2012, a large continual effort has been put into periodically checking products for their current availability and current claim to contain nanotechnology. This effort resulted in archiving 316 products in the Health and Fitness category – mainly in the Personal Care and Clothing subcategories – with 86 and 78 products archived between 2012 and 2014, respectively. \n\n![](images/9541ed43044947d0faa27bb1802e77fb2bd35377d63a71779a9c65a9a94886b1.jpg) \nFigure 1: Number of available products over time (since 2007) in each major category and in the Health and Fitness subcategories. \n\n# New nanomaterial descriptors \n\nEight new product descriptors were introduced to facilitate the use of this database by a variety of stakeholders (namely industry and the scientific and regulatory communities): \n\n1. main nanomaterial composition or type, \n2. nanomaterial shape and size, \n3. nanomaterial coating or stabilizing agent, \n4. nanomaterial location within the product, \n5. nanomaterial function in the product, \n6. potential exposure pathways, \n7. “how much we know”, \n8. “researchers say”. \n\nThe experimental section of this paper describes all new product descriptors. The results of the five new quantitative descriptors are presented and discussed below. Since the “nanomaterial shape and size”, “coating and stabilizing agent”, and the “researchers say” categories are text-entry data fields, thus qualitative information at this point, we have not included their analysis in this paper. \n\n# Nanomaterial composition \n\nOf the 1814 products listed in the CPI, $47\\%$ (846 products) advertise the composition of at least one nanomaterial component and 62 of those products list more than one nanomaterial component (e.g., a product comprised of both silver and titanium dioxide nanomaterials). There are 39 different types of nanomaterial components listed in the inventory (listed in Supporting Information File 1, Table S2), which have been grouped into five major categories in Figure 2 and Figure 4, to improve their legibility: metal, carbonaceous, silicon, not advertised, and other. Nominally, metals and metal oxides comprise the largest nanomaterial composition group advertised in the inventory, listed in $37\\%$ of products. \n\nTitanium dioxide $\\mathrm{(TiO}_{2}\\mathrm{)}$ ), silicon dioxide, and zinc oxide are the most produced nanomaterials worldwide (on a mass basis) and the global annual production of silver nanoparticles represents only $2\\%$ of that of $\\mathrm{TiO}_{2}$ [20,21]. However, silver nanoparticles are the most popular advertised nanomaterial in the CPI, present in 438 products $(24\\%)$ . The CPI reports the numbers of different consumer products and product lines available in the market, so there is no implication on mass, volume, or concentration of nanomaterials incorporated into products or the production volume of each product. \n\nOf carbonaceous nanomaterials (89 products), the majority of products listed contains carbon nanoparticles (sometimes described as carbon black, 39 products) and single- or multiwalled carbon nanotubes (CNT, 38 products). Unfortunately, \n\n891 $(49\\%)$ of the products included in the CPI do not present the composition or a detailed description of the nanomaterial used (Figure 2). \n\n![](images/1be3cd7a31c486d8f784b50f166c8e887b9c5f3f7a6400aef74b02e9ed86ded6.jpg) \nFigure 2: (a) Claimed composition of nanomaterials listed in the CPI, grouped into five major categories: not advertised, metal (including metals and metal oxides), carbonaceous nanomaterials (carbon black, carbon nanotubes, fullerenes, graphene), silicon-based nanomaterials (silicon and silica), and other (organics, polymers, ceramics, etc.). (b) Claimed elemental composition of nanomaterials listed in the metals category: silver, titanium, zinc, gold, and other metals (magnesium, aluminum oxide, copper, platinum, iron and iron oxides, etc.). (c) Claimed carbonaceous nanomaterials (CNT $\\mathbf{\\tau}=\\mathbf{\\tau}$ carbon nanotubes). \n\nThe percentages of nanomaterial compositions in the CPI 2.0 are somewhat in agreement with those of the Danish Nanodatabase. The Nanodatabase also lists a high fraction of products with unknown nanomaterial composition (944 products or $66\\%$ ) and, among known compositions, silver is also the most frequently advertised nanomaterial component, with 207 products or $14.5\\%$ [11]. Silver nanoparticles are popular consumer product additives due to their well-documented antimicrobial properties [22]. \n\nFigure 3 shows how the availability of these major nanomaterial composition groups changed over time. Since the start of the $\\mathrm{CPI}2.0$ project (2012), products with unknown (not advertised) nanomaterial compositions have decreased by $12\\%$ , which is partially due to these products being archived and of their composition being identified and added to the inventory. Products advertising to contain metal and metal oxide nanomaterials, silicon-based nanomaterials (mostly $\\mathrm{SiO}_{2}$ nanoparticles), and a variety of other nanomaterial components (organics, ceramics, polymers, clays, nanocellulose, liposomes, nano micelles, carnauba wax, etc.) have been growing in popularity. During the same period, carbonaceous nanomaterials have remained stable at around 50 products available in the market. \n\nOf the 846 products listed in the CPI for which we were able to determine a nanomaterial composition, 61 products $(7\\%)$ advertise to contain more than one main nanomaterial component. Figure 4 presents 11 nanomaterial components that were most frequently listed with others in the same product. \n\n![](images/4d28b21e8528a9a07dd44cc5a99c5fa89ec31886c476b691ccb795e25c828158.jpg) \nFigure 3: Major nanomaterial composition groups over time. Carbon $\\mathbf{\\tau}=\\mathbf{\\tau}$ carbonaceous nanomaterials (carbon black, carbon nanotubes, fullerenes, graphene). Other $\\mathbf{\\tau}=\\mathbf{\\tau}$ organics, ceramics, polymers, clays, nanocellulose, liposomes, nano micelles, carnauba wax, etc. Note the difference in scale between the top and bottom panels in this plot. \n\nSilver and titanium dioxide are the nanomaterial components most likely to be combined with other nanomaterials in consumer products, with 35 and 30 product combinations, respectively. Silver and titanium dioxide were paired with each other in 10 products (cosmetics and electronics); titanium dioxide and zinc oxide were paired in 10 products (sunscreens, cosmetics, and paints). The European Commission’s Cosmetics Regulation has permitted the use of nanoscale titanium dioxide in sunscreens, but not zinc oxide [17]. \n\nCalcium and magnesium were listed together in dietary supplements. Nano-ceramics and silver are used in combination in water filtration products, cosmetics, and a humidifier. These results demonstrate the use of nanohybrids [23] in consumer products and indicate that the use of nanotechnology-based consumer products in the home may, in some cases, lead to multiple exposures from a combination of nanomaterial compositions. These results suggest the need to examine nanomaterial toxicity effects that could be synergistic, additive, or even antagonistic. \n\n![](images/7cc82540f892fa7d7b30d4bc5aeee4368e4a1168e52871b9b4c55f374403f31d.jpg) \nFigure 4: Major nanomaterial composition pairs in consumer products Carbonaceous nanomaterials (carbon black, carbon nanotubes, fullerene, and graphene) were combined into the same category (carbon). Grey boxes in the diagonal represent the total times each nanomaterial composition has been listed with other compositions in the same product. \n\nirons, textiles). Figure 5 shows the location of nanomaterials for which a composition has been identified [24]. \n\nThe majority $(64\\%)$ of carbonaceous nanomaterials are embedded in solid products, whereas products of all other compositions are more commonly suspended in liquid. Of the few bulk nanomaterials that are available for purchase by consumers, the largest group $(42\\%)$ consists of metal and metal oxide nanomaterials. Metals and metal oxides were also the largest composition for surface-bound particles and those suspended in liquid products. The majority $(67\\%)$ of products with nanostructured surfaces consist of nanomaterials of undetermined composition. An example of such product is a liquid or spray products that forms a nanofilm upon application over a surface. Of nanostructured bulk materials, the majority $(57\\%)$ are siliconbased nanomaterials (e.g., computer processor parts). It is interesting to note that we expect nano-electronics to exist now in massive numbers of consumer products, such as mobile devices, where field effect transistors, the heart of chip technology, have components (sources, gates, collectors, channels) that are now in the nanoscale [25] and would fit into the nanostructured bulk category. However, because most of these products do not advertise their use of nanomaterials, we believe that they are grossly underrepresented in the CPI. \n\n# Nanomaterial location \n\nAbout $29\\%$ of consumer products in the CPI (528 products) contain nanomaterials suspended in a variety of fluids (e.g., water, skin lotion, oil, car lubricant). The second largest group in this category – with 307 products – comprises solid products with surface-bound nanoparticles (e.g., hair curling and flat \n\n# Nanomaterial function \n\nOf the 1814 inventory entries, 1244 were grouped according to the expected benefits of adding such nanomaterials to the product (Figure 6). A significant portion of products in the CPI $31\\%$ of products analyzed) utilize nanomaterials – mostly silver nanoparticles, but also titanium dioxide and others – to confer antimicrobial protection. Nanomaterials such as titanium dioxide and silicon dioxide are used to provide protective coatings $(15\\%)$ and for environmental treatment (to protect products against environmental damage or to treat air and water in the home, $15\\%$ ). Cosmetic products $(12\\%)$ are advertised to contain a variety of nanomaterials such as silver nanoparticles, titanium dioxide, nano-organics, gold, and others. A wide variety of nanomaterial compositions (silver, nano-organics, calcium, gold, silicon dioxide, magnesium, ceramics, etc.) were also advertised to be used for health applications, such as dietary supplements $(11\\%)$ . \n\n![](images/92059e0ef8d6a64f916a4a3fb7bfcc83edce106f5d8cc91e8eb81188a2eadb64.jpg) \nFigure 5: Locations of nanomaterials in consumer products for which a nanomaterial composition has been identified. \n\n![](images/a5e9b638649292e369e596f1091db5d23ce9c8d7eda401961183504ddb4cf3dd.jpg) \nFigure 6: Expected benefits of incorporating nanomaterial additives into consumer products. \n\n# Potential exposure pathways \n\nSince critical information such as nanomaterial size and concentration are not known for most products listed on the CPI, the actual health risks of these products remain largely unknown. Nevertheless, the CPI may be useful for inferring potential exposure pathways from the expected normal use of listed products. To investigate this utility, we analyzed a subset of 770 products from the CPI to determine their most likely route(s) of exposure (Figure 7). \n\n![](images/ecd4ed4245d9ebe464cc1baf9e27bd81bc25f1879727441776b75bce2daa8a47.jpg) \nFigure 7: Potential exposure pathways from the expected normal use of consumer products, grouped by major nanomaterial composition categories. \n\nWe identified the skin as the primary route of exposure for nanomaterials from the use of consumer products $58\\%$ of products evaluated). This is because many entries in the CPI consist of (1) solid products that contain nanomaterials on their surfaces and are meant to be touched or (2) liquid products containing nanomaterial suspensions which are meant to be applied on the skin or hair. Of the products evaluated, $25\\%$ present nanomaterials that can possibly be inhaled during normal use (e.g., sprays and hair driers) and $16\\%$ contain nanomaterials that may be ingested (e.g., supplements and throat sprays). Hansen et al. developed a framework for exposure assessment in consumer products. In this framework, products that contain nanomaterials suspended in liquid and products that may emit airborne nanoparticles during use are expected to cause exposure [26]. \n\nSince metals and metal oxides are the most common nanomaterial composition in the CPI, they are also the most likely materials to which consumers will be exposed during the normal use of product via dermal, ingestion, and inhalation routes. Products containing nanomaterials of unknown composition are most likely to lead to exposure via the dermal route. \n\nBerube et al. [7] offered a critique of the original CPI in 2010, which focused primarily on the lack of data pertinent to the dosages of nanomaterials to which consumers might be exposed through CPI-listed products. This is a valid criticism given that information used to populate the CPI is based primarily on marketing claims made by manufacturers. However, the most recent modifications of the CPI offer a potential remedy for data gaps through the contributions of third-party research teams. These modifications are especially timely as there is a growing number of published studies assessing consumer exposure to nanomaterials released during the use of nanotechnologyenhanced consumer products [27], such as cosmetic powders [28], sprays [29,30], general household products [31], and products for children [32,33]. One challenge is that there are no standardized methods for assessing consumer risks from using nanotechnology-enabled consumer products or a set of agreedupon metrics for characterizing nanomaterials to determine environmentally relevant concentrations [34]. The development of such standards is seen as a top strategy for safe and sustainable nanotechnology development in the next decade [35]. The Consumer Product Safety Commission recently requested \\$7 million to establish the Center for Consumer Product Applications and Safety Implications of Nanotechnology to help develop methods to identify nanomaterials in consumer products and to understand human exposure to those materials [36]. \n\n# How much we know \n\nThrough the “How much we know” descriptor, inventory en tr ies ar e r ated acco r d in g to th e r eliab ility o f th e manufacturer’s claim that products contain nanomaterials. We evaluated 1259 products present in the inventory for the “How much we know” descriptor and the majority $(71\\%)$ of products are not accompanied by information sufficient to support claims that nanomaterials are indeed used in the products, such as a manufacturer datasheet containing technical information about nanomaterial components (e.g., median size, size distribution, morphology, concentration). Only nine products have been classified in Category 1, “Extensively verified claim” due to the availability of scientific papers or patents describing the nanomaterials used in these products (Figure 8). The experimental section, below, presents a full description of these categories. \n\n![](images/5d5a5387f95d0bf7ed5e27e0a1ede7f725ab721c284b81130a15cd1cc1d9cee9.jpg) \nFigure 8: Distribution of products into the “How much we know” categories. \n\nHansen [37] performed interviews with 26 nanotechnology stakeholders who agreed on an incremental approach to nanomaterial regulation in consumer products, including classification and labeling. The European Commission’s Classification, Labeling, and Packaging (CLP) regulation covers nanomaterials that are classified by the Commission as hazardous chemical substances [15]. Becker [38] reported that there are diverging opinions in the nanotechnology industry with regards to labeling, ranging from ‘‘If it’s a nano-scale material, people should know, hands down” to not supporting labeling because “it wouldn’t accurately inform consumers of anything and would be bad for business because it would scare consumers.” \n\n# Nanotechnology expert survey \n\nAppropriate nanomaterial labeling containing sufficient technical information (i.e., at a minimum, nanomaterial composition, concentration, and median size) would better inform consumers and highly benefit researchers interested in understanding consumers’ exposure and nanomaterial fate and transport in the environment. \n\n# Crowdsourcing \n\nSince October 29, 2013, when the modified inventory (CPI 2.0) was released, 557 new user accounts have been requested. Of these, only approximately 10 users who were not directly or indirectly involved in the research team performing the CPI upgrade and maintenance suggested updates or edits to CPI entries. These edits have all been suggested by users from industry and academia. \n\nFuture work is needed to better educate users on their role as curators of $\\mathrm{CPI}~2.0$ and the importance of the data they contribute. Providing the supporting technical data required to verify the nature and quantity of nanomaterial components in CPI-listed products is a massive undertaking, and no single laboratory can accomplish it on its own or within a short amount of time. A long-term solution is to promote the importance of crowd-sourcing data collection and implementing standard data collection and reporting best practices that can help reliably populate the CPI with much needed supporting data. The new crowd-sourcing capability can also be used to provide high school-, undergraduate- and graduate-level educators with meaningful assignments that can help teach students about the prevalence of nanotechnology in everyday products and will contribute to the continued growth of this resource. \n\nThe survey was submitted to 147 people who have published research papers or reports in the applications of nanotechnology in consumer products and its potential impacts, participated in recent conferences in the field, or were notably involved in the field of nanotechnology and the consumer products industry. The survey had a $46\\%$ response rate (68 respondents), which is in the expected range for this type of survey [39]. The majority of respondents $(59\\%)$ ) had six to ten years of experience working with nanotechnology and $38\\%$ of respondents had more than ten years of experience. Half $(51\\%)$ of respondents work in academic institutions and $25\\%$ work in governmental agencies. Most respondents $(88\\%)$ ) have previously used the CPI in their work, and all respondents believe they will or may use it again in the future. \n\nResults convey a general belief or hope that the CPI will become more useful after the modifications reported in this publication. When asked the following open-ended questions: “How did you use the CPI in your work?” and “To what end do you think you might use the CPI in the future?”, answers could be easily grouped into three main categories: (1) for raising awareness, teaching, or for urging the need for regulation, (2) to justify the need for research in research proposals or papers, and (3) to use the inventory data for research (Figure 9). \n\nHalf the respondents $(51\\%)$ have used the CPI in the past to gather data for research (e.g., searching for consumer products of a certain nanomaterial composition to understand their potential applications or consumer exposure) while $74\\%$ believe they will use the CPI for that purpose in the future. The majority $(79\\%)$ of survey respondents believed the modified CPI would present more products than its previous version, which indicates their belief in the growing prevalence of nanotechnology in consumer products. \n\n![](images/7d09be830354f75f37af35c0406e29c6fdcd4a64166bb9d9a25bef07e2006671.jpg) \nFigure 9: Nanotechnology survey answers on how respondents have used the CPI in the past and how they might use it in the future. \n\nSurvey respondents suggested a number of new categories of information for the CPI 2.0, including nanomaterial type or composition, location of nanomaterial within the product, nanomaterial size, relevant scientific publications that describe the products in the inventory, a summary of known toxicity of the advertised nanomaterial, supply chain information, volume produced, and life cycle assessment information. \n\nMost of these suggestions were included in the CPI 2.0 as the new categories described in this work. Others, such as known nanomaterials toxicity were not pursued since toxicity can vary greatly depending on particle size, coating, and exposure route (e.g., inhalation versus ingestion). \n\nPiccinno et al. and Keller et al. provide global estimates for production and major applications of nanomaterials [20,21]. We recommend that future work associated with this inventory or others include information on the production volumes for each product, since this information is presently unavailable. \n\nAdditional results from this survey are available in Supporting Information File 1. \n\nability of the data associated with each entry. Finally, the CPI 2.0 has enabled crowdsourcing capabilities, which allow registered users to upload new findings such as basic product composition information, human and environmental exposure data, and complete life cycle assessments. There are inherent limitations to this type of database, but recent improvements address the majority of issues raised in published literature and in a survey of nanotechnology experts. \n\nImprovements to the CPI were motivated, in part, by the recognition that it represents and will continue to represent an important information resource for a broad range of stakeholders, especially consumers and the academic and regulatory communities. The CPI is a useful interactive database for educating consumers and legislators on the real-world applications of nanotechnology. Michaelson stated that the CPI transformed “the face of nanotechnology away from innovations in the realm of science fiction to the iconic images of everyday consumer products” [2]. The academic community can continue to make use of this inventory to help prioritize, for example, which types of products or nanomaterial components to evaluate in human exposure or toxicity studies, life cycle assessments, and nanomaterial release studies. \n\nThe CPI is useful for policy makers interested in regulating nanotechnology in consumer products by understanding their increasing numbers in the market, the main nanomaterial components that are chosen by manufacturers, and the likelihood for exposure. Beaudrie et al. [40] urge that there should be regulatory reforms to improve oversight of nanomaterials throughout their life cycle. \n\nFinally, the current lack of global standardized methods and metrics for nanomaterial characterization and labeling in consumer products is an issue that, if addressed, can lead to greater understanding between the key stakeholders in nanotechnology, especially researchers, regulators, and industry. Further, as we recognize the growing importance of tools like the CPI for the needs of diverse stakeholder groups, steps should be taken to help ensure that those tools are fully developed and refined to meet those needs. \n\n# Conclusion \n\nThe modified version of the Wilson Center’s nanotechnology consumer products inventory (CPI 2.0) was released in October 2013. We improved the searchability and utility of the inventory by including new descriptors for both the consumer products and the nanomaterial components of those products (e.g., size, concentration, and potential exposure routes). The updated CPI 2.0 now links listed products to published scientific information, where available, and includes a metric to assess the reli \n\n# Experimental Nanotechnology expert survey \n\nTo determine potentially useful improvements for the CPI, we developed a web-based survey to gather the informed opinions of nanotechnology experts – mostly in US-based academic institutions, governmental agencies, and research centers. Their answers guided the CPI modifications and provided an idea of the expectations related to the inventory. The survey questions are presented in the Supporting Information File 1. \n\n# New descriptors \n\nTo improve the utility and searchability of this database, seven product descriptors were created. Entries in the inventory were revised to go beyond a categorization of the consumer products and instead, to include more information on the nanomaterials themselves. We searched for this information mainly on the internet – on manufacturer’s websites, retailer’s websites, news sites and blogs, patents – and, when available, product labels. \n\n# Nanomaterial composition \n\nThe main composition of the nanomaterials used. This information, when available, was added to the database in the form of a check-box list, in which more than one nanomaterial composition can be selected for each consumer product. \n\n# Nanomaterial shape and size \n\nBecause there are many different ways in which manufacturers can measure and describe the shape and size of nanomaterials in consumer products (i.e., units of nanometers or micrometers, thickness of nanofilms, diameter or length of fibers or tubes, diameter or radius of nanoparticles, maximum, median, average, or minimum size), this descriptor was added as a text entry field in the database, which allows for any form of data entry but makes data analysis cumbersome. \n\n• Suspended in liquid: Nanomaterials suspended in a liquid product (e.g., disinfecting sprays, liquid supplements) • Suspended in solid: Nanomaterials suspended in a solid matrix, usually plastic or metal (e.g., composites of carbon nanotubes in a plastic matrix to confer strength). \n\n# Nanomaterial function \n\nWe created a metric to describe the reason why nanotechnology was added to each consumer product or the function it performs within each product. We investigated a subset of 1244 products in the CPI for each product’s intended use, the manufacturer claims, and, most importantly, the type or composition of nanomaterials used to infer potential nanomaterial functions (e.g., antimicrobial protection, hardness and strength, pigment). \n\n# Potential exposure pathways \n\nUsing methodology similar to that applied for the “nanomaterial functions” category, we investigated the CPI entries for possible exposure scenarios resulting from the expected normal use of each consumer product. Entries were only populated when a potential exposure risk was identified. \n\nWe created another text entry field in the CPI to include any available information on the coatings or stabilizing agent used along the nanomaterials in each product. \n\n# Nanomaterial location \n\nTo assist CPI users in understanding the potential for nanomaterial release and exposure scenarios from the use of these consumer products, we created a qualitative descriptor for the location of nanomaterials within each product. We adapted the categorization framework for nanomaterials from Hansen et al. [24] to determine the following nanomaterial locations within products: \n\n# Coatings \n\n• Bulk: Nanomaterials sold in powder form or in liquid suspensions \n• Nanostructured bulk: Products or parts that contain nanostructured features in bulk (e.g., nanoscale computer processors) \n• Nanostructured surface: Products or parts that contain nanostructured features on their surface (e.g., nanofilmcoated products) \n• Surface-bound particles: Nanoparticles added to the surface of a solid product or part (e.g., a computer keyboard coated with silver nanoparticles for antimicrobial protection) \n\n# How much we know \n\nIn an effort to verify the data associated with each product listed on the CPI, we created a metric called “How much we know”. Products were divided into five categories based on the information available to substantiate manufacturer claims that a particular product contains nanomaterial components (Table 2). Category 4, “Unsupported claim”, is the default category for products added to the CPI based soley on a manufacturer’s marketing claims. A product can rise in ranking according to the amount of information that is available to corroborate the manufacturer’s claim that the product contains nanomaterials. If the manufacturer provides supporting information (e.g., a datasheet containing electron micrographs showing the nanomaterials or a particle size distribution), the product is placed in Category 3, “Manufacturer-supported claim”. If a third-party further supports the information provided by the manufacturer, such as through a publication or technical report, then the product can be placed into Category 2, “Verified claim”. If a product is backed by multiple science-based sources (e.g., a peerreviewed scientific paper or patent documentation), it is then placed in Category 1, “Extensively verified claim”. Category 5, “Not advertised by the manufacturer”, is a special class for products that have been shown to contain nanomaterials but the manufacturer does not advertise this fact anywhere in product labeling or other informational materials. Category 5 has been added in recognition of the fact that not all nano-enabled products are marketed by manufacturers as such. \n\nTable 2: “How much we know” categorization, based on the information available to substantiate manufacturer claims that a particular product \n\n\n
contains nanomaterial components.
CategoryManu faturer hlaimgyo Mupfrtiginr providesThird-party information is availableCompelling information from multiple sources is available
1.Extensively verified claimyesyesyesyes
2.Verified claimyesyesyes
3. Manufacturer-supported claimyesyes
4. Unsupported claimyes
5.Not advertised by manufactureryes
\n\n# Researchers say \n\nIn order to add available scientific information to the inventory, we created a text-entry database field named “Researchers say”, which makes it possible to include an extract from a research paper (such as the abstract), author citation, and a link to the paper. \n\n# Crowdsourcing \n\nWe added a new crowdsourcing capability to the CPI website so that consumers, manufacturers, and the greater scientific community can contribute new information on nanomaterial composition of CPI products to the inventory. New contributors must request an account by completing a form with their contact information, and they must provide a reason why they would like to gain access to this crowdsourcing tool. Accounts are manually reviewed. Access is granted to all requesters who complete the form and have a legitimate purpose for contributing information. Once an account is created, users may sign in and suggest edits to any product (including the archiving of products no longer available or no longer advertising to contain nanomaterials) or suggest new products to the inventory. As a quality control measure, suggestions and new product forms contributed by registered users must be approved by a CPI curator before updates or revisions are posted to the inventory. \n\n# Supporting Information \n\n# Supporting Information File 1 \n\nA compilation of company and product numbers listed by country of origin. A list of all nanomaterial components included in the inventory. Nanotechnology expert survey questions. Additional nanotechnology expert survey results. [http://www.beilstein-journals.org/bjnano/content/ supplementary/2190-4286-6-181-S1.pdf] \n\n# Acknowledgements \n\nFunding for this work was provided by the Institute for Critical Technology and Applied Science (ICTAS) at Virginia Tech and the Virginia Tech Center for Sustainable Nanotechnology (VTSuN). We acknowledge the important help of J. Rousso, E. Bruning, S. Guldin, J. Wang, D. Yang, X. Zhou, L. Marr, the VTSuN graduate students in updating inventory entries, and the Laboratory for Interdisciplinary Statistical Analysis at Virginia Tech. We also acknowledge the Center for the Environmental Implications of Nanotechnology, funded under NSF Cooperative Agreement EF-0830093, for helping to inform our understanding of the broad world of manufactured nanomaterials. Co-author M. Hull acknowledges helpful discussions with A. Maynard of the Arizona State University Risk Innovation Lab that provided important motivation for this work. \n\n# References \n\n1. The Project on Emerging Nanotechnologies. Consumer Products Inventory. http://www.nanotechproject.org/cpi (accessed March 25, 2015). \n2. Michelson, E. S. Rev. Policy Res. 2013, 30, 464–487. doi:10.1111/ropr.12034 \n3. Currall, S. C.; King, E. B.; Lane, N.; Madera, J.; Turner, S. Nat. Nanotechnol. 2006, 1, 153–155. doi:10.1038/nnano.2006.155 \n4. Kahan, D. M.; Braman, D.; Slovic, P.; Gastil, J.; Cohen, G. Nat. Nanotechnol. 2009, 4, 87–90. doi:10.1038/nnano.2008.341 \n5. Maynard, A. D. Nanotechnology: A Strategy for Addressing Risk; Woodrow Wilson International Center for Scholars, 2006; p 45. \n6. Maynard, A. D.; Aitken, R. J.; Butz, T.; Colvin, V.; Donaldson, K.; Oberdörster, G.; Philbert, M. A.; Ryan, J.; Seaton, A.; Stone, V.; Tinkle, S. S.; Tran, L.; Walker, N. J.; Warheit, D. B. Nature 2006, 444, 267–269. doi:10.1038/444267a \n7. Berube, D. M.; Searson, E. M.; Morton, T. S.; Cummings, C. L. Nanotechnol. Law Bus. 2010, 7, 152–163. \n8. Nano Products and Technologies. http://www.nanoproducts.de (accessed Feb 28, 2015). \n9. National Institute of Advanced Industrial Science and Technology. A Nanotechnology-Claimed Consumer Products Inventory in Japan. http://www.aist-riss.jp/ (accessed Feb 28, 2015). \n10. The European Consumer Organization. http://www.beuc.org/ (accessed Feb 28, 2015). \n11. Danish Consumer Council. The Nanodatabase. http://nanodb.dk/ (accessed Feb 28, 2015). \n12. de la Iglesia, D.; Harper, S.; Hoover, M. D.; Klaessig, F.; Lippell, P.; Maddux, B.; Morse, J.; Nel, A.; Rajan, K.; Reznik-Zellen, R.; Tuominen, M. T. Nanoinformatics 2020 Roadmap; National Nanomanufacturing Network, 2011. doi:10.4053/rp001-110413 \n13. Toxic Substances Control Act (TSCA), 15 U.S.C. §2601–2692, Washington, DC, 1976. \n14. Environmental Protection Agency (EPA). Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA). http://www.epa.gov/agriculture/lfra.html (accessed March 2, 2015). \n15. European Commission. Nanomaterials - Chemicals - Enterprise and Industry. http://ec.europa.eu/enterprise/sectors/chemicals/reach/nanomaterials/i ndex_en.htm (accessed March 2, 2015). \n16. European Commission. Nanomaterials under Biocidal Products Regulation - Echa. http://echa.europa.eu/regulations/nanomaterials-under-bpr (accessed March 2, 2015). \n17. European Commission. Nanomaterials in Cosmetics. http://ec.europa.eu/growth/sectors/cosmetics/products/nanomaterials/in dex_en.htm (accessed March 2, 2015). \n18. Hermann, A.; Diesner, M.-O.; Abel, J.; Hawthorne, C.; Greßmann, A. Assessment of Impacts of a European Register of Products Containing Nanomaterials; Federal Environment Agency (Umweltbundesamt): Dessau-Roßlau, Germany, 2014; p 142. \n19. Maynard, A.; Michelson, E. S. The Nanotechnology Consumer Products Inventory; Woodrow Wilson International Center for Scholars, 2006. \n20. Piccinno, F.; Gottschalk, F.; Seeger, S.; Nowack, B. J. Nanopart. Res. 2012, 14, 1109. doi:10.1007/s11051-012-1109-9 \n21. Keller, A. A.; McFerran, S.; Lazareva, A.; Suh, S. J. Nanopart. Res. 2013, 15, 1692. doi:10.1007/s11051-013-1692-4 \n22. Nowack, B.; Krug, H. F.; Height, M. Environ. Sci. Technol. 2011, 45, 1177–1183. doi:10.1021/es103316q \n23. Saleh, N. B.; Aich, N.; Plazas-Tuttle, J.; Lead, J. R.; Lowry, G. V. Environ. Sci.: Nano 2015, 2, 11–18. doi:10.1039/C4EN00104D \n24. Hansen, S. F.; Larsen, B. H.; Olsen, S. I.; Baun, A. Nanotoxicology 2007, 1, 243–250. doi:10.1080/17435390701727509 \n25. Lu, W.; Lieber, C. M. Nat. Mater. 2007, 6, 841–850. doi:10.1038/nmat2028 \n26. Hansen, S. F.; Michelson, E. S.; Kamper, A.; Borling, P.; Stuer-Lauridsen, F.; Baun, A. Ecotoxicology 2008, 17, 438–447. doi:10.1007/s10646-008-0210-4 \n27. Royce, S. G.; Mukherjee, D.; Cai, T.; Xu, S. S.; Alexander, J. A.; Mi, Z.; Calderon, L.; Mainelis, G.; Lee, K.; Lioy, P. J.; Tetley, T. D.; Chung, K. F.; Zhang, J.; Georgopoulos, P. G. J. Nanopart. Res. 2014, 16, 2724. doi:10.1007/s11051-014-2724-4 \n28. Nazarenko, Y.; Zhen, H. J.; Han, T.; Lioy, P. J.; Mainelis, G. Environ. Health Perspect. 2012, 120, 885–892. doi:10.1289/ehp.1104350 \n29. Nazarenko, Y.; Han, T. W.; Lioy, P. J.; Mainelis, G. J. Exposure Sci. Environ. Epidemiol. 2011, 21, 515–528. doi:10.1038/jes.2011.10 \n30. Quadros, M. E.; Marr, L. C. Environ. Sci. Technol. 2011, 45, 10713–10719. doi:10.1021/es202770m \n31. Benn, T.; Cavanagh, B.; Hristovski, K.; Posner, J. D.; Westerhoff, P. J. Environ. Qual. 2010, 39, 1875–1882. doi:10.2134/jeq2009.0363 \n32. Quadros, M. E.; Pierson, R.; Tulve, N. S.; Willis, R.; Rogers, K.; Thomas, T. A.; Marr, L. C. Environ. Sci. Technol. 2013, 47, 8894–8901. doi:10.1021/es4015844 \n33. Tulve, N. S.; Stefaniak, A. B.; Vance, M. E.; Rogers, K.; Mwilu, S.; LeBouf, R. F.; Schwegler-Berry, D.; Willis, R.; Thomas, T. A.; Marr, L. C. Int. J. Hyg. Environ. Health 2015, 218, 345–357. doi:10.1016/j.ijheh.2015.02.002 \n34. Holden, P. A.; Klaessig, F.; Turco, R. F.; Priester, J. H.; Rico, C. M.; Avila-Arias, H.; Mortimer, M.; Pacpaco, K.; Gardea-Torresdey, J. L. Environ. Sci. Technol. 2014, 48, 10541–10551. doi:10.1021/es502440s \n35. Savolainen, K.; Backman, U.; Brouwer, D.; Fadeel, B.; Fernandes, T.; Kuhlbusch, T.; Landsiedel, R.; Lynch, I.; Pylkkänen, L. Nanosafety in Europe 2015-2025: Towards Safe and Sustainable Nanomaterials and Nanotechnology Innovations. Finnish Institute of Occupational Health: Helsinki, Finnland, 2013; http://www.ttl.fi/en/publications/Electronic_publications/Nanosafety_in_ europe_2015-2025/Documents/nanosafety_2015-2025.pdf. \n36. Consumer Product Safety Commission Fiscal Year 2016 Performance Budget Request. http://www.cpsc.gov/Global/About-CPSC/Budget-and-Performance/FY 2016BudgettoCongress.pdf (accessed March 2, 2015). \n37. Hansen, S. F. J. Nanopart. Res. 2010, 12, 1959–1970. doi:10.1007/s11051-010-0006-3 \n38. Becker, S. J. Nanopart. Res. 2013, 15, 1426. doi:10.1007/s11051-013-1426-7 \n39. Baruch, Y.; Holtom, B. C. Hum. Relat. 2008, 61, 1139–1160. doi:10.1177/0018726708094863 \n40. Beaudrie, C. E. H.; Kandlikar, M.; Satterfield, T. Environ. Sci. Technol. 2013, 47, 5524–5534. doi:10.1021/es303591x \n\n# License and Terms \n\nThis is an Open Access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. \n\nThe license is subject to the Beilstein Journal of Nanotechnology terms and conditions: (http://www.beilstein-journals.org/bjnano) \n\nThe definitive version of this article is the electronic one \nwhich can be found at: \ndoi:10.3762/bjnano.6.181 " + }, + { + "id": "10.1103_PhysRevX.5.031023", + "DOI": "10.1103/PhysRevX.5.031023", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevX.5.031023", + "Relative Dir Path": "mds/10.1103_PhysRevX.5.031023", + "Article Title": "Observation of the Chiral-Anomaly-Induced Negative Magnetoresistance in 3D Weyl Semimetal TaAs", + "Authors": "Huang, XC; Zhao, LX; Long, YJ; Wang, PP; Chen, D; Yang, ZH; Liang, H; Xue, MQ; Weng, HM; Fang, Z; Dai, X; Chen, GF", + "Source Title": "PHYSICAL REVIEW X", + "Abstract": "Weyl semimetal is the three-dimensional analog of graphene. According to quantum field theory, the appearance of Weyl points near the Fermi level will cause novel transport phenomena related to chiral anomaly. In the present paper, we report the experimental evidence for the long-anticipated negative magnetoresistance generated by the chiral anomaly in a newly predicted time-reversal-invariant Weyl semimetal material TaAs. Clear Shubnikov de Haas (SdH) oscillations have been detected starting from a very weak magnetic field. Analysis of the SdH peaks gives the Berry phase accumulated along the cyclotron orbits as pi, indicating the existence of Weyl points.", + "Times Cited, WoS Core": 1465, + "Times Cited, All Databases": 1568, + "Publication Year": 2015, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000359947000001", + "Markdown": "# Observation of the Chiral-Anomaly-Induced Negative Magnetoresistance in 3D Weyl Semimetal TaAs \n\nXiaochun Huang,1 Lingxiao Zhao,1 Yujia Long,1 Peipei Wang,1 Dong Chen,1 Zhanhai Yang,1 Hui Liang,1 Mianqi Xue,1 Hongming Weng,1,2 Zhong Fang,1,2 Xi Dai,1,2 and Genfu Chen1, 1Beijing National Laboratory for Condensed Matter Physics, and Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China 2Collaborative Innovation Center of Quantum Matter, Beijing 100084, China (Received 14 May 2015; published 24 August 2015) \n\nWeyl semimetal is the three-dimensional analog of graphene. According to quantum field theory, the appearance of Weyl points near the Fermi level will cause novel transport phenomena related to chiral anomaly. In the present paper, we report the experimental evidence for the long-anticipated negative magnetoresistance generated by the chiral anomaly in a newly predicted time-reversal-invariant Weyl semimetal material TaAs. Clear Shubnikov de Haas (SdH) oscillations have been detected starting from a very weak magnetic field. Analysis of the SdH peaks gives the Berry phase accumulated along the cyclotron orbits as $\\pi$ , indicating the existence of Weyl points. \n\nDOI: 10.1103/PhysRevX.5.031023 \n\nSubject Areas: Condensed Matter Physics, Materials Science, Topological Insulators \n\n# I. INTRODUCTION \n\nWhen two nondegenerate bands cross in threedimensional (3D) momentum space, the crossing points are called Weyl points, which can be viewed as magnetic monopoles [1] or topological defects in the band structure, like “knots” on a rope. Near Weyl points, the low-energy physics can be described by Weyl equations [2] with distinct chirality (either left- or right-handed), which mimics relativistic field theory in particle physics. On a lattice system, Weyl points always appear in pairs with opposite chirality and are topologically stable against perturbations that keep translational symmetry [3–6]. If two Weyl points with opposite chirality meet in momentum space, they will generally annihilate each other, but they may also be stabilized as 3D Dirac points by additional (such as crystalline) symmetry [7–10]. For materials with Weyl points located near the Fermi level, called Weyl semimetals (WSMs), exotic low-energy physics can be expected, such as Fermi arcs on the surface [4,5] and the chiral-anomaly-induced quantum transport [11–14]. Recently, 3D Dirac semimetals, $\\mathrm{Na}_{3}\\mathrm{Bi}$ and $\\mathrm{Cd}_{3}\\mathrm{As}_{2}$ , have been theoretically predicted [8,9] and experimentally confirmed [15–19], while WSMs are still waiting for experimental verification in spite of various theoretical proposals [4,5,20–24]. \n\nThe anomalous dc transport properties are an important consequence of the topological band structure [13,25,26]. In topological insulators (TI), the transport properties are dominated by the topological surfaces states (SS), where the lack of backscattering caused by the unique spin structure of the SS leads to the weak antilocalization (WAL) behavior. However, in WSMs the bulk states are semimetallic and dominate the dc transport. In relativistic field theory, for a continuing system described by the Weyl equation, chiral anomaly can be understood as the nonconservation of the particle number with given chirality, which only happens in the presence of parallel magnetic and electric fields [11]. For any realistic lattice systems, the chiral anomaly then manifests itself in the intervalley pumping of the electrons between Weyl points with opposite chirality. In the noninteracting case, the chiral anomaly can be simply ascribed to the zeroth Landau levels, which are chiral and have opposite signs of the velocity for states around Weyl points with opposite chirality, as shown in Fig. 1(d) [11]. The additional electric field parallel to the magnetic field will then generate charge imbalance between two chiral nodes, leading to an electric current that can only be balanced by intervalley scattering. Considering the fact that for clean samples the intervalley scattering time is extremely long and the degeneracy of the Landau level is proportional to the magnetic field strength, the chiral anomaly in WSM will, in general, lead to negative magnetoresistance $(\\mathrm{MR}=\\lceil\\rho(H)-\\rho(0)/\\rho(0)\\rceil)$ when the magnetic field is parallel to the current. On the other hand, for ordinary metal or semiconductors, the MR is weak, positive, and usually not very sensitive to the magnetic field direction. Therefore, the negative and highly anisotropic MR has been regarded as the most prominent signature in transport for the chiral anomaly, and it indicates the existence of 3D Weyl points. In addition, the chiral anomaly can also generate other fascinating phenomena, i.e., the anomalous Hall effect and the nonlocal transport properties [5,12]. \n\nUsing first-principle calculations, Weng et al. [23] predicted that a family of binary compounds represented by TaAs are time-reversal-invariant 3D WSMs with a dozen pairs of Weyl nodes that are generated by the absence of an inversion center. The exotic Fermi arch on the surface and Weyl nodes in the bulk have been identified by angleresolved photoemission spectroscopy and microwave transmission measurements [27–30]. Materials in the TaAs family are completely stoichiometric and nonmagnetic, providing an almost ideal platform for the study of the chiral anomaly in WSM. In this work, we perform transport studies of the TaAs single crystal down to $1.8\\mathrm{~K~}$ , with a magnetic field up to $9\\ \\mathrm{~T~}.$ Ultrahigh mobility $(\\mu_{e}\\approx1.8\\times10^{5}\\ \\mathrm{cm}^{2}\\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ at $10~\\mathrm{K}$ ) has been found with a multiband character. Extremely large positive MR ${\\approx}80000\\%$ at $1.8\\mathrm{~K~}$ in a field of $9\\mathrm{T},$ ) is discovered for a magnetic field perpendicular to the current (or the external electric field). Ultrahigh mobility and large MR in the same material have also been detected by Zhang et al. [31]. Unfortunately, in the configuration of $B//I$ , their MR data remain positive in the whole magnetic field up to $9\\mathrm{T}.$ In our work, when the magnetic field is rotated to be parallel to the current, notable negative MR has been observed, demonstrating the chiral anomaly effects in this particular material. Strong SdH oscillations have been found from a very low magnetic field, from which two sets of oscillation frequencies can be extracted, indicating two types of carriers, in good consistency with our firstprinciples calculations. \n\n# II. CRYSTAL STRUCTURE AND MEASURING METHOD \n\nTaAs crystallizes in a body-centered-tetragonal NbAstype structure with a nonsymmorphic space group of $I4_{1}m d$ , in which the $c$ axis is perpendicular to the ab plane [see Fig. 1(a)]. The lattice parameters are $a=b=$ $3.4348\\mathrm{~\\AA~}$ and $c=11.641\\mathrm{~\\AA~}$ [32]. Because of the lack of inversion symmetry, first-principles calculations predicted a dozen pairs of Weyl points in the Brillouin zone (BZ) [23]. A schematic diagram of theoretically predicted Weyl nodes projected on the (001) facet can be seen in Fig. 1(b). In this study, the single crystals of TaAs were grown by chemical vapor transport. A polycrystalline TaAs that previously reacted was filled in the quartz ampoule using $2~\\mathrm{mg}/\\mathrm{cm}^{3}$ of iodine as the transporting agent. After evacuating and sealing, the ampoule was kept at the growth temperature for three weeks. Large polyhedral crystals with dimensions up to $1.5~\\mathrm{mm}$ are obtained in a temperature field of $\\Delta T=1150^{\\circ}\\mathrm{C}-1000^{\\circ}\\mathrm{C}$ Figure 1(c) shows the $\\mathbf{X}$ -ray diffraction (XRD) from a TaAs crystal oriented with the scattering vector perpendicular to the (001) plane. The inset is the morphology of a representative crystal looking down the [001] direction. The crystal was polished into a rectangular sample $(1\\times0.3\\times0.08~\\mathrm{mm}^{3})$ ) for magnetoresistance and Hall resistivity measurements using fourpoint probe and alternating current transport methods in the Quantum Design PPMS. The electric current is always applied parallel to the (001) plane along the $a$ or $b$ axis in our studies. For MR (or Hall resistivity) measurements, any additional Hall (or resistive) voltage signals due to the misalignment of the voltage leads have been corrected by reversing the direction of the magnetic field. Firstprinciples calculations are performed by using the OpenMX [33] software package. The choice of a pseudo-atomic orbital basis set with $\\mathrm{Ta}9.0{\\cdot}\\mathrm{s}2\\mathrm{p}2\\mathrm{d}2\\mathrm{f}1$ and $\\mathrm{As9.0{\\-s2p2d1}}$ , the pseudopotential and the sampling of BZ $(10\\times10\\times10k$ grid) have been checked. The exchangecorrelation functional within a generalized gradient approximation parametrized by Perdew, Burke, and Ernzerhof has been used [34]. The optimized lattice constants $a=b=3.4824\\mathrm{~\\AA~}$ , $c=11.8038\\mathrm{~\\AA~}$ , and atomic sites are in agreement with the experimental values. \n\n![](images/2ab959d6b5572780d92dcff98827d92338a39e94a2c389e89386e707a848f190.jpg) \nFIG. 1. Structure and symmetry of a TaAs single crystal. (a) The crystal structure of TaAs with a nonsymmorphic space group of $I4_{1}m d$ . Blue and violet balls represent a Ta atom and an As atom, respectively. (b) Schematic diagram of a dozen pairs of Weyl points projected on the (001) facet. “ $+^{,,}$ and “−” denote Weyl points with positive and negative chiralities, respectively. The circles show that there are two Weyl points with the same chirality projected on the same point in the (001) facet. Γ, X, and M are the high symmetry points in the Brillouin zone. (c) X-ray diffraction pattern of a TaAs single crystal. The inset shows an optical image of a typical sample at the millimeter scale. (d) Schematic diagram of bulk Landau levels of a pair of Weyl nodes. The dotted lines represent the zeroth quantum Landau Level with “ $+^{,,}$ (blue) and “−” (red) chiralities in a magnetic field parallel to the electric current. \n\n# III. RESULTS AND DISCUSSION \n\n# A. Magnetoresistance measurements \n\nFigure 2 presents the MR measured at $1.8\\mathrm{K}$ by tilting the magnetic field $(B)$ at an angle $\\mathbf{\\eta}^{(\\theta)}$ with respect to the electric current $(I)$ . The Hall signal has been removed by averaging the $\\rho_{\\mathrm{xx}}$ data over positive and negative field directions. As shown in Fig. 2(a), when the magnetic field is applied perpendicular to the current $(B\\bot I,\\theta=0^{\\circ})$ , a surprising positive MR of up to $800\\%$ is observed. Near zero field, MR exhibits quadratic field dependence, which soon changes to almost linear dependence at a very low field without any trend towards saturation up to $9\\mathrm{T}$ . This giant conventional MR strongly relies on $\\theta$ and decreases considerably with increasing $\\theta$ . When the magnetic field is rotated parallel to the electric current $(\\theta=90^{\\circ})$ ), we observe negative MR, strong evidence of Weyl fermions in TaAs. Elaborate measurements at different angles around $\\theta=90^{\\circ}$ are implemented and presented in Fig. 2(b). As shown in the main panel, by rotating $\\theta$ from $87^{\\circ}$ to $91.8^{\\circ}$ , negative MR arises in the cases of $\\theta$ between $88^{\\circ}$ and \n\n$91.5^{\\circ}$ , and it reaches a maximum $(-30\\%)$ at $\\theta=90^{\\circ}$ $(B//I)$ . This can also be intuitively viewed as a consequence of the steep downturn of MR in the magnetic field range $1\\mathrm{~T~}{<}B<6\\mathrm{~T~}$ (and $-1\\mathrm{~T~}{<}B<-6\\mathrm{~T~})$ . In this range, for clarity, the minima of MR curves at different angles are listed in the inset of Fig. 2(b). The largest value, as expected, occurs at $\\theta=90^{\\circ}$ . We note that the negative MR in Fig. 2(b) disappeared as we rotated the field about $2^{\\circ}$ away from the current. This seems hard to believe. However, it makes sense when we recall that the conventional positive MR $(B\\bot I)$ of TaAs is very large ${\\approx}80000\\%$ at $1.8\\mathrm{K}$ in a field of $9\\mathrm{T}$ ) and increases remarkably with an increasing magnetic field. So, a slightly imperfect alignment of the magnetic field and the current in the sample will arouse a large perpendicular component and obscure the negative MR, especially in a large field. Thus, the negative MR is confined to about $\\pm2^{\\circ}$ of $B//E$ . In other words, in a system with smaller positive MR (at $\\theta=0^{\\circ}$ ), we may observe larger negative MR (at $\\theta=90^{\\circ}$ ) in a wide magnetic field range. Indeed, larger negative MR has been observed in $\\mathrm{Na}_{3}\\mathrm{Bi}$ [35] and TaP [36], which have much smaller positive MR than that of TaAs at $\\theta=0^{\\circ}$ . \n\nThe origin of the negative MR in TaAs can be explained by the chiral anomaly in the semiclassical regime [6,37]. Under the external magnetic field, the lowenergy states near the Weyl points reorganize to form Landau states for the motion perpendicular to the field and leave the momentum $k$ parallel to the field still a good quantum number. As shown in Fig. 1(d), the zeroth Landau levels are chiral, with the chirality determined by that of the Weyl point. With the additional electric field along the same direction, the equation of motion for the electrons on the chiral modes gives $\\hbar(d k/d t)=-e E.$ , which adiabatically pumps electrons from one valley to another one with opposite chirality. In order to equilibrate the charge imbalance between the positive- and the negative-handed fermions resulting from the chiral anomaly, large-momentum internode scattering is required. However, in a sufficiently clean sample, such processes are considerably weak. Hence, the internode scattering time $\\tau$ is very large, causing a remarkable increase in conductivity. Then, solving the corresponding Boltzmann equation under the semiclassical approximation gives chiral-anomaly-contributed conductivity as [6] \n\n![](images/2e5b031c0a66ffe2a9bb755d40ebbef31d2b8c1aafce81cccd168adae0b14db5.jpg) \nFIG. 2. Angular and field dependence of MR in a TaAs single crystal at $1.8\\mathrm{K}$ . (a) Magnetoresistance with respect to the magnetic field $(B)$ at different angles between $B$ and the electric current $(I)$ $(\\theta=0\\sp{\\circ}{-}90\\sp{\\circ}$ ). The inset zooms in on the lower MR part, showing negative MR at $\\theta=90^{\\circ}$ (longitudinal negative MR), and it depicts the corresponding measurement configurations. (b) Magnetoresistance measured in different rotating angles around $\\theta=90^{\\circ}$ with the interval of every $0.2\\L^{\\circ}$ . The negative MR appeared at a narrow region around $\\theta=90^{\\circ}$ , and most obviously when $B//I$ . Either positive or negative deviations from $90^{\\circ}$ would degenerate and ultimately kill the negative MR in the whole range of the magnetic field. Inset: The minima of MR curves at different angles $(88^{\\circ}-92.2^{\\circ})$ in a magnetic field from 1 to $6\\mathrm{T}.$ . (c) The negative MR at $\\theta=90^{\\circ}$ (open circles) and fitting curves (red dashed lines) at various temperatures. $T=1.8$ , 10, 25, 50, 75, and $100\\mathrm{K}$ . (d) Magnetoresistance in the perpendicular magnetic field component, $B\\times\\cos\\theta$ . The misalignment indicates the 3D nature of the electronic states. \n\n$$\n\\sigma^{\\mathrm{chiral}}=\\frac{e^{2}}{4\\pi^{2}\\hbar c}\\frac{v}{c}\\frac{(e B v)^{2}}{E_{F}^{2}}\\tau,\n$$ \n\nwhere $v$ is the Fermi velocity near the Weyl points and $E_{F}$ denotes the chemical potential measured from the energy of the Weyl points. The above chiral part of the conductivity increasing quadratically with magnetic field $B$ leads to negative MR, which has the maximum effect with $E$ parallel to $B$ . Of course, the total conductivity of the system will also include other contributions from the nonchiral states as well, such as conventional conductivity of nonlinear band contributions, $\\sigma_{\\mathrm{N}}$ , and the WAL, ${\\sigma}_{\\mathrm{WAL}}$ , which may weaken the negative MR effect or even overwhelm it if the nonchiral part dominates the dc transport. Therefore, in order to observe the chiral negative MR, the high-quality sample with chemical potential close enough to the Weyl point is crucial. In this work, this can be roughly recognized by the coexistence of SdH oscillations and giant transverse MR [see Fig. 2(a)], which usually implies small Fermi surfaces around the Fermi level [38]. In addition, the misposition of the electric leads and/or the unavoidable misalignment of the magnetic field and the electric current may also strongly weaken the negative MR because of the huge positive MR and Hall resistivity signals in this material. The high precision of the measurement setup enables a very reliable measurement and manifests itself by the highly symmetrical original data of $\\rho_{\\mathrm{xx}}$ observed in opposite magnetic fields (see Ref. [39]). \n\nQuantitative analyses are carried out by fitting the negative MR at $\\theta=90^{\\circ}$ with the semiclassical formula [26] in the magnetic field $-4\\mathrm{~T~}0$ an interesting situation occurs in which an increase in temperature results in an increase in the precipitated number of A-molecules, as observed experimentally for hybrid perovskites. This effect, as can be seen from equation (4), takes place if \n\n$$\n\\varepsilon_{\\mathrm{C}}>\\varepsilon\\cdot\\bigg(1+\\frac{\\nu_{\\mathrm{C}}}{\\nu_{\\mathrm{A}}}\\cdot\\left(n_{\\mathrm{S}}\\nu_{\\mathrm{S}}\\right)^{-j}\\cdot\\exp\\left(-\\frac{\\varepsilon_{\\mathrm{C}}}{T}\\right)\\bigg),\n$$ \n\nor if we accept that $\\begin{array}{r}{\\frac{\\nu_{\\mathrm{C}}}{\\nu_{\\mathrm{A}}}\\cdot\\left(n_{\\mathrm{S}}\\nu_{\\mathrm{S}}\\right)^{-j}\\cdot\\exp\\left(-\\frac{\\varepsilon_{\\mathrm{C}}}{T}\\right)\\ll1}\\\\ {\\frac{\\nu_{\\mathrm{S}}}{\\nu_{\\mathrm{A}}}\\cdot\\left(n_{\\mathrm{S}}\\nu_{\\mathrm{S}}\\right)_{.}^{-j}.}\\end{array}$ (that is, large enough $\\varepsilon_{C}/T$ ratio), then the inequality given by equation (5) \n\nreduces to $\\varepsilon_{\\mathrm{C}}>\\varepsilon$ . These analytical relation can be further understood in physical terms as follows: at low temperatures most of the A-molecules are bound in the complexes with the solvent; therefore, the solution has no supersaturation in terms of concentration of unbound A-molecules. When the temperature increases, the concentration of unbound A-molecules increases (because of dissociation of the complexes) and may reach the supersaturation, thus triggering the precipitation of A-particles. Conversely, when the temperature of the solution containing the precipitated A-particle is decreased, the concentration $n_{\\mathrm{A}}$ of unbound A-molecules is also decreased because of formation of many more complexes with solvent. This decrease in $n_{\\mathrm{A}}$ makes the solution too diluted in A-molecules such that the particle has to transfer some molecules to the solution, that is, it dissolves. It should be noted that the process of crystallization is endothermic with respect to A-molecules, as a molecule moves from the complex with higher binding energy to the precipitate, where its binding (cohesive) energy is lower. Therefore, the crystallization reaction consumes thermal energy. \n\nThe temperature behaviour described by equation (5) provides a qualitative framework to explain the effects observed experimentally for perovskite materials. A quantitative analysis requires a detailed investigation of the molecular content of the precursor solution, a subject of future research. \n\nIn summary, we report the novel observation of inverse solubility of hybrid organo-lead trihalide perovskites. A careful choice of solvent, temperature and other parameters made it possible to utilize this method to rapidly grow single crystals of $\\mathbf{\\bar{MAPb}}\\mathbf{B}\\mathbf{r}_{3}$ and $\\mathbf{MAPbI}_{3}$ in hot solutions via ITC. Despite the fact that these crystals grow very fast, they exhibit carrier transport properties comparable to those grown by the usual cooling or antisolvent vapour-assisted crystallization techniques. The ‘quantum leap’ in crystal growth rates in ITC, over the previously reported growth methods so far used for single crystal-hybrid perovskites, represents a major breakthrough in the field of perovskite single crystals for enabling the wide applications of these remarkable semiconductor materials. \n\n# Methods \n\nChemicals and reagents. Lead bromide $(\\geq98\\%)$ , lead iodide $(99.999\\%$ trace metal basis), DMF (anhydrous, $99.8\\%$ and GBL $(\\geq99\\%)$ were purchased from Sigma Aldrich. MABr and MAI were purchased from Dyesol Limited (Australia). All salts and solvents were used as received without any further purification. \n\nSynthesis of $\\M A P b\\times_{3}$ single crystals. One molar solution containing $\\mathrm{Pb}\\mathrm{X}_{2}$ and MAX was prepared in DMF or GBL for $\\mathrm{X=Br^{-}}$ , $\\mathrm{~I~}^{-}$ , respectively. The bromide solution was prepared at room temperature, whereas the iodide solution was heated up to $60^{\\circ}\\mathrm{C}$ . The solutions were filtered using PTFE filter with $0.2\\mathrm{-}\\upmu\\mathrm{m}$ pore size. Two millilitres of the filtrate were placed in a vial and the vial was kept in an oil bath undisturbed at 80 and $110^{\\circ}\\mathrm{C}$ for $\\mathbf{Br}\\mathbf{-}$ and I-based perovskites, respectively. All procedures were carried out under ambient conditions and humidity of $55\\mathrm{-}57\\%$ . The crystals used for measurements were grown for $^{3\\mathrm{h}}$ . The reaction yield for $\\mathbf{MAPbBr}_{3}$ and $\\mathbf{MAPbI}_{3}$ was calculated to be 35 and 11 wt $\\%$ , respectively. \n\nMeasurement and characterization. Powder X-ray diffraction was performed on a Bruker AXS D8 diffractometer using $\\mathrm{Cu-K}\\mathfrak{a}$ radiation. Single-crystal X-ray diffraction was performed on Bruker D8 Venture, CMOS detector, microfocus copper source. The steady-state absorption and photoluminescence were recorded using Cary 6000i spectrophotometer with an integrating sphere and Edinburgh Instrument spectrofluorometer, respectively. Time-resolved transient absorption decays were measured with a femto-nanoseconds pump \u0002 probe set-up. The excitation pulse at $480\\mathrm{nm}$ was generated using a spectrally tunable optical Parametric Amplifier (Light Conversion LTD) integrated to a Ti:sapphire femtosecond regenerative amplifier operating at ${800}\\mathrm{nm}$ with 35 fs pulses and a repetition rate of 1 kHz. The white light probe pulse, on the other hand, was generated by a super continuum source29,30. The pump and probe beams were overlapped spatially and temporally on the sample, and the transmitted probe light from the samples was collected and focused on the broad-band ultraviolet–visible-near-infrared detectors to record the time-resolved excitation-induced difference spectra. I–V characteristics were carried out in the dark under vacuum $({\\stackrel{\\bullet}{\\sim}}10^{-4}{\\bmod{\\mathrm{ar}}})$ at $300\\mathrm{K}$ , in the simple two electrode configuration $\\mathrm{(Au/MAPbX_{3}/A u}$ ). The perovskite crystal was sandwiched between the rectangular electrodes $3\\mathrm{mm}\\times2\\mathrm{mm})$ Au $(100\\mathrm{nm})$ , deposited on both sides of the single crystal, by an Angstrom thermal evaporator at a $0.5\\mathring{\\mathrm{A}}s^{-1}$ deposition rate. The thickness and rate of deposition during the evaporation of Au contact was monitored by an Inficon thickness monitor. The thickness of $\\mathbf{MAPbBr}_{3}$ and $\\operatorname{MAPbI}_{3}$ crystals were measured as 2.32 and $2.49\\mathrm{mm}$ , respectively, by the digital Vernier caliper. The typical nonlinear dark current, voltage plots followed the Lampert’s theory, where the current was found to be limited by the trap-assisted space charge conduction. Onset voltage $(V_{\\mathrm{TFL}})$ for the TFL was used for the calculation (equation (6)) of density of traps $(n_{\\mathrm{traps}})$ in the perovskite crystals \n\n$$\nn_{\\mathrm{traps}}=2\\varepsilon\\varepsilon_{0}V_{\\mathrm{TFL}}/q d^{2}\n$$ \n\nwhere $q$ is the electronic charge, $d$ is the thickness of the crystal, e is the dielectric constant of the material (25.5 for $\\mathbf{MAPbBr}_{3}$ and 32 for $\\mathrm{MA}\\dot{\\mathrm{PbI}_{3}})^{19,31}$ and $\\scriptstyle{\\varepsilon_{0}}$ is the vacuum permittivity. \n\n# References \n\n1. Docampo, P., Ball, J. M., Darwich, M., Eperon, G. E. & Snaith, H. J. Efficient organometal trihalide perovskite planar-heterojunction solar cells on flexible polymer substrates. Nat. Commun. 4, 2761 (2013). \n2. Kim, H. S. et al. Mechanism of carrier accumulation in perovskite thinabsorber solar cells. Nat. Commun. 4, 2242 (2013). \n3. Stranks, S. D. et al. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n4. Mei, A. et al. A hole-conductor-free, fully printable mesoscopic perovskite solar cell with high stability. Science 345, 295–298 (2014). \n5. Christians, J. A., Fung, R. C. M. & Kamat, P. V. An inorganic hole conductor for organo-lead halide perovskite solar cells. improved hole conductivity with copper iodide. J. Am. Chem. Soc. 136, 758–764 (2014). \n6. Liu, D., Yang, J. & Kelly, T. L. Compact layer free perovskite solar cells with $13.5\\%$ efficiency. J. Am. Chem. Soc. 136, 17116–17122 (2014). \n7. Nie, W. et al. High-efficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 347, 522–525 (2015). \n8. Choi, J. J., Yang, X., Norman, Z. M., Billinge, S. J. L. & Owen, J. S. Structure of methylammonium lead iodide within mesoporous titanium dioxide: active material in high-performance perovskite solar cells. Nano Lett. 14, 127–133 (2014). \n9. Xing, G. et al. Low-temperature solution-processed wavelength-tunable perovskites for lasing. Nat. Mater. 13, 476–480 (2014). \n10. Tan, Z.-K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nano 9, 687–692 (2014). \n11. Dou, L. et al. Solution-processed hybrid perovskite photodetectors with high detectivity. Nat. Commun. 5, 5404 (2014). \n12. Chen, Y.-S., Manser, J. S. & Kamat, P. V. All solution-processed lead halide perovskite-BiVO4 tandem assembly for photolytic solar fuels production. J. Am. Chem. Soc. 137, 974–981 (2015). \n13. Xing, G. et al. Long-range balanced electron- and hole-transport lengths in organic-inorganic $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ . Science 342, 344–347 (2013). \n14. Noh, J. H., Im, S. H., Heo, J. H., Mandal, T. N. & Seok, S. I. Chemical management for colorful, efficient, and stable inorganic–organic hybrid nanostructured solar cells. Nano Lett. 13, 1764–1769 (2013). \n15. Filip, M. R., Eperon, G. E., Snaith, H. J. & Giustino, F. Steric engineering of metalhalide perovskites with tunable optical band gaps. Nat. Commun. 5, 5757 (2014). \n16. D’Innocenzo, V., Kandada, A. R. S., De Bastiani, M., Gandini, M. & Petrozza, A. Tuning the light emission properties by band gap engineering in hybrid lead halide perovskite. J. Am. Chem. Soc. 136, 17730–17733 (2014). \n17. Shi, D. et al. Low trap-state density and long carrier diffusion in organolead trihalide perovskite single crystals. Science 347, 519–522 (2015). \n18. Stoumpos, C. C., Malliakas, C. D. & Kanatzidis, M. G. Semiconducting tin and lead iodide perovskites with organic cations: phase transitions, high mobilities, and near-infrared photoluminescent properties. Inorg. Chem. 52, 9019–9038 (2013). \n19. Dong, Q. et al. Electron-hole diffusion lengths $>175~{\\upmu\\mathrm{m}}$ in solution-grown $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ single crystals. Science 347, 967–970 (2015). \n20. Dang, Y. et al. Bulk crystal growth of hybrid perovskite material $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ . Cryst. Eng. Commun. 17, 665–670 (2015). \n21. Baikie, T. et al. Synthesis and crystal chemistry of the hybrid perovskite $\\mathrm{(CH_{3}N H_{3})}$ ) $\\mathrm{PbI}_{3}$ for solid-state sensitised solar cell applications. J. Mater. Chem. A 1, 5628–5641 (2013). \n22. S¨ohnel, O. & Novotny´, P. Densities of Aqueous Solutions of Inorganic Substances (Elsevier, 1985). \n23. Wu, Y. et al. Retarding the crystallization of $\\mathrm{PbI}_{2}$ for highly reproducible planar-structured perovskite solar cells via sequential deposition. Energy Environ. Sci. 7, 2934–2938 (2014). \n24. Miyamae, H., Numahata, Y. & Nagata, M. The crystal structure of lead(II) iodide-dimethylsulphoxide(1/2), $\\mathrm{PbI}_{2}(\\mathrm{dmso})_{2}$ . Chem. Lett. 9, 663–664 (1980). \n25. Wakamiya, A. et al. Reproducible fabrication of efficient perovskite-based solar cells: X-ray crystallographic studies on the formation of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ layers. Chem. Lett. 43, 711–713 (2014). \n26. Giorgi, G. & Yamashita, K. Organic–inorganic halide perovskites: an ambipolar class of materials with enhanced photovoltaic performances. J. Mater. Chem. A \n3, 8981–8991 (2015). \n27. Stamplecoskie, K. G., Manser, J. S. & Kamat, P. V. Dual nature of the excited state in organic-inorganic lead halide perovskites. Energy Environ. Sci. 8, \n208–215 (2015). \n28. Jeon, N. J., Noh, J. H., Kim, Y. C., Yang, W. S., Ryu, S. & Seok, S. I. Solvent engineering for high-performance inorganic-organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n29. Bose, R. et al. Direct femtosecond observation of charge carrier recombination in ternary semiconductor nanocrystals: the effect of composition and shelling. J. Phys. Chem. C 119, 3439–3446 (2015). \n30. Mohammed, O. F., Xiao, D., Batista, V. S. & Nibbering, E. T. J. Excited-state intramolecular hydrogen transfer (ESIHT) of 1,8-Dihydroxy-9,10-anthraquinone (DHAQ) characterized by ultrafast electronic and vibrational spectroscopy and computational modeling. J. Phys. Chem. A 118, 3090–3099 (2014). \n31. Poglitsch, A. & Weber, D. Dynamic disorder in methylammoniumtrihalogenoplumbates (II) observed by millimeter-wave spectroscopy. J. Chem. Phys. 87, 6373–6378 (1987). \n\n# Acknowledgements \n\nWe acknowledge the support of Awards URF/1/2268-01-01, URF/1/1741-01-01 and URF/1/1373-01-01 made by the King Abdullah University of Science and Technology (KAUST). \n\n# Author contributions \n\nM.I.S. and A.L.A. conceived the idea, developed the single-crystal growth, provided samples for all measurements, measured and analysed powder X-ray diffraction. I.D. and B.M. measured the steady-state PL and ultraviolet–visible. W.P. and Y.H. conducted single-crystal X-ray diffraction characterization. E.A. and O.F.M. conducted and analysed the TA measurement. B.M., L.W., O.F.M. and T.W. designed, performed and analysed the measurements of mobility and I–V trap-state density. G.M. assisted with the experimental synthesis. V.M.B. and A.G. did the theoretical studies. O.M.B. crafted and directed the overall research plan. M.I.S., A.L.A., V.M.B. and O.M.B. co-wrote the manuscript. All authors read and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Saidaminov, M. I. et al. High-quality bulk hybrid perovskite single crystals within minutes by inverse temperature crystallization. Nat. Commun. 6:7586 doi: 10.1038/ncomms8586 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1021_acsami.5b07517", + "DOI": "10.1021/acsami.5b07517", + "DOI Link": "http://dx.doi.org/10.1021/acsami.5b07517", + "Relative Dir Path": "mds/10.1021_acsami.5b07517", + "Article Title": "Origin of Outstanding Stability in the Lithium Solid Electrolyte Materials: Insights from Thermodynamic Analyses Based on First-Principles Calculations", + "Authors": "Zhu, YZ; He, XF; Mo, YF", + "Source Title": "ACS APPLIED MATERIALS & INTERFACES", + "Abstract": "First-principles calculations were performed to investigate the electrochemical stability of lithium solid electrolyte materials in all-solid-state Li-ion batteries. The common solid electrolytes were found to have a limited electrochemical window. Our results suggest that the outstanding stability of the solid electrolyte materials is not thermodynamically intrinsic but is originated from kinetic stabilizations. The sluggish kinetics of the decomposition reactions cause a high overpotential leading to a nominally wide electrochemical window observed in many experiments. The decomposition products, similar to the solid-electrolyte-interphases, mitigate the extreme chemical potential from the electrodes and protect the solid electrolyte from further decompositions. With the aid of the first-principles calculations, we revealed the passivation mechanism of these decomposition interphases and quantified the extensions of the electrochemical window from the interphases. We also found that the artificial coating layers applied at the solid electrolyte and electrode interfaces have a similar effect of passivating the solid electrolyte. Our newly gained understanding provided general principles for developing solid electrolyte materials with enhanced stability and for engineering interfaces in all-solid-state Li-ion batteries.", + "Times Cited, WoS Core": 1461, + "Times Cited, All Databases": 1607, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000363994700039", + "Markdown": "# Origin of Outstanding Stability in the Lithium Solid Electrolyte Materials: Insights from Thermodynamic Analyses Based on FirstPrinciples Calculations \n\nYizhou Zhu,† Xingfeng He,† and Yifei Mo\\*,†,‡ \n\n†Department of Materials Science and Engineering and ‡University of Maryland Energy Research Center, University of Maryland, College Park, Maryland 20742, United States \n\nSupporting Information \n\nABSTRACT: First-principles calculations were performed to investigate the electrochemical stability of lithium solid electrolyte materials in all-solid-state Li-ion batteries. The common solid electrolytes were found to have a limited electrochemical window. Our results suggest that the outstanding stability of the solid electrolyte materials is not thermodynamically intrinsic but is originated from kinetic stabilizations. The sluggish kinetics of the decomposition reactions cause a high overpotential leading to a nominally wide electrochemical window observed in many experiments. \n\n![](images/8a315c8b0e442eee07d103b33b4c5d705b65e78ef5a68f6e9aa5fe5c84bac6ac.jpg) \n\nThe decomposition products, similar to the solid-electrolyte-interphases, mitigate the extreme chemical potential from the electrodes and protect the solid electrolyte from further decompositions. With the aid of the first-principles calculations, we revealed the passivation mechanism of these decomposition interphases and quantified the extensions of the electrochemical window from the interphases. We also found that the artificial coating layers applied at the solid electrolyte and electrode interfaces have a similar effect of passivating the solid electrolyte. Our newly gained understanding provided general principles for developing solid electrolyte materials with enhanced stability and for engineering interfaces in all-solid-state Li-ion batteries. \n\nKEYWORDS: lithium ionic conductor, solid electrolyte, electrochemical stability, passivation, solid-electrolyte-interphases, first-principles calculations \n\n# 1. INTRODUCTION \n\nThe continued drive for high energy density Li-ion batteries has imposed ever stricter requirements on the electrolyte materials. Current organic liquid electrolytes are flammable, causing notorious safety issues for Li-ion batteries. The limited electrochemical window of the organic liquid electrolytes limits the choice of electrode materials and hence the achievable energy density of the Li-ion batteries. The solid electrolyte materials based on Li-ion conducting ceramics are promising alternatives for the conventional polymer electrolytes to make all-solid-state Li-ion batteries.1,2 Thanks to the recent discovery and development of Li ionic conductor materials such as Li thiophosphates1,3,4 and Li garnet-type materials,5 high Li ionic conductivities of $\\mathrm{1-10~mS/cm}$ comparable to the organic liquid electrolytes have been achieved in the solid electrolyte materials. Moreover, the claimed outstanding stability of ceramic solid electrolyte materials may provide intrinsic safety for the Li-ion batteries and may enable Li metal anode and high-voltage cathodes,1,2 which may significantly increase the energy density for Li-ion batteries.6−8 \n\nThe claimed outstanding stability of the solid electrolyte materials is based on the widely reported electrochemical window of $_{0-5\\mathrm{~V~}}$ from cyclic voltammetry (CV) measurements. $^{1,8-10}$ However, some recent experimental and computational studies questioned the claimed stability of solid electrolyte materials against Li metal and at high voltages. For example, the reduction and oxidation of $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ (LGPS) at low and high potentials, respectively, in contrast to the originally claimed $_{0-5\\mathrm{~V~}}$ electrochemical window, have been demonstrated by first-principles computation11 and the experiments.12 Recent in situ X-ray photoelectron spectroscopy (XPS) experiments have also observed the interfacial decomposition of LiPON,13 lithium lanthanum titanate,14 and NASICON-type15 solid electrolyte materials against Li metal. These reports lead to an outstanding discrepancy, i.e., the wide electrochemical windows of $_{0-5\\mathrm{~V~}}$ reported in many CV experiments are contradictory to the decomposition of the solid electrolyte against Li. Although the experimental evidences for the decompositions have been reported in a range of materials from sulfides to oxides and oxynitrides, it is not clear whether the decomposition of ceramic solid electrolytes is a universal phenomenon and whether some ceramic solid electrolyte can indeed achieve a “true” stability window of $_{0-5\\mathrm{~V~}}$ . It is speculated that the decomposition products form interphases to passivate the solid electrolytes and to inhibit the continuous bulk decompositions.11,14,15 However, little is understood about the fundamental physical and chemical mechanisms governing the decomposition and the passivation of the solid electrolyte materials in the all-solid-state Li-ion batteries. Why only certain materials can be spontaneously passivated but others cannot? In addition, the decomposition products at the interfaces between the solid electrolyte and electrode may cause high interfacial resistances and mechanical failures in the all-solid-state Li-ion batteries.2,16 Therefore, computation methods are needed to identify the potential formation of the interfacial decomposition products and to quantify the electrochemical window of the solid electrolyte with the considerations of the passivation effects. \n\nTable 1. Electrochemical Window and Phase Equilibria at the Reduction and Oxidation Potentials of the Solid Electrolyte Materials \n\n\n
reduction potential (V)phase equilibria at the reduction potential oxidation potential (V) phase equilibria at the oxidation potentia
LiS-LiS (stable at 0 V)2.01S
LGPS1.71P, Li4GeS4, LiS2.14LiPS4, GeS2, S
Li3.25Ge0.25P0.75S41.71P, Li4GeS4, LiS2.14LiPS4, GeS, S
LiPS41.71P, LiS2.31S, PSs
Li4GeS41.62LiS, Ge2.14GeS2, S
LiPS12.28LiPS4, P4S92.31S, PS5
LigPS5Cl1.71P, LiS, LiCl2.01LiPS4, LiCl, S
LiPSgI1.71P, LiS, LiI2.31LiI, S, PSs
LiPON0.68LiP, LiPN, LiO2.63PNs, LiPO, N
LLZO0.05ZrO, LaO3,LiO2.91LiO, LaO,LiZrO7
LLTO1.75LiTisO12, Li7/Ti11/6O4, LaTiO73.71O, TiO LaTiO7
LATP2.17P, LiTiPO5, AIPO4, LiPO44.21O, LiTi(PO4)3, Li4PO7, AIPO4
LAGP2.70Ge, GeO,LiPO7,AIPO44.27O2, GesO(PO4)6, Li4PO7, AIPO4
LISICON1.44Zn, Li4GeO43.39LiZnGeO4, LiGeO3,O
\n\nIn this study, we systematically investigated the electrochemical stability of common lithium solid electrolytes using first-principles computation methods. We identified the phase equilibria and decomposition reaction energies of the lithiation and delithiation of the solid electrolyte materials against Li metal and at high voltages. Our computation results determined that most solid electrolyte materials have a limited intrinsic electrochemical window and that the decomposition of most solid electrolyte materials are thermodynamically favorable forming decomposition interphases. The mechanisms were suggested regarding the origins of the high nominal electrochemical window observed in the experimental studies. In addition to the high overpotential due to the sluggish kinetics of the decomposition reactions, the passivation mechanism of the decomposition interphases were illustrated. The extensions of the electrochemical window provided by the interphases were quantified in the first-principles calculations. Similar to the interphases, the coating layer materials artificially applied at the interfaces were demonstrated to stabilize and passivate the solid electrolyte materials. These results establish general guidelines for designing solid electrolyte materials with enhanced stability, which is crucial to enable Li metal anode and high-voltage cathode materials in all-solid-state Li-ion batteries. \n\n# 2. METHODS \n\nAll density functional theory (DFT) calculations in this work were performed using the Vienna Ab initio Simulation Package (VASP) within the projector augmented-wave approach, and the Perdew− Burke−Ernzerhof (PBE) generalized gradient approximation (GGA) functional was used. The parameters of DFT calculations, such as the plane-wave energy cutoff and $k$ -points density, were consistent with the parameters used for the Materials Project (MP).17 The energy correction schemes for oxides, transition metals, and gas molecules were included as in the MP.18,19 The energies of most materials in this study were obtained from the MP database,20 and DFT calculations were performed only for the solid electrolyte materials that were not available from the MP database. Details of these solid electrolyte structures were summarized in the Supporting Information. In addition, the calculated reaction energies and voltages neglected the contribution of the PV terms and the entropy terms as in previous studies.11,21 \n\nWe constructed the grand potential phase diagram11,21 to study the electrochemical stability of the solid electrolyte materials. The grand potential phase diagram, which were generated using pymatgen,22 identified the phase equilibria of the material in equilibrium with an opening Li reservoir of Li chemical potential $\\mu_{\\mathrm{Li}}.$ . As in the previous studies,11,23 the applied electrostatic potential $\\phi$ was considered in the Li chemical potential $\\mu_{\\mathrm{Li}}$ as \n\n$$\n\\mu_{\\mathrm{Li}}(\\phi)=\\mu_{\\mathrm{Li}}^{\\:0}-e\\phi\n$$ \n\nwhere $\\mu_{\\mathrm{Li}}^{0}$ is the chemical potential of Li metal, and the potential $\\phi$ is referenced to Li metal in this study. To quantify the thermodynamic driving force, we calculated the decomposition reaction energy $E_{\\mathrm{D}}$ for the decomposition reactions at applied voltage $\\phi$ as \n\n$$\n\\begin{array}{r l}&{{E}_{\\mathrm{{D}}}(\\phi)=E(\\mathrm{phase\\equilibria},\\phi)-E(\\mathrm{solid\\electrolyte})}\\\\ &{\\phantom{E_{\\mathrm{{D}}}(\\phi)=E\\left(\\mathrm{phase\\equilibria},\\phi\\right)-}-\\Delta{n}_{\\mathrm{L}{\\mid}}\\mu_{\\mathrm{{Li}}}(\\phi)}\\end{array}\n$$ \n\nwhere E(phase equilibria, $\\phi$ ) is the energy of the phase equilibria at the potential $\\phi,$ $E$ (solid electrolyte) is the energy of the solid electrolyte, and $\\Delta n_{\\mathrm{Li}}$ is the change of the number of Li from the solid electrolyte composition to the phase equilibria composition during the lithiation or delithation reaction. \n\n# 3. RESULTS \n\n3.1. Stability of Solid Electrolyte Materials against Li Metal. We first evaluated the electrochemical stability of solid electrolyte materials against Li metal and at low voltages. The phase equilibria, i.e., the phases with the lowest energy, in equilibrium with Li metal were identified by the Li grand potential phase diagrams (Table 1). The solid electrolyte materials are not thermodynamically stable against Li metal (Table 2) and are reduced at low voltages with highly favorable decomposition energy (Figure 1 and Table 2). In contrast, the Li binary compounds, such as LiF, $\\mathrm{Li}_{2}\\mathrm{O},\\mathrm{Li}_{2}\\mathrm{S},\\mathrm{Li}_{3}\\mathrm{P},$ and $\\mathrm{Li}_{3}\\mathrm{N},$ are thermodynamically stable against Li metal (Figure 2a). The lithiation and reduction of $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ (LGPS) starts at $1.71\\mathrm{V},$ and the LGPS in equilibrium with Li metal is eventually lithiated into the phase equilibria consisting of $\\mathrm{Li}_{15}\\mathrm{Ge}_{4},$ $\\mathrm{Li}_{3}\\mathrm{P}_{i}$ , and $\\mathrm{Li}_{2}S$ . The Li reduction of the LGPS into these reaction products has a highly favorable reaction energy of $-1.25\\ \\mathrm{eV}/\\$ atom $(-3014\\mathrm{kJ/mol}$ of LGPS) at $0\\mathrm{v}$ (Figure 1 and Table 2). In agreement with our computation, the reduction of LGPS starting at $1.71\\mathrm{~V~}$ and the formation of Li−Ge alloy after the reduction have been demonstrated in the cyclic voltammetry (CV) and XPS experiments, respectively.12 Other sulfides materials, such as $\\mathrm{Li}_{3.25}\\mathrm{Ge}_{0.25}\\mathrm{P}_{0.75}\\mathrm{S}_{4},$ $\\mathrm{Li}_{3}\\mathrm{PS}_{4},$ $\\mathrm{Li}_{4}\\mathrm{GeS}_{4},$ $\\mathrm{Li}_{6}\\mathrm{PS}_{5}\\mathrm{Cl},$ and $\\mathrm{Li}_{7}\\mathrm{P}_{2}\\mathrm{S}_{8}\\mathrm{I},$ are reduced at a similar voltage of ${\\sim}1.6{-}1.7\\mathrm{~V~}$ . The reduction potential is mostly governed by the reduction of $\\mathrm{\\bfP}$ and Ge in the materials, and the reduction products include $\\mathrm{Li}_{3}\\mathrm{P}$ and $\\mathrm{Li}_{2}S$ at $0\\mathrm{V}$ . For those materials containing Ge, Cl, and I elements, Li−Ge alloy, LiCl, and LiI are formed, respectively, as a part of phase equilibria at $0\\mathrm{V}.$ The $\\mathrm{Li}_{7}\\mathrm{P}_{3}\\mathrm{S}_{11}$ is reduced at a voltage of $2.28\\mathrm{~V~}$ into $\\mathrm{Li_{3}P S_{4}}$ with a small decomposition energy (Figure 1a), and the majority of the reduction starts at 1.71 V due to the lithiation of $\\mathrm{Li}_{3}\\mathrm{PS}_{4}$ (Table 2). The decomposition energy for all these solid electrolyte decreases with the potential to $\\mathrm{{\\sim}}1\\mathrm{{eV}}/$ atom at $0\\mathrm{V}$ (Figure 1a and Table 2), indicating the highly favorable reduction reactions of the sulfide solid electrolytes. \n\nTable 2. Reduction Reaction of the Solid Electrolyte Materials with Li Metal \n\n\n
phase equilibria with Li metalED (eV/atom)
LiSLiS (stable)0
LGPSLisGe4, LiP, LiS-1.25
Li3.25Ge0.25P0.75S4LisGe4, LiP, LiS-1.28
LiPS4LiP, LiS-1.42
Li4GeS4LisGe4, LiS-0.89
LiPS1LiP, LiS-1.67
LigPS5ClLiP, LiS, LiCl-0.96
Li-PS8ILiP, LiS, LiI-1.26
LiPONLiP, LiN, LiO-0.66
LLZOZr (or ZrO), LaO3, LiO-0.021
LLTOTiO, LaO, LiO-0.34
LATPTiP, TiAl, LiP, LiO-1.56
LAGPLigAl4, LisGe4, LiP, LiO-1.99
LISICONLisGe4, LiZn, LiO-0.77
\n\nThe reduction of oxide solid electrolyte materials $\\mathrm{Li}_{0.33}\\mathrm{La}_{0.56}\\mathrm{TiO}_{3}$ (LLTO) and $\\mathrm{Li_{1.3}T i_{1.7}A l_{0.3}(P O_{4})_{3}}$ (LATP) starts at a voltage of 1.75 and $2.17\\mathrm{~V},$ respectively. Our predicted reduction potential of LLTO is in good agreement with the value of $1.7\\mathrm{-}1.8\\mathrm{~V~}$ reported in the CV experiments.24,25 The calculations also found the reduction of $\\mathrm{Ti}^{\\bar{4}+}$ in LLTO and LATP into $\\mathrm{Ti}^{3+}$ or lower valences at low voltages (Tables 1 and 2). The reduction of Ti is a widely known problem and is observed at the interfaces of $\\mathrm{LLTO}^{14}$ and $\\mathsf{\\bar{L}A T P}^{15}$ with Li metal by in situ XPS spectroscopy. In addition, t he reduction of Ge-cont aining oxide mat erials $\\mathrm{Li}_{1.5}\\mathrm{Al}_{0.5}\\mathrm{Ge}_{1.5}(\\mathrm{PO}_{4})_{3}$ (LAGP) and $\\mathrm{Li}_{3.5}\\mathrm{Zn}_{0.25}\\mathrm{GeO}_{4}$ (LISICON) starting at 2.7 and $1.4~\\mathrm{V}_{;}$ , respectively, and Li−Ge alloys are formed at low voltages (Figure 1b and Table 2). The reductions of LAGP and LISICON are consistent with the experiment studies.26−28 The good agreements between our computation results and many experiments demonstrated the validity of our computation scheme. \n\nOur calculations found the Li reduction of the solid electrolyte materials that are thought to be stable against Li. For example, LiPON, which is calculated using $\\mathrm{Li}_{2}\\mathrm{PO}_{2}\\mathrm{N}$ as a representative of the material class (details are provided in the Supporting Information), shows a reduction potential of 0.69 V. The final decomposition products of LiPON in equilibrium with Li metal are $\\mathrm{Li}_{3}\\mathrm{N},$ $\\mathrm{Li}_{2}\\mathrm O_{;}$ and $\\mathrm{Li}_{3}\\mathrm{P}$ (Table 2), which are consistent with the in situ XPS observations.13 Although the calculated decomposition energy of LiPON is as large as $-0.66$ eV/atom at $0\\mathrm{V}$ (Figure 1b and Table 2), LiPON is known to be compatible with Li metal as demonstrated by many experimental studies.10,29 Similarly, $\\mathrm{Li}_{3}\\mathrm{PS}_{4}$ and $\\mathrm{Li}_{7}\\mathrm{P}_{2}\\mathrm{S}_{8}\\mathrm{I},$ which are reported to be compatible with Li metal anode,8,30,31 are reduced against Li metal and at low voltages (Table 1 and Table 2). Therefore, the stability of these solid electrolyte materials against Li metal is not thermodynamically intrinsic. \n\nThe decomposition products, which form an interphase between the solid electrolyte and electrode, passivate the solid electrolyte and inhibit the continuous decomposition. For example, the decomposition products of LiPON, $\\mathrm{Li}_{3}\\mathrm{PS}_{4},$ and $\\mathrm{Li}_{7}\\mathrm{P}_{2}\\mathrm{S}_{8}\\mathrm{I}$ are Li binary compounds, such as $\\mathrm{Li_{2}O,\\ L i_{2}S,\\ L i_{3}P,}$ $\\mathrm{Li}_{3}\\mathrm{N},$ and LiI, formed at the Li reduction. The interphase consisting of these decomposition products are stable against the high $\\mu_{\\mathrm{Li}}$ of Li metal (Figure 2a), which is beyond the reduction potential (cathodic limit) of the solid electrolyte (Figure 2b). At the equilibrium, the redistribution of $\\mathrm{Li}^{+}$ and other charged carriers (such as electron $\\mathrm{e}^{-\\cdot}$ ) are formed at the interface to account for the potential drop across the electrode−electrolyte interface.34 The electrochemical potential of the highly mobile $\\mathrm{Li}^{+}$ , $\\tilde{\\mu}_{\\mathrm{Li}^{+}},$ which includes the electrostatic potential energy, is constant across the interface. In contrast, the electrochemical potential of the electronic carrier $\\tilde{\\mu}_{\\mathrm{e}^{-}}$ (red line in Figure 2b) decreases significantly in the interphase from the anode to the solid electrolyte, since these interphases have poor electronic mobility and conductivity. Therefore, the Li chemical potential $\\mu_{\\mathrm{Li}}$ (black line in Figure 2b), which equals to the sum of $\\tilde{\\mu}_{\\mathrm{Li}^{*}}$ and $\\tilde{\\mu}_{\\mathrm{e}^{-}},$ decreases in the interphase from the anode to the solid electrolyte. The high value of $\\mu_{\\mathrm{Li}}$ from the anode decreases to be within the electrochemical window of the solid electrolyte after the passivation of the decomposition interphase. As a result, the decomposition of the solid electrolyte has no thermodynamic driving force to continue into the bulk. The solid electrolyte is stabilized by the decomposition interphases, which essentially serve as solidelectrolyte-interphases (SEIs) in all-solid-state Li-ion batteries. In summary, the SEI of the decomposition interphase decreases the high Li chemical potential $\\mu_{\\mathrm{Li}}$ applied on the solid electrolyte and bridges the Li chemical potential gap between Li metal and the solid electrolyte. This passivation mechanism explained the observed Li metal compatibility of LiPON, $\\mathrm{Li}_{3}\\mathrm{PS}_{4},$ and $\\mathrm{Li}_{7}\\mathrm{P}_{2}\\mathrm{S}_{8}\\mathrm{I}.$ \n\n![](images/677ee4b2869c9ff1c7202d9d7be6773ad93811439df65641bd6a4441abde3bc2.jpg) \nFigure 1. Decomposition energy $E_{\\mathrm{D}}$ of (a) sulfide and (b) oxide solid electrolyte materials as a function of the applied voltage $\\phi$ or Li chemical potential $\\mu_{\\mathrm{Li}}.$ \n\n![](images/41295ceb4464ce4ddcf50864a13ea95890d5c2e29c6f3416950f3ab18e8dac61.jpg) \nFigure 2. (a) Electrochemical window (solid color bar) of solid electrolyte and other materials. The oxidation potential to fully delithiate the material is marked by the dashed line. (b) Schematic diagram about the change of Li chemical potentials $\\mu_{\\mathrm{Li}}$ (black line), the electrochemical potential $\\tilde{\\mu}_{\\mathrm{Li}^{+}}$ (blue dashed line), and $\\tilde{\\mu}_{\\mathrm{e}}^{-}$ (red dashed line) across the interface between the anode and the solid electrolyte. Since the actual profile of $\\tilde{\\mu}_{\\mathrm{e}}^{\\mathrm{~-~}}$ determined by the charge carrier distribution may be complicated,32,33 the profiles of chemical and electrochemical potential shown here are schematic and may not be linear. The vertical scale is for the electrostatic potential or the voltage referenced to Li metal and is reversed for the chemical potential or electrochemical potential (eq 1). \n\nThe passivation mechanism relies on the electronic insulating properties of the decomposition interphase layers to stabilize the solid electrolyte and is not active if the interphase layer is electronically conductive. For example, the reduction of LGPS, LAGP, and LISICON with Li metal forms electronically conductive Li−Ge alloys, and the lithiation of LLTO and LATP forms titanates with Ti of $^{3+}$ or lower valences. The decomposition interphases for these solid electrolytes at Li reductions are mixed electronic and ionic conductors. The electronic conductivity in the interphase cannot account for the drop of $\\tilde{\\mu}_{\\mathrm{e}^{-}}$ across the interface regardless of the specific electron transport mechanism being metallic, band, or polaronic conduction. These mixed conductor interphases cannot account for the $\\mu_{\\mathrm{Li}}$ drop as the change of both $\\tilde{\\mu}_{\\mathrm{Li}^{+}}$ and $\\tilde{\\mu}_{\\mathrm{e}^{-}}$ would be small across the interphase. As a result, the solid electrolyte is still exposed to the high $\\mu_{\\mathrm{Li}}$ of the anode, and the reduction reaction continues into the bulk. In addition, the mixed electronic and ionic conductor interphase facilitate the kinetic transport of Li ion and electrons for the decomposition reactions.14 The absence of the passivation mechanism explains the lithation and reduction of LGPS, LLTO, LATP, LAGP, and LISICON observed in the CV experiments. \n\nIt is worth noting that garnet LLZO shows the lowest reduction potential of as low as $0.05\\mathrm{V}$ against Li and the least favorable decomposition reaction energy of only $0.021\\ \\mathrm{~eV}/\\$ atom $(49\\mathrm{~kJ/mol}$ of LLZO) at $0\\mathrm{v}$ among all solid electrolyte materials examined (Figure 1 and Table 2). Given such small reaction energy, the Li reduction of garnet is likely to be kinetically inhibited, and the reduction products of $\\mathrm{Li}_{2}\\mathrm O$ , $\\mathrm{Zr}_{3}\\mathrm{O},$ and $\\mathrm{La}_{2}\\mathrm{O}_{3}$ (Table 1) may provide passivation to the material. These explain the widely reported $_{0-5\\mathrm{~V~}}$ window of garnet from the CV measurements in the literature.5,35 The reduction of garnet at $0.05\\mathrm{~V~}$ forms $\\mathrm{Zr}_{3}\\mathrm{O}$ (Table 1), following another plateau at $0.004\\mathrm{V}$ to form $\\mathrm{Zr}$ (Table 2 and Table S2) based on the DFT GGA energies. Since these small values of energy and voltage is below typical accuracy of DFT and the approximations of the scheme (see section 2), it is inconclusive whether the garnet LLZO is reduced to $\\mathrm{Zr}_{3}\\mathrm{O}$ or $Z\\mathbf{r}$ at $0\\mathrm{v}$ or against Li metal. Nevertheless, the formation of $\\mathrm{Zr}$ would be thermodynamically favorable at a potential significantly lower than $0\\mathrm{V},$ which corresponds to applying high current density at the Li−LLZO interface. Recent report of instability of garnet against Li at elevated temperatures of $300~^{\\circ}\\mathrm{C}$ may be an indication of the limited stability of garnet against Li metal,36 as the diffusion and phase nucleation are facilitated at high temperatures. \n\n3.2. Stability of Solid Electrolyte Materials at High Voltages. The oxidation reactions of the solid electrolyte materials were investigated using the same method in section 3.1. The LGPS material is delithiated and oxidized starting at $2.14\\mathrm{V}$ (Table 1 and Figure 1), and the final oxidation products of $\\mathrm{P}_{2}S_{5},$ ${\\mathrm{GeS}}_{2},$ and S are formed at the equilibrium oxidation potential of 2.31 V (Table 3). The oxidation potential of the \n\nTable 3. Oxidation Reaction of the Solid Electrolyte Materials at 5 V \n\n\n
phase equilibria at 5 V Ep (eV/atom)
LiSS -1.99
LGPS GeSz, PSs, S-1.12
Li3.25Ge0.25P0.75S4 PSs, S, GeS2-1.08
LiPS4 S, PSs-1.01
Li4GeS4 GeSz, S-1.27
LiPS1 S, PS5-0.92
LigPS5Cl PSs, S, PCl-1.33
Li-PS8I PSs, S, I-1.04
LiPON PNO, POs, N-0.69
LLZO OLaO,LaZrO-0.53
LLTO O,TiO, LaTiO7-0.15
LATP O,TiPO7,Ti5P4O20,AIPO4-0.065
LAGPGe5O(PO4)6, GePO7, AIPO4, O -0.056
LISICON ZnGeO4, GeO, O-0.57
\n\nLGPS is confirmed by the CV experiment.12 Similar to $\\mathrm{Li}_{2}S,$ all sulfide solid electrolytes such as $\\mathrm{Li}_{3.25}\\mathrm{Ge}_{0.25}\\mathrm{P}_{0.75}\\mathrm{S}_{4},$ $\\mathrm{Li}_{3}\\mathrm{PS}_{4},$ $\\mathrm{Li}_{4}\\mathrm{GeS}_{4},\\mathrm{Li}_{7}\\mathrm{P}_{3}\\mathrm{S}_{11},$ and $\\mathrm{Li}_{7}\\mathrm{P}_{2}\\mathrm{S}_{8}\\mathrm{I}$ are oxidized at $2{-}2.5\\mathrm{V}$ to form S (Table 1 and Table 3). The other elements, such as $\\mathrm{\\bfP}$ and Ge, are usually oxidized into $\\mathrm{P}_{2}\\mathrm{S}_{5}$ and ${\\mathrm{GeS}}_{2},$ respectively. The oxidation reactions of sulfide solid electrolytes are highly favorable at $\\ensuremath{5\\mathrm{~V~}}$ as described by the decomposition energy (Figure 1a and Table 3). \n\nOxide solid electrolyte materials have higher oxidation potential than sulfides. The oxidation of LLZO, LISICON, and LLTO starts at 2.91, 3.39, and $3.71~\\mathrm{V}_{;}$ , respectively. The NASICON materials, LATP and LAGP, show the best resistance to oxidation with the highest oxidation potential of 4.21 and $4.28~\\mathrm{~V},$ respectively (Table 1), and the lowest decomposition energy of only $\\mathrm{\\sim-}0.06~\\mathrm{eV/}$ atom at $_{5\\mathrm{~V~}}$ (Figure 1b and Table 3). The delithiation reactions continue at higher voltages, and $\\mathrm{O}_{2}$ gas is released during the oxidation at high voltages for all oxide solid electrolytes (Table 3). The oxidation of these solid electrolyte materials is not surprising, given that $\\mathrm{Li}_{2}\\mathrm O$ is oxidized at $2.9\\mathrm{V}$ and that the $\\mathrm{O}_{2}$ gas is released by the further oxidation of ${\\mathrm{Li}}_{2}{\\mathrm O}_{2}$ . LiPON starts oxidation at $2.63\\mathrm{~V~}$ with the $\\mathbf{N}_{2}$ gas release. Our computation results are consistent with the experiments by $\\mathrm{Yu}$ et al.,10 in which the onset of LiPON oxidation at ${\\sim}2.6\\mathrm{~V~}$ in the $I{-}V$ measurements and the microsized gas bubbles in the LiPON material were observed after applying a high voltage of $6\\mathrm{V}$ . \n\nA significant overpotential to the calculated thermodynamic equilibrium potential is expected for the oxidation reaction processes, which are likely to have slow kinetics. The kinetic limitations of the oxidation reactions may come from multiple aspects. Most decomposition products at high voltages (Table 3) are electronically insulating, and the diffusion of non-Li elements is usually slow in solids. Furthermore, the nucleation and release of $\\mathrm{O}_{2}$ and $\\mathbf{N}_{2}$ gas molecules are likely to have sluggish kinetics. For example, a significant overpotential of $^{>1}$ V is often observed in the oxygen evolution reactions in metalair batteries.37 Therefore, the overpotential of the decomposition reactions may provide a higher nominal oxidation potential of ${>}5\\mathrm{~V~}$ and a wider nominal electrochemical window observed in the CV experiments.1,8−10 \n\n![](images/00bbd9eb45f3a8e42f0067205e6b8af475ef2980d3b6d7cf63699146ced97e27.jpg) \nFigure 3. (a) Electrochemical stability window (solid color bars) of commonly used coating layer materials. The oxidation potential to fully delithiate the material is marked by the dashed line. The line at $3.9\\mathrm{~V~}$ represents the equilibrium voltage of the $\\mathrm{LiCoO}_{2}$ cathode material. (b) Schematic diagram about the change of Li chemical potentials $\\mu_{\\mathrm{Li}}$ (black line) and the electrochemical potential $\\tilde{\\mu}_{\\mathrm{Li}^{+}}$ (blue dashed line) and $\\tilde{\\mu}_{\\mathrm{e}}^{-}$ (red dashed line) across the interface between the solid electrolyte and the cathode material. \n\n3.3. Extend the Stability of Solid Electrolytes by Applying Coating Layers. Currently, the interfacial resistance has become a critical problem for the performance of allsolid-state Li-ion batteries. The engineering of the interface, such as the application of interfacial coating layers, is used to improve interfacial protection and to reduce interface resistance. In this section, we investigated the electrochemical stability of the coating layer materials, such as $\\operatorname{Li}_{4}\\operatorname{Ti}_{5}\\operatorname{O}_{12},$ 38,39 $\\mathrm{LiTaO_{3}^{'40}\\ L i N b O_{3}^{41,\\ddagger_{2}}\\ L i_{2}S i O_{3}^{'43}}$ and $\\mathrm{Li_{3}P O_{4}},^{44}$ wh5ich were demonstrated to suppress the mutual diffusion of non-Li elements and to reduce the interfacial resistance at the solid electrolyte−cathode interfaces in all-solid-state Li-ion batteries. $^{2,\\mathrm{i}6,40,45}$ Our calculations show that these coating layer materials have an electrochemical window from the reduction potential of $0.7\\mathrm{-}1.7\\mathrm{~V~}$ to the oxidation potential of $3.7\\mathrm{-}4.2\\mathrm{~V~}$ (Figure 3a). Therefore, the coating layer materials are stable between 2 and $4\\mathrm{V}_{i}$ , the usual voltage range during the cycling of Li-ion batteries. In addition, the coating layer materials have poor electronic conductivity and can serve as artificial SEIs to passivate the solid electrolyte through the same mechanisms illustrated in section 3.1 (Figure 3b). Given that the sulfide solid electrolyte materials are oxidized at as low as $2\\mathrm{V}$ and are not thermodynamically stable at the voltage of $4\\mathrm{V}_{i}$ , the coating layers serve as critical passivations through the same mechanism illustrated in section 3.1. The coating layers mitigate the low Li chemical potential $\\mu_{\\mathrm{Li}}$ from the cathode material applied on the solid electrolyte materials. As a result, the oxidation and delithiation of the solid electrolyte at the cathode interface is stopped, and the oxidation potential (anodic limit) of the solid electrolyte is extended by the artificial coating layer. Therefore, the coating layer effectively extended the anodic limit of the sulfide solid electrolyte from ${\\sim}2{-}2.3\\mathrm{~~V~}$ to ${\\sim}4\\mathrm{~V~}$ . The overpotential to oxidize the coating layers may further extend the nominal stability window. Similar strategy of applying artificial coating layers has been employed at the anode side for the protection and stabilization of Li metal anode. For example, Polyplus46 has applied coating layers between Li metal and LATP electrolyte to protect the LATP materials against Li metal. The passivation mechanism of the coating layer at the anode side is the same as the decomposition interphase demonstrated in section 3.1. \n\n# 4. DISCUSSION \n\nOur thermodynamic analyses based on first-principles calculations indicate that most solid electrolyte materials have a limited electrochemical window. In contrast to the widely held perception about the outstanding stability of the solid electrolyte materials, the solid electrolyte materials are reduced and oxidized at low and high potentials, respectively, and are not thermodynamically stable against Li metal. The sulfide solid electrolytes based on thio-phosphates are reduced at ${\\sim}1.6{-}1.7\\$ $\\mathrm{\\DeltaV}$ and oxidized at ${\\sim}2{\\-}{-}2.3\\ \\mathrm{V}.$ . The stability window of oxide solid electrolytes varies greatly from one material to another. Although some oxides have high reduction potential as sulfides, most oxide solid electrolytes have a significantly higher oxidation potential and are not oxidized until $>3\\mathrm{~V~}$ . In particular, the NASICON materials, LATP and LAGP, are thermodynamically stable up to ${\\sim}4.2\\mathrm{V}.$ . Among all these oxides investigated, the Li garnet materials, such as LLZO, have the best resistance to Li reduction. Overall, the oxide solid electrolyte materials have significantly wider electrochemical window than sulfides. The reduction and oxidation potentials as well as the decomposition products of solid electrolytes predicted from our calculations are in good agreement with prior experimental studies, confirming that our computation method based on the Li grand potential phase diagram is a valid scheme in evaluating the electrochemical stability of materials. \n\nOur calculation results demonstrated that the good stability of the solid electrolyte materials is originated from the kinetic stabilizations. First, the wide, nominal electrochemical window observed in many CV experiments can be partially attributed to the significant overpotential of the sluggish kinetics during the decomposition reactions (Figure 4). The decomposition reactions though kinetically sluggish are still thermodynamically favorable at the applied overpotential and may happen over an extended period of time, leading to the deterioration of the batteries. This kinetic stabilization from the sluggish kinetics of the reactions is different from the passivation mechanisms illustrated in section 3.1. The passivation mechanism of the interphases is the origin of the outstanding stability in the solid electrolyte. The decomposition interphases with good stability and poor electronic transport are effectively the SEIs in the allsolid-state Li-ion batteries to passivate the solid electrolytes (Figure 4). The interphases, which are stable against solid electrolytes and electrodes, mitigate the Li chemical potential discrepancy between the electrolyte and electrode at the interfaces. As a result, the anodic/cathode limits and the electrochemical window of the solid electrolyte are significantly extended by the extra electrochemical window provided by the interphases (Figure 4). The effective electrochemical window of the solid electrolyte materials is its own intrinsic electrochemical window plus the electrochemical window of the interphases (Figure 4). \n\n![](images/b619fdac14a7665f4d320d5a4e0eebf8f61c9e93addd0671397382d3242a3d10.jpg) \nFigure 4. Schematic diagram about the electrochemical window (color bars) and the Li chemical potential profile (black line) in the all-solidstate Li-ion battery. The profile of chemical potential is schematic in this plot and may not be linear. The high $\\mu_{\\mathrm{Li}}$ in the anode (silver) and low $\\mu_{\\mathrm{Li}}$ in the cathode (blue) are beyond the stability window of the solid electrolyte (green). The observed nominal electrochemical window is extended by the overpotential (dashed line) and by the interphases (orange and yellow), which account for the gap of $\\mu_{\\mathrm{Li}}$ between solid electrolyte and electrodes across the interfaces. \n\nIn this study, the electrochemical window of the solid electrolyte and the extensions by the interphases were calculated using the first-principles methods. Our computation scheme evaluated the electrochemical window based on the equilibrium of the neutral Li, which is a necessary condition for the equilibrium at the interface. As suggested by Goodenough,47 the electrochemical window of the electrolyte can also be estimated by the difference between the lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) states of the electrolyte based on the equilibrium of electrons across the interfaces. These equilibrium conditions of carriers other than neutral Li also need to be satisfied at the interfaces. The equilibria of the charged carriers such as electrons or $\\mathrm{Li^{+}}$ are subject to the formation of polarizations and interfacial space charge layers, which are dependent on the defect chemistry and the structures of the interface.32,33 In some cases, a significant amount of electrons or holes may accumulate in the interphases due to the charge redistribution, defect chemistry, or special interfacial structures and may activate the electronic conductions in the interphase deactivating the passivation effects. Nevertheless, our results based on the equilibrium of neutral Li are in good agreement with many experimental studies, suggesting the validity of our scheme. \n\nThe interphase stabilization mechanism provides guidance for the development of solid electrolyte materials. The formation of the decomposition interphases plays an essential role in the stability of the solid electrolyte and should be considered in the design of solid electrolyte materials. Our calculations have shown that the reduction of the solid electrolytes is generally governed by the reduction of the cations, and the interphases formed by the reduction of these cations often control the interfacial stability. For example, LGPS, LAGP, LATP, and LLTO solid electrolyte materials form electronically conductive interphases at low voltages, such as Li−Ge alloys or Li titanates, which cannot provide the passivation for the solid electrolyte materials. Therefore, our results suggest that certain cations or dopants, such as Ti and Ge, in the solid electrolyte materials, negatively affect the stability against Li metal. Other cations, such as Si, Sn, Al, and $Z\\mathrm{n},$ , may have a similar effect. However, doping with anions does not have such limitations for the stability of the solid electrolyte at low voltages. The Li reduction products of common anions, such as O, S, F, Cl, and I, are usually Li binary materials, such as lithium chalcogenides and lithium halides, which are thermodynamically stable against Li and are good electronic insulators. The passivation provided by these materials is the origin of Li metal compatibility for LiPON, $\\mathrm{Li}_{3}\\mathrm{PS}_{4},$ and $\\mathrm{Li}_{7}\\mathrm{P}_{2}\\mathrm{S}_{8}\\mathrm{I}$ solid electrolyte materials.8,10,13,30 Doping lithium halides is a highly effective method in the design of solid electrolyte to simultaneously achieve improved ionic conductivity and Li metal stability.30,48,49 \n\nIn addition, the properties of the decomposition interphases significantly affect the performance of all-solid-state Li-ion batteries. The decomposition interphases with electronic conductivity may enable the continuous decomposition of the solid electrolyte during the cycling of the batteries. For example, a recent experimental study12 has identified that the reduction and oxidation products of the LGPS can be reversibly cycled. Therefore, the interphases formed due to the decomposition of the solid electrolyte may effectively become a part of active electrode materials of the battery. Such decomposition of the solid electrolyte materials during the cycling of the battery may cause degradations of the interfaces, leading to high interfacial resistance, low coulombic efficiency, and poor reversibility, which are major limiting factors in the performance of all-solid-state Li-ion batteries. While the good electronic insulation of the decomposition products are preferred to achieve good stability and low thickness of the interphases, the high Li ionic conductivity is important for achieving low interfacial resistance. For example, $\\mathrm{Li}_{3}\\mathrm{N}$ and $\\mathrm{Li}_{3}\\mathrm{P}$ formed at the LiPON−Li interface are phases with high Li ionic conductivity,50,51 which may explain the good interfacial conductance for LiPON−Li interface. \n\nHowever, the properties of the decomposition interphases may not always be as desired, since these critical interfacial properties are determined by the spontaneous decomposition of the solid electrolytes and electrode materials.16 The undesired electronic conductivity of the decomposition products may cause continuous decompositions of the solid electrolyte materials, since the electronic insulation of the decomposition interphases is essential in stabilizing the solid electrolyte. The engineering of the interface, such as the application of artificial coating layer, is a demonstrated method for the interfacial protection and to reduce interfacial resistance if the spontaneously formed SEI layers have unsatisfactory properties (e.g., high electronic conductivity and low ${\\mathrm{Li}}^{+}$ conductivity). Our calculation results showed that the coating layer materials passivate the solid electrolyte against the oxidation at high voltages. The outstanding stability of the coating layer against both solid electrolyte and electrode also impedes the mutual diffusion of non-Li elements, such as Co and $s,$ at the interface, which is a known problem for the degradation of interfaces between the sulfide electrolyte and $\\mathrm{LiCoO}_{2}$ .16 Furthermore, the coating layer artificially applied through thin film deposition is as thin as a few nanometers,38,42 while the interphase layer formed by the spontaneous decomposition can be as thick as $100\\ \\mathrm{nm}.^{\\cdot16,42,45}$ The thinner coating layer of less than $10\\ \\mathrm{~nm}$ yields significantly lower interfacial resistance.16,42 In addition, as the applied coating layer bridges the differences of Li chemical potential between the solid electrolyte and the cathode material, the formation of space-charge layers is mitigated40 to reduce the interfacial resistance. Therefore, applying artificial coating layer provides multiple advantages compared to the interphases formed by the spontaneous decompositions. The development of materials processing techniques to engineer the interphases is critical for improving the performance of all-solid-state Li-ion batteries. \n\n# 5. CONCLUSIONS \n\nOur first-principles calculation results indicate that most solid electrolyte materials have limited electrochemical window in contrast to the widely held perception about the outstanding stability of the solid electrolyte materials. Most solid electrolyte materials are not thermodynamically stable against Li metal and are reduced and oxidized at low and high potentials, respectively. Sulfide-based solid electrolytes have significantly narrower electrochemical window than the oxide-based solid electrolytes. Our calculation results show that the good stability of the solid electrolyte materials is not thermodynamically intrinsic but is rather originated from the kinetic stabilization. This kinetic stabilization is achieved due to the sluggish kinetics of the decomposition reactions and the decomposition interphases with poor electronic transport similar to the SEIs. We illustrated the stabilization mechanisms of the decomposition interphases, which passivate the solid electrolytes by mitigating extreme Li chemical potential from the electrodes. Our results suggest that the decomposition interphases of the solid electrolyte and the engineering of the interface are critical for the performance of all-solid-state Li-ion batteries. The interphases with good electronic insulation and high Li ionic conductivity are preferred to achieve an interface with good stability and low resistance. The application of artificial coating layers is a promising method for the stabilizing interfaces and for reducing interfacial resistance. Our study demonstrated the computation scheme to evaluate the electrochemical stability and the decomposition interphases of solid electrolyte materials and provided the fundamental understanding to guide the future design of solid electrolytes and interphases in all-solidstate Li-ion batteries. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsami.5b07517. \n\nDescriptions about the solid electrolyte materials investigated in the computation and the calculated phase equilibria for the lithiation and delithiation of solid electrolyte and coating materials (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author $^{*}\\mathrm{E}$ -mail: yfmo@umd.edu. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nWe thank Prof. Chunsheng Wang and Fudong Han for helpful discussions. This work was supported by U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, under Award No. DE-EE0006860. This research used computational facilities from the University of Maryland supercomputing resources and from the Extreme Science and Engineering Discovery Environment (XSEDE) supported by National Science Foundation Award No. TG-DMR130142. \n\n# REFERENCES \n\n(1) Kamaya, N.; Homma, K.; Yamakawa, Y.; Hirayama, M.; Kanno, R.; Yonemura, M.; Kamiyama, T.; Kato, Y.; Hama, S.; Kawamoto, K.; Mitsui, A. A Lithium Superionic Conductor. Nat. Mater. 2011, 10, 682−686. (2) Takada, K. Progress and Prospective of Solid-State Lithium Batteries. Acta Mater. 2013, 61, 759−770. (3) Seino, Y.; Ota, T.; Takada, K.; Hayashi, A.; Tatsumisago, M. A Sulphide Lithium Super Ion Conductor Is Superior to Liquid Ion Conductors for Use in Rechargeable Batteries. Energy Environ. Sci. 2014, 7, 627−631. (4) Yamane, H.; Shibata, M.; Shimane, Y.; Junke, T.; Seino, Y.; Adams, S.; Minami, K.; Hayashi, A.; Tatsumisago, M. Crystal Structure of a Superionic Conductor, Li7P3S11. Solid State Ionics 2007, 178, 1163−1167. (5) Thangadurai, V.; Pinzaru, D.; Narayanan, S.; Baral, A. K. Fast Solid-State Li Ion Conducting Garnet-Type Structure Metal Oxides for Energy Storage. J. Phys. Chem. Lett. 2015, 6, 292−299. (6) Li, J.; Baggetto, L.; Martha, S. K.; Veith, G. M.; Nanda, J.; Liang, C.; Dudney, N. J. An Artificial Solid Electrolyte Interphase Enables the Use of a LiNi0.5Mn1.5O4 5 V Cathode with Conventional Electrolytes. Adv. Energy Mater. 2013, 3, 1275−1278. (7) Li, J.; Ma, C.; Chi, M.; Liang, C.; Dudney, N. J. Solid Electrolyte: The Key for High-Voltage Lithium Batteries. Adv. Energy Mater. 2015, 5, 1401408. (8) Liu, Z.; Fu, W.; Payzant, E. A.; Yu, X.; Wu, Z.; Dudney, N. J.; Kiggans, J.; Hong, K.; Rondinone, A. J.; Liang, C. Anomalous High Ionic Conductivity of Nanoporous Beta-Li3PS4. J. Am. Chem. Soc. 2013, 135, 975−978. \n\n(9) Thangadurai, V.; Weppner, W. Li6ALa2Ta2O12 $\\mathbf{\\Psi}_{\\mathbf{a}}^{\\prime}=S\\mathbf{r}_{i}$ , Ba): Novel Garnet-Like Oxides for Fast Lithium Ion Conduction. Adv. Funct. Mater. 2005, 15, 107−112. \n(10) Yu, X.; Bates, J. B.; Jellison, G. E.; Hart, F. X. A Stable Thin - Film Lithium Electrolyte: Lithium Phosphorus Oxynitride. J. Electrochem. Soc. 1997, 144, 524−532. \n(11) Mo, Y.; Ong, S. P.; Ceder, G. First Principles Study of the Li10GeP2S12 Lithium Super Ionic Conductor Material. Chem. Mater. 2012, 24, 15−17. \n(12) Han, F.; Gao, T.; Zhu, Y.; Gaskell, K. J.; Wang, C. A Battery Made from a Single Material. Adv. Mater. 2015, 27, 3473−3483. (13) Schwöbel, A.; Hausbrand, R.; Jaegermann, W. Interface Reactions between LiPON and Lithium Studied by in-Situ X-Ray Photoemission. Solid State Ionics 2015, 273, 51−54. \n(14) Wenzel, S.; Leichtweiss, T.; Krüger, D.; Sann, J.; Janek, J. Interphase Formation on Lithium Solid Electrolytesan in Situ Approach to Study Interfacial Reactions by Photoelectron Spectroscopy. Solid State Ionics 2015, 278, 98−105. \n(15) Hartmann, P.; Leichtweiss, T.; Busche, M. R.; Schneider, M.; Reich, M.; Sann, J.; Adelhelm, P.; Janek, J. Degradation of NASICONType Materials in Contact with Lithium Metal: Formation of Mixed Conducting Interphases (MCI) on Solid Electrolytes. J. Phys. Chem. C 2013, 117, 21064−21074. \n(16) Sakuda, A.; Hayashi, A.; Tatsumisago, M. Interfacial Observation between LiCoO2 Electrode and Li2S−P2S5 Solid Electrolytes of All-Solid-State Lithium Secondary Batteries Using Transmission Electron Microscopy. Chem. Mater. 2010, 22, 949−956. (17) Jain, A.; Hautier, G.; Moore, C. J.; Ping Ong, S.; Fischer, C. C.; Mueller, T.; Persson, K. A.; Ceder, G. A High-Throughput Infrastructure for Density Functional Theory Calculations. Comput. Mater. Sci. 2011, 50, 2295−2310. \n(18) Wang, L.; Maxisch, T.; Ceder, G. Oxidation Energies of Transition Metal Oxides within the $\\mathbf{GGA+U}$ Framework. Phys. Rev. B: Condens. Matter Mater. Phys. 2006, 73, 195107. \n(19) Jain, A.; Hautier, G.; Ong, S. P.; Moore, C. J.; Fischer, C. C.; Persson, K. A.; Ceder, G. Formation Enthalpies by Mixing GGA and $\\mathbf{G}\\mathbf{G}\\mathbf{A}{+}\\mathbf{U}$ Calculations. Phys. Rev. B: Condens. Matter Mater. Phys. 2011, 84, 045115. \n(20) Jain, A.; Ong, S. P.; Hautier, G.; Chen, W.; Richards, W. D.; Dacek, S.; Cholia, S.; Gunter, D.; Skinner, D.; Ceder, G.; Persson, K. A. Commentary: The Materials Project: A Materials Genome Approach to Accelerating Materials Innovation. APL Mater. 2013, 1, 011002. \n(21) Ong, S. P.; Wang, L.; Kang, B.; Ceder, G. Li−Fe−P−O2 Phase Diagram from First Principles Calculations. Chem. Mater. 2008, 20, 1798−1807. \n(22) Ong, S. P.; Richards, W. D.; Jain, A.; Hautier, G.; Kocher, M.; Cholia, S.; Gunter, D.; Chevrier, V. L.; Persson, K. A.; Ceder, G. Python Materials Genomics (Pymatgen): A Robust, Open-Source Python Library for Materials Analysis. Comput. Mater. Sci. 2013, 68, 314−319. \n(23) Ong, S. P.; Mo, Y.; Richards, W. D.; Miara, L.; Lee, H. S.; Ceder, G. Phase Stability, Electrochemical Stability and Ionic Conductivity of the $\\mathrm{Li}_{10\\pm1}\\mathrm{MP}_{2}\\mathrm{X}_{12}$ ( $\\mathbf{\\tilde{M}}=\\mathbf{Ge},$ , Si, Sn, Al or ${\\bf P}_{i}$ and $X=\\mathrm{{O}}$ , S or Se) Family of Superionic Conductors. Energy Environ. Sci. 2013, 6, 148− 156. \n(24) Chen, C. H.; Amine, K. Ionic Conductivity, Lithium Insertion and Extraction of Lanthanum Lithium Titanate. Solid State Ionics 2001, 144, 51−57. \n(25) Stramare, S.; Thangadurai, V.; Weppner, W. Lithium Lanthanum Titanates: A Review. Chem. Mater. 2003, 15, 3974−3990. (26) Feng, J. K.; Lu, L.; Lai, M. O. Lithium Storage Capability of Lithium Ion Conductor Li1.5Al0.5Ge1.5(PO4)3. J. Alloys Compd. 2010, 501, 255−258. \n(27) Alpen, U. v.; Bell, M. F.; Wichelhaus, W.; Cheung, K. Y.; Dudley, G. J. Ionic Conductivity of Li14Zn(GeO4)4 (LISICON). Electrochim. Acta 1978, 23, 1395−1397. \n(28) Knauth, P. Inorganic Solid Li Ion Conductors: An Overview. Solid State Ionics 2009, 180, 911−916. (29) West, W. C.; Whitacre, J. F.; Lim, J. R. Chemical Stability Enhancement of Lithium Conducting Solid Electrolyte Plates Using Sputtered LiPON Thin Films. J. Power Sources 2004, 126, 134−138. (30) Rangasamy, E.; Liu, Z.; Gobet, M.; Pilar, K.; Sahu, G.; Zhou, W.; Wu, H.; Greenbaum, S.; Liang, C. An Iodide-Based Li7P2S8I Superionic Conductor. J. Am. Chem. Soc. 2015, 137, 1384−1387. (31) Lepley, N. D.; Holzwarth, N. A. W.; Du, Y. A. Structures, $\\mathrm{Li}+$ Mobilities, and Interfacial Properties of Solid Electrolytes Li3PS4 and Li3PO4 from First Principles. Phys. Rev. B: Condens. Matter Mater. Phys. 2013, 88, 104103. \n(32) Leung, K.; Leenheer, A. How Voltage Drops Are Manifested by Lithium Ion Configurations at Interfaces and in Thin Films on Battery Electrodes. J. Phys. Chem. C 2015, 119, 10234−10246. \n(33) Haruyama, J.; Sodeyama, K.; Han, L.; Takada, K.; Tateyama, Y. Space−Charge Layer Effect at Interface between Oxide Cathode and Sulfide Electrolyte in All-Solid-State Lithium-Ion Battery. Chem. Mater. 2014, 26, 4248−4255. \n(34) Weppner, W., Fundamental Aspects of Electrochemical, Chemical and Electrostatic Potentials in Lithium Batteries. In Materials for Lithium-Ion Batteries; Julien, C., Stoynov, Z., Eds.; Springer Netherlands: Dordrecht, The Netherlands, 2000; Chapter 20, pp 401− 412. \n(35) Kotobuki, M.; Munakata, H.; Kanamura, K.; Sato, Y.; Yoshida, T. Compatibility of Li7La3Zr2O12 Solid Electrolyte to All-Solid-State Battery Using Li Metal Anode. J. Electrochem. Soc. 2010, 157, A1076− A1079. \n(36) Wolfenstine, J.; Allen, J. L.; Read, J.; Sakamoto, J. Chemical Stability of Cubic Li7La3Zr2O12 with Molten Lithium at Elevated Temperature. J. Mater. Sci. 2013, 48, 5846−5851. \n(37) McCloskey, B. D.; Scheffler, R.; Speidel, A.; Girishkumar, G.; Luntz, A. C. On the Mechanism of Nonaqueous Li−O2 Electrochemistry on C and Its Kinetic Overpotentials: Some Implications for Li−Air Batteries. J. Phys. Chem. C 2012, 116, 23897−23905. \n(38) Ohta, N.; Takada, K.; Zhang, L.; Ma, R.; Osada, M.; Sasaki, T. Enhancement of the High-Rate Capability of Solid-State Lithium Batteries by Nanoscale Interfacial Modification. Adv. Mater. 2006, 18, 2226−2229. \n(39) Kitaura, H.; Hayashi, A.; Tadanaga, K.; Tatsumisago, M. Improvement of Electrochemical Performance of All-Solid-State Lithium Secondary Batteries by Surface Modification of LiMn2O4 Positive Electrode. Solid State Ionics 2011, 192, 304−307. \n(40) Takada, K.; Ohta, N.; Zhang, L.; Fukuda, K.; Sakaguchi, I.; Ma, R.; Osada, M.; Sasaki, T. Interfacial Modification for High-Power Solid-State Lithium Batteries. Solid State Ionics 2008, 179, 1333−1337. (41) Ohta, N.; Takada, K.; Sakaguchi, I.; Zhang, L.; Ma, R.; Fukuda, K.; Osada, M.; Sasaki, T. LiNbO3-Coated LiCoO2 as Cathode Material for All Solid-State Lithium Secondary Batteries. Electrochem. Commun. 2007, 9, 1486−1490. \n(42) Kato, T.; Hamanaka, T.; Yamamoto, ${\\mathrm{K}}.{\\mathrm{}}$ Hirayama, T.; Sagane, F.; Motoyama, M.; Iriyama, Y. In-Situ Li7La3Zr2O12/LiCoO2 Interface Modification for Advanced All-Solid-State Battery. J. Power Sources 2014, 260, 292−298. \n(43) Sakuda, A.; Kitaura, H.; Hayashi, A.; Tadanaga, K.; Tatsumisago, M. Improvement of High-Rate Performance of All-Solid-State Lithium Secondary Batteries Using LiCoO2 Coated with Li2O−SiO2 Glasses. Electrochem. Solid-State Lett. 2008, 11, A1−A3. \n(44) Jin, Y.; Li, N.; Chen, C. H.; Wei, S. $\\mathsf{Q}.$ Electrochemical Characterizations of Commercial LiCoO2 Powders with Surface Modified by Li3PO4 Nanoparticles. Electrochem. Solid-State Lett. 2006, 9, A273−A276. \n(45) Kim, K. H.; Iriyama, Y.; Yamamoto, K.; Kumazaki, S.; Asaka, T.; Tanabe, K.; Fisher, C. A. J.; Hirayama, T.; Murugan, R.; Ogumi, Z. Characterization of the Interface between LiCoO2 and Li7La3Zr2O12 in an All-Solid-State Rechargeable Lithium Battery. J. Power Sources 2011, 196, 764−767. \n(46) Visco, S.; Nimon, V.; Petrov, A.; Pridatko, K.; Goncharenko, N.; Nimon, E.; De Jonghe, L.; Volfkovich, Y.; Bograchev, D. Aqueous and Nonaqueous Lithium-Air Batteries Enabled by Water-Stable Lithium Metal Electrodes. J. Solid State Electrochem. 2014, 18, 1443−1456. (47) Goodenough, J. B.; Kim, Y. Challenges for Rechargeable Li Batteries. Chem. Mater. 2010, 22, 587−603. \n(48) Rangasamy, E.; Li, J.; Sahu, G.; Dudney, N.; Liang, C. Pushing the Theoretical Limit of Li-CFx Batteries: A Tale of Bifunctional Electrolyte. J. Am. Chem. Soc. 2014, 136, 6874−6877. \n(49) Deiseroth, H.-J.; Kong, S.-T.; Eckert, H.; Vannahme, J.; Reiner, C.; Zaiß, T.; Schlosser, M. Li6PS5X: A Class of Crystalline Li-Rich Solids with an Unusually High $\\mathrm{Li^{+}}$ Mobility. Angew. Chem., Int. Ed. 2008, 47, 755−758. \n(50) Alpen, U. v.; Rabenau, A.; Talat, G. H. Ionic Conductivity in Li3N Single Crystals. Appl. Phys. Lett. 1977, 30, 621−623. \n(51) Nazri, G. Preparation, Structure and Ionic Conductivity of Lithium Phosphide. Solid State Ionics 1989, 34, 97−102. " + }, + { + "id": "10.1063_1.4908244", + "DOI": "10.1063/1.4908244", + "DOI Link": "http://dx.doi.org/10.1063/1.4908244", + "Relative Dir Path": "mds/10.1063_1.4908244", + "Article Title": "Characterization of Lorenz number with Seebeck coefficient measurement", + "Authors": "Kim, HS; Gibbs, ZM; Tang, YL; Wang, H; Snyder, GJ", + "Source Title": "APL MATERIALS", + "Abstract": "In analyzing zT improvements due to lattice thermal conductivity (kappa(L)) reduction, electrical conductivity (sigma) and total thermal conductivity (kappa(Total)) are often used to estimate the electronic component of the thermal conductivity (kappa(E)) and in turn kappa(L) from kappa(L) = similar to kappa(Total) - L sigma T. TheWiedemann-Franz law, kappa(E) = L sigma T, where L is Lorenz number, is widely used to estimate kappa(E) from sigma measurements. It is a common practice to treat L as a universal factor with 2.44 x 10(-8) W Omega K-2 (degenerate limit). However, significant deviations from the degenerate limit (approximately 40% or more for Kane bands) are known to occur for non-degenerate semiconductors where L converges to 1.5 x 10(-8) W Omega K-2 for acoustic phonon scattering. The decrease in L is correlated with an increase in thermopower (absolute value of Seebeck coefficient (S)). Thus, a first order correction to the degenerate limit of L can be based on the measured thermopower, vertical bar S vertical bar, independent of temperature or doping. We propose the equation: L = 1.5 + exp [ -vertical bar S vertical bar/116] (where L is in 10(-8) W Omega K-2 and S in mu V/K) as a satisfactory approximation for L. This equation is accurate within 5% for single parabolic band/acoustic phonon scattering assumption and within 20% for PbSe, PbS, PbTe, Si0.8Ge0.2 where more complexity is introduced, such as non-parabolic Kane bands, multiple bands, and/or alternate scattering mechanisms. The use of this equation for L rather than a constant value (when detailed band structure and scattering mechanism is not known) will significantly improve the estimation of lattice thermal conductivity. (C) 2015 Author(s).", + "Times Cited, WoS Core": 1564, + "Times Cited, All Databases": 1632, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000353828400013", + "Markdown": "# Characterization of Lorenz number with Seebeck coefficient measurement \n\nHyun-Sik Kim, Zachary M. Gibbs, Yinglu Tang, Heng Wang, and G. Jeffrey Snyder \n\nCitation: APL Materials 3, 041506 (2015); doi: 10.1063/1.4908244 \nView online: http://dx.doi.org/10.1063/1.4908244 \nView Table of Contents: http://scitation.aip.org/content/aip/journal/aplmater/3/4?ver=pdfcov \nPublished by the AIP Publishing \nArticles you may be interested in \nTowards a predictive route for selection of doping elements for the thermoelectric compound PbTe from first \nprinciples \nJ. Appl. Phys. 117, 175102 (2015); 10.1063/1.4919425 \nInterplay of chemical expansion, Yb valence, and low temperature thermoelectricity in the YbCu2Si2−xGex \nsolid solution \nJ. Appl. Phys. 117, 135101 (2015); 10.1063/1.4916786 \n\nComputational modeling and analysis of thermoelectric properties of nanoporous silicon J. Appl. Phys. 115, 124316 (2014); 10.1063/1.4869734 \n\nStrain effect analysis on the thermoelectric figure of merit in n-type Si/Ge nanocomposites J. Appl. Phys. 111, 054318 (2012); 10.1063/1.3693307 \n\nHigh thermoelectric power factor in alloys based on CoSi Appl. Phys. Lett. 94, 022115 (2009); 10.1063/1.3072799 \n\n# Characterization of Lorenz number with Seebeck coefficient measurement \n\nHyun-Sik Kim,1,2 Zachary M. Gibbs,3 Yinglu Tang,1 Heng Wang,1 \nand G. Jeffrey Snyder1,a \n1Department of Materials Science, California Institute of Technology, Pasadena, \nCalifornia 91125, USA \n2Materials Research Center, Samsung Advanced Institute of Technology, Samsung \nElectronics, Suwon 443-803, South Korea \n3Division of Chemistry and Chemical Engineering, California Institute of Technology, \nPasadena, California 91125, USA \n\n(Received 31 December 2014; accepted 1 February 2015; published online 18 February 2015) \n\nIn analyzing $z T$ improvements due to lattice thermal conductivity $(\\kappa_{L})$ reduction, electrical conductivity $(\\sigma)$ and total thermal conductivity $(\\kappa_{T o t a l})$ are often used to estimate the electronic component of the thermal conductivity $(\\kappa_{E})$ and in turn $\\kappa_{L}$ from $\\kappa_{L}=\\sim\\kappa_{T o t a l}-L\\sigma T$ . The Wiedemann-Franz law, $\\kappa_{E}=L\\sigma T$ , where $L$ is Lorenz number, is widely used to estimate $\\kappa_{E}$ from $\\sigma$ measurements. It is a common practice to treat $L$ as a universal factor with $2.44\\times10^{-8}\\mathrm{W}\\Omega\\mathrm{K}^{-2}$ (degenerate limit). However, significant deviations from the degenerate limit (approximately $40\\%$ or more for Kane bands) are known to occur for non-degenerate semiconductors where $L$ converges to $1.5\\times10^{-8}\\mathrm{W}\\Omega\\mathrm{K}^{-2}$ for acoustic phonon scattering. The decrease in $L$ is correlated with an increase in thermopower (absolute value of Seebeck coefficient (S)). Thus, a first order correction to the degenerate limit of $L$ can be based on the measured thermopower, $|S|$ , independent of temperature or doping. We propose the equation: $\\begin{array}{r}{L=1.5+\\exp\\left[-\\frac{\\left|S\\right|}{116}\\right]}\\end{array}$ (where $L$ is in $10^{-8}\\mathrm{W}\\Omega\\mathrm{K}^{-2}$ and $s$ in $\\upmu\\mathrm{V/K})$ ) as a satisfactory approximation for $\\bar{L}$ . This equation is accurate within $5\\%$ for single parabolic band/acoustic phonon scattering assumption and within $20\\%$ for PbSe, PbS, PbTe, $\\mathrm{Si}_{0.8}\\mathrm{Ge}_{0.2}$ where more complexity is introduced, such as non-parabolic Kane bands, multiple bands, and/or alternate scattering mechanisms. The use of this equation for $L$ rather than a constant value (when detailed band structure and scattering mechanism is not known) will significantly improve the estimation of lattice thermal conductivity. $\\circleddash$ 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License. [http://dx.doi.org/10.1063/1.4908244] \n\nA semiconductor with large Seebeck coefficient, high electrical conductivity, and low thermal conductivity is a good candidate for a thermoelectric material. The thermoelectric material’s maximum efficiency is determined by its figure of merit $\\begin{array}{r}{z T=\\frac{S^{2}\\sigma T}{\\kappa_{E}+\\kappa_{L}}}\\end{array}$ , where $T,S,\\sigma,\\kappa_{E}$ , and $\\kappa_{L}$ are the temperature, Seebeck coefficient, electrical conductivity, and the electronic and lattice contributions to the thermal conductivity, respectively. Because the charge carriers (electrons in $n$ -type or holes in $p$ -type semiconductors) transport both heat and charge, $\\kappa_{E}$ is commonly estimated using the measured $\\sigma$ using the Wiedemann-Franz law: $\\kappa_{E}=L\\sigma T$ , where $L$ is the Lorenz number. Once $\\kappa_{E}$ is known, $\\kappa_{L}$ is computed by subtracting the $\\kappa_{E}$ from the total thermal conductivity, $K_{T o t a l}=\\kappa_{E}+\\kappa_{L}$ . For this method, the bipolar thermal conductivity $\\left(\\kappa_{B}\\right)$ will also be included which can be written $\\kappa_{B}+\\kappa_{L}=\\kappa_{T o t a l}-L\\sigma T$ . \n\nSince a high $z T$ requires low $\\kappa_{T o t a l}$ but high $\\sigma$ simultaneously, one of the more popular routes towards improving $z T$ has been to reduce $\\kappa_{L}$ .1 However, depending on the value of $L$ , which maps from $\\sigma$ to $\\kappa_{E}$ , the resulting $\\kappa_{L}$ can often be misleading. For instance, in the case of lanthanum telluride, incautious determination of $L$ can even cause $\\kappa_{L}$ to be negative, which is not physical.2 Therefore, careful evaluation of $L$ is critical in characterizing enhancements in $z T$ due to $\\kappa_{L}$ reduction. \n\nFor most metals, where charge carriers behave like free-electrons, $L$ converges to $\\begin{array}{r}{\\frac{\\pi^{2}}{3}\\left(\\frac{k_{B}}{e}\\right)^{2}}\\end{array}$ $=2.44\\times10^{-8}\\ \\mathrm{W}\\Omega\\mathrm{K}^{-2}$ (degenerate limit). Although some heavily doped semiconductor thermoelectric materials have an $L$ very close to the degenerate limit, properly optimized materials often have charge carrier concentrations between the lightly doped (non-degenerate) and heavily doped (degenerate) regions3 $(\\xi_{o p t i m u m}$ is near the band edge where $\\xi$ is the electronic chemical potential) which can result in errors of up to ${\\sim}40\\%$ .4 \n\nDirect measurement of $L^{5}$ requires high mobility—typically beyond that attainable at the temperatures of interest $(>300\\mathrm{K})$ . Thus, $L$ is typically estimated either as a constant $(2.44\\times10^{-8}\\mathrm{W}\\Omega\\mathrm{K}^{-2})$ or by applying a transport model—such as the single parabolic band (SPB) model obtained by solving the Boltzmann transport equations—to experimental data. \n\nFor example, Larsen et al. proposed an approximate analytical solution of $L$ based on the SPB model as a function of carrier concentration $(n)$ and $(m^{*}T)^{-3/2}$ (where $m^{*}$ is the effective mass) along with various sets of parameters for distinct carrier scattering mechanisms.6 However, when the Hall carrier concentration, $n_{H}$ , of a material is not available, the use of the approximate solution by Larsen is not possible. It can be shown that for the SPB model with acoustic phonon scattering (SPB-APS), both $L$ and $s$ are parametric functions of only the reduced chemical potential $(\\eta=\\xi/k_{B}T$ , where $k_{B}$ is Boltzmann constant); thus, no explicit knowledge of temperature $(T)$ , carrier concentration $(n)$ , or effective mass $(m^{*})$ is required to relate them.7 We have utilized this correlation between $L$ and measured $s$ to estimate $\\kappa_{L}$ for a few known thermoelectric materials including: PbTe,8–10 Zintl materials,11–13 co-doped $\\mathrm{FeV_{0.6}N b_{0.4}S b}$ Half Heusler,14 $\\mathrm{La}_{3-\\mathrm{x}}\\mathrm{Te}_{4}$ ,2 resulting in much more satisfactory values for $\\kappa_{L}$ than the degenerate limit result $(L=2.44\\times10^{-8}\\mathrm{W}\\Omega\\mathrm{K}^{-2})$ would have. \n\nWhile the SPB model works well to estimate $L$ , a transcendental set of equations is needed to solve for $L$ in terms of $S$ —requiring a numerical solution. Considering that the typical measurement uncertainty for $\\kappa_{T o t a l}$ is $10\\%$ and that SPB-APS is only an approximation, a much simpler equation would supply sufficient accuracy. Here, we propose the equation \n\n$$\nL=1.5+\\exp\\left[-{\\frac{\\left|S\\right|}{116}}\\right]\n$$ \n\n(where $L$ is in $10^{-8}\\mathrm{W}\\Omega\\mathrm{K}^{-2}$ and $s$ in $\\mu\\mathrm{V/K},$ ) as a satisfactory approximation for $L$ . \n\nEquation (1) allows for a facile estimation of $L$ from an experimental $S$ only without requiring a numerical solution. We characterize the effectiveness of this estimate for $L$ using some experimental data from relevant thermoelectric materials (PbSe,15 PbS,16 PbTe,17,18 Zintl material $\\left(\\mathrm{Sr}_{3}\\mathrm{GaSb}_{3}\\right)$ ,11 Half Heusler (ZrNiSn),19 and $\\mathrm{Si}_{0.8}\\mathrm{Ge}_{0.2}{}^{20\\cdot},$ . \n\nFor a single parabolic band, $L$ and $S$ are both functions of reduced chemical potential $(\\eta)$ and carrier scattering factor $(\\uplambda)$ only \n\n$$\nL=\\left(\\frac{k_{B}}{e}\\right)^{2}\\frac{\\left(1+\\lambda\\right)\\left(3+\\lambda\\right)F_{\\lambda}\\left(\\eta\\right)F_{\\lambda+2}\\left(\\eta\\right)-\\left(2+\\lambda\\right)^{2}F_{\\lambda+1}\\left(\\eta\\right)^{2}}{\\left(1+\\lambda\\right)^{2}F_{\\lambda}\\left(\\eta\\right)^{2}},}\\\\ {S=\\frac{k_{B}}{e}\\left(\\frac{\\left(2+\\lambda\\right)F_{\\lambda+1}\\left(\\eta\\right)}{\\left(1+\\lambda\\right)F_{\\lambda}\\left(\\eta\\right)}-\\eta\\right).}\\end{array}\n$$ \n\nWhere $F_{j}\\left(\\eta\\right)$ represents the Fermi integral, \n\n$$\nF_{j}\\left(\\eta\\right)=\\int_{0}^{\\infty}{\\frac{\\epsilon^{j}d\\epsilon}{1+\\mathrm{Exp}\\left[\\epsilon-\\eta\\right]}}.\n$$ \n\nBy assuming that the carrier relaxation time is limited by acoustic phonon scattering (one of the most relevant scattering mechanisms for thermoelectric materials above room temperature17,21), Eqs. (2) and (3) can be solved numerically for $L$ and the corresponding $S$ as shown in Fig. 1 along with the proposed approximation (Eq. (1)). \n\n![](images/4533120a46c986c4d1ff6701bcc582b7feeb716ca6eb5cfe941b7e7a6ffc98ce.jpg) \nFIG. 1. Thermopower dependent Lorenz number calculated by the SPB model with APS and Eq. (1). For comparison, the degenerate limit of $2.44\\times\\mathrm{10^{-8}W}\\Omega\\mathrm{K}^{-2}$ is also presented in a red dashed line. \n\nAccording to the Fig. 1, the degenerate limit of $L$ $(2.44\\times10^{-8}\\ \\mathrm{W}\\Omega\\mathrm{K}^{-2})$ ) is valid with errors less than $10\\%$ for materials whose thermopower is smaller than $50~\\mu\\mathrm{V/K}$ (highly degenerate). In contrast, if the thermopower is large, the discrepancy with the degenerate limit can be up to $40\\%$ . \n\nTo decide an appropriate value of $L$ with a known $s$ easily, rather than graphically extracting it from Fig. 1, Eq. (1) can be used to quickly estimate $L$ , given a measured thermopower. Equation (1) is accurate within $5\\%$ for single parabolic band where acoustic phonon scattering is dominant scattering mechanism when $|S|>{\\sim}10~\\mu\\mathrm{V/K}$ . For $\\vert S\\vert<10~\\mu\\mathrm{V/K}$ , while the SPB model converges to the degenerate limit, Eq. (1) increases exponentially, thus reducing the accuracy of the Eq. (1). Although estimation of $L$ with an accuracy within $0.5\\%$ for SPB-APS is possible, this requires an approximate equation more complex than Eq. (1).22 \n\nExceptions are known where $L$ has been found to be outside the uncertainty described above for SPB-APS which are presented in Fig. 2 and Table I.22 These exceptions typically involve either non-parabolic band structures (PbTe, PbSe, and PbS) or alternative scattering mechanisms (other than acoustic phonons). Narrow-gap semiconductors (lead chalcogenides, for example) are often better described by the non-parabolic Kane model which yields a different $\\eta$ dependence of $L$ and $s$ which depends on the non-parabolicity parameter: $\\begin{array}{r}{\\alpha=\\frac{k_{B}T}{E_{g}}}\\end{array}$ ( ${\\mathrm{~\\it~E}}_{g}$ is the gap between conduction and valence band).23,24 For well-studied lead chalcogenides (PbTe, PbSe, and $\\mathrm{Pb}\\mathrm{S}$ ), a reasonable range of $\\alpha$ is from 0.08 $(300~\\mathrm{K})$ to 0.16 (850 K).25 Figure 2 shows that $L$ is at most ${\\sim}26\\%$ lower than that of the SPB-APS and Eq. (1) results over the entire range of temperatures. In other words, $\\kappa_{L}$ estimates will maintain the order: $\\kappa_{L,d e g}<\\kappa_{L,S P B-A P S}<\\kappa_{L,S K B-A P S}$ with the largest errors being for the degenerate limit when applied in the non-degenerate case.22 \n\n![](images/5ce7ed9ef3d0c5be47c3bb0285c7fee0e6cf6abd6d86a994b81cfcba0254e983.jpg) \nFIG. 2. Thermopower dependent Lorenz number obtained from materials whose band structure and scattering assumptions are different from those assumed in SPB-APS along with Eq. (1) calculation. For comparison, the degenerate limit of $2.44\\times10^{-8}\\mathrm{W}\\Omega\\mathrm{K}^{-2}$ is also presented in a red dashed line. \n\nTABLE I. Estimated maximum error to Eq. (1) for $L$ with different band structure and scattering assumptions. \n\n\n
BandaScatteringbExamplesMaximum error (%)
PAPSr3Gao.93Zno.07Sb3114.4
2PAP+ⅡISio.8Geo.2207.5
KAPPbtTe0.98810.012119.7
KAP+POPb1.002Se0.998Bro.0021519.5
PbSD.9978Cl0.002 ZNiSno.99sb6.0 1919.4
KAP+PO+AL25.6
2K+PAPPbTe0.85Se0.151714.9
\n\naBand is the type and number of bands involved in evaluating $L$ . For instance, $\\mathrm{^{*}2K+P^{*}}$ means two non-parabolic Kane bands ${\\mathrm{(K)}}$ and a parabolic band (P). bScattering is the type of scattering mechanism assumed in estimating $L$ . AP, II, PO, and AL are acoustic phonon, ionized impurities, polar, and alloy scattering, respectively. For example, $\\ensuremath{{}^{\\mathrm{s}}\\mathrm{AP}}+\\ensuremath{\\mathrm{PO}}^{\\ensuremath{\\prime}}$ means that both acoustic phonon and polar scatterings are assumed in calculating $L$ . \n\nAlternative scattering mechanisms can also yield deviations from the SPB-APS. For example, when ionized impurity scattering dominates $(\\uplambda=2)$ , the $L$ actually increases with increasing $S$ ; however, this example is not particularly prevalent in materials which have high dielectric constants (including the lead chalcogenides)26 or at high temperatures. However, when the ionized impurity scattering and acoustic phonon scattering are both considered, the deviation from the SPB-APS is not significant $\\mathrm{\\mathrm{Si}}_{0.8}\\mathrm{Ge}_{0.2}$ in Table I)–although limited data is available. For $\\mathrm{ZrNiSn_{0.99}S b_{0.01}}$ (Table I), acoustic phonon scattering and two other scattering mechanisms (polar and alloy scatterings) are taken into account; these result in a larger deviation as the Seebeck becomes larger. At low temperatures $(<100\\mathrm{K})$ , as $s$ approaches zero, it is expected that $L$ converges to the degenerate limit regardless of carrier scattering mechanism7 and parabolicity of bands involved in transport.22 However, a pronounced inelastic electron-electron scattering due to high mobility of carriers decreases $L$ from the degenerate limit, even for strongly degenerate materials. In case of $n$ -type PbTe, $L$ at $100~\\mathrm{K}$ is approximately $40\\%$ lower than its value at $300\\mathrm{K}$ .24 \n\nMultiple band behavior (present in $p$ -type $\\mathrm{PbTe}_{0.85}\\mathrm{Se}_{0.15}$ and $n$ -type $\\mathrm{Si}_{0.8}\\mathrm{Ge}_{0.2}$ , Fig. 2) can also lead to deviations in the thermopower-dependence of the Lorenz number. In the case of PbTe, hole population of both the light and heavy bands yields a more complicated relationship between $L$ and S; it is not simply a parametric function of $\\eta$ and depends on the specific effective mass and mobility contributions from each band. \n\nOne last, prevalent source of error occurs because the Wiedemann-Franz law does not take the bipolar thermal conductivity into consideration. $\\kappa_{L}$ calculated from the difference between κTotal and $\\kappa_{E}$ does include varying portion of bipolar conduction with respect to temperature and band structure of materials (which can become important for lightly doped materials with narrow gaps at high temperatures27). \n\nAn equation for $L$ entirely in terms of the experimentally determined $S$ is proposed and found to be accurate (within $20\\%$ ) for most common band structures/scattering mechanisms found for thermoelectric materials. Use of this equation would make estimates of lattice thermal conductivity much more accurate without requiring additional measurement. Therefore, $z T$ improvement due to lattice thermal conductivity reduction can be calculated with much improved accuracy and access. \n\nThe authors would like to acknowledge funding from The Materials Project: supported by Department of Energy’s Basic Energy Sciences program under Grant No. EDCBEE, DOE Contract No. DE-AC02-05CH11231 and as part of the Solid-State Solar-Thermal Energy Conversion Center \n\n# (S3TEC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, and Basic Energy Sciences under Award No. DE-SC0001299. \n\n1 G. J. Snyder and E. S. Toberer, Nat. Mater. 7, 105 (2008). \n2 A. F. May, J. P. Fleurial, and G. J. Snyder, Phys. Rev. B 78, 125205 (2008). \n3 Y. Pei, H. Wang, and G. J. Snyder, Adv. Mater. 24, 6124 (2012). \n4 E. S. Toberer, L. L. Baranowski, and C. Dames, Annu. Rev. Mater. Res. 42, 179 (2012). \n5 K. Lukas, W. Liu, G. Joshi, M. Zebarjadi, M. Dresselhaus, Z. Ren, G. Chen, and C. Opeil, Phys. Rev. B 85, 205410 (2012). \n6 E. Flage-Larsen and $\\varnothing$ . Prytz, Appl. Phys. Lett. 99, 202108 (2011). \n7 A. F. May and G. J. Snyder, in Thermoelectrics and its Energy Harvesting, edited by D. M. Rowe (CRC Press, London, \n2012), Vol. 1 Chap. 11. \n8 Y. Pei, A. LaLonde, S. Iwanaga, and G. J. Snyder, Energy Environ. Sci. 4, 2085 (2011). \n9 Y. Pei, J. Lensch-Falk, E. S. Toberer, D. L. Medlin, and G. J. Snyder, Adv. Funct. Mater. 21, 241 (2011). \n10 Y. Pei, N. A. Heinz, A. Lalonde, and G. J. Snyder, Energy Environ. Sci. 4, 3640 (2011). \n11 A. Zevalkink, W. G. Zeier, G. Pomrehn, E. Schechtel, W. Tremel, and G. J. Snyder, Energy Environ. Sci. 5, 9121 (2012). \n12 A. F. May, J.-P. Fleurial, and G. J. Snyder, Chem. Mater. 22, 2995 (2010). \n13 A. Zevalkink, E. S. Toberer, W. G. Zeier, E. Flage-Larsen, and G. J. Snyder, Energy Environ. Sci. 4, 510 (2011). \n14 C. Fu, Y. Liu, H. Xie, X. Liu, X. Zhao, G. J. Snyder, J. Xie, and T. Zhu, J. Appl. Phys. 114, 134905 (2013). \n15 H. Wang, Y. Pei, A. D. Lalonde, and G. J. Snyder, Proc. Natl. Acad. Sci. U.S.A. 109, 9705 (2012). \n16 H. Wang, E. Schechtel, Y. Pei, and G. J. Snyder, Adv. Energy Mater. 3, 488 (2013). \n17 Y. Pei, X. Shi, A. LaLonde, H. Wang, L. Chen, and G. J. Snyder, Nature 473, 66 (2011). \n18 A. D. LaLonde, Y. Pei, and G. J. Snyder, Energy Environ. Sci. 4, 2090 (2011). \n19 H. Xie, H. Wang, C. Fu, Y. Liu, G. J. Snyder, X. Zhao, and T. Zhu, Sci. Rep. 4, 6888 (2014). \n20 C. B. Vining, J. Appl. Phys. 69, 331 (1991). \n21 C. Wood, Rep. Prog. Phys. 51, 459 (1988). \n22 See supplementary material at http://dx.doi.org/10.1063/1.4908244 for an estimation of L with an accuracy within \n$0.5\\%$ for SPB-APS; more details about Fig. 2; more details regarding the L for the non-parabolic band model; and \nnon-parabolicity parameter dependent L as S approaches zero. \n$^{23}\\mathrm{C}$ . M. Bhandari and D. M. Rowe, J. Phys. D: Appl. Phys. 18, 873 (1985). \n24 Y. I. Ravich, B. A. Efimova, and I. A. Smirnov, Semiconducting Lead Chalcogenides (Plenum Press, New York, 1970), Vol. \n299, p. 181. \n$^{25}\\mathrm{H}$ . Wang, Ph.D. thesis, California Institute of Technology, 2014. \n$^{26}\\mathrm{P}.$ Zhu, Y. Imai, Y. Isoda, Y. Shinohara, X. Jia, and G. Zou, Mater. Trans. 46, 2690 (2005). \n27 Z. M. Gibbs, H.-S. Kim, H. Wang, and G. J. Snyder, Appl. Phys. Lett. 106, 022112 (2015). " + }, + { + "id": "10.1038_ncomms9056", + "DOI": "10.1038/ncomms9056", + "DOI Link": "http://dx.doi.org/10.1038/ncomms9056", + "Relative Dir Path": "mds/10.1038_ncomms9056", + "Article Title": "Low-threshold amplified spontaneous emission and lasing from colloidal nullocrystals of caesium lead halide perovskites", + "Authors": "Yakunin, S; Protesescu, L; Krieg, F; Bodnarchuk, MI; Nedelcu, G; Humer, M; De Luca, G; Fiebig, M; Heiss, W; Kovalenko, MV", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Metal halide semiconductors with perovskite crystal structures have recently emerged as highly promising optoelectronic materials. Despite the recent surge of reports on microcrystalline, thin-film and bulk single-crystalline metal halides, very little is known about the photophysics of metal halides in the form of uniform, size-tunable nullocrystals. Here we report low-threshold amplified spontaneous emission and lasing from similar to 10nm monodisperse colloidal nullocrystals of caesium lead halide perovskites CsPbX3 (X = Cl, Br or I, or mixed Cl/Br and Br/I systems). We find that room-temperature optical amplification can be obtained in the entire visible spectral range (440-700 nm) with low pump thresholds down to 5 +/- 1 mu J cm(-2) and high values of modal net gain of at least 450 +/- 30 cm(-1). Two kinds of lasing modes are successfully observed: whispering-gallery-mode lasing using silica microspheres as high-finesse resonators, conformally coated with CsPbX3 nullocrystals and random lasing in films of CsPbX3 nullocrystals.", + "Times Cited, WoS Core": 1310, + "Times Cited, All Databases": 1406, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000360352600003", + "Markdown": "# Low-threshold amplified spontaneous emission and lasing from colloidal nanocrystals of caesium lead halide perovskites \n\nSergii Yakunin1,2, Loredana Protesescu1,2, Franziska Krieg1,2, Maryna I. Bodnarchuk1,2, Georgian Nedelcu1,2, Markus Humer3, Gabriele De Luca4, Manfred Fiebig4, Wolfgang Heiss3,5,6 & Maksym V. Kovalenko1,2 \n\nMetal halide semiconductors with perovskite crystal structures have recently emerged as highly promising optoelectronic materials. Despite the recent surge of reports on microcrystalline, thin-film and bulk single-crystalline metal halides, very little is known about the photophysics of metal halides in the form of uniform, size-tunable nanocrystals. Here we report low-threshold amplified spontaneous emission and lasing from ${\\sim}10$ nm monodisperse colloidal nanocrystals of caesium lead halide perovskites $\\mathsf{C s P b}\\mathsf{X}_{3}$ $\\mathsf{X}=\\mathsf{C l}$ , Br or I, or mixed Cl/Br and Br/I systems). We find that room-temperature optical amplification can be obtained in the entire visible spectral range $(440-700\\mathsf{n m}.$ ) with low pump thresholds down to $5\\pm1\\upmu\\mathrm{l}\\mathrm{cm}^{-2}$ and high values of modal net gain of at least $450\\pm30\\mathsf{c m}^{-1}$ . Two kinds of lasing modes are successfully observed: whispering-gallery-mode lasing using silica microspheres as high-finesse resonators, conformally coated with $\\mathsf{C s P b}\\mathsf{X}_{3}$ nanocrystals and random lasing in films of $\\mathsf{C s P b}\\mathsf{X}_{3}$ nanocrystals. \n\nReocuetsnt ydeianrgs hpatvoe sceteron cmuclhtiaprlae rreipstoircts fdemeotanl rhatlindge form of thin films, microcrystals and bulk single crystals1–11. In particular, hybrid organic–inorganic lead halide perovskites such as $\\mathrm{MAPbX}_{3}$ (where $\\mathrm{MA}=$ methyl ammonium and $\\mathrm{X=Cl}_{\\mathrm{\\i}}$ , Br or I, or mixed $\\mathrm{Cl/Br}$ and $\\mathrm{Br/I}$ systems) have shown great potential as both light-absorbing and light-emitting direct-bandgap solution-deposited semiconductors. As absorber layers, $\\mathrm{MAPb}{\\mathrm{X}}_{3}$ materials have enabled inexpensive solar cells with certified power conversion efficiencies of up to $20\\%$ (NREL efficiency chart, www.nrel.gov)12 and highly sensitive solutioncast photodetectors operating in the visible13, ultraviolet14 and X-ray15 spectra regions. Owing to their bright photoluminescence (PL), $\\mathrm{MAPb}{\\mathrm{X}}_{3}$ thin films and nanowires have been used in electrically driven light-emitting diodes16 and as optical gain media for lasing17–21. We have recently shown that similarly high optoelectronic quality is also accessible in fully inorganic $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ analogues, when these compounds are synthesized in the form of colloidal nanocrystals $(\\mathrm{NC}\\dot{\\mathsf{s}})^{22}$ . In particular, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs exhibit bright emission with PL quantum yields (QYs) reaching $90\\%$ and narrow emission linewidths of $70\\mathrm{-}100\\mathrm{meV}$ ( $12{-}40\\mathrm{nm}$ , for PL peaks from 410 to $700\\mathrm{nm}$ , correspondingly). Precise and continuous tuning of bandgap energies over the entire visible spectral region is achievable foremost via compositional control (mixed halide Cl/Br and $\\mathrm{Br/I}$ systems), but also through quantum-size effects. $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs appear to be largely free from mid-gap trap states, similar to their $\\mathrm{MAPb}{\\mathrm{X}}_{3}$ cousins23. Both molecular solutions of $\\mathrm{MAPb}{\\mathrm{X}}_{3}$ and colloidal solutions of $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs share the common feature of facile solution deposition on arbitrary substrates. Further, $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs are readily miscible with other optoelectronic materials (polymers, fullerenes and other nanomaterials) and feature surface-capping ligands for further adjustments of the electronic and optical properties, and solubility in various media. We also note that $\\mathrm{CsPbX}_{3}$ NCs are formed in the pure cubic perovskite phase, in which $\\mathrm{PbX}_{6}$ octahedra are three-dimensionally interconnected by corner-sharing. In contrast, their bulk counterparts exist exclusively in wider-bandgap one-dimensional orthorhombic phases at ambient conditions24–26. This disparity is most pronounced for red-emitting $\\mathrm{CsPbI}_{3}$ NCs that exhibit a narrow gap of down to $1.75\\mathrm{eV}$ , whereas the corresponding bulk material has a ca. 1 eV larger bandgap and is yellow-colored and non-luminescent. A key practical advantage of $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs is the facile access to the blue–green spectral region of $410{-}530\\mathrm{nm}$ via one-pot synthesis22. In comparison, common metal chalcogenide colloidal quantum dots such as CdSe NCs need to be extremely small ( $:\\leq5\\mathrm{nm})$ to emit in the blue–green, and as-synthesized they exhibit rather low PL QYs of $\\leq5\\%$ due to mid-gap trap states. In addition, they are chemically and photochemically unstable, and require coating with an epitaxial layer of a more chemically robust, wider-gap semiconductor, such as CdS. On the other hand, narrow emission linewidths of ca. $100\\mathrm{meV}$ , high PL QYs of up $90\\%$ and high photochemical stability have been achieved for Cd-chalcogenide NCs as the result of two decades of research efforts to precisely engineer core-shell morphologies with independent control of the core and shell compositions and thicknesses (for example, $\\mathrm{CdSe}_{\\mathrm{core}}/$ $\\mathrm{ZnCdS_{shell}}$ or ‘giant-shell’ $\\mathrm{CdSe}_{\\mathrm{core}}/\\mathrm{CdS}_{\\mathrm{shell}})^{27-30}$ and anisotropic CdSe–CdS dot-in-rod and platelet-like morphologies31,32. Overall, each of these two families of colloidal semiconductors— $\\mathrm{.csPbX_{3}}$ NCs and Cd-chalcogenide nanostructures—feature their respective advantages. \n\nInspired by the highly efficient PL of $\\mathrm{CsPbX}_{3}\\mathrm{NCs}$ in this study we investigate the possibility of using $\\mathrm{CsPbX}_{3}$ NCs as an inexpensive optical gain medium. First, for thin films of $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs, we report the observation of amplified spontaneous emission (ASE), tunable over most of the visible range $(440-700\\mathrm{nm})$ with low pump thresholds down to $5\\pm1\\upmu\\mathrm{J}\\mathrm{cm}{\\breve{-2}}$ and high values of modal net gain of at least $450\\mathrm{cm}^{-1}$ . Among other colloidal semiconductor materials, such low-threshold pump fluencies have only been previously demonstrated for colloidal CdSe and CdSe/CdS nanoplatelets33–35, whereas CdSe/ZnCdS NCs exhibit higher thresholds (from $800\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ in the blue to $90\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ in the red)28 presumably due to stronger Auger recombination36. We then realize two different lasing regimes for $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs depending on the resonator configuration: whispering-gallery-mode (WGM) lasing using single silica microsphere resonators, conformally coated with $\\mathrm{Cs}\\bar{\\mathrm{Pb}}\\mathrm{X}_{3}$ NCs, and random lasing in $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NC films. \n\n# Results \n\nBasic characteristics of $\\mathbf{CsPb}\\mathbf{X}_{3}$ NCs in solutions and in films. As-synthesized $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs, capped with oleylamine and oleic acid as surface ligands, form stable colloidal dispersions in typical nonpolar solvents such as toluene (Fig. 1a)22. For the spectroscopic studies in this work, we selected monodisperse samples of cubic-shaped NCs with mean sizes of ca. $9-10\\mathrm{nm}$ (Fig. 1b). These NCs readily form uniform, compact films of sub-micron thickness on drop-casting onto a glass substrate. \n\nThe bandgap of $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs is controlled via compositional modulations, for example, by altering the Cl/Br ratio for the $410{-}530\\mathrm{nm}$ range, and $\\mathrm{Br/I}$ ratio for the $530\\mathrm{-}700\\mathrm{nm}$ range (Fig. 1c). A pronounced excitonic peak is preserved in the absorption spectrum of the $\\mathrm{CsPbBr}_{3}$ NC film (Fig. 1d). The absorption coefficients of the densely packed films are in the range of $(3.6{-}4.0)\\cdot10^{4}\\mathrm{cm}^{-1}$ (or $3.6{-}4.0\\upmu\\mathrm{m}^{-1})$ , indicating that up to $70\\mathrm{-}80\\%$ of the pumping laser light $\\lambda=400\\mathrm{nm})$ is absorbed by $300{-}400{-}\\mathrm{nm}$ thick films. The refractive index of a $\\mathrm{CsPbBr}_{3}$ NC film is estimated to be 1.85–2.30 at $400{-}530\\mathrm{nm}$ from the optical reflectance and absorption spectra (Supplementary Fig. 1). The PL from this NC film exhibits a peak with a narrow linewidth of $25\\mathrm{nm}$ $\\mathrm{\\Omega_{110meV)}}$ , Stokes-shifted by $13\\mathrm{nm}$ $(57\\mathrm{meV})$ with respect to the excitonic absorption peak (Fig. 1d). The PL QYs of the same NCs in the solution reach values of up to $70\\mathrm{-}90\\%$ (for green-to-red-emitting NCs) indicating a high degree of electronic surface passivation. The PL lifetimes are very similar for solutions and for films (Supplementary Fig. 2; 1–22 ns, longer for lower-bandgap NCs). PL excitation spectrum from an NC film closely resembles the absorption spectrum (Supplementary Fig. 3). \n\n![](images/ed9c7bf5fa634f7d4d908e447e9455d097ea516863d8e2cf81c1c987b1010234.jpg) \nFigure 1 | Colloidal caesium lead halide perovskite NCs. (a) Stable dispersions in toluene under excitation by a ultraviolet lamp $\\therefore\\lambda=365\\mathsf{n m};$ . (b) Lowand high-resolution transmission electron microscopy images of $\\mathsf{C s P b B r}_{3}$ NCs; corresponding scale bars are 100 and $5\\mathsf{n m}$ . (c) PL spectra of the solutions shown in (a). (d) Optical absorption and PL spectra of a ca. 400-nm-CsPbBr3 NC film. \n\nAmplified spontaneous emission from $\\mathbf{CsPb}\\mathbf{X}_{3}$ NCs. Clear signatures of the ASE emission—narrowing of the emission peaks and threshold behaviour with a steep rise in intensity above the threshold—are readily obtained from 300- to $400\\mathrm{-nm}$ thick films produced by drop-casting colloidal solutions onto glass substrates (Fig. 2a; excitation at $400\\mathrm{nm}$ with 100 fs pulses; and Supplementary Fig. 4 presenting ASE/PL on a logarithmic scale in a wider range of pumping intensities). ASE is spectrally different from PL emission; it has a narrower bandwidth of ${4\\mathrm{-}9\\mathrm{nm}}$ (full width at half maximum, FWHM; see Supplementary Fig. 5) due to a narrow gain in bandwidth and is red-shifted by ca. $10\\mathrm{nm}$ with respect to the PL maximum. When the ASE spectrum is overlaid with the Tauc plot of the direct-bandgap absorption (Supplementary Fig. 3), the ASE spectral maxima coincide with the end of the shallow absorption tail (Urbach tail). This red-shifted ASE may have its origins in re-absorbance during single-exciton lasing28,29 or in the excitonic binding energies in the bi-excitonic optical gain mechanism34,37. Similar to PL spectra, ASE can be obtained in the whole visible spectral region by varying the composition of $\\mathrm{CsPbX}_{3}$ NCs (Fig. 2b). The threshold for building ASE is ca. $5\\pm1\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ (Fig. 2c) for $\\mathrm{CsPbBr}_{3}$ perovskite NCs, and generally falls in the range of $5{-}22\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ for all other compositions (Supplementary Fig. 6). Notably, the ASE linewidth increases for samples with a lower ASE threshold suggesting that a larger portion of the emission falls within the optical gain conditions, enlarging the optical gain bandwidth. \n\nIn addition to the ASE threshold, the net modal gain is an important figure-of-merit that, from a practical point of view, indicates the efficiency of light amplification in the material and the quality of the resonator needed for achieving lasing38. Optical gain can be measured by using the variable stripe length method39, where the excitation light is shaped into a line of variable lengths on the sample surface (see the schematics in the inset of Fig. 2d and a photograph of the emitted light in \n\n![](images/9ffa0b4cd97db2e06bb0725e3b3b659d70d71fcb361c0956c2637ef8e2ba4767.jpg) \nFigure 2 | ASE spectra from thin films of $\\cos p_{6}x_{3}$ NCs. (a) Pump-fluence dependence of the emission from a $\\mathsf{C s P b B r}_{3}$ NC film (pumping intensity range was $3{-}25\\upmu\\uptau m^{-2})$ . (b) Spectral tunability of ASE via compositional modulation. (c) Threshold behaviour for the intensity of the ASE band of the $\\mathsf{C s P b B r}_{3}$ NC film shown in (a). (d) Variable stripe-length experiment for estimation of modal net gain for the $\\mathsf{C s P b B r}_{3}$ NC film. All spectra were excited at $\\lambda=400\\mathsf{n m}$ with 100 fs laser pulses. \n\n![](images/933c7a01b59188742d813d1a5e4f98d49f9a845d707e70c06a2f4b710477e178.jpg) \nFigure 3 | Time-resolved measurements from the $\\cos P b B r_{3}$ NC film. (a) Decay traces at pump fluences varied from subthreshold to well above ASE threshold values with emission recorded at ASE peak wavelengths. $(b-e)$ The corresponding full emission spectra. \n\nSupplementary Fig. 7), and the emission intensity is then measured as a function of stripe length, $L$ . When the stripe length reaches the threshold value where propagation losses are compensated by the optical amplification, the PL spectrum starts to show an additional ASE component that grows with stripe length (see Fig. 2d and corresponding spectra in Supplementary Fig. 8). The threshold region can be fitted with the model of net modal gain $(G)$ : $\\begin{array}{r}{I=\\frac{\\stackrel{A}{A}}{g}(e^{G L}-1)}\\end{array}$ , yielding high values of $G$ ranging from 450 to $500\\mathrm{cm}^{-1}$ . Considering these gain values, the build-up time for ASE was estimated to be 140 fs, considerably shorter than the ASE threshold lifetime of $300{\\mathrm{ps}}$ \n\nAnother characteristic and expected feature of ASE, seen in time-resolved experiments (Fig. 3), is the acceleration of radiative recombination due to switch from individual to collective emission. For $\\mathrm{CsPbBr}_{3}$ NC films in this work, at excitation intensities lower than the ASE threshold $(<2\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ ; Fig. 3b), typical PL lifetimes of several nanoseconds are observed with nearly single-exponent behaviour. Well above ASE thresholds $(80\\upmu)\\up c\\mathrm{m}^{-2}$ ; Fig. 3e), ASE lifetimes of 60 ps were estimated, again with clean, single-exponent line shape. At the ASE threshold, an ASE lifetime of 300 ps can be roughly estimated from a bi-exponential fit assuming competing ASE and PL processes. A ‘quasi-continuous wave’ regime of excitation can be observed with pumping pulses of longer duration than this ASE lifetime27, though at the expense of higher overall pumping fluence to maintain the same instant excitation intensity over the whole pulse duration. Such pulses can be provided by conventional, inexpensive nanosecond lasers. In this case, with a 300-ps ASE lifetime at $5{\\mathrm{-}}10\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ femtosecond pumping thresholds, we estimate a threshold fluence of $150{-}\\dot{3}00\\dot{\\upmu}\\mathrm{J}\\mathrm{cm}^{-2}$ for 10-ns excitation pulses. In close agreement, ASE thresholds of $400{-}500\\upmu\\mathrm{J}\\dot{\\mathrm{cm}}^{-2}$ were observed experimentally (Fig. 4). \n\nWhispering-gallery-mode lasing from $\\mathbf{CsPb}\\mathbf{X}_{3}$ NCs. Effective optical feedback from a high-quality optical resonator is needed to obtain lasing. In this regard, commercially available silica microspheres can serve as circular cavities in which the emitted light orbits around the circumference due to total internal reflection (Fig. 5a, inset). The resulting cavity modes are known as WGMs. WGM lasers can be conveniently observed by the adhesion of solution-processed lasing material onto the surface of the microspheres17,40,41. The great utility of microsphere resonators for research purposes stems from their extremely high and wavelength-independent $\\underline{{\\boldsymbol{Q}}}$ factors of up to ${10}^{9}$ (describing the degree of feedback of the cavity), and their rather isotropic leakage of the emitted light. In this work, we obtained well-resolved lasing modes with pumping threshold behaviour using $15\\upmu\\mathrm{m}$ (Fig. 5a) and $53\\upmu\\mathrm{m}$ (Supplementary Fig. 9) spheres, with intermodal distances dependent on the sphere diameter (the larger the sphere, the smaller the spacing). All spectra were excited at the wavelength $400\\mathrm{nm}$ with 100 fs laser pulses. The observed linewidths of lasing modes $(0.15{-}0.20\\mathrm{nm})$ are limited primarily by the resolution of the spectrometer used for detection. We note that the spectra presented herein were collected from single microspheres using a microscope objective. In contrast, when the emission from several spheres was integrated, lasing modes were often indistinguishable due to the small but essential standard size-deviation of the spheres of ca. $0.5\\mathrm{-}1\\%$ . \n\n![](images/5cedb6de8437614b791f7cde8b480ff571c50e7dfd724c7649297dcd45e8ac9d.jpg) \nFigure 4 | ASE from $\\cos P b B r_{3}$ NC film under nanosecond excitation. (a) Evolution of the emission spectra with the increase of pumping fluence and (b) corresponding dependence of the emission at $535\\mathsf{n m}$ on pump fluence. Spectra were excited at $\\lambda=355{\\mathsf{n m}}$ with 10 ns laser pulses. \n\nRandom lasing from $\\mathbf{CsPb}\\mathbf{X}_{3}$ nanocrystals. Lasing can also be observed without optical resonators, namely when the required optical feedback is provided via light scattering induced by intrinsic disorder in the lasing medium, leading to so-called random lasing42. Light diffuses in highly scattering media and randomly forms closed loops causing random fluctuations of lasing modes. Scattering occurs, for instance, on the aggregates of NCs, and is clearly pronounced in thicker films of several microns. Since the path of the light is unique and irreproducible, so are the lasing modes (Fig. 5b) generated by each shot of the pumping laser. For the $\\mathrm{CsPbX}_{3}$ NC films investigated in this work, the modes appear to be fully stochastic and their distribution for 256 consecutive laser shots is presented in Fig. 5c. \n\nThe multiple emission spectra expressed as a function of wave vector in k space, shown in Fig. 5c, can be Fourier transformed into a corresponding optical path-length distribution (Fig. 5d). The averaged distribution of path length, $l,$ over 256 shots is presented in the inset of Fig. 5b. The mean path length, $=93\\pm5{\\upmu\\mathrm{m}}$ , is obtained by integral averaging over the path-length range of $0{-}300\\upmu\\mathrm{m}$ . The criterion for Anderson localization, $k^{-}\\approx\\overset{\\smile}{10^{3}}$ , is much larger than unity, pointing to the case of weakly scattering random lasing. The medium is rather transparent and shows no apparent effects from film imperfections such as cracks and pinholes. The lasing threshold is of the same order of magnitude as ASE threshold discussed above. Due to the strong increase in intensity of Rayleigh scattering with decreasing wavelength $(I\\propto\\lambda^{-4})$ , aggregation-induced scattering and hence random lasing is most pronounced in blue-emitting samples, such as the one shown in Fig. 5b. \n\n![](images/3d44a039a66c39d1c7516bc55c2b2b94052d88a594af554ab8a3546ad2f4d52a.jpg) \nFigure 5 | Lasing in perovskite $\\cos p_{6}x_{3}$ NC films. (a) Evolution from PL to whispering-gallery-mode (WGM) lasing with increasing pump intensity in a microsphere resonator of $15\\upmu\\mathrm{m}$ in diameter, covered by a film of $\\mathsf{C s P b B r}_{3}\\mathsf{N C s}$ . (b) Single pump laser shot mode structure of random lasing from ${\\mathsf{C s P b}}({\\mathsf{B r/}}$ ${\\mathsf{C l}})_{3}\\mathsf{N C}$ film. The inset shows path-length distribution averaged over 256 pump laser shots. (c) Stochastic mode distribution in a series of 256 pump laser shots (PL background emission is subtracted). (d) Fast Fourier transform (FFT) of $\\mathbf{\\eta}(\\bullet)$ . \n\n# Discussion \n\nConsidering the colloidal nature of $\\mathrm{CsPb}\\mathrm{X}_{3}$ NCs, the most relevant comparison to be drawn is with strongly quantumconfined Cd-chalcogenide-based colloidal NCs. After the first demonstration of optical gain and stimulated emission from colloidal CdSe NCs (emission at $620\\mathrm{nm},$ ) in 2000 (ref. 37), colloidal NCs have been considered as an eventual alternative to more expensive epitaxial group III–V materials (for example, \n\nInGaN, GaAsP and InGaAs). The green spectral region is especially difficult to access by III–V compounds43. For this reason, the size-tunable emission of Cd-chalcogenide-based materials is highly appealing, but still lacks stability in the blue spectral region $(\\leq500\\mathrm{nm})^{29}$ . So far, the lowest pumping thresholds of Cd-based quantum dots (QDs) have been reported for specially engineered $\\mathrm{CdSe/ZnCdS}$ core-shell structures, ranging from $90\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ for red QDs to $800\\upmu\\mathrm{J}\\mathsf{c m}^{-2}.$ for blue QDs with single-exciton nature of the optical gain28. Recently, a large step forward was made by introducing pristine CdSe and core-shell CdSe/CdS nanoplatelets35,44,45, showing the lowest ASE thresholds for inorganic colloidal nanomaterials obtained to date $(6\\upmu)\\upepsilon\\mathrm{m}^{-2}$ at $520\\mathrm{nm}$ and $8\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ at $635\\mathrm{nm})^{34,35}$ . Furthermore, in such atomically flat CdSe nanoplatelets, where bandgaps are tunable stepwise by adjusting the number of unit cells in platelet thickness, only discrete emission wavelengths were so far demonstrated and ASE had not been reported below $510\\mathrm{nm}$ . Overall, in Cd-chalcogenide-based systems, emission wavelength tuning is almost exclusively achieved via quantum-size effects. On the contrary, in this study rather large $\\bar{\\mathrm{CsPb}}\\mathrm{X}_{3}$ NCs $(9-10\\mathrm{nm})$ with weak to no quantum confinement were chosen and the emission was found to be freely adjustable via compositional tuning (that is, by the halide ratio). Such convenient compositional tuning is not easily accessible in Cd-chalcogenide NCs. In experiments on smaller $\\mathrm{\\dot{C}s P b B r}_{3}$ NCs with pronounced quantum-size effects, by up to an order of magnitude higher ASE thresholds were observed. Thus, a clear complementarity is seen between weakly confined $\\mathrm{CsPbX}_{3}$ NCs (performing best in the blue–green with $\\leq10\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ blue ASE thresholds) and strongly confined Cd-chalcogenide-based materials (performing best in the green–red with $\\leq10\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ ASE thresholds for red CdSe/ CdS platelets). For a completely unbiased comparison, we have reproduced the synthesis of CdSe and core-shell CdSe/CdS nanoplatelets described by She et al.35, and observed same low thresholds of $\\mathsf{7}{-}15\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ (Supplementary Figs 10 and 11) under the same testing conditions as applied here for $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs using femtosecond excitations. For nanosecond excitation pulses (Fig. 4), ASE thresholds for $\\mathrm{CsPb}\\mathrm{X}_{3}$ NCs rise to $\\mathbf{\\tilde{\\alpha}}_{\\sim0.45\\mathrm{mJ}}\\mathbf{cm}^{-2}$ (and $1\\mathrm{mJ}\\mathrm{cm}^{-2}$ for $\\mathrm{CdSe/CdS}$ nanoplatelets; see Supplementary Fig. 12). Low ASE thresholds in $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs are also assisted by an extremely large absorption cross-section $(\\upsigma)$ . For $\\mathrm{CsPbBr}_{3}$ perovskite NCs, we estimated $\\sigma=$ $8\\times10^{-14}\\mathrm{cm}^{2}$ (or $8\\mathrm{\\dot{n}m}^{2}.$ ), that is almost two orders of magnitude larger than typically reported for CdSe $\\mathrm{QDs^{46}}$ , and similar to CdSe nanoplatelets47, emitting in the same wavelength range (green). No continuous-wave ASE could be observed at room temperature or down to $80\\mathrm{K}$ for neither $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs nor for Cd-chalcogenide platelets, up to excitation levels causing photo-damage of the samples. \n\nA comparison of our results for $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs with reports on closely related solution-deposited hybrid perovskite $\\mathrm{\\Delta}\\mathrm{\\bar{MAPb}}{\\mathrm{X}}_{3}$ films and microcrystals points to rather similar ASE thresholds (Supplementary Table $1)^{17-20}$ . $\\mathrm{MAPbX}_{3}$ films were also reported to exhibit random lasing48, lasing from vertical cavities20 and from spherical resonators17 and WGM lasing19. The comparably good performance of $\\mathrm{CsPbBr}_{3}$ NCs indicates that their high surface area does not impede their optical properties. Also the solution-processed organic semiconductor materials exhibit similar ASE thresholds under similar testing conditions (no cavity, plane wave-guiding films)49. So far, in only a few examples of vacuum-deposited organic semiconductors50 and epitaxial multiple-quantum-well structures51 were lower, sub- $\\upmu\\mathrm{J}{\\cdot}\\mathrm{cm}^{-2}$ ASE thresholds demonstrated, but usually with an order of magnitude lower optical gain values. At the time of the submission of this work, much lower thresholds $(0.22\\upmu\\mathrm{J}\\mathrm{cm}^{-2})$ ) were reported by Zhu et al.21, for lasing from $\\mathrm{MAPbI}_{3}$ wires, highlighting also the morphological effects (wire acts as a single-mode waveguide and laser resonator) and suggesting that future studies should focus on engineering $\\mathrm{CsPbX}_{3}$ wire-like morphologies with dimensions comparable to the wavelengths of light. As a first step in this direction and due to the lack of reports on bulk-like $\\mathrm{CsPbX}_{3}$ , we have prepared $\\mathrm{CsPbX}_{3}$ polycrystalline films (with crystalline domain sizes of several $\\upmu\\mathrm{m}\\dot{}$ ) and individual microcrystals simply by drop-casting from dimethylformamide solutions and inspected their PL/ASE characteristics. NCs and microcrystals of the same composition exhibit nearly identical PL peak wavelengths and linewidths, and radiative lifetimes (Supplementary Fig. 13). ASE thresholds of polycrystalline films were by an order of magnitude higher, but this may well be caused also by the difficult-to-control, suboptimal for ASE build-up morphologies of these films. Similarly to $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs, the ASE peaks were found to be red-shifted with respect to the PL maxima (Supplementary Fig. 14). For selected large microcrystals $(100-150\\upmu\\mathrm{m})$ clear WGM lasing modes were observed as well (Supplementary Fig. 15). No wire-like morphologies could be found for direct comparison with $\\mathbf{MAPbI}_{3}$ wires. Overall, we conclude that among the three distinct cases—small $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ QDs 1 $\\left(4\\mathrm{-}8\\mathrm{nm}\\right.$ , chemically unstable), $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs $\\left(10\\mathrm{nm}\\right)$ and $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ microcrystals—the NCs exhibit the best balance between optical performance (having generally the lowest ASE thresholds) and chemical versatility (exhibiting facile solution processing, and easily adjustable film thickness and morphology for obtaining various lasing regimes). \n\nAt present, we cannot fully answer the remaining question of this study—the exact mechanism for optical gain. This is also an open question in the $\\mathrm{MAPb}{\\mathrm{X}}_{3}$ -related literature. To speculate on this matter for $\\mathrm{CsPbX}_{3}$ NCs, the observed red shift of the ASE peaks with respect to PL maxima can be explained by ether bi-excitonic lasing (due to binding energy of bi-exciton)37 or by self-absorption in the case of a single-exciton $\\mathrm{gain}^{28,29}$ . We also evaluated the average density of excitons per each NC ( $\\cdot$ , for details, see Supplementary Note 1) at the ASE threshold and found $=0.5\\pm0.15$ . Expected theoretical values of ${}$ are 0.5 for single-exciton gain29 and 1 for bi-excitonic mechanism37,52. Increase of QY with pump intensity (Supplementary Fig. 16) might be another plausible evidence for single-exciton gain, as QY should decrease when Auger recombination is limiting the ASE (typically observed for bi-excitonic gain). \n\nIn summary, perovskite $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs, synthesized via a simple one-step reaction between $\\mathrm{PbX}_{2}$ and Cs-oleate in nonpolar solvent media, are particularly promising for achieving ASE/lasing in blue and green spectral regions. Optical gain is demonstrated here at room temperature for pulse durations of up to $10\\mathrm{ns}.$ , corresponding to the quasi-continuous wave (quasi-cw) excitation regime with low ASE threshold values down to $5\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ . High optical gain values of up to $450\\mathrm{cm}^{-1}$ allow for obtaining resonant conditions for lasing either by coating $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs onto spherical microresonators or via random lasing mediated by light scattering on NC aggregates. Random lasing, arising from the combined effect of wave guiding and light scattering in the optical gain medium of densely packed aggregates of $\\mathrm{CsPb}\\bar{\\mathrm{X}_{3}}$ NCs, does not require an ultraprecise cavity as in conventional lasing. This not only provides the obvious technological advantage of facile and inexpensive fabrication, but also enables various niche applications such as displays and lighting, benefitting from the broad spectral angular distribution of the random lasing42,53. Another promising area of application for random lasers, benefitting from the broad ASE spectrum, is as the light source in optical coherence tomography where it is critical to keep optical coherence moderately low but controlled54,55. Random lasing in the weak-scattering regime, where the spectral distribution of lasing modes is unique for each laser shot, can serve as a physically based method for random number generation and in cryptography56. \n\n# Methods \n\nPreparation of $\\cos p_{6}x_{3}$ NCs and microcrystalline films. $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ NCs were synthesized as described in our recent report22. The crude solution was cooled down with water bath and aggregated NCs were separated by centrifuging for $3\\mathrm{min}$ at 11,000 r.p.m. After centrifugation, the supernatant was discarded, the particles were redispersed in $0.3{\\mathrm{ml}}$ hexane and centrifuged again for $4\\mathrm{{min}}$ at 12,000 r.p.m. After repeating the previous step one more time, the precipitate was redispersed in $0.6\\mathrm{ml}$ toluene, and $0.2{\\mathrm{ml}}$ acetonitrile was added for precipitation. The NCs were centrifuged again for $4\\mathrm{{min}}$ at $12,000{\\mathrm{r.p.m}}$ , and after this, the supernatant was discarded and the precipitate was redispersed in toluene. Thin films of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs were obtained by drop-casting $10{-}50\\upmu\\mathrm{l}$ of $\\mathrm{CsPbX}_{3}$ NC solution at ambient conditions onto glass substrates, followed by drying at ambient conditions. For coating $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs onto silica microspheres, water-dispersed 15- and $53\\mathrm{-}\\upmu\\mathrm{m}$ silica microspheres (http://www.microspheres-nanospheres.com) were first drop-cast onto a hot glass substrate, followed by drop-casting of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs. For preparing microcrystalline films, $\\mathrm{Pb}{\\mathrm{X}}_{2}$ and $\\mathrm{CsX}$ were dissolved in dimethylformamide, and then drop- or spin-cast onto a glass substrate followed by heat treatment at $150^{\\circ}\\mathrm{C}$ Alternatively, films of $\\mathrm{PbX}_{2}$ can be converted into $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ on dipping into Cs-halide solutions. \n\nCharacterization of $\\cos p_{\\mathrm{b}}x_{3}$ NC solutions and films. UV-Vis absorption and reflection spectra of the NC films were collected using a Jasco V670 spectrometer equipped with an integrating sphere. Steady-state PL emission and excitation spectra were acquired with a Fluorolog iHR320 Horiba Jobin Yvon spectrofluorometer, equipped with Xe lamp and a photomultiplier tube (PMT) detector. PL lifetime measurements were performed using a time-correlated single-photon counting setup, equipped with SPC-130-EM counting module (Becker & Hickl GmbH) and an IDQ-ID-100-20-ULN avalanche photodiode (Quantique) for recording the decay traces. The emission of the perovskite NCs was excited by a $400\\mathrm{-nm~}100$ -fs laser pulses with a repetition of $1\\mathrm{kHz}$ synchronized to time-correlated single-photon counting module through an electronic delay generator (DG535 from Stanford Research Systems). Transmission electron microscopy images were recorded using a JEOL JEM-2200FS microscope operated at $200\\mathrm{kV}$ . For the thickness determination of the films, an AlphaStep D-120 profilometer was used. \n\nASE and lasing experiments. These experiments were performed with excitation light from nanosecond and femtosecond lasers. All experiments were conducted at room temperature. The femtosecond laser system consisted of an oscillator (Vitesse 800) and an amplifier (Legend Elite), both from Coherent Inc., with a frequency-doubling external beta barium borate (BBO) crystal; it yielded 100 fs pulses at $400\\mathrm{nm}$ , with a repetition rate of $1\\mathrm{kHz}$ and pulse energy of up to $4\\upmu\\upmu\\upmu$ . The laser beam profile had a $\\mathrm{TEM}_{00}$ mode with a 1-mm FWHM diameter. Laser power was measured by a LabMax-TOP laser energy meter (Coherent Inc.) with a nJmeasuring head. For variable stripe length (VSL) experiments, the beam was focused into a stripe by a cylindrical lens with a focal length of $75\\mathrm{mm}$ . The nanosecond laser system was a Quanta-Ray Pro 230-50 (Spectra-Physics), frequency tripled to $355\\mathrm{nm}$ , with a pulse duration of 10 ns and a top-hat beam profile focused to a spot of $1.5\\mathrm{mm}$ in diameter with a pulse energy of up to $30\\upmu\\mathrm{J}$ . To resolve the spectrally sharp lasing peaks, the optical emission was coupled into a Princeton Instruments SP-2300i spectrometer, equipped with a Thorlabs $\\mathrm{LCl}00/\\mathrm{M}$ CCD detector array $\\mathrm{{.0.14nm}}$ resolution). Fast Fourier Transform (FFT) analysis of random lasing mode patterns for large arrays of pump laser shots was performed using the Gwyddion software package. The laser beam intensity profiles were analysed by a LabMax-TOP camera from Coherent Inc. \n\n# References \n\n1. Gratzel, M. The light and shade of perovskite solar cells. Nat. Mater. 13, 838–842 (2014). \n2. Green, M. A., Ho-Baillie, A. & Snaith, H. J. The emergence of perovskite solar cells. Nat. Photon. 8, 506–514 (2014). \n3. Park, N. G. Organometal perovskite light absorbers toward a $20\\%$ efficiency low-cost solid-state mesoscopic solar cell. J. Phys. Chem. Lett. 4, 2423–2429 (2013). \n4. Zhou, H. et al. Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). \n5. Chung, I., Lee, B., He, J., Chang, R. P. & Kanatzidis, M. G. All-solid-state dye-sensitized solar cells with high efficiency. Nature 485, 486–489 (2012). \n6. Stranks, S. D. et al. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n7. Xing, G. et al. Long-range balanced electron- and hole-transport lengths in organic-inorganic $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ . Science 342, 344–347 (2013). \n8. Nie, W. et al. High-efficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 347, 522–525 (2015). \n9. Dong, Q. et al. Electron-hole diffusion lengths $>175$ um in solution-grown $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ single crystals. Science 347, 967–970 (2015). \n10. Shi, D. et al. Low trap-state density and long carrier diffusion in organolead trihalide perovskite single crystals. Science 347, 519–522 (2015). \n11. Zhang, F. et al. Brightly luminescent and color-tunable colloidal CH3NH3PbX3 $\\mathrm{{X}=\\mathrm{{Br}}}$ , I, Cl) quantum dots: potential alternatives for display technology. ACS Nano 9, 4533–4542 (2015). \n12. Jeon, N. J. et al. Compositional engineering of perovskite materials for high-performance solar cells. Nature 517, 476–480 (2015). \n13. Dou, L. et al. Solution-processed hybrid perovskite photodetectors with high detectivity. Nat. Commun. 5, 5404 (2014). \n14. Guo, Y. L., Liu, C., Tanaka, H. & Nakamura, E. Air-stable and solutionprocessable perovskite photodetectors for solar-blind UV and visible light. J. Phys. Chem. Lett. 6, 535–539 (2015). \n15. Yakunin, S. et al. Detection of X-ray photons by solution-processed lead halide perovskites. Nat. Photon. 9, 444–449 (2015). \n16. Tan, Z. K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n17. Sutherland, B. R., Hoogland, S., Adachi, M. M., Wong, C. T. & Sargent, E. H. Conformal organohalide perovskites enable lasing on spherical resonators. ACS Nano 8, 10947–10952 (2014). \n18. Xing, G. et al. Low-temperature solution-processed wavelength-tunable perovskites for lasing. Nat. Mater. 13, 476–480 (2014). \n19. Zhang, Q., Ha, S. T., Liu, X., Sum, T. C. & Xiong, Q. Room-temperature nearinfrared high-Q perovskite whispering-gallery planar nanolasers. Nano Lett. 14, 5995–6001 (2014). \n20. Deschler, F. et al. High photoluminescence efficiency and optically pumped lasing in solution-processed mixed halide perovskite semiconductors. J. Phys. Chem. Lett. 5, 1421–1426 (2014). \n21. Zhu, H. et al. Lead halide perovskite nanowire lasers with low lasing thresholds and high quality factors. Nat. Mater. 14, 636–642 (2015). \n22. Protesescu, L. et al. Nanocrystals of cesium lead halide perovskites (CsPbX, $\\mathbf{X}=\\mathbf{Cl}$ , Br, and I): novel optoelectronic materials showing bright emission with wide color gamut. Nano Lett. 15, 3692–3696 (2015). \n23. Oga, H., Saeki, A., Ogomi, Y., Hayase, S. & Seki, S. Improved understanding of the electronic and energetic landscapes of perovskite solar cells: high local charge carrier mobility, reduced recombination, and extremely shallow traps. J. Am. Chem. Soc. 136, 13818–13825 (2014). \n24. Sharma, S., Weiden, N. & Weiss, A. Phase diagrams of quasibinary systems of the type: $\\mathrm{ABX}_{3}–\\mathrm{A}^{\\prime}\\mathrm{BX}_{3}$ ; $\\mathrm{ABX}_{3}$ - $\\mathrm{AB^{\\prime}X}_{3}$ and $\\mathrm{ABX}_{3}$ - $\\mathrm{ABX}_{3}^{\\prime}$ ; $\\mathbf{X}=$ halogen. Z. Phys. Chem. 175, 63–80 (1992). \n25. Trots, D. M. & Myagkota, S. V. High-temperature structural evolution of caesium and rubidium triiodoplumbates. J. Phys. Chem. Solids 69, 2520–2526 (2008). \n26. Stoumpos, C. C., Malliakas, C. D. & Kanatzidis, M. G. Semiconducting tin and lead iodide perovskites with organic cations: phase transitions, high mobilities, and near-infrared photoluminescent properties. Inorg. Chem. 52, 9019–9038 (2013). \n27. Wang, Y. et al. Blue liquid lasers from solution of $\\mathrm{CdZnS/ZnS}$ ternary alloy quantum dots with quasi-continuous pumping. Adv. Mater. 27, 169–175 (2015). \n28. Dang, C. et al. Red, green and blue lasing enabled by single-exciton gain in colloidal quantum dot films. Nat. Nanotechnol. 7, 335–339 (2012). \n29. Dang, C. & Nurmikko, A. Beyond quantum dot LEDs: optical gain and laser action in red, green, and blue colors. MRS Bull. 38, 737–742 (2013). \n30. Chen, O. et al. Compact high-quality CdSe–CdS core–shell nanocrystals with narrow emission linewidths and suppressed blinking. Nat. Mater. 12, 445–451 (2013). \n31. Carbone, L. et al. Synthesis and micrometer-scale assembly of colloidal CdSe/CdS nanorods prepared by a seeded growth approach. Nano Lett. 7, \n2942–2950 (2007). \n32. Mahler, B., Nadal, B., Bouet, C., Patriarche, G. & Dubertret, B. Core/shell colloidal semiconductor nanoplatelets. J. Am. Chem. Soc. 134, 18591–18598 (2012). \n33. Lhuillier, E. et al. Two-dimensional colloidal metal chalcogenides semiconductors: synthesis, spectroscopy, and applications. Acc. Chem. Res. 48, \n22–30 (2015). \n34. Grim, J. Q. et al. Continuous-wave biexciton lasing at room temperature using solution-processed quantum wells. Nat. Nanotechnol. 9, 891–895 (2014). \n35. She, C. et al. Low-threshold stimulated emission using colloidal quantum wells. Nano Lett. 14, 2772–2777 (2014). \n36. Robel, I., Gresback, R., Kortshagen, U., Schaller, R. D. & Klimov, V. I. Universal size-dependent trend in auger recombination in direct-gap and indirect-gap semiconductor nanocrystals. Phys. Rev. Lett. 102, 177404 (2009). \n37. Klimov, V. I. et al. Optical gain and stimulated emission in nanocrystal quantum dots. Science 290, 314–317 (2000). \n38. Coldren, L. A., Corzine, S. W. & Masˇanovic´, M. L. in Diode Lasers and Photonic Integrated Circuits 247–333 (John Wiley & Sons, Inc., 2012). \n39. Shaklee, K. L. & Leheny, R. F. Direct determination of optical gain in semiconductor crystals. Appl. Phys. Lett. 18, 475–477 (1971). \n40. Grivas, C. et al. Single-mode tunable laser emission in the single-exciton regime from colloidal nanocrystals. Nat. Commun. 4, 2376 (2013). \n41. Xing, G. et al. Ultralow-threshold two-photon pumped amplified spontaneous emission and lasing from seeded CdSe/CdS nanorod heterostructures. ACS Nano 6, 10835–10844 (2012). \n42. Wiersma, D. S. The physics and applications of random lasers. Nat. Phys. 4, \n359–367 (2008). \n43. Laubsch, A., Sabathil, M., Baur, J., Peter, M. & Hahn, B. High-power and highefficiency InGaN-based light emitters. IEEE Trans. Electron Devices 57, 79–87 (2010). \n44. Ithurria, S. et al. Colloidal nanoplatelets with two-dimensional electronic structure. Nat. Mater. 10, 936–941 (2011). \n45. Tessier, M. D. et al. Efficient exciton concentrators built from colloidal core/crown CdSe/CdS semiconductor nanoplatelets. Nano Lett. 14, 207–213 (2014). \n46. Leatherdale, C. A., Woo, W. K., Mikulec, F. V. & Bawendi, M. G. On the absorption cross section of CdSe nanocrystal quantum dots. J. Phys. Chem. B \n106, 7619–7622 (2002). \n47. Kunneman, L. T. et al. Nature and decay pathways of photoexcited states in CdSe and CdSe/CdS nanoplatelets. Nano Lett. 14, 7039–7045 (2014). \n48. Dhanker, R. et al. Random lasing in organo-lead halide perovskite microcrystal networks. Appl. Phys. Lett. 105, 151112 (2014). \n49. Namdas, E. B. et al. Low thresholds in polymer lasers on conductive substrates by distributed feedback nanoimprinting: progress toward electrically pumped plastic lasers. Adv. Mater. 21, 799–802 (2009). \n50. Kozlov, V. G., Bulovic, V., Burrows, P. E. & Forrest, S. R. Laser action in organic semiconductor waveguide and double-heterostructure devices. Nature 389, 362–364 (1997). \n51. Thijs, P. J. A., Tiemeijer, L. F., Kuindersma, P. I., Binsma, J. J. M. & Van Dongen, T. High-performance 1.5 mu m wavelength InGaAs-InGaAsP strained quantum well lasers and amplifiers. IEEE J. Sel. Top. Quantum Electron. 27, 1426–1439 (1991). \n52. Klimov, V. I. et al. Single-exciton optical gain in semiconductor nanocrystals. Nature 447, 441–446 (2007). \n53. Cao, H. Lasing in random media. Waves Random Media 13, R1–R39 (2003). \n54. Redding, B., Choma, M. A. & Cao, H. Speckle-free laser imaging using random laser illumination. Nat. Photon. 6, 355–359 (2012). \n55. Redding, B. et al. Low spatial coherence electrically pumped semiconductor laser for speckle-free full-field imaging. Proc. Natl Acad. Sci. USA 112, 1304–1309 (2015). \n56. Reidler, I., Aviad, Y., Rosenbluh, M. & Kanter, I. Ultrahigh-speed random number generation based on a chaotic semiconductor laser. Phys. Rev. Lett. 103, 024102 (2009). \n\n# Acknowledgements \n\nM.V.K. acknowledges financial support from the European Union through the FP7 (ERC Starting Grant NANOSOLID, GA No. 306733). W.H. is grateful to the Austrian Science Foundation (FWF) for financial support via the SFB project IR_ON. Ehsan Hassanpour Yesaghi and Sebastian Manz are acknowledged for technical assistance in the laser lab. We thank Nadia Schwitz for help with photography of the emission from CsPbX3 solutions, Dr. Dmitry Dirin for syntesis of CdSe and CdSe/CdS nanoplatelets and Dr. Nicholas Stadie for reading the manuscript. \n\n# Author contributions \n\nM.V.K. conceived and initiated the work. S.Y., M.H. and W.H. performed the ASE and lasing measurements; S.Y. analysed the ASE/lasing results; L.P. and F.K. synthesized the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs; M.I.B. collected the transmission electron microscopy images; G.D.L. and M.F. provided fs and ns laser setups and technical advice; M.V.K., W.H. and M.F. supervised the work. S.Y. and M.K. wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Yakunin, S. et al. Low-threshold amplified spontaneous emission and lasing from colloidal nanocrystals of caesium lead halide perovskites. Nat. Commun. 6:8056 doi: 10.1038/ncomms9056 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms7293", + "DOI": "10.1038/ncomms7293", + "DOI Link": "http://dx.doi.org/10.1038/ncomms7293", + "Relative Dir Path": "mds/10.1038_ncomms7293", + "Article Title": "Exploring atomic defects in molybdenum disulphide monolayers", + "Authors": "Hong, JH; Hu, ZX; Probert, M; Li, K; Lv, DH; Yang, XN; Gu, L; Mao, NN; Feng, QL; Xie, LM; Zhang, J; Wu, DZ; Zhang, ZY; Jin, CH; Ji, W; Zhang, XX; Yuan, J; Zhang, Z", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Defects usually play an important role in tailoring various properties of two-dimensional materials. Defects in two-dimensional monolayer molybdenum disulphide may be responsible for large variation of electric and optical properties. Here we present a comprehensive joint experiment-theory investigation of point defects in monolayer molybdenum disulphide prepared by mechanical exfoliation, physical and chemical vapour deposition. Defect species are systematically identified and their concentrations determined by aberration-corrected scanning transmission electron microscopy, and also studied by ab-initio calculation. Defect density up to 3.5 x 10(13) cm(-2) is found and the dominullt category of defects changes from sulphur vacancy in mechanical exfoliation and chemical vapour deposition samples to molybdenum antisite in physical vapour deposition samples. Influence of defects on electronic structure and charge-carrier mobility are predicted by calculation and observed by electric transport measurement. In light of these results, the growth of ultra-high-quality monolayer molybdenum disulphide appears a primary task for the community pursuing high-performance electronic devices.", + "Times Cited, WoS Core": 1249, + "Times Cited, All Databases": 1361, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000350289800001", + "Markdown": "# Exploring atomic defects in molybdenum disulphide monolayers \n\nJinhua Hong1,\\*, Zhixin $\\mathsf{H u}^{2,\\star}$ , Matt Probert3, Kun Li4, Danhui Lv1, Xinan Yang5, Lin $\\mathsf{G u}^{5}$ , Nannan $M a o^{6,7}$ , Qingliang Feng6, Liming Xie6, Jin Zhang7, Dianzhong Wu8, Zhiyong Zhang8, Chuanhong Jin1, Wei $\\mathbf{\\boldsymbol{j}}_{\\mathrm{\\boldsymbol{l}}}2,9$ , Xixiang Zhang4, Jun Yuan1,3 & Ze Zhang1 \n\nDefects usually play an important role in tailoring various properties of two-dimensional materials. Defects in two-dimensional monolayer molybdenum disulphide may be responsible for large variation of electric and optical properties. Here we present a comprehensive joint experiment–theory investigation of point defects in monolayer molybdenum disulphide prepared by mechanical exfoliation, physical and chemical vapour deposition. Defect species are systematically identified and their concentrations determined by aberration-corrected scanning transmission electron microscopy, and also studied by ab-initio calculation. Defect density up to $3.5\\times10^{13}\\mathsf{c m}^{-2}$ is found and the dominant category of defects changes from sulphur vacancy in mechanical exfoliation and chemical vapour deposition samples to molybdenum antisite in physical vapour deposition samples. Influence of defects on electronic structure and charge-carrier mobility are predicted by calculation and observed by electric transport measurement. In light of these results, the growth of ultra-high-quality monolayer molybdenum disulphide appears a primary task for the community pursuing high-performance electronic devices. \n\nTephxehp souorcamtcieosns oaf fdg apphnhyseoinvceal olofopfwer-tsd sma npaitrowandoai-lgdim fnohsry itnchael (2D) crystal systems4,5. However, its intrinsic shortcoming lies in its zero bandgap, which strongly hinders its application in logical electronic devices. Among the post-graphene development, 2D semiconducting molybdenum disulphide and other transition metal dichalcogenides6,7 have recently appeared on the horizon of materials science and condensed matter physics. Monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ is a direct-gap semiconductor that exhibits a substantially improved efficiency in its photoluminescence8,9. Valley polarization occurs due to significant spin–orbit coupling and leads to optical circular dichroism10–12 in the monolayer system. The electronic transport of $\\mathbf{MoS}_{2}$ -based field effect transistors (FETs) shows steep sub-threshold swing of $70\\mathrm{mV}\\mathrm{dec}^{-1}$ (refs 13–15) and a high on/off ratio up to $\\mathsf{\\Omega}_{10}^{8}$ (ref. 16). A metalinsulator transition happens when carrier densities reaches $10^{13}\\mathrm{cm}^{-2}$ , which also increases the effective mobility17–19. Owing to its unique optical and electric properties, $\\ensuremath{\\mathrm{MoS}}_{2}$ is believed to be a promising candidate as a building block for future applications in nanoelectronics and optoelectronics6. \n\nWafer-scale production of atomically thin layers is paramount for $\\ensuremath{\\mathrm{MoS}}_{2}$ to be used as a candidate channel material for electronic and optoelectronic devices13–19. Among the currently available preparation methods, mechanical exfoliation (ME) is deemed less efficient for these large-scale applications, even though it produces the highest-quality samples exhibiting the best electric performance. Physical and chemical vapour deposition17,20–25 methods are more compatible for the scalable growth of high-quality samples. However, the experimentally attainable mobility is still one or two order-of-magnitude lower than the theoretical value of $410\\mathsf{c m}^{2}\\mathrm{V}^{-1}\\mathsf{s}^{-1}$ (refs 13,18,26–29). For back-gated $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ FET devices, the highest mobility reported so far reaches $81\\mathrm{cm}^{2}\\mathrm{\\bar{V}}^{-1}s^{-1}$ for ME sample28, $45\\mathrm{cm}^{2}\\dot{\\mathrm{V}}^{-1}{\\mathsf{s}}^{-1}$ for chemical vapour deposition $(\\mathrm{CVD})^{17}$ and $<1\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ for physical vapour deposition $(\\mathrm{PVD})^{25}$ . The major scattering mechanism for the mobility deterioration has been recently suggested as due to the presence of plentiful localized band tail states30 caused by short-range disordered structural defects (such as vacancies28,31 and grain boundaries32), and Coulomb traps33,34. However, the roles played by various defects in electric and optoelectronic properties are yet to be explicitly understood. There have been few investigations reported on point defects, mostly vacancies, and grain boundaries in $\\mathrm{m}{-}\\mathrm{Mo}{\\mathsf S}_{2}$ (refs 28,30–32,35,36). These studies are, however, often performed with samples made by preparatory methods, for example, ME or CVD, which essentially limits the scope of those studies. \n\nHere we present a systematic investigation of the point defects in distinctly prepared $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ by combining atomically resolved annular dark-field scanning transmission electron microscopy (ADF-STEM) imaging, density functional theory (DFT) calculation and electric transport measurements. We observe, for the first time, that antisite defects with molybdenum replacing sulphur are dominant point defects in PVD-grown $\\mathbf{MoS}_{2}$ while the sulphur vacancies are predominant in ME and CVD specimens. These experimental observations are further supported qualitatively by the growth mechanism and quantitatively by the defects’ formation energies calculations. The DFT calculations, in addition, predict the electronic structures and magnetic properties of $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ with antisite defects. We also discuss the influence of defects on the phonon-limited carrier mobility theoretically, and further examine them by electric transport in defective $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ -based FETs. Our systematic investigation of point defects, especially antisites, will further deepen our understanding of this novel 2D atomically thin semiconductor and pave the way for the scalable electronic application of the family of atomically thin transition metal chalcogenides. \n\n# Results \n\nStatistics of point defects. For the purpose of the analysis of defects and their concentration, we have chosen about ten samples prepared under the optimized fabrication condition (see the Methods section and Supplementary Note 1 for the details of sample synthesis) from each method (ME, PVD and CVD) and then transferred each sample onto at least two TEM grids independently for ADF-STEM characterizations. The crystalline quality and the choice of samples for statistical analysis are presented in Supplementary Figs 1–9. Figure 1 summarized the most significant results obtained from our analysis on these $\\mathbf{MoS}_{2}$ samples. For the PVD specimen, antisite defects with one Mo atom replacing one or two S atoms ( $\\mathbf{\\tilde{M}}\\mathbf{o}_{\\mathrm{{S}}}$ or $\\mathbf{Mo}_{\\mathbf{S}2}\\cdot$ ) are frequently observed, marked with red dashed circles shown in Fig. 1a, while the dominant defects for the ME and CVD samples are S vacancies with one $(\\mathrm{V}_{\\mathrm{S}})$ or two $(\\mathrm{V}_{\\mathrm{S}2})$ S atoms absent, as marked by green dashed circles in Fig. 1b. As the STEM’s $Z$ -contrast mechanism37, that is, $I{\\stackrel{\\smile}{\\sim}}Z^{1.6-2.0}$ ( $\\mathit{\\Pi}_{\\cdot}I$ and $Z$ are the image contrast and atomic number, respectively), predicts, Mo and S atoms can be unambiguously discriminated, with Mo $\\left(Z=44\\right)$ showing bright contrast and two superposed S atoms showing dim contrast in the lattice of $\\mathrm{m}{\\cdot}\\mathrm{Mo}{\\cal S}_{2}$ . Following a similar argument and quantitative image analysis, various defects, for example, $\\mathbf{Mo}_{\\mathrm{S}}$ or $\\mathrm{v_{s}}$ where the lattice image presents abnormal intensity variation, can be clearly identified individually through direct imaging and their atomic structures further verified by $a b$ -initio calculations (please refer to Supplementary Table 1 for details of each atomic defect). \n\nWe show the relative importance of each type of point defects in Fig. 1c,d. Figure 1c presents the total counts of different point defects based on over 70 atomically resolved ADF-STEM images for each type, that is, ME, PVD or CVD $\\mathrm{MoS}_{2}$ samples. It is found that the dominant type of point defects in each sample highly depends on the specific sample preparation method. The $\\mathrm{v_{s}}$ vacancy is the predominant point defects in ME and CVD samples, with its concentration of about $(1.2\\pm0.4)\\times10^{13}\\mathrm{cm}^{-2}$ (Supplementary Fig. 6), close to the results reported previously30. Atomic defects $\\mathrm{\\DeltaV_{Mo}}$ (one Mo atom missing) and $\\ensuremath{\\mathrm{S}}_{\\mathrm{Mo}}$ (one S atom replacing Mo site) were also found, but with much lower concentrations as shown in Fig. 1c. In contrast, the histogram also shows that antisite defects $\\mathbf{Mo}_{\\mathsf{S}2}$ and $\\mathbf{Mo}_{\\mathrm{S}}$ are dominant in PVD samples, with their concentrations higher than that of $\\mathrm{v_{s}}$ . The density of $\\mathbf{Mo}_{\\mathsf{S}2}$ and $\\mathbf{Mo}_{\\mathrm{S}}$ reaches $(\\breve{2}.8\\pm0.3)\\times10^{13}$ and $7.0\\times10^{12}\\mathrm{cm}^{-2}$ , corresponding to an atomic percent of $0.8\\%$ and $0.21\\%$ , respectively (counted on the total number of all Mo and S atoms). Such a defect concentration is surprisingly high if the defects were regarded as impurity doping, which is usually only achieved in degenerate semiconductor38 (for instance $10^{\\overset{.}{-}2}\\sim10^{-4})$ . It is, therefore, of vital importance to understand how they modify the electronic properties of $\\mathrm{m}{\\cdot}\\mathrm{Mo}{\\mathsf S}_{2}$ as elucidated below. \n\nStructural characterization of point defects. So far, there have been few reports concerning the structures of sulphur vacancies31,39 and their impacts on the electronic transport properties30,40 of $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ ; by contrast, there is still a lack of detailed knowledge on the antisite defects, which is at such an unexpected high doping level in PVD samples. Hence, we focus more on antisite defects. In Fig. 2a–e, we highlight all the images of the experimentally observed antisite defects in $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ (see also Supplementary Fig. 10), which can be grouped into two categories. One is the antisite defects with Mo atom(s) substituting S atom(s), including $\\mathbf{Mo}_{\\mathrm{S}}$ , $\\mathbf{Mo}_{{\\mathbb S}2}$ and $\\mathrm{Mo}2_{\\mathrm{S}2}$ (Fig. 2a–c). The other category is the antisite defects with S atom occupying the site of Mo, namely $\\ensuremath{\\mathrm{S}}_{\\ensuremath{\\mathrm{Mo}}}$ and $S2_{\\mathrm{Mo}}$ (Fig. 2d,e). The experimental identification of these antisite defects can be further unambiguously supported by the quantitative image simulation based on DFT-predicted atomic structures of all antisite defects. The fully relaxed DFT-predicted atomic structures of antisite defects were shown in Fig. 2k–t, where the atomic displacement and structure deformation are explicitly observable, especially for antisites $\\mathbf{Mo}_{{\\mathbb S}2}$ and $S2_{\\mathrm{Mo}}$ . Associated side views of these relaxed structures are available in Fig. 2p–t. The ADF image simulations (Fig. 2f–j) based on the calculated structures fit quite well with the experimental images shown in Fig. 2a–e, respectively, especially for the off-centre feature observable in antisites $\\mathbf{Mo}_{{\\mathbb S}2}$ and $S2_{\\mathrm{Mo}}$ which can be tentatively attributed to Jahn–Teller distortions. \n\n![](images/3f2208db0acc724773a2633a7037f66d70f9a515cadabbca0a2516476eaeeb7f.jpg) \nFigure 1 | Atomic resolved STEM–ADF images to reveal the distribution of different point defects. (a) Antisite defects in PVD ${M o S}_{2}$ monolayers. Scale bar, 1 nm. (b) Vacancies including ${\\sf V}_{\\sf S}$ and $\\mathsf{V}_{\\mathsf{S}2}$ observed in ME monolayers, similar to that observed for CVD sample. Scale bar, 1 nm. (c,d) Histograms of various point defects in PVD, CVD and ME monolayers. Error estimates are given for the dominant defects (more details on the statistics can be found in Supplementary Fig. 6). ME data are in green, PVD data in red and CVD in blue. \n\nEnergetics of predominant point defects in different $\\mathbf{m}{\\mathbf{-}}\\mathbf{M}\\mathbf{o}\\mathbf{S}_{2}$ . The distribution of different atomic defects in $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ certainly depends on their preparation process. A full exploration of the growth dynamics requires a comprehensive experiment–theory joint investigation, which is beyond the scope of the present work, although it is of fundamental interest. Here we provide a qualitative explanation, based on our DFT calculations, to reveal the microscopic physical mechanism of the preparation-processdependent defect formation. The formation energy $(\\Delta E_{\\mathrm{Form}})$ for all the point defects are calculated and summarized in Table 1, as consistent with a previous report35. Here, chemical potentials of elements Mo and S were employed to calculate the formation enthalpy $(\\Delta H_{\\mathrm{Form}})$ of defects. To account for a range of different possible reservoirs (for example, bulk element or bulk $\\begin{array}{r}{\\mathbf{MoS}_{2}.}\\end{array}$ ), each enthalpy is given with a range, as listed in Table 1. Two widely used DFT codes (CASTEP41 and VASP (Vienna $A b$ -initio Simulation Package)42) are adopted to exploit the full range of functionality available and demonstrate the consistency of the calculated results in Table 1. \n\nAn ME sample is exfoliated from $\\ensuremath{\\mathrm{MoS}}_{2}$ natural mineral. After the $\\ensuremath{\\mathrm{MoS}}_{2}$ mineral was formed and/or extracted, either element S or Mo of $\\ensuremath{\\mathrm{MoS}}_{2}$ is prone to reach a solid–gas phase equilibrium. Owing to a higher saturated vapour pressure of S, the mineral-form $\\mathrm{MoS}_{2}$ has to release more S than Mo atoms into the gas phase and thus S is prone to be deficient in $\\mathbf{MoS}_{2}$ . Reflecting this fact, vacancies $\\mathrm{v_{s}}$ and $\\mathrm{V}_{\\mathrm{S}2}$ have the lowest $\\Delta E_{\\mathrm{Form}}$ of $\\bar{2.12\\mathrm{eV}}$ and $4.14\\mathrm{eV}$ , respectively, among all the defects. The formation energies of all the antisite defects are higher than $5\\mathrm{eV}$ , indicating that the S-deficient mineral-form $\\ensuremath{\\mathrm{MoS}}_{2}$ favours the formation of S vacancies, leading to the observation of the most common defect of $\\mathrm{v}_{\\mathrm{s}},$ followed by $\\mathrm{V}_{\\mathrm{S}2}\\mathrm{:}$ and almost no antisite defect in ME samples. \n\nIn a typical PVD process, $\\mathbf{MoS}_{2}$ precursor is sublimated into the gas phase with clusters and atoms, carried by Ar gas (mixed with $\\begin{array}{r}{\\operatorname{H}_{2}\\dot{}.}\\end{array}$ ), and then condensed into a solid-phase $\\mathbf{MoS}_{2}$ . Sulphur has a larger saturated vapour pressure so that more S atoms in the gas phase will leave the preparation chamber, thus establishing a S-deficient and Mo-rich condition. These clusters and atoms are highly mobile and are thus prone to form an ordered structure of $\\ensuremath{\\mathrm{MoS}}_{2}$ in the lowest total energy. Considering $n+1$ Mo and $2n{-}1\\mathrm{s}$ atoms for example, they have two options, namely, forming (i) $n$ $\\mathbf{MoS}_{2}$ units with one $\\mathbf{Mo}_{\\mathrm{S}}$ antisite or (ii) $n+1\\ \\mathrm{MoS}_{2}$ units with three ${\\mathrm{v}}_{\\mathrm{s}}$ vacancies. The exact value of $n$ does not affect the energetic difference between these two types of defects. We thus arbitrarily instantiate $n$ as 107, namely $\\dot{1}\\dot{0}\\&\\ M\\mathrm{o}$ and $213\\mathrm{~S~}$ atoms in total. The total energy of the antisite option is $\\mathrm{-1,774.83eV}$ , while that for the vacancy case is $-1,774.26\\mathrm{eV}$ which is $0.57\\mathrm{eV}$ less stable than the former. A similar relation also applies to antisite defect $\\mathbf{Mo}_{\\mathsf{S}2}$ with an energy gain of $0.92\\mathrm{eV}$ . A sample with one antisite $\\mathbf{Mo}_{\\mathrm{S}}$ or $\\mathbf{Mo}_{\\mathsf{S}2}$ shares the same number of Mo and S atoms with another sample that has three or four S vacancies, respectively. The formation energies of antisites $\\mathbf{Mo}_{\\mathrm{S}}$ and $\\mathbf{Mo}_{{\\mathbb S}2}$ were, therefore, divided by three and four, respectively, to make amount of residual O atoms taking the position of S atoms in the resulting $\\ensuremath{\\mathrm{MoS}}_{2}$ sheets, due to the competition between $_{\\mathrm{Mo-O}}$ and $_{\\mathrm{Mo-}S}$ bonding in the reaction chamber. Our $a b$ -initio calculation, not shown here, suggests that these O atoms are $1.99\\mathrm{eV}$ less stable than corresponding 2S and usually tend to desorb into the gas phase leaving vacancies at the S sites, that is, S vacancies. It is argued that Mo atoms may jump into the S vacancies and form Mo antisites. Despite of the S-rich condition, even if Mo is rich in a certain local environment, Mo atoms may be firmly bonded with oxygen in the precursor, which strongly limits the diffusion of Mo, making the formation of Mo antisite from mobile Mo atom and S vacancy much less likely. \n\n![](images/653bb9b44b71f56491e4c91640ba3aa5cfb29e22ef140b33a218dc3c9d39b03b.jpg) \nFigure 2 | Atomic structures of antisite defects. (a–c) High-resolution STEM–ADF images of antisite $M_{\\mathsf{O}_{\\mathsf{S}}},$ ${M o}_{52}$ and $M\\circ2_{52}$ respectively. The former two antisites (highlighted by the red dashed rectangle in k) are dominant in PVD-synthesized ${M o S}_{2}$ single layers. Scale bar, $0.5\\mathsf{n m}$ (d,e) Atomic structures of antisite defects $\\mathsf{S}_{M\\circ}$ and $S2_{M_{0}},$ respectively. (f–j) Simulated STEM images based on the theoretically relaxed structures of the corresponding point defects in (a–e), using simulation software QSTEM49. $(|\\mathbf{k}\\mathbf{-}\\mathbf{t})$ Relaxed atomic model of all antisite defects in a–e through DFT calculation, with top and side views, respectively. Light blue, Mo atoms; gold, S atoms. For ease of comparison, we have presented the simulated ADF images before the atomistic schematics of the DFT calculated structures. \n\n
Table 1 | Formation energy (△EForm) and enthalpy (△HForm) of considered point defects.
CASTEP VASP
4HForm(eV)△HForm(eV)AEForm(eV)
Mos6.22~7.295.45~6.095.79
Mo2s211.157.957.54
Mo2s29.81~11.0910.49
SMo6.65~5.586.11~5.475.77
S2Mo8.007.097.49
Vs2.74~1.672.86~2.222.12
Vs25.63~4.344.14
Vmo6.98~4.847.28~5.996.20
\n\nCASTEP, Cambridge Sequential Total Energy Package; VASP, Vienna Ab-initio Simulation Package. The formation enthalpy is defined as $\\begin{array}{r}{\\varDelta H_{\\mathrm{Form}}=E_{\\mathrm{Defect}}-E_{\\mathrm{Pure}}+n\\times\\mu_{\\mathrm{Removed}}-m\\times k\\mu_{\\mathrm{Added}}.\\ \\mu}\\end{array}$ is the chemical potential of the removed and/or added atom to form a defect, while the formation energy is defined $a s\\varDelta E_{\\mathrm{Form}}=E_{\\mathrm{System}}-N_{\\mathrm{S}}\\times E_{\\mathrm{S}_{\\_}\\mathrm{ML}}-N_{\\mathrm{Mo}}\\times E_{\\mathrm{Mo}_{\\_}\\mathrm{ML}},$ where $E_{S_{-}M_{-}}$ and $E_{\\ensuremath{\\mathsf{M o}}_{-}\\ensuremath{\\mathsf{M L}}}$ are the single atom energy of Mo and S in a perfect monolayer. (Please refer to the Methods section for more details). Different exchange-correlation functionals are used in the VASP and CASTEP codes as discussed in the text. \n\nthese energies quantitatively comparable with a single S vacancy, as required by the comparison with Boltzmann distribution. We have renormalized $\\Delta\\bar{E}_{\\mathrm{{Form}}}^{\\prime}(\\mathrm{{Mo}_{\\mathrm{{S}}})=1.93\\:e V_{\\mathrm{{;}}}}$ , $\\Delta E_{\\mathrm{Form}}^{\\prime}(\\mathrm{Mo}_{\\mathrm{S}2})=$ $1.89\\mathrm{eV}$ , which give rise to a ratio of $\\begin{array}{r}{p(\\mathrm{Mo}_{\\mathrm{S}2}){:}p(\\mathrm{Mo}_{\\mathrm{S}}){:}p(\\mathrm{V}_{\\mathrm{S}})=}\\end{array}$ 10.5:6.7:1 at the growth temperature of $1,100\\mathrm{K}$ . This ratio is comparable with the experimental probability density ratio of $\\mathrm{Mo_{S2}}\\mathrm{:Mo_{S}:V_{S}=9:2.3:1}$ in PVD samples. \n\nThe CVD process is distinctly different from ME or PVD. Extra S vapour is supplied to replace $\\mathrm{~O~}$ in the $\\mathrm{MoO}_{3}$ precursor under an S-rich condition. We suspect that there are small \n\nElectronic structures. The electronic structure of point defects plays a crucial role in determining the electric properties of these defective $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ . Vacancy $\\mathrm{v_{s}}$ and its effect on electronic structures have been recently reported30,35; we thus focus on the less-studied antisite defects (please refer to Supplementary Fig. 11 for our ADF imaging and DFT calculation of ${\\mathrm{V}}_{\\mathrm{S}}{\\mathrm{,}}$ ). Figure 3 shows the theoretically predicted band structures and projected densityof-states of two primary antisites $\\mathbf{Mo}_{\\mathrm{S}}$ and $\\mathbf{Mo}_{\\mathsf{S}2}$ . Our results give a bandgap of $1.73\\mathrm{eV}$ for a defect-free $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ (Supplementary Fig. 12), close to the experimentally observed optical bandgap of $1.8\\mathrm{eV}$ (ref. 8). Defect states with nearly flat band dispersion for $\\mathbf{Mo}_{\\mathsf{S}2}$ and $\\mathbf{Mo}_{\\mathrm{S}}$ reside inside the band gap of a perfect $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ (Fig. 3a,d). These states mostly comprises the $d$ orbitals of four Mo atoms around the defect. In addition, the orbital hybridization of Mo and S atoms results in extended wavefunctions involving the surrounding atoms, forming a ‘superatom’ with a radius of roughly ${6\\mathring\\mathrm{A}}.$ , as shown in Fig. ${3}\\mathrm{b,c,f.}$ \n\nMagnetic properties of $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ have not been reported yet, as it is believed to be a non-magnetic material. Nevertheless, we did find a local magnetic moment of $2\\mu_{\\mathrm{B}}$ in antisite $\\mathbf{Mo}_{\\mathrm{S}}$ , while the values for other defects, for example, $\\mathrm{v}_{\\mathrm{s}},$ $\\mathrm{V}_{\\mathrm{S}2}$ and $\\mathbf{Mo}_{\\mathsf{S}2}$ , are smaller than $0.1\\mu_{\\mathrm{B}},$ and hence are negligible. The magnetic moment of $2\\mu_{\\mathrm{B}}$ for a $\\mathbf{Mo}_{\\mathrm{S}}$ antisite is not localized only on the central Mo atom, with the surrounding atoms contributing roughly $20\\%$ of the total moment probably due to the strong hybridization among these atoms in a ‘superatom’, as shown in the visualized total spin density (Fig. 3e). Detailed distribution of magnetic moment is available in Supplementary Fig. 13. The spin-resolved real-space distribution of a defect-induced state (state 3) marked in Fig. 3d was plotted in Fig. 3f to illustrate the origin of the magnetism. The occupied spin-up component (yellow isosurface) is mainly composed of the $\\bar{d}_{\\mathrm{xy}}$ and $d_{\\mathrm{x}2-\\mathrm{y}2}$ orbitals of the antisite Mo atom, while the unoccupied spin-down component (cyan isosurface) is projected onto the $d_{\\mathrm{xy}}$ and $d_{\\mathrm{z}2}$ orbitals of surrounding Mo atoms, consistent with the total spin charge density shown in Fig. 3e. More detailed discussion on the magnetic property of antisites are presented in Supplementary Fig. 14 and Supplementary Note 2. \n\n![](images/2c63d02591f71c012a397bfbd7b5033003ef6e0ac2c6e8df050e838b8a021212.jpg) \nFigure 3 | Electronic properties of predominant antisite defects in $M o S_{2}$ monolayer. (a) Band structure and corresponding density of states (DOS) of antisite defect $M\\upcirc_{\\mathsf{S}2}$ .The grey bands are from normal lattice sites, similar to conduction band and valence band of perfect monolayer, while the discrete red bands show the localized defects states. The DOS is projected onto the atoms around the defect (defect) and those in the middle plane of two adjacent defects (pure), respectively. The grey dash line indicates the position of the Fermi Level. (b,c) Real-space distribution of the wave functions of the two defect states below and above the Fermi energy. (d) The band structure and DOS of antisite $M o_{5}$ , with a similar colour scheme of a, but the two spin components are coloured in red (spin-up) and blue (spin-down), respectively. (e) Spin density of antisite $M_{\\sf O S}$ defined as $\\rho_{\\mathsf{u p}}-\\rho_{\\mathsf{d o w n}},$ charge densities $\\rho_{\\mathsf{u p}}$ and $\\rho_{\\mathsf{d o w n}}$ are spin-resolved for spin-up and -down components, which are represented by yellow and blue isosurfaces, respectively. (f) Spin-resolved real-space distribution of the wave function of the two marked defect states (State 3) in d. The isosurface value in b,c,e,f is 0.001e Bhor \u0003 3. \n\nCarrier mobility in defective samples. As there have been plentiful reports on the transport of ME $\\mathbf{MoS}_{2}$ -based FETs with electron mobility $1\\sim81\\mathrm{cm}^{2}\\dot{\\mathrm{V}}^{-1}s^{-1}$ (refs 15,16,18,26,28,43,44), we focus on the transport properties of CVD and PVD monolayers. Figure $4\\mathrm{a-d}$ presents the output and transfer characteristics of fabricated FETs based on PVD and CVD $\\mathbf{MoS}_{2}$ , respectively. Our transport measurements (in Fig. 4a–d) of defective $\\mathbf{MoS}_{2}$ -based FETs reveal that the PVD and CVD $\\mathrm{MoS}_{2}$ has electron mobility 0.5 and $11\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1};$ , respectively. All these results are well comparable with the reported mobilities of $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ of $1\\sim81\\mathrm{cm}^{2}\\mathrm{V}^{-1}s^{-1}$ for $\\mathbf{\\dot{M}E^{15,16,18,26,28,43,44}},$ $5\\sim45\\mathrm{cm}^{2}\\mathrm{V}^{-1}s^{-1}$ for $\\mathrm{CVD^{17,29}}$ and the reported values of $<1\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ for PVD $\\mathrm{m}{\\cdot}\\mathrm{Mo}{\\mathsf S}_{2}$ (ref. 25) respectively. \n\nTheoretically, we focus on the effect of the defects on the phonon-limited carrier mobilities45–47. Table 2 lists the calculated effective masses, deformation potentials and estimated mobilities derived based on the predicted electron mobility of $410\\mathsf{c m}^{2}\\mathrm{V}^{-1}\\mathsf{s}^{-1}$ in a perfect $\\ensuremath{\\mathbf{m}}{-}\\ensuremath{\\mathrm{Mo}}\\ensuremath{\\mathrm{S}_{2}}$ (ref. 48). $\\ensuremath{\\mathrm{MoS}}_{2}$ samples are usually n-type, we thus primarily focus on the electron mobility. It is found that the phonon-limited mobility of electrons flowing in the intrinsic conduction band is, exceptionally, nearly unaffected by the presence of vacancies ( $\\mathrm{\\DeltaV_{S}}$ or $\\mathrm{V}_{\\mathrm{S}2},$ ), but reduced by three times in the samples with antisite defects, whereas the phonon-limited mobility of holes carried by the intrinsic valence band is more sensitive to these defects and reduces roughly three times for vacancy and more than four times for antisite. Both vacancy and antisite are strong electron-scattering centres that the mobility derived from the defect states (d–e and d–h) for either electron or hole is fairly small, mostly smaller than 1 and $10\\mathsf{c m}^{2}\\mathrm{V}^{-1}\\mathsf{s}^{-1}$ , respectively. The defect states strongly affect, but not overwhelmingly dominate, the overall carrier mobility of the samples, owing to the relative low density of defects and the strongly localized defect states. On the other hand, in a real FET device the measured mobility can be affected by the contact resistance45 or the carrier density19. Furthermore, the trapped charges would act as a scattering centre15,40. A hopping transport caused by localized disorder is also observed30,33. Both can effectively reduce the mobility of the device. Nevertheless, our theory shows that the measured mobility is, most likely, correlated with the primary type of defects in a sample. \n\n![](images/f10735b779c4b1b032246c650db78c9063995f5f781b9b6940b3e3dc870d73a5.jpg) \nFigure 4 | Electric transport of defective $M O S_{2}$ . (a,b) Output and transfer characteristics of PVD ${M o S}_{2}$ -based FET. (c,d) Output and transfer characteristics of CVD ${M o S}_{2}$ -based FET. \n\n
Table 2| Phonon-limited carrer mobility estimation of perfect and defective MoS2 monolayers.
m*/moE(eV) μ (cm²v-'s-1)
ehd-ed-hehd-ed-hehd-ed-h
Perfect0.40-0.57- 14.9-3.44103850
Vs0.43-0.9635.2105.6-13.9-3.4-4.55.44101390<1<1
Vs20.42-1.231.19.2- 13.9-3.1-4.96.84261066<14
Mos0.99-1.275.534.1- 11.1-4.0-3.0-2.9123631<12
Mos20.71- 1.18.828.6- 13.3-3.6-4.3-6.816490210<1
elat close to an equivalent defect density revealed in the statistics.
\n\n# Discussion \n\nWe have to address the possible influence of electron beam irradiation on the formation of atomic defects and to distinguish the native from irradiation-induced defects. The observed antisite defects are believed to be native, not caused by electron beam irradiation. We envisage that two steps are involved in the formation of a $\\mathbf{Mo}_{\\mathrm{S}}$ defect from a well-prepared sample, namely the formation of a $\\mathrm{v_{s}}$ vacancy and Mo adatom, followed by the capture of the Mo adatom by the S vacancy. Although sulphur vacancy could be created by electron beam sputtering31,39, the formation of a Mo adatom and adjacent Mo vacancy need substantially high energy transfer from electron irradiation, which is less likely. The in-situ experiments show that the Mo adatoms are very mobile, but rarely jump into S vacancies to form antisite defects (Supplementary Note 3 and Supplementary Figs 15 and 16). On considering these experimental and simulation results, the observed $\\mathbf{Mo}_{\\mathrm{S}}$ and $\\mathbf{Mo}_{\\mathsf{S}2}$ antisites should be confidently regarded as intrinsic defects. In terms of S vacancies, as suggested by early studies30,31, the concentration of sulphur vacancies may be slightly overestimated due to beam damage even if the microscope works at low accelerating voltage (Supplementary Fig. 17). \n\n$\\ensuremath{\\mathrm{MoS}}_{2}$ sheets are extensively adopted in electronic devices. These point defects, as localized disorders, are significant scattering centres of carriers, which may reduce the mobility of charge carriers through the intrinsic conduction or valence band, especially for samples with antisite defects. Therefore, growth of ultra-high-quality $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ is of crucial importance to fabricate high-performance electronic devices. On the other side, the presence of defects may provide us novel routes to tailor the properties of $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ . We predicted theoretically for the first time that antisite $\\mathbf{Mo}_{\\mathrm{S}}$ shows a magnetic moment of $2\\mu_{\\mathrm{{B}}}$ . Our prediction of local magnetic moments may promote further investigations on the magnetic properties of defective $\\mathbf{MoS}_{2}$ monolayers. Given the strong optoelectronic response of $\\mathbf{MoS}_{2}$ layers with $\\mathbf{Mo}_{\\mathrm{S}}$ defects, it is a probable material that is capable for optical manipulation of local magnetic moment. If the defect density goes sufficiently high, it may expect an appreciably large magnetic exchange interaction between defects, and thus become a promising model system for the studies of dilute-magnetic semiconductors and 2D magnetism. \n\nBased on these findings, we propose an application-oriented strategy for fabricating atomically thin $\\mathbf{MoS}_{2}$ . In terms of electric applications, extra S should be introduced into the growth process or post-growth treatment, to restrain the formation of antisite defects for PVD specimen or to heal the abundant S vacancies for CVD and ME specimens, whereas in respect to magnetism, varied pressure of S in the PVD growth could produce different densities of $\\mathbf{Mo}_{\\mathrm{Sx}}$ antisites that remain to be explored for magnetic applications. \n\nIn summary, our systematic investigation of geometric and electronic structures of antisites and vacancies of $\\mathrm{m}{\\cdot}\\mathrm{Mo}{\\mathsf S}_{2}$ by ADFSTEM imaging and DFT calculation has led to a considerable progress in our understanding of the variation of the electric and magnetic properties induced by these point defects. We have demonstrated that minimizing point defects, especially antisites, is paramount for electric transport applications, while controllably introduced antisites may produce atomic size local magnetic moments. All these results considerably improve the understanding of point defect in atomically thin transition metal dichalcogenides and should benefit their potential applications in optoelectronic and nanoelectronic devices. \n\n# Methods \n\nSample preparations and transfer. ME $\\ensuremath{\\mathrm{m}}\\ensuremath{-}\\ensuremath{\\mathrm{Mo}}\\ensuremath{\\mathrm{S}}_{2}$ was prepared by micro-cleavage8 of natural bulk crystal (SPI Supplies) using scotch tapes. The monolayer was identified from the optical contrast of thin flakes under an optical microscope (Zeiss $\\mathbf{A}2\\mathbf{m})$ and then transferred onto copper TEM grids covered with holey carbon films. \n\nCVD monolayers were synthesized through the reduction of precursor $\\mathrm{MoO}_{3}$ by sulphur vapour flow at ambient pressures following the previously reported method21,32. PVD $\\mathbf{MoS}_{2}$ monolayers used in this study were synthesized by thermal evaporation of $\\mathbf{MoS}_{2}$ powders (Sigma-Aldrich, $99\\%$ ) at a temperature of $950^{\\circ}\\mathrm{C}.$ . Ar (2 s.c.c.m.) and $\\mathrm{H}_{2}$ (0.5 s.c.c.m.) were used as the carriers gases, following the reported method in ref. 25. The pressure of the growth chamber was about $8\\mathrm{Pa}$ and the growth time was usually $10\\mathrm{min}$ . In terms of sample synthesis, the advantages and disadvantages of these methods and liquid-phase exfoliation are compared in Supplementary Table 2. \n\nPVD and CVD $\\mathbf{MoS}_{2}$ monolayers were transferred onto the TEM grid as follows: first, the $\\mathrm{SiO}_{2}$ substrates with monolayer samples were covered with polymethyl methacrylate (PMMA) film after spin coating and then dried in air at $120^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ . The substrates were immersed into the boiling sodium hydroxide solution $(1\\mathrm{mol}1^{-1}$ ), which was heated up to $200^{\\circ}\\mathrm{C}$ to etch away the underneath $\\mathrm{SiO}_{2}$ layers. The floating PMMA film was picked up with a clean glass slide and then transferred into the distilled water for several cycles to wash away surface residues. In the next step, the PMMA film was lifted out by a TEM grid covered with lacey carbon film and then dried naturally in ambient. This TEM grid was heated at $120^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ in air before immersion into hot acetone for about $24\\mathrm{h}$ , to remove the PMMA. Before the ADF-STEM characterization, all the monolayer specimens on TEM grids were annealed at $200^{\\circ}\\mathrm{C}$ in air for $10\\mathrm{min}$ to reduce surface residues and/or contaminations. \n\nSTEM characterization and image simulation. Most of the structural characterizations of $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ were carried out with a probe-corrected Titan ChemiSTEM (FEI, USA). We operated this microscope at an acceleration voltage of $80\\mathrm{kV}$ to alleviate specimen damage induced by beam radiation. A low probe current was selected $(<70\\mathrm{pA})$ and the convergence angle was set to be 22 mrad. Under such a condition, the probe size was estimated to be close to $1.5\\mathrm{\\AA}$ . To enhance the contrast of the sulphur sublattices, the so-called medium-range ADF mode rather than the high-angle ADF mode was used by adjusting the camera length properly. Some experiments (such as Figs 1a and $2\\mathsf{a}-\\mathsf{c}$ ) were done with an ARM 200CF (JEOL, Japan), equipped with a cold field-emission gun. The advantage of higher energy resolution $(0.3\\mathrm{eV})$ and smaller probe size $({\\bar{<}}1.2\\mathrm{\\AA})$ provides higher resolution, thus giving rise to sharper contrast of the atomic images. All the experimental images shown in the main text and Supplementary Information were filtered through the standard Wiener deconvolution to partially remove the background noise for a better display (Supplementary Fig. 10). \n\nIt should be noted that intrinsic adatom defects were seldom observed experimentally and, therefore, they are not considered here. All the image statistics were done on the clean regions of the examined samples by ADF–STEM. On considering the good homogeneity of these samples prepared under the optimized conditions (see Supplementary Information), it shall not lead any large variations in the analysed defect population. \n\nSTEM–ADF image simulations of relaxed antisite defects were done by software QSTEM49. The input parameters were set according to the experimental conditions. Probe size, convergence angle and acceptance angle of the ADF detector are critical and accounted for in the image simulation. \n\nDFT calculations. The defect formation enthalpy for the first column of Table 1 was calculated using the total energy method with the plane-wave pseudopotential DFT code CASTEP41. The basic methodology is well known and has been widely used before for defect calculations. In this study, the Perdew-Burke-Ernzerhofgeneralized gradient approximation50 with ultrasoft potentials is used, as supplied in the CASTEP library. In addition, the dispersion interactions were added using the semi-empirical scheme of $\\mathrm{Grimm}^{51}$ . Structural optimizations of both ionic positions and cell vectors are performed using a modified Broyden-FletcherGoldfarb-Shanno-like scheme. The calculations were performed in a slab geometry of a $6\\times6$ supercell of $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ with a $15\\textup{\\AA}$ vacuum space in the $\\mathbf{\\Psi}_{c}$ axis direction perpendicular to the monolayer. A comparative study of the defect formation enthalpy and energy, together with the electronic and magnetic properties were also done by VASP simulation $\\mathrm{code^{42}}$ using the same slab model. The projector augmented-wave method52 combined with a plane wave basis is adopted in the calculations. The energy cutoff for plane wave is $400\\mathrm{eV}$ in structural relaxation and increases to $500\\mathrm{eV}$ while calculating the energy and electronic properties. The optB86b exchange functional53 together with the vdW correlation54,55 was adopted for exchange-correlation functional. The Brillouin zone of the supercell is sampled by a $3\\times3\\times1~k$ -mesh. All these structures are fully relaxed until the residual force for each atom is less than $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . \n\nEstimation of formation energy and enthalpy. The formation energy was defined as, $\\Delta E_{\\mathrm{Form}}=E_{\\mathrm{System}}-N_{\\mathrm{S}}\\times E_{\\mathrm{S\\_ML}}-N_{\\mathrm{Mo}}\\times E_{\\mathrm{Mo\\_ML}},$ where $E_{\\mathrm{S}_{-}\\mathrm{ML}}=E_{\\mathrm{S(single)}}$ $+E_{\\mathrm{Bond}}$ , ${\\cal E}_{\\mathrm{Mo\\_ML}}=E_{\\mathrm{Mo(single)}}+2{\\cal E}_{\\mathrm{Bond}}$ and $E_{\\mathrm{Bond}}=(E_{\\mathrm{ML}}{-}E_{\\mathrm{Mo(single)}}-2E_{\\mathrm{S(single)}})/3$ Formation enthalpy of defects is defined as $\\Delta H_{\\mathrm{Form}}=E_{\\mathrm{Defect}}-\\dot{E}_{\\mathrm{Pure}}+n\\times$ $\\mu_{\\mathrm{Removed}}-m\\times\\mu_{\\mathrm{Added}}$ , where $\\mu_{\\mathrm{Removed}}$ and $\\mu_{\\mathrm{Added}}$ are the chemical potentials of the removed and added atoms to form a defect, respectively. Chemical potentials of Mo and S in $\\mathbf{MoS}_{2}$ fulfill the equation $\\mu_{\\mathrm{Mo}}+2\\mu_{\\mathrm{S}}=\\mu_{\\mathrm{Mo}}^{*}+2\\mu_{\\mathrm{S}}^{*}+\\Delta H_{\\mathrm{MoS}_{2}}$ , where $\\mu_{\\mathrm{Mo}}^{*}$ is the chemical potential of Mo in the bulk form, $\\mu_{\\mathrm{{S}}}^{*}$ is the chemical potential of S in the $\\mathfrak{a}$ -phase crystal form and $\\Delta H_{\\mathrm{MoS_{2}}}$ is the formation enthalpy of $\\mathbf{MoS}_{2}$ . Although it is difficult to obtain the exact values of $\\mu_{\\mathrm{Mo}}$ and $\\mu_{\\mathrm{{S}}}$ the range of them can be deduced as $\\mu_{\\mathrm{Mo}}^{*}+\\Delta H_{\\mathrm{MoS}_{2}}\\leq\\mu_{\\mathrm{Mo}}\\leq\\mu_{\\mathrm{Mo}}^{*}$ , $\\begin{array}{r}{\\mu_{\\mathrm{S}}^{*}+\\frac{1}{2}\\Delta H_{\\mathrm{MoS}_{2}}\\le\\mu_{\\mathrm{S}}\\le\\mu_{\\mathrm{S}}^{*}}\\end{array}$ . \n\nThere are two formation enthalpy values in Table 1, the former one was computed by choosing $\\mu_{\\mathrm{Mo}}$ and $\\mu_{\\mathrm{{S}}}$ equal to $\\mu_{\\mathrm{{Mo}}}^{*}$ and $\\mu_{\\mathrm{{S}}}^{*},$ respectively, indicating that the removed (added) atoms come from (go to) the pure bulk form of Mo and S. For the latter value, we set $\\mu_{\\mathrm{Mo}}=\\mu_{\\mathrm{Mo}}^{*}+0.5{\\times}\\Delta H_{\\mathrm{MoS}_{2}}$ and $\\mu_{s}=\\mu_{s}^{*}+0.25{\\times}\\Delta H_{\\mathrm{MoS}_{2}}$ . In this case, the source and drain of defect atoms are pure $\\mathbf{MoS}_{2}$ ML. For antisite defects $\\mathbf{Mo}_{\\mathsf{S}2}$ and $S2_{\\mathrm{Mo}}$ , both schemes give the same result. \n\nEstimation of ‘phonon-limited’ carrier mobility. In 2D, the carrier mobility is given by the expression45–47 \n\n$$\n\\mu_{\\mathrm{2D}}={\\frac{e\\hbar^{3}C_{\\mathrm{2D}}}{k_{\\mathrm{B}}T m_{\\mathrm{e}}^{*}m_{\\mathrm{d}}\\left(E_{1}^{i}\\right)^{2}}}\n$$ \n\nwhere $m_{\\mathrm{e}}^{*}$ is the effective mass in the transport direction and $m_{d}$ is the average effective mass determined by $m_{d}=\\sqrt{m_{x}^{*}m_{y}^{*}}$ . The term $E_{1}$ represents the deformation potential constant of thepffivffiffiaffiffilffieffiffiffinffifficffie-band maximum for holes or conduction-band minimum for electrons along the transport direction, defined by $E_{1}^{i}=\\Delta V_{i}/(\\Delta l/l_{0})$ . Here $\\Delta V_{\\mathrm{i}}$ is the energy change of the $\\hat{\\boldsymbol{i}}^{\\mathrm{th}}$ band under proper cell compression and dilatation, $l_{0}$ is the lattice constant in the transport direction and $\\Delta l$ is the deformation of $l_{0}$ . \n\nFET fabrication and transport. The monolayer $\\mathbf{MoS}_{2}$ -based FET devices are fabricated through the following process. First, source (S) and drain (D) electrodes of the devices were defined via $\\mathbf{\\Delta}_{\\mathbf{e}}$ -beam lithography and a $5/45\\mathrm{nm}$ Ti/Au film was then evaporated followed by a standard lift-off process. In addition, the back-gated $\\ensuremath{\\mathrm{MoS}}_{2}$ FETs were then finished. Second, the top-gated devices were begun with forming gate insulator. Gate oxide layer ( $30\\mathrm{nm}\\mathrm{HfO}_{2}$ film) was grown under $90^{\\circ}\\mathrm{C}$ through Atomic Layer Deposition (Cambridge NanoTech Inc.). Lastly, the gate electrode window was also defined by e-beam lithography, followed by evaporation of $5\\mathrm{nm}\\mathrm{Ti}$ and $45\\mathrm{nm}$ Au thin film, and the top-gated $\\ensuremath{\\mathbf{MoS}}_{2}$ FETs are finished after a lift-off process. The as-fabricated devices were measured through Keithley 4200 semiconductor analyser on a probe station at room temperature and in air. An example of the device architecture is shown in Supplementary Fig. 18. \n\n# References \n\n1. Novoselov, K. S. et al. Two-dimensional gas of massless Dirac fermions in graphene. Nature 438, 197–200 (2005). \n2. Geim, A. K. & Novoselov, K. S. The rise of graphene. Nat. Mater. 6, 183–191 (2007). \n3. Zhang, Y. B., Tan, Y. W., Stormer, H. L. & Kim, P. Experimental observation of the quantum Hall effect and Berry’s phase in graphene. Nature 438, 201–204 (2005). \n4. Novoselov, K. S. et al. Electronic properties of graphene. Phys. Stat. Sol. B 244, 4106–4111 (2007). \n5. Li, X. et al. Large-area synthesis of high-quality and uniform graphene films on copper foils. Science 324, 1312–1314 (2009). Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. Nat. Nanotechnol. 7, 699–712 (2012). \n7. Ataca, C., Sahin, H. & Ciraci, S. Stable single-layer $\\mathrm{MX}_{2}$ transition-metal oxides and dichalcogenides in a honeycomb-like structure. J. Phys. Chem. C. 116, 8983–8999 (2012). \n8. Mak, K. F., Lee, C., Hone, J., Shan, J. & Heinz, T. F. Atomically thin $\\ensuremath{\\mathbf{MoS}}_{2}$ : a new direct-gap semiconductor. Phys. Rev. Lett. 105, 136805 (2010). \n9. Splendiani, A. et al. Emerging photoluminesence in monolayer $\\ensuremath{\\mathbf{MoS}}_{2}$ . Nano Lett. 10, 1271–1275 (2010). \n10. Zeng, H., Dai, J., Yao, W., Xiao, D. & Cui, X. Valley polarization in $\\mathbf{MoS}_{2}$ monolayers by optical pumping. Nat. Nanotechnol. 7, 490–493 (2012). \n11. Mak, K. F., He, K., Shan, J. & Heinz, T. F. Control of valley polarization in monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ by optical helicity. Nat. Nanotechnol. 7, 494–498 (2012). \n12. Cao, T. et al. Valley-selective circular dichroism of monolayer molybdenum disulphide. Nat. Commun. 3, 887 (2012). \n13. Radisavljevic, B., Radenovic, A., Brivio, J., Giacometti, V. & Kis, A. Single-layer $\\ensuremath{\\mathrm{MoS}}_{2}$ transistors. Nat. Nanotechnol. 6, 147–150 (2011). \n14. Kim, S. et al. High-mobility and low-power thin-film transistors based on multilayer $\\ensuremath{\\mathrm{MoS}}_{2}$ crystals. Nat. Commun. 3, 1011 (2012). \n15. Perera, M. M. et al. Improved carrier mobility in few-layer $\\ensuremath{\\mathbf{MoS}}_{2}$ field-effect transistors with ionic-liquid gating. ACS Nano 7, 4449–4458 (2013). \n16. Zhang, Y. J., Ye, J. T., Matsuhashi, Y. & Iwasa, Y. Ambipolar $\\mathbf{MoS}_{2}$ thin flake transistors. Nano Lett. 12, 1136–1140 (2012). \n17. Schmidt, H. et al. Transport properties of monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ grown by chemical vapor deposition. Nano Lett. 14, 1909–1913 (2014). \n18. Zou, X. M. et al. Interface engineering for high-performance top-gated $\\ensuremath{\\mathrm{MoS}}_{2}$ field-effect transistors. Adv. Mater. 26, 6255–6261 (2014). \n19. Radisavljevic, B. & Kis, A. Mobility engineering and a metal-insulator transition in monolayer $\\mathbf{MoS}_{2}$ . Nat. Mater. 12, 815–820 (2013). \n20. Wang, X., Feng, H., Wu, Y. & Jiao, L. Controlled synthesis of highly crystalline $\\ensuremath{\\mathbf{MoS}}_{2}$ flakes by chemical vapor deposition. J. Am. Chem. Soc. 135, 5304–5307 (2013). \n21. Lee, Y.-H. et al. Synthesis of large-area $\\ensuremath{\\mathrm{MoS}}_{2}$ atomic layers with chemical vapor deposition. Adv. Mater. 24, 2320–2325 (2012). \n22. Liu, K.-K. et al. Growth of large-area and highly crystalline $\\ensuremath{\\mathrm{MoS}}_{2}$ thin layers on insulating substrates. Nano Lett. 12, 1538–1544 (2012). \n23. Shi, Y. et al. van der Waals epitaxy of $\\ensuremath{\\mathrm{MoS}}_{2}$ layers using graphene as growth templates. Nano Lett. 12, 2784–2791 (2012). \n24. Wu, S. et al. Vapor-solid growth of high optical quality $\\mathbf{MoS}_{2}$ monolayers with near-unity valley polarization. ACS Nano 7, 2768–2772 (2013). \n25. Feng, Q. et al. Growth of large-area 2D $\\mathrm{MoS}_{2(1-\\bf{x})}$ $\\mathrm{Se}_{2\\mathrm{x}}$ semiconductor alloys. Adv. Mater. 26, 2648–2653 (2014). \n26. Fuhrer, M. S. & Hone, J. Measurement of mobility in dual-gated $\\ensuremath{\\mathrm{MoS}}_{2}$ transistors. Nat. Nanotechnol. 8, 146–147 (2013). \n27. Radisavljevic, B. & Kis, A. Measurement of mobility in dual-gated $\\mathbf{MoS}_{2}$ transistors. Nat. Nanotechnol. 8, 147–148 (2013). \n28. Yu, Z. et al. Towards intrinsic charge transport in monolayer molybdenum disulfide by defect and interface engineering. Nat. Commun. 5, 5290 (2014). \n29. Liu, H. et al. Statistical study of deep submicron dual-gated field-effect transistors on monolayer chemical vapor deposition molybdenum disulfide films. Nano Lett. 13, 2640–2646 (2013). \n30. Qiu, H. et al. Hopping transport through defect-induced localized states in molybdenum disulphide. Nat. Commun. 4, 2642 (2013). \n31. Komsa, H.-P. et al. Two-dimensional transition metal dichalcogenides under electron irradiation: defect production and doping. Phys. Rev. Lett. 109, 035503 (2012). \n32. Najmaei, S. et al. Vapour phase growth and grain boundary structure of molybdenum disulphide atomic layers. Nat. Mater. 12, 754–759 (2013). \n33. Ghatak, S., Pal, A. N. & Ghosh, A. Nature of electronic states in atomically thin $\\ensuremath{\\mathbf{MoS}}_{2}$ field-effect transistors. ACS Nano 5, 7707–7712 (2011). \n34. Li, S.-L. et al. Thickness-dependent interfacial Coulomb scattering in atomically thin field-effect transistors. Nano Lett. 13, 3546–3552 (2013). \n35. Zhou, W. et al. Intrinsic structural defects in monolayer molybdenum disulfide. Nano Lett. 13, 2615–2622 (2013). \n36. van der Zande, A. M. et al. Grains and grain boundaries in highly crystalline monolayer molybdenum disulphide. Nat. Mater. 12, 554–561 (2013). \n37. Pennycook, S. J. et al. Scanning Transmission Electron Microscopy-Imaging and Analysis (Springer, 2011). \n38. Sze, S. M. & Ng, K. K. Physics of Semiconductor Devices (John Wiley & Sons, Inc., New Jersey, 2007). \n39. Komsa, H. P., Kurasch, S., Lehtinen, O., Kaiser, U. & Krasheninnikov, A. V. From point to extended defects in two-dimensional $\\ensuremath{\\mathbf{MoS}}_{2}$ : evolution of atomic structure under electron irradiation. Phys. Rev. B 88, 035301 (2013). \n40. Zhu, W. et al. Electronic transport and device prospects of monolayer molybdenum disulphide grown by chemical vapour deposition. Nat. Commun. 5, 3087 (2014). \n41. Clark, S. J. et al. First principles methods using CASTEP. Z. Kristallogr. 220, 567–570 (2005). \n42. Kresse, G. & Furthmuller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n43. Baugher, B. W. H., Churchill, H. O. H., Yang, Y. & Jarillo-Herrero, P. Intrinsic electronic transport properties of high-quality monolayer and bilayer $\\mathbf{MoS}_{2}$ . Nano Lett. 13, 4212–4216 (2013). \n44. Bao, W. Z., Cai, X. H., Kim, D., Sridhara, K. & Fuhrer, M. S. High mobility ambipolar $\\ensuremath{\\mathrm{MoS}}_{2}$ field-effect transistors: substrate and dielectric effects. Appl. Phys. Lett. 102, 042104 (2013). \n45. Takagi, S.-i., Toriumi, A., Iwase, M. & Tango, H. On the universality of inversion layer mobility in Si MOSFET’s: part I-effects of substrate impurity concentration. IEEE Trans. Electr. Dev. 41, 2357–2362 (1994). \n46. Qiao, J. S. et al. High-mobility transport anisotropy and linear dichroism in few-layer black phosphorus. Nat. Commun. 5, 4475 (2014). \n47. Fiori, G. & Iannaccone, G. Multiscale modeling for graphene-based nanoscale transistors. Proc. IEEE 101, 1653–1669 (2013). \n48. Kaasbjerg, K., Thygesen, K. S. & Jacobsen, K. W. Phonon-limited mobility in n-type single-layer $\\ensuremath{\\mathrm{MoS}}_{2}$ from first principles. Phys. Rev. B 85, 115317 (2012). \n49. Koch, C. T. Determination of Core Structure Periodicity and Point Defect Density Along Dislocations. PhD thesis (Arizona State Univ., 2002). \n50. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n51. Grimme, S. Semiempirical GGA-type density functional constructed with a long-range dispersion correction. J. Comput. Chem. 27, 1787–1799 (2006). \n52. Blochl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n53. Klimes, J., Bowler, D. R. & Michaelides, A. Van der waals density functionals applied to solids. Phys. Rev. B 83, 195131 (2011). \n54. Dion, M., Rydberg, H., Schroder, E., Langreth, D. C. & Lundqvist, B. I. Van der Waals density functional for general geometries. Phys. Rev. Lett. 92, 246401 (2004). \n55. Lee, K., Murray, E. D., Kong, L., Lundqvist, B. I. & Langreth, D. C. Higheraccuracy van der waals density functional. Phys. Rev. B 82, 081101 (2010). \n\n# Acknowledgements \n\nThis work was financially supported by the National Basic Research Program of China under grant numbers 2012CB932704, 2014CB932500 and 2015CB921000; National Science Foundation of China under grant numbers 51222202, 11004244, 11274380, 91433103 and 51472215; and the Fundamental Research Funds for the Central Universities under grant numbers 2014XZZX003-07 (ZJU), 12XNLJ03 and 14XNH062 (RUC). JY and MP acknowledge the EPSRC (UK) funding (EP/G070326, EP/J022098 and EP/K013564). WJ was supported by the Program for New Century Excellent Talents in Universities. The work on electron microscopy was mainly done at the Center for Electron Microscopy of Zhejiang University. VASP Calculations were performed at the Physics Lab of High-Performance Computing of Renmin University of China and Shanghai Supercomputer Center, and Castep calculations were done in York. JY acknowledges Pao Yu-Kong International Foundation for a Chair Professorship. We thank Zheng Meng, Haiyan Nan and Zhenhua Ni for their assistance on PL measurements, Fang Lin for her assistance on provding the codes for Wiener filtering, and Yanfeng Zhang and Liying Jiao for providing high-quality CVD $\\mathbf{MoS}_{2}$ samples. We acknowledge Shengbai Zhang for his advice on formation mechanism of different defects and other calculations, and Wang Yao for his advices about the spin-valley effects in $\\mathrm{m}{\\cdot}\\mathrm{MoS}_{2}$ . \n\n# Author contributions \n\nJ.H. and Z.H. contributed equally to this work. C.J., J.Y. and W.J. conceived the research. J.H., D.L. and N.M. contributed to the sample preparations. J.H. and C.J did most of the STEM characterizations, with the assistance from K.L., X.Y., L.G. and X.Z., J.H., J.Y. and C.J. were responsible for the STEM data analysis and image simulations. Z.H., W.J. and M.P. did the DFT calculations. N.M., L.X. and J.H. contributed to the synthesis, measurement and analysis of PL spectra and the PVD devices of PVD samples. D.W. and Z.Z. contributed to the FET device fabrications and electric transport measurements on CVD samples. All authors discussed the results and contributed to the preparation of the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Hong, J. et al. Exploring atomic defects in molybdenum disulphide monolayers. Nat. Commun. 6:6293 doi: 10.1038/ncomms7293 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1126_sciadv.1500758", + "DOI": "10.1126/sciadv.1500758", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.1500758", + "Relative Dir Path": "mds/10.1126_sciadv.1500758", + "Article Title": "Three-dimensional printing of complex biological structures by freeform reversible embedding of suspended hydrogels", + "Authors": "Hinton, TJ; Jallerat, Q; Palchesko, RN; Park, JH; Grodzicki, MS; Shue, HJ; Ramadan, MH; Hudson, AR; Feinberg, AW", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "We demonstrate the additive manufacturing of complex three-dimensional (3D) biological structures using soft protein and polysaccharide hydrogels that are challenging or impossible to create using traditional fabrication approaches. These structures are built by embedding the printed hydrogel within a secondary hydrogel that serves as a temporary, thermoreversible, and biocompatible support. This process, termed freeform reversible embedding of suspended hydrogels, enables 3D printing of hydrated materials with an elastic modulus <500 kPa including alginate, collagen, and fibrin. Computer-aided design models of 3D optical, computed tomography, and magnetic resonullce imaging data were 3D printed at a resolution of similar to 200 mm and at low cost by leveraging open-source hardware and software tools. Proof-of-concept structures based on femurs, branched coronary arteries, trabeculated embryonic hearts, and human brains were mechanically robust and recreated complex 3D internal and external anatomical architectures.", + "Times Cited, WoS Core": 1275, + "Times Cited, All Databases": 1521, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000216598200039", + "Markdown": "# B I O M E D I C A L E N G I N E E R I N G \n\n# Three-dimensional printing of complex biological structures by freeform reversible embedding of suspended hydrogels \n\nThomas J. Hinton,1 Quentin Jallerat,1 Rachelle N. Palchesko,1 Joon Hyung Park,1 Martin S. Grodzicki,1 Hao-Jan Shue,1 Mohamed H. Ramadan,2 Andrew R. Hudson,1 Adam W. Feinberg1,3\\* \n\nWe demonstrate the additive manufacturing of complex three-dimensional (3D) biological structures using soft protein and polysaccharide hydrogels that are challenging or impossible to create using traditional fabrication approaches. These structures are built by embedding the printed hydrogel within a secondary hydrogel that serves as a temporary, thermoreversible, and biocompatible support. This process, termed freeform reversible embedding of suspended hydrogels, enables 3D printing of hydrated materials with an elastic modulus $<500\\mathsf{k P a}$ including alginate, collagen, and fibrin. Computer-aided design models of 3D optical, computed tomography, and magnetic resonance imaging data were 3D printed at a resolution of ${\\sim}200\\upmu\\mathrm{m}$ and at low cost by leveraging open-source hardware and software tools. Proof-of-concept structures based on femurs, branched coronary arteries, trabeculated embryonic hearts, and human brains were mechanically robust and recreated complex 3D internal and external anatomical architectures. \n\n# INTRODUCTION \n\nOver the past decade, the additive manufacturing (AM) of biomaterials has transitioned from a rapid prototyping tool used in research and development into a viable approach for the manufacturing of patientspecific medical devices. Key to this is the ability to precisely control structure and material properties in three dimensions and tailor these to unique anatomical and physiological criteria based on computed tomography (CT) and magnetic resonance imaging (MRI) medical imaging data. Firstin-human applications include customized polyetherketoneketone bone plates for the repair of large cranial defects $(1,2)$ and polycaprolactone bioresorbable tracheal splints for pediatric applications (3). The enabling three-dimensional (3D) printing technologies are primarily based on selective laser sintering of metal, ceramic, or thermoplastic microparticles; fused deposition modeling of thermoplastics, or on photopolymerization of photosensitive polymer resins (4, 5), and have tremendous growth potential for surgical and medical devices $(4,6)$ and scaffolds for tissue repair (7, 8). However, these approaches are limited in their ability to 3D print very soft materials such as elastomers, gels, and hydrogels that are integral components of many medical devices and are required for most future applications in tissue engineering and regenerative medicine (9, 10). Specifically, biological hydrogels composed of polysaccharides and/or proteins are a class of materials that are challenging to 3D print because they must first be gelled in situ during the fabrication process and then supported so that they do not collapse or deform under their own weight. Although the need for support materials is common across many AM techniques, it is particularly difficult for these soft biological hydrogels, where the elastic modulus is ${<}100\\mathrm{kPa}$ and there is a narrow range of thermal, mechanical, and chemical conditions that must be met to prevent damage to the materials and potentially integrated cells. \n\nCurrent approaches for the 3D printing of biological hydrogels have achieved important advances but are still in need of significant improvement $(9,I I)$ . For example, syringe-based extrusion has been used to 3D print polydimethylsiloxane (PDMS) elastomer and alginate hydrogel into multiple biological structures including the ear (12) and aortic heart valve (13, 14). Other research teams have demonstrated the direct bioprinting of fibrin (15, 16), gelatin (17), and mixtures of proteins derived from decellularized tissues (18) or cast extracellular matrix (ECM) gels around dissolvable templates (19). These results have expanded the range of materials that can be used and demonstrated the ability to incorporate and print live cells. There are also commercially available bioprinters from Organovo (20–22) and EnvisionTEC (7, 23) that have expanded the accessibility of bioprinters beyond the groups that custom build their own systems. However, the complexity of microstructures and the 3D anisotropy that can be created remain limited; often, the structures printed are simple square lattices, similar to stacked Lincoln Logs, which do not recapitulate the microstructure of real tissues. \n\nAs a field, significant improvements are still needed in terms of the ability to directly manufacture using biologically relevant hydrogels, controlling microstructure and anisotropy in 3D, and expanding biological AM research by driving down the cost of entry while increasing the quality and fidelity of the printing process. Our goal was to specifically address five major challenges including (i) deposition and crosslinking of soft biomaterials and viscous fluids with elastic moduli of ${<}100\\mathrm{kPa}$ , (ii) supporting these soft structures as they are printed so that they do not collapse or deform, (iii) anisotropically depositing the material to match the microstructure of real tissue, (iv) removing any support material that is used, and (v) keeping cells alive during this whole process using aqueous environments that are pH-, ionic-, temperature-, and sterility-controlled within tight tolerances (24–26). \n\n# RESULTS AND DISCUSSION \n\n# Using a thermoreversible support bath to enable freeform reversible embedding of suspended hydrogels \n\nHere, we report the development of a 3D bioprinting technique termed freeform reversible embedding of suspended hydrogels (FRESH). \n\nFRESH uses a thermoreversible support bath to enable deposition of hydrogels in complex, 3D biological structures and is implemented using open-source tools, serving as a highly adaptable and cost-effective biological AM platform. The key innovation in FRESH is deposition and embedding of the hydrogel(s) being printed within a second hydrogel support bath that maintains the intended structure during the print process and significantly improves print fidelity (Fig. 1, A and B, and movie S1). The support bath is composed of gelatin microparticles that act like a Bingham plastic during the print process, behaving as a rigid body at low shear stresses but flowing as a viscous fluid at higher shear stresses. This means that, as a needle-like nozzle moves through the bath, there is little mechanical resistance, yet the hydrogel being extruded out of the nozzle and deposited within the bath is held in place. Thus, soft materials that would collapse if printed in air are easily maintained in the intended 3D geometry. This is all done in a sterile, aqueous, buffered environment compatible with cells, which means cells can be extruded out of the printer nozzle with the hydrogel and maintain viability. Once the entire 3D structure is FRESH printed, the temperature is raised to a cell-friendly $37^{\\circ}\\mathrm{C},$ causing the gelatin support bath to melt in a nondestructive manner. Although Wu et al. (27) previously described 3D printing of a hydrogel ink within a hydrogel support bath for omnidirectional printing, the fugitive ink was designed to leave microchannels within a permanent support bath that was ultravioletly cross-linked afterward to repair nozzle-induced damage. In contrast, FRESH enables the direct 3D printing of biologically relevant hydrogel inks including alginate, fibrin, collagen type I, and Matrigel within a fugitive support bath designed to be removed afterward. \n\nFRESH is implemented on a MakerBot Replicator modified with a custom syringe-based extruder designed for precision hydrogel deposition. All plastic parts to convert the MakerBot into a bioprinter are printed in polylactic acid (PLA) using the stock thermoplastic extruder, which is then replaced with the custom syringe-based extruder [the STL (stereolithography) file can be downloaded from http://3dprint.nih.gov/]. Our syringe-based extruder uses the stepper motor, taken from the original extruder, to move the plunger of a 3-ml syringe via a direct gear drive (fig. S1). The overall size and mass is comparable to the original extruder and, once mounted, integrates seamlessly with the MakerBot hardware and software, requiring only calibration of the number of motor steps that extrudes a given volume of fluid. Typically, we use a $150\\mathrm{-}\\upmu\\mathrm{m}$ -diameter stainless steel needle on the end of the syringe, but a range of needle diameters can be selected to control the volume of material being extruded. \n\nThe FRESH support bath consists of a slurry of gelatin microparticles processed to have a Bingham plastic rheology. To do this, we blended a solid block of gelatin hydrogel to break up the material into microparticles and then centrifuged it to remove the supernatant and produce the final slurry (fig. S2). Increasing the blending time decreases microparticle size (Fig. 1C), with a blending time of $120\\ s$ producing microparticles with a mean Feret diameter of $55.3\\pm2\\upmu\\mathrm{m}$ (Fig. 1D). Rheometry confirmed that the gelatin slurry that was blended for $120s$ behaved like a Bingham plastic (Fig. 1E), not yielding until a threshold shear force is reached. Maintaining the gelatin slurry at room temperature $({\\sim}22^{\\circ}\\mathrm{C})$ preserves these rheological properties. For FRESH, the gelatin support slurry is loaded into a container of sufficient size to hold the part to be printed. In addition to its rheological and thermoreversible properties, gelatin was selected as the support bath material because it is biocompatible (28, 29). This is important, as it is unlikely that $100\\%$ of the gelatin is removed during the release process because it is a denatured form of collagen type I that can self-associate and bind to polysaccharides and other ECM proteins such as fibronectin (30, 31). Thus, it is unlikely that any small amount of residual gelatin will negatively affect cell integration and may actually enhance adhesion through integrin binding (32). \n\n![](images/ed25bf277ffe5404c8d36d9f9a913cde93c679e510ff6639379795cad26428ad.jpg) \nFig. 1. FRESH printing is performed by depositing a hydrogel precursor ink within the thermoreversible support bath consisting of gelatin microparticles and initiating gelling in situ through one of multiple cross-linking mechanisms. (A) A schematic of the FRESH process showing the hydrogel (green) being extruded and cross-linked within the gelatin slurry support bath (yellow). The 3D object is built layer by layer and, when completed, is released by heating to $37^{\\circ}\\mathsf{C}$ and melting the gelatin. (B) Images of the letters “CMU” FRESH printed in alginate in Times New Roman font (black) and released by melting the gelatin support (gray material in the petri dish). When the gelatin support melts the change in optical properties, convective currents and diffusion of black dye out of the alginate make it appear that the letters are deforming, although they are not. (C) Representative images of gelatin particles produced by blending for 30, 75, or 120 s. (D) The mean Feret diameter of gelatin particles as a function of blending time from 30 to $120s$ $(n>1000$ per time point; the red line is a linear fit and error bars indicate SD). (E) Rheological analysis of storage $(G)$ and loss $(G^{\\prime\\prime})$ modulus for gelatin support bath showing Bingham plastic behavior. Scale bars, 1 cm (B) and 1 mm (C). \n\n# Characterization of 3D printed hydrogels using FRESH \n\nFRESH works by extruding the liquid phase material from the syringe into the support bath, where the material must rapidly gel into a filament without diffusing away. This gelation process occurs via rapid cross-linking of the polymer molecules into a network, and the crosslinking mechanism depends on the hydrogel being 3D printed. We have validated this process using fluorescently labeled alginate crosslinked by divalent cations $(0.16\\%\\mathrm{CaCl}_{2}^{\\cdot}$ ) added to the support bath. A representative alginate filament embedded in the support bath illustrates that the gelatin microparticles are moved out of the way but still influence the surface morphology of the filament (Fig. 2A). As the alginate gels, there are visible “spurs” that form in between microparticles. However, these are not necessarily a problem in the context of a larger 3D printed structure because filaments fuse together to form the 3D printed part and thus these spurs may actually enhance this process by better bridging filaments. For this representative filament, the diameter of the extrusion was $199\\pm41{\\upmu\\mathrm{m}}$ (Fig. 2B). However, the diameter of the extruded hydrogel filament depends on a large number of factors including the hydrogel being printed and its cross-linking kinetics, gelatin microparticle size, nozzle diameter, extruder translation speed, and flow rate. Thus, similar to 3D printing of most materials, the resolution and morphology of a print depend on a number of machine settings and require optimization for each material used. \n\nAlthough the properties of single filaments are important, it is the ability of filaments to fuse into larger-scale structures that is required for 3D printing. Metal and plastic 3D printing typically produces parts that are $<100\\%$ solid, creating an external skin that is infilled using a repeating geometric structure with a defined porosity. For FRESH, we used rectilinear and octagonal infill algorithms to generate patterns of interconnected alginate filaments (Fig. 2, C to H). The rectilinear infill is a simple square lattice structure (Fig. 2C) that we FRESH printed at a ${500}{\\cdot}{\\upmu\\mathrm{m}}$ pitch (Fig. 2D). Confocal imaging and 3D rendering demonstrate that there is interconnectivity between filaments in the $x,y,$ , and $z$ axes (Fig. 2E). The octagonal infill is a more complex pattern of squares and octagons (Fig. 2F) that we FRESH printed at a $750\\mathrm{-}\\upmu\\mathrm{m}$ pitch (Fig. 2G). A 3D rendering again demonstrates the interconnectivity between filaments in the $x,y;$ , and $z$ axes (Fig. 2H). It should be noted that the fidelity of these infill patterns is comparable to that achieved using the stock thermoplastic extruder to print the same geometries in PLA, and further improvements are anticipated by performing FRESH on better hardware with optimized print parameters. \n\n![](images/549425645dbd0bd481f37caa7b86a1416f55ed01fc1f26cefbb9d6f26a8ccd03.jpg) \nFig. 2. Analysis of the hydrogel filaments and structures fabricated using FRESH. (A) A representative alginate filament (green) embedded within the gelatin slurry support bath (red). (B) Histogram of the diameter of isolated alginate filaments within the gelatin support bath showing a range from 160 to $260~{\\upmu\\mathrm{m}}$ . (C to E) A standard square lattice pattern commonly used for infill in 3D printing FRESH printed in fluorescent alginate (green) and viewed (D) top down and (E) in 3D. (F to H) An octagonal infill pattern FRESH printed in fluorescent alginate (green) and viewed (G) top down and (H) in 3D. (I) Example of a two-material print of coaxial cylinders in red and green fluorescently labeled alginate with a continuous interface shown in top down and lateral cross sections. (J) An example of a freeform, nonplanar FRESH print of a helix shown embedded in the gelatin support bath. (K) A zoomed-in view of the helix demonstrating that FRESH can print in true freeform and is not limited to standard layer-by-layer planar fabrication. Scale bars, $1\\:\\mathrm{mm}$ (A), $500~{\\upmu\\mathrm{m}}$ (D and G), $2{\\mathsf{m m}}$ (I), $10\\:\\mathrm{mm}$ (J), and $2.5~\\mathsf{m m}$ (K). \n\nFRESH can also be used to 3D print complex multimaterial parts and in nonplanar geometries. Dual syringe-based extruders can be mounted onto the MakerBot (fig. S1) and directly leverage the dualextruder printing capability built into the software to alternate between extruders (movie S2). To demonstrate dual-material printing, we printed two different fluorescently labeled alginates in concentric cylinders. Multiphoton imaging shows distinct layers, each $1\\mathrm{mm}$ wide, integrated together throughout a $3\\mathrm{-mm}$ thickness (Fig. 2I). Uniquely, FRESH is also not limited to standard layer-by-layer 3D printing and can freeform deposit material in 3D space with high fidelity as long as the extruder does not pass through previously deposited material. This is demonstrated by printing a single filament along a helical path (Fig. 2, J and K, and movie S3). This is a continuous, single filament with the extruder simultaneously moving in $x,y$ , and $z$ , showing the ability to deposit material in highly anisotropic structures in all three axes. \n\n# 3D printing of complex biological structures \n\nFRESH was next used to print complex biological structures based on medical imaging data to demonstrate its capability to fabricate complex geometries. Further, we wanted to validate that prints were mechanically robust and could be formed from multiple types of protein and polysaccharide hydrogels. First, a human femur from CT data (Fig. 3A) was scaled down to a length of ${\\sim}35\\mathrm{mm}$ and a minimum diameter of ${\\sim}2~\\mathrm{mm}$ and FRESH printed in alginate (Fig. 3B). The 3D printed femur only mimicked the external structure (surface) of the real femur and had a solid infill. Applying uniaxial strain showed that the femur could undergo ${\\sim}40\\%$ strain and recover elastically (Fig. 3C and movie S4), validating that there was mechanical fusion between the printed alginate layers. Further, the femur could be bent in half and elastically recover and, when strained to failure, fractured at an oblique angle to the long axis of the bone, confirming that failure was not due to layer delamination (movie S5). Next, we created a simple bifurcated tube in CAD (computer-aided design) to demonstrate the ability to FRESH print a hollow structure (fig. S3A). We used both the femur and bifurcated tube to show that other ECM hydrogels including collagen type I and fibrin can be FRESH printed with comparable fidelity to alginate (fig. S3, B to D, and movie S6). Printing multiple copies of the same bifurcated tube continuously for 4 hours also confirmed that the platform was thermally stable and that support bath rheological properties did not change over this period (fig. S3, C and D). Further, sheets of C2C12 myoblasts suspended in a mixture of fibrinogen, collagen type I, and Matrigel were printed at $20^{\\circ}\\mathrm{C}$ under sterile conditions and showed $99.7\\%$ viability by LIVE/DEAD staining (fig. S4, A and B). Multiday studies using C2C12 myoblasts and MC3T3 fibroblasts showed that cells were well distributed in 3D (fig. S4, C and E, respectively) and, over a 7-day culture period, formed a high-density cellular network (fig. S4, D and F, respectively). These examples demonstrate that FRESH can 3D print mechanically robust parts with biomimetic structure (Fig. 3C) and high repeatability (fig. S3, C and D) from a range of ECM hydrogels including collagen, fibrin, and Matrigel (figs. S3 and S4) and with embedded cells (fig. S4). \n\n![](images/b75ddbe48075f19d93bd5ee18d23621f663dbebcc995dca14cbc855cd9a64600.jpg) \nFig. 3. FRESH printing of biological structures based on 3D imaging data and functional analysis of the printed parts. (A) A model of a human femur from 3D CT imaging data is scaled down and processed into machine code for FRESH printing. (B) The femur is FRESH printed in alginate, and after removal from the support bath, it closely resembles the model and is easily handled. (C) Uniaxial tensile testing of the printed femur demonstrates the ability to be strained up to $40\\%$ and elastically recover. (D) A model of a section of a human right coronary arterial tree from 3D MRI is processed at full scale into machine code for FRESH printing. (E) An example of the arterial tree printed in alginate (black) and embedded in the gelatin slurry support bath. (F) A section of the arterial trees printed in fluorescent alginate (green) and imaged in 3D to show the hollow lumen and multiple bifurcations. (G) A zoomed-in view of the arterial tree shows the defined vessel wall that is $<1\\mathsf{m m}$ thick and the well-formed lumen. (H) A dark-field image of the arterial tree mounted in a perfusion fixture to position a syringe in the root of the tree. (I) A time-lapse image of black dye perfused through the arterial tree false-colored at time points of 0 to 6 s to show flow through the lumen and not through the vessel wall. Scale bars, $4\\mathsf{m m}$ (B), $10\\mathsf{m m}$ (E), $2.5\\mathsf{m m}$ (F), $1\\:\\mathrm{mm}$ (G), and $2.5~\\mathsf{m m}$ (H and I). \n\nAdditional mechanical characterization was performed by creating cast and 3D printed alginate dog bones (fig. S5A) and subjecting them to uniaxial tensile testing to generate stress-strain curves (fig. S5B), with the linear region from 5 to $20\\%$ strain used to calculate the elastic modulus (fig. S5C). Alginate is widely used in the tissue engineering field, and our results were comparable to those previously reported (33), although our gels were stiffer because of higher alginate and calcium concentrations. The cast alginate had a strain-to-failure of $42\\pm8\\%$ (fig. S5D), about two times that of the 3D printed alginate, and an elastic modulus of $446\\pm72\\mathrm{{kPa}}$ (fig. S5E), about nine times that of the 3D printed alginate. Part of this difference is because the 3D printed alginate dog bones were printed with $50\\%$ infill, effectively reducing the true cross-sectional area and introducing internal voids that initiated cracks at lower strains. Normalizing for the $50\\%$ infill by taking the cross-sectional area as half of that measured externally increased the elastic modulus from $51\\pm14\\mathrm{kPa}$ to $102\\pm27\\mathrm{kPa}$ , which is ${\\sim}25\\%$ of the cast alginate modulus. The lower mechanical properties of the 3D printed alginate were expected because the layer-by-layer fabrication approach is known to impart defects and material anisotropy (34, 35). However, these results, in combination with the straining of the 3D printed femur, demonstrate the mechanical fusion between printed layers and show that FRESH can be used to fabricate soft structures with mechanical integrity. \n\nWe next evaluated the ability to fabricate a more complex, perfusable structure using MRI data of part of the right coronary artery vascular tree and creating a hollow lumen with a wall thickness of $<1\\mathrm{mm}$ (Fig. 3D) (36). This was FRESH printed to scale with an overall length from trunk to tip of ${\\sim}4.5\\mathrm{cm}$ and contained multiple bifurcations with 3D tortuosity (Fig. 3E and movie S7). Arterial trees printed using fluorescent alginate confirmed that the internal lumens and bifurcations were well formed (Fig. 3F) and that a wall thickness of $<1\\mathrm{mm}$ and lumen diameters of 1 to $3\\mathrm{mm}$ were achieved (Fig. 3G). Detailed structural analysis comparing the 3D model (fig. S6A) to the 3D printed arterial tree (fig. S6B) showed good fidelity and accurate anatomical structure with $<15\\%$ variation in overall length and width and angles of the major bifurcations within $\\leq3^{\\circ}$ . Analysis of the wall thickness and lumen diameter confirmed that the 3D model (fig. S6C) was comparable to the 3D printed arterial tree (fig. S6D), although the printed wall thickness was increased and the lumen diameter decreased to ensure mechanical integrity of the overall vessel network for perfusion studies. A custom fixture to hold the arterial tree was 3D printed in PLA (Fig. 3H and fig. S7) and used to perfuse the print. Black dye pumped through the arterial tree confirmed that it was patent and manifold and that hydrogel density was sufficient to prevent diffusion through the wall (Fig. 3I and movie S8). Similar to the mechanical testing of the femur (Fig. 3C) and dog bones (fig. S5), the minimal diffusion through the arterial wall confirmed that the alginate layers were well fused together, forming a solid structure. \n\nFinally, we evaluated the ability to FRESH print 3D biological structures with complex internal and external architectures that would be extremely challenging or impossible to create using traditional fabrication techniques. First, we selected a day 5 embryonic chick heart (Fig. 4A) because of the complex internal trabeculations. We fixed and stained the heart for cell nuclei, F-actin, and fibronectin and generated a 3D optical image using confocal microscopy (Fig. 4B). The 3D optical image was then thresholded, segmented, and converted into a solid model for 3D printing (Fig. 4C and fig. S8). The diameter of the actual embryonic heart $(\\sim2.5~\\mathrm{mm})$ was scaled up by an order of magnitude $(\\sim2.5\\mathrm{cm})$ to better match the resolution of the printer and FRESH printed using fluorescently labeled alginate. The printed heart was then imaged using a multiphoton microscope to generate a cross section through the structure (Fig. 4D) showing internal trabeculation comparable to that in the model (Fig. 4C). Comparing the 3D model, G-code machine path, and final printed alginate heart (fig. S9, A to C) showed good co-registration of primary features when overlaid on one another (fig. S9, D to F). A dark-field image of the whole 3D printed heart provided further validation of print fidelity and the ability to fabricate complex internal structures down to the submillimeter length scale (Fig. 4E). Dimensional analysis comparing the 3D heart model (fig. S9G) to the 3D printed heart (fig. S9H) demonstrated nearly identical length, width, and size of major internal structures with $<10\\%$ variability. Overlaying images of the 3D model and printed heart helped further visualize the co-registration of the internal trabeculations and other anatomical features (fig. S9I). This embryonic heart is a good example of the types of structures that can be 3D printed with FRESH but are not possible to fabricate using traditional approaches because of the complex internal architecture. \n\nTo create complex external surface structures, we used an MRI image of the human brain (Fig. 4F) because of the intricate folds in the cortical tissues. A high-resolution view of the 3D brain model shows the surface in detail (Fig. 4G); however, the internal structure of the brain was solid infill. The embryonic heart model was scaled up in size, whereas the human brain model was scaled down to $3c m$ in length to evaluate the resolution limits of the printer and reduce print times. The model of the exterior surface of the human brain was 3D printed using alginate, and different regions including the frontal and temporal lobes of the cortex and the cerebellum were well defined (Fig. 4H). Visualization of the brain surface was enhanced with black dye and revealed structures corresponding to the major folds of the cerebral cortex in the 3D model (Fig. 4I and movie S9). A more detailed comparison confirmed the similar morphology of multiple surface folds of the cerebral cortex between the 3D model and the 3D printed brain (fig. S10). Together, both the 3D printed embryonic heart and brain demonstrate the unique ability of FRESH to print hydrogels with complex internal and external structures. \n\nLooking forward, can we leverage these FRESH bioprinting capabilities to engineer soft hydrogel scaffolds for advanced tissue engineering applications? In terms of complex scaffold design, our results demonstrate the ability to fabricate a wide range of 3D biological structures based on 3D imaging data with spatial resolution and fidelity that match or exceed previous results. Further, this is directly done with natural biopolymers such as alginate, fibrin, and collagen type I, which are cross-linked by ionic, enzymatic, and $\\mathrm{pH}/$ thermally driven mechanisms, respectively. This flexibility in materials used and architectures printed defines a new level of capability for the AM of soft materials. The square and octagonal infill patterns (Fig. 2, C to H) show results comparable to those achieved with thermoplastics (for example, PLA) printed on the stock MakerBot Replicator printer we used, suggesting that we may be limited by the hardware. We anticipate that higher resolution is possible using higher-precision printers, smaller-diameter needles, and gelatin slurries with a smaller particle diameter. Cost is also an important consideration for the future expansion of 3D bioprinting as a tissue biofabrication platform, as commercially available and custombuilt printers currently cost more than $\\$100,000$ and/or require specialized expertise to operate (7, 17, 20–23, 27). In contrast, FRESH is built on open-source hardware and software and the gelatin slurry is low cost and readily processed using consumer blenders. To emphasize the accessibility of the technology, we implemented FRESH on a $\\$400$ 3D printer (Printrbot Jr, movie S10) and the STL file to 3D print the custom syringe-based extruder can be downloaded from http:// 3dprint.nih.gov/. It should be acknowledged that the direct bioprinting of functional tissues and organs requires further research and development to become fully realized, and a number of companies and academic laboratories are actively working toward this goal. The low cost of FRESH and the ability to 3D print a range of hydrogels should enable the expansion of bioprinting into many academic and commercial laboratory settings and accelerate important breakthroughs in tissue engineering for a wide range of applications, from pharmaceutical testing to regenerative therapies. \n\n![](images/ae28a15d3f39921a15346f73b3dc1a73f91d093556e2d57022b0d1703c6c3417.jpg) \nFig. 4. FRESH printed scaffolds with complex internal and external architectures based on 3D imaging data from whole organs. (A) A darkfield image of an explanted embryonic chick heart. (B) A 3D image of the 5-day-old embryonic chick heart stained for fibronectin (green), nuclei (blue), and F-actin (red) and imaged with a confocal microscope. (C) A cross section of the 3D CAD model of the embryonic heart with complex internal trabeculation based on the confocal imaging data. (D) A cross section of the 3D printed heart in fluorescent alginate (green) showing recreation of the internal trabecular structure from the CAD model. The heart has been scaled up by a factor of 10 to match the resolution of the printer. (E) A dark-field image of the 3D printed heart with internal structure visible through the translucent heart wall. (F) A 3D rendering of a human brain from MRI data processed for FRESH printing. (G) A zoomed-in view of the 3D brain model showing the complex, external architecture of the white matter folds. (H) A lateral view of the brain 3D printed in alginate showing major anatomical features including the cortex and cerebellum. The brain has been scaled down to $\\sim3~\\mathsf{m m}$ in length to reduce printing time and test the resolution limits of the printer. (I) A top down view of the 3D printed brain with black dye dripped on top to help visualize the white matter folds printed in high fidelity. Scale bars, $1\\mathsf{m m}$ (A and B) and 1 cm (D, E, H, and I). \n\n# MATERIALS AND METHODS \n\n# Modification of a MakerBot Replicator for syringe-based extrusion \n\nAll 3D printing was performed using a MakerBot Replicator (MakerBot Industries) modified with a syringe-based extruder (fig. S1A). To do this, we removed the stock thermoplastic extruder assembly from the plastic $x\\cdot$ - axis carriage and replaced it with a custom-built syringe pump extruder (fig. S1, B and C). The syringe pump extruder was designed to use the NEMA-17 stepper motor from the original MakerBot thermoplastic extruder and mount directly in place of the extruder on the $x$ -axis carriage. The syringe pump extruder was printed in acrylonitrile butadiene styrene and PLA plastic using the thermoplastic extruder on the MakerBot before its removal. By using the same stepper motor, the syringe pump extruder was natively supported by the software that came with the printer. The design for the syringe pump extruder can be downloaded as an STL file from http://3dprint.nih.gov/ that can be printed on any RepRap or MakerBot 3D printer. In addition to a single extruder configuration, multiple syringe pump extruders could be mounted in a dual-extruder configuration, enabling 3D printing of multiple materials at one time (fig. S1D). No software modifications were necessary to operate the printer in single- or dual-extruder modes, aside from settings corresponding to nozzle diameter, filament diameter, and “start/end” G-code found in the software responsible for controlling the 3D printer. \n\n# Preparation and analysis of gelatin slurry support bath \n\nTo create the gelatin slurry support bath, we mixed $150\\mathrm{ml}$ of $4.5\\%$ (w/v) gelatin (Type A, Thermo Fisher Scientific) in $11\\mathrm{mM}\\mathrm{CaCl}_{2}$ (SigmaAldrich) into a solution and then gelled it for 12 hours at $4^{\\circ}\\mathrm{C}$ in a ${500}\\mathrm{-ml}$ mason jar (Ball Inc.). Next, $350~\\mathrm{ml}$ of $11\\mathrm{mM}\\mathrm{CaCl}_{2}$ at $4^{\\circ}\\mathrm{C}$ was added to the jar and its contents were blended (at “pulse” speed) for a period of 30 to $120\\ s$ on a consumer-grade blender (Osterizer MFG) (fig. S2A). Then, the blended gelatin slurry was loaded into $50\\mathrm{-ml}$ conical tubes (fig. S2B) and centrifuged at $4200~\\mathrm{rpm}$ for $2~\\mathrm{min}$ , causing slurry particles to settle out of suspension (fig. S2C). The supernatant was removed and replaced with $11\\mathrm{mM}\\mathrm{CaCl}_{2}$ at $4^{\\circ}\\mathrm{C}.$ . The slurry was vortexed back into suspension and centrifuged again. This process was repeated until no bubbles were observed at the top of the supernatant, which indicated that most of the soluble gelatin was removed. At this point, gelatin slurries could be stored at $4^{\\circ}\\mathrm{C}$ . For FRESH printing, the slurry was poured into a petri dish or a container large enough to hold the object to be printed (fig. S2D). Any excess fluid was removed from the gelatin slurry support bath using Kimwipes (Kimberly-Clark), which produced a slurry material that behaved like a Bingham plastic. All 3D printing was performed using gelatin blended for $120\\ s$ . \n\nTo measure the effect of blend time on gelatin particle size, we blended the gelatin for periods of 30, 45, 60, 75, 90, 105, and $120\\ s$ . Blend times longer than 120 s were not used because the gelatin particles began to entirely dissolve into the solution. For each blend time analyzed, $500\\upmu\\mathrm{l}$ of slurry was removed and diluted to $10\\mathrm{ml}$ with $11\\mathrm{mM}$ $\\mathrm{CaCl}_{2}$ and $0.1\\%$ (w/v) black food coloring (McCormick & Co.). Then, $140~\\upmu\\mathrm{l}$ of each diluted sample was mounted on a coverslip and imaged with a digital camera (D7000 SLR, Nikon) mounted on a stereomicroscope with oblique illumination (SMZ1000, Nikon). For each image, ImageJ (National Institutes of Health) (37) was used to enhance contrast, convert to LAB color space, and apply a lightness threshold. ImageJ was then used to count particles and measure their Feret diameters, areas, and circumferences using the “analyze particle” function. Linear regression of particle diameter as a function of time was performed using SigmaPlot 11 (Systat Software Inc.). \n\nTo measure the rheological properties of the gelatin slurry support bath, we blended the gelatin for $120s$ and then prepared it as described for the FRESH 3D printing process. The slurry was loaded onto a Gemini 200 Rheometer with a $40\\mathrm{-mm}$ , $4^{\\circ}$ cone (Malvern) and analyzed in frequency sweep from 0.001 to $100\\mathrm{Hz}$ at $150\\mathrm{-}\\upmu\\mathrm{m}$ separation and $25^{\\circ}\\mathrm{C}.$ The storage $\\left(G^{\\prime}\\right)$ and loss $\\left(G^{\\prime\\prime}\\right)$ moduli were measured and recorded in Microsoft Excel and plotted using SigmaPlot 11. \n\n# Preparation of hydrogel inks for 3D printing \n\nA solution of $2.0\\%$ (w/v) sodium alginate (FMC BioPolymer), $0.02\\%$ $\\left(\\mathbf{w}/\\mathbf{v}\\right)$ 6-aminofluorescein [fluorescein isothiocyanate (FITC), Sigma], $0.022\\%$ (w/v) 1-ethyl-3-(3dimethylaminopropyl)carbodiimide (Sigma), and $0.025\\%$ (w/v) sulfo- $N$ -hydroxysuccinimide (Sigma) in distilled water was prepared and stirred for 48 hours at $20^{\\circ}\\mathrm{C}$ to prepare fluorescently labeled alginate for 3D printing. Unreacted FITC was removed from FITC-labeled alginate by five consecutive 12-hour dialysis shifts against $2\\%$ (w/v) sodium alginate at $4^{\\circ}\\mathrm{C}$ in dialysis cassettes (Slide-A-Lyzer 3.5k MWCO, Thermo Fisher). After dialysis, $100\\upmu\\mathrm{l}$ of FITC-labeled alginate was added to a $\\scriptstyle10-{\\mathrm{ml}}$ solution of $4\\%$ $\\scriptstyle\\left(\\mathbf{w}/\\mathbf{v}\\right)$ sodium alginate, $0.4\\%$ (w/v) hyaluronic acid (Sigma), and $0.1\\%$ (w/v) black food coloring (for visualization during printing) to create a fluorescently labeled alginate ink. Fluorescent alginate prints were imaged using a Leica SP5 multiphoton microscope with a $10\\times$ [numerical aperture $(\\mathrm{NA})=0.4]$ objective and a $25\\times$ $\\mathrm{\\langleNA}=0.95$ ) water immersion objective. Higher-magnification images were obtained using a Zeiss LSM 700 confocal microscope with a $63\\times$ $(\\mathrm{NA}=1.4\\$ ) oil immersion objective. Bimaterial prints and arterial tree prints were imaged using a Nikon AZ-C2 macro confocal microscope with a $1\\times\\left(\\mathrm{NA}=0.1\\right)$ objective. 3D image stacks were deconvolved with AutoQuant X3 and processed with Imaris 7.5 (Bitplane Inc.). \n\nTo prepare fibrinogen for 3D printing of fibrin constructs, we prepared a solution of fibrinogen $\\mathrm{\\langle10mg/ml}$ ; VWR), $0.5\\%$ (w/v) hyaluronic acid (Sigma), $1\\%\\mathrm{(w/v)}$ bovine serum albumin (Sigma), $10\\mathrm{mM}$ sodium HEPES (Sigma), and $1\\times$ phosphate-buffered saline (PBS; VWR) and loaded it into a syringe for printing. To ensure crosslinking of the fibrinogen into fibrin once printed in the support bath, we supplemented the baths with thrombin $\\left(0.1\\mathrm{U}/\\mathrm{ml}\\right.$ ; VWR). Fibrin prints were released from the bath material by incubation at $37^{\\circ}\\mathrm{C}$ for at least 1 hour (fig. S3C). \n\nFor 3D printing of collagen, rat tail collagen type I (BD Biosciences) at concentrations ranging from 8.94 to $9.64~\\mathrm{mg/ml}$ in $0.02\\mathrm{~N~}$ acetic acid was used as received without further modification. To ensure cross-linking of collagen into a gel after extrusion, the support bath was supplemented with $10~\\mathrm{mM}$ HEPES to maintain a $\\mathsf{p H}$ of ${\\sim}7.4$ and neutralize the acetic acid. After printing, scaffolds were incubated at $37^{\\circ}\\mathrm{C}$ for at least 1 hour to further cross-link the collagen (fig. S3D) and melt the support bath. \n\nFor 3D printing of cellularized constructs, components of a multicomponent ECM ink were prepared at $4^{\\circ}\\mathrm{C}$ under sterile conditions in a biosafety cabinet. The ECM ink consisted of a solution of collagen type I $\\mathrm{(2~mg/ml)}$ BD Biosciences), Matrigel $0.25~\\mathrm{mg/ml}$ ; BD Biosciences), fibrinogen $\\mathrm{{'}10~m g/m l;}$ VWR), $0.5\\%$ (w/v) hyaluronic acid, $1\\%$ (w/v) bovine serum albumin (Sigma), $10\\ \\mathrm{mM}$ sodium HEPES (Sigma), and $1\\times$ PBS (VWR), which was prepared and thoroughly mixed at $4^{\\circ}\\mathrm{C}$ . This specific protein and polysaccharide mixture was experimentally determined to quickly gel while maintaining viability of printed cells. C2C12 myoblasts or MC3T3-E1.4 cells were suspended in media at a concentration of $\\mathrm{8\\times10^{6}~c e l l s/m l}$ and diluted 1:4 with the ECM mixture to create a final concentration of $2\\times$ ${10}^{6}$ cells/ml. The cellularized ink was then loaded into a sterile syringe used in the 3D printer. To ensure cross-linking of the ECM-based ink once printed, we supplemented the support bath with $10~\\mathrm{mM}$ HEPES and thrombin $(0.1~\\mathrm{U/ml})$ . \n\n# The FRESH 3D printing process \n\nDigital 3D models for FRESH prints were created using 3D imaging data or designed using SolidWorks software (Dassault Systèmes). The files for the human femur and coronary artery tree were downloaded from the BodyParts3D database (36). The model of the human brain was provided under creative commons licensing by A. Millns (Inition Co.). The 3D digital models were opened in MeshLab (http://meshlab.sourceforge.net/) to be exported in the STL file format. For the 3D model of the coronary artery tree, only the outer surface was provided by the BodyParts3D database; hence, the arterial tree was resampled to create a smaller daughter surface with inverted normals. When both surfaces were combined, a hollow model with internal and external surfaces with a wall thickness of ${\\sim}1~\\mathrm{mm}$ resulted, which was exported as an STL file for printing. \n\nAll STL files were processed by Skeinforge (http://fabmetheus. crsndoo.com/) or KISSlicer (www.kisslicer.com/) software and sliced into $80\\mathrm{-}\\upmu\\mathrm{m}$ -thick layers to generate G-code instructions for the 3D printer. G-code instruction sets were sent to the printer using ReplicatorG (http://replicat.org/), an open-source 3D printer host program. \n\nHydrogel precursor inks were first drawn into a $2.5–\\mathrm{ml}$ syringe (Model 1001 Gastight Syringe, Hamilton Company) with a $150\\mathrm{-}\\upmu\\mathrm{m}\\cdot$ - ID (inside diameter), 0.5-inch stainless steel deposition tip needle (McMaster-Carr) used as the nozzle to perform FRESH printing. The syringe was then mounted into the syringe pump extruder on the 3D printer (fig. S1, B and C). A petri dish or similar container large enough to hold the part to be printed was filled with the gelatin slurry support bath and manually placed on the build platform, and the container was held in place using a thin layer of silicone grease. The tip of the syringe needle was positioned at the center of the support bath in $x$ and $y$ and near the bottom of the bath in $z$ before executing the G-code instructions. It is important to initiate FRESH 3D printing within $30\\mathrm{{s}}$ of placing the syringe extruder in the support bath to avoid excessive cross-linking of material and clogging in the nozzle. Scaffolds were printed in a temperature-controlled room at $22\\pm1^{\\circ}\\mathrm{C}$ over a period of 1 min to 4 hours depending on the size and complexity of the printed construct as well as the ink used. For cellularized constructs, sterility was maintained by printing in a biosafety cabinet. Embedded constructs were heated to $37^{\\circ}\\mathrm{C}$ directly on the printer’s platform, placed on a dry bath, or placed inside an incubator to liquefy the support bath and release a print after FRESH. Once the gelatin was melted, alginate prints were rinsed with $11\\mathrm{\\mM}\\mathrm{CaCl}_{2}$ and stored at $4^{\\circ}\\mathrm{C}$ . Once the gelatin was melted for collagen and fibrin prints, the objects were rinsed with $1\\times$ PBS and stored at $4^{\\circ}\\mathrm{C}.$ . For multicomponent ECM prints containing cells, scaffolds were rinsed with the appropriate culture medium based on the incorporated cell types and incubated at $37^{\\circ}\\mathrm{C}$ . \n\n# Cell culture and fluorescent staining \n\nAll reagents were purchased from Life Technologies unless otherwise specified. The MC3T3-E1.4 fibroblast cell line and prints containing MC3T3 cells [CRL-2593, American Type Culture Collection (ATCC)] were cultured in $\\mathbf{\\alpha}_{\\mathrm{~\\mathfrak{~a~}~}}$ -MEM (minimum essential medium) supplemented with $10\\%$ fetal bovine serum (FBS; Gibco Labs), penicillin $\\left(100~\\mathrm{U/ml}\\right)$ , and streptomycin $(100\\mathrm{\\upmug/ml)}$ . The C2C12 myoblast cell line and prints containing C2C12 cells (CRL-1722, ATCC) were cultured at $37^{\\circ}\\mathrm{C}$ under $5\\%$ $\\mathrm{CO}_{2}$ in Dulbecco’s modified Eagle’s medium supplemented with $10\\%$ $\\left(\\mathbf{v}/\\mathbf{v}\\right)$ FBS, $1\\%$ (v/v) L-glutamine $(200~\\mathrm{mM})$ ), penicillin $\\left(100~\\mathrm{U/ml}\\right)$ , and streptomycin $(100~\\mathrm{\\upmug/ml})$ , based on published methods (38). \n\nCell viability after FRESH printing was assessed by performing a LIVE/DEAD assay (Life Technologies) on prints containing C2C12 cells (fig. S4, A and B). Each print was first washed with Opti-MEM media containing $2\\%$ FBS and $2\\%$ 10,000-U penicillin-streptomycin solution and incubated at $37^{\\circ}\\mathrm{C}$ under $5\\%\\mathrm{CO}_{2}$ for $30\\mathrm{min}$ . The prints were then removed from the incubator, rinsed with $1\\times\\mathrm{PBS}$ , incubated in $2~\\mathrm{ml}$ of PBS with $2\\upmu\\mathrm{l}$ of calcein AM and $4\\upmu\\mathrm{l}$ of ethidium homodimer per sample for $30\\mathrm{min}$ , and then imaged on a Zeiss LSM 700 confocal microscope. The number of live and dead cells in each of the five images per three independent samples was counted and the percent viability was calculated by dividing the number of live cells by the number of total cells per image. \n\nPrints containing cells were cultured for up to 7 days and analyzed at 1- and 7-day time points to verify cell survival and growth. After 1 and 7 days of culture, printed sheets were rinsed with $1\\times\\mathrm{PBS}$ (supplemented with $0.625\\mathrm{mMMgCl_{2}}$ and $0.109\\mathrm{mMCaCl}_{2}^{\\cdot}$ ) at $37^{\\circ}\\mathrm{C},$ fixed in $4\\%$ (w/v) formaldehyde (Polysciences Inc.) for $15~\\mathrm{min}$ , and then washed three times in $1\\times\\mathrm{PBS}$ . Fixed prints were incubated for 12 hours in a 1:200 dilution of $^{4^{\\prime},6}$ -diamidino-2-phenylindole (DAPI; Life Technologies) and a 3:200 dilution of phalloidin conjugated to Alexa Flour 488 (Life Technologies). Prints were then washed three times in PBS and mounted with ProLong Gold antifade reagent (Life Technologies) between a microscope glass slide and an N1.5 glass coverslip. The mounted samples were stored at room temperature and protected from light for 12 hours to allow the ProLong reagent to cure. Prints were imaged using a Leica SP5 multiphoton microscope with a $10\\times\\mathrm{(NA=0.4)}$ objective and a $25\\times$ $(\\mathrm{NA}=0.95)$ ) water immersion objective. 3D image stacks were deconvolved with AutoQuant X3 and processed with Imaris 7.5. \n\n# Perfusion of 3D printed coronary arterial tree \n\nTo evaluate whether the 3D printed arterial tree was manifold, we mounted it in a custom-made 3D printed perfusion fixture (fig. S7, A and B). A solution of $11\\mathrm{mMCaCl}_{2}$ (Sigma) and $0.1\\%$ (w/v) black food coloring was injected into the root of the tree using a standard $3{\\cdot}\\mathrm{ml}$ syringe (BD Biosciences) with a $150\\mathrm{-}\\upmu\\mathrm{m}$ -ID, 0.5-inch needle, and the tip at the end of each branch was cut off to permit outflow. Perfusion was captured with a digital camera (D7000 SLR, Nikon) mounted on a stereomicroscope with oblique illumination (SMZ1000, Nikon). \n\n# Creation of a 3D model of the heart of a 5-day-old chick embryo \n\nThe 3D model of the embryonic chick heart was generated from 3D optical imaging data of a fluorescently labeled 5-day-old heart. Fertilized eggs of White Leghorn chicken were incubated at $37^{\\circ}\\mathrm{C}$ and $50\\%$ humidity for 5 days to do this. Then, the embryo [HamburgerHamilton stage 27 to 28 (39)] was explanted and the heart (ventricles, atria, and outflow tract) was dissected and fixed for $15~\\mathrm{min}$ in PBS with calcium, magnesium, and $4\\%$ formaldehyde. After being washed in PBS, the heart was blocked and permeabilized for 2 hours at $37^{\\circ}\\mathrm{C}$ in PBS with $0.1\\%$ Triton X-100 and $5\\%$ goat serum. Two steps of immunostaining were carried out overnight at $4^{\\circ}\\mathrm{C}$ . The first stain used dilutions of 1:200 DAPI, 3:100 phalloidin conjugated to Alexa Fluor 633 (Life Technologies), and 1:100 anti-fibronectin primary antibody (mouse, Sigma-Aldrich). After being extensively washed in PBS, the samples were stained with a 1:100 dilution of goat anti-mouse secondary antibody conjugated to Alexa Fluor 546 (Life Technologies). Samples were then washed and dehydrated by immersion in successive solutions of PBS with an increasing concentration of isopropyl alcohol as previously described (40). Finally, the samples were cleared by transferring to a solution of 1:2 benzyl alcohol/benzyl benzoate (BABB) to match the refractive index of the tissue. The transparent sample was mounted in BABB and imaged with a Nikon AZ-C2 macro confocal microscope with a $5\\times$ objective $(\\mathrm{NA}=0.45$ ). \n\nThe 3D image stack was deconvolved using AutoQuant X3 and processed with Imaris 7.5, MATLAB (MathWorks), and ImageJ. The DAPI (fig. S8A), actin (fig. S8B), and fibronectin (fig. S8C) channels were merged to obtain an image with the simultaneously well-defined trabeculae and outer wall of the heart (fig. S6D). A detailed mask of the heart showing the trabeculae was created by segmenting the averaged signals using a high-pass threshold (fig. S8E). A rough mask showing the bulk of the heart was obtained using a low-pass threshold (fig. S8F). Next, the Imaris “Distance Transform” XTension was used on the bulk mask to create a closed shell of the outer wall of the heart. The high-detail mask and the mask of the closed shell were combined to obtain a complex model of the heart with detailed trabeculae and a completely closed outer wall (fig. S6G). The final model was smoothed and segmented using Imaris to preserve a level of detail adequate for 3D printing (fig. S8H). A 3D solid object was created by exporting the smoothed model as an STL file using the Imaris XT module and the “Surfaces to $\\operatorname{srL}^{\\mathfrak{N}}$ Xtension for MATLAB (fig. S8, I and J). \n\n# Mechanical characterization \n\nMechanical characterization comparing 3D printed and cast alginate constructs was performed using uniaxial tensile testing, adapted from our previously published method for characterizing soft PDMS (41). Briefly, tensile bar strips (dog bones) of $4\\%$ (w/v) alginic acid in $11\\mathrm{\\mM\\CaCl_{2}}$ were either 3D printed using the FRESH method or cast into laser-cut acrylic molds consisting of a grip section $(7\\times10\\mathrm{mm})$ , a reduced section $(3.45\\times25~\\mathrm{mm})$ ), and ${\\sim}1~\\mathrm{mm}$ thickness. The 3D printed strips were fabricated with a $250\\mathrm{-}\\upmu\\mathrm{m}$ -diameter nozzle in a slurry containing $\\boldsymbol{1}\\boldsymbol{1}\\mathrm{mMCaCl}_{2}$ . Settings for the 3D printed strips were $100\\mathrm{-}\\upmu\\mathrm{m}$ layers, $50\\%$ octagonal infill, and 1 perimeter. The width and thickness of each test strip were individually measured before mechanical analysis. Uniaxial tensile testing $\\overset{\\cdot}{n}=6$ of each type) was performed on an Instron 5943 (Instron) at a strain rate of $5\\mathrm{mm/min}$ until failure. The elastic modulus of each sample was determined from the slope of the linear region of the stress-strain curves from 5 to $20\\%$ (or until failure, if it failed before $20\\%$ ). \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/1/9/e1500758/DC1 \n\nFig. S1. Modification of an open-source 3D printer for FRESH printing. \nFig. S2. Preparation of the gelatin slurry support bath. \nFig. S3. Examples of 3D printed bifurcated tubes using alginate, fibrin, and collagen. \nFig. S4. 3D printed sheets of cells and ECM. \nFig. S5. Mechanical characterization of cast and 3D printed alginate dog bones using uniaxial tensile testing. \nFig. S6. A comparison of the 3D model and 3D printed arterial tree to assess print fidelity. \nFig. S7. A 3D printed perfusion fixture for the right coronary arterial tree. \nFig. S8. Generation of a 3D model of the embryonic heart from confocal microscopy. \nFig. S9. A comparison of the 3D model and 3D printed embryonic heart to assess print fidelity. \nFig. S10. A comparison of the 3D model and 3D printed brain. \nMovie S1. Time lapse of FRESH printing and heated release of the “CMU” logo. \nMovie S2. FRESH printing using the dual syringe pump extruders. \nMovie S3. Out-of-plane FRESH printing of a helix. \nMovie S4. Uniaxial strain of a FRESH printed femur model showing elastic recovery. \nMovie S5. Strain to failure of a FRESH printed femur. \nMovie S6. FRESH printing of soft collagen type I constructs. \nMovie S7. Time-lapse video of a coronary arterial tree being FRESH printed. \nMovie S8. Perfusion of a FRESH printed coronary arterial tree. \nMovie S9. Visualization of the 3D structure of a FRESH printed brain model. \nMovie S10. Modification of a sub-\\$400 3D printer for FRESH printing. \n\n# REFERENCES AND NOTES \n\n1. A. M. Shah, H. Jung, S. Skirboll, Materials used in cranioplasty: A history and analysis. Neurosurg. Focus 36, E19 (2014). \n2. FDA 510(k) summary statement for Osteofab Patient Specific Cranial Device. Report Number K121818, Center for Devices and Radiological Health (2013), http://www.accessdata. fda.gov/cdrh_docs/pdf12/K121818.pdf (viewed 10/11/15). 3. D. A. Zopf, S. J. Hollister, M. E. Nelson, R. G. Ohye, G. E. Green, Bioresorbable airway splint created with a three-dimensional printer. N. Engl. J. Med. 368, 2043–2045 (2013). \n4. S. K. Bhatia, S. Sharma, 3D-printed prosthetics roll off the presses. Chem. Eng. Prog. 110, 28–33 (2014), www.aiche.org/sites/default/files/cep/20140528.pdf (viewed 10/12/15). \n5. J. R. Tumbleston, D. Shirvanyants, N. Ermoshkin, R. Janusziewicz, A. R. Johnson, D. Kelly, K. Chen, R. Pinschmidt, J. P. Rolland, A. Ermoshkin, E. T. Samulski, J. M. DeSimone, Additive manufacturing. Continuous liquid interface production of 3D objects. Science 347, 1349–1352 (2015). \n6. J. N. Fullerton, G. C. M. Frodsham, R. M. Day, 3D printing for the many, not the few. Nat. Biotechnol. 32, 1086–1087 (2014). \n7. C. H. Lee, S. A. Rodeo, L. Ann Fortier, C. Lu, C. Erisken, J. J. Mao, Protein-releasing polymeric scaffolds induce fibrochondrocytic differentiation of endogenous cells for knee meniscus regeneration in sheep. Sci. Transl. Med. 6, 266ra171 (2014). \n8. B. Derby, Printing and prototyping of tissues and scaffolds. Science 338, 921–926 (2012). \n9. S. V. Murphy, A. Atala, 3D bioprinting of tissues and organs. Nat. Biotechnol. 32, 773–785 (2014). \n10. I. Martin, P. J. Simmons, D. F. Williams, Manufacturing challenges in regenerative medicine. Sci. Transl. Med. 6, 232fs16 (2014). \n11. G. Sinha, Cell presses. Nat. Biotechnol. 32, 716–719 (2014). \n12. M. S. Mannoor, Z. Jiang, T. James, Y. Lin Kong, K. A. Malatesta, W. O. Soboyejo, N. Verma, D. H. Gracias, M. C. McAlpine, 3D printed bionic ears. Nano Lett. 13, 2634–2639 (2013). \n13. L. A. Hockaday, K. H. Kang, N. W. Colangelo, P. Y. C. Cheung, B. Duan, E. Malone, J. Wu, L. N. Girardi, L. J. Bonassar, H. Lipson, C. C. Chu, J. T. Butcher, Rapid 3D printing of anatomically accurate and mechanically heterogeneous aortic valve hydrogel scaffolds. Biofabrication 4, 035005 (2012). \n14. B. Duan, L. A. Hockaday, K. H. Kang, J. T. Butcher, 3D bioprinting of heterogeneous aortic valve conduits with alginate/gelatin hydrogels. J. Biomed. Mater. Res. A 101A, 1255–1264 (2013). \n15. X. Cui, T. Boland, Human microvasculature fabrication using thermal inkjet printing technology. Biomaterials 30, 6221–6227 (2009). \n16. T. Xua, C. A. Gregorya, P. Molnara, X. Cuia, S. Jalotab, S. B. Bhadurib, T. Bolanda, Viability and electrophysiology of neural cell structures generated by the inkjet printing method. Biomaterials 27, 3580–3588 (2006). \n17. D. B. Kolesky, R. L. Truby, A. Sydney Gladman, T. A. Busbee, K. A. Homan, J. A. Lewis, 3D bioprinting of vascularized, heterogeneous cell-laden tissue constructs. Adv. Mater. 26, 3124–3130 (2014). \n18. F. Pati, J. Jang, D.-H. Ha, S. Won Kim, J.-W. Rhie, J.-H. Shim, D.-H. Kim, D.-W. Cho, Printing three-dimensional tissue analogues with decellularized extracellular matrix bioink. Nat. Commun. 5, 3935 (2014). \n19. J. S. Miller, K. R. Stevens, M. T. Yang, B. M. Baker, D.-H. T. Nguyen, D. M. Cohen, E. Toro, A. A. Chen, P. A. Galie, X. Yu, R. Chaturvedi, S. N. Bhatia, C. S. Chen, Rapid casting of patterned vascular networks for perfusable engineered three-dimensional tissues. Nat. Mater. 11, 768–774 (2012). \n20. F. Marga, K. Jakab, C. Khatiwala, B. Shepherd, S. Dorfman, B. Hubbard, S. Colbert, G. Forgacs, Toward engineering functional organ modules by additive manufacturing. Biofabrication 4, 022001 (2012). \n21. K. Jakab, C. Norotte, F. Marga, K. Murphy, G. Vunjak-Novakovic, G. Forgacs, Tissue engineering by self-assembly and bio-printing of living cells. Biofabrication 2, 022001 (2010). \n22. C. Norotte, F. S. Marga, L. E. Niklason, G. Forgacs, Scaffold-free vascular tissue engineering using bioprinting. Biomaterials 30, 5910–5917 (2009). \n23. A. Lantada, in Handbook on Advanced Design and Manufacturing Technologies for Biomedical Devices, A. D. Lantada, Ed. (Springer US, New York, 2013), pp. 261–275. \n24. F. P. W. Melchels, M. A. N. Domingos, T. J. Klein, J. Malda, P. J. Bartolo, D. W. Hutmacher, Additive manufacturing of tissues and organs. Prog. Polym. Sci. 37, 1079–1104 (2012). \n25. S. Tasoglu, U. Demirci, Bioprinting for stem cell research. Trends Biotechnol. 31, 10–19 (2013). \n26. I. T. Ozbolat, Y. Yu, Bioprinting toward organ fabrication: Challenges and future trends. IEEE Trans. Biomed. Eng. 60, 691–699 (2013). \n27. W. Wu, A. DeConinck, J. A. Lewis, Omnidirectional printing of 3D microvascular networks. Adv. Mater. 23, H178–H183 (2011). \n28. J. M. Dang, K. W. Leong, Natural polymers for gene delivery and tissue engineering. Adv. Drug Deliv. Rev. 58, 487–499 (2006). \n29. S. Young, M. Wong, Y. Tabata, A. G. Mikos, Gelatin as a delivery vehicle for the controlled release of bioactive molecules. J. Control. Release 109, 256–274 (2005). \n30. E. Engvall, E. Ruoslahti, E. J. Miller, Affinity of fibronectin to collagens of different genetic types and to fibrinogen. J. Exp. Med. 147, 1584–1595 (1978). \n31. Y. A. Antonov, N. P. Lashko, Y. K. Glotova, A. Malovikova, O. Markovich, Effect of the structural features of pectins and alginates on their thermodynamic compatibility with gelatin in aqueous media. Food Hydrocoll. 10, 1–9 (1996). \n32. J.-S. Chun, M.-J. Ha, B. S. Jacobson, Differential translocation of protein kinase C e during HeLa cell adhesion to a gelatin substratum. J. Biol. Chem. 271, 13008–13012 (1996). \n33. J. L. Drury, R. G. Dennis, D. J. Mooney, The tensile properties of alginate hydrogels. Biomaterials 25, 3187–3199 (2004). \n34. A. Bellini, S. Güçeri, Mechanical characterization of parts fabricated using fused deposition modeling. Rapid Prototyping J. 9, 252–264 (2003). \n35. A. Farzadi, M. Solati-Hashjin, M. Asadi-Eydivand, N. A. Abu Osman, Effect of layer thickness and printing orientation on mechanical properties and dimensional accuracy of 3D printed porous samples for bone tissue engineering. PLOS One 9, e108252 (2014). \n36. N. Mitsuhashi, K. Fujieda, T. Tamura, S. Kawamoto, T. Takagi, K. Okubo, BodyParts3D: 3D structure database for anatomical concepts. Nucleic Acids Res. 37, D782–D785 (2009). \n37. C. A. Schneider, W. S. Rasband, K. W. Eliceiri, NIH image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012). \n38. Y. Sun, R. Duffy, A. Lee, A. W. Feinberg, Optimizing the structure and contractility of engineered skeletal muscle thin films. Acta Biomater. 9, 7885–7894 (2013). \n39. V. Hamburger, H. L. Hamilton, A series of normal stages in the development of the chick embryo. J. Morphol. 88, 49–92 (1951). \n40. H. Y. Kim, L. A. Davidson, Punctuated actin contractions during convergent extension and their permissive regulation by the non-canonical Wnt-signaling pathway. J. Cell Sci. 124, 635–646 (2011). \n41. R. N. Palchesko, L. Zhang, Y. Sun, A. W. Feinberg, Development of polydimethylsiloxane substrates with tunable elastic modulus to study cell mechanobiology in muscle and nerve. PLOS One 7, e51499 (2012). \n\nAcknowledgments: We thank M. Blank for technical assistance with uniaxial tensile testing. Funding: This work was supported in part by the NIH Director’s New Innovator Award (DP2HL117750) and the NSF CAREER Award (1454248). Author contributions: T.J.H., Q.J., and A.W.F. designed the research, analyzed data, and wrote the paper. T.J.H., Q.J., J.H.P., M.S.G., H.-J.S., R.N.P., M.H.R., and A.R.H. performed the research. Competing interests: Carnegie Mellon University has filed for patent protection on the technology described herein, and T.J.H. and A.W.F. are named as inventors on the patent. Data and materials availability: The data presented here are available from http://dx.doi.org/10.5061/dryad.tp4cp. The 3D STL models of the syringe pump extruder and the embryonic chick heart are available at http://3dprint.nih.gov/. \n\nSubmitted 10 June 2015 \nAccepted 2 September 2015 \nPublished 23 October 2015 \n10.1126/sciadv.1500758 \n\nCitation: T. J. Hinton, Q. Jallerat, R. N. Palchesko, J. H. Park, M. S. Grodzicki, H.-J. Shue, M. H. Ramadan, A. R. Hudson, A. W. Feinberg, Three-dimensional printing of complex biological structures by freeform reversible embedding of suspended hydrogels. Sci. Adv. 1, e1500758 (2015). \n\nThree-dimensional printing of complex biological structures by freeform reversible embedding of suspended hydrogels Thomas J. Hinton, Quentin Jallerat, Rachelle N. Palchesko, Joon Hyung Park, Martin S. Grodzicki, Hao-Jan Shue, Mohamed H. Ramadan, Andrew R. Hudson and Adam W. Feinberg (October 23, 2015) \nSci Adv 2015, 1:. \ndoi: 10.1126/sciadv.1500758 \n\nThis article is publisher under a Creative Commons license. The specific license under which this article is published is noted on the first page. \n\nFor articles published under CC BY licenses, you may freely distribute, adapt, or reuse the article, including for commercial purposes, provided you give proper attribution. \n\nFor articles published under CC BY-NC licenses, you may distribute, adapt, or reuse the article for non-commerical purposes. Commercial use requires prior permission from the American Association for the Advancement of Science (AAAS). You may request permission by clicking here. \n\nThe following resources related to this article are available online at http://advances.sciencemag.org. (This information is current as of October 24, 2015): \n\nUpdated information and services, including high-resolution figures, can be found in the \nonline version of this article at: \nhttp://advances.sciencemag.org/content/1/9/e1500758.full.html \n\nSupporting Online Material can be found at: http://advances.sciencemag.org/content/suppl/2015/10/20/1.9.e1500758.DC1.html \n\nThis article cites 39 articles,8 of which you can be accessed free: http://advances.sciencemag.org/content/1/9/e1500758#BIBL " + }, + { + "id": "10.1038_ncomms8747", + "DOI": "10.1038/ncomms8747", + "DOI Link": "http://dx.doi.org/10.1038/ncomms8747", + "Relative Dir Path": "mds/10.1038_ncomms8747", + "Article Title": "Non-wetting surface-driven high-aspect-ratio crystalline grain growth for efficient hybrid perovskite solar cells", + "Authors": "Bi, C; Wang, Q; Shao, YC; Yuan, YB; Xiao, ZG; Huang, JS", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Large-aspect-ratio grains are needed in polycrystalline thin-film solar cells for reduced charge recombination at grain boundaries; however, the grain size in organolead trihalide perovskite (OTP) films is generally limited by the film thickness. Here we report the growth of OTP grains with high average aspect ratio of 2.3-7.9 on a wide range of non-wetting hole transport layers (HTLs), which increase nucleus spacing by suppressing heterogeneous nucleation and facilitate grain boundary migration in grain growth by imposing less drag force. The reduced grain boundary area and improved crystallinity dramatically reduce the charge recombination in OTP thin films to the level in OTP single crystals. Combining the high work function of several HTLs, a high stabilized device efficiency of 18.3% in low-temperature-processed planar-heterojunction OTP devices under 1 sun illumination is achieved. This simple method in enhancing OTP morphology paves the way for its application in other optoelectronic devices for enhanced performance.", + "Times Cited, WoS Core": 1462, + "Times Cited, All Databases": 1526, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000358858500053", + "Markdown": "# Non-wetting surface-driven high-aspect-ratio crystalline grain growth for efficient hybrid perovskite solar cells \n\nCheng Bi1,2, Qi Wang1,2, Yuchuan Shao1,2, Yongbo Yuan1,2, Zhengguo Xiao1,2 & Jinsong Huang1,2 \n\nLarge-aspect-ratio grains are needed in polycrystalline thin-film solar cells for reduced charge recombination at grain boundaries; however, the grain size in organolead trihalide perovskite (OTP) films is generally limited by the film thickness. Here we report the growth of OTP grains with high average aspect ratio of 2.3–7.9 on a wide range of non-wetting hole transport layers (HTLs), which increase nucleus spacing by suppressing heterogeneous nucleation and facilitate grain boundary migration in grain growth by imposing less drag force. The reduced grain boundary area and improved crystallinity dramatically reduce the charge recombination in OTP thin films to the level in OTP single crystals. Combining the high work function of several HTLs, a high stabilized device efficiency of $18.3\\%$ in low-temperature-processed planar-heterojunction OTP devices under 1 sun illumination is achieved. This simple method in enhancing OTP morphology paves the way for its application in other optoelectronic devices for enhanced performance. \n\nrganolead triiodide perovskite (OTP)-based solar cells have been attracting increasing attention from the solar energy community in the past few years due to the rapid increase of device power conversion efficiency (PCE) to the level of silicon solar cells and low-cost prospectus of this technology in terms of raw materials and device fabrication1–11. Nearly every important progress in device efficiency enhancement counts on the improved material quality of the OTP films for both mesoporous structure and planar heterojunction (PHJ) structure OTP devices1–3,12–17. Similar to any polycrystalline thin film solar cells, larger OTP grains with less grain boundaries have been shown to increase the efficiency of OTP devices3,12. More evidences have shown that grain boundaries in OTP films might cause increasing charge recombination due to the presence of large density of charge traps4,13,14,18–20. Our recent studies have shown that the carrier diffusion length can be boosted to record value of above $200\\upmu\\mathrm{m}$ under 1 sun illumination and larger than $3\\mathrm{mm}$ under weak light at room temperature for both electrons and holes in OTP single crystals that have no grain boundaries14. Although it is plausible to develop record high efficiency device with the OTP single crystals, the increasing material cost and lacking of techniques to scale up OTP single-crystal growth disgrace its prospectus for large-area, low-cost solar panels. An ideal OTP solar cell should have thin OTP layers with thickness sufficient to absorb most of the sun light, which is around $300{-}600\\mathrm{nm}$ thanks to the very high extinction efficiency of OTP materials6, and with grain size as large as the cells to simulate the single-crystal solar cells. However, the size of the OTP grains grown by many methods is generally limited by the film thickness of the OTP films3,12,21. \n\nA trick to grow large-size clear single-crystal ices is to use clean, smooth and non-wetting plastic container to prevent the formation of too dense nuclei from heterogeneous nucleation. In this manuscript, we used the same trick to grow OTP films with large crystalline grains on a wide range of non-wetting hole transport layers (HTLs). The average grain size/thickness aspect ratio in the OTP films grown on non-wetting HTLs reaches 2.3–7.9, which dramatically reduces charge trap density by 10–100-fold and boosts the PCE of OTP planar heterojunction solar cells to $18.3\\%$ . \n\n# Results \n\nMechanism of OTP grain growth on non-wetting surfaces. The mechanism of growing large-size OTP grain on non-wetting surfaces is illustrated in Fig. 1, which shows the difference of nucleation and grain growth process on a wetting and a nonwetting surface. Here the two-step thermal annealing-assisted interdiffusion method was employed that forms continuous and pinhole-free OTP films12. The first step of OTP film formation is OTP nucleation on the substrates after the chemical reaction of $\\mathrm{PbI}_{2}$ and MAI (MA is methylammonium). Then the followed drying and thermal annealing processes drive the interdiffusion and complete reaction of the two precursors, which forms and grows the OTP grains. It has been shown that thermal annealing increases the OTP grain size to above $300\\mathrm{nm}$ on the wetting surface of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), after $^{2\\mathrm{h}}$ annealing at $105^{\\circ}\\mathrm{C},$ while further increasing of thermal annealing time causes the decomposition of OTP films without significantly increasing the grain size. It indicates the grain boundaries were pinned, most likely, by the impurities lying in the grain boundaries22. Adding solvent vapour during thermal annealing can de-pin the grain boundary and drive larger grain formation, however, the average grain size in OTP films grown on PEDOT:PSS is still limited to be the film thickness12. Another feature of the solvent-annealed OTP films is the presence of some small grains close to PEDOT:PSS side and tilted grain boundaries between the large grains, as shown in cross-section scanning electron microscopy (SEM) image in Supplementary Fig. 1. This can be explained by the surface tension dragging force from the wetting PEDOT:PSS substrates, which reduces the grain boundary mobility. Such dragging force dramatically diminishes if the substrate is nonwetting and smooth, yielding a higher grain boundary mobility, which enables the growth of larger grains. The very smooth surface of the polymer HTL also suppresses the nucleation in small cavity and contributes to the high grain boundary mobility. \n\n![](images/d2277b5c5c359fb9133b78173268eaa01ceb65d09488a5caa1b876d12a5daf91.jpg) \nFigure 1 | Mechanism of large grain growth on non-wetting HTLs. Illustration of the nucleation and growth of the grains on wetting (a) and non-wetting HTLs (b) after thermal annealing. \n\nLarge aspect ratio OTP grain growth on non-wetting HTLs. The proposed grain growth mechanism was demonstrated by studying the grain morphology of methylammonium lead triiodide $(\\mathrm{MAPbI}_{3})$ films on a wide range of wetting and non-wetting polymer substrates, including polyvinyl alcohol (PVA), PEDOT: PSS, crosslinked $N4\\mathrm{,}N4^{\\prime}$ -bis(4-(6-((3-ethyloxetan-3-yl)methoxy) hexyl)phenyl)- ${\\cdot}N4{,}N4^{\\prime}$ -diphenylbiphenyl- $^{.4,4^{\\prime}}$ -diamine (c-OTPD), poly(bis(4-phenyl)(2,4,6-trimethylphenyl)amine) (PTAA) and poly $(N{-}9^{\\prime}$ -heptadecanyl-2,7-carbazole-alt-5,5-( $^{(4^{\\prime},7^{\\prime}}$ -di-2-thienyl- $^{2^{\\prime},1^{\\prime},3^{\\prime}}$ - benzothiadiazole)) (PCDTBT). The chemical structures of these polymers are shown in Supplementary Fig. 2. The hydroxyl group in PVA and PEDOT:PSS provides wetting surfaces, while other polymers are hydrophobic. The presence of oxygen group in $c$ -OTPD makes it less hydrophobic as PTAA or PCDTBT. The contacting angles of water on these polymers shown in Fig. 2a are $10^{\\circ}$ , $12^{\\circ}$ , $79^{\\circ}$ , $105^{\\circ}$ and $108^{\\circ}$ for PVA, PEDOT:PSS, $\\boldsymbol{\\mathbf{\\mathit{c}}}$ -OTPD, PTAA and PCDTBT, respectively. The measured contact angle measured here represents the wetting capability of the different substrate surfaces to water, and we hypothesize it is also an indication of the wetting capability of these surfaces to solid-state OTP because of its hydrophilic property, as it can be dissolved in many polar solvents like $N,N.$ -dimethylformamide (DMF). Solution process was used to fabricate the HTLs and the $\\mathbf{MAPbI}_{3}$ layer, where the HTL was first spun, and then some were crosslinked by ultraviolet curing and thermal annealing. The fabrication details of the HTLs are shown in the Methods section. The $\\mathbf{MAPbI}_{3}$ film was fabricated by thermal annealing-induced interdiffusion method5,10,12. The hydrophobic surfaces of non-wetting HTLs imposed a challenge in fabricating continuous pinhole-free hydrophilic OTP films on them although it is good for the large grain growth. Formation of continuous $\\mathrm{PbI}_{2}$ films on the HTLs is a prerequisite for the continuous OTP film formation. To form continuous $\\mathrm{PbI}_{2}$ on the HTLs, the $\\mathrm{PbI}_{2}$ solution was heated to $110^{\\circ}\\mathrm{C}$ and quickly dripped on the HTLs for spin coating, which yielded smooth $\\mathrm{PbI}_{2}$ films over the whole substrate as shown by the optical microscope images in Supplementary Fig. 3a. At lower solution temperature, $\\mathrm{PbI}_{2}$ solution formed nonuniform films with many spots, as shown in Supplementary Fig. 3b. \n\n![](images/19c670ca60137a3347c03f34e1cc3e8432a634c06f69732e86f15be1a0922768.jpg) \nFigure 2 | Morphology of $M A P b\\mid_{3}$ films grown on wetting and non-wetting HTLs. The contact angle of water on the varied HTLs (a), the crosssection SEM $(\\pmb{\\ b})$ , top-view SEM (c) and X-ray diffraction patterns of the $360\\cdot\\mathsf{n m}\\mathsf{M A P b l}_{3}$ grown on PVA-, PEDOT:PSS-, c-OTPD-, PTAA- and PCDTBTcovered ITO substrates ${\\bf\\Pi}({\\bf g})$ . Scale bars, $1\\upmu\\mathrm{m}$ in $\\mathbf{b},\\mathbf{c};$ (d,e) the top-view SEM images of the $M A P b\\mathsf{I}_{3}$ grown on PEDOT:PSS (top row) and c-OTPD (bottom row) right after drying and after 20, 40 and $65\\mathsf{m i n}$ of thermal annealing at $105^{\\circ}\\mathsf{C}$ Scale bar, $1\\upmu\\mathrm{m};$ (f) HTL-dependent X-ray diffraction (110) peak full width at half maximum (FWHM) and average grain size/thickness aspect ratio of the $M A\\mathsf{P b l}_{3}$ . \n\nHere all the $\\mathrm{MAPbI}_{3}$ films were thermal annealed for $65\\mathrm{{min}}$ at $105^{\\circ}\\mathrm{C}.$ . The cross-section and top-view SEM images of the $\\mathrm{MAPbI}_{3}$ films on these HTLs shown in Fig. $^{2\\mathrm{b},\\mathrm{c}}$ reveal a clear correlation between the substrate surface wetting capability and the grain morphology: First, the average grain size is much larger for $\\mathrm{MAPbI}_{3}$ films on hydrophobic HTLs. The grain size distribution for $\\mathrm{MAPbI}_{3}$ on various HTLs was summarized in Supplementary Fig. 4. The sizes of $\\mathrm{MAPbI}_{3}$ grains on wetting PVA $(277\\mathrm{nm})$ and PEDOT:PSS $(301\\mathrm{nm})$ are smaller than the film thickness $(\\sim360\\mathrm{nm})$ after $65\\mathrm{min}$ of thermal annealing. Most grains in $\\mathrm{MAPbI}_{3}$ films on non-wetting HTLs were much larger than the film thickness, with the average grain size/film thickness aspect ratio reaching 2.3, 3.2 and 7.9 for $c$ -OTPD, PTAA and PCDTBT (Fig. 2f), respectively. \n\nThe largest grain size on PCDTBT reached $\\sim5\\upmu\\mathrm{m}.$ , which is about 14-fold of the film thickness; second, most of the grain boundaries are perpendicular to the substrate for films on non-wetting HTLs to minimize the grain boundary energy. It is noted that PCDTBT is so hydrophobic so that the OTP films on PCDTBT were mostly not continuous, and SEM pictures were taken from areas with OTP films. \n\nThe influence of surface tension force on the grain nucleation and growth was verified by comparing grain morphology evolution of the $\\mathrm{MAPbI}_{3}$ films on two HTLs, wetting PEDOT:PSS and non-wetting $\\mathfrak{c}$ -OTPD. As shown by the SEM images in Fig. $^{2\\mathrm{d},\\mathrm{e}}$ , the average size of the $\\operatorname{MAPbI}_{3}$ grains on c-OTPD $(480\\mathrm{nm})$ is much larger than that on PEDOT:PSS $(230\\mathrm{nm})$ just after film drying, verifying that a non-wetting surface suppresses heterogeneous nucleation, results in less dense nuclei and thus larger grain size. The average size of the $\\mathrm{MAPbI}_{3}$ grains on $c$ -OTPD increased to $>800\\mathrm{nm}$ with the largest one reaching $>1.5{\\upmu\\mathrm{m}}$ after $65\\mathrm{{min}}$ of thermal annealing. In contrast, the average grain size for the $\\operatorname{MAPbI}_{3}$ film on PEDOT:PSS remained to be around $300\\mathrm{nm}$ even after 65 min of thermal annealing. Finally, the HTLs also impact the crystallinity of the OPT films formed on them. The X-ray diffraction peaks became stronger and sharper for perovskite films on hydrophobic HTLs, agreeing with disappearance of the small grains and better film crystallinity (Fig. 2f,g). No significant change of the diffraction peak ratio was observed, indicating the different HTLs do not cause crystal orientation change. \n\nInfluence of the grain aspect ratio on device performance. The influence of the increased grain size and crystallinity on the device performance was evaluated in PHJ devices with a structure shown in Fig. 3a. Again, c-OPTD and PEDOT:PSS devices were studied because of the excellent reproducibility of the device performance using these two HTLs. Figure 3b shows the photocurrent–voltage $\\left(J-V\\right)$ curves of the optimized $\\mathbf{MAPbI}_{3}$ devices using $c$ -OTPD and PEDOT:PSS as HTLs. The device with PEDOT:PSS as HTL has a relatively low efficiency of $12.3\\%$ , which is consistent with previous result for the devices using only thermal annealing22. The device’s short circuit current density $(J_{\\mathrm{SC}})$ increased from 18.6 to $21.2\\mathrm{mA}\\mathrm{cm}^{-2}$ and open circuit voltage $(V_{\\mathrm{OC}})$ increased significantly from 0.92 to $1.09\\mathrm{V}$ , when the device’s HTL was changed from PEDOT:PSS to c-OTPD. The device employing $\\mathfrak{c}$ -OTPD showed a decent fill factor (FF) of $75.5\\%$ , yielding a PCE of $17.5\\%$ . Negligible photocurrent hysteresis was observed by changing the scanning directions, as shown in Supplementary Fig. 5. The absence of obvious photocurrent hysteresis is commonly observed in our PHJ devices because the $\\mathrm{MAPbI}_{3}$ films have large grains, and charge traps at the film surface and grain boundaries are well passivated by fullerenes10,12,22,23. The devices with thicker $\\mathrm{MAPbI}_{3}$ film $(\\dot{5}00-600\\mathrm{nm})$ were fabricated to optimize the PCE. A thicker $\\mathrm{MAPb}\\mathrm{I}_{3}$ active layer at $500\\mathrm{nm}$ can produce a larger $J_{\\mathrm{SC}}$ of $22.4\\mathrm{m}\\dot{\\mathrm{A}}\\mathrm{cm}^{-2}$ , resulting in an increased PCE of $17.8\\%$ , despite of a decrease of $V_{\\mathrm{OC}}$ to $1.05\\mathrm{V}$ . Further increasing the film thickness did not increase the $J_{\\mathrm{SC}}$ but lowered the FF, which yielded a comparable but slightly lower efficiency of $17.2\\%$ , as shown in Fig. 3b. The device performance with varied HTLs, OTPs and OTP film thicknesses is summarized in Table 1. The peak external quantum efficiency (EQE) of the $c$ -OTPD device with $360–\\mathrm{nm}$ - thick $\\mathrm{MAPbI}_{3}$ reached $94.5\\%$ at ${390}\\mathrm{nm}$ , as shown in Fig. 3c, and the calculated $J_{\\mathrm{SC}}$ from EQE for the three devices are in good agreement to measured $J_{\\mathrm{SC}}$ . The increased $J_{\\mathrm{SC}}$ (21.8 and $2\\mathsf{1}.5\\mathsf{m A c m}^{-2}$ ) in the device with 500- and ${600-}\\mathrm{{nm}}$ -thick $\\mathrm{MAPbI}_{3}$ should mostly be ascribed to the improved absorption in the wavelength range of $650\\mathrm{-}800\\mathrm{nm}$ . The efficiency histogram in Fig. 3d shows $>35\\%$ of the devices the PCE higher than $16.0\\%$ , and $>80\\%$ devices have PCE higher than $15.0\\%$ . \n\n# Discussion \n\nTo find the correlation between the device PCE enhancement and larger grain size and better crystallinity, we performed thermal admittance spectroscopy (TAS) measurement to examine the trap density-of-states (tDOS) in the devices with two different HTLs, PEDOT:PSS and $\\mathfrak{c}$ -OTPD. Our previous study showed tDOS of the devices with PEDOT:PSS had a tDOS in the order of $10^{16}\\mathrm{m}^{-3}\\mathrm{eV}^{-1}$ in the trap band of $0.310{-}0.425\\mathrm{eV}$ towards the forbidden gap, which is correlated to grain boundaries4,12. As shown in Fig. 3e, the device with c-OTPD HTL had a 10–100-fold smaller tDOS of $10^{14}–10^{15}\\mathrm{m}^{-3}\\mathrm{eV}^{-1}$ . It should be noticed that this trap density is as low as those measured in single crystals using TAS characterization14. The much lower tDOS can be partially explained by significant enlarged $\\mathrm{MAPbI}_{3}$ grain size on c-OTPD (Fig. $^{2\\mathrm{b,c}}$ ). However, it is noted that $\\mathrm{MAPbI}_{3}$ grain size on c-OTPD is 2.7-fold that on PEDOT:PSS, which yields only 2.7 times less grain boundary area. If the specific tDOS in unit grain boundary area is the same for the films on both HTLs, there should be additional factors contributed the dramatically reduced tDOS. We speculate that the improved quality of $\\mathsf{c}{\\mathrm{-OTPD/MAPbI}}_{3}$ interface also contributes to the tDOS reduction. This speculation is supported by the observed large peak EQE of $94.5\\%$ at the $390\\mathrm{nm}$ in the device with c-OTPD, which is much higher than the devices with PEDOT:PSS10,12,13. Since shorter-wavelength light has shorter penetration depth in OTPs, the generated charges are more susceptible to charge recombination at the $\\mathrm{HTL}/\\mathrm{\\bar{MAPb}I_{3}}$ interface. A high EQE above $90\\%$ at shorter wavelength proves the very good passivation of charge traps in $\\mathrm{MAPbI}_{3}$ bottom surface close to the transparent electrode side. \n\nThe reduction of tDOS at $\\mathrm{MAPbI}_{3}$ bottom surface (c-OTPD side) was further confirmed by photoluminescence study. In our previous study of passivation of $\\mathrm{MAPbI}_{3}$ top surface by fullerenes, a blue shift of photoluminescence was observed for the fullerene-passivated $\\mathbf{MAPbI}_{3}$ when exciting light was from the top side, while there was no photoluminescence blue shift if the excitation light was from the bottom side, because fullerenes cannot reach the bottom surface of $\\mathbf{MAPbI}_{3}$ even after $^\\mathrm{1h}$ thermal annealing. Here we observed a blue shift of photoluminescence peak from 784 to $774\\mathrm{nm}$ for the $\\mathsf{c-O T P D}/$ $\\mathrm{\\bar{MAPbI}}_{3}$ films with incident light from indium tin oxide (ITO) side, as shown in Fig. 3f, confirming the scenario4,12. The absence of charge traps at $\\mathbf{MAPbI}_{3}$ bottom surface can be explained by (1) the absence of small $\\mathbf{MAPbI}_{3}$ grains close to $\\mathfrak{c}$ -OTPD and (2) excellent crystallinity and stoichiometry of the bottom surface. The large surface energy-driven interaction pushes any residual ions to merge to large grains, resembling the hydrophobic interaction that was used for single-crystal nanoparticle synthesis24. We speculate the vertical and straight grain boundaries facilitate the diffusion of fullerenes, allowing them move towards the bottom surface, which reduced the trap density near the bottom side. \n\nNow that both top and bottom surfaces of the $\\mathrm{MAPbI}_{3}$ thin films have low trap density, which resembles the passivation of silicon wafer at all surfaces by oxidization, the charge recombination lifetime $(\\tau_{\\mathrm{r}})$ should be significantly elongated. As shown in Fig. 3g, the $\\tau_{\\mathrm{r}}$ measured by impedance spectroscopy is significantly prolonged by 7–10 times in the bias region of $0{-}0.7\\mathrm{V}$ after replacing PEDOT:PSS with $\\mathfrak{c}$ -OTPD. $\\tau_{\\mathrm{r}}$ in c-OTPD device at $0\\mathrm{V}$ reached $69\\upmu\\mathrm{s},$ which is close to that of $\\mathbf{MAPbI}_{3}$ single crystals14. The carrier diffusion length in these large crystalline grains should be comparable to that in $\\mathrm{MAPbI}_{3}$ single crystals, which was demonstrated to exceed $175\\upmu\\mathrm{m}$ under 1 sun illumination because of the same carrier recombination lifetime and mobility4,14, which is already more than 100 times longer than the film’s thickness. Therefore, all the photogenerated charges can diffuse to the charge transport layers or grain boundaries without recombination, and the device efficiency is only determined by the charge recombination at grain boundaries or at electrode interfaces. It clearly demonstrated that excellent capability of non-wetting c-OTPD HTL in reducing trap density and suppressing charge recombination in $\\mathbf{MAPbI}_{3}$ . A longer $\\tau_{\\mathrm{r}}$ is expected to contribute to the observed increase of $J_{\\mathrm{SC}},\\ V_{\\mathrm{OC}}$ and FF, while partial of the increased $V_{\\mathrm{OC}}$ should be ascribed to a higher work function of $\\boldsymbol{\\mathbf{\\mathit{c}}}$ -OTPD than PEDOT:PSS. The work function of different HTLs was directly compared by Kelvin probe force microscopy measurement. Gold films deposited on both c-OTPD and PEDOT:PSS surface in the same batch were used as work function reference. As shown in Fig. 3h and Supplementary Fig. 6, a higher work function by $25\\mathrm{meV}$ for c-OTPD than PEDOT:PSS can be derived. The work function difference of the HTLs is much smaller than $V_{\\mathrm{OC}}$ improvement, indicating that the contribution from the reduced charge recombination due to the larger and better OTP grains formed on the non-wetting surface dominates the $V_{\\mathrm{OC}}$ enhancement observed here. This conclusion is further supported by the a recent observation by Kim and coworkers25 that a HTL with work function of $5.4\\mathrm{eV}$ , which is higher than ours, was applied in a same device structure with ours, while the highest $V_{\\mathrm{OC}}$ was only $0.98\\mathrm{V}$ . The much lower $V_{\\mathrm{OC}}$ in that work can be explained by the very small grain sizes. \n\n![](images/1d55e2c4f013191feb90a10efe8bb92879ef0b73d124223b5aeb61f1122f986f.jpg) \nFigure 3 | Characterization of the $M A P b\\mid_{3}$ devices with PEDOT:PSS and c-OTPD HTLs. (a) The PHJ device structure; (b) $J-V$ of the devices with PEDOT:PSS and c-OTPD HTLs, and with different $M A P b\\mathsf{I}_{3}$ thickness of 360, 500 and $600\\mathsf{n m};$ (c) EQE of the devices with c-OTPD HTL and with different $\\mathsf{M A P b l}_{3}$ thickness of 360, 500 and $600\\mathsf{n m},$ ; $({\\pmb d})$ efficiency histogram of the 50 devices using c-OTPD as $\\mathsf{H T L};$ (e) tdOS, (f) photoluminescence at room temperature and $\\mathbf{\\sigma}(\\mathbf{g})$ impedance spectroscopy lifetime at different bias for the devices with PEDOT:PSS and c-OTPD HTLs. (h) Work function distribution of the HTLs of PEDOT:PSS, c-OTPD and PTAA. \n\n
Table 1 | Summary of the best device performance for the OTP devices with different HTLs and different thickness of active layers.
HTL and active layer thickness(mA cm-2) Jsc(V) VocFF (%)PCE (%)
PEDOT:PSS 40O nm MAPbl3 c-OTPD 360 nm MAPbl3 c-OTPD 500 nm MAPbl3 c-OTPD 600 nm MAPbl318.60.9272.012.3
21.21.0975.517.5
22.4 22.21.05 1.0675.617.8
22.01.0773.4 76.817.2 18.1
\n\nIt is noted that PTAA has larger OTP grains on it and a slightly higher work function than $c$ -OTPD, therefore we finally optimized our device performance using PTAA HTL. Although larger OTP grains were observed on PCDTBT, most OTP films on PCDTBT have low film coverage $\\textless100\\%$ , as shown in Supplementary Fig. 7, and thus not suitable for device optimization. The PTAA layer was doped by $1\\mathrm{wt\\%}$ tetrafluoro-tetracyanoquinodimethane (F4-TCNQ) to enhance its conductivity. Here $\\operatorname{MAPbI}_{3}$ with a thickness of $500\\mathrm{nm}$ by the two-step interdiffusion method was fabricated. The optimized device performances are shown in Fig. 4a, and are summarized in Table 1. Compared with the device with c-OTPD, the $\\mathbf{MAPbI}_{3}$ device with PTAA showed a slightly higher efficiency of $18.1\\%$ with comparable $V_{\\mathrm{OC}}$ of $1.07\\mathrm{V}$ and $J_{\\mathrm{SC}}$ of $22.0\\mathrm{mAcin}^{-2}$ but a larger FF of $76.8\\%$ . The calculated $J_{\\mathrm{SC}}$ from EQE in Fig. 4b reached $21.6\\mathrm{mAcm}^{-2}$ , which is in good agreement with measured photocurrent. The photocurrent measured at $0.88\\mathrm{V}$ slightly increased from initial 20.5 to $20.8\\mathrm{mAcm}^{-2}$ (stabilized) after 60-s illumination, resulting in an increased stabilized PCE of $18.3\\%$ for the device with PTAA HTL (Fig. 4c). The quick turning on the photocurrent confirms the absence of large density charge traps, while the slow climbing of the $J_{\\mathrm{SC}}$ to the maximum value indicates the presence a relatively small density of deep traps in the devices despite of the passivation of traps on perovskite surface and grain boundaries by the double fullerene layer, which might originate from the deep traps in the fullerene layer itself. \n\nIn summary, the non-wetting HTLs were demonstrated to be effective in enhancing the efficiency of OTP PHJ devices to $18.3\\%$ . In addition to the higher PCE, these HTLs are expected to be much more stable than the acidic PEDOT:PSS. This work provided a simple method of achieving high-aspect, low-defect density, high-quality perovskite polycrystalline thin films, which possess much better optoelectronic properties such as fewer bulk and surface traps, and higher carrier mobilities. The improved property can potentially give rise to the applications in other fields, such as high mobility for transistors, higher responsivity and lower pink noise for photodetectors by removing the charge traps26, lower driving voltage for light emitting diodes and lower threshold excitation density and higher efficiency for lasers. \n\n# Methods \n\nHTL and OTP layer fabrication. To prepare the OTPD solution for spin coating, diphenyliodonium-hexafluorophosphate was added into OTPD solution with a weight ratio of $2-5\\mathrm{wt\\%}$ to OTPD as photoinitiator. For c-OTPD film fabrication, $0.25\\mathrm{wt\\%}$ OTPD solution was first spun on the ITO substrate at $6{,}000\\mathrm{r.p.m}$ . for $35s$ , and then the as-prepared OTPD film was crosslinked by ultraviolet curing (wavelength of $365\\mathrm{nm}$ ) for $3\\mathrm{{min}}$ . To promote the crosslinking, the ultraviolet cured c-OTPD film was thermally annealed at $110^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . PTAA film was prepared by spin coating $0.5\\mathrm{wt\\%}$ PTAA solution doped with $1\\mathrm{wt\\%}$ F4-TCNQ at $6{,}000\\mathrm{r.p.m}$ ., and the as-prepared film thermally annealed at $110^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . \n\n![](images/f6bb7266c8fd2f120483eacbed38f0619579c1d7aa94deae34ab8b85383a2cdb.jpg) \nFigure 4 | Performance of the $M A P b\\mid_{3}$ devices with PTAA HTL. (a) The photocurrent of the $M A P b\\mathsf{I}_{3}$ devices under 1 sun illumination; (b) EQE of the devices with the active layers of $\\mathsf{M A P b l}_{3};$ (c) stabilized photocurrent measurement of the $M A P b\\mathsf{I}_{3}$ device with PTAA HTL under 1 sun illumination with light turned on and off by a shutter. \n\nPCDTBT was prepared by spin coating $0.5\\mathrm{wt\\%}$ PCDTBT solution at $6{,}000\\mathrm{r.p.m}$ ., and the as-prepared film thermally annealed at $110^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . PEDOT:PSS (Baytron-P 4083) and $1\\mathrm{wt\\%}$ PVA solution was spin coated on clean ITO substrate at a speed of ${3,000}\\mathrm{r.p.m}$ . The films were then annealed at $130^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . \n\nThe $\\mathbf{MAPbI}_{3}$ films were fabricated by thermal annealing-induced interdiffusion method10. The $\\mathrm{PbI}_{2}$ layers on all HTLs were spin coated from $110^{\\circ}\\mathrm{C}$ pre-heated $\\mathrm{PbI}_{2}$ solution in DMF. $\\mathrm{PbI}_{2}$ beads $(99.999\\%$ trace metals basis) were purchased from Sigma-Aldrich, which have good solubility in DMF. Around $60\\upmu\\mathrm{l}$ of hot $\\mathrm{PbI}_{2}$ precursor solution, which was pre-heated to $110^{\\circ}\\mathrm{C},$ was directly transferred by plastic (polypropylene) disposable pipettes from the bottle of heated $\\mathrm{PbI}_{2}$ solution to the HTL-covered ITO substrates within $2s$ . The spinning was quickly started at the speed of $6{,}000\\mathrm{r.p.m}$ . after the injection of $\\mathrm{PbI}_{2}$ solution. The as-fabricated $\\mathrm{PbI}_{2}$ films were dried and annealed at $110^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ . To fabricate 360-, 500- and ${600-}\\mathrm{nm}$ -thick $\\mathrm{MAPbI}_{3}$ film, 600, 700 and $800\\mathrm{mg}\\mathrm{ml}^{-1}\\mathrm{\\PbI}_{2}$ DMF precursor solutions were used with 70, 80 and $95\\mathrm{mg}\\mathrm{ml}^{-1}$ methylammonium iodide (MAI) 2-propanol precursor solution, respectively. The MAI was synthesized from methylamine ( $40\\mathrm{wt\\%}$ in $\\mathrm{H}_{2}\\mathrm{O}$ Sigma-Aldrich) and hydroiodic acid $(57\\mathrm{wt\\%}$ in $\\mathrm{H}_{2}\\mathrm{O}$ , $99.95\\%$ , with stabilizer, Sigma-Aldrich) and the method was reported elsewhere9. The deposition of MAI layer was taken at $6{,}000\\mathrm{r}{.}\\mathrm{p}{.}\\mathrm{m}$ . and from a hot precursor solution at $70^{\\circ}\\mathrm{C}$ . The stacked precursor layers were annealed on the hotplate at $105^{\\circ}\\mathrm{C}$ with a Petri dish covering them. The following deposition of phenyl-C61-butyric acid methyl ester, $\\mathrm{C}_{60}$ , 2,9-dimethyl-4,7-diphenyl-1,10- \n\nphenanthroline and Al layers were reported elsewhere10,12,19. The device working area was $7.25\\mathrm{mm}^{2}$ , defined by the overlap of ITO substrate and Al cathode. \n\nFilm and device characterization. The microscope images of $\\mathrm{PbI}_{2}$ layer spin coated at 70 and $110^{\\circ}\\mathrm{C}$ were taken by an optical microscope Olympus BX61, with an integrated charge-coupled device (Photometrics, CoolSNAP-cf). X-ray diffraction pattern was obtained by a Rigaku D/Max-B X-ray diffractometer with Bragg–Brentano parafocusing geometry. A Co- $\\operatorname{K}\\upalpha$ tube was equipped in the diffractometer with an emitting wavelength of $1.79\\mathring{\\mathrm{A}}$ . The SEM images were taken from a Quanta 200 FEG environmental scanning electron microscope. The grain size was obtained by measuring the average diameter of the grains in the plane direction from SEM images. A Xenon lamp-based solar simulator (Oriel 67005, $150\\mathrm{W}$ solar simulator) was used to produce the simulated $\\mathrm{AM}\\ 1.5\\mathrm{G}$ irradiation $(100\\mathrm{mW}\\mathrm{cm}^{-2})$ , and the calibration of the light was carried out by a Si diode (Hamamatsu S1133) equipped with a Schott visible-colour glass filter (KG5 colour filter). The bias scanning rate was $0.13\\mathrm{V}\\mathrm{~s~}^{-1}$ for the device $J{-}V$ curve measurement. TAS measurement was performed by a LCR (inductance (L), capacitance (C), and resistance (R)) meter (Agilent E4980A) to obtain the devices’ frequency-dependent capacitance and voltage-dependent capacitance, which was used for devices’ tDOS derivation. The derivation procedure was reported elsewhere4. Impedance spectroscopy was also recorded by the LCR meter (Agilent E4980A) with home-made software. The devices were kept under 1 sun illumination at room temperature during the measurement. The recombination lifetime equates to the reciprocal of the angular frequency at the top of the arc in impedance spectra with the Nyquist $\\mathrm{plot}^{27}$ (Supplementary Fig. 8), which has good agreement with the fitted results from recombination resistance and chemical capacitance (Supplementary Figs 9 and 10). \n\n# References \n\n1. Burschka, J. et al. Sequential deposition as a route to high-performance perovskite-sensitized solar cells. Nature 499, 316–319 (2013). \n2. Liu, M., Johnston, M. B. & Snaith, H. J. Efficient planar heterojunction perovskite solar cells by vapour deposition. Nature 501, 395–398 (2013). \n3. Im, J.-H. et al. Growth of $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ cuboids with controlled size for high-efficiency perovskite solar cells. Nat. Nanotechnol. 9, 927–932 (2014). \n4. Shao, Y. et al. Origin and elimination of photocurrent hysteresis by fullerene passivation in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ planar heterojunction solar cells. Nat. Commun. 5, 5784 (2014). \n5. Xiao, Z. et al. Giant switchable photovoltaic effect in organometal trihalide perovskite devices. Nat. Mater. 14, 193–198 (2014). \n6. Green, M. A., Ho-Baillie, A. & Snaith, H. J. The emergence of perovskite solar cells. Nat. Photon. 8, 506–514 (2014). \n7. Malinkiewicz, O. et al. Perovskite solar cells employing organic chargetransport layers. Nat. Photon. 8, 128–132 (2014). \n8. Zhou, H. et al. Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). \n9. Lee, M. M. et al. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n10. Xiao, Z. et al. Efficient, high yield perovskite photovoltaic devices grown by interdiffusion of solution-processed precursor stacking layers. Energy Environ. Sci. 7, 2619–2623 (2014). \n11. Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n12. Xiao, Z. et al. Solvent-annealing of perovskite induced crystal growth for photovoltaic device efficiency enhancement. Adv. Mater. 26, 6503–6509 (2014). \n13. Chen, Q. et al. Planar heterojunction perovskite solar cells via vapor-assisted solution process. J. Am. Chem. Soc. 136, 622–625 (2013). \n14. Dong, Q. et al. Electron-hole diffusion length exceeding 3 millimeters in low-temperature solution grown $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ single crystals. Science 27, 967–970 (2015). \n15. Zhao, D. et al. High-efficiency solution-processed planar perovskite solar cells with a polymer hole transport layer. Adv. Energy Mater. 5, 1401855 (2015). \n16. Eperon, G. E. et al. Morphological control for high performance, solutionprocessed planar heterojunction perovskite solar cells. Adv. Funct. Mater. 24, 151–157 (2014). \n17. Conings, B. et al. Perovskite-based hybrid solar cells exceeding $10\\%$ efficiency with high reproducibility using a thin film sandwich approach. Adv. Mater. 26, 2041–2046 (2014). \n18. Wang, L. et al. Femtosecond time-resolved transient absorption spectroscopy of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite films: evidence for passivation effect of $\\mathrm{PbI}_{2}$ . J. Am. Chem. Soc. 136, 12205–12208 (2014). \n19. Chen, Q. et al. Controllable self-induced passivation of hybrid lead iodide perovskites toward high performance solar cells. Nano Lett. 14, 4158–4163 (2014). \n20. Noel, N. K. et al. Enhanced photoluminescence and solar cell performance via lewis base passivation of organic–inorganic lead halide perovskites. ACS Nano 8, 9815–9821 (2014). \n21. Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n22. Bi, C. et al. Understanding the formation and evolution of interdiffusion grown organolead halide perovskite thin films by thermal annealing. J. Mater. Chem. A 2, 18508–18514 (2014). \n23. Wang, Q. et al. Large fill-factor bilayer iodine perovskite solar cells fabricated by a low-temperature solution-process. Energy Environ. Sci. 7, 2359–2365 (2014). \n24. Xiao, Z. et al. Synthesis and application of ferroelectric P(VDF-TrFE) nanoparticles in organic photovoltaic devices for high efficiency. Adv. Energy Mater. 3, 1581–1588 (2013). \n25. Lim, K.-G. et al. Boosting the power conversion efficiency of perovskite solar cells using self-organized polymeric hole extraction layers with high work function. Adv. Mater. 26, 6461–6466 (2014). \n26. Fang, Y. et al. Resolving weak light of sub-picowatt per square centimeter by hybrid perovskite photodetectors enabled by noise reduction. Adv. Mater. 27, 2804–2810 (2015). \n27. Mora-Sero´, I. et al. Impedance spectroscopy characterisation of highly efficient silicon solar cells under different light illumination intensities. Energy Environ. Sci. 2, 678–686 (2009). \n\n# Acknowledgements \n\nWe thank the financial support from Department of Energy under Award DE-EE0006709, National Science Foundation under Awards ECCS-1201384 and ECCS-1252623 and the Nebraska Public Power District through the Nebraska Center for Energy Sciences Research. \n\n# Author contributions \n\nJ.H. conceived the idea; C.B. conducted most of device fabrication and device measurement, SEM and photoluminescence; Y.S. measured trap density, carrier lifetime and surface work function; Y.Y. conducted the X-ray diffraction measurement; J.H. wrote the paper. Q.W contributed to the contact angle measurement; Z.X. provided the Supplementary Fig. 1. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Bi, C. et al. Non-wetting surface-driven high-aspect-ratio crystalline grain growth for efficient hybrid perovskite solar cells. Nat. Commun. 6:7747 doi: 10.1038/ncomms8747 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms7242", + "DOI": "10.1038/ncomms7242", + "DOI Link": "http://dx.doi.org/10.1038/ncomms7242", + "Relative Dir Path": "mds/10.1038_ncomms7242", + "Article Title": "Observation of long-lived interlayer excitons in monolayer MoSe2-WSe2 heterostructures", + "Authors": "Rivera, P; Schaibley, JR; Jones, AM; Ross, JS; Wu, SF; Aivazian, G; Klement, P; Seyler, K; Clark, G; Ghimire, NJ; Yan, JQ; Mandrus, DG; Yao, W; Xu, XD", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Van der Waals bound heterostructures constructed with two-dimensional materials, such as graphene, boron nitride and transition metal dichalcogenides, have sparked wide interest in device physics and technologies at the two-dimensional limit. One highly coveted heterostructure is that of differing monolayer transition metal dichalcogenides with type-II band alignment, with bound electrons and holes localized in individual monolayers, that is, interlayer excitons. Here, we report the observation of interlayer excitons in monolayer MoSe2-WSe2 heterostructures by photoluminescence and photoluminescence excitation spectroscopy. We find that their energy and luminescence intensity are highly tunable by an applied vertical gate voltage. Moreover, we measure an interlayer exciton lifetime of similar to 1.8 ns, an order of magnitude longer than intralayer excitons in monolayers. Our work demonstrates optical pumping of interlayer electric polarization, which may provoke further exploration of interlayer exciton condensation, as well as new applications in two-dimensional lasers, light-emitting diodes and photovoltaic devices.", + "Times Cited, WoS Core": 1304, + "Times Cited, All Databases": 1433, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000350202400006", + "Markdown": "# Observation of long-lived interlayer excitons in monolayer MoSe2–WSe2 heterostructures \n\nPasqual Rivera1, John R. Schaibley1, Aaron M. Jones1, Jason S. Ross2, Sanfeng Wu1, Grant Aivazian1, Philip Klement1, Kyle Seyler1, Genevieve Clark2, Nirmal J. Ghimire3,4, Jiaqiang Yan4,5, D.G. Mandrus3,4,5, Wang Yao6 & Xiaodong $\\mathsf{X}\\mathsf{u}^{1,2}$ \n\nVan der Waals bound heterostructures constructed with two-dimensional materials, such as graphene, boron nitride and transition metal dichalcogenides, have sparked wide interest in device physics and technologies at the two-dimensional limit. One highly coveted heterostructure is that of differing monolayer transition metal dichalcogenides with type-II band alignment, with bound electrons and holes localized in individual monolayers, that is, interlayer excitons. Here, we report the observation of interlayer excitons in monolayer ${\\sf M o S e}_{2}–\\sf W S e_{2}$ heterostructures by photoluminescence and photoluminescence excitation spectroscopy. We find that their energy and luminescence intensity are highly tunable by an applied vertical gate voltage. Moreover, we measure an interlayer exciton lifetime of $\\sim1.8$ ns, an order of magnitude longer than intralayer excitons in monolayers. Our work demonstrates optical pumping of interlayer electric polarization, which may provoke further exploration of interlayer exciton condensation, as well as new applications in two-dimensional lasers, light-emitting diodes and photovoltaic devices. \n\nTrdheiefaflemrecnetonftlwydoe-vdiecmveelnopspiheoydnsiacls (bi2lbiDta)ys dmtoatoenrviearlvts nhalelryadledras aeWmnabealwes heterostructures $(\\mathrm{HSs})^{1}$ . The most successful example to date is the vertical integration of graphene on boron nitride. Such novel HSs not only markedly enhance graphene’s electronic properties2, but also give rise to superlattice structures demonstrating exotic physical phenomena3–5. A fascinating counterpart to gapless graphene is a class of monolayer direct bandgap semiconductors, namely transition metal dichalcogenides $(\\mathrm{TMDs})^{6-8}$ . Due to the large binding energy in these 2D semiconductors, excitons dominate the optical response, exhibiting strong light–matter interactions that are electrically tunable9,10. The discovery of excitonic valley physics11–15 and strongly coupled spin and pseudospin physics16,17 in 2D TMDs opens up new possibilities for device concepts not possible in other material systems. \n\nMonolayer TMDs have the chemical formula $\\mathbf{MX}_{2}$ where the M is tungsten (W) or molybdenum (Mo), and the X is sulfur (S) or selenium (Se). Although these TMDs share the same crystalline structure, their physical properties, such as bandgap, exciton resonance and spin–orbit coupling strength, can vary significantly. Therefore, an intriguing possibility is to stack different TMD monolayers on top of one another to form 2D HSs . Firstprinciple calculations show that heterojunctions formed between monolayer tungsten and molybdenum dichalcogenides have typeII band alignment18–20. Recently, this has been confirmed by X-ray photoelectron spectroscopy and scanning tunnelling spectroscopy21. Since the Coulomb binding energy in 2D TMDs is much stronger than in conventional semiconductors, it is possible to realize interlayer excitonic states in van der Waals bound heterobilayers, that is, bound electrons and holes that are localized in different layers. Such interlayer excitons have been intensely pursued in bilayer graphene for possible exciton condensation22, but direct optical observation demonstrating the existence of such excitons is challenging owing to the lack of a sizable bandgap in graphene. Monolayer TMDs with bandgaps in the visible range provide the opportunity to optically pump interlayer excitons, which can be directly observed through photoluminescence (PL) measurements. \n\nIn this report, we present direct observation of interlayer excitons in vertically stacked monolayer ${\\mathrm{MoSe}}_{2}{\\mathrm{-}}{\\mathrm{WSe}}_{2}$ HSs. We show that interlayer exciton PL is enhanced under optical excitation resonant with the intralayer excitons in isolated monolayers, consistent with the interlayer charge transfer resulting from the underlying type-II band structure. We demonstrate the tuning of the interlayer exciton energy by applying a vertical gate voltage, which is consistent with the permanent out-of-plane electric dipole nature of interlayer excitons. Moreover, we find a blue shift in PL energy at increasing excitation power, a hallmark of repulsive dipole–dipole interactions between spatially indirect excitons. Finally, time-resolved PL measurements yield a lifetime of $1.8\\mathrm{ns}$ , which is at least an order of magnitude longer than that of intralayer excitons. Our work shows that monolayer semiconducting HSs are a promising platform for exploring new optoelectronic phenomena. \n\n# Results \n\n$\\mathbf{MoSe}_{2}–\\mathbf{WSe}_{2}$ HS photoluminescence. HSs are prepared by standard polymethyl methacrylate (PMMA) transfer techniques using mechanically exfoliated monolayers of $\\mathrm{WSe}_{2}$ and $\\mathrm{MoSe}_{2}$ (see Methods). Since there is no effort made to match the crystal lattices of the two monolayers, the obtained HSs are considered incommensurate. An idealized depiction of the vertical ${\\mathrm{MoSe}}_{2}{\\mathrm{-}}{\\mathrm{WSe}}_{2}$ HS is shown in Fig. 1a. We have fabricated six devices that all show similar results as those reported below. The data presented here are from two independent ${\\mathrm{MoSe}}_{2}{\\mathrm{-}}{\\mathrm{WSe}}_{2}$ HSs, labelled device 1 and device 2. Figure 1b shows an optical micrograph of device 1, which has individual monolayers, as well as a large area of vertically stacked HS. This device architecture allows for the comparison of the excitonic spectrum of individual monolayers with that of the HS region, allowing for a controlled identification of spectral changes resulting from interlayer coupling. \n\nWe characterize the $\\mathrm{MoSe}_{2}\\mathrm{-WSe}_{2}$ monolayers and HS using PL measurements. Inspection of the PL from the HS at room temperature reveals three dominant spectral features (Fig. 1c). The emission at 1.65 and $1.57\\mathrm{eV}$ corresponds to the excitonic states from monolayer $\\mathrm{WSe}_{2}$ and $\\mathrm{MoSe}_{2}$ (refs 10,15), respectively. PL from the HS region, outlined by the dashed white line in Fig. 1a, reveals a distinct spectral feature at $1.35\\mathrm{eV}$ $(X_{\\mathrm{I}})$ . Twodimensional mapping of the spectrally integrated PL from $X_{\\mathrm{I}}$ shows that it is isolated entirely to the HS region (inset, Fig. 1c), with highly uniform peak intensity and spectral position (Supplementary Materials 1). \n\nLow-temperature characterization of the HS is performed with $1.88\\mathrm{eV}$ laser excitation at $20\\mathrm{K}$ PL from individual monolayer $\\mathrm{WSe}_{2}$ (top), $\\mathrm{MoSe}_{2}$ (bottom) and the HS area (middle) are shown with the same scale in Fig. 1d. At low temperature, the intralayer neutral $(X_{\\mathrm{M}}^{0})$ and charged $(X_{\\mathbf{M}}^{-})$ excitons are resolved10,15, where M labels either W or Mo. Comparison of the three spectra shows that both intralayer $X_{\\mathrm{M}}^{0}$ and $X_{\\mathbf{M}}^{-}$ exist in the HS with emission at the same energy as from isolated monolayers, demonstrating the preservation of intralayer excitons in the HS region. PL from $X_{\\mathrm{I}}$ becomes more pronounced and is comparable to the intralayer excitons at low temperature. We note that the $X_{\\mathrm{I}}$ energy position has variation across the pool of HS samples we have studied (Supplementary Fig. 1), which we attribute to differences in the interlayer separation, possibly due to imperfect transfer and a different twisting angle between monolayers. \n\nWe further perform PL excitation (PLE) spectroscopy to investigate the correlation between $X_{\\mathrm{I}}$ and intralayer excitons. A narrow bandwidth $(<50\\mathrm{kHz})$ frequency tunable laser is swept across the energy resonances of intralayer excitons (from 1.6 to $1.75\\mathrm{eV})$ while monitoring $X_{\\mathrm{I}}$ PL response. Figure 2a shows an intensity plot of $X_{\\mathrm{I}}$ emission as a function of photoexcitation energy from device 2. We clearly observe the enhancement of $X_{\\mathrm{I}}$ emission when the excitation energy is resonant with intralayer exciton states (Fig. 2b). \n\nNow we discuss the origin of $X_{\\mathrm{I}}$ . Since $X_{\\mathrm{I}}$ has never been observed in our exfoliated monolayer and bilayer samples, if its origin were related to defects, they must be introduced by the fabrication process. This would result in sample-dependent $X_{\\mathrm{I}}$ properties with non-uniform spatial dependence. However, our data show that key physical properties of $X_{\\mathrm{I}},$ such as the resonance energy and intensity, are spatially uniform and isolated to the HS region (inset of Fig. 1c and Supplementary Fig. 2). In addition, $X_{\\mathrm{I}}$ has not been observed in ${\\mathrm{WSe}}_{2}{\\mathrm{-}}{\\mathrm{WSe}}_{2}$ homostructures constructed from exfoliated or physical vapor deposition (PVD) grown monolayers (Supplementary Fig. 3). All these facts suggest that $X_{\\mathrm{I}}$ is not a defect-related exciton. \n\nInstead, the experimental results support the observation of an interlayer exciton. Due to the type-II band alignment of the $\\mathrm{MoSe}_{2}\\mathrm{^{-}}\\mathrm{WSe}_{2}\\mathrm{~HS}^{18-20}$ , as shown in Fig. 2c, photoexcited electrons and holes will relax (dashed lines) to the conduction band edge of $\\mathrm{MoSe}_{2}$ and the valence band edge of ${\\mathrm{WSe}}_{2}$ , respectively. The Coulomb attraction between electrons in the $\\mathrm{MoSe}_{2}$ and holes in the $\\mathrm{WSe}_{2}$ gives rise to an interlayer exciton, $X_{\\mathrm{I}},$ analogous to spatially indirect excitons in coupled quantum wells. The interlayer coupling yields the lowest energy bright exciton in the HS, which is consistent with the temperature dependence of $X_{\\mathrm{I}}$ PL, that is, it increases as temperature decreases (Supplementary Fig. 4). \n\n![](images/9716b558c301e2047643cf262645cbfd6952b05b461242e25d182787b4e5ac69.jpg) \nFigure 1 | Intralayer and interlayer excitons of a monolayer $M O S_{e_{2}}$ – $\\mathbf{w}\\mathbf{s}_{\\mathbf{e}_{2}}$ vertical heterostructure. (a) Cartoon depiction of a ${\\sf M o S e}_{2}{\\mathrm{-}}{\\sf W}{\\sf S e}_{2}$ heterostructure (HS). (b) Microscope image of a ${\\sf M o S e}_{2}–\\sf W S e_{2}$ HS (device 1) with a white dashed line outlining the HS region. (c) Room-temperature photoluminescence of the heterostructure under $20\\upmu\\up w$ laser excitation at $2.33\\mathrm{eV}.$ Inset: spatial map of integrated PL intensity from the low-energy peak $(1.273-1.400\\mathrm{eV})$ , which is only appreciable in the heterostructure area, outlined by the dashed black line. (d) Photoluminescence of individual monolayers and the HS at $20\\mathsf{K}$ under $20\\upmu\\upnu$ excitation at $1.88\\mathsf{e V}$ (plotted on the same scale). \n\n![](images/3796f17e6c62cf71d15642cd8b5672d11153c021dd7f997380212df0335c7c59.jpg) \nFigure 2 | Photoluminescence excitation spectroscopy of the interlayer exciton at 20 K. (a) PLE intensity plot of the heterostructure region with an excitation power of $30\\upmu\\mathsf{W}$ and 5 s charge-coupled device CCD integration time. (b) Spectrally integrated PLE response (red dots) overlaid on PL (black line) with $100\\upmu\\mathrm{W}$ excitation at $1.88\\mathsf{e V}.$ (c) Type-II semiconductor band alignment diagram for the 2D ${\\sf M o S e}_{2}{\\mathrm{-}}{\\sf W}{\\sf S e}_{2}$ heterojunction. \n\nFrom the intralayer and interlayer exciton spectral positions, we can infer the band offsets between the ${\\mathrm{WSe}}_{2}$ and $\\mathrm{MoSe}_{2}$ monolayers (Fig. 2c). The energy difference between $X_{\\mathrm{W}}$ and $X_{\\mathrm{I}}$ at room temperature is $310\\mathrm{meV}$ . Considering the smaller binding energy of interlayer than intralayer excitons, this sets a lower bound on the conduction band offset. The energy difference between $X_{\\mathrm{M}}$ and $X_{\\mathrm{I}}$ then provides a lower bound on the valence band offset of $230\\mathrm{meV}$ . This value is consistent with the valence band offset of $228\\mathrm{meV}$ found in ${\\mathrm{MoS}}_{2}{\\mathrm{-}}{\\mathrm{WSe}}_{2}$ HSs by micro X-ray photoelectron spectroscopy and scanning tunnelling spectroscopy measurements21. This experimental evidence strongly corroborates $X_{\\mathrm{I}}$ as an interlayer exciton. The observation of bright interlayer excitons in monolayer semiconducting HSs is of central importance, and the remainder of this paper will focus on their physical properties resulting from their spatially indirect nature and the underlying type-II band alignment. \n\n![](images/546631bf59bb9c59b6fb0c063b86f0971cb828db9a3f2d1f070632aa3ce43b5c.jpg) \nFigure 3 | Gate control of the interlayer exciton and band alignment. (a) Device 2 geometry. The interlayer exciton has a permanent dipole, corresponding to an out-of-plane electric polarization. (b) Electrostatic control of the band alignment and the interlayer exciton resonance. (c) Colourmap of interlayer exciton photoluminescence as a function of applied gate voltage under $70\\upmu\\upnu$ excitation at $1.744\\mathrm{eV},$ 1 s integration time. \n\nElectrical control of the interlayer exciton. Applying a vertical gate bias across the HS demonstrates that the emission energy of the interlayer exciton is highly electrically tunable. Figure 3a shows the contact geometry of device 2, where an indium contact has been fabricated on the $\\mathrm{\\dot{W}S e}_{2}$ layer, which is vertically stacked on top of the $\\mathrm{MoSe}_{2}$ . The HS is on $\\mathrm{SiO}_{2}$ , which provides insulation from the heavily doped silicon backgate. Electrostatic doping is performed on the HS by grounding the indium contact and applying a voltage to the backgate $(V_{\\mathrm{g}})$ . Figure 3c shows the interlayer exciton PL intensity as $V_{\\mathrm{g}}$ is varied from $+100$ to $-100\\mathrm{\\dot{V}}$ . Over this range, the peak centre blue shifts by about $45\\mathrm{meV}$ . Subsequent measurements on an inverted analogue of device 2, where the stacking order of $\\mathrm{MoSe}_{2}$ and $\\mathrm{WSe}_{2}$ is reversed, shows the peak centre red shift by about $60\\mathrm{meV}$ as $V_{\\mathrm{g}}$ is varied from $+70$ to $-70\\mathrm{V}$ (Supplementary Fig. 5). \n\nThe gate dependence of $X_{\\mathrm{I}}$ is consistent with that expected for the interlayer exciton, which maintains a dipole pointing from $\\mathrm{MoSe}_{2}$ to $\\dot{\\mathrm{WSe}}_{2}$ (Fig. 3a). At negative $V_{\\mathbf{g}},$ the electric field reduces the relative band-offset between the $\\mathrm{MoSe}_{2}$ and $\\mathrm{WSe}_{2}$ in device 2, increasing the energy separation between the $\\mathrm{MoSe}_{2}$ conduction band and the $\\mathrm{WSe}_{2}$ valence band, as shown in Fig. $^{3\\mathrm{b},\\mathrm{c}}$ . The interaction of the field and the anti-aligned dipole of the interlayer exciton thus results in the observed blue shift in the energy of PL from $X_{\\mathrm{I}}$ . Conversely, when $\\mathrm{MoSe}_{2}$ is located on top of ${\\mathrm{WSe}}_{2}$ , the field effect increases the relative band-offset at negative $V_{\\mathbf{g}},$ manifesting the observed red shift in $X_{\\mathrm{I}}$ PL (Supplementary Fig. 5). The electrical control of the energy of $X_{\\mathrm{I}}$ confirms the direction of its permanent dipole. On the basis of this electrical field and dipole interaction picture, we would expect that the $X_{\\mathrm{I}}$ PL intensity in devices 2 and 3 should have opposite behaviours. However, we observe that the $X_{\\mathrm{I}}$ PL increases as gate voltage decreases in both devices. This observation shows that in addition to the electrical field effect, carrier doping may play a significant role in tuning $X_{\\mathrm{I}}$ intensity. We expect devices with both top and bottom gates may further elucidate the observed phenomena. \n\nPower dependence and lifetime of interlayer exciton PL. The interlayer exciton PLE spectrum as a function of laser power with excitation energy in resonance with $X_{W}^{o}$ reveals several properties of the $X_{\\mathrm{I}}$ . Inspection of the normalized PLE intensity (Fig. 4a) shows the evolution of a doublet in the interlayer exciton spectrum, highlighted by the red and green bi-Lorentzian fits. Both peaks of the doublet display a consistent blue shift with increased laser intensity, shown by the dashed arrows in Fig. 4a, which are included as a guide to the eye. The spectrally integrated intensity of $X_{\\mathrm{I}}$ also exhibits a strong saturation as a function of laser power, as shown in Fig. 4b (absolute PL intensity shown in Supplementary Fig. 6). The sublinear power response of $X_{\\mathrm{I}}$ for excitation powers above $0.5\\upmu\\mathrm{W}$ is distinctly different than that for the intralayer excitons in isolated monolayers, which display a saturation power threshold of about $80\\upmu\\mathrm{W}$ (Supplementary Fig. 7). \n\nThe low power saturation of $X_{\\mathrm{I}}$ PL suggests a much longer lifetime than that of intralayer excitons. In the HS, the lifetime of the intralayer exciton is substantially reduced by the ultrafast interlayer charge hopping23, which is evidenced by the strong quenching of intralayer exciton PL (Fig. 1d; Supplementary Fig. 8). Moreover, the lifetime of the interlayer exciton is long, because it is the lowest energy configuration and its spatially indirect nature leads to a reduced optical dipole moment. This long lifetime is confirmed by time-resolved $\\mathrm{{\\PL,}}$ as shown in Fig. 4c. A fit to a single exponential decay yields an interlayer exciton lifetime of $1.8\\pm0.3\\mathrm{n};$ s. This timescale is much longer than the intralayer exciton lifetime, which is on the order of tens of $\\mathrm{ps}^{24-27}$ . By modelling the saturation behaviour using a simplified three-level diagram, the calculated saturation intensity for the interlayer exciton is about 180 times smaller than intralayer (Supplementary Fig. 7; Supplementary Discussion), consistent with our observation of low saturation intensity of $X_{\\mathrm{I}}$ . \n\n# Discussion \n\nWe attribute the observed doublet feature in Fig. 4a to the spinsplitting of the monolayer $\\mathrm{MoSe}_{2}$ conduction band (Fig. 4d). This assignment is mainly based on the fact that the extracted energy difference between the doublet is ${\\sim}25\\mathrm{meV}$ , which agrees well with $\\mathrm{MoSe}_{2}$ conduction band splitting predicted by first-principle calculations28. This explanation is also supported by the evolution of the relative strength of the two peaks with increasing excitation power, as shown in Fig. 4a (similar results in device 1 with $1.88\\mathrm{eV}$ excitation shown in Supplementary Fig. 9). At low power, the lowest energy configuration of interlayer excitons, with the electron in the lower spin-split band of $\\mathrm{MoSe}_{2}$ , is populated first. Due to phase space filling effects, the interlayer exciton configuration with the electron in the higher energy spin-split band starts to be filled at higher laser power. Consequently, the higher energy peak of the doublet becomes more prominent at higher excitation powers. \n\n![](images/7bcc936b1d24c8daa51e43a216a518650b3153e3bd5bc3f20c2f3980c5d9caf9.jpg) \nFigure 4 | Power-dependent photoluminescence of interlayer exciton and its lifetime at 20 K. (a) Power dependence of the interlayer exciton for $1.722\\mathsf{e V}$ excitation with a bi-Lorentzian fit to the 5 and $100\\upmu\\mathrm{W}$ plots, normalized for power and charge-coupled device (CCD) integration time. (b) Spectrally integrated intensity of the interlayer exciton emission as a function of excitation power shows the saturation effect. $\\mathbf{\\eta}(\\bullet)$ Time-resolved photoluminescence of the interlayer exciton $(1.35\\mathrm{eV})$ shows a lifetime of about $1.8{\\mathsf n}{\\mathsf s}$ . The dashed curve is the instrument response to the excitation lase pulse. (d) Illustration of the heterojunction band diagram, including the spin levels of the ${\\mathsf{M o S e}}_{2}$ conduction band. The $X_{1}$ doublet has energy splitting equal to $(\\omega_{1}^{\\prime}-\\omega_{1})$ $\\approx25\\mathsf{m e V}.$ \n\nThe observed blue shift of $X_{\\mathrm{I}}$ as the excitation power increases, indicated by the dashed arrows in Fig. 4a, is a signature of the repulsive interaction between the dipole-aligned interlayer excitons (cf. Fig. 3a). This is a hallmark of spatially indirect excitons in gallium arsenide (GaAs) coupled quantum wells, which have been intensely studied for exciton Bose-Einstein condensation (BEC) phenomena29. The observation of spatially indirect interlayer excitons in a type-II semiconducting 2D HS provides an intriguing platform to explore exciton BEC, where the observed extended lifetimes and repulsive interactions are two key ingredients towards the realization of this exotic state of matter. Moreover, the extraordinarily high binding energy for excitons in this truly 2D system may provide for degenerate exciton gases at elevated temperatures compared with other material systems30. The long-lived interlayer exciton may also lead to new optoelectronic applications, such as photovoltaics31–34 and 2D HS nanolasers. \n\n# Methods \n\nDevice fabrication. Monolayers of $\\mathrm{MoSe}_{2}$ are mechanically exfoliated onto $300\\mathrm{nm}$ $\\mathrm{SiO}_{2}$ on heavily doped Si wafers and monolayers of ${\\mathrm{WSe}}_{2}$ onto a layer of PMMA atop polyvinyl alcohol on Si. Both monolayers are identified with an optical microscope and confirmed by their PL spectra. Polyvinyl alcohol is dissolved in $\\mathrm{H}_{2}\\mathrm{O}$ and the PMMA layer is then placed on a transfer loop or thin layer of polydimethylsiloxane (PDMS). The top monolayer is then placed in contact with the bottom monolayer with the aid of an optical microscope and micromanipulators. The substrate is then heated to cause the PMMA layer to release from the transfer media. The PMMA is subsequently dissolved in acetone for $\\sim30\\mathrm{min}$ and then rinsed with isopropyl alcohol. \n\nLow-temperature PL measurements. Low-temperature measurements are conducted in a temperature-controlled Janis cold finger cryostat (sample in vacuum) with a diffraction-limited excitation beam diameter of $\\sim1\\upmu\\mathrm{m}$ . PL is spectrally filtered through a $0.5–\\mathrm{m}$ monochromator (Andor–Shamrock) and detected on a charge-coupled device (Andor—Newton). Spatial PL mapping is performed using a Mad City Labs Nano-T555 nanopositioning system. For PLE measurements, a continuous wave Ti:sapphire laser (MSquared—SolsTiS) is used for excitation and filtered from the PL signal using an $815\\mathrm{-nm}$ -long pass optical filter (Semrock). Electrostatic doping is accomplished with an indium drain contact deposited onto the monolayer $\\mathrm{WSe}_{2}$ region of device 2 and using the heavily doped Si as a tunable backgate. \n\nTime-resolved PL measurements. For interlayer lifetime measurements, we excite the sample with a $<200$ -fs pulsed Ti:sapphire laser (Coherent—MIRA). Interlayer PL is spectrally filtered through a $0.5\\mathrm{-m}$ monochromator (Princeton— Acton 2500), and detected with a fast time-correlated single-photon counting system composed of a fast ( $\\cdot<30\\mathrm{ps}$ full width at half maximum) single-photon avalanche detector (Micro Photon Devices—PDM series) and a picosecond event timer (PicoQuant—PicoHarp 300). \n\n# References \n\n1. Geim, A. K. & Grigorieva, I. V. Van der Waals heterostructures. Nature 499, 419–425 (2013). \n2. Dean, C. R. et al. Boron nitride substrates for high-quality graphene electronics. Nat. Nanotechnol. 5, 722–726 (2010). \n3. Hunt, B. et al. Massive Dirac fermions and Hofstadter butterfly in a van der Waals heterostructure. Science 340, 1427–1430 (2013). \n4. Dean, C. R. et al. Hofstadter’s butterfly and the fractal quantum Hall effect in moire superlattices. Nature 497, 598–602 (2013). \n5. Ponomarenko, L. A. et al. Cloning of Dirac fermions in graphene superlattices. Nature 497, 594–597 (2013). \n6. Novoselov, K. S. et al. Two-dimensional atomic crystals. Proc. Natl Acad. Sci USA 102, 10451–10453 (2005). \n7. Mak, K. F., Lee, C., Hone, J., Shan, J. & Heinz, T. F. Atomically thin $\\mathbf{MoS}_{2}$ : a new direct-gap semiconductor. Phys. Rev. Lett. 105, 136805 (2010). \n8. Splendiani, A. et al. Emerging photoluminescence in monolayer $\\mathbf{MoS}_{2}$ . Nano Lett. 10, 1271–1275 (2010). \n9. Mak, K. F. et al. Tightly bound trions in monolayer $\\mathbf{MoS}_{2}$ . Nat. Mater. 12, 207–211 (2013). \n10. Ross, J. S. et al. Electrical control of neutral and charged excitons in a monolayer semiconductor. Nat. Commun. 4, 1474 (2013). \n11. Xiao, D., Liu, G.-B., Feng, W., Xu, X. & Yao, W. Coupled spin and valley physics in monolayers of $\\mathbf{MoS}_{2}$ and other group-VI dichalcogenides. Phys. Rev. Lett. 108, 196802 (2012). \n12. Cao, T. et al. Valley-selective circular dichroism of monolayer molybdenum disulphide. Nat. Commun. 3, 887 (2012). \n13. Zeng, H., Dai, J., Yao, W., Xiao, D. & Cui, X. Valley polarization in MoS2 monolayers by optical pumping. Nat. Nanotechnol. 7, 490–493 (2012). \n14. Mak, K. F., He, K., Shan, J. & Heinz, T. F. Control of valley polarization in monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ by optical helicity. Nat. Nanotechnol. 7, 494–498 (2012). \n15. Jones, A. M. et al. Optical generation of excitonic valley coherence in monolayer $\\mathrm{WSe}_{2}$ . Nat. Nanotechnol. 8, 634–638 (2013). \n16. Gong, Z. et al. Magnetoelectric effects and valley-controlled spin quantum gates in transition metal dichalcogenide bilayers. Nat. Commun. 4, 2053 (2013). \n17. Jones, A. M. et al. Spin-layer locking effects in optical orientation of exciton spin in bilayer $\\mathrm{WSe}_{2}$ . Nat. Phys. 10, 130–134 (2014). \n18. Kang, J., Tongay, S., Zhou, J., Li, J. & Wu, J. Band offsets and heterostructures of two-dimensional semiconductors. Appl. Phys. Lett. 102, 012111–012114 (2013). \n19. Kos´mider, K. & Fern´andez-Rossier, J. Electronic properties of the ${\\mathrm{MoS}}_{2}–{\\mathrm{W}}\\boldsymbol{\\mathrm{S}}_{2}$ heterojunction. Phys. Rev. B 87, 075451 (2013). \n20. Terrones, H., Lopez-Urias, F. & Terrones, M. Novel hetero-layered materials with tunable direct band gaps by sandwiching different metal disulfides and diselenides. Sci. Rep. 3, 1549 (2013). \n21. Chiu, M.-H. et al.Determination of band alignment in transition metal dichalcogenide heterojunctions, Preprint at http://arXiv:1406.5137 (2014). \n22. Su, J.-J. & MacDonald, A. H. How to make a bilayer exciton condensate flow. Nat. Phys. 4, 799–802 (2008). \n23. Hong, X. P. et al. Ultrafast charge transfer in atomically thin MoS2/WS2 heterostructures. Nat. Nanotechnol. 9, 682–686 (2014). \n24. Wang, G. et al. Valley dynamics probed through charged and neutral exciton emission in monolayer ${\\mathrm{WSe}}_{2}$ . Phys. Rev. B 90, 075413 (2014). \n25. Lagarde, D. et al. Carrier and polarization dynamics in monolayer $\\mathbf{MoS}_{2}$ . Phys. Rev. Lett. 112, 047401 (2014). \n26. Mai, C. et al. Many-body effects in valleytronics: direct measurement of valley lifetimes in single-layer $\\mathbf{MoS}_{2}$ . Nano Lett. 14, 202–206 (2013). \n27. Shi, H. et al. Exciton dynamics in suspended monolayer and few-layer $\\mathbf{MoS}_{2}$ 2D crystals. ACS Nano 7, 1072–1080 (2012). \n28. Korma´nyos, A., Z´olyomi, V., Drummond, N. D. & Burkard, G. Spin-orbit coupling, quantum dots, and qubits in monolayer transition metal dichalcogenides. Phys. Rev. X 4, 011034 (2014). \n29. Butov, L. V., Lai, C. W., Ivanov, A. L., Gossard, A. C. & Chemla, D. S. Towards Bose-Einstein condensation of excitons in potential traps. Nature 417, 47–52 (2002). \n30. Fogler, M. M., Butov, L. V. & Novoselov, K. S. High-temperature superfluidity with indirect excitons in van der Waals heterostructures. Nat. Commun. 5, 4555 (2014). \n31. Lee, C. H. et al. Atomically thin p-n junctions with van der Waals heterointerfaces. Nat. Nanotechnol. 9, 676–681 (2014). \n32. Furchi, M. M., Pospischil, A., Libisch, F., Burgdorfer, J. & Mueller, T. Photovoltaic effect in an electrically tunable van der Waals heterojunction. Nano Lett. 14, 4785–4791 (2014). \n33. Cheng, R. et al. Electroluminescence and photocurrent generation from atomically sharp WSe2/MoS2 heterojunction p-n diodes. Nano Lett. 14, 5590–5597 (2014). \n34. Fang, H. et al. Strong interlayer coupling in van der Waals heterostructures built from single-layer chalcogenides. Proc. Natl Acad. Sci. USA 111, 6198–6202 (2014). \n\n# Acknowledgements \n\nThis work is mainly supported by the US DoE, BES, Materials Sciences and Engineering Division (DE-SC0008145). N.J.G., J.Y. and D.G.M. are supported by US DoE, BES, Materials Sciences and Engineering Division. W.Y. is supported by the Research Grant Council of Hong Kong (HKU17305914P, HKU9/CRF/13G), and the Croucher Foundation under the Croucher Innovation Award. X.X. thanks the support of the Cottrell Scholar Award. P.R. thanks the UW GO-MAP program for their support. A.M.J. is partially supported by the NSF (DGE-0718124). J.S.R. is partially supported by the NSF (DGE-1256082). S.W. and G.C. are partially supported by the State of Washington through the UW Clean Energy Institute. Device fabrication was performed at the Washington Nanofabrication Facility and NSF-funded Nanotech User Facility. \n\n# Author contributions \n\nX.X. and P.R. conceived the experiments. P.R. and P.K. fabricated the devices, assisted by J.S.R. P.R. performed the measurements, assisted by J.R.S., A.M.J., J.S.R., S.W. and G.A. P.R. and X.X. performed data analysis, with input from W.Y. N.J.G., J.Y. and D.G.M. synthesized and characterized the bulk ${\\mathrm{WSe}}_{2}$ crystals. X.X., P.R., J.R.S. and W.Y. wrote the paper. All authors discussed the results. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Rivera, P. et al. Observation of long-lived interlayer excitons in monolayer ${\\mathrm{MoSe}}_{2}{\\mathrm{-}}{\\mathrm{WSe}}_{2}$ heterostructures. Nat. Commun. 6:6242 doi: 10.1038/ncomms7242 (2015). " + }, + { + "id": "10.1103_PhysRevLett.114.223901", + "DOI": "10.1103/PhysRevLett.114.223901", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevLett.114.223901", + "Relative Dir Path": "mds/10.1103_PhysRevLett.114.223901", + "Article Title": "Scheme for Achieving a Topological Photonic Crystal by Using Dielectric Material", + "Authors": "Wu, LH; Hu, X", + "Source Title": "PHYSICAL REVIEW LETTERS", + "Abstract": "We derive in the present work topological photonic states purely based on conventional dielectric material by deforming a honeycomb lattice of cylinders into a triangular lattice of cylinder hexagons. The photonic topology is associated with a pseudo-time-reversal (TR) symmetry constituted by the TR symmetry supported in general by Maxwell equations and the C-6 crystal symmetry upon design, which renders the Kramers doubling in the present photonic system. It is shown explicitly for the transverse magnetic mode that the role of pseudospin is played by the angular momentum of the wave function of the out-of-plane electric field. We solve Maxwell equations and demonstrate the new photonic topology by revealing pseudospin-resolved Berry curvatures of photonic bands and helical edge states characterized by Poynting vectors.", + "Times Cited, WoS Core": 1271, + "Times Cited, All Databases": 1355, + "Publication Year": 2015, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000355563000002", + "Markdown": "# Scheme for Achieving a Topological Photonic Crystal by Using Dielectric Material \n\nLong-Hua Wu and Xiao Hu\\* International Center for Materials Nanoarchitectonics (WPI-MANA), National Institute for Materials Science, Tsukuba 305-0044, Japan Graduate School of Pure and Applied Sciences, University of Tsukuba, Tsukuba 305-8571, Japan (Received 10 February 2015; published 3 June 2015) \n\nWe derive in the present work topological photonic states purely based on conventional dielectric material by deforming a honeycomb lattice of cylinders into a triangular lattice of cylinder hexagons. The photonic topology is associated with a pseudo-time-reversal (TR) symmetry constituted by the TR symmetry supported in general by Maxwell equations and the $C_{6}$ crystal symmetry upon design, which renders the Kramers doubling in the present photonic system. It is shown explicitly for the transverse magnetic mode that the role of pseudospin is played by the angular momentum of the wave function of the out-of-plane electric field. We solve Maxwell equations and demonstrate the new photonic topology by revealing pseudospin-resolved Berry curvatures of photonic bands and helical edge states characterized by Poynting vectors. \n\nDOI: 10.1103/PhysRevLett.114.223901 \n\nPACS numbers: 42.70.Qs, 03.65.Vf, 73.43.-f \n\nIntroduction.—The discovery of the quantum Hall effect (QHE) opened a new chapter of condensed matter physics with topology as the central concept [1–11]. Topological states are not only interesting from an academic point of view, but also expected to yield significant impacts to applications because robust surface (or edge) states protected by bulk topology provide possibilities for spintronics and quantum computation [12–17]. However, electronic systems with nontrivial topology confirmed so far are still limited in number, and most of them exhibit topological properties only at very low temperatures, which hinders their better understanding and manipulation indispensable for practical applications. \n\nPhotonic crystals are analogues of conventional crystals with the atomic lattice replaced by a medium of periodic electric permittivity and/or magnetic permeability [18]. Metamaterials are designed to generate electromagnetic (EM) properties such as negative index, magnetic lens, and so on, which are not available in nature [19]. Recently, it has been recognized that topological states characterized by unique edge propagations of an EM wave can be realized in photonic crystals based on gyromagnetic materials under external magnetic field, bi-anisoctroic metamaterials with coupled electric and magnetic fields where bi-anisotropy acts as effective spin-orbit coupling, and coupled resonator optical waveguides (CROWs) [20–31] (for a review see Ref. [32]). \n\nIn the present work, we propose a two-dimensional (2D) photonic crystal purely made of conventional dielectric material. We notice that a honeycomb lattice is equivalent to a triangular lattice of hexagonal clusters composed by six neighboring sites, and that, taking this larger hexagonal unit cell instead of the primitive rhombic unit cell of two sites (see Fig. 1), the Dirac cones at $K$ and $K^{\\prime}$ points in the first \n\nBrillouin zone of honeycomb lattice are folded to doubly degenerate Dirac cones at the $\\Gamma$ point. It is then intriguing to observe that at the $\\Gamma$ point there are two 2D irreducible representations in the $C_{6}$ symmetry group associated with odd and even parities respective to spatial inversion operation. Based on these properties, we propose opening a topologically nontrivial band gap by deforming the honeycomb lattice in a way that keeps the hexagonal clusters and preserves the $C_{6}$ symmetry (see Fig. 1). Solving Maxwell equations, we reveal explicitly that harmonic transverse magnetic (TM) modes hosted by the hexagonal cluster, working as “artificial atom” in the present scheme, exhibit electronic orbital-like $p$ - and $d$ -wave shapes and form photonic bands. We clarify that there is a pseudo-timereversal (TR) symmetry constituted by the TR symmetry respected by Maxwell equations and the $C_{6}$ crystal symmetry upon design, which behaves in the same way as TR symmetry in electronic systems and renders the Kramers doubling in the present photonic system. This intimately gives the correspondence between the positive and negative angular momenta of the wave function of the out-of-plane electric field and the up and down spins of the electron. Evaluating the Berry curvatures of bulk photonic bands and the edge states for finite systems, we demonstrate the emergence of the topological phase. With the simple design free of requirements on any external field and gyromagnetic or bi-anisotropic materials, the present topological photonic state purely based on dielectric material is expected to be promising for future applications. \n\n![](images/c42cdc94c09baa5a78f49add77ef53ecc78c52a1b52a59292e2a171482df91f2.jpg) \nFIG. 1 (color online). Schematic plot of a triangular photonic crystal of “artificial atoms” composed by six cylinders of dielectric material. Dark gray (Red) dashed rhombus and hexagon are primitive cells of honeycomb and triangular lattices. The solid black hexagon labels an artificial atom, while the dashed black one marks the interstitial region among artificial atoms. $\\vec{a}_{1}$ and $\\vec{a}_{2}$ are unit vectors with length $a_{0}$ as the lattice constant. Right panel: enlarged view of a hexagonal cluster with $R$ the length of the hexagon edge and $d$ the diameter of cylinders. $\\varepsilon_{d}$ and $\\varepsilon_{A}$ are dielectric constants of cylinders and surrounding environment. \n\nArtificial atom and pseudospin.—Let us consider harmonic TM modes of the EM wave, namely, those of finite out-of-plane $E_{z}$ and in-plane $H_{x}$ and $H_{y}$ components with others being zero, in a dielectric medium (for coordinates see Fig. 1). For simplicity, the real electric permittivities of both cylinders $(\\varepsilon_{d})$ and environment $(\\varepsilon_{A})$ are taken frequency independent in the regime under consideration. The master equation for a harmonic mode of frequency $\\omega$ is then derived from the Maxwell equations [33] \n\n$$\n\\left[\\frac{1}{\\varepsilon(\\mathbf{r})}\\nabla\\times\\nabla\\times\\right]E_{z}(\\mathbf{r})\\hat{z}=\\frac{\\omega^{2}}{c^{2}}E_{z}(\\mathbf{r})\\hat{z},\n$$ \n\nwith $\\varepsilon(\\mathbf{r})$ the position-dependent permittivity and $c$ the speed of light. The magnetic field is given by the Faraday relation ${\\bf H}=-[i/(\\upmu_{0}\\upomega)]\\nabla\\times{\\bf E}$ , where the magnetic permeability $\\upmu_{0}$ is presumed as that of vacuum. The Bloch theorem applies for the present system when $\\varepsilon(\\mathbf{r})$ is periodic as shown in Fig. 1. Note, however, that the master equation (1) describes the EM waves instead of electrons carrying on the spin degrees of freedom, with the most prominent difference lying at the response upon TR operation. Equation (1) is solved in momentum space using package MIT PHOTONIC BANDS (MPB) [34]. For simplicity, we consider first a system infinite in the z direction which reduces the problem to two dimensions. \n\nWe start from a honeycomb lattice of dielectric cylinders, and deform it in such a way as to keep the hexagonal clusters composed by six neighboring cylinders and the $C_{6}$ symmetry. Now the alignment of dielectric cylinders is more convenient to be considered as a triangular lattice of hexagonal artificial atoms. There are two 2D irreducible representations in the $C_{6}$ symmetry group associated with the triangular lattice: $E^{\\prime}$ and $E^{\\prime\\prime}$ with basis functions $x(y)$ and $x y(x^{2}-y^{2})$ , corresponding to odd and even spatial parities, respectively [35]. As can be seen in Fig. 2(a) for the $E_{z}$ field at the $\\Gamma$ point, artificial atoms carry $p_{x}(p_{y})$ and $d_{x y}(d_{x^{2}-y^{2}})$ orbitals, with the same symmetry as those of electronic orbitals of conventional atoms in solids. \n\nWe now examine matrix representations of $\\pi/3$ rotation and its combinations for the orbitals $p_{x}(p_{y})$ and $d_{x y}(d_{x^{2}-y^{2}})$ . Since $p_{x}(p_{y})$ behave in the same way as $x(y)$ , it is easy to see \n\n![](images/3f45f01ff8052510f2ffcf423429f75c5bf196b186c77435db896c9cb1d70d67.jpg) \nFIG. 2 (color online). (a) Electric fields $E_{z}$ of the $p_{x}(p_{y})$ and $d_{x y}(d_{x^{2}-y^{2}})$ photonic orbitals hosted by the artificial atom at the $\\Gamma$ point. (b) Magnetic fields associated with $E_{z}$ fields with wave functions of positive and negative angular momenta $p_{\\pm}=(p_{x}\\pm i p_{y})/\\sqrt{2}$ and $d_{\\pm}=(d_{x^{2}-y^{2}}\\pm i d_{x y})/\\sqrt{2}$ . The angular momentum of the wave function of the $E_{z}$ field constitutes the pseudospin in the present photonic crystal. \n\n$$\nD_{E^{\\prime}}(C_{6}){\\binom{p_{x}}{p_{y}}}={\\left(\\begin{array}{l l}{{\\frac{1}{2}}}&{-{\\frac{\\sqrt{3}}{2}}}\\\\ {{\\frac{\\sqrt{3}}{2}}}&{{\\frac{1}{2}}}\\end{array}\\right)}{\\left(\\begin{array}{l}{p_{x}}\\\\ {p_{y}}\\end{array}\\right)}.\n$$ \n\nIt is noticed that $\\mathcal{U}=[D_{E^{\\prime}}(C_{6})+D_{E^{\\prime}}(C_{6}^{2})]/\\sqrt{3}=-i\\sigma_{y}$ with $D_{E^{\\prime}}(C_{6}^{2})\\equiv D_{E^{\\prime}}^{2}(C_{6})$ is associated with the $\\pi/2$ rotation of $p_{x}(p_{y})\\quad(\\sigma_{y}$ being the Pauli matrix). Therefore, $\\mathcal{U}^{2}(p_{x},\\tilde{p_{y}})^{\\mathrm{T}}=-(p_{x},p_{y})^{\\mathrm{T}}$ , which is consistent with the odd parity of $p_{x}(p_{y})$ with respect to spatial inversion. Similarly, one has \n\n$$\nD_{E^{\\prime\\prime}}(C_{6})\\binom{d_{x^{2}-y^{2}}}{d_{x y}}=\\binom{-\\frac12}{\\frac{\\sqrt{3}}{2}}\\stackrel{-\\sqrt{3}}{-\\frac{1}{2}}\\Bigg)\\binom{d_{x^{2}-y^{2}}}{d_{x y}},\n$$ \n\nwhich is same as $D_{E^{\\prime}}(C_{6}^{2})$ because the basis functions are now bilinear of $x(y)$ . It is then straightforward to check that $[D_{E^{\\prime\\prime}}(C_{6})^{^{.}}-D_{E^{\\prime\\prime}}(C_{6}^{2})]/\\sqrt{3}=\\mathcal{\\bar{U}}$ is associated with a $\\pi/4$ rotation of $d_{x y}(d_{x^{2}-y^{2}})$ , which yields $\\mathcal{U}^{2}(d_{x^{2}-y^{2}},d_{x y})^{\\mathrm{T}}=-(d_{x^{2}-y^{2}},d_{x y})^{\\mathrm{T}}$ . \n\nWe compose the antiunitary operator $\\tau=u\\kappa$ , where $\\kappa$ is the complex conjugate operator associated with the TR operation respected by Maxwell systems in general. Since ${\\dot{T}}^{2}=-1$ is guaranteed by $\\mathcal{U}^{2}=-1$ , $\\tau$ can be taken as a pseudo-TR operator that provides Kramers doubling in the same way as TR symmetry in electronic systems. It is clear that the crystal symmetry plays an important role in this pseudo-TR symmetry [36]. \n\nThe two pseudospin states are given by \n\n$$\np_{\\pm}=(p_{x}\\pm i p_{y})/\\sqrt{2};\\quad d_{\\pm}=(d_{x^{2}-y^{2}}\\pm i d_{x y})/\\sqrt{2},\n$$ \n\nwhich are related to the above basis functions by unitary transformation (see Supplemental Material [37]). Namely, the up and down pseudospins correspond to positive and negative angular momenta of the wave function of the $E_{z}$ field. The in-plane magnetic fields associated with $p_{\\pm}$ and $d_{\\pm}$ in Eq. (4) are shown in Fig. 2(b). The physics discussed above applies also for $K$ and $K^{\\prime}$ points with 2D irreducible representations. \n\nPseudospins discussed so far in photonic systems include bonding (antibonding) states of electric and magnetic fields [24,25], left-hand (right-hand) circular polarizations of EM waves [28], and clockwise (anticlockwise) circulations of light in CROWs [29,30]. \n\nPhotonic bands.—Now we calculate the photonic band dispersions described by the master equation (1) imposing periodic boundary conditions along unit vectors $\\vec{a}_{1}$ and $\\vec{a}_{2}$ given in Fig. 1. As shown in Fig. 3, double degeneracy in the band dispersions appears at the $\\Gamma$ point, which can be identified as $p_{\\pm}$ and $d_{\\pm}$ states, consistent with the symmetry consideration. For large lattice constant $a_{0}$ , the photonic band below (above) the gap is occupied by $p_{\\pm}$ $(d_{\\pm})$ states [see Fig. 3(a) for $a_{0}/R=3.125$ with $R$ the length of hexagon edge]. \n\nReducing the lattice constant to $a_{0}/R=3$ , the $p$ and $d$ states become degenerate at the $\\Gamma$ point, and two Dirac cones appear as shown in Fig. 3(b). This is because at this lattice constant the system is equivalent to the honeycomb lattice of individual cylinders, and the doubly degenerate Dirac cones are nothing but those at the $K$ and $K^{\\prime}$ point in the Brillouin zone of honeycomb lattice based on the primitive rhombic unit cell of two sites [31]. \n\nWhen the lattice constant is further reduced, a global photonic band gap is reopened near the Dirac point as shown in Fig. 3(c) for $a_{0}/R=2.9$ . Now the $E_{z}$ field at the low- (high-) frequency side of the band gap exhibits $d_{\\pm}$ $(p_{\\pm})$ characters around the $\\Gamma$ point, opposite to the order away from the $\\Gamma$ point. Namely, a band inversion takes place upon reducing the lattice constant in the present system. Quantitatively, the band gap is $\\Delta\\omega=5.47~\\mathrm{THz}$ at $\\omega=138.77~\\mathrm{THz}$ with $a_{0}=1\\ \\mu\\mathrm{m}$ , with all the quantities scaling with the lattice constant. \n\n![](images/3da9fc5e3d8daf165c85fbc02155292ea77fa4a4ad11147c246f282b64af0658.jpg) \nFIG. 3 (color). Dispersion relations of the TM mode for the 2D photonic crystals with $\\varepsilon_{d}=11.7$ , $\\varepsilon_{A}=1$ , and $d=2R/3$ for (a) $a_{0}/R=3.125$ (Inset: Brillouin zone of triangular lattice), (b) $a_{0}/R=3$ , and (c) $a_{0}/R=2.9$ . Blue and red are for $d_{\\pm}$ and $p_{\\pm}$ bands, respectively, and rainbow for hybridization between them. The case of $a_{0}/R=3$ corresponds exactly to the honeycomb lattice of individual cylinders. \n\nIn order to see what happens in the system around the band inversion, we check the real-space distribution of the pseudospin specific Poynting vector $\\vec{S}=\\mathrm{Re}[\\vec{E}\\times\\vec{H}^{*}]/2$ averaged over a period $\\tau=2\\pi/\\omega$ , which describes the energy flow in the present EM system. It is found that the Poynting vector is circling around individual atoms as shown in Fig. 4(a) for $a_{0}/R=3.125$ , with the chirality of the Poynting vector corresponding to the pseudospin (Poynting vector for pseudospin-up is not shown explicitly). The EM energy flows around individual atoms, characterizing a conventional “insulating” state. At $a_{0}/R=2.9$ , namely, after the band inversion, the Poynting vectors are much enhanced in interstitial regimes as shown in Fig. 4(b). It is in a sharp contrast to the case in Fig. 4(a), and hints at an unconventional insulating state. \n\nAlthough Dirac dispersions in photonic systems were discussed previously in both square and triangular lattices [42–44], possible nontrivial topology was not addressed. \n\nTopological edge state.—We also consider a ribbon of photonic crystal after band inversion by cladding its two edges in terms of two photonic crystals with trivial band gap (namely, before band inversion) at the same frequency window, which prevents possible edge states from leaking into free space. It should be kept in mind that, since the cluster of six cylinders is the basic block of the present design, we keep it intact for discussions of the main physics. As displayed in Fig. 5(a), there appear additional states as indicated by the double degenerate red curves within the bulk gap. Checking the real-space distribution of the $E_{z}$ field at typical momenta around the $\\Gamma$ point $[A$ and $B$ in the enlarged vision of Fig. 5(a) with $k_{x}=\\pm0.04(2\\pi/a_{0})]$ , we find that the in-gap states locate at the ribbon edges and decay exponentially into bulk as displayed in Fig. 5(b) (two other states are localized at the other ribbon edge and are not shown explicitly). As shown in the right insets of Fig. 5(b), the Poynting vectors exhibit a nonzero downward (upward) EM energy flow for the pseudospin-up (pseudospin-down) state even averaged over time. This indicates unambiguously counterpropagations of EM energy at the sample edge associated with the two pseudospin states, the hallmark of a quantum spin Hall effect (QSHE) state [2,3]. Distributions of the Poynting vectors of the bulk bands in Fig. 5(b) for the ribbon system are similar to those in Fig. 4(b) for the infinite system. QHE has been described by the cyclic motions of electrons under strong external magnetic field in a quasiclassic picture of electronic wave functions [45]. Note that the Poynting vector describes energy flows in systems governed by Maxwell equations, and therefore the distributions shown in Figs. 4 and 5(b) can be observed in experiments. The photonic QSHE in the present system can also be confirmed by evaluating the $\\mathbb{Z}_{2}$ topology index based on a $k\\cdot p$ model around the $\\Gamma$ point (see Supplemental Material [37]). \n\n![](images/7adbf2b65c5554e3fd57b458c9ba10b3293f8f65f40ac4b2956a71624f3467b3.jpg) \nFIG. 4 (color online). Real-space distributions of the timeaveraged Poynting vector associated with the pseudospin-down state at the $\\Gamma$ point below the photonic gap: (a) $a_{0}/R=3.125$ in the trivial regime and (b) $a_{0}/R=2.9$ in the topological regime. Other parameters are taken same as those in Fig. 3. \n\n![](images/89a432ee4fb21510d2d14da86a24437c9a45dac78814631de325b2858d41b980.jpg) \nFIG. 5 (color online). (a) Dispersion relation of a ribbon-shaped 2D topological photonic crystal, which is infinite in one direction and of 45 and 6 artificial atoms for the topological and trivial regions respectively in the other direction. Right panel: enlarged view of (a) around the band gap. Dark gray (Red) curves are for topological edge states. (b) Real-space distributions of $E_{z}$ fields at points A and B indicated in the right panel of (a). Right panels: time-averaged Poynting vectors $\\dot{S}$ over a period. (c) 3D photonic crystal of height $h$ with two horizontal gold plates placed at two ends symmetrically. (d) Distribution of energy-density of $E_{z}$ field $u_{E_{z}}(\\mathbf{r})\\bar{=}\\varepsilon(\\mathbf{r})|E_{z}(\\bar{\\mathbf{r}})|^{2}/2$ in the 3D topological photonic crystal in (c) stimulated by a linearly polarized source. (e) Leftward and (f) rightward unidirectional energy propagation stimulated by source $S_{+}$ and $S_{-}$ , which injects $E_{z}$ field with wave function of positive and negative, respectively, angular momentum in the region denoted by gray (green) solid frame in (d). The lattice constant and diameter of cylinder are kept same in the whole space $a_{0}=1~\\mu\\mathrm{m}$ and $d=0.24~\\mu\\mathrm{m}$ , while the edge length of hexagon is $R=0.345a_{0}$ $(a_{0}/R=2.9)$ ) and $R=0.32a_{0}$ $(a_{0}/R=3.125)$ ) in topological and trivial regions, and the frequency of all sources is $\\omega=135.6~\\mathrm{THz}$ within the topological band gap. In the 3D system the height of cylinder is $h=1\\ \\mu\\mathrm{m}$ . Other parameters are same as those in Fig. 3. \n\nSince the pseudo-TR symmetry and the pseudospin rely on the $C_{6}$ symmetry, deformations in the system that break the crystalline order and thus the pseudo-TR symmetry would mix the two pseudospin channels as in other $\\mathbb{Z}_{2}$ topological photonic systems [24,29]. Actually, there is a tiny gap at the $\\Gamma$ point in Fig. 5(a) (unnoticeable in the present scale) due to the reduction of $C_{6}$ crystalline symmetry at the ribbon edge. However, the photonic topology remains valid up to moderate deformations as far as the dispersions of edge states are not pushed into bulk bands (see Supplemental Material [37]). \n\nFor experimental implementation of the present topological state, the finite height of cylinders along the z direction has to be taken into account. We consider a square sample of topological photonic crystal sandwiched by two horizontal gold plates [see Fig. 5(c)] with separation $h$ chosen to prevent photonic bands with nonzero $k_{z}$ from falling into the topological band gap. Damping of EM waves in gold plates is taken into account by adopting a complex reflective index for gold. The size of the topological sample is $40\\vec{a}_{1}\\times20(\\vec{a}_{1}+\\vec{a}_{2})$ with all four edges clad by a trivial photonic crystal. A harmonic line source ${\\bf E}=E_{0}e^{i\\omega t}\\hat{z}$ is placed parallel to dielectric cylinders to inject the EM wave at the interface with the frequency in the topological band gap. We simulate the 3D system by solving time-dependent Maxwell equations using the finite difference time-domain method [46] implemented in the MIT electromagnetic equation propagation (MEEP) [47]. Since any harmonic source preserves TR symmetry respected by the Maxwell equations, the system exhibits helical topological edge states as shown in Fig. 5(d). When an EM wave characterized by an $E_{z}$ field with wave function of positive (negative) angular momentum is injected by line source $S_{+}$ (S−) [48], leftward (rightward) unidirectional energy propagation takes place [see Figs. 5(e) and (f)], as expected from the bulk topology. \n\nIn conclusion, we derive a two-dimensional photonic crystal with nontrivial topology purely based on conventional dielectric material, simply by deforming a honeycomb lattice of cylinders. A pseudo-time-reversal symmetry is constructed in terms of the time reversal symmetry respected by the Maxwell equations in general and the $C_{6}$ crystal symmetry upon design, which enables the Kramers doubling with the role of pseudospin played by the angular momentum of wave functions of the outof-plane electric field of transverse magnetic modes. The present topological photonic crystal with simple design backed up by the symmetry consideration can be fabricated relatively easily as compared with other proposals, and is expected to leave impacts on topological physics and related materials sciences. \n\nThe authors acknowledge K. Sakoda and T. Ochiai for useful discussions. This work was supported by the WPI Initiative on Materials Nanoarchitectonics, Ministry of Education, Culture, Sports, Science and Technology of Japan, and partially by Grant-in-Aid for Scientific Research under the Innovative Area “Topological Quantum Phenomena” (No. 25103723), Ministry of Education, Culture, Sports, Science and Technology of Japan. \n\n\\*To whom all correspondence should be addressed. HU.Xiao@nims.go.jp \n[1] K. v. Klitzing, G. Dorda, and M. Pepper, Phys. Rev. Lett. 45, 494 (1980). \n[2] M. Z. Hasan and C. L. Kane, Rev. Mod. Phys. 82, 3045 (2010). \n[3] X.-L. Qi and S.-C. Zhang, Rev. Mod. Phys. 83, 1057 (2011). \n[4] D. J. Thouless, M. Kohmoto, M. P. Nightingale, and M. den Nijs, Phys. Rev. Lett. 49, 405 (1982). \n[5] D. Xiao, M.-C. Chang, and Q. Niu, Rev. Mod. Phys. 82, 1959 (2010). \n[6] F. D. M. Haldane, Phys. Rev. Lett. 61, 2015 (1988). \n[7] C. L. Kane and E. J. Mele, Phys. Rev. Lett. 95, 226801 (2005). \n[8] B. A. Bernevig, T. L. Hughes, and S.-C. Zhang, Science 314, 1757 (2006). \n[9] D. Hsieh, D. Qian, L. Wray, Y. Xia, Y. S. Hor, R. J. Cava, and M. Z. Hasan, Nature (London) 452, 970 (2008). \n[10] R. Yu, W. Zhang, H.-J. Zhang, S.-C. Zhang, X. Dai, and Z. Fang, Science 329, 61 (2010). \n[11] C.-Z. Chang et al., Science 340, 167 (2013). \n[12] D. Pesin and A. H. MacDonald, Nat. Mater. 11, 409 (2012). \n[13] Q.-F. Liang, L.-H. Wu, and X. Hu, New J. Phys. 15, 063031 (2013). \n[14] C. Nayak, S. H. Simon, A. Stern, M. Freedman, and S. Das Sarma, Rev. Mod. Phys. 80, 1083 (2008). \n[15] T. D. Stanescu and S. Tewari, J. Phys. Condens. Matter 25, 233201 (2013). \n[16] C. W. J. Beenakker, Annu. Rev. Condens. Matter Phys. 4, 113 (2013). \n[17] L.-H. Wu, Q.-F. Liang, and X. Hu, Sci. Tech. Adv. Mater. 15, 064402 (2014). \n[18] E. Yablonovitch, Phys. Rev. Lett. 58, 2059 (1987). \n[19] J. B. Pendry, A. J. Holden, D. J. Robbins, and W. J. Stewart, IEEE Trans. Microwave Theory Tech. 47, 2075 (1999). \n[20] F. D. M. Haldane and S. Raghu, Phys. Rev. Lett. 100, 013904 (2008). \n[21] Z. Wang, Y. D. Chong, J. D. Joannopoulos, and M. Soljăcić, Phys. Rev. Lett. 100, 013905 (2008). \n[22] Z. Wang, Y. Chong, J. D. Joannopoulos, and M. Soljăcić, Nature (London) 461, 772 (2009). \n[23] K. Fang, Z. Yu, and S. Fan, Nat. Photonics 6, 782 (2012). \n[24] A. B. Khanikaev, S. H. Mousavi, W.-K. Tse, M. Kargarian, A. H. MacDonald, and G. Shvets, Nat. Mater. 12, 233 (2013). \n[25] T. Ma, A. B. Khanikaev, S. H. Mousavi, and G. Shvets, arXiv:1401.1276. \n[26] G. Q. Liang and Y. D. Chong, Phys. Rev. Lett. 110, 203904 (2013). \n[27] M. C. Rechtsman, J. M. Zeuner, Y. Plotnik, Y. Lumer, D. Podolsky, F. Dreisow, S. Nolte, M. Segev, and A. Szameit, Nature (London) 496, 196 (2013). \n[28] C. He, X.-C. Sun, X.-P. Liu, M.-H. Lu, Y. Chen, L. Feng, and Y.-F. Chen, arXiv:1405.2869. \n[29] M. Hafezi, E. A. Demler, M. D. Lukin, and J. M. Taylor, Nat. Phys. 7, 907 (2011). \n[30] M. Hafezi, S. Mittal, J. Fan, A. Migdall, and J. M. Taylor, Nat. Photonics 7, 1001 (2013). \n[31] T. Ochiai, Phys. Rev. B 86, 075152 (2012); Int. J. Mod. Phys. B 28, 1441004 (2014). \n[32] L. Lu, J. D. Joannopoulos, and M. Soljačić, Nat. Photonics 8, 821 (2014). \n[33] J. D. Joannopoulos, S. G. Johnson, J. N. Winn, and R. D. Meade, Photonic Crystals: Molding the Flow of Light (Princeton University Press, New Jersey, 2008). \n[34] S. G. Johnson and J. D. Joannopoulos, Opt. Express 8, 173 (2001). \n[35] M. S. Dresselhaus, G. Dresselhaus, and A. Jorio, Group Theory: Application to the Physics of Condensed Matter (Springer-Verlag, Berlin, Heidelberg, 2008). \n[36] L. Fu, Phys. Rev. Lett. 106, 106802 (2011). \n[37] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevLett.114.223901 for discussions of pseudo-time-reversal symmetry, effective $k\\cdot p$ Hamiltonian and propagations of edge states, which includes Refs. [38–41]. \n[38] E. Prodan, Phys. Rev. B 80, 125327 (2009). \n[39] Y. Yang, Z. Xu, L. Sheng, B. Wang, D. Y. Xing, and D. N. Sheng, Phys. Rev. Lett. 107, 066602 (2011). \n[40] S. Hughes, L. Ramunno, J. F. Young, and J. E. Sipe, Phys. Rev. Lett. 94, 033903 (2005). \n[41] S. Mazoyer, J. P. Hugonin, and P. Lalanne, Phys. Rev. Lett. 103, 063903 (2009). \n[42] X. Huang, Y. Lai, Z. H. Hang, H. Zheng, and C. T. Chan, Nat. Mater. 10, 582 (2011). \n[43] K. Sakoda, Opt. Express 20, 9925 (2012). \n[44] K. Sakoda, Opt. Express 20, 3898 (2012). \n[45] S. M. Girvin, The Quantum Hall Effect: Novel Excitations and Broken Symmetries (Springer-Verlag, Berlin, Heidelberg, 1999). \n[46] A. Taflove and S. C. Hagness, Computational Electrodynamics: The Finite-Difference Time-Domain Method (Artech: Norwood, MA, 2000). \n[47] A. F. Oskooi, D. Roundy, M. Ibanescu, P. Bermel, J. D. Joannopoulos, and S. G. Johnson, Comput. Phys. Commun. 181, 687 (2010). \n[48] In real experiments, one prepares source $S_{+}(S_{-})$ in terms $H_{0}e^{i\\omega t}(\\hat{x}\\mp i\\hat{y})$ with $H_{0}$ an arbitrary amplitude, $\\omega$ a fre " + }, + { + "id": "10.1038_nature15373", + "DOI": "10.1038/nature15373", + "DOI Link": "http://dx.doi.org/10.1038/nature15373", + "Relative Dir Path": "mds/10.1038_nature15373", + "Article Title": "nulloparticle biointerfacing by platelet membrane cloaking", + "Authors": "Hu, CMJ; Fang, RH; Wang, KC; Luk, BT; Thamphiwatana, S; Dehaini, D; Nguyen, P; Angsantikul, P; Wen, CH; Kroll, AV; Carpenter, C; Ramesh, M; Qu, V; Patel, SH; Zhu, J; Shi, W; Hofman, FM; Chen, TC; Gao, WW; Zhang, K; Chien, S; Zhang, LF", + "Source Title": "NATURE", + "Abstract": "Development of functional nulloparticles can be encumbered by unullticipated material properties and biological events, which can affect nulloparticle effectiveness in complex, physiologically relevant systems(1-3). Despite the advances in bottom-up nulloengineering and surface chemistry, reductionist functionalization approaches remain inadequate in replicating the complex interfaces present in nature and cannot avoid exposure of foreign materials. Here we report on the preparation of polymeric nulloparticles enclosed in the plasma membrane of human platelets, which are a unique population of cellular fragments that adhere to a variety of disease-relevant substrates(4-7). The resulting nulloparticles possess a right-side-out unilamellar membrane coating functionalized with immunomodulatory and adhesion antigens associated with platelets. Compared to uncoated particles, the platelet membrane-cloaked nulloparticles have reduced cellular uptake by macrophage-like cells and lack particle-induced complement activation in autologous human plasma. The cloaked nulloparticles also display platelet-mimicking properties such as selective adhesion to damaged human and rodent vasculatures as well as enhanced binding to platelet-adhering pathogens. In an experimental rat model of coronary restenosis and a mouse model of systemic bacterial infection, docetaxel and vancomycin, respectively, show enhanced therapeutic efficacy when delivered by the platelet-mimetic nulloparticles. The multifaceted biointerfacing enabled by the platelet membrane cloaking method provides a new approach in developing functional nulloparticles for disease-targeted delivery.", + "Times Cited, WoS Core": 1388, + "Times Cited, All Databases": 1500, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000362095100045", + "Markdown": "# Nanoparticle biointerfacing by platelet membrane cloaking \n\nChe-Ming J. $\\mathrm{{Hu^{1,2*}}}$ , Ronnie H. Fang1,2\\*, Kuei-Chun Wang3,4\\*, Brian T. Luk2,3, Soracha Thamphiwatana1,2, Diana Dehaini1,2, Phu Nguyen3,4, Pavimol Angsantikul1,2, Cindy H. Wen5, Ashley V. Kroll1,2, Cody Carpenter1, Manikantan Ramesh1, Vivian $\\mathrm{\\dot{Q}u}^{1}$ , Sherrina H. Patel5, Jie $\\mathrm{Zhu}^{\\mathrm{5}}$ , William $\\mathrm{\\shi}^{5}$ , Florence M. Hofman6, Thomas C. Chen6, Weiwei Gao1,2, Kang Zhang1,4,5,7, Shu Chien3,4 & Liangfang Zhang1,2,4 \n\nDevelopment of functional nanoparticles can be encumbered by unanticipated material properties and biological events, which can affect nanoparticle effectiveness in complex, physiologically relevant systems1–3. Despite the advances in bottom-up nanoengineering and surface chemistry, reductionist functionalization approaches remain inadequate in replicating the complex interfaces present in nature and cannot avoid exposure of foreign materials. Here we report on the preparation of polymeric nanoparticles enclosed in the plasma membrane of human platelets, which are a unique population of cellular fragments that adhere to a variety of disease-relevant substrates4–7. The resulting nanoparticles possess a right-side-out unilamellar membrane coating functionalized with immunomodulatory and adhesion antigens associated with platelets. Compared to uncoated particles, the platelet membrane-cloaked nanoparticles have reduced cellular uptake by macrophage-like cells and lack particle-induced complement activation in autologous human plasma. The cloaked nanoparticles also display platelet-mimicking properties such as selective adhesion to damaged human and rodent vasculatures as well as enhanced binding to platelet-adhering pathogens. In an experimental rat model of coronary restenosis and a mouse model of systemic bacterial infection, docetaxel and vancomycin, respectively, show enhanced therapeutic efficacy when delivered by the platelet-mimetic nanoparticles. The multifaceted biointerfacing enabled by the platelet membrane cloaking method provides a new approach in developing functional nanoparticles for diseasetargeted delivery. \n\nOwing to their role as circulating sentinels for vascular damage and for invasive microorganisms, platelets have inspired the design of many functional nanocarriers8–13. The multitude of platelet functions stem from a unique set of surface moieties responsible for immune evasion14,15, subendothelium adhesion5,16, and pathogen interactions6,7. By adopting a cell membrane cloaking technique17–19, we demonstrate the preparation of platelet membrane-cloaked nanoparticles (PNPs) consisting of a biodegradable polymeric nanoparticle core shielded entirely in the plasma membrane of human platelets. Several inherent platelet properties, including immunocompatibility, binding to injured vasculature and pathogen adhesion, as well as their therapeutic implications, were studied (Extended Data Fig. 1a). \n\nPNPs were prepared by fusing human platelet membrane with $100\\mathrm{-nm}$ poly(lactic-co-glycolic acid) (PLGA) nanoparticles. Before platelet collection, blood and plasma samples were mixed with EDTA, which prevents platelet aggregation by deactivating fibrinogenbinding integrin aIIbb3 (ref. 20). Platelets were then processed for nanoparticle membrane cloaking (Extended Data Fig. 1b). Physicochemical characterizations revealed that the final PNPs were approximately $15\\mathrm{nm}$ larger than the uncoated PLGA nanoparticles (bare NPs) and possessed an equivalent surface charge to that of platelets and platelet membrane-derived vesicles (platelet vesicles) (Fig. 1a). Transmission electron microscopy (TEM) visualization showed the formation of distinctive nanoparticulates and consistent unilamellar membrane coatings over the polymeric cores (Fig. 1b and Extended Data Fig. 2). Improved colloidal stability was observed with the PNPs compared to bare NPs (Fig. 1c), which is attributable to the stabilizing effect by the plasma membrane’s hydrophilic surface glycans21. Translocation of platelet membrane protein content, including immunomodulatory proteins, CD47, CD55, and $\\mathbf{CD59^{14,15}}$ , integrin components, aIIb, a2, a5, a6, $\\upbeta1$ , and $\\upbeta3$ , and other transmembrane proteins, GPIba, GPIV, GPV, GPVI, GPIX, and $\\mathrm{CLEC}{-2^{5,16}}$ , onto the nanoparticles was examined by western blotting (Fig. 1d and Extended Data Fig. 3). Platelets derived from multiple protocols were prepared in parallel for comparison, and it was observed that the PNP preparation resulted in membrane protein retention and enrichment that was very similar across the different platelet sources (Extended Data Fig. 3). Notably, platelets derived from blood treated with heparin, an anticoagulant that inactivates thrombin rather than platelets, showed evidence of higher platelet activation including increased GPIba cleavage and CLEC-2 oligomerization22. Using blood anticoagulated with EDTA as the platelet source, a right-sideout membrane orientation on the PNPs was verified by both immunogold staining and flow cytometric analysis with antibodies targeting either the intracellular or extracellular domain of CD47 (Fig. 1e and Extended Data Fig. 4). Pro-thrombotic, platelet-activating molecules such as thrombin, ADP and thromboxane were removed in the PNP formulation (Fig. 1f–h), thereby permitting PNP administration with little risk of a thrombotic response (Fig. 1i). \n\nThe platelet-mimicking functionalities of PNPs were first studied via binding of the particles to human type IV collagen, a primary subendothelial component23. Fluorescently labelled PNPs, along with bare NPs and red blood cell membrane-cloaked nanoparticles (RBCNPs), were incubated on collagen-coated plates. The PNPs showed significantly enhanced retention compared to bare NPs and RBCNPs (Fig. 2a), indicating that the collagen adhesion was membrane-typespecific. Reduced PNP retention on non-collagen-coated plates and in the presence of anti-GPVI antibodies supports a specific collagen– platelet membrane interaction attributable to the presence of membrane glycoprotein receptors for collagen16 (Extended Data Fig. 3). Further examination of the differential binding of PNPs to endothelial and collagen surfaces was performed using collagen-coated tissue culture slides seeded with human umbilical vein endothelial cells (HUVECs). PNPs adhered primarily outside of areas encompassed by the cells (Fig. 2b and Extended Data Fig. 5a–g). In addition, the \n\n![](images/ea9a77211c3e0906e24213fd4ab3cb7ea81be63723e6caedaa87f72561fdfebb.jpg) \nFigure 1 | Preparation and characterization of PNPs. a, Physicochemical characterization of platelets, platelet vesicles, bare NPs, and PNPs ${\\mathrm{(}}n=3{\\mathrm{)}}$ . $\\zeta$ -pot., surface charge. b, TEM images of bare NPs (left) and PNPs (right) negatively stained with uranyl acetate. Scale bar, $100\\mathrm{nm}$ . c, Particle diameter of bare NPs and PNPs in water and in $1\\times\\mathrm{PBS}$ $(n=3)$ . d, Representative protein bands resolved using western blotting. e, TEM image of PNPs primary-stained with extracellular-domainspecific anti-CD47, and secondary-stained by an immunogold conjugate. Scale bar, $40\\mathrm{nm}$ . f–h, Platelet-activating contents including thrombin (f), ADP $\\mathbf{\\tau}(\\mathbf{g})$ and thromboxane $(\\mathrm{TXB}_{2},\\mathbf{h})$ in platelets, platelet vesicles, and PNPs were quantified $(n=3$ ). i, Platelet aggregation assay in which citrate-stabilized platelet rich plasma (PRP) was mixed with PBS, PNPs, or thrombin followed by spectroscopic examination of solution turbidity. All bars represent means $\\pm\\:s.\\mathrm{d}$ . \n\nPNPs were incubated with the extracellular matrix derived from decellularized human umbilical cord arteries. After PBS washes, scanning electron microscopy (SEM) revealed a significant number of PNPs remaining on the fibrous structures on the luminal side of the artery (Fig. 2c and Extended Data Fig. 5h, i). \n\nExamination of PNPs’ immunocompatibility was conducted using differentiated human THP-1 macrophage-like cells. The platelet membrane cloaking reduced particle internalization in a CD47-specific manner24, as blocking by anti-CD47 antibodies increased the cellular uptake (Fig. 2d). The PNPs were further investigated for their interactions with the complement system based on quantifications of C4d and Bb split products. After incubation in human plasma, complement activation was observed with bare NPs, reflecting their susceptibility to opsonization as well as the spontaneous reaction between C3 thioesters and the hydroxyl groups on the PLGA particles25. In contrast, an equal amount of PNPs mixed with autologous plasma showed no observable complement activation (Fig. 2e, f). This suppression of the complement system can be attributed to membrane-bound complement regulator proteins such as CD55 and CD59 (ref. 26; Extended Data Fig. 3). This result also attests to the completeness of the membrane cloaking, which shields the polymeric cores from plasma exposure and minimizes the risk of anaphylatoxin generation frequently associated with injectable nanocarriers27. \n\n![](images/099d98a35dd918f3ed93b5b6e5a4b2b3891e77e5367e04c64dd687289e70686c.jpg) \nFigure 2 | Collagen binding and immunocompatibility. a, Fluorescence quantification of nanoparticle retention on collagen-coated and non-coated plates $(n=6)$ ). b, Localization of PNPs (stained in red) on collagen-coated tissue culture slides seeded with HUVECs (nuclei stained in blue). Cellular periphery is outlined based on cytosolic staining. Scale bar, $10\\upmu\\mathrm{m}$ . c, A pseudocoloured SEM image of the extracellular matrix of a decellularized human umbilical cord artery after PNP incubation (PNPs coloured in orange). Scale bar, $500\\mathrm{nm}$ . d, Flow cytometric analysis of nanoparticle uptake by human THP-1 macrophage-like cells $(n=3)$ ). e, f, Classical complement activation measured by C4d split products (e) and alternative complement activation measured by Bb split products (f) for bare NPs, platelet vesicles, and PNPs in autologous human plasma ${\\mathrm{(}}n=4{\\mathrm{)}}$ ). Zymosan and untreated plasma are used as positive and negative controls, respectively. All bars represent means $\\pm$ s.d. $^{*}P\\leq0.05$ , $\\ast\\ast P\\leq0.01$ , $^{***}P\\le0.001$ . \n\nThe therapeutic potential of PNPs was first examined by assessing their selective adherence to damaged vasculatures. A segment of the human carotid artery was surgically scraped to expose the subendothelial matrix (Fig. 3a). The intact and damaged artery samples were subsequently incubated with fluorescently labelled PNPs for 30 s followed by repeated PBS washes. The resulting arterial cross-sections and en face visualizations revealed that the denuded artery was more prone to PNP adhesion than the intact artery (Fig. 3b, c). In Fig. 3c, it can also be observed that PNPs bind preferentially to the edges of the intact artery, where subendothelium was exposed upon tissue incision. This selective PNP adhesion was further validated in a rat model of angioplasty-induced arterial injury. Pharmacokinetic analyses and biodistribution studies showed that $590\\%$ of the PNPs were distributed to tissues $30\\mathrm{min}$ after intravenous injection, with liver and spleen being the primary distribution organs (Extended Data Fig. 6a, b). A comprehensive blood chemistry panel analysis revealed that the PNPs did not inflict observable adverse effects in the rats (Extended Data Fig. 6c). Selective particle binding to the denuded artery was observed upon examination of the aortic branch $^{2\\mathrm{h}}$ after administration of PNP (Fig. 3d and Extended Data Fig. 7). The PNPs were localized on the luminal side above the smooth muscle layer (Fig. 3e), and retention at the injury site lasted for at least 5 days (Fig. 3f). In a rat model of coronary restenosis, therapeutic relevance of platelet-mimicking delivery was examined using docetaxel-loaded PNPs (PNP-Dtxl) (Extended Data Fig. 8). PNP-Dtxl treatment on day 0 and 5 at $0.3\\mathrm{mg}$ per kg body weight $(\\mathrm{mg}\\mathrm{kg}^{-1})$ of docetaxel dosing potently inhibited neointima growth in balloon-denuded rats as evidenced by the arterial cross-sections collected on day 14 (Fig. 3g, h and Extended Data Fig. 9). To evaluate the vascular remodelling quantitatively, intima-to-media ratio (I/M) and luminal obliteration were calculated. Compared to free docetaxel, which resulted in an $\\mathrm{I}/\\mathrm{M}$ of $0.76\\pm0.18$ (mean 6 s.d.) and a luminal obliteration of $33.6\\%$ , PNP-Dtxl yielded significantly lower values of $0.18\\pm0.06$ and $8.0\\%$ , respectively $P{\\leq}0.0001$ ) (Fig. 3i, j). These results demonstrate the benefit of PNP-directed delivery in improving drug localization to diseased vasculatures. \n\nWe further examined the therapeutic potential of PNPs against platelet-adhering pathogens. Opportunistic bacteria, including several strains of staphylococci and streptococci, exploit platelets by both direct and indirect adherence mechanisms for tissue localization and immune evasion6. To demonstrate that PNPs can exploit the inherent bacterial adherence mechanism for targeted antibiotics delivery, MRSA252, a strain of methicillin-resistant Staphylococcus aureus expressing a serine-rich adhesin for platelets (SraP)28, was used as a model pathogen for particle adhesion study. After $10\\mathrm{min}$ of incubation between formalin-fixed MRSA252 and different nanoformulations, the collected bacteria showed preferential binding by PNPs (Fig. 4a), exhibiting a 12-fold increase in PNP retention compared to bare NPs (Fig. 4b and Extended Data Fig. 10). This adherence was membrane-specific as RBCNPs showed lower retention than PNPs. The therapeutic potential of PNPs was further evaluated using vancomycin-loaded formulations. In an in vitro antimicrobial study, live MRSA252 bacteria were briefly incubated with free vancomycin, vancomycin-loaded RBCNPs (RBCNP-Vanc), or vancomycin-loaded PNPs (PNP-Vanc) followed by a wash and culturing in fresh media. The PNP-Vanc formulation showed statistically significant improvement in MRSA252 reduction that corroborates the targeting effect of the particles (Fig. 4c). An in vivo antimicrobial efficacy study was further conducted using a mouse model of systemic MRSA252 infection. Mice systemically challenged with $6\\times10^{6}$ colony-forming units (CFU) of MRSA252 received once daily intravenous treatment of free vancomycin, RBCNP-Vanc, or PNP-Vanc for 3 days at $10\\mathrm{mg}\\mathrm{kg}^{-1}$ of vancomycin. A control group of high-dose vancomycin treatment in which infected mice received free vancomycin at $3\\dot{0}\\mathrm{mg}\\mathrm{kg}^{-1}$ twice daily was conducted in parallel. $24\\mathrm{h}$ after the last treatment, bacterial enumeration at the primary infection organs showed that the PNP-Vanc resulted in the lowest mean bacterial counts across all organs (Fig. 4d–i). Statistical analyses revealed significance between PNP-Vanc and free vancomycin at equivalent dosage in the lung, liver, spleen and kidney. In comparison to free vancomycin at sixfold the dosage, PNP-Vanc showed significantly better antimicrobial efficacy in the liver and spleen and was at least as effective in the blood, heart, lung and kidney. Notably, compared to RBCNP-Vanc, PNP-Vanc showed significantly higher potency in the heart, lung, liver and spleen, reflecting membrane-specific modulation of nanoparticle performance. The study validates the feasibility of harnessing biomembrane interfaces to improve infectious disease treatment. \n\n![](images/f9e9ac556d5003a082771c73882093540bd16bc050d33b51def9fbf6506d379a.jpg) \nFigure 3 | Adherence to damaged human and rodent vasculatures. a, Haematoxylin and eosin (H&E)-stained cross-sections of undamaged (top) and damaged (bottom) human carotid arteries. Scale bar, $200\\upmu\\mathrm{m}$ . b, Fluorescence images of the cross-section (scale bar, $200\\upmu\\mathrm{m},$ ) and c, the luminal side (scale bar, $500\\upmu\\mathrm{m}\\dot{},$ ) of undamaged (top) and damaged (bottom) arteries after PNP incubation (tissue in green and PNPs in red). d, e, 3D reconstructed images of intact (top) and balloon-denuded (bottom) arterial walls from multisectional images after intravenous administration of PNPs in rats (cell nuclei in blue and PNPs in red). Dimensions, \n\n![](images/65e2c9f2a53d13cbf4e448769a58dc83d624f5cbe68cb62296b3fa99a350bdc9.jpg) \n$152.5\\upmu\\mathrm{m}\\times116\\upmu\\mathrm{m}\\times41\\upmu\\mathrm{m}$ f, Retention of PNPs at the denuded and the intact arteries over $120\\mathrm{h}$ after PNP administration $(n=6)$ . g, Representative H&E-stained arterial cross-sections from different treatment groups in a rat model of coronary restenosis. Scale bar, $200\\upmu\\mathrm{m}$ . h, Zoomed-in H&E-stained arterial cross-sections highlight the different vascular remodelling from the different treatment groups. I, intima; M, media. Scale bar, $100\\upmu\\mathrm{m}$ . i, j, Quantitative analysis of intima-to-media area ratio and luminal obliteration from the different treatment groups $(n=6)$ ). All bars represent means $\\pm$ s.d. NS, no statistical significance. \nFigure 4 | Binding to platelet-adhering pathogens. a, SEM images of MRSA252 bacteria after incubation with PBS (top left), bare NPs (top right), RBCNPs (bottom left), and PNPs (bottom right). Scale bar, $1\\upmu\\mathrm{m}$ . b, Normalized fluorescence intensity of dye-loaded nanoformulations retained on MRSA252 based on flow cytometric analysis. Bars represent means $\\pm\\:s.\\mathrm{d}$ . ${\\mathrm{(}}n=3{\\mathrm{)}}$ ). c, In vitro antimicrobial efficacy of free vancomycin, vancomycin-loaded RBCNPs (RBCNP-Vanc), and vancomycin-loaded PNPs (PNP-Vanc). Bars represent means $\\pm\\:s.\\mathrm{d}$ $(n=3)$ . d–i, $I n$ vivo antimicrobial efficacy of free vancomycin at $10\\mathrm{mg}\\mathrm{kg}^{-1}$ (Vanc-10), RBCNPVanc-10, PNP-Vanc-10, and free vancomycin at 6 times the dosing (Vanc-60, $60\\mathrm{mg}\\mathrm{kg}^{-1},$ ) was examined in a mouse model of systemic infection with MRSA252. After 3 days of treatments, bacterial loads in different organs including blood (d), heart (e), lung (f), liver $\\mathbf{\\sigma}(\\mathbf{g})$ , spleen ${\\bf\\Pi}({\\bf h})$ and kidney (i) were quantified. Bars represent means $\\pm$ s.e.m. ${\\displaystyle(n=14)}$ . $^{*}P\\leq0.05$ , $^{**}P\\le0.01$ , $\\ast\\ast\\ast P\\leq0.001$ , $****P\\le0.0001$ . \n\nThe vast medical relevance of platelets has inspired many plateletmimicking systems that target dysfunctional vasculature in cardiovascular diseases8,9, traumas10,11,13, cancers12 and acute inflammations29. The present PNP platform exploits platelet membrane in its entirety to enable biomimetic interactions with proteins, cells, tissues and microorganisms. Towards translation, the platform would benefit from existing infrastructures and logistics for transfusion medicine, polymeric nanotherapeutics and cell-derived pharmaceutics. Previous work on the cell membrane cloaking approach demonstrated high cloaking efficiency30 and viable storage18 upon platform optimization (Extended Data Fig. 2f–h). By employing large-scale purification and dispersion techniques commonly applied to biologics, reliable platelet membrane derivation and PNP production can be envisioned. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# Received 21 November 2014; accepted 12 August 2015. Published online 16 September 2015. \n\n1. Pelaz, B. et al. Interfacing engineered nanoparticles with biological systems: anticipating adverse nano-bio interactions. Small 9, 1573–1584 (2013). \n2. Salvati, A. et al. Transferrin-functionalized nanoparticles lose their targeting capabilities when a biomolecule corona adsorbs on the surface. Nature Nanotechnol. 8, 137–143 (2013). \n3. Tenzer, S. et al. Rapid formation of plasma protein corona critically affects nanoparticle pathophysiology. Nature Nanotechnol. 8, 772–781 (2013). \n4. Born, G. V. & Cross, M. J. The aggregation of blood platelets. J. Physiol. (Lond.) 168, 178–195 (1963). \n5. Kieffer, N. & Phillips, D. R. Platelet membrane glycoproteins: functions in cellular interactions. Annu. Rev. Cell Biol. 6, 329–357 (1990). \n6. Fitzgerald, J. R., Foster, T. J. & Cox, D. The interaction of bacterial pathogens with platelets. Nature Rev. Microbiol. 4, 445–457 (2006). \n7. Yeaman, M. R. Platelets in defense against bacterial pathogens. Cell. Mol. Life Sci. 67, 525–544 (2010). \n8. Peters, D. et al. Targeting atherosclerosis by using modular, multifunctional micelles. Proc. Natl Acad. Sci. USA 106, 9815–9819 (2009). \n9. Chan, J. M. et al. Spatiotemporal controlled delivery of nanoparticles to injured vasculature. Proc. Natl Acad. Sci. USA 107, 2213–2218 (2010). \n10. Bertram, J. P. et al. Intravenous hemostat: nanotechnology to halt bleeding. Sci. Transl. Med. 1, 11ra22 (2009). \n11. Modery-Pawlowski, C. L. et al. Approaches to synthetic platelet analogs. Biomaterials 34, 526–541 (2013). \n12. Simberg, D. et al. Biomimetic amplification of nanoparticle homing to tumors. Proc. Natl Acad. Sci. USA 104, 932–936 (2007). \n13. Anselmo, A. C. et al. Platelet-like nanoparticles: mimicking shape, flexibility, and surface biology of platelets to target vascular injuries. ACS Nano 8, 11243–11253 (2014). \n14. Olsson, M., Bruhns, P., Frazier, W. A., Ravetch, J. V. & Oldenborg, P. A. Platelet homeostasis is regulated by platelet expression of CD47 under normal conditions and in passive immune thrombocytopenia. Blood 105, 3577–3582 (2005). \n15. Sims, P. J., Rollins, S. A. & Wiedmer, T. Regulatory control of complement on blood platelets. Modulation of platelet procoagulant responses by a membrane inhibitor of the C5b-9 complex. J. Biol. Chem. 264, 19228–19235 (1989). \n16. Nieswandt, B. & Watson, S. P. Platelet-collagen interaction: is GPVI the central receptor? Blood 102, 449–461 (2003). \n17. Hu, C. M. et al. Erythrocyte membrane-camouflaged polymeric nanoparticles as a biomimetic delivery platform. Proc. Natl Acad. Sci. USA 108, 10980–10985 (2011). \n18. Hu, C. M., Fang, R. H., Copp, J., Luk, B. T. & Zhang, L. A biomimetic nanosponge that absorbs pore-forming toxins. Nature Nanotechnol. 8, 336–340 (2013). \n19. Hu, C. M., Fang, R. H., Luk, B. T. & Zhang, L. Nanoparticle-detained toxins for safe and effective vaccination. Nature Nanotechnol. 8, 933–938 (2013). \n20. Gachet, C. et al. Alpha IIb beta 3 integrin dissociation induced by EDTA results in morphological changes of the platelet surface-connected canalicular system with differential location of the two separate subunits. J. Cell Biol. 120, 1021–1030 (1993). \n21. Luk, B. T. et al. Interfacial interactions between natural RBC membranes and synthetic polymeric nanoparticles. Nanoscale 6, 2730–2737 (2014). \n22. Hughes, C. E. et al. CLEC-2 activates Syk through dimerization. Blood 115, 2947–2955 (2010). \n23. Kalluri, R. Basement membranes: structure, assembly and role in tumour angiogenesis. Nature Rev. Cancer 3, 422–433 (2003). \n24. Rodriguez, P. L. et al. Minimal “Self” peptides that inhibit phagocytic clearance and enhance delivery of nanoparticles. Science 339, 971–975 (2013). \n25. Law, S. K. A. & Dodds, A. W. The internal thioester and the covalent binding properties of the complement proteins C3 and C4. Protein Sci. 6, 263–274 (1997). \n26. Terstappen, L. W. M. M., Nguyen, M., Lazarus, H. M. & Medof, M. E. Expression of the DAF (CD55) and CD59 antigens during normal hematopoietic cell differentiation. J. Leukoc. Biol. 52, 652–660 (1992). \n27. Andersen, A. J., Hashemi, S. H., Andresen, T. L., Hunter, A. C. & Moghimi, S. M. Complement: alive and kicking nanomedicines. J. Biomed. Nanotechnol. 5, 364–372 (2009). \n28. Siboo, I. R., Chambers, H. F. & Sullam, P. M. Role of SraP, a Serine-Rich Surface Protein of Staphylococcus aureus, in binding to human platelets. Infect. Immun. 73, 2273–2280 (2005). \n29. Kamaly, N. et al. Development and in vivo efficacy of targeted polymeric inflammation-resolving nanoparticles. Proc. Natl Acad. Sci. USA 110, 6506–6511 (2013). \n30. Hu, C. M. et al. ‘Marker-of-self’ functionalization of nanoscale particles through a top-down cellular membrane coating approach. Nanoscale 5, 2664–2668 (2013). \n\nAcknowledgements This work is supported by the National Institutes of Health under Award Numbers R01DK095168 (L.Z.), R01HL108735 (S.C.) and R01EY25090 (K.Z.), and partially by the Defense Threat Reduction Agency Joint Science and Technology Office for Chemical and Biological Defense under Grant Number HDTRA1-14-1-0064 (L.Z.). R.H.F. is supported by a National Institutes of Health R25CA153915 training grant from the National Cancer Institute. \n\nAuthor Contributions C.-M.J.H., R.H.F., K.-C.W., B.T.L., K.Z., S.C. and L.Z. conceived and designed the experiments; C.-M.J.H., R.H.F., K.-C.W., B.T.L., S.T., D.D., P.N., P.A., C.H.W., A.V.K., C.C., M.R., V.Q., S.H.P., J.Z., W.S., F.M.H., T.C.C. and W.G. performed all the experiments. The manuscript was written by C.-M.J.H., R.H.F., B.T.L., W.G. and L.Z. All authors discussed the results and reviewed the manuscript. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Correspondence and requests for materials should be addressed to L.Z. (zhang@ucsd.edu), S.C. (shuchien@ucsd.edu) or K.Z. (kang.zhang@gmail.com). \n\n# METHODS \n\nHuman platelet isolation and platelet membrane derivation. Human type $\\mathrm{o^{-}}$ blood anti-coagulated with $1.5\\mathrm{mg}\\mathrm{ml}^{-1}$ EDTA was purchased from BioreclamationIVT and processed for platelet collection approximately $16\\mathrm{h}$ after blood collection. Unless otherwise stated, platelets derived from this commercial blood source were used in this study. Fresh human type $\\mathrm{o^{-}}$ blood was also collected with dipotassium EDTA-treated or lithium heparin-treated blood collection tubes (Becton, Dickinson and Company) under the approval of the Institutional Review Board (IRB) at the University of California, San Diego, USA. Patients consented to use of their blood samples for this study before collection. The freshly drawn blood was processed for platelet collection approximately $30\\mathrm{min}$ after blood draw. In addition, unexpired (in-dated) human type $\\mathrm{o}^{-}$ platelet rich plasma (PRP) in acid-citrate-dextrose (ACD) was purchased from the San Diego Blood Bank. Samples not originally drawn in EDTA were adjusted to a concentration of $5\\mathrm{mM}$ EDTA before platelet collection. To isolate platelets, the blood and plasma samples were centrifuged at $100g$ for $20\\mathrm{min}$ at room temperature to separate red blood cells and white blood cells. The resulting PRP was then centrifuged at $100g$ for $20\\mathrm{min}$ to remove remaining blood cells. PBS buffer containing $1\\mathrm{mM}$ of EDTA and $2\\upmu\\mathrm{M}$ of prostaglandin E1 (PGE1, Sigma Aldrich) was added to the purified PRP to prevent platelet activation. Platelets were then pelleted by centrifugation at $800g$ for $20\\mathrm{min}$ at room temperature, after which the supernatant was discarded and the platelets were resuspended in PBS containing $1\\mathrm{mM}$ of EDTA and mixed with protease inhibitor tablets (Pierce). $1.5\\mathrm{ml}$ aliquots of platelet solution containing ${\\sim}3\\times10^{9}$ platelets were prepared and used to cloak $1\\mathrm{mg}$ of PLGA nanoparticles. \n\nPlatelet membrane was derived by a repeated freeze-thaw process. Aliquots of platelet suspensions were first frozen at $-80^{\\circ}\\mathrm{C},$ thawed at room temperature, and pelleted by centrifugation at $4{,}000g$ for $3\\mathrm{min}$ After three repeated washes with PBS solution mixed with protease inhibitor tablets, the pelleted platelet membranes were suspended in water and sonicated in a capped glass vial for $5\\mathrm{min}$ using a Fisher Scientific FS30D bath sonicator at a frequency of $42\\mathrm{kHz}$ and a power of $100\\mathrm{W}$ . The presence of platelet membrane vesicles was verified by size measurement using dynamic light scattering (DLS) and morphological examination by transmission electron microscopy (TEM). \n\nPlatelet membrane-cloaked nanoparticle (PNP) preparation and characterization. $100\\mathrm{nm}$ polymeric cores were prepared using $0.67\\mathrm{dlg}^{-1}$ carboxylterminated 50:50 poly(lactic-co-glycolic) acid (PLGA) (LACTEL Absorbable Polymers) in a nanoprecipitation process. $1~\\mathrm{ml}$ of $10\\mathrm{mg}\\mathrm{ml}^{-1}$ PLGA solution in acetone was added dropwise to $3\\mathrm{ml}$ of water. For fluorescently labelled nano formulations, $^{1,1^{\\prime}}$ -dioctadecyl- $^{3,3,3^{\\prime},3^{\\prime}}$ -tetramethylindodicarbocyanine perchlorate (DiD, excitatio $\\mathrm{\\Omega_{1}=644\\mathrm{nm/emission=665\\mathrm{nm}_{\\Omega}}}$ , Life Technologies) was loaded into the polymeric cores at $0.1\\mathrm{wt\\%}$ . The mixture was then stirred in open air for 1 h and placed in vacuum for another $^{3\\mathrm{h}}$ . The resulting nanoparticle solution was filtered with 10 kDa MWCO Amicon Ultra-4 Centrifugal Filters (Millipore). Platelet membrane cloaking was then accomplished by dispersing and fusing platelet membrane vesicles with PLGA particles by sonication using an FS30D bath sonicator at a frequency of $42\\mathrm{kHz}$ and a power of $100\\mathrm{W}$ for $2\\mathrm{min}$ . The size and the surface zeta potential of replicate PNP samples $(n=3)$ were obtained by dynamic light scattering (DLS) measurements using a Malvern ZEN 3600 Zetasizer. PBS stability was examined by mixing $1\\mathrm{mg}\\mathrm{ml}^{-1}$ of PNPs in water with $2\\times{\\mathrm{PBS}}$ at a 1:1 volume ratio. Storability of PNPs was examined by suspending PNPs in $10\\%$ sucrose. The nanoparticle solutions were subject to either a freeze-thaw cycle or lyophilization followed by resuspension. The resulting particle solution was then monitored for particle size using DLS. The structure of PNPs was examined with TEM after negative staining with $1\\mathrm{wt\\%}$ uranyl acetate using an FEI $200\\mathrm{kV}$ Sphera microscope. RBCNPs were prepared using the same polymeric cores and RBC membranes of equivalent total surface area to the platelet membranes following a previously described protocol16. The RBCNPs were characterized using DLS and had similar size and zeta potential as the PNPs. \n\nDocetaxel-loaded PLGA nanoparticle cores were prepared by a nanoprecipitation process. $10\\mathrm{wt\\%}$ docetaxel was added to $5\\mathrm{mg}$ PLGA in acetone and precipitated dropwise into $3\\mathrm{ml}$ water. The solvent was evaporated as described above and free docetaxel was removed by repeated wash steps. Vancomycin-loaded nanoparticles were synthesized using a double emulsion process. The inner aqueous phase consisted of $25\\upmu\\mathrm{l}$ of vancomycin (Sigma Aldrich) dissolved in $1\\mathrm{MNaOH}$ at $\\mathrm{\\dot{2}00}\\mathrm{mgml^{-1}}$ . The outer phase consisted of $500\\upmu\\mathrm{l}$ of PLGA polymer dissolved in dichloromethane at $50\\mathrm{{mg}\\mathrm{{ml}^{-1}}}$ . The first emulsion was formed by sonication at $70\\%$ power pulsed $2s\\ \\mathrm{on}/1;$ s off) for $2\\mathrm{min}$ on a Fisher Scientific 150E Sonic Dismembrator. The resulting emulsion was then emulsified in aqueous solution under the same dispersion setting. The final water/oil/water emulsion was added to $10\\mathrm{ml}$ of water and the solvent was evaporated in a fume hood under gentle stirring for $^{3\\mathrm{h}}$ . The particles were collected by centrifugation at $80,000g$ in a Beckman Coulter Optima L-90K Ultracentrifuge. The particles were washed and resuspended in water. Upon preparation of drug-loaded PLGA cores, cell membrane coating was performed by adding the appropriate surface area equivalent of either platelet or red blood cell membrane followed by 3 min of sonication in a Fisher Scientific FS30D Bath Sonicator. Particle size, polydispersity (PDI), and surface zeta potential were characterized using DLS. Drug loading yield and release rate of replicate samples $(n=3$ ) were quantified by high performance liquid chromatography (HPLC). Drug release was determined by dialyzing $500\\upmu\\mathrm{l}$ of particle solution at a concentration of $2.67\\mathrm{mg}\\mathrm{ml}^{-1}$ in PBS using $3.5\\mathrm{K}$ MWCO Slide-A-Lyzers (Thermo Scientific). \n\nExamination of platelet membrane proteins. PNPs were purified from unbound proteins or membrane fragments by centrifugation at $16{,}000g$ in $10\\%$ sucrose. Platelet-rich plasma, platelets, platelet membrane vesicles, and PNPs were then normalized to equivalent overall protein concentration using a Pierce BCA Protein Assay Kit (Life Technologies). To examine the effect of different platelet derivation protocols on the membrane protein expression, platelets collected from commercial blood anti-coagulated in EDTA, freshly drawn blood anti-coagulated in EDTA or heparin, and transfusion-grade PRP in ACD were prepared in parallel. All platelets were processed using the aforementioned platelet membrane derivation protocol for PNP preparation. The samples containing equivalent total proteins were then lyophilized, prepared in lithium dodecyl sulfate (LDS) sample loading buffer (Invitrogen), and separated on a $4{-}12\\%$ Bis-Tris 17-well minigel in MOPS running buffer using a Novex Xcell SureLock Electrophoresis System (Life Technologies). Identification of key membrane proteins by western blotting was performed using primary antibodies including mouse anti-human CD47 (eBioscience, B6H12), mouse anti-human CD55 (Biolegend, JS11), mouse antihuman CD59 (Biolegend, p282 (H19)), mouse anti-human integrin aIIb subunit (Biolegend, HIP8), rat anti-human integrin a2 subunit (R&D Systems, 430907), rabbit anti-human integrin a5 subunit (Abgent, AP12204c), mouse anti-human integrin a6 subunit (Abgent, AM1828a), mouse anti-human integrin $\\upbeta1$ subunit (R&D Systems, 4B7R), mouse anti-human integrin b3 subunit (Biolegend, VIPL2), mouse anti-human GPIba (R&D Systems, 486805), mouse anti-human GPIV (R&D Systems, 877346), mouse anti-human GPV (Santa Cruz Biotech, G-11), rat anti-human GPVI (EMD Millipore, 8E9), rabbit anti-human GPIX (Santa Cruz Biotech, A-9), and mouse anti-human CLEC-2 (Genetex, 8J24). A goat anti-mouse IgG-HRP conjugate (Biolegend, Poly4053), a goat anti-rat IgGHRP conjugate (Biolegend, Poly4054), or a donkey anti-rabbit IgG–horseradish peroxidase (HRP) conjugate (Biolegend, Poly4064) was used for secondary staining based on the isotype of the primary antibody. MagicMark XP western protein standard (Invitrogen) was used as a molecular weight ladder. The nitrocellulose membrane was then incubated with ECL western blotting substrate (Pierce) and developed with the Mini-Medical/90 Developer (ImageWorks). \n\nExamination of protein sidedness on PNPs. For immunogold staining, a drop of the PNP solution $(1\\mathrm{mg}\\mathrm{ml}^{-1})$ was deposited onto a glow-discharged carboncoated grid. The grid was then washed 3 times with PBS, blocked with $1\\%$ BSA for $15\\mathrm{min}$ , and stained with $0.5\\mathrm{mg}\\mathrm{ml}^{-1}$ of anti-CD47 targeted to either the intracellular or extracellular domain of the protein. After $^{\\textrm{1h}}$ of incubation, the samples were rinsed with PBS containing $1\\%$ BSA for 6 times and stained with anti-rabbit IgG-gold conjugate $(5\\mathrm{nm})$ solution (Sigma Aldrich) for another hour. After 6 PBS washes, the samples were fixed with $1\\%$ glutaraldehyde in PBS for $5\\mathrm{{min}}$ and washed with water 6 times. The sample grids were subsequently stained with $2\\%$ vanadium solution (Abcam) and visualized using an FEI $200\\mathrm{kV}$ Sphera microscope. \n\nFor flow cytometric analysis, $2.0\\upmu\\mathrm{m}$ carboxyl-functionalized polystyrene beads at a concentration of $4\\mathrm{wt\\%}$ (Life Technologies) were functionalized with rabbit N terminus-targeted (extracellular) anti-human CD47 (Aviva Biosystems, ARP63284), rabbit intracellular-domain-targeted anti-CD47 (Genetex, EPR4150(2)), or rabbit anti-ovalbumin (Abcam, ab1221) as a sham antibody by EDC/NHS chemistry. The resulting antibody-modifed beads were re-suspended in $100\\upmu\\mathrm{l}$ of DI water. The bead solution was first incubated with $1\\mathrm{mg}$ of bovine serum albumin (BSA, Sigma Aldrich) to block non-specific interactions and then mixed with $\\mathrm{1ml}$ of fluorescently labelled PNPs $(200\\mathrm{\\textmugml^{-1}},$ . The mixture solution was incubated at room temperature for 2 h and then centrifuged to remove the unbound PNPs. The collected polystyrene beads were then subjected to flow cytometric analysis. \n\nPlatelet aggregation assay. Platelets, platelet membrane vesicles, and PNPs of equivalent membrane content were prepared and examined for platelet-activating molecules, including thrombin, ADP, and thromboxane, using a SensoLyte 520 Thrombin Activity Assay Kit (AnaSpec), ADP Colorimetric/Fluorometric Assay Kit (Sigma Aldrich), and Thromboxane B2 $\\mathrm{\\DeltaTXB}_{2})$ ELISA Kit (Enzo Life Sciences), respectively, based on the manufacturers’ instructions. Each sample was assayed in replicate $(n=3$ ). \n\nAggregation of platelets in the presence of PNPs was assessed using a spectrophotometric method. $1\\mathrm{ml}$ aliquot of platelet rich plasma (PRP) was first prepared from human whole blood with sodium citrate as the anti-coagulant. The plasma was then loaded into a cuvette followed by addition of $500\\upmu\\mathrm{l}$ of $2\\mathrm{mg}\\mathrm{ml}^{-1}$ PNPs in PBS solution. As negative and positive controls, the PRP was mixed with $500\\upmu\\mathrm{l}$ of PBS or $500\\upmu\\mathrm{l}$ of PBS containing $0.5\\mathrm{IU}\\mathrm{ml}^{-1}$ of human thrombin (Sigma Aldrich), respectively. The cuvettes were immediately placed in a TeCan Infinite M200 reader and monitored for change in absorbance at $650\\mathrm{nm}$ over time, and platelet aggregation was observed based on the reduction of turbidity. \n\nCollagen binding study. Collagen type IV derived from human placenta (Sigma Aldrich) was reconstituted to a concentration of $2.0\\mathrm{mg}\\mathrm{ml}^{-1}$ in $0.25\\%$ acetic acid. $200\\upmu\\mathrm{l}$ of the collagen solution was then added to each well of a 96-well assay plate and incubated overnight at $4^{\\circ}\\mathrm{C}$ . Prior to the collagen binding study, the plate was blocked with $2\\%$ BSA and washed three times with PBS. For the collagen binding study, $100\\upmu\\mathrm{l}$ of $1\\mathrm{mg}\\mathrm{ml}^{-1}$ DiD-loaded nanoformulations in water were added into replicate wells ${\\bf\\dot{\\boldsymbol{n}}}=6{\\bf\\dot{\\boldsymbol{\\mathbf{\\rho}}}},$ ) of collagen-coated or non-collagen-coated plates. After 30 s of incubation, the plates were washed three times. Retained nanoparticles were then dissolved with $100\\upmu\\mathrm{l}$ of DMSO for fluorescence quantification using a TeCan Infinite M200 reader. \n\nDifferential adhesion to endothelial and collagen surfaces. Collagen type IV was coated on 8-well Lab-Tek II chamber slides (Nunclon) as described above. The collagen-coated chamber slides were used to seed primary HUVECs obtained from the American Type Culture Collection and cultured in HUVEC Culture Medium (Sigma Aldrich) supplemented with $10\\%$ fetal bovine serum for $24\\mathrm{h}$ . The cells were then incubated with $1\\mathrm{mg}\\mathrm{ml}^{-1}$ DiD-loaded PNPs in PBS at $4^{\\circ}\\mathrm{C}$ for 30 s. Next the cells were washed with PBS three times and fixed with tissue fixative (Millipore) for $30\\mathrm{min}$ at room temperature. Fluorescence staining was done with $^{4^{\\prime},6}$ -diamidino-2-phenylinodle (DAPI, Life Technologies) for the nuclei and 22- $\\overset{\\cdot}{n}$ -(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-23,24-bisnor-5-cholen- $3\\upbeta$ -ol (NBD cholesterol, Life Technologies) for the cytosol before mounting the cells in ProLong Gold antifade reagent (Life Technologies) and imaged using a DeltaVision deconvolution scanning fluorescence microscope. $z$ -stacks were collected at $0.25\\upmu\\mathrm{m}$ intervals over $10\\upmu\\mathrm{m}$ . The images were deconvolved and superimposed. DiD fluorescence signal over collagen and endothelial surfaces as defined by the boundaries of NBD fluorescence were analysed using ImageJ. PNP retention over collagen and endothelial surfaces was quantified based on distinct images ${\\mathrm{(}n=10\\mathrm{)}}$ in which the average fluorescence per unit area was analysed. \n\nCellular uptake study with macrophage-like cells. THP-1 cells were obtained directly from the American Type Culture Collection and used without further authentication or testing for mycoplasma contamination. The cells were maintained in RPMI 1640 media (Life Technologies) supplemented with $10\\%$ FBS (Sigma Aldrich). THP-1 cells were differentiated in $\\mathrm{\\bar{100}n g{m l}^{-1}}$ phorbol myristate acetate (PMA, Sigma Aldrich) for $^{48\\mathrm{h}}$ and differentiation was visually confirmed by cellular attachment to Petri dishes. For the cellular uptake study, the differentiated macrophage-like cells were incubated in replicate wells ${\\bf\\dot{\\rho}}_{n}=3\\dot{\\bf\\rho}_{,}$ ) with DiD-loaded PNPs, anti-CD47 blocked PNPs, and bare NPs at $100\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ in culture media. After $30\\mathrm{min}$ of incubation at $37^{\\circ}\\mathrm{C}$ , the macrophage-like cells were scraped off the Petri dish and washed three times in PBS to remove non-internalized particles. Flow cytometry was performed to examine nanoparticle uptake by the macrophage-like cells. All flow cytometry studies were conducted on a FACSCanto II flow cytometer (BD Biosciences) and the data was analysed using FlowJo software from Tree Star. Statistical analysis was performed based on a twotailed, unpaired t-test. \n\nComplement activation study. To assess complement system activation, two complement split products (C4d and Bb) were analysed using enzyme-linked immunosorbent assay kits (Quidel Corporation). The nanoparticles were incubated in replicate aliquots $(n=4)$ of human serum at a volume ratio of 1:5 in a shaking incubator $({80}\\mathrm{r.p.m.})$ ) at $37^{\\circ}\\mathrm{C}$ for 1 h. The reaction was then stopped by adding 60 volumes of PBS containing $0.05\\%$ Tween-20 and $0.035\\%$ ProClin 300. Complement system activation of the nanoparticles was assayed following the manufacturer’s instructions, and zymosan was used as a positive control. \n\nPNP adherence to human carotid artery. Human umbilical cord was collected under the approval of the Institutional Review Board (IRB) at the University of California, San Diego, USA, and human carotid arteries were collected under the approval of the IRB at the University of Southern California, USA. Patients consented to use of their samples for this study before collection. To derive decellularized arterial extracellular matrix (ECM), human arteries were carefully dissected from the umbilical cord and removed from the surrounding Wharton’s jelly, and subsequently incubated in $2\\%$ sodium dodecyl sulfate (SDS, Sigma Aldrich) for $72\\mathrm{h}$ The decellularized tissue was then rinsed with PBS and incubated in PBS solution containing $200\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ PNPs for $30s$ . The sample was then transferred to PBS solution and rinsed extensively before examination by scanning electron microscopy (SEM). A control decellularized arterial tissue sample without PNP incubation was prepared and visualized for comparison. \n\nTo examine PNP binding on denuded vascular walls, approximately $2\\mathrm{mm}$ thick fresh human carotid artery sections were dissected and placed in normal saline on ice and transported immediately to the laboratory for a PNP binding study. To create the vascular characteristics of damaged arteries, an excised artery sample was surgically scraped on its luminal side with forceps to remove the endothelial layer. Successful denudation was confirmed by microscopy visualization. Prior to the nanoparticle binding experiment, both damaged and non-damaged artery samples were rinsed with PBS solution. The PNP binding experiment was performed by incubating the arterial samples in PBS solution containing $200\\upmu\\mathrm{{g}}\\mathrm{{ml}}^{-1}$ of DiD-loaded PNPs for $30s$ . The samples were then transferred to PBS solution and rinsed extensively before visualization by fluorescence microscopy. Endogenous tissue components such as collagen and elastin were identified based on their autofluorescence, which excites and emits maximally at ${\\sim}300-500\\mathrm{nm}$ and was captured using a FITC filter. DiD fluorescence was captured using a Cy5 filter to examine the deposition of PNPs. The arterial samples were imaged by a cross-sectional view of a histological section and a topdown view on the luminal side. The images were normalized to a reference illumination image for proper comparison. \n\nPharmacokinetics, biodistribution and safety of PNPs in a rat model of angioplasty-induced arterial denudation. All animal experiments were performed in accordance with NIH guidelines and approved by the Animal Care Committee of the University of California, San Diego. For the pharmacokinetics study, adult male Sprague–Dawley rats weighing $300{-}350~\\mathrm{g}$ (Harlan Laboratories) were administered with DiD-labelled PNPs and their blood was collected at specific time points via tail-vein blood sampling for fluorescence quantification. For the safety study, rats were injected with $1\\mathrm{ml}$ of $5\\mathrm{mg}\\mathrm{ml}^{-1}$ of PNPs on day 0 and day 5 followed by blood collection on day 10 for comprehensive metabolic panel analysis. Rats receiving equivalent PBS injections were prepared as a control. \n\nFor the biodistribution and vasculature-targeting studies, adult male Sprague– Dawley rats weighing $300{-}350\\mathrm{g}$ (Harlan Laboratories) were subjected to carotid balloon injury. In brief, the animals were anaesthetized with intraperitoneal ketamine (Pfizer) at $100\\mathrm{mg}\\mathrm{kg}^{-1}$ and xylazine (Lloyd Laboratories) at $10\\mathrm{mg}\\mathrm{kg}^{-1}$ . A ventral mid-line incision $(\\sim2\\mathrm{cm})$ was made in the neck, and the left common carotid artery and carotid bifurcation were exposed by blunt dissection. Proximal of left carotid artery, inner carotid artery and external carotid artery were temporarily clamped to avoid excessive blood loss during the induction of the 2F Fogarty arterial embolectomy catheter (Edwards Lifesciences). The catheter was introduced into the left carotid artery through an arteriotomy on the external carotid artery. The catheter was slowly inflated to a determined volume $(0.02\\mathrm{ml})$ and withdrawn with rotation for 3 times to denude the endothelium. The wound was later closed with 4-0 sutures. \n\nAfter the wound closure, rats were injected intravenously with $1\\mathrm{ml}$ of $5\\mathrm{mg}\\mathrm{ml}^{-1}$ DiD-loaded PNPs in $10\\%$ sucrose. At specified time points after the injection, animals were euthanized by $\\mathrm{CO}_{2}$ inhalation. After perfusion with PBS, organs including heart, lung, liver, spleen, kidney, gut, blood, and aortic branch including both the left and right carotid arteries were carefully collected and homogenized for biodistribution analysis. The overall PNP distribution at the aortic branch was visualized using a Keyence BZ-X700 fluorescence microscope. To examine the local distribution of PNP, damaged and undamaged arteries were cut longitudinally and stained with DAPI solution. En face examination was done on the luminal surfaces of denuded and intact areas for the binding of PNPs. Sequences of images along the $z$ -axis ( $0.5\\upmu\\mathrm{m}$ per section) from the intima to media layers of the carotid arteries were acquired with an Olympus ix81 fluorescence microscope. The 3D reconstruction of the arterial wall from multisectional images was performed using Image J. To analyse the PNP retention, damaged and undamaged arteries collected at specified time points were homogenized, and their respective fluorescence was normalized to the liver fluorescence for comparison. All replicates represent different rats subjected to the same treatment $(n=6)$ . \n\nTreatment of experimental coronary restenosis. Sprague–Dawley rats after angioplasty-induced arterial denudation were randomly placed into groups. The nanoparticle treatment group was injected intravenously with $\\mathrm{1ml}$ of $5\\mathrm{{mg}\\mathrm{{ml}^{-1}}}$ docetaxel-loaded PNPs in $10\\%$ sucrose at a docetaxel dose of $0.3\\mathrm{mg}\\mathrm{kg}^{-1}$ on day 0 and day 5. As controls, animals receiving PBS, free docetaxel, and empty PNPs were prepared. On day 14, animals were euthanized with an overdose of a ketamine-xylazine cocktail and perfused with PBS and $4\\%$ paraformaldehyde (PFA) at a pressure of $120{-}140\\mathrm{mmHg}$ . Segments of left and right carotid arteries were carefully dissected out, and the PFA-fixed carotid arteries were embedded with Tissue-Tek OCT compound (VWR International) in a tissue base mould and slowly submerged into pre-chilled 2-methyl butane until frozen completely. The frozen tissue block was then immediately stored at $-80^{\\circ}\\mathrm{C}$ until sectioning. Serial sectioning $:15\\upmu\\mathrm{m}$ per section) was performed with a Cyrotome cryostat machine (Leica), and the tissue sections were placed on polylysine-treated glass slides. Tissue sections on slides were dried at room temperature for $30\\mathrm{min}$ before staining. For immunohistochemistry, frozen sections on slides were first washed with PBS to remove residual OCT medium and then subjected to standard haematoxylin and eosin (H&E) staining. Areas of intima and media were analysed using Image J. Luminal obliteration is defined as the intima area/the area within the internal elastic lamina. Statistical analysis was performed using one-way ANOVA. No statistical methods were used to predetermine sample size. Studies were done in a non-blinded fashion. All replicates represent different rats subjected to the same treatment $(n=6)$ . \n\nStaphylococ u ureu (MRSA252) bacteria adherence study. MRSA252 obtained from the American Type Culture Collection was cultured on tryptic soy broth (TSB) agar (Becton, Dickinson and Company) overnight at $37^{\\circ}\\mathrm{C}$ A single colony was inoculated in TSB medium at $37^{\\circ}\\mathrm{C}$ in a rotary shaker. Overnight culture was refreshed in TSB medium at a 1:100 dilution at $37^{\\circ}\\mathrm{C}$ under shaking for another $^{3\\mathrm{h}}$ until the $\\mathrm{OD}_{600}$ of the culture medium reached approximately 1.0 (logarithmic growth phase). The bacteria were harvested by centrifugation at ${5,000g}$ for $10\\mathrm{min}$ and then washed with sterile PBS twice and then fixed with $10\\%$ formalin for $^{\\textrm{1h}}$ . The fixed bacteria were washed with sterile PBS and suspended in $10\\%$ sucrose to a concentration of $1\\times10^{8}\\mathrm{CFUml^{-1}}$ . For the nanoparticle adhesion study, aliquots of $0.8\\mathrm{ml}$ of $1\\times10^{8}\\mathrm{CFUml^{-1}}$ MRSA252 were mixed with $1.2\\mathrm{ml}$ of $200\\upmu\\mathrm{g}\\dot{\\mathrm{ml}}^{-1}$ DiD-loaded PNPs, RBCNPs, or bare NPs in $10\\%$ sucrose for $10\\mathrm{min}$ at room temperature. The bacteria were then isolated from unbound nanoparticles by repeated centrifugal washes in sucrose solution at ${5,000g}$ . The purified bacteria were then suspended in $10\\%$ sucrose for replicate measurements $(n=3)$ ) by flow cytometric analysis and SEM imaging. \n\nAntimicrobial efficacy study. For the in vitro antimicrobial efficacy study, $5\\times10^{6}$ CFU of MRSA252 was mixed with $500\\upmu\\mathrm{l}$ of $20\\mathrm{mg}\\mathrm{ml}^{-1}$ nanoparticles (4 wt% vancomycin loading) in saline. As controls, equivalent amounts of bacteria were incubated in either PBS or free vancomycin $(0.8\\mathrm{mg}\\mathrm{ml}^{-1},$ ). After $10\\mathrm{min}$ of incubation, bacteria were isolated from the solution by centrifugation at 2,500g for $5\\mathrm{min}$ . The collected bacteria pellet was resuspended with $500\\upmu\\mathrm{l}$ of TSB culture medium and incubated for $^{5\\mathrm{h}}$ . The resulting samples were serially diluted in PBS and spotted on TSB agar plates. After $24\\mathrm{h}$ of culturing, the colonies were counted to determine the bacteria count in each sample. Replicates represent separate bacterial aliquots incubated with the same formulation $(n=3)$ ). \n\nFor the in vivo antimicrobial efficacy study, vancomycin-loaded PNPs (PNPVanc) and vancomycin-loaded RBCNPs (RBCNP-Vanc) were suspended in $10\\%$ sucrose solution at $31.25\\mathrm{mg}\\mathrm{ml}^{-1}$ $4\\mathrm{wt\\%}$ vancomycin loading). An equivalent concentration of free vancomycin $(1.25\\mathrm{mg}\\mathrm{ml}^{-1}),$ was also suspended in $10\\%$ sucrose. Male CD-1 mice (Harlan Laboratories) weighing $\\sim25\\mathrm{g}$ were challenged intravenously with $6\\times10^{6}$ CFU of MRSA252 suspended in $100\\upmu\\mathrm{l}$ of PBS. $30\\mathrm{min}$ after the bacteria injection, mice were randomly placed into separate groups and injected with $200\\upmu\\mathrm{l}$ of PNP-Vanc, RBCNP-Vanc, free vancomycin (daily dosage: $10\\mathrm{mg}\\mathrm{kg}^{-1}$ vancomycin), or PBS. To compare to the clinical dosing of vancomycin, a control group treated with twice daily dosing of $30\\mathrm{mg}\\mathrm{kg}^{-1}$ free vancomycin was prepared (total daily dosage: $60\\mathrm{{mg}k g^{-1}}$ vancomycin). The mice received their corresponding treatments from day 0 to 2. On day 3, blood was collected from the submandibular vein. The mice were then euthanized, perfused with PBS, and their organs were collected. The organs were homogenized using a Biospec Mini Beadbeater in $1\\mathrm{ml}$ of PBS for $1\\mathrm{min}$ serially diluted in PBS by tenfold, and plated onto agar plates with a spotting volume of $50\\upmu\\mathrm{l}$ . After $48\\mathrm{h}$ of culture, bacterial colonies were counted to determine the bacterial load in each organ. Under the given experimental conditions, the detection limit was determined to be approximately 20 CFU per organ. Data points on the $x$ -axis represent samples with no detectable bacterial colonies. It was confirmed that samples prepared from unchallenged mice had no detectable colonies. The data was tested for normal distribution using the Shapiro-Wilk test. For blood and heart, which contained non-normal distributions, statistical analysis was performed using Kruskal–Wallis test. For the other organs, in which all groups were normally distributed and variance criteria were met, statistical analysis was performed using one-way ANOVA. Grubbs’ test was used to detect and remove statistical outliers. No statistical methods were used to predetermine sample size. Studies were done in a non-blinded fashion. Replicates represent different mice subjected to the same treatment $\\langle n=14$ ). \n\n![](images/7e59d8c8e9e455d73f2ce675cf2f2bb8c6b903fb884703c9ca223442f6e871bd.jpg) \nExtended Data Figure 1 | Schematic preparation of PNPs. a, Poly(lactic-coglycolic acid) (PLGA) nanoparticles are enclosed entirely in plasma membrane derived from human platelets. The resulting particles possess plateletmimicking properties for immunocompatibility, subendothelium binding, and pathogen adhesion. b, Schematic depicting the process of preparing PNPs. \n\n![](images/0d833188f6ae8d5eec9f34e472a04df1c0ac66a6657fc543ef6fab3eb3d7c9cb.jpg) \nExtended Data Figure 2 | PNP preparation and storage. a, Isolation of platelet rich plasma (PRP) was achieved by centrifugation at $100g$ PRP was collected from the top layer (yellow) separated from the red blood cells (red, bottom layer). b, Collected human platelets under light microscopy, which possess a distinctive morphology from c, red blood cells. Scale bars, $10\\upmu\\mathrm{m}$ . d, Transmission electron micrographs of platelet membrane vesicles and e, PNPs, both of which were negatively stained with $1\\%$ uranyl acetate. Scale bars, $200\\mathrm{nm}$ . f, Dynamic light scattering measurements of PNPs in $10\\%$ \n\nsucrose show that the particles retain their size and stability after a freezethaw cycle and re-suspension upon lyophilization ${\\mathrm{(}}n=3{\\mathrm{)}}$ ). Bars represent means $\\pm$ s.d. g, Transmission electron micrograph shows retentions of the core-shell structure of PNPs after a freeze-thaw cycle in $10\\%$ sucrose. Scale bar, $100\\mathrm{nm}$ . h, Transmission electron micrograph shows retentions of the coreshell structure of PNPs upon resuspension after lyophilization in $10\\%$ sucrose. Scale bar, $100\\mathrm{nm}$ . \n\n![](images/eb376658c8e05d5f25d51b0481def5358e477abbdb5a966fbb0ab4610b07716d.jpg) \nExtended Data Figure 3 | Overall protein content on PNPs resolved by western blotting. Primary platelet membrane protein/protein subunits including CD47, CD55, CD59, aIIb, a2, a5, a6, $\\upbeta1$ , b3, GPIba, GPIV, GPV, GPVI, GPIX, and CLEC-2 were monitored in platelet rich plasma, platelets, platelet vesicles, and PNPs. Platelets derived from four different protocols, including commercial blood anti-coagulated in EDTA, freshly drawn blood anti-coagulated in EDTA, freshly drawn blood anti-coagulated in heparin, and \n\ntransfusion-grade platelet rich plasma anti-coagulated in acid-citrate-dextrose (ACD), were examined to compare the membrane protein expression. Each sample was normalized to equivalent overall protein content before western blotting. It was observed that the PNP preparation resulted in membrane protein retention and enrichment very similar across the different platelet sources. \n\n![](images/211e6bd4c879d15537f7519ba64d9c4c8a79de9460bf92acff1f3b11c2aaeba0.jpg) \nExtended Data Figure 4 | Platelet membrane sidedness on PNPs. a, Transmission electron micrograph of PNPs primary-stained with anti-CD47 (intracellular), secondary-stained with immunogold, and negatively stained with $2\\%$ vanadium. The immunogold staining revealed presence of intracellular CD47 domains on collapsed platelet membrane vesicles, but not on PNPs. b, Transmission electron micrograph of PNPs primary-stained with anti-CD47 (extracellular), secondary-stained with immunogold, and negatively stained with $2\\%$ vanadium. PNPs were shown to display extracellular CD47 domains. \n\nAll scale bars, $100\\mathrm{nm}$ . c, $2\\upmu\\mathrm{m}$ polystyrene beads were functionalized with antiCD47 against the protein’s extracellular domain, anti-CD47 against the protein’s intracellular domain, or a sham antibody. Flow cytometric analysis of the different beads after DiD-loaded PNP incubation showed the highest particle retention to beads functionalized with anti-CD47 against the protein’s extracellular domain. d, Normalized fluorescence intensity of PNP retention to the different antibody-functionalized beads. Bars represent means $\\pm$ s.e.m. \n\n![](images/b1f00e364bfb85748eb55cae87b49fa5f64bf459d071bed5318dfd22ccd0f33e.jpg) \nExtended Data Figure 5 | PNP binding to collagen and extracellular matrix. a–f, Collagen-coated tissue culture slides seeded with human umbilical vein endothelial cells (HUVECs) were incubated with PNP solution for $30s$ . Fluorescence microscopy samples demonstrate differential PNP adherence to exposed collagen versus covered endothelial surfaces. a–c, Representative fluorescence images visualizing DiD-loaded PNPs (red), cellular cytosol (green), and cellular nuclei (blue). d–f, Images showing only the red and blue channels to highlight the differential localization of PNPs. Scale bar, $10\\upmu\\mathrm{m}$ . \n\ng, Fluorescence quantification of PNP per unit area on collagen and endothelial surfaces. Bars represent means $\\pm$ s.d. $(n=10)$ ). h, i, PNP adherence to arterial extracellular matrix (ECM) as visualized by SEM. h, SEM images of the ECM of a decellularized human umbilical cord artery. Left, scale bar, $1\\upmu\\mathrm{m}$ ; right, scale bar, $500\\mathrm{nm}$ . i, SEM images of the ECM of a decellularized human umbilical cord artery after PNP incubation. Left, scale bar, $1\\upmu\\mathrm{m}$ ; right, scale bar, $500\\mathrm{nm}$ . \n\n![](images/69edfece0918126355e61439bc58cc218d6aa2c1107a6e8c32bd8dca5a03f89c.jpg) \nExtended Data Figure 6 | Pharmacokinetics, biodistribution and safety of PNPs. a, DiD-loaded PNPs were injected intravenously through the tail vein of Sprague–Dawley rats. At various time points, blood was withdrawn via tail vein blood sampling for fluorescence quantification to evaluate the systemic circulation lifetime of the nanoparticles ${\\bf\\zeta}_{n}=6\\bf{\\zeta}_{,}$ ). b, Biodistribution of the PNP nanoparticles in balloon-denuded Sprague–Dawley rats at $^{2\\mathrm{h}}$ and $^{48\\mathrm{h}}$ after intravenous nanoparticle administration through the tail vein ${(n=6}$ ). \n\nc, Comprehensive metabolic panel of rats after injections with human-derived PNPs and PBS ${(n=6)}$ ). The rats received intravenous injections of PNPs and PBS on day 0 and day 5, and the blood test conducted on day 10 did not reveal significant changes between the two groups, indicating normal liver and kidney functions after the PNP administration. All bars and markers represent means $\\pm$ s.d. \n\n![](images/af7a24f8f317a55b62cdf1db09fe89f7c37bca57c5bc1dd52623ef1b7bcf665d.jpg) \n\nExtended Data Figure 7 | PNP targeting of damaged vasculatures upon intravenous injection to rats with angioplasty-induced arterial denudation. a, Fluorescence microscopy of the aortic branch revealed selective PNP binding to the denuded artery (right) as opposed to the undamaged artery (left) (PNP fluorescence in red). b, Fluorescence images acquired from the control artery, which did not reveal PNP fluorescence upon focusing on either the endothelium (top) or the smooth muscle layer (bottom) (nuclei in blue). c, Fluorescence images acquired from the denuded artery, which revealed \n\nsignificant PNP retention as fluorescent punctates (PNP fluorescence in red) above the smooth muscle layer. d, Fluorescence image of arterial cross-section acquired from the control artery, which showed nuclei of endothelial cells above the collagen layer (autofluorescence in green) and an absence of PNP fluorescence. e, Fluorescence image of arterial cross-section acquired from the denuded artery, which showed PNP retention as fluorescent punctates on the collagen layer (PNP fluorescence in red; collagen autofluorescence in green) and an absence of endothelial cell nuclei. All scale bars, $100\\upmu\\mathrm{m}$ . \n\n![](images/52ffd185ea1f7c2cd42b6bfca7c496276027c8cab9e39bd5b022264d93acafe9.jpg) \nExtended Data Figure 8 | Characterizations of drug-loaded cell membrane cloaked nanoparticles. a, Physicochemical properties of drug-loaded cell membrane cloaked nanoparticles. b, TEM visualization of docetaxel-loaded PNPs (PNP-Dtxl). Scale bar, $200\\mathrm{nm}$ . c, Drug release profile of PNP-Dtxl compared to polyethylene glycol (PEG)-PLGA diblock nanoparticles of equivalent size and docetaxel loading $(n=3$ ). d, TEM visualization of vancomycin-loaded PNPs (PNP-Vanc). Scale bar, $200\\mathrm{nm}$ . e, Drug release profiles of PNP-Vanc and RBCNP-Vanc ${\\mathit{\\Phi}}_{n}=3{\\mathit{\\Phi}}_{.}$ ). Bars represent means $\\pm$ s.d. \n\n![](images/93652613584020df2bf3d7f2a3f3e792450a015a700ede023fc5aa5af99414ba.jpg) \nExtended Data Figure 9 | Treatment of an experimental rat model of coronary restenosis. a–e, H&E-stained arterial cross-sections reveal the vascular structure of non-damaged arteries (serving as baseline, a) and denuded arteries after treatment with PNP-Dtxl (b), PBS (c), PNP with no docetaxel content (d), or free docetaxel (e). Scale bar, $200\\upmu\\mathrm{m}$ . \n\n![](images/8b85d5801f76119c260711baed7bf6b5efc5563d8e5f78e5d8df4df8e417d8b9.jpg) \nExtended Data Figure 10 | PNP adherence to MRSA252 bacteria. a, Flow cytometric analysis of MRSA252 bacteria after incubation with different DiD-loaded nanoformulations. b, Pellets of MRSA252 after incubation with DiD-loaded RBCNPs (left) and DiD-loaded PNPs (right) show differential retention of nanoformulation with MRSA252 upon pelleting of the bacteria. c, A pseudocoloured SEM image of PNPs binding to MRSA252 under high magnification (MRSA coloured in gold, PNP coloured in orange). Scale bar, $400\\mathrm{nm}$ . " + }, + { + "id": "10.1002_aenm.201501310", + "DOI": "10.1002/aenm.201501310", + "DOI Link": "http://dx.doi.org/10.1002/aenm.201501310", + "Relative Dir Path": "mds/10.1002_aenm.201501310", + "Article Title": "Formamidinium and Cesium Hybridization for Photo- and Moisture-Stable Perovskite Solar Cell", + "Authors": "Lee, JW; Kim, DH; Kim, HS; Seo, SW; Cho, SM; Park, NG", + "Source Title": "ADVANCED ENERGY MATERIALS", + "Abstract": "Although power conversion efficiency (PCE) of state-of-the-art perovskite solar cells has already exceeded 20%, photo- and/or moisture instability of organolead halide perovskite have prevented further commercialization. In particular, the underlying weak interaction of organic cations with surrounding iodides due to eight equivalent orientations of the organic cation along the body diagonals in unit cell and chemically non-inertness of organic cation result in photo- and moisture instability of organometal halide perovskite. Here, a perovskite light absorber incorporating organic-inorganic hybrid cation in the A-site of 3D APbI(3) structure with enhanced photo- and moisture stability is reported. A partial substitution of Cs+ for HC(NH2)(2)(+) in HC(NH2)(2)PbI3 perovskite is found to substantially improve photo- and moisture stability along with photovoltaic performance. When 10% of HC(NH2)(2)(+) is replaced by Cs+, photo- and moisture stability of perovskite film are significantly improved, which is attributed to the enhanced interaction between HC(NH2)(2)(+) and iodide due to contraction of cubo-octahedral volume. Moreover, trap density is reduced by one order of magnitude upon incorporation of Cs+, which is responsible for the increased open-circuit voltage and fill factor, eventually leading to enhancement of average PCE from 14.9% to 16.5%.", + "Times Cited, WoS Core": 1326, + "Times Cited, All Databases": 1357, + "Publication Year": 2015, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000363459400010", + "Markdown": "# Formamidinium and Cesium Hybridization for Photo- and Moisture-Stable Perovskite Solar Cell \n\nJin-Wook Lee, Deok-Hwan Kim, Hui-Seon Kim, Seung-Woo Seo, Sung Min Cho, and Nam-Gyu Park\\* \n\nAlthough power conversion efficiency (PCE) of state-of-the-art perovskite solar cells has already exceeded $20\\%$ , photo- and/or moisture instability of organolead halide perovskite have prevented further commercialization. In particular, the underlying weak interaction of organic cations with surrounding iodides due to eight equivalent orientations of the organic cation along the body diagonals in unit cell and chemically non-inertness of organic cation result in photo- and moisture instability of organometal halide perovskite. Here, a perovskite light absorber incorporating organic–inorganic hybrid cation in the A-site of 3D $\\mathsf{A P b l}_{3}$ structure with enhanced photo- and moisture stability is reported. A partial substitution of ${\\pmb{\\subset}}{\\pmb{s}}^{+}$ for $H C(N H_{2})_{2}^{+}$ in ${\\mathsf{H}}{\\mathsf{C}}({\\mathsf{N}}{\\mathsf{H}}_{2})_{2}{\\mathsf{P}}{\\mathsf{b}}|_{3}$ perovskite is found to substantially improve photo- and moisture stability along with photovoltaic performance. When $10\\%$ of $H C(N H_{2})_{2}^{+}$ is replaced by ${\\pmb{\\subset}}{\\pmb{s}}^{+}$ , photo- and moisture stability of perovskite film are significantly improved, which is attributed to the enhanced interaction between $H C(N H_{2})_{2}^{+}$ and iodide due to contraction of cubo-octahedral volume. Moreover, trap density is reduced by one order of magnitude upon incorporation of ${\\pmb{\\subset}}{\\pmb{s}}^{+}$ , which is responsible for the increased open-circuit voltage and fill factor, eventually leading to enhancement of average PCE from $14.9\\%$ to $16.5\\%$ . \n\n# 1. Introduction \n\nSince the initiation of organometal halide perovskite as a short-lived light harvester in liquid dye-sensitized solar cell structure, 1,2 stability of perovskite solar cell was revolutionary enhanced by replacing liquid electrolyte with solid-state hole transporting material. 3,4 Reports on long-term durable solidstate perovskite solar cells eventually triggered tremendous studies on fundamentals of perovskite light harvester, solar cell device architecture, fabrication process, and material engineering. As a result, power conversion efficiency (PCE) has been rapidly enhanced over the years. 5–14 Recently, a PCE of $20.1\\%$ was certified, 15 which assures that organolead halide perovskite solar cell is one of the most promising candidates for low-cost solar power. \n\nSuperb PCE of perovskite solar cell was found to result from its advantageous ambipolar charge transporting property along with high absorption coefficient in direct band gap transition. 16 Perovskite itself can transport the photogenerated electron and hole carriers in parallel with generation of the charge at high light harvesting efficiency. 17,18 This unique optoelectronic property of organometal halide perovskite enables diversity of device architecture from sensitized system to mesoscopic or planar heterojunction structure, which classifies perovskite solar cell as a new kind of solar cell. 19 Since the introduction of various device architecture, a surge of increase in PCE was followed by optimization of synthetic route. 14,15,20 Modification of synthetic route resulted in enhanced crystallinity with high surface coverage, resulting in PCE exceeding 20%. 21 \n\nUp to now, most of the reported per \n\novskite solar cells have been based on $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ (MAPbI3). 20 However, $\\mathbf{MAPbI}_{3}$ was reported to undergo reversible phase transition from tetragonal to cubic phase at $55~^{\\circ}\\mathrm{C}$ that is in the range of solar cell operating temperature. 22 Therefore, the structural phase transition is expected to have ill effect on photo- and thermal stability of perovskite solar cell. $\\mathrm{MAPbI}_{3}$ was reported to be unstable against the light and heat due to its low crystallization energy. 23–25 Recently, lead halide perovskite based on formamidinium cation $(\\mathrm{HC}(\\mathrm{NH}_{2})_{2}\\mathrm{PbI}_{3}$ $\\mathrm{FAPbI}_{3}\\mathrm{,}$ ) was suggested as an alternative to $\\mathrm{MAPbI}_{3}$ due to its extended light harvesting capability because of reduced band gap energy, longer charge diffusion length, and superior photostability. 26–34 $\\mathrm{FAPbI}_{3}$ is crystallized to either yellow hexagonal nonperovskite or black trigonal perovskite phase depending on heat-treatment temperature. 22 In contrast to $\\mathsf{M A P b I}_{3}$ $\\mathrm{FAPbI}_{3}$ was confirmed to be free from phase transition at temperature between 25 and $150~^{\\circ}\\mathrm{C}$ . 30 A PCE of $16.01\\%$ was reported by utilizing black polymorph $\\mathrm{FAPbI}_{3}$ in mesoscopic structure, 30 while a PCE of $14.2\\%$ was demonstrated using planar heterojunction structure. 27 \n\nIn spite of several advantages of $\\mathrm{FAPbI}_{3}$ over $\\mathsf{M A P b I}_{3}$ $\\mathrm{FAPbI}_{3}$ has not been studied intensively. It is probably due to instability of $\\mathrm{FAPbI}_{3}$ against humidity. Instability of black perovskite $\\mathrm{FAPbI}_{3}$ is due to either instability of black phase or formamidinium itself in presence of water. 22 Black perovskite $\\mathrm{FAPbI}_{3}$ was reported to convert to yellow nonperovskite phase in presence of solvent while formamidinium cation dissociated to ammonia and sym-triazine in presence of water although both were stable under dry atmosphere. 14,22 For stabilization of black $\\mathrm{FAPbI}_{3}$ mixed cation and/or halide system of $\\mathrm{FA}_{1-x}\\mathrm{MA}_{x}\\mathrm{PbI}_{3}$ or $\\mathrm{FA}_{1-x}\\mathrm{MA}_{x}\\mathrm{PbI}_{3-\\gamma}\\mathrm{Br}_{\\gamma}$ was suggested. 14,15,29,32 Incorporation of MA cation resulted in stabilization of black $\\mathrm{FAPbI}_{3}$ along with enhanced PCE, which was attributed to higher dipole of MA cation leading to stronger interaction with $\\mathrm{PbI}_{6}$ octahedral cage. 32 However, incorporation of MA cation might not overcome photo- and thermal stability when considering relatively volatile nature of MA cation. 25 Also, incorporation of bromide will lead to loss of advantageous narrow band gap of $\\mathrm{FAPbI}_{3}$ along with phase segregation problem. 35 \n\n![](images/41e1759499078b3a18b61cc58c04bf26b2028edad58ef406afa40d462f616588.jpg) \nFigure 1. a) Absorbance at $630~\\mathsf{n m}$ and b) X-ray diffraction (XRD) patterns of the $\\mathsf{F A}_{1-x}\\mathsf{C s}_{x}\\mathsf{P b l}_{3}$ films coated on glass. The film was dried in vacuum without heat treatment. Insets of (a) show photographs of films depending on Cs content. c) Differential scanning calorimetry (DSC) for $x=0$ and 0.10 in $\\mathsf{F A}_{1-x}\\mathsf{C s}_{x}\\mathsf{P b}\\mathsf{I}_{3}$ . \n\nHere, we report on $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ as an alternative light absorber to $\\mathrm{FAPbI}_{3}$ and $\\mathrm{MAPbI}_{3}$ $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite was formed via Lewis base adduct of $\\mathrm{PbI}_{2}$ 36 Optoelectronic properties and photovoltaic performance of Cs-incorporated $\\mathrm{FAPbI}_{3}$ were compared with those of pristine $\\mathrm{FAPbI}_{3}$ A PCE as high as $19.0\\%$ measured at reverse scan and average PCE of $16.5\\%$ from forward scan were demonstrated from $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film in planar structure. More importantly, we found that stability of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film against the light and humidity was improved compared to $\\mathrm{FAPbI}_{3}$ film. \n\n# 2. Result and Discussions \n\nFigure 1a shows absorbance of $\\mathrm{FA}_{1-x}\\mathrm{Cs}_{x}\\mathrm{PbI}_{3}$ films coated on glass at $630{\\mathrm{~nm~as}}$ a function of $x,$ in which the films are dried in vacuum without heat treatment. Without adding cesium iodide (CsI) in precursor solution $(x=0)$ , the film shows low absorbance at $630\\mathrm{nm}$ because of almost no absorption in entire wavelength (Figure S1a, Supporting Information), which is due to formation of pure nonperovskite yellow phase of $\\mathrm{FAPbI}_{3}$ 14 As the $x$ increases, color of the film gradually turns yellowish dark brown. As a result, absorbance at $630~\\mathrm{nm}$ increases and reaches its maximum at $x=0.10$ $(\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}})$ and then decreases with higher x The change of color of the film is indicative of formation of different phase. To investigate the phase of the films, X-ray diffraction (XRD) patterns of the films are measured in Figure 1b. For $x=0$ $(\\mathrm{FAPbI}_{3})$ , pure yellow phase is formed. However, mixed phase of yellow and black $\\mathrm{FAPbI}_{3}$ is formed upon adding CsI, where highest portion of black phase was detected at $x=0.10$ $(\\mathrm{FA}_{0.9}\\mathrm{Cs}_{0.1}\\mathrm{PbI}_{3})$ . When $x$ is higher than 0.10, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ phase starts to appear along with black $\\mathrm{FAPbI}_{3}$ phase. Highest photoluminescence (PL) intensity of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ in Figure S1b (Supporting Information) also supports highest portion of black $\\mathrm{FAPbI}_{3}$ phase formed at $x=0.10$ . In Figure 1c, differential scanning calorimetry (DSC) is measured to investigate the thermodynamic behavior of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ The samples for DSC measurement are prepared by peeling off the film (not heat-treated) after spin-coating each precursor solution. While $N,N.$ -dimethylformamide (DMF) is washed by diethyl ether, dimethyl sulfoxide (DMSO) exists in the film since it is not miscible with ether. 36 DMSO mixed with $\\mathrm{PbI}_{2}$ was reported to start to evaporate at temperature as low as $75~^{\\circ}\\mathrm{C}$ , 15 so the endothermic peaks observed at $89~^{\\circ}\\mathrm{C}$ for $x=0$ and $81.3~^{\\circ}\\mathrm{C}$ for $x=0.10$ in $\\mathrm{FA}_{1-\\mathrm{x}}\\mathrm{Cs}_{x}\\mathrm{Pb}\\mathrm{I}_{3}$ are due to evaporation of DMSO. Shift of the peak upon addition of CsI to lower temperature by $8.7~^{\\circ}\\mathrm{C}$ is probably due to weak bonding of DMSO in the presence of CsI. For the $\\mathrm{FAPbI}_{3}$ , an additional peak at $106.5~^{\\circ}\\mathrm{C}$ is attributed to phase transition from yellow to black phase. 15,30 In contrast to $\\mathrm{FAPbI}_{3}$ $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ shows no additional peaks except for a peak observed. Indeed the color of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film turns already black even at room temperature, while the color of as-prepared yellow $\\mathrm{FAPbI}_{3}$ film is changed to black when heat-treatment temperature reached $150^{\\circ}\\mathrm{C}$ (Figure S2, Supporting Information). \n\n![](images/74f17f5e81ff590d89e55fdd84acbd8b62e4777d992a8d241e545b1741939215.jpg) \nFigure 2. a) XRD patterns of the $\\mathsf{F A}_{1-x}\\mathsf{C s}_{x}\\mathsf{P b}\\mathsf{I}_{3}$ films. b) Magnified (101) peak of XRD patterns of $\\mathsf{F A}_{1-x}\\mathsf{C s}_{x}\\mathsf{P b}\\mathsf{I}_{3}$ films. Empty circles represent the measured data and solid lines indicate Gaussian fit result. c) Absorption coefficient $(\\alpha)$ as a function of wavelength for $\\mathsf{F A P b l}_{3}$ and $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{I}_{3}$ , where inset is $\\alpha$ at narrow wavelength region to show the difference in absorption onset profile. d) $(\\alpha h\\nu)^{2}$ of $\\mathsf{F A P b l}_{3}$ and $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{l}_{3}$ , where inset shows linear fit of the data at absorption onset region to determine band gap energy. \n\nXRD patterns of $150~^{\\circ}\\mathrm{C}$ annealed $\\mathrm{FA}_{1-x}\\mathrm{Cs}_{x}\\mathrm{PbI}_{3}$ films are depicted in Figure 2a. When $x$ is 0, 0.05, and 0.10, only black perovskite phase of $\\mathrm{FAPbI}_{3}$ was detected, while $\\mathrm{Cs}\\mathrm{P}{\\mathsf{b}}\\mathrm{I}_{3}$ peaks start to appear with $x=0.15$ and 0.20. Absorbance and normalized PL spectra of $\\mathrm{FA}_{1-x}\\mathrm{Cs}_{x}\\mathrm{Pb}\\mathrm{I}_{3}$ film in Figure S3 (Supporting Information) show that absorption onset shifts slightly to blue region at $x=0.05$ , while ${\\approx}10~\\mathrm{nm}$ blue shift is observed at $x=0.10$ , 0.15, and 0.20. Normalized PL peaks show $5\\ \\mathrm{nm}$ blue shift for $x=0.05$ and $8\\ \\mathrm{nm}$ blue shift for $x=0.10$ , 0.15, and 0.20. When considering the appearance of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ peaks in XRD patterns for $x=0.15$ and 0.20 along with identical absorption onset and position of PL peak for the $x=0.10$ , 0.15, and 0.20 films, it is likely that mixed phase of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ is formed for $x=0.15$ and 0.20. Interestingly, (110) and (220) peaks are highly enhanced for $x=0.10$ , which means that the $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film is highly oriented to (110) plane. (101) peaks in the XRD patterns of $\\mathrm{FA}_{1-x}\\mathrm{Cs}_{x}\\mathrm{Pb}\\mathrm{I}_{3}$ are fitted with Gaussian distribution function in Figure 2b to determine the position of the peak maximum and full width at half maximums (FWHMs). Position of peak maximum is determined to be $14.00^{\\circ}$ , $13.98^{\\circ}$ , $14.07^{\\circ}$ , $14.04^{\\circ}$ , and $14.01^{\\circ}$ for $x=0$ , 0.05, \n\n0.10, 0.15, and 0.20, respectively. All the peaks originated from $\\mathrm{FAPbI}_{3}$ shift with same tendency. The shift of peak maximum toward higher angle for $x=0.10$ , 0.15, and 0.20 is indicative of a decrease in lattice parameter. Since the XRD measurement system guarantees the error range of $2\\theta\\le\\pm0.01^{\\circ}$ , the observed peak shifts are not experimental error. The lattice parameters of $\\mathrm{FAPbI}_{3}$ $(x=0)$ are calculated to be $a=8.9377\\mathring\\mathrm{A}$ and $c=11.0098{\\mathring{\\mathrm{A}}}$ resulting in unit cell volume of $761.2263\\mathrm{~}\\mathring{\\mathrm{A}}^{3}$ , which is similar to the reported value of $a=8.9817\\mathrm{~\\AA~}$ and $c=11.0060\\mathrm{~\\AA~}$ with unit cell volume of $768.9\\mathring{\\mathrm{A}}^{3}$ 22 For $x=0.10$ the peaks shift to higher angle significantly, in which lattice parameters are calculated to be $\\overset{\\cdot}{a}=\\overset{\\cdot}{8}.911\\overset{\\circ}{6}\\overset{\\circ}{\\mathrm{A}}$ and $c=10.9763\\mathrm{~\\AA~}$ corresponding to unit cell volume of $749.4836\\mathrm{~\\AA~}^{3}$ The change in the lattice parameter is probably due to incorporation of much smaller ionic radius of ${\\mathrm{Cs}}^{+}$ (1.81 Å) compared to that of $\\mathrm{FA^{+}}$ $\\mathrm{^{\\prime}F A^{+}{=}H C(N H_{2})_{2}\\mathrm{^{+}}}$ 2.79 Å as estimated by DFT calculation), resulting in reduction of cubo-octahedral volume for A-site cation surrounded by corner shared eight $\\mathrm{PbI}_{6}$ octahedra in unit cell. 37 The shrinkage of cubo-octahedral volume for A-site cation leads to stronger interaction between A-site cation and iodide, 32 which is attributed to the presence of black perovskite phase at relatively lower temperature upon incorporation of Cs in $\\mathrm{FAPbI}_{3}$ FWHMs are calculated to be 0.2743, 0.2568, 0.1735, 0.1752, and 0.2438 for $x=0$ , 0.05, 0.10, 0.15, and 0.20, respectively. Overall, the decreased FWHMs by addition of CsI imply larger crystallite size according to Scherrer equation, whereas the increased FWHMs upon further increase in CsI amount of $x=0.15$ and 0.20 are likely to be due to formation of $\\mathrm{Cs}\\mathrm{Pb}\\mathrm{I}_{3}$ impurity. X-ray photoelectron spectroscopy is measured since the shrinkage of cubo-octahedral volume possibly leads to change of chemical bonding nature between $\\mathrm{\\Pb}$ and I. XPS spectra in Figure S4 (Supporting Information) calibrated according to C 1s of $284.6\\ \\mathrm{eV}$ shows that the peak at $287.9\\ \\mathrm{eV}$ is ascribed to $\\mathrm{C-N}$ or $\\mathrm{C}{=}\\mathrm{N}$ bond (Figure S4a, Supporting Information). 38 As can be seen in Figure S4b (Supporting Information), no Cs 3d peaks are observed from $\\mathrm{FAPbI}_{3}$ film, while it is detected from $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film. Notably, Pb 4f peaks shift to higher binding energy by $0.35\\mathrm{eV}$ and I 3d peaks shift slightly to higher binding energy by $0.1\\ \\mathrm{eV}.$ Shift of Pb 4f peaks toward higher binding energy is indicative of increase in cationic charge of $\\mathrm{Pb}$ ions, which is responsible for the shrinkage of lattice parameter observed in XRD measurement, resulting eventually in change of chemical bonding nature between $\\mathrm{Pb}$ and I. 39 \n\nSince the lattice structure and chemical bonding nature are closely related to optical properties of the material, we are motivated to compare the optical properties of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA}_{0.9}\\mathrm{Cs}_{0.1}\\mathrm{Pb}\\mathrm{I}_{3}$ . Absorption coefficients of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ are calculated from reflectance, transmittance, and thickness of the films in Figure 2c. 18 $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ shows slightly higher absorption coefficient in the wavelength ranging from visible to near IR, in which absorption onset shifts to lower wavelength by ${\\approx}10~\\mathrm{nm}$ . Since the blue shifts of both absorption onset and PL peak are indicative of change in optical band gap energy $(E_{\\mathrm{g}})$ , we determine $E_{\\mathrm{g}}$ s of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ by using Kubellka–Munk equation (Figure 2d). 40 $E_{\\mathrm{g}}$ s of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ are determined to be 1.53 and $1.55\\ \\mathrm{eV},$ respectively. Slight increase in $E_{\\mathrm{g}}$ is related to the stronger $\\mathrm{{Pb-I}}$ interaction as the result of the reduced lattice parameter. \n\nPhotovoltaic performance of $\\mathrm{FA}_{1-\\mathrm{x}}\\mathrm{Cs}_{x}\\mathrm{PbI}_{3}$ perovskite solar cell with $x=0$ , 0.05, 0.10, 0.15, and 0.20 is compared in Figure S5 (Supporting Information). Measured photovoltaic parameters are summarized in Table S1 (Supporting Information). The devices are fabricated under relative humidity (RH) of $55\\%$ . PCE is improved from $13.3\\pm0.804\\%$ to $14.7\\pm0.365\\%$ and to $16.0\\pm0.430\\%$ when $x$ is changed from 0 to 0.05 and to 0.10, respectively. The improved PCE is mainly due to the improved fill factor (FF) by $10.8\\%$ when $x$ is changed from 0 to 0.10, while $J_{\\mathrm{SC}}$ and $V_{\\mathrm{OC}}$ are slightly enhanced by $3.2\\%$ and $5.3\\%$ , respectively. However, when $x$ is increased to 0.15 and 0.20, PCE is diminished to $13.5\\pm0.941\\%$ and $5.30\\pm1.542\\%$ due to the decreased $J_{\\mathrm{SC:}}$ $V_{\\mathrm{OC}}:$ and FF. The decrease in PCE with $x=0.15$ and 0.20 is probably related to formation of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ as detected from XRD measurement. To clarify the reason for the degraded PCE upon formation of $\\mathrm{Cs}\\mathrm{P}{\\mathrm{b}}\\mathrm{I}_{3}$ , surface scanning electron microscopic (SEM) images of $\\mathrm{FA}_{1-\\mathrm{x}}\\mathrm{Cs}_{x}\\mathrm{Pb}\\mathrm{I}_{3}$ films are measured (Figure S6, Supporting Information). As the $x$ increases from 0 to 0.05 and to 0.10, the films become uniform and flat. When $x$ is further increased to 0.15 and 0.20, microsized rods are formed on top of the $\\mathrm{FA}_{1-x}\\mathrm{Cs}_{x}\\mathrm{Pb}\\mathrm{I}_{3}$ films as can be seen in Figure S6d,e (Supporting Information), which is due to the presence of $\\mathrm{Cs}\\mathrm{P}{\\mathrm{b}}\\mathrm{I}_{3}$ $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ formed on top of the perovskite film presumably impedes the contact between $\\mathrm{FA}_{1-x}\\mathrm{Cs}_{x}\\mathrm{Pb}\\mathrm{I}_{3}$ film and hole transporting material, which could have ill effect on photovoltaic performance. Steady-state PCE in Figure S7 (Supporting Information) shows that both PCE and $J_{\\mathrm{SC}}$ of the $\\mathrm{FAPbI}_{3}$ perovskite solar cell are continuously degraded after $20\\mathrm{~s~}$ , while those of the $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ one increase with time and keep their values constant after ${\\approx}60\\ \\mathrm{~s~}$ . When comparing \n\nPCE after $100\\mathrm{s}$ , $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ solar cell shows $19\\%$ higher PCE than $\\mathrm{FAPbI}_{3}$ one (from $11.5\\%$ to $13.6\\%)$ . External quantum efficiency (EQE) spectra of $\\mathrm{FA}_{1-\\mathrm{x}}\\mathrm{Cs}_{x}\\mathrm{Pb}\\mathrm{I}_{3}$ perovskite solar cells are demonstrated in Figure S8 (Supporting Information). Integrated $J_{\\mathrm{SC}}$ s from EQE are calculated to be 16.4, 16.7, 17.6, 10.7, and $8.20\\mathrm{\\mA\\cm^{-2}}$ for $x=0$ , 0.05, 0.10, 0.15, and 0.20, respectively, which were more than $30\\%$ lower compared with $J_{\\mathrm{SC}}{}^{\\mathrm{i}}$ s measured from $J{-}V$ curves. To verify whether the measured $J_{\\mathrm{SC}}$ in $J{-}V$ curve is accurate or not, time-dependent $J_{\\mathrm{SC}}$ is measured to obtain steady-state $J_{\\mathrm{SC}}$ under AM 1.5G one sun illumination for perovskite solar cell incorporating $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ (Figure S9, Supporting Information). Steadystate $J_{\\mathrm{SC}}$ after $50~\\mathrm{s}$ is stabilized to be $20.4~\\mathrm{mA}~\\mathrm{cm}^{-2}$ for $\\mathrm{FAPbI}_{3}$ and $21.4~\\mathrm{mA}~\\mathrm{cm}^{-2}$ for $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ . Both of the devices need at least ${\\approx}5$ s of light soaking to reach the steady state. Therefore, large discrepancy between $J_{\\mathrm{SC}}$ measured from $J{-}V$ curves and EQE spectra probably results from slow response of photocurrent and/or white light soaking effect, which was also reported in previous research on planar heterojunction solar cell incorporating FAPbI3 41 \n\nFigure 3a,b shows magnified surface SEM images of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ films on compact $\\mathrm{TiO}_{2}$ layer-coated FTO (fluorine-doped tin oxide) glass. $\\mathrm{FAPbI}_{3}$ film shows layered structure with relatively smaller crystal along with unclear grain boundary, whereas $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film shows larger crystal with clear grain boundary. Relatively large crystal size is well correlated with XRD pattern in Figure 2a,b. Different morphology of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ from $\\mathrm{FAPbI}_{3}$ can also be observed in cross-sectional image in full cell as can be seen in Figure 3c,d, in which $\\mathrm{FA}_{0.9}\\mathrm{Cs}_{0.1}\\mathrm{PbI}_{3}$ film shows larger crystal with grain boundaries perpendicular to substrate. Elemental distribution mapping of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film in Figure S10 (Supporting Information) confirms that Cs atom is homogeneously distributed on the entire $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film. Realistic stoichiometry of the nominal composition $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ is inferred from its thermogravimetric analysis (TGA) curve with respect to the one obtained from $\\mathrm{FAPbI}_{3}$ (Figure S11, Supporting Information). Both of the perovskites undergo significant weight loss upon heating at $350~^{\\circ}\\mathrm{C}_{\\mathrm{i}}$ which is due to sublimation of organic component of $\\mathrm{HC}(\\mathrm{NH}_{2})_{2}\\mathrm{I}$ (FAI). 28 The smaller weight loss $(\\approx3\\%)$ of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ is due to the remaining CsI (or CsPbI3), which is stable up to $600^{\\circ}\\mathrm{C}$ . 42,43 From the weight loss, the composition of the film with $10\\%$ of FAI replaced by CsI was calculated to be $\\mathrm{FA}_{0.884}\\mathrm{Cs}_{0\\cdot116}\\mathrm{PbI}_{3}$ which is close to nominal composition $(\\mathrm{FA}_{0.9}\\mathrm{Cs}_{0.1}\\mathrm{PbI}_{3})$ . \n\nEnhancement of photovoltaic performance upon incorporation of $10\\%$ Cs is further confirmed by comparing photovoltaic performance of 20 devices of perovskite solar cell employing $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ and pristine $\\mathrm{FAPbI}_{3}$ in Figure 4 The experiment is conducted under relative humidity $640\\%$ , which results in higher overall PCE. The measured data are summarized in Tables S2 and S3 (Supporting Information). Compared to average PCE of the $\\mathrm{FAPbI}_{3}$ based perovskite solar cell $(16.3\\pm0.667\\%)$ ), perovskite solar cell composed of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ shows $4.9\\%$ higher average PCE $(17.1\\pm0.753\\%)$ , which is mainly due to $3.9\\%$ improved FF (from $0.697\\pm0.017$ to $0.724\\pm0.016$ ) along with slight improvement in short-circuit current density $(J_{\\mathrm{SC}})$ and open-circuit voltage $(V_{\\mathrm{OC}})$ . Both $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cells show similar extent of $J{-}V$ hysteresis as can be seen in Figure S12 (Supporting Information), which is attributed to planar structure. Best performing perovskite solar cell incorporating $\\mathrm{FAPbI}_{3}$ in Figure 4c shows $17.4\\%\\ (J_{\\mathrm{SC}}=23.0\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ $V_{\\mathrm{OC}}=1.05\\ \\mathrm{V},$ , FF $=0.721$ ) at reverse scan and $12.4\\%(J_{\\mathrm{SC}}=22.9\\ \\mathrm{mA\\cm^{-2}}$ $V_{\\mathrm{OC}}=$ $0.99{\\mathrm{V}}, $ $\\mathrm{FF}=0.549)$ ) at forward scan, resulting in average PCE of $14.9\\%(J_{\\mathrm{SC}}{=}23.0\\ \\mathrm{mAcm^{-2}}$ $V_{\\mathrm{OC}}=1.02\\:\\mathrm{V},$ $\\mathrm{FF}=0.635\\$ ), while best performing $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cell shows $19.0\\%$ $(J_{\\mathrm{SC}}=23.4\\mathrm{mAcm}^{-2}$ $V_{\\mathrm{OC}}=1.07\\:\\mathrm{V}$ , $\\mathrm{FF}=0.759$ ) at reverse scan and $13.9\\%(J_{\\mathrm{SC}}=23.6\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ $V_{\\mathrm{OC}}=1.04\\:\\mathrm{V}_{\\mathrm{:}}$ , $\\mathrm{FF}=0.567)$ at forward scan, resulting in average PCE of $16.5\\%$ $J_{\\mathrm{SC}}=23.5$ mA $\\mathrm{cm}^{-2}$ $V_{\\mathrm{OC}}=1.06\\:\\mathrm{V}$ , $\\mathrm{FF}=0.663$ ). \n\n![](images/d41caa807ee954c85f76874e751031df9eccdbdba8b6cf0e5514de69b401b202.jpg) \nFigure 3. Surface scanning electron microscopic (SEM) images of a) $\\mathsf{F A P b l}_{3}$ and b) $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{l}_{3}$ . Cross-sectional SEM images of planar structured perovskite solar cell employing c) $\\mathsf{F A P b l}_{3}$ and d) $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{I}_{3}$ . Scale bars on the images represent $\\mathsf{100~n m}$ . $\\mathsf{B l-T i O}_{2}$ stands for blocking layer $\\mathsf{T i O}_{2}$ . \n\nIn Figure 5 recombination kinetics of the perovskite solar cells were investigated from transient photovoltage decay profiles. As can be seen in Figure 5a, perovskite solar cell with $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ shows longer time constant for charge recombination $(\\tau_{\\mathrm{R}})$ compared to $\\mathrm{FAPbI}_{3}$ one, which correlates with slightly higher $V_{\\mathrm{OC}}$ of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cell than that of $\\mathrm{FAPbI}_{3}$ one. Origin of different recombination kinetics is investigated by dark current measurement (Figure S13, Supporting Information). Shunt and series resistance are obtained from the inverse slope near zero bias and $V_{\\mathrm{OC}}$ region, respectively. 44 Ideality factor $(n)$ and saturation current $\\left(J_{0}\\right)$ are calculated by fitting the data to Equation $(1)^{[45]}$ \n\n$$\n\\ln(J_{\\mathrm{D}}){=}\\ln(J_{0}){+}{\\left({\\frac{1}{n}}\\right)}{\\frac{q}{k_{\\mathrm{B}}T}}V_{\\mathrm{b}}\n$$ \n\nwhere $J_{\\mathrm{D}},V_{\\mathrm{b}},q,k_{\\mathrm{B}}$ , and $T$ represent current density, bias voltage, electron charge, Boltzmann constant, and temperature, respectively. Fit results are summarized in Table S4 (Supporting Information). Series resistance is $46\\%$ lower $(8.16~\\Omega~\\mathrm{cm}^{2})$ for $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ than that for $\\mathrm{FAPbI}_{3}$ $(14.93\\Omega\\ \\mathrm{cm}^{2})$ ), while shunt resistance increases almost three times from 20 399.84 to $64\\:\\:683.05\\:\\Omega\\:\\mathrm{cm}^{2}$ , which is responsible for higher FF of $\\mathrm{FA}_{0.9}\\mathrm{Cs}_{0.1}\\mathrm{Pb}\\mathrm{I}_{3}$ perovskite solar cell. $J_{0}$ and $n$ are determined to be $3.32\\times10^{-6}\\mathrm{mAcm^{-2}}$ and 2.91 for $\\mathrm{FAPbI}_{3}$ , and $3.45\\times10^{-7}\\mathrm{mAcm^{-2}}$ and 2.53 for $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ , respectively. Higher $R_{\\mathrm{sh}}$ and lower $J_{0}$ are correlated with higher $V_{\\mathrm{OC}}$ of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cell. To elucidate the origin of higher shunt resistance and lower saturation current density, admittance spectroscopy measurement is carried out (Figure 5b,c). Using the admittance spectroscopy, trap density $(N_{\\mathrm{T}})$ of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ is estimated from angular frequency dependent capacitance (Figure 5b) using Equation $(2)^{[46-49]}$ \n\n![](images/5ffbde2af26f8042fb85c91788e8e988ab6fd980dfbd4272dd75d195c852b94f.jpg) \nFigure 4. Statistical distribution of power conversion efficiency (PCE) of the perovskite solar cell employing a) $\\mathsf{F A P b l}_{3}$ and b) $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{l}_{3}$ obtained under AM 1.5G one sun illumination $(700\\mathsf{m}\\mathsf{w}\\mathsf{c m}^{-2})$ at reverse scan $(V_{\\mathrm{OC}}\\mathrm{to}J_{\\mathsf{S C}})$ with the scan rate of $0.11\\vee{\\mathsf{s}}^{-1}$ . c) Current density–voltage $\\left(J-V\\right)$ curves of the best performing devices for $\\mathsf{F A P b l}_{3}$ and $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{I}_{3}$ at reverse scan (solid lines) and forward scan (dotted lines). \n\n![](images/470d6d7bc25d79b3afc0c645f7829a66d73fad1a1d4735870ec11b556b76c401.jpg) \nFigure 5. a) Time constant for charge recombination, b) capacitance–frequency, and c) calculated trap density $(N_{\\top})$ of $\\mathsf{F A P b l}_{3}$ and $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{l}_{3}$ perovskite solar cells measured at room temperature. \n\n$$\nN_{\\mathrm{T}}(E_{\\omega}){=}{-}\\frac{V_{\\mathrm{bi}}}{q\\mathrm{W}}\\frac{\\mathrm{d}C}{\\mathrm{d}\\omega}\\frac{\\omega}{k T}\n$$ \n\nwhere $V_{\\mathrm{bi}}$ denotes the built-in potential, $W$ is the depletion width, $C$ is the capacitance, $\\omega$ is the frequency, $k$ is Boltzmann constant, and $T$ is the temperature. $V_{\\mathrm{bi}}$ and $W$ are obtained from $C^{-2}-V$ plot as described elsewhere. 48,50 As shown in Figure 5c $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ shows almost one order of magnitude lower trap density compared to $\\mathrm{FAPbI}_{3}$ which indicates that incorporation of Cs in $\\mathrm{FAPbI}_{3}$ successfully reduces the overall trap state located above valence band $(E\\omega=E_{\\mathrm{T}}-E_{\\mathrm{V}},$ where $E_{\\mathrm{T}}$ and $E_{\\mathrm{V}}$ are trap energy and valence band edge, respectively) and thus improves FF and $V_{\\mathrm{OC}}$ $N_{\\mathrm{T}}$ peak near $E\\omega=0.15\\mathrm{~eV}$ is generally ascribed to the shallow traps in $\\mathrm{FAPbI}_{3}$ , which shows similar value with $\\mathsf{M A P b I}_{3}$ 48 Although the origin of distinctive deeper traps near $E\\omega=0.3\\mathrm{~eV}$ is not elucidated yet, it might come from the electrode polarization at the interface, which seems to be closely related to hysteresis. \n\nPhoto- and moisture stability of the $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ film are evaluated and compared with those of the $\\mathrm{FAPbI}_{3}$ one. Figure 6 shows normalized absorbance at $630~\\mathrm{nm}$ as a function of time (see the whole absorption spectra in Figures S14 and S15, Supporting Information). For the photostability test, $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ films formed on the compact $\\mathrm{TiO}_{2}$ layer coated FTO glass are prepared, which are exposed to continuous white light illumination using sulfur lamp with intensity of about $100\\mathrm{\\mw\\cm^{-2}}$ . The absorbance of both films decreases gradually and the decrease is pronounced after ${\\approx}10\\mathrm{~h~}$ (Figure 6a), which might be due to gradual increase of substrate temperature up to $60~^{\\circ}\\mathrm{C}$ . However, $\\mathrm{FAPbI}_{3}$ film shows more severe degradation $(85.9\\%$ degraded) than $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ $(65.0\\%$ degraded) after $^{19\\mathrm{~h~}}$ . We also compare photostability of $\\mathrm{MAPbI}_{3}$ with that of $\\mathrm{FA}_{0.5}\\mathrm{MA}_{0.5}\\mathrm{PbI}_{3}$ (Figure S14, Supporting Information). For the case of $\\mathrm{MAPbI}_{3}$ , the color of the film is completely bleached within $^\\mathrm{~1~h~}$ upon exposure to white light. Also, replacement of $50\\%$ of FA cation with MA cation $(\\mathrm{FA}_{0.5}\\mathrm{MA}_{0.5}\\mathrm{PbI}_{3})$ cannot avoid the degradation, in which the color of the film is completely bleached after $^{8\\mathrm{h}}$ . Mechanism of light-induced degradation of $\\mathrm{MAPbI}_{3}$ in ambient condition was reported to be due to generation of HI resulting from released proton from MA cation. 51,52 For the case of $\\mathrm{FAPbI}_{3}$ however, the degree to release the proton is expected to be less than MA cation case because the $\\mathrm{FA^{+}}$ ion is stabilized by the resonance characteristics of $\\mathsf{C-N}$ bonds. 32,53 Moreover, it is reasonable that the partial substitution of ${\\mathrm{Cs}^{+}}$ for $\\mathrm{FA^{+}}$ will lead to further enhancement of photostability because generation of HI will be quenched by CsI. For the humidity-stability test, both films are exposed to relative humidity of $85\\%$ at $25~^{\\circ}\\mathrm{C}$ (dark condition). Compared to $\\mathrm{FAPbI}_{3}$ $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ shows relatively superior stability against the humidity, where much more severe degradation for $\\mathrm{FAPbI}_{3}$ at 600 nm $(77.8\\%)$ than degradation of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ $(49.9\\%)$ is observed for 7 h (Figure 6b). Since poor stability of $\\mathrm{FAPbI}_{3}$ against the humidity results from either conversion of the black phase to yellow phase or accelerated dissociation of formamidinium cation to ammonia and sym-triazine. 22 $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ is expected to be more stable because incorporation of $10\\%$ Cs stabilizes the black $\\mathrm{FAPbI}_{3}$ at relatively low temperature as evidenced by XRD in Figure 1 and Cs cation hardly undergoes such a dissociation. In addition, the enhanced photo- and humidity stability of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ correlate with the decreased lattice parameter, associated with more tightly surrounded FA cation by Cs doping. \n\n![](images/d42b1c6dc383058924e5e3792fc782c659cc88ee82231efc953d462852e68440.jpg) \nFigure 6. Normalized absorbance of $\\mathsf{F A P b l}_{3}$ and $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b l}_{3}$ films measured a) under sulfur lamp (relative humidity (RH) $<50\\%$ , temperature $(T)<65^{\\circ}\\mathsf{C})$ and b) under constant humidity of RH $85\\%$ in dark ${\\bf\\nabla}\\cdot{\\bf\\nabla}T=$ $25^{\\circ}\\mathsf{C})$ as a function of time. The absorption spectra were measured every hour for photostability test and every half an hour for moisture-stability test. \n\n![](images/1b14768f95cdf88496abf9e6a683fa79c4afea0b36970e6ba797bb771774f1c2.jpg) \nFigure 7. Normalized PCE measured under continuous white light illumination $(700\\ m\\times100^{-2})$ in ambient condition (relative humidity (RH) $<$ $40\\%$ ). The devices were not encapsulated and the data were obtained at reverse scan with the scan rate of $0.11\\vee{\\mathsf{s}}^{-1}$ . The data were taken from the results of four devices. \n\nFinally, we investigate stability of the full cells with and without encapsulation. Figure 7 shows PCE as function of time, where the photovoltaic performance of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ was measured every $5\\ \\mathrm{min}$ under white light illumination $(100\\mathrm{mW}\\mathrm{cm}^{-2})$ ) without encapsulation in ambient condition $\\mathrm{RH}<40\\%)$ . To reduce the experimental error, four devices were tested for $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cells. As can be seen in Figure 7, the device employing $\\mathrm{FA}_{0.9}\\mathrm{Cs}_{0.1}\\mathrm{PbI}_{3}$ shows relatively better stability than the pristine $\\mathrm{FAPbI}_{3}$ based device. PCE for the pristine $\\mathrm{FAPbI}_{3}$ device are degraded by $81\\%$ after $30~\\mathrm{min}$ , whereas the $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ device shows $67\\%$ degradation. Enhanced stability in ambient condition is likely to be attributed to better intrinsic material stability against light and humidity, as observed in Figure 6 \n\nAlthough the stability of the $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cell is relatively better than that of the $\\mathrm{FAPbI}_{3}$ one without encapsulation, both of the devices are quickly degraded within $60\\mathrm{min}$ . We should consider the encapsulation of the device for realistic application. 54 The encapsulation was performed in $\\mathrm{N}_{2}$ filled glove box using UV-curable epoxy resin. Three devices were tested for $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ As can be seen in Figure 8, two of three $\\mathrm{FAPbI}_{3}$ perovskite solar cells are degraded quickly within $70\\mathrm{{h}}$ , while the other $\\mathrm{FAPbI}_{3}$ perovskite solar cell retains $\\approx70\\%$ of initial PCE after $220\\mathrm{~h~}$ . Although two of three $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cells show slower degradation compared to quickly degraded $\\mathrm{FAPbI}_{3}$ devices, it is difficult to conclude that encapsulated $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ perovskite solar cell is more stable than the encapsulated $\\mathrm{FAPbI}_{3}$ one because of no significant difference in long-term stability between the encapsulated devices for $220\\mathrm{h}$ . Therefore, at this stage, we concluded that stability of the device encapsulated under inert atmosphere is highly dependent on completeness of encapsulation technique, and degradation mechanism of the perovskite solar cells under inert atmosphere might be different from degradation mechanism in presence of humidity and air. \n\n![](images/3b20a207546df3f523595522da539a1d3f309d999e19626e7a2c237a3cb8fbea.jpg) \nFigure 8. Normalized short-circuit current density $(1\\varsigma{\\bf{c}})$ , open circuit voltage $(V_{\\mathrm{OC}})$ , fill factor (FF), and power conversion efficiency (PCE) of the encapsulated planar heterojunction perovskite solar cells employing $\\mathsf{F A P b l}_{3}$ (red) and $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{I}_{3}$ (blue) under continuous white light (sulfur lamp, ${\\approx}100~\\mathsf{m}\\mathsf{W}~\\mathsf{c m}^{-2},$ ) illumination (relative humidity $(\\mathsf{R H})<$ $50\\%$ , temperature $(T)<65^{\\circ}\\mathsf{C})$ . The devices were encapsulated under ${\\sf N}_{2}$ atmosphere using UV-curable sealant. The data were obtained at reverse scan $(V_{\\mathsf{O C}}$ to $J_{\\mathsf{S C}})$ . Three devices were tested. \n\n# 3. Conclusion \n\nIn conclusion, highly efficient planar heterojunction perovskite solar cells employing $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ were successfully fabricated by using Lewis base adduct of $\\mathrm{PbI}_{2}$ . PCE was enhanced from $14.9\\%$ to $16.5\\%$ by partial substitution of Cs cation for FA cation due to suppressed charge recombination. The suppressed charge recombination was attributed to reduced trap density being close to valence band maximum, which resulted \n\n# www.MaterialsViews.com \n\nin increase in shunt resistance and decrease in saturation current. Photo- and moisture stability of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ were found to be substantially improved compared to the pristine $\\mathrm{FAPbI}_{3}$ Incorporation of partial Cs ion in FA-site led to contraction of cubo-octahedral volume and thereby enhance (FA–I) interaction, which was mainly responsible for the improved stability of $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ . Eventually, perovskite solar cell employing $\\mathrm{FA_{0.9}C s_{0.1}P b I_{3}}$ demonstrates enhanced stability over the $\\mathrm{FAPbI}_{3}$ based device under continuous illumination. \n\n# 4. Experimental Section \n\nSynthesis of $H C(N H_{2})_{2}I$ : FAI was synthesized by reacting $30~\\mathsf{m L}$ hydroiodic acid $(57\\ \\mathrm{wt\\%}$ in water, Sigma-Aldrich) with $\\rceil5\\textrm{g}$ of formamidinium acetate $99\\%$ , Aldrich) at $0~^{\\circ}\\mathsf C$ . After stirring for $2\\ h$ , dark yellow precipitate was recovered by evaporating the solvent at $60~^{\\circ}C$ using rotary evaporator. The solid was washed with ether and recrystallized from ethanol. Resulting white precipitate was dried under vacuum for $24\\ h$ and stored in glove box filled with Ar. \n\nDevice Fabrication: All the devices were prepared in ambient condition, in which relative humidity was not controlled. FTO glass substrate (Pilkington, TEC-8, $8~\\Omega~{\\sf s q}^{-1}$ ) was cleaned by detergent and UV–ozone treatment followed by sonication in ethanol bath for 15 min. A compact $\\mathsf{T i O}_{2}$ layer with thickness of ${\\approx}60$ nm was deposited on the FTO substrate by repeated spin-coating of $0.7~\\mathrm{~w~}$ 1-butanol (Aldrich, $99.8\\%$ ) solution of titanium diisopropoxide bis(acetylacetonate) three times. Between each coating, the substrate was dried on hot plate at $125^{\\circ}\\mathsf{C}$ for 5 min, and finally annealed at $500~^{\\circ}\\mathsf{C}$ for $20\\mathrm{\\min}$ after completion of spincoating. Compact $\\mathsf{T i O}_{2}$ -coated FTO glass was treated with UV–ozone for $10\\min$ before spin-coating of perovskite solution. Perovskite solution was prepared by dissolving 1 mmol of $\\mathsf{P b l}_{2}$ $467\\ m g$ , Aldrich, $99\\%$ ), FAI $(772~\\mathsf{m g})$ , and DMSO ( $78~\\mathsf{m g}$ , Sigma, ${>}99.9\\%\\$ ) in $600~{\\mathfrak{m g}}$ of DMF (Sigma-Aldrich, $99.8\\%$ ). For $\\mathsf{F A}_{1-x}\\mathsf{C s}_{\\mathsf{x}}\\mathsf{P b}\\mathsf{I}_{3}$ , corresponding amount of CsI (Aldrich, $99.9\\%$ ) was added (13, 26, 39, and $52~{\\mathsf{m g}}$ of CsI for $x=0.05$ , 0.10, 0.15, and 0.20) instead of FAI. The solution was filtered by syringe filter having $0.45~{\\upmu\\mathrm{m}}$ pore size (Whatman). $30~\\upmu\\upiota$ of perovskite solution was spin-coated at 4000 rpm for $30~\\mathsf{s}$ , in which $500~\\upmu\\up L$ of diethyl ether (SAMCHUN, $99.0\\%$ ) was dropped on spinning substrate after $\\boldsymbol{\\mathsf{10}}\\boldsymbol{\\mathsf{s}}$ . The substrate was heat-treated at $50^{\\circ}C$ for 3 min and $\\mathsf{l}50^{\\circ}\\mathsf{C}$ for 5 min. SpiroMeOTAD solution was prepared by dissolving $72.3~\\mathrm{mg}$ of spiro-MeOTAD in $7m L$ of chlorobenzene, to which $28.8~\\upmu\\up L$ of 4-tert-butyl pyridine and $17.5~\\upmu\\upiota$ of lithium bis(trifluoromethanesulfonyl)imide solution $(520~\\mathsf{m g}$ LITFSI in $7m L$ acetonitrile (Sigma-Aldrich, $99.8\\%$ ) were added. SpiroMeOTAD was deposited by dropping $20~\\upmu\\upiota$ of spiro-MeOTAD solution on substrate spinning at 3000 rpm. For counter electrode, $\\mathsf{A g}$ was thermally evaporated at evaporation rate of $0.3\\mathring{\\mathsf{A}}\\mathsf{s}^{-1}$ for about 110 min. Au electrode was used for long-term stability test. \n\nCharacterization: Current density–voltage curve was measured using a Keithley 2400 source meter under one sun illumination (AM 1.5G, $100\\ m\\times1\\ c m^{-2},$ ), which was simulated by solar simulator (Oriel Sol 3A classAAA) equipped with 450 W Xenon lamp (Newport 6280NS). Light intensity was adjusted by NREL-calibrated Si solar cell equipped with KG-2 filter. During the measurement, device was covered with a metal aperture mask with active area of $0.125~{\\mathsf{c m}}^{2}$ . EQE was measured by a specially designed EQE system (PV Measurement Inc.). Monochromatic beam was generated from a 75 W Xenon source lamp (USHIO, Japan). EQE data were collected at DC mode without bias light. Absorption coefficient was calculated from transmittance and reflectance of the perovskite film coated on glass. Both transmittance and reflectance were measured by UV–vis spectrometer (Perkinelmer, lamda35) equipped with integrating sphere. Thickness of the perovskite film was measured by alpha-step IQ surface profiler (KAL Tencor). Differential scanning calorimetry was measured by DSC7020 (Seico Instruments). X-ray diffraction pattern was measured by Bruker AXS (D8 advance, Bruker Corporation) using $\\mathsf{C u}\\ \\mathsf{K}\\alpha$ radiation at a scan rate of $4^{\\circ}\\mathsf{m i n}^{-1}$ . \n\nX-ray photoelectron spectroscopy measurements were performed using ESCALAB 250 XPS system (Thermo Fisher Scientific) with Al $\\mathsf{K}\\alpha$ X-ray radiation $(7486.6\\ \\mathrm{eV})$ as the X-ray source. Time constant for charge recombination was measured with a weak laser pulse at $532\\ \\mathsf{n m}$ superimposed on a relatively large bias illumination at $680~\\mathsf{n m}$ using a transient photocurrent–voltage measurement setup described elsewhere. 11 Admittance spectroscopy measurements were performed with a potentiostat/galvanostat (PGSTAT 128N, Autolab, Eco-Chemie) in dark. To avoid unintended effect by bias voltage on capacitance, $20~\\mathsf{m V}$ of AC sinusoidal pulse with frequency from ${\\sf\\sf1}{\\sf H}z$ to 1 MHz was applied without any DC voltage. To convert $x\\cdot$ axis from angular frequency to Eω ${\\left(=k T\\left|_{\\mathsf{n}}(2\\nu_{0}/\\omega)\\right.\\right)}$ , the attempt-to-escape frequency $(\\nu_{0})$ was calculated from frequency-dependent capacitance plot via relaxation process instead of Arrhenius plot of characteristic frequency. 46,48 \n\nSamples for Evaluation of Stability: For testing stability of the films, $\\mathsf{F A P b l}_{3}$ , $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{I}_{3}$ , $\\mathsf{F A}_{0.5}\\mathsf{M A}_{0.5}\\mathsf{P b l}_{3},$ , and $\\mathsf{M A P b l}_{3}$ films were deposited by spin-coating each precursor solution on compact $\\mathsf{T i O}_{2}$ coated FTO glass. For $\\mathsf{F A}_{0.5}\\mathsf{M A}_{0.5}\\mathsf{P b l}_{3}$ and $\\mathsf{M A P b l}_{3}$ solution, corresponding amount of MAI was added to precursor solution instead of FAI. The devices for evaluation of stability were prepared by depositing spiro-MeOTAD and Au as described previously. Encapsulation of the devices was conducted in ${\\sf N}_{2}$ filled glove box by covering active area of the device with a glass substrate which was fixed by UV-curable epoxy resin. During the measurement with 30 min interval, the devices were continuously exposed to white light generated by $730\\ \\forall{}$ sulfur lamp (LG electronics, PSH0731B). \n\nPhotostability: $\\mathsf{F A P b l}_{3}$ , $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{I}_{3}$ , $\\mathsf{F A}_{0.5}\\mathsf{M A}_{0.5}\\mathsf{P b l}_{3}$ , and $\\mathsf{M A P b l}_{3}$ films were exposed to white light generated by 730 W sulfur lamp. Temperature of the film was measured to be ${\\approx}60~^{\\circ}\\mathsf{C}$ while relative humidity was less than $50\\%$ . \n\nMoisture Stability: $\\mathsf{F A P b l}_{3}$ and $\\mathsf{F A}_{0.9}\\mathsf{C s}_{0.1}\\mathsf{P b}\\mathsf{l}_{3}$ films were stored in constant humidity and temperature chamber in dark condition, in which humidity and temperature were controlled to be $25^{\\circ}C$ and $R H85\\%$ , respectively. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nJ.-W.L. and D.-H.K. contributed equally to this work. This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Ministry of Science, ICT & Future Planning (MSIP) of Korea under Contract Nos. NRF-2012M1A2A2671721, 2012M3A7B4049986 (Nano Material Technology Development Program) and NRF-2012M3A6A7054861 (Global Frontier R&D Program on Center for Multiscale Energy System). J.-W. Lee is grateful for a global PhD fellowship grant from NRF under Contract No. 2011-0008000. \n\nReceived: July 2, 2015 \nRevised: August 16, 2015 \nPublished online: September 16, 2015 \n\n[5] J. Burschka, N. Pellet, S. J. Moon, R. Humphry-Baker, P. Gao, M. K. Nazeeruddin, M. Grätzel, Nature 2013, 499, 316. \n[6] M. Liu, M. B. Johnston, H. J. Snaith, Nature 2013, 501, 395. \n[7] N. J. Jeon, J. H. Noh, Y. C. Kim, W. S. Yang, S. Ryu, S. I. Seok, Nat. Mater. 2014, 13, 897. \n[8] H. Zhou, Q. Chen, G. Li, S. Luo, T. b. Song, H. S. Duan, Z. Hong, J. You, Y. Liu, Y. Yang, Science 2014, 345, 542. \n[9] J.-H. Im, I.-H. Jang, N. Pellet, M. Gratzel, N.-G. Park, Nat. Nanotechnol. 2014, 9, 927. \n[10] D.-Y. Son, J.-H. Im, H.-S. Kim, N.-G. Park, J. Phys. Chem. C 2014, 118, 16567. \n[11] J.-W. Lee, T.-Y. Lee, P. J. Yoo, M. Grätzel, S. Mhaisalkard, N.-G. Park, J. Mater. Chem. A 2014, 2, 9251. \n[12] H.-S. Kim, J.-W. Lee, N. Yantara, P. P. Boix, S. A. Kulkarni, S. Mhaisalkar, M. Grätzel, N.-G. Park, Nano Lett. 2013, 13, 2412. \n[13] K. Mahmood, B. S. Swain, H. S. Jung, Nanoscale 2014, 6, 9127. \n[14] N. J. Jeon, J. H. Noh, W. S. Yang, Y. C. Kim, S. Ryu, J. Seo, S. I. Seok, Nature 2015, 517, 476. \n[15] W. S. Yang, J. H. Noh, N. J. Jeon, Y. C. Kim, S. Ryu, J. Seo, S. I. Seok, Science 2015, 348, 1234. \n[16] H.-S. Kim, I. Mora-Sero, V. Gonzalez-Pedro, F. Fabregat-Santiago, E. J. Juarez-Perez, N.-G. Park, J. Bisquert, Nat. Commun. 2013, 4, 2242. \n[17] S. D. Stranks, G. E. Eperon, G. Grancini, C. Menelaou, M. J. P. Alcocer, T. Leijtens, L. M. Herz, A. Petrozza, H. J. Snaith, Science 2013, 342, 341. \n[18] G. Xing, N. Mathews, S. Sun, S. S. Lim, Y. M. Lam, M. Grätzel, S. Mhaisalkar, T. C. Sum, Science 2013, 342, 344. \n[19] H.-S. Kim, S.-H. Im, N.-G. Park, J. Phys. Chem. C 2014, 118, 5615. \n[20] H. S. Jung, N.-G. Park, Small 2015, 11, 10. \n[21] N.-G. Park, J. Phys. Chem. Lett. 2013, 4, 2423. \n[22] C. C. Stoumpos, C. D. Malliakas, M. G. Kanatzidis, Inorg. Chem. 2013, 52, 9019. \n[23] Y. Han, S. Meyer, Y. Dkhissi, K. Weber, J. M. Pringle, U. Bach, L. Spiccia, Y. B. Cheng, J. Mater. Chem. A 2015, 3, 8139. \n[24] R. K. Misra, S. Aharon, B. Li, D. Mogilyansky, I. Visoly-Fisher, L. Etgar, E. A. Katz, J. Phys. Chem. Lett. 2015, 6, 326. \n[25] B. Conings, J. Drijkoningen, N. Gauquelin, A. Babayigit, J. D’Haen, L. D’Olieslaeger, A. Ethirajan, J. Verbeeck, J. Manca, E. Mosconi, F. D. Angelis, H.-G. Boyen, Adv. Energy Mater. 2015, 5, 1500477. \n[26] T. M. Koh, K. Fu, Y. Fang, S. Chen, T. C. Sum, N. Mathews, S. G. Mhaisalkar, P. P. Boix, T. Baikie, J. Phys. Chem. C 2014, 118, 16458. \n[27] G. E. Eperon, S. D. Stranks, C. Menelaou, M. B. Johnston, L. M. Herz, H. J. Snaith, Energy Environ. Sci. 2014, 7, 982. \n[28] S. Pang, H. Hu, J. Zhang, S. Lv, Y. Yu, F. Wei, T. Qin, H. Xu, Z. Liu, G. Cui, Chem. Mater. 2014, 26, 1485. \n[29] N. Pellet, P. Gao, G. Gregori, T. Y. Yang, M. K. Nazeeruddin, J. Maier, M. Grätzel, Angew. Chem., Int. Ed. 2014, 53, 3151. \n[30] J.-W. Lee, D.-J. Seol, A.-N. Cho, N.-G. Park, Adv. Mater. 2014, 26, 4991. \n[31] M. Hu, L. Liu, A. Mei, Y. Yang, T. Liu, H. Han, J. Mater. Chem. A 2014, 2, 17115. \n[32] A. Binek, F. C. Hanusch, P. Docampo, T. Bein, J. Phys. Chem. Lett. 2015, 6, 1249. \n[33] J.-W Lee, S.H. Lee, H.-S Ko, J. Kwon, J. H. Park, S. M. Kang, N. Ahn, M. Choi, J. K. Kim, N.-G. Park, J. Mater. Chem. A 2015, 3, 9179. \n[34] D.-J. Seol, J.-W. Lee, N.-G. Park, ChemSusChem 2015, 8, 2414. \n[35] E. T. Hoke, D. J. Slotcavage, E. R. Dohner, A. R. Bowring, H. I. Karunadas, M. D. McGehee, Chem. Sci. 2015, 6, 613. \n[36] N. Ahn, D.-Y. Son, I.-H. Jang, S. M. Kang, M. Choi, N.-G. Park, J. Am. Chem. Soc. 2015, 137, 8696. \n[37] A. Amat, E. Mosconi, E. Ronca, C. Quarti, P. Umari, Md. K. Nazeeruddin, M. Grätzel, F. D. Angelis, Nano Lett. 2014, 14, 3608. \n[38] A. P. Dementjev, A. de Graaf, M. C. M. van de Sandenb, K. I. Maslakova, A. V. Naumkina, A. A. Serova, Diamond Relat. Mater. 2000, 9, 1904. \n[39] R. Lindblad, N. K. Jena, B. Philippe, J. Oscarsson, D. Bi, A. Lindblad, S. Mandal, B. Pal, D. D. Sarma, O. Karis, H. Siegbahn, E. M. J. Johansson, M. Odelius, H. Rensmo, J. Phys. Chem. C 2015, 119, 1818. \n[40] H. Lin, C. P. Huang, W. Li, C. Ni, S. I. Shah, Y. H. Tseng, Appl. Catal., B 2006, 68, 1. \n[41] M. R. Leyden, M. V. Lee, S. R. Raga, Y. Qi, J. Mater. Chem. A 2015, 3, 16097. \n[42] D. M. Trots, S. V. Myagkota, J. Phys. Chem. Solids 2008, 69, 2520. \n[43] J. W. Johnson, P. A. Agron, M. A. Bredig, J. Am. Chem. Soc. 1955, 77, 2734. \n[44] S.-H. Oh, S.-I. Na, J. Jo, B. Lim, D. Vak, D.-Y. Kim, Adv. Funct. Mater. 2010, 20, 1977. \n[45] D. Zhu, J. Xu, A. N. Noemaun, J. K. Kim, E. F. Schubert, M. H. Crawford, D. D. Koleske, Appl. Phys. Lett. 2009, 94, 081113. \n[46] Q. Wang, Y. Shao, Q. Dong, Z. Xiao, Y. Yuan, J. Huang, Energy Environ. Sci. 2014, 7, 2359. \n[47] H. S. Duan, H. Zhou, Q. Chen, P. Sun, S. Luo, T. B. Song, B. Bob, Y. Yang, Phys. Chem. Chem. Phys. 2015, 17, 112. \n[48] S. Khelifi, K. Decock, J. Lauwaert, H. Vrielinck, D. Spoltore, F. Piersimoni, J. Manca, A. Belghachi, M. Burgelman, J. Appl. Phys. 2011, 110, 094509. \n[49] K. Suzue, S. N. Mohammad, Z. F. Fan, W. Kim, O. Aktas, A. E. Botchkarev, H. Morkoç, J. Appl. Phys. 1996, 80, 4467. \n[50] W. A. Laban, L. Etgar, Energy Environ. Sci. 2013, 6, 3249. \n[51] G. Niu, W. Li, F. Meng, L. Wang, H. Dong, Y. Qiu, J. Mater. Chem. A 2014, 2, 705. \n[52] S. Ito, S. Tanaka, K. Manabe, H. Nishino, J. Phys. Chem. C 2014, 118, 16995. \n[53] D. B. Mitzi, K. Liang, J. Solid State Chem. 1997, 134, 376. \n[54] L. K. Ono, S. R. Raga, M. Remeika, A. J. Winchester, A. Gabe, Y. Qi, J. Mater. Chem. A 2015, 3, 15451. " + }, + { + "id": "10.1038_ncomms7512", + "DOI": "10.1038/ncomms7512", + "DOI Link": "http://dx.doi.org/10.1038/ncomms7512", + "Relative Dir Path": "mds/10.1038_ncomms7512", + "Article Title": "Porous molybdenum carbide nullo-octahedrons synthesized via confined carburization in metal-organic frameworks for efficient hydrogen production", + "Authors": "Wu, HB; Xia, BY; Yu, L; Yu, XY; Lou, XW", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electrochemical water splitting has been considered as a promising approach to produce clean and sustainable hydrogen fuel. However, the lack of high-performance and low-cost electrocatalysts for hydrogen evolution reaction hinders the large-scale application. As a new class of porous materials with tunable structure and composition, metal-organic frameworks have been considered as promising candidates to synthesize various functional materials. Here we demonstrate a metal-organic frameworks-assisted strategy for synthesizing nullo-structured transition metal carbides based on the confined carburization in metal-organic frameworks matrix. Starting from a compound consisting of copper-based metal-organic frameworks host and molybdenum-based polyoxometalates guest, mesoporous molybdenum carbide nullo-octahedrons composed of ultrafine nullocrystallites are successfully prepared as a proof of concept, which exhibit remarkable electrocatalytic performance for hydrogen production from both acidic and basic solutions. The present study provides some guidelines for the design and synthesis of nullostructured electrocatalysts.", + "Times Cited, WoS Core": 1227, + "Times Cited, All Databases": 1270, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000352720000002", + "Markdown": "# Porous molybdenum carbide nano-octahedrons synthesized via confined carburization in metal-organic frameworks for efficient hydrogen production \n\nHao Bin Wu1,\\*, Bao Yu Xia1,\\*, Le $\\mathsf{Y u}^{1},$ , Xin-Yao $\\mathsf{Y u}^{1}$ & Xiong Wen (David) Lou1 \n\nElectrochemical water splitting has been considered as a promising approach to produce clean and sustainable hydrogen fuel. However, the lack of high-performance and low-cost electrocatalysts for hydrogen evolution reaction hinders the large-scale application. As a new class of porous materials with tunable structure and composition, metal-organic frameworks have been considered as promising candidates to synthesize various functional materials. Here we demonstrate a metal-organic frameworks-assisted strategy for synthesizing nanostructured transition metal carbides based on the confined carburization in metal-organic frameworks matrix. Starting from a compound consisting of copper-based metal-organic frameworks host and molybdenum-based polyoxometalates guest, mesoporous molybdenum carbide nano-octahedrons composed of ultrafine nanocrystallites are successfully prepared as a proof of concept, which exhibit remarkable electrocatalytic performance for hydrogen production from both acidic and basic solutions. The present study provides some guidelines for the design and synthesis of nanostructured electrocatalysts. \n\nTahse orcaipaitdedgernovwitrhonomf gnltoablail eunees ghya ceotnrsigugmerpetidotnheanudr tehnet chemical water splitting driven by solar energy has been considered as an attractive approach to produce hydrogen $\\left(\\operatorname{H}_{2}\\right)$ fuel, a sustainable, secure and environmentally benign energy vector1–3. Efficient water splitting requires high-performance electrocatalysts to promote the hydrogen evolution reaction (HER). Platinum (Pt) has been identified as the most active HER catalyst, whereas its high cost and low abundance hinder the large-scale application4. Therefore, numerous efforts have been devoted to search for noble metal-free HER catalysts5–18. Transition metal carbides, such as molybdenum (Mo) and tungsten (W) carbides have been under investigation for decades in the fields of catalysis in view of their high similarity to $\\mathrm{\\Pt}$ -group metals19,20, and have been recently suggested as promising electrocatalysts for $\\mathrm{HER}^{21,22}$ . Particularly, $\\upbeta$ -phase molybdenum carbide $_{\\mathrm{(\\beta-Mo_{2}C)}}$ has been demonstrated as a highly active HER catalyst even as bulky particles23, and the performance could be further improved by constructing proper nanostructures24–27. However, controllable synthesis of nanostructured metal carbides with small nanocrystallites and desirable porosity towards high electrocatalytic activity still remains as a great challenge, due to the difficulty to achieve uniform carburization and the inevitable coalescence of nanoparticles at high reaction temperature. \n\nIn recent years, metal-organic frameworks (MOFs) have emerged as a new class of porous materials with widespread applications in gas storage/separation, catalysis, sensing and drug delivery28–30. Moreover, syntheses of functional materials from MOFs have drawn fast-growing interests as well. The periodically porous and hybrid structure of MOFs offer unique benefits for the fabrication of carbon and/or metal-based nanostructured materials. Specifically, MOFs-derived porous carbon, metal oxides, metal/carbon and metal oxide/carbon nanocomposites have been reported by using MOFs as both the precursor and template31–36. For example, MOFs-derived nanoporous carbon materials exhibit exceptionally high surface area and uniform porosity, which are largely originated from the ordered and porous structure of $\\mathrm{MOFs}^{32,33,37}$ . We have previously used Prussian blue cubic microcrystals to prepare various iron oxidebased hollow microboxes with complex shell structures and compositions38,39. This category of MOFs-derived materials has been recently extended to iron carbide40. However, in most of these studies, MOFs are exclusively used as the sole precursor. Although the huge family of MOFs has covered a wide range of metal species, these conventional MOFs-derived strategies are mainly based on a limited number of MOFs that are easily obtainable and/or with controllable morphology. Consequently, the reported MOFs-derived metal-based materials are typically limited to a handful of elements (for example, Zn, Cu, Co, Fe and so on). \n\nIn this work, we develop a MOFs-assisted strategy for synthesizing porous molybdenum carbide octahedral nanoparticles (denoted as $\\mathrm{MoC}_{x}$ nano-octahedrons) that consist of very small nanocrystallites as electrocatalysts for efficient hydrogen production. Distinct from previous studies, the present synthesis strategy relies on the in situ and confined carburization reaction between the organic ligands (or their derived carbon-based species) of MOFs and guest polyoxometalates (POMs) that reside in the pores of the MOFs host. The introduction of guest metal species into the MOFs host as co-precursor enables easy synthesis of early transition metal (for example, Mo, W and V) carbides, which are difficult to obtain from a single MOFs source. Meanwhile, these non-coordinating POMs are also uniformly distributed and surrounded by organic ligands in atomic scale, thus guaranteeing in situ and homogeneous carburization reaction that produces small carbide nanocrystallites. In addition, the carburization process would be confined within the carbonaceous matrix derived from organic ligands of MOFs, which effectively prevents the agglomeration and coalescence of in situ-generated carbide nanocrystallites. As a proof of concept, we demonstrate the synthesis of molybdenum carbide using this MOFs-assisted approach in view of its promising application in catalysis (for example, for HER) and the easy encapsulation of Mo-based POMs in a particular MOFs host as discussed shortly. Interestingly, the as-prepared molybdenum carbide is in a $\\eta$ -MoC phase, which is unexpected at a relatively low carburization temperature of $800^{\\circ}\\mathrm{C}$ and has not been well investigated for electrocatalytic hydrogen production41. Benefiting from the porous and robust structure, as well as the ultrafine primary nanocrystallites, the as-prepared molybdenum carbide nanooctahedrons exhibit remarkable electrocatalytic activity for HER in both acidic and basic conditions. The present strategy is also applicable to synthesize W and Mo-W carbides, and could be extended to other early transition metals as well. \n\n![](images/49b4e85a31b2d2400a16581f24e9ac289cd406cc37af56bff31dee890620e061.jpg) \nFigure 1 | Schematic illustration of the synthesis procedure for porous $\\mathbf{MoC}_{x}$ nano-octahedrons. (a) Synthesis of NENU-5 nano-octahedrons with Mobased POMs residing in the pores of HKUST-1 host. (b) Formation of ${\\mathsf{M o C}}_{x}{\\mathsf{-C u}}$ nano-octahedrons after annealing at $800^{\\circ}\\mathsf{C}$ (c) Removal of metallic Cu nanoparticles by $\\mathsf{F e}^{3+}$ etching to produce porous ${\\mathsf{M o C}}_{x}$ nano-octahedrons for electrocatalytic hydrogen production. \n\nNATURE COMMUNICATIONS | 6:6512 | DOI: 10.1038/ncomms7512 | www.nature.com/naturecommunications \n\n# Results \n\nMOFs-assisted synthesis strategy for molybdenum carbide. The overall synthesis route to prepare porous $\\mathrm{MoC}_{x}$ octahedral submicrometre-sized particles (denoted as $\\mathrm{MoC}_{x}$ nano-octahedrons) as efficient HER catalysts is illustrated in Fig. 1. We choose a unique MOFs-based compound as the precursor with a formula of $\\mathrm{[Cu_{2}(B T C)_{4/3}(H_{2}O)_{2}]_{6}[H_{3}P M o_{12}O_{40}]}$ (NENU-5; ${\\mathrm{BTC}}=$ benzene-1,3,5-tricarboxylate), which is based on a well-studied Cu-based MOF [HKUST-1; $\\mathrm{Cu}_{3}(\\mathrm{BTC})_{2}(\\mathrm{H}_{2}\\mathrm{O})_{3}]$ with Mo-based Keggin-type POMs $\\left(\\mathrm{H}_{3}\\mathrm{PMo}_{12}\\mathrm{O}_{40}\\right)$ periodically occupying the largest pores42. In this work, NENU-5 nano-octahedrons are synthesized by a facile and scalable co-precipitation method at ambient temperature. The as-prepared NENU-5 nanooctahedrons containing substantial amount of Mo are directly heated at $800^{\\circ}\\mathrm{C}$ in $\\Nu_{2}$ gas flow to produce $\\mathrm{MoC}_{x}$ -Cu. During the annealing process, the Mo-based POMs react with carbonaceous species derived from BTC ligands to form $\\mathrm{MoC}_{x}$ nanocrystallites, meanwhile $\\mathrm{Cu}^{2+}$ clusters are reduced to metallic Cu. Finally, $\\mathrm{MoC}_{x}$ nano-octahedrons composed of small nanocrytallites are obtained by etching the metallic Cu nanoparticles with aqueous solution of $\\mathrm{FeCl}_{3}$ $(\\breve{2}~\\mathrm{Fe}^{3+}+\\mathrm{Cu}\\rightarrow\\mathrm{Cu}^{2+}+\\not{C}2~\\mathrm{Fe}^{2+})$ , and used as electrocatalysts for HER. \n\nSynthesis of porous $\\mathbf{MoC}_{x}$ nano-octahedrons. Figure 2a shows typical field-emission scanning electron microscopy (FESEM) images of the as-prepared NENU-5 particles in octahedral or slightly truncated octahedral shape with a sub-micrometre size of $\\sim800\\mathrm{nm}$ . The size of the as-prepared NENU-5 particles can be easily tuned by varying the addition amount of L-glutamic acid that slows down the nucleation rate (Supplementary Fig. 1). Powder X-ray diffraction (XRD) pattern shown in Fig. 2b (upper curve) confirms the phase purity as well as the excellent crystallinity of the NENU-5 nano-octahedrons. The XRD pattern of HKUST-1 is also provided for comparison (lower curve in Fig. 2b), which exhibits different diffraction peaks especially below $10^{\\circ}$ . Moreover, the successful incorporation of Mo-based POMs in the HKUST-1 framework can be visually verified by the green colour of the product, distinct from the blue colour of pristine HKUST-1 (insets of Fig. 2b)43. The chemical composition is further examined by energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDX). The spectrum (Fig. 2c) evidently shows the presence of substantial amount of Mo in the as-prepared NENU-5 nanooctahedrons. Moreover, a $\\mathrm{Mo/Cu}$ atomic ratio of $\\sim0.7$ suggested by EDX quantitative analysis is lower than the theoretical value of 1 in NENU-5. Therefore, some vacancies of POMs exist in the asprepared NENU-5 nano-octahedrons, which are probably due to the low synthesis temperature and/or the blocking of pores by other species from the solution. Such vacancies are also responsible for the low intensity of characteristic XRD peaks in small angle region43. Moreover, the vacancies of POMs would reduce the yield of $\\mathrm{MoC}_{x}$ and possibly result in less uniform distribution of $\\mathrm{MoC}_{x}$ nanocrystallites, which should be minimized in future studies. \n\nAfter the annealing and etching processes, the $\\mathrm{MoC}_{x}$ sample is obtained as a black powder (inset of Fig. 2d). FESEM image (Fig. 2d) reveals that the octahedral shape of the particles is well retained, while the surface becomes slightly rougher. The complete removal of Cu particles by $\\mathrm{Fe}^{3+}$ etching is confirmed by both XRD and EDX analyses. As shown in Fig. 2e, the three strong and sharp peaks from metallic $\\mathtt{C u}$ in the XRD pattern of $\\mathrm{MoC}_{x}^{\\mathrm{-}}$ -Cu sample (upper curve) are no longer observed in the pattern of $\\mathrm{MoC}_{x}$ sample (lower curve). Moreover, EDX spectrum of the $\\mathrm{MoC}_{x}$ sample confirms the main composition of Mo and $\\scriptstyle{\\mathrm{C}},$ and also excludes the presence of Cu (Fig. 2f). Surprisingly, the XRD pattern of $\\mathrm{Mo}\\bar{\\mathrm{C}}_{x}$ sample shows distinct results from previous reports that typically produce ${\\upbeta}{\\mathrm{-Mo}}_{2}C$ by annealing mixtures of molybdenum salts and organic compounds at similar temperatures25–27,44. The pattern can be satisfactorily assigned to hexagonal $\\eta$ -MoC phase (Supplementary Fig. 2) that is usually produced at much higher temperatures45,46 or in the presence of $\\mathrm{NiI}_{2}$ with short reaction duration41. In our system, the $\\eta$ -MoC phase can be produced between 750 and $\\mathrm{~\\i~}850^{\\circ}\\mathrm{C}$ with little alteration in the XRD patterns (Supplementary Fig. 3). This unusual result implies the distinct characteristics of chemical reactions confined in the MOFs matrix, which is also exemplified by the uncommon synthesis of pure brookite-phase $\\mathrm{TiO}_{2}$ through replication of $\\mathrm{MOF}s^{47}$ . Considering the likelihood to form substoichiometric $\\eta{-}\\mathrm{MoC}_{1-x}$ phases46, and the difficulty to determine the exact chemical composition due to the presence of extra amorphous carbon (as discussed shortly), the as-prepared molybdenum carbide is denoted as $\\mathrm{MoC}_{x}$ in this work. Moreover, the diffraction peaks are significantly broadened, suggesting the very small size of nanocrystallites due to the effective inhibition of coalescence and crystal growth during the confined carburization process. Meanwhile, excessive growth of Cu particles in the $\\mathrm{MoC}_{x}$ -Cu sample as suggested by the XRD pattern (see upper curve in Fig. 2e) still occurs during the annealing process, which is probably related to the relatively low melting point of Cu. \n\n![](images/b3f9ac710ecfd665aae2fca704700abe1a67580bc5f91902214779bc77b9572c.jpg) \nFigure 2 | Characterizations of precursors and $\\boldsymbol{\\mathsf{M o C}}_{\\boldsymbol{\\mathsf{x}}}$ nano-octahedrons. (a) FESEM image (inset: magnified image; scale bar, $500\\mathsf{n m},$ of the as-prepared NENU-5 nano-octahedrons; scale bar, $5\\upmu\\mathrm{m}$ . (b) XRD patterns (inset: digital photos) of NENU-5 (with Mo) and HKUST-1 (without Mo). (c) EDX spectrum of the as-prepared NENU-5 nano-octahedrons. (d) FESEM image (inset: digital photo) of porous ${\\mathsf{M o C}}_{x}$ nano-octahedrons; scale bar, $2\\upmu\\mathrm{m}$ . (e) XRD patterns and (f) EDX spectrums of ${M o C}_{x}–{C}{\\upmu$ and ${\\mathsf{M o C}}_{x}$ nano-octahedrons. \n\nStructural characterizations of $\\mathbf{MoC}_{x}$ nano-octahedrons. The structure of the as-prepared $\\mathrm{MoC}_{x}$ nano-octahedrons is further examined by transmission electron microscopy (TEM) as depicted in Fig. 3. The sample appears as rhombic or cubic particles under TEM observation as the projections of octahedral particles from different directions (Fig. 3a–c). A closer examination on the $\\mathrm{MoC}_{x}$ nano-octahedrons reveals the highly porous texture throughout the whole particle. Each $\\mathrm{MoC}_{x}$ nano-octahedron is composed of numerous small nanocrystallites, and the polycrystalline nature is confirmed by selected-area electron diffraction (SAED) pattern as shown in the inset of Fig. 3c. An interesting observation is that some large particles appear at the corners of the octahedral particles. This is probably due to the higher surface activity and stress in these regions that cause easy collapse of the MOFs matrix and subsequent growth of $\\mathrm{MoC}_{x}$ nanocrystallites during the high-temperature reaction. Indeed, our initial attempt to prepare $\\mathrm{MoC}_{x}$ using much smaller NENU-5 nanoparticles (shown in Supplementary Fig. 1a) with high surface activity results in strongly aggregated particles with a poorly crystallized ${\\mathsf{\\beta-M o}}_{2}\\mathrm{C}$ phase that cannot be well dispersed into suspension for subsequent electrochemical measurements (Supplementary Fig. 4). Therefore, a robust secondary structure with a moderate size (for example, sub-micrometre-sized NENU5 particles) is essential to successfully carry out the confined carburization reaction while providing large exposed surface for catalytic purpose. \n\nA closer TEM examination on the edge of a $\\mathrm{MoC}_{x}$ nanooctahedron gives more details of the nanostructure. Figure 3d clearly shows that numerous $\\mathrm{MoC}_{x}$ clusters (darker area with visible lattice fringes indicated by green circles) are embedded in amorphous carbon matrix. Judging from their crystal lattices, the size of primary $\\mathrm{MoC}_{x}$ nanocrystallites is typically within $5\\mathrm{nm}$ , although some seem to slightly aggregate and appear as larger clusters. The presence of amorphous carbon is also verified by thermogravimetric analysis and Raman spectrum (Supplementary Fig. 5), which might play important roles in prohibiting the growth of $\\mathrm{MoC}_{x}$ nanocrystallites and stabilizing the octahedral particles. A representative high-resolution (HR) TEM image (Fig. 3e) clearly shows lattice fringes with an interplanar distance of $0.24\\mathrm{nm}$ , corresponding to the (006) planes of $\\eta$ -MoC. The uniform distribution of Mo and C elements is illustrated by EDX elemental mappings shown in Fig. 3f. Moreover, the $\\mathrm{MoC}_{x}$ nanooctahedrons exhibit a highly mesoporous structure, as evidenced by a high specific Brunauer–Emmett–Teller surface area of $1\\dot{4}7\\mathrm{m}^{2}\\mathrm{g}^{-1}$ and abundant mesopores mainly distributed in the range of $4{\\mathrm{-}}10\\mathrm{nm}$ (Supplementary Fig. 6). The mesopores in the $\\mathrm{MoC}_{x}$ nano-octahedrons are obviously larger than the pores in the pristine HKUST-1, which would be related to the substantial mass loss (that is, loss of C, H, O, Cu elements) during the carburization process. Such a porous structure with high uniformity is largely inherited from the ordered porous architecture of the MOFs precursor, which would benefit the application in electrocatalysis. \n\nElectrocatalytic performance for HER. The as-prepared porous $\\mathrm{MoC}_{x}$ nano-octahedrons are evaluated as electrocatalysts for HER in both acidic and basic aqueous solutions. The porous $\\mathrm{MoC}_{x}$ nano-octahedrons exhibit optimal performance with a mass loading of $0.8\\mathrm{mg}\\mathrm{cm}^{-2}$ on a glassy carbon (GC) disk electrode (Supplementary Fig. 7), while the catalysts prepared with shorter carburization time or at higher temperature show slightly inferior performance (Supplementary Fig. 8). The representative polarization curve (current density is based on geometric area of the electrode) and Tafel plot of the $\\mathrm{MoC}_{x}$ electrocatalyst in $0.5\\mathbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ are shown in Fig. $^{4\\mathrm{a},\\mathrm{b}}$ , respectively, along with the performance of the benchmark $\\mathrm{Pt/C}$ catalyst $(40\\mathrm{wt\\%}$ Pt on carbon black from Johnson Matthey, mass loading of $0.8\\mathrm{mg}\\mathrm{cm}^{-2},$ for reference. As expected, the $\\mathrm{Pt/C}$ catalyst exhibits excellent catalytic activity with an onset potential of $\\mathord{\\sim}0\\mathrm{V}$ in acidic electrolyte. Meanwhile, the as-prepared $\\mathrm{MoC}_{x}$ electrocatalyst also shows a small onset potential of $\\sim25\\mathrm{mV}$ , estimated from the low current density region of the Tafel plot (Supplementary Fig. 9), beyond which the cathodic current increases rapidly48. To achieve current densities $(j)$ of 1 and $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , the $\\mathrm{MoC}_{x}$ electrocatalyst requires overpotentials $(\\eta)$ of $\\sim87$ and $142\\mathrm{mV}$ , respectively. Tafel plots depicted in Fig. 4b show a small Tafel slope of $53\\mathrm{mV}$ per decade for $\\mathrm{MoC}_{x}$ nano-octahedrons, higher than $29\\mathrm{mV}$ per decade for the $\\mathrm{Pt/C}$ catalyst. By extrapolating the Tafel plot, the exchange current density of $\\mathrm{MoC}_{x}$ nano-octahedrons can be calculated as $0.023\\mathrm{m}\\dot{\\mathrm{A}}\\mathrm{cm}^{-2}$ . Figure $^{4c,\\mathrm{d}}$ shows the electrocatalytic properties of the $\\mathrm{MoC}_{x}$ nano-octahedrons and $\\mathrm{Pt/C}$ in basic condition. Although the $\\mathrm{Pt/C}$ catalyst exhibits a small onset potential close to $0\\mathrm{V}$ compared with $\\mathrm{\\sim80mV}$ for the $\\mathrm{MoC}_{x}$ nano-octahedrons (Supplementary Fig. 10), the $\\mathrm{MoC}_{x}$ electrocatalyst outperforms the $\\bar{\\mathrm{Pt}}/\\mathrm{C}$ catalyst for $\\eta\\ge220\\mathrm{mV}$ with rapidly rising cathodic current. Small overpotentials of 92 and $151\\mathrm{mV}$ are required for the $\\mathrm{MoC}_{x}$ nano-octahedrons to drive $j=1$ and $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively. In addition, the $\\mathrm{MoC}_{x}$ nanooctahedrons exhibit a smaller Tafel slope $59\\mathrm{mV}$ per decade) than the $\\mathrm{Pt/C}$ catalyst $\\mathrm{113mV}$ per decade) as shown in Fig. 4d, along with an exchange current density of B0.029 mA cm \u0002 2. The above comparison is based on the same loading mass of catalysts, which better reflects their performance in practical application and can be directly translated into their relative mass activity. Alternatively, we further compare the current density based on the mass of active materials (MoC for $\\mathrm{MoC}_{x}$ nano-octahedrons and $\\mathrm{Pt}$ for $\\mathrm{Pt/C)}$ and the turnover frequency assuming all metal atoms are involved in the HER process (Supplementary Fig. 11). Similar trends are observed. Specifically, the $\\mathrm{Pt/C}$ catalyst possesses overwhelming advantage in acidic media, while in basic media the activity of $\\mathrm{\\bar{MoC}}_{x}$ nano-octahedrons approaches that of $\\mathrm{Pt/C}$ catalyst at high overpotential. The electrochemical properties of the $\\mathrm{MoC}_{x}$ nanooctahedrons are summarized in Table 1, demonstrating the remarkable electrocatalytic HER activity in both acidic and basic solutions. \n\n![](images/978d3622f280c7e75a76ac53d8dcbc12665e116ccb2bef06368d450dff4abd32.jpg) \nFigure 3 | Characterizations of $\\mathbf{MoC}_{x}$ nano-octahedrons. (a–c) TEM images (scale bar, $200\\mathsf{n m}.$ inset of c: SAED pattern), (d) magnified TEM image (scale bar, $5\\mathsf{n m}.$ ), (e) HRTEM image (scale bar, $2\\mathsf{n m}\\cdot$ ) and (f) elemental mapping (red: carbon; blue: molybdenum; scale bar, $50\\mathsf{n m}$ ) of porous ${M o C}_{x}$ nano-octahedrons. \n\n![](images/625ec7d494cbca868476e4ecf3adb7ac42ee3ad6e01fb9442bc97eaca304120a.jpg) \nFigure 4 | HER performance of porous $\\mathbf{MoC}_{x}$ nano-octahedrons. (a) Polarization curve at $2\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ and (b) Tafel plots in $0.5{\\ensuremath{\\mathsf{M}}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ . (c) Polarization curve at $2\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ and (d) Tafel plots in 1 M KOH. (e) Polarization curves after continuous potential sweeps at $50\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ (left) and 1 M KOH (right). (f) Time-dependent current density curves under $\\eta=170\\ensuremath{\\mathrm{mV}}$ in $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and $\\eta=180\\:\\mathrm{mV}$ in $1M\\mathsf{K O H}$ (insets: TEM images and SAED pattern after 5,000 potential sweeps in $0.5{\\ensuremath{\\mathsf{M}}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ . Scale bars, left inset ( $(200\\mathsf{n m})$ ) and right inset $(20\\mathsf{n m})$ ). \n\n
Table 1 | Summary of HER activities of porous MoCx nano-octahedrons.
ElectrolyteOnset n (mV versus RHE)n at j=1mAcm -2 (mV versus RHE)at j=10mA cm-2 (mV versus RHE) Tafel slope (mV per decade)Exchange current density (mA cm - 2)
0.5M HSO4~ 2587142530.023
1M KOH~8092151590.029
HER, hydrogen evolution reaction.
\n\nTo better understand the origin of such high electrocatalytic performance, we further compare our $\\mathrm{MoC}_{x}$ nano-octahedrons with the irregular $\\mathrm{MoC}_{x}$ nanoparticles (denoted as $\\mathrm{MoC}_{x}$ NPs, as shown in Supplementary Fig. 4 after grinding) as a reference sample, which exhibits similar composition but without welldefined nanostructure. Polarization curves in Supplementary Fig. 12 clearly reveal the much inferior performance of $\\mathrm{\\mathop{MoC}}_{x}\\mathrm{\\mathop{NPs}}$ with $\\eta\\approx230\\mathrm{mV}$ to drive $j=1\\mathrm{mA}\\mathrm{cm}^{\\frac{\\cdot}{-2}}$ in both acidic and basic solutions. To reveal whether the high activity comes from increased surface area, we compare the apparent electrochemical surface area (ECSA) of these two electrocatalysts by measuring the double-layer capacitance $(C_{\\mathrm{dl}})$ , which is typically used to represent the ECSA (Supplementary Fig. 13)12,18. Surprisingly, the $\\mathrm{MoC}_{x}$ NPs actually possess quite similar $C_{\\mathrm{dl}},$ equivalent to ECSA, compared with $\\mathrm{MoC}_{x}$ nano-octahedrons. Although the high surface area of $\\mathrm{MoC}_{x}$ nano-octahedrons would obviously result in certain advantages when compared with bulky or low surface area materials, this is not the sole reason accounting for the high electrocatalytic activity. \n\nElectrochemical impedance spectroscopy (EIS) analysis is performed on $\\mathrm{MoC}_{x}$ nano-octahedrons and ${\\mathrm{MoC}}_{x}{\\mathrm{NPs}}$ . Consistent with the previous studies, the EIS Nyquist plots of $\\mathrm{MoC}_{x}$ nanooctahedrons in both acidic and basic solutions exhibit two time constants (Supplementary Fig. 14). The first one at high frequency is related to the surface porosity of the electrode; the second one at low frequency, which depends on the overpotential, reflects the charge transfer process during $\\mathrm{HER}^{25,27}$ . Generally speaking, the charge-transfer resistance $(R_{\\mathrm{ct}})$ shows strong correlation with the electrochemical performance. Thus, the Nyquist plots of $\\mathrm{MoC}_{x}$ nano-octahedrons and $\\mathrm{MoC}_{x}$ NPs at given overpotentials (that is, $\\eta=90$ and $190\\mathrm{mV},$ ) in $0.5\\mathrm{M}\\mathrm{~H}_{2}\\mathrm{S}\\bar{\\mathrm{O}_{4}}$ are compared and fitted to an equivalent electrical circuit with two time constants (Supplementary Fig. 15). It can be seen that for both samples the $R_{\\mathrm{{ct}}}$ substantially reduces at high overpotential. However, the value for $\\mathrm{MoC}_{x}$ nano-octahedrons is much smaller (about one order of magnitude lower) than that for $\\mathrm{MoC}_{x}$ NPs at the same overpotential, in line with their different HER activity. The small charge transfer resistance would be mainly related to the synergistic effect and strong interaction between the $\\mathrm{MoC}_{x}$ nanocrytallites and the continuous and in situ-incorporated carbon matrix, which ensures the facile electron transfer in the porous $\\mathrm{MoC}_{x}$ nanooctahedrons. Together with the above analysis of ECSA, we speculate that the high electrochemical activity of $\\mathrm{MoC}_{x}$ nanooctahedrons is due to their improved electronic/chemical properties and/or the exposure of more active sites, which are related to their unique mesoporous structure and small primary nanocrystallites. Nevertheless, more in-depth investigations would be necessary to reveal the detailed mechanism involved. \n\nTo assess the durability of the $\\mathrm{MoC}_{x}$ electrocatalyst, accelerated linear potential sweeps are conducted repeatedly on the electrodes at a scan rate of $\\dot{5}0\\mathrm{mVs}^{-1}$ as shown in Fig. 4e. In acidic condition, the polarization curves show a small shift of $\\sim25\\mathrm{mV}$ at $j=10\\mathrm{mA}\\mathrm{cin}^{-2}$ in the initial 1,000 sweeps, and then appear rather stable afterwards. On the other hand, the $\\mathrm{MoC}_{x}$ nanooctahedrons exhibit a continuous but small loss of activity in basic condition on repeated potential sweeps, implying some minor corrosion of electrocatalyst in the basic electrolyte. It should be noted that loss of electrocatalyst from the electrode on rapid rotation might also account for some degradation of the performance. The stability of the electrocatalyst is also evaluated by prolonged electrolysis at constant potentials, as shown in Fig. 4f. In line with the above studies, the current density of $\\mathrm{MoC}_{x}$ nano-octahedrons generally remains stable in 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ for more than $10\\mathrm{{h}}$ , whereas small degradation is observed in $1\\mathrm{M}$ KOH on long-term operation. We have also examined the $\\mathrm{MoC}_{x}$ nano-octahedrons under TEM observation after continuous linear potential sweeps in acidic (insets of Fig. 4f) and basic (Supplementary Fig. 16) media. The nanostructure and crystallinity are well retained after the degradation measurement, again corroborating the good stability in acidic environment. However, some corrosion of the $\\mathrm{MoC}_{x}$ nano-octahedrons (especially the amorphous carbon) occurs during the potential sweeps in $1\\mathrm{M}$ KOH. Such corrosion would cause the disintegration of the $\\mathrm{MoC}_{x}$ nano-octahedrons and loss of active materials, which is expected to account for the small but continuous degradation in basic condition. \n\n# Discussion \n\nThe MOFs-assisted strategy presented in this work is facile and easily reproducible to synthesize porous $\\mathrm{MoC}_{x}$ particles composed of a few nanometer-sized nanocrystallites. Compared with other synthesis methods, such as solid–gas phase reaction49 and pyrolysis of composites containing metal and carbon sources24,25, this MOFs-assisted approach guarantees homogeneous and efficient reaction, as well as uniform mesoporosity of the carbide product, originating from the unique crystalline structure with atomically hybridized MOFs matrix and Mobased POMs. In addition, the highly localized and confined carburization process produces small nanocrystallites, which are embedded in an amorphous carbon matrix and prohibited from excessive growth. More importantly, the present strategy can be easily extended to synthesize tungsten carbide and molybdenum– tungsten mixed carbide (Supplementary Fig. 17), and potentially applicable to other early transition metals as well (Supplementary Note 1). \n\nIn virtue of the unique nanostructure, the porous $\\mathrm{MoC}_{x}$ nanooctahedrons exhibit excellent electrocatalytic activity for HER. In acidic aqueous electrolyte, the performance is among the best reported when compared with many representative noble metalfree electrocatalysts, such as various molybdenum-based compounds, transition metal dichalcogenides and phosphides (Supplementary Table 1). The HER performance in basic condition is also compared favourably with many HER catalysts (Supplementary Table 2). In particular, the electrocatalytic activity of $\\mathrm{MoC}_{x}$ nano-octahedrons in acidic media is comparable to the state-of-the-art ${\\mathsf{\\beta-M o}}_{2}{\\mathsf{C}}$ -based electrocatalysts with extra graphitic carbon supports (for example, graphene and/or carbon nanotubes)25,26,50. However, such high HER activity has not yet been achieved on other phases of molybdenum carbide41. Considering the sub-micrometre size of the $\\mathrm{MoC}_{x}$ nanooctahedrons, such catalytic activity is truly impressive. The high HER performance of our $\\mathrm{MoC}_{x}$ nano-octahedrons might be attributed to the following aspects. First, molybdenum carbides possess exceptional intrinsic HER activity, which is probably related to their $\\mathrm{Pt}$ -like electronic and chemical properties22. Second, the small size of primary $\\mathrm{MoC}_{x}$ nanocrystallites and the high porosity render large electrochemical active surface and more importantly, perhaps more active sites to the $\\mathrm{MoC}_{x}$ nanooctahedrons. Third, the uniform morphology and mesoporous structure are expected to facilitate the charge and mass transport within these relatively large octahedral particles, thus promoting the hydrogen production process. Moreover, the amorphous carbon matrix might grant high robustness of the octahedral particles and provide extra protection for the ultrafine $\\mathrm{MoC}_{x}$ nanocrystallites with high surface energy. Nevertheless, the active materials in the centre part of $\\mathrm{MoC}_{x}$ nano-octahedrons might not be fully utilized. Thus, further improvement is highly expected by optimizing the size/porosity of the particles and/or incorporating supports (for example, carbon nanotubes, graphene sheets and integrated current collectors). \n\nIn summary, we report a novel MOFs-assisted strategy for synthesizing nanostructured $\\mathrm{MoC}_{x}$ nano-octahedrons as a highly active electrocatalyst for HER. This strategy relies on the confined and in situ carburization reaction occurring in a unique MOFsbased compound (NENU-5) consisting of a Cu-based MOFs (HKUST-1) host and guest Mo-based Keggin POMs resided in pores, which enables the uniform formation of metal carbide nanocrystallites without coalescence and excess growth. The asprepared $\\mathrm{MoC}_{x}$ nano-octahedrons consist of ultrafine nanocrytallites with an unusual $\\eta$ -MoC phase embedded in an amorphous carbon matrix, and possess a uniform and highly mesoporous structure. Benefiting from the desirable nanostructure, these porous $\\mathrm{MoC}_{x}$ nano-octahedrons exhibit remarkable electrocatalytic activity for HER in both acidic and basic solutions with good stability. Moreover, such a strategy could be applicable for synthesizing other nanostructured transition metal carbides, thus opening new opportunities to develop high-performance functional materials for various applications. \n\n# Methods \n\nSynthesis of NENU-5 nano-octahedrons. All chemicals were purchased and used without further purification. In a typical synthesis, 1 mmol of copper (II) acetate monohydrate (Sigma-Aldrich), $0.5\\mathrm{mmol}$ of L-glutamic acid (Sigma-Aldrich) and $0.3\\mathrm{g}$ of phosphomolybdic acid hydrate (Sigma-Aldrich) were dissolved in $40\\mathrm{ml}$ of deionized water and stirred at ambient condition for $20\\mathrm{min}$ . After that, $0.67\\mathrm{mmol}$ of 1,3,5-benzenetricarboxylic acid (Merck) completely dissolved in $40\\mathrm{ml}$ of ethanol was poured into the above solution under continuous stirring. The solution immediately turns turbid due to the rapid formation of NENU-5 nanocrystals. After stirring for $14\\mathrm{h}$ at ambient condition, the green precipitate was collected by centrifugation and washed twice with ethanol. The product was dried at $70^{\\circ}\\mathrm{C}$ overnight for further experiment and characterizations. The size of the NENU-5 particles can be easily tuned by varying the added amount of $\\mathrm{~L~}$ -glutamic acid. \n\nSynthesis of porous $\\mathbf{MoC}_{x}$ nano-octahedrons. The NENU-5 nano-octahedrons were heated in a tube furnace under $\\Nu_{2}$ flow with a ramp rate of $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ maintained at $800^{\\circ}\\mathrm{C}$ for $^{6\\mathrm{h}}$ and then cooled down naturally. The as-prepared sample was denoted as $\\mathrm{MoC}_{x}$ -Cu. The copper particles were removed by dispersing the sample in $0.1\\mathrm{M}\\mathrm{FeCl}_{3}$ aqueous solution at ambient condition for $^{2\\mathrm{h}}$ . The resulting porous $\\mathrm{MoC}_{x}$ nano-octahedrons were collected by centrifugation, repeatedly washed with deionized water and then dried at $70^{\\circ}\\mathrm{C}$ overnight. \n\nMaterials characterizations. The morphologies and structures of the products were characterized with FESEM $\\mathrm{\\DeltaJEOL,}$ JSM-6700 F, 5 kV) and TEM (JEOL, JEM-2010 and JEM-2100F, $200\\mathrm{kV}$ ). The chemical compositions and elemental mapping of the samples were analysed by EDX attached to JSM-7600F (FESEM, JEOL, $15\\mathrm{kV}.$ ) and JEM-2100 F. The crystallographic information was collected by powder XRD (Bruker D8 Advance diffractometer with $\\operatorname{Cu}\\ K\\alpha$ radiation $\\overset{\\cdot}{\\lambda}=1.5406\\overset{\\circ}{\\mathrm{A}})$ . The $\\mathrm{N}_{2}$ adsorption–desorption isotherms were collected using a Quantachrome Instruments Autosorb AS-6B at liquid-nitrogen temperature. Raman spectrum was collected using a Renishaw system 1000 micro-Raman spectroscope (Renishaw, UK). Thermogravimetric analysis was performed under air flow with a temperature ramp of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ . \n\nElectrochemical measurements. The electrocatalytic activity was evaluated in a three-electrode configuration using a rotating disk electrode (PINE Research Instrumentation, at a rotation speed of $1500\\mathrm{r.p.m.}$ ) with an Autolab potentiostat/ galvanostat (Model PGSTAT-72637) workstation at ambient temperature. A GC disk electrode $\\mathrm{\\ddot{}}5\\mathrm{mm}$ in diameter) served as the support for the working electrode. The catalyst suspension was prepared by dispersing $10\\mathrm{mg}$ of catalyst in $2\\mathrm{ml}$ of solution containing $1.9\\mathrm{ml}$ of ethanol and $100\\upmu\\mathrm{l}$ of $0.5\\mathrm{wt\\%}$ Nafion solution followed by ultrasonication for $20\\mathrm{min}$ . Then the catalyst suspension was pipetted using a micropipettor on the GC surface. The working electrode was dried at ambient temperature. A saturated calomel electrode (SCE) was used as the reference electrode and a graphite rod was used as the counter electrode. Potentials were referenced to a reversible hydrogen electrode (RHE): $\\mathrm{E(RHE)}=\\mathrm{E(SCE)}+(0.242$ $+0.059\\mathrm{pH})\\mathrm{V}$ . Linear sweep voltammetry was recorded in $0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4}\\left(\\mathrm{pH}=0.3\\right)$ and $1\\mathrm{M}\\ \\mathrm{KOH}$ $(\\mathrm{pH}=14\\$ at a scan rate of $2\\mathrm{m}\\mathrm{V}\\mathrm{s}^{-1}$ to obtain the polarization curves. The long-term stability tests were performed by continuous linear sweep voltammetry scans from $-0.2$ to $-0.6\\mathrm{V}$ (versus SCE, in $0.5\\mathrm{M}\\mathrm{~H}_{2}\\mathrm{SO}_{4};$ and $-1.0$ to $-1.4\\mathrm{V}$ (versus SCE, in $1\\mathrm{M}\\mathrm{KOH}$ at a sweep rate of $50\\mathrm{mVs^{-1}}$ . All the data presented were corrected for iR losses and background current. To evaluate the ECSA, cyclic voltammograms were obtained from $-0.2$ to $0.2\\mathrm{V}$ (versus SCE, in $0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4},$ with sweep rates of 5, 10, 20, 50, $100\\mathrm{mVs}^{-1}$ . EIS was performed at various overpotentials with frequency from 0.1 to $100{,}000\\mathrm{Hz}$ and an amplitude of $10\\mathrm{mV}$ . \n\n# References \n\n1. Lewis, N. S. & Nocera, D. G. Powering the planet: chemical challenges in solar energy utilization. Proc. Natl Acad. Sci. USA 103, 15729–15735 (2006). \n2. Walter, M. G. et al. Solar water splitting cells. Chem. Rev. 110, 6446–6473 (2010). \n3. Cook, T. R. et al. Solar energy supply and storage for the legacy and nonlegacy worlds. Chem. Rev. 110, 6474–6502 (2010). \n4. Gray, H. B. Powering the planet with solar fuel. Nat. Chem. 1, 7–7 (2009). \n5. Liu, Q. et al. Carbon nanotubes decorated with CoP nanocrystals: a highly active non-noble-metal nanohybrid electrocatalyst for hydrogen evolution. Angew. Chem. Int. Ed. 53, 5427–5430 (2014). \n6. Xie, J. et al. Controllable disorder engineering in oxygen-incorporated $\\ensuremath{\\mathbf{MoS}}_{2}$ ultrathin nanosheets for efficient hydrogen evolution. J. Am. Chem. Soc. 135, \n17881–17888 (2013). \n7. Wang, H. et al. Electrochemical tuning of vertically aligned $\\ensuremath{\\mathrm{MoS}}_{2}$ nanofilms and its application in improving hydrogen evolution reaction. Proc. Natl Acad. Sci. USA 110, 19701–19706 (2013). \n8. Sun, Y. et al. Electrodeposited cobalt-sulfide catalyst for electrochemical and photoelectrochemical hydrogen generation from water. J. Am. Chem. Soc. 135, \n17699–17702 (2013). \n9. Kibsgaard, J., Chen, Z., Reinecke, B. N. & Jaramillo, T. F. Engineering the surface structure of $\\mathbf{MoS}_{2}$ to preferentially expose active edge sites for electrocatalysis. Nat. Mater. 11, 963–969 (2012). \n10. Voiry, D. et al. Enhanced catalytic activity in strained chemically exfoliated $\\mathrm{WS}_{2}$ nanosheets for hydrogen evolution. Nat. Mater. 12, 850–855 (2013). \n11. Popczun, E. J., Read, C. G., Roske, C. W., Lewis, N. S. & Schaak, R. E. Highly active electrocatalysis of the hydrogen evolution reaction by cobalt phosphide nanoparticles. Angew. Chem. Int. Ed. 53, 5427–5430 (2014). \n12. Faber, M. S. et al. High-performance electrocatalysis using metallic cobalt pyrite $\\mathrm{(CoS}_{2})$ micro- and nanostructures. J. Am. Chem. Soc. 136, 10053–10061 (2014). \n13. Vrubel, H., Merki, D. & Hu, X. Hydrogen evolution catalyzed by $\\ensuremath{\\mathrm{MoS}}_{3}$ and $\\ensuremath{\\mathrm{MoS}}_{2}$ particles. Energy Environ. Sci. 5, 6136–6144 (2012). \n14. Cao, B., Veith, G. M., Neuefeind, J. C., Adzic, R. R. & Khalifah, P. G. Mixed close-packed cobalt molybdenum nitrides as non-noble metal electrocatalysts for the hydrogen evolution reaction. J. Am. Chem. Soc. 135, 19186–19192 (2013). \n15. Li, Y. et al. $\\ensuremath{\\mathbf{MoS}}_{2}$ nanoparticles grown on graphene: an advanced catalyst for the hydrogen evolution reaction. J. Am. Chem. Soc. 133, 7296–7299 (2011). \n16. Gong, M. et al. Nanoscale nickel oxide/nickel heterostructures for active hydrogen evolution electrocatalysis. Nat. Commun. 5, 4695 (2014). \n17. Popczun, E. J. et al. Nanostructured nickel phosphide as an electrocatalyst for the hydrogen evolution reaction. J. Am. Chem. Soc. 135, 9267–9270 (2013). \n18. Tian, J., Liu, Q., Cheng, N., Asiri, A. M. & Sun, X. Self-supported $\\mathrm{Cu}_{3}\\mathrm{P}$ nanowire arrays as an integrated high-performance three-dimensional cathode for generating hydrogen from water. Angew. Chem. Int. Ed. 53, 9577–9581 (2014). \n19. Hwu, H. H. & Chen, J. G. Surface chemistry of transition metal carbides. Chem. Rev. 105, 185–212 (2004). \n20. Oyama, S. T. Preparation and catalytic properties of transition metal carbides and nitrides. Catal. Today 15, 179–200 (1992). \n21. Michalsky, R., Zhang, Y.-J. & Peterson, A. A. Trends in the hydrogen evolution activity of metal carbide catalysts. ACS Catal. 4, 1274–1278 (2014). \n22. Chen, W.-F., Muckerman, J. T. & Fujita, E. Recent developments in transition metal carbides and nitrides as hydrogen evolution electrocatalysts. Chem. Commun. 49, 8896–8909 (2013). \n23. Vrubel, H. & Hu, X. Molybdenum boride and carbide catalyze hydrogen evolution in both acidic and basic solutions. Angew. Chem. Int. Ed. 51, 12703–12706 (2012). \n24. Chen, W.-F. et al. Biomass-derived electrocatalytic composites for hydrogen evolution. Energy Environ. Sci. 6, 1818–1826 (2013). \n25. Chen, W. F. et al. Highly active and durable nanostructured molybdenum carbide electrocatalysts for hydrogen production. Energy Environ. Sci. 6, 943–951 (2013). \n26. Pan, L. F. et al. Molybdenum carbide stabilized on graphene with high electrocatalytic activity for hydrogen evolution reaction. Chem. Commun. 50, 13135–13137 (2014). \n27. Liao, L. et al. A nanoporous molybdenum carbide nanowire as an electrocatalyst for hydrogen evolution reaction. Energy Environ. Sci. 7, 387–392 (2014). \n28. Furukawa, H., Cordova, K. E., O’Keeffe, M. & Yaghi, O. M. The chemistry and applications of metal-organic frameworks. Science 341, 1230444 (2013). \n29. Kuppler, R. J. et al. Potential applications of metal-organic frameworks. Coord. Chem. Rev. 253, 3042–3066 (2009). \n30. James, S. L. Metal-organic frameworks. Chem. Soc. Rev. 32, 276–288 (2003). \n31. Torad, N. L. et al. Direct synthesis of MOF-derived nanoporous carbon with magnetic Co nanoparticles toward efficient water treatment. Small 10, 2096–2107 (2014). \n32. Torad, N. L. et al. Facile synthesis of nanoporous carbons with controlled particle sizes by direct carbonization of monodispersed ZIF-8 crystals. Chem. Commun. 49, 2521–2523 (2013). \n33. Jiang, H.-L. et al. From metal–organic framework to nanoporous carbon: toward a very high surface area and hydrogen uptake. J. Am. Chem. Soc. 133, 11854–11857 (2011). \n34. Yang, S. J. et al. Preparation and exceptional lithium anodic performance of porous carbon-coated ZnO quantum dots derived from a metal–organic framework. J. Am. Chem. Soc. 135, 7394–7397 (2013). \n35. Xu, X., Cao, R., Jeong, S. & Cho, J. Spindle-like mesoporous $\\scriptstyle\\alpha-\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ anode material prepared from MOF template for high-rate lithium batteries. Nano Lett. 12, 4988–4991 (2012). \n36. Chaikittisilp, W. et al. Synthesis of nanoporous carbon–cobalt-oxide hybrid electrocatalysts by thermal conversion of metal–organic frameworks. Chem. Eur. J. 20, 4217–4221 (2014). \n37. Wu, H. B. et al. Embedding sulfur in MOF-derived microporous carbon polyhedrons for lithium–sulfur batteries. Chem. Eur. J. 19, 10804–10808 (2013). \n38. Zhang, L., Wu, H. B., Madhavi, S., Hng, H. H. & Lou, X. W. Formation of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ microboxes with hierarchical shell structures from metal–organic frameworks and their lithium storage properties. J. Am. Chem. Soc. 134, 17388–17391 (2012). \n39. Zhang, L., Wu, H. B. & Lou, X. W. Metal–organic-frameworks-derived general formation of hollow structures with high complexity. J. Am. Chem. Soc. 135, 10664–10672 (2013). \n40. Hou, Y. et al. Metal \u0002 organic framework-derived nitrogen-doped core-shell-structured porous $\\mathrm{Fe/Fe}_{3}\\mathrm{C}\\ @\\mathrm{C}$ nanoboxes supported on graphene sheets for efficient oxygen reduction reactions. Adv. Energy Mater. 4, 1400337 (2014). \n41. Wan, C., Regmi, Y. N. & Leonard, B. M. Multiple phases of molybdenum carbide as electrocatalysts for the hydrogen evolution reaction. Angew. Chem. Int. Ed. 53, 6407–6410 (2014). \n42. Sun, C.-Y. et al. Highly stable crystalline catalysts based on a microporous metal \u0002 organic framework and polyoxometalates. J. Am. Chem. Soc. 131, 1883–1888 (2009). \n43. Liu, Y. et al. Facile synthesis of a nanocrystalline metal–organic framework impregnated with a phosphovanadomolybdate and its remarkable catalytic performance in ultradeep oxidative desulfurization. ChemCatChem 5, 3086–3091 (2013). \n44. Yan, Z. et al. MoC-graphite composite as a Pt electrocatalyst support for highly active methanol oxidation and oxygen reduction reaction. J. Mater. Chem. A 2, 4014–4022 (2014). \n45. Shohoji, N. et al. Formation of hexagonal $\\boldsymbol{\\mathrm{\\n-MoC_{1-x}}}$ phase at a temperature lower than $1660~^{\\circ}\\mathrm{C}$ by solar radiation heating under presence of excess free carbon. Int. J. Refract. Met. H. Mater. 25, 220–225 (2007). \n46. Hugosson, H. W. et al. Theory of phase stabilities and bonding mechanisms in stoichiometric and substoichiometric molybdenum carbide. J. Appl. Phys. 86, 3758–3767 (1999). \n47. Hall, A. S., Kondo, A., Maeda, K. & Mallouk, T. E. Microporous brookite-phase titania made by replication of a metal–organic framework. J. Am. Chem. Soc. 135, 16276–16279 (2013). \n48. Chen, W.-F. et al. Hydrogen-evolution catalysts based on non-noble metal nickel– molybdenum nitride nanosheets. Angew. Chem. Int. Ed. 51, 6131–6135 (2012). \n49. Lee, J. S., Oyama, S. T. & Boudart, M. Molybdenum carbide catalysts: I. Synthesis of unsupported powders. J. Catal. 106, 125–133 (1987). \n50. Youn, D. H. et al. Highly active and stable hydrogen evolution electrocatalysts based on molybdenum compounds on carbon nanotube–graphene hybrid support. ACS Nano 8, 5164–5173 (2014). \n\n# Acknowledgements \n\nWe are grateful to the Ministry of Education (Singapore) for financial support through the AcRF Tier-1 funding (RG 12/13, M401120000). \n\n# Author contributions \n\nH.B.W. and X.W.L. conceived the idea and co-wrote the manuscript. H.B.W. carried out the synthesis. H.B.W. and B.Y.X. carried out the electrochemical evaluation. L.Y. & X.-Y.Y. helped in materials characterizations. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Wu, H. B. et al. Porous molybdenum carbide nano-octahedrons synthesized via confined carburization in metal-organic frameworks for efficient hydrogen production. Nat. Commun. 6:6512 doi: 10.1038/ncomms7512 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1126_science.aaa1442", + "DOI": "10.1126/science.aaa1442", + "DOI Link": "http://dx.doi.org/10.1126/science.aaa1442", + "Relative Dir Path": "mds/10.1126_science.aaa1442", + "Article Title": "Blowing magnetic skyrmion bubbles", + "Authors": "Jiang, WJ; Upadhyaya, P; Zhang, W; Yu, GQ; Jungfleisch, MB; Fradin, FY; Pearson, JE; Tserkovnyak, Y; Wang, KL; Heinonen, O; te Velthuis, SGE; Hoffmann, A", + "Source Title": "SCIENCE", + "Abstract": "The formation of soap bubbles from thin films is accompanied by topological transitions. Here we show how a magnetic topological structure, a skyrmion bubble, can be generated in a solid-state system in a similar manner. Using an inhomogeneous in-plane current in a system with broken inversion symmetry, we experimentally blow magnetic skyrmion bubbles from a geometrical constriction. The presence of a spatially divergent spin-orbit torque gives rise to instabilities of the magnetic domain structures that are reminiscent of Rayleigh-Plateau instabilities in fluid flows. We determine a phase diagram for skyrmion formation and reveal the efficient manipulation of these dynamically created skyrmions, including depinning and motion. The demonstrated current-driven transformation from stripe domains to magnetic skyrmion bubbles could lead to progress in skyrmion-based spintronics.", + "Times Cited, WoS Core": 1212, + "Times Cited, All Databases": 1288, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000358218600045", + "Markdown": "# Blowing magnetic skyrmion bubbles \n\nWanjun Jiang,' Pramey Upadhyaya,2 Wei Zhang,' Guoqiang Yu,2 M. Benjamin Jungfleisch,1 Frank Y. Fradin,' John E. Pearson, Yaroslav Tserkovnyak,3 Kang L. Wang,² Olle Heinonen,1,4,5,6 Suzanne G. E. te Velthuis,1 Axel Hoffmannl\\* \n\nIMaterials Science Division,Argonne NationalLaboratory,Lemont,IL 6O439,USA.²Device Research Laboratory. DepartmentofElectricalEngineering,UniversityofCalifoniaLosAngeles,CA9o95,USADepartmentofPhysicsand AstronomyniversityofCalifoniaosAngelesCA95,USAepartmentofhysicsandAtronomy,Norhwster UniversityEantonUAorthwestergonnestitteofcienceandEngineringorthwesternniveity USA. 6Computation Institute, University of Chicago,Chicago,IL, USA. \n\n\\*Corresponding author. E-mail: hoffmann@anl.gov \n\nThe formation of soap bubbles from thin films is accompanied by topological transitions. Here we show how a magnetic topological structure, a skyrmion bubble, can be generated in a solid state system in a similar manner. Using an inhomogeneous in-plane current in a system with broken inversion asymmetry, we experimentally “blow\" magnetic skyrmion bubbles from a geometrical constriction. The presence of a spatially divergent spin-orbit torque gives rise to instabilities of the magnetic domain structures that are reminiscent of Rayleigh-Plateau instabilities in fluid flows. We determine a phase diagram for skyrmion formation and reveal the efficient manipulation of these dynamically created skyrmions, including depinning and motion. The demonstrated current-driven transformation from stripe domains to magnetic skyrmion bubbles could lead to progress in skyrmion-based spintronics. \n\nMagnetic skyrmions are topological spin textures that can be stabilized by Dzyaloshinskii-Moriya interactions (DMI) (1-9) in chiral bulk magnets, e.g., MnSi, FeGe, etc. Thanks to their unique vortex-like spin-texture they exhibit many fascinating features including emergent electromagnetic fields which enable their efficient manipulation $(4,5,8–10)$ . A particularly technologically interesting property is that skyrmi ons can be driven by a spin transfer torque mechanism at a very low current density, which has been demonstrated at cryogenic temperatures $(4,\\ 5,\\ 8,\\ 10)$ . Besides bulk chiral magnetic interactions, the interfacial symmetry-breaking in heavy metal/ultra-thin ferromagnet/insulator (HM/F/I) tri layers introduces an interfacial DMI (1l-14) between neigh boring atomic spins, which stabilizes Neel walls (cycloidal rotation of the magnetization direction) with a fixed chirality over the Bloch walls (spiral rotation of the magnetization direction) (l5-2O). This is expected to result in the for mation of skyrmions with a hedgehog configuration (14, 18, 21-25). This commonly accessible material system exhibits spin Hall effects from heavy metals with strong spin-orbit interactions (26), which in turn give rise to well-defined spin-orbit torques (SOTs) (17, 19, 27-29) that can control magnetization dynamics efficiently. However, it has been experimentally challenging to utilize the electric current and/or its induced SOTs (8, 21, 23, 24, 27, 30-32) for dynam ically creating and/or manipulating hedgehog skyrmions \n\nHere we address that issue. \n\nCentral to this work is how electric currents can manipulate a chiral magnetic domain wall (DW), i.e., the chirality of the magnetizationrotation(as shown in Fig. 1A) is identical for every domain wall. This fixed chirality is stabilized by the interfacial DMI (17-19, 21, 28).In HM/F/I heterostructures the current flowing through the heavy metal generates a transverse vertical spin current thanks to the spin Hall effect (27), which results in spin accumulation at the interface with the ferromagnetic layer. This spin accumulation gives rise to a SOT acting on the chiral DW (Fig. 1A). The resultant effective spin Hall field can be expressed as (17-19, 27) \n\n$$\n\\vec{\\bf B}_{\\mathrm{sh}}=B_{\\mathrm{sh}}^{0}\\left(\\hat{m}\\times\\left(\\hat{z}\\times\\hat{j}_{e}\\right)\\right)\n$$ \n\nwhere $\\hat{m}$ is the magnetization unit vector, $\\hat{z}$ is the unit vector normal to the film plane and $\\hat{j}_{e}$ is the direction of electron particle flux. Here $B_{\\mathrm{sh}}^{0}$ can be written as $\\left(\\hbar/2\\middle|e\\right|\\right)\\cdot\\left(\\theta_{s h}J_{c}\\middle/t_{f}M_{s}\\right)$ , where $\\hbar/2$ is the spin of an electron, $e$ is the charge of an electron, $t_{f}$ is the thickness of the ferromagnetic layer, and $M_{S}$ is the saturation (volume) magnetization. The spin Hall angle $\\theta_{s h}=J_{s}/J_{c}$ is defined by the ratio between spin current density $(J_{S})$ and charge current density $(J_{C})$ . For homogeneous current flow along the $x$ axis (Fig. 1B), a chiral SOT enables efficient DW motion (17- 19). In the case of a stripe domain with a chiral DW (Fig. 1B), the symmetry of Eq. 1 leads to a vanishing torque on the side walls parallel to the current and therefore only the end of the stripe domain is moved; if the opposite end is pinned this results in an elongation of the stripe. \n\nThe situation becomes more complex when the stripe domain is subjected to an inhomogeneous current flow. This can be achieved by introducing a geometrical constriction into a current-carrying trilayer wire (Fig. 1C). Such a constriction results in an additional current component along the $y$ axis - $j_{y}$ around the narrow neck (Fig. 1D). The total current $j$ is spatially convergent/divergent to the left/right of the constriction (33). Consequently, inhomogeneous effective forces on the DWs (caused by the spin Hall field) are created along the $y$ axis - ${\\bf F}_{s h}^{y}$ , these forces act to expand the end of the domain (Fig. 1E). As the domain end continually expands its radius the surface tension in the DW (resulting from the increasing DW energy determined by the combination of exchange and anisotropy fields) increases (34), which results in breaking the stripes into circular domains (Fig 1F). \n\nThis process resembles how soap bubbles develop out of soap films upon blowing air through a straw, or how liquid droplets form in fluid flow jets (35). Because of the interfacial DMI in the present system, the spin structures of the newly formed circular domains maintain a well-defined (left-handed) chirality (13, 14, 23, 24). These created synthetic hedgehog (Néel) skyrmions (14, 23), once formed, are stable thanks to topological protection and move very efficiently following the current direction, a process that can be described based on a modified Thiele equation (36). The dynamic skyrmion conversion could, in principle, happen at the other side of device where the spatially convergent current compresses stripe domains. However, sizeable currents/SOTs are required to compensate the enhanced (repulsive) dipolar interaction. The proposed mechanism differs from a recent theoretical proposal with similar geometry, where skyrmions are formed from the coalescence of two independent DWs extending over the full width of a narrow constriction at a current density $\\approx10^{8}~\\mathrm{A/cm^{2}}$ (32). For repeated skyrmion generation, this latter mechanism requires a continuous generation of paired DWs in the constriction, which is inconsistent with the experimental observations described below. \n\n# Transforming chiral stripe domains into skyrmions \n\nWe demonstrated this idea experimentally with a $\\mathrm{Ta}(5\\$ nm) $/\\mathrm{CO_{20}F e_{60}B_{20}(C o F e B)(1.1\\ n m)/T a O_{x}(3\\ n m)}$ trilayer grown by magnetron sputtering (37, 38) and patterned into constricted wires via photolithography and ion-milling (33). The wires have a width of $60~{\\upmu\\mathrm{m}}$ with a $3{\\cdot}{\\upmu}\\mathrm{m}$ wide and 20- μm long geometrical constriction in the center. Our devices are symmetrically designed across the narrow neck to main-tain balanced demagnetization energy. A polar magneto-optical Kerr effect (MOKE) microscope in a differential mode (39) was utilized for dynamic imaging experiments at room temperature. Before applying a current, the sample was first saturated at positive magnetic fields and subse-quently at a perpendicular magnetic field of are symmetrically designed across the narrow neck to maintain balanced demagnetization energy. A polar magnetooptical Kerr effect (MOKE) microscope in a differential mode (39) was utilized for dynamic imaging experiments at room temperature. Before applying a current, the sample was first saturated at positive magnetic fields and subse quently at a perpendicular magnetic field of $B_{\\perp}=+0.5~\\mathrm{mT},$ sparse magnetic stripe and bubble domains prevail at both sides of the wire (Fig. 2A). The lighter area corresponds to negative perpendicular magnetization orientation and darker area corresponds to positive orientation, respectively. \n\nIn contrast to the initial magnetic domain configuration, after passing a 1 s single pulse of amplitude $j_{e}=+5\\times10^{5}$ $\\mathrm{A/cm^{2}}$ (normalized by the width of device - $60~{\\upmu\\mathrm{m}})$ ,it is observed that the stripe domains started to migrate, subsequently forming extended stripe domains on the left side. \n\nThese domains were mostly aligned with the charge current flow and converged at the left side of constriction. The stripes were transformed into skyrmion bubbles immediate ly after passing through the constriction (Fig. 2B). These dynamically created skyrmions, varying in size between 700 nm and $2\\ \\upmu\\mathrm{m}$ (depending on the strength of the external magnetic field), are stable and do not decay on the scale of a typical laboratory testing period (at least 8 hours). The size of the skyrmions is determined by the interplay between Zeeman, magnetostatic interaction and interfacial DMI. In the presence of a constant electron current density of $j_{e}=+5$ $\\times~10^{5}~\\mathrm{A/cm^{2}}$ , these skyrmions are created with a high speed close to the central constriction and annihilated/destroyed at the end of the wire. Capturing the transformation dynamics of skyrmions from stripe domains is beyond the temporal resolution of the present setup. Reproducible generation of skyrmions is demonstrated by repeating pulsed experiments several times (33). Interestingly, the left side of the device remains mainly in the labyrinthine stripe domain state after removing the pulse current, which indicates that both skyrmion bubbles and stripe domains are metastable. \n\nWhen the polarity of the charge current is reversed to $j_{e}$ $=-5\\times10^{5}\\mathrm{\\A/cm^{2}}$ , the skyrmions are formed at the left side of device (Fig. 2, C and D). This directional dependence indicates that the spatially divergent current/sOT, determined by the geometry of the device, is most likely responsible for slicing stripe DWs into magnetic skyrmion bubbles, qualitatively consistent with the schematic presented in Fig. 1. \n\nAt a negative magnetic field $B_{\\perp}=-0.5~\\mathrm{mT}$ and current at $j_{e}=+5\\times10^{5}\\mathrm{A/cm^{2}}$ (Fig. 2, E and F), a reversed contrast, resulting from opposite inner/outer magnetization orientations, is observed as compared to positive fields. We varied the external magnetic field and charge current density systematically and determined the phase diagram for skyrmion formation shown in Fig. 2G. A large population of synthetic skyrmions is found only in the shadowed region, whereas in the rest of phase diagram, the initial domain configurations remain either stationary or flowing smoothly, depending on the strength of current density, as discussed below. This phase diagram is independent of pulse duration for pulses μs. It should be mentioned that no creation of skyrmions in regular shaped device with a homogeneous current flow (as illustrated in Fig. 1B) is observed up to a current density of je= +5 × 106A/cm2.Capturing the transformational dynamicsThe conversion from chiral stripe domains into magnetic skyrmions can be captured by decreasing the driving cur-rent, which slows down the transformational dynamics. Figure 3, A to D, shows the dynamics for a constant dccur-rent density of je= +6.4 × 104A/cm2at skyrmions in regular shaped device with a homogeneous current flow (as illustrated in Fig. 1B) is observed up to a current density of $j_{e}=+5\\times10^{6}\\mathrm{A/cm^{2}}$ . \n\n# Capturing the transformational dynamics \n\nThe conversion from chiral stripe domains into magnetic skyrmions can be captured by decreasing the driving current, which slows down the transformational dynamics Figure 3, A to D, shows the dynamics for a constant $d c$ current density of $j_{e}=+6.4\\times10^{4}~\\mathrm{A/cm^{2}}$ at $B_{\\perp}=+0.46$ mT. The original (disordered) labyrinthine domains on the left side squeeze to pass through the constriction (Fig. 3B). The stripe domains become unstable after passing through the constriction and are eventually converted into skyrmions on the right side of the device, as shown in Fig. 3, C and D. This can be seen in more detail in the MOKE movies (movies S1 and S2). Because the $x$ -component of the current results in an efficient motion of DWs, the skyrmion formation can happen away from the constriction. The synthetic skyrmions do not merge into stripe domains and in fact repel each other, indicating their topological protection as well as magnetostatic interactions. \n\nSome important features should be noticed. There exists a threshold current $j_{e-s k}=\\pm6\\times10^{4}~\\mathrm{A/cm^{2}}$ for persistently generating skyrmion bubbles from stripe domains for pulses μs. Above this current, the enhanced spin-orbit torques produce the instability of the DWs, which re-sults in the continuous formation of skyrmions. The present geometry for skyrmion generation is very efficient, resulting in the observed threshold current 3 orders of magnitude smaller than suggested by previous simulation studies (107-8A/cm2) in MnSi thin films with a bulk DMI where the driv-ing mechanism is the conventional spin transfer torque (30). Below this threshold for continuous skyrmion genera-tion, there is a threshold depinning current je–st= ±4.1 × 104A/cm2that produces a steady motion of stripe domains. The force (pressure) on the stripe from SOT at this current ex-ceeds the one required to maintain its shape. When je–st< je< je–sk, the stripe domains are moving smoothly through the constriction and prevail at both sides of devices, with just the occasional formation of skyrmions.Depinning and Motion of synthesized S= 1 skyrmionsThe magnetic skyrmion bubbles discussed so far have a top-ological charge given by the skyrmion number S= 1, as is determined by wrapping the unit magnetization vector over the sphere orbit torques produce the instability of the DWs, which re sults in the continuous formation of skyrmions. The present geometry for skyrmion generation is very efficient, resulting in the observed threshold current 3 orders of magnitude smaller than suggested by previous simulation studies $(10^{7-8}$ $\\mathrm{A/cm^{2}})$ in MnSi thin films with a bulk DMI where the driving mechanism is the conventional spin transfer torque (30). Below this threshold for continuous skyrmion generation, there is a threshold depinning current $j_{e-s t}=\\pm4.1\\times10^{4}$ $\\mathrm{A/cm^{2}}$ that produces a steady motion of stripe domains. The force (pressure) on the stripe from SOT at this current exceeds the one required to maintain its shape. When $j_{e-s t}
Samplesc-LPs [A]Density [g cm-3]Conductivity [S cm-1] Volumetric capacitance at 2 mV s-1 [F cm-3]Volumetric capacitance at 200 mV s-1 [Fcm-3]
TiCTx24.13.2123360162
Mixed TiCT/SWCNT26.93.0286300236
Sandwich-like TiCTx/SWCNT26.72.9385390280
Mixed TiCTx/MWCNT28.42.2189366236
Sandwich-like TiCTx/MWCNT28.52.7230321250
Sandwich-like TiCT/OLC-3.088397218
Sandwich-like TiCTx/rGO3.0350435320
\n\nTo evaluate the electrochemical performance of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{CNT}$ papers, they were tested as working electrodes in $1\\mathrm{~M~MgSO_{4}}$ aqueous electrolyte solution using a three-electrode asymmetrical setup with an $\\mathrm{\\sfAg/AgCl}$ reference electrode. $\\mathrm{Mg}\\mathrm{SO}_{4}$ is a benign and inexpensive neutral electrolyte that provides a broader voltage window compared to KOH. However, it has a rather low conductivity $(51~\\mathrm{mS~cm^{-1}},$ ) and a stronger decline in capacitance at high rates compared with KOH. 14 Thus, the improvement in the electrochemical and rate performances was anticipated to be more dependent on the electrode composition and its structure. \n\nThe cyclic voltammograms (CVs) of the composites and pristine $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene electrodes are shown in Figure 3a,b. From these results, it is clear that the shape of the CV profiles at $20~\\mathrm{mV}~\\mathrm{s}^{-1}$ for all $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{CNT}$ papers is more rectangular compared with that of the pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ paper electrodes, indicating improved capacitive behavior and decreased resistance. It is worth noting that for both MWCNT- and SWCNTcontaining composites, the electrochemical performance of the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{CNT}$ papers was slightly better than that of the randomly mixed ones. A similar trend was also observed in the rate performances of these electrode materials (Figure 3c and Figure S5, Supporting Information). All the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{CNT}$ papers exhibited significantly higher gravimetric capacitances and better rate performances than pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ papers; the best values were obtained from the sandwich-like papers. A capacitance of $150\\mathrm{~F~g^{-1}}$ was achieved for the $\\mathrm{Ti_{3}C_{2}T_{\\it x}/M W C N T}$ papers at $2~\\mathrm{mV~s^{-1}}$ Even at a rate of $200\\ \\mathrm{mV\\s^{-1}}$ a capacitance of $117\\mathrm{~F~g^{-1}}$ was measured, which is about $130\\%$ higher than that of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ paper at the same rate. \n\nAlthough the density of the electrodes decreased slightly with the incorporation of the CNTs (Table 1), higher volumetric capacitances were still obtained for the sandwichlike $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{CNT}$ electrodes, especially at high scan rates. At $2\\ \\mathrm{mV}\\ \\mathrm{s}^{-1}$ a maximum volumetric capacitance value of $390~\\mathrm{~F~}~\\mathrm{cm}^{-3}$ was achieved for the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}/$ SWCNT electrodes. At a scan rate as high as $200\\ \\mathrm{mV\\s^{-1}}$ the volumetric capacitances of the sandwich-like MWCNT- and SWCNT-containing papers were 250 and $280\\ \\mathrm{F\\cm^{-3}}$ respectively, which are $55\\%$ and $75\\%$ higher than those of the pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ electrodes. \n\nThese results demonstrate a significant improvement in volumetric capacitance and excellent rate performance of the sandwich-like $\\mathrm{Ti}_{3}\\mathrm C_{2}\\mathrm T_{x}/\\mathrm{CNT}$ electrodes. This improvement can be partially attributed to the fact that the electrical conductivities of the sandwich-like structures are better than those of both the pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ paper and the mixed assemblies (Table 1). For instance, at $385\\ \\mathrm{S\\cm^{-1}}$ the conductivity of the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\scriptscriptstyle x}/\\mathrm{SWCNT}$ paper was higher than the $123\\ \\mathrm{S\\cm^{-1}}$ of pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ or $286~\\mathrm{S~cm^{-1}}$ of the randomly mixed $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{SWCNT}$ papers. The same is true for the $\\mathrm{Ti_{3}C_{2}T_{\\it x}/M W C N T}$ composite paper. \n\nThe galvanostatic cycling performance for the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{CNT}$ papers is shown in Figure 3e,f. The sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{SWCNT}$ paper yielded a volumetric capacitance around $345\\ \\mathrm{F\\cm^{-3}}$ at $5\\mathrm{~A~g^{-1}}$ with no degradation after 10 000 cycles. For the sandwich-like $\\mathrm{Ti_{3}C_{2}T_{\\it x}/M W C N T}$ paper, a volumetric capacitance of $300\\ \\mathrm{F\\cm^{-3}}$ was achieved even at current densities as high as $10\\mathrm{Ag}^{-1}$ Moreover, this value increased even further to around $350~\\mathrm{F~cm}^{-3}$ after 10 000 cycles. This increase in capacitance can be attributed to the gradually improved accessibility of slit pores between MXene flakes during cycling. 14 Said otherwise, even in this architecture, there is room for further improvement. \n\nAs noted above, sandwich-like architectures – composed of 1D and 2D nanomaterials, typically fabricated using layerby-layer (LbL) assembly processes – have been demonstrated to generate excellent electrochemical performances. 19,20 The same is true herein; all the results show that the sandwichlike architecture results in electrode materials with high volumetric capacitances, good rate performances, and excellent cycling stabilities. The volumetric capacitances in the sandwich-like $\\mathrm{Ti}_{3}\\mathrm C_{2}\\mathrm T_{x}/\\mathrm{CNT}$ paper are significantly higher than those from carbon-based electrodes, such as activated carbons $(60-100\\mathrm{~F~}\\mathrm{cm}^{-3})$ , 4,21 carbide-derived carbons $(180\\ \\mathrm{F}\\ \\mathrm{cm}^{-3})$ , 22 graphene-based electrodes $({\\approx}260~\\mathrm{~F~}~\\mathrm{cm}^{-3})$ , 3 and graphene/ CNT nanocomposites $(165~\\mathrm{F~cm}^{-3})$ , 5 especially at high rates. LbL assembly is the most developed technique for sandwichlike assembly of nanomaterials. 19,20 Here, the method of alternating filtration of colloidal solutions was used, which does not require functionalization of the materials. Besides, films of several micrometers in thickness could be fabricated in tens of minutes — much faster than in the conventional LbL process. 23 Our method is thus simpler and faster, yet more effective, compared with LbL, 20,23,24 even though LbL deposition may lead to more controlled structures and provide further improvements in properties of MXene-based nanocomposites. \n\n![](images/fd7624430f722ca5562632a6e467603c172a17f1e6810dfc7ed36c58592b11bc.jpg) \nFigure 3. a,b) CV profiles of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ and $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ /CNT composite electrodes at a scan rate of $20\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . c) Gravimetric capacitances and, d) volumetric capacitances of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ and ${\\sf T i}_{3}{\\sf C}_{2}{\\sf T}_{x}/{\\sf C N T}$ electrodes at different scan rates. e,f) Cycling stability of sandwich-like ${\\ T i_{3}C_{2}T_{x}}/$ SWCNT electrode at $5\\mathsf{A}\\mathsf{g}^{-1}$ (e) and ${\\mathrm{Ti}_{3}}{\\mathrm C}_{2}{\\mathrm T}_{x}/$ MWCNT electrode at $\\overline{{10\\mathsf{A}\\mathsf{g}^{-1}}}$ (f). All the tests were conducted in a 1 M $\\mathsf{M g S O}_{4}$ aqueous solution. \n\nSpray deposition may also be used to produce similar films in large scale and with a larger thickness. 25 \n\nTo demonstrate the generality of our alternating filtration method to produce sandwich-like structures with impressive electrochemical energy-storage characteristics, sandwichlike assemblies of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes with 0D OLC and 2D rGO (Figure S6, Supporting Information) were prepared and tested. As shown in Figure 4a,b, both sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{OLC}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}/\\mathrm{r}\\mathrm{GO}$ papers, respectively, possessed more open structures compared with pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ papers. The same conclusion can be reached when the densities are compared (Table 1). The CV plots of these materials are shown in Figure 4c. Although a higher capacitance was achieved for the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}/\\mathrm{OLC}$ electrodes, the shapes of their CV profiles were comparable with those of their pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ counterparts (Figure 4c). This can be explained by the fact that the OLCs only served as spacers between $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes, yet their small quantity $(5~\\mathrm{wt\\%})$ was not enough to create a proper conductive network between the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ layers to improve the conductivity of the composite paper $(88\\ \\mathrm{~S~cm^{-1}}$ Table 1). Similar to CNTs, rGO can easily form a conductive network and enlarge the interlayer space between $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes simultaneously. As a result, the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}/\\mathrm{r}\\mathrm{GO}$ electrodes possessed a significantly higher capacitance and more rectangular-shaped CV profiles (Figure 4c,d). \n\n![](images/aa52b12cc9cb4ed9190000b0563000999bbde06d4eb990adfd64cabe0d7c92a0.jpg) \nFigure 4. a,b) SEM images showing the cross-section of the sandwich-like $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\boldsymbol{x}}/\\mathsf{O L C}$ (a) and ${\\sf T i}_{3}{\\sf C}_{2}\\sf T_{\\scriptscriptstyle X}/{\\sf r}{\\sf G}{\\sf O}$ (b) paper. c) CV profiles of the $\\mathrm{Ti}_{3}\\mathsf C_{2}\\mathsf T_{\\boldsymbol x}/\\mathsf r\\mathsf{G O}$ and ${\\sf T i}_{3}{\\sf C}_{2}{\\sf T}_{x}/{\\sf O L C}$ electrodes at a scan rate of $20\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . d) Volumetric capacitance of $\\Gamma\\mathrm{i}_{3}{\\mathsf C}_{2}\\mathsf T_{x},$ $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\boldsymbol{x}}/\\mathsf{O L C}$ and $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\boldsymbol{x}}/\\mathsf{r}\\mathsf{G O}$ electrodes at different scan rates. e) Cycling stability of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\mathrm{x}}/\\mathsf{r}\\mathsf{G}\\mathsf{O}$ paper at ${\\mathsf{10A}}{\\mathsf{g}}^{-1}.$ f) EIS results of the samples tested. All the tests were conducted using 1 M $\\mathsf{M g S O}_{4}$ aqueous solution. \n\nThese observations were further confirmed by the excellent rate performance of these materials shown in Figure 4d. Compared with pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{OLC}$ electrodes possessed slightly higher volumetric capacitances, without significant improvement in their rate performances. However, both the capacitive and rate performances were significantly improved for the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{r}\\mathrm{GO}$ papers. A high volumetric capacitance of $435\\ \\mathrm{F\\cm^{-3}}$ was obtained at $2\\ \\mathrm{mV}\\ \\mathrm{s}^{-1}$ When the scan rate was increased to $200\\ \\mathrm{mV\\\\mathrm{s^{-1}}}$ the capacitance dropped by $26\\%$ to $320\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ Furthermore, the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{r}\\mathrm{GO}$ electrodes also exhibited excellent cycling stability. At $10\\mathrm{~A~g^{-1}}$ their volumetric capacitance increased from 340 to $370\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ over 10 000 cycles. The comparison of the electrochemical impedance spectroscopy (EIS) results of the tested materials is shown in Figure 4f and Figure S7 (Supporting Information). It further confirms the significantly reduced resistivity for the sandwich-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}/$ nanocarbon composites compared with that of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ papers, with the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}/\\mathrm{CNT}$ composites showing the highest conductivity. \n\nIn summary, we have developed a simple, alternating filtration method to achieve the sandwich-like assembly of MXenes and CNTs from aqueous suspensions. The resulting MXene/ CNT papers are free-standing and highly flexible. When employed as electrode materials in supercapacitors, the sandwich-like MXene/CNT papers exhibited significantly higher volumetric capacitances and excellent rate performances compared with pure MXene and randomly mixed MXene/CNT papers. A high volumetric capacitance of $390\\ \\mathrm{F}\\ \\mathrm{cm}^{-3}$ was measured for the sandwich-like MXene/SWCNT papers at a scan rate of $2\\ \\mathrm{mV}\\ \\mathrm{s}^{-1}$ At $5\\mathrm{~A~g^{-1}}$ the sandwich-like MXene/CNT paper exhibited a volumetric capacitance around $350\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ with no degradation after 10 000 cycles. The performances reported here can certainly be improved further by optimizing the structure of the composites, such as the MXene compositions, the MXene to CNT mass ratios, and the thicknesses of MXene and CNT layers. \n\nThe properties of these sandwich-like MXene/CNT papers, such as good electrical conductivities, high surface areas accessible to ions and mechanical robustness, suggest their promising applications in other electrochemical energy storage and generation devices, including Li-ion batteries and fuel cells as well as desalination systems and electrochemical actuators. Furthermore, the strategy proposed in this work was also applied for 0D OLCs and 2D rGO, leading to the formation of flexible and free-standing sandwich-like MXene/OLC and MXene/rGO papers also with impressive electrochemical performance. The sandwich-like MXene/rGO papers yielded a high volumetric capacitance of $435~\\mathrm{~F~}\\mathrm{cm}^{-3}$ and exhibited excellent cycling stability. \n\n# Experimental Section \n\nMaterials Preparation: The $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ MAX phase was prepared by mixing commercial ${\\mathsf{T i}}_{2}{\\mathsf{A l C}}$ powders (Kanthal, Sweden) with TiC in a 1:1 molar ratio by ball milling for $18\\mathrm{~h~}$ . The mixture was then heated to ${1350^{\\circ}C}$ at $5~{}^{\\circ}{\\mathsf{C}}{\\mathsf{m i n}}^{-1}$ in a tube furnace under flowing Ar. The resulting, lightly sintered, brick was ground with a TiN-coated milling bit and sieved through a 400 mesh sieve to produce powder in which the particle size was $<38~\\upmu\\mathrm{m}$ . \n\nMultilayer $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ particles were prepared by treatment in $50\\ \\mathrm{wt\\%}$ aqueous HF solution (Fisher Scientific, Fair Lawn, NJ, USA) to extract Al from the $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ particles. 9 The colloidal solution of delaminated $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ dispersion was prepared by the sonication of dimethyl sulfoxide (DMSO)-intercalated multilayer $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ powders in DI water, followed by centrifuging at $3500~\\mathsf{r p m}$ for $\\textsf{l h}$ and collecting the supernatant. 12 The concentration of $\\mathrm{Ti}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ flakes in the colloidal solution was measured to be $0.68~\\mathsf{m g}~\\mathsf{m L}^{-1}$ . \n\nThe MWCNTs were prepared through a floating catalyst chemical vapor deposition (CVD) method. 26 The SWCNTs were prepared by the CVD of methane on $\\mathsf{F e/M g O}$ catalysts, and purified by HCl washing. 27 OLCs were made by annealing a nanodiamond precursor (UD90 grade, SP3 Diamond Technologies, USA) at $1800^{\\circ}\\mathsf{C}$ in a vacuum of ${\\approx}70^{-6}$ Torr for $3h$ in a custom-made vacuum furnace (Solar Atmospheres, USA). 28 The rGO was prepared by the hydrazine reduction of graphene oxide (GO) made by a modified Hummers method. 29 In a typical run, $0.5~\\mathsf{m L}$ of hydrazine hydrate was added into a $50~\\mathsf{m L}$ of GO aqueous solution. The latter was refluxed at ${\\mathsf{100}}\\ {\\mathsf{\\circ}}_{\\mathsf{C}}$ for $12\\ h$ to obtain a rGO suspension. The MWCNTs and SWCNTs dispersions were prepared by sonication in deionized water for $30~\\mathsf{m i n}$ with the assistance of sodium dodecylsulphate $(99.5\\%$ , Fisher Scientific, Fair Lawn, NJ, USA). The dispersions of OLCs and rGO were prepared by directly sonicating the materials in deionized water for $30~\\mathrm{rmin}$ . The concentration of these nanocarbons in their dispersions was controlled at $0.036~\\mathsf{m g}~\\mathsf{m L}^{-1}$ . The details for the material preparation are available in the related references. Sandwich-Like Assembly of MXene/CNT Papers: Sandwich-like MXene/MWCNT papers were prepared using an alternating filtration method. Specifically, a 1 mL $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ dispersion was filtered through a polypropylene membrane (3501 Coated PP, Celgard LLC, Charlotte, NC) to yield a thin $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ layer. Then, $7m L$ of the MWCNT dispersion was filtered on the top of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ layer. After that, another $1m L$ of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ dispersion was filtered on the top of MWCNT layer to form a sandwich-like structure. This alternate filtration was repeated several times to yield composite films composed of 6–10 alternating $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ and MWCNTs layers. The composite film was then dried in air at room temperature and peeled off from the polypropylene membrane, yielding free-standing sandwich-like MXene/MWCNT paper. The sandwich-like MXene/SWCNT, MXene/OLC, and MXene/rGO papers were prepared through a similar process. \n\nStructural Characterizations: The morphology of the samples was characterized using a scanning electron microscope (SEM) (Zeiss Supra 50VP, Germany) and a transmission electron microscope (TEM) (JEOL JEM-2100, Japan) using an accelerating voltage of 200 kV. The TEM samples were prepared by dropping several drops of the sample dispersion onto a copper grid and dried in air. \n\nThe electrical conductivities of the samples were measured using a four-point probe (ResTest v1, Jandel Engineering Ltd., Bedfordshire, UK) with a probe distance of $\\textsf{l m m}$ . The XRD patterns were recorded by a powder diffractometer (Rigaku Smart Lab, USA) with $\\mathsf{C u}\\ \\mathsf{K}_{\\alpha}$ radiation at a step rate of $0.2^{\\circ}\\mathsf{m i n}^{-1}$ and $0.5\\ s$ dwelling time. \n\nElectrochemical Measurements: The electrochemical measurements were performed in three-electrode Swagelok cells, where the MXenebased papers served directly as the working electrodes, over-capacitive activated carbon films were used as the counter electrodes, and $\\mathsf{A g/A g C l}$ in $3\\mathrm{~M~}\\mathsf{K C l}$ served as the reference electrode. Polypropylene membranes were employed as the separators, and a 1 M ${\\sf M g S O_{4}}$ aqueous solution was used as the electrolyte. CV, galvanostatic cycling, and EIS were performed using a VMP3 potentiostat (Biologic, France). The CVs were recorded using scan rates ranging from 2 to $200\\ m\\vee\\ s^{-1}$ . The specific \n\n# www.MaterialsViews.com \n\ncapacitances were calculated by integrating the discharge portions of the CVs. Galvanostatic cycling was performed between the potential limits of $^{-0.8}$ to $0.1~\\mathrm{\\lor}$ versus $\\sf A g/A g C l$ , and the corresponding capacitances were calculated from the slopes of the discharge curve. The EISs were performed at OCP, with a $\\mathsf{10}\\mathsf{m}\\mathsf{V}$ amplitude, and frequencies that ranged from $10~\\mathsf{m}\\mathsf{H}z$ to $200~\\mathsf{k H z}$ . \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nM.-Q. Zhao and C. E. Ren contributed equally to this work. Film preparation by M.-Q.Z. and work on carbon onions (K.L.V.A.) were supported as part of the Fluid Interface Reactions, Structures and Transport (FIRST) Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. Z.L., C.E.R. and C.Z. were supported by the Chinese Scholarship Council (CSC). XRD, SEM, and TEM investigations were performed at the Centralized Research Facilities (CRF) at Drexel University. \n\nReceived: September 8, 2014 Revised: October 10, 2014 Published online: \n\n[1] a) P. Simon, Y. Gogotsi, B. Dunn, Science 2014, 343, 1210; b) P. Simon, Y. Gogotsi, Nat. Mater. 2008, 7, 845. \n[2] Y. Gogotsi, P. Simon, Science 2011, 334, 917. \n[3] X. Yang, C. Cheng, Y. Wang, L. Qiu, D. Li, Science 2013, 341, 534. \n[4] M. Ghaffari, Y. Zhou, H. Xu, M. Lin, T. Y. Kim, R. S. Ruoff, Q. M. Zhang, Adv. Mater. 2013, 25, 4879. \n[5] N. Jung, S. Kwon, D. Lee, D.-M. Yoon, Y. M. Park, A. Benayad, J.-Y. Choi, J. S. Park, Adv. Mater. 2013, 25, 6854. \n[6] J. P. Zheng, P. J. Cygan, T. R. Jow, J. Electrochem. Soc. 1995, 142, 2699. \n[7] M. Ghidiu, M. Naguib, C. Shi, O. Mashtalir, L. M. Pan, B. Zhang, J. Yang, Y. Gogotsi, S. J. L. Billinge, M. W. Barsoum, Chem. Commun. 2014, 50, 9517. \n[8] M. Naguib, J. Halim, J. Lu, K. M. Cook, L. Hultman, Y. Gogotsi, M. W. Barsoum, J. Am. Chem. Soc. 2013, 135, 15966. \n[9] M. Naguib, M. Kurtoglu, V. Presser, J. Lu, J. Niu, M. Heon, L. Hultman, Y. Gogotsi, M. W. Barsoum, Adv. Mater. 2011, 23, 4248. \n[10] M. Naguib, O. Mashtalir, J. Carle, V. Presser, J. Lu, L. Hultman, Y. Gogotsi, M. W. Barsoum, ACS Nano 2012, 6, 1322. \n[11] M. Naguib, V. N. Mochalin, M. W. Barsoum, Y. Gogotsi, Adv. Mater. 2014, 26, 992. \n[12] O. Mashtalir, M. Naguib, V. N. Mochalin, Y. Dall’Agnese, M. Heon, M. W. Barsoum, Y. Gogotsi, Nat. Commun. 2013, 4, 1716. \n[13] Q. Tang, Z. Zhou, P. Shen, J. Am. Chem. Soc. 2012, 134, 16909. \n[14] M. R. Lukatskaya, O. Mashtalir, C. E. Ren, Y. Dall’Agnese, P. Rozier, P. L. Taberna, M. Naguib, P. Simon, M. W. Barsoum, Y. Gogotsi, Science 2013, 341, 1502. \n[15] a) S. Liu, J. Xie, C. Fang, G. Cao, T. Zhu, X. Zhao, J. Mater. Chem. 2012, 22, 19738; b) Q. Qu, S. Yang, X. Feng, Adv. Mater. 2011, 23, 5574. \n[16] a) Z. Fan, J. Yan, L. Zhi, Q. Zhang, T. Wei, J. Feng, M. Zhang, W. Qian, F. Wei, Adv. Mater. 2010, 22, 3723; b) R. Lv, E. Cruz-Silva, M. Terrones, ACS Nano 2014, 8, 4061; c) M.-Q. Zhao, X.-F. Liu, Q. Zhang, G.- -Q. Huang, W. Zhu, F. Wei, ACS Nano 2012, 6, 10759; Tang, Q. Zhang, M.-Q. Zhao, J.-Q. Huang, X.-B. Cheng, G.- H.-J. Peng, F. Wei, Adv. Mater. 2014, 26, 6100; e)M.-Q. Zhao, Q. Zhang, J.-Q. Huang, G.-L. Tian, J.-Q. Nie, H.-J. Peng, F. Wei, Nat. Commun. 2014, 5, 3410. \n[17] a)Y. P. Wu, T. F. Zhang, F. Zhang, Y. Wang, Y. F. Ma, Y. Huang, Y. Y. Liu, Y. S. CHen, Nano Energy 2012, 1, 820; b) J. Zhu, H. N. Zhang, N. A. Kotov, ACS Nano 2013, 7, 4818. \n[18] a) S. Yang, X. Feng, K. Müllen, Adv. Mater. 2011, 23, 3575; b)G. Zhou, S. Pei, L. Li, D.-W. Wang, S. Wang, K. Huang, L.-C. Yin, F. Li, H.-M. Cheng, Adv. Mater. 2014, 26, 625; c) R. Chen, T. Zhao, J. Lu, F. Wu, L. Li, J. Chen, G. Tan, Y. Ye, K. Amine, Nano Lett. 2013, 13, 4642; d) Y. Cao, X. Li, I. A. Aksay, J. Lemmon, Z. Nie, Z. Yang, J. Liu, Phys. Chem. Chem. Phys. 2011, 13, 7660. \n[19] H. R. Byon, B. M. Gallant, S. W. Lee, Y. Shao-Horn, Adv. Funct. Mater. 2013, 23, 1037. \n[20] a)H. R. Byon, S. W. Lee, S. Chen, P. T. Hammond, Y. Shao-Horn, Carbon 2011, 49, 457; b)M. Yang, Y. Hou, N. A. Kotov, Nano Today 2012, 7, 430. \n[21] a)S. Murali, N. Quarles, L. L. Zhang, J. R. Potts, Z. Tan, Y. Lu, Y. Zhu, R. S. Ruoff, Nano Energy 2013, 2, 764; b)Y. Zhu, S. Murali, M. D. Stoller, K. J. Ganesh, W. Cai, P. J. Ferreira, A. Pirkle, R. M. Wallace, K. A. Cychosz, M. Thommes, D. Su, E. A. Stach, R. S. Ruoff, Science 2011, 332, 1537. \n[22] M. Heon, S. Lofland, J. Applegate, R. Nolte, E. Cortes, J. D. Hettinger, P.-L. Taberna, P. Simon, P. Huang, M. Brunet, Y. Gogotsi, Energy Environ. Sci. 2011, 4, 135–138. \n[23] M. N. Hyder, R. Kavian, Z. Sultana, K. Saetia, P.-Y. Chen, S. W. Lee, Y. Shao-Horn, P. T. Hammond, Chem. Mater. 2014, 26, 5310. \n[24] a)K. Ariga, J. P. Hill, Q. M. Ji, Phys. Chem. Chem. Phys. 2007, 9, 2319; b)C. Y. Jiang, V. V. Tsukruk, Adv. Mater. 2006, 18, 829; c) P. T. Hammond, AIChE J. 2011, 57, 2928. \n[25] a)K. C. Krogman, J. L. Lowery, N. S. Zacharia, G. C. Rutledge, P. T. Hammond, Nat. Mater. 2009, 8, 512; b)A. Izquierdo, S. S. Ono, J. C. Voegel, P. Schaaf, G. Decher, Langmuir 2005, 21, 7558. \n[26] Q. Zhang, J.-Q. Huang, M.-Q. Zhao, W.-Z. Qian, Y. Wang, F. Wei, Carbon 2008, 46, 1152. \n[27] a)M.-Q. Zhao, Q. Zhang, X.-L. Jia, J.-Q. Huang, Y.-H. Zhang, F. Wei, Adv. Funct. Mater. 2010, 20, 677; b)Q. Zhang, M. Zhao, J. Huang, W. Qian, F. Wei, Chin. J. Catal. 2008, 29, 1138. \n[28] K. L. Van Aken, J. K. McDonough, S. Li, G. Feng, S. M. Chathoth, E. Mamontov, P. F. Fulvio, P. T. Cummings, S. Dai, Y. Gogotsi, J. Phys.: Condens. Matter 2014, 26, 284104. \n[29] H. Hu, Z. Zhao, Q. Zhou, Y. Gogotsi, J. Qiu, Carbon 2012, 50, 3267. " + }, + { + "id": "10.1016_j.actamat.2015.06.025", + "DOI": "10.1016/j.actamat.2015.06.025", + "DOI Link": "http://dx.doi.org/10.1016/j.actamat.2015.06.025", + "Relative Dir Path": "mds/10.1016_j.actamat.2015.06.025", + "Article Title": "Mechanical properties, microstructure and thermal stability of a nullocrystalline CoCrFeMnNi high-entropy alloy after severe plastic deformation", + "Authors": "Schuh, B; Mendez-Martin, F; Völker, B; George, EP; Clemens, H; Pippan, R; Hohenwarter, A", + "Source Title": "ACTA MATERIALIA", + "Abstract": "An equiatomic CoCrFeMnNi high-entropy alloy (HEA), produced by arc melting and drop casting, was subjected to severe plastic deformation (SPD) using high-pressure torsion. This process induced substantial grain refinement in the coarse-grained casting leading to a grain size of approximately 50 nm. As a result, strength increased significantly to 1950 MPa, and hardness to similar to 520 MV. Analyses using transmission electron microscopy (TEM) and 3-dimensional atom probe tomography (3D-APT) showed that, after SPD, the alloy remained a true single-phase solid solution down to the atomic scale. Subsequent investigations characterized the evolution of mechanical properties and microstructure of this nullocrystalline HEA upon annealing. Isochronal (for 1 h) and isothermal heat treatments were performed followed by microhardness and tensile tests. The isochronal anneals led to a marked hardness increase with a maximum hardness of similar to 630 HV at about 450 degrees C before softening set in at higher temperatures. The isothermal anneals, performed at this peak hardness temperature, revealed an additional hardness rise to a maximum of about 910 MV after 100 h. To clarify this unexpected annealing response, comprehensive microstructural analyses were performed using TEM and 3D-APT. New nullo-scale phases were observed to form in the originally single-phase HEA. After times as short as 5 min at 450 degrees C, a NiMn phase and Cr-rich phase formed. With increasing annealing time, their volume fractions increased and a third phase, FeCo, also formed. It appears that the surfeit of grain boundaries in the nullocrystalline HEA offer many fast diffusion pathways and nucleation sites to facilitate this phase decomposition. The hardness increase, especially for the longer annealing times, can be attributed to these nullo-scaled phases embedded in the HEA matrix. The present results give new valuable insights into the phase stability of single-phase high-entropy alloys as well as the mechanisms controlling the mechanical properties of nullostructured multiphase composites. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd.", + "Times Cited, WoS Core": 1065, + "Times Cited, All Databases": 1124, + "Publication Year": 2015, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000358459900024", + "Markdown": "# Mechanical properties, microstructure and thermal stability of a nanocrystalline CoCrFeMnNi high-entropy alloy after severe plastic deformation \n\nB. Schuh a, F. Mendez-Martin b, B. Völker a, E.P. George c,d,1, H. Clemens b, R. Pippan e, A. Hohenwarter a,⇑ a Department of Materials Physics, Montanuniversität Leoben, 8700 Leoben, Austria b Department of Physical Metallurgy and Materials Testing, Montanuniversität Leoben, 8700 Leoben, Austria c Formerly at the Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA d Materials Science and Engineering Department, University of Tennessee, Knoxville, TN 37996, USA e Erich Schmid Institute of Materials Science, Austrian Academy of Sciences, 8700 Leoben, Austria \n\n# a r t i c l e i n f o \n\nArticle history: Received 5 May 2015 Revised 2 June 2015 Accepted 2 June 2015 \n\nKeywords: \nHigh-entropy alloys \nSevere plastic deformation \nCompositionally complex alloys \n3 dimensional atom probe tomography \nMicrostructure \n\n# a b s t r a c t \n\nAn equiatomic CoCrFeMnNi high-entropy alloy (HEA), produced by arc melting and drop casting, was subjected to severe plastic deformation (SPD) using high-pressure torsion. This process induced substantial grain refinement in the coarse-grained casting leading to a grain size of approximately $50\\mathrm{nm}$ As a result, strength increased significantly to $1950\\mathrm{MPa}$ , and hardness to ${\\sim}520\\mathrm{HV}$ . Analyses using transmission electron microscopy (TEM) and 3-dimensional atom probe tomography (3D-APT) showed that, after SPD, the alloy remained a true single-phase solid solution down to the atomic scale. Subsequent investigations characterized the evolution of mechanical properties and microstructure of this nanocrystalline HEA upon annealing. Isochronal (for $^{\\textrm{1h}}$ ) and isothermal heat treatments were performed followed by microhardness and tensile tests. The isochronal anneals led to a marked hardness increase with a maximum hardness of ${\\sim}630\\mathrm{HV}$ at about $450^{\\circ}\\mathsf C$ before softening set in at higher temperatures. The isothermal anneals, performed at this peak hardness temperature, revealed an additional hardness rise to a maximum of about ${\\mathfrak{g}}10{\\mathrm{HV}}$ after $100\\mathrm{h}$ . To clarify this unexpected annealing response, comprehensive microstructural analyses were performed using TEM and 3D-APT. New nano-scale phases were observed to form in the originally single-phase HEA. After times as short as $5\\mathrm{min}$ at $450^{\\circ}\\mathsf C,$ a NiMn phase and Cr-rich phase formed. With increasing annealing time, their volume fractions increased and a third phase, FeCo, also formed. It appears that the surfeit of grain boundaries in the nanocrystalline HEA offer many fast diffusion pathways and nucleation sites to facilitate this phase decomposition. The hardness increase, especially for the longer annealing times, can be attributed to these nano-scaled phases embedded in the HEA matrix. The present results give new valuable insights into the phase stability of single-phase high-entropy alloys as well as the mechanisms controlling the mechanical properties of nanostructured multiphase composites. \n\n$\\circledcirc$ 2015 Acta Materialia Inc. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). \n\n# 1. Introduction \n\nCompositionally complex alloys consisting of five or more principal elements, frequently referred to as high-entropy alloys (HEAs), have received considerable attention in the material science community in the last few years [1–3]. In the huge pool of alloy systems that have been investigated, only a minority of alloys crystallize as pure single-phase solid solutions e.g. [4], which can be a desirable feature for achieving certain physical and mechanical properties. An example of such a single-phase HEA is the equiatomic CoCrFeMnNi alloy first reported by Cantor et al. [5]. Even though the elements in this five-element alloy possess different crystal structures, it crystallizes as a single-phase face-centered cubic (fcc) solid solution [6]. Its mechanical properties have been recently studied [7–16]. Among its interesting features is the observation that the alloy shows a strong increase of yield strength with decreasing temperature [7,9], especially in the cryogenic range, which is a characteristic of pure bodycentered cubic (bcc) metals and some binary fcc alloys but not pure fcc metals. The mechanism responsible for this phenomenon is still under discussion. Surprisingly, along with the increase of strength, ductility also improves significantly at low temperatures [7,9], which was attributed to deformation induced nano-twinning [7] and the resulting increase of the work hardening rate which postpones necking instability [7,9]. In addition, the fracture resistance of this alloy has been found to be unaffected (or even rises slightly by some measures) at cryogenic temperatures [16]. Comple mentary to the exceptional properties at low temperatures, the microstructure has been reported to be thermally stable at elevated temperatures [6]. \n\nA common method for the production of wrought fcc HEAs for mechanical property characterization involves melting and casting of the pure elements followed by rolling and recrystallization [7]. With this processing route, the smallest achievable grain size, which is preferably small for optimal mechanical properties, is determined by the degree of deformation during rolling. Because of this limitation of standard thermomechanical treatments, the entire body of research on single-phase HEAs has so far been on materials with grain sizes in the micrometer range or larger. A well-established approach to achieve significantly smaller grain sizes, is provided by methods of severe plastic deformation (SPD) [17–19]. These methods allow deformations far beyond those possible by cold rolling and can reduce grain sizes down to the ultrafine-grained (UFG) and even nanocrystalline (NC) regimes depending on various physical and technical factors [20]. In general, they impose no technical limitations on the processable alloys, which makes SPD attractive for the optimization of the microstructure and properties of HEAs. \n\nA drawback of many NC materials is that they lack sufficient ductility [21,22]. Therefore, heat treatments after deformation are usually required to obtain a good balance of properties by decreasing strength and increasing ductility. Based on these considerations, SPD of HEAs demands not only microstructural examination of grain refinement during processing but also in-depth investigation of thermal stability in terms of mechanical properties and microstructure upon annealing. These investigations can form the basis for a better understanding of the structure–property relationships of HEAs in the grain size regime well below $1\\upmu\\mathrm{m}$ . \n\nThe focus of the present study was the CoCrFeMnNi HEA discussed above. It was deformed by high-pressure torsion (HPT), which is a SPD process with some remarkable advantages. It allows the highest hydrostatic pressures among all SPD techniques [23], which is important for crack-free processing of difficult to deform metals, or alloys exhibiting a high hardening potential during deformation. The annealed microstructural states were mechanically characterized by performing micro-hardness and tensile tests and complemented with transmission electron microscopy (TEM) analyses. To link mechanical changes with the microstructure, 3-dimensional atom probe tomography (3D-APT) was used, which is capable of visualizing re-distributions of elements and the formation of new phases on the atomic scale. \n\n# 2. Experimental \n\nFor the synthesis of the CoCrFeMnNi HEA, high-purity elements (at least $99.9\\mathrm{wt\\%}$ were arc melted and drop cast under pure Ar atmosphere into cylindrical copper molds $25.4\\mathrm{mm}$ in diameter and $127\\mathrm{mm}$ long. The drop-cast ingots were encapsulated, evacuated in quartz ampules and homogenized for $48\\mathrm{h}$ at $1200^{\\circ}\\mathsf C.$ Further details of the melting and casting process can be found elsewhere [7]. Afterwards the material was subjected to high pressure torsion (HPT). An introduction to this processing technique is given in [24]. For the HPT process, disks with a diameter of $8\\mathrm{mm}$ and an initial thickness of $0.8\\mathrm{mm}$ were cut from the cast and homogenized ingot. During HPT, the shear strain, c, along the radius, $r,$ is given by: \n\n$$\n\\gamma=\\frac{2\\pi r}{t}n,\n$$ \n\nwhere $t$ is the thickness of the disk and $n$ the number of rotations. The process was conducted at room temperature at a nominal pressure of $7.8\\mathsf{G P a}$ and a rotational speed of 0.2 rotations/min for various values of n. Specimens subjected to 5 rotations were used for isochronal heat treatments for $^{1\\mathrm{h}}$ and isothermal heat treatments at $450^{\\circ}\\mathsf C$ . \n\nVickers micro-hardness measurements were conducted with a microhardness tester from Buehler (Micromet 5104) at a load of 1000 gf and dwell times of $15s.$ . Tensile tests were performed with dog-bone specimens having a gage length of $2.5\\mathrm{mm}$ and a square cross-section of $\\sim0.3\\ \\mathrm{mm}^{2}$ . The tests were conducted at room temperature on a tensile testing machine from Kammrath and Weiss with a crosshead speed of $2.5\\upmu\\mathrm{m}/s$ . \n\nMicrostructural characterization and fractographic studies were carried out with a scanning electron microscope (SEM, Zeiss 1525). Standard bright-field images and diffraction patterns were obtained using a transmission electron microscope from Philips (CM12) and STEM images were recorded using an image-side $C_{s}$ -corrected JEOL 2100F. For TEM specimen preparation, conventional electropolishing methods or Ar-ion milling were employed depending on the microstructure. Further in-depth microstructure investigations were made with 3 dimensional atom probe tomography (3D-APT) using the LEAP 3000X HR. The APT specimens were prepared by cutting rod-like specimens from selected microstructural states followed by electropolishing to pre-sharpen the tips. In addition, ion milling with a FEI Versa 3D DualBeam (FIB/SEM) workstation was employed to get the final shape of the specimens. The measurements were performed in voltage mode with a pulse fraction of $20\\%$ , a pulse rate of $200\\mathrm{kHz}$ and a temperature of $60\\mathrm{K}.$ . The reconstructions were performed with the visualization and analysis software IVAS, version 3.6.8 from Cameca. \n\n# 3. Results \n\n# 3.1. Mechanical and microstructural changes during SPD \n\nIn Fig. 1a the hardness evolution along the disk radius as a function of the number of rotations is presented. The data from 4 equivalent radial positions, see inset in Fig. 1b, were averaged and their standard deviations used as an indicator of the error. The undeformed specimen has a hardness of about $160\\mathrm{HV}.$ Pre-loading of the specimen at a nominal pressure of $7.8\\mathsf{G P a}$ (denoted as 0 rotations) produces a marked hardness increase in the outer edge region. There the degree of deformation is somewhat higher compared to the center of the disk due to the pressure distribution in the tool. With increasing number of rotations the hardness level further increases, which can be linked to severe grain fragmentation. After just $1/4$ rotation the hardness begins to saturate at the edge. After 5 rotations a broad plateau in hardness is reached, which begins at a radius of about $1\\mathrm{mm}$ from the center and extends to the outer edge of the disk. To take advantage of this pronounced plateau, only disks deformed to 5 rotations were used for all subsequent investigations. The plateau in hardness, with an average value of about ${520}\\mathrm{HV}$ , indicates a saturation in grain refinement. The minimum grain size in this region is reached after a characteristic strain that depends on the material and various physical factors [20]. The saturation behavior is also observed in Fig. 1b, where the hardness changes are plotted against the shear strain, c, according to Eq. (1) and a plateau occurs at shear strains higher than 50. \n\n![](images/d206578d187a34029395d7dd03404aeb019d90667438f1123127905e1cf764da.jpg) \nFig. 1. (a) Hardness variation along the radius of the HPT disks as a function of the number of rotations. (b) Hardness evolution as a function of applied shear strain. Inset image in (b) illustrates the locations of hardness indents spaced $0.5\\mathrm{mm}$ apart on the HPT disk. The error bars (±standard deviation) in (a) and (b) are only visible when they are larger than the symbol size. \n\nSince the saturated SPD state was the initial material for all further investigations, a short overview is first given of the most significant changes in the microstructure during SPD of the cast and homogenized alloy. Important stages in the breakdown of the microstructure are summarized using back-scattered electron images taken in the SEM along the axial viewing direction, Fig. 2a. Fig. 2b shows the undeformed initial cast and homogenized structure with grains that are several hundred micrometers in diameter. In Fig. 2c the central region of a HPT disk after $1/8$ of a rotation is presented. The vertical margins of the image correspond to a shear strain, $\\gamma$ , of ${\\sim}0.5$ , which is very small compared to the total imposed strain. Nevertheless, large changes in the local orientation of the grains are qualitatively visible through strong contrast changes. In addition, even after this small degree of deformation the formation of mechanical twins can be observed. With further deformation, $\\gamma\\sim2.4$ , Fig. 2d, the twin density increases and new twin variants are formed, which intersect each other to form micron-sized blocks of twin lamellae. Due to the large imposed rotational deformation the twin bundles also become bent. At higher strains, $\\gamma\\sim4.0$ , Fig. 2e, the clear twin lamellae become gradually diffuse in this imaging mode and the severely deformed structure eventually transforms into an apparently homogenous NC microstructure at a shear strain $\\gamma\\sim50$ , see Fig. 2f. \n\nA major part of the deformation leading to grain refinement at room temperature consists of deformation twinning. In previous investigations of the plasticity of this CoCrFeMnNi HEA using tensile tests, deformation twinning was mainly observed at liquid nitrogen temperature [7] and at both room and liquid nitrogen temperatures during plane-strain multi-pass rolling [8]. The relatively early onset of room-temperature twinning in this study can be explained by the very coarse grain size of our starting material, which is expected to have a higher propensity for twinning than finer grained metals [25]. Similar observations were made regarding twinning being the prevalent deformation mode during grain refinement with SPD in austenitic steels [26]. Deformation twins were also frequently observed in CuZn alloys [27], which are examples of low stacking fault energy materials. \n\n# 3.2. Saturation microstructure \n\nThe saturation microstructure in Fig. 2f was further investigated by TEM along the axial direction as shown in Fig. 3a. In general, the images for this microstructural state tend to show unclear (blurry) structures in which the boundaries are ill defined and difficult to discern. This is often associated with internal stresses or strains related to the non-equilibrium nature of grain boundaries in severely plastically deformed materials [28]. Only several grains could be clearly discriminated after inspection of a large number of images on the basis of which an average grain diameter of ${\\sim}50\\mathrm{nm}$ was estimated. Twins were seldom found, as one isolated example in the center of the image illustrates. The diffraction pattern (Fig. 3b) shows Debye rings with a sequence that is consistent with a single-phase fcc structure for the severely plastically deformed HEA. A calculation of the lattice constant yields a value of ${\\sim}3.6\\mathring{\\mathsf{A}}$ which is in good accordance with measurements using X-ray diffraction for the coarse-grained state [29]. \n\nTo illustrate the chemical composition and homogeneity of the structure, 3D-APT results are presented in Fig. 4a. These single-element images, as well as the chemical compositions along the long axis of the specimen, Fig. 4b, verify the single-phase solid solution character of the material with no observable inhomogeneities or clusters and a somewhat decreased Mn level compared to the nominal equiatomic composition. The discrepancy in the Mn level compared to the nominal composition might be a consequence of the high vapor pressure of Mn leading to evaporation of the element during the casting and homogenization process [30]. Based on the grain size estimated above from the TEM analysis, the volume analyzed by 3D-APT should contain several grain boundaries. Since they do not seem to be decorated by any specific species they cannot be visualized by the 3D-APT technique. This also means that no grain boundary segregants are present in the SPD state. \n\n# 3.3. Hardness evolution during annealing experiments \n\nIn Fig. 5a, the results of the isochronal heat treatments (1 h) are shown. Beginning from the hardness of the SPD state $(\\sim520\\mathrm{HV})$ , a clear rise in hardness occurs with a maximum hardness of $630\\mathrm{HV}$ at a temperature of $450^{\\circ}\\mathsf C.$ At higher annealing temperatures the hardness decreases. To shed light on the kinetics of hardness evolution, isothermal heat treatments were also performed for times up to $200\\mathrm{h}$ at the annealing temperature where hardness was found to be a maximum in the isochronal anneals. The results, shown in Fig. 5b, indicate a continuous increase in hardness from the SPD state to a peak hardness of ${\\sim}910\\mathrm{HV}$ after an annealing time of $100\\mathrm{h}$ before the hardness starts to decrease again. \n\n# 3.4. Microstructural analyses of annealed specimens \n\nTo correlate the hardness changes with the microstructure, 3D-APT and TEM analyses were performed on specimens annealed at $450^{\\circ}\\mathsf C$ for selected times. The chosen temperature corresponds to that at which peak hardness was observed in the isochronal experiments. In Fig. 6 the 3D-APT results are presented showing the presence of new phases besides the solid solution phase of the base HEA (Fig. 4a). These new phases will be denominated by their main constituents in the following discussion. After very short anneals $5\\mathrm{min}\\cdot$ , a phase rich in Mn and Ni and a second phase rich in Cr were found embedded in the HE phase, see Fig. 6a. The estimated compositions of these phases within the shown iso-concentration surfaces are summarized in Table 1. After a 1-h anneal, Fig. 6b, the same phases are present as after the 5-min anneal but their volume fractions increased markedly, as shown in Table 1. After $15\\mathrm{h}$ the hardness increased considerably, see Fig. 5b. The corresponding 3D-APT reconstruction, Fig. 6c, reveals the formation of an additional phase consisting mainly of Fe and Co and a further increase in the volume fractions of the first two phases. More or less independent of the annealing time the composition of the MnNi phase remains roughly constant, whereas the Cr content in the Cr phase increases with increasing annealing time. Even though the hardness continues to increase after $15\\mathrm{h}$ no further 3D-APT measurements were performed on these samples due to their high intrinsic brittleness which resulted in failure during several preparation attempts. \n\n![](images/584d635c1fcc7ae6c352d3003e2c380ce171e1aa4db7c454dcfb3a3859a6dbb4.jpg) \nFig. 2. Microstructural evolution in HPT disks investigated with SEM using back-scattered electron contrast. (a) Schematic diagram showing the principal viewing direction for SEM and TEM analyses. (b) Undeformed coarse-grained initial structure of the cast alloy. (c) Deformation structure of the HPT disk after $1/8$ of a rotation with the dashed circle showing the center of the disk. (d) Deformation structure with multiple twinning systems after a shear strain of $\\gamma\\sim2.4.$ . (e) Fragmentation of the twinned structure at higher strains, $\\gamma\\sim4.0$ . (f) Final saturation microstructure $(\\gamma\\sim50)$ . \n\n![](images/25b5e34990825f6ae65de01425cfdd7ba7541a75427c3c9bb28112fe1a596425.jpg) \nFig. 3. Microstructure of the severely plastically deformed CoCrFeMnNi alloy. (a) STEM image of the saturation microstructure (b) Detail of representative diffraction pattern displaying fcc reflections. \n\nTEM investigations of the same microstructural states as above allowed further structural information to be obtained for the newly formed phases and the results are compiled in Fig. 7. For very short anneals, Fig. 7a, the microstructure appears to become clearer compared to the one presented earlier for the SPD state (Fig. 3a); however, in the diffraction pattern, Fig. 7b, no significant changes can be seen (compared to Fig. 3b), even though the 3D-APT results clearly show the formation of new phases (Fig. 6a). This is due to their very small volume fractions (Table 1). After a 1-h anneal, a slight coarsening of the structure is visible in Fig. 7c and very weak additional reflections can be seen in the diffraction pattern, Fig. 7d. With a further increase in annealing time (to 15 h) the microstructure becomes coarser, Fig. 7e, while at the same time hardness increases (Fig. 5b). Furthermore, there is a pronounced change in the diffraction pattern from continuous to discontinuous rings comprising individual spots accompanied with the formation of additional Debye-Scherer rings compared to the SPD and 5-min-annealed states. The additional rings can be correlated with a bcc phase having a lattice constant of approximately ${\\sim}2.9\\mathring{\\mathsf{A}}.$ The precision with which lattice constants can be determined using simple diffraction patterns is undeniably lower compared to other techniques, which makes an unambiguous identification based on just the electron diffraction pattern difficult. However, the calculated value is close that of pure Cr, which has a lattice constant of $2.88\\mathring{\\mathsf{A}}$ [31], suggesting that these additional rings are very likely due to the Cr-rich phase, which itself is not pure but alloyed with other species (Table 1) that likely alter its lattice constant. \n\n![](images/c17271ba49cb35677c2a75bc3fc20920bae6c5594fa7df638ba48c9c5fa73eb5.jpg) \nFig. 4. Chemical analysis of the saturation microstructure. (a) 3D-reconstruction of the severely plastically deformed CoCrFeMnNi HEA investigated with 3D-APT showing Cr, Fe, Ni, Co and Mn maps. (b) Chemical composition along the long axis of the displayed atom-probe images. (For interpretation of the references to color in this figure, the reader is referred to the web-version of the article.) \n\nA closer look at the pattern in Fig. 7f reveals that there are two distinct sets of fcc rings. The second fcc set has a somewhat larger lattice constant of ${\\sim}3.8\\mathring{\\mathsf{A}}.$ To explain the possible origin of this set, we consulted the binary $\\mathsf{M n{-}N i}$ phase diagram [32]. It does not reveal a disordered fcc structure in the middle of the phase diagram around the composition shown in Table 1. Rather, the $\\textsf{\\textsf{a}}$ -MnNi phase in the diagram has the ordered $\\mathtt{L1}_{0}$ structure. The presence of other alloying elements (Cr, Fe, Co) in our Mn–Ni phase, see Table 1, might have induced disorder in what would have been an ordered phase in the pure Mn–Ni binary system. Assuming this is true in the present case, the disordered MnNi(Cr, Fe, Co) phase would be equivalent to a fcc phase giving rise to the second set of fcc rings. Lastly, a FeCo phase was identified by 3D-APT whose presence should, in principle, be found in the diffraction pattern as well. However, the lattice constant of such a phase is expected to be ${\\sim}2.85\\mathring{\\mathsf{A}}$ based on the binary Fe– Co system [33]. The diffraction rings stemming from this phase would be very close to those of the previously mentioned Cr phase (lattice constant, ${\\sim}2.9\\mathring{\\mathsf{A}}.$ ) making them virtually indistinguishable. Despite this uncertainty in phase identification based on the diffraction patterns, it is worth noting that the $^{15-\\mathrm{h}}$ specimen becomes strongly magnetic, which is likely due to the formation of the FeCo phase. \n\n![](images/bf95956c1e1e07076cfaf0d3dbd0cb4e4770ce7f6df089e85a33295799935252.jpg) \nFig. 5. Microhardness results of (a) isochronally (for $\\mathsf{1h}^{\\cdot}$ ) and (b) isothermally $(450^{\\circ}\\mathsf C)$ heat treated specimens. The isothermal treatments were performed at the peak hardness temperature in the isochronal treatments $(450^{\\circ}\\mathsf C)$ . \n\n# 3.5. Tensile tests \n\nIn Fig. 8, results of representative tensile tests performed after different annealing treatments are shown. Due to the restricted sample size only the displacement of the stroke (and not strain in the gage section) could be measured, which is satisfactory for comparison of the different microstructural states. The SPD state shows remarkably high strength accompanied with moderate ductility. Annealing at the peak hardness temperature leads to a further increase in strength but also a loss of ductility, which becomes even more pronounced for longer annealing times, Fig. 8a. In the case of the $15\\mathrm{-h}$ annealing treatment, the apparent loss in strength is simply a consequence of the extreme brittleness of the sample, which causes failure in the elastic regime of the tensile test. Subjecting the material to higher annealing temperature regains ductility, Fig. 8b, and for $800^{\\circ}\\mathsf C$ anneals pronounced work-hardening is restored, which is typical for this alloy in the coarse-grained state [7]. \n\n![](images/98a8b23baa066f4b6baa2c6cca67c53b04bb7355afd7ca948ae0300b54da7393.jpg) \nFig. 6. 3D-APT reconstruction of samples subjected to annealing treatments for (a) $5\\mathrm{min}$ , (b) 1 h (due to the smaller volumes obtained for this material state two samples are presented) and (c) $15\\mathrm{h}$ . Isoconcentration surfaces represent regions of ${>}70$ at.% ${\\mathsf{N i}}+{\\mathsf{M n}}$ (green), $>50$ at.% Cr (purple) and ${>}35$ at.% Co (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\nTable 1 Summary of 3D-APT results showing the estimated chemical compositions and volume fractions of the phases formed in the originally single-phase NC HEA after annealing for various times at $450^{\\circ}\\mathsf C.$ . The main constituents of each individual phase are shown in bold font. Due to the small analyzed volumes the values of the volume fraction provide general trends and not exact values. \n\n\n
Annealing statePhaseMn (at.%)Ni (at.%)Cr (at.%)Fe (at.%)Co (at.%)Vol% (%)
5 minNiMn43.546.22.82.74.70.6
Cr6.21.87113.67.30.9
1hNiMn46.045.72.02.04.29.1
Cr5.01.674.212.16.81.3
15hNiMn44.146.22.62.34.216.9
Cr3.40.481.89.64.113.5
FeCo5.71.70.346.745.327.3
\n\n# 4. Discussion \n\n# 4.1. Thermal stability and decomposition of the NC alloy \n\nIn view of the existing literature, the most significant phenomenon observed in this study was the decomposition tendency of the CoCrFeMnNi HEA upon annealing after SPD. In preceding publications on coarser-grained HEAs with similar composition, a true solid solution down to the atomic scale was found [34] as well as good high-temperature stability with no tendency of decomposition [6]. In this study, by contrast, the originally single-phase HEA with NC grains transforms relatively rapidly into a nanostructured multiphase composite consisting of several different new phases during annealing. As discussed later, a possible reason for this difference is that the nanocrystalline structure of the present alloy enhances overall diffusion by providing an abundance of grain boundaries. Otherwise, as shown by Tsai et al. [35], diffusion in this CoCrFeMnNi HEA is expected to be sluggish since the diffusivities of its constituent elements are smaller than their values in pure metals as well as in alloys consisting of fewer constituents than the quinary. \n\nAt the beginning a MnNi phase and a Cr-rich phase are formed, see Fig. 6a and b and after longer annealing times a FeCo phase could be detected, Fig. 6c. The chronological sequence of these phases can be rationalized by considering their relative diffusivities. The magnitude of the diffusion coefficients of the individual elements in the CoCrFeMnNi alloy was investigated by Tsai et al. [35]. They found a similar ordering of the diffusion coefficients as that of the pure metals [36]. The element that diffuses fastest at a fixed temperature is Mn, which is consistent with the formation of the MnNi phase first. The second phase to form has a very high Cr concentration, which has the next highest diffusion coefficient after Mn. Only after longer annealing times does the FeCo phase form, which consists of elements that have the next highest diffusion coefficients after Mn and Cr. These three new phases together with the primary fcc matrix phase form a multiphase NC microstructure. \n\nUnlike previous work in which this HEA was found to be thermally stable at times up to three days [6], phase decomposition occurs in the SPD-deformed HEA at much shorter times. This can be partly attributed to the chosen annealing temperature regime. The previous microcrystalline samples were processed by cold rolling followed by annealing in a temperature range somewhat above the recrystallization temperature, which is about $800^{\\circ}\\mathsf C$ depending on the degree of pre-deformation [37] and in this temperature regime a pure single-phase structure is formed. Zhang et al. [38] used the CALPHAD (Calculation of Phase Diagrams) approach to calculate phase diagrams for such multicomponent alloys and predicted a single-phase fcc-structure for temperatures above $600^{\\circ}\\mathsf C$ In this study a lower temperature regime for annealing was targeted to avoid recrystallization or grain growth, which would otherwise weaken the beneficial effect of grain refinement on strength. Of relevance to the annealing temperature range used in the present study is Zhang et al.’s prediction of a multiphase mixture below $600^{\\circ}{\\mathsf C}$ . For comparison, the microstructures obtained by annealing for $^{1\\mathrm{{h}}}$ at temperatures above $600^{\\circ}\\mathsf C$ are presented in Fig. 9. In contrast to the SPD state and those produced by annealing at $450^{\\circ}\\mathsf C$ , substantial grain growth can be observed at higher temperatures. More importantly, another phase or phases were still found after 1-h anneals above $600^{\\circ}\\mathsf C$ As an example the microstructure annealed at $700^{\\circ}\\mathsf C$ is presented in Fig. 9a, where second-phase particles (encircled) can be seen. Due to their small size it was not possible to analyze them in the SEM using energy dispersive $\\mathsf{X}$ -ray spectroscopy. Nevertheless, it is reasonable to assume that they are similar to the phases found by \n\n![](images/09f500e8feed5aee5c81a1a05594d316a4af99273b7997bc657b1f77760f7f70.jpg) \nFig. 7. Examples of the microstructures of differently annealed samples and their representative diffraction patterns. (a and b) 5-min anneal, (c and d) 1-h anneal, (e and f) $^{15-\\mathrm{h}}$ anneal. Note that for $5\\mathrm{-min}$ and 1-h anneals STEM images are shown whereas for the $^{15-\\mathrm{h}}$ specimen, due to the strong magnetism of the structure, a conventional bright-field image is presented with a slightly different magnification. \n\n![](images/1bb3751c40e634d04279b2a3d367430e2e3e157ce6bdf53faff7bbf6a85eb8ce.jpg) \nFig. 8. Results of tensile tests performed in the different annealed states. (a) Examples for annealing treatments performed at the peak temperature for the isochronal treatment. (b) Annealing treatments above the peak temperature. \n\n3D-APT and discussed earlier, Fig. 6. At the higher annealing temperature of $750^{\\circ}\\mathsf C$ , they can be clearly seen to be situated at grain boundaries and triple junctions, Fig. 9b. Interestingly, subjecting the material to an even higher annealing temperature of $800^{\\circ}\\mathsf C$ for 1 h leads once again to a pure single-phase material, but with a substantially increased grain size of about $10\\upmu\\mathrm{m}$ , Fig. 9c. This illustrates clearly that similar heat treatments as those used for heavily cold rolled materials [37], which were used to obtain a fully recrystallized structure with microcrystalline grain sizes, produce similar single-phase microstructures. \n\nBesides the annealing temperature being a factor, the intrinsic nature of NC metals also contributes to the kinetics of phase formation: the 3D-APT measurements together with the hardness measurements have clearly demonstrated that these phases appear very quickly, after just a few minutes of annealing. This fast formation of new phases can be understood by considering the role of grain boundaries in diffusion-controlled precipitation and phase formation processes in NC metals, see [39,40]. The total grain boundary area drastically increases by lowering the grain size. These boundaries can serve as fast diffusion pathways and represent energetically preferred nucleation sites for the formation of new phases with much faster kinetics than in coarser grained alloys where bulk diffusion prevails. In this context, the significant contribution of triple junctions in NC metals should be mentioned, which has been proposed to allow increased diffusion by short circuit diffusion [41]. This is supported by the micrographs in Fig. 9a and b showing the presence of second phase particles at triple junctions. However, it should be kept in mind that these micrographs depict the condition for high annealing temperatures, where the initial NC-structure has already coarsened. Focusing on the NC-structure, the diffusion coefficients measured for bulk diffusion in microcrystalline materials [35] play only a minor role in the NC state and a much larger diffusivity mainly triggered by grain boundary diffusion should be expected. It should be noted, however, that if the existence of these phases is thermodynamically predicted based on a minimum of the Gibbs free energy, they would also occur in coarser grained samples subjected to similar heat treatments. The only expected difference is the time scale that is needed to allow sufficient diffusion in the larger grain-size regime. \n\n![](images/715a4bded2dcd0a0812a427de0399317e7298a4adcdb4c774ac7b3f87db25893.jpg) \nFig. 9. Backscattered electron micrographs showing microstructural changes above the peak temperature after 1-h anneals at (a) $700^{\\circ}{\\mathsf{C}}.$ (b) $750^{\\circ}\\mathsf C$ and (c) $800^{\\circ}{\\mathsf C}$ Some examples of second-phase particles are indicated with circles in (a) and (b). \n\nAlthough the formation of these new phases is a rather new phenomenon in this HEA, other so-called HEAs exhibit a two- or multi-phase structure quite frequently [4]. Even in the CoCrFeMnNi alloy, the replacement of a single element by another or the removal of a specific species can lead to phase separation [42–44]. This suggests that single-phase HEAs are likely restricted to narrow compositional ranges. The current study has expanded our understanding of single-phase HEAs by uncovering previously unreported thermal aspects of phase stability. Although recrystallization temperatures around $800^{\\circ}\\mathsf C$ lead to a single-phase material, this study shows that subsequent thermal exposures in the range of $450–750^{\\circ}C$ during application could lead to long-term structural modifications combined with mechanical and physical property changes. This behavior could even be true for lower temperatures as a hardness increase was detected for temperatures below $450^{\\circ}\\mathsf C$ , see Fig. 5a. SPD provides a convenient way to probe these changes by accelerating the phase decomposition process and opening a window into the long-term phase stability of conventional-grain-size alloys. \n\n# 4.2. Strengthening mechanisms in the NC alloy \n\nEqually intriguing as the above decomposition behavior is the substantial increase in hardness upon annealing. At first glance, it is reasonable to suppose that this behavior is simply linked to the formation of the new phases as is the case in some other HEAs. For example, in a $\\mathsf{A l}_{0.3}\\mathsf{C r F e}_{1.5}\\mathsf{M n N i}_{0.5}$ alloy an increase in hardness has been associated with the formation of new phases after heat treatment where the entire matrix undergoes a phase transformation into a significantly harder phase [45]. Similarly, in a $\\mathsf{A l}_{0.3}\\mathsf{C o C r F e N i}$ alloy subjected to SPD and annealed for different temperatures the hardness increase has also been associated with the formation of a hard secondary phase [46]. However, we believe that the hardening mechanism in the present NC HEA is more complicated as discussed below. \n\nDue to energetic considerations, the nucleation sites for the new phases found by 3D-APT can be assumed to lie on the grain boundaries of the matrix phase. The resulting clusters or second phases that form at these sites can hinder dislocation emission and motion at grain boundaries. Such a grain boundary segregation based strengthening mechanism has been proposed before to explain the origin of the unusually high strength in SPD-processed Al alloys [47] and austenitic steels [48]. In the NC HEA, after very short anneals, the typical dimensions of these new phases are similar to those of the primary phase, i.e., several tens of nanometers, see Fig. 6b, and the hardness continuously increases as shown in Fig. 5b. This means that the strengthening cannot be exclusively explained by segregation at grain boundaries. For classical precipitation hardening, the precipitates are situated within individual grains and have to remain small compared to the grain size to be effective obstacles for dislocation motion. \n\nA further mechanism that can contribute to strengthening is a reduction of the dislocation density upon annealing [49,50]. The NC structure provides a large fraction of grain boundaries that can absorb dislocations during annealing. To realize plastic flow after annealing, new dislocation sources have to be activated. Especially in the NC grain size regime, the emission of dislocations from grain boundaries becomes significant [51]. In SPD structures, grain boundaries are often considered to be in a ‘‘non-equilibrium’’ state. This is a possible reason for the slightly blurry appearance of the microstructure seen in conventional TEM investigations [28], as well as in the present study, see Fig. 3a. These boundaries may relax during annealing necessitating an increased stress level compared to the SPD state for the emission and accommodation of dislocations at these recovered boundaries. \n\nAnother contribution to the strength can be envisaged by considering the microstructure as a nano-composite consisting of several phases differing markedly in their intrinsic strength. Two of the newly formed phases have an intermetallic character, which is commonly thought to provide high strength. As such, these intermetallic phases would be expected to yield at higher stress levels and partly constrain the deformation of the surrounding softer matrix resulting in an increased global strength of the alloy. Unfortunately, due to their small size, they cannot be individually tested, even with nano-indentation, so it remains unverified at present. Regardless, this composite based explanation can only hold when the volume fractions of the newly formed phases become large, see Table 1. For the early stages of hardening the aforementioned recovery but also the segregation at grain boundaries seem to be significant factors in the hardness increase. \n\nThere is a recent example in the literature that is suggestive of possible phase formation processes even in the coarse-grained version of this CoCrFeMnNi HEA [37]. A similar hardness increase as in the present study was observed after cold rolling and annealing in a similar temperature range below the recrystallization temperature. Due to a lower degree of deformation the absolute hardness values after deformation were lower and the relative hardness increase upon annealing less pronounced. An explanation for the slight hardness increase remained an open question in that paper [37] but it might be related to the results obtained by 3D-APT in this study. \n\n# 4.3. Impact of SPD and annealing on ductility \n\nUltrafine-grained (UFG) alloys obtained by various SPD techniques frequently show unprecedented mechanical properties [52]. Even when deformation related properties such as ductility are inferior compared to those of the coarse-grained starting materials, different strategies have been developed to regain ductility in such alloys. For example, with heat treatments the ductility can be markedly improved while keeping the loss of strength at an acceptable level [53]. However, applying this strategy to the present NC HEA leads to a further reduction of ductility, see Fig. 8a. The deterioration can also be seen on typical fractographs, presented in Fig. 10. Whereas the SPD state, Fig. 10a, is composed of dimples in the size range of several hundred nanometers, the fracture appearance becomes gradually more brittle along with grain boundary fracture the longer the material is annealed, Fig. 10b and c. The observed embrittlement is a consequence of the multiphase-composite formation. By increasing the annealing temperature, substantial grain growth occurs (Fig. 9), accompanied with a decrease in strength. Concurrently, there is a beneficial increase in ductility, which is evident in the tensile test results, Fig. 8b. In addition, the fractographs display ductile dimpled fracture for the different elevated annealing temperatures, Fig. 10d and e. The 600 and $700^{\\circ}\\mathsf C$ annealed specimens, Fig. 10d and e, show a dense population of dimples and their diameter is restricted by the average particle distance. Those particles are recognizable on the micrographs in Fig. 9 for anneals below $800^{\\circ}\\mathsf C$ as well and originate from the phase decomposition during annealing. For anneals above $800^{\\circ}\\mathsf C$ the high density of particles has vanished both on the fracture surface, Fig. 10f, as well as in the microstructure, Fig. 9c. The considerably larger dimples are initiated at the remaining inclusions, which can be even found in very pure materials elongated to fracture. \n\n![](images/be818a21c7ecf9bcc5a2bce64499ad06ea7cb845b710c58f0da32a14e33912a3.jpg) \nFig. 10. Typical fracture surfaces of the different annealed specimen states. (a) SPD state, (b) annealed at $450^{\\circ}\\mathsf C$ for 1 h, (c) at $450^{\\circ}\\mathsf C$ for $15\\mathrm{h}$ , (d) at $600^{\\circ}\\mathsf C$ for 1 h, (e) at $700^{\\circ}\\mathrm{C}$ for $^{1\\mathrm{h}}$ and (f) at $800^{\\circ}{\\mathsf C}$ for $^{1\\mathrm{h}}$ . \n\nFor possible future applications of NC HEAs an optimization of strength and ductility has to be strived for. To accomplish that, short-term anneals at temperatures above the peak-hardening temperature seem to be promising. By minimizing the temperature exposure, the NC grains may remain small, which is a pre-condition for keeping the strength at a reasonable level. Simultaneously, the decomposition leading to new phase formation could be suppressed when the target temperature corresponds thermodynamically to a single phase state, which may be around $800^{\\circ}\\mathsf C$ in this particular HEA. A higher annealing temperature, however, would accelerate grain growth as well. Therefore, in future research, it is crucial to carefully investigate how to balance annealing temperature and time to obtain optimum strength and ductility. \n\n# 5. Summary and conclusions \n\nAn equiatomic CoCrFeMnNi high-entropy alloy produced by arc melting and drop casting was homogenized and subjected to severe plastic deformation using high-pressure torsion. As a result, the microstructure was refined to a grain size of approximately $50\\mathrm{nm}$ along with an exceptional increase of strength. In the as-processed NC state, the true solid solution, single-phase, fcc structure of this HEA was maintained. The material was then used for subsequent annealing treatments and the main findings can be summarized as follows: \n\n(i) Isochronal heat treatments for 1 h lead to a significant hardening at temperatures to $450^{\\circ}\\mathsf C$ before softening sets in for higher annealing temperatures. \n(ii) Isothermal heat treatments at the peak-hardening temperature of $450^{\\circ}\\mathsf C$ result in a continuous increase of hardness up to approximately $100\\mathrm{h}$ . \n(iii) The hardening behavior, especially for the longer annealing times, can be mainly attributed to the formation of a nanostructured multiphase microstructure, consisting of a MnNi phase, a Cr-rich phase, and a Fe–Co phase embedded in the HE matrix. \n(iv) This phase decomposition from the initial solid solution state occurs relatively fast, in as little as 5 min at $450^{\\circ}\\mathsf C$ for the formation of the NiMn and Cr phases, and somewhat longer $(\\sim15\\mathrm{h})$ for the formation of the FeCo phase at $450^{\\circ}\\mathsf C$ \n(v) The nanocrystalline grain size of the SPD processed HEA appears to facilitate these phase transformations owing to \n\nthe large number of grain boundaries serving as fast diffusion pathways and preferential nucleation sites for the formation of new phases. \n\n(vi) In tensile tests, exceptional strength levels can be achieved, however the ductility is low. To overcome this drawback, short-term anneals above the isochronal hardness maximum are proposed to maintain the strength at a reasonable level while ductility is regained. \n\nThis observed phase instability of the CoCrFeMnNi (Cantor) alloy, which is often cited in the literature as one of the few true solid solution high-entropy alloys, suggests that careful consideration needs to be given in the future to the application temperature, possibly even in the case of coarser grained alloys that might be exposed for long times. \n\n# Acknowledgments \n\nThis work was supported by the Austrian Science Fund (FWF) in the framework of Research Project P26729-N19. Support for alloy production at the Oak Ridge National Laboratory was provided by the U.S. Department of Energy, Basic Energy Sciences, Materials Sciences and Engineering Division. \n\n# References \n\n[1] J.W. Yeh, S.K. Chen, S.J. Lin, J.Y. Gan, T.S. Chin, T.T. Shun, C.H. Tsau, S.Y. Chang, Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes, Adv. Eng. Mater. 6 (2004) 299–303. \n[2] M.H. Tsai, J.W. Yeh, High-entropy alloys: a critical review, Mater. Res. Lett. 2 (2014) 107–123. \n[3] D.B. Miracle, J.D. Miller, O.N. Senkov, C. Woodward, M.D. Uchic, J. Tiley, Exploration and development of high entropy alloys for structural applications, Entropy 16 (2014) 494–525. \n[4] R. Kozak, A. Sologubenko, W. Steurer, Single-phase high-entropy alloys – an overview, Z. Kristallogr. 230 (2015) 55–68. \n[5] B. Cantor, I.T.H. Chang, P. Knight, A.J.B. Vincent, Microstructural development in equiatomic multicomponent alloys, Mater. Sci. Eng., A 375–377 (2004) 213– 218. \n[6] F. Otto, Y. Yang, H. Bei, E.P. George, Relative effects of enthalpy and entropy on the phase stability of equiatomic high-entropy alloys, Acta Mater. 61 (2013) 2628–2638. \n[7] F. Otto, A. Dlouhy´ , Ch. Somsen, H. Bei, G. Eggeler, E.P. George, The influences of temperature and microstructure on the tensile properties of a CoCrFeMnNi high-entropy alloy, Acta Mater. 61 (2013) 5743–5755. \n[8] N. Stepanov, M. Tikhonovsky, N. Yurchenko, D. Zyabkin, M. Klimova, S. Zherebtsov, A. Efimov, G. Salishchev, Effect of cryo-deformation on structure and properties of CoCrFeNiMn high-entropy alloy, Intermetallics 59 (2015) 8– 17. \n[9] A. Gali, E.P. George, Tensile properties of high- and medium-entropy alloys, Intermetallics 39 (2013) 74–78. \n[10] A.J. Zaddach, C. Niu, C.C. Koch, D.L. Irving, Mechanical properties and stacking fault energies of NiFeCrCoMn high-entropy alloy, JOM 65 (2013) 1780–1789. \n[11] C. Zhu, Z.P. Lu, T.G. Nieh, Incipient plasticity and dislocation nucleation of FeCoCrNiMn high-entropy alloy, Acta Mater. 61 (2013) 2993–3001. \n[12] G.A. Salishchev, M.A. Tikhonovsky, D.G. Shaysultanov, N.D. Stepanov, A.V. Kuznetsov, I.V. Kolodiy, A.S. Tortika, O.N. Senkov, Effect of Mn and V on structure and mechanical properties of high-entropy alloys based on CoCrFeNi system, J. Alloys Compd. 591 (2014) 11–21. \n[13] J.Y. He, C. Zhu, D.Q. Zhou, W.H. Liu, T.G. Nieh, Z.P. Lu, Steady state flow of the FeCoNiCrMn high entropy alloy at elevated temperatures, Intermetallics 55 (2014) 9–14. \n[14] G. Laplanche, P. Gadaud, O. Horst, F. Otto, G. Eggeler, E.P. George, Temperature dependencies of the elastic moduli and thermal expansion coefficient of an equiatomic, single-phase CoCrFeMnNi high-entropy alloy, J. Alloys Compd. 623 (2015) 348–353. \n[15] A. Haglund, M. Koehler, D. Catoor, E.P. George, V. Keppens, Polycrystalline elastic moduli of a high-entropy alloy at cryogenic temperatures, Intermetallics 58 (2015) 62–64. \n[16] B. Gludovatz, A. Hohenwarter, D. Catoor, E.H. Chang, E.P. George, R.O. Ritchie, A fracture-resistant high-entropy alloy for cryogenic applications, Science 345 (2014) 1153–1158. \n[17] R.Z. Valiev, R.K. Islamgaliev, I.V. Alexandrov, Bulk nanostructured materials from severe plastic deformation, Prog. Mater. Sci. 45 (2000) 103–189. \n[18] A.P. Zhilyaev, T.G. Langdon, Using high-pressure torsion for metal processing: fundamentals and applications, Prog. Mater. Sci. 53 (2008) 893–979. \n[19] Y.T. Zhu, T.C. Lowe, T.G. Langdon, Performance and applications of nanostructured materials produced by severe plastic deformation, Scr. Mater. 51 (2004) 825–830. \n[20] R. Pippan, S. Scheriau, A. Taylor, M. Hafok, A. Hohenwarter, A. Bachmaier, Saturation of fragmentation during severe plastic deformation, Annu. Rev. Mater. Res. 40 (2010) 319–343. \n[21] Y.M. Wang, E. Ma, Three strategies to achieve uniform tensile deformation in a nanostructured metal, Acta Mater. 52 (2004) 1699–1709. \n[22] C.C. Koch, Optimization of strength and ductility in nanocrystalline and ultrafine grained metals, Scr. Mater. 49 (2003) 657–662. \n[23] A. Hohenwarter, A. Bachmaier, B. Gludovatz, S. Scheriau, R. Pippan, Technical parameters affecting grain refinement by high pressure torsion, Int. J. Mater. Res. 100 (2009) 1653–1661. \n[24] R. Pippan, S. Scheriau, A. Hohenwarter, M. Hafok, Advantages and limitations of HPT: a review, Mater. Sci. Forum 584–586 (2008) 16–21. \n[25] M.A. Meyers, O. Vöhringer, V.A. Lubarda, The onset of twinning in metals: a constitutive description, Acta Mater. 49 (2001) 4025–4039. \n[26] S. Scheriau, Z. Zhang, S. Kleber, R. Pippan, Deformation mechanisms of a modified 316L austenitic steel subjected to high pressure torsion, Mater. Sci. Eng., A 528 (2011) 2776–2786. \n[27] Y.H. Zhao, X.Z. Liao, Y.T. Zhu, Z. Horita, T.G. Langdon, Influence of stacking fault energy on nanostructure formation under high pressure torsion, Mater. Sci. Eng., A 410–411 (2005) 188–193. \n[28] X. Sauvage, G. Wilde, S.V. Divinski, Z. Horita, R.Z. Valiev, Grain boundaries in ultrafine grained materials processed by severe plastic deformation and related phenomena, Mater. Sci. Eng., A 540 (2012) 1–12. \n[29] P.P. Bhattacharjee, G.D. Sathiaraj, M. Zaid, J.R. Gatti, Chi Lee, Che-Wei Tsai, JienWei Yeh, Microstructure and texture evolution during annealing of equiatomic CoCrFeMnNi high-entropy alloy, Alloys Compd. 587 (2014) 544–552. \n[30] D.R. Stull, G.C. Sinke, Tabulated Values of Thermodynamic Properties, in: Thermodynamic Properties of the Elements, American Chemical Society, 1956, pp. 36–226. \n[31] R.W.G. Wyckoff, Crystal Structures, second ed., Interscience Publishers, New York, 1963, pp. 7–83. \n[32] H. Okamoto, Mn-Ni (Manganese-Nickel), J. Phase Equilib. Diffus. 28 (2007) 406–407. \n[33] W.B. Pearson, A Handbook of Lattice Spacings and Structures of Metals and Alloys, Pergamon Press, New York, 1958. \n[34] M. Laurent-Brocq, A. Akhatova, L. Perrière, S. Chebini, X. Sauvage, E. Leroy, Y. Champion, Insights into the phase diagram of the CrMnFeCoNi high entropy alloy, Acta Mater. 88 (2015) 355–365. \n[35] K.Y. Tsai, M.H. Tsai, J.W. Yeh, Sluggish diffusion in Co–Cr–Fe–Mn–Ni highentropy alloys, Acta Mater. 61 (2013) 4887–4897. \n[36] G. Neumann, C. Tuijn, Self Diffusion and Impurity Diffusion in Pure Metals: Handbook of Experimental Data, first ed., Elsevier, Oxford, 2009. \n[37] F. Otto, N.L. Hanold, E.P. George, Microstructural evolution after thermomechanical processing in an equiatomic, single-phase CoCrFeMnNi high-entropy alloy with special focus on twin boundaries, Intermetallics 54 (2014) 39–48. \n[38] F. Zhang, C. Zhang, S.L. Chen, J. Zhu, W.S. Cao, U.R. Kattner, An understanding of high entropy alloys from phase diagram calculations, Calphad 45 (2014) 1–10. \n[39] A. Hohenwarter, M. Faller, B. Rashkova, R. Pippan, Influence of heat treatment on the microstructural evolution of Al–3 wt.% Cu during high-pressure torsion, Philos. Mag. Lett. 94 (2014) 342–350. \n[40] B.B. Straumal, B. Baretzky, A.A. Mazilkin, F. Phillipp, O.A. Kogtenkova, M.N. Volkov, R.Z. Valiev, Formation of nanograined structure and decomposition of supersaturated solid solution during high pressure torsion of Al–Zn and Al–Mg alloys, Acta Mater. 52 (2004) 4469–4478. \n[41] Ying Chen, Christopher A. Schuh, Contribution of triple junctions to the diffusion anomaly in nanocrystalline materials, Scr. Mater. 57 (2007) 253–256. \n[42] N. Park, I. Watanabe, D. Terada, Y. Yokoyama, P.K. Liaw, N. Tsuji, Recrystallization behavior of CoCrCuFeNi high-entropy alloy, Metall. Mater. Trans. A 46 (2015) 1481–1487. \n[43] A. Manzoni, H. Daoud, R. Völkl, U. Glatzel, N. Wanderka, Phase separation in equiatomic AlCoCrFeNi high-entropy alloy, Ultramicroscopy 132 (2013) 212– 215. \n[44] C.C. Tasan, Y. Deng, K.G. Pradeep, M.J. Yao, H. Springer, D. Raabe, Composition dependence of phase stability, deformation mechanisms, and mechanical properties of the CoCrFeMnNi high-entropy alloy system, JOM 66 (2014) 1993–2001. \n[45] M.H. Tsai, H. Yuan, G. Cheng, W. Xu, W.W. Jian, M.H. Chuang, C.C. Juan, A.C. Yeh, S.J. Lin, Y. Zhu, Significant hardening due to the formation of a sigma phase matrix in a high entropy alloy, Intermetallics 33 (2013) 81–86. \n[46] Q.H. Tang, Y. Huang, Y.Y. Huang, X.Z. Liao, T.G. Langdon, P.Q. Dai, Hardening of an $\\mathsf{A l}_{0.3}$ CoCrFeNi high entropy alloy via high-pressure torsion and thermal annealing, Mater. Lett. 151 (2015) 126–129. \n[47] R.Z. Valiev, N.A. Enikeev, M.Yu. Murashkin, V.U. Kazykhanov, X. Sauvage, On the origin of the extremely high strength of ultrafine-grained Al alloys produced by severe plastic deformation, Scr. Mater. 63 (2010) 949–952. \n[48] M.M. Abramova, N.A. Enikeev, R.Z. Valiev, A. Etienne, B. Radiguet, Y. Ivanisenko, X. Sauvage, Grain boundary segregation induced strengthening of an ultrafine-grained austenitic stainless steel, Mater. Lett. 136 (2014) 349– 352. \n[49] X. Huang, N. Hansen, N. Tsuji, Hardening by annealing and softening by deformation in nanostructured metals, Science 312 (2006) 249–251. \n[50] O. Renk, A. Hohenwarter, K. Eder, K.S. Kormout, J.M. Cairney, R. Pippan, Increasing the strength of nanocrystalline steels by annealing: is segregation necessary?, Scr Mater. 95 (2015) 27–30. \n[51] A. Hasnaoui, H. Van Swygenhoven, P.M. Derlet, On non-equilibrium grain boundaries and their effect on thermal and mechanical behaviour: a molecular dynamics computer simulation, Acta Mater. 50 (2002) 3927–3939. \n[52] Y. Estrin, A. Vinogradov, Extreme grain refinement by severe plastic deformation: a wealth of challenging science, Acta Mater. 61 (2013) 782–817. \n[53] Y. Wang, M. Chen, F. Zhou, E. Ma, High tensile ductility in a nanostructured metal, Nature 419 (2002) 912–915. " + }, + { + "id": "10.1073_pnas.1416591112", + "DOI": "10.1073/pnas.1416591112", + "DOI Link": "http://dx.doi.org/10.1073/pnas.1416591112", + "Relative Dir Path": "mds/10.1073_pnas.1416591112", + "Article Title": "Penta-graphene: A new carbon allotrope", + "Authors": "Zhang, SH; Zhou, J; Wang, Q; Chen, XS; Kawazoe, Y; Jena, P", + "Source Title": "PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA", + "Abstract": "A 2D metastable carbon allotrope, penta-graphene, composed entirely of carbon pentagons and resembling the Cairo pentagonal tiling, is proposed. State-of-the-art theoretical calculations confirm that the new carbon polymorph is not only dynamically and mechanically stable, but also can withstand temperatures as high as 1000 K. Due to its unique atomic configuration, penta-graphene has an unusual negative Poisson's ratio and ultrahigh ideal strength that can even outperform graphene. Furthermore, unlike graphene that needs to be functionalized for opening a band gap, penta-graphene possesses an intrinsic quasi-direct band gap as large as 3.25 eV, close to that of ZnO and GaN. Equally important, penta-graphene can be exfoliated from T12-carbon. When rolled up, it can form pentagon-based nullotubes which are semiconducting, regardless of their chirality. When stacked in different patterns, stable 3D twin structures of T12-carbon are generated with band gaps even larger than that of T12-carbon. The versatility of penta-graphene and its derivatives are expected to have broad applications in nulloelectronics and nullomechanics.", + "Times Cited, WoS Core": 1253, + "Times Cited, All Databases": 1284, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000349911700035", + "Markdown": "# Penta-graphene: A new carbon allotrope \n\nShunhong Zhanga,b,c, Jian Zhouc, Qian Wanga,b,c,1, Xiaoshuang Chend,e, Yoshiyuki Kawazoef, and Puru Jenac aCenter for Applied Physics and Technology, College of Engineering, Peking University, Beijing 100871, China; bCollaborative Innovation Center of Inertial Fusion Sciences and Applications, Ministry of Education, Beijing 100871, China; cDepartment of Physics, Virginia Commonwealth University, Richmond, VA 23284; dNational Laboratory for Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China; eSynergetic Innovation Center of Quantum Information & Quantum Physics, University of Science and Technology of China, Hefei, Anhui 230026, China; and fInstitute for Materials Research, Tohoku University, Sendai, 980-8577, Japan \n\nEdited by Ho-kwang Mao, Carnegie Institution of Washington, Washington, DC, and approved January 5, 2015 (received for review August 28, 2014) \n\nA 2D metastable carbon allotrope, penta-graphene, composed entirely of carbon pentagons and resembling the Cairo pentagonal tiling, is proposed. State-of-the-art theoretical calculations confirm that the new carbon polymorph is not only dynamically and mechanically stable, but also can withstand temperatures as high as $\\pmb{1000}\\pmb{\\kappa}$ . Due to its unique atomic configuration, penta-graphene has an unusual negative Poisson’s ratio and ultrahigh ideal strength that can even outperform graphene. Furthermore, unlike graphene that needs to be functionalized for opening a band gap, penta-graphene possesses an intrinsic quasi-direct band gap as large as $3.25\\tt e V$ , close to that of ZnO and GaN. Equally important, penta-graphene can be exfoliated from T12-carbon. When rolled up, it can form pentagon-based nanotubes which are semiconducting, regardless of their chirality. When stacked in different patterns, stable 3D twin structures of T12-carbon are generated with band gaps even larger than that of T12-carbon. The versatility of penta-graphene and its derivatives are expected to have broad applications in nanoelectronics and nanomechanics. \n\ncarbon allotrope | carbon pentagon | stability | negative Poisson’s ratio | electronic structure \n\narbon is one of the most versatile elements in the periodic table and forms a large number of allotropes ranging from the well-known graphite, diamond, $\\mathrm{{C}_{60}}$ fullerene (1), nanotube (2), and graphene (3) to the newly discovered carbon nanocone (4), nanochain (5), graphdiyne (6), as well as 3D metallic structures (7, 8). The successful synthesis of graphene (3) has triggered considerable interest in exploring novel carbon-based nanomaterials. A wealth of 2D carbon allotropes beyond graphene has since been studied (see SI Appendix, Table S1 for details). Although some of these polymorphs such as graphdiyne (6) are metastable compared with graphene, they have been successfully synthesized. Moreover, some 2D carbon allotropes are predicted to exhibit remarkable properties that even outperform graphene, such as anisotropic Dirac cones (9), inherent ferromagnetism (10), high catalytic activity (6), and potential superconductivity related to the high density of states at the Fermi level (11). These results demonstrate that many of the novel properties of carbon allotropes are intimately related to the topological arrangement of carbon atoms and highlight the importance of structure–property relationships (12). \n\nPentagons and hexagons are two basic building blocks of carbon nanostructures. From zero-dimensional nanoflakes or nanorings (13) to 1D nanotube, 2D graphene, and 3D graphite and metallic carbon phases (7, 8), hexagon is the only building block. Extended carbon networks composed of only pentagons are rarely seen. Carbon pentagons are usually considered as topological defects or geometrical frustrations (14) as stated in the well-known “isolated pentagon rule” (IPR) (15) for fullerenes, where pentagons must be separated from each other by surrounding hexagons to reduce the steric stress. For instance, $\\mathrm{C}_{60}$ consists of 12 pentagons separated by 20 hexagons forming the shape of a soccer ball, which is a perfect footnote to IPR. The emergence of carbon pentagons is also found to be accompanied by carbon heptagons in some cases (14), but are separated from each other. Inspired by the synthesis of pure pentagon-based $\\mathbf{C}_{20}$ cage (16), considerable effort has been made to stabilize fusedpentagon-based and non-IPR carbon materials in various dimensionalities (10, 15). Some non-IPR fullerenes have been experimentally realized (15). A “pentagon-first” mechanism was postulated in the transformation from sp carbon chains to $s p^{2}$ carbon rings during surface growth of 2D carbon sheets (17). Thus, we conceived the idea of building 2D carbon sheets using fused pentagons as a structural motif. In this work, we show that a 2D carbon allotrope, penta-graphene, consisting entirely of pentagons, can indeed exist. The dynamical, thermal, and mechanical stability of this unique structure is confirmed by a series of state-of-the-art theoretical calculations. In addition, we show that pentagon-based carbon nanotubes, penta-tubes, formed by rolling up the penta-graphene sheet, and 3D twin structures of the recently reported T12-carbon (18) formed by stacking these sheets in different patterns, are both dynamically and thermally stable. We demonstrate that these exotic pentagon-based carbon materials exhibit interesting mechanical and electronic properties. \n\n# Results \n\nPenta-Graphene Exfoliated from T12-Carbon. Our search for an allpentagon-based 2D carbon sheet began by examining the recently proposed T12-carbon phase (18) that can be acquired by heating an interlocking-hexagon–based metastable carbon phase at high temperature (8). We note that there are two kinds of C–C bond lengths, namely, the slightly shorter intralayer bond $(d_{1})$ and the slightly longer interlayer bond $(d_{2})$ , as shown in Fig. 1A. Here the atoms displayed in ball–stick model and highlighted in yellow form a layered structure which can be chemically \n\n# Significance \n\nCarbon has many faces––from diamond and graphite to graphene, nanotube, and fullerenes. Whereas hexagons are the primary building blocks of many of these materials, except for $\\pmb{C}_{20}$ fullerene, carbon structures made exclusively of pentagons are not known. Because many of the exotic properties of carbon are associated with their unique structures, some fundamental questions arise: Is it possible to have materials made exclusively of carbon pentagons and if so will they be stable and have unusual properties? Based on extensive analyses and simulations we show that penta-graphene, composed of only carbon pentagons and resembling Cairo pentagonal tiling, is dynamically, thermally, and mechanically stable. It exhibits negative Poisson’s ratio, a large band gap, and an ultrahigh mechanical strength. \n\n![](images/dbbdc692ab572fb3c1c94b8ae0953b5cdf17c33801a982ba41a00e02dda7dafc.jpg) \nFig. 1. (A) Crystal structure of T12-carbon viewed from the [100] and [001] directions, respectively. (B) Top and side views of the atomic configuration of penta-graphene. The square marked by red dashed lines denotes a unit cell, and the highlighted balls represent the $\\scriptstyle s p^{3}$ hybridized C atoms. \n\nexfoliated from the T12-carbon phase. In fact, a monolayer can be fabricated from either a layered structure or a nonlayered structure (19). For van der Waals coupled layered structures like graphite, mechanical exfoliation (3) is sufficient to obtain the monolayer sheet (graphene), whereas for chemically bonded bulk phases like MAX (a family of transition metal carbides or nitrides), chemical exfoliation technique has been developed to extract a single layer (MXene) (20). \n\nThe optimized crystal structure of the 2D pentagon-based phase generated by exfoliating a single layer from T12-carbon is shown in Fig. $1B$ . The structure possesses $\\scriptstyle P-42_{1}m$ symmetry (space group no. 113) with a tetragonal lattice. The optimized lattice constants are $a=b=3.64\\textrm{\\AA}$ . The top view shows that the new phase is composed entirely of carbon pentagons, forming a beautiful pattern well known as Cairo pentagonal tiling (21). From the side view a buckling $(0.6\\mathrm{~\\AA~})$ is observed, leading to a 2D sheet with a total thickness of $1.2\\mathring\\mathrm{A}$ . This structure can be considered as a multidecker sandwich, with the 4-coordinated C atoms highlighted in yellow in Fig. $1B$ sandwiched between the 3-coordinated atoms. For convenience of discussion, we hereafter group the $s p^{3}$ - and $s p^{2}$ -hybridized $\\mathrm{~\\varsigma~}_{\\mathrm{~\\/~C~}}$ atoms as C1 and C2, respectively, and call this new graphene allotrope penta-graphene. The unit cell of penta-graphene contains six atoms as denoted by red dashed lines in Fig. $1B$ in which the C1 to C2 ratio is 1:2. The C1–C2 (1.55 Å) and C2–C2 $(1.34\\mathrm{~\\AA~})$ bond lengths show pronounced characters of single and double bonds, respectively, and the bond angle $_{{\\Theta}_{\\mathrm{C}2-\\mathrm{C}1-\\mathrm{C}2}}$ is $134.2^{\\circ}$ , indicating the distorted $s p^{3}$ character of C1 atoms. Such bond multiplicity (22) of carbon, although absent in the well-known diamond, graphite and graphene, has been found in a number of carbon structures with different dimensionalities (6–8, 22, 23) and is of general chemical interest as it leads to intermediate valency (23). Interestingly, we note that penta-graphene resembles the structure of experimentally identified layered silver azide $(\\mathrm{AgN}_{3})$ (24). By replacing the ${\\bf N}_{3}$ moieties and Ag atoms with the triconnected C dimers and tetra-connected $\\mathrm{~\\varsigma~}_{\\mathrm{~\\/~C~}}$ atoms, respectively, the geometry of pentagraphene can be realized. \n\nEnergetic Stability. Total energy calculations are performed to investigate the thermodynamic stability of penta-graphene. Although this phase is metastable compared with graphene and previously reported 2D carbon allotropes (6, 11, 14) due to its violation of the IPR, it is more stable than some nanoporous carbon phases such as 3D T-carbon (25), 2D $\\propto$ -graphyne (6), and (3, 12)-carbon sheet (26) (Fig. 2A). We also note that pentagraphene is energetically preferable over some experimentally identified carbon nanostructures such as the smallest fullerene, $\\ensuremath{\\mathrm{~C~}}_{20}$ and the smallest carbon nanotube, implying that the 2D penta-graphene sheet could be synthesized. Although $\\mathbf{C}_{20}$ cage and penta-graphene share the structural motif of fused pentagons, unlike the highly curved $\\mathrm{C}_{20}$ cage where all of the C atoms exhibit distorted $s\\overline{{p}}^{2}$ hybridization leading to a large strain energy, in penta-graphene the onset of $s p^{3}$ hybridization lowers the curvature of fused carbon pentagons, thus partially releasing the strain. \n\nDynamic Stability. Next we study the lattice dynamics of pentagraphene by calculating its phonon dispersion. The results are presented in Fig. 2B. The absence of imaginary modes in the entire Brillouin zone confirms that penta-graphene is dynamically stable. Similar to the phonons of graphene (27, 28), there are three distinct acoustic modes in the phonon spectra of pentagraphene. The in-plane longitudinal and in-plane transverse modes have linear dispersion near the $\\Gamma$ point, whereas the outof-plane (ZA) mode has quadratic dispersion when $\\pmb q$ approaches 0. The quadratic ZA mode in the long-wavelength region is closely associated with the bending rigidity and lattice heat capacity of the nanosheet, which is discussed in detail in $S I A p$ - pendix, text S1. A remarkable phonon gap is observed in the phonon spectra. Detailed analysis of the atom-resolved phonon density of states (PhDOS) reveals that the double bonds between the $s p^{\\tilde{2}}$ hybridized $C2$ atoms are predominant in the dispersionless high-frequency modes (Fig. $2B$ ), which is quite similar to the phonon modes in earlier reported ${\\mathit{s p}}^{2}{-}{{s p}}^{3}$ hybrid carbon structures (7, 8). \n\nThermal Stability. The thermal stability of penta-graphene is examined by performing ab initio molecular dynamics (AIMD) simulations using canonical ensemble. To reduce the constraint of periodic boundary condition and explore possible structure reconstruction, the 2D sheet is simulated by $(4\\times4)$ , $(6\\times6)$ , and $(4{\\sqrt{2}}\\times4{\\sqrt{2}})$ $R45^{\\circ}$ supercells, respectively. After heating at room temperature $(300~\\mathrm{K})$ for 6 ps with a time step of 1 fs, no structure reconstruction is found to occur in all of the cases. Furthermore, we find that the penta-graphene sheet can withstand temperatures as high as $\\bar{1},000\\bar{\\textbf{K}}$ , implying that this 2D carbon phase is separated by high-energy barriers from other local minima on the potential energy surface (PES) of elemental carbon. The snapshots of atomic configurations of penta-graphene at the end of AIMD simulations are shown in SI Appendix, Fig. S1. The effect of point defects or rim atoms on the stability of the penta-graphene sheet is also studied by introducing monoand di-vacancies, Stone–Wales-like defect, adatoms, and edge atoms. The results are presented in SI Appendix, text S2, Figs. S2–S4, where one can see that the stability and structure of penta-graphene is robust, despite the defects. \n\n![](images/d6f7b70e9137c552dac2d09ea424b055caeb38ddaa81dc324764183b4e6bcba7.jpg) \nFig. 2. (A) Area dependence of total energy per atom for some 2D carbon allotropes. The total energy of the experimentally identified dodecahedral $\\mathsf{C}_{20}$ cage is also calculated and plotted here for comparison. (B) Phonon band structures and PhDOS of penta-graphene. (Inset) High-symmetric $q$ -point paths: $\\Gamma\\left(0,0\\right)\\rightarrow\\textsf{X}(1/2,0)\\rightarrow\\textsf{M}(1/2,1/2)\\rightarrow\\Gamma\\left(0,0\\right).$ \n\n![](images/e4c763a3517fdf4e78eb817f08a10b1b742af6be0c20723d37550fc8c9778e16.jpg) \nFig. 3. (A) Strain energy with respect to the lateral lattice response when the penta-graphene lattice is under uniaxial strain along the $x$ direction. The arrows indicate the equilibrium magnitude of «yy. (B) Stress–strain relationship under equi-biaxial tensile strain. The red arrow denotes the maximum strain. (C) Phonon bands of penta-graphene at the extreme of equi-biaxial strain. $(D)$ Same as C for graphene. Blue lines and red circles represent phonons before and after the failure, respectively. (Insets) The high-symmetry $\\boldsymbol{q}$ -point paths in the reciprocal space. \n\nMechanical Stability. As we fix the supercell during all of the MD simulations, it is necessary to assess the effect of lattice distortion on structural stability. To guarantee the positive-definiteness of strain energy following lattice distortion, the linear elastic constants of a stable crystal has to obey the Born–Huang criteria (29). We calculate the change of energy due to the in-plane strain to determine the mechanical stability of penta-graphene. For a 2D sheet, using the standard Voigt notation (26), i.e., 1-xx, 2-yy, and 6-xy, the elastic strain energy per unit area can be expressed as \n\n$$\nU(\\pmb{\\varepsilon})=\\frac{1}{2}C_{11}\\varepsilon_{x x}^{2}+\\frac{1}{2}C_{22}\\varepsilon_{y y}^{2}+C_{12}\\varepsilon_{x x}\\varepsilon_{y y}+2C_{66}\\varepsilon_{x y}^{2},\n$$ \n\nwhere $\\mathrm{C}_{11},\\mathrm{C}_{22},\\mathrm{C}_{12}$ , and $C_{66}$ are components of the elastic modulus tensor, corresponding to second partial derivative of strain energy with respect to strain. The elastic constants can be derived by fitting the energy curves associated with uniaxial and equibiaxial strains. The curves are plotted in $S I$ Appendix, Fig. S5. For a mechanically stable 2D sheet (29), the elastic constants need to satisfy $C_{11}C_{22}^{\\bullet}-C_{12}^{2}>0$ and $C_{66}>0$ . Due to the tetragonal symmetry of penta-graphene, we have $C_{11}=C_{22}$ . Thus, in this case we only need to satisfy $C_{11}{>}|C_{12}|$ and $\\mathrm{C}_{66}>0$ . Under uniaxial strain, $\\varepsilon_{y y}=0$ , $U(\\varepsilon)=1/\\overset{\\cdot}{2}C_{11}\\varepsilon_{11}^{2}$ . Parabolic fitting of the uniaxial strain curve yields $C_{11}=265$ GPa·nm. Under equi-biaxial strain, $\\varepsilon_{x x}=\\varepsilon_{y y}$ we have $U(\\varepsilon)=(C_{11}+C_{12})\\varepsilon_{x x}^{2}$ . Again, by fitting the equi-biaxial strain curve we obtain $C_{11}+\\overleftrightarrow{C}_{12}=247\\mathrm{GPa{\\cdot}n m}$ , hence, $C_{12}=-18$ $\\mathbf{GPa}{\\cdot}\\mathbf{nm}$ . Thus, the calculated elastic constants satisfy $C_{11}>|C_{12}|$ , and the calculated $C_{66}$ is positive, indicating that the 2D pentagraphene sheet is mechanically stable. \n\nMechanical Properties. Having confirmed the stability of pentagraphene, we next systematically study its mechanical properties. The in-plane Young’s modulus, which can be derived from the elastic constants by $\\mathrm{\\bar{\\itE}}=(C_{11}^{2}-C_{12}^{2})/C_{11}$ , is calculated to be 263.8 GPa·nm, which is more than two-thirds of that of graphene (345 GPa·nm) (30) and is comparable to that of h-BN monolayer (26). Interestingly, we note that $C_{12}$ is negative for this nanosheet, leading to a negative Poisson’s ratio (NPR), viz., $\\nu_{12}=\\nu_{21}=$ $C_{12}/C_{11}^{-}=-0.068$ . To confirm this unusual result, we calculated the lateral response in the $y$ direction when the lattice endures a tensile strain in the $x$ direction. We examine cases with $\\varepsilon_{x x}=5\\%$ , $6\\%$ , and $7\\%$ . As expected, we find that the equilibrium lattice constant in the $y$ direction is expanded in all of the cases (Fig. 3A). This confirms the NPR of penta-graphene. It is well known that Poisson’s ratio is defined as the negative ratio of the transverse strain to the corresponding axial strain. Normally, this ratio is positive as most solids expand in the transverse direction when subjected to a uniaxial compression. Although the continuum mechanics theory does not rule out the possibility of emergence of NPR in a stable linear elastic material, it is fairly rare to find such NPR material in nature. However, it has been found that some artificial materials have NPR and exhibit excellent mechanical properties (31, 32). Such materials, usually referred to as auxetic materials or mechanical metamaterials, are of broad interest in both scientific and technological communities (33). Thus, penta-graphene with such unusual mechanical property may have multiple applications such as a tension activatable substrate, a nanoauxetic material, or a deformable variablestiffness material. \n\nBesides in-plane stiffness, ideal strength is also a very important mechanical property of a nanomaterial. We study the ideal strength of penta-graphene by calculating the variation of stress with equi-biaxial tensile strain using different cells. The results are plotted in Fig. 3B, which shows that the strain at the maximum stress is $21\\%$ . Such an ultrahigh ideal strength is exciting. However, we should note that phonon instability might occur before mechanical failure. Such failure mechanism has been well studied in graphene where the phonon softening induced by Kohn anomaly occurs before the stress reaches its maximum in the primitive cell (27, 28). To check whether similar phonondominant failure mechanism exists in penta-graphene, we compute the phonons under increasing equi-biaxial strain. The results at the critical point of phonon softening are plotted in Fig. 3C. We find that phonon softening does not arise until the magnitude of equi-biaxial strain reaches $17.2\\%$ , which is smaller than the magnitude of $21\\%$ obtained from the stress–strain curve. For comparison, we also calculate phonons of the equi-biaxially stretched graphene. The observed softening of the $\\mathbf{K}_{1}$ mode at the Dirac point under equi-biaxial tensile strain of $14.8\\%$ (Fig. $\\left.3D\\right\\rangle$ ) is in excellent agreement with previous work (27, 28). This indicates that the critical strain of penta-graphene is significantly larger than that of pristine graphene. It is also comparable to that of carrier-doping–strengthened graphene (28). At the critical strained state, the single bond lengths between C1 and C2 atoms reach ${\\sim}1.77\\mathrm{~\\AA~}$ , which is comparable with the experimentally (34) and theoretically (35) reported longest C–C bond length. Detailed analyses on the eigenvectors corresponding to the imaginary modes reveal that the structure fracture stems from the breakdown of some of the $\\sigma$ bonds between C1 and C2 atoms. \n\n![](images/775d7629e5b82c9a70a3b7f24aa946c20db361303284c5f0df3f3ddddc9fd2bf.jpg) \nFig. 4. (A) Electronic band structure and total and partial DOS of penta-graphene calculated by using HSE06 functional. The Fermi level is shifted to $0.00\\mathrm{eV}$ . Band-decomposed charge density distributions are depicted in $B$ to E: (B) the second highest occupied band, (C) the highest occupied band, (D) the lowest unoccupied band, and (E) the second lowest unoccupied band. \n\nElectronic Properties. To probe the electronic properties of pentagraphene, we calculate its band structure and corresponding total and partial density of states (DOS). As shown in Fig. 4A, penta-graphene is an indirect band-gap semiconductor with a band gap of $3.25\\mathrm{eV}$ [computed using the Heyd–Scuseria–Ernzerhof (HSE06) functional] (36, 37), because the valance band maximum (VBM) lies on the Γ–X path whereas the conduction band minimum is located on the $\\mathbf{M}{-}\\Gamma$ path. However, due to the existence of the sub-VBM on the M-Γ path, which is very close to the true VBM in energy, penta-graphene can also be considered as a quasi-direct– band-gap semiconductor. Analysis of its partial DOS reveals that the electronic states near the Fermi level primarily originate from the $s p^{2}$ hybridized C2 atoms, which is further confirmed by calculating the band-decomposed charge density distributions, as shown in Fig. 4 B–E. A simplified tight-binding model is used to understand the underlying physics behind the band-gap opening feature in the band structure of penta-graphene (see $S I$ Appendix, text S3 for details). We argue that it is the presence of the $s p^{3}$ -hybridized C1 atoms that spatially separates the $p_{z}$ orbitals of $\\boldsymbol{s p^{2}}$ -hybridized C2 atoms, hindering full electron delocalization and thus giving rise to a finite band gap. The dispersionless, partially degenerate valance bands lead to a high total DOS near the Fermi level, lending to the possibility that Bardeen–Cooper–Schrieffer superconductivity can be achieved in this nanosheet through hole doping (38). \n\nPenta-Tubes: Rolled-Up Penta-Graphene. It is well known that the electronic properties of carbon nanotubes are closely related to graphene according to the zone folding approximation (39). Due to the gapless semimetallic feature of graphene, the electronic properties of carbon nanotubes are highly chirality-dependent: a carbon nanotube is metallic only when its chiral vector $(n,m)$ \n\nsatisfies $n-m=3l$ , where $l$ is an integer. The difficulty in fabricating and separating carbon nanotubes with certain conductance (metallic or semiconducting) greatly hinders its application in nanoelectronics. A previous study proposed a family of metallic carbon nanotubes based on metallic Heackelite sheet (11). It is therefore natural to expect that the penta-graphene–based nanotubes could be semiconducting regardless of chirality. To test this hypothesis we have constructed a series of pentagonbased carbon nanotubes by rolling up the penta-graphene sheet along the $(n,m)$ chiral vectors, where $n=m$ range from 2 to 8 (Fig. 5A). The tubes with other chiralities $(n\\neq m)$ failed to converge to stable tubular structures. We name these pentagonbased carbon nanotubes penta-tubes. The optimized geometry of a (3, 3) penta-tube is illustrated in Fig. $5B$ . The dynamic and thermal stability of this nanotube is confirmed by carrying out phonon calculations and AIMD simulations, respectively. The results are presented in Fig. $5C$ and SI Appendix, Fig. S7, respectively. We find that not only all of the $(n,n)$ penta-tubes are dynamically robust ( $S I$ Appendix, Fig. S8) but also they are thermally stable up to $1{,}000\\mathrm{~K~}$ . Analysis of their band structures and DOS reveals that all of the stable penta-tubes are semiconducting. The calculated results are summarized in SI Appendix, Table S2. Except for the highly curved (2, 2) penta-tube, the band gaps of the $(n,n)$ penta-tubes are not sensitive to their diameters. Thus, chirality-independent semiconducting carbon nanotubes can be produced for application in nanoelectronics. The semiconducting behavior of penta-tubes can be attributed to the electronic structure of penta-graphene, which resembles the case of other semiconducting monolayers such as h-BN monolayer and the corresponding nanotubes (40) which inherit the semiconducting feature. \n\n3D Carbon Structures: Stacked Penta-Graphene Layers. To further explore the structural versatility of penta-graphene, we have altered the stacking patterns of the penta-graphene layers, leading to a 3D structure as shown in Fig. 6 $A$ and $B$ . Following the nomenclature used to analyze the structural character of fused-pentagon-based Pentaheptite (14), we define the layer stacking in T12-carbon as AB type. The stacking of the designed structure shown in Fig. $6A$ and $B$ is then termed as AA type. It can be viewed as a twin structure of the T12-carbon phase. The calculated phonon spectra of AA-T12 are presented in Fig. $6C$ , confirming its dynamical stability. Indeed, more complicated structures are expected to be built, akin to the pentaheptite modification of graphene (14). An example of such structures containing four penta-graphene layers (24 atoms) per unit cell, termed ABAAT24, is presented in SI Appendix, Fig. S9. The detailed structural information of these new 3D phases as well as T12-carbon, for comparison, is given in $S I$ Appendix, Table S3. The calculated cohesive energies (averaged on each carbon atom) are $-8.87$ , $-8.92$ , and $-8.98\\ \\mathrm{eV}$ for AA-T12, ABAA-T24, and T12-carbon, respectively, indicating that the AA-T12 and ABAA-T24 phases are nearly as stable as T12-carbon. Band structure calculations suggest that both AA-T12 and ABAA-T24 are semiconducting with the energy band gaps of 5.68 and $5.33\\ \\mathrm{eV}$ , respectively, which are even larger than that of T12-carbon $(4.56~\\mathrm{eV})$ , indicating that these phases can be highly electrically resistant and optically transparent like those products of cold compressed graphite (41). The bulk moduli of these polymorphs are calculated by fitting the third-order Birch Murnaghan equation of states (42). Although the bulk moduli of AA-T12 (359 GPa) and ABAA-T24 $(380~\\mathrm{GPa})$ are slightly smaller than that of T12- carbon $(403~\\mathrm{GPa})$ , they are comparable with that of cubic BN, suggesting their potential applications in machining. We note that a very recent theoretical work identified the AA-T12 structure by considering its Si analog (43). It is also pointed out that, like T12-carbon, AA-T12 is a universal structure shared by C, Si, Ge, and Sn, suggesting this family of tetragonal structures may be ubiquitous in elemental allotropes of group IVA elements. \n\n![](images/4c24940e25d42f9609d17d3f96d2cdbdec82ecfc997e9a42f64bc99a33088231.jpg) \nFig. 5. (A) Illustration of chiral vectors of penta-tube. Dashed lines with arrows denote the lattice basis vector. (B) Optimized structure of (3, 3) penta-tube from side view, and (C) the corresponding phonon spectra. \n\n![](images/d2e8cfb45b4f6f4e4d8fe4b69e2a0deb6878c04ef3a9351c1f27343dbdaf8b4e.jpg) \nFig. 6. (A) Crystal structure of AA-T12 carbon. (B) AA-T12 viewed from the [001] and [100] directions, and (C) the corresponding phonon spectra. \n\n# Discussion \n\nWe have demonstrated via AIMD simulations that the metastable penta-graphene structure can withstand very high temperature. We note that the experimentally synthesized dodecahedral $\\mathrm{C}_{20},$ the smallest carbon fullerene consisting of only carbon pentagons, is metastable, but possesses outstanding thermal stability (up to $3,000~\\mathrm{K}$ ) (44). These results imply that thermodynamic criteria may not be the deterministic factor in the synthesis of new carbon-based materials. In fact, due to the bonding versatility of carbon, the PES might be fairly complicated with numerous local minima (corresponding to metastable phases) separated from each other by considerable energy barriers. Graphite and cubic diamond are energetically superior to almost all other carbon polymorphs, namely, they correspond to the two lowestlying valleys on the PES. The high-energy barrier between graphite and diamond makes it possible for both graphite and diamond to coexist in nature. However, recent experimental (41) and theoretical (45) advances have identified many intermediate phases between graphite and diamond during cold compression of graphite. Some of these phases are pressure-recovered, i.e., they can exist when the external pressure is removed. This stability is also ascribed to the considerable energy barrier. In fact, even in some surfaces of carbon structures, different structural reconstruction patterns are separated by appreciable kinetic energy barriers (35). These findings highlight the vital role that kinetics (22, 23) plays in carbon structure evolution, and fuel the exploration of new metastable carbon phases as functional materials. \n\nWe now reflect on the relationship between the special atomic configuration and exotic mechanical properties of penta-graphene. When the structure is under uniaxial tension, the expansive lateral response has two kinds of impact on the total energy: on one hand, it elongates the bond and weakens the binding energy; on the other hand, it significantly reduces the difference between the two lattice constants $a$ and $b$ , thus helping the structure to get close to its original tetragonal symmetry, reducing the bond distortion around the $s p^{3}$ -bonded C1 atoms and lowering the strain energy. The structure thus evolves to its equilibrium as a result of compromise between these two competing factors. Detailed illustrations of atom evolution under uniaxial lattice stretch are presented in SI Appendix, text S4. Such regime is reminiscent of an earlier work (46) which argued that the combination of “chemical criteria” and “crystallographic criteria” in carbon materials can lead to exceptional mechanical properties. The ultrahigh critical strain of penta-graphene is also intimately related to its atomic structure. The buckled structure slows down the bond elongation and hence the structure is highly stretchable. Besides, graphene has topologically protected pointlike Fermi surface, and the coupling between the electron states near the Fermi level and certain phonon mode leads to fast phonon softening under biaxial tension (27), whereas penta-graphene does not suffer from Kohn anomaly, because it is semiconducting. \n\nOne practical issue in the synthesis of penta-graphene is how to selectively break the interlayer covalent bonds in T12-carbon (18). To address this challenge, we point to a similar strategy where hydrogen intercalation was successfully used to decouple a graphene layer from the H–SiC (0001) surface (47, 48). Details of our exfoliation scheme are given in SI Appendix, text S5. \n\nIn summary, we showed that a 2D carbon sheet, penta-graphene, composed entirely of pentagons can be obtained by chemically exfoliating a single layer from the T12-carbon phase. Although penta-graphene is energetically metastable compared with graphene, it is dynamically stable and can withstand temperatures up to $1{,}000\\dot{\\bf K}$ . Due to its special atomic configuration, penta-graphene has unusual properties, such as (i) it exhibits NPR, similar to that recently reported in a single-layer black phosphorus sheet (32); $(i i)$ it exhibits ultrahigh ideal strength that can even outperform graphene; (iii) it is semiconducting, thus, there is no need to functionalize penta-graphene for opening the band gap as is the case with graphene. In addition, penta-graphene can be rolled up to form a 1D pentagon-based nanotube that is semiconducting regardless of its chirality. Therefore, there is no need to develop special techniques to separate semiconducting nanotubes from the metallic ones as is the case with conventional carbon nanotubes. Penta-graphene can also be stacked to form 3D stable structures displaying different properties from those of the mother-phase T12-carbon. Thus, penta-graphene sheet not only possesses exotic properties by itself but also can be used to build new structures. We hope that these findings will motivate experimental efforts. Once synthesized, these new carbon allotropes may not only enrich carbon science but also may lead to an untold number of applications. \n\n# Methods \n\nFirst-principles calculations and AIMD simulations within the framework of density functional theory are performed using Vienna Ab initio Simulation Package (VASP) (49). The 2D system is separated from its periodic images by a vacuum distance of $20\\textup{\\AA}$ in the perpendicular direction. Projector augmented wave (PAW) (50) method is used to treat interactions between ion cores and valance electrons. Plane waves with a kinetic energy cutoff of $500~\\mathrm{eV}$ are used to expand the valance electron $(2s^{2}2p^{2})$ wavefunctions. The exchange-correlation potential is incorporated by using the generalized gradient approximation (51) due to Perdew–Burke–Ernzerhof in most of our calculations whereas a hybrid HSE06 (36, 37) functional is used for highaccuracy electronic structure calculations. The first Brillouin zone is represented by K points sampled using the Monkhorst–Pack scheme (52) with a grid density of $2\\uppi\\times0.02\\mathring{\\mathsf{A}}^{-1}$ . For geometry relaxation, the convergence thresholds for total energy and atomic force components are set at $10^{-4}\\mathsf{e V}$ and $10^{-3}\\thinspace{\\tt e V}\\thinspace{\\tt A}^{-1}$ , respectively. In AIMD simulations the convergence criterion of total energy is set as 1 meV. Temperature control is achieved by Nosé thermostat (53). Structure relaxations are performed without any symmetry constraint. Phonon properties are calculated using finite displacement \n\n1. Kroto HW, Heath JR, O’Brien SC, Curl RF, Smalley RE (1985) $\\mathsf{C}_{60}\\mathrm{:}$ Buckminsterfullerene. Nature 318(6042):162–163. \n2. Iijima S, Ichihashi T (1993) Single-shell carbon nanotubes of 1-nm diameter. Nature \n363(6430):603–605. \n3. Novoselov KS, et al. (2004) Electric field effect in atomically thin carbon films. Science \n306(5696):666–669. \n4. Charlier J-C, Rignanese G-M (2001) Electronic structure of carbon nanocones. Phys Rev Lett 86(26):5970–5973. \n5. Jin C, Lan H, Peng L, Suenaga K, Iijima S (2009) Deriving carbon atomic chains from graphene. Phys Rev Lett 102(20):205501. \n6. Li Y, Xu L, Liu H, Li Y (2014) Graphdiyne and graphyne: From theoretical predictions to practical construction. Chem Soc Rev 43(8):2572–2586. \n7. Bucknum MJ, Hoffmann R (1994) A hypothetical dense 3,4-connected carbon net and related $B_{2}C$ and $C N_{2}$ nets built from 1,4-cyclohexadienoid units. J Am Chem Soc \n116(25):11456–11464. \n8. Zhang S, Wang Q, Chen $\\times,$ Jena P (2013) Stable three-dimensional metallic carbon with interlocking hexagons. Proc Natl Acad Sci USA 110(47):18809–18813. \n9. Malko D, Neiss C, Viñes F, Görling A (2012) Competition for graphene: Graphynes with direction-dependent Dirac cones. Phys Rev Lett 108(8):086804. \n10. Mina M, Susumu O (2013) Two-dimensional $s p^{2}$ carbon network of fused pentagons: All carbon ferromagnetic sheet. Appl Phys Express 6(9):095101. \n11. Terrones H, et al. (2000) New metallic allotropes of planar and tubular carbon. Phys Rev Lett 84(8):1716–1719. \n12. Xu L-C, et al. (2014) Two dimensional Dirac carbon allotropes from graphene. Nanoscale 6(2):1113–1118. \n13. Omachi H, Nakayama T, Takahashi E, Segawa Y, Itami K (2013) Initiation of carbon nanotube growth by well-defined carbon nanorings. Nat Chem 5(7):572–576. \n14. Deza M, Fowler PW, Shtogrin M, Vietze K (2000) Pentaheptite modifications of the graphite sheet. J Chem Inf Comput Sci 40(6):1325–1332. \n15. Tan Y-Z, Xie S-Y, Huang R-B, Zheng L-S (2009) The stabilization of fused-pentagon fullerene molecules. Nat Chem 1(6):450–460. \n16. Prinzbach H, et al. (2000) Gas-phase production and photoelectron spectroscopy of the smallest fullerene, $\\mathsf{C}_{20}$ . Nature 407(6800):60–63. \n17. Wang Y, et al. (2011) Template effect in the competition between Haeckelite and graphene growth on Ni(111): Quantum chemical molecular dynamics simulations. J Am Chem Soc 133(46):18837–18842. \n18. Zhao Z, et al. (2012) Tetragonal allotrope of group 14 elements. J Am Chem Soc \n134(30):12362–12365. \n19. Naguib M, Gogotsi Y (2015) Synthesis of two-dimensional materials by selective extraction. Acc Chem Res 48(1):128–135. \n20. Naguib M, et al. (2011) Two-dimensional nanocrystals produced by exfoliation of $\\Gamma\\dot{\\mathsf{i}}_{3}$ ${\\mathsf{A l C}}_{2}$ . Adv Mater 23(37):4248–4253. \n21. Ressouche E, Simonet V, Canals B, Gospodinov M, Skumryev V (2009) Magnetic frustration in an iron-based Cairo pentagonal lattice. Phys Rev Lett 103(26):267204. \n22. Menéndez-Proupin E, Montero-Alejo AL, García de la Vega JM (2012) Ultrathin carbon nanotube with single, double, and triple bonds. Phys Rev Lett 109(10):105501. \n23. Merz KM, Hoffmann R, Balaban AT (1987) 3,4-connected carbon nets: Through-space and through-bond interactions in the solid state. J Am Chem Soc 109(22):6742–6751. \n24. Schmidt CL, Dinnebier R, Wedig U, Jansen M (2007) Crystal structure and chemical bonding of the high-temperature phase of $\\mathsf{A g N}_{3}$ . Inorg Chem 46(3):907–916. \n25. Sheng X-L, Yan Q-B, Ye F, Zheng Q-R, Su G (2011) T-carbon: A novel carbon allotrope. Phys Rev Lett 106(15):155703. \n26. Andrew RC, Mapasha RE, Ukpong AM, Chetty N (2012) Mechanical properties of graphene and boronitrene. Phys Rev B 85(12):125428. \n27. Marianetti CA, Yevick HG (2010) Failure mechanisms of graphene under tension. Phys Rev Lett 105(24):245502. \n\nmethod implemented in Phonopy (54). A $(4\\times4)$ supercell is constructed to calculate the atomic forces by using VASP, with a very high accuracy (stringent energy convergence criteria $10^{-8}$ eV per unit cell). Phonon calculations using a larger supercell $(6\\times6)$ yield consistent results. For phonon calculations in graphene, an $(8\\times8)$ supercell is used, which has been found in previous work (27) to be sufficient to take into account the long-range interatomic interactions. \n\nACKNOWLEDGMENTS. The authors thank the crew of the Center for Computational Materials Science, the Institute for Materials Research, Tohoku University (Japan), for their continuous support of the HITACHSR11000 supercomputing facility. This work is partially supported by grants from the National Natural Science Foundation of China (NSFC-51471004, NSFC-11174014, NSFC10990104, and NSFC-11334008), the National Grand Fundamental Research 973 Program of China (Grant 2012CB921404), and the Doctoral Program of Higher Education of China (20130001110033). S.Z. acknowledges funding from the Graduate School of Peking University that enabled him to visit $\\mathsf{P}.\\mathsf{J}.\\mathsf{'s}$ group at Virginia Commonwealth University, where the present work is partially conducted. P.J. acknowledges support of the US Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award DE-FG02-96ER45579. \n\n28. Si C, Duan W, Liu Z, Liu F (2012) Electronic strengthening of graphene by charge doping. Phys Rev Lett 109(22):226802. \n29. Ding Y, Wang Y (2013) Density functional theory study of the silicene-like SiX and $\\mathsf{x s i}_{3}$ $(\\mathsf{X}=\\mathsf{B}$ , C, N, Al, P) honeycomb lattices: The various buckled structures and versatile electronic properties. J Phys Chem C 117(35):18266–18278. \n30. Lee C, Wei $\\mathsf{x,}$ Kysar JW, Hone J (2008) Measurement of the elastic properties and intrinsic strength of monolayer graphene. Science 321(5887):385–388. \n31. Burns S (1987) Negative Poisson’s ratio materials. Science 238(4826):551. \n32. Jiang J-W, Park HS (2014) Negative Poisson’s ratio in single-layer black phosphorus. Nat Commun 5:4727. \n33. Greaves GN, Greer AL, Lakes RS, Rouxel T (2011) Poisson’s ratio and modern materials. Nat Mater 10(11):823–837. \n34. Schreiner PR, et al. (2011) Overcoming lability of extremely long alkane carbon-carbon bonds through dispersion forces. Nature 477(7364):308–311. \n35. Lu S, Wang Y, Liu H, Miao MS, Ma Y (2014) Self-assembled ultrathin nanotubes on diamond (100) surface. Nat Commun 5:3666. \n36. Heyd J, Scuseria GE, Ernzerhof M (2003) Hybrid functionals based on a screened Coulomb potential. J Chem Phys 118(18):8207–8215. \n37. Heyd J, Scuseria GE, Ernzerhof M (2006) Erratum: “Hybrid functionals based on a screened Coulomb potential.” J Chem Phys 124(21):219906. \n38. Savini G, Ferrari AC, Giustino F (2010) First-principles prediction of doped graphane as a high-temperature electron-phonon superconductor. Phys Rev Lett 105(3):037002. \n39. Charlier J-C, Blase $\\times,$ Roche S (2007) Electronic and transport properties of nanotubes. Rev Mod Phys 79(2):677–732. \n40. Ayala P, Arenal R, Loiseau A, Rubio A, Pichler T (2010) The physical and chemical properties of heteronanotubes. Rev Mod Phys 82(2):1843–1885. \n41. Mao WL, et al. (2003) Bonding changes in compressed superhard graphite. Science 302(5644):425–427. \n42. Murnaghan FD (1944) The compressibility of media under extreme pressures. Proc Natl Acad Sci USA 30(9):244–247. \n43. Nguyen MC, Zhao X, Wang C-Z, Ho K-M (2014) ${\\mathfrak{s p}}^{3}.$ -hybridized framework structure of group-14 elements discovered by genetic algorithm. Phys Rev B 89(18):184112. \n44. Davydov IV, Podlivaev AI, Openov LA (2005) Anomalous thermal stability of metastable $\\mathsf{C}_{20}$ fullerene. Phys Solid State 47(4):778–784. \n45. Niu H, et al. (2012) Families of superhard crystalline carbon allotropes constructed via cold compression of graphite and nanotubes. Phys Rev Lett 108(13):135501. \n46. Blase X, Gillet P, San Miguel A, Mélinon P (2004) Exceptional ideal strength of carbon clathrates. Phys Rev Lett 92(21):215505. \n47. Riedl C, Coletti C, Iwasaki T, Zakharov AA, Starke U (2009) Quasi-free-standing epitaxial graphene on SiC obtained by hydrogen intercalation. Phys Rev Lett 103(24): 246804. \n48. Sołtys J, Piechota J, Ptasinska M, Krukowski S (2014) Hydrogen intercalation of single and multiple layer graphene synthesized on Si-terminated SiC(0001) surface. J Appl Phys 116(8):083502. \n49. Kresse G, Furthmüller J (1996) Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys Rev B Condens Matter 54(16):11169–11186. \n50. Blöchl PE (1994) Projector augmented-wave method. Phys Rev B Condens Matter 50(24):17953–17979. \n51. Perdew JP, Burke K, Ernzerhof M (1996) Generalized gradient approximation made simple. Phys Rev Lett 77(18):3865–3868. \n52. Monkhorst HJ, Pack JD (1976) Special points for Brillouin-zone integrations. Phys Rev B 13(12):5188–5192. \n53. Nosé S (1984) A unified formulation of the constant temperature molecular dynamics methods. J Chem Phys 81(1):511–519. \n54. Togo A, Oba F, Tanaka I (2008) First-principles calculations of the ferroelastic transition between rutile-type and CaCl2-type $\\mathsf{S i O}_{2}$ at high pressures. Phys Rev B 78(13): 134106. " + }, + { + "id": "10.1039_c5ee02608c", + "DOI": "10.1039/c5ee02608c", + "DOI Link": "http://dx.doi.org/10.1039/c5ee02608c", + "Relative Dir Path": "mds/10.1039_c5ee02608c", + "Article Title": "Highly efficient planar perovskite solar cells through band alignment engineering", + "Authors": "Baena, JPC; Steier, L; Tress, W; Saliba, M; Neutzner, S; Matsui, T; Giordano, F; Jacobsson, TJ; Kandada, ARS; Zakeeruddin, SM; Petrozza, A; Abate, A; Nazeeruddin, MK; Grätzel, M; Hagfeldt, A", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "The simplification of perovskite solar cells (PSCs), by replacing the mesoporous electron selective layer (ESL) with a planar one, is advantageous for large-scale manufacturing. PSCs with a planar TiO2 ESL have been demonstrated, but these exhibit unstabilized power conversion efficiencies (PCEs). Herein we show that planar PSCs using TiO2 are inherently limited due to conduction band misalignment and demonstrate, with a variety of characterization techniques, for the first time that SnO2 achieves a barrier-free energetic configuration, obtaining almost hysteresis-free PCEs of over 18% with record high voltages of up to 1.19 V.", + "Times Cited, WoS Core": 1064, + "Times Cited, All Databases": 1117, + "Publication Year": 2015, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000362351700011", + "Markdown": "View Article Online View Journal \n\n# Energy & Environmental Science \n\nAccepted Manuscript \n\nThis article can be cited before page numbers have been issued, to do this please use: J. P. Correa Baena, L. Steier, W. Tress, M. Saliba, S. Neutzner, T. Matsui, F. Giordano, J. Jacobsson, A. R. Srimath Kandada, S. M. Zakeeruddin, A. petrozza, A. Abate, N. Mohammad K., M. Grätzel and A. Hagfeldt, Energy Environ. Sci., 2015, DOI: 10.1039/C5EE02608C. \n\n![](images/038c4213c2d9d07b020a10c415c73d2bef047182ad4beaa7c3be1bf3e7935705.jpg) \n\nThis is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication. \n\nAccepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof reading. Using this free service, authors can make their results available to the community, in citable form, before we publish the edited article. We will replace this Accepted Manuscript with the edited and formatted Advance Article as soon as it is available. \n\nYou can find more information about Accepted Manuscripts in the Information for Authors. \n\nPlease note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. \n\n# Highly Efficient Planar Perovskite Solar Cells through Band Alignment Engineering \n\nJuan Pablo Correa Baena,1\\* Ludmilla Steier,2 Wolfgang Tress,2,3 Michael Saliba,3 Stefanie Neutzner,4 Taisuke Matsui,5 Fabrizio Giordano,2 T. Jesper Jacobsson,1 Ajay Ram Srimath Kandada,4 Shaik M. Zakeeruddin,1,2 Annamaria Petrozza,4 Antonio Abate,2 Mohammad Khaja Nazeeruddin,3 Michael Grätzel,2 and Anders Hagfeldt1\\* \n\n1Laboratory for Photomolecular Science, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne, CH-1015-Lausanne, Switzerland. \n\n2Laboratory for Photonics and Interfaces, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne, CH-1015-Lausanne, Switzerland. \n\n3Group for Molecular Engineering of Functional Materials, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne, CH-1015- Lausanne, Switzerland \n\n4Center for Nano Science and Technology $@$ Polimi, Istituto Italiano di Tecnologia, via Pascoli 70/3 20133 Milano, Italy \n\n5Advanced Research Division, Panasonic Corporation,1006, (Oaza Kadoma), Kadoma City, Osaka 571-8501, Japan. \n\n\\*Corresponding authors: AH anders.hagfeldt@epfl.ch; JPCB juan.correa@epfl.ch. \n\nJPCB and LS contributed equally to this work. \n\nKeywords: Perovskite solar cell, hysteresis, electron selective layers, photovoltaics, $\\mathrm{SnO}_{2}$ , $\\mathrm{TiO}_{2}$ . \n\n# Abstract \n\nThe simplification of perovskite solar cells (PSCs), by replacing the mesoporous electron selective layer (ESL) with a planar one, is advantageous for large-scale manufacturing. PSCs with a planar $\\mathrm{TiO}_{2}$ ESL have been demonstrated, but these exhibit unstabilized power conversion efficiencies (PCEs). Herein we show that planar PSCs using $\\mathrm{TiO}_{2}$ are inherently limited due to a conduction band misalignment and demonstrate, with a variety of characterization techniques, for the first time that $\\mathrm{SnO}_{2}$ achieves a barrier-free energetic configuration, obtaining almost hysteresis-free PCEs of over $18\\%$ with record high voltages up to $1.19\\mathrm{V}$ . \n\n# Energy & Environmental Science \n\n# Introduction \n\nSolution processed, hybrid organic-inorganic perovskite materials were studied by Mitzi et al. in the 1990s and were recognized as excellent semiconducting materials.1 It was not, however, until Miyasaka and coworkers pioneered the work on dye-sensitized solar cell applications in 2009, that the material started to be recognized by the photovoltaic community.2 Since then, a myriad of works has been published exploring different device configurations. The currently highest reported PCE value of over $20\\%$ was achieved using a thin layer of mesoporous $\\mathrm{TiO}_{2}$ .3 In this architecture, the perovskite material, infiltrates a mesoporous $\\mathrm{TiO}_{2}$ layer which is sandwiched between a hole transporting layer (HTL, typically doped $^{2,2^{\\circ},7,7^{\\circ}}$ -tetrakis( $\\mathrm{R},N^{\\prime}$ -di-p-methoxyphenylamine)-9,9’- spirobifluorene (Spiro-OMeTAD)\t\n   or polytertiary arylamine (PTAA)) and an electron selective layer (ESL, typically $\\mathrm{TiO}_{2}$ ). \n\nFrom the earlier works, it was realized that the perovskite absorber material transports both holes and electrons.4-6 Naturally, this led towards the investigation of a thin film perovskite configuration with only a compact $\\mathrm{TiO}_{2}$ as the ESL.7 However, this device architecture shows pronounced hysteresis of the current voltage (J-V) curve,8-10 especially for fast voltage sweeps and to our knowledge no PCE of over $18\\%$ in this architecture has been reported without hysteresis and stabilized power output. Xing et al. showed that planar devices using PCBM as the ESL and methyl ammonium lead iodide (MAPbI3) as the absorbing and transporting material, had a much improved J-V hysteretic behaviour when compared to $\\mathrm{TiO}_{2}$ ESL, which they linked to the improved interfacial charge transfer. Wojciechowski and co-workers showed that modifying the $\\mathrm{TiO}_{2}$ surface with fullerene derivatives can work towards high efficiency PSCs.8 Recent works have shown the potential of $\\mathrm{SnO}_{2}$ -based ESLs,11-14 but so far these devices have not shown high efficiency without hysteretic behaviour. \n\nUsing a low temperature atomic layer deposition (ALD) process to fabricate $\\mathrm{SnO}_{2}$ ESLs, we demonstrate that planar PSCs can achieve almost hysteresis-free of above $18\\%$ with voltages exceeding 1.19 V. We show that this is not the case for the planar $\\mathrm{TiO}_{2}$ . We choose $\\mathrm{SnO}_{2}$ considering the favourable alignment of the conduction bands of the perovskite materials and the ESL and show an energy mismatch in the case of $\\mathrm{TiO}_{2}$ . Thus, using $\\mathrm{SnO}_{2}$ , which has a deeper conduction band, enables us to fabricate planar devices with high efficiencies, long term air stability and improved hysteretic behaviour, while keeping the processing at low temperatures $(<120~^{\\circ}\\mathrm{C})$ , which is key for process upscaling and high efficiency tandem devices.15 \n\n![](images/e9c197dce6e1aca578454620dbf9b2f8c5664bc02decb1ed48c58cada23cd3be.jpg) \n\nFigure 1. Energy level diagrams and electron injection characteristics of $\\mathrm{SnO}_{2}$ and $\\mathrm{TiO}_{2}.$ - based planar PSCs. a, Schematic energy level diagram of the perovskite films and the electron selective layers, $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ for b, MAPbI3 and c, $\\mathrm{(FAPbI_{3})_{0.85}(M A P b B r_{3})_{0.15}},$ labeled as ‘mixed’. \n\n# Results and Discussion \n\n# Energy & Environmental Science \n\nIn Figure 1a, we illustrate how electron injection is energetically hindered when the bands are mismatched. This is accompanied by a schematic of the planar device architecture of a typical glass/FTO/compact metal oxide/perovskite/hole transporter/gold stack. We analyse the band structure further using ultraviolet photoelectron spectroscopy (UPS) for two different perovskite materials (MAPbI3 and mixed halide/cation, i.e. $\\mathrm{(FAPbI_{3})_{0.85}(M A P b B r_{3})_{0.15}}$ , referred to as mixed perovskite throughout the text) atop the $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ as shown in Figure 1b and c as derived from Supplementary Figures S1 and S2, respectively. The ionization energy (IE), e.i. valence band position, measurements of the $\\mathrm{SnO}_{2}$ and $\\mathrm{TiO}_{2}$ were performed for the UV ozone-treated samples atop FTO, thus obtaining the valence band information for both substrates. It has been shown that the valence band position of the perovskite material measured by UPS has variations with respect to the substrate where they are deposited.16 Thus, we performed our measurements on perovskite films deposited on both $\\mathrm{SnO}_{2}$ and $\\mathrm{TiO}_{2}$ yielding IE differences of above 0.1 eV. We calculated the band diagram of the different components using the perovskite materials’ valence bands as our reference. The construction of the band diagram, including bandgap estimation for the perovskite materials (thickness of ca. $400\\ \\mathrm{nm},$ , is described in the Supplementary Figure S1-3. We found that for both perovskite materials there is a conduction band misalignment with $\\mathrm{TiO}_{2}$ ESLs, in stark contrast to $\\mathrm{SnO}_{2}$ where we have no such misalignment. The band diagram in Figure 1b, shows that the conduction band of MAPbI3 is ${\\sim}80\\ \\mathrm{meV}$ below than that of $\\mathrm{TiO}_{2}$ and about $170\\ \\mathrm{meV}$ above that of $\\mathrm{SnO}_{2}$ . This inhibits electron extraction by the $\\mathrm{TiO}_{2}$ and facilitates it using $\\mathrm{SnO}_{2}$ . Similarly, the conduction band of the mixed perovskite is 300 meV below compared to $\\mathrm{TiO}_{2}$ and only $30\\mathrm{meV}$ below compared to $\\mathrm{SnO}_{2}$ . Consequently, this band misalignment with $\\mathrm{TiO}_{2}$ may cause undesirable consequences such as accumulation of photogenerated charges, which could hamper the device performance. \n\nIt is important to note that the UPS measurements were carried out on perovskite films as thick as $400\\ \\mathrm{nm}$ . Since UPS is a surface measurement (measuring roughly the conditions in the first $10\\mathrm{nm}$ ), it is therefore a simplified picture our device energetics. Guerrero et al. have shown that the energetics throughout the perovskite film can be different and that bandbending can be induced when employing thick films.17 In addition, work by some of us has also shown that ion migration is induced in the perovskite material,18 which further complicates the energetic model in the device. Indeed, these two factors play a major role in the electronic configuration of the device and it is something that will be further investigated more in depth in future studies. However, with these measurements we elucidate that there is an intrinsic difference between the two ESL, which lead to understand that there is an energetic barrier at the $\\mathrm{TiO}_{2}$ , but not at the $\\mathrm{SnO}_{2},$ /Perovskite interface. \n\n![](images/0b3326720cf27adf182dc1b5684a8e37cb6b8b7929f96f3e440f6b8ae0a9a8e7.jpg) \nFigure 2. Photovoltaic device architecture and elemental composition of the electron selective layers (ESLs). a, Cross-sectional scanning electron micrograph of a typical \n\n# Energy & Environmental Science \n\nlayered photovoltaic device composed of FTO, $\\mathrm{SnO}_{2}$ as the electron selective layer (ESL), the perovskite film, a hole transporting layer (HTL, Spiro MeOTAD), and a gold top electrode. b, X-ray photoelectron spectroscopy of $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ thin layers used as ESLs. \n\nTo further investigate this phenomenon, we prepared planar devices of typical stack architecture: glass/FTO/ESL/perovskite/HTL/gold contact as seen in the cross-sectional scanning electron microscopy (SEM) image in Figure 2a. We deposited a $15\\ \\mathrm{nm}$ thick ESL of $\\mathrm{SnO}_{2}$ , $\\mathrm{TiO}_{2}$ or $\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ by ALD. The mixed perovskite layer, $\\mathrm{(FAPbI_{3})_{0.85}(M A P b B r_{3})_{0.15}}$ , was spin-coated on the electrode using a similar composition as reported by Jeon et al.19 A doped spiro-MeOTAD was spin-coated as the HTL and, finally, the gold top electrode was deposited by thermal evaporation. \n\nFigure 2b shows the $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) of the $15\\ \\mathrm{nm}$ thick $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ layers. For $\\mathrm{TiO}_{2}$ , no peaks other than oxygen O 1s at $528~\\mathrm{eV}$ , titanium Ti 2p at $458.5\\ \\mathrm{eV}$ and Ti $2{\\tt p}_{1/2}$ 464.2 eV were detected confirming the deposition of $\\mathrm{TiO}_{2}$ without traces of cross contamination.20 We detect no signal from the underlying FTO indicating conformal and pinhole-free $\\mathrm{TiO}_{2}$ coverage, which we further confirm by SEM (see Supplementary Figure S4a). Similarly, we confirm the formation of pure $\\mathrm{SnO}_{2}$ observing the oxygen peak O 1s at $530.9\\mathrm{eV}$ and $\\mathrm{Sn}^{4+}$ peaks at $495.6\\mathrm{eV}$ as well as at $487.2\\mathrm{eV}$ . The top-view SEM image also indicates a pinhole-free deposition of $\\mathrm{SnO}_{2}$ (see Supplementary Figure S4b). \n\n![](images/ce65c8c0fd796990208f7af1f359e21a37f17625268b9ce87aafc20e6d5e2fa4.jpg) \nFigure 3. Transient absorption measurements of $\\mathrm{SnO}_{2}$ and $\\mathrm{TiO}_{2}$ -based planar PSCs. \n\nDynamics of the photo-bleaching bands for photo-excited perovskite measured on a typical working device employing the mixed perovskite $\\mathrm{(FAPbI_{3})_{0.85}(M A P b B r_{3})_{0.15}}$ and $\\mathrm{SnO}_{2}$ or $\\mathrm{TiO}_{2}$ as the ESL. The device is held at short circuit condition during the measurement. The probe wavelength is $\\lambda=750\\mathrm{{nm}}$ . \n\nIn order to further understand the results by UPS in a device configuration we performed femtosecond transient absorption (TA) measurements. With this we intended to understand electron injection dynamics from the perovskite into the ESLs, and therefore, indirectly probe whether an energetic barrier exists for $\\mathrm{TiO}_{2}$ or $\\mathrm{SnO}_{2}$ . The measurements were performed on devices with $\\mathrm{SnO}_{2}$ and $\\mathrm{TiO}_{2}$ and the mixed perovskite under short circuit condition, wherein the charge injection can be resolved in time. In Figure 3, we show the TA dynamics taken at a probe wavelength of $750\\ \\mathrm{nm}$ - the peak of the photobleach (PB) of the perovskite. The PB band, spectrally located at the onset of the absorption spectrum of the semiconductor (Supplementary Figure S3), corresponds to the \n\n# Energy & Environmental Science \n\nphoto-induced transparency in the material due to the presence of electrons and holes in the bottom and top of the conduction and valence bands, respectively.17 Hence, the magnitude of this feature is correlated to the photo-induced carrier population and every effect changing the initial population, like electron/hole injection results in its quenching. We observe a PB decay in the nanosecond timescale for both $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ -based devices. However, while in the $\\mathrm{TiO}_{2}$ -based device the dynamic does not strongly differ from the one probed from the pristine perovskite deposited on bare glass,21 in the case of $\\mathrm{SnO}_{2}$ the decay is much faster. In fact, about $60\\%$ of the population is gone in about 1.5 ns. As both devices embody the same hole extracting layer, we conclude that the striking difference observed can be considered as the signature of different electron injection dynamics. This strongly supports our hypothesis of better electron extraction in pristine $\\mathrm{SnO}_{2}$ when compared to $\\mathrm{TiO}_{2}$ -based devices, due to favorable energetic alignment. \n\nWe note that the poor charge extraction in the $\\mathrm{TiO}_{2}$ based device may appear surprising. However, it must be considered that, in thin film PSCs in presence of planar $\\mathrm{TiO}_{2}$ as electron extracting layer, solar cells generally show $J_{\\mathrm{SC}}$ comparable to those using a mesoporous $\\mathrm{TiO}_{2}$ layer only when the device is pre-polarized.8, 9, 22-24 Indeed, some of us have recently demonstrated that the PB dynamics becomes faster when it is measured just after keeping the $\\mathrm{TiO}_{2}$ -based device at $1\\mathrm{\\DeltaV}$ for a few seconds, suggesting that the electron transfer is suddenly activated.23 This indicates that upon polarization, the $\\mathrm{TiO}_{2}/$ /perovskite interface is modified and such modification is needed to allow for an efficient charge transfer as also predicted by De Angelis et al.25 \n\n![](images/7c64d5de70f1be0e81778a05e9baa98ecd26e45b71f8617a2eec97b4129e4cb6.jpg) \nFigure 4. Photovoltaic characteristics of planar perovskite devices based on $\\mathrm{SnO}_{2}$ and \n\n$\\mathrm{TiO}_{2}$ ESL. a, Current-voltage properties of $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ -based planar mixed halide/cation perovskite devices. Black arrows indicate backward scan from $\\mathrm{V_{oc}}$ to $\\mathrm{J_{sc}}$ and red arrows indicate the reversed scan. b, Normalized transient photocurrents measured from $\\mathrm{V_{OC}}$ to maximum power point voltage for both planar systems. c, Scan rate effects on J-V characteristics of $\\mathrm{SnO}_{2}$ and $\\mathbf{d}$ , $\\mathrm{TiO}_{2}$ -based devices. We note that devices showed best performance when measured after 1 week of preparation. \n\nWe investigated the different electronic properties of devices with $\\mathrm{TiO}_{2}$ or $\\mathrm{SnO}_{2}$ ESLs by analyzing the current density-voltage curves based on the mixed perovskite. In Figure 4a, \n\n# Energy & Environmental Science \n\nwe observe a representative $\\mathrm{SnO}_{2}$ device with high performance and low hysteresis between the backward and forward scan (Table 1). This is indicative of good charge collection independent of voltage. In stark contrast, a representative $\\mathrm{TiO}_{2}$ -based device shows strong hysteresis and low current densities $(<5\\mathrm{\\mA\\cm^{-2}},$ ). This difference can also be seen in Figure 4b where we show transient photocurrents recorded at $0.8\\mathrm{V}$ resembling closely operating device conditions at maximum power point. After ${\\sim}50~\\mathrm{s}$ , we observe a steady photocurrent when switching from open circuit to $0.8\\mathrm{~V~}$ . After switching from open circuit to $0.8\\mathrm{V}$ , the current for the $\\mathrm{TiO}_{2}$ device drops by $70\\%$ from 10 to a stabilized $3\\mathrm{\\mA\\cm^{-2}}$ , whereas that for the $\\mathrm{SnO}_{2}$ drops by only $10\\%$ from 23 to a stabilized $20.2\\mathrm{\\mA}\\mathrm{cm}^{-2}$ . The stabilized current is in good agreement with the current seen in the J-V curve at $0.8\\mathrm{V}$ , which is found to be $20.7\\mathrm{mAcm^{-2}}$ (Figure 4a). In addition, $\\mathrm{SnO}_{2}$ -based devices showed good long-term stability; unencapsulated devices stored in dry air were measured for over 30 days with no significant PCE variability (Supplementary Figure S5). Small variations were found for 12 devices made in different batches with an average PCE of $16.7\\%$ (Supplementary Figure S6). Integrating the external quantum efficiency (EQE) yielded a $J_{S C}$ of $18\\mathrm{mA}\\mathrm{cm}^{-2}$ (Figure S7a), which is in very good agreement with the measured $J_{S C}$ in Figure S7b. \n\nTable\t\n   1.\t\n   Solar\t\n   cell\t\n   performance\t\n   parameters\t\n   for\t\n   the\t\n   mixed\t\n   perovskite\t\n   and $\\mathsf{S n O}_{2}$ device\t\n   for\t\n   backward\t\n   and\t\n   forward\t\n   scans\t\n   at\t\n   a\t\n   scan\t\n   rate\t\n   of $10\\ \\mathrm{mV}/s$ :\t\n   short\t\n   circuit photocurrent $(\\mathrm{J}_{\\mathrm{sc}})$ ,\t\n  power\t\n  conversion\t\n  efficiency\t\n  (PCE),\t\n  open\t\n  circuit\t\n  voltage $(\\mathrm{V_{oc}})$ ,\t\n   fill factor\t\n  (FF)\t\n  as\t\n  extracted\t\n  from\t\n  the\t\n  data\t\n  in\t\n  Figure\t\n  3a. \n\n
ESLScanJscVocFFPCELight intensity
\n\n
direction(mA cm-2)(V)(%)(mW cm-2)
SnO2backward21.31.14 0.7418.4
forward21.21.13 0.7518.198.4
\n\nWe note that for both $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ , we observe open circuit voltages of around $1.14\\mathrm{V}_{;}$ , which are close or even exceeds most devices prepared with mesoporous interlayers. Additionally, some of our $\\mathrm{SnO}_{2}$ devices yielded stabilized voltages of over 1.19 V (Supplementary Figure S7c) approaching the thermodynamic maximum $\\mathrm{\\DeltaV_{oc}}$ of approx. 1.32 V.26 This suggests exceptionally good charge selectivity and a low degree of charge recombination in our planar perovskite $/\\mathrm{SnO}_{2}$ devices. \n\nTo understand the reason for the reduced photocurrent for the $\\mathrm{TiO}_{2}$ based device, we performed current-voltage scans at varied voltage sweep rates. These are shown in Figure 4c and d, where only the backward scan is plotted which is obtained after the device was preconditioned at $1.2\\mathrm{V}$ for $10~\\mathrm{s}$ . For the $\\mathrm{SnO}_{2}$ device there is only a slight increase of the photocurrent when increasing the rate from 10 to $10000\\mathrm{mV/s}$ . Slightly enhanced sweep rates allow to collect almost all the photogenerated charges reaching a maximum $J_{S C}$ density of $23\\mathrm{\\mA\\cm^{-2}}$ . The dependence on scan rate is much more pronounced for the $\\mathrm{TiO}_{2}$ -based device showing high current densities of ca. $20\\mathrm{\\mA\\cm^{-2}}$ for the scan at $10\\mathrm{V/s}$ with a massive drop to about $5\\mathrm{mA}\\mathrm{cm}^{-2}$ when scanned at $10\\mathrm{mV/s}$ . This implies a low charge collection efficiency in the planar perovskite $\\mathrm{TiO}_{2}$ device at slow scan rates, though light absorption and photocurrent generation in the perovskite material is the same as for the perovskite $\\mathrm{\\DeltaSnO}_{2}$ configuration. The results are also in good agreement with the transient photocurrent in Figure 4b, the electron injection characteristics in Figure 3 and \n\n# Energy & Environmental Science \n\nour proposed band alignment measured by UPS in Figure 1, clearly indicating a barrier free charge transport across the perovskite $\\mathrm{SnO}_{2}$ in contrast to the perovskite $\\mathrm{\\TiO}_{2}$ interface. We investigated devices with ALD ${\\mathrm{Nb}}_{2}{\\mathrm{O}}_{5}$ as the ESL (Supplementary Figure S8) which has a similar conduction band position as $\\mathrm{TiO}_{2}$ .27 With this, we can crosscheck if the energy level alignment is indeed critical for high hysteresis and can exclude that other properties of the $\\mathrm{SnO}_{2}$ or $\\mathrm{TiO}_{2}$ are responsible for the above results. Very similar to $\\mathrm{TiO}_{2}$ , the ${\\bf N b}_{2}{\\bf O}_{5}$ -based devices exhibited large hysteresis behavior and very low photocurrent densities (Supplementary Figure S8). Several independent studies have shown similar or even more pronounced trends irrespective of $\\mathrm{TiO}_{2}$ deposition method. Spin-coating,8, 9, 23, 28-30 Sputtering30, 31 and spray pyrolysis32 of $\\mathrm{TiO}_{2}$ have all been demonstrated to yield highly hysteretic J-V curves in planar PSCs. \n\nTo further confirm what is found in the literature and show that our results are not unique to the ALD technique, we prepared $\\mathrm{TiO}_{2}$ by spray pyrolysis and found that the J-V curves exhibit strong hysteretic behavior (Supplementary Figure S9). In this case, the forward scan shows an s-shaped J-V curve indicative of unstabilized power output.33 However, the devices using spray-pyrolysed $\\mathrm{TiO}_{2}$ showed an increase in the $J_{s c}$ in the backward scan when compared to ALD $\\mathrm{TiO}_{2}$ . In order to understand the difference between these two layers, we investigated the effect of the ESLs using spiro and gold only. The perovskite-free devices were investigated in reverse bias to understand whether the ESLs suffer from pinholes. Our results, summarized in Supplementary Figure S10, show improved blocking properties for the ALD layers of both $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ when compared to spray pyrolysed $\\mathrm{TiO}_{2}$ . This difference likely explains the cause of increased photocurrent of the latter, which, we see in Supplementary Figure S9. \n\nA similar trend was found for planar devices using $\\mathbf{MAPbI}_{3}$ (Supplementary Figure S11). Here, the current densities measured are slightly higher in the backward but lower in the forward scan, suggesting the same limitation for charge extraction as noted above. This also matches our UPS results in Figure 1b, where the conduction bands of perovskite and $\\mathrm{TiO}_{2}$ are misaligned and highlights the importance of correct band alignment in all planar perovskite devices. Other works3, 19 have shown high performance at stabilized currents in thin mesoporous $\\mathrm{TiO}_{2}$ based ESLs, and we note that this may be due to a proper band alignment intrinsic to the mesoporous $\\mathrm{TiO}_{2}$ /Perovskite interface which is different from the planar configuration with the $\\mathrm{TiO}_{2}$ used in this study. \n\nWe hypothesize that the preconditioning under forward bias leads to accumulation of negative charge and ion migration at the ESL-perovskite interface inducing a high electric field and/or dipole formation at this interface.10, 22 An elevated electric field or possibly a reduced conduction band offset can facilitate electron injection into the ESL. After releasing the positive bias, this beneficial effect lasts for a few seconds only, which is the time needed for this charge to be removed. Sweep rates in this time range give rise to large hysteresis. For the $\\mathrm{SnO}_{2}$ devices, the energy levels are already well aligned without biasing the device. Thus, charge collection is efficient showing high FF and $J_{\\mathrm{sc}}$ independent of the scan rate (Figure 4c). \n\n# Conclusions \n\nIn summary, we have demonstrated that a barrier-free band alignment between the perovskite light harvester and the charge selective contact is of great importance for an efficient PSC. We found that planar PSCs employing the compact and pinhole- free semi \n\n# Energy & Environmental Science \n\ncrystalline $\\mathrm{TiO}_{2}$ layer made by ALD exhibit a band misalignment, leading to strong hysteresis behavior and scan rate dependent current densities, indicating capacitive effects at the interface. We chose a layer of $\\mathrm{SnO}_{2}$ , due to its deeper conduction band, as the electron selective contact, which achieved voltages and PCEs exceeding $1.19{\\mathrm{~V~}}$ and $18\\%$ , respectively. We proved that modifying the conduction band of the ESL can result in planar, high performance PSCs with high voltages and remarkably good stability over time. Furthermore, femtosecond TA measurements clearly show that the mixed $\\mathrm{(FAPbI_{3})_{0.85}(M A P b B r_{3})_{0.15}}$ perovskite materials extract charges efficiently into $\\mathrm{SnO}_{2}$ but not into $\\mathrm{TiO}_{2}$ corroborating the band misalignment at the $\\mathrm{TiO}_{2},$ /perovskite interface. From this we can conclude that a barrier-free charge transport across the $\\mathrm{SnO}_{2}/$ perovskite interface gives rise to the high and stable current densities – regardless of sweep rate – which are not observed in $\\mathrm{TiO}_{2}$ based devices. This study highlights the importance of a perfect band alignment for highly efficient PSCs, especially in planar devices with compact charge selective layers. \n\n# Methods \n\n# Electron selective layer preparation \n\n$\\mathrm{F}{:}\\mathrm{SnO}_{2}$ substrates were first wiped with acetone, and then cleaned for $10\\mathrm{min}$ in piranha solution $\\mathrm{(H_{2}S O_{4}/H_{2}O_{2}=3{:}l)}$ followed by $10\\ \\mathrm{min}$ in a plasma cleaner prior to ALD deposition. \n\nAtomic layer deposition (ALD) of semi-crystalline $\\mathrm{TiO}_{2}^{34}$ was carried out in a Savannah ALD 100 instrument (Cambridge Nanotech Inc.) at $120^{\\circ}\\mathrm{C}$ using tetrakis(dimethylamino)titanium(IV) (TDMAT, $99.999\\%$ pure, Sigma Aldrich) and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . TDMAT was held at $75^{\\circ}\\mathrm{C}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ at room temperature. The growth rate was $0.07\\mathrm{nm}/\\$ cycle at a $\\Nu_{2}$ flow rate of 5 sccm as measured by ellipsometry. \n\n$\\mathrm{SnO}_{2}$ was deposited at $118^{\\circ}\\mathrm{C}$ using Tetrakis(dimethylamino)tin(IV) (TDMASn, $99.99\\%$ - Sn, Strem Chemicals INC) and ozone at a constant growth rate of $0.065\\mathrm{nm/c}$ ycle measured by ellipsometry. TDMASn was held at $65~^{\\circ}\\mathrm{C}$ . Ozone was produced by an ozone generator ((AC-2025, IN USA Incorporated) fed with oxygen gas $(99.9995\\%$ pure, Carbagas) producing a concentration of $13\\%$ ozone in $\\mathrm{O}_{2}$ . Nitrogen was used as a carrier gas $(99.9999\\%$ pure, Carbagas) with a flow rate of 10 sccm. \n\n$\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ was deposited at $170^{\\circ}\\mathrm{C}$ and a carrier gas flow rate of 20 sccm using (tertbutylimido)bis(diethylamino)Niobium (TBTDEN, Digital Specialty Chemicals, Canada) and ozone with a constant growth rate of $0.06\\mathrm{nm}$ /cycle. TBTDEN was held at $130^{\\circ}\\mathrm{C}$ . \n\n# Perovskite precursor solution and film preparation \n\nBefore perovskite deposition, the ALD layers were treated with UV ozone for $10~\\mathrm{min}$ to remove by-products from the deposition process. The perovskite films were deposited \n\n# Energy & Environmental Science \n\nfrom a precursor solution containing FAI (1 M), $\\mathrm{PbI}_{2}$ (1.1 M, TCI Chemicals), MABr $(0.2\\mathrm{M})$ and $\\mathrm{Pb}{\\mathrm{Br}}_{2}$ $\\mathrm{~\\sc~\\cdot~}0.2\\mathrm{~M~}$ , AlfaAesar) in anhydrous DMF:DMSO 4:1 (v:v, Acros). The perovskite solution was spin-coated in a two-step program; first at 1000 for 10 s and then at $4000~\\mathrm{rpm}$ for $30~\\mathrm{s}$ . During the second step, $100\\upmu\\mathrm{L}$ of chlorobenzene were poured on the spinning substrate $15\\mathrm{~s~}$ prior the end of the program. The substrates were then annealed at $100^{\\circ}\\mathrm{C}$ for $^{1\\mathrm{h}}$ in a nitrogen filled glove box. \nThe spiro-OMeTAD (Merck) solution ( $70~\\mathrm{mM}$ in chlorobenzene) was spun at $4000\\ \\mathrm{rpm}$ for 20 s. The spiro-OMeTAD was doped at a molar ratio of 0.5, 0.03 and 3.3 with bis(trifluoromethylsulfonyl)imide lithium salt (Li-TFSI, Sigma Aldrich), tris(2-(1Hpyrazol-1-yl)-4-tert-butylpyridine)- cobalt(III) tris(bis(trifluoromethylsulfonyl)imide) (FK209, Dyenamo) and 4-tert-Butylpyridine (TBP, Sigma Aldrich), respectively.22, 35, 36 As a last step $70{-}80\\ \\mathrm{nm}$ of gold top electrode were thermally evaporated under high vacuum. \n\n# Solar cell characterization \n\nA\t\n   ZEISS\t\n   Merlin\t\n   HR-­‐SEM\t\n   was\t\n   used\t\n   to\t\n   characterize\t\n   the\t\n   morphology\t\n   of\t\n   the\t\n   device\t\n   crosssection.\t\n   \t\n   The solar cells were measured using a 450 W xenon light source (Oriel). The spectral mismatch between AM 1.5G and the simulated illumination was reduced by the use of a Schott K113 Tempax filter (Präzisions Glas & Optik GmbH). The light intensity was calibrated with a Si photodiode equipped with an IR-cutoff filter (KG3, Schott) and it was recorded during each measurement. Current-voltage characteristics of the cells were obtained by applying an external voltage bias while measuring the current response with a digital source meter (Keithley 2400). The voltage scan rate was $10\\mathrm{mVs^{-1}}$ and no device preconditioning was applied before starting the measurement, such as light soaking or forward voltage bias applied for long time. The starting voltage was determined as the potential at which the cells furnished $1\\ \\mathrm{mA}$ in forward bias, no equilibration time was used. The cells were masked with a black metal mask limiting the active area to $0.16\\mathrm{cm}^{2}$ and reducing the influence of the scattered light. It is important to note that the devices achieved the highest hysteresis-free efficiency after 1 week of preparation. \n\nThe EQE spectra were measured under constant white light bias with an intensity of $10\\mathrm{mW}\\mathrm{cm}^{-2}$ supplied by a LED array. The superimposed monochromatic light was chopped at $2\\ \\mathrm{\\Hz}$ . The homemade system comprises a 300 W Xenon lamp (ICL Technology), a Gemini-180 double-monochromator with 1200 grooves/mm grating (Jobin Yvon Ltd) and a lock-in amplifier (SR830 DSP, Stanford Research System). The EQE integration was performed according to the following equation \n\n$$\nJ_{s c}=\\int_{\\lambda_{1}}^{\\lambda_{2}}\\boldsymbol{q}\\cdot\\boldsymbol{\\phi}\\cdot E Q E d\\lambda\n$$ \n\nwith $\\lambda$ being the wavelength, $q$ the elementary charge and $\\phi$ the photon flux calculated from the ratio of the AM1.5 G spectral irradiance and the photon energy. \n\n# Energy & Environmental Science \n\n# Acknowledgements \n\nUPS and XPS were performed at the Advanced Research Division, Panasonic Corporation in Japan. HR-SEM images were taken at the Centre for Electron Microscopy (CIME) at EPFL. L.S. acknowledges support from the European FP7 FET project PHOCS (no. 309223). A.A. has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 291771. W.T., M.S. and M.K.N. thank the European Union for funding within the Seventh Framework Program (FP7/2007-2013) under grant agreement $\\mathrm{n}^{\\circ}604032$ of the MESO project. \n\n# Author contributions \n\nJ.P.C.B. developed the basic concept and coordinated the project. ALD layers were prepared by J.P.C.B. and L.S. Devices were prepared by J.P.C.B., A.A., M.S., T.M. and F.G. Measurements were performed by J.P.C.B., L.S., W.T., A.A., M.S., T.M., F.G., S.N. and A.R.S.K. A.P supervised the femtosecond spectroscopy measurements. S.M.Z., A.A., M.K.N and M.G. contributed with fruitful discussions. A.H. supervised the project. All authors contributed to the writing of the paper. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to A.H. or J.P.C.B. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. \n\n# Energy & Environmental Science \n\n# References \n\n1. C.\t\n  R.\t\n  Kagan,\t\n  D.\t\n  B.\t\n  Mitzi\t\n  and\t\n  C.\t\n  D.\t\n  Dimitrakopoulos,\t\n  Science,\t\n  1999,\t\n  286,\t\n  945-­‐ 947. \n2. A.\t\n  Kojima,\t\n  K.\t\n  Teshima,\t\n  Y.\t\n  Shirai\t\n  and\t\n  T.\t\n  Miyasaka,\t\n  Journal\t\n  of\t\n  the\t\n  American Chemical\t\n  Society,\t\n  2009,\t\n  131,\t\n  6050-­‐6051. \n3. W.\t\n  S.\t\n  Yang,\t\n  J.\t\n  H.\t\n  Noh,\t\n  N.\t\n  J.\t\n  Jeon,\t\n  Y.\t\n  C.\t\n  Kim,\t\n  S.\t\n  Ryu,\t\n  J.\t\n  Seo\t\n  and\t\n  S.\t\n  I.\t\n  Seok,\t\n  Science, 2015. \n4. M.\t\n  M.\t\n  Lee,\t\n  J.\t\n  Teuscher,\t\n  T.\t\n  Miyasaka,\t\n  T.\t\n  N.\t\n  Murakami\t\n  and\t\n  H.\t\n  J.\t\n  Snaith,\t\n  Science, 2012,\t\n  338,\t\n  643-­‐647. \n5. L.\t\n  Etgar,\t\n  P.\t\n  Gao,\t\n  Z.\t\n  Xue,\t\n  Q.\t\n  Peng,\t\n  A.\t\n  K.\t\n  Chandiran,\t\n  B.\t\n  Liu,\t\n  M.\t\n  K.\t\n  Nazeeruddin\t\n  and M.\t\n  Grätzel,\t\n  Journal\t\n  of\t\n  the\t\n  American\t\n  Chemical\t\n  Society,\t\n  2012,\t\n  134,\t\n  17396-­‐17399. \n6. S.\t\n  D.\t\n  Stranks,\t\n  G.\t\n  E.\t\n  Eperon,\t\n  G.\t\n  Grancini,\t\n  C.\t\n  Menelaou,\t\n  M.\t\n  J.\t\n  Alcocer,\t\n  T.\t\n  Leijtens,\t\n  L. M.\t\n  Herz,\t\n  A.\t\n  Petrozza\t\n  and\t\n  H.\t\n  J.\t\n  Snaith,\t\n  Science,\t\n  2013,\t\n  342,\t\n  341-­‐344. \n7. M.\t\n  Liu,\t\n  M.\t\n  B.\t\n  Johnston\t\n  and\t\n  H.\t\n  J.\t\n  Snaith,\t\n  Nature,\t\n  2013,\t\n  501,\t\n  395-­‐398. \n8. K.\t\n  Wojciechowski,\t\n  S.\t\n  D.\t\n  Stranks,\t\n  A.\t\n  Abate,\t\n  G.\t\n  Sadoughi,\t\n  A.\t\n  Sadhanala,\t\n  N. Kopidakis,\t\n  G.\t\n  Rumbles,\t\n  C.-­‐Z.\t\n  Li,\t\n  R.\t\n  H.\t\n  Friend\t\n  and\t\n  A.\t\n  K.-­‐Y.\t\n  Jen,\t\n  ACS\t\n  nano,\t\n  2014,\t\n  8, 12701-­‐12709. \n9. K.\t\n  Wojciechowski,\t\n  T.\t\n  Leijtens,\t\n  S.\t\n  Spirova,\t\n  C.\t\n  Schlueter,\t\n  M.\t\n  Hoerantner,\t\n  J.\t\n  T.-­‐W. Wang,\t\n  C.-­‐Z.\t\n  Li,\t\n  A.\t\n  K.\t\n  Y.\t\n  Jen,\t\n  T.-­‐L.\t\n  Lee\t\n  and\t\n  H.\t\n  J.\t\n  Snaith,\t\n  The\t\n  Journal\t\n  of\t\n  Physical Chemistry\t\n  Letters,\t\n  2015. \n10. Y.\t\n  Zhang,\t\n  M.\t\n  Liu,\t\n  G.\t\n  E.\t\n  Eperon,\t\n  T.\t\n  C.\t\n  Leijtens,\t\n  D.\t\n  McMeekin,\t\n  M.\t\n  Saliba,\t\n  W.\t\n  Zhang, M.\t\n  de\t\n  Bastiani,\t\n  A.\t\n  Petrozza,\t\n  L.\t\n  M.\t\n  Herz,\t\n  M.\t\n  B.\t\n  Johnston,\t\n  H.\t\n  Lin\t\n  and\t\n  H.\t\n  J.\t\n  Snaith, Materials\t\n  Horizons,\t\n  2015,\t\n  2,\t\n  315-­‐322. \n11. W.\t\n  Ke,\t\n  G.\t\n  Fang,\t\n  Q.\t\n  Liu,\t\n  L.\t\n  Xiong,\t\n  P.\t\n  Qin,\t\n  H.\t\n  Tao,\t\n  J.\t\n  Wang,\t\n  H.\t\n  Lei,\t\n  B.\t\n  Li,\t\n  J.\t\n  Wan,\t\n  G. Yang\t\n  and\t\n  Y.\t\n  Yan,\t\n  Journal\t\n  of\t\n  the\t\n  American\t\n  Chemical\t\n  Society,\t\n  2015,\t\n  137,\t\n  6730- 6733. \n12. Q.\t\n  Dong,\t\n  Y.\t\n  Shi,\t\n  K.\t\n  Wang,\t\n  Y.\t\n  Li,\t\n  S.\t\n  Wang,\t\n  H.\t\n  Zhang,\t\n  Y.\t\n  Xing,\t\n  Y.\t\n  Du,\t\n  X.\t\n  Bai\t\n  and\t\n  T. Ma,\t\n  The\t\n  Journal\t\n  of\t\n  Physical\t\n  Chemistry\t\n  C,\t\n  2015,\t\n  119,\t\n  10212-­‐10217. \n13. J.\t\n  Song,\t\n  E.\t\n  Zheng,\t\n  J.\t\n  Bian,\t\n  X.-­‐F.\t\n  Wang,\t\n  W.\t\n  Tian,\t\n  Y.\t\n  Sanehira\t\n  and\t\n  T.\t\n  Miyasaka, Journal\t\n  of\t\n  Materials\t\n  Chemistry\t\n  A,\t\n  2015,\t\n  3,\t\n  10837-­‐10844. \n14. Y.\t\n  Li,\t\n  J.\t\n  Zhu,\t\n  Y.\t\n  Huang,\t\n  F.\t\n  Liu,\t\n  M.\t\n  Lv,\t\n  S.\t\n  Chen,\t\n  L.\t\n  Hu,\t\n  J.\t\n  Tang,\t\n  J.\t\n  Yao\t\n  and\t\n  S.\t\n  Dai,\t\n  RSC Advances,\t\n  2015,\t\n  5,\t\n  28424-­‐28429. \n15. L.\t\n  Kranz,\t\n  A.\t\n  Abate,\t\n  T.\t\n  Feurer,\t\n  F.\t\n  Fu,\t\n  E.\t\n  Avancini,\t\n  J.\t\n  Löckinger,\t\n  P.\t\n  Reinhard,\t\n  S.\t\n  M. Zakeeruddin,\t\n  M.\t\n  Grätzel,\t\n  S.\t\n  Buecheler\t\n  and\t\n  A.\t\n  N.\t\n  Tiwari,\t\n  The\t\n  Journal\t\n  of\t\n  Physical Chemistry\t\n  Letters,\t\n  2015,\t\n  2676-­‐2681. \n16. E.\t\n  M.\t\n  Miller,\t\n  Y.\t\n  Zhao,\t\n  C.\t\n  C.\t\n  Mercado,\t\n  S.\t\n  K.\t\n  Saha,\t\n  J.\t\n  M.\t\n  Luther,\t\n  K.\t\n  Zhu,\t\n  V. Stevanovic,\t\n  C.\t\n  L.\t\n  Perkins\t\n  and\t\n  J.\t\n  van\t\n  de\t\n  Lagemaat,\t\n  Physical\t\n  Chemistry\t\n  Chemical Physics,\t\n  2014,\t\n  16,\t\n  22122-­‐22130. \n17. A.\t\n  Guerrero,\t\n  E.\t\n  J.\t\n  Juarez-­‐Perez,\t\n  J.\t\n  Bisquert,\t\n  I.\t\n  Mora-­‐Sero\t\n  and\t\n  G.\t\n  Garcia-­‐ Belmonte,\t\n  Applied\t\n  Physics\t\n  Letters,\t\n  2014,\t\n  105,\t\n  133902. \n18. W.\t\n  Tress,\t\n  N.\t\n  Marinova,\t\n  T.\t\n  Moehl,\t\n  S.\t\n  M.\t\n  Zakeeruddin,\t\n  M.\t\n  K.\t\n  Nazeeruddin\t\n  and\t\n  M. Gratzel,\t\n  Energy\t\n  &\t\n  Environmental\t\n  Science,\t\n  2015,\t\n  8,\t\n  995-­‐1004. \n19. N.\t\n  J.\t\n  Jeon,\t\n  J.\t\n  H.\t\n  Noh,\t\n  W.\t\n  S.\t\n  Yang,\t\n  Y.\t\n  C.\t\n  Kim,\t\n  S.\t\n  Ryu,\t\n  J.\t\n  Seo\t\n  and\t\n  S.\t\n  I.\t\n  Seok,\t\n  Nature, 2015,\t\n  517,\t\n  476-­‐480. \n20. H.\t\n  Bender,\t\n  W.\t\n  D.\t\n  Chen,\t\n  J.\t\n  Portillo,\t\n  L.\t\n  Van\t\n  den\t\n  Hove\t\n  and\t\n  W.\t\n  Vandervorst, Applied\t\n  Surface\t\n  Science,\t\n  1989,\t\n  38,\t\n  37-­‐47. \n21. G.\t\n  Xing,\t\n  N.\t\n  Mathews,\t\n  S.\t\n  Sun,\t\n  S.\t\n  S.\t\n  Lim,\t\n  Y.\t\n  M.\t\n  Lam,\t\n  M.\t\n  Grätzel,\t\n  S.\t\n  Mhaisalkar\t\n  and T.\t\n  C.\t\n  Sum,\t\n  Science,\t\n  2013,\t\n  342,\t\n  344-­‐347. \n22. H.\t\n  J.\t\n  Snaith,\t\n  A.\t\n  Abate,\t\n  J.\t\n  M.\t\n  Ball,\t\n  G.\t\n  E.\t\n  Eperon,\t\n  T.\t\n  Leijtens,\t\n  N.\t\n  K.\t\n  Noel,\t\n  S.\t\n  D. Stranks,\t\n  J.\t\n  T.-­‐W.\t\n  Wang,\t\n  K.\t\n  Wojciechowski\t\n  and\t\n  W.\t\n  Zhang,\t\n  The\t\n  Journal\t\n  of Physical\t\n  Chemistry\t\n  Letters,\t\n  2014,\t\n  5,\t\n  1511-­‐1515. \n23. C.\t\n  Tao,\t\n  S.\t\n  Neutzner,\t\n  L.\t\n  Colella,\t\n  S.\t\n  Marras,\t\n  A.\t\n  R.\t\n  Srimath\t\n  Kandada,\t\n  M.\t\n  gandini,\t\n  M. De\t\n  Bastiani,\t\n  G.\t\n  Pace,\t\n  L.\t\n  Manna,\t\n  M.\t\n  Caironi,\t\n  C.\t\n  Bertarelli\t\n  and\t\n  a.\t\n  petrozza,\t\n  Energy &\t\n  Environmental\t\n  Science,\t\n  2015. \n24. G.\t\n  Xing,\t\n  B.\t\n  Wu,\t\n  S.\t\n  Chen,\t\n  J.\t\n  Chua,\t\n  N.\t\n  Yantara,\t\n  S.\t\n  Mhaisalkar,\t\n  N.\t\n  Mathews\t\n  and\t\n  T.\t\n  C. Sum,\t\n  Small,\t\n  2015. \n25. J.\t\n  M.\t\n  Azpiroz,\t\n  E.\t\n  Mosconi,\t\n  J.\t\n  Bisquert\t\n  and\t\n  F.\t\n  De\t\n  Angelis,\t\n  Energy\t\n  & Environmental\t\n  Science,\t\n  2015. \n26. W.\t\n  Tress,\t\n  N.\t\n  Marinova,\t\n  O.\t\n  Inganäs,\t\n  M.\t\n  K.\t\n  Nazeeruddin,\t\n  S.\t\n  M.\t\n  Zakeeruddin\t\n  and M.\t\n  Graetzel,\t\n  Advanced\t\n  Energy\t\n  Materials,\t\n  2015,\t\n  5,\t\n  n/a-­‐n/a. \n27. R.\t\n  Marschall,\t\n  Advanced\t\n  Functional\t\n  Materials,\t\n  2014,\t\n  24,\t\n  2421-­‐2440. \n28. P.\t\n  Docampo,\t\n  F.\t\n  C.\t\n  Hanusch,\t\n  S.\t\n  D.\t\n  Stranks,\t\n  M.\t\n  Döblinger,\t\n  J.\t\n  M.\t\n  Feckl,\t\n  M. Ehrensperger,\t\n  N.\t\n  K.\t\n  Minar,\t\n  M.\t\n  B.\t\n  Johnston,\t\n  H.\t\n  J.\t\n  Snaith\t\n  and\t\n  T.\t\n  Bein,\t\n  Advanced Energy\t\n  Materials,\t\n  2014,\t\n  4,\t\n  n/a-­‐n/a. \n29. Q.\t\n  Chen,\t\n  H.\t\n  Zhou,\t\n  Z.\t\n  Hong,\t\n  S.\t\n  Luo,\t\n  H.-­‐S.\t\n  Duan,\t\n  H.-­‐H.\t\n  Wang,\t\n  Y.\t\n  Liu,\t\n  G.\t\n  Li\t\n  and\t\n  Y. Yang,\t\n  Journal\t\n  of\t\n  the\t\n  American\t\n  Chemical\t\n  Society,\t\n  2014,\t\n  136,\t\n  622-­‐625. \n30. J.\t\n  Xu,\t\n  A.\t\n  Buin,\t\n  A.\t\n  H.\t\n  Ip,\t\n  W.\t\n  Li,\t\n  O.\t\n  Voznyy,\t\n  R.\t\n  Comin,\t\n  M.\t\n  Yuan,\t\n  S.\t\n  Jeon,\t\n  Z.\t\n  Ning,\t\n  J.\t\n  J. McDowell,\t\n  P.\t\n  Kanjanaboos,\t\n  J.-­‐P.\t\n  Sun,\t\n  X.\t\n  Lan,\t\n  L.\t\n  N.\t\n  Quan,\t\n  D.\t\n  H.\t\n  Kim,\t\n  I.\t\n  G.\t\n  Hill,\t\n  P. Maksymovych\t\n  and\t\n  E.\t\n  H.\t\n  Sargent,\t\n  Nat\t\n  Commun,\t\n  2015,\t\n  6. \n31. A.\t\n  H.\t\n  Ip,\t\n  L.\t\n  N.\t\n  Quan,\t\n  M.\t\n  M.\t\n  Adachi,\t\n  J.\t\n  J.\t\n  McDowell,\t\n  J.\t\n  Xu,\t\n  D.\t\n  H.\t\n  Kim\t\n  and\t\n  E.\t\n  H. Sargent,\t\n  Applied\t\n  Physics\t\n  Letters,\t\n  2015,\t\n  106,\t\n  143902. \n32. B.\t\n  Wu,\t\n  K.\t\n  Fu,\t\n  N.\t\n  Yantara,\t\n  G.\t\n  Xing,\t\n  S.\t\n  Sun,\t\n  T.\t\n  C.\t\n  Sum\t\n  and\t\n  N.\t\n  Mathews,\t\n  Advanced Energy\t\n  Materials,\t\n  2015,\t\n  n/a-­‐n/a. \n33. E.\t\n  L.\t\n  Unger,\t\n  E.\t\n  T.\t\n  Hoke,\t\n  C.\t\n  D.\t\n  Bailie,\t\n  W.\t\n  H.\t\n  Nguyen,\t\n  A.\t\n  R.\t\n  Bowring,\t\n  T.\t\n  Heumuller, M.\t\n  G.\t\n  Christoforo\t\n  and\t\n  M.\t\n  D.\t\n  McGehee,\t\n  Energy\t\n  &\t\n  Environmental\t\n  Science,\t\n  2014, 7,\t\n  3690-­‐3698. \n34. J.\t\n  Azevedo,\t\n  L.\t\n  Steier,\t\n  P.\t\n  Dias,\t\n  M.\t\n  Stefik,\t\n  C.\t\n  T.\t\n  Sousa,\t\n  J.\t\n  P.\t\n  Araujo,\t\n  A.\t\n  Mendes,\t\n  M. Graetzel\t\n  and\t\n  S.\t\n  D.\t\n  Tilley,\t\n  Energy\t\n  &\t\n  Environmental\t\n  Science,\t\n  2014,\t\n  7,\t\n  4044-­‐4052 \n35. A.\t\n  Abate,\t\n  T.\t\n  Leijtens,\t\n  S.\t\n  Pathak,\t\n  J.\t\n  Teuscher,\t\n  R.\t\n  Avolio,\t\n  M.\t\n  E.\t\n  Errico,\t\n  J.\t\n  Kirkpatrik, J.\t\n  M.\t\n  Ball,\t\n  P.\t\n  Docampo,\t\n  I.\t\n  McPherson\t\n  and\t\n  H.\t\n  J.\t\n  Snaith,\t\n  Physical\t\n  Chemistry Chemical\t\n  Physics,\t\n  2013,\t\n  15,\t\n  2572-­‐2579. \n36. A.\t\n  Abate,\t\n  D.\t\n  R.\t\n  Staff,\t\n  D.\t\n  J.\t\n  Hollman,\t\n  H.\t\n  J.\t\n  Snaith\t\n  and\t\n  A.\t\n  B.\t\n  Walker,\t\n  Physical Chemistry\t\n  Chemical\t\n  Physics,\t\n  2014,\t\n  16,\t\n  1132-­‐1138. " + }, + { + "id": "10.1126_science.aad2114", + "DOI": "10.1126/science.aad2114", + "DOI Link": "http://dx.doi.org/10.1126/science.aad2114", + "Relative Dir Path": "mds/10.1126_science.aad2114", + "Article Title": "Near-unity photoluminescence quantum yield in MoS2", + "Authors": "Amani, M; Lien, DH; Kiriya, D; Xiao, J; Azcatl, A; Noh, J; Madhvapathy, SR; Addou, R; Santosh, KC; Dubey, M; Cho, K; Wallace, RM; Lee, SC; He, JH; Ager, JW; Zhang, X; Yablonovitch, E; Javey, A", + "Source Title": "SCIENCE", + "Abstract": "Two-dimensional (2D) transition metal dichalcogenides have emerged as a promising material system for optoelectronic applications, but their primary figure of merit, the room-temperature photoluminescence quantum yield (QY), is extremely low. The prototypical 2D material molybdenum disulfide (MoS2) is reported to have a maximum QY of 0.6%, which indicates a considerable defect density. Herewe report on an air-stable, solution-based chemical treatment by an organic superacid, which uniformly enhances the photoluminescence and minority carrier lifetime of MoS2 monolayers by more than two orders of magnitude. The treatment eliminates defect-mediated nonradiative recombination, thus resulting in a final QY of more than 95%, with a longest-observed lifetime of 10.8 0.6 nulloseconds. Our ability to obtain optoelectronic monolayers with near-perfect properties opens the door for the development of highly efficient light-emitting diodes, lasers, and solar cells based on 2D materials.", + "Times Cited, WoS Core": 1042, + "Times Cited, All Databases": 1188, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000366422600037", + "Markdown": "$\\mathrm{p{-}G a I n P_{2}/T i O_{2}}$ exhibit oscillations similar to that for $\\mathrm{p{\\mathrm{-GaInP_{2}/P t}}}$ , meaning that the surface field increases substantially when the $\\mathrm{TiO}_{2}$ thickness increases from 0.5 to $35\\mathrm{nm}$ . The formation and decay time constant of $\\Delta F$ for these samples are extracted from the corresponding TPR kinetics (fig. S9B). Best-fit parameters are tabulated in table S1. Thicker $\\mathrm{TiO}_{2}$ layers exhibit slightly faster field formation but slower decay, which is likely due to the larger built-in field that drives carriers apart and separates them at a greater distance, both of which lead to slower recombination. We find that the kinetics are effectively unperturbed once a sufficient amorphous $\\mathrm{TiO_{2}}$ thickness has been reached, suggesting that thicker layers would not drastically influence the photoconversion performance from a charge dynamics perspective. A thick $\\mathrm{TiO_{2}}$ layer may still be necessary for other reasons (such as elimination of pinholes) that affect stabilization against photocorrosion, as has been found for $\\scriptstyle140-\\mathrm{nm}$ -thick amorphous $\\mathrm{TiO}_{2}$ layers on Si, GaAs, and GaP photoanodes (2). \n\nOur results uncover key beneficial roles of amorphous $\\mathrm{TiO}_{2}$ in the energy-conversion process that have come under intense investigation after several recent reports of $\\mathrm{TiO_{2}}$ -stablized photoelectrodes (2, 29, 30). The TPR technique developed here furthermore introduces a general method to understand charge transfer at semiconductor junctions. \n\n# REFERENCES AND NOTES \n\n25. H. Shen, F. H. Pollak, Phys. Rev. B 42, 7097–7102 (1990). \n26. T. Kita et al., J. Appl. Phys. 94, 6487–6490 (2003). \n27. Y. S. Huang et al., Appl. Phys. Lett. 73, 214–216 (1998). \n28. F. J. Schultes et al., Appl. Phys. Lett. 103, 242106 (2013). \n29. B. Seger et al., J. Am. Chem. Soc. 135, 1057–1064 (2013). \n30. B. Seger et al., RSC Adv. 3, 25902–25907 (2013). \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Division of Chemical Sciences, Geosciences and Biosciences, Office of Basic Energy Sciences of the U.S. Department of Energy, through the Solar Photochemistry Program under contract no. DE-AC36-08GO28308 to the National Renewable Energy Laboratory. J.L.Y. acknowledges NSF Graduate \n\n# NANOMATERIALS \n\nResearch Fellowship Grant no. DGE 1144083. The U.S. government retains—and the publisher, by accepting the article for publication, acknowledges that the U.S. government retains—a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. government purposes. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/350/6264/1061/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S9 \nTables S1 to S4 \nReferences (31, 32) \n31 August 2015; accepted 19 October 2015 \n10.1126/science.aad3459 \n\n# Near-unity photoluminescence quantum yield in MoS2 \n\nMatin Amani,1,2\\* Der-Hsien Lien,1,2,3,4\\* Daisuke Kiriya,1,2\\* Jun Xiao,5,2 Angelica Azcatl,6 Jiyoung Noh,6 Surabhi R. Madhvapathy,1,2 Rafik Addou,6 Santosh KC,6 Madan Dubey,7 Kyeongjae Cho,6 Robert M. Wallace,6 Si-Chen Lee,4 Jr-Hau He,3 Joel W. Ager III,2 Xiang Zhang,5,2,8 Eli Yablonovitch,1,2 Ali Javey1,2† \n\nTwo-dimensional (2D) transition metal dichalcogenides have emerged as a promising material system for optoelectronic applications, but their primary figure of merit, the room-temperature photoluminescence quantum yield (QY), is extremely low. The prototypical 2D material molybdenum disulfide $(\\mathsf{M o S}_{2})$ is reported to have a maximum QYof $0.6\\%$ , which indicates a considerable defect density. Here we report on an air-stable, solution-based chemical treatment by an organic superacid, which uniformly enhances the photoluminescence and minority carrier lifetime of ${\\mathsf{M o S}}_{2}$ monolayers by more than two orders of magnitude.The treatment eliminates defect-mediated nonradiative recombination, thus resulting in a final QYof more than $95\\%$ , with a longest-observed lifetime of 10.8 0.6 nanoseconds. Our ability to obtain optoelectronic monolayers with near-perfect properties opens the door for the development of highly efficient light-emitting diodes, lasers, and solar cells based on 2D materials. \n\nonolayer transition metal dichalcogenides (TMDCs) have properties that make them highly suitable for optoelectronics (1, 2), 1 including the ability to form van der Waals heterostructures without the need for lat \ntice matching (3, 4), circular dichroism arising \nfrom the direct band gap occurring at the K and \n$\\mathbf{K}^{\\prime}$ points of the Brillouin zone $\\textcircled{5}$ , and widely \ntunable band structure through the application \n\nof external forces such as electric field and strain (6). Unlike III-V semiconductors, the optical properties of TMDCs are dominated by excitons with strong binding energies (on the order of $300\\mathrm{meV},$ (7–9) and large radii $\\cdot{\\mathrm{\\sim}}1.6\\ \\mathrm{nm},$ ) (10). However, TMDCs have exhibited poor luminescence quantum yield (QY)—that is, the number of photons the material radiates is much lower than the number of generated electron-hole pairs. QY values ranging from 0.01 to $6\\%$ have been reported, indicating a high density of defect states and mediocre electronic quality (11–13). The origin of the low quantum yield observed in these materials is attributed to defect-mediated nonradiative recombination and biexcitonic recombination at higher excitation powers (11, 13). \n\nTwo-dimensional (2D) monolayers are amenable to surface passivation by chemical treatments. We studied a wide range of chemical treatments and describe here an air-stable, solution-based process using an organic superacid that removes the contribution of defect-mediated nonradiative recombination acting on electronically active defect sites by uniformly passivating them, repairing them, or both. With the use of this process, the photoluminescence (PL) in $\\mathbf{MoS}_{2}$ monolayers increased by more than two orders of magnitude, resulting in a $Q Y>95\\%$ and a characteristic lifetime of $10.8\\pm0.6$ ns at low excitation densities. \n\n![](images/aabb8475ac8aca777dcc2bc84e704bc93a351fa6d85ef99307eae9c084e6a5da.jpg) \nFig. 1. Enhancement of PL by chemical treatment. (A) PL spectrum for both the as-exfoliated and TFSI-treated ${\\mathsf{M o S}}_{2}$ monolayers measured at an incident power of $1\\times10^{-2}$ W $\\mathsf{c m}^{-2}$ . The inset shows normalized spectra. (B and C) PL images of a ${\\mathsf{M o S}}_{2}$ monolayer before (B) and after treatment (C). Insets show optical micrographs. \nFig. 2. Steady-state luminescence. (A) Pump-power dependence of the integrated PL for as-exfoliated and treated ${\\mathsf{M o S}}_{2}$ . Dashed lines show power law fits for the three dominant recombination regimes. (B) Pump-power dependence of the $Q\\mathsf{Y}$ for as-exfoliated and treated ${\\mathsf{M o S}}_{2}$ . Dashed lines show the recombination model. \n\nIn this study, we treated $\\mathrm{MoS_{2}}$ monolayers with a nonoxidizing organic superacid: bis(trifluoromethane) sulfonimide (TFSI). Superacids are strong protonating agents and have a Hammett acidity function $(H_{0})$ that is lower than that of pure sulfuric acid. [Details of the sample preparation and treatment procedure are discussed in the supplementary materials and methods (14).] The PL spectra of a $\\mathbf{MoS}_{2}$ monolayer measured before and after TFSI treatment (Fig. 1A) show a 190-fold increase in the PL peak intensity, with no change in the overall spectral shape. The magnitude of the enhancement depended strongly on the quality of the original as-exfoliated monolayer (14). (The term \"as-exfoliated\" indicates that the $\\mathbf{MoS}_{2}$ flakes were not processed after exfoliation.) PL images of a monolayer (Fig. 1, B and C, and fig. S4) $(I4)$ , taken before and after treatment at the same illumination conditions, show that the enhancement from the superacid treatment is spatially uniform. \n\nCalibrated steady-state PL measurements (14) showed that the spectral shape of the emission remained unchanged over a pump intensity dynamic range spanning six orders of magnitude $(10^{-4}$ to ${\\mathrm{10^{2}}}$ W $\\mathrm{cm^{-2}}$ ) (fig. S2) (14). From the pump-power dependence of the calibrated luminescence intensity (Fig. 2A), we extracted the QY (Fig. 2B). As-exfoliated samples exhibited low QY, with a peak efficiency of $1\\%$ measured at $10^{-2}\\mathrm{W~cm^{-2}}$ . The absolute efficiency (12, 13) and observed power law (13) are consistent with previous reports for exfoliated $\\mathbf{MoS}_{2}$ . After TFSI treatment, the QY reached a plateau at a low pump intensity $(<10^{-2}\\mathrm{{W}c m^{-2})}$ , with a maximum value greater than $95\\%$ . The near-unity QY suggests that, within this range of incident power, there was negligible nonradiative recombination occurring in the sample. Although pure radiative recombination is commonly observed for fluorescent molecules that inherently have no dangling bonds, only a few semiconductors, such as GaAs double heterostructures (15) and surface-passivated quantum dots (16), show this behavior at room temperature. \n\nAt high pump power, we observed a sharp dropoff in the QY, possibly caused by nonradiative biexcitonic recombination. We consider several models to explain the carrier density–dependent recombination mechanisms in $\\mathbf{MoS}_{2}$ before and after TFSI treatment. Here, $n$ and $p$ are the 2D electron and hole concentrations, respectively. At high-level injection, the dopant concentration is much less than the number of optically generated carriers, allowing $n=p$ . The traditional interpretation without excitons $(I7)$ invokes a total recombination, $R$ , as $R=A n+B n^{2}+C n^{3}$ , where $A$ is the Shockley-Read-Hall (SRH) recombination rate, $B$ is the radiative recombination rate, and $c$ is the Auger recombination rate. The QY is given as the radiative recombination rate over the total recombination. Auger processes dominate at high carrier concentrations, whereas SRH recombination dominates at low carrier concentrations. In the SRH regime (i.e., low pump power), QY increases with pump intensity. This behavior, however, was not observed in previous $\\mathbf{MoS}_{2}$ studies (12, 13) or in this work. \n\nThe standard model poorly describes our QY data (fig. S10) $(I4)$ , which are strongly influenced by bound excitons (9). As a result, the radiative rate is proportional to the total exciton population, $\\langle N\\rangle$ (18). At high exciton densities, nonradiative biexcitonic recombination can dominate, leading to a recombination rate proportional to $\\left\\langle N\\right\\rangle^{2}$ (18). Previous reports also suggest that the luminescence in as-exfoliated samples is limited by nonradiative defect-mediated processes $(I9,2O)$ , resulting in low QY. Although the precise nature of the defectmediated nonradiative recombination is unclear, a simple analytical model can be developed to describe our experimental results. The total excitation rate, $R,$ , in $\\mathrm{MoS_{2}}$ is balanced by recombination \n\n$$\nR=B_{\\mathrm{nr}}n^{2}+B_{\\mathrm{r}}n^{2}\n$$ \n\nwhere $B_{\\mathrm{nr}}$ is the nonradiative defect-mediated recombination rate and $B_{\\mathrm{r}}$ is the formation rate of excitons. The generated excitons can then either undergo radiative recombination or nonradiatively recombine with a second exciton according to $B_{\\mathrm{r}}n^{2}=\\tau_{\\mathrm{r}}^{-1}\\langle N\\rangle+C_{\\mathrm{bx}}\\langle N\\rangle^{2}$ (19), where $\\tau_{\\mathrm{r}}$ is the radiative lifetime and $C_{\\mathrm{bx}}$ is the biexcitonic recombination rate. The QY is then given as \n\n![](images/8c0b4774beeef2627e21cdb0ed5e7a2e4c8e45ae1f9efc838fc3de43c90d08cd.jpg) \nFig. 3. Time-resolved luminescence. (A) Radiative decay of an as-exfoliated ${\\mathsf{M o S}}_{2}$ sample at various initial carrier concentrations $(\\mathsf{n}_{0})$ , as well as the instrument response function (IRF). (B) Radiative decay of a treated ${\\mathsf{M o S}}_{2}$ sample plotted for several initial carrier concentrations $(\\mathsf{n}_{0})$ , as well as the IRF. Dashed lines in (A) and (B) indicate single exponential fits. (C) Effective PL lifetime as a function of pump fluence. Dashed lines show a power law fit for the dominant recombination regimes. \n\n$$\nQ Y=\\frac{\\uptau_{\\mathrm{r}}^{-1}\\langle N\\rangle}{\\uptau_{\\mathrm{r}}^{-1}\\langle N\\rangle+B_{\\mathrm{nr}}n^{2}+C_{\\mathrm{bx}}\\langle N\\rangle^{2}}\n$$ \n\nFor the case of the TFSI-treated sample, $B_{\\mathrm{nr}}$ is negligible because the QY at low pump powers is $>95\\%$ , allowing us to extract a biexcitonic recombination coefficient $C_{\\mathrm{bx}}=2.8\\mathrm{cm}^{2}\\mathrm{s}^{-1}.$ For the as-exfoliated sample, the defect-mediated nonradiative recombination can be fit to ${\\cal B}_{\\mathrm{nr}}=1.5\\times$ $10^{6}\\mathrm{~cm^{2}~s^{-1}}$ , using the same $C_{\\mathrm{bx}}$ value. The fitting results are plotted as the dashed curves in Fig. 2B. \n\nTo investigate the carrier recombination dynamics, we performed time-resolved measurements on both as-exfoliated and chemically treated samples. The luminescence decay was nonexponential, but not in the standard form known for bimolecular $(B n^{2})$ recombination $(I7)$ . As-exfoliated monolayers of $\\mathrm{MoS_{2}}$ had extremely short lifetimes on the order of 100 ps (Fig. 3A and fig. S6) (14), consistent with previous reports (21). After treatment, we saw a substantial increase in the lifetime, which is shown at several pump fluences in Fig. 3A. Fitting was performed with a single exponential decay that described only the initial characteristic lifetime for a given pump intensity. After the pump pulse, the exciton population decayed, which resulted in nonexponential decay through reduced nonradiative biexcitonic recombination. At the lowest measurable pump fluences, we observed a luminescence lifetime of $10.8~\\pm~0.6$ ns in the treated sample, compared with ${\\sim}0.3$ ns in the untreated case at a pump fluence of $5\\times10^{-4}\\upmu\\mathrm{J}$ $\\mathrm{cm^{-2}}$ (Fig. 3C). The contrast between panels A and B of Fig. 3 is consistent with the QY trend. \n\nUrbach tails, which depict the sharpness of the band edges (22), were derived from the steadystate PL spectra via the van Roosbroeck–Shockley equation and are plotted in fig. S8. After treatment with TFSI, a noticeable decrease in the Urbach energy $(E_{0})$ from 17.4 to $\\mathrm{13.3~meV}$ was observed, indicating a reduction in the overall disorder from potential fluctuations and improved band-edge sharpness (22). A spatial map showing Urbach energy (fig. S8) (14) further indicates that the treatment was highly uniform. To evaluate stability, the QY in air for chemically treated $\\mathbf{MoS}_{2}$ was measured daily at a constant pump power over the course of 1 week, during which the sample was stored without any passivation in ambient lab conditions $20^{\\circ}$ to $22^{\\circ}\\mathrm{C}$ , 40 to $60\\%$ relative humidity), as shown in fig. S9 (14). The QY remained above $80\\%$ during this period, indicating that the treatment resulted in samples that were relatively stable. \n\nWe then turned our attention to the effect of TFSI treatment on other properties of $\\mathbf{MoS}_{2}$ . The monolayer surface was imaged by atomic force microscopy (AFM) before and after treatment (Fig. 4A). No visible change to the surface morphology was observed. We also investigated the effect of the treatment on the electrical properties of a back-gated $\\mathbf{MoS}_{2}$ transistor. The transfer characteristics of this majority carrier device before and after treatment showed a shift in the threshold voltage toward zero, indicating that the native n-type doping in the $\\mathbf{MoS}_{2}$ was removed while the same drive current was maintained (Fig. 4B). An improvement in the subthreshold slope indicated that the treatment reduces interface trap states. The Raman spectra of an as-exfoliated and treated monolayer (Fig. 4C) showed that there was no change in the relative intensity or peak position. Thus, the structure of $\\mathbf{MoS}_{2}$ was not altered during treatment, and the lattice was not subjected to any induced strain (23). Because absolute absorption was used in the calibration of QY, we performed careful absorption measurements using two different methods $(l4),$ , both before and after treatment (Fig. 4D). At the pump wavelength $(514.5\\mathrm{nm})$ ), no measurable change of the absolute absorption from the treatment was observed. The strong resonances at 1.88 and 2.04 eV (corresponding to the A and B excitons, respectively) are consistent with previous reports (12). We then performed surface-sensitive x-ray photoelectron spectroscopy (XPS) on bulk $\\mathbf{MoS}_{2}$ from the same crystal used for micromechanical exfoliation. The Mo 3d and $\\mathrm{{s2p}}$ core levels (Fig. 4E) showed no observable change in oxidation state and bonding after treatment (24). Thus, an array of different techniques for materials characterization shows that the structure of the $\\mathbf{MoS}_{2}$ remains intact after TFSI treatment, with only the minority carrier properties (i.e., QY and lifetime) enhanced. \n\nThe effect of treatment by a wide variety of molecules is shown in table S1 and discussed in the supplementary text. Various polar, nonpolar, and fluorinated molecules, including strong acids and the solvents used for TFSI treatment (dichlorobenzene and dichloroethane), were explored. Treatment with the phenylated derivative of superacid TFSI was also performed (fig. S11) (14). These treatments all led to no or minimal (less than one order of magnitude) enhancement in PL QY. \n\nThe exact mechanism by which the TFSI passivates surface defects is not fully understood. Exfoliated $\\mathbf{MoS}_{2}$ surfaces contain regions with a large number of defect sites in the form of sulfur vacancies, adatoms on the surface, and numerous impurities (25–27). In fig. S12A (14), the calculated midgap energy is shown for several defect types, including a sulfur vacancy, adsorbed –OH, and adsorbed water. Deep-level traps—which contribute to defect-mediated nonradiative recombination, resulting in a low QY (27)—are observed for all of these cases. The strong protonating nature of the superacid can remove absorbed water, hydroxyl groups, oxygen, and other contaminants on the surface. Although these reactions will not remove the contribution of defects to nonradiative recombination, they will open the active defect sites to passivation by a second mechanism. One possibility is the protonation of the three dangling bonds at each sulfur vacancy site. However, density functional theory calculations (fig. S12C) $(I4)$ show that this reaction is energetically unfavorable. A second possibility is that the surface is restructured to reduce the sulfur vacancies through rearrangement of sulfur adatoms on the surface, which can be facilitated by hydrogenation via TFSI (14). The presence of sulfur adatom clusters has previously been confirmed by scanning tunneling microscopy and energy-dispersive x-ray spectroscopy (27–30). Careful examination of the XPS data over multiple spots before and after TFSI treatment (fig. S13) $(I4)$ reveals that the ratio of bonded sulfur to molybdenum (S/Mo) increased from $1.84\\pm0.04$ in the as-exfoliated case to $1.95\\pm0.05$ after treatment (table S2) $(I4)$ . \n\n![](images/d4917ece64ec21bf4b184911e744d490e4662c425f97f04f562d5fa8a0aa8b6f.jpg) \nFig. 4. Material and device characterization. (A) AFM images taken before and after TFSI treatment. (B) Transfer characteristics of a monolayer ${\\mathsf{M o S}}_{2}$ transistor, both before and after treatment. $\\mathsf{V}_{\\mathsf{D S}}$ , drain-source voltage; S, source; D, drain; G, gate. (C) Raman spectrum of as-exfoliated and TFSI-treated ${\\mathsf{M o S}}_{2}$ samples. a.u., arbitrary units; E′, ${\\mathsf{M o S}}_{2}$ in-plane mode; A′, ${\\mathsf{M o S}}_{2}$ out-of-plane mode; Si, silicon Raman peak. (D) Absorption spectrum of the as-exfoliated and treated ${\\mathsf{M o S}}_{2}$ samples. A and B indicate the exciton resonances. (E) XPS spectrum of the $\\mathsf{S}2\\mathsf{p}$ and Mo 3d core levels before and after treatment. The insets show that there is no appearance of $\\mathsf{S O}_{x}$ or change in the ${\\mathsf{M o O}}_{x}$ peak intensity after treatment. \n\nWe have demonstrated an air-stable process by which the PL of monolayer $\\mathbf{MoS}_{2}$ can be increased by more than two orders of magnitude, resulting in near-unity luminescence yield. This result sheds light on the importance of defects in limiting the performance of 2D systems and presents a practical route to eliminate their effect on optoelectronic properties. The existence of monolayers with near-ideal optoelectronic properties should enable the development of new high-performance light-emitting diodes, lasers, and solar cells. These devices can fulfill the revolutionary potential of the 2D semiconductors $(I)$ , which require interfacial passivation, as in all classic semiconductors. \n\n# REFERENCES AND NOTES \n\n1. F. Xia, H. Wang, D. Xiao, M. Dubey, A. Ramasubramaniam, Nat. Photonics 8, 899–907 (2014). \n2. S. Wu et al., Nature 520, 69–72 (2015). \n3. H. Fang et al., Proc. Natl. Acad. Sci. U.S.A. 111, 6198–6202 (2014). \n4. L. Britnell et al., Science 340, 1311–1314 (2013). \n5. K. F. Mak, K. He, J. Shan, T. F. Heinz, Nat. Nanotechnol. 7, 494–498 (2012). \n6. S. B. Desai et al., Nano Lett. 14, 4592–4597 (2014). \n7. S. Tongay et al., Sci. Rep. 3, 2657 (2013). \n8. A. Chernikov et al., Phys. Rev. Lett. 113, 076802 (2014). \n9. H. M. Hill et al., Nano Lett. 15, 2992–2997 (2015). \n10. T. C. Berkelbach, M. S. Hybertsen, D. R. Reichman, Phys. Rev. B 88, 045318 (2013). \n11. L. Yuan, L. Huang, Nanoscale 7, 7402–7408 (2015). \n12. K. F. Mak, C. Lee, J. Hone, J. Shan, T. F. Heinz, Phys. Rev. Lett. 105, 136805 (2010). \n13. H. Wang, C. Zhang, F. Rana, Nano Lett. 15, 339–345 (2015). \n14. Materials and methods are available as supplementary materials on Science Online. \n15. I. Schnitzer, E. Yablonovitch, C. Caneau, T. J. Gmitter, Appl. Phys. Lett. 62, 131–133 (1993). \n16. Y. S. Park et al., Phys. Rev. Lett. 106, 187401 (2011). \n17. P. T. Landsberg, Phys. Status Solidi 41, 457–489 (1970). \n18. F. Wang, Y. Wu, M. S. Hybertsen, T. F. Heinz, Phys. Rev. B 73, 245424 (2006). \n19. H. Wang et al., Phys. Rev. B 91, 165411 (2015). \n20. C. Mai et al., Nano Lett. 14, 202–206 (2014). \n21. T. Korn, S. Heydrich, M. Hirmer, J. Schmutzler, C. Schuller, Appl. Phys. Lett. 99, 102109 (2011). \n22. A. Iribarren, R. Castro-Rodriguez, V. Sosa, J. L. Pena, Phys. Rev. B 58, 1907–1911 (1998). \n23. Z. Liu et al., Nat. Commun. 5, 5246 (2014). \n24. A. Azcatl et al., Appl. Phys. Lett. 104, 111601 (2014). \n25. C. P. Lu, G. Li, J. Mao, L. M. Wang, E. Y. Andrei, Nano Lett. 14, 4628–4633 (2014). \n26. S. McDonnell, R. Addou, C. Buie, R. M. Wallace, C. L. Hinkle, ACS Nano 8, 2880–2888 (2014). \n27. R. Addou et al., ACS Nano 9, 9124–9133 (2015). \n28. R. Addou, L. Colombo, R. M. Wallace, Appl. Mat. Interfaces. 7, 11921–11929 (2015). \n29. J. Y. Noh, H. Kim, Y. S. Kim, Phys. Rev. B 89, 205417 (2014). \n30. A. P. Nayak et al., Nat. Commun. 5, 3731 (2014). \n\n# ACKNOWLEDGMENTS \n\nWe thank F. R. Fischer for in-depth discussions on surface chemistry and A. B. Sachid for analysis of the electrical measurements. M.A., J.X., J.W.A., X.Z., and A.J. were funded by the Director, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division of the U.S. Department of Energy, under contract no. DE-AC02- 05Ch11231. A.A., J.N., R.A., S.KC, R.M.W., and K.C. were funded by the Center for Low Energy System Technology (LEAST), one of six centers supported by the STARnet phase of the Focus Research Program (FCRP), a Semiconductor Research Corporation program sponsored by Microelectronics Advanced Research Corporation and Defense Advanced Research Projects Agency. D.K. acknowledges support from Samsung, E.Y. acknowledges support from the NSF Center for Energy Efficient Electronics Science $(\\mathsf{E}^{3}\\mathsf{S})$ , J.-H.H. acknowledges support from the baseline fund of KAUST, and M.D. acknowledges support from the U.S. Army Research Lab Director’s Strategic Initiative program on interfaces in stacked 2D atomic layers and materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/350/6264/1065/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S13 \nTables S1 and S2 \nReferences (31–48) \n12 August 2015; accepted 13 October 2015 \n10.1126/science.aad2114 \n\nThis copy is for your personal, non-commercial use only. \n\nIf you wish to distribute this article to others, you can order high-quality copies for your colleagues, clients, or customers by clicking here. \n\nPermission to republish or repurpose articles or portions of articles can be obtained by following the guidelines here. \n\nThe following resources related to this article are available online at www.sciencemag.org (this information is current as of November 26, 2015 ): \n\nUpdated information and services, including high-resolution figures, can be found in the online \nversion of this article at: \nhttp://www.sciencemag.org/content/350/6264/1065.full.html \n\nSupporting Online Material can be found at: http://www.sciencemag.org/content/suppl/2015/11/24/350.6264.1065.DC1.html \n\nThis article cites 46 articles, 2 of which can be accessed free: http://www.sciencemag.org/content/350/6264/1065.full.html#ref-list-1 \n\nThis article appears in the following subject collections: Physics http://www.sciencemag.org/cgi/collection/physics " + }, + { + "id": "10.1038_ncomms8240", + "DOI": "10.1038/ncomms8240", + "DOI Link": "http://dx.doi.org/10.1038/ncomms8240", + "Relative Dir Path": "mds/10.1038_ncomms8240", + "Article Title": "Biomimetic mineralization of metal-organic frameworks as protective coatings for biomacromolecules", + "Authors": "Liang, K; Ricco, R; Doherty, CM; Styles, MJ; Bell, S; Kirby, N; Mudie, S; Haylock, D; Hill, AJ; Doonull, CJ; Falcaro, P", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Enhancing the robustness of functional biomacromolecules is a critical challenge in biotechnology, which if addressed would enhance their use in pharmaceuticals, chemical processing and biostorage. Here we report a novel method, inspired by natural biomineralization processes, which provides unprecedented protection of biomacromolecules by encapsulating them within a class of porous materials termed metal-organic frameworks. We show that proteins, enzymes and DNA rapidly induce the formation of protective metal-organic framework coatings under physiological conditions by concentrating the framework building blocks and facilitating crystallization around the biomacromolecules. The resulting biocomposite is stable under conditions that would normally decompose many biological macromolecules. For example, urease and horseradish peroxidase protected within a metal-organic framework shell are found to retain bioactivity after being treated at 80 degrees C and boiled in dimethylformamide (153 degrees C), respectively. This rapid, low-cost biomimetic mineralization process gives rise to new possibilities for the exploitation of biomacromolecules.", + "Times Cited, WoS Core": 1177, + "Times Cited, All Databases": 1249, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000357169000002", + "Markdown": "# Biomimetic mineralization of metal-organic frameworks as protective coatings for biomacromolecules \n\nKang Liang1, Raffaele Ricco1, Cara M. Doherty1, Mark J. Styles1, Stephen Bell2, Nigel Kirby3, Stephen Mudie3, David Haylock1,4, Anita J. Hill1, Christian J. Doonan2 & Paolo Falcaro1 \n\nEnhancing the robustness of functional biomacromolecules is a critical challenge in biotechnology, which if addressed would enhance their use in pharmaceuticals, chemical processing and biostorage. Here we report a novel method, inspired by natural biomineralization processes, which provides unprecedented protection of biomacromolecules by encapsulating them within a class of porous materials termed metal-organic frameworks. We show that proteins, enzymes and DNA rapidly induce the formation of protective metal-organic framework coatings under physiological conditions by concentrating the framework building blocks and facilitating crystallization around the biomacromolecules. The resulting biocomposite is stable under conditions that would normally decompose many biological macromolecules. For example, urease and horseradish peroxidase protected within a metal-organic framework shell are found to retain bioactivity after being treated at $80^{\\circ}C$ and boiled in dimethylformamide $(153^{\\circ}\\mathsf{C})$ , respectively. This rapid, low-cost biomimetic mineralization process gives rise to new possibilities for the exploitation of biomacromolecules. \n\nMsapneydcilsifitvrciuanlclgtyuordraelgsasinguinpsepmdo ofaobprriscoavftitedtemsesoxuloe1sc.kuleTalehrtasalbciphorilotoetgecitctuairlolenys induced, self-assembly process, termed biomineralization, is carried out with exquisite control of crystal morphology and compositional specificity under physiological conditions2. Furthermore, the resultant biocomposites typically exhibit superior mechanical properties with respect to their constituents3. Accordingly, such natural biomineralization processes have inspired ‘biomimetic’4 strategies for the synthesis of novel materials for photonics, biomedical implants, drug delivery and biochemical separations5–8. \n\nA goal of biomimetic mineralization is to adopt and translate the self-assembly processes found in natural biological systems to the development of a general method for encapsulating bioactive molecules within protective exteriors9. Success in this endeavour would significantly increase the potential for utilizing functional biomacromolecules in applications where enhanced thermal stability, tolerance to organic solvents or extended shelf-lifetime is required, such as industrial catalysis and biopharmaceutical delivery10–12. To this end, recent studies have demonstrated that coating bioactive macromolecules with inorganic shells (for example, calcium phosphate, CaP) can provide prolonged shelflifetime9. Although this report clearly demonstrates the potential applications of exploiting biomineral shells, seeding an inorganic architecture at an organic interface presents a significant challenge. Indeed, to stimulate growth of a CaP shell on vaccines, genetic modification was required to incorporate a specific peptide sequence known to have a high affinity for calcium ions9. This result highlights that enhancing the interfacial interactions between inorganic and organic components is a key to inducing biomineralization13. However, given that the tertiary structure of many biomacromolecules is critical to their function, it is unlikely that a strategy that involves modifying the primary peptide sequence could be generally applied. We posit that hybrid organic–inorganic materials would provide a more versatile and general method for encapsulating biomacromolecules as, in general, the protein domains have a high affinity for the organic moieties14. A rapidly growing class of hybrid materials termed metal-organic frameworks (MOFs) represent excellent candidates for this purpose, as they are: constructed from organic and inorganic components15, thermally and chemically $\\mathrm{stable}^{16-19}$ , can be grown on different substrates (films20, particles21 and gels22), and under mild biocompatible conditions19. In addition, they have been utilized as a biocompatible material for drug release19,23. Furthermore, MOFs possess open architectures and large pore volumes24, which can fparcoiltietcatie hpeorsoeulescctiovae tnrga2n5,s2p6,oretnaobf snmg atlhl mseollectiuvles nttheroauctgihon hoef the biomacromolecule (for example, enzymes) with the external environment. Hitherto, attempts to integrate biomacromolecules within MOFs have been limited in application by two main constraints: for post-synthetic infiltration only biomacromolecules analogous in size to the MOF pores can be loaded into the framework27–29, and in the preparation of MOF biocomposites only solvent resistant biomacromolecules can be used30. Overcoming these limitations would facilitate the fabrication of novel biocomposites and their exploitation for bioapplications31. \n\n![](images/ca3fb49763d3942cb33b8bcba9c975801a04dcf1159ab03e07ec9d790a6a173e.jpg) \nFigure 1 | Schematic illustration of biomimetically mineralized MOF. (a) Schematic of a sea urchin; a hard porous protective shell that is biomineralized by soft biological tissue (b) Schematic of a MOF biocomposite showing a biomacromolecule (for example, protein, enzyme or DNA), encapsulated within the porous, crystalline shell. \n\nHere we report that a wide range of biomacromolecules including proteins, DNA and enzymes can efficiently induce MOF formation and control the morphology of the resultant porous crystal via a biomimetic mineralization process under physiological conditions. Although biomineralization has been extensively investigated for inorganic systems, the concept has not been applied to MOFs. Here we demonstrate that the biomimetic mineralization of MOFs forms a nanoporous shell, which encapsulates the biomacromolecules and affords unprecedented protection from biological, thermal and chemical degradation with maintenance of bioactivity (Fig. 1). Furthermore, the encapsulated biomacromolecules can be released simply by a $\\mathsf{p H}$ change within a physiological environment. Zeolitic imidazolate framework-8 (ZIF-8), formed by coordination between $\\scriptstyle{\\mathrm{Zn}}^{2+}$ ions and 2-methylimidazole $(\\dot{\\mathrm{HmIm}})^{32}$ , is selected as a candidate MOF material for this study due to its high surface area, exceptional chemical and thermal stability and negligible cytotoxicity23,32,33. In addition, we demonstrate that other MOFs (HKUST-1, Eu/Tb-BDC and MIL-88A) can also be formed, highlighting the versatility of this biomimetic mineralization approach. \n\n# Results \n\nBiomimetic mineralization using bovine serum albumin. In a typical experiment for the biomimetically mineralized growth of ZIF-8, an aqueous solution containing $\\mathrm{\\dot{H}m I m}$ , $(160\\dot{\\mathrm{mM}},2\\mathrm{ml})$ and bovine serum albumin (BSA, 1 mg) were mixed with a separate aqueous solution of zinc acetate $(40\\mathrm{mM},2\\mathrm{ml})$ at room temperature. The solution instantaneously turned from transparent to opaque (within $^{1\\mathrm{s},}$ Supplementary Fig. 1). After centrifugation and washing, truncated cubic crystals of ZIF-8, $(\\sim1\\upmu\\mathrm{m})$ were found by scanning electron microscope (SEM; Fig. 2a) and powder X-ray diffraction (PXRD) measurements (Fig. 2d, Supplementary Methods). To ascertain that BSA is indeed encapsulated by a ZIF-8 crystalline shell, solutions of biomimetically mineralized ZIF-8 that had been washed with a surfactant to remove any surface bound proteins were examined by Fourier transform infrared spectroscopy (FTIR). The resulting spectra showed stretches characteristic of the BSA protein at $\\sim1,640\\ –1,660$ and $1,510{-}1,560\\mathrm{cm}^{-1};$ , corresponding to amide I (mainly from ${\\mathrm{C}}={\\mathrm{O}}$ stretching mode) and II band (mainly from a combination between of NH bending and CN stretching modes), respectively34. However, FTIR measurements collected from samples prepared by washing a solution containing a mixture of pre-formed ZIF-8 crystals and BSA protein with surfactant did not afford stretches attributable to BSA (Fig. 2e). These data clearly demonstrate that the mechanism of BSA encapsulation is not via absorption nor adsorption through the ZIF-8 pore network. Additional evidence of biomacromolecule encapsulation was garnered by using BSA tagged with fluorescein isothiocyanate (FITC) to induce the formation of ZIF-8. The resultant biocomposite was washed with surfactant and exposed to ultraviolet light, whereon a green emission at $521\\mathrm{nm}$ characteristic of FITC was observed (Fig. 2b). Furthermore, confocal microscopy revealed that the cross-sections of ZIF-8/ BSA crystals were homogenously luminescent (Fig. 2c, details in Supplementary Figs 2 and 3). In contrast, crystals isolated from a mixture of pre-formed ZIF-8 and FITC-labelled BSA were not emissive (Supplementary Fig. 4). \n\n![](images/8bcd5acc7a0923b479aa6f124a13d1fb8c757bcc47dc6990ea961f1ff6e535cb.jpg) \nFigure 2 | Characterization of biomimetically mineralized biocomposite. (a) SEM image showing the crystals obtained using BSA as a growth agent for biomimetic mineralization (scale bar, $1\\upmu\\mathrm{m})$ . (b) Photograph and (c) confocal laser scanning microscopy image of the biomomimetically mineralized ZIF-8 composite obtained using BSA labelled with FITC. This biocomposite (ZIF-8/FITC-BSA) was prepared at $37^{\\circ}\\mathsf C$ washed and exposed to ultraviolet light of wavelength 365 and $495\\mathsf{n m}$ , respectively (scale bar, $10\\upmu\\mathrm{m}\\rangle$ . (d) PXRD of the MOF-BSA biocomposite. (e) FTIR spectra of BSA (red), ZIF-8/BSA (orange), standard ZIF-8 post incubated with BSA after washing (blue), and standard ZIF-8 (black). (f) SAXS data of the ZIF-8/BSA biocomposite and a schematic showing the relative size of BSA to the mesopore. The observed Guinier knee can be fitted using the Unified model58 with a radius of gyration $(R_{\\mathrm{g}})^{59}$ of $35(\\pm5)\\mathbb{A},$ which is $17\\%$ larger than that of BSA $29.9\\AA$ (ref. 60). $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ Schematic proposing the biomimetically mineralized growth of ZIF-8. Each BSA molecule attracts 31 2-methylimidazole $({\\mathsf{H m l m}})$ ligands and $22Z{\\mathsf{n}}^{2+}$ ions, facilitating the nucleation of ZIF-8 crystals39. \n\nPhysical characterization of the ZIF-8/BSA biocomposite. To assess the permanent porosity of the ZIF-8/BSA biocomposite, a $77\\mathrm{K}$ nitrogen adsorption isotherm was measured (Supplementary Figs 5 and 6). The resulting isotherm is best described as Type 1 in shape and BET analysis of the data afforded a surface area of $1,381\\dot{\\mathrm{m}}^{2}\\mathrm{g}^{-1}$ , showing a decrease of porosity relative to pure ZIF-8 crystals32, which is consistent with the presence of BSA. To further investigate the hierarchical pore structure of the ZIF-8/ BSA biocomposite, small-angle X-ray scattering experiments (SAXS) were carried out. Analysis of the data indicates the presence of mesopores within the MOF with a radius of $\\bar{3}.5\\pm0.5\\mathrm{nm}$ (Fig. 2f). We note that such mesopores, which are of sufficient size to accommodate the biomolecule (Fig. 2f, inset), are not detected in pure ZIF-8 (Supplementary Fig. 7). \n\nThe biomineralization mechanism occurring in natural processes is widely attributed to the specific ability of amino acids, peptide fragments and more complex biological entities, to concentrate inorganic cations (for example $\\mathrm{Ca}^{2+}$ and $\\mathrm{Zn}^{2+}$ ) to seed biominerals9,35,36. In this case, we posit that MOF biomimetic mineralization is facilitated by the biomacromolecules affinity towards the imidazole-containing building block arising from intermolecular hydrogen bonding and hydrophobic interactions37,38. $^1\\mathrm{H}$ -NMR spectroscopy and ICP analysis confirmed that each BSA protein molecule accumulates $\\sim31$ HmIm ligands and $22\\ Z{\\mathrm{n}}^{2+}$ ions, respectively (Fig. $2\\mathrm{g}$ and Supplementary Fig. 8). Increasing the local concentration of both metal cations and organic ligands would facilitate prenucleation clusters of ZIF-8 around the biomacromolecules, and thus lead to controlled crystal formation39. This hypothesis is further confirmed by in situ synchrotron SAXS experiments designed to follow the MOF biomimetic mineralization process (Supplementary Figs 9 and 10). Analysis of the $\\mathrm{\\DeltaX}$ -ray scattering reveals that small particles (radius of gyration, $R_{\\mathrm{g}}=35\\mathrm{nm},$ were formed in small quantity in the aqueous solution immediately after injection of the ZIF-8 precursors. In contrast, when BSA was introduced into the solution, the rapid formation of a second generation of larger particles $(\\sim30s,$ $R_{\\mathrm{g}}=100\\mathrm{nm},$ and a simultaneous depletion of the small particles were observed (Supplementary Figs 9 and 10). Increasing the amount of BSA added to the MOF precursor solution still facilitated the prompt formation of particles (Supplementary Figs 11–14). After separation and washing, samples of the crystalline product analysed by PXRD revealed that increasing the amount of BSA was enough to modify the ZIF-8 framework from a crystalline to mostly amorphous morphology (Supplementary Fig. 13). This further demonstrates that the described method mimics the natural processes in which the degree of crystallinity is carefully tuned by living organisms due to complex biological regulation8,40. \n\n![](images/01bcdf210f09aea2e8aca9218f175c474bfe3d9c9b7516d1fb8b52973f746e32.jpg) \nFigure 3 | Characterization of biomimetically mineralized ZIF-8 with biomolecules. (a) PXRD patterns of the crystals obtained using various biomacromolecules as biomimetic mineralizion agents. Protein encapsulation efficiency: BSA $\\sim100\\%$ , human serum albumin (HSA) $\\sim100\\%$ OVA $\\sim100\\%$ , lysozyme $\\sim96\\%$ , HRP $\\sim100\\%$ , ribonuclease A $\\sim86\\%$ , haemoglobin $\\sim90\\%$ , trypsin $\\sim96\\%$ , lipase $\\sim88\\%$ , insulin $\\sim86\\%$ , glucose dehydrogenase (PQQ-GDH) $\\sim82\\%$ urease $\\sim95\\%$ . In each case, the intensity and peak positions of the biocomposites match those of pure ZIF-8. $(6-m)$ Scanning electron microscopy images showing crystals obtained using: $(\\pmb{\\ b})$ OVA, (c) ribonuclease ${\\mathsf A},$ (d) HSA, (e) pyroloquinoline quinonedependent glucose dehydrogenase ((PQQ)GDH), $(\\pmb{\\uparrow})$ lipase, $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ haemoglobin, ${\\bf\\Pi}({\\bf h})$ lysozyme, (i) insulin, $\\mathfrak{G}$ HRP, $(\\mathbf{k})$ trypsin, (l) urease and $\\mathbf{\\eta}(\\mathbf{m})$ oligonucleotide. Scale bars, $1\\upmu\\mathrm{m}$ . While several biomacromolecules induce the standard rhombic dodecahedral morphology for the ZIF-8 biocomposites $(\\mathbf{c,d,m})$ , other biomacromolecules gave rise to various morphological features such as truncated cubic (e,f,h,i,l), nanoleaf $(\\pmb{\\ b})$ , nanoflower $(\\mathbf{j})$ and nanostar ${\\bf\\Pi}({\\bf k})$ , respectively. \n\nExtension of bimimetic mineralization to other MOFs. Although we demonstrate biomimetically mineralized growth of ZIF-8, other types of MOFs such as $\\mathrm{{\\dot{C}u}}_{3}(\\mathrm{{BTC})}_{2}$ (HKUST-1), $\\mathrm{Eu}_{2}(1,4\\mathrm{-BDC})_{3}(\\bar{\\mathrm{H}}_{2}\\mathrm{O})_{4}$ , $\\mathrm{Tb}_{2}(1,4\\mathrm{-BDC})_{3}(\\mathrm{H}_{2}\\mathrm{O})_{4}$ and ${\\mathrm{Fe}}(\\mathrm{III})$ dicarboxylate MOF (MIL-88A) can be successfully induced by BSA (Supplementary Figs 15–19). FTIR performed before and after the BSA-induced MOF coating shows that the amide vibrational mode for the MOF/BSA composites is shifted towards higher wavenumbers (Fig. 2e and Supplementary Fig. 20), indicating that there is a protein–MOF interaction due to the coordination between the $Z\\mathrm{n}$ cations and the carbonyl group of the proteins41. \n\nBiomimetic mineralization extended to enzymes and DNA. We sought to explore the scope of biomimetically mineralized MOF growth by using a series of biomacromolecules including ovalbumin (OVA), ribonuclease A, human serum albumin (HSA), pyrroloquinoline quinone-dependent glucose dehydrogenase ((PQQ)GDH), lipase, haemoglobin, lysozyme, insulin, horseradish peroxidase (HRP), trypsin, urease and oligonucleotide. Notably, PXRD measurements (Fig. 3a) and nitrogen gas adsorption isotherms (Supplementary Fig. 21) confirm that ZIF-8 is present in its crystalline form and remains permanently porous. Furthermore, SEM images show that the crystal morphology has a unique dependence on the biomacromolecule (Fig. $3\\mathrm{b-m},$ ). This observation is analogous to natural biomineralization processes where intricate crystalline morphologies are common6. Indeed, in this work, nanoleaves, nanoflowers and nanostars are obtained by using OVA, HRP and trypsin as biomimetic mineralization agents and for single-strand DNA the typical rhombic ZIF-8 dodecahedron crystal morphology was observed. \n\nProtective properties of biomimetically mineralized ZIF-8. In nature, biomineral coatings are commonly used to protect soft tissue from its surrounding environment. This knowledge inspired us to examine whether MOF coatings could provide a similar barrier that would enable embedded biomacromolecules to withstand extreme conditions (for example, high temperature and organic solvents) that would normally lead to decomposition. Enhancing the robustness of functional biomacromolecules would extend their potential for use in the pharmaceutical and chemical synthesis sectors, addressing a major challenge in biotechnology2,27,42. \n\nTypically, exposing enzymes to elevated temperatures or organic solvents results in an irreversible loss of bioactivity due to the disruption of non-covalent interactions43. Thus, we selected three well-studied enzymes (HRP, (PQQ)GDH and urease, Supplementary Figs 22 and 23) and assessed whether a MOF coating could enhance their stability to extreme conditions. Accordingly, pyrogallol was added to a mixture of a ZIF-8/HRP biocomposite and trypsin in phosphate buffer at $\\mathrm{\\pH}\\ 7.4$ . Remarkably, in the presence of trypsin, the ZIF-8/HRP biocomposite essentially retained the bioactivity of HRP showing an $88\\%$ conversion of pyrogallol to purporogallin (Fig. 4). This compares with only $20\\%$ conversion for an analogous experiment where non-protected HRP was exposed to trypsin. This experiment confirms that the MOF coating acts as a protective layer for the enzyme that allows diffusion of the pyrogallol substrate $(0.64\\mathrm{nm})$ through the ZIF-8 pore cavities $(1.16\\mathrm{nm})$ while preventing the egress of the proteolytic agent trypsin. To benchmark the protective properties of the MOF layers, we compared them to other, commonly employed, porous protective coatings: $\\mathrm{CaCO}_{3}$ and $\\mathrm{SiO}_{2}$ with pores ranging from 7 to $100\\mathrm{nm}$ (Supplementary Figs 24 and 25). We immersed free HRP, $\\mathrm{CaCO_{3}/H R P}$ , $\\mathrm{SiO}_{2}/\\mathrm{HRP}$ and ZIF-8/HRP biocomposites in boiling water for $^\\mathrm{1h}$ (Fig. 4). As expected, the free enzyme completely lost activity, while the $\\mathrm{CaCO_{3}/H R P}$ converted $39\\%$ and $\\mathrm{SiO}_{2}^{-}/\\mathrm{HRP}$ composites converted $65\\%$ ( $7\\mathrm{nm}$ pore), $44\\%$ $20\\mathrm{nm}$ pore), $17\\%$ 1 $50\\mathrm{nm}$ pore) and $13\\%$ ( $\\mathsf{100}\\mathsf{n m}$ pore) of substrate, respectively. These values are substantially less than the $88\\%$ conversion achieved by the ZIF-8 protected HRP under the same conditions. In a further set of experiments, the same systems were immersed in boiling dimethylformamide for $^\\mathrm{1h}$ (Fig. 4). Once again, the free enzyme completely lost activity, while enzymes embedded in carbonate and silica particles showed 32 and $22\\%$ substrate conversion, respectively. Under these conditions, the MOF biocomposites showed a $90\\%$ conversion demonstrating again the unprecedented protective properties of the MOF layers. PXRD measurements of the biocomposites before and after the treatment in various harsh conditions showed that the peak characteristics of ZIF-8 remained unchanged (Supplementary Fig. 26), confirming the stability of the MOF biocomposites. \n\n![](images/1df442c392d28397eedf28346f5cf4aa5e62a29a6e11ba6ecc67096897949424.jpg) \nFigure 4 | Protective performance of ZIF-8 coatings on HRP. Product conversion of free HRP, the biomimetically mineralized ZIF-8 using HRP (ZIF-8/HRP), HRP protected by calcium carbonate $\\mathrm{\\DeltaCaCO_{3}/H R P)}$ and HRP protected by mesoporous silica ${\\mathrm{\\Omega}}\\langle{\\mathsf{S i O}}_{2}/{\\mathsf{H R P}},$ $\\mathsf{S i O}_{2}$ with average pore size of 7, 20, 50 and $100\\mathsf{n m},$ ) in the presence of proteolytic agent, trypsin, after treatment in boiling water for $1\\mathsf{h},$ , and after treatment in boiling dimethylformamide (DMF) for 1 h at $153^{\\circ}\\mathsf C,$ respectively. Data were normalized against free HRP activity at room temperature. Error bars represent the s.d. of three independent experiments. \n\nIt has been reported that smaller pores engender higher stability of the biomacromolecuels in denaturing conditions44. We confirm this trend in our experiments using silica nanoparticles of varied pore sizes (Fig. 4). Therefore, the superior stability afforded by the MOF protective layer compared with $\\dot{\\mathrm{CaCO}_{3}}$ and $\\mathrm{SiO}_{2}$ can be directly related to the tight encapsulation of each biomacromolecule by the MOF structure. Indeed, each cavity within the MOF was found to range from $17\\%$ (for BSA) to $30\\%$ (for urease) larger than the size of their copying biomacromolecules as measured using SAXS (Fig. 2f, Supplementary Fig. 27). In addition, FTIR experiments of biomimetically mineralized ZIF-8 confirmed the interaction between the carbonyl groups of the protein backbone and the $\\mathrm{Zn}^{2+}$ cations of ZIF-8 (Supplementary Fig. 28). Indeed, bonding interactions between enzymes and substrates are known to improve the robustness of biomacromolecules45–47; accordingly, these data point to a further contribution to the improved stability of the MOF-encapsulated biomolecules. Enzymatic activity studies performed on urease and $({\\mathrm{PQQ}}){\\mathrm{GDH}}$ as a biomimetic mineralization agent for the growth of ZIF-8 further confirmed improved stability over the corresponding free enzymes (Supplementary Figs 22 and 23). For example, urease, which denatures above $45^{\\circ}\\mathrm{C}$ (ref. 48), can be protected up to $80^{\\circ}\\mathrm{C}$ exemplifying a significant relative improvement in the enzyme stabilization. Because of the size of urease (B600 kDa)49 and its rapid degradation in presence of alcohols (for example, methanol)50, the proposed biomimetic mineralizion process overcomes the constraints of the previously reported methods that aimed to use MOFs as hosts for biomacromolecules (that is, biomolecules larger than MOF pores27–29 and/or the need for organic solvents30). \n\nRelease of enzymes and proteins from ZIF-8 biocomposites. While these MOF coatings display properties advantageous for protecting enzymes in applications such as industrial catalysis and environmental remediation, the ability to control the release of bioactive macromolecules such as proteins, enzymes and DNA is highly desired, as it would provide additional opportunities in the areas of therapeutic delivery and genetic engineering10. Indeed, as a class, biomacromolecules offer significant advantages over small molecules such as high specificity and potency1 0 To this end, we demonstrate that the biomimetically mineralized ZIF-8 layer can be removed via simple modulation of $\\mathrm{pH}^{23}$ (Supplementary Fig. 29), and, importantly, that the liberated biomacromolecule retains its native activity. To assess the effect of $\\mathrm{\\tt{pH}}$ on the protective layer, we employed ZIF-8/FITC-BSA biocomposites. The $\\mathrm{\\pH}$ -induced release profiles show that a change from 7.4 to 6 is sufficient to release the encapsulated proteins (Supplementary Fig. 30). \n\nTo demonstrate that the activity of the occluded biomacromolecule is maintained after the protective shell is removed, two separate biocomposites were prepared: a ZIF-8/ DQ-OVA (DQ-OVA is a fluorogenic protein that shows high florescence once proteolysis occurs) and ZIF-8/trypsin (trypsin is a proteolytic enzyme). The two biocomposites were added to a PBS solution at $\\mathrm{pH}~7.4$ . The fluorescent emission from this solution was monitored and found to be analogous to that of free intact DQ-OVA protein (Fig. 5a), thus indicating that the biomacromolecules remain stable within the MOF. When the pH of the solution was adjusted to 6.0, a drastic increase in the fluorescence intensity was observed which is attributed to the proteolysis of the DQ-OVA into luminescent fragments; suggesting that trypsin and DQ-OVA have been released from their protective MOF coatings and are free to interact in solution (Fig. 5b–e). This result confirms that the bioactivity of both the trypsin and the DQ-OVA is preserved following their release from ZIF-8 and, along with the combined low toxicity of the ZIF-8 coating23,33, supports the potential application of MOFs in the area of biobanking or drug delivery. \n\n# Discussion \n\nHere we have demonstrated the first example of biomimetic mineralization of MOFs. Furthermore, we show the presence of a crucial synergistic interaction in the solution between the MOF precursors and the biomacromolecules. This involves the biomacromolecule concentrating the MOF building blocks, which leads to nucleation of porous crystals. In this process, the biomacromolecules regulate the crystal size, morphology and crystallinity while encapsulating itself within the porous crystal and concomitantly generating new cavities that both tightly surround the biomacromolecules and form bonding interactions with the protein backbone. This mechanism is shown to protect a variety of biomacromolecules (for example, proteins and enzymes) from inhospitable environments. Enzymes encapsulated in MOFs were shown to maintain their activity even after the exposure to extreme conditions. This protective capacity is remarkable, and far exceeds that of current materials used for this purpose such as $\\mathrm{CaCO}_{3}$ and mesoporous silica. The controlled release of the biomacromolecules as a bioactive cargo from its protective MOF coating can be achieved via simple pH modification. We anticipate that this bioinspired approach for protecting and delivering functional biomacromolecules will facilitate their application in areas where stability has previously been an issue, such as industrial biocatalysis, biopharmaceuticals and biobanking. \n\n![](images/b3a064a1169b86f76fa5516a11ddd1756690ae6c03e73caa1d78bee53036bea1.jpg) \nFigure 5 | Controlled release of bioactive enzymes and proteins from ZIF-8 biocomposites. (a) Fluorescent measurement of the PBS solution containing biomimetically mineralized zeolitic imidazolate frameworkfluorogenic protein (ZIF-8/DQ-OVA) and biomimetically mineralized zeolitic imidazolate framework-trypsin (ZIF-8/trypsin) particles. At pH 7.4, the fluorescent emission (blue line) was analogous to that of free intact DQ-OVA protein (brown line). At $\\mathsf{p H}6.0$ , a drastic increase in the fluorescence intensity (red line) was observed, which was attributed to the proteolysis of the DQ-OVA into luminescent fragments suggesting that trypsin and DQ-OVA have been released and are free to interact in solution. (b–e) Schematics showing the release of DQ-OVA (red) and trypsin (yellow) from ZIF-8 biocomposites at $\\mathsf{p H}6.0$ and degradation of DQ-OVA into fluorescent fragments as a result of proteolysis by trypsin. \n\n# Methods \n\nMaterials. Cy3-labelled Oligonucleotide (50 bases, MW: 16 kDa) was purchased from Trilink Biotechnologies Inc. (San Diego, California, USA). DQ-ovalbumin (DQ-OVA) was obtained from Life Technologies (VIC, Australia). All other reactants were purchased from Sigma-Aldrich and used without further modification. \n\nBiomimetic mineralization of ZIF-8/proteins. Various amounts of the appropriate proteins (e.g. 10, 50, 100, $200\\mathrm{mg}$ BSA) and enzymes (e.g. $80\\mathrm{mg}\\mathrm{HRP}$ ) were added into a solution of 2-methylimidazole ( $160\\mathrm{mM}$ , $20\\mathrm{ml}$ , pH 10.3) in deionized water. (For insulin, $10\\mathrm{mg}$ insulin was added in water, the pH was adjusted to 3–4 with HCl $20\\mathrm{mM})$ to completely dissolve the insulin and adjusted back to $\\mathrm{pH}10.3$ before the addition of 2-methylimidazole $(160\\mathrm{mM})$ ). A separate solution of zinc acetate dihydrate dissolved in deionised water (40 mM, $20\\mathrm{ml}$ ) was also prepared. \n\nThese two solutions were combined and then agitated for $10s$ The resulting solution was aged for $12\\mathrm{{h}}$ at room temperature. The obtained precipitate was recovered by centrifugation at $6{,}000\\mathrm{r.p.m}$ . for $10\\mathrm{min}$ and then washed, sonicated, and centrifuged twice each in water followed by ethanol. The encapsulation efficiency of proteins in ZIF-8 was determined by fluorescent spectrophotometry using a pre-determined calibration curve of FITC-labelled proteins. Protein encapsulation efficiency: BSA $\\sim100\\%$ , HSA $\\sim100\\%$ , $\\sim100\\%$ , lysozyme $\\sim96\\%$ , HRP $\\sim100\\%$ , ribonuclease A $\\sim86\\%$ , haemoglobin $\\sim90\\%$ , trypsin $\\sim96\\%$ , lipase $\\sim88\\%$ , insulin $\\sim86\\%$ , PQQ-GDH $\\sim82\\%$ , urease $\\sim95\\%$ . \n\nBiomimetic mineralization of ZIF-8/DNA. Cy3-labelled oligonucleotide $(200\\upmu\\mathrm{l};\\$ $20.8\\upmu\\mathrm{M})$ was added into a solution of 2-methylimidazole $(160\\mathrm{mM},0.5\\mathrm{ml})$ in deionized water. A separate solution of zinc acetate dissolved in deionised water ( $\\mathrm{\\dot{2}0m M}$ , $0.5\\mathrm{ml}\\cdot$ ) was prepared. These two solutions were then mixed and vortexed for 10 s. The mixture was aged for $^{12\\mathrm{h}}$ at room temperature. The obtained precipitate was recovered by centrifugation at $6{,}000\\mathrm{r.p.m}$ . for $10\\mathrm{min}$ and then washed, sonicated, and centrifuged twice each in water followed by ethanol. The encapsulation efficiency $(75\\%)$ of the DNA in ZIF-8 was determined using a fluorescence spectrophotometer collecting the emission at $561\\mathrm{nm}$ $\\mathrm{\\DeltaCy3}$ emission maximum) from a pre-determined calibration curve, by measuring the concentrations of the DNA in the precursor solution and in the supernatant of the obtained crystals. \n\nBiomimetic mineralization of HKUST-1. Benzene-1,3,5-tricarboxylic acid (BTC) was dissolved in ethanol $53.45\\mathrm{mM}$ , $20\\mathrm{ml}$ ). A separate solution of copper(II) nitrate dissolved in deionized water ( $40.09\\mathrm{mM}$ , $20\\mathrm{ml}$ ) was also prepared. These two solutions were then mixed and vortexed for 10 s. BSA solution ( $(1.2\\mathrm{ml};$ ; $10\\mathrm{mg}\\mathrm{ml}^{-1}$ in MQ) was then added into the mixture. The mixture was aged for $^{12\\mathrm{h}}$ at room temperature. The suspension was centrifuged at $6{,}000\\mathrm{r.p.m}$ . for $20\\mathrm{min}$ , and subjected to centrifugation–wash cycles three times using ethanol. \n\nBiomimetic mineralization of Eu-BDC and Tb-BDC. Disodium terephthalate salt was prepared following the procedure from the literature51. $5\\mathrm{g}$ of terephthalic acid (BDC) was dissolved in deionized water to which $2.32{\\mathrm{g}}$ of sodium hydroxide was added. The resulting solution was evaporated to dryness and the solid was then resuspended in ethanol and refluxed for $^{\\mathrm{1h}}$ before filtering, washing with water and drying. The disodium salt of terephthalic acid was then dissolved in deionized water $(10\\mathrm{mM},20\\mathrm{ml})$ to which the $20\\mathrm{mg}$ of BSA was dissolved. The $\\mathrm{EuCl}_{3}.6\\mathrm{H}_{2}\\mathrm{O}$ or $\\mathrm{TbCl}_{3}.6\\mathrm{H}_{2}\\mathrm{O}$ was also dissolved in deionized water (10 mM, 20 ml). The lanthanide salt solution and the BSA ligand solution were then mixed and vortexed for $10\\mathrm{{s}}$ The solution was gently agitated for $12\\mathrm{h}$ before recovering the precipitate by centrifugation at $6{,}000\\mathrm{r.p.m}$ . for $20\\mathrm{min}$ and then washing and centrifuging in ethanol three times. \n\n# Biomimetic mineralization of MIL-88A. Various amount of BSA (2, 4, 8, \n\n$16\\mathrm{mgml})$ was dissolved in fumaric acid solution in deionized water $(25\\mathrm{mM})$ . A separate solution of $\\mathrm{FeCl}_{3}\\cdot6\\mathrm{H}_{2}\\mathrm{O}$ $25\\mathrm{mM})$ was prepared and immediately mixed with equal volumes of BSA-containing fumaric acid solution and vortexed for $10\\mathrm{{s}}$ The solution mixture was aged for 7 days at room temperature. The suspension was centrifuged at $6{,}000\\mathrm{r.p.m}$ . for $20\\mathrm{min}$ , and subjected to centrifugation–wash cycles three times using ethanol. \n\nBioactivity of ZIF-8/HRP. The obtained crystals were firstly redispersed in SDS $_{\\mathrm{(0.2g})}$ in $2\\mathrm{ml}$ deionized water) solution at $70^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ to wash off the free enzymes on the crystal surface52,53, followed by three centrifugation/wash cycles in water. The activity of HRP (1.11.1.7; lot no. 125F-9640, HRPO Type U; Sigma Chemical Co., St. Louis, MO) was determined by measuring the rate of decomposition of hydrogen peroxide with pyrogallol as the hydrogen donor, which can be converted to a yellowish product, purpurogallin54. In a typical assay, solution A containing $76\\upmu\\mathrm{l}\\mathrm{KH}_{2}\\mathrm{PO}_{3}$ ( $100\\mathrm{mM}$ , $\\mathrm{\\pH\\6.0\\dot{}}$ ), $38\\upmu\\mathrm{l}\\ \\mathrm{H}_{2}\\mathrm{O}_{2}$ $5\\%$ w/w in deionized water), $76\\upmu\\mathrm{l}$ pyrogallol $(5\\%$ w/w in deionized water) and $1.8\\mathrm{ml}$ of PBS buffer $\\mathrm{(pH7.4)}$ was prepared. To solution A, ZIF-8/HRP crystals were added, and the absorbance of the solution was immediately monitored at $420\\mathrm{nm}$ using a UV-Vis spectrophotometer at $30s$ increments. In an enzymatic activity assay using free HRP, the amount of free enzymes introduced into solution A was adjusted to be equal to the amount of enzymes loaded into ZIF-8/HRP, as determined from the loading efficiency. \n\nBioactivity of ZIF-8/(PQQ)GDH. The obtained crystals were redispersed in a SDS $(10\\%\\mathrm{w/w}$ in deionised water, $2\\mathrm{ml}.$ solution at $70^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ to wash off the free enzymes on the crystal surface,52,53 followed by three centrifugation/wash cycles in water. The activity of (PQQ)GDH was determined using phenazine methosulfate as an electron acceptor55,56. In a typical assay, solution B containing $\\mathrm{1ml}$ glucose $20\\mathrm{mM}$ in $10\\mathrm{mM}$ MOPS buffer $\\mathrm{pH}7.0$ ) $10\\upmu12,6$ -dichloroindophenol $\\mathrm{{(0.1\\mathrm{{mM}}}}$ in deionized water), $10\\upmu\\mathrm{l}$ phenazine methosulfate $\\mathrm{0.06\\:mM}$ in deionised water) was prepared. To solution B, ZIF-8/(PQQ)GDH crystals were added, and the absorbance of the solution was immediately monitored at $600\\mathrm{nm}$ using a UV-Vis spectrophotometer at $30s$ increments. In an enzymatic activity assay using free (PQQ)GDH, the amount of free enzymes introduced into solution B was adjusted to be equal to the amount of enzymes loaded into ZIF-8/(PQQ)GDH, as determined from the loading efficiency. \n\nBioactivity of ZIF-8/urease. The activity of ZIF-8/urease was determined by measuring the pH increase as a result of urea conversion to ammonia, using phenol red as a $\\mathrm{\\pH}$ indicator57. Phenol red solution was prepared by dissolving $10\\mathrm{mg}$ phenol red in $284\\upmu\\mathrm{l}$ of $\\mathrm{\\DeltaNaOH}$ solution (0.1 M), and made up to a final volume of $10\\mathrm{ml}$ with deionized water. In a typical assay, $10\\upmu\\mathrm{l}$ phenol red solution, ${990\\upmu\\mathrm{l}}$ urea solution $(0.5\\mathbf{M})$ and ZIF-8/urease was added into an ultraviolet–visible cuvette, and the absorbance of the solution was monitored at $560\\mathrm{nm}$ using a UV-Vis spectrophotometer at 30 s increments. \n\npH-triggered release of biomacromolecules. ZIF-8/FITC-BSA $\\mathrm{(1mg)}$ was dispersed in $2\\mathrm{ml}$ of pH-adjusted PBS at $\\mathrm{pH}7.4$ or $\\mathrm{pH}6.0$ at $37^{\\circ}\\mathrm{C}$ under gentle agitation. Over $24\\mathrm{h}$ , at regular time intervals, the crystal dispersion was centrifuged at $6{,}000\\mathrm{r.p.m}$ . for $20\\mathrm{min}$ , and the fluorescence intensity of the released FITC-BSA was assessed by monitoring the fluorescent intensity from the supernatant using a fluorescence spectrophotometer. \n\nBioactivity from released enzymes. Equal volumes of colloidal solution containing ZIF-8/trypsin and ZIF-8/DQ-OVA were added to $2\\mathrm{ml}$ pH-adjusted PBS at $\\mathrm{pH}7.4$ or $\\mathrm{pH}6.0$ at $37^{\\circ}\\mathrm{C}$ under gentle agitation. The fluorescent emission at $515\\mathrm{nm}$ from the BODIPY dye in the solution that resulted from the proteolysis of DQ-OVA by trypsin was constantly monitored using a fluorescence spectrophotometer. \n\n# References \n\n1. Estroff, L. A. Introduction: biomineralization. Chem. Rev. 108, 4329–4331 (2008). \n2. Meldrum, F. C. & Co¨lfen, H. Controlling mineral morphologies and structures in biological and synthetic systems. Chem. Rev. 108, 4332–4432 (2008). \n3. Natalio, F. et al. Flexible minerals: self-assembled calcite spicules with extreme bending strength. Science 339, 1298–1302 (2013). \n4. Xu, A.-W., Ma, Y. & Co¨lfen, H. Biomimetic mineralization. J. Mater. Chem. 17, 415–449 (2007). \n5. Aizenberg, J. New nanofabrication strategies: inspired by biomineralization. MRS Bull. 35, 323–330 (2010). \n6. Nudelman, F. & Sommerdijk, N. A. J. M. Biomineralization as an inspiration for materials chemistry. Angew. Chem. Int. Ed. 51, 6582–6596 (2012). \n7. Mann, S. Molecular tectonics in biomineralization and biomimetic materials chemistry. Nature 365, 499–505 (1993). \n8. Sanchez, C., Arribart, H. & Giraud Guille, M. M. Biomimetism and bioinspiration as tools for the design of innovative materials and systems. Nat. Mater. 4, 277–288 (2005). \n9. Wang, G. et al. Rational design of thermostable vaccines by engineered peptideinduced virus self-biomineralization under physiological conditions. Proc. Natl Acad. Sci. USA 110, 7619–7624 (2013). \n10. Mitragotri, S., Burke, P. A. & Langer, R. Overcoming the challenges in administering biopharmaceuticals: formulation and delivery strategies. Nat. Rev. Drug Discov. 13, 655–672 (2014). \n11. Bornscheuer, U. T. et al. Engineering the third wave of biocatalysis. Nature 485, 185–194 (2012). \n12. Savage, N. Logistics: keeping cool. Nature 507, S8–S9 (2014). \n13. Harding, J. H. et al. Computational techniques at the organic \u0002 inorganic interface in biomineralization. Chem. Rev. 108, 4823–4854 (2008). \n14. Vanden Heuvel, J. P. in Cellular and Molecular Toxicology Vol. 14 (eds Vanden Heuvel, J. P., Perdew, G. H., Mattes, W. B. & Greenlee, W. F.) 29–56 (Elsevier Science B.V., 2002). \n15. Yaghi, O. M. et al. Reticular synthesis and the design of new materials. Nature 423, 705–714 (2003). \n16. Furukawa, H., Cordova, K. E., O’Keeffe, M. & Yaghi, O. M. The chemistry and applications of metal-organic frameworks. Science 341, 1230444 (2013). \n17. Foo, M. L., Matsuda, R. & Kitagawa, S. Functional hybrid porous coordination polymers. Chem. Mater. 26, 310–322 (2014). \n18. D’Alessandro, D. M., Smit, B. & Long, J. R. Carbon dioxide capture: prospects for new materials. Angew. Chem. Int. Ed. 49, 6058–6082 (2010). \n19. Horcajada, P. et al. Metal–organic frameworks in biomedicine. Chem. Rev. 112, 1232–1268 (2012). \n20. Be´tard, A. & Fischer, R. A. Metal–organic framework thin films: from fundamentals to applications. Chem. Rev. 112, 1055–1083 (2012). \n21. Doherty, C. M. et al. Using functional nano- and microparticles for the preparation of metal–organic framework composites with novel properties. Acc. Chem. Res. 47, 396–405 (2014). \n22. Garai, A., Shepherd, W., Huo, J. & Bradshaw, D. Biomineral-inspired growth of metal–organic frameworks in gelatin hydrogel matrices. J. Mater. Chem. B 1, 3678–3684 (2013). \n23. Zhuang, J. et al. Optimized metal–organic-framework nanospheres for drug delivery: evaluation of small-molecule encapsulation. ACS Nano 8, 2812–2819 (2014). \n24. An, J. et al. Metal-adeninate vertices for the construction of an exceptionally porous metal-organic framework. Nat. Commun. 3, 604 (2012). \n25. Ameloot, R. et al. Interfacial synthesis of hollow metal–organic framework capsules demonstrating selective permeability. Nat. Chem. 3, 382–387 (2011). \n26. Falcaro, P. et al. A new method to position and functionalize metal-organic framework crystals. Nat. Commun. 2, 237 (2011). \n27. Deng, H. et al. Large-pore apertures in a series of metal-organic frameworks. Science 336, 1018–1023 (2012). \n28. Lykourinou, V. et al. Immobilization of MP-11 into a mesoporous metal– organic framework, MP-11@mesoMOF: a new platform for enzymatic catalysis. J. Am. Chem. Soc. 133, 10382–10385 (2011). \n29. Chen, Y. et al. How can proteins enter the interior of a MOF? investigation of Cytochrome c translocation into a MOF consisting of mesoporous cages with microporous windows. J. Am. Chem. Soc. 134, 13188–13191 (2012). \n30. Lyu, F., Zhang, Y., Zare, R. N., Ge, J. & Liu, Z. One-pot synthesis of proteinembedded metal–organic frameworks with enhanced biological activities. Nano Lett. 14, 5761–5765 (2014). \n31. Falcaro, P. et al. MOF positioning technology and device fabrication. Chem. Soc. Rev. 43, 5513–5560 (2014). \n32. Park, K. S. et al. Exceptional chemical and thermal stability of zeolitic imidazolate frameworks. Proc. Natl Acad. Sci. USA 103, 10186–10191 (2006). \n33. Sun, C.-Y. et al. Zeolitic imidazolate framework-8 as efficient pH-sensitive drug delivery vehicle. Dalton Trans. 41, 6906–6909 (2012). \n34. Barth, A. & Zscherp, C. What vibrations tell us about proteins. Q. Rev. Biophys. 35, 369–430 (2002). \n35. Trzaskowski, B., Adamowicz, L. & Deymier, P. A. A theoretical study of zinc(II) interactions with amino acid models and peptide fragments. J. Biol. Inorg. Chem. 13, 133–137 (2008). \n36. Hwang, E. T., Tatavarty, R., Chung, J. & Gu, M. B. New functional amorphous calcium phosphate nanocomposites by enzyme-assisted biomineralization. Appl. Mater. Interfaces 5, 532–537 (2013). \n37. Lukton, A. Participation of imidazole in intramolecular hydrogen bonding. Nature 192, 422–424 (1961). \n38. Caue¨t, E., Rooman, M., Wintjens, R., Lie´vin, J. & Biot, C. Histidine \u0002 aromatic interactions in proteins and protein \u0002 ligand complexes: quantum chemical study of X-ray and model structures. J. Chem. Theory Comput. 1, 472–483 (2005). \n39. Cravillon, J. et al. Fast nucleation and growth of ZIF-8 nanocrystals monitored by time-resolved in situ small-angle and wide-angle X-Ray scattering. Angew. Chem. Int. Ed. 50, 8067–8071 (2011). \n40. Weiner, S. & Dove, P. M. An overview of biomineralization processes and the problem of the vital effect. Rev. Mineral. Geochem. 54, 1–29 (2003). \n41. Feng, Y., Schmidt, A. & Weiss, R. A. Compatibilization of polymer blends by complexation. 1. spectroscopic characterization of ion \u0002 amide interactions in ionomer/polyamide blends. Macromolecules 29, 3909–3917 (1996). \n42. Koeller, K. M. & Wong, C.-H. Enzymes for chemical synthesis. Nature 409, 232–240 (2001). \n43. Toba, S. & Merz, K. M. The concept of solvent compatibility and its impact on protein stability and activity enhancement in nonaqueous solvents. J. Am. Chem. Soc. 119, 9939–9948 (1997). \n44. Hartmann, M. & Kostrov, X. Immobilization of enzymes on porous silicas – benefits and challenges. Chem. Soc. Rev. 42, 6277–6289 (2013). \n45. Secundo, F. Conformational changes of enzymes upon immobilisation. Chem. Soc. Rev. 42, 6250–6261 (2013). \n46. Su, Y. et al. Improving the thermostability of a methyl parathion hydrolase by adding the ionic bond on protein surface. Appl. Biochem. Biotechnol. 165, 989–997 (2011). \n47. Ferna´ndez-Lorente, G. et al. in Methods In Non-Aqueous Enzymology. (ed. Gupta, P. D. M. N.) 36–51 (Birkha¨user, 2000). \n48. Akg¨ol, S., Yalc¸ınkaya, Y., Bayramog˘lu, G., Denizli, A. & Arıca, M. Y. Reversible immobilization of urease onto Procion Brown MX-5BR-Ni(II) attached polyamide hollow-fibre membranes. Process Biochem. 38, 675–683 (2002). \n49. Krajewska, B. & Ureases, I. Functional, catalytic and kinetic properties: a view. J. Mol. Catal. B: Enzym. 59, 9–21 (2009). \n50. Prakash, O. & Upadhyay, L. S. B. Immobilization imparts stability to watermelon urease to work in water miscible organic media. Biotechnol. Bioprocess Eng. 11, 140–145 (2006). \n51. Daiguebonne, C. et al. Structural and luminescent properties of micro- and nanosized particles of lanthanide terephthalate coordination polymers. Inorg. Chem. 47, 3700–3708 (2008). \n52. Fish, W. W., Reynolds, J. A. & Tanford, C. Gel chromatography of proteins in denaturing solvents comparison between sodium dodecyl sulfate and guanidine hydrochloride as denaturants. J. Biol. Chem. 245, 5166–5168 (1970). \n53. Gudiksen, K. L., Gitlin, I. & Whitesides, G. M. Differentiation of proteins based on characteristic patterns of association and denaturation in solutions of SDS. Proc. Natl Acad. Sci. USA 103, 7968–7972 (2006). \n54. Chance, B. & Maehly, A. C. in Methods In Enzymology Vol. 2, 764–775 (Academic Press, 1955). \n55. Okuda, J. & Sode, K. PQQ glucose dehydrogenase with novel electron transfer ability. Biochem. Biophys. Res. Commun. 314, 793–797 (2004). \n56. Sode, K. et al. Over expression of PQQ glucose dehydrogenase in Escherichia coli under holo enzyme forming condition. Biotechnol. Lett. 16, 1265–1268 (1994). \n57. Sˇtefanac, Z., Tomasˇkovic´, M. & Rakovic´-tresic´, Z. Spectrophotometric method of assaying urease activity. Anal. Lett. 2, 197–210 (1969). \n58. Beaucage, G. Small-angle scattering from polymeric mass fractals of arbitrary mass-fractal dimension. J. Appl. Crystallogr. 29, 134–146 (1996). \n59. Wilkins, D. K. et al. Hydrodynamic radii of native and denatured proteins measured by pulse field gradient NMR techniques. Biochemistry 38, 16424–16431 (1999). \n60. Mylonas, E. & Svergun, D. I. Accuracy of molecular mass determination of proteins in solution by small-angle X-ray scattering. J. Appl. Crystallogr. 40, 95–106 (2007). \n\n# Acknowledgements \n\nK.L., R.R., M.J.S. acknowledge the CSIRO OCE Postdoctoral Fellowship and OCE Science Leader schemes. K.L., R.R., C.M.D., M.J.S., A.J.H. and P.F. acknowledge IP TCP and AMTCP funding. P.F. and C.M.D. are supported by the Australian Research Council (DE120102451 and DE140101359). C.J.D. gratefully acknowledges the Australian Research Council for funding Future Fellowships FT100100400. D.H. is supported by OCE Science Leader Award provided by the Office of the Chief Executive, CSIRO. Part of this research was conducted at the SAXS/WAXS and PXRD beamlines at the Australian \n\nSynchrotron. S. Firth is acknowledged for assistance with the CLSM measurements. \nWe thank Professor M. Hu and Dr J. Cui for valuable discussions. \n\n# Author contributions \n\nK.L. and P.F. developed the idea. K.L., P.F. and C.J.D. performed material synthesis, characterization and co-wrote the manuscript. R.R., C.M.D. and M.J.S. helped with the material synthesis and characterization including ultraviolet–visible, BET and PXRD, respectively. S.B. helped in performing biocatalysis experiments and conceptual design. N.K. and S.M. helped in synchrotron experiment set-up, measurement and characterization. D.H. and A.J.H. contributed to the conceptual design. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Liang, K. et al. Biomimetic mineralization of metal-organic frameworks as protective coatings for biomacromolecules. Nat. Commun. 6:7240 doi: 10.1038/ncomms8240 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms8081", + "DOI": "10.1038/ncomms8081", + "DOI Link": "http://dx.doi.org/10.1038/ncomms8081", + "Relative Dir Path": "mds/10.1038_ncomms8081", + "Article Title": "Perovskite-fullerene hybrid materials suppress hysteresis in planar diodese", + "Authors": "Xu, J; Buin, A; Ip, AH; Li, W; Voznyy, O; Comin, R; Yuan, MJ; Jeon, S; Ning, ZJ; McDowell, JJ; Kanjanaboos, P; Sun, JP; Lan, XZ; Quan, LN; Kim, DH; Hill, IG; Maksymovych, P; Sargent, EH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Solution-processed planar perovskite devices are highly desirable in a wide variety of optoelectronic applications; however, they are prone to hysteresis and current instabilities. Here we report the first perovskite-PCBM hybrid solid with significantly reduced hysteresis and recombination loss achieved in a single step. This new material displays an efficient electrically coupled microstructure: PCBM is homogeneously distributed throughout the film at perovskite grain boundaries. The PCBM passivates the key PbI3- antisite defects during the perovskite self-assembly, as revealed by theory and experiment. Photoluminescence transient spectroscopy proves that the PCBM phase promotes electron extraction. We showcase this mixed material in planar solar cells that feature low hysteresis and enhanced photovoltage. Using conductive AFM studies, we reveal the memristive properties of perovskite films. We close by positing that PCBM, by tying up both halide-rich antisites and unincorporated halides, reduces electric field-induced anion migration that may give rise to hysteresis and unstable diode behaviour.", + "Times Cited, WoS Core": 1015, + "Times Cited, All Databases": 1090, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000355531400007", + "Markdown": "# Perovskite–fullerene hybrid materials suppress hysteresis in planar diodes \n\nJixian $\\mathsf{X}\\mathsf{u}^{1}$ , Andrei Buin1, Alexander H. Ip1, Wei Li1, Oleksandr Voznyy1, Riccardo Comin1, Mingjian Yuan1, Seokmin Jeon2, Zhijun Ning1, Jeffrey J. McDowell1, Pongsakorn Kanjanaboos1, Jon-Paul Sun3, Xinzheng Lan1, Li Na Quan4, Dong Ha $\\mathsf{K i m}^{4}.$ , Ian G. Hill3, Peter Maksymovych2 & Edward H. Sargent1 \n\nSolution-processed planar perovskite devices are highly desirable in a wide variety of optoelectronic applications; however, they are prone to hysteresis and current instabilities. Here we report the first perovskite–PCBM hybrid solid with significantly reduced hysteresis and recombination loss achieved in a single step. This new material displays an efficient electrically coupled microstructure: PCBM is homogeneously distributed throughout the film at perovskite grain boundaries. The PCBM passivates the key $\\mathsf{P b l}_{3}^{-}$ antisite defects during the perovskite self-assembly, as revealed by theory and experiment. Photoluminescence transient spectroscopy proves that the PCBM phase promotes electron extraction. We showcase this mixed material in planar solar cells that feature low hysteresis and enhanced photovoltage. Using conductive AFM studies, we reveal the memristive properties of perovskite films. We close by positing that PCBM, by tying up both halide-rich antisites and unincorporated halides, reduces electric field-induced anion migration that may give rise to hysteresis and unstable diode behaviour. \n\nclass ocemsestehd metmaol nhiualimde lpeeardovskhiatleisd, espeecriaolvlsy ithees $\\\\\\\\\\\\\\\\\\\\\\rightarrow\\mathrm{(MAPbX_{3}}.$ the halide), are attractive as solar energy harvesters due to efficient ambipolar transport and strong light absorption. Progress in perovskite photovoltaics has benefited from the use of mesoporous scaffolds1–4 that lessen the need for long minority carrier drift and diffusion by including the active light absorber within nanometre-sized electron-harvesting pores. Effort to improve device performance with such architectures has led to 1,000-h long-term stability 5 and, in separate studies, certified solar power efficiency exceeding $18\\%$ (refs 6,7). \n\nPlanar-electrode (as distinct from mesoporous) devices also hold important application such as in photodetector arrays (which demand stringent spatial uniformity pixel to pixel), lasers (which require planarity for low-scatter waveguiding) and flexible photovoltaics (which strive to avoid high-temperature mesoporous oxide processing)8–13. The performance of planar perovskite rectifying junction devices has, to date, suffered from two potentially interrelated concerns: severe hysteresis14–16, specifically scan-direction- and scan-speed-dependence of photo ${\\bar{J-V}}$ characteristics17–19; and, relatedly, recombination, likely associated with defective grain boundaries induced by excess halides20–24. The dependence of hysteresis on device architectures has also been observed, where inverted structures have typically shown less serious hysteresis than regular planar devices, but a lower open-circuit voltage25,26. There has been, to date, no consensus as to the origins of these findings. \n\nHeterojunction contact engineering has been proposed to address this issue, such as the modification of the $\\mathrm{TiO}_{2}$ contact layer using a $\\mathrm{C}_{60}$ self-assembled monolayer27. Recent efforts have also sought to reduce hysteresis using interfacial treatment following the formation of perovskite films. However, these solid-state post-treatments typically feature long annealing steps at elevated temperature and therefore introduce undesirable complexity26,28. Furthermore, addition of passivants to the interface fails to address the defects found throughout the bulk21,29. \n\nBearing these considerations in mind, we pursue a solutionphase in situ passivation strategy with the goal of enabling simple low-temperature processing and efficient passivation throughout the grain boundaries in the bulk of the perovskite active layer. \n\n# Results \n\nImprovement of hysteresis and photovoltaic performance. In the course of device studies of mixed materials made from solutions containing both perovskites and the electron-acceptor PCBM (phenyl- $\\mathrm{C}_{61}$ -butyric acid methyl ester), we observe an enhancement in photovoltaic performance (Fig. 1a–c) and a reduction in hysteresis (Fig. $\\mathrm{1d,e}$ ) relative to control devices based on perovskites alone, and also compared with separate-layer PCBM–perovskite devices (Table 1, see Supplementary Figs 1 and 2 for different device structures). To create the mixed-material films, we disperse PCBM and lead acetate $({\\mathrm{Pb}}({\\mathrm{Ac}})_{2}$ ; ref. 20) in various ratios and form films using a one-step process3,9,30,31 employing methylammonium iodide (MAI) as the organohalide precursor (see Methods). As well as observing reduced hysteresis (Fig. 1d,e), we observe in the perovskite–PCBM mixed-material device a substantial voltage enhancement ( $\\mathrm{\\Phi.\\sim0.1V}$ ; Fig. 1a) and a higher fill factor compared with the PCBM-free and bilayer PCBM–perovskite controls (Table 1). \n\n![](images/dd927f970fc1175b39580d3c5b875674ec01cfc4504a3ef7bb11f1ce95d98ff8.jpg) \nFigure 1 | Steady-state photovoltaic performance of an ultrathin perovskite–PCBM hybrid film. (a) The steady-state open-circuit voltage, $V_{\\mathrm{OC}},$ (b) steady-state short circuit current density, $J_{\\mathsf{S C}}$ and $\\mathbf{\\eta}(\\bullet)$ the steady-state power conversion efficiency, PCE, of perovskite–PCBM hybrid film (red) compared with the control perovskite-only film (blue). During steady-state measurement, the integrating time for each point is $0.35s$ (d) The instantaneous $J-V$ curve of the control device (perovskite film) with high hysteresis. The thicker curve indicates forward scan starting from open-circuit condition; thin curve is the reverse scan from short circuit condition. The scanning rate is $0.2\\mathsf{V}\\mathsf{s}^{-1}$ . The fill factor (FF) of forward scan is $66\\%$ while reverse FF is reduced to $42\\%$ . The black point indicates the ‘maximum-power output point (MPP)’ is measured from the steady-state PCE as shown in (c). The MPP here is located between two instantaneous $J-V$ curves due to the significant hysteresis and current decay. (e) The $J-V$ scan of a hybrid device shows very low hysteresis and low current loss, as shown in (b). The FF for forward (reverse) scan is $74\\%$ $(70\\%)$ . The steady-state MPP is consistent with the forward $J-V$ curve, which demonstrates the stability of the hybrid film. The inset of figure (e) shows the external quantum efficiency (EQE) of a hybrid device. The current density predicted from EQE is $15.4\\mathsf{m A c m}^{-2}$ , consistent with the steady-state current density measured in (b); The inset figure of (d) shows the thickness of active layer in both devices is around $150\\mathsf{n m}$ . \n\nTable 1 | Statistics of steady-state performance with different PCBM distribution and thickness. \n\n\n
Device configurationSteady-state performanceInstantaneous
TypeThickness (nm)Voc (V)Jsc (mA cm -2)PCE (%)FF(%)forward/reverse
Control150 ±200.97± 0.0213.1± 0.86.7±0.562/38±3
Bilayer1.08 ± 0.0214.2 ± 0.410.6± 0.471/64±3
Hybrid1.09 ± 0.0214.4±0.410.9 ±0.472/65±2
Hybrid champion1.1114.611.973/68
Control300±200.98±0.0214.4±0.88.1±0.565/40±3
Bilayer1.06 ± 0.0216.1± 0.412.0 ± 0.572/56±3
Hybrid1.07± 0.0217.3± 0.413.6 ± 0.673/66±3
Hybrid champion1.08618.014.475/69
\n\nMechanistic study of perovkite–PCBM interaction. We proceed to seek mechanistic insights regarding the role, or roles, of the PCBM. Specifically, we asked whether the PCBM could interact with certain chemical species in the mixed-material solution and whether studies of incorporation into films using the new process indicated a homogeneous distribution of PCBM throughout the active layer, compared with segregation into a bilayer device with PCBM either substantially below or above the perovskite. \n\nSolution-phase spectroscopy provides one means to study the formation of complexes of PCBM with the various perovskite solution-phase precursors. When PCBM is mixed into our normal perovskite precursor solution, the bright yellow solution (Fig. 2a, left) turns dark brown (Fig. 2a, right). The absorption spectrum of perovskite–PCBM hybrid solution shows a peak at $1,020\\mathrm{nm}$ (Fig. 2b)32–34. This is in contrast with pure PCBM in the same solvent, which is observed to be transparent in this wavelength region. The $1{,}020\\mathrm{nm}$ spectral feature is associated in literature reports with the formation of a PCBM–halide radical (Fig. 2b, inset)32–34. \n\nThis reconfirmation of the strong PCBM–iodide interaction motivates us to explore, using density functional theory (DFT, see Supplementary Note 1 for details), what might occur in a solid material. We look in particular at reactions PCBM might participate in at the excess-halide-associated defects at grain boundaries previously reported to be a dominant source of electronic traps in lead MAI perovskites20–23. We focus specifically on the Pb-I antisite defect, in which iodine occupies the $\\mathrm{\\sfPb}$ site and forms a trimer with neighbouring iodine atoms (Fig. 2c, Supplementary Fig. 7)20. DFT reveals that, with the introduction of PCBM near such Pb-I antisite defects, the wavefunction of the ground state (Fig. 2d) is hybridized between the PCBM and the perovskite surface. We also find that the bonding of PCBM to defective halides is thermodynamically favoured (see binding energy calculations in Supplementary Figs 3–5 and Supplementary Table 1–3) and that this suppresses the formation of deep traps (Fig. 2e, Supplementary Fig. 6). \n\nPerovskite–PCBM mixture phase distribution. Next we seek to determine whether the PCBM is distributed throughout the entire thickness of the active layer that had been formed from the mixed perovskite–PCBM solution (Fig. 3a). Secondary ion mass spectrometry (SIMS) is used to probe the depth profile of PCBM and perovskite. $\\mathrm{Pb}$ and Ti are used as indicators of the perovskite and of the $\\mathrm{TiO}_{2}$ substrate, respectively. Since PCBM does not contain elements to identify it uniquely, we use instead for this portion of the study a thiophene-containing derivative, [60]ThCBM ([6,6]- (2-Thienyl)- $C_{61}$ -butyric acid methyl ester), which permits the use of sulfur as the tracer element35. The [60]ThCBM is present homogeneously throughout the thickness of hybrid film, with a uniform concentration as a function of depth (Fig. 3b, Supplementary Figs 18 and 19, Supplementary Note 2). Using X-ray diffraction (XRD), we find that the perovskite lattice diffraction peaks of the hybrid film are consistent with that of control film without PCBM (Fig. 3c). In addition, the average perovskite grain size in hybrid films, estimated from the XRD peak width, is comparable to that of control film (Supplementary Table 4, Supplementary Methods). \n\nAlso with the nature of the mixed material in mind, we employ Kelvin probe studies to examine the work function of mixedmaterial films. The work function of the mixed-material films lies between that of the pure perovskite and pure PCBM. Its value varies monotonically along this continuum as a function of PCBM fraction incorporated (Supplementary Fig. 10). When very high PCBM fractions are employed, evidence of phase separation and impact on film morphology emerge: the PCBM phase aggregates at perovskite grain boundaries and becomes clearly evident (Supplementary Figs 11 and 12). \n\nThese findings prompt us to posit the following picture of the mixed material. Perovskite grains are formed with similar size and crystallinity with and without the PCBM (XRD). The PCBM is distributed uniformly throughout the thickness of the film (SIMS), presumably in between the grains. The PCBM could bind iodide-rich defect sites on these grain boundaries (DFT) and/or simply bind up excess iodide from the solution. From an electronic standpoint, the incorporation of the PCBM throughout the film influences its work function in proportion with PCBM–perovskite ratio (Kelvin probe). \n\nCharge dynamics and hysteresis characterization. To seek further indications regarding the extent of electronic interaction between the PCBM and the perovskite grains in the mixed material, we acquire transient photoluminescence for pure perovskites, PCBM–perovskite bilayers and mixed materials, investigating each for the case of excitation from each side. The mixed-material film shows identical transient PL (photoluminescence) traces for top versus bottom illumination (Fig. 3d). In contrast, perovskite films with PCBM on one side exhibit different PL lifetimes when pumped from the different sides (Supplementary Fig. 14). The invariance of the PL lifetime with top-/bottom-side photoexcitation for the mixed-material system agrees with SIMS and further indicates that the hybrid film behaves as a homogenous optoelectronic material throughout its thickness. \n\n![](images/7d753c6c08de75fa7edeff9dba007a7436e69c3e73a3bb8ca492c38d3c904d38.jpg) \nFigure 2 | Perovskite–PCBM hybrid process and in situ passivation mechanism. (a) Pristine perovskite solution (left) comprised of ${\\mathsf{P b}}({\\mathsf{A c}})_{2}$ and MAI in dimethylformamide solvent is bright yellow; the formulated perovskite–PCBM hybrid solution (right) is brown; Simple one-step spin-coating is used to convert the hybrid solution into an hybrid solid film, and the perovskite is in situ passivated by PCBM during self-assembly; (b) Ultraviolet–visible absorption spectroscopy of the hybrid solution shows the interaction between PCBM and perovksite ions. PCBM radical anion’s absorption peak at $1,020\\mathsf{n m}$ is identified in hybrid solution (red); while PCBM in same solvent (black) has no absorption peak in this wavelength region; Inset of $(\\pmb{6})$ shows details of such interaction: In hybrid solution, electron transfer is induced between the perovskite anions $(|^{-}\\rangle$ and PCBM and will result in PCBM radical anion and PCBM– halide radical. (c) A schematic of in situ passivation of halide-induced deep trap: PCBM adsorbs on $P b-1$ antistite defective grain boundary during perovskite self-assembly. (d) The wavefunction overlap shows the hybridization between PCBM and defective surface, enabling the electron/hole transfer for absorbance and passivation. (e) DFT calculation of density of states (DOS) shows that deep trap state (black) induced by $P b-1$ antistite defect is reduced and becomes much shallower (red) upon the adsorption of PCBM on defective halide. Ec, the minimum of conduction band; Ev, maximum of valence band. \n\nA series of conductive atomic force microscopy (cAFM) studies provides added spatial resolution of the electronic properties of the films under study. We carry out the cAFM studies under high vacuum and dark conditions to rule out the effect of light and moisture. By overlapping the grain topography and the electrical current map of the films (Fig. 4a,e), we find that conductivity is greatest at grain boundaries, both in the pure-perovskite and in the mixed-material films. However, the mixed-material films have much higher conductivity near grain boundaries at positive bias voltages, consistent with the electron-transport medium PCBM accumulating near grain boundaries and providing continuous pathways for electron egress. We also obtain $I{-}V$ traces at various spatial positions and find that control perovskite films exhibit major hysteresis behaviour when scanned in the reverse bias direction (Fig. 4b–d). Given the pure perovskites’ slow response on the seconds timescale, the hysteretic $I{-}V$ curves are consistent with the proposed hysteresis mechanism of ionic transport in perovskite solids36–39. To our knowledge, this is the first direct experimental observation of memristive properties within the perovskite material itself via $\\boldsymbol{c}\\boldsymbol{\\mathrm{AFM}}^{39}$ . This observation is generally in agreement with the very recently reported ionic motion processes in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite materials25,40. In contrast, in perovskite–PCBM mixed film, the hysteresis effect is greatly suppressed under all conditions (Fig. 4f–h, Supplementary Fig. 17). These observations further substantiate a picture in which PCBM influences electronic properties when it associates with the perovskite grains at their grain boundaries. \n\nAdditional device studies offer further information about the role of PCBM in perovskite device performance and hysteresis. Planar devices incorporating PCBM—whether at an interface or throughout in bulk—are consistently superior in performance to control devices without PCBM (Table 1, Supplementary Figs 13 and 15). Incorporating the PCBM into the film becomes even more advantageous to collect current for thicker active layers, suggesting that the PCBM accepts photocharges and assists in their extraction to the $\\mathrm{TiO}_{2}$ . The champion planar devices were obtained using the perovskite–PCBM mixed material and exhibited steady-state power conversion efficiency (PCE) exceeding $14.4\\%$ (Supplementary Fig. 13), 1.5 times more efficient than our PCBM-free perovskite controls. \n\nWe also investigate the reverse saturation current density in the various devices and found that the hybrid films consistently reduced the dark current by two orders of magnitude. Rectifying behaviour is also maintained much longer in the mixed material compared with perovskite controls (Supplementary Fig. 16). \n\nThese last observations motivate further evaluation of role of PCBM in trap passivation at perovskite grain boundaries. We use transient photovoltage to quantify the prevalence of mid-gap trap states in each class of materials and devices (details see Methods). We obtain a notably longer carrier lifetime over a wide range of photovoltages in the mixed material (Fig. 5a). This indicates reduced non-geminate recombination for the perovskite–PCBM hybrid films. We also compare the transient photoluminescence of hybrid films to investigate the impact of PCBM on carrier extraction. When we increase the PCBM–perovskite hybrid ratio progressively, the PL exhibits consistently greater quenching, indicating efficient electronic coupling between the well-dispersed PCBM phase and the perovskite (Fig. 5b, orange, pink and red curve). When PCBM ratio is extremely high (Fig. 5b, black curve), the photoluminescence quenching efficiency began to degrade greatly. Significant phase segregation occurs, with the appearance of large PCBM domains that lack effective interconnectivity for carrier extraction (Supplementary Figs 11 and 12). We conclude that comprehensive incorporation of PCBM in the interstitial volumes among grains in the perovskite system is required (that is, sufficient PCBM material miscibility in the perovskite solid is needed) to produce continuous pathways for carrier extraction to enhance performance41. \n\n![](images/a2f915e64053ae233773b4e540cf9cd1a4a83a674987a10bac2990c49d26283c.jpg) \nFigure 3 | Three-dimensional phase separation and homogeneous PCBM distribution in hybrid solid. (a) Scheme of planar perovskite solar cell using perovskite–PCBM hybrid solid as the active absorber; PCBM phase is homogeneously distributed at grain boundaries throughout the perovskite layer. (b) SIMS depth profile of perovskite–PCBM hybrid film on $\\mathsf{T i O}_{2}$ substrate showing homogeneous distribution of PCBM throughout the film. The sputter etching begins at the air/film interface. PCBM is tracked by S element using analogous [60]ThPCBM; perovskite is tracked by Pb element; $\\mathsf{T i O}_{2}$ is tracked by Ti atom. (c) XRD pattern of pristine hybrid solid film (red) and the control perovskite film without PCBM (black). $\\mathsf{T i O}_{2}$ compact layer on FTO is used as substrate. XRD shows that in hybrid solid, the perovskite crystal lattice is same as control film, and thus PCBM only exists at the grain boundaries and interfaces throughout the film. (d) The transient photoluminescence of the hybrid film. Pumping from top of film (black) and pumping from bottom of film (red) give identical signals, showing PCBM homogeneous distribution. The hybrid film is displays dense grains and full-coverage as observed via SEM (inset left); The surface is ultra-flat with roughness $\\sim6\\mathsf{n m}$ as characterized by AFM (inset right). \n\n![](images/89344216326ffe87e493324953d61b14a35a34305a7ed93b5ffecdbe8b93bfce.jpg) \nFigure 4 | cAFM study of hysteresis-ion relationship for control films $(a,b,c,d)$ and hybrid films $\\mathbf{(e,f,g,h)}$ . (a,e) The grey-scaled contact-mode AFM (background) with overlaid colour-scaled conductive AFM images (positive bias voltage: 1 V). (b–d) $1-V$ hysteresis of control film increases when increase the negative bias and injected current (solid line, forward sweep; dashed line, reverse sweep). (f–h) $1-V$ hysteresis of hybrid film is suppressed when increasing the negative bias and injected current. Scanning rate is $\\sim0.5\\mathsf{V}\\mathsf{s}^{-1}$ (see Methods). \n\n![](images/e5f3c70723f21cccd86da1cef2a5f5b62f307f7b8094d45b8e72ac40338931c6.jpg) \nFigure 5 | Effect of PCBM on charge carrier dynamics. (a) Charge carrier lifetime of hybrid device (red) and control device (blue), determined from transient photovoltage measurement under open-circuit condition. (b) Transient photoluminescence of hybrid films with increasing PCBM ratio progressively (orange, pink, red and black) compared with control film on glass (blue), showing the enhanced electron extraction. The quenching efficiency increases monotonically with increasing hybrid ratio, indicating the increasing PCBM–perovskite interfaces. When keep increasing PCBM hybrid ratio (black), the quenching efficiency begins to reduce abnormally, due to the emergence of large domains of agglomerated PCBM (Supplementary Figs 11 and 12), reducing the effective interconnectivity between perovskite and PCBM. \n\n# Discussion \n\nWe close with a discussion of mechanisms likely at work, and one more speculative mechanism, in the mixed-material films. Our data suggest that PCBM, when incorporated at or near perovskite grain boundaries, makes a significant impact on electronic properties. The transient photovoltage, combined with the DFT analysis and the spectroscopy showing PCBM radical formation, suggest that PCBM plays a passivating role at iodide-rich trap sites on the surfaces of these grains. At the same time, the long timescale of hysteresis in pure-perovskite films and its substantial suppression in the mixed material, combined with the vastly lower reverse dark current in the mixed material, suggest to us an additional effect at work in addition to the passivating role. We propose that ions, such as the iodide anion, can potentially migrate under an applied electric field, producing an ionic current. This can explain the slow response of hysteresis36,39 and the instability of the dark current when pure-perovskite and bilayer devices are employed. By tying up iodide-rich surface sites, or simply unincorporated iodide anions, PCBM can reduce anion migration through defects at grain boundaries36,37. This rearrangement under external, and also built-in internal, electric fields, could account for solar cell hysteresis. For example, when the device is poised at the $J_{\\mathrm{SC}}$ condition, the large built-in field may induce anionic charge motion that works against this field, leading to a drop in photocurrent in time. A relatively rapid scan towards $V_{\\mathrm{OC}}$ will therefore suffer from low photocurrents; whereas, following an extended pause at $V_{\\mathrm{OC}},$ during which anions can diffuse back to equilibrium positions, a rapid scan to $J_{\\mathrm{SC}}$ will feature a high current in view of the lack of charge compensating the built-in field. \n\n# Methods \n\nPerovskite–PCBM hybrid solution preparation. Lead(II) acetate trihydrate (Sigma-Aldrich, $99.99\\%$ is dehydrated before use. Then, the dehydrated lead acetate $({\\mathrm{Pb}}({\\mathrm{Ac}})_{2})$ and MAI (Dyesol, $99\\%+\\cdot$ are dissolved in dimethylformamide (N,N-dimethylformamide, Sigma-Aldrich, $99.9\\%$ ) with the molar ratio 1:3 to form the perovskite precursor solution. To obtain ultrathin films and thick films, we tune the perovskite concentration between 0.2 and $1\\mathrm{mM}$ For hybrid solid, PCBM (Nano-C, $99.5\\%$ ) is mixed into the perovskite solution. In typical procedure, the PCBM-perovskite weight ratios are between 1:100 and 1:10. Specifically, PCBM can be dissolved into chlorobenzene first, and then mixed with perovskite solution before spin-coating. The solution is kept at $70^{\\circ}\\mathrm{C}$ before spinning. For low mixture ratio, the miscibility of mixture solution is good and can be stabilized at room temperature; for high-ratio mixtures approaching 1:10 and beyond, the solution needs to be used quickly after mixing. \n\nPlanar solar cell fabrication. A thin $\\mathrm{TiO}_{2}$ compact layer is first formed on fluorine doped tin oxide (FTO) substrate using magnetron sputtering ( $\\sim50\\mathrm{nm}$ , Kurt J. Lesker, $99.9\\%$ ) followed by a low-concentration $\\mathrm{TiCl_{4}}$ treatment for interfacial contact improvement4,42: soak in $120\\mathrm{mMTiCl_{4}}$ aqueous solution at $70^{\\circ}\\mathrm{C}$ for $0.5\\mathrm{h}$ followed by annealing at $500^{\\circ}\\mathrm{C}$ for $0.5\\mathrm{h}$ . The $\\mathrm{TiCl_{4}}$ treatment modifies the roughness without changing the planar structure of $\\mathrm{TiO}_{2}$ compact layer and final device (Supplementary Fig. 2). Perovskite–PCBM hybrid solid films are deposited on pre-heated $\\mathrm{TiO}_{2}$ substrate using spin-coating at $^{3,000-5,000\\mathrm{r.p.m}}$ for 60 s in a nitrogen glovebox. During the spin-coating, the film turns to dark brown, implying that the perovskite crystallization is almost done. The hybrid solid film is then heated for $10\\mathrm{min}$ at $70^{\\circ}\\mathrm{C}$ to remove the residual solvent. For a control planar heterojunction device, pure-perovskite solution is deposited on $\\mathrm{TiO}_{2}$ substrate in the same way. No excess acetate $(\\mathrm{Ac}^{-})$ and methylammonium $(\\mathrm{MA}^{-})$ are found in the final films (Supplementary Figs 8 and 9, Supplementary Methods). For bilayer control devices, PCBM in chlorobenzene $(\\sim20\\mathrm{mg}\\mathrm{ml}^{-1}$ ) is spin cast on a $\\mathrm{TiCl}_{4}$ -treated $\\mathrm{TiO}_{2}$ substrate and then annealed at $70^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ before spincoating the perovskite on top. A thin PCBM layer $\\cdot<30\\mathrm{nm}\\cdot$ between $\\mathrm{TiO}_{2}$ and perovskite is formed (Supplementary Fig. 20). Hole transfer layer is deposited by spin-coating of Spiro-OMeTAD (Borun Chemical, $99\\%+$ ) solution following the doping procedure reported in literature1. Top contact is $50\\mathrm{nm}$ thermally evaporated gold through the shadow mask under $10^{-7}$ torr vacuum using an Angstrom Engineering deposition system. \n\nSteady-state power conversion efficiency characterization. Steady-state opencircuit voltage, $V_{\\mathrm{OC}}(t)$ , is first measured by Keithley 2400 by fixing the current to zero and sampling the voltage at multiple time points. Steady-state short-circuit current, $J_{\\mathrm{{SC}}}(t)$ , is measured by Keithley while setting the bias voltage to zero and sampling the current at multiple time points. Instantaneous $J{-}V$ curves are then measured with a scanning rate of $0.2\\dot{\\mathrm{~V~}}s^{-1}$ , and the voltage of maximum power point $\\ensuremath{\\left(V_{\\mathrm{MPP}}\\right)}$ is determined from the instantaneous $J{-}V$ curve. Steady-state PCE, PCE(t), is measured by setting the bias voltage to the estimated $V_{\\mathrm{MPP}}$ . Under the bias of $V_{\\mathrm{MPP}}.$ , current density value are sampled during a long time period to get $J_{\\mathrm{MPP}}(t)$ . The $\\mathrm{PCE}(t)$ is obtained by the multiplication of $\\dot{V_{\\mathrm{MPP}}}$ and $J_{\\mathrm{MPP}}(t)$ . The active area is determined by the aperture before the solar cell to avoid overestimating the photocurrent. Through this aperture (area $0.049\\mathrm{cm}^{2}$ ), the illumination intensity was calibrated using a Melles–Griot broadband power meter and set to be 1 sun $(100\\mathrm{mW}\\mathrm{cm}^{-2},$ ). The AM1.5 solar power is supplied by a class A $(<25\\%$ spectral mismatch) solar simulator (ScienceTech). The spectral mismatch of the system was characterized using a calibrated reference solar cell (Newport). The total accuracy of the AM1.5 power conversion efficiency measurements was estimated to be $\\pm5\\%$ . \n\nConductive atomic force microscope characterization. Scanning probe microscopy experiments are carried out in a commercial ultrahigh-vacuum atomic force microscope (UHV bean-deflection AFM, Omicron) using $\\mathrm{Cr/Pt}$ -coated silicon cantilevers (Budget Sensor, Multi75E-G). All the measurements are performed at a background pressure of $<2\\times10^{-10}$ Torr after transferring the samples from ambient without any additional treatment. Contact-mode AFM images and two-dimensional current maps are simultaneously obtained with the tip in contact with the surface (loading force $\\mathrm{\\sim}1\\mathrm{nN}$ applying fixed bias voltages. The $I{-}V$ curves are acquired in the conductive AFM regime from various locations of the sample surfaces applying a linear bias ramp with a rate of $\\sim0.5\\mathrm{V}\\mathrm{s}^{-1}$ . \n\nOther characterizations. External quantum efficiency spectrum and transient photovoltage measurements are carried out following previously published processes42. Transient photoluminescence is carried out using time-correlated single photon counting (TCSPC) function of a HORIBA Fluorolog-3 spectrofluorometer, and following the method shown in literature to protect samples43. Samples are tested in $\\Nu_{2}$ ambient. \n\n# References \n\n1. Burschka, J. et al. Sequential deposition as a route to high-performance perovskite-sensitized solar cells. Nature 499, 316–319 (2013). \n2. Im, J.-H., Jang, I.-H., Pellet, N., Gra¨tzel, M. & Park, N.-G. Growth of CH3NH3PbI3 cuboids with controlled size for high-efficiency perovskite solar cells. Nat. Nano. 9, 927–932 (2014). \n3. Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n4. Heo, J. H. et al. Efficient inorganic-organic hybrid heterojunction solar cells containing perovskite compound and polymeric hole conductors. Nat. Photonics 7, 486–491 (2013). \n5. Mei, A. et al. A hole-conductor–free, fully printable mesoscopic perovskite solar cell with high stability. Science 345, 295–298 (2014). \n6. Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n7. Jeon, N. J. et al. Compositional engineering of perovskite materials for highperformance solar cells. Nature 517, 476–480 (2015). \n8. Deschler, F. et al. High photoluminescence efficiency and optically pumped lasing in solution-processed mixed halide perovskite semiconductors. J. Phys. Chem. Lett. 5, 1421–1426 (2014). \n9. Ball, J. M., Lee, M. M., Hey, A. & Snaith, H. J. Low-temperature processed meso-superstructured to thin-film perovskite solar cells. Energy Environ. Sci. 6, 1739–1743 (2013). \n10. Tan, Z.-K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nano. 9, 687–692 (2014). \n11. Liu, D. & Kelly, T. L. Perovskite solar cells with a planar heterojunction structure prepared using room-temperature solution processing techniques. Nat. Photonics 8, 133–138 (2014). \n12. Docampo, P., Ball, J. M., Darwich, M., Eperon, G. E. & Snaith, H. J. Efficient organometal trihalide perovskite planar-heterojunction solar cells on flexible polymer substrates. Nat. Commun. 4 (2013). \n13. Malinkiewicz, O. et al. Perovskite solar cells employing organic chargetransport layers. Nat. Photonics 8, 128–132 (2014). \n14. McGehee, M. D. Perovskite solar cells: continuing to soar. Nat. Mater. 13, 845–846 (2014). \n15. Gr¨atzel, M. The light and shade of perovskite solar cells. Nat. Mater. 13, 838–842 (2014). \n16. Green, M. A., Ho-Baillie, A. & Snaith, H. J. The emergence of perovskite solar cells. Nat. Photonics 8, 506–514 (2014). \n17. Snaith, H. J. et al. Anomalous hysteresis in perovskite solar cells. J. Phys. Chem. Lett. 5, 1511–1515 (2014). \n18. Kim, H.-S. & Park, N.-G. Parameters affecting I–V hysteresis of CH3NH3PbI3 perovskite solar cells: effects of perovskite crystal size and mesoporous TiO2 layer. J. Phys. Chem. Lett. 5, 2927–2934 (2014). \n19. Unger, E. L. et al. Hysteresis and transient behavior in current–voltage measurements of hybrid-perovskite absorber solar cells. Energy Environ. Sci. 7, 3690–3698 (2014). \n20. Buin, A. et al. Materials processing routes to trap-free halide perovskites. Nano Lett. 14, 6281–6286 (2014). \n21. Abate, A. et al. Supramolecular halogen bond passivation of organic–inorganic halide perovskite solar cells. Nano Lett. 14, 3247–3254 (2014). \n22. Agiorgousis, M. L., Sun, Y.-Y., Zeng, H. & Zhang, S. Strong covalency-induced recombination centers in perovskite solar cell material $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ . J. Am. Chem. Soc. 136, 14570–14575 (2014). \n23. Du, M. H. Efficient carrier transport in halide perovskites: theoretical perspectives. J. Mater. Chem. A 2, 9091–9098 (2014). \n24. Suarez, B. et al. Recombination study of combined halides (Cl, Br, I) perovskite solar cells. J. Phys. Chem. Lett. 5, 1628–1635 (2014). \n25. Tress, W. et al. Understanding the rate-dependent J-V hysteresis, slow time component, and aging in CH3NH3PbI3 perovskite solar cells: the role of a compensated electric field. Energy Environ. Sci. 8, 995–1004 (2015). \n26. Shao, Y., Xiao, Z., Bi, C., Yuan, Y. & Huang, J. Origin and elimination of photocurrent hysteresis by fullerene passivation in CH3NH3PbI3 planar heterojunction solar cells. Nat. Commun. 5, 5784 (2014). \n27. Wojciechowski, K. et al. Heterojunction modification for highly efficient organic-inorganic perovskite solar cells. ACS Nano 8, 12701–12709 (2014). \n28. Chen, Q. et al. Controllable self-induced passivation of hybrid lead iodide perovskites toward high performance solar cells. Nano Lett. 14, 4158–4163 (2014). \n29. Noel, N. K. et al. Enhanced photoluminescence and solar cell performance via lewis base passivation of organic–inorganic lead halide perovskites. ACS Nano 8, 9815–9821 (2014). \n30. Xiao, M. et al. A fast deposition-crystallization procedure for highly efficient lead iodide perovskite thin-film solar cells. Angew. Chem. Int. Ed. 53, 9898–9903 (2014). \n31. Zhou, H. et al. Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). \n32. Guldi, D. M. & Prato, M. Excited-state properties of C60 fullerene derivatives. Acc. Chem. Res. 33, 695–703 (2000). \n33. Li, C.-Z. et al. Doping of fullerenes via anion-induced electron transfer and its implication for surfactant facilitated high performance polymer solar cells. Adv. Mater. 25, 4425–4430 (2013). \n34. Weber, C. D., Bradley, C. & Lonergan, M. C. Solution phase n-doping of C60 and PCBM using tetrabutylammonium fluoride. J. Mater. Chem. A 2, 303–307 (2013). \n35. Popescu, L. M., van ’t Hof, P., Sieval, A. B., Jonkman, H. T. & Hummelen, J. C. Thienyl analog of 1-(3-methoxycarbonyl)propyl-1-phenyl-[6,6]- methanofullerene for bulk heterojunction photovoltaic devices in combination with polythiophenes. Appl. Phys. Lett. 89, 213507 (2006). \n36. Kumar, P. P. & Yashonath, S. Ionic conduction in the solid state. J. Chem. Sci. 118, 135–154 (2006). \n37. Lehovec, K. Space-charge layer and distribution of lattice defects at the surface of ionic crystals. J. Chem. Phys. 21, 1123–1128 (1953). \n38. Chua, L. O. Memristor-The missing circuit element. IEEE Trans. Circuit Theory 18, 507–519 (1971). \n39. Strukov, D. B., Snider, G. S., Stewart, D. R. & Williams, R. S. The missing memristor found. Nature 453, 80–83 (2008). \n40. Xiao, Z. et al. Giant switchable photovoltaic effect in organometal trihalide perovskite devices. Nat. Mater. 14, 193–198 (2015). \n41. Guo, X. et al. Polymer solar cells with enhanced fill factors. Nat. Photonics 7, 825–833 (2013). \n42. Ip, A. H. et al. Hybrid passivated colloidal quantum dot solids. Nat. Nanotechnol. 7, 577–582 (2012). \n43. Stranks, S. D. et al. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n\n# Acknowledgements \n\nThis publication is based in part on work supported by Award KUS-11-009-21, made by King Abdullah University of Science and Technology (KAUST), by the Ontario Research Fund—Research Excellence Program, and by the Natural Sciences and Engineering Research Council (NSERC) of Canada. Computations were performed on the GPC supercomputer at the SciNet HPC Consortium. SciNet is funded by: the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund—Research Excellence; and the University of Toronto. We thank Peter Brodersen from Surface Interface Ontario for SIMS measurements. A portion of this research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. L.N.Q. and D.H.K. acknowledge the financial support by National Research Foundation of Korea Grant funded by the Korean Government (2014R1A2A1A09005656). We thank Pengfei Li from the Department of Chemistry at the University of Toronto for help with time-of-flight mass spectrometry measurements. \n\n# Author contributions \n\nJ.X., A.B. and E.H.S. designed and directed this study, analysed results and co-wrote the manuscript; J.X. and W.L contributed to all experimental work; A.B. carried out the DFT simulations; O.V. and A.H.I. assisted on experiment design, results analysis and manuscript preparation; R.C. carried out electronic property characterization and transient photoluminescence; M.Y., Z.N., X.L., L.Q. and D.H.K. assisted the device fabrication and characterization; S.J. and P.M. carried out cAFM studies; J.P.S. carried out Kelvin probe study; P.K. and J.M. assisted in microscopic studies. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Xu, J. et al. Perovskite–fullerene hybrid materials suppress hysteresis in planar diodes. Nat. Commun. 6:7081 doi: 10.1038/ncomms8081 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms9058", + "DOI": "10.1038/ncomms9058", + "DOI Link": "http://dx.doi.org/10.1038/ncomms9058", + "Relative Dir Path": "mds/10.1038_ncomms9058", + "Article Title": "Accommodating lithium into 3D current collectors with a submicron skeleton towards long-life lithium metal anodes", + "Authors": "Yang, CP; Yin, YX; Zhang, SF; Li, NW; Guo, YG", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Lithium metal is one of the most attractive anode materials for electrochemical energy storage. However, the growth of Li dendrites during electrochemical deposition, which leads to a low Coulombic efficiency and safety concerns, has long hindered the application of rechargeable Li-metal batteries. Here we show that a 3D current collector with a submicron skeleton and high electroactive surface area can significantly improve the electrochemical deposition behaviour of Li. Li anode is accommodated in the 3D structure without uncontrollable Li dendrites. With the growth of Li dendrites being effectively suppressed, the Li anode in the 3D current collector can run for 600 h without short circuit and exhibits low voltage hysteresis. The exceptional electrochemical performance of the Li-metal anode in the 3D current collector highlights the importance of rational design of current collectors and reveals a new avenue for developing Li anodes with a long lifespan.", + "Times Cited, WoS Core": 1180, + "Times Cited, All Databases": 1209, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000360352600005", + "Markdown": "# Accommodating lithium into 3D current collectors with a submicron skeleton towards long-life lithium metal anodes \n\nChun-Peng Yang1,2, Ya-Xia Yin1, Shuai-Feng Zhang1,2, Nian-Wu Li1 & Yu-Guo Guo1,2 \n\nLithium metal is one of the most attractive anode materials for electrochemical energy storage. However, the growth of Li dendrites during electrochemical deposition, which leads to a low Coulombic efficiency and safety concerns, has long hindered the application of rechargeable Li-metal batteries. Here we show that a 3D current collector with a submicron skeleton and high electroactive surface area can significantly improve the electrochemical deposition behaviour of Li. Li anode is accommodated in the 3D structure without uncontrollable Li dendrites. With the growth of Li dendrites being effectively suppressed, the Li anode in the 3D current collector can run for $600\\mathsf{h}$ without short circuit and exhibits low voltage hysteresis. The exceptional electrochemical performance of the Li-metal anode in the 3D current collector highlights the importance of rational design of current collectors and reveals a new avenue for developing Li anodes with a long lifespan. \n\nEltecriterso,chweitmh chail e-neenregryg stdoernasgite saynsdtesmafs,e fonr celxeamnpfle ubraetsgrid, electric vehicles and portable electronics. Advanced electrode materials are the key to high-energy batteries. Lithium metal is an ideal anode material in terms of energy density because it delivers an attractively high specific capacity $(3,860\\mathrm{mAhg^{-1}})$ and has the lowest reduction potential (– $3.04\\mathrm{V}$ versus standard hydrogen electrode)1. However, the use of Li metal as anode faces several hurdles. The most challenging one is the formation of Li dendrites during cycling, which causes safety hazards and exposes the Li-metal batteries to wide safety concerns2. The use of Li-ion batteries, which use rocking Li ions and Li-intercalating materials (such as graphite) instead of Li metal as anode, has successfully circumvented this problem and gained great success3–5. Nevertheless, with the energy density of Li-ion batteries approaching the theoretical value, they will soon no longer meet the demands for advanced energy storage. We are coming to an age beyond Li-ion batteries, in which advanced energy storage systems are necessary6. \n\nIn this context, Li-metal batteries, which used to be considered ‘unsafe’, should be examined further. Advanced Li-metal batteries including Li–air $(\\mathrm{Li}{-}\\mathrm{O}_{2})$ , Li–S and Li–Se batteries have emerged as required because they can provide efficient energy storage7–11. Considerable efforts have been devoted to develop these novel Li-metal batteries. The electrochemical performances of the air, S and Se cathodes have been significantly improved12–20. The issues of Li anode, however, remain unsolved. The persistent challenge is the formation of dendritic Li during Li plating, which would lead to low Coulombic efficiency, short cycle life, internal short circuits and even catastrophic cell failure21,22. Only when the Li anode is improved markedly we can build viable Li-metal batteries for energy storage applications. Recently, attempts have been made to tackle the problems of Li anode23. Studies have been concentrated on the liquid electrolytes with optimal solvents and Li salts for stable interfaces between the Li metal and electrolyte $^{24-26}$ . Various electrolyte additives, such as ${\\mathrm{Cs}}^{+}$ and $\\mathrm{Rb^{+}}$ ions27, LiF (ref. 28), $\\mathrm{Cu(CH_{3}C O O)_{2}}$ (ref. 29), have been explored to restrain dendrite formation and reinforce protection for the Li surface. In addition, it is found effective to suppress the Li dendrites using physical protective layers such as a carbon nanosphere layer30, BN/graphene31, a graphite layer32 and other ex situ coated protective layers33. As for the Li metal itself, several studies have indicated that Li alloys such as Li–Al (ref. 34) and Li–B alloys35,36 can change Li deposition behaviour. Although these studies have contributed to improve Li-metal anodes, the dendrite-forming deposition nature of Li metal has hardly been changed. Thus, new means to suppress dendrite formation will provide additional approaches to improve the performance of Li-metal anode. \n\nAs a key component of the anode, the current collector could also have a significant influence on the Li anode. The current collector affects the nucleation at the initial period of Li plating, which is decisive for the morphology of the subsequently plated Li. However, the role of the current collector for the Li-metal anode has not been investigated thoroughly. Most of the current collectors used in the Li batteries are planar, such as conventional Cu and Li foils. The initial plating of Li on planar current collector is prone to inhomogeneous Li particle deposition, followed by the growth of Li dendrites on the Li particles. In this study, we show that a three-dimensional (3D) current collector with a submicron-sized skeleton and porous structure can change the plating behaviour. When the porous Cu foil is used as the 3D current collector, Li grows on the submicron-sized Cu skeleton and fills the pores of the 3D current collector. With Li-metal anode accommodated in the 3D current collector, we are able to get Li metal anodes free from the Li dendrite crux and remarkably improve the lifespan of Li-metal anodes. \n\n# Results \n\nPreparation for the 3D Cu foil with submicron skeleton. The 3D porous Cu foil is fabricated from a commercial planar $\\mathrm{Cu}$ foil via a facial and scalable method. The preparation process for the 3D porous $\\mathtt{C u}$ foil is schematically presented in Fig. 1a. The planar $\\mathtt{C u}$ foil was first immersed in an ammonia solution to allow $\\mathrm{Cu(OH)}_{2}$ deposition by self-assembly. Major chemical reactions took place during this period are (refs 37,38) \n\n$$\n\\mathrm{Cu}^{2+}+4\\mathrm{NH}_{3}\\rightarrow\\mathrm{Cu}(\\mathrm{NH}_{3})_{4}^{2+}\n$$ \n\n$$\n\\mathrm{Cu(NH_{3})_{4}^{2+}+2O H^{-}\\rightarrow C u(O H)_{2}+4N H_{3}\\uparrow}\n$$ \n\nThe $\\mathrm{Cu(OH)}_{2}$ on the Cu foil was dehydrated to get $\\mathtt{C u O}$ , which used to be applied as anodes, supercapacitors and others38,39. It was further reduced to get the porous $\\mathrm{Cu}$ as the porous current collector. From the powder X-ray diffraction profiles (Fig. 1b), it is evident that the cyan layer on the $\\mathrm{Cu}$ foil is $\\mathrm{Cu(OH)}_{2}$ and it is completely converted into Cu after dehydration and reduction (see Supplementary Fig. 1 for the photographs of the samples). The final Cu foil shows a 3D structure composed of bundles of Cu fibres, as shown in the scanning electron microscopy (SEM) images (Fig. 1c) The Cu fibres are several submicron in diameter and have a nanosized protuberant secondary structure on the surface, as shown in the inset in Fig. 1c. The Cu submicron fibres are roughly perpendicular to the foil, forming a jungle-like porous layer (see side view image in Supplementary Fig. 2). According to mercury porosimetry analysis (Supplementary Fig. 3), the median pore diameter of the 3D Cu is $2.1\\upmu\\mathrm{m}$ . The 3D Cu foil has an areal pore volume (pores o5 mm) of 1.5 \u0003 10 \u0002 3 cm3 cm \u0002 2 and a high areal pore area of $45\\mathrm{{cm}}^{2}\\mathrm{{cm}}^{-2}$ (pore area per unit geometric area). \n\n![](images/4d5146b7d4a3294bb102f2f47073dda8cb104f2644e4dad52b6ea726ef8b75ce.jpg) \nFigure 1 | Preparation and characterization for 3D Cu foil. (a) Schematic presentation of the procedures to prepare a 3D porous Cu foil from a planar Cu foil. (b) X-ray diffraction profiles of $C\\mathsf{u}(\\mathsf{O H})_{2}$ on the Cu foil and the final 3D Cu foil. The insets show digital images of the corresponding samples. (c) SEM images of the porous $\\mathsf{C u}$ (scale bar, $50\\upmu\\mathrm{m}\\right;$ . The inset shows the high-magnification image (scale bar, $2\\upmu\\mathrm{m})$ . \n\nLi-metal deposition behaviour. The 3D Cu foil was utilized to investigate the plating behaviour of Li metal on a 3D current collector. The pristine Cu foil was also tested as an example of planar current collectors. On a planar current collector, Li is apt to firstly form small Li dendrites $(0.1-0.5\\upmu\\mathrm{m}$ in diameter) on the smooth surface at the nucleation step. This nucleation mechanism has been well known and can be observed from the atomic force microscopy (AFM) image (Supplementary Fig. 4) at the nucleation step. The previously deposited small Li dendrite functions as a charge centre as the charges accumulate at sharp ends in the electric field (Fig. 2a). The subsequent Li metal is then deposited on these sharp ends and amplify the growth of the Li dendrites. In contrast, on the submicron skeleton of the 3D Cu foil, numerous protuberant tips on the submicron fibres function as the charge centres and nucleation sites. The electric field is roughly uniform and the charges are fairly homogeneously dispersed along the Cu skeleton. Therefore, Li is expected to nucleate and grow on the submicron Cu fibres with nanosized lumps, fill the pores of the 3D current collector, and eventually form a relatively even Li surface (Fig. 2b). To confirm this hypothesis, we plated Li on the planar and 3D Cu foils and disassembled the cells to observe the morphologies of the anodes. To focus on the effect of current collectors, we used 1 M lithium bis(trifluoromethane)sulfonimide (LiTFSI) dissolved in 1,3-dioxolane/1,2-dimethoxyethane (DOL/DME, 1:1 by volume) without any additives as electrolyte. Before further electrochemical procedures, the current collectors were first initialized by cycling at $_{0-1\\mathrm{V}}$ (versus $\\mathrm{Li^{+}/L i})$ at $50\\upmu\\mathrm{A}$ for five cycles to remove surface contaminations and stabilize the interface (Supplementary Fig. 5)30. A large area of mossy Li is observed on the planar Cu foil after depositing $2\\operatorname*{mA}\\mathrm{hcm}^{-2}$ of Li. A number of bumpy Li are found from the $52^{\\circ}$ side view image of the Li anode plated on the planar Cu. Li is deposited on the previously deposited Li dendrites and expands to larger and higher dendrites regardless of some area of bare $\\mathrm{cu}$ (Supplementary Fig. 6). The vertically grown dendrites can pierce through the separators and cause catastrophic cell failure. This plating behaviour of dendritic Li is consistent with previous reports and the drawbacks are well known40. For the 3D current collector, on the contrary, a relatively flat Li surface is obtained on the 3D Cu foil after depositing $2\\operatorname*{mA}\\mathrm{h}\\mathrm{cm}^{-2}$ of Li metal (Fig. 2c). According to the AFM image of the Li metal on the 3D current collector, the plated Li metal displays an undulating topography with gentle slopes whose height difference is $<2.5\\upmu\\mathrm{m}$ (Fig. 2d). No raised Li dendrites are found from the SEM and AFM images, thereby indicating that the possibility of the Li metal short-circuiting the cell is negligible. The morphology of the Li metal on the 3D Cu foil differs significantly from that on the planar Cu. The surface of the latter is so uneven that its height difference is beyond the measuring capability of AFM. The morphology of the Li-metal plated on the 3D current collector is in good agreement with the expectation, as illustrated in Fig. 2b. Therefore, by accommodating the Li metal into the 3D current collector, the growth of dendritic Li is effectively suppressed. \n\n![](images/4d166abacb982558f2606191c10004b9dba28d199841397f3341ee84892be020.jpg) \nFigure 2 | Electrochemical deposition behaviours of Li-metal anodes. Illustration of the proposed electrochemical deposition processes of Li metal on (a) planar current collector and (b) 3D current collector. The distribution of the electrons in the current collectors in the electrical field is schematically presented; the dashed lines illustrate the possible position where Li would be deposited. (c) Side view SEM image and (d) AFM height image of $2\\mathsf{m A h c m}^{-2}$ of Li deposited on the 3D Cu foil with a submicron skeleton. Scale bars, $10\\upmu\\mathrm{m}$ (c), $1\\upmu\\mathrm{m}$ (d). \n\nTo further examine spatial distribution of the Li metal deposited in the 3D Cu current collector, we employed time-offlight secondary ion mass spectrometry (ToF-SIMS) to probe the elemental distribution of $\\mathtt{C u}$ and Li in the Li-metal anode $(2\\mathrm{mA}\\mathrm{hcm}^{-2})$ in the 3D porous Cu current collector. The image of $\\mathrm{Cu^{+}}$ (Fig. 3a) shows the $\\mathrm{Cu}$ framework with pores. Li is plated mainly on the Cu skeleton and fills the pores of the 3D Cu foil (Fig. 3b). In addition, based on the depth profiles of $\\mathrm{Cu^{+}}$ and $\\mathrm{Li}^{+}$ (Supplementary Fig. 7) from the anode, their intensities with the sputter time (that is, depth distribution of Cu and Li) vary coincidently. These results confirm that the Li metal is accommodated into the 3D current collector rather than merely on the surface. The larger scale cross-sectional SEM images further demonstrate the accommodation of Li inside the 3D Cu. The thickness of the 3D Cu foil is $\\sim43\\upmu\\mathrm{m}$ and that of porous layer is $\\sim24\\upmu\\mathrm{m}$ (Fig. 3c). After plating $2\\operatorname*{inA}\\mathrm{h}\\mathrm{cm}^{-2}$ of Li metal, the porous layer is filled with Li, which is $\\sim20\\upmu\\mathrm{m}$ in thickness (Fig. 3d). In addition, it is evident that Li metal is constrained in the 3D Cu foil in a fairly compact manner. The densely deposited Li anode contributes to high areal capacity. The elemental distribution images obtained via ToF-SIMS and the crosssectional SEM images demonstrate that the Li metal is grown along the submicron Cu skeleton and is accommodated in the reserved porous structure. Even at higher current densities (2 and $5\\mathrm{\\mA}\\mathrm{cm}^{-2},$ ), Li is deposited inside the 3D structure (Supplementary Fig. 8). The accommodation of Li could be attributed to the unique structure of the Cu submicron fibres, which provide a high surface area inside the 3D structure (45 times that of the geometric area, see Supplementary Fig. 3). The high surface area of 3D current collector provides more electroactive surface area for Li ions and electrons in the porous layer, where Li ions get electrons and deposit inside the 3D current collector. If the 3D current collector can provide sufficient pore volume for Li anode, the plating and stripping of Li can be controlled and the Li-metal anode will not form fatal dendrites that may pierce the separator. \n\nWe also investigated the growing and stripping process of Li in detail to find the morphology evolution of the Li anode and the structural stability of the substrate (Fig. 4). From the SEM images of anodes with increasing Li amounts on the 3D Cu foil (Fig. 4a–d), Li grows on the Cu skeleton and gradually fills the pores of the porous Cu foil, forming an even surface (Fig. 4d). Given that the initially nucleated Li particles are several submicron in diameter, as reported in previous literature40 and demonstrated by the AFM image (Supplementary Fig. 4), the submicron Cu skeleton with nanosized protuberances is particularly appropriate for the nucleation and growth of Li metal. The Li metal can also be stripped reversibly from the submicron-structured 3D Cu current collector. As shown in the SEM images of the Li anodes during stripping (Fig. 4e–g), the Li metal is gradually stripped from the current collector and is completely stripped after recharging to $0.5\\mathrm{V}$ . Furthermore, the submicron Cu fibres remain structurally stable after Li stripping (Fig. 4g). After repeated cycles, the surface of the Li-metal anode still keeps even without presence of protruding Li dendrites (Fig. 4h and Supplementary Fig. 9). The dendritic problem is noticeably mitigated as the Li metal can plate and strip reversibly forming an even surface. We characterized the solid electrolyte interphase (SEI) film on the Li-metal anode with the 3D current collector after 10 cycles by X-ray photoelectron spectroscopy (XPS). According to the XPS spectra (Supplementary Fig. 10), the SEI film on the 3D Cu current collector is composed of ROLi, ROCOOLi, LiF and so on, in agreement with that reported in literature using a similar electrolyte41. The SEI film is generally stabilized during the initial cycling, which was applied to facilitate the interface stabilization30. After initialization, as indicated in \n\n![](images/59149a56043eb20f9deb6cccf057b3b73fad2cae660905ef9e13a0b58120e574.jpg) \nFigure 3 | Spatial distribution of Li anode in 3D current collector. Elemental distribution images of (a) $\\mathsf{C u}^{+}$ and $({\\pmb{6}}){\\sqcup}^{+}$ of the Li-metal anode $(2\\mathsf{m A}\\mathsf{h c m}^{-2})$ ) deposited in the submicron-structured 3D Cu probed via ToF-SIMS. Cross-sectional view SEM images of (c) the pristine 3D porous Cu foil and (d) $2\\mathsf{m A h c m}^{-2}$ of Li deposited on 3D porous Cu. Scale bars, $10\\upmu\\mathrm{m}$ (c), $20\\upmu\\mathrm{m}$ (d). \n\n![](images/ab1c3e12468bf96a1f5368655847d619124dd4c78ff4f2db3c6359b3e561cecd.jpg) \nFigure 4 | Morphology of Li-metal anode during plating/stripping. Top view SEM images of (a) pristine 3D porous Cu foil without Li metal and after plating (b) $0.5\\mathsf{m A h c m}^{-2}$ , (c) $1\\mathsf{m A h c m}^{-2}$ and (d) $2\\mathsf{m A h c m}^{-2}$ of Li metal into 3D current collectors; anodes after stripping (e) $1\\mathsf{m A h c m}^{-2}$ , (f) $1.5\\mathsf{m A h c m}^{-2}$ and $(\\pmb{\\mathsf{g}})2\\mathsf{m A}\\mathsf{h c m}^{-2}$ (that is, recharged to $0.5\\mathsf V.$ ) from the Li anodes $(2\\mathsf{m A}\\mathsf{h c m}^{-2})$ with 3D current collectors. ${\\bf\\Pi}({\\bf h})$ Side view SEM image of the Li anode with the 3D current collector after 10 cycles. Scale bars, $2\\upmu\\mathrm{m}$ . The rectangle symbols exhibit the amount of Li metal in each image; each solid rectangle represents $0.5\\mathsf{m A h c m}^{-2}$ of Li. The Li plating/stripping states $(\\mathsf{a}\\mathsf{-}\\mathsf{h})$ are indicated in (i) galvanostatic discharge/charge voltage profile at $0.5\\mathsf{m A c m}^{-2}$ . Note that due to the nature of the ex situ method, the profile is only an indication for the Li plating/stripping states in a–h, and is not necessarily the real test result of each sample. \n\nSupplementary Fig. 5, capacity contributed from the SEI formation is negligible compared with that from Li metal. We also note that despite the fibrous structure, the Cu submicron fibres themselves do not penetrate the separator because they are obtuse and flexible. This result is demonstrated by the electrochemical performance of the Li-metal anodes with the 3D porous Cu current collectors and Celgard separators in Fig. 4i and in the following discussion. \n\nElectrochemical performance. We examined the electrochemical behaviour of Li plating/stripping and the cycling stability on different current collectors by comparing the galvanostatic discharge/charge voltage profiles of the Li electrode with the planar or 3D porous $\\mathrm{Cu}$ current collectors $(\\mathrm{Li}@\\mathrm{Cu})$ in symmetric Li|Li@Cu cells (Fig. 5a). The symmetric cell contained a Li counter/reference electrode and a $\\mathrm{Li@Cu}$ working electrode. A hollow spacer was used substituting for the Celgard separator to allow possible internal short circuits (see Methods and Supplementary Fig. 11 for more details). During Li plating/ stripping at $0.2\\mathrm{\\mA}\\mathrm{cm}^{-2}$ (except the initial plating at $0.5\\mathrm{\\mA}\\mathrm{{cm}}^{-2},$ ), the Li electrode on the planar Cu shows random voltage oscillations, which could possibly be caused by the unstable Li/electrolyte interface and electrical disconnection because of repeated growth/corrosion of dendritic Li (ref. 30). After cycling for $\\sim470\\mathrm{h}$ , the continuously growing Li dendrites on the Cu foil finally reach the counter electrode and short-circuit the cell. In contrast, Li plating/stripping on the 3D Cu foil exhibits exceptional cycling stability with negligible potential fluctuation. After cycling for $\\mathsf{600h},$ no sign of short circuit is observed, indicating that the growth of dendritic Li has been significantly retarded. The short circuit phenomenon and voltage variation can be observed clearly from the voltage hysteresis curves (Fig. 5b). The voltage hysteresis is the difference between the voltages of Li stripping and plating and is mainly determined by the current density, interfacial properties and charge transfer resistance30,31. At a current density of $0.2\\operatorname{mA}\\mathrm{cm}^{-2}$ , Li plating/ stripping on the planar $\\mathtt{C u}$ foil shows an irregular fluctuating voltage hysteresis because of the unstable interface of Li on the planar Cu. The voltage hysteresis drops to $\\mathrm{\\sim10\\mathrm{mV}}$ abruptly after 94 cycles (that is, $470\\mathrm{h}$ ) because of the dendrite-induced short circuit. The voltage hysteresis of Li plating/stripping on the 3D Cu foil, however, is generally stable without any irregular oscillations. Although the voltage hysteresis on 3D Cu foil increases gradually after the initial cycle, it is still $<50\\mathrm{mV}$ after cycling for $600\\mathrm{h}$ , which is close to or better than the previously reported results30,31. This result could be attributed to the larger surface area of the porous $\\mathrm{Cu}$ than that of the planar one. The larger electroactive area can provide a larger Li/electrolyte interface, lower the practical current density, and reduce the charge transfer resistance during cycling compared with the planar $\\mathtt{C u}$ (Supplementary Fig. 12). The reduced hysteresis of the Li anode is in favour of low voltage polarization during discharge/charge in full Li-metal batteries. \n\nUnidirectional galvanostatic plating of Li was applied to accelerate the short-circuit analysis. Li was continuously plated onto different current collectors, including planar Cu foil, Li foil and 3D porous Cu foil, at $0.5\\operatorname{mA}\\mathrm{cm}^{\\preceq}\\dot{2}$ until short circuit. \n\n![](images/4f05df232e497780f7966981eb0ba2add4016f4f82e722745c2a5f07c49f38d9.jpg) \nFigure 5 | Electrochemical performance of Li metal anodes. (a) Voltage profiles and $(\\pmb{\\ b})$ average voltage hysteresis of Li metal plating/stripping at $0.2\\mathsf{m A c m}^{-2}$ in symmetric Li|L $\\mathsf{i}@\\mathsf{C u}$ cells with planar or 3D Cu foil as current collector. (c) Average short-circuit time $T_{\\mathsf{s c}}$ for unidirectional galvanostatic Li plating from Li foil to planar Cu foils, Li foils and 3D Cu foils in symmetric cells at $0.5\\mathsf{m A c m}^{-2}$ . The error bars are standard deviations obtained from at least three independent cells for each current collector. \n\nThe statistical results of the short-circuit time ( $T_{\\mathrm{sc}}$ , Fig. 5c) prove that dendritic Li growth on 3D Cu foil is considerably slower than on the planar foils, and the cell life of the Li anodes with porous current collectors is much longer. In fact, as long as there is room for Li accommodation in the 3D current collector, Li plating will be restricted within the reserved pores and will not cause cell failure. Therefore, a long lifespan of the Li-metal anode is expected with the 3D current collector. \n\nThe Coulombic efficiencies of the Li anodes on the planar $\\mathtt{C u}$ and 3D Cu are compared in Supplementary Fig. 13. On the planar Cu, the plating/stripping efficiency of Li metal changes from $70\\%$ to over $100\\%$ because of the unstable morphology of the Li dendrites and the anode/electrolyte interface during cycling. Because of the submicron structure in the porous Cu foil, the efficiency of Li on the 3D Cu is $\\sim97\\%$ after 50 cycles at $0.5\\mathrm{mA}\\mathrm{\\dot{c}m}^{-2}$ , which is considerably more stable than that on the planar $\\mathrm{Cu}$ foil. The initial Coulombic efficiency of the Li anode with 3D current collector is $71\\%$ in DOL/DME. To further improve the initial Coulombic efficiency of the Li anode, $\\mathrm{LiNO}_{3}$ and lithium polysulphide are used as additives in the electrolyte, which have been reported to play a synergetic effect on Li anode42. The initial Coulombic efficiency can be remarkably improved to $93\\%$ by adding $1\\%\\mathrm{LiNO}_{3}$ and $0.005\\mathrm{M}\\mathrm{Li}_{2}\\mathrm{S}_{6}$ in the electrolyte and it is finally stabilized to $98.5\\%$ (Supplementary Fig. 14). \n\nFollowing the methods in literature30,43, the Li anode with 3D Cu current collector was assembled into a full cell against a ${\\mathrm{LiFePO}}_{4}$ cathode. As shown in Supplementary Fig. 15a, the full cell shows a high capacity and cycling stability. As the preparation for the 3D Cu foils is facile and scalable (see a 3D Cu foil of $\\sim70\\mathrm{cm}^{2}$ in Supplementary Fig. 1), large Li-metal anodes using the 3D Cu current collectors was prepared and assembled into a pouch cell. The cell is demonstrated feasible by powering an LED device (Supplementary Fig. 15b), indicating the potential of the 3D Cu current collector for practical application. \n\n# Discussion \n\nThe pore volume, pore size and surface area are important parameters for 3D current collectors. For 3D current collectors, the pore volume of the porous structure determines the amount of Li that can be accommodated, that is, the areal capacity density of the anode. The porous layer of the 3D foil is $\\sim24\\upmu\\mathrm{m}$ (Fig. 3c). According to the mercury porosimetry analysis, the volume of effective pores is $1.5\\times10^{-3}\\mathrm{cm}^{3}\\mathrm{cm}^{-2}$ (Supplementary Fig. 3). The pore volume can accommodate $\\sim0.8\\operatorname*{mgcm}^{-2}$ of Li metal. The areal capacity density of Li anode accommodated in the porous $\\mathtt{C u}$ foil is estimated to be up to $\\sim3.1\\mathrm{mAhcm}^{-2}$ . The areal capacity density can fulfil most of the present demands and can be improved simply by increasing the pore volume of the 3D Cu foil. In fact, by increasing the immersion time of the Cu foil in the ammonia solution, the porous layer of the 3D Cu foil can be increased to $\\sim40\\upmu\\mathrm{m}$ with more abundant pores for Li accommodation (Supplementary Fig. 16). \n\nIn addition to the submicron-structured 3D Cu foil, there are other possible candidates for the 3D current collector. For example, fibrous $\\mathrm{Li}_{7}\\mathrm{B}_{6}$ derived from Li–B alloy has been reported as a 3D matrix for Li anode35,36. However, the 3D structure of the alloy is far less abundant than the porous Cu foil. Thus, the alloy is less satisfactory in terms of suppressing dendrite growth by the 3D structure, let alone its drawbacks of cost and mechanical strength compared with the porous Cu foil. \n\nRecently, nanostructured graphene framework was also found helpful for stable and efficient Li deposition44. The reported graphene network has hierarchical pores with an average pore size of $10\\mathrm{nm}$ . Another possible candidate as 3D current collector is Cu foam, which is commercially accessible and provides a large pore volume for Li. However, the average pore size of the $\\bar{\\mathrm{Cu}}$ foam is too large $(170\\upmu\\mathrm{m})$ with a wide pore size distribution (Supplementary Fig. 17). With such a large pore size approaching macroscopic scale, the Cu foam is more of a conventional current collector without any of the effects of space constraint and dendrite suppression. Unlike the Li anode inside the 3D Cu foil with a submicron skeleton, the Li metal can be detached easily from the backbones of the Cu foam, thereby resulting in electric disconnection. From the digital and SEM images of the Li anode with the Cu foam current collector after 20th Li stripping, a large amount of ‘dead Li’ is found in the intervals of the Cu backbones and even on the separator (Supplementary Fig. 18), resulting in a very poor plating/stripping efficiency. The plating/stripping processes of Li in the Cu foam are irreversible with an efficiency of only $\\sim40\\%$ (Supplementary Fig. 19). Therefore, the Cu foam with an inappropriately large pore size is not suitable as 3D current collector for the Li anode. In contrast, Li anode in the 3D current collector with a median pore size of $2.1\\upmu\\mathrm{m}$ can be reversibly plated/stripped from the substrate (Fig. 4) with a high Coulombic efficiency. Therefore, the submicron structure of the 3D Cu current collector, on one hand, provides a high pore volume to accommodate the Li anode with a favourable capacity density, and on the other hand, possesses suitable submicron 3D structure for stable and reversible Li plating/stripping. These results highlight the importance of the pore size of 3D current collectors for Li-metal anodes. \n\nAs a most important parameter affecting Li plating, the electroactive surface area of a 3D current collector (the surface area exposed to the electrolyte, that is, total pore area here) is crucial for a sufficient electric contact between the Li anode and the substrate. The percentage of Li metal deposited inside the 3D structure $(\\eta)$ is generally determined by the ratio of electroactive surface area to geometric area of electrode (electroactive area ratio, $\\boldsymbol{r}$ ). Assuming that the electrons distribute uniformly on the skeleton and the current density is not too high (that is, Li-ion diffusion is not limited), Li will be deposited on the electroactive surface equiprobably. In this case, as depicted in Fig. $6,\\ \\eta$ is determined by $\\boldsymbol{r},$ according to the following formula \n\n$$\n\\eta={\\frac{r-1}{r}}\n$$ \n\n![](images/bbdd5e302588a6303f722806046eefe16a8b4ec049100fbf1920c7598f1da158.jpg) \nFigure 6 | Li accommodation percentage with electroactive area ratio. The plot shows $\\eta$ as a simplified function of $r.$ The electroactive surface area and geometric area of the current collector are illustrated in the inset. The planar $\\mathsf{C u}$ Cu foam and 3D Cu are indicated in the plot. \n\nThe textural parameters of planar Cu, Cu foam and 3D Cu are compared in Supplementary Table 1. The 3D Cu possesses a much larger specific surface area than planar Cu and $\\mathrm{Cu}$ foam. As a result of the high electroactive area ratio of 3D Cu $(r=45)$ ), $98\\%$ of Li metal is deposited inside the 3D Cu structure. As shown in Fig. 6, for the planar current collectors, $r=1$ and $\\eta=0$ , indicating that all Li metal is deposited on surface of the electrode. For the Cu foam, $r=5.2$ and $\\eta=81\\%$ , indicating $19\\%$ of Li metal is deposited outside of the 3D structure. Although this formula is based on a simplified model, it explains why Li metal is accommodated in the 3D current collector rather than deposited at the top, even at higher current densities. Therefore, a high electroactive area ratio is of key importance for a 3D current collector accommodating Li metal and is a benchmark for effective 3D current collectors. \n\nWe have demonstrated that Li anode can be accommodated in the reserved pores of the 3D current collector with a submicron skeleton and high surface area, thereby suppressing the growth of dendritic Li and solving the associated problems of Li anodes. The accommodation of the Li anode into the reserved pores addresses the issue of dendrite growth remarkably. Hence, the Li metal anode can run for $600\\dot{\\mathrm{h}}$ without resulting in short circuit, thereby significantly improving the cell life and safety of Li-metal batteries. Because of the submicron structure of the 3D current collector, the Li anode holds a high areal capacity and maintains a good plating/stripping efficiency of $\\sim98.5\\%$ . In addition, because of the high electroactive area of the submicron 3D structure, a high portion of Li metal is accommodated inside the 3D current collector and the voltage hysteresis and charge transfer resistance of the Li anode is reduced compared with that on a planar current collector. The porous current collector may not be limited to the porous Cu foil; other advanced porous architectures could also help improve the lifespan and performance of the Li anodes. It is noteworthy that combined means should be taken to develop the Li-metal anodes. The submicron-structured 3D current collector is expected to play a synergistic effect with other rationally designed cell components, including suitable electrolytes and additives, Li surface protective layers, modified Li metal, and so forth, to improve the comprehensive performance of the Li-metal anode. The utilization of the 3D architecture to accommodate the Li anode will facilitate further investigations on Li anodes and hasten the development of Li-metal batteries towards nextgeneration energy storage devices. \n\n# Methods \n\nSynthesis. A Cu foil ( $25\\upmu\\mathrm{m}$ in thickness, GoodFellow) was first washed by diluted hydrochloric acid and subsequently with deionized water to remove surface impurities. The Cu foil was immersed in an ammonia solution $(5\\mathrm{wt\\%})$ for $36\\mathrm{h}$ (or $48\\mathrm{h}$ for thicker porous layer), during which the solution became blue and a cyan layer of $\\mathrm{Cu(OH)}_{2}$ generated on the surface of the Cu foil. The foil with the cyan layer was washed by water and dried at $60^{\\circ}\\mathrm{C}$ . It was finally heated at $180^{\\circ}\\mathrm{C}$ for $^{4\\mathrm{h}}$ for dehydration and reduced at $400^{\\circ}\\mathrm{C}$ for $^\\mathrm{10h}$ in a $\\mathrm{H}_{2}/\\mathrm{Ar}$ mixed flow $(5\\%\\mathrm{~H}_{2}$ in volume) to get the final 3D porous $\\mathrm{Cu}$ foil. The 3D porous $\\mathtt{C u}$ was punched out into circular disks $\\cdot\\Phi10\\mathrm{mm})$ as the 3D current collectors for Li anode after vacuum drying. \n\nElectrochemistry. CR2032-type coin cells were assembled to deposit Li on the current collectors to evaluate the Coulombic efficiency, electrochemical impedance spectra and other properties. The cells were assembled in an argon-filled glove box. The coin cell was composed of a Li foil as the counter/reference electrode, a Celgard separator, and a current collector as the working electrode. The electrolyte was 1 M LiTFSI in DOL/DME (1:1 by volume, $30\\upmu\\mathrm{l}.$ BASF) without any additives unless noted otherwise. The Coulombic efficiency was tested at $0.5\\mathrm{mA}\\mathrm{\\dot{c}}\\mathrm{m}^{-2}$ on a LAND electrochemical testing system at room temperature. The batteries were first cycled at $_{0-1\\mathrm{V}}$ (versus $\\mathrm{Li}^{+}/\\mathrm{Li})$ at $50\\upmu\\mathrm{A}$ for five cycles to stabilize the SEI and remove surface contaminations. After that, $1\\mathrm{mAhicm}^{-2}$ of Li was deposited onto the current collector and then charged to $0.5\\mathrm{V}$ (versus $\\mathrm{Li^{+}/L i}\\rangle$ to strip the Li at $0.5\\operatorname{mA}{\\mathrm{cm}^{-2}}$ for each cycle. The Coulombic efficiency was calculated based on the ratio of Li stripping and plating. Electrochemical impedance spectra measurement was performed using an Autolab workstation (Metrohm) in the frequency range of $100\\mathrm{kHz}$ to $100\\mathrm{mHz}$ after specific cycles. \n\nSymmetric cells were employed to evaluate the cycling stability and cycle life (short-circuit time $\\left[T_{\\mathrm{sc}}\\right]$ of the Li anodes on different current collectors. The symmetric cell was assembled using a hollow spacer substituting for the Celgard separator in a CR2032-type coin cell, as illustrated in Supplementary Fig. 11. The electrolyte (1 M LiTFSI in DOL/DME, $200\\upmu\\mathrm{l}{\\mathrm{l}},$ was carefully charged into the spacer without entrainment of bubbles. For the long-term galvanostatic discharge/charge test, $2\\operatorname*{mA}\\mathrm{h}\\mathrm{cm}^{-2}$ of Li was first deposited on the current collectors at $0.5\\operatorname{mA}\\mathrm{cm}^{-2}$ and the cells were then charged and discharged at $0.2\\operatorname{mA}\\mathrm{cm}^{-2}$ for $2.5\\mathrm{h}$ in each half cycle. For the unidirectional galvanostatic polarization (accelerated test for $\\begin{array}{l}{\\displaystyle{T_{\\mathrm{sc}}})}\\end{array}$ , Li was continuously plated onto the current collectors from the counter electrode at $0.5\\operatorname{mA}\\mathrm{cm}^{-2}$ until short circuit. The average $T_{\\mathrm{sc}}$ was obtained from at least three cells for each current collector. \n\nFor full cells with 3D Cu-based Li-metal anodes, $\\mathrm{LiFePO_{4}}$ (Sanxin Industrial) was employed as cathode material. LiFe $\\mathrm{\\cdotPO_{4}}$ was casted on an Al foil with an areal capacity density of $\\sim0.5\\mathrm{mAhcm}^{-2}$ . The 3D Cu was first assembled into a half cell using a Li foil as counter electrode. After plating $1\\mathrm{mAhcm}^{-2}$ of Li metal into the 3D current collector, Li anode was extracted from the half cell and reassembled into a full cell against ${\\mathrm{LiFePO}}_{4}$ cathode. The electrolyte was the same as that in the half cells (1 M LiTFSI in DOL/DME, $30\\upmu\\mathrm{l})$ ). Assembly of pouch cells was similar to that of the coin cells. The electrodes ( $\\sim42c m^{2}$ in area) were stacked and assembled in a pouch cell. Li anodes plated in the 3D current collector were assembled into a pouch cell against $\\mathrm{LiFePO_{4}}$ cathodes with $4\\mathrm{ml}$ of the electrolyte to gain the pouch full cell with a capacity of $\\mathrm{\\sim40\\mAh}$ . \n\nCharacterization. The X-ray diffraction profiles of the as-obtained samples were obtained using an Empyrean X-ray diffractometer (PANalytical) with $\\mathrm{Cu}\\ \\mathrm{K}\\mathfrak{a}$ radiation $\\acute{\\lambda}=\\bar{1}.54056\\bar{\\mathrm{A}},$ ) operated at $40\\mathrm{kV}$ and $40\\mathrm{mA}$ . The top view and cross-sectional view images were observed on a field emission SEM (JEOL 6701F) and the $52^{\\circ}$ side view images of the Li anode were obtained from a focused ion beam microscope (Helios NanoLab 600i, FEI) with a tiltable specimen holder. An AFM system (Bruker Multimode 8 with a Nanoscope V controller) was employed to measure the height images of the anode surfaces. ToF-SIMS (TOF.SIMS5 IONTOF GmbH) was used to perform elemental analysis and depth profiles of the Li anode on the 3D Cu foil. A $20\\mathrm{keV\\Ar_{n}^{+}}$ $(n=1,700)$ beam was used as sputter beam, which was scanned on an area of $300\\times300\\upmu\\mathrm{m}^{2}$ at a sputter rate of $\\stackrel{\\cdot}{\\sim}10\\upmu\\mathrm{mh}^{-1}$ . XPS was conducted on the ESCALab 250Xi (Thermo Scientific) using $200\\mathrm{W}$ monochromatized Al $\\operatorname{K}\\mathfrak{a}$ radiation. Porosity analysis was performed by a mercury porosimeter (AutoPore IV 9500, Micromeritics) with pressure from 0.1 to 60,000 psi. \n\nFor the ex situ analyses of the Li-metal anodes, batteries with specific discharge/ charge states were first disassembled in the glove box to harvest the Li anodes. Before any characterization, the Li anodes were rinsed using DOL and DME solvents to remove residual electrolyte and LiTFSI salt and then dried in the glove box at ambient temperature. The Li anodes on planar Cu were not rinsed because the Li metal was loosely plated on the planar Cu collector and would be easily removed if washed. For ex situ SEM observations, the anodes were transferred through a specially designed device from the glove box to the vacuum chamber of the SEM without exposing them to air. For ex situ ToF-SIMS and XPS analyses, the samples were protected by argon and quickly transferred into the vacuum chamber. The samples were exposed to dry air for $<30\\mathrm{s}$ . The ex situ AFM images were scanned directly in argon atmosphere using an AFM apparatus mounted on top of a suspended marble in the glove box. \n\n# References \n\n1. Tarascon, J. M. & Armand, M. Issues and challenges facing rechargeable lithium batteries. Nature 414, 359–367 (2001). \n2. Kim, H. et al. Metallic anodes for next generation seondary batteries. Chem. Soc. Rev. 42, 9011–9034 (2013). \n3. Whittingham, M. S. History, evolution, and future status of energy storage. Proc. IEEE 100, 1518–1534 (2012). \n4. Goodenough, J. B. & Park, K.-S. The Li-ion rechargeable battery: a perspective. J. Am. Chem. Soc. 135, 1167–1176 (2013). \n5. Zhu, J., Yang, D., Yin, Z., Yan, Q. & Zhang, H. Graphene and graphene-based materials for energy storage applications. Small 10, 3480–3498 (2014). \n6. Scrosati, B., Hassoun, J. & Sun, Y. K. Lithium-ion batteries. A look into the future. Energy Environ. Sci 4, 3287–3295 (2011). \n7. Bruce, P. G., Freunberger, S. A., Hardwick, L. J. & Tarascon, J. M. Li– ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ and Li–S batteries with high energy storage. Nat. Mater. 11, 19–29 (2012). \n8. Yin, Y.-X., Xin, S., Guo, Y.-G. & Wan, L.-J. Lithium–sulfur batteries: electrochemistry, materials, and prospects. Angew. Chem. Int. Ed. 52, 13186–13200 (2013). \n9. Song, M.-K., Cairns, E. J. & Zhang, Y. Lithium/sulfur batteries with high specific energy: old challenges and new opportunities. Nanoscale 5, 2186–2204 (2013). \n10. Ji, X. & Nazar, L. F. Advances in Li–S batteries. J. Mater. Chem. 20, 9821–9826 (2010). based on selenium and selenium-sulfur as a positive electrode. J. Am. Chem. Soc. 134, 4505–4508 (2012). \n12. Safari, M., Adams, B. D. & Nazar, L. F. Kinetics of oxygen reduction in aprotic Li– ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ cells: a model-based study. J. Phys. Chem. Lett. 5, 3486–3491 (2014). \n13. Dong, S. et al. Insight into enhanced cycling performance of Li– ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ batteries based on binary $\\mathrm{CoSe}_{2}/\\mathrm{CoO}$ nanocomposite electrodes. J. Phys. Chem. Lett. 5, 615–621 (2014). \n14. Manthiram, A., Chung, S. H. & Zu, C. Lithium–sulfur batteries: progress and rospects. Adv. Mater. 27, 1980–2006 (2015). \n15. Li, N. et al. An aqueous dissolved polysulfide cathode for lithium–sulfur batteries. Energy Environ. Sci 7, 3307–3312 (2014). \n16. Bresser, D., Passerini, S. & Scrosati, B. Recent progress and remaining challenges in sulfur-based lithium secondary batteries - a review. Chem. Commun. 49, 10545–10562 (2013). \n17. Wang, Z. et al. Enhancing lithium–sulphur battery performance by strongly binding the discharge products on amino-functionalized reduced graphene oxide. Nat. Commun. 5, 5002 (2014). \n18. Zhao, Q. et al. Sulfur nanodots electrodeposited on Ni foam as highperformance cathode for Li–S batteries. Nano Lett. 15, 721–726 (2015). \n19. Yang, C.-P., Yin, Y.-X. & Guo, Y.-G. Elemental selenium for electrochemical energy storage. J. Phys. Chem. Lett. 6, 256–266 (2015). \n20. Luo, C., Zhu, Y., Wen, Y., Wang, J. & Wang, C. Carbonized polyacrylonitrilestabilized $\\mathrm{SeS}_{x}$ cathodes for long cycle life and high power density lithium ion batteries. Adv. Funct. Mater. 24, 4082–4089 (2014). \n21. Lu, D. et al. Failure mechanism for fast-charged lithium metal batteries with liquid electrolytes. Adv. Energy Mater. 5, 1400993 (2015). \n22. Harry, K. J., Hallinan, D. T., Parkinson, D. Y., MacDowell, A. A. & Balsara, N. P. Detection of subsurface structures underneath dendrites formed on cycled lithium metal electrodes. Nat. Mater. 13, 69–73 (2014). \n23. Xu, W. et al. Lithium metal anodes for rechargeable batteries. Energy Environ. Sci. 7, 513–537 (2014). \n24. Park, M. S. et al. A highly reversible lithium metal anode. Sci. Rep. 4, 3815 (2014). \n25. Qian, J. et al. High rate and stable cycling of lithium metal anode. Nat. Commun. 6, 6362 (2015). \n26. Hu, J. J., Long, G. K., Liu, S., Li, G. R. & Gao, X. P. A LiFSI-LiTFSI binary-salt electrolyte to achieve high capacity and cycle stability for a Li–S battery. Chem. Commun. 50, 14647–14650 (2014). \n27. Ding, F. et al. Dendrite-free lithium deposition via self-healing electrostatic shield mechanism. J. Am. Chem. Soc. 135, 4450–4456 (2013). \n28. Lu, Y., Tu, Z. & Archer, L. A. Stable lithium electrodeposition in liquid and nanoporous solid electrolytes. Nat. Mater. 13, 961–969 (2014). \n29. Zu, C. & Manthiram, A. Stabilized lithium–metal surface in a polysulfide-rich environment of lithium–sulfur batteries. J. Phys. Chem. Lett. 5, 2522–2527 (2014). \n30. Zheng, G. et al. Interconnected hollow carbon nanospheres for stable lithium metal anodes. Nat. Nanotech. 9, 618–623 (2014). \n31. Yan, K. et al. Ultrathin two-dimensional atomic crystals as stable interfacial layer for improvement of lithium metal anode. Nano Lett. 14, 6016–6022 (2014). \n32. Huang, C. et al. Manipulating surface reactions in lithium-sulphur batteries using hybrid anode structures. Nat. Commun. 5, 3015 (2014). \n33. Ma, G. et al. Lithium anode protection guided highly-stable lithium–sulfur battery. Chem. Commun. 50, 14209–14212 (2014). \n34. Kim, H. et al. Enhancing performance of Li–S cells using a Li–Al alloy anode coating. Electrochem. Commun. 36, 38–41 (2013). \n35. Zhang, X. et al. Improved cycle stability and high security of Li-B alloy anode for lithium–sulfur battery. J. Mater. Chem. A 2, 11660 (2014). \n36. Cheng, X. B., Peng, H. J., Huang, J. Q., Wei, F. & Zhang, Q. Dendrite-free nanostructured anode: entrapment of lithium in a 3D fibrous matrix for ultra-stable lithium-sulfur batteries. Small 10, 4257–4263 (2014). \n37. Liu, J. et al. Hierarchical nanostructures of cupric oxide on a copper substrate: controllable morphology and wettability. J. Mater. Chem. 16, 4427–4434 (2006). \n38. Yuan, S. et al. Engraving copper foil to give large-scale binder-free porous CuO arrays for a high-performance sodium-ion battery anode. Adv. Mater. 26, 2273–2279 (2014). \n39. Yu, L. et al. 3D porous gear-like copper oxide and their high electrochemical performance as supercapacitors. CrystEngComm 15, 7657–7662 (2013). \n40. Yamaki, J.-i. et al. A consideration of the morphology of electrochemically deposited lithium in an organic electrolyte. J. Power Sources 74, 219–227 (1998). \n41. Xiong, S., Xie, K., Diao, Y. & Hong, X. On the role of polysulfides for a stable solid electrolyte interphase on the lithium anode cycled in lithium–sulfur batteries. J. Power Sources 236, 181–187 (2013). \n42. Li, W. et al. The synergetic effect of lithium polysulfide and lithium nitrate to prevent lithium dendrite growth. Nat. Commun. 6, 7436 (2015). \n43. Mukherjee, R. et al. Defect-induced plating of lithium metal within porous graphene networks. Nat. Commun. 5, 3710 (2014). \n\n44. Cheng, X.-B. et al. Dual-phase lithium metal anode containing a polysulfide-induced solid electrolyte interphase and nanostructured graphene framework for lithium–sulfur batteries. ACS Nano 9, 6373–6382 (2015). \n\n# Acknowledgements \n\nThis work was supported by the National Basic Research Program of China (Grant Nos. 2012CB932900 and 2013AA050903), the National Natural Science Foundation of China (Grant Nos. 51225204, 21127901 and U1301244), the ‘Strategic Priority Research Program’ of the Chinese Academy of Sciences (Grant No. XDA09010300), and CAS. The authors thank Dr Kui Wu and Prof. Fuyi Wang for their help on the ToF-SIMS experiments. \n\n# Author contributions \n\nY.-G.G. proposed and supervised the project. Y.-G.G. and C.-P.Y. conceived and designed the experiments with the help from Y.-X.Y and N.-W.L. S.-F.Z. proposed the method for preparing the 3D Cu foil. C.-P.Y. carried out the experiments. Y.-G.G., C.-P.Y. and Y.-X.Y. participated in analysing the experimental results and preparing the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Yang, C.-P. et al. Accommodating lithium into 3D current collectors with a submicron skeleton towards long-life lithium metal anodes. Nat. Commun. 6:8058 doi: 10.1038/ncomms9058 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1002_adma.201502110", + "DOI": "10.1002/adma.201502110", + "DOI Link": "http://dx.doi.org/10.1002/adma.201502110", + "Relative Dir Path": "mds/10.1002_adma.201502110", + "Article Title": "A Large-Bandgap Conjugated Polymer for Versatile Photovoltaic Applications with High Performance", + "Authors": "Zhang, MJ; Guo, X; Ma, W; Ade, H; Hou, JH", + "Source Title": "ADVANCED MATERIALS", + "Abstract": null, + "Times Cited, WoS Core": 1015, + "Times Cited, All Databases": 1045, + "Publication Year": 2015, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000359911500023", + "Markdown": "# A Large-Bandgap Conjugated Polymer for Versatile Photovoltaic Applications with High Performance \n\nMaojie Zhang, Xia Guo, Wei Ma,\\* Harald Ade,\\* and Jianhui Hou\\* \n\nBulk heterojunction (BHJ) polymer solar cells (PSCs), where a blend film of conjugated polymers as the donors and fullerene derivatives as the acceptors acts as the active layer, have attracted considerable attention in both academia and industry because of their low cost, light weight, easy fabrication, and potential for use in flexible devices. 1–3 Over the past few years, rapid progress has been made in this field. Power conversion efficiencies (PCEs) of more than $10\\%$ for traditional single PSCs and $11\\%$ for tandem PSCs have been achieved. 4,5 This trend brightens the application future of PSCs. \n\nAs is well known, the PCE of a PSC is determined by three key factors: its open-circuit voltage $(V_{\\mathrm{oc}})$ , short-circuit current $(J_{\\mathrm{sc}})$ , and fill factor (FF). 6 These parameters are closely related to the optical and electrical properties of the polymers and the blend morphology of the active layer in BHJ PSCs. In particular, $V_{\\mathrm{oc}}$ is directly determined by the energy gap between the highest occupied molecular orbital (HOMO) level of the electron donor (polymer) and the lowest unoccupied molecular orbital (LUMO) level of the acceptor (fullerene derivatives). 7 Hence, the donor–acceptor (D–A) alternating conjugated polymers attract much attention because of their tunable properties, including their optical absorption band, molecular energy level, and carrier mobility. Good photovoltaic performance with PCE over $10\\%$ has been obtained in PSCs based on D–A polymers. 4 \n\nOver the past few years, introducing the fluorine atom to the acceptor unit of D–A conjugated polymer has become a promising method for enhancing the efficiency of PSCs. 8–14 The fluorination can simultaneously lower the LUMO and \n\nHOMO levels of the polymer while incurring only a minor effect on the optical bandgaps. Accordingly, BHJ PSCs based on these fluorinated copolymers exhibit higher $V_{\\mathrm{oc}}$ and PCE than the corresponding non-fluorinated derivatives. However, this method is only used in several limited acceptor units that have suitable positions to attach fluorine atoms. Recently, our group successfully introduced the fluorine atoms to the conjugated side chain of the donor unit—benzodithiophene (BDT)—in D–A polymers. 15 It was found that when two fluorine atoms were introduced onto the conjugated side chains of BDT, the HOMO levels of the corresponding polymers decreased by 0.25 eV; hence, the $V_{\\mathrm{oc}}$ of the PSCs improved by $0.18{\\mathrm{~V}},$ and the $J_{\\mathrm{sc}}$ and FF of the devices also increased to a certain extent. Consequently, the PCE increased by more than $30\\%$ . Therefore, fluorination on the donor unit of the D–A polymer can effectively tune the molecular energy levels of the polymers and improve the photovoltaic performance of the devices. Recently, rapid progresses have been made for conjugated polymer materials with large bandgaps and these polymers showed advantages in fabricating semitransparent $\\mathrm{PSCS^{[16]}}$ (ST-PSCs) and the PCEs of $4-5\\%$ for single junction devices have been achieved. 16b,c Despite that the device performance is usually limited by the low $J_{\\mathrm{sc}}$ due to the narrow absorption spectra of the polymers and thin thickness of active layer, there is still a large room for improving PCE of semitransparent PSCs. From the view of materials design, to tune the molecular energy levels of the polymer should be an effective way to improve the $V_{\\mathrm{oc}}$ and hence PCE of the device. As mentioned above, introducing the BDT unit with fluorine substituent (BDT-F) units to the backbone of large-bandgap polymers may be a good way to improve the photovoltaic performance. \n\nHerein, we synthesized a new copolymer PM6 based on 4,8-bis(5-(2-ethylhexyl)-4-fluorothiophen-2-yl)benzo[1,2-b 4,5- $\\cdot b^{\\prime}]$ - dithiophene (BDT-F) and 1,3-bis(thiophen-2-yl)-5,7-bis(2-ethylhexyl)benzo-[1,2-c 4,5- $c^{\\prime}$ ]dithiophene-4,8-dione (BDD), as shown in Scheme 1a. The optical, electrochemical, and photovoltaic properties, the molecular packing pattern, and the morphology of the blend films were investigated. Compared with the nonfluorinated derivative PBDTBDD in Scheme 1a, PM6 exhibited a similar optical bandgap of $\\approx1.80\\ \\mathrm{eV}$ and a deeper HOMO level of $-5.45\\mathrm{eV}$ $(-5.25\\ \\mathrm{eV}$ for PBDTBDD 17 , which is beneficial for a high $V_{\\mathrm{oc}}$ . BHJ PSCs based on $\\mathbf{PM6}/\\mathrm{PC}_{71}$ BM with both conventional and inverted device structures were fabricated and showed promising photovoltaic performance: a high $V_{\\mathrm{oc}}$ of $0.98{\\mathrm{~V}}$ and a PCE of $8\\%$ for the conventional devices and up to $9.2\\%$ for the inverted devices. Furthermore, the $\\mathbf{PM6}/\\mathrm{PC}_{71}$ BMbased semitransparent device exhibited a PCE of $5.7\\%$ , which is among the highest values obtained for a semitransparent single-junction device. In addition, we found that the neat film of PM6 exhibited strong crystallinity and a dominant face on packing with respect to the electrodes, which is advantageous for charge transport. These results indicate that PM6 is a promising material for photovoltaic application. \n\n![](images/1ed7e6dcd80d7099577fc9497f9924f9f346f1e22cea017a3cd49d2d6faf4d49.jpg) \nScheme 1. a) Molecular structures of PBDTBDD and PM6 and b) synthetic routes for the monomer BDT-F and PM6: (a) 3-bromo-2-(2-ethylhexyl)- thiophene, THF, LDA, $-78^{\\circ}\\mathsf C,$ , 1 h; benzo[1,2-b:4,5-b ]dithiophen-4,8-dione, $50^{\\circ}C$ , $2h$ ; then, $\\mathsf{S n C l}_{2}{\\cdot}2\\mathsf{H}_{2}\\mathsf{O}$ , HCl, $50^{\\circ}C$ , overnight. (b) LDA, $-78^{\\circ}C$ , 1 h; Si $(C H_{3})_{3}C l$ , rt, $2h$ . (c) $n$ -BuLi, THF, $-78{}^{\\circ}\\mathsf{C};$ ${\\mathsf{P h S O}}_{2}{\\mathsf{N F}}$ , rt, overnight. (d) $C F_{3}C O O H/C H C l_{3}$ , room temperature, $5\\textmd{h}$ . (e) LDA, THF, $-78^{\\circ}\\mathsf C,$ $\\rceil\\mathfrak{h}$ ; $\\mathsf{S n}(\\mathsf{C H}_{3})_{3}\\mathsf{C l}$ , room temperature, $2h$ . (f ) Pd $(\\mathsf{P P h}_{3})_{4},$ toluene/DMF, $\\mathsf{l}\\mathsf{l}0^{\\circ}\\mathsf{C}$ . \n\nThe synthetic routes of the monomer (BDT-F) and PM6 are shown in Scheme 1b. The monomer BDT-F was synthesized according to our previously reported procedures. 15 PM6 was synthesized using a Pd-catalyzed Stille-coupling reaction. The polymer exhibits good solubility in chlorinated solvents such as chloroform, chlorobenzene, and $o$ -dichlorobenzene (o-DCB). The number average molecular weight $(M_{\\mathrm{n}})$ and polydispersity index (PDI) of the polymer are $19.3\\mathrm{~K~}$ and 2, respectively, which were estimated using gel-permeation chromatography (GPC) with 1,2,4-tricholorobenzene as the solvent and polystyrene as a standard. \n\nAs shown in Figure 1a, the UV–vis absorption spectra of PM6 in the solution show two distinct absorption bands in the range of $300{-}700~\\mathrm{nm}$ , which is typically observed for D–A copolymers. The absorption maximum of PM6 is located at ${\\approx}550~\\mathrm{nm}$ in the solution. In the solid film, the absorption maximum is redshifted to $570\\ \\mathrm{nm}$ , and a strong shoulder peak at ${\\approx}614~\\mathrm{nm}$ is observed, which should be attributed to the strong aggregation of polymer chains in the solid state. The absorption edge $(\\lambda_{\\mathrm{edge}})$ of the polymer film is at ${\\approx}690~\\mathrm{nm}$ , which corresponds to an optical bandgap $(E_{\\mathrm{g}}^{\\mathrm{\\opt}})$ of $\\approx1.80\\ \\mathrm{eV}.$ Electrochemical cyclic voltammetry (CV) was performed to determine the HOMO level of the polymer. As shown in Figure 1b, the onset oxidation potential $\\left(\\phi_{\\mathrm{ox}}\\right)$ is $0.74\\mathrm{~V~}$ versus $\\mathrm{\\sfAg/Ag^{+}}$ which corresponds to a HOMO level of $-5.45\\ \\mathrm{eV}.$ This \n\n![](images/498b1ccebccfb5463891db2711bffedfdbcb2782dc54751fb5c884d1d0a2f00c.jpg) \nFigure 1. a) Absorption spectra of PM6 in chloroform and film and b) cyclic voltammogram of the polymer film on a platinum electrode, which was measured in $0.1\\ m o l\\ \\mathsf{L}^{-1}$ $B u_{4}N P F_{6}$ acetonitrile solutions at a scan rate of $50\\ m\\vee\\mathsf{s}^{-1}$ . \n\n![](images/f4dd32d802bfb6b95710c2379cbfe13c0c58828113400b79262f5800f560abc8.jpg) \nFigure 2. a) $J{-}V$ characteristics and b) EQE curves of solar cells based on the $\\mathsf{P M}6/\\mathsf{P C}_{71}\\mathsf{B M}$ (1:1.2, $\\mathsf{w}/\\mathsf{w})$ blend with different additive contents. \n\nHOMO level was calculated using the following equation: $\\mathrm{HOMO}=-e(\\phi_{\\mathrm{ox}}+4.71)$ (eV). 18 PM6 exhibits a relatively low LUMO level of $-3.65\\mathrm{~eV},$ which was calculated from the HOMO level and optical bandgap. Compared with the non-fluorinated derivative PBDTBDD, the HOMO level of PM6 decreased by $0.22\\mathrm{eV}$ because two fluorine atoms were introduced at the BDT side chains, which was beneficial for the high $V_{\\mathrm{oc}}$ in polymer solar cells. Moreover, the LUMO and HOMO energy levels of PBDTBDD and PM6 were calculated by density functional theory (DFT) (B3LYP/6-31G (d, p)) as shown in Figure S1 (Supporting Information). The results indicated that attaching fluorine atoms to the BDT side chains could reduce both HOMO and LUMO levels of the polymer simultaneously. \n\nConventional BHJ PSC devices with the configuration of ITO/poly(3,4-ethylenedioxythiophene):polystyrenesulfonic acid (PEDOT:PSS) $\\mathrm{\\primePM6.PC_{71}B M/C a/A l}$ were fabricated with $\\textit{o}$ -DCB as the solvent and were tested under the illumination of AM 1.5G $(100\\mathrm{\\mw\\cm^{-2}},$ ). The $\\mathrm{{D/A}}$ weight ratios $(\\mathbf{PM6}/\\mathrm{PC}_{71}\\mathrm{BM}$ , $\\mathrm{w/w})$ of the blend in the active layer were optimized (Figure S2 and Table S1, Supporting Information). It was found that the optimal $\\mathrm{{D/A}}$ weight ratio of the blend was 1:1.2, and a PCE of $5.3\\%$ was obtained with $V_{\\mathrm{oc}}=1.02\\mathrm{~V},$ $J_{\\mathrm{sc}}=9.3~\\mathrm{mA}~\\mathrm{cm}^{-2}$ and $\\mathrm{FF}=56\\%$ . Figure 2 shows the current-density–voltage $\\left(J-V\\right)$ characteristics and external quantum efficiency (EQE) curves of the solar cells based on the PM6 $/\\mathrm{PC}_{71}\\mathrm{BM}$ (1:1.2, w/w) blend spin-coated without additive and with $1\\%$ , $2\\%$ , and $3\\%$ 1,8-diiodooctane $|{\\mathrm{DIO}}/o$ -DCB, v/v). The photovoltaic parameters of the fabricated devices under optimal conditions are summarized in Table 1 Compared with the devices that were processed without additive, the devices that were processed with DIO showed higher $J_{\\mathrm{sc}}$ and FF; thus, PCE was enhanced, despite a)The average PCE was obtained from more than 20 devices; b)Inverted structure of $170/\\mathsf{P F N/P M6}!\\mathsf{P C}_{71}\\mathsf{B M/M o O}_{3}/\\mathsf{A u}$ $(80\\ \\mathsf{n m})$ ; c)Semitransparent device with the structure of $17{\\mathsf{O}}/{\\mathsf{P F N}}/{\\mathsf{P M}}6!{\\mathsf{P C}}_{71}{\\mathsf{B M}}/{\\mathsf{M o O}}_{3}/{\\mathsf{A u}}$ ( $\\cdot\\mathsf{10}\\mathsf{n m})$ . \n\nTable 1. Photovoltaic properties of the PSCs based on PM6 and $\\mathsf{P C}_{71}\\mathsf{B M}$ $(1{:}1.2,\\mathrm{w/w})$ under the illumination of AM 1.5G, $\\mathsf{l o o m w c m}^{-2}$ . \n\n\n
DIO [v/v%]Voc MJsc [mA cm-2]FF [%]PCEmax (PCEavea)) [%]Thickness [nm]
1.029.3565.3 (5.1)78
0.9811.2738 (7.8)75
1b)0.9812.7749.2 (8.8)75
1°)0.969.4635.7 (5.4)75
0.9810.4707.1 (6.9)75
30.9810.3676.8 (6.6)75
\n\nthe slightly lower $V_{\\mathrm{oc}}.$ The best performance was obtained when $1\\%$ DIO was used, and a maximum $\\mathrm{PCE}=8\\%$ was found with $V_{\\mathrm{oc}}=0.98\\:\\mathrm{V},$ $J_{\\mathrm{sc}}=11.2~\\mathrm{mA}~\\mathrm{cm}^{-2}$ , and $\\mathrm{FF}=73\\%$ . As shown in Figure 2b, EQE was obviously enhanced for the solar cells that were fabricated with DIO as the additive. When $1\\%$ DIO was added, the quantum efficiency of the device significantly increased in the wavelength range of $350{\\mathrm{-}}650\\ \\mathrm{nm}$ , and a maximum EQE of $74\\%$ at $510~\\mathrm{nm}$ was recorded. The integrated $J_{\\mathrm{sc}}$ values from the EQE curves are consistent with the observed $J_{\\mathrm{sc}}$ values in the $J{-}V$ measurement, and the deviation is within $5\\%$ . To further improve the photovoltaic performance, an inverted device with the structure of ITO/poly [(9,9-bis( $3^{\\prime}$ - (N N-dimethylamino)propyl)-2,7-fluorene)-alt-2,7-(9,9-dioctylfluorene) (PFN) $/\\mathrm{PM6.PC_{71}B M/M o O_{3}/A u}$ was fabricated. Compared with the conventional device, the inverted device exhibited higher $J_{\\mathrm{sc}}$ of $12.7~\\mathrm{mA~cm}^{-2}$ , which resulted from the better charge collection and transmission of PFN than PEDOT:PSS. 19 Consequently, the high PCE of $9.2\\%$ was achieved for the inverted devices. \n\nSemitransparent solar cells have great potential to be used in many photovoltaic applications, such as building-integrated photovoltaics and solar windows. 16 Considering the PM6/ $\\mathrm{PC}_{71}\\mathrm{BM}$ -based device performed well when the thin film was only ${\\approx}75~\\mathrm{nm}$ , it would be a potential material for semitransparent PSC application. Therefore, the ST-PSCs were fabricated with the structure of $\\mathrm{ITO/PFN/PM6.PC_{71}B M/M o O_{3}/A u}$ $(10\\ \\mathrm{nm})$ ). Figure 3 shows the transmission spectrum and $J{-}V$ curves of the semitransparent PSC. The average light transmission in the visible range of $380{-}780~\\mathrm{nm}$ reaches ${\\approx}67\\%$ , and the maximum approaches $100\\%$ at the wavelength of $701~\\mathrm{nm}$ In the photograph of the device, the flowers and leaves are clearly observed. The device also exhibited a PCE of $5.7\\%$ with $V_{\\mathrm{oc}}=\\$ $0.96\\mathrm{~V},J_{\\mathrm{sc}}=9.4\\mathrm{~mA~cm^{-2}}$ , and $F F=63\\%$ under the illumination of AM 1.5G, $100\\mathrm{\\mA\\cm^{-2}}$ , which is among the highest values for single-junction ST-PSCs. These results indicate that PM6 is a promising material for versatile photovoltaic applications. \n\nGrazing-incidence X-ray diffraction (GIXD) and resonant soft X-ray scattering (RSoXS) were used to investigate the effect of the additive on the morphology of the blend films. Figure 4a shows the in-plane (IP) and out-of-plane (OOP) GIXD profiles of the samples, including the thin films of the pure PM6 film and $\\mathbf{PM6}{:}\\mathrm{PC}_{71}\\mathrm{BM}$ blend (1:1, w/w) films, which were cast from $\\mathbf{\\xi}_{o}$ -DCB without or with DIO as a processing additive. For the neat polymer film, the OOP profile shows pronounced (100) diffraction peaks at $0.31\\mathring{\\mathrm{A}}^{-1}$ with a $d$ -spacing of $20.3\\mathring\\mathrm{A}$ , whereas the IP profile also exhibits strong (100) and weak (200) diffraction peaks at 0.31 and $0.62\\mathring\\mathrm{~A}^{-1}$ respectively. In addition, the OOP profile shows one sharp and intensive peak at $1.66\\mathring{\\mathrm{~A~}}^{-1}$ which corresponds to the (010) $\\pi{-}\\pi$ stacking with a $d$ -spacing of ${\\approx}3.78$ Å. This result implies that the neat polymer film exhibits a face-on dominated molecular orientation with respect to the substrate. When blended with $\\mathrm{PC}_{71}\\mathrm{BM}$ , the IP (100) peak was distinctly weakened, whereas the OOP (100) peak hardly changed. Meanwhile, the $\\pi{-}\\pi$ stacking of the polymer in the blend films was completely disrupted. The broad peak at $q\\approx1.4\\mathring\\mathrm{A}^{-1}$ is attributed to $\\mathrm{PC}_{71}\\mathrm{BM}$ aggregation. When DIO was used as an additive, the lamellar diffraction and $\\pi{-}\\pi$ stacking diffraction significantly increased; with an increasing amount of DIO, the lamellar stacking continued increasing, and the $\\pi{-}\\pi$ stacking remained almost unchanged. We also calculated the coherence length $(L_{100})$ , which was deduced from the full width at half maximum (FWHM) of IP (100) peaks using Sherrer equation. 20 The values of 1.1, 1.4, and $2.2\\ \\mathrm{nm}$ for $1\\%$ , $2\\%$ , and $3\\%$ DIO were obtained, which are substantially increased with increasing DIO contents from $1\\%$ to $3\\%$ . Hence, with DIO as an additive, the overall crystallinity of the polymer was enhanced. \n\n![](images/d4b06516249ee3ae924f648a756d5a345b111e47527d2353b9337cbaf036bbcb.jpg) \nFigure 3. a) Transmission spectrum and photograph of the semitransparent device and b) current-density–voltage characterization of the semitransparent polymer solar cell with the device structure of ${\\mathsf{I T O}}/$ $\\mathsf{P F N/P M6.P C_{71}B M/M o O_{3}/A u}$ . \n\nThe phase-separated morphologies of the blends prepared using different conditions were further investigated using RSoXS. 21,22 A photon energy of $284.2\\ \\mathrm{eV}$ was selected to provide high polymer/fullerene contrast while avoiding the high absorption associated with the carbon 1s core level, which would produce background fluorescence and could lead to radiation damage. 23 Figure 4b shows the RSoXS profiles of the polymer: $\\mathrm{PC}_{71}\\mathrm{BM}$ (1:1.2, w/w) blend films that were cast from the $\\mathbf{\\xi}_{o}$ -DCB without or with DIO as a processing additive. The scattering profiles represent the distribution function of spatial frequency s $\\mathbf{\\xi}(s=q/2\\pi)$ of the samples and are dominated by lognormal distributions, which can be fitted by a set of Gaussians in the lin-log space. The distribution median $s_{\\mathrm{median}}$ corresponds to the characteristic median length scale $\\xi$ of the corresponding log-normal distribution in real space with $\\xi=1/s_{\\mathrm{median}}$ which is a model-independent statistical quantity. When the blend films were processed with pure $\\textit{o}$ -DCB, the profile showed a low scattering intensity with $\\xi$ of ${\\approx}20~\\mathrm{nm}$ , which indicates that the phase separation is weak and resulted in notably impure domains. When DIO was used as the additive, the scattering profile showed a much higher intensity and two log-normal distributions (Figure S3, Supporting Information). At high $\\boldsymbol{q}$ the value of $\\xi$ is located at ${\\approx}20~\\mathrm{nm}$ irrespective of processing, but at low $q,\\xi$ increases with the increase in DIO concentration. The corresponding $\\xi$ increases, i.e., 40, 45, and $63~\\mathrm{nm}$ for $1\\%$ , $2\\%$ , and $3\\%$ DIO, respectively. It is evident that the films that were cast with DIO as the additive show hierarchical or a twolength-scale structure and exhibit phase separation at a small length scale that is similar to that of the blend film that was processed using pure $o$ -DCB. It is reported that the hierarchical structure is a favorable morphology to improve the device performance. 24,25 Similarly, sufficient aggregation of the polymer and fullerene has to be present. Here, the improved performance is consistent with this paradigm and occurs due to the creation of more pure domain that provide better charge transport and reduced recombination. As the domains get too large, exciton harvesting suffers. \n\n![](images/39cfa118002558182e5cf4b8229c4230a36c496f90c4486a092de8d3bf9885ee.jpg) \nFigure 4. a) GIXD profiles for the pure film of PM6 and blend films of $\\mathsf{P M}6{:}\\mathsf{P C}_{71}\\mathsf{B M}$ (1:1.2, w/w) with different amounts of DIO and b) RSoXS profiles for the blend films of $\\mathsf{P M}6{:}\\mathsf{P C}_{71}\\mathsf{B M}$ (1:1.2, $\\upnu/\\upnu)$ with different amounts of DIO. \n\n![](images/3e7a85eb1a0045e319a2bacd9b72bb4738560594ebf9bdf53db4f15edff4ac0c.jpg) \nFigure 5. TEM images of $\\mathsf{P M}6{:}\\mathsf{P C}_{71}\\mathsf{B M}$ blend films: a) without DIO; b) with $1\\%$ DIO; c) with $2\\%$ DIO; and d) with $3\\%$ DIO. \n\nFurthermore, the surface and bulk of the blend films were also studied using atomic force microscopy (AFM) and transmission electron microscopy (TEM). As shown in Figure S4 (Supporting Information), the root-mean-square (RMS) values are 0.61, 1.63, 2.03, and $2.27\\ \\mathrm{nm}$ for the blends processed without additive and with $1\\%$ DIO, $2\\%$ DIO, and $3\\%$ DIO, respectively. However, increasing the amount of DIO results in an enhanced phase separation, which should be caused by the enhanced polymer crystallinity. As shown in Figure 5 the blend film that was processed using only $\\textit{o}$ -DCB shows a poor phase separation. When $1\\%$ DIO was added as the additive, a fibrillar network was clearly observed. When more DIO was added, the phase separation became much stronger, and the mesh size between the fibrils became larger. As previously mentioned, the AFM and TEM results are consistent with the GIXD and RSoXS measurements. \n\nIn summary, a new copolymer based on BDT-F as the donor and BDD as the acceptor, which is named PM6 was designed and synthesized for photovoltaic applications. The polymer exhibited a large bandgap of $1.80\\mathrm{eV}$ and a deep HOMO energy level of $-5.45\\ \\mathrm{eV}.$ The PM6-based inverted PSCs showed high PCE of $9.2\\%$ and $V_{\\mathrm{oc}}$ of $0.98{\\mathrm{~V~}}$ with a relatively thin film thickness of $75\\ \\mathrm{nm}$ , which is beneficial for tandem PSCs. Furthermore, the PM6-based semitransparent device exhibited a high average transmission of $67\\%$ in the visible range and a PCE of $5.6\\%$ , which is among the high values for single-junction semitransparent PSCs. These results indicate that PM6 is a versatile material for opaque or semitransparent single-junction PSCs and tandem PSCs. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThe authors would like to acknowledge the financial support from the Natural Science Foundation of China (Nos. 20874106, 21325419, 51203168, 51422306, and 91333204). The X-ray characterization by M.W. and H.A. was supported by the U.S. Department of Energy, Office of Science, Basic Energy Science, Division of Materials Science and Engineering under Contract No. DE-FG02-98ER45737. The X-ray data were acquired at beamlines $\\rceil1.0.1.2^{[26]}$ and $7.3.3[27]$ at the Advanced Light Source, which was supported by the Director, Office of Science, Office of Basic Energy Sciences of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. \n\nReceived: May 2, 2015 \nRevised: June 10, 2015 \nPublished online: July 14, 2015 \n\nZ. Hong, Y. Yang, Adv. Mater. 2014, 26, 5670; c) Z. Zheng, S. Zhang, M. Zhang, K. Zhao, L. Ye, Y. Chen, B. Yang, J. Hou, Adv. Mater. 2015, 27, 1189; d) J. H. Kim, J. B. Park, F. Xu, D. Kim, J. Kwak, A. C. Grimsdale, D. H. Hwang, Energy Environ. Sci. 2014, 7, 4118. \n[6] a) P. M. Beaujuge, J. M. J. Fréchet, J. Am. Chem. Soc. 2011, 133, 20009; b) M. J. Zhang, X. Guo, Y. F. Li, Adv. Energy Mater. 2011, 1, 557; c) X. Guo, C. H. Cui, M. J. Zhang, L. J. Huo, Y. Huang, J. H. Hou, Y. Li, Energy Environ. Sci. 2012, 5, 7943; d) Z. B. Henson, K. Müllen, G. C. Bazan, Nat. Chem. 2012, 4, 699; e) R. A. Janssen, J. Nelson, Adv. Mater. 2013, 25, 1847. \n[7] a) P. W. M. Blom, V. D. Mihailetchi, L. J. A. Koster, D. E. Markov, Adv. Mater. 2007, 19, 1551; b) C. J. Brabec, S. Gowrisanker, J. J. M. Halls, D. Laird, S. J. Jia, S. P. Williams, Adv. Mater. 2010, 22, 3839. \n[8] a) Y. Y. Liang, D. Q. Feng, Y. Wu, S. T. Tsai, G. Li, C. Ray, L. P. Yu, J. Am. Chem. Soc. 2009, 131, 7792; b) H. J. Son, W. Wang, T. Xu, Y. Y. Liang, Y. E. Wu, G. Li, L. P. Yu, J. Am. Chem. Soc. 2011, 133, 1885. \n[9] a) Z. Li, J. P. Lu, S. C. Tse, J. Y. Zhou, X. M. Du, Y. Tao, J. F. Ding, J. Mater. Chem. 2011, 21, 3226; b) S. C. Price, A. C. Stuart, L. Q. Yang, H. X. Zhou, W. You, J. Am. Chem. Soc. 2011, 133, 4625; c) Y. Zhang, S. C. Chien, K. S. Chen, H. L. Yip, Y. Sun, J. A. Davies, F. C. Chen, A. K. Y. Jen, Chem. Commun. 2011, 47, 11026; d) H. X. Zhou, L. Q. Yang, A. C. Stuart, S. C. Price, S. B. Liu, W. You, Angew. Chem. Int. Ed. 2011, 50, 2995; e) H. C. Chen, Y. H. Chen, C. C. Liu, Y. C. Chien, S. W. Chou, P. T. Chou, Chem. Mater. 2012, 24, 4766. \n[10] a) J. F. Jheng, Y. Y. Lai, J. S. Wu, Y. H. Chao, C. L. Wang, C. S. Hsu, Adv. Mater. 2013, 25, 2445; b) A. Stuart, . R. Tumbleston, H. X. Zhou, W. Liu H. Ade, W. You, J. Am. Chem. Soc. 2013, 135, 1806; Yang, R. Tumbleston, H. X. Zhou, H. Ade, W. You, Energy Environ Sci. 2013, 6, 316. \n[11] a) S. Albrecht, Janietz, W. Schindler, J. Frisch, J. Kurpiers, J. Kniepert, S. Inal, P. Pingel, K. Fostiropoulos, N. Koch, D. Neher, J. Am. Chem. Soc. 2012, 134, 14932; b) Y. Zhang, J. Y. Zou, C. C. Cheuh, H. L. Yip, A. K. Y. Jen, Macromolecules 2012, 45, 5427; c) H. Bronstein, J. M. Frost, A. Hadipour, Y. Kim, C. B. Nielsen, R. S. Ashraf, B. P. Rand, S. Watkins, I. McCulloch, Chem. Mater. 2013, 25, 277. \n[12] a) J. W. Jo, J. W. Jung, H.-W. Wang, P. Kim, T. P. Russell, W. H. Jo, Chem. Mater. 2014, 26, 4214; b) Q. Peng, X. J. Liu, D. Su, G. W. Fu, J. Xu, L. M. Dai, Adv. Mater. 2011, 23, 4554; c) Y. C. Yang, R. M. Wu, X. Wang, X. P. Xu, Z. J. Li, K. Li, Q. Peng, Chem. Commun. 2014, 50, 439; d) K. Li, Z. J. Li, K. Feng, X. P. Xu, L. Y. Wang, Q. Peng, J. Am. Chem. Soc. 2013, 135, 13549. \n[13] a) W. Li, S. Albrecht, L. Yang, S. Roland, J. R. Tumbleston, T. McAfee, L. Yan, M. A. Kelly, H. Ade, D. Neher, W. You, J. Am. Chem. Soc. 2014, 136, 15566; b) W. Li, L. Yang, J. R. Tumbleston, L. Yan, H. Ade, W. You, Adv. Mater. 2014, 26, 4456. \n[14] a) P. Liu, K. Zhang, F. Liu, Y. Jin, S. Liu, T. P. Russell, H.-L. Yip, F. Huang, Y. Cao, Chem. Mater. 2014, 26, 3009; b) T. L. Nguyen, H. Choi, S. J. Ko, M. A. Uddin, B. Walker, S. Yum, J. E. Jeong, M. H. Yun, T. J. Shin, S. Hwang, J. Y. Kim, H. Y. Woo, Energy Environ. Sci. 2014, 7, 3040. \n[15] M. J. Zhang, X. Guo, S. Q. Zhang, J. H. Hou, Adv. Mater. 2014, 26, 1118. \n[16] a) K.-S. Chen, J.-F. Salinas, H.-L. Yip, L. Huo, J. Hou, A. K. Y. Jen, Energy Environ. Sci. 2012, 5, 9551; b) Z. M. Beiley, M. G. Christoforo, P. Gratia, A. R. Bowring, P. Eberspacher, G. Y. Margulis, C. Cabanetos, P. M. Beaujuge, A. Salleo, M. D. McGehee, Adv. Mater. 2013, 25, 7020; c) C.-Y. Chang, L. Zuo, H.-L. Yip, Y. Li, C.-Z. Li, C.-S. Hsu, Y.-J. Cheng, H. Chen, A. K. Y. Jen, Adv. Funct. Mater. 2013, 23, 5084; d) C.-Y. Chang, L. Zuo, H.-L. Yip, C.-Z. Li, Y. Li, C.-S. Hsu, Y.-J. Cheng, H. Chen, A. K. Y. Jen, Adv. Energy Mater. 2014, 4, 1301645; e)A. R. B. M. Yusoff, S. J. Lee, F. K. Shneider, W. J. da Silva, J. Jang, Adv. Energy Mater. 2014, 4, 1301989. \n[17] D. P. Qian, L. Ye, M. J. Zhang, Y. R. Liang, L. J. Li, Y. Huang, X. Guo, S. Q. Zhang, Z. A. Tan, J. H. Hou, Macromolecules 2012, 45, 9611. \n[18] a) M. J. Zhang, H. J Fan, X. Guo, Y. J. He, Z. G. Zhang, J. Min, J. Zhang, G. J. Zhao, X. W. Zhan, Y. F. Li, Macromolecules 2010, 43, 5706; b) X. Guo, M. J. Zhang, J. H. Tan, S. Q. Zhang, L. J. Huo, W. P. Hu, Y. F. Li, J. H. Hou, Adv. Mater. 2012, 24, 6536. \n[19] a) Z. C. He, C. M. Zhong, X. Huang, W. Y. Wong, H. B. Wu, L. W. Chen, S. J. Su, Y. Cao, Adv. Mater. 2011, 23, 4636; b) Z. C. He, C. M. Zhong, S. J. Su, M. Xu, H. B. Wu, Y. Cao, Nat. Photonics 2012, 6, 591; c) X. Hu, C. Yi, M. Wang, C.-H. Hsu, S. Liu, K. Zhang, C. Zhong, F. Huang, X. Gong, Y. Cao, Adv. Energy Mater. 2014, 4, 1400378. \n[20] S.-J. Ko, W. Lee, H. Choi, B. Walker, S. Yum, S. Kim, T. J. Shin, H. Y. Woo, J. Y. Kim, Adv. Energy Mater. 2015, DOI:10.1002/ aenm.201401687. \n[21] a) M. J. Zhang, Y. Gu, X. Guo, F. Liu, S. Q. Zhang, L. J. Huo, T. P. Russell, J. H. Hou, Adv. Mater. 2013, 25, 4944; b) X. Guo, M. J. Zhang, W. Ma, L. Ye, S. Q. Zhang, S. J. Liu, H. Ade, F. Huang, J. H. Hou, Adv. Mater. 2014, 26, 4043; c) W. Ma, J. R. Tumbleston, L. Ye, C. Wang, J. H. Hou, H. Ade, Adv. Mater. 2014, 26, 4234; d) M. J. Zhang, X. Guo, W. Ma, H. Ade, J. H. Hou, Adv. Mater. 2014, 26, 5880. \n[22] a) S. Swaraj, C. Wang, H. P. Yan, B. Watts, L. N. Jan, C. R. McNeill, H. Ade, Nano Lett. 2010, 10, 2863; b) J. R. Tumbleston, B. A. Collins, L. Q. Yang, A. C. Stuart, E. Gann, W. Ma, W. You, H. Ade, Nat. Photonics 2014, 8, 385; c) B. A. Collins, J. E. Cochran, H. Yan, E. Gann, C. Hub, R. Fink, C. Wang, T. Schuettfort, C. R. McNeill, M. L. Chabinyc, H. Ade, Nat. Mater. 2012, 11, 536; d) L. Ye, S. Q. Zhang, W. Ma, B. H. Fan, X. Guo, Y. Huang, H. Ade, J. H. Hou, Adv. Mater. 2012, 24, 6335. \n[23] T. Coffey, S. G. Urquhart, H. Ade, J. Electron Spectrosc. 2002, 122, 65. \n[24] a) B. A. Collins, Z. Li, J. R. Tumbleston, E. Gann, C. R. McNeill, H. Ade, Adv. Energy Mater. 2013, 3, 65; b) J. J. van Franeker, M. Turbiez, W. Li, M. M. Wienk, R. A. Janssen, Nat. Commun. 2015, 6, 6229. \n[25] a) W. Chen, T. Xu, F. He, W. Wang, C. Wang, J. Strzalka, Y. Liu, J. G. Wen, D. J. Miller, J. H. Chen, K. L. Hong, L. P. Yu, S. B. Darling, Nano Lett. 2011, 11, 3707; b) H. Y. Lu, B. Akgun, T. P. Russell, Adv. Energy Mater. 2011, 1, 870; c) Y. Gu, C. Wang, T. P. Russell, Adv. Energy Mater. 2012, 2, 683; d) F. Liu, Y. Gu, C. Wang, W. Zhao, D. Chen, A. L. Briseno, T. P. Russell, Adv. Mater. 2012, 24, 3947; e) M. J. Zhang, X. Guo, W. Ma, S. Q. Zhang, L. J. Huo, H. Ade, J. H. Hou, Adv. Mater. 2014, 26, 2089. \n[26] E. Gann, A. T. Young, B. A. Collins, H. Yan, J. Nasiatka, H. A. Padmore, H. Ade, A. Hexemer, C. Wang, Rev. Sci. Instrum. 2012, 83, 045110. \n[27] A. Hexemer, W. Bras, J. Glossinger, E. Schaible, E. Gann, R. Kirian, A. MacDowell, M. Church, B. Rude, H. Padmore, J. Phys. Conf. Ser. 2010, 247, 012007. " + }, + { + "id": "10.1002_anie.201409524", + "DOI": "10.1002/anie.201409524", + "DOI Link": "http://dx.doi.org/10.1002/anie.201409524", + "Relative Dir Path": "mds/10.1002_anie.201409524", + "Article Title": "Enhanced Electron Penetration through an Ultrathin Graphene Layer for Highly Efficient Catalysis of the Hydrogen Evolution Reaction", + "Authors": "Deng, J; Ren, PJ; Deng, DH; Bao, XH", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "Major challenges encountered when trying to replace precious-metal-based electrocatalysts of the hydrogen evolution reaction (HER) in acidic media are related to the low efficiency and stability of non-precious-metal compounds. Therefore, new concepts and strategies have to be devised to develop electrocatalysts that are based on earth-abundant materials. Herein, we report a hierarchical architecture that consists of ultrathin graphene shells (only 1-3 layers) that encapsulate a uniform CoNi nulloalloy to enhance its HER performance in acidic media. The optimized catalyst exhibits high stability and activity with an onset overpotential of almost zero versus the reversible hydrogen electrode (RHE) and an overpotential of only 142 mV at 10 mAcm(-2), which is quite close to that of commercial 40% Pt/C catalysts. Density functional theory (DFT) calculations indicate that the ultrathin graphene shells strongly promote electron penetration from the CoNi nulloalloy to the graphene surface. With nitrogen dopants, they synergistically increase the electron density on the graphene surface, which results in superior HER activity on the graphene shells.", + "Times Cited, WoS Core": 1160, + "Times Cited, All Databases": 1202, + "Publication Year": 2015, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000349391000013", + "Markdown": "# Enhanced Electron Penetration through an Ultrathin Graphene Layer for Highly Efficient Catalysis of the Hydrogen Evolution Reaction\\*\\* \n\nJiao Deng, Pengju Ren, Dehui Deng,\\* and Xinhe Bao\\* \n\nAbstract: Major challenges encountered when trying to replace precious-metal-based electrocatalysts of the hydrogen evolution reaction (HER) in acidic media are related to the low efficiency and stability of non-precious-metal compounds. Therefore, new concepts and strategies have to be devised to develop electrocatalysts that are based on earth-abundant materials. Herein, we report a hierarchical architecture that consists of ultrathin graphene shells (only 1–3 layers) that encapsulate a uniform CoNi nanoalloy to enhance its HER performance in acidic media. The optimized catalyst exhibits high stability and activity with an onset overpotential of almost zero versus the reversible hydrogen electrode (RHE) and an overpotential of only $I42m V$ at $I O m A c m^{-2}$ , which is quite close to that of commercial $40\\%$ Pt/C catalysts. Density functional theory $(D F T)$ calculations indicate that the ultrathin graphene shells strongly promote electron penetration from the CoNi nanoalloy to the graphene surface. With nitrogen dopants, they synergistically increase the electron density on the graphene surface, which results in superior HER activity on the graphene shells. \n\nHydrogen, a renewable and clean fuel, is considered as a potential energy carrier for future energy infrastructure.[1,2] The electrocatalytic splitting of water by the hydrogen evolution reaction (HER) is an important process with high energy conversion efficiency for hydrogen production.[3] Currently, the state-of-the-art catalysts are based on precious metals, such as platinum,[4–6] but their limited Earth resource and high cost hinder the commercial application of this technology. Compounds such as $\\mathbf{MoS}_{2}$ ,[7–12] $\\mathbf{Mo}_{2}\\mathbf{C},$ [13] MoB,[13] MoP,[14] $\\mathbf{MoSe}_{2}$ ,[15] $\\mathbf{WS}_{2}$ ,[16] and 3d transition metals (TMs),[17–19] have been studied as potential substitutes for Pt-based catalysts for a long time. Recently, 3d TMs such as Fe, Co, Ni, and their derivatives have received increasing attention as potential replacements of Pt-based catalysts owing to their earth abundance and low cost,[20–22] but these metals readily suffer from corrosion in acidic solid polymer electrolytes. \n\nTo this end, we have previously proposed a strategy to encapsulate 3d TMs into carbon nanotubes, which can efficiently prevent the corrosion of 3d TMs in acidic medium and simultaneously promote the catalytic reaction on the carbon surface owing to electron penetration from the encapsulated 3d TMs.[23] This strategy represents a new concept for maintaining the high activity and stability of non-precious metals in acidic medium and has recently been further applied in a variety of catalytic systems, for example, for the oxygen reduction reaction (ORR),[23–26] the HER under acidic conditions,[27,28] the triiodide reduction reaction in dye-sensitized solar cells (DSSCs),[29] and the heterogeneously catalyzed oxidation and reduction reactions.[30,31] However, the carbon shells previously used for these catalysts are too thick and usually consist of multilayer graphitic carbon or composites thereof, which may significantly reduce the catalytic activity as the electronic structure of the outermost carbon layer is only modulated by the electron transferred from the encapsulated metal core when the shell consist of no more than three to four carbon layers.[32,33] Therefore, the synthesis of carbon-encapsulated 3d TM catalysts with a controllable number of graphene layers, especially of catalysts with less than three layers of graphene, will be important for the development of 3d TM catalysts with superior HER activity. Herein, we report a bottom-up method for the preparation of ultrathin graphene spheres with only one to three graphene layers that encapsulate CoNi nanoalloy $(\\mathrm{CoNi@NC})$ electrocatalysts by using $\\mathrm{Co}^{2+}$ , $\\mathbf{Ni}^{2+}$ , and ethylenediaminetetraacetate anions $\\mathrm{(EDTA^{4-})}$ as precursors (see the Supporting Information, Figure S1 for details). \n\nScanning electron microscopy (SEM; Figure 1 b, Figure S3) and transmission electron microscopy (TEM; Figure 1 c, Figure S4) images show that the $\\mathrm{CoNi@NC}$ samples consist of uniform nanospheres, forming lamellar superstructures on the micrometer scale (Figure 1a). Further highresolution (HR) TEM analysis indicates that the nanospheres consist of metal nanoparticles (NPs) that are completely coated by graphene shells (Figure 1 d, Figure S4–7). The metal NPs have a uniform size of generally $4{\\mathrm{-}}7{\\mathrm{nm}}$ (see the statistical analysis in Figure 1 c, inset) with a $d$ -spacing of $0.215\\mathrm{nm}$ , which corresponds to the (111) plane of the CoNi alloy (Figure 1e). According to the statistical analysis by \n\nsamples (Figure 2 d). Furthermore, the broad peaks of the CoNi alloy in the XRD pattern confirm that the metals are present as nanosized particles, which is consistent with the TEM statistical analysis (Figure 1 c). The very weak and broad C (002) peaks also confirm that ultrathin graphene shells have been formed, which is in agreement with the statistical analysis of the number of layers by HRTEM (Figure 1 g). These results indicate that uniform CoNi nanoalloys have been completely encapsulated in ultrathin graphene shells. \n\n![](images/b387e6ca652c7a4dce384fcc68a99eb86436eb4a59b74c9a37bfe2a123ca5e2a.jpg) \nFigure 1. a, b) SEM images of CoNi@NC. The magnified image in (b) clearly reveals the uniformly sized nanospheres. c) TEM image of CoNi@NC showing a similar structure as (b). Inset: particle size distribution of the metal nanoparticles. d, e) HRTEM images of CoNi@NC, showing the graphene shells and encapsulated metal nanoparticles. Inset (e): crystal (111) plane of the CoNi alloy. f) Schematic illustration of the ${\\mathsf{C o N i@N C}}$ structure shown in (e). g) Statistical analysis of the number of layers in the graphene shells encapsulating the metal nanoparticles in CoNi@NC. h–k) HAADF–STEM image and corresponding EDX maps of CoNi@NC for Co (i), Ni (j), and combined image (k). \n\nA typical three-electrode setup was adopted to evaluate the HER performance of the $\\mathrm{CoNi@NC}$ samples in $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte (0.1m). As shown in Figure 3 a, a blank glassy carbon (GC) electrode, the EDTA–CoNi complex, and pristine carbon nanotubes (CNTs) showed negligible or poor HER activities. In contrast, all $\\mathrm{CoNi@NC}$ catalysts prepared at different annealing temperatures exhibited a higher HER activity. The $\\mathrm{CoNi@NC}$ sample prepared at $475^{\\circ}\\mathrm{C}$ gave the highest activity, with an onset overpotential of only approxi \n\nHRTEM (Figure $\\mathrm{~1~g~}{\\bf\\dot{\\sigma}},$ ), the graphene shells on the CoNi NPs are very thin (only 1–3 layers), and most of the graphene shells $(>90\\%)$ consist of only one to two layers. A high-angle annular dark-field scanning transmission electron microscopy (HAADF–STEM) image with sub-\u0002ngstrçm resolution further confirmed that uniform metal NPs had been formed (Figure $\\mathrm{1h}$ ), and the corresponding energy-dispersive $\\mathbf{\\boldsymbol{X}}$ -ray (EDX) maps showed that the Co and Ni atoms were distributed homogeneously over all NPs (Figure 1i–k), further confirming the alloy structure of CoNi. \n\nSynchrotron-based $\\mathbf{\\boldsymbol{X}}$ -ray absorption near-edge structure (XANES) analysis, X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD) were used to investigate the electronic and structural properties of ${\\mathrm{CoNi@NC}}$ . The XANES spectra of the Co K-edge and the Ni K-edge indicated that Co and Ni are in a metallic state in all $\\mathrm{CoNi@NC}$ samples independent of the annealing temperature (Figure 2 a,b), which is consistent with the $\\mathrm{Co}2\\mathrm{p}$ and Ni 2p XPS spectral analysis (Figure 2 c). The XRD spectra showed that except for the graphitic carbon shell and the CoNi alloy, no other phases are present in the CoNi@NC mately $30\\mathrm{mV}$ and an overpotential of $224\\mathrm{mV}$ at a current density of $10\\mathrm{mAcm}^{-2}$ . Furthermore, the $\\mathrm{CoNi@NC}$ samples prepared at different temperatures exhibited a fairly stable performance within accelerated degradation measurements for 1000 cyclic voltammetry (CV) cycles (Figure 3 c) or during a galvanostatic measurement at a current density of $20\\mathrm{mAcm}^{-2}$ for 24 hours (Figure S10). The structures of the carbon shells encapsulating the metal nanoparticles were well maintained after the HER durability measurements, as confirmed by HRTEM (Figure S11) and Raman analysis (Figure S12). \n\nAccording to previous studies, the introduction of nitrogen into carbon materials or metal/carbon composites may have an important effect on the catalytic activity.[23,29,34] Raman analysis firstly excluded the influence of graphitization on the HER activity (Figure S9). Further chemical composition analysis showed that the nitrogen concentration (N/C) decreased gradually with an increase in annealing temperature (Figure 3b, Table S1), and the corresponding HER activity increased with an increase in nitrogen content. However, the $\\mathrm{CoNi@NC}$ sample prepared at $425^{\\circ}\\mathrm{C}$ showed a slightly lower activity than that prepared at $475^{\\circ}\\mathrm{C}$ even though the former had a higher nitrogen content. We hypothesize that the distinctively smaller metal content of the sample prepared at $425^{\\circ}\\mathrm{C}$ compared with the sample prepared at $475^{\\circ}\\mathrm{C}$ (Table S1) may offset the contribution of the nitrogen dopants to the catalytic activity, leading to a higher HER activity for the sample prepared at $475^{\\circ}\\mathrm{C}$ . \n\n![](images/bfbd857e878ade8ba1143f79d40b7e9206aa7f40249cdff6b604c1d205a22d3c.jpg) \nFigure 2. a, b) Co K-edge and Ni K-edge XANES spectra of ${\\mathsf{C o N i@N C}}$ samples. Insets: Corresponding XANES spectra of ${\\mathsf{C o N i@N C}}$ samples prepared at different annealing temperatures. c) $\\mathtt{C o2p}$ and Ni $2{\\mathsf{p}}$ XPS spectra of these CoNi@NC samples. d) XRD patterns of these ${\\mathsf{C o N i@N C}}$ samples. \n\n![](images/09f79193a6e414480e4f1b2c4d641057b0adeb399588ee89a05c0f49a0b99c54.jpg) \nFigure 3. a) HER polarization curves for ${\\mathsf{C o N i@N C}}$ samples prepared at different temperatures as well as for a ${\\mathsf{C o N i@N C}}$ sample prepared at $475^{\\circ}\\mathsf{C}$ with a catalyst mass loading of five equivalents on GC electrode compared to those of EDTA–CoNi, CNTs, $40\\%\\mathsf{P t/C}$ , and a blank GC electrode. b) Current densities at overpotentials of $\\boldsymbol{100}\\boldsymbol{\\mathrm{mV}}$ and $200~\\mathrm{mV}$ and the nitrogen concentration (N/C) as a function of the annealing temperature employed to synthesize the ${\\mathsf{C o N i@N C}}$ sample. c) Durability measurements with ${\\mathsf{C o N i@N C}}$ prepared at $475^{\\circ}\\mathsf C$ and $525^{\\circ}\\mathsf{C}$ . Polarization curves were recorded before the first and after $\\mathsf{1000}\\mathsf{C V}$ sweeps between $-142\\mathsf{m V}$ and $+708{\\mathrm{~mV}}$ (vs. RHE) at $\\mathsf{l}00\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . d) Tafel plots for ${\\mathsf{C o N i@N C}}$ samples prepared at $475^{\\circ}\\mathsf{C}$ and $525^{\\circ}\\mathsf{C}$ as well as for $40\\%$ Pt/C and the CoN $@N C$ sample prepared at $475^{\\circ}\\mathsf C$ with a catalyst mass loading of five equivalents on GC electrode. \n\nWhen the mass loading of catalyst on GC electrode was further increased to 5 wt equivalents, the HER activity of the $\\mathrm{CoNi@NC}$ catalyst obtained at $475^{\\circ}\\mathrm{C}$ was further enhanced with an onset overpotential of almost zero (ca. $\\mathrm{0\\mV}$ vs. the reversible hydrogen electrode (RHE)) and an overpotential of only $142\\mathrm{mV}$ at a current density of $10\\mathrm{mAcm}^{-2}$ (Figure 3 a). To the best of our knowledge, this compound is the most efficient carbon-based HER electrocatalyst in acidic medium reported thus far (see Table S2). \n\nTafel slopes can be used to reveal the inherent reaction processes of the HER.[5,35] For the $40\\%$ $\\mathrm{Pt/C}$ electrocatalyst used in this study, a value of $30\\mathrm{mV}\\mathrm{dec}^{-1}$ was determined, which is consistent with previously reported results.[5] In contrast, values of $107\\mathrm{mVdec}^{-1}$ and $104\\mathrm{mV}\\mathrm{dec}^{-1}$ were obtained for the $\\mathrm{CoNi@NC}$ samples prepared at $525^{\\circ}\\mathrm{C}$ and $475^{\\circ}\\mathrm{C}$ , respectively. The similar values for $\\mathrm{CoNi@NC}$ prepared at $475^{\\circ}\\mathrm{C}$ with different mass loadings shows that the Tafel slopes are almost independent of the catalyst mass loading (Figure 3d). These results indicate that the HER catalyzed by these $\\mathrm{CoNi@NC}$ samples is likely to occur by a Volmer– Heyrovsky mechanism.[5,27,35] \n\nDensity functional theory (DFT) calculations were carried out to gain further insights into the nature of this catalytic process. The processes that occur during the HER can be summarized in a three-state diagram, consisting of an initial $\\mathbf{H}^{+}$ state, an intermediate $\\mathrm{H^{*}}$ state and $1/2\\mathrm{H}_{2}$ as the final product (Figure 4 a). A good catalyst of the HER should have a moderate free energy for H adsorption $\\left(\\Delta G(\\mathrm{H^{*}})\\right)$ to compromise the reaction barriers of the adsorption and desorption steps.[7,36] Thus, the dependence of $\\Delta G(\\mathrm{H^{*}})$ on the measured current looks is represented by a volcano curve (Figure 4 b). In our DFT calculations, the adsorption of $\\mathrm{H^{*}}$ on the CoNi alloy was found to be too strong whereas it was too weak on the N-doped graphene shell, resulting in low HER activity in both cases. In contrast, the $\\Delta G(\\mathrm{H^{*}})$ value for the graphene shells of $\\mathrm{CoNi@C}$ can be effectively tuned by the encapsulated CoNi alloy, resulting in a high HER activity (Figure 4 a). \n\n![](images/e3aab5fe4acfe97895fb7194fce07d31957f8d509d52e9369c67fc2899586eac.jpg) \nFigure 4. a) Gibbs free energy (DG) profile of the HER on various catalysts. b) Volcano plot of the polarized current $({\\dot{I}}_{0})$ versus $\\Delta G(\\mathsf{H}^{\\ast})$ for a CoNi cluster, ${\\mathsf{C o N i@C}}$ , and an N-doped graphene shell (Ncarbon). c) The electronic potential of ${\\mathsf{C o N i@C}}$ ; the vacuum level was set to zero. d) The free energy of H adsorption $(\\Delta G(\\mathsf{H^{\\ast}}))$ on pure and N-doped (one, two, or three N atoms per shell) graphene shells with and without an enclosed CoNi cluster. Carbon gray, cobalt red, nickel green. \n\nAn analysis of the electronic potential of $\\mathrm{CoNi@C}$ shows that the electronic potential on the side that is closer to the enclosed CoNi cluster is approximately $0.3\\mathrm{eV}$ lower than that of the other sides, resulting in a higher proton affinity of the graphene shells (Figure 4 c). Calculated electronic structures reveal that the stabilization of the $\\mathrm{H^{*}}$ species should originate from the increase in the electron density on the graphene shells near the CoNi cluster (Figure 5 c), which can promote the HER activity. Furthermore, we also investigated how the nitrogen dopants cooperate with the metal clusters to promote the HER reaction. As shown in Figure 4d, increasing the number of nitrogen atoms from zero to three per shell leads to a decrease in $\\Delta G(H^{*})$ from $1.3\\mathrm{eV}$ to $0.1\\mathrm{eV}$ for graphene shells without an enclosed CoNi cluster, and the presence of the CoNi cluster leads to a further decrease in $\\Delta G(H^{*})$ , which suggests that nitrogen dopants and enclosed metal clusters can synergistically promote the adsorption of hydrogen on graphene shells. \n\nWe further studied the effect of the graphene layer on the HER by using a model where one to three graphene layers encapsulate a CoNi cluster. The differential electron densities $(\\Delta\\rho)$ in Figure 5 c clearly illustrate that the electron of a CoNi cluster can penetrate through three graphene layers. Furthermore, the differences in the free energy of $\\mathrm{~H~}$ adsorption $\\left[\\Delta\\Delta G(\\mathrm{H^{*}})\\right]$ for the different layers with and without a CoNi cluster were used to describe the effect of the CoNi cluster on the HER. As shown in Figure 5 b, the metal cluster induces a change in $\\Delta\\Delta G(H^{*})$ of $0.8\\mathrm{eV}$ when covered by a single graphene layer, whereas the effect decreases with an increase in the number of layers, but for the cluster with three graphene layers, the change still amounts to approximately $0.1\\ \\mathrm{eV}.$ Simultaneously, the difference in the electronic potential rapidly decreases from approximately $-0.5$ to $0\\mathrm{eV}$ when the number of graphene layer is increased from one to three. This result further indicates that the effect of the enclosed metal clusters on the graphene shells will decline when the graphene shell consists of more than three layers. These results demonstrate that the graphene layer thickness of the CoNi@C catalysts has a substantial influence on the HER activity, the thinner the graphene shells, the higher the catalytic activity. \n\n![](images/f9c0963df7c013fadaacb7b410f067496a60b21c21ec57841edad2ab7658254c.jpg) \nFigure 5. a) Schematic illustration of a CoNi alloy encapsulated in three-layer graphene. b) $\\Delta\\Delta G(H^{\\ast})$ (red line) and electronic potential (blue line) as a function of the number of graphene layers, where $\\Delta\\Delta G=\\Delta G$ (without metal) $-\\Delta G$ (with metal). c) Redistribution of the electron densities after the CoNi clusters have covered by one to three layers of graphene. The differential charge density $(\\Delta\\rho)$ is defined as the difference in the electron density with and without the CoNi cluster. The red and blue regions are regions of increased and decreased electron density, respectively. \n\nIn summary, we have reported a hierarchical architecture that consists of ultrathin graphene shells (only 1–3 layers) that encapsulate a uniform CoNi nanoalloy $(\\mathrm{CoNi@NC})$ , which provides a well-defined model for elucidating the role of carbon-encapsulated metal catalysts in the HER from theoretical calculations to the real system. Electrochemical measurements showed that CoNi@NC displays the best HER activity among the carbon-based electrocatalysts tested in acidic medium to date. DFT calculations indicate that the superior HER performance originates from the modulation of the electron density and the electronic potential distribution at the graphene surface by a penetrating electron from the CoNi core. Meanwhile, reducing the number of graphene layers and increasing the amount of the nitrogen dopant can significantly increase the electron density in the graphene shells, which further enhances the HER activity. These findings pave the way towards the development of high-performance, inexpensive HER electrocatalysts that can be used in acidic electrolytes as well as other energy-related catalysts. \n\nReceived: September 26, 2014 \nRevised: November 17, 2014 \nPublished online: January 7, 2015 \n\n.Keywords: electrocatalysis $\\cdot\\cdot$ graphene $\\cdot\\cdot$ non-precious metals $\\cdot$ hydrogen evolution reaction $\\mathbf{\\nabla}\\cdot\\mathbf{\\varepsilon}$ nanoparticles \n\n[16] L. Cheng, W. J. Huang, Q. F. Gong, C. H. Liu, Z. Liu, Y. G. Li, H. J. Dai, Angew. Chem. Int. Ed. 2014, 53, 7860; Angew. Chem. 2014, 126, 7994. \n[17] R. Solmaz, G. Kardas, Electrochim. Acta 2009, 54, 3726. \n[18] M. Gong, W. Zhou, M. C. Tsai, J. G. Zhou, M. Y. Guan, M. C. Lin, B. Zhang, Y. F. Hu, D. Y. Wang, J. Yang, S. J. Pennycook, B. J. Hwang, H. J. Dai, Nat. Commun. 2014, 5, 4695. \n[19] E. J. Popczun, C. G. Read, C. W. Roske, N. S. Lewis, R. E. Schaak, Angew. Chem. Int. Ed. 2014, 53, 5427; Angew. Chem. 2014, 126, 5531. \n[20] V. Artero, M. Chavarot-Kerlidou, M. Fontecave, Angew. Chem. Int. Ed. 2011, 50, 7238; Angew. Chem. 2011, 123, 7376. \n[21] P. W. Du, R. Eisenberg, Energy Environ. Sci. 2012, 5, 6012. \n[22] R. Subbaraman, D. Tripkovic, K. C. Chang, D. Strmcnik, A. P. Paulikas, P. Hirunsit, M. Chan, J. Greeley, V. Stamenkovic, N. M. Markovic, Nat. Mater. 2012, 11, 550. \n[23] D. H. Deng, L. Yu, X. Q. Chen, G. X. Wang, L. Jin, X. L. Pan, J. Deng, G. Q. Sun, X. H. Bao, Angew. Chem. Int. Ed. 2013, 52, 371; Angew. Chem. 2013, 125, 389. \n[24] J. Deng, L. Yu, D. H. Deng, X. Q. Chen, F. Yang, X. H. Bao, J. Mater. Chem. A 2013, 1, 14868. \n[25] Y. Hu, J. O. Jensen, W. Zhang, L. N. Cleemann, W. Xing, N. J. Bjerrum, Q. F. Li, Angew. Chem. Int. Ed. 2014, 53, 3675; Angew. Chem. 2014, 126, 3749. \n[26] H. T. Chung, J. H. Won, P. Zelenay, Nat. Commun. 2013, 4, 1922. \n[27] J. Deng, P. J. Ren, D. H. Deng, L. Yu, F. Yang, X. H. Bao, Energy Environ. Sci. 2014, 7, 1919. \n[28] X. C. Zou, X. C. Huang, A. Goswami, R. Silva, B. R. Sathe, E. Mikmekova, T. Asefa, Angew. Chem. Int. Ed. 2014, 53, 4372; Angew. Chem. 2014, 126, 4461. \n[29] X. J. Zheng, J. Deng, N. Wang, D. H. Deng, W. H. Zhang, X. H. Bao, C. Li, Angew. Chem. Int. Ed. 2014, 53, 7023; Angew. Chem. 2014, 126, 7143. \n[30] T. Fu, M. Wang, W. M. Cai, Y. M. Cui, F. Gao, L. M. Peng, W. Chen, W. P. Ding, ACS Catal. 2014, 4, 2536. \n[31] C. Wang, P. Zhai, Z. C. Zhang, Y. Zhou, J. Ju, Z. J. Shi, D. Ma, P. S. Han, F. Q. Huang, Part. Part. Syst. Charact. 2014, DOI: 10.1002/ppsc.201400039. \n[32] F. Guinea, Phys. Rev. B 2007, 75, 235433. \n[33] H. A. Chen, C. L. Hsin, Y. T. Huang, M. L. Tang, S. Dhuey, S. Cabrini, W. W. Wu, S. R. Leone, J. Phys. Chem. C 2013, 117, 22211. \n[34] Y. J. Gao, G. Hu, J. Zhong, Z. J. Shi, Y. S. Zhu, D. S. Su, J. G. Wang, X. H. Bao, D. Ma, Angew. Chem. Int. Ed. 2013, 52, 2109; Angew. Chem. 2013, 125, 2163. \n[35] N. Pentland, J. O. Bockris, E. Sheldon, J. Electrochem. Soc. 1957, 104, 182. \n[36] J. K. Nørskov, T. Bligaard, A. Logadottir, J. R. Kitchin, J. G. Chen, S. Pandelov, J. K. Nørskov, J. Electrochem. Soc. 2005, 152, J23. " + }, + { + "id": "10.1038_ncomms7694", + "DOI": "10.1038/ncomms7694", + "DOI Link": "http://dx.doi.org/10.1038/ncomms7694", + "Relative Dir Path": "mds/10.1038_ncomms7694", + "Article Title": "Formation of nickel cobalt sulfide ball-in-ball hollow spheres with enhanced electrochemical pseudocapacitive properties", + "Authors": "Shen, LF; Yu, L; Wu, HB; Yu, XY; Zhang, XG; Lou, XW", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "While the synthesis of hollow structures of transition metal oxides is well established, it is extremely challenging to fabricate complex hollow structures for mixed transition metal sulfides. Here we report an anion exchange method to synthesize a complex ternary metal sulfides hollow structure, namely nickel cobalt sulfide ball-in-ball hollow spheres. Uniform nickel cobalt glycerate solid spheres are first synthesized as the precursor and subsequently chemically transformed into nickel cobalt sulfide ball-in-ball hollow spheres. When used as electrode materials for electrochemical capacitors, these nickel cobalt sulfide hollow spheres deliver a specific capacitance of 1,036 F g(-1) at a current density of 1.0 A g(-1). An asymmetric supercapacitor based on these ball-in-ball structures shows long-term cycling performance with a high energy density of 42.3 Wh kg(-1) at a power density of 476 W kg(-1), suggesting their potential application in high-performance electrochemical capacitors.", + "Times Cited, WoS Core": 1214, + "Times Cited, All Databases": 1232, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000353043600001", + "Markdown": "# Formation of nickel cobalt sulfide ball-in-ball hollow spheres with enhanced electrochemical pseudocapacitive properties \n\nLaifa $\\mathsf{S h e n}^{1,2,\\star},$ Le $\\mathsf{Y u}^{1,\\star}$ , Hao Bin Wu1, Xin-Yao $\\mathsf{Y u}^{1}$ , Xiaogang Zhang2 & Xiong Wen (David) Lou1 \n\nWhile the synthesis of hollow structures of transition metal oxides is well established, it is extremely challenging to fabricate complex hollow structures for mixed transition metal sulfides. Here we report an anion exchange method to synthesize a complex ternary metal sulfides hollow structure, namely nickel cobalt sulfide ball-in-ball hollow spheres. Uniform nickel cobalt glycerate solid spheres are first synthesized as the precursor and subsequently chemically transformed into nickel cobalt sulfide ball-in-ball hollow spheres. When used as electrode materials for electrochemical capacitors, these nickel cobalt sulfide hollow spheres deliver a specific capacitance of $1,036\\mathsf{F g}^{-1}$ at a current density of $1.0\\mathsf{A}\\mathsf{g}^{-1}$ . An asymmetric supercapacitor based on these ball-in-ball structures shows long-term cycling performance with a high energy density of $42.3\\mathsf{W h}\\mathsf{k g}^{-1}$ at a power density of $476\\mathsf{W}\\mathsf{k g}^{-1}.$ suggesting their potential application in high-performance electrochemical capacitors. \n\nwing to their unique structural features and intriguing properties, hollow micro-/nanostructures with tunable size, shape, composition and interior architecture have attracted growing research interests for various applications, such as energy storage, catalysis, chemical sensors and biomedicine1–8. In the past decade, different types of hollow structures including hollow spheres9–12, boxes13–16 and micro-/nanotubes17–19 have been successfully synthesized through different synthesis routes. However, the configuration of most of available hollow structures appears relatively simple, such as single-shelled hollow spheres of one composition. Recently, extensive research efforts have been devoted to design and fabricate complex hollow structures with multi-shelled architecture and tunable chemical composition, which are expected to realize their optimized physical/chemical properties for specific applications. Until now, many types of metal oxides with multi-shelled structures have been successfully fabricated based on soft- or hard-template methods20–25. For example, Lou et al.26,27 have previously fabricated double-shelled $\\mathrm{SnO}_{2}$ hollow spheres using silica spheres as templates combining with designed procedures. Multi-shelled $\\mathrm{Cu}_{2}\\mathrm{O}$ hollow spheres have also been prepared using cetyl trimethylammonium bromide as soft template28. Wang et al.29 synthesized multishelled $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ hollow microspheres with carbonaceous microspheres as hard templates, which exhibit higher lithium storage capacity and improved cycling performance compared with single-shelled $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ microspheres. Very recently, we have developed a new ‘penetration–solidification–annealing’ method to synthesize various mixed metal oxide multi-shelled hollow spheres30. Despite these exciting advances, present studies on complex hollow structures are generally limited to metal oxides. \n\nRecently, transition metal sulfides have attracted great attention because of their excellent properties and promising applications in electronic, optical and optoelectronic devices31–35. In particular, ternary nickel cobalt sulfides have been regarded as a promising class of electrode materials for high-performance energy storage devices, since they offer higher electrochemical activity and higher capacity than mono-metal sulfides36–39. Moreover, nickel cobalt sulfides might exhibit much higher conductivity than corresponding ternary nickel cobalt oxides due to the smaller band $\\dot{\\mathrm{gap}}^{40,41}$ . Transition metal sulfides hollow structures reported so far with high quality usually possess simple configurations. It is very challenging to synthesize complex hollow structures of metal sulfides on the basis of protocols established for metal oxides because of the distinct physical/chemical properties between these two types of materials. \n\nHerein we report a facile anion exchange method to synthesize a novel ball-in-ball hollow structure of ternary nickel cobalt sulfide $\\left(\\mathrm{NiCo}_{2}\\mathrm{S}_{4}\\right)$ . The synthesis involves a facile solvothermal synthesis of metal-glycerate solid spheres and subsequent sulfidation in the presence of thioacetamide (TAA) to form $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres. Importantly, the interiors of the as-prepared $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres can be easily tuned by varying the reaction temperature during the anion exchange process. When used as electrode materials for electrochemical capacitors, the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres deliver excellent pseudocapacitve performance with high specific capacitance and remarkable rate capability. \n\n# Results \n\nFormation of ball-in-ball hollow spheres. We first develop a facile solvothermal method to prepare uniform nickel cobalt glycerate (NiCo-glycerate) spheres as the precursor (see Method for detailed synthesis procedure). Only a broad diffraction peak at around $12^{\\circ}$ can be seen in the $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) pattern of NiCo-glycerate (Supplementary Fig. 1), which is a characteristic of metal alkoxides42. The NiCo-glycerate spheres are highly uniform with a diameter of around $550\\mathrm{nm}$ (Supplementary Fig. 2a). The size distribution can be controlled by adjusting the solvothermal reaction temperature (Supplementary Fig. 3). A solution sulfidation process under solvothermal condition is then utilized to convert the NiCo-glycerate solid precursors into ball-in-ball $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres. The whole formation process can be generally divided into three stages as schematically illustrated in Fig. 1. At stage I, sulfide $(S^{2-})$ ions released from the decomposition of TAA at high temperature react with metal ions on the surface of NiCo-glycerate and produce NiCoglycerate $\\varpi{\\mathrm{NiCo}_{2}\\mathrm{S}_{4}}$ core–shell structure. This sulfidation process can be described as an anion exchange reaction of the NiCoglycerate. Further reaction between the inward diffused $S^{2-}$ ions and faster outward diffused metal cations supplies the growth of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ shell and leads to a well-defined gap between the shell and the NiCo-glycerate core. When the reaction proceeds to certain degree, it will be more difficult for the metal cations to diffuse to the outer shell through the enlarged empty gap. Thus, a secondary $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ shell would be formed on the remaining core as shown at stage II. On the completion of the anion exchange reaction, unique $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres are obtained at the end of stage III. \n\nTo illustrate the formation mechanism of these novel metal sulfide nanostructures, investigations using field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and powder XRD are conducted to monitor the morphological evolution and crystallization process as a function of the sulfidation time. It can be seen from Fig. 2a,e,i that the NiCo-glycerate precursor is composed of uniform solid spheres without visible pores. The surface of the spheres is very smooth. After sulfidation treatment at $160^{\\circ}\\mathrm{C}$ for $0.{\\bar{5}}\\mathrm{h}$ , the colour of the obtained product changes from initial brown to black, indicating the formation of metal sulfide. As shown in Fig. $^{2\\mathrm{b},\\mathrm{f},\\mathrm{j}}$ and Supplementary Fig. 2b, the products are still solid spheres but exhibit much rougher surface, which suggests the occurrence of sulfidation reaction on the surface. The surface of these solid microspheres is composed of closely packed nanoparticles. The corresponding XRD pattern demonstrates that these spheres are still mainly NiCo-glycerate with some diminishment in the peak intensity (Supplementary Fig. 4a). No diffraction peaks corresponding to $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ are found in the XRD pattern, most likely due to its low content and poor crystallinity. When prolonging the sulfidation duration to $^{2\\mathrm{h}}$ , there is an obvious gap between a well-defined shell and a solid core, forming a unique core–shell nanostructure (Fig. $2\\mathrm{g,k)}$ . Such a core–shell nanostructure possesses a porous shell consisting of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ , while retaining a dense core of NiCo-glycerate. The corresponding FESEM images (Fig. 2c; Supplementary Fig. 2c) clearly show that the roughness of the surface increases and some hollow spheres are broken. Two obvious diffraction peaks at $31.5^{\\circ}$ and $55.3^{\\circ}$ appear in the corresponding XRD pattern (Supplementary Fig. 4b), which can be indexed to the (311) and (440) planes of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}.$ , respectively. Meanwhile, the characteristic peak of NiCo-glycerate at low angle disappears, indicating a gradual phase transformation from NiCo-glycerate to $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ . The transformation from solid sphere to core–shell structure is likely due to the discrepancy in diffusion rate between metal cations and sulfide anions during the sulfidation process. However, similar sulfidation reaction generally results in simple hollow structures with a single shell and a completely void interior according to literature reports17,18,37,38,43. In our work, when further increasing the reaction time to $6\\mathrm{h}$ to complete the reaction, unique ball-in-ball hollow spheres are successfully obtained (Fig. $^{\\mathrm{2d,h,l)}}$ . The roughness of the surface further increases and more visible pores are observed in the shell. At the same time, more broken hollow spheres can be seen from the product (Supplementary Fig. 2d). These results imply the growth of primary $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanoparticles and the slight decrease of mechanical strength of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ shell. Nevertheless, majority of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres remain intact and complete, showing satisfactory structural robustness. The corresponding XRD pattern reveals that the NiCo-glycerate precursor is completely transformed into the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ phase (Supplementary Fig. 4c). The formation of such novel ball-in-ball hollow structures might be explained by the repeated anion exchange process taking place on the pre-formed solid cores as discussed earlier. \n\n![](images/d13bf67ab3305ee7d2acd54f700717de8a240a1376ca69b03c21d15abe77b2c7.jpg) \nFigure 1 | Schematic illustration of the formation process of $\\pmb{\\operatorname{Nic}}_{\\pmb{0}_{2}}\\pmb{\\mathbb S}_{4}$ ballin-ball hollow spheres. Stage I, surface $N i C o_{2}S_{4}$ formed by anion exchange method. Stage II, further diffusion of $\\mathsf{S}^{2-}$ and formation of $N i C o_{2}S_{4}$ on the inner NiCo-glycerate core. Stage III, completion of the anion exchange reaction. $M^{2+}$ refers to metal cations including ${\\mathsf{N i}}^{2+}$ and ${\\mathsf{C o}}^{2+}$ ions. \n\n![](images/617b9860b8b78ef96d13b795d477334ceb292dbbad0599392da330f60d598c83.jpg) \nFigure 2 | FESEM and TEM images of samples. (a,e,i) NiCo-glycerate solid spheres and products obtained after sulfidation of NiCo-glycerate solid spheres at $160^{\\circ}\\mathsf{C}$ for different durations: (b,f,j) $0.5\\mathsf{h};$ ; (c,g,k) $2h;$ (d,h,l) 6 h. Scale bars, $200\\mathsf{n m}$ . \n\nControlling the shell structure of hollow spheres. One of the crucial factors in the above formation of ball-in-ball hollow spheres is long-lasting supply of sulfide ions from the decomposition of TAA. The spheres obtained after sulfidation at low concentration of TAA are core–shell structures with the inner core diameter of about $400\\mathrm{nm}$ (Supplementary Fig. 5a). Ball-inball hollow spheres can still be obtained after sulfidation at high concentration of TAA (Supplementary Fig. 5b), but the diameter of inner core decreases to only $200\\mathrm{nm}$ . Apart from the concentration of TAA, reaction temperature is another important factor for the formation of hollow spheres, which not only affects the decomposition rate of TAA, but also influences the diffusion rate of ionic species. For example, only core–shell structure is obtained after sulfidation at a lower temperature of $120^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ (Supplementary Fig. 6a,b). After prolonging the solvothermal reaction to $12\\mathrm{h}$ , similar ball-in-ball hollow spheres can be successfully prepared but with a less pronounced gap between the two layers of shells (Supplementary Fig. 6c). Estimated from TEM image (Supplementary Fig. 6d), the average diameters of the outer and inner shells are about 590 and $250\\mathrm{nm}$ , respectively. At a lower reaction temperature, the sulfidation process substantially slows down. Moreover, the slower diffusion rate of ionic species especially metal cations results in the formation of the second metal sulfide shell closer to the outer shell. On the contrary, the solid NiCo-glycerate spheres are eventually transformed into $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres with the single shell after sulfidation at $200^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ (Supplementary Fig. 7a,b), as a result of the fast diffusion and anion exchange reaction before the formation of the inner metal sulfide layer on the remaining interior core. These observations also support the formation mechanism of the unique ball-in-ball structure as we discussed earlier. \n\nCharacterizations of ball-in-ball hollow spheres. An annealing treatment at $300^{\\circ}\\mathrm{C}$ in nitrogen $(\\Nu_{2})$ atmosphere is utilized to improve the crystallinity of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres. From the XRD pattern (Fig. 3a), all Bragg peaks can be indexed to cubic $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ phase (JCPDS card No. 43–1477). No residues or impurity phases are detected, indicating that the NiCo-glycerate precursor is completely converted to the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ phase after sulfidation. According to the Scherrer formula, the average crystallite size is calculated to be $\\sim14.6\\mathrm{nm}$ , which is consistent with TEM observations. The low-magnification FESEM examination reveals that the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres are still quite uniform, with a diameter of around $600\\mathrm{nm}$ (Fig. 3b). An enlarge FESEM image (Fig. 3c) shows that the surface of the spheres is very rough, which consists of small nanoparticles. TEM images provide an intuitive way to investigate the interior structure of the spheres by showing notable contrast difference between the hollow and solid parts. TEM images (Fig. 3d,e) show that these porous $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ spheres exhibit a unique ball-in-ball hollow architecture, which possesses good structural stability to withstand the thermal annealing process. Estimated from TEM images, the average diameters of the outer and inner shells are about 600 and $300\\mathrm{nm}$ , respectively. In line with the FESEM observation, a higher magnification TEM image depicted in Fig. 3f indicates that the spheres are highly porous and composed of small nanocrystals with an average size of around $10{-}30\\mathrm{nm}$ . \n\nIn addition, the outer shell is very thin, with an average thickness of around $30\\mathrm{nm}$ . A lattice spacing of $0.54\\mathrm{nm}$ is observed in the high-resolution HRTEM image (Supplementary Fig. 8), which is in good agreement with the interplanar spacing of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ (111) planes. Elemental mapping based on energy-dispersive X-ray spectroscopy (Supplementary Fig. 9) provides clearer information about the elemental distribution within the spheres. The distributions of $\\mathrm{Ni},$ Co and S elements in the hollow spheres are uniform, which further verifies the formation of phase-pure $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ . As determined by $\\Nu_{2}$ adsorption–desorption measurement (Supplementary Fig. 10), these $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres possess Brunauer–Emmett–Teller specific surface area of $5\\dot{3}.9\\mathrm{m}^{2}\\dot{\\mathrm{g}}^{-1}$ . Besides, most of the pores are smaller than $10\\mathrm{nm}$ in size, which are formed between the interconnected primary nanocrystals. \n\nMore importantly, the present concept of structural design is facile and potentially represents a general strategy that can be used to synthesize other mixed metal sulfides with ball-in-ball architecture. As an example, uniform MnCo-glycerate spheres with a diameter of around $550\\mathrm{nm}$ can be synthesized by a similar solvothermal method (Supplementary Fig. 11a,b). After the sulfidation reaction with TAA, the MnCo-glycerate precursor is chemically transformed into $\\mathrm{MnCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres (Supplementary Fig. 11c,d). \n\nElectrochemical evaluation of ball-in-ball hollow spheres. The pseudocapacitive properties of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres are evaluated by using a three-electrode cell configuration in $6.0\\mathrm{M}$ KOH solution, and the results are shown in Fig. 4. The representative cyclic voltammetry (CV) curves of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ electrode at various scan rates ranging from 2 to $60\\mathrm{{mVs}^{-1}}$ in a potential window of $-0.1$ to $0.55\\mathrm{V}$ are presented in Fig. 4a. The CV curves display two pairs of redox peaks, particularly at low scan rates, indicating the presence of redox reactions of $\\mathrm{\\DeltaNiCo_{2}S_{4}}$ during the electrochemical process. With a 30-fold increment in the sweep rate, from 2 to $60\\mathrm{mVs}^{-1}$ , there are no significant change in the position and shape of the current peaks, suggesting that the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ electrode is favourable for fast redox reactions. These distinct peaks might be attributed to the reversible Faradaic redox processes of $\\mathrm{Co}^{2+}/\\mathrm{Co}^{3+}/\\mathrm{Co}^{4+}$ and $\\mathrm{Ni}^{2+}/\\mathrm{Ni}^{3+}$ redox couples based on the following reactions40,43: \n\n![](images/bf6d68a87ba8376c356f49bd96b83bf64115982da8a17027db7c2f44186ab9ce.jpg) \nFigure 3 | Materials characterizations of the $N i c o_{2}S_{4}$ ball-in-ball hollow spheres after annealing in $M_{2}.$ (a) XRD pattern, (b,c) FESEM images. Scale bars, 500 and $100\\mathsf{n m}$ , respectively. (d,e) TEM images. Scale bars, $100\\mathsf{n m}$ . (f) Enlarged TEM image of the ${\\sf N i C o}_{2}{\\sf S}_{4}$ mesoporous shell. Scale bar, $20\\mathsf{n m}$ . \n\n![](images/9cbe5eb86d0201c0997f1428f6772c0dec655b91979c8feaa7f5c0755b38d0fb.jpg) \nFigure 4 | Electrochemical characterizations of the $\\mathsf{N i c o}_{2}\\mathsf{S}_{4}$ ball-in-ball hollow spheres electrode. (a) Cyclic voltammetry curves. (b) Galvanostatic charge/discharge voltage profiles. (c) Specific capacitance as a function of current density. (d) Cycling performance at a current density of $5\\mathsf{A g}^{-1}$ . SCE, saturated calomel electrode \n\n$$\n\\mathrm{CoS+OH^{-}\\rightleftarrows C o S O H+e^{-}}\n$$ \n\n$$\n\\mathrm{CoSOH}+\\mathrm{OH}^{-}\\rightleftharpoons\\mathrm{CoSO}+\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{e}^{-}\n$$ \n\n$$\n\\mathrm{NiS+OH^{-}\\rightleftarrows N i S O H+e^{-}}\n$$ \n\nFigure $\\boldsymbol{4\\mathrm{b}}$ presents the galvanostatic charge/discharge curves of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ electrode at different current densities ranging from 1 to $20\\mathrm{Ag^{-1}}$ . Consistent with the CV results, the poorly defined voltage plateaus in the charge/discharge curves suggest the pseudocapacitive behaviour and the presence of some Faradaic processes. The specific capacitance of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ electrode as a function of current density, calculated from the discharge curves, is shown in Fig. 4c. A maximum specific capacitance reaches up to ${1,036}{\\mathrm{Fg}}^{-\\mathrm{Y}}$ measured at a discharge current density of $\\mathrm{1Ag^{-1}}$ , and the corresponding volumetric capacitance is estimated to be $518\\mathrm{Fcm}^{-3}$ . With the increase of current density, the specific capacitance of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ electrode gradually decreases and still keeps a high value of $705\\mathrm{Fg}^{-1}$ at $20\\mathrm{Ag^{-1}}$ About $68.1\\%$ of the capacitance for $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres is retained when the current density increases from 1 to $20\\mathrm{Ag^{-1}}$ . Compared with $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres, single-shelled $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres exhibit inferior electrochemical performance when characterized under similar conditions (Supplementary Fig. 12), with a low specific capacitance of $567\\mathrm{F}\\dot{\\mathrm{g}}^{-1}$ at $20\\mathrm{Ag}^{-1}$ , corresponding to around $57.7\\%$ of the capacitance at $1\\mathrm{A}\\bar{\\bf g}^{-1}$ . The cycling performance of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres electrode is evaluated by repeated charge/discharge test at a current density of $5\\mathrm{Ag^{-1}}$ . The specific capacitance is $\\stackrel{\\smile}{8}92\\mathrm{F}\\mathrm{g}^{-1}$ for the first cycle and the value decreases to $774\\mathrm{Fg}^{-1}$ with about $13\\%$ loss after continuous cycling for 2,000 cycles (Fig. 4d). After cycling, the hollow structure can be well retained but the primary nanoparticles change to nanosheets (Supplementary Fig. 13). According to our previous experience, metal sulfides can be slowly electrochemically transformed into whisker-like metal hydroxides on the surface during the repeated charge/discharge processes44. \n\nElectrochemical evaluation of asymmetric capacitor. To further evaluate the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ electrode for practical application, an asymmetric supercapacitor (ASC) device is fabricated using the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ electrode as the cathode and a nanocomposite graphene/ carbon spheres $\\mathrm{(G/CSs)}$ film electrode as the anode in KOH aqueous electrolyte, with one piece of cellulose paper as the separator (Fig. 5a). The flexible $\\bar{\\mathbf{G}}/\\mathbf{C}\\mathbf{S}$ paper is fabricated by using a simple vacuum filtration method (Supplementary Fig. 14). Figure 5b presents typical CV curves of the $\\mathrm{NiCo_{2}S_{4}//G/C S}$ ASC device at various scan rates between 0 and $1.6\\mathrm{V}$ . Clearly, the CV curves show capacitance from both electric double-layer capacitance and pseudocapacitance. The current density increases with the increasing scan rate and all curves exhibit a similar shape. There is no obvious distortion in the CV curves even at a very high scan rate of $200\\mathrm{mVs}^{-1}$ , indicating excellent fast-charge/ discharge properties of the device. The calculated specific capacitance based on the CV curves as a function of the scan rate is plotted in Fig. 5c. The specific capacitance of the ASC is $\\dot{1}19.1\\mathrm{Fg}^{-1}$ at the scan rate of $5\\mathrm{m}\\dot{\\mathrm{V}}\\thinspace\\mathrm{s}^{-1}$ and it still retains $64.3\\mathrm{Fg}^{-1}$ at a very high scan rate of $200\\mathrm{mVs}^{-1}$ (based on the total mass of active materials of the two electrodes). Galvanostatic charge/discharge curves of the ASC at various current densities are shown in Supplementary Fig. 15. The charge/discharge curves remain in a good symmetry at cell voltage as high as $1.6\\mathrm{V}$ , implying that the cell has excellent electrochemical reversibility and capacitive characteristics. Figure 5d shows long-term cycling performance of the ASC at a current density of $5\\dot{\\mathrm{Ag}}^{-1}$ Remarkably, the ASC manifests very high cycling stability and still delivers $78.6\\%$ of its initial capacitance even after 10,000 cycles. We have further evaluated the energy and power densities of the $\\mathrm{NiCo_{2}S_{4}//G/C S}$ ASC. As shown in the Ragone plot (Supplementary Fig. 16), the ASC displays a high energy density of $\\dot{4}\\dot{2}.3\\mathrm{Wh}\\mathrm{kg}^{-1}$ at a power density of $476\\mathrm{W}\\mathrm{kg}^{-1}$ . Even at a high power density of $10208\\mathrm{W}\\mathrm{kg}^{-1};$ , the ASC still delivers an energy density of $\\dot{2}2.9\\mathrm{Wh}\\mathrm{kg}^{-1}$ . Overall, the performance of this $\\mathrm{NiCo_{2}S_{4}//G/C S}$ ASC is superior to that of many other ASCs, such as metal sulfide-based ASCs $\\mathrm{\\mathop{CoS}_{x}}/.$ /graphene45 and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}//$ graphene46), metal hydroxide-based ASCs $\\mathrm{(Ni(OH)}_{2}/$ /activated carbon $(\\mathrm{AC})^{47})$ ), metal oxide-based ASCs (NiO//graphene48 and $\\mathrm{Co_{3}O_{4}//A C^{49}};$ ), mixed metal oxide-based ASCs $(\\mathrm{\\checkNi}\\dot{\\mathrm{Co}}_{2}\\mathrm{O}_{4}//\\mathrm{AC}^{50}$ and $\\dot{\\mathrm{CoMoO_{4}//A C^{51}}},$ ). \n\n![](images/0bc9e848506f11344efb94dbc2afe78ca9d6a8507cb8a4950012e4892edc19a6.jpg) \nFigure 5 | Electrochemical evaluation of the ${\\sf N i c o}_{2}{\\sf S}_{4}//{\\sf G}/{\\sf C}{\\sf S}$ ASC. (a) Schematic illustration of the ASC device. (b) CV curves of the ASC device at various scan rates from 5 to $200\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ measured between 0 and $1.6{\\lor}.$ (c) Plot of the specific capacitance as a function of scan rate. (d) Cycling performance of the ASC device at a current density of $5\\mathsf{A g}^{-1}$ . SCE, saturated calomel electrode. \n\n# Discussion \n\nThe pseudocapacitive properties of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres are compare favourably to or even superior to that of many binary or ternary nickel- and cobalt-based sulfides (Supplementary Table 1)36–41,43,52–57. The improved pseudocapacitive performance of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres might be largely attributed to their unique structure. First, the shells consisting of small nanocrystals possess high porosity, and thus the electrolyte can easily penetrate through the shell for efficient redox reactions during the Faradaic charge storage process. Second, the unique ball-in-ball hollow architecture could significantly enlarge the active surface area and probably improve the structural integrity as well. As a result, both the specific capacitance and cycling stability are greatly enhanced. \n\nIn summary, a novel two-step method has been developed for the fabrication of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres with enhanced pseudocapacitive properties. The synthesis involves a facile solvothermal synthesis of uniform NiCo-glycerate solid spheres and a subsequent chemical sulfidation process. The formation mechanism of such interesting ball-in-ball hollow structures could be attributed to the discrepancy in diffusion rates of metal cations and sulfide anions during the sulfidation process. The resultant $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres exhibit a high specific capacitance of $1,036\\mathrm{Fg}^{-1}$ at a current density of $\\mathrm{1.0{Ag}^{-1}}$ . An asymmetric supercapacitor has been successfully fabricated using these unique $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres, which delivers high energy and power densities and exhibits outstanding cycle life. This work would open up new strategies for the controllable synthesis of complex hollow structures of metal sulfides and other functional materials for different applications. \n\n# Methods \n\nSynthesis of $\\mathbf{NiCo_{2}S_{4}}$ ball-in-ball hollow spheres. All the chemicals were directly used after purchase without further purification. In a typical synthesis, $0.25\\mathrm{mmol}$ of $\\mathrm{Co}(\\mathrm{NO}_{3})_{2}\\cdot6\\mathrm{H}_{2}\\mathrm{O},$ $0.125\\mathrm{mmol}$ of $\\mathrm{\\DeltaNi(NO_{3})_{2}\\cdot6H_{2}O}$ and $\\mathrm{8}\\mathrm{ml}$ of glycerol were dissolved into $40\\mathrm{ml}$ of isopropanol to form a transparent pink solution. The solution was then transferred to a Teflon-lined stainless steel autoclave and kept at $180^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ . After cooling to room temperature naturally, the brown precipitate was separated by centrifugation, washed several times with ethanol and dried in an oven at $80^{\\circ}\\mathrm{C}.$ For the preparation of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres, $30\\mathrm{mg}$ of the above NiCo-glycerate precursor was redispersed into $20\\mathrm{ml}$ of ethanol, followed by the addition of $50\\mathrm{mg}$ of TAA. Then the mixture was transferred into a Teflon-lined stainless steel autoclave and kept at different temperature. After centrifugation and washed with ethanol for several times, the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ hollow spheres were obtained. To improve the crystallinity, the final product was annealed under $\\Nu_{2}$ atmosphere at $300^{\\circ}\\mathrm{C}$ for $0.5\\mathrm{h}$ . \n\nSynthesis of $\\mathbf{G}/\\mathbf{C}\\mathbf{S}$ paper. Ordered mesoporous CSs were prepared by a hydrothermal method reported by Zhao et al.58 The freshly prepared carbon spheres were functionalized with poly(diallyldimethylammonium chloride) to own surface positive charges. Graphene oxide (GO) was synthesized from natural graphite flakes by a modified Hummers method59. The $\\mathrm{\\bfG}/\\$ CS paper was prepared by the following process: GO $(30\\mathrm{mg})$ was dispersed in distilled water $(40\\mathrm{ml})$ by ultrasonic treatment for $2\\mathrm{h}$ . CS functionalized with poly(diallyldimethylammonium chloride) $\\left(6\\:\\mathrm{mg}\\right)$ were added and then sonicated for another $2\\mathrm{h}$ . \n\nThe resulting complex dispersion was filtered by a vacuum filter equipped with a $0.2\\mathrm{-}\\upmu\\mathrm{m}$ porous polytetrafluoroethylene membrane to produce a $G O/C S$ paper. Subsequently, hydrazine in gas form was applied in a reaction chamber under ambient conditions for 3 days to reduce the GO to form $G/\\mathrm{CS}$ paper. \n\nMaterials characterization. Powder XRD patterns were collected on a Bruker D2 Phaser X-Ray Diffractometer with Ni filtered Cu $K\\alpha$ radiation $(\\lambda=1.5406\\mathring\\mathrm{A}$ ) at a voltage of $30\\mathrm{kV}$ and a current of $10\\mathrm{mA}$ . The microstructures were characterized using TEM (JEOL, JEM-2010) and FESEM (JEOL, JSM-6700F). Elemental mapping was acquired using energy-dispersive X-ray spectroscopy attached to JEM-2100F (TEM, JEOL). The $\\mathrm{N}_{2}$ sorption measurement was carried on Autosorb 6B at liquid $\\Nu_{2}$ temperature. \n\nElectrochemical measurements. For electrochemical measurements, the working electrode was prepared by mixing the electroactive material, carbon black (super-P-Li) and polymer binder (polyvinylidene difluoride) in a weight ratio of 70:20:10. The slurry was pressed onto Ni foam and dried at $90^{\\circ}\\mathrm{C}$ for $\\mathrm{10h}$ . Electrochemical measurements were conducted with a CHI 660C electrochemical workstation in an aqueous KOH electrolyte $(6.0\\mathrm{M})$ with a three-electrode cell where a $\\mathrm{\\Pt}$ foil serves as the counter electrode and a saturated calomel electrode as the reference electrode. The tap density of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ ball-in-ball hollow spheres was estimated by directly measuring the mass and physical dimensions occupied, which is about $0.5\\mathrm{gcm}^{-3}$ . The mass loading of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ is about $5\\mathrm{mg}\\mathrm{cm}^{-2}$ . \n\nThe specific capacitance is calculated by the following equation: \n\n$$\nC={\\frac{I\\Delta t}{m\\Delta V}},\n$$ \n\nwhere $I$ is the discharge current, $\\Delta t$ is the discharge time, $\\Delta V$ is the voltage range and $m$ is the mass of the active material. \n\nThe volumetric capacitance is calculated by the following equation: \n\n$$\nC_{\\nu}=C_{m}\\times\\rho,\n$$ \n\nwhere $C_{\\nu}$ is the volumetric capacitance, $C_{m}$ is the gravimetric capacitance and $\\rho$ is the materials density. \n\nFabrication and evaluation of supercapacitor devices. ASCs were fabricated by assembling $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ cathode and graphene/CS anode with one piece of cellulose paper as the separator in twoelectrode simulation cells. A $6\\mathrm{M}\\mathrm{KOH}$ solution was employed as the electrolyte. The mass ratio of positive electrode to negative electrode was decided according to the well-known charge balance equation $(q_{+}=q_{-})$ . In the relation, the charge stored by each electrode usually depends on the specific capacitance (C), the potential range $(\\Delta V)$ and the mass of the electrode $(m)$ following equation (6): \n\n$$\nq=C\\times\\Delta V\\times m\n$$ \n\nTo obtain $q_{+}=q_{-}$ , the mass balance will be expressed as following equation (7): \n\n$$\n\\frac{m_{+}}{m_{-}}=\\frac{C_{-}\\times\\Delta V_{-}}{C_{+}\\times\\Delta V_{+}}\n$$ \n\n$C_{+}$ and $C_{-}$ are the specific capacitance of the $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ and ${\\bf G}/{\\bf\\Sigma}$ CS electrodes, respectively. $\\Delta V_{+}$ and $\\Delta V_{-}$ are the voltage range of one scanning segment (V) of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ and $G/\\mathrm{CS}$ electrodes, respectively. \n\nThe specific capacitance (C) is calculated from the CV curve by following Equation 8: \n\n$$\nC=\\left(\\int I\\mathrm{d}V\\right)/(\\nu m V),\n$$ \n\nwhere $I$ is the current density $(\\mathrm{A}\\mathrm{cm}^{-2})$ , $V$ is the cell voltage (V), $\\nu$ is the potential scan rate $\\dot{(\\mathrm{mV}\\thinspace s^{-1})}$ and $m$ is the total mass of active materials on both electrodes $(\\mathrm{g}\\mathrm{cm}^{-2})$ . \n\nThe energy density $(E)$ and power density $(P)$ of ASCs against the two electrodes in device were calculated based on the total mass of the active materials using the following equations: \n\n$$\nE={\\frac{1}{2}}C V^{2}\n$$ \n\n$$\nP=\\frac{E}{\\Delta t},\n$$ \n\nwhere $V$ is the voltage range of one sweep segment and $\\Delta t$ is the time for a sweep segment. \n\n# References \n\n1. Oh, M. H. et al. Galvanic replacement reactions in metal oxide nanocrystals. Science 340, 964–968 (2013). \n2. Lou, X. W., Archer, L. A. & Yang, Z. C. Hollow micro-/nanostructures: synthesis and applications. Adv. Mater. 20, 3987–4019 (2008). \n3. Liu, J. et al. Yolk-shell hybrid materials with a periodic mesoporous organosilica shell: ideal nanoreactors for selective alcohol oxidation. Adv. Funct. Mater. 22, 591–599 (2012). \n4. Matsusaki, M., Ajiro, H., Kida, T., Serizawa, T. & Akashi, M. Layer-by-layer assembly through weak interactions and their biomedical applications. Adv. Mater. 24, 454–474 (2012). \n5. Liu, J., Qiao, S. Z., Hartono, S. B. & Lu, G. Q. Monodisperse yolk-shell nanoparticles with a hierarchical porous structure for delivery vehicles and nanoreactors. Angew. Chem. Int. Ed. 49, 4981–4985 (2010). \n6. Nai, J. W., Tian, Y., Guan, X. & Guo, L. Pearson’s principle inspired generalized strategy for the fabrication of metal hydroxide and oxide nanocages. J. Am. Chem. Soc. 135, 16082–16091 (2013). \n7. Wang, Z. Y., Zhou, L. & Lou, X. W. Metal oxide hollow nanostructures for lithium-ion batteries. Adv. Mater. 24, 1903–1911 (2012). \n8. Liu, X. H., Jin, X. B. & Ma, P. X. Nanofibrous hollow microspheres selfassembled from star-shaped polymers as injectable cell carriers for knee repair. Nat. Mater. 10, 398–406 (2011). \n9. Sun, H. T. et al. High-rate lithiation-induced reactivation of mesoporous hollow spheres for long-lived lithium-ion batteries. Nat. Commun. 5, 4526 (2014). \n10. Pan, A. Q., Wu, H. B., Yu, L. & Lou, X. W. Template-free synthesis of $\\mathrm{VO}_{2}$ hollow microspheres with various interiors and their conversion into $\\mathrm{V}_{2}\\mathrm{O}_{5}$ for lithium-ion batteries. Angew. Chem. Int. Ed. 52, 2226–2230 (2013). \n11. Lai, X. Y. et al. General synthesis and gas-sensing properties of multiple-shell metal oxide hollow microspheres. Angew. Chem. Int. Ed. 50, 2738–2741 (2011). \n12. Shokouhimehr, M., Lee, J. E., Han, S. I. & Hyeon, T. Magnetically recyclable hollow nanocomposite catalysts for heterogeneous reduction of nitroarenes and Suzuki reactions. Chem. Commun. 49, 4779–4781 (2013). \n13. Zhang, L., Wu, H. B. & Lou, X. W. Metal-organic-frameworks-derived general formation of hollow structures with high complexity. J. Am. Chem. Soc. 135, 10664–10672 (2013). \n14. Movia, D. et al. A safe-by-design approach to the development of gold nanoboxes as carriers for internalization into cancer cells. Biomaterials 35, 2543–2557 (2014). \n15. Nai, J. W., Wang, S. Q., Bai, Y. & Guo, L. Amorphous $\\mathrm{Ni(OH)}_{2}$ nanoboxes: fast fabrication and enhanced sensing for glucose. Small 9, 3147–3152 (2013). \n16. Wang, Z. Y., Wang, Z. C., Liu, W. T., Xiao, W. & Lou, X. W. Amorphous $\\mathrm{CoSnO}_{3}@\\mathrm{C}$ nanoboxes with superior lithium storage capability. Energy Environ. Sci. 6, 87–91 (2013). \n17. Xiao, J. W., Wan, L., Yang, S. H., Xiao, F. & Wang, S. Design hierarchical electrodes with highly conductive $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanotube arrays grown on carbon fiber paper for high-performance pseudocapacitors. Nano Lett. 14, 831–838 (2014). \n18. Chen, H. C. et al. In situ growth of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanotube arrays on Ni foam for supercapacitors: maximizing utilization efficiency at high mass loading to achieve ultrahigh areal pseudocapacitance. J. Power Sources 254, 249–257 (2014). \n19. Zhang, G. Q. et al. General formation of complex tubular nanostructures of metal oxides for the oxygen reduction reaction and lithium-ion batteries. Angew. Chem. Int. Ed. 52, 8643–8647 (2013). osphere for dye-sensitized solar cells with high efficiency. Adv. Mater. 24, 1046–1049 (2012). \n21. Dong, Z. H. et al. Quintuple-shelled $\\mathrm{SnO}_{2}$ hollow microspheres with superior light scattering for high-performance dyesensitized solar cells. Adv. Mater. 26, 905–909 (2014). \n22. Xu, P. F. et al. Hierarchical nanoscale multi-shell ${\\mathrm{Au/CeO}}_{2}$ hollow spheres. Chem. Sci. 5, 4221–4226 (2014). \n23. Xu, S. M. et al. ${\\tt a}{\\tt F e}_{2}{\\tt O}_{3}$ multi-shelled hollow microspheres for lithium ion battery anodes with superior capacity and charge retention. Energy Environ. Sci. 7, 632–637 (2014). \n24. Lai, X. Y., Halpert, J. E. & Wang, D. Recent advances in micro-/nano-structured hollow spheres for energy applications: from simple to complex systems. Energy Environ. Sci. 5, 5604–5618 (2012). \n25. Wang, J. Y. et al. pH-regulated synthesis of multi-shelled manganese oxide hollow microspheres as supercapacitor electrodes using carbonaceous microspheres as templates. Adv. Sci. doi:10.1002/advs.201400011 in the press. \n26. Lou, X. W., Li, C. M. & Archer, L. A. Designed synthesis of coaxial $\\mathrm{SnO}_{2}@$ carbon hollow nanospheres for highly reversible lithium storage. Adv. Mater. 21, 2536–2539 (2009). \n27. Lou, X. W., Yuan, C. L. & Archer, L. A. Shell-by-shell synthesis of tin oxide hollow colloids with nanoarchitectured walls: Cavity size tuning and functionalization. Small 3, 261–265 (2007). \n28. Xu, H. L. & Wang, W. Z. Template synthesis of multishelled $\\mathrm{Cu}_{2}\\mathrm{O}$ hollow spheres with a single-crystalline shell wall. Angew. Chem. Int. Ed. 46, 1489–1492 (2007). \n29. Wang, J. Y. et al. Accurate control of multishelled $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ hollow microspheres as high-performance anode materials in lithium-ion batteries. Angew. Chem. Int. Ed. 52, 6417–6420 (2013). \n30. Zhang, G. Q. & Lou, X. W. General synthesis of multi-shelled mixed metal oxide hollow spheres with superior lithium storage properties. Angew. Chem. Int. Ed. 53, 9041–9044 (2014). \n31. Lai, C. H., Lu, M. Y. & Chen, L. J. Metal sulfide nanostructures: synthesis, properties and applications in energy conversion and storage. J. Mater. Chem. 22, 19–30 (2012). \n32. Li, L. et al. Single-crystalline CdS nanobelts for excellent field-emitters and ultrahigh quantum-efficiency photodetectors. Adv. Mater. 22, 3161–3165 (2010). \n33. Radovanovic, P. V., Barrelet, C. J., Gradecak, S., Qian, F. & Lieber, C. M. General synthesis of manganese-doped II-VI and III-V semiconductor nanowires. Nano Lett. 5, 1407–1411 (2005). \n34. Fang, X. S. et al. Single-crystalline ZnS Nanobelts as ultraviolet-light sensors. Adv. Mater. 21, 2034–2039 (2009). \n35. Xiong, S. L. & Zeng, H. C. Serial ionic exchange for the synthesis of multishelled copper sulfide hollow spheres. Angew. Chem. Int. Ed. 51, 949–952 (2012). \n36. Chen, H. C. et al. Highly conductive $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ urchin-like nanostructures for high-rate pseudocapacitors. Nanoscale 5, 8879–8883 (2013). \n37. Yu, L., Zhang, L., Wu, H. B. & Lou, X. W. Formation of $\\mathrm{Ni}_{\\mathrm{x}}\\mathrm{Co}_{3-\\mathrm{x}}\\mathrm{S}_{4}$ hollow nanoprisms with enhanced pseudocapacitive properties. Angew. Chem. Int. Ed. 53, 3711–3714 (2014). \n38. Pu, J. et al. Direct growth of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanotube arrays on nickel foam as highperformance binder-free electrodes for supercapacitors. Chempluschem 79, 577–583 (2014). \n39. Chen, W., Xia, C. & Alshareef, H. N. One-step electrodeposited nickel cobalt sulfide nanosheet arrays for high-performance asymmetric supercapacitors. ACS Nano 8, 9531–9541 (2014). \n$40.\\mathrm{Pu},$ J. et al. Preparation and electrochemical characterization of hollow hexagonal $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanoplates as pseudocapacitor materials. ACS Sustainable Chem. Eng. 2, 809–815 (2014). \n41. Peng, S. J. et al. In situ growth of $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanosheets on graphene for highperformance supercapacitors. Chem. Commun. 49, 10178–10180 (2013). \n42. Zhu, G. Y. et al. Highly conductive three-dimensional $\\mathrm{MnO}_{2}$ -carbon nanotubegraphene-Ni hybrid foam as a binder-free supercapacitor electrode. Nanoscale 6, 1079–1085 (2014). \n43. Wan, H. Z. et al. $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ porous nanotubes synthesis via sacrificial templates: high-performance electrode materials of supercapacitors. CrystEngComm 15, 7649–7651 (2013). \n44. Yuan, C. Z., Gao, B., Su, L. H., Chen, L. & Zhang, X. G. Electrochemically induced phase transformation and charge-storage mechanism of amorphous cosx nanoparticles prepared by interface-hydrothermal method. J. Electrochem. Soc. 156, A199–A203 (2009). \n45. Dubal, D. P., Gund, G. S., Lokhande, C. D. & Holze, R. Controlled growth of $\\mathrm{CoS_{x}}$ nanostrip arrays $\\mathrm{\\CoS_{x}}$ -NSA) on nickel foam for asymmetric supercapacitors. Energy Technol. 2, 401–408 (2014). \n46. Dai, C. S. et al. Hierarchically structured $\\mathrm{Ni}_{3}\\mathrm{S}_{2}/$ carbon nanotube composites as high performance cathode materials for asymmetric supercapacitors. ACS Appl. Mater. Interfaces 5, 12168–12174 (2013). \n47. Li, H. B. et al. Amorphous nickel hydroxide nanospheres with ultrahigh capacitance and energy density as electrochemical pseudocapacitor materials. Nat. Commun. 4, 1894 (2013). \n48. Luan, F. et al. High energy density asymmetric supercapacitors with a nickel oxide nanoflake cathode and a 3D reduced graphene oxide anode. Nanoscale 5, 7984–7990 (2013). \n49. Zhang, C. M. et al. Electrochemical performance of asymmetric supercapacitor based on $\\mathrm{Co_{3}O_{4}/A C}$ materials. J. Electroanal. Chem. 706, 1–6 (2013). \n50. Lu, X. F. et al. Hierarchical $\\mathrm{NiCo}_{2}\\mathrm{O}_{4}$ nanosheets@hollow microrod arrays for high-performance asymmetric supercapacitors. J. Mater. Chem. A 2, 4706–4713 (2014). \n51. Yu, X. Z., Lu, B. A. & Xu, Z. Super long-life supercapacitors based on the construction of nanohoneycomb-like strongly coupled $\\mathrm{CoMoO_{4}}$ -3D graphene hybrid electrodes. Adv. Mater. 26, 1044–1051 (2014). \n52. Zhu, Y. R. et al. Mesoporous $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanoparticles as high-performance electrode materials for supercapacitors. J. Power Sources 273, 584–590 (2015). \n53. Wang, Q. H. et al. $\\mathrm{Co}_{3}\\mathrm{S}_{4}$ hollow nanospheres grown on graphene as advanced electrode materials for supercapacitors. J. Mater. Chem. 22, 21387–21391 (2012). \n54. Peng, S. J. et al. $\\ensuremath{\\mathrm{MS}}_{2}$ 1 $\\mathbf{\\dot{M}}=\\mathbf{Co}$ and Ni) hollow spheres with tunable interiors for high- performance supercapacitors and photovoltaics. Adv. Funct. Mater. 24, 2155–2162 (2014). \n55. Xia, X. H. et al. Synthesis of Free-Standing Metal Sulfide Nanoarrays via Anion Exchange Reaction and Their Electrochemical Energy Storage Application. Small. 10, 766–773 (2014). \n56. Pang, H. et al. Microwave-assisted synthesis of $\\mathrm{NiS}_{2}$ nanostructures for supercapacitors and cocatalytic enhancing photocatalytic $\\mathrm{H}_{2}$ production. Sci. Rep. 4, 3577 (2014). \n57. Yang, J. et al. Electrochemical performances investigation of NiS/rGO composite as electrode material for supercapacitors. Nano Energy 5, 74–81 (2014). \n58. Fang, Y. et al. A low-concentration hydrothermal synthesis of biocompatible ordered mesoporous carbon nanospheres with tunable and uniform size. Angew. Chem. Int. Ed. 49, 7987–7991 (2010). \n59. Hummers, W. S. & Offeman, R. E. Preparation of graphitic oxide. J. Am. Chem. Soc. 80, 1339–1339 (1958). \n\n# Author contributions \n\nX.W.L. and L.S. conceived the idea. L.S. carried out the materials synthesis and electrochemical testing. L.S., L.Y., H.B.W. and X.-Y.Y. characterized the materials. L.Y., H.B.W., X.Z. and X.W.L. co-wrote the manuscript. X.W.L. supervised the project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Shen, L. et al. Formation of nickel cobalt sulfide ball-in-ball hollow spheres with enhanced electrochemical pseudocapacitive properties. Nat. Commun. 6:6694 doi: 10.1038/ncomms7694 (2015). " + }, + { + "id": "10.1038_ncomms9144", + "DOI": "10.1038/ncomms9144", + "DOI Link": "http://dx.doi.org/10.1038/ncomms9144", + "Relative Dir Path": "mds/10.1038_ncomms9144", + "Article Title": "Realizing high figure of merit in heavy-band p-type half-Heusler thermoelectric materials", + "Authors": "Fu, CG; Bai, SQ; Liu, YT; Tang, YS; Chen, LD; Zhao, XB; Zhu, TJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Solid-state thermoelectric technology offers a promising solution for converting waste heat to useful electrical power. Both high operating temperature and high figure of merit zT are desirable for high-efficiency thermoelectric power generation. Here we report a high zT of similar to 1.5 at 1,200 K for the p-type FeNbSb heavy-band half-Heusler alloys. High content of heavier Hf dopant simultaneously optimizes the electrical power factor and suppresses thermal conductivity. Both the enhanced point-defect and electron-phonon scatterings contribute to a significant reduction in the lattice thermal conductivity. An eight couple prototype thermoelectric module exhibits a high conversion efficiency of 6.2% and a high power density of 2.2 Wcm(-2) at a temperature difference of 655 K. These findings highlight the optimization strategy for heavy-band thermoelectric materials and demonstrate a realistic prospect of high-temperature thermoelectric modules based on half-Heusler alloys with low cost, excellent mechanical robustness and stability.", + "Times Cited, WoS Core": 992, + "Times Cited, All Databases": 1041, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000363015800003", + "Markdown": "# Realizing high figure of merit in heavy-band p-type half-Heusler thermoelectric materials \n\nChenguang Fu1, Shengqiang Bai2, Yintu Liu1, Yunshan Tang2, Lidong Chen2, Xinbing Zhao1,3 & Tiejun Zhu1,3 \n\nSolid-state thermoelectric technology offers a promising solution for converting waste heat to useful electrical power. Both high operating temperature and high figure of merit $z T$ are desirable for high-efficiency thermoelectric power generation. Here we report a high zT of $\\sim1.5$ at $1,200\\mathsf{K}$ for the $p$ -type FeNbSb heavy-band half-Heusler alloys. High content of heavier Hf dopant simultaneously optimizes the electrical power factor and suppresses thermal conductivity. Both the enhanced point-defect and electron–phonon scatterings contribute to a significant reduction in the lattice thermal conductivity. An eight couple prototype thermoelectric module exhibits a high conversion efficiency of $6.2\\%$ and a high power density of $2.2\\mathsf{W}\\mathsf{c m}^{-2}$ at a temperature difference of $655\\mathsf{K}.$ These findings highlight the optimization strategy for heavy-band thermoelectric materials and demonstrate a realistic prospect of high-temperature thermoelectric modules based on half-Heusler alloys with low cost, excellent mechanical robustness and stability. \n\nT rhesedaercmhanindtfo rd sffuesrteanintatbylpeesenoefreginesrghyascsopnavrekresidosnigtencifihcnaonl-t ogies in the past decades. Thermoelectric materials, which can directly convert waste heat into usable electricity, have received more and more attention for promising application in energy harvesting1,2. The conversion efficiency $\\eta$ of a thermoelectric device is limited by the Carnot efficiency $\\eta_{\\mathrm{c}},$ and the figure of merit $z T$ of the thermoelectric materials, which is expressed as $z T=\\alpha^{2}\\upsigma T/(\\kappa_{\\mathrm{e}}+\\kappa_{\\mathrm{L}})$ , where $\\alpha,\\sigma,T,\\kappa_{\\mathrm{e}}$ and $\\kappa_{\\mathrm{L}}$ are the Seebeck coefficient. respectively, the electrical conductivity, the absolute temperature and the electronic and lattice components of total thermal conductivity $\\kappa$ (ref. 1). Thus, a high $\\eta_{\\mathrm{c}}$ and a high $z T$ will result in enhanced conversion efficiency. The thermoelectric parameters $\\alpha,\\sigma,$ and $\\kappa_{\\mathrm{e}}$ are intimately interrelated via carrier concentration and it has been a big challenge to decouple the thermal and electrical properties. Two main strategies, therefore, have been individually adopted to improve $z T.$ . One is to maximize the power factor $\\alpha^{2}\\sigma$ through optimal doping and band engineering1, 3,4. The other targets to reduce the lattice thermal conductivity $\\kappa_{\\mathrm{L}}$ by nanostructuring or phonon engineering5,6. \n\nTraditional good thermoelectric materials, such as $\\mathrm{Bi}_{x}\\mathrm{Sb}_{2-x}\\mathrm{Te}_{3}$ alloys near room temperature, $\\mathrm{Pb}\\mathrm{Te}_{1-x}\\mathrm{Se}_{x}$ alloys at moderate temperature and $\\mathrm{Si}_{1}{}_{-x}\\mathrm{Ge}_{x}$ alloys at high temperature, have high carrier mobility $\\mu$ and reduced $\\kappa_{\\mathrm{L}}$ (refs 7,8). A common character of these materials is that their band structures near the Fermi levels are dominated by the s or $\\boldsymbol{p}$ electronic states, accounting for the low density of states effective mass $m^{*}$ and high $\\mu$ . These light-band thermoelectric semiconductors with small $m^{*}$ $(0.1m_{\\mathrm{e}}{-}1.0m_{\\mathrm{e}})$ generally request relatively low-optimal carrier concentration $p_{\\mathrm{opt}}$ $(10^{19^{\\prime}}–10^{20}\\mathrm{cm}^{-3})$ , as shown in Fig. 1a, a low content of dopants is enough to optimize their power factors. \n\nIn recent years, some other semiconductors have also been identified as promising high-performance thermoelectric materials, such as tin selenides2, filled skutterudites9 and half-Heusler compounds10,11. Most of them contain transition metal elements, such as Fe, Co, Ni et al., and their localized $3d$ states make the valence band maximum or conduction band minimum flat and heavy12,13. Typically, the $m^{*}$ of these heavyband materials are in the range of $2\\:m_{\\mathrm{e}}{-}10\\:m_{\\mathrm{e}}$ (Fig. 1a). Thus, higher carrier concentrations, which demands for higher contents of dopants, are necessary to optimize the power factors. For example, the $p_{\\mathrm{opt}}$ of heavy-band ZrNiSn alloys is $\\sim4\\times10^{20}\\mathrm{^{{\\dot{c}}m}}^{-3}.$ , one order of magnitude higher than that of PbTe\u0003 $(\\sim3\\times10^{19}~\\mathrm{cm}^{-3})$ , while the $p_{\\mathrm{opt}}$ of filled $\\mathrm{CoSb}_{3}$ and FeNbSb system with larger $m^{*}$ are above $10^{21}~\\mathrm{cm}^{-3}$ (Fig. 1b). Note that even though these heavy-band thermoelectric materials have large $m^{*}$ and hence low $\\mu$ , their optimal power factors are 2–3 times higher than the state-of-the-art light-band PbTe, which is an important reason making these heavy-band thermoelectrics promising for power generation. An immediate question arises that what is the effective optimization strategy for achieving high $z T$ heavy-band thermoelectric materials? \n\nAlloying (substitution or doping) creates point-defect scattering for phonons due to mass fluctuation and strain field fluctuation between the host atoms and alloying atoms14, and results in reduced $\\kappa_{\\mathrm{L}}$ . In thermoelectric materials, dopants not only supply carriers to optimize the power factor, but deduce point-defect scattering of phonons to suppress $\\boldsymbol{\\kappa}_{\\mathrm{L}}$ . For light-band thermoelectric semiconductors, the $p_{\\mathrm{opt}}$ is relatively low and a slight content of dopants are enough to optimize the power factor15,16, and the dopants usually contribute less to the $\\kappa_{\\mathrm{L}}$ reduction. By contrast, in heavy-band semiconductors, higher contents of dopants are demanded for optimizing the carrier concentration to reach the same Femi level (Fig. 1c). For example, $\\sim20\\%$ Sn was doped to optimize the power factor of heavy-band $\\boldsymbol{Z}\\mathrm{r}\\mathrm{CoSb}$ compounds17. Such a high content of dopant will also definitely create strong point-defect phonon scattering to reduce $\\kappa_{\\mathrm{L}}$ . Furthermore, stronger point-defect phonon scattering may occur if the doping atoms have larger mass and strain field fluctuations compared with the host atoms (Fig. 1c), which could be an effective strategy for simultaneously optimizing electrical power factor and reducing thermal conductivity in heavy-band thermoelectric materials. \n\nA high Carnot limit, $\\eta_{\\mathrm{c}}=(T_{\\mathrm{H}}-T_{\\mathrm{C}})/T_{\\mathrm{H}},$ needs a large temperature difference between the temperature of hot side, $T_{\\mathrm{H}},$ and temperature of cold side, $T_{\\mathrm{C}},$ of the thermoelectric device. Therefore, high temperature thermoelectric materials with superior properties are highly desirable for power generation operating above $1{,}000\\mathrm{K}.$ Half-Heusler compounds have attracted more and more attention due to their good electrical and mechanical properties and thermal stability at high temperatures11,17–26. The highest $z T s$ of $\\sim1.0$ have been reported for $n$ -type ZrNiSn-based half-Heusler alloys18,20,21,24. But developing high-performance $\\boldsymbol{p}$ -type $\\mathrm{Zr}$ -based half-Heusler compounds is still a big challenge17,24. Recently, we found that $\\boldsymbol{p}$ -type $\\mathrm{Fe(V,Nb)Sb}$ -based heavy-band half-Heusler compounds show great potential as high-temperature thermoelectric materials and a high $z T$ of 1.1 has been reached at $1{,}100\\mathrm{K}$ in $\\mathrm{FeNb}_{1-x}\\mathrm{Ti}_{x}\\mathrm{Sb}$ with high Ti content up to $20\\%^{19,27}$ . Although the $\\kappa_{\\mathrm{L}}$ of T i\u0002-doped FeNbSb is remarkably reduced due to the enhanced point-defect scattering, it is still $\\sim3$ times as high as the calculated minimum $\\kappa_{\\mathrm{L}}$ $(\\sim1\\mathrm{\\breve{W}m}^{-1}\\mathrm{K}^{-1})^{19}$ . To achieve higher $z T$ in $\\boldsymbol{p}$ -type FeNbSb, it is imperative to further suppress its $\\kappa_{\\mathrm{L}}$ . Based on the above consideration and Fig. 1c, selecting the high contents of doping atoms having larger mass and radius differences with the host atoms may lead to further $\\kappa_{\\mathrm{L}}$ reduction at optimal carrier concentration and hence enhanced $z T$ . \n\nHere we indeed demonstrate that the thermoelectric properties of $\\boldsymbol{p}$ -type FeNbSb half-Heusler compound can be significantly enhanced through heavier Hf doping. A record-high $z T$ of up to 1.5 at $1{,}200\\mathrm{K}$ has been obtained in the heavy-band $\\mathrm{FeNb}_{1-x}\\mathrm{Hf}_{x}\\mathrm{Sb}$ alloys. High contents of Hf and $Z\\mathrm{r}$ dopants result in enhanced point-defect scattering of phonons, and the Hf doping at $\\mathrm{Nb}$ site leads to the stronger phonon scattering. Interestingly, the electron–phonon scattering is found to also strongly contribute to the reduced $\\kappa_{\\mathrm{L}}$ at high dopant contents. An eight $n{-}p$ couples prototype half-Heusler thermoelectric module, based on our high-performance $n$ -type $\\mathrm{ZrNiSn}$ (ref. 18) and $\\boldsymbol{p}$ -type FeNbSb compounds, is successfully assembled for the first time in this work. A maximum conversion efficiency of $6.2\\%$ and a power density of $2.2\\mathrm{W}\\mathrm{cm}^{-2}$ under a temperature difference of $655\\mathrm{K}$ are achieved, exhibiting the great potential of low-cost $\\boldsymbol{p}$ -type FeNbSb half-Heusler compounds for high temperature power generation. \n\n# Results \n\n$z T$ enhancement and prototype half-Heusler module. Highquality ${\\mathrm{FeNb}}_{1-x}{\\mathrm{Hf}}_{x}{\\mathrm{Sb}}$ and $\\mathrm{FeNb}_{1-y}\\mathrm{Zr}_{y}\\mathrm{Sb}$ $(x,\\quad y=0{-}0.16)$ samples were fabricated by levitation melting and spark plasma sintering. $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) patterns show that the single phase products were obtained (Supplementary Fig. 1). Figure 2a shows the $z T$ values of these samples. A peak $z T$ of $\\sim1.5$ is reached at $1{,}200\\mathrm{K}$ for $\\mathrm{FeNb}_{0.88}\\mathrm{Hf}_{0.12}\\mathrm{Sb}$ and $\\mathrm{FeNb}_{0.86}\\mathrm{Hf}_{0.14}\\mathrm{Sb}$ , $\\sim40\\%$ higher than that of Ti-doped FeNbSb19, and the $z T s$ are remarkably higher than other well-known state-of-the-art $\\boldsymbol{p}$ -type high-temperature thermoelectric materials over the whole temperature range. As known, the average $z T_{\\mathrm{avg}}$ is more important than the peak $z T$ for thermoelectric device application. The $z T_{\\mathrm{avg}}$ of $\\mathrm{FeNb}_{0.88}\\mathrm{Hf}_{0.12}\\mathrm{Sb}$ sample is calculated to be $\\sim0.8$ and $\\sim1.0$ in the temperature range of 300–1,200 and $500{-}1{,}200\\mathrm{K},$ respectively, even exceeding the industry benchmark set by conventional $\\boldsymbol{p}$ -type SiGe alloys (peak $z T\\dot{=}0.6)^{17}$ . \n\n![](images/9b1db51890d3832837e8bce22d02b2383510042db982b5f999b398b26f537639.jpg) \nFigure 1 | Comparison of transport character of light-band and heavy-band thermoelectric materials. (a) The optimal carrier concentration $p_{\\mathsf{o p t}}$ versus the density of state effective mass $m^{\\star}$ for thermoelectric materials15,16,27,31–33,36,39–45. The solid line is a guide for eyes. (b) Carrier concentration dependence of power factor for the typical light-band $\\mathsf{P b T e}^{15}$ , and the heavy-band system: $\\mathfrak{n}$ -type $Z r N i\\mathsf{S}\\mathsf{n}^{33}$ , $\\mathfrak{n}$ -type filled $\\mathsf{C o S b}_{3}{}^{46}$ and $p$ -type FeNbSb near $800\\mathsf{K}.$ (c) The schematic drawing shows the effect of band structure character on optimal doping content and hence phonon scattering. \n\n![](images/ea33068554dc81467ba99831877ba22ebe6410d03490a53ed068e8b993f6bd7f.jpg) \nFigure 2 | Thermoelectric performance for $\\pmb{p}$ -type FeNbSb-based HH compounds and prototype module. (a) zT comparison for Hf or Zr doped FeNbSb and other typical high temperature $p$ -type thermoelectric materials $17-19,40,47$ . (b) Maximum power output and conversion efficiency as a function of hot side temperature $T_{\\mathsf{H}}$ for the thermoelectric device made from our best $\\mathfrak{n}$ -type ZrNiSn-based alloys and $p$ -type FeNbSb HH compounds. The dash line represents the theoretical conversion efficiency of the module with a maximum value of $11.3\\%$ , assuming no electrical and thermal contact resistances. \n\nTo corroborate the present results, the prototype hightemperature thermoelectric modules with eight $n{-}p$ half-Heusler couples were assembled (Fig. 2b) for the first time based on the best $n$ -type ZrNiSn-based alloys (thermoelectric properties are shown in Supplementary Fig. 2) and $\\boldsymbol{p}$ -type FeNbSb compounds. The dimensions of the thermoelectric module made from the half-Heusler legs are $20\\mathrm{mm}$ by $20\\mathrm{mm}$ by $10\\mathrm{mm}$ thick. Under conditions of hot/cold-side temperatures of 991 K/336 K, the halfHeusler module exhibited a maximum power output of 8.9 W and \n\n$6.2\\%$ conversion efficiency, which is significantly higher than the conversion efficiency of $4.5\\%$ for the commercial half-Heusler modules based on $n$ -type ZrNiSn and $\\boldsymbol{p}$ -type ZrCoSb-based half-Heusler alloys. Extrapolated values indicate that $8.1\\%$ is achievable when the hot-side temperature is up to 1,200 K. The calculated total area power density for this half-Heusler module is about $2.2\\mathrm{W}\\mathrm{cm}^{-2}$ , which is significantly higher than other thermoelectric modules28–30 (Supplementary Table 1). The theoretical conversion efficiency is also calculated for comparison (dash line in Fig. 2b), which is higher than the experimental value. The discrepancy could be due to the matching between $n$ -type and $\\boldsymbol{p}$ -type legs, the insufficient contacting and the large radiation and convection losses and insufficient accuracy of measurement. Especially, the contact resistance contributes to about $3.2\\%$ efficiency loss (Supplementary Discussion). More work is needed to improve the contacting electrical and thermal resistance and use thermal isolation between the half-Heusler legs. \n\nDecoupling of electrical and thermal properties. Why do the $\\boldsymbol{p}$ -type heavy-band ${\\mathrm{FeNb}}_{1-x}{\\mathrm{Hf}}_{x}{\\mathrm{Sb}}$ alloys have so high $z T\\mathrm{s}?$ The thermoelectric properties of $\\mathrm{FeNb}_{1-x}\\mathrm{\\dot{H}f}_{x}\\mathrm{Sb}$ and $\\mathrm{Fe}\\mathrm{\\tilde{N}b}_{1-y}\\mathrm{Zr}_{y}\\mathrm{Sb}$ compounds are presented in Fig. 3, and analysed by using the single parabolic band (SPB) model31,32. The samples are heavily doped and the hole concentration is almost independent of temperature before intrinsic excitation (Supplementary Fig. 3). The electrical conductivity $\\sigma$ of the $\\mathrm{FeNb}_{1-x}\\mathrm{Hf}_{x}\\mathrm{Sb}$ and $\\mathrm{FeNb}_{1-y}\\mathrm{Zr}_{y}\\mathrm{Sb}$ samples shows a metal-like behaviour and follows a temperature dependence of $T^{-1.5}$ (Fig. 3a), implying an acoustic phonon-scattering-dominated charge transport. The Seebeck coefficient $\\alpha$ decreases with increasing carrier concentration (Fig. 3b). The calculated $\\boldsymbol{\\mathfrak{a}}$ by the SPB model agrees well with the experimental data before the intrinsic excitation. The $m^{*}$ was estimated to be $\\sim6.9m_{\\mathrm{e}}$ and almost unchanged at 300 and $800\\mathrm{K},$ as shown in the Pisarenko plot of Fig. 3c, indicating that the valence band structure has weak dependence on temperature and the dopant type of Hf, $Z\\mathrm{r}$ and Ti. \n\nThe carrier concentration dependence of power factor for Hf- and $Z\\mathrm{r}$ -doped FeNbSb samples at $800\\mathrm{K}$ is shown in Fig. 3d, together with Ti doping data19. The optimal power factor ranges from 4.3 to $5.5\\times10^{-3}\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-2}$ at $p_{\\mathrm{opt}}$ of $\\sim2\\times10^{21}\\mathrm{cm}^{\\simeq3}$ which are relatively high values among established thermoelectric materials and comparable to the optimized $n$ -type ZrNiSn-based half-Heusler compounds33. Figure 3d also indicates that the power factors of Hf-doped FeNbSb are higher than that of $Z\\mathbf{r}-$ or Ti-doped samples. Further analysis shows that the Hf dopant is more efficient in supplying carriers than Zr and Ti (Supplementary Fig. 4). Thus at the carrier concentration of $\\sim2\\stackrel{.}{\\times}10^{21}\\mathrm{cm}^{-3}$ for $\\boldsymbol{p}$ -type FeNbSb, the doping content of Hf, $Z\\mathrm{r}$ and Ti is about 12, 14 and $16\\%$ , respectively (Supplementary Fig. 4a). The corresponding room temperature carrier mobility for these samples are 18.4, 15.0 and $13.8\\dot{\\mathrm{cm}}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1},$ indicating that the less doping content for Hf-doped FeNbSb is beneficial for relatively higher carrier mobility due to the reduced alloy scattering of carriers. Therefore, at the same carrier concentration, the Hf-doped FeNbSb has higher power factors than $Z\\mathrm{r}-$ and Ti-doped samples (Supplementary Fig. 4b). It is noteworthy that the different dopants also generate different effects on the thermal conductivity (Fig. 3d). The heavier Hf dopant leads to the $\\sim30\\%$ lower thermal conductivity compared with the $Z\\mathrm{r}$ dopant, consistent with the discussion relevant to Fig. 1c. \n\nReduced lattice thermal conductivity and mechanisms. The temperature dependences of $\\kappa$ and $\\kappa_{\\mathrm{L}}$ of ${\\mathrm{FeNb}}_{1-x}{\\mathrm{Hf}}_{x}{\\mathrm{Sb}}$ and $\\mathrm{FeNb}_{1-y}\\mathrm{Zr}_{y}\\mathrm{Sb}$ compounds are presented in Fig. 4. The $\\kappa_{\\mathrm{L}}$ was obtained by subtracting the electronic component $\\kappa_{\\mathrm{e}}$ from the total thermal conductivity k. $\\kappa_{\\mathrm{e}}$ was calculated via Wiedemann– Franz relationship $\\kappa_{\\mathrm{e}}=L\\sigma T$ , where $L$ is the Lorenz number determined under the SPB approximation32. Figure 4a shows the $\\kappa$ of Hf- and $\\mathrm{Zr}$ -doped FeNbSb compounds are lower than that of FeNbSb. The decrease in $\\kappa$ mainly results from the greatly suppressed $\\kappa_{\\mathrm{L}}$ . As shown in Fig. 4b, with the same doping content, the $\\kappa_{\\mathrm{L}}$ of Hf-doped FeNbSb is lower than that of $Z\\mathbf{r}-$ and Ti-doped samples, and the high-temperature $\\kappa_{\\mathrm{L}}$ of $\\mathrm{FeNb}_{0.8}\\mathrm{Ti}_{0.2}\\mathrm{Sb}$ is only close to that of $\\mathrm{FeNb_{0.9}H f_{0.1}S b}$ , suggesting that Hf dopant leads to significantly reduced $\\kappa_{\\mathrm{L}}$ in FeNbSb even at a low content. The $\\kappa_{\\mathrm{L}}$ of $\\mathrm{FeNb}_{1-x}\\mathrm{Hf}_{x}\\mathrm{Sb}$ decreases greatly with increasing Hf content. Especially, at 300 and $1{,}000\\mathrm{K}$ the $\\kappa_{\\mathrm{L}}$ of $\\mathrm{FeNb}_{0.86}\\mathrm{Hf}_{0.14}^{-}\\mathrm{Sb}$ has $\\sim80\\%$ and $\\sim70\\%$ reduction respectively, compared with that of FeNbSb, which is a key to the high $z T$ in this composition. \n\n![](images/0b5a9ce7a1c9572de1e2fa3bf3bc7339e906e6550d8c9a40bb7e709f83a9cea0.jpg) \nFigure 3 | Thermoelectric properties for $\\boldsymbol{\\mathsf{F e N b}}_{1}\\mathbf{\\Pi}_{-}\\mathbf{\\Pi}_{\\mathbf{X}}\\mathbf{H}\\mathbf{f}_{x}\\mathbf{S}\\mathbf{b}$ and $\\bar{\\mathsf{F e N b}}_{1}\\mathsf{\\mathbf{b}}_{1}_{-\\mathsf{y}}\\mathsf{Z r}_{\\mathsf{y}}\\mathsf{S b}$ samples. (a) Electrical conductivity $\\sigma$ (b) Seebeck coefficient $\\alpha$ . The $\\alpha\\left(\\bullet\\right)$ and power factor $\\alpha^{2}\\sigma$ and thermal conductivity (d) of $H f-$ and $Z\\boldsymbol{\\mathsf{r}}$ -doped FeNbSb as a function of carrier concentration, together with the data for $\\upuparrows$ -doped FeNbSb19. The solid lines in b–d were calculated by the SPB model. \n\n![](images/a97e654bc50a4e90155c40bccb99208eefa3f8dfd4a9209bcf800addd9898201.jpg) \nFigure 4 | Thermal conductivity for $\\boldsymbol{\\mathsf{F e N b}}_{1}_{-}\\boldsymbol{\\mathsf{x}}\\boldsymbol{\\mathsf{H f}}_{\\boldsymbol{x}}\\boldsymbol{\\mathsf{S b}}$ and $\\bar{\\mathsf{F e N b}}_{1}\\mathsf{\\mathbf{b}}_{1}_{-\\mathsf{y}}\\mathsf{Z r}_{\\mathsf{y}}\\mathsf{S b}$ samples. (a) Total thermal conductivity $\\kappa$ $(\\pmb{6})$ Lattice thermal conductivity $\\kappa_{\\downarrow}$ . The solid curves in b are calculated using t h\u0002e Callaway model3 6\u0002,37. For comparison, $\\kappa_{\\mathrm{L}}$ of $T_{\\dot{\\mathsf{I}}}$ -doped FeNbSb is also shown19. (c) The calculated disorder parameter $\\boldsymbol{{\\cal T}}$ for the samples, where $\\boldsymbol{{\\Gamma_{\\mathrm{m}}}}$ (square) and $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{\\mathrm{{s}}}$ (circle) are mass and strain field fluctuation disorder parameters, respectively.14,34 ${\\cal T}_{\\mathrm{total}}={\\cal T}_{\\mathrm{m}}+{\\cal T}_{\\mathrm{s}}$ . (d) Comparison of experimental and calculated $\\kappa_{\\mathrm{L}}$ for the samples at $300\\mathsf{K}.$ The dash and solid curves are calculated without and with electron-phonon scattering, respectively. U, B, PD and EP denote the phonon-phonon Umklapp process, boundary, point-defect and electron-phonon scattering, respectively. \n\nWhy is Hf dopant more efficient in suppressing $\\kappa_{\\mathrm{L}}$ of FeNbSb despite of lower optimal content? As aforementioned, high content of dopants will create strong point-defect scattering of phonons, leading to the suppressed $\\kappa_{\\mathrm{L}}$ . Hf doping at Nb sites will deduce more remarkable point-defect scattering than $\\mathrm{Zr}$ and Ti because of the larger mass and radius differences between Hf and Nb. For comparison, Fig. 4c presents the calculated disorder parameter $\\boldsymbol{{\\cal T}}$ (larger $\\boldsymbol{{\\cal T}}$ indicates stronger point-defect scattering of phonons14,34,35) for Hf and $Z\\mathrm{r}$ at $\\mathrm{Nb}$ sites, which obviously shows that the Hf creates stronger mass and strain field fluctuations, leading to lower $\\kappa_{\\mathrm{L}}$ in $\\bar{\\mathrm{FeNb}}_{1-x}\\mathrm{Hf}_{x}\\mathrm{Sb}$ . \n\nThe $\\kappa_{\\mathrm{L}}$ of the samples was further calculated by the Callaway model19,36,37. Phonon–phonon Umklapp process, grain boundary and point-defect scattering of phonons were firstly considered in the modelling. At low doping content, the calculated $\\kappa_{\\mathrm{L}}$ has a good agreement with the experimental results (Fig. 4d). However, at high doping contents, the calculated $\\kappa_{\\mathrm{L}}$ significantly deviates from the experimentally values, suggesting that some other scattering sources should also contribute to the reduced $\\kappa_{\\mathrm{L}}$ at high Hf or $\\mathrm{zr}$ contents. With increasing dopant content, the carrier concentration largely increases up to $10^{\\cdot21}\\mathrm{cm}^{-3}$ . The electron– phonon interaction, an important part to scatter phonons in narrow semiconductors38, may exist in the $\\boldsymbol{p}$ -type FeNbSb heavy-band system. With the electron–phonon scattering evolved, a good agreement between the experimental data and the calculated curves is reached (Fig. 4d). To corroborate this result, temperature dependence of $\\kappa_{\\mathrm{L}}$ was calculated for $\\mathrm{FeNb}_{1-x}\\mathrm{Hf}_{x}\\mathrm{Sb}$ samples, and there is a good consistency with the experimental $\\kappa_{\\mathrm{L}}$ (Fig. 4b), indicating the enhanced electron– phonon scattering of phonons also contributes to the reduced $\\kappa_{\\mathrm{L}}$ for $\\mathrm{FeNb}_{1-x}\\mathrm{Hf}_{x}\\mathrm{Sb}$ and $\\mathrm{FeNb}_{1-y}\\mathrm{Zr}_{y}\\mathrm{Sb}$ , especially at high doping contents. The similar phenomenon is also found in other thermoelectric materials36. Thus the simultaneously enhanced point-defect and electron–phonon scattering of phonons concurrently contribute to the reduced $\\kappa_{\\mathrm{L}}$ in the heavy-band ${\\mathrm{FeNb}}_{1-x}{\\mathrm{Hf}}_{x}{\\mathrm{Sb}}$ system. \n\n# Discussion \n\nIn summary, by rationally selecting the heavier dopants at high contents, the interrelated thermoelectric parameters can be decoupled and the simultaneous optimization of electrical power factor and significant reduction in thermal conductivity can be achieved in heavy-band thermoelectric materials. Record-high $z T$ of 1.5 in $\\boldsymbol{p}$ -type ${\\mathrm{FeNb}}_{1-x}{\\mathrm{Hf}}_{x}{\\mathrm{Sb}}$ heavy-band half-Heusler compounds demonstrates the effective optimization strategy for achieving high thermoelectric performance. A prototype thermoelectric module made of $n$ -type ZrNiSn-based alloys and $\\boldsymbol{p}$ -type FeNbSb compounds exhibits a high conversion efficiency of $6.2\\%$ and a high power density of $2.2\\mathrm{W}\\mathrm{cm}^{-2}$ at a temperature difference of $655\\mathrm{K}$ These findings highlight the realistic prospect of high-temperature thermoelectric modules based on halfHeusler alloys with low cost, excellent mechanical properties and stability. \n\n# Methods \n\nSynthesis. The ingots with nominal composition ${\\mathrm{FeNb}}_{1-x}{\\mathrm{Hf}}_{x}S{\\mathrm{b}}$ and $\\mathrm{FeNb}_{1-y}\\mathrm{Zr}_{y}\\mathrm{Sb}$ $(x,\\stackrel{\\cdot}{y}=0{-}0.16)$ were prepared by levitation melting of stoichiometric amount of Fe (piece, $99.97\\%$ ), Nb (foil, $99.8\\%$ , Hf (piece, $99.99\\%$ ), $Z\\mathrm{r}$ (foil, $99.99\\%$ ) and Sb (block, $99.999\\%$ ) under an argon atmosphere for several minutes. The ingots were remelted for four times to ensure homogeneity. The obtained ingots were mechanically milled (Mixer Mill MM200, Retsch) for $\\boldsymbol{4\\mathrm{h}}$ under argon protection. The obtained powders were loaded into the graphite die and compacted by spark plasma sintering (SPS-1050, Sumitomo Coal Mining Co.) at $^{1,123\\mathrm{K}}$ for $10\\mathrm{min}$ under $65\\mathrm{{MPa}}$ in vacuum. The as-sintered samples, of which the relative densities were found to be $\\sim95\\%$ , were annealed at $^{1,073\\mathrm{K}}$ for 3 days. \n\nCharacterization. Phase structures of the samples were investigated by XRD on a RigakuD/MAX-2550PC diffractometer using Cu $\\mathrm{K}_{\\mathfrak{X}}$ radiation $(\\breve{\\lambda}_{0}=1.\\breve{5}406\\textrm{\\AA})$ . The XRD patterns of ${\\mathrm{FeNb}}_{1-x}{\\mathrm{Hf}}_{x}{\\mathrm{Sb}}$ and $\\mathrm{FeNb}_{1-y}\\mathrm{Zr}_{y}\\mathrm{Sb}$ show a single phase that can be indexed to the half-Heusler phase with a cubic MgAgAs-type crystal structure (space group, $\\mathrm{F}43\\mathrm{m}$ ) as shown in Supplementary Fig. 1. The lattice parameter of the samples increases with increasing dopant content as shown in Supplementary Fig. 5. The chemical compositions were checked by electron probe microanalysis (EPMA, JEOL and JXA-8100), which show that the actual compositions are close to the nominal ones (Supplementary Table 1). Scanning electron microscope and energy dispersive X-ray spectroscopy mapping were used to characterize the phase and compositional homogeneity (Supplementary Fig. 6). The average grain size of the sample was determined to be $\\sim0.8\\upmu\\mathrm{m}$ from the transmission electron microscope (FEI, Tecnai G2 F30 S-Twin) image (Supplementary Fig. 6). \n\nMeasurements. The Seebeck coefficient and electrical conductivity from 300 to $1{,}200\\mathrm{K}$ were measured on a commercial Linseis LSR-3 system using a differential voltage/temperature technique and a d.c. four-probe method. The accuracy is $\\pm5\\%$ and $\\pm3\\%$ , respectively. The thermal conductivity $\\kappa$ was calculated by using $\\kappa{=}D\\rho C_{\\mathrm{p}},$ where $\\rho$ is the sample density estimated by the Archimedes method. The thermal diffusivity $D$ and specific heat $C_{\\mathrm{p}}$ were measured by a laser flash method on Netzsch LFA457 instrument with a Pyroceram standard (Supplementary Fig. 7). The accuracy is $\\pm3\\%$ and $\\pm5\\%$ , respectively. The low-temperature Hall coefficients from 20 to $300\\mathrm{K}$ were measured using a Mini Cryogen Free Measurement System (Cryogenic Limited, UK). The carrier concentration $p_{\\mathrm{H}}$ was calculated by $\\displaystyle P_{\\mathrm{H}}=1/(e R_{\\mathrm{H}})$ , where $e$ is the unit charge and $R_{\\mathrm{H}}$ is the Hall coefficient. The estimated error of Hall coefficient is within $\\pm10\\%$ . The carriers mobility $\\mu_{\\mathrm{H}}$ was calculated by $\\mu_{\\mathrm{H}}=\\sigma R_{\\mathrm{H}}$ . The samples with highest $z T$ were repeatedly measured in Zhejiang University and Shanghai Institute of Ceramics, Chinese Academy of Science, and the results show good consistency (Supplementary Fig. 8). The high-temperature thermal stability of the sample was checked through the thermogravimetric analysis (Supplementary Fig. 9) and the accuracy is $5\\%$ . \n\nThermoelectric module. For the eight $n{-}p$ couple prototype module assembly, the cylindrical half-Heusler pucks were diced into legs of square $4\\mathrm{mm}$ by $4\\mathrm{mm}$ . Then the $n$ -type and $\\boldsymbol{p}$ -type half-Heusler legs were connected to metallic interconnects using high-temperature braze. The modules contain a total of 16 legs joined into 8 $n{-}p$ couples, all connected electrically in series and thermally in parallel. The power output, internal resistance and energy conversion efficiency of the half-Heusler prototype modules were evaluated in vacuum by using PEM-2 testing system (ULVAC-RIKO, Inc.). The electrodes coexist stably with $p/n$ half-Heusler alloys in the module’s working temperature range from 300 to $1{,}000\\mathrm{K}$ The accuracy of measurement for output power and conversion efficiency is about $10\\mathrm{-}15\\%$ . \n\n# References \n\n1. Snyder, G. J. & Toberer, E. S. Complex thermoelectric materials. Nat. Mater. 7, 105–114 (2008). \n2. Zhao, L. D. et al. Ultralow thermal conductivity and high thermoelectric figure of merit in SnSe crystals. Nature 508, 373–377 (2014). \n3. Pei, Y. Z. et al. Convergence of electronic bands for high performance bulk thermoelectrics. Nature 473, 66–69 (2011). \n4. Heremans, J. P. et al. Enhancement of thermoelectric efficiency in PbTe by distortion of the electronic density of states. Science 321, 554–557 (2008). \n5. Biswas, K. et al. High-performance bulk thermoelectrics with all-scale hierarchical architectures. Nature 489, 414–418 (2012). \n6. Toberer, E. S., Zevalkink, A. & Snyder, G. J. Phonon engineering through crystal chemistry. J. Mater. Chem. 21, 15843–15852 (2011). \n7. Ioffe, A. F. Semiconductor Thermoelements and Thermoelectric Cooling (Infosearch, 1957). \n8. Goldsmid, H. J. Introduction to Thermoelectricity (Springer, 2010). \n9. Sales, B. C., Mandrus, D. & Williams, R. K. Filled skutterudite antimonides: a new class of thermoelectric materials. Science 272, 1325–1328 (1996). \n10. Tritt, T. M. Holey and unholey semiconductors. Science 283, 804–805 (1999). \n11. Xie, H. H. et al. Beneficial contribution of alloy disorder to electron and phonon transport in half-Heusler thermoelectric materials. Adv. Funct. Mater. 23, 5123–5130 (2013). \n12. Yang, J. et al. Trends in electrical transport of $\\boldsymbol{p}$ -type skutterudites $R\\mathrm{Fe}_{4}\\mathrm{Sb}_{12}$ ( $R={\\bf N}{\\bf a}$ , K, Ca, Sr, Ba, La, Ce, Pr, Yb) from first-principles calculations and Boltzmann transport theory. Phys. Rev. B 84, 235205 (2011). \n13. Yang, J. et al. Evaluation of half-Heusler compounds as thermoelectric materials based on the calculation electrical transport properties. Adv. Funct. Mater. 18, 2880–2888 (2008). thermal conductivity of ZrNiSn-based thermoelectric compounds. Appl. Phys. Lett. 85, 1140–1142 (2004). \n15. Pei, Y. Z. et al. Optimum carrier concentration in n-type PbTe thermoelectrics. Adv. Energy Mater. 4, 1400486 (2014). \n16. Wang, H., Pei, Y. Z., LaLonde, A. D. & Snyder, G. J. Weak electron-phonon coupling contributing to high thermoelectric performance in n-type PbSe. Proc. Natl Acad. Sci. USA 109, 9705–9709 (2012). \n17. Culp, S. R. et al. $\\mathrm{Zr,Hf)Co(Sb,Sn)}$ half-Heusler phases as high-temperature $\\mathrm{\\Omega^{\\prime}>700^{\\circ}C)}$ $\\boldsymbol{p}$ -type thermoelectric materials. Appl. Phys. Lett. 93, 022105 (2008). \n18. Yu, C. et al. High performance half-Heusler thermoelectric materials $\\mathrm{Hf_{1-x}Z r_{x}N i S n_{1-y}S b_{y}}$ prepared by levitation melting and spark plasma sintering. Acta Mater. 57, 2757–2764 (2009). \n19. Fu, C. G., Zhu, T. J., Liu, Y. T., Xie, H. H. & Zhao, X. B. Band engineering of high performance p-type FeNbSb based half-Heusler thermoelectric materials for figure of merit $z T>1$ . Energy Environ. Sci. 8, 216–220 (2015). \n20. Schwall, M. & Balke, B. Phase separation as a key to a thermoelectric high efficiency. Phys. Chem. Chem. Phys. 15, 1868–1872 (2013). \n21. Chen, S. et al. Effect of Hf concentration on thermoelectric properties of nanostructured N-type half-Heusler materials $\\mathrm{Hf_{x}Z r_{1-x}N i S n_{0.99}S b_{0.01}}$ . Adv. Energy Mater. 3, 1210–1214 (2013). \n22. Graf, T., Felser, C. & Parkin, S. S. P. Simple rules for the understanding of Heusler compounds. Prog. Solid State Chem. 39, 1–50 (2011). \n23. Chen, S. & Ren, Z. Recent progress of half-Heusler for moderate temperature thermoelectric applications. Mater. Today 16, 387–395 (2013). \n24. Xie, W. et al. Recent advance in nanostructured thermoelectric half-Heusler compounds. Nanomaterials 2, 379–412 (2012). \n25. Schmitt, J., Gibbs, Z. M., Snyder, G. J. & Felser, C. Resolving the true band gap of ZrNiSn half-Heusler thermoelectric materials. Mater. Horiz. 2, 68–75 (2015). \n26. Joshi, G. et al. NbFeSb-based p-type half-Heuslers for power generation applications. Energy Environ. Sci. 7, 4070–4076 (2014). \n27. Fu, C. G. et al. High band degeneracy contributing to high thermoelectric performance in p-type half-Heusler compounds. Adv. Energy Mater. 4, 1400600 (2014). \n28. Bartholome´, K. et al. Thermoelectric modules based on half-Heusler materials produced in large quantities. J. Electron. Mater. 43, 1775–1781 (2014). \n29. Mikami, M., Kobayashi, K. & Tanaka, S. Power generation performance of thermoelectric module consisting of Sb-doped Heusler $\\mathrm{Fe}_{2}\\mathrm{VAl}$ sintered alloy. Mater. Trans. 52, 1546–1548 (2011). \n30. Salvador, J. R. et al. Conversion efficiency of skutterudite-based thermoelectric modules. Phys. Chem. Chem. Phys. 16, 12510–12520 (2014). \n31. Liu, X. H. et al. Low electron scattering potentials in high performance $\\mathrm{Mg}_{2}\\mathrm{Si}_{0.45}\\mathrm{Sn}_{0.55}$ based thermoelectric solid solutions with band convergence. Adv. Energy Mater. 3, 1238–1244 (2013). \n32. May, A. F., Toberer, E. S., Saramat, A. & Snyder, G. J. Characterization and analysis of thermoelectric transport in n-type $\\mathrm{Ba}_{8}\\mathrm{Ga}_{16-x}\\mathrm{Ge}_{30+x}.$ Phys. Rev. B 80, 125205 (2009). \n33. Xie, H. H. et al. The intrinsic disorder related alloy scattering in ZrNiSn half-Heusler thermoelectric materials. Sci. Rep. 4, 6888 (2014). \n34. Wang, H., LaLonde, A. D., Pei, Y. Z. & Snyder, G. J. The criteria for beneficial disorder in thermoelectric solid solutions. Adv. Funct. Mater. 23, 1586–1596 (2013). \n35. Abeles, B. Lattice thermal conductivity of disordered semiconductor alloys at high temperatures. Phys. Rev. 131, 1906–1911 (1963). \n36. Shi, X. Y., Pei, Y. Z., Snyder, G. J. & Chen, L. Optimized thermoelectric properties of $\\mathrm{Mo}_{3}\\mathrm{Sb}_{\\mathrm{7-x}}\\mathrm{Te}_{\\mathrm{x}}$ with significant phonon scattering by electrons. Energy Environ. Sci. 4, 4086–4095 (2011). \n37. Callaway, J. Model for lattice thermal conductivity at low temperatures. Phys. Rev. 113, 1046–1051 (1959). \n38. Delaire, O. et al. Phonon softening and metallization of a narrow-gap semiconductor by thermal disorder. Proc. Natl Acad. Sci. USA 108, 4725–4730 (2011). \n39. Wang, H., Schechtel, E., Pei, Y. Z. & Snyder, G. J. High thermoelectric efficiency of n-type PbS. Adv. Energy Mater. 3, 488–495 (2013). \n40. Vining, C. B., Laskow, W., Hanson, J. O., Vanderbeck, R. R. & Gorsuch, P. D. Thermoelectric properties of pressure-sintered $\\mathrm{Si}_{0.8}\\mathrm{Ge}_{0.2}$ thermoelectric alloys. J. Appl. Phys. 69, 4333–4340 (1991). \n41. Fu, C. G. et al. Electron and phonon transport in Co-doped $\\mathrm{FeV_{0.6}N b_{0.4}S b}$ half-Heusler thermoelectric materials. J. Appl. Phys. 114, 134905 (2013). \n42. Pei, Y. Z. et al. Improving thermoelectric performance of caged compounds through light-element filling. Appl. Phys. Lett. 95, 042101 (2009). \n43. Bux, S. K. et al. Glass-like lattice thermal conductivity and high thermoelectric efficiency in $\\mathrm{Yb}_{9}\\mathrm{Mn}_{4.2}\\mathrm{Sb}_{9}$ . J. Mater. Chem. A 2, 215–220 (2014). \n44. He, Y. et al. High thermoelectric performance in non-toxic earth abundant copper sulfide. Adv. Mater. 26, 3974–3978 (2014). \n45. Zhu, T. J., Gao, H., Chen, Y. & Zhao, X. B. Ioffe–Regel limit and lattice thermal conductivity reduction of high performance $(\\mathrm{AgSbTe}_{2})_{15}(\\mathrm{GeTe})_{85}$ thermoelectric materials. J. Mater. Chem. A 2, 3251–3256 (2014). \n46. Shi, X. et al. Multiple-filled skutterudites: High thermoelectric figure of merit through separately optimizing electrical and thermal transports. J. Am. Chem. Soc. 133, 7837–7846 (2011). \n47. Brown, S. R., Kauzlarich, S. M., Gascoin, F. & Snyder, G. J. $\\mathrm{Yb}_{14}\\mathrm{MnSb}_{11}$ : New high efficiency thermoelectric material for power generation. Chem. Mater. 18, 1873–1877 (2006). \n\n# Acknowledgements \n\nWe would like to thank Professor Xun Shi and Mr Dudi Ren from Shanghai Institute of Ceramics for the repeated measurement of thermoelectric properties and device simulation, respectively. This work was supported by the National Basic Research Program of China (2013CB632500), the Nature Science Foundation of China (51171171), the Program for New Century Excellent Talents in University (NCET-12- 0495) and the Key Research Program of Chinese Academy of Sciences (KGZD-EW-T06). \n\n# Author contributions \n\nC.F. and T.Z. designed the experiment. C.F. and Y.L. prepared the samples and carried out thermoelectric property measurements. C.F. and T.Z. analysed the experimental data and established the thermoelectric transport model. S.B., Y.T. and L.C. fabricated the \n\nprototype thermoelectric module and measured its conversion efficiency. C.F., S.B., L.C., X.Z. and T.Z. wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions. \n\nHow to cite this article: Fu, C. et al. Realizing high figure of merit in heavy-band $P$ -type half-Heusler thermoelectric materials. Nat. Commun. 6:8144 doi: 10.1038/ncomms9144 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms7929", + "DOI": "10.1038/ncomms7929", + "DOI Link": "http://dx.doi.org/10.1038/ncomms7929", + "Relative Dir Path": "mds/10.1038_ncomms7929", + "Article Title": "Na+ intercalation pseudocapacitance in graphene-coupled titanium oxide enabling ultra-fast sodium storage and long-term cycling", + "Authors": "Chen, CJ; Wen, YW; Hu, XL; Ji, XL; Yan, MY; Mai, LQ; Hu, P; Shan, B; Huang, YH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Sodium-ion batteries are emerging as a highly promising technology for large-scale energy storage applications. However, it remains a significant challenge to develop an anode with superior long-term cycling stability and high-rate capability. Here we demonstrate that the Na+ intercalation pseudocapacitance in TiO2/graphene nullocomposites enables high-rate capability and long cycle life in a sodium-ion battery. This hybrid electrode exhibits a specific capacity of above 90mAh g(-1) at 12,000mAg(-1) (similar to 36 C). The capacity is highly reversible for more than 4,000 cycles, the longest demonstrated cyclability to date. First-principle calculations demonstrate that the intimate integration of graphene with TiO2 reduces the diffusion energy barrier, thus enhancing the Na+ intercalation pseudocapacitive process. The Na-ion intercalation pseudocapacitance enabled by tailor-deigned nullostructures represents a promising strategy for developing electrode materials with high power density and long cycle life.", + "Times Cited, WoS Core": 1061, + "Times Cited, All Databases": 1081, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000353704100037", + "Markdown": "# Na þ intercalation pseudocapacitance in graphene-coupled titanium oxide enabling ultra-fast sodium storage and long-term cycling \n\nChaoji Chen1,\\*, Yanwei Wen1,\\*, Xianluo Hu1, Xiulei Ji2, Mengyu Yan3, Liqiang Mai3, Pei Hu1, Bin Shan1 \n& Yunhui Huang1 \n\nSodium-ion batteries are emerging as a highly promising technology for large-scale energy storage applications. However, it remains a significant challenge to develop an anode with superior long-term cycling stability and high-rate capability. Here we demonstrate that the ${\\mathsf{N a}}^{+}$ intercalation pseudocapacitance in $\\Gamma_{1}\\bigcirc_{2}$ /graphene nanocomposites enables high-rate capability and long cycle life in a sodium-ion battery. This hybrid electrode exhibits a specific capacity of above $90\\mathsf{m A}\\mathsf{h g}^{-1}$ at $12,000\\mathsf{m A g}^{-1}$ ( $\\cdot\\sim36{\\sf C})$ . The capacity is highly reversible for more than 4,000 cycles, the longest demonstrated cyclability to date. First-principle calculations demonstrate that the intimate integration of graphene with $\\mathsf{T i O}_{2}$ reduces the diffusion energy barrier, thus enhancing the ${\\mathsf{N a}}^{+}$ intercalation pseudocapacitive process. The Na-ion intercalation pseudocapacitance enabled by tailor-deigned nanostructures represents a promising strategy for developing electrode materials with high power density and long cycle life. \n\nver the past few decades, tremendous efforts have been focused on the development of lithium ion batteries (LIBs) used in portable electric devices and electric vehicles because of their high energy density and long cycle $\\mathrm{life}^{1-5}$ . Nowadays, the main concerns about LIBs lie in the growing cost and limited resources of lithium. In contrast, sodium ion batteries (SIBs) represent potential alternatives for large-scale energy storage because of low cost and resource abundance6–8. Recently, a variety of cathode materials have been investigated for SIBs, for instance, $\\mathrm{Na}_{3}\\mathrm{V}_{2}(\\mathrm{PO}_{4})_{3}$ (ref. 9), $\\mathrm{P}2\\mathrm{-}\\mathrm{Na}_{x}\\mathrm{VO}_{2}$ (ref. 10), olivine-type sodium metal phosphates11 and Prussian blue12. For anode materials in SIBs, various carbon materials have been reported because of their relatively high capacity and cyclability13–15. Among them, graphite is an intriguing material with different lithium and sodium storage properties $(372\\mathrm{mAhg}^{-1}$ in LIBs, but less than $35\\mathrm{\\mAh{g}^{-1}}$ in SIBs). Intriguingly, Wang and co-workers14 reported on an expanded graphite that delivered a high capacity of $284\\mathrm{mAhg}^{-1}$ and long cycle life by expanding the interlayer of graphite from 0.34 to $0.43\\mathrm{nm}$ . Co-intercalation between graphite and diglymebased electrolyte could also achieve a relatively high capacity of $\\sim90\\mathrm{mAhg}^{-1}$ and long cycle life15. Recent findings have shown that the anode materials for SIBs based on alloy-type (for example, metallic and intermetallic materials16–19) and conversion-type (for example, sulfides20–23) exhibited high initial capacity, but suffered from poor cyclability most likely due to the large volume change and the sluggish kinetics. In addition, organic anode materials (for example, $\\mathrm{\\tilde{Na}_{2}C_{8}H_{4}O_{4})}$ and carboxylate-based materials have been investigated as anode materials for $\\operatorname{SIBs}^{24,25}$ , but the electronic conductivity and cyclability still remain the significant challenge. Besides the aforementioned anode candidates, metal oxide materials26, especially Ti-based oxide materials were also proposed as anode materials for SIBs. Xiong and co-workers27 reported the first $\\mathrm{TiO}_{2}$ -based anode for SIBs by using amorphous $\\mathrm{\\bar{TiO}}_{2}$ nanowires grown on a Ti substrate, which delivered a gradually increasing capacity of up to $120\\mathrm{mAhg^{-1}}$ at $50\\mathrm{mAg^{-1}}$ . Recently, Myung et al.28 reported that a thin carbon layer coated on anatase $\\mathrm{TiO}_{2}$ nanorods helped enhance rate capability. They also proposed that the sodiation process of anatase nanorods is an intercalation reaction instead of an alloying reaction. Despite these advances, the long-term cyclability and detailed sodium storage mechanisms still need to be further explored. Another type of $\\mathrm{TiO}_{2}$ , termed $\\mathrm{TiO}_{2}$ -B, has also aroused interest as an anode for $\\mathrm{SIB}s^{29}$ . For insertion-type anodes, the tradeoff between structural stability and capacity should be taken into account. It is highly challenging but desirable to find an effective way to enhance the electrochemistry without sacrificing the stability of the host structure. \n\nRecently, pseudocapacitive charge storage that is not a diffusion-controlled process demonstrates superior high-rate performance and reversibility30–33. Previous works by Dunn and co-workers30 show great promise towards high-rate electrodes in LIBs driven by an intercalation pseudocapacitive mechanism. Inspired by this, it is highly expected to achieve superior rate capability and long cycle life of SIBs by introducing intercalation pseudocapacitive charge storage mechanism in electrodes. As far as we know, there have been several investigations focused on the surface redox reaction pseudocapacitance in a thin-film electrode of SIBs with most of the active material at the surface or subsurface31,34, rather than the intercalation pseudocapacitance. \n\nHere we report a SIB anode material, the graphene-coupled $\\mathrm{TiO}_{2}$ sandwich-like hybrid (referred to as $\\mathrm{\\bfG}{-}\\mathrm{Ti}\\mathrm{\\bfO}_{2}^{\\cdot},$ ). The $\\mathrm{\\bar{G}{-}\\bar{T}i O_{2}}$ electrode exhibits a superior rate capability and a super long-term cyclability. We first demonstrated that intercalation pseudocapacitance dominates the charge storage process in the $\\bar{\\bf G}{-}\\mathrm{Ti}{\\bf O}_{2}$ SIB anode, which contributes to the excellent rate capability and long-term stability. Furthermore, density functional theory (DFT) calculations were further performed to identify the structural characteristics and the sodiation mechanism of the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ electrode. \n\n# Results \n\nMorphology and structure of the sandwich-like $\\mathbf{G}{-}\\mathbf{TiO}_{2}$ . The $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{\\bfO}_{2}$ hybrid was prepared by a rapid microwave-assisted in-situ reduction-hydrolysis route using $\\mathrm{TiCl}_{3}$ and graphene oxide (GO) in ethylene glycol as the precursor (the detailed procedure is described in the Methods section). A subsequent heat treatment in air removed the residual organics and improved the crystallinity of the product. The experimental and simulated $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) patterns of the product with Rietveld refinement are presented in Fig. 1a. The XRD peaks can be indexed to the monoclinic $\\mathrm{TiO}_{2}$ -B phase (JCPDF No. 74–1940) and tetragonal anatase (JCPDF No. 65–5714), respectively. Anatase $\\mathrm{TiO}_{2}$ may originate from the partial transformation of metastable $\\mathrm{TiO}_{2}$ -B under heating treatment35–38. Refinement results quantify a mass percentage of ca. $76.9\\%$ for the $\\mathrm{TiO}_{2}$ -B phase (the calculation details are presented in Supplementary Method), which can be further confirmed by Raman analysis based on the peak areas of Raman spectra $\\cdot\\sim74\\%$ , Supplementary Fig. 1). The morphology of the product was identified by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). As shown in Fig. 1b, three-dimensional microsheet-connected networks with macropores could be distinctly observed. The SEM image at a higher magnification (Fig. 1c) reveals that there are numerous nanosheet arrays on both sides of the graphene sheets, forming a sandwich-like microstructure. The TEM image in Fig. 1d further confirms the unique nanosheet-on-microsheet sandwich-like architecture. Meanwhile, a nanoporous feature could also be observed in Fig. $^{\\mathrm{1d,e}}$ , which is further evidenced by the nitrogen adsorption–desorption measurement (Supplementary Fig. 2). Interestingly, numerous tiny nanoclusters $(\\sim3-5\\mathrm{nm})$ are also formed on the graphene sheet (Fig. 1e). The high-resolution TEM image (Fig. 1f) reveals clear lattices with spacings of 0.62 and $0.35\\mathrm{nm}$ , respectively, indicating the existence of both $\\mathrm{TiO}_{2}$ -B and anatase $\\mathrm{TiO}_{2}$ . The carbon content in the $\\mathrm{G}{-}\\mathrm{TiO}_{2}$ hybrid is evaluated to be about $10\\mathrm{wt\\%}$ by thermogravimetry (TG) analysis (Supplementary Fig. 3). \n\nThe surface chemical bonding state of the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ hybrid was determined by electron paramagnetic resonance (EPR) and X-ray photoelectron spectroscopy (XPS). The sample of $\\mathrm{TiO}_{2}$ nanosheets (T-NSs) without GO do not exhibit characteristic EPR response, whereas the $\\mathrm{G}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ hybrid presents a distinct EPR signal with a $g$ value of 1.948, indicating the existence of $\\mathrm{Ti}^{3+}$ on the surface of the material $(\\mathrm{Fig.\\1g)^{39,\\sharp0}}$ . The existence of $\\mathrm{Ti}^{3+}$ was further confirmed by the high-resolution XPS spectra of C 1 s and O 1 s (Fig $\\mathrm{1h,i}$ ). The peaks at 285.0, 286.5 and $288.5\\mathrm{eV}$ are associated with the carbon species from the graphene or the atmosphere. The peak at $283.5\\mathrm{eV}$ suggests the existence of the Ti-C bonds in the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ (ref. 40), which is also revealed by the O 1 s peak at $531.5\\mathrm{eV}$ for the O- $\\mathrm{Ti}^{3+}$ bond. The combination of the EPR and XPS results suggests that $\\mathrm{TiO}_{2}$ nanosheets and/or nanoclusters are chemically bonded with the graphene matrix rather than physical adsorption. \n\nSodium ion storage performance. Figure 2 demonstrates the representative galvanostatic cycling profiles for the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ electrode obtained at $500\\mathrm{mAg^{-1}}$ . The potential profiles are sloping curves, delivering a discharge capacity of 149 mA h $\\mathbf{g}^{-1}$ . Importantly, the polarization between the charge/discharge curves is very small $\\Delta E=\\sim0.1\\mathrm{V}.$ ). Furthermore, the sodium ion storage is mainly below $1.5\\mathrm{V}$ with an average discharging voltage plateau at $\\mathrm{\\sim}0.8\\mathrm{V}$ , much lower than those in a lithium cell ( $\\mathrm{.}1.5\\mathrm{V}$ for $\\mathrm{TiO}_{2}$ -B and $1.75\\mathrm{V}$ for anatase $\\mathrm{TiO}_{2}$ ). Further DFT calculations of the voltage profiles based on the sodium intercalation energies in bulk $\\mathrm{Ti}\\bar{\\mathrm{O}}_{2}$ -B with sodium concentrations of $x=0.065–0.5$ demonstrate an average discharging voltage of $\\mathrm{\\sim}1.0\\mathrm{V}$ , slightly higher $(\\sim0.2\\:\\mathrm{V})$ than the experimental value (Supplementary Fig. 4). Despite the calculation error caused by the overbinding of sodium metal and problems with dispersion term41, there are two factors that result in the differences between the experimental and calculated voltages: (i) polarization in the electrode material; (ii) sodiation energetic kinetics differences between nanosized and bulk $\\mathrm{TiO}_{2}$ materials. As polarization is dependent on the current density (namely, higher current densities would lead to bigger polarizations), the difference in the applied current densities of the experimental and calculated data $(\\bar{5}00\\mathrm{mAhg^{-1}}$ for the former and infinitely near zero at the equilibrium state for the latter) should be partially responsible for the difference between the two voltages. Previous works reveal that the alkalization potential of nanosized materials could differ from their corresponding bulk materials, due to the alkalization energetic kinetics differences between them42. Lower average lithiation potentials in nanosized $\\mathrm{TiO}_{2}$ than bulk $\\mathrm{TiO}_{2}$ materials have been observed in several $\\mathrm{TiO}_{2}$ -Li cells43,44. Similar effects on the average sodiation potentials are observed in the present work, possibly resulting from the ultrafine nanocrystals in the $\\mathrm{TiO}_{2}$ -graphene hybrid. As a negative electrode, the lower operation voltage in SIBs than in LIBs would lead to a higher energy density of full cells45. Meanwhile, the relatively higher sodiation voltage than hard carbon $(\\sim0.1\\mathrm{V})$ and ${\\mathrm{Na}}_{2}{\\mathrm{Ti}}_{3}{\\mathrm{O}}_{7}$ $(0.3\\mathrm{V})$ makes the $\\mathrm{\\bar{G}}{\\cdot}\\mathrm{TiO}_{2}$ much safer and avoids the formation of dendrites upon cycling46. \n\nAnother attractive property of the chemically bonded $\\mathrm{{G-TiO}}_{2}$ electrode is the superior rate performance, as presented in Fig. 2b. It can deliver reversible capacities of 265, 187, 149, 125, 114 and $102\\mathrm{mAhg^{-1}}$ at $50,\\ 200,\\ 500,\\ 1,500,\\ 3,000$ , and $6{,}000\\mathrm{mAg^{-1}}$ respectively. More excitingly, at an extremely high current density of $\\mathrm{i}2{,}000\\mathrm{\\dot{m}A g^{-1}}$ (ca $36\\mathrm{~C~}_{:}$ , assuming $\\mathrm{~i~}\\mathrm{C}=330\\mathrm{mAg}^{-1},$ , a surprisingly high capacity of more than $90\\mathrm{{mAh}\\ g^{-1}}$ can still be retained. To the best of our knowledge, this is the best rate capability among all reported Ti-based anode materials as well as the hard carbon and other metal oxides for $\\mathrm{SIBs}^{28,29,47,48}$ . \n\n![](images/a70d161190fba5d6382adddfda202b2e5f02f3e9513f3050590f298fe3c2fc56.jpg) \nFigure 1 | Morphology and structure of the $\\mathsf{\\pmb{G}}\\mathrm{-}\\mathsf{T i}\\mathsf{\\pmb{O}}_{2}$ hybrid. (a) XRD patterns for the $\\mathsf{G}\\mathrm{-}\\mathsf{T i O}_{2}$ product with Rietveld refinement, quantifying the content of ca $76.9\\mathrm{wt.\\%}$ for the $\\mathsf{T i O}_{2}$ -B phase. Calculation details were supplemented in Supplementary Method 1. (b) Low-magnification SEM image for $\\mathsf{G}\\mathrm{-}\\mathsf{T i O}_{2},$ demonstrating a three-dimensional porous morphology. (c) High-magnification SEM image for $\\mathsf{G}\\mathrm{-}\\mathsf{T i O}_{2},$ revealing the structural detail of an individual microsheet. (d,e) TEM images for $\\mathsf{G}\\mathrm{-}\\mathsf{T i O}_{2},$ indicating that tiny nanosheet arrays and nanoparticles co-anchor on the graphene sheet. $(\\pmb{\\uparrow})$ High-resolution TEM image, clear lattices with spacings of 0.62 and $0.35\\mathsf{n m}$ are assigned to the (001) plane of $\\mathsf{T i O}_{2}$ -B and (101) plane of anatase, respectively. $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ EPR spectra for the $\\mathsf{G}\\mathrm{-}\\mathsf{T i O}_{2}$ and T-NSs products. (h,i) High-resolution XPS spectra of C 1 s and O 1 s in the $\\mathsf{G}\\mathrm{-}\\mathsf{T i O}_{2}$ product. \n\n![](images/e553f086d6bed4e126952b9a17f21438629082479e0366d84cdfa17d44e46245.jpg) \nFigure 2 | Electrochemical performance of the $\\mathsf{\\pmb{G}}\\mathrm{-}\\mathsf{T i}\\mathsf{\\pmb{O}}_{2}$ electrode. (a) Galvanostatic cycling profile with a narrow $\\Delta E$ (b) Rate performance at various current densities from 50 to $12,000\\mathsf{m A g}^{-1}$ . (c) Charge–discharge profiles from selected cycles of 100th to 4,000th at $500\\mathsf{m A g}^{-1}$ . (d) Long-term cycling performance at a current density of $500\\mathsf{m A}\\mathsf{g}^{-1}$ $(\\sim2~\\mathsf{C})$ . \n\nLong-term cyclability is crucial but challenging for rechargeable SIBs, due to the difficulty in the insertion/extraction of the large sodium ions within the host, as well as the side reactions between the electrode and the electrolyte upon long-term cycling. In this regard, we have evaluated the cycling stability of the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{\\bfO}_{2}$ electrode. Figure 2d shows the long-term cycling performance of the $\\mathrm{{G-TiO}}_{2}$ electrode for over 4,300 cycles at a current rate of $500\\mathrm{mAg^{-1}}$ . After a slow capacity fading in the initial dozens of cycles, a reversible capacity of $120\\mathrm{\\mAhg^{-1}}$ keeps unchanged during the subsequent cycles, indicating a superior long-term cyclability. As far as we know, this is the longest cycle life up to date for both anode and cathode materials for SIBs using nonaqueous electrolytes7–29,32–34,47,48. We should also note that the Coulombic efficiency increased gradually up to $91.8\\%$ during the initial cycles. The irreversible capacity loss during initial cycles may result from the formation of a solid electrolyte interface film (caused by reactions between the surface –OH groups of titania and the carbonate-based electrolyte)49, and the irreversible trapping of sodium ions at active sites of the graphene matrix50. It was reported that a pre-sodiation or chemical treatment could mitigate the irreversible capacity $\\scriptstyle\\log s s^{28,49}$ . By replacing polyvinylidene fluoride (PVDF) with sodium polyacrylate (PAA-Na) as the binder or pretreating the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{\\bfO}_{2}$ hybrid material with butyl lithium, the initial Coulombic efficiency can be enhanced from $31.4\\%$ to $\\sim57.0\\%$ and $58.4\\%$ , respectively (Supplementary Fig. 5). Furthermore, a combined use of the PAA-Na binder and pretreatment leads to a much higher initial Coulombic efficiency, up to $80.6\\%$ (Supplementary Fig. 5 and Supplementary Table 1). Our preliminary results demonstrate that the irreversible capacity loss of the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ electrode upon cycling could be further reduced by optimizing the binder or the electrode surface. Figure 2c shows the galvanostatic charge–discharge profiles for the 100th, $500\\mathrm{{th}.}$ $\\bar{1},000{\\mathrm{th}}.$ , and 4,000th cycles. They possess an average voltage plateau at $\\mathrm{\\sim}0.8\\mathrm{V}$ , revealing the structural stability and the high reversibility of the insertion/extraction of sodium ions within the host material. When the potential window is narrowed to $0.05-1.5\\mathrm{V}$ , there is no significant change of the voltage curves (Supplementary Fig. 6), despite a slightly decrease in discharge capacity $(\\sim1\\dot{1}0\\dot{\\mathrm{mA}}\\mathrm{hg}^{-1}$ , ca $10\\mathrm{\\dot{mA}\\dot{h}g^{-1}}$ lower than the former). For comparison, we also explored the electrochemical performances of two pristine $\\mathrm{TiO}_{2}$ nanostructures: (i) T-NSs that were prepared at the similar conditions for $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ except using GO and (ii) $\\mathrm{TiO}_{2}$ nanobelts (T-NBs) obtained according to ref. 51. It was found that the electrode made of pristine $\\mathrm{TiO}_{2}$ nanosheets exhibited a much lower capacity of ${\\sim}70\\mathrm{mAhg^{-1}}$ corresponding to $0.21~\\mathrm{{\\Na}}$ insertion into a formula of $\\mathrm{TiO}_{2}$ (Supplementary Fig. 7a). Its capacity decayed drastically to below $20\\mathrm{\\dot{mA}h g^{-1}}$ after 50 cycles. Similarly, the performance of the T-NBs electrode was also much worse than that of $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ (Supplementary Fig. 7b). The synergistic effect from nanostructuring and hybridization might contribute to the substantial enhancement of the $\\mathrm{G}{-}\\mathrm{Ti}\\mathrm{O}_{2}^{-}$ electrode, where the electronic/ionic conductivity is improved, and high reversibility of chemically bonded $\\mathrm{\\bfG}{-}\\mathrm{Ti}\\mathrm{O}_{2}$ is achieved. \n\nFurthermore, STEM and HR-TEM images, energy dispersive X-ray elemental mappings and selected-area electron diffraction patterns confirm that the microstructure of the strongly coupled $\\bar{\\bf G}{-}\\mathrm{Ti}{\\bf O}_{2}$ hybrid is well maintained even after $^{4,300}$ discharge/ charge cycles (Supplementary Fig. 8). More importantly, the unique graphene- $\\cdot\\mathrm{TiO}_{2}$ interface in the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ hybrid provides a more feasible pathway for $\\mathrm{Na}^{+}$ insertion/extraction and prompts an intercalation pseudocapacitive behaviour of $\\mathrm{Na^{+}}$ in the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{\\bfO}_{2}$ electrode. It is highly beneficial to the fast transport of $\\mathrm{Na^{+}}$ , thus leading to superior rate capability and long cycle life. \n\nKinetics analysis. Cyclic voltammetry (CV) has been proven to be a powerful technique to evaluate the electrochemical kinetics of electrode materials towards $\\mathrm{Li^{+}}$ or $\\mathrm{Na^{+}}$ (refs 30–33). Here, kinetic analysis based on CV analysis was carried out to gain further insight into the electrochemistry of the $\\mathrm{G}{\\cdot}\\mathrm{TiO}_{2}/\\mathrm{Na}$ cell. Figure 3a displays the typical CV curves for the $\\mathrm{{G-TiO}}_{2}$ electrode during initial five cycles at a scan rate of $0.1\\mathrm{mVs^{-1}}$ . A pair of broad cathodic/anodic peaks are located at $\\sim0.75/0.85\\mathrm{V}$ with a small voltage offset of $0.1\\mathrm{V}$ , which agree well with the galvanostatic cycling profile. Meanwhile, the CV curves from the 3rd to the 5th cycle are overlapped, showing an excellent reversibility of the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ electrode. The CV curves at various scan rates from 0.1 to $100\\mathrm{mVs^{-1}}$ display similar shapes with broad peaks during both cathodic and anodic processes. It is interesting to note that the small peak separations $(\\sim0.1\\mathrm{V})$ are nearly identical if the scan rate increases from 0.1 to $2\\mathrm{mVs^{-1}}$ (inset of Fig. 3b and Supplementary Fig. 9), demonstrating small polarization at high rates. According to the relationship between the measured current $(i)$ and the scan rate $(\\nu)^{52}$ : \n\n![](images/57ffaea7adb203fe2d03825e7129fb7a918cc67572144bcefe753c1f1f3d18d2.jpg) \nFigure 3 | Kinetics analysis of the electrochemical behaviour towards $\\pmb{{\\mathsf{M}}}\\mathbf{a}^{+}$ for the $\\mathsf{\\pmb{G}}\\mathrm{-}\\mathsf{T i}\\mathsf{\\pmb{O}}_{2}$ electrode. (a) CV curves from 1st to 5th cycles at a scan rate of $0.1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . The open circuit potential (OCP) is ca $2.38{\\vee}.$ . $(\\pmb{6})$ CV curves at various scan rates, from 0.1 to $100\\mathrm{mVs}^{-1}$ . (c) Determination of the $b$ -value using the relationship between peak current and scan rate. (d) Capacity versus scan rate–1/2. (e) Separation of the capacitive and diffusion currents in $\\mathsf{G}\\mathrm{-}\\mathsf{T i O}_{2}$ at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . (f) Contribution ratio of the capacitive and diffusion-controlled charge versus scan rate. \n\n$$\n\\boldsymbol{i}=\\boldsymbol{\\mathsf{a}}\\boldsymbol{\\nu}^{b}\n$$ \n\nthe $b$ -value can be determined by the slope of the $\\log(\\nu)\\ –\\log(i)$ plots. In particular, the $b$ -value of 0.5 indicates a total diffusioncontrolled behaviour, whereas 1.0 represents a capacitive process. The $\\log(\\nu)\\ –\\log(i)$ plots for the $\\mathrm{\\bar{G}{-}\\bar{T}i O_{2}}$ electrode is shown in Fig. 3c. The $b$ -value of 0.94 for both cathodic and anodic peaks can be quantified at scan rates from 0.1 to $10\\mathrm{mVs^{-1}}$ , suggesting the kinetics of capacitive characteristics. A decrease of slope takes place at scan rates above $10\\mathrm{mVs^{-1}}$ , reflecting a decrease of $b$ -value from 0.94 to 0.56 for both cathodic and anodic peaks. Similar observations were reported on a $T–\\mathrm{Nb}_{2}\\mathrm{O}_{5}/\\mathrm{Li}$ cell by Dunn et al.30 The limitation to the rate capability should be attributed to an increase of the ohmic contribution and/or diffusion constrains upon an ultra-fast scan rate. The $b$ -value of 0.56 close to 0.5 evidences the limitation of the slow diffusion. The plot of capacity versus $\\nu^{-1/2}$ demonstrates that the capacity does not vary significantly as the scan rate increases in the range of $0.1{-}2\\mathrm{m}\\mathrm{\\check{V}}\\ s^{-1}$ (Fig. 3d). This indicates that capacitive contributions are independent of the scan rate. In contrast, the linear decrease of capacity upon the increase of scan rate in the region of $>10\\mathrm{mV}\\dot{\\mathrm{s}^{-1}}$ reflects a rate-limited diffusion process. The total capacitive contribution at a certain scan rate could be quantified on the base of separating the specific contribution from the capacitive and diffusion-controlled charge at a fixed voltage. As shown in Fig. 3e, the diffusion-controlled charge is mainly generated at around the peak voltage, indicating that the diffusion process is feasible at this region and corresponds to a redox reaction between Ti4 þ /Ti3 þ (ref. 44). Based on the quantification, $78.2\\%$ of the total charge (therefore, the capacity) is capacitive at a scan rate of $5\\mathrm{m}\\mathrm{\\check{V}}\\mathrm{s}^{-1}$ . Contribution ratios between the two different processes at other scan rates were also quantified. The quantified results (Fig. 3f) show that the capacitive capacity is improved gradually with increasing the scan rate, and finally reaches a maximum value of $90.2\\%$ at $\\mathrm{i0mVs^{-1}}$ . \n\n# Discussion \n\nThe $\\mathrm{Na}^{+}$ intercalation pseudocapacitive behaviour of the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ hybrid is attributed to the unique chemically bonded hybrid structure that provides a more feasible channel for $\\mathrm{Na^{+}}$ insertion/extraction in the graphene– $\\mathrm{\\cdotTiO}_{2}$ interface. Firstprinciple calculations were performed to obtain further insight into the $\\mathrm{Na}^{+}$ dynamics in the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ hybrid and to testify this hypothesis. As the main phase of the hybrid is $\\mathrm{TiO}_{2}–\\mathrm{B}$ , only $\\mathrm{TiO}_{2}$ -B was taken into account in the first-principle calculations. From the voltage profiles (Fig. 2e), it is observed that the voltage drops monotonically from $1.15\\mathrm{V}$ down to $0.05\\mathrm{V}$ . This suggests a solid-solution reaction of sodium with $\\mathrm{TiO}_{2}$ at an average voltage of $\\mathrm{\\sim}0.8\\mathrm{V}$ . The calculated voltage profiles show a similar dropping trend, despite the slightly higher values for the calculated voltages (Supplementary Fig. 4). \n\n![](images/35376880e7c2a4bf84c67a39318955865b384426ba6e1f4cbfe159be86958bd5.jpg) \nFigure 4 | Na diffusion in the partially bonded graphene– $\\cdot\\boldsymbol{\\Pi}\\mathbf{0}_{2}$ -B (001) interface. (a) Illustration of the partially bonded graphene– $\\cdot\\mathsf{T i O}_{2}$ -B (001) interface. (b) Top-view of a, illustrating the Na diffusion path along the [010] direction from Na1 to Na10 sites. (c) Migration activation energy of the ${\\mathsf{N a}}^{+}$ ion diffusing along the [010] direction in bulk $\\mathsf{T i O}_{2}$ -B, fully bonded and partially bonded graphene– $\\cdot\\mathsf{T i O}_{2}$ -B (001) interface calculated with DFT. \n\nTo gain further insight into the sodiation dynamics, sodiumdiffusion barriers of various trajectories were also investigated by first-principle calculations. In bulk $\\mathrm{TiO}_{2}–\\mathrm{B}$ , three typical sodium-diffusion paths were considered, as presented in Supplementary Fig. 10. The energy barriers for path ${\\bf i},$ ii and iii were 3.0, 4.9 and $2.2\\mathrm{eV}$ , respectively, which are similar to the previous report on a $\\mathrm{TiO}_{2}$ -B-Li battery41. It is reasonable that the energy barriers for sodium insertion into the $\\mathrm{TiO}_{2}$ -B host are higher than that of lithiation, considering the bigger radius of $\\mathrm{Na}^{+}$ . It means that path i along the [001] direction and path iii along the [010] direction are more accessible for $\\mathrm{Na}^{+}$ diffusion than path ii ([100] direction). Interestingly, much more feasible paths could be formed at the fully bonded graphene– $\\mathrm{TiO}_{2}$ -B interface in the hybrid (Supplementary Fig. 11). The energy barriers for path iii are reduced to be $1.5\\mathrm{eV}$ . Considering the existence of surface defects in the $\\mathrm{TiO}_{2}$ nanocrystals, surface $-\\mathrm{OH}$ groups49, and the mismatching between $\\mathrm{TiO}_{2}$ -B and graphene lattices, surface oxygen atoms cannot be entirely bonded with the carbon atoms of graphene. The dominated situation should be the partially bonded model, where a part of surface O atoms would be passivated by a neighbouring surface O atom $(\\mathrm{Ti}-\\mathrm{O}_{\\mathrm{surf.}}-\\mathrm{O}_{\\mathrm{surf.}}-\\mathrm{Ti})$ or surface –OH groups $(\\mathrm{Ti}-\\mathrm{O}_{\\mathrm{surf.}}-\\mathrm{H})$ , rather than the formation of $\\mathrm{Ti-\\mathrm{\\bar{O}-\\mathrm{\\bar{C}}}}$ bonds, to achieve a lower total energy of the system (Supplementary Fig. 12). Owing to the reduction of bonded surface oxygen atoms, the restriction to graphene by the $\\mathrm{TiO}_{2}$ -B nanocrystals becomes weaker, resulting in the slightly bending of graphene plate (Fig. 4). Consequently, the tunnel along the [010] direction will be more open and feasible for sodium transport, giving rise to a much lower activation energy barrier of $\\mathrm{\\sim}0.\\bar{2}\\mathrm{eV}$ (Fig. 4, unbounded surface O atoms reconstitute to form $\\mathrm{Ti}-\\mathrm{O}_{\\mathrm{{surf.}}}-\\mathrm{O}_{\\mathrm{{surf.}}}-\\mathrm{Ti})$ or $0.45\\mathrm{eV}$ (Supplementary Fig. 13, unbounded surface O atoms were passivated by the –OH groups). The isolated sodium diffusion should be much different from a certain concentration region in this system. In fact, the pervious results on the lithium diffusion in anatase $\\mathrm{TiO}_{2}$ with the Li concentration of $10{-}50\\%$ revealed that an increase in Li concentration resulted in a decrease in effective barrier (namely, it would be more diffusive with an increased Li concentration)53. It is much likely to occur in our system that the diffusion of sodium ions will be more feasible upon increasing sodium concentration. These calculation results agree well with the experimental results presented above. \n\nIn summary, the chemically bonded graphene- $\\cdot\\mathrm{TiO}_{2}$ hybrid demonstrates a reversible capacity of 265 mA h $\\mathbf{g}^{-1}$ at $50\\mathrm{m}\\mathrm{\\dot{A}g^{-1}}$ and more than $90\\mathrm{mAhg^{-1}}$ at $12,\\dot{0}00\\mathrm{mAg^{-1}}$ ( $\\left(\\sim36\\mathrm{C}\\right)$ , displaying the best rate capability compared with the ever reported Ti-based anodes for SIBs. More encouragingly, the hybrid electrode shows an ultra-long cycling life as demonstrated by over 4,300 cycles, representing the best cyclability among all ever reported SIBs using nonaqueous electrolytes. Kinetics analysis reveals an interesting $\\mathrm{\\Delta\\tilde{Na}^{+}}$ intercalation pseudocapacitive behaviour in the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{\\bfO}_{2}$ sodium cell and a high contribution of capacitive charge. This pseudocapacitive behaviour is highly beneficial to fast charge storage and long-term cyclability. Further sodiation dynamics analysis based on first-principle calculations shows that the hybridization of graphene with $\\mathrm{TiO}_{2}$ nanocrystals provides a more feasible channel at the graphene– $\\cdot\\mathrm{TiO}_{2}$ interface for sodium intercalation/deintercalation with a much lower energy barrier. Our findings will open up new opportunities for developing electrode materials of SIBs and hold great promise for the development of long-life SIBs for next-generation large-scale energy storage applications. \n\n# Methods \n\nMaterials synthesis. The $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ hybrid was prepared by a microwave-assisted reduction-hydrolysis route. The mixture of $\\mathrm{TiCl}_{3}$ $\\mathrm{{1ml}}$ , $15\\mathrm{wt\\%}$ in dilute hydrochloric acid solution), ethylene glycol ( $:15\\mathrm{ml}$ , anhydrous) and GO $(2\\bmod{.}$ $1\\dot{3}\\mathrm{mg}\\mathrm{ml}^{-1}$ , prepared via a modified Hummers method54) was sealed in a glass vessel and treated in a microwave synthesizer (2.45 GHz, 300 W, Discover S-Class, CEM) at $155^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . The black product was collected by centrifugation, and washed with DI water and ethanol for five times. After dry at $80^{\\circ}\\mathrm{C}$ overnight, the black powder was heated at $350^{\\circ}\\mathrm{C}$ for $^{4\\mathrm{h}}$ in air to remove the residual organics, and finally the $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{\\bfO}_{2}$ product was obtained. In a control experiment, the T-NSs product was prepared by a similar method to that of $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ except the use of GO. The T-NBs product was prepared according to the previous report51. For the pretreatment procedure, the materials treated with bultyl lithium were obtained by dispersing $\\mathrm{\\bfG}{\\mathrm{-}}\\mathrm{Ti}\\mathrm{O}_{2}$ powder $\\mathrm{128\\mg)}$ in $25\\mathrm{ml}$ of hexane and adding dropwise into a suspension of bultyl lithium hexane solution $\\mathrm{\\langle0.25ml}$ , 1.6 M). After stirred for $^{3\\mathrm{h}}$ the suspension was filtered and washed with hexane, and dried under vacuum at $60^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{h}}$ . \n\nMaterials characterization. The morphology and structure of the products were investigated by SEM (SIRION200), TEM, XRD (PANalytical B.V.) and XPS (VG MultiLab 2000 system with a monochromatic A1 Ka X-ray source, Thermo VG Scientific). TG analysis was carried out in air atmosphere from 40 to $750^{\\circ}\\mathrm{C}$ at a heating rate of $10^{\\circ}\\dot{\\mathrm{C}}\\operatorname*{min}^{-1}$ . Nitrogen adsorption and desorption isotherms and pore size distribution were collected at $77\\mathrm{K}$ using a Micromeritics ASPA 2020 analyzer. EPR measurements were performed on a Bruker EMX spectrometer equipped with a cylindrical cavity operating at a $100\\mathrm{kHz}$ field modulation at 77 K. Raman spectra were obtained on a Renishaw Invia spectrometer with an $\\mathrm{Ar^{+}}$ laser of $514.5\\mathrm{nm}$ at room temperature. \n\nElectrochemical measurements. The working electrodes were prepared by mixing $70\\mathrm{wt\\%}$ active material, $20\\mathrm{wt\\%}$ super $\\mathrm{~\\bf~P~}$ and $10\\mathrm{{wt\\%}}$ PVDF dissolved in $N.$ -methyl-2-pyrrolidone (for comparison, PVDF was also replaced by PAA-Na to mitigate the irreversible capacity loss), and then coated onto a Cu foil and dried at $80^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ before testing. The mass loading of the active material is about $2.5\\mathrm{mgcm}^{-2}$ . The testing cell contains the working electrode, sodium metal as the counter and reference electrode, glass fibre membrane (GF/D, Whatman) as the separator and $\\mathrm{1MNaClO_{4}}$ in a mixture of ethylene carbonate and propylene carbonate (2:1 by volume) as the electrolyte. Galvanostatic charge–discharge tests were carried out on a Land Battery Measurement System (Land) at various current densities with a cutoff potential window of $0.05{-}3\\mathrm{\\V}$ at room temperature. CV measurements at various scan rates from 0.1 to $100\\mathrm{mVs^{-1}}$ were carried out on a PARSTAT 2273 potentiostat. \n\nDFT calculations. First-principle calculations were performed using the Vienna Ab Initio Simulation Package55 within the projector augmented-wave approach. The generalized gradient approximation (GGA) exchange-correlation function developed by Perdew, Burke and Ernzerhof56 was used and the cutoff of the kinetic energy was set to $400\\mathrm{eV}$ for all calculations. As the Ti-based oxides are strongly correlated electron systems, the $\\mathrm{DFT+U}$ method was used with the Dudarev approach57 implemented in Vienna Ab Initio Simulation Package, where U is the on-site Coulomb parameter to calculate the average voltages of Na intercalating into $\\mathrm{TiO}_{2}$ -B. On the other hand, the standard GGA functional is used instead of the $\\mathrm{GGA}+\\mathrm{U}$ functional for the diffusion barrier calculations to avoid the mixing charge transfer barrier of alkali atoms hoping overestimated by the $\\mathrm{GGA}+\\mathrm{U}$ method45. The k-points were sampled on a $\\Gamma$ -centred Monkhorst-Pack grid of $4\\times8\\times6$ for the unit cell and the geometry was allowed to relax until Hellmann– Feynman force on each atom was less than $0.05\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . The minimum energy paths and activation barriers of Na diffusion along different channels were calculated by the climbing nudged elastic band method58 for the bulk $\\mathrm{TiO}_{2}$ -B and $\\mathrm{TiO}_{2}$ -B–graphene interface. For Na diffusion in bulk $\\mathrm{TiO}_{2}$ -B, a $1\\times2\\times1$ supercell was used to minimize the interaction between the periodic images. To model the $\\mathrm{TiO}_{2}$ -B–graphene interface, a $1\\times2$ supercell of $\\mathrm{TiO}_{2}$ -B (001) slab square lattice $(12.29\\times7.5\\dot{5}\\dot{\\mathrm{A}})$ with thickness of about $10\\mathrm{\\AA}$ was constructed to match with the graphene square lattice with a $3\\times3$ supercell $(12.78\\times7.38\\mathrm{\\AA})$ , including $36\\mathrm{~C~}$ atoms. The lattice mismatch in each direction was less than $5\\%$ . For more precise results, a vacuum thickness of $20\\textup{\\AA}$ was set along $\\boldsymbol{c}$ axis for the $\\mathrm{TiO}_{2}$ -B–graphene to avoid the interaction between neighbouring images. \n\n# References \n\n1. Bruce, P. G., Scrosati, B. & Tarascon, J. M. Nanomaterials for rechargeable lithium batteries. Angew. Chem. Int. Ed. 47, 2930–2946 (2008). \n2. Dunn, B., Kamath, H. & Tarascon, J. M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n3. Goodenough, J. B. Electrochemical energy storage in a sustainable modern society. Energy Environ. Sci. 7, 14–18 (2013). \n4. Ellis, B. L., Lee, K. T. & Nazar, L. F. Positive electrode materials for Li-Ion and Li-batteries. Chem. Mater. 22, 691–714 (2010). \n5. Choi, N. S. et al. Challenges facing lithium batteries and electrical double-layer capacitors. Angew. Chem. Int. Ed. 51, 9994–10024 (2012). \n6. Islam, M. S. & Fisher, C. A. J. Lithium and sodium battery cathode materials: computational insights into voltage, diffusion and nanostructural properties. Chem. Soc. Rev. 43, 185–204 (2014). \n7. Sun, Y. et al. Direct atomic-scale confirmation of three-phase storage mechanism in $\\mathrm{Li}_{4}\\mathrm{Ti}_{5}\\mathrm{O}_{12}$ anodes for room-temperature sodium-ion batteries. Nat. Commun 4, 1870 (2013). \n8. Wang, Y. et al. A zero-strain layered metal oxide as the negative electrode for long-life sodium-ion batteries. Nat. Commun 4, 2365 (2013). \n9. Jian, Z. L. et al. Superior electrochemical performance and storage mechanism of $\\mathrm{Na}_{3}\\mathrm{V}_{2}(\\mathrm{PO}_{4})_{3}$ cathode for room-temperature sodium-ion batteries. Adv. Energy Mater 3, 156–160 (2013). \n10. Guignard, M. et al. $\\mathrm{P}2\\mathrm{-}\\mathrm{Na}_{x}\\mathrm{VO}_{2}$ system as electrodes for batteries and electroncorrelated materials. Nat. Mater. 12, 74–80 (2013). \n11. Lee, K. T., Ramesh, T. N., Nan, F., Botton, G. & Nazar, L. F. Topochemical synthesis of sodium metal phosphate olivines for sodium-ion batteries. Chem. Mater. 23, 3593–3600 (2011). \n12. Lu, Y. H., Wang, L., Cheng, J. G. & Goodenough, J. B. Prussian blue: a new framework of electrode materials for sodium batteries. Chem. Commun. 48, 6544–6546 (2012). \n13. Lotfabad, E. M. et al. High-density sodium and lithium ion battery anodes from banana peels. ACS Nano 8, 7115–7129 (2014). \n14. Wen, Y. et al. Expanded graphite as superior anode for sodium-ion batteries. Nat. Commun 5, 4033 (2014). \n15. Jache, B. & Adelhelm, P. Use of graphite as a highly reversible electrode with superior cycle life for sodium-ion batteries by making use of co-intercalation phenomena. Angew. Chem. Int. Ed. 53, 10169–10173 (2014). \n16. Farbod, B. et al. Anodes for sodium ion batteries based on tin-germaniumantimony alloys. ACS Nano 8, 4415–4429 (2014). \n17. Xu, Y. H., Zhu, Y. J., Liu, Y. H. & Wang, C. S. Electrochemical performance of porous carbon/tin composite anodes for sodium-ion and lithium-ion batteries. Adv. Energy Mater 3, 128–133 (2013). \n18. Yu, D. Y. W. et al. High-capacity antimony sulphide nanoparticle-decorated graphene composite as anode for sodium-ion batteries. Nat. Commun 4, 2922 (2013). \n19. Wu, L. et al. Sb-C nanofibers with long cycle life as an anode material for highperformance sodium-ion batteries. Energy Environ. Sci. 7, 323–328 (2014). \n20. Qu, B. et al. Layered $\\mathrm{SnS}_{2}$ -reduced graphene oxide composite–a high-capacity, high-rate, and long-cycle life sodium-ion battery anode material. Adv. Mater. 26, 3854–3859 (2014). \n21. David, L., Bhandavat, R. & Singh, G. $\\ensuremath{\\mathrm{MoS}}_{2}$ graphene composite paper for sodium-ion battery electrodes. ACS Nano 8, 1759–1770 (2014). \n22. Wang, Y. et al. Reversible sodium storage via conversion reaction in $\\mathrm{MoS}_{2}/\\mathrm{C}$ composite. Chem. Commun. 50, 10730–10733 (2014). \n23. Zhu, C., Mu, X., van Aken, P. A., Yu, Y. & Maier, J. Single-layered ultrasmall nanoplates of $\\ensuremath{\\mathrm{MoS}}_{2}$ embedded in carbon nanofibers with excellent electrochemical performance for lithium and sodium storage. Angew. Chem. Int. Ed. 53, 2152–2156 (2014). \n24. Park, Y. et al. Sodium terephthalate as an organic anode material for sodium ion batteries. Adv. Mater. 24, 3562–3567 (2012). \n25. Abouimrane, A. et al. Sodium insertion in carboxylate based materials and their application in $3.6\\mathrm{V}$ full sodium cells. Energy Environ. Sci. 5, 9632–9638 (2012). \n26. Oh, S.-M. et al. Advanced $\\mathrm{Na[Ni_{0.25}F e_{0.5}M n_{0.25}]O_{2}/C\\mathrm{-Fe_{3}O_{4}}}$ sodium-ion batteries using EMS electrolyte for energy storage. Nano Lett. 14, 1620–1626 (2014). \n27. Xiong, H., Slater, M. D., Balasubramanian, M., Johnson, C. S. & Rajh, T. Amorphous $\\mathrm{TiO}_{2}$ nanotube anode for rechargeable sodium ion batteries. J. Phys. Chem. Lett. 2, 2560–2565 (2011). \n28. Kim, K. T. et al. Anatase titania nanorods as an intercalation anode material for rechargeable sodium batteries. Nano Lett. 14, 416–422 (2014). \n29. Huang, J. P. et al. Electrochemical sodium storage of $\\mathrm{TiO}_{2}(\\mathrm{B})$ nanotubes for sodium ion batteries. RSC Adv 3, 12593–12597 (2013). \n30. Augustyn, V. et al. High-rate electrochemical energy storage through $\\mathrm{Li^{+}}$ intercalation pseudocapacitance. Nat. Mater. 12, 518–522 (2013). \n31. Chen, Z. et al. High-performance sodium-ion pseudocapacitors based on hierarchically porous nanowire composites. ACS Nano 6, 4319–4327 (2012). \n32. Yu, P. F., Li, C. L. & Guo, X. X. Sodium storage and pseudocapacitive charge in textured $\\mathrm{Li}_{4}\\mathrm{Ti}_{5}\\mathrm{O}_{12}$ thin films. J. Phys. Chem. C 118, 10616–10624 (2014). \n33. Raju, V. et al. Superior cathode of sodium-ion batteries: orthorhombic $\\mathrm{V}_{2}\\mathrm{O}_{5}$ nanoparticles generated in nanoporous carbon by ambient hydrolysis deposition. Nano Lett. 14, 4119–4124 (2014). \n34. Gonzalez, J. R., Alcantara, R., Nacimiento, F., Ortiz, G. F. & Tirado, J. L. Microstructure of the epitaxial film of anatase nanotubes obtained at high voltage and the mechanism of its electrochemical reaction with sodium. CrystEngComm 16, 4602–4609 (2014). \n35. Liu, H. S. et al. Mesoporous $\\mathrm{TiO}_{2}$ -B microspheres with superior rate performance for lithium ion batteries. Adv. Mater. 23, 3450–3454 (2011). \n36. Liu, S. H. et al. Nanosheet-constructed porous $\\mathrm{TiO}_{2}$ -B for advanced lithium ion batteries. Adv. Mater. 24, 3201–3204 (2012). \n37. Chen, C. J. et al. Controllable growth of $\\mathrm{TiO}_{2}$ -B nanosheet arrays on carbon nanotubes as a high-rate anode material for lithium-ion batteries. Carbon N. Y. 69, 302–310 (2014). \n38. Chen, C. J. et al. $\\mathrm{TiO}_{2}$ -B nanosheets/anatase nanocrystals Co-anchored on nanoporous graphene: In situ reduction-hydrolysis synthesis and their superior rate performance as an anode material. Chem. Eur. J 20, 1383–1388 (2014). \n39. Breault, T. M. & Bartlett, B. M. Lowering the band gap of anatase-structured $\\mathrm{TiO}_{2}$ by coalloying with Nb and N: electronic structure and photocatalytic degradation of methylene blue eye. J. Phys. Chem. C 116, 5986–5994 (2012). \n40. Etacheri, V., Yourey, J. E. & Bartlett, B. M. Chemically bonded $\\mathrm{TiO}_{2}$ -bronze nanosheet/reduced graphene oxide hybrid for high-power lithium ion batteries. ACS Nano 8, 1491–1499 (2014). \n41. Arrouvel, C., Parker, S. C. & Islam, M. S. Lithium insertion and transport in the $\\mathrm{TiO}_{2}$ -B anode material: a computational study. Chem. Mater. 21, 4778–4783 (2009). \n42. Wang, L., Zhou, F., Meng, Y. S. & Ceder, G. First-principles study of surface properties of $\\mathrm{LiFePO_{4}}$ : Surface energy, structure, Wulff shape, and surface redox potential. Phy. Rev. B 76, 165435 (2007). \n43. Augustyn, V. et al. Lithium-ion storage properties of titanium oxide nanosheets. Mater. Horiz 1, 219–223 (2014). \n44. Wang, J., Polleux, J., Lim, J. & Dunn, B. Pseudocapacitive contributions to electrochemical energy storage in $\\mathrm{TiO}_{2}$ (anatase) nanoparticles. J. Phys. Chem. C 111, 14925–14931 (2007). \n45. Ong, S. P. et al. Voltage, stability and diffusion barrier differences between sodium-ion and lithium-ion intercalation materials. Energy Environ. Sci. 4, 3680–3688 (2011). \n46. Pan, H. L. et al. Sodium storage and transport properties in layered $\\mathrm{Na}_{2}\\mathrm{Ti}_{3}\\mathrm{O}_{7}$ for room-temperature sodium-ion batteries. Adv. Energy Mater 3, 1186–1194 (2013). \n47. Wu, L. M., Buchholz, D., Bresser, D., Gomes Chagas, L. & Passerini, S. Anatase $\\mathrm{TiO}_{2}$ nanoparticles for high power sodium-ion anodes. J. Power Sources 251, 379–385 (2014). \n48. Xu, Y. et al. Nanocrystalline anatase $\\mathrm{TiO}_{2}$ : a new anode material for rechargeable sodium ion batteries. Chem. Commun. 49, 8973–8975 (2013). \n49. Brutti, S., Gentili, V., Menard, H., Scrosati, B. & Bruce, P. G. $\\mathrm{TiO}_{2}$ -(B) nanotubes as anodes for lithium batteries: origin and mitigation of irreversible capacity. Adv. Energy Mater 2, 322–327 (2012). \n50. Cha, H. A., Jeong, H. M. & Kang, J. K. Nitrogen-doped open pore channeled graphene facilitating electrochemical performance of $\\mathrm{TiO}_{2}$ nanoparticles as an anode material for sodium ion batteries. J. Mater. Chem. A 2, 5182–5186 (2014). \n51. Yang, D. J. et al. An efficient photocatalyst structure: $\\mathrm{TiO}_{2}(\\mathrm{B})$ nanofibers with a shell of anatase nanocrystals. J. Am. Chem. Soc. 131, 17885–17893 (2009). \n52. Lindstro¨m, H. et al. $\\mathrm{Li^{+}}$ ion insertion in $\\mathrm{TiO}_{2}$ (anatase). 2. voltammetry on nanoporous films. J. Phys. Chem. B 101, 7717–7722 (1997). \n53. Yildirim, H., Greeley, J. & Sankaranarayanan, S. K. R. S. Effect of concentration on the energetics and dynamics of Li ion transport in anatase and amorphous $\\mathrm{TiO}_{2}$ . J. Phys. Chem. C 115, 15661–15673 (2011). \n54. Hummers, W. S. & Offeman, R. E. Preparation of graphitic oxide. J. Am. Chem. Soc. 80, 1339–1339 (1958). \n55. Kresse, G. & Furthmu¨ller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n56. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n57. Dudarev, S. L., Botton, G. A., Savrasov, S. Y., Humphreys, C. J. & Sutton, A. P. Electron-energy-loss spectra and the structural stability of nickel oxide: an LSDA U study. Phys. Rev. B 57, 1505–1509 (1998). \n58. Henkelman, G., Uberuaga, B. P. & Jo´nsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000). \n\n# Acknowledgements \n\nThis work was supported by Natural Science Foundation of China (no. 21271078 and 51472098), Program for New Century Excellent Talents in University (no. NECT-12-0223), and Program for Changjiang Scholars and Innovative Research Team in University (no. IRT1014). We are thankful to the Analytical and Testing Center of HUST for XRD, TG, SEM and TEM measurements. \n\n# Author contributions \n\nC.J.C. and Y.W.W had equal contribution to the article. C.J.C. synthesized the samples, carried out the electrochemical measurements and wrote the article; and Y.W.W performed the DFT calculations and the related analysis. X.L.H raised the idea, designed the experiments, analyzed the data and edited the manuscript. X.L.J. and B.S. provided \n\nvaluable advices and helped edit the manuscript. M.Y.Y, L.Q.M. and P.H. helped characterize the materials. Y.H.H. helped analyse the results and gave helpful discussions. All authors have read and approved the final manuscript. \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nHow to cite this article: Chen, C. et al. $\\mathrm{Na}+$ intercalation pseudocapacitance in graphene-coupled titanium oxide enabling ultra-fast sodium storage and long-term cycling. Nat. Commun. 6:6929 doi: 10.1038/ncomms7929 (2015). " + }, + { + "id": "10.1021_jacs.5b11199", + "DOI": "10.1021/jacs.5b11199", + "DOI Link": "http://dx.doi.org/10.1021/jacs.5b11199", + "Relative Dir Path": "mds/10.1021_jacs.5b11199", + "Article Title": "Highly Luminescent Colloidal nulloplates of Perovskite Cesium Lead Halide and Their Oriented Assemblies", + "Authors": "Bekenstein, Y; Koscher, BA; Eaton, SW; Yang, PD; Alivisatos, AP", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Anisotropic colloidal quasi-two-dimensional nulloplates (NPLs) hold great promise as functional materials due to their combination of low dimensional optoelectronic properties and versatility through colloidal synthesis. Recently, lead-halide perovskites have emerged as important optoelectronic materials with excellent efficiencies in photovoltaic and light-emitting applications. Here we report the synthesis of quantum confined all inorganic cesium lead halide nulloplates in the perovskite crystal structure that are also highly luminescent (PLQY 84%). The controllable self-assembly of nulloplates either into stacked columnar phases or crystallographic-oriented thin-sheet structures is demonstrated. The broad accessible emission range, high native quantum yields, and ease of self-assembly make perovskite NPLs an ideal platform for fundamental optoelectronic studies and the investigation of future devices.", + "Times Cited, WoS Core": 1009, + "Times Cited, All Databases": 1105, + "Publication Year": 2015, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000367636600008", + "Markdown": "# Highly Luminescent Colloidal Nanoplates of Perovskite Cesium Lead Halide and Their Oriented Assemblies \n\nYehonadav Bekenstein,†,§ Brent A. Koscher,†,§ Samuel W. Eaton,† Peidong Yang,†,‡,§, and A. Paul Alivisatos\\*,†,‡,§,∥ \n\n†Department of Chemistry, University of California, Berkeley, California 94720, United States ‡Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States §Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States ∥Kavli Energy NanoScience Institute, Berkeley, California 94720, United States \n\n\\*S Supporting Information \n\nABSTRACT: Anisotropic colloidal quasi-two-dimensional nanoplates (NPLs) hold great promise as functional materials due to their combination of low dimensional optoelectronic properties and versatility through colloidal synthesis. Recently, lead-halide perovskites have emerged as important optoelectronic materials with excellent efficiencies in photovoltaic and light-emitting applications. Here we report the synthesis of quantum confined all inorganic cesium lead halide nanoplates in the perovskite crystal structure that are also highly luminescent (PLQY $84\\%$ ). The controllable self-assembly of nanoplates either into stacked columnar phases or crystallographic-oriented thin-sheet structures is demonstrated. The broad accessible emission range, high native quantum yields, and ease of self-assembly make perovskite NPLs an ideal platform for fundamental optoelectronic studies and the investigation of future devices. \n\nquasi-2D NPLs presenting quantum size effects.4a−c As material stability is currently limiting the application of hybrid-based devices, all-inorganic perovskites, in which cesium replaces the organic cation, may yield improved stability in comparison to hybrid perovskites, as well as extending the range of materials, which can be investigated.5 \n\nRecently a synthetic protocol for three dimensionally confined all-inorganic colloidal cesium lead-halide perovskite nanocrystals was reported.6a−c The resulting nanocubes present excellent photoluminescent quantum yields (PLQYs) of up to $\\sim90\\%$ without requiring additional surface passivation. This exciting result motivated us to synthesize colloidal nanocrystals with quasi-2D geometries. \n\nF r(eNePstLasn) hnag udaesmi-otnwsot-rdatiemd esxicoenpatli n(a2lD) ontaonpohpylsaitceasl properties, such as increased exciton binding energy, enhanced absorption cross sections with respect to bulk, low threshold stimulated emission, and notable optical nonlinearities.1a−c Established colloidal synthetic methods enable exquisite control of their thickness and hence also optical properties. Moreover, controlling ligand interactions provides a route for the selfassembly of the NPLs into more complex structures.2a,b These characteristics highlight colloidal NPLs as an interesting class of nanocrystal geometry for future photophysical studies. Recently, metal halides with the perovskite crystal structure have emerged as important optoelectronic materials. The combination of excellent optical and electronic properties have already been used to demonstrate remarkable conversion efficiencies in photovoltaics and light emitting diode devices.3a,b These layered materials exhibit an $\\mathrm{ABX}_{3}$ crystal structure, where A is a monovalent cation and B is an inorganic−metal cation in an octahedral coordination with six halide ions, X. Recent studies have concentrated on thin film perovskite with A being an organic cation typically methylammonium. Nanocrystals of these organic−inorganic hybrid perovskite were synthesized with control over their shape, forming 2D materials and colloidal \n\nWe report the colloidal synthesis of lower symmetry allinorganic cesium lead halide perovskite nanoplates and demonstrate their assembly to either form stacked columnar structures or to fuse into thin oriented sheets. We directly synthesize perovskite $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NPLs, and through anion exchange, we readily control the halide composition forming $\\mathrm{Cs}\\mathrm{PbI}_{3},$ $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3},$ and mixed compositions with band gap emission covering the entire visible spectrum $\\left(385{-}690~\\mathrm{nm}\\right)$ . Due to the high PLQYs of ${\\sim}80\\%$ and ability to self-assembly into higher ordered structures, all-inorganic perovskites NPLs are an interesting system for the study of quantum confinement effects and are positioned to be favorable candidates for future devices, combining the excellent optoelectronic properties of perovskites with 2D geometry. \n\nColloidal synthesis of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ perovskite NPLs was carried out by modifying the nanocrystal synthesis reported by Protesescu et al.6a in which they demonstrated size control of nanometer sized cubes by varying the temperature from 140 to $200^{\\circ}\\mathrm{C}.$ . We have discovered that reactions at lower temperatures between 90 and $130~^{\\circ}\\mathrm{C}$ tend to strongly favor asymmetric growth producing quasi 2D geometries. NPLs were synthesized using standard air-free techniques. $\\mathrm{Pb}{\\bf B}{\\bf r}_{2}$ was solubilized in octadecene (ODE) with oleic acid and oleylamine, and then Csoleate was injected at elevated temperatures $\\left(90-130\\ ^{\\circ}\\mathrm{C}\\right)$ to form NPLs. \n\nThe ionic nature of the metathesis reaction dictates the rapid nucleation and growth kinetics of the resulting nanocrystals. We observed that the reaction temperature plays a critical role in determining the shape and thickness of the resulting NPLs. Reactions conducted at $150~^{\\circ}\\mathrm{C}$ produce mostly symmetrical nanocubes with green-color PL emission (Figures 1a).6a−c \n\n![](images/8f7534e1b42598c839e0c6fb642e7977d58a457eebbe41fd15524e1288bc4d07.jpg) \nFigure 1. Study of the influence of reaction temperature in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ colloidal synthesis. (a) At $150^{\\circ}\\mathrm{C},$ green emitting $8{-}10~\\mathrm{{nm}}$ nanocubes are formed. (b) At $130\\ ^{\\circ}\\mathrm{C},$ cyan emitting nanoplates with lateral dimensions of $20\\ \\mathrm{nm}$ and thickness of a few unit cells $(\\sim3\\ \\mathrm{nm})$ are formed. (c) At $90^{\\circ}\\mathrm{C},$ , blue emitting thin nanoplates are observed, along with several-hundred nanometers lamellar structures. We observe NPL growth along the lamellae (red arrow) $(\\mathsf{a}-\\mathsf{c},$ scale bar is $50\\ \\mathrm{nm}$ ). \n\nReactions conducted at lower temperatures present blue-shifted PL spectra, for example, at $130^{\\circ}\\mathrm{C}$ lower symmetry NPLs with cyan emission are formed (Figures 1b and S1). At 90 and $100^{\\circ}\\mathrm{C},$ very thin NPLs were detected along with lamellar structures ranging $200{-}300~\\mathrm{nm}$ in length. As TEM images depict, NPLs grow along and inside these lamellar structures (Figures 1c and S2), suggesting that organic mesostructures serve as growth directing soft templates that break the crystal’s inherent cubic symmetry and dictate the 2D growth. Such a mechanism is not without precedent, where a similar soft templating mechanism was reported for wurtzite CdSe NPLs.7 Reaction temperatures as low as $70~^{\\circ}\\mathrm{C}$ resulted in almost transparent suspensions, where the TEM showed amorphous micron size sheets with almost no crystals present, from this we hypothesize these objects are unreacted precursors (SI Figure S3). Interestingly, reactions at temperatures of $170{-}200^{\\circ}\\mathrm{C}$ produce bigger NCs and at longer reactions times high aspect ratio nanowires (SI Figure S4). Recent reports suggest these geometries evolve sequentially from each other.8 \n\nTo characterize the NPL structure the crude reaction suspension was centrifuged and cleaned. Cleaning the perovskite NPLs has been a challenging task, primarily due to the ionic nature of these crystals and their sensitivity to water, which makes them susceptible to degradation. NPLs are precipitated from ODE by centrifugation. However, after redispersion of the NPLs in hexane or toluene, any additional cleaning and separations are nontrivial, as typical methanol/acetone washing techniques dramatically reduce the bright PL and physically degrade the NPLs as verified by TEM (SI Figure S5). We have carefully tested a library of antisolvents that would destabilize the colloidal suspension without reducing their PLQY. We observed that ethyl acetate and methyl−ethyl ketone with polarity indexes of 4.4 and 4.7, respectively,9 are sufficiently polar to initiate NPL aggregation and precipitation upon centrifugation on the one hand, but prevent degradation and maintain the high PLQY on the other. This may be directly related to the low water solubility of these solvents ( $8.7\\%$ and $24\\%$ , respectively) and therefore also low inherent water content. Previous studies have shown that water dramatically degrades and reduces the PL efficiency of perovskite-based devices.10 We have observed a similar effect, of reduced PLQYs from the NPLs upon exposure to liquid water. The cleaned NPL suspension was further characterized by TEM and XRD. The NPLs present a lateral square geometry with a thin third dimension. The NPLs display a tendency to form stacked assemblies on their sides, allowing facile direct measurement of the NPL thickness with atomic resolution. Typically reactions at $130^{\\circ}\\mathrm{C}$ yield a majority of NPLs with lateral dimensions of ${\\sim}20~\\mathrm{nm}$ and thickness of $\\sim3~\\mathrm{nm}$ , which correspond to five unit cells (Figure $\\mathsf{2a},\\mathsf{c}_{\\mathsf{\\Lambda}_{\\mathsf{c}_{\\mathsf{\\Lambda}}}}$ ). These agree with thickness measured using small-angle X-ray scattering (SAXS discussed later). $d$ -spacing values of $0.58\\ \\mathrm{nm}$ are measured (Figure 2b) in agreement with reported values of cubic $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ unit cells.11 Materials of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ are known to exist in a variety of crystal phases, including orthorhombic, tetragonal, and cubic crystal phases. Of these, the cubic phase is the energetically stable crystallographic phase at elevated temperatures for all compounds.11 Remarkably, in the case of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NPLs the high temperature cubic phase remains stable even at room temperature (Figure 2d). Likewise, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ nanocubes maintain a stable room temperature cubic crystallographic phase6a (SI Figure S6). Interestingly, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ micron size nanowires, although $12\\ \\mathrm{nm}$ in diameter, exhibit the orthorhombic phase. The two phases present markedly different optical properties, with the cubic phase being highly luminescent with PLQYs of $80-90\\%$ and the orthorhombic phase having significantly lower PLQYs. \n\n![](images/325df45b968c7ad4a54498ced7f6cdc0f039f7fa6f68d8cdf5c80d46aac73e8b.jpg) \nFigure 2. (a) HR-TEM micrograph depicting atomic resolution of both flat lying and stacked NPLs. Two areas of interest are blown up. (b) Top view of the NPL depicting $d$ spacing of ${\\sim}0.58\\mathrm{nm}$ typical for cubic phase $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ . (c) Side-view of stacked NPLs with typical thickness of ${\\sim}3\\mathrm{nm}$ corresponding to five perovskite unit cells ( $\\mathsf{a{-}c}$ scale bar $3\\ \\mathrm{nm}$ ). (d) XRD spectra of cubic phase $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NPLs compared to the standard powder diffraction pattern of cubic bulk $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ $\\stackrel{\\prime}{\\lambda}_{\\mathrm{Co-k}\\alpha}=1.79\\mathring\\mathrm{A}_{\\cdot}^{\\cdot}$ ). \n\nAbsorption and PL spectra are presented in Figure 3a. The absorption spectrum is dominated by sharp exciton peaks; similar features were previously reported for CdSe NPLs,1b and recently also in hybrid perovskite NPLs.4a,b Reactions at lower temperatures present a blue-shift of the absorption and emission peaks and in some cases very small Stokes shifts $({\\sim}30~\\mathrm{meV})$ . The PL emission shifts from green ( $\\cdot512\\mathrm{nm}2.5\\mathrm{eV},$ ) to deep purple (405 $\\ensuremath{\\mathrm{nm}}3\\ensuremath{\\mathrm{eV}}_{,}$ ) for the strongly quantum confined band edge emission (Figure 3a). A typical reaction produces a mixture of PL peaks at fixed energies. The intensities of these peaks are directly related to the reaction temperature, amount of cleaning, and separations. We hypothesize that these successive emission peaks arise from NPLs with well-defined thickness that differ in thickness by an integer number of perovskite unit cells. Specifically we measured peaks at 488, 477, 462, 435, and $405~\\mathrm{nm}$ , where these may be assigned to thicknesses of 5, 4, 3, 2, and 1 Perovskite unit cells, respectively. In the case of the thicker plates, we were able to confirm this assumption by directly measuring the thickness of stacked NPLs with atomic resolution using HRTEM (Figure 2c). The different NPLs populations can be separated by sizeselective precipitation. The thinner plates (mono and bilayers) could be easily separated from the other populations, but difficult to separate from each other. Similarly, separation of the three, four, and five layered plates proved to be challenging. However, by selectively exciting the different populations at near band-edge energies, one can separately investigate the different populations (SI Figure S7). High PLQY values of $84.4\\pm1.8\\%$ , $44.7\\pm2.6\\%$ , and $10\\pm0.5\\%$ were measured for the five, four, and three monolayer thick NPLs. These high values are surprising since one would expect that the plate geometry, with its inherently high surface to volume ratio will be exceptionally sensitive to surface defects and exhibit low PLQY. This effect may indeed be reflected by the somewhat lower PLQY measured for the thinner plates. Traditionally a protective shelling layer of a wider band gap semiconductor is used for this purpose. For example $80\\%$ PLQY was possible in CdSe plates only after a protective CdS shell was grown.12 The high PLQYs are retained also in the other lead-halide compositions. By using a facile anion exchange process in which the $\\mathrm{Br}^{-}$ anions are replaced with either $\\mathrm{Cl}^{-}$ or $\\mathrm{I}^{-}$ , we are able to tune the platelets composition and therefore their emission spectra to cover all of the visible spectrum from typical $488\\mathrm{nm}$ (with $80\\mathrm{meV}$ fwhm) in the $\\mathrm{Br}^{-}$ deep red emission of 660 nm (fwhm $120\\mathrm{meV},$ ) in the $\\mathrm{I}^{-}$ and deep purple emission of 405 nm (fwhm 107 meV) in the $\\mathrm{Cl}^{-}$ case (Figure ${3\\mathrm{b},\\mathrm{c}}$ ). Interestingly, in respect to recent reported anion exchange results,13a,b the emission peaks of the exchanged NPLs are blue-shifted, consistent with quantum confinement. This along with TEM imaging further confirms that the 2D plate geometry is preserved also after the anion exchange process. \n\n![](images/e446eff6430d411728f388cc4a5704ddebaec6a46b2963ab57b04abf37712d4a.jpg) \nFigure 3. (a) Absorption (solid lines) and emission (dashed lines) spectra of NPLs and nanocubes for comparison. Five different emission peaks at fixed wavelengths can be resolved; these correspond to five different thicknesses of the plates (1−5 unit cells). (b) Colloidal solution of anion exchanged NPLs in hexane under UV illumination $\\lambda=365$ nm) spanning the entire visible spectrum. Corresponding PL spectra of the halide-anion exchanged samples. \n\nThe perovskite NPLs show a clear tendency to self-assemble into two different hierarchical structures. The first is assembly into stacked columnar phases, which form in concentrated NPL solutions when ligands strongly interact. These were characterized optically (SI Figure S8) and by TEM and SAXS. For a slowly dried sample, the SAXS intensity is anisotropic and characteristic of stacked plates in the out-of-plane orientation with respect to the substrate (Figure $4\\mathsf{a}$ and inset). In the angular 1D data, peaks at $q$ values of 0.327 and $1.068\\ \\mathrm{nm}^{-1}$ are observed, these correspond to distances of 19.5 and $5.77\\mathrm{nm}$ , which are the NPL lateral dimensions and thickness, respectively. These distances also include the length of the organic ligands; specifically, oleates and oleylammonium, ligands that are known to densely pack on surfaces, have already been reported to support NPL attachment into columnar phases.1a,2b By combining SAXS and TEM data one can calculate the effective distance between the stacked plates as ${\\sim}2.7\\mathrm{nm},$ which is smaller than the reported $3.6\\mathrm{nm}$ for an oleate double layer length. This can be explained by the intercalation of the ligand hydrocarbon chains, adding to the structural strength of these assemblies.1a Indeed we observe that once formed, stacked NPLs are difficult to breakdown with sonication. Interestingly, the $0.327\\mathrm{nm}^{-1}$ peak presents also higher order peaks at $2q$ $\\mathit{^{\\prime}0.654\\ n m^{-1}},$ ) and $3q$ $\\left(0.982{\\mathrm{nm}}^{-1}\\right)$ , and these higher harmonics demonstrate the longrange ordering in the samples and are also a consequence of the relatively high electron density of the plates. The second type of assembled structures are large 2D sheets formed by lateral crystallographic oriented attachment of single plates. These assemblies typically form in dilute samples where ligand passivation is destabilized. Weller et al.1a have reported a process of directed oriented attachment of $\\mathrm{Pb}S\\mathrm{NCs}$ into 2D plates with micron-sized lateral dimensions by the addition of alkene-halide cosolvents. Following this work, we have tested the effect of adding various alkene-halides and dialkene-halides to the NPL suspension. This was typically preformed in ODE after which the suspension was heated to $110^{\\circ}\\mathrm{C}$ for $5{-}15\\ \\mathrm{min}$ (more details in SI). The suspension was cleaned and characterized optically (SI Figure S9), by TEM and AFM. Typically large sheets of perovskite $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ of square/rectangular shapes with lateral dimensions of a few hundred nanometers were readily measured following the treatment. AFM images show NPL thicknesses to be $\\boldsymbol{5}\\mathrm{nm}$ , in good agreement with the thickness of primary plates, capped with organic ligands. It is of note that some HRTEM images of the sheets show clear boundaries between the attached primary plates (SI Figure S10). We hypothesize that under ligand destabilizing conditions the NPLs assemble through oriented attachment into large thin sheets. \n\n![](images/ebc64a1a8cd182e8b217a492c6a0cdcd7157883fe23689d1299ee2a20150b107.jpg) \nFigure 4. (a) Small angle X-ray scattering (SAXS) intensity map of dried NPLs sample. (inset) The anisotropic scattering intensity pattern is characteristic to oriented sheets. (b) Angular data yield peaks at $q$ values of 1.068 and $0.32\\bar{7}\\mathrm{nm}^{-1}.$ , corresponding to distances of 5.77 and $19.5\\mathrm{nm}$ the distance between centers of stacked NPLs and columns, respectively. Higher order peaks at $2q$ and $3q$ are also visible (black bars). (b) Two-dimensional sheets formed by lateral-oriented attachment of the primary (scale-bar $100\\ \\mathrm{nm}$ ). (c) AFM topography micrograph depicting the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ sheets with thickness ${\\sim}5~\\mathrm{nm}$ (inset), while the lateral dimensions are on the order of $100\\ \\mathrm{nm}$ (scale bar is ${500}\\mathrm{nm}$ ). \n\nIn summary, the synthesis of highly luminescent (PLQY $84\\%$ ), colloidal, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NPLs was reported. NPLs with thickness of only a few integer number of perovskite unit cells (1−5), present clear quantum size effects. We demonstrated emissions covering the entire visible spectrum and self-assembly of NPLs into higher order hierarchies. Various optoelectronic application using perovskite NPLs with the already reported properties may be envisioned. However, further understanding and control over their surface chemistry and solution processability is essential for achieving those aspirations. Future studies of the perovskite NPLs will concentrate on these aspects. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/jacs.5b11199. \n\nExperimental details, TEM, XRD, PL, and AFM data (PDF) \n\nThe authors declare no competing financial interest. \n\nCorresponding Author \\*ap_alivisatos@berkeley.edu \n\n# AUTHOR INFORMATION \n\n# ACKNOWLEDGMENTS \n\nThis work is supported by the Physical Chemistry of Inorganic Nanostructures Program, KC3103, Office of Basic Energy Sciences of the United States Department of Energy, under Contract No. DE-AC02-05CH11231. \n\n# REFERENCES \n\n# Notes \n\n(1) (a) Schliehe, C.; Juarez, B. H.; Pelletier, M.; Jander, S.; Greshnykh, D.; Nagel, M.; Meyer, A.; Foerster, S.; Kornowski, A.; Klinke, C.; Weller, H. Science 2010, 329 (5991), 550. (b) Ithurria, S.; Tessier, M. D.; Mahler, B.; Lobo, R. P. S. M.; Dubertret, B.; Efros, A. L. Nat. Mater. 2011, 10 (12), 936. (c) Rowland, C. E.; Fedin, I.; Zhang, H.; Gray, S. K.; Govorov, A. O.; Talapin, D. V.; Schaller, R. D. Nat. Mater. 2015, 14 (5), 484. (2) (a) Tang, Z.; Zhang, Z.; Wang, Y.; Glotzer, S. C.; Kotov, N. A. Science 2006, 314 (5797), 274. (b) Abécassis, B.; Tessier, M. D.; Davidson, P.; Dubertret, B. Nano Lett. 2014, 14 (2), 710. (3) (a) Lee, M. M.; Teuscher, J.; Miyasaka, T.; Murakami, T. N.; Snaith, H. J. Science 2012, 338 (6107), 643. (b) Tan, Z.-K.; Moghaddam, R. S.; Lai, M. L.; Docampo, P.; Higler, R.; Deschler, F.; Price, M.; Sadhanala, A.; Pazos, L. M.; Credgington, D.; Hanusch, F.; Bein, T.; Snaith, H. J.; Friend, R. H. Nat. Nanotechnol. 2014, 9 (9), 687. (4) (a) Tyagi, P.; Arveson, S. M.; Tisdale, W. A. J. Phys. Chem. Lett. 2015, 6 (10), 1911−1916. (b) Sichert, J. A.; Tong, Y.; Mutz, N.; Vollmer, M.; Fischer, S.; Milowska, K. Z.; García Cortadella, R.; Nickel, B.; Cardenas-Daw, C.; Stolarczyk, J. K.; Urban, A. S.; Feldmann, J. Nano Lett. 2015, 15 (10), 6521. (c) Dou, L.; Wong, A. B.; Yu, Y.; Lai, M.; Kornienko, N.; Eaton, S. W.; Fu, A.; Bischak, C. G.; Ma, J.; Ding, T.; Ginsberg, N. S.; Wang, L.-W.; Alivisatos, A. P.; Yang, P. Science 2015, 349 (6255), 1518. \n\n(5) Kulbak, M.; Cahen, D.; Hodes, G. J. Phys. Chem. Lett. 2015, 6 (13), 2452−2456. \n(6) (a) Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Krieg, F.; \nCaputo, R.; Hendon, C. H.; Yang, R. X.; Walsh, A.; Kovalenko, M. V. \nNano Lett. 2015, 15 (6), 3692. (b) Park, Y.-S.; Guo, S.; Makarov, N.; \nKlimov, V. I. ACS Nano 2015, 9 (10), 10386. (c) Swarnkar, A.; Chulliyil, R.; Ravi, V. K.; Irfanullah, M.; Chowdhury, A.; Nag, A. Angew. Chem., Int. \nEd. 2015, 276. \n(7) Son, J. S.; Wen, X. D.; Joo, J.; Chae, J.; Baek, S.; Park, K.; Kim, J. H.; \nAn, K.; Yu, J. H.; Kwon, S. G.; Choi, S. H.; Wang, Z.; Kim, Y. W.; Kuk, Y.; \nHoffmann, R.; Hyeon, T. Angew. Chem., Int. Ed. 2009, 48 (37), 6861. \n(8) Zhang, D.; Eaton, S. W.; Yu, Y.; Dou, L.; Yang, P. J. Am. Chem. Soc. \n2015, 137 (29), 9230−9233. \n(9) Sadek, P. C. HPLC Solvent Guide; John Wiley and Sons, Inc., 2002. \n(10) Grätzel, M. Nat. Mater. 2014, 13 (9), 838. \n(11) Stoumpos, C. C.; Malliakas, C. D.; Peters, J. A.; Liu, Z.; Sebastian, M.; Im, J.; Chasapis, T. C.; Wibowo, A. C.; Chung, D. Y.; Freeman, A. J.; \nWessels, B. W.; Kanatzidis, M. G. Cryst. Growth Des. 2013, 13 (7), 2722. \n(12) Tessier, M. D.; Mahler, B.; Nadal, B.; Heuclin, H.; Pedetti, S.; \nDubertret, B. Nano Lett. 2013, 13 (7), 3321. \n(13) (a) Nedelcu, G.; Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; \nGrotevent, M.; Kovalenko, M. V. Nano Lett. 2015, 15 (8), 5635. \n(b) Akkerman, Q. A.; D’Innocenzo, V.; Accornero, S.; Scarpellini, A.; \nPetrozza, A.; Prato, M.; Manna, L. J. Am. Chem. Soc. 2015, 137 (32), 10276. " + }, + { + "id": "10.1038_ncomms9508", + "DOI": "10.1038/ncomms9508", + "DOI Link": "http://dx.doi.org/10.1038/ncomms9508", + "Relative Dir Path": "mds/10.1038_ncomms9508", + "Article Title": "A tunable azine covalent organic framework platform for visible light-induced hydrogen generation", + "Authors": "Vyas, VS; Haase, F; Stegbauer, L; Savasci, G; Podjaski, F; Ochsenfeld, C; Lotsch, BV", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Hydrogen evolution from photocatalytic reduction of water holds promise as a sustainable source of carbon-free energy. Covalent organic frameworks (COFs) present an interesting new class of photoactive materials, which combine three key features relevant to the photocatalytic process, namely crystallinity, porosity and tunability. Here we synthesize a series of water-and photostable 2D azine-linked COFs from hydrazine and triphenylarene aldehydes with varying number of nitrogen atoms. The electronic and steric variations in the precursors are transferred to the resulting frameworks, thus leading to a progressively enhanced light-induced hydrogen evolution with increasing nitrogen content in the frameworks. Our results demonstrate that by the rational design of COFs on a molecular level, it is possible to precisely adjust their structural and optoelectronic properties, thus resulting in enhanced photocatalytic activities. This is expected to spur further interest in these photofunctional frameworks where rational supramolecular engineering may lead to new material applications.", + "Times Cited, WoS Core": 988, + "Times Cited, All Databases": 1034, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000363149200001", + "Markdown": "# A tunable azine covalent organic framework platform for visible light-induced hydrogen generation \n\nVijay S. Vyas1, Frederik Haase1,2, Linus Stegbauer1,2, Go¨kcen Savasci2, Filip Podjaski1, Christian Ochsenfeld2,3 \n& Bettina V. Lotsch1,2,4 \n\nHydrogen evolution from photocatalytic reduction of water holds promise as a sustainable source of carbon-free energy. Covalent organic frameworks (COFs) present an interesting new class of photoactive materials, which combine three key features relevant to the photocatalytic process, namely crystallinity, porosity and tunability. Here we synthesize a series of water- and photostable 2D azine-linked COFs from hydrazine and triphenylarene aldehydes with varying number of nitrogen atoms. The electronic and steric variations in the precursors are transferred to the resulting frameworks, thus leading to a progressively enhanced light-induced hydrogen evolution with increasing nitrogen content in the frameworks. Our results demonstrate that by the rational design of COFs on a molecular level, it is possible to precisely adjust their structural and optoelectronic properties, thus resulting in enhanced photocatalytic activities. This is expected to spur further interest in these photofunctional frameworks where rational supramolecular engineering may lead to new material applications. \n\nTchoe epcatsitondeocfacdoe hleasn woirtgnaensiscefd thme wsyornktsh1e–(s3CisOoFfs a dsiuvlteirnsge their light weight, high porosity and presence of organic chromophores, these COFs find applications in areas such as gas storage4–7, catalysis8 and sensing9. The structural regularity in COFs leads to long-range order, which has also encouraged the exploration of these materials as supramolecularly engineered organic semiconductors with a diverse set of optoelectronic properties10–12. As the optical and electronic properties of the resulting framework materials can readily be tuned by tailoring the organic precursors13–17, photofunctional COFs present an interesting area of research with a wide scope of potential applications. \n\nPhotocatalytic water splitting presents a promising method of producing clean energy from water by generating hydrogen using sunlight. Although continuing efforts are on to develop new materials as catalysts, the majority of them contain transition metals18 or rely on extended solids that offer little room for active-site engineering. New catalysts are usually investigated for their potential for photocatalytic water splitting by looking at hydrogen or oxygen evolution with a sacrificial electron donor or acceptor. This is widely regarded as the first step towards full water splitting19,20. Recent success in the synthesis of COFs that are not only air stable but also possess very good stability in acids and bases9,21,22 allows the exploration of these materials for applications such as photocatalytic water splitting where water and photostability are key requisites. \n\nHere, we show that as a direct consequence of molecular engineering, a triphenylarene platform can readily be tuned for photocatalytic water reduction. Using a series of triphenylarylaldehydes with the central aryl ring containing 0–3 nitrogen atoms as building blocks, two-dimensional (2D) azine-linked COFs were synthesized, which reflect the structural variations of the triphenylarene platform. Investigation of these COFs as a new generation of polymeric photocatalysts show progressively enhanced hydrogen evolution with increasing nitrogen content in the frameworks. This work demonstrates the potential of organic materials in solar energy conversion where a vast array of organic building blocks and bond-forming reactions provide an extensive toolbox for the systematic fine-tuning of their structural and physical properties23, thus making way for the application of COFs in photocatalytic water splitting24. \n\n# Results \n\nSynthesis and characterization of COFs. A progressive substitution of alternate carbons in the central aryl ring of the triphenylaryl platform (Fig. 1a, green dots) by nitrogen atoms leads to a change in the electronic and steric properties of the central ring, that is, $N=0$ (phenyl), $N=1$ (pyridyl), $N=2$ (pyrimidyl) and $N=3$ (triazine). As a consequence of the substitution of the $\\mathrm{C-H}$ moiety with nitrogen atoms, a change in dihedral angle between the central aryl ring and the peripheral phenyl rings is expected, which in turn leads to varied degrees of planarity in the platform. This was corroborated by density functional theory (DFT) calculations at the PBE0–D3/Def2–SVP level as evident by the decreasing dihedral angles in the energyminimized structures of precursor aldehydes $\\mathrm{N}_{x}$ –Alds (Table 1). In addition, this results in a progressive decrease in electron density in the central aryl ring of the COF platform (Fig. 1a) as the number of nitrogen atoms increase from 0 to 3. \n\nEncouraged by the theoretical calculations, we decided to synthesize $\\mathrm{N}_{x}$ –COFs $\\scriptstyle{\\left\\langle x=0\\right.}$ , 1, 2 and 3) by an azine formation reaction9,25 of the aldehydes with hydrazine and investigate the translation of chemical and structural variation in the precursors to the overall order and optoelectronic properties of the resulting COFs, with the consequent influence on photocatalytic hydrogen production. \n\nThe precursor aldehydes $\\mathrm{\\DeltaN}_{x}$ –Alds) were synthesized as described in the Supplementary Methods. $\\mathrm{N}_{x}$ –Alds as well as their precursors were characterized using $^1\\mathrm{H}$ and $^{13}\\mathrm{C}$ spectroscopy (Supplementary Figs 2–15). $\\mathrm{N}_{x}{-}\\mathrm{COFs}$ were synthesized in quantitative yields by a condensation reaction between the corresponding trialdehydes with hydrazine in the presence of $6\\mathrm{M}$ acetic acid using 1:1 mesitylene/dioxane as solvent at $120^{\\circ}\\mathrm{C}$ for $72\\mathrm{{h}}$ (Fig. 1b; Supplementary Fig. 1). Fourier transform infrared (FTIR) spectra of the $\\mathrm{N}_{x}{-}\\mathrm{COFs}$ were compared with the corresponding aldehydes and hydrazine (Supplementary Figs $16-$ 19), and show the disappearance of aldehydic $\\mathrm{C}-\\mathrm{H}$ and $\\mathbf{C}=\\mathbf{O}$ stretches and the appearance of the azine $\\mathrm{C}=\\mathrm{N}$ stretch at $1,622\\mathrm{cm}^{-1}$ . These observations were further corroborated by the complementary Raman spectra (Supplementary Fig. 20), which showed characteristic Raman signals at $1,000{-}1,\\dot{0}10\\dot{\\mathrm{cm}}^{-1}$ for the $\\mathrm{v(N\\mathrm{-}N)}$ stretch, $1,540{-}1,560\\mathrm{cm}^{-1}$ for the $\\upnu_{\\mathrm{sym}}(\\mathbf{C}=\\mathbf{N})$ stretch and at $1,600{-}1,625\\mathrm{cm}^{-1}$ for $\\upnu_{\\mathrm{asym}}$ $(\\mathrm{C}=\\mathrm{N})$ ) stretch26. The composition and local structures of the $\\mathrm{N}_{x}{\\mathrm{-COFs}}$ were further confirmed by X-ray photoelectron spectroscopy (XPS; Supplementary Fig. 80) and $^{13}\\mathrm{C}$ cross-polarization magic angle spinning (CP–MAS) solid-state NMR (ssNMR) spectroscopy. As seen in Fig. 2 and Supplementary Figs 50, 53, 56 and 59, the characteristic aldehyde carbonyl $^{13}\\mathrm{C}$ resonance located at $\\approx190\\mathrm{p.p.m}$ . in the precursor aldehydes disappears with the concomitant appearance of the azine $\\mathrm{C}=\\mathrm{N}$ peak at $\\approx160$ p.p.m., thereby attesting the conversion of the precursors into the respective COFs. The molecular structure of the building blocks remains intact during COF formation as evident by the largely unchanged chemical shifts of the peripheral phenyl rings as well as the central aryl ring that shows characteristic peaks in the NMR. Thus, for example, the C3 symmetric carbon in the central triazine ring in the $\\mathrm{N}_{3}{\\overline{{-}}}\\mathrm{Ald}$ at 171 p.p.m. shows minimal shift and appears at $\\sim168\\mathrm{p.p.m}$ . in ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ . Similarly, the characteristic $^{13}\\dot{\\mathrm{C}}$ NMR peak of the central pyridine/pyrimidine ring in $\\mathrm{N}_{1}$ –Ald and $\\Nu_{2}$ –Ald at 119 and 112 p.p.m., respectively, can easily be spotted in the corresponding COFs due to their upfield nature (Fig. 2). The assignment of these peaks was done using 2D heteronuclear multiple quantum coherence (HMQC) NMR of $\\mathrm{N}_{1}$ and $\\Nu_{2}$ aldehydes (Supplementary Figs 8 and 11). \n\n![](images/5cd3671170291ce750667cf067787172972c2b718d821912ca7ebd5d0d43da47.jpg) \nFigure 1 | Design and synthesis of the $\\ensuremath{\\mathbf{N}}_{\\ensuremath{\\boldsymbol{x}}}$ –COFs. (a) A tunable triphenylarene platform for photocatalytic hydrogen evolution. Replacement of $'C-H^{\\prime}$ by ‘nitrogen atoms’ at the green dots changes the angle between central aryl and peripheral phenyl rings, which leads to varied planarity in the platform. (b) Synthesis of ${\\mathsf{N}}_{x}–{\\mathsf{C O F s}}$ from $\\mathsf{N}_{x}$ –aldehydes and hydrazine. \n\nTable 1 | DFT geometry optimizations of precursor aldehydes at the PBE0–D3/Def2–SVP level. \n\n\n
AldehydeDihedral angle (deg):
ABC
NoA38.738.738.7
N1320.038.920.9
N16.717.90.5
N3B N0.00.00.0
\n\nStructural and morphological characterization. To gain insight into the structural details and morphology of the COFs, powder X-ray diffraction (PXRD), gas sorption, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses were performed. PXRD of $\\mathrm{N}_{x}$ –COFs indicated the formation of crystalline networks with 2D honeycomb-type lattices as evident by the presence of an intense 100 reflection at $2\\uptheta=3.52^{\\circ}$ and reflections at 6.0, 7.1 and $9.5^{\\circ}$ corresponding to the 110, 200 and 120 reflections, respectively (Fig. 3). The observed reflections match well with the calculated patterns (Supplementary Figs 42–45) obtained from structural simulations performed for an AA eclipsed layer stacking (Supplementary Figs 34–41), using the Materials Studio v6.0.0 program (Accelrys). \n\nIt should be noted that a slight lateral offset of the layers is expected for the stacked structures27, which however cannot be distinguished from the eclipsed topology by PXRD due to substantial peak broadening. Thus, for practical reasons, the eclipsed structure is used as a simplified working model28. Interestingly, as we traverse the series from $\\mathrm{N}_{0}$ to ${\\mathrm{N}}_{3}{\\mathrm{-COF}},$ the PXRD peaks become sharper with the appearance of prominent stacking peaks for $\\Nu_{2}$ and ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ at $2\\uptheta=26^{\\circ}$ arising from the $d$ -spacing between the 001 lattice planes. Thus, the variation in planarity in the precursor aldehydes as a function of the dihedral angles translates well into the crystallinity of the resulting COFs. The unit-cell parameters were obtained by Pawley refinements for all COFs and the results are included in Supplementary Table 1. \n\n![](images/34808c65b8a2c838a2d4b10056acee67e289adc0766575a6e947050836d9a6ff.jpg) \nFigure 2 | $\\mathfrak{s}_{\\mathfrak{C}}$ cross-polarization magic angle spinning solid-state NMR of the $\\pmb{\\operatorname{N}}_{\\pmb{x}}\\pmb{\\operatorname{coFs}}.$ . The azine ${\\mathsf{C}}={\\mathsf{N}}$ peak (marked a) appears at $\\approx160$ p.p.m. while the phenyl peaks (marked ${\\bf\\delta b}_{\\mathbf{\\alpha}}^{\\prime}$ ) and characteristic central aryl peaks (marked c,d,e) show minimal changes with respect to their precursor aldehydes. \n\nThe permanent porosities evaluated by measuring the argon adsorption isotherm at $87\\mathrm{K}$ (Supplementary Fig. 46) reveal that the Brunauer–Emmett–Teller (BET) surface area of symmetrical and unsymmetrical $\\mathrm{N}_{x}$ –COFs show a deviation from the trend expected from the increasing level of planarity from $\\mathrm{N}_{0}$ to $\\mathrm{N}_{3}{\\mathrm{-}}\\mathrm{Ald}$ . Thus, while PXRD shows a similar yet lower degree of crystallinity for $\\mathrm{N}_{0}$ and $\\mathrm{\\DeltaN_{1}-C O F}$ in comparison to that observed for $\\Nu_{2}$ and ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ , a further demarcation is seen in the BET area of the symmetrical and unsymmetrical COFs. Interestingly, the BET surface area of the symmetrical $\\operatorname{N}_{0}{\\mathrm{-COF}}$ was found to be $702\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , which is significantly higher than that of the unsymmetrical $\\mathrm{\\bfN}_{\\mathrm{1}}{\\mathrm{-}}\\mathrm{COF}$ with a BET area of $326\\mathrm{m}^{2}\\mathrm{g}^{-1}$ . Likewise, in case of comparatively planar $\\mathrm{N}_{2}$ and ${\\mathrm{N}}_{3}–{\\mathrm{COF}}$ , the symmetrical ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ showed a higher BET area of $\\mathbf{1},\\bar{5}37\\mathbf{m}^{2}\\mathbf{g}^{-1}$ as compared with the unsymmetrical $_\\mathrm{N}_{2}\\mathrm{-COF}$ with a BET area of $1,046\\mathrm{m}^{2}\\mathrm{g}^{-1}$ . Thus, the lowering of symmetry leads to a lower degree of order and hence lower BET surface area. Accordingly, a narrow pore-size distribution for the most crystalline ${\\bf N}_{3}–\\mathrm{COF}$ was calculated by the non-local DFT method with a peak maximum at ${\\approx}2\\dot{4}\\dot{\\mathrm{A}}$ , which is in excellent agreement with the pore size established from the structural analysis and simulations. The maximum at $24\\mathring{\\mathrm{A}}$ is accompanied by a minor peak in the pore size distribution (PSD) at $\\approx16\\mathring{\\mathrm{A}},$ which becomes more prominent in the other $\\mathrm{N}_{x}\\mathrm{-COFs}$ $\\scriptstyle(x=0-2$ ; Supplementary Fig. 47), likely resulting from an increasing degree of lateral layer offsets and stacking disorder in the less crystalline materials. \n\nSEM images show a change in morphology from purely ball-like agglomerates in ${\\mathrm{N}}_{0}{\\mathrm{-COF}}$ to elongated ones in ${\\mathrm{N}}_{1}{\\mathrm{-COF}}$ followed by transformation to rod-like morphology in $\\mathrm{N}_{2}$ and ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ (Fig. 4a–d; Supplementary Fig. 21). The structure and morphology of $\\mathrm{N}_{x}$ –COFs was further investigated by TEM analysis where hexagonal pores are clearly visible in $\\Nu_{2}$ and ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ (Fig. 4e,f; Supplementary Figs 24 and 25). Selected area electron diffraction along the [001] zone axis of the multilayers of ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ is consistent with a nanocrystalline, hexagonally ordered in-plane structure composed of crystalline domains with sizes $\\sim50\\mathrm{-}100\\mathrm{nm}$ . TEM analysis of $\\mathrm{N}_{0}$ and $\\mathsf{N}_{1}{-}\\mathrm{COF}$ , however, did not show any crystalline domains, possibly due to instability in the electron beam (Supplementary Figs 22 and 23). \n\n![](images/239d37bb615c6f85d6d08c7ea3ed5e427f8323f170bb72871ab5ca1aee5fd8cc.jpg) \nFigure 3 | Structure and stacking analysis of the $\\ensuremath{\\mathbb{N}}_{x}$ –COFs. (a) PXRD patterns of the ${\\sf N}_{x}$ –COFs compared with the simulated pattern calculated for the representative $N_{3}–C O F.$ (b) View of extended stacks of $\\mathsf{N}_{x}$ –COFs in space filling model along the stacking direction (nitrogen, blue; carbon, grey; hydrogen, white). Note that an eclipsed stacking arrangement was assumed for simplicity. \n\n![](images/3c1e01aa5f50d5cb23d82793df10d4ea56a2c765d50b831581d49345ca41aa16.jpg) \nFigure 4 | SEM and TEM images of $\\ensuremath{\\mathbf{N}}_{\\ensuremath{\\mathbf{x}}}$ –COFs. (a) SEM images of ${\\mathsf{N}}_{0}{\\mathsf{-C O F}},$ (b) ${\\mathsf{N}}_{1}{\\mathsf{-C O F}},$ , (c) $N_{2}{\\mathrm{-COF}}$ and (d) ${\\sf N}_{3}$ –COF indicating morphological variation along the series. (e) TEM image of $N_{2}{\\mathrm{-COF}}$ showing hexagonal pores, with fast Fourier transform (FFT) of the marked area (red circle) in the inset. (f) TEM image of $N_{3}–C O F$ with enlarged Fourier-filtered image (upper inset) of the marked area and representative selected area electron diffraction pattern (lower inset). Scale bars, $5\\upmu\\mathrm{m}$ (a,b,c,d); $50\\mathsf{n m}$ (e and $\\mathbf{f})_{i}$ $20\\mathsf{n m}$ (f, upper inset). \n\nThe thermal stability of the COFs was investigated by thermogravimetric analysis (TGA), suggesting that the COFs are stable up to $\\approx350^{\\circ}\\mathrm{C}$ in argon. TGA analysis in air shows total decomposition of all the COFs at temperatures $>550^{\\circ}\\mathrm{C},$ thus indicating the absence of any metal residues (Supplementary Figs 26–33). \n\nOptical properties and photocatalysis. The diffuse reflectance spectrum reveals that all the COFs absorb light in the ultraviolet and blue parts of the visible region and show similar absorption profiles with an absorption edge at $\\sim465\\ –475\\mathrm{nm}$ (Fig. 5a), thereby suggesting an optical band gap of ${\\approx}2.6{-}2.7\\mathrm{eV}$ as determined by the Kubelka-Munk function. These values are red shifted by $40{-}60\\mathrm{nm}$ in comparison to the solid-state absorption spectra of the precursor aldehydes and can be attributed to the introduction of the azine group and a higher degree of conjugation resulting from delocalization along as well as across the plane in the extended frameworks29. As seen in Fig. 5a, unsymmetrical $\\mathrm{N}_{1}$ and $\\Nu_{2}$ –Ald show a slightly red-shifted absorption in comparison to the symmetrical $\\mathrm{N}_{0}$ and $\\mathrm{N}_{3}{\\mathrm{-Ald}}$ . DFT calculations performed on the precursor aldehydes also indicate a similar trend in the optical band gaps of symmetrical and unsymmetrical aldehydes (Supplementary Table 4). To understand the differences in absorption spectra of symmetrical and unsymmetrical aldehydes in the solid state, the absorption spectra of the precursors were additionally recorded in dilute $(8\\upmu\\mathrm{M})$ dichloromethane solutions. The absorption profiles (Fig. 5b) are marked by a clear difference between the symmetrical ${\\bf N}_{3}$ –Ald with one absorption band and the unsymmetrical $\\mathrm{N}_{1}$ and $\\Nu_{2}$ –Ald with twin absorption bands arising from the non-planar and hence non-fully conjugated phenyl–aryl ring systems. The two bands in the absorption spectrum of $\\mathrm{N}_{0}$ –Ald are rationalized by absorptions from the two types of ring systems that are essentially decoupled due to strong out-of-plane torsion of the peripheral phenyl rings. The increase in planarity leading to a higher degree of conjugation (hence red shift) along the series $\\mathrm{N}_{0}$ to ${\\bf N}_{3}$ is partly compensated by the increase in electron-deficient character of the central aryl ring (hence blue shift), thereby resulting in minimal changes in the optical band gap on network formation. The similar optical gap makes the $\\mathrm{\\DeltaN}_{x}–\\mathrm{COF}$ ensemble an ideal model platform for photocatalysis experiments, as their relative activities will not be governed by differences in their light-harvesting capability. \n\nThe $\\mathrm{N}_{x}$ –COFs were next evaluated as photocatalysts for visible light-induced hydrogen evolution. The hydrogen evolution experiments were performed by taking a suspension of the COFs in PBS at $\\mathrm{pH}7$ and irradiating with visible light $\\left(\\geq420\\mathrm{nm}\\right)$ at $25^{\\circ}\\mathrm{C}$ . Hexachloroplatinic acid was added for the in situ formation of the platinum (Pt) co-catalyst30 to reduce the overpotential for hydrogen evolution, and triethanolamine (TEoA) was used as sacrificial electron donor31,32. \n\nNotably, all COFs evolve hydrogen in the test period of $^{8\\mathrm{h}}$ (Fig. 5c). Interestingly though, the $\\mathrm{\\iV}_{x}{\\mathrm{-COFs}}$ show about fourfold increase in hydrogen evolution with each substitution of $\\mathrm{C-H}$ by $\\mathrm{\\DeltaN}$ in the central aryl ring of the COF platform. Thus, at the end of $^{8\\mathrm{h}}$ the average amount of hydrogen produced by $\\mathrm{N}_{0},\\mathrm{N}_{1},$ $\\Nu_{2}$ and $\\Nu_{3^{-}}$ COF was 23, 90, 438 and $1{,}703\\mathrm{\\dot{\\upmu}m o l h}^{-1}\\dot{\\bf g}^{-1}$ , respectively. The amount of hydrogen evolved from the most active ${\\bf N}_{3}–\\mathrm{COF}$ is competitive with carbon nitride photocatalysts and outperforms benchmark systems such as $\\mathrm{\\Pt}$ -modified amorphous melon $(720\\upmu\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{g}^{-1})^{33}$ , $\\mathrm{\\dot{\\bar{g}}-\\vec{C}_{3}\\vec{N_{4}}}^{,}$ 0 $(840\\upmu\\mathrm{molh}^{-1}\\mathbf{g}^{-1})^{34}$ or crystalline poly(triazine imide) $(864\\upmu\\mathrm{molh}^{-1}\\mathbf{g}^{-\\upbar{\\Gamma}})^{33}$ . Photocatalysis lasting up to $48\\mathrm{h}$ using $\\mathrm{N}_{3}–\\mathrm{COF}$ showed that the amount of hydrogen evolved was about four times higher than the amount of hydrogen present in the COF (Supplementary Fig. 62), thus ascertaining that the primary hydrogen source is water rather than decomposition products of the COF. After photocatalysis, the COFs were isolated and checked for stability. The FTIR (Supplementary Figs 48, 51, 54 and 57) and ssNMR (Supplementary Figs 50, 53, 56 and 59) spectra of the $\\mathrm{N}_{x}$ –COFs obtained after photocatalysis did not show any significant structural change in the material, thus indicating the retention of molecular connectivity of the framework during photocatalysis. The framework crystallinity was preserved to a large extent in the post-photocatalysis recovered COFs, although a partial loss of the long-range order was observed by PXRD (Supplementary Figs 49, 52, 55 and 58). Such a decrease in long-range order has been attributed to the delamination of framework layers24,35. In addition, the TEM images obtained from the post-photocatalysis sample (Supplementary Fig. 61) clearly demonstrate the retention of hexagonally ordered crystalline domains in addition to the uniform distribution of platinum nanoparticles that are formed in situ during photocatalysis as observed in the SEM images (Supplementary Fig. 60). Photocatalysis experiments performed in the absence of hexachloroplatinic acid did not show measurable amounts of hydrogen, thus underlining the role of platinum as electrocatalyst and microelectrode to mediate the electron transfer process30. Long-term studies performed with ascorbic acid as sacrificial electron donor revealed that the $\\mathrm{N}_{3^{-}}$ COF is stable in light for over $^{120\\mathrm{h},}$ showing sustained hydrogen evolution (Supplementary Fig. 63). To quantify the spectral distribution of the photocatalytic activity of the four COFs, the photonic efficiency (PE) was calculated using four different bandpass filters with central wavelengths at 400, 450, 500 and $550\\mathrm{nm}$ (Fig. 5d; Supplementary Table 2; Supplementary Figs 64 and 65). These measurements clearly indicate that ${\\bf N}_{3}–\\mathrm{COF}$ shows the best PE over the entire spectral range, with the maximum of $0.44\\%$ with a $450\\mathrm{-nm}$ band-pass filter. \n\n![](images/b7086c945e7f264d76793ae2178ac90122df1b7640cb6f08c3433e7bf4641695.jpg) \nFigure 5 | Optical and photocatalytic properties of $\\ensuremath{\\mathbf{N}}_{\\ensuremath{\\boldsymbol{x}}}$ –COFs. (a) Diffuse reflectance spectra of ${\\mathsf{N}}_{x}{\\mathsf{-A l d s}}$ and ${\\mathsf{N}}_{x}–{\\mathsf{C O F s}}$ recorded in the solid state. (b) Absorption spectra of precursor aldehydes ${\\sf N}_{x}$ –Alds in dichloromethane at $22^{\\circ}\\mathsf{C}$ . (c) Hydrogen production monitored over $^{8\\mathfrak{h}}$ using ${\\mathsf{N}}_{x}–{\\mathsf{C O F s}}$ as photocatalyst in the presence of triethanolamine as sacrificial electron donor. (d) Photonic efficiency (PE) measured with four different band-pass filters with central wavelengths (CWLs) at 400, 450, 500 and $550\\mathsf{n m}$ . \n\nTheoretical calculations. To rationalize the observed trend and to provide insights into the change in band gaps and band positions along the $\\mathbf{N}_{x}$ series, Kohn-Sham band gaps were calculated at the PBE0–D3/Def2–SVP level for the precursor aldehydes $\\mathrm{\\Delta}\\mathrm{N}_{x}$ –Ald; Supplementary Figs 66 and 67; Supplementary Table 4), model phenylazines $(\\mathrm{N}_{x}{\\mathrm{-PhAz}};$ Supplementary Figs 68 and 69; Supplementary Table 5) and two sets of hexagons with different terminations (aldehydes $\\mathrm{N}_{x}$ –HxAl and hydrazones $\\mathrm{N}_{x}{\\mathrm{-HxHz}}$ ; Supplementary Figs 70–73; Supplementary Tables 6 and 7), serving as representative semi-extended model systems (Fig. 6). The hexagons $(\\mathrm{N}_{x}\\mathrm{-HxAl}$ and $\\mathrm{N}_{x}{\\mathrm{-HxHz}},$ were stacked up to three layers for probing the role of stacking on the band gaps and positions (Supplementary Figs 75 and 76; Supplementary Tables 8 and 9). \n\nKohn-Sham band gaps calculated for the oligomers (Fig. 7a,b) do not show significant variation on going from the $\\mathrm{N}_{0}-$ to the ${\\bf N}_{3}$ model systems, which is in line with the experimentally observed optical spectra of the COFs that show minor differences in their absorption edge (Fig. 5a). Also, as observed by Zwijnenburg and co-workers29, the stacked hexagons of ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ both with hydrazone $\\left(\\mathrm{N}_{3}–\\mathrm{HxHz}\\right)$ and aldehyde terminations $(\\mathrm{N}_{3}\\mathrm{-HxAl})$ show a decrease in the band gap with increasing numbers of layers (Fig. 7c). \n\nThe observed steady decrease in lowest unoccupied molecular orbital (LUMO) energy in these calculations for the $\\mathrm{N}_{x}\\mathrm{-COFs}$ with increasing nitrogen content suggests a decreased thermodynamic driving force for electrons to move to the platinum cocatalyst. This trend, however, does not account for the differences in the observed hydrogen evolution activities. Instead, the lowering of the highest occupied molecular orbital (HOMO) along the $\\mathrm{N}_{x}$ series may lead to an increase in the oxidizing power of the hole36. This increase in thermodynamic driving force may therefore facilitate hole removal from the COF by the sacrificial electron donor most efficiently in $\\mathrm{N}_{3}\\mathrm{-COF}^{37}$ . \n\n![](images/f27e219c96f9a2807f5611b72a1db9ea93f26b5c1cd635740a286dd0dbda7310.jpg) \nFigure 6 | General structure of the model systems used for theoretical calculations. ${\\sf N}_{0}{\\sf-}\\colon\\sf X=\\mathsf{Y}=\\mathsf{Z}={\\sf C}{\\sf-}{\\sf H}$ . ${\\sf N}_{1}-$ : ${\\sf X}={\\sf Y}={\\sf C}-{\\sf H}$ ; $Z={\\mathsf{N}}$ . ${\\mathsf N}_{2}-$ : ${\\sf X}={\\sf C}\\mathrm{-}{\\sf H}.$ $\\mathsf{Y}=\\mathsf{Z}=\\mathsf{N}$ . $\\mathsf{N}_{3}-$ : ${\\sf X}={\\sf Y}={\\sf Z}={\\sf N}$ . \n\n![](images/cdecfc04e8baac7769c6ef9ccbce69c17a3c6b8975063d8af2065a3f5e9df854.jpg) \nFigure 7 | Kohn-Sham HOMO and LUMO energies of different model systems with $\\ensuremath{\\mathbb{N}}_{\\ensuremath{\\boldsymbol{x}}}$ central core. (a) $\\mathsf{N}_{x}\\mathrm{-Ald}$ and $\\mathsf{N}_{x}{\\mathsf{-P h A z}}$ ; $(\\pmb{\\ b})$ hexagons with hydrazone $(N_{x}-H\\times H z)$ and aldehyde terminations $(N_{x}-H x A l)$ ; and $\\mathbf{\\eta}(\\bullet)$ stacked hexagon layers of ${\\sf N}_{3}$ –COF with hydrazone $(N_{3}-H\\times H z)$ and aldehyde terminations $(N_{3}-H\\times A l)$ . \n\nIn addition, molecular orbitals for the model systems were extracted and compared for the extended COF systems. Although HOMO–LUMO distributions are often invoked in the literature to rationalize exciton delocalization, charge separation and the location of potential charge-transfer sites38–40, it has to be stressed that orbitals are not observables and hence, such model considerations need to be taken with care. Also, since ${\\mathrm{DFTB}}+$ orbitals did not always agree with orbitals from DFT calculations in the case of our 7-hexagon model systems, orbital data from DFTB $^+$ calculations may be of limited use here. Nevertheless, unit cells of the ${\\mathrm{N}}_{x}{\\mathrm{-COFs}}$ were optimized on the $\\mathrm{DFTB}+/\\mathrm{mio}{-}1{-}0$ level of theory using periodic single-point calculations, and molecular orbitals were subsequently calculated on the same level of theory. Across the different ${\\mathrm{N}}_{x}{\\mathrm{-COFs}},$ , the HOMO is localized solely on the azine linker unit (Supplementary Fig. 77), while the LUMO is delocalized across the conjugated $\\pi$ -system of the framework (Supplementary Fig. 78). When associating the HOMO with the charge-transfer sites for holes, we may infer that efficient hole quenching is possible through hydrogen-bonding interactions with the sacrificial donor TEoA via the azine moiety for all COFs. \n\nFor smaller clusters calculated on a higher level of theory (PBE0–D3/Def2–SVP), we find that the HOMOs of hydrazoneterminated model hexagons are exclusively located at these terminations, while the LUMO is distributed along the hexagon with the maximum delocalization found for the planar $\\mathrm{N}_{3}{\\mathrm{-HxHz}}$ model (Supplementary Figs 72 and 73). To check the reliability of these model systems, even larger molecular clusters with 1,248 atoms were modelled for the ${\\bf N}_{3}$ system to reduce the influence of terminating groups on the electronic structure of the innermost aryl core. However, the terminal hydrazone moieties still strongly localize the HOMO, whereas the LUMO in the 7-hexagon system is still centred on the innermost hexagon, despite the vicinal hexagons (Supplementary Fig. 74). This suggests an efficient HOMO–LUMO separation for oligomers with electron-rich terminal groups, which could assist the charge separation process on excitation. Note, however, that the HOMO and LUMO do not necessarily correspond to the orbitals participating in the brightest transitions and further calculations are necessary to pinpoint the orbital contributions to the optical absorptions involved in the photocatalytic process. \n\nSince orbital considerations as non-observables are always difficult as discussed above, an alternative approach was pursued in considering the possible reaction intermediates. The stability of reactive intermediates formed during the photocatalytic process appears as a more reliable descriptor to rationalize the observed trend in the photocatalytic activity across the series of COFs. Hence, the energies and relative stabilities of radical anions of hydrazoneterminated $\\mathrm{N}_{x}$ –hexagons were calculated as outlined in Fig. 8. \n\n![](images/e317114690b9942458db34ccc79075bcc37d8782bf2965c49f56a755ee93a0cc.jpg) \nFigure 8 | Schematic representation of two possible pathways after photoexcitation of $\\ensuremath{\\boldsymbol{\\mathsf{N}}}_{\\ensuremath{\\boldsymbol{\\mathsf{X}}}}$ –COFs. Quenching the hole on the COF by the sacrificial electron donor leads to a radical anionic state for the COF (radical anion pathway, red arrow). The opposite order leads to the radical cationic pathway (dotted black arrows). Energies in red depict calculated vertical electron affinities as differences in total energies between radical anionic and neutral states of $\\mathsf{N}_{x}$ –HxHz model systems at PBE0–D3/Def2–SVP level. Asterisk $(^{\\star})$ denotes the excited state. \n\nElectron affinities of the $\\mathrm{N}_{x}$ -systems in the order of $-2\\mathrm{eV}$ were computed (Supplementary Table 10), whereas the ionization potential for ${\\mathrm{N}}_{3}–{\\mathrm{HxHz}}$ is estimated in the regime of roughly $+10\\mathrm{eV}$ in vacuum, thus rendering the formation of a radical cation during the photocatalytic process less likely. Considering the formation of a radical anion as the rate-determining step, which is most favoured for the ${\\bf N}_{3}$ system and least facile for the $\\mathrm{N}_{0}$ system, the observed energetics of the radical anion upholds the observed trend. On one hand, this finding emphasizes the role of the sacrificial electron donor that needs to swiftly remove the hole from the COF leading to the formation of a radical anion. On the other hand, it underlines the importance of the electron-poor character of the triazine building block, which is efficient at stabilizing the negative charge generated on the COF and at transferring it to the nearest platinum site. This trend is fully in line with the observed hydrogen evolution activity and we therefore reason that the formation of the radical anion is crucial for the photocatalytic process, as exemplified by $\\mathrm{N}_{x}\\mathrm{-COFs}$ . \n\n# Discussion \n\nAlthough the above calculations are fully in line with the observed exponential increase in hydrogen production across the $\\mathrm{N}_{x}.$ -series, the latter cannot be pinpointed to a single property change of the COFs but rather has to be ascribed to a complex interplay of several factors. For example, an increase in surface area may play a key role in the photocatalytic activity by providing a greater number of exposed active sites. However, in the present case, only a weak correlation with the surface area of the $\\mathrm{N}_{x}$ –COFs could be established, thus suggesting that surface area is not the central factor determining the photocatalytic activity (Supplementary Table 3). \n\nFurther, as observed earlier29, stacking likely plays a key role in the observed red shift of absorption spectra of the COFs as compared with the spectra of the aldehyde building blocks. In addition, as a consequence of the decreased dihedral angle along the series and hence improved crystallinity, enhanced structural definition and layer registry, most facile exciton migration within the COF plane and also along the well-stacked aryl rings is expected for ${\\mathrm{N}}_{3}{\\mathrm{-COF}}$ , which is in line with the observed trend in photocatalytic activity41,42. Although the exciton dynamics in such materials is expected to be complicated and dependent on both structural and electronic factors, it is interesting that a logarithmic plot of dihedral angles obtained from the geometry optimized precursor aldehydes against hydrogen production of the respective COFs shows a linear relationship (Supplementary Fig. 79). Regarding electronic factors, the computed increase in stabilization of the radical anions in the most nitrogen-rich COFs nicely correlates with the observed trend. The stabilization of the anion radical likely enhances the charge separation, thereby increasing the probability of successful electron migration to a nearby Pt co-catalyst. The relevance of the anion radical for hydrogen evolution likewise shifts the focus to the sacrificial electron donor, whose interaction with the COF likely determines how quickly the hole can be quenched. Therefore, our results suggest that tuning the interfacial interactions between the COF and the electron donor may be a promising route to optimize the hydrogen evolution efficiencies further in such systems. \n\nIn summary, we have synthesized a new COF platform that can be tuned for visible light-induced hydrogen evolution from water. Systematic variation in the properties of our four structurally related COFs clearly indicates that tuning the electronic and structural properties of the precursors has a significant impact on the photocatalytic activity of the resulting COFs. We have thus shown that engineering the building blocks and, hence, the electronic properties of photofunctional COFs opens new avenues to tunable, tailor-made supramolecular photocatalysts. Hydrogen evolution resulting from a crystalline COF that retains its structure during photocatalysis is an important stepping stone on the way to full water splitting by organic frameworks with embedded photophysical functions, and at the same time holds much room for further improvement through rational band gap and catalytic site engineering by tailoring the molecular building blocks. \n\n# Methods \n\nGeneral synthesis of COFs. All COFs were prepared by a procedure identical to the one described here for the synthesis of $\\bf N_{3}/c O F$ . In a Biotage $5\\mathrm{-ml}$ high precision glass vial, ${\\bf N}_{3}$ –Ald $(50\\mathrm{mg},0.13\\mathrm{mmol}$ ) was suspended in a mixture $1.0\\mathrm{ml}$ mesitylene, \n\n$1.0\\mathrm{ml}1{,}4$ -dioxane and $100\\upmu\\mathrm{l}$ aqueous $6\\mathrm{M}$ acetic acid. To the suspension, hydrazine hydrate $(10\\upmu\\updownarrow,$ $50\\mathrm{-}60\\%$ solution, Sigma-Aldrich) was then added. The vial was then sealed and heated in an oil bath at $120^{\\circ}\\mathrm{C}$ for 3 days at autogenous pressure. Thereafter, the vial was opened and the suspension was filtered and washed with chloroform $(2\\times5{\\mathrm{ml}})$ , acetone $(2\\times5{\\mathrm{ml}})$ and tetrahydrofuran $(2\\times5\\mathrm{ml})$ . The solid was dried in an oven at $60^{\\circ}\\mathrm{C}$ to afford $\\mathrm{N}_{3}{\\mathrm{-COF}}$ as a light yellow powder. Anal. Calcd. for $\\mathrm{(C_{24}N_{6}H_{15})_{n}};$ C, 74.40; N, 21.69; H, 3.90. Found: C, 72.36; N, 21.32; H, 4.07. $^{13}\\mathrm{C}$ CP–MAS NMR ${\\bf\\chi}_{100}\\bf{M H z}$ ) $\\delta$ p.p.m. 168.39, 159.55, 136.61 and 126.96. \n\nPhotocatalysis. All photocatalysis experiments were performed in a double-walled glass reactor, where the outer compartment is circulated with water kept at a constant temperature $(25^{\\circ}\\mathrm{C})$ through a thermostat. The reactor was top irradiated through a quartz window with a xenon lamp (Newport, $300\\mathrm{W}$ ) equipped with a water filter and a dichroic mirror $(900\\mathrm{nm}>\\lambda>420\\mathrm{nm})$ . For each experiment, the photocatalyst (COF; $5\\mathrm{mg},\\$ ) was suspended in PBS ( $10\\mathrm{ml}$ of $0.1\\mathrm{{M}}$ solution at $\\mathrm{pH}7\\mathrm{.}$ ) containing TEoA ( ${\\mathrm{100}}\\upmu\\mathrm{l};{}$ $0.738\\mathrm{mmol}$ ). For long-term experiments, ascorbic acid was used instead of TEoA. Hexachloroplatinic acid $(5\\upmu\\up$ $8\\mathrm{wt\\%}$ aqueous solution, SigmaAldrich) was added for the in situ formation of platinum as the co-catalyst. The actual loading with Pt as determined by the inductively coupled plasma optical emission spectroscopy (ICP-OES) analysis of COFs after photocatalysis was 2.14, 1.70, 0.94 and $0.68\\mathrm{wt\\%}$ for $\\mathrm{N}_{0}$ , $\\mathrm{N}_{1},$ $\\mathrm{N}_{2}$ and $\\mathrm{\\bfN}_{3}{\\mathrm{-COF}}$ , respectively. The head space was subjected to several cycles of evacuation and argon backfill before the experiment. In the course of the experiment, the head space of the reactor was periodically sampled and the components were quantified by gas chromatography (Thermo Scientific TRACE GC Ultra) equipped with a thermal conductivity detector (TCD) detector using argon as the carrier gas. For long-term photocatalysis experiments, the head space of the reactor was evacuated and purged with argon every $24\\mathrm{h}$ to avoid hydrogen buildup and the photocatalysis was resumed. After the photocatalysis experiment, the COFs were recovered by filtration, washed with water and then dried at $100^{\\circ}\\mathrm{C}$ . The PE of the photocatalysts were determined under irradiation using band-pass filters with central wavelengths (400, 450, 500 and $550\\mathrm{nm}$ ; Thorlabs). For this purpose, $10\\mathrm{mg}$ of COF was suspended in buffer (PBS, $10\\mathrm{ml}$ of $0.1\\mathrm{M}$ solution at $\\mathrm{pH}7$ ) containing TEoA $(1,000\\upmu\\up$ ; $7.38\\mathrm{mmol}_{.}$ ) and hexachloroplatinic acid ( $10\\upmu\\mathrm{l}$ $8\\mathrm{wt\\%}$ aqueous solution, Sigma-Aldrich). The power of the incident light was obtained from a thermo power sensor (Thorlabs). The PE was then calculated using the equation $\\mathrm{PE}=2\\cdot\\lbrack\\mathrm{H}_{2}\\rbrack/I$ where $\\left[\\mathrm{H}_{2}\\right]$ is the average hydrogen evolution rate and $I$ is the incident photon flux. \n\nCharacterization. Infrared spectra were recorded in attenuated total reflection (ATR) geometry on a PerkinElmer UATR Two equipped with a diamond crystal. The spectra were background corrected. Raman spectra were recorded with a Jobin Yvon-type V 010 labRAM single-grating spectrometer equipped with a double super razor edge filter and a peltier-cooled charge-coupled device (CCD) camera in quasi-backscattering geometry using the linearly polarized 632.817-nm He/Ne gas laser. Diffuse reflectance UV–visible absorption spectra were collected on a Cary 5000 spectrometer (referenced to barium sulphate). Absorption spectra were calculated from the reflectance data using the Kubelka-Munk function. The liquid state $^1\\mathrm{H}$ and $^{13}\\mathrm{C}$ NMR spectra were recorded on a Bruker 300-MHz NMR spectrometer, while the ssNMR was recorded on a Bruker 400- and 500-MHz spectrometer. For ssNMR spectroscopy, the sample was filled in a $2.5\\mathrm{-mm}\\mathrm{ZrO}_{2}$ rotor, which was mounted in a standard double resonance MAS probe (Bruker). The $^{13}\\mathrm{C}$ chemical shift was referenced relative to tetramethylsilane. The ${}^{1}\\mathrm{H}\\mathrm{-}{}^{13}\\mathrm{C}$ CP–MAS spectra were recorded at a spinning speed of $20\\mathrm{kHz},$ using a ramped-amplitude CP pulse on $^1\\mathrm{H}$ . Argon sorption measurements were performed at $87\\mathrm{K}$ with a Quantachrome Instruments Autosorb-iQ. The poresize distribution was calculated from Ar adsorption isotherms by non-local DFT using the ‘Ar–zeolite/silica cylindrical pores at $87\\mathrm{K}'$ kernel (applicable pore diameters $3.5\\mathrm{-}1,000\\mathring\\mathrm{A})$ . PXRD data were collected on a Huber G670 diffractometer in DebyeScherrer geometry using ${\\mathrm{Ge}}(111)$ -monochromatized $\\mathrm{Cu-K}\\alpha$ radiation $\\begin{array}{r}{\\lambda=1.540\\dot{6}\\mathrm{\\AA},}\\end{array}$ . CHN elemental analyses were performed with a vario EL elemental analyser (Elementar Analysensysteme GmbH). SEM images were obtained either by a VEGA TS 5130MM (TESCAN) or with a Zeiss Merlin with EsB (energy and angle selective BSE) and SE (secondary electron) detector. TEM was performed with a Philips $\\mathrm{CM}30~\\mathrm{ST}$ $300\\mathrm{kV}$ , $\\mathrm{LaB}_{6}$ cathode). The samples were suspended in $n$ -butanol and drop-cast onto a lacey carbon film (Plano). TGA measurements were performed on NETZSCH STA $409\\mathrm{C}/\\mathrm{CD}$ at a heating rate of $5\\mathrm{K}\\mathrm{min}^{-1}$ under argon and in air. For XPS, samples were pressed onto indium foil and the spectra were collected on an Axis Ultra (Kratos Analytical, Manchester) X-ray photoelectron spectrometer with charge neutralization. The spectra were referenced with the adventitious carbon 1-s peak at $284.80\\mathrm{eV}$ . \n\nCalculations. Structures for all investigated building blocks were optimized on the PBE0–D3/Def2–SVP level of theory. Kohn-Sham band gaps were obtained from single-point calculations on the same level of theory. Excitation energies for optimized building blocks were calculated on the TD–PBE0–D3/Def2–SVP level of theory. Excitations with the largest oscillator strength were selected for each optimized building block to compute the different densities. Calculations for precursor aldehydes and model compounds were done using the Turbomole program package in version 6.3.1 (ref. 43). Calculations for the hexagons with different terminations were done using the FermiONs $++$ program package44,45. Periodic calculations for optimizations and single points were performed using the ${\\mathrm{DFTB}}+$ program package46. \n\n# References \n\n1. Ding, S. Y. & Wang, W. Covalent organic frameworks (COFs): from design to applications. Chem. Soc. Rev. 42, 548–568 (2013). \n2. Feng, X., Ding, X. S. & Jiang, D. Covalent organic frameworks. Chem. Soc. Rev. 41, 6010–6022 (2012). \n3. Fang, Q. et al. Designed synthesis of large-pore crystalline polyimide covalent organic frameworks. Nat. Commun. 5, 4503 (2014). \n4. El-Kaderi, H. M. et al. Designed synthesis of 3D covalent organic frameworks. Science 316, 268–272 (2007). \n5. Yu, J.-T., Chen, Z., Sun, J., Huang, Z.-T. & Zheng, Q.-Y. Cyclotricatechylene based porous crystalline material: synthesis and applications in gas storage. J. Mater. Chem. 22, 5369–5373 (2012). \n6. Doonan, C. J., Tranchemontagne, D. J., Glover, T. G., Hunt, J. R. & Yaghi, O. M. Exceptional ammonia uptake by a covalent organic framework. Nat. Chem. 2, 235–238 (2010). \n7. Furukawa, H. & Yaghi, O. M. Storage of hydrogen, methane, and carbon dioxide in highly porous covalent organic frameworks for clean energy applications. J. Am. Chem. Soc. 131, 8875–8883 (2009). \n8. Ding, S. Y. et al. Construction of covalent organic framework for catalysis: Pd/COF-LZU1 in Suzuki-Miyaura coupling reaction. J. Am. Chem. Soc. 133, 19816–19822 (2011). \n9. Dalapati, S. et al. An azine-linked covalent organic framework. J. Am. Chem. Soc. 135, 17310–17313 (2013). \n10. Wan, S. et al. Covalent organic frameworks with high charge carrier mobility. Chem. Mater. 23, 4094–4097 (2011). \n11. Wan, S., Guo, J., Kim, J., Ihee, H. & Jiang, D. L. A belt-shaped, blue luminescent, and semiconducting covalent organic framework. Angew. Chem. Int. Ed. 47, 8826–8830 (2008). \n12. Ding, X. S. et al. Synthesis of metallophthalocyanine covalent organic frameworks that exhibit high carrier mobility and photoconductivity. Angew. Chem. Int. Ed. 50, 1289–1293 (2011). \n13. Gutzler, R. & Perepichka, D. F. pi-Electron conjugation in two dimensions. J. Am. Chem. Soc. 135, 16585–16594 (2013). \n14. Lukose, B., Kuc, A. & Heine, T. Stability and electronic properties of 3D covalent organic frameworks. J. Mol. Model. 19, 2143–2148 (2013). \n15. Zhu, P. & Meunier, V. Electronic properties of two-dimensional covalent organic frameworks. J. Chem. Phys. 137, 244703 (2012). \n16. Zhou, Y., Wang, Z., Yang, P., Zu, X. & Gao, F. Electronic and optical properties of two-dimensional covalent organic frameworks. J. Mater. Chem. 22, 16964–16970 (2012). \n17. Sprick, R. S. et al. Tunable organic photocatalysts for visible-light-driven hydrogen evolution. J. Am. Chem. Soc. 137, 3265–3270 (2015). \n18. Du, P. & Eisenberg, R. Catalysts made of earth-abundant elements (Co, Ni, Fe) for water splitting: recent progress and future challenges. Energy Environ. Sci. 5, 6012–6021 (2012). \n19. Teets, T. S. & Nocera, D. G. Photocatalytic hydrogen production. Chem. Commun. 47, 9268–9274 (2011). \n20. Artero, V. & Fontecave, M. Solar fuels generation and molecular systems: is it homogeneous or heterogeneous catalysis? Chem. Soc. Rev. 42, 2338–2356 (2013). \n21. Kandambeth, S. et al. Construction of crystalline 2D covalent organic frameworks with remarkable chemical (acid/base) stability via a combined reversible and irreversible route. J. Am. Chem. Soc. 134, 19524–19527 (2012). \n22. Biswal, B. P. et al. Mechanochemical synthesis of chemically stable isoreticular covalent organic frameworks. J. Am. Chem. Soc. 135, 5328–5331 (2013). \n23. Vyas, V. S. & Lotsch, B. V. Materials chemistry: organic polymers form fuel from water. Nature 521, 41–42 (2015). \n24. Stegbauer, L., Schwinghammer, K. & Lotsch, B. V. A hydrazone-based covalent organic framework for photocatalytic hydrogen production. Chem. Sci. 5, 2789–2793 (2014). \n25. Li, Z. P. et al. A 2D azine-linked covalent organic framework for gas storage applications. Chem. Commun. 50, 13825–13828 (2014). \n26. Aly, M. M. A. Infrared and Raman spectra of some symmetric azines. Spectrochim. Acta A Mol. Biomol. Spectrosc. 55, 1711–1714 (1999). \n27. Spitler, E. L. et al. A 2D covalent organic framework with 4.7-nm pores and insight into its interlayer stacking. J. Am. Chem. Soc. 133, 19416–19421 (2011). \n28. Chandra, S. et al. Chemically stable multilayered covalent organic nanosheets from covalent organic frameworks via mechanical delamination. J. Am. Chem. Soc. 135, 17853–17861 (2013). \n29. Butchosa, C., McDonald, T. O., Cooper, A. I., Adams, D. J. & Zwijnenburg, M. A. Shining a light on s-triazine-based polymers. J. Phys. Chem. C 118, 4314–4324 (2014). \n30. Kiwi, J. & Gratzel, M. Hydrogen evolution from water induced by visible-light mediated by redox catalysis. Nature 281, 657–658 (1979). \n31. Wang, C., Cao, S. & Fu, W.-F. A stable dual-functional system of visible-lightdriven Ni(II) reduction to a nickel nanoparticle catalyst and robust in situ hydrogen production. Chem. Commun. 49, 11251–11253 (2013). \n32. Martin, D. J. et al. Highly efficient photocatalytic H2 evolution from water using visible light and structure-controlled graphitic carbon nitride. Angew. Chem. Int. Ed. 53, 9240–9245 (2014). \n33. Schwinghammer, K. et al. Triazine-based carbon nitrides for visible-lightdriven hydrogen evolution. Angew. Chem. Int. Ed. 52, 2435–2439 (2013). \n34. Zhang, J. et al. Synthesis of a carbon nitride structure for visible-light catalysis by copolymerization. Angew. Chem. Int. Ed. 49, 441–444 (2010). \n35. Bunck, D. N. & Dichtel, W. R. Bulk synthesis of exfoliated two-dimensional polymers using hydrazone-linked covalent organic frameworks. J. Am. Chem. Soc. 135, 14952–14955 (2013). \n36. Berr, M. J. et al. Hole scavenger redox potentials determine quantum efficiency and stability of Pt-decorated CdS nanorods for photocatalytic hydrogen generation. Appl. Phys. Lett. 100, 223903 (2012). \n37. Simon, T. et al. Redox shuttle mechanism enhances photocatalytic H2 generation on Ni-decorated CdS nanorods. Nat. Mater. 13, 1013–1018 (2014). \n38. Jin, S. B. et al. Two-dimensional tetrathiafulvalene covalent organic frameworks: towards latticed conductive organic salts. Chem. Eur. J. 20, 14608–14613 (2014). \n39. Gunasinghe, R. N., Reuven, D. G., Suggs, K. & Wang, X. Q. Filled and empty orbital interactions in a planar covalent organic framework on graphene. J. Phy. Chem. Lett. 3, 3048–3052 (2012). \n40. Jin, S. B. et al. Charge dynamics in a donor-acceptor covalent organic framework with periodically ordered bicontinuous heterojunctions. Angew. Chem. Int. Ed. 52, 2017–2021 (2013). \n41. van der Horst, J.-W. et al. Predicting polarizabilities and lifetimes of excitons on conjugated polymer chains. Chem. Phys. Lett. 334, 303–308 (2001). \n42. Andrew, T. L. & Swager, T. M. Structure-property relationships for exciton transfer in conjugated polymers. J. Polym. Sci. B Pol. Phys. 49, 476–498 (2011). \n43. Ahlrichs, R., Bar, M., Haser, M., Horn, H. & Kolmel, C. Electronic-structure calculations on workstation computers: the program system TURBOMOLE. Chem. Phys. Lett. 162, 165–169 (1989). \n44. Kussmann, J. & Ochsenfeld, C. Pre-selective screening for matrix elements in linear-scaling exact exchange calculations. J. Chem. Phys. 138, 134114 (2013). \n45. Kussmann, J. & Ochsenfeld, C. Preselective screening for linear-scaling exact exchange-gradient calculations for graphics processing units and general strong-scaling massively parallel calculations. J. Chem. Theory Comput. 11, 918–922 (2015). \n46. Aradi, B., Hourahine, B. & Frauenheim, T. DFTB $^+$ , a sparse matrix-based implementation of the DFTB method. J. Phys. Chem. A 111, 5678–5684 (2007). \n\n# Acknowledgements \n\nWe thank Viola Duppel for SEM and TEM images and valuable discussions; Sebastian Vogel for helping with photocatalysis experiments; Christian Minke and Dr Igor Moudrakovski for solid-state NMR measurements; and Dr Mitsuharu Konuma for XPS measurements. We also thank Florian Ehrat, Thomas Simon and Jacek Stolarczyk (Feldmann group, LMU Munich) for helpful discussions. B.V.L. is grateful for the ERC Starting Grant (project COFLeaf, grant number 639233). C.O. acknowledges financial support by the DFG funding initiatives SFB749 (C7) and the Excellence Cluster EXC114 (CIPSM). \n\n# Author contributions \n\nV.S.V., F.H. and B.V.L. proposed the idea and designed the experiments. V.S.V. and B.V.L. wrote the manuscript. V.S.V. carried out the synthesis and photocatalysis experiments. F.H. helped in synthesis, photocatalysis and structure simulation of the COFs. L.S. performed the sorption experiments. F.P. performed electrochemistry for determining the band potential of COFs. G.S. and C.O. performed the theoretical calculations. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Vyas, V. S. et al. A tunable azine covalent organic framework platform for visible light-induced hydrogen generation. Nat. Commun. 6:8508 doi: 10.1038/ncomms9508 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms8069", + "DOI": "10.1038/ncomms8069", + "DOI Link": "http://dx.doi.org/10.1038/ncomms8069", + "Relative Dir Path": "mds/10.1038_ncomms8069", + "Article Title": "Subwavelength-thick lenses with high numerical apertures and large efficiency based on high-contrast transmitarrays", + "Authors": "Arbabi, A; Horie, Y; Ball, AJ; Bagheri, M; Faraon, A", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Flat optical devices thinner than a wavelength promise to replace conventional free-space components for wavefront and polarization control. Transmissive flat lenses are particularly interesting for applications in imaging and on-chip optoelectronic integration. Several designs based on plasmonic metasurfaces, high-contrast transmitarrays and gratings have been recently implemented but have not provided a performance comparable to conventional curved lenses. Here we report polarization-insensitive, micron-thick, high-contrast transmitarray micro-lenses with focal spots as small as 0.57 lambda. The measured focusing efficiency is up to 82%. A rigorous method for ultrathin lens design, and the trade-off between high efficiency and small spot size (or large numerical aperture) are discussed. The micro-lenses, composed of silicon nullo-posts on glass, are fabricated in one lithographic step that could be performed with high-throughput photo or nulloimprint lithography, thus enabling widespread adoption.", + "Times Cited, WoS Core": 927, + "Times Cited, All Databases": 1091, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000355531100005", + "Markdown": "# Subwavelength-thick lenses with high numerical apertures and large efficiency based on high-contrast transmitarrays \n\nAmir Arbabi1, Yu Horie1, Alexander J. Ball1, Mahmood Bagheri2 & Andrei Faraon1 \n\nFlat optical devices thinner than a wavelength promise to replace conventional free-space components for wavefront and polarization control. Transmissive flat lenses are particularly interesting for applications in imaging and on-chip optoelectronic integration. Several designs based on plasmonic metasurfaces, high-contrast transmitarrays and gratings have been recently implemented but have not provided a performance comparable to conventional curved lenses. Here we report polarization-insensitive, micron-thick, high-contrast transmitarray micro-lenses with focal spots as small as $0.57\\lambda$ . The measured focusing efficiency is up to $82\\%$ . A rigorous method for ultrathin lens design, and the trade-off between high efficiency and small spot size (or large numerical aperture) are discussed. The micro-lenses, composed of silicon nano-posts on glass, are fabricated in one lithographic step that could be performed with high-throughput photo or nanoimprint lithography, thus enabling widespread adoption. \n\nFlseattrn ltseunrasenesd. aHhreow mvweorse,t ceieonmceymoinfcayl rsoenamellipzlzeodxn y lohaf sFremsankel them not well suited for integration with wafer-scale processing. Effective medium structures have been proposed as an alternative1–5, but their deep subwavelength structures and high aspect ratios make their fabrication challenging. Recently, diffractive elements based on plasmonic metasurfaces composed of 2D arrays of ultrathin scatterers have attracted significant attention6–14, but their efficiency is limited to $25\\%$ by fundamental limitations15,16 and they also suffer from material absorption11. \n\nA novel approach is to use high-contrast gratings (HCGs), fabricated from semiconductors or high refractive index (highindex) dielectrics17–19, that can be designed with large reflection20 or transmission21 efficiencies. Wavefront control was originally achieved by rendering one dimensional gratings aperiodic by gradually modifying the local period and duty cycle of the gratin g21–23. Reflective focusing mirrors were realized using this approach21,23,24. Most devices based on 1D HCGs work only with one linear polarization and operate based on phase accumulation through the propagation or low-quality factor resonances in the grating. More recently, half wave plates were implemented using thin 1D HCGs, and lenses were realized through the Pancharatnam–Berry phase by locally rotating the half wave plates25. The later devices (which are referred to as dielectric gradient metasurface lenses) should be illuminated with a circularly polarized light, and their output is cross-polarized with respect to the input light25. \n\nA promising class of aperiodic HCGs can be realized by positioning high-index dielectric scatterers on a periodic subwavelength 2D lattice. The high-index results in negligible interaction among the scatterers, so the light scattered at each lattice site is dominated by the scatterer proprieties rather than by the collective behaviour of multiple coupled scatterers in the lattice. We refer to high-contrast zero-order gratings composed of disconnected scatterers, which operate in this local scattering regime, as high-contrast arrays. The term high-contrast transmitarrays (HCTAs) is used when they are designed for large transmission. Low numerical aperture (NA) lenses based on HCTA have been recently reported26,27. \n\nHere we explain the HCTA concept and discuss its unique features resulting from the localized scattering phenomena, which enable the implementation of diffractive elements with rapidly varying phase profiles. To demonstrate the HCTA versatility, we present design, simulation, fabrication and characterization results of polarization-insensitive high-NA micro-lenses with high focusing efficacy. High-NA lenses are required in microscopy, high-density data recording, focal plane arrays and coupling between on-chip photonic components and free-space beams. Current techniques to fabricate on-chip devices that impose rapid phase variation require grey-scale lithography28,29, a process that is difficult to control. On the other hand, the HCTA devices provide a more reliable alternative with fabrication techniques that lend themselves to wafer-scale processing. \n\n# Results \n\nTransmission characteristics of periodic HCTAs. An array of circular amorphous silicon posts arranged on a hexagonal lattice with subwavelength lattice constant is shown schematically in Fig. 1a. Due to the subwavelength lattice constant, the array acts as a zeroth order grating, and it is completely described by its transmission and reflection coefficients. Figure 1b shows the simulated transmission and phase of the transmission coefficient for two gratings composed of circular amorphous silicon posts arranged in hexagonal and rectangular lattices, as functions of lattice constant and post diameter (see Fig. 1 legend for dimensions). The gratings are designed to operate at $\\hat{\\lambda}=1,550\\mathrm{nm}$ , but the concept is scalable to any wavelength. In each case, the amplitude and phase depend primarily on the post diameter, which is an indication that, in this parameter regime, the scattering is a local effect and is not affected significantly by the coupling among the scatterers. This is also confirmed by the almost identical transmission properties of the hexagonal and square lattices. Examining the near-field distribution of the grating reveals the underlying physical mechanism behind the local scattering effect. As shown in Fig. 1c, light is concentrated inside the posts that behave as weakly coupled low-quality factor resonators. This behaviour is fundamentally different from the low-contrast gratings operating in the effective medium regime whose diffractive characteristics are mainly determined by the duty cycle and the filling factor. We also note that the structures created by changing the bar width and period of 1D HCGs (refs 21,23,24) are not considered HCTA since there is a strong coupling along the bar direction, and rapid variations of the local transmission or reflection properties of the structure are not achievable along that direction. \n\nDesign of HCTA micro-lenses. To design an HCTA that implements a transmissive phase mask, we find a family of periodic HCTAs with the same lattice but with different scatterers that provide large transmission amplitudes while their phases span the entire 0 to $2\\pi$ range. Such a family is shown in Fig. 1d where the diameters of $940\\mathrm{-nm}$ tall posts are varied from 200 to $550\\mathrm{nm}$ in a hexagonal lattice with an $800\\mathrm{-nm}$ period while transmission is ${>}92\\%$ . Large transmission has been reported for an array of circular posts with a height of $220\\mathrm{nm}$ (refs 30,31), but simulation results show that full $\\dot{2}\\pi$ phase coverage cannot be achieved for such an array by only changing the in-plane geometrical parameters. To design an HCTA that implements a desired phase mask, we start from an empty lattice and sample the desired phase profile at the lattice sites. Then, at each lattice site, we place a scatterer from the periodic HCTAs that most closely imparts the desired phase change onto the transmitted light. Any arbitrary transmissive phase masks can be realized using this method. To minimize scattering from aperiodic HCTAs into non-zero orders, a gradual change in the scatterer size is preferable. \n\nThe unprecedented possibility to realize any transmissive masks using HCTAs enables the implementation of micro-lenses with exotic phase profiles, such as high-NA micro-lenses, which are optimized for specific tasks. To design these components, the conventional ray tracing technique is not applicable. A general rigorous technique for determining the optimum transmissive mask to shape an incident optical wavefront to a desired form is given in Supplementary Note 1. Using this technique and the HCTAs in Fig. 1d, we found the optimum phase masks for microlenses that focus $\\lambda=1,550\\mathrm{nm}$ light from a single-mode fibre to the smallest diffraction limited spots. We designed a set of $400\\mathrm{-}\\upmu\\mathrm{m}$ diameter high-NA micro-lenses that focus the light from a single-mode fibre located $600\\upmu\\mathrm{m}$ away from the back side of a substrate $(500\\mathrm{-}\\upmu\\mathrm{m}$ thick fused silica) to points located at distances ranging from $d=50\\upmu\\mathrm{m}$ to $d=500\\upmu\\mathrm{{m}}$ away from the microlenses (Fig. 2a). We refer to $d$ as the focusing distance. \n\nMicro-lens full-wave simulation results. The performance of the micro-lenses was evaluated by 3D finite difference time domain (FDTD) simulations32. To reduce the simulation size, microlenses with the same NA but with a factor of four smaller dimensions ( $100\\upmu\\mathrm{m}$ diameter, $150\\upmu\\mathrm{m}$ spacing between the illuminating fibre and the back side of a $125\\mathrm{-}\\upmu\\mathrm{m}$ thick substrate) were simulated (see Methods for details). Figure $^{2\\mathrm{b},\\mathrm{c}}$ show the results for a micro-lens that focuses at $d=25\\upmu\\mathrm{m}$ away from the lens. The full width at half maximum (FWHM) of the focal spot is $1.06\\upmu\\mathrm{m}$ or $0.68\\lambda$ $\\langle\\lambda=1,550\\mathrm{nm},$ ). To differentiate between the power transmitted through the lens and the power directed by the lens toward the focus, we define the focusing efficiency as the fraction of the incident light that passes through a circular aperture in the plane of focus with a radius equal to three times the FWHM spot size. The simulation indicates $85\\%$ transmission efficiency and $72\\%$ focusing efficiency for the lens shown in Fig. $^{2\\mathrm{b},\\mathrm{c}}$ . \n\n![](images/a25c9bb800af6e4dd6d83378f08abc4b8f9d4a6a2c6b38c8aaa1fc5ce8761393.jpg) \nFigure 1 | Simulation results of periodic HCTAs. (a) A schematic representation of a periodic HCTA composed of high-index posts in a hexagonal lattice with transmission coefficient t and reflection coefficient r. The posts rest on a low-index substrate. (b) Simulated transmission and phase of the transmission coefficient for hexagonal and square lattice periodic HCTAs composed of circular amorphous silicon posts on a fused silica substrate as a function of the lattice constant and the post diameter. The insets show the corresponding lattices. (c) Top and side views of the colour coded magnetic energy density in a periodic HCTA for different post diameters D. The dashed black lines depict the boundaries of the silicon posts. A plane wave with magnetic energy density of 1 is normally incident on the silicon posts from the top. Scale bar, $1\\upmu\\mathrm{m}$ . (d) Simulated transmission and phase of the transmission coefficient for a family of periodic hexagonal HCTAs with lattice constant of $800{\\mathsf{n m}}.$ and varying post diameters. The shaded part of the graph is excluded when using this graph to map transmission phase to post diameter. In all these simulations, the posts are made of amorphous silicon $\\displaystyle{\\langle n=3.43\\rangle}$ ), are $940–\\mathsf{n m}$ tall and the wavelength is $\\lambda{=}1,550\\mathrm{nm}$ . \n\nSimulated values of the transmission, focusing efficiency and FWHM spot size for several micro-lenses with $d$ ranging from 12.5 to $125\\upmu\\mathrm{m}$ are presented in Fig. 2d. Higher NAs and smaller spot sizes correlate with decreased transmission and lower focusing efficiencies. This is due to the undersampling of the phase profiles of high-NA lenses, which rapidly vary close to the lens circumference. Shrinking the lattice constant of the HCTA reduces this trade-off (see Supplementary Note 2). \n\nThe micro-lens with $d=12.5{\\upmu\\mathrm{m}}$ has an FWHM spot size of $0.51\\lambda,$ which is close to the smallest possible diffraction limited value of $0.5\\lambda$ . The relatively high efficiency $(>50\\%)$ and the diffraction limited focusing of this micro-lens confirms the validity of our technique for determining the optimum phase profile, and demonstrates an example of the high performance that can be achieved by HCTA flat diffractive elements. \n\nFabrication and characterization of micro-lenses. The high-NA lenses were fabricated in a hydrogenated amorphous silicon film deposited on a ${500}\\mathrm{-}\\upmu\\mathrm{m}$ thick fused silica substrate as described in the Methods section. A schematic illustration and images of the fabricated devices are shown in Fig. 3a–d. The characterization was performed in a setup (Fig. 4a) consisting of a custom built microscope that images the plane of focus of the micro-lens (see Methods). The micro-lenses were illuminated with $1,550\\mathrm{-nm}$ light emitted from a cleaved single-mode fibre positioned $600\\upmu\\mathrm{m}$ away from the substrate back side. The normalized measured intensity profile at the plane of focus for a micro-lens with the focusing distance of $d{\\stackrel{-}{=}}50\\upmu\\mathrm{m}$ is shown in Fig. 4b. The intensity profiles for micro-lenses with different focusing distance are plotted in Fig. 4c. \n\n![](images/be0b3203cd56a64b820a7ba9d6aff9080d4a60fb43cbe0eec614d68bf3429b5f.jpg) \nFigure 2 | Simulation results of high-NA HCTA micro-lenses. (a) Illustration of high-NA focusing of the light from a cleaved optical fibre using an HCTA micro-lens. (b) Electric field distribution at the xz cross section, in the excitation plane (inset), and immediately after passing through the micro-lens (inset). Incident light propagates along the z direction. Scale bars, $10\\upmu\\mathrm{m}$ . (c) Logarithmic scale electric energy density in the xz cross section. The inset shows the real part of the z component of the Poynting vector at the plane of focus. Scale bars, $20\\upmu\\mathrm{m}$ in the main figure and $2\\upmu\\mathrm{m}$ in the inset. (d) Simulated plane of focus FWHM spot size, transmission and focusing efficiency of the high-NA HCTA micro-lenses for devices with varying focusing distances. The simulated points are shown by the symbols and the solid lines are eye guides. All the devices simulated in this figure are a factor of four smaller than the devices fabricated and measured in Figs 3 and 4. \n\n![](images/2200fdd076be44d5d57f7445179b22cee7097b9f80e0f4bc17fff89e2288b67f.jpg) \nFigure 3 | Schematic illustration and images of fabricated HCTA lenses. (a) Schematic of the aperiodic HCTA used to realize a high-NA micro-lens. (b) Optical microscope image of a fabricated HCTA lens with large NA. Scale bar, $100\\upmu\\mathrm{m}$ . (c,d) Scanning electron microscope images of the silicon posts forming the HCTA micro-lens. Scale bars, $1\\upmu\\mathrm{m}$ . \n\nFigure 4d shows the measured FWHM spot size, transmission and focusing efficiency for devices with different focusing distances. The micro-lens designed for $d=50\\upmu\\mathrm{m}$ focuses light to a $0.57\\lambda$ FWHM spot size, and the micro-lens designed for $d=500\\upmu\\mathrm{m}$ shows ${>}82\\%$ focusing efficiency. These results agree well with the simulation results presented in Fig. 2d, although the measured focusing efficiencies are $10\\%$ smaller $3\\%$ is attributed to reflection from substrate backside interface and $7\\%$ to scattering by the random roughness of the etched silicon posts). As it was expected from the simulations (Fig. 2d), the measured focusing efficiency decreases as the NA increases. \n\nWavelength dependence of HCTA micro-lenses. The wavelength dependence of the FWHM spot size and focusing efficiency of a micro-lens with $d=175{\\mathrm{~}}{\\mathrm{\\textmum}}$ are presented in Fig. 4e. The FWHM spot size increases slightly at shorter wavelength, and the focusing efficiency reduces by $\\sim5\\%$ at $50\\mathrm{nm}$ away from the design wavelength. Also, by changing the laser wavelength from 1,550 to $1,450\\mathrm{nm}$ , the focusing distance changed from $\\sim175$ to $\\sim195\\upmu\\mathrm{m}$ . \n\n# Discussion \n\nTable 1 summarizes the performance parameters of some of the experimentally reported thin flat micro-lenses. The HCTA microlenses with focusing efficiencies up to $82\\%$ , and FWHM spot sizes down to $0.57\\lambda$ , to the best of our knowledge, represent the best performance among any types of flat high-NA micro-lens experimentally reported so far. As discussed earlier, lenses with small focal spot size (or equivalently high NA) require rapidly varying phase profiles and accurate correction for spherical aberration. Rapidly varying phase profiles can be realized using arrays of scatterers provided that the phase profile is sampled by the scatterers with sufficient spatial resolution, and the scatterers are weakly coupled to each other to avoid the strong near-field coupling among them, which filters the rapid spatial variations in the phase profiles. As we showed, the couplings among the scatterers are weak in the HCTA platform, and the array period is smaller than a wavelength; therefore, this platform allows for the implementation of high-NA lenses. Also, the rigorous method we used for finding the optimum phase profile for the lenses minimizes the spherical aberration. Any metasurface platform that achieves the $2\\pi$ phase coverage, and samples rapidly varying phase profiles with subwavelength spatial resolution using weakly coupled scatterers can be used to implement the high-NA lenses; \n\n![](images/3ef180fd37a3cd74d9aa7b5400bb9bcb6bfc17e7d241c4c41383e9dac841e1e7.jpg) \nFigure 4 | Measurement results of high-NA HCTA micro-lenses. (a) Measurement setup for imaging the focal spot size and measuring the efficiency of the high-NA HCTA micro-lenses. The flip mirror was inserted into the setup only during efficiency measurements. (b) Measured 2D intensity profile at the plane of focus for a micro-lens with $d=50\\upmu\\mathrm{m}$ . Scale bar, $1\\upmu\\mathrm{m}$ . (c) Normalized measured intensity profiles of high-NA micro-lenses with different focal lengths at their planes of focus. (d) Measured plane of focus FWHM spot size, transmission and focusing efficiency of the HCTA micro-lenses as a function of their focusing distance. (e) Wavelength dependence of the FWHM spot size, transmission and focusing efficiency for the micro-lens with $d=175\\upmu\\mathrm{m}$ . The measurement data in d and e are represented by the symbols, the solid lines are eye guides, and the error bars represent the s.d. for three alignment repetitions. \n\n
Table 1 | Summary of previously reported thin flat micro-lenses.
ReferenceFWHM spot size ()EfficiencyPolarizationa (nm)Lens thickness ()
Aieta et al.11~33~1%Linear (cross*)1,5500.038
Ni et al.120.93~10%Linear (cross)6760.044
This work2.4~ 82%Insensitive1,5500.65
This work0.57~ 42%Insensitive1,5500.65
Vo et al.27~10~70%Insensitive8500.56
Lin et al.251.2 Not reportedCircular (cross)5500.18
\n\n\\*Cross: focused light is cross-polarized compared with the incident light. wThe ratio between the power of the cross-polarized light transmitted through the lens and the total power collected by the lens at the illumination side. $\\ddagger\\sim45\\%$ diffraction efficiency is reported for a blazed grating at $550\\mathsf{n m}.$ the operation wavelength of the lens. Higher diffraction efficiencies up to $85\\%$ can be theoretically achieved at other wavelengths. The diffraction efficiency is defined as the ratio of the first diffraction order power to the summation of the powers of the zeroth and first diffraction orders, and it does not take into account the losses due to reflection, absorption and incomplete polarization conversion. \n\nhowever, for achieving high focusing efficiency, it is essential to avoid platforms whose efficiencies are limited by absorption losses or fundamental physical limits. \n\nIn conclusion, the HCTAs enable shaping of the wavefront of light at will, efficiently and with subwavelength resolution. The exceptional freedom provided in the implementation of any desired masks allows for achieving the best performance for any particular functionality. Combined with their planar form factor, these structures will enable on-chip optical systems created by cascading multiple diffractive elements. One recent demonstration is a planar retroreflector integrating an HCTA lens and a reflectarray focusing mirror33. We envision near-future application of HCTA-based devices in realization of more complex optical systems with new functionalities. \n\n# Methods \n\nSample fabrication. The HCTA pattern was defined in ZEP520A positive resist using a Vistec EBPG5000 þ electron beam lithography system. After developing the resist, the pattern was transferred into a $70\\mathrm{-nm}$ thick aluminium oxide layer deposited by electron beam evaporation using the lift-off technique. The patterned aluminium oxide served as hard mask for the dry etching of the $940–\\mathrm{nm}$ thick silicon layer in a mixture of $\\mathrm{C_{4}F_{8}}$ and ${\\mathrm{SF}}_{6}$ plasma, and was subsequently removed through wet etching in a mixture of ammonium hydroxide and hydrogen peroxide at $80^{\\circ}\\mathrm{C}$ . \n\nMeasurement procedure. The microscope uses a $100\\times$ objective (Olympus UMPlanFl) with the NA of 0.95 and a tube lens (Thorlabs LB1945-C) with focal distance of $20\\mathrm{cm}$ , which is anti-reflection coated for the $1,050\\mathrm{-}1,620\\mathrm{nm}$ wavelength range. The magnification of the microscope was found by imaging a calibration sample with known feature dimensions. \n\nThe transmission and focusing efficiency of the micro-lenses were measured by inserting a flip mirror (as shown in Fig. 4a) in front of the camera. To measure the optical power focused by the micro-lens, the active area of the photodetector (Newport 818-IR) was reduced using an iris. The radius of the iris aperture was adjusted to three times of the measured FWHM spot size of the micro-lens on the camera. The total transmitted power was measured by opening the iris aperture completely. The total power incident on the microlens was measured by removing the micro-lens from the setup and bringing the fibre tip into the focus of the microscope. The non-uniformities seen in the intensity profile in Fig. 4 are due to the local variations in the sensitivity of the camera (Digital CamIR 1,550 by Applied Scintillation Technologies) and are observed even when directly imaging the light from an optical fibre. \n\nSimulations. We found the electric and magnetic fields of the light from the fibre on a plane close to the lens using the plane wave expansion technique. Then, these fields were used to determine the equivalent electric and magnetic surface current densities, which were used as excitation sources in the FDTD simulations. This allowed us to reduce the size of the simulation domain to a smaller volume surrounding the micro-lens. \n\nIn Fig. 2, the FWHM spot size is found by fitting a 2D Gaussian function to the $z$ component of the Poynting vector at the plane of focus (shown in Fig. 2c). The focusing efficiency is defined as the fraction of the incident light that passes through a circular aperture in the plane of focus with a radius equal to three times the FWHM spot size. \n\n# References \n\n1. Stork, W., Streibl, N., Haidner, H. & Kipfer, P. Artificial distributed-index media fabricated by zero-order gratings. Opt. Lett. 16, 1921–1923 (1991). \n2. Chen, F. T. & Craighead, H. G. Diffractive phase elements based on two-dimensional artificial dielectrics. Opt. Lett. 20, 121–123 (1995). \n3. Warren, M. E., Smith, R. E., Vawter, G. A. & Wendt, J. R. High-efficiency subwavelength diffractive optical element in GaAs for 975 nm. Opt. Lett. 20, 1441–1443 (1995). \n4. Chen, F. T. & Craighead, H. G. Diffractive lens fabricated with mostly zeroth-order gratings. Opt. Lett. 21, 177–179 (1996). \n5. Lalanne, P., Astilean, S., Chavel, P., Cambril, E. & Launois, H. Blazed binary subwavelength gratings with efficiencies larger than those of conventional e´chelette gratings. Opt. Lett. 23, 1081–1083 (1998). \n6. Verslegers, L. et al. Planar lenses based on nanoscale slit arrays in a metallic film. Nano Lett. 9, 235–238 (2009). \n7. Yu, N. et al. Light propagation with phase discontinuities: generalized laws of reflection and refraction. Science 334, 333–337 (2011). \n8. Kildishev, A. V., Boltasseva, A. & Shalaev, V. M. Planar photonics with metasurfaces. Science 339, 1232009 (2013). \n9. Yu, N. & Capasso, F. Flat optics with designer metasurfaces. Nat. Mater. 13, 139–150 (2014). \n10. Huang, F. M., Kao, T. S., Fedotov, V. A., Chen, Y. & Zheludev, N. I. Nanohole array as a lens. Nano Lett. 8, 2469–2472 (2008). \n11. Aieta, F. et al. Aberration-free ultrathin flat lenses and axicons at telecom wavelengths based on plasmonic metasurfaces. Nano Lett. 12, 4932–4936 (2012). \n12. Ni, X., Ishii, S., Kildishev, A. V. & Shalaev, V. M. Ultra-thin, planar, Babinet-inverted plasmonic metalenses. Light Sci. Appl. 2, e72 (2013). \n13. Genevet, P. et al. Ultra-thin plasmonic optical vortex plate based on phase discontinuities. Appl. Phys. Lett. 100, 013101 (2012). \n14. Karimi, E. et al. Generating optical orbital angular momentum at visible wavelengths using a plasmonic metasurface. Light Sci. Appl. 3, e167 (2014). \n15. Monticone, F., Estakhri, N. M. & Alu\\`, A. Full control of nanoscale optical transmission with a composite metascreen. Phys. Rev. Lett. 110, 203903 (2013). \n16. Arbabi, A. & Faraon, A. Fundamental limits of ultrathin metasurfaces. Preprint at http://arxiv.org/abs/1411.2537 (2014). \n17. Chen, L., Huang, M. C. Y., Mateus, C. F. R., Chang-Hasnain, C. J. & Suzuki, Y. Fabrication and design of an integrable subwavelength ultrabroadband dielectric mirror. Appl. Phys. Lett. 88, 031102 (2006). \n18. Kemiktarak, U., Metcalfe, M., Durand, M. & Lawall, J. Mechanically compliant grating reflectors for optomechanics. Appl. Phys. Lett. 100, 061124 (2012). \n19. Wu, T. T. et al. Sub-wavelength GaN-based membrane high contrast grating reflectors. Opt. Express 20, 20551–20557 (2012). \n20. Mateus, C., Huang, M., Deng, Y., Neureuther, A. & Chang-Hasnain, C. Ultrabroadband mirror using low-index cladded subwavelength grating. IEEE Photon. Technol. Lett. 16, 518–520 (2004). \n21. Lu, F., Sedgwick, F. G., Karagodsky, V., Chase, C. & Chang-Hasnain, C. J. Planar high-numerical-aperture low-loss focusing reflectors and lenses using subwavelength high contrast gratings. Opt. Express 18, 12606–12614 (2010). \n22. Astilean, S., Lalanne, P., Chavel, P., Cambril, E. & Launois, H. High-efficiency subwavelength diffractive element patterned in a high-refractive-index material for 633 nm. Opt. Lett. 23, 552–554 (1998). \n23. Fattal, D., Li, J., Peng, Z., Fiorentino, M. & Beausoleil, R. G. Flat dielectric grating reflectors with focusing abilities. Nat. Photonics 4, 466–470 (2010). \n24. Klemm, A. B. et al. Experimental high numerical aperture focusing with high contrast gratings. Opt. Lett. 38, 3410–3413 (2013). \n25. Lin, D., Fan, P., Hasman, E. & Brongersma, M. L. Dielectric gradient metasurface optical elements. Science 345, 298–302 (2014). \n26. Arbabi, A. et al. Controlling the phase front of optical fiber beams using high contrast metastructures - OSA Technical Digest (online). In CLEO: 2014. STu3M.4 Optical Society of America, 2014; Available at http://www. opticsinfobase.org/abstract.cfm?URI=CLEO_SI-2014-STu3M.4. \n27. Vo, S. et al. Sub-wavelength grating lenses with a twist. IEEE Photon. Technol. Lett. 26, 1375–1378 (2014). \n28. Shiono, T., Kitagawa, M., Setsune, K. & Mitsuyu, T. Reflection micro-Fresnel lenses and their use in an integrated focus sensor. Appl. Opt. 28, 3434–3442 (1989). \n29. Haruna, M., Takahashi, M., Wakahayashi, K. & Nishihara, H. Laser beam lithographed micro-Fresnel lenses. Appl. Opt. 29, 5120–5126 (1990). \n30. Staude, I. et al. Tailoring directional scattering through magnetic and electric resonances in subwavelength silicon nanodisks. ACS Nano 7, 7824–7832 (2013). \n31. Decker, M. et al.High-efficiency light-wave control with all- dielectric optical Huygens’ metasurfaces. Preprint at http://arxiv.org/abs/1405.5038 (2014). \n32. Oskooi, A. F. et al. Meep: A flexible free-software package for electromagnetic simulations by the FDTD method. Comput. Phys. Commun. 181, 687–702 (2010). \n33. Arbabi, A., Horie, Y. & Faraon, A. Planar retroreflector - OSA Technical Digest (online). In CLEO: 2014. STu3M.5 Optical Society of America, 2014; Available at http://www.opticsinfobase.org/abstract.cfm?URI=CLEO_SI-2014-STu3M.5. \n\n# Acknowledgements \n\nThis work was supported by the Caltech/JPL president and director fund (PDF). A.A. was also supported by DARPA. Y.H. was supported by the JASSO fellowship and the ‘Light-Material Interactions in Energy Conversion’ Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under Award no. DE-SC0001293. Alexander Ball was supported by the Summer Undergraduate Research Fellowship (SURF) at Caltech. The device nanofabrication was performed in the Kavli Nanoscience Institute at Caltech. We thank David Fattal and Sonny Vo for useful discussion. \n\n# Author contributions \n\nA.A., M.B. and A.F. conceived the experiment. A.A. and A.J.B. performed the FDTD simulations. A.A., Y.H. and M.B. fabricated the samples. A.A. performed the measurements, and analysed the data. A.A. and A.F. wrote the manuscript with input from all authors. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Arbabi, A. et al. Subwavelength-thick lenses with high numerical apertures and large efficiency based on high-contrast transmitarrays. Nat. Commun. 6:7069 doi: 10.1038/ncomms8069 (2015). " + }, + { + "id": "10.1021_jacs.5b08212", + "DOI": "10.1021/jacs.5b08212", + "DOI Link": "http://dx.doi.org/10.1021/jacs.5b08212", + "Relative Dir Path": "mds/10.1021_jacs.5b08212", + "Article Title": "Metal-Organic Frameworks for Electrocatalytic Reduction of Carbon Dioxide", + "Authors": "Kornienko, N; Zhao, YB; Kiley, CS; Zhu, CH; Kim, D; Lin, S; Chang, CJ; Yaghi, OM; Yang, PD", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "A key challenge in the field of electrochemical carbon dioxide reduction is the design of catalytic materials featuring high product selectivity, stability, and a composition of earth-abundant elements. In this work, we introduce thin films of nullosized metal organic frameworks (MOFs) as atomically defined and nulloscopic materials that function as catalysts for the efficient and selective reduction of carbon dioxide to carbon monoxide in aqueous electrolytes. Detailed examination of a cobalt porphyrin MOF, Al-2(OH)(2)TCPP-Co (TCPP-H-2 = 4,4',4 '',4 '''-(porphyrin-5,10,15,20-tetrayl)tetrabenzoate) revealed a selectivity for CO production in excess of 76% and stability over 7 h with a per-site turnover number (TON) of 1400. In situ spectroelectrochemical measurements provided insights into the cobalt oxidation state during the course of reaction and showed that the majority of catalytic centers in this MOF are redox-accessible where Co(II) is reduced to Co(I) during catalysis.", + "Times Cited, WoS Core": 959, + "Times Cited, All Databases": 1033, + "Publication Year": 2015, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000364727600025", + "Markdown": "# Metal−Organic Frameworks for Electrocatalytic Reduction of Carbon Dioxide \n\nNikolay Kornienko,†,□ Yingbo Zhao,†,□ Christopher S. Kley,† Chenhui Zhu,⊥ Dohyung Kim,‡ Song Lin,†,# Christopher J. Chang,†,§,∥,# Omar M. Yaghi, $*,\\dag,\\tilde{\\nabla},\\mathrm{O},\\Phi\\$ and Peidong Yang\\*,†,‡,∇,◆ \n\n†Department of Chemistry, ‡Department of Materials Science and Engineering, §Howard Hughes Medical Institute, and ∥Department \nof Molecular and Cell Biology, University of California, Berkeley, California 94720, United States \n⊥Advanced Light Source, #Chemical Sciences Division, and ∇Materials Sciences Division, Lawrence Berkeley National Laboratory, \nBerkeley, California 94720, United States \n○King Abdulaziz City of Science and Technology, P.O. Box 6086, Riyadh 11413, Saudi Arabia \n◆Kavli Energy Nanosciences Institute, Berkeley, California 94720, United States \n\n\\*S Supporting Information \n\nABSTRACT: A key challenge in the field of electrochemical carbon dioxide reduction is the design of catalytic materials featuring high product selectivity, stability, and a composition of earth-abundant elements. In this work, we introduce thin films of nanosized metal−organic frameworks (MOFs) as atomically defined and nanoscopic materials that function as catalysts for the efficient and selective reduction of carbon dioxide to carbon monoxide in aqueous electrolytes. Detailed examination of a cobalt− porphyrin MOF, $\\mathrm{Al}_{2}\\mathrm{(OH)}_{2}\\mathrm{TCPP-Co}$ $\\mathrm{^{\\prime}T C P P-H_{2}}=4{,}4^{\\prime}{,}4^{\\prime\\prime}{,}4^{\\prime\\prime\\prime}.$ -(porphyrin-5,10,15,20- tetrayl)tetrabenzoate) revealed a selectivity for CO production in excess of $76\\%$ and stability over $^\\mathrm{~7~h~}$ with a per-site turnover number (TON) of 1400. In situ spectroelectrochemical measurements provided insights into the cobalt oxidation state during the course of reaction and showed that the majority of catalytic centers in this MOF are redox-accessible where ${\\mathrm{Co}}(\\mathrm{II})$ is reduced to $\\mathrm{Co}(\\mathrm{I})$ during catalysis. \n\n![](images/7f7dae781ef8c81d6cd22ba7b1d31e2242ed00e7e1b19e7078e111c503d2537f.jpg) \n\n# INTRODUCTION \n\nOne of the most attractive approaches toward providing carbon-neutral energy is the electrochemical conversion of atmospheric carbon dioxide $\\left(\\mathrm{CO}_{2}\\right)$ into energy-dense carbon compounds to be used as fuels and chemical feedstock.1−4 Extensive efforts have been devoted to the development of homogeneous and heterogeneous catalysts for this purpose. The outstanding challenges remain in the design of catalyst systems featuring (i) selectivity for $\\mathrm{CO}_{2}$ reduction in water with minimum $\\mathrm{H}_{2}$ generation, (ii) long-term stability, (iii) catalytic efficiency at low electrochemical overpotential, and (iv) compositions of earth abundant materials. In this report, we show that nanosized metal−organic frameworks (MOFs) meet these criteria and also present additional opportunities because of the modular nature of MOFs in which their organic and inorganic components can be functionalized and modified prior to precise arrangement in the MOF crystal structure.5−12 We chose a stable cobalt porphyrin MOF where these porphyrin units are linked with aluminum oxide rods to form a 3D porous structure with pores of $6\\times11\\mathrm{~\\AA~}^{2}$ . Electrochemical $\\mathrm{CO}_{2}$ reduction studies were carried out on thin films of this MOF, which was found to convert $\\mathrm{CO}_{2}$ to CO selectively $(76\\%$ Faradaic efficiency) and with high turnover number $\\mathrm{\\Delta^{\\prime}T O N=}$ 1400). In situ spectroelectrochemical measurements revealed that the ${\\mathrm{Co}}(\\mathrm{II})$ centers are reduced to $\\mathrm{Co(I)}$ throughout the MOF and subsequently reduce $\\mathrm{CO}_{2}$ . This is the first MOF catalyst constructed for the electrocatalytic conversion of aqueous $\\mathrm{CO}_{2}$ to CO, and its high-performance characteristics are encouraging for the further development of this approach. \n\nIn the context of aqueous electrocatalytic $\\mathrm{CO}_{2}$ reduction studies where heterogeneous catalysts such as metal foils,13−17 metal nanostructures, 18−26 oxide-derived metals,27−29 2D materials,30 carbon nanomaterials,31−33 as well as bioinspired 34−3 7 and homogeneous molecular catalysts38−47 catalysts, are used, MOFs combine the favorable characteristics of both heterogeneous and homogeneous catalysts. Exploration of MOFs for $\\mathrm{CO}_{2}$ reduction has just begun through their use as photocatalysts in colloidal dispersions, however, with the aid of sacrificial reagents,48−52 and MOFs and COFs have only recently been utilized as electrocatalysts for $\\mathrm{CO}_{2}$ reduction.53−56 \n\nOur strategy to construct the MOF-based electrochemical $\\mathrm{CO}_{2}$ reduction system was to select MOFs with catalytic linker units and fabricate them into thin films covering conductive substrates (Figure 1): Appropriate catalytic linker units (Figure 1A) are assembled into a porous thin film MOF (Figures 1B and S1), which is grown on a conductive substrate (Figure 1C). We first screened MOFs with systematically varied building blocks and then chose the most promising MOF catalyst for indepth electrochemical studies. The thickness of the selected MOF was next optimized to yield the final $\\mathrm{CO}_{2}$ -reduction system, which was shown to be active, selective, and stable toward CO production. We also demonstrate that the majority of cobalt centers are reduced from ${\\mathrm{Co}}(\\mathrm{II})$ to $\\mathrm{Co(I)}$ during the electrochemical process through in situ spectroelectrochemical measurements. Using MOFs as heterogeneous electrocatalysts represents an efficient strategy to reticulate catalytic molecular units into a porous network in which the number of active sites is maximized and both charge and mass transported could be simultaneously balanced by controlling the nanoscopic MOF morphology and thickness. \n\n![](images/746d081dd3e8f4a659f8b1c4afd8ce161678ac38ef3d773a861c308bd72f78c3.jpg) \nFigure 1. Our MOF catalyst allows for modulation of metal centers, molecular linkers, and functional groups at the molecular level (A). The organic building units, in the form of cobalt-metalated TCPP, are assembled into a 3D MOF, $\\mathrm{Al}_{2}(\\mathrm{OH})_{2}\\mathrm{TCPP-Co}$ with variable inorganic building blocks (B). Co, orange spheres; $^{\\mathrm{~O~},}$ red spheres; C, black spheres; N, blue spheres; Al, light-blue octahedra; and pyrrole ring, blue. In this structure, each carboxylate from A is bound to the aluminum inorganic backbone.The MOF is integrated with a conductive substrate to achieve a functional $\\mathrm{CO}_{2}$ electrochemical reduction system (C). \n\n![](images/2a1ebf10087d88ab9f7c53b45053394a9de6f985321fa46b6f247e0352ec662e.jpg) \nFigure 2. Voltammogram trace of the MOF catalyst exhibits a current increase in a $\\mathrm{CO}_{2}$ environment relative to an argon-saturated environment (A). As the scan rate is systematically increased in a $\\mathrm{CO}_{2}$ -saturated electrolyte (B), the electrochemical waves increase in magnitude proportional to the square root of the scan rate (C), indicative of a diffusion-limited process. The MOF catalytic performance is maximized at a starting layer thickness of 50 ALD cycles (D), which offers a balance of charge transport, mass transport, and active-site density. The selectivity for each product is tested over a potential range of $-0.5$ to $-0.9$ vs RHE (E) and reaches upward of $76\\%$ for CO. The steady-state current density for product quantification is illustrated in F. In the low-overpotential region, the Tafel slope of $165\\mathrm{mV},$ /decade is closest to that of a one-electron reduction from $\\mathrm{CO}_{2}$ to the $\\mathrm{CO}_{2}$ · rate-limiting step (G). \n\n# RESULTS AND DISCUSSION \n\nThe catalysts we selected in this work are the $\\mathrm{\\calAl}_{2}(\\mathrm{OH})_{2}\\mathrm{TCPP}.$ - $\\mathrm{H}_{2}$ series $\\begin{array}{l l l}{{\\left[\\mathrm{TCPP-H_{2}}\\ =\\ 4,4^{\\prime},4^{\\prime\\prime},4^{\\prime\\prime\\prime}\\right.}}\\end{array}$ -(porphyrin-5,10,15,20- tetrayl)tetrabenzoate], which incorporates the porphyrinbased molecular units previously reported as selective and efficient homogeneous $\\mathrm{CO}_{2}$ -reduction electrocatalysts.39,57,58 \n\nSpecifically, the cobalt-metalated porphyrin units are known to be of particular interest for $\\mathrm{CO}_{2}$ reduction and are explored in detail in this work. $59-61$ The advantage over using molecular porphyrins as homogeneous catalysts is that each active site is simultaneously exposed to the electrolyte and electrically connected to the conductive support. We employ our previously developed methodology for thin-film MOF synthesis,62 which involves the ALD deposition of metal oxide thin films as metal precursors onto the electrode and subsequent MOF creation through reacting the coated electrode with the appropriate linker in a DMF solvent in a microwave reactor.63 \n\n![](images/8da59d9dc2052e7a315dadac314778f54ef2bab27faa643e012b84466e6958da.jpg) \nFigure 3. Stability of the MOF catalyst is evaluated through chronoamperometric measurements in combination with faradaic efficiency measurements. The green trace represents geometric current density, and the blue diamonds denote CO Faradaic efficiency (A). XRD analysis indicates that the MOF retains its crystalline structure after chronoamperometric measurement (B). SEM images of the MOF catalyst film before (C) and after electrolysis (D) reveal the retention of the platelike morphology. \n\nInitially, we studied the effect of employing different metal centers in the porphyrin units on the catalytic properties of the MOF (Figures S2 and S3). We began with 50 ALD cycles of alumina thin films (thickness of $5~\\mathrm{{nm}}$ ) deposited onto conductive carbon disk electrodes, and converted the alumina film to porphyrin-containing MOF $[\\mathrm{Al}_{2}(\\mathrm{OH})_{2}\\mathrm{TCPP-M^{\\prime}}]$ structures with free-base porphyrin as well as porphyrin centers metalated with $\\mathbf{M}^{\\prime}=\\mathbf{Z}\\mathbf{n}_{\\ast}$ , Cu, and Co. Cyclic voltammetry (CV) measurements of the synthesized metalated-porphyrin-containing MOFs under an argon or carbon dioxide environment were used to screen the MOF catalytic performance (Figure S2). The voltammogram traces feature redox waves attributed to the reduction of the metal centers and catalytic peaks stemming from the reduction of either protons or aqueous $\\mathrm{CO}_{2},$ qualitatively matching the behavior of previously studied analogous porphyrin homogeneous catalysts.57 Notably, the cobalt-metalated MOF exhibits the highest relative increase in current density after saturating the solution with carbon dioxide (1 atm, $33~\\mathrm{mM}$ concentration), increasing from 3.5 to ${5.9\\mathrm{\\mA}}/$ $\\mathrm{cm}^{2}$ . Hence, this particular catalyst is chosen for further indepth examination. Previous works have reported differences in activity and selectivity among porphyrins and porphyrin analogues with different metal centers, and cobalt was consistently among the best.64,65 The increase in current density under a $\\mathrm{CO}_{2}$ atmosphere for this catalyst may be due to the preferred binding to $\\mathrm{CO}_{2}$ and increased kinetics of $\\mathrm{CO}_{2}$ reduction relative to hydrogen generation for this active site. To exhibit a further layer of modularity with our MOF-based catalyst design, we modified the inorganic backbone to prepare cobalt-metalated $[\\bf M_{2}(\\mathrm{OH})_{2}T C P P{-}\\bar{\\bf C o},$ $\\mathbf{M}=\\mathbf{Al}$ and In] MOFs (Figures S4 and S5). The In- and In−Al-based MOF catalysts also exhibit significant current density increases under a $\\mathrm{CO}_{2}.$ - saturated aqueous bicarbonate electrolyte relative to an argonbubbled electrolyte, suggesting that the porphyrin units are the essential catalytic active center and that the inorganic backbone may be tuned for additional purposes. \n\nOn the basis of our initial catalyst screening, we focused our subsequent investigation on the $[\\mathrm{Al}_{2}(\\mathrm{OH})_{2}\\mathrm{\\bar{T}C P P-C o}]$ MOF. The voltammogram trace of this MOF showed an enhanced current density under a $\\mathrm{CO}_{2}$ -saturated solution relative to that in an argon-saturated solution and displayed a redox couple in addition to an irreversible catalytic peak (Figure 2A). Increasing the CV scan rates (Figure 2B) illustrated that a cathodic wave centered roughly at $-0.4$ to $-0.5\\mathrm{~V~}$ versus the reversible hydrogen electrode (RHE), an irreversible catalytic peak immediately following, and an anodic peak at $-0.2\\mathrm{~V~}$ vs RHE increase in magnitude in a manner linearly proportional to the square root of the sweep rate, indicative of a diffusion-limited process (Figure 2C).66,67 The first cathodic wave and the lone anodic wave are likely limited by counterion diffusion to balance a $\\mathrm{Co}\\mathrm{(II/I)}$ redox change, and the irreversible cathodic peak, which is not voltammetric, at the most negative potentials stems from the diffusion and subsequent reduction of carbon dioxide. The anodic−cathodic wave separation increased from ${\\sim}100$ to ${\\sim}250~\\mathrm{mV}$ with increasing sweep rate, which provided further evidence that the underlying reaction is not a simple reversible redox process. Previous electrochemical studies of cobalt porphyrins have attributed a cathodic wave at approximately $-0.5\\mathrm{~V~}$ vs RHE to the reduction of the ${\\mathrm{Co}}(\\mathrm{II})$ center to $\\mathrm{Co(I)}$ , and we see similar behavior for the homogeneous $\\mathrm{H_{4}T C P P-C o}$ (Figure S6).68 Spectroelectrochemical studies confirmed the chemical nature of this cathodic wave as discussed below. \n\nBalancing reactant diffusion and charge transport is essential for electrochemical catalysis. To this end, the thickness of the MOF catalyst film was tuned to optimize the performance of the MOF catalyst by varying the starting ALD alumina layer thickness from 0.5 to $10\\ \\mathrm{nm}$ (Figure 2D). Upon testing a carbon disk electrode with only 5 layers $\\left(0.5\\ \\mathrm{nm}\\right)$ of ALD precursor converted to the MOF, resulting in an ${\\sim}10~\\mathrm{nm}$ thick MOF layer, we observed a twofold increase in the catalytic current density (measured at $-0.57\\mathrm{~V~}$ vs RHE at a sweep rate of $100~\\mathrm{{mV/s}}$ ) relative to that of the bare carbon disk substrate. The performance of the MOF catalyst increased with increasing active-site loading until reaching a maximum at 50 ALD cycles (MOF thickness of ${\\sim}30{\\mathrm{-}}70~\\mathrm{nm},$ ). Inductively coupled plasma atomic emission absorption (ICP-AES) was utilized to quantify the total cobalt loading on this sample and indicated an upper limit of $6.1\\times10^{16}$ cobalt atoms $(\\bar{1.1}\\times10^{-7}\\mathrm{mol}),$ per square centimeter. The performance decrease observed for higher active-site loading is likely due to charge-transport limitations from the electrode to the MOF periphery or impedance through a thin insulating alumina layer not fully converted to the MOF. This result highlights the strength of our ALD-based MOF conversion technique, which allows nanometer precision of catalyst loading to balance active-site density with mass/ charge transfer. \n\n![](images/c17b7c996bf693a29f78cb8995f37a391b45c2aa503e27d831d6c5e9439d7385.jpg) \nFigure 4. In situ spectroelectrochemical analysis reveals the oxidation state of the cobalt catalytic unit of the MOF under reaction conditions. Upon varying the voltage from 0.2 to $-0.7\\:\\mathrm{V}$ vs RHE, the $\\mathrm{Co}(\\mathrm{II})$ Soret band decreases at $422~\\mathrm{nm}$ and is accompanied by a $\\mathrm{Co(I)}$ Soret band increase at $408~\\mathrm{nm}$ (A). This change is quantified and plotted (B) to elucidate a formal redox potential of the Co center, which is deemed to be at the peak of the first derivative (C) of the $\\mathrm{Co}(\\mathrm{II})$ bleach and $\\mathrm{Co}(\\mathrm{I})$ enhancement. \n\nComprehensive product analysis using gas chromatography (GC) and nuclear magnetic resonance (NMR) was carried out to reveal the nature of the chemical processes occurring within our MOF catalysts (Figure S7). As illustrated in Figure 2E, the two main products measured were CO and $\\mathrm{H}_{2},$ with current selectivity for CO reaching up to $76\\%$ at $-0.7\\mathrm{V}$ vs RHE. The average steady-state current density from these measurements is displayed in Figure 2F. In contrast, the unmetalated MOF produces primarily $\\mathrm{H}_{2}$ (Figure S8). When plotting the partial current density for CO production on a logarithmic scale versus the thermodynamic overpotential (Figure 2G), we obtain a Tafel slope of $165~\\mathrm{mV/}$ decade in the low-overpotential region, which points to a one-electron reduction of $\\mathrm{CO}_{2}$ to form the $\\mathrm{CO}_{2}^{\\cdot}$ radical as a probable rate-limiting step, though the reaction is likely to be at least in part diffusion-limited.16,69−71 However, the exact nature of the rate-limiting step is difficult to determine from the Tafel slope alone, especially in a more complicated system such as ours. For comparison, studies of porphyrin homogeneous catalysts have measured Tafel slopes ranging from 100 to $300\\ \\mathrm{mV/}$ decade; thus, the rate-limiting step and mechanism may depend on more than just the active site itself.72−74 We stress that this is the first incarnation of our MOF electrocatalyst, and efforts are being undertaken to further exploit the modular nature of such systems for the next generation of catalyst. \n\nThe stability of the MOF catalyst was next tested over an extended period of time. In controlled potential electrolysis at $-0.7\\mathrm{~V~}$ vs RHE in $\\mathrm{CO}_{2}$ -saturated aqueous bicarbonate buffer, the current density reached a stable state after several minutes and subsequently showed no sign of decrease for up to $^{7\\mathrm{~h,~}}$ generating $16~\\mathrm{mL}$ of CO $\\mathrm{(0.71mmol}$ , $5.25~\\mathrm{cm}^{2}$ substrate; Figures 3A, S8, and S9). The lower limit of the TON of the MOF catalyst is quantified through ICP analysis of the electrode after testing and is determined to be 1400 assuming every cobalt atom is an electrochemically active site (turnover frequency $(\\mathrm{TOF})~\\approx~200~\\mathrm{h}^{-1})$ . The MOF largely retains its crystallinity after electrolysis, and preservation of the framework was evidenced through the retention of the major powder X-ray diffraction (XRD) peaks (Figure 3B). Furthermore, scanning electron microscopy (SEM) analysis reveals that the platelike morphology has been retained (Figure 3C,D). In situ surfaceenhanced Raman spectroscopy (SERS) was utilized to confirm the integrity of the organic units throughout the catalytic process (Figure S11). At each applied potential, the primary SERS peaks attributed to the porphyrin linker remain in the SERS spectrum. \n\nIn situ spectroelectrochemical testing was next employed to ascertain the cobalt oxidation state under operating conditions. Such techniques have proven valuable for studying the electronic structure of porphyrins.68,75−81 We grew the MOF on a transparent conductive fluorine-doped tin oxide (FTO) substrate and measured the film’s UV−vis absorbance for a series of applied electrochemical potentials (Figure 4A). A typical absorption of the cobalt-metalated $\\begin{array}{r}{\\big[\\mathrm{Al}_{2}\\big(\\mathrm{OH}\\big)_{2}\\mathrm{TCPP}.}\\end{array}$ - $\\mathbf{Co}]$ MOF in open-circuit states featured a Soret band ( $\\left(S_{0}\\rightarrow\\right.$ $S_{2}$ ) at $422{\\mathrm{~nm}}$ and a Q band $\\left(S_{0}\\rightarrow S_{1}\\right)$ at $530\\mathrm{nm}$ . The increase in absorbance at lower wavelengths has also been attributed to the back-donation of $\\mathrm{Co(I)}$ into the porphyrin system.60 Upon applying increasingly negative potential (0 to $-0.7\\:\\mathrm{V}$ vs RHE) to the FTO/MOF electrode in a $\\mathrm{CO}_{2}$ -saturated electrolyte, the Soret band under steady-state conditions decreases in intensity at $422\\ \\mathrm{nm}$ and increases at $408~\\mathrm{nm}$ , with isosbestic points at 413 and $455\\ \\mathrm{nm}$ (Figure 4A). Plotting the difference spectra (Figure 4B) illustrates the band bleach and increase in the aforementioned spectral regions, which is subsequently quantified to deduce the formal redox potential $\\left(E_{1/2}\\right)$ of the cobalt center in our system. The peak in the first derivative of the difference magnitude in these two wavelengths signified the formal reduction potential of the cobalt porphyrin unit in the MOF at $-0.4\\mathrm{~V~}$ vs RHE (Figure 4C), which is consistent with the position of the first cathodic wave in the voltammogram trace. However, even at potentials more positive than $-0.4\\:\\mathrm{V}$ vs RHE, a fraction of the cobalt centers are still reduced and are likely to be participating in the catalytic conversion of $\\mathrm{CO}_{2}$ to CO. \n\nThe buildup of a $\\mathrm{Co(I)}$ species under operating conditions and a Tafel slope of $165~\\mathrm{mV},$ /decade indicates that the ratelimiting step in our reaction mechanism may be either a $\\mathrm{CO}_{2}$ molecule adsorbing onto a $\\mathbf{Co}(\\mathrm{I})$ porphyrin coupled with a one-electron reduction or a one-electron reduction of a $\\mathrm{Co(I)-}$ $\\mathrm{CO}_{2}$ adduct. We stress the importance of this spectroelectrochemical data in signifying that the majority of the cobalt centers are electrically connected to the electrode and are reduced to the catalytically active $\\mathrm{Co(I)}$ state. \n\n# CONCLUDING REMARKS \n\nWe have demonstrated the applicability of MOF-integrated catalytic systems as modular platforms for the electrochemical reduction of aqueous $\\mathrm{CO}_{2}$ . This study represents the development of our first generation of MOF-based $\\mathrm{CO}_{2}$ reduction electrocatalysts in which the active site, inorganic backbone, and thickness/loading were rationally chosen and the resulting MOF integrated onto a conductive support. The modularity of these systems yields many opportunities to further improve performance and open new directions in electrocatalysis. \n\n# EXPERIMENTAL SECTION \n\nChemicals. N,N-Dimethylformamide (DMF) $(99.8\\%)$ , dimethyl sulfoxide (DMSO) $(99.5\\%)$ , anhydrous acetonitrile, potassium carbonate, and cobalt(II) acetate tetrahydrate were purchased from Sigma-Aldrich. FTO substrates $(7~\\Omega/s\\mathbf{q})$ were purchased from SigmaAldrich and cut on site into desirable dimensions. Aluminum chloride hexahydrate $(99.9\\%)$ was purchased from Fluka. Ethanol was purchased from KOPTEC. $4,4^{\\prime},4^{\\prime\\prime},4^{\\prime\\prime\\prime}$ -(Porphyrin-5,10,15,20-tetrayl)- tetrabenzoic acid $\\mathrm{(H_{4}T C P P)}$ was purchased from TCI. 2-Methylimidazole $(99\\%)$ and biphenyl-4,4-dicarboxylic acid $(97\\%)$ were purchased from Aldrich. Trimethylaluminum and trimethylindium were purchased from Strem chemicals. Hydrochloric acid and anhydrous DMF were purchased from EMD Millipore. Sodium hydroxide and methanol were purchased from Fischer chemical. Carbon disk substrates were purchased from Ted Pella. All chemicals were used as received without further purification. \n\nAtomic Layer Deposition. Atomic layer deposition (ALD) was carried out with a home-built thermal ALD system. Trimethylaluminum, trimethylindium, and water were used as aluminum, indium, and oxygen sources, respectively. Precursors were held in customized vessels to allow for pulsed delivery. Alumina deposition was carried out at $150\\ ^{\\circ}\\mathrm{C},$ and indium oxide deposition was carried out at $200~^{\\circ}\\mathrm{C}$ . Pulse times for trimethylaluminum, trimethylindium, and water were 1.0, 2.0, and $0.5\\ \\mathrm{s},$ respectively. Nitrogen functioned as both a purge and carrier gas and was flowed at a rate of $10~\\mathrm{cm}^{3}/\\mathrm{min}$ . Following the desired amount of ALD cycles, the chamber was purged with nitrogen, and the samples were taken out and allowed to cool naturally to room temperature in an air environment. The calibration of the amorphous alumina growth rate was previously carried out with TEM measurements on a variety of surfaces and was consistently $0.1\\ \\mathrm{nm}$ /cycle. \n\nPowder X-ray Diffraction. Powder X-ray diffraction (PXRD) patterns were acquired with a Bruker D8 Advance diffractometer ( $\\mathrm{\\tilde{C}}\\mathrm{u}$ $\\mathrm{K}\\alpha$ radiation, $\\lambda\\stackrel{-}{=}1.54056\\mathrm{\\AA}$ ). \n\nUV−Vis Spectroscopy. The optical absorption spectra were recorded using a UV−vis−NIR scanning spectrophotometer equipped with an integration sphere (Shimadzu UV-3101PC). A quartz cuvette functioned as a one-compartment electrochemical cell with a $\\mathrm{Ag/AgCl}$ reference and $\\mathrm{Pt}$ -wire counter electrode. \n\nMOF Synthesis. Following the ALD coating on the desired substrate, no further modifications were made, and the substrate asmade was put through the MOF synthesis. MOF synthesis was carried out in pyrex microwave vials using a CEM Discover-SP W/Activent microwave reactor. In a typical synthesis, the desired ALD-coated sample was mixed with ${\\mathfrak{s m g}}$ of $\\mathrm{H_{4}T C P P}$ , $1.5~\\mathrm{mL}$ of DMF, and $0.5~\\mathrm{mL}$ of water. The vessel was heated to $140~^{\\circ}\\mathrm{C}$ for $10~\\mathrm{min}$ . Following this, the sample was allowed to naturally cool to room temperature and washed with DMF and ethanol. Further purification was carried out by soaking the sample for 4 days in DMF and exchanging the liquid daily. After the DMF soak, the samples were soaked in acetone for 1 day and held under vacuum at room temperature for one more day. The growth of the MOF thin films is believed to occur via a dissolution− recrystallization mechanism. XRD, UV−vis absorption, HRTEM, and grazing incidence wide-angle X-ray scattering (GIWAXS) measurements all confirmed the identity and phase purity of the MOF. \n\nElectrochemistry. For all experiments, $0.5{\\bf M}$ potassium carbonate was used as the electrolyte. Prior to electrochemical testing, the electrolyte was purified overnight by applying $2\\mathrm{V}$ potential difference between working and counter Ti foil electrodes to remove trace metal salts and organic species. A standard 3-electrode setup was employed with a titanium counter electrode and $\\mathrm{\\Ag/AgCl}$ reference electrode. For product quantification, a home-built two-compartment setup was used that featured a nafion membrane separating the working and counter compartments. All current densities are normalized by projected surface areas. \n\nGas Chromatography. A home-built electrochemical cell was utilized for quantitative product measurement. The cell had two compartments separated by a nafion membrane to prevent product oxidation at the counter electrode. A flow mode was used to quantify gas products. Liquid products were quantified after the electrochemical measurement. During the chronoamerometric measurement, gas from the cell was directed through the sampling loop of a gas chromatograph (SRI) and was analyzed in $20~\\mathrm{min}$ intervals. The gas chromatograph was equipped with a molecular sieve (13X) and hayesep D column with Ar (Praxair, 5.0 ultrahigh purity) flowing as a carrier gas. The separated gas products were analyzed by a thermal conductivity detector (for ${\\mathrm{H}}_{2,}^{\\cdot\\cdot}$ ) and a flame ionization detector (for CO and gaseous hydrocarbons). Liquid products were analyzed afterward by quantitative NMR (Bruker AV-500) using dimethyl sulfoxide as an internal standard. \n\nICP-AES. ICP-AES was carried out on a PerkinElmer optical emission spectrometer Optima 7000DV instrument. A carbon disk $(5.25~\\mathrm{cm}^{2})$ coated with the MOF was put in the bottom of a $20~\\mathrm{mL}$ glass vial with an acid-resistant cap. A $2~\\mathrm{mL}$ aliquot of $99.5\\%$ nitric acid was then added to the vial and reacted violently with the carbon disk, where the carbon disk was exfoliated and deformed. A substantial amount of heat was released during the process, and orange smoke, presumably $\\mathrm{NO}_{2},$ was generated. Two minutes later, $2\\ \\mathrm{\\mL}$ of deionized water was added to dilute the acid so that the oxidation of the carbon disk was terminated. This solution was kept for 3 days to completely digest the MOF. Next, $4~\\mathrm{mL}$ of deionized water was added to the vial to further dilute the nitric acid. The clear solution for ICP measurement was obtained by centrifuging this carbon−nitric acid mixture at $4400~\\mathrm{rpm}$ for $1~\\mathrm{min}$ and collecting the supernatant. The concentration of cobalt in this solution was determined to be $3.8~\\mathrm{ppm}$ with approximately $10\\%$ error, giving a total cobalt amount of $30.4\\mu\\mathrm{g},$ which was calculated to be $\\mathrm{5.1~\\times~}\\mathrm{10^{-7}}$ M. Considering the overall surface area of $5.25~\\mathrm{cm}^{2}$ on the carbon disk, the cobalt loading on carbon disk was $6.1\\times10^{16}$ cobalt atoms per square centimeter. \n\nSpectroelectrochemistry. FTO-coated glass $(7~\\mathrm{~}\\Omega/\\mathrm{sq})$ was utilized as a transparent conducting substrate for in situ spectroelectrochemical measurements. The alumina deposition and conversion to MOF procedure was identical to that used for the carbon disk substrate. A quartz $5~\\mathrm{\\mL}$ cell served as a one-compartment electrochemical cell, with $\\mathrm{Ag/AgCl}$ and Pt serving as reference and counter electrodes, respectively. The cell was filled with $0.5~\\mathrm{~M~}$ carbonate buffer saturated with carbon dioxide prior to measurements, and a carbon dioxide atmosphere was maintained throughout. The FTO working electrode was held at the desired potential for $3\\mathrm{min}$ to reach steady-state conditions before acquiring a spectrum. A \n\nShimadzu-3101 PC spectrometer fitted with an integrating sphere was used for all measurements. \n\nRaman Spectroscopy. Raman measurements are carried out on a Horiba Labram JY HR 800 with an Olympus SMPLN $100\\times$ objective. A $532~\\mathrm{nm}$ diode laser was utilized as an excitation source. An open one-compartment cell served as the in situ cell for the measurement with $\\mathrm{\\Ag/AgCl}$ and $\\mathrm{Pt}$ functioning as the reference and counter electrodes, respectively. The electrolyte used was $0.5\\mathrm{~M~}$ potassium bicarbonate, saturated with carbon dioxide. SERS substrates were fabricated through electrochemically roughening silver films. First, 300 nm of silver was thermally evaporated onto a titanium foil substrate. Next, the silver was electrochemically roughened through oxidation− reduction cycles in $3\\mathrm{~M~}$ potassium chloride electrolyte. The silvercoated titanium electrode was cycled 10 times between $-1.2$ and $0.3\\mathrm{V}$ vs RHE at $50~\\mathrm{mV},$ /second. All SERS measurements were conducted under steady-state conditions. \n\nGrazing Incidence Wide Angle $\\pmb{\\mathrm{x}}$ -ray Scattering. GIWAXS spectra were acquired with a Pilatus $^{2\\mathrm{~M~}}$ (Dectris) instrument on beamline 7.3.3 at the Advanced Light Source, Lawrence Berkeley National Laboratory $\\left(\\lambda=1.24\\mathrm{~\\AA~}\\right)$ . The incidence angle was held at 0.120 to optimize signal collection. Silver behenate was used to calibrate the sample−detector distance and the beam center. The Nika package for IGOR Pro (Wavemetrics) was utilized to reduce the acquired 1D raw data to a 2D format. \n\nBecause of the fact that the carbon disks are covered by the salt precipitating from the electrolyte after electrolysis, the GIWAXS measurements on those samples are not successful because of the strong scattering of the residue salts near the surface on high angle saturating the detector. The SEM images are also influenced by the presence of the salt. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/jacs.5b08212. \n\nExperimental details, additional structural, electrochemical, and spectroscopic characterization. (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Authors \\*yaghi@berkeley.edu \\*p_yang@berkeley.edu \n\nAuthor Contributions □N.K. and Y.Z. contributed equally. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nElectron microscopy was carried out at the National Center of Electron Microscopy (NCEM), which is supported by the Office of Science, Office of Basic Energy Sciences of the U.S. Department of Energy (DOE) under contract no. DE-AC02- 05CH11231. Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231. This research was partially supported by BASF SE (Ludwigshafen, Germany) for synthesis of MOF, and King Abdulaziz City of Science and Technology (Riyadh, Saudi Arabia) for electrochemical characterization. Financial support for nanocrystal catalysis in P.Y.’s laboratory work was supported by the Director, Office of Science, Office of Basic Energy Sciences, Materials Science and Engineering Division, U.S. Department of Energy under contract no. DE-AC02- 05CH11231(Surface). O.M.Y. is thankful to Dr. Turki Al Saud (KACST) for his continued input and interest. Grazing incidence wide-angle X-ray scattering (GIWAXS) measurements were carried out at the Advanced Light Source (ALS) at Lawrence Berkeley National Lab (LBNL). The ALS is an Office of Science User Facility operated for the U.S. DOE, Office of Science, by LBNL and supported by the U.S. DOE under contract no. DE-AC02-05CH11231. Y.Z. is supported by the Suzhou Industrial Park fellowship. C.S.K. acknowledges support by the Alexander von Humboldt Foundation. Financial support for energy catalysis in the C.J.C. laboratory (S.L. and C.J.C.) was provided by U.S. Department of Energy (DOE)/Lawrence Berkeley National Laboratory (LBNL) grant 101528-002. C.J.C. is an Investigator with the Howard Hughes Medical Institute. \n\n# REFERENCES \n\n(1) Appel, A. M.; Bercaw, J. E.; Bocarsly, A. B.; Dobbek, H.; DuBois, D. L.; Dupuis, M.; Ferry, J. G.; Fujita, E.; Hille, R.; Kenis, P. J.; et al. \nChem. Rev. 2013, 113, 6621. \n(2) Aresta, M.; Dibenedetto, A.; Angelini, A. Chem. Rev. 2014, 114, 1709. \n(3) Costentin, C.; Robert, M.; Savéant, J.-M. Chem. Soc. Rev. 2013, 42, 2423. \n(4) Quadrelli, E. A.; Centi, G.; Duplan, J. L.; Perathoner, S. \nChemSusChem 2011, 4, 1194. \n(5) Yaghi, O. M.; Li, H.; Davis, C.; Richardson, D.; Groy, T. L. Acc. \nChem. Res. 1998, 31, 474. \n(6) Yaghi, O. M.; O'Keeffe, M.; Ockwig, N. W.; Chae, H. K.; \nEddaoudi, M.; Kim, J. Nature 2003, 423, 705. \n(7) Lee, J.; Farha, O. K.; Roberts, J.; Scheidt, K. A.; Nguyen, S. T.; \nHupp, J. T. Chem. Soc. Rev. 2009, 38, 1450. \n(8) Zhou, H.-C.; Long, J. R.; Yaghi, O. M. Chem. Rev. 2012, 112, 673. \n(9) Kuppler, R. J.; Timmons, D. J.; Fang, Q.-R.; Li, J.-R.; Makal, T. \nA.; Young, M. D.; Yuan, D.; Zhao, D.; Zhuang, W.; Zhou, H.-C. Coord. \nChem. Rev. 2009, 253, 3042. \n(10) Wang, Z.; Cohen, S. M. Chem. Soc. Rev. 2009, 38, 1315. \n(11) An, J.; Rosi, N. L. J. Am. Chem. Soc. 2010, 132, 5578. \n(12) Kitagawa, S.; Kitaura, R.; Noro, S. i. Angew. Chem., Int. Ed. 2004, 43, 2334. \n(13) Hori, Y.; Murata, A.; Takahashi, R. J. Chem. Soc., Faraday Trans. \n1 1989, 85, 2309. \n(14) DeWulf, D. W.; Jin, T.; Bard, A. J. J. Electrochem. Soc. 1989, 136, 1686. \n(15) Rosen, B. A.; Salehi-Khojin, A.; Thorson, M. R.; Zhu, W.; \nWhipple, D. T.; Kenis, P. J.; Masel, R. I. Science 2011, 334, 643. \n(16) Kuhl, K. P.; Cave, E. R.; Abram, D. N.; Jaramillo, T. F. Energy Environ. Sci. 2012, 5, 7050. \n(17) Hoshi, N.; Kato, M.; Hori, Y. J. Electroanal. Chem. 1997, 440, 283. \n(18) Kim, D.; Resasco, J.; Yu, Y.; Asiri, A. M.; Yang, P. Nat. Commun. \n2014, 5, 4948. \n(19) Zhu, W.; Michalsky, R.; Metin, O. n.; Lv, H.; Guo, S.; Wright, C. \nJ.; Sun, X.; Peterson, A. A.; Sun, S. J. Am. Chem. Soc. 2013, 135, 16833. \n(20) Zhu, W.; Zhang, Y.-J.; Zhang, H.; Lv, H.; Li, $\\mathrm{Q.;}$ Michalsky, R.; \nPeterson, A. A.; Sun, S. J. Am. Chem. Soc. 2014, 136, 16132. \n(21) Zhang, S.; Kang, P.; Meyer, T. J. J. Am. Chem. Soc. 2014, 136, 1734. \n(22) Manthiram, K.; Beberwyck, B. J.; Alivisatos, A. P. J. Am. Chem. \nSoc. 2014, 136, 13319. \n(23) Gao, D.; Zhou, H.; Wang, J.; Miao, S.; Yang, F.; Wang, G.; \nWang, J.; Bao, X. J. Am. Chem. Soc. 2015, 137, 4288. \n(24) Medina-Ramos, J.; Pupillo, R. C.; Keane, T. P.; DiMeglio, J. L.; \nRosenthal, J. J. Am. Chem. Soc. 2015, 137, 5021. \n(25) Medina-Ramos, J.; DiMeglio, J. L.; Rosenthal, J. J. Am. Chem. \nSoc. 2014, 136, 8361. \n(26) Lu, $\\mathrm{Q.;}$ Rosen, J.; Zhou, Y.; Hutchings, G. S.; Kimmel, Y. C.; \nChen, J. G.; Jiao, F. Nat. Commun. 2014, 5, 3242. \n(27) Li, C. W.; Kanan, M. W. J. Am. Chem. Soc. 2012, 134, 7231. (28) Chen, Y.; Kanan, M. W. J. Am. Chem. Soc. 2012, 134, 1986. \n(29) Chen, Y.; Li, C. W.; Kanan, M. W. J. Am. Chem. Soc. 2012, 134, 19969. \n(30) Asadi, M.; Kumar, B.; Behranginia, A.; Rosen, B. A.; Baskin, A.; \nRepnin, N.; Pisasale, D.; Phillips, P.; Zhu, W.; Haasch, R.; et al. Nat. \nCommun. 2014, 5, 4470. \n(31) Wu, J.; Yadav, R. M.; Liu, M.; Sharma, P. P.; Tiwary, C. S.; Ma, L.; Zou, X.; Zhou, X.-D.; Yakobson, B. I.; Lou, J.; et al. ACS Nano 2015, 9, 5364. \n(32) Zhang, S.; Kang, P.; Ubnoske, S.; Brennaman, M. K.; Song, N.; \nHouse, R. L.; Glass, J. T.; Meyer, T. J. J. Am. Chem. Soc. 2014, 136, 7845. \n(33) Kumar, B.; Asadi, M.; Pisasale, D.; Sinha-Ray, S.; Rosen, B. A.; \nHaasch, R.; Abiade, J.; Yarin, A. L.; Salehi-Khojin, A. Nat. Commun. \n2013, 4, 2819. \n(34) Liu, C.; Gallagher, J. J.; Sakimoto, K. K.; Nichols, E. M.; Chang, C. J.; Chang, M. C.; Yang, P. Nano Lett. 2015, 15, 3634. \n(35) Torella, J. P.; Gagliardi, C. J.; Chen, J. S.; Bediako, D. K.; Colón, B.; Way, J. C.; Silver, P. A.; Nocera, D. G. Proc. Natl. Acad. Sci. U. S. A. \n2015, 112, 2337. \n(36) Reda, T.; Plugge, C. M.; Abram, N. J.; Hirst, J. Proc. Natl. Acad. \nSci. U. S. A. 2008, 105, 10654. \n(37) Schuchmann, K.; Müller, V. Science 2013, 342, 1382. \n(38) Seshadri, G.; Lin, C.; Bocarsly, A. B. J. Electroanal. Chem. 1994, 372, 145. \n(39) Costentin, C.; Drouet, S.; Robert, M.; Savéant, J.-M. Science 2012, 338, 90. \n(40) Smieja, J. M.; Sampson, M. D.; Grice, K. A.; Benson, E. E.; \nFroehlich, J. D.; Kubiak, C. P. Inorg. Chem. 2013, 52, 2484. \n(41) Fujita, E.; Haff, J.; Sanzenbacher, R.; Elias, H. Inorg. Chem. 1994, 33, 4627. \n(42) Thoi, V. S.; Kornienko, N.; Margarit, C. G.; Yang, P.; Chang, C. \nJ. J. Am. Chem. Soc. 2013, 135, 14413. \n(43) Kang, P.; Cheng, C.; Chen, Z.; Schauer, C. K.; Meyer, T. J.; \nBrookhart, M. J. Am. Chem. Soc. 2012, 134, 5500. \n(44) Schneider, J.; Jia, H.; Kobiro, K.; Cabelli, D. E.; Muckerman, J. \nT.; Fujita, E. Energy Environ. Sci. 2012, 5, 9502. \n(45) Tornow, C. E.; Thorson, M. R.; Ma, S.; Gewirth, A. A.; Kenis, P. \nJ. J. Am. Chem. Soc. 2012, 134, 19520. \n(46) Richardson, R. D.; Holland, E. J.; Carpenter, B. K. Nat. Chem. \n2011, 3, 301. \n(47) Lacy, D. C.; McCrory, C. C.; Peters, J. C. Inorg. Chem. 2014, 53, 4980. \n(48) Wang, C.; Xie, Z.; deKrafft, K. E.; Lin, W. J. Am. Chem. Soc. \n2011, 133, 13445. \n(49) Fu, Y.; Sun, D.; Chen, Y.; Huang, R.; Ding, Z.; Fu, X.; Li, Z. \nAngew. Chem. 2012, 124, 3420. \n(50) Liu, Y.; Yang, Y.; Sun, $\\mathrm{Q.;}$ Wang, Z.; Huang, B.; Dai, Y.; Qin, X.; \nZhang, X. ACS Appl. Mater. Interfaces 2013, 5, 7654. \n(51) Li, L.; Zhang, S.; Xu, L.; Wang, J.; Shi, L.-X.; Chen, Z.-N.; Hong, M.; Luo, J. Chem. Sci. 2014, 5, 3808. \n(52) Wang, D.; Huang, R.; Liu, W.; Sun, D.; Li, Z. ACS Catal. 2014, 4, 4254. \n(53) Hinogami, R.; Yotsuhashi, S.; Deguchi, M.; Zenitani, Y.; \nHashiba, H.; Yamada, Y. ECS Electrochem. Lett. 2012, 1, H17. \n(54) Kumar, R. S.; Kumar, S. S.; Kulandainathan, M. A. Electrohem. \nCommun. 2012, 25, 70. \n(55) Hod, I.; Sampson, M. D.; Deria, P.; Kubiak, C. P.; Farha, O. K.; \nHupp, J. T. ACS Catal. 2015, 6302. \n(56) Lin, S.; Diercks, C. S.; Zhang, Y.-B.; Kornienko, N.; Nichols, E. \nM.; Zhao, Y.; Paris, A. R.; Kim, D.; Yang, P.; Yaghi, O. M.; Chang, C. J. \nScience 2015, 349, 1208. \n(57) García, M.; Aguirre, M. J.; Canzi, G.; Kubiak, C. P.; Ohlbaum, M.; Isaacs, M. Electrochim. Acta 2014, 115, 146. \n(58) Bonin, J.; Chaussemier, M.; Robert, M.; Routier, M. \nChemCatChem 2014, 6, 3200. \n(59) Leung, K.; Nielsen, I. M.; Sai, N.; Medforth, C.; Shelnutt, J. A. J. \nPhys. Chem. A 2010, 114, 10174. (60) Behar, D.; Dhanasekaran, T.; Neta, P.; Hosten, C.; Ejeh, D.; Hambright, P.; Fujita, E. J. Phys. Chem. A 1998, 102, 2870. \n(61) RamÍRez, G.; Lucero, M.; Riquelme, A.; Villagrán, M.; Costamagna, J.; Trollund, E.; Aguirre, M. J. J. Coord. Chem. 2004, 57, 249. \n(62) Zhao, Y.; Kornienko, N.; Liu, Z.; Zhu, C.; Asahina, S.; Kuo, T.- R.; Bao, W.; Xie, C.; Hexemer, A.; Terasaki, O.; Yang, P.; Yaghi, O. M. J. Am. Chem. Soc. 2015, 137, 2199. \n(63) Reboul, J.; Furukawa, S.; Horike, N.; Tsotsalas, M.; Hirai, K.; Uehara, H.; Kondo, M.; Louvain, N.; Sakata, O.; Kitagawa, S. Nat. Mater. 2012, 11, 717. \n(64) Tripkovic, V.; Vanin, M.; Karamad, M.; Björketun, M. r. E.; Jacobsen, K. W.; Thygesen, K. S.; Rossmeisl, J. J. Phys. Chem. C 2013, 117, 9187. \n(65) Qiao, J.; Liu, Y.; Hong, F.; Zhang, J. Chem. Soc. Rev. 2014, 43, 631. \n(66) Bard, A. J.; Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications; Wiley: New York, 1980. \n(67) Newman, J.; Thomas-Alyea, K. E. Electrochemical Systems; John Wiley & Sons: Hoboken, NJ, 2012. \n(68) Ahrenholtz, S. R.; Epley, C. C.; Morris, A. J. J. Am. Chem. Soc. 2014, 136, 2464. \n(69) Russell, P.; Kovac, N.; Srinivasan, S.; Steinberg, M. J. Electrochem. Soc. 1977, 124, 1329. \n(70) Bandi, A. J. Electrochem. Soc. 1990, 137, 2157. \n(71) Hatsukade, T.; Kuhl, K. P.; Cave, E. R.; Abram, D. N.; Jaramillo, T. F. Phys. Chem. Chem. Phys. 2014, 16, 13814. \n(72) Riquelme, M.; Isaacs, M.; Lucero, M.; Trollund, E.; Aguirre, M.; Canales, J. J. Chil. Chem. Soc. 2003, 48, 89. \n(73) Najafi, M.; Sadeghi, M. ECS Electrochem. Lett. 2013, 2, H5. (74) Manbeck, G. F.; Fujita, E. J. Porphyrins Phthalocyanines 2015, 19, 45. \n(75) Kung, C.-W.; Chang, T.-H.; Chou, L.-Y.; Hupp, J. T.; Farha, O. K.; Ho, K.-C. Chem. Commun. 2015, 51, 2414. \n(76) Kadish, K.; Boisselier-Cocolios, B.; Coutsolelos, A.; Mitaine, P.; Guilard, R. Inorg. Chem. 1985, 24, 4521. \n(77) Wei, Z.; Ryan, M. D. Inorg. Chim. Acta 2001, 314, 49. \n(78) Lin, X.; Boisselier-Cocolios, B.; Kadish, K. Inorg. Chem. 1986, 25, 3242. \n(79) Quezada, D.; Honores, J.; García, M.; Armijo, F.; Isaacs, M. New J. Chem. 2014, 38, 3606. \n(80) Kadish, K. M.; Van Caemelbecke, E. J. Solid State Electrochem. 2003, 7, 254. \n(81) Kadish, K. M.; Smith, K. M.; Guilard, R., Eds. The Porphyrin Handbook; Academic Press: San Diego, CA, 1999. " + }, + { + "id": "10.1021_acs.jpclett.5b00968", + "DOI": "10.1021/acs.jpclett.5b00968", + "DOI Link": "http://dx.doi.org/10.1021/acs.jpclett.5b00968", + "Relative Dir Path": "mds/10.1021_acs.jpclett.5b00968", + "Article Title": "How Important Is the Organic Part of Lead Halide Perovskite Photovoltaic Cells? Efficient CsPbBr3 Cells", + "Authors": "Kulbak, M; Cahen, D; Hodes, G", + "Source Title": "JOURNAL OF PHYSICAL CHEMISTRY LETTERS", + "Abstract": "Hybrid organic-inorganic lead halide perovskite photovoltaic cells have already surpassed 20% conversion efficiency in the few years that they have been seriously studied. However, many fundamental questions still remain unullswered as to why they are so good. One of these is Is the organic cation really necessary to obtain high quality cells? In this study, we show that an all-inorganic version of the lead bromide perovslcite material works equally well as the organic one, in particular generating the high open circuit voltages that are an important feature of these cells.", + "Times Cited, WoS Core": 984, + "Times Cited, All Databases": 1063, + "Publication Year": 2015, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000357626700009", + "Markdown": "# How Important Is the Organic Part of Lead Halide Perovskite Photovoltaic Cells? Efficient $\\cos P\\mathsf{b}\\mathsf{B}\\mathsf{r}_{3}$ Cells \n\nMichael Kulbak, David Cahen,\\* and Gary Hodes\\* \n\nDepartment of Materials and Interfaces, Weizmann Institute of Science, Rehovot 76100, Israel \n\nSupporting Information \n\nABSTRACT: Hybrid organic−inorganic lead halide perovskite photovoltaic cells have already surpassed $20\\%$ conversion efficiency in the few years that they have been seriously studied. However, many fundamental questions still remain unanswered as to why they are so good. One of these is “Is the organic cation really necessary to obtain high quality cells?” In this study, we show that an all-inorganic version of the lead bromide perovskite material works equally well as the organic one, in particular generating the high open circuit voltages that are an important feature of these cells. \n\nrganic amine-lead-halide perovskite-based photovoltaic cells have become one of the most studied cells, if not the most studied, as well as being highly promising for practical applications, all in the past several years. These cells are commonly called “hybrid organic−inorganic perovskite cells”. However, much early work on these or related materials (not related to photovoltaic cells) involved totally inorganic lead halide compounds with alkali metal ions as the ‘A’ cation in the generalized $\\mathrm{APb}{\\mathrm{X}}_{3}$ ( $\\mathrm{\\ddot{X}=}$ halide) compound. Although all topperforming photovoltaic cells used alkyl ammonium or formamidinium as the A cation, we query as to whether an inorganic A cation would also form light absorbers with comparable properties to the alkyl ammonium ones. Some indirect evidence already provides strong support that this may be the case. For charge transport, the two most relevant parameters are charge mobility (directly related to diffusion coefficient) and lifetime, which, taken together, define the carrier diffusion/drift length. $\\mathrm{CsSnI}_{3}$ has been reported with high mobilities of electrons (up to ${\\sim}2300~\\mathrm{cm}^{2}/\\mathrm{V}{\\cdot}\\mathrm{\\hat{s}},$ ) and holes $({\\sim}320~\\mathrm{cm}^{2}/\\mathrm{V}{\\cdot}s)$ .1 We are aware of two studies of photovoltaic cells using $\\mathrm{CsSnI}_{3}$ as an absorber: an early report (2012) used in a planar Schottky cell configuration with a modest performance ( $0.9\\%$ efficiency) and a more recent one with an improved, but still low (compared to Pb perovskites) performance of $2\\%$ efficiency.3 More specifically, in a study of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ single crystals for use as photoconductive $X\\mathrm{-}$ and γ-ray detectors, Stoumpos et al. estimated an electron mobility of ${\\sim}1000~\\mathrm{cm}^{2}/\\mathrm{V}{\\cdot}s$ and an electron lifetime of $2.5~\\ \\mu\\mathrm{s}$ (and comparable $\\mu\\tau$ values for electrons and holes). From these parameters, it is clear that the organic cation is not necessarily essential to obtain long diffusion/drift lengths. However, one of the outstanding properties of the hybrid perovskites is the very high value of open circuit voltage $(V_{\\mathrm{OC}})$ that can be obtained relative to the semiconductor bandgap. In addition to mobility and lifetimes, other factors are important to obtain high $V_{\\mathrm{OC}},$ e.g., minimal tail absorption as broad tail absorption will reduce the available $V_{\\mathrm{OC}}$ . \n\n![](images/440561d6de0d16dbb52d7def2024df109b56919f5def068355e87bb37d5069b4.jpg) \n\nTo find out whether the organic nature or anisotropic geometry of the A cation is essential for the high performance of the hybrid cells, we chose $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ because, unlike the iodide compound, this material occurs at standard temperature and pressure in the perovskite structure and was shown to have very good charge transport properties. In this Letter, we show that $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ exhibits a photovoltaic performance comparable to that obtained by $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ (abbreviated here to $\\mathbf{MAPbBr}_{3},$ ), including relatively high values of $V_{\\mathrm{OC}}$ typical of the hybrid perovskites. \n\nTo prepare the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ layers, we used the two-step method, since (based on attempts with a few different solvents and excluding concentrated aqueous HBr as used in ref 4 to prepare starting material as being inconvenient for spincoating) we were unable to find a solvent that dissolved both the CsBr and the $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2};$ also the morphology obtained with the two-step method for $\\mathbf{MAPbBr}_{3}$ is more homogeneous and continuous than that from the one-step method.5 The $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ layers were annealed at $250~^{\\circ}\\mathrm{C}$ and the cells fabricated in ambient atmosphere. The relatively high annealing temperature and the fact that all processing was carried out in ambient atmosphere implies a fairly good stability, although, like the hybrid perovskites, liquid water will cause rapid degradation. \n\nWe studied various cell architectures, i.e., with mesoporous $\\mathrm{(mp)\\mathrm{-}T i O}_{2},$ with $\\mathrm{{mp-Al}}_{3}\\mathrm{{O}}_{3}$ and without mp layer (planar). Since cells with mp- $\\mathrm{\\cdotTiO}_{2}$ gave by far the best overall results, we concentrated on the architecture F-doped tin oxide (FTO)/ $\\mathrm{TiO_{2}(d e n s e)/m p–T i O_{2}/C s P b B r_{3}/H T M/A u}$ (where HTM represents hole transport medium), and all cells below are of this configuration unless stated otherwise. To maximize $V_{\\mathrm{OC}},$ we used several different HTMs, i.e., spiro-OMeTAD, poly[bis(4- phenyl)(2,4,6-trimethylphenyl)amine], and $^{4,4^{\\prime}}$ -bis(N-carbazolyl)- $^{1,1^{\\prime}}$ -biphenyl; abbreviated as spiro, PTAA and CBP, respectively. The highest occupied molecular orbital (HOMO) level of the HTM is an important factor in maximizing $V_{\\mathrm{OC}}-$ ideally it should be slightly closer to the vacuum level, $E_{\\mathrm{vac}}$ (i.e., slightly lower ionization energy, IE) than the top of the valence band $\\left(E_{\\mathrm{V}}\\right)$ of the perovskite. We measured by ultraviolet photoelectron spectroscopy (UPS) $E_{\\mathrm{V}}$ of our $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ on mp $\\mathrm{TiO}_{2}$ to be at ${\\mathfrak{s}}.{\\mathfrak{s}}{\\mathord{\\ \\left/{\\vphantom{\\mathfrak{s}}}\\right.\\kern-\\nulldelimiterspace}{\\mathrm{~eV}}}$ (vs the $\\scriptstyle{E_{\\mathrm{vac}}},$ ) which is very similar to the $5.9\\ \\mathrm{eV}$ we previously measured for $\\mathbf{MAPbBr}_{3}$ .6 Most common HTMs have $E_{\\mathrm{V}}/\\mathrm{IE}$ values considerably closer to $E_{\\mathrm{vac}}$ than this. For spiro, PTAA, and CBP, the values are ${\\sim}5.0\\ \\mathrm{\\eV},^{6}\\sim\\ 5.2$ $\\mathrm{eV}_{\\mathrm{}}^{7,8}$ and ${\\sim}5.7~\\mathrm{eV},^{9}$ respectively. As always, these values may change, dependent on processing, ambient conditions, and when contacted with another material, and should be taken as a guide rather than as exact numbers. \n\nFigure 1 shows a transmission spectrum (corrected for reflection) of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ on $\\mathrm{\\Delta\\np{-}T i O_{2}/F T O}$ glass. Attempts to calculate a bandgap from Tauc plots (Figures S1a and S1b in the Supporting Information (SI)) gave a direct gap of $2.36~\\mathrm{eV}$ (compared to 2.32 for the $\\mathrm{MAPbBr}_{3}^{10}$ ). However, at this energy, there is already a $2/3$ drop in transmission, implying a different absorption process at energies lower than $2.36\\ \\mathrm{eV}.$ . Fitting the Tauc plot to an indirect gap gave a linear range from ${\\sim}2.35{-}2.40~\\mathrm{eV}$ with an extrapolated indirect gap of ${\\sim}2.29\\ \\mathrm{eV}.$ . Based on a visual inspection of the transmission spectrum and assuming a direct gap, an estimated gap of $2.32\\pm\\:0.02$ is estimated. It may be that there is an indirect gap followed closely by a direct gap. While an indirect gap is not usually sharp, this need not necessarily always be the case. There also may be an excitonic contribution. A study of the absorption of this material will be the subject of future work and the bandgaps given here should be considered an estimation. It should be noted that Stoumpos et al. measured a direct gap of $2.25~\\mathrm{eV^{4}}$ for their single crystal $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ . Recently, several independent measurements of single crystal hybrid perovskites yielded bandgap values about $0.1\\ \\mathrm{eV}$ lower than those widely accepted for films of the same compounds.11,12 \n\n![](images/3f8d27579b1ddd2775cdbd21f9ca2f5d5393ca58b07e0a053b965da4a28b0d8d.jpg) \nFigure 1. Reflection-corrected transmission of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ on mp- $\\mathrm{TiO}_{2}$ (effective $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ thickness ca. $400{-}500\\ \\mathrm{~nm}$ ; see SEM image in Figure 2). \n\nThe X-ray diffraction (XRD, Figure S2 in the SI) pattern matches exactly that given in the literature for this compound.4 Figure 2 shows a scanning electron microscopy (SEM) image of a cross-section of a cell with spiro as the HTM. The mp$\\mathrm{TiO_{2}/C s P b B r_{3}}$ and spiro layers are each ${\\sim}450~\\mathrm{nm}$ thick, while the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ overlayer averages ${\\sim}270~\\mathrm{nm}$ thick. \n\nSpiro was first used, as it is expected to give good cells with bromide perovskites relative to many other HTMs, although with a lower $V_{\\mathrm{OC}}$ than can be achieved with optimal interfacial energy level alignment. This follows from the lower IE of spiro compared to the other HTMs used here (as also pointed out in ref 6) although there are some recent results showing high $V_{\\mathrm{OC}}$ with spiro (see Table S1 in the SI). Figure 3 shows the $_\\mathrm{I-V}$ characteristics of cells with different HTMs as well as without a HTM. \n\n![](images/4352eda25e24437a6b2a18caed88d080ddf1b56f75dbf6e8ce19e42c905c814a.jpg) \nFigure 2. SEM cross-section of a $\\mathrm{np{-}T i O_{2}/C s P b B r_{3}/s p i r o/A u}$ cell. The dense $\\mathrm{TiO}_{2}$ on the FTO is not clearly visible in this image. \n\nConsidering first the spiro cell (Figure 3A), high currents and fill factors (FF) with moderate voltages were obtained. The lower values of $V_{\\mathrm{OC}}$ than obtained in high voltage $\\mathbf{MAPbB}\\mathbf{r}_{3}$ cells using larger IE HTMs (which can give up to $1.5~\\mathrm{V}$ ) are reasonable considering that spiro is known to be suboptimal for this parameter. Additionally there is a small hysteresis and only between the maximum power range and open-circuit. This is not a temperature effect (as a rule of thumb, photovoltaic cells lose ${\\sim}2\\mathrm{mV}$ in $V_{\\mathrm{OC}}$ for every $^{\\circ}\\mathrm{C}$ rise in temperature13 since (a) the cells were allowed to equilibrate before measuring and (b) the forward scan was run first followed by the reverse scan, which would imply a higher $V_{\\mathrm{OC}}$ for forward scan in the case where temperature equilibrium was not reached. \n\nBased solely on its HOMO level, PTAA should give somewhat higher values of $V_{\\mathrm{OC}}$ than spiro. Indeed $>25\\%$ higher $V_{\\mathrm{OC}}$ values were obtained in first experiments, as can be seen from Figure 3B. The nearly $1.3\\mathrm{V}V_{\\mathrm{OC}}$ did not change the FF, although there was a $\\sim8\\%$ drop in current, likely due to suboptimal doping of the HTM. The hysteresis was slightly smaller, relative to that of the cells with spiro, and in this case was manifested mainly by a small change in the cell resistance. We note that some of these cells show virtually no hysteresis at all. \n\nThe maximum current that can be obtained for $100\\%$ EQE for a bandgap of $2.36\\ \\mathrm{eV}$ is ${\\sim}9\\mathrm{\\mA}/\\mathrm{cm}^{2}$ . The EQE values (without light bias) shown in Figure 4 translate to a current density of $\\sim5.5\\mathrm{mA}/\\mathrm{cm}^{2}$ which is slightly more than $10\\%$ lower than the directly measured $J_{\\mathrm{SC}}$ with PTAA as the hole conductor (Figure 3B). \n\nCells were also measured in natural sunlight $(900~\\mathrm{W/m}^{2})$ . Correcting for the difference between $900\\mathrm{\\:W}\\mathrm{\\bar{/m}}^{2}$ and the 1000 $\\mathrm{W}/\\mathrm{m}^{2}$ of the simulator, the $J_{\\scriptscriptstyle\\mathrm{SC}}$ values were very similar. Measurements of EQE with white light bias, which often influences the values of $\\begin{array}{r}{\\mathrm{EQE},}\\end{array}$ increases the EQE to close to $70\\%$ . Such an EQE value yields an equivalent $J_{\\mathrm{SC}}$ that agrees with the directly measured result (Figure 3B), even though the white light source used for this purpose was much weaker than the natural sunlight. In this respect, it is worth noting that we recently showed that weak white light illumination increases the effective diffusion length of charge carriers in $\\mathbf{MAPbB}\\mathbf{r}_{3}$ by up to a factor of 3 when measured by electron beam-induced current (EBIC)14 and there may well be a connection between these two different results. \n\n![](images/7d6042fd8316eb81a11d8ed6cd9d41e1a915bbfd6fe8149c9813d194fe4ec988.jpg) \nFigure 3. Light and dark $I{-}V$ plots of mp- $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ cells with the different HTMs as labeled (A−C) and without any HTM (D) $(100\\mathrm{mW/cm}^{2}$ simulated solar irradiation, masked cell area $0.16~\\mathrm{cm}^{2}$ ). Scan rate was $0.06\\mathrm{V}/s$ . \n\n![](images/f6fbf3f7b96b7886b8b2643ed94c8538f507a5fd9974fbf935f694f69d3f857d.jpg) \nFigure 4. External quantum efficiency (EQE) spectral response of the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ /PTAA cell from Figure 3B with and without light bias. \n\nUsing CBP as the HTM, a much higher $V_{\\mathrm{OC}}$ is expected (again based solely on the HOMO level of the CBP). Only a modest increase in this parameter was obtained, but the FF decreased considerably (Figure 3C). Also the hysteresis was much more prominent than in the previous cells. From our UPS measurements, done separately for the individual components, the CBP $_{\\mathrm{HOMO/CsPbBr}_{3}}$ offset should be much less than for the other $\\mathrm{HTM}/\\mathrm{CsPbBr}_{3}$ interfaces $-0.27$ eV $\\langle5.97-5.7\\ \\mathrm{~eV}$ as noted above), instead of $0.8\\mathrm{-}0.9\\ \\mathrm{\\eV}.$ . Taking into account that these values are only indicative, it is possible that the rate of hole transfer across the perovskite/ CBP interface is considerably slower than at the other perovskite/HTM interfaces, resulting in a hole buildup in the perovskite which would increase charge recombination (although we note that it does not affect the photocurrent at or close to zero bias). It may also be related to the higher series resistance of the CBP cell compared to the other HTM cells (a shallower slope of the high forward bias $_\\mathrm{I-V}$ characteristic), suggesting improvement might follow from higher doping of the CBP. This result is a further example that the commonly observed hysteresis is not merely a function of the perovskite bulk properties but is dependent also on the perovskite interfaces with other phases. \n\nWe also made cells without any HTM (Figure 3D). There have been a couple of reports of $\\mathbf{MAPbBr}_{3}$ cells made without a HTM with conversion efficiencies reaching $2\\%$ and $V_{\\mathrm{OC}}$ up to 1.35 V.15,16 With $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ we succeeded in obtaining HTMfree cells almost as good as our best cells with PTAA. Figure 3D shows the IV characteristics of such a cell, which is virtually hysteresis-free and with a performance that is only slightly inferior to that of cells with PTAA, mainly due to the somewhat lower VOC. \n\nCells on $\\mathrm{mp-Al}_{2}{\\mathrm{O}}_{3}$ instead of on $\\mathrm{TiO}_{2}$ normally give a considerably higher $V_{\\mathrm{OC}}$ .10,16,17 As noted above, the $\\ensuremath{\\mathrm{mp-TiO}}_{2}$ cells were much better than similar cells using mp- ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ . Up to now, the best cells using mp- $\\mathrm{Al}_{2}\\mathrm{O}_{3}$ are with spiro, with an overall efficiency of nearly $1.9\\%$ ; however, the $V_{\\mathrm{OC}}$ was, as expected higher (by ${>}300~\\mathrm{mV},$ at $1.33{\\mathrm{V}}.$ . The highest $V_{\\mathrm{OC}}$ we obtained was using $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ without any HTM, where we obtained $>1.4~\\mathrm{V}$ (overall cell efficiency $1\\%$ ). Current−voltage plots of these cells are shown in Figure S3 in the SI. \n\nThe fact that we have not (up to now) succeeded in fabricating cells on $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ or planar cells comparable in performance with the mp- $\\mathrm{TiO}_{2}$ cells suggests that the transport properties of our $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ are still far from optimal. Because single crystals of the same material have shown excellent transport properties,4 there is likely much room for improvement here. \n\nTo compare the above cells with hybrid $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ cells described in the literature, we have listed the hybrid cells in Table S1 in the Supporting Information. The important cell structure parameters are given since these have a strong effect on the cell performance, as does the electron transport material $\\mathrm{(TiO}_{2},$ either planar or planar $^+$ mesoscopic, or planar $\\mathrm{TiO}_{2}$ covered by mesoscopic $\\mathrm{Al}_{2}\\mathrm{O}_{3}.$ ) and the HTM material. \n\nOverall, the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ cells compare well with the $\\mathbf{MAPbBr}_{3}$ cells in the table. The cell by Heo et al.18 in the SI is outstanding and separate from all other cells and is not far from the theoretical maximum efficiency (the $V_{\\mathrm{OC}}$ is the only parameter that might be increased appreciably), but up to now, 8 months after that work was published, we are aware of only one recent paper by Sheng et al.19 with results that even begin to approach that value (and show a value of $J_{\\mathrm{SC}}$ that is equivalent to an EQE of ${\\sim}100\\%$ ). \n\nThe all-inorganic halide perovskites have both disadvantages and advantages compared to the hybrid analogues. The most obvious disadvantage is the relatively high cost of Cs compared to the organic A cations (medium purity CsBr costs in the order of $\\$1/8$ for $100-1000\\mathrm{~g~}$ quantities). However, we note that Cs is far from being a rare element (it is more earthabundant than $S\\mathrm{n}$ , to give a relevant comparison), and its present high cost is more a function of the low level of use than an intrinsic value. Also, while there are only two organic A cations that can presently be used in good halide perovskitebased cells, that is still twice the (present) number of suitable inorganic A cations. The availability of both increases the choice substantially. On the plus side, the all-inorganic compounds are certainly much more temperature stable than the hybrid analogues (e.g., we anneal the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ films at 250 $^{\\circ}\\mathrm{C}$ in air (see below), and the Cs component will not be lost by sublimation, although the resulting perovskites are still watersensitive. The purpose of this Letter is not to suggest that allinorganic cells will be better than hybrid cells (or for any other application that these compounds may be used in), but that • the organic moiety is not an essential component a priori, particularly in obtaining high $V_{\\mathrm{OC}}$ values, something that was not obvious up to now and is important for the fundamental science point of view, and useful comparative studies between hybrid organic− inorganic and all-inorganic metal halide perovskites can now be done. \n\n# EXPERIMENTAL METHODS \n\nFTO transparent conducting substrates (Xinyan Technology TCO-XY15) were cut and cleaned by sequential 15 min sonication in warm aqueous alconox solution, deionized water, acetone, and ethanol, followed by drying under ${\\bf N}_{2}$ stream. A compact $\\sim60\\ \\mathrm{nm}$ thin $\\mathrm{TiO}_{2}$ layer was then applied to the clean substrate by spray pyrolysis of a $30~\\mathrm{mM}$ titanium diisopropoxide bis(acetylacetonate) (Sigma-Aldrich) solution in isopropanol using air as the carrier gas on a hot plate set to 450 ${}^{\\circ}\\mathrm{C},$ followed by two step annealing procedure at 160 and 450 ${}^{\\circ}\\mathrm{C},$ each for $^\\textrm{\\scriptsize1h}$ in air. \n\nA $500~\\mathrm{{nm}}$ -thick mesoporous $\\mathrm{TiO}_{2}$ scaffold was deposited by spin coating a $\\mathrm{TiO}_{2}$ nanoparticle (P25) paste onto the dense $\\mathrm{TiO}_{2}$ coated substrates. Two grams of $\\mathrm{TiO}_{2}$ P25 (Evonik) was mixed with $0.34~\\mathrm{mL}$ of acetic acid, $0.85~\\mathrm{mL}$ of deionized water, and $22~\\mathrm{mL}$ of ethanol, followed by sonication for $30\\mathrm{min}$ . Then $3.58~\\mathrm{mL}$ of $\\alpha$ -terpineol, $_{0.1\\mathrm{~g~}}$ of $46~\\mathrm{cP}$ ethyl cellulose, $_{0.1\\mathrm{~g~}}$ of $10\\ \\mathrm{cP}$ ethyl cellose were mixed with $6.1\\ \\mathrm{mL}$ of ethanol and finally added to the suspension. The paste was spin-coated for 5 s at $500~\\mathrm{rpm}$ and 40 s at $4000\\ \\mathrm{rpm},$ followed by a two-step annealing procedure at 160 and $450\\ ^{\\circ}\\mathrm{C},$ each for $^\\textrm{\\scriptsize1h}$ in air. \n\nThe $\\mathrm{\\bar{C}s P b B r}_{3}$ films were prepared by a 2-step sequential deposition technique. $^{1\\mathrm{~M~}}$ of $\\mathrm{Pb}{\\bf B}{\\bf r}_{2}$ (Sigma-Aldrich) in DMF was stirred on a hot plate at $75~^{\\circ}\\mathrm{C}$ for $20~\\mathrm{min}$ . It was then filtered using a $0.2\\ \\mu\\mathrm{m}$ pore size PTFE filter and immediately used. The solution was spin-coated on preheated $(75~^{\\circ}\\mathrm{C})$ substrates for $1~\\mathrm{min}$ at $2500~\\mathrm{rpm}$ and was then dried on a hot plate at $75~^{\\circ}\\mathrm{C}$ for $30~\\mathrm{min}$ . After drying, the substrates were dipped for $10~\\mathrm{{min}}$ in a heated $(50~^{\\circ}\\mathrm{C})$ solution of $15~\\mathrm{mg/mL}$ CsBr (Sigma-Aldrich) in methanol for $10~\\mathrm{min}$ , washed with 2- propanol, dried under $\\mathbf{N}_{2}$ stream and annealed for $10\\ \\mathrm{min}$ at $250~^{\\circ}\\mathrm{C}$ . All procedures were carried out in an ambient atmosphere. The HTMs, Spiro-OMETAD (Borun Chemical), PTAA (Lumtec) and CBP (American Dye Source) were applied by spin-coating $3\\:s$ at $500~\\mathrm{rpm}$ followed by $40~\\mathsf{s}$ at 2000 rpm. The Spiro-OMETAD, PTAA and CBP solutions contained 100, 30, $40\\ \\mathrm{\\mg}$ of each HTM, respectively, in 1 mL of chlorobenzene, mixed with 10, 15, $3.6~\\mu\\mathrm{L}$ of tertbutylpyridine and 31, 15, $7~\\mu\\mathrm{L}$ of $170\\:\\:\\mathrm{\\mg/mL}$ LiTFSI [bis(trifluoromethane)sulfonamide (in acetonitrile)], respectively. \n\nThe samples were left overnight in the dark in dry air before $100\\ \\mathrm{nm}$ gold contacts were thermally evaporated on the back through a shadow mask with $0.24~\\mathrm{cm}^{2}$ rectangular holes. \n\nTransmission and reflection of films were measured using a Jasco V-570 spectrophotometer equipped with an integrating sphere. Transmission was corrected for reflection by using $T_{\\mathrm{corr}}$ $=T/(1-R)$ . \n\nA Leo Ultra 55 scanning electron microscope was used for SEM imaging. \n\nXRD measurements were conducted on a Rigaku ULTIMA III operated with a Cu anode at $40\\ensuremath{\\mathrm{~\\textrm~{~~}~}}\\ensuremath{\\mathrm{kV}}$ and $40\\ \\mathrm{\\mA}.$ The measurements were taken using a Bragg−Brentano configuration through a $10~\\mathrm{mm}$ slit, a convergence Soller $5^{\\circ}$ slit and a Ni filter. \n\nThe $J{-}V$ characteristics were measured with a Keithley 2400- LV SourceMeter and controlled with a Labview-based, in-house written program. A solar simulator (ScienceTech SF-150) equipped with a 1.5AM filter and calibrated with a Si solar cell IXOLAR High Efficiency SolarBIT $\\mathrm{'IXYSXOB17-}04\\times3)$ was used for illumination. The devices were characterized through a $0.16~\\mathrm{cm}^{2}$ mask. The $J{-}V$ characteristics were taken after light soaking for $10\\mathrm{~s~}$ at open circuit and at a scan rate of $0.06\\mathrm{V}/\\mathbf{s}$ . We note that variation of the scan rate between $0.06\\mathrm{V}/s$ and 1 $\\mathrm{v}/{\\mathrm{s}}$ made no difference to the $J{-}V$ characteristics (measured for the PTAA cell). \n\nExternal quantum efficiency/spectral response EQE was measured with a Thermo Oriel monochromator with the light chopped at $10\\ \\mathrm{Hz}$ . Current was measured using a Oriel Merlin and TTI PDA-700 photodiode amplifier. EQE was calculated by referencing to the spectral response of a Si photodiode with a known EQE. \n\nUPS measurements were carried out using a Kratos AXIS ULTRA system, with a concentric hemispherical analyzer for photoexcited electron detection. UPS was measured with a helium discharge lamp, using He I $(21.22~\\mathrm{eV})$ and He II (40.8 eV) radiation lines. The total energy resolution was better than $100~\\mathrm{{\\meV}},$ , as determined from the Fermi edge of an Au reference sample. \n\n# ASSOCIATED CONTENT \n\n# $\\bullet$ Supporting Information \n\nTauc plots, XRD, $J{-}V$ plots of $\\mathrm{mp-Al}_{2}{\\mathrm{O}}_{3}$ cells, table of hybrid $\\mathbf{MAPbBr}_{3}$ or $\\mathrm{FAPbBr}_{3}$ photovoltaic cells together with a list of HTMs used for comparison with the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ . The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpclett.5b00968. \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\n$^{*}\\mathrm{E}$ -mails: gary.hodes@weizmann.ac.il. \n$^{*}\\mathrm{E}$ -mails: david.cahen@weizmann.ac.il. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nWe thank Dr. Tatyana Bendikov for the UPS experiments. This work was supported by the Leona M. and Harry B. Helmsley Charitable Trust, the Sidney E. Frank Foundation through the Israel Science Foundation, the Israel Ministry of Science, and the Israel National Nano-Initiative. D.C. holds the Sylvia and Rowland Schaefer Chair in Energy Research. \n\n# REFERENCES \n\n(1) Stoumpos, C. C.; Malliakas; Kanatzidis, M. G. Semiconducting Tin and Lead Iodide Perovskites with Organic Cations: Phase Transitions, High Mobilities, and Near-Infrared Photoluminescent Properties. Inorg. Chem. 2013, 52, 9019−9038 and references therein. (2) Chen, Z.; Wang, J. J.; Ren, Y.; Yu, C.; Shum, K. Schottky Solar Cells Based on $\\mathrm{CsSnI}_{3}$ Thin-Films. Appl. Phys. Lett., 2012, 101. (3) Kumar, M. H.; Dharani, S.; Leong, W. L.; Boix, P. B.; Prabhakar, R. R.; Baikie, T.; Shi, C.; Ding, H.; Ramesh, $\\mathrm{R};$ Asta, M.; et al. LeadFree Halide Perovskite Solar Cells with High Photocurrents Realized Through Vacancy Modulation. Adv. Mater. 2014, 26, 7122−7127. (4) Stoumpos, C. C.; Malliakas, C. D.; Peters, J. A.; Liu, Z.; Sebastian, M.; Im, J.; Chasapis, C.; Wibowo, A. C.; Chung, D. Y.; Freeman, A. J.; et al. Crystal Growth of the Perovskite Semiconductor $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ : A New Material for High-Energy Radiation Detection. Cryst. Growth Des. 2013, 13, 2722−2727. \n(5) Work on controlled direct comparisons of identically prepared Cs- and MA- ${\\bf\\cdot P b B r}_{3}$ -based cells is ongoing. At present, our one-step $\\mathbf{MAPbBr}_{3}$ cells are considerably better than the two-step ones in spite of their less-homogeneous morphology. \n(6) Schulz, P.; Edri, E.; Kirmayer, S.; Hodes, G.; Cahen, D.; Kahn, A. Interface Energetics in Organo-Metal Halide Perovskite-Based Photovoltaic Cells. Energy Environ. Sci. 2014, 7, 1377−1381. \n(7) Ryu, S.; Noh, J. H.; Jeon, N. J.; Kim, Y. C.; Yang, W. S.; Seo, J.; Seok, S. I. Voltage Output of Efficient Perovskite Solar Cells with High Open-Circuit Voltage and Fill Factor. Energy Environ. Sci. 2014, 7, 2614−2618. \n(8) Choi, K.; Kwak, J.; Lee, C.; Kim, H.; Characteristic, K.; Kim, D.- Y.; Zentel, R. Thin Films of Poly-Triarylamines for Electro-Optic Applications. Polymer Bull. 2008, 59, 795−803. \n(9) Zhang, T.; Liang, Y.; Cheng, J.; Li, J. A CBP Derivative as Bipolar Host for Performance Enhancement in Phosphorescent Organic LightEmitting Diodes. J. Mater. Chem. C 2013, 1, 757−764. \n(10) Edri, E.; Kirmayer, S.; Cahen, D.; Hodes, G. High Open-Circuit Voltage Solar Cells Based on Organic-Inorganic Lead Bromide Perovskite. J. Phys. Chem. Lett. 2013, 3, 897−902. \n(11) Shi, D.; Adinolfi, V.; Comin, R.; Yuan, M.; Alarousu, E.; Buin, A.; Chen, Y.; Hoogland, S.; Rothenberger, A.; Katsiev, ${\\mathrm{K}}.{\\mathrm{}}$ et al. Low Trap-State Density and Long Carrier Diffusion in Organolead Trihalide Perovskite Single Crystals. Science 2015, 347, 519−522. (12) Dong, $\\mathrm{Q.;}$ Fang, Y.; Shao, Y.; Mulligan, P.; Qiu, J.; Cao, L.; Huang, J. Electron-Hole Diffusion Lengths $>175\\ \\mathrm{mm}$ in SolutionGrown $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ Single Crystals. Science 2015, 347, 967. \n(13) Fahrenbuch, A. L.; Bube, R. H. Fundamentals of Solar Cells; Academic Press: New York, 1983; pp 236−240. \n(14) Kedem, N.; Brenner, T. M.; Kulbak, M.; Schaefer, N.; Levcenco, S.; Levine, I.; Abou-Ras, D.; Hodes, G.; Cahen, D. Light-Induced Increase of Electron Diffusion Length in a p-n Junction Type $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ Perovskite Solar Cell. J. Phys. Chem. Lett. 2015, DOI: 10.1021/acs.jpclett.5b00889. (15) Aharon, S.; Cohen, B. E.; Etgar, L. Hybrid Lead Halide Iodide and Lead Halide Bromide in Efficient Hole Conductor Free Perovskite Solar Cell. J. Phys. Chem. C 2014, 118, 17160−17165. \n(16) Dymshits, A.; Rotem, A.; Etgar, L. High Voltage in Hole Conductor Free Organo Metal Halide Perovskite Solar Cells. J. Mater. Chem. A 2014, 2, 20776−20781. \n(17) Suarez, B.; Gonzalez-Pedro, V.; Ripolles, T. S.; Sanchez, R. S.; Otero, L.; Mora-Sero, I. Recombination Study of Combined Halides (Cl, Br, I) Perovskite Solar Cells. J. Phys. Chem. Lett. 2014, 5, 1628− 1635. \n(18) Heo, J. H.; Song, D. H.; Im, S. H. Planar $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ Hybrid Solar Cells with $10.4\\%$ Power Conversion Efficiency, Fabricated by Controlled Crystallization in the Spin-Coating Process. Adv. Mater. 2014, 26, 8179−8183. \n(19) Sheng, R.; Ho-Baillie, A.; Huang, S.; Chen, S.; Wen, X.; Hao, X.; Green, M. A. Methylammonium Lead Bromide Perovskite-Based Solar Cells by Vapor-Assisted Deposition. J. Phys. Chem. C 2015, 119, 3545−3549. " + }, + { + "id": "10.1038_NPHYS3372", + "DOI": "10.1038/NPHYS3372", + "DOI Link": "http://dx.doi.org/10.1038/NPHYS3372", + "Relative Dir Path": "mds/10.1038_NPHYS3372", + "Article Title": "Extremely large magnetoresistance and ultrahigh mobility in the topological Weyl semimetal candidate NbP", + "Authors": "Shekhar, C; Nayak, AK; Sun, Y; Schmidt, M; Nicklas, M; Leermakers, I; Zeitler, U; Skourski, Y; Wosnitza, J; Liu, ZK; Chen, YL; Schnelle, W; Borrmann, H; Grin, Y; Felser, C; Yan, BH", + "Source Title": "NATURE PHYSICS", + "Abstract": "Recent experiments have revealed spectacular transport properties in semimetals, such as the large, non-saturating magnetoresistance exhibited by WTe2 (ref.1). Topological semimetals with massless relativistic electrons have also been predicted(2) as three-dimensional analogues of graphene(3). These systems are known as Weyl semimetals, and are predicted to have a range of exotic transport properties and surface states(4-7), distinct from those of topological insulators(8,9). Here we examine the magneto-transport properties of NbP, a material the band structure of which has been predicted to combine the hallmarks of a Weyl semimetal(10,11) with those of a normal semimetal. We observe an extremely large magnetoresistance of 850,000% at 1.85 K (250% at room temperature) in a magnetic field of up to 9 T, without any signs of saturation, and an ultra-high carrier mobility of 5 x 10(6) cm(2) V-1 s(-1) that accompanied by strong Shubnikov-de Haas (SdH) oscillations. NbP therefore presents a unique example of a material combining topological and conventional electronic phases, with intriguing physical properties resulting from their interplay.", + "Times Cited, WoS Core": 958, + "Times Cited, All Databases": 1020, + "Publication Year": 2015, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000358851900016", + "Markdown": "# Extremely large magnetoresistance and ultrahigh mobility in the topological Weyl semimetal candidate NbP \n\nChandra Shekhar1, Ajaya K. Nayak1,2, Yan Sun1, Marcus Schmidt1, Michael Nicklas1, Inge Leermakers3, Uli Zeitler3, Yurii Skourski4, Jochen Wosnitza4, Zhongkai Liu5, Yulin Chen6, Walter Schnelle1, Horst Borrmann1, Yuri Grin1, Claudia Felser1 and Binghai $\\mathsf{Y a n}^{1,7\\star}$ \n\nRecent experiments have revealed spectacular transport properties in semimetals, such as the large, non-saturating magnetoresistance exhibited by $\\ensuremath{\\mathbf{w}}\\ensuremath{\\mathbb{T e}_{2}}$ (ref. 1). Topological semimetals with massless relativistic electrons have also been predicted2 as three-dimensional analogues of graphene3. These systems are known as Weyl semimetals, and are predicted to have a range of exotic transport properties and surface states4–7, distinct from those of topological insulators8,9. Here we examine the magneto-transport properties of NbP, a material the band structure of which has been predicted to combine the hallmarks of a Weyl semimetal10,11 with those of a normal semimetal. We observe an extremely large magnetoresistance of $850,000\\%$ at 1.85 K $(250\\%$ at room temperature) in a magnetic field of up to ${\\mathfrak{s T}},$ without any signs of saturation, and an ultrahigh carrier mobility of ${\\bf5}\\times10^{6}\\ c m^{2}\\vee-1\\ s^{-1}$ that accompanied by strong Shubnikov–de Haas (SdH) oscillations. NbP therefore presents a unique example of a material combining topological and conventional electronic phases, with intriguing physical properties resulting from their interplay. \n\nA Weyl semimetal (WSM) is a three-dimensional analogue of graphene, in which the conduction and valence bands cross near the Fermi energy. The band-crossing point, the so-called Weyl point, acts as a magnetic monopole (a singular point of Berry curvature) in momentum space and always comes in a pairs. Unusual transport properties and surface states such as Fermi arcs are predicted, stimulating strong interest in realizing the WSM state in real materials2,12,13. If the time-reversal and inversion symmetries are respected, a pair of Weyl points can become degenerate in energy as a result of the crystal symmetry, forming another topological phase called a Dirac semimetal14,15. WSMs and Dirac semimetals usually exhibit very high mobilities, possibly attributed to the high Fermi velocity of massless Dirac states, as observed in transport experiments (such as $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ ; refs 16,17). Generally, semimetals are new platforms to realize a huge magnetoresistance (MR; refs 18,19), an effect that has been pursued intensively in emerging materials in recent years, because of its significant application in state-of-theart information technologies20. Electrical transport in a semimetal usually consists of two types of carriers (electrons and holes), leading to a large MR when a magnetic field is applied at an electron–hole resonance1,21. In a simple Hall effect set-up, the transverse current carried by a particular type of carrier may be non-zero, although no net transverse current flows when the currents carried by the electrons and holes compensate for each other. These nonzero transverse currents will experience a Lorentz force caused by the magnetic field in the inverse-longitudinal direction. Such a back flow of carriers eventually increases the apparent longitudinal resistance, resulting in an extremely high MR that is much stronger than that in normal metals and semiconductors. Thus, it is crucial to obtain high-purity samples to realize a balance between electrons and holes and a high carrier mobility $(\\mu)$ as well, both of which will enhance the MR effect. \n\n![](images/315d7368580c53761d1757087b693db9fcbaf308382bf2ea7bfe74903a260bd7.jpg) \nFigure 1 | Band structure for diferent semimetals. Schematic illustration of diferent types of semimetals and representative materials. a, Normal semimetal with the coexistence of electron and hole pockets. b, Semimetal with quadratic conduction and valence bands touching at the same momentum point. c, Weyl semimetal and Dirac semimetal. d, Semimetal with one hole pocket from the normal quadratic band and one electron pocket from the linear Weyl semimetal band for NbP. The valence and conduction bands are indicated by blue and green shading, respectively. The Fermi energy is marked in each case by a horizontal line. \n\nElemental Bi (refs 22–25) and $\\mathrm{WTe}_{2}$ (ref. 1) exhibit a high MR as typical examples of semimetals, in which electron and hole pockets coexist on the Fermi surface (Fig. 1a). There is a special type of semimetal whose conduction-band bottom and valenceband top touch the Fermi surface at the same point in momentum $(k)$ space (Fig. $^{1\\mathrm{b,c}}$ ). Many such semimetals exhibit a high carrier mobility and relatively large MR, with a linear dependence on the magnetic field, such as zero-gap topological-insulator silver chalcogenides26,27 and Heusler compounds28–30, the Dirac semimetal $\\mathrm{Cd}_{3}\\mathrm{A}s_{2}$ $\\stackrel{\\cdot}{\\mu}=9\\times10^{6}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ at $5\\mathrm{K}$ , $\\mathrm{MR}=1{,}500\\%$ at $1.5\\mathrm{K}$ and \n\n![](images/6177ec588de4a2a0609c26bd1b37a04a64cf62d48d2d13151067eed55e31bc59.jpg) \nFigure 2 | Crystal structure, magnetoresistance and mobility. a, Orientation of the measured single-crystal NbP with the respective $\\mathsf{X}$ -ray difraction axial oscillation patterns. b, Crystal structure of NbP in a body-centred-tetragonal lattice. c, Temperature dependence of the resistivity, $\\rho_{x x},$ measured at diferent transverse magnetic fields, as labelled next to the corresponding curve. The inset of c shows the temperature dependence of resistance measured in zero field. d, Transverse magnetoresistance measured at diferent temperatures in magnetic fields up to ${9\\mathord{\\uparrow}}.$ The inset shows the magnetoresistance at higher temperatures. e, Temperature dependence of the mobility (left ordinate) and the carrier density (right ordinate). The inset shows the evolution of the Hall coefcient with temperature. The temperature regimes where electrons and holes act as the main charge carriers are marked with blue and red shading, respectively. f, Magnetoresistance measured at diferent angles, $\\theta$ , between the current $(1)$ and the magnetic field (B) as shown schematically in the inset. \n\n$14.5\\mathrm{T}$ ; refs 16,31–33), and the WSM TaAs $\\langle\\mu=5\\times10^{5}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ at $2\\mathrm{K},$ $\\mathrm{MR}=5.4\\times10^{5}\\%$ at $10\\mathrm{K}$ and $9\\mathrm{T}$ ; ref. 34). The high mobility may originate from the linear or nearly linear energy dispersion. The unsaturated linear MR is interpreted as a classical effect due to the strong inhomogeneity in the carrier density35 or as a quantum effect due to the linear energy dispersion at the band touching point36. The semimetal NbP combines the main features of the $\\mathrm{WTe}_{2}$ -type (showing extremely large MR) and $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ -type (showing ultrahigh mobility) semimetals in the band structure (Fig. 1d), exhibiting hole pockets from normal quadratic bands and electron pockets from linear Weyl bands. As we will see, NbP exhibits an ultrahigh carrier mobility, comparable to that of $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ , and an extremely large MR, surpassing that of $\\mathrm{WTe}_{2}$ . \n\nThe single crystal of NbP used for the present study and the respective $\\mathrm{\\DeltaX}$ -ray diffraction patterns are shown in Fig. 2a. The crystal structure of NbP is non-centrosymmetric space group $I4_{1}m d$ (Fig. 2b). No indication of twinning was found in the diffraction experiments. Both atom types have the same coordination number of six, and the same coordination environment in the form of a trigonal prism. A detailed overview of the structural characterization is presented in the Supplementary Information. A measurement of the temperature dependence of the resistivity, $\\rho_{x x}(T)$ , is a simple way to identify the electronic states of a material. On the basis of our high-quality single crystals of NbP grown via chemical vapour transport reactions, $\\rho_{x x}(T)$ is measured under various transverse magnetic fields ranging from 0 to $^{9\\mathrm{T}}$ as shown in Fig. 2c. At zero field, we observe metallic behaviour with $\\rho_{x x}(300\\mathrm{K})=73\\upmu\\Omega$ cm and a residual resistivity $\\rho_{x x}(2\\mathrm{K}){=}0.63\\upmu\\Omega\\mathrm{cm}.$ This results in a residual resistivity ratio $[\\rho_{x x}(300\\mathrm{K})/\\rho_{x x}(2\\mathrm{K})]{=}115$ , which is directly related to the metallicity and quality of the crystal. Compared to other similar materials at low temperature (2 K), NbP exhibits a resistivity that is about 30 times lower than that of $\\mathrm{WTe}_{2}$ (ref. 1) but 30 times higher than that of $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ (ref. 16). NbP does not become superconducting for temperatures above $0.10\\mathrm{K}.$ After applying a magnetic field, we observe a remarkable change in the resistivity. $\\rho_{x x}(T)$ changes from a positive slope (metallic) to a negative slope (semiconducting) at a very small field of $0.1\\mathrm{T},$ and becomes completely semiconducting at a field of $2\\mathrm{T}.$ This may be due to the opening of a gap at the Weyl point. In general, a conventional semimetal does not exhibit such behaviour, whereas some small-gap or gapless semimetals (for example, $\\mathrm{WTe}_{2}$ (ref. 1) and $\\mathrm{Cd}_{3}\\mathrm{A}\\mathsf{s}_{2}$ (ref. 16)) exhibit a similar trend, usually at very high fields and low temperature. Another important fact observed in the present material is that $\\rho_{x x}(T)$ also increases markedly owing to the application of magnetic fields at room temperature $(300\\mathrm{K})$ . \n\nWe now focus on the MR measurement in NbP. The MR is commonly calculated as the ratio of the change in resistivity due to the applied magnetic field $(H)$ , $[(\\rho(H)-\\bar{\\rho(0)})/\\rho(0)]\\times100\\%$ . Figure 2d shows the MR measured in transverse magnetic fields up to $9\\mathrm{T}$ at different temperatures. At low temperatures, we find that NbP exhibits an extremely large $\\mathrm{MR}=8.5\\times10^{5}\\%$ at $1.85\\mathrm{K}$ in a field of $9\\mathrm{T}.$ This MR is five times as large as that measured for the same field in $\\mathrm{WTe}_{2}$ (ref. 1) and nearly twice as large as that of TaAs (ref. 34), another WSM predicted in the same family as NbP (refs 10,11). On increasing the temperature, the MR of NbP remains almost unchanged up to $20\\mathrm{K}$ and then starts to decrease at higher temperatures. We note that the MR is still as high as $250\\%$ in a field of $9\\mathrm{T}$ at room temperature (inset of Fig. 2d). We have also measured the dependence of the MR on the direction of the magnetic field. Figure 2f shows the MR observed at different angles $\\left(\\theta\\right)$ between the field direction and the current direction. The MR decreases slightly from $8.5\\times10^{5}\\%$ at $\\theta=90^{\\circ}$ (transverse) to $2.5\\times10^{5}\\%$ at $\\theta=0^{\\circ}$ (longitudinal). Thus, the MR varies by a factor of only 3.4, implying a relatively isotropic nature of the material compared with the layered semimetal $\\mathrm{WTe}_{2}$ . \n\n![](images/fcdc2ed28e978e47ee731afc4ead3a88bdf76a75efff4c800fc42294dfa4e84a.jpg) \nFigure 3 | High-field magnetoresistance and SdH oscillation. a, Transverse MR measured in static magnetic fields of up to $30\\top$ at diferent temperatures. The inset of a shows the MR measured in a pulsed magnetic field up to $62\\top.$ b, SdH oscillations after subtracting the background from the $9\\top\\rho_{x x}$ measurements. The inset of b shows the temperature dependence of the relative amplitude of $\\Delta\\rho_{x x}$ for the SdH oscillation at $8.2\\top$ The solid line is a fit to the Lifshitz–Kosevich formula. c, SdH oscillations after subtracting the background from the 30 T $\\rho_{x x}$ measurements. \n\nA large MR is usually associated with a high mobility. The carrier mobility and concentration are two important parameters of a material that can be derived from the Hall coefficient. We have performed Hall effect measurements in both temperaturesweep and field-sweep modes to improve the accuracy of our data. The field dependence of the Hall resistivity $\\rho_{x y}(H)$ exhibits a linear characteristic at high fields (see Supplementary Information). However, the nonlinear behaviour in low fields indicates the involvement of more than one type of charge carrier in the transport properties. As seen from the inset of Fig. 2e, NbP exhibits a negative Hall coefficient, $R_{\\mathrm{H}}(T)$ , up to $125\\mathrm{K},$ which changes sign for temperatures above $125\\mathrm{K}$ . For the sake of simplicity, we use the single-carrier Drude band model, $n_{\\mathrm{e,h}}(T)=1/[e R_{\\mathrm{H}}(T)].$ , to calculate the carrier density and $\\mu_{\\mathrm{e},\\mathrm{h}}(T)=R_{\\mathrm{H}}(T)/\\rho_{x x}(T)$ to estimate the mobility, where $n_{\\mathrm{e}}(n_{\\mathrm{h}})$ and $\\mu_{\\mathrm{e}}(\\mu_{\\mathrm{h}})$ are the charge density and mobility of the electron (hole), respectively. We use the slope of $\\rho_{x y}(H)$ at high fields to calculate the Hall coefficient (Fig. 2e). The electron carrier concentration, $n_{\\mathrm{e}}$ , is found to be $1.5\\times10^{18}\\mathrm{cm}^{-3}$ at $1.85\\mathrm{K},$ and increases slowly with temperature, exhibiting a semimetal-like or very small gap-like behaviour. The mobility plays a major role in the charge transport in a material and consequently determines the efficiency of various devices. Here, NbP exhibits an ultrahigh mobility of $5\\times10^{6}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ at $1.85\\mathrm{K}$ . This value is close to that of $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ $(9\\times10^{6}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ ; ref. 16), one order magnitude higher than that of TaAs (ref. 34) at $2\\mathrm{K}.$ . We note that the current mobility is extracted from a simple one-band model that neglects anisotropy. This averaged mobility is below the record mobility measured in Bi $(10^{8}\\thinspace\\mathrm{cm}^{2}\\thinspace\\breve{\\mathrm{V}}^{-1}\\thinspace\\mathrm{s}^{-1}$ ; ref. 37). Furthermore, it has been shown that the mobility in $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ scales with the residual resistivity. Hence, it can be proposed that materials with a low residual resistivity exhibit high mobilities, with the present case being a good example. \n\nThe low-field measurements (Fig. 2d,f) show no saturation of the MR up to $9\\mathrm{T}$ in the entire temperature range. To pursue this finding to even higher fields, we have performed transverse MR measurements up to $30\\mathrm{T}$ in d.c. magnetic fields, as shown in Fig. 3a. The MR increases to $3.6\\times10^{6}\\%$ for a field of $30\\mathrm{T}$ at $1.3\\mathrm{K},$ and still shows no tendency of saturation. We have further corroborated this trend of a non-saturating magnetoresistance by performing experiments in pulsed magnetic fields up to $62\\mathrm{T}$ at $1.5\\mathrm{K}$ (inset of Fig. 3a). The MR continues to increase with magnetic field up to $62\\mathrm{T},$ the maximum field reached in the pulsed magnetic field experiments, when we find a MR of $8.1\\times10^{4}$ (or $8.1\\times10^{6}\\%$ ). In a field as high as $60\\mathrm{T},$ we note that $\\mathrm{WTe}_{2}$ (ref. 1) and Bi (ref. 25) are reported to exhibit a MR of $1.3\\times10^{5}$ and $1\\times10^{6}$ , respectively. As already indicated in the $9\\mathrm{T}$ MR data depicted in Fig. 2d,f, SdH quantum oscillations appear for $T\\le30\\mathrm{K}$ . At the lowest temperature $(1.85\\mathrm{K})$ the oscillations start for fields as low as $1\\mathrm{T}$ . Because SdH oscillations appear only when the energy spacing between two Landau levels is larger than their broadening due to disorder, we can estimate a lower limit to the quantum mobility of the carriers involved, $\\mu_{\\mathrm{q}}>10^{5}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ , in agreement with the large electron (transport) mobility extracted from the Hall effect. \n\nThe physical parameters of the charge carriers are derived from the Fermi surface that is measured by the oscillations observed in the transport properties. Both $\\rho_{x x}$ and $\\rho_{x y}$ measured up to $9\\mathrm{T}$ exhibit very clear SdH oscillations starting from $1\\mathrm{T}$ This indicates a very low effective mass, resulting in a high mobility. To obtain the amplitude of the SdH oscillations, $\\Delta\\rho_{x x}$ , from $\\rho_{x x}$ , we subtracted a smooth background. The results are plotted as a function of $1/(\\mu_{0}H)$ at various temperatures in Fig. 3b. As expected, the oscillations are periodic in $1/(\\mu_{0}H)$ . They occur owing to the quantization of energy levels, which directly gives the effective mass of the charge carriers. We observe three different oscillation frequencies of $F=7\\mathrm{T}_{\\cdot}$ , $13\\mathrm{T}$ and $32\\mathrm{T}$ from the data shown in Fig. 3b, which is consistent with the existence of tiny carrier pockets near the Weyl points in the calculated Fermi surface (Fig. 4). We note that these frequencies depend sensitively on the field direction. For example, the frequency of $F=32\\mathrm{T}_{\\mathrm{:}}$ which is equivalent to the periodicity $1/(\\mu_{0}\\Delta H)=0.03127\\mathrm{T}^{-1}$ , corresponds to a cross-sectional area of the Fermi surface $A_{\\mathrm{{F}}}{=}0.003\\mathring\\mathrm{{A}}^{-2}$ from the Onsager relationship $F=(\\varPhi_{0}/2\\pi^{2})A_{\\mathrm{F}}$ , where $\\varPhi_{0}$ is the magnetic flux quantum. This is a tiny area, only $0.08\\%$ of the cross-sectional area of the first Brillouin zone. Supposing a circular cross-section, a very small Fermi momentum $\\bar{k_{\\mathrm{F}}}=0.0\\bar{3}12\\mathring{\\mathrm{A}}^{-1}$ is obtained. The cyclotron effective mass of the carriers is determined by fitting the temperature dependence of amplitude of the oscillations to the Lifshitz–Kosevich formula, \n\n![](images/754eb18224d53fbadc5e9e548953a1538af8cce812058c9418b37d68639e403a.jpg) \nFigure 4 | Bulk band structures of NbP. a, Ab initio band structure. The dispersions along $k_{y}$ connecting a pair of Weyl points with opposite chirality are plotted for the W1- and W2-types of Weyl points in the right panels. Red and green circles represent positive and negative chiral Weyl points, respectively. The Fermi energy is shifted to zero. The valence and conduction bands are indicated by the red and blue lines, respectively. b, The first Brillouin zone in momentum space for the primitive unit cell. All twelve pairs of Weyl points are illustrated, in which W1 and W2-types of Weyl points are indicated. c, Bulk Fermi surfaces. The blue and red surfaces represent electron (W1 and W2) and hole (H) pockets, respectively. The Fermi energy is chosen as the slightly electron-doped case to qualitatively match the experiment. \n\n$$\n\\frac{\\Delta\\rho_{x x}(T,B)}{\\rho_{x x}(0)}{=}{\\mathrm e}^{-2\\pi^{2}k_{\\mathrm{B}}T_{\\mathrm{D}}/\\beta}\\frac{2\\pi^{2}k_{\\mathrm{B}}T/\\beta}{\\sinh(2\\pi^{2}k_{\\mathrm{B}}T/\\beta)}\n$$ \n\nwhere $k_{\\mathrm{B}}$ is Boltzmann’s constant, $\\beta=e h B/2\\uppi m^{*}$ and $T_{\\mathrm{D}}=h/4\\uppi^{2}\\tau k_{\\mathrm{B}}$ are the fitting parameters, which directly results in the effective mass $m^{*}$ and quantum lifetime $\\tau$ of the charge carriers. The value of $m^{*}$ calculated from the temperature-dependent SdH oscillations in a field of $8.2\\mathrm{T}$ is $0.076~m_{0}$ , where $m_{0}$ is the bare mass of the electron. This value is comparable to that reported for $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ (ref. 16). We also find a very large Fermi velocity $\\nu_{\\mathrm{{F}}}=\\hbar k_{\\mathrm{{F}}}/m^{*}=4.8\\times10^{5}\\mathrm{{m}}{\\mathrm{{s}}^{-1}}$ . The large Fermi velocity and low effective mass are responsible for the observed ultrahigh mobility in NbP. \n\nThe SdH oscillations at different temperatures obtained from the $30\\mathrm{T}$ dc magnetic field measurements are plotted in Fig. 3c. At the lowest temperature, marked by arrows, the SdH maxima at $^{8\\mathrm{T}}$ $(0.125\\mathrm{T}^{-1}),$ and $11\\mathrm{T}(0.091\\mathrm{T}^{-1})$ start to split into two distinct peaks, and the maximum at $16\\mathrm{T}$ $(0.0625\\mathrm{T}^{-1})_{~,}$ ) develops into four peaks. This can be assigned to the lifting of the spin degeneracy and the degeneracy of the dual Weyl point. \n\nTo further understand the transport properties and verify the Weyl physics of NbP, we have performed ab initio band-structure calculations. NbP crystallizes in a body-centred-tetragonal lattice with the non-symmorphic space group $I4_{1}m d$ . The lack of inversion symmetry of the lattice leads to the lifting of spin degeneracy in the band structure. Near the Fermi energy, twelve pairs of Weyl points lie aside the central planes in the Brillouin zone, consistent with recent calculations10,11. Twelve pairs of Weyl points can be classified into two groups, labelled as W1 and W2 (Fig. 4b). The W1 pair that lies in the $k_{z}=0$ plane is lower in energy that the W2 pair off the $k_{z}=0$ plane. An important feature in the band structure is that the Fermi energy crosses the quadratic-type valence bands and also the linear Weyl-type conduction bands, leading to very small hole and electron pockets on the Fermi surface, respectively. Four equivalent hole pockets appear around the Z point (labelled as H in Fig. 4c). Four larger and eight smaller electron pockets exist near the $\\Sigma$ and $\\mathrm{~N~}$ points, respectively, corresponding to W1 and W2 Weyl bands. This is consistent with multiple tiny Fermi surface areas with low effective masses extracted from SdH oscillations. We note that the specific shape of the Fermi surfaces relies sensitively on the position of the Fermi energy, which is determined by the dopant concentration of the sample. In Fig. 4c we set the Fermi energy as the ideal electron–hole compensation case. Furthermore, from the bulk to the surface, as a manifestation of topology, Fermi arcs exist between the projection of Weyl points with opposite chirality. Angle-resolved photoemission spectroscopy (ARPES) experiments are called for to verify NbP as a WSM by investigating the surface states. \n\nAs we have demonstrated here, NbP is an exotic semimetal with interesting transport properties. As seen in the band structure, it combines the electronic structures of a normal semimetal and a WSM together. Similar to normal semimetals such as $\\mathrm{WTe}_{2}$ and Bi, NbP exhibits both electron and hole pockets at different positions in the Brillouin zone; however, unlike $\\mathrm{WTe}_{2}$ and Bi, its electron pockets are relevant to the linear Weyl bands, from which the high mobility of the high-quality samples may originate. In contrast to Weyl semimetals (for example, TaAs) and Dirac semimetals (for example, $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ ), in which the Fermi energy may cross only one type of band (electron or hole), NbP naturally hosts both types of carriers and consequently exhibits a huge MR in an electron–hole resonance situation. \n\n# Methods \n\nMethods and any associated references are available in the online version of the paper. \n\n# Received 16 March 2015; accepted 19 May 2015; published online 22 June 2015 \n\n# References \n\n1. Ali, M. N. et al. Large, non-saturating magnetoresistance in $\\mathrm{WTe}_{2}$ . Nature 514, 205–208 (2014). \n2. Wan, X. G., Turner, A. M., Vishwanath, A. & Savrasov, S. Y. Topological semimetal and Fermi-arc surface states in the electronic structure of pyrochlore iridates. Phys. Rev. B 83, 205101 (2011). \n3. Novoselov, K. et al. Two-dimensional gas of massless Dirac fermions in graphene. Nature 438, 197–200 (2005). \n4. Turner, A. M. & Vishwanath, A. Beyond band insulators: Topology of semi-metals and interacting phases. Preprint at http://arxiv.org/abs/1301.0330 (2013). \n5. Hosur, P. & Qi, X. L. Recent developments in transport phenomena in Weyl semimetals. C. R. Phys. 14, 857–870 (2013). \n6. Vafek, O. & Vishwanath, A. Dirac Fermions in solids: From high- $T_{c}$ cuprates and graphene to topological insulators and Weyl semimetals. Annu. Rev. Condens. Matter Phys. 5, 83–112 (2014). \n7. Parameswaran, S. A., Grover, T., Abanin, D. A., Pesin, D. A. & Vishwanath, A. Probing the chiral anomaly with nonlocal transport in three-dimensional topological semimetals. Phys. Rev. X 4, 031035 (2014). \n8. Qi, X-L. & Zhang, S-C. Topological insulators and superconductors. Rev. Mod. Phys. 83, 1057–1110 (2011). \n9. Hasan, M. Z. & Kane, C. L. Colloquium: Topological insulators. Rev. Mod. Phys. 82, 3045–3067 (2010). \n10. Weng, H., Fang, C., Fang, Z., Bernevig, B. A. & Dai, X. Weyl semimetal phase in noncentrosymmetric transition-metal monophosphides. Phys. Rev. X 5, 011029 (2015). \n11. Huang, S-M. et al. An inversion breaking Weyl semimetal state in the TaAs material class. Preprint at http://arxiv.org/abs/1501.00755 (2015). \n12. Burkov, A. A. & Balents, L. Weyl semimetal in a topological insulator multilayer. Phys. Rev. Lett. 107, 127205 (2011). \n13. Xu, G., Weng, H., Wang, Z., Dai, X. & Fang, Z. Chern semimetal and the quantized anomalous Hall effect in $\\mathrm{HgCr}_{2}\\mathrm{Se}_{4}$ . Phys. Rev. Lett. 107, 186806 (2011). \n14. Wang, Z. et al. Dirac semimetal and topological phase transitions in $A_{3}{\\mathrm{Bi}}$ ${\\bf\\ddot{A}}={\\bf N\\vec{a}};$ , K, Rb). Phys. Rev. B 85, 195320 (2012). \n15. Wang, Z., Weng, H., Wu, Q., Dai, X. & Fang, Z. Three-dimensional Dirac semimetal and quantum transport in $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ . Phys. Rev. B 88, 125427 (2013). \n16. Liang, T. et al. Ultrahigh mobility and giant magnetoresistance in the Dirac semimetal $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ . Nature Mater. 14, 280–284 (2014). \n17. Narayanan, A. et al. Linear magnetoresistance caused by mobility fluctuations in n-doped $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ . Phys. Rev. Lett. 114, 117201 (2015). \n18. Baibich, M. N., Broto, J. M., Fert, A., Van Dau, F. N. & Petroff, F. Giant magnetoresistance of $(001)\\mathrm{Fe}/(001)\\mathrm{Cr}$ magnetic superlattices. Phys. Rev. Lett. 61, 2472–2475 (1988). \n19. Binasch, G., Grünberg, P., Saurenbach, F. & Zinn, W. Enhanced magnetoresistance in layered magnetic structures with antiferromagnetic interlayer exchange. Phys. Rev. B 39, 4828–4830 (1989). \n20. Parkin, S. et al. Magnetically engineered spintronic sensors and memory. Proc. IEEE 91, 661–680 (2003). \n21. Singleton, J. Band Theory and Electronic Properties of Solids (Oxford Univ. Press, 2001). \n22. Mangez, J. H., Issi, J. P. & Heremans, J. Transport properties of bismuth in quantizing magnetic fields. Phys. Rev. B 14, 4381–4385 (1976). \n23. Heremans, J. et al. Cyclotron resonance in epitaxial $\\mathrm{Bi}_{\\mathrm{l}-x}\\mathrm{Sb}_{x}$ films grown by molecular-beam epitaxy. Phys. Rev. B 48, 11329–11335 (1993). \n24. Yang, F. Y. et al. Large magnetoresistance of electrodeposited single-crystal bismuth thin films. Science 284, 1335–1337 (1999). \n25. Fauqué, B., Vignolle, B., Proust, C., Issi, J-P. & Behnia, K. Electronic instability in bismuth far beyond the quantum limit. New J. Phys. 11, 113012 (2009). \n26. Xu, R. et al. Large magnetoresistance in non-magnetic silver chalcogenides. Nature 390, 57–60 (1997). \n27. Zhang, W. et al. Topological aspect and quantum magnetoresistance of $\\beta$ -Ag2Te. Phys. Rev. Lett. 106, 156808 (2011). \n28. Chadov, S. et al. Tunable multifunctional topological insulators in ternary Heusler compounds. Nature Mater. 9, 541–545 (2010). \n29. Shekhar, C. et al. Ultrahigh mobility and nonsaturating magnetoresistance in Heusler topological insulators. Phys. Rev. B 86, 155314 (2012). \n30. Yan, B. & de Visser, A. Half-Heusler topological insulators. MRS Bull. 39, 859–866 (2014). \n31. He, L. P. et al. Quantum transport evidence for the three-dimensional Dirac semimetal phase in $\\mathrm{Cd}_{3}\\mathrm{A}s_{2}$ . Phys. Rev. Lett. 113, 246402 (2014). \n32. Feng, J. et al. Large linear magnetoresistance in Dirac semi-metal $\\mathrm{Cd}_{3}\\mathrm{As}_{2}$ with Fermi surfaces close to the Dirac points. Preprint at http://arxiv.org/abs/1405.6611v1 (2014). \n33. He, L. P. et al. Quantum transport evidence for the three-dimensional Dirac semimetal phase in $\\mathrm{Cd}_{3}\\mathrm{A}\\mathbf{s}_{2}$ . Phys. Rev. Lett. 113, 246402 (2014). \n34. Zhang, C. et al. Tantalum monoarsenide: An exotic compensated semimetal. Preprint at http://arxiv.org/abs/1502.00251 (2015). \n35. Parish, M. M. & Littlewood, P. B. Non-saturating magnetoresistance in heavily disordered semiconductors. Nature 426, 162–165 (2003). \n36. Abrikosov, A. Quantum magnetoresistance. Phys. Rev. B 58, 2788–2794 (1998). \n37. Collaudin, A., Fauqué, B., Fuseya, Y., Kang, W. & Behnia, K. Angle dependence of the orbital magnetoresistance in bismuth. Phys. Rev. X 5, 021022 (2015). \n\n# Acknowledgements \n\nThis work was financially supported by the Deutsche Forschungsgemeinschaft DFG (Project No.EB 518/1-1 of DFG-SPP 1666 ‘Topological Insulators’) and by the ERC Advanced Grant No. (291472) ‘Idea Heusler’. Y.C. acknowledge support from the EPSRC (UK) grant EP/K04074X/1 and a DARPA (US) MESO project (no. N66001-11-1-4105). We acknowledge the support of the High Magnetic Field Laboratory Dresden (HLD) at HZDR and High Field Magnet Laboratory Nijmegen (HFML-RU/FOM), members of the European Magnetic Field Laboratory (EMFL). \n\n# Author contributions \n\nB.Y. conceived the original idea for the project. C.S. performed the low-field PPMS measurement with the help of M.N. and W.S. C.S., I.L. and U.Z. performed the $30\\mathrm{T}$ static magnetic field measurements. Y.Skourski, A.K.N. and J.W. performed the pulsed high magnetic field experiments. M.S. grew the single-crystal samples. Y.Sun and B.Y. calculated band structures. H.B. and Y.G. characterized the crystal structure. Z.L. and Y.C. contributed to helpful discussions. All authors analysed the results. B.Y., C.S. and A.K.N. wrote the manuscript with substantial contributions from all authors. C.F. supervised the project. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to B.Y. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. \n\n# Methods \n\nHigh-quality single crystals of NbP were grown via a chemical vapour transport reaction using iodine as a transport agent. Initially, a polycrystalline powder of NbP was synthesized by a direct reaction of niobium (Chempur $99.9\\%$ ) and red phosphorus (Heraeus $99.999\\%$ ) kept in an evacuated fused silica tube for $^{48\\mathrm{h}}$ at $800^{\\circ}\\mathrm{C}$ Starting from this microcrystalline powder, the single crystals of NbP were synthesized by chemical vapour transport in a temperature gradient starting from $850^{\\circ}\\mathrm{C}$ (source) to $950^{\\circ}\\mathrm{C}$ (sink) and a transport agent with a concentration of $13.5\\mathrm{mg}\\mathrm{cm}^{-3}$ iodine (Alfa Aesar $99.998\\%$ ; ref. 38). The orientation and crystal structure of the present single crystal were investigated using the diffraction data sets collected on a Rigaku AFC7 diffractometer equipped with a Saturn $^{724+}$ charge-coupled device detector (monochromatic Mo $\\mathrm{Ka}$ radiation, $\\lambda{=}0.71073\\mathrm{\\AA}$ ). Structure refinement was performed by full-matrix least-squares on $F$ using the program package WinCSD. \n\nThe transport measurements were performed in various physical property measurement systems (PPMS, Quantum Design, ACT option, home build adiabatic demagnetization stage). The $30\\mathrm{T}$ static magnetic field measurements were performed at the High Field Magnet Laboratory HFML-RU/FOM in Nijmegen, and the pulsed magnetic field experiments were carried out at the \n\nDresden High Magnetic Field Laboratory HLD-HZDR; both laboratories are members of the European Magnetic Field Laboratory (EMFL). \n\nThe ab initio calculations were performed within the framework of density functional theory (DFT), implemented in the Vienna ab initio simulation package39. The core electrons were represented by the projector-augmented-wave potential and generalized gradient approximation (GGA) are employed for the exchange correlation functional. We interpolated the bulk Fermi surface using maximally localized Wannier functions (MLWFs; ref. 40). \n\n# References \n\n38. Martin, J. & Gruehn, R. Zum chemischen Transport von Monophosphiden MP ( $M=\\mathrm{Zr},$ Hf, Nb, Ta, Mo, W) und Diposphiden MP2 $\\mathbf{\\nabla}\\cdot M=\\mathrm{Ti}$ Zr, Hf ). Z. Kristallogr. 182, 180–182 (1988). \n39. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, \n11169–11186 (1996). \n40. Mostofi, A. A. et al. wannier90: A tool for obtaining maximally-localised Wannier functions. Comput. Phys. Commun. 178, 685–699 (2008). " + }, + { + "id": "10.1038_ncomms7962", + "DOI": "10.1038/ncomms7962", + "DOI Link": "http://dx.doi.org/10.1038/ncomms7962", + "Relative Dir Path": "mds/10.1038_ncomms7962", + "Article Title": "Highly compressible 3D periodic graphene aerogel microlattices", + "Authors": "Zhu, C; Han, TYJ; Duoss, EB; Golobic, AM; Kuntz, JD; Spadaccini, CM; Worsley, MA", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Graphene is a two-dimensional material that offers a unique combination of low density, exceptional mechanical properties, large surface area and excellent electrical conductivity. Recent progress has produced bulk 3D assemblies of graphene, such as graphene aerogels, but they possess purely stochastic porous networks, which limit their performance compared with the potential of an engineered architecture. Here we report the fabrication of periodic graphene aerogel microlattices, possessing an engineered architecture via a 3D printing technique known as direct ink writing. The 3D printed graphene aerogels are lightweight, highly conductive and exhibit supercompressibility (up to 90% compressive strain). Moreover, the Young's moduli of the 3D printed graphene aerogels show an order of magnitude improvement over bulk graphene materials with comparable geometric density and possess large surface areas. Adapting the 3D printing technique to graphene aerogels realizes the possibility of fabricating a myriad of complex aerogel architectures for a broad range of applications.", + "Times Cited, WoS Core": 940, + "Times Cited, All Databases": 1021, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000353704700014", + "Markdown": "# Highly compressible 3D periodic graphene aerogel microlattices \n\nCheng Zhu1, T. Yong-Jin Han1, Eric B. Duoss1, Alexandra M. Golobic1, Joshua D. Kuntz1, Christopher M. Spadaccini1 & Marcus A. Worsley1 \n\nGraphene is a two-dimensional material that offers a unique combination of low density, exceptional mechanical properties, large surface area and excellent electrical conductivity. Recent progress has produced bulk 3D assemblies of graphene, such as graphene aerogels, but they possess purely stochastic porous networks, which limit their performance compared with the potential of an engineered architecture. Here we report the fabrication of periodic graphene aerogel microlattices, possessing an engineered architecture via a 3D printing technique known as direct ink writing. The 3D printed graphene aerogels are lightweight, highly conductive and exhibit supercompressibility (up to $90\\%$ compressive strain). Moreover, the Young’s moduli of the 3D printed graphene aerogels show an order of magnitude improvement over bulk graphene materials with comparable geometric density and possess large surface areas. Adapting the 3D printing technique to graphene aerogels realizes the possibility of fabricating a myriad of complex aerogel architectures for a broad range of applications. \n\nraphene is an emerging class of ultrathin carbon membrane material1–3 with high specific surface area4, superior elasticity5, chemical stability3 and high electrical and thermal conductivity6,7. These intrinsic physicochemical properties enable graphene to find widespread applications in nanoelectronics8,9 , sensors10,11, catalysis12,13, composites14,15, energy storage16,17 and biomedical scaffolds18. To further explore various macroscopic applications of graphene materials, an essential prerequisite is controlled large-scale assembly of two-dimensional graphene building blocks and transfer of their inherent properties into three-dimensional (3D) structures. Template-guided methods, such as chemical vapour deposition coatings on metallic foams19 have been reported for the creation of 3D graphene monoliths, but the process is not scalable and the materials obtained from these methods are generally brittle under low compression20. Therefore, template-free approaches are still needed for scalable synthesis of 3D graphene macro-assemblies. Due to their simple and versatile synthesis scheme, and the ability to realize a wide range of pore morphologies, including ultrafine pore sizes $(<100\\mathrm{nm})$ , chemically derived graphene oxide (GO)-based aerogels are the most common 3D graphene found in the literature20–36. Starting from a widely available GO precursor, the main strategy to assemble porous 3D graphene networks is the self-assembly or gelation of the GO suspension via hydrothermal reduction20–22, chemical reduction27–31 or direct crosslinking33,34 of the GO sheets. Although some control over the pore morphology has been demonstrated with ice templating35,36, the architecture of these graphene networks remains largely random, precluding the ability to tailor transport and other mechanical properties of the material for specific applications (for example, separations, flow batteries, pressure sensors and so on) that might benefit from such engineering. Thus the fabrication of 3D graphene materials with tailored macro-architectures for specific applications via a controllable and scalable assembly method remains a significant challenge. \n\nThe functional characteristics of cellular materials are mostly determined by the intrinsic properties of their chemical composition, porosity and cell morphologies37. Several additive manufacturing techniques have been utilized to make highly ordered ultralight cellular materials possessing unique chemical, mechanical and structural properties by manipulation of their structures from the nanometre up to the centimetre scale38. For example, ultralight hollow metallic microlattices were produced using self-propagating photopolymer waveguide prototyping to form a template and subsequently coating the template with nickel–phosphorus via electroless plating39. Another example is the fabrication of ultralight, ultra-stiff octet truss metamaterials by the projection micro-stereolithography method40. However, these methods have limitations in their scaling and material diversity. Recently, an extrusion-based 3D printing technique, known as direct ink writing has also been applied to construct cellular elastomeric architectures41 and lightweight composites42. This technique employs a three-axis motion stage to assemble 3D structures by robotically extruding a continuous ‘ink’ filament through a micronozzle at room temperature in a layer-by-layer scheme43. The primary challenge for this method is to design gel-based viscoelastic ink materials possessing shear thinning behaviour to facilitate flow under pressure and a rapid pseudoplastic to dilatant recovery after deposition resulting in shape retention44,45. Although a number of ceramic, metallic, polymeric and even graphene–polymer composite ink materials43,46,47 have been developed to fabricate various complex 3D structures, there is no example using this technique to create 3D periodic graphene aerogel macroarchitectures. \n\nIn this work, we demonstrate a 3D printing strategy for the fabrication of 3D graphene aerogels with designed macroscopic architectures. Our approach is based on the precise deposition of GO ink filaments on a pre-defined tool path to create architected 3D structures. Two key challenges in this process are developing a printable graphene-based ink and maintaining the intrinsic properties of single graphene sheets (for example, large surface area, mechanical and electrical properties) in the 3D printed structures. To this end, we have developed a new GO-based ink and printing scheme that allows the manufacture of porositytunable hierarchical graphene aerogels with high surface area, excellent electrical conductivity, mechanical stiffness and supercompressibility. \n\nResults Three-dimensional printing of graphene aerogels. The first challenge for this fabrication strategy is to develop printable GO inks, by tailoring the composition and rheology required for reliable flow through fine nozzles, and self-supporting shape integrity after deposition (for example, highly viscous, nonNewtonian fluids). Printable GO ink development is challenging because most GO-based graphene aerogels begin with fairly dilute precursor GO suspensions $(<5\\mathrm{mg}\\mathrm{\\breve{ml}}^{-1}\\mathrm{\\breve{G}O})$ that do not possess the required rheological behaviour for a 3D printable ink as they are low-viscosity $(\\eta)$ Newtonian fluids20,48. Recently, the rheological behaviour of GO dispersions has been investigated to enable further fabrication of GO into complex architectures49. There are reports of higher concentration GO suspensions (for example, $10{\\dot{-}}20\\mathrm{mgml}^{-1}$ GO) that can also make high-quality graphene aerogels30,33. These reports demonstrate gelation of concentrated GO suspensions under basic conditions (for example, addition of ammonium hydroxide) or direct crosslinking using organic sol–gel chemistry (for example, resorcinol– formaldehyde (R–F) solution). As the gelation method can influence the aerogel microstructure34, both methods were applied to the high-concentration GO suspensions we investigated for the GO inks. Figure 1a shows the apparent viscosity of high-concentration GO suspensions as a function of shear rate, revealing that at $20\\mathrm{mg}\\mathrm{ml}^{-1}$ , the GO suspension shows orders of magnitude higher apparent viscosity than reported at lower concentrations48, and that the GO suspension at $20\\mathrm{mg}\\mathrm{ml}^{-1}$ is a shear-thinning non-Newtonian fluid, which is necessary for a printable ink. Further increasing the GO concentration to $40\\mathrm{mg}\\mathrm{ml}^{-1}$ results in another order-ofmagnitude increase in apparent viscosity, which further improves printability. Finally, addition of hydrophilic fumed silica powders to the GO suspensions imparts additional increases in viscosity. Silica filler serves as a removable viscosifier by imparting both shear thinning behaviour and a shear yield stress to the GO suspension to further enhance the printability of the GO inks. Figure 1b compares the pure GO suspensions and representative GO inks storage and loss moduli with varying compositions. Specifically, the pure $20{\\cdot}\\mathrm{mg}\\mathrm{ml}^{-1}\\mathrm{~C~}$ O suspensions without fillers exhibit a plateau value of its elastic modulus $\\left(G^{\\prime}\\right)$ $\\sim1,000\\mathrm{Pa}$ and a yield stress $(\\tau_{y})\\sim40\\mathrm{Pa}$ , respectively. By adding $20\\ \\mathrm{wt\\%}$ silica powders into pure $20\\mathrm{mg}\\mathrm{ml}^{-1}$ GO suspensions, both elastic modulus and yield stress increase by approximately an order of magnitude. Meanwhile, the addition of $10~\\mathrm{wt\\%}$ silica filler increases the elastic modulus and yield stress of $40\\mathrm{mg}\\mathrm{ml}^{-1}$ GO suspensions by over an order magnitude. The magnitudes of these key rheological parameters are in good agreement with those reported for other colloidal inks designed for this 3D filamentary printing technique45. Although the pure $40\\mathrm{-mg}\\mathrm{ml}^{-1}$ GO suspension ink is printable, the silica-filled GO inks were preferred due to their superior rheological properties and facile removal of the silica during post-processing. In addition to these, GO inks exhibit the desired viscoelasticity and they have a long pot life. \n\n![](images/778e8d2af093300674e12d2c33c0c3b6fb37a2738edf7fbacdda11cd989571a3.jpg) \nFigure 1 | Fabrication strategy and GO ink’s rheological properties. Log–log plots of (a) apparent viscosity as a function of shear rate and (b) storage and loss modulus as a function of shear stress of GO inks with and without silica fillers. (c) Schematic of the fabrication process. Following the arrows: fumed silica powders and catalyst (that is, $(N H_{4})_{2}C O_{3}$ or R–F solution) were added into as-prepared aqueous GO suspensions. After mixing, a homogeneous GO ink with designed rheological properties was obtained. The GO ink was extruded through a micronozzle immersed in isooctane to prevent drying during printing. The printed microlattice structure was supercritically dried to remove the liquid. Then, the structure was heated to $1,050^{\\circ}\\mathsf C$ under ${\\sf N}_{2}$ for carbonization. Finally, the silica filler was etched using HF acid. The in-plane centre-to-centre rod spacing is defined as $\\lfloor,$ , and the filament diameter is defined as d. \n\nThe process of 3D printing the GO inks such that a 3D graphene aerogel structure is produced also presents several obstacles. Aerogels are ultralow-density porous solids created by carefully replacing the liquid in the pores of the wet gel with air. To convert the 3D printed GO structure to an aerogel, the GO ink must remain wet through printing and gelation such that the liquid in the GO gel can be removed via supercritical- or freezedrying to avoid gel collapse due to capillary forces. This necessitates printing the GO ink into a bath of liquid that is not only less dense than water but immiscible with our aqueous GO inks. The fabrication scheme for accomplishing this is illustrated in Fig. 1c. An animation of the fabrication scheme used to print the graphene aerogel microlattices can also be seen in Supplementary Movie 1. The GO inks are prepared by combining a GO suspension and silica filler to form a homogenous, highly viscous and thixotropic ink. These GO inks are then loaded into a syringe barrel and extruded through a micronozzle to pattern 3D structures. To prevent the ink from drying in the air, which can clog the tip of the printing apparatus or cause pore collapse in the printed structure, the printing is carried out in an organic solvent bath (isooctane) that is not miscible with the aqueous ink. Finally, the printed structures can be processed according to standard literature methods29,30, followed by etching of the silica filler to obtain the ultimate periodic 3D graphene aerogel microlattices. \n\nTo demonstrate 3D printing of graphene aerogels, we first printed woodpile, ‘simple cubic’-like lattices consisting of multiple orthogonal layers of parallel cylindrical filaments successively printed in a layer-by-layer fashion. These 3D simple cubic lattices are designed with an in-plane centre-to-centre filament spacing $(L)$ of $1\\mathrm{mm}$ and a filament diameter $(d)$ of $0.25\\mathrm{mm}$ , resulting in a spacing-to-diameter ratio $(L/d)$ of 4 (Fig. 1c). By simply changing the filament spacing and diameter, we have the ability to 3D print graphene structures over a wide range of geometric densities. The printed 3D graphene aerogel microlattice shows excellent structural integrity and micro-architecture accuracy (Fig. 2a,b), which is indicative of the high quality of the ink material for this printing process (see Supplementary Movie 2). After the removal of silica fillers (Supplementary Fig. 1a), there are random large pores distributed in graphene aerogels (Fig. 2c,d; Supplementary Fig. 1b). Figure $^{2\\mathrm{c},\\mathrm{d}}$ also shows how the microstructure of the 3D printed graphene aerogels can be tuned by simply modifying the GO ink formulations. Similar to results observed in bulk monolithic graphene aerogels34, changes in the gelation chemistry can lead to significant microstructural changes. In this case, we use either basic solution (for example, $(\\mathrm{NH}_{4})_{2}\\mathrm{CO}_{3})$ to directly crosslink graphene sheets via the functional groups (for example, epoxide and hydroxide) or resorcinol (R) and formaldehyde (F) with sodium carbonate as a catalyst to ‘glue’ the sheets together. The use of organic sol–gel chemistry (R–F solution) to build the GO network led to a more open, less crosslinked network (Fig. 2d) compared with gelation methods based on GO’s native functionality (that is, no R–F) (Fig. 2c). The ability to tune the microstructure, in addition to the macrostructure, is important because it can affect a wide range of properties such as density, conductivity, surface area and, as noted below, mechanical properties. This approach opens new opportunities for the fabrication of graphene-based structures at the macroscale. To further demonstrate the flexibility of this 3D printing technique, we fabricated a series of graphene aerogel microlattices with varying thicknesses and a large area graphene aerogel honeycomb (Fig. $^{2\\mathrm{e,f)}}$ . \n\nPhysical properties of 3D printed graphene aerogels. Modifying the GO suspensions to make suitable inks has the potential to alter the properties of the final aerogel; however, most properties of the 3D printed graphene aerogels were found to meet or exceed those of the bulk material. For example, techniques such as Raman spectroscopy, X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy (EDS) were applied to see how microstructure, graphene layering and degree of GO reduction compare with bulk graphene aerogels. Raman spectra of the 3D printed graphene aerogels (Fig. 3a) all show strong D $\\dot{(1,350\\mathrm{cm}^{-1})},$ and G $(1,\\breve{5}82\\thinspace{\\mathrm{cm}}^{-\\breve{1}},$ ) bands with weak, broad $\\mathrm{\\DeltaD^{\\prime}}$ and $\\ensuremath{\\mathrm{G}^{\\prime}}$ features identical to those previously reported for bulk aerogels29,30, suggesting a similar microstructure and defect density. XRD spectra of 3D printed graphene aerogels (Fig. 3b) are also similar to those of bulk graphene aerogels29,30, showing weak, broad features indicative of single- and few-layer graphene. EDS (Supplementary Fig. 2) also shows that, like the bulk graphene aerogel, the C:O ratio of 3D printed graphene aerogel rises to $>20$ compared with 5 for the native GO, confirming a high level of GO reduction. EDS also confirms that the silica filler has been completely removed from the graphene microlattice. Together, the scanning electron microscopy (SEM), Raman, XRD and EDS show that the 3D printed graphene aerogel is quite similar to the bulk graphene aerogel and is not significantly degraded by the etching or printing process. \n\n![](images/f06ac31a763aa5aa919245abd931aa51b881a4e615a21c75441d639ef0fd7ed7.jpg) \nFigure 2 | Morphology and structure of graphene aerogels. (a) Optical image of a 3D printed graphene aerogel microlattice. SEM images of (b) a 3D printed graphene aerogel microlattice, (c) graphene aerogel without R–F after etching and (d) graphene aerogel with 4 wt% R–F after etching. Optical image of (e) 3D printed graphene aerogel microlattices with varying thickness and (f) a 3D printed graphene aerogel honeycomb. Scale bars, $5\\mathsf{m m}$ (a), $200\\upmu\\mathrm{m}$ (b), $100\\mathsf{n m}$ (c,d), 1 cm (f). \n\nStandard graphene aerogels are also notable for their large surface areas, low densities and high electrical conductivities. These characteristics are also evaluated for the modified formulations that we used to create the inks and are presented in Table 1. Nitrogen porosimetry (Table 1; Supplementary Fig. 3) show that the modified formulations maintain a high surface area $(700-1,100\\mathrm{m}^{2}\\mathrm{g}^{-1})$ and large mesopore volumes $(2{-}4\\cos^{3}\\mathrm{g}^{-1})$ , consistent with the SEM images and comparable to bulk graphene aerogels in the literature29,30. Four-probe and density measurements also show that the modified formulations retain a low density and high conductivity characteristic of standard graphene aerogels. As seen in previous reports29,30, all these properties (surface area, conductivity and density) can be tuned by changing the $\\mathrm{R-F}$ concentration in the initial suspension. The GO concentration also appears to impact the surface area of the aerogel. The slightly lower surface areas at higher GO concentrations likely stem from larger fractions of few-layer graphene due to less efficient exfoliation. \n\nGraphene aerogels are also known to be remarkably stiff and flexible. To quantify the mechanical properties of these aerogels, we conducted in-plane compression tests to measure the compressive stress $(\\sigma)$ as a function of strain (e) for all bulk and printed structures. The compressibility of these graphene aerogels is displayed in Fig. 4. It presents the stress–strain curves of five stepped compression cycles with strain amplitude of 10, 20, 30, 40 and $50\\%$ in sequence. The starting point for each cycle is the same and equal to the initial thickness of the sample, no matter how much unrecoverable compression is in the previous cycle. It is interesting that each succeeding loading curve exactly rises back to the maximum stress–strain point of the preceding cycle and continues the trend of the preceding loading curve in the full range of our measurements, showing a perfect strain memory effect. Figure $^{4\\mathrm{a},\\mathrm{b}}$ shows the stress–strain curves of bulk and printed graphene aerogels using the native functionality of the GO sheets with loading curves that display linear elastic properties from 10 to $50\\%$ strain. From the unloading curves, we can find each compression leads to a degree of permanent residual deformation, and the recoverability of the printed aerogels is slightly higher than that of bulk aerogels. \n\n![](images/8f430531bb8ae38f3c357bd2a7cd4a31c3d26c3c303ca8df478fac56964f7d80.jpg) \nFigure 3 | Raman and XRD spectra of graphene aerogels. (a) Raman and (b) XRD spectra of 3D printed graphene aerogel microlattices made with various ink formulations. Spectra of highly oriented pyrolytic graphite (HOPG) and graphene oxide (GO) powder are included for reference. \n\nIn contrast, bulk and printed graphene aerogels using GO inks with organic sol–gel chemistry to crosslink GO sheets exhibit extraordinary supercompressibility, with full recovery after large strains (Fig. $^{\\mathrm{4c,d}},$ ). As the main difference between the aerogels lies in their microstructure $(\\mathrm{Fig.~}2\\mathrm{c,d})^{34}$ , we propose that the difference in compressive behaviour is linked to their microstructural differences. The loading curves of both bulk and printed aerogels show three distinct regions typically observed in other cellular materials, namely an initial Hookean region at $5\\%<\\varepsilon<10\\%$ , a plateau at $10\\%<\\varepsilon<40\\%$ and a densification regime for $\\varepsilon>40\\%$ with a steep increase in stress. Thus, similar to other resilient cellular materials36,37, hysteresis loops are found in the loading–unloading cycles, which indicate energy dissipation that can be attributed to the buckling of microstructures, the friction and adhesion between branches and the cracks that occur primarily in the first compression for the large dissipation. The initial increase of stress in the range of $\\varepsilon<5\\%$ is attributed to the increase of contact area between the sample and the platen for our compression fixture. The primary deformation in the Hookean region is linear elastic dominated by bending mode deformation. The plateau is mainly attributed to the buckling deformation of the graphene sheets. As the graphene aerogel crosslinked via organic sol–gel chemistry has a more open, less crosslinked microstructure and the graphene sheets are free to bend and buckle under compression, there is substantial recovery when the load is removed. Even after compression to $90\\%$ strain, less than $5\\%$ residual deformation was observed (Supplementary Fig. 4). \n\n
Table 1 | Physical properties of different 3D printed graphene aerogel formulations.
Ink formulationAerogel density (mg cm -3)BET surface area (m²g-)Pore volume (cm3g-1)Conductivity (S m-1)
20 mg ml-1 GO 40 mg ml-1 GO 40 mg ml-1 GO with R-F311,0664.187
60955 7043.8 2.5198
123278
BET, Brunauer-Emmett-Teller; 3D, three-dimensional; GO, graphene oxide; R-F, resorcinol- formaldehyde.
\n\nTo further assess and characterize the stability of the cyclic resilient property of printed graphene aerogels, compression cycling of the graphene aerogel at $50\\%$ strain was conducted (Fig. 5). Energy dissipation is one of the key functions of cellular materials, and our printed graphene elastomers exhibit excellent energy absorption capability. In Fig. $^{5\\mathrm{a},\\mathrm{b}}$ , the energy loss coefficient of printed aerogels decreases from 60 to $30\\%$ in the first three cycles and then remains fairly constant. The maximum stress for each cycle in Fig. 5a also shows a similar trend (Fig. 5b). The electrical resistance of the printed graphene aerogels was also determined as a function of cyclic compression (Fig. 5c). The electrical resistance of the printed aerogels shows only a slight decrease after multiple compression events, confirming the remarkable structural resilience of the graphene aerogel microlattices. \n\nFinally, the effect of macroscopic architectural design on the mechanical properties is also reflected in superior rigidity of the graphene aerogel microlattices compared with bulk aerogels at the same overall geometric density. It has been shown that the stiffness of many conventional cellular solids is significantly diminished as their densities decrease due to quadratic or higher power scaling relationships between Young’s modulus $(E)$ and density $(\\rho)^{37}$ . Figure 5d shows the Young’s modulus as a function of density for our graphene microlattices (printed) and standard graphene aerogels (bulk) compared against other carbon, carbon nanotube and graphene assemblies found in the literature29–31,50–54 as a function of density. The bulk aerogel data are consistent with literature data, while the printed aerogel data are substantially offset from the known curve. The log–log plot in each case demonstrates the expected power-law density dependence of Young’s modulus. In both cases, Young’s modulus was found to scale with density as $E\\propto\\rho^{2.5}$ , consistent with other studies29. The similar values of the exponent $(\\sim2.5)$ indicate both printed and bulk aerogels show the same bendingdominated behaviour under compression. However, the magnitude of $E$ for the graphene microlattices was about one order of magnitude larger than that of most bulk graphene aerogels with same densities. In other words, the printed graphene aerogels can maintain the stiffness values of higherdensity bulk aerogels to much lower densities. This phenomenon is also commonly observed in traditional cellular materials, such as honeycombs, which exhibit stiffness values in certain loading directions that rival higher-density bulk solids37. In the case of the printed aerogels, the printed structures exhibit Young’s moduli that rival bulk aerogel values with nearly twice the density of their printed counterparts. Upon closer inspection, it is revealed that the Young’s modulus of the printed structure is approximately equal to that of the bulk aerogel with the same density as that of the printed aerogel filaments within the lattice. Thus, the improved performance is primarily attributed to the local density in the printed aerogels rather than the overall density, which accounts for the macroscale pores. In other words, the stiffness is controlled by the density of each filament, which is much higher than the geometric density of total microlattice. In fact, the actual geometric density of the printed aerogel is quite consistent with the theoretically expected value for each lattice (Supplementary Fig. 5). These observations show that the introduction of periodic macroscale pores in the 3D printed microlattices can provide additional functionality to the aerogel (for example, lower density, faster mass transport and so on) with negligible impact on the mechanical integrity of structure. Thus, the 3D printed graphene aerogels would benefit technologies such as catalysis, desalination and other filtration/ separation applications that require large surface areas, low density, superior mechanical rigidity and engineered porosity for predictable fluid flow characteristics. \n\n![](images/533c67eaf601d8a92ff99f8f33160cb4d933e030fe97d7f80e4553b2ee9f654c.jpg) \nFigure 4 | Compressive properties of graphene aerogels. Stress–strain curves during loading–unloading cycles in sequence of increasing strain amplitude for (a) bulk graphene aerogel $(31\\mathrm{mg}\\mathsf{c m}^{-3}.$ ) and (b) 3D printed graphene aerogel microlattice $(16\\mathsf{m g c m}^{-3})$ using the GO ink without R–F, (c) bulk graphene aerogel $(123\\mathsf{m g c m}^{-3},$ ) and (d) 3D printed graphene aerogel microlattice $(53\\operatorname*{mg}{\\mathsf{c m}}^{-3})$ using the GO ink with R–F. \n\n![](images/8b30333187dd41127dc605458ec1e20e203faee3781c7fa26f0334ef76ec6078.jpg) \nFigure 5 | Physical properties of graphene aerogels. (a) Compressive stress–strain curves of 10 cycles of loading–unloading. (b) Maximum stress and energy loss coefficient during 10 cycles. (c) Electrical resistance change when repeatedly compressed up to $50\\%$ of strain for 10 cycles. The graphene aerogel microlattice used for cyclic compression and conductivity measurements $(\\mathsf{a}-\\mathsf{c})$ has a geometric density of $53\\mathsf{m g c m}^{-3}$ . (d) The relationships between Young’s modulus and density of bulk and printed graphene aerogels. \n\n# Discussion \n\nWe present a general strategy for fabrication of periodic graphene aerogel microlattices via 3D printing. Key factors for successful 3D printing of aerogels included modifying GO precursor suspension such that it serves as printable ink, and adapting the 3D printing process to prevent premature drying of the printed structure. By addressing these issues, 3D printed aerogel microlattices were produced with properties that met or exceeded those of bulk aerogel materials. The graphene microlattices possess large surface areas, good electrical conductivity, low relative densities and supercompressibility, and are much stiffer than bulk graphene of comparable geometric density. By modifying the microstructure and density of the graphene aerogel through changing the ink formulation, we also showed how mechanical properties of the microlattices can be tuned. As graphene aerogels are currently being explored for a broad range of applications, having a manufacturing method for creating periodic or engineered structures using this novel material will further expand the range of applications where graphene can be utilized. In particular, our strategy makes it possible to explore the properties and applications of graphene in a self-supporting, structurally tunable and 3D macroscopic form. This work presents a versatile method for fabricating a broad class of 3D macroscopic graphene aerogel structures of determined geometries, and could lead to new types of graphene-based electronics, energy storage devices, catalytic scaffolds and separation devices. Furthermore, other functional materials can be readily incorporated into the open void space, offering opportunity to create new graphene-based nanocomposites. Finally, this fabrication scheme could be broadly applied to other aerogel systems enabling 3D printed aerogel structures for the myriad of technologies that require high surface area, low-density materials. \n\n# Methods \n\nGO ink preparation. Raw single-layer GO powder (Cheaptubes) was produced by the Hummer method55 and had lateral dimensions of $300{-}700\\mathrm{nm}$ . GO suspensions were prepared via ultrasonication at concentrations of 20 and $40\\mathrm{{\\dot{mg}m l^{-1}}}$ in water for $24\\mathrm{h}$ in a VWR Scientific Model 57T Aquasonic (sonic power $\\sim90\\mathrm{W}$ , frequency $\\sim40\\mathrm{kHz}$ ). After sonication, the lateral dimensions were in the range of $150\\mathrm{-}400\\mathrm{nm}$ . For GO inks gelled using the native functionality on the GO sheets, ammonium carbonate $((\\mathrm{NH}_{4})_{2}\\mathrm{CO}_{3})$ solution $(0.3\\mathrm{wt\\%})$ ) was used. In a typical synthesis, GO inks are prepared by mixing $6\\mathrm{g}$ of $40\\mathrm{mg}\\mathrm{ml}^{-1}$ GO suspension, $0.343\\mathrm{g}$ $(\\mathrm{NH}_{4})_{2}\\mathrm{CO}_{3}$ solution and $0.7\\mathrm{g}$ fumed silica (EH-5, Cabot), respectively. For GO inks gelled using organic sol–gel chemistry, the sol–gel mixture consisted of an aqueous solution of resorcinol (R), formaldehyde (F) and sodium carbonate catalyst (C). The R:F mole ratio was 1:2, the R:C mole ratio was 200:1 and the resultant R–F concentration was $11~\\mathrm{wt\\%}$ R–F solids. In a typical synthesis, $3.6\\mathrm{g}$ of $40\\mathrm{mg}\\mathrm{ml}^{-1}\\mathrm{GO}$ suspensions, $2\\mathrm{g}$ of R–F solution and $0.7\\mathrm{g}$ of fumed silica are mixed. A planetary centrifugal mixer (Thinky) was used for mixing these samples for $2\\mathrm{min}$ in a $35\\mathrm{-ml}$ container using a custom adaptor. \n\nInk rheology. Rheological properties of the inks were characterized using a stresscontrolled Rheometer (AR 2000ex, TA) with a $40\\mathrm{-mm}$ -flat plate geometry and a gap of $500\\upmu\\mathrm{m}$ . All measurements were preceded by a 1-min conditioning step at a constant shear rate of $1s^{-1}$ , followed by a 10-min rest period to allow the ink structure to reform. A stress sweep from $10^{-2}$ to $10^{3}\\mathrm{Pa}$ at a constant frequency of $1\\mathrm{Hz}$ was conducted to record the storage modulus and loss modulus variations as a function of sweep stress. The yield stress $(\\tau_{y})$ was defined as the stress where storage modulus falls to $90\\%$ of the plateau value. A strain sweep from $10^{-1}$ to $10^{\\frac{\\cdot}{2}}\\thinspace\\mathbf{s}^{-1}$ was also performed to record the apparent viscosity at varying shear rates. \n\n3D printing. The GO ink was housed in a $3\\mathrm{ml}$ syringe barrel (EFD) attached by a luer-lok to a smooth-flow tapered nozzle ( $250\\upmu\\mathrm{m}$ inner diameter, d). An airpowered fluid dispenser (Ultimus V, EFD) provided the appropriate pressure to extrude the ink through the nozzle. The target patterns were printed using a threeaxis positioning stage (ABL 9000, Aerotech The 3D GO structures were printed onto silicon wafers in an isooctane (2,2,4-trimethylpentane) bath, with an initial nozzle height of $0.7d$ to ensure adhesion to the substrate. Three-dimensional periodic microlattices were assembled by patterning an array of parallel (rod-like) filaments in a meanderline-like pattern in the horizontal plane such that the orientation of each successive layer was orthogonal to the previous layer. Threedimensional honeycomb structures were fabricated by stacking hexagonal unit-cell arrays into a lattice and then printed directly upon previous layers. Printed parts were cured in sealed glass vials at $85^{\\circ}\\mathrm{C}.$ After gelation, the wet GO gels were removed from the glass vials and washed in acetone to remove water from the pores. Supercritical $\\mathrm{CO}_{2}$ was used to dry the GO gels, and they were thermally reduced at $1{,}050^{\\circ}\\mathrm{C}$ under nitrogen. Finally, etching in hydrofluoric acid solution was used to remove the silica nanoparticle filler. \n\nCharacterization. The dimension and weight of the samples were determined with a caliper with an accuracy of $0.01\\mathrm{mm}$ and an ultra-micro balance (XP24, Mettler Toledo) with an accuracy of 0.001 mg. The relative density was calculated from the measured mass and volume of each specimen. The compressive characteristics of printed specimens were measured using a universal testing machine (Instron 5943) equipped with a $1{,}000\\mathrm{N}$ load cell at a nominal rate of $5\\upmu\\mathrm{m}\\mathrm{s}^{-1}$ . The Young’s modulus was calculated from the initial slope of the unloading stress–strain curves between 0 and $10\\%$ strain ranges56–58. Simultaneously, the electrical conductivity was measured by a two-electrode method and two metal wires were used as the current collectors. To optimize the electrical contact between conductive copper face sheets and aerogel, each end of the aerogel was carefully affixed to copper sheet with a thin layer of silver paste. The morphology of the printed samples was observed by optical camera and field-emission SEM. SEM and EDS was performed on a JEOL 7401-F at $10\\mathrm{keV}$ $(20\\mathrm{mA})$ in secondary electron imaging mode with a working distance of $2{-}8\\mathrm{mm}$ . Electrical conductivity was measured using the fourprobe method. Textural properties were determined by Brunauer–Emmett–Teller and Barrett–Joyner–Halenda methods using an ASAP 2000 Surface Area Analyzer (Micromeritics Instrument Corporation) via nitrogen porosimetry1. Samples of $\\mathrm{\\sim0.1g}$ were heated to $150^{\\circ}\\mathrm{C}$ under vacuum $(10^{-5}\\mathrm{T_{orr}})$ for at least $24\\mathrm{h}$ to remove all adsorbed species. XRD measurements were performed on a Bruker AXS D8 ADVANCE X-ray diffractometer equipped with a LynxEye 1-dimensional linear Si strip detector. The samples were scanned from 5 to $75^{\\circ}2\\theta$ . The step scan parameters were $0.02^{\\circ}$ steps and $2s$ counting time per step with a $0.499^{\\circ}$ divergence slit and a $0.499^{\\circ}$ antiscatter slit. The X-ray source was Ni-filtered Cu radiation from a sealed tube operated at $40\\mathrm{kV}$ and $40\\mathrm{mA}$ . Phases in the samples were identified by comparison of observed peaks to those in the International Centre for Diffraction Data (ICDD PDF2009) powder diffraction database, and also peaks listed in reference articles. Goniometer alignment was ensured using a Brukersupplied $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ standard. \n\n# References \n\n1. Geim, A. K. & Novoselov, K. S. The rise of graphene. Nature Mater. 6, 183–191 (2007). \n2. Li, D. & Kaner, R. B. Graphene-based materials. Science 320, 1170–1171 (2008). \n3. Geim, A. K. Graphene: status and prospects. Science 324, 1530–1534 (2009). \n4. Peigney, A., Laurent, C., Flahaut, E., Bacsa, R. R. & Rousset, A. Specific surface area of carbon nanotubes and bundles of carbon nanotubes. Carbon 39, 507–514 (2001). \n5. Lee, C., Wei, X., Kysar, J. W. & Hone, J. Measurement of the elastic properties and intrinsic strength of monolayer graphene. Science 321, 385–388 (2008). \n6. Balandin, A. A. et al. Superior thermal conductivity of single-layer graphene. Nano Lett. 8, 902–907 (2008). \n7. Li, X. et al. Highly conducting graphene sheets and Langmuir–Blodgett films. Nature Nanotech. 3, 538–542 (2008). \n8. Eda, G. & Chhowalla, M. Graphene-based composite thin films for electronics. Nano Lett. 9, 814–818 (2009). \n9. Eda, G., Fanchini, G. & Chhowalla, M. Large-area ultrathin films of reduced graphene oxide as a transparent and flexible electronic material. Nature Nanotech. 3, 270–274 (2008). \n10. Schedin, F. et al. Detection of individual gas molecules adsorbed on graphene. Nature Mater. 6, 652–655 (2007). \n11. Shao, Y. et al. Graphene based electrochemical sensors and biosensors: a review. Electroanalysis 22, 1027–1036 (2010). \n12. Machado, B. F. & Serp, P. Graphene-based materials for catalysis. Catal. Sci. Technol. 2, 54–75 (2012). \n13. Sutter, P. W., Flege, J.-I. & Sutter, E. A. Epitaxial graphene on ruthenium. Nature Mater. 7, 406–411 (2008). \n14. Ramanathan, T. et al. Functionalized graphene sheets for polymer nanocomposites. Nature Nanotech. 3, 327–331 (2008). \n15. Vickery, J. L., Patil, A. J. & Mann, S. Fabrication of graphene-polymer nanocomposites with higher-order three-dimensional architectures. Adv. Mater. 21, 2180–2184 (2009). \n16. Wang, X., Zhi, L. & Mu¨llen, K. Transparent, conductive graphene electrodes for dye-sensitized solar cells. Nano Lett. 8, 323–327 (2008). \n17. Yoo, E. et al. Large reversible Li storage of graphene nanosheet families for use in rechargeable lithium ion batteries. Nano Lett. 8, 2277–2282 (2008). \n18. Menaa, F., Abdelghani, A. & Menaa, B. Graphene nanomaterials as biocompatible and conductive scaffolds for stem cells: impact for tissue engineering and regenerative medicine. J. Tissue Eng. Regen. Med. doi: 10.1002/term.1910 (2014). \n19. Chen, Z. et al. Three-dimensional flexible and conductive interconnected graphene networks grown by chemical vapor deposition. Nature Mater. 10, 424–428 (2011). \n20. Xu, Y., Sheng, K., Li, C. & Shi, G. Self-assembled graphene hydrogel via a onestep hydrothermal process. ACS Nano 4, 4324 (2010). \n21. Bi, H. et al. Low temperature casting of graphene with high compressive strength. Adv. Mater. 24, 5124–5129 (2012). \n22. Zhao, J., Ren, W. & Cheng, H.-M. Graphene sponge for efficient and repeatable adsorption and desorption of water contaminations. J. Mater. Chem. 22, 20197–20202 (2012). \n23. Bai, H., Li, C., Wang, X. & Shi, G. A pH-sensitive graphene oxide composite hydrogel. Chem. Commun. 46, 2376–2378 (2010). \n24. Lin, Y., Ehlert, G. J., Bukowsky, C. & Sodano, H. A. Superhydrophobic functionalized graphene aerogels. ACS Appl. Mater. Interfaces 3, 2200–2203 (2011). \n25. Han, Z. et al. Ammonia solution strengthened three-dimensional macro-porous graphene aerogel. Nanoscale 5, 5462–5467 (2013). \n26. Cong, H. P., Ren, X. C., Wang, P. & Yu, S. H. Macroscopic multifunctional graphene-based hydrogels and aerogels by a metal ion induced self-assembly process. ACS Nano 6, 2693–2703 (2012). \n27. Chen, W. & Yan, L. In situ self-assembly of mild chemical reduction graphene for three-dimensional architectures. Nanoscale 3, 3132–3137 (2011). \n28. Sun, H. Y., Xu, Z. & Gao, C. Multifunctional, ultra-flyweight, synergistically assembled carbon aerogels. Adv. Mater. 25, 2554–2560 (2013). \n29. Worsley, M. A. et al. Toward macroscale, isotropic carbons with graphenesheet-like electrical and mechanical properties. Adv. Funct. Mater. 24, 4259–4264 (2014). \n30. Worsley, M. A. et al. Mechanically robust 3D graphene macroassembly with high surface area. Chem. Commun. 48, 8428–8430 (2012). \n31. Zhang, X. et al. Mechanically strong and highly conductive graphene aerogel and its use as electrodes for electrochemical power sources. J. Mater. Chem. 21, 6494–6497 (2011). \n32. Bai, H., Li, C., Wang, X. & Shi, G. On the gelation of graphene oxide. J. Phys. Chem. C. 115, 5545–5551 (2011). \n33. Worsley, M. A. et al. Synthesis of graphene aerogel with high electrical conductivity. J. Am. Chem. Soc. 132, 14067–14069 (2010). \n34. Worsley, M. A. et al. High surface area, sp2-cross-linked three-dimensional graphene monoliths. J. Phys. Chem. Lett. 2, 921–925 (2011). \n35. Barg, S. et al. Mesoscale assembly of chemically modified graphene into complex cellular networks. Nat. Commun. 5, 4328 (2014). \n36. Qiu, L., Liu, J. Z., Chang, S. L., Wu, Y. & Li, D. Biomimetic superelastic graphene-based cellular monoliths. Nat. Commun. 3, 1241 (2012). \n37. Gibson, L. J. & Ashby, M. F. Cellular Solids: Structure and Properties (Cambridge Univ. Press, 1999). \n38. Colombo, P. & Degischer, H. Highly porous metals and ceramics. Mater. Sci. Technol. 26, 1145–1158 (2010). \n39. Schaedler, T. et al. Ultralight metallic microlattices. Science 334, 962–965 (2011). \n40. Zheng, X. et al. Ultralight, ultrastiff mechanical metamaterials. Science 344, 1373–1377 (2014). \n41. Duoss, E. B. et al. Three-dimensional printing of elastomeric, cellular architectures with negative stiffness. Adv. Funct. Mater. 24, 4905–4913 (2014). \n42. Compton, B. G. & Lewis, J. A. 3D-printing of lightweight cellular composites. Adv. Mater. 26, 5930–5935 (2014). \n43. Lewis, J. A. Direct ink writing of 3D functional materials. Adv. Funct. Mater. 16, 2193–2204 (2006). \n44. Smay, J. E., Gratson, G. M., Shepherd, R. F., Cesarano, J. I. I. I. & Lewis, J. A. Directed colloidal assembly of 3D periodic structures. Adv. Mater. 14, 1279–1283 (2002). \n45. Zhu, C. & Smay, J. E. Thixotropic rheology of concentrated alumina colloidal gels for solid freeform fabrication. J. Rheol. 55, 655–672 (2011). \n46. Lewis, J. A. & Smay, J. E. in Cellular Ceramics: Structure, Manufacturing, Properties and Applications. (eds Scheffler, M. & Colombo, P.) 87–100 (WileyVCH, 2006). \n47. Garcı´a-Tun˜on, E. et al. Printing in three dimensions with graphene. Adv. Mater. 27, 1688–1693 (2015). \n48. Le, L. T., Ervin, M. H., Qiu, H., Fuchs, B. E. & Lee, W. Y. Graphene supercapacitor electrodes fabricated by inkjet printing and thermal reduction of graphene oxide. Electrochem. Commun. 13, 355–358 (2011). \n49. Naficy, S. et al. Graphene oxide dispersions: tuning rheology to enable fabrication. Mater. Horiz. 1, 326–331 (2014). \n50. Pekala, R., Alviso, C. & LeMay, J. Organic aerogels: microstructural dependence of mechanical properties in compression. J. Non-Cryst. Solids 125, 67–75 (1990). \n51. Tang, Z. H., Shen, S. L., Zhuang, J. & Wang, X. Noble-metal-promoted threedimensional macroassembly of single-layered graphene oxide. Angew. Chem. Int. Ed. 49, 4603–4607 (2010). \n52. Worsley, M. A., Kucheyev, S. O., Satcher, Jr. J. H., Hamza, A. V. & Baumann, T. F. Mechanically robust and electrically conductive carbon nanotube foams. Appl. Phys. Lett. 94, 073115 (2009). \n53. Kim, K. H., Oh, Y. & Islam, M. Graphene coating makes carbon nanotube aerogels superelastic and resistant to fatigue. Nature Nanotech. 7, 562–566 (2012). \n54. Si, Y., Yu, J., Tang, X., Ge, J. & Ding, B. Ultralight nanofibre-assembled cellular aerogels with superelasticity and multifunctionality. Nat. Commun. 5, 5802 (2014). \n55. Hummers, Jr. W. S. & Offeman, R. E. Preparation of graphitic oxide. J. Am. Chem. Soc. 80, 1339–1339 (1958). \n56. Kan, Q., Yan, W., Kang, G. & Sun, Q. Oliver-Pharr indentation method in determining elastic moduli of shape memory alloys—a phase transformable material. J. Mech. Phys. Solids 61, 2015–2033 (2013). \n57. Oliver, W. C. & Pharr, G. M. An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments. J. Mater. Res. 7, 1564–1583 (1992). \n58. Oliver, W. C. & Pharr, G. M. Measurement of hardness and elastic modulus by instrumented indentation: Advances in understanding and refinements to methodology. J. Mater. Res. 19, 3–20 (2004). \n\n# Acknowledgements \n\nThis work was supported by Lawrence Livermore National Laboratory under the auspices of the US Department of Energy under Contract DE-AC52-07NA27344, through LDRD award 14-SI-004 and 13-LW-099. We thank Tim Ford for optical image acquisition. \n\n# Author contributions \n\nC.Z., E.B.D., J.D.K., C.M.S. and M.A.W. conceived and designed experiments. C.Z., M.A.W., T.Y.-J.H. and A.M.G. prepared samples. M.A.W. and C.Z. were involved in electrical analysis. M.A.W. performed SEM, Raman, XRD, EDS and surface area analysis. C.Z. performed rheological and mechanical experiments. M.A.W., C.Z., E.B.D. and C.M.S. were mainly responsible for preparing the manuscript with further inputs from other authors. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Zhu, C. et al. Highly compressible 3D periodic graphene aerogel microlattices. Nat. Commun. 6:6962 doi: 10.1038/ncomms7962 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms9563", + "DOI": "10.1038/ncomms9563", + "DOI Link": "http://dx.doi.org/10.1038/ncomms9563", + "Relative Dir Path": "mds/10.1038_ncomms9563", + "Article Title": "Liquid exfoliation of solvent-stabilized few-layer black phosphorus for applications beyond electronics", + "Authors": "Hanlon, D; Backes, C; Doherty, E; Cucinotta, CS; Berner, NC; Boland, C; Lee, K; Harvey, A; Lynch, P; Gholamvand, Z; Zhang, SF; Wang, KP; Moynihan, G; Pokle, A; Ramasse, QM; McEvoy, N; Blau, WJ; Wang, J; Abellan, G; Hauke, F; Hirsch, A; Sanvito, S; O'Regan, DD; Duesberg, GS; Nicolosi, V; Coleman, JN", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Few-layer black phosphorus (BP) is a new two-dimensional material which is of great interest for applications, mainly in electronics. However, its lack of environmental stability severely limits its synthesis and processing. Here we demonstrate that high-quality, few-layer BP nullosheets, with controllable size and observable photoluminescence, can be produced in large quantities by liquid phase exfoliation under ambient conditions in solvents such as N-cyclohexyl-2-pyrrolidone (CHP). nullosheets are surprisingly stable in CHP, probably due to the solvation shell protecting the nullosheets from reacting with water or oxygen. Experiments, supported by simulations, show reactions to occur only at the nullosheet edge, with the rate and extent of the reaction dependent on the water/oxygen content. We demonstrate that liquid-exfoliated BP nullosheets are potentially useful in a range of applications from ultrafast saturable absorbers to gas sensors to fillers for composite reinforcement.", + "Times Cited, WoS Core": 954, + "Times Cited, All Databases": 1016, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000364932600010", + "Markdown": "# Liquid exfoliation of solvent-stabilized few-layer black phosphorus for applications beyond electronics \n\nDamien Hanlon1,2,\\*, Claudia Backes1,2,\\*, Evie Doherty1,2,3, Clotilde S. Cucinotta1,2, Nina C. Berner1,3, Conor Boland1,2, Kangho Lee1,3, Andrew Harvey1,2, Peter Lynch1,2, Zahra Gholamvand1,2, Saifeng Zhang4, Kangpeng Wang1,2,4, Glenn Moynihan1,2, Anuj Pokle1,2,3, Quentin M. Ramasse5, Niall McEvoy1,3, Werner J. Blau1,2, Jun Wang4, Gonzalo Abellan6, Frank Hauke6, Andreas Hirsch6, Stefano Sanvito1,2, David D. O’Regan1,2, Georg S. Duesberg1,3, Valeria Nicolosi1,2,3 & Jonathan N. Coleman1,2 \n\nFew-layer black phosphorus (BP) is a new two-dimensional material which is of great interest for applications, mainly in electronics. However, its lack of environmental stability severely limits its synthesis and processing. Here we demonstrate that high-quality, few-layer BP nanosheets, with controllable size and observable photoluminescence, can be produced in large quantities by liquid phase exfoliation under ambient conditions in solvents such as N-cyclohexyl-2-pyrrolidone (CHP). Nanosheets are surprisingly stable in CHP, probably due to the solvation shell protecting the nanosheets from reacting with water or oxygen. Experiments, supported by simulations, show reactions to occur only at the nanosheet edge, with the rate and extent of the reaction dependent on the water/oxygen content. We demonstrate that liquid-exfoliated BP nanosheets are potentially useful in a range of applications from ultrafast saturable absorbers to gas sensors to fillers for composite reinforcement. \n\nver the last few years, the study of two-dimensional (2D) materials1–6 such as graphene, BN and $\\ensuremath{\\mathrm{MoS}}_{2}$ have become one of the most exciting areas of nano-science. However, in the past year a new 2D material has been generating considerable excitement in the research community7. Phosphorene consists of atomically thin, 2D nanosheets of black phosphorus (BP). In BP, the monolayers stack together via van der Waals interactions to form layered crystals in much the same way as graphene stacks together to form graphite. Recently, it was shown that BP can be exfoliated by mechanical cleavage to form mono- and few-layer phosphorene, which we refer to as $\\mathrm{FL-BP^{8-12}}$ . This new material has a direct bandgap in mono-, few-layer and bulk forms, which varies with nanosheet thickness from $\\sim1.5\\mathrm{eV}$ for monolayer phosphorene to $\\sim0.3\\mathrm{eV}$ for bulk $\\mathrm{BP}^{8,13,14}$ . This is in contrast to graphene1 which has no bandgap and materials such as $\\begin{array}{r}{\\mathbf{MoS}_{2}.}\\end{array}$ , which display direct bandgaps only in the monolayer $\\mathrm{form}^{6}$ . As a result, BP is extremely attractive both for electronics and optoelectronics and has therefore been extensively studied in applications such as transistors7,12,15, photodetectors15,16 and solar cells9. \n\nIn addition, like other 2D materials, it is probable that BP has the potential to perform in a range of applications beyond (opto)electronics. Indeed, BP has already been fabricated into electrodes in lithium ion batteries17. Furthermore, theory predicts that FL-BP shows potential for use in gas sensors18 and thermoelectrics19. For most applications, it will be necessary to produce FL-BP in much larger quantities than can be achieved by mechanical exfoliation. One way to prepare nanosheets in large quantities is by liquid phase exfoliation $(\\dot{\\mathrm{LPE}})^{20,21}$ . This technique involves the sonication22,23 or shearing24,25 of layered crystals in appropriate liquids and has previously been applied to graphene and boron nitride, as well as a range of other 2D materials21–23,26–28. \n\nWhile phosphorene nanosheets have very recently been produced by liquid exfoliation29–31, this method remains problematic, largely because BP is known to be unstable7,8,32, degrading via reactions with water and oxygen. For this method to be useful, ways must be found to stabilize liquid-exfoliated FLBP nanosheets against oxidation. It is known that BP can be protected from reacting with environmental species by encapsulation, suggesting a possible way forward7,24. We hypothesized that LPE of BP may be practical if the solvent is carefully chosen to minimize oxidation of the exfoliated nanosheets in the liquid phase due to the solvation shell acting as a barrier to prevent oxidative species reaching the nanosheet surface. \n\nIf this could be achieved it would yield numerous advantages. LPE is a powerful technique to produce nanosheets in large quantities. In addition, the nanosheets are produced directly in the liquid phase and are thus inherently processable and can be easily formed into composites, coatings or films21, facilitating their use in a range of applications. Furthermore, size-control can be achieved by centrifugation, enabling processing for both applications and fundamental studies. For example, studying the oxidation of BP nanosheets of varying sizes would give insight into whether the degradation mechanism is associated with nanosheet edges or the basal plane. However, most importantly, protection of the nanosheets by an appropriate solvent would allow large-scale production in ambient conditions, dramatically simplifying future development of this material. \n\nIn this work, we demonstrate that BP can be exfoliated to give large quantities of FL-BP nanosheets by sonication in solvents such as $N\\mathrm{.}$ -cyclohexyl-2-pyrrolidone (CHP), even in ambient conditions. We show that these nanosheets can be readily sizeselected by controlled centrifugation. Such dispersions show direct gap photoluminescence (PL) with PL energy, width and relative quantum yield scaling strongly with layer number. The BP nanosheets are relatively stable in CHP, but degrade rapidly once water $/\\mathrm{O}_{2}$ is added. The reaction occurs predominantly at nanosheet edges, presumably following a different reaction pathway than previously observed32. Finally we demonstrate that liquid-exfoliated BP nanosheets can be used in applications beyond electronics. We show that dispersions of FL-BP have impressive nonlinear optical properties allowing them to be used in optical switching applications. In addition, the nanosheets can be incorporated into polymer matrices resulting in reinforced composites and are highly potent gas sensors. \n\n# Results \n\nExfoliation and basic characterization. To produce large quantities of BP nanosheets (see Fig. 1a for structure), we use $\\mathrm{LPE}^{22,23}$ . This technique is often carried out in amide solvents such as CHP or $N$ -methyl-2-pyrrolidone (NMP), although isopropanol (IPA) has proven useful in some cases22. Sonication of ground BP crystals (see Fig. 1b for scanning electron microscopic (SEM) image) in CHP yields a brown dispersion (Fig. 1c). In the simplest case, we remove unexfoliated material by centrifugation at $1{,}000\\mathrm{r.p.m}$ . $(106g)$ for $180\\mathrm{min}$ to yield a stable dispersion which we refer to as the standard sample (std-BP, see Supplementary Fig. 1 for process optimization). \n\nThe successful exfoliation of BP in CHP was confirmed by transmission electron microscopy (TEM) of nanosheets on holey carbon grids (TEM, Fig. 1d–f and Supplementary Fig. 2). These images show electron-transparent nanosheets with lateral dimensions $L\\sim1\\upmu\\mathrm{m}$ . As shown by scanning TEM (STEM) and highangle annular dark field (HAADF) STEM imaging, the lattice appears intact over wide regions (Fig. 1g,h). This suggests that, as with other 2D materials, BP can be exfoliated in liquids without the introduction of defects21–24,33. N.B. we used FL-BP exfoliated in IPA for STEM and HAADF, due to difficulties in completely removing the CHP. However, the intact lattice was also observed from the std-BP in CHP (Supplementary Fig. 3). To assess the lateral dimensions of the std-BP, we performed statistical TEM analysis, finding a bimodal size distribution with modes associated with $L\\sim100\\mathrm{nm}$ and $L\\sim3\\upmu\\mathrm{m}$ (Fig. 1i). We note that the larger nanosheets are considerably bigger than is typically observed for other 2D materials (for example, $L<1\\upmu\\mathrm{m})^{2\\dot{2},\\dot{2}6,33,\\dot{3}4}$ . \n\nTo further characterize the std-BP dispersion, we measured the extinction coefficient, e, as shown in Fig. 1j. This parameter is defined via the optical transmittance; $T=10^{'-\\varepsilon C l}$ , where $l$ is the cell length and $C$ is the nanosheet concentration (measured by filtration and weighing). The extinction coefficient includes contributions from both absorbance (a) and scattering (s)33,35, which can be isolated using an integrating sphere and are shown in Fig. 1j. Note that coefficients of extinction, absorbance and scattering are related by $\\varepsilon(\\lambda)=\\alpha(\\lambda)+\\sigma(\\lambda)^{33,35}$ . Because of size-dependent scattering contributions, the extinction coefficient cannot be used to accurately measure nanosheet concentration of varying sizes $^{33-35}$ . Instead, we can use the measured absorbance coefficient $(\\alpha(\\lambda=465\\mathrm{nm})=15\\mathrm{lg}^{-1}\\mathrm{cm}^{-1})$ to give the concentration of all subsequent FL-BP dispersions. For example, Fig. 1k shows the BP concentration measured this way to scale with the sonication time as $C\\propto t^{0.4}$ , similar to previous observations for graphene exfoliation24,36. Concentrations as high as $\\sim1\\mathrm{gl}^{-1}$ can easily be realized. \n\nTo further confirm the structural integrity of the FL-BP, the dispersion was filtered onto alumina membranes and subjected to Raman and X-ray photoelectron spectroscopy (XPS). SEM confirmed the homogeneity of the film (Fig. 1l inset). The Raman spectrum (Fig. 1l) shows the characteristic $\\mathrm{A}_{\\mathrm{g}}^{1},\\mathrm{B}_{2\\mathrm{g}}$ and $\\mathrm{A_{g}^{2}}$ phonons of $\\yen123,456$ . The P2p XPS core-level spectra (Fig. 1m) show the expected contributions from $\\mathrm{P}2\\mathrm{p}_{1/2}$ and $\\mathrm{P}2\\mathrm{p}_{3/2}$ components. Contributions from $\\mathrm{P}_{x}\\mathrm{O}_{y}$ species, presumably as a result of partial degradation (discussed below) are minor $(<15\\%)$ . \n\n![](images/63de164bc1410e9f325974f0075138ea220052e5e47f27d2e0d72251fe96e691.jpg) \nFigure 1 | Basic characterization of exfoliated black phosphorous. (a) Structure of black phosphorus (BP). (b) SEM image of a layered BP crystal (scale bar, $100\\upmu\\mathrm{m})$ . (c) Photograph of a dispersion of exfoliated FL-BP in CHP. (d–f) Representative low-resolution transmission electron microscopy (TEM) images of FL-BP exfoliated in $N_{\\l}$ -cyclohexyl-2-pyrrolidone (CHP) (scale bars in d–f: 500, 100 and $500\\mathsf{n m}.$ ). $\\mathbf{\\sigma}(\\mathbf{g})$ Bright-field scanning transmission TEM (STEM) image and $\\mathbf{\\eta}(\\mathbf{h})$ Butterworth-filtered high-angle annular dark field (HAADF) STEM image of FL-BP (exfoliated in isopropanol) showing the intact lattice (scale bars in $\\pmb{\\mathscr{g}}$ and h, 2 and $1\\mathsf{n m}\\dot{}$ ). (i) Nanosheet length histogram of the exfoliated FL-BP obtained from TEM (sample size $=239$ ). (j) Extinction, absorbance, scattering coefficient spectra of FL-BP in CHP. $(\\pmb{\\k})$ Concentration of FL-BP as a function of sonication time. The dashed line shows power law behaviour with exponent 0.4. (l) Raman spectrum (mean of 100 spectra, excitation $633\\mathsf{n m},$ ) of a filtered dispersion. Inset: scanning electron microscopic image of thin film (scale bar, $2\\upmu\\mathrm{m})$ . $(\\mathbf{m})$ X-ray photoelectron spectroscopy P core-level region. \n\nWe can obtain information about the nanosheet thickness using statistical atomic force microscopy (AFM) analysis (images Fig. 2a–c and Supplementary Fig. 4). To overcome the problems associated with deposition of nanosheets onto substrates from high-boiling point solvents, the std-BP in CHP was transferred to IPA prior to drop casting the samples (see Methods). Apparent AFM heights from liquid-exfoliated nanomaterials are usually overestimated due to residual solvent24,33,37, as well as contributions from effects such as capillary forces and adhesion38,39. To overcome these problems and to convert the apparent measured AFM thickness to the number of layers, we have applied a similar approach to that reported for graphene and $\\ensuremath{\\mathrm{MoS}}_{2}$ (refs 26,27). This involves AFM analysis of incompletely exfoliated nanosheets (Fig. 2d inset), measuring the height of the steps between terraces (Fig. 2d and Supplementary Fig. 5). By plotting the measured step heights in ascending order (Fig. 2e), groups of steps with similar apparent heights appear. It is clear that the apparent step height is always a multiple of $\\sim2\\mathrm{nm}$ , a value which we associate with the apparent monolayer height24,33. By plotting the mean apparent height associated with each group in ascending order (Fig. 5e inset), we find the apparent monolayer thickness to be $2.06\\pm0.18\\mathrm{nm}$ even though the real thickness is $\\sim0.5\\mathrm{-}0.7\\mathrm{nm}$ . We can use this information to convert the measured apparent AFM heights into number of layers, $N.$ . We then determine the mean number of layers of stdBP to be $=9.4\\pm1.3$ (see Supplementary Fig. 6 for the impact of uncertainty in apparent monolayer height). Shown in Fig. 2f is a plot of $N$ versus nanosheet area for std-BP, demonstrating a rough correlation between flake thickness and area: $N\\propto{\\sqrt{A}}$ , as previously observed for exfoliated $\\mathrm{MoO}_{3}$ and GaS nan/osheffieffiffits26,40. The nanosheets are reasonably thin: $\\sim70\\%$ of the observed nanosheets have $N{\\le}10$ (Fig. 2g). \n\nTo gain further insights into the spectroscopic properties of our LPE FL-BP, we have selected a sample area with nanosheets of varying sizes and thicknesses by AFM (Fig. 2h) and relocated the same area under a Raman microscope (Supplementary Fig. 7). A spatial Raman map $\\mathrm{(A_{g}^{1}}$ intensity, excitation wavelength $633\\mathrm{nm},$ ) of the region is shown in Fig. 2i. Single spectra (normalized to the $\\mathrm{A_{g}^{1}}$ mode) extracted at the positions indicated in the Figure are displayed in Fig. 2j. These roughly correspond to the nanosheets circled in Fig. 2i. It has been shown that the intensity ratio of the $\\mathrm{A_{g}^{1}/A_{g}^{2}}$ phonon sensitively depends on sample degradation as a result of oxidation32. We therefore analysed the $\\mathrm{\\tilde{A_{g}^{1}/A_{g}^{2}}}$ intensity ratio of 120 individual Raman spectra after baseline subtraction. The resultant intensity ratio histogram is plotted in Fig. 2k. None of the spectra showed $\\mathrm{A_{g}^{1}/A_{g}^{2}}<0.6$ , confirming the basal planes to be unoxidized32. Analysis of data collected using $532\\mathrm{nm}$ excitation gives very similar results (Supplementary Fig. 8). Furthermore, oxidation typically gives rise to a broad component under the $\\mathbf{B}_{2\\mathbf{g}}$ and $\\mathrm{A}_{\\mathrm{g}}^{2}\\ \\mathrm{\\modes}^{32}$ which is not observed in our samples, further confirming the structural integrity. \n\nSize selection. A great advantage of liquid exfoliation is the ability to perform size-selection24,33,41. This is important, as some applications (for example, mechanical reinforcement)42 require large nanosheets, while others (for example, catalysis)43 benefit from small nanosheets. To demonstrate that established sizeselection techniques can be applied to liquid-exfoliated FL-BP, we have performed controlled centrifugation to obtain dispersions with varying size distributions (Methods and Supplementary Figs 9-10). Nanosheet length histograms are displayed in Fig. 3a–c (and Supplementary Fig. 11) for three representative size distributions with mean $L$ ranging from 190 to $620\\mathrm{nm}$ . Note that, for much of the remainder of the study, in addition of the std-BP, we have studied dispersions containing small (S-BP, $=130\\mathrm{nm}$ ) and large (L-BP, $=2.3\\upmu\\mathrm{m},$ ) to gain insights into size effects (see Supplementary Methods and Supplementary Figs 10 and 12). \n\nWe have also analysed the ultraviolet–visible optical response of dispersions of nanosheets of varying size. For each sample, we have measured the optical extinction spectra as shown in Fig. 3d. \n\n![](images/944906174957ffc34f3112e9d1499f5de6af0b6c80bf7512dac52736cd048107.jpg) \nFigure 2 | Characterization of individual nanosheets. (a–c) Representative atomic force microscopic (AFM) images (scale bars in a, b and c: are 500, 200 and $1000\\mathsf{n m},$ . (d) Height profile of the nanosheet in the inset along the line showing clearly resolvable steps, each consisting of multiple monolayers (scale bar, $500\\mathsf{n m},$ . (e) Heights of $>70$ steps of deposited FL-BP nanosheets in ascending order. The step height clustered in groups and is always found to be a multiple of $\\sim2\\mathsf{n m}$ , which is the apparent height of one monolayer. The mean height for each group (the error is the sum of the mean step height error and the s.d. in step height within a given group) is plotted in ascending order in the inset with the slope giving a mean monolayer step height of $2.06\\pm0.18\\mathrm{nm}$ . (f) Plot of number of layers per nanosheet (obtained by dividing the apparent height by the step height) as a function of flake area determined from AFM. The dashed line indicates $N\\propto\\sqrt{A}$ behaviour. $\\mathbf{\\sigma}(\\mathbf{g})$ Histogram of number of monolayers per nanosheet (sample size $=126\\dot{.}$ ). The mean number of layers is determined as $9.4\\pm1.3\\mathsf{n m}$ (where the error is due to the uncertainty in the step height analysis and the s.e. of the distribution). (h,i) Large area AFM image (h, scale bar, $1\\upmu\\mathrm{m})$ and Raman ${\\mathsf{A}}_{\\mathrm{~g~}}^{1}$ intensity map (i, excitation wavelength $633\\mathsf{n m})$ of the same sample region. (j) Raman spectra (normalized to ${\\sf A}_{\\mathrm{g}}^{2\\cdot}$ ) of the nanosheets indicated in h and i (the numbers labelling the spectra in j correspond to the nanosheets marked by numbers in h and i). (k) Histogram of the intensity ratio of the $\\mathsf{A}_{\\mathrm{g}}^{1}/\\mathsf{A}_{\\mathrm{g}}^{2}$ modes obtained from the analysis of 120 baseline-corrected spectra acquired over an area of $25\\times25\\upmu\\mathrm{m}^{2}$ (sample size $=120$ ) The absence of spectra with an intensity ratio $<0.6$ strongly suggests that no basal plane oxidation has occurred32. \n\nThe absorbance and scattering spectra of the size-selected FL-BP dispersions are also shown in Fig. 3e,f. Very clear spectral changes as a function of size can be seen in all spectra. Such changes are primarily due to the fact that each sample contains a different distribution of nanosheet thicknesses, each of which contributes a significantly different component to the measured spectrum10. In addition, the effect of edges may also contribute to the sizedependent changes in spectral shape33,44. The scattering spectra shown in Fig. 3f also vary strongly with nanosheet length. We have characterized this in more detail in Supplementary Fig. 13, using this data to generate a metric to extract nanosheet length from scattering spectra. \n\nPhotoluminescence. A number of publications have demonstrated PL from mechanically exfoliated BP nanosheets with one to five layers13,45,46. To investigate the possibility of PL from liquid-exfoliated FL-BP, we prepared dispersions by performing the sonication under inert gas conditions to avoid any partial oxidation of the BP. However, we note that the sample produced using standard centrifugation was very similar to our std-BP exfoliated under ambient conditions (see Supplementary Figs $14-$ 19 for more information). Prior to the PL measurement, additional centrifugation steps were performed (see Methods) to further remove large and thick nanosheets. Shown in Fig. 4a,b are PL emission–excitation contour maps measured for an FL-BP dispersion in CHP. Very clear emission lines can be seen at $\\sim600$ and $\\sim900\\mathrm{nm}$ with weaker features appearing at $\\sim1,150,\\sim1,260$ and $\\sim1,325\\mathrm{nm}$ . We associate these features with PL from 1L to 5L BP, respectively. Plotted in Fig. 4c is a PL line spectrum, excited at $510\\mathrm{nm}$ with the measured extinction spectrum for comparison. We have fitted this spectrum to five Gaussian (due to inhomogeneous broadening) lines in Fig. 4d, representing \n\n1-, 2-, 3- 4- and 5-layer nanosheets. In agreement with previous results13, we see strong layer-number-dependence of both position and width of the fit components, reflecting the changes in the band structure of exfoliated $\\mathrm{\\dot{BP}}^{8,13,14}$ . The PL intensity also depends strongly on nanosheet thickness. To separate out the effects of thickness-dependent internal PL quantum yield (PLQY) and the population of nanosheets of a given thickness, we performed AFM analysis on this sample (inset of Fig. $4\\mathrm{g}$ and Supplementary Fig. 16). From such images, we measured nanosheet layer number and area (estimated as length $\\times$ width) for $\\sim300$ nanosheets with the layer-number distribution shown in Fig. 4g. We then calculate the relative PLQY by dividing the integrated PL area for each layer number by the volume fraction of nanosheets of that thickness (approximately equivalent to PL/ absorbance for each layer number, Fig. 4h, see Supplementary Table 1). As observed previously13, we find the PLQY to be extremely sensitive to nanosheet thickness varying by 4 orders of magnitude from one to five layers. This effect13 is due to the thickness-dependent band structure of BP, as the internal PLQY (and width) is governed by the density of states distribution for electrons/holes, which depends on the number of band maxima and valleys. \n\nDegradation. It has previously been shown that exfoliated BP degrades in the presence of water and oxygen, greatly limiting its application potential7,8,12,32. However, this may actually be less of a problem for liquid exfoliation as the solvation shell may protect the nanosheets from reacting with oxygen or water. To test this, we have monitored the temporal stability of liquid-dispersed BP by tracking the absorbance, $\\overset{\\cdot}{A}(\\lambda=465\\mathrm{nm})$ , of std-BP, S-BP and L-BP as a function of time $\\scriptstyle\\cdot A=\\alpha C l,$ Fig. 5a, Supplementary Fig. 20 and Supplementary Note 1). As we expect the reaction products to be molecules with wide HOMO-LUMO gaps32, the measured absorbance will be dominated by the unreacted BP. This is supported by the lack of spectral changes with time. All samples were shaken before measurement to avoid sedimentation effects and measured at similar absorbances/concentrations. In this case, degradation of the FL-BP should result in a fall in measured absorbance over time, which we do indeed observe for BP exfoliated in a number of solvents (Fig. 5a). It is clear that exfoliation in CHP and NMP results in low reactivity, which can be reduced even further by preparing the dispersions in dried and deoxygenated CHP under inert conditions (sample CHP GB). In addition, we see an increase in the reactivity with decreasing nanosheet size (Fig. 5b, Supplementary Table 2 and Supplementary Fig. 21), suggesting that the chemical reaction starts from the edge as previously found for other 2D materials such as $\\mathrm{TiS}_{2}$ (ref. 47). \n\n![](images/d8943dc9355fa191bfc9744e6606790593268181553a665e28bc9c8bc8d9be69.jpg) \nFigure 3 | Size dependence of optical properties of exfoliated Black Phosphorous. (a–c) TEM length histograms of size-selected FL-BP in CHP including representative TEM images as insets (scale bars in a–c: 100, 200 and $200\\mathsf{n m},$ . Sample sizes in a–c are 131, 111 and 140, respectively. (d) Extinction (e) spectra normalized to $355\\mathsf{n m}$ of FL-BP dispersions with different mean nanosheet lengths showing systematic changes as a function of size. Extinction spectra can be split into contributions from absorbance $(\\alpha)$ and scattering $(\\sigma)$ . (e) Absorbance spectra of the same dispersions (normalized to $340\\mathsf{n m}.$ ) and $(\\pmb{\\uparrow})$ scattering spectra. Scattering spectra were obtained by subtracting the absorbance spectra from the normalized extinction spectra. \n\nSimilar to Martel and co-workers32, we fit these curves to exponential decays: $A=A_{\\mathrm{UnRe}}+A_{\\mathrm{Re}}e^{-t/\\tau}$ , where $\\boldsymbol{A}_{\\mathrm{Re}}$ represents the total amount of FL-BP which reacts over time and $A_{\\mathrm{UnRe}}$ represents the component which never reacts. Typically we observe time constants of 10s–100s of hours. This is much longer than the decay times of $\\sim1\\mathrm{h}$ observed by Martel and co-workers32 for mechanically cleaved BP in water, implying the degredation kinetics to be considerably different for solvent exfoliated BP. Such fits allow us to parameterize good solvents as those with long $\\boldsymbol{\\tau}$ and small $\\mathrm{\\bar{\\itA}_{R e}/(\\it A_{U n R e}+\\bar{\\it A}_{R e})}$ (see Supplementary Table 3). In Fig. 5c, we plot t versus $A_{\\mathrm{Re}}/(A_{\\mathrm{UnRe}}+A_{\\mathrm{Re}})$ , extracted from Fig. 5a,b). This plot clearly shows FL-BP exfoliated in dry, deoxygenated CHP to be most stable, followed by NMP and CHP dispersions exfoliated in ambient conditions with ambient IPA dispersions being the least stable among the organic solvents. In addition, we have exfoliated BP in an aqueous surfactant solution with sodium cholate (NaC) as stabilizer (Supplementary Figs 23 and 28). The BP in the aqueous environment degrades most rapidly, although still with considerably longer time constants than micromechanically cleaved BP. This suggests the surfactant shell to offer partial protection, as with carbon nanotubes48. \n\n![](images/21d20c40bf312e5e6ec977c134ecd91217c4e48fbee56aa87ce18ade08e818c9.jpg) \nFigure 4 | Photoluminescence of dispersed black phosphorous nanosheets. (a,b) Photoluminescence emission–excitation contour maps measured on a size-selected BP dispersion in CHP exfoliated under inert gas conditions (see Methods) measured with a $550\\mathsf{n m}$ and $830{\\mathsf{n m}}$ cut-off filter in emission, respectively. (c) Photoluminescence line spectrum (wavelength, $\\lambda_{\\mathrm{exc}}=510\\mathsf{n m};$ for this BP dispersion in CHP. Also shown is the extinction spectrum for this dispersion as dashed line. (d) PL line spectrum, plotted versus photon energy, fitted to five Gaussian lines, representing the PL contributions from 1-, 2-, 3-, 4- and 5-layer nanosheets. (e,f) Position (e) and width (f) of fit lines shown in d, plotted versus layer number. The dashed lines in e,f show power law decays with exponents of $-0.48$ and 1.4, respectively. Also shown in e,f are data for mechanically cleaved BP nanosheets taken from Yang et al.46, Zhang et $a I$ .13 and Liu et $a l.^{45}\\left(\\pmb{\\mathsf{g}}\\right)$ AFM image (inset, scale bar $500\\mathsf{n m},$ and statistical analysis of nanosheet thickness (expressed as layer number, sample size $=281$ ) for the samples used to measure PL. ${\\bf\\Pi}({\\bf h})$ Relative PL quantum yield (by integrated PL area) as a function of layer number. \n\n![](images/ae47853968dfc3165656f5613bf6ace31caa355d809d487850547b76054fa5bb.jpg) \nFigure 5 | Stability of exfoliated black phosphorous nanosheets. \n\nThese results cannot solely be explained by residual water content of these solvents (Supplementary Fig. 22) so we suggest that the solvation shell of CHP does indeed protect the nanosheets from water and/or oxygen. This is consistent with recent computational studies which show NMP, CHP and IPA to form tightly packed solvation shells adjacent to BP surfaces. The same study showed the molecular ordering within the solvation shell to vary from solvent to solvent, perhaps explaining the observed solvent-dependent stability49. \n\nWe note that to stably exfoliate and suspend BP, a solvent must fulfil two criteria: it must have the correct surface energy50 to facilitate exfoliation and avoid reaggregation, and it must form a solvation shell which acts as a barrier to oxygen/water. Compared with most 2D materials, where only the first criterion is important, this implies that relatively few solvents will be successful at both exfoliating and protecting BP. Indeed we have only had success using CHP, NMP and to a lesser extent IPA. While others have used DMF, ethanol and other solvents to suspend $\\mathrm{FL-BP}^{30,31}$ , the in-solvent stability has generally not been studied making it impossible to assess whether they meet the second criterion. It is clear that more work is needed to expand the list of solvents that can both suspend and protect BP. \n\nHowever, such protection is clearly not perfect as we see some reactivity in all samples. To characterize this, we have added water (which also contains dissolved $\\mathrm{O}_{2}$ ) to dispersions of S-BP, std-BP and L-BP in CHP. Addition of water $/\\mathrm{O}_{2}$ significantly increases the reactivity (Fig. 5d, see Supplementary Table 4 and Supplementary Fig. 23) with $\\tau$ falling dramatically with added water content (Fig. 5e). In addition, $A_{\\mathrm{Re}}/(A_{\\mathrm{UnRe}}+A_{\\mathrm{Re}})$ increases linearly with water contents up to $\\sim10\\ \\mathrm{vol\\%}$ water, above which it saturates (Fig. 5e inset). Plotting $\\tau$ versus $A_{\\mathrm{Re}}/(A_{\\mathrm{UnRe}}+A_{\\mathrm{Re}})$ for the water addition samples shows a steady deterioration of stability as water is added (Fig. 5f). \n\n(a,b) Relative absorbance at $465\\mathsf{n m}$ , measured as a function of time, for (a) the standard FL-BP dispersion (std-BP) exfoliated in CHP, NMP and IPA, as well as BP exfoliated in CHP in a glovebox (CHP GB) and $(\\pmb{\\ b})$ std-BP in CHP compared with size-selected dispersions containing small (S-BP) and large nanosheets (L-BP). The dashed lines represent exponential decays: $A{=}A_{\\cup{\\mathsf{n R e}}}+A_{\\mathsf{R e}}{\\mathsf{e}}^{-t/\\tau},$ , where $\\boldsymbol{A}_{\\mathrm{Re}}$ represents the component of BP, which reacts with water/ $\\mathrm{\\tilde{O}}_{2}$ , $A\\cup\\lnot_{\\mathrm{nRe}}$ represents the unreacted component and t represents the reaction timescale. $\\mathbf{\\eta}(\\bullet)$ Reaction timescale, $\\tau,$ plotted versus the fraction of BP which reacts, $A_{\\mathrm{Re}}/A_{\\cup\\mathrm{nRe}}+A_{\\mathsf{R e}},$ for a number of different systems. (d) Fitted time-dependent absorbance $(465\\mathsf{n m})$ data for std-BP in CHP and std-BP dispersions with $3\\ \\mathrm{vol\\%}$ and $12.5~\\mathsf{v o l\\%}$ of water added. (e) Plot of $\\tau$ versus volume fraction of added water. The inset shows the fraction of unstable BP plotted versus water content. The dashed line demonstrates this fraction to scale initially linearly with water content. (f) Plot of $\\tau$ versus $A_{\\mathrm{Re}}/A_{\\cup\\mathsf{n R e}}+A_{\\mathsf{R e}}$ for BP exfoliated in CHP with and without the addition of water. $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ Sequence of AFM images of the same sample region of an as-prepared sample, and after 1, 4 and 11 days of exposure to ambient conditions, respectively (scale bar, $600\\mathsf{n m}.$ . Errors in c,e,f are statistical errors associated with the fits. (h) Map showing both fractional length, $\\lfloor,$ , and width, $w,$ changes as measured by AFM immediately after exfoliation after day 4. Negative values of $\\Delta w/w_{0}$ and ${\\Delta L}/{L_{0}}$ indicate that the nanosheets are getting smaller over time. (i) Mean Raman spectra $\\cdot633{\\mathsf{n m}}$ excitation) summed over the same sample region of an as-prepared sample, after 4 days and 11 days, respectively. Spectra are normalized to the silicon peak at $521\\mathsf{c m}^{-1}$ . Inset: Raman ${\\mathsf{A}}_{\\mathrm{~g~}}^{1}$ intensity map of the sample region (freshly prepared and after 11 days). (j) TEM images of the same flake deposited from a freshly prepared dispersion and after 16 days. \n\nFurthermore, we investigated the degradation of liquidexfoliated FL-BP after deposition onto substrates using AFM, Raman and TEM. In these experiments, we monitored the same sample region (that is, the same nanosheets) with AFM and Raman immediately after deposition until 11 days later. As shown by the AFM images in Fig. 5g (and Supplementary Figs 24–26), we observe broadening and blurring (that is, loss of fine structure) of the nanosheets. This is typically accompanied with shrinking of nanosheet length, $L$ and width, $\\ensuremath{\\boldsymbol{w}}$ (Fig. 5h, Supplementary Fig. 27). In some cases, we observe an increased apparent height which is typically accompanied with an increased contrast in the phase images (Supplementary Figs 25,26), attributed to the adsorption of water. However, it is important to note, that even after 11 days of ageing under ambient conditions, the CHPexfoliated FL-BP is clearly still intact, as the average Raman spectra (normalized to Si) of the same sample region show no spectral changes, especially with respect to $\\mathrm{\\dot{A}_{g}^{1}/A_{g}^{2}}$ (Fig. 5i and Supplementary Fig. 28). These data imply that the overall structure of the FL-BP nanosheets does not change with time, consistent with degradation occurring at nanosheet edges rather than the basal plane. This is further confirmed by XPS (Supplementary Fig. 29) and TEM analysis where we tracked the same nanosheets over time (Fig. 3j and Supplementary Fig. 30). While the flakes look disrupted and, as with AFM, blurred out at the edges, most of the nanosheets remain intact even after 16 days. It is important to emphasize that we clearly observe degradation when using a less favourable, low boiling point solvent such as IPA (Supplementary Fig. 31). Taken together this suggests that solvents such as CHP protect the nanosheets from degrading at the basal plane with the solvation shell remaining even after the bulk solvent has been removed. Importantly, it also shows that degradation starts at the edges. This implies that the structure of the solvation shell is different at the nanosheet edges in a way that makes water $/\\mathrm{O}_{2}$ ingress at the edges much more likely than at the basal plane. This preferential edge degradation has important implications for future applications of BP. Edge degradation leaves the basal plane intact and should not greatly affect the properties of the BP nanosheets other than their size. This makes the environmental instability of BP less problematic for applications than might previously have been thought. \n\nReaction mechanism. If the basal plane is protected by solvent such that the dominant reaction pathway in liquid-exfoliated nanosheets occurs at the edges, then the reaction mechanism may differ to that proposed by Martel and co-workers32 Here we suggest an alternative pathway involving nanosheet edges, which is supported by density functional theory calculations (see also Supplementary Note 2). Since we experimentally observe a drop in $\\mathrm{\\pH}$ with time after water addition and the formation of phosphorous and/or phosphoric acid (XPS), we propose the following acid–base disproportionation reaction involving nanosheet edges (Fig. 6a), which may become dominant when basal plane reactions are suppressed: \n\n$$\n\\mathrm{BP}+3\\mathrm{H}_{2}\\mathrm{O}\\longrightarrow\\mathrm{BP}_{\\mathrm{2VAC}}+\\mathrm{PH}_{3}+\\mathrm{H}_{3}\\mathrm{PO}_{3}\n$$ \n\nThis reaction was evaluated for both edge sites and basal plane $\\mathrm{~\\bf~P~}$ atoms. In both cases, a defective structure $\\mathrm{BP}_{2\\mathrm{VAC}},$ with two $\\mathrm{\\DeltaP}$ vacancies in the BP supercell is formed $(2.5\\%$ vacancy concentration, Supplementary Figs 32 and 33). The reaction energy of process (1) is evaluated as \n\n$$\n\\Delta E=\\left[E(\\mathrm{BP})+3E(\\mathrm{H}_{2}\\mathrm{O})\\right]-\\left[E(\\mathrm{BP}_{\\mathrm{2VAC}})+E(\\mathrm{PH}_{3})+E(\\mathrm{H}_{3}\\mathrm{PO}_{3})\\right]\n$$ \n\nwhere $[E(\\mathrm{BP})+3E(\\mathrm{H}_{2}\\mathrm{O})]$ is the energy of the nanosheet and three isolated water molecules at infinite distance from the nanosheet and $[E(\\mathrm{BP_{2VAC}})+E(\\mathrm{PH}_{3})+E(\\mathrm{H}_{3}\\mathrm{PO}_{3})]$ is the energy of the defective nanosheet infinitely distant from the other isolated reaction products. This reaction is exothermic $(\\Delta E=-1.2\\mathrm{eV}$ , see Fig. 6) when the process occurs at the edge but endothermic $(\\Delta E=0.26\\mathrm{eV},$ ) when occurring far from the edge (see Supplementary Figs 34 and 35). In either case, degradation is a multistep process. Since we are interested in whether a reaction starts at the edge or the basal plane, we have analysed the early steps in the reaction (approach of $_\\mathrm{H}_{2}\\mathrm{O}$ and splitting of $_{\\mathrm{H}_{2}\\mathrm{O}}$ to hydroxyl group and H atoms chemisorbed to neighbouring P). In both edge and basal plane cases, the water adsorption is slightly exothermic, while the splitting of the water is highly unfavourable on the basal plane (Supplementary Fig. 34). We have furthermore ruled out that the disproportionation reaction could proceed in the middle of BP nanosheet if activated by the formation of the first hole by studying the degradation process starting from a defective structure ${\\mathrm{BP}}_{2\\mathrm{VAC}}$ (Supplementary Fig. 36). The reaction is again endothermic by ${\\sim}\\bar{\\Delta}\\bar{E}{=}0.26\\mathrm{eV}$ further supporting that the reaction is unlikely to occur on the basal plane. \n\n![](images/d27a7e060489b6fa783123d4bae908ab5f5b699e924b9514093e3670163a460b.jpg) \nFigure 6 | Reactivity of solvent-stabilized Black Phosphorous with water. (a) Edge selective degradation model for BP exposed to pure neutral water. Top and bottom panel represent reagent (BP edge $^+$ three water molecules) and reaction products (BP defective edge $^+$ phosphine $^+$ phosphorous acid), respectively, with the reaction energy also given. Green, red and white balls represent P, O and H atoms, respectively. (b) Experimental data for amount of reacted phosphorus and water, respectively, as a function of time for std-BP GB in CHP after addition of $3\\ \\mathrm{vol\\%}$ of water. The data was obtained from tracking both water and BP concentrations by ultraviolet– visible spectroscopy (see Supplementary Note 3). (c) Molar ratio of water/ BP as a function of time measured for a std-BP GB dispersion in CHP after addition of 3 and $10\\mathrm{\\vol\\%}$ of water. The molar ratio is centred at 2–3, which is reasonably consistent with the proposed edge degradation reaction. \n\nThese calculations show that BP can react with water, even in the absence of oxygen, to remove $\\mathrm{\\DeltaP}$ atoms from the nanosheet edge although this reaction may only be important when basal plane reactions32 are suppressed. To test the validity of the proposed reaction, we attempted to experimentally determine the stoichiometric ratio of reacted BP and water. After addition of water to a BP dispersion, the consumption of both water and BP can be tracked by ultraviolet–visible spectroscopy (see Supplementary Figs 37 and 38, Supplementary Note 3). Knowing the extinction coefficients of both components, this data can be converted to the concentration of reacted BP and water, respectively (Supplementary Fig. 37). The reacted concentration as a function of time for both BP and water is shown in Fig. 6b (using the CHP GB dispersion after addition of $3\\mathrm{\\vol\\%}$ of water). It is clear that two to three water molecules are consumed for every P atom. As shown in Fig. 6c, a similar stoichiometry ratio is obtained when analysing a dispersion where initially $10\\ \\mathrm{\\vol\\%}$ of water was added. The thus experimentally determined $\\mathrm{H}_{2}\\mathrm{O}/\\mathrm{P}$ ratio of two to three agrees well with the proposed edge reaction. \n\nHowever, it can unfortunately not distinguish between the proposed edge disproportionation reaction and the reported basal plane oxidation32. \n\nApplications. For liquid-exfoliated FL-BP, the degradation timescale is slow enough to allow processing of nanosheets for applications testing in a number of areas. We believe that if applications potential is demonstrated, practical usage of FL-BP will be enabled by encapsulation7,24. In this work we have chosen three applications, which have not previously been described to demonstrate the broad potential of FL-BP. \n\n![](images/215949c9093dd95241d3ba8fb27d2006576cd638783b6fbd54faaaedb5e7e53d.jpg) \nFigure 7 | Applications of liquid-exfoliated FL-BP. (a,b) Sensing of $N H_{3}$ gas using std-BP films. (a) Sensor response plot shows percentile resistance change versus time of the FL-BP films with a bias voltage of 1 V at room temperature, on consequent $N H_{3}$ exposures at various concentrations from 1 to 10 p.p.m. (b) Plot of signal-to-noise ratio as a function of $N H_{3}$ concentration from 1 to 3 p.p.m. The error bar represents the s.d. of five devices and the linear line indicates the fitted line. $(\\bullet-\\bullet)$ Saturable absorption of std-BP and graphene in CHP for fematosecond pulses excited at (c) $1,030\\mathsf{n m}$ and (d) $515\\mathsf{n m}$ . Linear transmission $T_{O}$ is given in the legend. (e) Saturation intensity of FL-BP and graphene as a function of ${{T}_{O}}$ . (f) Representative stress–strain curves for PVC and PVC: FL-BP $(0.3\\ \\mathrm{vol\\%})$ . Inset: low strain regime. $(\\pmb{\\mathrm{g}}\\mathbf{-}\\mathbf{i})$ Young’s modulus, including the theoretical constant-strain rule-of-mixtures modulus prediction (blue using the Voigt– Reuss–Hill planar-averaged nanosheet modulus, blue-dashed using its Voigt and Reuss bounds) $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ , tensile strength ${\\bf\\Pi}({\\bf h})$ and tensile toughness (i) plotted as a function of FL-BP volume fraction. (j) Calculated orientation dependence of the in-plane two-dimensional Young’s modulus ( $Y_{\\mathsf{B P}},$ blue) and Poisson’s ratio $\\cdot\\boldsymbol{\\nu},$ red), of black phosphorus, together with the Voigt–Reuss–Hill averaged in-plane modulus $\\zeta$ , black). Errors in b,e,g–i are statistical errors associated with the fits. \n\nTheoretical work has suggested FL-BP nanosheets as gas sensors18. We prepared thin films of FL-BL nanosheets by vacuum filtration followed by transfer to interdigitated electrode arrays. Two-probe measurements showed relatively high conductivities of $\\sim1\\mathrm{Sm}^{-1}$ , similar to films of $\\mathrm{WTe}_{2}$ nanosheets51. Shown in Fig. 7a (and Supplementary Fig. 39) is the resistance change of a thin film of FL-BP nanosheets on exposure to ammonia $\\left(\\mathrm{NH}_{3}\\right)$ gas. We observe a resistance increase, consistent with $\\mathrm{NH}_{3}$ donating electrons to the p-type FL-BP. By extrapolation of the signal-to-noise level (Fig. 7b), and assuming the minimum detectable signal to be three times the root mean square noise level, we estimate a detection threshold of 80 p.p.b. This shows FL-BP networks to be competitive with other nano-sensors52–54 and a very promising material for gas detection. \n\nThe nonlinear optical response of the FL-BP dispersions was investigated by open-aperture $Z$ -scan using a 340-fs pulsed fibre laser55. In Fig. $^{7\\mathrm{c},\\mathrm{d},}$ it is clearly seen that normalized transmission of the FL-BP dispersions increases with laser intensity at both 1,030 and $515\\mathrm{nm}$ . Such broadband saturable absorption (SA) suggests that the FL-BP nanosheets could serve as an ultrafast nonlinear saturable absorber, an essential mode-locking element for ultrashort pulsed lasers56,57. Since graphene is a well-known broadband saturable absorber58, we carried out the same nonlinear measurement for graphene dispersions prepared by the similar liquid exfoliation. At the same level of linear transmission, the FL-BP dispersions exhibit much stronger SA response than the graphene dispersions at both wavelengths. The saturable intensity $I_{s}$ is obtained by fitting the Z-scan data with the SA model $\\mathrm{d}I/\\mathrm{d}z=-\\alpha I,$ where $\\alpha=\\alpha_{0}/(1+I/I_{\\mathrm{Sat}})$ : $\\scriptstyle{\\mathfrak{a}}_{0}$ is the linear absorption coefficient and $I$ is the excitation intensity. As shown in Fig. 7e, $\\boldsymbol{I}_{\\mathrm{Sat}}$ of FL-BP is much lower than that of graphene at both 1,030 and $515\\mathrm{nm}$ when the linear transmission is equal. The significant ultrafast nonlinear property of FL-BP implies a huge potential in the development of nanophotonic devices, such as mode-lockers, Q-switchers, optical switches and so on59. \n\nThe impressive mechanical properties of 2D materials in general60 suggest the potential to use FL-BP as a reinforcing filler in composites. Shown in Fig. 7f are the representative stress–strain curves for a film of polyvinylchloride (PVC) and a PVC:FL-BP $(0.3\\mathrm{\\vol\\%}$ , see methods and Supplementary Figs 40 and 41). It is clear that the mechanical properties improve considerably both in the high and low strain regimes. Shown in Fig. 7g-i are the composite modulus, strength and tensile toughness, plotted as a function of BP loading content. In each case, mechanical properties increase considerably for loading levels of only $0.3\\mathrm{\\vol}\\%$ . The modulus, Y, increases from ${500}\\mathrm{{MPa}}$ for PVC to $900\\mathrm{MPa}$ for the $0.3\\mathrm{\\vol}\\%$ composite. In addition, at $0.3\\mathrm{-vol\\%}$ loading, the measured strength of the composite doubles while its tensile toughness displays a sixfold increase. These are significant increases and are competitive with those found using graphene as a filler in both $\\mathrm{\\hat{P}V C^{61}}$ and polymers in general62. \n\nWe used first-principles simulations (see Supplementary Note 4) to obtain the bulk BP Young’s modulus as a function of orientation in the plane of the crystal as shown in Fig. 7j, yielding a Voigt–Reuss–Hill in-plane average modulus of $\\dot{\\langle Y_{\\mathrm{BP}}\\rangle}\\dot{=}97\\mathrm{GPa}$ . We also calculated the Poisson’s ratio finding it to be highly anisotropic. Assuming the BP nanosheets lie inplane63, we can use the calculated $\\langle\\bar{Y}_{\\mathrm{BP}}\\rangle$ , coupled with the rule of mixtures62 to predict the composite modulus as a function of BP volume fraction, $V_{\\mathrm{f}};Y_{\\mathrm{comp}}{=}\\langle\\bar{Y}_{\\mathrm{BP}}\\rangle V_{\\mathrm{f}}{+}Y_{\\mathrm{poly}}(1-V_{\\mathrm{f}})$ . We find this prediction (blue line) to agree well with the experimental data even though we have not corrected for the finite aspect ratio of the nanosheets or their layered nature. \n\n# Discussion \n\nIn conclusion, we have shown that the BP crystals can be efficiently exfoliated in appropriate solvents to yield high-quality, few-layered nanosheets with controllable size, which can be used for fundamental measurements such as PL studies. Compared with mechanically cleaved nanosheets, liquid-exfoliated FL-BP is remarkably stable in CHP, probably due to protection by the solvation shell. However, addition of water results in degradation of the nanosheets. Both experimental and computational studies indicate the degradation to occur at the nanosheet edge with no basal plane damage and proceed by reaction of the FL-BP with water. Based on this, we propose an alternative BP degradation reaction, which can occur when basal plane reactions are supressed. Importantly, this means that the net result of degradation is reduction on nanosheet size rather than alteration of flake properties. We demonstrate that liquid-exfoliated FL-BP nanosheets have potential for use in applications as gas sensors, saturable absorbers and reinforcing fillers for composites. We believe this work is important as it will facilitate the large-scale production of FL-BP. Such a goal is realizable in practise because, even when produced in ambient conditions, CHP-exfoliated FL-BP is stable for $\\sim200\\mathrm{h}$ $(c f,\\sim1\\mathrm{h}$ for mechanically cleaved BP). We believe these advances will facilitate its development in a broad range of applications. \n\n# Methods \n\nSample preparation. BP crystals were purchased from Smart Elements (purity $99.998\\%$ ) with all other materials sourced from Sigma Aldrich (all used as received). BP was lightly ground with pestle and mortar and immersed in CHP (concentration $2{\\mathrm{gl}}^{=}1{\\mathrm{\\Omega}},$ ). The dispersion was sonicated for $^{5\\mathrm{h}}$ at $60\\%$ amplitude with a horn-probe sonic tip (VibraCell CVX, 750W) under cooling, yielding a stoc dispersion. Aliquots of the stock dispersion were centrifuged at $1{,}000\\mathrm{r.p.m}$ . (106g) for time periods varying from 5 to $240\\mathrm{min}$ in a Hettich Mikro 220R centrifuge equipped with a fixed-angle rotor 1016. The supernatant was decanted and subjected to absorbance spectroscopy. The supernatant with centrifugation conditions $1{,}000\\mathrm{r.p.m}$ . for $180\\mathrm{min}$ was denoted std-BP. The std-BP was subsequently separated into small and large stable nanosheets. For this purpose, aliquots of std-BP dispersion were subjected to an additional centrifugation of 5 kr.p.m. (2,660g) for $120\\mathrm{min}$ . The supernatant (containing small flakes) was decanted and characterized as S-BP, while the sediment (containing large flakes) was redispersed in fresh CHP and characterized as L-BP. Alternatively, the FL-BP was size-selected by controlled centrifugation with subsequently increasing rotation speeds. The sediment after 2 kr.p.m. (426g, 2 h) was discarded, while the supernatant was subjected to further centrifugation at 3 kr.p.m. $(958g,2\\mathrm{h}$ ). The sediment was collected in fresh solvent, while the supernatant was subjected to further centrifugation at 4 kr.p.m. $(1,702g,$ 2 h). Again, the sediment was collected and the supernatant was centrifuged at high r.p.m. This procedure was repeated for 5 kr.p.m. $(2,660g,2\\mathrm{h})$ , 10 kr.p.m. $(10,170g,$ 2 h) and 16 kr.p.m. $(25,000g,2\\mathrm{h})$ to yield samples with decreasing sizes in the respective sediments. For part of the degradation studies and PL measurement, BP was exfoliated under inert conditions by sonication in an argon-filled glovebox $\\mathrm{\\langleO}_{2}{<}0.1$ p.p.m.; $\\mathrm{H}_{2}\\mathrm{O}{<}0.1$ p.p.m.) in pump-freeze deoxygenated and dry CHP with a water content of $29\\mathrm{p.p.m}$ . $(0.{\\bar{5}}\\mathbf{g}\\mathbf{l}^{-\\bar{1}}$ BP, $15\\mathrm{ml}$ CHP, tapered tip Bandelin Sonoplus 3100, $25\\%$ amplitude, $^{2\\mathrm{h}} $ pulse 2 s on, 2 s off). The resultant dispersions were transferred into centrifugation vials, which were sealed and centrifuged for $^{3\\mathrm{h}}$ at 100g to obtain the std-BP GB sample. To increase the population of few-layered species for the PL measurement, this std-BP GB sample was centrifuged for $16\\mathrm{h}$ at 25g. The sediment was discarded and the supernatant centrifuged again at $710g$ for $180\\mathrm{min}$ . The PL spectra shown in the main manuscript were acquired from the supernatant of this centrifugation after dilution to an optical density of $0.4\\mathrm{cm}^{-1}$ . All solvent transfer was carried out in the glovebox. \n\nCharacterization. Optical extinction and absorbance were measured on a Perkin Elmer 650 spectrometer in quartz cuvettes. To distinguish between contributions from scattering and absorbance to the extinction spectra, dispersions were measured in an integrating sphere using a home-built sample holder to place the cuvette in the centre of the sphere. The absorbance spectrum is obtained from the measurement inside the sphere. A second measurement on each dispersion was performed outside the sphere to obtain the extinction spectrum. This allows for the calculation of the scattering spectrum (extinction absorbance). The experiments to track both water and BP degradations were performed on a Perkin Elmer Lambda 1050 spectrometer in extinction. \n\nBright-field TEM imaging was performed using a JEOL 2100, operated at $200\\mathrm{kV}$ , while HRTEM was conducted on a FEI Titan TEM $(300\\mathrm{kV})$ . High resolution TEM images (Fig. 5f) were taken using an FEI Titan 60–300 Ultimate Microscope operated at $300\\mathrm{kV}$ . The FL-BP was dropped on grids using a drop casting method and excess fluid was absorbed by an underlying filter membrane. It was then baked in vacuum at $120^{\\circ}\\mathrm{C}$ for several hours. The samples were imaged on the day they were received which is termed Day 1. The same flake was then imaged on Day 3 and 16. No changes in nanosheet structure of morphology were observed between Day 1 and Day 3, but by Day 16 a combination of reaction products and water adsorption results in a liquid layer on the flake. This layer can be removed with the beam, and comparison of the shape of the flakes between Day 1 and Day 16 shows that the overall shape and size of the flake has not changed. There is also lattice apparent in the flake on Day 16 when using a high magnification $(\\times300\\mathrm{k})$ . \n\nAberration-corrected STEM images were taken using a Nion Ultrasteme 100 (cold filed emission gun at the SuperSTEM Laboratory in Daresbury, UK. The suspended FL-BP flakes were dropped onto lacey carbon-coated copper TEM grids as before. The samples were then prebaked at $120^{\\circ}\\mathrm{C}$ in a vacuum overnight. The images were recorded using a $100\\mathrm{kV}$ acceleration voltage with a HAADF field detector and low-pass bright-field imaging. Figure 1f shows a representative Butterworth-filtered HAADF STEM image and Figure 1g shows a low-by-pass bright-field STEM image of the material. The lattice shows high uniformity with the presence of very few defects or dislocations. Depending on the zone axis used, the lattice can exhibit a ‘dumbbell’-type configuration. \n\nAFM was carried out on a Veeco Nanoscope-IIIa (Digital Instruments) system equipped with an E-head $(13\\upmu\\mathrm{m}$ scanner) in tapping mode after depositing a drop of the dispersion transferred to IPA on a pre-heated $(150^{\\circ}\\mathrm{C})$ $\\mathrm{Si}/\\mathrm{SiO}_{2}$ wafer with an oxide layer of $300\\mathrm{nm}$ . Raman spectroscopy on individual flakes was performed using a Horiba Jobin Yvon LabRAM HR800 with $633\\mathrm{nm}$ excitation laser in air under ambient conditions. XPS was performed under ultra-high vacuum conditions $(<5\\times10^{-10}\\mathrm{mbar})$ , using monochromated Al $\\mathtt{K}\\mathtt{\\backslash}$ X-rays $(1,486.6\\mathrm{eV})$ from an Omicron XM1000 MkII X-ray source and an Omicron EA125 energy analyser. An Omicron CN10 electron flood gun was used for charge compensation and the binding energy scale was referenced to the adventitious carbon 1s core level at $284.8\\mathrm{eV}$ . Core-level regions were recorded at an analyser pass energy of $15\\mathrm{eV}$ and with slit widths of $6\\mathrm{mm}$ (entry) and $3\\mathrm{mm}\\times10\\mathrm{mm}$ (exit), resulting in an instrumental resolution of $0.48\\mathrm{eV}$ . After subtraction of a Shirley background, the core-level spectra were fitted with Gaussian–Lorentzian line shapes using the Marquardt’s algorithm. \n\nPL in dispersion was acquired on a Horiba Scientific Fluorolog-3 system equipped with 450 W Xe halogen lamp and a nitrogen-cooled InGaS diode array detector (Symphony iHR 320). Spectra were obtained at $5^{\\circ}\\mathrm{C}$ using appropriate cutoff filters (see Supplementary Figs 17–19). \n\nModelling. The QuantumEspresso package was used to evaluate the reaction energies. In this case, we selected an energy cutoff of 50 Ryd, a grid of $2\\times2\\times1$ Monchorst–Pack k-points (see Supplementary Note 2) and ultrasoft pseudopotentials. Langreth and Lundqvist van der Waals-corrected exchange and correlation functional64 was used and atomic forces were relaxed until they were $<5\\times10^{-3}\\mathrm{eV}\\mathrm{A}^{-1}$ . \n\nWe also calculated bulk and in-plane mechanical properties of BP (see Supplementary Note 4 and Supplementary Tables 5–7) to clarify the microscopic origins of an observed dramatic increase in the Young’s modulus of composites reinforced with BP nanosheets. In this case, the PBE functional, augmented with the empirical dispersion correction of the B97-D functional65 was used to compute the elastic constants of bulk phosphorus by finite-difference, the nanosheets in question being closer to the bulk than monolayer regime. The Voigt–Reuss–Hill approach,66 was used to estimate both isotropic (found to be comparable to current literature67) and nanosheet in-plane-only estimates of the average nanosheet Young’s modulus, as well as upper (Voigt) and lower (Reuss) expected error bounds. \n\nApplications. For nonlinear optical measurements, an open-aperture Z-scan system was used to study the ultrafast nonlinear optical properties of the FL-BP (std-BP) and graphene dispersions. This measures the total transmittance through a sample as a function of incident laser intensity, while the sample is sequentially moved through the focus of a lens (along the $z.$ -axis)55,57. All experiments were performed with 340-fs pulses from a mode-locked fibre laser, which was operated at $1,030\\mathrm{nm}$ and its second harmonic, $515\\mathrm{nm}$ , with a pulse repetition rate of $1\\mathrm{kHz}$ . All dispersion samples were tested in quartz cuvettes with $_{1-\\mathrm{mm}}$ pathlength. \n\nGas sensing was conducted on the FL-BP (std-BP) prepared in CHP and then subsequently transferred into 2-proponal by centrifugation as conducted for the AFM measurements to facilitate filtration onto a nitrocellulose membrane. Following filtration, the film was allowed to dry under vacuum conditions. The FLBP film was cut into $10\\times2\\mathrm{-mm}$ rectangular pieces. These were then transferred onto silicon dioxide wafer, while the nitrocellulose membrane was dissolved using the transfer method according to the study by Wu et al.68 \n\nFor gas sensing, gold electrodes were sputtered on top of an adhesion layer of nickel $(\\mathrm{Ni}/\\mathrm{Au}=30/70\\mathrm{nm})$ using a metal shadow mask, which has a $2\\mathrm{-mm}$ -wide and $200\\mathrm{-}\\upmu\\mathrm{m}$ -long channel. All devices were loaded in a gas-sensing chamber and annealed at $100^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ to remove residues and adsorbates on the surface. The gas-sensing chamber was kept at room temperature at a pressure of 10 Torr, with a 100 s.c.c.m. flow of the $\\mathrm{NH}_{3}$ and $\\Nu_{2}$ mixtures. The resistance change of five devices on interval gas exposure was simultaneously measured using a Keithley model 2612A SourceMeter and a Keithley 3706 System Switch at a constant bias voltage of 1 V. The initial resistance and root mean square noise were calculated from the first 500 data points, $\\sim2\\mathrm{min}$ before the first gas injection. ${\\mathrm{NH}}_{3}$ for $2\\mathrm{min}$ and pure $\\mathrm{N}_{2}$ for $5\\mathrm{{min}}$ were periodically introduced to record sensor response and recover, respectively. \n\nA previously prepared nanofiller FL-BP dispersion in CHP, centrifuged between 1 kr.p.m. for $180\\mathrm{min}$ and $3\\mathrm{kr.p.m}$ . for $120\\mathrm{min}$ and redispersed in fresh CHP solvent, was subsequently filtered onto a Polyester Membrane Filter $(0.2\\upmu\\mathrm{m})$ of known mass. The membrane was dried in a vacuum oven at $100^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ and the mass of the membrane was remeasured to attain the mass of the filtered nanofiller. The nanofiller was redispersed by bath sonication (Branson 1510 Model $45\\mathrm{kHz}$ ) in a 65:35 tetrahydrofuran (THF), chloroform solvent mixture. PVC was dissolved in a solvent mixture (65:35 THF/chloroform). A range of FL-BP/PVC/THF/ Chloroform dispersions (from 0 to 0.0074 volume fraction) were made by adding the FL-BP/THF/Chloroform filler solution to the PVC/THF/Chloroform solution with varying increments of loading. These solutions were of constant mass ( $\\mathrm{150mg}$ of FL-BP and polymer) and constant volume $\\mathrm{\\nabla}5\\mathrm{ml}$ of FL-BP, polymer and solvent). These samples were sonicated in the same bath as before for $^\\mathrm{1h}$ to homogenize after the blending of the solutions. The homogenized solution mixtures were then dropcast into $5\\times5\\times1\\mathrm{cm}$ Teflon trays and placed in a vacuum oven for $\\boldsymbol{4\\mathrm{h}}$ at $40^{\\circ}\\mathrm{C}$ under no vacuum to form composite films. The films were then kept overnight $(\\sim17\\mathrm{h})$ at $50^{\\circ}\\mathrm{C}$ under full vacuum to ensure that the solvent was completely removed and to protect the filler material from decomposition before testing. For mechanical measurements, the films were cut into $2.25\\mathrm{-mm}$ strips and then tested on a Zwick Roell tensile tester with a $100\\mathrm{N}$ load cell at a strain rate of $10\\mathrm{{mm}\\mathrm{{min}^{-1}}}$ . \n\n# References \n\n1. Geim, A. K. Graphene: status and prospects. Science 324, 1530–1534 (2009). \n2. Novoselov, K. S. et al. A roadmap for graphene. Nature 490, 192–200 (2012). \n3. Ferrari, A. C. et al. Science and technology roadmap for graphene, related twodimensional crystals, and hybrid systems. Nanoscale 7, 4598–4810 (2015). \n4. Chhowalla, M. et al. The chemistry of two-dimensional layered transition metal dichalcogenide nanosheets. Nat. Chem. 5, 263–275 (2013). \n5. Osada, M. & Sasaki, T. Exfoliated oxide nanosheets: new solution to nanoelectronics. J. Mater. Chem. 19, 2503–2511 (2009). tro meta dichalcogenides. Nat. Nanotechnol. 7, 699–712 (2012). 7. Wood, J. D. et al. Effective passivation of exfoliated black phosphorus transistors against ambient degradation. Nano Lett. 14, 6964–6970 (2014). \n8. Castellanos-Gomez, A. et al. Isolation and characterization of few-layer black phosphorus. 2D Materials 1, 025001 (2014). 9. Buscema, M., Groenendijk, D. J., Steele, G. A., van der Zant, H. S. J. & Castellanos-Gomez, A. Photovoltaic effect in few-layer black phosphorus PN junctions defined by local electrostatic gating. Nat. Commun. 5, 4651 (2014). \n10. Qiao, J., Kong, X., Hu, Z.-X., Yang, F. & Ji, W. High-mobility transport anisotropy and linear dichroism in few-layer black phosphorus. Nat. Commun. 5, 4475 (2014). \n11. Xia, F., Wang, H. & Jia, Y. Rediscovering black phosphorus as an anisotropic layered material for optoelectronics and electronics. Nat. Commun. 5, 4458 (2014). \n12. Li, L. et al. Black phosphorus field-effect transistors. Nat. Nanotechnol. 9, 372–377 (2014). \n13. Zhang, S. et al. Extraordinary photoluminescence and strong temperature/ angle-dependent Raman responses in few-layer phosphorene. ACS Nano 8, 9590–9596 (2014). \n14. Cai, Y., Zhang, G. & Zhang, Y.-W. Layer-dependent band alignment and work function of few-layer phosphorene. Sci. Rep. 4, 6677 (2014). \n15. Buscema, M. et al. Fast and broadband photoresponse of few-layer black phosphorus field-effect transistors. Nano Lett. 14, 3347–3352 (2014). \n16. Hong, T. et al. Polarized photocurrent response in black phosphorus field-effect transistors. Nanoscale 6, 8978–8983 (2014). \n17. Sun, J. et al. Formation of stable phosphorus–carbon bond for enhanced performance in black phosphorus nanoparticle–graphite composite battery anodes. Nano Lett. 14, 4573–4580 (2014). \n18. Kou, L., Frauenheim, T. & Chen, C. Phosphorene as a superior gas sensor: selective adsorption and distinct I–V response. J. Phys. Chem. Lett. 5, 2675–2681 (2014). \n19. Fei, R. et al. Enhanced thermoelectric efficiency via orthogonal electrical and thermal conductances in phosphorene. Nano Lett. 14, 6393–6399 (2014). \n20. Du, W., Jiang, X. & Zhu, L. From graphite to graphene: direct liquid-phase exfoliation of graphite to produce single- and few-layered pristine graphene. J. Mater. Chem. C 1, 10592–10606 (2013). \n21. Nicolosi, V., Chhowalla, M., Kanatzidis, M. G., Strano, M. S. & Coleman, J. N. Liquid exfoliation of layered materials. Science 340, 1226419 (2013). \n22. Coleman, J. N. et al. Two-dimensional nanosheets produced by liquid exfoliation of layered materials. Science 331, 568–571 (2011). \n23. Hernandez, Y. et al. High-yield production of graphene by liquid-phase exfoliation of graphite. Nat. Nanotechnol. 3, 563–568 (2008). \n24. Paton, K. R. et al. Scalable production of large quantities of defect-free few-layer graphene by shear exfoliation in liquids. Nat. Mater. 13, 624–630 (2014). \n25. Varrla, E. et al. Turbulence-assisted shear exfoliation of graphene using household detergent and a kitchen blender. Nanoscale 6, 11810–11819 (2014). \n26. Hanlon, D. et al. Production of molybdenum trioxide nanosheets by liquid exfoliation and their application in high-performance supercapacitors. Chem. Mater. 26, 1751–1763 (2014). \n27. Zhi, C. Y., Bando, Y., Tang, C. C., Kuwahara, H. & Golberg, D. Large-scale fabrication of boron nitride nanosheets and their utilization in polymeric composites with improved thermal and mechanical properties. Adv. Mater. 21, 2889–2893 (2009). \n28. Green, A. A. & Hersam, M. C. Solution phase production of graphene with controlled thickness via density differentiation. Nano Lett. 9, 4031–4036 (2009). \n29. Brent, J. R. et al. Production of few-layer phosphorene by liquid exfoliation of black phosphorus. Chem. Commun. 50, 13338–13341 (2014). \n30. Yasaei, P. et al. High-quality black phosphorus atomic layers by liquid-phase exfoliation. Adv. Mater. 27, 1887–1892 (2015). \n31. Kang, J. et al. Solvent exfoliation of electronic-grade, two-dimensional black phosphorus. ACS Nano 9, 3596–3604 (2015). \n32. Favron, A. et al. Photooxidation and quantum confinement effects in exfoliated black phosphorus. Nat. Mater. 14, 826–832 (2015). \n33. Backes, C. et al. Edge and confinement effects allow in situ measurement of size and thickness of liquid-exfoliated nanosheets. Nat. Commun. 5, 4576 (2014). \n34. O’Neill, A., Khan, U. & Coleman, J. N. Preparation of high concentration dispersions of exfoliated mos2 with increased flake size. Chem. Mater. 24, 2414–2421 (2012). \n35. Yadgarov, L. et al. Dependence of the absorption and optical surface plasmon scattering of mos2 nanoparticles on aspect ratio, size, and media. ACS Nano 8, 3575–3583 (2014). \n36. Khan, U., O’Neill, A., Lotya, M., De, S. & Coleman, J. N. High-concentration solvent exfoliation of graphene. Small 6, 864–871 (2010). \n37. Eda, G. et al. Photoluminescence from chemically exfoliated MoS2. Nano Lett. 11, 5111–5116 (2011). \n38. Ridings, C., Warr, G. G. & Andersson, G. G. Composition of the outermost layer and concentration depth profiles of ammonium nitrate ionic liquid surfaces. Phys. Chem. Chem. Phys. 14, 16088–16095 (2012). \n39. Nemes-Incze, P., Osv´ath, Z., Kamara´s, K. & Biro´, L. P. Anomalies in thickness measurements of graphene and few layer graphite crystals by tapping mode atomic force microscopy. Carbon 46, 1435–1442 (2008). \n40. Harvey, A. et al. Preparation of gallium sulfide nanosheets by liquid exfoliation and their application as hydrogen evolution catalysts. Chem. Mater. 27, 3483–3493 (2015). \n41. Khan, U. et al. Size selection of dispersed, exfoliated graphene flakes by controlled centrifugation. Carbon 50, 470–475 (2012). \n42. May, P., Khan, U., O’Neill, A. & Coleman, J. N. Approaching the theoretical limit for reinforcing polymers with graphene. J. Mater. Chem. 22, 1278–1282 (2012). \n43. Jaramillo, T. F. et al. Identification of active edge sites for electrochemical H-2 evolution from MoS2 nanocatalysts. Science 317, 100–102 (2007). \n44. Ramasubramaniam, A. & Muniz, A. R. Ab initio studies of thermodynamic and electronic properties of phosphorene nanoribbons. Phys. Rev. B. 90, 085424 (2014). \n45. Liu, H. et al. Phosphorene: an unexplored 2D semiconductor with a high hole mobility. ACS Nano 8, 4033–4041 (2014). \n46. Yang, J. et al. Unambiguous identification of monolayer phosphorene by phaseshifting interferometry. Preprint at http://arxiv.org/abs/1412.6701 (2014). \n47. Han, J. H. et al. Unveiling chemical reactivity and structural transformation of two-dimensional layered nanocrystals. J. Am. Chem. Soc. 135, 3736–3739 (2013). \n48. O’Connell, M. J. et al. Band gap fluorescence from individual single-walled carbon nanotubes. Science 297, 593–596 (2002). \n49. Sresht, V., Padua, A. A. H. & Blankschtein, D. Liquid-phase exfoliation of phosphorene: design rules from molecular dynamics simulations. ACS Nano 9, 8255–8268 (2015). \n50. Hughes, J. M., Aherne, D. & Coleman, J. N. Generalizing solubility parameter theory to apply to one- and two-dimensional solutes and to incorporate dipolar interactions. J. Appl. Polym. Sci. 127, 4483–4491 (2013). \n51. Cunningham, G., Hanlon, D., McEvoy, N., Duesberg, G. S. & Coleman, J. N. Large variations in both dark- and photoconductivity in nanosheet networks as nanomaterial is varied from MoS2 to WTe2. Nanoscale 7, 198–208 (2014). \n52. Lee, K., Gatensby, R., McEvoy, N., Hallam, T. & Duesberg, G. S. Highperformance sensors based on molybdenum disulfide thin films. Adv. Mater. 25, 6699–6702 (2013). \n53. O’Brien, M. et al. Plasma assisted synthesis of WS2 for gas sensing applications. Chem. Phys. Lett. 615, 6–10 (2014). \n54. Schedin, F. et al. Detection of individual gas molecules adsorbed on graphene. Nat. Mater. 6, 652–655 (2007). \n55. Sheikbahae, M., Said, A. A., Wei, T. H., Hagan, D. J. & Vanstryland, E. W. Sensitive measurement of optical nonlinearities using a single beam. IEEE J. Quant. Electron. 26, 760–769 (1990). \n56. Blau, W. J. & Wang, J. Variety pays off for nanotubes. Nat. Nanotechnol. 3, 705–706 (2008). \n57. Wang, K. et al. Ultrafast saturable absorption of two-dimensional MoS2 nanosheets. ACS Nano 7, 9260–9267 (2013). \n58. Sun, Z. et al. Graphene mode-locked ultrafast laser. ACS Nano 4, 803–810 (2010). \n59. Bonaccorso, F., Sun, Z., Hasan, T. & Ferrari, A. C. Graphene photonics and optoelectronics. Nat. Photonics 4, 611–622 (2010). \n60. Ataca, C., Sahin, H. & Ciraci, S. Stable, single-layer MX2 transition-metal oxides and dichalcogenides in a honeycomb-like structure. J. Phys. Chem. C 116, 8983–8999 (2012). \n61. Vadukumpully, S., Paul, J., Mahanta, N. & Valiyaveettil, S. Flexible conductive graphene/poly(vinyl chloride) composite thin films with high mechanical strength and thermal stability. Carbon 49, 198–205 (2011). \n62. Young, R. J., Kinloch, I. A., Gong, L. & Novoselov, K. S. The mechanics of graphene nanocomposites: a review. Compos. Sci. Technol 72, 1459–1476 (2012). \n63. Khan, U. et al. Polymer reinforcement using liquid-exfoliated boron nitride nanosheets. Nanoscale 5, 581–587 (2013). \n64. Dion, M., Rydberg, H., Schroder, E., Langreth, D. C. & Lundqvist, B. I. Van der Waals density functional for general geometries. Phys. Rev. Lett. 92, \n246401 (2004). \n65. Grimme, S. Semiempirical GGA-type density functional constructed with a long-range dispersion correction. J. Comput. Chem. 27, 1787–1799 (2006). \n66. Hill, R. The elastic behaviour of a crystalline aggregate. Proc. Phys. Soc. Lond. Sect. A 65, 349–355 (1952). \n67. Appalakondaiah, S., Vaitheeswaran, G., Lebegue, S., Christensen, N. E. & Svane, A. Effect of van der Waals interactions on the structural and elastic properties of black phosphorus. Phys. Rev. B. 86, 035105 (2012). \n68. Wu, Z. C. et al. Transparent, conductive carbon nanotube films. Science 305, \n1273–1276 (2004). \n\n# Acknowledgements \n\nThe research leading to these results has received funding from the European Union Seventh Framework Programme under grant agreement $\\mathrm{n}^{\\circ}604391$ Graphene Flagship. We have also received support from the Science Foundation Ireland (SFI) funded centre AMBER (SFI/12/RC/2278). In addition, JNC acknowledges the European Research Council (SEMANTICS) and SFI (11/PI/1087) for financial support. C.B. acknowledges the German research foundation DFG (BA 4856/1-1). E.D., A.P. and V.N. acknowledge ERC 2DNanoCaps, SFI PIYRA and FP7 MoWSeS. G.S.D., K.L., N.McE and N.C.B. acknowledge SFI for PI_10/IN.1/I3030 while W.B acknowledges an SFI Investigator Award (12/IA/1306). STEM experiments were performed at SuperSTEM, the EPSRC UK national facility for aberration-corrected STEM. J.W. and S.Z. acknowledge NSFC (61178007, 61522510 and 61308034), STCSM (12ZR1451800) and the External Cooperation Program of BIC, CAS (No. 181231KYSB20130007). S.S. and C.S.C. have been supported by the European Research Council (Quest project). All reaction energy calculations were performed on the Parsons cluster (project HPC_12_0722), and all mechanical property calculations on the Lonsdale cluster, (project HPC_14_00800), maintained by the Trinity Centre for High Performance Computing. These clusters were funded through grants from Science Foundation Ireland. G.A. acknowledges the EU for a Marie Curie Fellowship (FP7/2013-IEF-627386). \n\n# Author contributions \n\nD.H. and G.A. prepared liquid dispersions; D.H., C.B., A.H., N.McE. and G.S.D. performed the spectroscopy; C.B. performed AFM/Raman and PL; D.H. performed low-res TEM; E.D., A.P., Q.M.R. and V.N. performed hi-res TEM; C.Bo, Z.G. and P.L. prepared and tested composites; K.L. and G.S.D. tested gas sensing; C.S.C. and S.S. performed calculations on FL-BP stability; G.M., and D.D.O’R performed simulation of composite mechanical reinforcement by FL-BP loading; S.Z., K.W., W.J.B. and J.W. performed nonlinear optical measurements; G.A., A.Hi and F.H. supported the exfoliation under inert conditions; J.N.C. and C.B. planned the experiments and wrote the paper. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Hanlon, D. et al. Liquid exfoliation of solvent-stabilized few-layer black phosphorus for applications beyond electronics. Nat. Commun. 6:8563 doi: 10.1038/ncomms9563 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_NPHOTON.2015.82", + "DOI": "10.1038/NPHOTON.2015.82", + "DOI Link": "http://dx.doi.org/10.1038/NPHOTON.2015.82", + "Relative Dir Path": "mds/10.1038_NPHOTON.2015.82", + "Article Title": "Detection of X-ray photons by solution-processed lead halide perovskites", + "Authors": "Yakunin, S; Sytnyk, M; Kriegner, D; Shrestha, S; Richter, M; Matt, GJ; Azimi, H; Brabec, CJ; Stangl, J; Kovalenko, MV; Heiss, W", + "Source Title": "NATURE PHOTONICS", + "Abstract": "The evolution of real-time medical diagnostic tools such as angiography and computer tomography from radiography based on photographic plates was enabled by the development of integrated solid-state X-ray photon detectors made from conventional solid-state semiconductors. Recently, for optoelectronic devices operating in the visible and near-infrared spectral regions, solution-processed organic and inorganic semiconductors have also attracted a great deal of attention. Here, we demonstrate a possibility to use such inexpensive semiconductors for the sensitive detection of X-ray photons by direct photon-to-current conversion. In particular, methylammonium lead iodide perovskite (CH3NH3PbI3) offers a compelling combination of fast photoresponse and a high absorption cross-section for X-rays, owing to the heavy Pb and I atoms. Solution-processed photodiodes as well as photoconductors are presented, exhibiting high values of X-ray sensitivity (up to 25 mu C mGy(air)(-1) cm(-3)) and responsivity (1.9 x 10(4) carriers/photon), which are commensurate with those obtained by the current solid-state technology.", + "Times Cited, WoS Core": 938, + "Times Cited, All Databases": 1014, + "Publication Year": 2015, + "Research Areas": "Optics; Physics", + "UT (Unique WOS ID)": "WOS:000357406300009", + "Markdown": "# Detection of X-ray photons by solution-processed lead halide perovskites \n\nSergii Yakunin1,2, Mykhailo Sytnyk1, Dominik Kriegner1, Shreetu Shrestha3, Moses Richter3, Gebhard J. Matt3, Hamed Azimi3, Christoph J. Brabec3,4, Julian Stangl1, Maksym V. Kovalenko2,5 and Wolfgang Heiss1,3,4\\* \n\nThe evolution of real-time medical diagnostic tools such as angiography and computer tomography from radiography based on photographic plates was enabled by the development of integrated solid-state $\\pmb{x}$ -ray photon detectors made from conventional solid-state semiconductors. Recently, for optoelectronic devices operating in the visible and near-infrared spectral regions, solution-processed organic and inorganic semiconductors have also attracted a great deal of attention. Here, we demonstrate a possibility to use such inexpensive semiconductors for the sensitive detection of X-ray photons by direct photon-to-current conversion. In particular, methylammonium lead iodide perovskite $(C H_{3}N H_{3}P b l_{3})$ offers a compelling combination of fast photoresponse and a high absorption cross-section for $\\pmb{x}$ -rays, owing to the heavy Pb and I atoms. Solution-processed photodiodes as well as photoconductors are presented, exhibiting high values of $\\mathbf{x}.$ -ray sensitivity (up to $25\\upmu\\mathsf{c}\\mathsf{m G y}_{\\mathrm{air}}^{-1}\\mathsf{c m}^{-3})$ and responsivity $(1.9\\times10^{4}$ carriers/photon), which are commensurate with those obtained by the current solid-state technology. \n\nhe detection of X-ray photons is of utmost importance for a wide range of applications, from specific crystal structure determinations1 to radio astronomy2. The largest demand for X-ray detectors comes from medical radiography, where pixelarray detectors based on solid-state semiconductors are under development as a replacement for radiographic $\\mathrm{{flm}}s^{3-5}$ . Of the two currently available approaches to X-ray imaging—indirect conversion by the use of scintillators and direct conversion of X-ray photons into electrical current (for example, by photoconductivity)—the latter approach is reported to provide higher resolution4. Sensitive photoconduction is observable in various crystalline inorganic semiconductors under X-ray illumination, including amorphous $\\mathrm{Se}^{3,6}$ , crystalline $\\mathrm{Si^{7}}$ and $\\mathrm{CdTe}^{3,7}$ , but very few of these materials can be deposited uniformly onto the thin-film-transistor activematrix arrays needed for readout of the electronic signals in pixelarray detectors4,5,8 below the temperatures at which deterioration of the active matrix occurs. In this respect, solution-processed semiconductors such as those applied in photovoltaic and photoconducting devices operating in the visible or infrared spectral region9–12 may represent an appealing alternative, owing to their low-temperature, non-vacuum and large-scale deposition in the form of homogeneous films by inexpensive techniques such as ink-jet, slit and screen printing, spin-casting and spray-coating. Finding such solution-processable semiconductors with high photoconductivity under X-ray illumination is therefore a key prerequisite. Here, we report that methylammonium lead triiodide $(\\mathrm{MAPbI}_{3}$ , where MA is $\\mathrm{CH}_{3}\\mathrm{NH}_{3};$ ), a solution-processable organic– inorganic direct-gap semiconductor, can be used as a highly sensitive photoconductor for the direct conversion of X-ray photons into electrical current. Although solution processing at lower temperatures is generally thought to reduce the electronic quality of \n\nsemiconductors due to structural imperfections, numerous reports providing evidence of the very high suitability of such lead halide perovskites for optoelectronic applications have recently been presented. In particular, perovskite-based solar cells have rapidly progressed to certified power conversion efficiencies of up to $20\\%^{\\bar{13}-18}$ Thin films of $\\mathrm{MAPbI}_{3}$ have also been used in bright light-emitting-diodes19, as a lasing medium20 and in highly sensitive detectors operating in the visible spectral region21. \n\nFor X-ray detection, not only are the semiconducting properties of the active material important, but so is the nature of its atomic constituents. This is because X-ray absorption scales with atomic number $Z$ as $\\boldsymbol{Z^{4}}/A\\boldsymbol{E}^{3}$ , where $A$ is the atomic mass and $E$ is the X-ray photon energy. Thus, the absorption at photon energies of ${\\sim}10\\mathrm{keV}$ to $1\\mathrm{MeV}$ (plotted in Fig. 1a based on the atomic absorption coefficients22 of the individual constituents of $\\begin{array}{r}{\\mathbf{MAPbI}_{3}.}\\end{array}$ is dominated by the contribution of the $\\mathrm{Pb}$ ions. At these high energies, the absorption length is more than two orders of magnitude larger than in the visible range, even though $\\mathrm{Pb}$ is the second heaviest, after Bi, stable element in the periodic table. Thus, the ability to fabricate uniform semiconducting films with unusually large thicknesses, on the order of $10{-}100~{\\upmu\\mathrm{m}}.$ , is also a prerequisite for the optimization of X-ray detectors. In this study, such thicknesses are readily obtained by spray-coating solutions of $\\mathrm{MAPbI}_{3}$ dissolved in common polar solvents such as dimethylformamide (DMF, Supplementary Fig. 1). \n\nIn this proof-of-concept study, we successfully test two main device architectures: photovoltaic and photoconductive. Thin-film photovoltaic cells (photodiodes), in which charge separation is achieved by the built-in potential of a p–i–n junction, exhibit a specific X-ray sensitivity of $25~{\\upmu\\mathrm{C}}~\\mathrm{mGy}_{\\mathrm{air}}^{-1}\\mathrm{cm}^{-3}$ , which is commensurate with the performance of conventional solid-state semiconductor materials. In externally biased thick-film photoconductors, capable of absorbing a much larger portion of the incident X-rays, a similarly high X-ray sensitivity is obtained. Overall, up to ${\\sim}2\\times\\mathrm{i}0^{4}$ charge carriers are generated per each $8\\ensuremath{\\mathrm{\\keV}}$ photon from a conventional $\\mathrm{CuK}_{\\mathrm{a}}$ X-ray tube. \n\n![](images/1faeb2ac2e2ed942ed9aba392965c0c7f66e73c3da5cb05293afdc1f83c58790.jpg) \nFigure 1 | $M A P b\\mathsf{I}_{3}$ perovskite basic properties. a, Absorption coefficient and length as a function of photon energy, covering the infrared to $\\mathsf{X}$ -ray spectral region. b, Time-of-flight (TOF) transients for two bias directions, providing approximate electron and hole mobilities. c, Crystal structure of the perovskite: blue spheres, MA; black spheres, I; centres of the octahedrons, Pb. Inset: Cross-sectional micrograph of a spray-coated $M A P b|_{3}$ layer. \n\n# Photovoltaic cells \n\nWhen operated as solar cells, these devices take full advantage of the strong optical absorbance of the $\\mathrm{MAPbI}_{3}$ in the near-infrared and visible spectral regions (Fig. 1a), as well as the rather high carrier mobility (Fig. 1b) and long exciton diffusion lengths23–25 compared to those of other common solution-processed semiconductors. The beneficial transport properties are also related to the crystal structure of $\\mathrm{MAPbI}_{3}$ (Fig. 1c), comprising three-dimensionally interconnected $\\mathrm{PbI}_{6}$ octahedra, which leads to a relatively narrow bandgap $(1.56\\mathrm{eV})$ and small effective masses of the electrons and holes26. Furthermore, good crystallinity with large crystallite sizes ${>}250~\\mathrm{nm}$ ), seen as sharp peaks in their X-ray diffraction patterns (Supplementary Fig. 2), are also important attributes for efficient charge transport. \n\nFor the efficient operation of photovoltaic devices, an important condition is that the diffusion lengths of the minority carrier species should exceed the device thickness23. Recently demonstrated lead halide perovskite solar cells clearly fulfil this condition, resulting in high power conversion efficiencies of up to $20\\%$ (ref. 17). To harvest sunlight efficiently, active layer thicknesses on the order of $300\\mathrm{nm}$ are required, which match the absorption length (that is, inverse absorption coefficient, Fig. 1a) of $\\mathrm{MAPbI}_{3}$ in the visible and near-infrared spectral regions. The orders of magnitude higher absorption length in the X-ray spectral region, however, raises the question of whether solution-processed perovskite solar cells, which by default use rather thin absorbing layers, are applicable for the detection of X-rays at all. On the other hand, such photodiodes are nearly perfectly optimized for the efficient separation of photogenerated electrons and holes by the built-in electric potential. We therefore tested a $\\mathrm{{\\p-i-n}}$ type $\\mathrm{MAPbI}_{3}$ -based solar cell with poly (3,4-ethylenedioxythiophene) polystyrene sulphonate (PEDOT/ PSS) as the hole contact and the soluble fullerene-derivative phenyl- $C_{61}$ -butyric acid methyl ester (PCBM) as the electron contacts (Fig. 2a). Under AM1.5 illumination from a solar simulator, this device provided a power conversion efficiency of $10.4\\%$ (Fig. 2b), proving the efficient collection of photogenerated carriers. We then subjected this fully operational photodiode to illumination with a pulsed X-ray source ${75\\mathrm{keVp}}$ photon energy, ${\\sim}37\\mathrm{keV}$ on average), and a clear primary photocurrent response was observed under short-circuit conditions (without applying any bias). The solar cell measured the same $50\\mathrm{{Hz}}$ pulse train as was also detected by a commercial silicon photodiode reference detector with the help of a cerium-doped ytterbium aluminium garnet (YAG:Ce) scintillator sheet emitting at $530\\mathrm{nm}$ (Fig. 2c). The measured photocurrent density scales linearly with the averaged X-ray dose rate (Fig. 2d) and provides averaged values of up to $25\\mathrm{\\nA\\cm^{-2}}$ . These values can be recalculated as a specific sensitivity (in units of $\\upmu\\mathrm{C}\\mathrm{mGy}_{\\mathrm{air}}^{-1}\\mathrm{cm}^{-3},$ , which is a figure of merit for $\\mathrm{\\DeltaX}$ -ray detectors, by normalizing the averaged photocurrent by the dose rate (in air), the active area and the X-ray absorbing layer thickness. The resulting values (inset in Fig. 2d) are competitive with those exhibited by amorphous Se, which is the only large-area photoconductor material used in commercial clinical flat-panel-based X-ray imagers. The specific sensitivities of amorphous Se, depending on the operating field and thickness, have been reported to be in the range of $1{-}17\\upmu\\mathrm{C}\\ \\mathrm{mGy}_{\\mathrm{air}}^{-1}\\mathrm{cm}^{-3}$ (refs 27,28), whereas values of up to $25~{\\upmu\\mathrm{C}}~\\mathrm{mGy}_{\\mathrm{air}}^{-1}~\\mathrm{cm}^{-3}$ are obtained here. These results clearly demonstrate the great potential of $\\mathrm{MAPbI}_{3}$ for direct conversion of $\\mathrm{X}$ -ray radiation into mobile carriers. \n\n![](images/826b90507ee4d358c0d6e3f6ec099c0864039462f2fe46b0cecafd2fc5f0f428.jpg) \nFigure 2 | Photovoltaic device. a, Schematic of layer stacking of the $M A P b|_{3}$ -based $p-i-n$ photodiode. b, $J{-}V$ characteristics of the device in darkness and under AM1.5 illumination. c, Time-resolved short-circuit photocurrent under $\\mathsf{X}$ -ray exposure. The data shown in b and c are for a $\\mathsf{M A P b l}_{3}$ layer with thickness of $260\\pm60\\mathsf{n m}$ . d, Averaged short-circuit $\\mathsf{X}$ -ray photocurrent as function of dose rate. Inset: Sensitivity normalized to the active volume for $M A P b|_{3}$ layers with thicknesses of $260\\pm60~\\mathsf{n m}$ , $360\\pm80~\\mathsf{n m}$ and $600\\pm120\\mathrm{nm},$ respectively. \n\n# Photoconducting devices \n\nThe photovoltaic structure provides a high specific sensitivity (a value normalized by the volume of the active material), but a substantially improved response in the $\\mathrm{X}$ -ray regime could be expected for devices with much thicker active layers, with absorption lengths of up to ${\\sim}100\\ \\upmu\\mathrm{m}$ (Fig. 1a). Because this value is substantially larger than the measured minority carrier diffusion lengths in $\\mathrm{M}\\mathrm{\\bar{A}P b I}_{3}$ $(\\sim1\\upmu\\mathrm{m})^{23-25}$ , a sufficiently high external bias must be applied to provide efficient charge separation. Under external bias, lateral device architectures are advantageous compared to vertical ones because they are free of delicate interfaces between electron and hole extracting/blocking layers, which might lead to accelerated device degradation. Instead, they make use of two interdigitate gold contacts whose distance apart is approximately equivalent to the layer thickness (inset in Fig. 3a). As relatively high external fields are applied to such photoconductors, the device performance is mostly independent of the work function of the chosen electrode material, and is instead primarily dominated by the properties of the active layer. Thus, the main precondition for device preparation in this work is the ability to deposit uniform $\\operatorname{MAPbI}_{3}$ films with desired thicknesses onto patterned electrode structures. This was accomplished by spincasting to achieve layer thicknesses of up to $1{-}2~{\\upmu\\mathrm{m}}$ and by spray-coating to achieve much thicker films $(10-100~\\upmu\\mathrm{m}$ , Supplementary Fig. 1). \n\nSimilarly to the experiments with photovoltaic devices, we first tested the utility of a $\\mathrm{MAPbI}_{3}$ -based lateral photoconductor device for detecting photons in the visible spectral region. At these wavelengths, an optimal thickness of $1{-}2\\upmu\\mathrm{m}$ was estimated as necessary to exceed the absorption lengths. The high photon sensitivity of such a device is already seen in its $I{-}V$ characteristics (Supplementary Fig. 3). In darkness, a conductivity of $\\sim1.4\\times10^{-9}\\mathrm{Scm^{-1}}$ is measured, and this value increases by four orders of magnitude under white light illumination with an intensity of $20\\mathrm{mW}\\mathrm{cm}^{-2}$ . Furthermore, the responsivity spectrum, shown in Fig. 3a, closely reproduces the features of the absorption spectrum. The responsivity exceeds a value of $1\\mathrm{AW}^{-1}$ in almost the entire visible part of the light spectrum, which corresponds, by multiplication with the photon energy $\\cdot800\\mathrm{nm}$ is equivalent to $1.55\\mathrm{eV},$ ), to a product of external quantum efficiency and photoconducting gain of slightly above unity. Because the quantum efficiency is always less than 1, with the only exception being the case of multi-exciton generation taking place at energies well above the bandgap, the measured responsivity indicates the occurrence of low photoconductive gain in $\\mathrm{MAPbI}_{3}$ . Gain is observed when the carrier lifetime exceeds the carrier transit time, and thus high gain is often associated with carrier trapping10. Carrier trapping usually results in a slowing of the detector’s response. The photoconductors investigated herein, however, exhibit a very fast response. In particular, following laser excitation with short 10 ps pulses from a mode-locked laser, a pulse response with a full-width at half-maximum of 350 ps was measured by a sampling oscilloscope (inset in Fig. 3b). This short response time corresponds to a cutoff frequency of ${\\sim}3\\operatorname{GHz},$ which is higher than the recently reported maximum bandwidth of $3\\mathrm{MHz}$ in solution-processed perovskite photodetectors operating in the visible spectral region21. With $\\mathrm{MAPbI}_{3}$ being largely free of carrier trapping, the bandwidth is instead limited by the RC-constant of the device, which is substantially smaller in the lateral device geometry, leading to much faster operation as seen in this study. \n\n![](images/f9c974ca086d2d644c0bc6ea7f2c20d240717eb817c154171261257c82fce46c.jpg) \nFigure 3 | Visible and X-ray photoconductive devices. a, Responsivity and absorbance spectra of a $2-\\upmu\\mathrm{m}$ -thick $M A\\mathsf{P b l}_{3}$ perovskite film in the visible spectral region. Inset: Photoconducting device geometry with lateral interdigitate electrodes. b, Photoresponse to a pulsed laser (10 ps, $\\lambda=532\\:\\mathrm{nm};$ , providing a characteristic time at the full-width at half-maximum (FWHM) of 350 ps. c, $1-V$ characteristics of a $60\\mathrm{-}\\upmu\\mathrm{m}$ -thick $M A P b|_{3}$ perovskite photoconductor in darkness and under $\\mathsf{X}$ -ray illumination. d,e, Photograph (d) and corresponding X-ray image (e) of a leaf (Begonia obliqua L.), obtained with the photoconductor in c. f–i, $\\mathsf{X}$ -ray images revealing the contents of a Kinder Surprise egg and the chip and radiofrequency antenna integrated within an electronic key card. All scale bars are $10\\:\\mathrm{mm}$ . \n\nHaving established that $\\mathrm{MAPbI}_{3}$ is a fast and sensitive photoconductive material in the visible spectral region, we then investigated its response to $\\mathrm{X}$ -ray photons. As previously discussed, to absorb the majority of $\\mathrm{\\DeltaX}$ -ray photons to which a device is exposed, thicker active materials are required. For X-ray photoconductivity experiments, film thicknesses equal to or higher than the X-ray absorption length must be selected, which can be determined from the data presented in Fig. 1a or from the experimental thickness dependence of the transmittance (Supplementary Fig. 4). For a conventional $\\mathrm{CuK}_{\\mathrm{a}}$ X-ray tube source $(8\\mathrm{keV})$ , this thickness is $\\sim30\\upmu\\mathrm{m}$ . \n\nUnder ambient conditions, a photoconductor consisting of a $60~{\\upmu\\mathrm{m}}$ layer of $\\mathrm{MAPbI}_{3}$ exhibits a close to linear $I{-}V$ curve in darkness (Fig. 3c). Under X-ray irradiation of $1.4\\times10^{7}$ photons $\\mathrm{mm}^{-2}$ at a bias across the electrodes of $80\\mathrm{V}$ and with a spacing of $100\\upmu\\mathrm{m},$ a photocurrent density of $7\\upmu\\mathrm{Acm}^{-2}$ $40~\\mathrm{nA}$ photocurrent) was obtained, which is more than 100 times higher than the value obtained using photodiodes with submicrometre active layers. The responsivity of the detector reached $1.9\\times10^{4}$ carriers/photon. This high value is based on two contributions: impact ionization, known from electron dispersive $\\mathrm{\\DeltaX}$ -ray detectors29 and photoconducting gain. The theoretical multiplicity of impact ionization is given by the ratio of the X-ray photon energy to the ionization energy of the absorbing $\\mathrm{MAPbI}_{3}$ . Taking the latter value of $5\\mathrm{eV}$ for $\\mathrm{PbI}_{2}$ (ref. 29), the impact ionization could only account for $5\\times{10}^{3}$ charge carriers per photon. Thus, there must also be a contribution from photoconducting gain, which contributes to the observed sensitivity by a factor of at least 30. This value is clearly higher than that observed for the ${\\sim}500\\mathrm{-nm}$ -thick photoconductors under visible light illumination, and indicates considerably more charge trapping for the $60\\mathrm{-}\\upmu\\mathrm{m}$ -thick devices under $\\mathrm{\\DeltaX}$ -ray illumination. This observation can have several origins, including a less favourable electric field distribution in thick devices, trapping in highly excited states, a larger number of grain boundaries within the thicker films and, most importantly, the much smaller density of photoinduced carriers in thicker devices. Trap-induced photoconducting gain is in fact helpful for obtaining higher detector sensitivity, except when it leads to very slow response times, which is not observed in this study. \n\nA desirable property of a detector is a linear response as a function of intensity, such as that shown in Fig. 2d for the p–i–n diodes and in Supplementary Fig. 5 for the thick X-ray photoconductors, covering at least three orders of magnitude. Such a high dynamic range is promising for roentgenography (in medicine, security and so on), which is one of the most important applications of X-rays8,28. To test the applicability of $\\mathrm{MAPbI}_{3}$ devices for imaging, a single-element photoconductor was used, and various objects were $x,y.$ -scanned with the X-ray beam. As shown in Fig. 3d–i, well-resolved images could be obtained for several objects: the leaf of a house plant, a Kinder Surprise egg and an electronic card (used as a tag to identify products at the checkout of a shop). In all cases the X-ray images reveal details of the interior of the object that are not apparent externally: the veins of the Begonia obliqua L. leaf, the contents of the Kinder Surprise egg (a small guitar) and the circuit connected to a near-field radiofrequency antenna within the electronic card (see reference photos in Fig. 3). The X-ray images presented show sufficiently high contrast and dynamic range, with the spatial resolution limited only by the dimensions of the photodetector and the X-ray beam collimation. \n\nIn comparison to common X-ray detection technologies, typically based on elaborate high-vacuum deposition techniques, direct low-cost and low-temperature solution processing enables a wide range of possible device architectures and applications (for example, large-area X-ray scanners, required in medical diagnostics and for customs examinations, flexible X-ray scanners applied directly on the irregular contours of patients, and allprinted X-ray detectors). Nevertheless, certain properties of $\\mathrm{MAPbI}_{3}$ -based detectors require further improvement, including the mobility $\\mu$ and lifetime $\\tau,$ given that their product $\\mu\\tau$ (the carrier range) is an important controlling factor for the sensitivity27. This product term is usually extracted from the bias dependence of the responsivity30,31, which in this case provides a value of $2\\times10^{-7}\\mathrm{cm^{2}V^{-1}}$ (Supplementary Fig. 6). Values in the same range, between $4\\times10^{-7}$ and $1.3\\times\\mathrm{\\dot{1}0^{-\\ddot{6}}}\\mathrm{cm}^{2}\\mathrm{V}^{-1}$ , are also deduced from the measured mobility (Fig. 1c) and photoluminescence lifetimes26. Although these values are already comparable to those reported for amorphous selenium8,32 (the major material used in commercial X-ray imagers), X-ray detectors based on $\\mathrm{MAPbI}_{3}$ such as presented here might easily be improved in the future, for example by compositional engineering (using mixtures of halides such as $\\mathrm{MAPb(Br/Cl/I)}_{3})^{15,17,23,24}$ , by increasing the crystalline grain size33 and/or by smoothening the perovskite surfaces and interfaces. \n\nIn summary, we have presented the novel concept of applying solution-processed semiconductors for the detection of X-rays in both photoconductive and photovoltaic (p–i–n junction) device architectures. The X-ray sensitivity achieved by $\\mathrm{MAPbI}_{3}$ p–i–n photodiodes is comparable to those of established X-ray detector materials. The $\\mathrm{MAPbI}_{3}$ photoconductors, fabricated and tested under ambient conditions, show an almost ideal photoresponse in the near-infrared to visible range, with external quantum efficiencies close to $100\\%$ and fast response times corresponding to cutoff frequencies of $3\\operatorname{GHz}$ . In thick-film $(60\\upmu\\mathrm{m})$ photoconductors, ${\\sim}100$ -fold higher photocurrent densities are observed under X-ray illumination than in the $\\operatorname{p-i-n}$ diodes. This higher responsivity is achieved by matching the layer thickness, and is partly caused by a moderate photoconducting gain. The low-temperature solution processing of $\\mathrm{MAPbI}_{3}$ from molecular precursors suggests great promise for facile integration into inexpensive industrial readout electronics for imaging, applicable for scientific purposes and medical diagnostics. \n\n# Methods \n\nMethods and any associated references are available in the online version of the paper. \n\n# Received 27 January 2015; accepted 16 April 2015; published online 25 May 2015 \n\n# References \n\n1. Tegze, M. & Faigel, G. X-ray holography with atomic resolution. Nature 380, 49–51 (1996). \n2. Shanmugam, M. et al. Alpha particle X-ray spectrometer (APXS) on-board Chandrayaan-2 rover. Adv. Space Res. 54, 1974–1984 (2014). \n3. Yaffe, M. J. & Rowlands, J. A. X-ray detectors for digital radiography. Phys. Med. Biol. 42, 1–39 (1997). \n4. Kasap, S. O. & Rowlands, J. A. Direct-conversion flat-panel X-ray image sensors for digital radiography. Proc. IEEE 90, 591–604 (2002). \n5. Moy, J. P. Recent developments in X-ray imaging detectors. Nucl. Instrum. Meth. Phys. Res. 442, 26–37 (2000). \n6. Zhao, W. & Rowlands, J. A. X-ray imaging using amorphous selenium: feasibility of a flat panel self-scanned detector for digital radiology. J. Med. Phys. 22, 1595–1604 (1995). \n7. Oh, K. M. et al. Measurement of the electrical properties of a polycrystalline cadmium telluride for direct conversion flat panel X-ray detector. J. Instrum. 9, P01010 (2014). \n8. Kasap, S. et al. Amorphous and polycrystalline photoconductors for direct conversion flat panel X-ray image sensors. Sensors 11, 5112–5157 (2011). \n9. Halls, J. J. M. et al. Efficient photodiodes from interpenetrating polymer networks. Nature 376, 498–500 (1995). \n10. Konstantatos, G. et al. Ultrasensitive solution-cast quantum dot photodetectors. Nature 442, 180–183 (2006). \n11. Keuleyan, S., Lhuillier, E., Brajuskovic, V. & Guyot-Sionnest, P. Mid-infrared HgTe colloidal quantum dot photodetectors. Nature Photon. 5, 489–493 (2011). \n12. Rauch, T. et al. Near-infrared imaging with quantum-dot-sensitized organic photodiodes. Nature Photon. 3, 332–336 (2009). \n13. Chung, I., Lee, B., He, J., Chang, R. P. & Kanatzidis, M. G. All-solid-state dyesensitized solar cells with high efficiency. Nature 485, 486–489 (2012). \n14. Gratzel, M. The light and shade of perovskite solar cells. Nature Mater. 13, 838–842 (2014). \n15. Green, M. A., Ho-Baillie, A. & Snaith, H. J. The emergence of perovskite solar cells. Nature Photon. 8, 506–514 (2014). \n16. Im, J. H., Jang, I. H., Pellet, N., Gratzel, M. & Park, N. G. Growth of $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ cuboids with controlled size for high-efficiency perovskite solar cells. Nature Nanotech. 9, 927–932 (2014). \n17. Jeon, N. J. et al. Compositional engineering of perovskite materials for highperformance solar cells. Nature 517, 476–480 (2015). \n18. Zhou, H. et al. Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). \n19. Tan, Z. K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nature Nanotech. 9, 687–692 (2014). \n20. Xing, G. et al. Low-temperature solution-processed wavelength-tunable perovskites for lasing. Nature Mater. 13, 476–480 (2014). \n21. Dou, L. et al. Solution-processed hybrid perovskite photodetectors with high detectivity. Nature Commun. 5, 5404 (2014). \n22. Grodstein, G. W. X-ray Attenuation Coefficients from 10 keV to 100 MeV (US Department of Commerce, National Bureau of Standards, 1957). \n23. Stranks, S. D. et al. Electron–hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n24. Wehrenfennig, C., Eperon, G. E., Johnston, M. B., Snaith, H. J. & Herz, L. M. High charge carrier mobilities and lifetimes in organolead trihalide perovskites. Adv. Mater. 26, 1584–1589 (2014). \n25. Xing, G. et al. Long-range balanced electron- and hole-transport lengths in organic–inorganic $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ . Science 342, 344–347 (2013). \n26. Baikie, T. et al. Synthesis and crystal chemistry of the hybrid perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3};$ ) $\\mathrm{PbI}_{3}$ for solid-state sensitised solar cell applications. J. Mater. Chem. A 1, 5628–5641 (2013). \n27. Kasap, S. O. X-ray sensitivity of photoconductors: application to stabilized a-Se. J. Phys. D 33, 2853–2865 (2000). \n28. Schieber, M. et al. Thick films of X-ray polycrystalline mercuric iodide detectors. J. Cryst. Growth 225, 118–123 (2001). \n29. Juška, G. & Arlauskas, K. Impact ionization and mobilities of charge carriers at high electric fields in amorphous selenium. Phys. Status Solidi A 59, 389–393 (1980). \n30. Street, R. A. et al. Comparison of $\\mathrm{PbI}_{2}$ and $\\mathrm{HgI}_{2}$ for direct detection active matrix X-ray image sensors. J. Appl. Phys. 91, 3345–3355 (2002). \n31. Kabir, M. Z. & Kasap, S. O. Charge collection and absorption-limited sensitivity of X-ray photoconductors: applications to a-Se and $\\mathrm{HgI}_{2}$ . Appl. Phys. Lett. 80, 1664–1666 (2002). \n32. Masuzawa, T. et al. Development of an amorphous selenium-based photodetector driven by a diamond cold cathode. Sensors 13, 13744–13778 (2013). \n33. Nie, W. et al. High-efficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 347, 522–525 (2015). \n\n# Acknowledgements \n\nThe authors acknowledge the Austrian Science Fund FWF for financial support through the SFB project IR_ON. A part of the research was also performed at the Energie Campus Nürnberg and supported by funding through the ‘Aufbruch Bayern’ initiative of the state of Bavaria. M.K. and S.Y. acknowledge partial financial support from the European Union through the FP7 (ERC Starting Grant NANOSOLID, GA no. 306733). The authors thank V. Sassi, S. Roters, E. Nusko, W. Grafeneder and M. Bodnarchuk for technical assistance. S.Y. thanks M. Hardman for assisting with the selection of plants for X-ray imaging. The authors thank N. Stadie for reading the manuscript. \n\n# Author contributions \n\nThe manuscript was prepared with contributions from all authors. S.Y., M.S., D.K. and J.S. performed the work with the photoconductors. S.S., H.A., G.M. and M.R. prepared and tested the solar cell devices. W.H., G.M., C.B. and M.K. planned and supervised the work and had major input in the writing of the manuscript. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to W.H. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. \n\n# Methods \n\nSynthesis of $\\mathbf{MAPbI}_{3}$ perovskite. A methylamine solution $(33~\\mathrm{wt\\%})$ ) in absolute ethanol, hydriodic acid $(57\\mathrm{wt\\%})$ ) in water $(99.99\\%$ trace metals basis) and anhydrous diethyl ether were obtained from Sigma-Aldrich. Lead(II) iodide $(99.9985\\%$ ) and anhydrous DMF were purchased from Alfa Aesar. Absolute ethanol was supplied by Merck. All chemicals were used as received. MAI $\\mathrm{'CH}_{3}\\mathrm{NH}_{3}\\mathrm{I})$ was synthesized by a simple neutralization reaction between methylamine and hydriodic acid. Into $100\\mathrm{ml}$ absolute ethanol, $35~\\mathrm{ml}$ of a methylamine solution $(33\\mathrm{~wt\\%})$ ) and $20~\\mathrm{ml}$ hydroiodic acid $(57\\mathrm{~wt\\%})$ ) were added. The mixture was vigorously stirred and cooled to room temperature in a water bath. After $30~\\mathrm{min}$ , the solvent was removed by a rotary evaporator and a brown crystalline powder was collected. The powder was washed with $100~\\mathrm{ml}$ of anhydrous diethyl ether, which was stirred with the powder for $30\\mathrm{min}$ . After decanting the solvent, the washing step was repeated. For final purification, the powder was refluxed with $100~\\mathrm{ml}$ of ethyl ether for $^{2\\mathrm{h}}$ . The dispersion was then cooled to $-18{}^{\\circ}\\mathrm{C}$ and vacuum-filtered through a Schott funnel. The final white powder was dried under vacuum for $24\\mathrm{h}$ and stored under a nitrogen atmosphere. $\\mathbf{MAPbI}_{3}$ was prepared inside a glove box by mixing MAI and $\\mathrm{PbI}_{2}$ in a 1:1 molar ratio in anhydrous DMF. \n\nDevice preparation. The p–i–n photodiode consisted of four spin-cast layers (Fig. 2a). A hole-conducting layer of PEDOT:PSS ( $\\sim50~\\mathrm{nm}$ , VP Al 4083 from Heraeus Clevios) was deposited on top of an indium-tin-oxide-covered glass substrate $(6\\Omega\\bigtriangledown^{-1}\\bigtriangledown^{-1},$ ), followed by a layer of light-absorbing $\\operatorname{MAPbI}_{3}$ semiconductor. This perovskite layer was processed from either a 25, 30 or $40\\mathrm{wt\\%}$ $\\operatorname{MAI:PbI}_{2}$ precursor solution in anhydrous DMF, giving layer thicknesses of $260\\pm60~\\mathrm{nm}$ , $360\\pm80~\\mathrm{{nm}}$ and $600\\pm120\\ \\mathrm{nm}$ , respectively. The film was annealed for at least $90~\\mathrm{{min}}$ at $90~^{\\circ}\\mathrm{C}$ . To finish the device stack, an electron/hole conducting/blocking PCBM layer ${\\bf\\tilde{\\Psi}}\\sim100~\\mathrm{nm}$ ) was added, followed by a ZnO layer ${\\sim}40~\\mathrm{nm}$ , nanoparticular $\\mathrm{znO}$ dispersion provided by Nano-grade) and finally followed by a Ag top contact ( ${\\sim}100\\ \\mathrm{nm}$ , thermal evaporation deposited). All processing steps were performed in a dry $\\Nu_{2}$ glovebox. For the preparation of photoconductors, a $40\\mathrm{wt\\%}$ DMF solution was used. The solution was either spin-cast or spray-coated onto a glass substrate with interdigitate electrodes ( $\\mathrm{\\Au/Ti}$ with a width of $1.8\\mathrm{mm}$ and distances between 10 and $100\\upmu\\mathrm{m}$ , depending on the thickness of the perovskite layer). The perovskite layer was dried at $130^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ . \n\nMaterial and device characterization. The active layer thickness was determined by atomic force microscopy (Dimension 3100 from Veeco). Powder X-ray diffraction was performed with a custom-built Huber diffractometer equipped with a rotating Cu anode (Bruker AXS M18XCE). A double-bent parabolic multilayer was used to provide a parallel beam and a one-dimensional Bruker Vantec-1 detector was used for signal detection. Absorption spectra of $\\mathrm{MAPbI}_{3}$ layers were measured using a vis–NIR integrating sphere. Illumination was performed with a tungsten lamp and the spectra were collected with an AvaSpec-2048-SPU spectrometer. Photoconductivity measurements were performed according to ref. 34. Transient photoconductivity and time-of-flight measurements were carried out under excitation with 10 ps laser pulses from a frequency-doubled YAG:Nd laser, emitting at $\\lambda=532\\mathrm{nm}$ (Duettino from Time-Bandwidth) with $1-50\\upmu\\mathrm{J}$ pulse energies. The transients, averaged over 128 pulses, were recorded by a Tektronix 1102 digital oscilloscope with $100~\\mathrm{MHz}$ bandwidth (time-of-flight) or a Tektronix 11801C digital sampling oscilloscope equipped with a $20\\mathrm{GHz}$ sampling head. The steady-state photocurrent measurements of the p–i–n solar cell were performed with a Keithley 2400 instrument under AM1.5 illumination from a Newport Oriel Sol1A solar simulator. \n\nX-ray absorption and X-ray response were measured with the same instrument as used for X-ray diffraction. A $1\\times\\mathrm{1~mm}^{2}$ parallel beam of $\\mathrm{CuK}_{\\mathrm{a}}$ radiation was obtained after a pair of crossed slits. A commercial diffractometer detector (Bruker Vantec-1) was used for calibration of the $\\mathrm{\\DeltaX}$ -ray intensity. This was replaced by the $\\operatorname{MAPbI}_{3}$ photoconducting sample for its characterization. For X-ray absorption imaging, the imaged objects were moved into the X-ray beam by a two-dimensional scanner. All measurements were performed in complete darkness. The sample was biased with voltages up to $40\\mathrm{V}$ across an electrode distance of $100\\upmu\\mathrm{m}$ . The bias was applied by a Keithley 236 SMU and the chopped signal was recorded by a Stanford Research 830 lock-in amplifier. Control experiments were also made with plain electrodes (not covered by perovskites) to determine whether the photon currents were due to air ionization by X-rays or other artefacts. All X-ray absorbance measurements were performed and all images were collected with the same $\\mathrm{MAPbI}_{3}$ photoconductor, held in an ambient atmosphere. During all measurements, no degradation in detector sensitivity was observed. \n\nThe pulsed photocurrent of the p–i–n solar cell was recorded at $0\\mathrm{V}$ bias with a FEMTO DLPCA-200 transimpedance amplifier and a Tektronix DPO-2024 oscilloscope. The pulsed X-ray source (Nanodor 1 from Siemens) was operated with a tungsten anode and $75\\mathrm{kVp}$ acceleration voltage at $50\\ \\mathrm{Hz}$ . The X-ray dose was measured with an Iba Dosimax plus dosimeter, and attenuation of the X-ray exposure was achieved with a stack of $27-upmu\\mathrm{m}$ -thick lead foils. \n\n# References \n\n34. Yakunin, S. et al. High infrared photoconductivity in films of arsenic-sulfideencapsulated lead-sulfide nanocrystals. ACS Nano 8, 12883–12894 (2014). " + }, + { + "id": "10.1126_science.aah5557", + "DOI": "10.1126/science.aah5557", + "DOI Link": "http://dx.doi.org/10.1126/science.aah5557", + "Relative Dir Path": "mds/10.1126_science.aah5557", + "Article Title": "Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance", + "Authors": "Saliba, M; Matsui, T; Domanski, K; Seo, JY; Ummadisingu, A; Zakeeruddin, SM; Correa-Baena, JP; Tress, WR; Abate, A; Hagfeldt, A; Grätzel, M", + "Source Title": "SCIENCE", + "Abstract": "All of the cations currently used in perovskite solar cells abide by the tolerance factor for incorporation into the lattice. We show that the small and oxidation-stable rubidium cation (Rb+) can be embedded into a cation cascade to create perovskite materials with excellent material properties. We achieved stabilized efficiencies of up to 21.6% (average value, 20.2%) on small areas (and a stabilized 19.0% on a cell 0.5 square centimeters in area) as well as an electroluminescence of 3.8%. The open-circuit voltage of 1.24 volts at a band gap of 1.63 electron volts leads to a loss in potential of 0.39 volts, versus 0.4 volts for commercial silicon cells. Polymer-coated cells maintained 95% of their initial performance at 85 degrees C for 500 hours under full illumination and maximum power point tracking.", + "Times Cited, WoS Core": 3166, + "Times Cited, All Databases": 3333, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000387816500039", + "Markdown": "of photochemical and environmental stresses. X-ray diffraction (XRD) (Fig. 4B) analysis showed that performance degradation corresponded to the decomposition of the crystalline perovskite material into $\\mathrm{PbI_{2}}$ , which was not observed for the fully coated devices (see section 6 in the supplementary materials). \n\nGiven the stabilizing effect of the fluoropolymeric coating applied on both sides of the cells, a second aging test was designed to verify the stability of the front/back-coated PSCs under real outdoor atmospheric conditions, where temperature variations, precipitation phenomena, and pollution are typically encountered. A batch of five cells was exposed on the terrace of the Politecnico di Torino building in Turin $(45^{\\circ}06\\mathrm{N},$ , $7^{\\circ}66^{\\prime}\\mathrm{E},$ ), located in northwest Italy, in a humid subtropical climate zone from October to December 2015. The PSCs were subjected to highly variable climatic conditions, as outdoor temperatures ranged from $-3^{\\circ}$ to $+27^{\\circ}\\mathrm{C},$ and 27 out of 92 days were characterized by heavy rain and storms (33), as shown in Fig. 4C. The front/back-coated PSCs exhibited long-term stability retaining $95\\%$ of their initial efficiency after this test by (i) protecting the perovskite from UV radiation, converting it into exploitable visible photons; (ii) acting as a moisture barrier, thus preventing hydrolytic phenomena of the perovskite material; and (iii) keeping the front electrode clean by means of the easy-cleaning characteristics of this fluorinated polymer. Similar results were found for outdoor tests performed during Summer 2016, and the data collected are available in section 7 in the supplementary materials. \n\nTo demonstrate the water resistance of the photopolymerized fluorinated coatings, we kept five solar cells for 1 month in a closed chamber in the presence of a beaker containing boiling water $95\\%$ RH, fig. S1C), and the photovoltaic response was evaluated once a week. After 1 month, four of the five cells withstood the strong aging conditions and remarkably retained $96\\pm2\\%$ of their initial PCE. Only one device lost $95\\%$ of its initial efficiency after the first week. After inspection, we found a small area on the back side of the solar cell not thoroughly coated by the fluoropolymeric layer. The nonhomogeneous deposition of the coating caused a gradual hydrolysis of the underlying perovskite layer. We also dipped the front/back-coated devices into water. After 1 day of immersion, no changes in their photovoltaic performance were observed. \n\n11. Y. Rong, L. Liu, A. Mei, X. Li, H. Han, Adv. Energy Mater. 5, 1501066 (2015). \n12. T. Leijtens et al., Adv. Energy Mater. 5, 1500963 (2015). \n13. J. P. Correa Baena et al., Energy Environ. Sci. 8, 2928–2934 (2015). \n14. J. P. Correa-Baena et al., Adv. Mater. 28, 5031–5037 (2016). \n15. H. C. Weerasinghe, Y. Dkhissi, A. D. Scully, R. A. Caruso, Y. B. Cheng, Nano Energy 18, 118–125 (2015). \n16. I. Hwang, I. Jeong, J. Lee, M. J. Ko, K. Yong, ACS Appl. Mater. Interfaces 7, 17330–17336 (2015). \n17. M. Kaltenbrunner et al., Nat. Mater. 14, 1032–1039 (2015). \n18. J. You et al., Nat. Nanotechnol. 11, 75–81 (2016). \n19. K. Domanski et al., ACS Nano 10, 6306–6314 (2016). \n20. X. Li et al., Nat. Chem. 7, 703–711 (2015). \n21. A. Mei et al., Science 345, 295–298 (2014). \n22. L. Zhang et al., J. Mater. Chem. A 3, 9165–9170 (2015). \n23. W. Li et al., Energy Environ. Sci. 9, 490–498 (2016). \n24. Materials and methods are available as supplementary materials on Science Online. \n25. F. Bella et al., Adv. Funct. Mater. 26, 1127–1137 (2016). \n26. L. R. Wilson, B. S. Richards, Appl. Opt. 48, 212–220 (2009). \n27. D. Bi et al., Sci. Adv. 2, e1501170 (2016). \n28. F. Giordano et al., Nat. Commun. 7, 10379 (2016). \n29. D. Liu, T. L. Kelly, Nat. Photonics 8, 133–138 (2014). \n\n# SOLAR CELLS \n\n30. J.-H. Im, I.-H. Jang, N. Pellet, M. Grätzel, N.-G. Park, Nat. Nanotechnol. 9, 927–932 (2014). \n31. G. Griffini, M. Levi, S. Turri, Sol. Energy Mater. Sol. Cells 118, \n36–42 (2013). \n32. G. Griffini, M. Levi, S. Turri, Prog. Org. Coat. 77, 528–536 (2014). \n33. Il Meteo; http://www.ilmeteo.it/meteo/Torino (accessed September 2016). \n\n# ACKNOWLEDGMENTS \n\nAuthors from EPFL thank the Swiss National Science Foundation, the NRP 70 “Energy Turnaround,” the 9th call proposal 906 (CONNECT PV), SNF-NanoTera, and the Swiss Federal Office of Energy (SYNERGY) for financial support. All data used in this study are included in the main text and in the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/354/6309/203/suppl/DC1 \nMaterials and Methods \nSupplementary Text Sections 1 to 7 \nFigs. S1 to S8 \nReferences (34–40) \n21 June 2016; accepted 20 September 2016 \nPublished online 29 September 2016 \n10.1126/science.aah4046 \n\n# REFERENCES AND NOTES \n\n1. H. S. Kim et al., Sci. Rep. 2, 591 (2012). \n2. M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami, H. J. Snaith, Science 338, 643–647 (2012). \n3. H. Zhou et al., Science 345, 542–546 (2014). \n4. M. Liu, M. B. Johnston, H. J. Snaith, Nature 501, 395–398 (2013). \n5. J. Burschka et al., Nature 499, 316–319 (2013). \n6. National Center for Photovoltaics (NCPV) at the National Renewable Energy Laboratory (NREL); http://www.nrel.gov/ ncpv (accessed July 2016). \n7. N. G. Park, Mater. Today 18, 65–72 (2015). \n8. J. Seo, J. H. Noh, S. I. Seok, Acc. Chem. Res. 49, 562–572 (2016). \n9. H. S. Jung, N. G. Park, Small 11, 10–25 (2015). \n10. T. A. Berhe et al., Energy Environ. Sci. 9, 323–356 (2016). \n\n# Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance \n\nMichael Saliba,1\\*† Taisuke Matsui, $^{1,2_{+}}$ Konrad Domanski,1† Ji-Youn Seo,1 Amita Ummadisingu,1 Shaik M. Zakeeruddin,1 Juan-Pablo Correa-Baena,3 Wolfgang R. Tress,1 Antonio Abate,1 Anders Hagfeldt,3 Michael Grätzel1\\* \n\nAll of the cations currently used in perovskite solar cells abide by the tolerance factor for incorporation into the lattice. We show that the small and oxidation-stable rubidium cation $(\\mathsf{R b}^{+})$ can be embedded into a “cation cascade” to create perovskite materials with excellent material properties. We achieved stabilized efficiencies of up to $21.6\\%$ (average value, $20.2\\%$ ) on small areas (and a stabilized $19.0\\%$ on a cell 0.5 square centimeters in area) as well as an electroluminescence of $3.8\\%$ . The open-circuit voltage of 1.24 volts at a band gap of 1.63 electron volts leads to a loss in potential of 0.39 volts, versus 0.4 volts for commercial silicon cells. Polymer-coated cells maintained $95\\%$ of their initial performance at $85^{\\circ}\\mathsf{C}$ for 500 hours under full illumination and maximum power point tracking. \n\now-cost perovskite solar cells (PSCs) have achieved certified power conversion efficiencies (PCEs) of $22.1\\%$ $(I)$ . The organicinorganic perovskites used for photovoltaics (PV) have an $\\mathrm{AMX_{3}}$ formula that comprises \na monovalent cation, A [cesium ${\\mathrm{Cs}}^{+}$ , methylam \nmonium (MA) $\\mathrm{CH_{3}N H_{3}}^{+}$ , or formamidinium (FA) \n$\\mathrm{CH_{3}(N H_{2})_{2}}^{+}]$ ; a divalent metal, M $\\mathrm{{(Pb^{2+}}}$ or $\\mathrm{Sn^{2+}}$ ); \n\nand an anion, X $\\mathrm{\\Omega^{\\mathrm{\\prime}}}$ , $\\mathrm{Br}^{-}$ , or I–). The highestefficiency perovskites are Pb-based with mixed MA/FA cations and $\\mathrm{Br/I}$ halides (2–4). Recently, Cs was used to explore more complex cation combinations: Cs/MA, Cs/FA, and Cs/MA/FA (5–9). These perovskite formulations exhibit unexpected properties. For example, Cs/FA mixtures suppress halide segregation, enabling band gaps for perovskite/silicon tandems (10). The $\\mathrm{{Cs/MA/}}$ FA-based solar cells are more reproducible and thermally stable than MA/FA mixtures (9). \n\nIn general, increasing the perovskite complexity is motivated by the need to improve stability by adding more inorganic elements and increasing the entropy of mixing, which can stabilize ordinarily unstable materials (such as the “yellow,” nonphotoactive phase of $\\mathrm{FAPbI_{3}}$ that can be avoided by using small amounts of the otherwise unstable $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3},$ ) $(6,7)$ . However, all combinations of Cs, MA, and FA cations were selected because each individually forms a photoactive perovskite “black” phase (11–13). \n\n![](images/1201724aab55f79a02d0efd9bcd5bc3475f80db524d4e48ebf6396bac54eb806.jpg) \nFig. 1. Tolerance factor and perovskites at different temperatures. (A) Tolerance factor of $\\mathsf{A P b l}_{3}$ perovskite with the oxidation-stable A (Li, Na, K, Rb, or Cs) and MA or FA (see table S1 for detailed calculations and ionic radii). Empirically, perovskites with a tolerance factor between 0.8 and 1.0 (dashed lines) show a photoactive black phase (solid circles) as opposed to nonphotoactive phases (open circles). Rb (red open circle) is very close to this limit, making it a candidate for integration into the perovskite lattice. (B) $\\mathsf{C s P b l}_{3}$ [(a) to (c)] and ${\\mathsf{R b}}{\\mathsf{P b}}|_{3}$ [(d) to (f)] at $28^{\\circ}$ , $380^{\\circ},$ , or $460^{\\circ}\\mathrm{C}$ . Irreversible melting for both compounds occurs at $460^{\\circ}\\mathrm{C}$ . ${\\mathsf{R b}}{\\mathsf{P b}}|_{3}$ never shows a black phase. \n\n![](images/7ba8621d6dd4f3c6833e3854d7d74a729c2c25ee52170b6c35023843a23172f3.jpg) \nFig. 2. Characterization of unannealed and annealed films. (A) UV-vis (dashed lines) and PL (solid lines) of unannealed MAFA (black) and RbCsMAFA (red) films. The inset images show fluorescence microscopy measurements (image size ${\\sim}26\\upmu\\mathrm{m}\\times26\\upmu\\mathrm{m})$ of MAFA and RbCsMAFA films. Each image is an overlay of three emission ranges sampled from 640 to $650\\mathsf{n m}$ (assigned as green), 680 to 690 nm (blue), and 725 to $735\\mathsf{n m}$ (red).The colors were chosen to ensure easily discernible features. (B) XRD data of the unannealed MAFA and RbCsMAFA films. (C) UV-vis (dashed lines) and PL (solid lines) of MAFA (black) and RbCsMAFA (red) films annealed at $100^{\\circ}\\mathrm{C}$ for 1 hour. (D) XRD data of the annealed MAFA and RbCsMAFA films. The $\\mathsf{P b l}_{2}$ and yellow-phase peaks are denoted as # and d, respectively. \n\nFurther progress requires exploration of a wider circle of cations. Unfortunately, most monovalent cations are mismatched to sustain a photoactive $\\mathrm{\\APbI_{3}}$ perovskite with an appropriate Goldschmidt tolerance factor $[t=(r_{\\mathrm{A}}+r_{\\mathrm{I}})/\\sqrt{2}\\ (r_{\\mathrm{Pb}}+r_{\\mathrm{I}})$ , where $r$ is ionic radius] between 0.8 and 1.0 $(I4,I5)$ , rendering almost all elemental cations too small for consideration. We illustrate this point in Fig. 1A, which shows tolerance factor calculations for the alkali metals (Li, Na, K, Rb, Cs) as well as MA and FA (see table S1 for numeric values and ionic radii). We selected specifically the alkali metals that are oxidation-stable monovalent cations, as these would have a stability advantage over oxidation-prone $\\mathrm{{Pb/Sn}}$ mixtures that have distorted material electronic properties $(I6)$ . \n\nThe tolerance factor shows that only $\\mathrm{CsPbI_{3}},$ , $\\mathbf{MAPbI_{3}},$ , and $\\mathrm{FAPbI_{3}}$ fall into the range of “established perovskites” with a black phase. Li, $\\mathrm{{Na,}}$ and K are clearly outside of the range, whereas $\\mathrm{\\RbPbI_{3}}$ only misses by a small margin. The ionic radii of Cs and Rb are 167 pm and $152\\mathrm{pm}$ , respectively. This small difference still has a large impact, with $\\mathrm{\\RbPbI_{3}}$ and $\\mathrm{CsPbI_{3}}$ drawing the demarcation line between photoactive black perovskite and photoinactive yellow nonperovskite phases. As shown by heating $\\mathrm{CsPbI_{3}}$ and $\\mathrm{\\RbPbI_{3}}$ films at different temperatures (Fig. 1B), both films are yellow at $28^{\\circ}\\mathrm{C}$ ; upon heating to $380^{\\circ}\\mathrm{C},$ only $\\mathrm{CsPbI_{3}}$ turns black, whereas $\\mathrm{\\RbPbI_{3}}$ remains yellow. At $460^{\\circ}\\mathrm{C}$ , both films start melting irreversibly, without $\\mathrm{RbPbI}_{3}$ ever showing a black phase; this is consistent with the observations of Trots and Myagkota $(I7)$ . Thus, only $\\mathrm{CsPbI_{3}}$ has a black phase, which explains why Rb has so far not been used for PSCs despite its desirable oxidation stability. \n\nIn this work, we propose embedding $\\mathrm{{Rb}^{+}}$ , only slightly smaller than ${\\mathrm{Cs}}^{+}$ , into a photoactive perovskite phase using multiple A-cation formulations. We retain FA as the majority cation because of the beneficial, red-shifted band gap. We identify four previously unexplored combinations: RbFA, RbCsFA, RbMAFA, and RbCsMAFA. In (18) and figs. S1 to S3, following the antisolvent approach pioneered by Jeon et al. (2), we present device data on a glass/fluorine-doped tin oxide/compact $\\mathrm{TiO_{2}}$ /mesoporous $\\mathrm{TiO_{2}}$ perovskite/spiro-OMeTAD [2,2′,7,7′-tetrakis(N,N-di- $p$ -methoxyphenylamine)- 9,9′-spirobifluorene]/Au architecture. [See fig. S4A for a cross-sectional scanning electron microscopy (SEM) image and fig. S4C for an image of typical devices.] All preparation details are given in (18). We use the nomenclature of RbFA, RbCsFA, RbMAFA, and RbCsMAFA to denote the entire perovskite compounds at the optimized values found in (18) (usually achieved with an addition of 5 to $10\\%$ Rb). \n\nReasonable device performances were reached with RbFA $(14\\%)$ , RbCsFA $(19.3\\%)$ ),RbMAFA $(19.2\\%)$ ) [comparable to CsFA $(20\\%)],$ and CsMAFA $(19.2\\%)$ , as shown in figs. S1 to S3 (measured on a device area of $0.16\\mathrm{cm}^{2\\cdot}$ ). Thus, Rb can stabilize the black phase of FA perovskite and be integrated into PSCs, despite not being suitable as a pure $\\mathrm{\\RbPbI_{3}}$ compound. Surprisingly, RbCsMAFA (with $5\\%$ Rb; fig. S3) resulted in PCEs of $20.6\\%$ , with an open-circuit voltage $V_{\\mathrm{{oc}}}$ of $\\mathrm{1186~mV}$ (18). Hence, we focus below on RbCsMAFA to substantiate the impact of the $\\mathrm{{Rb}^{+}}$ integration approach for PSCs. \n\nWe investigated the starting condition of the crystallization process for the RbCsMAFA compound upon annealing at $100^{\\circ}\\mathrm{C}$ , which is needed to fully crystallize the perovskite films. In Fig. 2A, we present the ultraviolet-visible (UV-vis) and photoluminescence (PL) data of the unannealed MAFA and RbCsMAFA films. Whereas MAFA showed several PL peaks with maxima ranging from 670 to $790\\mathrm{nm}$ , the RbCsMAFA film had a narrow peak at $770\\mathrm{nm}$ attributable to perovskite. The insets in Fig. 2A are fluorescence microscopy maps of the surface of the unannealed films, showing that the MAFA films comprise various emissive species that force the preannealed film to crystallize with inhomogeneous starting conditions. However, the RbCsMAFA films were emissive in a narrow range and began to crystallize from more homogeneous conditions. Thus, the addition of the inorganic cations enforced a crystallization that starts with a photoactive perovskite phase (near the final emission after annealing) instead of a mixture of varying emissions that need to converge toward the final emission (see Fig. 2C). These results are consistent with the high reproducibility and lack of yellow phase in the RbCsMAFA films. \n\n![](images/ef1a848081e2c71aabad8a8cae60dca58c29065dc9bafc7a0ccc9b1c8fcdc1da.jpg) \nFig. 3. Efficiency, open-circuit voltage, electroluminescence, and high-temperature stability of the bestperforming RbCsMAFA solar cell. (A) Current density–voltage $(J-V)$ curve, taken at $10\\mathrm{mVs^{-1}}$ scan rate, of the solar cell with $21.8\\%$ efficiency $(V_{\\mathrm{oc}}=1180~\\mathrm{mV}$ , $J_{\\mathrm{sc}}=22.8\\mathsf{m A c m}^{-2}$ , and ${\\sf F F}=81\\%$ ).The forward and reverse scan is shown in table S2.The inset shows the scan rate–independent MPP tracking for $60\\mathrm{s}$ , \nefficiency of $21.6\\%$ at $977\\mathrm{mV}$ and $22.1\\mathsf{m A}\\mathsf{c m}^{-2}$ (displayed as triangles in visible red emission even under ambient light. At the same time, the right the $J-V$ and MPP scans). (B) $J-V$ curve of the highest- $\\cdot V_{\\mathrm{{oc}}}$ device. The inset area can be operated as a solar cell or a photodetector. (D) Thermal stability shows the $V_{\\mathrm{oc}}$ over $\\ensuremath{120\\mathrm{~s~}}$ , resulting in $1240~\\mathrm{mV}$ (displayed as the red test of a perovskite solar cell. The device was aged for 500 hours at $85^{\\circ}\\mathrm{C}$ triangles in the $J-V$ and $V_{\\mathrm{oc}}$ scans). (C) EQE electroluminescence (EL) as a under continuous full illumination and MPP tracking in a nitrogen atmofunction of voltage.The left inset shows the corresponding EL spectrum over sphere (red curve, circles). This aging routine exceeds industry norms. Durwavelength. The right inset shows a solar cell (device size ${\\sim}1.4\\ \\mathsf{c m}\\times2.8\\mathsf{c m}$ ) ing the light soaking at $85^{\\circ}\\mathrm{C}$ , the device retained $95\\%$ (dashed line) of its with two active areas. The left area is operated as an LED displaying a clearly initial performance. \n\nFurthermore, we collected the corresponding x-ray diffraction (XRD) data of the unannealed films (Fig. 2B) that showed a pronounced perovskite peak for RbCsMAFA as compared to MAFA films. In Fig. 2, C and D, we show analogous data after annealing, including UV-vis, $\\mathrm{PL},$ and XRD data, that reveal a RbCsMAFA band gap of ${\\sim}1.63\\mathrm{eV}$ (slightly blue-shifted relative to MAFA at $\\mathrm{\\sim}1.62~\\mathrm{eV})$ containing neither a $\\mathrm{PbI_{2}}$ nor a yellow-phase peak. The low-angle perovskite peaks for MAFA and RbCsMAFA occur at $14.17^{\\circ}$ and $14.25\\mathrm{^\\circ};$ respectively, revealing that Rb indeed modified the crystal lattice. In figs. S5 and S6, we show XRD data of \n\nRbMAFA perovskite where we increased the concentration of Rb. We observed, similar to CsMAFA (9), that the Pb excess and the yellow-phase impurities of MAFA perovskite disappeared when Rb was added. For ${\\mathrm{Rb}}_{5}{\\mathrm{MAFA}}$ , there was a shift to wider angles for the perovskite peak. Moreover, in figs. S7 and S8, we show a series of RbCsMAFA perovskite with an increased amount of Rb together with a $\\mathrm{\\RbPbI_{3}}$ reference. We observed that the perovskite peak shifted to wider angles for ${\\mathrm{Rb}}_{5}{\\mathrm{CsMAFA}}$ as well as further suppression of the residual $\\mathrm{PbI_{2}}$ $(12.7^{\\circ})$ and yellow-phase peak $(\\mathrm{{11.7^{\\circ}}})$ of FA-based perovskite. As more Rb was added, we noted the appearance of a second peak at $13.4^{\\circ}$ and a double peak at $10.1^{\\circ}$ that coincide with the peaks for the pure yellow-phase $\\mathrm{Rb}\\mathrm{Pb}\\mathrm{I}_{3},$ indicating phase segregation at higher Rb concentrations. This is in good agreement with previous work where a phase segregation was also observed as more and more Cs was added to FA-based perovskite (8). \n\nIn addition, top-view scanning electron microscopy (SEM) images revealed large crystals in the RbCsMAFA devices (fig. S9), which have been shown to be beneficial for the PV metrics (19). Energy-dispersive x-ray spectroscopy measurements (fig. S10) indicated the presence and distribution of Cs and Rb within the perovskite layer. \n\nWe collected statistical data on RbCsMAFA devices (with 12 CsMAFA and 17 RbCsMAFA devices measured at a scan rate of $\\mathrm{{10\\mVs^{-1}}}$ , without preconditioning such as light soaking or longterm forward voltage biasing; see fig. S11) and observed superior performance relative to CsMAFA. Remarkably, the average $V_{\\mathrm{oc}}$ increased from 1120 to $\\mathrm{1158\\mathrm{mV}}$ and the fill factor (FF) increased from 0.75 to 0.78. In Fig. 3A, we show that the bestperforming RbCsMAFA cell reached a stabilized power output of $21.6\\%$ with FF of $81\\%$ and $V_{\\mathrm{{oc}}}$ of $\\mathrm{1180mV}$ . The measured short-circuit current density $J_{\\mathrm{sc}}$ matched the incident photon to current efficiency (IPCE) measurement in fig. S12. We also achieved a stabilized PCE of $19.0\\%$ on a large-area $0.5\\mathrm{-cm^{2}}$ device (see fig. S13). \n\nTo correctly determine the value of $V_{\\mathrm{oc}},$ we investigated RbCsMAFA devices with the active area being fully illuminated, held at room temperature, and under an inert nitrogen atmosphere. This setup permitted an accurate $V_{\\mathrm{{oc}}}$ value without heating or degradation effects (from moisture, for example). In Fig. 3B, for one of our highest-performing devices, we measured an outstanding $V_{\\mathrm{oc}}$ of $\\mathrm{1240~mV}$ , as confirmed by the inset tracking $V_{\\mathrm{{oc}}}$ over time. The “loss in potential” (difference between $V_{\\mathrm{{oc}}}$ and band gap) is only ${\\sim}0.39\\mathrm{V}$ , which is one of the lowest recorded for any PV material, implying very small nonradiation recombination losses (20). The high $V_{\\mathrm{{oc}}}$ is particularly intriguing because this is the major parameter preventing PSCs from reaching their thermodynamic limit $(J_{\\mathrm{sc}}$ and FF are already approaching their maximal values). Theoretically, in very pure, defect-free materials with only radiative recombination, the loss in potential can be as small as $0.23\\mathrm{V}$ (band gap of 1 eV) to $0.3\\mathrm{V}$ (band gap of $2~\\mathrm{eV},$ ). In particular, silicon, the main industrial PV material, cannot approach this limit because of its indirect band gap and Auger recombination, exhibiting a loss in potential of ${\\sim}0.4\\mathrm{V}$ for the most efficient devices (20). \n\nThe nonradiative recombination losses were quantified by measuring the external electroluminescence quantum efficiency $(\\mathrm{EQE_{EL}})$ , which is $>1\\%$ at a driving current that is equal to the shortcircuit current (see Fig. 3C). This value is in the same order of magnitude and thus consistent with a measured external PL quantum yield of $3.6\\%$ for RbCsMAFA (and $2.4\\%$ for CsMAFA). Following the approach in (21–25) [see also fig. S14 and (18)], we used the $\\mathrm{EQE_{\\mathrm{EL}}}$ and the emission spectrum to predict a $V_{\\mathrm{{oc}}}$ value of $\\mathrm{1240~mV}$ , confirming independently the value measured from the J-V curve. \n\nFurthermore, for higher driving currents, the $\\mathrm{EQE_{\\mathrm{EL}}}$ in Fig. 3C reaches $3.8\\%$ , making the solar cell one of the most efficient perovskite LEDs as well, emitting in the near-infrared/red spectral range (Fig. 3C, inset) (26–28). Movie S1 shows a RbCsMAFA device mounted in our custom-made device holder. As we tuned toward maximum emission and back, we observed bright EL in daylight. For comparison, for commercially available Si solar cells, $\\mathrm{EQE_{EL}}\\approx0.5\\%$ (20). These values for our PSC devices indicate that all major sources of nonradiative recombination were strongly suppressed and that the material has very low bulk and surface defect density. We also investigated transport behavior by means of intensitymodulated photocurrent spectroscopy (IMPS); the findings suggest that the charge transport within the RbCsMAFA perovskite layer is substantially faster than in CsMAFA, which is already much more defect-free than MAFA (19) [see also fig. S15 and (18)]. \n\nDespite the high efficiencies and an outstanding EL, this Rb-containing perovskite material must be able to achieve high stability. This task is not trivial given the hygroscopic nature of perovskite films, phase instabilities, and light sensitivity (29). Interestingly, the Achilles’ heel of PSCs is not necessarily the perovskite itself, but rather the commonly used spiro-OMeTAD hole transporter material that becomes permeable (at elevated temperature) to metal electrode diffusion into the perovskite, causing irreversible degradation (30, 31). This effect can be mitigated with buffer layers or by avoiding the use of metal electrodes (30–32). Alternatively, for the combined heat-light stress tests in this work, we found a thin layer of polytriarylamine polymer (PTAA) (see SEM image in fig. S4B) to work equally well (33). We imposed the above protocols simultaneously and aged devices for 500 hours at $85^{\\circ}\\mathrm{C}$ under continuous illumination with full intensity and maximum power point (MPP) tracking in a nitrogen atmosphere. This compounded stress test exceeds industrial standards $(34)$ . We show the result in Fig. 3D (red curve). The device started with ${>}17\\%$ efficiency at room temperature before the aging protocol was applied (see fig. S16 for non-normalized values of PCE, $\\mathrm{FF},J_{\\mathrm{sc}},V_{\\mathrm{oc}},J_{\\mathrm{MPP}},$ and $V_{\\mathrm{MPP}}.$ ). During the $85^{\\circ}\\mathrm{C}$ step (in which $V_{\\mathrm{{oc}}}$ is inevitably lowered), the device retained $95\\%$ of its initial performance. \n\n# REFERENCES AND NOTES \n\n1. National Renewable Energy Laboratory, Best Research-Cell \nEfficiencies chart; www.nrel.gov/ncpv/images/efficiency_chart. \njpg. \n2. N. J. Jeon et al., Nature 517, 476–480 (2015). \n3. M. Saliba et al., Nat. Energy 1, 15017 (2016). \n4. X. Li et al., Science 353, 58–62 (2016). \n5. H. Choi et al., Nano Energy 7, 80–85 (2014). \n6. J. W. Lee et al., Adv. Energy Mater. 5, 1501310 (2015). \n7. C. Yi et al., Energy Environ. Sci. 9, 656–662 (2016). \n8. Z. Li et al., Chem. Mater. 28, 284–292 (2016). \n9. M. Saliba et al., Energy Environ. Sci. 9, 1989–1997 (2016). \n10. D. P. McMeekin et al., Science 351, 151–155 (2016). \n11. H. L. Wells, Z. Anorg. Chem. 3, 195–210 (1893). \n12. D. Weber, Z. Naturforsch. B 33, 1443 (1978). \n13. D. B. Mitzi, K. Liang, J. Solid State Chem. 134, 376–381 (1997). \n14. G. Kieslich, S. J. Sun, A. K. Cheetham, Chem. Sci. 5, 4712–4715 (2014). \n15. M. R. Filip, G. E. Eperon, H. J. Snaith, F. Giustino, Nat. Commun. \n5, 5757 (2014). \n16. F. Hao, C. C. Stoumpos, D. H. Cao, R. P. H. Chang, \nM. G. Kanatzidis, Nat. Photonics 8, 489–494 (2014). \n17. D. M. Trots, S. V. Myagkota, J. Phys. Chem. Solids 69, \n2520–2526 (2008). \n18. See supplementary materials on Science Online. \n19. J. P. Correa-Baena et al., Adv. Mater. 28, 5031–5037 (2016). \n20. M. A. Green, Prog. Photovolt. Res. Appl. 20, 472–476 (2012). \n21. K. Tvingstedt et al., Sci. Rep. 4, 6071 (2014). \n22. D. Bi et al., Sci. Advances 2, e1501170 (2016). \n23. U. Rau, Phys. Rev. B 76, 085303 (2007). \n24. R. T. Ross, J. Chem. Phys. 46, 4590 (1967). \n25. W. Tress et al., Adv. Energy Mater. 5, 1400812 (2015). \n26. H. Cho et al., Science 350, 1222–1225 (2015). \n27. L. Gil-Escrig et al., Chem. Commun. 51, 569–571 (2015). \n28. G. Li et al., Adv. Mater. 28, 3528–3534 (2016). \n29. N. H. Tiep, Z. L. Ku, H. J. Fan, Adv. Energy Mater. 6, 1501420 (2016). \n30. K. Domanski et al., ACS Nano 10, 6306–6314 (2016). \n31. K. A. Bush et al., Adv. Mater. 28, 3937–3943 (2016). \n32. A. Mei et al., Science 345, 295–298 (2014). \n33. J. H. Heo et al., Nat. Photonics 7, 487 (2013). \n34. Y. G. Rong, L. F. Liu, A. Y. Mei, X. Li, H. W. Han, Adv. Energy \nMater. 5, 1501066 (2015). \n\n# ACKNOWLEDGMENTS \n\nM.S. conceived, designed, and led the overall project; M.S., J.-Y.S., A.U., and J.-P.C.-B. conducted SEM, PL, and XRD experiments on the perovskite films; M.S. and W.R.T. performed EL and PL quantum yield experiments; A.U. conducted confocal laser scanning fluorescence microscopy for PL mapping; M.S., K.D., and W.R.T. conducted long-term aging tests on the devices; \n\n# BIOPHYSICS \n\nM.S., T.M., J.-P.C.-B., and A.A. prepared and characterized PV devices; A.H. participated in the supervision of the work; M.G. directed and supervised the research; M.S. wrote the first draft of the paper; and all authors contributed to the discussion and writing of the paper. Supported by the co-funded Marie Skłodowska Curie fellowship, H2020 grant agreement no. 665667 (M.S.); the European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 291771 (A.A.); the Swiss National Science Foundation, funding from the framework of Umbrella project (grant agreement nos. 407040-153952, 407040-153990, and 200021- 157135/1); the NRP 70 “Energy Turnaround”; the 9th call proposal 906: CONNECT PV; and SNF-NanoTera and the Swiss Federal Office of Energy (SYNERGY). We also acknowledge funding from the European Union’s Horizon 2020 program, through a FET-Open Research and Innovation Action under grant agreement no. 687008. A.A. conducted IMPS experiments at the Adolphe Merkle Institute, Fribourg, Switzerland. M.G. and S.M.Z. thank the King Abdulaziz City for Science and Technology for financial support under a joint research project. All data are available in the main paper and supplement. M.S., T.M., K.D., J.-Y.S., S.M.Z., W.R.T., and M.G. are inventors on European Patent Application 1618056.7 submitted by École Polytechnique Fédérale de Lausanne and Panasonic Corporation that covers the perovskite compounds in this work. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/354/6309/206/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S16 \nTables S1 and S2 \nMovie S1 \nReferences (35–41) \n\n18 July 2016; accepted 8 September 2016 \nPublished online 29 September 2016 \n10.1126/science.aah5557 \n\n# Bifurcating electron-transfer pathways in DNA photolyases determine the repair quantum yield \n\nMeng Zhang,1 Lijuan Wang,1 Shi Shu,1 Aziz Sancar,2 Dongping Zhong1\\* \n\nPhotolyase is a blue-light–activated enzyme that repairs ultraviolet-induced DNA damage that occurs in the form of cyclobutane pyrimidine dimers (CPDs) and pyrimidine-pyrimidone (6-4) photoproducts. Previous studies on microbial photolyases have revealed an electrontunneling pathway that is critical for the repair mechanism. In this study, we used femtosecond spectroscopy to deconvolute seven electron-transfer reactions in 10 elementary steps in all classes of CPD photolyases.We report a unified electron-transfer pathway through a conserved structural configuration that bifurcates to favor direct tunneling in prokaryotes and a two-step hopping mechanism in eukaryotes. Both bifurcation routes are operative, but their relative contributions, dictated by the reduction potentials of the flavin cofactor and the substrate, determine the overall quantum yield of repair. \n\nP hotolyases, which belong to the photolyase (PL)–cryptochrome (CRY) superfamily, use a fully reduced flavin (FADH−) cofactor to repair sunlight-induced DNA lesions, including cyclobutane pyrimidine dimers (CPDs) and pyrimidine-pyrimidone (6-4) photoproducts (1–5). On the basis of sequence analyses, CPD photolyases are highly diversified and can be subdivided into three classes (I to III) (6–8), as well as single-stranded DNA (ssDNA)–specific PLs (9) (Fig. 1A). Thus, the molecular repair \n\n# Science \n\n# Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance \n\nMichael Saliba, Taisuke Matsui, Konrad Domanski, Ji-Youn Seo, Amita Ummadisingu, Shaik M. Zakeeruddin, Juan-Pablo Correa-Baena, Wolfgang R. Tress, Antonio Abate, Anders Hagfeldt and Michael Grätzel \n\nScience 354 (6309), 206-209. DOI: 10.1126/science.aah5557originally published online September 29, 2016 \n\n# Improving the stability of perovskite solar cells \n\nInorganic-organic perovskite solar cells have poor long-term stability because ultraviolet light and humidity degrade these materials. Bella et al. show that coating the cells with a water-proof fluorinated polymer that contains pigments to absorb ultraviolet light and re-emit it in the visible range can boost cell efficiency and limit photodegradation. The performance and stability of inorganic-organic perovskite solar cells are also limited by the size of the cations required for forming a correct lattice. Saliba et al. show that the rubidium cation, which is too small to form a perovskite by itself, can form a lattice with cesium and organic cations. Solar cells based on these materials have efficiencies exceeding $20\\%$ for over 500 hours if given environmental protection by a polymer coating. \n\nScience, this issue pp. 203 and 206 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/354/6309/206 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2016/09/28/science.aah5557.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/354/6309/203.full \n\nREFERENCES \n\nThis article cites 39 articles, 5 of which you can access for free http://science.sciencemag.org/content/354/6309/206#BIBL \n\nPERMISSIONS \n\nhttp://www.sciencemag.org/help/reprints-and-permissions \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1016_j.matdes.2014.09.044", + "DOI": "10.1016/j.matdes.2014.09.044", + "DOI Link": "http://dx.doi.org/10.1016/j.matdes.2014.09.044", + "Relative Dir Path": "mds/10.1016_j.matdes.2014.09.044", + "Article Title": "Selective laser melting of AlSi10Mg alloy: Process optimisation and mechanical properties development", + "Authors": "Read, N; Wang, W; Essa, K; Attallah, MM", + "Source Title": "MATERIALS & DESIGN", + "Abstract": "The influence of selective laser melting (SLM) process parameters (laser power, scan speed, scan spacing, and island size using a Concept Laser M2 system) on the porosity development in AlSi10Mg alloy builds has been investigated, using statistical design of experimental approach, correlated with the energy density model. A two-factor interaction model showed that the laser power, scan speed, and the interaction between the scan speed and scan spacing have the major influence on the porosity development in the builds. By driving the statistical method to minimise the porosity fraction, optimum process parameters were obtained. The optimum build parameters were validated, and subsequently used to build rodshaped samples to assess the room temperature and high temperature (creep) mechanical properties. The samples produced using SLM showed better strength and elongation properties, compared to die cast Al-alloys of similar composition. Creep results showed better rupture life than cast alloy, with a good agreement with the Larson-Miller literature data for this alloy composition. (C) 2014 Elsevier Ltd. All rights reserved.", + "Times Cited, WoS Core": 932, + "Times Cited, All Databases": 1016, + "Publication Year": 2015, + "Research Areas": "Materials Science", + "UT (Unique WOS ID)": "WOS:000345520000051", + "Markdown": "# Selective laser melting of AlSi10Mg alloy: Process optimisation and mechanical properties development \n\nNoriko Read a, Wei Wang a, Khamis Essa b, Moataz M. Attallah a,⇑ \n\na School of Metallurgy and Materials, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK b School of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: Received 22 July 2014 Accepted 15 September 2014 Available online 7 October 2014 \n\nKeywords: Selective laser melting Aluminium alloys Mechanical properties \n\nThe influence of selective laser melting (SLM) process parameters (laser power, scan speed, scan spacing, and island size using a Concept Laser M2 system) on the porosity development in AlSi10Mg alloy builds has been investigated, using statistical design of experimental approach, correlated with the energy density model. A two-factor interaction model showed that the laser power, scan speed, and the interaction between the scan speed and scan spacing have the major influence on the porosity development in the builds. By driving the statistical method to minimise the porosity fraction, optimum process parameters were obtained. The optimum build parameters were validated, and subsequently used to build rodshaped samples to assess the room temperature and high temperature (creep) mechanical properties. The samples produced using SLM showed better strength and elongation properties, compared to die cast Al-alloys of similar composition. Creep results showed better rupture life than cast alloy, with a good agreement with the Larson–Miller literature data for this alloy composition. \n\n$\\circledcirc$ 2014 Elsevier Ltd. All rights reserved. \n\n# 1. Introduction \n\nAdditive layer manufacturing (ALM) has been used for more than 30 years and is now widely used for various materials [1–4]. Although there are many types of production machines, they are all similar, in the sense that they produce three-dimensional shapes by combining a number of two-dimensional slices. In recent years, ALM has been developed for ‘‘rapid manufacturing’’ of metallic components using, electron beam melting (EBM), direct laser fabrication (DLF), and selective laser melting (SLM) [5,6]. Aerospace manufacturers are focusing on the SLM powder-bed technology for Ti-alloy and Ni-superalloy components [7,8] where the potential cost reduction, fewer steps in the production process and design-freedom are among the factors driving this technology. There has been an increasing number of reports on ALM of Alalloys recently, because of the demand from the industrial field for lightweight structures with complex geometries [6,9]. \n\nAlSi10Mg alloy is a traditional cast alloy that is often used for die-casting. Because of its high strength and good mechanical properties, this alloy has been widely used in the automotive and aerospace industry. Because of its near eutectic composition of Al and Si, it has good weldability. Mg plays an important role in age hardening as $\\upbeta^{\\prime}$ and $\\mathsf{M g}_{2}\\mathsf{S i}$ ( $\\upbeta$ -phase) [10]. Recently, various reports have been published of the microstructure using a processing parameter study of SLM-fabricated AlSi10Mg [11,12]. \n\nThere are many factors that affect the final quality of the SLM samples, including the feedstock material characteristics (powder size, morphology and size distribution). The laser heat input is another source important parameter, as it controls the degree of consolidation of the powder particles, or could potentially aggravate defect formation by creating turbulences in the melt pool that can form a keyhole-like defect in the extreme conditions. One of the approaches to represent the laser heat input is using the energy density function $\\boldsymbol{\\Psi}$ [6], which is given as \n\n$$\n\\varPsi=\\frac{P}{\\nu\\cdot h\\cdot t}\n$$ \n\nwhere $P$ and $\\upsilon$ are respectively the laser power and scan speed, $h$ is scan spacing, and $t$ is layer thickness. Some studies [3] used the energy density concept to correlate the porosity development with the heat input, but the trend was generally inconsistent, although it identified an optimum energy density level where the build density was the maximum. \n\nAlternatively, the use of design of experiments (DOE) techniques such as the Response Surface Method, and statistical analysis using the analysis of variance (ANOVA), have been shown to be useful approaches to study the effect of many parameters in material processing applications. Response Surface design of experiment and \n\n![](images/1c02b328aaa69666914e24c539827c6900436d0dac6d630a593bd1991a1d8d37.jpg) \nFig. 1. (a) SEM micrograph, showing the morphology of the AlSi10Mg powder, and (b) the powder size distribution. \n\n![](images/cea5e17838242241d7bafbc691a99fef510d2c250973d9ac1361d45ae206c7cd.jpg) \nFig. 2. Schematic illustration of the island scan strategy, showing (a) each layer is divided into square (islands) and the inside of island is raster scanned, then (b) the successive layers are displaced $1\\mathrm{mm}$ in the $X$ and Y-directions. \n\nANOVA technique have been used for the significance of selective laser sintering (SLS) process variables on surface roughness [13]. Similarly, Carter [14] used response surface method and ANOVA techniques to optimise SLM for CMSX-486 Ni- superalloy, by studying the impact of the process parameters (laser power, scan speed, scan spacing and island size) on crack density and porosity fraction. \n\nThis paper focuses on the influence of SLM parameters for fabricating AlSi10Mg. Statistical experimental design was adopted to optimise the process parameters to minimise the defects (pores or cracks). Mechanical tests were performed on samples manufactured using optimised parameters that gave minimum porosity and voids. In this paper, the term ‘‘pore’’ includes spherical pores and irregular voids that are observed in the laser processed samples. The influence of the build orientation (vertically and horizontally built samples) on the tensile properties was investigated. In addition, high temperature mechanical (creep) properties were also measured for horizontally built samples. \n\n# 2. Experimental details \n\n# 2.1. Material \n\nThe AlSi10Mg powder, the composition of which is shown in Table 1, was supplied by LPW Technology Ltd. The size range was $20\\mathrm{-}63\\mathrm{~\\textmum}$ , as measured using Coulter LS230 laser diffraction particle size analyser. \n\nFig. 1(a) shows a Scanning Electron Microscope (SEM) micrograph of the powder. It is obvious that the powder particles are not spherical. The particles show a very irregular morphology, with many small irregular satellite particles attached to the big particles. These irregular shape with small satellite particles were observed elsewhere [15,16]. The particle size distribution affects the powder flowability for in powder bed systems, as well as their melting behaviour [6]. Fig. 1(b) shows the size distribution of the powder, which had an average particle size of ${\\sim}35\\upmu\\mathrm{m}$ . The slightly unsymmetrical distribution is potentially caused by the irregular powder morphology, and the potential agglomeration of the powder particles during the measurement. Despite the irregular morphology, the powder had a reasonable flowability and Hausner’s ratio for SLM. \n\n# 2.2. Statistical design of experiment (DoE) using response surface \n\nThe response surface methodology is a statistical technique to generate an experimental design to find an approximate model between the input and output parameters, and to optimise the process responses (e.g. towards a maximum and a minimum). It is a collection of statistical and mathematical methods that are useful for modelling and analysing engineering problems. In this technique, the main objective is to optimise the response surface, which is influenced by various process parameters. The response surface $Y$ can be expressed by a second order polynomial (regression) equation as shown in Eq. (2). \n\nTable 1 Chemical composition of the investigated AlSi10Mg alloy (Wt.%). \n\n\n
SiFeMnMgNiZnPbSnTiAl
9.920.1370.0040.2910.040.010.0040.0030.006Bal
\n\nTable 2 The range of matrix building parameters. \n\n\n
ParameterUnitsLevels
-2-1012
Laser powerW100125150175200
Scan speedmm/s7001025135016752000
Hatch spacing(a1)0.20.350.50.650.8
Island sizemm2.03.55.06.58.0
\n\nTable 3 Response surface model coefficients for cracking density and porosity fraction. \n\n\n
CoefficientThe corresponding value
bo-12.76
b1+2.07×E-1
b2+1.02×E-2
b3-20.44
b4+5.50
b5-1.39 ×E-4
b6-2.32×E-1
b7-2.4 × E-2
b8+5.01×E-2
bg-8.37 ×E-4
b10-1.45
\n\n$$\nY=b_{0}+\\sum b_{i}x_{i}+\\sum b_{i i}x_{i}^{2}+\\sum b_{i j}x_{i}x_{j}.\n$$ \n\n# 2.3. SLM \n\n\u0004 Identification of the key process parameters. \n\u0004 Selection of the upper and lower limit of the process parameters. \nSelection of the output response. \nDeveloping the experimental design matrix. \n\u0004 Conducting the experiments as per the design matrix. \n\u0004 Recording the output response. \nDeveloping a mathematical model to relate the process parameters with the output response. \nOptimising that model using genetic algorithm. \n\nThe experimental design procedure using the response surface methodology can be summarised as follows: \n\n![](images/5839a73e809b2b13f171c6ea54abb1fb1d029dda30e6fbe728de06ccca163263.jpg) \nFig. 4. Response surface plot showing the effect of the laser power and scan speed on the porosity, at 0.5 hatch-spacing a1 and $5\\mathrm{mm}$ island size. \n\nAll specimens were fabricated using a Concept Laser M2 Cusing\u0003 SLM (laser powder-bed) system. The M2 system has a Yb-Fibre laser, with laser power up to 200 W, $150\\upmu\\mathrm{m}$ laser track width, with laser scan speed up to $7000\\mathrm{mm}/s$ . All specimens were built using a $Z\\cdot$ -increment (vertical) of $30\\upmu\\mathrm{m}$ . All processing was carried out in an Argon atmosphere with an oxygen-content $<0.1\\%$ . An ‘‘island scanning strategy’’ was adopted to fabricate specimens [17], in which the filled layer is divided into several square (islands) with each island being built randomly and continuously. Inside each island, the laser is raster-scanned individually. After selective melting the islands, laser scans are carried out around the perimeter of the layer to improve the surface finish. For each subsequent layer, these islands are translated by $1\\mathrm{mm}$ in the $X$ and Y-directions, as illustrated in Fig. 2. The aim of the island deposition strategy is to balance the residual stresses in the build [18]. \n\n![](images/cd5af25217ad1abfae64a5195795ad538e2b2a9ad2049b9e541803db1ee70646.jpg) \nFig. 3. Schematic drawing of horizontal and vertical samples for the mechanical tests. \n\n# 2.4. Sample build and preparation \n\nTo perform the DoE and parametric optimisation, 27 parametric combinations were used to fabricate samples using a fractional factorial DoE. All samples were $10\\mathrm{mm}\\times10\\mathrm{mm}\\times10\\mathrm{mm}$ cubes. Since Concept Laser M2 uses a dimensionless number hatch spacing a1 instead of scan spacing, a1 parameter was used for this study. a1 is defined as, \n\na1 Hatch spacing $\\c=$ Scan spacing h=laser track width ðconstant;150 lmÞ \n\nTable 2 shows the range and levels of the investigated key process variables. \n\n# 2.5. Porosity and microstructural analysis \n\nTo characterise the area fraction and density of cracks and/or pores in the material, all samples were cut in the transverse direction (X–Y plane) $3\\mathrm{mm}$ from the top of the build, mounted in conducting Bakelite, and polished to a $0.05\\upmu\\mathrm{m}$ finish. Samples were analysed using a Zeiss Axioskop microscope, with an Axioskop $2^{\\circledast}$ image analyser and AxioVision\u0003 software. For each sample, 25 images were collected from the centre. Image threshold was applied to determine the porosity content (porosity $\\%$ ), using ImageJ Software [19]. Table 3 summarises the findings of porosity $\\%$ and the parametric combinations. No solidification cracks were observed, which was expected as AlSi10Mg alloy is has a generally low crack sensitivity [16], although oxide film crack-like features were observed. The microstructure of the samples was examined in a JEOL 6060 scanning electron microscope (SEM), equipped with a back-scattered electron (BSE) detector, and operated at $20\\mathrm{kV}$ . \n\nTable 4 Matrix building parameters and $\\%$ porosity. \n\n\n
RunLaser power (W)Scan speed (mm/s)Hatch spacing a1 (h/150 μm)Island size (mm)Porosity (%)
112516750.356.516.1
212516750.653.524.7
312510250.656.59.4
415013500.8510.8
512516750.656.529.9
61507000.5510.4
715013500.59.9
812516750.353.515.4
917510250.656.51.7
1017516750.656.55.5
1112510250.353.511.8
1215013500.2510.5
1312510250.356.514.1
1415013500.527.5
1510013500.520.5
1615013500.510.1
1717510250.356.53.5
1812510250.653.59.3
1917516750.356.56.4
2017516750.653.513.1
2120013500.50.8
2215020000.5518.0
2317516750.353.56.8
2415013500.555.5
25 2615013500.587.3
2717510250.653.50.8
17510250.353.52.4
\n\n# 2.6. Mechanical testing \n\nRod-shape samples were fabricated using the optimised parameters that produced the lowest porosity. Samples were built vertically and horizontally, as shown in Fig. 3. In the ‘vertical’ samples, the long boundary of the sample is parallel to the building direction, whereas the long boundary of the sample is perpendicular to the building direction in the ‘horizontal’ samples. Tensile tests were performed in accordance with BS EN 2002-1:2005 [20]. All mechanical test results are the average of 3 samples. In addition, creep tests were performed at the following conditions $180^{\\circ}{\\mathsf{C}}/$ $200\\mathsf{M P a}$ , $150^{\\circ}\\mathrm{C}/200\\mathrm{MPa}$ , and $180^{\\circ}\\mathsf C/150\\mathsf{M P a}$ for the horizontal samples, in according with BS EN 2002-5:2007 [21]. For each creep test, samples were kept at the test temperature for a minimum of $30\\mathrm{min}$ prior to the test. For the $150^{\\circ}\\mathrm{C}/200\\mathrm{MPa}$ and $180^{\\circ}{\\mathsf{C}}/$ $150\\ensuremath{\\mathrm{MPa}}$ conditions, tests were stopped at $20\\mathrm{h}$ . Fracture surface observation was performed using SEM after the creep test. \n\n![](images/cceab18a29ad85ee7c9e59f72c1fc121e31f5247057a4c29ea70f392b90d5da0.jpg) \nFig. 5. The impact of the interaction effect of scan speed and hatch spacing on the porosity, at $150\\mathrm{W}$ laser power and $5\\mathrm{mm}$ island size. The solid lines represent model prediction while the dash lines represent the variation of the actual data around the model prediction. \n\n![](images/dd810507d6d9d4b11f742edc012591b672fe9f9a49fd3d28270b69ca43ac5502.jpg) \nFig. 6. Predicted optimum laser power and scan speed for minimum porosity. \n\nTable 5 Predicted building parameter and actual porosity $\\%$ \n\n\n
SamplesPower (W)Scan speed (mm/s)Hatch spacing a1 (h/150 μm)Island size (mm)Porosity (%)
PredictedMeasured
A17510350.655.90.20.37
B17310250.656.50.20.38
C17510300.6460.20.46
D17410260.656.200.61
E17510250.655.600.29
\n\n![](images/d48540f8dcdcf4b0cf688070c9488fa4a7afa613368077d869126f0630d3e6e3.jpg) \nFig. 7. Optical micrograph images of (a) sample D and (b) sample E shown in Table 5. \n\n![](images/938c2fa81f5fba49e8d53b744c99fb0da0ffd7dc99aa1bd6c7a7f175a2f18a08.jpg) \nFig. 8. Tensile properties of SLM fabricated AlSi10Mg alloy, compared to die cast A360 alloy [24]. \n\n![](images/2e03b5851db8e956589e7469b73146d3e0bffdb3c18979ae4c2428e59b2c9490.jpg) \nFig. 9. Creep curves of SLM fabricated AlSi10Mg alloy (horizontal samples) at the following conditions: (a) $180^{\\circ}\\mathrm{C}/200\\mathrm{MPa}$ , (b) $150^{\\circ}\\mathrm{C}/200\\mathrm{MPa}$ , and (c) $180^{\\circ}\\mathsf{C}/$ $150\\mathrm{MPa}$ . \n\n# 3. Results and discussion \n\n# 3.1. ANOVA results \n\nThe response surface for porosity is a function of laser power $(P)$ scan speed $(\\nu)$ , hatch spacing (a1), and island size (Z) and can be expressed as follows: \n\n$$\n\\begin{array}{c}{{\\mathrm{Response}=b_{o}+b_{1}(P)+b_{2}(\\nu)+b_{3}(h)+b_{4}(Z)+b_{5}(P\\nu)}}\\\\ {{+b_{6}(P a1)+b_{7}(P Z)+b_{8}(a1\\nu)+b_{9}(\\nu Z)}}\\\\ {{+b_{10}(Z a1)}}\\end{array}\n$$ \n\nwhere $b_{0}$ is the average response, and $b_{1},b_{2},...,b_{10}$ are the model coefficients that depend on the main and interaction effects of the process parameters. The value of the coefficients for the porosity is shown in Table 4. The $R^{2}$ -value, a measure of model fit, showed that each of the models described the relationship between the process parameters and porosity was 0.87. The ANOVA indicates that, within the investigated range of parameters, the porosity is mainly affected by laser power, scan speed and the interaction between the scan speed and hatch spacing. The island size was found unlikely to have any influence on porosity. \n\n![](images/b348c6272377a5220ffee574da46d840e48b97b7cf1c046192f4f0ad353d3328.jpg) \nFig. 10. Backscattered SEM fractographs of SLM fabricated $\\mathsf{A l S i10M g}$ horizontal samples, showing (a) RT tensile test sample, (b) enlarged image, shown in yellow square in (a), (c) creep test sample, tested at $180^{\\circ}\\mathrm{C}/200\\mathrm{MPa}$ and (d) enlarged image, shown in yellow square in (c). Dimples-containing areas are circled, and the smooth areas are labelled using white rectangles. Unmelted particles are arrowed. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/d3822e91acbf41f34efe898a1ff697856a88feacbfe8811d18565f2869d0aaba.jpg) \nFig. 11. Secondary electron SEM images of irregular shape porosity showing an oxide film defect. The areas numbered have been analysed using EDX, as shown in the table. \n\nFig. 4 shows the response surface model prediction of porosity with respect to laser power and scan speed. It shows that decreasing the laser power and increasing the scan speed both result in an increased porosity. The influence of the laser power on porosity formation appears to be more significant at high scan speeds, and likewise the influence of the scan speed is more significant at lower laser power. A reduction in the laser power and an increase in the scan speed both have the effect of reducing the energy input into the material, as such these will result in the reduction of the melt pool which will lead to the formation of porosity due to the incomplete consolidation, and may ultimately lead to the breakdown of the SLM process. The relationship between energy input and porosity was also considered in Ti-alloys [22]. \n\n![](images/f36e0fb554f2ea25e7e044cbc7c0ae0736ecbe41b868010570c6171250ebcdfb.jpg) \nFig. 12. Porosity variation versus the energy density. The diamond points show the result of Table 3, and the circle shows the predicted parameter $E$ , shown in Table 5. \n\nFig. 5 shows the interaction effect between the scan speed and hatch spacing on the porosity. A low hatch spacing a1 of 0.35 appears to eliminate the effect of the scan speed on the porosity; whereas a high hatch spacing a1 of 0.65 significantly increases the effect of scan speed on porosity fraction. Likewise, an increase in the hatch spacing will ultimately result in porosity formation due to the lack of sufficient overlap between the laser scan tracks, leading to incomplete consolidation. Since the laser power, scan speed, and hatch spacing can individually control the heat input, it is conceivable that porosity formation can be mitigated using one of these parameters (within the investigated process window) to increase the heat input (e.g. use slow scan speed to fully consolidate the melt pool). It is important to state that these deductions are only valid within the investigated process window, since other mechanisms for porosity formation (e.g. melt pool turbulence or evaporation) could be triggered outside the investigated range. By considering the results presented in Figs. 4 and 5, it can be seen that in order to eliminate or minimise the porosity within the material, a high laser power, at low scan speed with a small hatch spacing should be used. \n\n# 3.2. Process optimisation \n\nDuring the optimisation, the objective function was set to minimise the porosity. The genetic algorithm was used to predict the process parameters based on the objective function. The equations modelling the response of porosity with respect to the four key process parameters (shown in Eq. (3) and the related coefficients listed in Table 4) were solved simultaneously. Fig. 6 shows the contour plot for the optimisation function to obtain minimum porosity for a range of laser powers and scan speeds. Kempen et al. [11] suggested optimum process parameter of $200\\mathsf{W}$ , $1400\\mathrm{mm}/\\mathrm{s},$ , with scan spacing $105\\upmu\\mathrm{{m}}$ . Additionally, Brandl et al. [23] used 250 W, $500\\mathrm{mm}/\\mathrm{s}$ , $150\\upmu\\mathrm{m}$ scan spacing, with $50\\upmu\\mathrm{m}$ layer thickness to achieve defect-free SLM of the AlSi10Mg alloy. \n\n# 3.3. Validation build \n\nTo confirm the relationship between the predicted optimum parameter sets and porosity, 5 samples were built using the optimised parameters. Table 5 shows the set of predicted parameters and the measured porosity. Fig. 7 shows micrographs for samples D and E. In sample D, irregular shaped voids (some of them are $200-300\\upmu\\mathrm{m}$ in size), rather than spherical, but the overall level of these irregular voids was very low. The irregular pores are most likely caused by improper powder spreading, especially as they were infrequent. \n\n# 3.4. Mechanical tests \n\nFig. 8 shows the tensile test results of horizontal and vertical samples together with data from die cast samples [24]. All samples were built using the parameters set E, shown in Table 5. There is no major influence for the build orientation on the tensile properties, although the horizontal samples show $\\sim10\\%$ high strength. Fig. 9 shows the time–strain curves of horizontal samples, for test conditions: (a) $180^{\\circ}\\mathrm{C}/200\\mathrm{MPa}$ , (b) $150^{\\circ}\\mathrm{C}/200\\mathrm{MPa}$ , and (c) $180^{\\circ}{\\mathsf{C}}/$ $150\\mathrm{MPa}$ . All the strain–time relations show normal creep behaviour, such as primary, secondary and tertiary creep. For test condition (a), the sample ruptured at $18.7\\mathrm{h}$ Using creep rupture data [24] for Larson miller plot for the same alloy, the predicted rupture time was $14.8\\mathrm{h}$ . \n\nFig. 10 shows the fractography of the samples tested to failure, for room temperature tensile tests (a, b) and creep tests (c, d). From these images, fracture surface are very rough and irregular. Deep cracks are generally obvious throughout the samples, interestingly all aligned in the same direction. At high magnifications, the fracture surface appears to contain a mix of small dimples and smooth areas. Moreover, fine unmelted powder particles are observed on both surfaces, Fig. 10(b) and (d), which could be due to the presence of thick oxide layers on the particles, which did not enable a full consolidation to occur locally where they existed. These un-bonded regions give rise to large cracks in the failed samples. The fracture surfaces are very similar in both the tension and creep samples, although a larger number of deep cracks was observed in the samples tested in tension. Furthermore, the crack surfaces appear smoother in the tension samples, than those of the creep samples. Similar fracture surfaces have been observed in the SLM of AA6061 [16]. The influence of these un-bonded regions on the tensile properties is small, because their effect on the reduction of the load-bearing cross section is small, but these defects may influence fatigue properties, especially if they are formed near to the surface. \n\nFig. 11 shows micrographs of the irregular voids. From the EDX data obtained from the areas arrowed in (b), it appears that area 2 is very high in oxygen, suggesting that this irregular void is associated with the presence of an oxide layer which prevented bonding. The analysis for oxygen, particularly on a rough surface, will not be quantitatively accurate, but the large difference between area 2 and other areas is considered as highly significant. \n\n# 3.5. Rationalising the porosity formation using the energy density \n\nFig. 12 shows a plot of porosity versus the energy density for the data previously provided in Table 2. The red dot indicates the predicted optimum parameter, E, previously provided in Table 5. The graph shows that at low energy density $(<50\\mathrm{J}/\\mathrm{mm}^{3})$ corresponds to a high porosity due to the lack of consolidation. The porosity content then decreases with increasing the energy density. This result supports the energy threshold for the full consolidation shown by Fig. 5. However, when the energy density exceeds approximately $60\\mathrm{J}/\\mathrm{mm}^{3}$ , the porosity content starts to scatter beyond that level until $120\\mathrm{J}/\\mathrm{mm}^{3}$ . In this region other defects, such as keyhole formation (due to vapourisation), have been observed within the material. Olakanmi also indicated that there is a certain threshold energy density that gives maximum material density, which is $60{-}75\\mathrm{J}/\\mathrm{mm}^{3}$ for Al, Al–Si and Al–Mg alloys [15]. Further in depth studies would be required to understand the factors governing this threshold level in various materials. \n\n# 4. Conclusions \n\nThis study has shown the following: \n\nA statistical method has been used to evaluate the influence of process parameters on the porosity of SLMed AlSi10Mg, which shows the trends of porosity in the SLM fabricated samples. \nThere is a critical energy density point that gives the minimum pore fraction for this alloy, approximately $60\\mathrm{J}/\\mathrm{m}^{3}$ . \nThe build direction does not strongly influence the tensile or creep strength of SLMed AlSi10Mg. Both building directions show higher strength than die cast A360, although the elongation is inferior to that of A360. \nFracture surfaces show the presence of significant amounts of un-melted powder, which give rise to local cracking. Further work is required to see if it is possible to eliminate these regions. \n\n# Acknowledgements \n\nThe authors would like to acknowledge the financial support from MicroTurbo/Safran Group. The support of the Materials and Components for Missiles (MCM) Innovation and Technology Partnership (ITP, and the Defence Science and Technology Laboratory (Dstl) is highly appreciated. \n\n# References \n\n[1] Casavola C, Campanelli SL, Pappalettere C. Preliminary investigation on distribution of residual stress generated by the selective laser melting process. J Strain Anal Eng Des 2009;44:93–104. \n[2] Osakada K, Shiomi M. Flexible manufacturing of metallic products by selective laser melting of powder. Int J Mach Tools Manuf 2006;46:1188–93. \n[3] Olakanmi EO, Cochrane RF, Dalgarno KW. Densification mechanism and microstructural evolution in selective laser sintering of Al–12Si powders. J Mater Process Technol 2011;211:113–21. \n[4] Yan C, Shi Y, Yang J, Liu J. Preparation and selective laser sintering of nylon-12 coated metal powders and post processing. J Mater Process Technol 2009;209:5785–92. \n[5] Vutova K, Vassileva V, Koleva E, Georgieva E, Mladenov G, Mollov D, et al. Investigation of electron beam melting and refining of titanium and tantalum scrap. J Mater Process Technol 2010;210:1089–94. [6] Liu A, Chua CK, Leong KF. Properties of test coupons fabricated by selective laser melting. Key Eng Mater 2010;447–448:780–4. [7] Gu D, Wang Z, Shen Y, Li Q, Li Y. In-situ TiC particle reinforced Ti–Al matrix composites: powder preparation by mechanical alloying and selective laser melting behavior. Appl Surf Sci 2009;255:9230–40. [8] Amato KN, Gaytan SM, Murr LE, Martinez E, Shindo PW, Hernandez J, et al. Microstructures and mechanical behavior of Inconel 718 fabricated by selective laser melting. Acta Mater 2012;60:2229–39. [9] Dadbakhsh S, Hao L. Effect of Al alloys on selective laser melting behaviour and microstructure of in situ formed particle reinforced composites. J Alloy Compd 2012;541:328–34. \n[10] Gupta AK, Lloyd DJ, Court SA. Precipitation hardening in Al–Mg–Si alloys with and without excess Si. Mater Sci Eng 2001;A316:11–7. \n[11] Thijs L, Kempen K, Kruth J-P, Humbeeck JV. Fine-structured aluminium products with controllable texture by selective laser melting of pre-alloyed AlSi10Mg powder. Acta Mater 2013;61:1809–19. \n[12] Kempen K, Thijs L, Humbeeck JV, Kruth J-P. Mechanical properties of AlSi10Mg produced by selective laser melting. Phys Procedia 2012;39:439–46. \n[13] Bacchewar PB, Singhal SK, Pandey PM. Statistical modelling and optimization of surface roughness in the selective laser sintering process. Proc Inst Mech Eng Part B: J Eng Manuf 2007;221:35–52. \n[14] Carter LN. Selective laser melting of Ni-superalloys for high temperature applications. Birmingham: University of Birmingham; 2013. \n[15] Olakanmi EO. Selective laser sintering/melting (SLS/SLM) of pure Al, Al–Mg, and Al–Si powders: Effect of processing conditions and powder properties. J Mater Process Technol 2013;213:1387–405. \n[16] Louvis E, Fox P, Sutcliff CJ. Selective laser melting of aluminium components. J Mater Process Technol 2011;211:275–84. \n[17] Thijs L, Verhaeghe F, Craeghs T, Humbeeck JV, Kruth J-P. A study of the microstructural evolution during selective laser melting of Ti–6Al–4V. Acta Mater 2010;58:3303–12. \n[18] Hofmann Group. Hofmann Innovation Group Website – Concept Laser. . 2012 [accessed 30.05.14]. \n[19] Rasband W. ImageJ. U.S. National Institutes of Health, Bethesda, Maryland, USA. ; 1997–2014. \n[20] British Standards Institution. Aerospace series. Metallic materials. Test methods. Tensile testing at room temperature (BS EN 2002-1:2005); 2006. \n[21] British Standards Institution. Aerospace series. Metallic materials. Test methods. Tensile testing at elevated temperature (BS EN 2002-2:2005); 2006. \n[22] Gong H, Rafi K, Starr T, Stucker B. The effects of processing parameters on defect regularity in Ti–6Al–4V parts fabricated by selective laser melting and electron beam melting. in: The 24th international SFF symposium: An additive manufacturing conference. The University Of Texas at Austin; 2013. \n[23] Brandl E, Heckenberger U, Holzinger V, Buchbinder D. Additive manufactured AlSi10Mg samples using Selective Laser Melting (SLM): microstructure, high cycle fatigue, and fracture behavior. Mater Des 2012;34:159–69. \n[24] Kaufman JG. In: Kaufman JG, editor. Properties of aluminum alloys tensile creep and fatigue data at high and low temperatures. Materials Park (Ohio); ASM International (Washington (D.C)); 1999. p. 264. " + }, + { + "id": "10.1126_science.aad5845", + "DOI": "10.1126/science.aad5845", + "DOI Link": "http://dx.doi.org/10.1126/science.aad5845", + "Relative Dir Path": "mds/10.1126_science.aad5845", + "Article Title": "A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells", + "Authors": "McMeekin, DP; Sadoughi, G; Rehman, W; Eperon, GE; Saliba, M; Hörantner, MT; Haghighirad, A; Sakai, N; Korte, L; Rech, B; Johnston, MB; Herz, LM; Snaith, HJ", + "Source Title": "SCIENCE", + "Abstract": "Metal halide perovskite photovoltaic cells could potentially boost the efficiency of commercial silicon photovoltaic modules from similar to 20 toward 30% when used in tandem architectures. An optimum perovskite cell optical band gap of similar to 1.75 electron volts (eV) can be achieved by varying halide composition, but to date, such materials have had poor photostability and thermal stability. Here we present a highly crystalline and compositionally photostable material, [HC(NH2)(2)](0.83)Cs0.17Pb(I0.6Br0.4)(3), with an optical band gap of similar to 1.74 eV, and we fabricated perovskite cells that reached open-circuit voltages of 1.2 volts and power conversion efficiency of over 17% on small areas and 14.7% on 0.715 cm(2) cells. By combining these perovskite cells with a 19%-efficient silicon cell, we demonstrated the feasibility of achieving >25%-efficient four-terminal tandem cells.", + "Times Cited, WoS Core": 2577, + "Times Cited, All Databases": 2797, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000367806500036", + "Markdown": "# SOLAR CELLS \n\n# A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells \n\nDavid P. McMeekin,1 Golnaz Sadoughi,1 Waqaas Rehman,1 Giles E. Eperon,1 Michael Saliba,1 Maximilian T. Hörantner,1 Amir Haghighirad,1 Nobuya Sakai,1 Lars Korte,2 Bernd Rech,2 Michael B. Johnston,1 Laura M. Herz,1 Henry J. Snaith1\\* \n\nMetal halide perovskite photovoltaic cells could potentially boost the efficiency of commercial silicon photovoltaic modules from ${\\sim}20$ toward $30\\%$ when used in tandem architectures. An optimum perovskite cell optical band gap of ${\\sim}1.75$ electron volts (eV) can be achieved by varying halide composition, but to date, such materials have had poor photostability and thermal stability. Here we present a highly crystalline and compositionally photostable material, $\\begin{array}{r}{[\\mathsf{H C}(\\mathsf{N H}_{2})_{2}]_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}(\\mathsf{I}_{0.6}\\mathsf{B r}_{0.4})_{3},}\\end{array}$ , with an optical band gap of ${\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}{\\mathsf{\\Pi}}$ , and we fabricated perovskite cells that reached open-circuit voltages of 1.2 volts and power conversion efficiency of over $17\\%$ on small areas and $14.7\\%$ on $0.715\\ \\mathsf{c m}^{2}$ cells. By combining these perovskite cells with a $19\\%$ -efficient silicon cell, we demonstrated the feasibility of achieving $>25\\%$ -efficient four-terminal tandem cells. \n\nO junction”; for example, by placing a wide– pnehoctonvcoeltpaticfsor(PiVmsp)riosvtiongcrtehaete faf c“iteancdyeomf band-gap “top cell” above a silicon (Si) “bottom cell.” This approach could realistically increase the efficiency of the Si cell from 25.6 to beyond $30\\%$ (1, 2). Given the crystalline Si band gap of 1.1 eV, the top cell material requires a band gap of ${\\sim}1.75~\\mathrm{eV}$ in order to current-match both junctions (3). However, suitable wide–band-gap top-cell materials for Si or thin-film technologies that offer stability, high performance, and low cost have been lacking. In recent years, metal halide perovskite–based PVs have gained attention because of their high power conversion efficiencies (PCEs) and low processing cost (4–11). An attractive feature of this material is the ability to tune its band gap from 1.48 to $2.3\\ \\mathrm{eV}$ (12, 13), implying that we could potentially fabricate an ideal material for tandem cell applications. \n\nPerovskite-based PVs are generally fabricated with organic-inorganic trihalide perovskites with the formulation $\\mathrm{ABX_{3}}$ , where A is the methylammonium $\\mathrm{(CH_{3}N H_{3})}$ (MA) or formamidinium $\\mathrm{[HC(NH_{2})_{2}]}$ (FA) cation, B is commonly lead $(\\mathrm{Pb})$ , and X is a halide (Cl, Br, or I). Although these perovskite structures offer high PCEs, reaching $>20\\%$ PCE with band gaps of around 1.55 eV $(I4)$ , fundamental issues have been discovered when attempting to tune their band gaps to the optimum 1.7- to $1.8\\mathrm{-eV}$ range. In the case of $\\mathrm{MAPb}[\\mathrm{I}_{(1-x)}\\mathrm{Br}_{x}]_{3},$ Hoke et al. reported that soaking it with light induces a halide segregation within the perovskite (15). The formation of iodide-rich domains with a lower band gap results in an increase in sub-gap absorption and a red shift of photoluminescence (PL). The lower–band-gap regions limit the voltage attainable with such a material, so this band-gap “photoinstability” limits the use of $\\mathrm{MAPb}[\\mathrm{I}_{(1\\circ c)}\\mathrm{Br}_{\\boldsymbol{x}}]_{3}$ in tandem devices (15). In addition, when considering real-world applications, $\\mathbf{MAPbI_{3}}$ is inherently thermally unstable at temperatures above $85^{\\circ}\\mathrm{C},$ , even in aninert atmosphere (international regulations require a commercial PV product to withstand this temperature) (16). \n\nConcerning the more thermally stable $\\mathrm{FAPbX_{3}}$ perovskite, an increase in optical band gap has not resulted in an expected increase in opencircuit voltage $(V_{\\mathrm{OC}})$ (13). Furthermore, as iodide is substituted with bromide, a crystal phase transition occurs from a trigonal to a cubic structure; in compositions near the transition, the material is unable to crystallize, resulting in an apparently “amorphous” phase with high levels of energetic disorder and unexpectedly low absorption. These compositions additionally have much lower charge-carrier mobilities in the range of $\\mathrm{1cm^{2}V^{-1}}$ $\\mathbf{s}^{-1},$ , in comparison to $>20\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ in the neat iodide perovskite (17). For tandem applications, these problems arise at the Br composition needed to form the desired top-cell band gap of ${\\sim}1.7$ to $1.8\\mathrm{eV}$ \n\n![](images/9a8795fdf70d4b7cfc3742ca45b276eccc58154fcd7ac5bb4cd79596694612e0.jpg) \nFig. 1.Tuning the band gap. Photographs of perovskite films with Br composition increasing from $x=0$ to 1 for (A) $\\mathsf{F A P b}[\\mathsf{I}_{(1-x)}\\mathsf{B r}_{x}]_{3}$ and (B) $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}[\\mathsf{I}_{(1-x)}\\mathsf{B r}_{x}]_{3}.$ (C) Ultraviolet-visible absorbance spectra of films of $\\mathsf{F A P b}[\\mathsf{I}_{(1-x)}\\mathsf{B r}_{x}]_{3}$ and (D) $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}[\\mathsf{I}_{(1-x]}\\mathsf{B r}_{x}]_{3},$ . a.u., arbitrary units. (E) XRD pattern of $\\mathsf{F A P b}[\\mathsf{I}_{(1-x)}\\mathsf{B r}_{x}]_{3}$ and (F) $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}[\\mathsf{I}_{(1-x)}\\mathsf{B r}_{x}]_{3}$ . The stated compositions are the fractional compositions of the ions in the starting solution, and the actual composition of the crystallized films may vary slightly. \n\n![](images/e5fed7ccc1ab1b4064e057bc14f6c19c51bcac208947b62e61721d1476fe4b2c.jpg) \nFig. 2. Material characteristics of $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}(\\mathsf{I}_{0.6}\\mathsf{B r}_{0.4})_{3}$ perovskite. Normalized PL measurement measured after 0, 5, 15, 30, and 60 min of light exposure of the (A) $\\mathsf{M A P b}(\\mathsf{I}_{0.6}\\mathsf{B r}_{0.4})_{3}$ and (B) $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}(\\mathsf{I}_{0.6}\\mathsf{B r}_{0.4})_{3}$ thin films. (C) Semi-log plot of EQE at the absorption onset for a $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}(\\mathsf{I}_{0.6}\\mathsf{B r}_{0.4})_{3}$ PV cell, measured using FTPS at short-circuit $(J_{\\mathsf{S C}})$ . (D) OPTP transients for a $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}(\\mathsf{I}_{0.6}\\mathsf{B r}_{0.4})_{3}$ thin film, measured after excitation with a 35-fs light pulse of wavelength $400\\ \\mathsf{n m}$ with different fluences. (E) Charge-carrier diffusion length $L$ as a function of charge-carrier concentration. \n\nNevertheless, perovskite/Si tandem PVs have already been reported in four-terminal (18, 19) and two-terminal (20) architectures. However, their reported efficiencies have yet to surpass the optimized single-junction efficiencies, in part because of non-ideal absorber band gaps. It is possible to form a lower–band-gap triiodide perovskite material and current-match the top and bottom junctions in a monolithic architecture by simply reducing the thickness of the top cell. However, this method results in non-ideal efficiency. \n\nHere we address the issues of forming a photostable FA-based perovskite with the ideal band gap for tandem PVs. We partially substituted the formamidinium cation with Cs and observed that the phase instability region was entirely eliminated in the iodide-to-bromide compositional range, delivering complete tunability of the band gap around $1.75\\ \\mathrm{eV}.$ . We fabricated planar heterojunction perovskite PVs, demonstrating PCE of ${>}17\\%$ and stabilized power output (SPO) of $16\\%$ . To demonstrate the potential impact of this new perovskite material in tandem solar cells, we created a semi-transparent perovskite device and measured the performance of a silicon PV after “filtering” the sunlight through the perovskite top cell. The Si cells delivered an efficiency boost of $7.3\\%$ , indicating the feasibility of achieving $>25\\%$ -efficient perovskite/Si tandem cells. \n\nThe A-site cations that could be used with lead halides to form suitable perovskites for PVs are Cs, $\\mathrm{MA},$ and FA. $\\mathrm{CsPbI_{3}}$ does form a “black phase” perovskite with a band gap of $1.73\\:\\mathrm{eV}$ , but this appropriate phase is only stable at temperatures above $200^{\\circ}$ to $300^{\\circ}\\mathrm{C},$ and the most stable phase at room temperature is a nonperovskite orthorhombic “yellow” phase. MA-based perovskites are thermally unstable and suffer from halide segregation instabilities, and are thus likely to be unsuitable (16). FA-based perovskites are the most likely to deliver the best balance between structural and thermal stability (13, 21–25). However, in Fig. 1A, we show photographs of a series of $\\mathrm{FAPb}[\\mathrm{I}_{(1-x)}\\mathrm{Br}_{x}]_{3}$ films; we observed a “yellowing” of the films for compositions of $x$ between 0.3 and 0.6, which is consistent with the previously reported phase instability caused by a transition from a trigonal $(x<0.3)$ ) to a cubic $(x>0.5)$ ) structure (13). \n\nWe have previously observed that the band gap changes from $1.48~\\mathrm{eV}$ for $\\mathrm{FAPbI_{3}}$ to $\\mathrm{1.73~eV}$ for $\\mathrm{CsPbI_{3}}$ (13). Recently it has been shown that mixing Cs with FA or MA results in a slight widening of the band gap (26, 27). We considered the possibility that if we partially substituted FA for Cs, we could push this region of structural instability in the Br-to-I phase space to higher energies, and thus potentially achieve a structurally stable mixed-halide perovskite with a band gap of $1.75\\ \\mathrm{eV}.$ . In Fig. 1B, we show photographs of thin films fabricated from mixed-cation lead mixed-halide $\\mathrm{FA_{0.83}C s_{0.17}P b[I_{(1-\\alpha)}B r_{\\it{x}}]_{3}}$ compositions. \n\n![](images/4f51c89a2fbe7549bd3d93b60e40bb7d1b70823de48a1a9c7c517b34dbcfb6fa.jpg) \nFig. 3. Device architecture and I-V characteristics for $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}(\\mathsf{I}_{0.6}\\mathsf{B r}_{0.4})_{3}$ perovskite and Si PV cells. (A) Scanning electron microscope image of a cross-section of a planar heterojunction solar cell. PCBM, phenyl-C60-butyric acid methyl ester. (B) Forward bias to short-circuit I-V curve for the best perovskite devices fabricated, using either a $\\mathsf{A g}$ metal or semi-transparent ITO top electrode, measured at a $0.38\\mathsf{V}/\\mathsf{s}$ scan rate. FF, fill factor. We also show the I-V curve of a SHJ cell, measured with direct light or with the simulated sunlight filtered through the semi-transparent perovskite solar cell (37). The SHJ cells were measured at the Centre For Renewable Energy Technologies, Loughborough, UK, under an extremely well-calibrated solar simulator. (C) Photocurrent density and power conversion efficiency measured at the maximum power point for a $30\\cdot5$ time span. (D) EQE spectrum measured in short-circuit $(J_{\\mathsf{S C}})$ configuration for the highest-efficiency perovskite cell and the SHJ cell measured with the incident light filtered through the semi-transparent perovskite cell. \n\nUnexpectedly, we did not simply shift the region of structural instability to higher energy, but we observed a continuous series of dark films throughout this entire compositional range. To confirm these observations, we also performed ultraviolet-visible absorption measurements. We obtained a sharp optical band edge for all compositions of the $\\mathrm{FA_{0.83}C s_{0.17}P b[I_{(1-\\alpha)}B r_{\\it{x}}]_{3}}$ material (Fig. 1, C and D), in contrast to $\\mathrm{FAPb}[\\mathrm{I}_{(1-x)}\\mathrm{Br}_{x}]_{3},$ which shows weak absorption in the intermediate range. \n\nIn order to understand the impact of adding Cs upon the crystallization of the perovskite, we performed x-ray diffraction (XRD) on the series of films covering the I-to-Br compositional range. In Fig. 1E, we show the XRD patterns for $\\mathrm{FAPb}[\\mathrm{I}_{(1-x)}\\mathrm{Br}_{x}]_{3},$ zoomed in to the peak around $2\\uptheta\\sim14^{\\circ}$ [the complete diffraction pattern is shown in fig. S1, along with more details on fitting these data (28)]. For the $\\mathrm{FA_{0.83}C s_{0.17}P b[I_{(1-\\alpha)}B r_{\\it{x}}]_{3}}$ perovskite, the material is in a single phase throughout the entire composition range. The monotonic shift of the (100) reflection that we observed from $2\\uptheta\\sim14.2\\ensuremath{^\\circ}$ to $14.9^{\\circ}$ is consistent with a shift of the cubic lattice constant from 6.306 to 5.955 Å as the material incorporates a larger fraction of the smaller halide, Br [in fig. S2, we show the complete diffraction pattern (28)]. Thus, for the $\\mathrm{FA_{0.83}C s_{0.17}P b[I_{(1-\\alpha)}B r_{\\it{\\alpha}x}]_{3}}$ perovskite, we have removed the structural phase transition and instability over the entire compositional range [in figs. S3 to S5 we show details of varying the Cs concentration and the Br-to-I concentration (28)]. Over the entire Br-to-I range, and for a large fraction of the Cs-FA range, the variation in lattice constant, composition, and optical band gap precisely follows Vegard's law [fig. S6 (28)], so we have total flexibility and predictability in tuning the composition and its impact on the band gap. For the results that follow below, we used the precise composition $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}},$ which has an optical band gap of 1.74 eV as determined by a Tauc plot [fig. S7 (28)]. \n\nPhotoinduced halide segregation has been reported in methylammonium lead mixed-halide perovskites $(I5)$ . A red shift in PL upon light illumination, for intensities ranging from 10 to $100\\mathrm{{mW}c m^{-2}}$ occurs, with the shift to lower energies resulting from the formation of iodine-rich domains that have lower band gaps. This limits the achievable open-circuit voltage of the solar cell device by introducing a large degree of electronic disorder. In Fig. 2, we show the PL from films of $\\mathrm{MAPb(I_{0.6}B r_{0.4})_{3}}$ perovskite and the mixed-cation mixed-halide material $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}},$ immediately after prolonged periods of light exposure, using a power density of ${\\sim}3\\mathrm{mW}\\mathrm{cm}^{-2}$ and a wavelength of $550\\mathrm{nm}$ as an excitation source. We confirmed the results observed by Hoke et al.; that is, we saw a time-dependent red shift in PL for the $\\mathbf{MAPb(I_{0.6}B r_{0.4})_{3}}$ film, which exhibited a 130- meV PL red shift after only 1 hour of illumination. We also show the time evolution of the PL from $\\mathrm{MAPb(I_{0.8}B r_{0.2})_{3}}$ , a composition previously reported in other devices (29), which shifts from 1.72 to $1.69\\mathrm{eV}$ [fig. S8 (28)]. In contrast, although we saw a rise in PL intensity, we observed no significant red shift in PL emission for the $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}}$ precursor after 1 hour of identical light illumination (which we show in Fig. 2B). Furthermore, we exposed a similar $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}}$ film to monochromatic irradiance of much higher irradiance of $5\\mathrm{W}\\mathrm{cm}^{-2}$ and observed no red shift after 240 s of illumination [fig. S9, (28)]. Under these identical conditions, we did observe a red shift in the PL for the single-cation $\\mathrm{FAPb(I_{0.6}B r_{0.4})_{3}}$ perovskite, as we have previously reported (17). In addition, under thermal stressing at $\\mathrm{130^{o}C,}$ we observed that the optical band gap and the crystal lattice of $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})}$ were stable, in contrast to those of $\\mathbf{MAPb(I_{0.6}B r_{0.4})_{3}}$ (fig. S10). \n\nBeyond halide segregation, a further deleterious observation previously made for mixed-halide perovskites has been that the energetic disorder in the material is greatly increased in comparison to the neat iodide perovskites. The ultimate opencircuit voltage that a solar cell material can generate is intimately linked to the steepness of the absorption onset just below the band edge, which can be quantified by the Urbach energy $\\left(E_{\\mathrm{u}}\\right)$ (30, 31). This $E_{\\mathrm{u}}$ reported by De Wolf et al. and Sadhanala et al. for $\\mathbf{MAPbI_{3}}$ was 15 meV (31), where small values of $E_{\\mathrm{u}}$ indicate low levels of electronic disorder. In contrast, the $E_{\\mathrm{u}}$ for $\\mathbf{MAPb(I_{0.6}B r_{0.4})_{3}}$ perovskite increased to $49.5\\mathrm{meV}$ (32). We determined $E_{\\mathrm{u}}$ by performing Fourier-transform photocurrent spectroscopy (FTPS) on complete planar heterojunction solar cells (details of the solar cells are discussed below), and in Fig. 2C we show the semi-log plot of external quantum efficiency (EQE) absorption edge of a device fabricated with the optimized precursor solution and annealing procedure. We calculated an $E_{\\mathrm{u}}$ of $16.5\\mathrm{meV}$ , which is near the values reported for the neat iodide perovskites. \n\nIn order to further assess the electronic quantity of $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3},}$ we performed optical pump terahertz-probe (OPTP) spectroscopy, which is a noncontact method of probing the photoinduced conductivity and effective charge-carrier mobility in the material. In Fig. 2D, we show the fluence dependence of the OPTP transients, which exhibit accelerated decay dynamics at higher initial photoinjected charge-carrier densities, as the result of enhanced contributions from bimolecular and Auger recombination. We extract the rate constants associated with different recombination mechanisms by global fits to these transient of the solutions to the rate equation \n\n$$\n\\frac{d n(t)}{d t}=-k_{3}n^{3}-k_{2}n^{2}-k_{1}n\n$$ \n\nwhich we show in Fig. 2D. In addition, we found that $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}}$ exhibits an excellent charge-carrier mobility of $21~\\mathrm{{cm}^{2}~V^{-1}~\\mathrm{{s}^{-1}}}$ . For comparison, the corresponding neat FA perovskite $\\mathrm{FAPb(I_{0.6}B r_{0.4})_{3}}$ only sustains charge-carrier mobilities $<1\\mathrm{cm}^{2}\\mathrm{V}^{1}\\mathrm{s}^{-1}$ that are related to the amorphous and energetically disordered nature of these materials $(I7)$ . Conversely, $\\mathrm{FA_{0.83}C s_{0.17}P b}$ $\\mathrm{(I_{0.6}B r_{0.4})_{3}}$ displays a mobility value intermediate to those we previously determined $(I7)$ for $\\mathrm{FAPbI_{3}}$ $\\mathrm{27cm^{2}V^{-1}\\thinspace s^{-1})}$ and $\\mathrm{FAPbBr_{3}}$ $\\mathrm{14~cm^{2}}$ $\\mathrm{~V~}^{-1}\\mathrm{~s~}^{-1})$ , which suggests that it is no longer limited by structural disorder. \n\nWe further assessed the potential of $\\mathrm{FA_{0.83}C s_{0.17}P b}$ $\\mathrm{(I_{0.6}B r_{0.4})_{3}}$ for incorporation into planar heterojunction PV architectures by deriving the chargecarrier diffusion length $L=[\\upmu k_{\\mathrm{B}}T/(e R)]^{0.5}$ as function of the charge-carrier density $n,$ where $R=k_{1}+n k_{2}+$ $n^{2}k_{3}$ is the total recombination rate, $k_{\\mathrm{B}}$ is the Boltzmann constant, $T$ is temperature, and $e$ is the elementary charge. In Fig. $^{\\mathrm{2E,}}$ we show that for charge-carrier densities typical under solar illuminatio $\\mathrm{n}(n\\sim10^{15}\\mathrm{cm}^{-3})$ a value of $L\\sim2.9\\upmu\\mathrm{m}$ is reached, which is comparable to values reported for highquality thin films of neat lead iodide perovskites (17, 33). The high charge-carrier mobility, slow recombination kinetics, and the long charge carrier diffusion length imply that this mixed-cation, mixed-halide perovskite should be just as effective as a high-quality solar cell absorber material as the neat halide perovskite $\\mathrm{FAPbI_{3}}$ . \n\nWe fabricated a series of planar heterojunction solar cells to assess the overall solar cell performance [in fig. S11 we describe in more detail and show data for solar cells fabricated with a range of compositional and processing parameters (28)]. We show the device architecture in Fig. 3A, which is composed of a $\\mathrm{{SnO}_{2}}$ /phenyl- $.\\mathrm{C}_{60}$ -butyric acid methyl ester $\\mathrm{\\langlePC_{60}B M},$ ) electron-selective layer, a solid $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}}$ perovskite absorber layer, and Li-TFSI–doped [TFSI, bis(trifluoromethanesulfonyl)imide] spiro-OMeTAD [2,2′,7, 7′-tetrakis(N,N-di-p-methoxyphenylamine)-9,9′- spirobifluorene] with 4-tert-butylpyridine (TBP) additive as the hole-collection layer, capped with an Ag electrode. We measured current-voltage (I-V) characteristics of such devices under a simulated air mass (AM) 1.5, under $100\\mathrm{\\mW\\cm^{-2}}$ of sunlight, and show the $I{-}V$ characteristics of one of the highest-performing devices in Fig. 3B. It delivered a short-circuit current density of $19.4~\\mathrm{mA~cm^{-2}}$ , a $V_{\\mathrm{OC}}$ of $1.2~\\mathrm{V},$ , and a PCE of $17.1\\%$ . By holding the cell at a fixed maximum power point forward-bias voltage of $0.95\\mathrm{V}$ , we measured the power output over time, reaching a stabilized efficiency of $16\\%$ (Fig. 3C). The highest $I{-}V$ scanned efficiency we measured was $17.9\\%$ [fig. S12 (28), along with a histogram of performance parameters for a large batch of devices in fig. S13 (28)]. To demonstrate that these cells can also operate with larger area, we fabricated $0.715\\mathrm{-cm^{2}}$ active layers in which the cells reach a stabilized power output of ${>}14\\%$ [fig. S14 (28)]. In Fig. 3D, we show the spectral response of the solar cell, which confirms the wider band gap of the solar cell and also integrates over the AM 1.5 solar spectrum to give $19.2\\mathrm{mAcm^{-2}}$ , in close agreement to the measured short-circuit current density $(J_{\\mathrm{SC}})$ . \n\nThis performance is very competitive with that of the best reported single-junction perovskite solar cell reported so far (30, 34), especially considering the wider band gap of our material, which should result in a few percentage points of absolute efficiency drop with respect to a 1.55-eV material (35). Importantly for tandem solar cells, this 1.74-eV material appears to be capable of generating a higher $V_{\\mathrm{OC}}$ than the 1.55-eV triiodide perovskites in planar heterojunction solar cells. Following Rau et al. (36), from the integration of the EQE over the blackbody radiation spectrum, we estimate the maximum attainable $V_{\\mathrm{OC}}$ for our $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}}$ device to be $\\mathrm{1.42V}$ (details shown in fig. S15), which is $\\boldsymbol{100}\\mathrm{mV}$ higher than that estimated for $\\mathrm{\\mathbf{MAPbI_{3}}}$ devices by Tvingstedt et al. and Tress et al. (30, 34). \n\nIn order to demonstrate the potential impact of using this new perovskite composition in a tandem architecture, we fabricated semitransparent perovskite solar cells by sputter-coating indium tin oxide (ITO) on top of the perovskite cells, with the additional inclusion of a thin “buffer layer” of solution-processed ITO nanoparticles between the spiro-OMeTAD and the ITO. The efficiency of the semi-transparent $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}}$ solar cells is $15.1\\%$ , as determined by the I-V curve, with a stabilized power output of $12.5\\%$ . Because the $J_{\\mathrm{SC}}$ is similar to that of the cell with the $\\mathbf{Ag}$ electrode, we expect that the slight drop in $V_{\\mathrm{OC}}$ and SPO will be surmountable by better optimization of the ITO sputter-deposition procedure and buffer layer. We measured a Si heterojunction (SHJ) cell, with and without a semi-transparent perovskite cell held in front of it, and determined an efficiency of $7.3\\%$ filtered and $19.2\\%$ when uncovered. These results demonstrate the feasibility of obtaining a combined tandem solar cell efficiency ranging from $19.8\\%$ , if we combine with the stabilized power output of the semi-transparent cell, to $25.2\\%$ if we combine with the highest current density–voltage $\\left(J{-}V\\right)$ measured efficiency of the $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.6}B r_{0.4})_{3}c e l l}.$ Considering further minor improvements in the perovskite, optical management and integration, and choice of Si rear cell, it is feasible that this system could deliver up to $30\\%$ efficiency. In addition, this monotonic tunability of the band gap across the visible spectrum, without the complications of a structural phase transition will have direct impact on the color tunability and optimization of perovskites for light-emitting applications. \n\n# REFERENCES AND NOTES \n\n1. V. Sivaram, S. D. Stranks, H. J. Snaith, Sci. Am. 313, 54–59 (2015). \n2. M. A. Green, K. Emery, Y. Hishikawa, W. Warta, E. D. Dunlop, Prog. Photovolt. Res. Appl. 23, 805–812 (2015). \n3. A. Shah, P. Torres, R. Tscharner, N. Wyrsch, H. Keppner, Science 285, 692–698 (1999). \n4. C. R. Kagan, D. B. Mitzi, C. D. Dimitrakopoulos, Science 286, 945–947 (1999). \n5. A. Kojima, K. Teshima, Y. Shirai, T. Miyasaka, Priv. Commun. 1, 1 (2009). \n6. M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami, H. J. Snaith, Science 338, 643–647 (2012). \n7. M. Liu, M. B. Johnston, H. J. Snaith, Nature 501, 395–398 (2013). \n8. J. Burschka et al., Nature 499, 316–319 (2013). \n9. M. Green, A. Ho-Baillie, H. J. Snaith, Nat. Photonics 8, 506–514 (2014). \n10. N. J. Jeon et al., Nat. Mater. 13, 897–903 (2014). \n11. N. J. Jeon et al., Nature 517, 476–480 (2015). \n12. J. H. Noh, S. H. Im, J. H. Heo, T. N. Mandal, S. I. Seok, Nano Lett. 13, 1764–1769 (2013). \n13. G. E. Eperon et al., Energy Environ. Sci. 7, 982 (2014). \n14. W. S. Yang et al., Science 348, 1234–1237 (2015). \n15. E. T. Hoke et al., Chem. Sci. 6, 613–617 (2015). \n16. B. Conings et al., Adv. Energy Mater. 10.1002/aenm.201500477 (2015). \n17. W. Rehman et al., Adv. Mater. 27, 7938–7944 (2015). \n18. C. D. Bailie et al., Energy Environ. Sci. 8, 956–963 (2015). \n19. P. Löper et al., Phys. Chem. Chem. Phys. 17, 1619–1629 (2015). \n20. S. Albrecht et al., Energy Environ. Sci. 10.1039/C5EE02965A (2015). \n21. A. Binek, F. C. Hanusch, P. Docampo, T. Bein, J. Phys. Chem. Lett. 6, 1249–1253 (2015). \n22. S. Pang et al., Chem. Mater. 26, 1485–1491 (2014). \n23. C. C. Stoumpos, C. D. Malliakas, M. G. Kanatzidis, Inorg. Chem. 52, 9019–9038 (2013). \n24. N. Pellet et al., Angew. Chem. Int. Ed. Engl. 53, 3151–3157 (2014). \n25. S. D. Stranks, H. J. Snaith, Nat. Nanotechnol. 10, 391–402 (2015). \n26. J.-W. Lee et al., Adv. Energy Mater. 10.1002/aenm.201501310 (2015). \n27. H. Choi et al., Nano Energy 7, 80–85 (2014). \n28. See the supplementary materials on Science Online. \n29. C. Bi, Y. Yuan, Y. Fang, J. Huang, Adv. Energy Mater. \n10.1002/aenm.201401616 (2014). \n30. K. Tvingstedt et al., Sci. Rep. 4, 6071 (2014). \n31. S. De Wolf et al., J. Phys. Chem. Lett. 5, 1035–1039 (2014). \n32. A. Sadhanala et al., J. Phys. Chem. Lett. 5, 2501–2505 (2014). \n33. R. L. Milot, G. E. Eperon, H. J. Snaith, M. B. Johnston, L. M. Herz, Adv. Funct. Mater. 25, 6218–6227 (2015). \n34. W. Tress et al., Adv. Energy Mater. 10.1002/aenm.201400812 (2014). \n35. H. J. Snaith, Adv. Funct. Mater. 20, 13–19 (2010). \n36. U. Rau, Phys. Rev. B 76, 085303 (2007). \n37. L. Mazzarella et al., Appl. Phys. Lett. 106, 023902 (2015). \n\n# ACKNOWLEDGMENTS \n\nThis project was funded in part by the Engineering and Physical Sciences Research Council through the Supergen Solar Energy Hub SuperSolar (EP/M024881/1, EP/M014797/1) and the European \n\nResearch Council through the Stg-2011 Hybrid Photovoltaic Energy Relays and the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 604032 of the MESO project, and the U.S. Office of Naval Research. M.H. is funded by Oxford PV Ltd. W.R. is supported by the Hans-BoecklerFoundation. We thank our colleagues from the Centre For Renewable Energy Technologies Photovoltaic Measurement and Testing Laboratory, Loughborough University, for their contributions to the measurements of the semi-transparent devices. We also thank K. Jacob and M. Wittig [Helmholtz-Zentrum Berlin (HZB), Institute for Silicon Photovoltaics], L. Mazzarella, and S. Kirner (HZB, Institute PVcomB) for their contributions to fabricating the SHJ cell. The University of Oxford has filed a patent related to this work. The project was designed and conceptualized by D.M. and H.J.S. D.M. performed experiments, analyzed data, and wrote the first draft of the paper. G.S. fabricated and measured devices with semi-transparent electrodes. W.R. characterized the material using THz spectroscopy. G.E. helped with the experimental work and provided technical feedback on the writing of the paper. M.S. provided input and technical direction on the FA/Cs cation mixture. M.H. performed simulations for the optical modeling and calculated the maximum achievable $V_{\\mathrm{OC}}$ . A.H. analyzed XRD data. N.S. provided input on the preparation of thin films using chemical bath depositions. L.K. and B.R. designed and supervised the fabrication of the SHJ cells. M.J. performed and analyzed EQE measurements. L.H. supervised and analyzed the THz spectroscopy measurements. H.J.S. supervised the overall conception and design of this project. All authors contributed to the writing of the paper. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/351/6269/151/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S15 \nReferences (38–42) \n\n5 October 2015; accepted 3 December 2015 \n10.1126/science.aad5845 \n\n# FOREST ECOLOGY \n\n# Dominance of the suppressed: Power-law size structure in tropical forests \n\nC. E. Farrior,1,2\\* S. A. Bohlman,3,4 S. Hubbell,4,5 S. W. Pacala6 \n\nTropical tree size distributions are remarkably consistent despite differences in the environments that support them. With data analysis and theory, we found a simple and biologically intuitive hypothesis to explain this property, which is the foundation of forest dynamics modeling and carbon storage estimates. After a disturbance, new individuals in the forest gap grow quickly in full sun until they begin to overtop one another. The two-dimensional space-filling of the growing crowns of the tallest individuals relegates a group of losing, slow-growing individuals to the understory. Those left in the understory follow a power-law size distribution, the scaling of which depends on only the crown area–to–diameter allometry exponent: a well-conserved value across tropical forests. \n\nWe explored temporal and spatial patterns in tropical forest size structure in 50 ha and 30 years of data from Barro Colorado Island, Panama (BCI) (15–17). Forest patches in the early stages of recovery from small-scale disturbances (18) develop a power function that extends through a greater range of diameters as time progresses (Fig. 2). At 25 to 30 years after disturbance, the power function extends through the full range of diameters present, and unlike in younger patches, a power law is a likely model of the data [(18), criteria following (19)]. However, the power-law fit is again lost in patches with more than 30 years since the last disturbance. \n\nHaving reached the limit of our temporal analyses, we examined forest patches as grouped by forest size. We used the metric $D_{\\mathrm{~\\tiny~est}}^{\\ast}$ as an estimate of the size threshold for tree canopy status in a patch (18). For each range of $D^{*}{}_{\\mathrm{est}},$ we fit a power function (with the same scaling as Fig. 1, fit to all data) that transitions at a single size class to an exponential distribution (Fig. 3A) (18). This best-fit size class of transition increases with $D_{\\mathrm{~\\tiny~est}}^{\\ast}$ (Fig. 3B, $P=0.005$ , $t$ test, $R$ -squared $=0.76$ , \n\nT rbeyesiize—daisrteribmuptiorntasn—ttehemferregqeunetnpcryopfetrteies of forests. Tree size distributions signal community-level interactions, are a critical diagnostic of the accuracy of scaling in mechanistic models, and are the basis of many aboveground forest carbon estimates (1–3). Despite differences in the tree vital rates that determine them, tropical forests worldwide have tree size distributions that follow tight power functions with very similar scaling for a wide range of diameters and commonly have deviations in the tails (4, 5) (Fig. 1). Such a consistent emergent pattern begs an explanation, one that is likely to provide an important key to understanding the mechanisms governing tropical forest dynamics $\\textcircled{6}$ . \n\nCurrent theories explaining the consistency of tropical forest size structure are controversial. Explanations based on scaling up individual metabolic rates (4, 7, 8) are criticized for ignoring the importance of asymmetric competition for light in causing variation in dynamic rates (9–11). Other theories, which embrace competition and scale individual tree vital rates through an assumption of demographic equilibrium $(5,10,12,13),$ are criticized for lacking parsimony, because predictions rely on site-level, size-specific parameterizations (14). Despite their differences, common to these theories is the notion that the predicted size structure is a property of steady-state forests far removed from the influence of disturbance. We tested this prediction. We explored the size structure within a well-studied tropical forest and, with theoretical corroboration, present a parsimonious and biologically intuitive explanation for the powerfunction size structure, observed deviations, and the consistency of the scaling across forests. \n\n![](images/626619351ce5c1265bd6ad994c9a257894ac0ebc57982516d05220b9260c8b5f.jpg) \nFig. 1. Size distribution of the 50-ha tropical forest dynamics plot on BCI. The average (points) and range (bars) by size class among all seven censuses are shown. The best-fit power law distribution to all diameters from censuses 3 to 7 (18) is drawn (black line).The expected range of variation for that power law, given the average census sample size by size class, is in gray $[95\\%$ range (18)]. \n\n# Science \n\n# A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells \n\nDavid P. McMeekin, Golnaz Sadoughi, Waqaas Rehman, Giles E. Eperon, Michael Saliba, Maximilian T. Hörantner, Amir Haghighirad, Nobuya Sakai, Lars Korte, Bernd Rech, Michael B. Johnston, Laura M. Herz and Henry J. Snaith \n\nScience 351 (6269), 151-155. DOI: 10.1126/science.aad5845 \n\n# Perovskites for tandem solar cells \n\nImproving the performance of conventional single-crystalline silicon solar cells will help increase their adoption. The absorption of bluer light by an inexpensive overlying solar cell in a tandem arrangement would provide a step in the right direction by improving overall efficiency. Inorganic-organic perovskite cells can be tuned to have an appropriate band gap, but these compositions are prone to decomposition. McMeekin et al. show that using cesium ions along with formamidinium cations in lead bromide−iodide cells improved thermal and photostability. These improvements lead to high efficiency in single and tandem cells. \n\nScience, this issue p. 151 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/351/6269/151 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2016/01/06/351.6269.151.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/351/6269/113.full \n\nREFERENCES \n\nThis article cites 40 articles, 4 of which you can access for free http://science.sciencemag.org/content/351/6269/151#BIBL \n\nPERMISSIONS \n\nhttp://www.sciencemag.org/help/reprints-and-permissions \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1039_c5ee03874j", + "DOI": "10.1039/c5ee03874j", + "DOI Link": "http://dx.doi.org/10.1039/c5ee03874j", + "Relative Dir Path": "mds/10.1039_c5ee03874j", + "Article Title": "Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency", + "Authors": "Saliba, M; Matsui, T; Seo, JY; Domanski, K; Correa-Baena, JP; Nazeeruddin, MK; Zakeeruddin, SM; Tress, W; Abate, A; Hagfeldt, A; Grätzel, M", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "Today's best perovskite solar cells use a mixture of formamidinium and methylammonium as the monovalent cations. With the addition of inorganic cesium, the resulting triple cation perovskite compositions are thermally more stable, contain less phase impurities and are less sensitive to processing conditions. This enables more reproducible device performances to reach a stabilized power output of 21.1% and similar to 18% after 250 hours under operational conditions. These properties are key for the industrialization of perovskite photovoltaics.", + "Times Cited, WoS Core": 4453, + "Times Cited, All Databases": 4732, + "Publication Year": 2016, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000378244200005", + "Markdown": "View Article Online View Journal \n\n# Energy & Environmental Science \n\nAccepted Manuscript \n\nThis article can be cited before page numbers have been issued, to do this please use: M. Saliba, T. \nMatsui, J. Seo, K. Domanski, J. Correa-Baena, N. Mohammad K., S. M. Zakeeruddin, W. Tress, A. Abate, A. \nHagfeldt and M. Grätzel, Energy Environ. Sci., 2016, DOI: 10.1039/C5EE03874J. \n\n![](images/56453218514136963e735a8523703d8919d4ebb74cd80aff57c113202ee6df15.jpg) \n\nThis is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication. \n\nAccepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof reading. Using this free service, authors can make their results available to the community, in citable form, before we publish the edited article. We will replace this Accepted Manuscript with the edited and formatted Advance Article as soon as it is available. \n\nYou can find more information about Accepted Manuscripts in the Information for Authors. \n\nPlease note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. \n\nDue to their enormous potential for the future of photovoltaics, perovskite solar cells have attracted much attention recently. However, achieving stable and reproducible high efficiency results is a major concern towards industrialization. \n\nTo date, the best perovskite solar cells use mixed organic cations (methylammonium (MA) and formamidinium (FA)) and mixed halides (Br and I). Unfortunately, MA/FA compositions are sensitive to processing conditions because of their intrinsic structural and thermal instability. The films frequently contain detrimental impurities and tend to be less crystalline explaining the large variability observed by many. Adding small amounts of inorganic cesium (Cs) in a “triple cation” (Cs/MA/FA) configuration results in highly monolithic grains of more pure perovskite. The films are more robust to subtle variations during the fabrication process enabling a breakthrough in terms of reproducibility where efficiencies larger than $20\\%$ are reached on a regular basis. Using this approach, efficiencies up to $21.1\\%$ (stabilized) and outputs of $18\\%$ , even after 250 hours of aging under operational conditions are achieved. \n\nTherefore, triple (or multiple) cation mixtures are a novel compositional strategy on the road to industrialization of perovskite solar cells with better stabilities and repeatable high efficiencies. \n\n# Cesium-containing Triple Cation Perovskite Solar Cells: Improved Stability, Reproducibility and High Efficiency \n\nReceived 00th January 20xx, Accepted 00th January 20xx \n\nDOI: 10.1039/x0xx00000x www.rsc.org/ \n\nMichael Saliba,a,d\\* Taisuke Matsui,b Ji-Youn Seo,a Konrad Domanski,a Juan-Pablo Correa-Baena,c Mohammad Khaja Nazeeruddin,d Shaik M. Zakeeruddin,a Wolfgang Tress,a Antonio Abate,a Anders Hagfeldt,c and Michael Grätzela \n\nToday’s best perovskite solar cells use a mixture of formamidinium and methylammonium as the monovalent cations. With the addition of the inorganic cesium, the resulting triple cation perovskite compositions are thermally more stable, contain less phase impurities and are less sensitive to processing conditions. This enables more reproducible device performances reaching a stabilized power output of $\\sim21.1\\%$ and $\\sim18\\%$ after 250 hours under operational conditions. These properties are key for the industrialization of perovskite photovoltaics. \n\n# Introduction \n\nPerovskite solar cells have attracted enormous interest in recent years with power conversion efficiencies (PCE) leaping from $3.8\\%$ in $2009^{1}$ to the current world record of $21.0\\%$ .2 \n\nThe organic-inorganic perovskite material has an $\\mathsf{A B X}_{3}$ structure and is typically comprised of an organic cation, $\\mathsf{A}=$ (methylammonium (MA) $C H_{3}N H_{3}^{+}$ ; formamidinium (FA) $C H_{3}(N H_{2})_{2}^{+}),^{3-5}$ a divalent metal, $\\mathsf{B}=(\\mathsf{P b}^{2+};\\mathsf{S n}^{2+};\\mathsf{G e}^{2+}),^{4,6}$ and an anion $\\mathsf{X}=(\\mathsf{C l}^{\\top};\\mathsf{B r}^{\\top},$ ; I-, $\\mathsf{B F}_{4}\\cdot\\overline{{\\mathsf{\\Omega}}}$ ; $\\mathsf{P F}_{6}^{-}$ ; SCN-).7-11 These perovskites can be processed by various techniques ranging from spin coating, di p coating,12 2-step interdiffusion,13 chemical vapour deposition,14 spray pyrolysis,15 atomic layer deposition,16 inkjet printing,17 to thermal evaporation18, 19 making them one of the most versatile photovoltaic (PV) technologies. The high performances of perovskite solar cells have been attributed to exceptional material properties such as remarkably high absorption over the visible spectrum,6 low exciton binding energ y,20, 21 charge carrier diffusion lengths in the μm-range, 22- \n\n24 a sharp optical band edge, and a tuneable band gap from 1.1 \nto $2.3\\ \\mathsf{e V}$ by interchanging the above cations,25, 2 6 metals27, 28 \nand/or halides.29 This has extended the scope of such \nperovskites towards lasing,30, 31 light emitting devices,32 \nplasmonics,33, 34 tandem solar cells,35, 36 photodetectors37, 38 \nand XRD-detection.39 \n\nUsing perovskites with mixed cations and halides has become important because the pure perovskite compounds suitable for PV applications, which are primarily ${\\mathsf{M A P b}}\\mathsf{X}_{3},$ $\\mathsf{F A P b}\\mathsf{X}_{3}$ and $\\mathsf{C s P b}\\mathsf{X}_{3}$ $[X=B r$ or I), come with numerous disadvantages. \n\n$\\mathsf{M A P b l}_{3}$ perovskites, for example, have never reached efficiencies larger than $20\\%$ despite the numerous attempts since the early days of the field.1, 4 Moreover, there are concerns with respect to the structural phase transition at $55^{\\circ}C,^{28}$ degradation on contact with moisture, thermal stability,40, 41 a s well as light-induced trap-state formation and halide segregation in the case of “mixed halide” perovskites MAPbBrxI(3-x). 42 \n\nIn principle, using $\\mathsf{F A P b l}_{3}$ instead of $\\mathsf{M A P b l}_{3}$ is advantageous due to a reduced band gap, which is closer to the singlejunction optimum43 and would thus allow for higher solar light harvesting efficiency. However, pure $\\mathsf{F A P b l}_{3}$ lacks structural stability at room temperature as it can crystallize either into a photoinactive, non-perovskite hexagonal δ-phase (“yellow phase”); or a photoactive perovskite $\\mathfrak{a}$ -phase (“black phase“),28, 44, 45 which is sensitive to solvents or humidity.46 \n\nAlternatively, the often overlooked purely inorganic cesium lead trihalide perovskites exhibit excellent thermal stability.47 However, ${\\mathsf{C s P b B r}}_{3}$ does not have an ideal band gap for PVs. The perovskite phase of $\\mathsf{C s P b l}_{3}$ on the other hand has a more suitable band gap of $1.73\\mathrm{eV}^{48}$ and has been investigated for its good emissive properties.49 Unfortunately, $\\mathsf{C s P b l}_{3}$ crystallizes in a photoinactive, orthorhombic δ-phase (“yellow phase”) at room temperature and the photoactive perovskite phase (“black phase”) is only stable at temperatures above $300^{\\circ}\\mathsf C$ .48 Consequently, the pure perovskite compounds fall short mainly due to thermal or structural instabilities. Therefore, it has become an important design principle to mix the cations and halides in order to achieve perovskite compounds with improved thermal and structural stability. \n\nIndeed, the perovskites for the highest PCEs, using the “antisolvent method”, have mixed cations and halides.46 Our group has followed a similar approach with a mixed $^{\\prime\\prime}\\mathsf{M A}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.83}\\mathsf{B r}_{0.17})_{3},\\mathsf{\\Omega}^{\\prime\\prime}$ formulation that has reached efficiencies exceeding $18\\%$ for planar devices.35 Using this material, we have recently achieved a PCE of $20.2\\%$ with a novel hole transporter material $\\left(\\mathsf{H T M}\\right)^{50}$ as well as $20.8\\%$ upon inclusion of a lead excess.51 This approach is also the basis for the current world record of $21.0\\%^{2}$ showing that combining different cations can combine the advantages of the constituents while avoiding their drawbacks. The recent success of the MA/FA mixtures demonstrates that a small amount of MA is already sufficient to induce a preferable crystallization into the photoactive phase of FA perovskite resulting in a more thermally and structurally stable composition than the pure MA or FA compounds. This illustrates that the MA can be thought of as a “crystallizer” (or stabilizer) of the black phase FA perovskite. From this, we can already conclude that using smaller cations such as MA plays a key role to form structurally stable black phase FA perovskite. However, even with MA present, it is still challenging to obtain FA perovskite with no traces of the yellow phase as frequently observed even for very high efficiency solar cells.25, 46 \n\nThese yellow phase impurities need to be avoided as even small quantities influence the crystal growths and morphology of the perovskite inhibiting efficient charge collection and therefore limiting the performance of the devices. \n\nOne cation that has recently attracted attention in mixed cation perovskites is the inorganic cesium (Cs) with an ionic radius of $\\mathsf{1.81\\AA},$ , which is considerably smaller than MA (2.70 Å) or FA (2.79 Å).52 To date, only a few reports investigate the effect of cation mixtures with Cs. Choi et al. present ${\\mathsf{C s/M A}}$ mixtures which prove, in principle, that embedding small amounts of Cs in a $\\mathsf{M A P b l}_{3}$ structure can result in a stable perovskite film reaching PCEs of $8\\%$ .53 Furthermore, Park and co-workers report on Cs/FA mixtures showing enhanced thermal and humidity stability, reaching PCEs of $16.5\\%$ .54 The improved structural stability is explained by Yi et al. who show that Cs is effective in assisting the crystallisation of the black phase in FA perovskite due to entropic stabilisation.55 In that work the halides (Br and I) are also mixed resulting in PCEs up to $18\\%$ . McMeekin et al. also found that a similar composition, with a shifted band gap, is particularly suitable for perovskitesilicon tandems.56 While this manuscript was prepared, another study by Li et al. found that the effective ionic radius of the $C s/F A$ cation can be used to fine-tune the Goldschmidt tolerance factor towards more structurally stable regions.57, 58 From this, it is evident that Cs is very effective in “pushing” FA into the beneficial black perovskite phase due to the large size difference between Cs and FA. MA on the other hand also induces the crystallisation of FA perovskite but at a much slower rate (because MA is only slightly smaller than FA) which still permits for a large fraction of the yellow phase to persist. As already mentioned, such MA/FA compounds already show impressive PCEs and thus advancing these compounds is a likely avenue to advance perovskite solar cells in general. \n\nHence, this gives rise to our novel strategy of using a triple Cs/MA/FA cation mixture where Cs is used to improve MA/FA perovskite compounds further. We hypothesize and show that already a small amount of Cs is sufficient to effectively suppress yellow phase impurities permitting for more pure, defect-free perovskite films. \n\nIn this work, we demonstrate that the use of all three cations, Cs, MA, FA, provides additional versatility in fine-tuning for high quality perovskite films that can yield stabilized PCEs exceeding $21\\%$ and $\\sim18\\%$ after 250 hours under operational conditions. The triple cation perovskite films are thermally more stable and less affected by fluctuating surrounding variables such as temperature, solvent vapours or heating protocol. This robustness is important for reproducibility, which is one of the (often underappreciated) key requirements for cost-efficient large scale manufacturing of perovskite solar cells. \n\n# Results and Discussion \n\nWe investigated triple cation perovskites of the generic form $^{\\prime\\prime}C s_{\\mathrm{x}}(\\mathsf{M A}_{0.17}\\mathsf{F A}_{0.83})_{(100-\\mathrm{x})}\\mathsf{P b}(\\mathsf{I}_{0.83}\\mathsf{B r}_{0.17})_{3}.^{\\prime\\prime}$ abbreviated for convenience as ${\\mathsf{C s}}_{\\mathrm{{x}}}{\\mathsf{M}}$ from here $\\mathbf{\\dot{x}}$ is in percent throughout the manuscript), where M stands for “mixed perovskite”. ${\\mathsf{C s}}_{0}{\\mathsf{M}},$ , i.e. no Cs, is the basic composition for the current world record devices.2 We note that these compositions refer to the precursor that also contains a lead excess as reported elsewhere.51, 59 All preparation details are given in the Supporting Information. \n\n# Film characterisation \n\n![](images/ecf9f7f741f8c50a652468ed56da6e45bc52cbadfc3f78dcb6acf273fd1eed1b.jpg) \nFig. 1 XRD and optical characterisation of ${\\mathsf{C s}}_{\\mathsf{x}}{\\mathsf{M}}$ compounds. (a) XRD spectra of perovskite upon addition of Cs investigating the series $\\mathsf{C s}_{\\mathrm{x}}(\\mathsf{M A}_{0.17}\\mathsf{F A}_{0.83})_{(1-\\mathrm{x})}\\mathsf{P b}(\\mathsf{I}_{0.83}\\mathsf{B r}_{0.17})_{3}$ , abbreviated as $\\mathsf{C s}_{\\mathsf{x}}\\mathsf{M}$ where M stands for “mixed perovskite. $\\mathsf{C s}_{\\mathsf{x}}\\mathsf{M}$ with $\\scriptstyle x=0$ ,5,10, $15\\%$ (b)Corresponding absorbance (dashed lines) and photoluminescence (PL) spectra (solid lines) \n\nIn Fig. 1a, we show X-ray diffraction (XRD) data for $C_{\\times}M$ with x ${\\bf\\Omega}=0.$ , 5, 10, $15\\%$ . All compositions exhibit the typical perovskite peak at ${\\sim}14^{\\circ}$ . For ${\\mathsf{C s}}_{0}{\\mathsf{M}}_{\\ast}$ , we also note the small side peaks at $\\Omega1.6^{\\circ}$ and $12.7^{\\circ}$ corresponding to the photoinactive hexagonal δ-phase of $\\mathsf{F A P b l}_{3}$ and the cubic $\\mathsf{P b l}_{2},$ respectively. This is a very typical observation for the mixed perovskite composition showing incomplete conversion of the FA perovskite into the photoactive black phase. This finding is noteworthy because the highest device efficiencies thus far may have been achieved despite these impurities. Upon addition of small amounts of Cs from 0, 5, 10, to $15\\%$ , the yellow phase and the $\\mathsf{P b l}_{2}$ peak disappear completely. Moreover, the absorption and photoluminescence (PL) spectra in Fig. 1b are blue-shifted by ${\\sim}10\\ \\mathsf{n m}$ from $\\mathsf{C s}_{0}\\mathsf{M}$ $\\mathsf{t o C s}_{15}\\mathsf{M}$ . In Fig. S1, we also show top view scanning electron microscopy (SEM) images for the $\\mathsf{C s}_{\\mathsf{x}}\\mathsf{M}$ series. \n\nThe data in Fig. 1 is consistent with the Cs cation being integrated into the perovskite lattice. The influence of the smaller Cs on the MA/FA combination is a lowering of the effective ${C S/M A/F A}$ cation radius in the new perovskite compound. This shifts the tolerance factor towards a cubic lattice structure that matches the black perovskite phase. Now, the photoactive black phase is entropically stabilized at room temperature, resulting in a suppression of the hexagonal yellow phase of FA perovskite (which is not entropically stabilized at room temperature anymore). This explanation is in good agreement with the recent works of Li et al.,57 Yi et al.,55 and Lee et al.54 who used Cs/FA mixtures as the effective cation. Interestingly, Li et al. also observe phase separation at relatively large Cs concentrations, which is attributed to the large size mismatch between Cs and FA. Using a mixture of three cations may alleviate this constraint because the relative size differences of the cations are smaller which in turn could decrease the entropic preference for phase separation. \n\nThe suppression of the yellow phase in the $\\mathsf{C s}_{\\mathsf{x}}\\mathsf{M}$ series is noteworthy because the $\\mathsf{C s}_{0}\\mathsf{M}$ perovskite already shows extraordinarily high PCEs that have resulted from a very laborious optimisation process (including the electron and hole extracting layers). Thus, finding another variable that can improve the transition into the black phase without affecting the other parameters is very important for further developments. This is especially true as we are getting closer to the theoretical Shockley-Queisser limit of $\\sim30\\%$ for a single junction PSC with a band gap of 1.55 eV.43 \n\nWe characterize the $\\mathsf{C s}_{\\mathsf{x}}\\mathsf{M}$ further by assessing its thermal stability and choose, for simplicity, to only compare $\\mathsf{C s}_{0}\\mathsf{M}$ and $\\mathsf{C s}_{10}\\mathsf{M}$ in the following (because we initially measured the best device performance close to $21\\%$ on a $\\mathsf{C s}_{10}\\mathsf{M}$ device, see Fig. S6a). In Fig. 2, we show films of ${\\mathsf{C s}}_{0}{\\mathsf{M}}$ and $\\mathsf{C s}_{10}\\mathsf{M}$ kept at $130^{\\circ}\\mathsf{C}$ for 3 hours in dry air. It is evident from the inset images that the perovskite films without Cs (Fig. 2a) start bleaching after this aggressive thermal stress test as evidenced by the decreased absorption spectrum. $\\mathsf{C s}_{10}\\mathsf{M}$ on the other hand retains the dark black colour and does not bleach noticeably (see Fig. 2b); albeit some degradation is visible but it is much less pronounced than for $\\mathsf{C s}_{0}\\mathsf{M}$ . Thus, we conclude an improved thermal stability for the $\\mathsf{C s}_{10}\\mathsf{M}$ films. In Supplementary Note 1, we show XRD data for different cationic mixtures. Fig. S2 shows $\\mathsf{C s}_{0}\\mathsf{M}$ and $\\mathsf{C s}_{10}\\mathsf{M}$ films at different times during the $130^{\\circ}\\mathsf{C}$ aging procedure revealing that the Cs-containing films degrade less quickly. Fig. S3 shows an MA-free version of our champion recipe, i.e. $^{\\prime\\prime}{\\sf C s}_{0.10}{\\sf F A}_{0.90}{\\sf P b}\\bigl(\\vert_{0.83}{\\sf B}{\\sf r}_{0.17}\\bigr)_{3}^{\\prime\\prime}$ after $4h$ at $130^{\\circ}\\mathsf{C}$ revealing rapid degradation compared to the similar $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.60}\\mathsf{B r}_{0.40})_{3}$ compound.56 Therefore, we conclude that Cs increases the thermal stability for a fixed halide ratio and also note that an increased Br content contributes considerably to thermal stability. \n\n![](images/c447ecb79f136f818a7a925691f16fea4d39cdce251d664e93f6f0bfe1bfef0c.jpg) \nFig. 2 Thermal stability and film formation dependence on processing conditions. UV–visible absorption of $\\mathsf{C s}_{0}\\mathsf{M}$ (a) and $\\mathsf{C s}_{10}\\mathsf{M}$ (b) films annealed at $130^{\\circ}\\mathsf{C}$ for 3 hours in dry air with corresponding images. (c) Absorption spectra of as-fabricated films (at room temperature) without the subsequent annealing step, the $\\mathsf{C s}_{0}\\mathsf{M}$ film is red (red line, image of red film). Upon addition of cesium, the $\\mathsf{C s}_{10}\\mathsf{M}$ film turns black (black line, image of black film). The inset XRD data shows that $\\mathsf{C s}_{10}\\mathsf{M}$ has the characteristic perovskite (black) pattern whereas $\\mathsf{C s}_{0}\\mathsf{M}$ does not. (d) When the spin coating processing temperature, $\\mathsf{T}_{\\mathsf{G l o v e}\\mathsf{b o x}},$ is kept at $18^{\\circ}\\mathsf C,$ $\\mathsf{C s}_{0}\\mathsf{M}$ does not form a perovskite phase even after annealing at $100^{\\circ}\\mathsf{C}$ for 1 hour (solid red line). The perovskite phase forms, however, when using a processing temperature of $25^{\\circ}\\mathsf{C}$ (dashed black line). $\\mathsf{C s}_{10}\\mathsf{M}$ forms readily the perovskite phase at $18^{\\circ}\\mathsf{C}$ (solid black line). The inset images show representative $\\mathsf{C s}_{0}\\mathsf{M}$ films at $18^{\\circ}\\mathsf{C}$ (red), $25^{\\circ}\\mathsf{C}$ (black); or for $\\mathsf{C s}_{10}\\mathsf{M}$ at $18^{\\circ}\\mathsf C$ (black). \n\nFurthermore, we investigate the film formation dependence on processing conditions in the glove box. Fig. 2c reveals that, unsurprisingly, $\\mathsf{C s}_{0}\\mathsf{M}$ does not form a perovskite phase directly after deposition (without annealing step) as can be seen from the absorbance data, which does not show the characteristic perovskite absorption onset. This is confirmed by the inset image (showing that the film remains red) and corresponding XRD data that does not exhibit the characteristic perovskite peak at ${\\sim}14^{\\circ}$ . On the other hand, the same deposition conditions for $\\mathsf{C s}_{10}\\mathsf{M}$ yield a clear black perovskite phase as evidenced by the film’s colour, the absorption spectrum and the perovskite peak in the inset XRD pattern confirming that Cs induces the black phase at room temperature. We hypothesize therefore that the Cs containing system is less sensitive to temperature variations in the heating protocol or the precise temperature in the glove box at the very beginning of the perovskite film formation. We verified this hypothesis by spincoating $\\mathsf{C s}_{0}\\mathsf{M}$ and $\\mathsf{C s}_{10}\\mathsf{M}$ precursor solutions in a temperaturecontrolled, nitrogen-filled glove box setting the temperature to \n\n$18^{\\circ}\\mathsf{C}$ and $25^{\\circ}C$ with subsequent annealing of the perovskite films at $100^{\\circ}\\mathsf{C}$ for 1 hour. The results are shown in Fig. 2d. At $18^{\\circ}\\mathsf C,$ , the ${\\mathsf{C s}}_{0}{\\mathsf{M}}$ perovskite precursor does not yield the black phase; it remains red and resembles the non-annealed films as shown in Fig. 2c despite heating at $100^{\\circ}\\mathsf{C}$ for 1 hour. On the other hand, the $\\mathsf{C s}_{10}\\mathsf{M}$ turns black directly after spin coating and remains in the black phase after the 1 hour annealing step. Increasing the temperature of the glove box by $7^{\\circ}C$ towards $25^{\\circ}C$ is already sufficient to induce the black phase formation in the $\\mathsf{C s}_{0}\\mathsf{M}$ perovskite as can be seen from the absorbance data. This last point is especially interesting as it may help identifying possible “hidden” variables during the manufacturing process, which are not taken into account adequately because their relevance is not appreciated sufficiently yet. Hence, we can already conclude that adding Cs benefits MA/FA perovskites in terms of suppression of the yellow phase, thermal stability and “robustness” to temperature variations during processing. In the next section, \n\nwe \npresent \nthe \napplicati \non of these \ntriple \ncation \nperovskit e films for solar cells. \nDevice \ncharacter \nisation \nAs \nillustrate \nd in the \ncross \nsectional \nSEM \n\n![](images/0ae961a668a8b098cf5be71f56259d4f5e39f80a54c779cb79cd49ca9717102d.jpg) \nFig. 3 Cross sectional scanning electron microscope (SEM) images of (a) $\\mathsf{C s}_{0}\\mathsf{M}$ (b) $\\mathsf{C s}_{5}\\mathsf{M}$ (c) low magnification ${\\mathsf{C s}}_{5}{\\mathsf{M}}$ device \n\nimages in Fig. 3, the solar cell architecture used is a stack of glass/fluorine-doped tin oxide/compact ${\\mathsf{T i O}}_{2},$ /Li-doped mesoporous $\\mathsf{T i O}_{2}^{59}.$ /perovskite/spiro-OMeTAD/gold. All fabrication details can be found in the Supporting Information. For the first optimisation, we use the above $\\mathsf{C s}_{\\mathsf{x}}\\mathsf{M}$ series and present current density-voltage (JV) scans in Fig. S4 (and Table S1). The efficiency for our baseline on this batch of devices was just below $17\\%$ with respectable currents of ${\\sim}20\\ m\\mathsf{A c m}^{-2}$ . Open circuit voltages in general were relatively high reaching $\\ensuremath{1.1\\vee}$ . The main parameter lacking was the fill factor at 0.7. As the Cs is added, the series improves mainly in fill factor reaching 0.77 at optimum $x=10\\%$ . \n\nWith three cations present, the parameter space for possible compositions is increased accordingly (especially considering that the halide ratio could be tuned as well). Thus, in Supplementary Note 2, together with Fig. S5 and Table S2, we vary the ratio of Cs:MA for the $\\mathsf{C s}_{10}\\mathsf{M}$ composition while keeping FA fixed. We show that the resulting device data has an optimum with both Cs and MA present indicating that the presence of both Cs and MA is highly relevant. Although we initially achieved our highest PCE with ${\\mathsf{C s}}_{10}\\mathsf{M}$ , we found later that we reach slightly more consistent and equally high values with $\\mathsf{C s}_{5}\\mathsf{M}$ (not shown here). In a next step, we compare the cross sectional SEM images of a full $\\mathsf{C s}_{0}\\mathsf{M}$ (Fig. 3a) and $\\mathsf{C s}_{5}\\mathsf{M}$ (Figs 3b and 3c) device. Interestingly, we observe that the perovskite grains for the $\\mathsf{C s}_{5}\\mathsf{M}$ devices are more monolithic, i.e. they tend to go from bottom to top. For ${\\mathsf{C s}}_{0}{\\mathsf{M}}_{\\ast}$ , the grains tend to stack on top of each other. This could be a first reason for the superior and more consistent device performances of $\\mathsf{C s}_{5}\\mathsf{M}$ because more uniform grains enable better charge transport, which explains the higher fill factor. We hypothesize that the film formation is assisted by the addition of Cs inducing perovskite seeds already at room temperature. These seeds in turn become nucleation sites for further growth during the crystallisation leading to more uniform grains. A similar process was recently reported by Li et al. where MAImodified PbS nanoparticles acted as seeds for crystal growth of highly uniform perovskite films.60 This presumed mechanism is supported by the fact that the Cs-based films are already black at room temperature with the XRD data showing a pronounced perovskite peak (see inset of Fig. 2c). However, we note that more research is necessary to fully characterise and prove the precise crystallisation mechanism. \n\nOne important aspect of perovskite solar cell research and development is manufacturability (production capacity and yields) without large batch-to-batch variations which, unfortunately, can be the case for the MA/FA mixtures. This has been hampering the entire research field and it is hard to pinpoint “hidden” variables influencing this system (apart from preparative errors). Simply put, perovskite solar cells can only be a serious contender in the PV industry if they can be shown to be long-term stable (towards which the Cs containing perovskites may contribute greatly as pointed out in the thermal stability tests in Figs 2a and 2b) and at the same time manufactured in a reproducible way at large scale. \n\nTable S3 is especially instructive to elucidate this point. In this experiment, we fixed $\\times$ to $17\\%$ and varied y from 0 to $17\\%$ . Thus, $\\mathsf{C s}_{0}\\mathsf{M}$ can be expressed as $\\mathbf{\\nabla}\\times\\mathbf{\\sigma}=0$ and $y=17\\%$ which should, in principle, result in high efficiency control devices. However, we had a “bad batch” with low device efficiencies $(<15\\%$ PCE) without any easily discernible explanation. Interestingly, upon addition of Cs, the device performances improved towards reasonable efficiencies of about $16\\%$ . We believe that this is an important hint to the cause of the variability observed for MA/FA mixtures by so many groups, including ours. As we have noted in Figs 2c and 2d, the stabilisation of the black phase of FA perovskite with MA alone is very sensitive to the temperature at the beginning of the crystallisation process. \n\n![](images/879929913c380e1e1b39e56f04a3dff3d0852db7346e0f23ec5817a4374ff232.jpg) \nFig. 4 Statistics of 40 controls $(\\mathsf{C s}_{0}\\mathsf{M})$ and 98 Cs-based $(\\mathsf{C s}_{5}\\mathsf{M})$ )devices as collected over 18 different batches. We note that alldevice parameters and the standard deviation (S.D.),a metric forthe reproducibility, improved: The $\\mathsf{V}_{\\mathsf{o c}}$ improved from $1121\\pm25$ $[n=40]$ to $1132\\pm25\\mathrm{~mV}$ $[n=98]$ , the $\\mathsf{J}_{\\mathsf{s c}}$ improved from $20.16{\\pm}1.39$ to $21.86{\\pm}0.69\\mathrm{mAcm^{-2}}$ , the FF improved from $0.693{\\scriptstyle\\pm0.028}$ to $0.748{\\scriptstyle\\pm0.018}$ , and the PCE improved from $16.37{\\scriptstyle\\pm1.49}$ to $19.20{\\scriptstyle\\pm0.91\\%}$ . 20 independent devices show efficiencies $>20\\%$ . \n\nThis could cause large deviation even within the same batch as the processing temperature may have changed during the fabrication. It is plausible that other variables, such as solvent vapours, affect the MA/FA perovskite composition strongly as well. Therefore, the MA/FA composition puts very narrow constraints on the manufacturing process as extreme care and precision is required in order to obtain high quality perovskite films. This is not a robust manufacturing protocol and therefore not suitable for industrial-scale manufacturing, where widening the parameter tolerance for high quality perovskite films translates into a higher likelihood for economic feasibility of the process. In the case of the “bad batch”, we deduced that temperature in the glove box was artificially low on the day of fabrication due to maintenance reasons, which highlights the need to have precise temperature control when using MA/FA mixtures. \n\nUpon reinstating the previous operation conditions, we conducted a large scale test with the $\\mathsf{C s}_{5}\\mathsf{M}$ composition. Fig. 4 shows the device statistics (open circuit voltage, short circuit current, fill factor and PCE) of 40 controls $(\\mathsf{C s}_{0}\\mathsf{M})$ and $98\\subset s_{5}{\\mathsf{M}}$ devices collected over 18 different batches (prepared by three different people). We note improvements in all device parameters and especially in the standard deviation (S.D.), which is a metric for the reproducibility: The $\\mathsf{V}_{\\mathsf{o c}}$ improved from $1121\\pm25$ $({\\mathsf n}~=~40)$ to $1132\\pm25\\mathrm{mV}$ $(11\\ =\\ 98)$ , the $\\mathsf{J}_{\\mathsf{s c}}$ improved from $20.16{\\pm}1.39$ to $21.86{\\pm}0.69\\mathrm{mAcm^{-2}}$ , the FF improved from $0.693{\\scriptstyle\\pm0.028}$ to $0.748{\\scriptstyle\\pm0.018}$ , and the PCE improved from $16.37{\\scriptstyle\\pm1.49}$ to $19.20{\\scriptstyle\\pm0.91\\%}$ . 20 independent devices show efficiencies $>20\\%$ . \n\nIn Fig. 5a, we show our highest stabilized PCE exceeding $21\\%$ . The inset depicts the stabilized power output under maximum power point tracking reaching ${\\sim}21.1\\%$ (at $960~\\mathrm{mV}_{\\it{i}}$ which is in good agreement with the JV scans. \n\nIn Figs S6a and S6b (together with Fig. S7, Tables S5 and S6), we show more high performance devices verifying the reproducibility of our devices. The voltage scan rate for all scans was $10\\mathsf{m}\\mathsf{v}^{-1}$ and no device preconditioning, such as light soaking or forward voltage bias applied for a long time, was applied before starting the measurement. This resembles quasi steady-state conditions as suggested by Unger et al. and Kamat and co-workers.61, 62 Additionally, in Fig. S8 we show another $\\mathsf{C s}_{5}\\mathsf{M}$ device measured with different scan speeds to illustrate further that the slow scan speeds are reliable for devices with little hysteresis. We note the exceptionally high fill factors reaching up to ${\\sim}0.8.$ , values rarely reached even for the highest performances. We predict that this composition can be the basis for $>21.1\\%$ devices in the future using simple manufacturing improvements. \n\n![](images/9d05dbfeab525603b725163801f62a18f40272f68e41b21ccb82a76ec3a09d8e.jpg) \nFig. 5 JV and stability characteristics (a) Current-voltage scans for the best performing ${\\mathsf{C s}}_{5}{\\mathsf{M}}$ device showing PCEs exceeding $21\\%$ .The fullhysteresisloop is reported inTable S4.The inset shows the poweroutput under maximum power pointtracking for $60s,$ starting from forward bias and resulting in a stabilized power output of $21.1\\%$ (at $960~\\mathrm{mV}$ ). The voltage scan rate for all scans was $\\mathsf{10m V s^{-1}}$ and no device preconditioning,such as light soaking or forward voltage bias applied for a long time, was applied before starting the measurement. (c) Aging for $250\\mathsf{h}$ of a high performance $\\mathsf{C s}_{5}\\mathsf{M}$ and $\\mathsf{C s}_{0}\\mathsf{M}$ device in nitrogen atmosphere heldatroom temperature under constantillumination and maximum power pointtracking.The maximum power point wasupdated every60sbymeasuringthecurrentresponse toasmallperturbation in potential.AJVscan was taken periodicallytoextract thedeviceparameters.Thisagingtestresemblessealeddevicesunderrealisticoperationalconditions(as opposedtoshelfstabilityfdeviceskeptinadryatmosphereinthedarkandmeasuredperiodicall).Thedeviceefficiencyof ${\\mathsf{C s}}_{5}{\\mathsf{M}}$ drops from $20\\%$ to $\\sim18\\%$ (red curve, circles) where it stays relatively stable for at least $250\\mathsf{h}$ . This is not the case for ${\\mathsf{C s}}_{0}{\\mathsf{M}}$ (black curve, squares). \n\nFurthermore, in Fig. 5b we investigate long-term device stability of a high performance $\\mathsf{C s}_{0}\\mathsf{M}$ and $\\mathsf{C s}_{5}\\mathsf{M}$ device in nitrogen atmosphere held at room temperature under constant illumination and maximum power point tracking. The maximum power point was updated every 60 s by measuring the current response to a small perturbation in potential. A JV scan was taken periodically to extract the observed device parameters. This aging protocol resembles sealed devices under realistic operational conditions (as opposed to “shelf stability” of devices kept in a dry atmosphere in the dark and measured periodically). The device efficiency of $\\mathsf{C s}_{5}\\mathsf{M}$ drops within a few hours from $20\\%$ to $\\sim18\\%$ where it stays stable for at least $250\\mathsf{h}$ . The $\\mathsf{C s}_{0}\\mathsf{M}$ device, on the other hand, shows much less stable behaviour. This biexponential decay behaviour is in agreement with our previous work where we extract a half-life parameter as a long-term metric for stability.63 In our case the $\\mathsf{C s}_{5}\\mathsf{M}$ device has a slow half-life component of $\\sim5000\\mathsf{h}$ which is one of the highest values reported for comparable system high efficiency perovskite solar cells (see Table S7). \n\nThis indicates that the film stabilities from above correlate with improved device stabilities. The other device parameters $(\\mathsf{J}_{\\mathsf{s c}},\\mathsf{V}_{\\mathsf{o c}}$ and FF) are shown in Fig. S9. It is noteworthy that the current and voltage do not decrease significantly and that most degradation stems from the fill factor. This could potentially be remedied by choosing a suitable HTM or advanced sealing techniques as fill factor losses can stem from decreased conductivity of a degraded organic HTM.63-65 As a comparison, we show also more control device in Fig. S10. We observe that none of the high performing $\\mathsf{C s}_{0}\\mathsf{M}$ devices (16- $18\\%$ ) was as stable as the best Cs device and especially the current degraded significantly over time. The stability tests are not complete yet and more data (which is very timeconsuming for aging tests) is needed for a full study on the long term potential of the triple cation compositions. \n\nThis stability data is noteworthy because it was collected on some of the highest performing devices in the field and to our knowledge this is the first test where a state-of-the-art $20\\%$ device was aged (which is more likely to show a pronounced loss compared to a lower performing device) demonstrating the great potential of perovskite solar cells for industrial applications. \n\n# Conclusion \n\nThis work, for the first time, used a mixture of a triple $C s/M A/F A$ cation, to achieve high efficiency perovskite solar cells with stabilized PCEs at $21.1\\%$ and outputs at $18\\%$ under operational conditions after 250 hours (maximum power point tracking under full illumination held at room temperature). Adding Cs to MA/FA mixtures, which are the basis of the current world record, suppresses yellow phase impurities and induces highly uniform perovskite grains extending from electron to hole collecting layer consistent with seed-assisted crystal growth. \n\nThe triple cation perovskites are also more robust to subtle variations during the fabrication process enabling a breakthrough in terms of reproducibility where PCEs $>20\\%$ were reached on a regular basis. This work also opens the prospect for other alkali metals, such as Li, Na, K and Rb, to be explored as cations for perovskites. Therefore, triple (or multiple) cation mixtures are a novel compositional strategy on the road to industrialization of perovskite solar cells. \n\n# Acknowledgement \n\nM. S. and T. M. contributed equally. M. S. and T. M. conceived and designed the overall experiments. J.-Y. S. and J.-P. C.-B. conducted SEM, PL and XRD experiments on the perovskite films. K. D. and W. T. conducted long-term aging tests on the devices. M. S., T. M., J.-P. C.-B. and A. A. prepared and characterised PV devices. \n\nM. S. wrote the first draft of the paper. All authors contributed to the discussion and writing of the paper. \n\nA. A. and M. S. received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 291771. M. G. thanks the Financial support from the SNSFNanoTera (SYNERGY) and Swiss Federal Office of Energy (SYNERGY) , CCEM-CH in the 9th call proposal 906: CONNECT PV, the SNSF NRP70 \"Energy Turnaround\" and the King Abdulaziz City for Science and Technology (KACST) is gratefully acknowledged. \n\n# References \n\n1. A. Kojima, K. Teshima, Y. Shirai and T. Miyasaka, J Am Chem Soc, 2009, 131, 6050-6051. \n2. NREL chart, \nhttp://www.nrel.gov/ncpv/images/efficiency_chart.jpg, Accessed 02.03.2016, 2016. \n3. T. M. Koh, K. W. Fu, Y. N. Fang, S. Chen, T. C. Sum, N. Mathews, S. G. Mhaisalkar, P. P. Boix and T. Baikie, J Phys Chem C, 2014, 118, 16458-16462. \n4. M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami and H. J. Snaith, Science, 2012, 338, 643-647. \n5. H. S. Kim, C. R. Lee, J. H. Im, K. B. Lee, T. Moehl, A. \nMarchioro, S. J. Moon, R. Humphry-Baker, J. H. Yum, J. E. Moser, M. Gratzel and N. G. Park, Sci Rep, 2012, 2, 591. 6. F. Hao, C. C. Stoumpos, D. H. Cao, R. P. H. Chang and M. G. Kanatzidis, Nat Photonics, 2014, 8, 489-494. \n7. C. H. Hendon, R. X. Yang, L. A. Burton and A. Walsh, Journal of Materials Chemistry A, 2015, 3, 9067-9070. \n8. J. H. Heo, D. H. Song and S. H. Im, Adv Mater, 2014, 26, 8179-8183. \n9. Q. Jiang, D. Rebollar, J. Gong, E. L. Piacentino, C. Zheng and T. Xu, Angewandte Chemie, 2015, 54, 7617-7620. \n10. S. Nagane, U. Bansode, O. Game, S. Chhatre and S. Ogale, Chemical communications, 2014, 50, 9741-9744. \n11. P. Prajongtat and T. Dittricht, J Phys Chem C, 2015, 119, 9926-9933. \n12. J. Burschka, N. Pellet, S. J. Moon, R. Humphry-Baker, P. Gao, M. K. Nazeeruddin and M. Gratzel, Nature, 2013, 499, 316-319. 13. Z. G. Xiao, C. Bi, Y. C. Shao, Q. F. Dong, Q. Wang, Y. B. Yuan, C. G. Wang, Y. L. Gao and J. S. Huang, Energy & \nEnvironmental Science, 2014, 7, 2619-2623. \n14. Q. Chen, H. Zhou, Z. Hong, S. Luo, H. S. Duan, H. H. Wang, Y. Liu, G. Li and Y. Yang, J Am Chem Soc, 2014, 136, 622-625. 15. A. T. Barrows, A. J. Pearson, C. K. Kwak, A. D. F. Dunbar, A. R. Buckley and D. G. Lidzey, Energy & Environmental \nScience, 2014, 7, 2944-2950. \n16. B. R. Sutherland, S. Hoogland, M. M. Adachi, P. \nKanjanaboos, C. T. Wong, J. J. McDowell, J. Xu, O. Voznyy, Z. Ning, A. J. Houtepen and E. H. Sargent, Adv Mater, 2015, 27, 53-58. \n17. Z. Wei, H. Chen, K. Yan and S. Yang, Angewandte Chemie, 2014, 53, 13239-13243. \n18. M. Liu, M. B. Johnston and H. J. Snaith, Nature, 2013, 501, 395-398. \n19. O. Malinkiewicz, A. Yella, Y. H. Lee, G. M. Espallargas, M. Graetzel, M. K. Nazeeruddin and H. J. Bolink, Nat Photonics, 2014, 8, 128-132. \n20. Q. Q. Lin, A. Armin, R. C. R. Nagiri, P. L. Burn and P. \nMeredith, Nat Photonics, 2015, 9, 106-112. \n21. A. Miyata, A. Mitioglu, P. Plochocka, O. Portugall, J. T. W. Wang, S. D. Stranks, H. J. Snaith and R. J. Nicholas, Nat Phys, 2015, 11, 582-U594. \n22. S. D. Stranks, G. E. Eperon, G. Grancini, C. Menelaou, M. J. Alcocer, T. Leijtens, L. M. Herz, A. Petrozza and H. J. Snaith, Science, 2013, 342, 341-344. \n23. G. Xing, N. Mathews, S. Sun, S. S. Lim, Y. M. Lam, M. Gratzel, S. Mhaisalkar and T. C. Sum, Science, 2013, 342, 344- 347. \n24. Q. Dong, Y. Fang, Y. Shao, P. Mulligan, J. Qiu, L. Cao and J. Huang, Science, 2015, 347, 967-970. \n25. N. Pellet, P. Gao, G. Gregori, T. Y. Yang, M. K. \nNazeeruddin, J. Maier and M. Gratzel, Angewandte Chemie, 2014, 53, 3151-3157. \n26. W. S. Yang, J. H. Noh, N. J. Jeon, Y. C. Kim, S. Ryu, J. Seo and S. I. Seok, Science, 2015, 348, 1234-1237. \n27. Y. Ogomi, A. Morita, S. Tsukamoto, T. Saitho, N. Fujikawa, Q. Shen, T. Toyoda, K. Yoshino, S. S. Pandey, T. Ma and S. Hayase, J Phys Chem Lett, 2014, 5, 1004-1011. \n28. C. C. Stoumpos, C. D. Malliakas and M. G. Kanatzidis, Inorg Chem, 2013, 52, 9019-9038. \n29. J. H. Noh, S. H. Im, J. H. Heo, T. N. Mandal and S. I. Seok, Nano Lett, 2013, 13, 1764-1769. \n30. G. Xing, N. Mathews, S. S. Lim, N. Yantara, X. Liu, D. \nSabba, M. Gratzel, S. Mhaisalkar and T. C. Sum, Nature \nmaterials, 2014, 13, 476-480. \n31. M. Saliba, S. M. Wood, J. B. Patel, P. K. Nayak, J. Huang, J. A. Alexander-Webber, B. Wenger, S. D. Stranks, M. T. \nHorantner, J. T. Wang, R. J. Nicholas, L. M. Herz, M. B. \nJohnston, S. M. Morris, H. J. Snaith and M. K. Riede, Adv Mater, 2016, 28, 923-929. \n32. Z. K. Tan, R. S. Moghaddam, M. L. Lai, P. Docampo, R. Higler, F. Deschler, M. Price, A. Sadhanala, L. M. Pazos, D. Credgington, F. Hanusch, T. Bein, H. J. Snaith and R. H. \nFriend, Nature nanotechnology, 2014, 9, 687-692. 33. M. Saliba, W. Zhang, V. M. Burlakov, S. D. Stranks, Y. Sun, J. M. Ball, M. B. Johnston, A. Goriely, U. Wiesner and H. J. Snaith, Adv Funct Mater, 2015, 25, 5038-5046. \n34. W. Zhang, M. Saliba, S. D. Stranks, Y. Sun, X. Shi, U. \nWiesner and H. J. Snaith, Nano Lett, 2013, 13, 4505-4510. 35. J. P. C. Baena, L. Steier, W. Tress, M. Saliba, S. Neutzner, T. Matsui, F. Giordano, T. J. Jacobsson, A. R. S. Kandada, S. M. Zakeeruddin, A. Petrozza, A. Abate, M. K. Nazeeruddin, M. Gratzel and A. Hagfeldt, Energy & Environmental Science, 2015, 8, 2928-2934. \n36. S. Albrecht, M. Saliba, J. P. C. Baena, F. Lang, L. \nKegelmann, M. Mews, L. Steier, A. Abate, J. Rappich, L. Korte, R. Schlatmann, M. K. Nazeeruddin, A. Hagfeldt, M. Gratzel and B. Rech, Energy & Environmental Science, 2016, 9, 81-88. 37. R. Dong, Y. Fang, J. Chae, J. Dai, Z. Xiao, Q. Dong, Y. Yuan, A. Centrone, X. C. Zeng and J. Huang, Adv Mater, 2015, 27, 1912-1918. \n38. K. Domanski, W. Tress, T. Moehl, M. Saliba, M. K. \nNazeeruddin and M. Gratzel, Adv Funct Mater, 2015, 25, 6936-6947. \n39. S. Yakunin, M. Sytnyk, D. Kriegner, S. Shrestha, M. \nRichter, G. J. Matt, H. Azimi, C. J. Brabec, J. Stangl, M. V. Kovalenko and W. Heiss, Nat Photonics, 2015, 9, 444-U444. 40. B. Conings, J. Drijkoningen, N. Gauquelin, A. Babayigit, J. D'Haen, L. D'Olieslaeger, A. Ethirajan, J. Verbeeck, J. Manca, E. Mosconi, F. De Angelis and H. G. Boyen, Adv Energy Mater, 2015, 5. \n41. R. K. Misra, S. Aharon, B. Li, D. Mogilyansky, I. VisolyFisher, L. Etgar and E. A. Katz, J Phys Chem Lett, 2015, 6, 326- 330. \n42. E. T. Hoke, D. J. Slotcavage, E. R. Dohner, A. R. Bowring, H. I. Karunadasa and M. D. McGehee, Chem Sci, 2015, 6, 613- 617. \n43. W. Shockley and H. J. Queisser, J Appl Phys, 1961, 32, 510-&. \n44. G. E. Eperon, S. D. Stranks, C. Menelaou, M. B. Johnston, L. M. Herz and H. J. Snaith, Energy & Environmental Science, 2014, 7, 982-988. \n45. J. W. Lee, D. J. Seol, A. N. Cho and N. G. Park, Adv Mater, 2014, 26, 4991-4998. \n46. N. J. Jeon, J. H. Noh, W. S. Yang, Y. C. Kim, S. Ryu, J. Seo and S. I. Seok, Nature, 2015, 517, 476-480. \n47. M. Kulbak, D. Cahen and G. Hodes, J Phys Chem Lett, 2015, 6, 2452-2456. \n48. C. K. Moller, Nature, 1958, 182, 1436-1436. \n49. Y. Bekenstein, B. A. Koscher, S. W. Eaton, P. Yang and A. P. Alivisatos, J Am Chem Soc, 2015, 137, 16008-16011. \n50. M. Saliba, S. Orlandi, T. Matsui, S. Aghazada, M. \nCavazzini, J.-P. Correa-Baena, P. Gao, R. Scopelliti, E. \nMosconi, K.-H. Dahmen, F. De Angelis, A. Abate, A. Hagfeldt, G. Pozzi, M. Graetzel and M. K. Nazeeruddin, Nature Energy, 2016, 1, 15017. \n51. D. Bi, W. Tress, M. I. Dar, P. Gao, J. Luo, C. Renevier, K. Schenk, A. Abate, F. Giordano, J. P. Correa Baena, J. D. \nDecoppet, S. M. Zakeeruddin, M. K. Nazeeruddin, M. Gratzel and A. Hagfeldt, Sci Adv, 2016, 2, e1501170. 52. A. Amat, E. Mosconi, E. Ronca, C. Quarti, P. Umari, M. K. Nazeeruddin, M. Gratzel and F. De Angelis, Nano Lett, 2014, 14, 3608-3616. \n53. H. Choi, J. Jeong, H. B. Kim, S. Kim, B. Walker, G. H. Kim and J. Y. Kim, Nano Energy, 2014, 7, 80-85. \n54. J. W. Lee, D. H. Kim, H. S. Kim, S. W. Seo, S. M. Cho and N. G. Park, Adv Energy Mater, 2015, 5. \n55. C. Yi, J. Luo, S. Meloni, A. Boziki, N. Ashari-Astani, C. \nGrätzel, S. M. Zakeeruddin, U. Röthlisberger and M. Grätzel, Energy Environ. Sci., 2016, 9, 656-662. \n56. D. P. McMeekin, G. Sadoughi, W. Rehman, G. E. Eperon, M. Saliba, M. T. Horantner, A. Haghighirad, N. Sakai, L. Korte, B. Rech, M. B. Johnston, L. M. Herz and H. J. Snaith, Science, 2016, 351, 151-155. \n57. Z. Li, M. Yang, J.-S. Park, S.-H. Wei, J. J. Berry and K. Zhu, Chemistry of Materials, 2016, 28, 284-292. \n58. V. M. Goldschmidt, Die Naturwissenschaften, 1926, 14, 477-485. \n59. F. Giordano, A. Abate, J. P. Correa Baena, M. Saliba, T. Matsui, S. H. Im, S. M. Zakeeruddin, M. K. Nazeeruddin, A. Hagfeldt and M. Graetzel, Nat Commun, 2016, 7, 10379. 60. S.-S. Li, C.-H. Chang, Y.-C. Wang, C.-W. Lin, D.-Y. Wang, J.- C. Lin, C.-C. Chen, H.-S. Sheu, H.-C. Chia, W.-R. Wu, U. S. Jeng, C.-T. Liang, R. Sankar, F.-C. Chou and C.-W. Chen, Energy & Environmental Science, 2016. \n61. E. L. Unger, E. T. Hoke, C. D. Bailie, W. H. Nguyen, A. R. Bowring, T. Heumuller, M. G. Christoforo and M. D. \nMcGehee, Energy & Environmental Science, 2014, 7, 3690- 3698. \n62. J. A. Christians, J. S. Manser and P. V. Kamat, J Phys Chem Lett, 2015, 6, 852-857. \n63. A. Abate, S. Paek, F. Giordano, J. P. Correa-Baena, M. Saliba, P. Gao, T. Matsui, J. Ko, S. M. Zakeeruddin, K. H. \nDahmen, A. Hagfeldt, M. Gratzel and M. K. Nazeeruddin, Energy & Environmental Science, 2015, 8, 2946-2953. \n64. K. A. Bush, C. D. Bailie, Y. Chen, A. R. Bowring, W. Wang, W. Ma, T. Leijtens, F. Moghadam and M. D. McGehee, Adv Mater, 2016, $n/\\mathsf{a}\\mathsf{-n}/\\mathsf{a}$ . \n65. W. Chen, Y. Z. Wu, Y. F. Yue, J. Liu, W. J. Zhang, X. D. Yang, H. Chen, E. B. Bi, I. Ashraful, M. Gratzel and L. Y. Han, Science, 2015, 350, 944-948. " + }, + { + "id": "10.1126_science.aaf1525", + "DOI": "10.1126/science.aaf1525", + "DOI Link": "http://dx.doi.org/10.1126/science.aaf1525", + "Relative Dir Path": "mds/10.1126_science.aaf1525", + "Article Title": "Homogeneously dispersed multimetal oxygen-evolving catalysts", + "Authors": "Zhang, B; Zheng, XL; Voznyy, O; Comin, R; Bajdich, M; García-Melchor, M; Han, LL; Xu, JX; Liu, M; Zheng, LR; de Arquer, FPG; Dinh, CT; Fan, FJ; Yuan, MJ; Yassitepe, E; Chen, N; Regier, T; Liu, PF; Li, YH; De Luna, P; Janmohamed, A; Xin, HLL; Yang, HG; Vojvodic, A; Sargent, EH", + "Source Title": "SCIENCE", + "Abstract": "Earth-abundant first-row (3d) transition metal-based catalysts have been developed for the oxygen-evolution reaction (OER); however, they operate at overpotentials substantially above thermodynamic requirements. Density functional theory suggested that non-3d high-valency metals such as tungsten can modulate 3d metal oxides, providing nearoptimal adsorption energies for OER intermediates. We developed a room-temperature synthesis to produce gelled oxyhydroxides materials with an atomically homogeneous metal distribution. These gelled FeCoW oxyhydroxides exhibit the lowest overpotential (191 millivolts) reported at 10 milliamperes per square centimeter in alkaline electrolyte. The catalyst shows no evidence of degradation after more than 500 hours of operation. X-ray absorption and computational studies reveal a synergistic interplay between tungsten, iron, and cobalt in producing a favorable local coordination environment and electronic structure that enhance the energetics for OER.", + "Times Cited, WoS Core": 2118, + "Times Cited, All Databases": 2222, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000373990100038", + "Markdown": "# ELECTROCHEMISTRY \n\n# Homogeneously dispersed multimetal oxygen-evolving catalysts \n\nBo Zhang,1,2\\* Xueli Zheng,1,3\\* Oleksandr Voznyy,1\\* Riccardo Comin,1 Michal Bajdich,4,5 \nMax García-Melchor,4,5 Lili $\\mathbf{Han},^{3,6}$ Jixian Xu,1 Min Liu,1 Lirong Zheng,7 \nF. Pelayo García de Arquer,1 Cao Thang Dinh,1 Fengjia Fan,1 Mingjian Yuan,1 \nEmre Yassitepe,1 Ning Chen,8 Tom Regier,8 Pengfei Liu,9 Yuhang Li,9 Phil De Luna,1 \nAlyf Janmohamed,1 Huolin L. Xin,6 Huagui Yang,9 \nAleksandra Vojvodic, $^{4,5}\\dag$ Edward H. Sargent1† \n\nEarth-abundant first-row (3d) transition metal–based catalysts have been developed for the oxygen-evolution reaction (OER); however, they operate at overpotentials substantially above thermodynamic requirements. Density functional theory suggested that non-3d high-valency metals such as tungsten can modulate 3d metal oxides, providing nearoptimal adsorption energies for OER intermediates. We developed a room-temperature synthesis to produce gelled oxyhydroxides materials with an atomically homogeneous metal distribution.These gelled FeCoW oxyhydroxides exhibit the lowest overpotential (191 millivolts) reported at 10 milliamperes per square centimeter in alkaline electrolyte. The catalyst shows no evidence of degradation after more than 500 hours of operation. X-ray absorption and computational studies reveal a synergistic interplay between tungsten, iron, and cobalt in producing a favorable local coordination environment and electronic structure that enhance the energetics for OER. \n\nC ftfriocliyesnetr,scaorset ea cercuticviea,l amnidssilnogngp-liievcedaleolencg1 tahbelepealtehc rtiociftuy $(\\boldsymbol{I},\\boldsymbol{2})$ .ntThesibzoetdt ewnietchkrien iemwproving water-splitting technologies is the oxygen-evolving reaction (OER), in which even the most efficient precious-metal catalysts require a substantial overpotential $(\\upeta)$ to reach the desired current densities of $\\geq10\\mathrm{mA}\\mathrm{cm}^{-2}(2,3).$ . Researchers have explored earth-abundant first-row (3d) transition-metal oxides (4–9), including 3d metal oxyhydroxides $(4,5),$ oxide perovskites $(7),$ cobalt phosphate composites $\\textcircled{6}$ , nickel borate composites $(I O)$ , and molecular complexes $(9,{\\cal I I})$ . The OER performance of multimetal oxides based on iron (Fe), cobalt (Co), and nickel $\\mathrm{(Ni)}$ is particularly promising, and OER activity often outperforms that of the corresponding single-metal oxides (5, 12–15). \n\nWe examined whether multimetal oxide OER catalysts could be improved by systematically modulating their 3d electronic structure. Prior results suggest that the introduction of additional metals has a limited impact on the behavior of the 3d metals, likely because of their undesired separation into two noninteracting metal oxide phases (16, 17). For modulation, we focus in particular on tungsten (W), which in its highest oxidation state is a structurally versatile coordination host $(9,I I)$ . We began with computational studies aimed at identifying effects of W-modulation of the local coordination environment and the impacts on the resulting electronic structure and on the consequent energetics of the OER. The OER performance of unary Co, Fe, and Ni oxides has been well established both from theory and experiment $(\\cal{I4},\\cal{I5},\\cal{I8})$ . Previous computational studies show that the OER activity is mainly driven by the energetics of the OER intermediates $({}^{\\ast}\\mathrm{OH},{}^{\\ast}\\mathrm{O};$ , and $^{*}\\mathrm{OOH}$ ) on the surfaces, with the O to OH adsorption energy difference being the main descriptor for the observed activity trends among these materials (14, 15, 18). Binary metal oxides such as Ni-Fe and Co-Fe, as well as doped unary oxides, have also been investigated, and their activity can also be predicted by using the above-mentioned descriptor-based approach $(5,I2,I3)$ . Theoretical studies suggest that for a given unary metal oxide, the energetics of OER intermediates can be modulated by incorporating metal elements, and that in turn these tune the catalytic activity of these materials. \n\nTheoretical calculations of ternary and higher mixtures of oxides have been hindered by the complexity of these materials and the associated computational cost. We simplified our approach by starting from the calculated OER energetics for the pure $\\scriptstyle\\mathrm{{\\beta-CoOOH}}$ $\\gamma{\\mathrm{-FeOOH}}$ , and $\\mathrm{WO_{3}}$ phases and estimating the effect of alloying on the energetics of OER intermediates via simple linear interpolation arguments. Our density functional theory plus U $(\\mathrm{DFI+U})$ ) calculations revealed that the adsorption energy of OH is too strong on the FeOOH(010) surface, whereas it is too weak on the CoOOH(01-12) and $\\mathrm{WO_{3}(001)}$ surfaces (Fig. 1A) (19). To test the interpolation principle, we next calculated the OH adsorption energy on the Fe-doped CoOOH(01-12) surface: This energy falls approximately halfway between the one obtained for the unary CoOOH(01-12) and FeOOH(010) surfaces. Similarly, adding Co into $\\mathrm{WO_{3}}(001)$ or adding W into CoOOH(01-12) led to an averaged OH adsorption energy for the $\\mathrm{CoWO_{4}}$ system (20) and W-doped CoOOH(01-12). By extending this scheme to ternary Co-Fe-W metal-oxide systems, we estimate that FeW-doped CoOOH(01-12) should result in near-optimal $^{*}\\mathrm{OH}$ energetics for OER. \n\nNext, we proceeded to calculate the energetics of all intermediates $^{\\prime*}\\mathrm{OH}$ , $^{*}0$ , and $^{*}\\mathrm{OOH},$ and extracted overpotentials for the set of unary and Fe- and W-doped surfaces mentioned above [computational methodology is provided (19)]. Given the plethora of possible ternary Co-Fe-W oxide alloys, we limited our computational study to the investigation of the above active site motifs, which are also expected to benefit from the interpolation scheme of Fig. 1A. We chose to study only the chemistry of substitutionally metal-doped surface sites. All calculated theoretical OER overpotentials shown in the two-dimensional (2D) volcano plot of Fig. 1B support the general validity of the interpolation scheme not just for $^{*}\\mathrm{OH}$ energetics, but also for the O to OH adsorption energy difference, denoted as $\\Delta\\mathrm{G}_{\\mathrm{O}^{-}}\\Delta\\mathrm{G}_{\\mathrm{OH}}$ . The potential limiting kinetic barriers for the reaction were also experimentally determined and found to be small compared with thermodynamics (19). The tunability of adsorption energies upon alloying would hence allow for substantial improvement in OER activity. \n\nWe found that the OER activity of the unary pure CoOOH(01-12) surface can be improved via single-site doping with subsurface Fe atoms. This improvement can be attributed to the change in $\\Delta\\mathrm{G}_{\\mathrm{OH}}$ and also in $\\Delta\\mathrm{G}_{\\mathrm{O}^{-}}\\Delta\\mathrm{G}_{\\mathrm{OH}}$ at the Co-site and can be rationalized by the difference in electron affinity between ${\\mathrm{Co}}^{4+}$ (at the surface) and $\\mathrm{Fe^{3+}}$ (subsurface) sites. Furthermore, adding a W dopant in the vicinity of the Co active site of the Fedoped CoOOH surface (Fig. 1B, inset) further improves the energetics for OER. The substitution of a W dopant at a ${\\mathrm{Co}}^{4+}$ site results in (i) migration of protons away from W, which prefers the $\\mathrm{W}^{6+}$ formal oxidation state, toward oxygen at Co sites, and (ii) compressive strain of larger W atoms on the surrounding Co sites. As a result of these geometric and electronic changes, we identified a favorable direct $\\mathrm{O}_{2}$ mechanism for OER with a theoretical overpotential of only $0.4\\mathrm{V}$ compared with the standard electrochemical OOH mechanism [computational methodology details are provided in (19)]. \n\nIn light of these findings, we sought to devise a controlled process to incorporate $\\mathrm{W}^{6+}$ into FeCo for WFe-doped $\\upbeta$ and active sites at the potential limiting step. DFT about these systems are available in (19). \n\n![](images/54c534d28651b68b6f04a8c8190feb3ea2f0d7d426f936e4715addc09050ccb7.jpg) \nFig. 1. Tuning the energetics of OER intermediates via alloying. (A) Change in OH adsorption energetics as a function of increasing composition obtained by interpolation between the calculated pure phases: $\\mathsf{W O}_{3}$ (001), CoOOH (01-12), FeOOH (010), and $\\mathsf{C o W O_{4}}$ (010) (20). (B) OER activities of pure Fe,Co oxyhydroxides and W,Fe-doped Co oxyhydroxides, cobalt tungstate, and W oxides calculated with $D F T+U$ . The optimum is obtai \n\n![](images/55342870310a68a5fda0c4009356fc909afdf8d6cbd9c82261b173af223d0998.jpg) \nFig. 2. Preparation of G-FeCoW oxyhydroxides catalysts. (A) Schematic illustration of the preparation process for the gelled structure and pictures of the corresponding sol, gel, and gelled film. (B) HAADFSTEM image of nanoporous structure of G-FeCoW. (C) SAED pattern. (D) Atomic-resolution HAADFSTEM image. (E) EELS elemental mapping from the G-FeCoW oxyhydroxides sample. \n\noxyhydroxides in an atomically homogeneous manner. We explored a room-temperature solgel procedure that would feature precursors mixed in a homogeneous manner that would be hydrolyzed at a controlled rate so as to achieve atomic homogeneity. First, we dissolved inorganic metal chloride precursors in ethanol. These were controllably hydrolyzed in order to produce a multimetal oxyhydroxide gel via a room-temperature sol-gel process (Fig. 2A) (21). The hydrolysis rates of $\\mathrm{CoCl_{2}},$ $\\mathrm{FeCl}_{3},$ and $\\mathrm{wcl}_{6}$ vary greatly, so very low concentrations of water and propylene oxide were used to tune their hydrolysis independently— a strategy that we anticipated could lead to the desired homogeneous spatial distribution of the three metallic elements (19). \n\nAfter supercritical drying with $\\mathrm{CO}_{2}$ , the gel transformed into amorphous metal oxyhydroxides powders. From inductively coupled plasma optical emission spectrometry (ICP-OES) analysis, we determined the molar ratio of Fe:Co:W to be 1:1.02:0.70. Atomic-resolution scanning transmission electron microscopy (STEM) performed in high-angle annular dark field (HAADF) mode (Fig. 2D and fig. S5A), combined with selectedarea electron diffraction (SAED) analysis (Fig. 2C), revealed the absence of a crystalline phase. X-ray diffraction (XRD) (fig. S2A) further confirmed that the gelled FeCoW is an amorphous phase (19). The STEM measurements show a crumpled and entangled structure composed of nanosheets and nanopores (Fig. 2B). Electron energy loss spectroscopy (EELS) elemental maps with subnanometer resolution (Fig. 2E) showed a uniform, uncorrelated spatial distribution of Fe, Co, and W. The statistics of the atom-pair separation distances, obtained from the STEM elemental maps, show that the nearest-neighbor separations of all two-metal atom pairs are highly consistent (figs. S3, S4, and S6, A to E) (19). This homogeneity results from (i) the homogeneous dispersion of three precursors in solution and (ii) controlled hydrolysis, the latter enabling the maintenance of the homogeneous phase in the final gel state without phase separation of different metals caused by precipitation. In contrast, conventional processes (17), even when their precursors are homogeneously mixed, result in crystalline products formed heterogeneously during the annealing process leading to phase separation caused by lattice mismatch. For structural comparison with prior sol-gel reports that used an annealing step $(I7)$ , we annealed the samples at $500^{\\circ}\\mathrm{C}$ and then found crystalline phases (figs. S5B, highresolution TEM images, and S2B, XRD) that included separated $\\mathrm{Fe_{3}O_{4}}$ , $\\mathrm{Co_{3}O_{4}},$ and $\\mathrm{CoWO_{4}}$ . Elemental mapping of this sample (fig. S6, A1 to E1) further confirmed the phase separation of Fe from Co and W atoms (19). \n\n![](images/542d27954a7d1644347ca666c1ce6544a52ca25164541739e6669e72fc61d415.jpg) \nFig. 3. Surface and bulk x-ray absorption spectra of G-FeCoW oxyhydroxide catalysts and A-FeCoW controls. (A) Surface-sensitive TEY XAS scans at the Fe L-edge before and after OER at $+1.4\\vee$ (versus RHE), with the corresponding molar ratio of $\\mathsf{F e}^{2+}$ and $\\mathsf{F e}^{3+}$ species. (B) Surface-sensitive TEY XAS scans at the Co L-edge before and after OER at $+1.4$ V (versus RHE). (C) Bulk Co K-edge XANES spectra before and after OER at $+1.4\\ V$ (versus RHE). (Inset) The zoomed in pre-edge profiles. The Co K-edge data of $\\mathsf{C o}(\\mathsf{O H})_{2}$ and CoOOH are from (30). (D) Bulk W L3-edge XANES spectra before and after OER at $+1.4$ V (versus RHE). \n\nTable 1. Comparison of catalytic parameters of G-FeCoW and controls. \n\n\n
SamplesOn gold foam On glassy carbon electrode (GCE)On Au(111)References
Overpotential* (mV)Overpotential* (mV)TOFt (s-1)Overpotential* (mV)H (kJ mol-1) at n=300 mV
LDH FeCo279(±8)331(±3)0.0085429 (±4)81This work
G-FeCo215 (±6)277 (±3)0.043346 (±4)60Thiswork
G-FeCoW191(±3)223 (±2)0.46 (±0.08)315(±5)49Thiswork
A-FeCoW Amorphous-FeCoOx232 (±4).301(±4)0.17405 (±2)80This work
LDH NiFe300 3000.07(4)
CoOOH550(25)
IrO2.2600.05(23)
NiFeOOH34066 (-/+5)(25)
Ni60C040 oxides26372.6S(27) (29)
NiFe LDH/ GO2100.1(22)
\n\nObtained at the current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ , without iR correction. †Obtained at $95\\%$ iR corrected $\\mathfrak{n}=300\\mathrm{~mV},$ assuming all loaded 3d-metal atoms as active sites. ‡Obtained from the LSV plots at the current density of $4\\mathsf{m A}\\mathsf{c m}^{-2}$ in 0.1 M KOH aqueous solution. $\\S0$ btained at $280~\\mathrm{mV}$ in 1M NaOH aqueous solution. \n\nWe investigated the influence of incorporating W (with its high oxidation state) on the electronic and coordination structures of Fe and Co using x-ray absorption spectroscopy (XAS). We examined (i) conventionally layered double hydroxides of FeCo (LDH FeCo) that have the same structure as the state-of-the-art OER catalysts (LDH NiFe) (22), (ii) FeCo oxyhydroxides (without W) prepared via the annealing-free sol-gel process (gelled FeCo, labeled G-FeCo), (iii) gelled FeCoW oxyhydroxides (G-FeCoW), and (iv) annealed G-FeCoW at $500^{\\circ}\\mathrm{C}$ (A-FeCoW). \n\nTo evaluate the change of oxidation states of metal elements during OER, we performed XAS on the G-FeCoW and A-FeCoW samples before and after OER; the latter condition was realized by oxidizing samples at $+1.4\\mathrm{V}$ versus the reversible hydrogen electrode (RHE) in the OER region. XAS in total electron yield (TEY) mode provides information on the near-surface chemistry (below $10\\mathrm{nm}$ ). We acquired TEY data at the Fe and Co L-edges on samples prepared ex situ. For comparison, on the same samples we also measured in situ XAS (during OER) at the Fe and Co Kedges via fluorescent yield, a measurement that mainly probes chemical changes in the bulk. TEY XAS spectra in Fig. 3A revealed that the surface $\\mathrm{Fe^{2+}}$ ions in G-FeCoW had been oxidized to $\\mathrm{Fe^{3+}}$ at $+1.4\\mathrm{V}$ , which is in agreement with thermodynamic data for Fe. However, the oxidation states of Co in G-FeCoW and A-FeCoW samples were appreciably different at $+1.4\\mathrm{V}$ . In G-FeCoW, the valence states of both surface (Fig. 3B) and bulk (Fig. 3C) Co were similar to pure ${\\mathrm{Co}}^{3+}$ , including only a modest admixture with ${\\mathrm{Co}}^{2+}$ (fig. S12); in particular, the Co-K edge profile closely resembled CoOOH (23), which is consistent with our DFT model. In contrast, in A-FeCoW (in which W is phase-separated), even after a potential of $+1.4\\mathrm{V}$ was applied, the surface (Fig. 3B) and bulk (Fig. 3C) manifested a substantially higher ${\\mathrm{Co}}^{2+}$ content (fig. S12), which is consistent with the $\\mathrm{Co_{3}O_{4}}$ and $\\mathrm{CoWO_{4}}$ phases. These oxides had been found to be much less reactive in DFT simulations (14, 20). The bulk and surface Fe and Co edge profiles are shown in figs. S7 to S11 and discussed in (19). \n\nstate. These results indicate that Fe and Co also inversely influence W in the homogeneous ternary metal oxyhydroxides. \n\nIn situ extended x-ray absorption fine structure (EXAFS) (figs. S13 and S14) on G-FeCoW showed a significant decrease in Co-O bond distance, from 2.06 to ${\\bf1.91\\AA},$ after a potential of $+1.4\\mathrm{V}$ was applied. This decrease is consistent with the reported results that the Co-O bond distance in CoOOH is shorter than that in $\\mathrm{Co(OH)_{2}}$ (23). EXAFS data at the Fe edge in G-FeCoW show the same trend (figs. S15 and S16). Ex situ EXAFS data before OER are also shown in figs. S17 to S20 and table S3. In contrast, the local structural arrangement in A-FeCoW remains unchanged at \n\n1.4 V. Overall, we conclude that Co in the GFeCoW structure is more readily oxidized to high valence, which is consistent with G-FeCoW being more active than the control annealed samples. \n\nWe compared the OER performance of our gelled sample G-FeCoW with that of the reference samples G-FeCo, LDH FeCo, and A-FeCoW. Representative OER currents of the samples were measured for spin-coated thin films (thickness $\\sim30\\mathrm{nm}$ ) (fig. S21) (19) on a well-defined Au(111) single-crystal electrode (Fig. 4A) in 1 M KOH aqueous electrolyte at a scan rate of $\\mathrm{1mVs^{-1}}$ (currents are uncorrected and thus include the effects of resistive losses incurred within the electrolyte). The G-FeCoW–onAu(111) required an overpotential of only $315\\mathrm{mV}$ \n\nThe white lines of W $\\mathrm{L}_{3}$ -edge x-ray absorption near-edge structure (XANES) spectra of all samples in Fig. 3D show that W in G-FeCoW and A-FeCoW samples before and after OER has a distorted $\\mathrm{WO}_{6}$ octahedral symmetry (24). The W $\\mathrm{{L}_{3}}$ amplitude in pre-OER A-FeCoW was low, a finding attributable to the loss of bound water during annealing (24). When a $+1.4\\mathrm{~V~}$ bias was applied, the $\\mathrm{WL}_{3}$ intensity in G-FeCoW increased, indicating that the valence of W decreases, which is consistent with increased distortion of $\\mathrm{{WO}}_{6}$ octahedra (24). This result agrees with the results of DFT, in which W-doped CoOOH(01-12) is expected to produce W residing in a lower oxidation at $\\mathrm{10\\mAcm^{-2}}$ (Table 1, all current densities based on projected geometric area). This potential is $\\mathrm{114mV}$ lower than that of precipitated FeCo LDH fabricated for the present study. When W was not introduced, the resultant G-FeCo gelled catalyst required an additional overpotential of $31\\mathrm{mV}$ to reach a similar current density. When the gelled sample was subjected to a postsynthetic thermal treatment $500^{\\circ}\\mathrm{C}$ anneal), the overpotential of the FeCoW electrode increased to $405\\mathrm{mV}$ at $\\mathrm{10\\mA\\cm^{-2}}$ . \n\n![](images/4158dc48738663896f5e56f5b5f708cac2ffb156696d5477bbb5ae79adc0abd5.jpg) \nFig. 4. Performance of G-FeCoW oxyhydroxides catalysts and controls in three-electrode configuration in 1 M KOH aqueous electrolyte. (A and B) The OER polarization curve of catalysts loaded on two different substrates with $1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ scan rate, without $i R$ correction: (A) $\\mathsf{A u}(111)$ electrode and (B) goldplated Ni foam. (C) Overpotentials obtained from OER polarization curves at the current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ tested on Au(111), GCE and gold-plated $\\mathsf{N i}$ foam, respectively, without $i R$ correction. (D) Arrhenius plot of the kinetic current at ${\\mathfrak{n}}=300{\\mathrm{~mV}},$ , tested on $\\mathsf{A u}(111)$ , without $i R$ correction. (E) Chronopotentiometric curves obtained with the G-FeCoW oxyhydroxides on gold-plated Ni foam electrode with constant current densities of $30\\mathsf{m A}\\mathsf{c m}^{-2}$ , and the corresponding remaining metal molar ratio in G-FeCoW calculated from ICP-AES results. (F) Chronopotentiometric curves obtained with the $\\mathsf{G}$ -FeCoW oxyhydroxides on goldplated Ni foam electrode with constant current densities of $30\\mathsf{m A}\\mathsf{c m}^{-2}$ , and the corresponding Faradaic efficiency from gas chromatography measurement of evolved $\\mathsf{O}_{2}$ . \n\nTo assess the impact of the electrode support and compare the performance of the new catalysts with the state-of-the-art NiFeOOH, we tested on glassy carbon electrode (GCE) using the identical three-electrode system and with a catalyst loading mass of $0.21\\mathrm{{mg}\\ c m^{-2}}$ . The trend of the overpotentials remains the same (fig. S22), with the G-FeCoW–on-GCE electrode requiring an overpotential of $223\\mathrm{mV}$ at $\\mathrm{10\\mA\\cm^{-2}}$ . Without carbon additives, and without $i R$ corrections $\\because$ current; $R$ , resistance), the G-FeCoW catalyst consistently outperforms the best oxide catalysts previously reported (Table 1) (4, 22, 25). \n\nNext, we investigated whether the OERperformance of G-FeCoW originates from intrinsic catalytic activity of multimetal active sites or exclusively from an enhanced surface area. We analyzed the Brunauer-Emmett-Teller (BET) surface area, which allowed us to report normalized kinetic current density (referred to as specific activity) as a function of potential versus RHE (7). We confirmed that the intrinsic activity of G-FeCoW is notably higher than that of the controls and also higher than those previously reported (fig. S26) (7). \n\nThe intrinsic activity of G-FeCoW was further confirmed by determining the mass activities and turnover frequencies (TOFs) for this catalyst. We used data obtained on GCE with $95\\%$ iR correction at $\\upeta=300\\mathrm{mV}$ (the remaining data in this work are not corrected by $95\\%\\ i R$ , unless stated). As shown in Table 1 and tables S5 and S9 $(I9)$ , the G-FeCoW catalysts on GCE exhibit TOFs of $0.46~\\mathrm{{s}^{-1}}$ per total 3d metal atoms and mass activities of 1175 A $\\mathbf{g}^{-1}$ (considering the total loading mass on the lower limiting case). If only considering electrochemically active 3d metals or mass (obtained from the integration of Co redox features) (26), G-FeCoW catalysts exhibit much higher TOFs of $1.5~\\mathrm{{s}^{-1}}$ and $3500{\\mathrm{Ag}}^{-1}$ . These are more than three times above the TOF and mass activities of the optimized control catalysts and the repeated state-of-the-art NiFeOOH (table S9) $(5,26)$ . \n\nTo assess the kinetic barriers involved in $\\mathrm{OER},$ we studied the effect of temperature on the performance of the catalysts (fig. S27). OER proceeds more rapidly at elevated temperatures, reflecting the exponential temperature dependence of the chemical rate constant (27). The Arrhenius plots at $\\upeta=300\\mathrm{mV}$ for four different catalysts (Fig. 4D) allowed us to extract electrochemical activation energies that agree well with the values reported previously (Table 1) (27). We found that G-FeCoW has the lowest apparent barrier value of $49\\mathrm{kJ}\\mathrm{mol}^{-1}$ . The similar data obtained for all catalysts suggests that OER proceeds via the same potential-determining step on all catalysts investigated in this work. \n\nTo obtain a highly efficient catalytic electrode, we increased the conductivity of the substrate by loading our catalysts on a nickel foam that was covered with gold in order to avoid any spurious effects arising from interaction of the catalyst with Ni. The activity trends of catalysts remained the same as observed on the Au(111) surface and GCE, whereas the absolute performance of each sample was substantially improved (Fig. 4B). The G-FeCoW showed a low overpotential of 191 mV at $\\mathrm{10\\mA\\cm^{-2}}$ on the gold-plated nickel foam (projected geometric area) (Table 1). On the basis of the above discussion and the overpotentials on Au(111), gold foam, GCE, and fluorine-doped tin oxide (Fig. 4C, fig. S30, and table S6), it can be seen that the catalytic activity of G-FeCoW is much higher than that of the annealed control (A-FeCoW), gelled FeCo without W (G-FeCo), and the LDH FeCo having the same structure as the state-of-the-art LDH NiFeOOH OER catalysts. \n\nThe operating stability of the OER catalysts is essential to their application (28). To characterize the performance stability of the G-FeCoW catalysts, we ran water oxidation on the catalyst deposited on gold-plated Ni foam under constant current of $30\\mathrm{mAcm^{-2}}$ continuously for 550 hours. We observed no appreciable increase in potential in this time interval (Fig. 4, E and F). To check that the catalyst remained physically intact, we tested in situ its mass using the electrochemical quartz crystal microbalance (EQCM) technique (figs. S31 and S32) and also assessed whether any metal had leached into the electrolyte by using inductively coupled plasma atomic emission spectroscopy (ICP-AES) (figs. S33 to S36 and table S7). After the completion of an initial burn-in period in which (presumably unbound) W is shed into the electrolyte, we saw stable operation and no discernible W loss. EELS mapping of G-FeCoW after OER (fig. S37) indicates that the remaining W continues to be distributed homogeneously in the sample. By measuring the $\\mathbf{O}_{2}$ evolved from the G-FeCoW/gold-plated Ni foam catalyst, we also confirmed the high activity throughout the entire duration of stability test, obtaining quantitative (unity Faradaic efficiency) gas evolution of $\\mathrm{O}_{2}$ to within our available $\\pm5\\%$ experimental error (Fig. 4F). These findings suggest that modulating the 3d transition in metal oxyhydroxides by using a suitable transition metal, one closely atomically coupled through homogeneous solidstate dispersion, may provide further avenues to OER optimization. \n\n# REFERENCES AND NOTES \n\n1. C. R. Cox, J. Z. Lee, D. G. Nocera, T. Buonassisi, Proc. Natl. Acad. Sci. U.S.A. 111, 14057–14061 (2014). \n2. J. Luo et al., Science 345, 1593–1596 (2014). \n3. M. Schreier et al., Nat. Commun. 6, 7326 (2015). \n4. R. D. L. Smith et al., Science 340, 60–63 (2013). \n5. D. Friebel et al., J. Am. Chem. Soc. 137, 1305–1313 (2015). \n6. M. W. Kanan, D. G. Nocera, Science 321, 1072–1075 (2008). \n7. J. Suntivich, K. J. May, H. A. Gasteiger, J. B. Goodenough, Y. Shao-Horn, Science 334, 1383–1385 (2011). \n8. A. Vojvodic, J. K. Nørskov, Science 334, 1355–1356 (2011). \n9. Q. Yin et al., Science 328, 342–345 (2010). \n10. M. Dincă, Y. Surendranath, D. G. Nocera, Proc. Natl. Acad. Sci. U.S.A. 107, 10337–10341 (2010). \n11. F. M. Toma et al., Nat. Chem. 2, 826–831 (2010). \n12. M. S. Burke, M. G. Kast, L. Trotochaud, A. M. Smith, S. W. Boettcher, J. Am. Chem. Soc. 137, 3638–3648 (2015). \n13. M. W. Louie, A. T. Bell, J. Am. Chem. Soc. 135, 12329–12337 (2013). \n14. M. Bajdich, M. García-Mota, A. Vojvodic, J. K. Nørskov, A. T. Bell, J. Am. Chem. Soc. 135, 13521–13530 (2013). \n15. C. C. L. McCrory et al., J. Am. Chem. Soc. 137, 4347–4357 (2015). \n16. J. A. Haber et al., Energy Environ. Sci. 7, 682–688 (2014). \n17. J. A. Haber, E. Anzenburg, J. Yano, C. Kisielowski, J. M. Gregoire, Adv. Ener. Mat. 5, 1402307 (2015). \n18. P. Liao, J. A. Keith, E. A. Carter, J. Am. Chem. Soc. 134, 13296–13309 (2012). \n19. Materials and methods are available as supplementary materials on Science Online. \n20. C. Ling, L. Q. Zhou, H. Jia, RSC Adv. 4, 24692–24697 (2014). \n21. V. Augustyn et al., Nat. Mater. 12, 518–522 (2013). \n22. W. Ma et al., ACS Nano 9, 1977–1984 (2015). \n23. R. Subbaraman et al., Nat. Mater. 11, 550–557 (2012). \n24. A. Balerna et al., Nucl. Instrum. Methods Phys. Res. A 308, 240–242 (1991). \n25. F. Song, X. Hu, Nat. Commun. 5, 4477 (2014) . \n26. A. S. Batchellor, S. W. Boettcher, ACS Catal. 5, 6680–6689 (2015). \n27. J. R. Swierk, S. Klaus, L. Trotochaud, A. T. Bell, T. D. Tilley, J. Phys. Chem. C 119, 19022–19029 (2015). \n28. N. Danilovic et al., Angew. Chem. Int. Ed. Engl. 126, 14240–14245 (2014). \n29. F. Rosalbino, S. Delsante, G. Borzone, G. Scavino, Int. J. Hydrogen Energy 38, 10170–10177 (2013). \n30. D. Friebel et al., Phys. Chem. Chem. Phys. 15, 17460–17467 (2013). \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Ontario Research Fund–Research Excellence Program, Natural Sciences and Engineering Research Council of Canada, and the Canadian Insititute for Advanced Research Bio-Inspired Solar Energy program. B.Z. acknowledges funding from China Scholarship Council/University of Toronto Joint Funding Program (201406745001), Shanghai Municipal Natural Science Foundation (14ZR1410200), and the National Natural Science Foundation of China (21503079). X.Z. acknowledges a scholarship from the China Scholarship Council (CSC) (20140625004). This work was also supported by the U.S. Department of Energy (DOE), Office of Basic Energy Science grant to the SUNCAT Center for Interface Science and Catalysis and the Laboratory-Directed Research and Development program funded through the SLAC National Accelerator Laboratory. M.G.-M. acknowledges funding from the Agency for Administration of University and Research Grants of Catalonia (AGAUR, 2013 BP-A 00464). This work has also benefited from the Hard X-ray Micro-Analysis and Spherical Grating Monochromator beamlines at CLS and the BL14W1 beamline at the Shanghai Synchrotron Radiation Facility (SSRF). B.Z. and R.C. acknowledge the CLS Post-Doctoral Student Travel Support Program. The TEM study in this work is supported by the Center for Functional Nanomaterials, which is a DOE Office of Science Facility, at Brookhaven National Laboratory under contract DE-SC0012704. E.Y. acknowledges a Fundação de Amparo à Pesquisa do Estado de São Paulo–Bolsa Estágio de Pesquisa no Exterior (2014/18327-9) fellowship. E.H.S. and F.P.G.A acknowledge funding from the Connaught Global Challenge program of the University of Toronto. The authors thank D. Bélanger and G. Chamoulaud at Université du Québec à Montréal for assistance in EQCM measurements and T.-O. Do and C.-C. Nguyen at Laval University for surface area analysis. The authors thank Y. J. Pang, X. Lan, L. N. Quan, and S. Hoogland for fruitful discussions; M. X. Liu and X. W. Gong for fabrication assistance; and R. Wolowiec and D. Kopilovic for assistance. B.Z., X.Z., J.X., M.L., C.T.D, and E.H.S. of the University of Toronto have filed provisional patent application no. 62288648 regarding the preparation of multimetal catalysts for oxygen evolution. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/352/6283/333/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S43 \nTables S1 to S9 \nReferences (31–56) \n23 December 2015; accepted 9 March 2016 \n10.1126/science.aaf1525 \n\n# Science \n\n# Homogeneously dispersed multimetal oxygen-evolving catalysts \n\nBo Zhang, Xueli Zheng, Oleksandr Voznyy, Riccardo Comin, Michal Bajdich, Max García-Melchor, Lili Han, Jixian Xu, Min Liu, Lirong Zheng, F. Pelayo García de Arquer, Cao Thang Dinh, Fengjia Fan, Mingjian Yuan, Emre Yassitepe, Ning Chen, Tom Regier, Pengfei Liu, Yuhang Li, Phil De Luna, Alyf Janmohamed, Huolin L. Xin, Huagui Yang, Aleksandra Vojvodic and Edward H. Sargent \n\nScience 352 (6283), 333-337. DOI: 10.1126/science.aaf1525originally published online March 24, 2016 \n\n# Modulating metal oxides \n\nThe more difficult step in fuel cells and water electrolysis is the oxygen evolution reaction. The search for earth-abundant materials to replace noble metals for this reaction often turns to oxides of three-dimensional metals such as iron. Zhang et al. show that the applied voltages needed to drive this reaction are reduced for iron-cobalt oxides by the addition of tungsten. The addition of tungsten favorably modulates the electronic structure of the oxyhydroxide. A key development is to keep the metals well mixed and avoid the formation of separate phases. \n\nScience, this issue p. 333 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_nature16521", + "DOI": "10.1038/nature16521", + "DOI Link": "http://dx.doi.org/10.1038/nature16521", + "Relative Dir Path": "mds/10.1038_nature16521", + "Article Title": "Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis", + "Authors": "Gao, W; Emaminejad, S; Nyein, HYY; Challa, S; Chen, KV; Peck, A; Fahad, HM; Ota, H; Shiraki, H; Kiriya, D; Lien, DH; Brooks, GA; Davis, RW; Javey, A", + "Source Title": "NATURE", + "Abstract": "Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual's state of health(1-12). Sampling human sweat, which is rich in physiological information(13), could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state(14-18). Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.", + "Times Cited, WoS Core": 3671, + "Times Cited, All Databases": 4013, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000368673800033", + "Markdown": "# Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis \n\nWei Gao1,2,3\\*, Sam Emaminejad $^{1,2,3,4*}$ , Hnin Yin Yin  Nyein1,2,3, Samyuktha Challa4, Kevin Chen1,2,3, Austin Peck5, Hossain M. Fahad1,2,3, Hiroki Ota1,2,3, Hiroshi Shiraki1,2,3, Daisuke Kiriya1,2,3, Der-Hsien Lien1,2,3, George A. Brooks5, Ronald W. Davis4 & Ali Javey1,2,3 \n\nWearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health1–12. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other noninvasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14–18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plasticbased sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications. \n\nWearable electronics are devices that can be worn or mated with human skin to continuously and closely monitor an individual’s activities, without interrupting or limiting the user’s motions1–9. Thus wearable biosensors could enable real-time continuous monitoring of an individual’s physiological biomarkers10–12. At present, commercially available wearable sensors are only capable of tracking an individual’s physical activities and vital signs (such as heart rate), and fail to provide insight into the user’s health state at molecular levels. Measurements of human sweat could enable such insight, because it contains physiologically and metabolically rich information that can be retrieved non-invasively13. Sweat analysis is currently used for applications such as disease diagnosis, drug abuse detection, and athletic performance optimization13. For these applications, the sample collection and analysis are performed separately, failing to provide a real-time profile of sweat content secretion, while requiring extensive laboratory analysis using bulky instrumentation19. Recently, wearable sweat sensors have been developed, with which a variety of biosensors have been used to measure analytes of interest (Supplementary Table 1)14–18. \n\nGiven the multivariate mechanisms that are involved in sweat secretion, an attractive strategy would be to devise a fully integrated multiplexed sensing system to extract the complex information available from sweat. Here we present a wearable flexible integrated sensing array (FISA) for simultaneous and selective screening of a panel of biomarkers in sweat (Fig. 1a). Our solution bridges the existing technological gap between signal transduction (electrical signal generation by sensors), conditioning (here, amplification and filtering), processing (here, calibration and compensation) and wireless transmission in wearable biosensors by merging commercially available integrated-circuit technologies, consolidated on a flexible printed circuit board (FPCB), with flexible and conforming sensor technologies fabricated on plastic substrates. This approach decouples the stringent mechanical requirements at the sensor level and electrical requirements at the signal conditioning, processing and transmission levels, and at the same time exploits the strengths of the underlying technologies. The independent and selective operation of individual sensors is preserved during multiplexed measurements by employing highly specific surface chemistries and by electrically decoupling the operating points of each sensor’s interface. This platform is a powerful tool with which to advance largescale and real-time physiological and clinical studies by facilitating the identification of informative biomarkers in sweat. \n\nAs illustrated in Fig. 1a, the FISA allows simultaneous and selective measurement of a panel of metabolites and electrolytes in human perspiration as well as skin temperature during prolonged indoor and outdoor physical activities. By fabricating the sensors on a mechanically flexible polyethylene terephthalate (PET) substrate, a stable sensor– skin contact is formed, while the FPCB technology is exploited to incorporate the critical signal conditioning, processing, and wireless transmission functionalities using readily available integrated-circuit components (Fig. 1b). The panel of target analytes and skin temperature was selected to facilitate an understanding of an individual’s physiological state (see Supplementary Information for selection of the target analytes). For example, excessive loss of sodium and potassium in sweat could result in hyponatremia, hypokalemia, muscle cramps or dehydration20; sweat glucose is reported to be metabolically related to blood glucose21; sweat lactate can potentially serve as a sensitive marker of pressure ischaemia ; and skin temperature is clinically informative of a variety of diseases and skin injuries such as pressure ulcers23,24. Additionally, skin temperature measurements are needed to compensate for and eliminate the influence of temperature variation in the readings of the chemical sensors through a built-in signal processor. \n\nFigure 1c illustrates the schematic of the multiplexed sensor array (each electrode is $3\\mathrm{mm}$ in diameter) for sweat analysis; fabrication processes are detailed in Methods and Extended Data Fig. 1. Here, amperometric glucose and lactate sensors (with current output) are based on glucose oxidase and lactate oxidase immobilized within a permeable film of the linear polysaccharide chitosan. A $\\mathrm{\\Ag/AgCl}$ electrode serves as a shared reference electrode and counter electrode for both sensors. The use of Prussian blue dye as a mediator minimizes the reduction potentials to approximately $0\\mathrm{V}$ (versus $\\mathrm{Ag/AgCl)}$ (Extended Data Fig. 2a), and thus eliminates the need for an external power source to activate the sensors. These enzymatic sensors autonomously generate current signals proportional to the abundance of the corresponding metabolites between the working electrode and the $\\mathrm{Ag/AgCl}$ electrode. The measurement of $\\mathrm{Na^{+}}$ and $\\mathrm{K^{+}}$ levels is facilitated through the use of ion-selective electrodes (ISEs), coupled with a polyvinyl butyral (PVB)- coated reference electrode to maintain a stable potential in solutions with different ionic strengths (Extended Data Fig. 2b–d). By using poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) as an ion-to-electron transducer in the ISEs and carbon nanotubes in the PVB reference membrane25, robust potentiometric sensors (with voltage output) can be obtained for long-term continuous measurements with negligible voltage drift. A resistance-based temperature sensor is realized by fabricating Cr/Au metal microwires. Parylene is used as an insulating layer to ensure reliable sensor reading by preventing electrical contact of the metal lines with skin and sweat. \n\n![](images/49a9ce631efd29c0ba25f33ca381d78f247e8120674b954f7da42f2360c1328d.jpg) \nFigure 1 | Images and schematic illustrations of the FISA for multiplexed perspiration analysis. a, Photograph of a wearable FISA on a subject’s wrist, integrating the multiplexed sweat sensor array and the wireless FPCB. (All photographs in this paper were taken by the authors.) b, Photograph of a flattened FISA. The red dashed box indicates the location of the sensor array and the white dashed boxes indicate the locations of the integrated circuit components. c, Schematic of the sensor array (including glucose, lactate, sodium, potassium and temperature sensors) for multiplexed perspiration analysis. GOx and LOx, glucose \n\noxidase and lactate oxidase. d, System-level block diagram of the FISA showing the signal transduction (orange) (with potential $V$ , current I and resistance $R$ outputs), conditioning (green), processing (purple) and wireless transmission (blue) paths from sensors to the custom-developed mobile application (numbers in parentheses indicate the corresponding labelled components in b). ADC, analogue-to-digital converter. The inset images show the home page (left) and the real-time data display page (right) of the mobile application. \n\nFigure 1d illustrates the system-level overview of the signal transduction, conditioning, processing, and wireless transmission paths to facilitate multiplexed on-body measurements. The signalconditioning path for each sensor is implemented with analogue circuits and in relation to the corresponding transduced signal. The circuits are configured to ensure that the final analogue output of each path is finely resolved while staying within the input voltage range of the analogue-to-digital converter. Furthermore, the microcontroller’s computational and serial communication capabilities are used to calibrate, compensate, and relay the conditioned signals to an on-board wireless transceiver. The transceiver facilitates wireless data transmission to a Bluetooth-enabled mobile handset with a custom-developed application (Extended Data Fig. 3), containing a user-friendly interface for sharing (through email, SMS, and so on) or uploading the data to cloud servers. The circuit design, calibration, and power delivery diagram of the FISA are described in Methods and Extended Data Figs 4 and 5. \n\nThe performance of each sensor was monitored separately with different analyte solutions. Figure 2a and b shows the representative current responses of the glucose and lactate sensors, measured chronoamperometrically in $0{-}200{-}\\upmu\\mathrm{M}$ glucose solutions and $_{0-30-\\mathrm{mM}}$ lactate solutions, respectively. A linear relationship between current and analyte concentrations with sensitivities of $2.{\\overset{\\cdot}{35}}\\mathrm{nA}\\upmu\\mathrm{M}^{-1}$ for glucose sensors and $220\\mathrm{nAmM^{-1}}$ for lactate sensors was observed. Figure 2c and d illustrates the open circuit potentials of $\\mathrm{Na^{+}}$ and $\\mathrm{K^{+}}$ sensors in the electrolyte solutions with physiologically relevant concentrations of $10{-}160{\\mathrm{-}}\\mathrm{mMNa^{+}}$ and $1{-}32{\\mathrm{-}}\\mathrm{mMK^{+}}$ respectively. Both ion-selective sensors show a near-Nerstian (according to the Nerstian equation, the theoretical sensitivity of the ISE-based sensors should be 59) behaviour with sensitivities of $64.2\\mathrm{mV}$ and $61.3\\mathrm{mV}$ per decade of concentration for $\\mathrm{Na^{+}}$ and $\\mathrm{K^{+}}$ sensors, respectively. Results of repeatability and longterm stability studies indicate that the sensitivities of the biosensors are consistent over a period of at least four weeks (Extended Data Fig. 6). Figure 2e displays the linear response of the resistive temperature sensor in the physiological skin temperature range of $20{-}40^{\\circ}\\mathrm{C}$ with a sensitivity of approximately $0.18\\%$ per degree Celsius (normalized to the resistance at $20^{\\circ}\\mathrm{C}$ ). \n\n![](images/6db7fd19459f3806f750e7cf0c9bf612f67661fd547840aa73e1e3718be9a1ec.jpg) \nFigure 2 | Experimental characterizations of the wearable sensors. PBS. Insets in a–e show the corresponding calibration plots of the sensors. a, b, The chronoamperometric responses of the glucose (a) and lactate Data recording was paused for 30 s for each solution change in a–e. (b) sensors to the respective analyte solutions in phosphate-buffered f, System-level interference studies of the sensor array. g, The influence of saline (PBS). c, d, The open circuit potential responses of the sodium (c) temperature on the responses of the glucose and lactate sensors. h, Systemand potassium (d) sensors in NaCl and KCl solutions. e, The resistance level real-time temperature $T$ compensation for the glucose and lactate response of the temperature sensor to temperature changes $(20–40^{\\circ}\\mathrm{C})$ in sensors in $100\\mathrm{-}\\upmu\\mathrm{M}$ glucose and $5\\mathrm{-mM}$ lactate solutions, respectively. \n\nThe selectivity of sweat sensors is crucial, because various electrolytes and metabolites in sweat can influence the accuracy of the sensor readings. Extended Data Fig. 7a–d shows that the presence of nontarget electrolytes and metabolites causes negligible interference to the response of each sensor. When all five sensors are integrated in the FISA, simultaneous system-level measurements maintain excellent selectivity upon varying concentrations of each analyte (Fig. 2f and Extended Data Fig. 7e–h). Although temperature has a minimal effect on the potentiometric sensors, it greatly influences the performance of the enzymatic sensors. Figure $2\\mathrm{g}$ shows that the responses of glucose and lactate sensors increase rapidly upon elevation of the solution temperature from $22^{\\circ}\\mathrm{C}$ to $40^{\\circ}\\mathrm{C},$ reflecting the effect of increased enzyme activities26. System integration allows for the implementation of real-time compensation to calibrate the sensor readings on the basis of temperature variations. Figure 2h illustrates that with the increase of temperature, the uncompensated sensor readouts can lead to substantial overestimation of the actual concentration of the given glucose and lactate solutions; however, the temperature compensation allows for accurate and consistent readings. \n\nIt is essential for wearable devices to be able to withstand the stress of daily human wear and physical exercise. A study on mechanical deformation conducted by monitoring the performance of both the sensor array and the FPCB before, during and after bending (radii of curvature are $1.5\\mathrm{cm}$ and $3\\mathrm{cm}$ , respectively) (Extended Data Fig. 8) reveals minimal output changes in the FISA’s responses. \n\nThe FISAs can be comfortably worn on various body parts, including the forehead, wrists and arms. Figure 3a shows a human subject wearing two FISAs, packaged as a ‘smart wristband’ and a ‘smart headband’, allowing for real-time perspiration monitoring on the wrist and forehead simultaneously during stationary leg cycling. To ensure the fidelity of sensor readings, the data collection of each channel took place when a sufficient sweat sample was present, as shown by stabilization of sensor readings within the physiologically relevant range (see Methods). The accuracy of on-body measurements was verified through the comparison of on-body sensor readings from the forehead with ex situ (off-body) measurements from collected sweat samples (Fig. 3b). \n\nReal-time physiological monitoring was performed on a subject during constant-load exercise on a cycle ergometer. The protocol involved a 3-min ramp-up, 20-min cycling at $150\\mathrm{W},$ and a 3-min cool-down. During the exercise, the heart rate, oxygen consumption $(V_{\\mathrm{O}_{2}})$ , and pulmonary minute ventilation were measured using external monitoring instruments, and were found to increase proportionally with increasing power output as shown in Fig. 3c. Figure 3d illustrates the corresponding real-time measurements on the subject’s forehead using a FISA. The skin temperature remains constant at $34^{\\circ}\\mathrm{C}$ up to perspiration initiation at about $320s$ The dip in temperature at this point indicates the beginning of perspiration and evaporative cooling27. With continued perspiration, the skin temperature rises at about $400s$ because of muscle heat conductance to skin and then remains stable, while the concentration of both lactate and glucose in sweat decrease gradually. The decreases in concentration of lactate and glucose in sweat are expected, owing to the dilution effect caused by an increase in sweat rate, which is visually observed as exercise continues13. However, lactate concentration becomes relatively stable after $1,100s$ , indicating the stabilization of physiological responses to continuous, sub-maximal constant-exercise power output22. Sweat $\\left[\\mathrm{Na^{+}}\\right]$ increases and $[\\mathrm{K^{+}}]$ decreases in the beginning of perspiration, in line with the previous ex situ studies from the collected sweat samples28,29. Both $\\mathrm{[Na^{+}]}$ and $[\\mathrm{K^{+}}]$ stabilize as the cycling continues. By wearing a FISA on different parts of the body, the site-specific variations in electrolyte and metabolite levels29 can also be monitored and studied simultaneously. Sweat analyte levels on the wrist follow similar trends but with concentrations different from those obtained at the forehead (Extended Data Fig. 9). In this case, because the subject had a lower sweat rate at the wrist29, the sensors were activated at a later time. \n\nThe physiological response of the subjects to a sudden change in exercise intensity was also investigated, in a graded-load exercise which involved a 5-min rest, $20\\mathrm{-min}$ cycling at 75 W followed by cycling at $200\\mathrm{W}$ power output until volitional fatigue, and a $10\\mathrm{-min}$ recovery period (Fig. 3e and f). As demonstrated in Fig. 3e, the dramatic increase in the exercise power output from $75\\mathrm{W}$ to $200\\mathrm{W}$ immediately leads to abrupt elevations of heart rate, minute ventilation and $V_{\\mathrm{O}_{2}}$ . Responses of the FISA during 75-W power output follow profiles similar to those observed during the constant-load study. After the power is raised, the sweat rate visibly increases, followed by a sharp increase in skin temperature and sweat $\\mathrm{[Na^{+}]}$ as well as a slight increase in $[\\mathrm{K^{+}}]$ (in three of the seven subjects, $[\\mathrm{K^{+}}]$ remained stable). The relatively stable behaviour of $[\\mathrm{K^{+}}]$ is explained by its passive ion partitioning mechanism13. With the cessation of exercise, these physiological responses decrease and then remain stable. No apparent difference is observed for glucose concentration at different power output settings, a finding consistent with the response of blood glucose to graded, short-term exercise30. The change in lactate concentration, on the other hand, varies between subjects. This observation can be attributed to the increase in both lactate excretion rate and sweat rate upon the increase of the workload31. \n\n![](images/b515520521da516e6ef308019c0be75f842d7091baea6c9a148ae454a3b0be13.jpg) \nFigure 3 | On-body real-time perspiration analysis during stationary cycling. a, Photographs of a subject wearing a ‘smart headband’ and a ‘smart wristband’ during stationary cycling. b, Comparison of ex situ calibration data of the sodium and glucose sensors from the collected sweat samples with the on-body readings of the FISA during the stationary cycling exercise detailed in f. c, d, Constant-load exercise at 150 W: power output, heart rate (in beats per minute, b.p.m.), oxygen consumption $(V_{\\mathrm{O}_{2}})$ and pulmonary minute ventilation, as measured by external monitoring \nsystems (c) and the real-time sweat analysis results of the FISA worn on a subject’s forehead (d). e, f, Graded-load exercise, involving a dramatic power increase from $75\\mathrm{W}$ to $200\\mathrm{W}$ : power output, heart rate, $V_{\\mathrm{O}_{2}}$ and pulmonary minute ventilation, as measured by external monitoring systems (e) and the real-time analysis results using the FISA worn on a different subject’s forehead (f). Data collection for each sensor took place when a sufficient sweat sample was present (see Methods). \n\n![](images/829294948c8d10f08168bbfc48848ce9ab0f36a9dad077429b97dd1d21143653.jpg) \nFigure 4 | Hydration status analysis during group outdoor running using the FISAs. a, Schematic illustration showing the group outdoor running trial based on wearable FISAs (packaged as ‘smart headbands’) The data are transmitted to the user’s cell phone and uploaded to cloud \n\nMonitoring hydration status is of the utmost importance to athletes because fluid deficit impairs endurance performance and increases carbohydrate reliance32. To evaluate the utility of a FISA for effective and non-invasive identification of dehydration, real-time sweat $\\mathrm{[Na^{+}]}$ and $[\\mathrm{K^{+}}]$ measurements were conducted simultaneously on a group of subjects engaged in prolonged outdoor running trials (Fig. 4a). Figure 4b and c shows that sweat $\\mathrm{[Na^{+}]}$ and $[\\mathrm{K^{+}}]$ are stable throughout running in euhydration trials (with water intake of $150\\mathrm{ml}$ per 5 min) after the initial $\\mathrm{[Na^{+}]}$ increase and $[\\mathrm{K^{+}}]$ decrease. On the other hand, a substantial increase in sweat $\\mathrm{[Na^{+}]}$ and a smaller increase in sweat $[\\mathrm{K^{+}}]$ (no clear increase in $[\\mathrm{K^{+}}]$ was observed in two out of six subjects) were observed in dehydration trials (without water intake) after $80\\mathrm{min}$ when subjects had lost a large amount of water ( ${\\sim}2.5\\%$ of body weight) (Fig. 4d and e). $E x$ situ measurements of $\\mathrm{[Na^{+}]}$ and $[\\mathrm{K^{+}}]$ from collected sweat samples in Extended Data Fig. 10 also show similar phenomena. These trends are probably caused by increased blood serum $[\\mathrm{Na^{+}}]$ and $[\\mathrm{K^{+}}]$ with dehydration and increased neural stimulation, a conclusion in agreement with previous ex situ sweat analyses33. Thus, sweat $[\\mathrm{Na^{+}}]$ can potentially serve as an important biomarker for monitoring dehydration. We believe that this wearable platform may enable new fundamental physiology studies through further on-body evaluation. \n\nThus, we have merged skin-conforming plastic-based sensors (five different sensors) and conventional commercially available integratedcircuit components (more than ten chips) at an unprecedented level of integration, not only to measure the output of an array of multiplexed and selective sensors, but also to obtain an accurate assessment via signal processing of the physiological state of the human subjects. This application could not have been realized by either of the technologies (flexible sensors and silicon integrated circuits) alone, owing to their respective inherent limitations. The plastic-based device technologies lack the ability to implement sophisticated electronic functionalities for critical signal conditioning and processing. On the other hand, the silicon integrated-circuit technology does not provide sufficiently large active areas nor the intimate skin contact required to achieve stable and sensitive on-body measurements. Importantly, the entire system is mechanically flexible, thus delivering a practical wearable sensor technology that can be used for prolonged indoor and outdoor physical activities. This platform could be exploited or reconfigured for in situ analyses of other biomarkers within sweat and other human fluid samples to facilitate personalized and real-time physiological and clinical investigations. We envision that the large data sets that could be collected through such studies, along with voluntary community participation, would enable data-mining techniques with which to generate predictive algorithms for understanding the health status and clinical needs of individuals and society. \n\nservers. b, c, Representative real-time sweat sodium (b) and potassium (c) levels during an endurance run with water intake. d, e, Representative realtime sweat sodium (d) and potassium (e) levels during an endurance run without water intake. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# Received 26 June; accepted 23 November 2015. \n\n1. Kim, D. H. et al. Epidermal electronics. Science 333, 838–843 (2011). \n2.\t Lipomi, D. J. et al. Skin-like pressure and strain sensors based on transparent elastic films of carbon nanotubes. Nature Nanotechnol. 6, 788–792 (2011). \n3.\t Takei, K. et al. Nanowire active-matrix circuitry for low-voltage macroscale artificial skin. Nature Mater. 9, 821–826 (2010). \n4.\t Wu, W. et al. Piezoelectricity of single-atomic-layer ${\\mathsf{M o S}}_{2}$ for energy conversion and piezotronics. Nature 514, 470–474 (2014). \n5. McAlpine, M. C., Ahmad, H., Wang, D. & Heath, J. R. Highly ordered nanowire arrays on plastic substrates for ultrasensitive flexible chemical sensors. Nature Mater. 6, 379–384 (2007). \n6. Kaltenbrunner, M. et al. An ultra-lightweight design for imperceptible plastic electronics. Nature 499, 458–463 (2013). \n7. Xu, S. et al. Soft microfluidic assemblies of sensors, circuits, and radios for the skin. Science 344, 70–74 (2014). \n8. Wang, C. et al. User-interactive electronic skin for instantaneous pressure visualization. Nature Mater. 12, 899–904 (2013). \n9. Liang, J., Li, L., Niu, X., Yu, Z. & Pei, Q. Elastomeric polymer light-emitting devices and displays. Nature Photon. 7, 817–824 (2013). \n10.\t Kim, D. H., Ghaffari, R. & Rogers, J. A. Flexible and stretchable electronics for biointegrated devices. Annu. Rev. Biomed. Eng. 14, 113–128 (2012). \n11.\t Patel, S., Park, H., Bonato, P., Chan, L. & Rodgers, M. A review of wearable sensors and systems with application in rehabilitation. J. Neuroeng. Rehabil. 9, \n21 (2012). \n12.\t Bandodkar, A. J. & Wang, J. Non-invasive wearable electrochemical sensors: a review. Trends Biotechnol. 32, 363–371 (2014). \n13.\t Sonner, Z. et al. The microfluidics of the eccrine sweat gland, including biomarker partitioning, transport, and biosensing implications. Biomicrofluidics \n9, 031301 (2015). \n14.\t Schazmann, B. et al. A wearable electrochemical sensor for the real-time measurement of sweat sodium concentration. Anal. Methods 2, 342–348 (2010). \n15.\t Jia, W. et al. Electrochemical tattoo biosensors for real-time noninvasive lactate monitoring in human perspiration. Anal. Chem. 85, 6553–6560 (2013). \n16.\t Coyle, S. et al. BIOTEX—biosensing textiles for personalised healthcare management. IEEE Trans. Inf. Technol. Biomed. 14, 364–370 (2010). \n17.\t Bandodkar, A. J. et al. Epidermal tattoo potentiometric sodium sensors with wireless signal transduction for continuous non-invasive sweat monitoring. Biosens. Bioelectron. 54, 603–609 (2014). \n18.\t Rose, D. P. et al. Adhesive RFID sensor patch for monitoring of sweat electrolytes. IEEE Trans. Biomed. Eng. 62, 1457–1465 (2015). \n19.\t Boysen, T. C., Yanagawa, S., Sato, F. & Sato, K. A modified anaerobic method of sweat collection. J. Appl. Physiol. 56, 1302–1307 (1984). \n20.\t Speedy, D. B., Noakes, T. D. & Schneider, C. Exercise-associated hyponatremia: a review. Emerg. Med. 13, 17–27 (2001). \n21.\t Talary, M. S., Dewarrat, F., Huber, D. & Caduff, A. In vivo life sign application of dielectric spectroscopy and non-invasive glucose monitoring. J. Non-Cryst. Solids 353, 4515–4517 (2007). \n22.\t Derbyshire, P. J., Barr, H., Davis, F. & Higson, S. P. Lactate in human sweat: a critical review of research to the present day. J. Physiol. Sci. 62, 429–440 (2012). \n23.\t Webb, R. C. et al. Ultrathin conformal devices for precise and continuous thermal characterization of human skin. Nature Mater. 12, 938–944 (2013). \n24.\t Sprigle, S., Linden, M., McKenna, D., Davis, K. & Riordan, B. Clinical skin temperature measurement to predict incipient pressure ulcers. Adv. Skin Wound Care 14, 133–137 (2001). \n25.\t Zhu, J., Qin, Y. & Zhang, Y. Preparation of all solid-state potentiometric ion sensors with polymer-CNT composites. Electrochem. Commun. 11, 1684–1687 (2009). \n26.\t Jobst, G. et al. Thin-film microbiosensors for glucose-lactate monitoring. Anal. Chem. 68, 3173–3179 (1996). \n27.\t Nadel, E. R., Bullard, R. W. & Stolwijk, J. A. Importance of skin temperature in the regulation of sweating. J. Appl. Physiol. 31, 80–87 (1971). \n28.\t Cage, G. W., Wolfe, S. M., Thompson, R. H. & Gordon, R. S. Jr. Effects of water intake on composition of thermal sweat in normal human volunteers. J. Appl. Physiol. 29, 687–690 (1970). \n29.\t Patterson, M. J., Galloway, S. D. R. & Nimmo, M. A. Variations in regional sweat composition in normal human males. Exp. Physiol. 85, 869–875 (2000). \n30.\t Messonnier, L. A. et al. Lactate kinetics at the lactate threshold in trained and untrained men. J. Appl. Physiol. 114, 1593–1602 (2013). \n31.\t Buono, M. J., Lee, N. V. & Miller, P. W. The relationship between exercise intensity and the sweat lactate excretion rate. J. Physiol. Sci. 60, 103–107 (2010). \n32.\t Barr, S. I. Effects of dehydration on exercise performance. Can. J. Appl. Physiol. 24, 164–172 (1999). \n33.\t Morgan, R. M., Patterson, M. J. & Nimmo, M. A. Acute effects of dehydration on sweat composition in men during prolonged exercise in the heat. Acta Physiol. Scand. 182, 37–43 (2004). \n\n# Supplementary Information is available in the online version of the paper. \n\nAcknowledgements The sensor design, characterization and testing aspects of this work were supported by the Berkeley Sensor and Actuator Center, and National Institutes of Health grant number P01 HG000205. The sensor fabrication was performed in the Electronic Materials (E-MAT) laboratory funded by the Director, Office of Science, Office of Basic Energy Sciences, Material Sciences and Engineering Division of the US Department of Energy under contract number DE-AC02-05CH11231. K.C. acknowledges funding from the NSF Nanomanufacturing Systems for mobile Computing and Energy Technologies (NASCENT) Center. H.O. acknowledges support from a Japan Society for the Promotion of Science (JSPS) Fellowship. We thank J. Bullock, C. M. Sutter-Fella, H. W. W. Nyein, Z. Shahpar, M. Zhou, E. Wu and W. Chen for their help. \n\nAuthor Contributions W.G., S.E. and A.J. conceived the idea and designed the experiments. W.G., S.E., H.Y.Y.N. and S.C. led the experiments (with assistance from K.C., A.P., H.M.F., H.O., H.S., H.O., D.K., D.-H.L.). W.G., S.E., A.P., G.A.B., R.W.D. and A.J. contributed to data analysis and interpretation. W.G., S.E., H.Y.Y.N., G.A.B. and A.J. wrote the paper and all authors provided feedback. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Correspondence and requests for materials should be addressed to A.J. (ajavey@eecs.berkeley.edu). \n\n# METHODS \n\nMaterials. Selectophore grade sodium ionophore X, bis(2-ethylehexyl) sebacate (DOS), sodium tetrakis[3,5-bis(trifluoromethyl)phenyl] borate (Na-TFPB), high-molecular-weight polyvinyl chloride (PVC), tetrahydrofuran, valinomycin (potassium ionophore), sodium tetraphenylborate (NaTPB), cyclohexanone, polyvinyl butyral resin BUTVAR B-98 (PVB), sodium chloride (NaCl), 3,4- ethylenedioxythiophene (EDOT), poly(sodium 4-styrenesulfonate) (NaPSS), glucose oxidase (from Aspergillus niger), chitosan, single-walled carbon nanotubes, iron (III) chloride, potassium ferricyanide (III), multiwall carbon nanotubes and block polymer PEO-PPO-PEO (F127) were obtained from Sigma Aldrich. L-lactate oxidase ${>}80$ activity units per milligram) was procured from Toyobo Corp. and PBS $(\\mathrm{pH}7.2)$ was obtained from Life Technologies. Moisture-resistant $100\\mathrm{-}\\upmu\\mathrm{m}$ -thick PET was purchased from McMaster-Carr. \n\nFabrication of electrode arrays. The fabrication process of the electrode arrays is detailed in Extended Data Fig. 1. Briefly, the sensor arrays on PET were patterned by photolithography using positive photoresist (Shipley Microposit S1818) followed by $30\\mathrm{nm}\\mathrm{Cr}/50\\mathrm{nm}$ Au deposited via electron-beam evaporation and lift-off in acetone. A ${500}\\mathrm{-nm}$ parylene C insulation layer was then deposited in a SCS Labcoter 2 Parylene Deposition System. Subsequently, photolithography was used to define the final electrode area ( $3\\mathrm{mm}$ diameter) followed by $\\mathrm{O}_{2}$ plasma etching for 450 s at $300\\mathrm{W}$ to remove the parylene completely. Electron-beam evaporation was then performed to pattern 180-nm Ag onto the electrode areas, followed by lift-off in acetone. The Ag patterns on working electrode area were dissolved in a 6-M ${\\mathrm{HNO}}_{3}$ solution for 1 min. The $\\mathrm{Ag/AgCl}$ reference electrodes were obtained by injecting $10\\upmu\\mathrm{l}0.1\\mathrm{-}\\mathrm{MFeCl}_{3}$ solution on top of each Ag reference electrode using a micropipette for $1\\mathrm{min}$ . \n\nDesign of electrochemical sensors. For amperometric glucose and lactate sensors, a two-electrode system where $\\mathrm{Ag/AgCl}$ acts as both reference and counter electrode was chosen to simplify circuit design and to facilitate system integration. The two-electrode system is a common strategy for low-current electrochemical sensing34,35. The output currents (between the working electrode and the $\\mathrm{\\Ag/AgCl}$ reference/counter electrode) of the glucose and lactate sensors could be converted to a voltage potential through a transimpedance amplifier. It is known that amperometric sensors with larger area provide larger current signal. Considering the low concentration of glucose in sweat, we designed the sensors to be $3\\mathrm{mm}$ in diameter to obtain a high current. \n\nPreparation of $\\mathbf{Na}^{+}$ and ${{\\bf K}}^{+}$ selective sensors. The $\\mathrm{Na^{+}}$ selective membrane cocktail consisted of Na ionophore X ( $1\\%$ weight by weight, w/w), $\\mathrm{Na}$ -TFPB ( $0.55\\%$ w/w), PVC $(33\\%\\mathrm{w/w})$ , and DOS $65.45\\%$ w/w). $100\\mathrm{mg}$ of the membrane cocktail was dissolved in $660\\upmu\\mathrm{l}$ of tetrahydrofuran17. The $\\mathrm{K^{+}}$ -selective membrane cocktail was composed of valinomycin $(2\\%\\mathrm{w/w})$ , NaTPB $(0.5\\%)$ , PVC ( $32.7\\%$ w/w), and DOS $64.7\\%$ w/w). $100\\mathrm{mg}$ of the membrane cocktail was dissolved in $350\\upmu\\mathrm{l}$ of cyclohexanone. The ion-selective solutions were sealed and stored at $4^{\\circ}\\mathrm{C}$ . The solution for the PVB reference electrode was prepared by dissolving $79.1\\mathrm{mg}\\mathrm{PVB}$ and $50\\mathrm{mg}$ of $\\mathrm{\\DeltaNaCl}$ into 1 ml methanol36. $2\\mathrm{mg}\\mathrm{F}127$ and $0.2\\mathrm{mg}$ of multiwall carbon nanotubes were added into the reference solution to minimize the potential drift25. \n\nPoly(3,4-ethylenedioxythiophene) PEDOT:PSS was chosen as the ion– electron transducer to minimize the potential drift of the $\\mathrm{ISEs}^{37}$ and deposited onto the working electrodes by galvanostatic electrochemical polymerization with an external $\\mathrm{Ag/AgCl}$ reference electrode from a solution containing 0.01-M EDOT and 0.1-M NaPSS. A constant current of $14\\upmu\\mathrm{A}$ $(2\\operatorname{mA}\\mathrm{cm}^{-2},$ ) was applied to produce polymerization charges of $10\\mathrm{mC}$ onto each electrode. \n\nIon-selective membranes were then prepared by drop-casting $10\\upmu\\mathrm{l}$ of the $\\mathrm{Na^{+}}$ - selective membrane cocktail and $4\\upmu\\mathrm{l}$ of the $\\mathrm{K}^{+}$ -selective membrane cocktail onto their corresponding electrodes. The common reference electrode for the $\\mathrm{Na^{+}}$ and $\\mathrm{K^{+}}$ ISEs was modified by casting $10\\upmu\\mathrm{l}$ of reference solution onto the $\\mathrm{Ag/AgCl}$ electrode. The modified electrodes were left to dry overnight. The sensors could be used without pre-conditioning (with a small drift of ${\\sim}2{-}\\bar{3}\\mathrm{mVh^{-1}}$ ). However, to obtain the best performance for long-term continuous measurements such as dehydration studies, the ion-selective sensors were covered with a solution containing $0.1{-}\\mathrm{MNaCl}$ and 0.01-M KCl through microinjection (without contact to glucose and lactate sensors) for 1 h before measurements. This conditioning process was important to minimize the potential drift further. \n\nPreparation of lactate and glucose sensors. $1\\%$ chitosan solution was first prepared by dissolving chitosan in $2\\%$ acetic acid and magnetic stirring for about 1 h; next, the chitosan solution was mixed with single-walled carbon nanotubes $(2\\mathrm{mg}\\mathrm{ml}^{-1})$ by ultrasonic agitation over $30\\mathrm{min}$ to prepare a viscous solution of chitosan and carbon nanotubes. To prepare the glucose sensors, the chitosan/carbon nanotube solution was mixed thoroughly with glucose oxidase solution $(10\\mathrm{mg}\\mathrm{ml}^{-1}$ in PBS of $\\mathrm{pH}7.2$ ) in the ratio 2:1 (volume by volume). A Prussian blue mediator layer was deposited onto the Au electrodes by cyclic voltammetry from $0\\mathrm{V}$ to $0.5\\mathrm{V}$ (versus Ag/AgCl) for one cycle at a scan rate of $20\\mathrm{mVs}^{-1}$ in a fresh solution containing $2.5\\mathrm{mM}$ $\\mathrm{FeCl}_{3}$ , $100\\mathrm{mM}$ KCl, $2.5\\mathrm{mM}$ $\\mathrm{K}_{3}\\mathrm{Fe(CN)}_{6},$ and $100\\mathrm{mM}$ HCl. A thinner Prussian blue layer can provide better sensitivity, which is essential for low-glucose-level measurements in sweat. The glucose sensor was obtained by drop-casting $3\\upmu\\mathrm{l}$ of the glucose oxidase/chitosan/carbon nanotube solution onto the Prussian blue/Au electrode. For the lactate sensors, the Prussian blue mediator layer was deposited onto the Au electrodes by cyclic voltammetry from $-0.5\\mathrm{V}$ to $0.6\\mathrm{V}$ (versus $\\mathrm{Ag/AgCl)}$ for 10 cycles at $50\\mathrm{mVs^{-1}}$ in a fresh solution containing $2.5\\mathrm{mMFeCl_{3}}$ , $100\\mathrm{mM}$ KCl, 2.5 m $\\mathrm{~M~K_{3}F e(C N)_{6},}$ and $100\\mathrm{mM}$ HCl. A thicker Prussian blue layer can provide a wider linear response range, which is crucial for lactate measurement in sweat. $3\\upmu\\mathrm{l}$ of the chitosan/carbon nanotube solution was drop-cast onto the Prussian blue/Au electrode and dried in the ambient environment; the electrode was later covered with $2\\upmu\\mathrm{l}$ of lactate oxidase solution $(40\\mathrm{mg}\\mathrm{ml}^{-1}.$ ) and finally $3\\upmu\\mathrm{l}$ of the chitosan/ carbon nanotube solution. The sensor arrays were allowed to dry overnight at $4^{\\circ}\\mathrm{C}$ with no light. The solutions were stored at $4^{\\circ}\\mathrm{C}$ when not in use. \n\nSignal conditioning, processing and wireless transmission circuit design. The circuit diagram of the analogue signal-conditioning block of the FISA is shown in Extended Data Fig. 4. At the core of our system we used an ATmega328P (Atmel 8-bit) microcontroller that could be programmed on-board through an in-circuit serial programming interface. This microcontroller is compatible with the popular Arduino development environment, and is commonly used in autonomous systems with low power and low cost requirements. By exploiting the microcontroller’s built-in 10-bit analogue-to-digital converter block as well as its computational and serial communication capability, we relayed the signals (as transduced by our sensor module and as conditioned by our analogue circuitry) to the Bluetooth transceiver. \n\nThe conditioning path for each sensor was implemented in relation to the corresponding sensing mode. In the case of the amperometric-based glucose and lactate sensors, the originally generated signal was in the form of electrical current. Therefore, in the respective signal conditioning paths, we first used a transimpedance amplifier stage to convert the signal current into voltage. In our electrical current measurements, the direction of the current was from the shared $\\mathrm{\\Ag/AgCl}$ reference/counter electrode towards the working electrode of each of the glucose and lactate sensors, which would result in a negative transimpedance output voltage. Hence, for both glucose and lactate paths, the transimpedance amplifiers were followed by inverter stages to make the respective voltage signals positive, since the analogue-to-digital converter stage took only positive input values. The feedback resistors in each of the transimpedance sections was chosen (1 MΩ for the glucose path and $0.5\\mathrm{M}\\Omega$ for the lactate path) such that the converted voltage signal could be finely resolved, while staying within the input voltage range of the analogue-to-digital converter stage of the microcontroller. The current sensing signal paths were capable of measuring current levels as low as 1 nA, which was much lower than the minimum signal in our measurements (tens of nanoamperes). In this implementation, with the transimpedance amplifier at the front-end, the $\\mathrm{Ag/AgCl}$ reference/counter electrode of the amperometric-based sensors needed to be grounded. This requirement prevented us from grounding the shared PVB reference electrodes in the potentiometric-based sensors, because the potential difference between the Ag/AgCl reference and PVB electrodes changes in the presence of different chloride ion concentrations (Extended Data Fig. 2b). In the case of the ISE-based sensors, the generated signals were essentially the voltage differences between the PVB-coated shared reference electrode and the working electrode of the respective sensors. Therefore, without grounding the PVB electrode, we measured the difference in potential of the floating ISE working and shared electrodes directly. To this end, the signal conditioning paths of the potentiometric-based sensors included a voltage buffer interfacing the respective working and reference electrodes, followed by a differential amplifier to effectively implement an instrumentation amplifier configuration. With this approach we ensured that the voltage-sensing and current-sensing paths were electrically isolated. Furthermore, the differential sensing stage also helped to minimize the unwanted common-mode interferences which would have otherwise degraded the fidelity of our sensor readings. Also, the high impedance nature of the ISE-based sensors37 required the use of high-impedance voltage buffers to ensure accurate open voltage measurement as intended. \n\nAll the analogue signal conditioning paths concluded with a corresponding unity gain four-pole low pass filter, each with a $^{-3}$ -dB frequency at $1\\mathrm{Hz}$ to minimize the noise and interference in our measurements. The choice of using active filters in our system also gave us flexibility in tuning the gain in our signalconditioning path if needed. The low pass filters were connected to the analogue-to-digital converter stage of the microcontroller, to facilitate the conversion of the filtered analogue signals to their respective digital forms. In our implementation, each of the analogue signal conditioning paths were electrically characterized to validate the linear output response of the channels with respect to the corresponding electrical input signals mimicking the sensor output signals. For this characterization step, electrical current was applied as an input to the glucose and lactate channel terminals to model the respective amperometric-based sensor output and differential voltage was applied at the terminals of the sodium and potassium channels to model the corresponding potentiometric-based sensor output. As illustrated in Extended Data Fig. 5a–d, all four signal-conditioning channels demonstrated an excellent linear response (correlation factor $R^{2}=1$ ). To eliminate the non-ideal effects such as voltage offset and to obtain precise signal readings, the exact numerical linear relationship between output and input was obtained to map the original input signal to the analogue circuit readouts, which in turn allowed for subsequent signal calibration and processing at the software level. Upon processing and averaging the data, the microcontroller was exploited to relay the data to the Bluetooth module for wireless transmission. \n\nPower delivery to the FISA. The FISA was powered by a single rechargeable lithium-ion polymer battery with a nominal voltage of $3.7\\mathrm{V}$ of a desired capacity (a representative 105-mAh battery is illustrated in Extended Data Fig. 5e and f). The protection circuitry included protects the battery against unwanted output shorts and over-charging. Step-up direct current/direct current converters were used to produce a fixed, regulated output of $+5\\mathrm{V}$ for the microcontroller and $+3.3\\mathrm{V}$ for the Bluetooth modules. This regulated output also served as the positive power supply for the analogue peripheral components. The negative power supply $(-5\\mathrm{V})$ for the analogue peripheral components was implemented through the use of inverting charge pump direct current/direct current converters that produce negative regulated outputs. \n\nThe custom mobile application design. A mobile application (the Perspiration Analysis App) was designed to accompany the FISA and to provide a user-friendly interface for data display and aggregation (Extended Data Fig. 3). To use this application, first, the user should wear the FISA and open the Perspiration Analysis App on the mobile device. The application establishes a secure Bluetooth connection to the FISA. Subsequently, it receives and displays the stream of data that are transmitted in real time from the FISA. The application is capable of plotting a graph of these values versus time during the user’s physical activities. The data and graphs can be stored on the device, uploaded to cloud servers online, and can be shared via social media. Additionally, the application keeps track of the duration of exercise as well as the distance travelled. Although the current implementation was programmed in the Android environment, similar application interfaces could easily be developed in other popular mobile operating systems such as iOS. \n\nThe characterization of the sensors. A set of electrochemical sensors was characterized to explore their reproducibility in solutions of target analytes. Extended Data Fig. 6a–d show that $\\mathrm{Na^{+}}$ and $\\mathrm{K^{+}}$ sensors had a relative standard deviation of ${\\sim}1\\%$ in sensitivity while glucose and lactate sensors had a relative standard deviation of ${\\sim}5\\%$ in sensitivity. However, there are differences in absolute potential values for ISEs in the same solution. Therefore, one-point calibration in a standard solution containing 1 mM KCl and $10\\mathrm{mMNaCl}$ was performed for $\\mathrm{Na^{+}}$ and $\\mathrm{K^{+}}$ sensors before each use. The measured potential of ISEs in the standard solution was then set to zero by the microcontroller. (Such calibration is similar to what is done in commercial finger-stick glucose sensors.) No calibration was needed for the glucose and lactate sensors. Longterm stability of the sensors was also evaluated over a period of four weeks using five different sensor arrays each week (Extended Data Fig. 6e–h). It was observed that the $\\mathrm{Na^{+}}$ and $\\mathrm{K^{+}}$ sensors had approximately the same sensitivities of $62.5\\mathrm{mV}$ and $59.5\\mathrm{mV}$ per decade of concentration, respectively, in ambient conditions. The sensitivities of the glucose and lactate sensors were similarly maintained within $5\\%$ of their original values over the four-week period when stored at $4^{\\circ}\\mathrm{C}$ . The glucose and lactate sensors were characterized chronoamperometrically using a Gamry Electrochemical Potentiostat (Fig. 2a and b). Owing to Faraday and capacitive currents38, the responses of both sensors showed drift initially but stabilized within 1 min of the data recording. The in vitro temperature compensation experiments (Fig. 2h) were performed continuously using the same sensor in four Petri dishes containing solutions at different temperatures on different hot plates. The convection and non-uniform distributions of solution temperature could result in noticeable noise in the signal measurements. \n\nFor continuous use, all the sensors displayed excellent stability over the entire exercise period. The sensor array could be repeatedly used for continuous temperature and sweat electrolyte monitoring. However, the glucose and lactate responses degraded beyond the exercise period (after two hours) owing to decreased enzyme activity. The sensor–FPCB interface allows for convenient replacement of the fresh sensor arrays for subsequent use. \n\nAnalysis of the effect of mechanical deformation on the sensors was performed by repeatedly bending the $\\mathrm{{Na^{+}}}$ , glucose sensors, and temperature sensors (radius of curvature, $1.5\\mathrm{cm}\\dot{}$ ) as well as the FPCB (radius of curvature, $3\\mathrm{cm}$ ) for a total of 60 cycles (Extended Data Fig. 8). Performance of the sensors was recorded after every 30 cycles. Continuous measurement on sensor performance during bending and no bending was also performed. \n\n$\\boldsymbol{E}\\boldsymbol{x}$ situ evaluation of the sweat samples. $E x$ situ sensor performance was also conducted by testing sweat samples collected from the subjects’ foreheads. Sweat samples were collected every $2{-}4\\mathrm{min}$ by scratching their foreheads with microtubes, and subjects’ foreheads were wiped and cleaned with gauze after every sweat collection19. The changes of $\\mathrm{[Na^{+}]}$ and $[\\mathrm{K^{+}}]$ during euhydration and dehydration trials were also studied ex situ in the same manner. The calibration of the sensor arrays was performed before ex situ measurements using artificial sweat containing $22\\mathrm{mM}$ urea, $5.5\\mathrm{mM}$ lactic acid, 3 mM $\\mathrm{NH_{4}^{+}}$ , $0.4\\dot{\\mathrm{mM}}\\mathrm{Ca}^{2+}$ , $50\\upmu\\mathrm{M}$ $\\ensuremath{\\mathrm{Mg^{2+}}}$ and $25\\upmu\\mathrm{M}$ uric acid with varying glucose concentrations of $0{-}200\\upmu\\mathrm{M}$ , $[\\mathrm{K^{+}}]$ of $1{-}16\\mathrm{mM}$ and $\\mathrm{[Na^{+}]}$ of $10{-}160\\mathrm{mM}$ . \n\nThe setup of FISA for on-body testing. A water-absorbent thin rayon pad was placed between the skin and the sensor array during on-body experiments to absorb and maintain sufficient sweat for stable and reliable sensor readings, and to prevent direct mechanical contact between the sensors and skin. The pad could absorb about $10\\upmu\\mathrm{l}$ of sweat, which was sufficient to provide stable sensor readings. During on-body tests, the newly generated sweat would refill the pad and ‘rinse away’ the old sweat. The on-body measurement results were also consistent with ex situ tests using freshly collected sweat samples. Assuming a singlecentred flow model13, the best-case sampling interval can be calculated to be less than $1\\mathrm{min}$ , based on the sweat rate $(\\sim3-4\\mathrm{mg}\\mathrm{min}^{-1}<\\mathrm{m}^{-2})^{39}$ and the pad size $(1.5\\mathrm{cm}\\times2\\mathrm{cm}\\times50\\upmu\\mathrm{m})$ . The intrinsic response time of FISA was smaller than the body’s response time to the changes in physiological conditions. An increase in temperature was observed when the ‘smart headband’ or ‘smart wristband’ was worn owing to the use of the plastic substrate on skin. Although this may result in a small error in measuring the actual skin temperature, it should be noted that this does not have an impact on the measurement of the electrolytes and metabolites, owing to the on-board temperature calibration. To ensure the fidelity of sensor readings further, the data collection of each channel took place when a sufficient sweat sample was present, as shown by the stabilization of the sensor readings (varying within $10\\%$ of the readings of the continuous five data points) within the physiologically relevant range: $\\mathrm{[Na^{+}]}$ , $20{-}120\\mathrm{mM}$ ; $[\\mathrm{K^{+}}]$ , $2{\\mathrm{-}}16{\\mathrm{mM}}$ ; glucose concentration, $0{-}200\\upmu\\mathrm{M}$ ; and lactate concentration, $2{-}30\\mathrm{mM}$ . \n\nOn-body sweat analysis. The on-body evaluation of the FISA was performed in compliance with the protocol that was approved by the institutional review board at the University of California, Berkeley (CPHS 2014-08-6636). 26 healthy subjects (4 females and 22 males), aged 20–40, were recruited from the University of California, Berkeley campus and the neighbouring community through advertisement by posted notices, word of mouth, and email distribution. All subjects gave written, informed consent before participation in the study. The study was conducted as three trials: constant workload cycle ergometry, graded workload cycle ergometry, and outdoor running. Constant workload cycle ergometry was conducted on 14 volunteers (4 females and 10 males between the ages of 20 and 40). The graded cycle ergometry was conducted on 7 male volunteers (who were also involved in the constant workload cycle study). 12 male volunteers between the ages of 20 and 40 were recruited for the outdoor running study. An electronically braked leg-cycle ergometer (Monark Ergomedic 839E, Monark Exercise AB) was used for cycling trials, which included real-time monitoring of heart rate, oxygen consumption $(V_{\\mathrm{O}_{2}})$ , and pulmonary minute ventilation. The power output was calibrated and monitored through the ergometer. Heart rate was measured using a Tickr heart rate monitor (Wahoo fitness), and $V_{\\mathrm{O}_{2}}$ and minute ventilation were continuously recorded throughout trials via an open-circuit, automated, indirect calorimetry system (TrueOne metabolic system; ParvoMedics). The FISAs were packaged inside traditional sweatbands during the indoor and outdoor trials. The sensor arrays were calibrated, and the subjects’ foreheads and wrists were cleaned with alcohol swabs and gauze before sensors were worn on-body. For the constant workload cycling trial subjects were cycling at $50\\mathrm{W}$ with 50-W increments every 90 s up to $150\\mathrm{W},$ and $20\\mathrm{min}$ of cycling at 150 W. The power output was then decreased by 50 W every 90 s. The graded workload trial consisted of $5\\mathrm{{min}}$ of seated rest followed by cycling at 75 W for $20\\mathrm{min}$ and then cycling at $200\\mathrm{W}$ until fatigue followed by a $10\\mathrm{-min}$ rest. The outdoor running trial was conducted with a group of 12 subjects in which 6 were instructed to drink $150\\mathrm{ml}$ water every $5\\mathrm{{min}}$ and 6 did not drink water throughout the trial. Subjects consented to run until volitional fatigue at a self-selected pace $(8-12\\mathrm{kmh^{-1}}$ ) and the $\\mathrm{{Na^{+}}}$ and $\\mathrm{K^{+}}$ sensor responses (from their foreheads) were recorded. \n\n![](images/ea59fd857598a0ae50a9528dd7c846b5f7c1369ec4570bb962f02502c8978319.jpg) \nExtended Data Figure 1 | Fabrication process of the flexible sensor the electrode areas. e, Electron-beam deposition of the Ag layer followed array. a, PET cleaning using acetone, isopropanol and $\\mathrm{O}_{2}$ plasma etching. by lift-off in acetone. f, Ag etching on the Au working electrode area and b, Patterning of $\\mathrm{Cr/Au}$ electrodes using photolithography, electron- Ag chloridation on the reference electrode area. g, Optical image of the beam evaporation and lift-off in acetone. c, Parylene insulating layer flexible electrode array. h, Photograph of the multiplexed sensor array after deposition. d, Photolithography and $\\mathrm{O}_{2}$ plasma etching of parylene in surface modification. \n\n![](images/4340ab5ed18967e8835c05b5481bcbec94da73afb5c4b588e7774ed6d11e26d8.jpg) \nExtended Data Figure 2 | The characterizations of the modified electrodes. a, Cyclic voltammetry of the amperometric glucose and lactate sensors using Prussian blue as a mediator in PBS $(\\mathrm{pH}7.2)$ . Scan range, $-0.2\\mathrm{V}$ to $0.5\\mathrm{V};$ scan rate, $50\\mathrm{mVs^{-1}}$ . b, Potential stability of a PVB-coated $\\mathrm{Ag/AgCl}$ electrode and a solid-state $\\mathrm{\\Ag/AgCl}$ reference electrode (versus \ncommercial aqueous $\\mathrm{Ag/AgCl}$ electrode) in different $\\mathrm{\\DeltaNaCl}$ solutions. c, d, The stability of a PVB-coated reference electrode in solutions containing $50\\mathrm{mMNaCl}$ and $10\\mathrm{mM}$ of different anionic (c) and cationic (d) solutions. Data recording was paused for $30\\mathrm{s}$ for each solution change in $\\mathbf{b-d}$ . \n\n![](images/1bc1a27c77fbdbdcbfcc5b5d9d00e034b2bbc5cb35f0aac4567da31c9d951b4d.jpg) \nExtended Data Figure 3 | The custom-developed mobile application for data display and aggregation. a, The home page of the application after Bluetooth pairing. b, Real-time data display of sweat analyte levels as well as skin temperature during exercise. c, Real-time data progression of individual sensor. d, Available data sharing and uploading options. \n\n![](images/694fb2010f49cf908093747948ec9fa0652f10b794c5293608b45b303bed6eab.jpg) \nExtended Data Figure 4 | Schematic diagram of signal-conditioning circuit. a–d, Signal conditioning circuits for (a) glucose, (b) lactate, (c) sodiu and (d) potassium channels. VDD and VSS represent the positive and negative power supplies, respectively. LT1462 is the integrated-circuit chip part \n\n![](images/12a53804e7cdcf3f3e6aa83987ecc9d44d22405e98f342d2f4bfc30a384f57d8.jpg) \nExtended Data Figure 5 | The calibration and power delivery of the FISA. a–d, Flexible PCB calibration for glucose (a), lactate (b), sodium (c) and potassium (d) channels. e, Power delivery diagram of the system. f, Photograph of a small rechargeable battery module used in \nthe current work (placed next to a quarter-dollar coin for comparison). g, Representative photograph of the power delivery package inside a transparent wristband on a subject’s wrist. \n\n![](images/aae06ac8918932066a043ca1a5c8612b38bf7f686896f4c696e3abd08caa44d1.jpg) \nExtended Data Figure 6 | Reproducibility and long-term stability of the glucose (g) and lactate (h) sensors. Sensitivity is measured in millivolts per biosensors. a–d, The reproducibility of the sodium (a), potassium decade of concentration. The error bars represent the standard deviations (b), glucose (c) and lactate (d) sensors (eight samples for each kind of of the measured data for five samples. sensor). e–h, The long-term stability of the sodium (e), potassium (f), \n\n![](images/9d0e4ea52e3e06ae8eecbacb88d0e528e3fbae02002b80d394ac8dee511983ec.jpg) \nExtended Data Figure 7 | Selectivity study for electrochemical (e) and calibration plot (f) of the amperometric glucose and lactate sensor biosensors. a–d, The interference study for individual glucose (a), lactate array with a shared solid-state $\\mathrm{Ag/AgCl}$ reference electrode. g, h, The real(b), sodium (c) and potassium (d) sensors using an electrochemical time interference study $\\mathbf{\\tau}(\\mathbf{g})$ and calibration plot (h) of the potentiometric working station. Data recording was paused for $30\\mathrm{s}$ for the addition of $\\mathrm{{Na}^{+}}$ and $\\mathrm{K^{+}}$ sensor array with a shared PVB-coated reference electrode. each analyte in c and d. e, f, The real-time system-level interference study Data recording was paused for $30s$ for each solution change in e and $\\mathbf{g}$ \n\n![](images/1102a1b789923dab4f2063009d358cdc99571d484ff44111225a545a54de2fbc.jpg) \nExtended Data Figure 8 | Mechanical deformation study of the flexible potassium $\\mathbf{\\tau}(\\mathbf{h})$ , glucose (i), lactate (j),and temperature (k) sensors and sensors and the FPCB. a–f, The responses of the sodium (a), potassium of the FPCB (l) during bending. The radii of curvature for the bending (b), glucose (c), lactate (d), temperature (e) sensors and of the FPCB (f) study of sensors and the FPCB were $1.5\\mathrm{cm}$ and $3c\\mathrm{m}$ , respectively. Data after 0, 30 and 60 cycles of bending. $\\mathbf{g-l},$ The responses of the sodium $\\mathbf{\\sigma}(\\mathbf{g})$ , recording was paused for $30s$ to change the conditions and settings. \n\n![](images/64cfa378a08dd0596a7d02ac2660080f98d49f90e828f3ae5fd0e3deee111de6.jpg) \nExtended Data Figure 9 | On-body real-time perspiration analysis during stationary cycling using the FISA on a subject’s wrist. Conditions are as in Fig. 3c and d. \n\n![](images/227f4cbfc15ea2d5fbb1a34f43cfa8317ba65ca4e953d1dd0ef889fd0a85ef03.jpg) \nExtended Data Figure 10 | $\\boldsymbol{E}\\boldsymbol{x}$ situ measurement of collected sweat weight dehydration). b, d, The ex situ results of $\\mathrm{[Na^{+}]}$ (b) and $[\\mathrm{K^{+}}]$ (d) samples using the FISA on a subject during stationary cycling at $\\mathbf{150W}$ . from the sweat samples collected from the subject’s forehead with water a, c, The ex situ results of $\\mathrm{[Na^{+}]}$ (a) and $[\\mathrm{K^{+}}]$ (c) from the sweat samples intake ( $\\mathrm{150ml}$ per $5\\mathrm{{min}}$ ). collected from the subject’s forehead without water intake $(\\sim2.5\\%$ of body " + }, + { + "id": "10.1038_ncomms7486", + "DOI": "10.1038/ncomms7486", + "DOI Link": "http://dx.doi.org/10.1038/ncomms7486", + "Relative Dir Path": "mds/10.1038_ncomms7486", + "Article Title": "Nitrogenated holey two-dimensional structures", + "Authors": "Mahmood, J; Lee, EK; Jung, M; Shin, D; Jeon, IY; Jung, SM; Choi, HJ; Seo, JM; Bae, SY; Sohn, SD; Park, N; Oh, JH; Shin, HJ; Baek, JB", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Recent graphene research has triggered enormous interest in new two-dimensional ordered crystals constructed by the inclusion of elements other than carbon for bandgap opening. The design of new multifunctional two-dimensional materials with proper bandgap has become an important challenge. Here we report a layered two-dimensional network structure that possesses evenly distributed holes and nitrogen atoms and a C2N stoichiometry in its basal plane. The two-dimensional structure can be efficiently synthesized via a simple wet-chemical reaction and confirmed with various characterization techniques, including scanning tunnelling microscopy. Furthermore, a field-effect transistor device fabricated using the material exhibits an on/off ratio of 10(7), with calculated and experimental bandgaps of approximately 1.70 and 1.96 eV, respectively. In view of the simplicity of the production method and the advantages of the solution processability, the C2N-h2D crystal has potential for use in practical applications.", + "Times Cited, WoS Core": 969, + "Times Cited, All Databases": 997, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000352635600005", + "Markdown": "# Nitrogenated holey two-dimensional structures \n\nJaveed Mahmood1, Eun Kwang Lee1,2, Minbok Jung3, Dongbin Shin4, In-Yup Jeon1, Sun-Min Jung1, Hyun-Jung Choi1, Jeong-Min Seo1, Seo-Yoon Bae1, So-Dam Sohn3, Noejung Park4, Joon Hak $\\mathsf{O h}^{2}$ , Hyung-Joon Shin3 & Jong-Beom Baek1 \n\nRecent graphene research has triggered enormous interest in new two-dimensional ordered crystals constructed by the inclusion of elements other than carbon for bandgap opening. The design of new multifunctional two-dimensional materials with proper bandgap has become an important challenge. Here we report a layered two-dimensional network structure that possesses evenly distributed holes and nitrogen atoms and a $C_{2}\\mathsf{N}$ stoichiometry in its basal plane. The two-dimensional structure can be efficiently synthesized via a simple wetchemical reaction and confirmed with various characterization techniques, including scanning tunnelling microscopy. Furthermore, a field-effect transistor device fabricated using the material exhibits an on/off ratio of ${10}^{7}$ , with calculated and experimental bandgaps of approximately 1.70 and $1.96\\mathsf{e V},$ respectively. In view of the simplicity of the production method and the advantages of the solution processability, the $C_{2}N-h20$ crystal has potential for use in practical applications. \n\nTrheseraerccehnetrds icno evrayriofugs fipehledns, hparismgarinlye bdeicnatuesre of itms crystal electronic structure1. The properties of graphene promise many applications such as nanoelectronics2, hydrogen storage3, batteries4 and sensors5. The plentiful scientific discussions in the field of graphene research have triggered huge interest in new 2D ordered crystals constructed by inclusion of elements other than carbon6. Scientists around the world are working towards the synthesis of 2D crystals with tuneable structures and properties using a bottom-up approach7–10. One of the strongest motivations is the possibility of establishing a finite dimension stable bandgap9 in a well-defined 2D structure10, which is one of the fundamental prerequisites for a material to be used as an active switching element in electronics11,12. Various structural modifications, including doping of heteroatoms, have been tested with this goal in mind. Among these modifications, the substitution of nitrogen (N) atoms appears to be an excellent choice because its atomic size and five-electron valence structure 1 $\\cdot s p^{2}$ hybridization) allow it to naturally fit into a strong covalent network structure of carbon atoms13. The multiformity of the technological applications of bandgap-created 2D materials can aid in the search for easy and simple routes to produce N-containing 2D structures. Recently, a variety of techniques have been used to obtain N-containing 2D crystals from graphene14,15 and graphene oxide16; however, these methods offer poor control, involve toxic reagents and harsh reaction conditions and tend to result in metal contamination. Most importantly, however, the structures of N-containing 2D materials are not well-defined for practical use. As a result, creating a properly controlled large-scale production protocol for an N-containing 2D framework has become a substantial challenge for the scientific community7,8,17. \n\nHere, we design and prepare a 2D crystal with uniform holes and nitrogen atoms. The structure and bandgap of the prepared 2D crystal is studied using experimental techniques and density functional theory (DFT). Furthermore, the prepared N-containing holey 2D crystal may be a foundational material for the future development of multifunctional 2D crystals. \n\n# Results \n\nSynthesis and characterization of $\\mathbf{C}_{2}\\mathbf{N}$ -h2D crystals. The difference between graphene (Supplementary Fig. 1a) and holey graphene (Supplementary Fig. 1b) is that the latter has uniform periodic holes in a fused aromatic network structure. However, the holey graphene has not yet been previously developed and the chance is very low. The structure of the newly synthesized holey nitrogenated 2D crystal (Supplementary Fig. 1c) not only has uniform holes, but the holes and phenyl rings are also surrounded by aromatic nitrogen atoms (cyan blue spheres in Supplementary Fig. 1c). In contrast to the fully conjugated $\\pi$ -electron structures of graphene (Supplementary Fig. 1a), an ordered inclusion of uniform holes and nitrogen atoms is expected to widen the gap between the valence and conduction bands (that is, the bandgap) to a level ideal for a bandgap-opened material, which would be useful, for example, in semiconductor applications. The unique N-containing holey 2D crystal was simply synthesized by the reaction between hexaaminobenzene (HAB) trihydrochloride (Fig. 1a)18 and hexaketocyclohexane (HKH) octahydrate in $N.$ -methyl-2-pyrrolidone (NMP) in the presence of a few drops of sulphuric acid $\\mathrm{(H}_{2}\\mathrm{SO}_{4})$ or in trifluoromethanesulphonic acid. The tremendous potential energy gain by aromatization (approximately $-\\dot{8}9.7\\mathrm{kcalUmol}^{-1}$ calculated using DFT, Supplementary Fig. 2) is responsible for the spontaneous polycondensation between the HAB and HKH and leads to the formation of a layered crystalline 2D network structure (Supplementary Fig. 2)19. The resultant dark-black graphite-like solid (Fig. 1b), whose appearance was a strong indication of the formation of a conjugated layered 2D crystal, was Soxhlet extracted with water and then methanol, respectively, to completely remove any small mass impurities and was finally freeze-dried at $-120^{\\circ}\\mathrm{C}$ under reduced pressure $(0.05\\mathrm{mmHg})$ . Utilizing such a strong driving force for the aromatization, the 3D fused $\\pi$ -conjugated microporous polymers were also conveniently realized by solvothermal reaction in the sealed glass tube20 and ionothermal process in the presence of $\\mathrm{\\AlCl}_{3}$ for energy storage21. When the sample solution was cast onto a $\\mathrm{SiO}_{2}$ substrate, annealed at $700^{\\circ}\\mathrm{C}$ under an argon atmosphere and collected by etching in hydrofluoric acid, the solution contained shiny flakes observable under a strong light (Fig. 1c). A large-area film was also cast and transferred onto a flexible polyethylene terephthalate (PET) substrate (Fig. 1d). \n\nThe empirical formulas of the product are $\\mathrm{C}_{2}\\mathrm{N}$ for the repeating unit in the basal plane (structure 2 in Supplementary Fig. 2) and ${\\mathrm{C}}_{6}{\\mathrm{H}}_{2}{\\mathrm{N}}_{3}{\\mathrm{O}}$ for the entire molecule, including the edge functional the groups (structure 1 in Supplementary Fig. 2). Various elemental analyses using different techniques confirmed the chemical formula of the molecule (Supplementary Table 1). Hence, we named the 2D crystal $\\mathrm{{}^{\\circ}C}_{2}\\mathrm{{N}}$ holey 2D crystal’ or $\\ensuremath{\\mathrm{~c~}}_{2}\\ensuremath{\\mathrm{N}}-h2\\ensuremath{\\mathrm{D}}$ crystal’ and determined it to be soluble in various commonly used solvents, in which it exhibits colloidal scattering (Supplementary Fig. 3). \n\nThe powder X-ray diffraction (XRD) pattern of the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal indicates that its structure is readily layered and highly crystalline. Like the XRD pattern of graphite, the pattern of this crystal also shows a sharp 002 diffraction peak at $27.12^{\\circ}$ (Supplementary Fig. 4a), whose position corresponds to an interlayer distance ( $\\overset{\\cdot}{d}$ -spacing) of $0.328\\mathrm{nm}$ . However, this $d$ -spacing is narrower than the $d$ -spacing of graphite ( $\\cdot d=0.335$ $\\mathrm{nm}\\Bigr)^{22}$ . The narrower $d$ -spacing of the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal is thought to originate from the evenly distributed nitrogen atoms and holes. Nitrogen has a smaller atomic size $(70\\mathrm{pm})$ and greater electronegativity $(\\chi=3.07)$ than carbon $77\\mathrm{pm}$ and $\\chi=2.55,$ . In addition to van der Waals forces, the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal exhibits polar attraction, resulting in stronger interlayer interactions than those in graphite. \n\n$\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) measurements were performed to probe the chemical composition of the new material. The characteristic band for the K-edge of nitrogen appeared at $399\\mathrm{eV}$ , indicating the presence of $\\overline{{s p^{2}}}$ -hybridized nitrogen atoms in the holey 2D structure. The survey scan spectrum from the XPS analysis revealed the presence of C1s, N1s and O1s without any other impurities (Supplementary Fig. 4b, Supplementary Note 1). The corresponding high-resolution XPS spectra and the XPS spectra of the heat-treated samples are presented in Supplementary Figs 5 and 6, respectively. Thermogravimetric analysis indicated that the as-prepared $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal underwent a gradual weight loss from the beginning of the scan (Supplementary Fig. 4c). However, the $\\mathrm{C}_{2}\\mathrm{\\bar{N}}{\\cdot}h2\\mathrm{D}$ crystal heated at $700^{\\circ}\\mathrm{C}$ under an argon atmosphere exhibited high thermal stability under both air and argon (Supplementary Fig. 4d), indicating that the early weight loss of the as-prepared sample was due to the volatilization of entrapped substances in the holes. As a result, the Brunauer–Emmett–Teller-specific surface areas of the untreated and heat-treated samples were 26 and $281\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , respectively. \n\nThe bulk morphologies of the 2D crystals were examined using field-emission scanning electron microscopy. The grain sizes of the as-prepared and heat-treated samples were as large as a few hundred micrometres (Supplementary Fig. 7a–c). The transmission electron microscopy (TEM) image obtained from the dispersed sample appears to show a wrinkled morphology (Supplementary Fig. 7d), which is attributed to the flexible nature of the holey 2D structure23. The high-magnification TEM image indicates high crystallinity (Supplementary Fig. 7e) with an interlayer $d$ -spacing of $0.327\\mathrm{nm}$ (Supplementary Fig. 7f), which is in good agreement with the XRD results $\\cdot0.328\\mathrm{nm}$ , see Supplementary Fig. 4a), confirming that the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal has the thinnest layered 2D structure reported to date. TEM element maps obtained by energy-dispersive X-ray spectroscopy and electron energy loss spectroscopy indicate that the elemental compositions of the samples are in accordance with the theoretical values (Supplementary Fig. 8). Uniform films with various thicknesses were also cast onto a $\\mathrm{SiO}_{2}(300\\mathrm{nm})/\\mathrm{Si}$ wafer (Fig. 1d and Supplementary Fig. 9). We performed scanning tunnelling microscopy (STM) experiments to verify the molecular structure of the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal. A single-layer $\\dot{\\mathrm{C}_{2}}\\mathrm{N}\\mathrm{-}h2\\mathrm{D}$ crystal sample was deposited thermally onto a $\\mathrm{Cu}(111)$ substrate under ultrahigh vacuum (UHV) conditions (Supplementary Fig. 10). Figure 2a shows a high-resolution STM image of the $\\mathrm{C}_{2}\\mathrm{\\tilde{N}}{\\cdot}h2\\mathrm{D}$ monolayer on the $\\bar{\\mathrm{Cu}}(111)$ substrate. The STM image clearly reveals the uniformly distributed holey structure in hexagonal arrays (left inset, Fig. 2a), which matches precisely with the theoretically derived image (Fig. 2b). The inter-hole distance measured from the height profiles and the 2D fast Fourier transform image is approximately $8.24\\pm0.96\\mathring{\\mathrm{A}}$ (Fig. 2c). The topographic height difference between the holes and the hexagonal lattice is $0.27\\pm0.017\\mathring\\mathrm{A}$ , and the benzene rings are imaged slightly higher than the $\\mathrm{C-N}$ bridged regions (Fig. 2d), contributing to the narrower interlayer $d$ -spacing than in graphite (Supplementary Fig. 11a) and $h$ -BN (Supplementary Fig. 11b). \n\n![](images/83644aabbff2e988bb171dfb9eb736b9f2add6baf135cbb454c1eaa672acc273.jpg) \nFigure 1 | Preparation and structure. (a) Schematic representation of the reaction between hexaaminobenzene (HAB) trihydrochloride and hexaketocyclohexane (HKH) octahydrate to produce the $C_{2}N-h2D$ crystal. The inset in the image of HAB is a polarized optical microscopy image of the HAB single crystal. Digital photographs: (b) as-prepared $C_{2}N-h2D$ crystal; (c) solution-cast $C_{2}N-h2D$ crystal on a $\\mathsf{S i O}_{2}$ surface after heat-treatment at $700^{\\circ}\\mathsf{C};$ (d) a $C_{2}N-h2D$ crystal film (thickness: approximately $330{\\mathsf{n m}}.$ ) transferred onto a PET substrate. The shiny metallic reflection of the sample indicates that it is highly crystalline. \n\nThe extensively investigated 2D crystals of graphene (Supplementary Fig. $^\\mathrm{11a,d)}$ and $h$ -BN (Supplementary Fig. $^{11\\mathrm{b},\\mathrm{e}^{\\cdot}}$ ) are fundamentally different in terms of their electronic structures, despite their geometrical similarity. For example, graphene is a conductor with a vanishingly small bandgap24 whereas $h$ -BN is an insulator with a wide bandgap of $5.05{-}6.40\\mathrm{eV}$ (ref. 24). Thus, the electronic structure of the newly developed $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal is worthy of investigation. The direct bandgap was empirically determined using ultraviolet– visible spectroscopy (Fig. 3a): it is approximately $1.96\\mathrm{eV}$ , which is well within the range of semiconductor bandgaps25. To elucidate the band structure of the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal, we measured cyclic voltammograms to determine the onset reduction potential, which corresponds to the bottom of the conduction band, or the lowest unoccupied molecular orbital (LUMO). To acquire the cyclic voltammograms (Fig. 3b), we deposited a $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{\\bar{D}}$ crystal onto glassy carbon as a working electrode. Relative to an ${\\mathrm{Ag/\\dot{A}g^{+}}}$ reference electrode, the onset reduction potential appeared at $-0.81\\mathrm{V}$ . The LUMO was calculated from the reduction potential to be $-3.63\\mathrm{eV}$ (Supplementary Fig. 12). On the basis of the direct optical bandgap of the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal (Fig. 3a), the top of the valence band, or highest occupied molecular orbital, was calculated to be $-5.59\\mathrm{e}\\bar{\\mathrm{V}}$ (Supplementary Note 2). \n\nTheoretical calculations. We also conducted first-principles DFT calculations to investigate the electronic structure of the $\\bar{\\mathrm{C}}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal (Supplementary Methods). The band structure along the symmetry line in the Brillouin zone, from $\\Gamma$ to M, and the density of electronic states are shown in Fig. 3c,d, respectively. According to the gradient-corrected DFT calculations, the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal shows a finite band-gap of approximately $1.70\\mathrm{eV}$ (Fig. 3c), which is smaller (by approximately $0.26\\mathrm{eV},$ than the optically determined value $(1.96\\mathrm{eV})$ . The underestimation of the Kohn–Sham treatment of the DFT is well known26. The magnitude of the bandgap and the existence of flat bands near the Fermi levels suggest that the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal is a completely different 2D material from graphene and $h$ -BN. In the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal, the benzene rings are bridged by pyrazine rings, which consist of a six-membered D2h ring with two nitrogen atoms facing each other (Fig. 1a and Supplementary Fig. 2). As such, the $\\pi$ - electronic structure of the benzene ring is isolated, resulting in unusual flat bands (whereas graphene has cone-shaped bands) near the edges of the valence and conduction bands. The conduction band minimum consists of a flat band that originates from the localized $\\boldsymbol{p}$ orbital of the nitrogen atoms (Fig. 3e) and one dispersive band delocalized over the entire plane. The valence-band maximum consists of doubly degenerate flat bands, which originate predominantly from the non-bonding $\\sigma$ -states localized at the nitrogen atoms (Fig. 3f). The flat bands near the band edges can be engineered to produce useful phenomena. For example, hole-doping could result in a magnetic state whose spins originate from the two flat bands. Therefore, this material can offer complementary features to the more widely studied graphene, which has a vanishing bandgap (that is a conductor) and $h$ -BN, which has a wide bandgap (that is an insulator). \n\n![](images/06fa380453335907afba8e080c9b55d56af93e487505ead61d396162f6029e7c.jpg) \nFigure 2 | STM characterization. (a) An atomic-resolution STM topography image of the $C_{2}N-h2D$ crystal on Cu(111). The STM image was obtained at a sample bias of $0.7\\mathrm{V}$ and a tunnelling current of $300{\\mathsf{p A}}$ . The top-left inset is the structure of the $C_{2}N-h2D$ crystal superimposed on the image. The bottom-right inset is 2D fast Fourier transform. (b) Simulated image (see the first-principles calculations in ESI). $\\mathbf{\\eta}(\\bullet)$ The topographic height profile along deep-blue line. (d) The topographic height profile along green line. Green arrow indicates the location of the C–N bridged region. The scale bars in (a), the inset in (a) and $(\\pmb{6})$ are $2.0\\mathsf{n m}$ , $2.0\\mathsf{n m}^{-1}$ and $2.0\\mathsf{n m}$ , respectively. \n\nFET device properties of the $\\mathbf{C}_{2}\\mathbf{N}\\mathbf{-}h2\\mathbf{D}$ crystal. To illustrate the electrical properties, field-effect transistors (FETs) were fabricated using $\\mathrm{C}_{2}\\mathrm{\\bar{N}}{\\cdot}h\\mathrm{\\bar{2}D}$ crystals as the active layer. A schematic of the details of film preparation by solution casting and device fabrication are presented in Supplementary Fig. 13, see also Supplementary Note 3. The optical images of typical $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal flakes are presented in Supplementary Fig. 14. Because of stronger interlayer interactions, the isolation of a single layer was not possible using this method. Atomic force microscopy analysis of the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal flakes revealed that the average (mean) thickness of the sample (out of ten samples) was $8.0\\pm3.5\\mathrm{nm}$ (Fig. 4a), implying that multilayers of the $\\bar{\\mathrm{C}}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal were stacked. Figure 4b shows the optical image of the fabricated FET device, and the inset shows the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystals before the deposition of gold electrodes. The devices were annealed at $100^{\\circ}\\mathrm{C}$ under reduced pressure $(5\\times10^{-6}$ torr) to remove chemical impurities that might have been trapped and/or adsorbed into holes and interlayers during the fabrication process. \n\nTypical transfer curves of the $\\bar{\\bf C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal FET devices are presented in Fig. 4c, and the electrical properties of the $\\mathrm{C}_{2}\\mathrm{N}$ -h2D crystals are summarized in Supplementary Table 2. The on/off current ratio of the transistor was defined as the ratio between the maximum and minimum drain currents; the maximum on/off current ratio obtained from 50 FET devices was $4.6\\times10^{7}$ . Furthermore, when the off current was defined as the average drain current before the turn-on state, the average on/off current ratio remained as high as $2.1\\times10^{5}$ with a standard deviation o $\\mathrm{f}\\pm3.9\\times10^{5}$ . These results clearly indicate that the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystals possess a bandgap. In addition, the corresponding output characteristics exhibited well-defined field-effect behaviours under hole-enhanced operation (Supplementary Fig. 15a). Because the work function of gold (approximately $5.10\\mathrm{eV})$ is much closer to the highest occupied molecular orbital level $(-5.59\\mathrm{eV})$ of the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal than to its LUMO level $(\\mathrm{-}3.63\\mathrm{eV})$ , p-type operation is clearly favourable with gold electrodes (see Supplementary Fig. 16 for the energy-level diagram). Interestingly, the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal exhibited semimetallic (graphene-like) behaviour before annealing (Supplementary Fig. 15b), showing ambipolar charge transport with a Dirac point of $-7\\mathrm{V}$ , an electron mobility of $\\overset{\\cdot}{13.5}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ and a hole mobility of $20.6\\thinspace\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\thinspace s^{-1}$ . The semimetallic behaviour is attributed to the unintentional doping effects by the trapped impurities and/or adsorbed gases in the holey $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystal structure, thereby suggesting that the electronic properties of the $\\mathrm{C}_{2}\\mathrm{N}$ -h2D crystal are tuneable. \n\n# Discussion \n\nTo the best of our knowledge, this work represents the synthesis of micrometre-sized 2D holey crystals with high crystallinity via a simple wet-logical reaction as a bottom-up approach without template assistance. The unique geometric and electronic structure of the $\\mathrm{C}_{2}\\mathrm{N}{\\cdot}h2\\mathrm{D}$ crystals can be further exploited for use in numerous potential applications for which graphene and $h$ -BN have inherent limitations. Comparisons between the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal and other related materials are shown in Supplementary Fig. 17, and their characteristics are summarized in Supplementary Table 3. For example, multifunctionality stemming from uniformly distributed holes and nitrogen atoms is highly attractive for many interesting applications (Supplementary Fig. 18). Specifically, purely organic non-metal magnetism could be achieved after engineering a hole-doping level27; size and shape selective absorption of transition metals and biomolecules could be induced via coordinative interactions28–30; and new catalysts could be developed for the oxygen reduction reaction15 and various organic reactions (see Supplementary Fig. 19, Supplementary Methods). \n\n![](images/a51d370cfcf1b0f3d69ec346b11b4dceee791f8f5923f8ab4954d4c83c2cc486.jpg) \nFigure 3 | Experimental and theoretical band gap calculations. (a) Results of optical band-gap measurements and a plot of the absorbance squared vs. photon energy $(h\\nu)$ extrapolated to zero absorption. The inset is the ultraviolet absorption curve. (b) Cyclic voltammograms of the $C_{2}N\\cdot h20$ crystal at a scan rate of $100\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ using a ${\\mathsf{A g}}/{\\mathsf{A g}}^{+}$ reference electrode. (c) The band structure from the zone centre to the M point of the 2D triangular lattice. (d) The density of electronic states. An iso-surface plot of the Kohn–Sham orbital at the gamma point: (e) the conduction-band minimum state; $(\\pmb{\\uparrow})$ the doubly degenerate valence-band maximum state. The insets in e and f signify the $p$ and $\\sigma$ -orbital characters of the corresponding bands. \n\n![](images/2d2cec795a39f75ad6d5f807eab860f7bbbcdac6d6650c84a186e04b4d7c3ca9.jpg) \nFigure 4 | Field-effect transistor (FET) device study. (a) Atomic force microscopy image of the $C_{2}N-h2D$ crystal; the scale bar is $7\\upmu\\mathrm{m}$ . The height profile (cyan-blue line) was obtained along the cyan-blue line. (b) Optical microscopy image of a $C_{2}N\\cdot h20$ crystal FET prepared on a $\\mathsf{S i O}_{2}(300\\mathsf{n m})/\\mathsf{n}^{+}+$ Si wafer. The channel length $(L)$ of the device is $500\\mathsf{n m}$ , and the channel width-to-length $(W/L)=13$ . The inset is an optical microscopy image taken before the deposition of Au electrodes on the crystal. The scale bars are $60\\upmu\\mathrm{m}$ . (c) Transfer curves of the $C_{2}N-h2D$ crystal FET devices measured at $25^{\\circ}C$ under $5\\times10^{-6}$ torr $(V_{\\mathsf{D S}}=-30\\mathsf{V})$ . \n\nIn summary, we have established that the thinnest layered 2D crystal (designated as $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal) reported to date can be simply synthesized via a bottom-up wet-chemical reaction. The crystal has evenly distributed holes and nitrogen atoms in the layered structure with high crystallinity; we verified its structure by atomic-resolution STM imaging. The crystal exhibits $\\displaystyle s p^{2}$ hybridization features with a semiconducting bandgap of approximately $1.96\\mathrm{eV}$ (DFT calculated value: $1.70\\mathrm{eV})$ with unusual flat bands. The FET device exhibits a $10^{7}$ on/off ratio, confirming the semiconducting nature of the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal. There are many known difficulties involved in the synthesis of graphene and $h$ -BN, and the synthesis of the $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystals is a simple and highly efficient method for the formation of a fused aromatic 2D network structure. This unique material will open new opportunities in materials science and technology and thus broaden the horizon of applications in electronics, sensors, catalysis and many more research areas, which may lead to complementary uses for graphene and $h$ -BN. Furthermore, successful synthesis using a simple and powerful conceptual wet-chemistry-based bottom-up approach coupled with the versatility of organic synthesis may open a new chapter in the cost-effective generation of other 2D materials with tuneable properties, which will be a flourishing new area of research. \n\n# Methods \n\nSynthesis of the $\\mathsf{\\pmb{C}}_{2}\\mathsf{\\pmb{M}}$ -h2D. HAB $\\mathrm{(2g,7.20mmol)}$ and HKH $(2.248\\mathrm{g},7.20\\mathrm{mmol},$ ) were charged in a three-necked round bottom flask under argon atmosphere and placed in ice bath. Deoxygenated NMP $(80\\mathrm{ml})$ with a few drops of sulfuric acid or freshly distilled trifluoromethanesulfonic acid $(80\\mathrm{ml})$ was slowly added. The reaction flask was allowed to warm up to room temperature for 2 h. The ice bath was replaced with oil bath and heated to $175^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{h}}$ . Then, the flask was cooled to room temperature and water was added. The solid product that precipitated was collected by suction filtration using polytetrafluoroethylene (PTFE) $(0.5\\upmu\\mathrm{m})$ membrane. The resultant dark solid was further Soxhlet extracted with methanol and water, respectively, and freeze-dried at $-120^{\\circ}\\mathrm{C}$ under reduced pressure $\\left(0.05\\mathrm{mmHg}\\right)$ for 3 days. \n\nSTM experiments. The STM experiments were carried out in a UHV lowtemperature scanning tunnelling microscope (SPECS JT-STM) at 77 K. The $\\mathrm{Cu}(111)$ single crystal was cleaned by a few cycles of $\\mathrm{Ar^{+}}$ sputtering and annealing. After cleaning the $\\mathrm{Cu}(111)$ substrate, the solution-synthesized $\\mathrm{C}_{2}\\mathrm{N}{-}h2\\mathrm{D}$ crystal was deposited on the pre-cleaned $\\mathrm{Cu}(111)$ substrate by in-situ thermal evaporation under UHV condition. The sample evaporation temperature was about $600\\mathrm{K},$ and the temperature of the substrate was maintained at room temperature. To simulate the STM image, we integrated the Kohn–Sham charge density in the energy window of $0.7\\mathrm{eV}$ below and above the Fermi level. The shown image in Fig. 2b is the conduction bands part of the charge density in the plane $1\\textup{\\AA}$ about the atomic layer. \n\nPreparation of thin films by solution casting. Large-area films were fabricated by drop casting of the $\\mathrm{C}_{2}\\mathrm{N}$ -h2D crystal dispersed in trifluoromethanesulfonic acid on the preheated $(140^{\\circ}\\mathrm{C})$ $\\mathrm{SiO}_{2}(300\\mathrm{nm})/\\mathrm{Si}$ substrate and subsequently heat-treated at $700^{\\circ}\\mathrm{C}$ in argon for $^{2\\mathrm{h}}$ . Before transferring the solution-casted films on the other substrates, poly(methylmethaacrylate) (PMMA) solution was spin coated on the holey structure films. The $\\mathrm{SiO}_{2}$ substrate was etched off by an aqueous solution of $2\\%$ hydrofluoric acid. Then, the PMMA-coated $\\mathrm{C}_{2}\\mathrm{N}$ -h2D crystal films were transferred on PET substrate and the PMMA was washed off by immersing in acetone and dichloromethane to produce $\\mathrm{C}_{2}\\mathrm{N}$ -h2D crystal films on PET (Fig. 1d). Large-area films on various other substrates such as quartz and glass can be readily prepared through similar procedure, showing more or less very similar results. \n\nMaterial characterization. Themogravimetric analysis was conducted in air and argon atmospheres at a heating rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ using a Thermogravimetric \n\nAnalyzer Q200 TA Instrument. Scanning electron microscope images were taken on Field Emission Scanning Electron Microscope Nanonova 230 FEI. XPS was performed on X-ray Photoelectron Spectroscopy Thermo Fisher K-alpha. XRD studies were taken on High Power X-Ray Diffractometer D/MAZX 2500V/PC ( $_\\mathrm{Cu-K}\\upalpha$ radiation, $35\\mathrm{kV}$ , $20\\mathrm{mA}$ , $\\lambda=1.\\dot{5}418\\mathring\\mathrm{A}$ ), Rigaku. Conventional TEM was performed by using JEM-2100F (JEOL) under an operating voltage of $200\\mathrm{keV}$ . The samples for TEM were prepared by drop casting NMP dispersion on Quantifoil holey carbon TEM grid and dried in oven at $80^{\\circ}\\mathrm{C}$ \n\nReferences \n1. Novoselov, K. S. et al. Electric field effect in atomically thin carbon films. Science 306, 666–669 (2004). \n2. Son, Y.-W., Cohen, M. L. & Louie, S. G. Half-metallic graphene nanoribbons. Nature 444, 347–349 (2006). \n3. Novoselov, K. S. et al. Two-dimensional atomic crystals. Proc. Natl Acad. Sci. USA 102, 10451–10453 (2005). \n4. Takamura, T. et al. Identification of nano-sized holes by TEM in the graphene layer of graphite and the high rate discharge capability of Li-ion battery anodes. Electrochim. Acta 53, 1055–1061 (2007). \n5. Schedin, F. et al. Detection of individual gas molecules adsorbed on graphene. Nat. Mater. 6, 652–655 (2007). \n6. Mas-Balleste, R., Gomez-Navarro, C., Gomez-Herrero, J. & Zamora, F. 2D materials: to graphene and beyond. Nanoscale 3, 20–30 (2011). \n7. Sakamoto, J., van Heijst, J., Lukin, O. & Schlu¨ter, A. D. Two-dimensional polymers: just a dream of synthetic chemists? Angew. Chem. Int. Ed. 48, 1030–1069 (2009). \n8. Perepichka, D. F. & Rosei, F. Extending polymer conjugation into the second dimension. Science 323, 216–217 (2009). \n9. Jariwala, D., Srivastava, A. & Ajayan, P. M. Graphene synthesis and band gap opening. J. Nanosci. Nanotechnol. 11, 6621–6641 (2011). \n10. Denis, P. A. Band gap opening of monolayer and bilayer graphene doped with aluminium, silicon, phosphorus, and sulfur. Chem. Phys. Lett. 492, 251–257 (2010). \n11. Martins, T. B. et al. Electronic and transport properties of boron-doped graphene nanoribbons. Phys. Rev. Lett. 98, 196803 (2007). \n12. Wehling, T. O. et al. Molecular doping of graphene. Nano Lett. 8, 173–177 (2007). \n13. Lee, S. U., Belosludov, R. V., Mizuseki, H. & Kawazoe, Y. Designing nanogadgetry for nanoelectronic devices with nitrogen-doped capped carbon nanotubes. Small 5, 1769–1775 (2009). \n14. Wang, X. et al. N-Doping of graphene through electrothermal reactions with ammonia. Science 324, 768–771 (2009). \n15. Qu, L., Liu, Y., Baek, J.-B. & Dai, L. Nitrogen-doped graphene as efficient metalfree electrocatalyst for oxygen reduction in fuel cells. ACS Nano 4, 1321–1326 (2010). \n16. Wang, H. et al. Nitrogen-doped graphene nanosheets with excellent lithium storage properties. J. Mater. Chem. 21, 5430–5434 (2011). \n17. Gutzler, R. & Perepichka, D. F. $\\pi$ -Electron conjugation in two dimensions. J. Am. Chem. Soc. 135, 16585–16594 (2013). \n18. Mahmood, J., Kim, D., Jeon, I.-Y., Lah, M. S. & Baek, J.-B. Scalable synthesis of pure and stable hexaaminobenzene trihydrochloride. Synlett. 24, 246–248 (2013). \n19. Schleyer, P. v. R. Introduction: Aromaticity. Chem. Rev. 101, 1115–1118 (2001). \n20. Guo, J. et al. Conjugated organic framework with three-dimensionally ordered stable structure and delocalized p clouds. Nat. Commun. 4, 2736 (2013). \n21. Kou, Y., Xu, Y., Guo, Z. & Jiang, D. Supercapacitive energy storage and electric power supply using an Aza-fused $\\pi$ -conjugated microporous framework. Angew. Chem. Int. Ed. 50, 8753–8757 (2011). \n22. Jeong, H.-K. et al. Evidence of graphitic AB stacking order of graphite oxides. J. Am. Chem. Soc. 130, 1362–1366 (2008). \n23. Gu, W. et al. Graphene sheets from worm-like exfoliated graphite. J. Mater. Chem. 19, 3367–3369 (2009). \n24. Bao, Q. & Loh, K. P. Graphene photonics, plasmonics, and broadband optoelectronic devices. ACS Nano 6, 3677–3694 (2012). \n25. Liu, S. et al. Solution-phase synthesis and characterization of single-crystalline SnSe nanowires. Angew. Chem., Int. Ed. 50, 12050–12053 (2011). \n26. Perdew, J. P. & Levy, M. Physical content of the exact Kohn-Sham orbital energies: band gaps and derivative discontinuities. Phys. Rev. Lett. 51, 1884–1887 (1983). \n27. Blundell, S. J. & Pratt, F. L. Organic and molecular magnets. J. Phys. Condens. Matter 16, R771 (2004). \n28. Merchant, C. A. et al. DNA translocation through graphene nanopores. Nano Lett. 10, 2915–2921 (2010). \n29. Lu, C.-H., Yang, H.-H., Zhu, C.-L., Chen, X. & Chen, G.-N. A graphene platform for sensing biomolecules. Angew. Chem. Int. Ed. 48, 4785–4787 (2009). \n\n30. Wang, Y., Li, Z., Wang, J., Li, J. & Lin, Y. Graphene and graphene oxide: biofunctionalization and applications in biotechnology. Trends Biotechnol. 29, 205–212 (2011). \n\n# Acknowledgements \n\nThis work was supported by the Creative Research Initiative (CRI), Mid-Career Researcher (MCR), BK21 Plus, Basic Science Research and Basic Research Laboratory (BRL) programs through the National Research Foundation (NRF) of Korea, and the US Air Force Office of Scientific Research (AFOSR). We thank Professor Hu-Young Jung at UNIST for assisting us with the acquisition of TEM images and Professors Konstantin Novoselov of Manchester University and Philip Kim of Harvard University for their thoughtful discussions on this work. \n\n# Author contributions \n\nJ.-B.B. conceived the $\\mathrm{C}_{2}\\mathrm{N}$ -h2D crystal and oversaw all the research phases. J.M. and J.-B.B. designed the experiments and interpreted the data. J.M. conducted the syntheses and characterizations. M.J., S.-D.S. and H.-J.S. conducted the STM studies. E.K.L, S.-Y.B. and J.H.O carried out the FET device study. J.-M.S., H.-J.C. and I.-Y.J conducted the electrochemical study. N.P. and D.S. were involved in the ab initio study of the new material by DFT. S.-M.J., J.-M.S. and H.-J.C. were involved in the TEM experiments. \n\nJ.-B.B., J.M., N.P., J.H.O. and H.-J.S. wrote the paper and discussed the results. All authors contributed to and commented on this manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions. \n\nHow to cite this article: Mahmood, J. et al. Nitrogenated holey two-dimensional structures. Nat. Commun. 6:6486 doi: 10.1038/ncomms7486 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1016_j.cpc.2015.05.011", + "DOI": "10.1016/j.cpc.2015.05.011", + "DOI Link": "http://dx.doi.org/10.1016/j.cpc.2015.05.011", + "Relative Dir Path": "mds/10.1016_j.cpc.2015.05.011", + "Article Title": "Optimization algorithm for the generation of ONCV pseudopotentials", + "Authors": "Schlipf, M; Gygi, F", + "Source Title": "COMPUTER PHYSICS COMMUNICATIONS", + "Abstract": "We present an optimization algorithm to construct pseudopotentials and use it to generate a set of Optimized Norm-Conserving Vanderbilt (ONCV) pseudopotentials for elements up to Z = 83 (Bi) (excluding Lanthanides). We introduce a quality function that assesses the agreement of a pseudopotential calculation with all-electron FLAPW results, and the necessary plane-wave energy cutoff. This quality function allows us to use a Nelder-Mead optimization algorithm on a training set of materials to optimize the input parameters of the pseudopotential construction for most of the periodic table. We control the accuracy of the resulting pseudopotentials on a test set of materials independent of the training set. We find that the automatically constructed pseudopotentials (http://www.quantum-simulation.org) provide a good agreement with the all-electron results obtained using the FLEUR code with a plane-wave energy cutoff of approximately 60 Ry. (C) 2015 The Authors. Published by Elsevier B.V.", + "Times Cited, WoS Core": 897, + "Times Cited, All Databases": 993, + "Publication Year": 2015, + "Research Areas": "Computer Science; Physics", + "UT (Unique WOS ID)": "WOS:000362602900005", + "Markdown": "# Optimization algorithm for the generation of ONCV pseudopotentials \n\nMartin Schlipf ∗, François Gygi \n\nDepartment of Computer Science, University of California Davis, Davis, CA 95616, USA \n\n# a r t i c l e i n f o \n\nArticle history: \nReceived 13 February 2015 \nReceived in revised form \n22 April 2015 \nAccepted 13 May 2015 \nAvailable online 29 May 2015 \nKeywords: \nDensity functional theory \nPseudopotential \nPlane wave \nAll-electron calculation \nCondensed matter \n\n# a b s t r a c t \n\nWe present an optimization algorithm to construct pseudopotentials and use it to generate a set of Optimized Norm-Conserving Vanderbilt (ONCV) pseudopotentials for elements up to $Z=83$ (Bi) (excluding Lanthanides). We introduce a quality function that assesses the agreement of a pseudopotential calculation with all-electron FLAPW results, and the necessary plane-wave energy cutoff. This quality function allows us to use a Nelder–Mead optimization algorithm on a training set of materials to optimize the input parameters of the pseudopotential construction for most of the periodic table. We control the accuracy of the resulting pseudopotentials on a test set of materials independent of the training set. We find that the automatically constructed pseudopotentials (http://www.quantum-simulation.org) provide a good agreement with the all-electron results obtained using the FLEUR code with a plane-wave energy cutoff of approximately $60\\ensuremath{\\mathrm{Ry}}$ . \n\n$\\circledcirc$ 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). \n\n# 1. Introduction \n\nPseudopotentials were introduced over three decades ago as an elegant simplification of electronic structure computations [1]. They allow one to avoid the calculation of electronic states associated with core electrons, and focus instead on valence electrons that most often dominate phenomena of interest, in particular chemical bonding. In the context of Density Functional Theory (DFT), pseudopotentials have made it possible to solve the Kohn–Sham equations [2,3] using a plane-wave basis set, which considerably reduces the complexity of calculations, and allows for the use of efficient Fast Fourier Transform (FFT) algorithms. The introduction of norm-conserving pseudopotentials (NCPPs) by Hamann et al. in 1979 [4,5] greatly improved the accuracy of DFT plane wave calculations by imposing a constraint (norm conservation) in the construction of the potentials, thus improving the transferability of potentials to different chemical environments. More elaborate representations of pseudopotentials were later proposed, most notably ultrasoft pseudopotentials [6] (USPPs) and the projector augmented wave [7] (PAW) method, improving computational efficiency by reducing the required plane wave energy cutoff. The implementation of these PPs is however more complex than NCPPs [8]. In particular for advanced calculations involving hybrid density functionals [9], many-body perturbation theory [10], or density-functional perturbation theory [11] terms treating the additional on-site contributions have to be developed [12]. Both USPPs and PAWs have been used with great success in a large number of computational studies published over the past two decades. NCPPs were also widely used but suffered from the need to use a large plane wave basis set for some elements, especially transition metals. \n\nRecently, Hamann suggested [8] a method to construct optimized norm-conserving Vanderbilt (ONCV) potentials following the USPP construction algorithm without forfeiting the normconservation. The resulting potentials have an accuracy comparable to the USPPs at a moderately increased plane-wave energy cutoff. \n\nSince the very first pseudopotentials were introduced, there has been an interest in a database of transferable, reference potentials that could be applied for many elements in the periodic table [5,13,14]. The need for a systematic database in high-throughput calculations led to a recent revival of this field: Garrity et al. [15] proposed a new set of USPPs for the whole periodic table except the noble gases and the rare earths. Dal Corso [16] constructed a high- and a low-accuracy PAW set for all elements up to Pu. Common to these approaches is the fact that the input parameters of the PP construction are selected by experience based on the results of the all-electron (AE) calculation of the bare atom. The quality of the constructed PP is then tested by an evaluation of different crystal structures and by comparing to the all-electron FLAPW [17–19] results. To standardize the testing procedure, Lejaeghere et al. [20] suggested to compare the area between a Murnaghan fit [21] obtained with the PP and the AE calculation resulting in a quality factor $\\varDelta$ . Küçükbenli et al. [22] proposed a crystalline monoatomic solid test, where this quality factor is evaluated for the simple cubic (sc), body-centered cubic (bcc), and face-centered cubic (fcc) \n\nstructure to assess the quality of a PP. There are two improvements over these construction principles that we propose to address in this work. First, we introduce a quality function that takes into account the computational efficiency of the PP as well as its accuracy. Second, we allow for a systematic feedback of this quality function onto the input parameters defining the PP. In this way, we can introduce an automatic construction algorithm that optimizes the properties of the PP without bias from the constructor. We apply this algorithm to construct ONCV pseudopotentials and compare their performance with recent USPP [15] and PAW [16] PP libraries. The pseudopotentials are available in UPF and XML format on our webpage [23]. \n\nThis paper is organized as follows: In Section 2, we outline the properties of the ONCV PPs and introduce the input parameters that will be optimized by the algorithm. In Section 3, we introduce the quality function to assess the performance of a PP, specify the materials we use to construct and test a PP, outline the setting of the DFT calculation, and finally present the optimization algorithm that iterates construction and testing until a good PP is found. We compare the constructed PPs to results obtained with the FLAPW, the USPP, and the PAW method in Section 4 and draw our conclusions in Section 5. \n\n# 2. ONCV pseudopotentials \n\nThe optimized norm-conserving Vanderbilt (ONCV) pseudopotentials were recently proposed by Hamann [8]. Here, we briefly sketch their construction, following Hamann, to highlight the input parameters (bold in text) that determine the properties of the PP. The general idea is to introduce an upper limit wave vector $q_{\\mathrm{c}}$ and optimize the pseudo wave functions $\\varphi_{i}(\\boldsymbol{r})$ such that the residual kinetic energy \n\n$$\nE_{i j}(q_{\\mathrm{c}})=\\int_{q_{\\mathrm{c}}}^{\\infty}\\mathrm{d}q q^{4}\\varphi_{i}(q)\\varphi_{j}(q)\n$$ \n\nabove this cutoff is minimized. Here, $\\varphi_{i}(q)$ is the Fourier transform of the pseudo wave function \n\n$$\n\\varphi_{i}(q)=4\\pi\\int_{0}^{\\infty}\\mathrm{d}r r^{2}\\mathbf{j}_{l}(q r)\\varphi_{i}(r),\n$$ \n\n${\\bf j}_{l}(q r)$ a spherical Bessel function, and $l$ the angular momentum of the pseudo wave function. On the one hand, the cutoff $q_{\\mathrm{c}}$ determines which features of the physical potential can be described by the PP. On the other hand, increasing $q_{\\mathrm{c}}$ makes the PP harder and hence more costly to evaluate. \n\nFor every angular momentum, a projector radius $r_{\\mathrm{c}}$ determines in which region the pseudoization is done. The projector radius is approximately inversely proportional to the cutoff $q_{\\mathrm{c}}$ so that a smaller value increases the computational cost along with the accuracy. Outside of this radius the wave function should follow the true all-electron wave function $\\psi$ . To ensure the continuity at this radius, one imposes $M$ constraints on the continuity of the pseudo wave function \n\n$$\n\\left.{\\frac{\\mathrm{d}^{n}\\varphi}{\\mathrm{d}r^{n}}}\\right|_{r_{\\mathrm{{c}}}}=\\left.{\\frac{\\mathrm{d}^{n}\\psi}{\\mathrm{d}r^{n}}}\\right|_{r_{\\mathrm{{c}}}},\n$$ \n\nfor $n=0,\\ldots,M-1.$ In this work, we use $M=5$ for all constructed PPs. \n\nThe basis set used in the optimization is constructed from spherical Bessel functions. As the basis functions are only used inside the sphere, they are set to zero outside of the projector radius. This destroys the orthogonality of the basis, so that one needs to orthogonalize it again. A linear combination of the orthogonalized basis functions yields a new basis where a single basis function $\\varphi_{0}$ satisfies the constraints in Eq. (3) and for all other basis functions $\\xi_{n}^{\\mathrm{N}}$ the value and the $M-1$ derivatives at $r_{\\mathrm{c}}$ are zero. As a consequence, the sum of $\\varphi_{0}$ and any linear combination of the $\\xi_{n}^{\\mathrm{N}}$ will satisfy the constraints in Eq. (3). It is advantageous to select those linear combinations of $\\dot{\\xi}_{n}^{\\mathrm{N}}$ that have a maximal impact on the residual energy by evaluating the eigenvalues $\\boldsymbol{e}_{n}$ and eigenvectors $\\xi_{n}^{\\tt R}$ \n\n$$\n\\varphi_{i}=\\varphi_{0}+\\sum_{n=1}^{N-M}x_{n}\\xi_{n}^{\\mathrm{R}}.\n$$ \n\nIn this work, we construct the PPs with $N=8$ basis functions. Notice that the optimization of the pseudo wave function is performed under the constraint that the norm of the all-electron wave function is conserved \n\n$$\n\\int_{0}^{r_{\\mathrm{c}}}\\mathrm{d}r r^{2}\\big[\\varphi_{i}^{\\ast}(r)\\varphi_{j}(r)-\\psi_{i}^{\\ast}(r)\\psi_{j}(r)\\big]=0.\n$$ \n\nFrom the obtained pseudo wave functions, one can construct projectors $\\chi_{i}$ \n\n$$\n\\chi_{i}(\\boldsymbol{r})=(\\varepsilon_{i}-T-V_{\\mathrm{loc}})\\phi_{i}(\\boldsymbol{r}),\n$$ \n\nwhere $T$ is the kinetic energy operator. $V_{\\mathrm{loc}}$ is the local potential that follows the all-electron potential outside of $r_{\\mathrm{c}}$ and is extended smoothly to the origin by a polynomial. For occupied states $\\varepsilon_{i}$ is the eigenvalue of the all-electron calculation. For unoccupied states, one needs to specify this energy shift before the construction of the PP. Following Ref. [8], we construct two projectors per angular momentum $l\\leq{l_{\\mathrm{max}}}$ and only the local potential for all $l>{l_{\\mathrm{{max}}}}$ above. The projectors define the following nonlocal potential \n\n$$\nV_{\\mathrm{NL}}=\\sum_{i j}\\bigl|\\chi_{i}\\bigr\\rangle B_{i j}^{-1}\\bigl\\langle\\chi_{j}\\bigr|\n$$ \n\nwhere \n\n$$\nB_{i j}=\\bigl\\langle\\varphi_{i}\\bigl|\\chi_{j}\\bigr\\rangle,\n$$ \n\nwhich is a Hermitian matrix when normconserving pseudo wave functions are constructed [6]. One can simplify this potential by a unitary transformation to the eigenspace of the $B$ matrix. \n\n# 3. Computational details \n\n# 3.1. Quality function \n\nIn order to employ numerical optimization algorithms in the construction of PPs, we need a function that maps the multidimensional input parameter space onto a single number, the quality of the PP. A good PP is characterized by a small relative deviation \n\n$$\n\\delta_{a_{\\mathrm{lat}}}^{\\mathrm{PP}}=a_{\\mathrm{lat}}^{\\mathrm{PP}}/a_{\\mathrm{lat}}^{\\mathrm{AE}}-1\n$$ \n\nbetween the lattice constant obtained in the plane-wave PP calculation $a_{\\mathrm{lat}}^{\\mathsf{P P}}$ and in the AE calculation $a_{\\mathrm{lat}}^{\\mathrm{AE}}$ , respectively. A second criterion is the plane-wave energy cutoff $E_{\\mathrm{cut}}$ necessary to converge the PP calculation. These two criteria compete with each other because the pseudoization of the potential reduces the necessary energy cutoff at the cost of a lower accuracy near the nucleus. Hence, we need to specify a target accuracy $\\delta_{0}$ which we want to achieve for our PPs, i.e., for all materials $\\big|\\delta_{a_{\\mathrm{lat}}}^{\\mathrm{PP}}\\big|\\leq\\delta_{0}$ . We select $\\delta_{0}=0.2\\%$ motivated by the fact that the choice of different codes or input parameters in the all-electron calculation may already lead to a relative error of approximately $0.1\\%$ . To discriminate between PPs within the target accuracy, we include a term $\\propto1/E_{\\mathrm{cut}}$ in the quality function, favoring smoother PPs over hard ones. For PPs that are significantly outside $\\left\\vert\\delta_{a_{\\mathrm{lat}}}^{\\mathrm{PP}}\\right\\vert>2\\delta_{0}$ our target accuracy, we only focus on optimizing the relative deviation by an $1/(\\delta_{a_{\\mathrm{lat}}}^{\\mathrm{PP}})^{2}$ term. We choose a smooth continuation between the two regions, resulting in the function depicted in Fig. 1. The quality function has the following form \n\n![](images/fb26180ad8b3cb3a5c75984110e4df56de4c4d07b5269ba601d848947e72c679.jpg) \nFig. 1. (Color online) Quality function for various energy-cutoffs $E_{\\mathrm{cut}}$ . For small $\\delta$ , it is proportional to $1/E_{\\mathrm{cut}}$ ; for large $\\delta$ proportional to $1/\\delta^{2}$ and independent of $E_{\\mathrm{cut}}$ . \n\n$$\nq(\\delta,E_{\\mathrm{cut}})=\\left\\{\\begin{array}{l l}{A+C\\delta^{2}+D\\delta^{3}+E\\delta^{4}+F\\delta^{5}}&{\\delta<2\\delta_{0}}\\\\ {(2\\delta_{0}/\\delta)^{2}}&{\\delta\\geq2\\delta_{0}}\\end{array}\\right.\n$$ \n\nwith \n\n$$\n\\begin{array}{r l}&{A=1+\\cfrac{1280}{E_{\\mathrm{cut}}}\\quad y_{0}=1+\\cfrac{680}{E_{\\mathrm{cut}}}}\\\\ &{C=\\cfrac{32y_{0}-16A-29}{4\\delta_{0}^{3}}\\quad D=\\cfrac{19A-48y_{0}+54}{4\\delta_{0}^{2}}}\\\\ &{E=\\cfrac{96y_{0}-33A-122}{16\\delta_{0}^{4}}\\quad F=\\cfrac{5A-16y_{0}+22}{16\\delta_{0}^{5}}.}\\end{array}\n$$ \n\nThe function can be multiplied by an arbitrary scaling constant, which we set such that the value of the quality function is 1 at $\\left\\lvert\\delta_{a_{\\mathrm{lat}}}^{\\mathrm{PP}}\\right\\rvert=2\\delta_{0}$ . \n\n# 3.2. Sets of materials \n\nAs the constructed pseudopotentials depend on the set of materials used in the optimization algorithm, it is important that the set contain physically relevant environments of the atom. Furthermore, we select highly symmetric structures with at most two atoms per unit cell to reduce the computation time. As representatives of a metallic environment, we select the simple cubic (sc), the body-centered cubic (bcc), the face-centered cubic (fcc), and the diamond-cubic (dc) structure. Ionic environments are provided in a rock-salt or zinc-blende structure, where we combine elements such that they assume their most common oxidation state. This leads to a combination of elements from the lithium group with the fluorine group, the beryllium group with the oxygen group, and so on. We always use the three smallest elements of the respective groups to guarantee a variation in size of the resulting compounds. For the transition metals, several oxidation states are often possible. Hence, we combine them with carbon, nitrogen, and oxygen to test these different valencies. As the noble gases do not form compounds, we test them only in the sc, bcc, fcc, and dc structure. \n\nFinally, we need to separate these materials into two sets. The training set consists of the bcc, and the fcc structure as well as all rock-salt compounds. It is used in the optimization algorithm to construct the PPs. As the PPs are specifically optimized to reproduce the structural properties of the training set, we can only judge if the PPs are highly accurate by calculating an independent test set. The test set contains the sc and the dc structure as well as all zinc-blende compounds. In total, the training and test sets consist of 602 materials, where every noble-gas atom is part of four materials, and every other element is part of at least ten materials. \n\n# 3.3. Computational setup \n\nAll pseudopotentials are constructed using the Perdew–Burke– Ernzerhof (PBE) generalized gradient density functional [24]. We use an $8\\times8\\times8$ Monkhorst–Pack $\\pmb{k}$ -point mesh in the AE as well as in the PP calculation. While this may not be sufficient to completely converge the lattice constant with respect to the numbers of $\\pmb{k}$ -points, the errors in the PP and the AE calculation are expected to be the same, so that we can still compare the results. To ensure that metallic systems converge, we use a Fermi-type smearing with a temperature of 315.8 K corresponding to an energy of 0.001 htr. \n\nFor the AE calculation, we use the FLAPW method as implemented in the Fleur code [25]. We converge the plane-wave cutoff and add unoccupied local orbitals to provide sufficient variational freedom inside the muffin-tin spheres. The precise numerical values necessary to converge the calculation are different for every material; all input files can be obtained from our web page [23]. We obtain the lattice constant by a Murnaghan fit [21] through 11 data points surrounding the minimum of the total energy. We converge the AE lattice constant such that the relative error is at most $0.1\\%$ . There are methodological limitations of the FLAPW method that make a higher accuracy difficult to obtain for some elements: (i) On the one hand, only core states are treated fully relativistically. On the other hand, the non-spherical parts of the potential are only taken into account for valence states. (ii) Because the plane-waves only exist in the interstitial region, the maximum number of basis functions is limited to avoid linear dependence of the basis set. (iii) The additional basis functions in the muffin-tin spheres must be linearly independent, limiting the minimal energy parameter for these functions. \n\nThe automatic construction of pseudopotentials requires every material to be calculated several hundred times. Hence, we approximate the Murnaghan equation of state by a parabola that we fit through data points at the AE lattice constant and a $1\\%$ enlarged or reduced value. We test the constructed PPs with the Quantum ESPRESSO [26] plane-wave DFT code. Our test consists of a calculation with a large energy cutoff of $E_{\\mathrm{cut}}^{\\mathrm{max}}=160\\:\\mathrm{Ry}$ that we consider to be the converged solution. Then, we decrease the cutoff in steps of $\\varDelta E=10$ Ry to the minimum of 40 Ry. Notice that as illustrated by Fig. 2, the actual deviation compared to the AE calculation may decrease even though we reduced the accuracy of the calculation. To correct for this, we adjust the deviation such that it is monotonically decreasing using the following correction \n\n$$\n\\delta_{\\mathrm{corr}}^{\\mathrm{PP}}(E_{\\mathrm{cut}}^{i})=|\\delta^{\\mathrm{PP}}(E_{\\mathrm{cut}}^{\\mathrm{max}})|+\\sum_{k=1}^{i}|\\delta^{\\mathrm{PP}}(E_{\\mathrm{cut}}^{k})-\\delta^{\\mathrm{PP}}(E_{\\mathrm{cut}}^{k-1})|\n$$ \n\nwhere Ei $E_{\\mathrm{cut}}^{i}~=~E_{\\mathrm{cut}}^{\\mathrm{max}}-10i$ . This ensures that the deviation at a given cutoff energy is an upper bound to the deviation at any larger cutoff. \n\n# 3.4. Optimizing pseudopotentials \n\nWe use a Nelder–Mead algorithm [27] also known as the Downhill Simplex Method [28] to optimize the PPs. In this algorithm, the $N$ input parameters of a specific PP are represented by a point in a $N$ -dimensional space. We start with $(N+1)$ PPs that form a simplex in this space. By replacing the worst corner by a better PP the simplex contracts towards the optimal PP. As convergence criteria, we visually inspect the change of quality of the PP. In addition, we require that the input parameters of the PP are converged to at least two significant digits. The advantages of the Nelder–Mead algorithm are that we do not need to know the derivatives of the quality function with respect to the input parameters and that it can find PP parameters that lie outside of the starting simplex. \n\n![](images/0c0629209db273934fdd7ed4036ffb3b006c3fb28b199c73e3acc669ab64f5eb.jpg) \nFig. 2. (Color online) Relative deviation δ of a PP w.r.t. the AE calculation. The blue circles indicate the deviation obtained at a certain energy cutoff $E_{\\mathrm{cut}}$ . The red diamonds show the corrected deviation that is monotonically decreasing with increasing cutoff (see text). \n\nTo create the initial simplex, we start from a reasonable starting guess for the $N$ input parameters to construct a PP for the neutral atom. We used the example input files provided with the ONCVPSP package [8], where available, or generated our own PP otherwise. States that could be considered as semicore states are included in the valence window. A detailed list for the individual elements is given in the supplementary material [29]. We construct $(N+1)$ PPs based on the starting-guess PP with random modifications to the input parameters. We allow changes of up to $20\\%$ of any of the input parameters, but control that the necessary conditions (e.g. projector radius $\\geq$ radius of local potential) are always fulfilled. \n\nWe assess the quality for each of the initial PPs and each of the PPs that are created during the optimization procedure in the following fashion: (i) The PP is rejected if it cannot be created by the ONCVPSP code or if it exhibits ghost states in the vicinity of the Fermi energy. The latter is evidenced by changes in the logarithmic derivative as compared to the AE result. (ii) If the PP is not rejected, we evaluate the quality function on the training set of materials. (iii) We compute the geometric mean of all the materials the tested PP is used in. \n\nIn the case of the rock-salt compounds, we test always only one of the PP and for the other element we use a PP from the GBRV database [15]. After 80–200 iterations of the Nelder–Mead algorithm, all PPs have converged. Then, we restart the algorithm using these first generation PP as starting guess. Now, we employ the first generation PPs in the compounds so that our resulting PPs become independent of the GBRV database. Once the second generation is converged as well (another 100 iterations), the properties of the training set are well reproduced for almost all materials. \n\n# 3.5. Refining the training set \n\nFor a few materials, the second generation PPs do not reproduce the AE results on the test set of materials. Our proposed optimization algorithm provides an easy solution to overcome these cases by adding additional materials to the training set. In particular, for the early transition metals (Sc–Mn) it is necessary to include the sc structure in the training set. Furthermore, we include the dimer of hydrogen and nitrogen into the test set, because the second generation PPs for these two elements do not describe the bond length of the dimer accurately. \n\nTable 1 Comparison of the performance of the USPPs in the GBRV database [15] and the high-accuracy PAWs in PSLIB [16] with the ONCV PPs in the SG15 database (this work) for materials in a bcc structure. We analyze the relative deviation of the lattice constant $\\delta_{a_{\\mathrm{lat}}}$ and the bulk modulus $\\delta_{B_{0}}$ between a PP and the AE calculation. The average reveals if the $\\mathsf{P P s}$ have a systematic bias and the root-mean-square (rms) average tests the size of the error. We also show the proportion of materials that are not accurately described at various energy cutoffs. \n\n\n
GBRVPSLIBSG15
Average Salat (%)0.030.030.04
rms average Salat (%)0.120.110.08
% of materials with |alat| > 0.2%110.9440.0023.19
% of materials with |Slat> 0.2%29.3815.568.70
% of materials with |8alat I > 0.2%39.384.442.90
Average 8Bg (%)0.36-0.320.52
rms average SBg (%)3.312.533.19
% of materials with |8B| > 5.0%125.0062.2253.62
% of materials with |8Bol > 5.0%214.0626.6718.84
% of materials with |8Bol > 5.0%39.388.897.25
Total number of materials644569
\n\n1 With an energy cutoff of 40Ry. 2 With an energy cutoff of 60Ry. 3 With an energy cutoff of 160Ry. \n\nWe emphasize that our optimization algorithm could account for other material properties. As long as one is able to define a quality function, which maps the result of a PP potential calculation onto a number, it is possible to optimize the input parameters of the PP generation by standard numerical optimization techniques. \n\n# 4. Results \n\nWe compare the performance of the ONCV PPs constructed in this work (SG15) [23] with the USPPs in the GBRV database [15] and the high-accuracy PAWs in the PSLIB [16]. For the latter, we generate the potentials of PSLIB version 1.0.0 with Quantum ESPRESSO version 5.1.1. When we state that a certain pseudoization has a particular convergence behavior, we refer to the properties of the PPs in these libraries. \n\nIn the first subsection, we focus on the lattice constants and bulk moduli of the materials in the training set. In the second subsection, we investigate the materials in the test set. In the third subsection, we look into materials that are not represented in the test set to check the accuracy of the pseudopotentials. In the first two subsections, we focus only on the trends across all materials in the training and test set, respectively. For the results for a specific compound, please refer to the supplementary material [29]. \n\n# 4.1. Training set \n\nIn Table 1, we present the results obtained for the materials in a bcc structure. We see that the USPPs require the smallest energy cutoff and have the best performance at 40 Ry. On the other hand increasing the energy cutoff beyond $40~\\mathrm{Ry}$ hardly improves the results. For the PAWs and the ONCV PPs, a large number of materials are not converged at $40~\\mathrm{Ry}$ , but increasing the energy cutoff improves the accuracy, so that they are able to improve on the USPP results. For the converged calculation, the root-meansquare (rms) error is around $0.1\\%$ for all PPs and smallest for the ONCV PPs. We see a similar trend for the bulk moduli though the converged results require a larger energy cutoff on average. The average error for the converged bulk moduli is roughly $3\\%$ and the USPPs converge with a lower energy cutoff than the PAWs and the ONCV PPs, which have a similar convergence behavior. In Fig. 3, we see that the converged lattice constant deviates by more than $0.2\\%$ with the ONCV PPs only for two materials (carbon and calcium). \n\n![](images/666304cfb3134c57676e9fac0551225f4b2203e969ca1244c39d866a7787bb71.jpg) \nFig. 3. (Color online) Relative change $\\delta(\\%)$ of the lattice constant in the training set for the SG15 (red circle), the GBRV (green square), and the PSLIB (blue diamond) results as compared to the FLAPW ones for the bcc (top left), fcc (top right) and rock-salt compounds (bottom). \n\nTable 2 Same as Table 1 for fcc structures. \n\n\n
GBRVPSLIBSG15
Average Salat (%)0.030.030.03
rms average Saat (%)0.110.070.07
% of materials with |Salat I > 0.2%19.3827.0824.64
% of materials with (Salat! > 0.2%29.386.255.80
% of materials with |Salat l > 0.2%39.380.001.45
Average 8Bg (%)0.230.000.31
rms average 8Bg (%)2.281.832.00
% of materials with |8Bg| > 5.0%112.5068.7543.48
% of materials with |8Bg| > 5.0%27.8116.6717.39
% of materials with |8Bg| > 5.0%33.124.175.80
Total number of materials644869
\n\n1 With an energy cutoff of 40Ry. 2 With an energy cutoff of 60Ry. 3 With an energy cutoff of 160Ry. \n\nFor both of these materials the USPP and the PAW approach show large deviations as well. \n\nThe fcc structures presented in Table 2 follow the same trend as the bcc structures. The USPPs require the smallest energy cutoff but cannot be improved further by increasing the energy cutoff. The PAWs and the ONCV PPs require an energy cutoff of $60~\\mathrm{Ry}$ to converge most materials, but have fewer inaccurate elements when increasing the energy cutoff. Overall the ONCV PPs and the PAWs are a bit better than the USPPs, but all PPs are close to the AE results. In Fig. 3, we see that only a single material (cadmium) is outside the $0.2\\%$ boundary, when using the converged calculation and the ONCV PPs. The USPP result shows a deviation of similar size for this material, whereas the PAW lattice constant is close to the FLAPW result. \n\nWhen combining two materials to form rock-salt compounds, we obtain the results depicted in Table 3. In comparison to the metallic (bcc and fcc) system, the accuracy for the ionic compounds is a bit higher in particular for the bulk modulus. With a large energy cutoff the ONCV PPs essentially reproduce the AE results and the accuracy at $60~\\mathrm{Ry}$ for the lattice constant is very good. For the bulk modulus, about $10\\%$ of the materials require a larger energy cutoff. The USPPs have a slightly larger mismatch for the lattice constants, but converge both lattice constants and bulk moduli with 40 Ry. The PAW potentials provide a similar convergence behavior as the ONCV potentials; they deviate a bit more for the lattice constants, but provide slightly better bulk moduli. \n\nIn Fig. 4, we show a histogram of the relative error of the lattice constant for all the examined PPs (with the converged cutoff of \n\nTable 3 Same as Table 1 for rocksalt structures. \n\n\n
GBRV PSLIBSG15
Average Salat (%)0.010.02-0.02
rms average 8alat (%)0.110.090.06
% of materials with |Salat| > 0.2%16.1335.9530.67
% of materials with (Salat l > 0.2%26.136.541.23
% of materials with |alat| > 0.2%36.133.920.00
Average 8Bo (%)-0.02-0.03-0.48
rms average 8Bg (%)1.671.291.34
% of materials with |8Bg| > 5.0%11.8453.5955.83
% of materials with |8Bo| > 5.0%21.845.2310.43
% of materials with |8Bol > 5.0%31.840.000.61
Total number of materials163153163
\n\n1 With an energy cutoff of 40Ry. 2 With an energy cutoff of 60Ry. 3 With an energy cutoff of 160Ry. \n\n![](images/5f4f01ecde9f1691283056ca86b453bde5efbc0fe303fd22dcc9787264ba3768.jpg) \nFig. 4. (Color online) Histogram of the relative error of the lattice constant compared to the all-electron result. We show the results for all materials in the training set for the SG15 (red solid line), the GBRV (green dotted line), and the PSLIB (blue dashed line) calculations. \n\n$160~\\mathrm{Ry}$ ). The histogram confirms the conclusions we drew from Table 1 to 3: All PPs show a very good agreement with the allelectron results and the USPPs have a slightly lower accuracy. The tails with large errors are very flat indicating that there are only a few outliers. \n\n# 4.2. Test set \n\nIn the sc structure (see Table 4), the performance of the ONCV potentials is comparable to the training set for the lattice constants and slightly worse for the bulk moduli. We observe the same trend also for the USPP and the PAW calculations. With an overall deviation of about $0.1\\%$ for the lattice constant and $4\\%$ for the bulk moduli, all PPs show a good agreement with the AE reference data. The convergence with respect to the energy cutoff is best in the GBRV database, which does not change significantly for the lattice constants above 40 Ry. Most of the ONCV lattice constants converge at 60 Ry whereas the PAW ones occasionally need a larger cutoff. For the bulk moduli, all PPs show a similar convergence behavior. However, we observe that as compared to the other structures a larger fraction of $>~10\\%$ is not accurate even with an energy cutoff of $160~\\mathrm{Ry}$ . In Fig. 5, we see that the ONCV PPs reproduce the lattice constant within the $0.2\\%$ boundary for all materials except calcium and lanthanum. While the ONCV PP gives similar results to the other PPs for calcium, we find that the lattice constant in lanthanum is underestimated by the ONCV PP and overestimated by the USPP. For this material, the PAW calculation did not converge. \n\nTable 4 Same as Table 1 for sc structures. \n\n\n
GBRV PSLIBSG15
Average Salat (%)0.020.030.02
rms average Salat (%)0.120.090.09
% of materials with |Salat| > 0.2%16.2546.3027.54
% of materials with |8at > 0.2%26.2516.675.80
% of materials with |SalatI > 0.2%36.253.702.90
Average B (%)0.320.31-0.01
rms average SBg (%)3.793.964.47
% of materials with |8Bol > 5.0%140.6274.0762.32
% of materials with |8Bol > 5.0%220.3127.7821.74
% of materials with |8Bl > 5.0%312.5012.9611.59
Total number of materials645469
\n\n1 With an energy cutoff of 40Ry. 2 With an energy cutoff of 60Ry. 3 With an energy cutoff of 160Ry. \n\nTable 5 Same as Table 1 for diamond structures. \n\n\n
GBRVPSLIBSG15
Average Salat (%) 0.030.020.01
rms average Salat (%) 0.160.100.12
% of materials with |Salat | > 0.2%1 7.8149.1234.78
% of materials with |SalatI > 0.2%2 7.8122.8111.59
% of materials with |Salat I > 0.2%3 7.817.028.70
Average SB (%) 0.451.30-0.24
rms average SBg (%) 4.496.543.06
% of materials with |8Bo| > 5.0%1 31.2571.9353.62
% of materials with |8Bol > 5.0%2 18.7531.5814.49
% of materials with |8Bo| > 5.0%3 9.387.027.25
Total number of materials 645769
\n\n1 With an energy cutoff of 40Ry. 2 With an energy cutoff of 60Ry. 3 With an energy cutoff of 160Ry. \n\nIn Table 5, we present our results for the materials in the diamond structure. These are the structures which exhibit overall the largest deviation from the all-electron result. The lattice constants of the USPPs are converged well with the energy cutoff of $40\\ \\mathrm{Ry}$ , whereas the PAWs and the ONCV PPs frequently require a cutoff of $60~\\mathrm{Ry}$ . For the bulk moduli, we find that the ONCV PPs provide the best agreement with the AE results. The quality of the USPPs is similar, but the PAW potentials show an average error larger than the desired $5\\%$ tolerance. However the fraction of materials that are well described with the PP calculation is similar for all methods. This indicates that a few specific materials show a particular large deviation, whereas the rest is accurately described. For the ONCV PPs the lattice constants of boron, chlorine, scandium, nickel, rubidium, and yttrium deviate by more than $0.2\\%$ from the FLAPW results. In Fig. 5, we observe that the deviations between the different pseudoizations are larger than for the other structures. A possible explanation is that the diamond structure is an extreme case for many materials, because of its low space filling. For the zincblende compounds (cf. Table 6), we observe results similar to for the rock-salt compounds. We find that the USPPs converge for most materials with an energy cutoff of $40\\ensuremath{\\mathrm{Ry}}$ , whereas a third of the materials with the ONCV PPs and half of the materials with the PAWs need an energy cutoff of 60 Ry to converge. Overall the accuracy of the ONCV PPs is slightly better than the alternatives, but all pseudoizations are on average well below the target of $0.2\\%$ . For the bulk moduli a larger energy cutoff is necessary, but when converged the deviation from the AE results is around $1\\%$ . In Fig. 5, we identify that only for BeO the deviation between the ONCV calculation and the AE result is larger than $0.2\\%$ . \n\nIn Fig. 6, the histogram of the relative error of the lattice constant for the test set confirms the conclusions we drew from Table 4 to 6: The deviation from the all electron results is very small for all PPs. The USPPs show a slightly larger deviation than the PAWs and the ONCV PPs. The histogram reveals that this is partly due to some outliers, for which the lattice constant is overestimated by more than $0.4\\%$ . Overall, we notice that the accuracy of the ONCV PPs for the test set of materials is not significantly worse than for the training set. Hence, we are confident that these PPs are transferable to other materials as well. \n\n![](images/b5ad6af8c4ac8439906542f10f9efeded7c17e0c7836c1abe4a0244e2a54fd02.jpg) \nFig. 5. (Color online) Relative change $\\delta(\\%)$ of the lattice constant in the test set for the SG15 (red circle), the GBRV (green square), and the PSLIB (blue diamond) results as compared to the FLAPW ones for the sc (top left), diamond (top right) and zincblende compounds (bottom). \n\n![](images/27a3b9856291b0db4d90ddf65a5c8a109f44d221e734e31de186bf90ddd847df.jpg) \nFig. 6. (Color online) Histogram of the relative error of the lattice constant compared to the all-electron result. We show the results for all materials in the test set for the SG15 (red solid line), the GBRV (green dotted line), and the PSLIB (blue dashed line) calculations. \n\nTable 6 Same as Table 1 for zincblende structures. \n\n\n
GBRVPSLIBSG15
Average Salat (%) 0.040.040.00
rms average Salat (%) 0.100.090.07
% of materials with |Salat I > 0.2%1 5.5237.5033.74
% of materials with |SatI > 0.2%2 4.916.582.45
% of materials with |Salat| > 0.2%3 3.073.290.61
Average SB (%) 0.240.14-0.27
rms average SBg (%) 1.260.961.03
% of materials with |8Bo| > 5.0%1 4.2955.2655.21
% of materials with |8Bol > 5.0%2 1.844.619.20
% of materials with |8Bg| > 5.0%3 0.610.000.00
Total number of materials 163152163
\n\n1 With an energy cutoff of 40Ry. 2 With an energy cutoff of 60Ry. 3 With an energy cutoff of 160Ry. \n\n# 4.3. Dimers and ternary compounds \n\nOur training and test set are limited to mono- and diatomic crystals, hence one may wonder if the constructed ONCV PPs work outside this scope. To test this we investigated diatomic molecules and ternary compounds. For the compounds, we use the same computational setup as for the materials in the training and in the test set. For the molecules, we optimize the bond length inside a box with dimensions $15\\mathring{\\mathsf{A}}\\times15\\mathring{\\mathsf{A}}\\times30\\mathring{\\mathsf{A}}$ with the long side parallel to the axis of the molecule. \n\nIn Table 7, we show the bond lengths and the lattice constants of the investigated materials. Depending on the pseudoization, some diatomic molecules show large deviations from the reference data from the CCCB DataBase [30]. Overall, the ONCV PPs exhibit the smallest deviations. The relative error is larger than $0.2\\%$ only for the $0_{2}$ $(0.25\\%)$ and the $\\mathsf{F}_{2}$ $(0.35\\%)$ dimer. For the USPPs, all diatomic molecules are outside of the desired relative accuracy of $0.2\\%$ , except for the $\\mathsf{B r}_{2}$ dimer. In PAW, the only molecule with the desired accuracy is the $\\mathrm{H}_{2}$ dimer. The other molecules show deviations of similar magnitude to the USPPs and the $\\mathsf{B r}_{2}$ dimer did not converge. \n\nPerovskites are accurately described by all pseudoizations; we frequently find a relative agreement of better than $0.1\\%$ in the lattice constant with the FLAPW result. The worst case for the ONCV PPs is $\\mathsf{L a A l O}_{3}$ , which deviates by $-0.13\\%$ . The USPPs and the PAWs both overestimate the lattice constant of ${\\tt B a T i O}_{3}$ by $0.25\\%$ and $0.27\\%$ , respectively. The PAW potentials also feature a larger deviation than the other two pseudoizations for $\\mathrm{SrTiO}_{3}$ . \n\nFinally, we consider the half-Heusler compounds. All materials are within the desired accuracy with all pseudoizations. The ONCV PPs show slightly larger deviations than the USPPs and the PAWs for GeAlCu and NMgLi. For NiScSb, the ONCV PPs and PAWs overestimate the lattice constant more than the USPPs. The lattice constant of BScSb and PdZrSn are essentially the same with FLAPW and in any pseudoization used. In PZNa, all PPs produce very similar results and a slightly larger lattice constant than the FLAPW result. \n\n# 5. Conclusion \n\nWe have presented an algorithm to optimize the input parameters of a pseudopotential (PP) construction. We demonstrated it by developing the SG15 dataset [23] of ONCV pseudopotentials, which exhibits a similar accuracy as the ultrasoft PP database GBRV [15] and the PAW library PSLIB [16]. The idea of the algorithm is to map a PP onto a single numeric value so that standard optimization techniques can be employed. For this, we developed a quality function that considers the accuracy of the lattice constant of a PP calculation and compares it with a high accuracy FLAPW one. In addition, the quality function takes into account the energy cutoff necessary to converge the calculation. Hence, the optimization of the PPs with respect to the quality function yields accurate and efficient potentials. In order to ensure that the constructed PPs are of a high accuracy, we systematically chose a set of approximately 600 materials and evaluate their properties with FLAPW. We split this set in two parts, a training set used for the optimization of the PPs and a test set to analyze the performance of the PPs. When a PP does not produce our desired accuracy after optimizing on the training set, we can improve the quality of this PP by extending the training set by more materials. \n\nIn Table 8, we collect the results of all materials in test and training set. Compared to the PPs from the GBRV database [15] and PSLIB [16], the PPs in the SG15 set have the lowest rootmean-square deviation from the FLAPW results for the lattice constant. With an energy cutoff of $60~\\mathrm{Ry}$ , the ONCV PPs feature the least number of materials with an inaccurate lattice constant (deviation larger than $0.2\\%$ from FLAPW results). The advantage of the ultrasoft PPs is that they offer a similar accuracy with an energy cutoff of 40 Ry. For the bulk moduli larger energy cutoffs are necessary for all pseudoization methods. The ONCV PPs have the smallest root-mean-square deviation for the tested materials. The fraction of materials that can be accurately described with the ONCV PPs at a certain energy cutoff is very similar to the performance of the PAWs. The ultrasoft PPs exhibit a similar accuracy at a moderately lower energy cutoff. For materials that go beyond the training and test set, we find that the ONCV PPs provides the best description of diatomic molecules. All pseudopotentials are very accurate for perovskite and half-Heusler compounds. \n\nTable 7 Bond length of diatomic molecules and lattice constant of perovskites and halfHeusler compounds investigated with different methods. For the half-Heusler compounds, the first element is in Wyckoff position c. All values are given in Å. \n\n\n
Materialref.1GBRVPSLIBSG15
H20.7500.7570.7500.749
N21.1021.1081.1101.101
021.2181.2241.2301.221
F21.4121.4241.4191.417
Cl22.0122.0042.0062.015
Br22.3112.3112.314
AsNCa34.7644.7654.7644.764
BaTiO34.0184.0284.0294.020
KMgCl35.0245.0235.0255.023
LaAl033.8143.8173.8153.809
PNCa34.7204.7204.7204.719
SrTiO33.9373.9393.9423.938
BScBe5.3185.3195.3165.317
GeAICu5.9105.9145.9135.920
NiScSb6.1186.1206.1236.123
NMgLi5.0045.0065.0065.010
PdZrSn6.3926.3926.3946.394
PZnNa6.1416.1496.1486.148
\n\n1 We evaluate the lattice constant perovskites and half Heusler with FLAPW and take the bond length of the dimers from the CCCB DataBase [30]. \n\nTable 8 Summary of the results depicted in Table 1 to 6 with same notation as Table 1. \n\n\n
GBRV PSLIBSG15
Average Salat (%)0.030.030.01
rms average Sajat (%)0.120.090.08
% of materials with |Salat | > 0.2%17.0438.5130.07
% of materials with |alat > 0.2%26.7010.224.65
% of materials with |Salat | > 0.2%36.193.731.99
Average 8B (%)0.210.18-0.14
rms average SBg (%)2.612.852.40
% of materials with |8Bg| > 5.0%113.7560.5154.49
% of materials with j8Bo| > 5.0%27.7313.3613.62
% of materials with |8Bgl > 5.0%34.473.343.82
Total number of materials582509602
\n\n1 With an energy cutoff of 40Ry. 2 With an energy cutoff of 60Ry. 3 With an energy cutoff of 160Ry. \n\nWe encourage the community to use the algorithm presented in this work to optimize pseudopotentials for different functionals and with different construction methods. With only a modest increase in the energy cutoff, the proposed SG15 library of normconserving pseudopotentials provides a competitive alternative to the libraries using USPP and PAW. As these pseudopotentials are less complex than the alternatives, this results in a great simplification in the development and implementation of new algorithms. \n\n# Acknowledgments \n\nWe would like to thank I. Castelli and N. Marzari for pointing out to us the importance of rejecting pseudopotentials with ghost states. \n\nThis work was supported by the US Department of Energy through grant DOE-BES DE-SC0008938. An award of computer time was provided by the DOE Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the US Department of Energy under contract DE-AC02-06CH11357. \n\n# Appendix A. Supplementary material \n\nSupplementary material related to this article can be found online at http://dx.doi.org/10.1016/j.cpc.2015.05.011. \n\n# References \n\n[1] R.M. Martin, Electronic Structure: Basic Theory and Practical Methods, Cambridge University Press, 2004. \n[2] P. Hohenberg, W. Kohn, Phys. Rev. 136 (1964) B864. http://dx.doi.org/10.1103/PhysRev.136.B864. \n[3] W. Kohn, L.J. Sham, Phys. Rev. 140 (1965) A1133. http://dx.doi.org/10.1103/PhysRev.140.A1133. \n[4] D.R. Hamann, M. Schlüter, C. Chiang, Phys. Rev. Lett. 43 (1979) 1494. http://dx.doi.org/10.1103/PhysRevLett.43.1494. \n[5] G.B. Bachelet, D.R. Hamann, M. Schlüter, Phys. Rev. B 26 (1982) 4199. http://dx.doi.org/10.1103/PhysRevB.26.4199. \n[6] D. Vanderbilt, Phys. Rev. B 41 (1990) 7892. http://dx.doi.org/10.1103/PhysRevB.41.7892. \n[7] P.E. Blöchl, Phys. Rev. B 50 (1994) 17953. http://dx.doi.org/10.1103/PhysRevB.50.17953. \n[8] D.R. Hamann, Phys. Rev. B 88 (2013) 085117. http://dx.doi.org/10.1103/PhysRevB.88.085117. \n[9] A.D. Becke, J. Chem. Phys. 98 (1993) 1372. http://dx.doi.org/10.1063/1.464304; A.D. Becke, J. Chem. Phys. 98 (1993) 5648. \n[10] F. Aryasetiawan, O. Gunnarsson, Rep. Progr. Phys. 61 (1998) 237. \n[11] S. Baroni, P. Giannozzi, A. Testa, Phys. Rev. Lett. 58 (1987) 1861. http://dx.doi.org/10.1103/PhysRevLett.58.1861. \n[12] C. Audouze, F. m. c. Jollet, M. Torrent, X. Gonze, Phys. Rev. B 73 (2006) 235101. http://dx.doi.org/10.1103/PhysRevB.73.235101. \n[13] N. Troullier, J.L. Martins, Phys. Rev. B 43 (1991) 1993. http://dx.doi.org/10.1103/PhysRevB.43.1993. \n[14] C. Hartwigsen, S. Goedecker, J. Hutter, Phys. Rev. B 58 (1998) 3641. http://dx.doi.org/10.1103/PhysRevB.58.3641. \n[15] K.F. Garrity, J.W. Bennett, K.M. Rabe, D. Vanderbilt, Comput. Mater. Sci. 81 (2014) 446. http://dx.doi.org/10.1016/j.commatsci.2013.08.053. \n[16] A. Dal Corso, Comput. Mater. Sci. 95 (2014) 337. http://dx.doi.org/10.1016/j.commatsci.2014.07.043. \n[17] E. Wimmer, H. Krakauer, M. Weinert, A.J. Freeman, Phys. Rev. B 24 (1981) 864. http://dx.doi.org/10.1103/PhysRevB.24.864. \n[18] M. Weinert, E. Wimmer, A.J. Freeman, Phys. Rev. B 26 (1982) 4571. http://dx.doi.org/10.1103/PhysRevB.26.4571. \n[19] H.J.F. Jansen, A.J. Freeman, Phys. Rev. B 30 (1984) 561. http://dx.doi.org/10.1103/PhysRevB.30.561. \n[20] K. Lejaeghere, V. Van Speybroeck, G. Van Oost, S. Cottenier, Crit. Rev. Solid State Mater. Sci. 39 (2014) 1. http://dx.doi.org/10.1080/10408436.2013.772503. \n[21] F. Murnaghan, Proc. Nat. Acad. Sci. USA 30 (1944) 244. \n[22] E. Kucukbenli, M. Monni, B. Adetunji, X. Ge, G. Adebayo, N. Marzari, S. de Gironcoli, A.D. Corso, arXiv:1404.3015. \n[23] http://www.quantum-simulation.org. \n[24] J.P. Perdew, K. Burke, M. Ernzerhof, Phys. Rev. Lett. 77 (1996) 3865. http://dx.doi.org/10.1103/PhysRevLett.77.3865. \n[25] http://www.flapw.de. \n[26] P. Giannozzi, S. Baroni, N. Bonini, M. Calandra, R. Car, C. Cavazzoni, D. Ceresoli, G.L. Chiarotti, M. Cococcioni, I. Dabo, A. Dal Corso, S. de Gironcoli, S. Fabris, G. Fratesi, R. Gebauer, U. Gerstmann, C. Gougoussis, A. Kokalj, M. Lazzeri, L. Martin-Samos, N. Marzari, F. Mauri, R. Mazzarello, S. Paolini, A. Pasquarello, L. Paulatto, C. Sbraccia, S. Scandolo, G. Sclauzero, A.P. Seitsonen, A. Smogunov, P. Umari, R.M. Wentzcovitch, J. Phys.: Condens. Matter. 21 (2009) 395502 (19pp). \n[27] J.A. Nelder, R. Mead, Comput. J. 7 (1965) 308. http://dx.doi.org/10.1093/comjnl/7.4.308. \n[28] W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes 3rd Edition: The Art of Scientific Computing, third ed., Cambridge University Press, New York, NY, USA, 2007. \n[29] See Supplemental material at http://dx.doi.org/10.1016/j.cpc.2015.05.011 for a list of all the calculated lattice constants and bulk moduli. We also list the choice of valence states for the pseudopotentials and provide the input files for the pseudopotential construction. \n[30] R.D. Johnson III (Ed.), NIST Computational Chemistry Comparison and Benchmark Database, NIST Standard Reference Database Number 101, Release 16a (August 2013). " + }, + { + "id": "10.1038_NMAT4489", + "DOI": "10.1038/NMAT4489", + "DOI Link": "http://dx.doi.org/10.1038/NMAT4489", + "Relative Dir Path": "mds/10.1038_NMAT4489", + "Article Title": "Hydrogels with tunable stress relaxation regulate stem cell fate and activity", + "Authors": "Chaudhuri, O; Gu, L; Klumpers, D; Darnell, M; Bencherif, SA; Weaver, JC; Huebsch, N; Lee, HP; Lippens, E; Duda, GN; Mooney, DJ", + "Source Title": "NATURE MATERIALS", + "Abstract": "Natural extracellular matrices (ECMs) are viscoelastic and exhibit stress relaxation. However, hydrogels used as synthetic ECMs for three-dimensional (3D) culture are typically elastic. Here, we report a materials approach to tune the rate of stress relaxation of hydrogels for 3D culture, independently of the hydrogel's initial elastic modulus, degradation, and cell-adhesion-ligand density. We find that cell spreading, proliferation, and osteogenic differentiation of mesenchymal stem cells (MSCs) are all enhanced in cells cultured in gels with faster relaxation. Strikingly, MSCs form a mineralized, collagen-1-rich matrix similar to bone in rapidly relaxing hydrogels with an initial elastic modulus of 17 kPa. We also show that the effects of stress relaxation are mediated by adhesion-ligand binding, actomyosin contractility and mechanical clustering of adhesion ligands. Our findings highlight stress relaxation as a key characteristic of cell-ECM interactions and as an important design parameter of biomaterials for cell culture.", + "Times Cited, WoS Core": 1758, + "Times Cited, All Databases": 1971, + "Publication Year": 2016, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000370967400019", + "Markdown": "# Hydrogels with tunable stress relaxation regulate stem cell fate and activity \n\nOvijit Chaudhuri1,2,3†, Luo $\\mathsf{G u}^{1,2\\dag}$ , Darinka Klumpers1,2,4, Max Darnell1,2, Sidi A. Bencherif1,2, James C. Weaver2, Nathaniel Huebsch1,5, Hong-pyo Lee3, Evi Lippens2,6, Georg N. Duda6 and David J. Mooney1,2\\* \n\nNatural extracellular matrices (ECMs) are viscoelastic and exhibit stress relaxation. However, hydrogels used as synthetic ECMs for three-dimensional (3D) culture are typically elastic. Here, we report a materials approach to tune the rate of stress relaxation of hydrogels for 3D culture, independently of the hydrogel’s initial elastic modulus, degradation, and cell-adhesion-ligand density. We find that cell spreading, proliferation, and osteogenic diferentiation of mesenchymal stem cells (MSCs) are all enhanced in cells cultured in gels with faster relaxation. Strikingly, MSCs form a mineralized, collagen-1-rich matrix similar to bone in rapidly relaxing hydrogels with an initial elastic modulus of 17 kPa. We also show that the efects of stress relaxation are mediated by adhesion-ligand binding, actomyosin contractility and mechanical clustering of adhesion ligands. Our findings highlight stress relaxation as a key characteristic of cell–ECM interactions and as an important design parameter of biomaterials for cell culture. \n\nydrogels composed of crosslinked networks of polymers, such as polyethylene glycol (PEG; refs 1,2), alginate3,4 and hyaluronic acid5,6, that are covalently coupled to integrinbinding ligands, such as RGD, are often used for 3D cell culture or as cell-laden biomaterial implants to promote tissue regeneration3,7–11. The use of these hydrogels is often preferred over reconstituted ECMs of collagen, fibrin, or basement membrane owing to the independent control over the physical and chemical properties (for example, matrix elasticity, ligand density, and porosity) possible in these hydrogels4,12–14, as well as their homogeneity at the microscale. However, normal cellular processes, such as shape change, migration and proliferation, are inhibited in these hydrogels unless they are designed to degrade over $\\mathrm{time}^{2,4,6,15}$ . Although non-degradable hydrogels can capture some characteristics of physiological ECM, they are typically almost purely elastic. In contrast, reconstituted extracellular matrices, such as collagen or fibrin2, and various tissues, such as brain16, liver17, adipose tissue18, coagulated bone marrow, initial fracture haematomas, or the soft callus of regenerating bone19, are all viscoelastic and exhibit partial stress relaxation when a constant strain of $15\\%$ is applied (Fig. 1a). For comparison, cells typically exert strains of up to $3\\mathrm{-}4\\%$ in 2D culture20, and $20{-}30\\%$ in 3D culture21 (Supplementary Note 1). Also, peak stresses measured during stress relaxation tests of these tissues ranged from 100 to $1,000\\mathrm{Pa}$ , well within the range of stresses generated by cells in 3D culture21,22 (Supplementary Table 1). A decrease in stress corresponds to a decrease in the relaxation modulus or the resistance to deformation over time. As it has been well established that the mechanical properties of materials regulate adherent cell behaviour23–29, the ability of a substrate to either store (purely elastic) \n\nor dissipate (viscoelastic) cellular forces could provide a powerful cue to interacting cells. Indeed, recent studies have found an impact of altered substrate viscoelasticity, independent of substrate stiffness, on various cell behaviours using hydrogels as substrates for cell culture30–33. In gels that exhibit stress relaxation, each force or strain a cell applies to the matrix over time is initially resisted with a certain stiffness, defined by the initial elastic modulus, followed by a decrease in resistance over time. For hydrogels formed with weak crosslinks, relaxation arises in part from unbinding of crosslinks and hydrogel flow, so that cellular forces can mechanically remodel the matrix33. Here we investigate the influence of hydrogel viscoelasticity and stress relaxation on cell spreading, proliferation and MSC differentiation in 3D culture. \n\n# Hydrogels with tunable stress relaxation \n\nFirst we modulated the nanoscale architecture of hydrogels to develop a set of materials with a wide range of stress relaxation rates, but a similar initial elastic modulus. As hydrogels exhibiting minimal degradation were desired, the polysaccharide alginate was chosen for these studies as mammalian cells do not express specific enzymes that can degrade this polymer34. Alginate presents no intrinsic integrin-binding sites for cells and minimal protein absorption, but cell adhesion can be promoted through covalent coupling of the RGD cell-adhesion peptide to the alginate chains3. Although the stress relaxation properties of hydrogels have been altered previously by changing crosslinking chemistries32,35 or polymer concentration30, we developed an alternative materials approach to control the rate of stress relaxation of hydrogels with a single crosslinker type and the same concentration of alginate. \n\n![](images/f2d34eb5d25033672e1d45914b749e836a967ad643c67ff3bead72b79afa23a8.jpg) \nFigure 1 | Modulating the nanoscale architecture of alginate hydrogels to modulate stress relaxation properties independent of initial elastic modulus and matrix degradation to capture the viscoelastic behaviours of living tissues. a, Living tissues are viscoelastic and exhibit stress relaxation. Stress relaxation tests of a crosslinked hydrogel (polyacrylamide), a collagen gel, an initial fracture haematoma (human), and various tissues (rat) at a strain of $15\\%$ . Stress is normalized by the initial stress. b, Schematic depicting how lowering the molecular weight (MW) of alginate polymers (blue) crosslinked by calcium (red) decreases entanglement and connectivity (orange arrows) of the network, and coupling of small spacers provides a steric spacing of crosslinking zones in the alginate. Both approaches are predicted to increase the rate of stress relaxation. c, Stress relaxation tests on gels composed of alginates with diferent molecular weights, or low-MW alginate coupled to a PEG spacer ( $15\\%$ compressional strain). d, Quantification of timescale at which the stress is relaxed to half its original value, $\\tau_{1/2},$ from stress relaxation tests in c. The timescale of stress relaxation decreases significantly with alteration in architecture (Spearman’s rank correlation coefcient, $p{<}0.0001\\rangle$ . e, Initial modulus measurements of gels in c. Diferences between elastic moduli are not significant, and elastic moduli show no statistical trend with altered architecture. f, Initial elastic modulus of alginate hydrogels after 1 day or 7 days in culture, normalized by the value at day 1. g, Measured dry mass of alginate hydrogels after 1 day or 7 days in culture normalized by the value at day 1. All data are shown as mean $\\pm{\\sf s.d}$ . \n\nWe hypothesized that by using different molecular weight polymers in combination with different crosslinking densities of calcium, which ionically crosslinks alginate, the stress relaxation properties of the resulting hydrogels could be modulated owing to the altered connectivity and chain mobility36 in the network (Fig. 1b). Any associated decrease in the initial elastic modulus resulting from decreased polymer molecular weight could be compensated for by increased crosslinking. Further, we hypothesized that covalent coupling of short PEG spacers to the alginate would provide a steric hindrance to crosslinking of alginate chains and enhance stress relaxation in the gel (Fig. 1b). Both approaches would alter the net avidity between individual polymer chains and therefore be expected to control the relaxation behaviour. This was confirmed, as it was found that by lowering the molecular weight of the alginate from 280 to $35\\mathrm{kDa}$ , and further by coupling $5\\mathrm{kDa}$ PEG spacers to the $35\\mathrm{kDa}$ alginate, the rate of stress relaxation was enhanced markedly (Fig. 1c). Specifically, the time for the initial stress of the material to be relaxed to half its value during a stress relaxation test $\\left(\\tau_{1/2}\\right)$ was modulated from ${\\sim}1\\mathrm{h}$ to ${\\sim}1\\mathrm{min}$ , while holding the alginate polymer concentration and the initial gel elastic modulus constant (Fig. 1c–e and Supplementary Table 2). These timescales span a range similar to that measured in various tissues (Fig. 1a). Further, this range of timescales is relevant to cell behaviours, as cells are thought to respond to force oscillations over a timescale of ${\\sim}1\\ s$ (ref. 37), exert traction forces on a timescale of minutes30, and undergo cell spreading on a timescale of minutes to hours38. The stress relaxation behaviour of these materials follows that of a two-element Maxwell–Weichert linear viscoelastic model (Supplementary Note 2 and Supplementary Fig. 1). It was previously shown that stress relaxation measured in ionically crosslinked alginate gels represents viscoelasticity of the hydrogel and unbinding of ionic crosslinks followed by matrix flow35. This interpretation was confirmed by a measurement of the frequency-dependent rheology of the gels, as an increase in the rate of stress relaxation correlated with a greater rate of decrease in the shear storage modulus with decreasing frequency (Supplementary Fig. 2). Also consistent with this interpretation is the near-complete relaxation of the stress, indicating that these matrices can be plastically deformed/mechanically remodelled and that the shorter the $\\tau_{1/2}$ , the faster the matrices remodel under stress. Homogeneity of the gels at the microscale was confirmed with confocal fluorescence microscopy (Supplementary Fig. 3). Importantly, the mechanical properties of these gels and the dry polymer mass of the gels were both stable over a timescale of at least seven days under tissue culture conditions (Fig. 1f,g). In combination, these observations indicate that the degradation of these matrices is negligible over this timescale. Taken together, these demonstrate an approach to control matrix stress relaxation, independent of the initial elastic modulus and polymer concentration, and without hydrogel degradation. \n\n![](images/32d30827f5377571b0480c51b4d95dbddc4d643cde2476b3617e2a2538991e1c.jpg) \nFigure 2 | Cell spreading and proliferation for fibroblasts encapsulated within gels are enhanced with faster stress relaxation. a, Representative images of 3T3 cells encapsulated within alginate gels with the indicated relaxation time $\\tau_{1/2}$ for stress relaxation and two RGD concentrations (average initial modulus of $9\\mathsf{k P a})$ . Green colour represents actin staining and blue represents nucleus. Images were taken after seven days in culture. Scale bar is $100\\upmu\\mathrm{m}$ for the larger images and $20\\upmu\\mathrm{m}$ for the insets. b, Quantification of the longest dimension of the smallest bounding box fully containing individual 3T3 cells for the indicated conditions. ∗∗indicates $p<0.01$ (Student’s t-test). Spreading increases significantly with faster stress relaxation (Spearman’s rank correlation, $p<0.0001$ for both values of RGD). c, Quantification of proliferating cells. ∗indicates $p<0.05$ (Student’s t-test). Proliferation was found to increase with faster stress relaxation (Spearman’s rank correlation, $p<0.0001$ for both values of RGD). d, Quantification of the longest dimension of the smallest bounding box fully containing individual 3T3 cells as a function of RGD density in alginate gels with a relaxation time of 70 or 170 s. Spreading increases significantly with increased RGD concentration for both gels (Spearman’s rank correlation, $p<0.0001$ for both values of $\\tau_{1/2}$ ). Data are shown as mean $\\pm{\\sf s.d}$ . \n\n# Stress relaxation afects cell spreading and proliferation \n\nWith this set of materials, the effect of the rate of substrate stress relaxation on cell spreading and proliferation in 3D culture was investigated, and striking differences in both were observed. First, 3T3 fibroblasts were encapsulated within RGD-coupled alginate hydrogels with varying stress relaxation rates but all with an initial elastic modulus of ${\\sim}9\\mathrm{kPa}$ (Fig. 2a). Both cell spreading and proliferation were suppressed within materials with long timescales for stress relaxation $(\\tau_{1/2}\\sim1\\mathrm{h})$ , and the rounded cell morphologies typical of cells in non-degradable elastic hydrogels were observed under this condition. Strikingly, both spreading and proliferation were found to increase with faster stress relaxation (Fig. $^{2\\mathrm{b},\\mathrm{c},}$ Spearman’s rank correlation, $\\textstyle P<0.0001$ for both). The influence of substrate stress relaxation on cell spreading and proliferation was enhanced when RGD cell-adhesion-ligand density was increased in gels with faster relaxation, indicating that the effect of stress relaxation is mediated through integrin-based adhesions (Fig. 2d, Spearman’s rank correlation, $\\begin{array}{r}{p<0.0001}\\end{array}.$ ). This enhancement in spreading and proliferation was attributable to altered stress relaxation alone, as the initial elastic modulus and alginate concentration was constant, and RGD cell-adhesion-ligand density was also held constant at either 0, 150, or $^{1,500\\upmu\\mathrm{M}}$ . The observation of striking changes in cell shape in the rapidly relaxing hydrogels suggest mechanical remodelling of the hydrogel by the cells, as these hydrogels are nanoporous and non-degradable, so that cell shape change and proliferation must be accommodated by matrix displacement. \n\nMatrix stress relaxation regulates MSC diferentiation Next, we looked at the influence of substrate stress relaxation on the differentiation of a murine mesenchymal stem cell line (D1, MSCs) in 3D culture. A previous study found that D1 MSCs, as well as primary human MSCs, encapsulated in ionically crosslinked alginate hydrogels undergo predominantly adipogenic differentiation at initial moduli of $1{-}10\\mathrm{kPa}$ , and predominantly osteogenic differentiation at initial moduli of $11-30\\mathrm{kPa}$ (ref. 4). An intuitive expectation might be that cells integrate the elastic modulus over time and feel an effectively lower elastic modulus on a viscoelastic substrate (Supplementary Fig. 4). If this were the case, osteogenic differentiation of MSCs in matrices with an initial elastic modulus of $11-30\\mathrm{kPa}$ would be reduced with faster relaxation in the gel. To test whether this is the case, MSCs were encapsulated in alginate hydrogels with various timescales of stress relaxation and initial elastic moduli (Fig. 3a,b and Supplementary Fig. 5). When the initial elastic modulus of the matrix was ${\\sim}9\\mathrm{kPa}$ , MSCs exhibited primarily adipogenic differentiation, as indicated by staining for neutral lipids, and very low levels of osteogenic differentiation, as indicated by alkaline phosphatase staining and a quantitative assay of alkaline phosphatase activity, for all timescales of stress relaxation probed (Fig. 3a,b). The level of adipogenesis was found to decrease in rapidly relaxing gels, which had a relaxation time of ${\\sim}1\\mathrm{min}$ . In contrast, at a higher initial elastic modulus of ${\\sim}17\\mathrm{kPa}$ , no adipogenic differentiation was observed, and osteogenic differentiation was significantly enhanced in gels with faster stress relaxation (Fig. $^{3\\mathrm{a,b}}\\mathrm{:}$ , Spearman’s rank correlation, $\\begin{array}{r}{p<0.0001,}\\end{array}$ ). This is surprising, as if cells were simply integrating the elastic modulus of the matrix over time, decreased osteogenesis and increased adipogenesis would be expected with faster stress relaxation. Calcium used to crosslink the alginate gels did not influence differentiation (Supplementary Fig. 6), consistent with previous findings4. Faster stress relaxation also promoted a greater degree of cell spreading in MSCs, similar to the result with 3T3s (Supplementary Fig. 7). Even though the initial seeding density of cells was held constant, there seemed to be a higher density of cells in the stiffer gels after seven days, possibly due to differences in proliferation between the adipogenically and osteogenically differentiated cells (Supplementary Fig. 7). Interestingly, cell morphologies were similar between MSCs in slow-relaxing gels (for example, $\\tau_{1/2}$ of $2,300\\mathrm{s})$ with an elastic modulus of $9\\mathrm{kPa}$ , in which adipogenesis is observed, and $17\\mathrm{kPa},$ in which osteogenesis is observed (Supplementary Fig. 7). In addition, cell morphology was similar for MSCs in $17\\mathrm{kPa}$ hydrogels with stress relaxation times of $2,300\\mathrm{s}$ and ${}^{300\\mathrm{s},}$ a range over which a striking increase in osteogenesis is observed (Supplementary Fig. 7 and Fig. 3). Thus MSC fate was decoupled from cell shape, consistent with previous findings regarding MSC differentiation in 3D culture4,13. \n\n![](images/f56fcc4d8f4683d5fe1eafeac04cfd2a89a5767a36e7b2c7ce1cc3cc5d32bab1.jpg) \nigure 3 | MSCs undergo osteogenic diferentiation and form an interconnected mineralized collagen-1-rich matrix only in rapidly relaxing gels. \na, Representative images of cryosections with Oil Red O (ORO) staining (red), indicating adipogenic diferentiation, and alkaline phosphatase staining (blue), indicating early osteogenic diferentiation, for MSC cultured in gels of indicated initial modulus and timescale of stress relaxation for seven days. RGD density is $1,500\\upmu\\mathrm{M}$ . Scale bars are $25\\upmu\\mathrm{m}$ . b, Quantification of the percentage of cells staining positive for ORO, and a quantitative assay for alkaline phosphatase activity from lysates of cells in gels from the indicated conditions at seven days in culture. ∗, ∗∗, and ∗∗∗∗indicate $p<0.05$ , 0.01, and 0.0001 respectively (Student’s t-test). Bars for $\\%$ cells staining for ORO in gels with initial modulus of $17k P a$ and alkaline phosphatase activity of cells in gels with initial modulus of $9\\mathsf{k P a}$ are barely visible owing to the small values relative to the other conditions. Osteogenic diferentiation increases significantly with a faster stress relaxation (Spearman’s rank correlation, $p{<}0.0001\\rangle$ . c, Von Kossa (mineralization) and collagen-1 stain on cryosections from gels with the indicated conditions after two weeks of culture. Scale bars are $25\\upmu\\mathrm{m}$ . d, Scanning electron microscope and energy-dispersive $\\mathsf{X}$ -ray spectrometry (SEM-EDS) images of sections of gels with the indicated conditions (all gels at $1,500\\upmu\\mathrm{M}$ RGD) after two weeks of 3D culture of MSCs. Phosphorus elemental maps (P mapped in red) are overlaid on their corresponding backscattered SEM images. Scale bar is $50\\upmu\\mathrm{m}$ . All data are shown as mean $\\pm$ s.d. For simplicity, $\\tau_{1/2}$ values shown in this figure are an average of the $\\tau_{1/2}$ values at $9\\mathsf{k P a}$ and $17k P a$ . Specific values for each condition are shown in Supplementary Table 2. \n\n![](images/ca90a6803af87e4d9092e90a31afe12d30114312dc6b427e671ea536600a1802.jpg) \nFigure 4 | Osteogenic diferentiation of MSCs mediated through ECM ligand density, enhanced RGD ligand clustering, and myosin contractility in stifer hydrogels. a, Quantification of ALP activity of MSCs encapsulated in hydrogels with an initial elastic modulus of $17k P a$ after seven days in culture with an RGD density of 150 or $1,500\\upmu\\mathrm{M}$ . b, Representative immunofluorescence staining for actin (green), nucleus (blue) and β1 integrin (red) in MSCs cultured in the indicated conditions for a week. c, Schematic of assay using FRET between RGD–fluorescein and RGD–rhodamine coupled to diferent alginate chains to monitor mechanical clustering of RGD ligands at the nanoscale by cells. d, Representative confocal microscope images of nucleus (DAPI/ blue) and FRET acceptor signal from hydrogel (red) surrounding MSCs cultured in hydrogels with diferent stress relaxation properties after $18\\mathsf{h}$ of culture. Blank spot in FRET signal images indicates location of cell. e, Quantification of enhancement of FRET acceptor signal within ${\\sim}2\\ –3\\upmu\\mathrm{m}$ of cell border relative to the background of the hydrogel. Data are shown as mean $\\pm{\\sf s.d.}$ . and ∗∗∗∗indicates $p<0.0001$ (Student’s t-test). f, ALP activity of MSCs in the presence of ML-7, a myosin light chain kinase inhibitor. g, ALP activity of MSCs in the presence of a Rho kinase inhibitor, Y-27632. h, ALP activity of MSCs in the presence of a Rac1 inhibitor, NSC 23766. All experiments were done in hydrogels with an initial elastic modulus of 17 kPa and RGD concentration of $1,500\\upmu\\mathrm{M}$ All data are shown as mean $\\pm$ s.d. ∗, ∗∗indicate $p<0.05$ , 0.01 respectively (Student’s t-test). Scale bars are all $10\\upmu\\mathrm{m}$ . \n\nIn addition to characterizing differentiation of the MSCs, the functional activity of the osteogenically differentiated stem cells was examined. Previous studies have found osteogenic differentiation of MSCs within 3D matrices of slowly relaxing alginate gels4, PEG gels39, degradable hyaluronic acid gels13, or thixotropic PEG silica gels40. However, formation of an interconnected, mineralized and collagen-1-rich matrix, the three key structural features of bone, by these differentiated cells has not been reported. Here, Von Kossa staining, immunohistochemistry and energy-dispersive X-ray spectroscopy (EDS) revealed that matrix mineralization and type-1 collagen deposition were both enhanced after 14 days in culture with faster stress relaxation (Fig. 3c,d and Supplementary Fig. 8). Strikingly, MSCs formed an interconnected bone-like matrix in rapidly relaxing gels that exhibit a time constant of stress relaxation of the order of ${\\sim}1\\mathrm{min}$ . Intriguingly, this timescale of stress relaxation approaches that of an initial fracture haematoma (Fig. 1a), and is similar to that reported for an early fracture callous19. This result demonstrates that the rapidly relaxing gels not only promote maximal osteogenesis, but also enable boneforming activity in the osteogenically differentiated stem cells. \n\nAfter finding strong effects of the initial elastic modulus and the rate of stress relaxation on MSC differentiation and bone-forming activity, we investigated the underlying mechanism by which fast stress relaxation promotes these behaviours. Cells sense mechanical cues in the ECM through binding to ECM ligands, so the impact of RGD density on MSC differentiation was first examined (Fig. 4a and Supplementary Fig. 9). At a lower RGD density of $150\\upmu\\mathrm{M}.$ a more graded trend of enhanced osteogenesis with faster stress relaxation is observed in hydrogels with an initial elastic modulus of $17\\mathrm{kPa}$ (Spearman’s rank correlation, $\\begin{array}{r}{p<0.0001.}\\end{array}$ ), but the degree of osteogenic differentiation was significantly diminished relative to at a higher RGD density (Fig. 4a). These findings demonstrate that the effect of stress relaxation on osteogenic differentiation is mediated through ECM ligands. Cells bind to ECM ligands through integrin receptors41. An examination of the localization of $\\upbeta1$ integrin using an antibody recognizing an epitope of primed $\\upbeta1$ integrin revealed increased localization of primed $\\upbeta1$ integrin to the periphery of the cell in gels with faster relaxation (Fig. 4b). However, localization of paxillin to the periphery of the cells was not observed, indicating that conventional focal adhesions42 were not being formed in this 3D material system at any level of stress relaxation (Supplementary Fig. 10). As it was previously found that ligand clustering was associated with osteogenic differentiation, the clustering of RGD ligands was next assessed using a Förster resonance energy transfer (FRET)-based technique4,43. FRET between fluoresceinand carboxytetramethylrhodamine (TAMRA)-labelled RGD coupled to the alginate was analysed in slow- and fast-relaxing hydrogels with encapsulated cells using confocal microscopy (Fig. 4c,d). A higher degree of energy transfer was measured in regions of the hydrogels adjacent to MSCs in gels with fast relaxation relative to MSCs in gels with slower relaxation after eighteen hours of culture (Fig. 4e). The FRET signal was typically enhanced in the entire area surrounding the cells in fast-relaxing gels, although in some cases a more asymmetric enhancement was observed (Supplementary Fig. 11). As the FRET signal is a highly sensitive function of distance between donor and acceptor fluorophores, this demonstrates nanoscale clustering of RGD ligands and mechanical remodelling of the hydrogel by cells locally in hydrogels with faster relaxation and an initial elastic modulus of $17\\mathrm{kPa}$ . Although a similar trend of increased RGD ligand clustering with faster relaxation was observed for cells in gels with an initial elastic modulus of $9\\mathrm{kPa}$ , the degree of transfer in faster-relaxing gels was significantly lower when compared to the stiffer fast-relaxing gels (Supplementary Fig. 11). \n\nAs binding and clustering of integrins activates signalling pathways44,45, we examined the role of signalling pathways in mediating osteogenesis in gels with different levels of stress relaxation. Previous work has found that cells sense the stiffness of ECM substrates through actomyosin contractility46, often mediated through activation of the Rho signalling pathway, and sense the loss modulus of 2D acrylamide substrates through activation of the Rac signalling pathway30. Pharmacological inhibition of myosin, Rho and Rac1 was performed on MSCs encapsulated within hydrogels with an initial elastic modulus of $17\\mathrm{kPa}$ . Inhibition of myosin light chain kinase with ML-7 diminished osteogenesis, demonstrating that enhanced osteogenesis in substrates with fast stress relaxation involves myosin contractility (Fig. 4f). Interestingly, inhibition of Rho with Y-27632 resulted in enhanced osteogenesis, in three of four rates of stress relaxation (Fig. 4g). Inhibition of Rac1 with NSC 23766 did not have a significant effect on osteogenesis (Fig. 4h). Next, nuclear localization of the YAP transcriptional regulator was examined. The YAP transcriptional regulator is thought to be the key regulatory element controlling the gene expression of cells in response to mechanical or geometric cues47. Nuclear localization of YAP was previously found to direct MSC differentiation into adipogenic or osteogenic lineages47,48 for MSCs cultured on 2D acrylamide substrates in response to altered substrate stiffness. We find nuclear translocation of YAP increases with faster stress relaxation for both values of initial elastic moduli tested (Spearman’s rank correlation, $\\begin{array}{r}{p<0.0001}\\end{array}$ for both), indicating that matrix stress relaxation has an impact on transcriptional factor activity. Interestingly, the levels of nuclear YAP spanned the same range for the two different moduli (Fig. 5a,b and Supplementary Fig. 12). As adipogenic differentiation is primarily observed in substrates with an elastic modulus of ${\\sim}9\\mathrm{kPa}$ , and osteogenic differentiation is primarily observed in substrates with an elastic modulus of ${\\sim}17\\mathrm{kPa}$ , this demonstrates a decoupling of nuclear translocation of YAP from MSC fate (Fig. 5c,d). These findings indicate that localization of YAP does not by itself control the differentiation of MSCs in 3D cell culture. \n\n# Outlook \n\nThis work demonstrates an approach to modulating stress relaxation properties in alginate hydrogels, and indicates that substrate stress relaxation has a profound effect on cell biology. Several recent studies have used alternative material approaches to examine the role of altered substrate viscoelasticity on cell biology. These include modulating both the covalent crosslinking density and polymer concentration in acrylamide hydrogels to tune the loss modulus for 2D culture30,31, utilizing different stoichiometries of dynamic covalent crosslinkers with different affinities to modulate stress relaxation in PEG hydrogels32, or the use of covalent versus physical crosslinking of alginate hydrogels33. These approaches revealed that an enhanced loss modulus and substrate creep led to increased spreading and osteogenic differentiation of MSCs in 2D culture30,31, and that increased substrate stress relaxation promoted cell spreading and proliferation in 2D culture33 and altered cell morphology in 3D culture32. The approach described in this paper is unique in that only one type of crosslinking is utilized, while maintaining compatibility with 3D culturing of cells and holding alginate concentration constant. The nanoscale architecture of these gels does not capture the fibrillarity of some natural ECM in vivo49. However, this approach does allow modulation of stress relaxation properties over a range similar to that observed in various tissues16 and enables presentation of a homogeneous microenvironment to cells, providing a well-controlled system for probing cell–ECM interactions. There is some coupling between the initial elastic modulus and the range of stress relaxation timescales for alginate with a given molecular weight and PEG coupling state, as stiffening the hydrogels from 9 to $17\\mathrm{kPa}$ shifted the range of stress relaxation timescales from $^{3,300-70s}$ to $1,300{-}40s$ . Generally, this approach to decouple the initial elastic modulus from relaxation rate, and the associated development of rapidly relaxing gels, may be useful in a variety of material applications. \n\n![](images/e36cbf136ac3559bc7ed8996ae7f86ff91d3bc65e69707d29d1372e3cb49260e.jpg) \nFigure 5 | Nuclear localization of YAP is enhanced by faster stress relaxation, but decoupled from MSC fate. a, Representative immunofluorescence staining for actin (green), nucleus (blue) and YAP (red) in MSCs cultured in the indicated conditions for a week. Scale bar is $10\\upmu\\mathrm{m}$ . b, Quantification of the ratio of the concentration of nuclear YAP, to the concentration of YAP in the cytoskeleton. Nuclear YAP increases significantly with faster stress relaxation for both initial elastic moduli (Spearman’s rank correlation, $p<0.0001$ for both). c, Quantification of the percentage of D1 cells that stain positive for ORO as a function of the relative nuclear YAP. d, Quantification of ALP in diferentiated D1 cells as a function of the relative nuclear YAP. No trend is observed in c and d. All data are shown as mean $\\pm\\thinspace s.\\mathsf{d}$ . \n\nMechanistically, we find that the enhancement in cell spreading, proliferation, and osteogenic differentiation of MSCs by faster matrix stress relaxation is mediated through integrin-based adhesions, local clustering of RGD ligands, actomyosin contractility, and nuclear localization of YAP (Supplementary Fig. 13). MSC differentiation depended strongly on the initial elastic modulus in viscoelastic matrices in 3D, with osteogenesis occurring only when the initial elastic modulus was $17\\mathrm{kPa}$ . In contrast, MSC differentiation loses sensitivity to matrix stiffness in covalently crosslinked hydrogels13, which are presumably elastic, highlighting the importance of stress relaxation in cells responding to mechanical cues of ECM. Inhibition of actomyosin contractility completely abrogated osteogenesis, indicating the role of contractile forces in sensing stiffness and stress relaxation, and driving osteogenesis. As forces exerted by cells on the crosslinked alginate hydrogels are relaxed through unbinding of weak ionic crosslinks and matrix flow, actomyosin contractility coupled to the matrix through binding to RGD ligands mechanically clusters RGD ligands over time in gels with faster relaxation. RGD ligand and integrin clustering in turn is known to activate signalling pathways44,45, and has been associated previously with osteogenic differentiation4, providing a mechanistic link between altered stress relaxation and modulation of biological signalling and long-term cell fate. Although Rhomediated contractility has been found to be critical for osteogenesis in 3D culture in degradable hydrogels13, inhibition of Rho did not diminish osteogenesis in the non-degradable alginate hydrogels, and in some cases enhanced it. Further, previous work has found that an increased loss modulus in acrylamide substrates increases Rac activation31, whereas inhibition of Rac did not diminish osteogenesis in alginate hydrogels. These suggest that the role of Rho and Rac in osteogenesis is context dependent. \n\nAlthough many previous studies have highlighted the importance of matrix remodelling through proteolytic degradation on cell function, the altered behaviour of cells in rapidly relaxing gels suggests that the ability of cells to mechanically remodel their matrix is also an essential component of cell–ECM interactions (Fig. 6). In particular, it is likely that the greater malleability of fast-relaxing hydrogels that enabled increased RGD ligand clustering on short timescales also facilitated the physical aspects of the processes of cell spreading, proliferation and formation of an interconnected bone-like matrix by osteogenically differentiated MSCs over longer timescales, in the absence of matrix degradation. Similar to the observed trend of diminishing osteogenic differentiation with decreased stress relaxation, a recent study showed that osteogenic differentiation of MSCs was inhibited in non-degradable covalently crosslinked gels, which presumably cannot be remodelled mechanically, although differences in material systems preclude a direct comparison13. Previous work has highlighted the effect of matrix degradation in bone regeneration15 or cartilage formation10 in implantable scaffolds, as well as on cell shape and MSC differentiation in 3D culture in vitro13. Our work suggests the possibility that the effect of degradation may be in part due to enhanced matrix stress relaxation in regions of the matrix that exhibit substantial degradation. Indeed, it was recently found that proteolytic degradation of covalently crosslinked PEG hydrogels by encapsulated MSCs locally converts elastic matrices into viscoelastic fluids50. \n\n![](images/a2edf8f19d139e44ce0a7b153d96e90d2815005ab5ff40f25c93086f17e0e046.jpg) \nFigure 6 | Hypothesis for how initial elastic modulus and stress relaxation properties of matrix regulate cellular behaviours. A cell in a 3D matrix initially exerts strains on the matrix, resulting in forces/stresses resisting this strain, as determined by the initial elastic modulus of the matrix. In an elastic matrix, these forces are never relaxed, so that there is no remodelling of the matrix microenvironment. In a viscoelastic matrix, forces in the matrix can be relaxed over time as a result of mechanical yielding and remodelling of the matrix. The rate of stress relaxation determines the degree of this mechanical remodelling of the matrix. In fast-relaxing matrices, this facilitates adhesion-ligand clustering, cell shape change, proliferation and bone matrix formation by MSCs undergoing osteogenic diferentiation. \n\nBroadly, these results highlight the importance of considering matrix stress relaxation as a fundamental signal in understanding the basics of cell–ECM interactions and the underlying biophysics of mechanotransduction, because most physiological extracellular matrices exhibit some degree of stress relaxation. These findings point towards the use of stress relaxation as a design parameter for materials in tissue engineering8, particularly in the context of regulating cell proliferation and promoting bone regeneration. \n\n# Methods \n\nMethods and any associated references are available in the online version of the paper. \n\nReceived 5 June 2014; accepted 26 October 2015; published online 30 November 2015 \n\n# References \n\n1. Burdick, J. A. & Anseth, K. S. Photoencapsulation of osteoblasts in injectable RGD-modified PEG hydrogels for bone tissue engineering. Biomaterials 23, \n4315–4323 (2002). \n2. Raeber, G. P., Lutolf, M. P. & Hubbell, J. A. Molecularly engineered PEG hydrogels: A novel model system for proteolytically mediated cell migration. Biophys. J. 89, 1374–1388 (2005). \n3. Rowley, J. A., Madlambayan, G. & Mooney, D. J. Alginate hydrogels as synthetic extracellular matrix materials. Biomaterials 20, 45–53 (1999). \n4. Huebsch, N. et al. Harnessing traction-mediated manipulation of the cell/matrix interface to control stem-cell fate. Nature Mater. 9, 518–526 (2010). \n5. Park, Y. D., Tirelli, N. & Hubbell, J. A. Photopolymerized hyaluronic acid-based hydrogels and interpenetrating networks. Biomaterials 24, \n893–900 (2003). \n6. Burdick, J. A., Chung, C., Jia, X., Randolph, M. A. & Langer, R. Controlled degradation and mechanical behavior of photopolymerized hyaluronic acid networks. Biomacromolecules 6, 386–391 (2005). \n7. Lutolf, M. P. & Hubbell, J. A. Synthetic biomaterials as instructive extracellular microenvironments for morphogenesis in tissue engineering. Nature Biotechnol. 23, 47–55 (2005). \n8. Langer, R. & Tirrell, D. A. Designing materials for biology and medicine. Nature 428, 487–492 (2004). \n9. Healy, K. E., Rezania, A. & Stile, R. A. Designing biomaterials to direct biological responses. Ann. N. Y. Acad. Sci. 875, 24–35 (1999). \n10. Metters, A. T., Anseth, K. S. & Bowman, C. N. Fundamental studies of biodegradable hydrogels as cartilage replacement materials. Biomed. Sci. Instrum. 35, 33–38 (1999). \n11. Nguyen, K. T. & West, J. L. Photopolymerizable hydrogels for tissue engineering applications. Biomaterials 23, 4307–4314 (2002). \n12. Peyton, S. R., Raub, C. B., Keschrumrus, V. P. & Putnam, A. J. The use of poly(ethylene glycol) hydrogels to investigate the impact of ECM chemistry and mechanics on smooth muscle cells. Biomaterials 27, 4881–4893 (2006). \n13. Khetan, S. et al. Degradation-mediated cellular traction directs stem cell fate in covalently crosslinked three-dimensional hydrogels. Nature Mater. 12, \n5571–5580 (2013). \n14. Wen, J. H. et al. Interplay of matrix stiffness and protein tethering in stem cell differentiation. Nature Mater. 13, 979–987 (2014). \n15. Alsberg, E. et al. Regulating bone formation via controlled scaffold degradation. J. Dent. Res. 82, 903–908 (2003). \n16. Levental, I., Georges, P. C. & Janmey, P. A. Soft biological materials and their impact on cell function. Soft Matter 3, 299–306 (2007). \n17. Liu, Z. & Bilston, L. On the viscoelastic character of liver tissue: Experiments and modelling of the linear behaviour. Biorheology 37, 191–201 (2000). \n18. Geerligs, M., Peters, G. W. M., Ackermans, P. A. J., Oomens, C. W. J. & Baaijens, F. P. T. Linear viscoelastic behavior of subcutaneous adipose tissue. Biorheology 45, 677–688 (2008). \n19. McDonald, S. J. et al. Early fracture callus displays smooth muscle-like viscoelastic properties ex vivo: Implications for fracture healing. J. Orthop. Res. 27, 1508–1513 (2009). \n20. Discher, D. E., Janmey, P. & Wang, Y.-L. Tissue cells feel and respond to the stiffness of their substrate. Science 310, 1139–1143 (2005). \n21. Legant, W. R. et al. Measurement of mechanical tractions exerted by cells in three-dimensional matrices. Nature Methods 7, 969–971 (2010). \n22. Legant, W. R. et al. Microfabricated tissue gauges to measure and manipulate forces from 3D microtissues. Proc. Natl Acad. Sci. USA 106, 10097–10102 (2009). \n23. Pelham, R. J. Jr & Wang, Y. l. Cell locomotion and focal adhesions are regulated by substrate flexibility. Proc. Natl Acad. Sci. USA 94, 13661–13665 (1997). \n24. Flanagan, L. A., Ju, Y.-E., Marg, B., Osterfield, M. & Janmey, P. A. Neurite branching on deformable substrates. Neuroreport 13, 2411–2415 (2002). \n25. Engler, A. et al. Substrate compliance versus ligand density in cell on gel responses. Biophys. J. 86, 617–628 (2004). \n26. Kong, H. J. et al. Non-viral gene delivery regulated by stiffness of cell adhesion substrates. Nature Mater. 4, 460–464 (2005). \n27. Paszek, M. J. et al. Tensional homeostasis and the malignant phenotype. Cancer Cell 8, 241–254 (2005). \n28. Engler, A., Sen, S., Sweeney, H. & Discher, D. Matrix elasticity directs stem cell lineage specification. Cell 126, 677–689 (2006). \n29. Chaudhuri, O. et al. Extracellular matrix stiffness and composition jointly regulate the induction of malignant phenotypes in mammary epithelium. Nature Mater. 13, 970–978 (2014). \n30. Cameron, A. R., Frith, J. E. & Cooper-White, J. J. The influence of substrate creep on mesenchymal stem cell behaviour and phenotype. Biomaterials 32, 5979–5993 (2011). \n31. Cameron, A. R., Frith, J. E., Gomez, G. A., Yap, A. S. & Cooper-White, J. J. The effect of time-dependent deformation of viscoelastic hydrogels on myogenic induction and Rac1 activity in mesenchymal stem cells. Biomaterials 35, 1857–1868 (2014). \n32. McKinnon, D. D., Domaille, D. W., Cha, J. N. & Anseth, K. S. Biophysically defined and cytocompatible covalently adaptable networks as viscoelastic 3D cell culture systems. Adv. Mater. 26, 865–872 (2013). \n33. Chaudhuri, O. et al. Substrate stress relaxation regulates cell spreading. Nature Commun. 6, 6364 (2015). \n34. Lee, K. Y. & Mooney, D. J. Hydrogels for tissue engineering. Chem. Rev. 101, 1869–1879 (2001). \n35. Zhao, X., Huebsch, N., Mooney, D. J. & Suo, Z. Stress-relaxation behavior in gels with ionic and covalent crosslinks. J. Appl. Phys. 107, 63509 (2010). \n36. Graessley, W. W. Synthesis and Degradation Rheology and Extrusion Vol. 47, 67–117 (Springer, 1982). \n37. Vogel, V. & Sheetz, M. Local force and geometry sensing regulate cell functions. Nature Rev. Mol. Cell Biol. 7, 265–275 (2006). \n38. Mooney, D. J., Langer, R. & Ingber, D. E. Cytoskeletal filament assembly and the control of cell spreading and function by extracellular matrix. J. Cell Sci. 108, 2311–2320 (1995). \n39. Parekh, S. H. et al. Modulus-driven differentiation of marrow stromal cells in 3D scaffolds that is independent of myosin-based cytoskeletal tension. Biomaterials 32, 2256–2264 (2011). \n40. Pek, Y. S., Wan, A. C. A. & Ying, J. Y. The effect of matrix stiffness on mesenchymal stem cell differentiation in a 3D thixotropic gel. Biomaterials 31, 385–391 (2010). \n41. Humphries, J. D., Byron, A. & Humphries, M. J. Integrin ligands at a glance. J. Cell Sci. 119, 3901–3903 (2006). \n42. Kanchanawong, P. et al. Nanoscale architecture of integrin-based cell adhesions. Nature 468, 580–584 (2010). \n43. Kong, H. J., Polte, T. R., Alsberg, E. & Mooney, D. J. FRET measurements of cell-traction forces and nano-scale clustering of adhesion ligands varied by substrate stiffness. Proc. Natl Acad. Sci. USA 102, 4300–4305 (2005). \n44. Arnold, M. et al. Activation of integrin function by nanopatterned adhesive interfaces. ChemPhysChem 5, 383–388 (2004). \n45. Maheshwari, G., Brown, G., Lauffenburger, D. A., Wells, A. & Griffith, L. G. Cell adhesion and motility depend on nanoscale RGD clustering. J. Cell Sci. 113, 1677–1686 (2000). \n46. Wozniak, M. A. & Chen, C. S. Mechanotransduction in development: A growing role for contractility. Nature Rev. Mol. Cell Biol. 10, 34–43 (2009). \n47. Dupont, S. et al. Role of YAP/TAZ in mechanotransduction. Nature 474, 179–183 (2011). \n48. Swift, J. et al. Nuclear lamin-A scales with tissue stiffness and enhances matrix-directed differentiation. Science 341, 1240104 (2013). \n49. Hynes, R. O. The extracellular matrix: Not just pretty fibrils. Science 326, 1216–1219 (2009). \n50. Schultz, K. M., Kyburz, K. A. & Anseth, K. S. Measuring dynamic cell-materia interactions and remodeling during 3D human mesenchymal stem cell migration in hydrogels. Proc. Natl Acad. Sci. USA 112, E3757–E3764 (2015). \n\n# Acknowledgements \n\nThe authors acknowledge the help of S. Koshy, M. Mehta, C. Verbeke, X. Zhao (now at MIT), and other members of the Mooney lab. The authors also thank the Weitz lab for use of a rheometer, O. Uzun for help with GPC, S. Reinke (Berlin-Brandenburg Center for Regenerative Therapies) for providing the human bone haematoma samples, and D. Wulsten and S. Reinke for the support in bone fracture haematoma testing. This work was supported by an NIH Grant to D.J.M. (R01 DE013033), an NIH F32 grant to O.C. (CA153802), an Einstein Visiting Fellowship for D.J.M., funding of the Einstein Foundation Berlin through the Charité—Universitätsmedizin Berlin, Berlin-Brandenburg School for Regenerative Therapies GSC 203, ZonMW-VICI grant 918.11.635 (The Netherlands) for D.K., and Harvard MRSEC for D.J.M. (DMR-1420570). This work was performed in part at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Infrastructure Network (NNIN). \n\n# Author contributions \n\nO.C., L.G., D.K., M.D., N.H. and D.J.M. designed the experiments. O.C. and L.G. conducted most of the experiments. D.K. helped with experiments involving the MSCs. S.A.B. helped with alginate characterization. J.C.W. helped with EDS experiments and analysis. H.-p.L. assisted with mechanical characterization. E.L. and G.N.D. carried out fracture haematoma measurement. O.C. and L.G. analysed the data. O.C., L.G., D.K. and D.J.M. wrote the manuscript. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to D.J.M. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. \n\n# Methods \n\nAlginate preparation. Sodium alginate rich in guluronic acid blocks and with a high molecular weight $280\\mathrm{kDa}$ , LF20/40) was purchased from FMC Biopolymer, and was prepared as has been described previously3. Briefly, high-MW alginate was irradiated by a 3 or 8 Mrad cobalt source to produce mid- or low-MW alginates. RGD–alginate was prepared by coupling the oligopeptide GGGGRGDSP (Peptides International) to the alginate using carbodiimide chemistry at concentrations such that 2 or 20 RGD peptides were coupled to 1 alginate chain on average for high-MW alginate (peptide molar concentrations in low-MW alginates were kept the same according to high-MW alginate for each degree of substitution, respectively). For FRET experiments, either GGGGRGDASSK(carboxyfluorescein)Y or GGGGRGDASSK(carboxytetramethylrhodamine)Y were used instead of the standard RGD peptide sequence, and were coupled at a concentration of 2 peptides per alginate chain on average for high-MW alginate (peptide molar concentrations in low-MW alginates were kept the same according to the high-MW alginate). The coupling efficiency using this procedure was previously characterized using $^{125}\\mathrm{I}$ -labelled RGD peptides3. These correspond to densities of $150\\upmu\\mathrm{M}$ and $^{1,500\\upmu\\mathrm{M}}$ RGD in a $2\\%$ wt/vol alginate gel. Alginate was dialysed against deionized water for 2–3 days (molecular weight cutoff of $3.5\\mathrm{kDa}$ ), treated with activated charcoal, sterile filtered, lyophilized, and then reconstituted in serum-free DMEM (Life Technologies). \n\nPolyethylene glycol (PEG)–alginate was prepared by coupling PEG-amine (5 kDa, Laysan Bio) to the low-MW alginate $(35\\mathrm{kDa})$ using carbodiimide chemistry with a similar procedure to the RGD coupling3. In brief, $295\\mathrm{mg}$ of PEG-amine was mixed with $50\\mathrm{ml}$ of $10\\mathrm{mg}\\mathrm{ml}^{-1}$ alginate in $0.1\\mathrm{M}$ MES (2- $N$ -morpholino)ethanesulfonic acid, Sigma-Aldrich) buffer at $\\mathrm{pH}6.5$ . Then $242\\mathrm{mg}$ of EDC $N$ -(3-dimethylaminopropyl)- ${\\bf\\nabla}\\cdot N^{\\prime}$ -ethylcarbodiimide hydrochloride, Sigma-Aldrich) and $137\\mathrm{mg}$ of Sulpho-NHS (N -hydroxysulphosuccinimide, Thermo Fisher Scientific) were added into the solution. The reaction was carried out for $20\\mathrm{h}$ under constant stirring. The product was dialysed against deionized water for three days (molecular weight cutoff of $10\\mathrm{kDa}$ ), filtered with activated charcoal, sterile filtered, and lyophilized. The structure of the PEG–alginate was confirmed with nuclear magnetic resonance (NMR) and gel permeation chromatography (GPC). Based on the change of molecular weight of alginate before and after PEG coupling (from 35 to $45\\mathrm{kDa}$ ), an average of 2 PEG molecules were coupled to 1 alginate chain. This number was confirmed by $\\mathrm{^{1}H}$ NMR spectroscopy (Supplementary Fig. 14). \n\nAlginate characterization. Molecular weights of alginates and PEG–alginate were analysed with a Malvern Viscotek 270max GPC equipped with a GPCmax solvent and sample delivery module, an Eldex Ch-150 temperature-controlled column holder, a VE 3580 refractive index (RI) detector, Viscotek 270 Dual Detector featuring intrinsic viscosity (IV-DP) and right-angle light scattering (RALS), and OmniSec software. Samples were dissolved in 0.1 M $\\mathrm{NaNO}_{3}$ buffer solution at a concentration of $5\\mathrm{mg}\\mathrm{ml^{-1}}$ , and $200\\upmu\\mathrm{l}$ of sample was injected. Polymers separated through a set of two TSK-gel columns (G4000PWXL and G3000PWXL) were analysed with the triple-detector system. Malvern PEO and pullulan standards were used in molecular weight calculation, and weight-average molecular weights $(M_{\\mathrm{w}})$ were used. \n\nHigh-resolution $^{1}\\mathrm{H}$ NMR spectra were obtained in deuterium oxide $\\mathrm{(D}_{2}\\mathrm{O})_{\\cdot}$ ) using a Varian Unity-400 $\\boldsymbol{400}\\mathrm{MHz}$ ) NMR spectrometer (Varian). $\\mathrm{^{1}H}$ NMR was used to characterize PEG coupling of alginate and the degree of functionalization of PEG–alginate. \n\nMechanical characterization. Rheology measurements were made with an AR-G2 stress controlled rheometer (TA Instruments). Alginate gels were deposited directly onto the surface plate of the rheometer immediately after mixing with the crosslinker. A $20\\mathrm{mm}$ plate was immediately brought down, forming a $20\\mathrm{mm}$ disk of gel with an average thickness of ${\\sim}1.8\\mathrm{mm}$ . The mechanical properties were then measured over time until the storage modulus reached an equilibrium value. The storage modulus at $0.5\\%$ strain and at $1\\mathrm{Hz}$ was recorded periodically for $45\\mathrm{min}$ . Then, a strain sweep was performed to confirm this value was within the linear elastic regime, followed by a frequency sweep. No prestress was applied to the gels for these measurements. \n\nThe initial elastic moduli and stress relaxation properties of alginate gels were measured from compression tests of the gel disks $15\\mathrm{mm}$ in diameter, $2\\mathrm{mm}$ thick, equilibrated in DMEM for $24\\mathrm{h}$ ) using a previously published method4,35. The gel disks were compressed to $15\\%$ strain with a deformation rate of $1\\mathrm{mm}\\mathrm{min}^{-1}$ using an Instron 3342 single column apparatus. Within $15\\%$ compression, the stress versus strain relations of the gels are almost linear, and the slope of the stress–strain curves (first $5\\mathrm{-}10\\%$ of strain) gives the initial elastic modulus. Subsequently, the strain was held constant, while the load was recorded as a function of time. Compression and stress relaxation measurements of polyacrylamide hydrogels and biological tissues were performed using the same procedure. Polyacrylamide hydrogels were formed following previously established protocols28. In brief, $0.2\\mathrm{g}$ of acrylamide and $_{0.02\\mathrm{g}}$ of bis-acrylamide were dissolved in $2\\mathrm{ml}$ of water. Then \n\n$60\\upmu\\mathrm{l}$ of $137\\mathrm{mg}\\mathrm{ml}^{-1}$ ammonium persulphate and $60\\upmu\\mathrm{l}$ of $70\\mathrm{mg}\\mathrm{ml}^{-1}$ tetramethylethylenediamine (TEMED) were added into above mixture. The solution was mixed and allowed to gel for 6 h. The hydrogel was then equilibrated in PBS for $24\\mathrm{h}$ before mechanical testing. We note that some stress relaxation of the covalently crosslinked hydrogels is observed at longer timescales, but this was previously found to arise from water leaving the hydrogel under bulk compression35. Sprague Dawley Rats (male, seven weeks of age, Charles River Lab) were euthanized in compliance with National Institutes of Health and institutional guidelines. Brain, liver and adipose were collected immediately after euthanization and tested with an Instron 3342 single column apparatus. Bone marrows from multiple rat femurs and tibias were collected fresh after euthanization and allowed to coagulate for 1 h before compression testing. A fracture haematoma from a human patient was retrieved from the bone fracture site at the moment of bone stabilization surgery. The surgery took place seven days after occurrence of the fracture, when the surrounding soft tissue trauma around the fracture gap was sufficiently stabilized. The complete haematoma was collected and processed for mechanical testing within 1 h after surgery. The same procedure of compression and relaxation measurements was performed as with the rat samples, but on a Bose TestBench LM1 system using a $250\\mathrm{g}$ load cell. Care was taken not to test samples that contained bone chips. Fracture haematoma collection was approved by the Institutional Review Board of the Charité University Hospital Berlin, where the collection and testing were performed, and the participant gave written informed consent. Stress relaxation tests that were noisy were smoothed with a Savitzky–Golay filter in Igor Pro (Wavemetrics) with a 4 s window. \n\nCharacterization of gel degradation. For characterization of gel degradation, hydrogels were formed and incubated in culture media at $37^{\\circ}\\mathrm{C}$ for 1 or 7 days. Then, the hydrogels were removed from the incubation medium, frozen, and then lyophilized. The dry mass of the hydrogels was then measured following lyophilization. \n\nCharacterization of gel homogeneity. Gels were formed with RGD–fluorescein-coupled alginates for each rate of stress relaxation with an initial elastic modulus of $9\\mathrm{{kPa}}$ . Gels were incubated in cell culture media in the incubator for one day. Multiple fluorescence images were taken of at least three gels for each of the conditions with a $\\times20$ objective using a laser scanning confocal microscope (Zeiss, LSM 710). ImageJ was used to collect histograms of pixel intensity from each image. \n\nCell culture. 3T3 fibroblasts (ATCC, cells were verified to be free of mycoplasma by the manufacturer) were cultured in standard Dulbecco’s Modified Eagles Medium (DMEM, Invitrogen) with $10\\%$ Fetal Bovine Serum (Invitrogen) and $1\\%$ penicillin/streptomycin (Invitrogen). D1 cells (ATCC, cells were verified to be free of mycoplasma by the manufacturer), clonally derived mouse bone marrow stromal mesenchymal stem cells, were originally obtained from $\\mathrm{Balb/c}\\mathrm{mice}^{51}$ . The D1s were maintained at sub-confluency in DMEM containing $10\\%$ Fetal Bovine Serum and $1\\%$ Pen/Strep. For differentiation experiments, the culture medium was supplemented with $50\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ L-ascorbic acid (Sigma), $10\\mathrm{mM\\beta}$ -glycerophosphate (Sigma) and $0.1\\upmu\\mathrm{M}$ dexamethasone $(\\mathrm{Sigma})^{51}$ . The medium was changed every 3–4 days. \n\nEncapsulation of cells within hydrogels. Cells in flasks were trypsinized using $0.05\\%$ trypsin/EDTA (Invitrogen), washed once in serum-free DMEM, and resuspended in serum-free media at $10\\times$ the final concentration. The concentration of the cells was determined using a Coulter counter (Beckman Coulter). Cells were then mixed well with alginate, also reconstituted in serum-free DMEM using Luer lock syringes (Cole-Parmer) and a female–female Luer lock coupler (Value-plastics). The cell–alginate solution was then rapidly mixed with DMEM containing the appropriate concentration of calcium sulphate, and then deposited between two glass plates spaced $1\\mathrm{mm}$ apart. The solutions were allowed to gel for $45\\mathrm{min}$ , and then disks of hydrogel were punched out and transferred to well plates where they were immersed in media. \n\nImmunohistochemistry. For immunohistochemical staining, media was first removed from the gels. The gels were then fixed with $4\\%$ paraformaldehyde in serum-free DMEM at $37^{\\circ}\\mathrm{C}$ for $30{\\mathrm{-}}45\\operatorname*{min}$ . Gels were then washed three times in PBS containing calcium (cPBS), and incubated overnight in $30\\%$ sucrose in cPBS at $4^{\\circ}\\mathrm{C}$ . The gels were then placed in a mix of $50\\%$ of a $30\\%$ sucrose in cPBS solution, and $50\\%$ OCT (Tissue-Tek) for several hours. Then the media was removed, the gels were embedded in OCT and frozen. The frozen gels were sectioned with a cryostat (Leica CM1950) to a thickness of $30{\\mathrm{-}}100\\upmu\\mathrm{m}.$ , and stained following standard immunohistochemistry protocols. The following antibodies/reagents were used for immunohistochemistry: Rabbit-anti-mouse Collagen-1 polyclonal antibody (Abcam, cat. $\\#34710$ ), YAP antibody (Cell signalling, cat. $\\#4912$ ), Paxillin antibody (Abcam, cat. $\\#32084$ ), $\\upbeta1$ integrin antibody (BD Biosciences, cat. $\\#550531$ ), Prolong Gold antifade reagent with DAPI (Invitrogen), AF-488 Phalloidin to stain actin (Invitrogen), Goat anti-Rabbit IgG AF 647 (Invitrogen). \n\nThe Click-IT EdU cell proliferation assay (Invitrogen) was used to identify proliferating cells. \n\nImage analysis. For measurements of YAP nuclear localization in 3D, images of DAPI/phalloidin/YAP antibody stained cells were taken with a $\\times63~\\mathrm{NA}=1.40$ PlanApo oil immersion objective with a laser scanning confocal microscope (Zeiss, LSM710). Images were thresholded on each colour channel to determine the nuclear area and cell/cytoskeleton area outside of the nucleus. The YAP nuclear localization ratio was then determined as the summed intensity of the YAP signal within the nucleus normalized by the nuclear area divided by the summed intensity of the YAP signal outside of the nucleus normalized by the non-nuclear cytoskeleton area. For quantification of the percentage of MSCs with nuclear YAP shown in Supplementary Fig. 12, the number of cells exhibiting nuclear YAP in cryosection stains was manually counted; this number was then divided by the total number of cells and multiplied by 100 to get a percentage. \n\nSpreading of 3T3 cells was quantified using Imaris software (Bitplane). Z-stack images of DAPI/phalloidin stained cells were taken with a laser scanning confocal microscope. The stacks were analysed using Imaris with the embedded cell body algorithm. The DAPI channel was used for nuclei detection and the phalloidin channel was used for cell body detection. Statistics of the cells were generated by the algorithm, and the longest dimension of the object-oriented bounding box of each cell was determined as an indication of cell spreading. \n\nAnalysis of MSC differentiation. Oil Red O staining was performed on $100{\\upmu\\mathrm{m}}$ frozen sections to probe for neutral lipids. Slides were equilibrated in $60\\%$ isopropanol and stained in $1.8\\mathrm{mg}\\mathrm{ml}^{-1}$ Oil Red O in $60\\%$ isopropanol for $30\\mathrm{min}$ . Frozen sections were probed for alkaline phosphatase by Fast Blue staining. The slides were equilibrated in alkaline buffer ( $\\mathrm{\\cdot}100\\mathrm{mM}$ Tris-HCl, $100\\mathrm{mMNaCl}_{\\mathrm{\\Omega}}$ , $0.1\\%$ Tween-20, $50\\mathrm{mM}$ MgCl2, $\\mathrm{pH}8.2)$ for $15\\mathrm{min}$ and stained in $500\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ naphthol AS-MX phosphate (Sigma) and $500\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ Fast Blue BB Salt Hemi $(Z\\mathrm{nCl})$ salt (Sigma) in alkaline buffer for $60\\mathrm{min}$ . The sections were then washed in alkaline buffer and neutralized in PBS. Von Kossa staining was performed on $30\\upmu\\mathrm{m}$ frozen sections to probe for mineralized matrix. Samples were equilibrated in distilled water and exposed to $3\\%$ silver nitrate solution under ultraviolet light for $1\\mathrm{min}$ . After several dips in distilled water, a $2.5\\%$ sodium thiosulphate solution in $50\\mathrm{mM}$ HEPES with $25\\mathrm{mM}$ CaCl2 was added for $2\\mathrm{min}$ , followed by washes in distilled water. \n\nTo quantify ALP enzyme activity, cells were retrieved from the gels after seven days of culture. Cells were collected by incubation in trypsin for $10\\mathrm{min}$ followed by a PBS wash, and soaking gels in $50\\mathrm{mM}$ EDTA in PBS for $10\\mathrm{min}$ at room temperature. The cells were washed, counted using a Z2 Coulter Counter and lysed for $30\\mathrm{min}$ in lysis buffer $50\\mathrm{mM}$ Tris-HCl, $0.1\\%$ Triton X-100) at $4^{\\circ}\\mathrm{C}$ . $10\\upmu\\mathrm{l}$ of each lysate was added to $100\\upmu\\mathrm{l}4$ -methylumbelliferyl phosphate (4-MUP) substrate (Sigma) and incubated for $25\\mathrm{min}$ at $37^{\\circ}\\mathrm{C}$ . Bovine ALP (Sigma) was used to create a standard curve. After incubation, fluorescence was read by a fluorescent plate reader (BioTek) and measured ALP activity was normalized to cell counts. \n\nColour micrographs of Oil Red $\\scriptstyle\\mathrm{O},$ Fast Blue, and von Kossa staining were acquired using a Nikon E800 upright microscope and an Olympus DP-70 colour camera. \n\nStructural and compositional analyses of the alginate gels were performed with a Tescan Vega environmental scanning electron microscope (SEM) equipped with a Bruker XFlash 5030 energy-dispersive X-ray spectrometer (EDS). Frozen sections of alginate gels with a thickness of $100{\\upmu\\mathrm{m}}$ were attached to a silicon wafer with conductive carbon tape. The gel sections were washed in DI water four times, for $5\\mathrm{min}$ each time to remove any soluble $\\mathrm{Ca^{2+}}$ and phosphate, and dried under vacuum overnight before SEM-EDS. Elemental mapping and compositional analysis of phosphorus for each sample was performed under identical conditions at an accelerator voltage of $20\\mathrm{keV}$ and a pressure of $12\\mathrm{Pa}$ . \n\nFRET measurements of RGD clustering. FRET-based analysis of ligand clustering was carried out through imaging energy transfer between fluorescein-labelled RGD donors and tetramethylrhodamine-labelled RGD acceptors coupled to different alginate chains using confocal microscopy, following a previously established technique4,43. High- and low-MW-PEG alginate were coupled to RGD–fluorescein (RGD–FITC) and RGD–tetramethylrhodamine (RGD–TAMRA) separately, as described above. MSCs were encapsulated in hydrogels that had a final concentration of $40\\upmu\\mathrm{M}$ RGD–FITC and $40\\upmu\\mathrm{M}$ RGD–TAMRA, an initial elastic modulus of $17\\mathrm{kPa}$ or $9\\mathrm{kPa}$ , and different levels of stress relaxation, as described above. The gels were then incubated in phenol red-free complete culture media for $18\\mathrm{h}$ following encapsulation, and then treated with DAPI to stain the nuclei of cells for $10\\mathrm{min}$ . Images of the FRET signal were taken with a laser scanning confocal microscope (Zeiss, LSM710) using a $\\times20$ objective $(\\mathrm{NA}=0.8\\$ ), by exciting the fluorescein donor ( $\\cdot488\\mathrm{nm},$ and collecting emissions from the TAMRA acceptor $(580-720\\mathrm{nm})$ . A confocal 3D stack of images of DAPI and FRET signals was taken for each cell. The $z$ -slice corresponding to the centre of the cell body, or where the cell body took up the maximum area, was selected for image analysis. FRET enhancement for each cell was calculated as the average FRET signal within ${\\sim}2\\ –3\\upmu\\mathrm{m}$ of the cell border divided by the background FRET signal in the hydrogel, which was determined as the average FRET signal ${\\sim}10{-}20\\upmu\\mathrm{m}$ away from each cell. At least 30 cells were analysed for each condition. Images were analysed using ImageJ. \n\nInhibition studies. For pharmacological inhibition studies, the inhibitors were added to the culture media following encapsulation. The concentrations used for each inhibitor were: $25\\upmu\\mathrm{M}$ for ML-7 (Tocris Bioscience); $10\\upmu\\mathrm{M}$ for Y-27632 (Tocris Bioscience); and $25\\upmu\\mathrm{M}$ for NSC 23766 (Tocris Bioscience). These concentrations matched those used in similar studies13,31. Analysis of alkaline phosphatase activity was performed as described above after seven days of culture. \n\n# References \n\n51. Diduch, D. R., Coe, M. R., Joyner, C., Owen, M. E. & Balian, G. Two cell lines from bone marrow that differ in terms of collagen synthesis, osteogenic characteristics, and matrix mineralization. J. Bone Joint Surg. Am. 75, 92–105 (1993). " + }, + { + "id": "10.1002_jcc.24300", + "DOI": "10.1002/jcc.24300", + "DOI Link": "http://dx.doi.org/10.1002/jcc.24300", + "Relative Dir Path": "mds/10.1002_jcc.24300", + "Article Title": "LOBSTER: A Tool to Extract Chemical Bonding from Plane-Wave Based DFT", + "Authors": "Maintz, S; Deringer, VL; Tchougréeff, AL; Dronskowski, R", + "Source Title": "JOURNAL OF COMPUTATIONAL CHEMISTRY", + "Abstract": "The computer program LOBSTER (Local Orbital Basis Suite Towards Electronic-Structure Reconstruction) enables chemical-bonding analysis based on periodic plane-wave (PAW) density-functional theory (DFT) output and is applicable to a wide range of first-principles simulations in solid-state and materials chemistry. LOBSTER incorporates analytic projection routines described previously in this very journal [J. Comput. Chem. 2013, 34, 2557] and offers improved functionality. It calculates, among others, atom-projected densities of states (pDOS), projected crystal orbital Hamilton population (pCOHP) curves, and the recently introduced bond-weighted distribution function (BWDF). The software is offered free-of-charge for noncommercial research. (C) 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.", + "Times Cited, WoS Core": 2363, + "Times Cited, All Databases": 2467, + "Publication Year": 2016, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000374023100008", + "Markdown": "# LOBSTER: A Tool to Extract Chemical Bonding from Plane-Wave Based DFT \n\nStefan Maintz,[a] Volker L. Deringer,[a] Andrei L. Tchougr\u0002eeff,[a,b,c] and Richard Dronskowski\\*[a,d] \n\nThe computer program LOBSTER (Local Orbital Basis Suite Towards Electronic-Structure Reconstruction) enables chemicalbonding analysis based on periodic plane-wave (PAW) densityfunctional theory (DFT) output and is applicable to a wide range of first-principles simulations in solid-state and materials chemistry. LOBSTER incorporates analytic projection routines described previously in this very journal [J. Comput. Chem. 2013, 34, 2557] and offers improved functionality. It calculates, among others, atom-projected densities of states (pDOS), projected crystal orbital Hamilton population (pCOHP) curves, and the recently introduced bond-weighted distribution function (BWDF). The software is offered free-of-charge for noncommercial research. $\\circledcirc$ 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. \n\nDOI: 10.1002/jcc.24300 \n\n# Introduction \n\nMethods for electron partitioning in molecules have been around in quantum chemistry since Mulliken’s ingenious approach for assigning electrons to atoms and bonds.[1] These models and concepts are likewise helpful for periodic systems, so an analogous scheme was introduced within non-variational extended H€uckel (eH) theory[2] and dubbed Crystal Orbital Overlap Population (COOP); pioneered in the 1980s, it proved powerful ever since.[3] With the advent of variational density-functional theory (DFT), the Crystal Orbital Hamilton Population (COHP) scheme was suggested, which partitions energies rather than electrons but otherwise resembles COOP in that it allows to extract chemical interactions between atoms from band-structure calculations.[4] COHPs have been implemented and widely used within TB-LMTO-ASA theory,[5] which is DFT-type but shares with eH the use of localized basis sets for periodic solids. \n\nAs of today, many condensed-matter quantum-mechanical codes employ plane waves (PW), which naturally (and effectively) fulfill Bloch’s theorem but are delocalized by their very nature, making bondanalytical approaches such as COOP and COHP unavailable in PW frameworks. Nonetheless, there are ways to transfer PW to localized functions using projection schemes as pioneered by S\u0002anchez-Portal et al.[6] For large atomic numbers, however, PW become impractical for the near-core regions, so the success of the pseudopotential (PP) approach[7] in computational materials science is easily understandable. Nowadays, Blo€chl’s projector-augmented wave (PAW) method is the most powerful of the PP descendants.[8] To project PAW functions[8] onto localized orbitals (say, of the Slater type), we have recently developed an analytical formalism[9] to apply bond-analytic tools even though the system was brought to selfconsistency in a PW basis; other bond-analytical approaches[10] exist as well. Our technique makes COOP or COHP analyses feasible beyond densely packed systems[9] (such as intermetallics[11]) and can, other than before, be seamlessly applied to scenarios such as molecular crystals[12] or even amorphous matter.[13] \n\nTo facilitate chemical-bonding analyses and other methods for a multitude of systems and applications, we are offering the LOBSTER (Local Orbital Basis Suite Towards Electronic-Structure Reconstruction) software free-of-charge for non-commercial purposes at http://www. cohp.de. In this article, we describe recently developed methodology and functionality added to LOBSTER. A number of illustrative applications are presented, and directions for further reading are given. \n\n# Methods \n\nBefore describing recent developments which have found their way into LOBSTER, we refer the reader to our initial publication[9] for a more comprehensive account of the underlying formalisms, and to the manual shipped with the code for any practical questions. A (simplified) scheme of what LOBSTER does is presented in Figure 1. \n\n# Local basis sets \n\nThe initial step in projection is finding a suitable choice of local auxiliary basis functions. For reasons of simple chemical \n\nThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. \n\n![](images/039483c0e51bc67c636f283d29f3357d238c2435f9849244d717d532cccdf209.jpg) \nFigure 1. Overview of LOBSTER’s functional principle: a quantum-chemical system, characterized by its one-electron (Bloch) wavefunctions $\\varPsi_{j}$ and the according eigenvalues $\\varepsilon_{j}$ (band energies), has been brought to self-consistency using some plane-wave DFT program. A local auxiliary basis is then selected to determine the overlap matrix S and the transfer matrix T between the delocalized and localized representations. From those, the projected coefficient and Hamiltonian matrices $\\pmb{c}^{(\\mathsf{p})}$ and ${\\pmb H}^{(\\mathsf{p})}$ , respectively, are accessible, which allow for various bond-analytic tools. The LOBSTER logo is copyrighted by the Chair of Solid-State and Quantum Chemistry at RWTH Aachen University. \n\ninterpretation, LOBSTER employs minimal basis sets that nonetheless carry the correct nodal behavior in the core region, which is necessary to fit PAW wavefunctions. LOBSTER first came with contracted primitive Slater-type orbitals (STOs) fitted to atomic functions,[14] a reasonable choice for postprocessing bonding information. There are also systems, however, where the bonding situation requires additional basis functions which deviate from those of the corresponding free atoms. In elemental beryllium, for example, its 2p levels are unoccupied in the free atom. For bulk Be, however, the 2p levels do get involved into bonding and define the metallic character, so the Be basis set must also include 2p functions. \n\nFor demonstration, let’s look at the high-temperature phase,[15] body-centered cubic beryllium, $\\beta$ -Be. Its electronic structure was calculated with ABINIT employing the JTH atomic datasets[16] and the GGA-PBE parametrization for exchange and correlation.[17] On the LOBSTER side, the original basis set[14a] and its basis functions (1s and 2s) somehow manage to reconstruct the PAW electronic structure but with an unacceptable absolute charge spilling of roughly $19\\%$ (see below for definitions). For analysis, the differences between the original and projected wavefunctions were calculated and an isosurface at $65\\%$ of the maximum resulting density was plotted for several bands at $T_{\\cdot}$ The fourth band showed enormous deviations (Fig. 2, left) because the basis lacks an orbital of $\\mathsf{p}$ -symmetry, as reasoned before. Adding a 2p function strongly reduces the absolute charge spilling to $1.73\\%$ . For comparison, the $65\\%$ densitydifference maxima decrease by two orders of magnitude (Fig. 2, right). While the functions were added by fitting VASP data, they turn out to be general enough to easily fit other PAW wavefunctions, for example, those calculated by ABINIT, too. \n\nHence, free-atom calculations in large supercells have been performed for all elements up to $Z=96$ (curium) using GGA \n\nPBE[17] as implemented in VASP.[18] In nearly all cases up to $Z=$ 80 (mercury) did the new basis functions match the previously given ones well, and they allowed us to numerically fit and add missing (polarization) functions. Obviously, these new functions had to be orthogonalized with regard to the existing functions of the same l azimuthal quantum number to enlarge the basis sets already available in LOBSTER. In the next step, visual evaluation of the calculated PAW atomic orbitals yielded wavefunctions of the desired symmetry and shape; hence they were corroborated as a valid basis choice. \n\nWhile the basis functions are aligned with the Cartesian axes by default, LOBSTER 2.0.0 supports user-defined rotations of the basis functions as has been described recently;[19] this new feature can be especially useful when isolated, orbitalwise interactions must be studied. \n\n![](images/4e27de778ad151b1b504537c4f6cbc764ea4dad63d365669faabb408776ff4fa.jpg) \nFigure 2. Isosurfaces (in $\\mathring{\\mathsf{A}}^{-3})$ at $65\\%$ of the differences between the ABINIT-based PAW densities and the LOBSTER-projected densities for the fourth band of $\\beta$ -Be at $T$ . On the left side, the basis contains only 1s and 2s functions as given by Bunge et al., whereas on the right this basis was enlarged by 2p functions. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] \n\n# Improved measures for projection quality \n\nBefore analyzing the projected wavefunctions, one must ensure that the auxiliary basis suffices. To do so, S\u0002anchezPortal et al. introduced the so-called “spilling” and “chargespilling” criteria,[6b] which measure the percentage of electronic density lost during projection; this approach was also used in former LOBSTER versions.[9] \n\nNonetheless, in a localized basis, unwanted effects such as the basis-set superposition error[20] or counterintuitive orbital mixing[21] can lead to projected wavefunctions with a norm artificially larger than unity; note that the original spilling criterion correctly assumes that the norm of a projected wavefunction is bound to unity. If this condition is broken, averaging the spilling over multiple bands $j$ and $\\vec{k}$ points may lead to error cancellation such that the projection quality looks better than it actually is. To counteract, LOBSTER 2.0.0 comes with an improved definition which we dub “absolute spilling” $s$ and “absolute charge spilling”, ${\\cal{S}}_{\\cal{Q}},$ defined analogously to its predecessor,[6b] but averaging absolute values: \n\n$$\nS_{\\boldsymbol{Q}}\\mathrm{=}\\frac{1}{N_{j}}\\sum_{\\vec{k}}^{N_{\\vec{k}}}{w_{\\vec{k}}\\sum_{j}^{N_{j}}{\\mathrm{abs}(1-O_{j j}(\\vec{k}))}},\n$$ \n\nwith \n\n$$\n\\bullet(\\vec{k})=\\bullet^{(\\mathfrak{p})}{}^{\\dagger}(\\vec{k})\\bullet(\\vec{k})\\bullet^{(\\mathfrak{p})}(\\vec{k}),\n$$ \n\nwhere $\\mathbf{C}^{(\\mathsf{p})}(\\vec{k})$ and $\\pmb{\\mathsf{S}}(\\vec{k})$ are the coefficient and overlap matrices, respectively, and $w_{\\vec{k}}$ denotes the normalized $\\vec{k}$ point weights. The absolute charge spilling, $s,$ is collected only over occupied bands, that is, those with nonzero occupation numbers, $f_{j}(\\vec{k})\\neq0$ . \n\nAnother way to assess the deviation is given by the rootmean-square error (RMS) of projected wavefunctions. If the PW part of the PAW functions is given on a reciprocal grid at values of ${\\vec{k}}+{\\vec{G}},$ one may define the RMS of the projection (RMSp) by comparing the projected LCAO function $|\\vec{k}+\\vec{G}|X_{j}\\rangle$ to its PAW reference $|\\vec{k}+\\vec{G}|\\Psi_{j}\\rangle$ : \n\n$$\n{\\sf R M S p}=\\sqrt{\\frac{1}{N}\\sum_{\\vec{k},\\vec{G},j}{\\sf a b s}(|\\vec{k}+\\vec{G}|\\varPsi_{j}\\rangle-|\\vec{k}+\\vec{G}|X_{j}\\rangle)^{2}}.\n$$ \n\nThe sum runs over all $N$ vectors $\\vec{k}{+}\\vec{G}$ at each band $j$ in the plane-wave basis. Using the reciprocal representation of the wavefunctions enables us to rewrite the difference in the former equation: \n\nthe projection by LOBSTER anyway [such as the LCAO coefficients $C_{\\mu,j}^{(\\mathsf{p})}(\\vec{k})$ and the Fourier-transforms of the local basis functions $\\tilde{\\chi}_{\\mu}(\\vec{k})],$ or they can be obtained by a Fourier–Bessel transform \n\n$$\n\\bar{\\phi}_{i}(\\vec{\\kappa}){=}4\\pi\\mathsf{i}^{I_{i}}\\int\\bar{\\phi}_{i}(r)j_{I_{i}}(\\mathsf{a b s}(\\vec{\\kappa})r)r\\mathsf{d}r Y_{m_{i}}^{I_{i}}(\\hat{\\kappa}),\n$$ \n\nwhere $\\bar{\\phi}_{i}(\\boldsymbol{r})$ is a shorthand notation for the difference between the all-electron and pseudo-space partial-waves in the PAW method and $\\scriptstyle{\\vec{\\kappa}}={\\vec{k}}+{\\vec{G}}$ . $j_{I}(x)$ designates the spherical Bessel function, and $Y_{m}^{I}(\\vartheta,\\varphi)$ is a spherical harmonic. \n\nIn contrast to the originally defined spilling, the RMSp method is bound to zero independent of assumptions, which makes it a well-suited optimization criterion. If desired, one may normalize RMSp to the range of reference data, viz. $\\mathsf{m a x}(|\\vec{k}+\\vec{G}|\\varPsi_{j}\\rangle){\\-}\\mathsf{m i n}(|\\vec{k}+\\vec{G}|\\varPsi_{j}\\rangle)$ , for example, when comparing results from primitive unit cells to those from supercell models, a rather practical real-world scenario. \n\n$$\n\\begin{array}{c}{{\\displaystyle{|\\vec{k}+\\vec{G}|\\:\\psi_{j}\\rangle-|\\vec{k}+\\vec{G}|X_{j}\\rangle=C_{\\vec{G},j}^{\\mathsf{P W}}(\\vec{k})+\\sum_{i}\\bar{\\phi}_{i}(\\vec{k}+\\vec{G})\\langle\\tilde{p}_{i}|\\tilde{\\psi}_{j}\\rangle}}}\\\\ {{{-\\displaystyle\\sum_{\\mu}C_{\\mu,j}^{(\\mathsf{p})}(\\vec{k})\\tilde{\\chi}_{\\mu}(\\vec{k}+\\vec{G}).}}}\\end{array}\n$$ \n\nAll of these expressions are either known directly from the PAW calculation (like the plane-wave coefficients $C_{\\vec{G},j}^{\\mathsf{P W}}(\\vec{k})$ and so-called wavefunction characters $\\langle\\tilde{p}_{i}|\\tilde{\\Psi}_{j}\\rangle$ , evaluated during \n\n# Orthonormalization \n\nAs stated before, the targeted analytic methods are bound to minimal basis sets on purpose and hence prevent using sophisticated multi- $\\cdot\\zeta$ basis sets easily. Consequently, we apply L€owdin’s symmetric orthonormalization (LSO) to the projected wavefunctions.[9] Even if significant (but comparable) amounts of charge are lost around every atom, this technique was found to ensure properly projected densities of states (pDOS), a crucial ingredient for other bond-analytical tools in the sequel. \n\nWithin LOBSTER 2.0.0, LSO is also applied to the basis functions themselves. We note that traditional COHP analysis by means of TB-LMTO-ASA theory[5] works with an intrinsically orthogonal basis set which overlaps due to the atomicspheres-approximation: likewise, the basis functions in LOBSTER do overlap. To improve correspondence between traditional COHP and its projected analogue, the projected Hamiltonian matrix ${\\pmb H}^{(\\mathrm{p})}(\\vec{k})$ is now reconstructed after likewise applying LSO to the basis functions, yielding \n\n$$\n{\\pmb{H}}^{(\\mathrm{p})}(\\vec{k}){\\pmb{C}}^{(\\mathrm{p})\\prime}(\\vec{k}){=}{\\pmb{C}}^{(\\mathrm{p})\\prime}(\\vec{k}){\\pmb{\\varepsilon}}(\\vec{k}),\n$$ \n\nwhere ${\\pmb C}^{(\\mathsf{p})\\prime}(\\vec{k})$ designates the coefficient matrix within the orthogonalized set of basis functions. In contrast, all other bond-analytic tools such as projected COOP still use $\\pmb{C}^{(\\mathfrak{p})}(\\vec{k})$ since the overlap populations would be rendered meaningless in an orthogonal basis set. \n\n# Visualization \n\nExamining the causes of an imperfect projection is a nontrivial task but may be significantly simplified by visual inspection. To do so, the internal development version of LOBSTER writes the values of both projected and PAW wavefunctions on a user-defined, linearly equidistant grid which can either be an arbitrarily oriented line or a threedimensional grid within a cuboid, both bounded by the unit cell. This enables density-difference plots as shown in Figure 2, but can also be used to examine the signed wavefunctions directly. \n\n![](images/77ee341dac72e7a8e170608613a0ff1b68c71d5ce645b060234f8fbd687712ea.jpg) \nFigure 3. LOBSTER analysis of a diffusion pathway through crystalline GeTe, as originally mapped out using nudged-elastic-band (NEB) theory[35a] and previously analyzed by pCOOP analysis in the thesis of one of us.[38] Top: structural drawing of the supercell setup, with only selected atoms shown for clarity.[38] A germanium atom jumps from one octahedron into an adjacent one; a second one further away serves as reference. Bottom: pCOHP analysis for the sum of the three short Ge–Te bonds shown, respectively. Energy is shifted so that the Fermi level eF equals zero. \n\n# Technical aspects \n\nLOBSTER is written in modern, object-oriented $\\mathsf{C}++$ and uses the famous Boost library[22] for various algorithms and concepts for object or memory management, as well as their organization. Even though many of them were incorporated into the $\\mathsf{C}++11$ standard, Boost is still a valuable asset for mathematical special functions and interaction with the operating system. Furthermore, LOBSTER has evolved into a multiplatform tool, supporting Linux, Windows and OS X. Wherever possible, it employs matrix or vector algebra to employ the data structures and algorithms, for example, for matrix decompositions, provided by the highly efficient Eigen library.[23] Results of computationally expensive but repeatedly evaluated functions are cached internally. LOBSTER is parallelized using \n\nOpenMP, still making efficient use of its internal caches through multiple-readers/single-writer lock patterns. To optimize CPU usage, LOBSTER uses memory mapped I/O to read large chunks of input data from the file system when available and beneficial. \n\nAt present, LOBSTER 2.0.0 processes and analyzes PAW results from two third-party codes, VASP[18] and ABINIT,[24] but further interfaces are possible. Due to lack of direct tabulation in the case of ABINIT, the projector functions $\\tilde{p}_{i}(r)$ must be transformed to reciprocal space once using the Fourier–Bessel transform, as stated above. \n\n# Program Features \n\nOnce the coefficient matrix has been reconstructed (Fig. 1), LOBSTER can readily calculate pDOS and pCOOP by $\\vec{k}$ space integration.[9] Additionally, it writes their energy-integrated counterpart IpDOS (which yields the total number of electrons of the respective atoms, Mulliken’s gross population) and IpCOOP (Mulliken’s overlap population). Based on these IpCOOP values, bonding analysis can be applied even to amorphous structures by means of the recently proposed bond-weighted distribution function (BWDF).[13] The coefficient matrices have also been used directly to analyze orbital mixing (or hybridization in the physicists’ language).[25] Reconstructing the Hamiltonian matrix in a second step facilitates pCOHP analysis.[9,26] Energy integration up to the Fermi level yields IpCOHP, which might likewise serve as a bondweighting indicator for BWDF.[13] For further detail on each specific method, we redirect to the original literature. \n\n# Applications \n\nSince its initial publication, LOBSTER has found diverse applications. Being interfaced to state-of-the-art DFT codes such as VASP, it allows to process output from modern methods such as hybrid-DFT results.[27] LOBSTER has begun to play its part in surface chemistry: exploring oxide catalysts,[28] square-planar carbon at transition-metal surfaces,[29] or local structural fragments at quartz-type $\\mathsf{G e O}_{2}$ surfaces.[30] Less-than-densely packed three-dimensional (3D) networks have been of interest as well: complex clathrate structures,[31] hydrogen bonding in molecular crystals,[12] or the stability ranking of metal azide polymorphs.[32] \n\nWe round out this article by presenting two representative applications from fields of current research interest. \n\n# Atomic motion in phase-change materials \n\nPhase-change materials (PCMs) can be switched between crystalline and amorphous phases, and thus be used to encode “ones” and “zeroes” in digital data storage.[33] Atomistic simulations, generally a cornerstone of PCM research,[34] have recently been concerned with transition pathways and atomic motion in crystalline PCMs.[35] \n\nThe prototypical PCM germanium telluride (GeTe) has been studied using COHPs more than a decade ago using TB-LMTO-ASA theory.[36] With the new projection techniques at hand, we may now explore not only its crystalline and amorphous phases,[13] but also the formation and diffusion of vacancies on the crystalline (distorted rocksalt-type) lattice, as visualized in Figure 3 (top). The well-known presence of antibonding interactions in PCMs[37] is also seen in LOBSTER output (Fig. 3, bottom). While these regions $(-\\mathsf{p c o H P}<0)$ are there both for the moving atom (red) and away from the transition state (gray), they critically depend on the local environment: the antibonding peaks are much more dominant in the transition-state geometry (Fig. 3, bottom left). This reflects the moving Ge atom which has to “squeeze” through an octahedral face to leave its groundstate position, which costs over $100~\\mathrm{kJ/mol}$ according to DFT simulations.[35a] Further away, on the contrary, the bonding situation seems relatively unperturbed (Fig. 3, bottom right) and compares well to what is found in the ground-state structure. The bonding analysis also allows us to rationalize previously made observations regarding Fermi level tuning: lowering it makes the transition state $(\\ddagger)$ less unfavorably bonded, and thus reduces the activation energy for the Ge hop significantly.[35a,38] \n\n![](images/ed6fbf9e41f9aecdc992904fb5910682bd4cecc52ce8f37d1486f09ecc6ad7f6.jpg) \nFigure 4. Bonding analysis of $\\alpha$ -iron using (left) COHP as implemented in TB-LMTO-ASA in a non-magnetic (NM) setup and (middle) using ${\\mathsf{p c o H P}}$ based on PAW results by VASP processed with LOBSTER. By allowing for spin polarization (SP, right), the resulting exchange splitting affects the chemical bonding between the Fe atoms which becomes stronger. COHP and ${\\mathsf{p c o H P s}}$ are given as the sum over all symmetry-equivalent bonds in the unit cell. Energy is shifted so that the Fermi level eF equals zero. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] \n\n![](images/56d0e59b2063366d9657e5259588f2039bc08f3c37987f51a579b62f89374277.jpg) \nFigure 5. Spin polarization and chemical bonding in a two-dimensional Ru sheet supported on an Ag(001) surface. The left-hand side shows the supercell setup, and a large “vacuum” area is clearly visible, as commonly used in PW based DFT simulations of surfaces and nanomaterials. The right-hand side shows the LOBSTER-computed ${\\mathsf{p c o H P}}$ curve for a single nearest-neighbor Ru–Ru contact in the spin-polarized case; compare with Figure 4 (right). Energy is shifted so that the Fermi level $\\varepsilon_{\\mathsf{F}}$ equals zero. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] \n\n# The orbital origins of ferromagnetism, revisited: from $\\pmb{\\alpha}$ -iron to Ru monolayers \n\nFerromagnetism of $\\alpha$ -Fe can be chemically understood as a consequence of orbital interactions which has previously been rationalized at the hand of COHP analysis,[39] and this concept later served as a predictive guideline for the design of more complex magnetic materials.[11,40] Figure 4 (left) presents a COHP analysis based on a traditional TB-LMTO-ASA calculation at the spin-restricted (non-magnetic, NM) GGA level showing occupied antibonding levels at the Fermi level which destabilize the system. The middle and right of Figure 4 offer analogous analyses, but employ the methods and frameworks given in this work. In the non-magnetic case, the VASP/LOBSTER combination recovers what has been known before. By switching on spin-polarization, the majority (a) electrons lower in energy (and its associated spin orbitals spatially contract) while the minority $(\\beta)$ electrons increase energetically (and its orbitals expand);[39] as a result, antibonding states are diminished and the chemical bonding strengthens. \n\nWhile the above is merely validation, the new method (in contrast to TB-LMTO-ASA theory) can easily handle “open” systems such as two-dimensionally extended surface structures. Magnetism in such systems has been explored earlier, and one of them is shown in Figure 5 (left): a monolayer of ruthenium atoms supported on a slab of Ag. As originally predicted by Bl€ugel,[41] ruthenium becomes ferromagnetic in this configuration. Figure 5 (right) now delves into the chemical-bonding nature again, and it suggests an explanation that is principally analogous to the $\\alpha$ -iron case: namely significant exchange splitting and strengthening of the Ru–Ru bonds while becoming ferromagnetic, now so easily rationalized using LOBSTER. \n\n# Conclusions \n\nWe have presented new developments in the LOBSTER software for chemical-bonding analysis. LOBSTER processes delocalized PAW wavefunctions calculated with VASP or ABINIT and performs projection into an auxiliary LCAO basis, which makes bond-analytic tools such as pDOS, pCOOP, and pCOHP accessible for state-of-the-art plane-wave based PAW simulations. \n\nTo reliably assess the quality of the projection, we here introduced two modified criteria, dubbed absolute (charge) spilling and root-mean-square of the projection (RMSp). Additionally, visual evaluation of either the PAW or the projected wavefunctions has been demonstrated. A new and improved basis set available in LOBSTER has also been described. Finally, to improve correspondence to traditional COHP analysis based on LMTO theory, we now also apply L€owdin’s symmetric orthogonalization to the basis functions. \n\n# Acknowledgments \n\nWe thank Marc Esser for reviewing the basis rotation code. We are also thankful to Janine George and all other group members who carefully tested the internal code versions, as well as to many users worldwide for their ongoing and valuable feedback. The work of V.L.D. and R.D. on LOBSTER analyses of phasechange materials has been supported by Deutsche Forschungsgemeinschaft (DFG) within SFB 917 (Nanoswitches). V.L.D. gratefully acknowledges a scholarship from the German National Academic Foundation (Studienstiftung des deutschen Volkes). \n\nKeywords: chemical bonding $\\cdot\\cdot$ plane waves $\\cdot^{\\ast}$ DFT $\\cdot^{\\cdot}$ projection $\\cdot\\cdot$ COHP \n\nHow to cite this article: S. Maintz, V. L. Deringer, A. L. Tchougr\u0002eeff, R. Dronskowski. J. Comput. Chem. 2016, 37, 1030– 1035. DOI: 10.1002/jcc.24300 \n\n[1] (a) R. S. Mulliken, J. Chem. Phys. 1955, 23, 1833; (b) R. S. Mulliken, J. Chem. Phys. 1955, 23, 1841; (c) R. S. Mulliken, J. Chem. Phys. 1955, 23, 2338; (d) R. S. Mulliken, J. Chem. Phys. 1955, 23, 2343. [2] (a) R. Hoffmann, J. Chem. Phys. 1963, 39, 1397; (b) R. Hoffmann, J. Chem. Phys. 1964, 40, 2745; (c) R. Hoffmann, J. Chem. Phys. 1964, 40, 2474. [3] T. Hughbanks, R. Hoffmann, J. Am. Chem. Soc. 1983, 105, 3528. [4] R. Dronskowski, P. E. Blo€chl, J. Phys. Chem. 1993, 97, 8617. [5] O. K. Andersen, O. Jepsen, Phys. Rev. Lett. 1984, 53, 2571. [6] (a) D. Sa\u0002nchez-Portal, E. Artacho, J. M. Soler, Solid State Commun. 1995, 95, 685; (b) D. S\u0002anchez-Portal, E. Artacho, J. M. Soler, J. Phys. Condens. Matter 1996, 8, 3859. [7] H. Hellmann, J. Chem. Phys. 1935, 3, 61. [8] P. E. Blo€chl, Phys. Rev. B 1994, 50, 17953. \n[9] S. Maintz, V. L. Deringer, A. L. Tchougr\u0002eeff, R. Dronskowski, J. Comput. Chem. 2013, 34, 2557. \n[10] (a) M. D. Segall, R. Shah, C. J. Pickard, M. C. Payne, Phys. Rev. B 1996, 54, 16317; (b) B. D. Dunnington, J. R. Schmidt, J. Chem. Theory Comput. 2012, 8, 1902; (c) T. R. Galeev, B. D. Dunnington, J. R. Schmidt, A. I. Boldyrev, Phys. Chem. Chem. Phys. 2013, 15, 5022; (d) M. Raupach, R. Tonner, J. Chem. Phys. 2015, 142, 194105. \n[11] J. Brgoch, C. Goerens, B. P. T. Fokwa, G. J. Miller, J. Am. Chem. Soc. 2011, 133, 6832. \n[12] V. L. Deringer, U. Englert, R. Dronskowski, Chem. Commun. 2014, 50, 11547. \n[13] V. L. Deringer, W. Zhang, M. Lumeij, S. Maintz, M. Wuttig, R. Mazzarello, R. Dronskowski, Angew. Chem. Int. Ed. 2014, 53, 10817. \n[14] (a) C. F. Bunge, J. A. Barrientos, A. V. Bunge, Atomic Data Nucl. Data Tables 1993, 104, 113; (b) T. Koga, K. Kanayama, S. Watanabe, A. J. Thakkar, Int. J. Quant. Chem. 1999, 7, 491; (c) T. Koga, K. Kanayama, T. Watanabe, T. Imai, A. J. Thakkar, Theor. Chem. Acc. 2000, 104, 411. \n[15] S. Adhikari, P. Mukhopadhyay, Miner. Process. Extr. Metall. Rev. 1995, 14, 253. \n[16] F. Jollet, M. Torrent, N. Holzwarth, Comput. Phys. Commun. 2014, 185, 1246. \n[17] J. P. Perdew, K. Burke, M. Ernzerhof, Phys. Rev. Lett. 1996, 77, 3865. \n[18] (a) G. Kresse, J. Hafner, Phys. Rev. B 1993, 47, 558; (b) G. Kresse, J. Furthmu€ller, Comput. Mater. Sci. 1996, 6, 15; (c) G. Kresse, J. Furthmu€ller, Phys. Rev. B 1996, 54, 11169; (d) G. Kresse, D. Joubert, Phys. Rev. B 1999, 59, 1758. \n[19] S. Maintz, M. Esser, R. Dronskowski, Acta Phys. Pol. B, in press. \n[20] R. S. Fellers, D. Barsky, F. Gygi, M. Colvin, Chem. Phys. Lett. 1999, 312, 548. \n[21] J. H. Ammeter, H. B. B€urgi, J. C. Thibeault, R. Hoffmann, J. Am. Chem. Soc. 1978, 100, 3686. \n[22] http://www.boost.org. \n[23] G. Guennebaud, B. Jacob, http://eigen.tuxfamily.org, 2010. \n[24] (a) X. Gonze, J. M. Beuken, R. Caracas, F. Detraux, M. Fuchs, G. M. Rignanese, L. Sindic, M. Verstraete, G. Zerah, F. Jollet, M. Torrent, A. Roy, M. Mikami, J. Y. Ph. Ghosez, D. C. Raty, Allan, Comput. Mater. Sci. 2002, 180, 478; (b) X. Gonze, G. M. Rignanese, M. Verstraete, J. M. Beuken, Y. Pouillon, R. Caracas, F. Jollet, M. Torrent, G. Zerah, M. Mikami, Ph. Ghosez, M. Veithen, J. Y. Raty, V. Olevano, F. Bruneval, L. Reining, R. Godby, G. Onida, D. R. Hamann, D. C. Allan, Z. Kristallogr. 2005, 2, 558; (c) X. Gonze, B. Amadon, P. M. Anglade, J. M. Beuken, F. Bottin, P. Boulanger, F. Bruneval, D. Caliste, R. Caracas, M. Cote, T. Deutsch, L. Genovese, Ph. Ghosez, M. Giantomassi, S. Goedecker, D. Hamann, P. Hermet, F. Jollet, G. Jomard, S. Leroux, M. Mancini, S. Mazevet, M. J. T. Oliveira, G. Onida, Y. Pouillon, T. Rangel, G. M. Rignanese, D. Sangalli, R. Shaltaf, M. Torrent, M. J. Verstraete, G. Z\u0002erah, J. W. Zwanziger, Comput. Phys. Commun. 2009, 2582; (d) M. Torrent, F. Jollet, F. Bottin, G. Z\u0002erah, X. Gonze, Comput. Mater. Sci. 2008, 42, 337. \n[25] M. Esser, V. L. Deringer, M. Wuttig, R. Dronskowski, Solid State Commun. 2015, 203, 31. \n[26] V. L. Deringer, A. L. Tchougr\u0002eeff, R. Dronskowski, J. Phys. Chem. A 2011, 115, 5461. \n[27] V. Wang, W. Xiao, D. M. Ma, R. J. Liu, C. M. Yang, J. Appl. Phys. 2014, 115, 043708. \n[28] R. A. van Santen, I. Tranca, E. J. M. Hensen, Catal. Today 2015, 244, 63. \n[29] A. Nandula, Q. T. Trinh, M. Saeys, A. N. Alexandrova, Angew. Chem. Int. Ed. 2015, 54, 5312. \n[30] V. L. Deringer, R. Dronskowski, Chem. Sci. 2014, 5, 894. \n[31] T. Zeng, R. Hoffmann, R. Nesper, N. W. Ashcroft, T. A. Strobel, D. M. Proserpio, J. Am. Chem. Soc. 2015, 137, 12639. \n[32] X. Liu, J. George, S. Maintz, R. Dronskowski, Angew. Chem. Int. Ed. 2015, 54, 1954. \n[33] M. Wuttig, N. Yamada, Nat. Mater. 2007, 6, 824. \n[34] W. Zhang, V. L. Deringer, R. Dronskowski, R. Mazzarello, E. Ma, M. Wuttig, MRS Bull. 2015, 40, 856. \n[35] (a) V. L. Deringer, M. Lumeij, R. P. Stoffel, R. Dronskowski, Chem. Mater. 2013, 25, 2220; (b) M. Xu, W. Zhang, R. Mazzarello, M. Wuttig, Adv. Sci. 2015, 2, 1500117; (c) X. Yu, J. Robertson, Sci. Rep. 2015, 5, 12612. \n[36] U. V. Waghmare, N. A. Spaldin, H. C. Kandpal, R. Seshadri, Phys. Rev. B 2003, 67, 125111. \n[37] M. Wuttig, D. Lu€sebrink, D. Wamwangi, W. Wełnic, M. Gilleßen, R. Dronskowski, Nat. Mater. 2007, 6, 122. \n[38] V. L. Deringer, Dissertation, RWTH Aachen University, Aachen, Germany (2014). \n[39] G. A. Landrum, R. Dronskowski, Angew. Chem. Int. Ed. 2000, 39, 1560. \n[40] (a) R. Dronskowski, K. Korczak, H. Lueken, W. Jung, Angew. Chem. Int. Ed. 2002, 41, 2528; (b) B. P. T. Fokwa, H. Lueken, R. Dronskowski, Chem. Eur. J. 2007, 13, 6040. \n[41] S. Bl€ugel, Phys. Rev. Lett. 1992, 68, 851. " + }, + { + "id": "10.1021_acs.chemmater.6b00847", + "DOI": "10.1021/acs.chemmater.6b00847", + "DOI Link": "http://dx.doi.org/10.1021/acs.chemmater.6b00847", + "Relative Dir Path": "mds/10.1021_acs.chemmater.6b00847", + "Article Title": "Ruddlesden-Popper Hybrid Lead Iodide Perovskite 2D Homologous Semiconductors", + "Authors": "Stoumpos, CC; Cao, DH; Clark, DJ; Young, J; Rondinelli, JM; Jang, JI; Hupp, JT; Kanatzidis, MG", + "Source Title": "CHEMISTRY OF MATERIALS", + "Abstract": "The hybrid two-dimensional (2D) halide perovskites have recently drawn significant interest because they can serve as excellent photoabsorbers in perovskite solar cells. Here we present the large scale synthesis, crystal structure, and optical characterization of the 2D (CH3(CH2)(3)NH3)(2)(CH3NR3)(n-1)PbnI3n+1 (n = 1, 2, 3, 4, infinity) perovskites, a family of layered compounds with tunable semiconductor characteristics. These materials consist of well-defined inorganic perovskite layers intercalated with bulky butylammonium cations that act as spacers between these fragments, adopting the crystal structure of the Ruddlesden-Popper type. We find that the perovskite thickness (n) can be synthetically controlled by adjusting the ratio between the spacer cation and the small organic cation, thus allowing the isolation of compounds in pure form and large scale. The orthorhombic crystal structures of (CH3(CH2)(3)NH3)(2)(CH3NH3)-Pb2I7 (n = 2, Cc2m; a = 8.9470(4), b = 39.347(2) angstrom, c = 8.8589(6)), (CH3(CH2)(3)NH3)(2)(CH3NH3)(2)Pb3I10 (n = 3, C2cb; a = 8.9275(6), b = 51.959(4) angstrom, c = 8.8777(6)), and (CH3(CH2)(3)NH3)(2)(CH3NH3)(3)Pb4I13 (n = 4, Cc2m; a = 8.9274(4), b = 64.383(4) angstrom, c = 8.8816(4)) have been solved by single-crystal X-ray diffraction and are reported here for the first time. The compounds are noncentrosymmetric, as supported by measurements of the nonlinear optical properties of the compounds and density functional theory (DFT) calculations. The band gaps of the series change progressively between 2.43 eV for the n = 1 member to 1.50 eV for the n = infinity adopting intermediate values of 2.17 eV (n = 2), 2.03 eV (n = 3), and 1.91 eV (n = 4) for those between the two compositional extrema. DFT calculations confirm this experimental trend and predict a direct band gap for all the members of the Ruddlesden Popper series. The estimated effective masses have values of m(h) = 0.14 m(0) and m(e) = 0.08 m(0) for holes and electrons, respectively, and are found to be nearly composition independent. The band gaps of higher n members indicate that these compounds can be used as efficient light absorbers in solar cells, which offer better solution processability and good environmental stability. The compounds exhibit intense room-temperature photoluminescence with emission wavelengths consistent with their energy gaps, 2.35 eV (n = 1), 2.12 eV (n = 2), 2.01 eV (n = 3), and 1.90 eV (n = 4) and point to their potential use in light-emitting diodes. In addition, owing to the low dimensionality and the difference in dielectric properties between the organic spacers and the inorganic perovskite layers, these compounds are naturally occurring multiple quantum well structures, which give rise to stable excitons at room temperature.", + "Times Cited, WoS Core": 1704, + "Times Cited, All Databases": 1861, + "Publication Year": 2016, + "Research Areas": "Chemistry; Materials Science", + "UT (Unique WOS ID)": "WOS:000375244500043", + "Markdown": "# Ruddlesden−Popper Hybrid Lead Iodide Perovskite 2D Homologous Semiconductors \n\nConstantinos C. Stoumpos,†,¶ Duyen H. Cao,†,¶ Daniel J. Clark,‡ Joshua Young,§,⊥ James M. Rondinelli,⊥ Joon I. Jang,‡ Joseph T. Hupp,† and Mercouri G. Kanatzidis\\*,† \n\n†Department of Chemistry, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208, United States \n‡Department of Physics, Applied Physics and Astronomy, Binghamton University, P.O. Box 6000, Binghamton, New York 13902, \nUnited States \n§Department of Materials Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, Pennsylvania 19102, \nUnited States \n⊥Department of Materials Science and Engineering, Northwestern University, 2220 Campus Drive, Evanston, Illinois 60208, \nUnited States \n\n\\*S Supporting Information \n\nABSTRACT: The hybrid two-dimensional (2D) halide perovskites have recently drawn significant interest because they can serve as excellent photoabsorbers in perovskite solar cells. Here we present the large scale synthesis, crystal structure, and optical characterization of the 2D $(\\mathrm{CH_{3}}(\\mathrm{CH_{2}})_{3}\\mathrm{NH_{3}})_{2}(\\mathrm{CH_{3}N H_{3}})_{n-1}\\mathrm{Pb}_{n}\\mathrm{\\bar{I}_{3n+1}}$ $(n=1,2,3,4,\\infty)$ perovskites, a family of layered compounds with tunable semiconductor characteristics. These materials consist of well-defined inorganic perovskite layers intercalated with bulky butylammonium cations that act as spacers between these fragments, adopting the crystal structure of the Ruddlesden−Popper type. We find that the perovskite thickness $(n)$ can be synthetically controlled by adjusting the ratio between the spacer cation and the small organic cation, thus allowing the isolation of compounds in pure form and large scale. The orthorhombic crystal structures of $\\mathrm{(\\bar{C}H_{3}(C H_{2})_{3}N H_{3})}_{2}^{\\bullet}$ $\\mathrm{(CH_{3}N H_{3})}$ - $\\mathrm{Pb}_{2}\\mathrm{I}_{7}$ ${\\mathit{n}}=2,$ , $C c2m$ ; $a=8.9470(4)$ , $b=39.347(2)$ Å, $c=8.8589(6)_{,}^{\\setminus}$ , $\\mathrm{(CH_{3}(C H_{2})_{3}N H_{3})_{2}(C H_{3}N H_{3})_{2}P b_{3}I_{10}}$ ${\\mathit{\\check{n}}}=3,$ C2cb; $a=$ 8.9275(6), $b=51.959(4)\\mathring{\\mathrm{A}},c=8.8777(6))$ , and $(\\mathrm{CH_{3}(C H_{2})_{3}N H_{3}})_{2}(\\mathrm{CH_{3}N H_{3}})_{3}\\mathrm{Pb_{4}I_{13}}$ ${n=4,}$ Cc2m; $a=8.9274(4)$ , $b=64.383(4)\\mathring{\\mathrm{A}},$ $c=8.8816(4);$ ) have been solved by single-crystal X-ray diffraction and are reported here for the first time. The compounds are noncentrosymmetric, as supported by measurements of the nonlinear optical properties of the compounds and density functional theory (DFT) calculations. The band gaps of the series change progressively between $2.43\\mathrm{eV}$ for the $n=1$ member to $1.50\\mathrm{eV}$ for the $n=\\infty$ adopting intermediate values of 2.17 eV $\\left(n=2\\right)$ , $2.03\\mathrm{eV}\\left(n=3\\right).$ , and 1.91 eV $\\left(n=4\\right)$ for those between the two compositional extrema. DFT calculations confirm this experimental trend and predict a direct band gap for all the members of the Ruddlesden− Popper series. The estimated effective masses have values of $m_{\\mathrm{h}}=0.14m_{0}$ and $m_{\\mathrm{e}}=0.08\\ m_{0}$ for holes and electrons, respectively, and are found to be nearly composition independent. The band gaps of higher $n$ members indicate that these compounds can be used as efficient light absorbers in solar cells, which offer better solution processability and good environmental stability. The compounds exhibit intense room-temperature photoluminescence with emission wavelengths consistent with their energy gaps, $2.35\\mathrm{eV}\\left(n=1\\right),$ $2.12{\\mathrm{~eV}}{\\left(n=2\\right)},2.01{\\mathrm{~eV}}{\\left(n=3\\right)},$ and $1.90\\mathrm{~eV}\\left(n=4\\right)$ and point to their potential use in light-emitting diodes. In addition, owing to the low dimensionality and the difference in dielectric properties between the organic spacers and the inorganic perovskite layers, these compounds are naturally occurring multiple quantum well structures, which give rise to stable excitons at room temperature. \n\n![](images/f311468c8d921c0234e9f09c86ca29cc5e7068a01fbea77ce205d7304e7643ec.jpg) \n\n# INTRODUCTION \n\nThe class of halide perovskite compounds of the chemical formula $\\mathrm{AMX}_{3}$ $\\mathbf{\\check{A}}=\\mathbf{C}\\mathbf{s}^{\\dagger}.$ , $\\mathrm{CH}_{3}\\mathrm{NH}_{3}^{+}$ , or $\\mathrm{HC}(\\mathrm{NH}_{2})_{2}^{+}$ ; $\\mathbf{M}=\\mathbf{Ge}^{2+}$ , $\\mathrm{Sn^{2+},P b^{2+};X=C l^{-},B r^{-},I^{-})}$ has witnessed a spectacular surge in scientific interest in the last five years and has enabled revolutionary achievements in the field of solid-state photovoltaics.1−9 The recent strong scientific activity in the halide perovskites was triggered by the successful demonstration of $\\mathrm{CH_{3}N H_{3}P b}X_{3}$ $\\left(\\mathrm{X}\\ \\right)=\\ \\mathrm{Br},\\ \\mathrm{I},$ ) as an efficient light absorber1−9 and $\\mathrm{CsSnI}_{3}$ as an efficient hole transporter in dye-sensitized solar cells (DSCs).10,11 These were followed by the utilization of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ as a light absorbing material producing solidstate solar cells with remarkable efficiency in late 2012.12−14 \n\nDespite the astonishing photovoltaic performance, reaching ∼20% conversion efficiency in 2015,15−17 some drawbacks of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ have become evident, with major concerns focusing on the insufficient long-term stability of the devices incorporating these materials and the toxicity of lead.18,19 Although the latter problem could be potentially resolved by replacing $\\mathrm{Pb}$ with the more environmentally friendly Sn metal (a technology still in its infancy),20−25 the former has not yet been addressed in a satisfactory manner. One solution to the long-term stability problem has been recently proposed in the form of the layered iodide perovskites, which are two-dimensional (2D) derivatives of the three-dimensional (3D) perovskite formed by “slicing” the 3D frameworks into well-defined 2D slabs.26,27 The 2D derivatives in hybrid lead iodides have not been studied extensively; however, they offer far more tunability and flexibility in terms of being able to control the physical properties. \n\nFurther motivation for examining the 2D hybrid iodide perovskites in much greater detail comes from recent processingdependent optical responses observed in 3D perovskite films. In particular, we previously observed the formation of red colored films upon spin-coating $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ solutions onto mesoporous $\\mathrm{TiO}_{2}$ films prior to the formation of the expected black $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ film, in addition to slightly varying absorption spectra of CH3NH3PbI3 films with different PbI2 fraction.28 These observations led us to the hypothesis that some intermediate 2D compounds may be formed during the film fabrication process and that these optical responses could be due to quantum confinement effects in either nanoscale variants of perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ or the intrinsic properties of 2D metastable derivative phases. Such confinement effects studied through pair distribution function (PDF) analysis on $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films29 arise from a structurally disordered perovskite dimensionally confined within the nanosized $\\mathrm{TiO}_{2}$ pores and are responsible for a significant blue shift $({\\sim}50\\ \\mathrm{meV})$ of the optical absorption edge. Thus, we set out to study in detail the 2D perovskites as a well-defined example of naturally forming semiconductor materials with quantum confinement. \n\nThe 2D perovskites have the generic chemical formula of $(\\mathrm{RNH_{3}})_{2}(\\mathrm{A}\\mathbf{\\hat{)}}_{n-1}\\mathrm{MX}_{3n+1}$ ( $\\overset{\\cdot}{n}$ is an integer), where ${\\mathrm{RNH}}_{3}$ is a primary aliphatic or aromatic alkylammonium cation acting as a spacer between the perovskite layers, and the A and M cations and X anions form the perovskite framework. The 2D network consists of inorganic perovskite layers of corner-sharing $\\mathrm{[MX_{6}]^{4-}}$ octahedra confined between interdigitating bilayers of long chain alkylammonium cations.30 The unit layers are held together by a combination of Coulombic and hydrophobic forces, which maintain the structural integrity. The existence of the 2D homologous $\\mathbf{M}=\\mathbf{\\mathrm{Pb}}$ series of halide perovskites $(\\mathrm{RNH_{3}})_{2}(\\mathrm{A})_{n-1}\\mathrm{MX}_{3n+1}$ has been known for more than 25 years30,31 and was subsequently demonstrated for the $\\mathbf{M}=\\mathbf{\\mathrm{Sn}}$ series.32−34 Although these 2D halide perovskites are analogues to the oxide perovskites described by Ruddlesden and Popper,35−37 the most wellstudied compounds in the class of 2D halide perovskites are the $(\\mathrm{RNH}_{3})_{2}\\mathrm{MI}_{4}^{-}$ $\\mathbf{\\Phi}(n\\mathbf{\\Phi}=\\mathbf{\\Phi}1)$ family, where $\\mathbf{M}$ is a group $14^{38}$ or lanthanide39 metal, and little is known for the higher members. \n\nThe initial discovery of the 2D perovskites immediately drew attention because these systems can be regarded as natural multiple-quantum-wells in which the semiconducting inorganic layers act as potential “wells” and the insulating organic layers act as potential “barriers”.40,41 The electronic confinement in the perovskite 2D semiconductors in subnanometer layers induces the generation of stable excitons with unusually high binding energy and a Bohr radius that extends beyond the limits of a single layer.31 The exploration of this exciting phenomenon drew the attention of many researchers who devised novel experiments42−47 and performed extensive theoretical analyses48,49 aiming to understand and control the origins of the unique properties of the 2D perovskites. The most remarkable finding was that the stability of the exciton does not arise from the dimensional confinement alone but that the organic material plays an important role by modulating the dielectric properties of the material.50,51 The stability of the exciton in the $n=1$ 2D perovskites gives rise to an intense photoluminescence (PL), which persists even at room temperature. As a result, the 2D perovskites are frequently employed in optical and electronic devices such as field-effect transistors (FETs),34 light-emitting diodes (LEDs),31 and hard radiation detectors.52 The higher $n$ members of the homologous series, however, remain less explored.53−55 They are now of intense interest because of their tunable optical properties, which have led to the fabrication of promising solar cells,26,27 and studies of their photophysical properties.56−58 The lack of extensive synthetic and structural information on the higher 2D perovskites further prompted us to investigate the Ruddlesden−Popper homologous series. \n\nIn this article, we report the scalable synthesis, crystal structure, and optical properties of the homologous 2D series of lead iodide perovskites $\\left(\\mathrm{CH}_{3}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3}\\right)_{2}(\\mathrm{CH}_{3}\\mathrm{NH}_{3})_{n-1}$ $\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}.\\ensuremath{\\mathrm{^{30,46,53,}}}56$ +1.30,46,53,56 We find that the (CH3(CH2)3NH3)2(CH3NH3)- $\\mathrm{Pb}_{2}\\mathrm{I}_{7}$ $\\left(n\\ =\\ 2\\right)$ , $\\mathrm{(CH_{3}(C H_{2})_{3}N H_{3})_{2}(C H_{3}N H_{3})_{2}P b_{3}I_{10}}$ $\\left(n\\ =\\ 3\\right)$ , and $\\mathrm{(CH_{3}(C H_{2})_{3}N H_{3})_{2}(C H_{3}N H_{3})_{3}P b_{4}I_{13}}$ $(n~=~4)$ members combine the structural features of the simple 2D $\\left(n=1\\right)$ and 3D $\\left(n=\\infty\\right)$ perovskite end members. We further find that these intermediate phases exhibit tunable band gaps resulting from quantum confinement due to the dimensional reduction of the perovskite spacer layers. Furthermore, we show that the $n=2{-}4$ compounds display optoelectronic properties that are different from either the $n=1$ or $n=\\infty$ end-members. Thus, they define a novel class of naturally forming superlattice semiconductors with thickness-dependent optical properties reminiscent of the complex quantum-wells in AlGaAs/GaAs heterostructures.59,60 \n\n# EXPERIMENTAL SECTION \n\nStarting Materials. All chemicals were purchased from SigmaAldrich and used as received. Methylammonium iodide (MAI) was synthesized by neutralizing equimolar amounts of a $57\\%\\mathrm{w/w}$ aqueous hydriodic acid (HI) and $40\\%\\ \\mathrm{w/w}$ aqueous methylamine $\\left(\\mathrm{CH}_{3}\\mathrm{NH}_{2}\\right)$ $\\mathrm{(pH\\approx7)}$ ). The white precipitate was collected by evaporation of the solvent using rotary evaporation at $60~^{\\circ}\\mathrm{C}$ under reduced pressure. \n\nFor convenience, we denote the 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite as $\\mathbf{MAPbI}_{3}$ and the 2D $\\left(n\\mathrm{-CH}_{3}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3}\\right)_{2}(\\mathrm{CH}_{3}\\mathrm{NH}_{3})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ family as $\\mathbf{\\widetilde{\\Gamma}}(\\mathbf{BA})_{2}(\\mathbf{MA})_{n-1}\\mathbf{Pb}_{n}\\mathbf{I}_{3n+1}$ $\\overset{\\prime}{\\underset{\\mathrm{\\scriptsize{\\cdot}}}{\\boldsymbol{n}}}=4,3,2,1\\overset{\\cdot}{\\underset{\\mathrm{\\scriptsize{\\cdot}}}{\\boldsymbol{\\mathrm{\\scriptscriptstyle{\\cdot}}}}}$ throughout. \n\nSyntheses. $M A P b I_{3}$ ${\\bf\\tilde{\\it n}}=\\infty)$ . PbO powder $\\left(\\bar{2}232\\mathrm{mg},10\\mathrm{mmol}\\right)$ ) was dissolved in a mixture of $57\\%$ w/w aqueous HI solution $\\mathrm{^{'}10.0~m L,}$ $76\\mathrm{mmol},$ ) and $50\\%$ aqueous $\\mathrm{H}_{3}\\mathrm{PO}_{2}$ (1.7 mL, 15.5 mmol) by heating to boiling under constant magnetic stirring for about $\\ensuremath{5}\\mathrm{{min}}$ , which formed a bright yellow solution. Subsequent addition of solid $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Cl}$ $(675~\\mathrm{{\\dot{m}}\\mathrm{{g}},~10~\\mathrm{{mmol})}}$ to the hot yellow solution initially caused the precipitation of a black powder, which rapidly redissolved under stirring to afford a clear bright yellow solution. The stirring was then discontinued, and the solution was left to cool to room temperature and left to stand overnight to afford black polyhedral crystals. The crystals were collected by suction filtration and dried under reduced pressure. Yield $3.8\\mathrm{~g~}$ $(60\\%)$ . Diffuse reflectance infrared Fourier transformed (DRIFT) spectrum, $(\\mathrm{KBr,cm^{-1}},$ ): 3180br, 2823w, 2711w, 2485w, 2383w, 1820w, 1581s, 1467s, $1248\\mathrm{m}$ , 960s, 910s, $490\\mathrm{m}$ . \n\n$(B A)_{2}(M A)_{3}P b_{4}I_{13}$ $(n=4)$ . PbO powder $\\mathrm{2232~mg,~10~mmol},$ was dissolved in a mixture of $57\\%\\ \\mathrm{w/w}$ aqueous HI solution $\\mathrm{^{'}10.0~m L,}$ $76\\mathrm{mmol}\\mathrm{\\AA}$ ) and $50\\%$ aqueous $\\mathrm{H}_{3}\\mathrm{PO}_{2}$ ( $1.7\\mathrm{mL}$ , 15.5 mmol) by heating to boiling under constant magnetic stirring for about $\\mathsf{S}\\operatorname*{min},$ which formed a bright yellow solution. Subsequent addition of solid $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Cl}$ $(507\\ \\mathrm{\\mg},\\ 7.5\\ \\mathrm{\\mmol})$ to the hot yellow solution initially caused the precipitation of a black powder, which rapidly redissolved under stirring to afford a clear bright yellow solution. In a separate beaker, $n{\\mathrm{-}}\\mathrm{CH}_{3}\\mathrm{(CH}_{2}\\mathrm{)}_{3}\\mathrm{NH}_{2}\\left(248\\mu\\mathrm{L},2.5\\mathrm{mmol}\\right)$ was neutralized with H $[\\mathrm{I}57\\%\\mathrm{w/w}$ $\\left(5\\mathrm{mL},38\\mathrm{mmol}\\right)$ in an ice bath resulting in a clear pale yellow solution. Addition of the $n{\\mathrm{-CH}}_{3}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3}\\mathrm{I}$ solution to the $\\mathrm{PbI}_{2}$ solution initially produced a black precipitate, which subsequently dissolved under heating the combined solution to boiling. The stirring was then discontinued, and the solution was left to cool to room temperature during which time black rectangular-shaped plates started to crystallize. The precipitation was deemed to be complete after ${\\sim}2\\mathrm{h}$ . The crystals were isolated by suction filtration and thoroughly dried under reduced pressure. Yield $2.1\\mathrm{g}$ ( $33\\%$ based on total $\\mathrm{Pb}$ content). DRIFT spectrum, (KBr, $\\mathrm{cm}^{-1}.$ ): 3174br, 2962w, 2929w, $2725\\mathrm{m}$ , 2485w, 2382w, 1815w, 1577s, 1468s, $1250\\mathrm{m},$ , $1149\\mathrm{m},$ , $1072\\mathrm{m}$ , $1034\\mathrm{m},$ , $960\\mathrm{m}$ , 912s, 785w, 735w, 476m. \n\n$(B A)_{2}(M A)_{2}P b_{3}I_{10}$ $(n=3)$ . PbO powder $(2232~\\mathrm{mg},~10~\\mathrm{mmol})$ was dissolved in a mixture of $57\\%\\ \\mathrm{w/w}$ aqueous HI solution $\\mathrm{(10.0~mL,}$ $76\\mathrm{mmol}\\AA$ ) and $50\\%$ aqueous $\\mathrm{H}_{3}\\mathrm{PO}_{2}$ $\\left(1.7\\mathrm{mL},15.5\\mathrm{mmol}\\right)$ by heating to boiling under constant magnetic stirring for about $\\mathsf{S}\\operatorname*{min}$ , which formed a bright yellow solution. Subsequent addition of solid $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Cl}$ $(450\\ \\mathrm{\\mg},\\ 6.67\\ \\mathrm{\\mmol})$ to the hot yellow solution initially caused the precipitation of a black powder, which rapidly redissolved under stirring to afford a clear bright yellow solution. In a separate beaker, $n{\\mathrm{-}}\\mathrm{CH}_{3}\\mathrm{\\bar{(}C H}_{2}\\mathrm{)}_{3}\\mathrm{NH}_{2}$ $\\left(327\\mu\\mathrm{L},3.33\\mathrm{mmol}\\right)$ was neutralized with HI $57\\%$ $\\mathbf{w}/\\mathbf{w}$ $\\cdot\\left(5\\ \\mathrm{mL},38\\ \\mathrm{mmol}\\right)$ in an ice bath resulting in a clear pale yellow solution. Addition of the $n{\\mathrm{-}}\\mathrm{CH}_{3}\\mathrm{(CH}_{2}\\mathrm{)}_{3}\\mathrm{NH}_{3}\\mathrm{\\bar{I}}$ solution to the $\\mathrm{PbI}_{2}$ solution initially produced a black precipitate, which was subsequently dissolved under heating the combined solution to boiling. The stirring was then discontinued, and the solution was left to cool to room temperature during which time deep-red/purple rectangular-shaped plates started to crystallize. The precipitation was deemed to be complete after ${\\sim}2\\mathrm{h}$ . The crystals were isolated by suction filtration and thoroughly dried under reduced pressure. Yield $2.5\\ \\mathrm{g}$ ( $36\\%$ based on total $\\mathrm{Pb}$ content). DRIFT spectrum, $(\\mathrm{KBr,\\cm^{-1}}.$ ): 3174br, 2962w, 2929w, 2873w, $2713\\mathrm{m}$ , 2463w, 2382w, 1810w, 1573s, 1468s, $1389\\mathrm{w},$ 1335w, 1255w, $1149\\mathrm{m}$ , $1072\\mathrm{m}$ , $1017\\mathrm{m}$ , $1001\\mathrm{m}$ , $964\\mathrm{{m},}$ 914s, 785w, 748w, 735w, $484\\mathrm{m}$ . \n\n$(B A)_{2}(M A)P b_{2}I_{7}$ $(n=2)$ . PbO powder $(2232\\ \\mathrm{mg},\\ 10\\ \\mathrm{mmol})$ ) was dissolved in a mixture of $57\\%\\ \\mathrm{w/w}$ aqueous HI solution $\\mathrm{^{'10.0~mL,}}$ $76\\mathrm{mmol}\\AA$ ) and $50\\%$ aqueous $\\mathrm{H}_{3}\\mathrm{PO}_{2}$ $\\left(1.7\\mathrm{mL},15.5\\mathrm{mmol}\\right)$ by heating to boiling under constant magnetic stirring for about $\\mathsf{S}\\operatorname*{min}$ , which formed a bright yellow solution. Subsequent addition of solid $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Cl}$ $(338\\mathrm{~mg,~5~mmol})$ to the hot yellow solution initially caused the precipitation of a black powder, which rapidly redissolved under stirring to afford a clear bright yellow solution. In a separate beaker, $\\ensuremath{n}\\mathrm{-CH_{3}(C H_{2})_{3}N H_{2}}$ $\\left(694\\ \\mu\\mathrm{L},\\ 7\\ \\mathrm{mmol}\\right)$ was neutralized with HI $57\\%$ $\\mathbf{w}/\\mathbf{w}$ $\\left(5\\ \\mathrm{mL},38\\ \\mathrm{mmol}\\right)$ in an ice bath resulting in a clear pale yellow solution. Addition of the $n{\\mathrm{-}}\\mathrm{CH}_{3}\\mathrm{(CH}_{2}\\mathrm{)}_{3}\\mathrm{NH}_{3}\\mathrm{\\bar{I}}$ solution to the $\\mathrm{PbI}_{2}$ solution initially produced a black precipitate, which was subsequently dissolved under heating the combined solution to boiling. The stirring was then discontinued, and the solution was left to cool to room temperature during which time cherry red rectangular-shaped plates started to crystallize. The precipitation was deemed to be complete after ${\\sim}2\\mathrm{~h~}$ . The crystals were isolated by suction filtration and thoroughly dried under reduced pressure. Yield $3.0\\mathrm{~g~}$ ( $41\\%$ based on total $\\mathrm{Pb}$ content). DRIFT spectrum, (KBr, $\\mathsf{c m}^{-1}$ ): 3174br, 2962w, $2929\\mathrm{w}$ , 2880w, 2721w, 2474w, 2389w, 1808w, 1574s, 1468s, 1385w, 1335w, 1255w, $1149\\mathrm{m}$ , $1070\\mathrm{m},$ , $1017\\mathrm{m}$ , $1002\\mathrm{m}$ , $968\\mathrm{{m}}$ , 914s, 785w, $748\\mathrm{m},$ $737\\mathrm{m},$ $476\\mathrm{m}$ . \n\n$(B A)_{2}P b I_{4}(n=1)$ . PbO powder $(2232\\mathrm{mg},10\\mathrm{mmol}$ ) was dissolved in a mixture of $57\\%\\ \\mathrm{w/w}$ aqueous HI solution $\\left(10.0\\ \\mathrm{mL},76\\ \\mathrm{mmol}\\right)$ and $50\\%$ aqueous $\\mathrm{H}_{3}\\mathrm{PO}_{2}$ $\\left(1.7\\ \\mathrm{mL},15.5\\ \\mathrm{mmol}\\right)$ ) by heating to boiling under constant magnetic stirring for about $\\mathsf{S}\\operatorname*{min},$ , which formed a bright yellow solution. Subsequent addition of liquid. In a separate beaker, $\\ensuremath{n}\\mathrm{-CH_{3}(C H_{2})_{3}N H_{2}}$ $\\left(924~\\mu\\mathrm{L},10~\\mathrm{mmol}\\right)$ was neutralized with HI $57\\%$ $\\mathbf{w}/\\mathbf{w}\\left(5\\ \\mathrm{mL},38\\ \\mathrm{mmol}\\right)$ in an ice bath resulting in a clear pale yellow solution. Addition of the $n{\\mathrm{-}}\\mathrm{CH}_{3}\\mathrm{(CH}_{2}\\mathrm{)}_{3}\\mathrm{NH}_{3}\\mathrm{\\bar{I}}$ solution to the $\\mathrm{PbI}_{2}$ solution initially produced a black precipitate, which was subsequently dissolved under heating the combined solution to boiling. The stirring was then discontinued, and the solution was left to cool to room temperature during which time orange rectangular-shaped plates started to crystallize. The precipitation was deemed to be complete after ${\\sim}2\\mathrm{h}.$ The crystals were isolated by suction filtration and thoroughly dried under reduced pressure. Yield $3.5~\\mathrm{g}$ ( $49\\%$ based on total $\\mathrm{Pb}$ content). DRIFT spectrum, $\\left(\\mathrm{KBr,cm}^{-1}\\right..$ ): 3025br, 2960w, 2929w, 2880w, $2739\\mathrm{w},$ $2472\\mathrm{m}$ , $2389\\mathrm{w},$ , $1830\\mathrm{w}$ , 1572s, 1475s, 1385w, $1390\\mathrm{m}$ , 1255w, $1159\\mathrm{m}$ , $1081\\mathrm{m}$ ${1047}\\mathrm{m},$ $1004\\mathrm{{m}}$ , $968\\mathrm{m}$ , 920s, 787w, $737\\mathrm{m}$ , 474m. \n\nCharacterization. Single-crystal X-ray diffraction data were collected using an image plate STOE IPDS II diffractometer using Mo $\\mathrm{K}\\alpha$ radiation $\\overset{\\prime}{\\lambda}=0.{\\overset{\\cdot}{7}}1073\\ \\overset{\\circ}{\\mathrm{A}}_{,}^{\\cdot}$ , operating at $50\\mathrm{kV}$ and $40~\\mathrm{mA}.$ Data reduction and numerical absorption corrections were performed using the X-AREA suite. Single-crystals of the $\\left(\\mathrm{BA}\\right)_{2}\\left(\\mathrm{MA}\\right)_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ compounds were mounted on the end of the glass tip directly from the mother liquor, and the use of glue or dispersion oil was avoided due to the clear deterioration of the crystals. All structures were solved by direct methods and refined by full-matrix least-squares on $\\mathrm{F}^{2}$ using the SHELXTL-2013 program package.61 The PLATON62 functions operating within the WinGX platform63 were used to ensure the validity of the refined crystal structures. \n\nThe structures were refined based on the following considerations. The perovskite lattice $\\{{\\mathrm{Pb}}_{n}{\\mathrm{I}}_{3n+1}\\}$ was refined anisotropically without any constraints on the $\\mathrm{Pb}$ and I atoms. The highly anisotropic shape of the thermal ellipsoids of coordinated iodide ions appears due to a high thermal motion relative to the $\\mathrm{Pb-I}$ bond vector. This is typical for the halide perovskites structures at room temperature, and therefore no special treatment was used.64 All organic atoms were refined isotropically. Restraints were applied to the $\\scriptstyle{\\mathrm{C-C}}$ and $_{\\mathrm{C-N}}$ bond lengths. Each cation was treated as having equivalent thermal parameters. Significant disorder exists in the interlayer cations, particularly for the $\\mathrm{C}\\dot{\\mathrm{H}}_{3}\\mathrm{CH}_{2}-$ tail of butylammonium (the $\\mathrm{NH}_{3}\\mathrm{CH}_{2}\\mathrm{CH}_{2}-$ head is relatively stable), causing the atoms to move and destabilize the refinement. The bond length restraints cannot account for the motion of the interlayer cations. Therefore, the cations were modeled manually on idealized positions based on reasonable bond length and bond angle parameters. Thus, the whole butylammonium cations were constructed on top of the mirror planes imposed by the space group by slightly modifying the positions of the off-plane $\\mathrm{\\DeltaQ}$ peaks found in the electron density map. The mirror planes have the $(x,\\overset{\\cdot}{y},1/4)/(x,y,3/4)$ and $\\scriptstyle(x,y,$ $1/2$ ) coordinates for the Ccmm (and $C c2m$ ) and Acam space groups, respectively, whereas in the case of $C2c b$ where no mirror plane is crystallographically imposed, the cations were modeled based on the initial Q-peaks. In the final steps of the refinement, the $\\{(\\mathrm{CH}_{3}\\mathrm{NH}_{3})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}\\}$ structure segment was refined without restraints, while the butylammonium cations were fixed. The purpose of this treatment was to generate chemically reasonable models without disorder. The modeled cations increase the R-values slightly compared to the unrestrained or disordered refinement and make the e.s.u.’s unrealistically small. Because of this, a BLOC instruction was used to finalize the refinement, which fixed the positions of the butylammonium cations and refined the rest of the atoms separately, to maintain the proper e.s.u.’s of the perovskite layers. \n\nPowder and film X-ray diffraction patterns were collected using a Rigaku MiniFlex $600\\mathrm{X}$ -ray diffractometer $\\mathrm{'Cu}\\mathrm{K}\\alpha,1.5406\\mathring\\mathrm{A},$ operating at $\\bar{4}0\\mathrm{kV}$ and $15~\\mathrm{mA}$ . \n\nScanning electron microscope (SEM) images were acquired at an accelerating voltage of $10{-}20~\\mathrm{kV}$ using either a Hitachi SU8030 or a Hitachi SU3400 instruments equipped with Oxford X-max 80 SDD EDS detectors. \n\nOptical diffuse-reflectance spectra were collected at room temperature using a Shimadzu UV-3600 PC double-beam, double-monochromator spectrophotometer on powdered samples using ${\\tt B a S O}_{4}$ as a $100\\%$ reflectance reference. The samples were irradiated with a halogen (NIR/Visible, 50W, 2000H) and a $\\mathbf{D}_{2}$ lamp (UV, 2000H), and the spectra were recorded using a PbS photoconductive element (NIR) and a PMT (R928) detectors from $2500{-}200~\\mathrm{\\nm}$ . Band gaps were determined as described elsewhere.65,66 \n\nDRIFT spectra were recorded on a Nicolet 6700 IR spectrometer in the $400{-}40\\mathrm{{}}\\mathrm{{00}}\\ \\mathrm{{cm}^{-1}}$ spectral region with KBr beam splitter. \n\nTable 1. Crystal Data and Structure Refinement for $\\scriptstyle\\left(\\mathbf{BA}\\right)_{2}\\left(\\mathbf{MA}\\right)_{n-1}\\mathbf{Pb}_{n}\\mathbf{I}_{3n+1}\\left(n=2-4\\right)$ at 293(2) Ka \n\n\n
empirical formula(BA)(MA)PbI (n = 2)(BA)(MA)Pb3Io (n = 3)(BA)(MA)Pb4I3 (n = 4)
formula weight1483.042103.002722.95
temperature293(2) K
wavelength0.71073A
refinement methodfull-matrix least-squares on F²
cryst systorthorhombicorthorhombicorthorhombic
space groupCc2mC2cbCc2m
colorreddark redblack
unit cell dimensions8.9470(4)8.9275(6)8.9274(4)
a,A39.347(2)51.959(4)64.383(3)
b,A8.8589(6)8.8777(6)8.8816(4)
c,A90°90°90°
α=β= y, deg
volume, A33118.7(3)4118.0(5)5104.9(4)
Z444
density (calc), g/cm3 absorption coeff., mm-13.1593.3923.543
F(000)17.71219.73921.026
cryst size (mm3)256036004640
θ range0.140 × 0.081 X 0.0250.098 X 0.092 X 0.0520.079 × 0.073 × 0.009
completeness to 2.521-25.000°1.568-24.996°2.471-24.999°
index ranges99.7%99.9%99.4%
-10≤h≤10-10≤h≤10-10≤h≤10
-46≤k≤46-61≤k≤61-76≤k≤76
reflns collected-10≤1≤10-10110-10≤1≤10
94521285813717
independent reflns2732 [Rint = 0.0365]3633[Rint = 0.0722]4671 [Rint = 0.0506]
data/restraints/parameters2732/3/793633/3/844671/7/135
GOF1.1451.1030.986
final R indicesRobs = 0.0529Robs = 0.0781Robs = 0.0431
[1>20(1)]wRobs = 0.1394wRobs = 0.1748wRobs = 0.1123
R indices [all data]Rl = 0.0638Ral = 0.1234Rall = 0.0864
largest diff. peak and hole (e A-3)Rall = 0.1478wRall = 0.1997 3.289 and -1.719wRall = 0.1387 1.746 and -1.470
\n\n${}^{a}R=\\Sigma||F_{\\circ}|-|F_{\\mathrm{c}}||/\\Sigma|F_{\\circ}|,{\\mathbf w}R=\\left\\{\\Sigma\\big[{\\mathbf w}\\big(|F_{\\circ}|^{2}-|F_{\\mathrm{c}}|^{2}\\big)^{2}\\big]/\\Sigma\\big[{\\mathbf w}\\big(|F_{\\circ}|^{4}\\big)\\big]\\right\\}^{1/2}$ and $n=2$ , $(0.0916\\mathrm{P})^{2}+15.8934\\mathrm{P}]$ ; $n=4,$ $w=1/[\\sigma^{2}(\\mathrm{Fo}^{2})+(0.0736\\mathrm{P})^{2}]$ , where $P=\\left(F\\mathbf{o}^{2}+~2F\\mathbf{c}^{2}\\right)/3$ . \n\nRaman spectra were recorded on a DeltaNu Advantage NIR spectrometer equipped with a CW diode laser $(785\\ \\mathrm{nm},\\ 60\\ \\mathrm{mW})$ and a CCD camera detector in a backscattered geometry. The powdered samples were packed in standard melting point capillaries $(0.8\\ \\mathrm{mm}\\ \\mathrm{ID}),$ . \n\nPhotoluminescence spectra were collected on oriented rectangular crystals of $(\\mathrm{BA})_{2}(\\mathrm{MA})_{n-1}^{\\circ}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ $(n~=~4,~3,~2,~1)$ and rhombic dodecahedral crystals of $\\mathbf{MAPbI}_{3}$ using Horiba LabRam Evolution highresolution confocal Raman microscope spectrometer $\\mathit{\\Omega}^{\\prime}600\\:\\:\\:\\mathrm{g}/\\mathrm{mm}$ diffraction grating) equipped with a diode CW laser $(473\\ \\mathrm{\\nm},$ $25~\\mathrm{mW}$ ) and a Synapse CCD camera. The incident laser beam was parallel to the (010) direction of the crystals and focused at ${\\sim}1\\mu\\mathrm{m}$ spot size. Unless stated otherwise, the maximum power output of the laser source was filtered to $0.1\\%$ of the maximum power output. \n\nSecond harmonic generation (SHG) and third harmonic generation (THG) spectra were recorded on powdered $(\\mathrm{BA})_{2}(\\mathrm{MA})_{n-1}^{\\bullet}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskite samples and a powdered $\\alpha{\\mathrm{-}}S{\\mathrm{i}}{\\mathrm{O}}_{2}$ reference for a particle size distribution from $90~\\mu\\mathrm{m}-125~\\mu\\mathrm{m}$ placed in standard melting point capillaries $\\mathrm{(0.8~mm~ID)}$ ) using reflection geometry with a fiber-optic bundle as described previously.67,68 The bundle was coupled to a Horiba iHR320 spectrometer ( $600~\\mathrm{g/mm}$ diffraction grating) equipped with a Synapse CCD camera. To prevent absorption effects during the SHG measurement, the fundamental beam from an optical parametric oscillator, pumped by a Nd:YAG laser, was tuned to $\\lambda=1800\\mathrm{nm}$ so that the SHG photon energy $(\\hbar\\omega_{\\mathrm{SHG}}=1.38\\ \\mathrm{eV})$ was below the band gap of all the materials. The incident pulse energy was tuned to $\\sim30\\mu\\mathrm{J}$ using a Glan-Thompson polarizer with a beam spot size of ${\\sim}0.5\\ \\mathrm{mm}$ All detector exposure times were scaled to $ 60\\ s.$ . The THG photon energy on the other hand was above the band gap (except $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4})$ $(\\hbar\\omega_{\\mathrm{THG}}^{\\mathrm{~\\tiny~}}=~2.07~\\mathrm{eV})$ , and therefore THG was significantly underestimated because of the self-absorption processes in the material. However, this absorption effect was properly taken into account for the comparison between SHG and THG using the absorbance data. \n\nComputational Methods. We investigated three of the synthesized compounds using density functional theory: $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4},$ $\\big(\\mathrm{BA}\\big)_{2}\\big(\\mathrm{MA}\\big)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ and $(\\mathbf{\\bar{B}A})_{2}(\\mathbf{MA})_{3}\\mathbf{Pb}_{4}\\mathbf{I}_{13}$ . All calculations were performed with the Vienna ab initio Simulation Package (VASP)69,70 using projector augmented-wave (PAW) potentials within the PBEsol exchange-correlation functional.71,72 We initially generated a centrosymmetric and a noncentrosymmetric structure for each of the three compounds through manipulation of the organic cations, which was inferred by the symmetries identified in the experimental structure refinements. Subsequently, we fixed the lattice parameters and cell volume to those determined in our experiments (Table 1) and fully relaxed the internal atomic positions until the forces were less than $1\\mathrm{meV}\\mathring{\\mathrm{A}}^{-1}$ using a ${500}\\mathrm{eV}$ plane-wave cutoff and $\\quad5\\times1\\times5$ Monkhorst− Pack mesh73 to sample the Brillouin zone. We computed the density of states and band structures in the noncentrosymmetric crystal structures, which were found to be the lowest energy phases in each case using a $5\\times1\\times5$ Monkhorst−Pack mesh and increased $550~\\mathrm{eV}$ planewave cutoff. \n\n# RESULTS AND DISCUSSION \n\nSynthesis. The 2D $(\\mathrm{CH}_{3}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3})_{2}(\\mathrm{CH}_{3}\\mathrm{NH}_{3})_{n-1}$ $\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ family of perovskite compounds $\\scriptstyle(n\\ =\\ 1-4)$ was synthesized from a stoichiometric reaction between ${\\mathrm{PbI}}_{2},$ $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ (MAI), and $n$ -butylamine (BA). A homogeneous solution of concentrated, $\\mathrm{I}_{2}$ -free hydroiodic acid containing stoichiometric amounts of $\\mathrm{PbI}_{2}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ (MA), according to the desired composition, was allowed to react with half the stoichiometric amount of BA by addition of the neutralized base into the boiling acid solution under vigorous stirring. This highly exothermic reaction resulted in the formation of a clear, bright yellow solution, which upon cooling to ambient conditions precipitates into the layered perovskite compounds $\\left(n=2{-4}\\right)$ in the form of colorful rectangular plates with the spectral range spanning from red to black (Figure 1). We find that the use of BA as the reaction limiting reagent is essential in obtaining the compounds in pure form; at the same time, it is detrimental to the reaction yield, which is limited to $\\sim50\\%$ based on the total Pb content due to the high solubility of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ in the $\\mathrm{HI}/\\mathrm{H}_{3}\\mathrm{PO}_{2}$ solvent medium. The employment of this concept takes advantage of the different solubility of the 2D perovskite members in the solvent medium, which increases as the number of perovskite layers increases up to a maximum solubility obtained for the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ end-member ${\\bf\\omega}_{\\bf\\sim}0.6\\ \\mathrm{M}$ at the boiling point). Interestingly, the solubility trend is inverted in intermediate polarity solvents such as acetone or acetonitrile. In these solvents, the 2D compounds are relatively soluble, where the member with the largest organic fraction becomes the most soluble (i.e., $n=1$ ). Using $\\mathrm{{HI}/\\mathrm{{H}}_{3}\\mathrm{{PO}}_{2}}$ as a solvent medium, we find that if BA is used stoichiometrically or MA is used in excess, as has been previously recommended,26,54,74,75 then the end product is contaminated either with the $\\left(n{-}1\\right)$ member in the former case, which acts as a kinetic barrier, or with the $\\left(n+1\\right)$ member in the latter case, which acts as a thermodynamic sink during synthesis of the compounds. Thus, the driving force to guide the reaction into a single $n$ -member product comes from careful control of the stoichiometry based on the “limiting reagent” principle. \n\n![](images/f97315124d080aa8c35a8fae492071fc24b0444d53852e3efc114260022b9e10.jpg) \nFigure 1. SEM images (top) and photographs of the $\\mathrm{(BA)}_{2}(\\mathrm{MA)}_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskite crystals (bottom) (scale bars $=200\\mu\\mathrm{m}\\dot{}$ ). \n\nThe above procedure consists of a scalable and efficient method of preparing these layered compounds in pure form. The reaction scheme described above can be conveniently used to prepare the 2D perovskite members ${\\mathit{\\Psi}}(n=2,3{\\mathit{\\Psi}}$ , and 4), which contradicts a proposed axiom that Ruddlesden−Popper halide perovskites with $n>3$ cannot be isolated in pure form.76 Note that when we attempted to isolate higher members of the 2D series by adjusting the $\\mathrm{Pb}^{2+}/\\mathrm{MA}^{+}$ ratio, the reactions always yielded the $n=4$ member. Nevertheless, we believe that $n>4$ members of the 2D series may be isolated by varying either the nature of the “spacer” (the long chain amine) or the “perovskitizer” (the small organic cation)a hypothesis whose testing lies outside the scope of the present work. To the best of our knowledge, this is the only method by which the individual compounds with $n>2$ can be isolated on a gram scale. The availability of pure bulk materials with $n>2$ facilitates in-depth studies of their photophysical properties and the deployment of the title compounds in future solid-state solar cells.27,77 \n\nCrystal Structure Description. Basic Structural Characteristics. The crystal structures of the $(\\mathrm{BA})_{2}(\\mathrm{MA})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ $\\left(n=1{-}4\\right)$ compounds are shown in Figure 2, and selected crystallographic information is tabulated in Tables 1 and 2. Detailed crystallographic data are provided in the Supporting Information (Section S2). All compounds crystallize in orthorhombic space groups; $(\\mathrm{BA})_{2}\\mathrm{PbI}_{4}$ crystallizes in the primitive centrosymmetric Pbca space group, as previously reported,38,78 whereas $\\big(\\mathrm{BA}\\big)_{2}\\big(\\mathrm{MA}\\big)\\mathrm{\\bar{P}b}_{2}\\mathrm{I}_{7},$ $(\\bar{\\mathrm{BA}})_{2}(\\bar{\\mathrm{MA}})_{2}\\mathrm{Pb}_{3}\\bar{\\mathrm{I}}_{10},$ and $(\\mathbf{BA})_{2}(\\mathbf{MA})_{3}\\mathbf{Pb}_{4}\\mathrm{I}_{13},$ which have been determined in the present study, crystallize in the polar $\\left(C_{2\\nu}\\right)$ , base-centered $C c2m$ $C2c b_{;}$ , and $C c2m$ , space groups, respectively. The noncentrosymmetric configurations represent the case where all MA cations are oriented in the same direction or nearly so, which results in an unquenched net dipole moment within the unit cell. The respective centrosymmetric $\\left(D_{2h}\\right)$ space groups Ccmm, \n\n![](images/c97cc4dd858d833466c6bc2857ebdc7f5406ca276952bc6eff46e8d55d2c5c21.jpg) \nFigure 2. Crystal structures of the 2D lead iodide perovskites, $\\begin{array}{r}{\\big(\\mathrm{BA}\\big)_{2}\\big(\\mathrm{MA}\\big)_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1},}\\end{array}$ extending from $n=1$ to $n=\\infty$ . The $L$ -value denotes the thickness of the inorganic layer in each compound. The numerical values refer to the distance between the terminal iodide ions of each layer and were determined directly from the refined crystal structures. \n\nAcam, and Ccmm, which provide an equally good structural solution, were considered to be less likely on the basis of the wellknown classical crystallographic Hamilton statistical significance criteria,79,80 whereas SHG measurements and DFT calculations, independently, bear out this assignment. Nevertheless, the structural solutions in the centrosymmetric space groups are also provided as a supplement in this work (see Supporting Information) in aid of the quest for addressing the ferroelectric behavior of these compounds by other researchers, as will be discussed in detail in the SHG properties section. We consider the centrosymmetric crystal structures to represent the average structure of the bulk materials, whereas the polar crystal structures may be considered as domains of a polycrystal and may account for the presence of ferroelectric domains where local polarization can be observed. This is supported by our 0 K DFT calculations, presented below, which find the noncentrosymmetric structures to be lower in energy than the centrosymmetric phases. \n\nThe $(\\mathrm{BA})_{2}(\\mathrm{M}\\bar{\\mathrm{A}})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ family joins a handful of other structurally characterized multilayer hybrid halide perovskites $\\left(n>1\\right)$ with a group 14 metal in the octahedral site. These include the $(n=\\bar{2})\\ \\bar{(}\\mathrm{PEA})_{2}(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7}$ $(\\mathrm{in}~P\\overline{{1}})^{30}$ and the very recently reported $(n~=~3)~\\mathrm{(PEA)_{2}(M A)_{2}P b_{3}I_{10}}$ (in P1)26 perovskites (PEA is the phenylethylammonium cation), although the crystal structures have been only tentatively assigned. For the $n=3$ Sn compound $(\\mathrm{BA})_{2}(\\mathrm{MA})_{2}\\mathrm{Sn}_{3}\\mathrm{\\bar{I}}_{10}(\\mathrm{in}C\\mathrm{\\bar{\\itmca}})^{33}$ and the $n=2$ Pb compounds, $(\\mathrm{MBA})_{2}(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7}$ (MBA is the 4-methylbenzylammonium cation),81 $(\\mathrm{TMA})_{2}(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7}$ (TMA is the 2-thienylmethylammonium cation),82 and $(\\mathrm{ABA})_{2}(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7}$ (ABA is the 4-ammoniobutanoic acid cation),83 the Pbcn, $A b a2\\ \\left(\\equiv\\ C2c b\\right)$ and $C2c b$ space groups, respectively, have been rigorously assigned. The unit cell in all compositions contains two inorganic layers and two organic bilayers $(4~\\mathrm{f.u./cell})$ with the inorganic layer defining the ac plane ( $a b$ plane for $n=1$ ) and the organic bilayers intercalating along the $b$ -axis ( $c$ -axis for $n=1$ ). \n\nEach 2D inorganic layer relates to the tetragonal parent 3D compound ${\\bf\\zeta}_{n}=\\infty)$ by slicing the perovskite along the (110) plane such that some of the oriented MA cations are partially $(n=2,3,4,\\ldots)$ or fully $\\left(n=1\\right)$ substituted by the terminal \n\nBA cations.30 Similar to the parent compound, the layers consist of tilted, corner-sharing $[\\mathrm{P}\\hat{\\mathbf{b}}\\ensuremath{\\mathrm{I}_{6}}]^{4-}$ octahedra that propagate in two directions (the ac plane), whereas in the third dimension (the $b$ -axis), the octahedral sheets are physically disconnected by the intercalated organic bilayers. The separation of the inorganic layers results in an increase of the lattice constants as the incorporation of the BA spacers requires a gap of ${\\sim}7.8\\mathring\\mathrm{A}$ between the perovskite layers; the simplest case of $n=1$ has a thickness of ${\\\\hat{\\sim}}6.4{\\ \\hat{\\mathrm{A}}},$ which roughly corresponds to the sum of the two $\\mathrm{Pb-I}$ bond lengths. \n\nAs the 2D perovskite layers grow thicker by introducing MA cations in the crystal structure, the unit cell incrementally expands by addition of a single perovskite layer at a time. These changes in the unit cell can be monitored by X-ray diffraction (XRD), which characteristically reveals an additional low angle reflection for each added perovskite layer (Figure 3a,b). Namely, the $n=2$ analogue shows two evenly spaced reflections, the $n=3$ analogue three, and the $n=4$ analogue four reflections below ${\\sim}2\\theta=14^{\\circ}$ . The $2\\theta$ cut off for numbering is based on the fact that at this angle the $d$ -spacing matches the distance between the discrete perovskite layers in both the 2D [(111) reflection] and 3D perovskites [(110) reflection]. This simple numerical estimation of the crystal structure could be a useful analytical tool for further study of the $\\mathrm{(BA)}_{2}(\\mathrm{MA)}_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ or related Ruddlesden−Popper systems. \n\nThe reported Ruddlesden−Popper perovskites have the same gross symmetry determined by the positions of the heavy atoms (i.e., the $[\\mathrm{Pb}_{n}\\dot{\\mathrm{I}}_{3n+1}]^{-(n+1)}$ layers), but the space groups differ because the nature of the organic spacer indirectly dictates the details of crystal symmetry of the final layered compound. This occurs because the organic spacer component influences the relative rotation and tilting of the $\\left[\\mathrm{PbI}_{6}\\right]^{4-}$ octahedra rather than the MA cations in the cages or the $^{\\alpha}{\\mathrm{MA}}_{n-1}{\\mathrm{Pb}}_{n}{\\mathrm{I}}_{3n+1},$ layers themselves. A similar point has been previously made for the case of the $(\\mathrm{CH}_{3}(\\mathrm{CH}_{2})_{\\mathrm{m}}\\mathrm{\\bar{N}H}_{3})_{2}\\mathrm{PbI}_{4}$ $\\mathrm{{\\acute{n}}}=1,m=3-17\\mathrm{{\\acute{,}}}$ ) series,78,84,85 where it was shown that the compounds undergo a series of temperature-induced, structural phase transitions, with the critical temperature of the transition displaying a strong dependence on the length of the alkyl chain ( $m$ -value). Interestingly, the set of phase transitions in the 2D $\\mathrm{(RNH_{3})_{2}P b I_{4}}$ perovskites strongly resembles the properties of the 3D $\\mathrm{APbI}_{3}$ counterparts, where small changes in the ${\\mathbf A}^{+}$ cation (from Cs to $\\mathrm{CH}_{3}\\mathrm{NH}_{3}$ to $\\mathrm{HC}(\\mathrm{NH}_{2})_{2},$ ) result in similar structural changes in the inorganic $\\{{\\mathrm{PbI}}_{3}\\}^{-}$ frameworks, where $\\alpha\\mathrm{,~}\\beta\\mathrm{.~}$ -, and $\\gamma$ -phases evolve as a function of temperature.64 It is very likely that similar phase transitions exist for the higher members of the 2D perovskite series as well, but because of their complexity, we limit our discussion to the room temperature structures of these compounds in the present manuscript. Such considerations allow us to suggest that the role of the A cations in the 3D perovskites is assumed by the spacer cations in the 2D perovskites. \n\nTable 2. Selected Bond Lengths $[\\hat{\\bf A}]$ and Bond Angles [°] for $(\\mathbf{BA})_{2}(\\mathbf{MA})_{n-1}\\mathbf{Pb}_{n}\\mathbf{I}_{3n+1}$ at 293(2) K with Estimated Standard Deviations in Parentheses \n\n\n
(BA)PbI4 (n = 1)a(BA)(MA)PbI (n = 2)(BA)(MA)PbIo (n = 3)(BA)(MA)Pb4I13 (n = 4)MAPbI (n = ∞0)b
label Pb-I(1)distances 3.205(3)label Pb(1)-1(7)distances 3.081(7)label Pb(1)-I(4)distances 3.065(8)label Pb(1)-I(4)distances 3.12(2)label Pb-I(1)distances 3.125(8)
Pb-I(2) Pb-I(2)'3.1554(18) 3.2072(18)Pb(1)-1(1) Pb(1)-1(2) Pb(1)-I(5) Pb(2)-1(6) Pb(2)-I(3) Pb(2)-I(4) Pb(2)-I(5)3.1561(14) 3.1749(16) 3.249(8) 3.075(6) 3.169(2) 3.1715(19) 3.278(8)Pb(1)-I(1) Pb(1)-I(4)' Pb(2)-I(5) Pb(2)-I(2) Pb(2)-1(3) Pb(2)-1(2)' Pb(2)-I(3)'3.157(3) 3.249(8) 3.047(4) 3.152(6) 3.160(6) 3.170(6) 3.179(6)Pb(1)-I(3) Pb(1)-I(6) Pb(1)-I(2) Pb(2)-1(5) Pb(2)-I(13) Pb(2)-I(1) Pb(2)-I(4) Pb(3)-I(10) Pb(3)-I(8) Pb(3)-I(12) Pb(3)-I(3) Pb(4)-I(11) Pb(4)-I(9) Pb(4)-1(7)3.14(2) 3.154(8) 3.164(8) 3.122(17) 3.156(8) 3.170(8) 3.26(2) 3.06(2) 3.161(8) 3.172(9) 3.27(2) 3.01(2) 3.164(8)Pb-I(1)' Pb-I(2)3.196(8) 3.1613(8)
Pb-I(2)-Pb' 155.38(8) Pb(1)-I(1)-Pb(1)label angleslabelPb(4)-I(5) 3.330(15) (BA)(MA)Pb4I13 (n = 4)label angles
Pb(1)-I(2)-Pb(1)' 164.3(3)173.1(3)Pb(1)-I(1)-Pb(2)angles 169.52(12) 172.28(17)label Pb(2)-I(1)-Pb(2) Pb(1)-I(2)-Pb(1)'angles 166.1(12)Pb-I(1)-Pb' 180
label angles Pb(2)-I(3)-Pb(2)' Pb(2)'-I(4)-Pb(2) Pb(1)-I(5)-Pb(2) aCentrosymmetric reference. Noncentrosymmetric reference.64165.1(4) 167.6(3) 165.62(11)Pb(2)-I(2)-Pb(2)' Pb(2)-I(3)-Pb(2)' Pb(1)-I(4)-Pb(1)' 171.3(3)164.57(15)Pb(1)-I(3)-Pb(3) Pb(1)-I(4)-Pb(2) Pb(2)-I(5)-Pb(4) Pb(1)-I(6)-Pb(1)' Pb(4)-I(7)-Pb(4)' Pb(3)'-I(8)-Pb(3) 170.4(14) Pb(4)'-I(9)-Pb(4) 172.9(14) Pb(3)-I(12)-Pb(3)' 165.5(13)168.8(14) 167.6(12) 167.2(6) 165.0(9) 172.4(12) 162.6(14)Pb-I(2)-Pb' 163.55(6)
\n\nGiven the complexity in assigning the proper space group in Ruddlesden−Popper perovskites, as discussed above, we generated the simulated precession images of reciprocal space from the raw experimental single-crystal diffraction data for the $\\left(\\mathrm{BA}\\right)_{2}\\left(\\mathrm{MA}\\right)_{n-1}\\bar{\\mathrm{Pb}}_{n}\\mathrm{I}_{3n+1}$ family (Figure 3c,d). The data confirm the assigned space groups ( $C c2m$ or Ccmm for $n=2$ , $C2c b$ or Acam for $n=3$ , and $C c2m$ or Ccmm for $n=4{\\dot{\\overline{{\\mathbf{\\rho}}}}},$ ) based on systematically absent reflection conditions; moreover, they uncover an underlying trend that compounds with an odd number of layers $\\left(n\\ =\\ 1,\\ 3\\right)$ systematically adopt a higher symmetry configuration (in terms of increasing space group number) in comparison with the structures consisting of an even number of layers ${\\mathit{\\Omega}}(n=2,4$ ). Such a distinction between crystal structures of the odd and even layers, already established for oxide perovskites of the Ruddlesden−Popper type,86,87 can serve as a guiding principle in predicting the crystal structures of the higher $n$ -members of the $\\left(\\mathrm{BA}\\right)_{2}\\left(\\mathrm{MA}\\right)_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ family. \n\nComparison between the 2D and 3D Perovskites. To elaborate on the structural differences among the compounds, let us first consider the fundamental monolayer consisting of $\\mathrm{^{\\prime}[P b_{9}I_{36}]^{18\\mathrm{-}\\mathrm{9}}}$ units shaded in yellow in Figure 4. In the simplest case of the $\\mathrm{\\big(BA\\big)}_{2}\\mathrm{PbI}_{4}\\mathrm{\\big(}n=1\\mathrm{\\big)}$ compound (Figure 4, left column), a single slab is isolated between the BA ions, which align perpendicular to it as viewed along the [110] direction; the $\\mathrm{\\cdotNH_{3}}^{+}$ “head” of the ammonium cation points toward the center of the rhombic cavity generated by four adjacent octahedra, while the ${\\mathrm{-CH}}_{3}$ “tail” points toward the interlayer space. The accommodation of the $\\mathrm{-NH_{3}}^{+}$ “head” in the near vicinity of the corner-connected octahedra (presumably by electrostatic attraction and aided by $\\mathrm{NH_{2}{-}H{\\cdot}{\\cdot}{\\cdot}I{-}P b}$ hydrogen bonding) forming the perovskite slab forces the octahedra to tilt and induces a $155.20^{\\circ}\\ \\mathrm{Pb-I-Pb}$ angle in $\\mathrm{(BA)}_{2}\\mathrm{PbI}_{4}$ . It is important to point out that the corner-connected octahedra in a single slab always need to rotate in an opposite sense (out-of-phase) to maintain their structural integrity. Interestingly, the other endmember, $\\mathbf{MAPbI}_{3}$ ${\\bf\\tilde{\\rho}}_{n}=\\infty)$ , exhibits similar behavior with respect to octahedral tilting although in a more complex fashion as the octahedral tilting also occurs in the third direction. To better illustrate this point, we define the different $^{\\alpha}[\\mathrm{Pb}_{9}\\mathrm{I}_{36}]^{18-\\prime\\prime}$ units expanding along the $c$ -axis shaded in blue, green, or yellow for clarity purposes (Figure 4, right). The individual “ $\\mathrm{[\\tilde{Pb}_{9}I_{36}]^{18\\rightarrow9}}$ slabs fuse along the [001] direction to form a $\\mathrm{^{\\ast}[P b_{27}I_{81}]^{27-99}}$ box and 3D octahedral network within which the MA cations are contained. The MA cations align along the crystallographic $c$ -axis with the ${\\cdot}\\mathrm{NH_{3}}^{+}$ groups again, as in the case of BA cations, pointing at the center of the $\\mathrm{I}_{4}$ rectangle generated by four adjacent octahedra, causing a significant degree of distortion. As a result of this distortion, the $\\mathrm{Pb-I-Pb}$ angle in $\\mathbf{MAPbI}_{3}$ becomes $163.55^{\\circ}$ . \n\n![](images/cb06aefc0bff317ff5fa5579cb912ecc4ea6461c101e881f35fe8585e0b2f27a.jpg) \nFigure 3. $(\\mathsf{a},\\mathsf{b})$ X-ray diffraction patterns $(\\mathrm{Cu}\\ K\\alpha)$ of the $\\mathrm{(BA)}_{2}(\\mathrm{MA)}_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskites: (a) Bulk powder diffraction and (b) close-up views of the characteristic regions between $2\\theta=2{-}15^{\\circ}$ (left) and $2\\theta=25{-30^{\\circ}}$ (right) where some pronounced differences of the 2D versus 3D perovskites occur. Miller hkl indices are included to describe the strong preferred orientation of the 2D materials. $(\\mathbf{c},\\mathbf{d})$ Precession images of the $\\mathbf{BA}_{2}\\mathbf{M}\\mathbf{A}_{n-1}\\mathbf{P}\\mathbf{b}_{n}\\mathbf{I}_{3n+1}$ simulated from single-crystal X-ray diffraction $(\\mathrm{MoK}\\bar{\\alpha})$ . (c) Images along the (001) direction emphasizing on the characteristic allowed reflections and reflection conditions for the assigned space groups. Note that for $n=1$ , the corresponding direction is (01̅0). (d) Images along the (101̅) direction emphasizing on the ordering of the 2D perovskites with increasing number of layers and with respect to the parent compounds $n=1$ and $n=\\infty$ (top). The green circles correspond to the marked reflections in panel $\\mathbf{b},$ whereas the red circles highlight the number of distinct, extra reflections for the layered perovskites with respect to the 3D perovskite. Note that for $n=1$ and $n=\\infty$ , the corresponding directions is (11̅0), whereas for $n=4$ , the (101) direction is shown for clarity. \n\n![](images/013c119cba49cf536b927444e3509ac982fedb2ea180a9f3a00604a819c8d598.jpg) \nFigure 4. Views of the $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4}$ single-layer $\\left(n=1\\right)$ , $\\left(\\mathrm{BA}\\right)_{2}\\left(\\mathrm{MA}\\right)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ three-layer $\\left(n=3\\right)$ 2D, and $\\mathbf{MAPbI}_{3}$ ${\\bf\\zeta}(n=\\infty)$ 3D lead iodide perovskite crystal structures, highlighting their three-dimensional distortions. The defined “ $\\mathrm{\\bar{[Pb_{9}I_{36}]}}^{\\mathrm{18-9}}$ slabs represent a $3\\times3$ building block of the perovskite in two dimensions and are used as a basic model to visualize the distortion. A single slab is composed of nine corner-connected octahedra (yellow) that distort out-of-phase along the perovskite plane. The tilting scheme in the $n=1$ 2D perovskite can be solely described by a single slab. As the perovskite thickness increases, the $[\\mathrm{Pb}_{9}\\mathrm{I}_{36}]$ 18‑” slabs connect to form $\\^{\\epsilon}[\\mathrm{Pb}_{27}\\mathrm{I}_{81}]^{27-9}$ boxes in three dimensions, which are the representative building units for the three-layer structure in the $n=3$ 2D perovskite and a fragment of the infinite layers in the $n=\\infty$ 3D perovskite. This figure illustrates the difference in the distortion modes of the $n=3$ perovskite emphasizing the in-plane and out-of-plane views of the perovskite slabs. Slabs belonging in different layers have been drawn in different colors (yellow, blue, green) to project the connectivity of the slabs in the third dimension. \n\n![](images/f440b35076d898a3a4099e7c918198ff4157eb36e5d9d2529970bc0acdc6e35b.jpg) \nFigure 5. Optical properties of the $(\\mathrm{BA})_{2}(\\mathrm{MA})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskites (for $n=1,2,34,\\infty)$ . (a) Optical absorption of polycrystalline samples obtained from diffuse reflectance measurements converted using the Kubelka−Munk function $(\\alpha/\\mathrm{S}=(1\\dot{-}R)^{2}/2R)$ .65,66(b) Photoluminescence of oriented crystals with the wide planar facets oriented perpendicular to the laser beam $\\dot{\\lambda}_{\\mathrm{exc}}=473\\mathrm{nm}$ ) with the illumination vector pointing toward the (010) axis for $n=2$ , 3, 4, (001) for $n=1$ and (100) for $n=\\infty$ . Plots a and b are scaled to match; the dashed lines in panel a correspond to the photoluminescence maximum in panel b and are used as a guide to the eye to illustrate the absorption features that correspond to the emission maxima. (c) Plot of the band gap and photoluminesce versus layer thickness with the latter expressed in the form of $1/n^{2}$ . Note that in panels $\\mathsf{a{-}c}$ the energy is plotted in a reciprocal scale and the wavelength in a linear scale. (d) Plot of the exciton energy, defined by convention as the difference in energy of the absorption edge to the emission maximum (see Table 3) versus layer thickness expressed in the form of $1/n^{2}$ . \n\nThe distinct structural features of $\\mathbf{MAPbI}_{3},$ however, become evident when the perovskite begins to self-assemble into $\\mathrm{\\mathrm{'}P b}_{27}\\mathrm{I}_{81}]^{27-}$ boxes”, as shown in Figure 4. The boxes consist of three stacked $\\mathrm{^{\\prime}[P b_{9}I_{36}]^{18\\rightarrow\\ }}$ slabs, which themselves display an outof-phase octahedral distortion and connect along the direction defined by the $\\mathrm{C-N}$ bond while displaying no rotation in the plane perpendicular to the $\\mathrm{C-N}$ bond direction (the $a^{0}a^{0}c^{-}$ tilt pattern in Glazer notation, Figure 4, right column).88 This pattern is characteristic of the 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{MX}_{3}$ perovskites in general and is opposite to the $\\mathrm{CsMX}_{3}^{10}$ and $\\mathrm{H}\\mathrm{\\bar{C}(N H_{2})_{2}M X_{3}}^{64}$ counterparts, which adopt an in-phase tilting ( $\\stackrel{\\cdot}{a^{0}}a^{0}c^{+}$ in Glazer notation) when the $\\overline{{[\\mathrm{Pb}_{9}\\mathrm{I}_{36}]}}^{18-9}$ slabs connect along the unique crystallographic direction. On the basis of the above characteristics, it becomes evident that the nature and orientation of the ammonium cation influence the tilting pattern in the hybrid perovskites and strongly impact the degree of distortion of the inorganic component. \n\nA unique situation arises in the $\\mathrm{(BA)}_{2}(\\mathrm{MA)}_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ multilayered compounds where both MA and BA cations are present, owing to the competition between the two cations trying to satisfy their stereochemical demands. Because the situation is similar for $n=2,$ , 3, and 4, we will limit our discussion to the $n=3$ compound for simplicity (Figure 4, center column). Continuing with the $\\ensuremath{{}^{\\omega}[\\mathrm{Pb}_{9}\\mathrm{I}_{36}]}^{\\mathrm{i}_{8\\mathrm{-}}}$ slab” concept, see Figure 4, we can clearly observe that the configuration of the perovskite slab as well as the perovskite box in $\\mathbf{\\bar{B}}\\mathbf{A}_{2}(\\mathbf{MA})_{2}\\mathbf{Pb}_{3}\\mathbf{I}_{10}^{-}$ differs from both of the parent compounds. The most obvious difference arises from the fact that the out-of-phase rotation axis now coincides with the orientation of BA cations’ (the [010] direction), whereas the plane parallel to the MA cation (the [101] direction) remains relatively undistorted. The term “relatively” is used because the decrease in symmetry from tetragonal $\\left(n=\\infty\\right)$ to orthorhombic $\\left(n=3\\right)$ , which precludes a $180^{\\circ}~\\mathrm{Pb-I-Pb}$ angle connectivity between the octahedra, introduces a small relative rotation. An examination of the placement of the - $\\cdot\\mathrm{NH_{3}}^{+}$ “heads” reveals that the heads of the BA cations appear optimally “centered” in $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4}$ with respect to the perovskite slab, whereas the MA heads lose their ideal alignment by becoming slightly “offcentered” with respect to the perovskite slabs (unlike $\\beta{\\mathrm{-MAPbI}}_{3},$ . In that sense, neither BA nor MA is in its preferred configuration, with BA trying to distort the perovskite along the $b$ -axis and MA trying to distort the ac-plane. \n\nThe net result of this competition is an overall distortion in the intermediate 2D perovskites, which occurs across two different directions (as opposed to $\\mathrm{(BA)}_{2}\\mathrm{PbI}_{4}$ and $\\mathbf{MAPbI}_{3,}^{\\cdot}$ ), but it is less severe compared to the parent compounds due to the competing interactions between MA and BA. For example, in $\\big(\\mathrm{BA}\\big)_{2}\\big(\\mathrm{M}\\bar{\\mathrm{A}}\\big)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ the distortion angles are $\\big(\\mathrm{Pb-I-Pb}\\big)_{010}\\:=\\:$ $169.52^{\\circ}$ , $\\left(\\mathrm{Pb{-}I{-}\\mathrm{Pb}}\\right)_{101}=164.58^{\\circ};$ , and $\\left(\\mathrm{Pb}\\mathrm{-I}\\mathrm{-Pb}\\right)_{101}=172.26^{\\circ}$ . The mixed cation configuration as well as the competition between the constituting cations renders the multilayered perovskites fundamentally different from both the simple 2D single-layer compounds as well as the 3D perovskites and provides them with some unique properties, which will be discussed in detail below. \n\nTable 3. Optical Parameters of the $(\\mathbf{BA})_{2}(\\mathbf{MA})_{n-1}\\mathbf{Pb}_{n}\\mathbf{I}_{3n+1}$ Perovskites \n\n\n
compoundband gap E(ev)excitonic absorption (eV)aphotoluminescence PL (eV)(Eg-PL) (meV)electron effective mass (mexz2)bhole effective mass (mh,x)b
(BA)PbI42.432.352.35800.0820.144
(BA)(MA)PbI2.172.082.1250
(BA)(MA)PbI102.031.962.01200.0970.141
(BA)(MA)Pb4I131.911.851.90100.0940.153
MAPbI1.501.591.60n/a
\n\naPosition of the excitonic peak in the diffuse reflectance spectra. bCalculated at the DFT-PBEsol level in this work. $m_{x z}$ is reported as the average of the effective mass along the $x$ and $z$ directions and is in units of the bare electron mass. \n\nBand Gaps, Electronic Structure, and Photoluminescence. Figure 5 displays the room-temperature absorption and photoluminescence spectra of bulk samples from the $\\mathbf{\\widetilde{\\Gamma}}(\\mathbf{BA})_{2}(\\mathbf{MA})_{n-1}\\mathbf{Pb}_{n}\\mathbf{I}_{3n+1}$ series. The optical absorption edges are remarkably sharp and increase in energy with decreasing $n$ value, from $1.50\\mathrm{eV}$ $\\left(n=\\infty\\right)$ to $2.43\\mathrm{eV}$ $\\left(n=1\\right)$ , a property arising from the dimensional reduction of the 3D perovskite lattice into the lower dimensionality homologous structures (Figure 5a).89−91 From the experimental spectra, we assign the higher energy absorption edge to the band gap of the materials (Table 3). In all compounds, the onset of the optical absorption consists of sharp edges, although occasionally an absorption tail can be observed in samples of the $n=3$ and $n=4$ compounds possibly arising from small impurities of intergrown higher order homologous members. The sharp nature of the absorption edges points toward a direct band gap in all compounds. A similar band gap trend can be also observed from thin-films of these materials deposited by spin coating dimethylformamide (DMF) precursor solutions as we reported previously,27 confirming that thin films of pure 2D compounds can be made by direct deposition onto the substrates. \n\nUsing DFT, we computed the electronic band structure and density of states for the $n=1,3,$ , and 4 structures (Figure 6). All compounds are semiconducting, with the valence band almost exclusively consisting of I $5p$ states with a small amount of Pb 6s character, while the bottom of the conduction band primarily consists of Pb 6p states (Figure 7). The three studied compounds also each exhibit a clear direct band gap. The band gaps are $1.99\\mathrm{eV}$ for $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4},$ $1.78\\ \\mathrm{eV}$ for $\\mathrm{\\big(BA\\big)}_{2}^{-}(\\mathrm{\\bar{M}A})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ and $0.96~\\mathrm{{\\eV}}$ for ( $\\mathbf{BA})_{2}(\\mathbf{MA})_{3}\\mathbf{Pb}_{4}\\mathbf{I}_{13}$ . Although consistently underestimated within DFT at the PBEsol level, we find the same general trend of decreasing band gap with increasing number of perovskite layers to be in agreement with our experimental results (Table 3). \n\nAs with other $\\mathrm{Pb}$ -based metal−organic halide perovskites,92 the bands near the valence and conduction edges are highly dispersive in reciprocal space along the corresponding real-space axes in which the $\\mathrm{PbI}_{6}$ octahedra are corner-connected, indicating small hole and electron effective masses ( $\\cdot m_{\\mathrm{h}}$ and $m_{\\mathrm{e}},$ respectively) along the $x$ and $z$ directions. By applying the parabolic band approximation to the computed electronic structure, we find that $m_{\\mathrm{h}}$ and $m_{\\mathrm{e}}$ are approximately $0.14~m_{0}$ and $0.08~m_{0}$ along both $x$ and $z,$ where $m_{0}$ is the rest electron mass, and are nearly independent of the number of perovskite and spacing layers (Table 3). Because in the Ruddlesden− Popper structure the inorganic semiconducting network is disconnected along the y axis (Figure 1), it has a nearly flat bands along this direction, indicating that the effective masses along this direction are extremely large, which would tend to restrict the charge transport to the $_{x z}$ plane. When spin−orbit interactions (SOIs) are included in our calculations, for example, in the $n=1$ phase, we find the band gap decreases to $1.25\\mathrm{eV},$ and there are changes to the band degeneracies, but the band curvature remains the same; furthermore, the noncentrosymmetric configuration discussed above remains lower in energy than the centrosymmetric. Unfortunately, the large size of the unit cells prevented us from including SOI in the higher order compounds, but we expect the same trends to persist. \n\n![](images/e453dd22ef23a3299f6576e2775f467b92353dfc4c3b3ac4461b4ff5bff72fbc.jpg) \nFigure 6. Electronic band structure of the polar configurations of selected $\\left(\\mathrm{BA}\\right)_{2}\\left(\\mathrm{MA}\\right)_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskites. (a) $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4}$ ${\\bf\\zeta}_{n}=1)$ , (b) $(\\mathrm{BA})_{2}(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ $\\left(n=3\\right)$ , and (c) $(\\mathrm{BA})_{2}(\\mathrm{MA})_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13}$ ${(n=4)}$ along the $\\Gamma(0,0,0)\\mathrm{-X/S}\\big(1/2,0,0\\big)\\mathrm{-U/R}\\big(1/2,0,1/2\\big)\\mathrm{-Z}\\big(0,0,1/2\\big)\\mathrm{-}\\Gamma(0,0,0)$ path (solid vertical lines) throughout the Brillouin zone. The Fermi level is set to $0~\\mathrm{eV}$ and indicated by the horizontal broken red line. \n\n![](images/5c7dfe15080f8981512a5a9d550be9d47d9db484a5377c983a00607f3d54a8dd.jpg) \nFigure 7. Density of states of the polar configurations of selected (BA) $\\mathbf{\\Phi}_{2}(\\mathbf{MA})_{n-1}\\mathbf{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskites. (a) $(\\mathrm{BA})_{2}\\mathrm{\\bar{Pb}I_{4}}$ $\\mathbf{\\Phi}(n\\mathbf{\\Phi}=\\mathbf{\\Phi}1)$ , (b) $\\mathrm{(BA)}_{2}\\mathrm{(MA)}_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}\\mathrm{~(}$ ${\\binom{\\prime}{n}}=3)$ , and (c) $(\\mathrm{BA})_{2}(\\mathrm{MA})_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13}$ $\\left(n=4\\right)$ . Iodine $5p$ (red) and lead 6s (blue) states make up the top of the valence band, while $\\mathrm{Pb}6p$ states (green) form the bottom of the conduction band. \n\nIn addition to the primary absorption edge, we consistently observe another peak below this region appearing in the 2D perovskites. For clarity, the raw reflectance data clearly illustrating the presence of the second peak are also provided in the Supporting Information (Figure S1). The intensity of the second peak is strongest for the $\\textbf{\\textit{n}}=\\textbf{1}$ compound and progressively subsides as the thickness of the inorganic slabs increases reaching a minimum for $n=\\infty$ where the peak sits nearly on top of the absorption edge (Figure 5a). The presence of the secondary absorption in the optical absorption peak spectra of these compounds, which is similar in nature with that observed for the 3D perovskites $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}\\mathrm{Br_{3}},^{93}$ suggests the presence of stable excitons even at room temperature. Because of the presence of excitons, the band gap of the material was estimated by extrapolating the high energy edge (the fundamental edge) to the hypothetical line parallel to the energy axis where the fundamental edge is interrupted by the low energy absorption (the exciton). \n\n$\\mathbf{MAPbI}_{3}$ in itself was reported to have a relatively large exciton binding energy $\\left(E_{\\mathrm{b}}\\right)$ of ${\\sim}\\hat{5}0\\mathrm{meV},^{94,95}$ which becomes smaller in the high-frequency regime due to charge screening from resonant phonons.77 This value has been recently questioned in favor of a negligible binding energy model assuming an exciton Bohr radius of $\\mathrm{\\sim}\\bar{2}0\\mathrm{nm}$ .96 On the other hand, $E_{\\mathrm{{b}}}\\approx400\\mathrm{{meV}}^{40}$ or even $\\boldsymbol{500}\\mathrm{meV}^{58}$ for exfoliated nanosheets has been reported for the $n=1$ 2D perovskite homologue, whereas the estimated energies from the multiple-layer 2D systems tend to float between these two values.46,54 The effect of higher exciton binding energies for lower dimensional perovskites is typical and can be understood in terms of reduced dielectric screening and stronger quantum confinement effects.50,51 A similar effect was observed in few-layered transition metal dichalcogenide systems.97,98 These excitons are favored by the multiplequantum-well nature of these 2D perovskites. \n\nUnlike the artificially constructed quantum well structures of the classical III−V semiconductors (for example, the GaAs/ AlAs/GaAs heterostructures)99 where the excitons are observable only at low temperature, the excitons in $\\mathrm{BA}_{2}(\\mathrm{MA})_{n-1}$ $\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ are stable at room temperature.58 As it has been suggested,41 the stable excitons in the 2D perovskites are due to the Coulombic charge screening effect, which results from the charged nature of the perovskite $\\{\\mathrm{MA}_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}\\}^{2-}$ slabs as opposed to the neutral covalent framework of GaAs-based quantum well structures. The consequence of this difference is that upon generation, the exciton is strongly confined within the built-in electric field between the positive organic spacers and the negative perovskite slabs, which acts upon the photogenerated $\\mathrm{{e}^{-}/\\mathrm{{h}^{+}}}$ pairs inhibiting exciton splitting into free carriers. This in turn causes strong photoluminescence at room temperature (Figure 5b). \n\nWe chose to perform the photoluminescence studies using a confocal microscope setup with a steady-state excitation source $(473\\mathrm{nm})$ on oriented crystals (excitation along (010) direction for $n=2$ , 3, 4, (001) direction for $n=1$ and (100) direction for $n=\\infty$ of the $\\left(\\mathrm{BA}\\right)_{2}\\left(\\mathrm{MA}\\right)_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ compounds. Previous studies have shown both 2D $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4}$ and 3D $\\mathbf{MAPbI}_{3}$ perovskite compounds display photoluminescence at room temperatur e,31,64 although the photoluminescence intensity and wavelength can vary widely based on the preparation conditions. The photoluminescence emission energy of all the 2D perovskites described here decreases with increasing slab thickness similar to the band gap trend (Figure 5). \n\nUnlike the absorption spectra, which are characterized by an absorption edge and an excitonic peak, the photoluminescence spectra consist of one single emission peak corresponding to the energy value of the excitonic peak in the absorption spectra. This is because the relaxation pathway is dictated by direct radiative recombination of an exciton, which is typical for an excitonic material. As predicted from the above 2D effects, the energy differences between the band gap and the photoluminescence emission values (or the excitonic absorption values) decrease with increased $n$ ( $80\\mathrm{meV}$ for $n=1$ to almost $10\\mathrm{meV}$ for $n=4$ ) as shown in Table 3; here, the emphasis is given to the correct trend in this energy difference as a function of $n,$ but the actual exciton binding energies should be more precisely determined at low temperatures. \n\nFor the 3D perovskite, it was challenging to extract the correct bandgap energy due to the spectral proximity between the primary absorption edge and the excitonic peak. In fact, the primary absorption onset at ${\\sim}1.50\\ \\mathrm{eV}$ in Figure 5 (panel a) should be interpreted as the “low-energy tail” of the excitonic transition, not the fundamental band edge $(E_{\\mathrm{g}})$ that is located slightly higher in energy due to the contribution of the exciton binding energy. This picture is indeed in line with the spectral matching of the photoluminescence maximum $(\\sim1.6~\\mathrm{e\\bar{V}})$ and the absorption saturation $\\left({\\sim}1.59\\mathrm{~\\eV}\\right)$ . Another remarkable feature of the photoluminescence spectra is the line shape of the photoluminescence peaks, which is symmetric for the 3D perovskites but not for the 2D analogues. Such a behavior has been recently assigned to trap states in the perovskite framework characteristic of both 2D and 3D perovskites, but the number of trap states has been shown to be higher in the 2D compounds.56,57 \n\nElectronic Structure Calculations and Phase Stability. To obtain further insight into the structural character and electronic structure of these 2D perovskite systems, we performed several investigations using DFT calculations. We first computed the relative energies of $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4}$ $\\mathbf{\\Phi}(n\\ =\\ 1)$ , $(\\mathrm{BA})_{2}^{\\circ}(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ $\\left(n=3\\right)$ , and $\\left(\\mathrm{BA}\\right)_{2}\\left(\\mathrm{MA}\\right)_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13}$ ${\\bf\\chi}_{n}^{\\prime}=4\\bf{\\chi},$ in both the centrosymmetric and noncentrosymmetric crystal structures to evaluate their differences in stability. In $\\left(\\mathrm{BA}\\right)_{2}\\mathrm{PbI}_{4},$ we found that the $P b c2_{1}$ and $P c a b$ phases are energetically degenerate within the precision of our calculations, with the $P b c2_{1}$ structure negligibly lower in energy by $0.58\\mathrm{\\meV/f.u}$ . Although this could support the classification of $\\mathrm{(BA)}_{2}\\mathrm{PbI}_{4}$ into the polar $P b c2_{1}$ symmetry, it more accurately indicates that intergrowths of the two phases is likely, granting local variations in noncentrosymmetry. Remarkably, when the number of perovskite layers is increased to $n=3$ and $n=4,$ the noncentrosymmetric phase becomes significantly more stable than the centrosymmetric structure. In $\\mathrm{\\bar{(BA)}}_{2}\\mathrm{(MA)}_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ we find that the $C2c b$ structure is lower in energy than the centric $\\left(A c a m\\right)$ phase by $527.9~\\mathrm{\\meV/f.u}$ , while in $\\mathrm{\\big(BA\\big)}_{2}\\mathrm{\\big(MA\\big)}_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13},$ the formation energy of the centric structure (Ccmm) lies much higher than that of the acentric $\\left(C c2m\\right)$ space group, which is strongly favored. The results are in good agreement with similar calculations on $\\mathbf{MAPbI}_{3},$ , which predict the acentric $\\left(I4c m\\right)$ structure to lay slightly lower in energy compared to the centric $\\left(I4/m c m\\right)$ structure by $100\\mathrm{meV/f.u.}$ .,100 which is very close to the experimentally determined value of $10.4\\mathrm{kJ/mol}$ $\\stackrel{\\prime}{=}108\\mathrm{meV/f.u.})$ , obtained earlier from temperature-dependent $\\mathrm{^{1}H}$ NMR experiments for the isotropic reorientation of MA ions at room temperature. These large energy differences show that the noncentrosymmetric structures in the 2D perovskite with larger numbers of layers are favorable, despite the weak SHG signal obtained from the compounds experimentally. These initial results reveal that there is a complex interrelationship between the perovskite layer thickness $\\bar{(n)}$ and a yet to be understood correlation length scale required for cooperative lifting of inversion symmetry. Detailed calculations for the structural interrelationships will be explored in a future study. \n\nOur DFT calculations reveal a contrasting trend in the stability of the polar structure in the $(\\mathrm{BA})_{2}(\\mathrm{MA})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskite relative to the experimental SHG results (see Figure 8a below). \n\n![](images/54d7234269cfd169a48a9b1ad4a1b20f684a16b9872bf6d2bf9dbde65751db3f.jpg) \nFigure 8. (a) $I(\\mathrm{SHG})/I_{\\mathrm{q}}(\\mathrm{SHG})$ (solid bars) for powdered samples of $(\\bar{\\mathrm{BA}})_{2}(\\mathrm{MA})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ and $\\mathbf{MAPbI}_{3}$ . The red dashed line is the criterion for the noncentrosymmetry assignment based on the $\\mathrm{SiO}_{2}$ method. (b) SHG/THG (solid bars) for the powdered samples of $\\left(\\mathrm{BA}\\right)_{2}(\\mathrm{MA})_{n-1}$ $\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ and $\\mathbf{MAPbI}_{3}$ . \n\nThe DFT calculations show the $n=1$ compound to be less susceptible to symmetry-breaking, whereas the compound experimentally exhibits the relatively strongest SHG response. Along the same lines, when the number of layers increases and the material acquires 3D-like characteristics, the SHG response declines reaching a minimum (although nonzero) value for the $n=\\infty$ perovskite despite the DFT calculation results predicting an opposite trend. This behavior could possibly be rationalized by the ability of the perovskite to accommodate defects that could generate individual domains with opposing polarity and lead to the expression of residual local polarization. This is reasonable because the MA ions are small enough to realign inside the perovskite cages at a small energy cost; however, the BA ions are relatively rigid and in that sense they “lock” the crystal structure in a preferred configuration. In other words, $\\mathbf{MAPbI}_{3}$ and the 2D slabs favors an acentric configuration that cannot be kinetically maintained because of the MA reorientations, whereas $\\mathbf{\\Sigma}(\\mathrm{BA})_{2}\\mathrm{PbI}_{4}$ favors a centric configuration that once perturbed cannot be kinetically restored. These statements can be further supported by a recent report for the chloride analogue of the $\\textbf{\\textit{n}}=\\textbf{1}$ compound where clear ferroelectric behavior was observed,101 whereas the ferroelectric properties of $\\mathbf{MAPbI}_{3}$ are still under debate.102 An important aspect of the ferroelectricity discussion that cannot be neglected is the light-enhanced polarization observed in perovskites,103,104 an observation that suggests that the generation and motion of domains in the halide perovskites is in fact light-induced, and therefore the polarization of the halide perovskites should be better described in the context of photoferroics.105 \n\nNonlinear Optical Properties of the 2D Perovskites. Although the compounds presented here were assigned as polar, based on crystallographic criteria and DFT calculation, some ambiguity in the assignment of the space group remains. Indirect evidence of the acentricity of the compounds is also provided by means of Raman and IR spectroscopy through the mutual exclusion principle (see Supporting Information, Figure S2), where the vibrational modes that are both IR and Raman active cannot be expressed simultaneously in centrosymmetric compounds, as described previously.68 Although insightful, this comparison is difficult to achieve in the case of the lead iodide perovskites because of the very strong fluorescence, which masks some of the Raman-active vibrational modes and lowers the quality of the spectra. Therefore, to probe if inversion symmetry is present in the structure, we performed SHG and THG measurements on polycrystalline samples of the perovskites. \n\nAll of the 2D compounds and the 3D perovskites displayed weak SHG response as well as THG response. Typically, the SHG signal vanishes for a centrosymmetric compound within the dipole approximation, whereas THG signal is insensitive to the crystal symmetry. The criterion for classifying a material as noncentrosymmetric according to the Kurz-Perry method is satisfied if the SHG ratio between the sample and the known $\\alpha$ -quartz reference $\\left(\\mathrm{SiO}_{2}{:}\\chi^{(2)}=0.6\\mathrm{pm}/\\mathrm{V}\\right);$ , defined as $I({\\mathrm{SHG}})/{\\$ $I_{\\mathrm{q}}(\\bar{\\mathrm{SHG}})$ , is larger than $10^{-2}$ ,106,107 as indicated by the red dashed line in Figure 8, panel a. The measured SHG ratios for the 2D and 3D perovskite samples are rather close to the borderline for considering them to be noncentrosymmetric (red dashed line), with the $n=1$ and $n=2$ perovskites exhibiting SHG signals slightly above the red dashed line and the $n=3$ , $n=4$ and $n=\\infty$ lying slightly below. We have confirmed from repeated, averaged out measurements that there is a general trend of an increasing SHG response with a decreasing thickness of perovskite layers (that is, $\\mathrm{SHG}(n=1)>\\mathrm{SHG}(n=2\\bar{)}>\\mathrm{SHG}(n=3\\bar{)}>\\mathrm{SHG}(n=4)>$ ${\\mathrm{SHG}}(n=\\infty)$ ), which is unusual since the SHG trend opposes the expected behavior, which dictates that the SHG response should increase following the reduction of the band gap. Since in some instances a centrosymmetric medium may yield a small, nonzero SHG response due to secondary effects such as quadrupole transitions and surface-induced processes ,106 the Kurz-Perry method is not an absolute measure but rather a good guideline for the space group assessment. \n\nBecause of the uncertainty inherent to the Kurz-Perry powder method, we proceeded in evaluating the crystal symmetry of the $(\\mathrm{BA})_{2}(\\mathrm{MA})_{n-1}^{-}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskites by employing an alternative method based on the comparison of the relative intensities between the SHG and the THG signals.108 This method is more reliable because any effects arising from extrinsic sources would cancel out in the “ratio” of the two harmonic generation intensities. In principle, SHG as the lower order NLO term should produce a much stronger response than THG in a noncentrosymmetric medium. Figure 8, panel b shows the experimental SHG/THG ratios of the samples and the reference material $\\alpha{\\mathrm{-}}{\\mathrm{SiO}_{2}}$ . To compensate for the THG absorption effect, which produces photons with higher energy than the band gap, we employed a proper correction factor to each material based on its relative absorbance values at the SHG and THG wavelengths, 900 and $600\\mathrm{nm}$ , respectively (discussed above in the context of Figure 5). As expected, the response for $\\alpha{\\mathrm{-}}{\\mathrm{SiO}_{2}}$ SHG dominates over THG for $\\alpha{\\mathrm{-}}{\\mathrm{SiO}_{2}}$ thus confirming that $\\alpha{\\mathrm{-}}\\mathrm{SiO}_{2}$ is indeed noncentrosymmetric. In contrast, all the $\\mathrm{(BA)}_{2}(\\mathrm{MA)}_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ perovskites exhibit a THG response, which dominates over SHG suggesting that the perovskite samples are more likely to be centrosymmetric and that the SHG response occurs mainly through secondary processes. \n\nNevertheless, it is still remarkable that the SHG response from the bulk material, albeit weak, is not negligible. This finite SHG response seems to arise from local symmetry-breaking effects within the highly polarizable structure of the perovskites. Our analysis therefore implies that the perovskite samples can exhibit large local polar domains with differing polarities, but in the overall bulk material “matrix” averages out to centrosymmetric. Similar symmetry-breaking phenomena have also been observed for the noncentrosymmetric artificial GaAs/AlAs quantumwells,109 which could be regarded as the III−IV semiconductor equivalents of the natural quantum-well halide Ruddlesden− Popper systems. \n\nIn view of the NLO results, the 2D perovskites may be best described as noncentrosymmetric ( $C c2m$ for even $n$ and $C2c b$ for odd $n$ ) reflecting the presence of local domains generated by local symmetry breaking, whereas the centrosymmetric models (Ccmm for even $n$ and Acam for odd $n$ ) refer to the averaged crystal structure resulting from the random orientation of the local polar domains. A similar description may also apply to the $\\mathbf{MAPbI}_{3}$ $n=\\infty$ homologue where the local crystal structure is polar and can be described using the noncentrosymmetric (ferroelectric) model (space group I4cm),110,111 whereas the apparent crystal structure of bulk samples is centrosymmetric (space group $I4/m c m)$ due to the canceling out of the polarization from the randomly oriented local polar domains. \n\n# CONCLUDING REMARKS \n\nWe have demonstrated the facile, large-scale synthesis of the 2D $\\mathrm{(BA)}_{2}\\mathrm{(MA)}_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}\\left(n=1,2,3,4,\\bar{\\infty}\\right)$ perovskites that belong to the Ruddlesden−Popper family. The convenient isolation of the pure materials allowed for the accurate characterization of the crystal structure of the compounds, which are reported here for the first time for $n=2$ , 3, and 4. The 2D perovskites crystallize in polar space groups reflecting the alignment of the MA cations to generate an uncompensated dipole moment. All 2D homologous compounds have sharp absorption edges in the visible spectral range suggesting a direct band gap, which asymptotically approaches the band gap of the 3D $\\mathbf{MAPbI}_{3}$ perovskite. DFT calculations confirm that the 2D perovskites are indeed direct band gap semiconductors with large bandwidths and small effective masses for both electrons and holes. The absorption of the 2D perovskites is accompanied by a strong photoluminescence emission at room temperature, which is characteristically red-shifted with respect to the absorption edge. The optical physics of the 2D perovskites is characterized by the presence of stable excitons, which act like the active chromophores at room temperature, owing to their natural quantum well electronic structure, which is analogous to that of the artificial III−V semiconductor quantum wells. \n\nIn view of their exciting properties, the 2D perovskites can indeed be a new source of functional, tunable semiconductors expanding on the properties of the 3D species. For example, the intense room-temperature photoluminescence possible from the 2D perovskites points to their potential utility in light-emitting diodes and lasers. On the other hand, the optimal band gaps of higher n members indicate that these compounds can be used as efficient light absorbers for solution-processed solar cells, which offers better solution processability in addition to their superior environmental stability. More complicated concepts like electrooptical modulators can also be envisaged, taking advantage of the quantum well tunable architecture of the 2D perovskites. The great advantage of the 2D perovskites over the 3D ones is that the complex electronic structure of the 2D materials can be chemically tuned through subtle modification of the crystal structure, adjusting the layer-to-layer spacing or the spacerperovskite interactions. Work in progress is directed in synthesizing and structurally characterizing more homologous series to be able to correlate the effects of the chemical composition in the semiconducting properties of the perovskites to the observed systematically evolving optoelectronic properties. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.chemmater.6b00847. \n\nVibrational spectra, detailed crystallographic tables for $(\\mathrm{BA})_{2}(\\mathrm{MA})_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ $\\left(n=2{-4}\\right)$ for the noncentrosymmetric (proper assignment) and centrosymmetric (alternative model) refinements (PDF) \nCrystallographic files (CIF) \nCrystallographic files (CIF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author \n$^{*}\\mathrm{E}$ -mail: m-kanatizdis@northwestern.edu. \nAuthor Contributions \n¶These authors contributed equally to this work. Notes \nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by Grant No. SC0012541 from the U.S. Department of Energy, Office of Science. D.H.C. acknowledges support from the Link Foundation through the Link Foundation Energy Fellowship Program. J.Y. and J.M.R. were supported by the National Science Foundation (NSF) through the Pennsylvania State University MRSEC under Award No. DMR-1420620. DFT calculations were performed on the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF Grant No. ACI-1053575, and the QUEST high performance computing facility at Northwestern University, which is jointly supported by the Office of the Provost, the Office for Research, and Northwestern University Information Technology. Electron microscopy was done at the Electron Probe Instrumentation Center (EPIC) at Northwestern University. Raman spectroscopy was performed at the Integrated Molecular Structure Education and Research Center (IMSERC) at Northwestern University. Confocal microscope studies were performed at the SPID facility (NUANCE Center-Northwestern University), which has received support from the State of Illinois through the International Institute for Nanotechnology. \n\n# REFERENCES \n\n(1) Burschka, J.; Pellet, N.; Moon, S. J.; Humphry-Baker, R.; Gao, P.; Nazeeruddin, M. K.; Gratzel, M. Sequential Deposition as a Route to High-Performance Perovskite-Sensitized Solar Cells. Nature 2013, 499, 316−319. (2) Jeon, N. J.; Noh, J. H.; Kim, Y. C.; Yang, W. S.; Ryu, S.; Il Seol, S. Solvent Engineering for High-Performance Inorganic-Organic Hybrid Perovskite Solar Cells. Nat. Mater. 2014, 13, 897−903. (3) Boix, P. P.; Agarwala, S.; Koh, T. M.; Mathews, N.; Mhaisalkar, S. G. Perovskite Solar Cells: Beyond Methylammonium Lead Iodide. J. Phys. Chem. Lett. 2015, 6, 898−907. (4) Gao, P.; Gratzel, M.; Nazeeruddin, M. K. Organohalide Lead Perovskites for Photovoltaic Applications. Energy Environ. Sci. 2014, 7, 2448−2463. (5) De Angelis, F. Modeling Materials and Processes in Hybrid/ Organic Photovoltaics: From Dye-Sensitized to Perovskite Solar Cells. Acc. Chem. Res. 2014, 47, 3349−3360. (6) Green, M. A.; Ho-Baillie, A.; Snaith, H. J. The Emergence of Perovskite Solar Cells. Nat. Photonics 2014, 8, 506−514. \n\n(7) Miyasaka, T. Perovskite Photovoltaics: Rare Functions of Organo Lead Halide in Solar Cells and Optoelectronic Devices. Chem. Lett. 2015, 44, 720−729. \n(8) Stoumpos, C. C.; Kanatzidis, M. G. The Renaissance of Halide Perovskites and Their Evolution as Emerging Semiconductors. Acc. Chem. Res. 2015, 48, 2791−802. \n(9) Jung, H. S.; Park, N.-G. Perovskite Solar Cells: From Materials to Devices. Small 2015, 11, 10−25. \n(10) Chung, I.; Song, J.-H.; Im, J.; Androulakis, J.; Malliakas, C. D.; Li, H.; Freeman, A. J.; Kenney, J. T.; Kanatzidis, M. G. $\\mathrm{CsSnI}_{3}$ : Semiconductor or Metal? High Electrical Conductivity and Strong Near-Infrared Photoluminescence from a Single Material. High Hole Mobility and Phase-Transitions. J. Am. Chem. Soc. 2012, 134, 8579− 8587. \n(11) Kojima, A.; Teshima, K.; Shirai, Y.; Miyasaka, T. Organometal Halide Perovskites as Visible-Light Sensitizers for Photovoltaic Cells. J. Am. Chem. Soc. 2009, 131, 6050−6051. \n(12) Etgar, L.; Gao, P.; Xue, Z.; Peng, $\\mathrm{Q.;}$ Chandiran, A. K.; Liu, B.; Nazeeruddin, M. K.; Grätzel, M. Mesoscopic $\\mathrm{CH_{3}N H_{3}P b I_{3}/T i O_{2}}$ Heterojunction Solar Cells. J. Am. Chem. Soc. 2012, 134, 17396−17399. (13) Lee, M. M.; Teuscher, J.; Miyasaka, T.; Murakami, T. N.; Snaith, H. J. Efficient Hybrid Solar Cells Based on Meso-Superstructured Organometal Halide Perovskites. Science 2012, 338, 643−647. \n(14) Kim, H.-S.; Lee, C.-R.; Im, J.-H.; Lee, K.-B.; Moehl, T.; Marchioro, A.; Moon, S.-J.; Humphry-Baker, R.; Yum, J.-H.; Moser, J. E.; Grätzel, M.; Park, N.-G. Lead Iodide Perovskite Sensitized All-Solid-State Submicron Thin Film Mesoscopic Solar Cell with Efficiency Exceeding $9\\%$ . Sci. Rep. 2012, 2, 591. \n(15) Zhou, H. P.; Chen, Q.; Li, G.; Luo, S.; Song, T. B.; Duan, H. S.; Hong, Z. R.; You, J. B.; Liu, Y. S.; Yang, Y. Interface Engineering of Highly Efficient Perovskite Solar Cells. Science 2014, 345, 542−546. (16) Jeon, N. J.; Noh, J. H.; Yang, W. S.; Kim, Y. C.; Ryu, S.; Seo, J.; Seok, S. I. Compositional Engineering of Perovskite Materials for HighPerformance Solar Cells. Nature 2015, 517, 476−480. \n(17) Yang, W. S.; Noh, J. H.; Jeon, N. J.; Kim, Y. C.; Ryu, S.; Seo, J.; Seok, S. I. High-Performance Photovoltaic Perovskite Layers Fabricated Through Intramolecular Exchange. Science 2015, 348, 1234−1237. (18) Fabini, D. Quantifying the Potential for Lead Pollution from Halide Perovskite Photovoltaics. J. Phys. Chem. Lett. 2015, 6, 3546− 3548. \n(19) Niu, G.; Guo, X.; Wang, L. Review of Recent Progress in Chemical Stability of Perovskite Solar Cells. J. Mater. Chem. A 2015, 3, 8970− 8980. \n(20) Hao, F.; Stoumpos, C. C.; Cao, D. H.; Chang, R. P. H.; Kanatzidis, M. G. Lead-Free Solid-State Organic-Inorganic Halide Perovskite Solar Cells. Nat. Photonics 2014, 8, 489−494. \n(21) Noel, N. K.; Stranks, S. D.; Abate, A.; Wehrenfennig, C.; Guarnera, S.; Haghighirad, A.; Sadhanala, A.; Eperon, G. E.; Pathak, S. K.; Johnston, M. B.; Petrozza, A. M.; Herz, L. M.; Snaith, H. J. Lead-Free Organic-Inorganic Tin Halide Perovskites for Photovoltaic Applications. Energy Environ. Sci. 2014, 7, 3061−3068. \n(22) Ogomi, Y.; Morita, A.; Tsukamoto, S.; Saitho, T.; Fujikawa, N.; Shen, $\\mathrm{Q.;}$ Toyoda, T.; Yoshino, K.; Pandey, S. S.; Ma, T.; Hayase, S. $\\mathrm{CH_{3}N H_{3}S n_{x}P b_{(1-x)}I_{3}}$ Perovskite Solar Cells Covering up to $1060\\ \\mathrm{nm}$ . J. Phys. Chem. Lett. 2014, 5, 1004−1011. \n(23) Zuo, F.; Williams, S. T.; Liang, P.-W.; Chueh, C.-C.; Liao, C.-Y.; Jen, A. K. Y. Binary-Metal Perovskites Toward High-Performance Planar-Heterojunction Hybrid Solar Cells. Adv. Mater. 2014, 26, 6454− 6460. \n(24) Hao, F.; Stoumpos, C. C.; Chang, R. P.; Kanatzidis, M. G. Anomalous Band Gap Behavior in Mixed Sn and Pb Perovskites Enables Broadening of Absorption Spectrum in Solar Cells. J. Am. Chem. Soc. 2014, 136, 8094−8099. \n(25) Hao, F.; Stoumpos, C. C.; Guo, P.; Zhou, N.; Marks, T. J.; Chang, R. P. H.; Kanatzidis, M. G. Solvent-Mediated Crystallization of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{SnI}_{3}$ Films for Heterojunction Depleted Perovskite Solar Cells. J. Am. Chem. Soc. 2015, 137, 11445−11452. \n(26) Smith, I. C.; Hoke, E. T.; Solis-Ibarra, D.; McGehee, M. D.; Karunadasa, H. I. A Layered Hybrid Perovskite Solar-Cell Absorber with Enhanced Moisture Stability. Angew. Chem., Int. Ed. 2014, 53, 11232− 11235. \n(27) Cao, D. H.; Stoumpos, C. C.; Farha, O. K.; Hupp, J. T.; Kanatzidis, M. G. 2D Homologous Perovskites as Light-Absorbing Materials for Solar Cell Applications. J. Am. Chem. Soc. 2015, 137, 7843−7850. (28) Cao, D. H.; Stoumpos, C. C.; Malliakas, C. D.; Katz, M. J.; Farha, O. K.; Hupp, J. T.; Kanatzidis, M. G. Remnant $\\mathrm{PbI}_{2},$ an Unforeseen Necessity in High-Efficiency Hybrid Perovskite-Based Solar Cells? APL Mater. 2014, 2, 091101. \n(29) Choi, J. J.; Yang, X.; Norman, Z. M.; Billinge, S. J.; Owen, J. S. Structure of Methylammonium Lead Iodide Within Mesoporous Titanium Dioxide: Active Material in High-Performance Perovskite Solar Cells. Nano Lett. 2014, 14, 127−133. \n(30) Calabrese, J.; Jones, N. L.; Harlow, R. L.; Herron, N.; Thorn, D. L.; Wang, Y. Preparation and Characterization of Layered Lead Halide Compounds. J. Am. Chem. Soc. 1991, 113, 2328−2330. \n(31) Ishihara, T.; Takahashi, J.; Goto, T. Exciton-State in TwoDimensional Perovskite Semiconductor $\\left(\\mathrm{C_{10}H_{21}N H_{3}}\\right)_{2}\\mathrm{PbI_{4}}$ . Solid State Commun. 1989, 69, 933−936. \n(32) Mitzi, D. B.; Wang, S.; Feild, C. A.; Chess, C. A.; Guloy, A. M. Conducting Layered Organic-Inorganic Halides Containing $<110>\\cdot$ - Oriented Perovskite Sheets. Science 1995, 267, 1473−1476. \n(33) Mitzi, D. B.; Feild, C. A.; Harrison, W. T. A.; Guloy, A. M. Conducting Tin Halides with a Layered Organic-Based Perovskite Structure. Nature 1994, 369, 467−469. \n(34) Kagan, C. R.; Mitzi, D. B.; Dimitrakopoulos, C. D. OrganicInorganic Hybrid Materials as Semiconducting Channels in Thin-Film Field-Effect Transistors. Science 1999, 286, 945−947. \n(35) Ruddlesden, S. N.; Popper, P. New Compounds of the ${\\mathrm{K}}_{2}{\\mathrm{NiF}}_{4}$ Type. Acta Crystallogr. 1957, 10, 538−539. \n(36) Ruddlesden, S. N.; Popper, P. The Compound $\\mathrm{Sr}_{3}\\mathrm{Ti}_{2}\\mathrm{O}_{7}$ and its Structure. Acta Crystallogr. 1958, 11, 54−55. \n(37) For a recent review, see: Schaak, R. E.; Mallouk, T. E. Perovskites by Design: A Toolbox of Solid-State Reactions. Chem. Mater. 2002, 14, 1455−1471. \n(38) Mitzi, D. B. Synthesis, Crystal Structure, and Optical and Thermal Properties of $(\\mathrm{C_{4}H_{9}N H_{3}})_{2}\\mathrm{MI_{4}(M=G e,S n,P b)}$ ). Chem. Mater. 1996, 8, 791−800. \n(39) Mitzi, D. B.; Liang, K. Preparation and Properties of $(\\mathrm{C_{4}H_{9}N H_{3}})_{2}\\mathrm{EuI_{4}}$ : A Luminescent Organic−Inorganic Perovskite with a Divalent Rare-Earth Metal Halide Framework. Chem. Mater. 1997, 9, 2990−2995. \n(40) Kataoka, T.; Kondo, T.; Ito, R.; Sasaki, S.; Uchida, K.; Miura, N. Magneto-Optical Study on Excitonic Spectra in $(\\mathrm{C_{6}H_{13}N H_{3}})_{2}\\mathrm{PbI_{4}}.$ Phys. Rev. B: Condens. Matter Mater. Phys. 1993, 47, 2010−2018. (41) Muljarov, E. A.; Tikhodeev, S. G.; Gippius, N. A.; Ishihara, T. Excitons in Self-Organized Semiconductor-Insulator Superlattices - PbIBased Perovskite Compounds. Phys. Rev. B: Condens. Matter Mater. Phys. 1995, 51, 14370−14378. \n(42) Ishihara, T.; Takahashi, J.; Goto, T. Optical-Properties Due to Electronic-Transitions in 2-Dimensional Semiconductors $(\\mathrm{C}_{n}\\mathrm{H}_{2n+1}\\mathrm{NH}_{3})_{2}\\mathrm{PbI}_{4}$ . Phys. Rev. B: Condens. Matter Mater. Phys. 1990, 42, 11099−11107. \n(43) Hong, X.; Ishihara, T.; Nurmikko, A. V. Dielectric Confinement Effect on Excitons in $\\mathrm{PbI}_{4}$ -Based Layered Semiconductors. Phys. Rev. B: Condens. Matter Mater. Phys. 1992, 45, 6961−6964. \n(44) Ishihara, T.; Hong, X.; Ding, J.; Nurmikko, A. V. Dielectric Confinement Effect for Exciton and Biexciton States in $\\mathrm{PbI}_{4}$ -Based 2- Dimensional Semiconductor Structures. Surf. Sci. 1992, 267, 323−326. (45) Hirasawa, M.; Ishihara, T.; Goto, T. Exciton Features in 0- Dimensional, 2-Dimensional, and 3-Dimensional Networks of $\\mathrm{[PbI_{4}]^{4-}}$ Octahedra. J. Phys. Soc. Jpn. 1994, 63, 3870−3879. \n(46) Koutselas, I. B.; Ducasse, L.; Papavassiliou, G. C. Electronic Properties of Three- and Low-Dimensional Semiconducting Materials with Pb Halide and Sn Halide Units. J. Phys.: Condens. Matter 1996, 8, 1217−1227. \n(47) Kondo, T.; Iwamoto, S.; Hayase, S.; Tanaka, K.; Ishi, J.; Mizuno, M.; Ema, K.; Ito, R. Resonant Third-Order Optical Nonlinearity in the Layered Perovskite-Type Material $(\\mathrm{C}_{6}\\mathrm{H}_{13}\\mathrm{NH}_{3})_{2}\\mathrm{PbI}_{4}$ . Solid State Commun. 1998, 105, 503−506. \n(48) Knutson, J. L.; Martin, J. D.; Mitzi, D. B. Tuning the Band Gap in Hybrid Tin Iodide Perovskite Semiconductors Using Structural Templating. Inorg. Chem. 2005, 44, 4699−4705. \n(49) Umebayashi, T.; Asai, K.; Kondo, T.; Nakao, A. Electronic Structures of Lead Iodide Based Low-Dimensional Crystals. Phys. Rev. B: Condens. Matter Mater. Phys. 2003, 67, 155405. \n(50) Shimizu, M.; Fujisawa, J.-I.; Ishi-Hayase, J. Influence of Dielectric Confinement on Excitonic Nonlinearity in Inorganic-Organic Layered Semiconductors. Phys. Rev. B: Condens. Matter Mater. Phys. 2005, 71, 205306. \n(51) Tanaka, $\\mathrm{K};$ Takahashi, T.; Kondo, T.; Umebayashi, T.; Asai, K.; Ema, K. Image Charge Effect on Two-Dimensional Excitons in an Inorganic-Organic Quantum-Well Crystal. Phys. Rev. B: Condens. Matter Mater. Phys. 2005, 71, 045312. \n(52) Shibuya, ${\\mathrm{K}}.{\\mathrm{}}$ Koshimizu, M.; Takeoka, ${\\mathrm{Y.;}}$ Asai, K. Scintillation Properties of $(\\mathrm{C_{6}H_{13}N H_{3}})_{2}\\mathrm{PbI_{4}}$ : Exciton Luminescence of an Organic/ Inorganic Multiple Quantum Well Structure Compound Induced by 2.0 MeV Protons. Nucl. Instrum. Methods Phys. Res., Sect. B 2002, 194, 207− 212. \n(53) Papavassiliou, G. C.; Koutselas, I. B. Structural, Optical and Related Properties of Some Natural Three- and Lower-Dimensional Semiconductor Systems. Synth. Met. 1995, 71, 1713−1714. \n(54) Tanaka, K.; Kondo, T. Bandgap and Exciton Binding Energies in Lead-Iodide-Based Natural Quantum-Well Crystals. Sci. Technol. Adv. Mater. 2003, 4, 599−604. \n(55) Ishihara, T. Optical-Properties of PbI-Based Perovskite Structures. J. Lumin. 1994, 60−61, 269−274. \n(56) Wu, X.; Trinh, M. T.; Niesner, D.; Zhu, H.; Norman, Z.; Owen, J. S.; Yaffe, O.; Kudisch, B. J.; Zhu, X. Y. Trap States in Lead Iodide Perovskites. J. Am. Chem. Soc. 2015, 137, 2089−2096. \n(57) Wu, X.; Trinh, M. T.; Zhu, X. Y. Excitonic Many-Body Interactions in Two-Dimensional Lead Iodide Perovskite Quantum Wells. J. Phys. Chem. C 2015, 119, 14714−14721. \n(58) Yaffe, O.; Chernikov, A.; Norman, Z. M.; Zhong, Y.; Velauthapillai, A.; van der Zande, A.; Owen, J. S.; Heinz, T. F. Excitons in Ultrathin Organic-Inorganic Perovskite Crystals. Phys. Rev. B: Condens. Matter Mater. Phys. 2015, 92, 045414. \n(59) Bugajski, M.; Reginski, K. Optical Properties of Semiconductor Quantum Wells. Opto-Electr. Rev. 1996, 4, 83−100. \n(60) Miller, D. A. B. Optical Physics of Quantum Wells. In Quantum Dynamics of Simple Systems; Oppo, G. -L., Barnett, S. M., Riis, E., Wilkinson, M., Eds.; Institute of Physics: London, 1996; pp 239−266. (61) Sheldrick, G. A Short History of SHELX. Acta Crystallogr., Sect. A: Found. Crystallogr. 2008, 64, 112−122. \n(62) Spek, A. L. Structure Validation in Chemical Crystallography. Acta Crystallogr., Sect. D: Biol. Crystallogr. 2009, 65, 148−155. \n(63) Farrugia, L. WinGX and ORTEP for Windows: an Update. J. Appl. Crystallogr. 2012, 45, 849−854. \n(64) Stoumpos, C. C.; Malliakas, C. D.; Kanatzidis, M. G. Semiconducting Tin and Lead Iodide Perovskites with Organic Cations: Phase Transitions, High Mobilities, and Near-Infrared Photoluminescent Properties. Inorg. Chem. 2013, 52, 9019−9038. \n(65) Chondroudis, ${\\mathrm{K}}.{\\mathrm{}}$ McCarthy, T. J.; Kanatzidis, M. G. Chemistry in Molten Alkali Metal Polyselenophosphate Fluxes. Influence of Flux Composition on Dimensionality. Layers and Chains in $\\mathrm{APbPSe}_{4},$ $\\mathrm{A}_{4}\\mathrm{Pb}\\bar{(\\mathrm{PSe}_{4})}_{2}$ $(\\boldsymbol{\\mathrm{A}}=\\boldsymbol{\\mathrm{Rb}},\\boldsymbol{\\mathrm{Cs}}^{\\dagger}$ ), and $\\mathrm{K_{4}E u(P S e_{4})_{2}}$ . Inorg. Chem. 1996, 35, 840−844. \n(66) McCarthy, T. J.; Kanatzidis, M. G. Synthesis in Molten Alkali Metal Polyselenophosphate Fluxes: A New Family of Transition Metal Selenophosphate Compounds, $\\mathrm{A}_{2}\\mathrm{MP}_{2}\\mathrm{Se}_{26}$ $\\mathrm{\\bf{A}}=\\mathrm{\\bf{K}},$ Rb, Cs; $\\mathbf{M}=\\mathbf{M}\\mathbf{n}$ , Fe) and $\\mathbf{A}_{2}\\mathbf{M}_{2}^{\\prime}\\mathbf{P}_{2}S\\mathbf{e}_{6}$ $\\mathrm{\\boldmath~\\cal~A}=\\mathrm{\\boldmath~\\cal~K~},$ Cs; $\\mathbf{M}^{\\prime}=\\mathbf{C}\\mathbf{u},\\mathbf{A}\\mathbf{g})$ . Inorg. Chem. 1995, 34, 1257− 1267. \n(67) Haynes, A. S.; Saouma, F. O.; Otieno, C. O.; Clark, D. J.; Shoemaker, D. P.; Jang, J. I.; Kanatzidis, M. G. Phase-Change Behavior and Nonlinear Optical Second and Third Harmonic Generation of the One-Dimensional $\\mathrm{K}_{\\mathrm{(1-x)}}\\mathrm{Cs_{x}P S e}_{6}$ and Metastable $\\beta\\mathrm{-CsPSe}_{6}$ . Chem. Mater. 2015, 27, 1837−1846. (68) Stoumpos, C. C.; Frazer, L.; Clark, D. J.; Kim, Y. S.; Rhim, S. H.; Freeman, A. J.; Ketterson, J. B.; Jang, J. I.; Kanatzidis, M. G. Hybrid Germanium Iodide Perovskite Semiconductors: Active Lone Pairs, Structural Distortions, Direct and Indirect Energy Gaps, and Strong Nonlinear Optical Properties. J. Am. Chem. Soc. 2015, 137, 6804−6819. (69) Kresse, G.; Furthmüller, J. Efficiency of ab-initio Total Energy Calculations for Metals and Semiconductors Using a Plane-Wave Basis Set. Comput. Mater. Sci. 1996, 6, 15−50. \n(70) Kresse, G.; Hafner, J. Ab initio Molecular Dynamics for Liquid Metals. Phys. Rev. B: Condens. Matter Mater. Phys. 1993, 47, 558−561. (71) Blöchl, P. E. Projector Augmented-Wave Method. Phys. Rev. B: Condens. Matter Mater. Phys. 1994, 50, 17953−17979. \n(72) Perdew, J. P.; Ruzsinszky, A.; Csonka, G. I.; Vydrov, O. A.; Scuseria, G. E.; Constantin, L. A.; Zhou, X.; Burke, K. Restoring the Density-Gradient Expansion for Exchange in Solids and Surfaces. Phys. Rev. Lett. 2008, 100, 136406. \n(73) Monkhorst, H. J.; Pack, J. D. Special Points for Brillouin-Zone Integrations. Phys. Rev. B 1976, 13, 5188−5192. \n(74) Tabuchi, Y.; Asai, K.; Rikukawa, M.; Sanui, K.; Ishigure, K. Preparation and Characterization of Natural Lower Dimensional Layered Perovskite-Type Compounds. J. Phys. Chem. Solids 2000, 61, 837−845. \n(75) Elleuch, S.; Dammak, T.; Abid, Y.; Mlayah, A.; Boughzala, H. Synthesis, Structural and Optical Properties of a Novel Bilayered Organic−Inorganic Perovskite $\\mathrm{C}_{5}\\mathrm{Pb}_{2}\\mathrm{I}_{5}$ . J. Lumin. 2010, 130, 531−535. (76) Papavassiliou, G. C. Three- and Low-Dimensional Inorganic Semiconductors. Prog. Solid State Chem. 1997, 25, 125−270. \n(77) Valverde-Chavez, D. A.; Ponseca, C. S.; Stoumpos, C. C.; Yartsev, A.; Kanatzidis, M. G.; Sundstrom, V.; Cooke, D. G. Intrinsic Femtosecond Charge Generation Dynamics in Single Crystal $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ . Energy Environ. Sci. 2015, 8, 3700−3707. \n(78) Billing, D. G.; Lemmerer, A. Synthesis, Characterization and Phase Transitions of the Inorganic-Organic Layered Perovskite-Type Hybrids $\\left[(\\mathbf{C}_{n}\\mathrm{H}_{2n+1}\\mathrm{NH}_{3})_{2}\\mathbf{PbI}_{4}\\right]$ , $n=4.$ 5 and 6. Acta Crystallogr., Sect. B: Struct. Sci. 2007, 63, 735−747. \n(79) Hamilton, W. Significance Tests on the Crystallographic R Factor. Acta Crystallogr. 1965, 18, 502−510. \n(80) Rogers, D. On the Application of Hamilton’s Ratio Test to the Assignment of Absolute Configuration and an Alternative Test. Acta Crystallogr., Sect. A: Cryst. Phys., Diffr., Theor. Gen. Crystallogr. 1981, 37, 734−741. \n(81) Papavassiliou, G. C.; Mousdis, G. A.; Raptopoulou, C. P.; Terzis, A. Some New Luminescent Compounds Based on 4-MethyIbenzylamine and Lead Halides. Z. Naturforsch., B: J. Chem. Sci. 2000, 55b, 536− 540. \n(82) Zhu, X.-H.; Mercier, N.; Riou, A.; Blanchard, P.; Frere, P. $(\\mathrm{C_{4}H_{3}S C H_{2}N H_{3}})_{2}(\\mathrm{CH_{3}N H_{3}})\\mathrm{Pb_{2}I_{7}}$ : Non-Centrosymmetrical Crystal Structure of a Bilayer Hybrid Perovskite. Chem. Commun. 2002, 2160− 2161. \n(83) Mercier, N. $\\mathrm{(HO_{2}C(C H_{2})_{3}N H_{3})_{2}(C H_{3}N H_{3})P b_{2}I_{7}};$ : a Predicted Non-Centrosymmetrical Structure Built up from Carboxylic Acid Supramolecular Synthons and Bilayer Perovskite Sheets. CrystEngComm 2005, 7, 429−432. \n(84) Lemmerer, A.; Billing, D. G. Synthesis, Characterization and Phase Transitions of the Inorganic-Organic Layered Perovskite-Type Hybrids $[(\\mathrm{C}_{n}\\mathrm{H}_{2n+1}\\mathrm{NH}_{3})_{2}\\mathrm{PbI}_{4}]$ , $n=7,$ 8, 9 and 10. Dalton Trans. 2012, 41, 1146−1157. \n(85) Billing, D. G.; Lemmerer, A. Synthesis, Characterization and Phase Transitions of the Inorganic-Organic Layered Perovskite-Type Hybrids $[(\\mathrm{C}_{n}\\mathrm{H}_{2n+1}\\mathrm{NH}_{3})_{2}\\mathrm{PbI}_{4}]$ ( ${\\bf\\dot{\\boldsymbol{n}}}=12,$ 14, 16 and 18). New J. Chem. 2008, 32, 1736−1746. \n(86) Aleksandrov, K. S.; Beznosikov, B. V.; Misyul, S. V. Successive Phase Transitions in Crystals of ${\\mathrm{K}}_{2}{\\mathrm{Mg}}{\\mathrm{F}}_{4}$ -Type Structure. Phys. Status Sol. A 1987, 104, 529−543. \n(87) Aleksandrov, K. S.; Bartolome, J. Octahedral Tilt Phases in Perovskite-Like Crystals with Slabs Containing an Even Number of Octahedral Layers. J. Phys.: Condens. Matter 1994, 6, 8219−8235. \n\n(88) Glazer, A. The Classification of Tilted Octahedra in Perovskites. Acta Crystallogr., Sect. B: Struct. Crystallogr. Cryst. Chem. 1972, 28, 3384− 3392. (89) Axtell, E. A.; Liao, J. H.; Pikramenou, Z.; Kanatzidis, M. G. Dimensional Reduction in II-VI Materials: $\\mathrm{A}_{2}\\mathrm{Cd}_{3}\\mathrm{Q}_{4}$ ( $\\mathrm{\\boldmath~\\cal~A}=\\mathrm{\\boldmath~\\cal~K~},$ $\\mathrm{Q}={\\cal S}_{\\cdot}$ , Se, Te; $\\mathbf{A}=\\mathbf{Rb}$ , $\\mathrm{Q}={\\cal S},$ Se), Novel Ternary Low-Dimensional Cadmium Chalcogenides Produced by Incorporation of $\\mathbf{A}_{2}\\mathbf{Q}$ in CdQ. Chem. - Eur. J. 1996, 2, 656−666. (90) Axtell, E. A.; Park, Y.; Chondroudis, ${\\mathrm{K}}.{\\mathrm{}}$ ; Kanatzidis, M. G. Incorporation of $A_{2}\\mathrm{Q}$ into $H_{8}\\mathrm{Q}$ and Dimensional Reduction to ${\\bf A}_{2}{\\mathrm{Hg}}_{3}{\\bf Q}_{4}$ and $\\mathrm{A_{2}H g_{6}Q_{7}}$ $\\mathrm{\\bf\\ddot{A}}=\\mathrm{\\bfK},$ Rb, Cs; $\\mathrm{Q}=\\mathrm{S},$ Se). Access of Li Ions in $\\mathrm{A_{2}H g_{6}Q_{7}}$ Through Topotactic Ion-Exchange. J. Am. Chem. Soc. 1998, 120, 124−136. (91) Androulakis, J.; Peter, S. C.; Li, H.; Malliakas, C. D.; Peters, J. A.; Liu, Z. F.; Wessels, B. W.; Song, J. H.; Jin, H.; Freeman, A. J.; Kanatzidis, M. G. Dimensional Reduction: A Design Tool for New Radiation Detection Materials. Adv. Mater. 2011, 23, 4163−4167. (92) Umari, P.; Mosconi, E.; De Angelis, F. Relativistic GW Calculations on $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{SnI}_{3}$ Perovskites for Solar Cell Applications. Sci. Rep. 2014, 4, 4467. (93) Sebastian, M.; Peters, J. A.; Stoumpos, C. C.; $\\scriptstyle{\\mathrm{Im}},$ J.; Kostina, S. S.; Liu, Z.; Kanatzidis, M. G.; Freeman, A. J.; Wessels, B. W. Excitonic Emissions and Above-Band-Gap Luminescence in the Single-Crystal Perovskite Semiconductors $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ . Phys. Rev. B: Condens. Matter Mater. Phys. 2015, 92, 235210. (94) D’Innocenzo, $\\mathrm{V.j}$ Grancini, G.; Alcocer, M. J. P.; Kandada, A. R. S.; Stranks, S. D.; Lee, M. M.; Lanzani, G.; Snaith, H. J.; Petrozza, A. Excitons Versus Free Charges in Organo-Lead Tri-Halide Perovskites. Nat. Commun. 2014, 5, 3586. (95) Miyata, A.; Mitioglu, A.; Plochocka, P.; Portugall, O.; Wang, J. T. W.; Stranks, S. D.; Snaith, H. J.; Nicholas, R. J. Direct Measurement of the Exciton Binding Energy and Effective Masses for Charge Carriers in Organic-Inorganic Tri-Halide Perovskites. Nat. Phys. 2015, 11, 582− U94. (96) Lin, $\\mathrm{Q.;}$ Armin, A.; Nagiri, R. C. R.; Burn, P. L.; Meredith, P. Electro-Optics of Perovskite Solar Cells. Nat. Photonics 2014, 9, 106− 112. (97) Mak, K. F.; Lee, C.; Hone, J.; Shan, J.; Heinz, T. F. Atomically Thin $\\mathbf{Mo}S_{2}$ : A New Direct-Gap Semiconductor. Phys. Rev. Lett. 2010, 105, 136805. (98) Ramasubramaniam, A. Large Excitonic Effects in Monolayers of Molybdenum and Tungsten Dichalcogenides. Phys. Rev. B: Condens. Matter Mater. Phys. 2012, 86, 115409. (99) Jones, E. D.; Drummond, T. J.; Hjalmarson, H. P.; Schirber, J. E. Photoluminescence Studies of GaAs/AlAs Short Period Superlattices. Superlattices Microstruct. 1988, 4, 233−236. (100) Quarti, C.; Mosconi, E.; De Angelis, F. Interplay of Orientational Order and Electronic Structure in Methylammonium Lead Iodide: Implications for Solar Cell Operation. Chem. Mater. 2014, 26, 6557− 6569. (101) Liao, W.-Q.; Zhang, Y.; $\\mathrm{H}\\mathbf{u},$ C.-L.; Mao, J.-G.; Ye, H.-Y.; Li, P.-F.; Huang, S. D.; Xiong, R.-G. A Lead-Halide Perovskite Molecular Ferroelectric Semiconductor. Nat. Commun. 2015, 6, 7338. (102) Fan, Z.; Xiao, J.; Sun, K.; Chen, L.; Hu, Y.; Ouyang, J.; Ong, K. P.; Zeng, K.; Wang, J. Ferroelectricity of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ Perovskite. J. Phys. Chem. Lett. 2015, 6, 1155−1161. (103) Xiao, Z.; Yuan, Y.; Shao, Y.; Wang, $\\mathrm{Q.;}$ Dong, $\\mathrm{Q.;}$ Bi, C.; Sharma, P.; Gruverman, A.; Huang, J. Giant Switchable Photovoltaic Effect in Organometal Trihalide Perovskite Devices. Nat. Mater. 2014, 14, 193− 198. (104) Coll, M.; Gomez, A.; Mas-Marza, E.; Almora, O.; GarciaBelmonte, G.; Campoy-Quiles, M.; Bisquert, J. Polarization Switching and Light-Enhanced Piezoelectricity in Lead Halide Perovskites. J. Phys. Chem. Lett. 2015, 6, 1408−1413. (105) Butler, K. T.; Frost, J. M.; Walsh, A. Ferroelectric Materials for Solar Energy Conversion: Photoferroics Revisited. Energy Environ. Sci. 2015, 8, 838−848. \n\n(106) Hollis, D. B. Review of Hyper-Rayleigh and Second-Harmonic Scattering in Minerals and Other Inorganic Solids. Am. Mineral. 1988, 73, 701−706. \n(107) Kurtz, S. K.; Perry, T. T. A Powder Technique for the Evaluation of Nonlinear Optical Materials. J. Appl. Phys. 1968, 39, 3798−3813. (108) Balédent, V.; Chattopadhyay, S.; Fertey, P.; Lepetit, M. B.; Greenblatt, M.; Wanklyn, B.; Saouma, F. O.; Jang, J. I.; Foury-Leylekian, P. Evidence for Room Temperature Electric Polarization in ${\\mathrm{RMn}}_{2}{\\mathrm{O}}_{5}$ Multiferroics. Phys. Rev. Lett. 2015, 114, 117601. \n(109) Tronc, P.; Kitaev, Y. E.; Panfilov, A. G.; Limonov, M. F.; Wang, G.; Smirnov, V. P. Bound-state Symmetries and Optical Transitions in GaAs/AlAs Quantum Wells and Superlattices with Impurities and Defects. Phys. Rev. B: Condens. Matter Mater. Phys. 2000, 61, 1999−2007. (110) Bertoluzzi, L.; Sanchez, R. S.; Liu, L.; Lee, J.-W.; Mas-Marza, E.; Han, H.; Park, N.-G.; Mora-Sero, I.; Bisquert, J. Cooperative Kinetics of Depolarization in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ Perovskite Solar Cells. Energy Environ. Sci. 2015, 8, 910−915. \n(111) Kim, H.-S.; Kim, S. K.; Kim, B. J.; Shin, K.-S.; Gupta, M. K.; Jung, H. S.; Kim, S.-W.; Park, N.-G. Ferroelectric Polarization in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ Perovskite. J. Phys. Chem. Lett. 2015, 6, 1729−1735. " + }, + { + "id": "10.1038_ncomms13638", + "DOI": "10.1038/ncomms13638", + "DOI Link": "http://dx.doi.org/10.1038/ncomms13638", + "Relative Dir Path": "mds/10.1038_ncomms13638", + "Article Title": "Platinum single-atom and cluster catalysis of the hydrogen evolution reaction", + "Authors": "Cheng, NC; Stambula, S; Wang, D; Banis, MN; Liu, J; Riese, A; Xiao, BW; Li, RY; Sham, TK; Liu, LM; Botton, GA; Sun, XL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Platinum-based catalysts have been considered the most effective electrocatalysts for the hydrogen evolution reaction in water splitting. However, platinum utilization in these electrocatalysts is extremely low, as the active sites are only located on the surface of the catalyst particles. Downsizing catalyst nulloparticles to single atoms is highly desirable to maximize their efficiency by utilizing nearly all platinum atoms. Here we report on a practical synthesis method to produce isolated single platinum atoms and clusters using the atomic layer deposition technique. The single platinum atom catalysts are investigated for the hydrogen evolution reaction, where they exhibit significantly enhanced catalytic activity (up to 37 times) and high stability in comparison with the state-of-the-art commercial platinum/carbon catalysts. The X-ray absorption fine structure and density functional theory analyses indicate that the partially unoccupied density of states of the platinum atoms' 5d orbitals on the nitrogen-doped graphene are responsible for the excellent performance.", + "Times Cited, WoS Core": 1711, + "Times Cited, All Databases": 1810, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000388872900001", + "Markdown": "# Platinum single-atom and cluster catalysis of the hydrogen evolution reaction \n\nNiancai Cheng1,\\*, Samantha Stambula2,\\*, Da Wang3,\\*, Mohammad Norouzi Banis1, Jian Liu1, Adam Riese1, Biwei Xiao1, Ruying Li1, Tsun-Kong Sham4, Li-Min Liu3, Gianluigi A. Botton $2,5,6$ & Xueliang Sun1 \n\nPlatinum-based catalysts have been considered the most effective electrocatalysts for the hydrogen evolution reaction in water splitting. However, platinum utilization in these electrocatalysts is extremely low, as the active sites are only located on the surface of the catalyst particles. Downsizing catalyst nanoparticles to single atoms is highly desirable to maximize their efficiency by utilizing nearly all platinum atoms. Here we report on a practical synthesis method to produce isolated single platinum atoms and clusters using the atomic layer deposition technique. The single platinum atom catalysts are investigated for the hydrogen evolution reaction, where they exhibit significantly enhanced catalytic activity (up to 37 times) and high stability in comparison with the state-of-the-art commercial platinum/carbon catalysts. The X-ray absorption fine structure and density functional theory analyses indicate that the partially unoccupied density of states of the platinum atoms’ $5d$ orbitals on the nitrogen-doped graphene are responsible for the excellent performance. \n\nSeocnue onf trheenewoarblde nfod eremlioasbt hsoalulrecnegs o. Acldedarn esinegr tyhis also aid in the mitigation of environmental and health hazards caused by fossil fuels1. Hydrogen is the cleanest fuel available and is believed to be one of the most promising energy sources of the twenty-first century2,3. However, the majority of the hydrogen produced today is derived from steam-reformed methane, which is sourced from fossil reserves and produces a substantial amount of $\\mathrm{CO}_{2}$ (ref. 4). The production of hydrogen from water electrolysis is a promising alternative to the current $\\mathrm{CO}_{2}$ -emitting fossil fuel-based energy systems5,6. \n\nPlatinum (Pt)-based catalysts are generally considered to be the most effective electrocatalysts for the hydrogen evolution reaction $(\\mathrm{HER})^{5,7}$ . Unfortunately, Pt is expensive and scarce, limiting the commercial potential for such catalysts. The development of active, stable and inexpensive electrocatalysts for water splitting is a key step in the realization of a hydrogen economy, which is based on the use of molecular hydrogen for energy storage. \n\n![](images/994686a75c9a8b3965b75c268b29adb98fee515714436858aefb7f55388a8ba4.jpg) \nFigure 1 | ADF STEM images and schematic illustration of the Pt ALD mechanism on NGNs. ADF STEM images of ALDPt/NGNs samples with (a,b) 50 and (c,d) 100 ALD cycles. Scale bars, $10\\mathsf{n m}$ (a,c); $5\\mathsf{n m}$ (b,d). (e) Schematic illustration of the Pt ALD mechanism on NGNs. The ALD process includes the following: the Pt precursor $({\\mathsf{M e C p P t M e}}_{3})$ first reacts with the N-dopant sites in the NGNs (i). During the following $\\mathsf{O}_{2}$ exposure, the Pt precursor on the NGNs is completely oxidized to ${\\mathsf{C O}}_{2}$ and ${\\mathsf{H}}_{2}{\\mathsf{O}},$ creating a Pt containing monolayer (ii). These two processes (i and ii) form a complete ALD cycle. During process (ii), a new layer of adsorbed oxygen forms on the platinum surface, which provides functional groups for the next ALD cycle process (iii). \n\nSignificant effort has been devoted to the search of non-preciousmetal-based HER catalysts, including sulfide-based materials8–11, and $\\mathrm{C}_{3}\\mathrm{N}_{4}$ (refs 12–14). Although these candidate materials show promising activities for the HER, the activities of these catalysts in their present form are insufficient for industrial applications15. \n\nTo overcome the challenges associated with the Pt HER catalysts and to drive the cost of $\\mathrm{H}_{2}$ production from water electrolysis down, it is very important to markedly decrease the Pt loading and increase the $\\mathrm{Pt}$ utilization efficiency. Currently, supported $\\mathrm{Pt}$ nanoparticles (NPs) are typically used to promote Pt activity towards the HER. Unfortunately, the geometry of the NPs limit the majority of the Pt atoms to the particle core, deeming them ineffective, as only surface atoms are involved in the electrochemical reaction16. Reducing the size of the Pt NPs to clusters or even single atoms could significantly decrease the noble metal usage and increase their catalytic activity, which is highly desirable to enhance the $\\mathrm{\\Pt}$ utilization and decrease the cost of the electrocatalysts17. It has been shown that single Pt atoms dispersed on an $\\mathrm{FeO}_{x}$ surface have a higher catalytic activity for CO oxidation compared with the corresponding Pt $\\mathrm{NPs^{18}}$ . Moreover, the single-atom catalysts also exhibited a significantly improved catalytic activity towards methanol oxidation, up to 10 times greater than the state-of-the-art commercial carbon-supported Pt $\\mathrm{(Pt/C)}$ catalysts19. \n\nControlled and large-scale synthesis of stable single atoms and clusters remains a considerable challenge due to the natural tendency for metal atoms to diffuse and agglomerate, resulting in the formation of larger particles20,21. In practical applications, it is required that the single atoms not only have a high activity but also exhibit a satisfactory stability17,22,23. Moreover, it is also desired to produce a high density of single atoms to meet the practical applications. Consequently, an ideal single-atom catalyst must have a high activity, a high stability and a high density. Thus, we need to discover an effective means to synthesize this ideal single-atom catalyst. In this paper, the atomic layer deposition (ALD) technique was utilized, as it has been proven to be a powerful tool for large-scale synthesis of stable singleatom and cluster catalysts19,24. ALD has the ability to precisely control the size and distribution of particles on a substrate by using sequential and self-limiting surface reactions25–27. \n\nIn this work, we fabricate single platinum atoms and clusters supported on nitrogen-doped graphene nanosheets (NGNs) for the HER using the ALD technique, resulting in the utilization of nearly all the Pt atoms. The size and density of the Pt catalysts on the NGNs are precisely controlled by simply adjusting the number of ALD cycles. The Pt atoms and clusters on the NGNs show much greater activity for the HER in comparison with conventional Pt NP catalysts. \n\n# Results \n\nElectron microscopy characterization. The morphology of the ALD $\\mathrm{\\Pt}$ on NGNs with 50 and 100 cycles (denoted hereafter as ALD50Pt/NGNs and ALD100Pt/NGNs, respectively) were characterized by annular dark field (ADF) imaging with aberrationcorrected scanning transmission electron microscopy (STEM). The high spatial resolution allowed for the precise determination of the size and distribution of the individual metal atoms, thus providing local structural information about the metal species on the NGN supports24,28,29. It can be clearly observed in Fig. 1a,b that the numerous individual Pt atoms (bright spots), as well as very small Pt clusters are uniformly dispersed on the NGNs’ surface for the ALD50Pt/NGNs catalysts. Through examination of multiple NGNs, small NPs were also detected on this sample (Supplementary Fig. 1a). After 100 ALD cycles many single Pt atoms and small clusters were still present, yet it appears as though some Pt clusters have grown to form NPs at a larger quantity than observed for the 50 ALD cycles (Fig. 1c,d and Supplementary Fig. 1b). These findings suggest that ALD is a suitable technique for preparing single atoms/clusters on nitrogen-doped graphene supports. As shown in Fig. 1e, during the ALD process, the Pt precursor $\\mathrm{(MeCpPtMe_{3})}$ ) first reacts with the NGNs as influenced by the N-dopant. The chemical bonding between the Pt precursor and NGNs ensures a strong interaction between the deposited material and the support30. The Pt loading after ALD was confirmed using inductively coupled plasmaatomic emission spectroscopy, in which a loading of 2.1 and $7.6\\mathrm{wt\\%}$ was obtained for the 50 and 100 ALD cycled samples, respectively. \n\nCatalytic performance and stability. The HER activity of the ALDPt/NGNs with 50 and 100 cycles were measured in comparison with commercial $\\mathrm{Pt/C}$ catalysts by conducting linear sweep voltammetry measurements in $0.5{\\bf M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ at room temperature. The NGNs without $\\mathrm{Pt}$ catalysts exhibited a poor HER activity (Fig. 2a), which is consistent with previous studies12. As shown in Fig. 2a, both ALDPt/NGN and $\\mathrm{Pt/C}$ catalysts exhibited excellent catalytic activities towards the HER, with negligible overpotentials. Importantly, the ALDPt/NGN catalysts exhibited much higher HER activities than that of the commercial $\\mathrm{Pt/C}$ catalysts (Fig. 2a). It was observed that the HER catalytic activity of the ALDPt/NGNs decreased with an increased number of ALD cycles. This is likely attributed to the increased formation of clusters or NPs in the sample with 100 ALD cycles. Supplementary Fig. 2 showed consistent results with previous studies, as the $\\mathrm{\\bar{P}t/C}$ catalyst achieved a Tafel slope of $31\\mathrm{mV}\\mathrm{dec}^{-1}$ (ref. 31). Following the same measurement parameters, a smaller Tafel slope than the $\\mathrm{Pt/C}$ catalysts was achieved for the ALDPt/NGNs catalysts at $29\\mathrm{mV}\\mathrm{dec}^{-1}$ . The specific activity for each catalyst was calculated from the polarization curves by normalizing the current with the geometric area of the electrode. As shown in Supplementary Fig. 3, the HER activities for the $\\mathrm{ALD50Pt}/\\mathrm{NGNs}$ , $\\mathrm{ALD100Pt}/$ NGNs and $\\mathrm{Pt/C}$ catalysts are 16, 12.9 and $8.2\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively, at the overpotential of $0.05\\mathrm{V}$ . Furthermore, normalized to the $\\mathrm{\\Pt}$ loading (Fig. 2b), the mass activity of the HER for the ALD50Pt/NGNs catalysts at the overpotential of $0.05\\mathrm{V}$ was $10.1\\mathrm{A}\\mathrm{mg}^{-1}$ . Remarkably, the mass activity of the $\\mathrm{ALD50Pt/NGNs}$ catalyst was 7.8 times greater than the ALD100Pt/NGNs catalyst $(2.12\\mathrm{A}\\mathrm{mg}^{-1})$ and 37.4 times greater than the $\\mathrm{Pt/C}$ catalyst $(\\mathrm{{\\dot{0}}.27\\mathrm{{Amg}^{-1}}}.$ ). These findings suggest that the single $\\mathrm{\\Pt}$ atoms and clusters can significantly increase the Pt utilization activity in comparison to their NP counterparts18,32, with the additional benefit of decreasing the cost of the catalyst for the HER. \n\nThe long-term stability of the ALDPt/NGNs and $\\mathrm{Pt/C}$ catalysts were examined by extended electrolysis at fixed potentials. Supplementary Fig. 4 shows that the ALDPt/NGNs catalysts appear stable at $0.04\\mathrm{V}$ versus reversible hydrogen electrode (RHE), while the current density of the $\\mathrm{Pt/C}$ catalysts degraded with time at the same operating conditions. The lower stability of the $\\mathrm{Pt/C}$ catalysts may be due to a weak interaction between the supported $\\mathrm{\\Pt}$ particles and the C substrate33, resulting in the detachment and/or agglomeration of the Pt NPs. Accelerated degradation tests (ADTs) were also adopted to evaluate the durability of the Pt atom/cluster catalysts for the HER activity. As exhibited in Fig. 2c, the ALD50Pt/NGNs catalysts’ polarization curve after 1,000 cycles retained a similar performance to the initial test, resulting in a loss of only $4\\%$ of its initial current density at an overpotential of $0.05\\mathrm{V}$ (Supplementary Fig. 5). The significant stability of the $\\mathrm{ALD50Pt/NGNs}$ catalysts can be observed when comparing its performance with the $\\mathrm{ALD100Pt}/$ \n\n![](images/19dc9b8095338f8d69246ded52b443ce161ca83157af06eeadbefe8705efb7bb.jpg) \nFigure 2 | Electrocatalytic properties. (a) The HER polarization curves for ALDPt/NGNs and Pt/C catalysts were acquired by linear sweep voltammetry with a scan rate of $2\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at room temperature. ${\\sf N}_{2}$ was purged before the measurements. The inset shows the enlarged curves at the onset potential region of the HER for the different catalysts. (b) Mass activity at $0.05\\mathsf{V}$ (versus RHE) of the ALDPt/NGNs and the Pt/C catalysts for the HER. (c) Durability measurement of the ALD50Pt/NGNs. The polarization curves were recorded initially and after 1,000 cyclic voltammetry sweeps between $+0.4$ and $-0.15\\vee$ (versus RHE) at $100\\mathrm{mVs}^{-1}$ in $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at a scan rate of $2{\\mathsf{m}}{\\mathsf{V}}{\\mathsf{s}}^{-1}$ . (d) ADF STEM images of ALD50Pt/NGNs samples after ADT; scale bar, $20\\mathsf{n m}$ . \n\nNGNs catalysts ( $\\mathrm{\\sim10\\%}$ loss) and the $\\mathrm{Pt/C}$ catalysts ( $19\\%$ loss) under the same measurement conditions (Supplementary Figs 5 and 6). \n\nSTEM images acquired from the ALDPt/NGNs after the ADTs (Fig. 2d and Supplementary Fig. 7) showed that there was only a slight increase in the Pt size with no obvious aggregation. This further supports the excellent stability observed in the activity from the ALDPt/NGNs catalysts during the ADTs for the HER. In contrast, according to high-resolution transmission electron microscope images, the $\\mathrm{Pt/C}$ catalysts (Supplementary Fig. 8) coalesced into larger particles (marked with white circles in Supplementary Fig. 8b) with the average size of Pt NPs increasing from 4.2 to $5.5\\mathrm{nm}$ after the ADT. The growth of the NPs may be caused by $\\mathrm{Pt}$ migration due to weak interactions between the catalyst and the support34,35. As shown in Supplementary Fig. 9, the negative potentials of a HER cathode are generally not conducive for electro-oxidation of the support material. In addition, Pt is one of the most stable electrocatalyst materials36,37, and $\\mathrm{Pt}$ oxidation/dissolution is typically not observed at potentials $<0.85\\mathrm{V}$ versus RHE in acidic conditions, thus the $\\mathrm{Pt}$ and the C supports are stable under HER conditions. This suggests that the higher stability of the Pt atoms/clusters observed on the ALDPt/NGNs samples could be ascribed to the stronger interactions between the $\\mathrm{Pt}$ and the NGNs supports compared to the $\\mathrm{Pt/C}$ catalysts. \n\nX-ray absorption spectroscopy studies. X-ray absorption spectroscopy was used to study the local electronic structure of the Pt catalysts and their interaction with the support material38,39. The normalized X-ray absorption near edge structure (XANES) spectra for both the Pt $\\mathrm{L}_{3}$ - and $\\mathrm{L}_{2}$ -edges of the ALDPt/NGNs and $\\mathrm{Pt/C}$ catalysts are shown in Fig. 3 with comparison to a standard Pt foil. It can be seen in Fig. 3 that the threshold energy $(E_{0})$ and the maximum energy $(E_{\\mathrm{peak}})$ of the $\\mathrm{Pt}~\\mathrm{L}_{3}$ -edge for the ALDPt/NGNs are similar to those of the corresponding metal foil, thus confirming the metallic nature of the $\\mathrm{Pt}$ atoms and clusters on the ALDPt/NGNs samples. Furthermore, detailed examination of the spectra was conducted by qualitative and quantitative analysis of the $\\mathrm{Pt}\\ L_{2}$ and $\\mathrm{L}_{3}$ white line (WL) edges. It has been shown that the area under the WL of the $\\mathrm{L}_{2,3}$ -edge of the Pt metal is directly related to the unoccupied density of states of the $\\mathrm{Pt}~5d$ orbitals. This in turn has been used to correlate the catalytic activity of $\\mathrm{Pt}$ -based electrocatalysts to changes in their local electronic structure. Close examination reveals that the intensity of the $\\mathrm{Pt}~\\mathrm{L}_{3}$ WL exhibits small differences for the ALDPt/NGNs and the $\\mathrm{Pt/C}$ catalysts. The magnitude of the $\\mathrm{Pt}$ WL intensity at the Pt $\\mathrm{L}_{3}$ -edge appears to increase in the order of Pt foil $<\\mathrm{Pt}/\\mathrm{C}<\\mathrm{ALD}100\\mathrm{Pt}/\\mathrm{NGN}s<\\mathrm{ALD}50\\mathrm{Pt}/\\mathrm{NGN}s$ (Fig. 3a). In contrast, the corresponding $\\mathrm{L}_{2}$ -edge WL exhibits considerably more variation among the samples and a higher sensitivity compared with that of the Pt $\\mathrm{L}_{3}$ -edge, resulting in a different trend for the ALDPt/NGNs and the $\\mathrm{Pt/C}$ materials. The order of increasing intensity of the WL in the Pt $\\mathrm{L}_{2}$ -edge is as follows: Pt foil $<\\mathrm{ALD100Pt/NGNs}\\leq\\mathrm{Pt/C}<\\mathrm{ALD50Pt/NGNs}$ (Fig. 3b). This observation clearly confirms that for $5d$ noble metal states, the $5d_{5/2}$ and $5d_{3/2},$ demonstrate subtle but different chemical sensitivity due to the large spin–orbit coupling of the Pt 5d orbitals, and that both the $\\mathrm{L}_{3^{-}}$ and $\\mathrm{L}_{2}$ -edge WLs should be used together to address the chemistry of the material19. \n\nTo fully understand the effect of the unoccupied densities of $5d$ states of the $\\mathrm{Pt}$ catalysts, quantitative WL intensity analysis has been conducted on the basis of a reported method to determine the occupancy of the $5d$ states in each sample38,40,41 (see details in Methods). The $\\mathrm{Pt}~\\mathrm{L}_{3^{-}}$ and Pt $\\mathrm{L}_{2}$ -edge threshold and WL parameters were summarized in Table 1. The results indicate that the ALD50Pt/NGNs catalysts have the highest total unoccupied density of states of $\\mathrm{Pt}5d$ character, while the $\\mathrm{Pt/C}$ sample has the lowest. It has been demonstrated in literature that the vacant $d$ -orbitals of individual atoms play a vital role in the activity of catalysts and account for the excellent catalytic activity of single-atom catalysts18,42. \n\n![](images/b0cc97e3c60068707067fdebfea505b6367a199be2799d5ca2b1fb4e4ea66a03.jpg) \nFigure 3 | X-ray absorption studies. (a) The normalized XANES spectra at the Pt $\\mathsf{L}_{3}$ -edge of the ALDPt/NGNs, Pt/C catalysts and Pt foil. The inset shows the enlarged spectra at the Pt $\\mathsf{L}_{3}$ -edge. (b) The normalized XANES spectra at the $\\mathsf{P t}\\ \\mathsf{L}_{2}$ -edge of ALDPt/NGNs, $\\mathsf{P t/C}$ catalysts and $\\mathsf{P t}$ foil. The inset shows the enlarged spectra at the Pt $\\mathsf{L}_{2}$ -edge WL. \n\nFurthermore, to study the local atomic structure of Pt using Xray absorption spectra (XAS), the extended X-ray absorption fine structure (EXAFS) region of the $\\mathrm{\\DeltaX}$ -ray absorption spectra was studied. The Fourier transforms of the EXAFS region plotted in Supplementary Fig. 10 shows several main peaks. The peak at $2.6\\mathring\\mathrm{A}$ is associated with the $\\mathrm{\\Pt{-}P t}$ peak, which is significant in the Pt foil spectra. This peak shifts towards lower values in the $\\mathrm{Pt/C}$ samples $(2.5\\mathring\\mathrm{A})$ , and is significantly dampened and shifted to higher values $(2.7\\mathring\\mathrm{A})$ in the ALD-deposited samples. This is consistent with previously reported data on ALD-deposited Pt nanostructures19. However, as expected, due to the higher Pt content of the ALD100Pt/NGNs sample, the intensity of the $\\mathrm{Pt}-$ Pt peak in comparison with the ALD50Pt/NGNs sample is stronger, which confirms the presence of larger clusters and the higher loading observed in the ALD100Pt/NGNs samples by ADF imaging and inductively coupled plasma-atomic emission spectroscopy results. The peaks observed around $1.7\\mathring\\mathrm{A}$ in the ALD-deposited samples can be related to $\\mathrm{Pt-O}$ or $\\mathrm{Pt-C}$ bonds, but individual bond lengths are not distinguishable due to a similar backscattering phase. The significant intensity of $\\mathrm{Pt-O}$ or $\\mathrm{Pt-C}$ bonds and considerable deviation of the $\\mathrm{Pt-Pt}$ bond of the ALD samples compared with the Pt foil indicates the presence of single $\\mathrm{Pt}$ atoms in these samples. \n\n
Table 1 | Pt L-edge and Pt Lz-edge WL parameters.
SamplePt L3-edge WLPt Lz-edge WLhs/2
Eo(eV)Epeak(eV)I(eV)△A3E.(eV)Epeak (eV)I (eV)△A2
Pt foil11,56411,567.36.45.6121313,27313,275.86.53.381680.5117330.157245409 h3/2
Pt/C11,563.9811,567.57.36.1803113,27313,276.76.24.436690.55801970.206302528
ALD5OPt/NGNs11,563.9411,567.48.57.7290713,272.9813,276.88.64.925130.70269080.229014596
ALD100Pt/NGNs11,563.9811,567.487.1089213,27313,276.77.84.632920.64550940.215427066
\n\n# Discussion \n\nIt has been demonstrated that a strong interaction between the deposited metal and the support material plays a vital role in the stabilization of supported catalysts43. Despite the controlled deposition process during ALD, atomic diffusion and agglomeration are still possible and probable, if a weak interaction exists between the atoms and the support, thus resulting in the formation of large particles. This suggests the importance of the support selection when striving to prepare stable atom catalysts. It has been reported in the literature that doping the graphene lattice with N can enhance the $\\mathrm{Pt-C}$ support interaction energy, resulting in highly stable Pt catalysts44–46. This enhanced binding energy from the incorporation of N-dopants in the graphene lattice has been attributed to creating preferred nucleation sites for metals and metal oxides47. In addition, it was determined in one of our previous experiments that the Pt atoms and clusters favour deposition at edge locations on NGNs, thus stabilizing the creation of $\\mathrm{Pt}$ atoms and clusters without the formation of $\\mathrm{NPs}^{24}$ . To further examine the effects of the N-dopants on the stability of the $\\mathrm{\\Pt}$ atoms and clusters observed in Fig. 1 and to expand on the understanding of the N-dopant’s contribution to the HER, we have prepared ALD-deposited Pt on graphene nanosheets (GNs) for comparison. Supplementary Fig. 11 exhibits low- and highmagnification ADF images of $\\mathrm{ALD}50\\mathrm{Pt}/\\mathrm{GN}s.$ , in which there is a wide distribution of $\\mathrm{Pt}$ sizes from atoms and clusters to larger NPs. It can be suggested that the formation of larger particles on the GNs during the ALD procedure can be attributed to the weaker interaction between the $\\mathrm{Pt}$ and the graphene support in contrast to the N-doped graphene support. Furthermore, the HER activity was evaluated for the ALD50Pt/GNs sample using linear sweep voltammetry with a scan rate of $2\\mathrm{m}\\mathrm{V}\\mathrm{~s~}^{-1}$ in $0.5\\dot{\\mathrm{M}}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4},$ which revealed a lower mass and specific activity in comparison with the ALD50Pt/NGNs sample (Supplementary Fig. 12). The stability of the Pt catalysts on the GNs was also confirmed using ADT tests. It was determined that the ALD50Pt/GNs sample lost $24\\%$ of its initial HER activity (Supplementary Fig. 13), while as previously reported, the ALD50Pt/NGNs only decreased its activity by $4\\%$ . Following the ADT test, the ALD50Pt/GNs sample was examined using ADF imaging, where an increased frequency of larger clusters and NPs was observed (Supplementary Figs 11 and 13). This suggests that the increased $\\mathrm{\\Pt}$ particle size on the ALD50Pt/GNs sample from the ADT tests is responsible for the reduced HER activity after cycling. It can be suggested that the increased Pt particle size with cycling on the GNs is likely originating from a weaker adsorption energy, thus leading to a decreased stability of the Pt atoms, clusters and NPs, allowing them to become susceptible to degradation mechanisms48. Ultimately, this supports the argument that the strength of the interaction between the Pt catalysts and support increases on NGNs in comparison with GNs, which accounts for the increased stability and activity after ADT cycling. \n\nTo understand the stabilization mechanism of $\\mathrm{Pt}$ atoms on N-doped graphene, we applied density functional theory (DFT) calculations. The DFT calculations have been carried out using a graphene $(5\\times5\\times1)$ supercell containing $48\\mathrm{~C~}$ atoms and $^\\textrm{\\scriptsize1N}$ atom to identify the distribution of single $\\mathrm{Pt}$ atoms on the NGNs. All inequivalent $\\mathrm{\\Pt}$ -adsorption configurations around the N atom have been considered, and the most stable configurations are shown in Supplementary Fig. 14. It can be seen that in site III, Pt is located closest to the $\\mathrm{\\DeltaN}$ atom, while in site I, II, IX, X and XI the $\\mathrm{\\Pt}$ atom is situated further away from the N-dopant. To determine the most stable adsorption site for the $\\mathrm{\\Pt}$ atom, the adsorption energies $\\left(E_{\\mathrm{a}}\\right)$ for each site in Supplementary Fig. 14 were calculated by the following equation: \n\n$$\nE_{\\mathrm{a}}=(E_{\\mathrm{NGNs}}+n E_{\\mathrm{Pt}}-E_{\\mathrm{NGNs}+n\\mathrm{Pt}})/n\n$$ \n\nwhere $E_{\\mathrm{{Pt}}}$ is the energy of an isolated $\\mathrm{Pt}$ atom, $E_{\\mathrm{NGNs}}$ is the total energy of the N-doped graphene and $E_{\\mathrm{NGNs}+n\\mathrm{Pt}}$ is the total energy of the N-doped graphene with $n$ adsorbed $\\mathrm{Pt}$ atoms, respectively. A positive $E_{\\mathrm{a}}$ indicates the successful adsorption of the $\\mathrm{Pt}$ atoms during the N-doped graphene. \n\nAs shown in Supplementary Table 1, the $\\mathrm{\\Pt}$ atom prefers to directly bond to the N-dopant, as demonstrated by the significantly larger calculated adsorption energy of $5.171\\mathrm{eV}$ for a $\\mathrm{Pt}$ atom in site III in comparison with the other adsorption sites. Moreover, the calculated Bader charge shows that $0.257~e$ is transferred from the $\\mathrm{Pt}$ to the $\\mathrm{\\DeltaN}$ atom in the N-doped graphene substrate when the system is in its most stable configuration (site III), confirming the relatively large Pt adsorption energy at this site. These results clearly suggest that the Pt prefers to adsorb to the N-dopant sites on Pt deposition. \n\nTo further examine the distribution of the $\\mathrm{Pt}$ atoms on the N-doped graphene and their propensity to agglomerate, the energy difference between an isolated $\\mathrm{Pt}$ atom and a Pt cluster configuration, $\\Delta E_{\\mathrm{d}},$ was calculated, in which the total energy of the isolated configuration was used as a reference energy. In this scheme, a relatively large positive value for $\\Delta E_{\\mathrm{d}}$ indicates that $\\mathrm{\\Pt}$ atoms energetically favour the single-atom form and will tend to avoid clustering. For comparison of substrates, the production of various Pt cluster configurations on pristine graphene was also examined. As shown in Supplementary Fig. 15 and Supplementary Table 2, it is more favourable for the $\\mathrm{\\Pt}$ atoms to be isolated $(\\Delta E_{\\mathrm{d}}=+1.145\\mathrm{eV})$ on the N-doped graphene, while the $\\mathrm{Pt}$ atoms prefer to cluster on the pristine graphene $(\\Delta E_{\\mathrm{d}}=-1.357\\mathrm{eV})$ . This fully supports the experimental observations of the increased size of the Pt clusters and NPs on the graphene substrate in comparison with the N-doped graphene. \n\nA Bader charge analysis (Supplementary Table 2) has also been performed on the adsorption models for the pristine and N-doped graphene to understand the formation of bonds through charge transfer. A charge transfer (about $0.25~e_{\\mathrm{,}}$ ) from the $\\mathrm{Pt}$ atom to the support occurs on the N-doped graphene for the single $\\mathrm{\\Pt}$ atom case, while almost no charge transfer exists between the Pt atom and the pristine graphene. When two $\\mathrm{Pt}$ atoms form a dimer on the N-doped graphene, one $\\mathrm{Pt}$ atom $(\\mathrm{Pt}^{1})$ interacts with the graphene support, whilst the other $(\\mathrm{Pt}^{2})$ atom sits above and bonds directly to $\\bf{\\dot{P}t^{1}}$ . Meanwhile, $\\mathrm{Pt}^{1}$ loses $0.521~e$ to $\\mathrm{Pt}^{2},$ and $\\mathrm{Pt}^{2}$ gains $0.389~e$ due to the strong bonding between $\\mathrm{Pt}^{1}{-}\\mathrm{Pt}^{2}$ . In this cluster configuration, the surrounding $\\mathrm{\\DeltaN}$ and C atoms acquire the remaining $\\left.0.132\\ e\\right.$ , which is less than the single-atom case. This suggests that the two $\\mathrm{Pt}$ atoms result in an increased electron transfer to the substrate when they exist in isolation as compared with forming a dimer; therefore, the stabilization of single atoms is favoured. On the other hand, the $\\mathrm{Pt}$ dimer adsorbed on the pristine graphene leads to an electron transfer of $0.193~e$ from $\\mathrm{Pt}^{1}$ $\\bar{(0.087~e)}$ and the graphene support to $\\mathrm{Pt}^{2}$ , whereas very little electron transfer occurs during the formation of the single isolated atoms on the pristine graphene. Thus, the dimer results in a system of increased stability. It can be concluded from the Bader charge and the $\\Delta E_{\\mathrm{d}}$ that isolated atoms are the preferred form of $\\mathrm{Pt}$ adsorption on the N-doped graphene support, while pristine graphene will favour the formation of Pt clusters. \n\nThe chemical bonding of $\\mathrm{Pt}$ with the N-doped graphene has also led to unique electronic properties of single $\\mathrm{Pt}$ atoms with respect to $\\mathrm{Pt}\\ \\mathrm{NPs}.$ , due to the charge transfer required for bond formation. The single metal atoms still carry a charge after adsorption onto the N-doped graphene substrate, which can be verified by various spectral measurements and computational modelling of the catalysts18,49–51. In our study, it was found that the discrete $5d.$ -orbitals of the single $\\mathrm{\\Pt}$ atoms are mixed with the $\\mathrm{N}{-}2p$ orbitals around the Fermi level (Fig. 4). The calculated Bader charges (Table 2) show that the single Pt atoms are positively charged, where the N atom obtains the electron. In this case, the single Pt atoms on the N-doped graphene contain more unoccupied $\\dot{5}d$ densities of states. On H chemisorption (Fig. 4b), the $5d$ orbitals of the $\\mathrm{Pt}$ atoms interact strongly with the 1s orbital of the $\\mathrm{~H~}$ atoms, leading to electron pairing and hydride formation. In addition, more Pt (5d) states are found above the Fermi level, which is consistent with the calculated charge transfer from the $\\mathrm{Pt}$ atoms to the H atoms. To fully understand the unique electronic properties of the single Pt atom catalysts for the HER, Pt clusters were also examined. As shown in Supplementary Fig. 16, the electronic properties for H adsorption on Pt clusters was investigated using a typical cluster of $\\mathrm{Pt}_{44}$ (ref. 52). On the basis of the partial density of states and Bader charge analysis of both H adsorption on $\\mathrm{Pt}_{44}$ and on the single $\\mathrm{Pt}$ atoms/NGNs system (Table 2, Fig. 4 and Supplementary Fig. 16) it was found that the electron transfer from each surface Pt atom of $\\mathrm{Pt}_{44}$ to $\\mathrm{~H~}$ is $<0.1\\ e$ , which is less than that of the single $\\mathrm{\\Pt}$ atoms $\\left(\\begin{array}{l}{+0.421~e}\\end{array}\\right)$ . This suggests that upon H adsorption, each $\\mathrm{Pt}$ atom of the $\\mathrm{Pt}_{44}$ cluster remains metallic, while the single Pt atoms on the NGNs become nonmetallic through the donation of electrons to both the substrate and H atoms. This leads to the unique electronic structure of the single $\\mathrm{Pt}$ atoms on the NGNs and is expected to be the primary reason of the increased HER activity of the ALD50Pt/NGNs sample. \n\nOur XANES data have experimentally shown that the ALD Pt atoms do in fact have a higher total unoccupied density of $5d$ states, which agrees with the partial density of states calculation. \n\n![](images/7fd3dfa6e1a4515ad5d6ffdbcd866bfcd00a710dd38813fa80064cc0c6ca58f0.jpg) \nFigure 4 | The electronic structure of a single Pt atom before and after hydrogen adsorption. Partial density of states (PDOS) of (a) non-H and $(\\pmb{\\ b})$ two H atoms adsorbed on a single $\\mathsf{P t}$ atom of ALDPt/NGNs. The Fermi level is shifted to zero. The upper part of the panel shows the PDOS of graphene, the middle part of the panel gives the PDOS of the N atom and the lower part of the panel exhibits the PDOS of the $d$ orbital of Pt. \n\nPrevious research has suggested that a change in the electronic properties of catalysts will affect the catalytic performance52. Thus, we carried out a series of DFT calculations to obtain a fundamental understanding of the unexpectedly high electrocatalytic activity of the single-atom catalysts. For the HER in acidic media, the overall HER pathway $(\\dot{\\mathrm{H}^{+}}+e^{-}\\rightarrow1/2\\mathrm{H}_{2})$ can be divided into two separate pathways comprising either the Volmer–Heyrovsky or the Volmer–Tafel mechanism53,54. The first step of both pathways involves the bonding of the hydrogen ion to the catalyst, $\\mathrm{H}^{+}\\dot{+}e^{-}\\rightarrow\\mathrm{H}^{*}$ (Volmer reaction), where $\\mathrm{H^{*}}$ indicates an available surface site on the catalyst for hydrogen adsorption. In the next stage, the molecular hydrogen can be released through the Heyrovsky $(\\mathrm{H}^{+}+e^{-}+\\dot{\\mathrm{H}}^{*}\\xrightarrow{}\\mathrm{H}_{2}^{\\uparrow}.$ ) or the Tafel $(\\mathrm{H}^{*}\\to\\bar{1/2}\\mathrm{H}_{2}^{\\uparrow}$ ) reaction. Many previous studies55–57 have shown that the Tafel mechanism in the electrocatalytic HER is preferred at high H coverage conditions on both $\\mathrm{Pt}$ surfaces and Pt NPs. To verify the proposed HER mechanism, we performed a computational study on the single $\\mathrm{Pt}$ atom catalysts to gain detailed insights into the HER process. The average $\\mathrm{Pt\\mathrm{-}H}$ distance for the H chemisorption configuration was found to be \n\n
Table 2 | Calculated bond lengths and the Bader charge of the non-H and two H atoms adsorbed on the single Pt atom of ALDPt/NGNs.
IPt-n (A) IPt-H (A)
2.105Bader charge (e) Pt NH
-1.202-0.073
Hydrogen adsorption Non-H2.3091.659+0.421-0.193 -1.076
1.580 +0.278
\n\nHere the bond lengths of Pt–N $(I_{P t-N})$ and Pt–H $(I_{P t-H})$ are listed. The Bader charge for both Pt, N and $\\mathsf{H}$ are shown before and after H adsorption. \n\n$1.623\\mathring\\mathrm{A}$ , which was similar with the cases of $\\mathrm{~H~}$ adsorbed on Pt surfaces and nanoclusters58,59. It was also determined that the adsorption strengths of both $\\mathrm{H}$ and $\\mathrm{H}_{2}$ decreased with an increase in the number of adsorbed $\\mathrm{~H~}$ atoms, eventually leading to a minimum value when four $\\mathrm{H}$ atoms were adsorbed, as shown in the Supplementary Fig. 17. In the presence of a single H atom, the most optimal orbital interaction with the $\\mathrm{Pt}$ catalyst results in the bond formation with the most favourable $\\mathrm{Pt}$ orbital, $d_{z^{2}},$ with a corresponding adsorption energy of $0.8\\mathrm{eV}$ . As the number of interacting H atoms is increased, their bond formation with $\\mathrm{\\Pt}$ is affected by the electrostatic repulsion between the $\\mathrm{~H~}$ atoms. The Pt to H interaction now depends on the number of interacting H atoms, and the distinct orbitals for bond formation becomes a compromise between the $_\\mathrm{H-H}$ electrostatic repulsion and the orbital interaction of $\\mathrm{Pt\\mathrm{-}H}$ . Specifically in the case of two $\\mathrm{~H~}$ atoms, the interacting orbitals between the H atoms and the Pt catalyst become the $d_{y z}$ and $d_{x^{2}-y^{2}}$ (Supplementary Fig. 18a), resulting in a corresponding adsorption energy of $0.735\\mathrm{eV}$ per H. Furthermore, when three $\\mathrm{~H~}$ atoms adsorb onto a single Pt atom, two of the $\\mathrm{~H~}$ atoms automatically form an $\\mathrm{H}_{2}$ dimer, due to the fact that the initial two $\\mathrm{H}$ atoms have occupied the two empty $5d$ orbitals of the $\\mathrm{Pt}$ catalyst. The resulting corresponding adsorption energy for three H atoms is $0.514\\mathrm{eV}$ per H. Finally, as the number of $\\mathrm{~H~}$ atoms reaches four (Supplementary Fig. 18c), the interaction between the $\\mathrm{Pt}$ and H atoms are through the $d_{y z}$ and $d_{x^{2}-y^{2}}$ orbitals, which can effectively avoid the repulsion between the $\\dot{\\mathrm{~H~}}$ atoms. The corresponding adsorption configuration is one in which an $\\mathrm{H}_{2}$ dimer and two isolated H atoms are formed with an adsorption energy of $0.458\\mathrm{eV}$ per H. The maximum number of adsorbed $\\mathrm{~H~}$ atoms in this situation is four, as $\\mathrm{Pt}$ no longer has empty $5d$ orbitals or physical space to allow for the interaction with an additional H atom. \n\nWe further calculated the reaction pathways and activation barriers based on the number of adsorbed $\\mathrm{~H~}$ atoms to verify the proposed HER mechanism on the Pt/NGNs supports, as shown in the Supplementary Fig. 19. The calculated activation barrier was completed for the two models: a low loading of two $\\mathrm{H}$ atoms and a high loading of four H atoms, resulting in energies of 0.664 and $0.571\\mathrm{eV}$ , respectively. As previously discussed, the adsorption energy of a H atom on the single Pt atom catalyst decreases with an increase in the number of adsorbed H atoms (Supplementary Fig. 17), which promotes the formation of the $\\mathrm{H}_{2}$ molecules. The adsorption of two $\\mathrm{~H~}$ atoms on $\\mathrm{\\Pt}$ (Supplementary Fig. 18a,b) results in a transformation of the hybrid orbital between the $\\mathrm{~H~}$ and $\\mathrm{Pt}$ atoms to change from $\\dot{d_{x^{2}}}-y^{2}+d_{y z}$ to $d_{x y}+d_{y z}$ when forming the $\\mathrm{H}_{2}$ molecule. This orbital transformation results in the calculated energy barrier of $0.664\\mathrm{eV}$ . On the other hand, when considering four H atoms, two reaction models previously outlined must be considered. The first model is the adsorption of two isolated H atoms and one $\\mathrm{H}_{2}$ dimer, which results in the transformation of the hybrid orbital between the $\\mathrm{~H~}$ and $\\mathrm{Pt}$ atoms to change from $d_{x^{2}-y^{2}}+d_{y z}$ to $d_{x y}+d_{y z}$ with an energy barrier of $0.571\\mathrm{eV}$ Second, the adsorption of two $\\mathrm{\\ddot{H}}_{2}$ dimers on $\\mathrm{Pt}$ results in a decreased adsorption energy of $0.336\\mathrm{eV}$ per H in comparison with the four H atom model, which should further promote the ease of $\\mathrm{H}_{2}$ production on the $\\mathrm{Pt}$ atom. Importantly, it should be noted that the energy barrier for $\\mathrm{H}_{2}$ formation is lower when four $\\mathrm{~H~}$ atoms are present, thus clarifying that the $\\mathrm{H}_{2}$ formation on single $\\mathrm{\\Pt}$ atom catalysts is preferred at high H coverage. Moreover, the calculated activation barriers for both the two H and four $\\mathrm{~H~}$ atoms models is smaller than that of the conventional $\\mathrm{Pt}$ (111) surface $(\\sim0.85\\mathrm{eV})^{56,57}$ . The decreased activation barrier calculated for the HER of the single $\\mathrm{Pt}$ atoms on N-doped graphene is consistent with our experimentally observed fast HER kinetics. \n\nFor practical applications concerning single-atom catalysts, a high activity and good stability are paramount to ensure a competitive performance is achieved in comparison with conventional NP catalysts. Furthermore, the performance will rely on achieving a high density of single atoms to ensure that the number of active sites is not reduced. To examine this effect, the performance of 50 ALD cycles was compared with 25 cycles. It was found that the current density of the ALD25Pt/NGNs sample was below that of commercial $\\mathrm{Pt/C}$ catalysts, resulting in the lowest current density shown in Supplementary Fig. 20. The low specific activity of the ALD25Pt/NGNs sample may result from a low density of single Pt atoms/clusters (Pt loading of $0.19\\%$ on the N-doped graphene. The low Pt density could be an effect of the low cycle number and nucleation delay60 in the first few ALD cycles. \n\nIn conclusion, we fabricated novel Pt catalysts supported by NGNs for the HER using the ALD technique. The size of the Pt catalysts ranged from single atoms, sub-nanometre clusters, to NPs, which were precisely controlled by adjusting the number of ALD cycles. Single Pt atoms and clusters showed exceptionally high activity and stability as HER catalysts compared with commercial $\\mathrm{\\Pt/C}$ catalysts. The remarkable performance of the single $\\mathrm{Pt}$ atoms and clusters arise from their small size and the unique electronic structure originating from of the adsorption of the single $\\mathrm{Pt}$ atoms on the N-doped graphene, as confirmed by XANES and DFT analysis. Our work provides a promising approach for the design of highly active and stable nextgeneration catalysts based on single $\\mathrm{Pt}$ atoms and clusters, which have a great potential to reduce the high cost of industrial commercial noble-metal catalysts. \n\n# Methods \n\nSynthesis of GNs and NGNs. Graphite oxide was first obtained by a modified Hummers method previously reported by our group61,62. The received graphite oxide was then rapidly exfoliated via a thermal treatment at $1{,}050^{\\circ}\\mathrm{C}$ under Ar atmosphere, yielding the product of GNs. NGNs were prepared by post-heating the graphene under high purity ammonia mixed with Ar at $900^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . \n\nALD synthesis of Pt on NGNs. Pt was deposited on the NGNs by ALD (Savannah 100, Cambridge Nanotechnology Inc., USA) using $\\mathrm{MeCpPtMe}_{3}$ and $\\ensuremath{\\mathrm{~\\textrm~{~~}~}}\\ensuremath{\\mathrm{\\mathrm{O}}}_{2}$ as precursors and a procedure similar to one previously reported19. High-purity $\\Nu_{2}$ $(99.9995\\%$ ) was used as both a purging gas and carrier gas. The powder NGNs or GNs were placed in a container inside the ALD reactor chamber. The deposition temperature was $250^{\\circ}\\mathrm{C},$ while the container for $\\mathrm{MeCpPtMe}_{3}$ was kept at $65^{\\circ}\\mathrm{C}$ to provide a steady-state flux of $\\mathrm{MeCpPtMe}_{3}$ to the reactor. Gas lines were held at $100^{\\circ}\\mathrm{C}$ to avoid precursor condensation. For each ALD cycle, 1 s of the $\\mathrm{MeCpPtMe}_{3}$ pulse and 5 s of the $\\mathrm{O}_{2}$ pulse were separated by a $20\\mathrm{~s~}\\ensuremath{\\mathrm{N}_{2}}$ purge. The size, density and distribution of the Pt catalysts on the NGNs or GNs were precisely controlled by adjusting the number of ALD cycles. \n\nPhysical characterization. The ADF STEM images were acquired using an FEI Titan 80–300 Cubed TEM equipped with a monochromator, hexapole-based aberration corrector (Corrected Electron Optical Systems GmbH) in both the probe and imaging lenses, and a high-brightness gun (XFEG) operated with an $80\\mathrm{kV}$ accelerating voltage. High-resolution transmission electron microscopy was performed using an FEI 80–300 Cryo-Twin TEM with a Schottky field emission gun under negative $C_{s}$ imaging conditions using a hexapole-based aberration \n\ncorrector in the imaging lens and the electron source operated at $300\\mathrm{kV}$ accelerating voltage. Samples were baked under vacuum at $100^{\\circ}\\mathrm{C}$ before imaging to prevent beam contamination. \n\nX-ray absorption spectroscopy. XANES measurements of the Pt $\\mathbf{L}_{2}$ -edge and the Pt $\\mathrm{L}_{3}$ -edge were conducted on the 06ID superconducting wiggler sourced hard X-ray microanalysis beamline at the Canadian Light Source. Each sample spectra were collected in fluorescence yield using a solid-state detector, while the high-purity Pt metal foil spectra were collected in transmission mode for comparison and monochromatic energy calibration. \n\nWL intensity analysis was conducted based on previous research38,40. In this method, the Pt $\\mathrm{\\DeltaL}_{3}$ -edge WL intensity was obtained by subtracting the Pt $\\mathrm{L}_{3}$ -edge XANES from the corresponding XANES of Au. The area under the difference curve was integrated between the two vertical bars, and $\\Delta A_{3}$ and $\\Delta A_{2}$ were calculated using the following expressions: \n\n$$\n\\Delta A_{3}=\\int\\mu(\\mathrm{Pt})_{\\mathrm{L}_{3}\\mathrm{WL}}-\\mu(\\mathrm{Au})_{\\mathrm{L}_{3}\\mathrm{WL}}\n$$ \n\n$$\n\\Delta A_{2}{=}\\int\\mu(\\mathrm{Pt})_{\\mathrm{L}_{2}\\mathrm{WL}}{-\\mu(\\mathrm{Au})_{\\mathrm{L}_{2}\\mathrm{WL}}}\n$$ \n\nAccording to Sham et al.40, these values are related to the following theoretical expressions: \n\n$$\n\\Delta A_{3}{=}C_{0}N_{0}E_{3}(R_{d}^{2p_{2/3}})^{2}\\left[\\frac{6h_{5/2}+h_{3/2}}{15}\\right]\n$$ \n\n$$\n\\Delta\\mathrm{A}_{2}{=}C_{0}N_{0}E_{2}\\left(R_{d}^{2p_{1/2}}\\right)^{2}\\left(\\frac{1}{3}h_{3/2}\\right)\n$$ \n\nwhere $C_{0}{=}4\\pi r^{2}\\alpha/3$ $\\alpha$ is the fine structure constant), $N_{0}$ is the density of $\\mathrm{Pt}$ atoms, $h_{j}$ is the 5d hole counts, $R$ is the radial transition matrix element, and $E_{2}$ and $E_{3}$ are the corresponding edge thresholds $(E_{\\mathrm{o}})$ for the $\\mathrm{L}_{2}$ - and $\\mathrm{L}_{3}$ -edges, respectively. By assuming that the $R$ terms are similar for both edges \n\n$$\nC=C_{0}N_{0}R^{2}\n$$ \n\nand with this approximation \n\n$$\nh_{\\frac{5}{2}}{=}\\frac{1}{2C}\\left[5\\frac{E_{2}}{E_{3}}\\Delta A_{3}-\\Delta A_{2}\\right]\n$$ \n\n$$\nh_{3/2}=\\left[{\\frac{3\\Delta A_{2}}{C}}\\right]\n$$ \n\nThe $C$ value for these equations was previously derived for the Pt metal as $7.484\\times10^{4}\\mathrm{cm}^{-1}$ (ref. 63). \n\nElectrochemical characterization. A three-compartment cell was used for the electrochemical measurements with a glassy carbon rotating-disk electrode (Pine Instruments) as the working electrode. $\\mathrm{Hg/Hg_{2}S O_{4}}$ electrode and a $\\mathrm{\\Pt}$ wire were used as the reference and the counter electrode, respectively. The potentials presented in this study are referred with respect to RHE. \n\nThe catalyst dispersions were prepared by mixing $3\\mathrm{mg}$ of catalyst in a $2\\mathrm{ml}$ aqueous solution containing $\\mathrm{1ml}$ of isopropyl alcohol and $30\\upmu\\mathrm{l}$ of $5\\mathrm{wt\\%}$ Nafion solution. Following the solution preparation, the mixture was ultrasonicated for $30\\mathrm{min}$ . Next, the working electrode was created by transferring $10\\upmu\\mathrm{l}$ of the aqueous catalyst dispersion onto the glassy carbon rotating disk electrode $(0.196\\mathrm{cm}^{2})$ . The working electrode was rotated at $1{,}600\\mathrm{r.p.m}$ . to remove the $\\mathrm{H}_{2}$ gas bubbles formed at the catalyst surface. \n\nComputational methods. Our calculations are performed based on DFT calculations, as implemented in the Vienna ab initio package64,65. The general gradient approximation of Perdew–Burke–Ernzerhof is adopted for the exchange-correlation functional66. Moreover, the electron wave functions were expanded by a plane wave cutoff of $400\\mathrm{eV}$ . The $(5\\times5\\times1)$ supercell N-doped graphene contains $48\\mathrm{~C~}$ atoms and $^\\textrm{\\scriptsize1N}$ atom was constructed by a periodic boundary condition, and the vacuum layers were set to be larger than $20\\mathrm{\\AA}$ to avoid periodic interaction. Reciprocal space was performed by the Monkhorst–Pack special $k$ -point scheme with $5\\times5\\times1$ grid meshes for structure relaxation for the $\\mathrm{\\Pt}$ adsorbed on N-doped graphene. Atomic relaxation was performed until the total energy variation was smaller than $10^{-6}\\mathrm{eV}$ and all forces on each atom were $<0.0\\dot{1}\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . The van der Waals density functional67,68 approach was used to evaluate the effect of the van der Waals interaction68. \n\nWe determined the free energy barrier for the HER on the Pt adsorbed on N-doped graphene according to the Volmer–Tafel route using the climb image nudged elastic band method69. A set of images $(N=9)$ is uniformly distributed along the reaction path connecting the initial and final states optimized in our simulation. To ensure the continuity of the reaction path, the images are coupled with elastic forces, and each intermediate state was fully relaxed in the hyperspace perpendicular to the reaction coordinate. The Bader charge analysis70 was \n\nperformed to quantitatively estimate the amount of charge transfer between the adsorbed Pt (or H) and the N-doped graphene. \n\nDate availability. The data that support the findings of this study are available from the corresponding authors on request. \n\nReferences \n1. Tong, W., West, A., Cheung, K., Yu, K.-M. & Tsang, S. C. E. Dramatic effects of gallium promotion on methanol steam reforming Cu–ZnO catalyst for hydrogen production: formation of $5\\textup{\\AA}$ copper clusters from $\\mathrm{Cu{-}Z n G a O_{x}}$ . ACS Catal. 3, 1231–1244 (2013). \n2. Crabtree, G. W., Dresselhaus, M. S. & Buchanan, M. V. The hydrogen economy. Phys. Today 57, 39–44 (2004). \n3. Yu, K. M. K. et al. Non-syngas direct steam reforming of methanol to hydrogen and carbon dioxide at low temperature. Nat. Commun. 3, 1230 (2012). \n4. Chorkendorff, I. & Niemantsverdriet, J. W. Concepts of Modern Catalysis and Kinetics (Wiley-VCH, 2003). \n5. Subbaraman, R. et al. Enhancing hydrogen evolution activity in water splitting by tailoring $\\mathrm{Li^{+}}$ - $\\cdot\\mathrm{Ni}(\\mathrm{OH})_{2}$ -Pt interfaces. Science 334, 1256–1260 (2011). \n6. Subbaraman, R. et al. Trends in activity for the water electrolyser reactions on 3d $\\mathrm{M(Ni,Co,Fe,Mn)}$ hydr(oxy)oxide catalysts. Nat. Mater. 11, 550–557 (2012). \n7. Yin, H. J. et al. Ultrathin platinum nanowires grown on single-layered nickel hydroxide with high hydrogen evolution activity. Nat. Commun. 6, 6430 (2015). \n8. Merki, D. & Hu, X. L. Recent developments of molybdenum and tungsten sulfides as hydrogen evolution catalysts. Energ. Environ. Sci. 4, 3878–3888 (2011). \n9. Chen, S., Duan, J., Tang, Y., Jin, B. & Qiao, S. Molybdenum sulfide clustersnitrogen-doped graphene hybrid hydrogel film as an efficient threedimensional hydrogen evolution electrocatalyst. Nano Energy 11, 11–18 (2015). \n10. Voiry, D. et al. Enhanced catalytic activity in strained chemically exfoliated $\\mathrm{WS}_{2}$ nanosheets for hydrogen evolution. Nat. Mater. 12, 850–855 (2013). \n11. Gao, M. R. et al. An efficient molybdenum disulfide/cobalt diselenide hybrid catalyst for electrochemical hydrogen generation. Nat. Commun. 6, 5982 (2015). \n12. Zheng, Y. et al. Hydrogen evolution by a metal-free electrocatalyst. Nat. Commun. 5, 3783 (2014). \n13. Duan, J., Chen, S., Jaroniec, M. & Qiao, S. Porous $\\mathrm{C}_{3}\\mathrm{N}_{4}$ nanolayers@Ngraphene films as catalyst electrodes for highly efficient hydrogen evolution. ACS Nano 9, 931–940 (2015). \n14. Liu, J. et al. Metal-free efficient photocatalyst for stable visible water splitting via a two-electron pathway. Science 347, 970–974 (2015). \n15. Stephens, I. E. L. & Chorkendorff, I. Minimizing the use of platinum in hydrogen-evolving electrodes. Angew. Chem. Int. Ed. 50, 1476–1477 (2011). \n16. Esposito, D. V. et al. Low-cost hydrogen-evolution catalysts based on monolayer platinum on tungsten monocarbide substrates. Angew. Chem. Int. Ed. 49, 9859–9862 (2010). \n17. Yang, X. F. et al. Single-atom catalysts: a new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748 (2013). \n18. Qiao, B. T. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}/F e O_{x}}$ . Nat. Chem. 3, 634–641 (2011). \n19. Sun, S. H. et al. Single-atom catalysis using Pt/graphene achieved through atomic layer deposition. Sci. Rep. 3, 1775 (2013). \n20. Uzun, A., Ortalan, V., Hao, Y. L., Browning, N. D. & Gates, B. C. Nanoclusters of gold on a high-area support: almost uniform nanoclusters imaged by scanning transmission electron microscopy. ACS Nano 3, 3691–3695 (2009). \n21. Mackus, A. J. M., Verheijen, M. A., Leick, N., Bol, A. A. & Kessels, W. M. M. Influence of oxygen exposure on the nucleation of platinum atomic layer deposition: consequences for film growth, nanopatterning, and nanoparticle synthesis. Chem. Mater. 25, 1905–1911 (2013). \n22. Yang, M. et al. Catalytically active Au- $\\mathrm{\\partial)(OH)_{x}}$ -species stabilized by alkali ions on zeolites and mesoporous oxides. Science 346, 1498–1501 (2014). \n23. Zhang, X. F. et al. Catalytically active single-atom niobium in graphitic layers. Nat. Commun. 4, 1924 (2013). \n24. Stambula, S. et al. Chemical structure of nitrogen-doped graphene with single platinum atoms and atomic clusters as a platform for the PEMFC electrode. J. Phys. Chem. C 118, 3890–3900 (2014). \n25. George, S. M. Atomic layer deposition: an overview. Chem. Rev. 110, 111–131 (2010). \n26. Marichy, C., Bechelany, M. & Pinna, N. Atomic layer deposition of nanostructured materials for energy and environmental applications. Adv. Mater. 24, 1017–1032 (2012). \n27. Puurunen, R. L. Surface chemistry of atomic layer deposition: A case study for the trimethylaluminum/water process. J. Appl. Phys. 97, 121301 (2005). \n28. Lu, J., Aydin, C., Browning, N. D. & Gates, B. C. Imaging isolated gold atom catalytic sites in zeolite NaY. Angew. Chem. Int. Ed. 51, 5842–5846 (2012). \n29. Wang, S. W. et al. Dopants adsorbed as single atoms prevent degradation of catalysts. Nat. Mater. 3, 274–274 (2004). between Pt and $\\boldsymbol{Z}\\mathrm{r}\\boldsymbol{\\mathrm{C}}$ for highly stable electrocatalysts. Energ. Environ. Sci. 8, 1450–1455 (2015). \n31. Conway, B. E. & Tilak, B. V. Interfacial processes involving electrocatalytic evolution and oxidation of $\\mathrm{H}_{2},$ and the role of chemisorbed H. Electrochim. Acta 47, 3571–3594 (2002). \n32. Zhang, S. R. et al. Catalysis on singly dispersed bimetallic sites. Nat. Commun. 6, 7938 (2015). \n33. Liu, Y. & Mustain, W. E. Evaluation of tungsten carbide as the electrocatalyst support for platinum hydrogen evolution/oxidation catalysts. Int. J. Hydrogen Energ. 37, 8929–8938 (2012). \n34. Jiang, Z. Z., Wang, Z. B., Chu, Y. Y., Gu, D. M. & Yin, G. P. Ultrahigh stable carbon riveted $\\mathrm{Pt}/\\mathrm{TiO}_{2}$ -C catalyst prepared by in situ carbonized glucose for proton exchange membrane fuel cell. Energ. Environ. Sci. 4, 728–735 (2011). \n35. Xia, B. Y. et al. Sandwich-structured $\\mathrm{TiO}_{2}$ -Pt-graphene ternary hybrid electrocatalysts with high efficiency and stability. J. Mater. Chem. 22, 16499–16505 (2012). \n36. Shao-Horn, Y. et al. Instability of supported platinum nanoparticles in low-temperature fuel cells. Top. Catal. 46, 285–305 (2007). \n37. Cheng, N. A. C., Mu, S. C., Pan, M. & Edwards, P. P. Improved lifetime of PEM fuel cell catalysts through polymer stabilization. Electrochem. Commun. 11, 1610–1614 (2009). \n38. Banis, M. N. et al. $\\mathrm{TiSi}_{2}\\mathrm{O}_{\\mathrm{x}}$ coated N-doped carbon nanotubes as Pt catalyst support for the oxygen reduction reaction in PEMFCs. J. Phys. Chem. C 117, 15457–15467 (2013). \n39. Ho, V. T. T., Pan, C.-J., Rick, J., Su, W.-N. & Hwang, B.-J. Nanostructured $\\mathrm{Ti}_{0.7}\\mathrm{Mo}_{0.3}\\mathrm{O}_{2}$ support enhances electron transfer to Pt: high-performance catalyst for oxygen reduction reaction. J. Am. Chem. Soc. 133, 11716–11724 (2011). \n40. Sham, T. K., Naftel, S. J. & Coulthard, I. $\\mathbf{M}_{3,2}$ -edge $\\mathrm{\\DeltaX}$ -ray absorption near-edge structure spectroscopy: an alternative probe to the $\\mathrm{L}_{3,2}$ -edge near-edge structure for the unoccupied densities of d states of 5d metals. J. Appl. Phys. 79, 7134–7138 (1996). \n41. Mansour, A. N., Cook, J. W. & Sayers, D. E. Quantitative technique for the determination of the number of unoccupied $\\mathrm{~d~}$ -electron states in a platinum catalyst using the $\\mathrm{L}_{2,3}$ X-ray absorption-edge spectra. J. Phys. Chem. 88, 2330–2334 (1984). \n42. Hu, P. P. et al. Electronic Metal-support interactions in single-atom catalysts. Angew. Chem. Int. Ed. 53, 3418–3421 (2014). \n43. Qiao, B. et al. Ultrastable single-atom gold catalysts with strong covalent metal-support interaction (CMSI). Nano Res. 8, 2913–2924 (2015). \n44. Kondo, T., Suzuki, T. & Nakamura, J. Nitrogen doping of graphite for enhancement of durability of supported platinum clusters. J. Phys. Chem. Lett. 2, 577–580 (2011). \n45. Chen, Y. G. et al. Enhanced stability of Pt electrocatalysts by nitrogen doping in CNTs for PEM fuel cells. Electrochem. Commun. 11, 2071–2076 (2009). \n46. Bulushev, D. A. et al. Single atoms of Pt-group metals stabilized by N-doped carbon nanofibers for efficient hydrogen production from formic acid. ACS Catal. 6, 3442–3451 (2016). \n47. Cheng, N. et al. Extremely stable platinum nanoparticles encapsulated in a zirconia nanocage by area-selective atomic layer deposition for the oxygen reduction reaction. Adv. Mater. 27, 277–281 (2015). \n48. Wu, J. F. et al. A review of PEM fuel cell durability: degradation mechanisms and mitigation strategies. J. Power Sources 184, 104–119 (2008). \n49. Ghosh, T. K. & Nair, N. N. $\\mathrm{Rh}1/\\upgamma$ - ${\\bf\\cdot A l}_{2}{\\bf O}_{3}$ single-atom catalysis of $\\mathrm{O}_{2}$ activation and CO oxidation: mechanism, effects of hydration, oxidation state, and cluster size. ChemCatChem 5, 1811–1821 (2013). \n50. Hackett, S. F. J. et al. High-activity, single-site mesoporous $\\mathrm{Pd}/\\mathrm{Al}_{2}\\mathrm{O}_{3}$ catalysts for selective aerobic oxidation of allylic alcohols. Angew. Chem. Int. Ed. 119, 8747–8750 (2007). \n51. Zhang, X., Shi, H. & Xu, B. Q. Catalysis by gold: isolated surface ${\\mathrm{Au}}^{3+}$ Ions are active sites for selective hydrogenation of 1, 3-butadiene over $\\mathrm{Au}/\\mathrm{ZrO}_{2}$ catalysts. Angew. Chem. Int. Ed. 44, 7132–7135 (2005). \n52. Norskov, J. K., Bligaard, T., Rossmeisl, J. & Christensen, C. H. Towards the computational design of solid catalysts. Nat. Chem. 1, 37–46 (2009). \n53. Conway, B. & Tilak, B. Interfacial processes involving electrocatalytic evolution and oxidation of $\\mathrm{H}_{2}$ , and the role of chemisorbed H. Electrochim. Acta 47, 3571–3594 (2002). \n54. Parsons, R. The rate of electrolytic hydrogen evolution and the heat of adsorption of hydrogen. Trans. Faraday Soc. 54, 1053–1063 (1958). \n55. Ge, M., Fang, X., Rong, J. & Zhou, C. Review of porous silicon preparation and its application for lithium-ion battery anodes. Nanotechnology 24, 422001 (2013). \n56. Wei, G.-F. & Liu, Z.-P. Restructuring and hydrogen evolution on Pt nanoparticle. Chem. Sci. 6, 1485–1490 (2015). \n57. Sku´lason, E. et al. Modeling the electrochemical hydrogen oxidation and evolution reactions on the basis of density functional theory calculations. J. Phys. Chem. C 114, 18182–18197 (2010). \n58. Okamoto, Y. Comparison of hydrogen atom adsorption on Pt clusters with that on Pt surfaces: a study from density-functional calculations. Chem. Phys. Lett. 429, 209–213 (2006). \n59. Papoian, G., Nørskov, J. K. & Hoffmann, R. A comparative theoretical study of the hydrogen, methyl, and ethyl chemisorption on the Pt (111) surface. J. Am. Chem. Soc. 122, 4129–4144 (2000). \n60. Cheng, N., Shao, Y., Liu, J. & Sun, X. Electrocatalysts by atomic layer deposition for fuel cell applications. Nano Energy. http://dx.doi.org/10.1016/ j.nanoen.2016.01.016 (2016). \n61. Geng, D. et al. High oxygen-reduction activity and durability of nitrogen-doped graphene. Energ. Environ. Sci. 4, 760–764 (2011). \n62. Kibsgaard, J., Gorlin, Y., Chen, Z. & Jaramillo, T. F. Meso-structured platinum thin films: active and stable electrocatalysts for the oxygen reduction reaction. J. Am. Chem. Soc. 134, 7758–7765 (2012). \n63. Mattheiss, L. F. & Dietz, R. E. Relativistic tight-binding calculation of core-valence transitions in Pt and Au. Phys. Rev. B 22, 1663–1676 (1980). \n64. Kresse, G. & Furthmu¨ller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n65. Kresse, G. & Furthmu¨ller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169 (1996). \n66. Perdew, J. P. et al. Atoms, molecules, solids, and surfaces: applications of the generalized gradient approximation for exchange and correlation. Phys. Rev. B 46, 6671 (1992). \n67. Dion, M., Rydberg, H., Schroder, E., Langreth, D. C. & Lundqvist, B. I. Van der Waals density functional for general geometries. Phys. Rev. Lett. 92, 246401 (2004). \n68. Klimes, J., Bowler, D. R. & Michaelides, A. Van der Waals density functionals applied to solids. Phys. Rev. B 83, 195131 (2011). \n69. Henkelman, G., Uberuaga, B. P. & Jo´nsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000). \n70. Henkelman, G., Arnaldsson, A. & J´onsson, H. A fast and robust algorithm for Bader decomposition of charge density. Comput. Mater. Sci. 36, 354–360 (2006). \n\n# Acknowledgements \n\nThis research was supported by Catalysis Research for Polymer Electrolyte Fuel Cells (CaRPE-FC), Natural Sciences and Engineering Research Council of Canada (NSERC), Canadian Light Source (CLS), Canada Research Chair (CRC) Program, Canada Foundation for Innovation (CFI), Ontario Research Fund (ORF), Automotive Partnership of Canada (APC) and the University of Western Ontario. The electron microscopy presented here was completed at the Canadian Center for Electron Microscopy, a facility supported by the Canada Foundation for Innovation, NSERC and McMaster University. L.L.M. was supported by the National Natural Science Foundation of China (NSFC) (grant no. 51572016 and U1530401). The computation supports from Tianhe-JK at the Beijing Computational Science Research Center (CSRC) and the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase) are also acknowledged. \n\n# Author contributions \n\nN.C. designed the project and performed the catalyst preparation, characterizations and catalytic tests; S.S. conducted the STEM image acquisition and N.C. conducted STEM image analyses; M.N.B. carried out measurements and data analyses of EXAFS; J.L. helped with the ALD process; A.R., R.L. and B.X. helped to analyse the data; D.W. and L.-M.L. performed the DFT calculations; X.S., G.A.B. and T.-K.S. proposed, planned, designed and supervised the project. All authors reviewed the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Cheng, N. et al. Platinum single-atom and cluster catalysis of the hydrogen evolution reaction. Nat. Commun. 7, 13638 doi: 10.1038/ncomms13638 (2016). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1016_j.actamat.2015.08.076", + "DOI": "10.1016/j.actamat.2015.08.076", + "DOI Link": "http://dx.doi.org/10.1016/j.actamat.2015.08.076", + "Relative Dir Path": "mds/10.1016_j.actamat.2015.08.076", + "Article Title": "A precipitation-hardened high-entropy alloy with outstanding tensile properties", + "Authors": "He, JY; Wang, H; Huang, HL; Xu, XD; Chen, MW; Wu, Y; Liu, XJ; Nieh, TG; An, K; Lu, ZP", + "Source Title": "ACTA MATERIALIA", + "Abstract": "Recent studies indicated that high-entropy alloys (HEAs) possess unusual structural and thermal features, which could greatly affect dislocation motion and contribute to the mechanical performance, however, a HEA matrix alone is insufficiently strong for engineering applications and other strengthening mechanisms are urgently needed to be incorporated. In this work, we demonstrate the possibility to precipitate nullosized coherent reinforcing phase, i.e., L1(2)-Ni-3(TLA1), in a fcc-FeCoNiCr HEA matrix using minor additions of Ti and Al. Through thermomechanical processing and microstructure controlling, extraordinary balanced tensile properties at room temperature were achieved, which is due to a well combination of various hardening mechanisms, particularly precipitation hardening. The applicability and validity of the conventional strengthening theories are also discussed. The current work is a successful demonstration of using integrated strengthening approaches to manipulate the properties of fcc-HEA systems, and the resulting findings are important not only for understanding the strengthening mechanisms of metallic materials in general, but also for the future development of high-performance HEAs for industrial applications. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.", + "Times Cited, WoS Core": 1963, + "Times Cited, All Databases": 2061, + "Publication Year": 2016, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000365368800020", + "Markdown": "# A precipitation-hardened high-entropy alloy with outstanding tensile properties \n\nJ.Y. He a, H. Wang a, H.L. Huang a, X.D. Xu b, M.W. Chen b, Y. Wu a, X.J. Liu a, T.G. Nieh c, K. An d, Z.P. Lu a, \\* \n\na State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing, Beijing 100083, China \nb Advanced Institute for Materials Research, Tohoku University, Sendai 980-8577, Japan \nc Department of Materials Science and Engineering, the University of Tennessee, Knoxville, TN 37996, USA \nd Spallation Neutron Source, Oak Ridge National Laboratory, TN 37996, USA \n\n# a r t i c l e i n f o \n\nArticle history: \nReceived 11 August 2015 Received in revised form 29 August 2015 \nAccepted 29 August 2015 Available online xxx \nKeywords: \nHigh-entropy alloys \nPrecipitation hardening \nStrengthening mechanisms \nMechanical properties \n3 dimensional atom probe tomography \n\n# a b s t r a c t \n\nRecent studies indicated that high-entropy alloys (HEAs) possess unusual structural and thermal features, which could greatly affect dislocation motion and contribute to the mechanical performance, however, a HEA matrix alone is insufficiently strong for engineering applications and other strengthening mechanisms are urgently needed to be incorporated. In this work, we demonstrate the possibility to precipitate nanosized coherent reinforcing phase, i.e., $\\mathsf{L}1_{2}\\mathrm{-Ni}_{3}(\\mathrm{Ti},\\mathsf{A l})$ , in a fcc-FeCoNiCr HEA matrix using minor additions of Ti and Al. Through thermomechanical processing and microstructure controlling, extraordinary balanced tensile properties at room temperature were achieved, which is due to a well combination of various hardening mechanisms, particularly precipitation hardening. The applicability and validity of the conventional strengthening theories are also discussed. The current work is a successful demonstration of using integrated strengthening approaches to manipulate the properties of fccHEA systems, and the resulting findings are important not only for understanding the strengthening mechanisms of metallic materials in general, but also for the future development of high-performance HEAs for industrial applications. \n\n$\\circledcirc$ 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. \n\n# 1. Introduction \n\nConventional alloy design strategy, which is usually based on one principal constituent and adds other minor elements for further optimization of properties and performances, has created a variety of metallic materials for our daily life. Recently, a revolutionary alloy design concept, namely, high-entropy alloy (HEAs) concept, was proposed and the basic idea is to simultaneously alloy multiple principal elements in equimolar or near equimolar ratios to increase the configuration entropy to stabilize the structures. Since its inception, this new family of alloys has been attracted extensive attention due to their unique properties and the related scientific importance [1e5]. Due to their high mixing entropy, these alloys tend to form single-phase structures with a high symmetry, such as fcc (face-centered cubic), bcc (body-centered cubic), and hcp (hexagonal close-packed) [4,6e8]. They have been demonstrated to exhibit several special intrinsic characteristics, for example, high configuration entropy [9], sluggish atomic diffusion [10], and large lattice distortion [3,11]. These features are anticipated to enhance formation and stabilization of solid solution phases and impede dislocation motion, thereby improving the mechanical strength, particularly at high temperatures. Nevertheless, recent studies [12e14] indicate that a HEA matrix alone, especially single-phase fcc structure, is insufficiently strong for practical applications. In other words, other strengthening mechanisms are needed so that desirable mechanical properties can be obtained. While, qualitative descriptions and equations of strengthening mechanisms for traditional solid solution alloys are well established, such theories are missing for the highly concentrated HEAs because it is difficult to clearly identify their “solvent” and “solutes”. Therefore, strengthening mechanisms in these emerging metallic materials must be carefully investigated so that reliable theories can be established. \n\nFeCoNiCrMn is generally recognized as a “model” HEA with a simple fcc structure, and exhibits both outstanding ductility and fracture toughness property [12], even at the liquid nitrogen temperature. However, its strength is relatively low, only around $200~\\mathrm{MPa}$ in the as-cast state [13,14], which is far from practical structural applications. To make it useful, additional strengthening methods, without sacrificing its ductility, must be induced in the alloy and, the underlying mechanisms need to be scrutinized so that general understanding of the strengthening of HEAs can be achieved. \n\nAlong this line, Otto et al. made attempts to enhance the strength of this fcc-FeCrNiCoMn by grain refinement and found that the room-temperature yield strength of the alloy increased from 200 to 350 MPa when the grain size was reduced from 144 to $4.4~{\\upmu\\mathrm{m}}$ [13]. This work suggests grain boundary hardening can be induced in the fcc-FeCrNiCoMn alloy, but the hardening is seemingly not extraordinary. To further improve the strength without losing plastic stability, one must, therefore, rely on other mechanisms, such as precipitation hardening, which would require a modification of the chemical composition of the alloy. \n\nIn terms of precipitation hardening in HEAs, published results appear somewhat sketchy. A few publications reported the observation of precipitation behavior in HEAs, e.g., in a mixed fcc $^+$ bcc $\\mathrm{CuCr}_{2}\\mathrm{Fe}_{2}\\mathrm{NiMn}$ [15], a mixed fcc $^+$ bcc $\\mathsf{A l}_{0.3}\\mathsf{C r F e}_{1.5}\\mathsf{M n N i}_{0.5}$ and single-phase bcc- ${\\bf\\cdot A l}_{0.5}{\\bf C r F e}_{1.5}{\\bf M n N i}_{0.5}$ [16]. The precipitates in these HEAs were relatively bulky (generally, larger than $\\upmu\\mathrm{m}$ in size), significantly different from the distribution of fine precipitates $\\scriptstyle(\\sim\\mathrm{nm})$ commonly observed in traditional precipitation-hardened alloys. Nevertheless, Yeh et al. have reported the presence of nano-scale precipitates in some HEAs [5]. In this case, a distribution of extremely tiny precipitates (diameter ${\\sim}3{\\mathrm{-}}7\\ \\mathrm{nm}{\\cdot}$ was observed in a CuCoNiCrAlFe HEA with a modulated structure. Tensile properties and possible strengthening of the alloy were unfortunately not evaluated. However, these observations are quite encouraging and suggest that proper selection of the chemical composition combined with appropriate thermomechanical treatment may offer the opportunity to manipulate precipitation strengthening of HEAs. \n\nIn the present paper, we demonstrate that minor alloy additions of Ti and Al to a single-phase fcc-FeCoNiCr HEA can induce the formation of $\\mathtt{L}1_{2}$ coherent nano-size precipitates in the alloy matrix. Subsequently, both yield and ultimate tensile strengths of the alloys are drastically increased. The strengthening efficacies from various strengthening mechanisms are evaluated based on the resulting microstructure in the current highly concentrated HEA matrix. \n\n# 2. Experimental \n\nTwo HEA compositions were prepared by vacuum arc melting: the base alloy, FeCoNiCr (in equimolar ratio) for comparison, and another with the nominal composition of $\\mathrm{(FeCoNiCr)_{94}T i_{2}A l_{4}}($ (at.%). The alloy ingots were prepared by arc-melting a mixture of pure metals (purity larger than $99.9\\%$ ), and re-melted at least four times to ensure homogeneity. The master ingots were then drop-casted into a copper mold with a dimension of $10\\times10\\times60\\mathrm{\\mm}^{3}$ , and subsequently tube-sealed and homogenized at 1473 K for $^{4\\mathrm{h}}$ . \n\nTwo thermomechanical procedures were conducted on the alloyed HEA to obtain fine structures. The first treatment, P1, includes an initial cold rolling of $30\\%$ , subsequent annealing at 1273 K for $^{2\\mathrm{h}}$ , aging at $1073\\mathrm{K}$ for $^{18\\mathrm{~h~}}$ , and followed by water quenching. The second process, P2, includes an initial cold rolling of $70\\%$ , and then aging at 923 K for $^{4\\mathrm{h}}$ , followed by water quenching. Therefore, four different HEA samples were prepared, i.e., the as-homogenized FeCoNiCr (alloy A), as-homogenized $\\mathrm{(FeCoNiCr)_{94}T i_{2}A l_{4}}$ (alloy B), P1 and P2. \n\nA CMT4105 universal electronic tensile testing machine was employed for tensile tests at room temperature with a nominal strain rate of $1\\times10^{-3}\\ s^{-1}.$ . The dog bone-shaped tensile samples had a gauge length of $20~\\mathrm{mm}$ , a width of $5\\mathrm{mm}$ and a thickness of $1.3~\\mathrm{mm}$ . The surface of test samples was polished down to a 2000- grit SiC paper to eliminate scratches. \n\nConsidering the relative low accuracy of X-ray diffraction (XRD) in nano-precipitates detection, phase identification in this study was conducted by neutron diffraction, at the VULCAN instrument, beam line 7, Oak Ridge National Laboratory Spallation Neutron Source (ORNL, SNS), USA, at room temperature. The microstructure was characterized by a Zeiss Supra55 scanning electron microscope (SEM) and a JEOL ARM200 transmission electron microscope (TEM) equipped with an objective lens corrector and a thermal fieldemission gun (FEG). SEM specimens were initially polished to 2000-grit SiC paper and, subsequently, electrochemically polished for the final surface clarification using a $\\mathrm{HClO}_{4};\\mathrm{C}_{2}\\mathrm{H}_{6}0=1{\\cdot}9$ solution with a direct voltage of $30\\mathrm{V}$ at room temperature. TEM samples were primarily punched to $\\Phi3\\ \\mathrm{mm}$ circle sheets and then ground to about $50~{\\upmu\\mathrm{m}}$ followed by twin-jet electro-polishing using a mixed solution of $\\mathrm{HNO}_{3}{:}\\mathrm{CH}_{4}0=1{:}4$ with a direct voltage of $28\\mathrm{V}$ and a current of $60~\\mathrm{{mA}}$ at a temperature around $233\\mathrm{K}$ \n\nSharp tip specimens for atom probe tomography (APT) were made by a two-step electrochemical polishing. The $0.3\\ \\mathrm{mm}\\times0.3\\ \\mathrm{mm}$ blanks were cut by low speed diamond saw, followed by electrochemical polishing using $10\\%$ perchloric acid at a direct voltage of $15{\\mathrm{V}},{\\mathrm{}}$ the tips were then polished by using weaker electrolyte $(2\\%)$ of perchloric acid at a direct voltage of $\\boldsymbol{8\\vee}$ . Data acquisition was performed by using a local electrode atom probe (LEAP 4000HR) equipped with an energy-compensated reflectron by which the mass resolution can be greatly improved. The APT acquisition temperature was set at ${\\sim}60~\\mathrm{K}$ and the pulse frequency and pulse fractions were $200~\\mathrm{kHz}$ and $20\\%$ , respectively. CAMECA Integrated Visualization and Analysis Software (IVAS 3.6.8) package was used for the data processing and three-dimensional (3D) atomic reconstruction. \n\nShear modulus and Poisson's ratio of polished specimens with a dimension of $5.5\\times5.5\\times2.5~\\mathrm{mm}^{3}$ were measured using RUSpec resonant ultrasound spectrometer, Teclab, USA. To determine the dislocation density using the Williamson-Hall method, XRD tests were conducted using $\\mathtt{C u K}\\mathtt{a}$ radiation (Rigaku Dmax 2500 V) with a scanning 2q range of $40^{\\circ}-100^{\\circ}$ and a step of $0.02^{\\circ}$ . Annealed single crystal Si powder was also tested to define the instrument peak broadening in this method. \n\n# 3. Results \n\n# 3.1. Neutron diffraction and SEM results \n\nNeutron diffraction patterns of the four HEA specimens, i.e., the homogenized FeCoNiCr (Alloy A) and $(\\mathrm{FeCoNiCr})_{94}\\mathrm{Ti}_{2}\\mathrm{Al}_{4}$ (Alloy B), and two thermomechanically processed $\\mathrm{(FeCoNiCr)_{94}T i_{2}A l_{4}}$ alloys P1 and P2, respectively, are presented in Fig. 1. A single family of fcc peaks are clearly observed for alloy A and B. By contrast, extra series of minor peaks identified as $_{\\mathrm{L1}_{2}-\\mathrm{Ni}_{3}(\\mathrm{Ti},\\mathrm{Al})}$ are detected in P1 and P2 samples, indicating the precipitation of secondary phases. It should also be noticed that, there are still two weak peaks at ${\\sim}1.4\\mathring{\\mathsf{A}}$ in alloy A and B and another one at ${\\sim}1.1\\mathrm{\\AA}$ in alloy P1 and P2 being unknown. Due to the relative low intensity and limited amount of peaks, one can hardly determine the exact phase structure they belong to. Nevertheless, the matrix of the four alloys is mainly composed of an fcc structure. \n\nFig. 2 shows the corresponding SEM micrographs of the four kinds of HEA samples. As can be seen, both A and B alloys appear to be single-phase structure in Fig. 2a and b, respectively, with only few dirt on the surface probably introduced during the electropolishing process. In accordance with the neutron diffraction results, however, both P1 (Fig. 2c) and P2 (Fig. 2d) show a significant amount of fine precipitates. In addition to these fine precipitates, a few blocky particles at the micro-scale were observed to form near the grain boundary region in P1 (marked by arrows in Fig. 2c). Additional study of these large particles using TEM-EDX indicates that they are enriched in Ni, Al and Ti, and the corresponding TEM selected area electron diffraction (SAED) patterns (not shown) identify it as the $\\mathrm{\\DeltaNi_{2}A l T i}$ phase; the results are summarized in Table 1. According to a recent work by Choudhuri et al. [17], this phase has a $\\mathtt{L2}_{1}$ Heusler-like structure (strong but brittle at room temperature), and is incoherent with the fcc HEA matrix. An enlarged view of the precipitate morphology is presented in Fig. 2e and f for P1 and P2, respectively. In P1 (Fig. 2e), two regions with distinct precipitate morphologies are observed (as marked). Region I consists of spherical particles with a size less than $40\\ \\mathrm{nm}$ and homogenously distributed inside the grain, whilst Region II consists of plate-like precipitates with a width larger than $70~\\mathrm{nm}$ . In P2 (Fig. 2f), however, precipitates appear to be more uniform throughout the entire matrix, with a diameter ranging from 20 to $100\\mathrm{nm}$ . The $\\mathrm{L}2_{1}\\mathrm{Ni_{2}A l T i}$ particles are also found, but in a finer scale of ${\\sim}100\\ \\mathrm{nm}$ and they appear as irregular blocks, as arrowed in Fig. 2f. Further detailed structure description and strengthening mechanism analysis of this $\\mathtt{L2}_{1}$ phase are considered not important, because of the relative low volume fraction in both P1 and P2. \n\n![](images/316e3fa7e49faff54b1c96b2fd53a8de859f7787a2c9b6a80e7d2a0289bbf731.jpg) \nFig. 1. Neutron diffraction patterns of the four HEA samples. \n\n# 3.2. TEM characterization \n\nSince the precipitation sequence in alloy P1 and P2 are expected to be similar with only some minor differences, for simplicity and clarity, we mainly focus on the discussion of the microstructure in P1. A representative bright field (BF) TEM image taken from P1 is presented in Fig. 3a, which gives a general view of two regions of nano-precipitates. In the right insets of Fig. 3a, three SAED patterns along different Z-axes taken from Region I are shown. The main diffraction spots confirm that the matrix is indeed fcc, whilst additional weak spots observed in all the images affirm the presence of precipitates which has a superlattice $\\mathtt{L}1_{2}$ structure. Together with the neutron diffraction results, we can eventually identify the $\\mathbf{L}1_{2}$ phase as $\\mathrm{{Ni_{3}(T i,\\ A l)}}$ type $\\boldsymbol{\\gamma}^{\\prime}$ phase (hereafter denoted as $\\boldsymbol{\\gamma}^{\\prime}$ phase). Similar diffraction patterns were also obtained in Region II (e.g., the image along Z-[1 1 0] shown in the left inset of Fig. 3a), suggesting that precipitates in both regions are the same, although their morphologies are obviously different. The lattice parameter of both the disordered fcc matrix and precipitates were measured to be $0.358~\\mathrm{nm}$ . The lattice mismatch appears to be extremely small, revealing a coherent interface between them. \n\nFurther, two corresponding bright and dark field images are shown in Fig. 3b and c. With a upper region boundary and a under twin boundary, a group of spherical $\\boldsymbol{\\gamma}^{\\prime}$ phase particles dispersed in the Region I matrix is demonstrated. To reveal the interfacial coherence, a high resolution TEM picture showing the interface between a particle and the fcc matrix is presented in Fig. 3d. The fast Fourier transformation (FFT) images indicate a (1 1 1) atomic plane, for both matrix and particle. In the figure, two groups of atoms across the interface are selected, and labeled with different colors, to conveniently distinguish each other: pink for atoms belonging to the particle and green for those of the matrix (seen in Fig. 3d). In this manner, the transition of atomic arrangement across the particle-matrix interface is directly shown. The corresponding lattice sketches are also inserted, exhibiting the typical (1 1 1) plane of atoms of the A1 crystal structure (i.e., the basic fcc structure) and $\\mathbf{L}1_{2}$ crystal structure, for green and pink regions respectively. The blue balls represent small constituent atoms (here are Ni, Fe, Co or Cr) which compose of the A1 matrix lattice, while the orange ones stand for the large atoms of Al or Ti, occupying the face centered position in the superlattice. These results provide us with a visual understanding of the particle-matrix interface structure in detail. \n\n# 3.3. Atom probe tomography (APT) analysis \n\nTo obtain the chemical distribution of the constituent atoms, we employed 3D-APT reconstruction of alloy P1. Atom maps in Region I in P1 with Fe, Co, Cr and Ni, Al, Ti color-coded and resolved in two boxes are given in Fig. 4a. Generally, many visible particles enriched with Ni, Al, Ti in a size of tens of nanometers are embedded in the homogeneous matrix. A $35\\%$ Ni iso-concentration map is further displayed to delineate the outline of particles. In Fig. 4b, the elemental partitioning is shown in a proximity histogram constructed across the interface between the matrix and precipitates. It is noted that, in $\\boldsymbol{\\gamma}^{\\prime}$ phase particles, despite up to $50\\%$ Ni concentration, some of the Ni sites are still taken by substitutional atoms, such as Fe, Co and Cr $.\\sim30\\%$ in total). In Region II, separate plots of each element are shown in Fig. 4c. The depletion or enrichment of each element in some regions easily reveals the plate-like precipitation morphology and its accompanied compositional separation, just as shown in the corresponding proximity histogram of elemental concentration in Fig. 4d. In the precipitates side (on the right-hand-side of the figure), Ni concentration almost reaches 60 at.%, whilst Fe and Cr are largely depleted. Also, the concentration difference between the precipitate and matrix is larger, which means being more close to the components of $\\mathrm{Ni}_{3}\\mathrm{Al}$ compounds than the spherical particles in Region I. From the above observations, we can tentatively conclude that Region II may have initially evolved from Region I during the long aging process. Additional work to identify the kinetic path for precipitate formation is currently underway. \n\n![](images/293ab3f533b75ec087955169055302b5b0746fb775d6782c20adc90e149d5f0e.jpg) \nFig. 2. SEM micrographs of electrochemical polished HEAs; (a) alloy A, (b) alloy B, (c) alloy P1 and (d) alloy P2 at low magnification. An enlarged view of the precipitate morphology is given in (e) and (f) for alloy P1 and P2, respectively. \n\nTable 1 Chemical compositions of different phases in high-entropy alloys A, B, P1 and P2 by TEM-EDX measurements (at.%). \n\n\n
AlloysPhasesChemical compositions (at.%)
AlTiCrFeCoNi
Amatrix23.1 ± 0.425.9 ± 0.724.3 ± 0.924.7 ± 1.0
Bmatrix一 4.4 ± 0.12.1 ± 0.122.0 ± 0.224.1 ± 0.223.3 ± 0.224.1 ± 0.3
P1matrix1.3 ± 0.10.8 ± 0.125.8 ± 0.124.4 ± 0.226.1 ± 0.221.6 ± 0.2
Y'8.4 ± 0.12.1 ± 0.211.6 ± 0.213.3 ± 0.217.4 ± 0.347.1 ± 0.4
P2NizAITi22.3 ± 0.217.4 ± 0.23.4 ± 0.15.0 ± 0.222.2 ± 0.331.7 ± 0.4
matrix2.2 ± 0.10.2 ± 0.126.8 ± 0.426.7 ± 0.425.1 ± 0.419.0 ± 0.4
Y'6.3 ± 0.12.7 ± 0.119.2 ± 0.320.2 ± 0.321.2 ± 0.330.4 ± 0.4
NiAITi18.6 ± 0.214.5 ± 0.23.1 ± 0.16.2 ± 0.219.3 ± 0.338.3 ± 0.4
\n\n![](images/7bc4254ee8f39629b395fb824980002c8ec297605dce8e7e2fa6305c92173ecb.jpg) \nFig. 3. Bright TEM field image of Region I and II (a); (b) and (c) are the corresponding bright and dark field images showing the particles distribution in Region I, (d) high-resolution TEM image showing the interface between one single nano-particle and fcc matrix, with relative FFT patterns are shown in the left; the atomic arrangement are directly distinguished. \n\n![](images/73fb6663ca8403c219952c42f1d1eec8240855f3304516ff855bef94fa4d1655.jpg) \nFig. 4. APT results in P1. For Region I; two boxes of atom maps with Fe, Co, Cr and Al, Ni, Ti separately and one box with $35\\%$ Ni iso-concentration surface showing the outline of particles (a), and (b) the proximity histogram constructed across the interface between the matrix and precipitates. For Region II: atom map of each component showing a plate-like structure (c), and (d) the proximity histogram indicating a larger difference of element distribution. \n\n# 3.4. Tensile properties at room temperature \n\nRepresentative tensile stressestrain curves of the four specimens are shown in Fig. 5a. The ultimate strengths of A and B samples are noted to be 453 and $503\\mathrm{\\mpa}$ respectively. Since there is essentially no second phase in these two alloys, the slight strength increase in the homogenized sample B $({\\sim}50\\ \\mathsf{M P a})$ is probably attributable to the solid-solution effect caused by the Ti and Al additions. After thermomechanical treatments, strengths of both P1 and P2 alloys are noted to dramatically increase, and specifically the yield and ultimate tensile strengths of P1 become 645 and 1094 MPa, respectively, without significant loss in plasticity $(\\sim39\\%)$ . For the P2 sample, yield and ultimate tensile strengths are even higher at 1005 and $1273\\mathrm{\\mPa}$ , respectively, whilst the elongation still remains at a respectable value of $17\\%$ The yield strength of over 1 GPa is particularly noteworthy since, to the authors' knowledge, such high yield strength has not been reported in fcc-HEAs before. We can further estimate the toughness of these alloys and compare it with that of other conventional alloys. The product of strength and elongation for P1 reaches a value of $42,600~\\mathrm{MPa\\%}$ , which well exceeds the level of many TRIP steels (only about $15,000{-}30,000\\ \\mathrm{MPa\\%}$ [18e21]. A direct comparison of the tensile strength and elongation of the current HEAs with those of several advanced steels (data from Ref. [19]) is presented in Fig. 5b. The current P1 and P2 HEAs are located at the upper-right above the general curve for the conventional alloys, clearly indicating that they outperform most advanced steels. \n\n# 4. Discussion \n\nStrengthening mechanisms in polycrystalline materials are traditionally summarized into four categories: solid-solution hardening, grain-boundary hardening, dislocation hardening, and precipitation hardening. As the four mechanisms are operating independently, yield strength is a simple summation of the four individual contributions and can be expressed as [22]: \n\n![](images/1cab384ff91355e391145e4be2531451cc8ec1a02da9102f552cff72cc8c2750.jpg) \nFig. 5. Tensile properties of alloys A, B, P1 and P2 at room temperature (a), and the map of ultimate tensile strengtheductility combinations of various advanced steels including P1 and P2 HEAs (b), showing great advantage of the current HEAs. \n\n$$\n\\upsigma_{0.2}=\\upsigma_{\\mathrm{A}}+\\Delta\\upsigma_{\\mathrm{S}}+\\Delta\\upsigma_{\\mathrm{G}}+\\Delta\\upsigma_{\\mathrm{D}}+\\Delta\\upsigma_{\\mathrm{P}}\n$$ \n\nwhere $\\upsigma_{\\mathsf{A}}=165\\:M P a$ is the yield strength of alloy A, which is the intrinsic strength, or the so-called lattice friction strength, and $\\Delta\\upsigma_{S}$ $\\Delta\\upsigma_{\\mathrm{G},}\\Delta\\upsigma_{\\mathrm{D}}$ and $\\Delta\\upsigma_{\\mathrm{P}}$ are strengthening contributions from solid solution, grain boundary, dislocations, and precipitates, respectively. In the following, we will focus on these mechanisms and evaluate their contributions to the overall strength in the current HEA individually. \n\n# 4.1. Solid solution hardening \n\nTraditional approaches of measuring the effect of solid-solution hardening are all based on dilute solution alloys, especially for binary systems [23,24]. However, for HEAs, generally known as “concentrated solid-solution” systems, the terms “solute” and “solvent” lose their conventional meanings. How to evaluate, or just define, the precise contribution of solid-solution strengthening in HEAs, remains a challenge. Recently, Toda-Caraballo et al. [25] made special efforts to extend the traditional solid solution hardening theories to include concentrated multicomponent alloys such as HEAs, however, the model still has difficulties to describe materials with complex chemical structures (for example, precipitates, a mixed fcc plus bcc structure). Fortunately, the current HEA can be simply treated as a FeCoNiCr solvent matrix containing $\\mathrm{Ti}+\\mathrm{Al}$ solutes, and a standard model for substitutional solid solution strengthening based on dislocation-solute elastic interactions can be directly applied to evaluate the potency of solution strengthening caused by Ti and Al [26,27], namely, \n\n$$\n\\Delta\\upsigma_{\\mathsf{S}}=\\mathbf{M}\\cdot\\frac{G\\cdot\\varepsilon_{s}^{3/2}\\cdot c^{1/2}}{700}\n$$ \n\nwhere G is the shear modulus for the Ti2Al4 system $(78.5\\mathsf{G P a})$ . c is the total molar ratio of $\\mathrm{Ti}+\\mathrm{Al}$ in the simple fcc matrix, which is listed in Table $1.\\mathrm{M}=3.06$ is the Taylor factor, a factor that converts shear stress to normal stress for a fcc polycrystalline matrix. The interaction parameter $\\varepsilon_{s}$ is expressed as: \n\n$$\n\\varepsilon_{S}=\\left|\\frac{\\varepsilon_{G}}{1+0.5\\varepsilon_{G}}-3\\cdot\\varepsilon_{a}\\right|\n$$ \n\nwhich combines the effects of elastic and atomic size mismatches, i.e., $\\varepsilon_{G}$ and $\\varepsilon_{\\mathrm{{a}}}$ , and they are defined as: \n\n$$\n\\begin{array}{c c c}{\\displaystyle}\\\\ {\\displaystyle}\\\\ {\\varepsilon_{\\mathrm{G}}=\\frac{1}{G}\\frac{\\partial G}{\\partial c}}\\end{array}\n$$ \n\nwhere $a$ is the lattice constant of the FeCoNiCr base alloy matrix. \n\nThe parameter $\\varepsilon_{\\mathbf{a}}$ can be readily obtained from refined XRD patterns (lattice parameters are: 0.3578, 0.3594 and $0.3590\\mathrm{nm}$ for A, P1 and P2, respectively), while the parameter G is usually negligible compared to $\\varepsilon_{\\mathsf{a}}$ . In this case, the value of $\\varepsilon_{s}$ and thus $\\Delta\\upsigma$ can be properly estimated. The strength enhancement caused by solid-solution hardening in P1 and P2 (as compared to the base alloy A) can be subsequently calculated to be $\\Delta\\upsigma_{\\mathsf{S}1}=25.4\\mathsf{M P a}$ and $\\Delta\\upsigma_{\\mathsf{S}2}=14.4~\\mathsf{M P a}$ , respectively. These values are obviously too small to account for the strength difference, suggesting that solid solution hardening is not the dominant mechanism. \n\n# 4.2. Grain-boundary hardening \n\nIt is also known that grain-size refinement can improve the strength of an alloy. Smaller grain size offers a higher volume fraction of grain-boundaries, which could impede dislocation motion. The relationship between yield strength and grain size can be well described by the classical Hall-Petch equation [28,29]: \n\n$$\n{\\upsigma}_{\\mathrm{y}}={\\upsigma}_{0}+{\\upk}_{\\mathrm{y}}\\Big/d^{1/2}\n$$ \n\nwhere $\\upsigma_{\\mathrm{y}}$ is the yield stress, $\\upsigma_{0}$ is again the lattice friction stress, ky is the strengthening coefficient and d is the average grain diameter. According to Eq. (6), yield strength increase caused by grain size difference $(\\Delta\\upsigma_{\\mathsf{G}})$ can be expressed as: \n\n$$\n\\Delta\\upsigma_{\\mathrm{G}}=\\mathbf{k}_{\\mathrm{y}}\\left(\\mathbf{d}_{P}^{-1/2}-\\mathbf{d}_{A}^{-1/2}\\right)\n$$ \n\nwhere $\\mathbf{d}_{\\mathrm{P}}$ represent the grain size of the thermomechancially processed materials. In this work, we adopt the value of $\\mathbf{k}_{\\mathrm{y}}$ from the FeCoNiCrMn system, that is, $226~\\mathrm{MPa\\cdot\\upmum}^{1/2}$ according to the study of Liu et al. [30]. The average grain sizes of alloys A, P1 and P2 measured from using SEM and TEM are $\\mathbf{d}_{\\mathsf{A}}=289.7~\\upmu\\mathrm{m}$ $\\mathrm{d}_{\\mathsf{P1}}=15.7~\\upmu\\mathrm{m},$ , and $\\mathbf{d}_{\\mathrm{P}2}=2.8~\\upmu\\mathrm{m}$ , respectively. The current alloys are noted to contain only a few twins. Even including these twin boundaries in the calculations, we obtain $\\Delta\\upsigma_{\\mathrm{G1}}=43.7M P a$ and $\\Delta\\upsigma_{\\mathrm{G2}}=122.6M P a$ . The grain boundary contribution in P2 alloy is almost three times as much as that in the P1 alloy. However, both values are relatively small to account for the total strength increase. \n\n# 4.3. Dislocation hardening \n\nPlastic deformation results from the movement of mobile dislocations, and these dislocations interact with each other, then impede their own motion. In general, a higher dislocation density leads to a higher yield strength. A BaileyeHirsch formula [31] is applied here to describe the relationship as: \n\n$$\n\\Delta\\upsigma_{\\mathrm{D}}=M\\alpha G b\\rho^{1/2}\n$$ \n\nwhere $\\alpha=0.2$ is a constant for fcc metals, $\\rho$ stands for the dislocation density, and b is the burger vector, for a fcc structure, $\\scriptstyle\\mathtt{b}={\\sqrt{2}}$ $2\\times\\mathsf{a_{T i2A l4}}=0.255~\\mathrm{nm}$ (see Ref. [32]). \n\nWe roughly estimated the dislocation density through the Williamson-Hall method, a widely used first approximation to assess the effects of micro strain and crystallite size [33,34]. In this approach, the true XRD peak broadening $\\upbeta$ (the observed peak broadening deducting the instrument broadening) consists of two parts: the crystallite size broadening $\\upbeta_{G}$ and the strain broadening bS [35,36], and based on the assumption of Cauchy-type function, they are: \n\n$$\n\\begin{array}{l}{\\upbeta=\\upbeta_{G}+\\upbeta_{S}}\\\\ {\\upbeta_{G}=\\mathrm{K}\\uplambda/(D\\cdot c o s\\theta)}\\\\ {\\upbeta_{S}=4\\upepsilon\\cdot\\mathrm{tan}\\uptheta}\\end{array}\n$$ \n\nwhere $K\\sim0.9$ is a constant, $\\lambda=0.15405~\\mathrm{nm}$ is the wavelength of Cu Ka radiation, D is the crystallite size, is the micro strain, and q is the Bragg angle of the certain peak. Focusing on the micro strain only, Eq. (9) can be rewritten as: \n\n$$\n\\upbeta c o s\\theta=\\upK\\uplambda/D+(45\\mathrm{in}\\uptheta)\\cdot\\upvarepsilon\n$$ \n\nThe slope of the linear fit of the bcosq 4sinq plot determines the parameter . Such plots for P1 and P2 are shown in Fig. 6. It is seen that, the micro strain of P2, i.e., $\\varepsilon_{2}=0.102$ , with a relative small positive intercept of 0.03 resulting from the experimental errors. However, the micro strain for P1, i.e., the $\\varepsilon_{1}$ value, is nearly zero $(\\sim-0.002)$ . This kind of phenomenon has also be observed in another alloy system [37] in which it was suggested to be caused by the fact that the fully annealed structure has few dislocations. Here, we believe the occurrence of a similar situation in P1, which was heat-treated $^{2\\mathrm{~h~}}$ at a relatively high temperature of $1273\\mathrm{K}$ (above $0.75\\mathrm{Tm}\\dot{}$ ). Considering the data and pattern refinement error, it is reasonable to treat the micro strain in P1 as $\\protect\\varepsilon_{1}=0$ . \n\n![](images/ded7a848e26e05ad8cd6729985ea1663b87ed20f9b375c3ae7fe9729c2a9b378.jpg) \nFig. 6. The peak broadening $\\upbeta$ as a function of 4tanq; the slope of the linear fit shows the value of micro strain . \n\nThe dislocation density, can then be derived from the micro strain above [34,38]: \n\n$$\n\\uprho=~2\\sqrt{3}{\\cdot}\\varepsilon/(D b)\n$$ \n\nfrom which, the dislocation density in P1 and P2 can be determined as $\\uprho1\\approx0$ and $\\mathsf{p}2=5.02\\times10^{14}\\mathrm{\\m}^{-2}$ . Inserting these values into Eq. (8), the yield strength increment from dislocation strengthening is evaluated as $\\Delta\\upsigma_{\\mathrm{D1}}=0$ and $\\Delta\\upsigma_{\\mathrm{D2}}=274.5M P a$ in P1 and P2, respectively. The result indicates that dislocation hardening plays a somewhat important role on the strength of P2. It also suggests that annealing at the intermediate temperature of $923\\mathrm{~K~}$ is insufficient to annihilate the large amount of dislocations created during the heavy cold work $(70\\%)$ . \n\n# 4.4. Precipitation hardening \n\nAs shown in Fig 2, both P1 and P2 are full of fine precipitates and these precipitates are expected to produce hardening, either through a dislocation by-pass mechanism (Orowan-type) or particle shearing mechanism. Generally, Orowan mechanism occurs when the radius of particles exceeds a critical value or is incoherent with the matrix, however, shearing mechanism would dominate when precipitates are sufficiently small and coherent. Based on the current precipitate morphology, particle shearing is expected to take the control. We will, therefore, focus our discussion on this mechanism in the following. \n\nAs discussed earlier, the microstructure of P1 consists of two different regions each with its own precipitate size and distribution. In this case, a simple composite model is applicable to estimate the strength, namely, \n\n$$\n\\upsigma_{\\mathrm{P1}}=\\upsigma_{\\mathrm{I}}{\\cdot}C_{I}+\\upsigma_{\\mathrm{II}}{\\cdot}C_{I I}\n$$ \n\nwhere $\\upsigma_{\\mathrm{P1}}$ is the overall strength, $\\upsigma_{\\mathrm{I}}$ and $\\upsigma_{\\mathrm{II}}$ represent the intrinsic strength of Region I and II, respectively, and $\\mathsf{C}_{\\mathrm{I}}$ and $C_{\\mathrm{II}}$ are the volume fractions of Region I and $\\mathrm{II}$ , respectively. Many of the precipitates in Region $\\mathrm{II}$ are noted to be actually plate-like, but to simplify our analysis, we will treat these particles as spherical. The fraction, size and spacing of precipitates are evaluated from the microstructural observation and summarized in Table 2. \n\nIn the calculation of the effect of particles sheared by dislocations, three contributing factors are considered and they are particle-matrix coherency $(\\Delta\\upsigma_{C S})$ , modulus mismatch $(\\Delta\\upsigma_{\\mathrm{MS}})$ and atomic ordering $(\\Delta\\upsigma_{0\\mathsf{S}})$ [39e41]. The former two make contributions prior to the shearing, while the latter one contributes during the shearing. In principle, the larger one of $\\Delta\\upsigma_{\\mathsf{C S}}+\\Delta\\upsigma_{\\mathsf{M S}}$ and $\\Delta\\upsigma_{0S}$ determines the resultant contribution in these sequential processes. The equations for these contributions are [42]. \n\n$$\n\\Delta\\upsigma_{C S}=M\\cdot\\alpha_{\\varepsilon}{\\left(G\\cdot\\varepsilon\\right)}^{3/2}{\\left(\\frac{r f}{0.5G b}\\right)}^{1/2}\n$$ \n\n$$\n\\Delta\\upsigma_{\\mathrm{MS}}=M\\cdot0.0055(\\Delta G)^{3/2}\\left(\\frac{2f}{G}\\right)^{1/2}\\left(\\frac{r}{b}\\right)^{3m/2-1}\n$$ \n\nTable 2 Fraction, size and spacing data of precipitates in P1 and P2 alloys. Specially, in Region II of alloy P1, the spacing and radius data are calculated in width direction of the plates. The strengthening effect of the $\\mathrm{\\DeltaNi_{2}A l T i}$ phase is negligible due to its low volume fraction. \n\n\n
AlloysRegions or particlesRegion fraction C (%)Precipitates fraction f (%)Precipitates radius r (nm)Particle spacing Lp (nm)
P168.123.312.617.2
31.916.246.390.9
P2Y'.26.89.711.3
NizAITi-2.7725.9182.9
\n\n$$\n\\Delta\\upsigma_{0\\mathrm{S}}=M\\cdot0.81\\frac{\\gamma_{A P B}}{2b}\\left(\\frac{3\\pi f}{8}\\right)^{1/2}\n$$ \n\nwhere $\\alpha_{\\varepsilon}=2.6$ for fcc structure, $\\mathbf{m}=0.85$ , $\\scriptstyle\\varepsilon\\approx2/3\\cdot({\\Delta a}/{a})$ is the constrained lattice parameter mismatch, with $(\\Delta a/a)=0.0026$ in this work, where $\\Delta a$ is the difference of lattice constant between $\\mathrm{{Ni}_{3}(T i,A l)}$ phase and the fcc matrix of P1 and P2 calculated from the XRD results; $f$ is the volume fraction of the precipitates, $\\Delta G$ is the shear modulus mismatch between precipitates and matrix, and gAPB is the anti-phase boundary energy of the precipitates, $\\Delta G=81-77=4G P a$ , $\\gamma_{A P B}=0.12J/m^{2}$ are adopted from the corresponding data of $\\mathrm{Ni}_{3}\\mathrm{Al}$ precipitates in Ni-based superalloys [43]. The calculated individual values of $\\Delta\\upsigma_{\\mathrm{CS}}$ , $\\Delta\\upsigma_{\\mathrm{MS}}$ and $\\Delta\\upsigma_{0\\mathsf{S}}$ are listed in Table 3, and the final strength increment from shearing $\\Delta\\upsigma_{S\\mathrm{H}}$ is determined to be $\\Delta\\upsigma_{S\\mathrm{H1-I}}=305.6M P c$ and $\\Delta\\upsigma_{\\mathrm{SH1-II}}=371.9M P a$ for Regions I and II in sample P1, respectively, and $\\Delta\\upsigma_{\\mathrm{SH2-Ni3(Ti,Al)}}=327.7M P a$ in sample P2. Consequently, the overall hardening contributed by precipitates in samples P1 and P2 are $\\Delta\\upsigma_{\\mathrm{P1}}=326.7M P a$ and $\\Delta\\upsigma_{\\mathrm{P}2}=327.7M P a$ , respectively. This result shows that the two alloys actually have a similar strengthening effect from precipitation. \n\nBased on the discussion above, the yield strengths of P1 and P2 HEAs are calculated as $\\upsigma_{1}=560.8\\:M P a$ and $\\upsigma_{2}=904.2M P a$ . For clarity, we summarize a column chart (Fig. 7) to directly show the strength contributions from the four individual mechanisms as well as the overall contributions (right column). It is apparent that the predicted data are in reasonable agreement with the experimental values (marked by the black and red dots). The small discrepancy may be attributable to a couple of reasons. First, the precipitates in Region II of P1, are considered to be spherical in the models to simplify calculations, however, many of them are actually in plate-like shape. Irregular plate-shaped particles are expected to produce more resistance to plastic flow as compared to smooth spherical particles. Secondly, texture difference actually exists, according to the Neutron diffraction results before. It could be developed during the cold-rolling and recrystallization process in present HEAs, according to the reported results by Dan recently [44], which can to some degree affect the overall strength of the materials. Furthermore, in our calculations, several intrinsic parameters (e.g., DG and gAPB) are borrowed from Ni-based superalloys. Nevertheless, the agreement between experiments and calculations is quite satisfactory. It is especially noted that, in the thermomechanically processed P1 and P2, precipitation hardening offers the largest strength increment. The P2 alloy, in particular, shows a much higher strength yet still keeps a respectable ductility, due to a good utilization of various hardening mechanisms: grain boundary hardening, dislocation hardening, and most importantly, the precipitation hardening. \n\n![](images/4cd10ca0bbe467d8467c51bc241e87b51cf1fc9c7ead2421e2494e64ad694fd6.jpg) \nFig. 7. The strength contributions from different hardening mechanisms. The calculation values agree well with the experimental data. \n\n# 5. Conclusion \n\nAs elaborated above, for the first time, we demonstrate that a minor Ti and Al alloying addition can produce a fine dispersion of $\\mathbf{L}1_{2}$ coherent nano-precipitates in a fcc HEA alloy by proper thermomechanical treatments. These nano-precipitates can drastically enhance the strength of the alloy without compromising its tensile ductility. \n\nWe have presented two examples to illustrate the strengthening effects. The first example is a HEA (alloy P1), whose structure is composed of a mixture of two precipitate morphologies: Region I consists of nano-precipitates less than $40\\mathrm{nm}$ in size, while Region II consists of particles coarser than $100~\\mathrm{{nm}}$ . All of these nano-scaled precipitates are identified to be the $\\mathsf{L}1_{2}\\ \\mathsf{N i}_{3}(\\mathsf{T i},\\mathsf{A l})$ -type $\\gamma^{\\prime}$ phase. This simple composites structure results in a 645 MPa yield strength with an outstanding $39\\%$ elongation. Precipitation hardening is the dominant strengthening mechanism in this alloy, which contributes a strength increment of about $326.7\\mathrm{MPa}$ . In the second example (alloy P2), the alloy consists of very fine dispersion of nano-precipitates, main the coherent $\\boldsymbol{\\Upsilon}^{\\prime}$ phase, although there are also minor nano-scale $\\mathsf{N i}_{2}\\mathsf{A l T i}$ particles. This alloy exhibits even higher yield strength of over 1 GPa, but still keeps a reliable $17\\%$ tensile ductility. The exceptionally high yield strength results from contributions of precipitation hardening (327.7 MPa), dislocation hardening $(274.5\\mathrm{MPa}) $ ), and grain boundary hardening (122.6 MPa). \n\nTable 3 Strength contributions during shearing process, showing the total strength increment derived from the shearing mechanism. \n\n\n
AlloysRegions or particles△cs (MPa)△Ms (MPa)△gos (MPa)△acs + △aMS (MPa)△USH (MPa)
P1[216.829.8305.6246.6305.6
II346.535.6254.8382.1382.1
P2204.029.8327.7233.8327.7
\n\nIn summary, we have shown a successful exploration to find a way for effectively strengthening fcc-HEA systems using a controllable thermomechanical procedure. The resultant microstructure consists of precipitates with an $\\mathbf{L}1_{2}$ -structure and structurally coherent with their fcc alloy matrices. It bear great resemblance to that of $\\gamma^{\\prime}-\\gamma$ Ni superalloys, which are the cornerstone of high-temperature gas turbine engine materials. Our findings open a new door for the future development of HEAs for hightemperature structural applications. \n\n# Acknowledgments \n\nThis research was supported by National Natural Science Foundation of China (51531001, 51422101 and 51271212, 51371003), 111 Project (B07003), International S&T Cooperation Program of China (2015DFG52600) and Program for Changjiang Scholars and Innovative Research Team in University (IRT_14R05). TGN acknowledges the support of US National Science Foundation under Contract DMR-1408722. The portion of this research at ORNL's Spallation Neutron Source was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, US Department of Energy. \n\n# References \n\n[1] Y.J. Zhou, Y. Zhang, Y.L. Wang, G.L. Chen, Microstructure and compressive properties of multicomponent Alx(TiVCrMnFeCoNiCu)100 $\\mathbf{\\nabla}\\cdot\\mathbf{x}$ high-entropy alloys, Mater. Sci. Eng. A 454e455 (2007) 260e265. \n[2] Y.J. Zhou, Y. Zhang, Y.L. Wang, G.L. Chen, Solid solution alloys of AlCoCrFeNiTix with excellent room-temperature mechanical properties, Appl. Phys. Lett. 90 (2007) 181904. \n[3] J.W. Yeh, S.Y. Chang, Y.D. Hong, S.K. Chen, S.J. Lin, Anomalous decrease in Xray diffraction intensities of CueNieAleCoeCreFeeSi alloy systems with multi-principal elements, Mater. Chem. Phys. 103 (2007) 41e46. \n[4] B. Cantor, I.T.H. Chang, P. Knight, A.J.B. Vincent, Microstructural development in equiatomic multicomponent alloys, Mater. Sci. Eng. A 375e377 (2004) 213e218. \n[5] J.W. Yeh, S.K. Chen, S.J. Lin, J.Y. Gan, T.S. Chin, Nanostructured high-entropy alloys with multiple principal elements novel alloy design concepts and outcomes, Adv. Eng. Mater 6 (2004) 299. \n[6] O.N. Senkov, J.M. Scott, S.V. Senkova, D.B. Miracle, C.F. Woodward, Microstructure and room temperature properties of a high-entropy TaNbHfZrTi alloy, J. Alloy. Compd. 509 (2011) 6043e6048. \n[7] O.N. Senkov, S.V. Senkova, C.F. Woodward, Effect of aluminum on the microstructure and properties of two refractory high-entropy alloys, Acta Mater 68 (2014) 214e228. \n[8] K.M. Youssef, A.J. Zaddach, C. Niu, D.L. Irving, C.C. Koch, A novel low-density, high-hardness, high-entropy alloy with close-packed single-phase nanocrystalline structures, Mater. Res. Lett. 3 (2014) 1e5. \n[9] J.W. Yeh, Alloy design strategies and future trends in high-entropy alloys, JOM 65 (2013) 1759e1771. \n[10] K.Y. Tsai, M.H. Tsai, J.W. Yeh, Sluggish diffusion in CoeCreFeeMneNi highentropy alloys, Acta Mater 61 (2013) 4887e4897. \n[11] W. Guo, W. Dmowski, J.Y. Noh, P. Rack, P.K. Liaw, T. Egami, Local atomic structure of a high-entropy alloy: an X-ray and neutron scattering study, Metall. Mater. Trans. A 44 (2012) 1994e1997. \n[12] B. Gludovatz, A. Hohenwarter, D. Catoor, E.H. Chang, E.P. George, R.O. Ritchie, A fracture-resistant high-entropy alloy for cryogenic applications, Science 345 (2014) 1153e1158. \n[13] F. Otto, A. Dlouhý, C. Somsen, H. Bei, G. Eggeler, E.P. George, The influences of temperature and microstructure on the tensile properties of a CoCrFeMnNi high-entropy alloy, Acta Mater 61 (2013) 5743e5755. \n[14] Y. Wu, W.H. Liu, X.L. Wang, D. Ma, A.D. Stoica, T.G. Nieh, Z.B. He, Z.P. Lu, In-situ neutron diffraction study of deformation behavior of a multi-component high-entropy alloy, Appl. Phys. Lett. 104 (2014) 051910. \n[15] B. Ren, Z.X. Liu, B. Cai, M.X. Wang, L. Shi, Aging behavior of a CuCr2Fe2NiMn high-entropy alloy, Mater. Des. 33 (2012) 121e126. \n[16] S.T. Chen, W.Y. Tang, Y.F. Kuo, S.Y. Chen, C.H. Tsau, T.T. Shun, J.W. Yeh, Microstructure and properties of age-hardenable AlxCrFe1.5MnNi0.5 alloys, Mater. Sci. Eng. A 527 (2010) 5818e5825. \n[17] D. Choudhuri, T. Alam, T. Borkar, B. Gwalani, A.S. Mantri, S.G. Srinivasan, M.A. Gibson, R. Banerjee, Formation of a Huesler-like L21 phase in a CoCrCuFeNiAlTi high-entropy alloy, Scr. Mater 100 (2015) 36e39. \n[18] V.F. Zackay, E.R. Parker, D. Fahr, B. Bush, The enhancement of ductility on high strength steels, Trans. ASM 60 (1967) 8. \n[19] Y. Gan, Y.Q. Weng, H. Dong, Advanced Steels: the Recent Scenario in Steel Science and Technology, Metallurgical Industry Press, Beijing and Springer, 2011, p. 372. \n[20] G. Krauss, Martensite in steel: strength and structure, Mater. Sci. Eng. A 273e275 (1999) 40e57. \n[21] S.J. Kim, C.G. Lee, T.H. Lee, C.S. Oh, Effect of Cu, Cr and Ni on mechanical properties of 0.15 wt.% C TRIP-aided cold rolled steels, Scr. Mater 48 (2003) 539e544. \n[22] N. Kamikawa, K. Sato, G. Miyamoto, M. Murayama, N. Sekido, K. Tsuzaki, T. Furuhara, Stressestrain behavior of ferrite and bainite with nanoprecipitation in low carbon steels, Acta Mater 83 (2015) 383e396. \n[23] R.L. Fleischer, Substitutional solution hardening, Acta Metall. (1963) 11. \n[24] T.H. Courtney, Mechanical Behavior of Materials, McGraw-Hill Press, 1990. \n[25] I. Toda-Caraballo, P.E.J. Rivera-Díaz-del-Castillo, Modelling solid solution hardening in high entropy alloys, Acta Mater 85 (2015) 14e23. \n[26] C.A. Schuh, T.G. Nieh, H. Iwasaki, The effect of solid solution W additions on the mechanical properties of nanocrystalline Ni, Acta Mater. 51 (2003) 431e443. \n[27] J.Y. He, W.H. Liu, H. Wang, Y. Wu, X.J. Liu, T.G. Nieh, Z.P. Lu, Effects of Al addition on structural evolution and tensile properties of the FeCoNiCrMn high-entropy alloy system, Acta Mater 62 (2014) 105e113. \n[28] E.O. Hall, The deformation and ageing of mild steel III discussion of results, Proc. Phys. Soc. Sect. B 64 (1951) 747e753. \n[29] N.J. Petch, The cleavage strength of polycristals, J. Iron Steel Inst. 174 (1953). \n[30] W.H. Liu, Y. Wu, J.Y. He, T.G. Nieh, Z.P. Lu, Grain growth and the HallePetch relationship in a high-entropy FeCrNiCoMn alloy, Scr. Mater 68 (2013) 526e529. \n[31] T.H. Courtney, Mechanical Behavior of Materials, Long Grove Press, Waveland, 2005. \n[32] J.Y. He, C. Zhu, D.Q. Zhou, W.H. Liu, T.G. Nieh, Z.P. Lu, Steady state flow of the FeCoNiCrMn high entropy alloy at elevated temperatures, Intermetallics 55 (2014) 9e14. \n[33] G.K. Williamson, W.H. Hall, X-ray line broadening from filed aluminium and wolfram, Acta Metall. 1 (1953) 22e31. \n[34] G.K. Williamson, R.E. Smallman III, Dislocation densities in some annealed and cold-worked metals from measurements on the X-ray debye-scherrer spectrum, Philos. Mag. 1 (1956) 34e46. \n[35] M. Karolus, E. ٞagiewka, Crystallite size and lattice strain in nanocrystalline NieMo alloys studied by Rietveld refinement, J. Alloy. Compd. 367 (2004) 235e238. \n[36] S. Kumari, D.K. Singh, P.K. Giri, Strain anisotropy in freestanding germanium nanoparticles synthesized by ball milling, J. Nanosci. Nanotechno 9 (2009) 5231e5236. \n[37] G. Sharma, P. Mukherjee, A. Chatterjee, N. Gayathri, A. Sarkar, J.K. Chakravartty, Study of the effect of $a$ irradiation on the microstructure and mechanical properties of nanocrystalline Ni, Acta Mater 61 (2013) 3257e3266. \n[38] Y.H. Zhao, X.Z. Liao, Z. Jin, R.Z. Valiev, Y.T. Zhu, Microstructures and mechanical properties of ultrafine grained 7075 Al alloy processed by ECAP and their evolutions during annealing, Acta Mater 52 (2004) 4589e4599. \n[39] H. Wen, T.D. Topping, D. Isheim, D.N. Seidman, E.J. Lavernia, Strengthening mechanisms in a high-strength bulk nanostructured CueZneAl alloy processed via cryomilling and spark plasma sintering, Acta Mater 61 (2013) 2769e2782. \n[40] K. Ma, H. Wen, T. Hu, T.D. Topping, D. Isheim, D.N. Seidman, E.J. Lavernia, J.M. Schoenung, Mechanical behavior and strengthening mechanisms in ultrafine grain precipitation-strengthened aluminum alloy, Acta Mater 62 (2014) 141e155. \n[41] D.N. Seidman, E.A. Marquis, D.C. Dunand, Precipitation strengthening at ambient and elevated temperatures of heat-treatable Al(Sc) alloys, Acta Mater 50 (2002) 4021e4035. \n[42] C. Booth-Morrison, D.C. Dunand, D.N. Seidman, Coarsening resistance at $400^{\\circ}\\mathsf C$ of precipitation-strengthened AleZreSceEr alloys, Acta Mater 59 (2011) 7029e7042. \n[43] A.S. Argon, T.M. Pollock, Creep resistance of CMSX-3 nickel base superalloy single crystals, Acta Mater 40 (1992) 30. \n[44] G. Dan Sathiaraj, P.P. Bhattacharjee, Analysis of microstructure and microtexture during grain growth in low stacking fault energy equiatomic CoCrFeMnNi high entropy and Ni-60 wt.% Co alloys, J. Alloy. Compd. 637 (2015) 267e276. " + }, + { + "id": "10.1016_j.apsusc.2015.11.089", + "DOI": "10.1016/j.apsusc.2015.11.089", + "DOI Link": "http://dx.doi.org/10.1016/j.apsusc.2015.11.089", + "Relative Dir Path": "mds/10.1016_j.apsusc.2015.11.089", + "Article Title": "X-ray photoelectron spectroscopy of select multi-layered transition metal carbides (MXenes)", + "Authors": "Halim, J; Cook, KM; Naguib, M; Eklund, P; Gogotsi, Y; Rosen, J; Barsoum, MW", + "Source Title": "APPLIED SURFACE SCIENCE", + "Abstract": "In this work, a detailed high resolution X-ray photoelectron spectroscopy (XPS) analysis is presented for select MXenes a recently discovered family of two-dimensional (2D) carbides and carbonitrides. Given their 2D nature, understanding their surface chemistry is paramount. Herein we identify and quantify the surface groups present before, and after, sputter-cleaning as well as freshly prepared vs. aged multi layered cold pressed discs. The nominal compositions of the MXenes studied here are Ti-3 C2Tx,Ti3CNTx, Nb2CTx and Nb4C3Tx where T represents surface groups that this work attempts to quantify. In all the cases, the presence of three surface terminations, O, OH and F, in addition to OH-terminations relatively strongly bonded to H2O molecules, was confirmed. From XPS peak fits, it was possible to establish the average sum of the negative charges of the terminations for the aforementioned MXenes. Based on this work, it is now possible to quantify the nature of the surface terminations. This information can, in turn, be used to better design and tailor these novel 2D materials for various applications. Published by Elsevier B.V.", + "Times Cited, WoS Core": 1559, + "Times Cited, All Databases": 1628, + "Publication Year": 2016, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000368657900056", + "Markdown": "# Accepted Manuscript \n\nTitle: X-ray Photoelectron Spectroscopy of Select Multi-layered Transition Metal Carbides (MXenes) \n\nAuthor: Joseph Halim Kevin M. Cook Michael Naguib Per Eklund Yury Gogotsi Johanna Rosen Michel W. Barsoum \n\nPII: S0169-4332(15)02784-1 \nDOI: http://dx.doi.org/doi:10.1016/j.apsusc.2015.11.089 \nReference: APSUSC 31806 \n\nTo appear in: APSUSC \n\nReceived date: 20-8-2015 \nRevised date: 2-11-2015 \nAccepted date: 7-11-2015 \n\nPlease cite this article as: J. Halim, K.M. Cook, M. Naguib, P. Eklund, Y. Gogotsi, J. Rosen, M.W. Barsoum, X-ray Photoelectron Spectroscopy of Select Multi-layered Transition Metal Carbides (MXenes), Applied Surface Science (2015), http://dx.doi.org/10.1016/j.apsusc.2015.11.089 \n\nThis is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. \n\n# X-ray Photoelectron Spectroscopy of Select Multi-layered Transition Metal Carbides (MXenes) \n\nHalim, et al. \n\n# Highlights: \n\nSurface chemistry of MXenes characterized by XPS. \nStudied the surface chemistry of the MXenes $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ , $\\mathrm{Ti}_{3}\\mathrm{CNT}_{\\mathrm{x}}$ , $\\mathbf{Nb}_{2}\\mathbf{CT}_{\\mathrm{x}}$ and Nb4C3Tx Freshly prepared and aged surfaces were compared. \nFour surface moieties were confirmed, including $-0$ , –OH and $-\\mathrm{F}$ , $\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ \n\n![](images/8bb76b5a3ce59ccfd2fb63364f34ee1f2ae0667808858e89d8a92fef780c978b.jpg) \n\n# X-ray Photoelectron Spectroscopy of Select Multi-layered Transition Metal Carbides (MXenes) \n\nJoseph Halim1,2,3, Kevin M. Cook4,\\* Michael Naguib5, Per Eklund3, Yury Gogotsi1,2, Johanna Rosen3, and Michel W. Barsoum1,3 \n\n1Department of Materials Science & Engineering, Drexel University, Philadelphia, PA 19104, USA. \n2A.J. Drexel Nanomaterials Institute, Drexel University, Philadelphia, PA 19104, USA. 3Thin Film Physics Division, Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-583 31 Linköping, Sweden. \n4Materials Engineering Division, Naval Air Systems Command, Patuxent River, MD 20670, USA. \n5Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA. \n\\*Corresponding Author \nE-mail: kevin.m.cook1@navy.mil \n\n# Abstract \n\nIn this work, a detailed high resolution $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) analysis is presented for select MXenes – a recently discovered family of two-dimensional (2D) carbides and carbonitrides. Given their 2D nature, understanding their surface chemistry is paramount. Herein we identify and quantify the surface groups present before, and after, sputter-cleaning as well as freshly prepared vs. aged multi-layered cold pressed discs. The nominal compositions of the MXenes studied here are $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ , $\\mathrm{Ti_{3}C N T_{x}}$ , $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ and $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ , where T represents surface groups that this work attempts to quantify. In all the cases, the presence of three surface terminations, $-0$ , $-\\mathrm{OH}$ and $-\\mathrm{F}$ , in addition to OH-terminations relatively strongly bonded to $\\mathrm{H}_{2}\\mathrm{O}$ molecules, was confirmed. From XPS peak fits, it was possible to establish the the average sum of the negative charges of the terminations for the MXenes. Based on this work, it is now possible to quantify the nature of the surface terminations. This information can, in turn, be used to better design and tailor these novel 2D materials for various applications. \n\nOnline supplementary data available from \n\n# 1. Introduction \n\nTwo-dimensional (2D) materials have become a major focus of the scientific community due to an unprecedented combination of properties and behaviors that result from their reduced dimensionality. For example, single-layer graphene – the most explored 2D material – was shown to have high conductivity at room temperature, while transmitting $97.7\\%$ of visible light.[1-3] In addition to graphene, other 2D materials have been reported, such as hexagonal boron nitride (BN),[4] transition metal dichalcogenides (TMD),[5] such as $\\mathbf{MoS}_{2}$ ,[6, 7] and metal oxides and hydroxides.[8] Most 2D solids are typically strongly bonded within atomic sheets that, in turn, are held together in stacks by weak inter-layer forces. As may be expected, the latter allow for the intercalation of molecules between the layers, as well as, the delamination, or separation of the layers into individual flakes.[9] \n\nBy definition, both stacked 2D layers and individual 2D flakes are almost entirely comprised of surface. As such, their surface chemistries have a critical influence on their properties and characteristics. For example, hydrophobic graphene can be rendered hydrophilic by oxidizing it to form graphene oxide.[10] The determination of the surface chemistry is therefore an integral component in the characterization and understanding of 2D materials.[11-16] \n\nIn 2011, a large new family of 2D materials – layered transition metal carbides and carbonitrides, we labelled MXenes – was discovered.[17] These materials are produced from layered ternary carbides and nitrides known as the $\\mathbf{M}_{\\mathrm{n+1}}\\mathbf{A}\\mathbf{X}_{\\mathrm{n}}.$ or MAX, phases,[18] which, in turn, are a large $(70+)$ group of layered hexagonal compounds, where M is an early transition metal, A is an A-group element (mostly groups 13 and 14), X is C or/and N and n is 1 to 3. To form the corresponding MXene, the A-layers are selectively etched using hydrofluoric acid, HF, or fluoride salts and inorganic acids, such as hydrochloric acid, HCl.[19] When the Al-layers are etched, they are replaced by surface terminations, such as $-0$ , $-\\mathrm{OH}$ , and –F,[20-22] resulting in weakly bound stacks of 2D sheets with a $\\mathbf{M}_{\\mathrm{n+1}}\\mathbf{X}_{\\mathrm{n}}\\mathbf{T}_{\\mathrm{x}}$ composition,[23] where $\\mathrm{{T_{x}}}$ stands for surface termination.[20-22] To date, the following MXenes have been reported: $\\mathrm{Ti_{3}C_{2}T_{x},\\Delta T i_{2}C T_{x},}$ $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ , $\\mathrm{V}_{2}\\mathrm{CT}_{\\mathrm{x}}$ , $(\\mathrm{Ti_{0.5},N b_{0.5}})_{2}\\mathrm{CT_{x}}$ , $(\\mathrm{V}_{0.5},\\mathrm{Cr}_{0.5})_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , $\\mathrm{Ti_{3}C N T_{x}}$ , $\\mathrm{Ta}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ , $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}},\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{\\mathrm{x}}.$ and $\\mathbf{Mo}_{2}\\mathrm{Ti}_{2}\\mathbf{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ .[17, 20, 21, 24, 25] \n\nStudies on these materials have included their possible use in energy storage systems, such as lithium ion batteries,[21, 26-28] lithium ion capacitors,[29] aqueous pseudocapacitors,[19, 30] and transparent conductive films.[22] We have also shown that it is possible to intercalate various small organic molecules between the layers.[27] Very recently, we also demonstrated that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ not only adsorbed select organic molecules, but may also lead to their photocatalytic decomposition in aqueous environment.[31] The same compound also can be used for various applications from removing Pb from water to supporting catalysts.[32, 33] The $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ produced using a mixture of LiF and HCl has clay-like properties, and swelled in volume when hydrated. When used as an electrode in a supercapacitor, volumetric capacitance of the order of $900\\mathrm{F/cm}^{3}$ was measured for this material, while a volumetric capacitance of about $530\\ \\mathrm{~F/cm}^{3}$ was measured when the material was used in flexible nanocomposite polymer films.[19, 34] Furthermore, exfoliated MXene particles were shown to delaminate and form a suspension in water after intercalation with several compounds, such as tetrabutylammonium hydroxide and isopropylamine.[35, 36] Common to all of these applications is a need for proper detection and understanding of the functional surface groups present, as they in many cases, largely determine performance. \n\nGiven the crucial and vital importance of surface chemistry on MXene properties and applications, it is somewhat surprising that, to date, these surfaces have not been systematically characterized. This paper is a first serious attempt to do so. Herein, we carefully study the surface chemistries of five different MXenes by XPS; the ultimate goal being the building a library of data that can be used to further understand these intriguing materials. XPS is an excellent tool for such studies since it can be used to determine the surface chemical compositions and the chemical states of the various species. By their very nature, non-oxide 2D materials, such as silicene, germanene, phosphorene,[37] and transition metal dichalcogenides,[38] are prone to oxidation. The same is true for MXenes such as $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ .[39-42] It follows that an important aim of this work was to probe the oxidation products of the various MXene chemistries. To that effect, we used XPS to examine all the Ti-containing MXenes both directly after synthesis, and after samples were stored in air, for about 12 months. We henceforth refer to the fresh MXene samples as “as-prepared,” or \"ap- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ ,\" for example. We refer to the stored samples as “aged,” or \"ag- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ ,\" for example. \n\nA comparison of the XPS spectra of as-prepared MXene samples and those stored in air, provides valuable information concerning their propensity to oxidation. The results presented herein show that, despite being stored in air for 12 months, flakes of the Ti-based compositions, did not appear - aside from a shallow $\\sim10$ to $50\\ \\mathrm{nm}$ ) oxidized outer layer - to be unduly oxidized. The pressed $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ and $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ discs were also analyzed both directly after synthesis, and after storing in air. In this case, the samples were stored for about a month before making the measurements. Given the different aging times, between the Ti- and Nb-containing materials we cannot draw any conclusions as to which is more susceptible to oxidation. The information obtained, however is still valuable since information on changes in oxidation species will be obtained nonetheless. \n\nIn previous work, the surfaces of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ and $\\mathrm{V}_{2}\\mathrm{CT}_{\\mathrm{x}}$ were analyzed by XPS [17, 21] in order to better understand the role of surface terminations and intercalants on energy storage systems,[27] dye adsorption,[31] and transparent conductive thin films.[22] In this work, we report on more systematic measurements on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ , and extend them to $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ , $\\mathrm{Ti}_{3}\\mathrm{CNT}_{\\mathrm{x}}$ and $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ . \n\n# 2. Material and Methods \n\nSample synthesis details can be found in the supplementary materials section S1 along with other information on experimental details and additional data. \n\n# 2.1. X-ray Photoelectron Spectroscopy Analysis \n\nXPS was performed using a surface analysis system (Kratos AXIS UltraDLD, Manchester, U.K.) using monochromatic Al- $\\cdot\\mathrm{K}_{\\mathrm{a}}$ (1486.6 eV) radiation for all the samples, except for the ap- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ (See supplementary materials section S4 for details). The cold-pressed samples were mounted on double-sided tape and grounded to the sample stage with copper contacts. The X-ray beam irradiated the surface of the samples at an angle of $45^{\\circ}$ , with respect to the surface and provided an $\\mathrm{\\DeltaX}$ -ray spot size of $300\\mathrm{~x~}800\\mathrm{~\\textmum}$ . The electron energy analyzer accepted the photoelectrons perpendicular to the sample surface with an acceptance angle of $\\pm15^{\\circ}$ . Charge neutralization was performed using a co-axial, low energy $(\\sim0.1\\ \\mathrm{eV})$ electron flood source to avoid shifts in the recorded binding energy, BE. XPS spectra were recorded for F 1s, O 1s, C 1s, Al 2p, Ti 2p, and Nb 3d, as well as, the N 1s for the $\\mathrm{Ti}_{3}\\mathrm{CNT}_{\\mathrm{x}}$ composition. The analyzer pass energy used for all of the regions was $20~\\mathrm{eV}$ with a step size of $0.1\\ \\mathrm{eV}$ , giving an overall energy resolution better than $0.5~\\mathrm{eV}$ . The BE scale of all XPS spectra was referenced to the Fermi-edge $(\\mathrm{E_{F}})$ , which was set to a BE of zero eV. Normalization of all spectra was performed at the background on the low-BE side of the main peak/peaks. \n\nThe quantification, using the obtained core-level intensities, was carried out using CasaXPS Version 2.3.16 RP 1.6. Peak fitting of core-level spectra was performed using IGOR Pro, Version 6.22A. Prior to peak fitting, the background contributions were subtracted using a Shirley function. For all $2{\\tt p}_{3/2}$ and $2{\\tt p}_{1/2}$ components and $3\\mathrm{d}_{5/2}$ and $3\\mathrm{d}_{3/2}$ components, the intensity ratios of the peaks were constrained to be 2:1 and 3:2, respectively. A detailed description of the curve fitting process can be found in Supplementary Materials, S4, including information regarding the choice of lineshapes and constraints used to quantify the spectra. \n\nThe first step in this study was to establish the chemical nature of these compounds before, and after, $\\mathrm{Ar}^{+}$ sputtering for 600 s using a $4\\ensuremath{\\mathrm{~keV}}\\ensuremath{\\mathrm{Ar}}^{+}$ beam raster of $2\\mathrm{x}2\\ \\mathrm{mm}^{2}$ over the probed area. Since all samples were in the form of compressed powder discs, comprised of 2D-flakes with high surface areas and varied contours, they presented a challenge. However, obtaining spectra before sputter-cleaning allowed for the characterization of the outermost layers of these pressed discs. By their very nature, the un-sputtered surfaces inherently contain a much larger amount of contamination, from ambient oxygen and/or as a result of processing. Nevertheless, such an analysis is crucial for applications that are sensitive to the identity of species in the outermost layers such as photocatalysis. As noted above they also shed critically important light on the stability of these compounds vis-à-vis oxidation. We note in passing that the long time between processing and analysis was in part to understand the stability of the MXene flakes to long-term oxidation. \n\nAs will become evident shortly, these systems are non-trivial to characterize, since a relatively large number of surface terminations exist. To render the discussion more transparent, henceforth, each type of termination will be depicted by Roman numerals, as shown in Figure 1 and Table 1. In Figure 1, oxygen atoms are colored red, fluorine blue, hydrogen white and the M atoms – Ti and Nb - yellow. Table 1 summarizes the moieties assumed in the MXenes and their peak positions. When taken from the literature, the references are cited. In reference to Figure 1, the following is how they are defined: \n\n![](images/4609d53c09c57e2d2c447b61d8cf4bb7c0e4f36c710027128ea895cd428abfb3.jpg) \n\ni) Moiety I (labeled I in Figure 1) refers to M atoms bonded to C atoms and one oxygen atom, e.g. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{O}_{\\mathrm{x}}$ or $\\mathrm{Nb}_{2}\\mathrm{CO}_{\\mathrm{x}}$ . \nii) Moiety II refers to M atoms bonded to C atoms and an OH group, e.g. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}(\\mathrm{OH})_{\\mathrm{x}}$ or $\\mathrm{\\bfNb}_{2}\\mathrm{\\bfC}(\\mathrm{\\bfOH})_{\\mathrm{x}}.$ \niii) Moiety III refers to M atoms bonded to C and F atoms, e.g. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{F}_{\\mathrm{x}}$ or $\\mathrm{Nb}_{2}\\mathrm{CF}_{\\mathrm{x}}$ . \niv) Moiety IV refers to M atoms bonded to OH-terminations that in turn are relatively strongly physisorbed to water molecules forming OH- $\\mathrm{.H}_{2}\\mathrm{O}$ complexes (shown as moiety IV in Figure 1), viz. $\\mathrm{Ti}_{3}{\\mathrm{C}}_{2}{\\mathrm{OH-H}}_{2}{\\mathrm{O}}.|$ [43] These will be henceforth be referred to as $\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ . \n\nFigure 1. Side (a) and Top (b) view schematics of a $\\mathbf{M}_{3}\\mathbf{X}_{2}\\mathbf{T}_{\\mathbf{x}}$ structure showing various M atoms and their terminations. I refers to a M atom bonded to an O atom, i.e. an oxo group; II to OH; III, to a M atom directly bonded to a $\\mathrm{~F~}$ -atom; IV, to an M atom bonded to OH, that, in turn, is strongly bonded to a $\\mathrm{H}_{2}\\mathrm{O}$ molecule. In this schematic, \n\nM atoms are colored yellow, X, black, O, red, H white and F, blue (not to scale). M atoms only bonded to C atoms are designated, $\\mathbf{M}^{*}$ . \n\nTable 1. Summary of moieties assumed to exist in MXenes and their characteristic energies. Roman numerals refer to the various moieties shown in Figure 1. \n\n\n
MoietySpeciesBinding energy [eV]Ref.
C-Ti-Ox531.3 (O 1s region)[43] This work
C-Nb-Ox531.0 (O 1s region)
II IIIC-Ti-(OH)x C-Nb-(OH)x531.7 (O 1s region) 531.6 (O ls region)[43] This work
C-Ti-Fx685.2 (F 1s region)[44]
C-Nb-Fx Nbt685.3 (F 1s region) 203.1 [3d5/2]; 205.9 [3d5/2] (Nb 3d[45] This work
Nb-Cvregion) 282.3 (C 1s region)This work
Nb*203.5 [3d5/2]; 206.3 [3d3/2] (Nb 3d region)[46, 47]
IVHOads [Ti-case] H2Oads [Nb-533.3 (O ls region) 533.3 (O 1s region)[43] This work
\n\n‡Nb near a C vacancy \\*Interior Nb bound to only C (no surface terminations) $^\\mathrm{v}_{\\mathrm{C}}$ bound to $\\mathrm{Nb}^{\\ddag}$ \n\nThe M atoms that are bonded to C atoms alone – e.g. those in the central layers of the $n>1$ MXene flakes – will be referred to by an asterisk, or $\\mathbf{M}^{*}$ . In the Ti case, we could not differentiate between moiety I and ${\\mathrm{Ti}^{*}}$ atoms and thus both are labeled I. In the $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ case, there was a clear distinction between the ${\\mathrm{Nb}}^{*}$ atoms and moiety I. However, one complication with the Nb-containing MXenes is Ar beam damage. A peak – possibly emanating from a Nb atom bonded to one less C-atom than its neighbors – will henceforth be referred to as $\\mathrm{Nb}_{\\ddag}^{\\ddag}$ . A peak arising from a C atom bonded to $\\mathrm{Nb}_{\\ddag}^{\\ddag}$ and next to a vacant C site will henceforth be referred to as ${\\mathrm{Nb-C}}^{\\mathrm{v}}$ . The fraction of the latter species after sputtering was $<10\\%$ . \n\nTo recapitulate, for the Ti flakes, the following moieties were assumed to exist: I, II, III and IV. For the Nb compositions, moieties I, II, III, IV, ${\\mathrm{Nb}}^{*}$ , ${\\mathrm{Nb}}^{\\mathrm{V}}$ and $\\mathrm{Nb}_{\\ddag}^{\\ddag}$ (after sputtering only) \n\nwere invoked. Table 1 lists the energies associated with each termination. In addition a number of peaks associated with $\\mathrm{TiO}_{2}$ and ${\\tt N b}_{2}{\\tt O}_{5}$ , as separate species due to oxidation were also identified. We also identified M atoms that are bonded to O atoms alone – i.e. in oxide form – that are, in turn, bonded to a F-atom, i.e. $\\mathrm{TiO}_{2\\mathrm{-}\\mathrm{x}}\\mathrm{F}_{\\mathrm{x}}$ or $\\mathrm{NbO}_{\\mathrm{1-x}}\\mathrm{F}_{\\mathrm{x}}$ , as separate oxyfluoride species. It is with this in mind that we stress that the sheer chemical complexity (from internal moieties, adventitious organic species to oxidation products) of MXene systems can cause ambiguity within spectra. The existence of so many chemical species necessitates the inclusion of a large number of fitting components in XPS analysis in order to account for their presence. Having established these fitting schemes as a robust system has advantages, however, since as shown here it allows us to track any shifts in surface terminations, such as oxidation, with time. \n\n# 3. Results \n\nAt the outset, it is important to note that some binary carbide impurity phases were present in the initial MAX phase powders. Based on XRD patterns of the parent MAX phases (not shown) we estimate that 15 mole $\\%$ TiC impurity phase was present in $\\mathrm{Ti}_{2}\\mathrm{AlC}$ ; 15 mole $\\%$ of TiCN in Ti3AlCN; 20 mole% of $\\mathrm{Nb}_{4}\\mathrm{AlC}_{3}$ in $\\mathrm{Nb}_{2}\\mathrm{AlC}$ and 5 mole $\\%$ of NbC in $\\mathrm{Nb}_{4}\\mathrm{AlC}_{3}$ . In all results reported herein, the presence of these binary carbides were accounted for, and subtracted from the chemical compositions more details are found in supplementary materials S3. \n\nSince the most important contribution of this work is assigning – in a comprehensive and consistent manner – the various energy peaks to different moieties, in this section we focus on the component peak-fitting (deconvolution) of XPS spectra for the pre- and post-sputter cleaned ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and the sputter-cleaned ag- ${\\cdot}\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ as being representative of the chemical species present in all MXenes studied herein. The XPS spectra and peak-fits for the other MXenes can be found in supplementary material (See Section S5). In addition, we measured the XPS spectra of all parent MAX phases after sputtering (see Supplementary material section S6 and Figures S12 to S16). \n\n# 3.1. Ti3C2Tx (Figure 2; Tables 2 and 3) \n\nFigures 2a-d plot, respectively, the spectra for Ti, C, O and F for pre-sputter-cleaned ap$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , together with their peak-fits. The respective spectra, after sputtering, are plotted in Figures 2 e-g. The peak positions obtained from the fits are summarized in Tables 2 and 3 for the pre- and post-sputtered ap- $\\mathrm{\\cdotTi}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ samples, respectively. \n\n3.1.1. Ti 2p region. The Ti 2p region for the pre-sputtered ap- $\\mathbf{\\cdot}\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample (Figure 2a), was fit by the components listed in column 5 in Table 2. The majority of the species are Ti atoms (Ti, $\\mathrm{Ti}^{2+},\\mathrm{Ti}^{3+})$ , that belong to moieties I, II, and/or IV and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{F}_{\\mathrm{x}}$ , viz. moiety III. These comprise $93\\%$ of the photoemission in the Ti 2p region. The same region, for the sputtered ap- $\\cdot\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample (Figure 2e, Table 2), was fit by the same moities (I, II, and/or IV, and III). In this case, they comprise $98\\%$ of the photoemission in the Ti 2p region. It is worth noting that similar oxidation states for Ti reported here, viz. $\\mathrm{Ti}^{2+}$ and $\\mathrm{Ti}^{3+}$ , were reported for TiC.[48] \n\nFor the pre-sputtered ag- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample (see Figure S2, Table S3), the moieties I, II, or IV, and III comprise $77\\%$ of the Ti 2p region photoemission. After sputtering they comprise $83\\%$ (see Figure S3, Table S4). In other words, for the pre-sputtered ag- $\\mathrm{\\cdotTi}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample, almost a quarter of the Ti $2\\mathfrak{p}$ region belongs to $\\mathrm{TiO}_{2}$ and $\\mathrm{TiO}_{2\\mathrm{-}\\mathrm{x}}\\mathrm{F}_{\\mathrm{x}}$ . This percentage decreases slightly after sputtering. \n\nNote that the BE of the Ti $2{\\tt p}_{3/2}$ peaks in the ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample decreases slightly, from 455.0 eV to $454.8\\mathrm{eV}$ , upon sputtering. This decrease might be due to the introduction of defects and/or incorporated Ar ions due to sputtering, which is a commonly observed for transition metal carbides. [49] For the ag- $-\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample, the BE decreases from $455.2\\ \\mathrm{eV}$ to $454.9\\ \\mathrm{eV}$ upon sputtering. Note that the pre-sputtered BE of this peak increased by $0.2\\ \\mathrm{eV}$ after aging the sample, indicative of the removal of electron density as the sample oxidized. \n\nIn general, the BEs for the Ti peaks of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ samples $\\mathrm{(\\approx455~eV)}$ , are higher than the $454.6\\ \\mathrm{eV}$ value in the parent MAX phase, $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (Figure S13a).[50] This shift is due to the replacement of the Al layers by more electronegative surface terminations such as O, OH and F. 3.1.2. C 1s region. The C 1s region (Figure 2b) of the pre-sputtered ap- $\\mathbf{\\cdot}\\Gamma\\mathbf{i}_{3}\\mathbf{C}_{2}\\mathbf{T}_{\\mathrm{x}}$ sample was fit by three peaks. The largest ( $\\approx54\\%$ of the C 1s region), at a BE of $282.0\\:\\mathrm{eV}$ , corresponds to C-Ti- $\\cdot\\mathrm{T_{x}}$ (moieties I, II, III, and/or IV). After sputtering, the BEs do not change (compare Figure 2b and Figure 2f), but the fraction of this peak, however, increases from $54\\%$ to $85\\%$ after sputtering. Its energy is slightly higher than that of C in $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (281.5-281.8 eV)[50] (see also Figure S13b). This can possibly be attributed to defects introduced in the Ti-C layers due to the etching procedure. \n\nThe other two peaks correspond to graphitic C-C and $\\mathrm{CH}_{\\mathrm{x}}$ or C-O (Figures 2b and 2f and Tables 2 and 3). The former could be due to selective dissolution of Ti during etching, which can result in graphitic C-C formation.[51] The $\\mathrm{CH_{x}}$ , and C-O species, on the other hand, likely result from the solvents used in the separation and drying processes and/or the exposure of the highsurface area material to the ambient. Note that the percentages of C-C, $\\mathrm{CH}_{\\mathrm{x}}$ and C-O decrease to about $15\\%$ of the photoemission in the C 1s region for the ap- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ sample after sputtering. Not surprisingly, the concentration of these species $(69\\%)$ in the ag- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ sample before sputtering is the highest. That value drops to $13\\%$ after sputtering (See Supplementary materials S5.2), \n\n3.1.3. O 1s region. The O 1s region for the pre-sputtered ap- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ sample (Figure 2c), was fit by components corresponding to C-Ti- ${\\bf\\cdot O}_{\\bf x}$ (moiety I), C-Ti- $(\\mathrm{OH})_{\\mathrm{x}}$ (moiety II), and $\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ (moiety \n\nIV), which are the majority fractions $(53\\%)$ of that region. The balance is in the form of $\\mathrm{TiO}_{2}$ , $\\mathrm{TiO}_{2\\mathrm{-x}}\\mathrm{F}_{\\mathrm{x}}$ , and ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ (Column 5 in Table 2). After sputtering, the total fraction of the latter is reduced to $29\\%$ . Sputtering does not affect any of the BEs of the oxygen species in the ap$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample. \n\nThe O 1s region for the pre-sputtered ag- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample (Figure S2c) was fit by the same components as above. However, in this case the content of $\\mathrm{TiO}_{2}$ , $\\mathrm{TiO}_{2\\mathrm{-x}}\\mathrm{F}_{\\mathrm{x}}$ and ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ is $31\\%$ . (Column 4 in Table S3). A large contribution to this region is from organic contamination, which overlaps with, and obscures, many other peaks. After sputtering, the total fraction of these oxides increases slightly to $34\\%$ , largely because of the removal of organic contamination. Sputtering does not affect any of the BEs of the oxygen species in the ap- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ sample. \n\nThe BEs of moiety I in the ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and $\\mathrm{ag-Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ samples, before and after sputtering, ranged from 531 to $531.3\\ \\mathrm{eV}$ . These values are close to those of an O atom near to a vacant site in $\\mathrm{TiO}_{2}$ , i.e. a defective $\\mathrm{TiO}_{2}$ $531.5\\ \\mathrm{eV})$ .[43] The peak for moiety II is located at BEs ranging from 531.7 to $532~\\mathrm{eV}$ , which is quite close to that of OH groups at bridging sites on $\\mathrm{TiO}_{2}$ .[43] The binding energy for moiety II shifts to a lower BEs upon aging and/or sputtering, which indicates that the local environment of such species is changed upon aging and/or sputtering As discussed above, the $\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ component (moiety IV) reflects the aqueous nature of the production of MXenes. The BE of its peak, for the pre- and post-sputtered ap- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ – at 533.8 and $533.7\\mathrm{eV}$ , respectively – are quite close to each other and to that of water adsorbed on titania $(533.5~\\mathrm{eV})$ ).[43] This BE is higher than that for the same component in the $\\mathbf{ag-Ti_{3}C_{2}T_{x}}$ sample pre- and post-sputtering, which are at 533.2 and $533.3\\mathrm{eV}$ , respectively, (see Figures S2c and S3c and Tables S3 and S4). This species has been observed for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , as well as other MXenes such as $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ and $\\mathrm{V}_{2}\\mathrm{CT}_{\\mathrm{x}}$ .[22, 52] The $\\operatorname{Al}(\\operatorname{OF})_{\\mathrm{x}}$ species, present in ap- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ after sputtering, and ag- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ before, and after, sputtering is present as a by-product of the synthesis procedure. The presence of $\\operatorname{Al}(\\operatorname{OF})_{\\mathrm{x}}$ after sputtering in ap- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ probably reflects inhomogeneities in the etched powders and/or less than perfect washing. \n\nNo useful quantitative information – as opposed to BEs – could be obtained from the O XPS spectra of the aged samples before sputtering because the fitted peaks in the $531~\\mathrm{eV}$ to $534~\\mathrm{eV}$ BE range overlaped with those of other organic compounds [53] whose concentration is nontrivial. \n\n3.1.4. F 1s region. The major component in the F 1s region (Figure 2d) prior to sputtering for the ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample was C-Ti- $\\cdot\\mathrm{F_{x}}$ (i.e. moiety III in Figure 1) at a BE of $685.0\\ \\mathrm{eV}$ . This BE is 0.1 eV higher than that of $\\mathrm{TiF}_{4}$ , [54] a similar compound that should have a value close to that of the Ti-F bond in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{F}_{\\mathrm{x}}$ . After sputtering, the BE increases to $685.2\\mathrm{eV}$ (Figure 2h, and Table 3). Before sputtering of the ag- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample, the BE of moiety III drops $0.2\\ \\mathrm{eV}$ (Figure S2d and Table S3). After sputtering, the BE of this moiety, is identical to that of the ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ (Figure 2d and Table 2). All samples contained small fractions of $\\mathrm{TiO}_{2\\mathrm{-x}}\\mathrm{F}_{\\mathrm{x}}$ , $\\mathrm{AlF_{x}}$ and $\\operatorname{Al}(\\operatorname{OF})_{\\mathrm{x}}$ (Tables 2, 3, S3 and S4). The latter two are present as byproducts of the synthesis procedure, and their presence was confirmed by high-resolution XPS spectra in the Al 2p region (Figure S2e). \n\n![](images/79ba08a97359ebe3ce1cc5932c70e61e8121f98c7290a00f990c4dc9568b7240.jpg) \nFigure 2. \nComponent peak-fitting of XPS spectra for ap- $\\mathbf{\\cdot}\\Gamma\\mathbf{i}_{3}\\mathbf{C}_{2}\\mathbf{T}_{\\mathbf{x}},$ (a) Ti 2p, (b) C 1s, (c) O 1s, and (d) F 1s before sputtering and, (e) Ti 2p, (f) C 1s, (g) O 1s and, (h) F 1s after sputtering. The various peaks under the spectra represent various moieties assumed to exist. The results are summarized in Tables 2 and 3 for the pre and post-sputtering samples, respectively. \n\nTable 2. XPS peak fitting results for ap- $\\mathbf{\\cdotTi_{3}C_{2}T_{x}}$ before sputtering. The numbers in brackets in column 2 are peak locations of Ti $2{\\mathsf{p}}_{1/2}$ ; their respective full-widths at half maximum, FWHM, are listed in column 3 in brackets. \n\n
RegionBE [eV]aFWHM [eV]aFractionAssigned toReference
Ti 2p3/2 (2p1/2)455.0 (461.2)0.8 (1.5)0.28Ti (I, II or IV)[48, 50]
455.8 (461.3)1.5 (2.2)0.30Ti²+ (I, II, or IV)[48]
457.2 (462.9)2.1 (2.1)0.32Ti3+ (I, II, or IV)[48]
458.6 (464.2)0.9 (1.0)0.02TiO2[55, 56]
459.3 (465.3)0.9 (1.4)0.03TiO2-xFx[57]
460.2 (466.2)1.6 (2.7)0.05C-Ti-Fx (III)[54]
C1s282.00.60.54C-Ti-Tx (I, II,III, or IV)[48, 50]
284.71.60.38C-C[58]
286.31.40.08CHx /C-0[58]
O 1s529.91.00.29TiO2[43, 56]
531.21.40.18C-Ti-Ox (I) and/or ORb[43,53]
532.01.10.18C-Ti- (OH)x (II) and/or ORb[43,53]
532.81.20.19AlO3 and/or ORb[53,59, 60]
533.82.00.17 H2Oads (IV) and/or ORb[43, 53]
F 1s685.01.7
685.31.10.38 0.29C-Ti-Fx (III)[54]
686.42.00.30TiO2-xFx AIFx[57] [57]
688.32.00.02Al(OF)x[59]
\n\na Values in parenthesis correspond to the $2{\\mathsf{p}}_{1/2}$ component. b OR stands for organic compounds due to atmospheric surface contaminations. \n\nTable 3. XPS peak fitting results for ap- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ after sputtering. Numbers in brackets in column 2 are peak locations of Ti $\\mathsf{2}\\mathsf{p}_{1/2}$ ; their full-widths at half maximum, FWHM, are listed in column 3 in brackets. \n\n\n
RegionBE[eV]FWHM [eV]FractionAssigned toReference
Ti 2p3/2 (2p1/2)454.8 (461.0)1.0 (1.9)0.52Ti (I, II or IV)[48, 50]
455.9 (461.5)2.2 (2.4)0.14Ti2+ (I, II, or IV)[48]
457.5 (463.2)2.3 (2.0)0.21Ti?*+ (I, II, or IV)[48]
459.0 (464.7)1.0 (1.1)0.02TiO2[55,56]
\n\n
460.4 (466.1)2.1 (2.9)0.11C-Ti-Fx (III)[44]
C 1s282.00.60.85C-Ti-Tx (I, II,III, or IV)[48,50]
284.60.180.14C-C[58]
286.51.40.01C0.Hx/C-0[58]
O1s530.31.10.16TiO2[43,56]
531.21.20.39C-Ti-Ox (I) and/or ORb[43, 53]
531.91.10.24C-Ti- (OH)x (II) and/or ORb[43, 53]
532.81.20.09AlO3 and/or ORb[53, 59, 60]
533.71.70.08HOads (IV) and/or ORb[43, 53]
534.91.70.04A1(OF)x[59]
F 1s685.21.80.44C-Ti-Fx (III)[44]
686.21.60.30AlFx[59]
687.32.50.26A1(OF)x[59]
\n\na Values in parenthesis correspond to the $2{\\mathsf{p}}_{1/2}$ component. b OR stands for organic compounds due to atmospheric surface contaminations. \n\n# 3.2. ag-Nb4C3Tx (Figure 3; Table 4) \n\nFigures 4a to d plot the post-sputtered spectra for Nb, C, O and F, respectively, in the ag$\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ sample, together with their peak fits. The results are summarized in Table 4. \n\n3.2.1. Nb 3d region. The XPS spectra of this region (Figure 3a) were fit by the corresponding components listed in column 5 in Table 4: Nb‡, Nb\\*, Nb (moieties I, II, and/or IV), and C-Nb- $\\cdot\\mathrm{F_{x}}$ (moiety III). These species comprised $86\\%$ of the photoemission in the region, while the rest is assigned to the various oxides, NbO, $\\mathrm{Nb}{\\mathrm{O}}_{2}$ , $\\mathrm{NbO}_{\\mathrm{l-x}}\\mathrm{F}_{\\mathrm{x}}$ and ${\\tt N b}_{2}{\\tt O}_{5}$ and a nearly negligible unidentified component at a BE of $209.2\\mathrm{eV}$ (only $1\\%$ of photoemission), which could be due to the effect of Ar sputtering. \n\nThe peak assigned to moieties I, II and/or IV has a BE of $203.8\\mathrm{eV}$ , which is $0.4\\mathrm{eV}$ lower than to its counterpart in $\\mathrm{Nb}_{4}\\mathrm{AlC}_{3}$ (Figure S17a) and is 0.1 eV lower than of its counterpart in NbC.[46, 47] Since this species corresponds to the two outer Nb layers, this decrease in BE is, again, due to the replacement of the Al layers by more electronegative surface terminations.[46] \n\nConversely, the peak attributed to the two inner metal atom layers $(\\boldsymbol{\\mathrm{Nb}}^{*})$ has a BE of $203.5\\ \\mathrm{eV}$ , which is $0.2\\ \\mathrm{eV}$ lower than that of its NbC counterpart $(203.7{\\mathrm{~eV}})$ . This somewhat unexpected result suggests that the inner Nb atoms in $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ take on additional electron density as compared to those in NbC. \n\nBoth inner and outer Nb species exist before sputtering (Supplementary materials section S5.4, Figures S5 and Table S7). However, after sputtering a peak appears at a lower BE (203.1 eV), that was not present before. This peak can thus be attributed to sputter damage of Nb and/or Nb\\*. 3.2.2. C 1s region. The C 1s region (Figure 3b) was fit by components corresponding to Nb-Cv, C-Nb- $\\cdot\\mathrm{T_{x}}$ (I, II, or IV) and small fractions for graphitic C-C and $\\mathrm{CH}_{\\mathrm{x}}$ . The peak corresponding to Nb-C (I, II, III and/or IV) has a BE of $282.8\\ \\mathrm{eV}$ , which is slightly higher than that of $\\mathrm{Nb}_{4}\\mathrm{AlC}_{3}$ (282.7 eV) (Figure S16b) and NbC (281.8 eV).[61] A peak at a lower BE $(282.3\\ \\mathrm{eV})$ is also present before, and after, sputtering, which can be attributed to a C near a vacancy, or defect, site (Nb-Cv). \n\n3.2.3. O 1s region. The spectra in this region (Figure 3c) were fit by components corresponding to $\\mathrm{C-Nb.O_{x}}$ (moiety I, 531.0 eV), C-Nb- $\\mathrm{(OH)_{x}}$ (moiety II, 531.6 eV) and $\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ (moiety IV, $533.3\\ \\mathrm{eV})$ . These species comprise $68\\%$ of the O 1s region photoemission (Table 5). Note that the $\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ peak position is located quite close to the same species discussed above for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , lending credence its assignment. The remainder of the photoemission is fit by components corresponding to oxides of $\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ $(530.5~\\mathrm{eV})$ , ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ $(532.4~\\mathrm{eV})$ and oxyfluorides of $\\operatorname{Al}(\\operatorname{OF})_{\\mathrm{x}}$ (534.7 eV). [59, 60, 62-64] These species are a result of surface oxidation and/or are by-products of the synthesis. \n\n3.2.4. F 1s region. The spectra in this region (Figure 3d) were fit by a peak corresponding to CNb- $\\cdot\\mathrm{F_{x}}$ (moiety III) that comprised $75\\%$ of the photoemission for the region. The other $25\\%$ of photoemission was fit by components for $\\mathrm{NbO_{1-x}F_{x}}$ and $\\mathrm{AlF_{x}}$ (Table 4). The peak assigned to moiety III sits at a BE of $685.3\\ \\mathrm{eV}$ , which is slightly higher than the F 1s peak value for NbF5.[45] The peak for $\\mathrm{NbO_{1-x}F_{x}}$ is at $684.0\\ \\mathrm{eV}$ . The presence of $\\mathrm{AlF_{x}}$ is confirmed by the appearance of a peak for this species in the Al 2p region (Figure S6). \n\n![](images/a222347a9fcd8bfab15d0d777d3c2d87f8e0934dd4cb8060602892ae5229f3e1.jpg) \nFigure 3. Post $\\mathrm{Ar}^{+}.$ -sputtering component peak-fitting of XPS spectra for, (a) Nb 3d, (b) C 1s, (c) O 1s and, (d) F 1s for ag- $\\mathbf{\\cdotNb}_{4}\\mathbf{C}_{3}\\mathbf{T}_{\\mathrm{x}}$ sample. The various peaks represent various moieties assumed to exist. The results, after sputtering, are summarized in Table 4. \n\nTable 4. XPS peak fitting of results – shown in Figure 3 – for ag- ${\\cdot}\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ after sputtering. The numbers in brackets in column 2 are peak locations of Nb $3\\mathrm{d}_{3/2}$ ; their full-widths at half maximum, FWHM, are listed in column 3 in brackets. \n\n
RegionBE [eV]aFWHM [eV]FractionAssigned toReference
Nb 3d5/2 (3d3/2)203.1 (205.9)0.5 (0.7)0.23Nb
203.5 (206.3)0.5 (0.7)0.38Nb*
203.8 (206.6)0.5 (0.7)0.23Nb (I,II, or IV)[46, 47]
204.1 (206.9)0.8 (0.9)0.04NbO[46, 65, 66]
205.6 (208.4)0.9 (1.0)0.02Nb(3+)-0
206.7 (209.5)0.9 (1.0)0.02Nb(4+)-O[46, 65, 66]
207.6 (210.4)0.9 (1.0)0.05Nb2O5[46, 65, 66]
208.4 (211.2)1.1 (1.2)0.02C-Nb-Fx (III)[45, 66]
C 1s282.30.70.06Nb-Cv
282.80.70.74Nb-C[61]
284.72.00.16C-C[58]
286.12.00.04CHx[58]
O 1s530.51.00.26Nb2O5[62-64]
531.01.00.32C-Nb-Ox (I)
531.61.10.24C-Nb-(OH)x (II)
532.41.10.04AlO3[59,60]
533.32.00.12HOads (IV)
534.71.30.02Al(OF)x[59]
F1s684.01.40.06NbO1-xFx
685.31.40.75C-Nb-Fx (III)[45]
686.12.10.19AIFx[59]
\n\na Values in parenthesis correspond to the $3\\mathrm{d}_{3/2}$ component. \n\n# 3.3. Distributions of Terminations \n\nFigure 4 plots the post-sputtered moles of the various $\\mathrm{{T_{x}}}$ species (as derived from the fits of the non-metal spectral regions) per MXene formula unit (as derived from the fits of the metal spectral regions) for all samples examined herein. These same results, including the C-content, are also presented in Table 5 as chemical formulas. A perusal of these results shows that: \n\na) Before sputtering, most of the OH-terminations have adsorbed $\\mathrm{H}_{2}\\mathrm{O}$ associated with them, i.e. moiety IV (yellow in Fig. 4) is prevalent. Sputtering and aging increase moiety II (grey in Fig. 4) at the expense of moiety IV. \n\nb) The fraction of F-terminations – moiety III (red in Fig. 4) – is highest for the un-sputtered, freshly prepared samples. Sputtering and aging combined with sputtering increase moieties II and IV (hatched regions in Fig. 4) at the expense of moiety III. Note that the grey and blue colored cross-hatched regions in Fig. 4 represent OH-terminations. \n\nc) The fraction of moiety I (blue in Fig. 4) for the as-prepared, un-sputtered Ti-containing MXenes is about 0.3. Sputtering and aging combined with sputtering increase that fraction significantly. For example, in the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ case, moiety I is doubled after sputtering. As noted above, aging and sputtering increase the OH-terminations at the expense of the Fterminations. A fraction of these OH-terminations are, in turn, strongly bonded to $_\\mathrm{H}_{2}\\mathrm{O}$ water molecules (blue hatched regions in Figure 4). About 22 to 33 mole $\\%$ of the Ti atoms are terminated with oxygen atoms (blue) and $\\approx17$ mole $\\%$ are F-terminated (red). \n\nd) Replacing $50\\%$ of the C atoms by $\\mathrm{\\DeltaN}$ atoms, led to a decrease in moiety I, a slight decrease moiety III and a concomitant increase in OH-terminations (compare ag- $\\mathrm{\\cdotTi}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and ag$\\mathrm{Ti}_{3}\\mathrm{CNT}_{\\mathrm{x}}$ in Fig. 4). \n\ne) For the un-sputtered, fresh, Nb-based MXenes, the major effect of increasing $n$ , is the presence of a significantly higher fraction of the hydroxyl terminations (Table 5). For the Ti-based MXenes, increasing $n$ , results in an increase in moiety I, while the combined total of moieties II and IV remains approximately the same. \n\nf) For the un-sputtered, ap- ${\\cdot}\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ composition, the total number of moles for all terminations exceeds the maximum possible value of 2 (see Fig. 1b)– assuming one termination per surface M atom – by 0.6 moles.[67] The reason for this surface state is unclear, but it is possible that some of the terminating atoms end up occupying C-vacancy \n\nsites. In this MXene, the fraction of $^{-0}$ (blue region in Figure 4), $-\\mathrm{F}$ (orange region in Figure 4) and OH-terminations (hatched regions in Figure 4) are roughly equal. \ng) The fraction of oxygen terminations (moiety I) is highest in $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ (blue regions in Figure 4). Those in $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ are comparable to their Ti counterparts (compare blue regions in Figure 4). Interestingly, a majority of the OH-terminations in $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ have strongly bonded water molecules attached to them. \nh) With the notable exceptions of ap- $\\mathrm{\\cdotTi}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and ag- ${\\cdot}\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ , the fraction of F-terminations (orange regions in Fig. 4) is significantly lower than their –O or –OH counterparts. \ni) With the exception of the $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ -based MXene, the general effect of sputtering is to decrease the X content below the value measured for the un-sputtered samples of the same composition. For example, the sputtered ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and ap- $\\mathrm{Ti}_{3}\\mathrm{CNT}_{\\mathrm{x}}$ sample are $10\\%$ deficient in X; and the sputtered ap- $\\mathbf{\\cdotNb}_{4}\\mathbf{C}_{3}\\mathbf{T}_{\\mathrm{x}}$ composition the C content drops from 2.6 to 2.4 after sputtering. As described below in the Discussion section, this is due to ${\\mathrm{Ar}}^{+}$ ion beam damage, which selectively sputters C and N atoms from the lattice. \nj) Finally, aging seems to reverse the aforementioned trend. In all cases, the X-deficiency after aging and sputtering is less than directly after sputtering of the fresh samples. \n\n![](images/f89d04accde907c22122034e387269a6ec0ba727def45982b0ab263f4e5dc251.jpg) \nFigure 4. Ratio of moles of terminations per $\\mathbf{M}_{\\mathrm{n+1}}\\mathbf{X}_{\\mathrm{n}}$ formula unit, obtained herein. The results obtained for columns labeled by arrows were obtained before sputtering; all the rest after Ar sputtering. The formulas for before sputtering are marked with $\\ddagger$ . Both as-prepared, ap, and after aging, ag, samples are shown. The hatched regions represent the total fraction of OH terminations; the ones with $\\mathrm{H}_{2}\\mathrm{O}$ adsorbed are depicted in yellow. Note that if one termination is assumed per M atom, then in all cases the theoretical $\\mathrm{{T_{x}}}$ number per formula unit is 2 given by the horizontal dashed line. \n\nTable 5. Summary of results obtained in this work. Entries labeled $\\ddagger$ were determined from spectra before sputtering. The net negative charges on the terminations – assuming the charges on the oxygen atoms are - 2, those on F and OH, -1 – are shown in brackets below the formulas. \n\n\n
MXTxMXTxM4XTx
t ap-TiC0.9O0.3(OH)o.1(OH-HOads)0.4F0.8 (1.9)t ap-TiC2O0.3(OH)0.02(OH-HOads)0.3F1.2 (2.12)t ap-Nb4C2.6O0.9(OH)0.1(OH-HOads)0.9F0.7 (3.5)
ap-TiCo.9Oo.5(OH)0.1(OH-HOads)0.2F0.7 (2.0)ap-TiC1.8O0.6(OH)0.3(OH-HOads)0.1F0.8 (2.4)ap-Nb4C2.4O0.8(OH)0.1(OH-HOads)0.4F0.6 (2.7)
ag-TiCo.8O0.4(OH)0.6(OH-HOads)0.3F0.3 (2.0)ag-Ti3C1.8O0.6(OH)0.4(OH-HOads)0.5F0.3 (2.4)ag-Nb4C2.3O0.9(OH)0.35(OH-HOads)0.35F0.7 (3.2)
ap-NbCOo.8(OH-H2Oads)0.5F0.7 (2.8) ap-TiCNO0.23(OH)0.03(OH-H2Oads)0.3F1.3 (2.09)
ap-NbC0.9O0.6(OH)0.01(OH-HOads)0.3F0.4 (1.91)ap-TiC0.9N0.9Oo.5(OH)0.07(OH-HOads)0.3F0.5 (1.87)
ag-Nb2CO1.1(OH)o.2(OH-HOads)0.4F0.3 (3.1)ag-TiCo.6No.8O0.4(OH)0.6(OH-HOads)0.6F0.25 (2.25)
\n\n‡ Before sputtering. \n\n# 3.4. Global Chemistries and Effect of Sputtering \n\nTable 6 summarizes the global chemistries (including non-MXene species) as deduced from the XPS spectra, before and after sputtering. The most notable trend seen in these results is the reduction – by $\\approx50\\%$ in some cases – of the C signal and the subsequent increase in the Msignal upon sputtering. For example, for the ag- $\\cdot\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample, the Ti percentage increased from about 17 at. $\\%$ before sputtering to $28\\%$ after sputtering; concomitantly, the C percentage decreased from 33 to $16\\mathrm{at.\\%}$ . \n\nTable 6. Summary of global atomic percentages - including non-MXene entities - before and after sputtering. \n\n\n
Ti at%Nb at.%C at.%F at.%O at.%Al at.%N at.%
ap-TiCTx (before)26.1±0.131.4±0.225.5±0.215.1±0.21.9±0.1<0.1
ap-TiCTx (after)34.1±0.223.7±0.320.9±0.218.0±0.23.3±0.2<0.1
\n\n
ag-TiCTx (before)16.8±0.333.4±0.524.8±0.420.1±0.43.3±0.61.6±0.3
ag-TiCTx (after)28.4±0.516.2±0.724.0±0.526.4±0.54.2±0.6<0.1
ap-TiCTx (before)27.2±0.939.4±0.913.4±0.620.0±0.7<0.1< 0.1
ap-TiCTx (after)33.4±0.929.5±0.913.7±0.723.4±0.9<0.1< 0.1
ag-TiCTx (before)19.3±0.331.1±0.611.4±0.434.9±0.61.2±0.7<0.1
ag-TiCTx (after)33.7± 0.515.8±0.711.8±0.535.5±0.61.9±0.71.3±0.3
ap-TiCNTx (before)30.6±1.829.4±1.116.1±0.812.1±0.7<0.111.8±0.6
ap-TiCNTx (after)36.5±1.518.8±1.013.4±0.718.3±1.0< 0.112.9±0.7
ag-TiCNTx (before)20.5±0.320.1±0.613.4±0.538.0±0.61.9±0.56.1±0.4
ag-TiCNTx (after)32.8±0.59.3±0.615.1±0.531.3±0.61.5±0.710.0±0.5
ap-NbCTx (before)25.0±0.7 31.4±0.912.6± 0.631.0±0.8< 0.1<0.1
ap-NbCTx (after)42.5±0.9 24.3±1.111.7±0.535.1±0.8<0.1< 0.1
ag-NbCTx (before)16.0±0.3 33.6±0.815.1± 0.532.6±0.61.2±0.51.5±0.6
ag-NbCTx (after)38.8±0.521.0±1.0 9.5±0.528.3±0.71.4±0.6< 0.1
ap-Nb4CTx (before)25.3±0.255.0±1.0 4.2±0.615.5±0.7<0.1<0.1
ap-Nb4C3Tx (after)29.7±0.452.3±0.6 3.6±0.414.4±0.5<0.1< 0.1
ag-Nb4C3Tx (before)10.8±0.236.0±1.0 21.7±0.626.3±0.75.0±1.5< 0.1
ag-Nb4C3Tx (after)39.9±0.524.4±0.7 7.3±0.324.7±0.53.7±0.6<0.1
\n\nSpectra collected before sputtering for the fresh MXenes in this study show that the M:X ratio is the same as the theoretical ratio for all MXenes except $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ has a M:X ratio of 2:0.9 ( $10\\%$ deficiency in X). This deficiency might be due to preferential HF-etching of the X element. After sputtering of fresh MXene samples, an increase in the M:X ratio is observed for all MXenes (except $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}\\mathrm{,}$ ) which is due to $\\mathrm{Ar}^{+}$ ion beam damage, selectively sputtering C atoms from the lattice. After sputtering, the aged MXenes in this study exhibit a further increase in the M:X ratio, compared to the fresh sputtered samples.. For example, ag- $\\mathbf{\\cdot}\\mathrm{Ti}_{2}\\mathbf{CT}_{\\mathrm{x}}$ has a M:X ratio of 2:0.8 ( $20\\%$ deficiency in X), ag- $\\mathrm{\\cdotTi_{3}C N T_{x}}$ has a M:X ratio of 3:1.2 ( $40\\%$ deficiency in X), and ag$\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ has a M:X ratio of 4:2.3 ( $40\\%$ deficiency in X). This change in ratio may be attributable to a replacement of some of the C atoms in the MXenes sheets by O during oxidation. \n\nTo further explore the effect of sputtering, the moles of C and moles – per formula unit – of moieties I, II, III and IV in ap- $\\mathrm{\\cdotTi_{3}C_{2}T_{x}}$ , before and after ${\\mathrm{Ar}}^{+}$ sputtering are plotted in Figure 5. From these results it is obvious that the F-content is also reduced, with a concomitant increase in moiety I. There is also a decrease in the moles of $\\mathrm{H}_{2}\\mathrm{O}$ strongly adsorbed to the surface, i.e. moiety IV, (see Figure 5). The same tendency can also be gleaned from comparing the derived formulae before $\\left[\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{O}_{0.3}(\\mathrm{OH})_{0.32}\\mathrm{F}_{1.2}\\right]$ and after $\\mathrm{[Ti_{3}C_{1.8}O_{0.6}(O H)_{0.4}F_{0.8}]}$ sputtering. It is thus obvious that the reduction in moiety III is accompanied with an increase in moiety I. Said otherwise, neither the C-atoms in ap- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ nor the F-terminations – i.e. moiety III – are immune to the sputtering procedure used in this work. The same analysis of other compositions is not possible, due to organic (ambient) contamination obscuring relevant peaks, however a similar trend would be expected. Whether the entirety of the increase in M:F is due to preferential $-\\mathrm{F}$ sputtering, or has some contribution from a decreased concentration of $-\\mathrm{F}$ on the interior of the MXenes is unclear. Regardless, the C- and F-contents of sputtered samples reported herein most probably underestimate their true values. \n\n![](images/34ba8b6efa45312f98d2f2e4ab393265e3f7edeec9b689fe8f26eea3ed063ade.jpg) \nFigure 5. Number of moles of C and moles of moieties I, II, III and IV, per $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ formula unit, for the ap$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample before, and after, Ar sputtering. \n\nThe effects of sputtering on the fraction of the various oxides present in the various MXenes are plotted in Figures S18 and S19. From these results it is clear that sputtering decreases the total fraction of Ti oxides and oxyflourides in the Ti-containing compositions (Figure S18) and the Nb oxides and oxyflourides in the Nb-containing compositions (Figure S19). Some MXenes appear to be more prone to oxidation than others. For example, sputter cleaning ag- $\\mathbf{\\cdotTi_{3}C N T_{x}}$ decreased the fraction of oxides from $88.3\\%$ to about $50.2\\%$ , compared to fractions of $48.3\\%$ and $34.6\\%$ for the $\\mathbf{ag}{-}\\mathrm{Ti}_{3}\\mathbf{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample. No clear correlation was found between oxidation susceptibility and n or M. \n\nFigures S20a and b plot the atomic percentages of the various C species in the ap- and ag$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ samples before, and after, sputtering, respectively. From these results it is clear that the atomic percentages of the C-species associated with the ap- $\\mathrm{\\cdotTi}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene structure, increase from $\\sim54$ at. $\\%$ before, to $\\sim85$ at. $\\%$ after sputtering (Tables 2 and 3, Figure S20a). In the case of the aged sample, the respective values are $\\sim31$ at. $\\%$ to $\\sim87$ at. $\\%$ (Tables S3 and S4, Figure \n\nS20b). We note that the presence of a thin adventitious C film on the outermost surfaces of our pressed discs that were stored in air for a relatively long time is not too surprising. This is all confirmed by the fact that the fraction of adventitious $\\mathrm{~C~}$ and hydrocarbons for the ap- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sample before sputtering was only $10\\%$ ; after sputtering it was $<1\\%$ . For all other MXenes the adventitious C and hydrocarbons concentrations were $<2\\%$ after sputtering. \n\nThe effects of aging on the samples are demonstrated in Tables 5 and 6. It can be seen in Table 5 that upon aging, the amount of $-\\mathrm{F}$ terminations are reduced for all of the MXenes, except $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ , which stays the same. Concomitantly, the amount of $-\\mathrm{OH}$ terminations are increased for all of the MXenes during aging. When viewed from a stoichiometric perspective, the M:O ratio (with the O content derived from the sum of moieties I, II and IV) decreases for all of the MXenes as they age (Table 5). For example, the M:O ratio for ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ is 3:1, while the M:O ratio for a $\\underline{{\\mathbf{y}}}_{-}\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ is 3:1.5. These data indicate that as MXenes age, the surface chemistry changes as $-\\mathrm{F}$ groups are predominately replaced with –OH groups. Note also, that the total number of moles for the various terminations gradually increases over time, indicating that oxidation of the MXenes begins as surface functionalization. As more evidence for this trend, the global (including non-MXene species) M:O ratio also decreases from 3:1.6 for ap- $\\mathbf{\\cdotTi}_{3}\\mathbf{C}_{2}\\mathbf{T}_{\\mathrm{x}}$ to 3:2.8 for ag- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ (Table 6). The change in the global M:O ratio for these samples indicates the uptake of oxygen over time as oxides are formed. Similar trends occur for all of the MXenes, though again, some show to be more prone to oxidation than others. For example, the global M:O ratio for ap- $\\mathbf{\\cdot}\\mathbf{\\vec{I}\\vec{1}_{2}C T_{x}}$ is 3:2.1 while the ratio for ag $\\succ\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ is 1:1.05. The fact that these trends are seen for all MXenes, however, clearly indicates the surface chemistry and global changes due to aging are processes that are ubiquitous. \n\nCombined with the observation that sputtering decreases the amount of oxides, the oxygen and carbon data help to illustrate the overall framework of the aged MXene samples, wherein the MXene sits at the center of the grain, surrounded by a thin layer of oxides, which is then coated in a C-film. Graphitic carbon is present as a synthetic by-product as well, and likely helps to maintain conductive contact between MXene particles. The comparison between as-prepared and aged samples demonstrates that the use of MXene shortly after synthesis greatly reduces the amount of oxides and adventitious carbon present. \n\n# 4. Discussion \n\nBased on the totality of the results, summarized in Fig. 4 and Table 5, we conclude that the overall formulas for the Ti-containing MXenes – calculated without including the $\\mathrm{TiO}_{2}$ and other known oxide fractions – are $\\mathrm{Ti_{3}C_{2}O_{0.3}(O H)_{0.32}F_{1.2}}$ and $\\mathrm{Ti_{3}C_{1.8}O_{0.6}(O H)_{0.4}F_{0.8}}$ for ap- $\\cdot\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , before and after sputtering, respectively. For the sputtered samples measured after aging in air, the formulas are: $\\mathrm{Ti_{3}C_{1.8}O_{0.6}(O H)_{0.9}F_{0.3},\\ T i_{2}C_{0.8}O_{0.4}(O H)_{0.9}F_{0.3}}$ and $\\mathrm{Ti_{3}C_{0.6}N_{0.8}O_{0.4}(O H)_{1.2}F_{0.25}}$ . Interestingly, if one assumes the charge of $-0$ is - 2, and those of $-\\mathrm{F}$ and $-\\mathrm{OH}$ are $^{-1}$ , then the average net negative charges on the surface terminations – shown in brackets below the formulas in Table 4 – for the Ti-based compounds are $2.15{\\pm}0.2\\$ . In case of the Nb-containing MXenes, the average value is $2.9{\\pm}0.6\\$ . This is an important result because it suggests that the $\\mathbf{M}_{\\mathrm{n+1}}\\mathbf{X}_{\\mathrm{n}}$ surface layers have a fixed net positive charge to which the composition of surface terminations must adjust to compensate and result in a neutral structure. \n\nRecent XANES measurements have shown that the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ spectra as quite comparable to those of TiO and that the average oxidation state of the Ti atoms was $\\approx2.4$ .[68] Using this value – and assuming the oxidation states of the –O, –OH and $-\\mathrm{F}$ groups to be -2, -1 and -1, respectively – one can solve for the average oxidation states of the C atoms. Using the results shown in Table 4, the average C oxidation state in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ is $-2.6{\\pm}0.1\\$ . Why these are the favored oxidation states is not clear at this time, but is a fruitful area of research for theoreticians. Similar calculations for the other compositions must await XANES measurements to determine the average M oxidation states. \n\nFrom the results shown in Figure 4, we conclude that the overall formulas for ag- ${\\cdot}\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ and ag- $-\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ – in the presence of ${\\tt N b}_{2}{\\tt O}_{5}$ that is excluded from the analysis – are $\\mathrm{Nb}_{2}\\mathrm{C}_{0.9}\\mathrm{O}_{1.1}(\\mathrm{OH})_{0.6}\\mathrm{F}_{0.3}$ and $\\mathrm{Nb}_{4}\\mathrm{C}_{2.3}\\mathrm{O}_{0.9}(\\mathrm{OH})_{0.7}\\mathrm{F}_{0.7}$ . Comparing these two compounds, it is obvious that the number of oxygen terminations per surface Nb atom in the former is slightly higher than in the latter. Conversely, the concentration of F-terminations, per surface Nb atom, is roughly half in the former than in the latter. The OH-terminations are more or less comparable. Looking at the adsorbed water component (yellow regions in Fig. 4), it is slightly larger in the ag- $-\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ case, compared to ag- $\\mathbf{\\cdotNb}_{4}\\mathbf{C}_{3}\\mathbf{T}_{\\mathrm{x}}$ . These results are important because they confirm that what determines the terminations of a given MXene is not just the nature of the M-element, but also the number of those layers, viz. $n$ in $\\mathbf{M}_{\\mathrm{n+1}}\\mathbf{X}_{\\mathrm{n}}\\mathbf{T}_{\\mathrm{x}}$ . These comments notwithstanding (and as noted above), why the average moles of terminations is $>2$ is unclear at this time, but could be due to the diffusion of some terminations within the C-vacancies. \n\nPost-synthesis, the dominant surface group on most MXenes is –F, viz. moiety III. This result is not surprising, given that HF is used for their production. However, another important result of this work is the instability of these F-terminations, as evidenced by the reduction in their concentrations after sputtering (Figure 5, and Table 5), and upon aging (Table 5, and compare bars labeled ap- and ag- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ in Figure 4). The exchange of these $-\\mathrm{F}$ groups for –OH as the samples age indicates that, in the presence of oxygen and/or water, the –OH termination is more favored, as predicted theoretically.[69] \n\nBased on our results it should be possible to tailor the surface terminations to suit the properties sought. For example, in some energy storage applications, OH terminations may be desirable, in others, not.[69] The fact that it is possible to tune, or control, the surface terminations is thus an important advance. For example, it was found in recent work that the replacement of F-terminations with –OH groups led to an increase in the electrochemical performance of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ -based supercapacitor.[70] The overall predisposition of Ti-MXenes to have –OH surface terminations is interesting, however, as it is the opposite of what is known for TiC and $\\mathrm{TiO}_{2}$ . TiC is known to react with water, dissociating the molecule into oxo groups.[71] Additionally, $\\mathrm{TiO}_{2}$ typically only contains $\\sim25\\%$ –OH groups, which is less than the $39-50\\%$ observed herein for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ .[43] \n\n# 5. Conclusions \n\nHerein, we presented an in-depth analysis of the XPS spectra of the core levels of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ , $\\mathrm{Ti}_{3}\\mathrm{CNT}_{\\mathrm{x}}$ , $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ and $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ cold pressed, 2D multilayered flakes. Before and after ${\\mathrm{Ar}}^{+}$ sputtering, the MXene surfaces are terminated by mixtures of $-0$ , $-\\mathrm{F}$ , and –OH, where a fraction of the latter are relatively strongly bonded to adsorbed $_\\mathrm{H}\\mathrm{}_{2}\\mathrm{O}$ molecules. For freshly prepared samples, –F is the predominant surface group. With time, the latter is gradually oxidized, leading to the formation of metal oxyfluorides and a decrease in their concentration. The MXenes all oxidize over time, and demonstrate an increase in oxygen content. Additionally, some MXenes are more prone to oxidation than others, displaying a large percentage of oxidation products when allowed to age. \n\nThe ap- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ compositions before and after sputtering were determined to be $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{O}_{0.3}(\\mathrm{OH})_{0.32}\\mathrm{F}_{1.2}$ and $\\mathrm{Ti_{3}C_{1.8}O_{0.6}(O H)_{0.4}F_{0.8}}$ , respectively, indicating that sputtering selectively removes C from this MXene lattice, as well as reduces the concentration of Fterminations. The same holds true for ap- $\\mathrm{\\cdotTi_{3}C N T_{x}}$ before and after sputtering, where their compositions were determined to be $\\mathrm{Ti_{3}C N O_{0.23}(O H\\mathrm{-}H_{2}O_{a d s})O_{0.3}F_{1.3}}$ and Ti3C0.9N$\\phantom{-}_{0.9}\\mathrm{O}_{0.5}(\\mathrm{OH})_{0.03}(\\mathrm{OH}\\mathrm{-}\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}})_{0.3}\\mathrm{F}_{0.5},$ , respectively. Combining these results with recent XANES measurements, we conclude that the average oxidation states of the Ti and C atoms in the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ compositions are $\\approx+2.4$ and $\\approx-2.6$ , respectively. It follows that the net charge on a MX block is positive and is neutralized by the adsorption of various negative terminations. \n\nThe ap- $\\mathrm{\\cdotTi_{2}C T_{x}}$ compositions, before and after sputtering, however, were determined to be $\\mathrm{Ti_{2}C_{0.9}O_{0.3}(O H)_{0.1}(O H\\mathrm{-}H_{2}O_{a d s})_{0.4}F_{0.8}}$ and $\\mathrm{Ti_{2}C_{0.9}O_{0.5}(O H)_{0.1}(O H\\mathrm{-}H_{2}O_{a d s})_{0.2}F_{0.7}},$ respectively. In this case, the major effect of sputtering is to convert some of the OH terminations to O. The overall formulas for the other aged MXenes, measured after sputtering, were determined to be $\\mathrm{Ti_{3}C_{1.8}O_{0.6}(O H)_{0.9}(F)_{0.3}}$ , Ti2C0.8O0.4(OH)0.9(F)0.3, $\\mathrm{Ti_{3}C_{0.6}N_{0.8}O_{0.4}(O H)_{1.2}(F)_{0.25}},$ $\\mathrm{Nb}_{2}\\mathrm{C}_{0.9}\\mathrm{O}_{1.1}(\\mathrm{OH})_{0.6}\\mathrm{F}_{0.3}$ and $\\mathrm{Nb}_{4}\\mathrm{C}_{2.3}\\mathrm{O}_{0.9}(\\mathrm{OH})_{0.7}\\mathrm{F}_{0.7}$ . \n\nThrough this study, we were able to focus on the distribution of terminations for the various MXenes and the effect of changing several parameters such as the number of layers, M element and X element on the distribution of the terminations. In the case of Ti-MXenes, changing the number of layers, $n$ , or the X element has little effect on the fraction of F-terminations. However, both of these factors affect the ratio of the $^{-0}$ to $-\\mathrm{OH}$ terminations: increasing $n$ from 1 to 2 leads to an increase in the $-0$ to –OH ratio, while changing $50\\%$ of the X element causes the –O to $-\\mathrm{OH}$ ratio to decrease. For the Nb-MXenes, the mole $\\%$ of F-terminations doubles from $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\mathrm{x}}$ to $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\mathrm{x}}$ . The change in the $^{-0}$ to $-\\mathrm{OH}$ ratio for the Nb-MXenes shows the opposite trend of the Ti-MXenes, as $n$ increases, that ratio decreases. \n\nWhen combined, these observations should impact the choice of the MXene to use for a specific application. The usefulness of quantifying under which conditions certain functional groups will be present on MXene surfaces is a significant development that will aid the intelligent design of any chemical systems that include these exciting and promising 2D compounds. \n\n# 6. Acknowledgments \n\nThis work was supported by the European Research Council under the European Communities Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no. [258509]. J. R. acknowledges funding from the Swedish Research Council (VR) grant no. 642-2013-8020 and from the KAW Fellowship program. The Swedish Foundation for Strategic Research (SSF) is acknowledged for support through the synergy grant FUNCASE and the Future Research Leaders 5 program. MN was partially sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy. We also acknowledge Dr. Jian Yang for providing $\\mathrm{Nb}_{4}\\mathrm{AlC}_{3}$ powders. \n\n# 7. References \n\n[1] K.S. Novoselov, V.I. Fal'ko, L. Colombo, P.R. Gellert, M.G. Schwab, K. Kim, A roadmap for graphene, Nature, 490 (2012) 192-200. \n[2] K.I. Bolotin, K.J. Sikes, Z. Jiang, M. Klima, G. Fudenberg, J. Hone, P. Kim, H.L. Stormer, Ultrahigh electron mobility in suspended graphene, Solid State Commun., 146 (2008) 351-355. [3] R.R. Nair, P. Blake, A.N. Grigorenko, K.S. Novoselov, T.J. Booth, T. Stauber, N.M. Peres, A.K. Geim, Fine structure constant defines visual transparency of graphene, Science, 320 (2008) 1308. \n[4] L. Ci, L. Song, C. Jin, D. Jariwala, D. Wu, Y. Li, A. Srivastava, Z.F. Wang, K. Storr, L. Balicas, F. Liu, P.M. Ajayan, Atomic layers of hybridized boron nitride and graphene domains, Nat. Mater., 9 (2010) 430-435. \n[5] J.N. Coleman, M. Lotya, A. O'Neill, S.D. Bergin, P.J. King, U. Khan, K. Young, A. Gaucher, S. De, R.J. Smith, I.V. Shvets, S.K. Arora, G. Stanton, H.Y. Kim, K. Lee, G.T. Kim, G.S. Duesberg, T. Hallam, J.J. Boland, J.J. Wang, J.F. Donegan, J.C. Grunlan, G. Moriarty, A. Shmeliov, R.J. Nicholls, J.M. Perkins, E.M. Grieveson, K. Theuwissen, D.W. McComb, P.D. Nellist, V. Nicolosi, Two-dimensional nanosheets produced by liquid exfoliation of layered materials, Science, 331 (2011) 568-571. \n[6] A.M. van der Zande, P.Y. Huang, D.A. Chenet, T.C. Berkelbach, Y. You, G.H. Lee, T.F. Heinz, D.R. Reichman, D.A. Muller, J.C. Hone, Grains and grain boundaries in highly crystalline monolayer molybdenum disulphide, Nat. Mater., 12 (2013) 554-561. \n[7] S. Najmaei, Z. Liu, W. Zhou, X. Zou, G. Shi, S. Lei, B.I. Yakobson, J.C. Idrobo, P.M. Ajayan, J. Lou, Vapour phase growth and grain boundary structure of molybdenum disulphide atomic layers, Nat. Mater., 12 (2013) 754-759. \n[8] R. Ma, T. Sasaki, Nanosheets of oxides and hydroxides: Ultimate 2D charge-bearing functional crystallites, Adv. Mater., 22 (2010) 5082-5104. \n[9] V. Nicolosi, M. Chhowalla, M.G. Kanatzidis, M.S. Strano, J.N. Coleman, Liquid exfoliation of layered materials, Science, 340 (2013) 1420-+. \n[10] S. Stankovich, D.A. Dikin, R.D. Piner, K.A. Kohlhaas, A. Kleinhammes, Y. Jia, Y. Wu, S.T. Nguyen, R.S. Ruoff, Synthesis of graphene-based nanosheets via chemical reduction of exfoliated graphite oxide, Carbon, 45 (2007) 1558-1565. \n[11] M.K. Kinyanjui, C. Kramberger, T. Pichler, J.C. Meyer, P. Wachsmuth, G. Benner, U. Kaiser, Direct probe of linearly dispersing 2D interband plasmons in a free-standing graphene monolayer, EPL, 97 (2012) 57005. \n[12] Y. Liu, R. Willis, K. Emtsev, T. Seyller, Plasmon dispersion and damping in electrically isolated two-dimensional charge sheets, Phys Rev B, 78 (2008) 201403. \n[13] A. Politano, A.R. Marino, V. Formoso, D. Farias, R. Miranda, G. Chiarello, Evidence for acoustic-like plasmons on epitaxial graphene on Pt(111), Phys Rev B, 84 (2011) 033401. [14] E. Bekyarova, M.E. Itkis, P. Ramesh, C. Berger, M. Sprinkle, W.A. de Heer, R.C. Haddon, Chemical modification of epitaxial graphene: spontaneous grafting of aryl groups, J. Am. Chem. Soc., 131 (2009) 1336-1337. \n[15] D.R. Dreyer, S. Park, C.W. Bielawski, R.S. Ruoff, The chemistry of graphene oxide, Chem. Soc. Rev., 39 (2010) 228-240. \n[16] K.N. Kudin, B. Ozbas, H.C. Schniepp, R.K. Prud'homme, I.A. Aksay, R. Car, Raman spectra of graphite oxide and functionalized graphene sheets, Nano Lett., 8 (2008) 36-41. [17] M. Naguib, M. Kurtoglu, V. Presser, J. Lu, J.J. Niu, M. Heon, L. Hultman, Y. Gogotsi, M.W. Barsoum, Two-dimensional nanocrystals produced by exfoliation of Ti3AlC2, Adv. Mater., 23 (2011) 4248-4253. \n[18] M.W. Barsoum, MAX Phases: Properties of machinable ternary carbides and nitrides, John Wiley & Sons 2013. \n[19] M. Ghidiu, M.R. Lukatskaya, M.Q. Zhao, Y. Gogotsi, M.W. Barsoum, Conductive twodimensional titanium carbide 'clay' with high volumetric capacitance, Nature, 516 (2014) 78-81. [20] M. Naguib, O. Mashtalir, J. Carle, V. Presser, J. Lu, L. Hultman, Y. Gogotsi, M.W. Barsoum, Two-dimensional transition metal carbides, ACS Nano, 6 (2012) 1322-1331. \n[21] M. Naguib, J. Halim, J. Lu, K.M. Cook, L. Hultman, Y. Gogotsi, M.W. Barsoum, New twodimensional niobium and vanadium carbides as promising materials for Li-ion batteries, J. Am. Chem. Soc., 135 (2013) 15966-15969. \n[22] J. Halim, M.R. Lukatskaya, K.M. Cook, J. Lu, C.R. Smith, L.A. Naslund, S.J. May, L. Hultman, Y. Gogotsi, P. Eklund, M.W. Barsoum, Transparent conductive two-dimensional titanium carbide epitaxial thin films, Chem. Mater., 26 (2014) 2374-2381. \n[23] M. Naguib, V.N. Mochalin, M.W. Barsoum, Y. Gogotsi, 25th anniversary article: MXenes: a new family of two-dimensional materials, Adv. Mater., 26 (2014) 992-1005. \n[24] M. Ghidiu, M. Naguib, C. Shi, O. Mashtalir, L.M. Pan, B. Zhang, J. Yang, Y. Gogotsi, S.J. Billinge, M.W. Barsoum, Synthesis and characterization of two-dimensional $\\mathrm{Nb}_{4}\\mathrm{C}_{3}$ (MXene), Chem Commun (Camb), 50 (2014) 9517-9520. \n[25] B. Anasori, Y. Xie, M. Beidaghi, J. Lu, B.C. Hosler, L. Hultman, P.R. Kent, Y. Gogotsi, M.W. Barsoum, Two-dimensional, ordered, double transition metals carbides (MXenes), ACS Nano, (2015) DOI: 10.1021/acsnano.5b03591. \n[26] M. Naguib, J. Come, B. Dyatkin, V. Presser, P.L. Taberna, P. Simon, M.W. Barsoum, Y. Gogotsi, MXene: a promising transition metal carbide anode for lithium-ion batteries, Electrochem. Commun., 16 (2012) 61-64. \n[27] O. Mashtalir, M. Naguib, V.N. Mochalin, Y. Dall'Agnese, M. Heon, M.W. Barsoum, Y. Gogotsi, Intercalation and delamination of layered carbides and carbonitrides, Nature communications, 4 (2013) 1716. \n[28] Q. Tang, Z. Zhou, P. Shen, Are MXenes promising anode materials for Li ion batteries? Computational studies on electronic properties and Li storage capability of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{X}_{2}$ (X ${\\bf\\omega}=\\mathrm{F}$ , OH) monolayer, J. Am. Chem. Soc., 134 (2012) 16909-16916. \n[29] J. Come, M. Naguib, P. Rozier, M.W. Barsoum, Y. Gogotsi, P.L. Taberna, M. Morcrette, P. Simon, A non-aqueous asymmetric cell with a $\\mathrm{Ti}_{2}\\mathrm{C}$ -Based two-dimensional negative electrode, J. Electrochem. Soc., 159 (2012) A1368-A1373. \n[30] M.R. Lukatskaya, O. Mashtalir, C.E. Ren, Y. Dall'Agnese, P. Rozier, P.L. Taberna, M. Naguib, P. Simon, M.W. Barsoum, Y. Gogotsi, Cation intercalation and high volumetric capacitance of two-dimensional titanium carbide, Science, 341 (2013) 1502-1505. \n[31] O. Mashtalir, K.M. Cook, V.N. Mochalin, M. Crowe, M.W. Barsoum, Y. Gogotsi, Dye adsorption and decomposition on two-dimensional titanium carbide in aqueous media, Journal of Materials Chemistry A, 2 (2014) 14334-14338. \n[32] Q. Peng, J. Guo, Q. Zhang, J. Xiang, B. Liu, A. Zhou, R. Liu, Y. Tian, Unique lead adsorption behavior of activated hydroxyl group in two-dimensional titanium carbide, J. Am. Chem. Soc., 136 (2014) 4113-4116. [33] X. Li, G. Fan, C. Zeng, Synthesis of ruthenium nanoparticles deposited on graphene-like transition metal carbide as an effective catalyst for the hydrolysis of sodium borohydride, International Journal of Hydrogen Energy, 39 (2014) 14927-14934. \n[34] Z. Ling, C.E. Ren, M.-Q. Zhao, J. Yang, J.M. Giammarco, J. Qiu, M.W. Barsoum, Y. Gogotsi, Flexible and conductive MXene films and nanocomposites with high capacitance, Proceedings of the National Academy of Sciences, 111 (2014) 16676-16681. \n[35] M. Naguib, R.R. Unocic, B.L. Armstrong, J. Nanda, Large-scale delamination of multilayers transition metal carbides and carbonitrides \"MXenes\", Dalton Trans., 44 (2015) 9353- 9358. \n[36] O. Mashtalir, M.R. Lukatskaya, M.Q. Zhao, M.W. Barsoum, Y. Gogotsi, Amine\u001fassisted delamination of $\\mathrm{Nb}_{2}\\mathrm{C}$ MXene for Li\u001fion energy storage devices, Adv. Mater., 27 (2015) 3501- 3506. \n[37] S. Balendhran, S. Walia, H. Nili, S. Sriram, M. Bhaskaran, Elemental analogues of graphene: silicene, germanene, stanene, and phosphorene, Small, 11 (2015) 640-652. \n[38] H.S. Liu, N.N. Han, J.J. Zhao, Atomistic insight into the oxidation of monolayer transition metal dichalcogenides: from structures to electronic properties, Rsc Advances, 5 (2015) 17572- 17581. \n[39] M. Naguib, O. Mashtalir, M.R. Lukatskaya, B. Dyatkin, C. Zhang, V. Presser, Y. Gogotsi, M.W. Barsoum, One-step synthesis of nanocrystalline transition metal oxides on thin sheets of disordered graphitic carbon by oxidation of MXenes, Chem Commun (Camb), 50 (2014) 7420- 7423. \n[40] H. Ghassemi, W. Harlow, O. Mashtalir, M. Beidaghi, M.R. Lukatskaya, Y. Gogotsi, M.L. Taheri, In situ environmental transmission electron microscopy study of oxidation of twodimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and formation of carbon-supported $\\mathrm{TiO}_{2}$ , Journal of Materials Chemistry A, 2 (2014) 14339-14343. \n[41] Z. Li, L. Wang, D. Sun, Y. Zhang, B. Liu, Q. Hu, A. Zhou, Synthesis and thermal stability of two-dimensional carbide MXene $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , Materials Science and Engineering: B, 191 (2015) 33- 40. \n[42] J. Li, Y. Du, C. Huo, S. Wang, C. Cui, Thermal stability of two-dimensional $\\mathrm{Ti}_{2}\\mathrm{C}$ nanosheets, Ceram. Int., 41 (2015) 2631-2635. \n[43] S. Yamamoto, H. Bluhm, K. Andersson, G. Ketteler, H. Ogasawara, M. Salmeron, A. Nilsson, In situ x-ray photoelectron spectroscopy studies of water on metals and oxides at ambient conditions, J Phys-Condens Mat, 20 (2008) 184025. \n[44] C. Mousty-Desbuquoit, J. Riga, J.J. Verbist, Electronic structure of titanium(III) and titanium(IV) halides studied by solid-phase X-ray photoelectron spectroscopy, Inorg. Chem., 26 (1987) 1212-1217. \n[45] Y. Luo, P. Wang, L.P. Ma, H.M. Cheng, Hydrogen sorption kinetics of $\\mathrm{MgH}_{2}$ catalyzed with ${\\mathrm{NbF}}_{5}$ , J. Alloys Compd., 453 (2008) 138-142. \n[46] J. Halbritter, A. Darlinski, Angle resolved XPS studies of oxides at Nb-, NbN-, NbC- and $\\mathrm{Nb}_{3}\\mathrm{Sn}\\cdot$ surfaces, IEEE Trans. Magn., 23 (1987) 1381-1384. \n[47] M.T. Marques, A.M. Ferraria, J.B. Correia, A.M.B.d. Rego, R. Vilar, XRD, XPS and SEM characterisation of Cu–NbC nanocomposite produced by mechanical alloying, Mater. Chem. Phys., 109 (2008) 174-180. \n[48] V. Schier, H.J. Michel, J. Halbritter, ARXPS-Analysis of Sputtered TiC, SiC and $\\mathrm{Ti_{0.5}S i_{0.5}C}$ Layers, Fresen J Anal Chem, 346 (1993) 227-232. [49] E. Lewin, M. Gorgoi, F. Schäfers, S. Svensson, U. Jansson, Influence of sputter damage on the XPS analysis of metastable nanocomposite coatings, Surf. Coat. Technol., 204 (2009) 455- 462. \n[50] S. Myhra, J.A.A. Crossley, M.W. Barsoum, Crystal-chemistry of the $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{Ti}_{4}\\mathrm{AlN}_{3}$ layered carbide/nitride phases - characterization by XPS, J. Phys. Chem. Solids, 62 (2001) 811- 817. \n[51] M.R. Lukatskaya, J. Halim, B. Dyatkin, M. Naguib, Y.S. Buranova, M.W. Barsoum, Y. Gogotsi, Room-temperature carbide-derived carbon synthesis by electrochemical etching of MAX phases, Angew Chem Int Ed Engl, 53 (2014) 4877-4880. \n[52] M. Naguib, J. Halim, J. Lu, K. Cook, L. Hultman, Y. Gogotsi, M.W. Barsoum, New twodimensional niobium and vanadium carbides as promising materials for Li-ion batteries, J. Am. Chem. Soc., 135 (2013) 15966-15969. \n[53] G. Beamson, D. Briggs, High Resolution XPS of Organic Polymers: The Scienta ESCA300 Database, Wiley, 1992. \n[54] T. Sultana, G.L. Georgiev, G. Auner, G. Newaz, H.J. Herfurth, R. Patwa, XPS analysis of laser transmission micro-joint between poly (vinylidene fluoride) and titanium, Appl. Surf. Sci., 255 (2008) 2569-2573. \n[55] F. Santerre, M.A. El Khakani, M. Chaker, J.P. Dodelet, Properties of TiC thin films grown by pulsed laser deposition, Appl. Surf. Sci., 148 (1999) 24-33. \n[56] U. Diebold, $\\mathrm{TiO}_{2}$ by XPS, Surface Science Spectra, 4 (1996) 227. \n[57] T. Tanuma, H. Okamoto, K. Ohnishi, S. Morikawa, T. Suzuki, Partially fluorinated metal oxide catalysts for a Friedel–Crafts-type reaction of dichlorofluoromethane with tetrafluoroethylene, Catal. Lett., 136 (2009) 77-82. \n[58] P.M. Jayaweera, E.L. Quah, H. Idriss, Photoreaction of ethanol on $\\mathrm{TiO}_{2}(110)$ single-crystal surface, J. Phys. Chem. C, 111 (2007) 1764-1769. \n[59] K.H. Ernst, D. Grman, R. Hauert, E. Hollander, Fluorine-induced corrosion of aluminum microchip bond pads - an XPS and AES analysis, Surf. Interface Anal., 21 (1994) 691-696. [60] I. Popova, V. Zhukov, J.T. Yates, Depth-dependent electrical impedance distribution in ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ films on Al(111)-detection of an inner barrier layer, Langmuir, 16 (2000) 10309-10314. [61] A. Dacca, G. Gemme, L. Mattera, R. Parodi, XPS analysis of the surface composition of niobium for superconducting RF cavities, Appl. Surf. Sci., 126 (1998) 219-230. \n[62] R. Romero, J.R. Ramos-Barrado, F. Martin, D. Leinen, ${\\mathrm{Nb}}_{2}{\\mathrm{O}}_{5}$ thin films obtained by chemical spray pyrolysis, Surf. Interface Anal., 36 (2004) 888-891. \n[63] L. Chen, Q.Q. Sun, J.J. Gu, Y. Xu, S.J. Ding, D.W. Zhang, Bipolar resistive switching characteristics of atomic layer deposited ${\\mathrm{Nb}}_{2}{\\mathrm{O}}_{5}$ thin films for nonvolatile memory application, Current Applied Physics, 11 (2011) 849-852. \n[64] S.Q. Guo, X. Zhang, Z. Zhou, G.D. Gao, L. Liu, Facile preparation of hierarchical $\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ microspheres with photocatalytic activities and electrochemical properties, Journal of Materials Chemistry A, 2 (2014) 9236-9243. \n[65] C.F. Miller, G.W. Simmons, R.P. Wei, High temperature oxidation of Nb, NbC and Ni3Nb and oxygen enhanced crack growth, Scr. Mater., 42 (2000) 227-232. \n[66] Z. Weibin, W. Weidong, W. Xueming, C. Xinlu, Y. Dawei, S. Changle, P. Liping, W. Yuying, B. Li, The investigation of NbO2 and Nb2O5 electronic structure by XPS, UPS and first principles methods, Surf. Interface Anal., 45 (2013) 1206-1210. [67] Y. Xie, P. Kent, Hybrid density functional study of structural and electronic properties of functionalized $\\mathrm{Ti}_{\\mathrm{n+1}}\\mathrm{X}_{\\mathrm{n}}$ $\\mathrm{\\Delta}X{=}\\mathrm{\\Delta}C$ , N) monolayers, Phys Rev B, 87 (2013) 235441. \n[68] S.-M.B. M. R. Lukatskaya, X. Yu, X.Q. Yang, M.W. Barsoum, Y.Gogotsi, Probing the mechanism of high capacitance in 2D titanium carbide using in situ X-ray absorption spectroscopy, Advanced Energy Materials, DOI: 10.1002/aenm.201500589 (2015). \n[69] Y. Xie, M. Naguib, V.N. Mochalin, M.W. Barsoum, Y. Gogotsi, X. Yu, K.W. Nam, X.Q. Yang, A.I. Kolesnikov, P.R. Kent, Role of surface structure on Li-ion energy storage capacity of two-dimensional transition-metal carbides, J. Am. Chem. Soc., 136 (2014) 6385-6394. \n[70] Y. Dall'Agnese, M.R. Lukatskaya, K.M. Cook, P.-L. Taberna, Y. Gogotsi, P. Simon, High capacitance of surface-modified 2D titanium carbide in acidic electrolyte, Electrochem. Commun., 48 (2014) 118-122. \n[71] S.V. Didziulis, P. Frantz, S.S. Perry, O. El-bjeirami, S. Imaduddin, P.B. Merrill, Substratedependent reactivity of water on metal carbide surfaces, J. Phys. Chem. B, 103 (1999) 11129- 11140. " + }, + { + "id": "10.1038_NCHEM.2491", + "DOI": "10.1038/NCHEM.2491", + "DOI Link": "http://dx.doi.org/10.1038/NCHEM.2491", + "Relative Dir Path": "mds/10.1038_NCHEM.2491", + "Article Title": "Experimental realization of two-dimensional boron sheets", + "Authors": "Feng, BJ; Zhang, J; Zhong, Q; Li, WB; Li, S; Li, H; Cheng, P; Meng, S; Chen, L; Wu, KH", + "Source Title": "NATURE CHEMISTRY", + "Abstract": "A variety of two-dimensional materials have been reported in recent years, yet single-element systems such as graphene and black phosphorus have remained rare. Boron analogues have been predicted, as boron atoms possess a short covalent radius and the flexibility to adopt sp(2) hybridization, features that favour the formation of two-dimensional allotropes, and one example of such a borophene material has been reported recently. Here, we present a parallel experimental work showing that two-dimensional boron sheets can be grown epitaxially on a Ag(111) substrate. Two types of boron sheet, a beta(12) sheet and a chi(3) sheet, both exhibiting a triangular lattice but with different arrangements of periodic holes, are observed by scanning tunnelling microscopy. Density functional theory simulations agree well with experiments, and indicate that both sheets are planar without obvious vertical undulations. The boron sheets are quite inert to oxidization and interact only weakly with their substrate. We envisage that such boron sheets may find applications in electronic devices in the future.", + "Times Cited, WoS Core": 1511, + "Times Cited, All Databases": 1584, + "Publication Year": 2016, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000376529000012", + "Markdown": "# Experimental realization of two-dimensional boron sheets \n\nBaojie Feng1, Jin Zhang1, Qing Zhong1, Wenbin Li1, Shuai Li1, Hui $L i^{\\star}$ , Peng Cheng1, Sheng Meng1,2, Lan Chen1\\* and Kehui $\\mathbf{W_{u}}1,2\\star$ \n\nA variety of two-dimensional materials have been reported in recent years, yet single-element systems such as graphene and black phosphorus have remained rare. Boron analogues have been predicted, as boron atoms possess a short covalent radius and the flexibility to adopt $S p^{2}$ hybridization, features that favour the formation of two-dimensional allotropes, and one example of such a borophene material has been reported recently. Here, we present a parallel experimental work showing that two-dimensional boron sheets can be grown epitaxially on a $\\pmb{\\Delta}\\pmb{\\mathrm{g}}(\\pmb{1}\\pmb{1}\\pmb{1})$ substrate. Two types of boron sheet, a ${\\bf\\beta_{12}}$ sheet and a $x_{3}$ sheet, both exhibiting a triangular lattice but with different arrangements of periodic holes, are observed by scanning tunnelling microscopy. Density functional theory simulations agree well with experiments, and indicate that both sheets are planar without obvious vertical undulations. The boron sheets are quite inert to oxidization and interact only weakly with their substrate. We envisage that such boron sheets may find applications in electronic devices in the future. \n\nBcohroenmis rtyhethafthis $\\mathbf{B}_{12}$ oendt ion tyhteopcearriobdoinc t3a.blAe satrnidk nhags eaatriucrhe blocks in bulk boron and many boron compounds2,3. This differs from its neighbouring element, carbon, which prefers a twodimensional (2D) layered structure (graphite) in its bulk form. Meanwhile, boron clusters of medium size have been predicted to be planar or quasi-planar, for example, $\\mathrm{B_{12}}^{-},\\mathrm{B_{13}}^{+},\\mathrm{\\bar{B}_{19}}^{-}$ and $\\mathrm{B}_{36}$ (refs 4–10). This is also in contrast to carbon clusters, which exhibit various cage structures (fullerenes). Now, with the boom in graphene research, an intriguing question is whether boron can also form a monoatomic-layer 2D sheet structure? Here, we report the realization of 2D boron sheets by molecular beam epitaxy. Two types of boron sheet, consisting of a triangular boron lattice with different arrangements of hexagonal holes, have been identified. An X-ray photoelectron spectroscopy (XPS) study indicated that the 2D boron sheets are quite stable against oxidization, suggesting that they merit future investigation for potential applications. \n\nGraphene is the building block in a number of carbon nanostructures, including fullerenes and nanotubes11,12. Boron has the same short covalent radius and the flexibility to adopt $\\ensuremath{s p}^{2}$ hybridization as carbon, which would favour the formation of various low-dimensional allotropes, such as boron nanotubes, fullerenes and 2D boron sheets13–15. The 2D boron structure is particularly interesting as it has been predicted to be metallic16–20, despite bulk boron being a semiconductor. In fact, compound $\\mathrm{MgB}_{2}$ , which consists of alternative boron and magnesium layers, exhibits high- $T_{c}$ superconductivity21. Some 2D boron structures have recently been predicted to host Dirac fermions22. Theoretically, a large variety of planar 2D boron structures with competitive cohesive energy, such as α sheets16,17, $\\upbeta$ sheets16,17 and $\\chi$ sheets19,20, named after the connectivity of the boron, have been predicted. However, the experimental realization of 2D boron sheets remains a challenge. Recently, it was suggested that 2D boron sheets can form on metal substrates, such as $\\mathrm{Cu}(111)^{23}$ , $\\mathrm{Ag}(111)$ and $\\mathrm{Au}(111)^{24}$ , due to the stabilization of $\\ s p^{2}$ hybridization by metal passivation. Following this idea, we used molecular beam epitaxy (MBE) to grow boron sheets on a $\\mathrm{Ag}(111)$ surface in ultrahigh vacuum (UHV) and successfully obtained 2D boron sheets, in a manner similar to those recently reported in a parallel work by A. J. Mannix et al., referred to as ‘borophene’ in analogy with graphene25. \n\n# Results and discussion \n\nGrowth of 2D boron. Boron was grown on a single-crystal $\\mathrm{Ag}(111)$ surface by direct evaporation of a pure boron source. When the substrate temperature during growth was below $500~\\mathrm{K},$ we found only clusters or disordered structures on the surface (Supplementary Fig. 1a). At a temperature of ${\\sim}570\\mathrm{K},$ monolayer (ML) islands with a perfectly ordered structure form on the surface, as shown in Fig. 1a. The scanning tunnelling microscope (STM) image with high contrast in Fig. 1b shows parallel stripes on the island surface in the [\u0001110] direction of $\\mathrm{Ag}(111)$ . The separation between stripes is $1.5\\mathrm{nm}$ (indicated by the solid lines in Fig. 1b). The high-resolution STM image in Fig. 1c reveals ordered, parallel rows of protrusions along the [\u0001112] direction of the $\\mathrm{Ag}(111)$ substrate (horizontal direction in Fig. 1c). The distance between nearest-neighbour protrusions is $3.0\\mathrm{\\AA}$ along the rows and $5.0\\mathring\\mathrm{~A~}$ across the rows, respectively (marked by the black rectangle). The $1.5\\mathrm{nm}$ stripes observed in large-scale images (black lines in Fig. 1b) correspond to the slightly brighter protrusions, which are aligned in the direction perpendicular to the rows, as marked by the lines in Fig. 1c. This phase is labelled $^{\\cdot}\\mathrm{s}_{1}\\mathrm{\\cdot}$ . \n\nBy annealing the sample to $650~\\mathrm{K},$ we observed the transition of the S1 phase to another ordered structure (labelled ‘S2’), as shown in Fig. 1d. The S2 phase usually coexists with the S1 phase in the temperature range from 650 to $800~\\mathrm{K}.$ At higher temperatures, most areas of the surface will be transformed to the S2 phase. The S2 phase can also be obtained by directly growing boron on $\\mathrm{Ag}(111)$ with a substrate temperature of ${\\sim}680\\mathrm{~K~}$ (Supplementary Fig. 1c). The high-resolution STM images in Fig. 1e,f show that the S2 phase also consists of parallel rows of protrusions in the [\u0001112] direction of the $\\mathrm{Ag}(111)$ substrate. The distance between nearest-neighbour protrusions is $3.0\\mathring{\\mathrm{A}}$ along the rows, and $4.3\\mathring\\mathrm{A}$ across the rows. Another obvious feature is that the protrusions along the rows are divided into sections with alternate brighter and darker protrusions. Each section comprises five protrusions, so the periodicity along the row is $3.0\\mathring{\\mathrm{A}}\\times5\\mathring{=}1.5\\mathrm{nm}$ . \n\n![](images/db81dcf05bcd781d478eef1ad98a7bd27efa197674ac2c53b5132cb709fe75d3.jpg) \nFigure 1 | Formation of 2D boron sheets on Ag(111). a, STM topographic image of boron structures on ${\\sf A g}(111)$ , with a substrate temperature of ${\\sim}570\\mathrm{K}$ during growth. The boron islands are labelled as ‘S1’ phase. b, Three-dimensional version of a, in which the stripes with $1.5\\mathsf{n m}$ intervals are clearly resolved. c, High-resolution STM image of S1 phases. The S1 unit cell is marked by a black rectangle, and the $1.5\\mathsf{n m}$ stripes are indicated by solid lines. d, STM image of boron sheets after annealing the surface in a to $650~\\mathsf{K}.$ The two different phases are labelled ‘S1’ and ‘S2’. Most boron islands are transformed to the S2 phase, but the S1 phase still remains in small parts of the islands. e, STM image obtained on the area marked by the black rectangle in d. f, High-resolution STM image of the S2 phase, zoomed from e. Note that the orientation of the image is rotated to allow comparison with c. Bias voltages of STM images: $-4.0\\vee$ (a,b), $0.9\\mathrm{V}$ (c), $-4.0\\vee$ (d), $1.0\\:\\vee$ (e,f). \n\nStructures of 2D boron. As boron has very low solubility in bulk silver, we first assume that both of these structures are pure boron sheets. Among a large number of planar boron monolayer models in the literature, we find that the $\\beta_{12}$ sheet structure20 agrees very well with the S1 phase. In fact, the $\\upbeta_{12}$ sheet was predicted to form on a $\\mathrm{Ag}(111)$ substrate in a recent, independent theoretical study26. The $\\upbeta_{12}$ sheet model is characterized by hole chains separated by hexagonal boron rows. Its unit cell is rectangular, with lattice constants of 3.0 and $5.0\\mathring{\\mathrm{A}}$ in the two directions. To confirm this model, we performed first-principles calculations on the $\\upbeta_{12}$ sheet involving the $\\mathrm{Ag}(111)$ substrate. The $\\upbeta_{12}$ sheet was placed on $\\mathrm{Ag}(111)$ with the boron rows in the [\u0001112] direction of the $\\mathrm{Ag}(111)$ surface, as shown in Fig. 2a. After relaxation, the global structure of the $\\upbeta_{12}$ sheet remains planar. It is noted that, due to the lattice mismatch, five times the lattice constant of the boron sheet along the rows $(3.0\\mathring{\\mathrm{A}}\\times5=15.0\\mathring{\\mathrm{A}})$ fits well with three times the period of $\\mathrm{Ag}(111)$ $(3\\times2.9\\mathrm{~\\AA~}\\times\\sqrt{3}=15.06\\mathrm{~\\AA~})$ . This means that a Moiré pattern with $1.5\\mathrm{nm}$ periodicity will form along the boron row direction, which explains the $1.5\\mathrm{nm}$ stripes observed in the STM image (Fig. 1c). The simulated STM image of the $\\upbeta_{12}$ sheet on $\\mathrm{Ag}(111)$ shown in Fig. 2c reproduces both the rectangular lattice and the parallel striped patterns, in agreement with the STM images. \n\nOn the other hand, the S2 phase most probably corresponds to the $\\chi_{3}$ sheet model in the literature20, as shown in Fig. 2d. The structure of the $\\chi_{3}$ sheet consists of similar, but narrower zigzag boron rows separated by hole arrays. This can explain the observed slightly smaller inter-row distance in the S2 phase $(4.3\\mathring\\mathrm{A})$ than in the S1 phases $(5.0\\mathring\\mathrm{A})$ . Our first-principles calculation also suggests good commensuration between the $\\chi_{3}$ sheet and $\\mathrm{Ag}(111)$ , and the structure remains planar after relaxation, as shown in Fig. 2e. Similarly, the simulated STM image of the $\\chi_{3}$ sheet in Fig. 2f shows zigzag rows and alternate bright–dark protrusions along the rows, agreeing perfectly with our STM observations. \n\nBecause the atomic structures of the $\\upbeta_{12}$ sheet and $\\chi_{3}$ sheet on $\\mathrm{Ag}(111)$ remain planar, without obvious vertical undulation, the $1.5\\mathrm{nm}$ periodicity along the vacancy chains in the S1 phase and the dark–bright alternation in the S2 phase should correspond to the modulation of the electron density on the boron sheets. To address this question, we calculated the atomic charges of these two phases based on the Bader analysis (Supplementary Fig. 2). Inhomogeneous charge distribution is found along the boron rows in both S1 and S2 phases. Such charge inhomogeneity comes from the commensuration between the boron lattices and the $\\mathrm{Ag}(111)$ lattice, which results in different locations of the boron atoms on the $\\mathrm{Ag}(111)$ lattice, especially along the boron row direction. \n\nThe validity of the above models has been confirmed experimentally by measuring the atomic density of boron in the two phases. To precisely calibrate the boron coverage we used the well-known Si(111)-B- ${\\sqrt{3}}\\times{\\sqrt{3}}$ structure as reference. Boron atoms were deposited consecutively onto the $\\mathrm{Ag}(111)$ surface and a clean Si(111)- $7\\times7$ surface in the same deposition cycle, thus ensuring exactly the same flux and position of the samples. The B/Si(111) sample was then annealed to $1{,}000\\mathrm{~K~}$ to obtain a ${\\mathrm{Si}}(111){\\mathrm{-B}}{\\mathrm{-}}{\\sqrt{3}}\\times{\\sqrt{3}}$ surface. Each boron atom on the Si(111) could be counted easily in the STM images, and so the boron flux could be determined precisely. \n\n![](images/2249f5e22f05f5d27ae98c596569947efe5f169c2e63d37fad3775999ed9e2f3.jpg) \nFigure 2 | Structure models of S1 and S2 phases of 2D boron sheets based on DFT calculations. a,b, Top and side views of the S1 model, which corresponds to the $\\upbeta_{12}$ sheet of 2D boron on a Ag(111) surface. c, Simulated STM topographic image of the $\\upbeta_{12}$ sheet. d,e, Top and side views of the S2 model, which corresponds to $\\mathtt{a}\\mathtt{\\backslash}\\mathtt{\\backslash}\\mathtt{\\backslash}\\mathtt{\\backslash}$ sheet of 2D boron on $\\mathsf{A g}(111)$ . f, Simulated STM topographic image of the $\\chi_{3}$ sheet. Orange and grey balls in a,b,d,e represent boron and silver atoms, respectively. The basic vectors of the super cell including the $\\mathsf{A g}(111)$ substrate are marked by yellow arrows. Models of the $\\upbeta_{12}$ and $\\chi_{3}$ sheets are superimposed on their simulated STM images, which agree very well with the experiments. The striped pattern of S1 and the alternating bright–dark protrusions of S2 are both reproduced well. \n\nThe total atomic density of boron grown on $\\mathrm{Ag}(111)$ was determined from the calibrated boron flux and the deposition time. By counting the area ratio of the S1 phase on $\\mathrm{Ag}(111)$ in the STM images, the atomic density of boron in phase S1 was obtained. We performed experiments on samples with different boron coverages, and the calibrated atomic density of boron in the S1 phase was found to be $33.6\\pm2.0\\mathrm{\\nm}^{-2};$ , identical to that calculated using the $\\upbeta_{12}$ sheet model $\\left(34.48\\ \\mathrm{nm}^{-2\\cdot}\\right.$ ), within a small range of error. The details of the above data and analysis are provided in Supplementary Section 4. On the other hand, when we annealed the S1 surface and turned it into the S2 phase, we did not observe a significant change in the total area of the islands, indicating that the boron densities in the two structures are approximately the same. This is consistent with the fact that the $\\chi_{3}$ sheet model has a similar boron density $(31.3\\ \\mathrm{nm}^{-2})$ as the $\\upbeta_{12}$ sheet. The above experimental facts confirm the validity of our structure models, and rule out the possibility of boron–silver alloying. \n\nBy increasing the boron coverage, the 2D boron sheets can extend in size until they spread to cover almost the entire surface (Supplementary Fig. 3). It should be noted that when the boron coverage is close to 1 ML, many three-dimenstional (3D) clusters form on the surface, which agrees with the observation in ref. 25. Because of this 3D cluster formation, it is difficult to obtain multilayer boron films. We suggest that this is because the silver– boron interface interaction is necessary to stabilize boron atoms in a 2D form. When the boron coverage exceeds $^{1\\mathrm{ML},}$ the interface interaction will saturate, resulting in spontaneous formation of 3D boron clusters. \n\nOne of the two 2D boron phases in our study, the S2 phase, was also reported in the parallel work by J. Mannix and colleagues25. They observed two distinct boron phases: a homogeneous one that corresponds to the S2 phase we describe here, and a more corrugated ‘striped’ one that forms at very high substrate temperature (1,000 K). The S1 phase we describe here was not observed, and conversely we did not observe the striped phase in our study. Instead, under high-temperature conditions we observed the growth of 3D boron clusters (Supplementary Fig. 1d). Therefore, at least three stable boron sheets have now been observed experimentally, which agrees with the large number of energetically close phases found in theoretical predictions. \n\nXPS study on 2D boron. The chemical bonding in our 2D boron sheets on Ag(111) was investigated by ex situ XPS. Figure 3a,b presents the XPS data for a typical sample of $0.7\\mathrm{ML}$ pure S1 phase. Figure 3a shows the boron 1s signal, as well as carbon 1s and O 1s peaks, which are due to air contamination during sample transfer under ambient conditions. Three peaks can be resolved in the boron 1s signal in Fig. 3b, 191.5, 188.2 and $187.1\\mathrm{eV},$ indicating that there are three types of boron atom with different chemical environments. As the binding energy of the boron 1s peak in bulk boron is ${\\sim}189{\\mathrm{-}}190~\\mathrm{eV}$ (ref. 27), the two low binding energy peaks (188.2 and $187.1\\ \\mathrm{eV}$ ), which are slightly redshifted compared with the bulk value, are most probably from B–B bonds in the pristine 2D boron sheets. On the other hand, the higher energy peak $(191.5\\mathrm{eV})$ implies oxidation of boron during exposure of the samples to air, in accordance with the oxidized boron peaks reported previously28. Note that as the boron sheet is metallic and the oxidized boron is insulating, we used asymmetric peaks to fit the two B–B peaks and a symmetric peak to fit the oxidized boron peak. Importantly, the measured area ratio of the B–O peak to $\\mathrm{B-B}$ peak is ${\\sim}0.23$ , indicating that most boron atoms remain intact. To further strengthen this point, we performed a STM experiment on the 2D boron sheets exposed to oxygen gas in different doses, and the results are shown in Supplementary Fig. 6. We found no sign of oxidation of the film at small $\\mathrm{O}_{2}$ dose. With high $\\mathrm{O}_{2}$ dose, bright spots occur at the edges of the boron sheets, but the terrace of boron remains almost intact. This experiment confirms that the boron sheets are oxidized from their edges, and the boron atoms inside the islands are quite inert to oxidation. This is why the ratio of oxidized to unoxidized boron atoms is small (0.23), even with long exposure to air. The two B–B peaks (188.2 and $187.1\\mathrm{eV},$ can be explained by the different distributions of the atomic charges in 2D boron. Interestingly, the boron atoms in our 2D boron sheets can be classified into two groups: those in the centre of the hexagonal boron rows are negatively charged, and those around the holes are positively charged (Supplementary Fig. 2). As such, the boron atoms in our 2D boron sheets have two different chemical environments, agreeing well with the two B–B peaks observed in XPS measurements. \n\n![](images/6fee6449582a8ac99243741196657d49e77f346670046f07754f82028d45b765.jpg) \nFigure 3 | XPS results for 2D boron sheets on Ag(111) after exposure to air. a,b, Full-scale survey (a) and boron 1s spectrum (b) of boron sheets on $\\mathsf{A g}(111)$ (the S1 phase) with boron coverage of ${\\sim}0.7$ ML. c, Boron 1s spectrum of boron sheets on $\\mathsf{A g}(111)$ with boron coverage of $1.0\\mathsf{M L}$ . Three peaks can be resolved. The peak at higher binding energy corresponds to the B–O peak, and the two peaks at lower binding energy are B–B peaks. These peaks were fitted using asymmetric and symmetric Gaussian–Lorentzian functions for the B–B and B–O peaks, respectively. The Lorentzian component was fixed at $10\\%$ for all fits. A Shirley background was subtracted before peak fitting. Grey, red and blue curves correspond to original data, fitting lines and sum of fitting lines, respectively. It is evident that most boron atoms remain unoxidized in b (low coverage sample), and the number of oxidized boron atoms increases notably in c (high coverage sample). \n\n
Table1 | Formation energies for free-standing and epitaxial S1 and S2 boron sheets.
S1S2
EFB (eV per atom)6.23 6.19
EEB (eV per atom)6.32 6.35
E (eV per atom) 0.090.16
E(eV A-2)0.03 0.05
\n\n$E_{\\mathsf{F B}}$ is the formation energy per atom for the free-standing boron sheet. $E_{\\tt E B}$ is the formation energy per boron atom for the epitaxial boron sheet. $\\Delta E_{1}$ is the adhesion energy of the boron sheet per boron atom. $\\Delta\\bar{E}_{2}$ is the adhesion energy of the boron sheet per unit area. \n\nOn the other hand, the XPS data of another sample with a boron coverage of ${\\sim}1\\mathrm{ML}$ also shows three boron 1s peaks (Fig. 3c), but the area ratio of the B–O peak to the B–B peak increases to ${\\sim}0.46$ . As the major difference between the low-coverage and high-coverage samples is the appearance of 3D boron clusters at high coverage (Supplementary Fig. 3c), we suggest that the increased B–O peak mainly comes from the oxidation of 3D boron clusters. Combined with STM experiments on the oxidization of our 2D boron sheets (Supplementary Fig. 6), we suggest that the 2D boron sheet is more inert to oxidation than the 3D boron clusters. This chemical stability of 2D boron sheets is promising for future device applications. \n\nFormation mechanism. Previously, a large number of 2D boron sheet structures have been predicted theoretically, with competitive formation energies. However, among these models, neither $\\upbeta_{12}$ nor $\\chi_{3}$ corresponds to the global energy minimum20. To understand why we observe these two structures, we calculated the formation energies of the S1 and S2 structures, as shown in Table 1. The formation energy of freestanding S1 is $0.04\\mathrm{eV}$ higher than that of S2, indicating a higher stability of isolated S1 over S2. Nevertheless, the adhesion energy of S2 ( $_{0.16\\mathrm{eV}}$ per atom) on $\\mathrm{Ag}(111)$ is larger than that of S1 $(0.09\\mathrm{eV}$ per atom). Thus, the total formation energy for S1 ( $6.32\\:\\mathrm{eV}$ per atom) is actually slightly smaller than that of S2 ( $6.35\\:\\mathrm{eV}$ per atom). This means that S2 is thermodynamically more stable when it adsorbs on Ag(111), which agrees with the higher thermal stability of the S2 phase in our experiment. Our calculation agrees with the independent theoretical work by Zhang and colleagues, which predicted that the $\\upbeta_{12}$ structure is stable for boron on $\\mathrm{Ag}(111)^{26}$ . In addition, in a direct comparison, a recent theoretical work29 has suggested that our two structures are more stable than the distorted triangular structure proposed in ref. 25. The ‘striped phase’ reported in ref. 25 is thermodynamically less stable, and may thus require specific conditions to form. For example, careful control of the boron flux was found to be critical for the formation of this phase25, which may explain why we did not observe it in our study. \n\nThe boron–silver interaction should play an important role in the formation of 2D boron on the $\\mathrm{Ag}(111)$ substrate, resulting in optimal structures not necessarily corresponding to a global energy minimum in vacuum. Furthermore, the perfect commensuration of the lattice parameters of the $\\beta_{12}$ and $\\chi_{3}$ sheets with that of $\\mathrm{Ag}(111)$ can efficiently lower the strain, favouring their formation on Ag(111). Finally, 2D boron structures with hexagonal holes in the triangular lattice can be described by the hole density $\\eta,$ which is defined as the ratio of hexagonal holes to boron atoms in the original triangular lattice. The $\\upbeta_{12}$ and $\\chi_{3}$ sheets have very close hole densities (1/6 and $1/5)^{20}$ which explains the easy transition between the two structures on annealing. \n\nThe fact that both the $\\upbeta_{12}$ sheet and the $\\chi_{3}$ sheet maintain their isolated planar structures after adsorption on $\\mathrm{Ag}(111)$ implies that the interactions between the boron sheets and the $\\mathrm{Ag}(111)$ surface are not strong, in agreement with previous theoretical results24. Indeed, the calculated adhesion energy between the S1 phase and $\\mathrm{Ag}(111)$ is $0.03\\mathrm{eV}\\mathring{\\mathrm{A}}^{-2};$ , on the same order as the binding energy of graphite $(0.019\\mathrm{~eV}\\mathring{\\mathrm{A}}^{-2})^{30}$ and monolayer graphene on $\\mathrm{Cu}(111)$ $(0.\\dot{0}2\\dot{2}\\mathrm{eV}\\mathring{\\mathrm{A}}^{-2})^{31}$ . This implies that the S1 boron sheet could be separated from the substrate, in a manner analogous to graphene, and as also suggested by previous work24. The slightly larger adhesive energy $(\\sim0.05\\mathrm{eV}\\mathring\\mathrm{A}^{-2})$ for the S2 phase on $\\mathrm{Ag}(111)$ indicates that S2 is more strongly bonded to the substrate, but still not difficult to detach. According to our first-principles calculations, the weak interfacial interaction is also reflected by the large distance between the boron sheets and the substrate $({\\sim}2.4\\mathrm{\\AA})$ , as well as by the very tiny charge transfer from $\\mathrm{Ag}(111)$ to the boron sheet $(\\sim0.03$ electrons per boron atom). Combined with the XPS and STM results, which indicate that the boron sheets are hard to oxidize, it may be possible to obtain freestanding 2D boron sheets, and construct the devices based on 2D boron in the future. \n\nThe calculated band structures of the two types of boron sheet are presented in Supplementary Fig. 7. Both boron structures are metallic, in accordance with the band structures determined in previous calculations19,20 and our density functional theory (DFT) results on freestanding 2D boron (Supplementary Fig. 8). Scanning tunnelling spectroscopy (STS) of the 2D boron surface (Supplementary Fig. 9b) shows a prominent peak at $-2.5\\mathrm{V}$ (the STS results of phases S1 and S2 are similar). The local density of states (LDOS) at a bias ranging from $-2\\mathrm{V}$ to $+2\\mathrm{V}$ is relatively low, but the spectrum at a lower range of bias voltage (Supplementary Fig. 9c) shows a significant density of states (DOS) around the Fermi level, which proves that the 2D boron sheets are metallic. We also calculated the projected density of states (PDOS) of 2D boron (Supplementary Fig. 10), which gave a high $\\boldsymbol{p}$ -band peak at $-2.0\\mathrm{eV}$ $(-2.5\\mathrm{eV})$ for the S1 (S2) phase and a DOS distribution around the Fermi level, in good agreement with the experimental STS results. \n\nAlthough the boron–silver interaction was found to be weak in our 2D boron sheets, intensive edge electronic states are indicated by the brighter edges of 2D boron islands observed in the STM images (Fig. 1a,d). STS on the edges (Supplementary Fig. ${9}\\mathrm{b},\\mathrm{c}{\\mathrm{)}}$ show additional shoulders around $-3.0$ and $-0.2\\mathrm{eV}$ , and the $\\mathrm{d}I/\\mathrm{d}V$ maps at $-3.2$ and $-0.2\\mathrm{eV}$ (Supplementary Fig. 9e,g) show most prominent bright edges, indicating the existence of edge states. Our first-principles calculations on boron nanoribbons (for details see Supplementary Section 10) indicate that the boron sheets are bonded to the $\\mathrm{Ag}(111)$ substrate predominately through their edges, where the electron density is much higher than in the inner part of the boron sheet. Such edge interactions, as well as the resulting edge state, may play important roles in the future electronic applications of 2D boron nanoribbons. \n\n# Conclusions \n\nOur experiments and first-principles calculations have confirmed the formation of two types of 2D boron structure on $\\mathrm{Ag}(111)$ : $\\upbeta_{12}$ sheet (independently predicted theoretically during the submission of our manuscript)26 and $\\chi_{3}$ sheet. The boron sheets are quite inert to oxidation, and interact only weakly with the $\\mathrm{Ag}(111)$ substrate. Our results pave the way to exploring boron-based microelectronic device applications. As well as $\\mathrm{Ag}(111)$ , other substrates, such as Au(111), $\\mathrm{Cu}(111)$ and metal borides23,24, might also be good platforms for the synthesis of monolayer boron sheets. Substrates with different interactions with boron may produce 2D boron sheets with different structures. The novel physical or chemical properties of boron sheets, such as massless Dirac fermions22 and novel reconstruction geometries32, may be realized in 2D boron sheets with special structures, and remain to be investigated in the future. \n\n# Methods \n\nExperiments. The experiments were performed in a UHV chamber combining a MBE system and a low-temperature (4.5 K) STM with a base pressure of $2\\times{10}^{-11}$ torr. The samples were grown in the MBE chamber. Single-crystal $\\mathrm{Ag}(111)$ was cleaned by repeated argon ion sputtering and annealing cycles. Pure boron $(99.9999\\%$ ) was evaporated from an electron-beam evaporator onto the clean $\\mathrm{Ag}(111)$ substrate while keeping the substrate at appropriate temperatures. The pressure during boron growth was better than $6\\times\\bar{10}^{-1\\bar{1}}$ torr. After growth, the sample was transferred to the STM chamber without breaking the vacuum. All the STM images and STS spectra were taken at $78\\mathrm{K},$ and the bias voltages were defined as the tip bias with respect to the sample. The XPS experiments were performed ex situ by taking the as-prepared sample out into air, and transferring it into the XPS system (ThermoFisher Scientific ESCALAB 250X with a monochromatic Al $\\mathrm{K}_{\\mathrm{a}}$ X-ray source, $h\\nu=1,486.6\\ensuremath{\\mathrm{~eV}})$ . The XPS instrumental resolution was $0.48\\mathrm{eV}$ (determined from the Ag $3d_{5/2}$ peak). The binding energy and Fermi level were calibrated by measurements on pure Au, Ag and Cu surfaces. The software used for XPS data fitting was XPSPEAK. The XPS peaks were fitted with a mixture of Gaussian and Lorentzian functions. The ratio of Lorentzian and Gaussian components was fixed to the same value, and other parameters such as peak height and full-width at half-maximum were allowed to change. We tested different Lorentzian/Gaussian ratios, and the current one $10\\%$ Lorentzian) gave the best fitting. \n\nCalculations. DFT calculations were performed using a projector-augmented wave (PAW) pseudopotential in conjunction with the Perdew–Burke–Ernzerhof (PBE)33 function and plane-wave basis set with energy cutoff at $400~\\mathrm{eV}.$ . For the S1 phase, the calculation cell contained a boron film on a five-layer $3\\sqrt{3}\\times5\\mathrm{-Ag(111)}$ surface. The surface Brillouin zone was sampled by a $3\\times3\\times1$ Monkhorst–Pack $k$ -mesh. For the S2 phase, the boron film was positioned on five-layer $3\\times3{\\mathrm{-Ag}}(111)$ surface. The Brillouin zone was sampled by a $5\\times5\\times1$ Monkhorst–Pack $k$ -mesh. As the PBE function usually overestimates the chemical bond length, the lattice constant of $\\mathrm{Ag}(111)$ used in the calculations was $3\\%$ larger than the experimental value, and a vacuum region of ${\\sim}15\\mathrm{\\AA}$ was applied. All structures were fully relaxed until the force on each atom was less than $0.{\\dot{0}}{\\dot{5}}{\\mathrm{eV}}{\\mathring{\\mathrm{A}}}^{-1}$ , and the bottom two layers of silver atoms were fixed. The simulated STM images were obtained using the constant current mode based on calculated electron densities. All calculations were performed with the Vienna Ab initio Simulation Package $(\\mathrm{VASP})^{34}$ . \n\n# Received 17 July 2015; accepted 2 March 2016; published online 28 March 2016 \n\n# References \n\n1. Woods, W. G. An introduction to boron: history, sources, uses, and chemistry. Environ. Health Perspect 102, 5–11 (1994). \n2. Albert, B. & Hillebrecht, H. Boron: elementary challenge for experimenters and theoreticians. Angew. Chem. Int. Ed. 48, 8640–8668 (2009). \n3. Ogitsu, T., Schwegler, E. & Galli, G. $\\upbeta$ -Rhombohedral boron: at the crossroads of the chemistry of boron and the physics of frustration. Chem. Rev. 113, 3425–3449 (2013). \n4. Fowler, J. E. & Ugalda, J. M. The curiously stable ${{\\mathrm{B_{13}}}^{+}}$ cluster and its neutral and anionic counterparts: the advantages of planarity. J. Phys. Chem. A 104, 397–403 (2000). \n5. Zhai, H.-J., Kiran, B., Li, J. & Wang, L.-S. Hydrocarbon analogues of boron clusters—planarity, aromaticity and antiaromaticity. Nature Mater. 2, 827–833 (2003). \n6. Aihara, J.-I. ${\\mathrm{B_{13}}}^{+}$ is highly aromatic. J. Phys. Chem. A 105, 5486–5489 (2001). \n7. Huang, W. et al. A concentric planar doubly $\\pi\\cdot$ -aromatic ${\\mathrm{B_{19}}}^{-}$ cluster. Nature Chem. 2, 202–206 (2010). \n8. Popov, I. A. et al. A combined photoelectron spectroscopy and ab initio study of the quasi-planar $\\mathrm{B}_{24}^{-}$ cluster. J. Chem. Phys. 139, 144307 (2013). \n9. Sergeeva, A. P. et al. Understanding boron through size-selected clusters: structure, chemical bonding, and fluxionality. Acc. Chem. Res. 47, 1349–1358 (2014). \n10. Piazza, Z. A. et al. Planar hexagonal $\\mathrm{B}_{36}$ as a potential basis for extended singleatom layer boron sheets. Nature Commun. 5, 3313 (2013). \n11. Castro Neto, A. H., Guinea, F., Peres, N. M. R., Novoselov, K. S. & Geim, A. K. The electronic properties of graphene. Rev. Mod. Phys. 81, 109–162 (2009). \n12. Geim, A. K. & Novoselov, K. S. The rise of graphene. Nature Mater. 6, 183–191 (2007). \n13. Wang, X. J. et al. Single crystalline boron nanocones: electric transport and field emission properties. Adv. Mater. 19, 4480–4485 (2007). \n14. Liu, F. et al. Metal-like single crystalline boron nanotubes: synthesis and in situ study on electric transport and field emission properties. J. Mater. Chem. 20, 2197–2205 (2010). \n15. Zhai, H.-J. et al. Observation of an all-boron fullerene. Nature Chem. 6, 727–731 (2014). \n16. Tang, H. & Ismail-Beigi, S. Novel precursors for boron nanotubes: the competition of two-center and three-center bonding in boron sheets. Phys. Rev. Lett. 99, 115501 (2007). \n17. Tang, H. & Ismail-Beigi, S. Self-doping in boron sheets from first principles: a route to structural design of metal boride nanostructures. Phys. Rev. B 80, 134113 (2009). \n18. Penev, E. S., Bhowmick, S., Sadrzadeh, A. & Yakobson, B. I. Polymorphism of two-dimensional boron. Nano Lett. 12, 2441–2445 (2012). \n19. Ozdogan, C. et al. The unusually stable $\\mathrm{\\DeltaB_{100}}$ fullerene, structural transitions in boron nanostructures, and a comparative study of $a-$ and $\\gamma$ -boron and sheets. J. Phys. Chem. C. 114, 4362–4375 (2010). \n20. Wu, X. et al. Two-dimensional boron monolayer sheets. ACS Nano 6, 7443–7453 (2012). \n21. Nagamatsu, J., Nakagawa, N., Muranaka, T., Zenitani, Y. & Akimitsu, J. Superconductivity at $39\\mathrm{~K~}$ in magnesium diboride. Nature 410, 63–64 (2001). \n22. Zhou, X.-F. et al. Semimetallic two-dimensional boron allotrope with massless Dirac fermions. Phys. Rev. Lett. 112, 085502 (2014). \n23. Liu, H., Gao, J. & Zhao, J. From boron cluster to two-dimensional boron sheet on $\\mathrm{Cu}(111)$ surface: growth mechanism and hole formation. Sci. Rep. 3, 3238 (2013). \n24. Liu, Y., Penev, E. S. & Yakobson, B. I. Probing the synthesis of two-dimensional boron by first-principles computations. Angew. Chem. Int. Ed. 52, 3156–3159 (2013). \n25. Mannix, A. J. et al. Synthesis of borophenes: anisotropic, two-dimensional boron polymorphs. Science 350, 1513–1516 (2015). \n26. Zhang, Z., Yao, Y., Gao, G. & Yakobson, B. I. Two-dimensional boron monolayers mediated by metal substrates. Angew. Chem. Int. Ed. 54, 13022–13026 (2015). \n27. Moudler, J. F., Stickle, W. F., Sobol, P. E. & Bomben, K. D. Handbook of X-ray Photoelectron Spectroscopy (Perkin-Elmer, 1992). \n28. Ong, C. W. et al. X-ray photoemission spectroscopy of nonmetallic materials: electronic structures of boron and $\\mathrm{B}_{x}\\mathrm{O}_{y}.$ J. Appl. Phys. 95, 3527–3534 (2004). \n29. Xu, S. G., Zhao, Y. J., Liao, J. H. & Yang, X. B. The formation of boron sheet at the Ag(111) surface: From clusters, ribbons, to monolayers. Preprint at http://arxiv.org/abs/1601.01393 (2016). \n30. Liu, Z. et al. Interlayer binding energy of graphite: a mesoscopic determination from deformation. Phys. Rev. B 85, 205418 (2012). \n31. Olsen, T., Yan, J., Mortensen, J. J. & Thygesen, K. S. Dispersive and covalent interactions between graphene and metal surfaces from the random phase approximation. Phys. Rev. Lett. 107, 156401 (2011). \n32. Amsler, M., Botti, S., Marques, M. A. L. & Goedecker, S. Conducting boron sheets formed by the reconstruction of the α-boron (111) surface. Phys. Rev. Lett. 111, 136101 (2013). \n33. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n34. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11185 (1996). \n\n# Acknowledgements \n\nThe authors thank Qinlin Guo for useful discussions regarding XPS data analysis. This work was supported by the MOST of China (grant numbers 2012CB921703, 2013CB921702 and 2013CBA01600), the NSF of China (grant numbers 11334011, 11322431, 11174344 and 91121003), and the Strategic Priority Research Program of the Chinese Academy of Sciences (grant number XDB07020100). \n\n# Author contributions \n\nK.W. and L.C. designed the experiments. B.F., L.C., Q.Z., W.L. and S.L. performed experiments and data analysis (under the supervision of K.W.). J.Z., H.L. and S.M. performed the DFT calculations. B.F., L.C. and K.W. wrote the manuscript, with contributions from all authors. All authors contributed to data analyses and discussions. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to H.L., L.C. and K.W. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. " + }, + { + "id": "10.1080_08927022.2015.1010082", + "DOI": "10.1080/08927022.2015.1010082", + "DOI Link": "http://dx.doi.org/10.1080/08927022.2015.1010082", + "Relative Dir Path": "mds/10.1080_08927022.2015.1010082", + "Article Title": "RASPA: molecular simulation software for adsorption and diffusion in flexible nulloporous materials", + "Authors": "Dubbeldam, D; Calero, S; Ellis, DE; Snurr, RQ", + "Source Title": "MOLECULAR SIMULATION", + "Abstract": "A new software package, RASPA, for simulating adsorption and diffusion of molecules in flexible nulloporous materials is presented. The code implements the latest state-of-the-art algorithms for molecular dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker's minimisation. We show example applications of RASPA in computing coexistence properties, adsorption isotherms for single and multiple components, self- and collective diffusivities, reaction systems and visualisation. The software is released under the GNU General Public License.", + "Times Cited, WoS Core": 1435, + "Times Cited, All Databases": 1532, + "Publication Year": 2016, + "Research Areas": "Chemistry; Physics", + "UT (Unique WOS ID)": "WOS:000362190200001", + "Markdown": "This article was downloaded by: [University of Nebraska, Lincoln] \nOn: 14 April 2015, At: 03:10 \nPublisher: Taylor & Francis \nInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, \n37-41 Mortimer Street, London W1T 3JH, UK \n\n# Molecular Simulation \n\nPublication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gmos20 \n\n# RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials \n\nDavid Dubbeldama, Sofía Calerob, Donald E. Ellisc & Randall Q. Snurrd \na Van 't Hoff Institute of Molecular Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands \nb Department of Physical, Chemical and Natural Systems, University Pablo de Olavide, Sevilla 41013, Spain \nc Department of Physics and Astronomy, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA \nd Department of Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA \nPublished online: 26 Feb 2015. \n\nTo cite this article: David Dubbeldam, Sofía Calero, Donald E. Ellis & Randall Q. Snurr (2015): RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials, Molecular Simulation, DOI: 10.1080/08927022.2015.1010082 \n\nTo link to this article: http://dx.doi.org/10.1080/08927022.2015.1010082 \n\nPLEASE SCROLL DOWN FOR ARTICLE \n\nTaylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Versions of published Taylor & Francis and Routledge Open articles and Taylor & Francis and Routledge Open Select articles posted to institutional or subject repositories or any other third-party website are without warranty from Taylor & Francis of any kind, either expressed or implied, including, but not limited to, warranties of merchantability, fitness for a particular purpose, or non-infringement. Any opinions and views expressed in this article are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor & Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. \n\nThis article may be used for research, teaching, and private study purposes. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions \n\nIt is essential that you check the license status of any given Open and Open Select article to confirm conditions of access and use. \n\n# RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials \n\nDavid Dubbeldama\\*, Sofı´a Calerob1, Donald E. Ellisc2 and Randall Q. Snurrd3 aVan ’t Hoff Institute of Molecular Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands; bDepartment of Physical, Chemical and Natural Systems, University Pablo de Olavide, Sevilla 41013, Spain; cDepartment of Physics and Astronomy, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA; dDepartment of Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA \n\n(Received 7 October 2014; final version received 16 January 2015) \n\nA new software package, RASPA, for simulating adsorption and diffusion of molecules in flexible nanoporous materials is presented. The code implements the latest state-of-the-art algorithms for molecular dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker’s minimisation. We show example applications of RASPA in computing coexistence properties, adsorption isotherms for single and multiple components, self- and collective diffusivities, reaction systems and visualisation. The software is released under the GNU General Public License. \n\nKeywords: molecular simulation; Monte Carlo; molecular dynamics; adsorption; diffusion; software \n\n# 1. Introduction \n\nMolecular sieves are selective, high-capacity adsorbents because of their high intracrystalline surface areas and strong interactions with adsorbates. Molecules of different size generally have different diffusion properties in a given molecular sieve, and molecules can be separated on the basis of their size and structure relative to the size and geometry of the apertures of the sieve. Much progress has been made in understanding the subtle interaction between molecules and the confinement, and much of this understanding comes from computer simulations that are able to analyse the chemistry and physics at the atomistic level. \n\nThe two main computational approaches to tackle these systems are (i) quantum mechanical calculations and (ii) force field-based simulations. The first approach is required for studying properties such as bond breakage and formation and is available in many excellent commercial and non-commercial packages. The second approach is useful for studying larger systems and for calculating a wide variety of thermodynamic and dynamic properties. Force field-based approaches include Monte Carlo (MC) simulations, molecular dynamics (MD) simulations and energy minimisations. We introduce here a code, RASPA, that focuses on MC, MD and minimisation of systems described by classical force fields. \n\nThe RASPA code was written as a collaboration among Northwestern University (USA), the University of Amsterdam (The Netherlands) and the University Pablo de Olavide (Spain), with recent contributions also from the University of Delft (The Netherlands). The code evolved initially from the post-doc project (2006–2009) of David Dubbeldam at Northwestern University, where the Snurr group had another MUltipurpose SImulation Code (MUSIC), which was written in object-oriented Fortran 90.[1,2] MUSIC provides functionality for performing MD and MC simulations in a number of different ensembles, minimisations and free energy calculations for bulk and adsorbed phases using a variety of force fields, but not for treating flexible adsorbent frameworks and hence RASPA was developed. Version 1.0 of this code has been used internally by the authors and a growing list of collaborators. In this paper, we present version 2.0 available for public use. Its main areas of utility are thermodynamic properties of liquids and gases, and adsorption/diffusion behaviour of adsorbates in crystalline nanoporous materials. \n\nExamples of nanoporous materials are clays, carbon nanotubes, zeolites and metal-organic frameworks (MOFs). MOFs are a relatively new class of materials composed of metal nodes connected by organic linkers. MOFs possess almost unlimited structural variety because of the many combinations of building blocks that can be imagined. The building blocks self-assemble during synthesis into crystalline materials that, after evacuation of the structure, may find applications in adsorption separations, gas storage and catalysis.[3–5] MOFs have crystal structures that exhibit unusual flexibility. An extreme example is the ‘breathing MOF’ MIL-53 that expands or shrinks to admit guest molecules such as $\\mathrm{CO}_{2}$ and water.[6] For simulation of zeolites, it is common practice to keep the positions of the framework atoms fixed, but this assumption is not valid for many large-pore MOFs. New algorithms and a new code were developed to handle these systems. \n\nRASPA is a serial code. A single point of an isotherm can be obtained within hours for a simple system and in days for more complicated systems. MC codes are ideally suited for task-farm parallelism. Here, simulations are independent and are run as batches of serial simulations that differ in temperature, pressure, etc. For example, (assuming no hysteresis), each point of an isotherm can be run independently. Memory requirements of MC codes are modest. \n\nPrograms can be written in various ways, but often it is true that the fastest codes are probably the hardest to read, while programs strictly based on readability lack efficiency. RASPA (being a ‘research’ code) chooses the middle-ground and is based on the following ideas: \n\nCorrectness and accuracy. For all techniques and algorithms available in RASPA, we have implemented the ‘best’ ones (in our opinion) available in the literature. For example, RASPA uses configurational-bias Monte-Carlo (CBMC) and continuous fractional component Monte Carlo (CFCMC); it uses the Ewald summation for electrostatics; MD is based on symplectic and measure-preserving integrators. . Functional design. Examining the source code, one can notice that there are not a large number of files. The program is split up according to its function: ‘grid.c’ contains the code to make and use an energy/ force grid of a framework, ‘ewald.c’ handles all the electrostatic calculations, ‘mc_moves.c’ contains all the moves to be used in MC, ‘potentials.c’ contains all the van der Waals potentials, etc. Input made easy. The requirements for the input files are kept as minimal as possible. Only for more advanced options are extra commands in the input file needed. Also the format of the input is straightforward. Fugacity coefficients and excess adsorption are automatically computed. Integrated simulation environment. The code is built up of many functions and routines which can be easily combined. MD can be used in MC and vice versa. Extension and modification of the code is relatively straightforward. \n\nThis article provides an overview of the application areas of the code. For a detailed description of the algorithms themselves and the inner working of MC and MD codes, we refer to Refs.[7,8] \n\n# 2. Units, input and conventions \n\nA small set of internal units needs to be chosen. A convenient set, which is chosen in DLPOLY [9], RASPA, and many other codes, is the following: \n\n(1) The unit of length $l_{0}$ is chosen as the A˚ ngstrom, i.e. $l_{0}=10^{-10}\\mathrm{m}$ \n(2) The unit of time $t_{0}$ is chosen as the picosecond, i.e. $t_{0}=10^{-12}$ s \n(3) The unit of mass $m_{0}$ is chosen as the atomic mass unit, i.e. $m_{0}=1.660540210^{-27}{\\mathrm{kg}}$ \n(4) The unit of charge $q_{0}$ is chosen as the unit of proton charge, i.e. $m_{0}=1.6021773310^{-19}\\mathrm{C}$ . \n\nAll other units follow from this choice. For example, one Pascal $[\\mathrm{Pa}=\\mathrm{mass}/(\\mathrm{length}\\times\\mathrm{time}^{2})]$ is $1.66054\\times10^{7}$ in internal units. A pressure input of $10\\mathrm{Pa}$ in the input file is converted to ‘internal units’ by dividing by $1.66054\\times10^{7}$ . Similarly, at output the pressure in internal units is converted to Pa by multiplying by $1.66054\\times10^{7}$ . \n\nRASPA used three generic ‘types’ or ‘groups’ for the particles: (1) ‘framework atoms’, (2) ‘adsorbates’ and (3) ‘cations’. (The classification was done with respect to porous materials, for pure fluids the meaning of ‘adsorbates’ reduces to ‘molecules’.) The advantage is that the different components of the total energy are available and the interactions can be examined (also the energies in the Ewald Fourier part are split [10]). Cations are considered as part of the framework (they are included in the total mass of the framework). Another example is when using thermostats, e.g. in LTA5A, a different thermostat can operate on the framework atoms, the adsorbates and the cations (these all vibrate/move at different length- and time scales). There are no restrictions on the number of molecules or the number of components. This allows for example an adsorption simulation of a mixture of $\\mathrm{CO}_{2}$ and $\\Nu_{2}$ in LTA5A with Na and Ca ions. In this example, there are four components: two adsorbate components, $\\mathrm{CO}_{2}$ and $\\Nu_{2}$ , and two cation components, Na and Ca. For each component the MC move types and relative attempt frequency can be specified. In this case, $\\mathrm{CO}_{2}$ and ${\\bf N}_{2}$ can undergo particle insertion and deletion moves, while Na and Ca only use translation (the cations can be simulated as mobile). A typical input for such a simulation at 298 K, 1 bar (1:3 mixture of $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ ) looks like: \n\nSimulationType MonteCarlo NumberOfCycles 250000 NumberOfInitialisationCycles 100000 PrintEvery 1000 \n\nForcefield GenericZeolites ModifyOxgensConnectedToAluminium yes \n\nFramework 0 \nFrameworkName LTA5A \nRemoveAtomNumberCodeFromLabel yes \nUnitCells 1 1 1 \nExternalTemperature 298.0 \nExternalPressure 10000.0 \n\nComponent 0 MoleculeName sodium MoleculeDefinition Cations TranslationProbability 1.0 RandomTranslationProbability 1.0 ExtraFrameworkMolecule yes CreateNumberOfMolecules 32 \n\nComponent 1 MoleculeName calcium MoleculeDefinition Cations TranslationProbability 1.0 RandomTranslationProbability 1.0 ExtraFrameworkMolecule yes CreateNumberOfMolecules 32 \n\nComponent 2 MoleculeName CO2 MoleculeDefinition TraPPE MolFraction 0.25 BlockPockets yes BlockPocketsFilename LTA TranslationProbability 1.0 RotationProbability 1.0 ReinsertionProbability 1.0 SwapProbability 2.0 ExtraFrameworkMolecule no CreateNumberOfMolecules 0 \n\nComponent 3 MoleculeName N2 MoleculeDefinition TraPPE MolFraction 0.75 BlockPockets yes BlockPocketsFilename LTA TranslationProbability 1.0 RotationProbability 1.0 ReinsertionProbability 1.0 SwapProbability 2.0 ExtraFrameworkMolecule no CreateNumberOfMolecules 0 \n\nNumbering of frameworks, components, etc., is based on the C-convention, i.e. starting from zero. The ‘SimulationType’ line sets the simulation type (e.g. MC, MD, transition state theory (TST), minimisation). RASPA ‘cycles’ for MD is the number of integration steps. For MC a cycle is $\\operatorname*{max}(20,\\ N)$ -move-attempts with $N$ being the number of molecules. In one cycle each molecule experiences on average one MC move attempt (either accepted or rejected). More molecules require more MC moves and the use of a ‘cycle’ allows for a specification of the simulation length that is relatively insensitive to the number of molecules. Once a line like ‘Framework $0^{\\circ}$ has been read, the lines below it refer to that framework until another line like ‘Framework $\\mathbf{\\Omega}_{1}\\mathbf{\\cdot}\\mathbf{\\Omega}$ is encountered (it is possible to define multiple frameworks per system). Similarly, the MC-move probabilities are set for a specific component (set with the ‘Component [number] MoleculeName [string]’ line). For each component you can specify mole fraction, fugacity coefficient, MC moves, whether the component is an adsorbate or a cation, the initial number of molecules, etc. The MC-move probabilities are appropriately normalised by the code and therefore only have to be given relative to each other. In this example, twice the number of ‘swap’-moves (i.e. insertion/deletion) will be used compared to translation, rotation and reinsertion. If no fugacity coefficients are given in the input, then the Peng–Robinson equation of state will be used to convert pressure to fugacity. Therefore, if a fugacity coefficient of unity is specified, then adsorption will be computed as a function of fugacity instead of pressure. Any specified initial number of molecules will be created at start up using the CBMC algorithm. This avoids the need to create the initial positions by hand. \n\nIn addition to this input file, force-field files need to be created. If one uses a generic force field, then a simple ‘Forcefield GenericZeolites’ is sufficient. If one creates force field files in the current directory, then these files are read instead of the generic files. This is convenient for force field fitting where one needs to change the parameters frequently. The first two force field files are ‘force_field_ mixing_rules.def’ and ‘force_field.def’. The first is read to construct an initial force field based on the parameters for each atom-type and using mixing rules. The second file allows you to overwrite an interaction pair directly. Both ways of specifying a force field occur in the zeolite and MOF literature. A third file making up the force field is ‘pseudo_atoms.def’ which defines atom properties such as the name, atomic weight, charge and so on. \n\nNext, for each component a definition must be provided. Many molecules have been already been created for general use and for these one can simply specify, e.g. ‘MoleculeDefinition TraPPE’. The atom names from this file are also those used in the files for defining the molecules. These list all the bond, bend and torsion interactions. For defining a flexible framework, the bond, bend and torsions are specified by type and an algorithm searches automatically for all occurrences of these. Details and examples are given in the manual accompanying the source code. \n\n# 3. Vapour–liquid coexistence \n\nRASPA was initially developed to simulate porous materials. However, it can also be used to model vapour– liquid equilibrium (VLE) as illustrated in this section. \n\n# 3.1 Coexistence properties \n\nThe enthalpy of vapourisation $\\Delta H_{\\mathrm{vap}}$ (or heat of vapourisation) is the enthalpy change required to transform a given quantity of a substance from a liquid into a gas at a given pressure. The enthalpy of vapourisation is given without approximation by \n\n$$\n\\begin{array}{r}{\\Delta H_{\\mathrm{vap}}=U(\\mathrm{gas})-U(\\mathrm{liquid})+p[V(\\mathrm{gas})}\\\\ {-V(\\mathrm{liquid})],\\qquad}\\end{array}\n$$ \n\nwhere $U$ is the internal energy per molecule, $p$ is the pressure and $V$ is the volume per molecule. $\\Delta H_{\\mathrm{vap}}$ can be conveniently computed in the canonical Gibbs ensemble. In the canonical Gibbs ensemble, the two fluid phases (i.e. vapour and liquid) are explicitly simulated in two separate simulation boxes. Martin and Biddy noted that, for properties such as enthalpy of vapourisation that involve the pressure, it is preferable to calculate the pressure from the vapour phase.[15] The observed error bars on liquid box pressures are quite large in a molecular simulation and an equilibrated Gibbs ensemble simulation has the same pressure in both boxes. The Gibbs ensemble method, which is implemented in RASPA, is ideally suited to compute properties such as the vapour pressure, gas and liquid densities, compressibility, heat of vapourisation, second virial coefficients, boiling and critical points. \n\n# 3.2 NVT Gibbs ensemble for vapour–liquid equilibrium \n\nThe Gibbs ensemble MC simulation technique allows direct simulation of phase equilibria in fluids.[16,17] NVT (also called ‘canonical’) Gibbs ensemble simulations are performed in two separate microscopic regions, each with periodic boundary conditions. The temperature $T$ is held constant, as a well as the total volume $V$ and the total number of particles $N.$ The equilibrium conditions are (i) equal temperature, (ii) equal pressure and (iii) equal chemical potential for each species in the two boxes. The equal temperature in both boxes is imposed via the MC scheme for configurational equilibration (MC moves like translation and rotation). Condition (ii) is enforced by a volume move, and condition (iii) by a particle transfer move. The volume move makes one box larger and the other box smaller, which leads to pressure equilibration. The transfer of particles between the boxes leads to equal chemical potential. \n\nVan der Waals parameters are very difficult to obtain from experiment or from ab initio calculations. However, the VLE curves are very sensitive to, e.g. the strength parameter 1 and size parameter $\\sigma$ of the Lennard-Jones potentials. Martin and Siepmann developed the transferable potentials for phase equilibria (TraPPE) force field for a large variety of molecules. It includes (and historically started with) united-atom linear and branched alkanes. [12,13] Figure 1 shows simulation data calibrated to experimentally available VLE data. The simulation results of RASPA agree very well with the simulation data of Martin and Siepmann. By fitting sequentially to methane $\\mathrm{(CH_{4})}$ , ethane $\\left(\\mathrm{CH}_{3}\\right)$ , propane $\\left(\\mathrm{CH}_{2}\\right)$ , isobutane (CH) and neopentane (C), the five atom types in the model can be uniquely fitted. Other data for alkanes can then be used to validate the force field. These types of simulations are also useful for re-optimising force fields for a different cut-off or change from tail-correction to a shifted potential type. [18,19] The chief advantage of VLE-fitted force fields is that over a large range of pressures and temperatures, the density of the fluid is accurately reproduced. \n\nFor pure component systems, the Gibbs phase rule requires that only one intensive variable (usually the temperature) can be independently specified when two phases coexist. The density and pressure are obtained from the simulation. By contrast, for multi-component systems, pressure can be specified in advance, with the total system being considered at constant NpT. The only change necessary is that the volume changes in the two regions are now independent. \n\n![](images/e6812db8e2e925a30ee41c1caa8dfee6f729264abaf59cb1598d1e1f15504242.jpg) \nFigure 1. (Colour online) Vapour–liquid coexistence curves for methane, ethane, propane, isobutane and neopentane computed in the Gibbs ensemble. Line, experimental data taken from the NIST database [11]; closed symbols, previous simulation data of Martin and Siepmann [12,13] using the Towhee code [14], open symbols, this work using RASPA. The order of the data from top-to-bottom is the same as the order in the legend. \n\n# 4. Adsorption \n\n# 4.1 Adsorption in the NpT Gibbs ensemble \n\nThe fundamental concept in adsorption science is the adsorption isotherm. It is the equilibrium relationship between the quantity of the molecules adsorbed and the pressure or concentration in the bulk fluid phase at constant temperature.[21] The Gibbs ensemble method can be used to compute adsorption isotherms in nanoporous materials.[16,22] One of the boxes contains the framework, while the other box contains the fluid phase (either gas or liquid) that is in equilibrium with the adsorbed phase. For adsorption of a system of $n$ components, the Gibbs phase rule requires that $n+1$ intensive variables be set, if you consider the adsorbent as an additional component. These $n+1$ variables are conveniently taken as the temperature, the pressure of the fluid phase, and $n{-}1$ mole fractions in the fluid phase. The system is then simulated using the NpT Gibbs ensemble. The fluid-phase box is maintained at constant pressure (and temperature) by applying volume moves. For adsorption in a flexible framework, the adsorbed-phase box is also maintained at constant pressure, but volume moves in a multi component Gibbs ensemble are performed independently for each box. For the simulation of adsorption in a rigid framework, the volume moves on the adsorbed-phase box are switched off; there is no requirement for mechanical equilibrium.[16] The equilibrium constraints are equal temperature in both systems and equal chemical potentials in the bulk and in the interior of the framework (similar to the VLE, the chemical potential equilibrium is enforced by particle swap moves between the boxes). \n\nFigure 2(a) shows adsorption isotherms of xylenes in MIL-47 using the NpT-Gibbs ensemble. Although we use a slightly different model (all-atom OPLS/DREIDING/UFF model,[23]) the results generally agree with the previous simulation data of Castillo et al. [24]. Note that experiments measure ‘excess adsorption’ while simulations calculate ‘absolute adsorption’. Excess adsorption is the number of molecules in the nanopores in excess of the amount that would be present in the pore volume at the equilibrium density of the bulk gas.[25,26] RASPA calculates absolute adsorption and, if the pore-volume fraction is given (can be computed separately), it also calculates the excess adsorption for convenience. With this type of modelling, the experimental results are well reproduced. The snapshots from the simulation (Figure 3) explain the ortho-selectivity: because ortho-xylene is commensurate with the size of the channel, it forms two layers of molecules that stack very efficiently.[24,23] The advantage of the Gibbs adsorption method is that the reservoir is explicitly simulated and hence the conversion from pressure to fugacity is consistently computed with the same force field. This avoids having to find and use an accurate equation of state for the adsorbates. Downsides include having to explicitly simulate the fluid phase (which can be expensive, especially in the liquid phase), and also the computed fugacity coefficient depends on the quality of the chosen force field and representation of the adsorbates. \n\n![](images/dede9fa609c93d73c0f8436159be7687d9ad883b5e251810425ed397251553b2.jpg) \nFigure 2. (Colour online) Pure component isotherms of $o\\mathrm{-}$ -, $m\\cdot$ and $p$ -xylene in MIL-47 at $423\\mathrm{K}$ : closed symbols represent experimental data [20], open symbols represent simulation data. \n\n![](images/6fcca9a525c710f453067b9f7f6eb5fd80c1265bd164dc1efd51eeec9ff8b5a6.jpg) \nFigure 3. (Colour online) Snapshot of $o$ -xylene in MIL-47 at $433\\mathrm{K}$ , (left) view along the channel, (right) side view with the channel $45^{\\circ}$ rotated around the channel axis (the line in the centre is an edge of the unit cell). The 1D channels of MIL-47 are about $8.5\\mathring\\mathrm{A}$ in diameter, which optimally stacks molecules that are commensurate with this dimension (i.e. $o$ -xylene). Figure courtesy of Ariana Torres Knoop. \n\n# 4.2 Adsorption in the grand-canonical ensemble \n\nIn the limit of low pressure, fugacity and pressure are equal (i.e. the fugacity coefficient is unity). There is, therefore, no need to explicitly simulate the fluid phase. But also if an accurate equation of state is available, or if the fugacity coefficient is known experimentally, or if one is simply interested in adsorption as a function of fugacity, then the reservoir computation is not necessary. In the grand-canonical (GC) ensemble $\\mu V T$ ensemble), the chemical potential is imposed at fixed temperature in a fixed volume (determined in this case by the crystallographic definition of the host framework). Insertion and deletion moves are used in the $\\mu V T$ ensemble to equilibrate the system at the fixed value of the chemical potential which is directly related to the fugacity $f$ by $\\beta\\mu=\\beta\\mu_{i d}^{0}+l n(\\beta f)$ (where $\\mu_{i d}^{0}$ is the reference chemical potential). \n\nFigure 2(b) shows the results for the xylene-MIL-47 system using the GC ensemble. The results of the Gibbs ensemble and grand canonical Monte Carlo (GCMC) simulations agree very well. In the GCMC simulations, the pressure was converted to fugacity using the Peng– Robinson equation of state, which uses the critical temperature, critical pressure and the ‘acentric factor’ that has been tabulated for many compounds. As output it gives whether under these conditions the fluid is a gas or liquid (or metastable), as well as properties such as the fugacity coefficient, the compressibility and the density of the bulk fluid phase. The density is needed to convert absolute adsorption to excess adsorption and vice versa. \n\n![](images/b1e1159194712795e8243b75d8e07c5b78e782a399ad4ef22ad22098058ca780.jpg) \nFigure 4. (Colour online) Pure component adsorption isotherms of benzene in MFI at 603 and $703\\mathrm{K}$ . Closed symbols, previous simulation result of Hansen [27] using BIGMAC [28]; open symbols, this work using RASPA. \n\nIn theory and simulation, it is common to plot loading as a function of fugacity because these plots are unaffected by the gas–liquid transition. For validation of the GCMC capabilities of RASPA, we show in Figure 4 adsorption results for benzene in MFI-type zeolite compared to the previous simulation results of Hansen [27] using the BIGMAC code.[28] Both simulations use fugacity and absolute loadings, and the agreement is excellent. \n\nSimulations of mixture adsorption require the specification of chemical potentials for each component. For gas phase adsorption, an empirical equation of state can be employed. The same treatment is often not readily generalisable to liquid mixtures because of the lack of accurate activity models.[29] A convenient simulation setup for such systems is to use NpT Gibbs-ensemble simulations using three boxes: (i) the adsorbed phase with the host framework, (ii) the solution phase and (iii) a vapour phase transfer medium. The molecules are not swapped directly between the adsorbed phase and the liquid phase but instead rely on the vapour phase as an intermediate transfer medium.[29] \n\nMeasuring mixed-gas adsorption experimentally is difficult. The ideal adsorption solution theory (IAST) of Myers and Prausnitz [30] is often used to estimate the mixture loading from the pure component isotherms. The validity of IAST can be checked using simulations. Figure 5 shows single component isotherms, and results for an equimolar four-component mixture of para-, meta-, ortho-xylene and ethylbenzene in MAF- $^{\\mathbf{\\nabla}_{\\mathbf{X}}8}$ at 433 K.[23] The IAST prediction is validated with explicit mixture simulations and for this system the IAST is applicable. Another reason to validate IAST is because it is convenient to use IAST as the input for breakthrough simulations.[31] \n\n# 4.3 Adsorption in the ${\\pmb{\\mu}}_{1}\\mathbf{N}_{2}\\mathbf{PT}$ ensemble (flexible frameworks) \n\nThe $\\mu_{1}N_{2}P T$ ensemble [35,36] is the natural ensemble to compute adsorption for flexible frameworks. The system is considered as two components, where the chemical potential of component 1 (the guest species) is kept constant (and has variable particle number), while component 2 (the framework) has constant particle number. As in GCMC, only the adsorbed phase is simulated, but now the volume moves are included to hold the pressure constant. For a single component system, it is not possible to vary three intensive variables independently because of the Gibbs–Duhem relation (from which Gibbs’ phase rule follows) which relates them. However, for two (or more) species systems, it is possible to derive, rigorously, a statistical ensemble in which $T$ , $P$ and $\\mu_{\\mathrm{ads}}$ and $N_{\\mathrm{host}}$ are held fixed. For this ensemble, $\\mu_{\\mathrm{ads}}$ is the chemical potential of the adsorbate and $N_{\\mathrm{host}}$ is the fixed number of atoms of the framework (host). This is a hybrid statistical ensemble which has some properties similar to the single species $(N p T)$ and $(\\mu V T)$ ensembles. In $(\\mu_{1}N_{2}p T)$ MC simulation, one carries out (at least) three distinct types of trial procedures [35,36] (i) the conventional configuration change moves, (ii) the change of volume and/or size of the system and (iii) a creation or deletion move. \n\n![](images/638d75dec71c2c9ea1bd6ff7a5ce926206924e5492662c491de3be982a1079b6.jpg) \nFigure 5. (Colour online) Xylene separation at $433\\mathrm{K}$ using MAF- $\\mathbf{\\sigma}\\cdot\\mathbf{x}8$ ,[23] (a) single components fitted with dual-site Langmuir– Freundlich isotherms, (b) equimolar mixture simulations and IAST prediction based on single component isotherms. \n\nFigure 6 shows simulated adsorption results of $\\mathrm{CO}_{2}$ in a flexible IRMOF-1 compared to simulations using a rigid structure (the energy-minimised structure with the same force field), and also compared to experimental data. The results for the rigid and flexible model are very similar for this system and in excellent agreement with experimental data. The computation of adsorption in the flexible structure was feasible because the IRMOF-1 structure stays relatively close to its equilibrium structure. The framework motions are efficiently sampled using the MC/ MD-hybrid move.[37,38] \n\n![](images/3fc6f0083f2499cebc6d6fb6fae22289a80572ccb696221bd5d5d541db1c0a31.jpg) \nFigure 6. (Colour online) $\\mathrm{CO}_{2}$ adsorption in IRMOF-1 showing step-like isotherms [32]. Lines, experimental data [33];, filled coloured points, rigid framework model [34];, open symbols, flexible framework model.[34] \n\n# 4.4 Efficient algorithms for open ensembles \n\nA system where the number of molecules varies is called an open system. All open-ensemble methods suffer from a major drawback: the insertion and deletion probabilities become vanishingly low at high densities. This problem is particularly severe for long chain molecules. For adsorption simulations, the fraction of successful insertions into the pores becomes too low. To increase the number of successfully inserted molecules, the CBMC technique was developed in the early 1990s.[7,39–41] Instead of generating ideal gas configurations and trying to insert the molecule as a whole, the CBMC method inserts chains part by part, biasing the growth process towards energetically favourable configurations, and therefore significantly reduces overlap with the framework and other particles. \n\nAn alternative scheme to remedy the insertion problem is the recently developed CFCMC method of Shi and Maginn [42–44]. The system is expanded with an additional particle whose interactions with the other atoms in the system are scaled by a parameter $\\lambda$ , where $0\\leq\\lambda\\leq1$ . Note that only the inter-molecular energy is scaled (not the intra-molecular energy). Many variations on the algorithm are possible. For example $\\lambda$ can be changed per molecule or per atom. Both methods slowly ‘inflate’ and ‘deflate’ the molecule like a balloon but differently. \n\nCFCMC uses conventional NVT MC for thermalisation (such as translation, rotation and/or MC–MD hybrid moves), but in addition attempts to change $\\lambda$ of the fractional molecule using $\\lambda(\\mathrm{new})=\\lambda(\\mathrm{old})+\\Delta\\lambda.\\ \\Delta\\lambda$ is chosen uniformly between $-\\Delta\\lambda^{\\mathrm{max}}$ and $+\\Delta\\lambda^{\\mathrm{max}}$ and scaled to achieve around $50\\%$ acceptance. However, many systems show a behaviour where $\\lambda$ -changes are hard. An additional bias $\\eta$ on $\\lambda$ can be used. This bias will be removed by the acceptance rules. A careful calibration of $\\eta$ can make $\\lambda$ histograms flat and hence can avoid that the system gets stuck in a certain range of $\\lambda$ . There are three possible outcomes of a change of $\\lambda({\\mathrm{old}})$ to $\\lambda(\\mathrm{new})$ : (i) $\\lambda$ remains between 0 and 1; there is no change in the number of particles, nor in the positions, nor in the intra-molecular energies. Only $\\lambda$ and the inter-molecular energy have changed. (ii) $\\lambda$ becomes larger than 1; when $\\lambda$ exceeds unity, $\\lambda=1+\\varepsilon$ , the current fractional molecule is made fully present $\\lambda=1\\dot{}$ ), and a new fractional molecule is randomly inserted with $\\lambda=\\varepsilon$ . Shi and Maginn used a methodology where a rigid conformation is chosen from a ‘reservoir’ of ideal gas molecules generated before the simulation. (iii) $\\lambda$ becomes smaller than 0: when $\\lambda$ falls below 0, $\\lambda=-\\varepsilon$ , the current fractional molecule is removed from the system $\\lambda=0$ Þ, and a new fractional molecule is chosen with $\\lambda=1-\\varepsilon$ . \n\nRASPA implements both CBMC and CFCMC, but also a combination (named CB/CFCMC) of the two developed by Torres-Knoop et al. [45]. The basic CFCMC algorithm is used with $\\lambda$ -biasing, but the insertion and deletion moves are performed using configurational biasing. Figure 2(c) shows that smoother curves are obtained by using this method. The method leads to very reliable results. Other implemented methods in RASPA to improve the efficiency of MC simulations are parallel-tempering and mole fraction replica exchange.[46,47] \n\n# 5. Screening \n\nContinued research and investments in high-performance computing have produced computing platforms that are now fast enough to permit predictive simulations and largescale screening studies. Simulation (virtual) screening is significantly cheaper than experimental screening and can be used to increase the successful hit rate. A hierarchical or step-wise approach is often used. \n\n. Initial screening (millions of structures). Screening on the basis of properties that can be computed very quickly. Example properties are pore volume, surface area, pore-size distribution, Henry coefficients and heats of adsorption at infinite dilution. . High throughput screening (hundreds of thousands of structures). In the pressure range of practical interest, the heat of adsorption and loadings are simulated (usually using relatively short runs). This allows a comparison of structures and an elucidation of structure–property relationships.[48–52] Detailed analysis (tens or hundreds of structures). Detailed analysis of the most promising structures could include simulations of single-component and mixture isotherms, diffusivities and efficiency estimates of the performance in a fixed-bed adsorber using breakthrough simulations.[23,53] \n\nFigure 7 shows two examples of screening. Go´mezGualdr´on et al. [48] investigated physical limits for methane storage and delivery in nanoporous materials, with a focus on whether it is possible to reach a methane deliverable capacity of $315\\mathrm{cm}^{3}(\\mathrm{STP})/\\mathrm{cm}^{3}$ in line with the adsorption target established by the ARPA-E agency. Using GCMC simulations, methane adsorption and delivery properties were studied in a population of 122,835 hypothetical pcu MOFs and 39 idealised carbon-based porous materials. From the simulation results, an analytical equation was obtained that delimits the necessary material properties to reach specific methane deliverable capacity targets. This high-throughput analysis elucidates how both geometric and chemical properties, such as void fraction, volumetric surface area and heat of adsorption, impact methane deliverable capacity. \n\n![](images/3e31fbc059fa87eda7972c5431737bd7dab43478d558bf5051ec31a597995dea.jpg) \nFigure 7. (Colour online) Screening results for (a) physical limits for methane storage and delivery in about hundred thousand nanoporous materials,[48] (b) fixed bed performance of para-selective MOFs.[23] Figure (a) courtesy of Diego A. Go´mez-Gualdro´n. \n\nThe second example is a detailed analysis by TorresKnoop et al. on separation of benzene, toluene, meta-, ortho-, para-xylene and ethylbenzene (BTEX process).[23] Many ortho-xylene selective structures have been found, but finding para-selective structures is much harder. Small pore structures are able to separate para-xylene using ‘sieving’ (the smaller molecules fit into the structure, but the larger molecules are excluded), but these are unable to separate para-xylene from ethylbenzene (same smallest dimension) and are usually diffusion limited. TorresKnoop et al. studied about 30 structures in full detail and elucidated why some structures are ortho-selective and others are para-selective. Using snapshots, the reason for a selectivity was explained. Snapshots in Figure 3 show that strong ortho-selectively can be obtained by a two-layer molecular stacking in the MIL-47 structure. The orthoxylene fits in perfectly, while meta-xylene fits less well. Para-xylene and ethylbenzene are too long and are forced to align obliquely. In their work, a para-selective structure was sought. Using the same mechanism, it is then required that the channel dimension are perfectly commensurate with the para-xylene dimensions. The screening found a strongly para-selective structure (MAF- $\\mathbf{\\nabla}\\cdot\\mathbf{x}8_{}$ ). The single component isotherms were computed, the IAST prediction was validated with mixture simulations and the IAST solution was the input for simulating breakthrough curves. These breakthrough simulations have the ‘cycle-time’ as output, i.e. the time needed before needing to start the expensive desorption process. As can be seen from Figure 7, the MAF$^{\\mathbf{\\delta}_{\\mathbf{X}8}}$ would be better than the currently used technology (BaX). The study also revealed that other para-xyleneselective structures, such as MIL-125 and JUC-77, would be diffusion limited (decreasing their performance). \n\nRASPA provides perl scripts to submit jobs for screening purposes. One specifies the list of adsorbates, structures, temperatures, pressure range and number of pressure points, whether fugacity or pressure is used, whether the points are equally spaced in normal or logscale, etc. The script then generates all the necessary input files and has as output the job scripts needed to submit it to a cluster (with a single command). \n\n# 6. Reactive Monte Carlo \n\nThe RxMC method allows computation of equilibrium properties for chemically reacting or associating fluids. [54,55] The method samples forward and backward reactions using MC moves directly (without going through the transition states). No chemical potentials or chemical potential differences need to be specified for the reaction steps, just the stoichiometry of the reactions. Essentially, the method enhances the GCMC with a ‘forward’ and ‘backward’ reaction step, which ensures that the chemical reaction equilibria between the reactants and the products are maintained. \n\nAs an example, the industrially important propene metathesis is described by three equilibrium reactions [57] $2\\mathrm{C}_{3}\\mathrm{H}_{6}\\leftrightarrow\\mathrm{C}_{2}\\mathrm{H}_{4}+$ trans- $\\mathrm{{C_{4}H_{8}}}$ $\\mathrm{2C_{3}H_{6}\\leftrightarrow C_{2}H_{4}+c i s–C_{4}H_{8}}$ cis- ${\\mathrm{C}}_{3}{\\mathrm{H}}_{6}\\leftrightarrow$ trans- $\\mathrm{C_{4}H_{8}}$ \n\nOnly two reactions are independent and need to be included. In addition to the MC moves associated with simulating a chosen ensemble, also ‘reaction’ moves are performed: \n\n(1) randomly choose a reaction, \n(2) randomly choose whether to do a forward or backward reaction (this determines the ‘reactant’ and ‘product’ molecule types), \n(3) randomly select the reactant molecules and remove them from the system, \n(4) insert the product molecules at random positions, \n(5) accept or reject the reaction step with the appropriate acceptance probability. \n\nInserting molecules at high densities is difficult and even more so when one needs to insert several molecules at the same time. To overcome these difficulties, Hansen et al. [56] and Jakobtorweihen et al. [58] combined the $\\mathbf{RxMC}$ method with CBMC. Recently, Rosch and Maginn combined the CFCMC method with the RxMC method. [44] For the propene metathesis reactions simulated with reactions 2 and 3, six fractional reaction molecules are added to the system. Each reaction has an associated reaction $\\lambda$ (between 0 and 1) and MC moves are performed trying to change $\\lambda_{o}$ to $\\lambda_{n}$ . When $\\lambda_{n}>1$ a forward reaction is performed and, if accepted, $\\lambda$ is set to $\\lambda_{n}-1$ . If $\\lambda_{n}<0$ a backward reaction is performed and, if accepted, $\\lambda$ is set to $\\lambda_{n}+1$ . The insertions and deletions are biased in $\\lambda$ which allows the method to efficiently overcome insertion and deletion difficulties. \n\nFigure 8 shows the results from RASPA using the CFCMC–RxMC method compared to the CBMC–RxMC simulation results of Hansen et al. [56]. The RASPA results are in excellent agreement. Previously, Rosch and Maginn [44] validated their implementation with the results of Hansen et al. and also found excellent agreement. \n\n# 7. Diffusion \n\n# 7.1 Molecular dynamics \n\nIn many applications of nanoporous materials, the rate of molecular transport inside the pores plays a key role in the overall process. The size of the pores is usually of the same order as the size of the adsorbates. Diffusion properties of guest molecules in nanoporous materials can therefore be quite sensitive to small differences between different host materials. Molecular-level modelling has become a useful tool for gaining a better understanding of diffusion in nanoporous materials. Many different diffusion coefficients can be defined for guest molecules in nanoporous materials, but it is useful to put them into two general classes: transport diffusivities and self-diffusivities. The transport (or Fickian) diffusivity describes the transport of mass and the decay of density fluctuations in the system, while self-diffusion describes the diffusive motion of a single particle. By omitting the thermodynamic contribution in the transport diffusion, the so-called ‘corrected diffusivity’ (also called ‘collective diffusivity’) is obtained. The self-, corrected and transport diffusivities are equal only in the limit of zero loading. \n\n![](images/75a5b22767d8d3c421932648db74ee1443eba58449c7c3a75ece90e49967b7b6.jpg) \nFigure 8. (Colour online) Selectivity of the propene metathesis reaction system in the temperature range between 300 and $600\\mathrm{K}$ . Closed symbols, previous simulation result of Hansen et al. [56]; open symbols, this work using RASPA. \n\nIn an equilibrium molecular dynamics simulation, the self-diffusion coefficient $D_{\\alpha}^{S}$ of component $\\alpha$ is computed by taking the slope of the mean-squared displacement (MSD) at long times \n\n$$\nD_{\\alpha}^{S}=\\frac{1}{2\\mathrm{d}N_{\\alpha}}\\operatorname*{lim}_{t\\rightarrow\\infty}\\frac{\\mathrm{d}}{\\mathrm{d}t}\\Bigg\\langle\\sum_{i=1}^{N_{\\alpha}}(r_{i}^{\\alpha}(t)-r_{i}^{\\alpha}(0))^{2}\\Bigg\\rangle,\n$$ \n\nwhere $N_{\\alpha}$ is the number of molecules of component $\\alpha,d$ is the spatial dimension of the system, $t$ is the time and $r_{i}^{\\alpha}$ is the centre-of-mass of molecule $i$ of component $\\alpha$ . The order- $\\cdot n$ algorithm for measuring MSDs conveniently and efficiently captures correlations over short, medium and long times.[59] In crystalline materials the MSDs become linear beyond $\\lambda^{2}$ , where $\\lambda$ is the repeating distance (usually the unit cell distance). Since the MSD accuracy rapidly decreases over increasing times, a good practice is to fit the diffusivities from a few data points after the MSD has become linear. \n\nFor a single adsorbed component, the transport diffusion coefficient $D^{T}$ is given by \n\n$$\nD^{T}=\\frac{\\Gamma}{2\\mathrm{d}N}\\operatorname*{lim}_{t\\rightarrow\\infty}\\frac{\\mathrm{d}}{\\mathrm{d}t}\\Bigg\\langle\\Bigg(\\sum_{i=1}^{N}(r_{i}(t)-r_{i}(0))\\Bigg)^{2}\\Bigg\\rangle.\n$$ \n\nNote that here first the distances are summed and then squared. Hence collective diffusion can be considered a ‘centre-of-mass’ diffusion. The thermodynamic factor $\\Gamma$ is \n\n$$\n\\Gamma=\\left(\\frac{\\partial\\ln f}{\\partial\\ln c}\\right)_{T}=\\frac{\\left}{\\left-\\left^{2}},\n$$ \n\nwhere $c$ denotes the concentration (adsorbate loading in the framework), and can be obtained from the adsorption isotherm or from the fluctuation formula.[60] The omission of the thermodynamic factor in Equation (3) leads to the ‘corrected diffusivity’ (also called ‘collective diffusivity’) $D^{C}$ . The concept of collective diffusivity can be extended to multi-component systems using \n\n$$\n\\begin{array}{c l}{{\\displaystyle\\Delta_{\\alpha\\beta}=\\frac{1}{2\\mathrm{d}N_{\\alpha}}\\operatorname*{lim}_{t\\rightarrow\\infty}\\frac{\\mathrm{d}}{\\mathrm{d}t}\\Bigg\\langle\\left(\\sum_{i=1}^{N_{\\alpha}}(\\mathbf{r}_{i}^{\\alpha}(t)-\\mathbf{r}_{i}^{\\alpha}(0))\\right)}}\\\\ {{\\displaystyle\\times\\left(\\sum_{i=1}^{N_{\\beta}}(\\mathbf{r}_{i}^{\\beta}(t)-\\mathbf{r}_{i}^{\\beta}(0))\\right)\\Bigg\\rangle,}}\\end{array}\n$$ \n\nwhere the $\\Delta$ elements for components $\\alpha$ and $\\beta$ are known as the Onsager $\\Delta$ elements. Maxwell –Stefan diffusivities are related to the elements of $\\left[B\\right]=\\left[\\Delta\\right]^{-1}$ and can be obtained by matrix inversion.[61,62] Equations relating $\\Delta_{\\alpha\\beta}$ to the Fickian diffusion coefficients can also be derived.[63] From a phenomenological point of view, there are three different approaches to setting up the flux–driving force relationship for diffusion in nanoporous materials under non-equilibrium conditions. The Fickian-, Maxwell–Stefan- and Onsager formulations are strictly equivalent, and all three viewpoints are needed for different purposes. \n\nIf the framework is kept fixed, the potential energy surface induced by the framework can be pre-computed. [64,65] Instead of looping over all framework atoms in order to compute the host-adsorbate energy at each time step, one can construct a 3D grid before the simulation and then obtain the energy by interpolation during the simulation. The more points in the grid the higher the accuracy. RASPA implements the triclinic grid interpolation scheme in three dimensions of Lekien and Marsden [45,66]. The algorithm is based on a specific $64\\times64$ matrix that provides the relationship between the derivatives at the corners of the elements and the coefficients of the tricubic interpolant for this element. The cubic interpolant and its first three derivatives are continuous and consistent. The same grids can, therefore, be used for both MC and MD with no additional energy drift besides the drift due to the integration scheme, i.e. the energy gradients are the exact derivatives of the energy at each point in the element. \n\nRASPA uses symplectic or measure-preserving and reversible integrators. Symplectic integrators tend to preserve qualitative properties of phase space trajectories: trajectories do not cross, and although energy is not exactly conserved, energy fluctuations are bounded. Since symplectic integrators preserve the topological structure of trajectories in phase space, they are more reliable for longterm integration than non-symplectic integrators. The implemented NVE integrator is the symplectic and time reversible integrator for molecules with an arbitrary level of rigidity, developed by Miller et al. [67] based on a novel quaternion scheme. Thermo- and barostats can be combined with the Miller scheme to control the temperature and pressure.[68,70,71] Figure 9 shows that this type of scheme has excellent energy conservation over many nanoseconds. The $\\mathrm{CO}_{2}$ is modelled as rigid and integrated using the quaternion integration scheme of Miller et al. [67]. Separate thermostats are used to thermostat the translation and the rotation of the molecules. The framework–molecule interactions are computed using a grid interpolation scheme.[45,66] The grid spacing was $\\mathrm{0.1\\mathring{A}}$ . A separate grid is used for each van der Waals interaction of the O and the C of the adsorbate molecule, and another grid is used for the real part of the Ewald summation. In the Fourier part of the Ewald summation, the contribution of the rigid framework atoms is pre-computed at the start of the simulation.[10] \n\nFigure 10 shows the self- and collective diffusivities of small gases $(\\mathrm{H}_{2}$ , $\\mathbf{N}_{2}$ , Ar, $\\mathrm{CH}_{4}$ and $\\mathrm{CO}_{2}\\mathrm{\\cdot}$ ) in IRMOF-1 at $298\\mathrm{K}$ as a function of loading using the force field of Skoulidas and Sholl [69]. The results of RASPA agree quantitatively with previous simulation results of Skoulidas and Sholl. Self-diffusivities can be computed very accurately because it is a single particle property (which can be averaged over all particles). The collective diffusivity is much more difficult to compute because it is a system property. The self-diffusivities are more strongly influenced by correlation effects (kinetic and vacancy correlations) than the collective diffusivities. Correlations between the particles increase with loading. \n\n# 7.2 Dynamically corrected transition state theory \n\nFor some systems, the molecules move too slowly and the diffusion coefficients cannot be calculated reliably using MD. An alternative approach is to use transition state theory (TST). In the TST approximation, one computes a rate constant for hopping between states A and B by computing the equilibrium particle flux through the dividing surface. The dividing surface should partition the system into two well-defined states along a reaction coordinate, which describes the progress of the diffusion event from state $A$ to state $B$ . In many nanoporous materials, the reaction coordinate follows directly from the geometry of the confinement. For example, in Figure 11 the reaction coordinate for methane in LTL (Linde Type L)-type zeolite is shown: the projection of the position on the channel-axis. The location of the dividing surface is denoted by $q^{*}$ . In ‘dynamically corrected’ TST, one computes the hopping rate over the barrier in two steps [72,73]: \n\n(1) the relative probability $P(q^{*})=\\mathrm{e}^{-\\beta F(q^{*})}/$ $\\int_{\\mathrm{cageA}}{\\mathrm{e}^{-\\beta F(q)}}\\mathrm{d}q$ is computed to find a particle at the dividing surface $q^{*}$ relative to finding it in state $A$ , \n(2) the average velocity at the top of the barrier is computed as $\\sqrt{k_{B}T/2\\pi m}$ (assuming that the particle \n\n![](images/65eba08de5fe3e9e54a62739bc17b57b52870df3fa2aa8afa4bef0e1e27c9f3f.jpg) \nFigure 9. (Colour online) Molecular dynamics of $\\mathrm{CO}_{2}$ at 20 molecules per IRMOF-1 unit cell $(2\\times2\\times2$ system) at room temperature using the quaternion integration scheme of Miller et al. [67]: (a) the individual contributions to the conserved quantity, (b) the instantaneous and average energy drift. The temperature is maintained by using a Nose´ –Hoover chain.[68] The molecule–framework interactions are computed using a grid-interpolation scheme [45,66]. \n\n![](images/b2c5a36cbedcfb6fcf260e1abacf99ccc2440580aa0c3cc4111f0f0101535d43.jpg) \nFigure 10. (Colour online) Simulated diffusivities of small gases in IRMOF-1 at $298\\mathrm{K}$ . Closed symbols, previous simulation result of Skoulidas and Sholl [69]; open symbols, this work using RASPA. \n\nvelocities follow a Maxwell–Boltzmann distribution), and the probability $\\kappa$ (dynamical correction) that the system ends up in state $B$ is obtained by running short MD trajectories from the dividing surface. \n\nThe transmission rate $k_{A\\rightarrow B}$ from cage $A$ to cage $B$ is then given by \n\n$$\nk_{A\\rightarrow B}=\\kappa\\times\\sqrt{\\frac{k_{B}T}{2\\pi m}}\\times\\frac{\\mathrm{e}^{-\\beta F(q^{*})}}{\\int\\mathrm{e}^{-\\beta F(q)}\\mathrm{d}q},\n$$ \n\nwhere $\\beta=1/(k_{B}T),k_{i}$ $k_{B}$ is the Boltzmann constant, $T$ the temperature, $m$ the mass involved in the reaction coordinate and $F(q)$ the Helmholtz free energy as a function of $q$ . Calculating TST rate constants is therefore equivalent to calculating free energy differences. The exact rate can be recovered by running short MD trajectories from the dividing surface to compute a dynamical correction.[72] The extension to non-zero loading (or to a flexible framework) simply involves sampling these effects ‘in the background’.[73,74] In Figure 11 the free energy profile for methane in LTL is plotted for an average loading of three molecules per unit cell (a unit cell contains two channels). The barrier of this free energy profile is denoted as $q^{*}$ and corresponds to an entropic constriction of the channel. The dynamic correction is computed from many snapshots with one particle constrained to $q^{*}$ and $N-1$ particles free (the snapshots are easily sampled using MC). Each snapshot is used to start an MD path with initial velocities sampled from a Maxwell–Boltzmann distribution. The velocity of the barrier particle is pointing towards cage $B$ . For all of these snapshots, MD paths are simulated and the flux at the top of the barrier is computed. Figure 12 shows data for methane, ethane and propane in LTL-type zeolite with dcTST compared to MD (for this system both are feasible). It can be seen that the two methods give identical results. The dcTST method, however, is also applicable for slow diffusion $(\\ll10^{-12}\\mathrm{m}^{2}/s)$ that is (currently) impossible to compute with MD. \n\n![](images/7278743449ba7e6388992d59a101c56ac5644b272ee86ea3abff6dda7ff6985e.jpg) \nFigure 11. (Colour online) A typical snapshot of a tagged methane particle (green) in LTL-type zeolite restrained to the barrier $q^{\\bar{*}}$ surface at an average loading of three methane molecules per unit cell (there are two parallel channels per unit cell) at $30\\mathrm{{0}K}$ . Four unit cells each of $7.474\\mathring\\mathrm{A}$ in length are shown. The constrictions are caused by the 12-T-membered rings, which form free energy barriers impeding diffusion. The free energy profile in dimensionless units at this average loading is plotted in white, where the reaction coordinate is chosen parallel to the channel direction. If the free energy barriers are high enough, diffusion can be considered a hopping process from minimum to minimum $(q_{A},q_{B},q_{C}$ ; etc). \n\nThe dcTST sampling is an example where it is convenient to be able to constrain MC moves. RASPA includes ways to constrain the movement of a component to a line, plane or sub-volume (box, cylinder, etc.). Any attempt to move a particle outside the sub-volume is rejected. Another useful feature is ‘blocking’ volumes that are large enough to contain a molecule, but where that volume is not accessible from the main channel. Yet another common example is a channel system where one would like to always have equal particles for each channel. This can be achieved by creating a different component for each channel, and only allow MC moves to a cylinder that encompasses that channel. \n\n![](images/5b83543fa33c2fc79aae9f4b072cb7cd7d77dff863264b02b83663e7087058db.jpg) \nFigure 12. (Colour online) Diffusion of methane $(C_{1})$ , ethane $(C_{2})$ and propane $(C_{3})$ at $300\\mathrm{K}$ as a function of loading in LTLtype zeolite computed by TST, dcTST and MD. \n\n# 8. Material properties \n\n# 8.1 Surface area, void fraction and pore-size distribution \n\nSurface area is the most basic property of porous materials. Along with pore volume, surface area has become the main benchmark characterisation method for any porous material. The surface area is usually determined for experimental samples by measuring a nitrogen isotherm at $77\\mathrm{K}$ and then applying the Brunauer–Emmett–Teller (BET) model. Walton and Snurr [75] examined the consistency of the surface areas obtained from the BET model with those calculated geometrically from the crystal structure for several prototypical MOFs with varying pore sizes. Geometric surface areas can be calculated by using a simple MC integration technique in which a nitrogen probe $(3.681\\mathring{\\mathrm{A}})$ molecule is rolled along the surface of the framework.[26,76,77] Walton and Snurr provided compelling evidence for the importance of calculating the BET surface area from the proper region of the adsorption isotherm.[75] Commercial ‘BET’ instruments are typically set to automatically choose a fixed range for BET fitting. The operator must ensure that the range results in consistent BET model parameters. \n\nThe pore-size distribution (PSD) can be calculated geometrically in RASPA using the method of Gelb and Gubbins [77,78]. For every point in the void volume, the largest sphere is found that encloses the point but does not overlap with any framework atoms. This yields the cumulative pore volume curve. Let $V_{\\mathrm{pore}}(r)$ be the volume of the void space ‘coverable’ by spheres of radius $r$ or smaller; a point $x$ is in $V_{\\mathrm{pore}}(r)$ only if we can construct a sphere of radius $r$ that overlaps $x$ and does not overlap any substrate atoms. This volume is equivalent to that enclosed by the pore’s ‘Connolly surface’. $V_{\\mathrm{pore}}(r)$ is a monotonically decreasing function of $r$ and is easily compared with the ‘cumulative pore volume’ curves often calculated in isotherm-based PSD methods. The derivative $-\\mathrm{d}V_{\\mathrm{pore}}(r)/\\mathrm{d}r$ is the fraction of volume coverable by spheres of radius $r$ but not by spheres of radius $r+\\mathrm{d}r$ and is a direct definition of the pore size distribution. The $V_{\\mathrm{pore}}(r)$ function can be calculated by a MC volume integration in RASPA. \n\nKnowledge of the density of porous materials is critical for full characterisation of the adsorbents and for fixed-bed adsorber design studies. Talu and Myers [25] proposed a simulation methodology that mimics the experimental procedure. For consistency with experiment, the helium void fraction $\\xi$ is determined by probing the framework with a helium molecule using the Widom particle insertion method: \n\n$$\n\\xi=\\int\\mathrm{e}^{-\\beta U}\\mathrm{d}\\mathbf{r}.\n$$ \n\nWidom insertion uses a probe particle that is inserted at random positions to measure the energy required for or obtained by insertion of the particle in the system. Usually a reference temperature of $25^{\\circ}\\mathrm{C}$ (298 K) is chosen for the determination of the helium void volume. Computationally, one can also use the $r\\longrightarrow0$ limit of the pore size distribution to evaluate the void fraction. The helium void fraction is needed to convert absolute loadings to excess values (or vice versa). \n\n# 8.2 Thermal and mechanical properties \n\nStructural flexibility is a well-known property of MOFs. [79] For example, MIL-53 exhibits breathing [6] and IRMOFs exhibit negative thermal expansion.[34] RASPA allows a wide variety of flexible models for the framework. Flexible models are needed to obtain properties such as thermal expansion of the framework itself. Thermal and mechanical transport properties are calculated either from equilibrium Green–Kubo relations or by setting up a small non-equilibrium flux across the system. Thermal expansion can be calculated from NpT MD simulations using a flexible framework. \n\nFigure 13 plots the unit cell size of IRMOF-1 as a function of temperature.[34] The structure become smaller with increasing temperature, in contrast to most materials which expand when you heat them. The classical models, quantum mechanical results and experimental data are qualitatively consistent. The quantum results at zero Kelvin depend very much on the used level of theory and basis sets. The negative thermal expansion of IRMOFs is a direct result of the inherent structure of MOFs: linker molecules connected via metal corners. The wiggling of the linkers becomes larger with increasing temperature leading to a reduced ‘projected’ length. Viewed oppositely, when the temperature is lowered the linkers ‘stretch out’. Therefore, negative thermal expansion is very likely a generic property of many MOFs. \n\n![](images/beb591aa4484e307ef450476f20354d2322593e4dfe7eed82841cf878deb1916.jpg) \nFigure 13. (Colour online) Unit cell size of IRMOF-1 as a function of temperature; experimental data, quantum simulations and three classical models. For further details see text and Ref. [34]. \n\n# 9. Zero Kelvin modelling \n\n# 9.1 Unit cells \n\nTo study the shape and size of unit cells, one needs a model for the framework itself. Core-shell models are very suitable for minerals, metal-oxides and zeolites. The coreshell model introduces charged, massless shells around each core. For minimisation of core-shell models, the generalised Hessian matrix contains both the cores and the shells because the shells need to be minimised with respect to the cores, too. In the shell model, the short-range repulsion and van der Waals interactions are taken to act between the shell particles. \n\nIn Table 1 we compare our results to those obtained with GULP [80,81] for the minimisation of various zeolites and minerals using Baker’s mode-following technique.[83] Using mode-following minimisation, the gradients on the cell and particles can be lowered arbitrarily close to zero and a true minimum energy is obtained (i.e. all positive eigenvalues of the Hessian matrix). The results of the RASPA and GULP codes are identical. The structures are minimised in space group P1 (no symmetry) with a cut-off of $12\\mathring{\\mathrm{A}}$ using the mode-following technique with full unit cell fluctuation, i.e. all cell lengths and angles are allowed to change. The GULP simulations are computed using GULP 3.1 and experimental data are taken from Schro¨der and \n\nSauer [82]. The RASPA simulations were fully converged to forces smaller than $10^{-8}\\mathrm{K/\\mathring{A}}$ and $10^{-8}\\mathrm{K}/\\$ strain (1 degree Kelvin is $8.621738\\times10^{-5}\\mathrm{eV})$ . \n\n# 9.2 Elastic constants \n\nElastic constants express the degree to which a material possesses elasticity and mechanical stability (Born criteria). The elasticity tensor $C_{\\alpha\\beta\\mu\\nu}$ is the second derivative of the energy with respect to strain $\\eta$ and can be described in terms of fluctuations in the stress tensor $\\sigma$ [84] \n\n$$\n\\begin{array}{c}{{C_{\\alpha\\beta\\mu\\nu}=\\Big\\langle C_{\\alpha\\beta\\mu\\nu}^{B}\\Big\\rangle}}\\\\ {{{}}}\\\\ {{-\\displaystyle\\frac{V}{k_{B}T}\\Big[\\Big\\langle\\sigma_{\\alpha\\beta}^{B}\\sigma_{\\mu\\nu}^{B}\\Big\\rangle-\\Big\\langle\\sigma_{\\alpha\\beta}^{B}\\Big\\rangle\\Big\\langle\\sigma_{\\mu\\nu}^{B}\\Big\\rangle\\Big]}}\\\\ {{{}}}\\\\ {{+\\rho k_{B}T\\Big(\\delta_{\\alpha\\mu}\\delta_{\\beta\\nu}+\\delta_{\\alpha\\nu}\\delta_{\\beta\\mu}\\Big),}}\\end{array}\n$$ \n\nwhere the first term on the right is the so-called Born term \n\n$$\nC_{\\alpha\\beta\\mu\\nu}^{B}=\\frac{1}{V}\\frac{\\partial^{2}U}{\\partial\\eta_{\\alpha\\beta}\\partial\\eta_{\\mu\\nu}}\n$$ \n\nand the second and third terms are the stress-fluctuations term and ideal gas term, respectively. The $\\delta$ is the Kronecker’s delta, the function is 1 if the variables are equal, and 0 otherwise. \n\nTable 1. Comparison of RASPA vs GULP for two core-shell models: the model of Catlow and Gale as provided in GULP [80,81] and Schro¨der and Sauer [82]. \n\n\n
StructureRASPAGULP
a[A]b[A]c[A]α[]β[°][]a[A]b [A]c[A]α[°]β[][]
FAU (Catlow)24.22624.22624.22690909024.22624.22624.226909090
FAU (Schroder)24.63124.63124.63190909024.63224.63224.632909090
FAU (exp.)24.2624.2624.26909090
MFI (Catlow)19.97919.73913.32090.814909019.98019.74013.32090.8139090
MFI (Schroder)20.42520.20513.63490909020.42520.20513.634909090
MFI (exp.)20.1119.8813.3790.79090
CHA (Catlow)9.1989.1989.19894.75294.75294.7529.1989.1989.19894.75194.75194.751
CHA (Schroder)9.3359.3359.33594.52494.52494.5249.3359.3359.33594.52494.52494.524
CHA (exp.)9.3269.3269.32694.794.794.7
TON (Catlow)13.81417.3875.00290909013.81517.3885.002909090
TON (Schroder)14.12717.7795.15590909014.12717.7795.155909090
TON (exp.)13.8617.425.04909090
SOD (Catlow)8.7678.7678.7679090908.7678.7678.767909090
SOD (Schroder)8.9518.9518.9519090908.9518.9518.951909090
SOD (exp.)8.838.838.83909090
Coesite (Catlow)7.02512.2907.11590122.485907.02612.2907.11590122.48590
Coesite (Schroder)7.18712.5387.25690122.803907.18712.5387.25690122.80390
Coesite (exp.)7.1412.377.1790120.390
α-quartz (Catlow)4.8354.8355.34690901204.8364.8365.3469090120
α-quartz (Schroder)4.9884.9885.50690901204.9884.9885.5069090120
α-quartz (exp.)4.924.925.419090120
\n\nAt zero Kelvin, the elastic constants reduce to the Born term minus a ‘relaxation term’ [85] \n\n$$\n\\begin{array}{r l}&{C_{\\alpha\\beta\\mu\\nu}=-\\frac{\\partial\\sigma_{\\alpha\\beta}^{B}}{\\partial\\eta_{\\mu\\nu}}\\biggr\\rvert_{h=0}}\\\\ &{\\qquad=\\underbrace{\\cfrac{1}{V}\\frac{\\partial^{2}U}{\\partial\\eta_{\\alpha\\beta}\\partial\\eta_{\\mu\\nu}}}_{\\mathrm{Borm~term}}-\\underbrace{\\cfrac{1}{V}\\frac{\\mathrm{d}\\sigma_{\\alpha\\beta}}{\\mathrm{d}r_{i\\lambda}}\\left(\\mathcal{H}^{-1}\\right)_{i\\lambda,j\\bar{\\xi}}\\frac{\\mathrm{d}\\sigma_{\\mu\\nu}}{\\mathrm{d}r_{i\\bar{\\xi}}}}_{\\mathrm{Relaxaition~term}}.}\\end{array}\n$$ \n\nNote that the derivative needs to be evaluated at constant zero gradient $\\pmb{h}=0$ , which is an algebraic relation between the coordinates at zero temperature. That is, the state before and after a strain is applied must be in a state of zero net force. When more than one particle is present in the system, this requires a ‘relaxation’ of the atoms relative to one another when the system is strained. [85] The zero temperature limit of the stress fluctuation term in Equation (8) is the relaxation term (and the ideal gas term vanishes in this limit). All expressions in Equation (10) are contained in the generalised Hessian matrix, which is the central quantity used in Baker’s minimisation scheme. The elastic constants at $0\\mathrm{K}$ can therefore be computed with very high accuracy. In Table 2 we show the elastic constants at $0\\mathrm{K}$ computed from RASPA and GULP for several zeolites and other silicates. The results are identical. Note that RASPA uses the upper triangular matrix for the simulation cell with the $a$ direction of the lattice always aligned with the $x$ -axis. This means that during the minimisation, the cell does not change orientation. This is convenient when computing elastic constants (which are directional) because the elastic constants are computed along the Cartesian axes (so the crystal should be aligned with these axes). \n\n# 9.3 Approach angles \n\nIn catalysis, insight into chirality transfer from catalyst to reactant can be gained by performing constrained minimisations of the reactant–catalyst complex. Because the mechanism of asymmetric induction for epoxidation of olefins by (salen)Mn catalysts is thought to involve steric interactions between the olefin and the catalyst, the direction of olefin approach has been studied by Oxford et al. [86] using hybrid MC simulations combined with classical optimisations. Four main directions of approach to the Mn-oxo moiety have been proposed in the literature (Figure 14(a)); see Ref. [86] and references therein. To examine the approach of 2,2-dimethyl-2H-chromene to the active site of $\\mathrm{(salen)Mn=O}$ , the potential energy surface for rotation around the dihedral angle of approach was mapped using constrained classical optimisations. In these optimisations using RASPA, the distance between the oxo ligand and $\\mathbf{C}_{1}$ atom was constrained to $2.0\\mathring\\mathrm{A}$ , and the angle defined by the manganese atom, oxoligand and $\\mathbf{C}_{1}$ atom was constrained to $122^{\\circ}$ (see Figure 14(b)) because this geometry is similar to that expected in the transition state.[87] Hard constraints were employed, using the $r^{2}$ -SHAKE, $\\cos^{2}\\cdot$ -SHAKE and the $\\varphi$ -SHAKE algorithms [88] for the bond, bend and torsion angle constraints, respectively. The minimisation method used guaranteed that the minimum found was a true minimum (all eigenvalues of the Hessian matrix are positive). \n\nTable 2. Comparison of elastic constants at zero Kelvin in units of GPa as computed by GULP and RASPA. \n\n\n
MFI (RASPA)MFI (GULP)CHA (RASPA)CHA (GULP)Coesite (RASPA)Coesite (GULP)α-quartz (RASPA)α-quartz (GULP)
C1197.7197.75124.05124.07124.69124.7594.5594.59
C2288.9989.03122.24122.26210.93210.9594.5594.59
C3379.3679.40119.85119.88160.29160.35116.04116.06
C4428.6528.6717.5117.5228.2828.3249.9750.00
C5526.2726.2917.9117.9271.0071.0049.9750.00
C6623.0923.1018.3218.3243.5543.5838.0638.08
C1212.0912.1057.7057.7184.1584.1618.4318.41
C1326.4926.4956.8256.8498.0998.0919.6719.67
C14-2.15-2.16-5.53-5.52- 14.48-14.49
C15-5.53-5.52-34.12-34.13
C16-5.11-5.10
C2325.44-25.4556.0556.0645.2445.2519.6719.67
C24-7.93-7.93-6.32-6.3114.4814.49
C25-5.48-5.479.739.73
C26-7.24-7.23
C34-5.78-5.78-8.71-8.70
C35-8.10-8.09-62.03-62.02
C365.31-5.30
C45- 2.73-2.73/
C46- 2.69- 2.690.630.65
C56-0.78-0.782.532.53-14.48-14.49
\n\nFigure 15 shows adsorption energies of 2,2-dimethyl2H-chromene on the homogeneous catalyst as a function of the approach angle. The approach angle $\\varphi$ was the dihedral angle defined by the midpoint of the oxygen atoms in the salen catalyst, the manganese atom, the oxo ligand and the $\\mathbf{C}_{1}$ atom of the reactant that would be forming a bond with the oxo ligand in the first transition state to the radical intermediate. The $\\mathbf{C}_{1}$ atom of chromene was chosen assuming that the phenyl group would stabilise the radical on the $\\mathbf{C}_{2}$ atom. The Si and Re enantiofaces of chromene are defined by the chirality of the $\\mathrm{C}_{1}$ atom in the reactant–catalyst complex. The reactant–catalyst complex was optimised at $10^{\\circ}$ intervals in $\\varphi$ . The simulations predict the Re enantioface to be the preferred enantioface, in agreement with experiments. The Re enantioface favours the approach from $\\varphi=-60^{\\circ}$ (approximately equivalent to the approach from direction C in Figure 14), while the Si enantioface prefers to approach from direction D, with a minimum in energy at $\\varphi=-10^{\\circ}$ . \n\n![](images/6c0f4b7129f8b47af455605aa81abcb3986f5280092196676e94dcc165b84011.jpg) \nFigure 14. (Colour online) Asymmetric induction for epoxidation of olefins by (salen)Mn catalysts. (a) Proposed directions of approach to the active Mn-oxo moiety of (salen)Mn. $\\varphi$ is the approach angle defined by the midpoint between the oxygen atoms in the salen ligand, the manganese atom, the oxo ligand and the carbon of the reactant forming a bond with the oxo ligand. (b) The bond-, bend- and dihedral constraints of the saddle point. The inset shows the two enantiofaces (Si and Re) of 2,2-dimethyl-2H-chromene. Figure courtesy of G.A.E. Oxford. \n\n![](images/fe3be13a64e2cc952819f240518b33afcceafa618b53ac442e7500d21c5225cb.jpg) \nFigure 15. (Colour online) Adsorption energies of 2,2- dimethyl-2H-chromene on the homogeneous salen catalyst as a function of the approach angle. \n\n# 10. Visualisation \n\nIt is difficult to determine the connectivity, shape and size of a channel/cage system just by examining the atomic positions of the framework. Early simulation work therefore used visualisations of energy contour plots and 3D density distributions, e.g. for benzene in silicalite,[90] to obtain siting information. The visualization toolkit (VTK) is an open-source, freely available software system for 3D computer graphics, image processing and visualisation.[91] RASPA has a stand-alone utility, written in $^{C++}$ , which visualises output files written by RASPA using VTK. RASPA produces 3D VTK files for visualising channel structures and 3D VTK files of the histograms of molecule positions during adsorption. For mixtures, a 3D histogram is produced for each component. This allows one to check and study ‘segregation’ of molecules.[92] Figures 3 and 11 have been made using RASPA and VTK. \n\nFigure 16(a) shows the MFI-type zeolite. The orthorhombic unit cell has edge lengths $a=20.022\\mathring\\mathrm{A}$ , $b=19.899\\mathring{\\mathrm{A}}$ and $c=13.383\\mathring\\mathrm{A}$ . The visualisation shows two straight channels, two ‘zig–zag’ channels and four intersections per unit cell. The depicted surface is how a methane molecule would feel the adsorption surface. To visualise molecules inside the structure, the pore walls can be rendered transparent. RASPA generates 3D energy landscapes using the free energy obtained from the Widom insertion method. The simulation cell is divided up into, e.g. $150\\times150\\times150$ voxels. The adsorbate is randomly inserted millions of times and the voxels corresponding to the atom positions of the adsorbate are updated with the current Boltzmann weight. The resulting data-set has regions with value $\\langle\\mathrm{e}^{-\\beta U}\\rangle\\approx0$ , which correspond to overlap with the structure. The ratio of the non-zero values to the total number of voxels is the void fraction. Multiplying by the volume of the unit cell, we can compute the pore volume. \n\nFigure 16(b) shows a snapshot of 2,3-dimethylbutane in MFI. To see the molecules themselves, the framework has to be either cut open or rendered transparent. The combination of the snapshot and the transparent framework allows for an analysis of adsorption sites, molecular positions and orientations, and molecule – molecule correlations. Snapshots are useful to detect differences in adsorption sites of the various species. For example, in this system the linear alkanes predominantly adsorb in the channels while the dibranched molecules adsorb first in the intersections. \n\nSnapshots are very useful, but sometimes one needs to examine a large number of them to start to see a pattern. By keeping track of the atomic positions using 3D histograms the ‘density’ can be visualised. Figure 16(c) is the average of many snapshots. Therefore, the density is very convenient to obtain the siting information at the unit cell level. The picture is made using atomic positions (you could also use the centre of mass position) and, therefore, gives information on the average configuration (position and orientation). Using this type of approach we previously showed that average positions and occupations of the adsorption sites of argon and nitrogen in IRMOF-1 match well with experiments.[93] \n\n![](images/8e6634efb96c76e9b5fe12121c41b3081e9b58203f7054540a867a75f8988cf0.jpg) \nFigure 16. (Colour online) Energy landscape of MFI. The MFI unit cell has edge lengths $a=20.022\\mathring\\mathrm{A}$ , $b=19.899\\mathring{\\mathrm{A}}$ and $c=13.383\\mathring\\mathrm{A}$ , with cell angles $\\alpha=\\beta=\\gamma=90^{\\circ}$ . The MFI pore system (a) consists of straight channels running in the c-direction, which are connected via ‘zig–zag’ channels. About $29\\%$ of the structure is void. Colour code: oxygen (red), silicon (yellow). The snapshot (b) and density plot (c) are at $433\\mathrm{K}$ and $100\\mathrm{{kPa}}$ . Pictures adapted from Ref. [89]. \n\n# 11. Conclusions \n\nWe have provided an overview of the algorithms that RASPA implements and showed examples of its application in computing coexistence properties, adsorption isotherms for single and multiple components, selfand collective diffusivities and reaction systems. RASPA is provided as source code under the GPL. The login information for the ‘git’-server can be obtained by emailing one of the authors of this manuscript. RASPA is provided without any kind of support or warranty. It should be viewed as an educational ‘research-code’ that could be useful for researchers working in the field. \n\n# Acknowledgements \n\nThe partition function values for the RxMC propene metathesis were computed by Sayee Prasaad Balaji; Diego A. G´omezGualdro´n provided Figure 7a; Ariana Torres Knoop provided Figure 3; R. Krishna provided the IAST computation in Figure 5. We would like to thank the following people for their help and input to improve the program and for the very helpful discussions about the algorithms: Sayee Prasaad Balaji, Youn-Sang Bae, Xiaoying Bao, Rocı´o Bueno Pe´rez, Nicholas C. Burtch, Tom Caremans, Ana Martı´n Calvo, Yamil Colon, Juan Manuel Castillo Sanchez, Allison Dickey, Tina Du¨ren, Titus van Erp, Denise Ford, Houston Frost, Rachel Getman, Pritha Ghosh, Elena Garcı´a Pe´rez, Gloria Oxford, Sudeep Punnathanam, Almudena Garcia Sanchez, Juan Jose Gutierrez Sevillano, John J. Low, Patrick Merkling, Patrick Ryan, Lev Sarkisov, Ben Sikora, Ariana Torres Knoop, Krista S. Walton, Chris Wilmer, Ozgur Yazaydin and Decai Yu. Very special thanks to Thijs Vlugt. \n\n# Funding \n\nThis material is supported by the Netherlands Research Council for Chemical Sciences (NWO/CW) through a VIDI grant (David Dubbeldam), by the European Research Council through an ERC Starting Grant [grant number ERC-StG-279520] (Sofia Calero), and by the U.S. National Science Foundation Grant [grant number DMR-1308799] (Randall Snurr). \n\n# Disclosure statement \n\nNo potential conflict of interest was reported by the authors. \n\n# Notes \n\n1. Email: scalero@upo.es \n2. Email: don-ellis $@$ northwestern.edu \n3. Email: snurr $@$ northwestern.edu \n\n# References \n\n[1] Gupta A, Chempath S, Sanborn MJ, Clark LA, Snurr RQ. Objectoriented programming paradigms for molecular modeling. Mol. Simulat.. 2003;29:29–46. doi:10.1080/0892702031000065719. \n[2] Chempath S, Du¨ren T, Sarkisov L, Snurr RQ. Experiences with the publicly available multipurpose simulation code, Music. Mol. Simulat. 2013;39:1223–1232. doi:10.1080/08927022.2013.819103. \n[3] Snurr RQ, Hupp JT, Nguyen ST. Prospects for nanoporous metalorganic materials in advanced separations processes. AIChE J. 2004;50:1090–1095. doi:10.1002/aic.10101. \n[4] Long JR, Yaghi OM. The pervasive chemistry of metal-organic frameworks. Chem. Soc. Rev. 2009;38:1213–1214. doi:10.1039/ b903811f. \n[5] Li JR, Ma YG, McCarthy MC, Sculley J, Yu JM, Jeong HK, Balbuena PB, Zhou C. Carbon dioxide capture-related gas adsorption and separation in metal-organic frameworks. Coordin. Chem. Rev. 2011;255:1791–1823. \n[6] Serre C, Millange F, Thouvenot C, Nogue\\`s M, Marsolier G, Loue¨r D, Fe´rey G. Very large breathing effect in the first nanoporous chromium(iii)-based solids: Mil-53 or Cr-III(OH) $\\mathrm{\\{O_{2}C-C_{6}H_{4}.}}$ - $\\mathrm{CO}_{2}\\mathrm{\\cdot}$ $\\{\\mathrm{HO}_{2}\\mathrm{C}\\mathrm{-}\\mathrm{C}_{6}\\mathrm{H}_{4}\\mathrm{-}\\mathrm{CO}_{2}\\mathrm{H}\\}_{\\mathrm{x}}\\mathrm{~H}2\\mathrm{O}_{\\mathrm{y}}.$ J. Am. Chem. Soc. 2002;124: 13519–13526. doi:10.1021/ja0276974. \n[7] Dubbeldam D, Torres-Knoop A, Walton KS. On the inner workings of Monte Carlo codes. Mol. Simulat. 2013;39:1253–1292. \n[8] Dubbeldam D, Snurr RQ. Recent developments in the molecular modeling of diffusion in nanoporous materials. Mol. Simulat. 2007; 33:305–325. doi:10.1080/08927020601156418. [9] Todorov IT, Smith W, Trachenko K, Dove MT. Dl_poly_3: new dimensions in molecular dynamics simulations via massive parallelism. J. Mater. Chem. 2006;16:1911–1918. doi:10.1039/ b517931a. \n[10] Vlugt TJH, Garcia-Perez E, Dubbeldam D, Ban S, Calero S. Computing the heat of adsorption using molecular simulations: The effect of strong coulombic interactions. J. Chem. Theory. Comput. 2008;4:1107–1118. doi:10.1021/ct700342k. \n[11] Linstrom PJ, Mallard WG, editors. NIST Chemistry WebBook, NIST Standard Reference Database Number 69. Gaithersburg MD: National Institute of Standards and Technology; 2014. \n[12] Martin MG, Siepmann JI. Transferable potentials for phase equilibria. 1. United-atom description of n -alkanes. J. Phys. Chem. B. 1998;102: 2569–2577. doi:10.1021/jp972543þ. \n[13] Martin MG, Siepmann JI. Novel configurational-bias Monte Carlo method for branched molecules. transferable potentials for phase equilibria. 2. united-atom description of branched alkanes. J. Phys. Chem. B. 1999;103:4508–4517. doi:10.1021/jp984742e. \n[14] Martin MG. MCCCS Towhee: a tool for Monte Carlo molecular simulation. Mol. Simulat. 2013;39:1212–1222. doi:10.1080/ 08927022.2013.828208. \n[15] Martin MG, Biddy MJ. Monte Carlo molecular simulation predictions for the heat of vaporization of acetone and butyramide. Fluid Phase Equilibria. 2005;236:53–57. doi:10.1016/j.fluid.2005. 06.003. \n[16] Panagiotopoulos AZ. Adsorption and capillary condensation of fluids in cylindrical pores by Monte Carlo simulation in the Gibbs ensemble. Mol. Phys. 1987;62:701 – 719. doi:10.1080/ 00268978700102501. \n[17] Panagiotopoulos AZ, Quirke N, Stapleton NM, Tildesley DJ. Phase equilibria by simulation in the Gibbs ensemble - alternative derivation, generalization and application to mixture and membrane equilibria. Mol. Phys. 1988;63:527–545. doi:10.1080/002689788 00100361. \n[18] Garcia-Sanchez A, Ania CO, Parra JB, Dubbeldam D, Vlugt TJH, Krishna R, Calero S. Transferable force field for carbon dioxide adsorption in zeolites. J. Phys. Chem. C. 2009;113: 8814–8820. \n[19] Guti´errez-Sevillano JJ, Martı´n-Calvo A, Dubbeldam D, Calero S, Hamad S. Adsorption of hydrogen sulphide on metal-organic frameworks. RSC Adv. 2013;3:14737–14749. doi:10.1039/c3ra 41682h. \n[20] Finsy V, Verelst H, Alaerts L, de Vos DE, Jacobs PA, Baron GV, Denayer JEM. Pore-filling-dependent selectivity effects in the vapor-phase separation of xylene isomers on the metal–organic framework MIL-47. J. Am. Chem. Soc. 2008;130:7110–7118. doi: 10.1021/ja800686c. \n[21] Da˛browski A. Adsorption - from theory to practice. Adv. Colloid Interface Sci. 2001;93:135–224. doi:10.1016/S0001-8686(00) 00082-8. \n[22] McGrother SC, Gubbins E. Constant pressure Gibbs ensemble Monte Carlo simulations of adsorption into narrow pores. Mol. Phys. 1999;97:955–965. doi:10.1080/00268979909482897. \n[23] Torres-Knoop A, Krishna R, Dubbeldam D. Separating xylene isomers by commensurate stacking of p-xylene within channels of MAF-X8. Angew. Chem. Int. Ed. 2014;53:7774–7778. doi: 10.1002/anie.201402894. \n[24] Castillo JM, Vlugt TJH, Calero S. Molecular simulation study on the separation of xylene isomers in MIL-47 metal–organic frameworks. J. Phys. Chem. C. 2009;113:20869 – 20874. doi:10.1021/ jp908247w. \n[25] Talu O, Myers AL. Molecular simulation of adsorption: Gibbs dividing surface and comparison with experiment. AIChE. J. 2001; 47:1160–1168. doi:10.1002/aic.690470521. \n[26] D¨uren T, Sarkisov L, Yaghi OM, Snurr RQ. Design of new materials for methane storage. Langmuir. 2004;20:2683–2689. doi:10.1021/ la0355500. \n[27] Hansen N. Multiscale modeling of reaction and diffusion in Zeolites. [PhD thesis], Technische Universita¨t Hamburg, Hamburg, Germany. 2010. \n[28] Vlugt TJH, Smit B. The BIGMAC: A configurational Bias Monte Carlo Program. Amsterdam: University of Amsterdam; 1998. \n[29] Bai P, Tsapatsis M, Siepmann JI. Multicomponent adsorption of alcohols onto silicalite-1 from aqueous solution: isotherms, structural analysis, and assessment of ideal adsorbed solution theory. Langmuir. 2012;28:15566–15576. doi:10.1021/ la303247c. \n[30] Myers AL, Prausnitz JM. Thermodynamics of mixed-gas adsorption. AIChE J. 1965;11:121–127. doi:10.1002/aic.690110125. \n[31] Krishna R, Long JR. Screening metal-organic frameworks by analysis of transient breakthrough of gas mixtures in a fixed bed adsorber. J. Phys. Chem. C. 2011;115:12941–12950. doi:10.1021/ jp202203c. \n[32] Walton KS, Millward AR, Dubbeldam D, Frost H, Low JJ, Yaghi OM, Snurr RQ. Understanding inflections and steps in carbon dioxide adsorption isotherms in metal–organic frameworks. J. Am. Chem. Soc. 2008;130:406–407. doi:10.1021/ja076595g. \n[33] Millward AR. Adsorption of environmentally significant gases $\\left(\\mathrm{H}_{2}\\right)$ $\\mathrm{CO}_{2}$ , $\\mathrm{H}_{2}\\mathrm{S}$ , $\\mathrm{CH}_{4}\\mathrm{,}$ ) in metal-organic frameworks. [PhD thesis]. The University of Michigan, the United States of America. 2006. \n[34] Dubbeldam D, Walton KS, Ellis DE, Snurr RQ. Exceptional negative thermal expansion in isoreticular metal-organic frameworks. Angew. Chem. Int. Ed. 2007;46:4496–4499. doi:10.1002/ anie.200700218. \n[35] Wolf RJ, Lee MW, Davis RC, Fay PJ, Ray JR. Pressure-composition isotherms for palladium hydride. Phys. Rev. B. 1993;48: 12415–12418. doi:10.1103/PhysRevB.48.12415. \n[36] Spyriouni T, Economou IG, Theodorou DN. Phase equilibria of mixtures containing chain molecules predicted through a novel simulation scheme. Phys. Rev. Lett. 1998;80:4466–4469. doi:10. 1103/PhysRevLett.80.4466. \n[37] Duane S, Kennedy AD, Pendleton BJ, Roweth D. Hybrid Monte Carlo. Phys. Lett. B. 1987;195:216–222. doi:10.1016/0370-2693 (87)91197-X. \n[38] Chempath S, Clark LA, Snurr RQ. Two general methods for grand canonical ensemble simulation of molecules with internal flexibility. J. Chem. Phys. 2003;118:7635–7643. doi:10.1063/1. 1562607. \n[39] Rosenbluth MN, Rosenbluth AW. Monte carlo calculation of the average extension of molecular chains. J. Chem. Phys. 1955;23: 356–359. doi:10.1063/1.1741967. \n[40] Siepmann JI. A method for the direct calculation of chemical potentials for dense chain systems. Mol. Phys. 1990;70:1145–1158. doi:10.1080/00268979000101591. \n[41] Laso M, de Pablo JJ, Suter UW. Simulation of phase-equilibria for chain molecules. J. Phys. Condens. Matter. 1992;97:2817–2819. \n[42] Shi W, Maginn EJ. Continuous fractional component Monte Carlo: an adaptive biasing method for open system atomistic simulations. J. Chem. Theory Comput. 2007;3:1451–1463. doi:10.1021/ ct7000039. \n[43] Shi W, Maginn EJ. Improvement in molecule exchange efficiency in Gibbs ensemble Monte Carlo: Development and implementation of the continuous fractional component move. J. Comput. Chem. 2008; 29:2520–2530. doi:10.1002/jcc.20977. \n[44] Rosch TW, Maginn EJ. Reaction ensemble Monte Carlo simulation of complex molecular systems. J. Chem. Theory Comput. 2011;7: 269–279. doi:10.1021/ct100615j. \n[45] Torres-Knoop A, Prasaad Balaji S, Vlugt T, Dubbeldam D. A comparison of advanced Monte Carlo methods for open systems: CFCMC vs. CBMC. J. Chem. Theor. Comp. 2014;10:942–952. \n[46] van Erp TS, Caremans TP, Dubbeldam D, Martin-Calvo A, Calero S, Martens JA. Enantioselective adsorption in achiral zeolites. Angew. Chem. Int. Edit. 2010;49:3010–3013. doi:10.1002/anie. 200906083. \n[47] Qiao Z, Torres-Knoop A, Dubbeldam D, Fairen-Jimenez D, Zhou J, Snurr RQ. Advanced Monte Carlo simulations of the adsorption of chiral alcohols in a homochiral metal-organic framework. AIChE J. 2014;60:2324–2334. doi:10.1002/aic.14415. \n[48] G´omez-Gualdr´on DA, Wilmer CE, Farha OK, Hupp JT, Snurr RQ. Exploring the limits of methane storage and delivery in nanoporous materials. J. Phys. Chem. C. 2014;118:6941–6951. doi:10.1021/ jp502359q. \n[49] Wilmer CE, Leaf M, Lee CY, Farha OK, Hauser BG, Hupp JT, Snurr RQ. Large-scale screening of hypothetical metal-organic frameworks. Nat. Chem. 2012;4:83–89. doi:10.1038/nchem.1192. \n[50] Wilmer CE, Farha OK, Bae YS, Hupp JT, Snurr RQ. Structureproperty relationships of porous materials for carbon dioxide separation and capture. Energy Env. Sci. 2012;5:9849–9856. doi: 10.1039/c2ee23201d. \n[51] Col´on YJ, Snurr RQ. High-throughput computational screening of metal-organic frameworks. Chem. Soc. Rev. 2014;43:5735–5749. doi:10.1039/C4CS00070F. \n[52] Sikora BJ, Winnegar R, Proserpio DM, Snurr RQ. Textural properties of a large collection of computationally constructed MOFs and zeolites. Microporous Mesoporous Mater. 2014;186: 207–213. doi:10.1016/j.micromeso.2013.11.041. \n[53] Dubbeldam D, Krishna R, Calero S, Yazaydın O. Computer-assisted screening of ordered crystalline nanoporous adsorbents for separation of alkane isomers. Angew. Chem. Int. Ed. 2012;51: 11867–11871. doi:10.1002/anie.201205040. \n[54] Johnson JK, Panagiotopoulos AZ, Gubbins KE. Reactive canonical Monte Carlo: a new simulation technique for reacting or associating fluids. Mol. Phys. 1994;81:717 – 733. doi:10.1080/ 00268979400100481. \n[55] Smith WR, Triska B. The reaction ensemble method for the computer simulation of chemical and phase equilibria. i. theory and basic examples. J. Chem. Phys. 1994;100:3019. doi:10.1063/1. 466443. \n[56] Hansen N, Jakobtorweihen S, Keil FJ. Reactive Monte Carlo and grand-canonical Monte Carlo simulations of the propene metathesis reaction system. J. Chem. Phys. 2005;122:164705. doi:10.1063/1. 1884108. \n[57] Wittcoff HA, Reuben BG, Plotkin JS. Industrial Organic Chemicals. Hoboken NJ: Wiley; 2004. \n[58] Jakobtorweihen S, Hansen N, Keil FJ. Combining reactive and configurational-bias Monte Carlo: Confinement influence on the propene metathesis reaction system in various zeolites. J. Chem. Phys. 2006;125:224709. doi:10.1063/1.2404658. \n[59] Dubbeldam D, Ford DC, Ellis DE, Snurr RQ. A new perspective on the order-n algorithm for computing correlation functions. Mol. Simulat. 2009;35:1084–1097. \n[60] Reed DA, Ehrlich G. Surface diffusivity and the time correlation of concentration fluctuations. Surf. Sci. 1981;105:603–628. doi:10. 1016/0039-6028(81)90021-2. \n[61] Krishna R, van Baten JM. Describing binary mixture diffusion in carbon nanotubes with the Maxwell – Stefan equations. An investigation using molecular dynamics simulations. Ind. Eng. Chem. Res. 2006;45:2084–2093. doi:10.1021/ie051126d. \n[62] Krishna R, van Baten JM. Diffusion of alkane mixtures in zeolites: validating the Maxwell–Stefan formulation using md simulations. J. Phys. Chem. B. 2005;109:6386–6396. doi:10.1021/jp044257l. \n[63] Theodorou DN, Snurr RQ, Bell AT. Molecular dynamics and diffusion in microporous materials. In: Alberti G, Bein T, editors. Comprehensive Supramolecular Chemistry. volume 7, chapter 18 Oxford: Pergamon Oxford; 1996. p. 507–548. \n[64] June RL, Bell AT, Theodorou DN. Molecular dynamics study of methane and xenon in silicalite. J. Phys. Chem. 1990;94: 8232–8240. doi:10.1021/j100384a047. \n[65] Snurr RQ, June RL, Bell AT, Theodorou DN. Molecular simulations of methane adsorption in silicalite. Mol. Simulat. 1991;8:73–92. doi:10.1080/08927029108022468. \n[66] Lekien F, Marsden J. Tricubic interpolation in three dimensions. Int. J. Numer. Methods Eng. 2005;63:455–471. doi:10.1002/nme.1296. \n[67] Miller TF, Eleftheriou M, Pattnaik P, Ndirango A, Newns D, Martyna GJ. Symplectic quaternion scheme for biophysical molecular dynamics. J. Chem. Phys. 2002;116:8649–8659. doi: 10.1063/1.1473654. \n[68] Tuckerman ME, Alejandre J, L´opez-rend´on R, Jochim AL, Martyna GJ. A Liouville-operator derived measure-preserving integrator for molecular dynamics simulations in the isothermal –isobaric ensemble. J. Phys. A. 2006;39:5629–5651. doi:10.1088/0305- 4470/39/19/S18. \n[69] Skoulidas AI, Sholl DS. Self-diffusion and transport diffusion of light gases in metal-organic framework materials assessed using molecular dynamics simulations. J. Phys. Chem. B. 2005;109: 15760–15768. doi:10.1021/jp051771y. \n[70] Martyna GJ, Tuckerman M, Tobias DJ, Klein ML. Explicit reversible integrators for extended systems dynamics. Mol. Phys. 1996;87:1117–1157. doi:10.1080/00268979600100761. \n[71] Yu T-Q, Alejandre J, Lo´pez-rend´on R, Martyna GJ, Tuckerman ME. Measure-preserving integrators for molecular dynamics in the isothermal-isobaric ensemble derived from the Liouville operator. Chem. Phys. 2010;370:294–305. doi:10.1016/j.chemphys.2010.02. 014. \n[72] Frenkel D, Smit B. Understanding molecular simulation 2nd ed. London: Academic Press; 2002. \n[73] Beerdsen E, Smit B, Dubbeldam D. Molecular simulation of loading dependent slow diffusion in confined systems. Phys. Rev. Lett. 2004;93:248301. doi:10.1103/PhysRevLett.93.248301. \n[74] Dubbeldam D, Beerdsen E, Vlugt TJH, Smit B. Molecular simulation of loading-dependent diffusion in nanoporous materials using extended dynamically corrected transition state theory. J Chem Phys. 2005;122:224712. doi:10.1063/1.1924548. \n[75] Walton KS, Snurr RQ. Applicability of the BET method for determining surface areas of microporous metal–organic frameworks. J. Am. Chem. Soc. 2007;129:8552–8556. doi:10.1021/ja071174k. \n[76] D¨uren T, Millange F, Fe´rey G, Walton KS, Snurr RQ. Calculating geometric surface areas as a characterization tool for metal–organic frameworks. J. Phys. Chem. C. 2007;111:15350–15356. doi:10. 1021/jp074723h. \n[77] Sarkisov L, Harrison A. Computational structure characterisation tools in application to ordered and disordered porous materials. Mol. Phys. 2011;37:1248–1257. \n[78] Gelb LD, Gubbins KE. Pore size distributions in porous glasses: a computer simulation study. Langmuir. 1999;15:305–308. doi:10. 1021/la9808418. \n[79] Fletcher AJ, Thomas KM, Rosseinsky MJ. Flexibility in metalorganic framework materials: Impact on sorption properties. J. Solid State Chem. 2005;178:2491–2510. doi:10.1016/j.jssc. 2005.05.019. \n[80] Gale JD. Gulp: A computer program for the symmetry-adapted simulation of solids. J. Chem. Soc. Faraday Trans. 1997;93: 629–637. doi:10.1039/a606455h. \n[81] Gale JD, Rohl AL. The general utility lattice program (gulp). Mol. Sim. 2003;29:291–341. doi:10.1080/0892702031000104887. \n[82] Schr¨oder K-P, Sauer J. Potential functions for silica and zeolite catalysts based on ab initio calculations. 3. a shell model ion pair potential for silica and aluminosilicates. J. Phys. Chem. 1996;110: 11043–11049. \n[83] Dubbeldam D, Krishna R, Snurr RQ. Method for analyzing structural changes of flexible metal 2 organic frameworks induced by adsorbates. J. Phys. Chem. C. 2009;113:19317–19327. doi:10. 1021/jp906635f. \n[84] van Workum K, Gao G, Schall JD, Harrison JA. Expressions for the stress and elasticity tensors for angle-dependent potentials. J. Chem. Phys. 2006;125:144506. doi:10.1063/1.2338522. \n[85] Lutsko JF. Generalized expressions for the calculation of elastic constants by computer simulation. J. Appl. Phys. 1989;65: 2991–2997. doi:10.1063/1.342716. \n[86] Oxford GAE, Dubbeldam D, Broadbelt LJ, Snurr RQ. Elucidating steric effects on enantioselective epoxidation catalyzed by (salen) Mn in metal-organic frameworks. J. Mol. Catal. A. 2011;334: 89–97. doi:10.1016/j.molcata.2010.11.001. \n[87] Jacobsen H, Cavallo L. A possible mechanism for enantioselectivity in the chiral epoxidation of olefins with [Mn(salen)] catalysts. Chem. Eur. J. 2001;7:800–807. doi:10.1002/1521-3765(20010216) $7.4<800$ :AID-CHEM800.3.0.CO;2-1. \n[88] Dubbeldam D, Oxford GAE, Krishna R, Broadbelt LJ, Snurr RQ. Distance and angular holonomic constraints in molecular simulations. J. Chem. Phys. 2010;133:034114. doi:10.1063/1. 3429610. \n[89] Dubbeldam D, Walton KS. On the application of classical molecular simulations of adsorption in metal-organic frameworks. In: Jianwen J, editor. Metal-organic frameworks: materials modeling towards engineering applications. Pan Stanford Publishing Pte Ltd; 2014. \n[90] Snurr RQ, Bell AT, Theodorou DN. Prediction of adsorption of aromatic hydrocarbons in silicalite from grand canonical Monte Carlo simulations with biased insertions. J. Phys. Chem. 1993;97: 13742–13752. doi:10.1021/j100153a051. \n[91] Schroeder W, Martin K, Lorensen B. The Visualization Toolkit: an object-oriented approach to 3D graphics. Upper Saddle River, New Jersey: Prentice-Hall,Inc; 1996. p. 07458. \n[92] Dubbeldam D, Galvin CJ, Walton KS, Ellis DE, Snurr RQ. Separation and molecular-level segregation of complex alkane mixtures in metal 2 organic frameworks. J. Am. Chem. Soc. 2008; 130:10884–10885. doi:10.1021/ja804039c. \n[93] Dubbeldam D, Frost H, Walton KS, Snurr RQ. Molecular simulation of adsorption sites of light gases in the metal-organic framework IRMOF-1. Fluid Phase Equilibria. 2007;261:152–161. doi:10.1016/j.fluid.2007.07.042. " + }, + { + "id": "10.1126_sciadv.1501170", + "DOI": "10.1126/sciadv.1501170", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.1501170", + "Relative Dir Path": "mds/10.1126_sciadv.1501170", + "Article Title": "Efficient luminescent solar cells based on tailored mixed-cation perovskites", + "Authors": "Bi, DQ; Tress, W; Dar, MI; Gao, P; Luo, JS; Renevier, C; Schenk, K; Abate, A; Giordano, F; Baena, JPC; Decoppet, JD; Zakeeruddin, SM; Nazeeruddin, MK; Grätzel, M; Hagfeldt, A", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "We report on a new metal halide perovskite photovoltaic cell that exhibits both very high solar-to-electric power-conversion efficiency and intense electroluminescence. We produce the perovskite films in a single step from a solution containing a mixture of FAI, PbI2, MABr, and PbBr2 (where FA stands for formamidinium cations andMA stands for methylammonium cations). Using mesoporous TiO2 and Spiro-OMeTAD as electron-and hole-specific contacts, respectively, we fabricate perovskite solar cells that achieve a maximum power-conversion efficiency of 20.8% for a PbI2/FAImolar ratio of 1.05 in the precursor solution. Rietveld analysis of x-ray diffraction data reveals that the excess PbI2 content incorporated into such a film is about 3 wt %. Time-resolved photoluminescence decay measurements show that the small excess of PbI2 suppresses nonradiative charge carrier recombination. This in turn augments the external electroluminescence quantum efficiency to values of about 0.5%, a record for perovskite photovoltaics approaching that of the best silicon solar cells. Correspondingly, the open-circuit photovoltage reaches 1.18 V under AM 1.5 sunlight.", + "Times Cited, WoS Core": 1672, + "Times Cited, All Databases": 1748, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000376972900023", + "Markdown": "# A P P L I E D O P T I C S \n\n# Efficient luminescent solar cells based on tailored mixed-cation perovskites \n\nDongqin Bi,1 Wolfgang Tress,2\\* M. Ibrahim Dar,2,3 Peng Gao,3 Jingshan Luo,2 Clémentine Renevier,2 Kurt Schenk,4 \nAntonio Abate,2 Fabrizio Giordano,2 Juan-Pablo Correa Baena,1 Jean-David Decoppet,2 \nShaik Mohammed Zakeeruddin,2 Mohammad Khaja Nazeeruddin,3 Michael Grätzel,2 Anders Hagfeldt1 \n\nWe report on a new metal halide perovskite photovoltaic cell that exhibits both very high solar-to-electric powerconversion efficiency and intense electroluminescence. We produce the perovskite films in a single step from a solution containing a mixture of FAI, $\\left.\\mathsf{P b l}_{2},\\right.$ MABr, and $\\mathsf{P b B r}_{2}$ (where FA stands for formamidinium cations and MA stands for methylammonium cations). Using mesoporous $\\bar{\\mathsf{T i O}}_{2}$ and Spiro-OMeTAD as electron- and hole-specific contacts, respectively, we fabricate perovskite solar cells that achieve a maximum power-conversion efficiency of $20.8\\%$ for a $\\mathsf{P b l}_{2}/\\mathsf{F A l}$ molar ratio of 1.05 in the precursor solution. Rietveld analysis of x-ray diffraction data reveals that the excess $\\mathsf{P b l}_{2}$ content incorporated into such a film is about 3 wt $\\%$ . Time-resolved photoluminescence decay measurements show that the small excess of $\\mathsf{P b l}_{2}$ suppresses nonradiative charge carrier recombination. This in turn augments the external electroluminescence quantum efficiency to values of about $0.5\\%,$ a record for perovskite photovoltaics approaching that of the best silicon solar cells. Correspondingly, the open-circuit photovoltage reaches 1.18 V under AM 1.5 sunlight. \n\n# INTRODUCTION \n\nMetal halide perovskites of the composition $\\mathrm{ABX}_{3}$ $\\mathrm{[A=Cs^{+}}$ , $\\mathrm{CH}_{3}\\mathrm{NH}_{3}^{+}$ (MA), or ${\\mathrm{NH}}{=}\\mathrm{CHNH}_{3}{}^{+}$ (FA); $\\mathbf{B}=\\mathrm{Pb}$ or Sn $\\mathbf{\\boldsymbol{\\;}}\\mathrm{{X}}=\\mathrm{{Br,}}\\mathrm{{I}}]$ have recently attracted strong research interest because of their outstanding photovoltaic properties (1). The development was triggered by the reports of Kojima et al. (2) and Im et al. (3) on liquid electrolyte-based quantum dot solar cells. Adoption of solid-state hole conductor and new deposition techniques (4–8) boosted the power-conversion efficiency (PCE) from $3\\%$ (2) to the present record of $20.1\\%$ (8). The latter was reached with perovskites using mixtures of A and X ions with a general formula of $\\mathrm{FA}_{1-x}\\mathrm{MA}_{x}\\mathrm{Pb}(\\mathrm{I}_{1-y}\\mathrm{Br}_{y})_{3}.$ , pioneered by Pellet et al. (9) and Jeon et al. (10). \n\nAlthough the current PCE of $20.1\\%$ is impressive, the open-circuit voltage $(V_{\\mathrm{OC}})$ of these solar cells remains below $1.1\\mathrm{V}$ , which is lower than their theoretical $V_{\\mathrm{OC}}$ limit of $1.32\\mathrm{V}$ (for $\\mathrm{MAPbI}_{3}$ ) in AM $1.5\\mathrm{G}$ sunlight $(l l)$ . The loss of more than $200~\\mathrm{mV}$ arises from nonradiative recombination of photogenerated charge carriers and manifests itself in a low external quantum yield $(\\lessapprox0.01\\%)$ for electroluminescence measured at a forward bias potential corresponding to $V_{\\mathrm{OC}}\\left(l l,\\ l2\\right)$ . Reducing nonradiative recombination would pave the way for higher $V_{\\mathrm{OC}}$ and PCE values. Recent attempts toward this end used additives such as phenyl- $\\mathrm{C}_{61}$ -butyric acid methyl ester (PCBM) (13), oxygen (14), and $\\mathrm{PbI}_{2}$ (15–19). Cao et al. (19) maintained unreacted $\\mathrm{PbI}_{2}$ during sequential deposition (7) of $\\mathrm{MAPbI}_{3}$ on a mesoporous $\\mathrm{TiO}_{2}$ scaffold, causing an increase in $V_{\\mathrm{OC}}$ of up to $1.036\\mathrm{~V~}$ $\\mathrm{(PCE=9.7\\%}$ ) at a residual $\\mathrm{PbI}_{2}$ level of $1.7\\%$ . This was ascribed to elimination of surface states by $\\mathrm{PbI}_{2}$ , in agreement with photovoltage spectroscopy measurements that also point to a decrease in $\\mathrm{MAPbI}_{3}$ defect states by unreacted $\\mathrm{PbI}_{2}$ (18). Similar beneficial effects have been ascribed by \n\nChen et al. (15) and Pathak et al. (20) to the surface enrichment of $\\mathrm{PbI}_{2}$ formed by thermal decomposition of $\\mathbf{MAPbI}_{3}$ . In contrast, Shao et al. (13) found that such $\\mathrm{PbI}_{2}$ -enriched perovskite layers are $\\mathfrak{n}$ -doped and contain a high level of defects that were eliminated by the deposition of a PCBM overlayer. In most of these cases, the influence of excess $\\mathrm{PbI}_{2}$ was studied using devices with poor or moderate performance $(\\mathrm{PCE}\\lessapprox12\\%$ ). Hence, it appears that it is difficult to attribute these sometimes contradictory effects to the mere presence of excess $\\mathrm{PbI}_{2}$ . \n\n# RESULTS \n\nHere, we report for the first time on a perovskite solar cell (PSC) using a new $\\mathrm{PbI}_{2}$ -enriched composition that exhibits both very high solar-to-electric PCE and intense electroluminescence. We produce the mixed-cation mixed-halide perovskite films in a single step from a solution of FAI, $\\mathrm{PbI}_{2}$ , MABr, and $\\mathrm{Pb}\\mathrm{Br}_{2}$ in a mixed solvent containing dimethyl formamide (DMF) and dimethyl sulfoxide (DMSO). We vary the molar ratio for $\\mathrm{PbI}_{2}/\\mathrm{FAI}$ $(R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}})$ from 0.85 to 1.54 while maintaining a fixed molar ratio of 5.67 for $\\mathrm{PbI}_{2}/\\mathrm{PbBr}_{2}$ in the precursor solutions. By using this technique, we fabricate PSC with the structure Au/Spiro-OMeTAD/perovskite/ mesoporous $\\mathrm{TiO}_{2}/$ compact $\\mathrm{TiO}_{2}/\\mathrm{FTO}$ . We achieve the highest PCE $(20.8\\%)$ with $R_{\\mathrm{PbI_{2}/F A I}}=1.05$ , corresponding to a $3\\%$ weight excess of $\\mathrm{PbI}_{2}$ in the perovskite. The photovoltaic metrics of the device are as follows: short-circuit current density $(J_{\\mathrm{SC}})=24.6~\\mathrm{mA}~\\mathrm{cm}^{-2}$ , open-circuit voltage $(V_{\\mathrm{OC}})=1.16~\\mathrm{V}_{\\mathrm{:}}$ , and fill factor $\\mathrm{(FF)}=0.73$ (Fig. 1A). By integrating the incident photon-to-electron conversion efficiency (IPCE) spectrum over the AM 1.5 photon flux, we obtain $J_{\\mathrm{SC}}$ values that agree within $4\\%$ of the measured values. One of the devices was sent for certification to Newport Corporation, an accredited photovoltaic testing laboratory, confirming PCEs of $19.90\\%$ (backward scan) and $19.73\\%$ (forward scan) with a $J_{\\mathrm{SC}}$ of $23.2\\mathrm{mA}\\mathrm{cm}^{-2}$ and a $V_{\\mathrm{OC}}$ of $1.13\\mathrm{V}$ (fig. S1). The normalized IPCE spectrum is shown in fig. S1 as well. The commonly observed hysteresis (13, 21) is not pronounced in our devices, as proven by $J{-}V$ curves shown in Fig. 1C (table S1), where the voltage sweep rate was varied from 10 to $\\mathrm{\\bar{5}000\\ m V\\ s^{-1}}$ . A crosssectional scanning electron microscopy (SEM) image of a champion PSC is shown in Fig. 1B, visualizing a thick perovskite capping layer of around $500\\mathrm{nm}$ . A histogram of 40 devices (figs. S2 and S3) indicates good performance reproducibility, with an average PCE of $19.5\\%$ . A preliminary stability investigation shows that the devices stored in the dark at room temperature are relatively stable, with a PCE drop of only $0.3\\%$ for 1 month (fig. S4 and table S2). \n\n![](images/5a0f49e1cf693b2842067f54e5567d5766e803545ffab5788c1e96b8b7461b31.jpg) \nFig. 1. Basic characteristics of fabricated perovskite solar cells. (A) $J_{-}V$ curves for the champion solar cell under AM $1.5\\mathsf{G}$ illumination, measured from $V_{\\mathrm{OC}}$ to JSC. (B) Cross-sectional SEM image of the champion cell. (C) Hysteresis measurements of one PSC at different scanning speeds under AM 1.5 G illumination. \n\nThe photovoltaic metrics of the PSCs made by varying $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}$ in the precursor solution are summarized in Fig. 2 (A to D). For $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}<1$ or $R_{\\mathrm{PbI_{2}/F A I}}>1.23$ , the device performance deteriorates considerably. However, in the range of $R_{\\mathrm{PbI_{2}/F A I}}=1{-}1.16,$ $J_{\\mathrm{SC}}$ and FF show a plateau, whereas $V_{\\mathrm{OC}}$ increases substantially, reaching a maximum of $1.17\\mathrm{V}$ at $R_{\\mathrm{PbI_{2}/F A I}}=~1.16$ $1.18{\\mathrm{V}}$ without aperture; see discussion in Materials and Methods). This is the highest $V_{\\mathrm{OC}}$ observed so far for lead iodide–based PSCs on mesoporous $\\mathrm{TiO}_{2}$ , resulting in a PCE larger than $19\\%$ . During the rise of $V_{\\mathrm{OC}},J_{\\mathrm{SC}}$ maintains a large value (more than $23\\mathrm{\\mA\\cm}^{-2}$ ) because the band gap does not alter strongly for the different perovskite compositions, as shown by the absorbance spectra in fig. S5. The FF is around 0.72, indicating that a moderate excess of $\\mathrm{PbI}_{2}$ does not retard charge collection, which is efficient in these mixed perovskites, allowing for the use of ${500}\\mathrm{-nm}$ capping layers to obtain a sharp IPCE onset and extraordinarily high photocurrents. Thus, overstoichiometric $\\mathrm{Pb}\\mathrm{I}_{2}$ in this range does not strongly influence the composition and optical properties of the perovskite films but improves their electronic quality. This allows for simultaneously high $J_{\\mathrm{SC}}$ and $V_{\\mathrm{OC}}$ but avoids the commonly observed “tradeoff” between $V_{\\mathrm{OC}}$ and $J_{\\mathrm{SC}}$ when tuning the band gap (22, 23). In the following sections, we quantify and characterize the $\\mathrm{PbI}_{2}$ content remaining in the film. Subsequently, we investigate the role of $\\mathrm{PbI}_{2}$ in reducing nonradiative recombination. \n\n![](images/592ceaf5247ef61db56f86d4f6adb8aa091f15ddc9cb71ddbd8996332ea41b6f.jpg) \nFig. 2. Influence and characterization of remnant $\\left|\\mathsf{P}\\mathbf{b}\\right|_{2}$ in the fabricated solar cells and films as a function of the ratio between $\\left|\\mathsf{P b l}_{2}\\right.$ and FAI in the precursor solution. (A to D) Photovoltaic parameters $J_{\\mathsf{S C}}$ (A), $V_{\\mathrm{{OC}}}$ (B), FF $(\\mathsf{C}),$ and PCE (D) versus $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}},$ measured under AM $1.5\\mathsf{G}$ illumination $(100\\mathrm{\\mw\\cm^{-2}})$ . (E) Fraction of remnant $\\mathsf{P b l}_{2}$ (left axis, orange line) and relative perovskite absorbance (right axis, blue line). (F) Mean crystallite sizes of $\\mathsf{F A P b l}_{3}$ (left axis, green line) and $\\mathsf{P b l}_{2}$ (left axis, orange line) phases determined by Rietveld refinement of thin-film XRD patterns and mean crystallite size ratio of $\\mathsf{P b l}_{2}/\\mathsf{F A l}$ (right axis). \n\nSEM images of perovskite films deposited on a mesoporous $\\mathrm{TiO}_{2}/$ compact $\\mathrm{TiO}_{2}/\\mathrm{FTO}$ substrate with varied $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}$ are shown in fig. S6. The film morphology changes when $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}<1$ and $R_{\\mathrm{PbI_{2}/F A I}}>1.23$ indicating a modification of the perovskite morphology or the appearance of new phases. To further explore the film composition, we conducted thin-film $\\mathbf{x}$ -ray diffraction (XRD) measurements for perovskite films deposited again on mesoporous $\\mathrm{TiO}_{2},$ /compact $\\mathrm{TiO}_{2}$ /FTO substrates (table S3 and figs. S7 and S8). Except for the sample with $R_{\\mathrm{PbI_{2}/F A I}}=0.85$ , a peak at $12.5^{\\circ}$ is observed, which is attributed to the (001) lattice planes of hexagonal $2H$ polytype) $\\mathrm{PbI}_{2}$ . The $\\mathrm{PbI}_{2}$ content (Fig. 2E) increases with $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}$ , showing a $3.8\\%$ excess in weight for the most efficient device $(R_{\\mathrm{PbI_{2}/F A I}}=1.05)$ and a $7.5\\%$ excess in weight for the highest $V_{\\mathrm{OC}}$ device $(R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}=1.16)$ ) (table S1). These values are close to those expected from the molar ratios of the precursors in the spincoating solution, which correspond to approximately 3 and 10 wt $\\%$ , respectively. The relative amount of perovskite (Fig. 2E) deduced from absorption measurements shows a reverse trend as compared with the remnant $\\mathrm{PbI}_{2}$ but follows the $J_{\\mathrm{SC}}$ values (Fig. 2A), indicating that losses in $J_{\\mathrm{SC}}$ are due to reduced light harvesting rather than reduced charge collection. Because the thicknesses of all perovskite films are similar (fig. S9), the changes in absorbance indicate a significant ratio of nonperovskite material. The opposite trends in the mean crystallite sizes of $\\mathrm{PbI}_{2}$ and perovskite (Fig. 2F) could be due to the competitive expansion of two crystal domains. Coincidentally, the mean crystallite size of the perovskite phase follows the same trend as $V_{\\mathrm{OC}}$ (shown in Fig. 2B). The trend in the crystallite size ratio of $\\mathrm{PbI}_{2}$ and perovskite (Fig. 2F) mirrors that of $V_{\\mathrm{OC}}$ and reaches 0.35 for the film with the highest $V_{\\mathrm{OC}}.$ . Thus, excess $\\mathrm{PbI}_{2}$ not only exists as a crystalline phase but also influences the morphology and crystallite size of the perovskite phase. The observed correlation of the opencircuit voltage with the mean crystallite size is likely due to the fact that larger perovskite crystallites exhibit a reduced area of grain boundaries. Consequently, the overall density of defect states is lower. \n\n# DISCUSSION \n\nTo study the electronic quality of the device and to identify the recombination mechanisms limiting $V_{\\mathrm{OC};}$ we performed electroluminescence measurements in which we applied a forward bias to the solar cell in the dark and operated it as a light-emitting diode (LED). Figure 3A contains data for the device $(R_{\\mathrm{PbI_{2}/F A I}}=1.16)$ , with a $V_{\\mathrm{OC}}$ of $1.18\\mathrm{V}$ . The blue curve shows injection current versus voltage, where the signature of a shunt for low voltages is followed by an exponential region dominated by recombination in the device. For voltages larger than $1.2~\\mathrm{V}_{:}$ , limitations by the series resistance become apparent. The red curve shows the emitted photon flux, which increases exponentially with voltage. The diode ideality factor derived from the “slope” is approximately 2 for the current and 1 for the emitted photon flux, indicating that much of the recombination happens through defects [Shockley-Read-Hall (SRH)], whereas emission originates from bandto-band recombination. The external electroluminescence quantum efficiency $(\\mathrm{EQE_{\\mathrm{EL}}})$ increases linearly with injection current (fig. S10), as expected from a device with an ideality factor of 2 (24), and approaches $0.5\\%$ for currents in the range of $J_{\\mathrm{SC}}$ . This value translates into a voltage loss of $k T/e\\ln(\\mathrm{1/EQE_{EL}})=0.14\\mathrm{~V},$ confirming the measured $V_{\\mathrm{OC}}=1.32~\\mathrm{V}-0.14~\\mathrm{V}=1.18~\\mathrm{V}$ [where $1.32\\mathrm{V}$ is the theoretical maximum $V_{\\mathrm{OC}}$ (radiative limit)], which we determined for this solar cell using its IPCE action spectrum and following the approach of Tress et al. $(l l)$ . \n\nAn $\\mathrm{EQE_{EL}}$ of $0.5\\%$ is a record for solution-processed solar cells such as organics, where it is commonly $<10^{-6}$ (25), and approaches that of the best silicon solar cells (26). Even when compared to perovskitebased LEDs, our $\\mathrm{EQE_{EL}}$ is among the highest. Our solar cell LED delivers an overall electric power to light conversion efficiency of as high as $0.5\\%$ at a voltage of $1.5\\mathrm{V}$ (which is still below $E_{\\mathrm{g}}/e)$ , whereas reported LEDs show the same efficiency at voltages higher than 3 to $4\\mathrm{V}$ (27, 28). An LED efficiency of $3.5\\%$ has been obtained recently, but under much larger charge carrier densities [that is, not under solar cell operating conditions $(2.2~\\mathrm{V},160~\\mathrm{mA}~\\mathrm{cm}^{-2}$ , and $50\\mathrm{-nm}$ layer thickness)] (29). Our high $\\mathrm{EQE_{EL}}$ indicates a high-quality perovskite film and a very good charge selectivity of the contacts, accompanied by a high built-in potential and/or very balanced injection and transport of electrons and holes. \n\nTo analyze the dynamics of recombination, we performed timecorrelated single photon counting (TCSPC) measurements at different excitation fluences. The photoluminescence (PL) decays for perovskite films with $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}=1$ and $R_{\\mathrm{PbI_{2}/F A I}}=1.16$ deposited on mesoporous $\\mathrm{TiO}_{2}$ /compact $\\mathrm{TiO}_{2}/\\mathrm{FTO}$ substrate are shown in Fig. 3 (B and C) (for all samples in figs. S11 and S12). \n\nFor the highest light intensity generating approximately $n=2\\times{10}^{17}$ charges per cubic centimeter, the overall decay becomes faster as a result of direct electron-hole recombination, where the recombination coefficient $\\upbeta\\approx2...4\\times10^{-11}\\mathrm{cm}^{3}\\mathrm{s}^{-1}$ in $d n/d t=-\\upbeta n^{2}-k n$ describes radiative recombination resulting in the expected $V_{\\mathrm{OC}}$ of ${\\approx}1.3\\mathrm{V}$ (derivation in Materials and Methods). For long time scales or decreased excitation intensity, the PL shows monoexponential decay characteristic of SRH recombination. We deduced 220 and 350 ns, respectively, as nonradiative lifetimes $1/k$ for the two perovskite films with $R_{\\mathrm{PbI}_{2}/\\mathrm{FAI}}=1$ and $R_{\\mathrm{PbI_{2}/F A I}}=1.16$ , consistent with the trend in $V_{\\mathrm{OC}}.$ In addition, the signal drops strongly in the first few nanoseconds as a result of trap filling. The loss of $\\mathrm{PL}$ is more significant for the stoichiometric device, in particular when illuminated from the $\\mathrm{TiO}_{2}$ side. This indicates that the trap density is lower for $R_{\\mathrm{PbI_{2}/F A I}}=1.16$ as a result of either a better passivation of traps at the perovskite $\\mathrm{\\DeltaTiO}_{2}$ interface or a better quality of the perovskite crystallites. \n\nTo further elucidate this, we investigate $V_{\\mathrm{OC}}$ as a function of illumination intensity, represented by $J_{\\mathrm{SC}}$ in Fig. 3D $(J_{\\mathrm{SC}}\\propto$ intensity). The dashed lines visualizing the theoretical slope for SRH recombination indicate that $V_{\\mathrm{OC}}$ is mainly limited by SRH recombination. The device with $R_{\\mathrm{PbI_{2}/F A I}}=1.16$ shows a reduced slope toward higher intensities. This is consistent with the bending seen in $\\mathrm{EQE_{EL}}$ as a function of injection current (fig. S10). Because $V_{\\mathrm{OC}}$ is still below the radiative limit, this reduced slope is most likely due to losses of charges at a nonperfectly selective contact. \n\n![](images/c4a7b582b93a2b726cf12a8732c001bfd150ddb4aa9001a839746f84a7294b0e.jpg) \nFig. 3. Characterization of recombination mechanisms and rates. (A) Current-voltage curve in the dark (blue), emitted photon flux (red), and external electroluminescence quantum efficiency $(\\mathsf{E Q E}_{\\mathsf{E L}})$ (green) of a device with $R_{\\mathrm{PbI_{2}/F A I}}=~1.16.$ . Lines are a guide to the eye, indicating the slopes for an ideality factor of 2 and 1, respectively, assuming a temperature of $3201.$ au, arbitrary units. (B and C) PL decay for a film with $R_{\\mathrm{PbI_{2}/F A I}}=~1.0$ and $R_{\\mathrm{PbI_{2}/F A I}}=1.16$ . Lines are calculated according to the rate equation in the text. (D) $V_{\\mathrm{OC}}$ as a function of short-circuit current $I_{S C}$ proportional to the light intensity, which was varied for blue and red illuminations. \n\nWe use illumination with different wavelengths to tune the absorption profile in the perovskite film. Because of the strong dependence of the absorption coefficient on wavelength (fig. S5), red light $(630~\\mathrm{nm})$ and blue light $(460\\mathrm{nm})$ penetrate the film to varied extent: $90\\%$ of the blue light is absorbed over a distance ${<}200\\ \\mathrm{nm}$ away from FTO, whereas red light penetrates much farther. Figure 3D shows a significant difference only for the stoichiometric device, where $V_{\\mathrm{OC}}$ is lower for blue illumination despite the fact that the generated charge carrier density is higher. This is in accordance with the PL decay and proves that this device shows its highest defect density close to $\\mathrm{TiO}_{2}$ , the impact of which is reduced in the presence of overstoichiometric $\\mathrm{PbI}_{2}$ . \n\nFrom the PL decay and the monochromatic $V_{\\mathrm{OC}}$ study, we contend that the role of excess $\\mathrm{PbI}_{2}$ is to reduce recombination close to the perovskite $/\\mathrm{TiO}_{2}$ interface. Thus, $\\mathrm{PbI}_{2}$ crystallites, which are located within the mesoporous $\\mathrm{TiO}_{2}$ scaffold, prevent recombination of holes photogenerated in this region of the absorber. Furthermore, $\\mathrm{PbI}_{2}$ crystallites, which are present within the mesoporous $\\mathrm{TiO}_{2}$ layer, favor the growth of bigger perovskite crystallites, which exhibit a reduced area of grain boundaries and, therefore, fewer defects. \n\nTo conclude, we have shown that an excess of $\\mathrm{PbI}_{2}$ of up to ${\\approx}8{}$ wt $\\%$ can enhance the electronic quality of the perovskite $\\slash\\mathrm{TiO}_{2}$ film. With the adoption of this approach, devices based on mixed perovskite enabled a PCE of $20.8\\%$ and an open-circuit voltage of $1.18\\mathrm{V}$ , accompanied by a high external electroluminescence quantum efficiency of $0.5\\%$ , which is attributed to reduced recombination via defects due to a moderate excess of $\\mathrm{PbI}_{2}$ . Further optimization along this path will lead to solution-processed solar cells approaching the theoretical limits for open-circuit voltage and efficiency. \n\n# MATERIALS AND METHODS \n\n# Materials \n\nAll materials were purchased from Sigma-Aldrich and used as received, unless stated otherwise. \n\n# Synthesis of inorganic/organic halide materials \n\n$\\mathrm{NH}{=}\\mathrm{CHNH}_{3}\\mathrm{I}$ was synthesized by slowly dropping $15~\\mathrm{ml}$ of hydroiodic acid (45 wt $\\%$ in water) (Applichem) to a solution of $_{5\\mathrm{~g~}}$ of formamidine acetate in methanol cooled at $0^{\\circ}\\mathrm{C}$ . The solution was further stirred for 5 hours at room temperature. The light-yellow solution was concentrated by rotary evaporation at $80^{\\circ}\\mathrm{C}$ until no obvious liquid remained. The crude solid was then dissolved by a minimum amount of methanol, reprecipitated in diethyl ether, and filtered. The procedure was repeated three times, and the resulting white solid was collected and dried at $80^{\\circ}\\mathrm{C}$ under vacuum for 2 days: $^{1}\\mathrm{H}$ nuclear magnetic resonance (DMSO- $\\cdot\\mathrm{d}_{6}^{\\phantom{*}}$ ) d 8.76 (s, $4H)$ ), 7.85 (s, $1H,$ ppm; $^{13}\\mathrm{C}$ nuclear magnetic resonance (DMSO- $\\mathrm{\\bf{d}}_{6}$ ) $\\delta157.05\\mathrm{ppm}$ . \n\n$\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Br}$ was synthesized by slowly dropping $31.1\\mathrm{ml}$ of hydrobromide acid (48 wt $\\%$ in water) (Fluka) to a solution of $27.86~\\mathrm{ml}$ of $\\mathrm{CH}_{3}\\mathrm{NH}_{2}$ (40 wt $\\%$ solution in absolute methanol; TCI) cooled at $0^{\\circ}\\mathrm{C}.$ The solution was further stirred for 5 hours at room temperature. The colorless solution was concentrated by rotary evaporation at $50^{\\circ}\\mathrm{C}$ until no obvious liquid remained. The crude solid was then dissolved by a minimum amount of ethanol, reprecipitated in diethyl ether, and filtered. The procedure was repeated three times, and the resulting white solid was collected and dried at room temperature under vacuum for 2 days. \n\n# Solar cell preparation \n\nThe fluorine-doped tin oxide–coated glass (NSG) was sequentially cleaned using detergent, acetone, and ethanol. A 20- to $30\\mathrm{-nm\\TiO_{2}}$ blocking layer was deposited on the cleaned FTO by spray pyrolysis, using $\\mathrm{O}_{2}$ as carrier gas, at $450^{\\circ}\\mathrm{C}$ from a precursor solution of $0.6\\mathrm{ml}$ of titanium diisopropoxide and $0.4~\\mathrm{ml}$ of bis(acetylacetonate) in $7~\\mathrm{ml}$ of anhydrous isopropanol. A $200\\mathrm{-nm}$ mesoporous $\\mathrm{TiO}_{2}$ was coated on the substrate by spin coating at a speed of $4500~\\mathrm{rpm}$ for $15\\ s$ with a ramp-up of $2000\\mathrm{\\dot{rpm}s^{-1}}$ from a diluted $30\\mathrm{-nm}$ particle paste (Dyesol) in ethanol; the weight ratio of $\\mathrm{TiO}_{2}$ (Dyesol paste) to ethanol is 5.5:1. After spin coating, the substrate was immediately dried on a hotplate at $80^{\\circ}\\mathrm{C},$ and the substrates were then sintered at $500^{\\circ}\\mathrm{C}$ for $20~\\mathrm{min}$ . The perovskite film was deposited by spin coating onto the $\\mathrm{TiO}_{2}$ substrate. The precursor solution was prepared in a glovebox of $1.35~\\mathrm{M}$ $\\mathrm{Pb}^{2+}$ $\\mathrm{(PbI_{2}}$ and $\\mathrm{Pb}\\mathrm{Br}_{2}$ ) in a mixed solvent of DMF and DMSO; the volume ratio of DMF to DMSO was 4:1. The molar ratio for $\\mathrm{PbI}_{2}$ (specified purity ${>}98\\%$ ; TCI) $\\mathrm{\\PbBr}_{2}$ (purity, $99.999\\%$ ; Alfa Aesar) was fixed at 0.85:0.15, and the molar ratio for $\\mathbf{MABr/PbBr}_{2}$ was fixed at 1:1. A comprehensive analysis carried out by an analytical institution and covering more than 70 elements showed that the purity of the TCI product $(\\mathrm{Pb}\\ensuremath{\\mathrm{I}_{2}})$ exceeded $99.99\\%$ . Thus, it was much purer than specified, implying that changes in molar ratio within the range of some percentages in the precursor solutions are not superimposed by the effects of impurities. \n\nBy changing the amount of FAI, we obtained different molar ratios for $\\mathrm{PbI}_{2}/\\mathrm{FAI}$ varying from 1.54 to 1.37, 1.23, 1.16, 1.10, 1.05, 1.00, and 0.85. The spin-coating procedure was performed in an argon flowing glovebox: first, $2000~\\mathrm{rpm}$ for $10\\ s$ with a ramp-up of $2\\bar{0}0\\ \\mathrm{rpm\\s^{-1}}$ ; second, $6000~\\mathrm{rpm}$ for $30~\\mathsf{s}$ with a ramp-up of $\\bar{2000}\\ \\mathrm{rpm\\s^{-1}}$ . Chlorobenzene $(\\mathrm{110~\\upmul})$ was dropped on the spinning substrate during the second spin-coating step $20~\\mathsf{s}$ before the end of the procedure. The substrate was then heated at $100^{\\circ}\\mathrm{C}$ for $90~\\mathrm{min}$ on a hotplate. After cooling down to room temperature, Spiro-OMeTAD (Merck) was subsequently deposited on top of the perovskite layer by spin coating at $3000~\\mathrm{rpm}$ for $20~\\mathsf{s}$ . The Spiro-OMeTAD solution was prepared by dissolving Spiro-OMeTAD in chlorobenzene $(60\\mathrm{\\mM})$ ), with the addition of $30~\\mathrm{mM}$ bis(trifluoromethanesulfonyl)imide (from a stock solution in acetonitrile) and $200~\\mathrm{mM}$ tert-butylpyridine. Finally, FK209 [tris(2-( $1H$ -pyrazol-1-yl)-4-tert-butylpyridine)- cobalt(III) tris(bis(trifluoromethylsulfonyl)imide); Dyenamo AB] was added to the Spiro-OMeTAD solution (from a stock solution in acetonitrile); the molar ratio for FK209 and Spiro-OMeTAD was 0.03. Finally, $80\\ \\mathrm{nm}$ of gold was deposited by thermal evaporation using a shadow mask to pattern the electrodes. \n\n# Characterization \n\nCurrent-voltage characteristics were recorded by applying an external potential bias to the cell while recording the generated photocurrent with a digital source meter (Keithley model 2400). The light source was a 450-W xenon lamp (Oriel) equipped with a Schott K113 Tempax sunlight filter (Praezisions Glas & Optik GmbH) to match the emission spectrum of the lamp with the AM $1.5\\mathrm{~G~}$ standard. Before each measurement, the exact light intensity was determined using a calibrated Si reference diode equipped with an infrared cutoff filter (Schott KG-3). \n\nTo specify the illuminated area, we used an aperture (shadow mask) with an area of $0.16~\\mathrm{cm}^{2}$ , whereas the total device area defined by the overlap of the electrodes was approximately $0.36~\\mathrm{cm}^{2}$ . This approach allows for an accurate determination of the short-circuit current density but has drawbacks when determining the open-circuit voltage $(V_{\\mathrm{OC}})$ as $V_{\\mathrm{OC}}$ depends on the dark current flowing through the device according to the equation: $V_{\\mathrm{OC}}=n_{\\mathrm{ID}}k T/e\\ln(I_{\\mathrm{SC}}/I_{0}+1)$ . If there is a mismatch between the illuminated area and the dark area, the ratio between the photocurrent $I_{\\mathrm{SC}}$ and the dark saturation current $I_{0}$ is artificially changed by this ratio. Therefore, the open-circuit voltage was additionally measured without aperture. \n\nXRD spectra were recorded on an X’Pert MPD PRO (PANalytical) equipped with a ceramic tube providing Ni-filtered (CuKa, $\\lambda=$ $1.{\\dot{5}}4{\\dot{0}}{\\dot{6}}0\\ {\\dot{\\mathrm{A}}},$ radiation and on an RTMS X’Celerator (PANalytical). The measurements were performed in Bragg-Brentano geometry $2{\\uptheta}=$ $8^{\\circ}$ to $88^{\\circ}$ . The samples were mounted without further modification, and the automatic divergence slit $(10~\\mathrm{mm})$ and beam mask $\\mathrm{{(10~mm)}}$ were adjusted to the dimension of the films. A step size of $0.008^{\\circ}$ was chosen for an acquisition time of $270.57\\ s\\ \\mathrm{deg}^{-1}$ . A baseline correction was applied to all x-ray thin-film diffractograms to compensate for the broad feature arising from the FTO glass and anatase substrate. The presence of strong thermal diffuse scattering and turbostratic disorder, mainly in the $\\mathrm{PbI}_{2}$ films, thwarted a successful Rietveld refinement of up to six phases. Finally, the areas of the (001) maximum of $\\mathrm{PbI}_{2}$ and the (011)/(101) peaks of $\\mathrm{FAPbI}_{3}.$ , calculated by means of a pseudo-Voigt function, were used to estimate the weight fractions. These pseudoVoigt functions also furnished the full widths at half maximum, which were subsequently used to compute the sizes of the coherent domains along the diffraction vectors by means of Scherrer’s equation, setting $K=1$ . SEM images were recorded using a high-resolution scanning electron microscope (Zeiss Merlin). \n\nElectroluminescence yield. The emitted photon flux was detected with a large-area $(1~\\mathrm{{cm}}^{2})$ Si-photodiode (Hamamatsu S1227- 1010BQ) positioned close to the sample. Because of the nonconsidered angular dependence of emission and detector sensitivity, $\\mathrm{EQE_{EL}}$ was expected to be slightly underestimated (on the order of $10\\%$ ). The driving voltage was applied using a Bio-Logic SP300 potentiostat, which was also used to measure the short-circuit current of the detector at a second channel. \n\nAbsorption spectra were measured on a PerkinElmer ultraviolet (UV)–vis spectrophotometer. Absorbance was determined from a transmittance measurement using an integrating sphere. We used the “PerkinElmer Lambda $950~\\mathrm{nm^{\\prime\\prime}}$ setup with the integrating sphere system $^{\\alpha}60\\ \\mathrm{nm}$ InGaAs integrating sphere.” The sources were deuterium and tungsten halogen lamps, and the signal was detected by a gridless photomultiplier with Peltier-controlled PbS detector. The UV WinLab software was used to process the data. \n\nPL and TCSPC experiments. PL spectra were recorded by exciting the perovskite films deposited onto mesoporous $\\mathrm{TiO}_{2}$ at $460\\ \\mathrm{nm}$ with a standard 450-W Xenon CW lamp. The signal was recorded with a spectrofluorometer (Fluorolog; Horiba Jobin Yvon Technology FL1065) and analyzed with the software FluorEssence. \n\nThe PL decay experiments were performed on the same samples using the same Fluorolog with a pulsed source at $406~\\mathrm{nm}$ (Horiba NanoLED 402-LH; pulse width $<200$ ps, 11 pJ per pulse, approximately $1\\ \\mathrm{mm}^{2}$ in spot size), and the signal was recorded using TCSPC. The samples were excited from the perovskite and glass side under ambient conditions. \n\nAnalysis of the PL decay. From the pump fluence, we estimated an initial photogenerated charge carrier density on the order of $2\\times$ $10^{17}\\mathrm{cm}^{-3}$ upon excitation at the highest intensity. For a filter with a transmittance of $2.5\\%$ , we expected $5\\times10^{15}~\\mathrm{cm}^{-3}$ . Assuming that most of the charge carriers in the perovskite are photogenerated (that is, the intrinsic charge carrier density is low), we can set the electron density equal to the hole density and write the continuity equation for photogenerated electrons: $d n/{\\dot{d t}}=-\\upbeta n^{2}-k n,$ assuming that changes in the charge density $n$ are due to either a bimolecular process or monomolecular recombination. Solving this equation for $n(t)$ and assuming that the PL signal is proportional to $n^{\\dot{2}}(t)$ , we can calculate the PL decay (solid lines in the main paper). \n\nThe ideal solar cell without nonradiative recombination should have $k=0$ . Then, $V_{\\mathrm{OC}}$ can be calculated, assuming that the charge carrier generation rate $G$ equals the recombination rate $\\operatorname{R}\\colon G=R=$ $\\upbeta n^{2}$ . For a semiconductor using Boltzmann statistics and effective mass approximation, $V_{\\mathrm{OC}}$ can be written as $e V_{\\mathrm{OC}}=E_{\\mathrm{g}}-k T\\ln(N_{\\mathrm{c}}N_{\\mathrm{v}}/n p).$ with the effective densities of states in conduction and valence band: $N_{\\mathrm{c,v}}=2\\times(2\\uppi m_{\\mathrm{e,h}}\\mathrm{{}}^{*}k_{\\mathrm{B}}T/h^{2})^{3/2}$ . Thus, knowing the effective mass $m_{\\mathrm{e,h}},$ temperature $T,\\ \\upbeta.$ , band gap $E_{\\mathrm{g}},$ and light intensity, $V_{\\mathrm{OC}}$ can be calculated as $V_{\\mathrm{OC}}=E_{\\mathrm{g}}/e-k T/e\\bar{\\ln}(N_{\\mathrm{c}}N_{\\mathrm{v}}\\upbeta/G)\\approx1.3\\mathrm{~V},$ where we approximated $G=J_{\\mathrm{SC}}/(e\\times\\mathrm{thickness})=3\\times10^{27}\\mathrm{m}^{-3}\\mathrm{s}^{-1}.$ . This is a rough estimation where the order of magnitude of the input parameters—but not their exact values—is known. Effective masses have been taken from Giorgi et al. (30). \n\nFig. S6. Top-view SEM images of perovskite films on m ${\\mathsf{s}}–\\mathsf{T i O}_{2}/{\\mathsf{c}}–\\mathsf{T i O}_{2}/{\\mathsf{F T O}}$ with varying $\\mathsf{P b l}_{2}/\\mathsf{F A l}$ ratios (0.85, 1, 1.05, 1.1, 1.16, 1.23, 1.37, and 1.54) in the precursor solutions. \nFig. S7. XRD patterns of perovskite films on $\\mathsf{m s}{-}\\mathsf{T i O}_{2}/\\mathsf{c}{-}\\mathsf{T i O}_{2}/\\mathsf{F T O}$ with varying $\\mathsf{P b l}_{2}/\\mathsf{F A l}$ ratios (0.85, 1, 1.05, 1.1, 1.16, 1.23, 1.37, and 1.54) in the precursor solutions. \nFig. S8. Normalized (001) peaks of $\\mathsf{P b l}_{2}$ phase showing the variation in full widths at half maximum with increasing ratios of $\\mathsf{P b l}_{2}/\\mathsf{F A P b l}_{3}$ fraction. \nFig. S9. Cross-sectional SEM images of perovskite films on m ${\\mathsf{s}}–\\mathsf{T i O}_{2}/{\\mathsf{c}}–\\mathsf{T i O}_{2}/{\\mathsf{F T O}}$ with varying $\\mathsf{P b l}_{2}/\\mathsf{F A l}$ ratios (1, 1.05, 1.1, 1.23, 1.37, and 1.54) in the precursor solution. \nFig. S10. External electroluminescence quantum efficiency as a function of the injection current for the device with $\\mathsf{P b l}_{2}/\\mathsf{F A l}=1.16$ . \nFig. S11. Normalized PL spectra of perovskite films on ms-TiO2/bl-TiO2/FTO with varying $\\mathsf{P b l}_{2}/\\mathsf{F A l}$ ratios (1, 1.05, 1.1, 1.23, 1.37, and 1.54) in the precursor solution. \nFig. S12. PL decay of perovskite films on ${\\sf15-T i O}_{2}/{\\sf b l-T i O}_{2}/{\\sf F T O}$ with varying $\\mathsf{P b l}_{2}/\\mathsf{F A l}$ ratios (1, 1.05, 1.1, 1.16, 1.23, 1.37, and 1.54) in the precursor solution. \nTable S1. Photovoltaic parameters for PSCs measured using forward scan (from $J_{S C}$ to $\\boldsymbol{V_{\\mathrm{OC}}})$ and backward scan (from $V_{\\mathrm{OC}}$ to $J_{5\\mathsf{C}})$ at different scanning speeds (B, backward; F, forward). Table S2. Photovoltaic parameters for the stability of PSCs measured under AM 1.5 G illumination (solar cells were sealed with epoxy and stored in a dessicator). \nTable S3. Composition of perovskite composite film determined by Rietveld refinement. \n\n# REFERENCES AND NOTES \n\n1. M. Grätzel, The light and shade of perovskite solar cells. Nat. Mater. 13, 838–842 (2014). \n2. A. Kojima, K. Teshima, Y. Shirai, T. Miyasaka, Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n3. J.-H. Im, C.-R. Lee, J.-W. Lee, S.-W. Park, N.-G. Park, $6.5\\%$ efficient perovskite quantum-dotsensitized solar cell. Nanoscale 3, 4088–4093 (2011). \n4. I. Chung, B. Lee, J. He, R. P. H. Chang, M. G. Kanatzidis, All-solid-state dye-sensitized solar cells with high efficiency. Nature 485, 486–489 (2012). \n5. H.-S. Kim, C.-R. Lee, J.-H. Im, K.-B. Lee, T. Moehl, A. Marchioro, S.-J. Moon, R. Humphry-Baker, J.-H. Yum, J. E. Moser, M. Grätzel, N.-G. Park, Lead iodide perovskite sensitized all-solid-state submicron thin film mesoscopic solar cell with efficiency exceeding $9\\%.$ . Sci. Rep. 2, 591 (2012). \n6. M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami, H. J. Snaith, Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n7. J. Burschka, N. Pellet, S.-J. Moon, R. Humphry-Baker, P. Gao, M. K. Nazeeruddin, M. Grätzel, Sequential deposition as a route to high-performance perovskite-sensitized solar cells. Nature 499, 316–319 (2013). \n8. W. S. Yang, J. H. Noh, N. J. Jeon, Y. C. Kim, S. Ryu, J. Seo, S. I. Seok, High-performance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237 (2015). \n9. N. Pellet, P. Gao, G. Gregori, T.-Y. Yang, M. K. Nazeeruddin, J. Maier, M. Grätzel, Mixed-organiccation perovskite photovoltaics for enhanced solar-light harvesting. Angew. Chem. Int. Ed. 53, 3151–3157 (2014). \n10. N. J. Jeon, J. H. Noh, W. S. Yang, Y. C. Kim, S. Ryu, J. Seo, S. I. Seok, Compositional engineering of perovskite materials for high-performance solar cells. Nature 517, 476–480 (2015). \n11. W. Tress, N. Marinova, O. Inganäs, M. K. Nazeeruddin, S. M. Zakeeruddin, M. Graetzel, Predicting the open-circuit voltage of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ perovskite solar cells using electroluminescence and photovoltaic quantum efficiency spectra: The role of radiative and non-radiative recombination. Adv. Energy Mater. 5, 1400812 (2015). \n12. L. Gil-Escrig, G. Longo, A. Pertegás, C. Roldán-Carmona, A. Soriano, M. Sessolo, H. J. Bolink, Efficient photovoltaic and electroluminescent perovskite devices. Chem. Commun. 51, 569–571 (2015). \n13. Y. Shao, Z. Xiao, C. Bi, Y. Yuan, J. Huang, Origin and elimination of photocurrent hysteresis by fullerene passivation in $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ planar heterojunction solar cells. Nat. Commun. 5, 5784 (2014). \n14. Z. Ren, A. Ng, Q. Shen, H. C. Gokkaya, J. Wang, L. Yang, W.-K. Yiu, G. Bai, A. B. Djurišić, W. W.-F. Leung, J. Hao, W. K. Chan, C. Surya, Thermal assisted oxygen annealing for high efficiency planar $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ perovskite solar cells. Sci. Rep. 4, 6752 (2014). \n15. Q. Chen, H. Zhou, T.-B. Song, S. Luo, Z. Hong, H.-S. Duan, L. Dou, Y. Liu, Y. Yang, Controllable self-induced passivation of hybrid lead iodide perovskites toward high performance solar cells. Nano Lett. 14, 4158–4163 (2014). \n16. T. Supasai, N. Rujisamphan, K. Ullrich, A. Chemseddine, T. Dittrich, Formation of a passivating $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}/\\mathsf{P b l}_{2}$ interface during moderate heating of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ layers. Appl. Phys. Lett. 103, 183906 (2013). \n17. L. Wang, C. McCleese, A. Kovalsky, Y. Zhao, C. Burda, Femtosecond time-resolved transient absorption spectroscopy of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ perovskite films: Evidence for passivation effect of $\\mathsf{P b l}_{2}$ . J. Am. Chem. Soc. 136, 12205–12208 (2014). \n18. V. Somsongkul, F. Lang, A. R. Jeong, M. Rusu, M. Arunchaiya, T. Dittrich, Hole blocking $\\mathsf{P b l}_{2}/$ $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ interface. Phys. Status Solidi 8, 763–766 (2014). \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/2/1/e1501170/DC1 \nFig. S1. Independent certification from Newport Corporation confirming PCEs of $19.90\\%$ (backward scan) and $19.73\\%$ (forward scan) and a normalized electroluminescence quantum efficiency. \nFig. S2. Photograph of two real devices (front view and back view) showing the active area of the solar cell, the high reflectivity of the smooth gold electrode, and the densely opaque optical appearance of the perovskite film. \nFig. S3. Histogram of solar cell efficiencies for 40 solar cells, with the optimized $\\mathsf{P b l}_{2}/\\mathsf{F A l}=1.05$ . Fig. S4. Initial stability test of PSCs sealed using epoxy and stored in a desiccator in the dark. Fig. S5. Absorption spectra of perovskite films on $\\mathsf{m}{-}\\mathsf{T i O}_{2}/\\mathsf{c}{-}\\mathsf{T i O}_{2}/\\mathsf{F T O}$ substrate with varying $R_{\\mathrm{PbI_{2}/F A I}}$ measured in transmission. \n19. D. H. Cao, C. C. Stoumpos, C. D. Malliakas, M. J. Katz, O. K. Farha, J. T. Hupp, M. G. Kanatzidis, Remnant $\\mathsf{P b l}_{2},$ an unforeseen necessity in high-efficiency hybrid perovskite-based solar cells? APL Mater. 2, 091101 (2014). \n20. S. Pathak, A. Sepe, A. Sadhanala, F. Deschler, A. Haghighirad, N. Sakai, K. C. Goedel, S. D. Stranks, N. Noel, M. Price, S. Hüttner, N. A. Hawkins, R. H. Friend, U. Steiner, H. J. Snaith, Atmospheric influence upon crystallization and electronic disorder and its impact on the photophysical properties of organic-inorganic perovskite solar cells. ACS Nano 9, 2311–2320 (2015). \n21. H. J. Snaith, A. Abate, J. M. Ball, G. E. Eperon, T. Leijtens, N. K. Noel, S. D. Stranks, J. T.-W. Wang, K. Wojciechowski, W. Zhang, Anomalous hysteresis in perovskite solar cells. J. Phys. Chem. Lett. \n5, 1511–1515 (2014). \n22. E. T. Hoke, K. Vandewal, J. A. Bartelt, W. R. Mateker, J. D. Douglas, R. Noriega, K. R. Graham, J. M. J. Fréchet, A. Salleo, M. D. McGehee, Recombination in polymer:fullerene solar cells with open-circuit voltages approaching and exceeding 1.0 V. Adv. Energy Mater. 3, 220–230 (2013). \n23. D. Di Nuzzo, G.-J. A. H. Wetzelaer, R. K. M. Bouwer, V. S. Gevaerts, S. C. J. Meskers, J. C. Hummelen, P. W. M. Blom, R. A. J. Janssen, Simultaneous open-circuit voltage enhancement and short-circuit current loss in polymer: Fullerene solar cells correlated by reduced quantum efficiency for photoinduced electron transfer. Adv. Energy Mater. 3, 85–94 (2013). \n24. N. Marinova, W. Tress, R. Humphry-Baker, M. I. Dar, V. Bojinov, S. M. Zakeeruddin, M. K. Nazeeruddin, M. Grätzel, Light harvesting and charge recombination in $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ perovskite solar cells studied by hole transport layer thickness variation. ACS Nano 9, 4200–4209 (2015). \n25. K. Vandewal, K. Tvingstedt, A. Gadisa, O. Inganäs, J. V. Manca, On the origin of the opencircuit voltage of polymer-fullerene solar cells. Nat. Mater. 8, 904–909 (2009). \n26. T. Kirchartz, A. Helbig, W. Reetz, M. Reuter, J. H. Werner, U. Rau, Reciprocity between electroluminescence and quantum efficiency used for the characterization of silicon solar cells. Prog. Photovolt. Res. Appl. 17, 394–402 (2009). \n27. Z.-K. Tan, R. S. Moghaddam, M. L. Lai, P. Docampo, R. Higler, F. Deschler, M. Price, A. Sadhanala, L. M. Pazos, D. Credgington, F. Hanusch, T. Bein, H. J. Snaith, R. H. Friend, Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n28. O. A. Jaramillo-Quintero, R. S. Sanchez, M. Rincon, I. Mora-Sero, Bright visible-infrared light emitting diodes based on hybrid halide perovskite with Spiro-OMeTAD as a hole-injecting layer. J. Phys. Chem. Lett. 6, 1883–1890 (2015). \n29. J. Wang, N. Wang, Y. Jin, J. Si, Z.-K. Tan, H. Du, L. Cheng, X. Dai, S. Bai, H. He, Z. Ye, M. L. Lai, R. H. Friend, W. Huang, Interfacial control toward efficient and low-voltage perovskite light-emitting diodes. Adv. Mater. 27, 2311–2316 (2015). \n\n30. G. Giorgi, J.-I. Fujisawa, H. Segawa, K. Yamashita, Small photocarrier effective masses featuring ambipolar transport in methylammonium lead iodide perovskite: A density functional analysis. J. Phys. Chem. Lett. 4, 4213–4216 (2013). \n\nAcknowledgments: We thank A. Wakamiya (Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan) for providing purified ${\\mathsf{P b l}}_{2}$ . Funding: This work was supported by the European Union Seventh Framework Program (FP7/2007-2013) under grant agreement 604032 (ENERGY.2012.10.2.1) of the MESO project (FP7/2007-2013) and under grant agreement 308997 (NANOMATCELL). M.G. gratefully acknowledges financial support from SNSF-NanoTera (SYNERGY), the Swiss Federal Office of Energy (SYNERGY), CCEM-CH in the 9th call proposal 906: CONNECT PV, the SNSF NRP70 “Energy Turnaround,” and the GRAPHENE project supported by the European Commission Seventh Framework Program (under contract 604391). M.I.D. thanks the European Community’s Seventh Framework Program (FP7/2007-2013) under grant agreement 281063 of the Powerweave project. A.A. and J.L. received funding from the European Union’s Seventh Framework Program for research, technological development, and demonstration under grant agreement 291771. Author contributions: D.B. designed and carried out the experimental study on device fabrication and basic characterization. W.T. performed optoelectronic measurements, analyzed and interpreted the data, and wrote the manuscript together with P.G., M.G., A.H., and D.B. XRD measurements and analyses were performed by P.G., K.S., and M.I.D., whereas J.L. performed SEM measurements. M.I.D. performed PL measurements. C.R. performed optoelectronic characterization. A.A., F.G., and J.-P.C.B. developed the basic recipe for the perovskite deposition. J.-D.D. was responsible for the certification. S.M.Z. and M.K.N. coordinated the research, whereas A.H. and M.G. supervised the project. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or in the Supplementary Materials. Additional data are available from D.B. (dongqin.bi@epfl.ch) upon request. \n\nSubmitted 26 August 2015 \nAccepted 6 November 2015 \nPublished 1 January 2016 \n10.1126/sciadv.1501170 \n\nCitation: D. Bi, W. Tress, M. I. Dar, P. Gao, J. Luo, C. Renevier, K. Schenk, A. Abate, F. Giordano, J.-P. Correa Baena, J.-D. Decoppet, S. M. Zakeeruddin, M. K. Nazeeruddin, M. Grätzel, A. Hagfeldt, Efficient luminescent solar cells based on tailored mixed-cation perovskites. Sci. Adv. 2, e1501170 (2016). \n\n# Efficient luminescent solar cells based on tailored mixed-cation perovskites \n\nDongqin Bi, Wolfgang Tress, M. Ibrahim Dar, Peng Gao, Jingshan Luo, Clémentine Renevier, Kurt Schenk, Antonio Abate, Fabrizio Giordano, Juan-Pablo Correa Baena, Jean-David Decoppet, Shaik Mohammed Zakeeruddin, Mohammad Khaja Nazeeruddin, \nMichael Grätzel and Anders Hagfeldt (January 1, 2016) \nSci Adv 2016, 2:. \ndoi: 10.1126/sciadv.1501170 \n\nThis article is publisher under a Creative Commons license. The specific license under which this article is published is noted on the first page. \n\nFor articles published under CC BY licenses, you may freely distribute, adapt, or reuse the article, including for commercial purposes, provided you give proper attribution. \n\nFor articles published under CC BY-NC licenses, you may distribute, adapt, or reuse the article for non-commerical purposes. Commercial use requires prior permission from the American Association for the Advancement of Science (AAAS). You may request permission by clicking here. \n\nThe following resources related to this article are available online at http://advances.sciencemag.org. (This information is current as of January 10, 2016): \n\nUpdated information and services, including high-resolution figures, can be found in the \nonline version of this article at: \nhttp://advances.sciencemag.org/content/2/1/e1501170.full \n\nSupporting Online Material can be found at: http://advances.sciencemag.org/content/suppl/2015/12/28/2.1.e1501170.DC1 \n\nThis article cites 30 articles,2 of which you can be accessed free: http://advances.sciencemag.org/content/2/1/e1501170#BIBL " + }, + { + "id": "10.1016_j.marpolbul.2016.01.006", + "DOI": "10.1016/j.marpolbul.2016.01.006", + "DOI Link": "http://dx.doi.org/10.1016/j.marpolbul.2016.01.006", + "Relative Dir Path": "mds/10.1016_j.marpolbul.2016.01.006", + "Article Title": "Synthetic fibers in atmospheric fallout: A source of microplastics in the environment?", + "Authors": "Dris, R; Gasperi, J; Saad, M; Mirande, C; Tassin, B", + "Source Title": "MARINE POLLUTION BULLETIN", + "Abstract": "Sources, pathways and reservoirs of microplastics, plastic particles smaller than 5 mm, remain poorly documented in an urban context. While some studies pointed out wastewater treatment plants as a potential pathway of microplastics, none have focused on the atmospheric compartment. In this work, the atmospheric fallout of microplastics was investigated in two different urban and sub-urban sites. Microplastics were collected continuously with a stainless steel funnel. Samples were then filtered and observed with a stereomicroscope. Fibers accounted for almost all the microplastics collected. An atmospheric fallout between 2 and 355 particles/m(2)/day was highlighted. Registered fluxes were systematically higher at the urban than at the sub-urban site. Chemical characterization allowed to estimate at 29% the proportion of these fibers being all synthetic (made with petrochemicals), or a mixture of natural and synthetic material. Extrapolation using weight and volume estimates of the collected fibers, allowed a rough estimation showing that between 3 and 10 tons of fibers are deposited by atmospheric fallout at the scale of the Parisian agglomeration every year (2500 km(2)). These results could serve the scientific community working on the different sources of microplastic in both continental and marine environments. (C) 2016 Elsevier Ltd. All rights reserved.", + "Times Cited, WoS Core": 1336, + "Times Cited, All Databases": 1518, + "Publication Year": 2016, + "Research Areas": "Environmental Sciences & Ecology; Marine & Freshwater Biology", + "UT (Unique WOS ID)": "WOS:000374198100046", + "Markdown": "# Synthetic fibers in atmospheric fallout: A source of microplastics in the environment? \n\nRachid Dris ⁎, Johnny Gasperi, Mohamed Saad, Cécile Mirande, Bruno Tassin \n\nUniversité Paris-Est, LEESU (laboratoire eau environnement et systèmes urbains), 61 avenue du Général de Gaulle, 94010 Cedex Créteil, France \n\n# a r t i c l e i n f o \n\nArticle history: \nReceived 2 October 2015 \nReceived in revised form 22 December 2015 \nAccepted 5 January 2016 \nAvailable online xxxx \n\nKeywords: Microplastics Urban environment Atmospheric fallout Microplastic sources Synthetic fibers \n\n# a b s t r a c t \n\nSources, pathways and reservoirs of microplastics, plastic particles smaller than 5 mm, remain poorly documented in an urban context. While some studies pointed out wastewater treatment plants as a potential pathway of microplastics, none have focused on the atmospheric compartment. In this work, the atmospheric fallout of microplastics was investigated in two different urban and sub-urban sites. Microplastics were collected continuously with a stainless steel funnel. Samples were then filtered and observed with a stereomicroscope. Fibers accounted for almost all the microplastics collected. An atmospheric fallout between 2 and 355 particles $/\\mathrm{m}^{2}/$ day was highlighted. Registered fluxes were systematically higher at the urban than at the sub-urban site. Chemical characterization allowed to estimate at $29\\%$ the proportion of these fibers being all synthetic (made with petrochemicals), or a mixture of natural and synthetic material. Extrapolation using weight and volume estimates of the collected fibers, allowed a rough estimation showing that between 3 and 10 tons of fibers are deposited by atmospheric fallout at the scale of the Parisian agglomeration every year $(2500\\mathrm{km}^{2}.$ . These results could serve the scientific community working on the different sources of microplastic in both continental and marine environments. \n\n$\\circledcirc$ 2016 Elsevier Ltd. All rights reserved. \n\n# 1. Introduction \n\nMicroplastics are a widespread particular contaminant originating from the breakdown of larger plastic debris (secondary) or directly manufactured on a millimetric or submilletric size (primary) (Cole et al., 2011). These plastics have been defined as particles with the largest dimension smaller than $5\\mathrm{mm}$ (Arthur et al., 2008); they cover a continuous spectrum of sizes and shapes including 1D-fibers, 2D-fragments and 3D-spheres. \n\nGiven their size, these microparticles can be ingested by a wide range of species, either in marine (Anastasopoulou et al., 2013; Lusher et al., 2013; Thompson et al., 2004) or freshwater environments (Sanchez et al., 2014). These microplastics have negative effects on organisms and the possibility of their translocation, bioaccumulation and trophic accumulation is currently being debated (Wright et al., 2013). \n\nWhile marine plastic pollution has been well documented, there has been limited focus on the continental contamination (Dris et al., 2015b; Wagner et al., 2014). Moreover, its sources, pathways and reservoirs in urban environments remain largely unknown. It is crucial to gather a better knowledge about these particles in the continental environment as rivers are said to be the main source of marine microplastics (Andrady, 2011). If it is very often cited that $80\\%$ of the fibers in the marine environment come from the continent, this estimation is not well documented and demonstrated. \n\nSynthetic fibers are one of the forms in which microplastics can be found. They derive presumably from synthetic clothing or macroplastics. Different pathways are thought to be an important source of fibrous microplastics in the aquatic environment. It has been shown that laundry washing machines discharge large amounts of microplastics into wastewaters (reaching 1900 fibers in one wash (Browne et al., 2011)). During wastewater treatment, synthetic fibers are known to contaminate sewage sludge (Habib et al., 1998; Zubris and Richards, 2005). The sources and fate of microplastics in the various compartments of the urban environment are poorly documented (Dris et al., 2015a); this paper focuses on the atmospheric compartment and investigates the contribution of the atmospheric fallout as a potential vector of plastic pollution. \n\n# 2. Materials and methods \n\nTotal atmospheric fallout was collected on two sampling sites: one in a dense urban environment $(48^{\\circ}47^{\\prime}17.8^{\\prime\\prime}\\mathrm{N}$ , $2^{\\circ}26^{\\prime}36.2^{\\prime\\prime}\\mathrm{E}$ – Site 1 – Fig. 1) and one in a less dense sub-urban environment. $(48^{\\circ}50^{\\prime}27.8^{\\prime\\prime}\\mathrm{N}$ , $2^{\\circ}35^{\\prime}$ $15.3^{\\prime\\prime}\\mathrm{E}$ – Site 2 – Fig. 1). Site 1 was monitored over a period of one year (February 19th 2014 to March 12th 2015) and site 2 for a shorter period from October 3rd to 12th March 2015. Site 1 is localized in an area of 7900 inhabitants $\\ensuremath{{\\mathrm{km}}^{2}}$ while site 2 is characterized by a surrounding population of 3300 inhabitants $\\mathrm{\\km}^{2}$ (Insee — Régions, départements et villes de France, 2011). \n\nThe sampling surface was $0.325~\\mathrm{m}^{2}$ allowing for total atmospheric fallout (dry and wet deposition) to be collected through a stainless steel funnel. A $20\\mathrm{L}$ glass bottle was placed at the bottom of the funnel in an opaque box to collect the water. The samples were collected at various frequencies during the monitoring period depending on cumulative rainfall leading to 24 samples at site 1 and 9 at site 2. When both sites were monitored, the collection of samples was carried out the same day for both sites in order to allow comparison. No interruption of the sampling occurred during the whole monitoring period in each site, providing a full view of the annual variability of the atmospheric fallout. \n\n![](images/f8cd888a5200df69e7ffee1b6e51504e28eed32b16d0e198bfe9cd8e0556c23d.jpg) \nFig. 1. Localization, sampling device and synthetic fibers for each site. \n\nEach time the atmospheric fallout was collected, the funnel was rinsed with $3^{*}1\\mathrm{~L~}$ of reverse osmosed water in order to recover all particles adhering to the funnel. As commonly done in studies focusing on the pollutant fluxes in atmospheric fallout, preliminary tests demonstrated the efficiency of such rinses. Consecutive rinses with 1 L showed that in the fourth rinse, the number of microplastics is similar to the one in the laboratory blanks. After the rinsing step, samples were immediately covered until the processing step to avoid any contamination. Given the sampling period and the collecting surface area, the atmospheric fallout is expressed as a number of particles per square meter per day. The rainfall was recorded for both sites. \n\nAll samples were filtered on quartz fiber GF/A Whatman filters $(1.6\\upmu\\mathrm{m})$ . To minimize post-sampling contamination from indoor air, samples were always covered. The filters and the vessel were heated to $500^{\\circ}\\mathrm{C}$ prior to their use. All laboratory procedures were performed wearing a cotton laboratory coat. Laboratory blanks were performed to verify that no microplastics are added to the samples during the laboratory procedures. Globally, blank results do not reveal any significant contamination in comparison to the levels found in samples (1 to 2 fibers per filter, representing between 0.5 and $5\\%$ of the fibers on the samples). \n\nFilters were observed with a stereomicroscope (Leica MZ12). Previously used criteria were employed in order to identify synthetic fibers (Dris et al., 2015a; Hidalgo-Ruz et al., 2012; Norén, 2007). The accuracy of the method was estimated by comparing the counting of 3 different observers on the same filters. No difference $>5\\%$ in the total number of fibers was observed. In 11 of the collected samples, the length of the fibers was measured during the counting (the software “Histolab” coupled with the stereomicroscope). The observation size limit was defined to $50\\upmu\\mathrm{m}$ . \n\nAtmospheric fallout in this study is presented as a number of total fibers. Chemical characterization was also performed. A subsample of ${\\mathfrak{n}}=24$ fibers was analyzed with Fourier Transform infrared (FT-IR) micro spectroscopy (Microscope LUMOS FT-IR — Brucker) coupled with an ATR (Attenuated Total Reflectance) accessory in order to characterize the proportion of synthetic and natural fibers and identify the predominant plastic polymers. The fibers were categorized according to the classification proposed by the international organization for standardization (ISO/TR 11827:2012 Textiles — Composition testing — Identification of fibers). \n\n# 3. Results and discussion \n\nBased on a long term monitoring (one year), our results show large amounts of fibers in the atmospheric fallout, which has not yet been reported in the literature. Throughout the year of monitoring (site 1), the atmospheric fallout ranged from 2 to 355 particles $/\\mathrm{m}^{2}.$ /day (Fig. 2) with an average atmospheric fallout of $110\\pm96$ particles $/\\mathrm{m}^{2}.$ /day (mean $\\pm$ SD), indicating a high annual variability. On Site 2 (6-month monitoring), the atmospheric fallout was around $53\\pm38$ particles $\\langle{\\bf m}^{2}$ /day $(\\mathrm{mean}\\pm\\mathrm{SD})$ ). \n\nFig. 3 illustrates the proportion of fibers belonging to each size range considered for 11 samples. It can be seen that the smallest fibers (in the $200{-}400\\upmu\\mathrm{m}$ and $400{-}600\\upmu\\mathrm{m}$ size ranges) are predominant while fibers in the larger size ranges are rare. Few fibers have been found in the $50\\upmu\\mathrm{m}-200\\upmu\\mathrm{m}$ size range. Fibers smaller than $<50\\upmu\\mathrm{m}$ are also observed with the stereomicroscope, but since their nature can be hardly identified, they were not taken into account. The length of the fibers was measured during counting. The diameter of the fibers varies mainly between 7 and $15\\upmu\\mathrm{m}$ . \n\nRainfall seems to be an important factor influencing the fallout flux. In fact, particularly low numbers of fibers were found during dry weather or low cumulated rainfall periods. For rainfall between 0 and $0.2\\ \\mathrm{mm/day}$ , an atmospheric fallout between 2 and 34 particles $/\\mathrm{m}^{2}$ /day was recorded. During rainy periods (from 2 to $5\\mathrm{mm/day},$ ), highly variable levels of atmospheric fallout were encountered ranging from 11 to 355 particles/ ${\\mathrm{m}}^{2}$ /day. No significant correlation between the levels of fibers in atmospheric fallout and the mean daily rainfall was highlighted. The same conclusion is obtained by considering the cumulative rainfall and the total amount of fibers collected. This indicates that if the absence of rain limits the microplastics atmospheric fallout, rainfall height is a significant factor, though not the only one, contributing to fallout variability; other mechanisms and temporal conditions also contribute to the fallout flux, but remain to be identified. \n\nWhen the levels on both sites are compared side by side, it can be seen that through all the monitoring periods, the sub-urban site systematically showed fewer fibers then the urban one (Fig. 4). Statistical tests showed a significant difference between the atmospheric fallout on the urban and the sub-urban site (Wilcoxon matched pairs test, confidence level of $5\\%$ , $\\mathsf{p}_{\\mathrm{value}}=0.007$ ). One of the reasons that could explain this difference is the density of the surrounding population, which is considered as a proxy of the local activity. This is a pilot study as it contains only two sampling locations leading to a limited statistical power. \n\nFourier Transform infrared (FT-IR) spectroscopy showed that half of the analyzed fibers are natural fibers $(50\\%)$ being mainly cotton or wool. The remaining fibers are man-made. For $21\\%$ of the total fibers, they are manufactured by transformation of natural polymers (rayon or acetate from cellulose). In other hand, $17\\%$ of the fibers correspond to purely synthetic fibers, mainly polyethylene-terephthalate and only one fiber of polyamide. The other $12\\%$ fibers are made with a mixture of different materials including purely synthetic materials fibers (mixture of polyethylene-terephthalate and polyurethane) and fibers being a mixture of natural and synthetic materials (cotton and polyamide). Therefore, petrochemicals are found in $29\\%$ of the analyzed fibers in atmospheric fallout. \n\n![](images/0e165f22b2980d94b56f2832c740c604cee4a31494d7937f2b7996aacaa35f70.jpg) \nFig. 3. Size distribution of synthetic fibers in 11 atmospheric fallout samples (site 1). Boxplots are plotted from bottom to top with: [Lower quartile $^{-1.5*}$ Interquartile range], [Lower quartile], [Median], [Upper quartile], and [Upper quartile $^{+1.5*}$ Interquartile range]. Outliers are displayed as isolated points. \n\nGiven the lack of studies and data addressing the issue of plastic sources and fluxes in an urban area, it is hard to evaluate the importance of the atmospheric fallout as a source of microplastics. According to the average atmospheric flux of total fibers on each site (110 and 53 parti${\\mathrm{cles}}/{\\mathrm{m}}^{2}/{\\mathrm{day}})$ , the length of the fibers (Fig. 3), their approximated section $(80\\upmu\\mathrm{m}^{2}.$ ), and the mass of fibers in the atmospheric fallout per year may be assessed. Two densities were considered: 1 for the polyamide and $1.45~\\mathrm{g/cm^{3}}$ for the polyethylene-terephthalate, corresponding to two low and heavy plastic polymers widely used in the textile industry (Hidalgo-Ruz et al., 2012). At the scale of the Parisian agglomeration (area around $2500\\mathrm{km}^{2}.$ ), it was estimated that between 3 and 10 tons of synthetic fibers, including microplastics, could originate annually from the atmosphere. \n\n# 4. Conclusions \n\nThese results show a significant amount of fibers in atmospheric fallout, which leads to the hypothesis that the atmospheric compartment \n\n![](images/25f0ad2d6aca7972a2664360e62e6b7f914ef914dd9e887480b1c96bbbc826d6.jpg) \nFig. 2. Atmospheric fallout of microplastics on the site 1 in parallel with daily rainfall. \n\nPlease cite this article as: Dris, R., et al., Synthetic fibers in atmospheric fallout: A source of microplastics in the environment?, Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.01.006 \n\n![](images/6623a747523361b0d55e69b8e05ec369814b0c440e6fe2bb9b2f5216561eeaf3.jpg) \nFig. 4. Atmospheric fallout of microplastics on an urban site (site 1) and a sub-urban site (site 2). \n\nshould not be neglected as a potential source of microplastics, specially knowing that we estimated at $29\\%$ the amount of these fibers containing at least partially plastic polymers. These microplastics have different possible sources: synthetic fibers from clothes and houses, degradation of macroplastics, and landfills or waste incineration. The characterization indicates that the hypothesis of the clothing being the main source of these fibers is the more plausible. These fibers in the atmosphere, including microplastics, could be transported by wind to the aquatic environment (Free et al., 2014) or deposited on surfaces of cities or agrosystems. After deposition, they could impact terrestrial organisms or be transported into the aquatic systems through the runoff. More work is needed in order to investigate these atmospheric fibers and understands where they come from, where they end up and which mechanisms and factors lead to their transport and their fallout. \n\nThe micro IR-TF spectroscopy analysis shows the presence of microplastic fibers in the atmospheric fallout. Nevertheless, some questions arise regarding the definition of microplastics in relation with their nature and the ISO classification. Only fibers made of petrochemicals are generally considered in the literature as microplastics (Song et al., 2015). Authors think that fibers made of a mixture of natural and synthetic materials should be also included in the identification of microplastics. Further discussions are also needed to identify if artificial fibers, which are manufactured by transformation of natural polymers, could be included in microplastics. In fact, these fibers might also be prevalent in marine and continental environments and could cause physical impacts on organisms. Moreover, harmful additives and dyes can be used when manufacturing these fibers. \n\nFurthermore, this study could serve the implementation of the marine strategy framework directive (MSFD) (Galgani et al., 2013) aiming to achieve by 2020 the good environmental status for European marine waters. The indicator 10 of the MSFD related to marine liter with a focus on microplastics indicates that the solution for marine plastic pollution is to tackle the problem at its source. This work does not aim to provide accurate atmospheric fluxes for microplastics as a lot of uncertainties remain and more studies are needed, but serves to highlight the important role that this source could play in continental and marine environments and encourages scientists to take it into consideration in future works. \n\n# Acknowledgments \n\nWe address sincere thanks to the members of the LISA (Laboratoire Interuniversitaire des Systèmes Atmosphériques), especially Anne Chabas. The PhD of Rachid Dris is funded by the region Île-de-France Research Network on Sustainable Development (2013-02) (R2DS Ile-deFrance). We thank Kelsey Flanagan for lingual improvements on the manuscript. We thank the members of the ICMPE (Institut de Chimie et des Materiaux Paris-Est) especially Mohamed Guerrouache and Valérie Langlois. We also thank Ludovic Lemee and Gregory Candor from Brucker Optics. \n\n# References \n\nAnastasopoulou, A., Mytilineou, C., Smith, C.J., Papadopoulou, K.N., 2013. Plastic debris ingested by deep-water fish of the Ionian Sea (Eastern Mediterranean). Deep Sea Res. Part Oceanogr. Res. Pap. 74, 11–13. http://dx.doi.org/10.1016/j.dsr.2012.12.008. \nAndrady, A.L., 2011. Microplastics in the marine environment. Mar. Pollut. Bull. 62, 1596–1605. http://dx.doi.org/10.1016/j.marpolbul.2011.05.030. \nArthur, C., Baker, J., Bamford, H., 2008. Proceedings of the International Research. Presented at the Worshop on the Occurence, Effects and Fate of Microplastic Marine Debris. Sept 9–11 2008. NOAA Technical Memorandum NOS-OR&R-30. \nBrowne, M.A., Crump, P., Niven, S.J., Teuten, E., Tonkin, A., Galloway, T., Thompson, R., 2011. Accumulation of microplastic on shorelines woldwide: sources and sinks. Environ. Sci. Technol. 45, 9175–9179. http://dx.doi.org/10.1021/es201811s. \nCole, M., Lindeque, P., Halsband, C., Galloway, T.S., 2011. Microplastics as contaminants in the marine environment: a review. Mar. Pollut. Bull. 62, 2588–2597. http://dx.doi. org/10.1016/j.marpolbul.2011.09.025. \nDris, R., Gasperi, J., Rocher, V., Saad, M., Renault, N., Tassin, B., 2015a. Microplastic contamination in an urban area: a case study in Greater Paris. Environ. Chem. 12, 592–599. \nDris, R., Imhof, H., Sanchez, W., Gasperi, J., Galgani, F., Tassin, B., Laforsch, C., 2015b. Beyond the ocean: contamination of freshwater ecosystems with (micro-) plastic particles. Environ. Chem. 12, 539–550. \nFree, C.M., Jensen, O.P., Mason, S.A., Eriksen, M., Williamson, N.J., Boldgiv, B., 2014. Highlevels of microplastic pollution in a large, remote, mountain lake. Mar. Pollut. Bull. 85, 156–163. http://dx.doi.org/10.1016/j.marpolbul.2014.06.001. \nGalgani, F., Hanke, G., Werner, S., De Vrees, L., 2013. Marine litter within the European marine strategy framework directive. ICES J. Mar. Sci. 70, 1055–1064. http://dx.doi. org/10.1093/icesjms/fst122. \nHabib, D., Locke, D.C., Cannone, L.J., 1998. Synthetic fibers as indicators of municipal sewage sludge, sludge products, and sewage treatment plant effluents. Water Air Soil Pollut. 103, 1–8. \nHidalgo-Ruz, V., Gutow, L., Thompson, R.C., Thiel, M., 2012. Microplastics in the marine environment: a review of the methods used for identification and quantification. Environ. Sci. Technol. 46, 3060–3075. http://dx.doi.org/10.1021/es2031505. \nInsee — Régions, départements et villes de France, 2011. [WWW Document]. URL http:// www.insee.fr/fr/themes/theme.asp?theme $\\mathrel{\\mathop:}=\\dot{}$ 1&sous_theme $^{\\cdot=2}$ (accessed 5.22.15). \nLusher, A.L., McHugh, M., Thompson, R.C., 2013. Occurrence of microplastics in the gastrointestinal tract of pelagic and demersal fish from the English channel. Mar. Pollut. Bull. 67, 94–99. http://dx.doi.org/10.1016/j.marpolbul.2012.11.028. \nNorén, F., 2007. Small plastic particles in Coastal Swedish waters — KIMO reports. http:// www.kimointernational.org/WebData/Files/Small%20plastic%20particles%20in% 20Swedish%20West%20Coast%20Waters.pdf. \nSanchez, W., Bender, C., Porcher, J.-M., 2014. Wild gudgeons (Gobio gobio) from French rivers are contaminated by microplastics: preliminary study and first evidence. Environ. Res. 128, 98–100. http://dx.doi.org/10.1016/j.envres.2013.11.004. \nSong, Y.K., Hong, S.H., Jang, M., Han, G.M., Rani, M., Lee, J., Shim, W.J., 2015. A comparison of microscopic and spectroscopic identification methods for analysis of microplastics in environmental samples. Mar. Pollut. Bull. http://dx.doi.org/10.1016/j.marpolbul. 2015.01.015. \nThompson, R.C., Olsen, Y., Mitchell, R.P., Davis, A., Rowland, S.J., John, A.W., McGonigle, D., Russell, A.E., 2004. Lost at sea: where is all the plastic? Science 304, 838-838. http:// dx.doi.org/10.1126/science.1094559. \nWagner, M., Scherer, C., Alvarez-Muñoz, D., Brennholt, N., Bourrain, X., Buchinger, S., Fries, E., Grosbois, C., Klasmeier, J., Marti, T., Rodriguez-Mozaz, S., Urbatzka, R., Vethaak, A.D., Winther-Nielsen, M., Reifferscheid, G., 2014. Microplastics in freshwater ecosystems: what we know and what we need to know. Environ. Sci. Eur. 26, 1–9. http://dx. doi.org/10.1186/s12302-014-0012-7. \nWright, S.L., Thompson, R.C., Galloway, T.S., 2013. The physical impacts of microplastics on marine organisms: a review. Environ. Pollut. 178, 483–492. http://dx.doi.org/10. 1016/j.envpol.2013.02.031. \nZubris, K.A.V., Richards, B.K., 2005. Synthetic fibers as an indicator of land application of sludge. Environ. Pollut. 138, 201–211. http://dx.doi.org/10.1016/j.envpol.2005.04.013. " + }, + { + "id": "10.1038_ncomms8760", + "DOI": "10.1038/ncomms8760", + "DOI Link": "http://dx.doi.org/10.1038/ncomms8760", + "Relative Dir Path": "mds/10.1038_ncomms8760", + "Article Title": "Long-life Li/polysulphide batteries with high sulphur loading enabled by lightweight three-dimensional nitrogen/sulphur-codoped graphene sponge", + "Authors": "Zhou, GM; Paek, E; Hwang, GS; Manthiram, A", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Lithium-sulphur batteries with a high theoretical energy density are regarded as promising energy storage devices for electric vehicles and large-scale electricity storage. However, the low active material utilization, low sulphur loading and poor cycling stability restrict their practical applications. Herein, we present an effective strategy to obtain Li/polysulphide batteries with high-energy density and long-cyclic life using three-dimensional nitrogen/sulphur codoped graphene sponge electrodes. The nitrogen/sulphur codoped graphene sponge electrode provides enough space for a high sulphur loading, facilitates fast charge transfer and better immobilization of polysulphide ions. The hetero-doped nitrogen/sulphur sites are demonstrated to show strong binding energy and be capable of anchoring polysulphides based on first-principles calculations. As a result, a high specific capacity of 1,200 mAhg(-1) at 0.2C rate, a high-rate capacity of 430 mAhg(-1) at 2C rate and excellent cycling stability for 500 cycles with similar to 0.078% capacity decay per cycle are achieved.", + "Times Cited, WoS Core": 955, + "Times Cited, All Databases": 1005, + "Publication Year": 2015, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000358858800004", + "Markdown": "# Long-life Li/polysulphide batteries with high sulphur loading enabled by lightweight three-dimensional nitrogen/sulphur-codoped graphene sponge \n\nGuangmin Zhou1, Eunsu Paek2, Gyeong S. Hwang2 & Arumugam Manthiram1 \n\nLithium–sulphur batteries with a high theoretical energy density are regarded as promising energy storage devices for electric vehicles and large-scale electricity storage. However, the low active material utilization, low sulphur loading and poor cycling stability restrict their practical applications. Herein, we present an effective strategy to obtain Li/polysulphide batteries with high-energy density and long-cyclic life using three-dimensional nitrogen/ sulphur codoped graphene sponge electrodes. The nitrogen/sulphur codoped graphene sponge electrode provides enough space for a high sulphur loading, facilitates fast charge transfer and better immobilization of polysulphide ions. The hetero-doped nitrogen/sulphur sites are demonstrated to show strong binding energy and be capable of anchoring polysulphides based on first-principles calculations. As a result, a high specific capacity of $1,200\\mathsf{m A h g}^{-1}$ at 0.2C rate, a high-rate capacity of $430\\mathsf{m A h}\\mathsf{g}^{-1}$ at 2C rate and excellent cycling stability for 500 cycles with $\\sim0.078\\%$ capacity decay per cycle are achieved. \n\ns energy storage devices, lithium-ion batteries (LIBs) play a dominant role in portable electronic devices due to their high performance compared with other battery systems1,2. However, the increased demand for electric vehicles and largescale smart grid stringently requires batteries with high-energy density, low cost and long cycle life3. The current main challenge is the capacity mismatch between the cathode and anode, which makes LIB approach its theoretical energy density limits4,5. The relatively lagged progress on cathodes becomes a barrier in further improving the energy density of LIBs, which has triggered the exploration of new electrochemical systems, such as the Lithium–sulphur (Li–S) batteries with a high theoretical energy density of $\\dot{2}{,}600\\mathrm{Wh}\\mathrm{kg}^{-1}$ (refs 6,7). Despite the considerable advantages of Li–S battery, several problems prevent it from practical applications: (1) the insulating characteristic of sulphur and its discharge products $(\\mathrm{Li}_{2}\\mathrm{S})$ , leading to a low utilization of active material; (2) large volumetric expansion/shrinkage $(80\\%)$ during discharge/charge, resulting in an instability of the electrode structure; (3) the soluble intermediates $(\\mathrm{Li}_{2}\\mathrm{S}_{x},3{\\stackrel{.}{\\leq}}x\\leq8)$ in the organic liquid electrolyte during the cycle process bring about the polysulphide ‘shuttle effect’, which leads to irreversible capacity loss and corrosion on the lithium-metal anode4,8,9. \n\nMuch effort has been devoted to solving these issues: improving the electrical conductivity of the sulphur electrode by integrating with carbon materials or conductive polymers8–14; adcecsiogmnimngo ytoe t-she l lsturmuce reex wnistih otef saul vhouird1 s6p; ue tog novel electrolyte additives such as $\\mathrm{P}_{2}\\mathrm{S}_{5}$ or ${\\mathrm{Cs}}^{+}$ to suppress the polysulphide shuttle and passivate the lithium-metal surface17,18; and modifying the surface chemistry of the hosts to prevent the shuttle effect of the soluble polysulphides between the cathode and the anode, enabling better cycle performance19–22. However, the areal loading of sulphur electrode in most of the reported work is $<2.0\\mathrm{mg}\\mathrm{cm}^{-2}$ and the sulphur content in the electrode is $<70$ wt. $\\%$ , which are not enough to satisfy the demands for high-energy density batteries5,12,23–25. Generally, conventional electrode requires the use of inactive materials such as conductive agents, metallic current collectors and binders, which will also offset the high-energy density advantage of Li–S batteries. \n\nMoreover, flat current collectors face the challenge of increasing the electrode thickness due to the easy delamination of active materials and limitation in lithium diffusion kinetics. Therefore, three-dimensional (3D) battery electrode design has recently been explored as an effective way to enhance the energy per surface area of batteries26,27. For example, Miao et al.28 synthesized 3D carbon fibre cloth current collectors to host sulphur for achieving high sulphur loading and high areal capacity in Li–S batteries; Wu’s group29 impregnated sulphur into a 3D graphene framework to increase the sulphur areal mass loading in the composite electrodes; Yuan et al.30 adopted a bottom-up strategy to fabricate 3D hierarchical free-standing carbon nanotube-S paper electrodes to improve the sulphur content; and Cheng’s group31 reported flexible 3D graphene foams as the current collector to accommodate large amount of sulphur with high areal capacity. However, with the increase of sulphur loading, the internal sulphur is not easily accessible to the electrolytes and hard to be used rapidly, which leads to the phenomenon of ‘sulphur activation’ with lower capacity in the initial few cycles28,29,31. Therefore, a simpler and more effective way to enable high sulphur utilization, especially when sulphur loading is high, is still challenging while worth exploring. \n\nInstead of adopting solid sulphur as the precursor followed by melt-diffusion or liquid infiltration methods, the dissolved lithium polysulphide systems have recently been proved to make active materials distribute more uniformly, improve sulphur utilization, alleviate electrode structure variation and facilitate the kinetics of the Li–S redox reaction5,7,32–35. Taking the above discussion into consideration, we present the use of a lightweight, porous nitrogen- and sulphur- (abbreviated as N, S) codoped 3D graphene sponge as the additive/binder-free electrode structure to accommodate large amounts of dissolved lithium polysulphides. The active materials could reach as high as $4.{\\dot{6}}\\mathrm{mg}\\mathrm{cm}^{-2}$ when the graphene sponge is employed as a 3D current collector. The interconnected graphene network facilitates fast electron and ion transfer. The sulphur and/or nitrogen doping could facilitate fast charge transfer, increase the affinity between the polysulphide species and the carbon-based framework, facilitate better immobilization of the polysulphide ions, and promote the $\\mathrm{Li}_{2}\\mathrm S/$ polysulphide/S reversible conversion to improve the electrochemical performance of Li–S batteries19,21,22,36. The combination of physical adsorption of lithium polysulphides onto porous graphene and the chemical binding of polysulphides to $\\mathrm{\\DeltaN}$ and S sites in graphene suppresses sulphur loss during the discharge/charge processes, enabling a high specific capacity of $\\mathrm{1,200mAhg^{-1}}$ at $\\bar{0.2\\mathrm{C}}$ rate, a high-rate capacity of $430\\mathrm{\\dot{m}A h\\dot{g}^{-1}}$ at 2C rate and excellent cycling stability for 500 cycles with nearly $100\\%$ Coulombic efficiency for the N,S-codoped graphene electrode. \n\n# Results \n\nSynthesis and characterization of graphene-based sponges. Figure 1a demonstrates the typical photographs of the as-prepared reduced graphene oxide (rGO), S-doped graphene, N-doped graphene and N,S-codoped graphene sponges obtained by hydrothermal reaction using, respectively, GO, ${\\mathrm{G}}{\\bar{\\mathrm{O}}}/{\\mathrm{N}}{\\mathrm{a}}_{2}{\\mathrm{S}}_{\\mathrm{\\Omega}}$ , GO/ urea and GO/thiourea as precursors followed by freeze-drying. ${\\mathrm{Na}}_{2}{\\mathrm{S}}_{\\mathrm{i}}$ , urea and thiourea were employed as sulphur, nitrogen and nitrogen/sulphur sources, as well as reducing agents for GO during the hydrothermal assembly process. After freeze-drying, the morphology of the samples was retained and no obvious shrinkage/expansion is observed. The size and shape of the graphene-based sponges can be adjusted by controlling the concentration of GO, reaction temperature and the volume/shape of the used autoclaves. The freeze-dried N,S-codoped graphene sponge is light and can stand stably on the top of a dandelion without deforming it at all (Fig. 1b), which makes it a good candidate as a lightweight 3D current collector. It can be cut and pressed into slices for direct use as a host for dissolved lithium polysulphides without metal current collectors, binders and conductive additives, and the sulphur/nitrogen doping in graphene is suggested to interact with lithium polysulphide $/\\mathrm{Li}_{2}\\mathrm{S}$ to improve the cycle stability of Li–S batteries, as illustrated in Fig. 1c. \n\nFigure 2a and Supplementary Figure 1 show the typical scanning electron microscopy (SEM) images of the graphenebased sponges. The alkaline solution environment, when using $\\mathrm{Na}_{2}\\mathrm{S}$ and urea as doping sources, is not beneficial for the formation of intact nitrogen- or sulphur-doped graphene sponges in a one-pot hydrothermal reaction due to the increased electrostatic repulsion between the rGO sheets37,38, so the synthesis of rGO sponge followed by sulphur and nitrogen doping strategy is adopted. Therefore, the rGO, S-doped graphene and N-doped graphene sponges show quite similar morphologies (Supplementary Fig. 1a–c), displaying a relatively loose structure with large pores of tens of micrometres formed by linked graphene sheets. In contrast, the N,S-codoped graphene sponge cross-links to form a 3D interconnected network structure with rich pores in a smaller size of $2{-}8\\upmu\\mathrm{m}$ (Fig. 2a). The macropores in the 3D hierarchical network structure allow efficient ion diffusion/mass transfer and could also be used as the buffering/absorption reservoir of polysulphides39,40. Scanning transmission EM (STEM) and high-magnification SEM characterizations reveal that the resultant N,S-codoped graphene sponge consists of wrinkled graphene sheets (Fig. 2b and Supplementary Fig. 2). $\\Nu_{2}$ isothermal adsorption–desorption analysis (Supplementary Fig. 3, Supplementary Table 1) reveals that the Brunauer– Emmmett–Teller specific surface areas of N,S-codoped graphene, N-doped graphene and S-doped graphene sponges are, respectively, $\\mathsf{171.4m^{2}g^{-1}}$ , $136.7\\dot{\\mathrm{m}}^{2}\\mathrm{g}^{-1}$ and $133.5\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , which are slightly higher than that of the rGO sponge $(108.7\\mathrm{m}^{2}\\mathrm{g}^{-1})$ . The $\\Nu_{2}$ adsorption–desorption isotherms of all the graphene-based sponges show a main adsorption at a relative pressure $>0.9$ with a small hysteresis loop (Supplementary Fig. 3a), indicating the predominant meso/macropore structure, consistent with the pore size distributions (Supplementary Fig. 3b) and SEM/STEM observation (Fig. 2a, Supplementary Figs 1 and 2a). Energydispersive X-ray spectroscopy (EDS) reveals the presence of C, O, Cu (from Cu grid), N and S in the N,S-codoped graphene sponge (Fig. 2c), indicating the successfully incorporated N,S atoms into the carbon framework. The EDS elemental mapping further confirms the existence and homogeneous distribution of C, O, N and S on the surface of N,S-codoped graphene (Fig. $2\\mathrm{d-g)}$ . These functional groups are beneficial to restrict the polysulphides from escaping to the electrolyte, which will be discussed below. \n\n![](images/a61825bbbcc187b59a7fffc424e2529076955435b99bf9b5bab7b6fba45fef1c.jpg) \nFigure 1 | Photographs of graphene sponges and schematic model of the assembled cell. (a) Photographs of the rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene sponges after the hydrothermal reaction and freeze-drying. (b) A lightweight N,S-codoped graphene sponge standing on a dandelion. (c) Illustration of the formation process of the N,S-codoped graphene electrode and schematic of the fabrication of a Li/dissolved polysulphide cell with N,S-codoped graphene electrode after adding polysulphide catholyte. \n\n![](images/ce1fa60c22d9560e7b3a8d274587d1f0743ce3804ffbfe49784ddb22d3e66b00.jpg) \nFigure 2 | Morphology and microstructure of the N,S-codoped graphene sponge. (a) SEM image of the N,S-codoped graphene sponge. (b) Highmagnification SEM image of the N,S-codoped graphene sponge. (c) EDS spectrum of the N,S-codoped graphene. (d) Carbon, (e) oxygen, (f) nitrogen and $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ sulphur elemental mappings of the N,S-codoped graphene in b. \n\nThe transformation from GO to the final graphene-based sponges was examined by $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) and Raman spectroscopy (Supplementary Fig. 4). GO shows the typical diffraction peak at $\\sim11^{\\circ}$ (ref. 41). After the hydrothermal reaction, this peak disappears while a broad diffraction peak emerges between $18^{\\circ}$ and $28^{\\circ}$ in the XRD patterns for rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene sponges, demonstrating the reduction of GO (Supplementary Fig. 4a). Moreover, this peak for the N,S-codoped graphene sponge is sharper and shifted to higher angles compared with that of rGO, S-doped graphene and N-doped graphene sponges, suggesting the more efficient reduction process by N,S-doping. Raman spectra further provide additional evidence of the doping and reduction processes (Supplementary Fig. 4b). Two prominent peaks are observed at $1,365\\dot{\\mathrm{cm}}^{-1}$ and $1,\\dot{5}90\\mathrm{cm}^{-1}$ , corresponding to the characteristic $\\mathrm{~D~}$ and $\\mathbf{G}$ bands of carbon materials41, respectively. Generally, the intensity ratio of the D band to $\\mathrm{~G~}$ band $(I_{\\mathrm{D}}/I_{\\mathrm{G}})$ is used to evaluate the degree of defects in carbon materials, and a higher ratio indicates an increased amount of defects that is proportional to the extent of reduction41. Compared with GO $(I_{\\mathrm{D}}/I_{\\mathrm{G}}=0.93)$ , the $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratio increases to 0.99, 1.03, 1.07 and 1.16 for rGO, S-doped graphene, N-doped graphene and N,Scodoped graphene sponges, respectively, suggesting the removal of oxygen-containing groups and the insertion of heteroatoms into the graphene network with more structural defects42. The increased $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratio is indicative of the enhanced reduction, which is in agreement with the electrical conductivity tests of these sponges (Supplementary Fig. 5). \n\nThe surface chemical composition and functional groups of the GO, rGO, S-doped graphene, N-doped graphene and N,Scodoped graphene were identified by X-ray photoelectron spectroscopy (XPS), as shown in Fig. 3. For GO and rGO, only C 1 s and O 1 s signals were detected in the XPS survey spectra. After nitrogen and nitrogen/sulphur doping, a new peak located at $\\sim400.5\\mathrm{eV}$ is observed in both the N-doped graphene and N,Scodoped graphene, corresponding to $\\mathrm{~N~}\\dot{1}\\:s^{43}$ ; two other peaks appearing at 164.5 and $228.2\\mathrm{eV}$ for S-doped graphene and N,S-codoped graphene are attributed to $\\mathtt{S}2\\mathtt{p}$ and $\\textrm{S}2\\:s$ (Fig. 3a), respectively, suggesting the efficient S-doping in graphene. The elemental contents in these samples are summarized in Supplementary Table 2. The nitrogen contents in the N-doped graphene and N,S-codoped graphene reach, respectively, 5.1 at. $\\%$ and $5.4~\\mathrm{at.\\%}$ , and the sulphur contents are $0.6\\ \\mathrm{at.}\\%$ and $3.9\\ \\mathrm{at.\\%}$ , respectively, in S-doped graphene and N,S-codoped graphene, which further confirm that the S and/or N are incorporated into the carbon framework. GO shows a $\\mathrm{C}/\\mathrm{O}$ ratio of 2.4 and this value increases to 6.9 for rGO after the hydrothermal reaction, implying the partial reduction of GO (Fig. 3b). After the S, N- and N/S-doping, the C/O ratio further increases to, respectively, 9.0, 9.5 and 11.4, indicating a more efficient reduction during the doping process, which is consistent with the XRD and Raman results. The deconvoluted C 1 s spectra of GO show four peaks at $284.6\\mathrm{eV}$ , $286.6\\mathrm{eV}$ , $288.1\\mathrm{eV}$ and $288.8\\mathrm{eV}$ (Fig. 3c), respectively, corresponding to $\\mathrm{C-C/C=C}$ , $C{\\mathrm{-}}\\mathrm{O}$ , ${\\mathrm{C}}={\\mathrm{O}}$ and $\\mathrm{{O-}\\dot{C}=\\dot{O}^{44}}$ . After the N,S-doping, these oxygen-containing groups decrease significantly, and the peak intensity corresponding to the $\\mathsf{s p}^{2}$ carbon increases and becomes narrower (Fig. 3d), indicating the removal of oxygen-containing functional groups and the possible formation of $\\mathrm{{C-S/C-N}}$ bonds during the reduction process22,45. The S 2p spectra of the N,S-codoped graphene can be deconvoluted into six peaks (Fig. 3e), which correspond to, respectively, sulphide at 162.1 eV, S–S/S–C bonds at 163.7 and $16\\bar{4}.9\\mathrm{eV}$ , S–O species at 164.7 and $165.9\\mathrm{eV}$ , and sulfate species at $168.6\\mathrm{eV}$ (refs 20,36,45–47). In the N1s spectrum (Fig. 3f), the three different peaks at $398.6\\mathrm{eV}$ , $399.{\\bar{7}}\\mathrm{eV}$ and $401.2\\mathrm{eV}$ are ascribed to, respectively, pyridinic $\\mathrm{\\DeltaN_{:}}$ pyrrolic $\\mathrm{~N~}$ and quaternary $\\mathrm{N}^{21,43}$ . These functional groups are suggested to contribute to improving the affinity and binding energy of the nonpolar carbon atoms with polar polysulphides $/\\mathrm{Li}_{2}\\mathrm{S}_{\\mathrm{:}}$ thus significantly enhancing the cycle stability and rate capability of Li–S batteries19–21,36. \n\n![](images/bcf60b915f20b77cb5c5a0b1d96fd0e7a559ffd022d030b687cb2f21810c799e.jpg) \nFigure 3 | Surface composition analysis. (a) XPS spectra of the surface chemical composition of GO, rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene. (b) Relationship of the C/O ratio in the GO, rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene. C 1s XPS spectra of the (c) GO and (d) N,S-codoped graphene. (e) S 2p XPS spectrum of the N,S-codoped graphene. (f) N 1s XPS spectrum of the N,S-codoped graphene. \n\nAdsorption capabilities and electrochemical performance. The polysulphide adsorption capabilities of these graphene-based sponges were investigated with ultraviolet–visible absorption spectroscopy. Pure $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution was used as a reference, the rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene sponges were immersed into the $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution for $^{\\mathrm{2h}}$ and the concentration variation of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution was analysed. The typical peaks of the polysulphide solution located at 260, 280, 300 and $340\\mathrm{nm}$ (Supplementary Fig. 6) are attributed to the $S_{6}^{2-}$ species48–50. After the absorption for $^{2\\mathrm{h},}$ it can be clearly seen that the intensity decreases in these characteristic absorption peaks and the N,S-codoped graphene sponge exhibits the best adsorption capability compared with the rGO, S-doped graphene and N-doped graphene sponges, demonstrating the improvement in affinity and adsorption between the $S_{6}^{2-}$ species and the graphene after the N,S functionalization. \n\nTo show whether the doped heteroatoms of S and/or N on the graphene have a positive effect on the performance of Li–S batteries, these graphene sponges were cut into slices, compressed and directly used as free-standing electrodes for a series of electrochemical measurements. Different from two-dimensional graphene materials, 3D interconnected porous graphene sponges can provide multidimensional electron transport pathways and easily accessible active sites. Therefore, electrochemical impedance spectroscopy was used to analyse the kinetics of the electrochemical reactions. Figure 4a shows the Nyquist plots of the graphene-based sponge electrodes at the open-circuit voltage before cycling, and the equivalent circuit is shown in Supplementary Fig. 7. The high frequency intercept at the real axis corresponds to the internal impedance $(R_{\\mathrm{e}})$ , and the semicircles located in the higher and lower frequency regions, respectively, correspond to the surface film resistance $(R_{\\mathrm{f}})$ and the charge-transfer resistance $(R_{\\mathrm{ct}})$ of the batteries51. The other elements in the equivalent circuit include a constant phase element (CPE) about the double-layer capacitance, Warburg impedance $(Z_{\\mathrm{w}})$ and space charge capacitance $(\\mathrm{CPE^{\\prime}})^{52}$ . From the plots, it can be seen that the rGO electrode has the largest internal resistance $(13.7\\Omega)$ , while this resistance in the S-doped graphene $(5.5\\Omega)$ , N-doped graphene $(4.3\\Omega)$ and N,S-codoped graphene $(3.7\\Omega)$ electrodes are lower, which are in accordance with the results of the electrode electrical conductivity (Supplementary Fig. 5). The $R_{\\mathrm{ct}}$ of the N,S-codoped graphene electrode is much smaller than those of the rGO, S-doped graphene and N-doped graphene electrodes (Supplementary Table 3), which could be attributed to the interconnected porous graphene network and doped $\\mathrm{N}/\\mathrm{S}$ atoms, facilitating the charge transfer for surface reactions21,22,36. Figure 4b demonstrates the galvanostatic charge/ discharge profiles of the Li/dissolved polysulphide batteries with the rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene electrodes at 0.2C rate $\\mathrm{'l\\dot{C}=\\dot{1},675m A g^{-1}}.$ ). Compared with the rGO, S-doped graphene and N-doped graphene electrodes, the discharge/charge profiles of the $^{\\mathrm{~\\sc~N},S}$ -codoped graphene electrode have an obvious higher discharge plateau at ${\\stackrel{-}{\\sim}}2.32\\mathrm{V}$ (reduction of sulphur to long-chain lithium polysulphides) and a longer plateau at ${\\sim}2.10\\mathrm{V}$ (formation of short-chain lithium polysulphides) with corresponding charge plateaus at $\\sim2.30$ and $\\sim2.45\\mathrm{V}$ (transformation from $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ to long-chain lithium polysulphides and then to sulphur)53. These plateaus are longer and flatter with lower polarization and are well-retained even at higher current densities of $0.3–2\\mathrm{C}$ rates between the charge/discharge processes when compared with those of rGO, S-doped graphene and N-doped graphene electrodes (Fig. 4c and Supplementary Fig. 8), suggesting better redox reaction kinetics with good reversibility. For example, the overpotential is $809\\mathrm{mV}$ in the N,S-codoped graphene electrode at a high rate of $2\\mathrm{C},$ much lower than that of rGO electrode $(1,185\\mathrm{mV})$ , S-doped graphene $\\mathrm{(1,080mV)}$ and N-doped graphene electrode $(1,010\\mathrm{mV})$ . \n\nThe cycle performances of these electrodes were first tested at a small current density of 0.2C rate, as shown in Fig. 4d. The N,Scodoped graphene electrode delivers an initial discharge capacity of $1,\\dot{2}00\\dot{\\mathrm{mAhg}}^{-1}$ , and the capacity is retained at $822\\mathrm{mA}\\dot{\\mathrm{h}}\\mathrm{g}^{-1}$ after 100 cycles with nearly $100\\%$ Coulombic efficiency, which is much higher than that of the rGO, S-doped graphene and N-doped graphene electrodes with values of $495\\mathrm{mAh}\\mathrm{g}^{-1}$ , $646\\mathrm{{\\dot{mAh}g^{-1}}}^{\\cdot}$ and $705\\mathrm{{mAhg}^{-1}}$ , respectively. Lithium nitrate $\\left(\\mathrm{LiNO}_{3}\\right)$ is added to promote the formation of a stable passivation film, and the capacity decay at the initial few cycles is partially due to the $\\mathrm{LiNO}_{3}^{-}$ decomposition and the formation of a SEI film on the lithium anode surface54,55. To further elucidate the electrochemical reactivity of doped sulphur in the graphene framework, the blank galvanostatic charge/discharge profiles and the cyclic stability of N,S-codoped graphene are shown in Supplementary Fig. 9. It can be seen that the first discharge capacity is $2\\mathrm{i}9\\mathrm{m}\\mathrm{\\breve{A}h g^{-1}}$ , and the voltage plateau at $\\mathrm{\\sim}1.6\\mathrm{V}$ is attributed to the reduction of $\\mathrm{LiNO}_{3}$ on the carbon and lithium surface55. The capacity remains to be only $46\\mathrm{mAhg^{-1}}$ after 100 cycles, demonstrating its little contribution to the overall capacity. To demonstrate the rate capabilities of these electrodes, the current density was changed from 0.2 to 2C rate, as shown in Fig. 4e. The average discharge capacities for the $_{\\mathrm{~N},S}$ -codoped graphene electrode at 0.2C, 0.5C, 1C and 2C rates are, respectively, $\\mathrm{1,157\\mAh{g}^{-1}}$ , $912\\mathrm{mAh}\\mathrm{g}^{-1}$ , $675\\mathrm{{mAhg}^{-1}}$ and $43\\bar{0}\\mathrm{mAh}\\mathrm{g}^{-1}$ , indicating a high charge/discharge capability. However, the rGO electrode shows almost no capacity at 2C rate, demonstrating poor rate performance. When the current density was reduced back to $0.5\\mathrm{C}$ rate, the discharge capacity can be recovered to $878\\mathrm{mAh}\\mathrm{g}^{-1}$ for the N,S-codoped graphene electrode, indicating that the electrode structure remains stable after the high-current-density test. Even after the rate capability test, the N,S-codoped graphene electrode still shows excellent long-cyclic performance with higher capacity $(550\\mathrm{mAh}\\mathrm{g}^{-1})$ and retention $(63\\%)$ compared with the rGO ( $(66\\mathrm{mAh}\\mathrm{g}^{-1}$ , $16\\%$ , S-doped graphene $(1\\dot{9}0\\mathrm{mAh}\\mathbf{g}^{-1}$ , $42\\%)$ ) and N-doped graphene $(221\\mathrm{\\bar{mAhg}^{-1}}$ , $43\\%$ ) electrodes at a current density of $0.5\\mathrm{C}$ rate up to 500 cycles. The capacity decay is only $0.078\\%$ per cycle for the N,S-codoped graphene electrode, much better than those of the rGO, S-doped graphene and N-doped graphene electrodes with decay rates of $0.179\\%$ , $0.124\\%$ and $0.121\\%$ per cycle, respectively. These results imply that the nitrogen- and sulphurdoped 3D porous graphene sponge could not only facilitate fast electron/ion transfer, but also interact strongly with lithium polysulphides to significantly enhance the rate performance and long-term cyclic stability. \n\n![](images/99dcc31c7db910d01a497e9b001c4b83201aa0d7e4db85e993667ee88d6e6186.jpg) \nFigure 4 | Electrochemical performance of Li/polysulphide batteries with different graphene electrodes. (a) Nyquist plots of the rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene electrodes before cycling from 1 MHz to $100\\boldsymbol{\\mathrm{m}}\\boldsymbol{\\mathrm{H}}z$ at room temperature. $(\\pmb{6})$ The second galvanostatic charge/discharge profiles of the rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene electrodes at 0.2C rate within a potential window of $1.5\\substack{-2.8\\vee}$ versus $\\mathsf{L i}^{+}/\\mathsf{L i}^{0}$ . (c) Comparison of the potential difference between the charge and discharge plateaus at different current densities. (d) Cycling performance and Coulombic efficiency of the Li polysulphide batteries with the rGO, S-doped graphene, N-doped graphene and N,Scodoped graphene electrodes at 0.2C rate for 100 cycles. (e) Rate performance of the rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene electrodes at different current densities and long-term cycle stability of the corresponding electrodes at 0.5C for 500 cycles after the highcurrent-density test. \n\nTo further improve the energy density of the whole battery system and satisfy the demands of high-energy batteries, the active material loading was increased from 4.6 to $\\stackrel{.}{8}.5\\mathrm{mg}\\mathrm{cm}^{-2}$ by adding more $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte into the N,S-codoped graphene electrode with the help of a graphene-coated separator, which has been confirmed as a very useful approach to obtain highperformance Li–S batteries56. From the charge/discharge curves of the N,S-codoped graphene electrodes with graphene-coated separator (Fig. 5a), it is obviously observed that two discharge/ charge plateaus are well-retained even at a high rate of 2C, indicating that the reaction dynamic is not affected by high sulphur loading. Owing to the uniform distribution of liquidphase active materials, the polysulphides could be utilized effectively, thereby avoiding the phenomenon of ‘sulphur activation’28,29,31. The unique structure enables the battery to deliver a high capacity of $\\mathrm{i},070\\mathrm{mAhg}^{-1}$ at $0.2\\mathrm{C}$ rate, and the reversible discharge capacity could reach ca. $500\\mathrm{mAhg^{-1}}$ at a large current density of 2C rate (Fig. 5b). In addition, a long-term cyclic test at 0.5C rate was carried out and the initial specific capacity is $925\\mathrm{{mAh}\\mathrm{{g}^{-1}}}$ , which stabilizes $\\sim670\\mathrm{mAhg^{-1}}$ after 200 cycles (Fig. 5c). The advantages of such electrode configuration design includes the following: (i) the graphene sponge functions as a 3D current collector to accommodate a large amount of active material, and the internal graphene layer further improves the polysulphide utilization due to the increased overall electrical conductivity of the system; (ii) the graphene layers effectively trap the dissolved lithium polysulphide and provide more active sites for $\\mathrm{Li}_{2}\\mathrm{S}$ deposition; (iii) the 3D graphene network and graphene layer can accommodate the volume change of the active material during cycling; and (iv) the chemical binding between the sulphur/nitrogen heteroatoms and lithium polysulphide $\\mathrm{\\DeltaLi}_{2}\\mathrm{S}$ reduces the active material loss, realizing long cycle life and high-energy/power density Li–S batteries. \n\n![](images/801c2c8ce32af1611f5992feabb68de139423b3d8ba88a9bcdf81b777b291c94.jpg) \nFigure 5 | Electrochemical measurement of N,S-codoped graphene electrode with graphene-coated separator. (a) Galvanostatic charge/discharge profiles of the N,S-codoped graphene electrode with graphene-coated separator at various rates within a potential window of $1.5\\substack{-2.8\\vee}$ versus $\\mathsf{L i^{+}}/\\mathsf{L i^{0}}$ . (b) Rate performance of the N,S-codoped graphene electrode with graphene-coated separator at different current densities. (c) Cycling performance and Coulombic efficiency of the Li polysulphide batteries with the N,S-codoped graphene electrodes and graphene-coated separator at 0.5C rate for 200 cycles. \n\n# Discussion \n\nTo understand the structure and surface modification in improving the performance of N,S-codoped graphene electrode, the cells were disassembled inside the glove box and the surface morphology of the graphene-based sponge cathodes and the lithium metallic anodes after 100 cycles were observed by SEM. It can be seen that a thick layer of lithium sulphide $(\\mathrm{Li}_{2}\\mathrm{S})$ deposition is present on the surface of rGO and the corresponding metallic lithium surface is rough with many coarse lithium agglomerations (Supplementary Figs 10a and 11a), suggesting a serious parasitic reaction between dissolved lithium polysulphides and metallic lithium anode during cycling. This can also be confirmed from the corresponding sulphur elemental mapping characterization and EDS compositional analysis (Supplementary Fig. 11b, Supplementary Table 4). In contrast, less deposition is seen on the S-doped graphene and N-doped graphene electrodes (Supplementary Fig. $^{10\\mathrm{b},\\mathrm{c}^{\\mathrm{}}}$ , and no obvious aggregations of sulphur species are observed on the N,S-codoped graphene electrode (Supplementary Fig. 10d), showing less dissolution loss of polysulphides into the electrolyte and their re-deposition on the S-doped, N-doped and N,S-codoped graphene electrodes. Correspondingly, the lithium surface of S-doped graphene, N-doped graphene and N,S-codoped graphene electrodes is also smoother (Supplementary Fig. 11c,e,g) with respect to the rGO electrode, showing that less side reactions have occurred on the surface of metallic lithium, thereby alleviating the lithium surface corrosion and contributing to the improved cycling performance (Supplementary Fig. ${\\bar{1}}{\\bar{1}}{\\bar{\\mathrm{d}}},{\\bar{\\mathrm{f}}},{\\bar{\\mathrm{h}}}$ and Supplementary Table 4). \n\nTo better understand the doping effect, density functional theory (DFT) calculations were performed to examine how the binding strength of the Li–S end of linear lithium polysulphides $(\\mathrm{Li}_{2}\\mathsf{S}_{x})$ is influenced by the incorporation of N and/or S atoms into the graphene lattice. Here we used a small LiSH molecule to model the Li–S end. This model is simple but should be sufficient enough to demonstrate the influence of doping particularly on the binding interaction of the terminal $\\mathrm{Li^{+}}$ cation with a doped graphene sheet, although lithium polysulphides may also exist as complex clusters57–59. To confirm whether the H-terminated S will influence the predicted binding strength of the terminal $\\mathrm{Li^{+}}$ , we also considered $\\mathrm{Li}_{2}\\mathrm S$ adsorption at a few selected dopant sites, as shown in Supplementary Fig. 12. There are no significant binding energy differences between $\\mathrm{Li}_{2}\\mathrm S$ and LiSH, implying that it would be reasonable and feasible to use LiSH for the purpose of supporting our experimental observations. For a reference, we first considered the binding of LiSH to a pristine graphene sheet and a 1,3-dioxolane (DOL) molecule, which is widely used for the electrolyte in a Li–S cell. As shown in Fig. 6a, the Li of LiSH is preferentially located at the hollow site above the centre of a hexagon ring with a predicted binding energy of $E_{\\mathrm{b}}=0.78\\mathrm{eV}_{\\mathrm{:}}$ , in good agreement with the previous DFT results57. Here the $\\boldsymbol{E_{\\mathrm{b}}}$ is given by $E_{\\mathrm{LiSH}}+E_{\\mathrm{Gr}}-E_{\\mathrm{LiSH/Gr}},$ where $E_{\\mathrm{LiSH}},~E_{\\mathrm{Gr}}$ and $E_{\\mathrm{LiSH/Gr}}$ represent the total energies of an isolated LiSH, pristine (or doped) graphene and LiSH adsorbed graphene, respectively. Our calculations also predict that the Li of LiSH can be strongly bound to the O site of DOL with $E_{\\mathrm{b}}=0.93\\mathrm{eV}$ (Fig. 6b); the larger $\\boldsymbol{E_{\\mathrm{b}}}$ than that for the graphene case $(0.78\\mathrm{eV})$ may suggest that lithium polysulphides would dissolve into the DOL-based electrolyte instead of adsorbing on the graphene surface, consistent with the existing experimental observations10,47. \n\nNext, we examined the interaction of LiSH with doped graphene. Figure 6 shows the adsorption configurations of LiSH at highly probable binding sites identified from our DFT calculations; (Fig. 6c–e) S doped, (Fig. 6f–h) N doped and (Fig. 6i–k) N,S codoped. Compared with the case of pristine graphene, the $\\boldsymbol{E_{\\mathrm{b}}}$ is predicted to increase by $0.24\\mathrm{eV}$ at the thionic S site (Fig. 6c), but decrease by $0.26\\mathrm{eV}$ at the thiophenic S site (Fig. 6d). We also considered the interaction of LiSH with S placed on the basal plane of graphene (Fig. 6e), but the weakly bound S turns out to easily desorb off the graphene surface by forming $\\mathrm{LiS}_{2}\\mathrm{H}$ LiSH is also found to strongly interact with pyridinic and pyrrolic $\\mathrm{~N~}$ at the edge of graphene (Fig. $\\lvert6\\mathrm{f},\\mathrm{g}\\rangle$ ; the predicted $E_{\\mathrm{b}}$ of $1.29\\mathrm{eV}$ and $1.43\\mathrm{eV}$ , respectively, are substantially greater than that of the pristine graphene case $(0.78\\mathrm{eV})$ . On the other hand, the quaternary $\\mathrm{~N~}$ doping (Fig. 6h) appears to insignificantly affect the LiSH binding strength, although the electron-rich surface due to electron donation from N likely leads to the increase in $\\boldsymbol{E_{\\mathrm{b}}}$ to a certain extent. Overall, our results are consistent with the previously reported DFT results19,21,22. Looking at N,S-codoped graphene, our DFT calculations predict that thionic S can exist adjacent to pyridinic or pyrrolic N, as shown in Fig. 6i,j; the total energy of the codoped graphene tends to increase (decrease) with the $_{S-\\mathrm{N}}$ distance in the case of pyridinic (pyrrolic) N, but only marginally $(<0.05\\mathrm{eV})$ . When thionic S and pyridinic (pyrrolic) $\\mathrm{~N~}$ are located nearby, the binding strength of LiSH is predicted to increase significantly, yielding $E_{\\mathrm{b}}=1.82$ $(2.06)\\mathrm{eV}$ as compared with the separately doped cases (Fig. $\\lvert6\\mathrm{f},\\mathrm{g}\\rvert$ ). In addition, we find that LiSH is likely to interact more strongly with thionic S in the quaternary N-doped graphene (Fig. 6k), in comparison to the case of single doped graphene (Fig. 6c). \n\nN and S atoms could be incorporated into graphene in various configurations, yielding a wide range of $E_{\\mathrm{b}};$ a few additional cases are presented in Supplementary Fig. 13. Nonetheless, our DFT results clearly demonstrate that the coexistence of $\\mathrm{~N~}$ and S can significantly enhance the binding of lithium polysulphides, when compared with the undoped or single N/S-doping cases. In addition, according to our calculations, thionic S and pyridinic (or pyrrolic) N could exist adjacent to each other at graphene edges and vacancies, which may in turn lead to an increase in the amount of dopants, when N and S are codoped as compared with the cases of single N (or S)-doping. Overall, our theoretical findings regarding the synergistic effect of N,S-codoping wellsupport our experimental observations. \n\n![](images/19640e7fba3874d2e933cbea5e2eed5ee9fd24482cc920f4ac8a3f265a5b892f.jpg) \nFigure 6 | Theoretical calculations. Optimized configurations for the binding of LiSH to (a) pristine graphene, (b) 1,3-dioxolane, (c–e) S-doped graphene, (f–h) N-doped graphene and (i–k) N,S-codoped graphene. Charge density difference isosurfaces are shown in the insets; the blue and yellow colours indicate the regions of charge gain and loss (of $\\pm0.001$ e per bohr3), respectively. Grey, white, blue, yellow, purple and red balls represent C, H, N, S, Li and O atoms, respectively. LiSH binding energies (in eV) and selected bond distances (in Å) are also indicated. \n\nIn summary, we have built a strong bound interface between graphene and soluble lithium polysulphides by N,S-codoping to optimize the electrochemical performance towards stable and high-energy density Li–S batteries. The N,S-codoped graphene conductive framework provides high electrical conductivity, strong adsorption abilities for polysulphides and rapid ontransport channels, and works as a 3D scaffold to accommodate high active material loading. As a result, the N,S-codoped graphene electrode with a high sulphur loading of $4.6\\mathrm{mg}\\mathrm{cm}^{-2}$ exhibits fast reaction dynamics, reduced polarization and stabilized cycling performance with only $0.078\\%$ capacity decay per cycle up to 500 cycles. In addition, the sulphur loading could be further increased to $8.5\\mathrm{mg}\\mathrm{cm}^{-2}$ using the 3D N,S-codoped graphene current collector with the help of a graphene-coated separator. The high loading polysulphides could be effectively utilized with high reversibility and excellent stability. This work demonstrates the great potential of using 3D current collector and surface chemical modifications for high-energy density, long-life energy storage devices. \n\n# Methods \n\nSynthesis of GO. GO was synthesized using natural graphite flakes by a modified Hummers’ method60. The concentration of the GO suspension obtained was $2.6\\mathrm{mg}\\mathrm{ml}^{-1}$ , which was determined by freeze-drying the suspension and weighing the dried GO. \n\nSynthesis of rGO sponge. Hydrothermal assembly and freeze-drying process were combined to fabricate rGO sponge. In a typical procedure, $50\\mathrm{ml}$ of GO suspension was transferred into a $100\\mathrm{{\\dot{m}}} $ Teflon-lined stainless steel autoclave and hydrothermally treated at $180^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . Then the autoclave was naturally cooled to room temperature, the black rGO hydrogel was washed with distilled water and the wet hydrogel was freeze-dried to obtain the rGO sponge. \n\nSynthesis of S-doped graphene sponge. About $0.01\\mathrm{mol}$ of $\\mathrm{Na}_{2}\\mathrm{S}$ was added to $50\\mathrm{ml}$ of distilled water and the above obtained rGO hydrogel was then transferred into the solution, sealed in the autoclave and maintained at $180^{\\circ}\\mathrm{C}$ for $12\\mathrm{{h}}$ . After that, the S-doped graphene hydrogel was dipped into distilled water and washed several times to remove the residual salts and freeze-dried to obtain the S-doped graphene sponge. \n\nSynthesis of N-doped graphene sponge. About $0.01\\mathrm{mol}$ of urea was added to $50\\mathrm{ml}$ of distilled water and stirred magnetically for $30\\mathrm{min}$ . The obtained rGO hydrogel was then transferred into the solution and sealed in the autoclave and maintained at $180^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . After that, the N-doped graphene hydrogel was dipped into distilled water and washed several times to remove the residual urea and freeze-dried to obtain the N-doped graphene sponge. \n\nSynthesis of N,S-codoped graphene sponge. In brief, $50\\mathrm{ml}$ of the GO aqueous dispersion and $0.01\\mathrm{mol}$ of thiourea were mixed and the mixture was stirred for $30\\mathrm{min}$ and sealed in a $100\\mathrm{ml}$ Teflon-lined stainless steel autoclave for hydrothermal reaction at $180^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . Then the black hydrogel was washed with distilled water several times to remove the residual thiourea and freeze-dried to obtain the N,S-codoped graphene sponge. \n\nMaterials characterization. SEM observations were carried out on a FEI Quanta 650 SEM operated at $20\\mathrm{kV}$ . STEM was performed with a Hitachi S-5500 SEM, and EDS was used for collecting elemental signals and mapping. XRD patterns were collected with a Philips X-ray diffractometer with Cu $\\mathtt{K}\\mathtt{\\backslash}$ radiation $\\ '\\lambda=0.154056$ nm) between $10^{\\circ}$ and $70^{\\circ}$ at a scan rate of $0.04^{\\circ}\\thinspace s^{-1}$ . Raman spectra were collected with a $488\\mathrm{nm}$ laser under ambient conditions with a WITEC Alpha300 S micro \n\nRaman system at room temperature. XPS analysis was performed on a Kratos Analytical spectrometer at room temperature with monochromatic $\\mathrm{AlK}\\propto$ $(1,486.6\\mathrm{eV})$ radiation. Ultraviolet–visible absorption spectroscopy analysis was performed to evaluate the polysulphide adsorption capability of rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene sponges. About $4\\mathrm{mg}$ each of rGO, S-doped graphene, N-doped graphene and $^{\\mathrm{N},\\mathrm{S}}$ -codoped graphene sponges were separately added into four sealed vials of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution ( $\\mathrm{\\dot{4}m l}$ each, $0.1\\mathrm{mmoll}^{-1}$ ), and the $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution without adding anything was used as a control. After absorption for $^{2\\mathrm{h}}$ , the ultraviolet–visible absorption spectra of these solutions were collected with an Evolution 300 UV–vis spectrophotometer with baseline correction. The electrical conductivity of the electrodes was measured by a standard four-point probe resistivity measurement system (S-302-4, Lucas Labs Resistivity, USA). Three measurements were taken at different positions on the sample, and the average value was taken. \n\nPreparation of electrolyte and polysulphide catholyte. The blank electrolyte was prepared by dissolving an appropriate amount of lithium trifluoromethanesulfonate $(\\mathrm{LiCF}_{3}\\mathrm{SO}_{3}$ $98\\%$ , Acros Organics, 1 M) and $\\mathrm{LiNO}_{3}$ $(99+\\%$ , Acros Organics, $0.1\\mathrm{M})$ in DME $(99+\\%,$ Acros Organics) and DOL $(99.5\\%)$ Acros Organics) (1:1 by volume). The polysulphide catholyte was prepared by chemically reacting sublimed sulphur $(99.5\\%$ , Fisher Scientific) and an appropriate amount of $\\mathrm{Li}_{2}\\mathrm{S}$ $99.9\\%$ , Acros Organics) in the blank electrolyte to form $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ (1.0 M) in the solution. The solution was then stirred at $50^{\\circ}\\mathrm{C}$ in an Ar-filled glove box overnight to produce a brownish-red $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte solution. \n\nElectrochemical measurements. The Li/dissolved polysulphide cells (CR2032 coin cells) were assembled in an Ar-filled glove box. The rGO, S-doped graphene, N-doped graphene and N,S-codoped graphene sponges were dried at $120^{\\circ}\\mathrm{C}$ under vacuum overnight before using. These samples were cut, compressed and shaped into rectangular plates to be used as the current collectors with an area of $0.5\\dot{\\mathrm{cm}}^{2}$ and a mass of $0.9\\mathrm{-}1.4\\mathrm{mg}$ . About $12\\upmu\\mathrm{l}$ of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte $(1.0\\mathbf{M})$ was added into each of the rGO, S-doped graphene, N-doped graphene and $_{\\mathrm{~N},S}$ -codoped graphene electrodes, corresponding to a sulphur loading of $4.6\\mathrm{mg}\\mathrm{cm}^{-2}$ . The Celgard 2500 separator was then placed on top of the electrode, followed by adding $30\\upmu\\mathrm{l}$ of the blank electrolyte. Finally, the lithium-metal foil anode was placed on the separator as the anode. An Arbin battery cycler was used to perform the galvanostatic cycling measurements at $1.5\\mathrm{-}2.8\\mathrm{V}$ (versus $\\mathrm{Li/Li^{+}}$ ) at room temperature. The current density set for tests was referred to the mass of sulphur in the cathode and was varied from 0.2C to 2C rate. For the high sulphur loading cathode, $22\\upmu\\updownarrow$ of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte $(1.0\\mathrm{M})$ was added into the N,S-codoped graphene electrodes, corresponding to a sulphur loading of $8.5\\mathrm{mg}\\mathrm{cm}^{-2}$ . The graphene-coated separator was used to place on the top of the sulphur cathode followed by adding $50\\upmu\\mathrm{l}$ of the blank electrolyte. Electrochemical impedance spectroscopy measurements were performed with a Solartron Impedance Analyzer (Solartron 1260A) in the frequency range of 1 MHz to $0.1\\mathrm{Hz}$ with an AC voltage amplitude of $5\\mathrm{mV}$ at the open-circuit potential. For the cycled samples, the cycled cells were disassembled inside an Ar-filled glove box, and the electrodes were rinsed with 1,2-dimethoxyethane solvent to remove the lithium salt and dried inside the glove box at room temperature before analysis. \n\nTheoretical calculations. The atomic configurations and binding energies reported herein were calculated using DFT within the Perdew–Berke–Ernzerhof generalized gradient approximation (GGA-PBE)61, as implemented in the Vienna $\\vert A b$ initio Simulation Package $(\\mathrm{VASP})^{62}$ . We employed the projector augmented wave method to describe the interaction between ion core and valence electrons and a plane-wave basis set with a kinetic energy cutoff of $400\\mathrm{eV}$ . A graphene sheet was modelled using a hexagonal $7\\times7$ supercell; we used the GGA-optimized lattice constant of $2.466\\mathring{\\mathrm{A}}$ , which is close to the experimental value of $2.46\\mathring{\\mathrm{A}}$ . Periodic boundary conditions were employed in all three directions with a vacuum gap of $15\\mathrm{\\AA}$ in the vertical $(z)$ direction to avoid interactions between graphene and its periodic images. To model N and/or S dopant atoms at graphene edges and vacancies, we employed a graphene flake consisting of 37C atoms in a periodic simulation box of dimensions $\\mathrm{\\overline{{20}}}\\times20\\times15\\mathrm{\\AA}$ ; dangling C bonds were passivated by H atoms. A gamma-centred $2\\times2\\times1$ Monkhorst–Pack mesh of $\\mathbf{k}$ points was used for the Brillouin zone integration. All atoms were fully relaxed until the residual forces on constituent atoms became smaller than $0.02\\dot{\\mathrm{eV}}\\mathring{\\mathrm{A}}^{-1}$ . We used the semiempirical approach proposed by Grimme63 to take into account the vdW interactions within DFT. \n\n# References \n\n1. Tarascon, J. M. & Armand, M. Issues and challenges facing rechargeable lithium batteries. Nature 414, 359–367 (2001). \n2. Dunn, B., Kamath, H. & Tarascon, J.-M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n3. Bruce, P. G., Freunberger, S. A., Hardwick, L. J. & Tarascon, J.-M. Li- ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ and Li–S batteries with high energy storage. Nat. Mater. 11, 19–29 (2012). \n4. Yang, Y., Zheng, G. & Cui, Y. Nanostructured sulfur cathodes. Chem. Soc. Rev. \n42, 3018–3032 (2013). sulfur batteries. Chem. Rev. 114, 11751–11787 (2014). \n6. Liang, Z. et al. Sulfur cathodes with hydrogen reduced titanium dioxide inverse opal structure. ACS Nano 8, 5249–5256 (2014). \n7. Manthiram, A., Fu, Y. & Su, Y.-S. Challenges and prospects of lithium–sulfur batteries. Acc. Chem. Res. 46, 1125–1134 (2012). \n8. Wang, D.-W. et al. Carbon-sulfur composites for Li–S batteries: status and prospects. J. Mater. Chem. A 1, 9382–9394 (2013). \n9. Zhang, Q., Cheng, X. B., Huang, J. Q., Peng, H. J. & Wei, F. Review of carbon materials for advanced lithium-sulfur batteries. New Carbon Mater. 29, 241–264 (2014). \n10. Ji, X. L., Lee, K. T. & Nazar, L. F. A highly ordered nanostructured carbonsulphur cathode for Lithium–sulphur batteries. Nat. Mater. 8, 500–506 (2009). \n11. Zheng, G. et al. Amphiphilic surface modification of hollow carbon nanofibers for improved cycle life of lithium sulfur batteries. Nano Lett. 13, 1265–1270 (2013). \n12. Yin, Y. X., Xin, S., Guo, Y. G. & Wan, L. J. Lithium-sulfur batteries: electrochemistry, materials, and prospects. Angew. Chem. Int. Ed. 52, 13186–13200 (2013). \n13. Lv, W. et al. Tailoring microstructure of graphene-based membrane by controlled removal of trapped water inspired by the phase diagram. Adv. Funct. Mater. 24, 3456–3463 (2014). \n14. Li, Z. et al. Insight into the electrode mechanism in lithium-sulfur batteries with ordered microporous carbon confined sulfur as the cathode. Adv. Energy Mater. 4, 1301473 (2014). \n15. Seh, Z. et al. Sulphur– $\\cdot\\mathrm{TiO}_{2}$ yolk–shell nanoarchitecture with internal void space for long-cycle lithium–sulphur batteries. Nat. Commun. 4, 1331 (2013). \n16. Zhou, W., Xiao, X., Cai, M. & Yang, L. Polydopamine-coated, nitrogen-doped, hollow carbon–sulfur double-layered core–shell structure for improving lithium–sulfur batteries. Nano Lett. 14, 5250–5256 (2014). \n17. Lin, Z., Liu, Z., Fu, W., Dudney, N. J. & Liang, C. Phosphorous pentasulfide as a novel additive for high-performance lithium-sulfur batteries. Adv. Funct. Mater. 23, 1064–1069 (2013). \n18. Ding, F. et al. Dendrite-free lithium deposition via self-healing electrostatic shield mechanism. J. Am. Chem. Soc. 135, 4450–4456 (2013). \n19. Song, J. et al. Nitrogen-doped mesoporous carbon promoted chemical adsorption of sulfur and fabrication of high-areal-capacity sulfur cathode with exceptional cycling stability for lithium-sulfur batteries. Adv. Funct. Mater. 24, 1243–1250 (2014). \n20. Zhou, G. M. et al. Fibrous hybrid of graphene and sulfur nanocrystals for highperformance lithium–sulfur batteries. ACS Nano 7, 5367–5375 (2013). \n21. Peng, H.-J. et al. Strongly coupled interfaces between a heterogeneous carbon host and a sulfur-containing guest for highly stable lithium-sulfur batteries: mechanistic insight into capacity degradation. Adv. Mater. Interfaces 1, 1400227 (2014). \n22. Wang, Z. et al. Enhancing lithium–sulphur battery performance by strongly binding the discharge products on amino-functionalized reduced graphene oxide. Nat. Commun. 5, 5002 (2014). \n23. Hagen, M. et al. Development and costs calculation of lithium–sulfur cells with high sulfur load and binder free electrodes. J. Power Sources 224, 260–268 (2013). \n24. Gao, J. & Abrun˜a, H. D. Key parameters governing the energy density of rechargeable Li/S batteries. J. Phys. Chem. Lett. 5, 882–885 (2014). \n25. Qie, L. & Manthiram, A. A facile layer-by-layer approach for high-arealcapacity sulfur cathodes. Adv. Mater. 27, 1694–1700 (2015). \n26. Hu, L. et al. Lithium-ion textile batteries with large areal mass loading. Adv. Energy Mater. 1, 1012–1017 (2011). \n27. Mazouzi, D. et al. Very high surface capacity observed using Si negative electrodes embedded in copper foam as 3D current collectors. Adv. Energy Mater. 4, 1301718 (2014). \n28. Miao, L., Wang, W., Yuan, K., Yang, Y. & Wang, A. A lithium-sulfur cathode with high sulfur loading and high capacity per area: a binder-free carbon fiber cloth-sulfur material. Chem. Commun. 50, 13231–13234 (2014). \n29. Lu, S., Chen, Y., Wu, X., Wang, Z. & Li, Y. Three-dimensional sulfur/graphene multifunctional hybrid sponges for lithium-sulfur batteries with large areal mass loading. Sci. Rep. 4, 4629 (2014). \n30. Yuan, Z. et al. Hierarchical free-standing carbon-nanotube paper electrodes with ultrahigh sulfur-loading for lithium–sulfur batteries. Adv. Funct. Mater. 24, 6105–6112 (2014). \n31. Zhou, G. M. et al. A graphene foam electrode with high sulfur loading for flexible and high energy Li–S batteries. Nano Energy 11, 356–365 (2015). \n32. Fu, Y., Su, Y.-S. & Manthiram, A. Highly reversible lithium/dissolved polysulfide batteries with carbon nanotube electrodes. Angew. Chem. Int. Ed. 52, 6930–6935 (2013). \n33. Yang, Y., Zheng, G. & Cui, Y. A membrane-free lithium/polysulfide semi-liquid battery for large-scale energy storage. Energy Environ. Sci. 6, 1552–1558 (2013). \n34. Pu, X., Yang, G. & Yu, C. Liquid-type cathode enabled by 3D sponge-like carbon nanotubes for high energy density and long cycling life of Li–S batteries. Adv. Mater. 26, 7456–7461 (2014). polysulfide reservoir for highly reversible Li–S batteries. Adv. Mater. 26, 1360–1365 (2014). \n36. See, K. A. et al. Sulfur-functionalized mesoporous carbons as sulfur hosts in Li–S Batteries: increasing the affinity of polysulfide intermediates to enhance performance. ACS Appl. Mater. Interfaces 6, 10908–10916 (2014). \n37. Bai, H., Li, C., Wang, X. & Shi, G. A pH-sensitive graphene oxide composite hydrogel. Chem. Commun. 46, 2376–2378 (2010). \n38. Shin, Y.-E. et al. An ice-templated, pH-tunable self-assembly route to hierarchically porous graphene nanoscroll networks. Nanoscale 6, 9734–9741 (2014). \n39. Wang, D. W., Li, F., Liu, M., Lu, G. Q. & Cheng, H. M. 3D aperiodic hierarchical porous graphitic carbon material for high-rate electrochemical capacitive energy storage. Angew. Chem. Int. Ed. 47, 373–376 (2008). \n40. Li, L. et al. Monolithic $\\mathrm{Fe}_{2}\\mathrm{O}_{3}/$ graphene hybrid for highly efficient lithium storage and arsenic removal. Carbon 67, 500–507 (2014). \n41. Pei, S. & Cheng, H.-M. The reduction of graphene oxide. Carbon 50, 3210–3228 (2012). \n42. Wang, S. Y. et al. BCN graphene as efficient metal-free electrocatalyst for the oxygen reduction reaction. Angew. Chem. Int. Ed. 51, 4209–4212 (2012). \n43. Wu, Z.-S. et al. Three-dimensional nitrogen and boron co-doped graphene for high-performance all-solid-state supercapacitors. Adv. Mater. 24, 5130–5135 (2012). \n44. Stankovich, S. et al. Synthesis of graphene-based nanosheets via chemical reduction of exfoliated graphite oxide. Carbon 45, 1558–1565 (2007). \n45. Zhao, J., Ren, W. & Cheng, H.-M. Graphene sponge for efficient and repeatable adsorption and desorption of water contaminations. J. Mater. Chem. 22, 20197–20202 (2012). \n46. Demir-Cakan, R. et al. Cathode composites for Li–S batteries via the use of oxygenated porous architectures. J. Am. Chem. Soc. 133, 16154–16160 (2011). \n47. Ji, L. W. et al. Graphene oxide as a sulfur immobilizer in high performance lithium/sulfur cells. J. Am. Chem. Soc. 133, 18522–18525 (2011). \n48. Barchasz, C. et al. Lithium/sulfur cell discharge mechanism: an original approach for intermediate species identification. Anal. Chem. 84, 3973–3980 (2012). \n49. Han, K. et al. Free-standing nitrogen-doped graphene paper as electrodes for high-performance lithium/dissolved polysulfide batteries. ChemSusChem 7, 2545–2553 (2014). \n50. Zhou, G. M., Zhao, Y., Zu, C. & Manthiram, A. Free-standing $\\mathrm{TiO}_{2}$ nanowireembedded graphene hybrid membrane for advanced Li/dissolved polysulfide batteries. Nano Energy 12, 240–249 (2015). \n51. Zu, C. X., Su, Y. S., Fu, Y. Z. & Manthiram, A. Improved lithium-sulfur cells with a treated carbon paper interlayer. Phys. Chem. Chem. Phys. 15, 2291–2297 (2013). \n52. Yuan, L., Qiu, X., Chen, L. & Zhu, W. New insight into the discharge process of sulfur cathode by electrochemical impedance spectroscopy. J. Power Sources 189, 127–132 (2009). \n53. Xiao, L. F. et al. A soft approach to encapsulate sulfur: polyaniline nanotubes for lithium-sulfur batteries with long cycle life. Adv. Mater. 24, 1176–1181 (2012). \n54. Aurbach, D. et al. On the surface chemical aspects of very high energy density, rechargeable Li–Sulfur batteries. J. Electrochem. Soc. 156, A694–A702 (2009). \n55. Zhang, S. S. Role of $\\mathrm{LiNO}_{3}$ in rechargeable lithium/sulfur battery. Electrochim. Acta 70, 344–348 (2012). \n56. Zhou, G. M. et al. A graphene–pure-sulfur sandwich structure for ultrafast, long-life lithium–sulfur batteries. Adv. Mater. 26, 625–631 (2014). \n57. Wang, B., Alhassan, S. M. & Pantelides, S. T. Formation of large polysulfide complexes during the lithium-sulfur battery discharge. Phys. Rev. Appl. 2, 034004 (2014). \n58. Assary, R. S., Curtiss, L. A. & Moore, J. S. Toward a molecular understanding of energetics in Li–S batteries using nonaqueous electrolytes: a high-level quantum chemical study. J. Phys. Chem. C 118, 11545–11558 (2014). \n59. Wang, L. et al. A quantum-chemical study on the discharge reaction mechanism of lithium-sulfur batteries. J. Energy Chem. 22, 72–77 (2013). \n60. Zhao, J., Pei, S., Ren, W., Gao, L. & Cheng, H.-M. Efficient preparation of largearea graphene oxide sheets for transparent conductive films. ACS Nano 4, 5245–5252 (2010). \n61. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n62. Kresse, G. & Furthmu¨ller, J. VASP: the Guide. Vienna University of Technology (2001). \n63. Grimme, S. Semiempirical GGA-type density functional constructed with a long-range dispersion correction. J. Comput. Chem. 27, 1787–1799 (2006). \n\n# Acknowledgements \n\nThis work was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), US Department of Energy, under Award Number DE-AR0000377. G.S.H. also gratefully acknowledges the Robert A. Welch foundation (F-1535) for partial \n\nfinancial support of the computational work and the Texas Advanced Computing Center (TACC) for providing HPC resources. \n\n# Author contributions \n\nG.Z. designed and conducted the experiments and wrote the manuscript. E.P. performed the theoretical calculations and wrote the manuscript. A.M. and G.S.H. conceived and supervised this research and contributed to the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Zhou, G. et al. Long-life Li/polysulphide batteries with high sulphur loading enabled by lightweight three-dimensional nitrogen/sulphur codoped graphene sponge. Nat. Commun. 6:7760 doi: 10.1038/ncomms8760 (2015). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1126_science.aad3749", + "DOI": "10.1126/science.aad3749", + "DOI Link": "http://dx.doi.org/10.1126/science.aad3749", + "Relative Dir Path": "mds/10.1126_science.aad3749", + "Article Title": "Ultrahigh power factor and thermoelectric performance in hole-doped single-crystal SnSe", + "Authors": "Zhao, LD; Tan, GJ; Hao, SQ; He, JQ; Pei, YL; Chi, H; Wang, H; Gong, SK; Xu, HB; Dravid, VP; Uher, C; Snyder, GJ; Wolverton, C; Kanatzidis, MG", + "Source Title": "SCIENCE", + "Abstract": "Thermoelectric technology, harvesting electric power directly from heat, is a promising environmentally friendly means of energy savings and power generation. The thermoelectric efficiency is determined by the device dimensionless figure of merit ZT(dev), and optimizing this efficiency requires maximizing ZT values over a broad temperature range. Here, we report a record high ZT(dev) similar to 1.34, with ZT ranging from 0.7 to 2.0 at 300 to 773 kelvin, realized in hole-doped tin selenide (SnSe) crystals. The exceptional performance arises from the ultrahigh power factor, which comes from a high electrical conductivity and a strongly enhanced Seebeck coefficient enabled by the contribution of multiple electronic valence bands present in SnSe. SnSe is a robust thermoelectric candidate for energy conversion applications in the low and moderate temperature range.", + "Times Cited, WoS Core": 1906, + "Times Cited, All Databases": 2011, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000367806500033", + "Markdown": "# Ultrahigh power factor and thermoelectric performance in hole-doped single-crystal SnSe \n\nLi-Dong Zhao,1,2\\* Gangjian Tan,2 Shiqiang Hao,3 Jiaqing He,4 Yanling Pei,1 Hang Chi,5 Heng Wang,6 Shengkai Gong,1 Huibin Xu,1 Vinayak P. Dravid,3 Ctirad Uher,5 G. Jeffrey Snyder,3 Chris Wolverton,3 Mercouri G. Kanatzidis2\\* \n\nThermoelectric technology, harvesting electric power directly from heat, is a promising environmentally friendly means of energy savings and power generation. The thermoelectric efficiency is determined by the device dimensionless figure of merit $Z T_{\\mathrm{dev}},$ and optimizing this efficiency requires maximizing ZT values over a broad temperature range. Here, we report a record high $Z T_{\\mathrm{dev}}$ ${\\sim}1.34$ , with ZT ranging from 0.7 to 2.0 at 300 to 773 kelvin, realized in hole-doped tin selenide (SnSe) crystals. The exceptional performance arises from the ultrahigh power factor, which comes from a high electrical conductivity and a strongly enhanced Seebeck coefficient enabled by the contribution of multiple electronic valence bands present in SnSe. SnSe is a robust thermoelectric candidate for energy conversion applications in the low and moderate temperature range. \n\nith more than $60\\%$ of the world’s produced energy being lost as waste heat in the low and moderate temperature range, a compelling need exists for highperformance thermoelectric materials \nthat can directly convert this heat to electrical \npower (1–5). The thermoelectric conversion ef \nficiency is characterized by the temperature \ndependent quantity $Z T=S^{2}\\upsigma T/\\upkappa$ , where $s$ is the \nSeebeck coefficient, $\\upsigma$ is the electrical conduc \ntivity, $\\upkappa$ is the total thermal conductivity, $T$ is the \ntemperature, and the product $(S^{2}\\upsigma)$ is the power \nfactor $(P F)$ . The conversion efficiency of heat to \nelectricity for a large number of potential appli \ncations requires enhancing $Z T$ over a wide range \nof temperatures. However, many previous ad \nvances have focused on improving the maximum \n$Z T(Z T_{\\operatorname*{max}})$ as a function of temperature (6–16). \nMany such improvements in $Z T_{\\mathrm{max}}$ came from \nstrategies such as hierarchical architecturing, \nband structure engineering, and intrinsically low \nthermal conductivity, which enabled huge reduc \ntions in lattice thermal conductivity (e.g., nano \nstructuring) (6–8). Materials that incorporate \none or more of these strategies include the sys \n\ntems $\\mathrm{AgPb_{m}S b T e_{m+2}}$ (LAST) $(6,8);$ PbTe-SrTe (9), $\\mathrm{NaPb}_{\\mathrm{m}}\\mathrm{SbTe}_{\\mathrm{m+2}}$ (SALT) $(I O)$ , PbTe-Tl $(I I)$ , PbTePbSe (12), $\\mathrm{Mg_{2}(S i,S n)}$ $(I3)$ , MgAgSb $(I4)$ , PbSeCdS $(I5)$ , and triple filled Skutterudites (16). Many of these thermoelectrics are heavy-metal–based materials, which include rare-earth metals and elements with low abundance. Therefore, developing thermoelectrics requires not only a high maximum ZT, but a high ZT value over a wide range of temperatures, and materials made from relatively nontoxic and more earth-abundant elements. \n\nA surprising choice for a promising thermoelectric candidate is SnSe single crystal, because its two-dimensional (2D) anisotropic and lowsymmetry crystal structure would not have been expected to exhibit high carrier mobility (17). Recently, we showed that SnSe exhibits one of the lowest lattice thermal conductivities known for crystalline materials $(<0.4\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at 923 K) (18) and without any doping exhibits record high ZTs along the $b$ and $c$ crystallographic directions at 723 to 973 K (fig. S1). Unlike the facile doping behavior of $\\mathrm{Pb}$ -based rock-salt chalcogenides $(5,I9)$ , doping SnSe is challenging because of the layered anisotropic structure, where each SnSe layer is two atoms thin, and the locally distorted bonding around the Sn and Se atoms. Here, we demonstrate successful hole doping in single crystals of SnSe using sodium as an effective acceptor and find a vast increase in ZT from 0.1 (undoped) to 0.7 (doped) along the $b$ axis at $300\\mathrm{K}$ while obtaining the $Z T_{\\mathrm{max}}$ of 2.0 at 773 K (Fig. 1A). The holedoped SnSe ( $\\mathbf{\\epsilon}_{b}$ axis) outperforms most of current state-of-the-art p-type materials at 300 to $773\\mathrm{K}$ (9, 10, 14, 18, 20, 21) (Fig. 1B). The high $P F$ and $Z T$ give the highest device $Z T(Z T_{\\mathrm{dev}})$ from 300 to $773\\mathrm{K}$ known in the field of thermoelectric materials of \\~1.34. The $Z T_{\\mathrm{dev}}$ over the entire working temperature range is important, as it determines the thermoelectric conversion efficiency (h). The thermoelectric efficiency of a material between a hot temperature $T_{\\mathrm{h}}$ and cold side temperature $T_{\\mathrm{c}}\\mathrm{can}$ be calculated from the Seebeck coefficient, electrical conductivity, and thermal conductivity as a function of $T(22)$ \n\n$$\n\\eta=\\frac{T_{\\mathrm{h}}-T_{\\mathrm{c}}}{T_{\\mathrm{h}}}\\frac{\\sqrt{1+Z T_{\\mathrm{dev}}}-1}{\\sqrt{1+Z T_{\\mathrm{dev}}}+T_{\\mathrm{c}}/T_{\\mathrm{h}}}\n$$ \n\nThe $Z T_{\\mathrm{dev}}$ of hole-doped SnSe is much higher than that of typical high-performance thermoelectrics (9, 18, 23) from 300 to 773 K (Fig. 1C). Although the extremely low thermal conductivity enables the high $Z T$ of undoped SnSe crystals from 723 to 973 K, we attribute the large $Z T_{\\mathrm{dev}}$ enhancement in hole-doped SnSe to the enormous boost in $P F$ in the temperature range from 300 to $773\\mathrm{K}$ The projected conversion efficiency of holedoped SnSe for $T_{\\mathrm{c}}=300\\mathrm{K}$ and $T_{\\mathrm{h}}=773$ K is $\\mathrm{\\sim16.7\\%},$ , which is higher than that of other high-performance thermoelectrics (9, 18, 23) (Fig. 1D). \n\nThe origins of the high performance come from various different contributions. We increased the electrical conductivity of SnSe from ${\\sim}12~\\mathrm{S}\\mathrm{cm}^{-1}$ to $>1500\\ \\mathrm{S\\cm^{-1}}$ (Fig. 2A) by hole doping the material, changing the temperature dependence from semiconductor-like to metal-like. With rising temperature, the electrical conductivity of holedoped SnSe $\\mathit{b}$ axis) decreases from $1486\\ensuremath{\\mathrm{~S~}}\\ensuremath{\\mathrm{cm}}^{-1}$ at $300\\mathrm{K}$ to $148\\mathrm{~Scm^{-1}}$ at 773 K. We estimated the carrier density at $300\\mathrm{~K~}$ using Hall data as ${\\sim}4\\times$ $\\mathrm{{10^{19}\\mathrm{cm}^{-3}}}$ . The Seebeck coefficient is $\\mathrm{\\sim+160\\upmuVK^{-1}}$ at 300 K, close to that of commercial $\\mathrm{Bi}_{2-x}\\mathrm{Sb}_{x}\\mathrm{Te}_{3}$ with similar hole concentrations $\\scriptstyle(24),$ , and increases to ${\\sim}+300~\\upmu\\mathrm{V}~\\mathrm{K}^{-1}$ at $773\\ \\mathrm{K}.$ . The combination of increased electrical conductivity and high Seebeck coefficient results in a $P F$ of ${\\sim}40~\\upmu\\mathrm{W}\\ \\mathrm{cm}^{-1}$ $\\mathrm{K}^{-2}$ for hole-doped SnSe $\\mathit{\\Delta}_{b}$ axis) at $300\\mathrm{~K~}$ (Fig. 2C). This value rivals that of optimized p-type $\\mathrm{Bi}_{2}$ - ${\\bf\\nabla}_{x}\\mathrm{Sb}_{x}\\mathrm{Te_{3}}$ along its $a b$ crystallographic plane direction (24). The $P F s$ remain at a high value of ${\\sim}14\\ \\upmu\\mathrm{W}\\ \\mathrm{cm}^{-1}\\ \\mathrm{K}^{-2}$ around $773\\mathrm{~K~}$ for holedoped SnSe $\\mathit{b}$ axis), which is twice as high as the value of ${\\sim}6.4~\\upmu\\mathrm{W}\\ \\mathrm{cm}^{-1}\\ \\mathrm{K}^{-2}$ at $773\\mathrm{~K~}$ for the undoped SnSe ${\\it B}$ axis) (Fig. 2C, inset). Therefore, the main contribution to the huge enhancement of ZT from 300 to $773\\mathrm{{K}}$ is the superior $P F$ afforded by doping. \n\nThe total thermal conductivity $\\bf\\Pi_{\\mathrm{(K_{tot})}}$ of holedoped SnSe is low and shows a decreasing trend with rising temperature (Fig. 2D). $\\upkappa_{\\mathrm{tot}}$ of holedoped SnSe $(b$ axis) decreases from ${\\sim}1.65\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at $300\\mathrm{K}$ to ${\\sim}0.55\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at $773\\mathrm{K}$ The lattice thermal conductivity $\\mathrm{(\\kappa_{lat})}$ of hole-doped SnSe is as low as that of undoped SnSe. We previously explained this low thermal conductivity in terms of density functional theory (DFT)–calculated large Grüneisen parameters of SnSe caused by strong anharmonic bonding (18). This anharmonicity has recently been experimentally confirmed by inelastic neutron scattering measurements (25). The $\\upkappa_{\\mathrm{lat}}$ values of hole-doped SnSe are still as low as that (0.2 to $0.3\\mathrm{~W~m^{-1}~K^{-1}},$ of undoped SnSe at 773 K (fig. S2D). We note that the intrinsically low thermal conductivity of SnSe is sensitive to the stoichiometric ratio (26) and the sample processing conditions (27). A recent neutron powder diffraction analysis demonstrated a nearly ideal stoichiometry and an exceptionally high anharmonicity of the chemical bonds of SnSe and reported an ultralow thermal conductivity value close to $0.1\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at room temperature for polycrystalline SnSe (26). By strictly eliminating exposure to the atmosphere during sample preparation, Zhang et al. (27) observed lattice thermal conductivities of polycrystalline SnSe as low as those of the SnSe single crystals (18). \n\nThe PFs achieved in hole-doped SnSe are much higher than those in the rock-salt lead and tin chalcogenides (19, 28–30), especially in the 300 to $500\\mathrm{K}$ range. These high PFs derive from the much larger Seebeck coefficient, because the electrical conductivity of hole-doped SnSe $\\mathbf{\\nabla}^{\\mathcal{b}}$ axis) is comparable to those of rock-salt chalcogenides. To obtain insight into the enhanced Seebeck coefficients and PFs, we plotted (similar to a Pisarenko plot) the room-temperature Seebeck coefficients of rocksalt chalcogenides with similar carrier density of $\\sim4\\times10^{19}\\mathrm{cm}^{-3}$ (Fig. 3A). The Seebeck coefficient for hole-doped SnSe at $\\mathord{\\sim}+160\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ is clearly much higher than $\\mathrm{\\sim+70\\upmuVK^{-1}}$ for PbTe (19), $\\sim+60\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ for PbSe (28), $\\sim+50\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ for PbS (29), and ${\\sim}+25\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ for SnTe (30). \n\nFor heavily hole-doped PbTe and PbSe, the Fermi level is pushed downward toward the heavy valence band (19), enhancing the Seebeck coefficient because of the contribution of this second valence band to transport. This enhancement, however, only appears at high temperatures, as the extra contribution of the heavy valence band requires a carrier density of $(\\sim4\\:\\mathrm{to}\\:5)\\times10^{19}\\:\\mathrm{cm}^{-3}$ and (1 to $2)\\times10^{20}\\:\\mathrm{cm}^{-3}$ at $300~\\mathrm{K}$ because the energy difference between the two valence bands in PbTe $\\mathrm{0.15~eV})$ (15) and PbSe $(0.25\\mathrm{eV})$ (19) decreases at high temperatures. The energy difference for PbS and SnTe between the two bands is even larger $\\mathrm{\\Omega_{\\mathrm{>}0.3\\mathrm{eV})}}$ (29, 30), resulting in decreasing Seebeck coefficients from PbTe, to PbSe, to PbS, to SnTe (Fig. 3A). We observed a much larger Seebeck coefficient of $\\mathrm{\\sim+160\\upmuVK^{-1}}$ (at 300 K) for the hole-doped SnSe than expected from a singleband contribution $(\\sim+30\\upmu\\mathrm{V}\\mathrm{K}^{-1})$ , which is well supported by the Pisarenko plot (Fig. 3B). The large Seebeck coefficient suggests the contribution of more than one valence band. This conclusion is supported by Hall data and DFT calculations of the band structure. \n\nThe Hall coefficient $(R_{\\mathrm{H}})$ is consistent with multivalley transport, as it shows a continuous increase with temperature in the range 10 to $773\\mathrm{K}$ (fig. S3A). The values of $R_{\\mathrm{H}}$ in hole-doped SnSe are temperature dependent, thus ruling out the single-band model of transport. The Hall data imply that the convergence of multiple band maxima of hole-doped SnSe is in effect already at very low temperatures; i.e., the energy difference between the competing valence bands is much lower than in other chalcogenide materials. To estimate the energy gap $(\\Delta E)$ between the first two bands, we used a well-developed model for a typical two-band compound to analyze the Hall data. In this model, the temperature-dependent $R_{\\mathrm{H}}\\left(T\\right)$ can be expressed as (19) \n\n$$\n\\frac{R_{\\mathrm{H}}(T)-R_{\\mathrm{H}}(0)}{R_{\\mathrm{H}}(0)}=\\bigg(1-\\frac{\\upmu_{2}}{\\upmu_{1}}\\bigg)^{2}\\bigg(\\frac{m_{2}}{m_{1}}\\bigg)^{3/2}e^{-\\frac{\\Delta E}{k_{\\mathrm{B}}T}}\n$$ \n\nwhere $R_{\\mathrm{H}}(0)$ represents the Hall coefficient at $0\\mathrm{K}$ ; $\\upmu_{1},\\upmu_{2};$ , and $m_{1},m_{2}$ denote the carrier mobilities and density-of-states (DOS) effective masses of the first and the second valence band, respectively; $k_{\\mathrm{B}}$ is the Boltzmann constant; and $\\Delta E$ is the energy separation between the two valence band maxima. The slope $(-\\Delta E/k_{\\mathrm{B}})$ of $\\ln[R_{\\mathrm{H}}(T)-R_{\\mathrm{H}}(0)]/$ $R_{\\mathrm{H}}(0)$ versus $1/T$ yields $\\Delta E\\sim0.02\\ \\mathrm{eV}$ at $0~\\mathrm{K},$ assuming that $\\Delta E$ varies linearly with temperature (fig. S4). This energy gap between the first two valence bands of SnSe is much smaller than that in PbTe, PbSe, PbS, and SnTe (19, 28–31). The $\\Delta E$ $\\sim0.02\\ \\mathrm{eV}$ value is comparable to $k_{\\mathrm{B}}T$ at room temperature, suggesting that the valence bands are nearly equal in energy. This near-degeneracy is consistent with the much higher Seebeck coefficients and PFs observed at room temperature. As the temperature increases, the carriers are thermally distributed over several bands of similar energy, resulting in the enhanced Seebeck coefficient of $\\sim+160\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ at $300\\mathrm{K}$ \n\n![](images/659aed1cdb0dbe54eb87f1769d6f954e7d3bf7e3fcd18c6a08272590d133e6f7.jpg) \nFig. 1. ZT values of hole-doped SnSe crystals and projected efficiency. (C) Device ZT values of hole-doped SnSe (b axis), undoped SnSe (b axis) $(\\boldsymbol{\\mathit{18}})$ , (A) ZTvalues along different axial directions of hole-doped SnSe and undoped PbTe-4SrTe-2Na (9), and PbTe-30PbS-2.5K (23); inset shows typical hole-doped SnSe crystals (18); the ZT measurement uncertainty is about $20\\%$ . (B) ZT SnSe crystals. The temperature range for these values is from 300 to $773\\mathsf{K}.$ . values of hole-doped SnSe (b axis) and the current state-of-the-art $\\mathsf{p}$ -type (D) The calculated efficiency as a function of hot side temperature (cold side thermoelectrics, BiSbTe (20), MgAgSb (14), (GeTe) $\\phantom{-}0.8(\\mathsf{A g S b l e}_{2})_{0.2}$ (21), temperature is 300 K) of hole-doped SnSe (b axis), undoped SnSe (b axis) $\\mathsf{N a P b}_{\\mathsf{m}}\\mathsf{S b}\\mathsf{T e}_{\\mathsf{m}+2}$ (SALT) (10), PbTe-4SrTe-2Na (9), and SnSe (b axis) (18). (18), PbTe-4SrTe-2Na (9), and PbTe-30PbS-2.5K (23). \n\n![](images/101f8f90e0b92cd0cbdec8ecfd8f460d98b90d5dd436cc08f6751e4c4dfbcbb9.jpg) \nFig. 2. Thermoelectric properties as a function of temperature for hole-doped SnSe crystals. (A) Electrical conductivity. (B) Seebeck coefficient. (C) Power factor $(P F)$ ; the inset shows the $P F s$ of hole-doped SnSe and undoped SnSe along the b axis. (D) Total thermal conductivity. \n\nWe analyzed the electronic structure and thermoelectric properties of hole-doped SnSe using DFT calculations of the low-temperature Pnma phase (Fig. 3C). The DFT valence band maximum (VBM) lies in the G-Z direction (band 1 in Fig. 3C), but another valence band is located just below the VBM (band 2). A third band also exists with its band maximum along the $U{-}X$ direction (band 3). The calculation shows a very small energy gap between the first two valence bands in the G-Z direction of ${\\sim}0.06\\mathrm{eV},$ consistent with the very small value experimentally estimated above $(0.02\\mathrm{eV})$ . We found this slight energy difference between calculation and experiment to be reasonable given the approximations underlying the DFT calculations. Such a small energy gap is easily crossed by the Fermi level as the hole doping approaches $\\cdot4\\mathrm{to}5)\\times10^{19}\\mathrm{cm}^{-3}$ . In addition, the energy gap between the first and the third band (i.e., maximum of $U{-}X$ to the maximum $\\Gamma{-}Z)$ is only $0.13\\mathrm{eV}$ . This value is smaller than the $0.15\\mathrm{eV}$ between the first and the second valence bands of PbTe, in which the heavy hole band contribution becomes considerable as the carrier density exceeds $\\sim(4\\tan5)\\times$ $10^{19}\\mathrm{cm}^{-3}\\left(I{\\ensuremath{\\boldsymbol}},3I\\right)$ . Interestingly, the electronic valence bands of SnSe are much more complex than those of PbTe, and the Fermi level of SnSe even approaches the fourth, fifth, and sixth valence bands for doping levels as high as $5\\times10^{20}\\mathrm{cm}^{-3}$ (Fig. 3C). Another illustration of the complex band structure is shown in the Fermi surface, which has multiple types of pockets (or valleys) coming from the numerous valence bands, all within a small energy window (Fig. 3, C to F). The multitude of valence band maxima is a distinctive feature of SnSe and is absent in the rock-salt chalcogenides. \n\nThe SnSe effective masses at each valence-band extremum are also anisotropic, in agreement with previous calculations (32). Because of the 2D nature of the material, the effective mass has a larger value along the $k_{x}$ direction $\\mathit{\\Pi}_{\\mathit{a}}$ axis) than along either of the in-plane directions $k_{y}$ and $k_{z}$ (b and $c$ axes). For the first valence maximum along $\\Gamma{-}Z,$ , the effective masses are $m_{\\mathrm{kx}}{}^{\\ast}=0.76m_{0},m_{\\mathrm{ky}}{}^{\\ast}=$ $0.33m_{0},$ and $m_{\\mathrm{kz}}{}^{*}=0.14m_{0}$ . For the second maximum along $\\Gamma{-}Z,$ the ${m_{\\mathrm{{k}}}}^{\\mathrm{{*}}}=2.49\\:\\:m_{0},\\:{m_{\\mathrm{{ky}}}}^{\\mathrm{{*}}}=0.18$ $m_{0},$ , and $m_{\\mathrm{kz}}{}^{*}=0.19m_{0}$ are heavier than for the first band. These heavy holes play an important role in enhancing the Seebeck coefficients. We also performed Seebeck coefficient calculations as a function of hole concentration at $300\\mathrm{K}$ using both a single-band model and a calculation that includes multivalley effects (33). We calculated the Seebeck coefficients by taking into account multiple valleys (considering all bands within $\\pm2\\mathrm{eV}$ of the Fermi level) and using a single parabolic band model with three different effective masses: ${m_{\\mathrm{d}}}^{*}=0.47m_{0}$ , $m_{\\mathrm{d}}{}^{*}=0.75m_{0}$ , and $m_{\\mathrm{d}}{}^{*}\\substack{=1.20m_{0}}$ (Fig. 3B). The Seebeck coefficient calculated with the full, multivalley DFT band structure is $+168\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ at $4\\times10^{19}\\mathrm{cm^{-3}}$ , which is very close to the experimentally observed value for this carrier concentration, $+160\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ . In contrast, using a single-band model, we cannot reproduce the experimental Seebeck coefficient, even with a range of possible effective masses: A single-band model with our calculated DOS effective mass $(0.47m_{0})$ from the first VBM yields a Seebeck coefficient of only $+84\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ at $4\\times10^{19}\\mathrm{cm^{-3}}$ . An estimated effective mass of $0.75m_{0}$ , obtained by fitting experimental Seebeck coefficients in polycrystalline SnSe (34, 35), gives a single-band model Seebeck coefficient of ${\\sim}+110\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ at $4\\times10^{19}\\mathrm{cm^{-3}}$ . The effective mass $m_{\\mathrm{d}}{}^{*}=1.20m_{0}$ is an extreme value that we obtained by fitting the single-band Seebeck coefficients at extremely low concentrations (e.g., $<1\\times10^{17}\\mathrm{cm}^{-3})$ to the full multivalley calculated Seebeck coefficients. Even with this very heavy effective mass, the Seebeck coefficients (Fig. 3B, black dashed line) are still lower than those of the multivalley model at higher hole concentrations. We cannot explain the observed Seebeck coefficient enhancements with a single-band model, even with a wide range of possible effective masses. In SnSe, the experimental Seebeck coefficients exhibit isotropic values (Fig. 2B) along all three crystallographic directions. The electrical conductivity values, however, along these directions are different and reflect the respective mobilities, with the highest being along the $b$ and $c$ axes, in agreement with the calculated lighter effective masses along these axes. The distinctive crystal structure of SnSe, therefore, plays a key role in the exceptional electronic band structure characteristics that result in an ultrahigh $P F$ and ZT. The 2D sheets in SnSe have strong, accordion-like corrugation and are well separated from one another, with long intersheet Sn···Se bonding interactions of ${\\sim}3.5\\mathrm{~\\AA~}$ (Fig. 4). Longer Sn-Se bonding interactions of ${\\sim}3.3\\mathrm{~\\AA~}$ are also present along the corrugation direction $\\mathit{\\Pi}_{\\mathrm{:}\\mathit{c}}$ axis). Along the $\\boldsymbol{c}$ and $b$ directions, the Sn-Se bonding is shorter, at 3.3 and $2.8\\mathrm{\\AA},$ respectively. As a result, the width of the valence bands along these in-plane directions is wider (and the effective hole masses lower) than along the $a$ direction (lower carrier mobilities and larger effective hole masses). \n\n![](images/f1def15827fbbf4c1218ea19d6f1de4e9565efc21078fa04012788c26157647b.jpg) \nFig. 3. Comparison of Seebeck coefficients of lead and tin chalcogenides, Pisarenko line, and DFT electronic band structure (Pnma). (A) Room-temperature Seebeck coefficients for lead and tin chalcogenides (19, 28–30) with a similar carrier density of ${\\sim}4\\times10^{19}~\\mathrm{cm}^{-3}$ . (B) Calculated Seebeck coefficients as a function of carrier density at $300~\\mathsf{K}$ . The line connecting the red circles is calculated from the full multivalley DFT band structure. Single-band calculations yield lower Seebeck coefficients, even for a range of effective masses, and cannot reproduce the measured values. (C) Electronic band structure of hole-doped SnSe indicates nonparabolic, complex multiband valence states. The red dotted lines (from top to bottom) represent the Fermi levels with carrier densities of $5\\times10^{17}$ , $5\\times10^{19}$ , $2\\times10^{20}$ , and $5\\times10^{20}~\\mathrm{cm}^{-3}$ , respectively, indicating that heavy doping pushes the Fermi level deep into the multivalence band structure. (D to F) The Fermi surfaces of SnSe (Pnma) at $5\\times10^{19}$ , $2\\times10^{20}$ , and $5\\times$ $10^{20}~\\mathsf{c m}^{-3}$ , respectively. The Fermi surface also illustrates the multiple types of pockets (or valleys) coming from the numerous valence bands, all within a small energy window. \n\n![](images/24fac0afc6a9f510311baa7b7a12a8a4b30d74cf79e4f3e0f782f1d7fcd34518.jpg) \nFig. 4. Crystal structure of SnSe. The structure is shown along (A) the $c$ -axis direction and (B) the b-axis direction. Blue atoms are Sn, red atoms are Se.The dashed wavy line is shown as a rough guide to the corrugation motif in the 2D slab.The closest Sn···Se interactions between the slabs are indicated with the blue dashed lines. The corrugation spacing within a single SnSe slab is also indicated with the green dashed line.The arrows indicate the directions along which the $Z T_{\\mathrm{dev}}$ is marked. \n\nWe demonstrate that hole doping SnSe pushes its Fermi level deep into the band structure, activating multiple valence band maxima that lie close together in energy, enabling enhanced Seebeck coefficients and power factors (PFs). Therefore, the unique electronic band structure of SnSe is key to the high power factor and thermoelectric performance of the doped samples over a wide temperature plateau, from 300 to 773 K. The high conversion efficiency improves the prospects of realizing very efficient thermoelectric devices with hole-doped SnSe crystals as a p-type leg. \n\n# REFERENCES AND NOTES \n\n1. L. E. Bell, Science 321, 1457–1461 (2008). \n2. J. P. Heremans, M. S. Dresselhaus, L. E. Bell, D. T. Morelli, Nat. Nanotechnol. 8, 471–473 (2013). \n3. X. Zhang, L. D. Zhao, J. Materiomics 1, 92–105 (2015). \n4. M. S. Dresselhaus et al., Adv. Mater. 19, 1043–1053 (2007). \n5. L. D. Zhao, V. P. Dravid, M. G. Kanatzidis, Energy Environ. Sci. 7, 251–268 (2014). \n6. K. F. Hsu et al., Science 303, 818–821 (2004). \n7. B. Poudel et al., Science 320, 634–638 (2008). \n8. M. Zhou, J. F. Li, T. Kita, J. Am. Chem. Soc. 130, 4527–4532 (2008). \n9. K. Biswas et al., Nature 489, 414–418 (2012). \n10. P. F. R. Poudeu et al., Angew. Chem. Int. Ed. 45, 3835–3839 (2006). \n11. J. P. Heremans et al., Science 321, 554–557 (2008). \n12. Y. Pei et al., Nature 473, 66–69 (2011). \n13. W. Liu et al., Phys. Rev. Lett. 108, 166601 (2012). \n14. H. Z. Zhao et al., Nano Energy 7, 97–103 (2014). \n15. L. D. Zhao et al., J. Am. Chem. Soc. 135, 7364–7370 (2013). \n16. X. Shi et al., J. Am. Chem. Soc. 133, 7837–7846 (2011). \n17. M. M. Nassary, Turk. J. Phys. 33, 201–208 (2009). \n18. L. D. Zhao et al., Nature 508, 373–377 (2014). \n19. Y. I. Ravich, B. A. Efimova, I. A. Smirnov, Semiconducting Lead Chalcogenides (Plenum, New York, 1970), vol. 5. \n20. S. I. Kim et al., Science 348, 109–114 (2015). \n21. S. K. Placheova, Phys. Status Solidi (a) 83, 349–355 (1984). \n22. G. J. Snyder, in Thermoelectrics Handbook: Macro to Nano, D. M. Rowe, Ed. (CRC/Taylor and Francis, Boca Raton, FL, 2006), chap. 9. \n23. H. J. Wu et al., Nat. Commun. 5, 4515 (2014). \n24. D. M. Rowe, CRC Handbook of Thermoelectrics (CRC Press, London, 1995). \n25. C. W. Li et al., Nat. Phys. 11, 1063–1069 (2015). \n26. F. Serrano-Sánchez et al., Appl. Phys. Lett. 106, 083902 (2015). \n27. Q. Zhang et al., Adv. Energy Mater. 5, 1500360 (2015). \n28. H. Wang, Y. Pei, A. D. LaLonde, G. J. Snyder, Adv. Mater. 23, 1366–1370 (2011). \n29. L. D. Zhao et al., J. Am. Chem. Soc. 134, 7902–7912 (2012). \n30. G. Tan et al., J. Am. Chem. Soc. 136, 7006–7017 (2014). \n31. Y. Pei, H. Wang, G. J. Snyder, Adv. Mater. 24, 6125–6135 (2012). \n32. G. Shi, E. Kioupakis, J. Appl. Phys. 117, 065103 (2015). \n33. Details of the calculations are available as supplementary materials on Science Online. \n34. C. L. Chen, H. Wang, Y. Y. Chen, T. Day, G. J. Snyder, J. Mater. Chem. A 2, 11171–11176 (2014). \n35. S. Sassi et al., Appl. Phys. Lett. 104, 212105 (2014). \n\n# ACKNOWLEDGMENTS \n\nThis work was supported in part by the U.S. Department of Energy, Office of Science and Office of Basic Energy Sciences, under award DE-SC0014520 (G.T., H.C., V.P.D., S.H., C.W., and M.G.K.); and S3TEC-EFRC grant DE-SC0001299 (G.J.S.). This work was also supported by the “Zhuoyue” Program from Beihang University and the Recruitment Program for Young Professionals and the National Natural Science Foundation of China under grant 51571007 (L.-D.Z., Y.P., S.G., and H.X.). and by the Science, Technology and Innovation Commission of Shenzhen Municipality under grant no. ZDSYS20141118160434515 and Guangdong Science and Technology Fund under grant no. 2015A030308001 (J.H.). The synthesis, characterization, transport measurements, and DFT calculations \n\nwere supported by DE-SC0014520. The validation measurements were supported by DE-SC0001299. Measurements at University of Michigan (C.U.) were supported by Energy Frontier Research Centers (EFRC) grant DE-SC0001054. All data in the main text and the supplementary materials are available online at www.sciencemag.org. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/351/6269/141/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S13 \nReferences (36–47) \n3 September 2015; accepted 12 November 2015 \nPublished online 26 November 2015 \n10.1126/science.aad3749 \n\n# GEOPHYSICS \n\n# Shear deformation of bridgmanite and magnesiowüstite aggregates at lower mantle conditions \n\nJennifer Girard, George Amulele,\\* Robert Farla,† Anwar Mohiuddin, Shun-ichiro Karato‡ \n\nRheological properties of the lower mantle have strong influence on the dynamics and evolution of Earth. By using the improved methods of quantitative deformation experiments at high pressures and temperatures, we deformed a mixture of bridgmanite and magnesiowüstite under the shallow lower mantle conditions.We conducted experiments up to about $100\\%$ strain at a strain rate of about $3\\times10^{-5}$ second−1. We found that bridgmanite is substantially stronger than magnesiowüstite and that magnesiowüstite largely accommodates the strain. Our results suggest that strain weakening and resultant shear localization likely occur in the lower mantle. This would explain the preservation of long-lived geochemical reservoirs and the lack of seismic anisotropy in the majority of the lower mantle except the boundary layers. \n\n■ caortmh’psolsaerdgoef, $\\mathrm{(Mg,Fe)SiO_{3}}$ rbrimdagnmtlaenitse $(\\sim70\\%)$ E anfedw(Mpge,rFce)nOt omfacgalnceisuiomwpüesrtiotve $(\\sim20\\%)$ $\\mathrm{CaSiO_{3}},$ ) [e.g., $(I)]$ . Many of Earth’s geochemical and geophysical questions depend strongly on the rheological properties of materials in this region. For instance, geochemical observations suggest that the lower mantle hosts a large amount of incompatible elements working as a reservoir of these elements (2, 3). The degree of preservation of these reservoirs is controlled by the nature of mixing or stirring of materials (4, 5), which strongly depends on the rheological properties of materials in this region. However, very little is currently known about the rheological properties of materials in the lower mantle because of the difficulties in quantitative experimental studies of deformation under the conditions of the lower mantle. \n\nThe main difficulties include the controlled generation of stress (or strain rate) and reliable measurements of stress and strain under the high-pressure and -temperature conditions [e.g., (6)]. Consequently, previous studies on plastic deformation of lower mantle minerals were either performed at high pressures and low temperatures (7–10), at high pressures and high temperatures without stress-strain rate control $(I I)$ , or on analog materials at low pressures (12–14). Applying low-temperature experiments to Earth’s interior is difficult because rheological properties are highly sensitive to temperature. Also the mechanisms by which deformation occurs are sensitive to temperature and strain rate, creating extrapolation issues for both low-temperature and poorly controlled strain-rate (stress) measurements [e.g., (15)]. Furthermore, microstructural evolution often leads to strain-dependent rheological behavior, which is particularly important for a sample containing two materials with a large strength contrast (16). The lower mantle approximates a two-phase mixture (bridgmanite and magnesiowüstite) with presumably a large strength contrast [e.g., (13, 17, 18)], and therefore large strain $(>30\\%)$ ) experiments are essential to \n\n# Science \n\n# Ultrahigh power factor and thermoelectric performance in hole-doped single-crystal SnSe \n\nLi-Dong Zhao, Gangjian Tan, Shiqiang Hao, Jiaqing He, Yanling Pei, Hang Chi, Heng Wang, Shengkai Gong, Huibin Xu, Vinayak P. Dravid, Ctirad Uher, G. Jeffrey Snyder, Chris Wolverton and Mercouri G. Kanatzidis \n\nScience 351 (6269), 141-144. DOI: 10.1126/science.aad3749originally published online November 26, 2015 \n\n# Heat conversion gets a power boost \n\nThermoelectric materials convert waste heat into electricity, but often achieve high conversion efficiencies only at high temperatures. Zhao et al. tackle this problem by introducing small amounts of sodium to the thermoelectric SnSe (see the Perspective by Behnia). This boosts the power factor, allowing the material to generate more energy while maintaining good conversion efficiency. The effect holds across a wide temperature range, which is attractive for developing new applications. \n\nScience, this issue p. 141; see also p. 124 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/351/6269/141 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2015/11/24/science.aad3749.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/351/6269/124.full \n\nREFERENCES \n\nThis article cites 41 articles, 6 of which you can access for free http://science.sciencemag.org/content/351/6269/141#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1002_anie.201602237", + "DOI": "10.1002/anie.201602237", + "DOI Link": "http://dx.doi.org/10.1002/anie.201602237", + "Relative Dir Path": "mds/10.1002_anie.201602237", + "Article Title": "Interface Engineering of MoS2/Ni3S2 Heterostructures for Highly Enhanced Electrochemical Overall-Water-Splitting Activity", + "Authors": "Zhang, J; Wang, T; Pohl, D; Rellinghaus, B; Dong, RH; Liu, SH; Zhuang, XD; Feng, XL", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "To achieve sustainable production of H-2 fuel through water splitting, low-cost electrocatalysts for the hydrogen-evolution reaction (HER) and the oxygen-evolution reaction (OER) are required to replace Pt and IrO2 catalysts. Herein, for the first time, we present the interface engineering of novel MoS2/Ni3S2 heterostructures, in which abundant interfaces are formed. For OER, such MoS2/Ni3S2 heterostructures show an extremely low overpotential of ca. 218 mV at 10 mAcm(-2), which is superior to that of the state-of-the-art OER electrocatalysts. Using MoS2/Ni3S2 heterostructures as bifunctional electrocatalysts, an alkali electrolyzer delivers a current density of 10 mAcm(-2) at a very low cell voltage of ca. 1.56 V. In combination with DFT calculations, this study demonstrates that the constructed interfaces synergistically favor the chemisorption of hydrogen and oxygen-containing intermediates, thus accelerating the overall electrochemical water splitting.", + "Times Cited, WoS Core": 1508, + "Times Cited, All Databases": 1520, + "Publication Year": 2016, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000377921300021", + "Markdown": "# Interface Engineering of $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ Heterostructures for Highly Enhanced Electrochemical Overall-Water-Splitting Activity \n\nJian Zhang, Tao Wang, Darius Pohl, Bernd Rellinghaus, Renhao Dong, Shaohua Liu, Xiaodong Zhuang, and Xinliang Feng\\* \n\nAbstract: To achieve sustainable production of $H_{2}$ fuel through water splitting, low-cost electrocatalysts for the hydrogen-evolution reaction (HER) and the oxygen-evolution reaction (OER) are required to replace $P t$ and $I r O_{2}$ catalysts. Herein, for the first time, we present the interface engineering of novel $M o S_{2}/N i_{3}S_{2}$ heterostructures, in which abundant interfaces are formed. For OER, such $M o S_{2}/N i_{3}S_{2}$ heterostructures show an extremely low overpotential of ca. $2l8m V$ at $I O m A c m^{-2}$ , which is superior to that of the state-of-the-art OER electrocatalysts. Using $M o S_{2}/N i_{3}S_{2}$ heterostructures as bifunctional electrocatalysts, an alkali electrolyzer delivers a current density of $I O m A c m^{-2}$ at a very low cell voltage of ca. $1.56~V.$ In combination with DFT calculations, this study demonstrates that the constructed interfaces synergistically favor the chemisorption of hydrogen and oxygen-containing intermediates, thus accelerating the overall electrochemical water splitting. \n\nTo achieve sustainable hydrogen production, electrochemical and photoelectrochemical water splitting are favorable strategies benefiting from abundant water resources and giving high-purity $\\mathrm{H}_{2}$ production.[1] Electrocatalysts are particularly vital to the hydrogen-evolution reaction (HER) and the oxygen-evolution reaction (OER) by lowering the dynamic overpotentials.[2] Currently, Pt is the most efficient HER electrocatalyst with a near-zero overpotential, while $\\mathrm{IrO}_{2}$ and $\\mathrm{RuO}_{2}$ hold the benchmark for OER electrocatalysts.[3] However, the scarcity and high-cost of these noblemetal-based electrocatalysts considerably impede their largescale utilization in commercial electrolyzers.[4] For the HER in an alkaline solution, the kinetics are determined through a subtle balance between the water dissociation (Volmer step) and the subsequent chemisorption of the water-splitting intermediates $\\mathrm{OH^{-}}$ and $\\mathrm{H^{*}}$ ) on the surface of the HER electrocatalyst.[5] Thus, once an electrocatalyst facilitates the synergistic chemisorption of both $\\mathrm{H^{*}}$ and $\\mathrm{OH^{-}}$ intermediates on the surface, the HER performance will be improved. Similarly, for the OER in an alkaline solution, the chemisorption and dissociation of $\\mathrm{OH^{-}}$ and the yielded intermediates ( $\\mathrm{\\DeltaOH^{*}}$ , $\\scriptstyle\\mathrm{{OOH^{*}}}$ , and $\\mathrm{H^{+}}$ ) on the surface of the electrocatalysts determine the water-oxidation activity.[6] Therefore, OER electrocatalysts capable of binding both the oxygencontaining and hydrogen intermediates are expected to favor the water-oxidation reaction. Nevertheless, only the chemisorption free energy of hydrogen (or oxygen-containing) intermediates has been considered for developing HER (or OER) electrocatalysts thus far.[7] \n\nMolybdenum-based nanostructures, particularly $\\mathbf{MoS}_{2}$ , have been extensively investigated as HER electrocatalysts.[8] Both DFT calculations and experimental investigations revealed that the undercoordinated Mo-S sites along the edges of $\\mathbf{MoS}_{2}$ possess high chemisorption capability for hydrogen, analogous to Pt.[9] For OER electrocatalysts earthabundant transition-metal (Fe, Co, and Ni, particularly Ni)- based sulfides,[10] oxides,[11] hydroxides,[12] layered double hydroxides (LDHs),[13] and phosphates[14] have been explored. The undercoordinated metal sites on the surface are pivotal in water oxidation because of their outstanding chemisorption of $\\mathrm{\\Omega_{oH}-}$ and oxygen-containing intermediates. Therefore, integrating the advantages of the HER and OER electrocatalysts to construct novel heterostructures, which possess binding affinities to both hydrogen and oxygen-containing intermediates, is extremely beneficial for enhancing the overall electrochemical water-splitting activity. \n\nHerein, for the first time, we present the interface engineering of novel $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures on nickel foam. In the resultant $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures, the outer $\\mathbf{MoS}_{2}$ nanosheets are decorated on the surface of the inner $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles, which generates abundant interfaces. Such $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures exhibit both highly efficient OER and HER activities in $1\\mathrm{{w}\\ K O H}$ solution. In particular, the OER onset potential of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures is as low as around $175\\mathrm{mV},$ and the OER current density reaches $10\\mathrm{mAcm}^{-2}$ at an overpotential of about $218\\mathrm{mV}$ which is superior to the reported OER electrocatalysts. Furthermore, utilizing the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructure as a bifunctional electrocatalyst, an alkaline electrolyzer with a current density of $10\\mathrm{mAcm}^{-2}$ is operated at a low cell voltage of $1.56\\mathrm{V}_{;}$ which is considerably lower than that of the state-of-the-art overall-water-splitting electrocatalysts, such as NiFe–LDH,[15] NiSe nanowires,[16] ${\\bf N i}_{2}{\\bf P}$ nanoparticles,[17] and electrodeposited cobalt-phosphorous-derived films[18] (cell voltages ${}>1.6{\\mathrm{V}}{\\mathrm{~}}$ ). Combined with DFT calculations, our results suggest that the established interfaces between $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\mathbf{MoS}_{2}$ as well as the in situ generated interfaces between NiO (surface electrochemical oxidation of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ under OER condition) and $\\mathbf{MoS}_{2}$ facilitate the synchronous chemisorption of hydrogen and oxygen-containing intermediates, consequently improving the overall electrochemical water-splitting activity. \n\n$\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures were prepared using a commercial nickel foam $(1\\times3\\mathrm{cm}^{2})$ and $\\mathrm{(NH_{4})_{2}M o S_{4}}$ $\\mathrm{\\langle40\\mg\\rangle}$ through a one-pot solvothermal reaction at $200^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ in $15\\mathrm{mL}N,N.$ -dimethylformamide (DMF; see Supporting Information). During the solvothermal reaction, $(\\mathrm{NH_{4}})_{2}\\mathrm{MoS_{4}}$ not only served as the precursor of $\\mathbf{MoS}_{2}$ nanosheets but also provided the sulfur source for the in situ growth of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles on the nickel foam. The loading amount of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures on the nickel foam is approximately $9.7\\mathrm{mg}\\mathrm{cm}^{-2}$ ; this value could be controlled by adjusting the amount of $\\mathrm{(NH_{4})_{2}M o S_{4}}$ in the solution. For instance, the loading weights of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures were approximately 5.7 and approximately $13.1\\mathrm{mg}\\mathrm{cm}^{-2}$ when the amounts of $(\\mathrm{NH_{4}})_{2}\\mathrm{MoS_{4}}$ were 20 and $80\\mathrm{mg}$ , respectively (Figure S1–S3 in the Supporting Information). \n\nAs shown in Figure 1 a and the inset, the resulting nickel foam coated with $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures has macroporous and free-standing features. The crystalline structure and surface composition of the $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures were first confirmed through $\\mathbf{X}$ -ray diffraction (Figure S4) and Raman spectroscopy (Figure S5) studies. To analyze the as-obtained $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures, scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM) were used. Figure $1\\ensuremath{\\mathrm{b}}$ reveals numerous heterostructures, which consist of inner $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles and decorated $\\mathbf{MoS}_{2}$ nanosheets. The size of the $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles was about several hundred nanometers. The size and thickness of the $\\mathbf{MoS}_{2}$ nanosheets were 30–130 and $5\\mathrm{-}15~\\mathrm{{nm}}$ , respectively. The element distributions of the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures were further analyzed through the elemental mapping of field-emission SEM (FE-SEM) (Figure S6 a–d). Notably, the nickel element was mainly distributed over the nanoparticles, whereas molybdenum and sulfur were spread on and around the nanoparticles. The molar content of $\\mathbf{MoS}_{2}$ in $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures was determined to be about $7.8\\%$ through energy-dispersive X-ray spectroscopy (EDX) (Figure S6 e), which is consistent with the inductively coupled plasma mass spectrometer (ICPMS) analysis (ca. $8.0\\%$ ). We further peeled off $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures from the nickel foam by sonication and investigated the samples by HRTEM (Figure 1c, 1d, S7 and S8). Lattice fringes with lattice distances of 0.27 and $0.61\\mathrm{nm}$ corresponded to the (100) and (002) facets of $\\mathbf{MoS}_{2}$ , respectively, while the lattice distances of 0.40 and $0.28\\mathrm{nm}$ were ascribed to the (101) and (110) facets of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , respectively. The (002) and (100) facets of $\\mathbf{MoS}_{2}$ and the neighboring (101) and (110) surfaces of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ constitute the interfaces in $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures. Next, the X-ray photoelectron spectroscopy (XPS) survey spectrum of $\\mathbf{MoS}_{2}/$ $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ demonstrates that the chemical composition of Ni, Mo, and S is consistent with the EDX results (Figure S9). For bare $\\mathbf{MoS}_{2}$ nanosheets, the peaks of Mo $3\\mathrm{d}_{5/2}$ and Mo $3\\mathrm{d}_{3/2}$ appear at 228.5 and $231.8\\mathrm{eV}$ , respectively. However, the binding energies of Mo $3\\mathrm{d}_{5/2}$ and Mo $3\\mathrm{d}_{3/2}$ in $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures shift to 228.6 and $232.2\\mathrm{eV},$ respectively (Figure 1 e). Similarly, the $\\mathrm{Ni}2\\mathrm{p}_{3/2}$ signal in the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures exhibits a positive shift of about $0.3\\mathrm{eV}$ relative to that in the bare $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles (Figure 1 f). These results strongly suggest the existence of strong electronic interactions between $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\mathbf{MoS}_{2}$ , which implies the establishment of coupling interfaces. \n\n![](images/a7a1c25daf4d2219b86cbe7318e8f8b371b4fd8cc99ddc4d96331632da53f37f.jpg) \nFigure 1. a) and b) scanning electron microscopy and c) and d) high-resolution transmission electron microscopy images of ${\\mathsf{M o S}}_{2}/{\\mathsf{N i}}_{3}{\\mathsf{S}}_{2}$ heterostructures. High-resolution X-ray photoelectron spectroscopy spectrum of e) Mo 3d and f) Ni 2p. Inset of (a): digital image of nickel foam coated with ${\\mathsf{M o S}}_{2}/{\\mathsf{N i}}_{3}{\\mathsf{S}}_{2}$ heterostructures. The ringed sections of (b) highlight the ${\\mathsf{M o S}}_{2}$ nanosheets. \n\nTo evaluate the OER performance of the as-prepared $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures, a three-electrode configuration was applied using an $\\mathrm{Hg/HgO}$ electrode and a $\\mathrm{Pt}$ rod as the reference and counter electrodes, respectively (Figure S10). The OER activities of the nickel foam, $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles, $\\mathbf{MoS}_{2}$ nanosheets, $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures, and $\\mathrm{IrO}_{2}$ were examined through cyclic voltammetry (CV) at a scan rate of $1\\mathrm{mVs}^{-1}$ in a $1\\mathrm{{w}\\ K O H}$ aqueous solution purged with $\\mathbf{O}_{2}$ (Figure 2 a). Bare $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles and $\\mathbf{MoS}_{2}$ nanosheets exhibited OER onset overpotentials of approximately 230 and $280\\mathrm{mV},$ respectively. By contrast, for $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures, oxygen generation occurred at an extremely low overpotential (ca. $175\\mathrm{mV}$ ), which is considerably lower than that of commercial $\\mathrm{IrO}_{2}$ (ca. $250\\mathrm{mV},$ ) (Figure S11 and S12). Significantly, the current density of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures reached $10\\mathrm{mAcm}^{-2}$ at an extremely low overpotential of approximately $218\\mathrm{mV},$ which outperformed $\\mathrm{IrO}_{2}$ (ca. $330\\mathrm{mV}$ and the NiFe-LDH film (ca. \n\n![](images/05c93966a7409421890dd49367c90b97161ea90e4feb7a86cfffcd3dd0fe8937.jpg) \nFigure 2. a) CV curves and $\\mathsf{c})$ ) related Tafel slopes of the nickel foam, ${\\mathsf{M o S}}_{2}$ nanosheets, $\\mathsf{N i}_{3}\\mathsf{S}_{2}$ nanoparticles, $\\mathsf{M o S}_{2}/\\mathsf{N i}_{3}\\mathsf{S}_{2}$ heterostructures, and $\\mathsf{I r O}_{2}$ ; b) OER overpotentials of the ${\\mathsf{M o S}}_{2}/{\\mathsf{N i}}_{3}{\\mathsf{S}}_{2}$ heterostructures and the reported electrocatalysts for comparison at $\\mathsf{l o\\ m A c m}^{-2}$ ; and d) the longterm electrochemical OER test of the ${\\mathsf{M o S}}_{2}/{\\mathsf{N i}}_{3}{\\mathsf{S}}_{2}$ heterostructures at $\\mathsf{l o m A c m}^{-2}$ . Electrolyte: $\\rceil_{\\textsf{M}}$ KOH solution; CV scan rate: $\\mathsf{l}\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . \n\nThe polarization curves in Figure 3a show that the onset overpotentials of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles and $\\mathbf{MoS}_{2}$ nanosheets are approximately 120 and $236\\mathrm{mV}_{:}$ , respectively. However, the onset overpotential of the $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures is substantially lower at around $50\\mathrm{mV},$ approaching that of the $\\mathrm{\\Pt}$ catalyst. At $10\\mathrm{mAcm}^{-2}$ , the applied overpotential is approximately $110\\mathrm{mV}$ , substantially lower than that of the $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles (ca. $193\\mathrm{mV}$ ), the $\\mathbf{MoS}_{2}$ nanosheets (ca. $431\\mathrm{mV},$ ), and the recently reported WC nanocrystals on carbon nanotubes (ca. $150\\mathrm{mV}$ ),[22] CoP on carbon cloth (ca. $209\\mathrm{mV},$ ,[23] $\\mathbf{MoC}_{\\mathrm{x}}$ nano-octahedrons (ca. $150\\mathrm{mV},$ ,[24] and cobalt-nitrogen-rich carbon nanotubes (ca. $360\\mathrm{mV}$ )[25] (Figures S13,S14). The Tafel slopes of the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures, $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles, and $\\mathbf{MoS}_{2}$ nanosheets are around 83, 85, and $308\\mathrm{mV}$ per decade, respectively (Figure 3 b). Such a Tafel slope of the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures suggests a combined Volmer–Heyrovsky mechanism for hydrogen production.[26] Under a cathodic current of $10\\mathrm{mAcm}^{-2}$ \n\n$240\\mathrm{mV})$ ,[15] $(\\mathrm{Ln}_{0.5}\\mathrm{Ba}_{0.5})\\mathrm{CoO}_{3-\\delta}$ perovskite (ca. $320\\mathrm{mV},$ ,[19] single-crystal $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{CoO}$ (ca. $430\\mathrm{mV},$ ),[20] and electrodeposited Co-P film (ca. $300\\mathrm{mV})^{[19]}$ (Figure 2 b).[10, 21] \n\nFigure 2 c illustrates that the Tafel slope of the $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures is approximately $88\\mathrm{mV}$ decade¢1, which is considerably lower than that of the $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles (ca. $118\\mathrm{mVdecade^{-1}}$ ), the $\\mathbf{MoS}_{2}$ nanosheets (ca. $166\\mathrm{mV}$ decade¢1), and the nickel foam (ca. $98\\mathrm{mV}$ decade¢1). This result strongly suggests that the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures activate water-oxidation reaction kinetics. \n\nTo assess the electrochemical OER stability of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures, a long-term water oxidation was conducted at $10\\mathrm{mAcm}^{-2}$ in 1m KOH media. Figure 2d illustrates that the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures retained steady OER activity and no noticeable potential augment was observed for more than $10\\mathrm{{h}}$ of oxygen release. \n\nThe HER activities of the asprepared samples were evaluated in 1m KOH electrolyte purged with ${\\bf N}_{2}$ . \n\n![](images/e00779a25eb058ad59a541319a24553690ad9a35b2d8f464c8512c2bfd317031.jpg) \nFigure 3. a) Polarization curves and b) corresponding Tafel slopes of the nickel foam, ${\\mathsf{M o S}}_{2}$ nanosheets, $\\mathsf{N i}_{3}\\mathsf{S}_{2}$ nanoparticles, $\\mathsf{M o S}_{2}/\\mathsf{N i}_{3}\\mathsf{S}_{2}$ heterostructures, and Pt; c) polarization curves of $\\mathsf{M o S}_{2}/\\mathsf{N i}_{3}\\mathsf{S}_{2}$ heterostructures and ${\\mathsf{I r O}}_{2}$ -Pt couple in a two-electrode system; and d) durable operation of the ${\\mathsf{M o S}}_{2}/{\\mathsf{N i}}_{3}{\\mathsf{S}}_{2}$ (lower trace) heterostructures and $\\mathsf{I r O}_{2}$ -Pt couple (upper trace) at $\\mathsf{10\\ m A c m^{-2}}$ in an alkaline electrolyzer. Electrolyte: 1 m KOH solution; CV scan rate: $\\mathsf{l}\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . \n\nthere is no noticeable degradation over a $10\\mathrm{{h}}$ galvanostatic test, which indicates an excellent electrochemical HER stability (Figure S15). \n\nThe $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures were utilized as a bifunctional electrocatalyst for overall water splitting in a twoelectrode setup in $1\\mathrm{{M}\\ K O H}$ solution (Figure S16). A current density of $10\\mathrm{mAcm}^{-2}$ was delivered at approximately $1.56\\mathrm{V},$ that is, a combined overpotential of about $330\\mathrm{mV}$ for electrochemical overall water splitting (Figure 3 c). Figure S17 reveals that the overall water splitting activity of the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures is much higher than that of the $\\mathrm{IrO}_{2}$ -Pt couple (ca. $1.7\\mathrm{V}$ ) and other recently reported overall water splitting electrocatalysts such as NiFe-LDH (ca. $1.7\\mathrm{V},$ ),[16] NiSe nanowires (ca. $1.63\\mathrm{V})$ ,[17] and ${\\bf N i}_{2}{\\bf P}$ nanoparticles (ca. 1.63 V).[18] Over a $10\\mathrm{{h}}$ galvanostatic electrolysis at $10\\mathrm{mAcm}^{-2}$ , the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures presented an excellent durability with negligible degradation, which is superior to that of the noble metal $\\mathrm{IrO}_{2}–\\mathrm{Pt}$ couple (Figure 3 d). We further tested the overall electrocatalytic water splitting performance under an extremely high current density of $500\\mathrm{mAcm}^{-2}$ . Figure S18 and Movie 1 show that massive bubbles were rapidly generated on both electrodes at an applied voltage of approximately $1.6\\mathrm{V}.$ Such a prominent performance of the constructed electrolyzer utilizing the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures is close to the commercial requirement of a water splitting electrolyzer (voltage $\\leq1.55\\mathrm{V}$ at $500\\mathrm{mAcm}^{-2}$ ).[27] \n\nAs shown in Figure S20, the reduction and oxidation peaks of $\\mathbf{Mo^{\\delta+}}/\\mathbf{Mo^{\\varepsilon+}}$ $\\left(\\varepsilon>\\delta\\ge4\\right)$ in $\\mathbf{MoS}_{2}$ nanosheets are located at $\\approx0.333$ and $0.449\\mathrm{V}$ , while the redox reactions of $\\mathrm{Ni^{2+}/N i^{3+}}$ in $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles occur at around 0.254 and $0.369{\\mathrm{V}}_{\\cdot}$ . In contrast, the redox peaks in the $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures are centered at about 0.216 and $0.489\\mathrm{V}.$ These results suggest that the fabricated $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures offer new water splitting active sites, which are endowed with the electrocatalytic properties of both $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\mathbf{MoS}_{2}$ . The reduction peak area of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures is approximately 9.3 and 17.7 times larger than those of the $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles and $\\mathbf{MoS}_{2}$ nanosheets, respectively. After the electrochemical OER process at $10\\mathrm{mAcm}^{-2}$ for $10\\mathrm{{h}}$ in 1m KOH solution, the structure of the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures was analyzed by SEM, HRTEM, XPS, element mapping and EDX, and XPS analyses (Figure S21–S24). Notably, a thin layer of NiO with thickness of approximately $12.6\\mathrm{nm}$ was identified on $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ surface, for which the lattice fringe with a lattice distance of $0.21{\\mathrm{nm}}$ was indexed to be the (010) facet of NiO (Figure S20c). XPS result in Figure S24 further revealed the existence of NiO. The formation of NiO is due to the in situ surface electrochemical oxidation of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ during the OER process which is in agreement with literature reports; and the NiO sites are electrochemically active for the OER process.[10,16] Therefore, we consider that the constructed inter \n\nThe nature and amount of undercoordinated metal sites are crucial for the electrochemical water splitting. The effects of the surface area on OER and HER activities of the obtainedelectrocatalysts were firstly studied through electrochemical double-layer capacitances ( $\\mathrm{\\cdot}\\mathrm{c_{dl}}$ Figure S19). As shown in Table S1, $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures show a larger $\\mathbf{C}_{\\mathrm{dl}}$ $(15.6\\:\\mathrm{mF})$ than $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles $(2.1\\mathrm{mF})$ ) and $\\mathbf{MoS}_{2}$ nanosheets $(8.2\\mathrm{mF})$ . In sharp contrast, for OER (or HER), the current density of $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures at $1.53\\mathrm{V}$ (or $-0.15\\mathrm{V})$ reached 94.8 (or $45)\\mathrm{mAcm}^{-2}$ , which is substantially higher than those of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles $(5.0\\mathrm{mAcm}^{-2}$ for OER; $4.7\\mathrm{mAcm}^{-2}$ for HER) and $\\mathbf{MoS}_{2}$ nanosheets (1.6 mA cm¢2 for OER; $2.5\\mathrm{mAcm}^{-2}$ for HER). Thereby, the greatly enhanced water splitting activities of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures are mainly attributed to the constructed interfaces, rather than the active surface areas. \n\n![](images/5fbc1344e6d9ea47a1d5f4a6e7ba0b498bf8f4b3dcfc23805b56bb231ea70056.jpg) \nFigure 4. a) Chemisorption models of H and OH intermediates on the surfaces of ${\\mathsf{M o S}}_{2}$ , $\\mathsf{N i}_{3}\\mathsf{S}_{2}$ , NiO, ${\\mathsf{M o S}}_{2}/{\\mathsf{N i}}_{3}{\\mathsf{S}}_{2}$ heterostructures (Ni- ${\\mathsf{M o S}}_{2}$ and Mo- $N_{1}S_{2}$ models), and ${\\mathsf{M o S}}_{2}/{\\mathsf{N i O}}$ heterostructures (Ni${\\mathsf{M o S}}_{2}$ and Mo-NiO models) respectively; b) the proposed mechanisms of the dissociation of $H_{2}O$ , OH, and OOH intermediates on the $\\mathsf{M o S}_{2}/\\mathsf{N i}_{3}\\mathsf{S}_{2}$ heterostructures. Yellow $=5$ , green ${\\bf\\Lambda}={\\sf N i}$ , blue $=M\\circ$ , white $\\mathbf{\\tau}=\\mathsf{H}$ , red $=0$ \n\nfaces between the $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\mathbf{MoS}_{2}$ stably facilitate HER process and the interfaces between the in situ formed NiO and $\\mathbf{MoS}_{2}$ are favorable for the OER process. \n\nTo further investigate the role of the constructed interfaces in electrochemical OER and HER, the $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures with different molar contents of $\\mathbf{MoS}_{2}$ have been synthesized on carbon cloth (see Experimental Section in Supporting Information). Figure S25 shows that the OER and HER overpotentials of the bare $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanoparticles and $\\mathbf{MoS}_{2}$ nanosheets at $10\\mathrm{mAcm}^{-2}$ are approximately 379 and 421 and 341 and $429\\mathrm{mV}_{;}$ respectively. However, the electrochemical OER and HER performances of the $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures are noticeably enhanced. When the molar content of $\\mathbf{MoS}_{2}$ is around $8.3\\%$ , the OER and HER overpotentials of the $\\mathbf{MoS}_{2}/\\mathbf{Ni}_{3}\\mathbf{S}_{2}$ heterostructures at $10\\mathrm{mAcm}^{-2}$ are as low as approximately 330 and $150\\mathrm{mV}_{:}$ respectively. For comparison, the physically mixed $\\mathrm{MoS}_{2}/$ $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ composite (having the same chemical composition as the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures) deliver OER and HER current densities of $10\\mathrm{mAcm}^{-2}$ at overpotentials of about 356 and $199\\mathrm{mV}_{:}$ , respectively, which are considerably higher than those of the $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures. These results clearly show the crucial role of the constructed interfaces between $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\mathbf{MoS}_{2}$ as well as the interfaces between NiO and $\\mathbf{MoS}_{2}$ , which are responsible for the enhanced electrochemical hydrogen and oxygen evolutions, respectively. \n\nTo clarify the effect of the constructed interfaces on the chemisorption of hydrogen and oxygen-containing intermediates, we utilized DFT to calculate the chemisorption free energies of hydrogen $(\\Delta G_{\\mathrm{H}})$ and hydroxide $(\\Delta G_{\\mathrm{OH}})$ on the (101) surface of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , the (010) surface of NiO, and the (002) surface of $\\mathbf{MoS}_{2}$ (Figure 4 a). Contrary to the chemisorption on the (101) surface of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ $\\Delta G_{\\mathrm{H}}=-1.81\\ \\mathrm{eV},$ and (002) surface of $\\mathbf{MoS}_{2}$ $\\Delta G_{\\mathrm{H}}=-2.71\\ \\mathrm{eV},$ ), H is prone to adsorb on the Mo-S edge sites of Ni-doped $\\mathbf{MoS}_{2}$ model (denoted as Ni$\\mathbf{MoS}_{2}^{\\cdot}$ ) because of a lower chemisorption free energy of $-3.17\\mathrm{eV}.$ As expected, the surface undercoordinated Ni sites of Mo-doped $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ model (denoted as $\\mathbf{Mo-Ni}_{3}\\mathbf{S}_{2}$ ) have a HOchemisorption energy of $-2.92\\mathrm{eV},$ , which is lower than the $-1.68\\mathrm{eV}$ energy of HO-chemisorption on $\\mathbf{MoS}_{2}$ and $-2.36\\mathrm{eV}$ energy of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ . The (101) surface of $\\mathbf{Mo-Ni}_{3}\\mathbf{S}_{2}$ thus exhibits superior binding activity toward oxygen-containing groups. Moreover, considering the formed interfaces between $\\mathbf{MoS}_{2}$ and NiO for OER, the Mo sites of the Modoped NiO model (Mo-NiO) show a significantly increased HO-chemisorption energy up to $-5.12\\mathrm{eV}.$ Accordingly, a HER mechanism on $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures and an OER mechanism on $\\mathrm{MoS}_{2}/\\mathrm{NiO}$ heterostructures are proposed in Figure $4\\mathrm{b}$ . The constructed interfaces between $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\mathbf{MoS}_{2}$ as well as the interfaces between NiO and $\\mathbf{MoS}_{2}$ have the advantages of the H-chemisorption of $\\mathbf{MoS}_{2}$ and the HO-chemisorption of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and NiO. As a result, the Gibbs free energies of the corresponding intermediates are efficiently decreased, facilitating the dissociation of the $\\mathrm{O-H}$ bonds of the $\\mathrm{H}_{2}\\mathrm{O}$ molecule and the OH and OOH intermediates. Eventually, the OER and HER processes are highly accelerated. \n\nIn summary, we have presented a novel approach for developing earth-abundant and high-activity overall-watersplitting electrocatalysts through interface engineering. The as-prepared $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures with abundant interfaces manifest excellent chemisorption abilities for both hydrogen and oxygen-containing intermediates, leading to outstanding OER and HER electrocatalytic activities in alkaline media. Therefore, the engineering and understanding of the interfaces formed provide a favorable direction for developing low-cost and high-activity water-splitting electrocatalysts, which have potential applications in photochemical, photoelectrochemical, and electrochemical $\\mathrm{H}_{2}$ production and $\\mathrm{CO}_{2}$ reduction. \n\n# Acknowledgements \n\nThis work was financially supported by the ERC Grant on 2DMATER and EC under Graphene Flagship (No. CNECTICT-604391). We also acknowledge the Cfaed (Center for Advancing Electronics Dresden) and the Dresden Center for Nanoanalysis (DCN) at TU Dresden. \n\nKeywords: electrocatalysts $\\mathbf{\\nabla}\\cdot\\mathbf{\\varepsilon}$ interface engineering molybdenum disulfide $\\cdot$ nickel sulfide $\\cdot\\cdot$ water splitting \n\nHow to cite: Angew. Chem. Int. Ed. 2016, 55, 6702–6707 Angew. Chem. 2016, 128, 6814–6819 \n\n[15] J. Luo, J.-H. Im, M. T. Mayer, M. Schreier, M. K. Nazeeruddin, N.-G. Park, S. D. Tilley, H. J. Fan, M. Gr•tzel, Science 2014, 345, 1593 – 1596. \n[16] C. Tang, N. Cheng, Z. Pu, W. Xing, X. Sun, Angew. Chem. Int. Ed. 2015, 54, 9351 – 9355; Angew. Chem. 2015, 127, 9483 – 9487. \n[17] L.-A. Stern, L. Feng, F. Song, X. Hu, Energy Environ. Sci. 2015, 8, 2347 – 2351. \n[18] N. Jiang, B. You, M. Sheng, Y. Sun, Angew. Chem. Int. Ed. 2015, 54, 6251 – 6254; Angew. Chem. 2015, 127, 6349 – 6352. \n[19] A. Grimaud, K. J. May, C. E. Carlton, Y.-L. Lee, M. Risch, W. T. Hong, J. Zhou, Y. Shao-Horn, Nat. Commun. 2013, 4, 2439 – 2445. \n[20] C.-W. Tung, Y.-Y. Hsu, Y.-P. Shen, Y. Zheng, T.-S. Chan, H.-S. Sheu, Y.-C. Cheng, H. M. Chen, Nat. Commun. 2015, 6, 8106 – 8114. \n[21] a) F. Song, X. Hu, Nat. Commun. 2014, 5, 4477 – 4485; b) H. Wang, H.-W. Lee, Y. Deng, Z. Lu, P.-C. Hsu, Y. Liu, D. Lin, Y. Cui, Nat. Commun. 2015, 6, 7261 – 7268; c) L.-L. Feng, G. Yu, Y. Wu, G.-D. Li, H. Li, Y. Sun, T. Asefa, W. Chen, X. Zou, J. Am. Chem. Soc. 2015, 137, 14023 – 14026; d) W. Chen, H. Wang, Y. Li, \n\nY. Liu, J. Sun, S. Lee, J.-S. Lee, Y. Cui, ACS Cent. Sci. 2015, 1, 244 – 251; e) J. Wang, K. Li, H. - x. Zhong, D. Xu, Z.-l. Wang, Z. Jiang, Z.-j. Wu, X.-b. Zhang, Angew. Chem. Int. Ed. 2015, 54, 10530 – 10534; Angew. Chem. 2015, 127, 10676 – 10680. [22] X. Fan, H. Zhou, X. Guo, ACS Nano 2015, 9, 5125 – 5134. [23] J. Tian, Q. Liu, A. M. Asiri, X. Sun, J. Am. Chem. Soc. 2014, 136, 7587 – 7590. [24] H. B. Wu, B. Y. Xia, L. Yu, X.-Y. Yu, X. W. Lou, Nat. Commun. 2015, 6, 6512 – 6519. [25] X. Zou, X. Huang, A. Goswami, R. Silva, B. R. Sathe, E. Mikmekov‚, T. Asefa, Angew. Chem. Int. Ed. 2014, 53, 4372 – 4376; Angew. Chem. 2014, 126, 4461 – 4465. [26] M. Gong, W. Zhou, M.-C. Tsai, J. Zhou, M. Guan, M.-C. Lin, B. Zhang, Y. Hu, D.-Y. Wang, J. Yang, S. J. Pennycook, B.-J. Hwang, H. Dai, Nat. Commun. 2014, 5, 4695 – 4700. [27] X. Lu, C. Zhao, Nat. Commun. 2015, 6, 6616 – 6622. " + }, + { + "id": "10.1002_aenm.201502588", + "DOI": "10.1002/aenm.201502588", + "DOI Link": "http://dx.doi.org/10.1002/aenm.201502588", + "Relative Dir Path": "mds/10.1002_aenm.201502588", + "Article Title": "A Novel Aluminum-Graphite Dual-Ion Battery", + "Authors": "Zhang, XL; Tang, YB; Zhang, F; Lee, CS", + "Source Title": "ADVANCED ENERGY MATERIALS", + "Abstract": null, + "Times Cited, WoS Core": 1748, + "Times Cited, All Databases": 1772, + "Publication Year": 2016, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000379311500012", + "Markdown": "# A Novel Aluminum–Graphite Dual-Ion Battery \n\nXiaolong Zhang, Yongbing Tang,\\* Fan Zhang, and Chun-Sing Lee\\* \n\nLithium ion batteries based on cation intercalation have been powering the increasingly mobile society for decades. 1 In a conventional lithium ion battery, the intercalation of lithium ions in both cathode (i.e., $\\mathrm{LiCoO}_{2}$ $\\mathrm{LiFePO_{4}})$ and anode (i.e., graphite, silicon) materials have been thoroughly studied, while the utilization of the anions in the electrolyte has drawn much less attention. 2 In fact, the phenomenon of anion intercalate into graphite by chemical or electrochemical means was discovered and proposed as a possible positive electrode for batteries by Rüdorff and Hofmann in 1938. 3 However, the anion intercalation was achieved by using high concentration acid solution as electrolyte, this brought serious safety issue that hindered its application. 4 In the 1990s, soon after the commercial application of lithium ion battery, Carlin et al. reported dual graphite intercalating molten electrolyte batteries that realized the application of anion intercalated graphite as positive electrode in batteries by using room temperature ionic liquids as electrolyte. 5 In the following decades, continuous progresses have been made in anion intercalated graphite based dual carbon batteries, such as investigation of anion intercalation in non-aqueous electrolyte, in situ characterization of the staged anion intercalation process, and systematic study of the intercalation of different anions into graphite. 6 However, due to electrolyte decomposition caused by the high positive potential of anion intercalated graphite $(\\approx5\\:\\mathrm{V}$ vs $\\mathrm{Li/Li^{+}})$ ) and exfoliation of graphite layers upon repeated ion/solvent molecule intercalation/deintercalation, reported dual-carbon batteries showed unsatisfied charge–discharge reversibility. 7 \n\nA key challenge of developing highly reversible dual-graphite battery is to find a suitable electrolyte enabling both $\\mathrm{Li^{+}}$ intercalation into graphite negative electrode and anion intercalation into graphite positive electrode simultaneously. Conventional carbonate electrolytes were mainly composed of ethylene carbonate (EC), acyclic carbonate, and lithium salt. EC in the electrolyte is an important component for the formation of solid electrolyte interphase (SEI) and the protection of the negative graphitic electrode. 8 Unfortunately, when applied in a dualgraphite battery, the EC molecules in the electrolyte can bind tightly with $\\mathrm{PF}_{6}{}^{-}$ anions, and prevent the intercalation of these anions into the interlayer spaces of graphite positive electrodes. 9 Recently, with the developments of novel electrolyte formulas, several studies have reported significantly improved reversibility of dual-carbon batteries. 10 Read et al. reported a reversible dual-graphite battery with simultaneous accommodation of $\\mathrm{Li^{+}}$ and $\\mathrm{PF}_{6}^{-}$ in graphitic structures enabled by a high voltage electrolyte based on fluorinated solvent and additive. 10a The battery demonstrated a reversible capacity of $60\\ \\mathrm{mAh\\g^{-1}}$ and a capacity retention of $62\\%$ after 50 cycles at C/7 rate. Rothermel et al. reported a dual-graphite battery based on a mixture of lithium bis-(trifluoromethanesulfonyl)-imide (LiTFSI) and ionic liquid with SEI-forming additive. This electrolyte formula not only enabled stable $\\mathrm{TFSI^{-}}$ intercalation into the graphite positive electrode, but also allowed highly reversible intercalation of $\\mathrm{Li^{+}}$ into the graphite negative electrode. 10b Under an upper cut-off potential of $5.0~\\mathrm{V},$ , the full graphite battery presented a capacity of $97~\\mathrm{mAh~g^{-1}}$ at a current rate of $10\\ \\mathrm{mA\\g^{-1}}$ and $50\\ \\mathrm{mAh\\g^{-1}}$ at $500\\ \\mathrm{mA}\\ \\mathrm{g}^{-1}$ which shed light on the potential application of dual-ion batteries as an environmentally friendly energy storage technology. \n\nHerein, we report a novel aluminum–graphite dual-ion battery (AGDIB) in an ethyl–methyl carbonate (EMC) electrolyte with high reversibility and high energy density. It is the first report on using an aluminum anode in dual-ion battery. The battery shows good reversibility, delivering a capacity of ${\\approx}100\\ \\mathrm{mAh}\\ \\mathrm{g}^{-1}$ and capacity retention of $88\\%$ after 200 charge– discharge cycles at $2\\mathrm{~C~}$ $1\\mathrm{~C~}$ corresponding to $100\\ \\mathrm{mA}\\ \\mathrm{g}^{-1}.$ ). To the best of our knowledge, performance of the battery is among the best of reported dual-ion batteries. \n\nFigure 1a schematically illustrates the initial and charged states of the AGDIB. Upon charging, $\\mathrm{PF}_{6}^{-}$ anions in the electrolyte intercalate into the graphite cathode, while the $\\mathrm{Li^{+}}$ ions in the electrolyte deposit onto the aluminum counter electrode to form an Al–Li alloy. The discharge process is the reverse of the charge process, where both $\\mathrm{PF}_{6}{}^{-}$ anions and $\\mathrm{Li^{+}}$ ions diffuse back into the electrolyte. The Al counter electrode acts as both the anode and the current collector, which greatly benefits the specific energy density and volumic energy density of the AGDIB. 11 Figure 1b shows galvanostatic charge–discharge curves of the AGDIB, exhibiting a typical profile of anion intercalation/deintercalation into/from graphite. The charge curve is mainly composed of three regions between 4.08 and 4.59 V (stage III), 4.59 and $4.63\\mathrm{V}$ (stage II), and 4.63 and $5.0\\mathrm{V}$ (stage I), each region corresponds to an anion intercalation stage of graphite, according to previous reports. 6e A dQ/dV differential curve of the battery is shown in the inset of Figure 1b. Peaks in the profile correspond to electrochemical processes in the AGDIB during charge–discharge. Stage III contains three wide weak peaks, while stage II contains a strong peak and small shoulder peak. No obvious peak in stage I can be observed. \n\n![](images/58797d0d6cc7a29c7d50e29920e0b488bbfcc37aabd67d6bbe784e9a757a853a.jpg) \nFigure 1. a) Schematic illustration of the AGDIB in the initial state (up) and the charged state (below). b) Galvanostatic charge–discharge curve of th AGDIB at $0.5\\textsf{C}$ (1 C corresponding to a current rate of $\\mathsf{l o o m A g^{-1}}.$ ). Insets are the ${\\mathsf{d Q}}/{\\mathsf{d V}}$ differential curve of the battery and a photograph showing that a single AGDIB cell lighting up two yellow LEDs in series. \n\nOnly three peaks are found in the discharge process, due to the diminish or disappear of two peaks during anion deintercalation process, as reported in previous report. 10b The AGDIB shows a working voltage range of $4.8\\substack{-3.4\\mathrm{~V~}}$ with a middle working voltage of ${\\approx}4.2~\\mathrm{V}$ at $0.5\\mathrm{~C~}$ current rate, which is much higher than most of those in commercial lithium ion batteries $(\\approx3.7~\\mathrm{V})$ . 12 The relative high discharge voltage of the AGDIB enabled a single coin cell to light up two yellow LEDs (nominal voltage of ${\\approx}2.5\\mathrm{~V~}$ ) in series (Figure 1b inset). \n\nWe believe that the good performance of the AGDIB battery is resulted from its specially designed configuration. Firstly, unlike other reported dual-ion batteries, we use aluminum instead of graphite anode. This design eliminates the needs for an addition metallic current collector and lead to considerable weight saving. Another advantage is that we can now eliminate the use of EC, which is commonly used in the electrolyte for protecting the graphite anode. This allows us to use a $100\\%$ EMC solvent in the electrolyte which not only solve the problem of binding between EC and $\\mathrm{PF}_{6}{}^{-}$ as reported by Wand and Gao et al., 9,13 it can also dissolve a much higher concentration of $\\mathrm{LiPF}_{6}$ comparing to the commonly used mixed solvents with EC. Seel and Dahn 14 have shown that using a high salt concentration can reduce the potential required for anion intercalation into the graphite cathode. Figure S2 in the Supporting Information shows charge–discharge curves in Li | $\\mathrm{LiPF}_{6}$ in EMC | Graphite batteries with different $\\mathrm{LiPF}_{6}$ concentrations. As the concentration of $\\mathrm{LiPF}_{6}$ increases from 1 to $4\\mathrm{~M~}$ the anion intercalation potential decreases from 4.45 to $4.34~\\mathrm{V}$ (Figure S2b, Supporting Information). This leads to a corresponding increase in specific capacity from 54 to $84~\\mathrm{mAh}~\\mathrm{g}^{-1}$ \n\nWe also found that performance of the battery depends critical on the metal used in the anode. We tested metal $\\mid4\\mathrm{~}_{\\mathrm{~M~}}$ $\\mathrm{LiPF}_{6}$ in EMC | graphite batteries with different metal counter electrodes (Cu, Fe, Li, Al). Surprisingly, the aluminum $\\mid4\\mathrm{~}_{\\mathrm{~M~}}$ $\\mathrm{LiPF}_{6}$ in EMC | graphite battery shows much higher initial discharge capacity and coulombic efficiency than the other batteries (Figure 2). As both Cu and Fe are inert to form alloy with lithium, the batteries based on Cu and Fe counter electrodes were unable to maintain the lithium ions deposited on them during the charge process. Therefore, only limited discharge capacities were observed in these batteries. On contrary, aluminum is able to form alloy with lithium and it has been studied as a promising anode material for lithium ion battery. 15 During charge process, lithium ions in the electrolyte obtain electrons on the surface of aluminum counter electrode and form stable aluminum–lithium alloy. This alloy enabled the controlled release of the lithium ions in the discharge process. \n\nAlthough the Al | $4\\mathrm{~M~LiPF}_{6}$ in EMC | Graphite battery exhibits impressive initial discharge capacity, the cycle stability of this battery is poor, resulting from the pulverization caused by the volume expansion of aluminum during the alloying process. 15a To improve the cycle stability, we tried to add SEI formation additive into the electrolyte to protect the aluminum counter electrode from pulverization. After screening of different electrolyte additives, we found that a small amount of vinylene carbonate (VC) is very effective in improving the cycle stability of the aluminum–graphite battery. Figure S3 in the Supporting Information shows the charge–discharge curves of the formation process of the AGDIB with different amount of VC in the electrolyte. With the presence of VC, the charge curves show an extra plateau at about 4.37 V, which corresponds to the decomposition of VC and the formation of SEI layer. 8b Meanwhile, the amount of VC was found to be critical for improving the cycle stability of the AGDIB. When the amount of VC is low (i.e., 1 wt%), the battery showed fast capacity decay (Figure S4a, Supporting Information). On the other hand, high amount of VC (i.e., $5\\mathrm{wt\\%}$ ) will lead to relatively lower coulombic efficiency during cycling and a battery failure was tricked after several charge–discharge cycles (Figure S4b, Supporting Information). We found that batteries with $2\\mathrm{wt\\%}$ VC in the electrolyte showed the best stability. Figure 3 shows the charge–discharge cycle test results of aluminum–graphite battery with commercial carbonate electrolyte $\\mathrm{1~M~LiPF_{6}}$ in EC/EMC/DMC), 4 M $\\mathrm{LiPF}_{6}$ in EMC, and $4\\mathrm{~M~LiPF}_{6}$ in $E\\mathrm{M}\\mathrm{C}+2\\mathrm{wt}\\%\\backslash$ C. With the presence of VC additive, the AGDIB exhibits a reversible discharge capacity of 105 mAh $\\mathbf{g}^{-1}$ (the seventh cycle) and a capacity retention of $96\\%$ after 50 cycles at $0.5\\mathrm{~C~}$ current rate. For comparison, the capacity of the batteries without VC additive dramatically decayed within the first 20 charge–discharge cycles. \n\nThe battery with $2\\mathrm{\\mt}\\%$ VC additive was then cycled at various charge–discharge rates ranging from 0.5 to $5\\mathrm{~C~}$ over a potential window of $3.0{-}5.0~\\mathrm{V}.$ Typical galvanostatic profiles of the battery are shown in Figure 4a. All the curves show the typical three-stage charge–discharge profile of anion intercalation in graphite, as discussed before. The gradually increased charge–discharge plateau separation implies small electrode polarization at low current rate and relatively large polarization at high current rates. Figure 4b further shows the charge–discharge capacities and corresponding coulombic efficiencies of the AGDIB during the rate capacity tests. At the rates of 0.5, 1, 2, 3, and $5\\mathrm{~C~}$ , the battery show discharge capacities of 105, 104, 100, 93, and 79 mAh $\\boldsymbol{\\mathrm{g}}^{-1}$ respectively. The battery can regain the high capacity when the current rate was set back to lower value gradually, demonstrating its high reversibility. The gradually increasing coulombic efficiencies $(67\\%-83\\%)$ during the first few cycles at $0.5\\mathrm{~C~}$ , was attributed to the formation of protective SEI layer on the surface of the electrodes. After the first 10 cycles at $0.5\\mathrm{~C~}$ , the battery shows stable coulombic efficiencies at each of the following current rates, with values of $91\\%$ , $92\\%$ , $96\\%$ , and $98\\%$ at 1, 2, 3, and $5\\mathrm{~C~}$ , respectively. Figure $4c$ illustrates the long term cycling performance of the AGDIB at a current rate of $2\\mathrm{~C~}$ . Compared with batteries based on anion intercalated graphite reported in literature, 7c 10,16 this AGDIB cell shows much improved cyclability. Notably, the discharge capacity varies from 104 to $92\\ \\mathrm{mAh\\g^{-1}}$ during the 200 charge– discharge cycles, corresponding to capacity retention of $88\\%$ and only $0.06\\%$ capacity loss per cycle. The electrochemical performance of this AGDIB is among the best of reported dual-ion batteries (Table S3). \n\n![](images/6da6e50174c1930269a782e67d00bbc6d3a79b8dfc7eedded1de11ac876e9a31.jpg) \nFigure 2. Charge–discharge curves of Metal $\\mid4\\ M\\ \\mathsf{L i P F}_{6}$ in EMC | Graphite batteries with respectively a) Cu, b) Fe, c) Li, and d) Al counter electrode. \n\n![](images/1fa24f371cf0c31d0273ae6feda7bffa6d0967c9964c56405f58e9439928da29.jpg) \nFigure 3. Charge–discharge cycle results of the batteries using different electylotes. The test current rate was $0.5\\mathrm{~C~}$ . a) Al $\\mid{\\mathsf{I}}{\\mathsf{\\Pi}}_{\\mathsf{M}}\\sqcup{\\mathsf{I i P F}}_{6}$ in EC–EMC– DMC | Graphite, b) Al $\\mid4\\mathrm{~M~}\\mathsf{L i P F}_{6}$ in EMC | Graphite, c) Al $14\\ M\\ L i\\mathsf{P F}_{6}$ in E $:M C+2w t\\%$ VC | Graphite. \n\nThe AGDIB reported here was composed of only environmentally friendly low cost materials (i.e., aluminum and graphite) as electrode materials, and conventional lithium salt and carbonate solvent as electrolyte. Compared with conventional secondary battery technologies (mainly lithium ion batteries), it shows an obvious advantage in production cost. Furthermore, as the Al counter electrode in the AGDIB acts as both the anode and the current collector, the dead load and dead volume of this battery could be significantly reduced, which result in a battery with both high specific energy density and high volume energy density. We roughly estimated the specific energy density and power density of the AGDIB based on the tested results and the mass composition of conventional packaged batteries (detail of the calculation is available in supporting materials). The calculation results (Table S1) show that the AGDIB can deliver a specific energy density of ${\\approx}222$ Wh $\\mathrm{kg^{-1}}$ at a power density of $132~\\mathrm{{W}~k g^{-1}}$ and ${\\approx}150\\ \\mathrm{Wh\\kg^{-1}}$ at $1200~\\mathrm{W~kg^{-1}}$ Figure 4d shows a comparison of the AGDIB with several main-stream energy storage technologies. Apparently, comparing with commercial lithium ion battery $(\\approx200\\ \\mathrm{Wh\\kg^{-1}}$ at $50~\\mathrm{W~kg^{-1}}$ and ${\\approx}100\\ \\mathrm{\\Wh}\\ \\mathrm{kg}^{-1}$ at $1000~\\mathrm{\\textW~kg}^{-1})$ ) and electrochemical capacitor $({\\approx}5\\mathrm{\\Wh\\kg^{-1}}$ at $5000~\\mathrm{W~kg^{-1}})$ ), the AGDIB shows significantly improved performances. 17 \n\n![](images/97fda2f71e88619dee3b8d5f553319ceacb964dcc7d9c2dc067d037fb7b9ccec.jpg) \nFigure 4. a) Charge–discharge curves of the AGDIB under 0.5, 1, 2, 3, and 5 C current rate $\\rceil\\mathsf{C}$ corresponding to $\\mathsf{l o o\\ m A\\ g^{-1}},$ . b) Rate capacities and corresponding coulombic efficiencies of the AGDIB. c) Long term cycle test result of the AGDIB at a current rate of 2 C. d) Performance comparison of the AGDIB with conventional electrochemical energy storage devices and several recently reported advanced energy storage devices, where DGB represents dual-graphite battery. \n\nTo understand the charge–discharge mechanism of the AGDIB, further characterizations of the electrodes were carried out. The anion intercalation in graphite positive electrode is a reported phenomenon. The intercalation of $\\mathrm{PF}_{6}^{-}$ (size of $4.36\\ \\mathring\\mathrm{A}\\bar{\\big/}^{[18]}$ into graphite sheets (distance of $3.36\\mathrm{~\\AA~}$ ) is accompanied by significant inter space expansion and gradual exfoliation of the graphite sheets (Figure S5, Supporting Information), which is responsible for the slow capacity degradation during cycling. The electrochemical process on the Al counter electrode is of great interests. The charge–discharge curves of a Li–Al half cell is shown in Figure S6 in the Supporting Information. It shows that the Al–Li alloying process on the aluminum electrode exhibited a flat plateau at about $0.22\\mathrm{~V~}$ versus $\\mathrm{Li/Li^{+}}$ , and $0.52\\mathrm{~V~}$ versus $\\mathrm{{Li/Li^{+}}}$ during dealloying process. Figure 5a,b shows photographs of the Al electrodes before and after charged in the AGDIB. A rough layer on the surface of the charged Al electrode could be observed by naked eyes. Scanning electron microscopic (SEM) image shows that the rough layer possess nanoporous microstructures (Figure 5d), which was likely to be caused by the formation of SEI layer and the Al–Li alloying process. Energy dispersive X-ray spectroscopy (EDS) mapping (Figure S7 and Table S2, Supporting Information) on the surface of the charged Al electrode show the existence of F, C, and O, which are common composing elements of SEI layers. 19 This SEI layer could protect the Al electrode from destruction during Li–Al alloying and dealloying process. For comparison, much less elements component of SEI layer were found (Figure S8, Supporting Information) on the surface of Al electrode without the presence of VC. Without the protection of SEI layer, pulverization and cracks were found on the surface of the Al electrode (Figure S9, Supporting Information).The existence of Al–Li alloy on the charged Al electrode was verified by the XRD patterns (Figure 5e), where diffraction peaks of both Al (JCPDS Card No. 65-2869) and AlLi (JCPDS Card No. 65-3017) can be clearly observed. According to the characterization results, electrochemical reactions in the AGDIB are proposed as follows. \n\nThe half cell reaction at the negative electrode is considered to be \n\n![](images/a0d3d62ecd01d978511c03243b658f804489d5b1cd83c6cd3ec828acf4a7f844.jpg) \nFigure 5. Photographs of a) a fresh Al foil and b) an Al electrode in a charged battery. SEM images of c) a fresh Al foil and d) an Al electrode in a charged battery. e) XRD patterns of a fresh Al foil (below) and an Al electrode in a charged battery (up). \n\n$$\n\\mathrm{Al+Li^{+}+e^{-}\\leftrightarrow A l L i}\n$$ \n\nAnd the half cell reaction at the positive electrode is considered to be 14 \n\n$$\nx\\mathrm{C}+\\mathrm{PF}_{6}^{-}\\leftrightarrow\\mathrm{C}_{x}\\left(\\mathrm{PF}_{6}\\right)+\\mathrm{e}^{-}\n$$ \n\nThe full cell reaction is \n\n$$\n\\mathsf{A l}+x\\mathsf{C}+\\mathrm{Li}^{+}+\\mathsf{P F6}^{-}\\leftrightarrow\\mathsf{A l L i}+\\mathsf{C}_{x}\\left(\\mathsf{P F}_{6}\\right)\n$$ \n\nThe Al–Li alloying process has been studied as a potential anode of lithium ion battery in previous works. 15,20 The theoretical capacity of aluminum could reach $2235\\mathrm{\\mAh\\g^{-1}}$ in the form of $\\mathrm{Li_{9}A l_{4}}$ However, the lithiation of aluminum faces a ${\\approx}100\\%$ volume expansion, which would tear up the anode SEI layer and cause the pulverization of the active material. Here in the AGDIB, the lithiation of Al electrode was stabilized for the following two reasons. Firstly, compared with the deep lithiation in $\\mathrm{Li_{9}A l_{4}}$ the volume expansion caused by the shallow lithiation (AlLi) in the present AGDIB is smaller, which could help reduce the stress in the Al electrode caused by lithiation. Secondly, VC induced SEI layer on the surface of Al electrode could protect the Al electrode from destruction caused by the Li–Al alloying process. Detailed mechanism of this AGDIB battery, in particularly the role of VC are still under further investigation. \n\nIn summary, we have developed a novel AGDIB composed of only environmentally friendly low-cost materials (i.e., aluminum as counter electrode, graphite as positive electrode), and a specially designed carbonate electrolyte. As aluminum acted as both the negative current collector and the negative active material, the AGDIB shows significantly reduced dead load and dead volume. The AGDIB delivers a reversible capacity of $104~\\mathrm{{mAh}~g^{-1}}$ (based on the mass of graphite) at $2\\mathrm{~C~}$ current rate, and a capacity retention of $88\\%$ after 200 cycles. According to the composition of conventional packaged battery, a packaged AGDIB cell is estimated to delivery an energy density of ${\\approx}220$ Wh $\\mathrm{kg^{-1}}$ at a power density of ${\\approx}130$ W $\\mathrm{kg^{-1}}$ and ${\\approx}150$ Wh $\\mathrm{kg^{-1}}$ at ${\\approx}1200~\\mathrm{W~kg^{-1}}$ which are significantly higher than most commercial lithium ion batteries, indicating its potential to be a low-cost power source with both high energy density and high power density. \n\n# Experimental Section \n\nAluminum foil (thickness of ${\\mathsf{7}}5{\\mathsf{\\upmu m}}_{\\mathrm{,}}^{\\mathsf{\\prime}}$ ) purchased from Shenzhen Kejingstar was used as the counter electrode. The graphite positive electrode composes of $80\\mathrm{\\textperthousand}$ of natural graphite $(d_{002}$ spacing of $3.363\\mathring{\\mathsf{A}}$ , SEM image shown in Figure S1, Supporting Information), $10\\mathrm{{wt\\%}}$ of conductive carbon black, and $10\\mathrm{\\textmum}\\%$ of polyvinylidene fluoride (PVDF) as binder.N-methyl-2-pyrrolidone (NMP) was added to the above mixture and grounded to form a uniform slurry. Then the slurry was pasted onto aluminum foil and dried in vacuum in an $80~^{\\circ}C$ oven. The mass loading of the graphite positive electrode was $1.5~\\mathsf{m g}\\mathsf{c m}^{-2}$ .The components of the electrolyte, namely EMC, VC, and $\\mathsf{L i P F}_{6}$ were used as purchased from Dodochem. The commercial electrolyte, $\\rceil\\mathrm{~}\\mathsf{M}$ $\\mathsf{L i P F}_{6}$ EC–EMC–DMC (1:1:1), was kindly provided by Capchem. \n\nPowder X-ray diffraction (XRD) analysis was carried out on a Rigaku $\\mathsf{D}/$ $M a x-2500$ diffractometer using Cu $\\mathsf{K}\\alpha$ radiation with a scan rate of $8^{\\circ}\\operatorname*{min}^{-1}$ , operating at $40~\\mathsf{k V}$ and $30~\\mathsf{m A}$ . XRD samples of the charged electrodes were prepared in glove box, washed with EMC, and coated with parafilm to protect them from been oxidized by air. SEM images were collected on a HITACHI S-4800 field emission scanning electron microscope. \n\nElectrochemical tests were performed with CR2032 coin-type cells. The graphite positive electrode was countered with different metal electrodes (Li, Al, Fe, Cu). Lab-made electrolyte or the purchased commercial electrolyte were used as the electrolyte and glass fiber was used as separator. The preparation of electrolyte and fabrication of battery were conducted in an argon filled glove box (Etelux Lab2000). Cyclic voltammetry (CV) tests were done on an AUTOLAB PGSTAT302N electrochemical station. Galvanostatic charge–discharge tests were carried out on LAND CT2011A battery test system at room temperature. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThis project was financially supported by the National Natural Science Foundation of China (Nos. 51272217, 51302238), Science and Technology Planning Project of Guangdong Province (Nos. 2014A010105032, 2014A010106016), Guangdong Innovative and Entrepreneurial Research Team Program (No. 2013C090), Shenzhen Municipality Project (No. JCYJ20140417113430618, JSGG20150602143328010), and Scientific Equipment Project of Chinese Academy of Sciences (yz201440) \n\n[1] a) D. Larcher, J. M. Tarascon, Nat. Chem. 2015, 7, 19; b) J. B. Goodenough, K. S. Park, J. Am. Chem. Soc. 2013, 135, 1167; c) J. Cabana, L. Monconduit, D. Larcher, M. R. Palacín, Adv. Mater. 2010, 22, E170. \n[2] A. Vlad, N. Singh, C. Galande, P. M. Ajayan, Adv. Energy Mater. 2015, 5, 1402115. \n[3] W. Rüdorff, U. Hofmann, Z. Anorg. Allg. Chem. 1938, 238, 1. \n[4] F. Beck, H. Junge, H. Krohn, Electrochim. Acta 1981, 26, 799. \n[5] R. T. Carlin, H. C. De Long, J. Fuller, P. C. Trulove, J. Electrochem. Soc. 1994, 141, L73. \n[6] a) T. Placke, S. Rothermel, O. Fromm, P. Meister, S. F. Lux, J. Huesker, H. W. Meyer, M. Winter, J. Electrochem. Soc. 2013, 160, A1979; b) T. Ishihara, Y. Yokoyama, F. Kozono, H. Hayashi, J. Power Sources 2011, 196, 6956; c) T. E. Sutto, T. T. Duncan, T. C. Wong, Electrochim. Acta 2009, 54, 5648; d) W. C. West, J. F. Whitacre, N. Leifer, S. Greenbaum, M. Smart, R. Bugga, M. Blanco, S. R. Narayanan, J. Electrochem. Soc. 2007, 154, A929; e) M. Noel, R. Santhanam, J. Power Sources 1998, 72, 53. \n[7] a) J. Gao, M. Yoshio, L. Qi, H. Wang, J. Power Sources 2015, 278, 452; b) X. Qi, B. Blizanac, A. DuPasquier, P. Meister, T. Placke, M. Oljaca, J. Li, M. Winter, Phys. Chem. Chem. Phys. 2014, 16, 25306; c) H. Nakano, Y. Sugiyama, T. Morishita, M. J. S. Spencer, I. K. Snook, Y. Kumai, H. Okamoto, J. Mater. Chem. A 2014, 2, 7588. \n[8] a) J. Li, C. Ma, M. Chi, C. Liang, N. J. Dudney, Adv. Energy Mater. 2015, 5, 1401408; b) K. Xu, Chem. Rev. 2014, 114, 11503. \n[9] H. Wang, M. Yoshio, Chem. Commun. 2010, 46, 1544. \n[10] a) J. A. Read, A. V. Cresce, M. H. Ervin, K. Xu, Energy Environ. Sci. 2014, 7, 617; b) S. Rothermel, P. Meister, G. Schmuelling, O. Fromm, H.-W. Meyer, S. Nowak, M. Winter, T. Placke, Energy Environ. Sci. 2014, 7, 3412. \n[11] a) V. Aravindan, Y. S. Lee, S. Madhavi, Adv. Energy Mater. 2015, 5, 1402225; b) Z. Cai, L. Xu, M. Yan, C. Han, L. He, K. M. Hercule, C. Niu, Z. Yuan, W. Xu, L. Qu, K. Zhao, L. Mai, Nano Lett. 2015, 15, 738. \n[12] a) X. Zhang, F. Cheng, J. Yang, J. Chen, Nano Lett. 2013, 13, 2822; b) A. Kraytsberg, Y. Ein-Eli, Adv. Energy Mater. 2012, 2, 922. \n[13] J. Gao, S. Tian, L. Qi, M. Yoshio, H. Wang, J. Power Sources 2015, 297, 121. \n[14] J. A. Seel, J. R. Dahn, J. Electrochem. Soc. 2000, 147, 892. \n[15] a) S. Li, J. Niu, Y. C. Zhao, K. P. So, C. Wang, C. A. Wang, J. Li, Nat. Commun. 2015, 6; b) J. H. Park, C. Hudaya, A. Y. Kim, D. K. Rhee, S. J. Yeo, W. Choi, P. J. Yoo, J. K. Lee, Chem. Commun. 2014, 50, 2837; c) E. C. Gay, D. R. Vissers, F. J. Martino, K. E. Anderson, J. Electrochem. Soc. 1976, 123, 1591. \n[16] a) M. L. Aubrey, J. R. Long, J. Am. Chem. Soc. 2015; b) P. Meister, V. Siozios, J. Reiter, S. Klamor, S. Rothermel, O. Fromm, H.-W. Meyer, M. Winter, T. Placke, Electrochim. Acta 2014, 130, 625; c) G. Park, N. Gunawardhana, C. Lee, S. M. Lee, Y. S. Lee, M. Yoshio, J. Power Sources 2013, 236, 145; d) A. K. Thapa, G. Park, H. Nakamura, T. Ishihara, N. Moriyama, T. Kawamura, H. Y. Wang, M. Yoshio, Electrochim. Acta 2010, 55, 7305. \n[17] a) T. Lin, I.-W. Chen, F. Liu, C. Yang, H. Bi, F. Xu, F. Huang, Science 2015, 350, 1508; b) M. C. Lin, M. Gong, B. Lu, Y. Wu, D. Y. Wang, M. Guan, M. Angell, C. Chen, J. Yang, B. J. Hwang, H. Dai, Nature 2015, 520, 325; c) F. Zhang, T. Zhang, X. Yang, L. Zhang, K. Leng, Y. Huang, Y. Chen, Energy Environ. Sci. 2013, 6, 1623; d) T.-H. Kim, J.-S. Park, S. K. Chang, S. Choi, J. H. Ryu, H.-K. Song, Adv. Energy Mater. 2012, 2, 860; e) A. Du Pasquier, I. Plitz, S. Menocal, G. Amatucci, J. Power Sources 2003, 115, 171. \n[18] J. A. Read, J. Phys. Chem. C 2015, 119, 8438. \n[19] K. Tasaki, A. Goldberg, J.-J. Lian, M. Walker, A. Timmons, S. J. Harris, J. Electrochem. Soc. 2009, 156, A1019. \n[20] C. J. Wen, B. A. Boukamp, R. A. Huggins, W. Weppner, J. Electrochem. Soc. 1979, 126, 2258. " + }, + { + "id": "10.1126_science.aah6133", + "DOI": "10.1126/science.aah6133", + "DOI Link": "http://dx.doi.org/10.1126/science.aah6133", + "Relative Dir Path": "mds/10.1126_science.aah6133", + "Article Title": "Biaxially strained PtPb/Pt core/shell nulloplate boosts oxygen reduction catalysis", + "Authors": "Bu, LZ; Zhang, N; Guo, SJ; Zhang, X; Li, J; Yao, JL; Wu, T; Lu, G; Ma, JY; Su, D; Huang, XQ", + "Source Title": "SCIENCE", + "Abstract": "Compressive surface strains have been necessary to boost oxygen reduction reaction (ORR) activity in core/shell M/platinum (Pt) catalysts (where M can be nickel, cobalt, or iron). We report on a class of platinum-lead/platinum (PtPb/Pt) core/shell nulloplate catalysts that exhibit large biaxial strains. The stable Pt (110) facets of the nulloplates have high ORR specific and mass activities that reach 7.8 milliampere (mA) per centimeter squared and 4.3 ampere per milligram of platinum at 0.9 volts versus the reversible hydrogen electrode (RHE), respectively. Density functional theory calculations reveal that the edge-Pt and top (bottom)-Pt (110) facets undergo large tensile strains that help optimize the Pt-O bond strength. The intermetallic core and uniform four layers of Pt shell of the PtPb/Pt nulloplates appear to underlie the high endurance of these catalysts, which can undergo 50,000 voltage cycles with negligible activity decay and no apparent structure and composition changes.", + "Times Cited, WoS Core": 1351, + "Times Cited, All Databases": 1430, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000390261300040", + "Markdown": "# ELECTROCATALYSIS \n\n# Biaxially strained PtPb/Pt core/shell nanoplate boosts oxygen reduction catalysis \n\nLingzheng Bu,1 Nan Zhang,1 Shaojun Guo,2,3,4\\* Xu Zhang,5 Jing Li,6 Jianlin Yao,1 Tao $\\mathbf{w}_{\\mathbf{u}}$ ,1 Gang Lu,5 Jing-Yuan Ma,7 Dong Su,6\\* Xiaoqing Huang1\\* \n\nCompressive surface strains have been necessary to boost oxygen reduction reaction (ORR) activity in core/shell M/platinum (Pt) catalysts (where M can be nickel, cobalt, or iron). We report on a class of platinum-lead/platinum (PtPb/Pt) core/shell nanoplate catalysts that exhibit large biaxial strains. The stable Pt (110) facets of the nanoplates have high ORR specific and mass activities that reach 7.8 milliampere (mA) per centimeter squared and 4.3 ampere per milligram of platinum at 0.9 volts versus the reversible hydrogen electrode (RHE), respectively. Density functional theory calculations reveal that the edge-Pt and top (bottom)–Pt (110) facets undergo large tensile strains that help optimize the Pt-O bond strength. The intermetallic core and uniform four layers of Pt shell of the PtPb/Pt nanoplates appear to underlie the high endurance of these catalysts, which can undergo 50,000 voltage cycles with negligible activity decay and no apparent structure and composition changes. \n\nN caantoasltyrsutcftourrfeudelplcaetlilnsuasm $\\mathrm{(Pt)}$ ias avnareifofiucsieintdustrial chemical reactions (1–4), but its high cost impedes its large-scale commercialization (5–7). The most successful catalysts for boosting the activity of catalysts for the oxygen reduction reaction (ORR) on a per-Pt-atom basis have been PtM alloy nanoparticles (NPs) (where M has been Ni, Co, or Fe, among other metals) with a Pt-skin surface (core-shell structure). However, the formation of either a disordered PtM core or nonuniform Pt-skin layer (8–14) usually results in poor electrocatalytic stability after long-term voltage cycling. \n\nIn general, tuning or optimizing the oxygen adsorption energy through adjusting the compressive strain of the Pt surface is believed to be an effective approach to improve the ORR activity (15, 16). Ordered intermetallic phases with high transition metal content can be used to provide better control over the compressive strain effect for optimized catalysis (17). The optimal compressive strain to Pt (111) facet in PtM/Pt core/ shell NPs is particularly necessary for boosting ORR catalysis. The tensile strain on the Pt (111) \n\nfacet is usually believed to be undesirable because such surface strain will result in overly strong binding of the oxygen species to the surfaces during the catalysis process. Although the activity enhancement has been demonstrated in the core/shell electrocatalyst with a Pt monolayer shell (causing limited durability) and an intermetallic PtPb core (18), the control over the stable and active facets of Pt shell onto PtPb core, and the investigation of strong tensile strain for ORR enhancement have not been explored. \n\nWe report on a class of highly uniform PtPb/Pt core/shell nanoplates with large biaxial tensile strain for boosting ORR. Rather than use compressive strain to optimize the oxygen adsorption energy, we show that at a very high tensile strain, the Pt (110) plane located outside the nanoplates can exhibit the superior electrocatalytic activity for ORR (19, 20). By integrating the strong tensile strain of PtPb to Pt (110) facet along [100] direction with thin two-dimensional (2D) morphology and intermetallic phase (ensuring high chemical stability), the as-prepared nanoplate can deliver specific and mass activities for ORR that are 33.9 and 26.9 times greater than those of the commercial $\\mathrm{Pt/C}$ catalyst (8, 21, 22). The PtPb nanoplates show negligible activity decay and no obvious structure and composition changes after a 50,000-cycle electrochemical accelerated durability test (ADT). They are also extremely active and stable for anodic oxidation reactions, largely outperforming those based on the PtPb NPs and the commercial $\\mathrm{Pt/C}$ in both methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR). \n\nWe synthesized $\\mathrm{PtPb/Pt}$ core/shell hexagonal nanoplates in nonaqueous conditions using platinum (II) acetylacetonate $\\mathrm{[Pt(acac)_{2}]}$ and lead (II) acetylacetonate $\\mathrm{[Pb(acac)_{2}]}$ as the metal precursors, oleylamine (OAm)/octadecene (ODE) mixture as solvents and surfactants, and ascorbic acid (AA) as the reducing agent [details in the supplementary materials (23)]. The structure of nanoplates was characterized by transmission electron microscopy (TEM) and high-angle annular dark-field scanning TEM (HAADF-STEM). The as-prepared hexagonal nanoplates were the dominant product, with monodisperse edge length of ${\\sim}16~\\mathrm{nm}$ and the synthetic yield approaching $100\\%$ (Fig. 1, A and B). The thickness of PtPb nanoplates was determined to be $4.5\\pm0.6\\ \\mathrm{nm}$ by analyzing the nanoplates vertical on the TEM grid (fig. S1). The overall $\\mathrm{Pt/Pb}$ composition, measured by inductively coupled plasma atomic emission spectroscopy (ICP-AES), was 55.9/44.1 (Pt/Pb), consistent with the TEM energy-dispersive x-ray spectroscopy (TEM-EDX) result (Fig. 1C). \n\nPowder x-ray diffraction (PXRD) pattern of the PtPb nanoplates showed that they were highly crystalline with intermetallic PtPb phase [Joint Committee on Powder Diffraction Standards (JCPDS) no. 06-0374] (Fig. 1D and fig. S2). The selected-area electron diffraction (SAED) of a single PtPb nanoplate showed its single crystalline and was consistent with the diffraction pattern from the [001] zone axis of PtPb (P63/mmc) hexagonal phase (Fig. 1E). However, a high-resolution TEM (HRTEM) image of the same nanoplate (Fig. 1F) revealed that the edge has a different crystalline structure with the interior. A few edge dislocations were also observed between the edge layer and the interior around the corners, which help to relax the misfit strain between the edge phases. The fast Fourier transform (FFT) patterns indicate a cubic phase at the edge layer and a hexagonal phase of the interior (see the insets of Fig. 1F). \n\nThe elemental distribution of Pt and Pb at the nanoplates was characterized using STEM-electron energy-loss spectroscopy (EELS) mapping (Fig. 1G), where the Pt (green), Pb (red), and combined (green versus red) images indeed confirmed the presence of a Pt edge layer around the PtPb core (Fig. 1G). Considering the SAED, HRTEM, and STEM-EELS mapping results together, we can conclude that a Pt shell layer with a cubic phase $\\mathrm{(Fm-3m)}$ formed at the edge, and the diffraction pattern of Fig. 1E can be interpreted as the overlapped diffraction patterns from the ${<}\\mathrm{{110}}\\mathrm{{>}}$ zone axis of strained Pt phase and [001] zone axis of PtPb phase. The Pt shell thickness was determined to be about 0.8 to $1.2\\ \\mathrm{nm}$ (four to six atomic layers). \n\nThe abreaction-corrected HAADF-STEM imaging technique was further used to characterize the facets and interfaces of the PtPb nanoplates. The nanoplates were imaged from both the plate view and the side view (Fig. 2A). Figure 2B is a HAADFSTEM image along the PtPb [100] zone axis (side view), whereas Fig. 2C is a HAADF-STEM image from the [001] PtPb zone axis (plate view). Figure 2, D to F, are atomic-resolution STEM-HAADF images taken at higher magnifications from the areas indicated by the yellow rectangles. The Pt and PtPb phases can be identified from their different stacking sequences. Image simulation with a multisliced method, as well as the projection of atoms, was overlapped on Fig. 2, D to F. The results confirmed the PtPb(hexagonal)/ Pt(cubic) core/shell structure: In addition to the [(110)Pt/ (100)PtPb] and the side interface [(110)Pt /(001)PtPb]. \n\n![](images/40a8f9d973416610b32522ea19ab75ad52c49383d8e3738545a2097c214d9e5a.jpg) \nFig. 1. Morphology and structure characterization of PtPb hexagonal nanoplates. \nand integrated mapping of Pt and Pb are shown. The compositional ratio between Pt/Pb is 55.9/44.1, as revealed by ICP-AES. \n\n![](images/5c54921af6a0e8f09fbf4d4e2f585a923b3362fa1eba35a7969fc3de686720f7.jpg) \nRepresentative (A) HAADF-STEM image, (B) TEM image, (C) TEMEDX, and (D) PXRD pattern of PtPb hexagonal nanoplates. (E) SAED and (F) HRTEM of one single hexagonal nanoplate. Insets of Fig. 1F are the FFT patterns from the white squares at the edge of and inside the nanoplate, respectively. (G) STEMEELS elemental mapping of PtPb hexagonal nanoplates: HAADFSTEM image, Pt mapping in green, Pb mapping in red, \nFig. 2. Structure analysis of PtPb nanoplates. (A) A model of one single hexagonal nanoplate, (B) HAADFSTEM image from in-plate view, (C) HAADF-STEM image from out-of-plate view. (D to F) (D) is a high-resolution HAADF image from the selected area in (C). (E) and (F) are high-resolution HAADF images from the selected areas in (B). Simulated HAADF images as well as the atomic models are superimposed on the experimental images. (G) The schematic atom models of the nanoplate showing the top interface \n\nPt edge layers, there were top (bottom)-Pt layers on the plane surfaces of nanoplates, forming the “perfect” core/shell structure. Thus, two types of interfacial planes formed in PtPb nanoplates: $\\{010\\}\\mathrm{PtPb}//\\{110\\}\\mathrm{Pt}$ between the PtPb and the edge-Pt layer, and $\\{001\\}\\mathrm{PtPb}//\\{110\\}\\mathrm{Pt}$ between PtPb and top (bottom)-Pt layer (atomic schematic model of Fig. 2G and figs. S3 to S6). Herein, the unique Pt {110} surface would be beneficial for ORR activity enhancement because Pt {110} facet has been demonstrated to be intrinsically more active than $\\mathbb{P}\\{\\mathfrak{m}\\}$ facet for the ORR in perchloric acid (24, 25). The SAED, HRTEM, and selectedarea FFT analysis (figs. S4 to S6) further revealed that the top-Pt layers were fully coherent to the PtPb core, with an $11\\%$ compressive strain along the $[01\\mathrm{-}1]_{\\mathrm{Pt}}$ and a $7.5\\%$ tensile strain along $[100]_{\\mathrm{Pt}},$ whereas in the edge-Pt layer, the [001] direction of Pt was fully confined within PtPb, resulting in a $7.5\\%$ tensile strain and little compressive strain $(1.0\\%)$ ) along [110] Pt (fig. S3). \n\nThe synthesis of 2D pure metal nanoplates is challenging because of the intrinsically isotropic growth behavior of metals (26–28). Time-dependent composition and structure changes revealed that making intermetallic PtPb/Pt core/shell hexagonal nanoplates involved the initial formation of $\\mathrm{Pb_{3}(C O_{3})_{2}(O H)_{2}}$ , the transformation of $\\mathrm{Pb_{3}(C O_{3})_{2}(O H)_{2},}$ , the reduction of Pt species, and hereafter the interdiffusion to form structurally ordered intermetallic PtPb nanoplates (figs. S7 and S8). The use of AA as reductant is the key for the formation of wellorganized Pt atomic layers because during the synthetic process, AA can work as a weak acid for removing the $\\mathrm{\\mathbf{Pb}}$ , allowing the Pt atoms to diffuse and rearrange at higher temperatures. \n\nWe performed a set of control experiments using a variety of synthetic parameters, such as precursor, surfactant, and reducing agent, to investigate how the different synthetic reagents affect the growth of the well-defined PtPb hexagonal nanoplates. The synthesis of well-defined PtPb/Pt nanoplates depended highly on the concentration of Pt and Pb precursors, the combined use of OAm to ODE, and the use of proper reducing agents (figs. S9 to S15). The concentration of AA also had to stay within a critical range to obtain a high yield of PtPb/Pt core/shell nanoplates (fig. S14), and PtPb hexagonal nanoplates could not be made by replacing AA with other reducing agents, such as glucose and citric acid (fig. S15). \n\nThe electrochemical properties of the PtPb nanoplates as well as PtPb nanoparticles that we synthesized (figs. S16 and S17) were studied and further benchmarked against the commercial $\\mathrm{Pt/C}$ from Johnson Matthey (JM) $(\\mathrm{Pt}/\\mathrm{C},$ , 20 weight $\\%$ Pt on Vulcan XC72R carbon, Pt particle size 2 to $5\\mathrm{nm}$ ) (fig. S18, A and B). Before the electrochemical measurement, the PtPb nanostructures were uniformly deposited on a commercial carbon (C, Vulcan) support (figs. S19 and S20, named as PtPb nanoplates/C and PtPb nanoparticles/C) via the sonication of PtPb nanostructures and C solution. The products were further treated with the mixture of ethanol/acetic acid to remove the surfactant (29). The inset of \n\n![](images/3f05084eca4502f971df00997138c86f6afdd2f150211f113f4ad4eb2273d456.jpg) \nFig. 3. Electrocatalytic performance of PtPb nanoplates/C, PtPb nanoparticles/C, and commercial Pt/C catalysts for ORR. (A) ORR polarization curves and (B) specific and mass activities of different catalysts. Inset in (A) is the CVs of different catalysts in 0.1 M $H C l O_{4}$ solution at a sweep rate of $50\\mathrm{mV/s}$ . The ORR polarization curves were recorded at room temperature in an ${{\\mathrm O}_{2}}$ -saturated 0.1 M $H C l O_{4}$ aqueous solution.The activities were calculated based on five parallel measurements after Ohmic drop correction. (C) ORR polarization curves of the PtPb nanoplates/C catalyst before and after different potential cycles between 0.6 and 1.1 V versus RHE. (D) The changes on specific and mass activities of the $\\mathsf{P t P b}$ nanoplates/ C catalyst before and after different potential cycles. (E) The changes on specific and mass activities of the PtPb nanoparticles/C catalyst before and after different potential cycles. (F) The changes on specific and mass activities of the commercial Pt/C catalyst before and after different potential cycles. \n\nFig. 3A shows cyclic voltammograms (CVs) of PtPb nanoplates/C, PtPb nanoparticles/C, and commercial $\\mathrm{Pt/C}$ catalysts in $\\mathbf{N}_{2}$ -purged $0.1\\mathrm{M}$ $\\mathrm{HClO}_{4}$ solution at a sweep rate of $50\\mathrm{mV/s}$ . The PtPb nanoplates showed greater electrochemical active surface area (ECSA) of $55.0\\mathrm{m}^{2}/\\mathrm{g}$ than PtPb nanoparticles $(43.4\\mathrm{m}^{2}/\\mathrm{g})$ because of their thinness and even comparable ECSA to that of the commercial Pt/C $(68.9\\mathrm{m}^{2}/\\mathrm{g})$ . \n\nTo evaluate the electrocatalytic activities toward ORR, the ORRpolarization curves of PtPb nanoplates/ C, PtPb nanoparticles/C and commercial $\\mathrm{Pt/C}$ were measured in an $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{M}\\mathrm{HCl}0_{4}$ solution under Ohmic drop correction (Fig. 3A). As shown in Fig. 3B and table S1, the specific activity (SA) of PtPb nanoplates/C could reach $7.8\\mathrm{mA}/\\mathrm{cm}^{2}$ at $0.9{\\mathrm{V}}$ versus reversible hydrogen electrode (RHE), 4.1 and 33.9 times greater than those of PtPb nanoparticles/C $(1.9\\ \\mathrm{mA}/\\mathrm{cm}^{2})$ and commercial $\\mathrm{Pt/C(0.23\\mathrm{mA/cm^{2})}}$ . The mass activity (MA) of PtPb nanoplates/C is $4.3\\mathrm{A}/\\mathrm{mg_{Pt}}$ at $0.9\\mathrm{V}$ versus RHE, which is ${\\sim}9.8$ times that of the 2020 U.S. Department of Energy target (30), and places them among the most efficient bimetallic catalysts reported for ORR (8, 21, 22). \n\nThe electrochemical durability of the $\\mathrm{PtPb/Pt}$ core/shell nanoplates was evaluated at the potential between 0.6 and 1.1 V versus RHE in 0.1 M $\\mathrm{HClO_{4}}$ solution. Figure 3C shows the ORR polarization curves of the PtPb nanoplates/ C before and after 10,000, 20,000, 30,000, 40,000, and 50,000 potential cycles. After 50,000 sweeping cycles, there was almost no shift in ORR polarization curves and only $7.7\\%$ loss of mass activity for the PtPb nanoplates (Fig. 3D). However, under the same condition, the PtPb nanoparticles/C showed a large negative shift in ORR polarization curves (fig. S21A) and $37.0\\%$ loss of mass activity (Fig. 3E). The commercial $\\mathrm{Pt/C}$ showed a much larger negative shift in ORR polarization curves (fig. S21B) with $66.7\\%$ loss of mass activity (Fig. 3F). The structures of the catalysts before and after the durability tests were characterized by TEM, SEM-EDX, HRTEM, elemental mappings, and extended x-ray absorption fine structure (EXAFS) (figs. S19, S22, and S23), showing that there was negligible change on the morphology and composition of the PtPb nanoplates (figs. S19, G to I, and S22, D to F) and Pt-Pt atomic distance (fig. S23) after long-term cycles. Under the same condition, the PtPb nanoparticles show noticeable morphology and composition changes (fig. S20, C and D), and the commercial $\\mathrm{Pt/C}$ catalyst exhibited large size changes and substantial aggregation after 50,000 cycles (fig. S18, C and D). We think that the high catalytic stability of PtPb/ Pt core/shell nanoplates originates from their special structure, in which the well-defined Pt shell can hinder the loss of interior transition metal through the place-exchange mechanism during electrochemical condition and thus improve their ORR durability, which is hardly afforded by the previously reported PtPb/Pt core/shell structures suffering from the typical electrocatalytic activity loss possibly due to their too thin Pt shell (18, 31). \n\n![](images/9dbec6a58e4c3f7264c3122a226400b426d04090684d59f618f65272eb004254.jpg) \nFig. 4. DFT calculations of oxygen adsorption energy. \n(A) Atomic models of the Pt (110) surface. Three stable adsorption sites for oxygen: hollow (“h”) and two bridge sites (“b1” and “b2”). The blue and green spheres represent Pt and O atoms, respectively. (B to D) On the Pt (110) surface, $\\Delta E_{\\mathrm{{O}}}$ as a function of biaxial strain in [110] and [001] directions for the “h” site (B) and the “b1” site (C), and the “b2” site is plotted in (D). The optimal $\\Delta E_{\\mathrm{{O}}}$ value is set to be 0. $\\Delta E_{\\mathrm{{O}}}$ value falling into \nthe shaded region implies a higher ORR activity than that on the flat Pt (111) surface. \n\nTo understand the exceptional ORR performance of the core/shell PtPb/Pt nanoplates, we performed density functional theory (DFT) calculations for the oxygen adsorption energy $(E_{\\mathrm{O}})$ on the PtPb nanoplates. The ORR activity reaches the maximum at some optimal value of $E_{\\mathrm{O}}$ (32, 33). For convenience, we shifted the optimal $E_{\\mathrm{O}}$ value to $0\\mathrm{eV}$ and use $\\Delta E_{\\mathrm{O}}$ to represent the difference of a given $E_{\\mathrm{O}}$ value relative to this optimal reference. In general, both surface strain and ligand effect can influence the catalytic activity of a coreshell nanostructure, and they can be tuned by the variation of alloy composition in the core. We ignored the ligand effect because it is often negligible for a shell thickness ${>}0.6~\\mathrm{nm}$ (34). The HRTEM images revealed that the Pt skin thickness of $\\mathrm{PtPb/Pt}$ nanoplates is between 0.8 and $1.2~\\mathrm{nm}$ . Therefore, herein we focus entirely on surface strain. \n\nThe SAED and HRTEM results revealed a large tensile strain along [001] and a compressive strain along [110] on both the top-Pt and edge-Pt surfaces of the nanoplates. Thus, we calculated $\\Delta E_{\\mathrm{O}}$ on the Pt (110) surface as a function of strain in the [001] and [110] directions. Specifically, the strain applied in [001] direction ranged from $-1\\%$ (compressive) to $9\\%$ (tensile), and the strain applied in [110] direction varied from $1\\%$ to $-9\\%$ . Under each biaxial strain, three types of the most stable oxygen adsorption sites on the (110) surface were examined (Fig. 4A): the face-center cubic (fcc) hollow sites $(^{\\omega}\\mathrm{h}^{\\dag})$ , the bridge sites in [001] direction $(^{\\mathfrak{s q}})$ , and the bridge sites in [110] direction $(^{69}\\mathrm{b2^{\\prime3}})$ . Both “b1” and “b2” sites consist of the low-coordinated surface atoms. We also calculated $\\Delta E_{\\mathrm{O}}$ on the flat (111) surface of Pt. The results of $\\Delta E_{\\mathrm{O}}$ calculations are reported in Fig. 4, B to D. \n\nThe $\\Delta E_{\\mathrm{O}}$ values on the $\\ensuremath{^\\mathrm{{s}}}\\ensuremath{\\mathrm{{h}}}^{\\ensuremath{\\mathfrak{N}}}$ sites were nearly optimal for a wide range of biaxial strains. The adsorbed oxygen atom was metastable when the tensile strain in [001] direction was relatively small or the compressive strain in [110] direction was relatively large. In both cases, the Pt-O binding was much weaker on the $^{\\mathrm{{s}}}\\mathrm{{h}}^{\\prime\\mathrm{{s}}}$ sites than their adjacent $^{\\mathrm{62}}$ sites (Fig. 4, B and D) and the diffusion barrier was $<0.05\\ \\mathrm{eV}$ from an “h” site to a “b2” site. Thus, the “h” sites under such biaxial strains did not contribute meaningfully to the overall ORR. However, under large tensile strain of $7.5\\%$ in [001] direction or a small compressive strain of $1\\%$ in [110] direction, the “h” sites became catalytically active and their $\\Delta E_{\\mathrm{O}}$ values were comparable to those on the “b2” sites. Thus, the $^{\\mathrm{*}}\\mathrm{h}^{\\mathrm{*}}$ sites on the edge-Pt surface of the nanoplates were stable and active for ORR. The “b1” sites were not active for large tensile strains in [001] direction and were not responsible for the ORR performance of the nanoplates (Fig. 4C). On the ${}^{\\mathrm{~sq~}}{}^{\\mathrm{~s~}}$ sites, the Pt-O bond was usually strong and could poison the catalyst. However, the strong Pt-O binding could be weakened by tensile strains in [001] direction (Fig. 4D) and the ${\\mathfrak{s o}}^{\\mathfrak{n}}$ sites became catalytically active under a large tensile strain of $7.5\\%$ in [001] direction. Because $\\Delta E_{\\mathrm{O}}$ values were insensitive to the strain in [110] direction, the “b2” sites were active for ORR at both the top-Pt and edge-Pt surfaces. We attribute the high ORR activity of the PtPb/Pt core/ shell nanoplates to the active $\\mathbf{\\hat{\\Pi}}^{\\left<\\mathcal{\\epsilon}\\right>}$ and ${\\mathfrak{s o}}^{\\mathfrak{s}}$ sites under the appropriate large biaxial strains. It is generally believed that in $\\mathbf{M}/\\mathrm{Pt}$ core/shell catalyst, the compressive strain can weaken the Pt-O binding on Pt (111) surface and increase the ORR activity (34–36), and low-coordinated surface atoms have stronger Pt-O binding, lowering the ORR activity (37, 38). However, our DFT calculations show that the tensile strains on Pt (110) facet can also increase the ORR activity and that the low-coordinated surface atoms $(^{69}\\mathrm{b2^{33}})$ can be activated by large tensile strains. \n\nThe PtPb/Pt core/shell nanoplates reported herein also show high electrocatalytic activity and stability toward anodic fuel cell reactions such as methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR). As shown in figs. S24 to S26 and table S2, the PtPb nanoplates/C exhibit the MOR mass activity of $1.5~\\mathrm{A/mgPt}$ , 2.4 times and 7.9 times higher than those of PtPb nanoparticles and Pt catalysts, respectively, as well as higher stability. For EOR, it displays the specific activity of $2.5\\mathrm{mA}/\\mathrm{cm}^{2}$ and mass activity of $\\mathrm{1.4A/mg}$ Pt, 1.9 and 2.5 times greater than those of PtPb nanoparticles/C, and 10.4 times and 8.8 times higher than those of the commercial $\\mathrm{Pt/C}$ (fig. S24 and table S3), as well as greater stability (figs. S24 to S26). \n\n# REFERENCES AND NOTES \n\n1. M. Winter, R. J. Brodd, Chem. Rev. 104, 4245–4270 (2004). \n2. A. Chen, P. Holt-Hindle, Chem. Rev. 110, 3767–3804 (2010). \n3. M. S. Dresselhaus, I. L. Thomas, Nature 414, 332–337 (2001). \n4. P. Strasser, Science 349, 379–380 (2015). \n5. H. A. Gasteiger, S. S. Kocha, B. Sompalli, F. T. Wagner, Appl. Catal. B 56, 9–35 (2005). \n6. H. A. Gasteiger, N. M. Marković, Science 324, 48–49 (2009). \n7. J. K. Nørskov, T. Bligaard, J. Rossmeisl, C. H. Christensen, Nat. Chem. 1, 37–46 (2009). \n8. S. I. Choi et al., Nano Lett. 13, 3420–3425 (2013). \n9. F. Saleem et al., J. Am. Chem. Soc. 135, 18304–18307 (2013). \n10. X. Xu et al., Angew. Chem. Int. Ed. 53, 12522–12527 (2014). \n11. T. Bian et al., Nano Lett. 15, 7808–7815 (2015). \n12. L. Zhang et al., Science 349, 412–416 (2015). \n13. C. Wang et al., J. Am. Chem. Soc. 133, 14396–14403 (2011). \n14. H. Zhu, S. Zhang, S. Guo, D. Su, S. Sun, J. Am. Chem. Soc. 135, 7130–7133 (2013). \n15. J. Zhang, H. Yang, J. Fang, S. Zou, Nano Lett. 10, 638–644 (2010). \n16. H. Yang, J. Zhang, K. Sun, S. Zou, J. Fang, Angew. Chem. Int. Ed. 49, 6848–6851 (2010). \n17. D. Wang et al., Nat. Mater. 12, 81–87 (2013). \n18. T. Ghosh, M. B. Vukmirovic, F. J. DiSalvo, R. R. Adzic, J. Am. Chem. Soc. 132, 906–907 (2010). \n19. J. Greeley et al., Nat. Chem. 1, 552–556 (2009). \n20. M. F. Francis, W. A. Curtin, Nat. Commun. 6, 6261 (2015). \n21. C. Chen et al., Science 343, 1339–1343 (2014). \n22. X. Q. Huang et al., Science 348, 1230–1234 (2015). \n23. See the supplementary materials on Science Online. \n24. N. M. Marković, R. R. Adžić, B. D. Cahan, E. B. Yeager, J. Electroanal. Chem. 377, 249–259 (1994). \n25. M. D. Maciá, J. M. Campiña, E. Herrero, J. M. Feliu, J. Electroanal. Chem. 564, 141–150 (2004). \n26. X. Huang et al., Nat. Nanotechnol. 6, 28–32 (2011). \n27. X. Xia, J. Zeng, Q. Zhang, C. H. Moran, Y. Xia, J. Phys. Chem. C 116, 21647–21656 (2012). \n28. L. Chen et al., Nano Lett. 14, 7201–7206 (2014). \n29. V. Mazumder, S. Sun, J. Am. Chem. Soc. 131, 4588–4589 (2009). \n30. U.S. Department of Energy, Technical Plan: Fuel Cells (2016); www.energy.gov/sites/prod/files/2016/06/f32/ fcto_myrdd_fuel_cells_0.pdf. \n31. C. Roychowdhury et al., Chem. Mater. 18, 3365–3372 (2006). \n32. J. K. Nørskov et al., J. Phys. Chem. B 108, 17886–17892 (2004). \n33. V. Stamenkovic et al., Angew. Chem. Int. Ed. 45, 2897–2901 (2006). \n34. X. Zhang, G. Lu, J. Phys. Chem. Lett. 5, 292–297 (2014). \n35. M. Mavrikakis, B. Hammer, J. K. Nørskov, Phys. Rev. Lett. 81, 2819–2822 (1998). \n36. P. Strasser et al., Nat. Chem. 2, 454–460 (2010). \n37. L. Li et al., J. Phys. Chem. Lett. 4, 222–226 (2013). \n38. D. F. van der Vliet et al., Nat. Mater. 11, 1051–1058 (2012). \n\n# ACKNOWLEDGMENTS \n\nThis work was financially supported by the National Key Research and Development Program of China (2016YFB0100201), the National Natural Science Foundation of China (21571135 and 51671003), the Ministry of Science and Technology (2016YFA0204100), the start-up funding from Soochow University and Peking University, Young Thousand Talented Program, and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Part of the electron microscopy work was performed at the Center for Functional Nanomaterials, Brookhaven National Laboratory, which is supported by the U.S. Department of Energy (DOE), Office of Basic Energy Science, under contract DE-SC0012704. The work at California State University Northridge was supported by the U.S. Army Research Office via the MURI grant W911NF-11-1-0353. We thank S. Cheng for his help in the simulation of STEM imaging. All data are reported in the main text and supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/354/6318/1410/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S28 \nTables S1 to S3 \nReferences (39–84) \n\n21 July 2016; accepted 2 November 2016 \n10.1126/science.aah6133 \n\n# ELECTROCATALYSIS \n\n# Ultrafine jagged platinum nanowires enable ultrahigh mass activity for the oxygen reduction reaction \n\nMufan Li,1 Zipeng Zhao,2 Tao Cheng,3 Alessandro Fortunelli,3,4 Chih-Yen Chen,2 Rong Yu,5 Qinghua Zhang,6 Lin Gu,6 Boris V. Merinov,3 Zhaoyang Lin,1 Enbo Zhu,2 Ted Yu,3,7 Qingying Jia,8 Jinghua Guo,9 Liang Zhang,9 William A. Goddard III,3\\* Yu Huang, $\\mathbf{2}{\\mathrm{,10*}}$ Xiangfeng Duan1,10\\* \n\nImproving the platinum (Pt) mass activity for the oxygen reduction reaction (ORR) requires optimization of both the specific activity and the electrochemically active surface area (ECSA). We found that solution-synthesized Pt/NiO core/shell nanowires can be converted into PtNi alloy nanowires through a thermal annealing process and then transformed into jagged Pt nanowires via electrochemical dealloying. The jagged nanowires exhibit an ECSA of 118 square meters per gram of Pt and a specific activity of 11.5 milliamperes per square centimeter for ORR (at 0.9 volts versus reversible hydrogen electrode), yielding a mass activity of 13.6 amperes per milligram of Pt, nearly double previously reported best values. Reactive molecular dynamics simulations suggest that highly stressed, undercoordinated rhombus-rich surface configurations of the jagged nanowires enhance ORR activity versus more relaxed surfaces. \n\nP latinum $\\left(\\mathrm{Pt}\\right)$ represents the essential element for catalyzing the oxygen reduction reaction (ORR) (1–3). However, the high cost of Pt is the primary limiting factor preventing the widespread adoption of fuel cells that critically depend on ORR (4, 5). Therefore, higher Pt mass activity—the catalytic activity per given mass of Pt—must be achieved to reduce the required platinum usage. The Pt mass activity is determined by the specific activity (normalized by surface area) and the electrochemically active surface area (ECSA, normalized by mass). The specific activity can be optimized by tuning the chemical environment, including chemical composition (6–9), exposed catalytic surface (1, 10–12), and Pt coordination environment (13–16). To date, the highest specific activities have generally been achieved on single-crystal surfaces or well-defined nanoparticles (NPs) with specifically engineered facet structure and alloy compositions. For example, the $\\mathrm{Pt_{3}N i}$ (111) singlecrystal facet $(I)$ and $\\mathrm{Pt_{3}N i}$ octahedral NPs have been shown to exhibit ORR-favorable surface structure for greatly enhanced activity (17–19), but such alloys typically suffer from insufficient stability because of electrochemical leaching of Ni during electrochemical cycling, as well as decreased ECSA because of agglomeration of the NPs. Introduction of Mo surface dopants can mitigate such leaching processes and help maintain the ORR-favorable $\\mathrm{Pt_{3}N i}$ (111) surface for enhanced activity and stability (19). On the other hand, ECSA may be improved by tailoring the geometrical factors through the creation of ultrafine nanostructures (20, 21) or core/shell nanostructures with an ultrathin Pt skin (22–24) that exposes most Pt atoms on the surface. Although high surface areas have been achieved on these structures, the reported ECSA values for these optimized structures are typically limited to ${\\sim}70~\\mathrm{m^{2}/g_{\\mathrm{pt}}}$ . \n\nTo boost Pt mass activity and Pt utilization efficiency, an ideal catalyst should have an ORRfavorable chemical environment for high specific activity, optimized geometric factors for high ECSA (20–24), and a mechanism to maintain these high values for long periods of operation. We report the preparation of ultrafine jagged Pt nanowires (JPtNWs) with rich ORR-favorable rhombic configurations that lead to a specific activity of $\\mathrm{11.5mA/cm^{2}}$ [at $0.9{\\mathrm{~V~}}$ versus RHE (reversible hydrogen electrode)] and an ECSA of 118 $\\mathrm{m^{2}/g_{P t}}$ Together, these J-PtNWs deliver a mass activity of $13.6\\mathrm{A}/\\mathrm{mg_{Pt}}$ (at $0.9{\\mathrm{V}}$ versus RHE), which is $\\sim50$ times that of the state-of-the-art commercial $\\mathrm{Pt/C}$ catalyst and nearly double the highest previously reported mass activity values of $6.98\\mathrm{A}/\\mathrm{mg}_{\\mathrm{Pt}}(I9)$ and $5.7\\mathrm{A/mg_{Pt}}(23).$ . We prepared Pt/NiO core/shell nanowires by reducing platinum (II) acetylacetonate $\\mathrm{[Pt(acac)_{2}]}$ and nickel(II) acetylacetonate $\\mathrm{[Ni(acac)_{2}]}$ in a mixture solvent of 1-octadecene and oleylamine (25). Transmission electron microscopy (TEM) showed that the as-synthesized nanowires exhibit an apparent core/shell structure with a contrast of darker core and lighter shell. The nanowires have a typical overall diameter of $\\sim5\\mathrm{nm}$ or less, and a length of \\~250 to ${300}\\mathrm{nm}$ (Fig. 1A and fig. S1A). High-resolution TEM (HRTEM) confirmed the core/shell structure with a typical core diameter of $2.0\\pm0.2\\:\\mathrm{nm}$ (Fig. 1D). The shell shows wellresolved lattice fringes with a spacing of $0.24\\mathrm{nm}$ , \n\nBiaxially strained PtPb/Pt core/shell nanoplate boosts oxygen \nreduction catalysis \nLingzheng Bu, Nan Zhang, Shaojun Guo, Xu Zhang, Jing Li, Jianlin \nYao, Tao Wu, Gang Lu, Jing-Yuan Ma, Dong Su and Xiaoqing \nHuang (December 15, 2016) \nScience 354 (6318), 1410-1414. [doi: 10.1126/science.aah6133] \n\nEditor's Summary \n\n# An activity lift for platinum \n\nPlatinum is an excellent but expensive catalyst for the oxygen reduction reaction (ORR), which is critical for fuel cells. Alloying platinum with other metals can create shells of platinum on cores of less expensive metals, which increases its surface exposure, and compressive strain in the layer can also boost its activity (see the Perspective by Stephens et al.). Bu et al. produced nanoplates−−platinum-lead cores covered with platinum shells −−that were in tensile strain. These nanoplates had high and stable ORR activity, which theory suggests arises from the strain optimizing the platinum-oxygen bond strength. Li et al. optimized both the amount of surface-exposed platinum and the specific activity. They made nanowires with a nickel oxide core and a platinum shell, annealed them to the metal alloy, and then leached out the nickel to form a rough surface. The mass activity was about double the best reported values from previous studies. \n\nScience, this issue p. 1410, p. 1403; see also p. 1378 \n\nThis copy is for your personal, non-commercial use only. \n\n# Article Tools \n\nVisit the online version of this article to access the personalization and article tools: http://science.sciencemag.org/content/354/6318/1410 \n\n# Permissions \n\nObtain information about reproducing this article: http://www.sciencemag.org/about/permissions.dtl " + }, + { + "id": "10.1002_aelm.201600255", + "DOI": "10.1002/aelm.201600255", + "DOI Link": "http://dx.doi.org/10.1002/aelm.201600255", + "Relative Dir Path": "mds/10.1002_aelm.201600255", + "Article Title": "Effect of Synthesis on Quality, Electronic Properties and Environmental Stability of Individual Monolayer Ti3C2 MXene Flakes", + "Authors": "Lipatov, A; Alhabeb, M; Lukatskaya, MR; Boson, A; Gogotsi, Y; Sinitskii, A", + "Source Title": "ADVANCED ELECTRONIC MATERIALS", + "Abstract": "2D transition metal carbide Ti3C2Tx (T stands for surface termination), the most widely studied MXene, has shown outstanding electrochemical properties and promise for a number of bulk applications. However, electronic properties of individual MXene flakes, which are important for understanding the potential of these materials, remain largely unexplored. Herein, a modified synthetic method is reported for producing high-quality monolayer Ti(3)C(2)Tx flakes. Field-effect transistors (FETs) based on monolayer Ti(3)C(2)Tx flakes are fabricated and their electronic properties are measured. Individual Ti(3)C(2)Tx flakes exhibit a high conductivity of 4600 +/- 1100 S cm(-1) and field-effect electron mobility of 2.6 +/- 0.7 cm(2) V-1 s(-1). The resistivity of multilayer Ti(3)C(2)Tx films is only one order of magnitude higher than the resistivity of individual flakes, which indicates a surprisingly good electron transport through the surface terminations of different flakes, unlike in many other 2D materials. Finally, the fabricated FETs are used to investigate the environmental stability and kinetics of oxidation of Ti(3)C(2)Tx flakes in humid air. The high-quality Ti(3)C(2)Tx flakes are reasonably stable and remain highly conductive even after their exposure to air for more than 24 h. It is demonstrated that after the initial exponential decay the conductivity of Ti(3)C(2)Tx flakes linearly decreases with time, which is consistent with their edge oxidation.", + "Times Cited, WoS Core": 1314, + "Times Cited, All Databases": 1363, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000392939300004", + "Markdown": "# Effect of Synthesis on Quality, Electronic Properties and Environmental Stability of Individual Monolayer Ti3C2 MXene Flakes \n\nAlexey Lipatov, Mohamed Alhabeb, Maria R. Lukatskaya, Alex Boson, Yury Gogotsi,\\* and Alexander Sinitskii\\* \n\n2D transition metal carbide $\\bar{\\Gamma}\\dot{\\mathsf{I}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\mathsf{X}}$ (T stands for surface termination), the most widely studied MXene, has shown outstanding electrochemical properties and promise for a number of bulk applications. However, electronic properties of individual MXene flakes, which are important for understanding the potential of these materials, remain largely unexplored. Herein, a modified synthetic method is reported for producing high-quality monolayer $\\bar{\\Gamma}\\dot{\\mathsf{I}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\mathsf{X}}$ flakes. Field-effect transistors (FETs) based on monolayer $\\bar{\\Gamma}\\dot{\\mathsf{i}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\times}$ flakes are fabricated and their electronic properties are measured. Individual $\\bar{\\Gamma}\\dot{\\mathsf{i}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\mathsf{x}}$ flakes exhibit a high conductivity of $4600\\pm1100\\leq\\mathrm{cm}^{-1}$ and field-effect electron mobility of $\\textstyle2.6\\pm0.7\\ c m^{2}\\bigvee^{-1}\\thinspace s^{-1}$ . The resistivity of multilayer $\\bar{\\Gamma}\\dot{\\mathsf{i}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\times}$ films is only one order of magnitude higher than the resistivity of individual flakes, which indicates a surprisingly good electron transport through the surface terminations of different flakes, unlike in many other 2D materials. Finally, the fabricated FETs are used to investigate the environmental stability and kinetics of oxidation of $\\bar{\\Gamma}\\dot{\\mathsf{i}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\mathsf{x}}$ flakes in humid air. The high-quality $\\bar{\\Gamma}\\dot{\\mathsf{I}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\mathsf{X}}$ flakes are reasonably stable and remain highly conductive even after their exposure to air for more than $24\\ h$ . It is demonstrated that after the initial exponential decay the conductivity of $\\bar{\\Gamma}\\dot{\\mathsf{i}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{\\mathsf{x}}$ flakes linearly decreases with time, which is consistent with their edge oxidation. \n\nmetal, X is carbon and/or nitrogen, and T is a surface termination.[1] MXenes are produced from layered ternary metal carbides/nitrides, called MAX phases, by chemical extraction of interleaving layers of an “A” element (group IIIA and IVA elements, e.g., Al). Fluoride-containing acidic solutions, such as HF,[1,2] $\\mathrm{NH}_{4}\\mathrm{HF}_{2}$ ,[3] or LiF-HCl,[4] are used for the A-element (typically, Al) extraction, which results in mixed oxygen- and fluorine-containing surface terminations. It was found that MXenes’ surface chemistry,[5] conductivity,[3] capacitance,[4,6,7] and other properties are significantly affected by the synthesis method. For example, HF etching results in predominantly fluoride-containing functional groups, whereas LiF−HCl treatment yields a material with mostly oxygencontaining surface groups.[8,9] \n\nMXenes are a large family of 2D carbides and nitrides with a general formula $\\mathrm{{M}_{n+1}\\mathrm{{X}_{n}\\mathrm{{T}_{x},}}}$ where M stands for a transition \n\n# 1. Introduction \n\nMXenes have demonstrated promise for a variety of applications and in particular for the energy storage in Li-ion,[1] Li-S,[10] Na-ion batteries,[11] and supercapacitors.[4,6] Yet, the applications of this new family of the 2D materials in electronic devices, such as transistors and sensors, remain underdeveloped.[1,12–14] One of the reasons for this is the lack of experimental data on electronic properties of single- and multi-layer MXenes. Electronic properties of the most widely studied MXene, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}},$ were measured for bulk,[4,15] thin film,[3] and individual multilayer particles,[16] and—only recently—individual flakes[17] (see Table S1 in the Supporting Information for a comparison). However, studies of other 2D materials, such as graphene,[18] phosphorene,[19] transition metal chalcogenides,[20] etc., have demonstrated the importance of characterizing electronic transport properties of individual monolayers and few-layer flakes. Furthermore, electronic properties of the 2D flakes strongly depend on the materials fabrication approaches and synthesis conditions. With little information that is currently available on the electrical properties of individual flakes of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , there is a limited understanding of how these properties depend on the approaches used for MXenes’ synthesis. Further electrical characterization of individual $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes should establish the importance of the optimization of synthetic conditions for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}},$ provide insights into its intrinsic properties, and reveal its potential for relevant applications. \n\nTable 1.  Summary of the experimental parameters for the original and modified etching/delamination procedures. \n\n\n
Mass (TiAIC2) [g]Mass (LiF) [g]Volume (6 m HCl) [mL]Molar ratio TiAIC2:LiF:HCIEtching time [h]Centrifugation speed/ timeSonication
Original procedure, Route 110.67101.0:5.0:11.7243500 rpm/l hYes,1 h
Modified procedure, Route 21201.0:7.5:23.4243500 rpm/l hNo
\n\nFor electronic property studies, controlled synthesis and delamination of MXenes into large monolayer flakes of high quality is required. High-yield delamination strategies depend on the synthesis method. MXenes produced by HF etching require an additional step of intercalation with organic molecules, such as $\\mathrm{DMSO}^{[21]}$ or amines,[22,23] whereas LiF−HCl etched MXene (also known as a “MXene clay”) can be delaminated right away by sonication in water.[4] \n\nThe purpose of this study is manifold. First, we report on the transport property measurements of monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes. Second, we show that electronic properties and environmental stability of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes strongly depend on their synthesis conditions. Particular attention has been paid to the optimization of LiF−HCl etching of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ to produce large high-quality MXene flakes with low concentration of defects. Finally, we demonstrate that electrical measurements can be used to study the kinetics of environmental degradation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes, which is an important issue for some of MXenes’ potential applications. \n\n# 2. Results and Discussion \n\nTwo types of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes were produced for this study. Following the original procedure (Route 1) reported by Ghidiu et al.,[4] $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ was synthesized by immersing $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ powder into a LiF–HCl solution maintaining the molar ratio of LiF to MAX equal to 5:1 (see Experimental Section for details). Previous studies have shown that this method yields primarily monolayer flakes.[4] In the modified procedure (Route 2), the molar ratio of LiF to MAX was increased to 7.5:1 to provide excess of $\\mathrm{Li^{+}}$ ions for intercalation and the HCl to LiF ratio was doubled to facilitate etching of aluminum. Other aspects of the procedure remained identical, except no sonication was needed to delaminate $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ particles that were produced using Route 2 (see Table 1). Key differences between Routes 1 and 2 are summarized in Figure 1A. \n\nFirst, we evaluated the quality of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes produced by different methods by electron microscopy techniques (Figure 1B–E). Both solutions were drop-casted on silicon substrates and characterized by scanning electron microscopy (SEM). The majority of the flakes produced by Route 1 are $200{-}500~\\mathrm{nm}$ in diameter (Figure 1B), and despite their small size some of the flakes are not completely exfoliated. In contrast, Route 2 MXene flakes are substantially larger, ranging from 4 to $15~{\\upmu\\mathrm{m}}$ in size (Figure 1D); they look uniform, have clean surfaces and the same brightness in the image, suggesting that they likely have the same thickness. Further characterization of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes produced by different methods was performed by transmission electron microscopy (TEM). Images of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes prepared using Routes 1 and 2 are shown in Figure 1C and Figure 1E, respectively. Low magnification images reveal that synthetic conditions significantly affect shape, size, and morphology of the flakes. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes produced by Route 1 are smaller and have uneven edges decorated with tiny dark particles (Figure 1C), which we attribute to titanium dioxide, based on the results of prior studies.[24] In high resolution TEM images, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes produced by Route  1 reveal numerous pin holes (Figure 1C). On the other hand, flakes produced using Route 2 are larger, have well-defined and clean edges and are visually hole-free (Figure 1E). Crystallographic shape of the Route 2 MXene flakes in TEM images shows that MAX phase crystals can be delaminated without breaking the sheets. High-resolution (HR) TEM images that are presented in Figure 1C,E demonstrate hexagonal arrangement of atoms, showing that the crystal structures of both flakes are identical, which was further confirmed by selected area electron diffraction (SAED) patterns. From this side-by-side comparison, it is clear that the modified synthesis procedure (Route 2) yields $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes of visibly higher quality and larger size compared to the flakes produced using Route 1. We attribute this improvement to the change in the composition of the etching solution, which facilitated both etching of aluminum and intercalation of lithium. As a result, multilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes can be delaminated to monolayer flakes by a manual shake, with no need for sonication that shreds flakes into smaller pieces. \n\nThe mechanical properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXenes produced by Routes 1 and 2 are quite different. Once MXene material is synthesized by either method, it is filtered on a polyvinylidene difluoride (PVDF) membrane, forming a film (a “MXene paper”), which is then dried in vacuum. Optical photographs of the filtrated films of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXenes produced by both Routes 1 and 2 are shown in Figure 2A. The MXene paper prepared from the Route 1 $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ can be easily ground to produce a fine black powder, see Figure 2A. However, more efforts are necessary to grind the filtrated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ film prepared by Route 2. Even shredding and more extensive grinding result in the material that consists of coarse shiny flakes, see Figure 2A. This is consistent with the results of SEM and TEM that demonstrate better exfoliation and larger flake size for the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene material produced by Route 2, as large thin flakes are expected to stack better and form more mechanically stable structures. \n\nDifferent stacking scenarios for the MXene flakes produced by two methods are manifested in the results of powder X-ray diffraction (XRD) measurements. Figure 2B shows that the XRD spectrum of the Route $2\\ \\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes exhibits only a series of 00l reflections, indicating a layered structure of stacked flakes with an interplanar distance of $1.242\\ \\mathrm{nm}$ . In contrast, only 001 reflection is seen in the XRD pattern of the Route 1 $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes (Figure 2B), indicating that they form less ordered stacks compared to the flakes produced by Route 2. \n\n![](images/fa779719dff4a9a6bbce8f6f4edad9a04912d916fa5340e8f19cae53ac61c69e.jpg) \nFigure 1.  Synthesis and electron microscopy characterization of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ flakes produced by different routes. A) Summary of Routes 1 and 2 and sche matic structures of $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ and $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ . B) SEM and C) TEM images of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ flakes produced using Route 1. D) SEM and E) TEM images of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ flakes synthesized using Route 2. Small panels in (C) and (E) show HR TEM images and SAED patterns of monolayer 2D crystals of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ . \n\nAlso, this XRD pattern shows some peaks of the original MAX phase, which means that the transformation of MAX phase to MXene by Route 1 was not complete and some remaining incompletely exfoliated MAX particles are still present in the sample. \n\nThe thickness and shapes of the flakes produced by both methods were investigated by atomic force microscopy (AFM), see Figure 2C–G. The comparison of AFM images in Figure 2C and D presented at the same magnification shows that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes synthesized by Route 2 are significantly larger compared to the material produced by Route 1. The AFM height profile measured along the blue dashed line in Figure 2D shows that all $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes have the same height of $\\approx2.7\\ \\mathrm{nm}$ (Figure 2F) and are identified as monolayers, as can be seen from Figure 2G that shows a folded $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake produced by Route 2. The AFM height profile in the inset shows that the height of the folded region relative to the rest of the flake is $\\approx1.5~\\mathrm{nm}$ , which corresponds to a single layer of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ (according to DFT calculations and TEM studies, the thickness of an individual MXene flake is $0.98\\ \\mathrm{nm}^{[4,25]}$ ). However, the AFM height of the flake relative to the $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate is $2.7\\ \\mathrm{nm}$ , as in case of Figure 2D,F. The increased height is likely due to the presence of surface adsorbates, such as water molecules, that are trapped under the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake; similar observations have been previously reported for other 2D materials as well.[26–29] In contrast, the AFM height profiles measured along the dashed lines in Figure 2C show that the flakes produced by Route 1 have different thicknesses (Figure 2E). This observation further supports incomplete exfoliation of MAX phase via Route 1, which is consistent with the results obtained by other materials characterization methods. \n\nThe comparison of XPS spectra in the Ti 2p region for MXenes produced by Routes 1 and 2 is presented in Figure 2H. The fitting and analysis of the spectra were performed as described in previous works.[5,30,31] While the signals that are marked as $\\mathrm{C}{\\cdot}\\mathrm{Ti}{\\cdot}\\mathrm{T_{x}}~2\\mathrm{p}_{3/2}$ and C-Ti-Tx $2\\mathrm{p}_{1/2}[30]$ and correspond to Ti interactions with carbons and terminal atoms in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ look similar in both spectra, there is a visible increase in the signal intensities at ${\\approx}459\\$ and ${\\approx}465~\\mathrm{eV}$ (these peaks are marked as $\\mathrm{TiO}_{2}\\ 2\\mathrm{p}_{3/2}$ and $\\mathrm{TiO}_{2}$ $2\\mathrm{p}_{1/2}$ , respectively),[31] which is another indication of oxidation of MXenes produced via Route 1. \n\nTo study electronic properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes, we fabricated field-effect transistors (FETs) with individual MXene flakes as conductive channels. First, the diluted colloidal solution of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes with concentration of about $0.01~\\mathrm{mg~mL^{-1}}$ produced by Route 2 was drop-casted onto a $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate. \n\n![](images/a7447efa56e2d9458c0b71af27cdad63e8915508037a2aee9c20b0f38dc9a748.jpg) \nFigure 2.  Comparison of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ materials produced by different routes. A) Optical photographs of MXene paper samples produced by different routes before and after grinding; see the text for details. B) XRD pattern collected fo r the owde f $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ aterials shown in panel A. XRD spectrum of the original $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ phase is shown refe C,D) AFM i of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ flakes dep $\\mathsf{S i}/\\mathsf{S i O}_{2}$ Route 1 and D) Route 2. E) AFM height profiles measured along the dashed li of th ofiles s of the dashed lines in (C). F) AFM height profile measu the da folded $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ flak $\\mathsf{S i}/\\mathsf{S i O}_{2}$ The inset shows the height profile measured along the red dashed lin $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ of Ti with carbon and terminal atoms produce three signals (blu $2{\\mathsf{p}}_{3/2}$ C-Ti- $\\mathsf{T}_{\\mathsf{x}}$ $2{\\mathsf{p}}_{1/2}$ . These signals correspond to different oxidation states of Ti. Titani $\\mathsf{T i O}_{2}$ produ s distinctive signals ${\\approx}459$ ${\\approx}465~\\mathrm{eV}$ ed as $\\mathsf{T i O}_{2}2\\mathsf{p}_{3/2}$ and $\\mathsf{T i O}_{2}2\\mathsf{p}_{1/2})$ . \n\nSimilar to graphene and $\\mathrm{MoS}_{2}$ , monolayer flakes of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ have a good optical contrast on a $300\\ \\mathrm{nm}\\ \\mathrm{SiO}_{2}$ on Si (see panel B in Figure S1 in the Supporting Information), so optical microscopy was used to establish flakes’ position on the substrate. The largest flakes were up to $15~{\\upmu\\mathrm{m}}$ in size and uniform in color, which made them suitable for device fabrication. After the flakes were selected, e-beam lithography was used for device patterning. Metal contacts composed of $3\\ \\mathrm{nm}$ of $\\mathrm{Cr}$ and $20~\\mathrm{nm}$ of Au were deposited via e-beam evaporation. Special precautions were taken to avoid prolonged exposure of \n\n![](images/ab2e3b34522653b15cbab052bae51a3633f96105abeff2594eb10876b351c3ae.jpg) \nFigure 3.  Device fabrication and electronic properties of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ flakes synthesized using Route 2. A) Schematic of a $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\mathsf{X}}$ -based FET; see the text for details. B) SEM images of a $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ flake before and after device fabrication. C) $\\boldsymbol{I}_{\\mathrm{DS}}-\\boldsymbol{V}_{\\mathrm{DS}}$ curves for the device shown in (B) at different gate voltages. D) $I_{\\mathsf{D}\\mathsf{S}}-V_{\\mathsf{G}}$ dependence for the device shown in (B). \n\nMXene flakes to air during device fabrication. The total time of the exposure of the MXene flakes to air was limited to ${\\approx}30$ min from the moment of solution drop-casting to loading devices into a vacuum chamber for electrical measurements. Figure 3A shows the schematic illustration of the final $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ -based FET on $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate where $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake bridges $\\mathrm{Cr/Au}$ source (S) and drain (D) electrodes, and back gate (G) electrode, a conductive highly p-doped Si, is separated from the MXene flake by $300\\mathrm{nm}$ of $\\mathrm{SiO}_{2}$ dielectric. SEM images of a typical $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake before and after device fabrication are shown in Figure 3B, additional SEM images of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ devices are provided in Figure S2 in the Supporting Information. \n\nThe electrical properties of Route $2\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ FETs were investigated for a total of ten devices via the two-terminal method by measuring drain–source current $(I_{\\mathrm{DS}})$ while applying gate voltage $(V_{\\mathrm{G}})$ to the bottom electrode. Samples were kept at room temperature and drain–source voltage $(V_{\\mathrm{DS}})$ was $0.1\\mathrm{V}.$ In order to reduce the effect of surface adsorbates,[32] the measurements were performed in vacuum $(p\\approx2\\times10^{-6}$ Torr) after two days of evacuation. $I_{\\mathrm{DS}}{-}V_{\\mathrm{DS}}$ curves (Figure 3C) exhibit a linear dependence, which indicates Ohmic behavior. Calculated sheet resistivity at $V_{\\mathrm{{G}}}=0$ is $\\uprho=1590\\Omega\\bigstar\\bigstar$ . The results for other devices are summarized in Table S2 in the Supporting Information. The average resistivity for all measured devices is $2310\\pm570\\Omega\\square^{-1}$ , which is comparable to the sheet resistivity of graphene.[33] Since the thickness of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake is about $1\\ \\mathrm{nm}$ ,[4,25] the calculated single-flake resistivity is $2.31\\pm0.57~{\\upmu\\Omega}\\cdot\\mathrm{m}.$ . We also performed resistivity measurements on the bulk $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ clay using van der Paw method, see details in the Supporting Information (Figure S3 and comments therein). $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ film composed of exactly the same material as for monolayer property measurements revealed resistivity of $15.8\\pm1.3~{\\upmu\\Omega}{\\cdot}\\mathrm{m}$ . The difference between bulk and monolayer flake resistivities may be explained by the contribution of the contact resistances at the interfaces between individual MXene flakes, i.e., the resistance perpendicular to the basal plane. The difference between the resistivities of an individual monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake and a film is within one order of magnitude, which is surprisingly small. In graphite, a stack of 2D sheets of graphene, the resistances perpendicular and parallel to the basal plane differs by three orders of magnitude.[34] In the recent study of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ particles,[16] the reported resistance anisotropy was also of about one order of magnitude. Moreover, the ratio strongly depended on the mechanical load (stretching or compressing) perpendicular to the basal plane, and comparable in- and out-of-plane resistances could be achieved when $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ layers were pressed to each other.[16] These data as well as the results of our measurements demonstrate a good inter-flake conductance through the surface functional groups. \n\nApplication of external field via the gate electrode changes the Fermi level of MXene flakes, thus changing $I_{\\mathrm{DS}}$ . As can be seen from Figure 3D, $I_{\\mathrm{DS}}$ increases as $V_{\\mathrm{G}}$ increases, indicating that electrons are major charge carriers. Leakage current is negligible (on the order of $10^{-\\mathrm{{i}}1}$ A), so the electric field effect is intrinsic. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ field-effect electron mobility $(\\upmu_{\\mathrm{FE}})$ was estimated by fitting the $I_{\\mathrm{DS}}/\\mathrm{-}V_{\\mathrm{G}}$ curve with Equation (1):[35] \n\n$$\n\\mu_{\\mathrm{FE}}=\\frac{1}{C_{\\mathrm{G}}}\\times\\frac{d\\Big(\\big<\\int\\rho\\Big)}{d V_{\\mathrm{G}}},\n$$ \n\nwhere $C_{\\mathrm{G}}$ is a capacitance of the $300\\ \\mathrm{nm\\SiO_{2}}$ dielectric layer. The resulting value of $\\upmu_{\\mathrm{FE}}$ for the device shown in Figure 3B is about $4.23\\ \\mathrm{cm}^{2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ . The mobility is consistent across all measured devices with the average value of $2.6\\pm0.7\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ (see Table S2 in the Supporting Information for the summary of the results of electrical measurements). The distribution of the mobility values for MXene devices is rather narrow compared to a number of other solution-processed 2D materials, such as monolayer reduced graphene oxide (rGO) sheets[36] and nanoribbons,[37] suggesting the structural uniformity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes produced by Route 2. However, similarly to rGO mono­ layers, which due to defects and randomly distributed oxygencontaining functionalities have mobilities orders of magnitude lower than in pristine graphene,[36] non-periodic surface terminations (-OH, -F, -O)[8] in MXene flakes may negatively impact their mobilities. Also, $\\mathrm{SiO}_{2}$ surface and contaminations are known to contribute to mobility decrease in graphene due to electron–phonon[38] and Coulomb[35] scatterings. Encapsulation as well as dielectric screening can improve the mobility of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ devices, as shown for other 2D materials.[20,39–42] \n\nAs we pointed out in the discussion of AFM results in Figure 2, monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes on $\\mathrm{Si}/\\mathrm{SiO}_{2}$ show step heights larger their expected thickness of $\\approx1~\\mathrm{{nm}}$ ,[4,25] which is likely due to the presence of surface adsorbates. Water molecules are known to cover $\\mathrm{SiO}_{2}$ thermally grown on Si in ambient conditions by hydrogen bonding to the surface SiOH silanol groups.[43,44] This hydrogen-bonded water cannot be completely desorbed by evacuation at room temperature, but can be removed by annealing at temperatures over $200~^{\\circ}\\mathrm{C}$ in dry environments.[45] In order to study the effect of adsorbed water on the electronic properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ devices, we annealed them at $300^{\\circ}\\mathrm{C}$ in Ar for $30\\mathrm{min}$ . This procedure resulted in the decrease of the AFM heights of the device channels from $\\approx2$ to ${\\approx}1.5~\\mathrm{nm}$ (Figure S4, Supporting Information), which is comparable to the values measured for the relative thicknesses of folded regions of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes (Figure 2G). The decrease in the AFM heights of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ channels after annealing is likely due to the thermal desorption of water. However, the annealing did not have a significant effect on the electronic properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ FETs, which remained qualitatively the same (see Figure S4 in the Supporting Information for details), so in the following experiments we discuss the results for devices prepared at room temperature. \n\nDrop-casting of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ colloidal solution produced by Route 1 onto $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate mostly yielded non-uniform agglomerates of flakes which were not suitable for manufacturing devices with monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ channels (see panel A in Figure S1 in the Supporting Information). Occasionally, small $(<5~\\upmu\\mathrm{m})$ flakes could be spotted. FETs with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes produced by Route 1 were fabricated using the same procedure as for the Route 2 flakes, and representative SEM images of the devices are shown in Figure S5 in the Supporting Information. The devices were not conductive, and we explain this results by a higher oxidation degree of the Route 1 flakes compared to the Route 2 ones (Figure 2H), and their lower environmental stability due to numerous pin-hole defects (Figure $1\\mathrm{C}$ ), which facilitate oxidation of MXene flakes in air. These results, demonstrate the importance of the synthesis procedure for highquality and environmentally stable MXene flakes for electronic applications. \n\nMonolayer MXene flakes cannot sustain prolonged exposure to oxygen in the presence of water[24] or at high temperature.[46] Previous studies showed the formation of titanium dioxide and carbon, with nucleation of titania crystals along the edges of MXene flakes.[46] For instance, when colloidal solution of delaminated MXene in water is exposed to air, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes are completely oxidized within several days. This results in the solution color change from translucent black/brown to cloudy white, with a white precipitate of titania accumulating at the bottom of a vial. In this work, we studied kinetics of the environmental degradation of an individual $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake in situ by measuring the change of FETs’ conductivity in air as a function of time. Device measurements have been previously used to study kinetics of other reactions involving 2D materials, such as diazonium functionalization of graphene.[47] \n\nIn these measurements we monitored the $I_{D S}$ every $10\\mathrm{~s~}$ , while exposing one of the previously discussed $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ devices to air at room temperature and relative humidity of $\\approx50\\%$ . Figure 4A shows the resulting time-dependence of $I_{\\mathrm{DS}}$ . Black points at time $(t)<0$ correspond to the readings in vacuum before the device was exposed to air. The readings were stable in vacuum but once the lid of a vacuum chamber was opened, the drain–source current started to decrease (see red data points in Figure 4A). The data were collected for $2.5\\times10^{5}$ s $(\\approx70\\ \\mathrm{h})$ during which the $\\boldsymbol{I_{\\mathrm{DS}}}$ decreased from 20.5 to $16.7\\upmu\\mathrm{A}$ . The $I_{\\mathrm{DS}}$ first decayed strongly in a non-linear manner within the initial ${\\approx}2\\times10^{4}~\\mathrm{s}$ , however, later, $I_{\\mathrm{DS}}$ exhibited a linear decay over time. It should also be noted that linear dependence of $I_{\\mathrm{DS}}{-}V_{\\mathrm{DS}}$ curves was preserved after the device was kept in air for $70\\mathrm{~h~}$ , which indicates the degradation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake rather than contacts between the flake and metal electrodes. \n\nThe observed decrease in the conductivity of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake represents interplay of several different effects. First of all, we consider molecular adsorption on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes (Figure 4B). It was previously shown that surface adsorbates may cause doping of 2D materials, such as graphene.[32,48,49] In case of air, particularly important adsorbates are oxygen and water molecules, both of which have been demonstrated to behave as electron acceptors when adsorbed on graphene resulting in p-doping.[48,50] Since we demonstrate that electrons are the major charge carriers in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}},$ its p-doping by surface adsorbates should result in a decrease in conductivity, which is consistent with our observations (Figure 4). Also, this conductivity change should be reversible if the molecules are desorbed from the surface of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake in vacuum. In order to estimate the contribution of the molecular adsorbates to the overall decrease in conductivity of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ FET we measured the recovery of the $\\boldsymbol{I_{\\mathrm{DS}}}$ in vacuum after the prolonged exposure of the device to air; see the inset in Figure 4A. After evacuation of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ FET, the $I_{\\mathrm{DS}}$ first increases but then saturates after $\\approx15$ min, recovering only ${\\approx}0.8\\%$ $({\\approx}0.17\\upmu\\mathrm{A})$ of original $I_{\\mathrm{DS}}$ value (compared to the overall $18.5\\%$ loss $(3.79\\upmu\\mathrm{A})$ of $I_{\\mathrm{DS}}$ during $70\\mathrm{{h}}$ of the device exposure to air). \n\n![](images/85bc0b78d86d00ae4b5de456bff8f65b069242b7791d5bb434af3c3444221b5f.jpg) \nFigure 4.  Environmental degradation of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ in air. A) Representative $\\boldsymbol{I_{\\mathrm{DS}}}$ –time dependence for a $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ FET exposed to air. The device was first kept under vacuum (black points) and then in air (red points). Fragment of the $\\boldsymbol{I}_{\\mathrm{DS}}$ –time dependence for the same device, which shows partial restoration of the conductivity of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ FET cuated. B,C) Schematic illustrations of phenomena that contribute to the decrease in the conductivity of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ devices in air: B) reversible ecular adso and C) irreversible edge oxidation; ents the width of the conductive channel of the device that decreased due to the ida ) Fit of the IDS time dependence shown in (A). Red data oints show the experimental data and the black curve shows the fit. Both lin (blue line) contributi o the final fit (black line) are shown. E) AFM images of a fragment of the channel of a $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\mathrm{x}}$ FET before and after the prolonged exposure to air, and height profiles measured along blue and red dashed lines in AFM images. \n\nThese results suggest that the major contribution to conductivity decrease in air is irreversible and thus likely related to the oxidation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes in air (Figure 4C). Oxidation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ resulting in the formation of titanium dioxide has been discussed in previous studies[24] and is also illustrated by Figure 1C and 2H. It is well known that oxidation of a 3D material often results in the formation of a passivating layer of a product that slows the reaction as it grows in thickness. The $I_{\\mathrm{DS}}$ –time dependence that illustrates the kinetics of oxidation of a 2D MXene looks noticeably different (Figure 4A). In the first ${\\approx}2\\times10^{4}$ s, the $I_{\\mathrm{DS}}$ –time dependence shows an exponential decay and the oxidation rate indeed decreases with time, as expected. However, after the initial ${\\approx}2\\times10^{4}~\\mathrm{s}$ of exposure to air the oxidation rate does not decrease any further—it becomes constant and the $I_{\\mathrm{DS}}$ –time dependence enters the linear regime (Figure 4A). \n\nThese observations can be rationalized as follows. In the beginning of the experiment the edges of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake are fully exposed to air and the oxidation proceeds rather quickly. Titanium dioxide, formed at the edges of the flake, slows the reaction at first. However, further kinetics is different from the oxidation kinetic of a 3D material, where the oxidation product passivates the entire surface of a material and the reaction rate decreases as oxide layer become thicker. In case of the 2D edge oxidation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}.$ , the titanium oxide that forms at the sides of a flake does not fully passivate the material from the environment (Figure 4C). Furthermore, once the edges of the flakes are oxidized and the reaction is slowed down to a certain extent, then the oxidation should proceed with a nearly constant rate, because the oxidizing species diffuse not through the oxide layer, like in 3D case, but directly at the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}/\\mathrm{TiO}_{2}$ interface (Figure 4C). We have recorded $I_{\\mathrm{DS}}$ –time dependencies for several $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ FETs exposed to air, and in all cases after the initial exponential decay we observed a linear decrease in conductivity with time, which is consistent with the described model. We believe that similar kinetics could be observed for reactions involving other 2D materials as well, particularly when the reactions primarily happen at the edges rather than on the basal plane. \n\nTo further illustrate the transition from exponential decay to linear regime, we fitted the experimental data using the following equation: \n\n$$\nI_{\\mathrm{DS}}(t)=A-B\\cdot t+C\\cdot\\exp(-\\gamma\\cdot t),\n$$ \n\nwhere $A,B,C,$ and $\\gamma$ are the fitting parameters. The fit worked very well in the entire time range as shown in the top panel in Figure 4D. The values extracted by fitting the experimental data with Equation (2) are $A=19.599(2)$ A, $B=1.068(3)\\times10^{-5}\\mathrm{~A~s~}$ $\\mathbf{s}^{-1}$ , $C=0.810(3)$ A, and $\\gamma=1.16(1){\\times}10^{-4}~\\mathrm{s}^{-1}$ . The middle and bottom panels in Figure 4D demonstrate individual contributions of linear and exponential parts of Equation (2). They further demonstrate that the exponential term initially dominates, but then the contribution of the linear term becomes more important. \n\nEdges of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes and other structural defects (Ti vacancies and pin holes) are the most vulnerable sites for oxidation. For the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes with high structural quality (prepared by Route 2), it is reasonable to assume that the edge oxidation will proceed faster than the oxidation at the basal plane and thus will make the largest contribution to the overall conductivity decrease. This scenario is illustrated by Figure 4C that shows that the edge oxidation decreases the width of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ FET channel $(\\boldsymbol{w})$ , which results in the conductivity decrease. To verify this assumption, we compared AFM images of as-prepared $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ FETs with AFM images of the same device after prolonged exposure to air. Figure 4E shows that the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ channel of as-prepared device has a uniform thickness of $\\approx2~\\mathrm{nm}$ . After exposure to air the flake becomes visibly thicker at the edges, but the thickness does not change at the basal plane. This observation is consistent with the assumption that the environmental degradation primarily happens at the exposed edges of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flake, while the basal plane is reasonably inert to oxidation. The height profiles measured along the same portion of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ channel before and after exposure to air for $70\\mathrm{{h}}$ show that the flake thickness increases at the edges by $\\approx1~\\mathrm{nm}$ (see arrows in Figure 4E). The AFM data confirm the conclusion made from the results of electrical measurements that environmental degradation of high-quality $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes is reasonably slow. Since the oxidized edges are less conductive than the interiors of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes, they could be visualized by scanning electron microscopy. SEM images of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes that were deposited on $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrates and exposed to air for several days show that the edges of flakes are visibly brighter than their interiors (Figure S6, Supporting Information)—such contrast was not observed for the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes that were imaged shortly after their deposition on $\\mathrm{Si}/$ $\\mathrm{SiO}_{2}$ substrates, see Figure 1B,D. \n\nThe sensitivity of the conductivity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ to molecular adsorbates and some reversibility of the process suggest the potential of this material and other MXenes for sensor applications. Previously, different kinds of sensors were demonstrated for many other 2D materials, such as graphene, graphene oxide, and transition metal chalcogenides; which benefit from high surface-to-volume ratios and tunable electronic properties.[51,52] Very rich surface chemistry of MXenes with about 20 compositions of various transition metals and their combinations available to date[53,54] makes MXene FETs promising for sensing applications as well. Of course, the environmental degradation could be a serious issue for such sensors. However, considering that the oxidation of high-quality $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes primarily happens at the edges, this issue could be mitigated by passivating edges with inert oxide materials using, for example, a technique like atomic layer deposition, or encapsulating them with impermeable 2D materials, such as hexagonal boron nitride (h-BN). \n\n# 3. Conclusions \n\nIn summary, we demonstrate an improved method of selective etching of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ , a MAX phase, which yields large high-quality monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene flakes with well-defined and clean edges and visually defect-free surfaces. We fabricated FETs based on monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes, which exhibited a field-effect electron mobility of $2.6\\pm0.7\\ \\mathrm{cm}^{2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ and a low resistivity of $2.31\\pm0.57{\\upmu\\Omega}\\cdot\\mathrm{m}$ ( $4600\\pm1100\\mathrm{~S~cm^{-1}})$ ). The single flake resistivity is only one order of magnitude higher than the resistivity of bulk $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ and thin films made from $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes, suggesting that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes form low-resistance electric contacts with each other, which is a practically important result for bulk applications of this material. Finally, we used fabricated FETs to investigate the environmental stability of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes in humid air. The high-quality $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes are reasonably stable and remain highly conductive even after their exposure to air for $70\\mathrm{{h}}$ . After the initial exponential decay the drain–source current linearly decreases with time. We explain these observations by the edge oxidation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes and support this explanation by AFM measurements. We believe that similar kinetics could be observed for reactions involving other 2D materials as well, in cases when the reactions primarily happen at the edges. Many of such kinetics studies of other conductive 2D materials may potentially be carried out using the electrical measurement scheme that was disclosed in this paper. \n\n# 4. Experimental Section \n\nSynthesis of $\\overline{{T}}\\dot{I}_{3}C_{2}\\overline{{T}}_{x}$ Following the Original[4] and Modified Procedure: MAX phase precursor, $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ , was produced as described elsewhere.[4] Following the procedure reported by Ghidiu et al.,[4] $\\boldsymbol{0.67\\ \\mathrm{g}}$ of LiF was dissolved in $70~\\mathsf{m L}$ of $6\\textrm{\\textmu}\\mathsf{H C l}$ and the solution was allowed to mix thoroughly at room temperature for a few minutes. After that, $\\texttt{1g}$ of $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ was slowly added over the course of $5\\mathrm{\\min}$ to avoid initial overheating due to exothermic nature of the reaction. Then, the temperature was brought to $35^{\\circ}C$ and the reaction allowed to proceed under continuous stirring $(550\\ r p m)$ for $24\\ h$ . The resulting MXene powder was repeatedly washed with DI water until almost neutral pH $(\\geq6)$ . The product was then collected using vacuum-assisted filtration through a PVDF membrane $(0.45~\\upmu\\mathrm{m}$ pore size, Millipore) and dried in a vacuum desiccator at room temperature for $24\\mathrm{~h~}$ . To delaminate $_{0.2\\ \\mathrm{g}}$ of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times},$ the freshly produced powder was bath sonicated in $50~\\mathrm{mL}$ of DI water for $\\textsf{l h}$ under continuous argon (Ar) bubbling to minimize oxidation. Then, the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\mathrm{x}}$ solution was centrifuged at 3500 rpm for $\\textsf{l h}$ and the supernatant, a colloidal solution of MXene, was collected. Previous studies have shown that this solution contains primarily monolayer flakes.[4] In the modified procedure, $\\rceil\\textrm{g}$ of MAX was added to the mixture of $\\texttt{l g}$ of LiF in $20~\\mathsf{m L}$ of $6\\mathrm{~M~HCl}$ . Other aspects of the procedure remained identical except that the delamination of the resulting $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\mathrm{x}}$ powder did not require sonication (Table 1). \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nAlexey Lipatov and Mohamed Alhabeb contributed equally to this work. All the authors have given approval to the final version of the manuscript. This work was supported by the National Science Foundation (NSF) through ECCS-1509874 with a partial support from the Nebraska \n\n# www.MaterialsViews.com \n\nMaterials Research Science and Engineering Center (MRSEC) (grant no. DMR-1420645). Materials synthesis at Drexel University was supported by the Fluid Interface Reactions, Structures and Transport (FIRST) Center, the Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. The authors thank Patrick Urbankowskifor for the XPS characterization of MXene flakes. The authors declare no competing financial interests. \n\nReceived: July 2, 2016 \nRevised: July 26, 2016 \nPublished online: November 2, 2016 \n\n[1]\t M. Naguib, V. N. Mochalin, M. W. Barsoum, Y. Gogotsi, Adv. Mater. 2014, 26, 992, \n[2]\t M.  Naguib, M.  Kurtoglu, V.  Presser, J.  Lu, J. J.  Niu, M.  Heon, L. Hultman, Y. Gogotsi, M. W. Barsoum, Adv. Mater. 2011, 23, 4248. [3]\t J.  Halim, M. R.  Lukatskaya, K. M.  Cook, J.  Lu, C. R.  Smith, L. A.  Naslund, S. J.  May, L.  Hultman, Y.  Gogotsi, P.  Eklund, M. W. Barsoum, Chem. Mater. 2014, 26, 2374. [4]\t M.  Ghidiu, M. R.  Lukatskaya, M. Q.  Zhao, Y.  Gogotsi, M. W. Barsoum, Nature 2014, 516, 78. \n[5]\t J.  Halim, K. M.  Cook, M.  Naguib, P.  Eklund, Y.  Gogotsi, J.  Rosen, M. W. Barsoum, Appl. Surf. Sci. 2015, 362, 406. \n[6]\t M. R. Lukatskaya, O. Mashtalir, C. E. Ren, Y. Dall’Agnese, P. Rozier, P. L.  Taberna, M.  Naguib, P.  Simon, M. W.  Barsoum, Y.  Gogotsi, Science 2013, 341, 1502. [7]\t Y.  Dall’Agnese, M. R.  Lukatskaya, K. M.  Cook, P. L.  Taberna, Y. Gogotsi, P. Simon, Electrochem. Commun. 2014, 48, 118. [8]\t H.-W.  Wang, M.  Naguib, K.  Page, D. J.  Wesolowski, Y.  Gogotsi, Chem. Mater. 2016, 28, 349. \n[9]\t M. A. Hope, A. C. Forse, K. J. Griffith, M. R. Lukatskaya, M. Ghidiu, Y. Gogotsi, C. P. Grey, Phys. Chem. Chem. Phys. 2016, 18, 5099. \n[10]\t X.  Liang, A.  Garsuch, L. F.  Nazar, Angew. Chem. Int. Ed. 2015, 54, 3907. \n[11]\t X. Wang, S. Kajiyama, H. Iinuma, E. Hosono, S. Oro, I. Moriguchi, M. Okubo, A. Yamada, Nat. Commun. 2015, 6, 6544. \n[12]\t J.  Chen, K.  Chen, D.  Tong, Y.  Huang, J.  Zhang, J.  Xue, Q.  Huang, T. Chen, Chem. Commun. 2015, 51, 314. \n[13]\t S.  Lai, J.  Jeon, S. K.  Jang, J.  Xu, Y. J.  Choi, J.-H.  Park, E.  Hwang, S. Lee, Nanoscale 2015, 7, 19390. \n[14]\t C.  Xu, L.  Wang, Z.  Liu, L.  Chen, J.  Guo, N.  Kang, X.-L.  Ma, H.-M. Cheng, W. Ren, Nat. Mater. 2015, 14, 1135. \n[15]\t M.  Naguib, O.  Mashtalir, J.  Carle, V.  Presser, J.  Lu, L.  Hultman, Y. Gogotsi, M. W. Barsoum, ACS Nano 2012, 6, 1322. \n[16]\t T.  Hu, H.  Zhang, J.  Wang, Z.  Li, M.  Hu, J.  Tan, P.  Hou, F.  Li, X. Wang, Sci. Rep. 2015, 5, 16329. \n[17]\t A.  Miranda, J.  Halim, M. W.  Barsoum, A.  Lorke, Appl. Phys. Lett. 2016, 108, 033102. \n[18]\t K. S.  Novoselov, A. K.  Geim, S. V.  Morozov, D.  Jiang, Y.  Zhang, S. V.  Dubonos, I. V.  Grigorieva, A. A.  Firsov, Science 2004, 306, 666. \n[19]\t H. Liu, A. T. Neal, Z. Zhu, Z. Luo, X. Xu, D. Tománek, P. D. Ye, ACS Nano 2014, 8, 4033. \n[20]\t B.  Radisavljevic, A.  Radenovic, J.  Brivio, V.  Giacometti, A.  Kis, Nat. Nanotechnol. 2011, 6, 147. \n[21]\t O. Mashtalir, M. Naguib, V. N. Mochalin, Y. Dall’Agnese, M. Heon, M. W. Barsoum, Y. Gogotsi, Nat. Commun. 2013, 4, 1716. \n[22]\t O.  Mashtalir, M. R.  Lukatskaya, M. Q.  Zhao, M. W.  Barsoum, Y. Gogotsi, Adv. Mater. 2015, 27, 3501. \n[23]\t M.  Naguib, R. R.  Unocic, B. L.  Armstrong, J.  Nanda, Dalton Trans. 2015, 44, 9353. \n[24]\t O.  Mashtalir, K. M.  Cook, V. N.  Mochalin, M.  Crowe, M. W. Barsoum, Y. Gogotsi, J. Mater. Chem. A 2014, 2, 14334. \n[25]\t X.  Wang, X.  Shen, Y.  Gao, Z.  Wang, R.  Yu, L.  Chen, J. Am. Chem. Soc. 2015, 137, 2715. \n[26]\t K. S. Novoselov, D. Jiang, F. Schedin, T. J. Booth, V. V. Khotkevich, S. V.  Morozov, A. K.  Geim, Proc. Natl. Acad. Sci. USA 2005, 102, 10451. \n[27]\t K. Xu, P. Cao, J. R. Heath, Science 2010, 329, 1188. \n[28]\t O. Ochedowski, B. K. Bussmann, M. Schleberger, Sci. Rep. 2014, 4, 6003. \n[29]\t H. Coy Diaz, R. Addou, M. Batzill, Nanoscale 2014, 6, 1071. \n[30]\t C. E.  Ren, M.-Q.  Zhao, T.  Makaryan, J.  Halim, M.  Boota, S.  Kota, B. Anasori, M. W. Barsoum, Y. Gogotsi, ChemElectroChem 2016, 3, 689. \n[31]\t Z. Song, J. Hrbek, R. Osgood, Nano Lett. 2005, 5, 1327. \n[32]\t A.  Sinitskii, A.  Dimiev, D. V.  Kosynkin, J. M.  Tour, ACS Nano 2010, 4, 5405. \n[33]\t A.  Lipatov, B. B.  Wymore, A.  Fursina, T. H.  Vo, A.  Sinitskii, J. G. Redepenning, Chem. Mat. 2015, 27, 157. \n[34]\t H. O.  Pierson, in Handbook of Carbon, Graphite, Diamonds and Fullerenes (Ed: H. O. Pierson), William Andrew Publishing, Oxford, 1993, p. 43. \n[35]\t J. H.  Chen, C.  Jang, S.  Adam, M. S.  Fuhrer, E. D.  Williams, M. Ishigami, Nat. Phys. 2008, 4, 377. \n[36]\t C. Gomez-Navarro, R. T. Weitz, A. M. Bittner, M. Scolari, A. Mews, M. Burghard, K. Kern, Nano Lett. 2007, 7, 3499. \n[37]\t A.  Sinitskii, A. A.  Fursina, D. V.  Kosynkin, A. L.  Higginbotham, D. Natelson, J. M. Tour, Appl. Phys. Lett. 2009, 95, 253108. \n[38]\t D. K. Efetov, P. Kim, Phys. Rev. Lett. 2010, 105, 256805. \n[39]\t C. R.  Dean, A. F.  Young, I.  Meric, C.  Lee, L.  Wang, S.  Sorgenfrei, K.  Watanabe, T.  Taniguchi, P.  Kim, K. L.  Shepard, J.  Hone, Nat. Nano 2010, 5, 722. \n[40]\t F. Chen, J. Xia, D. K. Ferry, N. Tao, Nano Lett. 2009, 9, 2571. \n[41]\t C.  Jang, S.  Adam, J. H.  Chen, E. D.  Williams, S.  Das Sarma, M. S. Fuhrer, Phys. Rev. Lett. 2008, 101, 146805. \n[42]\t A.  Lipatov, P. M.  Wilson, M.  Shekhirev, J. D.  Teeter, R.  Netusil, A. Sinitskii, Nanoscale 2015, 7, 12291. \n[43]\t D. B. Asay, S. H. Kim, J. Phys. Chem. B 2005, 109, 16760. \n[44]\t A.  Verdaguer, C.  Weis, G.  Oncins, G.  Ketteler, H.  Bluhm, M. Salmeron, Langmuir 2007, 23, 9699. \n[45]\t L. T.  Zhuravlev, Colloids Surf. A: Physicochem. Eng. Aspects 2000, 173, 1. \n[46]\t H.  Ghassemi, W.  Harlow, O.  Mashtalir, M.  Beidaghi, M. R. Lukatskaya, Y. Gogotsi, M. L. Taheri, J. Mater. Chem. A 2014, 2, 14339. \n[47]\t A.  Sinitskii, A.  Dimiev, D. A.  Corley, A. A.  Fursina, D. V.  Kosynkin, J. M. Tour, ACS Nano 2010, 4, 1949. \n[48]\t F.  Schedin, A. K.  Geim, S. V.  Morozov, E. W.  Hill, P.  Blake, M. I. Katsnelson, K. S. Novoselov, Nat. Mater. 2007, 6, 652. \n[49]\t H. Liu, Y. Liu, D. Zhu, J. Mater. Chem. 2011, 21, 3335. \n[50]\t Y. Sato, K. Takai, T. Enoki, Nano Lett. 2011, 11, 3468. \n[51]\t A.  Lipatov, A.  Varezhnikov, P.  Wilson, V.  Sysoev, A.  Kolmakov, A. Sinitskii, Nanoscale 2013, 5, 5426. \n[52]\t A.  Lipatov, A.  Varezhnikov, M.  Augustin, M.  Bruns, M.  Sommer, V.  Sysoev, A.  Kolmakov, A.  Sinitskii, Appl. Phys. Lett. 2014, 104, 013114. \n[53]\t M. Naguib, Y. Gogotsi, Acc. Chem. Res. 2015, 48, 128. \n[54]\t B.  Anasori, Y.  Xie, M.  Beidaghi, J.  Lu, B. C.  Hosler, L.  Hultman, P. R. C. Kent, Y. Gogotsi, M. W. Barsoum, ACS Nano 2015, 9, 9507. " + }, + { + "id": "10.1126_science.aah4698", + "DOI": "10.1126/science.aah4698", + "DOI Link": "http://dx.doi.org/10.1126/science.aah4698", + "Relative Dir Path": "mds/10.1126_science.aah4698", + "Article Title": "MoS2 transistors with 1-nullometer gate lengths", + "Authors": "Desai, SB; Madhvapathy, SR; Sachid, AB; Llinas, JP; Wang, QX; Ahn, GH; Pitner, G; Kim, MJ; Bokor, J; Hu, CM; Wong, HSP; Javey, A", + "Source Title": "SCIENCE", + "Abstract": "Scaling of silicon (Si) transistors is predicted to fail below 5-nullometer (nm) gate lengths because of severe short channel effects. As an alternative to Si, certain layered semiconductors are attractive for their atomically uniform thickness down to a monolayer, lower dielectric constants, larger band gaps, and heavier carrier effective mass. Here, we demonstrate molybdenum disulfide (MoS2) transistors with a 1-nm physical gate length using a single-walled carbon nullotube as the gate electrode. These ultrashort devices exhibit excellent switching characteristics with near ideal subthreshold swing of similar to 65 millivolts per decade and an On/Off current ratio of similar to 10(6). Simulations show an effective channel length of similar to 3.9 nm in the Off state and similar to 1 nm in the On state.", + "Times Cited, WoS Core": 1217, + "Times Cited, All Databases": 1368, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000387777900038", + "Markdown": "10. A. Schirotzek, C.-H. Wu, A. Sommer, M. W. Zwierlein, Phys. Rev. Lett. 102, 230402 (2009). \n11. S. Nascimbène et al., Phys. Rev. Lett. 103, 170402 (2009). \n12. C. Kohstall et al., Nature 485, 615–618 (2012). \n13. M. Koschorreck et al., Nature 485, 619–622 (2012). \n14. Y. Zhang, W. Ong, I. Arakelyan, J. E. Thomas, Phys. Rev. Lett. 108, 235302 (2012). \n15. P. Massignan, M. Zaccanti, G. M. Bruun, Rep. Prog. Phys. 77, 034401 (2014). \n16. M. Sidler et al., http://arXiv.org/abs/1603.09215 (2016). \n17. J. Goold, T. Fogarty, N. Lo Gullo, M. Paternostro, T. Busch, Phys. Rev. A 84, 063632 (2011). \n18. M. Knap et al., Phys. Rev. X 2, 041020 (2012). \n19. M. Cetina et al., Phys. Rev. Lett. 115, 135302 (2015). \n20. See supplementary materials on Science Online. \n21. D. Naik et al., Eur. Phys. J. D 65, 55–65 (2011). \n22. J. Loschmidt, Sitzungsber. Akad. Wissenschaften Wien 73, 128 (1876). \n23. E. L. Hahn, Phys. Rev. 80, 580–594 (1950). \n24. P. Nozières, C. T. De Dominicis, Phys. Rev. 178, 1097–1107 (1969). \n25. R. A. Jalabert, H. M. Pastawski, Adv. Solid State Phys. 41, 483–496 (2001). \n26. F. Chevy, Phys. Rev. A 74, 063628 (2006). \n27. X. Cui, H. Zhai, Phys. Rev. A 81, 041602 (2010). \n28. J. Dubois et al., Nature 502, 659–663 (2013). \n29. C. Mora, F. Chevy, Phys. Rev. Lett. 104, 230402 (2010). \n30. Z. Yu, S. Zöllner, C. J. Pethick, Phys. Rev. Lett. 105, 188901 (2010). \n31. W. Zwerger, Ed., The BCS-BEC Crossover and the Unitary Fermi Gas (Springer, 2012). \n32. R. A. Hart et al., Nature 519, 211–214 (2015). \n33. L. J. LeBlanc, J. H. Thywissen, Phys. Rev. A 75, 053612 (2007). \n\n# ACKNOWLEDGMENTS \n\nWe thank M. Baranov, F. Schreck, G. Bruun, N. Davidson, and R. Folman for stimulating discussions. Supported by NSF through a grant for ITAMP at Harvard University and the Smithsonian Astrophysical Observatory (R.S.); the Technical University of Munich-Institute for Advanced Study, funded by the German \n\nExcellence Initiative and the European Union FP7 under grant agreement 291763 (M.K.); the Harvard-MIT Center for Ultracold Atoms, NSF grant DMR-1308435, the Air Force Office of Scientific Research Quantum Simulation Multidisciplinary University Research Initiative (MURI), the Army Research Office MURI on Atomtronics, M. Rössler, the Walter Haefner Foundation, the ETH Foundation, and the Simons Foundation (E.D.); and the Austrian Science Fund (FWF) within the SFB FoQuS (F4004-N23) and within the DK ALM (W1259-N27). \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/354/6308/96/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S11 \nTable S1 \nReferences (34–56) \n20 February 2016; accepted 6 September 2016 \n10.1126/science.aaf5134 \n\n# DEVICE TECHNOLOGY \n\n# $\\mathbf{MoS}_{2}$ transistors with 1-nanometer gate lengths \n\nSujay B. Desai,1,2,3 Surabhi R. Madhvapathy,1,2 Angada B. Sachid,1,2 Juan Pablo Llinas,1,2 Qingxiao Wang,4 Geun Ho Ahn,1,2 Gregory Pitner,5 Moon J. Kim,4 Jeffrey Bokor,1,2 Chenming Hu,1 H.-S. Philip Wong,5 Ali Javey1,2,3\\* \n\nScaling of silicon (Si) transistors is predicted to fail below 5-nanometer (nm) gate lengths because of severe short channel effects. As an alternative to Si, certain layered semiconductors are attractive for their atomically uniform thickness down to a monolayer, lower dielectric constants, larger band gaps, and heavier carrier effective mass. Here, we demonstrate molybdenum disulfide $(\\mathsf{M o S}_{2})$ transistors with a 1-nm physical gate length using a single-walled carbon nanotube as the gate electrode. These ultrashort devices exhibit excellent switching characteristics with near ideal subthreshold swing of $\\mathord{\\sim}65$ millivolts per decade and an On/Off current ratio of $\\mathord{\\sim}10^{6}$ . Simulations show an effective channel length of ${\\sim}3.9\\ \\mathsf{n m}$ in the Off state and $\\mathbf{\\omega}\\tilde{\\mathbf{\\Gamma}}^{\\mathbf{\\Gamma}}\\tilde{\\mathbf{\\Gamma}}^{1}\\mathbf{\\mathfrak{n}}\\mathbf{m}$ in the On state. \n\ns Si transistors rapidly approach their projected scaling limit of ${\\sim}5{\\mathrm{-nm}}$ gate lengths, exploration of new channel materials and device architectures is of utmost interest \nH (1–3). This scaling limit arises from short \nchannel effects (4). Direct source-to-drain tunnel \ning and the loss of gate electrostatic control on the \nchannel severely degrade the Off state leakage cur \nrents, thus limiting the scaling of Si transistors \n(5, 6). Certain semiconductor properties dictate \nthe magnitude of these effects for a given gate \nlength. Heavier carrier effective mass, larger \nband gap, and lower in-plane dielectric constant \nyield lower direct source-to-drain tunneling cur \nrents (7). Uniform and atomically thin semicon \n\ndirect source-to-drain tunneling currents (ISD-LEAK) in the Off state for different channel lengths and thicknesses using a dual-gate device structure (fig. S1) as a means to compare the two materials. $\\mathbf{MoS}_{2}$ shows more than two orders of magnitude reduction in $I_{\\mathrm{SD}}$ -LEAK relative to Si mainly because of its larger electron effective mass along the transport direction $(m_{n}^{*}\\sim0.55m_{0}$ for $\\mathbf{MoS}_{2}$ versus $\\stackrel{\\bullet}{m_{n}}\\sim0.19m_{0}$ for Si [100]) (19), with a trade-off resulting in lower ballistic On current. Notably, $I_{\\mathrm{SD-LEAK}}$ does not limit the scaling of monolayer $\\mathbf{MoS}_{2}$ even down to the \\~1-nm gate length, presenting a major advantage over Si [see more details about calculations in the supplementary materials (20)]. Finally, few-layer $\\mathbf{MoS}_{2}$ exhibits a lower in-plane dielectric constant $(\\mathord{\\sim}4)$ compared with bulk Si (\\~11.7), Ge (\\~16.2), and GaAs (\\~12.9), resulting in a shorter electrostatic characteristic length (l) as depicted in fig. S2 (21). \n\nductors with low in-plane dielectric constants are desirable for enhanced electrostatic control of the gate. Thus, investigation and introduction of semiconductors that have more ideal properties than Si could lead to further scaling of transistor dimensions with lower Off state dissipation power. \n\nTransition metal dichalcogenides (TMDs) are layered two-dimensional (2D) semiconductors that have been widely explored as a potential channel material replacement for Si (8–11), and each material exhibits different band structures and properties (12–16). The layered nature of TMDs allows uniform thickness control with atomic-level precision down to the monolayer limit. This thickness scaling feature of TMDs is highly desirable for well-controlled electrostatics in ultrashort transistors (3). For example, monolayer and few-layer $\\mathrm{MoS_{2}}$ have been shown theoretically to be superior to Si at the sub-5-nm scaling limit (17, 18). \n\nThe scaling characteristics of $\\mathrm{MoS_{2}}$ and Si transistors as a function of channel thickness and gate length are summarized in Fig. 1. We calculated \n\nThe above qualities collectively make $\\mathrm{MoS_{2}}$ a strong candidate for the channel material of future transistors at the sub-5-nm scaling limit. However, to date, TMD transistors at such small gate lengths have not been experimentally explored. Here, we demonstrate 1D gated, 2D semiconductor field-effect transistors (1D2D-FETs) with a single-walled carbon nanotube (SWCNT) gate, a $\\mathbf{MoS}_{2}$ channel, and physical gate lengths of ${\\sim}1\\mathrm{nm}.$ The 1D2D-FETs exhibit near ideal switching characteristics, including a subthreshold swing (SS) of $\\mathrm{\\sim}65\\mathrm{mV}$ per decade at room temperature and high On/Off current ratios. The SWCNT diameter $d\\sim$ $1\\mathrm{nm}$ for the gate electrode (22) minimized parasitic gate to source-drain capacitance, which is characteristic of lithographically patterned tall gate structures. The \\~1-nm gate length of the SWCNT also allowed for the experimental exploration of the device physics and properties of $\\mathbf{MoS}_{2}$ transistors as a function of semiconductor thickness (i.e., number of layers) at the ultimate gate-length scaling limit. \n\nThe experimental device structure of the 1D2DFET (Fig. 2A) consists of a $\\mathbf{MoS}_{2}$ channel (number of layers vary), a $\\mathrm{ZrO_{2}}$ gate dielectric, and a SWCNT gate on a $50\\mathrm{-nm}\\mathrm{SiO_{2}/S i}$ substrate with a physical gate length $(L_{\\mathrm{G}}\\sim\\ d)$ of ${\\sim}1\\mathrm{nm}$ . Long, aligned SWCNTs grown by chemical vapor deposition were transferred onto a $n^{+}~\\mathrm{Si/SiO_{2}}$ substrate (50-nm-thick $\\mathrm{{SiO_{2}},}$ ) (23), located with a scanning electron microscope (SEM), and contacted with palladium via lithography and metallization. These steps were followed by atomic layer deposition (ALD) of $\\mathrm{zrO_{2}}$ and pick-and-place dry transfer of $\\mathbf{MoS}_{2}$ onto the SWCNT covered by $\\mathrm{zrO_{2}}$ $(I4)$ . Nickel source and drain contacts were made to $\\mathbf{MoS}_{2}$ to complete the device. The detailed process flow and discussion about device fabrication is provided in fig. S3. \n\n![](images/964c05eb8777be82014c987674bf817332da99e47e3f245ff5c9d119e65d0aa8.jpg) \nFig. 1. Direct source-to-drain tunneling leakage current. (A) Normalized direct source-to-drain tunneling leakage current (ISD-LEAK), calculated using the WKB (Wentzel-Kramers-Brillouin) approximation as a function of channel thickness $T_{\\mathsf{C H}}$ for Si and ${\\mathsf{M o S}}_{2}$ in the Off state. $V_{\\mathsf{D S}}=V_{\\mathsf{D D}}=0.43$ V from the International Technology Roadmap for Semiconductors (ITRS) 2026 technology node. (B) $I_{S D-L E A K}$ as a function of gate length $L_{\\ G}$ for different thicknesses of Si and ${\\mathsf{M o S}}_{2}$ for the same Off state conditions as Fig. 1A.The dotted line in Fig. 1, A and B represents the low operating power limit for the 2026 technology node as specified by the ITRS. \n\n![](images/98d7f0d6e6292e6274fe9acde1a83cb5de1d4896d47f449ea11e81cbe24dcfff.jpg) \nFig. 2. 1D2D-FET device structure and characterization. (A) Schematic of 1D2D-FET with a ${\\mathsf{M o S}}_{2}$ channel and SWCNT gate. (B) Optical image of a representative device shows the ${\\mathsf{M o S}}_{2}$ flake, gate (G), source (S), and drain (D) electrodes. (C) False-colored SEM image of the device showing the SWCNT (blue), $Z\\mathrm{rO}_{2}$ gate dielectric (green), ${\\mathsf{M o S}}_{2}$ channel (orange), and the Ni source and drain electrodes (yellow). (D) Cross-sectional TEM image of a representative sample showing the SWCNTgate, $Z\\r\\Gamma\\mathsf{O}_{2}$ gate dielectric, and bilayer ${\\mathsf{M o S}}_{2}$ channel. (E) EELS map showing spatial distribution of carbon, zirconium, and sulfur in the device region, confirming the location of the SWCNT, ${\\mathsf{M o S}}_{2}$ flake, and $Z\\r\\Gamma\\mathsf{O}_{2}$ dielectric. \n\nFigure 2B shows the optical image of a representative 1D2D-FET capturing the $\\mathbf{MoS}_{2}$ flake, the source and drain contacts to $\\mathrm{MoS_{2},}$ and the gate contacts to the SWCNT. The SWCNT and the $\\mathbf{MoS}_{2}$ flake can be identified in the false-colored SEM image of a representative sample (Fig. 2C). The 1D2D-FET consists of four electrical terminals; source (S), drain (D), SWCNT gate (G), and the $n^{+}$ Si substrate back gate (B). The SWCNT gate underlaps the $\\mathrm{\\DeltaS/D}$ contacts. These underlapped regions were electrostatically doped by the Si back gate during the electrical measurements, thereby serving as $n^{+}$ extension contact regions. The device effectively operated like a junctionless transistor $\\scriptstyle(24),$ , where the SWCNT gate locally depleted the $n^{+}\\ \\mathrm{MoS_{2}}$ channel after applying a negative voltage, thus turning Off the device. \n\nA cross-sectional transmission electron microscope (TEM) image of a representative 1D2DFET (Fig. 2D) shows the SWCNT gate, $\\mathrm{zrO_{2}}$ gate dielectric (thickness $T_{\\mathrm{OX}}{\\sim}5.8\\ \\mathrm{nm},$ ), and the bilayer $\\mathbf{MoS}_{2}$ channel. The topography of $\\mathrm{zrO_{2}}$ surrounding the SWCNT and the $\\mathrm{MoS_{2}}$ flake on top of the gate oxide was flat, as seen in the TEM image. This geometry is consistent with ALD nucleation initiating on the $\\mathrm{SiO_{2}}$ substrate surrounding the SWCNT and eventually covering it completely as the thickness of deposited $\\mathrm{zrO_{2}}$ exceeds the SWCNT diameter $d$ (25). The spatial distribution of carbon, zirconium, and sulfur was observed in the electron energy-loss spectroscopy (EELS) map of the device region (Fig. 2E), thus confirming the location of the SWCNT, $\\mathrm{ZrO_{2}}$ , and $\\mathbf{MoS}_{2}$ in the device (fig. S4) (20). \n\nThe electrical characteristics for a 1D2D-FET with a bilayer $\\mathbf{MoS}_{2}$ channel (Fig. 3) show that the $\\mathbf{MoS}_{2}$ extension regions (the underlapped regions between the SWCNT gate and S/D contacts) could be heavily inverted (i.e., $n^{+}$ state) by applying a positive back-gate voltage of $V_{\\mathrm{BS}}=5$ V to the Si substrate. The $I_{\\mathrm{D}^{-}}V_{\\mathrm{BS}}$ characteristics (fig. S5) indicate that the $\\mathbf{MoS}_{2}$ flake was strongly inverted by the back gate at $V_{\\mathrm{BS}}=5\\mathrm{V}$ . The $I_{\\mathrm{D}^{-}}V_{\\mathrm{GS}}$ characteristics for the device at $V_{\\mathrm{BS}}=5\\mathrm{V}$ and $V_{\\mathrm{DS}}=$ $50\\mathrm{mV}$ and 1 V (Fig. 3A) demonstrate the ability of the \\~1-nm SWCNT gate to deplete the $\\mathbf{MoS}_{2}$ channel and turn Off the device. The 1D2D-FET exhibited excellent subthreshold characteristics with a near ideal SS of ${\\sim}65~\\mathrm{mV}$ per decade at room temperature and $_\\mathrm{On/Off}$ current ratio of ${\\sim}10^{6}$ . The drain-induced barrier lowering (DIBL) was ${\\sim}290\\mathrm{mV/V}.$ Leakage currents through the SWCNT gate $\\left({{I_{\\mathrm{G}}}}\\right)$ and the $n^{+}$ Si back gate $\\left(I_{\\mathrm{B}}\\right)$ are at the measurement noise level (Fig. 3A). The interface trap density $(D_{\\mathrm{IT}})$ of the $\\mathrm{ZrO_{2}\\mathrm{-MoS_{2}}}$ interface estimated from SS was ${\\sim}1.7\\ \\times\\ 10^{12}\\ \\mathrm{cm^{-2}}\\ \\mathrm{eV^{-1}}$ , which is typical for transferred $\\mathbf{MoS}_{2}$ flakes (26) because of the absence of surface dangling bonds (20). \n\nFigure 3B shows the $I_{\\mathrm{D}^{-}}V_{\\mathrm{DS}}$ characteristics at different $V_{\\mathrm{GS}}$ values and fixed $V_{\\mathrm{BS}}=5\\:\\mathrm{V}$ . The $I_{\\mathrm{D}}.$ $V_{\\mathrm{GS}}$ characteristics depended strongly on the value of $V_{\\mathrm{BS}},$ , which affects the extension region resistance. The inversion of the extension regions increased with increasing $V_{\\mathrm{BS}},$ , thus reducing the series resistance and contact resistance and led to an increase in the On current and an improvement in the SS. At more positive values of $V_{\\mathrm{BS}},$ , $V_{\\mathrm{GS}}$ had to be more negative in order to deplete the $\\mathbf{MoS}_{2}$ channel, which in turn made the threshold voltage $(V_{\\mathrm{T}})$ more negative. Above $V_{\\mathrm{BS}}=1\\mathrm{V},$ , the SS and $I_{\\mathrm{On}}$ did not improve any further, and the extension regions were strongly inverted (Fig. 3C). Thus, the 1D2D-FET operated as a short-channel device. \n\nWe performed detailed simulations using Sentaurus TCAD to understand the electrostatics of the 1D2D-FET. The Off and On state conditions correspond to $(V_{\\mathrm{GS}}–V_{\\mathrm{T}})$ of $-0.3{\\mathrm{~V}}$ and $1.5\\mathrm{V}_{:}$ , respectively (which give an On/Off current ratio of ${\\sim}10^{6})$ . The electric field contour plot (Fig. 3D) in the Off state has a region of low electric field in the $\\mathbf{MoS}_{2}$ channel near the SWCNT, indicating that it is depleted. The reduced electron density in the $\\mathrm{MoS_{2}}$ channel (Fig. 3E), and the presence of an energy barrier to electrons in the conduction band (fig. S6A) are also consistent with the Off state of the device. The extension regions are still under inversion because of the positive backgate voltage. The electron density of the $\\mathbf{MoS}_{2}$ channel in the depletion region can be used to define the effective channel length $(L_{\\mathrm{EFF}})$ of the 1D2D-FET, which is the region of channel controlled by the SWCNT gate (27–29). The channel is considered to be depleted if the electron density falls below a defined threshold $(n_{\\mathrm{threshold}}).$ The Off state $L_{\\mathrm{EFF}},$ defined as the region of $\\mathbf{MoS}_{2}$ with electron density $nL_{\\tt G}$ in the Off state because of the fringing electric fields from the SWCNTgate. \n\n![](images/e3ae629a449acffa917d57910c76f59bcfd90725f7bf887cba1921e6a358c2fe.jpg) \nFig. 4. $M O S_{2}$ thickness dependence. (A) Dependence of ${\\mathsf{M o S}}_{2}$ channel thickness on the performance of 1D2D-FET. SS increases with increasing ${\\mathsf{M o S}}_{2}$ channel thickness. (B) Extracted SS from experimental curves and TCAD simulations show increasing SS as channel thickness $T_{\\mathsf{C H}}$ increases. \n\nThe effect of $\\mathbf{MoS}_{2}$ thickness on the device characteristics was systematically explored. At the scaling limit of the gate length, the semiconductor channel thickness must also be scaled down aggressively, as described earlier. The electrostatic control of the SWCNT gate on the $\\mathbf{MoS}_{2}$ channel decreased with increasing distance from the $\\mathrm{ZrO_{2}}$ - $\\mathrm{MoS_{2}}$ interface. Thus, as the $\\mathbf{MoS}_{2}$ flake thickness was increased, the channel could not be completely depleted by applying a negative $V_{\\mathrm{GS}}.$ Because of this effect, the SS for a 12-nm-thick $\\mathbf{MoS}_{2}$ device $\\mathord{\\mathrm{\\sim}}\\mathrm{170}\\mathrm{mV}$ per decade) was much larger than that of bilayer $\\mathbf{MoS}_{2}$ $\\mathrm{\\sim65\\mV}$ per decade), and as the thickness of $\\mathbf{MoS}_{2}$ was increased to $\\mathrm{\\sim}31~\\mathrm{nm}$ , the device could no longer be turned off (Fig. 4A). The experimental SS as a function of $\\mathbf{MoS}_{2}$ thickness was qualitatively consistent with the TCAD simulations (Fig. 4B and S10), showing an increasing trend with increasing channel thickness. The unwanted variations in device performance caused by channel thickness fluctuations (Fig. 4B and fig. S10), and the need for low Off state current at short channel lengths (Figs. 1 and 3), thus justify the need for layered semiconductors like TMDs at the scaling limit. \n\nTMDs offer the ultimate scaling of thickness with atomic-level control, and the 1D2D-FET structure enables the study of their physics and electrostatics at short channel lengths by using the natural dimensions of a SWCNT, removing the need for any lithography or patterning processes that are challenging at these scale lengths. However, large-scale processing and manufacturing of TMD devices down to such small gate lengths are existing challenges requiring future innovations. For instance, research on developing process-stable, low-resistance ohmic contacts to TMDs, and scaling of the gate dielectric by using high- $\\kappa2\\mathrm{D}$ insulators is essential to further enhance device performance. Wafer-scale growth of high-quality films (30) is another challenge toward achieving very-large-scale integration of TMDs in integrated circuits. Finally, fabrication of electrodes at such small scale lengths over large areas requires considerable advances in lithographic techniques. Nevertheless, the work here provides new insight into the ultimate scaling of gate lengths for a FET by surpassing the 5-nm limit (3–7) often associated with Si technology. \n\n# REFERENCES AND NOTES \n\n1. T. N. Theis, P. M. Solomon, Science 327, 1600–1601 (2010). \n2. R. Chau, B. Doyle, S. Datta, J. Kavalieros, K. Zhang, Nat. Mater. 6, 810–812 (2007). \n3. A. D. Franklin, Science 349, aab2750 (2015). \n4. M. Lundstrom, Science 299, 210–211 (2003). \n5. M. Luisier, M. Lundstrom, D. A. Antoniadis, J. Bokor, in Electron Devices Meeting (IEDM), 2011 IEEE International (IEEE, 2011), pp. 11.12.11–1.12.14. \n6. H. Kawaura, T. Sakamoto, T. Baba, Appl. Phys. Lett. 76, 3810–3812 (2000). \n7. W. S. Cho, K. Roy, IEEE Electron Device Lett. 36, 427–429 (2015). \n8. B. Radisavljevic, A. Radenovic, J. Brivio, V. Giacometti, A. Kis, Nat. Nanotechnol. 6, 147–150 (2011). \n9. D. Sarkar et al., Nature 526, 91–95 (2015). \n10. H. Liu, A. T. Neal, P. D. Ye, ACS Nano 6, 8563–8569 (2012). \n11. H. Wang et al., Nano Lett. 12, 4674–4680 (2012). \n12. K. F. Mak, K. L. McGill, J. Park, P. L. McEuen, Science 344, 1489–1492 (2014). \n13. D. Jariwala, V. K. Sangwan, L. J. Lauhon, T. J. Marks, M. C. Hersam, ACS Nano 8, 1102–1120 (2014). \n14. H. Fang et al., Proc. Natl. Acad. Sci. U.S.A. 111, 6198–6202 (2014). \n15. K. S. Novoselov et al., Proc. Natl. Acad. Sci. U.S.A. 102, 10451–10453 (2005). \n16. C.-H. Lee et al., Nat. Nanotechnol. 9, 676–681 (2014). \n17. Y. Yoon, K. Ganapathi, S. Salahuddin, Nano Lett. 11, 3768–3773 (2011). \n18. L. Liu, Y. Lu, J. Guo, IEEE Trans. Electron. Dev. 60, 4133–4139 (2013). \n19. D. Wickramaratne, F. Zahid, R. K. Lake, J. Chem. Phys. 140, 124710 (2014). \n20. Supplementary materials are available on Science Online. \n21. K. Suzuki, T. Tanaka, Y. Tosaka, H. Horie, Y. Arimoto, IEEE Trans. Electron. Dev. 40, 2326–2329 (1993). \n22. J. Svensson et al., Nanotechnology 19, 325201 (2008). \n23. N. Patil et al., IEEE Trans. NanoTechnol. 8, 498–504 (2009). \n24. J.-P. Colinge et al., Nat. Nanotechnol. 5, 225–229 (2010). \n25. A. Javey et al., Nano Lett. 4, 1319–1322 (2004). \n26. X. Zou et al., Adv. Mater. 26, 6255–6261 (2014). \n27. Y. Taur, IEEE Trans. Electron. Dev. 47, 160–170 (2000). \n28. L. Barbut, F. Jazaeri, D. Bouvet, J.-M. Sallese, Int. J. Microelectron. Comput. Sci. 4, 103–109 (2013). \n29. S. Hong, K. Lee, IEEE Trans. Electron. Dev. 42, 1461–1466 (1995). \n30. K. Kang et al., Nature 520, 656–660 (2015). \n\n# ACKNOWLEDGMENTS \n\nS.B.D. and A.J. were supported by the Electronics Materials program funded by the Director, Office of Science, Office of Basic \n\nEnergy Sciences, Materials Sciences and Engineering Division of the U.S. Department of Energy under contract DE-AC02- 05CH11231. A.B.S. was funded by Applied Materials, Inc., and Entegris, Inc., under the I-RiCE program. J.P.L. and J.B. were supported in part by the Office of Naval Research BRC program. J.P.L. acknowledges a Berkeley Fellowship for Graduate Studies and the NSF Graduate Fellowship Program. Q.W. and M.J.K. were supported by the NRI SWAN Center and Chinese Academy of Sciences President’s International Fellowship Initiative (2015VTA031). G.P. and H.-S.P.W. were supported in part by the SONIC Research Center, one of six centers supported by the STARnet phase of the Focus Center Research Program (FCRP) a Semiconductor Research Corporation program sponsored by MARCO and DARPA. A.J., H.-S.P.W., and J.B. acknowledge the NSF Center for Energy Efficient Electronics Science $(\\mathsf{E}^{3}\\mathsf{S})$ . A.J. acknowledges support from Samsung. The authors acknowledge the Molecular Foundry, Lawrence Berkeley National Laboratory for access to the scanning electron microscope. The authors acknowledge H. Fahad for useful discussions about the analytical modeling. All data are reported in the main text and supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\n# BIOCATALYSIS \n\nwww.sciencemag.org/content/354/6308/99/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S10 \nTable S1 \nReferences (31–44) \n30 June 2016; accepted 7 September 2016 \n10.1126/science.aah4698 \n\n# An artificial metalloenzyme with the kinetics of native enzymes \n\nP. Dydio,1,2\\* H. M. Key,1,2\\* A. Nazarenko,1 J. Y.-E. Rha,1 V. Seyedkazemi,1 D. S. Clark,3,4 J. F. Hartwig1,2† \n\nNatural enzymes contain highly evolved active sites that lead to fast rates and high selectivities. Although artificial metalloenzymes have been developed that catalyze abiological transformations with high stereoselectivity, the activities of these artificial enzymes are much lower than those of natural enzymes. Here, we report a reconstituted artificial metalloenzyme containing an iridium porphyrin that exhibits kinetic parameters similar to those of natural enzymes. In particular, variants of the P450 enzyme CYP119 containing iridium in place of iron catalyze insertions of carbenes into $c-H$ bonds with up to $98\\%$ enantiomeric excess, 35,000 turnovers, and 2550 hours−1 turnover frequency. This activity leads to intramolecular carbene insertions into unactivated $c-H$ bonds and intermolecular carbene insertions into C–H bonds. These results lift the restrictions on merging chemical catalysis and biocatalysis to create highly active, productive, and selective metalloenzymes for abiological reactions. \n\nT tion sphere of the metal and the surrounding dhetecratmailynteidc abcytibvoityh otfheapmriemtalrlyoecnozoyrmdieniasprotein scaffold. In some cases, laboratory evolution has been used to develop variants of native metalloenzymes for selective reactions of unnatural substrates $(\\boldsymbol{I},\\boldsymbol{2})$ . Yet with few exceptions (3), the classes of reactions that such enzymes undergo are limited to those of biological transformations. To combine the favorable qualities of enzymes with the diverse reactivity of synthetic transition-metal catalysts, abiological transition-metal centers or cofactors have been incorporated into native proteins. The resulting artificial metalloenzymes catalyze classes of reactions for which there is no known enzyme (abiological transformations) (3, 4). \n\nAlthough the reactivity of these artificial systems is new for an enzyme, the rates of these reactions have been much slower and the $\\mathbf{MoS}_{2}$ transistors with 1-nanometer gate lengths Sujay B. Desai, Surabhi R. Madhvapathy, Angada B. Sachid, Juan Pablo Llinas, Qingxiao Wang, Geun Ho Ahn, Gregory Pitner, Moon J. Kim, Jeffrey Bokor, Chenming Hu, H.-S. Philip Wong and Ali Javey (October 6, 2016) Science 354 (6308), 99-102. [doi: 10.1126/science.aah4698] \n\nEditor's Summary \n\n# A flatter route to shorter channels \n\nHigh-performance silicon transistors can have gate lengths as short as $5\\mathrm{nm}$ before source-drain tunneling and loss of electrostatic control lead to unacceptable leakage current when the device is off. Desai et al. explored the use of $\\mathbf{MoS}_{2}$ as a channel material, given that its electronic properties as thin layers should limit such leakage. A transistor with a $_{1-\\mathrm{nm}}$ physical gate was constructed with a $\\mathrm{MoS}_{.2}$ bilayer channel and a single-walled carbon nanotube gate electrode. Excellent switching characteristics and an on-off state current ratio of ${\\sim}10^{6}$ were observed. \n\nScience, this issue p. 99 \n\nThis copy is for your personal, non-commercial use only. \n\n# Article Tools \n\n# Permissions \n\nObtain information about reproducing this article: http://www.sciencemag.org/about/permissions.dtl " + }, + { + "id": "10.1038_ncomms11203", + "DOI": "10.1038/ncomms11203", + "DOI Link": "http://dx.doi.org/10.1038/ncomms11203", + "Relative Dir Path": "mds/10.1038_ncomms11203", + "Article Title": "Balancing surface adsorption and diffusion of lithium-polysulfides on nonconductive oxides for lithium-sulfur battery design", + "Authors": "Tao, XY; Wang, JG; Liu, C; Wang, HT; Yao, HB; Zheng, GY; Seh, ZW; Cai, QX; Li, WY; Zhou, GM; Zu, CX; Cui, Y", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Lithium-sulfur batteries have attracted attention due to their six-fold specific energy compared with conventional lithium-ion batteries. Dissolution of lithium polysulfides, volume expansion of sulfur and uncontrollable deposition of lithium sulfide are three of the main challenges for this technology. State-of-the-art sulfur cathodes based on metal-oxide nullostructures can suppress the shuttle-effect and enable controlled lithium sulfide deposition. However, a clear mechanistic understanding and corresponding selection criteria for the oxides are still lacking. Herein, various nonconductive metal-oxide nulloparticle-decorated carbon flakes are synthesized via a facile biotemplating method. The cathodes based on magnesium oxide, cerium oxide and lanthanum oxide show enhanced cycling performance. Adsorption experiments and theoretical calculations reveal that polysulfide capture by the oxides is via monolayered chemisorption. Moreover, we show that better surface diffusion leads to higher deposition efficiency of sulfide species on electrodes. Hence, oxide selection is proposed to balance optimization between sulfide-adsorption and diffusion on the oxides.", + "Times Cited, WoS Core": 1247, + "Times Cited, All Databases": 1319, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000373622000001", + "Markdown": "# Balancing surface adsorption and diffusion of lithium-polysulfides on nonconductive oxides for lithium–sulfur battery design \n\nXinyong $\\mathsf{T a o}^{1,2,\\star}$ , Jianguo Wang3,\\*, Chong Liu2, Haotian Wang2, Hongbin $\\mathsf{Y a o}^{2}$ , Guangyuan Zheng2, Zhi Wei Seh2, Qiuxia Cai3, Weiyang $\\mathsf{L i}^{2},$ Guangmin Zhou2, Chenxi $Z\\mathsf{u}^{2}\\&\\mathsf{Y i}\\mathsf{C u i}^{2,4}$ \n\nLithium–sulfur batteries have attracted attention due to their six-fold specific energy compared with conventional lithium-ion batteries. Dissolution of lithium polysulfides, volume expansion of sulfur and uncontrollable deposition of lithium sulfide are three of the main challenges for this technology. State-of-the-art sulfur cathodes based on metal-oxide nanostructures can suppress the shuttle-effect and enable controlled lithium sulfide deposition. However, a clear mechanistic understanding and corresponding selection criteria for the oxides are still lacking. Herein, various nonconductive metal-oxide nanoparticledecorated carbon flakes are synthesized via a facile biotemplating method. The cathodes based on magnesium oxide, cerium oxide and lanthanum oxide show enhanced cycling performance. Adsorption experiments and theoretical calculations reveal that polysulfide capture by the oxides is via monolayered chemisorption. Moreover, we show that better surface diffusion leads to higher deposition efficiency of sulfide species on electrodes. Hence, oxide selection is proposed to balance optimization between sulfide-adsorption and diffusion on the oxides. \n\nRebdceuhcea tmgo tbohlne liotfhwit-uhceoms–tm oalrnfeud xh(ciLigithi–n-Ssg)pebcnaitefitrceg ns orhrgayv ofrs csetuelnftmulysr cathodes1–27. Although there have been significant developments for designing state-of-the-art Li–S batteries in the past two decades, the practical application is still hindered by many material challenges, including dissolution of intermediate lithium polysulfides $(\\mathrm{Li}_{2}\\mathrm{S}_{x},\\ x>3)$ in the electrolyte28, large volumetric expansion $(80\\%)$ of sulfur upon lithiation6, and poor electronic/ ionic conductivity of sulfur and lithium sulfide $(\\mathrm{Li}_{2}\\mathrm{S})$ (ref. 6). To date, tremendous efforts have been made to solve the above problems by constructing advanced composite cathode materials. One effective strategy is the encapsulation of sulfur to prevent the leakage of active materials and suppress the shuttle effect of highorder $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ (refs 3,6). Oxides6, carbon3,29, polymers30 and metals31 are proved to be good matrix materials for the encapsulation of sulfur19. The second approach is the controllable deposition of the discharge product $\\mathrm{Li}_{2}\\mathrm{S},$ which is an ionic and electronic insulator4. The detaching and irreversible phase transformation of $\\mathrm{Li}_{2}\\mathrm S$ is considered as the main reason for capacity fading4,32. The third strategy is using $\\mathrm{Li}_{2}\\mathrm S$ as a starting cathode material, which undergoes volumetric contraction instead of the expansion in the case of sulfur20. In addition, $\\mathrm{Li}_{2}\\mathrm S$ -based cathodes can be paired with lithium metal-free anodes such as graphite, silicon and alloys33, thus suppressing the dendrite growth and the corresponding safety concerns of lithium-metal anodes. \n\nAll the previous research reveals the importance of understanding the sulfide species interaction with the matrix materials. Our earlier work pointed out that the usual carbon substrates interact with $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ weakly but the polar group enabled strong interaction with $\\mathrm{Li}_{2}\\mathrm{S}_{x},$ which can facilitate the $\\mathrm{Li}_{2}\\mathrm S_{x}$ trapping and promote the attachment of solid $\\mathrm{Li}_{2}\\mathrm{S}_{2}$ and $\\mathrm{Li}_{2}\\mathrm S$ and improve the cycling stability of Li–S batteries34. Many similar examples followed-up using polymers35,36, oxides4,19, sulfides20, functionalized graphene18,26,27,37,38, metal organic framework39 and nitrogen doped carbon36,40, which all have polar surfaces to adsorb $\\mathrm{Li}_{2}\\mathrm S_{x}$ species. Results from this study seem to suggest that the stronger the binding, the better the Li–S batteries. In addition, it was recognized that using conducting materials such as indium tin oxide4 and $\\mathrm{Ti}_{4}\\mathrm{O}_{7}$ (ref. 19) is preferable due to the electron transfer needed to induce electrochemical reaction. Our recent work showed that indium tin oxide decorated carbon nanofibres can enhance the redox kinetics of ${\\mathrm{Li}}_{2}{\\mathrm S}_{x},$ realize the controllable deposition of $\\mathrm{Li}_{2}\\mathrm{S}$ and improve the electrochemical performance of Li–S batteries . \n\nBesides the conductive matrix material, there are indeed abundant insulating materials to trap $\\mathrm{Li}_{2}\\mathrm S_{x}$ . But there is a fundamental problem here: insulated materials cannot transport electrons. Trapping $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ on insulating materials would cause them to be accumulated in electronically inactive areas and reduce the capacity retention. However, some studies have shown improvements of the electrochemical properties after the decoration of the electrode with poor conductive oxides such as $\\mathrm{MnO}_{2}$ (ref. 16), $\\mathrm{Mg_{0.6}N i_{0.4}O}$ (ref. 12), ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ (ref. 41) and $\\mathrm{La}_{2}\\mathrm{O}_{3}$ (ref. 42). \n\nThe above background research has motivated us to hypothesize that surface diffusion of $\\mathrm{Li}_{2}\\mathrm S_{x}$ species on solid substrates can play an important role in Li–S battery electrochemical performance. This is particularly important for insulating solid materials with strong adsorption of $\\mathrm{Li}_{2}\\mathrm S_{x}$ . The competition between the adsorption and diffusion of the $\\mathrm{Li}_{2}\\mathrm S_{x}$ adsorbates on solid substrates can be very important, yet has been overlooked for Li–S batteries. \n\nUsually, the nonconductive metal oxides work together with the carbon matrix to improve the conductivity of sulfur cathodes. For the modified carbon matrix with some nonconductive metal oxides nanostructures (Fig. 1), there is no direct electron transfer between these oxides and $\\mathrm{Li}_{2}\\mathrm S_{x}$ species. Because of the poor conductivity of the metal oxide, the absorbed $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ should be transferred from the surface of the oxide to the conductive carbon substrate to undergo the electrochemical reaction. Therefore the competitive surface diffusion and adsorption of sulfur species must play key roles in the Li–S batteries. If the metal oxide has weak $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ capture capability (Fig. 1a), a large amount of $\\mathrm{Li}_{2}\\mathrm S_{x}$ can diffuse away from the carbon matrix, resulting in serious shuttle effect and uncontrollable deposition of $\\mathrm{Li}_{2}\\mathrm S$ . When the diffusion of sulfur species from the surface of oxide to carbon is difficult (Fig. 1c), the electrochemical reaction of $\\mathrm{Li}_{2}\\mathrm S_{x}$ and the corresponding growth of $\\mathrm{Li}_{2}\\mathrm{S}$ on the oxide/carbon is impeded. Therefore, the balance optimization between $\\mathrm{Li}_{2}\\mathrm S_{x}$ adsorption and diffusion on the metal oxides surface is necessary (Fig. 1b). \n\nIn this work, various nonconductive metal oxide $\\mathrm{{(MgO_{\\it{i}}}}$ , ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ , $\\mathrm{CeO}_{2}$ , $\\mathrm{La}_{2}\\mathrm{O}_{3}$ and $\\mathrm{CaO}{\\mathrm{'}}$ ) nanoparticles-decorated carbon flakes are synthesized via a facile and generic biotemplating method using Kapok trees fibres as both the template and the carbon source. The sulfur cathodes based on MgO, $\\mathrm{CeO}_{2}$ and $\\mathrm{La}_{2}\\mathrm{O}_{3}$ show higher capacity and better cycling stability. Adsorption test, microstructure analysis and electrochemical performance evaluation combined with density functional theory (DFT) calculations reveal that better surface diffusion leads to higher deposition efficiency of sulfide species. A comprehensiveoxide-selection criteria referring to the strong binding, high surface area and good surface diffusion properties is proposed. \n\n![](images/b413f9cf3fbe428c5fb6a115de6ec648717a4a2199bc3f872975ea5a61f9d3c2.jpg) \nFigure 1 | Schematic of the $\\mathbf{Li}_{2}\\mathbb{S}_{x}$ adsorption and diffusion on the surface of various nonconductive metal oxides. (a) The metal oxide with weak $\\mathsf{L i}_{2}\\mathsf{S}_{x}$ adsorption capability; only few $\\mathsf{L i}_{2}\\mathsf{S}_{x}$ can be captured by the oxide; (b) the metal oxide with both strong adsorption and good diffusion, which is favourable for the electrochemical reaction and the controllable deposition of sulfur species; (c) the metal oxide with strong bonding but without good diffusion; the growth of $\\mathsf{L i}_{2}\\mathsf{S}$ and the electrochemical reaction on the oxide/ C surface is impeded. \n\n# Results \n\nSulfide capture by metal oxides. To reveal the role of metal oxides in Li–S batteries, five kinds of pure metal oxidenanoparticles were prepared by a generic Pechini sol–gel method13. 1,3-dioxolane (DOL) and dimethoxyethane (DME) are commonly used solvent in the Li–S battery electrolyte4. Therefore, $0.005\\mathrm{M}\\ \\mathrm{Li}_{2}\\mathrm{S}_{8}$ in DOL/DME (1:1, v-v) was prepared for the adsorption test of sulfides. Figure 2a shows the camera image of the adsorption test using different mass of oxide samples with the same total surface area. The colour of the solution containing ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ and $\\mathrm{CeO}_{2}$ is lighter than the others, indicating better adsorption of these two metal oxide nanoparticles. Inductively coupled plasma-optical emission spectroscopy (ICP-OES) results reveal that $\\mathrm{Al}_{2}^{-}\\mathrm{O}_{3}$ and CaO show the biggest and the smallest absorption capability, respectively (Fig. 2b). In addition, it was found that the adsorption capacity increases slightly with the rise of temperature (Fig. 2b and Supplementary Table 1), which is one essential characteristic of chemisorption. The measured $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ adsorption quantity of metal oxides is in the range of $2.78{-}4.94\\upmu\\mathrm{mol}\\dot{\\mathrm{m}^{-2}}$ , close to the simulated monolayer adsorption capacity ranging from 2.76 to $4.88\\upmu\\mathrm{mol}\\mathrm{m}^{-2}$ (Fig. 2b). Therefore, the $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ capture involves monolayer adsorption, which is another well-known characteristic of chemisorption. \n\nIn order to better understand the absorption mechanism, DFT calculation was performed to reveal the corresponding adsorption energy and sites (Fig. 2c,d and Supplementary Figs 2–6). Considering both low-order and high-order, $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ are important discharge products of Li–S batteries, we choose both $\\mathrm{Li}_{2}\\mathrm S$ and $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ as the prototype for modelling. Figure 2c shows the optimized geometries of the most stable $\\mathrm{Li}_{2}\\mathrm{S}$ on $\\mathrm{CeO}_{2}(111)$ , $\\bar{\\mathrm{Al}_{2}\\mathrm{O}_{3}}(110)$ , $\\mathrm{La}_{2}\\mathrm O_{3}(001)$ , $\\mathrm{{MgO(100)}}$ and $\\mathrm{CaO}(100)$ surfaces. On the entire surface, the most favourable binding site of $\\mathrm{Li}_{2}\\mathrm{S}$ is two Li atoms bonding with the oxygen atom of metal oxide (Fig. 2c). On $\\mathrm{Al}_{2}\\mathrm{O}_{3}(110)$ , the Li of $\\mathrm{Li}_{2}\\mathrm S$ is the bridge site of two oxygen atoms, on other four metal oxides, the Li is on the atop site of oxygen. On $\\mathrm{{MgO(100)}}$ CaO(100) and $\\mathrm{La}_{2}\\mathrm O_{3}(001)$ surfaces, the sulfur of $\\mathrm{Li}_{2}\\mathrm{S}$ is away from the metal oxides surface. Sulfur is bonding with oxygen on $\\mathrm{CeO}_{2}(111)$ , in which the sulfur–oxygen distance is $1.70\\mathring\\mathrm{A}$ while with Al on $\\mathrm{Al}_{2}\\mathrm{O}_{3}(110)$ , in which the Al–S distance is $2.21\\mathring\\mathrm{A}$ . The adsorption energy of $\\mathrm{Li}_{2}\\mathrm S$ on $\\mathrm{CeO}_{2}(111)$ , $\\mathrm{Al}_{2}\\mathrm{O}_{3}(110)$ , $\\mathrm{La}_{2}\\mathrm O_{3}(001)$ , $\\mathrm{MgO(100)}$ and $\\mathrm{CaO}(100)$ surfaces is $-6.33,\\:-7.12,\\:-0.5.85,\\:-5.71$ and $-5.49\\mathrm{eV}$ , respectively. The optimized stable configurations of $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ on five different surfaces are also shown in Fig. 2d and Supplementary Figs 2–6. Although the Li of $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ has similar bonding sites on the metal oxide surface as that of $\\mathrm{Li}_{2}\\mathrm{S},$ the optimized most stable configuration of $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ on each metal oxide is quite different. A lot of initial geometries of $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ on each metal oxide have been considered in our calculations. It is found that after optimization, the structures have big change due to the interaction between $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ and metal oxides. For both $\\mathrm{Li}_{2}\\mathrm S$ and $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ on metal oxides, the bonding between Li and oxygen plays a major role. In addition, only two or three sulfur atoms of $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ are bonding with the oxide surface. The adsorption energies of $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ have similar trend on these metal surfaces with $\\mathrm{Li}_{2}\\mathrm S$ while are much weaker than $\\mathrm{Li}_{2}\\mathrm S$ . The calculated adsorption energies of both $\\mathrm{Li}_{2}\\mathrm S$ and $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ are in agreement with the experimental adsorption test results of $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ on the oxide nanoparticles (Fig. 2b and Supplementary Table 1). \n\nBiotemplated fabrication of oxides/carbon nanostructures. Although most of these oxides have remarkable adsorption behaviour for sulfide species, they are poor electronic conductors. Conductivity is one of the most important factors affecting the performance of Li–S batteries. Therefore, we fabricated metal-oxides (MgO, ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ , $\\mathrm{CeO}_{2}$ , $\\mathrm{La}_{2}\\mathrm{O}_{3}$ and $\\mathrm{CaO}_{\\cdot}^{\\cdot}$ ) nanoparticles anchored on porous carbon nanoflakes to form an electronic conductive oxide/carbon nanocomposite. To fabricate the nanocomposite, Kapok fibres $\\left(\\mathrm{KFs}\\right)^{43}$ were used as both the template and the carbon source (Fig. 3a). KFs are low-cost and high-yield agriculture products derived from the fruits of Kapok tree, which is chemically composed of $64\\%$ cellulose, $13\\%$ lignin and $23\\%$ pentosan43. In addition, the KFs have unique hollow lumens with a thin wall thickness $\\leq1\\upmu\\mathrm{m}$ , which enables good sorption capacity through capillary force. Therefore, metal nitrate solution can be easily absorbed into the KFs (Fig. 3a). When the ${\\mathrm{NH}}_{3}$ gas diffuses into the KFs through the porous cell wall and the open end, metal hydroxides nanoparticles will be formed on the surface of the cell wall due to the confinement effect of KF template. After drying at $90^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ , carbonization at $850^{\\circ}\\mathrm{C}$ for $\\bar{1}.5\\mathrm{h}$ and the following facile grinding, carbon nanoflakes decorated with metal oxide nanoparticles can be obtained (Fig. 3a). Figure 3b–f shows the scanning electron microscopy (SEM) images of $\\mathrm{\\DeltaAl_{2}O_{3}/C,C e O_{2}/C,L a_{2}O_{3}/C,M g O/C}$ and $\\mathrm{CaO/C}$ nanocomposites, respectively. The composite remains the macromorphology of the original Kapok tree fibres, which have a unique hollow structure with a large lumen and a thin fibre wall. After simple grinding, the delicate carbon microtubes are converted to carbon nanoflakes (Fig. $3\\mathrm{g-k}$ and Supplementary Figs 7–9). \n\n![](images/81dbbab97ccc7566441e882b62df24e1015982835cda6e367e8d0a27ecc5d89a.jpg) \nFigure 2 | Adsorption test and relative models of sulfide species on the surface of metal oxides. (a) Digital images of the $\\mathsf{L i}_{2}\\mathsf{S}_{8}$ trapping by the metal oxide nanoparticles in DOL/DME (1:1, v-v) solution. (b) Experimental and simulated adsorption amount of $\\mathsf{L i}_{2}\\mathsf{S}_{8}$ on different metal oxides. The simulated adsorption was based on the monolayer adsorption model. (c) Optimized geometries of the most stable $\\mathsf{L i}_{2}\\mathsf{S}$ on ${\\mathsf{C e O}}_{2}(111)$ , $\\mathsf{A l}_{2}\\mathsf{O}_{3}(110)$ , $\\mathsf{L a}_{2}\\mathsf{O}_{3}(001)$ , ${\\cal M g}{\\cal O}(100)$ and CaO(100) surfaces. (d) Optimized geometries of most stable $\\mathsf{L i}_{2}\\mathsf{S}_{8}$ on the metal oxide surface. \n\n![](images/26966ec7b678e9359e76ffa35e022c916be52f4ae275529820587ab15794bb62.jpg) \nFigure 3 | Fabrication and microstructures of oxides/carbon nanostructures. (a) Schematic illustration of synthesis of oxides/carbon using the kapok tree fibres (KF) as both template and carbon sources. (b–f) SEM images of $A l_{2}O_{3}/C$ , ${\\mathsf{C e O}}_{2}/{\\mathsf{C}}$ , $\\mathsf{L a}_{2}\\mathsf{O}_{3}/\\mathsf{C}$ , $M g O/C$ and $\\mathsf{C a O/C}$ composites, respectively (scale bar $=50\\upmu\\mathrm{m}\\mathrm{\\'}$ ). $(\\pmb{\\mathsf{g}}\\mathbf{-}\\pmb{\\mathsf{k}})$ The corresponding TEM images of $A l_{2}O_{3}/C$ , ${\\mathsf{C e O}}_{2}/{\\mathsf{C}},$ , $\\mathsf{L a}_{2}\\mathsf{O}_{3}/\\mathsf{C}$ , $M g O/C$ and ${\\mathsf{C a O/C}}$ respectively (scale bar $=300{\\mathsf{n m}}.$ . $(1-p)$ The corresponding HRTEM images of ${\\mathsf{A l}}_{2}{\\mathsf{O}}_{3}/{\\mathsf{C}},$ $\\mathsf{C e O}_{2}/\\mathsf{C}$ , $\\mathsf{L a}_{2}\\mathsf{O}_{3}/\\mathsf{C}_{\\iota}$ $M g O/C$ and ${\\mathsf{C a O/C}}_{\\mathsf{.}}$ , respectively (scale bar $=3{\\mathsf{n m}}$ ). \n\nMoreover, transmission electron microscopy (TEM) images show that abundant oxide nanostructures are located on the carbon matrix (Fig. 3g–k). Figure 3l is the representative high resolution TEM (HRTEM) image of the $\\mathrm{\\bar{Al}}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ sample, showing the amorphous structure of ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ and partially graphitized structure of C. The interlayer spacing is about $0.35\\mathrm{nm}$ , corresponding to (002) planes of graphite. Figure $3\\mathrm{m}$ shows the [001] zone axis HRTEM image of a typical ${\\mathrm{CeO}}_{2}$ nanoparticle in $\\mathrm{CeO}_{2}/\\mathrm{C}$ composite. The lattice spacing of $0.19\\mathrm{nm}$ in Fig. $3\\mathrm{m}$ can be attributed to $\\{220\\}$ crystal planes of the face centred cubic (fcc) phase ${\\mathrm{CeO}}_{2}$ . The TEM image of $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ is showed in Fig. 3i, suggesting that abundant rod-shaped nanoparticles are distributed in the carbon matrix. The corresponding HRTEM image in Fig. 3n shows that the $\\mathrm{La}_{2}\\mathrm{O}_{3}$ particle is single crystalline. The lattice spacings (0.15 and $0.33\\mathrm{nm}\\mathrm{,}$ ) and the interplanar angle match the finger print of (004) and (100) planes of hexagonal phase $\\mathrm{La}_{2}\\mathrm{O}_{3}$ . HRTEM image of $\\mathrm{MgO/C}$ sample in Fig. 3o indicates lattice fringes with regular spacing of $0.25\\mathrm{nm}$ , which can be indexed to (111) planes of fcc $\\mathrm{\\bar{MgO}}$ . Figure 3p shows the HRTEM image of $\\mathrm{CaO/C}$ sample. The fringes with spacing of $0.27\\mathrm{nm}$ is corresponding to (111) planes of fcc CaO. These TEM results indicate that the Kapok tree fibre can act as ideal and general template for the synthesis of oxide nanostructures due to the confinement effect of fibre substrate. \n\nElectrochemical performance of composite cathodes. Thermal diffusion method was used to fabricate the sulfur $/\\mathrm{M}_{x}\\mathrm{O}_{y}/\\mathrm{C}$ composite19. The mass loading of the electrode ranges from 0.7 to $\\mathrm{\\hat{1}}.2\\mathrm{mg}\\mathrm{cm}^{-2}$ . The electrolyte was 1 M Lithium bis (trifluoromethanesulphonyl)imide in DOL and DME, with $\\mathrm{LiNO}_{3}$ as additive to passivate the lithium anode. Figure 4a shows the representative charge–discharge curves of the composite electrode based on different oxide/carbon nanostructures at a current rate of $0.1\\mathrm{C}$ $\\mathrm{1C=1,672mAg^{-1}};$ . All the discharge curves show two typical discharge plateaus at 2.35 and $2.10\\mathrm{\\bar{V}}$ , which can be assigned to the formation of high-order and loworder ${\\mathrm{Li}}_{2}{\\mathrm S}_{x},$ respectively9. No obvious difference can be found for the potential of the discharge plateaus. However, the $\\mathrm{CaO/C}$ and \n\n![](images/0a6364f1f01cacedbd26b770e1b36873ccb150c91b9b40385af67a930644a79e.jpg) \nFigure 4 | Charge–discharge curves and cycling performance of the sulfur composite electrodes. (a) Representative charge–discharge profiles of the composite electrodes based on different oxide/carbon nanostructures at 0.1 C. (b) Specific capacity and the corresponding Coulombic efficiency of the composite electrodes upon prolonged 300 charge–discharge cycles at $0.5\\mathsf{C}$ . \n\nC composite cathodes show higher charge over-potentials than those of $\\mathrm{CeO}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C},$ $\\bar{\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}}$ and $\\mathrm{MgO/C}$ composite electrodes (Fig. 4a). The specific discharge capacities of $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}_{:}$ $\\mathrm{CeO}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{{O}}_{3}/\\mathrm{{C}},$ $\\mathrm{MgO/C}$ , $\\mathrm{CaO/C}$ and $\\mathsf{C}$ at $0.1\\mathrm{C}$ rate are measured to be 1,330, 1,388, 1,345, 1,368, 1,246 and $1,230\\mathrm{mAhg}^{-1}$ , respectively (Fig. 4a). It can be found that the $\\mathrm{CaO/C}$ and C composite cathodes show relatively lower discharge capacity. The high over-potential and low discharge capacity may result from the serious dissolution of $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ in electrolyte (shuttle effect), which causes the active material loss and the increase of electrolyte viscosity. ICP-OES test (Supplementary Table 2) based on the same mass of ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}/{\\mathrm{C}},$ ${\\mathrm{CeO}}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ , $\\mathrm{MgO/C}$ , $\\mathrm{CaO/C}$ and C samples reveal that both $\\mathrm{CaO/C}$ and C have poorer $\\mathrm{Li}_{2}\\mathrm S_{x}$ capture capability compared with other samples. \n\nBesides the specific capacity, cycling performance is one of the most important characteristics for Li–S batteries. Therefore, all the cathodes were subject to prolonged cycling. Figure 4b shows the discharge capacity and the corresponding Coulombic efficiency of the cathodes upon prolonged 300 cycles at $0.5\\mathrm{C}$ . The representative charge/discharge curves (Fig. 4a) and the cycling performance (Fig. 4b) indicate that ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}/{\\mathrm{C}},$ ${\\mathrm{CeO}}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ and $\\mathrm{MgO/C}$ composite electrode show high specific capacity in the first several cycles. However, the composite electrodes show distinct capacity retention capability. The ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}/{\\mathrm{C}},$ $\\mathrm{CaO/C}$ and C cathodes exhibit obvious capacity fading especially in the first 100 cycles. Compared with $\\mathrm{Al}_{2}\\mathrm{{O}}_{3}/\\mathrm{{C}},$ , $\\mathrm{CaO/\\bar{C}}$ and C cathodes, the electrode based on ${\\mathrm{CeO}}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ and $\\mathrm{MgO/C}$ show better cycling performance and the $\\mathrm{MgO/C}$ cathode is the best among all the samples. The capacity decay per cycle is 0.171, 0.066, 0.047, 0.034, 0.136 and $0.170\\%$ for $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\bar{\\mathrm{C}}.$ , $\\mathrm{CeO}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C},$ $\\mathrm{MgO/C},$ $\\mathrm{CaO/C}$ and $\\mathrm{C}_{:}$ , respectively. Considering the serious capacity, decay mainly happens in the first 50 cycles, the average Columbic efficiency in the first 100 cycles was calculated (Fig. 4b). $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}.$ , ${\\mathrm{CeO}}_{2}/{\\mathrm{C}},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ , ${\\mathrm{MgO/C}}_{\\mathrm{:}}$ , CaO/C and C cathodes show 99.6, 99.1, 98.7, 99.4, 98.3 and $98.8\\%$ columbic efficiency. Lower Columbic efficiency of Li–S batteries resulted from the significant $\\operatorname{Li}_{2}\\mathsf{S}_{x}$ dissolution, which cause the loss of S material and shuttle effect19. This can be also supported by the ICP-OES results, revealing that $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ has the best capture capability and $\\mathrm{CaO/C}$ and C have poorer capture capability for $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ (Supplementary Table 2). Although $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ cathodes possess high initial discharge capacity and good Columbic efficiency, the rate of capacity decay is higher than those of ${\\mathrm{CeO}}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ and $\\mathrm{MgO/C}$ cathodes. The distinct Columbic efficiency for $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ $(99.6\\%)$ cathode from both $\\mathrm{CaO/C}$ $(98.3\\%)$ and C $(98.8\\%)$ cathodes may imply different capacity decay mechanism. \n\nAnalysis of capacity failure mechanism of composite cathodes. In order to further reveal the detailed capacity decay mechanism, some batteries were disassembled after 100 cycles at $0.5\\mathrm{C}$ to observe the morphology evolution of the cathode materials by SEM. Figure 5a–f shows low magnification SEM images of the cycled electrodes based on $\\mathrm{Al}_{2}\\mathrm{O}_{3}\\bar{/}\\mathrm{C},$ $\\mathrm{CeO}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C},$ $\\mathrm{MgO/C},$ $\\dot{\\mathrm{CaO}}/\\mathrm{C}$ and C nanostructures, respectively. In contrast to $\\mathrm{CeO}_{2}/\\mathrm{C}$ (Fig. 5b), $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ (Fig. 5c) and $\\mathrm{MgO/C}$ (Fig. 5d) electrodes with uniform and flat surface, the $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ (Fig. 5a), $\\mathrm{CaO/C}$ (Fig. 5e) and C (Fig. 5f) cathodes show high surface roughness. Some carbon nanoflakes with well-defined profile can be observed on the surface of the $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ (Fig. 5a), $\\mathrm{CaO/C}$ (Fig. 5e) and C (Fig. 5f) cathodes after 100 cycles. In addition, some cracks and pinholes can be found in the $\\mathrm{CaO/C}$ and carbon cathodes, which may result from the significant dissolution and loss of sulfur. Figure $5\\mathrm{g-l}$ and $\\mathrm{m-r}$ shows the top-view and cross-sectional SEM images of cycled ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}/{\\mathrm{C}},$ ${\\mathrm{CeO}}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ , ${\\mathrm{MgO/C}},$ CaO/C and C cathodes, respectively. Only a thin, uniform and dense $\\mathrm{Li}_{2}\\mathrm{S}$ film can be found on the surface of $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ (Fig. ${5}\\mathrm{g,m})$ . Abundant $\\mathrm{Li}_{2}\\mathrm S$ particles with irregular shape were formed between the $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ nanoflakes (Supplementary Fig. 1). Similar phenomenon can also be found in the $\\bar{\\mathrm{CaO}}/\\mathrm{C}$ (Fig. $5\\mathrm{k,q}$ ) and C (Fig. $^{51,\\mathrm{r}}$ cathodes. Some characteristic stripes (Fig. $^{5\\mathrm{kJ}}$ ) and distinct fracture surface (Fig. $\\mathrm{5q,r}\\mathrm{\\\"}$ indicate that the $\\mathrm{Li}_{2}\\mathrm S$ particles are detached from the oxides/C matrix and may become electrochemically inactive. This is due to the uncontrollable precipitation of $\\mathrm{Li}_{2}\\mathrm{S}$ on the non-polar or weakly polar surface6, which leads the further decay of capacity. In contrast, it is not easy to identify the oxide/carbon nanoflakes from the $\\mathrm{CeO}_{2}/\\mathrm{C}$ (Fig. 5h), $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ (Fig. 5i) and $\\mathrm{MgO/C}$ (Fig. 5j) cathodes. To obtain the cross-sectional morphology of the cathodes, the electrode materials were scraped from the Al foil current collector and mounted on a copper foil with rough surface for SEM observation. $\\mathrm{CeO}_{2}/\\mathrm{C}$ (Fig. 5n), $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ (Fig. 5o) and $\\mathrm{MgO/C}$ (Fig. 5p) nanoflakes were wrapped by thick $\\mathrm{Li}_{2}\\mathrm S$ layer. Supposing that the average thickness of carbon nanoflakers is $450\\mathrm{nm}$ , the thickness of $\\mathrm{Li}_{2}\\mathrm{S}$ layer deposited on the surface of $\\mathrm{CeO}_{2}/\\mathrm{C},$ $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ and $\\mathrm{MgO/C}$ will be 1,400, 1,677 and $1,573\\mathrm{nm}$ , respectively. After mechanical scrapping and mounting processes, no detachment can be observed, indicating that there is good cohesion between the $\\operatorname{Li}_{2}S$ layer and the oxide/C nanoflakes. These results are consistent with our DFT calculation results in Fig. 2. Because the $\\mathrm{Li}_{2}S$ is a poor ionic and electronic conductor, the good combination of $\\mathrm{Li}_{2}\\mathrm{S}$ with the conductive matrix must be favourable for the reversible electrochemical reaction in the following charging process4. Therefore, the better cycling performance of ${\\mathrm{CeO}}_{2}/\\mathrm{C},$ $\\bar{\\mathrm{La}}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ and $\\mathrm{MgO/C}$ cathodes can be attributed to the controllable precipitation of $\\mathrm{Li}_{2}\\mathrm{S}$ on the polar surface of carbon matrix. \n\n![](images/83555de6304c6defaa427a5913be57b66bd6415fd4c5054bf1ed4ea9a83bf024.jpg) \nFigure 5 | Morphology of the discharged composite electrodes after cycling. (a–f) SEM images of the cycled composite electrodes based on ${\\sf A l}_{2}{\\sf O}_{3}/{\\sf C},$ ${\\mathsf{C e O}}_{2}/{\\mathsf{C}}$ , $\\mathsf{L a}_{2}\\mathsf{O}_{3}/\\mathsf{C}$ , MgO/C, CaO/C and carbon nanostructures, respectively. $(\\pmb{\\mathsf{g}}\\pmb{\\mathsf{1}})$ Top view and $(\\pmb{\\m}\\mathbf{m}-\\pmb{\\mathsf{r}})$ cross-sectional SEM images show typical ${\\sf A l}_{2}{\\sf O}_{3}/{\\sf C},$ ${\\mathsf{C e O}}_{2}/{\\mathsf{C}},$ $\\mathsf{L a}_{2}\\mathsf{O}_{3}/\\mathsf{C}_{1}$ $M g O/C,$ , CaO/C and C nanostructures after cycling, respectively. Scale bars $=10\\upmu\\mathrm{m}$ $(\\mathsf{a}\\mathsf{-}\\dagger)$ and ${\\sf1}\\upmu\\sf{m}\\left(\\pmb{g}\\cdot\\pmb{r}\\right)$ . \n\n![](images/c898668cd0f42361c3d3e3e950bd69eaf08d6cec9e0ffc48e83fc6487ce08f22.jpg) \nFigure 6 | Lithium ion diffusion properties of the electrode at various voltage scan rates. Plot of CV peak current of $\\mathbf{\\eta}(\\mathbf{a})$ the cathodic reaction 1 $(\\mathsf{S}_{8}\\to\\mathsf{L i}_{2}\\mathsf{S}_{4})$ , (b) the cathodic reaction 2 $(\\mathsf{L i}_{2}\\mathsf{S}_{4}\\to\\mathsf{L i}_{2}\\mathsf{S})$ , (c) the anodic reaction 1 $\\mid(\\mathsf{L i}_{2}\\mathsf{S}\\rightarrow\\mathsf{L i}_{2}\\mathsf{S}_{4})$ and (d) the anodic reaction 2 $(\\mathsf{L i}_{2}\\mathsf{S}_{4}\\to\\mathsf{S}_{8})$ versus the square root of scan rates. \n\nBy now, some important questions arise: why $\\mathrm{Li}_{2}\\mathrm S$ shows different deposition behaviour on various oxide/C surfaces? Which kind of oxide/C surface is favourable for the controllable precipitation of $\\mathrm{Li}_{2}\\mathrm{S}\\?$ Because the nucleation and initial growth sites of $\\mathrm{Li}_{2}\\mathrm{S}$ are located on the surface of oxide/C, the growth behaviour of $\\mathrm{Li}_{2}\\mathrm S$ must be related to surface chemical properties of oxide/C matrix. First, the oxide/C surface should absorb highorder $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ owing to its strong adsorption ability (Fig. 2d), which acts as the sulfur source for the growth of $\\mathrm{Li}_{2}\\mathrm S$ . The absorbed $\\mathrm{Li}_{2}\\mathrm S_{x}$ must be transferred from the oxide surface to conductive carbon surface to enable the electrochemical reactions due to the insulating properties of these metal oxides. Therefore, the distribution and structure of $\\mathrm{Li}_{2}\\mathrm S$ will be affected by the surface diffusion properties of $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ species on the oxide/C substrate. \n\nLithium ion diffusion properties and mechanism of the cathodes. Although it is very difficult to get the diffusivity of $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ on the oxide surface from the electrochemical measurement, the lithium diffusivity in the whole Li–S batteries can offer the important information about $\\mathrm{Li}_{2}\\mathrm S_{x}$ surface diffusion because of that the most favourable binding site of sulfides is two Li atoms bonding with metal oxide (Fig. $^{2\\mathrm{c},\\mathrm{d}},$ ). In order to explore the lithium diffusion properties, we performed cyclic voltammetry (CV) measurements under different scanning rates ranging from 0.2 to $0.5\\mathrm{mVs^{-1}}$ . As shown in Fig. 6, all cathodic and anodic peak currents are linear with the square root of scan rates, from which the lithium diffusion performance can be estimated using the classical Randles Sevcik equation44: \n\n$$\nI_{\\mathrm{p}}=\\left(2.69{\\times}10^{5}\\right)n^{1.5}a D^{0.5}C\\nu^{0.5}\\Delta C_{\\mathrm{o}},\n$$ \n\nwhere, $I_{\\mathrm{p}}$ is the peak current, $n$ is the number of electrons per reaction species, $^a$ is the active electrode area, $D$ is the lithium ion diffusion coefficient, $\\Delta C_{\\mathrm{o}}$ is the Li concentration change corresponding to the electrochemical reaction. The $n$ , a and $\\bar{\\Delta}C_{\\mathrm{o}}$ are constant in our battery system. The slopes of curves in Fig. 6a–d are positively correlated to the corresponding lithium ion diffusion, which indicates that the sulfur composite cathode based on both $\\mathrm{CaO/C}$ and C have lower diffusivity. Abundant high viscosity $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ dissolved in the electrolyte and the poor $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ capture capability of both $\\mathrm{CaO/C}$ and C is believed to be the main reason for their low diffusivity. Compared with $\\mathrm{CaO/C}$ , $\\mathrm{CeO}_{2}/\\mathrm{C},$ $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ and C electrodes, $\\mathrm{La}_{2}\\mathrm{O}_{3}^{-}/\\mathrm{C}$ and $\\mathrm{MgO/C}$ samples show better diffusion properties and the measured diffusivity of $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ cathode is comparable with the $\\mathrm{CeO}_{2}/\\mathrm{C}$ . \n\nThe diffusion of lithium on the surface of various metal oxides has been investigated by the DFT calculation (Fig. 7). Because the most favourable binding site of sulfides is two Li atoms bonding with metal oxide (Fig. 2c,d), the calculated Li ion diffusion can also indicate the diffusivity of sulfides species on the surface of the oxide. On $\\mathrm{{MgO}(100)}$ , CaO(100) and $\\mathrm{\\bar{L}a}_{2}\\mathrm{O}_{3}(001)$ surfaces, the diffusions of Li in different dimensions can be realized on three equivalent adsorption sites (Fig. 7). Among the three kinds of surfaces, the diffusion barrier of Li on $\\dot{\\mathrm{CaO}}(100)$ is largest. The space group of $\\mathrm{MgO}$ is same with $\\mathrm{CaO}$ , however, the diffusion barrier of Li on $\\mathrm{{MgO(100)}}$ is about $0.45\\mathrm{eV}$ lower than that on $\\mathrm{CaO}(100)$ . The suitable adsorption energies of sulfide species and small diffusion barriers of Li on $\\mathrm{MgO}$ will lead to the formation of abundant $\\mathrm{Li}_{2}\\mathrm S$ particles on $\\mathrm{MgO/C}$ surfaces, which are responsible for the best cycling performance of $\\mathrm{MgO/C}$ cathodes. On $\\mathrm{CeO}_{2}(111)$ surfaces, the large diffusion barrier is $0.66\\mathrm{eV}$ , which is similar with that on $\\mathrm{La}_{2}\\mathrm O_{3}(001)$ surfaces. This may explain why $\\mathrm{CeO}_{2}/\\mathrm{C}$ and $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ cathodes show similar cycling performance. Among the five kinds of metal oxides surfaces, the largest diffusion barrier $(1.22\\mathrm{eV})$ of Li is found to be on $\\mathrm{Al}_{2}\\mathrm{O}_{3}(110)$ , which is about three times of that on $\\mathrm{{MgO}(100)}$ . It is seen that sulfide species can strongly adsorb, however, difficult to diffuse on $\\mathrm{Al}_{2}\\mathrm{\\bar{O}}_{3}$ . Although $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ has the strongest $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ adsorption (Fig. 2), the slow diffusion of $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ indicated that $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ may not be a good additive for sulfur cathode. \n\n# Discussion \n\nBased on our experimental results, we clarify three functions of these oxides. The first basic function of these metal oxides is the $\\mathrm{Li}_{2}\\mathrm S_{x}$ adsorption. Although many literatures have reported the $\\mathrm{Li}_{2}\\mathrm{S}_{x}$ capture capacities, the detailed absorption mechanism is still unclear. Our DFT calculation and temperature swing adsorption experiments (Fig. 2) confirm that the monolayer chemisorption is dominant during the $\\mathrm{Li}_{2}\\mathrm S_{x}$ capture. The second function of these metal oxides, especially some nonconductive oxides, is the $\\mathrm{Li}_{2}\\mathrm S_{x}$ transfer station, which transports the $\\mathrm{Li}_{2}\\mathrm S_{x}$ from the poorly conductive oxide surface to high conductive carbon matrix to ensure the full electrochemical conversion. The third function is to induce the controlled growth of $\\mathrm{Li}_{2}\\mathrm{S}$ species on the surface of the composite instead of random deposition. Many reports proved that the uncontrolled deposition will result in electrochemically inactive large agglomerations of $\\mathrm{Li}_{2}\\mathrm S$ . The subsequent detachment of $\\mathrm{Li}_{2}S$ from the oxide/carbon matrix is the main capacity decay mechanism, which can be supported by the SEM observation in Fig. 5. The SEM observations, diffusion test and DFT calculations revealed that the deposition of $\\mathrm{Li}_{2}\\mathrm S$ on the surface of oxide/carbon matrix may be influenced by the lithium ion diffusion properties on the surface of metal oxides, which has not yet been identified. Surface diffusion properties will affect the distribution and growth of $\\mathrm{Li}_{2}\\mathrm S$ . \n\nBased on these functions of nonconductive metals oxides, we can propose an oxide selection criterion for the Li–S batteries. \n\n![](images/bc95462043d5400daaff220cf013ed272c6f7b8d40890045ebddea08948e940e.jpg) \nFigure 7 | Lithium diffusion mechanism on the surface of various metal oxides. (a–e) Minimum energy path for lithium ion diffusion on $\\mathsf{A l}_{2}\\mathsf{O}_{3}(110),$ ${\\mathsf{C e O}}_{2}$ (111), $\\mathsf{L a}_{2}\\mathsf{O}_{3}(001)$ , ${\\cal M g}{\\sf O}(100)$ and CaO(100) surfaces, respectively. (f) Potential energy profiles for ${\\mathsf{L i}}^{+}$ diffusion along different adsorption sites on the oxide surface. \n\nBecause the first role of oxides is adsorption, the binding between the sulfides species and the matrix should be strong, which can both suppress the shuttle effect and enable the full utilization of active materials. Considering that the $\\mathrm{Li}_{2}\\mathrm S_{x}$ capture is the monolayer chemisorption and the adsorption amount will depend on the surface area of oxides, uniformly distributed oxides nanostructures with high surface area are essential. Although strong binding and high surface area are preconditions, the surface diffusion properties of oxides are also very important, which affect the distribution and structure of $\\mathrm{Li}_{2}\\mathrm S$ . An optimized balance between $\\mathrm{Li}_{2}\\mathrm S_{x}$ adsorption and surface diffusion is favourable for the sulfide species to deposit on the surface of oxide/carbon matrix, keep active during the cycling and ensure the final good cycling performance of batteries. In addition, some other factors such as electric conductivities, chemical stability and lithiation/delithiation of the oxides also need to be considered. \n\nIn conclusion, a series of nonconductive metal oxides $\\mathrm{(MgO;}$ $\\mathrm{Al}_{2}\\mathrm{O}_{3},\\mathrm{CeO}_{2},\\mathrm{La}_{2}\\mathrm{O}_{3}$ and $\\mathrm{CaO}_{\\cdot}^{\\cdot}$ ) nanoparticles anchored on porous carbon nanoflakes have been synthesized successfully via a facile and generic biotemplating method using Kapok trees fibres as both the template and the carbon source. The composite cathode materials based on the $\\mathrm{MgO/C}$ , $\\mathrm{La}_{2}\\mathrm{O}_{3}/\\mathrm{C}$ and $\\mathrm{CeO}_{2}/\\mathrm{C}$ nanoflakes show higher capacity and better cycling performance. Moreover, the working mechanisms of these oxides were revealed by adsorption test, microstructure analysis, electrochemical performance evaluation and DFT calculations. In addition, the comprehensive oxide selection criteria referring to the strong binding, high surface area and good surface diffusion properties were proposed for the first time. We believe that our proposed selection criteria can be generalized to other matrix materials for high performance Li–S batteries such as metal sulfides, metal nitrides, metal chlorides, and so on. \n\n# Methods \n\nPreparation of metal oxide nanoparticles. A generic Pechini sol–gel method13 was used to synthesize the pure metal oxides. $0.01\\mathrm{mol}$ metal nitrates of the desired metals were dissolved in $5\\mathrm{ml}$ of deionized water under stirring. $0.015\\mathrm{mol}$ citric acid was then added in to the prepared solution to chelate the metal ions and heated to $200^{\\circ}\\mathrm{C}$ to form a dry and porous gel. After the calcination of the gel at $850^{\\circ}\\mathrm{C}$ for $^{\\mathrm{1h,}}$ pure metal oxide ${\\mathrm{.Al}}_{2}{\\mathrm{O}}_{3}$ , $\\mathrm{CeO}_{2}$ , $\\mathrm{La}_{2}\\mathrm{O}_{3}$ , MgO and CaO) nanoparticles were obtained. \n\nBiotemplated fabrication of metal oxide/carbon nanoflakes. Owing to the poor electric conductivity of ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ , $\\mathrm{CeO}_{2}.$ , $\\mathrm{La}_{2}\\mathrm{O}_{3}$ , MgO and CaO, a series or metal oxide decorated porous carbon flakes were fabricated using the Kapok tree fibres as both the template and the carbon sources. To start with, $0.01\\mathrm{mol}$ metal nitrates of the desired metals were dissolved in $40\\mathrm{ml}$ of deionized water to form transparent solution. Commercial Kapok tree fibre was washed with acetone and ethanol to remove the surface wax and dipped in to the nitrate solution. After $^{2\\mathrm{h}}$ soaking, the nitrate loaded fibres were separated from the solution and introduced into ammonia atmosphere to ensure the formation of the metal hydroxides, followed by the drying at $100^{\\circ}\\mathrm{C}$ for $\\mathrm{10h}$ to remove the water. Then the dried fibres were inserted into the tube furnace and calcined at $850^{\\circ}\\mathrm{C}$ for $^{\\textrm{\\scriptsize1h}}$ with $100\\mathrm{sccm}$ continuous flow of argon. After cooling, the obtained carbon microtubes remaining the macromorphology of original Kapok tree fibres were easily grinded into carbon nanoflakes decorated with metal oxide nanoparticles. \n\nAdsorption test. To prepare $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ solution, stoichiometric $\\mathrm{Li}_{2}\\mathrm S$ and sulfur were dissolved in 1,3-dioxolane/1,2-dimethoxyethane solution (1:1 in volume) and stirred at $80^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . Then the $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ solution was diluted to $0.005\\mathrm{M}$ for the capture test. Before the adsorption test, all the oxide and oxide/carbon samples were dried under vacuum at $80^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . After the immersion of the samples in $0.005\\mathrm{M}\\mathrm{Li}_{2}\\mathrm{S}_{8}$ at different temperatures, $20\\upmu\\mathrm{l}$ of the solution was transferred for the ICP-OES test45. \n\nCharacterization. The morphology and the microstructure were studied using SEM (FEI, XL30 Sirion) and TEM (FEI, Tecnai G2 F20 X-TWIN). The specific surface area was characterized from nitrogen adsorption–desorption measurement (Micromeritics, ASAP 2020). ICP-OES was conducted using a Thermo Scientific ICAP 6300 Duo View Spectrometer. \n\nElectrochemical measurements. The sulfur cathode materials were prepared via a facile thermal diffusion method19. First, sulfur and grinded oxide/carbon nanoflakes with a weight ratio of 1:3 were mixed with appropriate amount of $\\mathrm{CS}_{2}$ solution. After the evaporation of $\\mathrm{CS}_{2}$ , the mixture were pressed and heated at $155^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ under vacuum to obtain the composite cathode materials. To fabricate the 2,023 type coin cells for the electrochemical measurements, the synthesized composites were grinded again and mixed with conductive carbon black and polyvinylidene fluoride binder in N-methyl-2-pyrrolidinone (70:20:10 by weight) to form a slurry. After a $^{12\\mathrm{h}}$ magnetic stirring, the slurry was coated onto the aluminium foil and dried overnight at $60^{\\circ}\\mathrm{C}$ under vacuum. The sulfur content was in the range of $63\\mathrm{-}70\\mathrm{wt\\%}$ and the mass loading of the electrodes ranges from 0.7 to $1.2\\mathrm{mg}\\mathrm{cm}^{-2}$ . 1 M lithium bis(trifluoromethanesulphonyl)imide dissolved in a mixture of 1,3-dioxolaneand dimethoxymethane (1:1 by volume) with $0.1\\mathrm{{M}}$ $\\mathrm{LiNO}_{3}$ additive was used as the electrolyte. Galvanostatic cycling was performed on Arbin or MTI testers with the potential range of $1.8\\substack{-2.6\\mathrm{V}}$ versus $\\mathrm{Li/Li^{+}}$ at ambient temperature. \n\nDFT calculations. All calculations were performed using the Vienna ab initio Simulation Package code46 based on density functional theory. The projector augmented wave potentials were used to describe the interaction between ions and electrons47,48. Nonlocal exchange correlation energy was evaluated using the Perdew-Burke-Ernzehof functional. The electron wave function was expanded using plane waves with an energy cutoff of $400\\mathrm{eV}$ . All structures were optimized with force convergence criterion of $10\\mathrm{meV}\\mathrm{\\AA}^{-1}$ . All oxide surfaces were created based on the corresponding optimized bulk unit cell, which were in good agreement with the experimental values. A $4\\times4\\times1$ Monkhorst–Pack k-point mesh and a vacuum slab of about $15\\mathrm{\\AA}$ was inserted between the surface slabs for all the metal oxide models. The cell parameter is $8.40\\times8.07\\times25.00\\mathring{\\mathrm{A}}$ for $\\mathrm{Al}_{2}\\mathrm{O}_{3}(110)$ , $11.67\\times11.67\\times22.94\\mathring{\\mathrm{A}}$ for $\\mathrm{CeO}_{2}(111)$ , $11.82\\times11.82\\times25.00\\mathrm{\\AA}$ for $\\mathrm{La}_{2}\\mathrm O_{3}(001)$ , $8.99\\times8.99\\times20.00\\mathring\\mathrm{A}$ for $\\mathrm{MgO}(100)$ and $10.25\\times10.25\\times20.00{\\AA}$ for CaO(100). $\\mathrm{DFT}+U$ approach, where $U$ is an empirical parameter for on site electronic correlations, was used in the calculation of $\\mathrm{CeO}_{2}(111)$ with a $U$ value of $5.0\\mathrm{eV}$ (ref. 49). The adsorption energies $\\left(E_{\\mathrm{a}}\\right)$ for S and $\\mathrm{Li}_{2}\\mathrm S$ on the metal oxide surfaces are defined as $E_{\\mathrm{a}}=E_{\\mathrm{total}}–E_{\\mathrm{ads}}–E_{\\mathrm{suf}},$ where $E_{\\mathrm{total}}$ is the total energy of the adsorbed system, $E_{\\mathrm{ads}}$ is the energy of the adsorbate in vacuum and $E_{\\mathrm{suf}}$ is the energy of the optimized clean surface slab. \n\n# References \n\n1. Bruce, P. G., Freunberger, S. A., Hardwick, L. J. & Tarascon, J. M. Li- ${\\bf\\cal O}_{2}$ and Li-S batteries with high energy storage. Nat. Mater. 11, 19–29 (2012). \n2. Yamin, H., Gorenshtein, A., Penciner, J., Sternberg, Y. & Peled, E. Lithium sulfur battery-oxidation reduction-mechanisms of polysulfides in the solutions. J. Electrochem. Soc. 135, 1045–1048 (1988). \n3. Ji, X. L., Lee, K. T. & Nazar, L. F. A highly ordered nanostructured carbonsulphur cathode for lithium-sulphur batteries. Nat. Mater. 8, 500–506 (2009). \n4. Yao, H. B. et al. Improving lithium–sulphur batteries through spatial control of sulphur species deposition on a hybrid electrode surface. Nat. Commun. 5, 3943 (2014). \n5. Su, Y. S. & Manthiram, A. Lithium-sulphur batteries with a microporous carbon paper as a bifunctional interlayer. Nat. Commun. 3, 1166 (2012). \n6. Seh, Z. W. et al. Sulphur- $\\cdot\\mathrm{TiO}_{2}$ yolk-shell nanoarchitecture with internal void space for long-cycle lithium-sulphur batteries. Nat. Commun. 4, 1331 (2013). \n7. Guo, J. C., Xu, Y. H. & Wang, C. S. Sulfur-impregnated disordered carbon nanotubes cathode for lithium-sulfur batteries. Nano Lett. 11, 4288–4294 (2011). \n8. Demir-Cakan, R. et al. Li-S batteries: simple approaches for superior performance. Energy Environ. Sci. 6, 176–182 (2013). \n9. Yang, Y., Zheng, G. Y. & Cui, Y. Nanostructured sulfur cathodes. Chem. Soc. Rev. 42, 3018–3032 (2013). \n10. Zhou, G. M. et al. A graphene-pure-sulfur sandwich structure for ultrafast, long-life lithium-sulfur batteries. Adv. Mater. 26, 625–631 (2014). \n11. Kim, J. S., Hwang, T. H., Kim, B. G., Min, J. & Choi, J. W. A lithium-sulfur battery with a high areal energy density. Adv. Funct. Mater. 24, 5359 (2014). \n12. Zhang, Y. G., Zhao, Y., Yermukhambetova, A., Bakenov, Z. & Chen, P. Ternary sulfur/polyacrylonitrile $\\mathrm{\\primeMg_{0.6}N i_{0.4}O}$ composite cathodes for high performance lithium/sulfur batteries. J. Mater. Chem. A 1, 295–301 (2013). \n13. Tao, X. Y. et al. Highly mesoporous carbon foams synthesized by a facile, costeffective and template-free Pechini method for advanced lithium-sulfur batteries. J. Mater. Chem. A 1, 3295–3301 (2013). \n14. Zhou, G. M. et al. A flexible sulfur-graphene-polypropylene separator integrated electrode for advanced Li-S batteries. Adv. Mater. 27, 641–647 (2015). \n15. Wang, J., He, Y.-S. & Yang, J. Sulfur-based composite cathode materials for high-energy rechargeable lithium batteries. Adv. Mater. 27, 569–575 (2015). \n16. Liang, X. et al. A highly efficient polysulfide mediator for lithium-sulfur batteries. Nat. Commun. 6, 5682 (2015). \n17. Zhao, M.-Q. et al. Unstacked double-layer templated graphene for high-rate lithium-sulphur batteries. Nat. Commun. 5, 3410 (2014). \n18. Wang, Z. et al. Enhancing lithium-sulphur battery performance by strongly binding the discharge products on amino-functionalized reduced graphene oxide. Nat. Commun. 5, 5002 (2014). \n19. Tao, X. Y. et al. Strong sulfur binding with conducting Magneli-phase $\\mathrm{Ti}_{\\mathrm{n}}\\mathrm{O}_{2\\mathrm{n}-1}$ nanomaterials for improving lithium-sulfur batteries. Nano Lett. 14, 5288–5294 (2014). \n20. Seh, Z. W. et al. Two-dimensional layered transition metal disulphides for effective encapsulation of high-capacity lithium sulphide cathodes. Nat. Commun. 5, 5017 (2014). \n21. Qiu, Y. C. et al. High-rate, ultra long cycle-life lithium/sulfur batteries enabled by nitrogen-doped graphene. Nano Lett. 14, 4821–4827 (2014). \n22. Huang, C. et al. Manipulating surface reactions in lithium-sulphur batteries using hybrid anode structures. Nat. Commun. 5, 3015 (2014). \n23. Suo, L., Hu, Y.-S., Li, H., Armand, M. & Chen, L. A new class of Solvent-in-Salt electrolyte for high-energy rechargeable metallic lithium batteries. Nat. Commun. 4, 1481 (2013). \n24. Kim, H., Lee, J., Ahn, H., Kim, O. & Park, M. J. Synthesis of threedimensionally interconnected sulfur-rich polymers for cathode materials of high-rate lithium-sulfur batteries. Nat. Commun. 6, 7278 (2015). \n25. Chen, H. W. et al. Monodispersed sulfur nanoparticles for lithium sulfur batteries with theoretical performance. Nano Lett. 15, 798–802 (2015). \n26. Chen, H. W. et al. Rational design of cathode structure for high rate performance lithium-sulfur batteries. Nano Lett. 15, 5443–5448 (2015). \n27. Wang, B., Alhassan, S. M. & Pantelides, S. T. Formation of large polysulfide complexes during the lithium-sulfur battery discharge. Phys. Rev. Appl. 2, 034004 (2014). \n28. Mikhaylik, Y. V. & Akridge, J. R. Polysulfide shuttle study in the Li/S battery system. J. Electrochem. Soc. 151, A1969–A1976 (2004). \n29. Wang, H. L. et al. Graphene-wrapped sulfur particles as a rechargeable lithiumsulfur battery cathode material with high capacity and cycling stability. Nano Lett. 11, 2644–2647 (2011). \n30. Yang, Y. et al. Improving the performance of lithium-sulfur batteries by conductive polymer coating. ACS Nano. 5, 9187–9193 (2011). \n31. Tao, X. Y. et al. Decoration of sulfur with porous metal nanostructures: an alternative strategy for improving the cyclability of sulfur cathode materials for advanced lithium-sulfur batteries. Chem. Commun. 49, 4513–4515 (2013). \n32. Cheon, S. E. et al. Rechargeable lithium sulfur battery—II. Rate capability and cycle characteristics. J. Electrochem. Soc. 150, A800–A805 (2003). \n33. Yang, Y. et al. New nanostructured $\\mathrm{Li}_{2}\\mathrm S/$ silicon rechargeable battery with high specific energy. Nano Lett. 10, 1486–1491 (2010). \n34. Zheng, G. Y. et al. Amphiphilic surface modification of hollow carbon nanofibers for improved cycle life of lithium sulfur batteries. Nano Lett. 13, 1265–1270 (2013). \n35. Li, W. Y. et al. Understanding the role of different conductive polymers in improving the nanostructured sulfur cathode performance. Nano Lett. 13, 5534–5540 (2013). \n36. Zhou, W. D., Xiao, X. C., Cai, M. & Yang, L. Polydopamine-coated, nitrogendoped, hollow carbon sulfur double-layered core-shell structure for improving lithium sulfur batteries. Nano Lett. 14, 5250–5256 (2014). \n37. Wang, C. et al. Macroporous free-standing nano-sulfur/reduced graphene oxide paper as stable cathode for lithium-sulfur battery. Nano Energy 11, 678–686 (2015). \n38. Zhou, G. M., Paek, E., Hwang, G. S. & Manthiram, A. Long-life Li/polysulphide batteries with high sulphur loading enabled by lightweight three-dimensional nitrogen/sulphur-codoped graphene sponge. Nat. Commun. 6, 7760 (2015). \n39. Zheng, J. M. et al. Lewis acid-base interactions between polysulfides and metal organic framework in lithium sulfur batteries. Nano Lett. 14, 2345–2352 (2014). \n40. Zhou, G. M., Zhao, Y. B. & Manthiram, A. Dual-confined flexible sulfur cathodes encapsulated in nitrogen-doped double-shelled hollow carbon spheres and wrapped with graphene for Li-S batteries. Adv. Energy Mater. 5, 1402263 (2015). \n41. Dong, K., Wang, S. P., Zhang, H. Y. & Wu, J. P. Preparation and electrochemical performance of sulfur-alumina cathode material for lithium-sulfur batteries. Mater. Res. Bull. 48, 2079–2083 (2013). \n42. Sun, F. G. et al. A high-rate lithium-sulfur battery assisted by nitrogen-enriched mesoporous carbons decorated with ultrafine $\\mathrm{La}_{2}\\mathrm{O}_{3}$ nanoparticles. J. Mater. Chem. A 1, 13283–13289 (2013). \n43. Chaiarrekij, S., Apirakchaiskul, A., Suvarnakich, K. & Kiatkamjornwong, S. Kapok I: characteristcs of Kapok fiber as a potential pulp source for papermaking. Bioresources 7, 475–488 (2012). \n44. Li, P. et al. Lithium sodium vanadium phosphate and its phase transition as cathode material for lithium ion batteries. Electrochim. Acta 180, 120–128 (2015). \n45. Diao, Y., Xie, K., Xiong, S. & Hong, X. Analysis of polysulfide dissolved in electrolyte in discharge-charge process of Li-S battery. J. Electrochem. Soc. 159, A421–A425 (2012). \n46. Kresse, G. & Furthmuller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, \n15–50 (1996). \n47. Blochl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n48. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n49. Nolan, M., Parker, S. C. & Watson, G. W. The electronic structure of oxygen vacancy defects at the low index surfaces of ceria. Surf. Sci. 595, \n223–232 (2005). \n\n# Acknowledgements \n\nY.C. acknowledges the support from the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the US Department of Energy under the Battery Materials Research (BMR) Program. X.Y.T. and J.G.W. acknowledge support from the Natural Science Foundation of Zhejiang Province (grants LR13E020002) and the National Natural Science Foundation of China (51002138 and 21136001). \n\n# Author contributions \n\nY.C. and X.Y.T. conceived the idea. X.Y.T. designed the experiments, synthesized the materials and performed electrochemical test. J.G.W. and Q.X.C. carried out the DFT calculation and analyzed the result. C.L., H.T.W., G.Y.Z. and other authors conducted materials characterization. All authors discussed the electrochemical results and the whole paper. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Tao, X. Y. et al. Balancing surface adsorption and diffusion of lithium-polysulfides on nonconductive oxides for lithium–sulfur battery design. Nat. Commun. 7:11203 doi: 10.1038/ncomms11203 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1021_acsnullo.5b06295", + "DOI": "10.1021/acsnullo.5b06295", + "DOI Link": "http://dx.doi.org/10.1021/acsnullo.5b06295", + "Relative Dir Path": "mds/10.1021_acsnullo.5b06295", + "Article Title": "Highly Dynamic Ligand Binding and Light Absorption Coefficient of Cesium Lead Bromide Perovskite nullocrystals", + "Authors": "De Roo, J; Ibáñez, M; Geiregat, P; Nedelcu, G; Walravens, W; Maes, J; Martins, JC; Van Driessche, I; Koyalenko, MV; Hens, Z", + "Source Title": "ACS nullO", + "Abstract": "Lead halide perovskite materials have attracted significant attention in the context of photovoltaics and other optoelectronic applications, and recently, research efforts have been directed to nullostructured lead halide perovskites. Collodial nullocrystals (NCs) of cesium lead halides (CsPbX3, X = Cl, Br, I) exhibit bright photoluminescence, with emission tunable over the entire visible spectral region. However, previous studies on CsPbX3 NCs did not address key aspects of their chemistry and photophysics such as surface chemistry and quantitative light absorption. Here, we elaborate on the synthesis of CsPbBr3 NCs and their surface chemistry. In addition, the intrinsic absorption coefficient was determined experimentally by combining elemental analysis with accurate optical absorption measurements. H-1 solution nuclear magnetic resonullce spectroscopy was used to characterize sample purity, elucidate the surface chemistry, and evaluate the influence of purification methods on the surface composition. We find that ligand binding to the NC surface is highly dynamic, and therefore, ligands are easily lost during the isolation and purification procedures. However, when a small amount of both oleic acid and oleylamine is added, the NCs can be purified, maintaining optical, colloidal, and material integrity. In addition, we find that a high amine content in the ligand shell increases the quantum yield due to the improved binding of the carboxylic acid.", + "Times Cited, WoS Core": 1547, + "Times Cited, All Databases": 1636, + "Publication Year": 2016, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000370987400044", + "Markdown": "# Highly Dynamic Ligand Binding and Light Absorption Coefficient of Cesium Lead Bromide Perovskite Nanocrystals \n\nJonathan De Roo,†,‡,§,∥ Maria Ibáñez,∥,⊥ Pieter Geiregat,‡,# Georgian Nedelcu,∥ Willem Walravens,‡,# Jorick Maes,‡,# Jose C. Martins,§ Isabel Van Driessche,† Maksym V. Kovalenko,\\*,∥,⊥ and Zeger Hens\\*,‡,# \n\n†Sol−Gel Center for Research on Inorganic Powders and Thin Films Synthesis (SCRiPTS), Ghent University, B-9000 Ghent, \nBelgium \n‡Physics and Chemistry of Nanostructures Group (PCN), Ghent University, B-9000 Ghent, Belgium \n§NMR and Structure Analysis Unit, Ghent University, B-9000 Ghent, Belgium \n∥Laboratory of Inorganic Chemistry, ETH Zürich, CH-8093 Zürich, Switzerland \n⊥Laboratory for Thin Films and Photovoltaics, Empa-Swiss Federal Laboratories for Materials Science and Technology, CH-8600 \nDübendorf, Switzerland \n#Center for Nano and Biophotonics, Ghent University, B-9000 Ghent, Belgium \n\n\\*S Supporting Information \n\nABSTRACT: Lead halide perovskite materials have attracted significant attention in the context of photovoltaics and other optoelectronic applications, and recently, research efforts have been directed to nanostructured lead halide perovskites. Collodial nanocrystals (NCs) of cesium lead halides $(\\mathbf{CsPbX_{3}},\\ \\textbf{X}=\\ \\mathbf{Cl},\\ \\mathbf{Br},\\ \\textbf{I})$ exhibit bright photoluminescence, with emission tunable over the entire visible spectral region. However, previous studies on $\\mathbf{Cs}\\mathbf{P}\\mathbf{b}\\mathbf{X}_{3}$ NCs did not address key aspects of their chemistry \n\n![](images/1695d90b0d2cfc5e1580e1699ea310d21a718a048dde902c03a3939cc1af5129.jpg) \n\nand photophysics such as surface chemistry and quantitative light absorption. Here, we elaborate on the synthesis of $\\mathbf{CsPbBr}_{3}$ NCs and their surface chemistry. In addition, the intrinsic absorption coefficient was determined experimentally by combining elemental analysis with accurate optical absorption measurements. ${}^{1}\\mathbf{H}$ solution nuclear magnetic resonance spectroscopy was used to characterize sample purity, elucidate the surface chemistry, and evaluate the influence of purification methods on the surface composition. We find that ligand binding to the NC surface is highly dynamic, and therefore, ligands are easily lost during the isolation and purification procedures. However, when a small amount of both oleic acid and oleylamine is added, the NCs can be purified, maintaining optical, colloidal, and material integrity. In addition, we find that a high amine content in the ligand shell increases the quantum yield due to the improved binding of the carboxylic acid. \n\nKEYWORDS: NMR, $C s P b B r_{3},$ absorption coefficient, surface chemistry \n\nS ipnehcroeo tsvhkoeil adiicms dotevrveiracyle ,oa1fs−5hiyrgbehrslieyd coffirhg iaencnitticv−liitiginehost gahabansvioec heoralsredinde and applications are found in X-ray detectors,6 photodetectors,7 LEDs,8 and lasing.9,10 Recently, efforts were directed to the synthesis of these perovskites as nanocrystals (NCs). Either hybrid organic−inorganic (i.e., $\\mathrm{RNH_{3}}\\dot{\\mathrm{Pb}}\\mathrm{X_{3}}^{11-17},$ ) or fully inorganic (e.g., $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}_{3}}^{18-21}.$ ) colloidal nanocrystals were synthesized and they show great promise regarding photoluminescence (PL) quantum yield and color tunability. However, their surface chemistry remains unexplored, leading to difficulties in the development of effective isolation and purification procedures while maintaining outstanding PL properties. Compared to the classical chalcogenide quantum dots, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ are more ionic in nature and the interactions with capping ligands are also more ionic and labile. Consequently, when polar solvents are added to isolate the nanocrystals, the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs often lose their bright $\\mathrm{{PL},}$ colloidal stability and sometimes even structural integrity. These observations call for an exhaustive investigation and insight in the surface chemistry of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs. \n\nOver the last 5 years, it has been shown that the binding of ligands to nanocrystals can be conveniently described by the Covalent Bond Classification (CBC), as developed by Green22,23 to classify metal−ligand interactions and the ensuing complexes. Here, ligands are defined as L-, X-, or Z-type, depending on the number of electrons that the neutral ligand contributes to the metal−ligand bond (2, 1 or 0, respectively). Various (cation rich) metal sulfide and selenide nanocrystals, including for example CdSe, CdTe, PbS, and PbSe, proved to be coordinated by X-type ligands such as carboxylates or phosphonates that bind to excess surface cations with a binding motif abbreviated as $\\mathrm{NC}(\\mathrm{MX}_{n})$ , where NC refers to the charge neutral, stoichiometric nanocrystal and M equals a metal $^{n+}$ cation (Figure 1).24 A more involved binding motif was demonstrated in the case of metal oxide nanocrystals such as $\\mathrm{HfO}_{2}$ or $\\mathrm{ZrO}_{2}$ . These stoichiometric NCs proved to be passivated by dissociated carboxylic acids, which brings 2 different $\\mathrm{\\DeltaX}$ -type ligands on the surface, the carboxylate and the proton, in a binding motif abbriviated as $\\mathrm{NC}(\\mathrm{X})_{2}$ .25,26 L-type ligands are Lewis bases and $Z$ -type ligands are Lewis acids that in the case of binary nanocrystals will coordinate to acidic (surface cations) or basic (surface anions) surface sites, respectively. Such binding motifs can be concisely written as $\\mathtt{N C(L)}$ and $\\operatorname{NC}(Z)$ (Figure 1). Note that $\\mathrm{CdSe}(\\mathrm{CdX}_{2})$ can be considered as both $\\mathrm{NC}(\\mathrm{MX}_{2})$ or $\\operatorname{NC}(Z)$ as ligand exchange reactions might invoke either only the X-type ligand exchange or the displacement of the entire $\\mathbf{MX}_{2}$ moiety. Such ligand exchange reactions can be concisely written with the proposed binding motif nomenclature (Table 1). \n\n![](images/42ebe73b287a3e74341881441812bd3cdbb94bc66cc5cc4958230884617cac20.jpg) \nThe covalent bond classification \nFigure 1. Schematic representation of the most important ligand classes within the covalent bond classification scheme. L-type ligands are Lewis bases, donating 2 electrons to the NC−Ligand bond. $\\mathbf{z}$ -type ligands are Lewis acids, offering an empty orbital, while $\\mathbf{X}$ -type ligands offer 1 electron. Schematic representations reflect the observable chemical reactivity of the ligand shell, not the atomistic details of the surface (basically unknown). For instance, $\\mathbf{NC}(\\mathbf{MX}_{n})$ and $\\mathbf{NC}(\\mathbf{Z})$ can correspond to the very same structure, such as CdSe $\\mathbf{\\tilde{C}d X}_{2})$ ). \n\nOne of the most powerful tools to study the organic− inorganic interface of the NC ligand shell and unravel binding motifs is Nuclear Magnetic Resonance (NMR) spectroscopy. One-dimensional, solution $^{1}\\mathrm{H}$ and $^{31}\\mathrm{P}$ NMR are readily accessible and were shown to aid considerably in the elucidation of NC−ligand interactions,27−32 and the effect of purification procedures.33,34 $\\mathrm{^{1}H}$ NMR in particular has the possibility to go beyond the structure analysis of organic compounds in solution and can effectively probe the dynamics of ligand−NC binding. Two-dimensional Diffusion Ordered Spectroscopy (DOSY) enables the molecular diffusion coefficient to be determined. This diffusion coefficient decreases (i.e., slower translation) when a ligand is bound to a NC.32 However, in cases where the ligand exchanges fast between a bound and a free state, only an average diffusion coefficient is measured. Therefore, it is difficult to assess ligand binding when the fraction of free ligand is much larger than the bound fraction. In that case, a NOESY (Nuclear Overhauser Effect Spectroscopy) NMR experiment can ascertain ligand binding since the NOE effect is strongly dominated by the bound fraction.35 \n\nHere, we focus on inorganic $\\mathrm{CsPbBr}_{3}\\mathrm{NCs}_{\\mathrm{.}}$ , synthesized by an approach slightly modified from the protocol reported by Protesescu et al.18 and gain more insight in the underlying chemical reactions and surface chemistry. We performed ICP− MS (Inductively Coupled Plasma−Mass Spectrometry) and light absorption measurements and thus determined the intrinsic absorption coefficient. We use it to accurately estimate the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ isolation/purification yield and the NC concentration. Via solution ${}^{1}\\mathrm{H}~\\mathrm{NMR},$ we show that difficulties with the purification arise from the dynamic nature of the NC− ligand bonding and demonstrate that this problem can be tackled by manipulating the bonding equilibrium with an excess of free ligands. Both carboxylic acids and long chain amines were found necessary to stabilize the surface during purification steps; however, for optimal PL quantum yield, amines proved key. Similar to what has been found with metal oxide NCs, our findings indicate $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs are terminated by pairs of Xtype ligands, either oleylammonium bromide or oleylammonium carboxylate, yielding a $\\mathrm{{NC}(X)_{2}}$ binding motif. This work sheds, thus, more light on the surface chemistry of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs and opens the way for further surface modifications, required for the optoelectronic applications of these NCs. \n\nTable 1. Overview of Different Exchange Reactions, Their Concise Notation, and Examplesa \n\n\n
exchange reactionexample
NC(X)+ 2L NC(L)+ (LX)+(X)-Displacement of dissociated carboxylic acid by amines from HfO NCs, driven by ion-pair formation25
NC(MX)+2HX'NC(MX)+2HXExchange of carboxylate for phosphonate ligands on CdSe NCs46
NC(MX)+ (n +1)LNC(L)+MXL Displacement of Cd carboxylate by amines from CdSe NCs driven by complex formation27
\n\n$^{a}\\mathrm{NC}(\\mathrm{MX}_{2})$ can be involved in either an $X^{\\prime}$ -for-X exchange or an L-type promoted Z-type displacement. Since the L, X, Z notation only applies to coordinating ligands and disregards the (partial) charge on the ligand after binding, using the same symbols to describe adducts of ligands can be ambiguous, especially if the latter involves an ion pair. In such cases, the symbol referring to the coordinating moiety is placed between parentheses and the charge it acquires within the ion pair is added outside the brackets. \n\n![](images/5f25b7875d0395cd2e2ef0dae37c39d457ccf7746e0dd453d1be369bf50a0ca5.jpg) \nFigure 2. (A) Schematic overview of the reagents and outcome of a $\\mathbf{CsPbBr}_{3}$ NC synthesis. (B) TEM image and (C) XRD diffractogram, showing the cubic perovskite phase. (D) UV−vis and normalized PL of a standard $\\mathbf{CsPbBr}_{3}$ synthesis, purified with the standard protocol as described in the Methods section. For $\\mathbf{PL},$ the excitation wavelength was $460\\ \\mathrm{nm}$ and 5 vol $\\%$ oleylamine was added to the suspension prior to dilution for quantum yield determination. \n\n# RESULTS AND DISCUSSION \n\nSynthesis. $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs are prepared by the injection of cesium oleate in an octadecene solution containing $\\mathrm{Pb}{\\bf B}{\\bf r}_{2},$ oleic acid and oleylamine. Note that the reagents were used as received, without additional purification or drying. Immediately after injection of cesium oleate at ${180~^{\\circ}C},$ the NCs precipitate from the solution (see Figure 2A) and are collected by centrifugation and redissolution in hexane. More illustrative photographs concerning the synthesis process can be found in the Supporting Information (Figure S1). A small excess of oleic acid and oleylamine is added and the NCs are precipitated with acetone and redispersed in hexane (see Methods for experimental details). The NCs have an average cube edge length of $8.4\\mathrm{nm}$ according to transmission electron microscopy (TEM, Figure 2B) and have a cubic crystal structure as attested by the XRD (X-ray diffraction) diffractogram, see Figure 2C. The absorption spectrum (Figure 2D) shows the first excitonic peak at $498~\\mathrm{nm}$ and a PL centered at ${508}\\mathrm{nm}$ with a fwhm (full width at half-maximum) of $19\\ \\mathrm{nm}$ . The PL quantum yield of a purified sample was determined at $83\\%$ . However, as we shall see further, the PL quantum yield is strongly dependent on the properties of the NC surface and therefore on the manipulation of NC colloids. \n\nTo gain more insight in the complex reaction mixture and therefore the nature of possible ligands, it is helpful to consider the underlying reaction mechanism. We can formally write the perovskite formation reaction as \n\n$$\n\\begin{array}{r l}&{\\mathrm{2Cs(OOCR)}+3\\mathrm{PbBr_{2}}\\rightarrow2\\mathrm{CsPbBr_{3}}+\\mathrm{Pb}\\mathrm{(OOCR)}_{2}}\\\\ &{\\mathrm{OOCR}=\\mathrm{oleate}}\\end{array}\n$$ \n\nLead oleate is an obvious byproduct of the synthesis and full yield in lead can thus never be achieved with these reagents. However, this reaction is performed with a lead bromide excess and cesium oleate is the limiting reagent. The recognition that lead oleate is formed is important since it is known to act as a ligand toward NC surfaces, such as in the case of PbS NCs.27 \n\nEquation 1 describes the overall reaction, but in reality, neat octadecene does not dissolve $\\mathrm{Pb}{\\mathbf{B}}{\\mathbf{r}}_{2}$ . Moreover, neither the addition of 8 equiv of oleylamine nor that of oleic acid was sufficient to dissolve $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2};$ only the addition of both succeeded in complete dissolution. This suggests an early stage anion exchange between lead bromide and oleic acid, aided by the formation of oleylammonium bromide (oleylamine binds HBr). \n\n$$\n\\begin{array}{r l}&{\\mathrm{PbBr_{2}}+x\\mathrm{HOOCR}+x\\mathrm{RNH_{2}}\\rightarrow\\mathrm{PbBr}_{(2-x)}(\\mathrm{OOCR})_{x}}\\\\ &{~+x\\mathrm{RNH_{3}B r}\\qquadx=1\\mathrm{or}2}\\end{array}\n$$ \n\nTherefore, at the end of the reaction, the synthesis mixture probably comprises, apart from NCs, lead oleate, oleylammonium bromide, oleic acid and oleylamine, which are all potent surface binding species. \n\nIndirect confirmation that eq 2 applies, and an interesting synthesis variation, is found when octadecene and oleic acid are replaced by oleylamine, thus having pure oleylamine as solvent. Heated to $12{\\dot{0}}^{\\circ}\\mathrm{C},$ $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ dissolves in oleylamine and the solution is slightly yellow-green, probably due to the coordination of amines to the metal center. Nonetheless, addition of oleic acid at this stage results in a colorless solution, thus experimentally confirming the interaction between oleic acid and $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ . If, instead of oleic acid, cesium oleate is injected in the solution at $180^{\\circ}\\mathrm{C},$ $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs are formed and do not immediately precipitate, in contrast to the standard synthesis in octadecene. Unfortunately, the particles degrade during the cooldown to room temperature, probably due to a reaction with the excess of amine. This can be prevented by quenching the reaction mixture with an excess of toluene. Such NCs are very polydisperse but still have a PL centered around $510~\\mathrm{nm}$ with a fwhm of $21~\\mathrm{nm}$ (TEM, UV−vis and PL in Figure S2). \n\nThe Intrinsic Absorption Coefficient. A convenient feature of colored materials is their concentration dependent light absorption as described by the law of Bouguer−Lambert− Beer, which makes for a swift way of determining the NC volume fraction and concentration in a NC dispersion. Here, the intrinsic absorption coefficient $\\mu_{i}$ is a most convenient quantity as it was found to be independent of the NC size for various quasi-spherical semiconductor NCs at photon energies well above their band gap.36 By definition, $\\mu_{i}$ is related to the absorbance $A$ of a NC dispersion, the volume fraction $f$ of the NC material, defined as the ratio between the NC volume and the dispersion volume, and the optical path length $L$ : \n\n$$\n\\mu_{i}={\\frac{\\ln10A}{f L}}\n$$ \n\nHence, the combination of $\\mu_{i}$ and an absorbance measurement of a given sample allows for the determination of the amount of NC material (the total volume of $\\mathrm{Cs}\\mathrm{Pb}\\mathrm{Br}_{3},$ ) and the NC concentration (if the average volume of a NC is known). \n\nHere, we obtained $\\mu_{i}$ by combining elemental analysis and UV−vis absorption spectroscopy on the same sample. For elemental analysis, three samples were taken from the same $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NC reaction. After careful purification, each sample was dried and digested in a known amount of ${\\mathrm{HNO}}_{3}$ and analyzed for its $\\mathrm{\\dot{Pb}}$ and Cs content using ICP−MS. The samples feature a Pb:Cs ratio of 1.00 (see Supporting Information Table S1), a result indicating that the sample preparation indeed effectively separated NCs from residual reagents or the lead oleate byproduct. With the use of the $\\mathrm{Pb}$ content to determine the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ volume fraction in the original samples, a $\\mu_{i}$ spectrum for each aliquot could be calculated according to eq 3. The corresponding average $\\mu_{i}$ spectrum is shown in Figure 3A, where the gray area represents the error on the analysis and the inset shows the variation on $\\mu_{i,335},$ i.e., the intrinsic absorption coefficient at $335~\\mathrm{nm}$ , of the different samples and the thus obtained average value is $(2.0\\pm$ $0.1\\AA)\\times10^{5}~\\mathrm{{cm}^{-1}}$ . \n\nThe intrinsic absorption coefficient of a dispersed colloid depends on the complex dielectric function $\\epsilon_{\\mathrm{d}}=\\epsilon_{\\mathrm{d,r}}+i\\epsilon_{\\mathrm{d,i}}$ of the NC, the refractive index of the (presumed optically transparent) solvent $n_{\\mathrm{s}}=\\sqrt{\\epsilon_{\\mathrm{s}}}$ and the wavelength of light $\\lambda$ : \n\n![](images/d6cbd9719a84e40f58f6003283e977578888039577e87626d124bd7b85a95670.jpg) \nFigure 3. (A) The experimental spectrum of the intrinsic absorption coefficient (determined by a combination of UV−vis and $\\mathbf{ICP-MS},$ and the effective-medium-theory predictions based on a complex dielectric function determined by density functional theory (DFT).37 The gray area represents the error on the experimental $\\pmb{\\mu}_{i}$ spectrum and the inset shows the different values at $335\\ \\mathbf{nm}$ for the different ICP/UV−vis samples. (B) UV−vis spectra of different sized $\\mathbf{CsPbBr}_{3}$ NCs, obtained by size selective precipitation; details are provided in Methods section and the Supporting Information. \n\n$$\n\\mu_{_i}=\\frac{2\\pi}{\\lambda n_{\\mathrm{s}}}\\vert f_{\\mathrm{LF}}^{}\\vert^{2}\\boldsymbol{\\epsilon}_{\\mathrm{d,i}}\n$$ \n\nHere, $f_{\\mathrm{LF}}$ denotes the so-called local field factor, which is the ratio between the electric field inside a NC and the incident electric field. For a spherical particle, it reads \n\n$$\nf_{\\mathrm{LF}}=\\frac{3\\epsilon_{\\mathrm{s}}}{\\epsilon_{\\mathrm{d}}+2\\epsilon_{\\mathrm{s}}}\n$$ \n\nHaving the complex dielectric function of a material thus allows to predict an intrinsic absorption coefficient. On the other hand, experimental data on the intrinsic absorption coefficient could be used to validate the calculation of complex dielectric functions by first-principles. As an example, we used the bulk dielectric function of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ obtained by a density functional theory study37 to calculate a theoretical intrinsic absorption coefficient of cubic $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs. As shown in Figure 3A, not all features of the experimental spectrum are closely followed by the predicted values, yet the order or magnitude is correct and especially at shorter wavelengths, the theoretical and experimental absorption coefficient seem to match. \n\nNote that for a given NC shape and a given solvent, eqs 4 and 5 imply that $\\mu_{i}$ will be independent of NC size when $\\epsilon_{\\mathrm{d}}$ is size-independent. This situation is typically seen with semiconductor NCs at wavelengths considerably shorter than their band-gap transition. Figure 3B therefore shows absorption spectra of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ dispersions containing NCs with different average diameters (see Supporting Information Figure S3), normalized at $\\mu_{i,335}=2.0\\times\\mathrm{{\\hat{10}^{5}}\\ c m^{-\\tilde{1}}}$ . The spectra are obviously size-dependent around the band gap transition and some sizevariation remains at the features around 360 and $400~\\mathrm{{nm}}$ . On the other hand, they coincide surprisingly well in wavelength regions where the absorption is largely featureless, such as 325−345 and $415{-}455\\ \\mathrm{\\nm}$ . The concomitant absorption coefficients can thus also be used for analyzing the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ volume fraction in NC dispersions, irrespective of the NC size, and a tabulated absorption coefficient spectrum is therefore added to the Supporting Information. For one thing, having a size-independent absorption coefficient leads to an analytical expression of the molar extinction coefficient $\\varepsilon_{335},$ linking absorbance at $335~\\mathrm{nm}$ to NC concentration, of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}{\\mathrm{NCs}}$ : \n\n$$\n\\varepsilon_{\\scriptscriptstyle{335}}=\\frac{N_{\\mathrm{A}}V_{\\scriptscriptstyle{\\mathrm{NC}}}}{\\ln10}\\mu_{\\scriptscriptstyle{i}}\\approx(0.052\\pm0.002)d^{3}\\mathrm{\\cm}^{-1}\\mu\\mathrm{M}^{-1}\n$$ \n\nHere, $N_{\\mathrm{A}}$ is Avogadro’s number, $V_{\\mathrm{NC}}$ is the nanocrystal volume, and $d$ is the cube edge in nanometer. \n\nImportantly, even if $\\epsilon_{\\mathrm{d}}$ is size-independent, intrinsic absorption coefficients of NCs will depend on the NC shape. Hence, shape differences may compromise the analysis of volume fractions in different NC samples using a single, sizeindependent absorption coefficient. Since $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs typically feature a cubic shape, we therefore used the theoretical dielectric function of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ to calculate $\\mu_{i}$ for cubic and spherical NCs (Figure S4). The resulting absorption coefficients only differ by ${\\approx}10\\%$ , a result indicating that the experimentally determined absorption coefficients here on a sample of cubic $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs can be used for analyzing spherical NCs without introducing major errors. Importantly, a similar conclusion will also apply to, e.g., $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ NCs, but not to $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ or $\\mathrm{Pb}S\\ \\mathrm{NCs}$ as the imaginary part of the dielectric function is so large for these materials that deviations between both values become unacceptable (up to $50\\%$ , see calculations in Supporting Information and Figure S4). \n\n![](images/41ba0be4cd2a4d26f357e751ef2572f5a4ca20ac039989ee59cd389560b6d27a.jpg) \nFigure 4. (A) ${}^{1}\\mathbf{H}$ NMR spectrum ${\\bf8.4\\ n m}$ $\\mathbf{CsPbBr}_{3}$ NCs purified with acetone and filtered. Concentration of QDs: $2.2\\ \\mu\\mathbf{M}$ . The reference spectrum for oleic acid is displayed and impurities of octadecene (ODE) are also indicated. (B) NOESY spectrum of the sample purified with acetone in $\\mathbf{CDCl}_{3}$ . (C) Schematic representation of the dynamic surface stabilization by oleylammonium bromide. Oleic acid is not part of the ligand shell. \n\nHaving $\\mu_{i,335},$ we are now able to characterize the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NC synthesis in terms of chemical yield, where we find that the relatively monodisperse fraction as displayed in Figure 2 after isolation and purification represents a yield of only $15\\%$ . However, a large fraction of the NCs was discarded in the isolation process. To increase the isolation yield of the synthesis, acetone can be added to the raw synthesis mixture, prior to the first centrifugation step and the precipitate is dispersed in $10~\\mathrm{mL}$ of hexane. This mixture was then again purified with acetone and small amounts of oleylamine and oleic acid, and the final yield was $82\\%$ , but the particles are more polydisperse (see TEM in Figure S5). Interestingly, the PL is still quite narrow $\\mathrm{(fwhm}=21\\ \\mathrm{nm}$ ) but slightly red-shifted to ${514}~\\mathrm{nm}$ (Figure S5), consistent with the larger particle size in TEM. \n\nSurface of As-synthesized NCs. It is common practice in NC syntheses to purify NCs by multiple precipitation/ redispersion steps using polar solvents such as ethanol, methanol, 2-propanol, acetone, acetonitrile or ethyl acetate. However, when these solvents are added in excess, the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs lose their PL, colloidal stability and often even structural integrity. In this respect, a slightly higher robustness was noted when using non-dried solvents during synthesis. Small amounts of acetone or acetonitrile can be added, precipitating part of the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs. Another part of the NCs is apparently lost as the supernatant after centrifugation is strongly colored. The precipitate is redispersed in hexane, resulting in a green suspension. Unfortunately, in the $\\mathrm{^{1}H}$ NMR spectrum of such a “purified” suspension, we observe the characteristic resonances of a terminal alkene, presumable octadecene (ODE), at 4.94 and $5.8~\\mathrm{\\ppm}$ (Figure 4A) indicating that this sample is insufficiently purified (all reference spectra of oleic acid, oleylamine and ODE are presented in Figure S6). Comparing with the reference spectrum of oleic acid, we also recognize the characteristic resonances 1 and 2 of oleic acid in the sample. These resonances have fine structure and appear at exactly the same chemical shift as the reference, as opposed to the typical behavior of bound ligands, which feature broadened and slightly shifted resonances. Resonances 3, 4, and 6 of oleic acid show overlap with those of oleylamine and octadecene and are therefore of little use. The very broad resonances $\\alpha$ and $\\beta$ are ascribed to the $\\mathrm{NH}_{3}^{+}$ and $\\alpha\\mathrm{-CH}_{2}$ of oleylammonium, respectively, in compliance with earlier reports,26 and a more detailed argumentation is provided in the Supporting Information, see Figure S7. The presence of (protonated) oleylamine is also confirmed by analysis of resonance 5 at 5.33 ppm, which corresponds to the alkene resonance of either oleylamine, oleic acid or both. The total concentration of oleyl species (determined from resonance 5) is $8.3\\mathrm{\\mM},$ while the concentration of oleic acid (determined from resonance 1) is $5.1\\mathrm{mM}$ . The difference $\\left(3.2\\mathrm{mM}\\right)$ is ascribed to the presence of (protonated) oleylamine. Although peak broadening typically indicates bound ligands, it is uncommon for the protons, closest to the surface, to be detected.25 This conundrum will be addressed further on. \n\nThe NOESY spectrum (Figure 4B) confirms that octadecene and oleic acid are not bound to the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs as they feature positive (red) cross peaks, which is conclusive proof for lack of interaction with the surface.38 The observation that oleic acid does not bind is in accordance with an earlier report on the stoichiometric nature of the $\\mathrm{Cs}\\mathrm{Pb}\\mathrm{Br}_{3}\\mathrm{NCs}.^{1}$ 8 Indeed, to bind as a negative X-type ligand, the negative charge of the oleate would require compensation by a cationic excess on the surface, which is not present. To bind in a $\\mathrm{{NC}}(\\mathrm{{X}})_{2}$ binding motif, in a dissociative mode with both proton and oleate as ligand,25 the NC’s anion should have a high affinity toward protons, which is not the case for bromide (HBr is significantly more acidic than oleic acid). In contrast, the negative (black) cross peaks between the resonances of oleylamine corroborate the interaction of oleylamine with the surface. In light of the previously described chemical equations, ligand possibilities and protonated state of oleylamine, we infer that oleylammonium bromide is the acting ligand in this sample. This is a pair of Xtype ligands, binding with the oleylammonium cation to surface bromide, presumably through a hydrogen bridge, and with the bromide anion to the surface cesium or lead ions, see Figure S8. It is no surprise that the highly ionic $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs prefer ionic ligands, compared to ligands that bind with a highly covalent character such as lead oleate. \n\nTo gain more insight in the dynamics of stabilization, the diffusion coefficient $D$ of a molecule is a helpful parameter as the diffusion coefficient of a bound ligand is equal to the diffusion coefficient of the total object (NC plus ligand shell). The diffusion coefficient can be obtained from Diffusion Ordered NMR Spectroscopy (DOSY) and can be related to the size of the molecule via the Stokes−Einstein equation with $f$ the friction coefficient, $k_{\\mathrm{B}}$ the Boltzmann constant, and $T$ the absolute temperature: \n\n![](images/8ca75162ddb8219bea2c674a6e6594652573131af16ac4e5366441e5d665fd33.jpg) \nFigure 5. (A) ${\\bf\\Pi^{1}H}$ NMR spectrum 8.4 nm $\\mathbf{CsPbBr}_{3}$ NCs purified with acetone and filtered, before and after addition of ${\\mathfrak{s}}\\mu\\mathbf{L}$ of oleylamine. Concentration of QDs: $2.2\\mu\\mathbf{M}$ . The octadecene (ODE) impurities are also indicated. (B) NOESY spectrum of the sample $^+$ oleylamine. (C) Schematic representation of the dynamic surface stabilization by oleylammonium bromide, oleylammonium oleate and oleylamine. In addition, the relevant acid/base equilibria are depicted. \n\n$$\nD={\\frac{k_{\\mathrm{{B}}}T}{f}}\n$$ \n\nFor spherical particles, the friction coefficient is $f=6\\pi\\eta r_{s}$ $\\dot{\\boldsymbol{\\eta}}$ the solvent’s viscosity, $r_{\\mathrm{s}}$ the solvodynamic radius of the object/ molecule) and this expression was already repeatedly used to calculate the solvodynamic radius of NCs from DOSY data.26,32,39−41 For non-spherical NCs, the friction coefficient needs adjustin g42,43 and the general expression is f = 6πηC with $C$ the so-called capacity of the object.44 Although there is no previous account of DOSY NMR on cubic NCs, Hubbard44 and Douglas45 calculated the capacity of arbitrary shaped objects. For a cube, the capacity proved $C=0.66d$ with $d$ the cube edge length, and we will use this relation throughout this paper. \n\nFrom DOSY measurements, we obtained the diffusion coefficient of oleylammonium bromide in the NC suspension, $D=166\\pm18~\\dot{\\mu}\\mathrm{m}^{2}/s,$ significantly smaller than the diffusion coefficient in the absence of NCs $\\mathrm{(}D~=~361~\\mu\\mathrm{m}^{2}/s\\mathrm{)}$ . The decrease in $D$ (slower diffusion) confirms the interaction of oleylammonium bromide with the NC surface, as already indicated by the NOESY analysis. However, 166 $\\mu\\mathrm{m}^{2}/\\dot{\\mathbf{s}}$ corresponds to a cube edge length of $3.7~\\mathrm{nm}$ , clearly smaller than expected, as the NCs measure $8.4\\ \\mathrm{nm}$ in TEM. This observation implies that the oleylammonium bromide is not tightly bound to the NC surface but exchanges fast between its bound and free state,38 and therefore, an average diffusion coefficient is measured. This highly dynamic stabilization mechanism with oleylammonium bromide may well explain the ease of anion exchange reactions with these nanocrystals.19,21 Particularly, the observation of an inter-NC anion exchange when two parent NCs $(e.g.,\\mathrm{CsPbBr}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}_{3}},$ ) are mixed in solution advocates for the dynamic interaction of oleylammonium halides with the surface. Unfortunately, the dynamic stabilization is also the origin of purification difficulties, as the desorption of oleylammonium bromide in polar solvents will proceed swiftly. \n\nIf we assume that the NCs plus ligand shell would amount to an object of about $10\\mathrm{nm}_{\\cdot}$ the diffusion coefficient of the bound ligand fraction $\\left(D_{2}\\right)$ can be estimated at $60~\\mu\\mathrm{m}^{2}/\\mathrm{s}$ by eq 7. Neglecting all other equilibria except for the ligand binding event, the diffussion coefficient of the free oleylammonium bromide ligand is $D_{1}=361~\\mu\\mathrm{m}^{2}/s$ . In case of fast exchange, the observed diffusion coefficient $(D)$ is a weighed average of the fractions. Hence, the bound fraction can be calculated from the observed average diffusion coefficient and the diffusion coefficients of either fraction: \n\n$$\nx=\\frac{D_{1}-D}{D_{1}-D_{2}}\n$$ \n\nUsing eq 8, we thus estimate the bound fraction at $65\\%$ . This rather high fraction of bound ligands, yet in fast exchange with a pool of free ligands, explains why the resonances $\\alpha$ and $\\beta,$ being close to the surface, are broadened yet still detectable in the $\\mathrm{^{1}\\check{H}}$ NMR spectrum (Figure 4). After all, the line width is also an average between the free and bound state. \n\nFor the same sample, the $^1\\mathrm{H}$ NMR spectrum yields a total oleylammonium bromide concentration of $3.3~\\mathrm{\\mM},$ , which means $2.15~\\mathrm{mM}$ is in the bound state. Together with the NC concentration of $2.2\\ \\mu\\mathrm{M}$ (calculated with the molar extinction coefficient for $8.4\\ \\mathrm{nm}\\ \\mathrm{NCs}_{.}$ , vide supra), we calculate a ligand density of 2.3 ligands $\\mathrm{nm}^{-2}$ . Considering the lattice parameter $\\left(0.58\\dot{7}\\mathrm{nm}\\right)$ and the crystal structure, there is one cation/anion pair per $0.344~\\mathrm{nm}^{2}$ of surface, resulting in a theoretical ligand density of $2.9\\ \\mathrm{\\nm}^{-2}$ . The close correspondence with the experimental value indicates almost complete passivation of the surface and indeed, the suspension is brightly green luminescent. \n\nOleylamine draws oleic acid into the ligand shell. The chemical shift of the $\\alpha$ resonance in Figure 4 suggests that oleylamine is almost $100\\%$ in its protonated state. However, the acidic proton can be rapidly transferred to an unprotonated amine and therefore, the $\\alpha$ and $\\beta$ resonances sharpen and shift in the spectrum when $25~\\mathrm{mM}$ of unprotonated oleylamine is added to the NC dispersion (Figure 5A). In particular, we observe the averaged resonances at a chemical shift position between the original position and the position in the reference spectrum of oleylamine. Since the unprotonated amine is added in almost 10-fold excess, the $\\beta$ resonance has a chemical shift, close to the reference chemical shift (Figure 5A). In addition, the diffusion coefficient increased to $681\\pm10\\mu\\mathrm{m}^{2}/s,$ again an average over all the populations but closest to the diffusion coefficient of pure oleylamine: $880\\pm10~\\mu\\mathrm{m}^{2}/s$ (as expected because of the high excess). We conclude that oleylamine is primarily in the free, unprotonated state but is involved in several equilibria. \n\n![](images/1934deadc6d4ce905337104a164548a3b3f4934451043ca4038497f6bad017f2.jpg) \nFigure 6. (A) ${}^{1}\\mathbf{H}$ NMR spectrum of $\\mathbf{CsPbBr}_{3}$ NCs purified with 10 vol $\\%$ oleylamine and acetone. The resonance denoted with $\\mathbf{x}$ is an unknown impurity, presumably the amide of oleic acid and oleylamine judging from its chemical shift. (B) 2D NOESY spectrum of the sample in (A). (C) $\\bar{}_{\\mathbf{H}}^{\\mathsf{i}}$ NMR spectrum of $\\mathbf{CsPbBr}_{3}$ NCs purified with 5 vol $\\%$ oleic acid, 5 vol $\\%$ oleylamine and acetone, three times (a) or 5 vol $\\%$ oleic acid, 10 vol $\\%$ of oleylamine and acetone, two times (b). \n\nInterestingly, the NOESY spectrum in Figure 5B still features negative (black) NOE cross peaks for oleylamine, indicating that at least a fraction is still interacting with the surface. As it happens, oleylamine has many possibilities to do so, see Figure 5C. First, oleylamine is involved in the acid/base equilibrium with hydrogen bromide, and binds to the surface as oleylammonium bromide $\\left(\\mathrm{NC}(\\mathrm{X})_{2}\\right)$ . Second, oleylamine can deprotonate oleic acid and form oleylammonium oleate. Indeed, resonance 1 of oleic acid has shifted to lower parts per million $\\left(\\mathrm{ppm}\\right)$ values, consistent with deprotonation. In addition, the cross peaks of oleic acid in the NOESY spectrum have switched sign and are now negative. Therefore, we infer that oleate is binding to the NC surface as an ion pair with oleylammonium. This is again an example of a pair of X-type ligands, coordinating to a stoichiometric surface, $\\bar{\\bf N C}(\\mathrm{X})_{2}$ . Once more, this surface ligation is highly dynamic because we observe an average diffusion coefficient of $\\dot{D}_{\\mathrm{oleate}}=370\\pm22~\\mu\\mathrm{m}^{2}/s.$ . Although lower than the reference value for a mixture of oleic acid and oleylamine $(575\\mu\\mathrm{m}^{2}/\\mathrm{s})$ , this diffusion coefficient is far from the expected diffusion coefficient of a tightly bound ligand $(60~\\mu\\mathrm{m}^{2}/\\mathrm{s})$ . Since the original surface was already fully passivated (see previous section), the observation that the oleylammonium oleate is binding to the surface implies a ligand exchange of the original oleylammonium bromide: \n\n$$\n\\mathrm{NC}(\\mathrm{X})_{2}+(\\mathrm{X^{\\prime}})^{+}(\\mathrm{X^{\\prime}})^{-}\\rightarrow\\mathrm{NC}(\\mathrm{X^{\\prime}})_{2}+(\\mathrm{X})^{+}(\\mathrm{X})^{-}\n$$ \n\nHere, $(\\mathrm{X}^{\\prime})^{+}(\\mathrm{X}^{\\prime})^{-}$ and $(\\mathrm{X})^{+}(\\mathrm{X})^{-}$ are short hand descriptions of oleylammonium bromide and oleylammonium oleate as ion pairs of two moieties that will bind as X-type ligands. Third and last, oleylamine could also bind in its unprotonated state, as an L-type ligand coordinating to the surface cations. Again, this involves a ligand exchange: \n\n$$\n\\mathrm{NC}(\\mathrm{X})_{2}+\\mathrm{L}\\rightarrow\\mathrm{NC(L)}+(\\mathrm{X})^{+}(\\mathrm{X})^{-}\n$$ \n\nWe conclude that the single set of oleylamine resonances encompasses a large variety of states that exchange rapidly among each other. The negative NOE (Figure 5B) and lower diffusion coefficient (compared to pure oleylamine) indicate that at least one of these states is interacting with the surface. It is however impossible to disentangle the individual contributions. \n\nTightly Bound Oleylammonium Oleate by Large Amine Excess. To investigate the role of oleylamine in more detail, we added a relatively large amount $(10\\mathrm{\\vol\\\\%})$ ) to an unpurified $\\mathrm{Cs}\\mathrm{Pb}\\mathbf{Br}_{3}\\mathbf{NC}$ suspension and only a small amount of acetone ( $50\\ \\mathrm{vol}\\ \\%$ ). This process precipitated part of the \n\nNCs and the precipitate could be redispersed in toluene after centrifugation. In Figure 6A, the $\\mathrm{^{1}\\bar{H}}$ NMR spectrum in deuterated toluene is displayed. Again, octadecene resonances are present, in addition to the alkene resonance and the distinct resonance $\\beta$ of oleylamine. Focusing on the alkene resonance around $5.5\\ \\mathrm{ppm},$ , we observe a broad contribution shifted to slightly higher ppm values $\\langle5.65\\mathrm{ppm},$ indicated with an arrow). The NOESY spectrum (6B) reveals broad negative cross peaks for this broadened resonance, confirming its bound nature. Moreover, the sharp alkene resonance also features negative NOE cross peaks and there is a cross peak from the broad to the sharp alkene resonance, most probably due to chemical exchange (see inset Figure 6B). Such observations were already explained in earlier work, the broad resonance was assigned to tightly bound ligands, in slow exchange with weakly bound ligands, featuring sharp resonances.24,27,29 Indeed, in the DOSY experiment we observed a slowly diffusing component with $D=$ $59\\pm9\\mu\\mathrm{m}^{2}/s$ . This diffusion coefficient corresponds to a cube edge length $d=9.7\\pm1.5\\mathrm{{nm}}$ , in agreement with NCs of $8.4\\mathrm{nm}$ and an additional ligand shell, confirming the existence of a tightly bound ligand fraction. Despite this encouraging conclusion, the NCs are only stable for a limited amount of time and a fraction precipitates after $24\\mathrm{~h~}$ . However, the addition of a few microliters of trifluoroacetic acid brings the NCs back in suspension (brightly luminescing), again emphasizing the importance of acid−base equilibria in the NC stabilization, and pointing to the complexity of the involved surface reactions. \n\nAlthough examples exist in literature of strongly bound amine ligands,29,42 we cannot exclude the tightly bound fraction to be composed of oleic acid since it will also contribute to the alkene resonance. In addition, the characteristic resonances of oleic acid (1 and 2) are not visible in the spectrum (Figure 6A), possibly because oleic acid is strongly bound to such large NCs, leading to excessive broadening of resonances close to the surface.25 Therefore, we decided to synthesize the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs with dodecylamine instead of oleylamine. We purified the sample 3 times by adding both dodecylamine and oleic acid before precipitation with acetone. This allowed us to quantitatively precipitate the NCs (colorless supernatant) and redisperse the NCs with excellent colloidal stability and bright luminescense. First, the $^1\\mathrm{H}$ NMR spectrum does not feature any octadecene resonances (Figure 6C, sample a), the NCs are thus effectively purified. Second, although now both characteristic resonances of dodecylamine and oleic acid are recognized in the spectrum, only oleic acid contributes to the alkene resonance, and therefore, we conclude that the tightly bound fraction (indicated with an arrow) belongs to oleic acid. Since we previously concluded that oleic acid cannot bind by itself but only as an ion pair with amine, the actual tightly bound ligand will be alkylammonium oleate. In sample b, the ratio of dodecylamine to oleic acid during purification was increased and the appearance of the strongly broadened resonance (the tightly bound fraction) is more pronounced (see Figure 6C, sample b, indicated by arrow), confirming the influence of the amine on the extent of the tightly bound fraction. \n\nImplications on Purification, Quantum Yield, and Applications. As-synthesized, the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs are stabilized with oleylammonium bromide, which is however in fast exchange between a free and bound state. Although the ligand density was found sufficiently high to fully passivate the surface in apolar media, the NCs lose colloidal and structural integrity and PL when polar solvents are added in excess, presumably due to rapid desorption of the ligand. Having established the surface as highly dynamic and the common purification methods as inadequate, we sought an improved protocol. When there is an excess of amine, also oleic acid can bind to the $\\mathrm{CsPbBr_{3}\\ N C s}$ as an ion pair with oleylamine or dodecylamine. Addition of this ligand combination, prior to precipitation with acetone, proves essential to allow for multiple precipitation and redispersion steps while maintaining colloidal stability and PL. Proceeding in this manner, octadecene contamination can be removed by three washing cycles. Caution is however needed, as a too high amount of surfactants causes decomposition of the NCs, i.e., loss of color and formation of a white precipitate. A purified dispersion featured a quantum yield of $40\\%$ but the addition of 5 vol $9\\%$ oleylamine to the disperison caused the quantum yield to increase to $83\\%$ , probably due to a higher fraction of tightly bound oleate. Again there is a fine line between quantum yield optimization and NC decomposition due to excess of amine $\\left(>20\\mathrm{\\vol\\}\\%\\right)$ ). In addition, this tightly bound fraction does not prevent the complete dissolution of the NCs by large quantities of polar solvents, because the strongly bound fraction relies on an amine excess and controlled acid−base equilibria. \n\nThe behavior of these $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs is thus significantly different from classical oleate or phosphonate stabilized NCs (e.g., CdSe, PbS, etc.) where purified dispersions often contain only a monolayer of tightly bound ligands. $^{24-27,32,33,46,47}$ In this respect, the $\\mathrm{CsPbBr_{3}N C s},$ stabilized by a pair of X-type ligands $\\left(\\mathrm{NC}(\\mathrm{X})_{2}\\right)$ , better resemble the CdTe−dodecylamine systems $(\\mathrm{NC}(\\mathrm{L}))^{35}$ where a rapid exchange between bound and free ligands has also been established. To keep the NCs in dispersion, and certainly to precipitate them without desintegration, an excess of surfactants is always needed. This, of course, limits the number of applications. A possible solution to overcome these problems might be to devise multidentate or even polymeric ligands, containing both carboxylic acid and amine groups. Such ligands might be found to be tightly bound as a single monolayer and without excess in solution. This can render the perovskite NCs suitable for applications such as organic−inorganic composites, but still, applications where charge transport is required will be hampered. Next to colloidal stability and $\\mathrm{PL},$ also the structural integrity is compromised by polar solvents. This may render the transfer to polar solvents all but impossible (except with an extensive, organic capping layer) which appears as an inherent limitation of these nanocrystals. \n\n# CONCLUSION \n\nWe have analyzed the synthesis of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs, gained new insights in the mechanism, and provided alternative reaction conditions. We experimentally determined the intrinsic absorption coefficient of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs and found the wavelengths of 335 and $450\\ \\mathrm{nm}$ to be suited to analyze the volume fraction of a $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NC dispersion. In addition, we established that a difference in NC shape (cubic versus spherical) only minimally influences the intrinsic absorption coefficient in case of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Cl}}_{3}$ NCs but introduces large errors in the case of $\\mathrm{CsPbI}_{3}$ or PbS NCs. Via $\\mathrm{^{1}H}$ solution NMR, we established the surface as dynamically stabilized with either oleylammonium bromide or oleylammonium oleate and we showed the inadequacy of standard solvent/nonsolvent procedures for purification. This prompted us to add small amounts of excess oleic acid and oleylamine before precipitation, thereby preserving the colloidal integrity and photoluminescence of the NCs. In addition, the presence of an amine excess in the solution after purification causes the occurrence of a strongly bound fraction of oleic acid and results in high quantum yields. The insights obtained in this paper could thus help to bridge the gap between the synthesis of these fascinating materials and their actual applications. \n\n# METHODS \n\nPreparation of Cs-oleate: $\\boldsymbol{0.407\\mathrm{~g~}}$ of $\\mathrm{Cs}_{2}\\mathrm{CO}_{3}$ $2.5\\mathrm{\\mmol}$ , Aldrich, $99.9\\%$ ) was loaded into a $50~\\mathrm{mL}$ 3-neck flask along with $20~\\mathrm{mL}$ of octadecene (octadecene, Sigma-Aldrich, $90\\%$ ) and $1.55~\\mathrm{mL}$ of oleic acid $\\mathbf{\\zeta}_{5\\mathrm{mmol}}$ , oleic acid, Sigma-Aldrich, $90\\%$ ), dried for $^{\\textrm{1h}}$ at $120^{\\circ}\\mathrm{C},$ and then heated under $\\Nu_{2}$ to $150~^{\\circ}\\mathrm{C}$ until all $\\mathrm{Cs}_{2}\\mathrm{CO}_{3}$ dissolved. Since Cs-oleate is insoluble in octadecene at room temperature, it has to be preheated before injection. Final concentration: $0.116\\mathrm{~M~}$ . \n\n$\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ synthesis: The required reagents and quantities are listed in Table 2. No special care was taken to dry solvents or surfactants. \n\nTable 2. Reagents of a Typical Synthesis \n\n\n
quantitymmolratio on Pb
PbBr269 mg0.191
Oleylamine0.5 mL1.528.1
Oleic acid0.5 mL1.588.4
Cs-oleate solution0.4 mL0.0460.25
Octadecene5 mL
\n\nEither syntheses based on 138 or $69\\mathrm{mg}$ of $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ were performed. For a synthesis with $138~\\mathrm{\\mg}$ of $\\mathrm{Pb}{\\bf B}{\\bf r}_{2},$ the amounts of cesium and surfactants are doubled except that $7.5~\\mathrm{mL}$ of octadecene was used. $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ is weighed in the glovebox and transferred to a $25~\\mathrm{mL}$ 3-neck flask together with octadecene. The cloudy suspension is heated to 120 $^{\\circ}\\mathrm{C}$ under vacuum or nitrogen. Subsequently, oleic acid and oleylamine are injected under nitrogen atmosphere (also other long chain amines such as dodecylamine can be used in equal molar amounts). After the quick dissolution of $\\mathrm{Pb}{\\bf B}{\\bf r}_{2},$ the synthesis mixture is heated to $180~^{\\circ}\\mathrm{C}$ and Cs-oleate is injected. After ${\\bar{\\textsf{S s}}},$ the cloudy, yellow mixture was cooled with a water bath, and upon cooling, the color changed to bright green. Illustrative photographs are provided in the Supporting Information (Figure S1). \n\nSynthesis in oleylamine as solvent: $69~\\mathrm{mg}$ of $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ was dispersed in $6~\\mathrm{mL}$ of oleylamine and the mixture placed under vacuum for $\\ensuremath{5}\\ensuremath{\\mathrm{~min~}}$ ; then, the temperature was raised to $120~^{\\circ}\\mathrm{C}$ and lead bromide dissolved. The temperature was raised to $180~^{\\circ}\\mathrm{C}$ and $0.4~\\mathrm{mL}$ of Csoleate solution was injected. Two seconds later, $15~\\mathrm{mL}$ of toluene was injected. After cooldown, the particles can be precipitated with acetone. The unpurified mixture has only limited long-term stability (less than $24\\mathrm{~h~}$ ). \n\nPurification (for a synthesis based on $69~\\mathrm{mg}$ of $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}.$ ): the crude solution is centrifuged for $3\\mathrm{\\min}$ at 10 000 rpm and the colored supernatant is discarded. Then, $300\\mu\\mathrm{L}$ of hexane is added (or more to improve yield but resulting in a more polydisperse ensemble of NCs) and the NCs are dispersed by shaking. Then, the suspension is centrifuged $(3\\mathrm{~\\min},\\mathrm{~\\}10000\\mathrm{~\\rpm})$ to discard larger NCs and agglomerates. Another $300~\\mu\\mathrm{L}$ of hexane is added to the supernatant, resulting in a colloidally stable, green dispersion of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs. However, the dispersion still contains ODE and other impurities. To obtain only NCs and ligands, $25\\mu\\mathrm{L}$ of both oleic acid and oleylamine and $600~\\mu\\mathrm{L}$ of acetone were added. After centrifugation (3 min, 4400 rpm), the colorless supernatant is discarded and ${\\bar{6}}00\\ \\mu\\mathrm{L}$ of hexane is added to redisperse the NCs. This procedure can be repeated several times without destroying the NCs or decreasing their PL. To have less organics in the last mixture, one decrease the amounts and add only 5 $\\mu\\mathrm{L}$ of both ligands. This was the purification used for the ICP measurements, but such dispersions have poor long-term stability (less than 1 week). \n\nSize selection (for a synthesis based on $138~\\mathrm{mg}$ lead bromide): The crude synthesis mixture is centrifuged and the colored supernatant is discarded. Then, $150\\mu\\mathrm{L}$ of hexane is added to disperse the precipitate and this suspension is centrifuged. The supernatant containing small particles is discarded and another $150\\mu\\mathrm{L}$ of hexane is added, followed by centrifugation to discard larger NCs and agglomerates. Then, 300 $\\mu\\mathrm{L}$ of hexane is added to the supernatant, resulting in a colloidally stable dispersion of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs that is more monodisperse as the very small and very big NCs are discarded. To this refined dispersion, $20~\\mu\\mathrm{L}$ of both oleylamine and oleic acid are added to preserve the PL of the NCs during the next steps. Now, acetone is added droplet by droplet until the dispersion turns cloudy. By centrifugation, a first fraction of NCs with a mean diameter of $12.6\\ \\mathrm{nm}$ can be collected (Figure 3). This procedure can be repeated over 10 times, each time yielding a fraction of dots with a smaller average diameter than the previous fraction. After 10 cycles the mean diameter is reduced to 7.6 nm (Figure 3). The size was confirmed with TEM and the mentioned sizes are based on an ensemble of 100 particles. \n\nGeneral characterizaton: UV−vis absorption spectra were collected using a Jasco V670 spectrometer in transmission mode. Fluorolog iHR 320 Horiba Jobin Yvon spectrofluorimeter equipped with a PMT detector was used to acquire steady-state PL spectra from solutions and films. The quantum yield was determined referenced to the standard dye fluorescein. The quantum yields provided in this paper were calculated as the average the quantum yields at excitation wavelengths of 440 and $460\\ \\mathrm{nm}$ . Powder X-ray diffraction patterns (XRD) were collected with STOE STADI $\\mathrm{~\\bf~P~}$ powder diffractometer, operating in transmission mode. Germanium monochromator, Cu Kα1 irradiation and silicon strip detector Dectris Mythen were used. Transmission electron microscopy (TEM) images were recorded using JEOL JEM-2200FS microscope operated at $200\\mathrm{kV}.$ . Details on the ICP analysis are found in the Supporting Information, section: the experimental molar extinction coefficient. \n\nNMR characterization: Nuclear Magnetic Resonance (NMR) measurements were recorded on a Bruker Avance III HD Spectrometer operating at a $\\mathrm{^{1}H}$ frequency of $500.26~\\mathrm{\\MHz}$ and equipped with a BBFO-Z probe. The sample temperature was set to 298.2 K. One dimensional (1D) $^{1}\\mathrm{H}$ and 2D NOESY (Nuclear Overhauser Effect Spectroscopy) spectra were acquired using standard pulse sequences from the Bruker library. For the quantitative 1D $^{1}\\mathrm{H}$ measurements, $64\\mathrm{k}$ data points were sampled with the spectral width set to $20\\ \\mathrm{ppm}$ and a relaxation delay of 30 s. NOESY mixing time was set to $300~\\mathrm{{ms}}$ and 4096 data points in the direct dimension for 512 data points in the indirect dimension were typically sampled, with the spectral width set to $10\\ \\mathrm{ppm}$ . Diffusion measurements (2D DOSY) were performed using a double stimulated echo sequence for convection compensation and with monopolar gradient pulses.48 Smoothed rectangle gradient pulse shapes were used throughout. The gradient strength was varied linearly from 2 to $95\\%$ of the probe’s maximum value in 32 or 64 increments, with the gradient pulse duration and diffusion delay optimized to ensure a final attenuation of the signal in the final increment of less than $10\\%$ relative to the first increment. For 2D processing, the spectra were zero filled until a 4096−2048 real data matrix. Before Fourier transformation, the 2D spectra were multiplied with a squared cosine bell function in both dimensions, the 1D spectra were multiplied with an exponential window function. Concentrations were obtained using the Digital ERETIC method, as provided in the standard software of Bruker. The diffusion coefficients were obtained by fitting the appropriate StejskalTanner equation to the signal intensity decay.49 \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.5b06295. \n\nCovalent bond classification concepts; explanatory photographs; TEM, UV−vis and PL characterization of NCs synthesized with different protocols than the standard procedure; experimental data and calculations on the ICP−MS measurements and intrinsic absorption coefficient; theoretical calculations on the intrinsic absorption coefficient; additional NMR spectra; a spreadsheet with the experimental $\\mu_{i}$ values at every wavelength (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\n$^{*}\\mathrm{E}$ -mail: mvkovalenko@ethz.ch. \n$^{*}\\mathrm{E}$ -mail: zeger.hens@ugent.be. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThe authors thank Mathias Grotevent for additional TEM measurements. J.D.R. thanks the FWO (Research Foundation Flanders) for financial support. The authors thank Laura Piveteau for interesting scientific discussions. We thank the NMR Research Facility of the Laboratory for Inorganic Chemistry of the ETH Zrich for use of the NMR equipment. M.V.K. and Z.H. acknowledge support by the European Comission via the Marie-Sklodowska Curie action Phonsi (H2020-MSCA-ITN-642656). Z.H. acknowledges the FWOVlaanderen (project G.0760.12), the Belgian Science Policy office (IAP 7.35, photonics@be) and Ghent University (GOA 01G01513) for funding. M.I. thanks AGAUR for her Beatriu de Pinos postdoctoral grant. \n\n# REFERENCES \n\n(1) Chung, I.; Lee, B.; He, J. $\\mathrm{Q.;}$ Chang, R. P. H.; Kanatzidis, M. G. \nAll-Solid-State Dye-Sensitized Solar Cells with High Efficiency. Nature \n2012, 485, 486−489. \n(2) Green, M. A.; Ho-Baillie, A.; Snaith, H. J. The Emergence of \nPerovskite Solar Cells. Nat. Photonics 2014, 8, 506−514. (3) Hao, F.; Stoumpos, C. C.; Cao, D. H.; Chang, R. P. H.; \nKanatzidis, M. G. Lead-Free Solid-State Organic-Inorganic Halide \nPerovskite Solar Cells. Nat. Photonics 2014, 8, 489−494. (4) Miyata, A.; Mitioglu, A.; Plochocka, P.; Portugall, O.; Wang, J. T. \nW.; Stranks, S. D.; Snaith, H. J.; Nicholas, R. J. Direct Measurement of \nthe Exciton Binding Energy and Effective Masses for Charge Carriers \nin Organic-Inorganic Tri-Halide Perovskites. Nat. Phys. 2015, 11, \n582−587. (5) Burschka, J.; Pellet, N.; Moon, S. J.; Humphry-Baker, R.; Gao, P.; \nNazeeruddin, M. K.; Gratzel, M. Sequential Deposition as a Route to \nHigh-Performance Perovskite-Sensitized Solar Cells. Nature 2013, \n499, 316−319. (6) Yakunin, S.; Sytnyk, M.; Kriegner, D.; Shrestha, S.; Richter, M.; Matt, G. J.; Azimi, H.; Brabec, C. J.; Stangl, J.; Kovalenko, M. V.; Heiss, W. Detection of X-Ray Photons by Solution-Processed Lead Halide Perovskites. Nat. Photonics 2015, 9, 444−449. \n(7) Dou, L. T.; Yang, Y.; You, J. B.; Hong, Z. R.; Chang, W. H.; Li, G. Solution-Processed Hybrid Perovskite Photodetectors with High Detectivity. Nat. Commun. 2014, 5, 5404. \n(8) Tan, Z. K.; Moghaddam, R. S.; Lai, M. L.; Docampo, P.; Higler, R.; Deschler, F.; Price, M.; Sadhanala, A.; Pazos, L. M.; Credgington, D.; Hanusch, F.; Bein, T.; Snaith, H. J.; Friend, R. H. Bright LightEmitting Diodes Based on Organometal Halide Perovskite. Nat. Nanotechnol. 2014, 9, 687−692. \n(9) Xing, G. C.; Mathews, N.; Lim, S. S.; Yantara, N.; Liu, X. F.; Sabba, D.; Gratzel, M.; Mhaisalkar, S.; Sum, T. C. Low-Temperature Solution-Processed Wavelength-Tunable Perovskites for Lasing. Nat. Mater. 2014, 13, 476−480. \n(10) Yakunin, S.; Protesescu, L.; Krieg, F.; Bodnarchuk, M. I.; Nedelcu, G.; Humer, M.; De Luca, G.; Fiebig, M.; Heiss, W.; Kovalenko, M. V. Low-Threshold Amplified Spontaneous Emission and Lasing from Colloidal Nanocrystals of Caesium Lead Halide Perovskites. Nat. Commun. 2015, $\\begin{array}{r}{{6},}\\end{array}$ 8056. \n(11) Zhang, F.; Zhong, H.; Chen, C.; Wu, X.-g.; Hu, X.; Huang, H.; Han, J.; Zou, B.; Dong, Y. Brightly Luminescent and Color-Tunable Colloidal CH3NH3PbX3 $\\mathrm{(X=Br,~I,~}$ Cl) Quantum Dots: Potential Alternatives for Display Technology. ACS Nano 2015, 9, 4533−4542. (12) Zhu, F.; Men, L.; Guo, Y.; Zhu, $\\mathrm{Q.;}$ Bhattacharjee, U.; Goodwin, P. M.; Petrich, J. W.; Smith, E. A.; Vela, J. Shape Evolution and Single Particle Luminescence of Organometal Halide Perovskite Nanocrystals. ACS Nano 2015, 9, 2948−2959. \n(13) Schmidt, L. C.; Pertegás, A.; González-Carrero, S.; Malinkiewicz, O.; Agouram, S.; Mínguez Espallargas, G.; Bolink, H. J.; Galian, R. E.; Pérez-Prieto, J. Nontemplate Synthesis of CH3NH3PbBr3 Perovskite Nanoparticles. J. Am. Chem. Soc. 2014, 136, 850−853. \n(14) Tyagi, P.; Arveson, S. M.; Tisdale, W. A. Colloidal Organohalide Perovskite Nanoplatelets Exhibiting Quantum Confinement. J. Phys. Chem. Lett. 2015, 6, 1911−1916. \n(15) Jang, D. M.; Park, K.; Kim, D. H.; Park, J.; Shojaei, F.; Kang, H. S.; Ahn, J. P.; Lee, J. W.; Song, J. K. Reversible Halide Exchange Reaction of Organometal Trihalide Perovskite Colloidal Nanocrystals for Full-Range Band Gap Tuning. Nano Lett. 2015, 15, 5191−5199. (16) Horvath, E.; Spina, M.; Szekrenyes, Z.; Kamaras, K.; Gaal, R.; Gachet, D.; Forro, L. Nanowires of Methylammonium Lead Iodide CH3NH3Pbl3 Prepared by Low Temperature Solution-Mediated Crystallization. Nano Lett. 2014, 14, 6761−6766. \n(17) Ayguler, M. F.; Weber, M. D.; Puscher, B. M. D.; Medina, D. D.; Docampo, P.; Costa, R. D. Light-Emitting Electrochemical Cells Based on Hybrid Lead Halide Perovskite Nanoparticles. J. Phys. Chem. C 2015, 119, 12047−12054. \n(18) Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Krieg, F.; Caputo, R.; Hendon, C. H.; Yang, R. X.; Walsh, A.; Kovalenko, M. V. Nanocrystals of Cesium Lead Halide Perovskites (CsPbX3, $\\mathrm{X}=\\mathrm{Cl},$ Br, and I): Novel Optoelectronic Materials Showing Bright Emission with Wide Color Gamut. Nano Lett. 2015, 15, 3692−3696. \n(19) Nedelcu, G.; Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Grotevent, M. J.; Kovalenko, M. V. Fast Anion-Exchange in Highly Luminescent Nanocrystals of Cesium Lead Halide Perovskites (CsPbX3, $\\mathbf{X}=\\mathbf{Cl} $ , Br, I). Nano Lett. 2015, 15, 5635−5640. \n(20) Zhang, D.; Eaton, S. W.; Yu, Y.; Dou, L.; Yang, P. SolutionPhase Synthesis of Cesium Lead Halide Perovskite Nanowires. J. Am. Chem. Soc. 2015, 137, 9230−9233. \n(21) Akkerman, $\\mathsf{Q}.$ A.; D’Innocenzo, V.; Accornero, S.; Scarpellini, A.; Petrozza, A.; Prato, M.; Manna, L. Tuning the Optical Properties of Cesium Lead Halide Perovskite Nanocrystals by Anion Exchange Reactions. J. Am. Chem. Soc. 2015, 137, 10276−10281. \n(22) Green, M. L. H. A. New Approach to the Formal Classification of Covalent Compounds of the Elements. J. Organomet. Chem. 1995, 500, 127−148. (23) Green, M. L. H.; Parkin, G. Application of the Covalent Bond Classification Method for the Teaching of Inorganic Chemistry. J. Chem. Educ. 2014, 91, 807−816. \n(24) Fritzinger, B.; Capek, R. K.; Lambert, K.; Martins, J. C.; Hens, Z. Utilizing Self-Exchange To Address the Binding of Carboxylic Acid Ligands to CdSe Quantum Dots. J. Am. Chem. Soc. 2010, 132, 10195− 10201. \n(25) De Roo, J.; Justo, Y.; De Keukeleere, K.; Van den Broeck, F.; Martins, J. C.; Van Driessche, I.; Hens, Z. Carboxylic-Acid-Passivated Metal Oxide Nanocrystals: Ligand Exchange Characteristics of a New Binding Motif. Angew. Chem., Int. Ed. 2015, 54, 6488−6491. \n(26) De Roo, J.; Van den Broeck, F.; De Keukeleere, K.; Martins, J. C.; Van Driessche, I.; Hens, Z. Unravelling the Surface Chemistry of Metal Oxide Nanocrystals, the Role of Acids and Bases. J. Am. Chem. Soc. 2014, 136, 9650−9657. \n(27) Anderson, N. C.; Hendricks, M. P.; Choi, J. J.; Owen, J. S. Ligand Exchange and the Stoichiometry of Metal Chalcogenide Nanocrystals: Spectroscopic Observation of Facile Metal-Carboxylate Displacement and Binding. J. Am. Chem. Soc. 2013, 135, 18536− 18548. \n(28) Cros-Gagneux, A.; Delpech, F.; Nayral, C.; Cornejo, A.; Coppel, Y.; Chaudret, B. Surface Chemistry of InP Quantum Dots: A Comprehensive Study. J. Am. Chem. Soc. 2010, 132, 18147−18157. (29) Valdez, C. N.; Schimpf, A. M.; Gamelin, D. R.; Mayer, J. M. Low Capping Group Surface Density on Zinc Oxide Nanocrystals. ACS Nano 2014, 8, 9463−9470. \n(30) Protesescu, L.; Nachtegaal, M.; Voznyy, O.; Borovinskaya, O.; Rossini, A. J.; Emsley, L.; Coperet, C.; Gunther, D.; Sargent, E. H.; Kovalenko, M. V. Atomistic Description of Thiostannate-Capped CdSe Nanocrystals: Retention of Four-Coordinate SnS4Motif and Preservation of Cd-Rich Stoichiometry. J. Am. Chem. Soc. 2015, 137, 1862−1874. \n(31) Morris-Cohen, A. J.; Frederick, M. T.; Lilly, G. D.; McArthur, E. A.; Weiss, E. A. Organic Surfactant-Controlled Composition of the Surfaces of CdSe Quantum Dots. J. Phys. Chem. Lett. 2010, 1, 1078− 1081. \n(32) Moreels, I.; Fritzinger, B.; Martins, J. C.; Hens, Z. Surface Chemistry of Colloidal PbSe Nanocrystals. J. Am. Chem. Soc. 2008, 130, 15081−15086. \n(33) Morris-Cohen, A. J.; Donakowski, M. D.; Knowles, K. E.; Weiss, E. A. The Effect of a Common Purification Procedure on the Chemical Composition of the Surfaces of CdSe Quantum Dots Synthesized with Trioctylphosphine Oxide. J. Phys. Chem. C 2010, 114, 897−906. (34) Hassinen, A.; Moreels, I.; De Nolf, K.; Smet, P. F.; Martins, J. C.; Hens, Z. Short-Chain Alcohols Strip X-Type Ligands and Quench the Luminescence of PbSe and CdSe Quantum Dots, Acetonitrile Does Not. J. Am. Chem. Soc. 2012, 134, 20705−20712. \n(35) Fritzinger, B.; Moreels, I.; Lommens, P.; Koole, R.; Hens, Z.; Martins, J. C. In Situ Observation of Rapid Ligand Exchange in Colloidal Nanocrystal Suspensions Using Transfer NOE Nuclear Magnetic Resonance Spectroscopy. J. Am. Chem. Soc. 2009, 131, 3024−3032. \n(36) Hens, Z.; Moreels, I. Light Absorption by Colloidal Semiconductor Quantum Dots. J. Mater. Chem. 2012, 22, 10406−10415. (37) Murtaza, G.; Ahmad, I. First Principle Study of the Structural and Optoelectronic Properties of Cubic Perovskites CsPbM3 $\\mathbf{\\tilde{M}}=\\mathbf{Cl},$ Br, I). Phys. B 2011, 406, 3222−3229. \n(38) Hens, Z.; Martins, J. C. A Solution NMR Toolbox for Characterizing the Surface Chemistry of Colloidal Nanocrystals. Chem. Mater. 2013, 25, 1211−1221. \n(39) Van Lokeren, L.; Maheut, G.; Ribot, F.; Escax, V.; Verbruggen, I.; Sanchez, C.; Martins, J. C.; Biesemans, M.; Willem, R. Characterization of Titanium Dioxide Nanoparticles Dispersed in Organic Ligand Solutions by Using a Diffusion-Ordered Spectroscopy-Based Strategy. Chem. - Eur. J. 2007, 13, 6957−6966. \n(40) Sangeetha, N. M.; Gauvin, M.; Decorde, N.; Delpech, F.; Fazzini, P. F.; Viallet, B.; Viau, G.; Grisolia, J.; Ressier, L. A Transparent Flexible Z-Axis Sensitive Multi-Touch Panel Based on Colloidal ITO Nanocrystals. Nanoscale 2015, 7, 12631−12640. (41) Matioszek, D.; Ojo, W. S.; Cornejo, A.; Katir, N.; El Ezzi, M.; Le Troedec, M.; Martinez, H.; Gornitzka, H.; Castel, A.; Nayral, C.; Delpech, F. From Rational Design of Organometallic Precursors to Optimized Synthesis of Core/Shell Ge/GeO2 Nanoparticles. Dalton Trans. 2015, 44, 7242−7250. \n(42) Dierick, R.; Van den Broeck, F.; De Nolf, K.; Zhao, $\\mathrm{Q.;}$ Vantomme, A.; Martins, J. C.; Hens, Z. Surface Chemistry of CuInS2 Colloidal Nanocrystals, Tight Binding of L-Type Ligands. Chem. Mater. 2014, 26, 5950−5957. \n(43) Van Lokeren, L.; Willem, R.; van der Beek, D.; Davidson, P.; Morris, G. A.; Ribot, F. Probing the Anions Mediated Associative Behavior of Tin-12 Oxo-Macrocations by Pulsed Field Gradient NMR Spectroscopy. J. Phys. Chem. C 2010, 114, 16087−16091. \n(44) Hubbard, J. B.; Douglas, J. F. Hydrodynamic Friction of Arbitrarily Shaped Brownian Particles. Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 1993, 47, R2983−R2986. \n(45) Douglas, J. F.; Zhou, H. X.; Hubbard, J. B. Hydrodynamic Friction and the Capacitance of Arbitrarily Shaped Objects. Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 1994, 49, 5319− 5337. \n(46) Gomes, R.; Hassinen, A.; Szczygiel, A.; Zhao, $\\mathsf{Q}.$ A.; Vantomme, A.; Martins, J. C.; Hens, Z. Binding of Phosphonic Acids to CdSe Quantum Dots: A Solution NMR Study. J. Phys. Chem. Lett. 2011, 2, 145−152. \n(47) Owen, J. S.; Park, J.; Trudeau, P. E.; Alivisatos, A. P. Reaction Chemistry and Ligand Exchange at Cadmium-Selenide Nanocrystal Surfaces. J. Am. Chem. Soc. 2008, 130, 12279−12280. \n(48) Connell, M. A.; Bowyer, P. J.; Bone, P. A.; Davis, A. L.; Swanson, A. G.; Nilsson, M.; Morris, G. A. Improving the Accuracy of Pulsed Field Gradient NMR Diffusion Experiments: Correction for Gradient Non-Uniformity. J. Magn. Reson. 2009, 198, 121−131. (49) Sinnaeve, D. The Stejskal-Tanner Equation Generalized for any Gradient Shape-an Overview of Most Pulse Sequences Measuring Free Diffusion. Concepts Magn. Reson., Part A 2012, 40A, 39−65. " + }, + { + "id": "10.1038_NCHEM.2524", + "DOI": "10.1038/NCHEM.2524", + "DOI Link": "http://dx.doi.org/10.1038/NCHEM.2524", + "Relative Dir Path": "mds/10.1038_NCHEM.2524", + "Article Title": "The structural and chemical origin of the oxygen redox activity in layered and cation-disordered Li-excess cathode materials", + "Authors": "Seo, DH; Lee, J; Urban, A; Malik, R; Kang, S; Ceder, G", + "Source Title": "NATURE CHEMISTRY", + "Abstract": "Lithium-ion batteries are now reaching the energy density limits set by their electrode materials, requiring new paradigms for Li+ and electron hosting in solid-state electrodes. Reversible oxygen redox in the solid state in particular has the potential to enable high energy density as it can deliver excess capacity beyond the theoretical transition-metal redox-capacity at a high voltage. Nevertheless, the structural and chemical origin of the process is not understood, preventing the rational design of better cathode materials. Here, we demonstrate how very specific local Li-excess environments around oxygen atoms necessarily lead to labile oxygen electrons that can be more easily extracted and participate in the practical capacity of cathodes. The identification of the local structural components that create oxygen redox sets a new direction for the design of high-energy-density cathode materials.", + "Times Cited, WoS Core": 1190, + "Times Cited, All Databases": 1265, + "Publication Year": 2016, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000378280400013", + "Markdown": "# The structural and chemical origin of the oxygen redox activity in layered and cation-disordered Li-excess cathode materials \n\nDong-Hwa Seo1,2†, Jinhyuk Lee1,2†, Alexander Urban2, Rahul Malik1, ShinYoung Kang1 and Gerbrand Ceder1,2,3\\* \n\nLithium-ion batteries are now reaching the energy density limits set by their electrode materials, requiring new paradigms for ${{\\bf{L}}{\\bf{j}}^{+}}$ and electron hosting in solid-state electrodes. Reversible oxygen redox in the solid state in particular has the potential to enable high energy density as it can deliver excess capacity beyond the theoretical transition-metal redoxcapacity at a high voltage. Nevertheless, the structural and chemical origin of the process is not understood, preventing the rational design of better cathode materials. Here, we demonstrate how very specific local Li-excess environments around oxygen atoms necessarily lead to labile oxygen electrons that can be more easily extracted and participate in the practical capacity of cathodes. The identification of the local structural components that create oxygen redox sets a new direction for the design of high-energy-density cathode materials. \n\nver the past two decades, lithium-ion battery technology has contributed greatly to human progress and enabled many of the conveniences of modern life by powering increasingly capable portable electronics1. However, with the increasing complexity of technology comes a demand for batteries with higher energy density, which thus leads to a requirement for cathode materials with higher energy densities2–4. \n\nThe traditional design paradigm for Li-ion battery cathodes has been to create compounds in which the amount of extractable ${\\mathrm{Li}}^{+}$ is well balanced with an oxidizable transition metal (TM) species (such as Mn, Fe, Co or Ni) to provide the charge-compensating electrons, all contained in an oxide or sulfide host. Transition metals have been considered the sole sources of electrochemical activity in an intercalation cathode, and as a consequence the theoretical specific capacity is limited by the number of electrons that the transitionmetal ions can exchange per unit mass5–9. Recent observations have brought this simple picture into question and argued that oxygen ions in oxide cathodes may also participate in the redox reaction. This oxygen redox is often ascribed to covalency, following theoreti$\\mathrm{cal^{10,11}}$ and experimental12–16 work in the last two decades that has demonstrated large electron density changes on oxygen when the transition metal is oxidized. However, covalency cannot lead to a higher capacity than would be expected from the transition metal alone, as the number of transition-metal orbitals remains unchanged when they hybridize with the oxygen ligands. The more important argument for the future of the Li-ion battery field is whether oxygen oxidation can create extra capacity beyond what is predicted from the transition-metal content alone, as has been argued for several Li-excess materials, such as $\\mathrm{Li}_{1.2}\\mathrm{Ni}_{0.2}\\mathrm{Mn}_{0.6}\\mathrm{O}_{2}$ $\\mathrm{Li}_{2}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{2}$ and $\\mathrm{Li_{1.3}M n_{0.4}N b_{0.3}O_{2}}$ (refs 3,17,18). \n\nIn this Article, we use ab initio calculations to demonstrate which specific chemical and structural features lead to electrochemically active oxygen states in cathode materials. Our results uncover a specific atomistic origin of oxygen redox and explain why this oxygen capacity is so often observed in Li-excess materials and why it is observed with some metals and not with others. The specific nature of our findings reveals a clear and exciting path towards creating the next generation of cathode materials with substantially higher energy density than current cathode materials. \n\n# Results and discussion \n\nAppearance of labile oxygen states in Li metal oxides. It is generally understood that the relative energy of the TM versus oxygen states determines which species (TM versus O) are oxidized upon delithiation1,19. As the energy level of those states depends on the species in a compound and their chemical bonding, local environments in a crystal structure can play a critical role in the redox processes and the participation of oxygen in them10. Unlike in conventional stoichiometric layered cathode materials, which are well ordered and in which only a single local environment exists for oxygen ions, a variety of local oxygen environments exist in Li-excess materials or materials with cation disorder. By systematically calculating and analysing the density of states (DOS) and charge/spin density around oxygen ions in various local environments using density functional theory (DFT) (ref. 20), we demonstrate that the Li-excess content and the local configuration sensitively affect oxygen redox activity in the oxide cathodes. To accurately study the oxygen redox activity, all calculations were performed with DFT using the Heyd–Scuseria–Ernzerhof (HSE06) hybrid functional21, which can correct the self-interaction errors (SIEs) for both metal (M) and O atoms. Note that the generalized gradient approximation (GGA) and $\\mathrm{GGA{+}U}_{\\mathrm{i}}$ , which are frequently used in DFT calculations, cannot properly predict the oxygen redox activity, because they cannot correct the SIE for O atoms22. \n\nWe start with $\\mathrm{LiNiO}_{2}$ (containing site disorder) and $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ as two simple model systems before moving on to more complex materials. $\\mathrm{LiNiO}_{2}$ is one of the most studied materials and Ni is the dominant redox active species in many technologically important cathodes such as $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ and $\\mathrm{LiNi_{0.8}C o_{0.15}A l_{0.05}O_{2}}$ (refs 23,24). In perfectly layered $\\mathrm{LiNiO}_{2}$ , oxygen ions are exclusively coordinated by three Li and three Ni (Fig. 1b). The other two environments in Fig. 1 are created by $\\mathrm{Li/Ni}$ exchange (anti-sites): two Li and four Ni (Fig. 1a) and four Li and two Ni (Fig. 1c). \n\n![](images/c6cbcec5c4e7c826b1ce2bce3e909db149b45ef8f436858c872ecc9880aa88c4.jpg) \nFigure 1 | Effect of local atomic environments on the electronic states of O ions in cation-mixed layered $\\mathbf{LiNiO}_{2}$ . Cation mixing introduces various local environments around oxygen. a–c, Projected density of states (pDOS) of the $\\textsf{O}2p$ orbitals of O atoms in cation-mixed layered $\\mathsf{L i N i O}_{2}$ coordinated by two Li and four Ni (a), three Li and three Ni (b) and four Li and two Ni (c). Insets: coordination of the O ion. d, Isosurface of the charge density (yellow) around the oxygen coordinated by four Li and two Ni $(\\bullet)$ , in the energy range of 0 to $-1.64\\mathrm{eV.}$ Increased pDOS can be found near the Fermi level for the $\\textsf{O}$ ion coordinated by four Li and two Ni, which originates from the particular Li–O–Li configuration. \n\nThe projected DOS (pDOS) of the oxygen $2p$ states of the three oxygen environments are shown in Fig. 1a–c. Although there is not much change in the oxygen pDOS between the 4Ni/2Li and 3Ni/3Li configurations, the oxygen pDOS changes substantially when four Li ions are near the oxygen (Fig. 1c). In particular, a much greater pDOS between 0 and $-2.5\\mathrm{eV}$ of the Fermi level is found for the oxygen ion coordinated with four Li and two Ni ions (Fig. 1c). The origin of this increased DOS can be identified by visualizing the charge density around the oxygen ion for the energy range between 0 and $-1.64\\mathrm{~eV}$ (Fig. 1d). This energy range corresponds to the extraction of one electron per $\\mathrm{LiNiO}_{2}$ . As seen in the isosurface plot, a large charge density resembling the shape of an isolated O $2p$ orbital is present along the direction where oxygen is linearly bonded to two Li (Li–O–Li configuration). This result indicates that the labile electrons from the O ion in the local Li-excess environment originate from this particular Li–O–Li configuration. This state has moved up from the bonding O $2p$ manifold of states at lower energies. \n\nIn many of the new exciting cathode materials2,3,18,25, Li-excess is created by the substitution of some (transition) metals by Li, necessarily leading to more Li–O–Li configurations and, as a consequence, more potentially labile oxygen electrons (Supplementary Fig. 7). To confirm this hypothesis, we studied the oxygen electronic states in $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ in which all O ions are in a local Li-excess environment containing a Li–O–Li configuration (Fig. 2a)26,27. \n\nFigure 2b presents pDOS from the O $2p$ orbitals and the $\\mathrm{Mn}\\ 3d$ orbitals in $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ . A much larger pDOS originates from the oxygen states than from the manganese states between 0 and $-2.5\\mathrm{eV}.$ . The corresponding charge density plot around the O ion within 0 to $-0.9\\mathrm{eV}$ again resembles an oxygen $\\boldsymbol{p}$ orbital along the Li–O–Li axis (Fig. 2c), confirming that the oxygen orbital along the Li–O–Li configuration contributes to the large oxygen pDOS close to the Fermi level. Within 0 to $-0.9\\mathrm{eV}_{\\mathrm{i}}$ roughly two electrons per $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ can be extracted. Oxygen oxidation in this compound is consistent with theoretical work in the literature26,27. To summarize, the Li–O–Li configuration introduces labile oxygen electrons in $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ , as in the case of the partially cation-mixed $\\mathrm{LiNiO}_{2}$ . \n\nOxygen charge transfer from the labile oxygen states in Li-excess cathode materials. With the basic ideas in hand of how labile oxygen states can be created, we investigated more complex Li-excess compounds in which extra redox capacity beyond the theoretical TM-redox capacity has been observed: $\\mathrm{Li}(\\mathrm{Li}/\\mathrm{Mn}/\\mathrm{M})\\mathrm{O}_{2}$ \n\n1 $\\begin{array}{r}{\\mathbf{M}=\\mathbf{N}\\mathbf{i},}\\end{array}$ $\\begin{array}{r}{\\ C\\boldsymbol{0},}\\end{array}$ and so on) and $\\mathrm{Li}_{2}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{3}$ are layered Li-excess materials17,28, and $\\mathrm{Li}_{1.25}\\mathrm{Mn}_{0.5}\\mathrm{Nb}_{0.25}\\mathrm{O}_{2}$ $\\mathrm{(\\approxLi_{1.3}M n_{0.4}N b_{0.3}O_{2})}$ and $\\mathrm{Li_{1.2}N i_{1/3}T i_{1/3}M o_{2/15}O_{2}}$ are cation-disordered Li-excess materials18,29,30. For each of the compounds we constructed unit cells that take into account as much as is known about the structures. Fragments of these unit cells are shown in the top row of Fig. 3 (for more details see Supplementary Section ‘Preparation of the structure models’). All compounds were delithiated beyond the conventional limit from TM redox. \n\nFigure 3a–d plots the isosurface of the spin density around oxygen in partially delithiated $\\mathrm{Li}_{1.17-x}\\mathrm{Ni}_{0.25}\\mathrm{Mn}_{0.58}\\mathrm{O}_{2}$ $\\langle x=0.5\\$ , 0.83), $\\mathrm{Li}_{2-x}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{3}$ $\\stackrel{\\cdot}{x}=0.5$ , 1.5), $\\mathrm{Li}_{1.17-x}\\mathrm{Ni}_{0.33}\\mathrm{Ti}_{0.42}\\mathrm{Mo}_{0.08}\\mathrm{O}_{2}$ ( $\\stackrel{\\cdot}{x}=0.5$ 0.83) and $\\mathrm{Li}_{1.25-x}\\mathrm{Mn}_{0.5}\\mathrm{Nb}_{0.25}\\mathrm{O}_{2}$ $\\begin{array}{r}{x=0.75,}\\end{array}$ 1.0), respectively. To simplify the presentation, the spin densities around metal ions are not drawn in the figures. In all cases, we observe a large spin density from the oxygen ions along the Li–O–Li configuration with the shape of an isolated O $2p$ orbital, indicating a hole along the Li–O–Li configuration. These holes along the Li–O–Li configurations increase in number and density upon delithiation. As a hole on an O ion is direct evidence of oxygen oxidation31, these results demonstrate that extraction of the labile oxygen electrons along the Li–O–Li configuration is the origin of oxygen oxidation and extra capacity beyond the TM redox capacity. Note that in the partially delithiated $\\mathrm{Li}_{1.17-x}\\mathrm{Ni}_{0.33}\\mathrm{Ti}_{0.42}\\mathrm{Mo}_{0.08}\\mathrm{O}_{2}$ , one of the oxidized oxygens with the Li–O–Li configuration is not in a local Li-excess environment (Fig. 3c). This oxygen is coordinated with three TM (two $\\mathrm{Ni,}$ one Ti) and three Li, but it still has the Li–O–Li configuration because of local cation disorder (Supplementary Fig. 7). In $\\mathrm{Li}_{0.5}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{3}$ we observe a weak $\\sigma$ bond between two of the oxidized O ions (blue dashed oval) and an accompanying small rotation of their Li–O–Li axes (Supplementary Fig. 8). This is consistent with the experimental finding of O−O bonds (peroxo-like species) in the compound at high delithiation3. The conditions under which oxygen hole formation leads to peroxo-like bonds are discussed in more detail in the section ‘Conditions for peroxo-like O–O bond formation’ and in Supplementary Figs 8 and 9. \n\nSo far, we have established that the Li–O–Li configuration, either as a result of excess Li or cation disorder, gives rise to the labile oxygen electrons that participate in redox activity. In the following, we will unravel the structural and chemical origin of this phenomenon and show how, through the judicious choice of (transition) metal chemistry, it can be modified and controlled. \n\nOrigin of the labile oxygen states and their redox processes. In stoichiometric well-layered Li metal oxides, such as $\\mathrm{LiCoO}_{2}$ , all O ions are coordinated by exactly three metal (M) ions and three \n\n![](images/ab2ea90174d4d70a6a59f347e3e702b87c5561dd9d2852e964df03a0c87b9857.jpg) \nFigure 2 | Effect of Li–O–Li configurations on the electronic states of O ions in $\\mathsf{L i}_{2}\\mathsf{M n O}_{3}$ . The Li–O–Li configurations also lead to labile oxygen states in this material. a, Illustration of Li–O–Li configurations in $\\mathsf{L i}_{2}\\mathsf{M n O}_{3}$ . b, pDOS of the O $2p$ orbitals (black) and Mn 3d orbitals (red) in $\\mathsf{L i}_{2}\\mathsf{M n O}_{3}$ . c, Isosurface of the charge density (yellow) around oxygen in $\\mathsf{L i}_{2}\\mathsf{M n O}_{3}$ , in the energy range of 0 to $-0.9\\mathrm{eV}$ . \n\nLi ions, in such a way that each O $2p$ orbital can hybridize with the M $d/s/p$ orbitals along the linear Li–O–M configuration (Fig. 4a). From here on, $\\mathbf{\\dot{M}}^{\\mathbf{\\alpha}}$ refers to both TM and non-TM species with $d$ electrons. Due to the symmetry of this configuration, hybridized molecular orbitals (states) with seven different characters arise from the orbital interactions, which then form distinct bands under the periodic potential in a crystal (Fig. 4b)10,32. Overlap between M $3d_{x2-y2}$ , $\\bar{d}_{z2}$ (or $4d$ equivalents) and O $2p$ orbitals leads to $e_{g}^{\\mathrm{b}}$ (bonding) and $e_{g}^{*}$ (anti-bonding) states, overlap between M 4s (or 5s) and O $2p$ orbitals leads to $a_{1g}^{\\mathrm{b}}$ (bonding) and $a_{1g}^{*}$ (anti-bonding) states, and overlap between M $^{4p}$ (or $5p\\textunderscore$ ) and O $2p$ orbitals leads to $t_{1u}^{b}$ (bonding) and $t_{1u}^{*}$ (anti-bonding) states. Finally, the overlap of the M $d_{x y},d_{y z}$ and $d_{x z}$ orbitals with the O $2p$ orbital is negligible, which results in isolated $t_{2g}$ states that have a nonbonding characteristic. Considering the dominant contributions in these hybridized states, the $t_{2g}$ , $e_{g}^{*}$ , $a_{1g}^{*}$ and $t_{1u}^{*}$ states can be thought of as M (dominated) and the $\\begin{array}{l l}{{\\vec{t}}_{1u}^{\\mathrm{b}},}&{{a}_{1g}^{\\mathrm{b}}}\\end{array}$ and $e_{g}^{\\mathrm{b}}$ states as O (dominated)10,12,18,28,33. This is the conventional view of the band structure of layered Li-M oxides such as $\\mathrm{LiCoO}_{2}$ (Fig. 4b). Because the Fermi level for the Li–M oxides lies in the $e_{g}^{*}$ or $t_{2g}$ band, oxidation proceeds by removing electrons from these Mdominant states. Hence, although filling or emptying an orbital near the Fermi level can cause some rehybridization and accompanying charge redistribution of the other orbitals10, oxidation in these stoichiometric well-ordered oxides can be considered to be on the M ions (TM ions)10,12. \n\nHowever, this picture needs to be modified for other types of orbital interaction that occur in Li-excess layered or cationdisordered materials. For example, Li-excess in layered materials creates two types of O $2p$ orbital: the O $2p$ orbitals along the Li–O–M configurations and those along the Li–O–Li configurations (Fig. 4c). The O $2p$ orbitals along the Li–O–M configurations hybridize with the M orbitals to form the same hybridized states (bands) as in the stoichiometric layered oxides (Fig. 4b). However, those O $2p$ orbitals along the Li–O–Li configurations do not have an M orbital to hybridize with and do not hybridize with the Li 2s orbital either because of the large energy difference between the O $2p$ and Li 2s orbitals34. Thus, there will be orphaned unhybridized O $2p$ states (bands) whose density of states is proportional to the number of Li–O–Li configurations in the crystal structure (Fig. 4d). \n\nJust as the energy levels of the $t_{2g}$ states are close to those of unhybridized M $d_{x y}/d_{y z}/d_{x z}$ orbitals10,32, the energy level of such an orphaned Li–O–Li state is close to that of the unhybridized O $2p$ orbital, putting it at a higher energy than the hybridized O bonding states $({t}_{1u}^{\\mathrm{b}},\\ {a}_{1g}^{\\mathrm{b}}$ and $e_{g}^{\\mathrm{b}}$ states), but lower than the antibonding $\\mathbf{M}$ states $(e_{g}^{\\ast},a_{1g}^{\\ast}$ and $t_{1u}^{*}$ states). The relative position of the orphaned oxygen state with respect to the non-bonding M $(t_{2g})$ states depends on the M species. Note that in an actual band structure there can be some overlap in energy between different states due to the broadening of the molecular-orbital energy levels under the periodic potential in the crystal structure. Therefore, competition can arise between different states (bands) upon charge transfer35. \n\nThe preferential oxygen oxidation along the Li–O–Li configuration as observed in Fig. 3 can now be explained. As the electrons in the Li–O–Li states are higher in energy than those in the other O $2p$ states (Fig. 4d), oxygen oxidation preferentially occurs from the orphaned Li–O–Li states whenever Li-excess layered or cation-disordered materials are highly delithiated. Such labile Li–O–Li states in Li-excess materials may also explain why oxygen oxidation can be substantial even at a relatively low voltage of ${\\sim}4.3\\mathrm{V}$ in Li-excess materials3,17,18,28. \n\nConditions for peroxo-like $\\mathbf{O-O}$ bond formation. In some cases, oxygen oxidation has been claimed to result in peroxo-like species $^{3,36,37}$ . The insights presented in this Article can now be used to understand under which conditions oxygen holes can coalesce to form peroxo species and when they remain isolated. In rocksalt-like compounds where the oxygen anions form a face-centred cubic array and the cations occupy octahedral sites, oxygen $\\boldsymbol{p}$ orbitals point towards the cations. The almost $90^{\\circ}$ angle between the directions of $\\boldsymbol{p}$ orbitals on neighbouring oxygens prevents their $\\sigma$ overlap. As a result, we find that an $_{\\mathrm{O-O}}$ bond arises only if two neighbouring oxidized oxygens can rotate to hybridize their (oxidized) Li–O–Li states without sacrificing much $\\bf{M}\\mathrm{-}\\mathrm{O}$ hybridization (Supplementary Figs 8 and 9). We find that this rotation to form peroxo-like bonds is facilitated when (1) the oxygen is bonded to a low amount of metal ions and (2) when those metal ions are not transition metals. Transition metals with partially filled $d$ shells create strong directional bonds38 that prevent rotation of the neighbouring oxygen bonds needed to form peroxo species. Lowering the metal coordination around oxygen, as occurs in Li-excess materials, and substituting some of the transition metals with non-transition metals, which provide weaker and less directional $\\bf{M}-\\boldsymbol{O}$ bonds owing to the completely filled (or no) $d$ shells, therefore facilitate peroxo-like $_{\\mathrm{O-O}}$ bond formation. \n\nFor example, the peroxo-like species in $\\mathrm{Li}_{0.5}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{3}$ arises from $\\sigma$ hybridization between two neighbouring Li–O–Li states that have $_{\\mathrm{Li-O-Sn}}$ configurations along the other axes (Fig. 3b and Supplementary Fig. 8). In highly Li-excess materials, such $_{\\mathrm{O-O}}$ bond formation is therefore sometimes possible because most O ions are coordinated with at most two metal ions (Fig. 4c), so their displacement to form an $_{\\mathrm{O-O}}$ bond incurs less penalty. Similar effects can be expected for oxygens coordinated with Li–O–Li and Sb atoms along the two other directions. Oxygens in these environments satisfy all conditions for peroxo formation: (1) they are more easily oxidized due to the Li–O–Li configuration and (2) their M–O bonds rotate more easily because along the other directions, the completely filled (or no) $d$ shells of the non-transition metals (for example, Sn and Sb) lead to a less directional $\\bf{M}\\mathrm{-}\\mathrm{O}$ bond. \n\n![](images/f2f0004439dd97089d4872e9072bc81a321463c0de77468e2c5edcfcea0100f2.jpg) \nFigure 3 | Illustrations of preferred oxygen oxidation along the Li–O–Li configuration in various Li-excess materials. a–d, Atomic configuration of fully lithiated and partially delithiated Li-excess materials and the isosurface of spin density (yellow) around oxygen (red spheres) in $\\mathsf{L i}_{1.17}\\mathsf{N i}_{0.25}\\mathsf{M n}_{0.58}\\mathsf{O}_{2}.$ , Li0.67Ni0.25Mn0.58O2 and Li0.33Ni0.25Mn0.58O2 (a), in $\\mathsf{L i}_{2}\\mathsf{R u}_{0.5}\\mathsf{S n}_{0.5}\\mathsf{O}_{3}$ , $\\mathsf{L i}_{1.5}\\mathsf{R u}_{0.5}\\mathsf{S n}_{0.5}\\mathsf{O}_{3}$ and $\\mathsf{L i}_{0.5}\\mathsf{R u}_{0.5}\\mathsf{S n}_{0.5}\\mathsf{O}_{3}$ (b), in Li1.17Ni0.33Ti0.42Mo0.08O2, $\\mathsf{L i}_{0.67}\\mathsf{N i}_{0.33}\\mathsf{T i}_{0.42}\\mathsf{M o}_{0.08}\\mathsf{O}_{2}$ and $\\mathsf{L i}_{0.33}\\mathsf{N i}_{0.33}\\mathsf{T i}_{0.42}\\mathsf{M o}_{0.08}\\mathsf{O}_{2}$ (c) and in $\\mathsf{L i}_{1.25}\\mathsf{M n}_{0.5}\\mathsf{N b}_{0.25}\\mathsf{O}_{2}$ , $\\mathsf{L i}_{0.5}\\mathsf{M n}_{0.5}\\mathsf{N b}_{0.25}\\mathsf{O}_{2}$ and $\\mathsf{L i}_{0.25}\\mathsf{M n}_{0.5}\\mathsf{N b}_{0.25}\\mathsf{O}_{2}$ (d). To simplify the presentation, the spin densities around metal ions are not drawn. Black dashed circles in the middle and the bottom panels indicate Li ions that have been extracted upon delithiation. In these materials, oxygen oxidation occurs preferably along the Li–O–Li configuration, which competes with transition metal oxidation. ${\\mathsf{R u}}^{4.x+}$ and $\\mathsf{R u}^{5.x+}$ in the Ru-Sn compound indicate partially oxidized ${\\mathsf{R}}{\\mathsf{u}}^{4+}$ and ${\\mathsf{R}}{\\mathsf{U}}^{5+},$ , respectively. Note that the peroxo-like species that can be observed in $\\mathsf{L i}_{0.5}\\mathsf{R u}_{0.5}\\mathsf{S n}_{0.5}\\mathsf{O}_{3}$ (blue dashed oval) arise from the $\\sigma$ hybridization between two neighbouring Li–O–Li states that have Li–O–Sn configurations along the other axes (Supplementary Fig. 8). \n\nTherefore, peroxo-like species can form more easily in Li-excess materials containing such non-transition metals, explaining the experimental observations of peroxo-like species in $\\mathrm{Li}_{2}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{3}$ or ${\\mathrm{Li}}_{4}{\\mathrm{FeSbO}}_{6}$ (refs 3,36). We show in Supplementary Section ‘Conditions for the O–O bond formation’ that such $_{\\mathrm{O-O}}$ bond formation depends not only on the nature of $_{\\mathrm{M-O}}$ hybridization, but also on the population and geometric arrangement of the oxidized Li–O–Li states (Supplementary Figs 8 and 9). \n\nCompetition between transition metal and oxygen redox. The labile electrons from the Li–O–Li states can further explain the competition between the TM redox and O redox in Li-excess materials. For example, oxidized O ions within the Li–O–Li configuration coexist with $\\mathrm{{Ru}}^{4.x+}$ (partially oxidized $\\mathrm{{Ru}^{4+}}$ ) in $\\mathrm{Li}_{1.5}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{3}$ (Fig. 3b), indicating an overlap between the $t_{2g}$ band (corresponding to the $\\mathrm{Ru}^{4+}/\\mathrm{Ru}^{6+}$ redox) and the Li–O–Li band (states)28. Such overlap between the TM band and the Li–O–Li band is also present in $\\mathrm{Li}_{1.17-x}\\mathrm{Ni}_{0.33}\\mathrm{Ti}_{0.42}\\mathrm{Mo}_{0.08}\\mathrm{O}_{2}$ (ref. 30). After extracting $0.5\\mathrm{Li},\\$ oxidized O ions within the Li–O–Li configuration coexist with $\\mathrm{Ni}^{3+}$ and ${\\mathrm{Ni}^{4+}}$ (Fig. 3c), indicating an overlap of the Li–O–Li band and the $e_{g}^{*}$ band $\\mathrm{(Ni^{2+}/N i^{4+})}$ . These results suggest that labile oxygen electrons in the Li–O–Li states are probably the reason why some of the Li-excess layered or cation-disordered materials, such as $\\mathrm{Li_{1.2}N i_{0.2}T i_{0.6}O_{2}}$ and $\\mathrm{Li_{1.2}F e_{0.4}T i_{0.4}O_{2}}$ , do not allow full TM oxidation19,39–41. However, overlap between the $e_{g}^{*}$ band and the Li–O–Li band is not observed in $\\mathrm{Li}_{1.25-x}\\mathrm{Mn}_{0.5}\\mathrm{Nb}_{0.25}\\mathrm{O}_{2}$ . As a result, oxygen oxidation only occurs after extracting more than $0.5~\\mathrm{Li}$ and after complete $\\mathrm{Mn}^{3+}$ oxidation to $\\mathrm{{Mn}^{4+}}$ (Fig. 3d)40. \n\nBecause the orphaned Li–O–Li state is essentially an unhybridized O $2p$ state, its energy level remains relatively invariant with respect to changes of the structure or metal species (Supplementary Fig. 10). Hence, whether oxygen oxidation occurs before, after or simultaneously with TM oxidation depends on the energy level of the $d$ states of different TM species. For example, both $\\mathrm{Li_{1.17}N i_{0.33}T i_{0.42}M o_{0.08}O_{2}}$ and $\\mathrm{Li}_{1.25}\\mathrm{Mn}_{0.5}\\mathrm{Nb}_{0.25}\\mathrm{O}_{2}$ use TM redox from, respectively, the Ni-dominated and Mn-dominated hybridized $e_{g}^{*}$ state. As the energy level of the $\\ensuremath{\\mathrm{Mn}}3d$ orbitals is higher than that of the $\\mathrm{Ni}3d$ orbitals, the corresponding $e_{g}^{*}$ state will also be higher in energy in $\\mathrm{Li}_{1.25}\\mathrm{Mn}_{0.5}\\mathrm{Nb}_{0.25}\\mathrm{O}_{2}$ than in $\\mathrm{Li}_{1.17}\\mathrm{Ni}_{0.33}\\mathrm{Ti}_{0.42}\\mathrm{Mo}_{0.08}\\mathrm{O}_{2}$ This reduces the overlap between the $e_{g}^{*}$ band and the Li–O–Li band, allowing for better use of TM redox in $\\mathrm{Li}_{1.25}\\mathrm{Mn}_{0.5}\\mathrm{Nb}_{0.25}\\mathrm{O}_{2}$ as seems to be supported by experiments18,29. \n\nBased on this understanding, it seems necessary to first find the right TM species to maximize either TM redox or O redox capacity in the Li-excess materials. For example, to maximize the TM redox capacity, V, Cr, Mo or Mn can be introduced as the TM redox species. The $d$ states of these TMs are high in energy, which raises the energy level of the $e_{g}^{*}$ and $t_{2g}$ bands42. This leads to less overlap between the TM band and the Li–O–Li band, thereby maximizing the TM redox capacity. Band overlap and thus the redox mechanism can also be modified by engineering the lattice parameters by cation-substitution preferably with a redox-inactive metal species or by external stress through microstructure control. Modifying the lattice parameters changes the TM–O distances, which in turn alters the overlap between TM $d$ orbitals and O $2p$ orbitals10,32. As the TM–O distance increases (decreases), the overlap between TM $d$ orbitals and O $2p$ orbitals decreases (increases), so the energy level of hybridized TM $d$ states with anti-bonding characteristic will decrease (increase) relative to the orphaned Li–O–Li states. Hence, increasing the lattice parameter should in general help to favour oxygen oxidation over TM oxidation. However, such structure manipulation needs further investigation as it might also affect other electrochemical properties or promote side reactions (for example, O loss at the surface, reactions with the electrolyte)17,30. \n\n![](images/dea7de0e5065e01784b3e3fee4f438f19950c260f3acb7ee46f0d9cb630b9e6a.jpg) \nFigure 4 | Structural and chemical origin of the preferred oxygen oxidation along the Li–O–Li configuration. a, Local atomic coordination around oxygen consisting of three Li–O–M configurations in stoichiometric layered Li metal oxides (Li–M oxides). b, Schematic of the band structure for stoichiometric layered Li–M oxides such as $\\mathsf{L i C o O}_{2}$ . c, Local atomic coordination around oxygen with one Li–O–Li and two Li–O–M configurations in Li-excess layered or cation-disordered Li–M oxides. d, Schematic of the band structure for Li-excess layered Li–M oxides such as $\\mathsf{L i}_{2}\\mathsf{M n O}_{3}$ . The Li–O–Li configurations lead to unhybridized $\\textnormal{O}2p$ states (Li–O–Li states) whose energies are higher than those of hybridized O $2p$ states $(t_{1u}^{\\mathrm{b}},a_{1g}^{\\mathrm{b}},e_{g}^{\\mathrm{b}})$ and as a result are more easily oxidized. \n\nIn summary, we have identified the chemical and structural features that lead to oxygen oxidation and therefore to extra capacity in lithium intercalation compounds. Oxygen redox activity in Li-excess layered and disordered materials originates from very specific Li–O–Li configurations that create orphaned oxygen states that are lifted out of the bonding oxygen manifold and become positioned in the TM-dominated complex of $e_{g}^{*}$ and $t_{2g}$ states, making oxygen oxidation and TM oxidation compete with each other. This effect is distinct from the prevailing argument that the holes are introduced in O $2p$ states that are hybridized with TM $d$ states, which occurs due to the covalent nature of the TM–O bonding10–16. In stark contrast with this current belief, we demonstrated that oxygen oxidation in Li-excess materials mainly occurs by extracting labile electrons from unhybridized O $2p$ states sitting in Li–O–Li configurations and is therefore unrelated to any hybridized TM–O states. This distinction is important, because the number of electrons, and thus the capacity, from the hybridized TM $d$ states (for example, the $e_{g}^{*}$ state) stays the same, regardless of the oxygen contribution to these states. Only the energy (voltage) of these TM states is modified by their hybridization22. Hence, unlike oxygen redox states created by Li–O–Li configurations, oxygen redox participation through (re)hybridization with TM states is not a useful mechanism to extend capacity beyond the conventional, TM-determined theoretical capacity limit. \n\n# Conclusion \n\nCreating unhybridized (orphaned) oxygen states in Li-intercalation cathodes is a promising mechanism to achieve higher-energydensity cathode materials as it lifts the fundamental restriction on transition metal content that has existed for decades in the Li-ion battery field. We have shown very specifically how Li-excess and cation disorder create oxygen states that compete with the transition metal states for oxidation. Although many challenges are likely to be found for such oxygen active intercalation compounds, this is an exciting new direction for the development of higher-energydensity cathode materials. \n\n# Methods \n\nAll ab initio calculations in this work are based on DFT (ref. 20) using the projectoraugmented wave method and the HSE06 hybrid functional21, as implemented in the Vienna $A b$ initio Simulation Package $(\\mathrm{VASP})^{43}$ . The hybrid mixing parameter for each system was adjusted to reproduce reference bandgaps to calibrate the TM and oxygen electronic states22. The method to prepare the structures of $\\mathrm{Li}_{1.17-x}\\mathrm{Ni}_{0.25}\\mathrm{Mn}_{0.58}\\mathrm{O}_{2}$ , $\\mathrm{Li}_{2-x}\\mathrm{Ru}_{0.5}\\mathrm{Sn}_{0.5}\\mathrm{O}_{3}$ , $\\mathrm{Li_{1.17-x}N i_{0.33}T i_{0.42}M o_{0.08}O_{2}}$ and $\\mathrm{Li}_{1.25-x}\\mathrm{Mn}_{0.5}\\mathrm{Nb}_{0.25}\\mathrm{O}_{2}$ and further computational details are provided in Supplementary pages 3–8. \n\n# Received 15 December 2015; accepted 31 March 2016; published online 30 May 2016 \n\n# References \n\n1. Goodenough, J. B. & Park, K.-S. The Li-ion rechargeable battery: a perspective. J. Am. Chem. Soc. 135, 1167–1176 (2013). \n2. Lee, J. et al. Unlocking the potential of cation-disordered oxides for rechargeable lithium batteries. Science 343, 519–522 (2014). \n3. Sathiya, M. et al. Reversible anionic redox chemistry in high-capacity layeredoxide electrodes. Nature Mater. 12, 827–835 (2013). \n4. Gallagher, K. G. et al. Quantifying the promise of lithium-air batteries for electric vehicles. Energy Environ. Sci. 7, 1555–1563 (2014). \n5. Kang, B. & Ceder, G. Battery materials for ultrafast charging and discharging. Nature 458, 190–193 (2009). \n6. Kang, K., Meng, Y. S., Breger, J., Grey, C. P. & Ceder, G. Electrodes with high power and high capacity for rechargeable lithium batteries. Science 311, 977–980 (2006). \n7. Mizushima, K., Jones, P. C., Wiseman, P. J. & Goodenough, J. B. ${\\mathrm{Li}}_{x}{\\mathrm{CoO}}_{2}$ $0\\leq x\\leq-1)$ : a new cathode material for batteries of high energy density. Mater. Res. Bull. 15, 783–789 (1980). \n8. Ohzuku, T., Ueda, A., Nagayama, M., Iwakoshi, Y. & Komori, H. Comparative study of $\\mathrm{LiCoO}_{2}$ , $\\mathrm{LiNi}_{1/2}\\mathrm{Co}_{1/2}\\mathrm{O}_{2}$ and $\\mathrm{LiNiO}_{2}$ for 4 volt secondary lithium cells. Electrochim. Acta 38, 1159–1167 (1993). \n9. Lu, Z., MacNeil, D. D. & Dahn, J. R. Layered L $\\mathrm{[Ni}_{x}\\mathrm{Co}_{1-2x}\\mathrm{Mn}_{x}]\\mathrm{O}_{2}$ cathode materials for lithium-ion batteries. Electrochem. Solid-State Lett. 4, A200–A203 (2001). \n10. Aydinol, M. K., Kohan, A. F., Ceder, G., Cho, K. & Joannopoulos, J. Ab initio study of lithium intercalation in metal oxides and metal dichalcogenides. Phys. Rev. B 56, 1354 (1997). \n11. Ceder, G. et al. Identification of cathode materials for lithium batteries guided by first-principles calculations. Nature 392, 694–696 (1998). \n12. Yoon, W.-S. et al. Oxygen contribution on Li-ion intercalation–deintercalation in $\\mathrm{LiCoO}_{2}$ investigated by O K-edge and Co L-edge X-ray absorption spectroscopy. J. Phys. Chem. B 106, 2526–2532 (2002). \n13. Yoon, W.-S. et al. Investigation of the charge compensation mechanism on the electrochemically Li-ion deintercalated $\\mathrm{Li}_{1-x}\\mathrm{Co}_{1/3}\\mathrm{Ni}_{1/3}\\mathrm{Mn}_{1/3}\\mathrm{O}_{2}$ electrode system by combination of soft and hard X-ray absorption spectroscopy. J. Am. Chem. Soc. 127, 17479–17487 (2005). \n14. Graetz, J. et al. Electronic structure of chemically-delithiated $\\mathrm{LiCoO}_{2}$ studied by electron energy-loss spectrometry. J. Phys. Chem. B 106, 1286–1289 (2002). \n15. Dahéron, L. et al. Electron transfer mechanisms upon lithium deintercalation from $\\mathrm{LiCoO}_{2}$ to $\\mathrm{CoO}_{2}$ investigated by XPS. Chem. Mater. 20, 583–590 (2008). \n16. Yoon, W.-S. et al. Combined NMR and XAS study on local environments and electronic structures of electrochemically Li-ion deintercalated $\\mathrm{Li}_{1-x}\\mathrm{Co}_{1/3}\\mathrm{Ni}_{1/3}$ $\\mathrm{Mn}_{1/3}\\mathrm{O}_{2}$ electrode system. Electrochem. Solid-State Lett. 7, A53–A55 (2004). \n17. Koga, H. et al. Reversible oxygen participation to the redox processes revealed for $\\mathrm{Li_{1.20}M n_{0.54}C o_{0.13}N i_{0.13}O_{2}}.$ J. Electrochem. Soc. 160, A786–A792 (2013). \n18. Yabuuchi, N. et al. High-capacity electrode materials for rechargeable lithium batteries: $\\mathrm{Li}_{3}\\mathrm{Nb}{\\mathrm{O}}_{4}.$ -based system with cation-disordered rocksalt structure. Proc. Natl Acad. Sci. USA 112, 7650–7655 (2015). \n19. Goodenough, J. B. & Kim, Y. Challenges for rechargeable Li batteries. Chem. Mater. 22, 587–603 (2010). \n20. Kohn, W. & Sham, L. J. Self-consistent equations including exchange and correlation effects. Phys. Rev. 140, A1133 (1965). \n21. Heyd, J., Scuseria, G. E. & Ernzerhof, M. Hybrid functionals based on a screened Coulomb potential. J. Chem. Phys. 118, 8207–8215 (2003). \n22. Seo, D.-H., Urban, A. & Ceder, G. Calibrating transition metal energy levels and oxygen bands in first principles calculations: accurate prediction of redox potentials and charge transfer in lithium transition metal oxides. Phys. Rev. B 92, 115118 (2015). \n23. Ohzuku, T. & Makimura, Y. Layered lithium insertion material of $\\mathrm{LiCo}_{1/3}\\mathrm{Ni}_{1/3}$ $\\mathrm{Mn}_{1/3}\\mathrm{O}_{2}$ for lithium-ion batteries. Chem. Lett. 30, 642–643 (2001). \n24. Cho, Y. & Cho, J. Significant improvement of $\\mathrm{LiNi_{0.8}C o_{0.15}A l_{0.05}O_{2}}$ cathodes at $60^{\\circ}\\mathrm{C}$ by $\\mathrm{SiO}_{2}$ dry coating for Li-ion batteries. J. Electrochem. Soc. 157, A625–A629 (2010). \n25. Lu, Z. H., MacNeil, D. D. & Dahn, J. R. Layered cathode materials Li $[\\mathrm{Ni}_{x}\\mathrm{Li}_{(1/3-2x/3)}$ $\\mathrm{Mn}_{(2/3-x/3)}]\\mathrm{O}_{2}$ for lithium-ion batteries. Electrochem. Solid-State Lett. 4, A191–A194 (2001). \n26. Xiao, R., Li, H. & Chen, L. Density functional investigation on $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ . Chem. Mater. 24, 4242–4251 (2012). \n27. Lee, E. & Persson, K. A. Structural and chemical evolution of the layered Liexcess $\\mathrm{Li}_{x}\\mathrm{MnO}_{3}$ as a function of Li content from first-principles calculations. Adv. Energy Mater. 4, 1400498 (2014). \n28. Sathiya, M. et al. High performance $\\mathrm{Li}_{2}\\mathrm{Ru}_{1-y}\\mathrm{Mn}_{y}\\mathrm{O}_{3}$ $0.2\\leq y\\leq0.8,$ ) cathode materials for rechargeable lithium-ion batteries: their understanding. Chem. Mater. 25, 1121–1131 (2013). \n29. Wang, R. et al. A new disordered rock-salt Li-excess material with high capacity: $\\mathrm{Li}_{1.25}\\mathrm{Nb}_{0.25}\\mathrm{Mn}_{0.5}\\mathrm{O}_{2}$ . Electrochem. Commun. 60, 70–73 (2015). \n30. Lee, J. et al. A new class of high capacity cation-disordered oxides for rechargeable lithium batteries: Li-Ni-Ti-Mo oxides. Energy Environ. Sci. 8, 3255–3265 (2015). \n31. Petersburg, C. F., Li, Z., Chernova, N. A., Whittingham, M. S. & Alamgir, F. M. Oxygen and transition metal involvement in the charge compensation mechanism of $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ cathodes. J. Mater. Chem. 22, 19993–20000 (2012). \n32. Ballhausen, C. J. Ligand Field Theory (McGraw Hill, 1962). \n33. Oishi, M. et al. Charge compensation mechanisms in $\\mathrm{Li_{1.16}N i_{0.15}C o_{0.19}M n_{0.50}O_{2}}$ positive electrode material for Li-ion batteries analyzed by a combination of hard and soft $\\mathrm{\\DeltaX}$ -ray absorption near edge structure. J. Power Sources 222, 45–51 (2013). \n34. Pauling, L. The Nature of the Chemical Bond Vol. 3 (Cornell Univ. Press, 1960). \n35. Ashcroft, N. W. & Mermin, N. D. Solid State Physics 490–495 (Holt, Rinehart and Winston, 1976). \n36. McCalla, E. et al. Understanding the roles of anionic redox and oxygen release during electrochemical cycling of lithium-rich layered $\\mathrm{Li_{4}F e S b O_{6}}$ . J. Am. Chem. Soc. 137, 4804–4814 (2015). \n37. Saubanere, M., McCalla, E., Tarascon, J. M. & Doublet, M. L. The intriguing question of anionic redox in high-energy density cathodes for Li-ion batteries. Energy Environ. Sci. 9, 984–991 (2016). \n38. Morrison, S. The Chemical Physics of Surfaces (Springer, 2012). \n39. Zhang, L. et al. Synthesis and electrochemistry of cubic rocksalt Li–Ni–Ti–O compounds in the phase diagram of $\\mathrm{LiNiO}_{2}.$ –LiTiO2–Li[Li $\\mathbf{\\Omega}_{1/3}\\mathrm{Ti}_{2/3}]\\mathrm{O}_{2}$ . J. Power Sources 185, 534–541 (2008). \n40. Shigemura, H., Tabuchi, M., Sakaebe, H., Kobayashi, H. & Kageyama, H. Lithium extraction and insertion behavior of nanocrystalline $\\mathrm{Li}_{2}\\mathrm{TiO}_{3}$ –LiFeO2 solid solution with cubic rock salt structure. J. Electrochem. Soc. 150, A638–A644 (2003). \n41. Glazier, S. L., Li, J., Zhou, J., Bond, T. & Dahn, J. R. Characterization of disordered $\\mathrm{Li}_{(1+x)}\\mathrm{Ti}_{2x}\\mathrm{Fe}_{(1-3x)}\\mathrm{O}_{2}$ as positive electrode materials in Li-ion batteries using percolation theory. Chem. Mater. 27, 7751–7756 (2015). \n42. Lias, S. Ionization energy search, NIST chemistry webbook, NIST standard reference database 69 (2005); http://webbook.nist.gov/chemistry/ie-ser.html \n43. Kresse, G. & Furthmuller, J. Efficiency of $a b$ -initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n\n# Acknowledgements \n\nThis work was supported by Robert Bosch Corporation and Umicore Specialty Oxides and Chemicals, and by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the US Department of Energy under contract no. DE-AC02–05CH11231, under the Batteries for Advanced Transportation Technologies (BATT) Program subcontract no. 7056411. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant no. ACI-1053575, and resources of the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the US Department of Energy under contract no. DE-C02- 05CH11231. D.-H.S. acknowledges support from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2014R1A6A3A03056034). J.L. acknowledges financial support from a Samsung Scholarship. \n\n# Author contributions \n\nG.C. planned the project, supervised all aspects of the research, contributed to the main theory and to writing the manuscript. D.-H.S. and J.L. conceived and designed project details. D.-H.S. performed DFT calculations. D.-H.S. and J.L. analysed the data. J.L. and D.-H.S. developed the main theory and authored the manuscript. D.-H.S and J.L. contributed equally to this work. A.U. and S.Y.K. performed preliminary DFT calculations. A.U. and R.M. assisted in data analysis and in writing the manuscript. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to G.C. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. " + }, + { + "id": "10.1038_npjcompumats.2016.28", + "DOI": "10.1038/npjcompumats.2016.28", + "DOI Link": "http://dx.doi.org/10.1038/npjcompumats.2016.28", + "Relative Dir Path": "mds/10.1038_npjcompumats.2016.28", + "Article Title": "A general-purpose machine learning framework for predicting properties of inorganic materials", + "Authors": "Ward, L; Agrawal, A; Choudhary, A; Wolverton, C", + "Source Title": "NPJ COMPUTATIONAL MATERIALS", + "Abstract": "A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method for partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability.", + "Times Cited, WoS Core": 1121, + "Times Cited, All Databases": 1266, + "Publication Year": 2016, + "Research Areas": "Chemistry; Materials Science", + "UT (Unique WOS ID)": "WOS:000426821500024", + "Markdown": "# ARTICLE OPEN A general-purpose machine learning framework for predicting properties of inorganic materials \n\nLogan Ward1, Ankit Agrawal2, Alok Choudhary2 and Christopher Wolverton1 \n\nA very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method for partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability. \n\nnpj Computational Materials (2016) 2, 16028; doi:10.1038/npjcompumats.2016.28; published online 26 August 2016 \n\n# INTRODUCTION \n\nRational design of materials is the ultimate goal of modern materials science and engineering. As part of achieving that goal, there has been a large effort in the materials science community to compile extensive data sets of materials properties to provide scientists and engineers with ready access to the properties of known materials. Today, there are databases of crystal structures, superconducting critical temperatures (http://supercon.nims.go. jp/), physical properties of crystalline compounds2–5 and many other repositories containing useful materials data. Recently, it has been shown that these databases can also serve as resources for creating predictive models and design rules—the key tools of rational materials design.6–12 These databases have grown large enough that the discovery of such design rules and models is impractical to accomplish by relying simply on human intuition and knowledge about material behaviour. Rather than relying directly on intuition, machine learning offers the promise of being able to create accurate models quickly and automatically. \n\nTo date, materials scientists have used machine learning to build predictive models for a handful of applications.13–27 For example, there are now models to predict the melting temperatures of binary inorganic compounds,21 the formation enthalpy crystalline compounds,14,15,28 which crystal structure is likely to form at a certain composition,5,16,29–31 band gap energies of certain classes of crystals32,33 and the mechanical properties of metal alloys.24,25 While these models demonstrate the promise of machine learning, they only cover a small fraction of the properties used in materials design and the data sets available for creating such models. For instance, no broadly-applicable, machine-learning-based models exist for band gap energy or glass-forming ability even though large-scale databases of these properties have existed for years.2,34 \n\nProvided the large differences between the approaches used in the literature, a systematic path forward to creating accurate machine learning models across a variety of new applications is not clear. While techniques in data analytics have advanced significantly, the development of routine methods for transforming raw materials data into the quantitative descriptions required for employing these algorithms is yet to emerge. In contrast, the chemoinformatics community benefits from a rich library of methods for describing molecular structures, which allow for standard approaches for deciding inputs into the models and, thereby, faster model development.35–37 What is missing are similar flexible frameworks for building predictive models of material properties. \n\nIn this work, we present a general-purpose machine-learningbased framework for predicting the properties of materials based on their composition. In particular, we focus on the development of a set of attributes—which serve as an input to the machine learning model—that could be reused for a broad variety of materials problems. Provided a flexible set of inputs, creating a new material property model can be reduced to finding a machine learning algorithm that achieves optimal performance—a wellstudied problem in data science. In addition, we employ a novel partitioning scheme to enhance the accuracy of our predictions by first partitioning data into similar groups of materials and training separate models for each group. We show that this method can be used regardless of whether the materials are amorphous or crystalline, the data are from computational or experimental studies, or the property takes continuous or discrete values. In particular, we demonstrate the versatility of our technique by using it for two distinct applications: predicting novel solar cell materials using a database of density functional theory (DFT)- predicted properties of crystalline compounds and using experimental measurements of glass-forming ability to suggest new metallic glass alloys. Our vision is that this framework could be used as a basis for quickly creating models based on the data available in the materials databases and, thereby, initiate a major step forward in rational materials design. \n\n# RESULTS AND DISCUSSION \n\nThe results of this study are described in two major subsections. First, we will discuss the development of our method and the characterisation of the attribute set using data from the Open Quantum Materials Database (OQMD). Next, we will demonstrate the application of this method to two distinct material problems. \n\nGeneral-purpose method to create materials property models Machine learning (ML) models for materials properties are constructed from three parts: training data, a set of attributes that describe each material, and a machine learning algorithm to map attributes to properties. For the purposes of creating a general-purpose method, we focused entirely on the attributes set because the method needs to be agnostic to the type of training data and because it is possible to utilise already-developed machine learning algorithms. Specifically, our objective is to develop a general set of attributes based on the composition that can be reused for a broad variety of problems. \n\nThe goal in designing a set of attributes is to create a quantitative representation that both uniquely defines each material in a data set and relates to the essential physics and chemistry that influence the property of interest.14,17 As an example, the volume of a crystalline compound is expected to relate to the volume of the constituent elements. By including the mean volume of the constituent elements as an attribute, a machine learning algorithm could recognise the correlation between this value and the compound volume, and use it to create a predictive model. However, the mean volume of the constituent elements neither uniquely defines a composition nor perfectly describes the volumes of crystalline materials.38 Consequently, one must include additional attributes to create a suitable set for this problem. Potentially, one could include factors derived from the electronegativity of the compound to reflect the idea that bond distances are shorter in ionic compounds, or the variance in atomic radius to capture the effects of polydisperse packing. The power of machine learning is that it is not necessary to know which factors actually relate to the property and how before creating a model—those relationships are discovered automatically. \n\nThe materials informatics literature is full of successful examples of attribute sets for a variety of properties.13–16,21,32,39 We observed that the majority of attribute sets were primarily based on statistics of the properties of constituent elements. As an example, Meredig et al.15 described a material based on the fraction of each element present and various intuitive factors, such as the maximum difference in electronegativity, when building models for the formation energy of ternary compounds. Ghiringhelli et al.14 used combinations of elemental properties such as atomic number and ionisation potential to study the differences in energy between zinc-blende and rocksalt phases. We also noticed that the important attributes varied significantly depending on material property. The best attribute for describing the difference in energy between zinc-blende and rocksalt phases was found to be related to the pseudopotential radii, ionisation potential and electron affinity of the constituent elements.14 In contrast, melting temperature was found to be related to atomic number, atomic mass and differences between atomic radii.21 From this, we conclude that a general-purpose attribute set should contain the statistics of a wide variety of elemental properties to be adaptable. \n\nBuilding on existing strategies, we created an expansive set of attributes that can be used for materials with any number of constituent elements. As we will demonstrate, this set is broad enough to capture a sufficiently-diverse range of physical/ chemical properties to be used to create accurate models for many materials problems. In total, we use a set of 145 attributes, which are described in detail and compared against other attribute sets in the Supplementary Information, that fall into four distinct categories: \n\n1. Stoichiometric attributes that depend only on the fractions of elements present and not what those elements actually are. These include the number of elements present in the compound and several $L^{p}$ norms of the fractions. \n2. Elemental property statistics, which are defined as the mean, mean absolute deviation, range, minimum, maximum and mode of 22 different elemental properties. This category includes attributes such as the maximum row on periodic table, average atomic number and the range of atomic radii between all elements present in the material. \n3. Electronic structure attributes, which are the average fraction of electrons from the $s,p,d$ and $f$ valence shells between all present elements. These are identical to the attributes used by Meredig et $a I$ .15 \n4. Ionic compound attributes that include whether it is possible to form an ionic compound assuming all elements are present in a single oxidation state, and two adaptations of the fractional ‘ionic character’ of a compound based on an electronegativitybased measure.40 \n\nFor the third ingredient, the machine learning algorithm, we evaluate many possible methods for each individual problem. Previous studies have used machine learning algorithms including partial least-squares regression,13,29 Least Absolute Shrinkage and Selection Operator (LASSO),14,33,41 decision trees,15,16 kernel ridge regression,17–19,42 Gaussian process regression19–21,43 and neural networks.22–24 Each method offers different advantages, such as speed or interpretability, which must be weighed carefully for a new application. We generally approach this problem by evaluating the performance of several algorithms to find one that has both reasonable computational requirements (i.e., can be run on available hardware in a few hours) and has low error rates in cross-validation—a process that is simplified by the availability of well-documented libraries of machine learning algorithms.44,45 We often find that ensembles of decision trees (e.g., rotation forests46) perform best with our attribute set. These algorithms also have the advantage of being quick to train, but are not easily interpretable by humans. Consequently, they are less suited for understanding the underlying mechanism behind a material property but, owing to their high predictive accuracy, excellent choices for the design of new materials. \n\nWe also utilise a partitioning strategy that enables a significant increase in predictive accuracy for our ML models. By grouping the data set into chemically-similar segments and training a separate model on each subset, we boost the accuracy of our predictions by reducing the breadth of physical effects that each machine learning algorithm needs to capture. For example, the physical effects underlying the stability intermetallic compounds are likely to be different than those for ceramics. In this case, one could partition the data into compounds that contain only metallic elements and another including those that do not. As we demonstrate in the examples below, partitioning the data set can significantly increase the accuracy of predicted properties. Beyond using our knowledge about the physics behind a certain problem to select a partitioning strategy, we have also explored using an automated, unsupervised-learning-based strategy for determining distinct clusters of materials.47 Currently, we simply determine the partitioning strategy for each property model by searching through a large number of possible strategies and selecting the one that minimises the error rate in crossvalidation tests. \n\n# Justification for large attribute set \n\nThe main goal of our technique is to accelerate the creation of machine learning models by reducing or eliminating the need to develop a set of attributes for a particular problem. Our approach was to create a large attribute set, with the idea that it would contain a diverse enough library of descriptive factors such that it is likely to contain several that are well-suited for a new problem. To justify this approach, we evaluated changes in the performance of attributes for different properties and types of materials using data from the OQMD. As described in greater detail in the next section, the OQMD contains the DFT-predicted formation energy, band gap energy and volume of hundreds of thousands of crystalline compounds. The diversity and scale of the data in the OQMD make it ideal for studying changes in attribute performance using a single, uniform data set. \n\nWe found that the attributes which model a material property best can vary significantly depending on the property and type of materials in the data set. To quantify the predictive ability of each attribute, we fit a quadratic polynomial using the attribute and measured the root mean squared error of the model. We found the attributes that best describe the formation energy of crystalline compounds are based on the electronegativity of the constituent elements (e.g., maximum and mode electronegativity). In contrast, the best-performing attributes for band gap energy are the fraction of electrons in the $p$ shell and the mean row in the periodic table of the constituent elements. In addition, the attributes that best describe the formation energy vary depending on the type of compounds. The formation energy of intermetallic compounds is best described by the variances in the melting temperature and number of $d$ electrons between constituent elements, whereas compounds that contain at least one nonmetal are best modelled by the mean ionic character (a quantity based on electronegativity difference between constituent elements). Taken together, the changes in which attributes are the most important between these examples further support the necessity of having a large variety of attributes available in a generalpurpose attribute set. \n\nIt is worth noting that the 145 attributes described in this paper should not be considered the complete set for inorganic materials. The chemical informatics community has developed thousands of attributes for predicting the properties of molecules.35 What we present here is a step towards creating such a rich library of attributes for inorganic materials. While we do show in the examples considered in this work that this set of attributes is sufficient to create accurate models for two distinct properties, we expect that further research in materials informatics will add to the set presented here and be used to create models with even greater accuracy. Furthermore, many materials cannot be described simply by average composition. In these cases, we propose that the attribute set presented here can be extended with representations designed to capture additional features such as structure (e.g., Coulomb Matrix17 for atomic-scale structure) or processing history. We envision that it will be possible to construct a library of general-purpose representations designed to capture structure and other characteristics of a material, which would drastically simplify the development of new machine learning models. \n\n# Example applications \n\nIn the following sections, we detail two distinct applications for our novel material property prediction technique to demonstrate its versatility: predicting three physically distinct properties of crystalline compounds and identifying potential metallic glass alloys. In both cases, we use the same general framework, i.e., the same attributes and partitioning-based approach. In each case, we only needed to identify the most accurate machine learning algorithm and find an appropriate partitioning strategy. Through these examples, we discuss all aspects of creating machinelearning-based models to design a new material: assembling a training set to train the models, selecting a suitable algorithm, evaluating model accuracy and employing the model to predict new materials. \n\nAccurate models for properties of crystalline compounds DFT is a ubiquitous tool for predicting the properties of crystalline compounds, but is fundamentally limited by the amount of computational time that DFT calculations require. In the past decade, DFT has been used to generate several databases containing the ${\\cal T}=0\\mathsf{K}$ energies and electronic properties of $\\sim10^{5}$ crystalline compounds, $\\lambda^{2-5,4\\bar{8}}$ which each required millions of hours of CPU time to construct. While these databases are indisputablyuseful tools, as evidenced by the many materials they have been used to design,3,49–54 machine-learning-based methods offer the promise of predictions at several orders of magnitude faster rates. In this example, we explore the use of data from the DFT calculation databases as training data for machine learning models that can be used rapidly to assess many more materials than what would be feasible to evaluate using DFT. \n\nTraining data. We used data from the OQMD, which contains the properties of \\~ 300,000 crystalline compounds as calculated using DFT.2,3 We selected a subset of 228,676 compounds from OQMD that represents the lowest-energy compound at each unique composition to use as a training set. As a demonstration of the utility of our method, we developed models to predict the three physically distinct properties currently available through the OQMD: band gap energy, specific volume and formation energy. \n\nMethod. To select an appropriate machine learning algorithm for this example, we evaluated the predictive ability of several algorithms using 10-fold cross-validation. This technique randomly splits the data set into 10 parts, and then trains a model on 9 partitions and attempts to predict the properties of the remaining set. This process is repeated using each of the 10 partitions as the test set, and the predictive ability of the model is assessed as the average performance of the model across all repetitions. As shown in Table 1, we found that creating an ensemble of reduced-error pruning decision trees using the random subspace technique had the lowest mean absolute error in cross-validation for these properties among the 10 ML algorithms we tested (of which, only 4 are listed for clarity).55 Models produced using this machine learning algorithm had the lowest mean absolute error in crossvalidation, and had excellent correlation coefficients of above 0.91 between the measured and predicted values for all three properties. \n\nAs a simple test for how well our band gap model can be used for discovering new materials, we simulated a search for compounds with a band gap within a desired range. To evaluate the ability of our method to locate compounds that have band gap energies within the target range, we devised a test where a model was trained on $90\\%$ of the data set and then was tasked with selecting which 30 compounds in the remaining $10\\%$ were most likely to have a band gap energy in the desired range for solar cells: $0.9\\mathrm{-}1.7\\mathrm{eV.}^{56}$ For this test, we selected a subset of the OQMD that only includes compounds that were reported to be possible to be made experimentally in the ICSD (a total of 25,085 entries) so that only band gap energy, and not stability, needed to be considered. \n\nFor this test, we compared three selection strategies for finding compounds with desirable band gap energies: randomly selecting nonmetal-containing compounds (i.e., without machine learning), using a single model trained on the entire training set to guide selection, and a model created using the partitioning approach introduced in this manuscript. As shown in Figure 1, randomly selecting a nonmetal-containing compound would result in just over $12\\%$ of the 30 selected compounds to be within the desired range of band gap energies. Using a single model trained on the entire data set, this figure dramatically improves to $\\sim46\\%$ of selected compounds having the desired property. We found the predictive ability of our model can be increased to $\\sim67\\%$ of predictions actually having the desired band gap energy by partitioning the data set into groups of similar compounds before training. Out of the 20 partitioning strategies we tested, we found the best composite model works by first partitioning the data set using a separate model trained to predict the expected range, but not the actual value, of the band gap energy (e.g., compounds predicted to have a band gap between 0 and $1.5\\mathsf{e V}$ are grouped together), and then on whether a compound contains a halogen, chalcogen or pnictogen. Complete details of the hierarchical model are available in the Supplementary Information. By partitioning the data into smaller subsets, each of the individual machine learning models only evaluates compounds with similar chemistries (e.g., halogen-containing compounds with a band gap expected to be between 0 and $1.5\\mathsf{e V}$ ), which we found enhances the overall accuracy of our model. \n\n
Table 1.Comparison of the ability ofseveral machine learning algorithms to predict propertiesof materials from the OQMD
Machine learning algorithm
Linear regresson Reduced-error pruning tree (REPTree) Rotation forest46+REPTreeRandom subspace5+REPTree
Property Volume (A² per atom) 1.220.8160.563
0.126
Formation energy (eV per atom)0.0701
Band gap energy (eV)
Abbreviations: DFT, density functional theory; OQMD, Open Quantum Materials Database.
compounds.Datafffl
\n\n![](images/97d7c832015eaeeff476becfb9882bf7196d5e2d62f9036622bf747f0a0e3467.jpg) \nFigure 1. Performance of three different strategies to locate compounds with a band gap energy within a desired range: randomly selecting nonmetal-containing compounds, and two strategies using the machine-learning-based method presented in this work. The first machine learning strategy used a single model trained on the computed band gap energies of 22,667 compounds from the ICSD. The second method a model created by first partitioning the data into groups of similar materials, and training a separate model on each subset. The number of materials that were actually found to have a band gap within the desired range after 30 guesses was over 5 times larger when using our machine learning approach than when randomly selecting compounds. Error bars represent the $95\\%$ confidence interval. \n\n
Table 2. Compositions and predicted band gap energies of materials predicted using machine learning to be candidates for solar cell applications
Composition Eg (eV)
ScHg4Cl7 1.26 VHgCl7 1.16 Mn6CCl8 1.28 Hf4S11Cl 1.11 VCu5Clg 1.19
Abbreviations: DFT, density functional theory; OQMD, open quantum materialsdatabase. Compositions represent the nominal compositions of novel ternary compounds predicted by using methods developed in ref. 15. Band gap energies were predicted using a machine learning model trained on DFT band gap energies from the OQMD² using methods described in this work.
\n\nOnce we established the reliability of our model, we used it to search for new compounds (i.e., those not yet in the OQMD) with a band gap energy within the desired range for solar cells: 0.9–1.7 eV. To gain the greatest predictive accuracy, we trained our band gap model on the entire OQMD data set. Then, we used this model to predict the band gap energy of compositions that were predicted by Meredig et $\\mathsf{\\bar{\\Pi}}_{a l.}\\mathsf{\\Pi}^{15}$ to be as-yet-undiscovered ternary compounds. Out of this list of 4,500 predicted compounds, we found that 223 are likely to have favourable band gap energies. A subset with the best stability criterion (as reported in ref. 15) and band gap energy closest to $1.3\\mathsf{e V}$ are shown in Table 2. As demonstrated in this example and a recent work by Sparks et al.,57 having access to several machine learning models for different properties can make it possible to rapidly screen materials based on many design criteria. Provided the wide range of applicability of the machine learning technique demonstrated in this work and the growing availability of material property data, it may soon be possible to screen for materials based on even more properties than those considered here using models constructed based on several different data sets. \n\n# Locating novel metallic glass alloys \n\nMetallic glasses possess a wide range of unique properties, such as high-wear resistance and soft magnetic behaviour, but are only possible to create at special compositions that are difficult to determine a priori.58 The metallic glass community commonly relies on empirical rules (e.g., systems that contain many elements of different sizes are more likely to form glasses59) and extensive experimentation to locate these special compositions.55 While searches based on empirical rules have certainly been successful (as evidenced by the large variety of known alloys,60) this conventional method is known to be slow and resourceintensive.61 Here, we show how machine learning could be used to accelerate the discovery of new alloys by using known experimental data sets to construct predictive models of glassforming ability. \n\n![](images/f67bd6b0deb81b5074ebb44ec7c2568baf39fb4f0d3e11ef15f63890ca2bd8a8.jpg) \nFigure 2. (a) Experimental measurements of metallic glass-forming ability in the Al–Ni–Zr ternary, as reported in ref. 34. Green circles (AM) mark compositions at which it is possible to create a fully-amorphous ribbon via melt spinning, blue squares (AC) mark compositions at which only a partially-amorphous ribbon can be formed, and red crosses (CR) mark compositions where it is not possible to form any appreciable amount of amorphous phase. (b) Predicted glass-forming ability from our machine learning model. Points are coloured based on relative likelihood of glass formation, where 1 is the mostly likely and 0 is the least. The model used to make these predictions was developed using the methods outlined in this work, and was not trained on any measurements from the Al–Ni–Zr ternary or any of its constituent binaries. \n\nData. We used experimental measurements taken from ‘Nonequilibrium Phase Diagrams of Ternary Amorphous Alloys,’ a volume of the Landolt–Börnstein collection.32 This data set contains measurements of whether it is possible to form a glass using a variety of experimental techniques at thousands of compositions from hundreds of ternary phase diagrams. For our purposes, we selected 5,369 unique compositions where the ability to form an amorphous ribbon was assessed using melt spinning. In the event that multiple measurements for glassforming ability were taken at a single composition, we assume that it is possible to form a metallic glass if at least one measurement found it was possible to form a completely amorphous sample. After the described screening steps, $70.8\\%$ of the entries in the training data set correspond to metallic glasses. \n\nMethod. We used the same set of 145 attributes as in the band gap example and ensembles of Random Forest classifiers62 created using the random subspace technique as the machine learning algorithm, which we found to be the most accurate algorithm for this problem. This model classifies the data into two categories (i.e., can and cannot form a metallic glass) and computes the relative likelihood that a new entry would be part of each category. For the purposes of validating the model, we assume any composition predicted to have a $>50\\%$ probability of glass formation to be a positive prediction of glass-forming ability. Using a single model trained on the entire data set, we were able to create a model with $90\\%$ accuracy in 10-fold cross-validation. \n\nAs a test of the ability of our method to predict new alloys, we removed all entries that contained exclusively Al, Ni and Zr (i.e., all Al–Ni–Zr ternary compounds, and any binary formed by any two of those elements) from our training data set and then predicted the probability of an alloy being able to be formed into the amorphous state for the Al–Ni–Zr ternary system. As shown in Figure 2a, it is possible to form amorphous ribbons with melt spinning in one region along the Ni–Zr binary and in a second, Al-rich ternary region. Our model is able to accurately predict both the existence of these regions and their relative locations (see Figure 2b), which shows that models created using our method could serve to accurately locate favourable compositions in yet-unassessed alloy systems. \n\nWe further validated the ability of our models to extrapolate to alloy systems not included in the training set by iteratively using each binary system as a test set. This procedure works by excluding all alloys that contain both of the elements in the binary, training a model on the remaining entries and then predicting the glass-forming ability of the alloys that were removed. For example, if the Al–Ni binary were being used as a test set, then $\\mathsf{A l}_{50}\\mathsf{N i}_{50}$ and $\\mathsf{A l}_{50}\\mathsf{N i}_{25}\\mathsf{F e}_{25}$ would be removed but $\\mathsf{A l}_{50}\\mathsf{F e}_{50}$ and $\\mathsf{A l}_{50}\\mathsf{F e}_{25}\\mathsf{Z r}_{25}$ would not. This process is then repeated for all 380 unique binaries in the data set. We measured that our model has an $80.2\\%$ classification accuracy over 15,318 test entries where $71\\%$ of entries were measured to be glasses—in contrast to the $90.1\\%$ measured in 10-fold cross-validation with a similar fraction of glasses in the test set. We also found that by training separate models for alloys that contain only metallic elements and those that contain a nonmetal/metalloid it is possible to slightly increase the prediction accuracy to $80.7\\%$ —a much smaller gain than that observed in the band gap example $(23\\%)$ . Overall, this exclusion test strongly establishes that our model is able to predict the glass-forming ability in alloy systems that are completely unassessed. \n\nTo search for new candidate metallic glasses, we used our model to predict the probability of glass formation for all possible ternary alloys created at $2\\ \\mathsf{a t}\\%$ spacing by any combination of elements found in the training set. Considering that the data set included 51 elements, this space includes $\\sim24$ million candidate alloys, which required $\\sim6\\mathsf{h}$ to evaluate on eight $2.2G H z$ processors. To remove known alloys from our prediction results, we first removed all entries where the $L_{1}$ distance between the composition vector (i.e., $\\langle x_{\\mathsf{H}},x_{\\mathsf{H e}},x_{\\mathsf{L i}},\\hdots\\rangle)$ of the alloy and any amorphous alloy in the training set was $<30\\mathsf{a t\\%}$ . We then found the alloys with the highest predicted probability of glass formation in each binary and ternary. Eight alloys with the highest probability of glass formation are shown in Table 3. One top candidate, $Z\\mathrm{r}_{0.38}\\mathsf{C o}_{0.24}\\mathsf{C u}_{0.38},$ is particularly promising considering the existence of Zr-lean Zr–Co and $Z r-C u$ binary alloys and $Z r{-}A l{-}$ ${\\mathsf{C o}}{\\mathsf{-C u}}$ bulk metallic glasses.63 To make the ability to find new metallic glasses openly available to the materials science community, we have included all of the software and data necessary to use this model in the Supplementary Information and created an interactive, web-based tool(http://oqmd.org/static/ analytics/glass_search.html). \n\n
Table 3. Compositions of candidate metallic glass alloys predicted using a machine learning model trained on experimental measurements of glass-forming ability
Alloycomposition Zr0.38CO0.24CU0.38 Hfo.7Sio.16Nio.14 V0.16Nio.64B0.2 Hfo.48Zr0.16Nio.36 Zr0.46Cr0.36Nio.18 Zro.48Fe0.46Nio.06 Zro.5Fe0.38W0.12 Smo.22Fe0.54Bo.24
These alloys were predicted to have the highest probability being able to be formed into an amorphous ribbon via melting spinning out of 24 million candidates.
\n\n# CONCLUSIONS \n\nIn this work, we introduced a general-purpose machine learning framework for predicting the properties of a wide variety of materials and demonstrated its broad applicability via illustration of two distinct materials problems: discovering new potential crystalline compounds for photovoltaic applications and identifying candidate metallic glass alloys. Our method works by using machine learning to generate models that predict the properties of a material as a function of a wide variety of attributes designed to approximate chemical effects. The accuracy of our models is further enhanced by partitioning the data set into groups of similar materials. In this manuscript, we show that this technique is capable of creating accurate models for properties as different as the electronic properties of crystalline compounds and glass formability of metallic alloys. Creating new models with our strategy requires only finding which machine learning algorithm maximises accuracy and testing different partitioning strategies, which are processes that could be eventually automated.64 We envision that the versatility of this method will make it useful for a large range of problems, and help enable the quicker deployment and wider-scale use machine learning in the design of new materials. \n\n# MATERIALS AND METHODS \n\nAll machine learning models were created using the Weka machine learning library.44 The Materials Agnostic Platform for Informatics and Exploration (Magpie) was used to compute attributes, perform the validation experiments and run searches for new materials. Both Weka and Magpie are available under open-source licenses. The software, training data sets and input files used in this work are provided in the Supplementary Information associated with this manuscript. \n\n# ACKNOWLEDGEMENTS \n\nThis work was performed under the following financial assistance award 70NANB14H012 from U.S. Department of Commerce, National Institute of Standards and Technology as part of the Center for Hierarchical Materials Design (CHiMaD). In addition, AA and AC were supported in part by the following grants: DARPA SIMPLEX award N66001-15-C-4036; NSF awards IIS-1343639 and CCF-1409601; DOE award DESC0007456; and AFOSR award FA9550-12-1-0458. LW was partially supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. \n\n# CONTRIBUTIONS \n\nCW conceived the project, and jointly developed the method with LW, AA and AC. LW wrote all software and performed the necessary calculations with help and guidance from AA and AC. LW led the manuscript writing, with contributions from all other authors. \n\n# COMPETING INTERESTS \n\nThe authors declare no conflict of interest. \n\n# REFERENCES \n\n1. Belsky, A., Hellenbrandt, M., Karen, V. L. & Luksch, P. New developments in the Inorganic Crystal Structure Database (ICSD): accessibility in support of materials research and design. Acta Crystallogr. Sect. B Struct. Sci. 58, 364–369 (2002). \n2. Kirklin, S. et al. The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies. NPJ Comput. Mater. 1, 15010 (2015). \n3. Saal, J. E., Kirklin, S., Aykol, M., Meredig, B. & Wolverton, C. Materials design and discovery with high-throughput density functional theory: the open quantum materials database (OQMD). JOM 65, 1501–1509 (2013). \n4. Jain, A. et al. Commentary: the materials project: a materials genome approach to accelerating materials innovation. APL Mater. 1, 011002 (2013). \n5. Curtarolo, S. et al. AFLOWLIB.ORG: a distributed materials properties repository from high-throughput ab initio calculations. Comput. Mater. Sci. 58, \n227–235 (2012). \n6. Kalidindi, S. R. & De Graef, M. Materials data science: current status and future outlook. Annu. Rev. Mater. Res. 45, 171–193 (2015). \n7. Kalinin, S. V., Sumpter, B. G. & Archibald, R. K. Big-deep-smart data in imaging for guiding materials design. Nat. Mater. 14, 973–980 (2015). \n8. Rajan, K. Materials informatics: the materials ‘gene’ and big data. Annu. Rev. Mater. Res. 45, 153–169 (2015). \n9. Rajan, K. Materials informatics. Mater. Today 8, 38–45 (2005). \n10. Lookman, T., Alexander, F. J. & Bishop, A. R. Perspective: codesign for materials science: an optimal learning approach. APL Mater. 4, 053501 (2016). \n11. Mulholland, G. J. & Paradiso, S. P. Perspective: Materials informatics across the product lifecycle: Selection, manufacturing, and certification. APL Mater. 4, \n053207 (2016). \n12. Agrawal, A. & Choudhary, A. Perspective: Materials informatics and big data: Realization of the ‘fourth paradigm’ of science in materials science. APL Mater. 4, \n053208 (2016). \n13. Srinivasan, S. & Rajan, K. ‘Property phase diagrams’ for compound semiconductors through data mining. Materials (Basel) 6, 279–290 (2013). \n14. Ghiringhelli, L. M., Vybiral, J., Levchenko, S. V., Draxl, C. & Scheffler, M. Big data of materials science: critical role of the descriptor. Phys. Rev. Lett. 114, \n105503 (2015). \n15. Meredig, B. et al. Combinatorial screening for new materials in unconstrained composition space with machine learning. Phys. Rev. B 89, 094104 (2014). \n16. Kong, C. S. et al. Information-theoretic approach for the discovery of design rules for crystal chemistry. J. Chem. Inf. Model. 52, 1812–1820 (2012). \n17. Faber, F., Lindmaa, A., von Lilienfeld, O. A. & Armiento, R. Crystal structure representations for machine learning models of formation energies. Int. J. Quantum Chem. 115, 1094–1101 (2015). \n18. Schütt, K. T. et al. How to represent crystal structures for machine learning: towards fast prediction of electronic properties. Phys. Rev. B 89, 205118 (2014). \n19. Pilania, G., Wang, C., Jiang, X., Rajasekaran, S. & Ramprasad, R. Accelerating materials property predictions using machine learning. Sci. Rep. 3, 2810 (2013). \n20. Bartók, A. P., Payne, M. C., Kondor, R. & Csányi, G. Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons. Phys. Rev. Lett. 104, 136403 (2010). \n21. Seko, A., Maekawa, T., Tsuda, K. & Tanaka, I. Machine learning with systematic density-functional theory calculations: application to melting temperatures of single- and binary-component solids. Phys. Rev. B 89, 054303 (2014). \n22. Hou, Z.-Y., Dai, $\\mathsf{Q}_{\\cdot},$ Wu, X.-Q. & Chen, G.-T. Artificial neural network aided design of catalyst for propane ammoxidation. Appl. Catal. A Gen. 161, 183–190 (1997). \n23. Sumpter, B. & Noid, D. On the design, analysis, and characterisation of materials using computational neural networks. Annu. Rev. Mater. Sci. 26, 223–277 (1996). \n24. Bhadeshia, H. K. D. H., Dimitriu, R. C., Forsik, S., Pak, J. H. & Ryu, J. H. Performance of neural networks in materials science. Mater. Sci. Technol. 25, 504–510 (2009). \n25. Chatterjee, S., Murugananth, M. & Bhadeshia, H. K. D. H. δ TRIP steel. Mater. Sci. Technol. 23, 819–827 (2007). \n26. Hautier, G. in Prediction and Calculation of Crystal Structures. (eds Atahan-Evrenk, S. & Aspuru-Guzik, A.) 139-179 (Springer International Publishing, 2014). \n27. Yang, L. & Ceder, G. Data-mined similarity function between material compositions. Phys. Rev. B 88, 224107 (2013). \n28. Deml, A. M., Hayre, R. O., Wolverton, C. & Stevanovic, V. Predicting density functional theory total energies and enthalpies of formation of metal-nonmetal compounds by linear regression. Phys. Rev. B 93, 085142 (2016). \n29. Curtarolo, S., Morgan, D., Persson, K., Rodgers, J. & Ceder, G. Predicting crystal structures with data mining of quantum calculations. Phys. Rev. Lett. 91, \n135503 (2003). \n30. Fischer, C. C., Tibbetts, K. J., Morgan, D. & Ceder, G. Predicting crystal structure by merging data mining with quantum mechanics. Nat. Mater. 5, 641–646 (2006). \n31. Hautier, G., Fischer, C., Ehrlacher, V., Jain, A. & Ceder, G. Data mined ionic substitutions for the discovery of new compounds. Inorg. Chem. 50, 656–663 (2011). \n32. Dey, P. et al. Informatics-aided bandgap engineering for solar materials. Comput. Mater. Sci. 83, 185–195 (2014). \n33. Pilania, G. et al. Machine learning bandgaps of double perovskites. Sci. Rep. 6, 19375 (2016). \n34. Kawazoe, Y., Yu, J. Z., Tsai, A. P. & Masumoto T (eds). Nonequilibrium Phase Diagrams of Ternary Amorphous Alloys. (Springer-Verlag, Berlin, Germany, 1997). \n35. Todeschini, R. & Consonni, V. Handbook of Molecular Descriptors (Wiley-VCH Verlag GmbH, 2000). \n36. Ruiz-Blanco, Y. B., Paz, W., Green, J. & Marrero-Ponce, Y. ProtDCal: a program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins. BMC Bioinformatics 16, 162 (2015). \n37. Mauri, A., Consonni, V., Pavan, M. & Todeschini, R. Dragon software: an easy approach to molecular descriptor calculations. Match Commun. Math. Comput. Chem. 56, 237–248 (2006). \n38. Denton, A. R. & Ashcroft, N. W. Vegards law. Phys. Rev. A 43, 3161–3164 (1991). \n39. Villars, P., Cenzual, K., Daams, J., Chen, Y. & Iwata, S. Data-driven atomic environment prediction for binaries using the Mendeleev number. J. Alloys Compd. 367, 167–175 (2004). \n40. Callister, W. D. Materials Science and Engineering: An Introduction (Wiley, 2007). \n41. Seko, A., Takahashi, A. & Tanaka, I. Sparse representation for a potential energy surface. Phys. Rev. B 90, 024101 (2014). \n42. Rupp, M., Tkatchenko, A., Müller, K.-R., Lilienfeld, V. & Anatole, O. Fast and accurate modeling of molecular atomization energies with machine learning. Phys. Rev. Lett. 108, 58301 (2012). \n43. Pyzer-Knapp, E. O., Simm, G. N. & Aspuru-Guzik, A. A Bayesian approach to calibrating high-throughput virtual screening results and application to organic photovoltaic materials. J. Mater. Chem. 2, 303 (2015). \n44. Hall, M. et al. The WEKA data mining software. ACM SIGKDD Explor. Newslett. 11, 10 (2009). \n45. King, D. Dlib-ml: a machine learning toolkit. J. Mach. Learn. Res. 10, 1755–1758 (2009). \n46. Rodríguez, J. J., Kuncheva, L. I. & Alonso, C. J. Rotation forest: a new classifier ensemble method. IEEE Trans. Pattern Anal. Mach. Intell. 28, 1619–1630 (2006). \n47. Meredig, B. & Wolverton, C. Dissolving the periodic table in cubic zirconia: data mining to discover chemical trends. Chem. Mater. 26, 1985–1991 (2014). \n48. Jain, A. et al. A high-throughput infrastructure for density functional theory calculations. Comput. Mater. Sci. 50, 2295–2310 (2011). \n49. Curtarolo, S. et al. The high-throughput highway to computational materials design. Nat. Mater. 12, 191–201 (2013). \n50. Kirklin, S., Meredig, B. & Wolverton, C. High-throughput computational screening of new Li-ion battery anode materials. Adv. Energy Mater. 3, 252–262 (2013). \n51. Gautier, R. et al. Prediction and accelerated laboratory discovery of previously unknown 18-electron ABX compounds. Nat. Chem. 7, 308–316 (2015). \n52. Chen, H. et al. Carbonophosphates: a new family of cathode materials for Li-ion batteries identified computationally. Chem. Mater. 24, 2009–2016 (2012). \n53. Liu, M. et al. Spinel compounds as multivalent battery cathodes: a systematic evaluation based on ab initio calculations. Energy Environ. Sci. 8, 964–974 (2014). \n54. Yang, K., Setyawan, W., Wang, S., Buongiorno Nardelli, M. & Curtarolo, S. A search model for topological insulators with high-throughput robustness descriptors. Nat. Mater. 11, 614–619 (2012). \n55. Ho, T. K. The random subspace method for constructing decision forests. IEEE Trans. Pattern Anal. Mach. Intell. 20, 832–844 (1998). \n56. Shockley, W. & Queisser, H. J. Detailed balance limit of efficiency of p-n junction solar cells. J. Appl. Phys. 32, 510 (1961). \n57. Sparks, T. D., Gaultois, M. W., Oliynyk, A., Brgoch, J. & Meredig, B. Data mining our way to the next generation of thermoelectrics. Scr. Mater. 111, 10–15 (2015). \n58. Wang, W. H., Dong, C. & Shek, C. H. Bulk metallic glasses. Mater. Sci. Eng. R Rep. 44, 45–89 (2004). \n59. Inoue, A. Stabilization of metallic supercooled liquid and bulk amorphous alloys. Acta Mater. 48, 279–306 (2000). \n60. Löffler, J. F. Formation of bulk metallic glasses and their composites. MRS Bull. 32, 624–628 (2007). \n61. Ding, S. et al. Combinatorial development of bulk metallic glasses. Nat. Mater. 13, 494–500 (2014). \n62. Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001). \n63. Wada, T., Zhang, T. & Inoue, A. Formation and high mechanical strength of bulk glassy alloys in Zr-Al-Co-Cu system. Mater. Trans. 44, 1839–1844 (2003). \n64. Thornton, C., Hutter, F., Hoos, H. H. & Leyton-Brown, K. in Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (ACM, New York, NY, 2013). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/ by/4.0/ \n\n$\\circledcirc$ The Author(s) 2016 " + }, + { + "id": "10.1126_science.aab1031", + "DOI": "10.1126/science.aab1031", + "DOI Link": "http://dx.doi.org/10.1126/science.aab1031", + "Relative Dir Path": "mds/10.1126_science.aab1031", + "Article Title": "Electrical switching of an antiferromagnet", + "Authors": "Wadley, P; Howells, B; Zelezny, J; Andrews, C; Hills, V; Campion, RP; Novák, V; Olejník, K; Maccherozzi, F; Dhesi, SS; Martin, SY; Wagner, T; Wunderlich, J; Freimuth, F; Mokrousov, Y; Kunes, J; Chauhan, JS; Grzybowski, MJ; Rushforth, AW; Edmonds, KW; Gallagher, BL; Jungwirth, T", + "Source Title": "SCIENCE", + "Abstract": "Antiferromagnets are hard to control by external magnetic fields because of the alternating directions of magnetic moments on individual atoms and the resulting zero net magnetization. However, relativistic quantum mechanics allows for generating current-induced internal fields whose sign alternates with the periodicity of the antiferromagnetic lattice. Using these fields, which couple strongly to the antiferromagnetic order, we demonstrate room-temperature electrical switching between stable configurations in antiferromagnetic CuMnAs thin-film devices by applied current with magnitudes of order 10(6) ampere per square centimeter. Electrical writing is combined in our solid-state memory with electrical readout and the stored magnetic state is insensitive to and produces no external magnetic field perturbations, which illustrates the unique merits of antiferromagnets for spintronics.", + "Times Cited, WoS Core": 1158, + "Times Cited, All Databases": 1233, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000369291600036", + "Markdown": "Cite as: P. Wadley et al., Science 10.1126/science.aab1031 (2016). \n\n# Electrical switching of an antiferromagnet \n\nP. Wadley,1\\*† B. Howells,1\\* J. Železný,2,3 C. Andrews,1 V. Hills,1 R. P. Campion,1 V. Novák,2 K. Olejník,2 F. Maccherozzi,4 S. S. Dhesi,4 S. Y. Martin,5 T. Wagner,5,6 J. Wunderlich,2,5 F. Freimuth,7 Y. Mokrousov,7 J. Kuneš,8 J. S. Chauhan,1 M. J. Grzybowski,1,9 A. W. Rushforth,1 K. W. Edmonds,1 B. L. Gallagher,1 T. Jungwirth,2,1 \n\n1School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, UK. 2Institute of Physics, Academy of Sciences of the Czech Republic, Cukrovarnická 10, 162 00 Praha 6, Czech Republic. 3Faculty of Mathematics and Physics, Charles University, Ke Karlovu 3, 121 16 Prague 2, Czech Republic. 4Diamond Light Source, Chilton, Didcot, Oxfordshire, OX11 0DE, UK. 5Hitachi Cambridge Laboratory, J. J. Thomson Avenue, Cambridge CB3 0HE, UK. 6Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0HE, UK. 7Peter Grünberg Institut and Institute for Advanced Simulation, Forschungszentrum Jülich and JARA, 52425 Jülich, Germany. 8Institute of Physics, Academy of Sciences of the Czech Republic, Na Slovance 2, 182 21 Praha 8, Czech Republic. 9Institute of Physics, Polish Academy of Sciences, al. Lotnikow 32/46, 00-681 Warsaw, Poland. \n\n\\*These authors contributed equally to this work. †Corresponding author. E-mail: peter.wadley@nottingham.ac.uk \n\nAntiferromagnets are hard to control by external magnetic fields because of the alternating directions of magnetic moments on individual atoms and the resulting zero net magnetization. However, relativistic quantum mechanics allows for generating current-induced internal fields whose sign alternates with the periodicity of the antiferromagnetic lattice. Using these fields, which couple strongly to the antiferromagnetic order, we demonstrate room-temperature electrical switching between stable configurations in antiferromagnetic CuMnAs thin film devices by applied current with magnitudes of order $10^{6}\\mathsf{A c m}^{-2}$ . Electrical writing is combined in our solid-state memory with electrical readout and the stored magnetic state is insensitive to and produces no external magnetic field perturbations, which illustrates the unique merits of antiferromagnets for spintronics. \n\nIn charge-based information devices, perturbations such as ionizing radiation can lead to data loss. In contrast, spinbased devices, in which different magnetic moment orientations in a ferromagnet (FM) represent the zeros and ones $(I)$ , are robust against charge perturbations. However, the FM moments can be unintentionally reoriented and the data erased by perturbing magnetic fields generated externally or internally within the memory circuitry. If magnetic memories were based on antiferromagnets (AFMs) instead, they would be robust against charge and magnetic field perturbations. Additional advantages of AFMs compared to FMs include the invisibility of data stored in AFMs to external magnetic probes, ultrafast spin dynamics in AFMs, and the broad range of metal, semiconductor, or insulator materials with room-temperature AFM order (2–7). \n\nThe energy barrier separating stable orientations of ordered spins is due to the magnetic anisotropy energy. It is an even function of the magnetic moment which implies that the magnetic anisotropy and the corresponding memory functionality are readily present in both FMs and AFMs (8, 9). The magneto-transport counterpart of the magnetic anisotropy energy is the anisotropic magnetoresistance (AMR). In the early $\\mathrm{1990^{\\circ}s}$ , the first generation of FM MRAM micro-devices used AMR for the electrical readout of the memory state (10). AMR is an even function of the magnetic moment which again implies its presence in AFMs (11). Although AMR in AFMs was experimentally confirmed in several recent studies (12–17), efficient means for manipulating AFM moments have remained elusive. \n\nIt has been proposed that current-induced spin transfer torques of the form $d M/d t\\sim M\\times(M\\times p)$ , which are used for electrical writing in the most advanced FM magnetic random access memories (MRAMs) $(I)$ , could also produce large angle reorientation of the AFM moments (18). In these antidamping-like torques, $M$ is the magnetic moment vector and $p$ is the electrically injected carrier spinpolarization. Translated to AFMs, the effective field proportional to $(M_{\\mathit{A,B}}\\times p)$ that drives the antidamping-like torque $d M_{_{A,B}}/d t\\sim M_{_{A,B}}\\times(M_{_{A,B}}\\times p)$ on individual spin sublattices A and B has the favorable staggered property, i.e., alternates in sign between the opposite spin sublattices. \n\nIn FM spin-transfer-torque MRAMs, spin polarized carriers are injected into the free FM layer from a fixed FM polarizer by an out-of-plane electrical current driven through the FM-FM stack. In analogy, Ref. (18) assumes injection of the spin polarized carriers into the AFM from a fixed FM polarizer by out-of-plane electrical current driven in a FM-AFM stack. However, relativistic spin-orbit coupling may offer staggered current-induced fields which do not require external polarizers and which act in bare AFM crystals (19). The effect occurs in AFMs with specific crystal and magnetic structures for which the spin sublattices form space-inversion partners. Among these materials is a high Néel temperature AFM, tetragonal-phase CuMnAs, which was recently synthesized in the form of single-crystal epilayers on III-V semiconductor substrates (20). \n\nRelativistic current-induced fields observed previously in broken inversion-symmetry FM crystals (21–29) can originate from the inverse spin galvanic effect (30–34) (Fig. 1, A and B). The full lattice of the CuMnAs crystal (Fig. 1C) has an inversion symmetry with the center of inversion at an interstitial position (green ball in the figure). This implies that the mechanism described in Figs. 1, A and B will not generate a net current-induced spin-density when integrated over the entire crystal. However, Mn atoms form two sublattices (depicted in Fig. 1C in red and purple) whose local environment has broken inversion symmetry and the two Mn sublattices form inversion partners. The inverse spin galvanic mechanisms of Figs. 1A,B will generate locally non-equilibrium spin polarizations of opposite signs on the inversion-partner Mn sublattices. For these staggered fields to couple strongly to the antiferromagnetic order it is essential that the inversion-partner Mn sublattices coincide with the two spin-sublattices A and $\\mathbf{B}$ of the AFM ground-state (19). The resulting spin-orbit torques have the form $d M_{_{A,B}}/d t\\sim M_{_{A,B}}\\times p_{_{A,B}}$ where the effective field proportional to $p_{{\\scriptscriptstyle A}}=-p_{{\\scriptscriptstyle B}}$ acting on the spin-sublattice magnetizations $M_{_{A,B}}$ alternates in sign between the two sublattices. The CuMnAs crystal and magnetic structures (Fig. 1C) fulfil these symmetry requirements (20). \n\nTo quantitatively estimate the strength of the staggered current-induced field we performed microscopic calculations based on the Kubo linear response formalism (35) (see supplementary online text for details). The calculations (Fig. 1D) confirm the desired opposite sign of the current-induced field on the two spin-sublattices and highlight the expected dependence on the magnetic moment angle, which implies that the AFM moments will tend to align perpendicular to the applied current. For reversible electrical switching between two stable states and the subsequent electrical detection by the AMR, the setting current pulses can therefore be applied along two orthogonal in-plane cubic axes of CuMnAs. The magnitude of the effect seen in Fig. 1D is comparable to typical current-induced fields applied in FMs, suggesting that CuMnAs is a favorable material for observing current-induced switching in an AFM. \n\nOur experiments were conducted on epitaxial films of the tetragonal phase of CuMnAs, which is a member of a broad family of high-temperature I-Mn-V AFM compounds (6, 7, 20). We have observed the electrical switching and readout effects described below in more than 20 devices fabricated from 5 different CuMnAs films, with thickness ranging from $40\\ \\mathrm{nm}$ to $80\\ \\mathrm{nm}$ , grown on either GaP or GaAs substrates. The electrical data shown in Figs. 2-4 were obtained on a $46\\ \\mathrm{nm}$ epilayer on lattice-matched GaP(001), whose transmission electron microscopy image (Fig. 2A) demonstrates excellent structural and chemical order (20). Consistent with the AFM order of the CuMnAs film, superconducting quantum interference device (SQUID) magnetometry measurements (Fig. 2B) show only the diamagnetic background of the sample substrate. X-ray magnetic linear dichroism photoelectron emission microscopy (XMLDPEEM) measurements at the Mn L3 absorption edge show that the AFM moments are oriented in the plane of the film, with a sub-micron scale domain structure (Fig. 2C). Neutron diffraction confirmed collinear AFM order with a Néel temperature $T_{N}=480$ K (20, 36). The CuMnAs film is metallic with a room-temperature sheet resistivity of $160~\\mu\\Omega$ cm. \n\nIn Fig. 2E, we demonstrate the electrical writing in a CuMnAs device (Fig. 2D). The sample was held at a stable temperature of $273\\mathrm{~K~}$ inferred from the temperature calibration of the resistivity of the CuMnAs film. Three successive $50~\\mathrm{~ms~}$ writing pulses of amplitude $J_{w r i t e}=4{\\times}10^{6}$ Acm  −2 were applied alternately along the [100] crystal axis of CuMnAs (black arrow in Fig. 2D and black points in Fig. 2E) and along the [010] axis (red arrow in Fig. 2D and red points in Fig. 2E). Note that $J_{{_{w r i t e}}}=4{\\times}10^{6}\\ \\mathrm{Acm}^{-2}$ is the current density in the central region of the device obtained from finite element modelling for the applied current of 90 mA driven through the $28~\\mu\\mathrm{~m~}$ wide writing arms of the device. The reading current $J_{r e a d}$ was applied along the [ 1 10] in-plane diagonal and resistance signals, $R_{\\perp}$ , transverse to $J_{r e a d}$ are recorded 10 s after each $J_{w r i t e}$ pulse. A constant offset is subtracted from $R_{\\perp}$ . \n\nThe [100]-directed writing pulses are expected to set a preference for domains with AFM spin-axis along the [010] direction (black double-arrow in Fig. 2D) and the [010]- directed pulses for domains with AFM spin-axis along the [100] direction (red double-arrow in Fig. 2D). Consistent with this picture, successive $J_{w r i t e}$ pulses in one direction increase the amplitude of the read-out $R_{\\perp}$ signal of one sign and pulsing in the orthogonal direction increases the amplitude of $R_{\\perp}$ of the opposite sign. As seen in Fig. 2E, all the AFM memory states can be written reproducibly. The signals are independent of the polarity of the writing current which is expected for the current-induced switching in AFMs. The amplitude of the switching current applied in our AFM memory is comparable to FM spin transfer torque MRAMs and is significantly lower than in the early observations of spin-orbit torque switching in ferromagnetic metals, where 100 MA cm  −2 pulses were used to reverse magnetiza \n\ntion in a $\\mathrm{Pt/Co}$ bilayer (29). \n\nIn Figs. $^{3\\mathrm{A},\\mathrm{B}}$ we explore in more detail the domain reconfiguration by applying a series of fifty $J_{w r i t e}$ pulses of varying length and amplitude along the [010] direction (red points) and [100] direction (black points) at $273\\ \\mathrm{K}$ . The data, which again show highly reproducible switching patterns, illustrate that the imbalance in the domain populations increases with the length and amplitude of the writing pulses and tends to saturate with the increasing number of pulses. Since in these measurements heating of the central region of the device can reach tens of degrees during the writing pulses, we did not explore the switching behavior further beyond the pulse lengths and amplitudes shown in Figs. $^{3\\mathrm{A,B}}$ . More intense pulses in our device design can lead to irreproducible characteristics or device failure due to structural changes. Apart from the absolute $R_{\\perp}$ values, we also indicate in Figs. $^{3\\mathrm{A,B}}$ relative values $R_{\\perp}/\\overline{{R}}$ of the signal, where $\\overline{{R}}$ is the longitudinal resistance $R$ averaged over the different states set by the writing pulses along the [100]/[010] directions. Below we will associate $R_{\\perp}/\\overline{{R}}$ , reaching $0.2\\%$ , with the transverse AFM AMR. Further confirmation of the picture of the current-induced domain reconfiguration by the applied writing pulses is given by XMLD-PEEM measurements and XMLD spectroscopy (see figs. S1, S2 and supplementary online text.) \n\nWe now analyze the symmetry of the measured resistances for different probe current directions. Figure 4 shows switching data for both the transverse resistance signal and the longitudinal signal, $\\Delta R/\\overline{{R}}$ where $\\Delta R=R-\\overline{{R}}$ , obtained at the sample temperature of $\\mathbf{150~K}$ . In these lower-temperature experiments, we applied five successive 275 ms pulses of amplitude $J_{_{w r i t e}}=4.5\\times10^{6}$ Acm  −2 along the [100] or [010] axis to obtain signals comparable to the higher-temperature measurements. Each row in Fig. 4 corresponds to a different axis along which we apply the probe current $J_{r e a d}$ . From top to bottom, the reading current is applied along the crystal axis $[1\\overline{{1}}0]$ , [110], [100], and [010]. \n\nConsistent with the AMR symmetry, the transverse signals (also known as the planar Hall effect) are detected for the AFM spin-axes angle set toward $\\pm45^{\\circ}$ from the probe current and the transverse signal flips sign when the probe current is rotated by $90^{\\circ}$ . The corresponding longitudinal signals vanish in this geometry. For AFM spin-axes set toward $\\pm90^{\\circ}$ from the probe current, the transverse signal vanishes and the longitudinal signal is detected which is again consistent with the AMR symmetries. The AMR nature of the electrical signals is further confirmed by the comparable amplitudes of the transverse and longitudinal signals. We note that apart from the stable AMR signals, the longitudinal resistances show an additional timedependence which is due to the cooling of the sample after the writing pulses. These isotropic changes in $R$ correspond to a temperature change of a fraction of a Kelvin over the probing time-interval. \n\nWe also observe these AMR symmetries in highertemperature measurements. However, the AMR changes sign between the higher- and lower-temperature data as seen when comparing the transverse resistance signals in Fig. 2 and 3 with the corresponding measurements in the first row of Fig. 4. The change in sign of the AMR is further confirmed in fig. S3 (see also the supplementary online text), where the measured temperature dependence of AMR is shown and compared to calculations. From this comparison we can infer the preferred AFM spin axis direction for the given writing current direction. The experimental and theoretical AMR signs match if the AFM spin axis aligns perpendicular to the writing current. This is consistent with the predicted direction of the spin-orbit current-induced fields and with the XMLD-PEEM results. Measurements at high magnetic fields shown in fig. S3 (see also supplementary online text) give further confirmation that the AFM spin axis aligns perpendicular to the setting current pulses. These measurements also highlight that our AFM memory can be read and written by the staggered current-induced fields and the memory state retained even in the presence of strong magnetic fields. \n\nThe staggered current-induced fields we observe are not unique to CuMnAs. The high Néel temperature AFM $\\mathbf{M}\\mathbf{n}_{\\mathbf{\\Omega}_{2}}$ Au (37) is another example in which the spin-sublattices form inversion partners and where theory predicts large field-like torques of the form $d M_{_{A,B}}/d t\\sim M_{_{A,B}}\\times p_{_{A,B}}$ with $p_{{\\scriptscriptstyle A}}=-p_{{\\scriptscriptstyle B}}$ $(I9)$ . From our microscopic density-functional calculations, we obtain a current-induced field of around 20 Oe per $10^{7}\\:\\:\\mathrm{Am}^{-2}$ in $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{n}}_{\\ 2}\\ensuremath{\\mathbf{A}}\\ensuremath{\\mathbf{u}}$ , which combined with its higher conductivity may make this a favorable system for observing current-driven AFM switching. AFMs which do not possess these specific symmetries can in principle be switched by injecting a spin current into the AFM from a spin-orbit coupled non-magnetic (NM) layer using an applied in-plane electrical current via the spin Hall effect, generating the antidamping-like torque $d M_{_{A,B}}/d t\\sim M_{_{A,B}}\\times(M_{_{A,B}}\\times p)$ (19). The same type of torque can be generated by the spin-orbit Berry-curvature mechanism acting at the inversion-asymmetric AFM/NM interface or in bare AFM crystals with globally non-centrosymmetric unit cells like CuMnSb (19). Our experiments in CuMnAs, combined with the prospect of other realizations of these relativistic non-equilibrium phenomena in AFMs, indicate that AFMs are now ready to join the rapidly developing fields of basic and applied spintronics, enriching this area of solid state physics and microelectronics by the range of unique characteristics of AFMs. \n\n# REFERENCES AND NOTES \n\n1. C. Chappert, A. Fert, F. N. Van Dau, The emergence of spin electronics in data storage. Nat. Mater. 6, 813–823 (2007). doi:10.1038/nmat2024 Medline \n2. A. V. Kimel, A. Kirilyuk, A. Tsvetkov, R. V. Pisarev, T. Rasing, Laser-induced ultrafast spin reorientation in the antiferromagnet TmFeO3. Nature 429, 850– 853 (2004). doi:10.1038/nature02659 Medline \n3. M. Fiebig, N. P. Duong, T. Satoh, B. B. Van Aken, K. Miyano, Y. Tomioka, Y. Tokura, Ultrafast magnetization dynamics of antiferromagnetic compounds. J. Phys. D Appl. Phys. 41, 164005 (2008). doi:10.1088/0022-3727/41/16/164005 \n4. T. Yamaoka, Antiferromagnetism in γ-phase Mn-Ir alloys. J. Phys. Soc. Jpn. 36, 445–450 (1974). doi:10.1143/JPSJ.36.445 \n5. W. Zhang, M. B. Jungfleisch, W. Jiang, J. E. Pearson, A. Hoffmann, F. Freimuth, Y. Mokrousov, Spin Hall effects in metallic antiferromagnets. Phys. Rev. Lett. 113, 196602 (2014). doi:10.1103/PhysRevLett.113.196602 Medline \n6. T. Jungwirth, V. Novák, X. Martí, M. Cukr, F. Máca, A. B. Shick, J. Mašek, P. Horodyská, P. Němec, V. Holý, J. Zemek, P. Kužel, I. Němec, B. L. Gallagher, R. P. Campion, C. T. Foxon, J. Wunderlich, Demonstration of molecular beam epitaxy and a semiconducting band structure for I-Mn-V compounds. Phys. Rev. B 83, 035321 (2011). doi:10.1103/PhysRevB.83.035321 \n7. F. Máca, J. Mašek, O. Stelmakhovych, X. Martí, H. Reichlová, K. Uhlířová, P. Beran, P. Wadley, V. Novák, T. Jungwirth, Room-temperature antiferromagnetism in CuMnAs. J. Magn. Magn. Mater. 324, 1606–1612 (2012). doi:10.1016/j.jmmm.2011.12.017 \n8. L. Néel, http://www.nobelprize.org/nobel_prizes/physics/laureates/1970/neellecture.pdf. \n9. R. Y. Umetsu, A. Sakuma, K. Fukamichi, Magnetic anisotropy energy of antiferromagnetic L10-type equiatomic Mn alloys. Appl. Phys. Lett. 89, 052504 (2006). doi:10.1063/1.2236103 \n10. J. Daughton, Magnetoresistive memory technology. Thin Solid Films 216, 162– 168 (1992). doi:10.1016/0040-6090(92)90888-I \n11. A. B. Shick, S. Khmelevskyi, O. N. Mryasov, J. Wunderlich, T. Jungwirth, Spin-orbit coupling induced anisotropy effects in bimetallic antiferromagnets: A route towards antiferromagnetic spintronics. Phys. Rev. B 81, 212409 (2010). doi:10.1103/PhysRevB.81.212409 \n12. B. G. Park, J. Wunderlich, X. Martí, V. Holý, Y. Kurosaki, M. Yamada, H. Yamamoto, A. Nishide, J. Hayakawa, H. Takahashi, A. B. Shick, T. Jungwirth, A spin-valve-like magnetoresistance of an antiferromagnet-based tunnel junction. Nat. Mater. 10, 347–351 (2011). doi:10.1038/nmat2983 Medline \n13. Y. Y. Wang, C. Song, B. Cui, G. Y. Wang, F. Zeng, F. Pan, Room-temperature perpendicular exchange coupling and tunneling anisotropic magnetoresistance in an antiferromagnet-based tunnel junction. Phys. Rev. Lett. 109, 137201 (2012). doi:10.1103/PhysRevLett.109.137201 Medline \n14. X. Marti, I. Fina, C. Frontera, J. Liu, P. Wadley, Q. He, R. J. Paull, J. D. Clarkson, J. Kudrnovský, I. Turek, J. Kuneš, D. Yi, J. H. Chu, C. T. Nelson, L. You, E. Arenholz, S. Salahuddin, J. Fontcuberta, T. Jungwirth, R. Ramesh, Room-temperature antiferromagnetic memory resistor. Nat. Mater. 13, 367–374 (2014). doi:10.1038/nmat3861 Medline \n15. I. Fina, X. Marti, D. Yi, J. Liu, J. H. Chu, C. Rayan-Serrao, S. Suresha, A. B. Shick, J. Zelezný, T. Jungwirth, J. Fontcuberta, R. Ramesh, Anisotropic magnetoresistance in an antiferromagnetic semiconductor. Nat. Commun. 5, 4671 (2014). doi:10.1038/ncomms5671 Medline \n16. T. Moriyama, N. Matsuzaki, K.-J. Kim, I. Suzuki, T. Taniyama, T. Ono, Sequential write-read operations in FeRh antiferromagnetic memory. Appl. Phys. Lett. 107, 122403 (2015). doi:10.1063/1.4931567 \n17. D. Kriegner et al., http://arxiv.org/abs/1508.04877. \n18. H. V. Gomonay, V. M. Loktev, Spin transfer and current-induced switching in antiferromagnets. Phys. Rev. B 81, 144427 (2010). doi:10.1103/PhysRevB.81.144427 \n19. J. Železný, H. Gao, K. Výborný, J. Zemen, J. Mašek, A. Manchon, J. Wunderlich, J. Sinova, T. Jungwirth, Relativistic Néel-order fields induced by electrical current in antiferromagnets. Phys. Rev. Lett. 113, 157201 (2014). doi:10.1103/PhysRevLett.113.157201 Medline \n20. P. Wadley, V. Novák, R. P. Campion, C. Rinaldi, X. Martí, H. Reichlová, J. Zelezný, J. Gazquez, M. A. Roldan, M. Varela, D. Khalyavin, S. Langridge, D. Kriegner, F. Máca, J. Mašek, R. Bertacco, V. Holý, A. W. Rushforth, K. W. Edmonds, B. L. Gallagher, C. T. Foxon, J. Wunderlich, T. Jungwirth, Tetragonal phase of epitaxial room-temperature antiferromagnet CuMnAs. Nat. Commun. 4, 2322 (2013). doi:10.1038/ncomms3322 Medline \n21. B. Bernevig, O. Vafek, Piezo-magnetoelectric effects in p -doped semiconductors. Phys. Rev. B 72, 033203 (2005). doi:10.1103/PhysRevB.72.033203 \n22. A. Chernyshov, M. Overby, X. Liu, J. K. Furdyna, Y. Lyanda-Geller, L. P. Rokhinson, Evidence for reversible control of magnetization in a ferromagnetic material by means of spin–orbit magnetic field. Nat. Phys. 5, 656–659 (2009). doi:10.1038/nphys1362 \n23. M. Endo, F. Matsukura, H. Ohno, Current induced effective magnetic field and magnetization reversal in uniaxial anisotropy (Ga,Mn)As. Appl. Phys. Lett. 97, 222501 (2010). doi:10.1063/1.3520514 \n24. D. Fang, H. Kurebayashi, J. Wunderlich, K. Výborný, L. P. Zârbo, R. P. Campion, A. Casiraghi, B. L. Gallagher, T. Jungwirth, A. J. Ferguson, Spin-orbit-driven ferromagnetic resonance. Nat. Nanotechnol. 6, 413–417 (2011). doi:10.1038/nnano.2011.68 Medline \n25. A. Manchon, S. Zhang, Theory of nonequilibrium intrinsic spin torque in a single nanomagnet. Phys. Rev. B 78, 212405 (2008). doi:10.1103/PhysRevB.78.212405 \n26. I. M. Miron, G. Gaudin, S. Auffret, B. Rodmacq, A. Schuhl, S. Pizzini, J. Vogel, P. Gambardella, Current-driven spin torque induced by the Rashba effect in a ferromagnetic metal layer. Nat. Mater. 9, 230–234 (2010). Medline \n27. U. H. Pi, K. Won Kim, J. Y. Bae, S. C. Lee, Y. J. Cho, K. S. Kim, S. Seo, Tilting of the spin orientation induced by Rashba effect in ferromagnetic metal layer. Appl. Phys. Lett. 97, 162507 (2010). doi:10.1063/1.3502596 \n28. T. Suzuki, S. Fukami, N. Ishiwata, M. Yamanouchi, S. Ikeda, N. Kasai, H. Ohno, Current-induced effective field in perpendicularly magnetized Ta/CoFeB/MgO wire. Appl. Phys. Lett. 98, 142505 (2011). doi:10.1063/1.3579155 \n29. I. M. Miron, K. Garello, G. Gaudin, P. J. Zermatten, M. V. Costache, S. Auffret, S. Bandiera, B. Rodmacq, A. Schuhl, P. Gambardella, Perpendicular switching of a single ferromagnetic layer induced by in-plane current injection. Nature 476, 189–193 (2011). doi:10.1038/nature10309 Medline \n30. A. Y. Silov, P. A. Blajnov, J. H. Wolter, R. Hey, K. H. Ploog, N. S. Averkiev, Currentinduced spin polarization at a single heterojunction. Appl. Phys. Lett. 85, 5929 (2004). doi:10.1063/1.1833565 \n31. Y. K. Kato, R. C. Myers, A. C. Gossard, D. D. Awschalom, Current-induced spin polarization in strained semiconductors. Phys. Rev. Lett. 93, 176601 (2004). doi:10.1103/PhysRevLett.93.176601 Medline \n32. S. D. Ganichev et al., http://arxiv.org/abs/cond-mat/0403641 (2004). \n33. J. Wunderlich, B. Kaestner, J. Sinova, T. Jungwirth, http://arxiv.org/abs/condmat/0410295v1 (2004). \n34. J. Wunderlich, B. Kaestner, J. Sinova, T. Jungwirth, Experimental observation of the spin-Hall effect in a two-dimensional spin-orbit coupled semiconductor system. Phys. Rev. Lett. 94, 047204 (2005). doi:10.1103/PhysRevLett.94.047204 Medline \n35. F. Freimuth, S. Blügel, Y. Mokrousov, Spin-orbit torques in Co/Pt(111) and Mn/W(001) magnetic bilayers from first principles. Phys. Rev. B 90, 174423 (2014). doi:10.1103/PhysRevB.90.174423 \n36. V. Hills, P. Wadley, R. P. Campion, V. Novak, R. Beardsley, K. W. Edmonds, B. L. Gallagher, B. Ouladdiaf, T. Jungwirth, Paramagnetic to antiferromagnetic transition in epitaxial tetragonal CuMnAs (invited). J. Appl. Phys. 117, 172608 (2015). doi:10.1063/1.4914119 \n37. V. M. T. S. Barthem, C. V. Colin, H. Mayaffre, M.-H. Julien, D. Givord, Revealing the properties of Mn2Au for antiferromagnetic spintronics. Nat. Commun. 4, 2892 (2013). doi:10.1038/ncomms3892 Medline \n38. J. Kuneš, P. M. Oppeneer, Anisotropic x-ray magnetic linear dichroism at the L 2, 3 edges of cubic Fe, Co, and Ni: Ab initio calculations and model theory. Phys. Rev. B 67, 024431 (2003). doi:10.1103/PhysRevB.67.024431 \n39. T. McGuire, R. Potter, Anisotropic magnetoresistance in ferromagnetic 3d alloys. IEEE Trans. Magn. 11, 1018–1038 (1975). doi:10.1109/TMAG.1975.1058782 \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge support from EU ERC Advanced Grant No. 268066, from the Ministry of Education of the Czech Republic Grant No. LM2011026, from the Grant Agency of the Czech Republic Grant no. 14-37427, from the UK EPSRC Grant No. EP/K027808/1, from the EU 7th Framework Programme Grant No. REGPOT-CT-2013-316014 and FP7-People-2012-ITN-316657, from HGF Programme VH-NG 513 and DFG SPP 1568, supercomputing resources at Jülich Supercomputing Centre and RWTH Aachen University, and Diamond Light Source for the allocation of beamtime under proposal number SI-12504. We thank Christopher Nelson for providing the STEM measurement. \n\nSUPPLEMENTARY MATERIALS \nwww.sciencemag.org/cgi/content/full/science.aab1031/DC1 \nSupplementary Text \nFigs. S1 to S3 \nReferences (38, 39) \n\n![](images/0eb8a93b62378ba0b90f166f8e64c21b5aa573f89a2624969ac15a83237b9e14.jpg) \nFig. 1. Theory of the staggered current-induced field in CuMnAs. (A) Schematic of the inverse spin galvanic effect in a model inversion asymmetric Rashba spin texture (red arrows). $k_{x,y}$ are the in-plane momentum components. The non-equilibrium redistribution of carriers from the left side to the right side of the Fermi surface results in a net inplane spin polarization (thick red arrow) along $+z\\times J$ direction, where $J$ is the applied current (black arrow). (B) Same as (A) for opposite sense of the inversion asymmetry resulting in a net in-plane spin polarization (thick purple arrow) along $-z\\times J$ direction. (C) CuMnAs crystal structure and AFM ordering. The two Mn spin-sublattices A and B (red and purple) are inversion partners. This and panels (A) and (B) imply opposite sign of the respective local current-induced spin polarizations, $p_{{_A}}=-p_{_B}$ , at spin-sublattices A and B. The full CuMnAs crystal is centrosymmetric around the interstitial position highlighted by the green ball. (D) Microscopic calculations of the components of the spin-orbit field transverse to the magnetic moments per current density $10^{7}\\mathsf{A c m}^{-2}$ at spin-sublattices A and B as a function of the magnetic moment angle $\\varphi$ measured from the x-axis ([100] crystal direction). The electrical current is applied along the x and y-axes. \n\n![](images/5dfa4da7642f0205c42309262de4555a2392225e746f758a462feb34d4fbc6b1.jpg) \nFig. 2. Electrical switching of the AFM CuMnAs. (A) Scanning transmission electron microscopy image of CuMnAs/GaP in the [100]–[001] plane. (B) Magnetization versus applied field of an unpatterned piece of the CuMnAs/GaP wafer measured by SQUID magnetometer. (C) XMLD-PEEM image of the CuMnAs film with $\\mathsf{x}$ -rays at the Mn L3 absorption edge incident at $16^{\\circ}$ from the surface along the [100] axis. (D) Optical microscopy image of the device and schematic of the measurement geometry. (E) Change in the transverse resistance after applying three successive 50 ms writing pulses of amplitude $J_{_{w r i t e}}=4{\\times}10^{6}$ Acm  −2 alternatively along the [100] crystal direction of CuMnAs (black arrow in panel D and black points in panel E) and along the [010] axis (red arrow in panel D and red points in panel E). The reading current $J_{r e a d}$ is applied along the [ 1 10] axis and transverse resistance signals $R_{\\perp}$ are recorded 10 s after each writing pulse. A constant offset is subtracted from $R_{\\perp}$ . Measurements were done at sample temperature of $273\\mathsf{K}$ . \n\n![](images/4ebd24d6767130648ae74ab28e198550d7a5393482c0625c4917cc12df129c71.jpg) \nFig. 3. Dependence of the switching on the writing pulse length and amplitude. Transverse resistance after successive writing pulses along the [100] axis (black points) and [010] axis (red points) for different current amplitudes (A) or pulse lengths (B). $R_{\\perp}$ is recorder 10 s after each writing pulse. $\\overline{{R}}$ is the average of the longitudinal resistance $R$ . Measurements were done at sample temperature of $273\\mathsf{K}.$ . A constant offset is subtracted from $R_{\\perp}$ . \n\n![](images/96394fe8becf13f73f3ee30d5167fb078e684aaf95b1d81e7f897cad80ca4eb2.jpg) \nFig. 4. AMR symmetry of the electrical readout signals. (A) Optical microscopy image of the device and of the measurement geometries with different probe current directions (green arrows). The writing current directions are shown by black and red arrows. (B) Normalised transverse resistance $R_{\\perp}/\\overline{{R}}$ after five writing current pulses along the [100] axis (black) and five pulses along the [010] axis (red) for the reading current directions shown in (A). Vertical lines indicate the times of the pulses. The pulse length is 275 ms and amplitude $J_{_{w r i t e}}=4.5\\times10^{6}$ $\\mathsf{A c m}^{-2}$ . Measurements were done at sample temperature of $150~\\mathsf{K}.$ . A constant offset is subtracted from $R_{\\perp}$ . (C) As for (B) but for the normalised longitudinal resistance change, $\\Delta R/\\overline{{R}}$ where $\\Delta R=R-\\overline{{R}}$ . " + }, + { + "id": "10.1179_1743284715Y.0000000073", + "DOI": "10.1179/1743284715Y.0000000073", + "DOI Link": "http://dx.doi.org/10.1179/1743284715Y.0000000073", + "Relative Dir Path": "mds/10.1179_1743284715Y.0000000073", + "Article Title": "Wire plus Arc Additive Manufacturing", + "Authors": "Williams, SW; Martina, F; Addison, AC; Ding, J; Pardal, G; Colegrove, P", + "Source Title": "MATERIALS SCIENCE AND TECHNOLOGY", + "Abstract": "Depositing large components (>10 kg) in titanium, aluminium, steel and other metals is possible using Wire + Arc Additive Manufacturing. This technology adopts arc welding tools and wire as feedstock for additive manufacturing purposes. High deposition rates, low material and equipment costs, and good structural integrity make Wire + Arc Additive Manufacturing a suitable candidate for replacing the current method of manufacturing from solid billets or large forgings, especially with regards to low and medium complexity parts. A variety of components have been successfully manufactured with this process, including Ti-6Al-4V spars and landing gear assemblies, aluminium wing ribs, steel wind tunnel models and cones. Strategies on how to manage residual stress, improve mechanical properties and eliminate defects such as porosity are suggested. Finally, the benefits of non-destructive testing, online monitoring and in situ machining are discussed.", + "Times Cited, WoS Core": 1158, + "Times Cited, All Databases": 1263, + "Publication Year": 2016, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000378338600005", + "Markdown": "# Wire + Arc Additive Manufacturing \n\nS. W. Williams, F. Martina, A. C. Addison, J. Ding, G. Pardal & P. Colegrove \n\nTo cite this article: S. W. Williams, F. Martina, A. C. Addison, J. Ding, G. Pardal & P. Colegrove (2016) Wire $^+$ Arc Additive Manufacturing, Materials Science and Technology, 32:7, 641-647, DOI: 10.1179/1743284715Y.0000000073 \n\nTo link to this article: https://doi.org/10.1179/1743284715Y.0000000073 \n\n# Wire Arc Additive Manufacturing \n\nS. W. Williams, F. Martina\\*, A. C. Addison, J. Ding, G. Pardal and P. Colegrove \n\nDepositing large components $(>10~\\mathsf{k g})$ in titanium, aluminium, steel and other metals is possible using Wire $+$ Arc Additive Manufacturing. This technology adopts arc welding tools and wire as feedstock for additive manufacturing purposes. High deposition rates, low material and equipment costs, and good structural integrity make Wire þ Arc Additive Manufacturing a suitable candidate for replacing the current method of manufacturing from solid billets or large forgings, especially with regards to low and medium complexity parts. A variety of components have been successfully manufactured with this process, including Ti–6Al–4V spars and landing gear assemblies, aluminium wing ribs, steel wind tunnel models and cones. Strategies on how to manage residual stress, improve mechanical properties and eliminate defects such as porosity are suggested. Finally, the benefits of non-destructive testing, online monitoring and in situ machining are discussed. \n\nKeywords: Additive manufacturing, Wire $^+$ Arc Additive Manufacturing, Titanium, Steel, Aluminium, Rolling, Microstructure control, Mechanical properties \n\n# This paper is part of a Themed Issue on Additive manufacturing of metals for aerospace applications \n\n# Introduction \n\nAdditive manufacturing (AM) is a technology that promises to reduce part cost by reducing material wastage and time to market.1 Furthermore, AM can also enable an increase in design freedom, which potentially results in weight saving as well as facilitating the manufacture of complex assemblies formerly made of many subcomponents.2 \n\nA basic AM system consists of a combination of a motion system, heat source and feedstock. Owing to its intrinsic characteristics, each process is naturally suitable for certain applications. For instance, selective laser melting delivers net shape components with high resolution; however, similarly to electron beam melting, deposition rates are relatively low, and part size is limited by the enclosed working envelope.3 Consequently, this class of processes is best suited to small components with high complexity. The main business drivers for their adoption are freedom of design, customisation and possibly reduced time to market.1 The benefit associated with the reduction in material waste is limited; the mass of the components is already low to begin with. While the possibility of topologically optimising certain components is important, there is a growing requirement for larger reductions in material waste, for the following reasons. First, with the increasing usage of carbon fibre reinforced polymers, aircraft designers are forced to shift from aluminium to titanium, the former being electrochemically incompatible with carbon.4 Second, with the current and forecast aircraft market expansion rate, the demand for titanium parts is increasing accordingly.5 Third, titanium is an expensive material to source and machine.6 Therefore, in the aerospace industry, there is a pressing need for the development of a process that could replace the current method of manufacturing large structures such as cruciforms, stiffened panels, wing ribs, etc., which are machined from billets or large forgings, with unsustainable buy/fly (BTF) ratios. This metric is the ratio of the mass of the initial workpiece to the one of the finished product; in the aerospace sector, values of 10 or even 20 are not unusual.7 \n\n# Wire $+$ Arc AM (WAAM) \n\nThe combination of an electric arc as heat source and wire as feedstock is referred to as WAAM and has been investigated for AM purposes since the 1990s,8 although the first patent was filed in 1925.9 WAAM hardware currently uses standard, off the shelf welding equipment: welding power source, torches and wire feeding systems. Motion can be provided either by robotic systems (Fig. 1a) or computer numerical controlled gantries. Figure $1b$ shows a friction stir welding machine, which has been equipped with a metal inert gas (MIG) power source. The retrofitted machine features a bed, which is $5\\mathrm{m}\\times3\\mathrm{m}$ in size. \n\n# Processes \n\nWhenever possible, $\\mathrm{MIG}^{10}$ is the process of choice: the wire is the consumable electrode, and its coaxiality with the welding torch results in easier tool path. In particular, Fronius cold metal transfer (CMT) is a modified MIG variant, which relies on controlled dip transfer mode mechanism; this is supposed to deliver beads with excellent quality, lower thermal heat input and nearly without spatter.11 While meeting these expectations when depositing materials such as aluminium and steel, unfortunately, with titanium, this process is affected by arc wandering, 12 which results in increased surface roughness. Consequently, tungsten inert gas,13 or plasma arc welding,14 is currently used for titanium deposition. These processes, however, rely on external wire feeding; for deposition consistency, the wire must be fed always from the same direction, which requires rotation of the torch, thus complicating robot programming.14 \n\n![](images/ce7618ff42dcd751cbe7288083cb8340eb58b3b75f0787d5a474536ee70597ee.jpg) \na six-axis ABB welding robot; b deposition system retrofitted onto former friction stir welding machine 1 Motion systems options for WAAM \n\n# Example parts \n\nWAAM’s layer height is normally in the range of $1-$ $2\\mathrm{mm}$ , resulting in a surface roughness (the waviness) of roughly $500~{\\upmu\\mathrm{m}}$ for single track deposits.14 Consequently, WAAM cannot be considered a net shape process, and machining is required to finish the part. It follows that WAAM is better suited for low to medium complexity and medium to large scale parts. \n\nFigure $2a$ shows a $1.2\\mathrm{m}\\mathrm{Ti}{-}6\\mathrm{Al}{-}4\\mathrm{V}$ wing spar made for BAE Systems,15 which was deposited in a flexible enclosure using plasma arc welding with a seven-axis robotic system. The part features straight and curved features, all perpendicular to the substrate, and T junctions. Two parts were built simultaneously by alternating deposition on either sides of a sacrificial substrate (Fig. 2b); the reason for this will be discussed later. The deposition rate was $0.8\\mathrm{{kg/h}}$ with a BTF ratio of 1.2. \n\nFigure $2c$ shows a $24\\mathrm{kg}$ Ti–6Al–4V external landing gear assembly. The part was also built at $0.8\\mathrm{~kg/h}$ on either side of the plane, which gave the largest symmetry (see ‘Residual stress’ under ‘Challenges’), sharing the same set-up of the spar of Fig. $2a$ and $b$ . This part features T junctions, crossings, perpendicular and slightly tilted walls. With a BTF ratio of 1.2, WAAM enabled material savings in excess of $220\\mathrm{kg}$ . \n\nFigure $2d$ shows a $2.5\\mathrm{m}$ aluminium wing rib, which is currently machined from solid with a BTF ratio of $37-$ $670\\mathrm{kg}$ are required for a finished product of $18~\\mathrm{kg}$ . A part rotator was also employed, and the rib feet were added by WAAM at $1.1\\mathrm{kg/h}$ using Fronius CMT Advanced11 on either side of the plane of symmetry, which coincided with the substrate. Owing to the size of the part, two robots were depositing material simultaneously. No enclosure was required. The final part has a stiffening web in between the rib feet, which was not deposited but will be machined out of the thicker substrate, which is accommodating it. This results in a BTF ratio for WAAM of 12, sufficient to enable material savings of roughly $500\\mathrm{kg}$ per part. \n\nFigure $2e$ shows a $0.8\\mathrm{m}$ wing for wind tunnel testing built in partnership with Aircraft Research Association. Specifically, Aircraft Research Association is aiming at reducing the time between the release of design surfaces to the gathering of data in the wind tunnel. The deposition process was Fronius $\\mathbf{C}\\mathbf{M}\\mathbf{T}^{11}$ with a deposition rate of $3.5\\mathrm{kg/h}$ . The wing features a hollow structure up until its midpoint (Fig. 2f) and will be machined to an accuracy of $0.05\\mathrm{mm}$ . \n\nFinally, Fig. $2g$ shows a steel profiled cone also built by Fronius $\\dot{\\mathbf{C}}\\mathbf{M}\\mathbf{\\bar{I}}^{11}$ at $2.6\\mathrm{kg/h}$ . The deposition parameters produced a wall thickness of $2.5\\mathrm{mm}$ ; against a target of $2\\mathrm{mm}$ , the BTF ratio was 1.25. Further to this, lead time can be cut potentially from 6 months to just a few hours. \n\n# Benefits \n\n# Capital cost \n\nA six-axis robot (£50k), a power source and torch (£30k) and the clamping tooling (£10k) constitute the basic WAAM hardware, for a total of $\\operatorname{\\mathbb{E90k}}$ . This system is suitable for deposition of steel and aluminium. In case of titanium, given the additional requirement for an inert atmosphere, an enclosure might be necessary (an extra £20k). \n\n# Open architecture \n\nThe end user can potentially combine any brand of power source and manipulator retaining total control over the hardware. This is managed by software, WAAMsoft, which controls the process and can be adapted to the specific equipment available in the manufacturing cell. Furthermore, the user retains the freedom to change any deposition parameter; the software suggests the deposition parameters on a feature basis, but the user can customise them if required. \n\n# Part size \n\nMaterials such as aluminium or steel do not have a stringent requirement for gas shielding; consequently, the maximum part size is determined uniquely by the reach capability of the manipulator. For materials that require shielding such as titanium, the size is limited by the inner envelope of the chamber or tent used to create the inert atmosphere. \n\n# Deposition rate \n\nDeposition rates are sufficiently high to make the deposition of large scale parts achievable in reasonable times. With rates ranging from $1\\mathrm{{kg/h}}$ to $4\\mathrm{kg/h}$ for \n\n![](images/0a683a48f0946c8cc527aedcaad2a0f238822fda59bb7f4c8f1d37b979877052.jpg) \na 1.2 m Ti–6Al–4V wing spar built for BAE Systems, top view (courtesy BAE Systems;15process: PAWWAAM); b side view (please note two-component built back to back; courtesy of BAE Systems15); $\\mathtt{c24k g}$ Ti–6Al–4V external landing gear assembly (process: PAWWAAM); $_{d2.5\\mathsf{m}}$ aluminium wing spar (process: Fronius CMT Advanced 1 1 WAAM); e high strength steel wing model for wind tunnel testing (process: Fronius CMT11 WAAM); $\\pmb{f}$ particular of hollow structure; $\\pmb{g}$ mild steel truncated cone (process: Fronius CMT11 WAAM) \n\n# 2 Recent parts built by WAAM \n\naluminium and steel respectively, most parts can be manufactured within one working day. Higher deposition rates can be achieved (e.g. $10\\mathrm{kg/h}$ ), but this then compromises the fidelity of the part. For instance, at $10\\mathrm{kg/h}$ , the BTF ratio can be as high as 10 for the final deposited part,16 which is effectively a preform, thus requiring significant machining as well as the deposition of much more material, making the process less attractive from an economic point of view. Keeping the deposition rate at medium levels (e.g. $1\\mathrm{{kg/h}}$ for titanium and aluminium, and $3\\mathrm{kg/h}$ for steel) ensures that a BTF ratio of $<1.5$ is always achieved, maximising the cost saving. \n\n# Material cost and utilisation \n\nWelding wire is a cheap form of feedstock. Steel is priced between $\\pm2/\\mathrm{kg}$ and $\\operatorname{\\pounds}15/\\operatorname{kg}$ (depending upon wire diameter and alloy composition), aluminium between $\\mathrm{\\pounds6/kg}$ and $\\operatorname{\\mathbb{f}}100/\\mathrm{kg}$ (depending upon wire diameter and alloy composition) and Ti–6Al–4V between $\\mathrm{\\tl{00}/k g}$ and $\\pounds250/\\mathrm{kg}$ (depending upon wire diameter and alloy composition). Furthermore, wire avoids many of the challenges associated with powders such as control of particle size or distribution, which affect process performance. Finally, at the point of deposition, the wire is entirely molten and becomes part of the final structure, and the likelihood of contamination is low compared with powder. \n\n# Materials \n\n# $T i{-}6A l{-}4V$ \n\nAdditively manufactured Ti–6Al–4V displays superior damage tolerance properties; in particular, high cycle fatigue can be one order of magnitude better than that of the wrought alloy.13 However, Ti–6Al–4V is affected by strong anisotropy of both tensile strength and elongation. Owing to its solidification characteristics, AM components display columnar prior $\\beta$ grains13 and a highly textured microstructure.17 This results in higher strength in the direction parallel to that of the layers; vice versa, the elongation is superior in the perpendicular direction. \n\nTo overcome this problem, rolling may be used to plastically deform the deposit by applying a vertical load.18,19 A schematic of the equipment used to perform high pressure interpass rolling is shown in Fig. 3. The process refines the prior $\\beta$ grain microstructure as well as the $\\alpha$ phase laths, ultimately resulting in isotropic mechanical properties.20,21 Rolling strains the component in both the normal and transverse directions;19 the energy stored in the crystallographic system combined with the heat provided upon deposition of a new layers triggers recrystallisation. The refined material has a yield strength of $994\\mathrm{\\:MPa}$ , an ultimate tensile strength of $1078\\mathrm{MPa}$ and an elongation of $13\\%$ ;20,21 these values are all better than the wrought alloy ${950}\\mathrm{{MPa}}$ , $1034\\mathrm{MPa}$ and $12\\%$ respectively)13 and are not dependent upon solidification conditions; rather, they rely on the mechanical processing of the part during deposition.21 \n\n# Aluminium \n\nAdditively manufactured aluminium is affected by porosity.22 It has been shown that, using a combination of good quality welding wires and certain synergic operating modes, porosity can be eliminated.23,22 In particular, Fronius CMT in its pulsed advanced11 variant is particularly beneficial, thanks to lower heat input, which results in finer equiaxed grains and effective oxide cleaning of wire and substrate.22 \n\nBesides Ti–6Al–4V and aluminium; steel, invar, brass, copper and nickel have been successfully deposited. \n\nWith each material, the focus is on guaranteeing mechanical properties and eliminating defects such as porosity. \n\n# Challenges \n\n# Residual stress \n\nThe significant heat input associated with arc sources leads to high residual stress, manifest in distortion once the component is unclamped.24 Residual stresses are associated with the shrinkage during cooling and are largest along the direction of deposition.25 Currently, the following methods are employed to mitigate this issue. \n\n# Symmetrical building \n\nA plane of symmetry is identified within the volume of the component; the initial substrate will coincide with this plane. Using a part rotator, the deposition of the layers is alternated on the two sides of the substrate; the layer deposited on one side produces stresses, which balance those produced on the other side. Whenever a plane of symmetry cannot be identified, the substrate will be aligned to the plane, which separates the two resulting volumes in the most balanced way. The part shown in Fig. $2c$ was built with this strategy. \n\nOne additional benefit of this approach is the more effective heat management; while a new layer is deposited, the previous one cools down. The disadvantage is that parts could require redesign; for example, a C section component will need to be redesigned into an I section one. \n\n# Back to back building \n\nWhen the starting plate is not part of the component, or when a redesign of the part is not possible, components can be built on either side of the same substrate, which, in this case, is sacrificial. The part shown in Fig. $2b$ was built in this way. This approach does not require redesign and is also characterised by improved heat management; however, two distinct components are made in each step. Consequently, this strategy is recommended when two symmetrical parts are needed, such as when manufacturing wing spars. The parts are subsequently heat treated to relax the residual stresses, before separation. \n\n# Optimising part orientation \n\nThe deposition of shorter layers leads to lower residual stress and distortion; consequently, in preproduction, the part can be orientated in such a way that the slicing produces the shortest tool paths. For instance,the wing spar shown in Fig. $2b$ could be deposited vertically, i.e. with the planes of the layers perpendicular to its longest dimension. Figure $4a$ shows a feasibility study in steel in which the same spar was deposited with this approach. It was possible to produce horizontal features without the need for support structures by relying on the surface tension of the molten metal. An appropriate selection of the deposition parameters is even more crucial when depositing out of position. In particular, the travel speed (TS) has the largest effect on deposits quality.26 Figure $4b$ shows that, for a given wire feed speed/TS ratio of 30 (keeping the WFS/TS ratio constant ensures that both the amount of material per unit of length and the heat input are kept constant), the lowest TS of $0.2\\mathrm{m}/\\mathrm{min}$ resulted in the best deposit; the quality progressively deteriorated for increasing TSs, and finally, deposits were unacceptable for a TS of 0.5 m/min.26 \n\n![](images/1da8428ab7231f94b4847c64fb29bf48ca9018a299d390e9bb7700f99cb0fae4.jpg) \n3 Schematic diagram of rolling and welding equipment \n\nHowever, while desirable from a residual stress point of view, reorientation of the part also resulted in a much larger number of starts/stops, which is often impractical in a real industrial manufacturing scenario. \n\n# High pressure interpass rolling \n\nBesides the microstructural benefits (discussed in the ‘Materials’ section), the strain introduced by a rolling pass results also in mitigation of the residual stress.27 Figure $5c$ shows the effect of roller type and rolling load on the longitudinal residual stress distribution of G3Si1/ER70S-6 WAAM linear components. While the unrolled specimen showed a peak stress of $600\\mathrm{{MPa}}$ , that of the components rolled at $50\\mathrm{kN}$ was $300\\mathrm{{MPa}}$ . The slotted roller, which provided additional side restraints and therefore resulted in a larger strain in the longitudinal direction, reduced the peak stress even further to $250\\mathrm{MPa}$ . Moreover, in the region at the top of the wall, wherein the as deposited specimens residual stresses are moderately tensile, rolling resulted in compressive stresses. \n\nFigure $5b$ shows the residual stress distribution of rolled and unrolled linear Ti–6Al–4V components. The final stress status was very similar to their steel equivalent: rolling reduced the peak stress at the interface between the component and the substrate, and introduced larger compressive stresses at the top of the deposits.25 \n\nUnfortunately, rolling alone has not proved to be capable of eliminating distortion completely due to unrestrained shrinkage and deformation,28 and other strategies are being investigated. \n\n# Non-destructive testing (NDT) and online monitoring (OLM) \n\nWith the view of qualifying WAAM for applications such as structural components for civil aviation, NDT and OLM must be developed. With regards to NDT, shape, porosity levels and grain size must be measured during deposition. The shape measurement is necessary to ensure that each layer is deposited consistent to the tool path, which is generated after slicing of the computer aided design (CAD) drawing. Furthermore, it monitors whether any unexpected distortion due to residual stress occurs. \n\nPorosity might occur due to poor quality wire, as well as its mishandling.13 Identifying pores as soon as they appear allows their in-process elimination, for instance using in-process machining (see following section). \n\nFinally, within the Engineering and Physical Sciences Research Council funded HiDepAM project, spatially resolved acoustic spectroscopy29 is being investigated to assess the grain refinement produced by high pressure rolling, in situ. Spatially resolved acoustic spectroscopy is a non-contact and non-destructive technique, which relies on laser generated and detected surface acoustic waves, determining the local acoustic velocity and thus mapping the microstructure of polycrystalline materials. \n\nWith regards to OLM, arc parameters such as voltage and current, as well as WFS are recorded by a digital logger. From a quality management point of view, monitoring such data allows root cause analysis should a problem arise during deposition. A system for monitoring arc and part temperature is currently being developed. The former is useful to identify deviation from controlled processing parameters, the latter to ensure that each new layer is deposited within consistent thermal conditions. Changes in these result in unexpected variations of the geometry of the deposit bead, which reduces accuracy with regards to both the width of the deposited track and the height of the layer. \n\n![](images/9c8644170de2c24a8cf53a17ca611043d0c874a4f7b049401e9b8a85241f0187.jpg) \na box structure deposited vertically; b horizontal features deposited without supports26 4 Study to assess feasibility of reorientation of spar shown in Fig. 2b (material: mild steel; process: Fronius CMT11 WAAM) \n\n![](images/1622a81e00cf837caf30f8f825420874e801468839ca283e8a8c5014163a9942.jpg) \na residual stress reduction in steel WAAM components; $^{19}b$ residual stress reduction in Ti–6Al–4V WAAM components25,28 5 Effect of high pressure interpass rolling on residual stress in longitudinal direction for WAAM components \n\nThe latter, in particular, is key in terms of reproducing the CAD slicing accurately. \n\n# Integrated machining \n\nWAAM is a near net shape process, which requires a finish machining pass. As discussed previously, WAAM cells can be based on either robotic systems or computer numerical controlled gantries. With the latter being typically retrofitted machine tools, and with robotic machining becoming more common,30 both systems will be able to provide integrated machining. \n\nFor example, a milling cutter was mounted in the spindle of the three-axis machine shown in Fig. 2, formerly used for friction stir welding; with this configuration, a $3\\mathrm{m}$ long, $0.3{\\mathrm{m}}$ tall aluminium linear structure was deposited and finished without any change of set-up. A six-axis machine with automatic tool selection could be equipped with welding power source and torch, and used to produce a fully finished part, thus avoiding issues related to part relocation and datum reference, as well as minimising nonvalue adding activities. \n\nMoreover, in-process machining can be used to correct errors or eliminate defects, as soon as they are identified thanks to NDT and OLM, avoiding scrapping of the part and reducing waste even further. \n\n# Conclusions \n\nAmong the different AM processes, Wire $^+$ Arc Additive Manufacturing seems suited to the manufacturing of medium to large scale components, thanks to the relatively high deposition rates, potentially unlimited build volume, low BTF ratios and low capital and feedstock costs. Substantial reductions in material waste and lead time are WAAM’s main business drivers. These complement the increased freedom of design, which is a prerogative of powder based processes such as selective laser melting and electron beam melting. Thus, WAAM is a candidate to replace the current method of manufacturing aerospace components from billets or forgings; its open architecture means that potentially any welding equipment could be used for AM purposes; however, the current lack of a commercially available platform limits the industrial evaluation and adoption of this technology. Efforts are being undertaken to produce CAD and manufacturing software capable of producing parts automatically. \n\n# Acknowledgements \n\nThe authors would like to express their gratitude to B. Brooks and F. Nielsen for the technical support. The work was supported by the WAAMMat programme industry partners. Furthermore, financial contribution by Engineering and Physical Sciences Research Council under grant no. EP/K029010/1 is acknowledged. \n\nEnquiries for access to the data referred to in this article should be directed to researchdata@cranfield.ac.uk. \n\n# References \n\n1. J. Coykendall, M. Cotteleer, J. Holdowsky and M. Mahto: ‘3D opportunity in aerospace and defense: additive manufacturing takes flight’ ‘A Deloitte series on additive manufacturing’, 1; 2014, Westlake, TX, Deloitte University Press. \n2. M. Cotteleer and J. Joyce: ‘3D opportunity – additive manufacturing paths to performance, innovation, and growth’, Deloitte Rev., 2014, 14. \n3. W. E. Frazier: ‘Metal additive manufacturing: a review’, J. Mater. Eng. Perform., 2014, 23, (6), 1917–1928. \n4. C. Vargel: ‘Corrosion of aluminium’, 1st edn, ; 2004, Oxford, Elsevier Ltd. \n5. C. Cui, B. Hu, L. Zhao and S. Liu: ‘Titanium alloy production technology, market prospects and industry development’, Mater. Des., 2011, 32, (3), 1684–1691. \n6. G. L¨utjering and J. Williams: ‘Titanium’, 2nd edn, ; 2007, New York, Springer. \n7. J. Allen: ‘An investigation into the comparative costs of additive manufacturing vs. machine from solid for aero engine parts’ ‘Cost effective manufacturing via net-shape processing’, Proc. Meet. RTO-MP-AVT-139, Neuilly-sur-Seine, France, May 2006, NATO. \n8. R. Acheson: ‘Automatic welding apparatus for weld build-up and method of achieving weld build-up’; US patent no. 4 952 769 1990. \n9. R. Baker: ‘Method of making decorative articles’; US patent no. 1 533 300 1925. \n10. P. S. Almeida and S. Williams: ‘Innovative process model of Ti– 6Al–4V additive layer manufacturing using cold metal transfer (CMT)’, Proc. 21st Int. Solid Freeform Fabrication Symp., Austin, TX, USA, August 2010, University of Texas, 25–36. \n11. fronius.com: ‘CMT Advanced’; 2015. https://www.fronius.com/ cps/rde/xchg/SID-2BF524E9-5150258D/fronius_international/hs.xsl/ 79_17482_ENG_HTML.htm. \n12. B. W. Shinn, D. F. Farson and P. E. Denney: ‘Laser stabilisation of arc cathode spots in titanium welding’, Sci. Technol. Weld. Join., 2005, 10, (4), 475–481. \n13. F. Wang, S. Williams, P. A. Colegrove and A. Antonysamy: ‘Microstructure and mechanical properties of wire and arc additive manufactured Ti–6Al–4V’, Metall. Mater. Trans. A, 2013, 44A, (2), 968–977. \n14. F. Martina, J. Mehnen, S. W. Williams, P. Colegrove and F. Wang: ‘Investigation of the benefits of plasma deposition for the additive layer manufacture of Ti–6Al–4V’, J. Mater. Process. Technol., 2012, 212, (6), 1377–1386. \n15. baesystems.com: ‘Growing knowledge, growing parts: innovative 3D printing process reveals potential for aerospace industry’; 2014. http://www.baesystems.com/article/BAES_163742/growingknowledge-growing-parts. \n16. Sciaky: ‘Sciaky’s metal additive manufacturing – 3D printing brochure’; 2014. http://www.sciaky.com/documents/Sciaky_ Direct_Manufacturing.pdf. \n17. A. Antonysamy: ‘Microstructure, texture and mechanical property evolution during additive manufacturing of Ti6Al4V alloy for aerospace applications’; PhD thesis, School of Materials, University of Manchester, Manchester, UK 2012. \n18. S. Kurkin and V. Anufriev: ‘Preventing distortion of welded thinwalled members of AMg6 and 1201 aluminum alloys by rolling the weld with a roller behind the welding arc’, Weld. Prod., 1984, 31, (10), 32–34. \n19. P. A. Colegrove, H. Coules, J. Fairman, F. Martina, T. Kashoob, H. Mamash and L. D. Cozzolino: ‘Microstructure and residual stress improvement in wire and arc additively manufactured parts through high-pressure rolling’, J. Mater. Process. Technol., 2013, 213, (10), 1782–1791. \n20. F. Martina, S. W. Williams and P. A. Colegrove: ‘Improved microstructure and increased mechanical properties of additive manufacture produced Ti–6Al–4V by interpass cold rolling’, Proc. 24th Int. Solid Freeform Fabrication Symp., Austin, TX, USA, August 2013, University of Texas, 490–496. \n21. F. Martina: ‘Investigation of methods to manipulate geometry, microstructure and mechanical properties in titanium large scale wire $^+$ arc additive manufacturing’; PhD thesis, Cranfield University, UK, Cranfield, UK 2014. \n22. B. Cong, J. Ding and S. W. Williams: ‘Effect of arc mode in cold metal transfer process on porosity of additively manufactured Al– $6.3\\%\\mathrm{Cu}$ alloy’, Int. J. Adv. Manuf. Technol., 2015, 76, 1593–1606. \n23. J. Gu, B. Cong, J. Ding, S. W. Williams and Y. Zhai: ‘Wire $+$ arc additive manufacturing of aluminium’, Proc. 25th Int. Solid Freeform Fabrication Symp., August 2014, University of Texas, 451–458. \n24. J. Ding, P. A. Colegrove, J. Mehnen, S. Ganguly, P. M. Sequeira Almeida, F. Wang and S. W. Williams: ‘Thermo-mechanical analysis of wire and arc additive layer manufacturing process on large multi-layer parts’, Comput. Mater Sci., 2011, 50, (12), 3315–3322. \n25. P. A. Colegrove, F. Martina, M. J. Roy, B. Szost, S. Terzi, S. W. Williams, P. J. Withers and D. Jarvis: ‘High pressure interpass rolling of wire $^+$ arc additively manufactured titanium components’, Adv. Mater. Res., 2014, 996, 694–700. \n26. P. Kazanas, P. Deherkar, P. Almeida, H. Lockett and S. Williams: ‘Fabrication of geometrical features using wire and arc additive manufacture’, Proc. IMechEng B, 2012, 226B, (6), 1042–1051. \n27. P. A. Colegrove, J. Ding, M. Benke and H. E. Coules: ‘Application of high-pressure rolling to a friction stir welded aerospace panel’, Mater. Modell. Ser., 2012, 10, 691–702. \n28. F. Martina, M. J. Roy, P. A. Colegrove and S. W. Williams: ‘Residual stress reduction in high pressure interpass rolled wire $+$ arc additive manufacturing Ti–6Al–4V components’, Proc. 25th Int. Solid Freeform Fabrication Symp., August 2014, University of Texas, 89–94. \n29. S. D. Sharples, M. Clark and M. G. Somekh: ‘Spatially resolved acoustic spectroscopy for fast noncontact imaging of material microstructure’, Opt. Express, 2006, 14, (22), 10435–10440. \n30. J. Pandremenos, C. Doukas, P. Stavropoulos and G. Chryssolouris: ‘Machining with robots: a critical review’, Proc. DET2011, Athens, Greece, September 2011, University of Patras, 614–621. " + }, + { + "id": "10.1038_ncomms10602", + "DOI": "10.1038/ncomms10602", + "DOI Link": "http://dx.doi.org/10.1038/ncomms10602", + "Relative Dir Path": "mds/10.1038_ncomms10602", + "Article Title": "Exceptional damage-tolerance of a medium-entropy alloy CrCoNi at cryogenic temperatures", + "Authors": "Gludovatz, B; Hohenwarter, A; Thurston, KVS; Bei, HB; Wu, ZG; George, EP; Ritchie, RO", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "High-entropy alloys are an intriguing new class of metallic materials that derive their properties from being multi-element systems that can crystallize as a single phase, despite containing high concentrations of five or more elements with different crystal structures. Here we examine an equiatomic medium-entropy alloy containing only three elements, CrCoNi, as a single-phase face-centred cubic solid solution, which displays strength-toughness properties that exceed those of all high-entropy alloys and most multi-phase alloys. At room temperature, the alloy shows tensile strengths of almost 1 GPa, failure strains of similar to 70% and K-JIc fracture-toughness values above 200 MPa m(1/2); at cryogenic temperatures strength, ductility and toughness of the CrCoNi alloy improve to strength levels above 1.3 GPa, failure strains up to 90% and K-JIc values of 275 MPa m(1/2). Such properties appear to result from continuous steady strain hardening, which acts to suppress plastic instability, resulting from pronounced dislocation activity and deformation-induced nullo-twinning.", + "Times Cited, WoS Core": 1416, + "Times Cited, All Databases": 1498, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000371019700020", + "Markdown": "# Exceptional damage-tolerance of a mediumentropy alloy CrCoNi at cryogenic temperatures \n\nBernd Gludovatz1, Anton Hohenwarter2, Keli V.S. Thurston1,3, Hongbin Bei4, Zhenggang Wu5, Easo P. George4,5,w & Robert O. Ritchie1,3 \n\nHigh-entropy alloys are an intriguing new class of metallic materials that derive their properties from being multi-element systems that can crystallize as a single phase, despite containing high concentrations of five or more elements with different crystal structures. Here we examine an equiatomic medium-entropy alloy containing only three elements, CrCoNi, as a single-phase face-centred cubic solid solution, which displays strength-toughness properties that exceed those of all high-entropy alloys and most multi-phase alloys. At room temperature, the alloy shows tensile strengths of almost $\\mathsf{1G P a},$ failure strains of $\\sim70\\%$ and $K_{\\mathrm{Jlc}}$ fracture-toughness values above $200M\\mathsf{P a}\\mathsf{m}^{1/2},$ ; at cryogenic temperatures strength, ductility and toughness of the CrCoNi alloy improve to strength levels above $1.3\\mathsf{G P a}$ failure strains up to $90\\%$ and $K_{\\mathrm{Jlc}}$ values of $275\\mathsf{M P a}\\mathsf{m}^{1/2}$ . Such properties appear to result from continuous steady strain hardening, which acts to suppress plastic instability, resulting from pronounced dislocation activity and deformation-induced nano-twinning. \n\nEavqlaulrioiayotsuosmolyri csomhmuilpgtioh-s-cieotinmotrnpoaopllny nacltlomyseptl(aelHxlEcaAllmso)a,ytse,m iuhalaltsiv,-ecoegfmenrpreoernadteetndot considerable excitement in the materials science community of late as a new class of materials that derive their properties not from a single dominant constituent, such as iron in steels, but rather from multiple principal elements with the potential for unique combinations of mechanical properties compared with conventional alloys1–19. Much of the interest is predicated on the belief that many new alloys with useful properties are likely to be discovered near the centres (as opposed to the corners) of phase diagrams in compositionally complex systems17. \n\nOne of the extensively investigated high-entropy alloys, an equiatomic, face-centred cubic (fcc) metallic alloy comprising five transition elements, Cr, Mn Fe, Co and $\\mathrm{Ni,}$ was introduced in 2004 (ref. 1), although it was not for a decade that its mechanical properties were first systematically characterized6–8,13–15. CrMnFeCoNi (often termed the Cantor alloy1) displays strongly temperature-dependent strength and ductility with only a small strain-rate dependence6,7. Furthermore, between room temperature and $77\\mathrm{K},$ the alloy displays fracture toughness, $K_{\\mathrm{JIc}},$ values at crack initiation that remain well above $2\\bar{0}0\\mathrm{MPa}\\mathrm{m}^{1/2}$ associated with an increase in tensile strength $(763\\to1,280\\mathrm{MPa})$ ) and ductility $\\langle0.5\\to0.7\\rangle$ ), making it not simply an ideal material for cryogenic applications but putting it among the most damage-tolerant materials in that temperature range8. \n\nAlthough this excellent combination of properties can be related to progressively increasing strain hardening with hardening exponents above 0.4 (refs 7,8), it remains unclear why this particular combination of elements with very different crystal structures produces a single-phase microstructure7,10–12,20,21, whereas many others with comparable configurational entropies do not5. In fact, a relatively small number of the reported multi-element high-entropy alloys are simple solid solutions22. Cantor et al.1 produced an alloy with 20 elements in equal atomic ratios that crystallized as a very brittle multi-phase microstructure indicating that high configurational entropy by itself is unable to suppress the formation of intermetallic phases comprising the constituent elements. As pointed out recently16, while the equiatomic composition maximizes configurational entropy, it does not necessarily minimize the total Gibbs free energy of a multi-component solid solution, and increasing the number of constituent elements could actually lead to the formation of undesirable intermetallic phases. Clearly, it is the nature of the alloying elements and not just their sheer number that is relevant. However, there is also a question of the role of high configurational entropy in these materials with respect to properties, particularly how such high-entropy alloys compare with other equiatomic multi-element systems. Here we examine a variant of the single-phase CrMnFeCoNi high-entropy alloy in which two of the elements have been removed. The resulting CrCoNi alloy, an equiatomic ‘medium-entropy alloy’ (MEA), has a single-phase, fcc crystal structure23, whose uniaxial tensile properties have recently been reported24. The experimental results (X-ray diffraction and backscattered electron, BSE, images)23 are consistent with the CrCoNi ternary phase diagrams25, which indicate that the equiatomic composition is a single-phase solid solution at elevated temperatures. (XRD and BSE analyses of the five-component CrMnFeCoNi alloy after casting and homogenization5 showed that it too is single-phase fcc and remains so after recrystallization when examined by transmission electron microscopy7. In addition, threedimensional atom probe tomography on the five-component CrMnFeCoNi alloy in the cast/homogenized state21 and after severe plastic deformation20 have shown that it retains its true single-phase character at the much finer atomic scale. \n\nSignificantly, we find here that the fracture toughness properties of the three-component CrCoNi MEA are even better than those of the five-component CrMnFeCoNi HEA, and are further enhanced with decrease in temperature between 293 and $77\\mathrm{K}.$ . making it one of the toughest metallic materials reported to date. \n\n# Results \n\nMicrostructure. The CrCoNi MEA was produced from high-purity elements $(>99.9\\%$ pure) which were arc-melted under argon atmosphere and drop-cast into rectangular cross-section copper moulds followed by cold forging and cross rolling at room temperature into sheets of roughly $10\\mathrm{mm}$ thickness (Fig. 1a). Following recrystallization, optical microscopy (Fig. 1b), scanning electron microscopy (SEM) (Fig. 1c) and electron back-scattered diffraction (EBSD; Fig. 1d) images taken from the cross-section of the sheets revealed an equiaxed grain structure with a variable grain size of $5\\mathrm{-}50\\upmu\\mathrm{m}$ and numerous recrystallization twins (inset of Fig. 1c); the equiatomic elemental distribution of the alloy can be seen from energy-dispersive X-ray (EDX) spectroscopy in Fig. 1e. Uniaxial tensile specimens and compact-tension C(T) fracture-toughness specimens were cut from the sheets using electrical discharge machining; the $\\mathrm{{C(T)}}$ samples were fatigue precracked and subsequently side-grooved, in general accordance with ASTM standard E1820 (ref. 26). \n\nStrength and ductility. Using uniaxial, dog-bone-shaped tensile specimen, we measured stress–strain curves at room temperature (293 K), in a mixture of dry ice and ethanol (198 K), and in liquid nitrogen (77 K). Results in Fig. 2a show a $\\sim50\\%$ increase in both yield strength, $\\sigma_{\\mathrm{y}},$ and ultimate tensile strength, $\\sigma_{\\mathrm{UTS}}$ , with decreasing temperature to values of $\\sigma_{\\mathrm{y}}{=}657\\mathrm{MPa}$ and $\\sigma_{\\mathrm{UTS}}=1,311$ MPa at $77\\mathrm{K}.$ The tensile ductility (strain to failure, $\\varepsilon_{\\mathrm{f}})$ similarly increased by $\\sim25\\%$ to $\\sim0.9$ , leading to an increase in fracture energy of more than $80\\%$ , associated with a high strain-hardening exponent, $n$ of 0.4. (Note that compared with pure Ni, this material displays both higher strain hardening and higher elongation to failure24, consistent with the widely accepted Considere’s criterion that higher work-hardening ability promotes ductility by postponing plastic (geometric) instability.) \n\nThe yield strength of this alloy is not particularly high, although it does significantly strain harden to give lowtemperature tensile strengths above 1 GPa. However, as discussed below, its outstanding characteristic is a combination of high strength, ductility and especially fracture toughness which is enhanced significantly at cryogenic temperatures. This refers to its damage tolerance which is invariably the most important property for the application of a structural material. \n\nFracture toughness. To assess the fracture toughness of the CrCoNi alloy and account for both the elastic and extensive plastic contributions involved in the deformation process and during crack growth, we applied nonlinear-elastic fracture mechanics analysis to determine $J$ -based crack-resistance curves, that is, $J_{\\mathrm{R}}$ as a function of crack extension $\\Delta a,$ as shown in Fig. 2b. At room temperature, our $\\mathrm{{C(T)}}$ specimens show fracture toughness, $J,$ values in excess of $200\\mathrm{kJ}\\mathrm{m}^{-2}$ at crack initiation, which increased to above $400\\mathrm{kJ}\\mathrm{m}^{-2}$ with crack extensions of slightly more than $2\\mathrm{mm}$ , the maximum extent of cracking permitted for this geometry by ASTM standards26. Despite the much higher strength at lower temperatures, at $77\\mathrm{K}$ the critical $J$ increased even further to above $350\\mathrm{kJ}\\mathrm{m}^{-2}$ at crack initiation and to almost $950\\mathrm{kJ}\\mathrm{m}^{-2}$ at full extension of the crack. Given that the requirements for $J.$ -dominant conditions, that is, $b_{.}$ , $B>>10$ (J per $\\sigma_{\\mathrm{flow}})$ , where $b$ is the uncracked ligament width (sample width, $W-a)$ , $B$ the sample thickness and $\\sigma_{\\mathrm{flow}}$ the flow stress $(\\sigma_{\\mathrm{flow}}=(\\sigma_{\\mathrm{y}}+\\sigma_{\\mathrm{UTS}})/2)$ , were met, the standard $J{-}K$ equivalence (mode I) relationship, $K_{\\mathrm{J}}=(J\\ E^{\\prime})^{1/2}$ , was used to determine stress-intensity $K$ values corresponding to these measured $J$ toughnesses. (Here, $E^{\\prime}=E,$ the Young’s modulus in plane stress and $E/(1-\\nu^{2})$ in plane strain, $\\nu$ is the Poisson’s ratio, where values of $E$ and $\\nu$ were determined at each temperature using resonance ultrasound spectroscopy methods described elsewhere27.) Fracture toughnesses for the CrCoNi alloy, defined at crack initiation, were strictly valid by ASTM Standard E1820 (ref. 26), with measured $K_{\\mathrm{JIc}},$ values of $208\\mathrm{MPa}\\mathrm{m}^{1/2}\\quad(J_{\\mathrm{t}c}=212\\mathrm{kJ}\\mathrm{m}^{-2}$ at $293\\mathrm{K}$ increasing to 273 MPa m1/2 $(J_{\\mathrm{Ic}}=363\\mathrm{kJ}\\mathrm{m}^{-2})$ at 77 K. ASTM valid crack-growth toughnesses, defined at $\\Delta a\\sim2\\mathrm{mm}.$ , were significantly higher with critical stress-intensity values above ${\\sim}290\\mathrm{MPa}\\mathrm{m}^{1/2}(J{\\sim}400\\mathrm{kJ}\\mathrm{m}^{-2})$ at $293\\mathrm{K}.$ rising up to ${\\sim}430\\mathrm{MPa}\\mathrm{m}^{1/2}$ $(J\\sim900\\mathrm{kJ}\\mathrm{m}^{-2})$ at 77 K. \n\n![](images/aa4279116235d003e4557a5b3e8a205d276059241cad91560791e3b8a569d611.jpg) \nFigure 1 | Processing and microstructure of the medium-entropy alloy CrCoNi. (a) The material was processed by arc melting, drop casting, forging and rolling into sheets of roughly $10\\mathsf{m m}$ thickness from which samples for cross-sectional analysis, tensile tests and fracture toughness tests were machined. (b) Optical microscopy image shows the varying degree of deformation through the thickness of the sheets. (c) Scanning electron microscopy images reveal the non-uniform grain size of the material resulting from the deformation gradients, equiaxed grains and numerous annealing twins after recrystallization (inset). (d) Grain maps from electron back-scatter diffraction scans confirm the varying grain size and show the fully recrystallized microstructure. (e) Energy-dispersive X-ray spectroscopy verifies the equiatomic character of the alloy. The scale bars in b,c and the inset of c and ${\\bf d}$ are $1\\mathsf{m m}$ , $200\\upmu\\mathrm{m}$ , $20\\upmu\\mathrm{m}$ and ${150\\upmu\\mathrm{m}}$ , respectively. \n\nDeformation and failure mechanisms. The extremely high fracture toughness values of the CrCoNi alloy (Fig. 2) are associated with fully ductile fracture, with a pronounced stretch-zone at crack initiation (Fig. 2c) and failure by microvoid coalescence (Fig. 2d). The volume fraction of the void-initiating inclusions was lower than in the five-component CrMnFeCoNi alloy8, which is partly an effect of removing Mn that is known to increase the number of inclusions6. The particles here were analysed by EDX spectroscopy and found to be $\\mathrm{Cr}$ -rich (insets of Fig. 2d), whereas in the five-component HEA, both Cr and Mn-rich particles were found8. In both alloys, we believe that these particles are oxide inclusions that typically form when alloys containing reactive elements are melted. Consistent with this, a recent study identified $\\mathrm{MnCr}_{2}\\mathrm{O}_{4}$ oxide particles in an induction melted CrMnFeCoNi HEA by EDX analysis28. To quantify their effects on ductility and fracture, further studies are needed in the future that would accurately determine the relative volume fractions of the void-initiating inclusions in the MEA and HEA and identify their chemistry and crystal structure by TEM after extraction from the voids. \n\nWhile the yield strength and $K_{\\mathrm{JIc}}$ fracture toughness of the medium-entropy $\\mathrm{CrCoNi}$ and high-entropy CrMnFeCoNi alloys are comparable, the tensile strengths, tensile ductility and work of fracture of the CrCoNi alloy are significantly higher, by respectively $\\sim15,\\ \\sim30$ and $\\sim50\\%$ , at room temperature. At cryogenic temperatures, the strengths of the two alloys are comparable $(\\sigma_{\\mathrm{UTS}}\\sim1,300\\mathrm{MPa}$ at $77\\mathrm{K})$ , but the $K_{\\mathrm{JIc}}$ fracture toughness, tensile ductility and work of fracture are again markedly higher in the CrCoNi alloy, by $\\sim25,\\ \\sim27$ and $\\sim31\\%$ , respectively. The yield strength, $\\sigma_{\\mathrm{y}},$ at $77\\mathrm{K}$ is slightly below that of the CrMnFeCoNi alloy, which we believe is due to the non-uniform grain size of our present material (Fig. 1b–d). Consistent with this notion, in a previous study where the grain size of CrCoNi was uniform and comparable to that of the CrMnFeCoNi alloy, the tensile properties of the three-component alloy were found to exceed those of the five-component alloy at all temperatures24. \n\n# Discussion \n\nTo seek the origins of such strength, ductility and fracture resistance between 293 and $77\\mathrm{K}.$ we conducted detailed SEM analysis of the vicinity of the propagated crack; this was performed on samples sliced in two through the thickness to ensure that deformation conditions had been in fully plane strain (Fig. 3a). The EBSD scans taken in the wake of the propagated crack of a sample tested at $293\\mathrm{K}$ (Fig. 3b), ahead of the crack tip of a sample tested at 198 K (Fig. 3c) and at a crack flank of a sample tested at $77\\mathrm{K}$ (Fig. 3d) show grain misorientations as gradual changes in colour within individual grains indicative of significant amounts of dislocation plasticity. Similarly, back-scattered electron (BSE) scans taken on specimens fractured at room (Fig. 3b) and cryogenic temperatures (Fig. 3d) show the formation of pronounced dislocation cell structures akin to the five-component CrMnFeCoNi HEA where dislocation motion is associated with glide of $\\scriptstyle1/_{2}<110>$ dislocations on $\\{111\\}$ planes7, a typical deformation mechanism for fcc materials, which we presume also occurs in our three-component CrCoNi MEA. In addition, the EBSD scans show a few recrystallization twins in all samples (approximately one or two per grain) as well as the presence of deformation-induced nano-twins at $77\\mathrm{K}$ (Fig. 3d). The BSE images, however, clearly reveal that deformation-induced nano-twinning is a dominant deformation mechanism occurring initially at room temperature but with increasing intensity at 198 and 77 K. From the images in Fig. 3, the nano-twins in the EBSD scans become very clear by overlaying the scan on an image quality, IQ, map of the same data set, which permits the measurement of the typical misorientation angle of ${60}^{\\circ}$ for twinning (Fig. 3e). We conclude from these results that between room and cryogenic temperatures where the strength, ductility and toughness of the mediumentropy $\\mathrm{CrCoNi}$ are all simultaneously enhanced, nano-twinning contributes an important additional deformation mode that helps alleviate the deleterious effects of high strength that would normally be expected to result in lower toughness29. \n\n![](images/a45ecf00c4076eb012a0aedcd8bb4b7178895c0082d240d53406da28d024a426.jpg) \nFigure 2 | Mechanical properties and failure characteristics of the CrCoNi medium-entropy alloy. (a) Tensile tests show a significant increase in yield strength, $\\sigma_{\\mathrm{y\\prime}}$ ultimate tensile strength, sUTS and strain to failure, $\\delta{\\sf f},$ with decreasing temperature from room temperature, $293\\mathsf{K},$ to cryogenic temperatures, 198 and 77 K. In the same temperature range, the work of fracture increases from $3.5\\mathsf{M J}\\mathsf{m}^{-2}$ to $6.4\\mathsf{M J}\\mathsf{m}^{-2}$ $(\\pmb{6})$ Fracture toughness tests on compacttension, C(T), specimens show an increasing fracture resistance with crack extension and crack initiation, $K_{\\mathrm{Jlc}},$ values of 208, 265 and $273\\mathsf{M P a m}^{1/2}$ at 293, 198 and $77\\mathsf{K},$ respectively. (c) Stereo microscopy and scanning electron microscopy images show a clear transition from the notch to the pre-crack and a pronounced stretch-zone between the pre-crack and the fully ductile fracture region of a sample that was tested at $198\\mathsf{K}$ (d) The fracture surface shows ductile dimpled fracture and Cr-rich particles that act as void initiation sides. (Data points shown are mean $\\pm{\\sf s.d}$ ; see Supplementary Table 1 for exact values.) The scale bars in c and d, and the insets of d are 75, 5 and $2\\upmu\\mathrm{m}.$ , respectively. \n\nWe did not observe deformation nano-twinning at room temperature in the five-component alloy, where deformation at $293{\\mathrm{\\bar{K}}}$ is solely carried by dislocation $\\mathrm{slip}^{7,8}$ , specifically, involving the rapid movement of partial dislocations and the much slower planar slip of undissociated dislocations30, although as with the present three-component alloy, twinning became a major deformation mode at $77\\mathrm{K}$ . We believe that the earlier onset of deformation nano-twinning is key to the exceptional damage-tolerance of this medium-entropy alloy. Although in most materials the achievement of strength and toughness is invariably a compromise29—high strength is often associated with lower toughness and vice versa—it has become increasingly apparent that the presence of twinning as the dominant deformation mechanism serves to ‘defeat this conflict’, specifically by providing a steady source of strain hardening, which promotes ductility by delaying the onset of plastic instability by necking, and an additional deformation mode besides dislocation plasticity to accommodate the imposed strain. In addition to the high- and medium-entropy alloys, there are now several other materials known to benefit from twinning, including copper thin films31–34 and $11-15\\mathrm{wt}.\\%$ (Hadfield) Mn-steels (used in the mining industry for rock crushers because of their hardness and fracture resistance) and their modern variant known as twinning-induced plasticity steels35–42, which have application in the automobile industry. \n\n![](images/f68d68818c7c2adde5e81901bcb133e7f5014d5534b5d129139530943be7b9fc.jpg) \nFigure 3 | Deformation mechanisms in CrCoNi between 293 and 77 K. (a) After testing, some samples were sliced in two along the half-thickness mid-plane, and the crack-tip regions in the centre of the samples (plane strain) were investigated in the scanning electron microscope using back-scattered electrons (BSE) and electron-backscatter diffraction (EBSD). (b) EBSD scans in the wake of the propagated crack of a sample tested at room temperature show a few recrystallization twins and grain misorientations indicative of dislocation plasticity whereas BSE scans reveal cell formation and nano-twinning as additional deformation mechanism. (c) Similar to room temperature behaviour, EBSD scans of samples tested at $198\\mathsf{K}$ show recrystallization twins and misorientations indicative of dislocation plasticity ahead of the propagated crack-tip. (d) Samples tested at $77\\mathsf{K}$ show pronounced nano-twinning and the formation of dislocation cells (BSE), whereas EBSD scans reveal dislocation plasticity in the form of grain misorientations, some recrystallization twins and deformation induced nano-twins. (e) An arbitrarily chosen path on an EBSD image overlaid on an image quality (IQ) map shows $60^{\\circ}$ misorientations typical for the character of such deformation twins. (The IQ map measures the quality of the collected EBSD patterns and is often used to visualize microstructural features.) The scale bars of the BSE image, the EBSD image and the inset of the EBSD image in b are 5, 75 and $25\\upmu\\mathrm{m},$ respectively; the ones of the EBSD image and its inset in c are 50 and $10\\upmu\\mathrm{m}$ , respectively. The BSE image and its corresponding inset, and the EBSD image and its inset have scale bars of 10, 5, 200 and $15\\upmu\\mathrm{m}.$ , respectively. The scale bar in e is $15\\upmu\\mathrm{m}$ . \n\nThe current medium-entropy CrCoNi alloy, however, appears to optimize these features to achieve literally unparalleled mechanical performance at low temperatures. Although solid-solution hardening provides the ideal hardening mechanism for cryogenic use, the increasing role of nano-twinning with decreasing temperature, as is evident from the apparently denser network of nano-twins at $77\\mathrm{K}$ (inset in Fig. 3d) compared with room temperature (Fig. 2b), acts to progressively further enhance damage-tolerance (strength, ductility and toughness) with decreasing temperature, to achieve extremely high strainhardening exponents on the order of 0.4. \n\nSuch damage-tolerant properties of the CrCoNi mediumentropy alloy are literally unprecedented for mechanical behaviour at cryogenic temperatures. For a material with a tensile strength of $\\mathrm{1.3GPa}$ to display ductilities (failure strains) of \n\n$90\\%$ , and ‘valid’ crack-growth fracture toughnesses that exceeds $430\\mathrm{MPa}\\mathrm{m}^{1/2}$ , all at liquid-nitrogen temperatures, is exceptional and clearly exceed the excellent cryogenic properties of our previously reported CrMnFeCoNi high-entropy alloy8. Its ductility compares favourably to high-Mn twinning-induced plasticity steels35–42 and strength and toughness are comparable to the very best cryogenic steels, for example, certain austenitic stainless steels43–47 and high-Ni steels48–51; in addition, the strength, ductility and toughness of the CrCoNi alloy exceed the properties of all medium- and high-entropy alloys reported to date (Fig. 4). Moreover, with a uniformly fine grain size, it is eminently feasible that the strength, ductility and toughness properties of this CrCoNi alloy may further improve. \n\nWith respect to high-entropy alloys in general, by comparing the CrCoNi and CrMnFeCoNi alloys, the current work does lend credence to our belief that it is the nature of elements in complex solid solutions that is more important than their mere number. Indeed, in terms of (valid) crack-initiation and crack-growth toughnesses, the CrCoNi medium-entropy alloy represents one of the toughest materials in any materials class ever reported. \n\n# Methods \n\nMaterials processing and microstructural characterization. The CrCoNi MEA was produced from high-purity elements $(>99.9\\%$ pure), which were arc-melted under argon atmosphere and drop-cast into rectangular cross-section copper moulds measuring $25.4\\times19.1\\times127\\mathrm{mm}$ . The ingots were homogenized at $1{,}200^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ in vacuum, cut in half length-wise and then cold-forged and cross-rolled at room temperature along the side that is $25.4\\mathrm{mm}$ to a final thickness of $\\sim10\\mathrm{mm}$ , as shown in Fig. 1a (total reduction in thickness of $\\sim60\\%$ ). Each piece was subsequently annealed at $800^{\\circ}\\mathrm{C}$ for $^{\\textrm{\\scriptsize1h}}$ in air leading to sheets with a fully recrystallized microstructure consisting of equiaxed grains $\\sim5\\mathrm{-}50\\upmu\\mathrm{m}$ in size. \n\n![](images/81405f26250087eac8c33a84fec567febcd0e42b6ff68ec1df38dc47ad8e5b9e.jpg) \nFigure 4 | Ashby map of fracture toughness versus yield strength for various classes of materials. The investigated medium-entropy alloy CrCoNi compares favourably with materials classes like metals and alloys and metallic glasses. Its combination of strength and toughness (that is damage tolerance) is comparable to cryogenic steels, for example, certain austenitic stainless steels $43-47$ and high-Ni steels48–51, and exceeds all high- and medium-entropy alloys reported to date. \n\nTo analyse the microstructure of the material after processing, two pieces were cut from the recrystallized sheets perpendicular to the rolling direction, embedded in conductive resin and metallographically polished in stages to a final surface finish of $0.04\\upmu\\mathrm{m}$ using colloidal silica. For optical microscopy analysis, one polished surface was chemically etched using a standard solution for austenitic steels $\\mathrm{'10mlH_{2}O}$ , 1 ml ${\\mathrm{HNO}}_{3}.$ , $5\\mathrm{ml}$ HCl and $\\begin{array}{r}{1\\mathrm{g}\\mathrm{FeCl}_{3},}\\end{array}$ ; the other was analysed as is in an LEO (Zeiss) 1525 FE-SEM (Carl Zeiss, Oberkochen, Germany) scanning electron microscope (SEM) operated at $20\\mathrm{kV}$ in the back-scattered electron mode. \n\nMechanical characterization. Rectangular dog-bone-shaped tensile specimens with a gauge length of $12.7\\mathrm{mm}$ were machined from the recrystallized sheets by electrical discharge machining. Both sides of the specimen were ground using SiC paper resulting in a final thickness of $\\sim1.5\\mathrm{{mm}}$ and a gauge width of $\\sim3.0\\mathrm{mm}$ . The gauge length was marked with Vickers microhardness indents $\\left(300\\mathrm{g}\\right.$ load) to enable elongations to be measured after fracture using a Nikon travelling microscope. Tensile tests were performed at an engineering strain rate of $10^{-3}{\\mathsf{s}}^{-1}$ in a screw-driven Instron $^{4,204}$ load frame. Groups of four samples were tested at three different temperatures $(N=12)$ ); at room temperature (293 K), in a bath of dry ice and ethanol (198 K), and in a bath of liquid nitrogen (77 K). \n\nThe elongation of the gauge length of each sample was measured after testing, and engineering stress–strain curves were calculated from the load-displacement data. Yield strength, $\\sigma_{\\mathrm{y}},$ ultimate tensile strength, ${\\sigma}_{\\mathrm{u}},$ and elongation to failure, $\\varepsilon_{\\mathrm{f}},$ were determined from the uniaxial tensile stress–strain curves and are shown in Supplementary Table 1 as mean $\\pm\\:s.\\mathrm{d}$ . for each set of tests at the individual temperatures. True stress–strain curves were calculated from the engineering stress–strain curves and strain-hardening exponents, $n$ , were determined for each temperature based on the constitutive law $\\sigma\\bar{=}\\kappa\\varepsilon^{n}$ , where $\\sigma$ and e are, respectively, the true stress and plastic strain, $k$ is a scaling constant and $n$ the strain-hardening exponent; $n$ values are also listed in Supplementary Table 1. \n\nNine $(N=9)$ ) compact-tension $\\mathrm{{C(T)}}$ specimens, of nominal width $W{=}18\\mathrm{mm}$ and thickness $B{=}9\\mathrm{mm}$ , were prepared in strict accordance with ASTM standard E1820 (ref. 26) using electrical discharge machining (EDM). Notches, $6.6\\mathrm{mm}$ in length with notch root radii of $\\sim100\\upmu\\mathrm{m}.$ , were cut using EDM; before precracking, the faces of all samples were metallographically ground and polished in stages to a final $1\\upmu\\mathrm{m}$ surface finish to allow accurate crack-length measurements using optical microscopy. All the samples were fatigue pre-cracked and tested using an electroservo-hydraulic MTS 810 load frame (MTS Corporation, Eden Prairie, MN, USA) controlled by an Instron 8800 digital controller (Instron Corporation, \n\nNorwood, MA, USA). Fatigue pre-cracks were created under load control (tension–tension loading) at a stress intensity range of $\\Delta K{=}K_{\\operatorname*{max}}{-}K_{\\operatorname*{min}}$ of $15\\mathrm{{MPam}^{1/2}}$ and a constant frequency of $10\\mathrm{{Hz}}$ (sine wave) with a load ratio $R=0.1$ , where $R$ is the ratio of minimum to maximum applied load. During pre-cracking, the crack length was optically checked from both sides of the sample to ensure a straight crack front with crack extension monitored using an Epsilon clip gauge of $3\\mathrm{mm}$ $(-1/+2.5\\mathrm{mm})$ gauge length (Epsilon Technology, Jackson, WY, USA) mounted at the load-line of the sample; final crack lengths, a were in the range of $8.1\\mathrm{-}12.6\\mathrm{mm}$ $(a/W{\\sim}0.45{-}0.7)$ and thus were well above the ASTM standard’s minimum length requirement for a pre-crack of $1.3\\mathrm{mm}$ To improve the constraint conditions at the crack tip during testing, all the samples were sidegrooved using EDM to depths of $\\sim1\\mathrm{mm}$ , which resulted in a net sample thickness of $B_{\\mathrm{N}}{\\sim}7\\mathrm{mm}$ ; this reduction in thickness did not exceed $20\\mathrm{-}25\\%$ , as mandated by ASTM Standard E1820 (ref. 26). \n\nNonlinear-elastic fracture mechanics methodologies were used to incorporate both the elastic and inelastic contributions to the measurement of the fracture toughness; specifically, the change in crack resistance with crack extension, that is, crack-resistance curve ( $R$ -curve) behaviour, was characterized in terms of the $J.$ -integral as a function of crack growth at three different temperatures: 293, 198 and $77\\mathrm{K}$ . The samples were tested under displacement control at a constant displacement rate of $2\\mathrm{mm}\\mathrm{min}^{-1}$ . The onset of cracking as well as subsequent subcritical crack growth were determined by periodically unloading the sample ( $\\cdot\\sim20\\%$ of the peak-load) to record the elastic unloading compliance using an Epsilon clip gauge of $3\\mathrm{{mm}(-1/+7\\mathrm{{mm})}}$ gauge length (Epsilon Technology, Jackson, WY, USA) mounted in the load-line of the sample. Crack lengths, $a_{i}$ were calculated from the compliance data obtained during the test using the compliance expression of a C(T) sample at the load-line : \n\n$$\na_{1}/W=1.000196-4.06319u+11.242u^{2}-106.043u^{3}+464.335u^{4}-650.677u^{5},\n$$ \n\nwhere \n\n$$\nu=\\frac{1}{\\left[B_{e}E C_{c\\mathrm{(i)}}\\right]^{1/2}+1}.\n$$ \n\n$C_{\\mathrm{c(i)}}$ is the rotation-corrected, elastic unloading compliance and $B_{e}$ the effective sample thickness of a side-grooved sample calculated as $B_{\\mathrm{e}}=B-\\dot{(}B-B_{\\mathrm{N}})^{2}/B$ . (Initial and final crack lengths were additionally verified by post-test optical measurements.) For each crack length data point, $a_{\\mathrm{i}},$ the corresponding $J_{\\mathrm{i}}$ -integral was computed as the sum of elastic, $J_{\\mathrm{{el}\\mathrm{{\\(i)}}}}$ and plastic components, $J_{\\mathrm{{pl}\\ (i)}}$ , such that the $J$ -integral can be written as follows: \n\n$$\nJ_{\\mathrm{i}}=K_{\\mathrm{i}}^{2}/E^{\\prime}+J_{\\mathrm{pl(i)}},\n$$ \n\nwhere $E^{\\prime}=E_{\\mathrm{{;}}}$ the Young’s modulus, in plane stress and $E/(1-\\nu^{2})$ in plane strain; $\\nu$ \n\nis Poisson’s ratio. $K_{\\mathrm{i}},$ the linear elastic stress intensity corresponding to each data point on the load-displacement curve, was calculated for the C(T) geometry from: \n\n$$\nK_{\\mathrm{i}}={\\frac{P_{\\mathrm{i}}}{(B B_{N}W)^{1/2}}}f(a_{\\mathrm{i}}/W),\n$$ \n\nwhere $P_{\\mathrm{i}}$ is the applied load at each individual data point and $f(a_{\\mathrm{i}}/W)$ is a geometrydependent function of the ratio of crack length, $a_{\\mathrm{i,}}$ to width, $W_{;}$ , as listed in the ASTM standard. The plastic component of $J_{\\mathrm{i}}$ can be calculated from the following equation: \n\n$$\nJ_{\\mathrm{pl(i)}}=\\left[J_{\\mathrm{pl(i-1)}}+\\left(\\frac{\\eta_{\\mathrm{pl(i-1)}}}{b_{\\mathrm{(i-1)}}}\\right)\\frac{A_{\\mathrm{pl(i)}}-A_{\\mathrm{pl(i-1)}}}{B_{N}}\\right]\\left[1-\\gamma_{\\mathrm{(i-1)}}\\left(\\frac{a_{\\mathrm{(i)}}-a_{\\mathrm{(i-1)}}}{b_{\\mathrm{(i-1)}}}\\right)\\right],\n$$ \n\nwhere $\\eta_{\\mathrm{pl\\(i-1)}}=2+0.522\\ b_{\\mathrm{(i-1)}}/W$ and $\\gamma_{\\mathrm{{pl}\\ {(i-1)}}}=1+0.76\\ b_{(\\mathrm{{i-1}})}/W.\\ .$ $A_{\\mathrm{pl}}$ (i) $-A_{\\mathrm{{pl}}\\ \\mathrm{{(i-1)}}}$ is the increment of plastic area underneath the load-displacement curve, and $b_{\\mathrm{i}}$ is the uncracked ligament width (that is, $b_{\\mathrm{i}}=W-a_{\\mathrm{i}})$ . Using this formulation, the value of $J_{\\mathrm{i}}$ can be determined at any point along the loaddisplacement curve and together with the corresponding crack lengths, the $J-\\Delta a$ resistance curve created. (Here, $\\Delta a$ is the difference of the individual crack lengths, $a_{\\mathrm{i}},$ during testing and the initial crack length, $a_{i}$ , after pre-cracking.) \n\nThe intersection of the resistance curve with the $0.2\\mathrm{mm}$ offset/blunting line $\\left(J=2~\\sigma_{0}\\Delta a\\right)$ where $\\sigma_{0}$ is the flow stress) defines a provisional toughness $J_{\\mathrm{Q}},$ which can be considered as a size-independent (valid) fracture toughness, $J_{\\mathrm{Ic}},$ provided the validity requirements for $J$ -field dominance and plane-strain conditions prevail, that is , that $B$ , $b_{0}>10\\ J_{\\mathrm{Q}}/\\sigma_{0},$ where $b_{0}$ is the initial ligament length. The fracture toughness expressed in terms of the stress intensity was then computed using the standard $J-K$ equivalence (mode I) relationship $\\dot{K_{\\mathrm{JIc}}}=(E^{\\prime}J_{\\mathrm{Ic}})^{1/2}$ . Values for $E$ and $\\nu$ at the individual temperatures were determined by resonance ultrasound spectroscopy using the procedure described in Haglund et al.27; at 293, 198 and $77\\mathrm{K},$ Young’s moduli, $E$ of 229, 235 and 241 GPa and Poisson’s ratios, $\\nu$ of 0.31, 0.30 and 0.30 were used, respectively. \n\nTo discern the mechanisms underlying the measured fracture toughness values and investigate the microstructure in the vicinity of the crack tip and wake in the plane-strain region in the interior of the sample after testing, one sample from each of the tested temperatures was sliced in two, each with a thickness of $\\sim B/2$ . For each sample, one half was embedded in conductive resin, progressively polished to a $0.04\\upmu\\mathrm{m}$ surface finish using colloidal silica, and analysed in the SEM in backscattered electron mode as well as by electron back-scatter diffraction, EBSD using a TEAM EDAX analysis system (Ametek EDAX, Mahwah, NJ, USA). \n\nThe remaining ligament of all other samples was cycled to failure at a $\\Delta K$ of ${\\sim}30\\mathrm{MPa}\\mathrm{m}^{1/2}$ , a frequency of $100\\mathrm{Hz}$ (sine wave) and a load ratio $R=0.5$ so that both the initial and the final crack lengths could be optically determined with precision from the change in fracture mode. In addition, the mating fracture surfaces of each sample were examined in the SEM at an accelerating voltage of $20\\mathrm{kV}$ in the secondary electron mode. Particles inside the microvoids of samples tested at 293 and $77\\mathrm{K}$ were analysed using an Energy Dispersive Spectroscopy (EDS) system from Oxford Instruments (Model 7426, Oxford, England). EDS analyses were performed on five randomly chosen particles from samples tested at both room and liquid nitrogen temperature to determine their chemical composition. \n\n# References \n\n1. Cantor, B., Chang, I. T. H., Knight, P. & Vincent, A. J. B. Microstructural development in equiatomic multicomponent alloys. Mater. Sci. Eng. A 375–377, 213–218 (2004). \n2. Yeh, J.-W. et al. Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes. Adv. Eng. Mater. 6, 299–303 (2004). \n3. Hsu, C.-Y., Yeh, J.-W., Chen, S.-K. & Shun, T.-T. Wear resistance and hightemperature compression strength of Fcc CuCoNiCrAl0.5Fe alloy with boron addition. Metall. Mater. Trans. A 35, 1465–1469 (2004). \n4. Senkov, O. N., Wilks, G. B., Scott, J. M. & Miracle, D. B. Mechanical properties of Nb25Mo25Ta25W25 and V20Nb20Mo20Ta20W20 refractory high entropy alloys. Intermetallics 19, 698–706 (2011). \n5. Otto, F., Yang, Y., Bei, H. & George, E. P. Relative effects of enthalpy and entropy on the phase stability of equiatomic high-entropy alloys. Acta Mater. 61, 2628–2638 (2013). \n6. Gali, A. & George, E. P. Tensile properties of high- and medium-entropy alloys. Intermetallics 39, 74–78 (2013). \n7. Otto, F. et al. The influences of temperature and microstructure on the tensile properties of a CoCrFeMnNi high-entropy alloy. Acta Mater. 61, 5743–5755 (2013). \n8. Gludovatz, B. et al. A fracture-resistant high-entropy alloy for cryogenic applications. Science 345, 1153–1158 (2014). \n9. Manzoni, A., Daoud, H., Vo¨lkl, R., Glatzel, U. & Wanderka, N. Phase separation in equiatomic AlCoCrFeNi high-entropy alloy. Ultramicroscopy 132, 212–215 (2013). equiatomic FeMnNiCoCr high-entropy alloy with exceptional phase stability and tensile ductility. Scripta Mater. 72–73, 5–8 (2014). \n11. Tasan, C. C. et al. Composition dependence of phase stability, deformation mechanisms, and mechanical properties of the CoCrFeMnNi high-entropy alloy system. JOM 66, 1993–2001 (2014). \n12. Deng, Y. et al. Design of a twinning-induced plasticity high entropy alloy. Acta Mater. 94, 124–133 (2015). \n13. He, J. Y. et al. Effects of Al addition on structural evolution and tensile properties of the FeCoNiCrMn high-entropy alloy system. Acta Mater. 62, 105–113 (2014). \n14. He, J. Y. et al. Steady state flow of the FeCoNiCrMn high entropy alloy at elevated temperatures. Intermetallics 55, 9–14 (2014). \n15. Stepanov, N. et al. Effect of cryo-deformation on structure and properties of CoCrFeNiMn high-entropy alloy. Intermetallics 59, 8–17 (2015). \n16. Zhang, F. et al. An understanding of high entropy alloys from phase diagram calculations. CALPHAD 45, 1–10 (2014). \n17. Cantor, B. Multicomponent and high entropy alloys. Entropy 16, 4749–4768 (2014). \n18. Senkov, O. N., Senkova, S. V., Woodward, C. & Miracle, D. B. Lowdensity, refractory multi-principal element alloys of the Cr–Nb–Ti–V–Zr system: microstructure and phase analysis. Acta Mater. 61, 1545–1557 (2013). \n19. Miracle, D. B. et al. Exploration and development of high entropy alloys for structural applications. Entropy 16, 494–525 (2013). \n20. Schuh, B. et al. Mechanical properties, microstructure and thermal stability of a nanocrystalline CoCrFeMnNi high-entropy alloy after severe plastic deformation. Acta Mater. 96, 258–268 (2015). \n21. Laurent-Brocq, M. et al. Insights into the phase diagram of the CrMnFeCoNi high entropy alloy. Acta Mater. 88, 355–365 (2015). \n22. Kozak, R., Sologubenko, A. & Steurer, W. Single-phase high-entropy alloys—an overview. Z. Kristallogr. 230, 55–68 (2015). \n23. Wu, Z., Bei, H., Otto, F., Pharr, G. M. & George, E. P. Recovery, recrystallization, grain growth and phase stability of a family of FCC-structured multi-component equiatomic solid solution alloys. Intermetallics 46, 131–140 (2014). \n24. Wu, Z., Bei, H., Pharr, G. M. & George, E. P. Temperature dependence of the mechanical properties of equiatomic solid solution alloys with face-centered cubic crystal structures. Acta Mater. 81, 428–441 (2014). \n25. Kaufman, L. & Nesor, H. Co-Cr-Ni Phase Diagram, ASM Alloy Phase Diagrams Database. (eds Villars, P., Okamoto, H. & Cenzual, K.) http://www1.asminternational.org/AsmEnterprise/APD (ASM International, 2006). \n26. E08 Committee. E1820-13 Standard Test Method for Measurement of Fracture Toughness (ASTM International, 2013). \n27. Haglund, A., Koehler, M., Catoor, D., George, E. P. & Keppens, V. Polycrystalline elastic moduli of a high-entropy alloy at cryogenic temperatures. Intermetallics 58, 62–64 (2015). \n28. Laplanche, G., Horst, O., Otto, F., Eggeler, G. & George, E. P. Microstructural evolution of a CoCrFeMnNi high-entropy alloy after swaging and annealing. J. Alloys Compd. 647, 548–557 (2015). \n29. Ritchie, R. O. The conflicts between strength and toughness. Nat. Mater. 10, 817–822 (2011). \n30. Zhang, Z.-J. et al. Nanoscale origins of the damage tolerance of the highentropy alloy CrMnFeCoNi. Nat. Commun. 6, 10143 (2015). \n31. Dao, M., Lu, L., Shen, Y. F. & Suresh, S. Strength, strain-rate sensitivity and ductility of copper with nanoscale twins. Acta Mater. 54, 5421–5432 (2006). \n32. Lu, L., Chen, X., Huang, X. & Lu, K. Revealing the maximum strength in nanotwinned copper. Science 323, 607–610 (2009). \n33. Lu, K., Lu, L. & Suresh, S. Strengthening materials by engineering coherent internal boundaries at the nanoscale. Science 324, 349–352 (2009). \n34. Singh, A., Tang, L., Dao, M., Lu, L. & Suresh, S. Fracture toughness and fatigue crack growth characteristics of nanotwinned copper. Acta Mater. 59, 2437–2446 (2011). \n35. Hadfield, R. A. Hadfield’s manganese steel. Science 12, 284–286 (1888). \n36. Schumann, V. H. Martensitische Umwandlung in austenitischen ManganKohlenstoff-Sta¨hlen. Neue Hu¨tte 17, 605–609 (1972). \n37. Remy, L. & Pineau, A. Twinning and strain-induced F.C.C. $\\rightarrow$ H.C.P. transformation in the Fe-Mn-Cr-C system. Mater. Sci. Eng. 28, 99–107 (1977). \n38. Kim, T. W. & Kim, Y. G. Properties of austenitic Fe-25Mn-1Al-0.3C alloy for automotive structural applications. Mater. Sci. Eng. A 160, 13–15 (1993). \n39. Gr¨assel, O., Frommeyer, G., Derder, C. & Hofmann, H. Phase transformations and mechanical properties of Fe-Mn-Si-Al TRIP-steels. J. Phys. IV 07, C5–383–C5–388 (1997). \n40. Gr¨assel, O., Kru¨ger, L., Frommeyer, G. & Meyer, L. W. High strength Fe–Mn–(Al, Si) TRIP/TWIP steels development—properties—application. Int. J. Plast. 16, 1391–1409 (2000). \n41. Frommeyer, G., Bru¨x, U. & Neumann, P. Supra-ductile and high-strength manganese-TRIP/TWIP steels for high energy absorption purposes. ISIJ Int. 43, 438–446 (2003). \n42. Chen, L., Zhao, Y. & Qin, X. Some aspects of high manganese twinninginduced plasticity (TWIP) steel, a review. Acta Metall. Sin. Engl. Lett. 26, 1–15 (2013). \n43. Read, D. T. & Reed, R. P. Fracture and strength properties of selected austenitic stainless steels at cryogenic temperatures. Cryogenics 21, 415–417 (1981). \n44. Mills, W. J. Fracture toughness of type 304 and 316 stainless steels and their welds. Int. Mater. Rev. 42, 45–82 (1997). \n45. Sokolov, M. et al. Effects of Radiation on Materials: 20th International Symposium (eds Rosinski, S., Grossbeck, M., Allen, T. & Kumar, A.) 125–147 (ASTM International, 2001). \n46. Shindo, Y. & Horiguchi, K. Cryogenic fracture and adiabatic heating of austenitic stainless steels for superconducting fusion magnets. Sci. Technol. Adv. Mater. 4, 319 (2003). \n47. Sa, J. W. et al. Twenty-First IEEE/NPS Symposium on Fusion Engineering 2005 1–4 (IEEE, 2005). \n48. Strife, J. R. & Passoja, D. E. The effect of heat treatment on microstructure and cryogenic fracture properties in 5Ni and 9Ni steel. Metall. Trans. A 11, 1341–1350 (1980). \n49. Syn, C. K., Morris, J. W. & Jin, S. Cryogenic fracture toughness of 9Ni steel enhanced through grain refinement. Metall. Trans. A 7, 1827–1832 (1976). \n50. Pense, A. W. & Stout, R. D. Fracture toughness and related characteristics of the cryogenic nickel steels. Weld. Res. Counc. Bull 205, 1–43 (1975). \n51. Stout, R. D. & Wiersma, S. J. Advances in Cryogenic Engineering Materials. (eds Reed, R. P. & Clark, A. F.) 389–395 (Springer, 1986). \n\n# Acknowledgements \n\nThis research was sponsored by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, \n\nthrough the Materials Science and Technology Division at the Oak Ridge National Laboratory (for H.B, Z.W. and E.P.G.) and the Mechanical Behavior of Materials Program (KC13) at the Lawrence Berkeley National Laboratory (for B.G., K.V.S.T. and R.O.R.). \n\n# Author contributions \n\nB.G., E.P.G. and R.O.R. designed the research; H.B. and E.P.G. made the alloy; B.G., A.H., K.V.S.T., H.B. and Z.W. mechanically characterized the alloy; B.G., A.H., K.V.S.T., H.B., E.P.G. and R.O.R. analysed and interpreted the data; B.G., E.P.G. and R.O.R. wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Gludovatz, B. et al. Exceptional damage-tolerance of a medium-entropy alloy CrCoNi at cryogenic temperatures. Nat. Commun. 7:10602 doi: 10.1038/ncomms10602 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1039_c6ee01674j", + "DOI": "10.1039/c6ee01674j", + "DOI Link": "http://dx.doi.org/10.1039/c6ee01674j", + "Relative Dir Path": "mds/10.1039_c6ee01674j", + "Article Title": "Transition of lithium growth mechanisms in liquid electrolytes", + "Authors": "Bai, P; Li, J; Brushett, FR; Bazant, MZ", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "Next-generation high-energy batteries will require a rechargeable lithium metal anode, but lithium dendrites tend to form during recharging, causing short-circuit risk and capacity loss, by mechanisms that still remain elusive. Here, we visualize lithium growth in a glass capillary cell and demonstrate a change of mechanism from root-growing mossy lithium to tip-growing dendritic lithium at the onset of electrolyte diffusion limitation. In sandwich cells, we further demonstrate that mossy lithium can be blocked by nulloporous ceramic separators, while dendritic lithium can easily penetrate nullopores and short the cell. Our results imply a fundamental design constraint for metal batteries (Sand's capacity''), which can be increased by using concentrated electrolytes with stiff, permeable, nulloporous separators for improved safety.", + "Times Cited, WoS Core": 1211, + "Times Cited, All Databases": 1330, + "Publication Year": 2016, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000386336200026", + "Markdown": "# Transition of lithium growth mechanisms in liquid electrolytes† \n\nPeng Bai,\\*a Ju Li,bc Fikile R. Brushetta and Martin Z. Bazant\\*ade \n\nReceived 10th June 2016, Accepted 8th August 2016 \n\nDOI: 10.1039/c6ee01674j www.rsc.org/ees \n\nNext-generation high-energy batteries will require a rechargeable lithium metal anode, but lithium dendrites tend to form during recharging, causing short-circuit risk and capacity loss, by mechanisms that still remain elusive. Here, we visualize lithium growth in a glass capillary cell and demonstrate a change of mechanism from root-growing mossy lithium to tip-growing dendritic lithium at the onset of electrolyte diffusion limitation. In sandwich cells, we further demonstrate that mossy lithium can be blocked by nanoporous ceramic separators, while dendritic lithium can easily penetrate nanopores and short the cell. Our results imply a fundamental design constraint for metal batteries (‘‘Sand’s capacity’’), which can be increased by using concentrated electrolytes with stiff, permeable, nanoporous separators for improved safety. \n\n# Broader context \n\nConsumer electronic devices, portable power tools, and electric vehicles have been enabled, but also constrained, by the steady improvement of lithium-ion batteries. To develop batteries with higher energy density, such as $\\mathbf{Li-O}_{2}$ , Li–S, and other Li metal batteries using intercalation cathodes, lithium is believed to be the ideal anode material for its extremely high theoretical specific capacity $(3860~\\mathrm{\\mA~h~g^{-1}})$ , low density $\\left(0.59\\mathrm{~g~cm}^{-3}\\right)$ and the lowest negative electrochemical potential $_{-3.04\\mathrm{~V~}}$ vs. the standard hydrogen electrode). Unfortunately, lithium growth is unstable during battery recharging and leads to rough, mossy deposits, whose fresh surfaces consume the electrolyte to form solid–electrolyte interphase layers, resulting in high internal resistance, low Coulombic efficiency and short cycle life. Finger-like lithium dendrites can also short-circuit the cell by penetrating the porous separator, leading to catastrophic accidents. Controlling such hazardous instabilities requires accurately determining their mechanisms, which are more complex than the well-studied diffusion-limited growth of copper or zinc from aqueous solutions. Such fundamental understanding is critical for the success of the lithium metal anode and could provide guidance for the optimal design and operation of rechargeable lithium metal batteries. \n\n# Introduction \n\nThe lithium metal anode is a key component of future highenergy batteries, such as Li–S and Li– ${\\bf O}_{2}$ batteries,1 for economical and long-range electric vehicles.2 It also holds the promise to reduce the volume and weight of lithium-ion batteries by replacing the standard graphite anode, if lithium dendrites can be safely controlled during recharging to avoid internal shorts and life-threatening accidents.3 While it has been demonstrated that electrolyte additives,4–6 artificial solid electrolyte interphase (SEI) layers,7,8 and increasing the salt concentration in electrolytes,9,10 either alone or in combination, can improve the stability of lithium under small currents4–7 and low capacities,9,11 the challenge of suppressing dendrites at practical currents $\\left(>1\\mathrm{\\mA\\cm}^{-2}\\right)$ ) and areal capacities $(>1\\mathrm{\\mA}\\mathrm{\\h\\cm}^{-2})$ remains a major obstacle for the development of rechargeable lithium metal batteries.8,12 The time is ripe for a thorough investigation of lithium growth mechanisms under these conditions, in order to establish theoretical principles and design constraints for dendrite-free charging. \n\nThe prevailing understanding of lithium growth instability is largely based on the simpler case of aqueous copper electrodeposition,13–17 where dendritic fractal patterns are telltale signs of long-range diffusion-limited growth.18–20 When a current is applied to recharge the battery, cations are consumed by reduction reaction, as anions are expelled by the electric field. In a binary electrolyte, the evolution of neutral salt concentration obeys an effective diffusion equation.21 For currents exceeding diffusion limitation, the salt concentration at the electrode surface decreases to zero at a characteristic time,22,23 and uniform electroplating becomes unstable.13,14,17 This characteristic time, $t_{\\mathrm{Sand}},$ was first derived by Sand in 1901,22 and is now known as ‘‘Sand’s time’’,23 after which the scarce supply of cations preferentially deposits onto surface protrusions, leading to a selfamplifying process of dendritic growth (i.e. tip growth mode) that propagates at the velocity of bulk anion electromigration, in order to preserve electroneutrality.13,17,21,24,25 \n\nAttempts to transfer this understanding from copper to lithium have been inconclusive. In lithium/polymer-electrolyte cells,26–28 the onset time for dendritic growth exhibits similar scaling with current as Sand’s time, but surprisingly, far below the diffusion-limited current.27 In lithium/liquid-electrolyte cells, decreasing the mobility and the transference number of anions by using modified separators can enhance the cycle life,29 albeit again at currents well below the diffusion-limited current. Ramified moss-like or ‘‘mossy’’ deposits have even been observed at a current density of $10~{\\upmu\\mathrm{A}}~{\\mathrm{cm}}^{-2}$ (ref. 30) and have been observed to grow from their roots,31 rather than their tips, in contrast to all existing growth models. Moreover, the microscopic morphology of serpentine lithium filaments observed in various electrolytes,3,5,9,32–35 over a range of length scales, do not resemble the branched, fractal structure of copper dendrites. These striking discrepancies between lithium and copper metal electrodeposition have lingered for decades without a clear explanation. \n\nIn this study, we aim to determine the precise conditions for short-inducing dendritic lithium to form, in order to establish design constraints for safe rechargeable metal batteries. We choose one of the most successful electrolytes for lithium-ion batteries, $^{36}\\mathrm{LiPF}_{6}$ in the $1{:}1$ mixture of ethylene carbonate (EC) and dimethyl carbonate (DMC), and conduct two sets of experiments to investigate the mechanisms of lithium dendrite growth under various conditions. The first experiments with novel capillary cells reveal that the relatively dense ‘‘mossy’’ lithium growth is reaction-limited and changes to fractal ‘‘dendritic’’ lithium in response to electrolyte diffusion limitation. The second experiments using sandwich cells demonstrate that root-growing mossy lithium can be blocked by a nanoporous ceramic membrane, while tip-growing dendritic lithium can easily penetrate the nanopores and cause the internal short only at over-limiting currents. Our results suggest that optimizing and monitoring the intrinsic transport properties of the battery could eliminate the formation of dendritic lithium and the risk of internal shorts thereafter. \n\n# Results \n\n# Transition from mossy to dendritic lithium \n\nTo better track the growth of lithium in situ, we fabricate a lithium|electrolyte|lithium symmetric cell in a special glass capillary, whose middle part is pulled thinner (Fig. 1a). A small piece of lithium metal is pushed into each end of the capillary until it lodges in the tapering part to seal the cell. Here, we are interested in the lithium deposition (reduction reaction), so the corresponding electrode should be called cathode. However, in order to be consistent with the convention of lithium metal anodes, we assume that the electrodeposition is a recharging process and the electrode is designated as an anode. \n\nWhen a constant current is applied, moss-like lithium starts to deposit (Fig. 1c and d), and the salt concentration near the surface starts to decrease,37 as indicated by the gradually increasing voltage (Fig. 1b). After $\\sim40\\ \\mathrm{min}$ of polarization, the voltage starts to diverge upon salt depletion at the anode surface,38 and a wispy dendrite suddenly shoots out (at 2678s in Fig. 1e) in an obvious tip-growing manner, leaving behind stagnant mossy lithium. The dendrite’s fractal structure remains the same after two weeks of relaxation. \n\nThe striking differences in morphology and dynamics imply two different mechanisms, switching from reaction-limited to transport-limited growth at the voltage spike. In the early stages of electrodeposition, mossy lithium mainly grows from its roots, as revealed by the movement of the tips, which barely change shape as they are pushed forward $^{\\mathrm{(ESI,\\dag}}$ Fig. S1 and Movies S1, S2). Root growth has also been observed by Yamaki et al.31 below the limiting current and attributed to internal stress release beneath the SEI layer on the lithium electrode. While growing into the open electrolyte, the mossy lithium also thickens, and the process has been described vividly as ‘‘rising dough’’.30 It is noteworthy that at the microscopic scale, the relatively dense moss-like structure is composed of whiskers, although the width of an individual whisker varies in different electrolytes.5,9,30,35 Such random surface growth is typical of reaction-limited deposition.19 Compared with copper electrodeposition,14 the key difference is that lithium, covered by SEI, develops whiskers and mossy structures, while copper, without SEI, forms whisker-free yet compact deposition before Sand’s time.39 Due to the insulating SEI that forms on individual lithium whiskers, mossy lithium is unable to transform into a uniform metallic film through a ripening process, even under mechanical pressure. At the voltage spike, sparse lithium dendrites grow explosively from their tips with the fractal morphology of diffusion-limited aggregation,19 also shared by copper dendrites,13,14 because electrodeposition is in the same universality class.40,41 The similarity between lithium and copper dendrites implies that both metals have similar surface tension, so the formation of dendritic lithium is correlated with the lack of lithium salt to form SEI different from that of mossy lithium, or very little SEI until the concentration relaxes after the initial burst of growth. \n\nTo test the hypothesis of diffusion limitation, the experimental times to reach the voltage spike are used to calculate an apparent diffusion coefficient Dapp from Sand’s formula,22 \n\n$$\nt_{\\mathrm{Sand}}=\\pi D_{\\mathrm{app}}{\\frac{\\left(z_{\\mathrm{c}}c_{0}F\\right)^{2}}{4\\left(J t_{\\mathrm{a}}\\right)^{2}}}\n$$ \n\nwhere $z_{\\mathrm{c}}$ is the charge number of the cation $\\left(z_{\\mathrm{c}}\\ =\\ 1\\right.$ for $\\mathrm{Li}^{+}$ , $c_{0}$ is the bulk salt concentration, $F$ is the Faraday’s constant, \n\n![](images/5fd1a7abe2d62ea02514ee180136e28c3026d063db0a083ffd3422c3f5c664a5.jpg) \nFig. 1 In situ observations of lithium electrodeposition in a glass capillary filled with an electrolyte solution consisting of 1 M $\\mathsf{L i P F}_{6}$ in EC/DMC. (a) Photo of the capillary cell, whose middle part was pulled thinner for easier optical observation. (b) Voltage responses of the capillary cell at a deposition current density of $2.61\\mathsf{m A}\\mathsf{c m}^{-2}$ . $({\\mathsf{C}}-{\\mathsf{g}})$ In situ snapshots of the growth of lithium during the electrodeposition. Red arrow in (e) points to the emergence of dendritic lithium. Red dash line in (g) labels the clear morphological difference between the pre- and post-Sand’s time lithium deposits. (h) Theoretical interpretation of the growth mechanisms of lithium electrodeposition during concentration polarization. \n\n$J$ is the current density, and $t_{\\mathrm{Li}}=0.38$ and $t_{\\mathrm{a}}=1-t_{\\mathrm{Li}}$ are the transference numbers of lithium cations and associated anions. For $c_{0}=1\\mathrm{~M~}$ , the calculated value, $D_{\\mathrm{app}}=1.0\\times10^{-6}~\\mathrm{cm}^{2}~\\mathrm{s}^{-1}$ , is consistent with reported values $3.0{-}3.5\\ \\times\\ 10^{-6}\\ \\mathrm{cm}^{2}\\ \\mathrm{s}^{-1}$ for small-current relaxation.42,43 As shown in Fig. 2a, the voltage spike at Sand’s time is consistently observed above the limiting current density, $J_{\\mathrm{lim}}=2z_{\\mathrm{c}}c_{0}F D_{\\mathrm{app}}(t_{\\mathrm{a}}L)^{-1}\\approx1\\mathrm{\\mA\\cm}^{-2}$ , where $L\\approx5\\:\\mathrm{mm}$ is the distance between the electrodes. With the aid of the in situ snapshots (Fig. 2b), we accurately measured the ‘‘experimental Sand’s time’’ for the onset of dendrites at each current density. The log–log plot can be fitted with a slope of $-1.40$ (Fig. 2c). Scaling exponents $>-2$ have also been reported (without explanation) for the short-circuiting time in other lithium cells.44 As shown in the $\\mathrm{ESI},\\dag$ the deviation observed here is attributable to convection by electro-osmotic flow in the depleted zone,45,46 although other effects, such as spatially varying porosity and/or deposit morphology, can also lead to different scaling laws for propagating diffusion layers in porous media.47 \n\nAs a new battery relevant metric, we convert Sand’s time into ‘‘Sand’s capacity’’ by multiplying with the current density. The plot of Sand’s capacity versus current density (Fig. 2d) provides a simple design constraint to avoid dendritic lithium. Interestingly, most state-of-the-art lithium metal anodes do not operate in the regime of dendritic lithium identified by the capillary cell, which is already much lower than that of the sandwich cells. Since the growth mechanism switches by diffusion limitation, absolute current densities cannot be meaningfully compared across different cells. It is the relative current density, with respect to the system-specific limiting current, that controls the transition from mossy to dendritic lithium. \n\n# Blockage of mossy lithium \n\nWe then apply the knowledge of growth mechanisms from the capillary cell to investigate the ability of a nanoporous separator to block mossy and dendritic lithium in a battery relevant sandwich cell. Since the smallest known whiskers in mossy lithium are $\\sim1\\upmu\\mathrm{m}$ thick,3 we construct the cell using an anodic aluminum oxide (AAO) membrane with submicron pores $(<200\\ \\mathrm{nm})$ , to see whether the mossy lithium can be blocked (Fig. 3a). \n\n![](images/d28cf7bb5b48d44e293c36e6f70e2cf72021b9f87d5e2eb877a4679295344219.jpg) \nFig. 2 Change of growth mechanism at Sand’s time during concentration polarization. (a) Voltage responses of capillary cells at various deposition current densities. (b) Representative optical images of lithium deposits demonstrating the clear change of morphologies at Sand’s time for various current densities. (c) Log–log plot of the experimental Sand’s times for various current densities. (d) Current-dependent Sand’s capacity with previous reports shown. \n\nBased on the electrode separation, $300\\upmu\\mathrm{m}$ , the limiting current density for the sandwich cell is approximately $20\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ When an under-limiting current density of $10\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ is applied, the voltage stabilizes at $0.2{\\mathrm{~V~}}$ and lasts for a capacity well beyond the pure lithium limit that the compartment below the AAO can accommodate (Fig. 3a), indicating some deformation of the membrane. After dissembling the cell, an intact, free-standing AAO membrane is recovered with a dense lithium disk below it (Fig. S5, $\\mathrm{ESI\\dagger}$ ), which confirms the complete blockage of mossy lithium growth. Surprisingly, even when the AAO membrane is pressed in direct contact with the lithium metal anode, a significant amount of porous lithium can still be deposited below the AAO, as shown in Fig. 3c and d. The mossy lithium shown in the SEM images is clearly too bulky to penetrate AAO, and only forms a space-filling porous layer between the electrode and the separator, reducing the risk of short circuit below the limiting current. These results help explain why various ceramic membranes can prevent lithium short circuits,6,44,48,49 especially under normal conditions $\\left(<10\\mathrm{\\mA\\cm^{-2}}\\right)$ ), where only the dense root-growing mossy lithium is developed in the cell. \n\nAs demonstrated in the capillary cell experiments, once Sand’s capacity is exceeded, dendritic lithium suddenly appears. When an over-limiting current density of $50\\mathrm{\\mA}\\mathrm{cm}^{-2}$ is applied to the sandwich cell, the voltage quickly increases and leads to a short circuit. As revealed by the SEM images, very thin lithium filaments can now be found among mossy deposits on the anode side (Fig. 3e and f). Clusters of granular deposits, smaller than the pores of AAO, are also clearly visible on the cathode side (Fig. $_{39}$ and h), which confirm that lithium penetration through the ceramic nanopores caused the short circuit. The stark difference between mossy and dendritic lithium deposits leads us to propose that the term ‘‘dendrite’’ be used more narrowly, only to describe a fractal, tip-growing deposit resulting from diffusion-limited growth, consistent with the well-studied copper and zinc dendrites. If lithium dendrite penetration in AAO were mainly opposed by surface tension, then the breakthrough voltage (where the overpotential exceeds the Young–Laplace pressure) would scale with the inverse of the pore size. The dendrite penetration may be further suppressed by modifying the surface charge of the nanopores,15 when over-limiting mass transfer is opposed by surface conduction.46 \n\n![](images/b5214a08431037459baf35e36655fd7bc123bd99b49db47295634efb0f6f9d73.jpg) \nFig. 3 Lithium electrodeposition in sandwich cells. (a) Structure of the symmetric sandwich cell, where names of the electrodes follow the convention of lithium batteries, i.e. lithium deposits onto the anode during recharging. (b) Voltage responses of the sandwich cells, indicating the complete blockage of lithium deposits even beyond the theoretical capacity of the lower compartment at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ , as well as the quick penetration of AAO and shortcircuiting of the cell at $50\\ m\\mathsf{A}\\mathsf{c m}^{-2}$ . (c and d) Scanning electron microscopy (SEM) images of the AAO/Li-deposit interface, revealing the blockage of bulky porous lithium formed in the under-limiting current conditions. (e and f) SEM images of the anode-facing side of AAO, displaying both bulky and needle-like lithium deposits formed in the over-limiting current conditions. (g and h) SEM images of the cathode-facing side of AAO, showing nanosized lithium deposits coming out of the nanopores of AAO. Inset: Magnification of the clusters of granular lithium deposits around the pores of AAO (appear as black dots). \n\n# Sand’s capacity as the safety limit \n\nOur results reveal why the risk of dendrites increases with aging, and how to mitigate it. According to the definition of Sand’s capacity, \n\n$$\nC_{\\mathrm{Sand}}=J t_{\\mathrm{Sand}}=\\pi D_{\\mathrm{app}}{\\frac{(z_{\\mathrm{c}}c_{0}F)^{2}}{4J t_{\\mathrm{a}}^{2}}}\n$$ \n\ndilution of the electrolyte alone could significantly lower the safety limit, which is verified experimentally with our capillary cells by varying the salt concentration $c_{0}$ (Fig. 4). In practical cells, the cycling of mossy lithium consumes a large amount of the liquid electrolyte (salt and solvent) to form SEI layers.8,12,51,52 This lowers the amount of the dissolved lithium salt, and thereby the effective diffusivity $D_{\\mathrm{app}}$ , which not only results in higher impedance, but also steadily lowers the intrinsic Sand’s capacity. While the high impedance has been identified in a few experiments as a major cause of battery failure,8,9,12,51 dendritic lithium can still develop and short aged cells when using 1 M electrolyte,9 where the decrease of the intrinsic Sand’s capacity below the cycled capacity could be an explanation. Therefore, increasing Sand’s capacity by increasing the salt concentration in the electrolyte should be an effective method to improve the safety of rechargeable metal batteries. Interestingly, highly concentrated electrolytes have already enabled very high Coulombic efficiency,9,10,35 which is beneficial to longer cycle life. \n\n# Dimensionless safety criterion \n\nIn order to compare different systems and make general scaling predictions about the safety limit, we employ dimensional analysis. Following earlier definitions, $L$ is the distance between the two electrodes, then $L/2$ is a characteristic length scale for electrolyte diffusion with apparent diffusivity $D_{\\mathrm{app}}.$ i.e. the distance from the electrode (where salt depletion occurs) to a reservoir at concentration $c_{0}$ . Let $J_{\\mathrm{lim}}$ be the steady-state diffusion-limited current, and $C_{\\mathrm{Sand}}$ be the maximum (Sand’s) areal capacity for safe operation at a given current density $J.$ If these are the only important parameters, then, simply as a consequence of their physical units, Buckingham’s theorem53 states that there must exist a scaling relation $\\tilde{C}_{\\mathrm{Sand}}=f(\\tilde{J})$ between the dimensionless Sand’s capacity and the dimensionless applied current density, \n\n$$\n\\tilde{C}_{\\mathrm{Sand}}=\\frac{4C_{\\mathrm{Sand}}D_{\\mathrm{app}}}{J L^{2}}\n$$ \n\n$$\n\\tilde{J}=\\frac{J}{J_{\\mathrm{lim}}}\n$$ \n\nSubstitution of eqn (2) and (4) into eqn (3), with the limiting current density for the dilute binary electrolyte, $J_{\\mathrm{lim}}=2z_{\\mathrm{c}}c_{0}F D_{\\mathrm{app}}(t_{\\mathrm{a}}L)^{-1}$ , yields the scaling function, \n\n$$\n\\tilde{C}_{\\mathrm{Sand}}=f_{\\mathrm{dilute}}(\\tilde{J})=\\frac{\\pi}{4\\tilde{J}^{2}}\n$$ \n\n![](images/393eeebe5c294f6c9fa52661c9255a36263350fd3cd1810438eb6becfa926882.jpg) \nFig. 4 Concentration-dependent Sand’s behavior. Experimental (a) Sand’s times and (b) Sand’s capacities for $0.5M$ and $2M$ electrolytes, with results of 1 M electrolyte from Fig. 2 as references. \n\n![](images/79578fda5936ff787bf5754e6f31b97f07d201475a6935b89425360272428c02.jpg) \nFig. 5 Linear and logarithmic (inset) plots of dimensionless Sand’s capacity versus dimensionless current density. Dashed line is the prediction of Sand’s formula for dilute electrolytes, while solid line is the best fit to the experimental data. \n\nThe same scaling function governs the time, $t_{\\mathrm{Sand}}~=~C_{\\mathrm{Sand}}{\\cal J}^{-1},$ required to reach Sand’s capacity at constant current, scaled to the diffusion time: $\\tilde{t}_{\\mathrm{Sand}}=4t_{\\mathrm{Sand}}D_{\\mathrm{app}}L^{-2}=f(\\tilde{J}),$ which can also be derived by solving the ambipolar diffusion equation for transient overlimiting current density $\\tilde{J}>1\\left(\\mathrm{ESI}\\dagger\\right)$ . \n\nThe scaling function will differ for concentrated electrolytes54 (with concentration-dependent diffusivities and coupled Stefan– Maxwell fluxes) in porous separators47 (with possibly variable porosity and tortuosity, surface conduction and electro-osmotic flows), but the trend should be the same as predicted by dilute solution theory.55 When the experimental data shown in Fig. 4b are nondimensionalized with corresponding $D_{\\mathrm{app}}$ (Table S3, ESI†) and plotted in Fig. 5 as $\\tilde{C}_{\\mathrm{Sand}}\\nu e r s u s\\tilde{J};$ a reasonable data collapse is observed, similar to the dilute solution prediction, eqn (5), but with a modified scaling function, $f(\\tilde{J})=0.265\\tilde{J}^{-1.274}$ , which is mainly attributable to electro-osmotic convection in the capillary cells (Fig. S4, ESI†). \n\n# Discussion \n\nOur results suggest that monitoring the capacity loss and transient responses to estimate transport properties and the associated Sand’s capacity could enable battery management systems to avoid dendrites by adjusting the applied current or cycled capacity windows in real time, which is particularly important for rechargeable lithium metal batteries cycling at high capacities. This prediction may seem at odds with the fact that some Li–S prototypes can be cycled at a very large specific capacity for hundreds of times without signs of internal shorts. There is no contradiction, however, after accounting for capacity differences. By multiplying the specific capacity with the small loading mass of the active sulfur,56 the converted areal capacity (in units of mA h $\\mathrm{cm}^{-2}$ ) that matters for the metal anode is actually smaller than those of mature lithium-ion batteries.56,57 For future rechargeable lithium metal batteries that possess a high specific energy with respect to the total mass, and operate at a truly large areal capacity, on-board diagnosis of the intrinsic Sand’s capacity of the battery to avoid dendritic lithium may become a practical solution for safe operation, before a robust chemistry that can completely suppress the continuous consumption of electrolyte (due to the growth of lithium whiskers) is developed. \n\nCarbonate-base electrolytes, such as what we use in this work, are known to effect relatively thin lithium whiskers.32 Ether-based electrolytes, in contrast, allow lithium whiskers to grow much thicker.7–9,58,59 At a given areal capacity, thicker lithium whiskers create less surface area and therefore consume less lithium salt and solvent to develop SEI layers. In addition, fluorosulfonate species used in these electrolytes, such as lithium bis(trifluoromethane-sulphonyl)imide (LiTFSI) and lithium bis(fluorosulfonyl)imide (LiFSI), could undergo extensive reactions with lithium to form a robust LiF-rich SEI,52,59 which could also be facilitated by employing very high salt concentrations.9 However, whether the SEI layers formed in ether-based electrolytes will remain stable during cycling at larger areal capacities, and thereby retard the continuous consumption of electrolytes12,60 to retain high Coulombic efficiency and long cycle life is yet to be verified experimentally. Investigating the fundamental mechanisms alongside may help engineer better SEI in other high-voltage solvents,36,61 with which the standard graphite anode in lithiumion batteries may be replaced by ultrathin lithium metal anodes or simply removed to double the energy density. Of course, the chemistry of SEI does not override transport processes in electrolytes. Transitions from root-growing mossy lithium to tip-growing dendritic lithium also occur in ether-based electrolytes (Fig. S7 and Movie S6, S7, ESI†). \n\nAn important implication of our study is the need for consistent terminology, not only to refer to the different lithium morphologies, but also to clarify the underlying mechanisms for rational battery design and engineering. Comparing various published work with ours, the thin needle-like lithium filaments that grow from their roots below the limiting current should be called ‘‘whiskers’’, which interweave with each other to form a ‘‘mossy’’ structure as the capacity increases. In contrast, the widely-used term ‘‘dendrites’’ should be reserved for the classical branched fractal structures that grow at their tips, which only occur at diffusion limitation and cannot revert to form a mossy structure. Although individual whiskers in the mossy structure may become thinner or disconnected over many deposition/ dissolution cycles, as long as the current density remains underlimiting, the root-growth mechanism will make penetrating ceramic nanopores as difficult as threading a needle. With further investigations of SEI formation on mossy lithium and its interaction with ceramic separators during cycling, an ultimate safe solution should be possible. \n\n# Conclusions \n\nWhile the failure mechanisms in practical batteries with opaque separators are still challenging to investigate in situ,62 our capillary cells provide a simple and effective means to explore the hidden physics. We have demonstrated that lithium growth in liquid electrolytes follows two different mechanisms, depending on the applied current and capacity. Below Sand’s capacity, reaction-limited mossy lithium mainly grows from the roots and cannot penetrate hard ceramic nanopores in a sandwich cell. Above Sand’s capacity, transport-limited dendritic lithium grows at the tips and can easily cross the separator to short the cell. Our results suggest maximizing Sand’s capacity by increasing the salt concentration in the electrolyte. Electrolyte degradation should also be monitored to prevent dendrites by keeping the cycled capacity below Sand’s capacity. Ceramic separators with pores smaller than mossy lithium whiskers could replace conventional polyolefin separators with flexible large pores to enhance safety and cycle life, and the effect could be further reinforced with lithium salts and solvents that favor thicker columnar deposits. To the broader field of electrodeposition, our results clarify the physical connections between lithium and copper/zinc dendrites formed in liquid electrolytes. Mechanisms and mathematical models of copper/zinc dendrite growths cannot be and should not be applied to explain either the development or the suppression of lithium whiskers. Future theoretical investigations should take into account the dynamics of SEI formation during both the root-growth and tip-growth processes of lithium electrodeposition. \n\n# Methods \n\n# Materials \n\nThe battery grade electrolyte $(1\\mathrm{M}\\mathrm{LiPF}_{6}$ in ethylene carbonate/ dimethyl carbonate with a volume ratio of $\\boldsymbol{1}:\\boldsymbol{1}$ ), ethylene carbonate (EC, anhydrous, $99\\%$ ), dimethyl carbonate (DMC, anhydrous, $\\geq99\\%$ ), and Whatman AAO membranes (pore size $100\\ \\mathrm{nm}$ , thickness $60~{\\upmu\\mathrm{m}}$ , diameter $13\\ \\mathrm{mm}$ ) were purchased from Sigma-Aldrich, and used as received. Lithium bis(trifluoromethane-sulphonyl)imide (LiTFSI), 1,3-dioxolane (DOL) and 1,2-dimethoxyethane (DME) were purchased from BASF Corporation. Lithium bis(fluorosulfonyl)imide (LiFSI) was purchased from Oakwood Products Inc. Copper wires, stainless steel wires, and polyvinylidene fluoride (PVDF) sheets were purchased from McMaster-Carr. The glass capillaries were purchased from Narishige Co., Ltd. Lithium chips $(99.9\\%$ , thickness $250~{\\upmu\\mathrm{m}}.$ diameter $15.6~\\mathrm{mm}$ ) were purchased from MTI Corporation. \n\n# Cell fabrication and electrochemical testing \n\nThe glass capillaries were pulled 7 mm longer with a vertical type micropipette puller (PC-10, Narishige Co., Ltd). The pulled capillary was bonded onto a glass slide with silicone and then transferred into the Argon-filled glovebox. To avoid gas bubbles, the electrolyte was filled in only by the capillary effect. Then, a small piece of lithium metal was pushed into each end of the cell by a metal wire to clog at the tapering part of the capillary to seal the cell. Separation between the lithium electrodes is around $5~\\mathrm{mm}$ for all cells. Sandwich cells were constructed in the split test cells purchased from MTI Corporation. A piece of lithium chip was first gently pressed onto the bottom part of the cell and covered by a customized PVDF washer punched off from the PVDF sheet. Several drops of electrolyte were dispensed on the surface of lithium, which also immerse the PVDF washer. A piece of AAO was then carefully placed on top of the PVDF washer and covered by another piece of PVDF washer. A few more drops of electrolyte were dispensed on AAO until the second PVDF washer is immersed. Finally the second lithium chip was stacked on top of the second PVDF, and then covered by a stainless steel disk. The whole cell was assembled together with the upper part (spring-loaded) of the test cell. Electrochemical tests were conducted with an Arbin battery tester (BT 2043, Arbin Instruments). In situ images were captured by an optical microscope (MU500, AmScope). All experiments were performed at room temperature in an Argon-filled glovebox (Vigor Tech USA) with water and oxygen content less than 1 ppm. \n\n# SEM characterization \n\nAAO separators with lithium deposits harvested from sandwich cells were washed with DMC for three times, then fixed onto the \n\nSEM sample holders with carbon adhesive and sealed in an air-tight box before moving out of the Argon-filled glovebox. The residual DMC on the samples helps protect the lithium from the ambient atmosphere when transferring them into the chamber of the Analytical Scanning Electron Microscope (JEOL, 6010LA), which usually takes less than 10 s before the vacuum evacuation. \n\n# Acknowledgements \n\nThis work is supported by Robert Bosch LLC through the MIT Energy Initiative (MITei). P. B. thanks Mr William DiNatale in the Institute for Soldier Nanotechnologies at MIT for providing the access to the micropipette puller. J. L. acknowledges support by NSF DMR-1410636. M. Z. B. acknowledges support from the Global Climate and Energy Project at Stanford University and by the US Department of Energy, Basic Energy Sciences through the SUNCAT Center for Interface Science and Catalysis. The authors thank Dr Sarah Stewart for helpful discussions. \n\n# Notes and references \n\n1 P. G. Bruce, S. A. Freunberger, L. J. Hardwick and J. M. Tarascon, Nat. Mater., 2012, 11, 19–29. \n2 J. M. Tarascon and M. Armand, Nature, 2001, 414, 359–367. \n3 W. Xu, J. Wang, F. Ding, X. Chen, E. Nasybulin, Y. Zhang and J.-G. Zhang, Energy Environ. Sci., 2014, 7, 513–537. \n4 F. Ding, W. Xu, G. L. Graff, J. Zhang, M. L. Sushko, X. L. Chen, Y. Y. Shao, M. H. Engelhard, Z. M. Nie, J. Xiao, X. J. Liu, P. V. Sushko, J. Liu and J. G. Zhang, J. Am. Chem. Soc., 2013, 135, 4450–4456. \n5 W. Y. Li, H. B. Yao, K. Yan, G. Y. Zheng, Z. Liang, Y. M. Chiang and Y. Cui, Nat. Commun., 2015, 6, 7436. \n6 Y. Y. Lu, Z. Y. Tu and L. A. Archer, Nat. Mater., 2014, 13, 961–969. \n7 G. Y. Zheng, S. W. Lee, Z. Liang, H. W. Lee, K. Yan, H. B. Yao, H. T. Wang, W. Y. Li, S. Chu and Y. Cui, Nat. Nanotechnol., 2014, 9, 618–623. \n8 D. Aurbach, E. Zinigrad, H. Teller and P. Dan, J. Electrochem. Soc., 2000, 147, 1274–1279. \n9 J. F. Qian, W. A. Henderson, W. Xu, P. Bhattacharya, M. Engelhard, O. Borodin and J. G. Zhang, Nat. Commun., 2015, 6, 6362. \n10 L. Suo, Y.-S. Hu, H. Li, M. Armand and L. Chen, Nat. Commun., 2013, 4, 1481. \n11 M. H. Ryou, Y. M. Lee, Y. J. Lee, M. Winter and P. Bieker, Adv. Funct. Mater., 2015, 25, 834–841. \n12 D. Aurbach, E. Zinigrad, Y. Cohen and H. Teller, Solid State Ionics, 2002, 148, 405–416. \n13 V. Fleury, M. Rosso, J. N. Chazalviel and B. Sapoval, Phys. Rev. A: At., Mol., Opt. Phys., 1991, 44, 6693–6705. \n14 J. Elezgaray, C. Leger and F. Argoul, J. Electrochem. Soc., 1998, 145, 2016–2024. \n15 J.-H. Han, E. Khoo, P. Bai and M. Z. Bazant, Sci. Rep., 2014, 4, 7056. \n16 R. M. Brady and R. C. Ball, Nature, 1984, 309, 225–229. \n17 C. Leger, J. Elezgaray and F. Argoul, Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top., 1998, 58, 7700–7709. \n18 T. A. Witten and L. M. Sander, Phys. Rev. Lett., 1981, 47, 1400–1403. \n19 A.-L. s. Barab´asi and H. E. Stanley, Fractal concepts in surface growth, Press Syndicate of the University of Cambridge, New York, NY, USA, 1995. \n20 A. Bunde and S. Havlin, Fractals and disordered systems, Springer, Berlin, New York, 1996. \n21 J. S. Newman and K. E. Thomas-Alyea, Electrochemical systems, J. Wiley, Hoboken, NJ, 2004. \n22 H. J. S. Sand, Philos. Mag., 1901, 1, 45–79. \n23 A. J. Bard and L. R. Faulkner, Electrochemical methods: fundamentals and applications, Wiley, New York, 2001. \n24 D. P. Barkey and P. D. Laporte, J. Electrochem. Soc., 1990, 137, 1655–1656. \n25 M. Z. Bazant, Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top., 1995, 52, 1903–1914. \n26 C. Brissot, M. Rosso, J. N. Chazalviel and S. Lascaud, J. Power Sources, 1999, 81–82, 925–929. \n27 M. Rosso, T. Gobron, C. Brissot, J. N. Chazalviel and S. Lascaud, J. Power Sources, 2001, 97–98, 804–806. \n28 M. Rosso, C. Brissot, A. Teyssot, M. Dolle, L. Sannier, J. M. Tarascon, R. Bouchetc and S. Lascaud, Electrochim. Acta, 2006, 51, 5334–5340. \n29 Z. Y. Tu, P. Nath, Y. Y. Lu, M. D. Tikekar and L. A. Archer, Acc. Chem. Res., 2015, 48, 2947–2956. \n30 J. Steiger, D. Kramer and R. Moenig, Electrochim. Acta, 2014, 136, 529–536. \n31 J. Yamaki, S. Tobishima, K. Hayashi, K. Saito, Y. Nemoto and M. Arakawa, J. Power Sources, 1998, 74, 219–227. \n32 F. Ding, W. Xu, X. L. Chen, J. Zhang, M. H. Engelhard, Y. H. Zhang, B. R. Johnson, J. V. Crum, T. A. Blake, X. J. Liu and J. G. Zhang, J. Electrochem. Soc., 2013, 160, A1894–A1901. \n33 R. R. Miao, J. Yang, Z. X. Xu, J. L. Wang, Y. Nuli and L. M. Sun, Sci. Rep., 2016, 6, 21771. \n34 Z. Li, J. Huang, B. Y. Liaw, V. Metzler and J. B. Zhang, J. Power Sources, 2014, 254, 168–182. \n35 R. Cao, J. Chen, K. S. Han, W. Xu, D. Mei, P. Bhattacharya, M. H. Engelhard, K. T. Mueller, J. Liu and J.-G. Zhang, Adv. Funct. Mater., 2016, 26, 3059–3066. \n36 K. Xu, Chem. Rev., 2004, 104, 4303–4417. \n37 H. J. Chang, A. J. Ilott, N. M. Trease, M. Mohammadi, A. Jerschow and C. P. Grey, J. Am. Chem. Soc., 2015, 137, 15209–15216. \n38 C. Brissot, M. Rosso, J. N. Chazalviel and S. Lascaud, J. Electrochem. Soc., 1999, 146, 4393–4400. \n39 K. I. Popov, S. S. Djokic and B. N. Grgur, Fundamental aspects of electrometallurgy, Kluwer Academic/Plenum Publishers, New York, 2002. \n40 M. Z. Bazant, Proc. R. Soc. A, 2004, 460, 1433–1452. \n41 M. Z. Bazant, J. Choi and B. Davidovitch, Phys. Rev. Lett., 2003, 91, 045503. \n42 L. O. Valoen and J. N. Reimers, J. Electrochem. Soc., 2005, 152, A882–A891. \n43 A. Nyman, M. Behm and G. Lindbergh, Electrochim. Acta, 2008, 53, 6356–6365. \n44 S. Choudhury, R. Mangal, A. Agrawal and L. A. Archer, Nat. Commun., 2015, 6, 10101. \n45 J. M. Huth, H. L. Swinney, W. D. Mccormick, A. Kuhn and F. Argoul, Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top., 1995, 51, 3444–3458. \n46 E. V. Dydek, B. Zaltzman, I. Rubinstein, D. S. Deng, A. Mani and M. Z. Bazant, Phys. Rev. Lett., 2011, 107, 118301. \n47 A. Mani and M. Z. Bazant, Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys., 2011, 84, 061504. \n48 Y.-k. Ahn, J. Park, D. Shin, S. Cho, S. Y. Park, H. Kim, Y. Piao, J. Yoo and Y. S. Kim, J. Mater. Chem. A, 2015, 3, 10715–10719. \n49 Z. Tu, Y. Kambe, Y. Lu and L. A. Archer, Adv. Energy Mater., 2014, 4, 1300654. \n50 A. Jana, D. R. Ely and R. E. Garcia, J. Power Sources, 2015, 275, 912–921. \n51 D. P. Lv, Y. Y. Shao, T. Lozano, W. D. Bennett, G. L. Graff, B. Polzin, J. G. Zhang, M. H. Engelhard, N. T. Saenz, W. A. Henderson, P. Bhattacharya, J. Liu and J. Xiao, Adv. Energy Mater., 2015, 5, 1400993. \n52 X. B. Cheng, R. Zhang, C. Z. Zhao, F. Wei, J. G. Zhang and Q. Zhang, Adv. Sci., 2016, 3, 1500213. \n53 G. I. Barenblatt, Dimensional analysis, Gordon and Breach Science Publishers, New York, 1987, pp. 31–48. \n54 S. A. Mareev, D. Y. Butylskii, A. V. Kovalenko, A. V. Petukhova, N. D. Pismenskaya, L. Dammak, C. Larchet and V. V. Nikonenko, Electrochim. Acta, 2016, 195, 85–93. \n55 M. Z. Bazant, 10.626 Electrochemical Energy Systems (Spring 2014), Massachusetts Institute of Technology: MIT OpenCourseWare, http://ocw.mit.edu. License: Creative Commons BY-NC-SA. \n56 M. Hagen, D. Hanselmann, K. Ahlbrecht, R. Maca, D. Gerber and J. Tubke, Adv. Energy Mater., 2015, 5, 1401986. \n57 H. H. Zheng, J. Li, X. Y. Song, G. Liu and V. S. Battaglia, Electrochim. Acta, 2012, 71, 258–265. \n58 J. Steiger, G. Richter, M. Wenk, D. Kramer and R. Monig, Electrochem. Commun., 2015, 50, 11–14. \n59 R. R. Miao, J. Yang, X. J. Feng, H. Jia, J. L. Wang and Y. N. Nuli, J. Power Sources, 2014, 271, 291–297. \n60 D. Aurbach, Y. Talyosef, B. Markovsky, E. Markevich, E. Zinigrad, L. Asraf, J. S. Gnanaraj and H. J. Kim, Electrochim. Acta, 2004, 50, 247–254. \n61 K. Xu, Chem. Rev., 2014, 114, 11503–11618. \n62 K. J. Harry, D. T. Hallinan, D. Y. Parkinson, A. A. MacDowell and N. P. Balsara, Nat. Mater., 2014, 13, 69–73. " + }, + { + "id": "10.1021_jacs.6b03714", + "DOI": "10.1021/jacs.6b03714", + "DOI Link": "http://dx.doi.org/10.1021/jacs.6b03714", + "Relative Dir Path": "mds/10.1021_jacs.6b03714", + "Article Title": "Contributions of Phase, Sulfur Vacancies, and Edges to the Hydrogen Evolution Reaction Catalytic Activity of Porous Molybdenum Disulfide nullosheets", + "Authors": "Yin, Y; Han, JC; Zhang, YM; Zhang, XH; Xu, P; Yuan, Q; Samad, L; Wang, XJ; Wang, Y; Zhang, ZH; Zhang, P; Cao, XZ; Song, B; Jin, S", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Molybdenum disulfide (MoS2) is a promising nonprecious catalyst for the hydrogen evolution reaction (HER) that has been extensively studied due to its excellent performance, but the lack of understanding of the factors that impact its catalytic activity hinders further design and enhancement of MoS2-based electrocatalysts. Here, by using novel porous (holey) metallic 1T phase MoS2 nullosheets synthesized by a liquid-ammonia-assisted lithiation route, we systematically investigated the contributions of crystal structure (phase), edges, and sulfur vacancies (S-vacancies) to the catalytic activity toward HER from five representative MoS2 nullosheet samples, including 2H and IT phase, porous 2H and IT phase, and sulfur-compensated porous 2H phase. Superior HER catalytic activity was achieved in the porous IT phase MoS2 nullosheets that have even more edges and S-vacancies than conventional 1T phase MoS2. A comparative study revealed that the phase serves as the key role in determining the HER performance, as IT phase MoS2 always outperforms the corresponding 2H phase MoS2 samples, and that both edges and S-vacancies also contribute significantly to the catalytic activity in porous MoS2 samples. Then, using combined defect characterization techniques of electron spin resonullce spectroscopy and positron annihilation lifetime spectroscopy to quantify the S-vacancies, the contributions of each factor were individually elucidated. This study presents new insights and opens up new avenues for designing electrocatalysts based on MoS2 or other layered materials with enhanced HER performance.", + "Times Cited, WoS Core": 1095, + "Times Cited, All Databases": 1163, + "Publication Year": 2016, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000378984300030", + "Markdown": "# Contributions of Phase, Sulfur Vacancies, and Edges to the Hydrogen Evolution Reaction Catalytic Activity of Porous Molybdenum Disulfide Nanosheets \n\nYing Yin, Jiecai Han, Yumin Zhang, Xinghong Zhang, Ping Xu, Quan Yuan, Leith Samad, Xianjie Wang, Yi Wang, Zhihua Zhang, Peng Zhang, Xingzhong Cao, Bo Song, and Song Jin J. Am. Chem. Soc., Just Accepted Manuscript $\\cdot$ DOI: 10.1021/jacs.6b03714 • Publication Date (Web): 07 Jun 2016 Downloaded from http://pubs.acs.org on June 8, 2016 \n\n# Just Accepted \n\n“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier $(\\mathsf{D O}|\\oplus)$ . “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts. \n\n# Contributions of Phase, Sulfur Vacancies, and Edges to the Hydrogen Evolution Reaction Catalytic Activity of Porous Molybdenum Disulfide Nanosheets \n\nYing Yin,† Jiecai Han, † Yumin Zhang, † Xinghong Zhang, † Ping Xu,\\*,‡ Quan Yuan, † Leith Samad,§ Xianjie Wang,Δ Yi Wang,‖ Zhihua Zhang,∫ Peng Zhang,ѫ Xingzhong Cao, ѫ Bo Song\\*,Δ, ‖ and Song Jin\\*,§ \n\n†Centre for Composite Materials and Structures, Harbin Institute of Technology, Harbin 150080, China \n‡MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, School of Chemistry and \nChemical Engineering, Harbin Institute of Technology, Harbin 150080, China \n§Department of Chemistry, University of Wisconsin–Madison, 1101 University Avenue, Madison, Wisconsin 53706, USA \nΔDepartment of Physics, Harbin Institute of Technology, Harbin 150080, China \n‖Academy of Fundamental and Interdisciplinary Sciences, Harbin Institute of Technology, Harbin 150080, China \n∫School of Materials Science and Engineering, Dalian Jiaotong University, Dalian 116028, China \nѫ Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China \n\nABSTRACT: Molybdenum disulfide $(\\mathbf{MoS}_{2})$ is a promising non-precious catalyst for the hydrogen evolution reaction (HER) that has been extensively studied due to its excellent performance, but the lack of understanding on the factors that impact its catalytic activity hinders further design and enhancement of $\\mathbf{MoS}_{2}$ -based electrocatalysts. Here, by using novel porous $\\mathsf{M o S}_{2}$ nanosheets synthesized through a liquid ammonia-assisted lithiation route, we systematically investigated the contributions of crystal structure (phase), edges, and sulfur vacancies (S-vacancies) to the catalytic activity towards HER from five representative $\\mathbf{MoS}_{2}$ nanosheet samples, including $2\\mathrm{H}$ and 1T-phase, porous $2\\mathrm{H}$ and 1T-phase, and sulfur compensated porous $\\boldsymbol{\\mathsf{\\Omega}}_{2\\mathrm{H}}$ -phase. Superior HER catalytic activity was achieved in the porous 1T-phase $\\mathbf{MoS}_{2}$ nanosheets that have even more edges and S-vacancies than conventional 1T-phase $\\mathbf{MoS}_{2}$ . A comparative study revealed that not only phase serves as the key role in determining the HER performance, as 1T-phase $\\mathsf{M o S}_{2}$ always outperforms the corresponding 2H-phase $\\mathbf{MoS}_{2}$ samples, but also both edges and S-vacancies also contribute significantly to the catalytic activity in porous $\\mathbf{MoS}_{2}$ samples. Then, using combined defect characterization techniques of electron spin resonance (ESR) spectroscopy and positron annihilation lifetime spectroscopy (PALS) to quantify the S-vacancies, the contributions of each factor were individually elucidated. This study presents new insights and opens up new avenues for designing electrocatalysts based on $\\mathsf{M o S}_{2}$ or other layered materials with enhanced HER performance. \n\n# ■INTRODUCTION \n\nHydrogen $\\left(\\operatorname{H}_{2}\\right)$ is a promising clean and sustainable energy carrier and can be a suitable candidate to solve the energy and environmental crisis brought by the consumption of fossil fuels. As a result, the hydrogen evolution reaction (HER) has attracted a great deal of attention due to this urgent need for clean energy.1-6 Noble metals, such as platinum, have excellent catalytic activity toward HER but unfortunately, its application in large-scale hydrogen production is limited by the high cost and natural scarcity.6 Development of new Earth-abundant electrocatalysts to replace these rare and expensive noble metal catalysts is therefore highly desirable to realize highly efficient and sustainable hydrogen production.1 Among the Earth-abundant electrocatalysts explored,5,6 including transition metal sulfides,7-18 selenides,9,19 phosphides,20-22 $\\ensuremath{\\mathrm{MS}}_{2}$ 1 $\\mathbf{\\dot{M}}=\\mathbf{M}\\mathbf{o}$ or W) with two-dimensional $\\mathrm{(2D)}$ layered crystal structures are very promising catalysts with high HER catalytic activities7,8,10-17 that potentially rival the state-of-the-art catalysts in solar-driven photoelectrochemical cells.23 \n\nHowever, debate over the key factors influencing HER catalytic activity restricts further design and improvement of the $\\mathbf{MoS}_{2}$ -based electrocatalysts, although considerable efforts have been made during the past few years.4,10,11,13 The HER activity of semiconducting $\\mathsf{M o S}_{2}$ arising from the edge sites was first confirmed,24 therefore many works focused on engineering higher densities of edges sites.9,12 Conductivity and electrical contact was identified as another crucial factor25 and considerable effort was devoted to the improvement of either or both of these factors for enhancing HER performance of $\\mathbf{MoS}_{2}$ catalysts.25-27 Recently, the nanosheets (NS) of exfoliated metallic 1T phase $\\mathsf{M o S}_{2}$ and $\\mathsf{W S}_{2}$ (with octahedral structure) were demonstrated to exhibit superior HER catalytic performance to that of the semiconducting 2H phase (with trigonal-prismatic coordination) due to enhanced intrinsic catalytic activity facilitating the charge transfer kinetics.15,17 Although subsequent theoretical28-31 and experimental results8,16,17,32 have confirmed the critical role of the electronic structure of the $\\mathbf{1}\\mathrm{T}\\mathbf{-}\\mathbf{M}\\mathbf{o}\\mathsf{S}_{2}$ NS on the HER catalytic activity, the intrinsic mechanism for the HER enhancement in $\\mathbf{1}\\mathrm{T}\\mathbf{-}\\mathbf{M}\\mathbf{o}\\mathsf{S}_{2}$ has yet to be completely elucidated, especially the roles of the edges and S-vacancies. For instance, once converted into the 1T metallic phase, are the edges of $\\mathsf{M o S}_{2}$ still the only catalytic active sites, as in the case of semiconducting 2H $\\mathrm{MoS}_{2},^{24}$ and can the defects of the $\\mathbf{1}\\mathrm{T}\\mathbf{-}\\mathbf{M}\\mathbf{o}\\mathbf{S}_{2}$ be catalytically active as well? The basal plane of the 1T-phase were suggested to be also catalytically active both experimentally32 and theoretically,28-31 which challenges the contribution of the edges in HER activity.29 In addition, the common defects of S-vacancies in MoS2 were recently suggested to have significant impact on HER catalytic activity.33 It is notable that defect-rich $2\\mathrm{H}{-}\\mathrm{MoS}_{2}$ NS with additional exposure of active edge sites exhibited enhanced HER performance34 and both structural and electronic benefits for enhanced HER activity in 2H-phase $\\mathsf{M o S}_{2}$ have been realized by controllable disorder engineering and simultaneous oxygen incorporation.14 In light of these complexities, a comprehensive and systematic investigation of these factors including phase, edges, and defects on the HER performance in both 2H- and 1T-phase $\\mathsf{M o S}_{2}$ is required. \n\n![](images/26df906ea5668bf247e55764f90b90e24f279f7c0bc2360156a95f2d95e8c1f3.jpg) \nFigure 1. Schematic illustration of the preparation of mesoporous 1T phase $\\mathbf{MoS}_{2}$ nanosheets (P-1T $\\mathbf{MoS}_{2}$ , d) from bulk $\\mathbf{MoS}_{2}$ (a) by a liquid ammonia-assisted lithiation process, including lithiation, desulphurization, and exfoliation (Step I, II and III). Mesoporous 2H phase $\\mathbf{MoS}_{2}$ nanosheets $(\\mathrm{P}{-}2\\mathrm{H}\\mathrm{M}\\mathbf{o}\\mathrm{S}_{2},$ e) can be obtained by a simple thermal annealing process from P-1T $\\mathbf{MoS}_{2}$ (Step IV). \n\nTo elucidate the contributions of edges and S-vacancies, mesoporous $\\mathbf{1}\\mathrm{T}\\mathbf{-}\\mathbf{M}\\mathbf{o}\\mathbf{S}_{2}$ NS with increased content of both could meet this requirement. Recently, a liquid ammonia-assisted lithiation (LAAL) strategy was developed to exfoliate 2D layered materials.35 Here, we used this strategy to synthesize novel mesoporous 1T-phase $\\mathsf{M o S}_{2}$ NS $\\left(\\mathrm{P-1T}\\mathrm{MoS}_{2}\\right),$ ) with many edge sites and a large concentration of S-vacancies for the first time (Figure 1). Due to the severe desulfurization reaction between lithium and $\\mathbf{MoS}_{2}$ , such unique mesoporous 1T-phase $\\mathsf{M o S}_{2}$ NS not only exhibit superior catalytic performance but also serve as an ideal platform for probing the roles of phase, edges, and S-vacancies in 1T-phase $\\mathbf{MoS}_{2}$ for HER in a holistic way. Additionally, another four representative samples including mesoporous 2H-phase $\\mathbf{MoS}_{2}$ NS $({\\mathrm{P}}{-}2{\\mathrm{H}}{\\mathrm{MoS}}_{2})$ ), mesoporous 2H-phase $\\mathbf{MoS}_{2}$ NS after sulfur compensation $(\\mathrm{P}\\mathrm{-}2\\mathrm{H}$ $\\begin{array}{r}{\\mathbf{MoS}_{_{2}+}\\mathbf{S},}\\end{array}$ ), 1T-phase $\\mathbf{MoS}_{2}$ NS (1T $\\mathrm{MoS}_{2})$ , and 2H-phase $\\mathbf{MoS}_{2}$ NS $\\left(2\\mathrm{H}\\mathrm{MoS}_{_{2}}\\right)$ were also prepared as model systems for a comprehensive investigation of the key factors influencing the HER catalysis of $\\mathbf{MoS}_{2}$ . This study shows that in addition to the crystal phase that was determined to be the key factor in the HER catalytic activity of $\\mathrm{P-}\\mathrm{1T}$ $\\mathrm{MoS}_{{\\scriptscriptstyle2}},$ both S-vacancies and the edges also contribute significantly. The superior HER performance of the $\\mathrm{P-}\\mathrm{1T}$ $\\mathbf{MoS}_{2}$ NS can be ascribed to the cooperative effect of phase, edges, and S-vacancies. This study provides a unique opportunity to understand the intrinsic electrocatalytic nature in $\\mathrm{MoS}_{{\\scriptscriptstyle2}},$ which allow us to achieve a superior HER performance with only pure $\\mathbf{MoS}_{2}$ and may pave the way for the further design of $\\mathbf{MoS}_{2}$ -based electrocatalysts for HER and other applications. \n\n# ■MATERIALS AND METHODS \n\nMaterials. $\\mathsf{M o S}_{2}$ $(99.99\\%)$ , metal lithium $(99.999\\%)$ , sulfur powder $(99.99\\%)$ , N-methylpyrrolidone (NMP) $(99.99\\%)$ ), were purchased from Alfa Aesar Chemical Co., Ltd. n-Butyl lithium $(99.99\\%)$ ) was purchased from Aladdin. All the reagents were used without any further purification. \n\n# Synthesis of the Materials. \n\nMesoporous 1T-phase $\\mathbf{MoS}_{2}$ Nanosheets $\\begin{array}{r}{(\\mathbf{P-1T\\MoS}_{2})}\\end{array}$ ). The preparation of P-1T $\\mathbf{MoS}_{2}$ from bulk $\\mathsf{M o S}_{2}$ materials was carried out by a three step lithiation process using lithium-liquid ammonia medium similar to a previous work (Figure 1).35 In Step $\\mathrm{I},\\sim\\mathbf{o}.5\\ \\mathrm{g}$ bulk $\\mathsf{M o S}_{2}$ powder and lithium pieces with a molar ratio of 1:5 were loaded in a test tube (Figure S1a) in an argon-filled glove box to prevent air and water contamination. The testing tube was then dipped into a liquid nitrogen bath and evacuated to a pressure of $5{\\times}10^{-4}$ Pa. High purity ammonia gas was introduced into the tube and condensed into ${\\sim}12$ mL of liquid in which bulk $\\mathsf{M o S}_{2}$ powder was immersed \n\n# Journal of the American Chemical Society \n\n(Figure S1b). The lithiation reaction started when the liquid ammonia contacted with lithium, with the blue color (the characteristic color of $\\left.\\mathrm{e}{-}(\\mathrm{NH}_{3})_{n}\\right)$ gradually fading within 30 min (Figure S1c). In Step II, the liquid ammonia was carefully removed by evaporation (Figure S1d). After the intercalation process, the Li-intercalated sample was exfoliated and ultrasonicated in deionized water for 30 min, during which a large number of bubbles were observed and an opaque suspension was produced (Figure S1e). In Step III, the suspension was centrifuged at 1,500 RPM to remove the residual unexfoliated $\\mathsf{M o S}_{2}$ particles and washed five times with deionized water to isolate the $\\mathrm{P-1TMoS}_{2}$ . Mesoporous 1T-phase $\\mathbf{MoS}_{2}$ samples prepared with different molar ratios of lithium and $\\mathsf{M o S}_{2}$ (1:1, 2:1, 3:1, and 4:1) were also obtained following this route. \n\nMesoporous 2H-phase $\\mathbf{MoS}_{2}$ Nanosheets $\\left(\\mathbf{P}{-}2\\mathbf{H}\\mathbf{M}\\mathbf{o}\\mathbf{S}_{2}\\right)$ ). P-2H $\\mathbf{MoS}_{2}$ was prepared through a simple annealing process from P-1T $\\mathsf{M o S}_{2}$ (Step IV in Figure 1). About $\\mathbf{15~mg}$ of as-prepared P-1T $\\mathbf{MoS}_{2}$ was loaded in an alumina boat and placed in a single-zone tube furnace. The reactor was evacuated and flushed five times with high-purity argon $(99.999\\%)$ before heated to $550^{\\circ}\\mathrm{C}$ with a ramp rate of $\\sim5$ $^\\mathrm{{{\\circ}}}C/\\mathrm{{min}}$ under an argon flow of \\~ 50 sccm and maintained at $550^{\\circ}\\mathrm{C}$ for 2h to ensure a complete transition from 1T to 2H-phase. After that, the furnace was cooled to room temperature naturally with a flow of \\~ 100 sccm argon. \n\nSulfur compensated Mesoporous 2H-phase $\\mathbf{MoS}_{2}$ Nanosheets $\\left(\\mathbf{P}{-}2\\mathbf{H}\\mathbf{MoS}_{2}{+}\\mathbf{S}\\right)$ ). An alumina boat loaded with ${\\sim}8\\mathrm{mg}\\mathrm{P}{\\cdot}2\\mathrm{H}\\mathrm{MoS}_{\\scriptscriptstyle2}$ was placed at the downstream end of the tube furnace. Then, $\\sim{\\bf1}\\mathrm{~g~}$ sulfur powder in another alumina boat was positioned at the upstream end of the quartz tube. The distance between the two boats was \\~ 30 cm. Tube furnace was then evacuated and high purity argon was flowed at \\~ 50 sccm for 20 min while the temperature was ramped to $550~^{\\circ}\\mathrm{C}$ . The temperature was held for $^{2\\mathrm{~h~}}$ at $550^{\\circ}\\mathrm{C}$ with 80 sccm argon carrier gas flow. Finally, the furnace was then naturally cooled down to room temperature. \n\n2H-phase $\\mathbf{MoS}_{2}$ Nanosheets $(\\mathbf{2H\\MoS_{2}},$ ). The ultrathin 2H $\\mathsf{M o S}_{2}$ was obtained by liquid exfoliation of bulk $\\mathsf{M o S}_{2}$ powders in NMP.36 About 100 mg of bulk $\\mathsf{M o S}_{2}$ powder was dispersed in 10 mL NMP and then ultrasonicated for 10 h followed by $_{24}\\mathrm{~h~}$ standing. The as-formed suspension was then centrifuged at $\\sim_{3},000$ RPM to remove the residual unexfoliated $\\mathbf{MoS}_{2}$ . After centrifugation, the top one-third of the suspension was extracted by pipetting. \n\n1T-phase $\\mathbf{MoS}_{2}$ Nanosheets $\\mathbf{\\Gamma}(\\mathbf{u}\\mathbf{T}\\ \\mathbf{M_{O}}\\mathbf{S_{2}},$ ). The preparation of 1T $\\mathbf{MoS}_{2}$ was performed in an argon-filled glove box.15 About $\\mathbf{0.5~g}$ bulk $\\mathsf{M o S}_{2}$ powder was soaked in 40 mL $\\mathbf{n}$ -butyl lithium $(2.7\\mathrm{M}$ in heptane) in a sealed vial at room temperature for $>72\\mathrm{~h~}$ , and subsequently exfoliated by the reaction between the intercalated lithium with water. Excess $\\mathbf{n}$ -butyl lithium was removed by rinsing the samples with dry heptane followed by deionized water. \n\nStructural Characterization. XRD measurements were performed on a Rigaku D/max 2500 $\\mathrm{\\DeltaX}$ -ray diffractometer using Cu Kα radiation. High-angle annular dark-field (HAADF) imaging was performed using a JEOL ARM 200F (JEOL, Tokyo) transmission electron microscope. The attainable resolution defined by the probe forming objective lens was $<80$ picometers. The raw images were processed with an average background subtraction filter (ABSF) to reduce noise. The thickness of $\\mathbf{MoS}_{2}$ NS was analyzed by atomic force microscopy (AFM) on a Bruker DI MultiMode-8 system. X-ray photoelectron spectra were recorded on an ESCALAB MKII using an Al $\\mathrm{K}\\upalpha$ excitation source. Raman spectra were collected on a Renishaw inVia confocal micro-Raman spectroscopy system using a TE air-cooled $576\\times400$ CCD array with a 633 nm excitation laser. \n\n![](images/502c39aa7b35184cac6a8b703b8e0a384ea58e314b75666662449ce3b5c84ad8.jpg) \nFigure 2. Morphology and structure characterizations of P-1T $\\mathbf{MoS}_{2}$ nanosheets. (a) low-resolution STEM image. (b) high-resolution STEM image (c) SAED pattern corresponding to (a). (d) AFM image. \n\nElectron Spin Resonance Spectroscopy Measurement. Electron spin resonance (ESR) measurements were performed on a Bruker ER 200D spectrometer at room temperature. The as-prepared samples of $\\mathrm{\\sim28~mg}$ were loaded in a quartz tube. The microwave frequency was maintained in the range from $9.8591\\mathrm{-}9.8599$ G $\\mathrm{Hz}$ \n\n# Journal of the American Chemical Society \n\n(X-band) and the microwave power was fixed at \\~ 20 mW to avoid saturation. \n\nPositron Annihilation Measurement. As-obtained samples were pressed into two pellets with a thickness of \\~1mm. A sandwiched structure of the sample-source-sample (e.g. P-1T $\\mathsf{M o S}_{2}/\\mathsf{N a}$ source/P-1T $\\mathbf{MoS}_{2}^{\\cdot}$ ) were utilized for the positron lifetime spectroscopy (PALS) experiments performed on a fast-slow coincidence ORTEC system with a time resolution of \\~195 ps at full width half-maximum. More than two million counts were accumulated for each spectrum to reduce the statistical error in the calculation of lifetimes. Positron lifetime spectra were de-convoluted and analyzed using the LT- $9$ program.37 \n\nElectrode Preparation and Electrochemical Characterization. Electrochemical measurements were performed with a standard three-electrode setup (CH Instruments) using $\\mathrm{Ag/AgCl}$ (in $_{3\\cdot5}\\mathrm{M}$ KCl solution) as the reference electrode, a graphite rod (Alfa Aesar, $99.9995\\%$ ) as the counter electrode, and glassy carbon electrode (3 mm in diameter) coated with $\\mathsf{M o S}_{2}$ catalysts as the working electrode in a rotating disk electrode (RDE) operating at 2,000 RPM. The catalyst was ultrasonically dispersed in a water-ethanol solution $\\left(\\mathbf{v}/\\mathbf{v}\\ 3\\mathbf{:}\\mathbf{1}\\right)$ containing 0.1 wt $\\%$ Nafion, and a drop of the catalyst (5 μL, 2.0 $\\mathrm{mg/mL})$ was then transferred onto the glassy carbon electrode serving as a working electrode. The amount of deposited solid mass was calculated to be 10 $\\upmu\\mathrm{g},$ yielding an estimated catalyst loading of $\\mathbf{0.14\\pm0.01\\mg/cm^{2}}$ on the glassy carbon electrode with a geometric area of $\\mathbf{o.o7~cm}^{2}$ All measurements were performed in $\\mathrm{H}_{2}$ -saturated $\\mathbf{0.5\\M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ (aq) and measured using a linear sweep with a scan rate of $5~\\mathrm{mV}~\\mathrm{s}^{-1}$ . Cyclic voltammograms at various scan rates (20, 40, 60, 80, 100, 120, 140, 160, & $180\\ \\mathrm{mV/s},$ ) were collected in the 0.1–0.2 V vs. RHE range and used to estimate the double-layer capacitance. The electrochemical impedance spectroscopy (EIS) measurements were carried out at $250~\\mathrm{mV}$ overpotential with the frequency ranging from 106 to ${\\bf{0.1H z}}$ . To better compare the true catalytic activity of the different catalysts, we used the series resistance determined from EIS experiments to correct the polarization measurements and subsequent Tafel analysis for the $i R$ losses. All of the potentials were referenced to a reversible hydrogen electrode (RHE). \n\n# ■RESULTS AND DISCUSSION \n\nP-1T $\\mathbf{MoS}_{2}$ was successfully synthesized by the LAAL method with a molar ratio of lithium to $\\mathsf{M o S}_{2}$ at 5:1 as illustrated in Figure 1 (Steps I-III, see details in Experimental Section) and scanning transmission electron microscopy (STEM) (Figure 2a) was used to verify the ultrathin characteristics of the as-prepared samples. Furthermore, high resolution STEM (Figure 2b) demonstrates the porous features as denoted by the red arrows, which are in clear contrast to previously reported $\\mathbf{1}\\mathrm{T}\\mathbf{-}\\mathbf{M}\\mathbf{o}\\mathbf{S}_{2}$ NS exfoliated using n-butyl lithium.15 The selected area electron diffraction (SAED) pattern (Figure 2c) demonstrates a typical hexagonal spot pattern corresponding to 2H-phase $\\mathsf{M o S}_{2}$ and an extra strong hexagonal spot at $30^{\\circ}$ between the hexagonal spots assigned to the 1T-phase $\\mathbf{MoS}_{2}$ .38 The thickness of the as-synthesized samples was evaluated by tapping mode AFM (Figure 2d) with topographic height of $\\sim1.5\\ \\mathrm{nm}$ , suggesting the P-1T $\\mathbf{MoS}_{2}$ NS have a nearly uniform thickness of $\\sim1-2$ layers. The absence of diffraction peaks in XRD pattern (Figure $S_{2}$ ) clearly demonstrated that the long-range stacking order of the layers along the c axis was destroyed and the bulk $\\mathsf{M o S}_{2}$ was efficiently exfoliated into NS of single or few layers. Characterization of other porous samples prepared with different molar ratios of $\\mathsf{M o S}_{2}$ and lithium reveals the evolution of mesoporous structures and increased content of 1T-phase $\\mathsf{M o S}_{2}$ with increased lithiation (Figure $S_{3^{-}}S_{5}$ and Table S1). The P-1T $\\mathsf{M o S}_{2}$ NS sample prepared with a molar ratio of lithium to $\\mathbf{MoS}_{2}$ at 5:1 was selected as the representative sample in the following discussion due to its saturated content of 1T phase and most prominent mesoporous features. The as-prepared P-1T $\\mathbf{MoS}_{2}$ NS were subsequently converted into $\\mathrm{P}{-}2\\mathrm{H}\\ \\mathrm{MoS}_{2}$ NS by annealing at $550~^{\\circ}\\mathrm{C}$ in argon (Step IV in Figure 1), with further annealing in sulfur vapor to (partially) compensate the S-vacancies at the same temperature and generate the P-2H $\\begin{array}{r}{\\mathbf{MoS}_{2}{+}\\mathbf{S}}\\end{array}$ sample. High-resolution STEM images of P-2H $\\mathbf{MoS}_{2}$ and P-2H $\\begin{array}{r}{\\mathbf{MoS}_{2}{+}S}\\end{array}$ indicate that the porous features of P-1T $\\mathsf{M o S}_{2}$ can be well maintained during the annealing process (Figure S6). For comparison, reference samples of $2{\\mathrm{H}}{\\mathrm{-}}{\\mathrm{MoS}}_{2}$ and $\\mathbf{1}\\mathrm{T}\\mathbf{-}\\mathbf{M}\\mathbf{o}\\mathbf{S}_{2}$ were obtained following previous reports.15,36 It has been reported that the layer number of $\\mathsf{M o S}_{2}$ material can greatly affect its HER activity,39-41 and here five representative samples with the same thickness (layer number) are selected for further study in order to eliminate the influence of the layer numbers (see AFM in Figure $S_{7}$ ). \n\nA comparison of the Raman features of P-1T, 1T, $P-2H$ , $\\mathrm{P}{-}2\\mathrm{H}{+}S$ , and $2\\mathrm{H}\\mathrm{MoS}_{2}\\mathrm{NS}$ with the bulk $\\mathsf{M o S}_{2}$ is shown in Figure 3a. Due to the difference of the symmetry elements in crystal structures, the emergence of new Raman modes located at \\~195, 218, and $351~\\mathrm{{cm}^{-1}}$ observed in $\\mathbf{\\Omega}_{\\mathrm{1T}}$ samples provides convincing evidence of the structural transition from pristine 2H to 1T-phase $\\mathbf{MoS}_{2}$ .42,43 High resolution XPS measurements then were performed to further quantify the extent of the 1T-phase (Figure 3b). For $\\boldsymbol{\\mathsf{2}}\\boldsymbol{\\mathrm{H}}$ -phase $\\mathbf{MoS}_{2}$ , Mo $_{3}d$ spectra consist of peaks at around 229.4 and $232.5\\mathrm{eV}$ corresponding to the Mo $3d_{5/2}$ and Mo $3d_{3/2}$ components, respectively. Notably, an obvious red-shift for both the Mo $3d_{5/2}$ and Mo $3d_{3/2}$ peaks to the lower binding energies by \\~ 0.81 eV and 0.75 eV were observed in 1T-phase $\\mathsf{M o S}_{2}$ and are consistent with previous reports.32 Quantification of these peaks reveals that a maximum value of \\~ $82\\%$ 1T-phase (Figure S8) was obtained by the LAAL route, similar to that prepared by using lithium borohydride $(\\mathrm{LiBH}_{4})$ .32 Similarly, with respect to the $\\mathrm{~S~}_{2p}$ peak, an obvious shift towards lower binding energies due to a structure transition from 2H- to 1T-phase $\\mathbf{MoS}_{2}$ was also observed (Figure S9). \n\n# Journal of the American Chemical Society \n\n![](images/10e5dafe16ce9a8c1b6418cf74f42c0e9189ed2cdacff81b33083bdbd926af25.jpg) \nFigure $^3$ . Structure characterization of the representative $\\mathbf{MoS}_{2}$ nanosheets. (a) Raman spectra and (b) XPS spectra for P-1T, 1T, $P-2H$ $\\mathrm{P}{-}2\\mathrm{H}{+}S$ , and 2H $\\mathbf{MoS}_{2}$ NS in contrast with the bulk $\\mathbf{MoS}_{2}$ powder. \n\nNext, we measured the electrochemical characteristics of various $\\mathbf{MoS}_{2}$ samples drop-casted on glassy carbon electrodes toward the HER catalytic performance using a rotating disk electrode (RDE) at a rate of 2,000 RPM in 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ in comparison to a platinum wire (see Experimental Section for details). The key electrochemical results are also listed in Table 1. Figure 4a shows that P-1T, 1T, P-2H, $\\mathrm{P}{-}2\\mathrm{H}{+}S$ , and 2H $\\mathsf{M o S}_{2}$ can achieve a geometric catalytic current density of 10 $\\mathrm{\\mA}{\\cdot}\\mathrm{cm}^{-2}$ at overpotentials $(\\eta)$ of 154, 202, 219, 257, and 334 $\\mathrm{mV}$ (vs. RHE after $i R$ correction), respectively (see Table 1) The featureless polarization curve indicates that bulk $2\\mathrm{H}$ $\\mathsf{M o S}_{2}$ powder provides almost negligible HER activity. From the extrapolation of the linear region of overpotential $(\\eta)$ vs. log $j$ (Figure 4b), we obtained Tafel slopes of 43, 48, 62, 82, and $\\mathrm{106~mV}$ per decade (after iR correction) for P-1T, 1T, P-2H, $\\mathrm{P}{-}2\\mathrm{H}{+}S.$ , and 2H $\\mathrm{MoS}_{{\\scriptscriptstyle2}},$ respectively (Table 1). Such low Tafel slope values around 40 mV/decade for P-1T and 1T $\\mathsf{M o S}_{2}$ suggest a two-electron transfer process,44 which is smaller than that of many other reported $\\mathbf{MoS}_{2}.$ -based HER catalysts9,12,34 and indicates efficient kinetics of $\\mathrm{H}_{2}$ evolution. The low overpotential of P-1T $\\mathsf{M o S}_{2}$ $\\mathrm{\\Delta_{154}m V}$ vs. RHE for achieving 10 $\\mathrm{mA}/\\mathrm{cm}^{2})$ is better than or at least comparable to most of the reported phase-pure $\\mathbf{MoS}_{2}$ -based HER catalysts (or $\\mathbf{MoS}_{2}$ nanocarbon composites).14,15,32,45-47 From the intercept of the linear region of the Tafel plots, geometrical exchange current densities $(j_{\\mathrm{o,geometrical}})$ of 15.8, 12.6, 10.5, 7.9, and $3.2\\ \\upmu\\mathrm{A}\\ \\mathrm{cm}^{-2}$ were obtained for P-1T, 1T, $\\mathrm{P}{-}2\\mathrm{H}$ , $\\mathrm{P}{-}2\\mathrm{H}{+}S$ , and ${\\mathsf{2H M o S}}_{2}$ , respectively. The remarkable j0,geometrical, value again suggests the excellent HER catalytic activity of P-1T $\\mathrm{MoS}_{2},$ , with more effective active sites originated from its unique structure characteristics. \n\n![](images/34d9ad0108c38820fb4f3b0b0b2fb3dccf41bbe6c1566494ed9b560a2ac70109.jpg) \nFigure 4. Electrochemical characterization of various $\\mathbf{MoS}_{2}$ samples for HER catalysis. (a) $J{-}V$ curves after $i R$ correction show the catalytic performance of various $\\mathbf{MoS}_{2}$ samples in comparison to a $\\mathrm{Pt}$ wire; (b) Tafel plots for the data presented in (a); (c) Plots showing the extraction of the $C_{\\mathrm{dl}}$ for different $\\mathbf{MoS}_{2}$ samples; and (d) Electrochemical impedance spectroscopy (EIS) Nyquist plots for various $\\mathbf{MoS}_{2}$ samples. All the measurement was carried out with catalyst loading of $\\mathbf{0.14\\pm0.01\\mg/cm^{2}}$ on the glassy carbon electrode. \n\nTo probe the difference in HER performance by the various $\\mathbf{MoS}_{2}$ samples, we measured the double-layer capacitance $(C_{\\mathrm{dl}})$ derived from the cyclic voltammogrametry measurement results (Figure S10), which is proportional to the effective electrochemically active surface area (ECSA). Capacitive current was plotted \n\n# Journal of the American Chemical Society \n\nas a function of scan rate to extract the $C_{\\mathrm{dl}}$ (Figure 4c), whose slope is equivalent to twice the value of $C_{\\mathrm{dl}}$ . The calculated $C_{\\mathrm{dl}}$ values were 63.1, 23.8, 8.2, 5.9, and 0.3 $\\mathrm{mF}{\\cdot}\\mathrm{cm}^{-2}$ for P-1T, 1T, P-2H, $P-2H+S_{2}$ , and 2H $\\mathbf{MoS}_{2}$ , respectively (Table 1). This indicates that 1T phase $\\mathsf{M o S}_{2}$ samples display higher exposure of catalytically active sites. Furthermore, when comparing P-1T with 1T $\\mathrm{MoS}_{_{2}},$ , introducing more edges and S-vacancies creates more HER-active sites, verifying the effect of edges and S-vacancies in HER catalysis, which was also observed for $P-2H$ and ${\\sf2H\\ M o S_{2}}$ . After sulfur compensation, the ECSA was reduced in comparison between $\\mathrm{P}{\\cdot}{2}\\mathrm{H}\\mathrm{MoS}_{2}$ and $P-2H$ $\\begin{array}{r}{\\mathbf{MoS}_{2}{+}\\mathbf{S}_{2}}\\end{array}$ , an indication that the S-vacancies may promote the HER activity by way of providing more active sites. \n\nFurthermore, the electrochemical stability of the P-1T $\\mathsf{M o S}_{2}$ NS was also demonstrated. Obviously, after 1000 cycles (or 20000 s) of continuous operation, as-synthesized P-1 $\\because M o S_{\\scriptscriptstyle2}$ NS displayed $<7\\%$ $({\\bf{15\\%}})$ decay, respectively, in the electrocatalytic current density (Figure S11). We also applied electrochemical impedance spectroscopy (EIS) to provide further insight into the electrode kinetics during HER. The Nyquist plots (Figure 4d) were fitted using an equivalent circuit inset in Figure 4d to extract the charge transfer resistance $(R_{\\mathrm{ct}})$ of 16, 30, 280, $558$ , and 928 $\\Omega$ for P-1T, 1T, $P-2\\mathrm{H}$ , $\\rho_{-2}\\mathrm{H}+S$ , and 2H $\\mathbf{MoS}_{2}.$ , respectively (Table 1). The $R_{\\mathrm{ct}}$ of both 1T $\\mathsf{M o S}_{2}$ samples is at least one order of magnitude smaller than that of 2H $\\mathbf{MoS}_{2}$ , \n\nTable 1. Summary of the electrocatalytic parameters, ESR signal, and positron lifetime parameters for various $\\mathsf{M o S}_{2}$ NS samples in contrast with bulk $\\mathbf{MoS}_{2}$ powder. \n\n\n
Samples\"(my vsr j=-10 mA cm-²Tafel slope (mV dec-l)Ca(mF cm-2)(Ω2) Rctjo, geometrical (μA cm²)ESR Intensit y of S (x103 a.u./mg)Positron lifetime parameters
T (ps)1 (%)T (ps)I (%)
P-1T MoS21534363.11615.81.67 ±0.06172.4 ±6.243.0 ±0.4346.1 ±5.455.5 ±0.5
P-2H MoS2218628.228010.50.81 ±0.08183.8 ±1.143.9 ±0.6334.9 ±2.854.5 ±0.6
P-2H MoS+S257825.95587.91.76 ±0.05179.9 ±6.843.2 ±0.5356.7 ±7.252.9 ±0.6
1T MoS22034823.83012.63.36 ±0.10175.1 ±4.758.9 ±0.8361.6 ±5.440.1 ±0.5
2H MoS23431060.39283.21.87 ±0.05171.1 ±1.762.2± 0.8315.5 ±5.536.2 ±0.6
Bulk MoS21.91 ±0.02170.0 ±4.066.4 ±1.0321.8 ±9.532.2 ±0.8
\n\nwhich suggests an ultrafast Faradaic process and thus superior HER kinetics. The smallest $R_{\\mathrm{ct}}$ from P-1T $\\mathsf{M o S}_{2}$ is attributed to its unique structure in addition to phase, where more edges and S-vacancies are introduced during the LAAL lithiation process. Furthermore, sulfur compensation almost doubles the $R_{\\mathrm{ct}}$ value of $\\mathrm{P-2H~MoS_{2}+S}$ as compared to that of P-2H $\\mathbf{MoS}_{2}$ and is another indication that S-vacancies also facilitates charge transfer during HER. The catalytic turnover frequency (TOF) has also been estimated (See Supporting Information),48 which is about $\\mathbf{o}.5\\ \\mathrm{H}_{2}\\ \\mathbf{s}^{\\cdot}$ $\\mathbf{s}^{-1}$ per surface site for the representative P-1T $\\mathbf{MoS}_{2}$ sample. \n\nThe comprehensive comparison of the electrochemical performances from these representative $\\ensuremath{\\mathbf{MoS}}_{2}$ samples above (Table 1) reveals several important points. First, the 1T phase (including both conventional 1T and porous 1T) $\\mathbf{MoS}_{2}$ always demonstrates superior HER catalytic activity than the corresponding 2H phase, consistent with previous studies.15,16,32 Of note is that increasing the density of edges, as found in the P-1T $\\mathsf{M o S}_{2}$ and P-2H $\\mathbf{MoS}_{2}$ samples, can further improve the catalytic performance because the edge-terminated features can ensure an isotropic electron transport as compared to their bulk morphologies.45 More importantly, porous 1T $\\mathbf{MoS}_{2}$ does perform better than 1T $\\mathrm{MoS}_{2},$ , which suggests that the edges in 1T $\\mathbf{MoS}_{2}$ NS are still important for catalytic activity. However, the contribution of S-vacancies to the HER catalysis also should not be neglected as it manifests as a decrease in the overpotential of $P-2H$ $\\begin{array}{r}{\\mathbf{MoS}_{2}{+}\\mathbf{S}}\\end{array}$ when sulfur was replenished to $P{-}2\\mathrm{H}\\mathrm{MoS}_{2}$ to reduce S-vacancies. Though quantitative determination of the edges is not available currently, the positive effect of S-vacancies has been clearly revealed in our case. These electrochemical data clearly indicate that the HER activity of the $\\mathsf{M o S}_{2}$ samples is dominated by a cooperative effect of crystal phase, concentration of edges, and S-vacancies. \n\nTo further study the contribution of S-vacancies in $\\mathsf{M o S}_{2}$ for HER, we employed electron spin resonance (ESR) spectroscopy to provide fingerprint information for paramagnetic (PM) signal. Among them, the $s$ signal observed at \\~ 3500 G $(g=1.9^{1-2.003})$ can be ascribed to the contribution from Mo-S dangling bonds,49,50 where a higher intensity indicates less S-vacancies. As shown in Figure 5 and Table 1, the S signal increases significantly from pristine bulk $\\mathbf{MoS}_{2}$ $\\mathrm{'}{\\sim}1.91{\\times}10^{3}\\mathrm{a.u.}/\\mathrm{mg})$ to 1T $\\mathbf{MoS}_{2}$ $\\left(\\sim3{\\cdot}36{\\times}10^{3}\\mathrm{a.u.}/\\mathrm{mg}\\right)$ due to the expansion of the Mo-S bond during the formation of the 1T-phase. Significant reduction in $s$ signal intensity of P-1T $\\mathsf{M o S}_{2}$ as compared to that of $\\mathbf{1}\\mathrm{T}\\mathbf{-}\\mathbf{M}\\mathbf{o}\\mathsf{S}_{2}$ reveals an obvious increase of S-vacancies introduced during the harsh lithiation process of LAAL. The annealing process that transformed the crystal structure from $\\mathrm{P-1T}$ to P-2H $\\mathbf{MoS}_{2}$ , accompanied by partial reconstruction of Mo-S bonding, led to a significantly decreased $s$ signal from $\\mathbf{\\widetilde{\\Gamma}}_{\\sim1.67}\\times\\mathbf{10}^{3}$ to \\~ $\\mathbf{0.81\\times10^{3}}$ a.u./mg. Subsequently, it follows that the $s$ signal was enhanced from P-2H $\\mathsf{M o S}_{2}$ to P-2H $\\begin{array}{r}{\\mathbf{MoS}_{2}{+}\\mathbf{S}}\\end{array}$ as the concentration of S-vacancies was reduced after sulfur compensation. Furthermore, with the increase in the molar ratio of $\\mathsf{M o S}_{2}$ to lithium from 1:1 to 1:5 in the various porous samples prepared via LAAL, the value of $s$ signal exhibited a decrease from ${\\sim}3.22{\\times}10^{3}$ to $\\sim1.67\\times10^{3}\\mathrm{a.u./mg}$ (Figure S12 and Table $S_{2}$ ), suggesting a gradual increase of the S-vacancy concentration in P-1T $\\mathbf{MoS}_{2}$ samples. \n\n![](images/3b24b65fef13a710ac0ca41ea0c906724e3c05523fe47fb4a19c11bf3f080f7a.jpg) \nFigure 5. Electron spin resonance (ESR) spectra for various $\\mathbf{MoS}_{2}$ samples. The $s$ signal is ascribed to the contribution from Mo-S dangling bonding, and a higher intensity indicates lower concentration of S-vacancies. \n\nTo provide direct information on the S-vacancies with ppm-level sensitivity in various $\\mathsf{M o S}_{2}$ samples, we further employed positron annihilation lifetime spectroscopy (PALS).51,52 Normally, the positron lifetime spectra (Figure $\\mathrm{S}_{13}\\rangle$ ) can be fit to an exponential function of three components corresponding to different annihilation sites. Herein, the long lifetime of more than 2 ns, usually assigned to the annihilations at voids/surface, was not considered owing to its negligible contribution.53 Then, we only consider two lifetime components in PALS spectra, $\\tau_{\\mathrm{{r}}}$ , and $\\tau_{2}$ , with relative intensities $I_{\\mathrm{{}_{1}}}$ , and $I_{\\O_{2}}$ (Table 1). The predominant shorter component $\\mathit{\\check{\\tau}}_{1},\\ 170\\ \\pm\\ 5\\$ ps) was assigned to the bulk lifetime of $\\mathbf{MoS}_{2}$ , while another longer life component $\\left(\\tau_{2},321.8\\pm7\\right.$ ps) was attributed to the positron annihilation corresponding to S-vacancies.54,55 This is what we will focus our discussion on. The relative concentration of S-vacancies can be determined from the relative intensity I. $I_{\\O_{2}}$ of ${\\sf2H M o S}_{2}$ is a little higher than that of bulk $\\mathrm{MoS}_{{\\scriptscriptstyle2}},$ , revealing very limited S-vacancies in ${\\sf2H\\ M o S_{2}}$ . After lithiation, the S-vacancies become dominant in the P-1T, $\\mathrm{P}{-}2\\mathrm{H}$ , and $\\mathrm{P}{-}2\\mathrm{H}{+}S$ samples, with $I_{\\O_{2}}$ exceeding $\\sim52\\%$ . Furthermore, as shown in Table S2, the content of S-vacancies gradually increases with increasing ratio of lithium to $\\mathsf{M o S}_{2}$ in various porous $\\mathsf{M o S}_{2}$ samples prepared via the LAAL process due to the enhanced desulphurization reaction, in good agreement with the ESR results above. From $\\mathrm{P-}\\mathrm{1T}$ to $\\mathrm{P}{-}2\\mathrm{H}$ , it was found that although the quantity of Mo-S bonding decreased, the content of S-vacancies remained unchanged. This further confirms the critical role of phase for HER catalytic activity of $\\mathsf{M o S}_{2}$ while the contributions from edges and S-vacancies are kept constant. When comparing $P-2H$ and $\\mathrm{P}{-}2\\mathrm{H}{+}S$ , the slight decrease in $I_{\\mathrm{{2}}}$ indicates that S-vacancies were partially restored by sulfur compensation successfully. It is worth noting that not all of the sulfur was utilized to fill in the S-vacancies, but also to form new Mo-S dangling bonds simultaneously, as revealed by an increased S signal in ESR from \\~ $\\mathbf{0.81\\times10}^{3}$ to $\\mathbf{1.76\\xio^{3}}$ a.u./mg. Finally, from $\\mathrm{P}{-}2\\mathrm{H}{+}S$ to $\\mathrm{P}{-}2\\mathrm{H}\\ \\mathrm{MoS}_{2}$ , it can observed that with all other factors being equal, the increased S-vacancy concentration can lead to enhanced HER catalytic activity independent of whether the S-vacancies come from the edges or the basal plane, which is consistent with a recent report.33 \n\nBoth ESR and PALS characterization techniques above provide convincing evidences to reveal and quantify S-vacancies and confirm their influence on HER catalysis. As a result, we can conclude that: (i) comparing P-1T with P-2H $\\mathbf{MoS}_{2}$ , similar $I_{\\O_{2}}$ values suggest that phase rather than edges or S-vacancies dominates the electrocatalytic activity of $\\mathbf{MoS}_{2}$ ; (ii) comparing $\\mathrm{P-}\\mathrm{1T}$ with 1T $\\mathbf{MoS}_{2}$ , both edges and S-vacancies also play important roles in determining the superior HER performance in P-1T $\\mathbf{MoS}_{2}$ ; (iii) from comparing $P-2H$ and $\\mathrm{P}{-}_{2}\\mathrm{H}{+}\\mathrm{S}$ with identical content of edges and same crystal phase, increased content of S-vacancies improves the HER performance. The enhanced catalytic activity and superior HER catalytic performance in P-1T $\\mathbf{MoS}_{2}$ was therefore attributed to the cooperative effect of phase, edges, and S-vacancies. \n\n# ■CONCLUSIONS \n\nIn summary, we have used a series of representative (and in some cases unique) samples, including porous 1T, porous 2H, porous $2\\mathrm{H}+\\mathrm{S}$ , 1T, and ${\\mathsf{2H\\ M o S_{2}}}$ nanosheets, to systematically probe the contributions of phase, edges, and S-vacancies to the HER catalytic activity by utilizing Raman, XPS, and electrochemical impedance spectroscopy, as well as electron spin resonance and positron annihilation lifetime spectroscopy. These comprehensive studies conclusively show that not only the crystal phase serves as the key role in determining the HER catalytic activity in both conventional $\\mathbf{\\Omega}_{\\mathrm{1T}}$ and porous 1T phase $\\mathsf{M o S}_{2}$ nanosheets, but also the edges and S-vacancies make significant contributions to the electrocatalytic properties of $\\mathbf{MoS}_{2}$ . Due to the cooperative effects of the phase, S-vacancies, and edges, high intrinsic HER activity can be obtained on the porous \n\n1T $\\mathbf{MoS}_{2}$ nanosheets, with $\\eta=153~\\mathrm{mV}$ vs RHE for $j=-10$ mA $\\mathrm{cm}^{-2}$ , a Tafel slope of $43~\\mathrm{mV}$ per decade, and higher electrochemically active surface area. This study provides new and comprehensive insights to reveal the critical factors that influence the catalytic activity of $\\mathbf{MoS}_{2}$ , which will enable the design and improvement of Earth-abundant electrocatalysts based on $\\mathsf{M o S}_{2}$ and other layered materials with further enhanced catalytic performance. \n\n# ■ACCOCIATED CONTENT \n\n# Supporting Information. \n\nFigure $\\mathrm{S}_{1^{-}}\\mathrm{S}_{13}$ , Table $S_{1^{-}S2}$ , and estimation of catalytic turnover frequency (TOF). This material is available free of charge via the Internet at http://pubs.acs.org. \n\n# ■AUTHOR INFORMATION \n\n# Corresponding Authors \n\npxu@hit.edu.cn; jin@chem.wisc.edu; songbo@hit.edu.cn; \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ■ACKNOWLEDGMENTS \n\nThis work is supported by the Major State Basic Search Program (No. 2014CB46505), Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant no. 10821201) and the National Natural Science Foundation of China (Grant Nos. 51172055, 51372056, 51472064, 21471039), Fundamental Research Funds for the Central University (Grant Nos. HIT.BRETIII.201220, HIT.NSRIF.2012045, HIT.ICRST.2010008, PIRS of HIT A201502), International Science & Technology Cooperation Program of China (2012DFR50020) and the Program for New Century Excellent Talents in University (NCET-13-0174). S.J. thanks support by the US Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering, under Award DE-FG02-09ER46664. \n\n# ■REFERENCES \n\n(1) Turner, J. A. Science 2004, 305, 972. (2) Lewis, N. S.; Nocera, D. G. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 15729. (3) Hou, Y.; Abrams, B. L.; Vesborg, P. C. K.; Björketun, M. E.; Herbst, K.; Bech, L.; Setti, A. M.; Damsgaard, C. D.; Pedersen, T.; Hansen, O.; Rossmeisl, J.; Dahl, S.; Nørskov, J. K.; Chorkendorff, I. Nature Mater. 2011, 10, 434. (4) Laursen, A. B.; Kegnaes, S.; Dahl, S.; Chorkendorff, I. Energy Environ. Sci. 2012, 5, 5577. (5) Morales-Guio, C. G.; Stern, L.-A.; Hu, X. Chem. Soc. Rev. 2014, 43, 6555. (6) Faber, M. S.; Jin, S. Energy Environ. Sci. 2014, 7, 3519. (7) Hinnemann, B.; Moses, P. G.; Bonde, J.; Jørgensen, K. P.; Nielsen, J. H.; Horch, S.; Chorkendorff, I.; Nørskov, J. K. J. Am. Chem. Soc. 2005, 127, 5308. (8) Lukowski, M. A.; Daniel, A. S.; English, C. R.; Meng, F.; Forticaux, A.; Hamers, R. J.; Jin, S. Energy Environ. Sci. 2014, 7, 2608. \n\n(9) Kong, D.; Wang, H.; Cha, J. J.; Pasta, M.; Koski, K. J.; Yao, J.; Cui, Y. Nano Lett. 2013, 13, 1341. (10) Morales-Guio, C. G.; Hu, X. Acc. Chem. Res. 2014, 47, 2671. (11) Benck, J. D.; Hellstern, T. R.; Kibsgaard, J.; Chakthranont, P.; Jaramillo, T. F. ACS Catal. 2014, 4, 3957. (12) Kibsgaard, J.; Chen, Z.; Reinecke, B. N.; Jaramillo, T. F. Nature Mater. 2012, 11, 963. (13) Vrubel, H.; Hu, X. ACS Catal. 2013, 3, 2002. (14) Xie, J.; Zhang, J.; Li, S.; Grote, F.; Zhang, X.; Zhang, H.; Wang, R.; Lei, Y.; Pan, B.; Xie, Y. J. Am. Chem. Soc. 2013, 135, 17881. (15) Lukowski, M. A.; Daniel, A. S.; Meng, F.; Forticaux, A.; Li, L.; Jin, S. J. Am. Chem. Soc. 2013, 135, 10274. (16) Wang, H.; Lu, Z.; Xu, S.; Kong, D.; Cha, J. J.; Zheng, G.; Hsu, P.-C.; Yan, K.; Bradshaw, D.; Prinz, F. B.; Cui, Y. Proc. Natl. Acad. Sci. U.S.A. 2013, 110, 19701. (17) Voiry, D.; Yamaguchi, H.; Li, J.; Silva, R.; Alves, D. C. B.; Fujita, T.; Chen, M.; Asefa, T.; Shenoy, V. B.; Eda, G.; Chhowalla, M. Nature Mater. 2013, 12, 850. (18) Faber, M. S.; Dziedzic, R.; Lukowski, M. A.; Kaiser, N. S.; Ding, Q.; Jin, S. J. Am. Chem. Soc. 2014, 136, 10053. (19) Kong, D.; Cha, J. J.; Wang, H.; Lee, H. R.; Cui, Y. Energy Environ. Sci. 2013, 6, 3553. (20) Popczun, E. J.; Read, C. G.; Roske, C. W.; Lewis, N. S.; Schaak, R. E. Angew. Chem. Int. Ed. 2014, 53, 5427. (21) Popczun, E. J.; McKone, J. R.; Read, C. G.; Biacchi, A. J.; Wiltrout, A. M.; Lewis, N. S.; Schaak, R. E. J. Am. Chem. Soc. 2013, 135, 9267. (22) Caban-Acevedo, M.; Stone, M. L.; Schmidt, J. R.; Thomas, J. G.; Ding, Q.; Chang, H.-C.; Tsai, M.-L.; He, J.-H.; Jin, S. Nature Mater. 2015, 14, 1245. (23) McKone, J. R.; Lewis, N. S.; Gray, H. B. Chem. Mater. 2014, 26, 407. (24) Jaramillo, T. F.; Jørgensen, K. P.; Bonde, J.; Nielsen, J. H.; Horch, S.; Chorkendorff, I. Science 2007, 317, 100. (25) Li, Y.; Wang, H.; Xie, L.; Liang, Y.; Hong, G.; Dai, H. J. Am. Chem. Soc. 2011, 133, 7296. (26) Tan, Y.; Liu, P.; Chen, L.; Cong, W.; Ito, Y.; Han, J.; Guo, X.; Tang, Z.; Fujita, T.; Hirata, A.; Chen, M. W. Adv. Mater. 2014, 26, 8023. (27) Islam, M. R.; Kang, N.; Bhanu, U.; Paudel, H. P.; Erementchouk, M.; Tetard, L.; Leuenberger, M. N.; Khondaker, S. I. Nanoscale 2014, 6, 10033. (28) Putungan, D. B.; Lin, S.-H.; Kuo, J.-L. Phys. Chem. Chem. Phys. 2015, 17, 21702. (29) Tsai, C.; Chan, K.; Nørskov, J. K.; Abild-Pedersen, F. Surf. Sci. 2015, 640, 133. (30) Fan, X.-L.; Yang, Y.; Xiao, P.; Lau, W.-M. J. Mater. Chem. A 2014, 2, 20545. (31) Lin, S.-H.; Kuo, J.-L. Phys. Chem. Chem. Phys. 2015, 17, 29305. (32) Voiry, D.; Salehi, M.; Silva, R.; Fujita, T.; Chen, M.; Asefa, T.; Shenoy, V. B.; Eda, G.; Chhowalla, M. Nano Lett. 2013, 13, 6222. (33) Li, H.; Tsai, C.; Koh, A. L.; Cai, L.; Contryman, A. W.; Fragapane, A. H.; Zhao, J.; Han, H. S.; Manoharan, H. C.; Abild-Pedersen, F.; Norskov, J. K.; Zheng, X. Nature Mater. 2016, 15, 48. (34) Xie, J.; Zhang, H.; Li, S.; Wang, R.; Sun, X.; Zhou, M.; Zhou, J.; Lou, X. W.; Xie, Y. Adv. Mater. 2013, 25, 5807. (35) Yin, Y.; Han, J.; Zhang, X.; Zhang, Y.; Zhou, J.; Muir, D.; Sutarto, R.; Zhang, Z.; Liu, S.; Song, B. RSC Adv. 2014, 4, 32690. \n\n(36) Coleman, J. N.; Lotya, M.; O’Neill, A.; Bergin, S. D.; King, P. J.; Khan, U.; Young, K.; Gaucher, A.; De, S.; Smith, R. J.; Shvets, I. V.; Arora, S. K.; Stanton, G.; Kim, H.-Y.; Lee, K.; Kim, G. T.; Duesberg, G. S.; Hallam, T.; Boland, J. J.; Wang, J. J.; Donegan, J. F.; Grunlan, J. C.; Moriarty, G.; Shmeliov, A.; Nicholls, R. J.; Perkins, J. M.; Grieveson, E. M.; Theuwissen, K.; McComb, D. W.; Nellist, P. D.; Nicolosi, V. Science 2011, 331, 568. (37) Kansy, J.; Hanc, A.; Pająk, L.; Giebel, D. Phys. Status Solidi C 2009, 6, 2326. (38) Wypych, F.; Schollhorn, R. J. Chem. Soc., Chem. Commun. 1992, 1386. (39) Yu, Y.; Huang, S.-Y.; Li, Y.; Steinmann, S. N.; Yang, W.; Cao, L. Nano Lett. 2014, 14, 553. (40) Laursen, A. B.; Vesborg, P. C. K.; Chorkendorff, I. Chem. Commun. 2013, 49, 4965. (41) Seo, B.; Jung, G. Y.; Sa, Y. J.; Jeong, H. Y.; Cheon, J. Y.; Lee, J. H.; Kim, H. Y.; Kim, J. C.; Shin, H. S.; Kwak, S. K.; Joo, S. H. Acs Nano 2015, 9, 3728. (42) Yang, D.; Sandoval, S. J.; Divigalpitiya, W. M. R.; Irwin, J. C.; Frindt, R. F. Phys. Rev. B 1991, 43, 12053. (43) Jiménez Sandoval, S.; Yang, D.; Frindt, R. F.; Irwin, J. C. Phys. Rev. B 1991, 44, 3955. (44) Conway, B. E.; Tilak, B. V. Electrochim. Acta 2002, 47, 3571. (45) Gao, M.-R.; Chan, M. K. Y.; Sun, Y. Nat Commun 2015, 6, 7493. \n\n(46) Smith, A. J.; Chang, Y.-H.; Raidongia, K.; Chen, T.-Y.; Li, L.-J.; Huang, J. Adv. Energy Mater. 2014, 4, 1400398. (47) Li, Y.; Wang, H.; Xie, L.; Liang, Y.; Hong, G.; Dai, H. J. Am. Chem. Soc. 2011, 133, 7296. (48) Zhuo, J.; Caban-Acevedo, M.; Liang, H.; Samad, L.; Ding, Q.; Fu, Y.; Li, M.; Jin, S. ACS Catal. 2015, 5, 6355. (49) Deroide, B.; Belougne, P.; Zanchetta, J. V. J. Phys. Chem. Solids 1987, 48, 1197. (50) Deroide, B.; Bensimon, Y.; Belougne, P.; Zanchetta, J. V. J. Phys. Chem. Solids 1991, 52, 853. (51) Alatalo, M.; Barbiellini, B.; Hakala, M.; Kauppinen, H.; Korhonen, T.; Puska, M. J.; Saarinen, K.; Hautojärvi, P.; Nieminen, R. M. Phys. Rev. B 1996, 54, 2397. (52) Tuomisto, F.; Makkonen, I. Rev. Mod. Phys. 2013, 85, 1583. (53) Liang, L.; Li, K.; Xiao, C.; Fan, S.; Liu, J.; Zhang, W.; Xu, W.; Tong, W.; Liao, J.; Zhou, Y.; Ye, B.; Xie, Y. J. Am. Chem. Soc. 2015, 137, 3102. (54) Ohdaira, T.; Suzuki, R.; Mikado, T.; Ohgaki, H.; Chiwaki, M.; Yamazaki, T.; Hasegawa, M. Appl. Surf. Sci. 1996, 100–101, 73. (55) Viswanath, R. N.; Ramasamy, S. J. Mater. Sci. 1990, 25, 5029. \n\n# For Table of Contents Only \n\n![](images/65d128e3f9f1b6e92c24e43c0fa48aad850938fe24af3201a9949b1012d8be8c.jpg) " + }, + { + "id": "10.1038_srep32355", + "DOI": "10.1038/srep32355", + "DOI Link": "http://dx.doi.org/10.1038/srep32355", + "Relative Dir Path": "mds/10.1038_srep32355", + "Article Title": "Formation of oxygen vacancies and Ti3+ state in TiO2 thin film and enhanced optical properties by air plasma treatment", + "Authors": "Bharti, B; Kumar, S; Lee, HN; Kumar, R", + "Source Title": "SCIENTIFIC REPORTS", + "Abstract": "This is the first time we report that simply air plasma treatment can also enhances the optical absorbance and absorption region of titanium oxide (TiO2) films, while keeping them transparent. TiO2 thin films having moderate doping of Fe and Co exhibit significant enhancement in the aforementioned optical properties upon air plasma treatment. The moderate doping could facilitate the formation of charge trap centers or avoid the formation of charge recombination centers. Variation in surface species viz. Ti3+, Ti4+, O2-, oxygen vacancies, OH group and optical properties was studied using X-ray photon spectroscopy (XPS) and UV-Vis spectroscopy. The air plasma treatment caused enhanced optical absorbance and optical absorption region as revealed by the formation of Ti3+ and oxygen vacancies in the band gap of TiO2 films. The samples were treated in plasma with varying treatment time from 0 to 60 seconds. With the increasing treatment time, Ti3+ and oxygen vacancies increased in the Fe and Co doped TiO2 films leading to increased absorbance; however, the increase in optical absorption region/red shift (from 3.22 to 3.00 eV) was observed in Fe doped TiO2 films, on the contrary Co doped TiO2 films exhibited blue shift (from 3.36 to 3.62 eV) due to Burstein Moss shift.", + "Times Cited, WoS Core": 1122, + "Times Cited, All Databases": 1152, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000382157500001", + "Markdown": "# SCIENTIFIC REPORTS \n\n# OPEN \n\nreceived: 03 May 2016 \naccepted: 03 August 2016 \nPublished: 30 August 2016 \n\n# Formation of oxygen vacancies and Ti3+ state in TiO thin film and enhanced optical properties by air plasma treatment \n\nBandna Bharti1, Santosh Kumar2, Heung-No Lee3 & Rajesh Kumar1 \n\nThis is the first time we report that simply air plasma treatment can also enhances the optical absorbance and absorption region of titanium oxide $(\\mathsf{T i O}_{2})$ films, while keeping them transparent. $\\mathsf{T i O}_{2}$ thin films having moderate doping of Fe and Co exhibit significant enhancement in the aforementioned optical properties upon air plasma treatment. The moderate doping could facilitate the formation of charge trap centers or avoid the formation of charge recombination centers. Variation in surface species viz. $\\bar{\\mathsf{T}}\\mathsf{i}^{3+},\\bar{\\mathsf{T}}\\mathsf{i}^{4+},\\mathsf{O}^{2-},$ , oxygen vacancies, OH group and optical properties was studied using X-ray photon spectroscopy (XPS) and UV-Vis spectroscopy. The air plasma treatment caused enhanced optical absorbance and optical absorption region as revealed by the formation of $\\tt T i^{3+}$ and oxygen vacancies in the band gap of $\\bar{\\mathsf{T i O}}_{2}$ films. The samples were treated in plasma with varying treatment time from 0 to 60 seconds. With the increasing treatment time, $\\pi^{3+}$ and oxygen vacancies increased in the Fe and Co doped $\\bar{\\mathsf{T i O}}_{2}$ films leading to increased absorbance; however, the increase in optical absorption region/ red shift (from 3.22 to 3.00 eV) was observed in Fe doped $\\bar{\\mathsf{T i O}}_{2}$ films, on the contrary Co doped $\\bar{\\mathsf{T i O}}_{2}$ films exhibited blue shift (from 3.36 to 3.62 eV) due to Burstein Moss shift. \n\nAmong various metal oxide semiconductors, $\\mathrm{TiO}_{2}$ is considered as a prime candidate due to its many peculiar properties1,2 for diverse applications. It is the most suitable candidate for photocatalytic applications due to its biological and chemical inertness, strong oxidizing power, non-toxicity and long term stabilization against photo and chemical corrosion3. The films of $\\mathrm{TiO}_{2}$ have valuable applications in LEDs, gas sensors, heat reflectors, transparent electrodes, thin film photo-anode to develop new photovoltaic, photo-electrochemical cells, solar cells and water splitting4–10. In anodic applications, it is a preferred material because of its low density/molar mass and structural integrity over many charge and discharge cycles11. However, the efficiency of pure $\\mathrm{TiO}_{2}$ is substantially low because of its wide band gap and fast recombination of photo-generated electrons and holes. The key issue to improve the performance of $\\mathrm{TiO}_{2}$ relies on efficient light harvesting, including the increase of its photo-efficiency and expansion of photo-response region, and to ensure efficient number of photo-generated electrons and holes reaching to the surface before their recombination. In order to meet these desired performances the bands structure modification of $\\mathrm{TiO}_{2}$ is preferred. \n\nGenerally, three fundamental approaches are implemented for band structure modification viz. doping with metallic/non-metallic elements or co-doping of metallic and non-metallic elements1,12–14, modification via introducing defects such as oxygen vacancies and $\\mathrm{Ti}^{3+}$ in the band gap15,16, and surface modification by treatment methods11,17–19. In metallic doping, among the range of dopants such as Ni, Mn, Cr, Cu, Fe etc.3,20–23, the Fe is found most suitable due to its half filled electronic configuration. Similarly, from non-metallic dopants S, C, F, N etc.24–27, the N is preferred. In the case of metallic dopants, there are some contradictory reports that show disadvantages of thermal and chemical instability of $\\mathrm{TiO}_{2}$ . Also, their high doping although enhances the band gap but at the same time reduces optical/photocatalytic activity because of increasing carrier recombination centers28–31. What is the mechanism of observed photo-response of doped/modified $\\mathrm{TiO}_{2}$ ; it is still a question, however a generally accepted concern states that the photo absorption of a material is explained better by introducing the defects in the lattice of $\\mathrm{TiO}_{2}$ . For example, $\\bar{\\mathrm{Ti}}^{3+}$ and oxygen vacancies32 create trap centers, rather than the recombination centers unlike the high doping case, and results in the variation of band gap of pristine $\\mathrm{TiO}_{2}$ . \n\nOn the other hand, surface modification methods including surface hydrogenation33, vacuum activation32 and plasma treatment34 are also practiced. In the hydrogenation method, the surface of $\\mathrm{TiO}_{2}$ is terminated with hydrogen leading to an enhanced photocatalytic activity35 in visible region; however, it is still unknown that how does the hydrogenation modify a surface to enhance its optical performance (photocatalytic activity)36. The drawback of the hydrogenation method is that it requires high temperature and the obtained $\\mathrm{TiO}_{2}$ sample/film are black35, which makes the films unable for many optoelectronic applications, such as a transparent electrode in optoelectronic devices. Both the vacuum activation and plasma treatment methods create highly stable $\\mathrm{Ti}^{3+}$ and oxygen vacancies32,34. In vacuum activation method, the sample may exhibit higher absorption intensity but it appears brown in color35, that makes it unable for transparent electrode applications. Finally, in case of plasma treatment methods, generally hydrogen gas is used to create $\\mathrm{Ti}^{3+}$ and oxygen vacancies in $\\mathrm{TiO}_{2}$ , but it is always avoidable to use such a hazardous and expensive gas. Except hydrogen there are few reports on the use of argon37, oxygen38 and nitrogen plasma39 for surface modification of $\\mathrm{TiO}_{2}$ . We know that the implementation of gas in the treatment chamber may be hazardous and cost effective; therefore, it is always required to avoid the use of hazardous gas, and to implement a simple and low cost approach to meet the requirements. In this regard, treatment by air plasma may be an effective approach. However, to the best of our knowledge there is no report on the application of air plasma for the surface modification of $\\mathrm{TiO}_{2}$ film. \n\nIn this report, the band structure modification of thin transparent films of $\\mathrm{TiO}_{2}$ was done by implementing simply the air plasma and thus creating $\\mathrm{Ti}^{3+}$ and oxygen vacancies in $\\mathrm{TiO}_{2}$ films. The effect of air plasma treatment was studied in conjunction with metallic doping. First, Fe and Co doped $\\mathrm{TiO}_{2}$ thin films were formed on glass substrate, which were subsequently treated in air plasma. Considering the drawback of high metallic doping (formation of recombination centers), in this study, a moderate amount of dopants were used to enhance the optical properties of $\\mathrm{TiO}_{2}$ thin film and thereafter the air plasma was applied to enhance them further. The moderate amount of metallic dopant not only favors the separation of electrons and holes but also narrows the band gap of $\\mathrm{TiO}_{2}{}^{3}$ . We observed that simultaneous effect of the joint approaches increases photo absorbance as well as expends photo response region of the films towards both the visible and UV spectrum. The doped films of $\\mathrm{TiO}_{2}$ were treated in plasma with varying treatment time. The moderate doping of Fe and Co elements reduces band gap minutely in both the cases, but when treated with air plasma a significant change in the optical properties was observed due to the formation of $\\mathrm{Ti}^{3+}$ and oxygen vacancies in the band gap. \n\n# Results and Discussion \n\nAfter fabricating, the thin films of pure $\\mathrm{TiO}_{2}$ , Fe and Co doped $\\mathrm{TiO}_{2}$ were treated in air plasma for 0, 10, 30 and 60 seconds, which were analyzed for surface morphology and crystal structure variations using SEM (see Supplementary Information; Figure S1) and XRD. Here we show XRD pattern of doped thin films for extreme treatment time 0 and 60 seconds (for XRD spectra of samples treated at other treatment time, please see Supplementary Information; Figure S2). Figure 1(a,b) represents XRD pattern of Fe doped, and Fig. 1(c,d) represents XRD pattern of Co doped $\\mathrm{TiO}_{2}$ thin films for 0 (untreated) and 60 seconds of plasma treatment time. Since there is no detection of Fe and Co signals, it indicates that all the Fe and Co ions in the respective samples gets incorporated into the structure of $\\mathrm{TiO}_{2}$ by replacing some of Ti ion, and occupying the interstitial sites40. \n\nAbsence of sharp peak in XRD patterns represents amorphous phase of $\\mathrm{TiO}_{2}$ thin $\\mathrm{{\\flms^{41}}}$ . After plasma treatment $2\\theta$ angle and FWHM of the peaks remain almost unchanged, indicating negligible effect on the film structure. XRD indicates that plasma treatment does not create any change in the crystal structure of Fe and Co doped $\\mathrm{TiO}_{2}$ thin films. The obtained low signal-to-noise ratio in the above XRD spectra is due to the low crystallinity of the films and small crystallite size; such observations have been reported by others as well42. \n\nThe presence of atomic percentage of the dopants in $\\mathrm{TiO}_{2}$ thin films was detected by EDX signals (see Supplementary Information; Figure S3). The EDX of Fe doped $\\mathrm{TiO}_{2}$ film shows the atomic percentage of Fe, Ti and O as $1.66\\%$ , $12.93\\%$ and $85.41\\%$ , respectively, which closely matches to the stoichiometry of elements in $\\mathrm{Ti}_{0.95}\\mathrm{Fe}_{0.05}\\mathrm{O}_{2}$ . Similarly, in case of Co doped $\\mathrm{TiO}_{2}$ , the obtained atomic percentage of Co, Ti and O in EDX are $1.33\\%$ , $23.33\\%$ and $75.35\\%$ , respectively, which confirms the stoichiometry of elements of $\\mathrm{Ti}_{0.95}\\mathrm{Co}_{0.05}\\mathrm{O}_{2}$ thin film. \n\nVariation in optical properties of $\\mathrm{TiO}_{2}$ thin films by doping and subsequent air plasma treatment was analyzed by UV-Vis spectrophotometer. The change in absorption edge and corresponding band gap is mentioned in Table 1. Pure $\\mathrm{TiO}_{2}$ film (undoped and untreated) showed absorption edge at $367\\mathrm{nm}$ and band gap $3.37\\mathrm{eV},$ whereas Fe doped $\\mathrm{TiO}_{2}$ film showed a shift in the absorption edge to $385\\mathrm{nm}$ , with a decreasing in the band gap to $3.22\\mathrm{eV}.$ Similarly, Co doping shifts the absorption edge from $367\\mathrm{nm}$ to $369\\mathrm{nm}$ with a reduction in the band gap to $3.36\\mathrm{eV}.$ The observed red shift in absorption edge and narrowing band gap in both dopants cases is similar to other reports on metallic doping3. In both the cases, samples were doped with a moderate $(5\\%)$ concentration of Fe and $\\scriptstyle\\mathrm{Co}$ forming $\\mathrm{Ti}_{0.95}\\mathrm{Fe}_{0.05}\\mathrm{O}_{2}$ and $\\mathrm{Ti}_{0.05}\\mathrm{Co}_{0.05}\\mathrm{O}_{2}$ respectively. We could have tuned the optical properties further by increasing the dopant concentration but that would form recombination centers28; therefore, to avoid the formation of recombination centers, a further tuning in the optical properties was done by treating these moderately doped $\\mathrm{TiO}_{2}$ films in air plasma. The films were treated in air plasma for treatment time (0, 10, 30 and 60 seconds), and investigated for the shift in absorption edge and band gap variation. With increasing treatment time, the absorption edge of Fe doped $\\mathrm{TiO}_{2}$ films shifts continuously from $385\\mathrm{nm}$ (for 0 seconds treatment time) to $413\\mathrm{nm}$ (for 60 seconds treatment time), with a corresponding band gap change from $3.22\\mathrm{eV}$ to $3.00\\mathrm{eV},$ showing a significant increase in the absorption region. In case of Co doped $\\mathrm{TiO}_{2}$ films, the absorption edge shifts from $369\\mathrm{nm}$ to $342\\mathrm{nm}$ (for 60 seconds treatment time) with a corresponding band gap change from 3.36 to $3.62\\mathrm{eV},$ which shows an increase in the optical band gap/UV absorption region probably due to the Burstein-Moss effect43, explained latter. \n\n![](images/03d7ac9bfe536d807eb0f50a7d01ed05ab3a644460c32b4e7a571411af6c9ff9.jpg) \nFigure 1.  X-ray diffraction spectra of (a) Fe doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second, (b) Fe doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 second, (c) Co doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second and (d) Co doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 second. \n\nTable 1.  Variation in absorption edge and band gap of Fe and Co doped $\\mathbf{TiO}_{2}$ thin films with plasma treatment time. \n\n\n
Plasma treatment time [sec]Absorption edge [nm]Band gap [eV]
Fe dopingCo dopingFe dopingCo doping
0.3853693.223.36_ by doping
103963603.133.44
304023453.083.59|by plasma treatment
604133423.003.62
\n\nFrom the Table, it is observed that the change in optical properties of $\\mathrm{TiO}_{2}$ films appears at two levels; first by the doping of Fe and Co, and then by plasma treatment. However, here it should be noted that the change in the band gap due to the doping is smaller as compared to the subsequent band gap change by plasma treatment. While discussing the effect of doping on the change of band gap, we know that the reduction may take place due to either by the increasing grain size of highly crystalline sample44 or the formation of electronic energy levels within energy band gap45. In our study, since the XRD results showed the samples to be amorphous, thus the first reason can be discarded. Therefore, $\\mathrm{Fe}^{3+}$ and ${\\mathrm{Co}}^{2+}$ ions substitute $\\mathrm{Ti^{4+}}$ ions in $\\mathrm{TiO}_{2}$ matrix and cause a change in the band gap by forming their mid gap energy levels in the respective samples along with the formation of $\\mathbf{\\bar{T}i}^{3+}$ and oxygen vacancies. The electronic transition from valance band to dopant level and then from dopant level to conduction band, and/or from valance band to oxygen level and then form oxygen level to $\\mathrm{Ti}^{3+}$ level/dopant level effectively cause a red shift in the absorption edge, showing reduced band $\\mathrm{gap^{\\bar{4}6-48}}$ . In many cases, the localized level of $\\mathbf{t}_{2\\mathrm{g}}$ state of the doping element even lies in the middle of band gap (in case of, Cr, Mn or Fe as the doping materials), and at the top of the valance band (when Co is used as a dopant)49. Next, the variation in the absorption edge/band gap with plasma treatment time is due to the increase of $\\mathrm{Ti}^{3+}$ and oxygen vacancies, detailed discussion is given under XPS studies in the following section. \n\nFigure 2 shows variation in the absorption spectra of Fe doped $\\mathrm{TiO}_{2}$ thin film treated for 60 seconds of time (Fig. 2(b)) with respect to untreated one (Fig. 2(a)) (to see the increase in the absorption edge and reduction in band gap, please refer to Supplementary Information; Figure S4). There is a continuous change in the absorbance, absorption edge and band gap of the films with plasma treatment time. The absorbance of the film increased from $60\\%$ (untreated film) to $87\\%$ (treated for 60 seconds) along with a red shift in the absorption edge and band gap narrowing by $0.22\\mathrm{eV}$ (Tauc plot shown in the inset of Fig. 2(b)). The band gap and absorption edge were estimated using the following equations50: \n\n![](images/c0a5eab6b71ff6d391fa888871205fe6ff24c5e820d677444102db0b6be7cfcc.jpg) \nFigure 2.  Optical absorption spectra and Tauc plot $((\\alpha h\\nu)^{1/2}$ versus hv plot) in the inset for (a) Fe doped/ untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second and (b) Fe doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 second. \n\n![](images/a7b66c2cf3bb3175fed0a12f99f1476af4a2aabd036cd6c0bd7304d752745d89.jpg) \nFigure 3.  Optical absorption spectra and Tauc plot $((\\alpha h\\nu)^{1/2}$ versus $h\\nu$ plot) in the inset for (a) Co doped/ untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second and (b) Co doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 second. \n\n$$\n(\\alpha h\\nu)^{I/2}=C(h\\nu-E_{g})\n$$ \n\n$$\nE_{e V}=h c/\\lambda\n$$ \n\nwhere $\\alpha$ is absorption coefficient and $E_{g}$ is band gap energy. \n\nSimilarly, the variation in absorption spectra of Co doped $\\mathrm{TiO}_{2}$ thin film treated for 0 and 60 seconds is shown in Fig. 3(a,b) (details of other samples is given in Supplementary Information; Figure S5). In this case, doping shows a red shift due to the presence of Co levels in the energy gap of $\\mathrm{TiO}_{2}$ , whereas after plasma treatment the film shows continuous blue shift with increasing treatment time. This overall shift (due to treatment in plasma for 60 seconds) in the band gap is $0.26\\mathrm{eV}.$ The observed blue shift can be explained by Burstein-Moss effect43, resulted by the change in the position of Fermi level into the conduction band. General equation representing enhancement in the band gap energy is given by: \n\n![](images/10b7ff18ae20f8ae473f392a347ef07897d44d17debf3896a03902d761b4f6b8.jpg) \nFigure 4.  Plots for variation of optical band gap of Fe and Co doped $\\mathbf{TiO}_{2}$ thin film with plasma treatment time. \n\n$$\n\\Delta E_{g}^{B M}=\\frac{\\hbar^{2}K_{F}^{2}}{2}\\biggl[\\frac{1}{m_{e}^{*}}+\\frac{1}{m_{h}^{*}}\\biggr]\n$$ \n\nwhere $m_{h}^{*}$ and $m_{e}^{*}$ are the effective mass of hole and electron in the respective bands, and $K_{F}$ is Fermi wave vector. In our case, the shift of Fermi level into the conduction band leads to the energy band widening. Absorption edge shifts to shorter wavelength region due to the increase in the carrier concentration, which is discussed in XPS studies section. \n\nThe overall variation in the absorption edge and band gap of $\\mathrm{TiO}_{2}$ thin film due to the doping (Fe and Co) and air plasma treatment is plotted in Fig. 4. In the plasma treatment region, a remarkable change in the band gap values can be observed with treatment time. \n\nXPS study.  In order to understand the mechanism resulting the change in the band gap of Fe and Co doped $\\mathrm{TiO}_{2}$ films with plasma treatment time, the films were investigated by XPS. The XPS being surface sensitive technique provides information about the change in chemical state of film constituting species. Here, the variation in the chemical state of elements $\\mathrm{{^{\\circ}O}}$ and ‘Ti’ with plasma treatment time was analyzed in detail to correlate it with the observed variations in the band gap of the films. Figure 5(a,b) shows XPS survey spectra of untreated and plasma treated Fe and Co doped $\\mathrm{TiO}_{2}$ thin films, respectively. In these spectra, C1s is probably an instrumental impurity. The intensities of O1s and Ti2p peaks increase with the increasing plasma treatment time, indicating an increase in these states with treatment time. \n\nFigure 6(a) shows high resolution XPS spectrum of pure $\\mathrm{TiO}_{2}$ film. In this spectrum, the doublet $\\mathfrak{S}_{\\mathrm{Ti}2\\mathrm{p}_{3/2}}$ (binding energy $458.6\\mathrm{eV}$ ) and $\\mathrm{Ti}2\\mathsf{p}_{1/2}$ (binding energy $464.4\\mathrm{eV})$ ’ arises from spin orbit-splitting. These peaks are consistent with $\\mathrm{Ti^{4+}}$ in $\\mathrm{TiO}_{2}$ lattice51. Also, the shoulder $\\mathrm{Ti}2\\mathsf{p}_{1/2}$ at binding energy $460.2\\mathrm{eV}$ is corresponding to $\\mathrm{Ti}^{3+52}$ in ${\\mathrm{Ti}}_{2}{\\mathrm{O}}_{3}$ . This indicates that both $\\mathrm{TiO}_{2}$ and ${\\mathrm{Ti}}_{2}{\\mathrm{O}}_{3}$ are formed in the film (Without deconvolution, the XPS spectra are shown in Supplementary Figure S6). After doping with Fe, the high resolution XPS spectrum (Fig. 6(b)) shows a slight shift in the position along with a variation in the area of the original peaks. The peaks in the Fe doped samples are now located at binding energies 458.4 $(\\mathrm{Ti}2\\mathsf{p}_{3/2})$ , $464.3\\mathrm{eV}$ $(\\mathrm{Ti}2\\mathsf{p}_{1/2})$ and $459.0\\mathrm{eV}$ $(\\mathrm{Ti}2\\mathsf{p}_{1/2})$ , respectively (see Supplementary Information; Table S1). The shift in the position of these peaks indicates an influence of Fe addition on the electronic state of Ti element; probably some of the Ti ions get substituted with Fe ions in the lattices. After doping, the area of $\\mathrm{Ti}^{3+}$ peak increased by $81\\%$ and that of the peak $\\mathrm{Ti^{4+}}$ decreased by $19\\%$ . The increase in the area of $\\mathrm{Ti}^{3+}$ peak indicates that either ${\\mathrm{Ti}}_{2}{\\mathrm{O}}_{3}$ is formed in large amount or some mixed oxide structure with Fe (having oxidation state $\\mathrm{Ti}^{3+}$ ) is formed after doping. Meanwhile, the decreasing area of $\\mathrm{Ti^{4+}}$ indicates a reduction of $\\mathrm{TiO}_{2}$ in the sample, and probably formation of Ti-O-Fe structure in the $\\mathrm{TiO}_{2}$ lattice through the substitution of transition metal ions. Observed shift in the peaks also indicates interaction between Ti and Fe atoms and an overlapping of their 3d orbital53. This causes an electronic excitation from Fe to $\\mathrm{Ti}$ in the optical absorption experiment, which shows a reduction in the band gap of Fe doped $\\mathrm{TiO}_{2}$ film (as observed in the optical analysis). \n\nAfter doping, the film was treated in air plasma. In the XPS results, only the sample which was treated for 60 seconds in plasma is demonstrated. The XPS shows a further increase in the peak corresponding to $\\mathrm{Ti}^{3+}$ at $459.0\\mathrm{eV}$ (Fig. 6(c)) and a decrease in the peak area of $\\mathrm{Ti^{4+}}$ . The change in stoichiometry was estimated by the change in the area of relative peaks. The peak area of $\\mathrm{Ti}^{3+}$ increases by $20\\%$ and that of $\\mathrm{Ti^{4+}}$ decreases by $12\\%$ . The increase in the peak area of $\\bar{\\mathrm{Ti}}^{3+}$ indicates that after plasma treatment there is removal of oxygen from the lattice, which shows a relative increase in $\\mathrm{Ti}^{3+}$ in the XPS spectrum. On the other hand decreasing peak area of $\\mathrm{Ti^{4+}}$ is inferred due to the reaction of $\\mathrm{Ti^{4+}}$ with electrons coming either from plasma or due to the formation of oxygen vacancies in the surface layer generated by the plasma treatment41. Now, as observed in optical analysis, the band gap of Fe doped films $(3.22\\mathrm{eV})$ decreased to $3.00\\mathrm{eV}$ (for 60 seconds of treatment time), this is correlated with the increasing career/electrons density due to plasma treatment. As we know that in the doped samples, the possible reasons of red shift/decreasing band gap is the introduction of donor states in the energy gap (here oxygen vacancies and $\\mathrm{Ti}^{3+}$ , Table 1). In the present case, the band gap decreases further with increasing treatment time, while the concentration of the dopant was kept constant, which is due to the change in the surface states of the constituents i.e. Ti element and oxygen vacancies. \n\n![](images/ce8bb3a617627ca5ad888343dc30b1540f48de39da0ca62cb59cc2b6d88bc47a.jpg) \nFigure 5.  XPS survey spectra in a(i) pure $\\mathrm{TiO}_{2}$ film indicating all the peaks of elements present in the sample, here the appeared carbon peak is instrumental impurity, a(ii) Fe doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 seconds, a(iii) Fe doped/treated $\\mathrm{TiO}_{2}$ ; plasma treatment time 60 seconds, $\\mathbf{b}(\\mathrm{i})$ pure $\\mathrm{TiO}_{2}$ film which is similar to a(i), and b(ii) Co doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 seconds, b(iii) Co doped/ treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 seconds. \n\nNext, the O1s spectrum of pure $\\mathrm{TiO}_{2}$ thin film is shown in Fig. 6(d), which is fitted with three peaks. The peaks at binding energies $529.9\\mathrm{eV},$ $530.3\\mathrm{eV}$ and $531.3\\mathrm{eV}$ are attributed to lattice oxygen, ${\\mathrm{Ti}}_{2}{\\mathrm{O}}_{3}$ and non-lattice oxy$\\mathrm{gen}^{54,55}$ . Similarly, for the doped sample, O1s spectrum of Fe doped $\\mathrm{TiO}_{2}$ thin film fitted with two peaks is shown in Fig. 6(e). In this spectrum, only two peaks at binding energies $529.8\\mathrm{eV}.$ , and $531.9\\mathrm{eV}$ are observed which are attributed to lattice oxygen and surface adsorbed OH group, whereas the peak $530.3\\mathrm{eV}$ corresponding to $\\mathrm{Ti}_{2}\\mathrm{O}_{3}$ , disappears. This indicates that in the doping process $\\mathrm{TiO}_{2}$ is formed along with some mixed oxide. Again, the change in stoichiometry was estimated by the change in area of relative peaks. In case of Fe doped $\\mathrm{TiO}_{2}$ film, the area of the peak at 529.7 increases by $64\\%$ and that of the peak at $531.5\\mathrm{eV}$ increases by $54\\%$ . \n\nAfter plasma treatment, the binding energy of lattice oxygen (O in $\\mathrm{TiO}_{2}$ ) shifts slightly from $529.8\\mathrm{eV}$ to $529.7\\mathrm{eV}$ (Fig. 6(f)), whereas its area increases by $35\\%$ . Also, the area of the peak at $531.5\\mathrm{eV}$ (non-lattice oxygen/OH) increases by $15\\%$ (see Supplementary Information; Table S1). The increase in the area of non-lattice oxygen indicates the formation of oxygen vacancies in the lattice. This result is analogues to the XPS spectrum of Ti2p (Fig. $6(\\mathrm{c})_{,}^{\\cdot}$ . \n\nFe doping results in a minor shift in the binding energy, indicating that Fe ions are better dispersed in the substitutional sites of $\\mathrm{TiO}_{2}$ lattice and produce more mixed oxide structure, probably Fe-O-Ti. Figure 7(a) shows high resolution XPS spectrum (for $\\mathrm{Fe}2\\mathrm{p}_{3/2}$ ) of Fe doped $\\mathrm{TiO}_{2}$ film. After plasma treatment, the high resolution XPS spectrum of $\\mathrm{Fe}2\\mathrm{p}_{3/2}$ is shown in Fig. 7(b). These spectra are fitted with Gauss–peak shapes as shown in Fig. 7(c,d). The deconvoluted XPS spectrum of $\\mathrm{Fe}2\\mathrm{p}_{3/2}$ (Fig. 7(c,d)) contains main peaks at $710.1\\mathrm{eV}$ and $724.6.1\\mathrm{eV}$ corresponding to $\\mathrm{Fe}2\\mathrm{p}_{3/2}$ and $\\mathrm{Fe}2\\mathsf{p}_{1/2},$ respectively (see Supplementary Information; Table S2). The appearance of these peaks supports the presence of Fe in $\\mathrm{Fe}^{3+}$ ionic state55. Further, after plasma treatment the shift in the binding energy of $\\mathrm{Fe}2\\mathrm{p}_{3/2}$ from $710.1\\mathrm{eV}$ to $711.3\\mathrm{eV}$ also indicates the presence of $\\mathrm{Fe}^{3+}$ species, irrespective of the particular oxide (i.e., $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ , $\\mathrm{Fe}_{3}\\mathrm{O}_{4},$ and FeOOH). Shake up satellite at $716.9\\mathrm{eV}$ also supports that Fe is presented in $\\mathrm{Fe}^{3+}$ state (oxide)56. These shake-up satellites are associated with Fe3d-O2p hybridization. Thus XPS analysis confirmed that Fe ions are doped into $\\mathrm{TiO}_{2}$ matrix in the form of Fe-O-Ti. From the XPS analysis, we confirmed that by increasing the plasma treatment time the concentration of $\\mathrm{Ti}^{3+}$ and oxygen vacancies also increases. \n\nThe Co doped samples after treating in plasma show adverse effect on the band gap of the doped $\\mathrm{TiO}_{2}$ film. In this case, band gap increases with the increasing treatment time as observed in optical studies. To investigate this divergent behavior, the samples were analyzed via XPS, Fig. 8 shows high resolution spectra. Figure 8(a) shows the XPS spectrum of pure $\\mathrm{TiO}_{2}$ , and Fig. 8(b) shows XPS for Co doped sample. As discussed above in the case of Fe doped sample, the XPS of pure $\\mathrm{TiO}_{2}$ is also fitted with three peaks corresponding to titanium dioxide $(\\mathrm{Ti^{4+}})$ and titanium sub oxide $(\\mathrm{Ti}^{3+})$ in $\\mathrm{Ti}2\\mathsf{p}_{1/2}$ and $\\mathrm{Ti}2\\mathrm{p}_{3/2}$ , respectively. These peaks are fitted as $\\mathrm{Ti}^{4+}2\\mathrm{p}_{1/2}$ at $464.4\\mathrm{eV},$ $\\mathrm{Ti^{4+}}2\\mathrm{p}_{3/2}$ at $458.6\\mathrm{eV},$ and $\\mathrm{Ti}^{3+}2\\mathrm{p}_{3/2}$ at $460.2\\mathrm{eV}.$ The line separation between $\\mathrm{Ti}2\\mathrm{p}1/2$ and $\\mathrm{Ti}2\\mathsf{p}3/2$ is $5.8\\mathrm{eV},$ which is consistent with the standard binding energy of $\\mathrm{TiO}_{2}^{51}$ . However, in this case the Ti2p spectrum (Fig. 8(b)) is fitted with four peaks as 464.4 for $\\mathrm{Ti}^{4+}2\\mathrm{p}_{1/2},$ $458.6\\mathrm{eV}$ for $\\mathrm{Ti}^{4+}2\\mathrm{p}_{3/2},$ 460.4 for $\\mathrm{Ti}^{3+}2\\mathrm{p}_{3/2}$ and $457.9\\mathrm{eV}$ for $\\mathrm{Ti}^{3+}2\\mathrm{p}_{1/2}{}^{57}$ , respectively (see Supplementary Information; Table S1). In comparison to the pure $\\mathrm{TiO}_{2}$ , the area of $\\mathrm{Ti}^{3+}$ peak in Co doped $\\mathrm{TiO}_{2}$ increases by $26\\%$ , while that of the peak $\\mathrm{Ti^{4+}}$ decreases by $7\\%$ , indicating a reduction in the formation of $\\mathrm{TiO}_{2}.$ , which is similar to the case of Fe doped samples. \n\n![](images/68bd7d33b8728815c625a0f53e76a90103eeb1ef6619c167def8e34c23385ab4.jpg) \nFigure 6.  High resolution XPS spectra of Ti2p and O1s in (a) pure/untreated $\\mathrm{TiO}_{2}$ film, (b) Fe doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second, (c) Fe doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 seconds, (d) O1s for pure/untreated $\\mathrm{TiO}_{2}$ film, (e) O1s for Fe doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second, and (f) O1s for Fe doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 seconds. \n\n![](images/d9ffc298bd3f558643a162be3b3d1ce311988ba029993133a7cb60c51f9669ef.jpg) \nFigure 7.  High resolution XPS spectra of Fe2p in (a) Fe doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second, (b) Fe doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 seconds, (c,d) are Gaussian fit of (a,b). \n\n![](images/da6094a1ac6bc3585dd63ddaa2120c6ccba491e6062f54cb73b73fd42b651e06.jpg) \nFigure 8.  High resolution XPS spectra of Ti2p and O1s in (a) pure/untreated $\\mathrm{TiO}_{2}$ film, (b) Co doped/ untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second, (c) Co doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 seconds, (d) O1s for pure/untreated $\\mathrm{TiO}_{2}$ film, (e) O1s for Co doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second, and (f) O1s for Co doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 seconds. \n\nAfter the plasma treatment (Fig. 8(c)), binding energies of the mentioned peaks are shifted slightly to the positions such as $464.3\\mathrm{eV}$ $(\\mathrm{Ti}^{4+}2\\mathsf{p}_{1/2})$ , $\\mathrm{458.5eV}$ $(\\mathrm{Ti}^{4+}\\bar{2}\\mathsf{p}_{3/2})$ , $460.6\\mathrm{eV}$ $(\\mathrm{Ti}^{3+}2\\mathsf{p}_{3/2})$ and $457.4\\mathrm{eV}$ $(\\mathrm{Ti}^{3+}2\\bar{\\mathrm{p}_{1/2}})$ , respectively. The change in stoichiometry was estimated by the change in peak area of respective peaks. \n\nAfter plasma treatment, while investigating for peak area, we observed that the peak area of ${\\mathrm{Ti}}^{3+}$ increases by $30\\%$ , whereas the peak area of $\\mathrm{Ti^{4+}}$ decreases by $12\\%$ . Again, this is expected due to the reaction of $\\mathrm{Ti^{4+}}$ with the electrons coming either from plasma or due to the formation of oxygen vacancies in the surface layer by the plasma treatment. Further, the high resolution O1s XPS spectrum obtained for Co doped sample is shown in Fig. 8(d–f). The spectrum is fitted with three peaks i.e. $529.9\\mathrm{eV},$ $530.3\\mathrm{eV}$ and $531.6\\mathrm{eV}$ that correspond to lattice oxygen of $\\mathrm{TiO}_{2}.$ , oxygen in $\\mathrm{Ti}_{2}\\mathrm{O}_{3}$ and non-lattice oxygen, respectively. \n\nThe change in stoichiometry was estimated by change in the peak area of relative peaks. With the doping of Co, the lattice oxygen (corresponding to $\\mathrm{TiO}_{2}.$ ) peak at 529.9 shifts to the position $530.3\\mathrm{eV},$ and the area of the peaks at $530.3\\mathrm{eV}$ and $531.6\\mathrm{eV}$ increases by $51\\%$ and $24\\%$ , respectively. The original peak at $530.3\\mathrm{eV}$ (Fig. 8(d)) corresponding to $\\mathrm{Ti}_{2}\\mathrm{O}_{3}$ disappears after doping (Fig. 8(e)), which is due to the formation of mixed oxide structure. Further, with the increasing treatment time, the areas of the peaks at $530.3\\mathrm{eV}$ and $531.6\\mathrm{eV}$ ((Fig. 8(f)) also increases by $24\\%$ and $25\\%$ , respectively. (To explain in a more quantitative manner we have tabulated all the data in a table by comparing all the peaks at different plasma treatments time, see Supplementary Information; Table S1). \n\nNext, Fig. 9(a) corresponds to high resolution XPS spectra of $\\mathtt{C o2p}$ region of Co doped $\\mathrm{TiO}_{2}$ thin films and Fig. 9(b) shows high resolution XPS spectra with plasma treatment. Figure $\\mathfrak{g}(\\mathfrak{c},\\mathrm{d})$ represent deconvoluted XPS spectra of doped $\\mathrm{TiO}_{2}$ and plasma treated $\\mathrm{TiO}_{2}$ thin films, respectively. The core level binding energies of peaks $\\mathrm{Co2p_{1/2}}$ and $\\mathrm{Co}2\\mathrm{p}_{3/2}$ are $796.9\\mathrm{eV}$ and $781.0\\mathrm{eV},$ respectively. The satellite peaks at $787\\mathrm{eV}$ and $802\\mathrm{eV}$ reveal high spin $\\mathrm{Co}(\\mathrm{II})$ state with complex transitions58. These results are an indication that Co does not precipitate as metallic Co on the film surface. After plasma treatment, the satellites peaks shifts slightly to the $785.3\\mathrm{eV}$ and $802.3\\mathrm{eV.}$ Also, the binding energies of $\\mathrm{Co}2\\mathsf{p}_{1/2}$ and $\\mathrm{Co}2\\mathrm{p}_{3/2}$ are shifted to $796.6\\mathrm{eV}$ and $781.2\\mathrm{eV},$ respectively (see Supplementary Information; Table S1). These spectra are typical of compounds containing high-spin ${\\mathrm{Co}}^{2+}$ ions59,60, reveling the presence of $\\mathrm{CoO}(\\mathrm{Co}^{2+})$ , $\\mathrm{CoTiO}_{3}\\left(\\mathrm{Co}^{2+}\\right)$ , $\\mathrm{Co}_{2}\\mathrm{O}_{3}$ $(\\mathrm{Co}^{3+})$ or mixed valence $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ ( $C\\mathrm{o}^{2+}$ and ${\\mathrm{Co}}^{3+}.$ ) in the surface. The presence of strong satellites indicates that Co atoms in the doped $\\mathrm{TiO}_{2}$ film are in $^{2+}$ oxidation state, referring the possible formation of $\\mathrm{CoO}$ or $\\mathrm{CoTiO}_{3}$ inside the film. \n\n![](images/f6f1b5b05b283c1a49aa743f227e1838887eb9dba9f23d47d1a5d0ea1c761d7f.jpg) \nFigure 9.  High resolution XPS spectra of Co2p in (a) Co doped/untreated $\\mathrm{TiO}_{2}$ film; plasma treatment time 0 second, (b) Co doped/treated $\\mathrm{TiO}_{2}$ film; plasma treatment time 60 seconds, (c,d) are Gaussian fit of (a,b). \n\nNow we discuss the probable reason of band gap narrowing in $\\mathrm{TiO}_{2}$ film with Fe doping, and widening in the case of Co doping after plasma treatment. As reported, the iron dopant acts as an acceptor impurity in $\\mathrm{TiO}_{2}$ lattice61. Thus when the $\\mathrm{TiO}_{2}$ film is doped with Fe, the acceptor levels of Fe along with oxygen vacancies are created in the band gap of $\\mathrm{TiO}_{2}^{62}$ . In our case, as discussed above $\\mathrm{Ti}^{3+}$ is also formed which creates energy level in the band gap, contributing to the reduction of band gap. Next, when this Fe doped $\\mathrm{TiO}_{2}$ film was treated in air plasma, the $\\mathrm{Ti}^{3+}$ levels and oxygen vacancies increases further with the treatment time, whereas no change in the dopant levels occurs as the dopant concentration was kept constant. The increase in $\\mathrm{Ti}^{3+}$ levels and oxygen vacancies would further reduce the band gap of Fe doped $\\mathrm{TiO}_{2}$ film. In case of Co doping, there is a formation of Co acceptor levels along with $\\mathrm{Ti}^{3+}$ and oxygen vacancies levels in the band gap which reduces the band gap of Co doped $\\mathrm{TiO}_{2}$ film. But when the film was treated with plasma we observed continuous widening in the band gap with treatment time. The observed increase in the band gap can be explained by Burstein-Moss effect. The probable reason for Burstein-Moss shift in this case is that with the treatment time the $\\mathrm{Ti}^{3+}$ levels and oxygen vacancies increases more as compared to Fe doped case. By plasma treatment for 60 seconds the $\\mathrm{Ti}^{3+}$ increases by $20\\%$ , oxygen vacancies increases by $15\\%$ in case of Fe doped $\\mathrm{TiO}_{2}$ , whereas Co doped $\\mathrm{TiO}_{2}\\mathrm{Ti}^{3+}$ increases $30\\%$ , oxygen vacancies increases $25\\%$ . These created levels donate more electrons and thus shift the Fermi level to the conduction band, which increases the band gap of Co doped $\\mathrm{TiO}_{2}$ film. The exact reason for this divergent behavior is unclear as of now but the most appropriate reason seems to us is, the on-site coulomb interaction/repulsion that are occurring only in case of Co doped $\\mathrm{TiO}_{2}$ films63. When ${\\mathrm{Co}}^{2+}$ ion substitutes $\\mathrm{Ti^{4+}}$ ions, the imbalance positive charge inside the lattice is compensated by the formation of oxygen vacancies located near Co ion. The formation of oxygen vacancies is equivalent to the addition of two electrons per Co ion64,65. The oxygen vacancies produced in case of Co doped $\\mathrm{TiO}_{2}$ thin films are higher as compared to Fe doped $\\mathrm{TiO}_{2}$ films as observed by XPS. Suppose both Fe and Co doped films increase by same values of $\\mathrm{Ti}^{3+}$ levels and oxygen vacancies, but due to Columbian interactions, which are only in case of Co doped $\\mathrm{TiO}_{2}{}^{64,65}$ , the optical transition results in the blue shift of the absorption spectra. The proposed mechanism for both the Fe and Co doped $\\mathrm{TiO}_{2}$ is illustrated in Fig. 10. \n\n![](images/e711a4af9f2a557c4b8854447573625d1ec2385e34c5cd0c33e7138c32a9defa.jpg) \nFigure 10.  Schematic diagram of the energy levels of (a) pure/untreated $\\mathrm{TiO}_{2}$ films, (b) Fe doped/untreated $\\mathrm{TiO}_{2}$ film, (c) Fe doped/treated $\\mathrm{TiO}_{2}$ ; for 60 seconds of treatment time, (d) Co doped/untreated $\\mathrm{TiO}_{2}$ film, (e) Co doped/treated $\\mathrm{TiO}_{2}$ film; for 10, 30 and 60 seconds of treatment time, indicating Burstein Moss effect. $(\\mathrm{O}_{\\mathrm{v}}$ represents oxygen vacancies). \n\n# Conclusion \n\nTreatment by air plasma leads to significant change in the optical properties of $\\mathrm{TiO}_{2}$ thin films. Unlike other treatment methods, in this approach the transparency of $\\mathrm{TiO}_{2}$ thin film remains invariant. The charge separation centers i.e. oxygen vacancies and $\\mathrm{Ti}^{3+}$ is created with the doping of metallic Fe and Co elements; however, they are significantly enhanced by the air plasma treatment. In Fe doped $\\mathrm{TiO}_{2}$ thin film, the formation of oxygen vacancies and $\\mathrm{Ti}^{3+}$ causes enhances absorbance and red shift due to the formation of energy levels in the band gap, whereas in Co doped $\\mathrm{TiO}_{2}$ the Burstein-Moss shift is effective to make blue shift in the absorption spectra. Conclusively, we can say that the joint approaches i.e. low level/moderate doping and safe and low cost air plasma treatment resulted in enhanced optical properties of transparent $\\mathrm{TiO}_{2}$ thin films, making them efficient candidate for transparent electrode applications. \n\n# Experimental Methods \n\nThin films of $\\mathrm{TiO}_{2}$ , Fe doped $\\mathrm{TiO}_{2}$ $\\mathrm{Ti}_{0.95}\\mathrm{Fe}_{0.05}\\mathrm{O}_{2})$ and Co doped $\\mathrm{TiO}_{2}$ $(\\mathrm{Ti}_{0.95}{\\bf C o}_{0.05}{\\bf O}_{2})$ were fabricated on glass substrate using dip-coating method. Titanium (IV) isopropoxide (TTIP, Ti[OCH $\\mathrm{(CH}_{3})_{2}]_{4}$ , $97\\%$ , Aldrich) was used as precursor solution. First of all triethanolamine ${\\mathrm{C}}_{6}{\\mathrm{H}}_{15}{\\mathrm{NO}}_{3},$ , a stabilization agent was dissolved in $\\mathrm{C_{2}H_{5}O H}$ , which resulted in a colorless solution. In this solution, the precursor solution $\\mathrm{Ti}[\\mathrm{OCH}(\\mathrm{CH}_{3})_{2}]_{4}$ was added dropwise to form a pale yellow solution with a continuous stirring. To avoid the precipitation of $\\mathrm{TiO}_{2}$ , $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ and $\\mathrm{H}_{2}\\mathrm{O}$ was added in a ratio 9:1. Now during the sol gel synthesis the solutions of ferric nitrate (F $:\\mathrm{e}\\left(\\mathrm{NO}_{3}\\right)_{3}.9\\mathrm{H}_{2}\\mathrm{O})$ , and cobalt nitrate $(\\mathrm{Co}\\ (\\mathrm{NO}_{3})_{2}.6\\mathrm{H}_{2}\\mathrm{O})$ were added separately as the dopant in $\\mathrm{TiO}_{2}$ . These solutions were stirred for two hours and allowed for ageing overnight. Then glass substrates cleaned with $\\mathrm{H}_{2}\\mathrm{O},$ detergent, ${\\mathrm{C}}_{3}{\\mathrm{H}}_{6}{\\mathrm{O}}$ and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ were coated with the aged solution. Coated films were dried and annealed at $400^{\\circ}\\mathrm{C}$ to form transparent thin films. The fabricated films were treated in air plasma, generated in a vacuum coating unit (Hindhivac model: 12A4D), for varying treatment time; 0, 10, 30, and 60 seconds, respectively. The air plasma was generated at reduced pressure of $\\dot{10}^{-3}$ mbar in the vacuum chamber. During the treatment process the applied bias voltage was 30 volts with a power of 22.7 watt. After treating in plasma, the samples were analyzed for optical, structural, morphological and surface properties. \n\nMaterials Characterization.  The optical (absorbance, shift in absorption edge and band gap) properties of the films were studied by UV-Vis spectrophotometer (Perkin-Elmer Lambda 750). The band gap of Fe and Co doped thin films was calculated by using the absorbance spectra by plotting $(\\alpha h\\nu)^{1/2}$ against $h\\nu$ , where $h\\nu$ being incident photon energy. Surface morphology was studied using scanning electron microscopy (SEM), and elemental confirmation was done using energy dispersive X-ray (EDX). The structural analysis of the samples was done using X-ray diffractometer (XRD) (company name Rigaku, with $\\operatorname{Cu}\\operatorname{k}\\alpha$ ​radiation, $\\lambda{=}1.5406\\mathring\\mathrm{A}$ ), and to observe the effect of plasma treatment on surfaces states, X-ray photoelectron spectroscopy (XPS: VG Multilab 2000, Thermo electron corporation, UK) studies were performed. \n\n# References \n\n1.\t Hamal, D. B. et al. A multifunctional biocide/sporocide and photocatalyst based on titanium dioxide $\\mathrm{(TiO}_{2},$ codoped with silver, carbon, and sulfur. Langmuir 26, 2805–2810 (2010). \n2.\t O’Regan, B. & Grätzel, M. A. Low-cost, high-efficiency solar cell based on dye-sensitized colloidal $\\mathrm{TiO}_{2}$ films. Nature 353, 737–740 (1991). \n3.\t Zhou, M., Yu, J. & Cheng, B. Effects of Fe-doping on the photocatalytic activity of mesoporous $\\mathrm{TiO}_{2}$ powders prepared by an ultrasonic method. J. Hazard. Mater. 137, 1838–1847 (2006). \n4.\t Lin, Y., Zhou, S., Liu, X., Sheehan, S. & Wang, D. $\\mathrm{TiO}_{2}/\\mathrm{TiSi}_{2}$ Heterostructures for High-Efficiency Photoelectrochemical $\\mathrm{H}_{2}\\mathrm{O}$ Splitting. J. Am. Chem. Soc. 131, 2772–2773 (2009). \n5.\t Sauvage, F. et al. Dye-Sensitized Solar Cells Employing a Single Film of Mesoporous $\\mathrm{TiO}_{2}$ Beads Achieve Power Conversion Efficiencies Over $10\\%$ . ACS Nano. 4, 4420–4425 (2010). \n6.\t Zhang, Y. et al. Synthesis and characterization of $\\mathrm{TiO}_{2}$ nanotubes for humidity sensing. Appl. Surf. Sci. 254, 5545–5547 (2008). \n8.\t Rabaste, S. et al. Sol-gel fabrication of thick multilayers applied to Bragg reflectors and microcavities. Thin Solid Films 416, 242–247 (2002). \n9.\t Liao, Y. et al. New Mechanistic Insight of Low Temperature Crystallization of Anodic $\\mathrm{TiO}_{2}$ Nanotube Array in Water. Cryst. Growth Des. 16, 1786–1791 (2016). \n10.\t Gültekİn, A. Effect of Au Nanoparticles Doping on the Properties of $\\mathrm{TiO}_{2}$ Thin Films. Mater. Sci. 20, 10–14 (2014). \n11.\t Shin, J., Joo, J. H., Samuelis, D. & Maier, J. Oxygen-Deficient $\\mathrm{TiO}_{2\\cdot\\delta}$ nanoparticles via hydrogen reduction for high capability Lithium batteries. Chem. Mater. 24, 543–551 (2012). \n12.\t Peng, B. et al. General synthesis and optical properties of monodisperse multifunctional metal-ion-doped $\\mathrm{TiO}_{2}$ hollow particles. J. Phys. Chem. C 113, 20240–20245 (2009). \n13.\t Asahi, R., Mikawa, T., Ohwaki, T., Aoki, K. & Taga, Y. Visible Light Photocatalysis in Nitrogen-Doped Titanium Oxides. Science. 293, 269–271 (2001). \n14.\t Kurtoglu, M. E., Longenbach, T., Sohlberg, K. & Gogotsi, Y. Strong Coupling of Cr and N in $\\mathrm{Cr}$ -N-doped $\\mathrm{TiO}_{2}$ and Its Effect on Photocatalytic Activity. J. Phys. Chem. C 115, 17392–17399 (2011). \n15.\t Amano, F., Nakata, M., Yamamoto, A. & Tanaka, T. Effect of $\\mathrm{Ti}^{3+}$ Ions and Conduction Band Electrons on Photocatalytic and Photoelectrochemical Activity of Rutile Titania for Water Oxidation. J. Phys. Chem. C 120, 6467–6474 (2016). \n16.\t Chen, C. S. et al. Effect of $\\mathrm{Ti}^{3+}$ on $\\mathrm{TiO}_{2}$ -supported Cu catalysts used for CO oxidation. Langmuir 28, 9996–10006 (2012). \n17.\t Liu, H. et al. The enhancement of $\\mathrm{TiO}_{2}$ photocatalytic activity by hydrogen thermal treatment. Chemosphere 50, 39–46 (2003). \n18.\t Nakamura, I., Sugihara, S. & Takeuchi, K. Mechanism for NO Photooxidation over the Oxygen-Deficient $\\mathrm{TiO}_{2}$ Powder under Visible Light Irradiation. Chem. lett. 29, 1276–1277 (2000). \n19.\t Zhang, Z. K., Bai, M. L., Guo, D. Z., Hou, S. M. & Zhang, G. M. Plasma-electrolysis synthesis of $\\mathrm{TiO}_{2}$ nano/microspheres with optical absorption extended into the infra-red region. Chem. Commun. 47, 8439–8441 (2011). \n20.\t Jing, D., Zhang, Y. & Guo, L. Study on the synthesis of Ni doped mesoporous $\\mathrm{TiO}_{2}$ and its photocatalytic activity for hydrogen evolution in aqueous methanol solution. Chem. Phys. Lett. 415, 74–78 (2005). \n21.\t Gracia, F., Holgado, J. P., Caballero, A. & Gonzalez-Elipe, A. R. Structural, optical, and photoelectrochemical properties of $\\mathrm{M}^{\\mathrm{n+\\_TiO}_{2}}$ model thin film photocatalysts. J. Phys. Chem. B 108, 17466–17476 (2004). \n22.\t Zhu, J. et al. Hydrothermal doping method for preparation of ${\\mathrm{Cr}}^{3+}{\\mathrm{-TiO}}_{2}$ photocatalysts with concentration gradient distribution of $\\mathrm{Cr}^{3+}$ . Appl. Catal. B Environ. 62, 329–335 (2006). \n23.\t Colón, G., Maicu, M., Hidalgo, M. C. & Navío, J. A. Cu-doped $\\mathrm{TiO}_{2}$ systems with improved photocatalytic activity. Appl. Catal. B Environ. 67, 41–51 (2006). \n24.\t Yang, K., Dai, Y. & Huang, B. Understanding photocatalytic activity of S- and P-doped $\\mathrm{TiO}_{2}$ under visible light from first-principles. J. Phys. Chem. C 111, 18985–18994 (2007). \n25.\t Ren, W. et al. Low temperature preparation and visible light photocatalytic activity of mesoporous carbon-doped crystalline $\\mathrm{TiO}_{2}$ Appl. Catal. B Environ. 69, 138–144 (2007). \n26.\t Yu, J. C., Yu, J., Ho, W., Jiang, Z. & Zhang, L. Effects of F-doping on the photocatalytic activity and microstructures of nanocrystalline $\\mathrm{TiO}_{2}$ powders. Chem. Mater. 14, 3808–3816 (2002). \n27.\t Sato, S., Nakamura, R. & Abe, S. Visible-light sensitization of $\\mathrm{TiO}_{2}$ photocatalysts by wet-method N doping. Appl. Catal. A Gen. 284, 131–137 (2005). \n28.\t Xing, M., Zhang, J., Chen, F. & Tian, B. An economic method to prepare vacuum activated photocatalysts with high photo-activities and photosensitivities. Chem. Commun. 47, 4947–4949 (2011). \n29.\t Pan, X., Yang, M. Q., Fu, X., Zhang, N. & Xu, Y. J. Defective $\\mathrm{TiO}_{2}$ with oxygen vacancies: synthesis, properties and photocatalytic applications. Nanoscale 5, 3601–3614 (2013). \n30.\t Pan, X., Yang, M. Q. & Xu, Y. J. Morphology control, defect engineering and photoactivity tuning of $\\mathrm{znO}$ crystals by graphene oxide–a unique 2D macromolecular surfactant. Phys. Chem. Chem. Phys. 16, 125589–125599 (2014). \n31.\t Zhang, N., Yang, M. Q., Liu, S., Sun, Y. & Xu, Y. J. Waltzing with the versatile platform of graphene to synthesize composite photocatalysts. Chem. Rev. 115, 10307–10377 (2015). \n32.\t Liu, Y., Wang, J., Yang, P. & Matras-Postolek, K. Self-modification of $\\mathrm{TiO}_{2}$ one-dimensional nano-materials by $\\mathrm{Ti}^{3+}$ and oxygen ancy using ${\\mathrm{Ti}}_{2}{\\mathrm{O}}_{3}$ as precursor. RSC Adv. 5, 61657–61663 (2015). \n33.\t Lu, X. et al. Hydrogenated $\\mathrm{TiO}_{2}$ Nanotube Arrays for Supercapacitors. Nano Lett. 12, 1690–1696 (2012). \n34.\t Konstantakou, M. et al. Influence of Fluorine Plasma Treatment of $\\mathrm{TiO}_{2}$ Films on the Behavior of Dye Solar Cells Employing the Co (II)/(III) Redox Couple. J. Phys. Chem. C 118, 16760–16775 (2014). \n35.\t Lu, H. et al. Safe and facile hydrogenation of commercial Degussa P25 at room temperature with enhanced photocatalytic activity. RSC Adv. 4, 1128–1132 (2014) \n36.\t Zheng, Z. et al. Hydrogenated titania: synergy of surface modification and morphology improvement for enhanced photocatalytic activity. Chem. Commun. 48, 5733–5735 (2012). \n37.\t Heo, C. H., Lee, S. B. & Boo, J. H. Deposition of $\\mathrm{TiO}_{2}$ thin films using RF magnetron sputtering method and study of their surface characteristics. Thin Solid Films 475, 183–188 (2005). \n38.\t Li, Y. & Jang, B. W. L. Investigation of calcination and $\\mathrm{O}_{2}$ plasma treatment effects on $\\mathrm{TiO}_{2}$ -supported palladium catalysts. Ind. Eng. Chem. Res. 49, 8433–8438 (2010). \n39.\t Yamada, K. et al. Photocatalytic activity of $\\mathrm{TiO}_{2}$ thin films doped with nitrogen using a cathodic magnetron plasma treatment. Thin Solid Films 516, 7560–7564 (2008). \n40.\t Cong, Y., Zhang, J., Chen, F., Anpo, M. & He, D. Preparation, photocatalytic activity, and mechanism of nano- $\\mathrm{\\cdotTiO}_{2}$ co-doped with nitrogen and iron (III). J. Phys. Chem. C 111, 10618–10623 (2007). \n41.\t Bharti, B., Kumar, S. & Kumar, R. Superhydrophilic $\\mathrm{TiO}_{2}$ thin film by nanometer scale surface roughness and dangling bonds. Appl. Surf. Sci. 364, 51–60 (2016). \n42.\t Li, S., Xu, Q., Uchaker, E., Cao, X. & Cao, G. Comparison of amorphous, pseudo hexagonal and orthorhombic ${\\mathrm{Nb}}_{2}{\\mathrm{O}}_{5}$ for high-rate lithium ion insertion. Cryst. Eng. Comm. 18, 2532–2540 (2016). \n43.\t Bhachu, D. S. et al. Solution processing route to multifunctional titania thin films: Highly conductive and photcatalytically active Nb: $\\mathrm{TiO}_{2}$ . Adv. Funct. Mater. 24, 5075–5085 (2014). \n44.\t White, C. W., McHargue, C. J., Sklad, P. S., Boatner, L. A. & Farlow, G. C. Ion implantation and annealing of crystalline oxides. Mater. Sci. Reports 4, 41–146 (1989). \n45.\t Sathish, M., Viswanathan, B., Viswanath, R. P. & Gopinath, C. S. Synthesis, Characterization, Electronic Structure, and Photocatalytic Activity of Nitrogen-Doped $\\{\\mathrm{TiO}_{2}\\}$ Nanocatalyst. Chem. Mater. 17, 6349–6353 (2005). \n46.\t George, S. et al. Role of Fe doping in tuning the band gap of $\\mathrm{TiO}_{2}$ for photo-oxidation induced cytotoxicity paradigm. J. Am. Chem. Soc. 133, 11270–11278 (2011). \n47.\t Shwetharani, R., Fernando, C. A. N. & Balakrishna, G. R. Excellent hydrogen evolution by a multi approach via structure–property tailoring of titania. RSC Adv. 5, 39122–39130 (2015). \n48.\t Moser, J., Grätzel, M. & Gallay, R. Inhibition of Electron-Hole Recombination in Substitutionally Doped Colloidal Semiconductor Crystallites. Helv. Chim. Acta. 70, 1596–1604 (1987). \n49.\t Umebayashi, T., Yamaki, T., Itoh, H. & Asai, K. Analysis of electronic structures of 3d transition metal-doped $\\mathrm{TiO}_{2}$ based on band calculations. J. Phys. Chem. Solids 63, 1909–1920 (2002). \n50.\t Yang, J. Y. et al. Grain size dependence of electrical and optical properties in Nb-doped anatase $\\mathrm{TiO}_{2}$ . Appl. Phys. Lett. 95, 213105 (2009). \n51.\t Sanjinés, R. et al. Electronic structure of anatase $\\mathrm{TiO}_{2}$ oxide. J. Appl. Phys. 75, 2945–2951 (1994). \n52.\t Bert, I., Mohai, M., Sullivan, J. L. & Saied, S. O. Surface characterisation of plasma-nitrided an XPS study titanium: Appl. Surf. Sci. 84, 357–371 (1995). \n53.\t Wang, E., Yang, W. & Cao, Y. Unique Surface Chemical Species on Indium Doped $\\mathrm{TiO}_{2}$ and Their Effect on the Visible Light Photocatalytic Activity. J. Phys. Chem. C 113, 20912–20917 (2009). \n54.\t Xu, N. et al. Characteristics and mechanism of conduction/set process in $\\mathrm{TiN/ZnO/Pt}$ resistance switching random-access memories. Appl. Phys. Lett. 92, 35–38 (2008). \n55.\t Hsieh, P. T., Chen, Y. C., Kao, K. S. & Wang, C. M. Luminescence mechanism of ZnO thin film investigated by XPS measurement. Appl. Phys. A Mater. Sci. Process. 90, 317–321 (2008). \n56.\t Mekki, A., Holland, D., McConville, C. F. & Salim, M. An XPS study of iron sodium silicate glass surfaces. J. Non-Cryst. Solids 208, 267–276 (1996). \n57.\t Kim, H. J., Kim, J. & Hong, B. Effect of hydrogen plasma treatment on nano-structured $\\mathrm{TiO}_{2}$ films for the enhanced performance of dye-sensitized solar cell. Appl. Surf. Sci. 274, 171–175 (2013). \n58.\t Fu, L. et al. Beaded Cobalt Oxide Nanoparticles along Carbon Nanotubes: Towards More Highly Integrated Electronic Devices. Adv. Mater. 17, 217–221 (2005). \n59.\t Tan, B. J., Klabunde, K. J. & Sherwood, P. M. A. XPS studies of solvated metal atom dispersed catalysts. Evidence for layered cobaltmanganese particles on alumina and silica. J. Am. Chem. Soc. 113, 855–861 (1991). \n60.\t Brik, Y., Kacimi, M., Ziyad, M. & Bozon-Verduraz, F. Titania-Supported Cobalt and Cobalt–Phosphorus Catalysts: Characterization and Performances in Ethane Oxidative Dehydrogenation. J. Catal. 202, 118–128 (2001). \n61.\t Radeka. M., Rekas. M. & Zakrzewcka. K. Electrical and optical proeprties of undoped and Fe doprd $\\mathrm{TiO}_{2}$ single nanocrystal. Solid State Phenom. 39, 113–116 (1994). \n62.\t Zhang, J. et al. Synthesis, surface morphology, and photoluminescence properties of anatase iron-doped titanium dioxide nanocrystalline films. Phys. Chem. Chem. Phys. 13, 13096–13105 (2011). \n63.\t Simpson, J. R. et al. Optical band-edge shift of anatase $\\mathrm{Ti}_{1-\\mathrm{x}}\\mathrm{Co}_{\\mathrm{x}}\\mathrm{O}_{2-\\delta}$ . Phys. Rev. B 69, 193205 (2004). \n64.\t Kong, L. G. et al. Oxygen-vacancies-related room-temperature ferromagnetism in polycrystalline bulk Co-doped $\\mathrm{TiO}_{2}$ . Electrochem. Solid State Lett. 9, G1–G3 (2006). \n65.\t Anisimov, V. I. et al. The role of transition metal impurities and oxygen vacancies in the formation of ferromagnetism in Co-doped $\\mathrm{TiO}_{2}$ J. Phys. Condens. Matter 18, 1695–1704 (2006). \n\n# Acknowledgements \n\nThis work was supported by research grant for Nanotechnology Lab of Jaypee University of Information Technology, also by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (NRF-2015R1A2A1A05001826). \n\n# Author Contributions \n\nB.B. fabricated and characterized the entire sample and wrote the manuscripts. S.K. carried out XPS studies of the samples. H.L. helped in the revision of the manuscript. R.K. supervised the work, reviewed and corrected the manuscript. All the authors participated in the discussion and commented on the paper. \n\n# Additional Information \n\nupplementary information accompanies this paper at http://www.nature.com/sre \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nHow to cite this article: Bharti, B. et al. Formation of oxygen vacancies and $\\mathrm{Ti}^{3+}$ ​state in $\\mathrm{TiO}_{2}$ thin film and enhanced optical properties by air plasma treatment. Sci. Rep. 6, 32355; doi: 10.1038/srep32355 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms12122", + "DOI": "10.1038/ncomms12122", + "DOI Link": "http://dx.doi.org/10.1038/ncomms12122", + "Relative Dir Path": "mds/10.1038_ncomms12122", + "Article Title": "Array of nullosheets render ultrafast and high-capacity Na-ion storage by tunable pseudocapacitance", + "Authors": "Chao, DL; Zhu, CR; Yang, PH; Xia, XH; Liu, JL; Wang, J; Fan, XF; Savilov, SV; Lin, JY; Fan, HJ; Shen, ZX", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Sodium-ion batteries are a potentially low-cost and safe alternative to the prevailing lithium-ion battery technology. However, it is a great challenge to achieve fast charging and high power density for most sodium-ion electrodes because of the sluggish sodiation kinetics. Here we demonstrate a high-capacity and high-rate sodium-ion anode based on ultrathin layered tin(II) sulfide nullostructures, in which a maximized extrinsic pseudocapacitance contribution is identified and verified by kinetics analysis. The graphene foam supported tin(II) sulfide nulloarray anode delivers a high reversible capacity of similar to 1,100 mAhg(-1) at 30 mA g (-1) and similar to 420 mAh g(-1) at 30 A g(-1), which even outperforms its lithium-ion storage performance. The surface-dominated redox reaction rendered by our tailored ultrathin tin(II) sulfide nullostructures may also work in other layered materials for high-performance sodium-ion storage.", + "Times Cited, WoS Core": 1196, + "Times Cited, All Databases": 1215, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000379114900001", + "Markdown": "# Array of nanosheets render ultrafast and high-capacity Na-ion storage by tunable pseudocapacitance \n\nDongliang Chao1, Changrong Zhu1, Peihua Yang1, Xinhui Xia2, Jilei Liu1, Jin Wang3, Xiaofeng Fan4, Serguei V. Savilov5, Jianyi Lin3, Hong Jin Fan1 & Ze Xiang Shen1,3 \n\nSodium-ion batteries are a potentially low-cost and safe alternative to the prevailing lithium-ion battery technology. However, it is a great challenge to achieve fast charging and high power density for most sodium-ion electrodes because of the sluggish sodiation kinetics. Here we demonstrate a high-capacity and high-rate sodium-ion anode based on ultrathin layered tin(II) sulfide nanostructures, in which a maximized extrinsic pseudocapacitance contribution is identified and verified by kinetics analysis. The graphene foam supported tin(II) sulfide nanoarray anode delivers a high reversible capacity of $\\sim1,100\\mathsf{m A h g}^{-1}$ at $30\\mathsf{m A g}^{-1}$ and ${\\sim}420\\mathsf{m A h g}^{-1}$ at $30\\mathsf{A}\\mathsf{g}^{-1},$ which even outperforms its lithium-ion storage performance. The surface-dominated redox reaction rendered by our tailored ultrathin tin(II) sulfide nanostructures may also work in other layered materials for high-performance sodium-ion storage. \n\nW ihnilecoonpsternucftrianmg ekiwnoertkicamllaytfearivaolsurhaablve pordoivuemn eNffae)c-tiiovne channels as cathodes for sodium-ion batteries $(\\mathrm{SIBs})^{1-7}$ , the sluggish Na-ion transport and severe volume expansion currently limit the rate performance and stability in most anode materials. The typical alloying materials (for example, Sn, Ge, $\\mathrm{Pb}$ , Sb) possess high capacities $\\mathrm{(Na_{15}S n_{4}}$ : $847\\mathrm{~mAh~g^{-1}}$ $\\mathrm{Na}_{3}\\mathrm{Ge}$ : $1,108\\mathrm{\\dot{mAh}g^{-1}}$ , $\\mathrm{\\DeltaNa_{15}P b_{4}}$ : $484\\mathrm{mAh}\\mathrm{g}^{-1}$ , ${\\mathrm{Na}}_{3}{\\mathrm{Sb}}$ $660\\mathrm{{mAhg}^{-1}},$ ) for Na storage but have severe volume expansion/contraction during the Na alloying/dealloying $(\\sim360-420\\%)$ (refs 8–10). To address this pulverization issue, one effective approach is to design integrated electrodes in which nanosized active materials are grafted to a secondary matrix8,10. Compared with tin (Sn) metal anodes, tin-based oxides and chalcogenides can store $\\mathrm{Na}^{+}$ through a combined electrochemical conversion and alloying mechanisms, giving rise to higher theoretical capacities $(\\mathrm{{SnO}}_{2}$ : $1,378\\mathrm{mAhg^{-1}}$ $\\mathrm{SnS}_{2}$ : $1,13\\dot{6}\\operatorname*{mAh}{\\mathrm{g}^{-1}}$ , $\\mathsf{s n s}$ : $1,\\bar{0}22\\mathrm{mAhg}^{-1},$ ) (ref. 11). Sulfides are typically more reversible than oxides due to relatively weaker ${\\bf{M}}-\\dot{\\bf{S}}$ ionic bonds compared with $\\bf{M}-\\boldsymbol{O}$ bonds, resulting in kinetically more favourable and higher first-cycle efficiency of tin chalcogenides11. Moreover, with merits of high electrical conductivity $(0.193-0.0083\\mathrm{Scm}^{-1})$ , higher capacity and earth abundancy, tin(II) sulfide (SnS) is considered to be a very promising anode material for SIBs. SnS has a smaller lattice expansion $(242\\%)$ in the sodiation/desodiation process than $\\mathrm{SnS}_{2}$ $(324\\%)$ (ref. 11). This correlates to a two-structure phase reaction in SnS (from orthorhombic-SnS to cubic-Sn to orthorhombic$\\mathrm{Na}_{15}\\mathrm{Sn}_{4})$ compared with the three-structure transformation in $\\mathrm{SnS}_{2}$ (from hexagonal- ${\\mathrm{.}}{\\mathrm{sn}}{\\mathrm{S}}_{2}$ to tetragonal-Sn to orthorhombic$\\mathrm{Na}_{15}\\mathrm{Sn}_{4}$ (ref. 11). Despite the high capacities in Sn-based alloying materials, high rate capability and fast-charging have not yet been reported, to the best of our knowledge. \n\nCompared with the diffusion-controlled process (insertion, conversion and alloying) in conventional Li/Na-ion storage battery materials, capacitive charge storage has the advantage of rendering high charging rate and therefore high power. In particular, pseudocapacitance refers to underpotential deposition, faradaic charge-transfer reactions including surface or nearsurface redox reactions and bulk fast ion intercalation12–16. Pseudocapacitance can be intrinsic or extrinsic to a material12; intrinsic ones (such as $\\mathrm{RuO}_{2}$ , $\\mathrm{MnO}_{2}$ and $\\mathrm{Nb}_{2}\\mathrm{O}_{5},$ ) display the capacitive characteristics for a wide range of particle sizes and morphologies, whereas extrinsic ones (such as $\\mathrm{LiCoO}_{2}$ , $\\mathrm{MoO}_{2}$ and $\\mathrm{\\DeltaV}_{2}\\mathrm{O}_{5}\\mathrm{,\\d}$ emerge only when they are made into nanoscale dimensions to maximize reaction sites on the surface14–17. So far, enhanced pseudocapacitive contributions have been realized in some insertion and conversion Li-ion battery (LIB) and SIB materials with high-rate performance (see summary in Supplementary Table $1)^{12,18-20}$ . However, it has not yet been implemented in alloying-type materials where the challenge is to realize high-capacity materials that can accommodate fast kinetics. \n\nHere we demonstrate and prove by quantitative kinetics analysis, the pseudocapacitive contribution to the high capacity of Na-ion storage in few-layered SnS nanosheet arrays directly grown on a graphene foam (GF) backbone (Fig. 1). To the best of our knowledge, our purposely engineered SnS nanohoneycomb structure exhibits the highest reversible capacity, rate capability compared with the reported carbon allotrope, metal/alloy and metal oxides/sulfides as SIB anodes. Excitingly, due to the maximized pseudocapacitive contribution, its rate performance in Na-ion storage even exceeds that for Li ion. Our result may bring a paradigm shift in SIB anode materials to layered metal sulfides, and also afford deeper understanding as well as other nanoscale engineering strategies to boost the performance of SIBs. \n\n# Results \n\nStructure and growth mechanism. Figure 1a–c illustrates the fabrication procedure of the flexible GF-supported SnS electrodes by a rapid one-step in situ hot bath route (details are described in the Methods section). To demonstrate the morphology-dependent property, we obtained three types of samples with gradient morphologies that are denoted as nanowall (NW), nanoflakes (NF) and nanohoneycomb (NH). Herein, it is important to control the precursor concentration and nucleation rates to achieve desirable SnS nanostructure. Our synthesis leads to a full and uniform coverage of the substrate by SnS nanostructures, for which the size distribution can also be tailored (Supplementary Fig. 1). The $\\mathrm{{sns}}$ presents average lateral sizes of 400–500, 400–500 and $50{-}70\\mathrm{nm}$ and thickness of $\\sim150$ , 10 and $5\\mathrm{nm}$ for NW, NF and NH, respectively. The growth of the SnS nanostructures is also proved substrate friendly (Ni foam, carbon cloth and ITO, see Supplementary Fig. 2). A growth mechanism is proposed based on the crucial roles of the substrate and ethanol, which involves (i) the hydrolysis of thioacetamide and (ii) the in situ metathesis reactions, self-assembly and oriented crystallization processes (details are provided in Supplementary Fig. 3 and Supplementary Note $1)^{5}$ . The structure evolution and purity are verified by X-ray diffraction , energy-dispersive spectroscopy and Raman measurements (Supplementary Figs 4 and 5). The surface chemical-bonding state of GF-SnS electrode is also detected by $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) and presented in Supplementary Fig. 6. The existence of $C{-}S$ bonds is confirmed by spectra of both S 2p ( $163.7\\mathrm{eV})$ and C 1s $(285.7\\mathrm{eV})$ . XPS results suggest that the SnS might be chemically bonded with the GF matrix besides physical deposition19 (details are provided in Supplementary Note 2). \n\nTransmission electron microscopy (TEM) and high-resolution transmission electron microscopy (HRTEM) images in Fig. 2 further confirm the crystallographic orientation and unique nanosheet-on-microstructure three-dimensional (3D) porous nanowall, nanoflake and nanohoneycomb architectures. For SnS NW (Fig. 2a,b), the lattice-resolved HRTEM image shows interplanar spacing of $2.9\\mathring\\mathrm{A}$ for the (101) planes of SnS. Further, the inset fast Fourier transform spots also reveal the existence of (101), (002) and (100) facets in the [010] zone axis, demonstrating that the layers of SnS are stacked along the [010] direction (see illustration in Fig. 1e). For SnS NF (Fig. 2c,d), the interconnected nanoflakes are regular with a periodic stacking of fringes ( $\\sim15$ layers) enforced by van der Waals interactions along the [010] direction. The layer distance is measured as $\\mathrm{\\sim}6.\\mathrm{\\overset{\\sim}{2}\\AA}$ , which is slightly larger than the layer-to-layer spacing in reported work21. The lateral view of the nanoflake in Fig. 2d also illustrates an interplanar spacing of $2.9\\mathring\\mathrm{A}$ for the (101) planes of $\\mathrm{{sns}}$ with a crystal grain size $\\sim20\\mathrm{nm}$ . The results also confirm the formation of nanosheets by stacking of (010) facets. Similarly, SnS NH also presents intrinsic corrugations and lamellar structure in the nanosheets with interlayer spacing $\\mathrm{\\sim}6.2\\mathring\\mathrm{A}.$ but with thinner thickness ( $\\sim6$ layers). Interestingly, numerous tiny nanoclusters $(\\sim5\\mathrm{nm})$ and nanocavities $(3-5\\mathrm{nm})$ are also observed from the cross-section of the wrinkles in Fig. 2f. Meanwhile, HRTEM and fast Fourier transform pattern reveals clear lattices with spacings of 3.4 and $2.8\\mathring\\mathrm{A}$ for (120) and (040) planes, respectively, under [001] zone axis. A schematic illustration of the SnS laminar structure seen from [001] zone axis can be seen from Fig. 1d. \n\nNa-ion storage performance. Our designed battery electrodes allow electron and sodium-ion transfer through the $\\mathrm{GF-SnS}$ network without the necessity of extra binders, conductive additives or metal Cu current collectors, which are essential for exploring intrinsic sodium-storage properties of active material and increasing the energy/power densities of the full cell5,22. Herein, GF serves as both a lightweight 3D porous current collector (for electron transfer) and compressible/flexible backbone. The porous nanoarray feature prevents the aggregation and expansion of SnS during charge/discharge cycles. During sodiation, electrolyte can enter the interval between nanoarrays on both outside and inner surface of GF, so that the Na ion and electrons can react with the SnS nanoarrays effectively. \n\n![](images/82e3c47267bf9e97ec6473028c26cbdf2fb4c5dbc6ab5551137fe389ded65206.jpg) \nFigure 1 | Synthesis and structure of SnS nanostructures. (a–c) SnS nanostructures synthesized in different solution concentrations for (a) nano-wall; (b) nano-flake; (c) nano-honeycomb. Scale bar, $200\\mathsf{n m}$ . (d–f) Schematic illustrations of the SnS laminar structure viewed along the [001], [010] and [100] zone axis with inserted (101) planes. \n\n![](images/c5435bf3990d5ad0719d532e0684226d886223271b044541eb6afa2b39f524f6.jpg) \nFigure 2 | TEM images of SnS nanostructures. (a,b) HRTEM images for the nanowall SnS structure. Scale bar, 5 nm. Inset a: low magnification TEM image (scale bar, $100\\mathsf{n m})$ and (b) fast Fourier transform (FFT) pattern along [010] zone axis. (c,d) HRTEM images for nanoflake SnS structure. Scale bar, $5\\mathsf{n m}$ . Insets c,d: low magnification TEM images. Scale bars of 400 and $10\\mathsf{n m}$ , respectively. (e,f) HRTEM images for nanohoneycomb SnS structure. Scale bar, $5\\mathsf{n m}$ . Inset e: low magnification TEM image. Scale bar, $30\\mathsf{n m}$ . Inset f: FFT pattern in the [001] zone axis. The dashed loops denote the mesopores. \n\n![](images/a923eac72f52d05d7fccdc708ec56518c715d6ecb56c9962db28ef381a949fef.jpg) \nFigure 3 | Electrochemical $\\pmb{{\\mathsf{M}}}\\mathbf{a}^{+}$ storage performance of SnS electrodes. (a) Galvanostatic charge/discharge profiles during the first 10 cycles of the nanohoneycomb electrode. (b) CV curves of the first three cycles of the SnS nanohoneycomb electrode at a scan rate of $0.2\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . (c) Galvanostatic charge/discharge profiles of SnS electrodes after five cycles activation. (d) Long-term cycling performances of SnS electrodes and the pure graphene foam electrode at a current density of $100\\mathsf{m A g}^{-1}$ . (e) Rate performances of SnS electrodes at various current densities from 30 to $30,000\\mathsf{m A g}^{-1}$ . (f) Fast charging (charge at $30\\mathsf{A}\\mathsf{g}^{-1}$ in 1 min, discharge at $30\\mathsf{m A g}^{-1}$ and $1\\mathsf{A}\\mathsf{g}^{-1}$ with $\\sim13\\mathfrak{h}$ and $30\\mathrm{min}$ , respectively) properties of the nanohoneycomb electrode. \n\nThe reaction of $\\mathrm{{sns}}$ with sodium undergoes two steps: conversion followed by alloying according to equations (1) and (2) (ref. 11): \n\n$$\n\\mathrm{SnS}+2\\mathrm{Na}^{+}+2\\mathrm{e}^{-}\\leftrightarrow\\mathrm{Sn}+\\mathrm{Na}_{2}\\mathrm{S}\n$$ \n\n$$\n4\\mathrm{Sn}+15\\mathrm{Na^{+}+15\\mathrm{e^{-}\\leftrightarrow\\mathrm{Na_{15}\\mathrm{Sn_{4}.}}}}\n$$ \n\nFrom the galvanostatic discharge–charge results (Fig. 3a and Supplementary Fig. 7), the first discharge presents a steep decrease and remains relatively flat in voltage. This may be due to the following two possible reasons: (1) deactivated surface and related high electrochemical polarization during the first sodiation; (2) transition from crystalline $\\mathrm{{sns}}$ to metal Sn nanograins and ${\\mathrm{Na}}_{2}{\\mathrm{S}}$ (equation (1)) (refs 11,23). However, the subsequent curves after the first three cycles almost overlap, indicating a stable surface state, structure and electrochemical reversibility after the initial activation process. The detailed reaction processes could be disclosed by the cyclic voltammetric (CV) curves (Fig. 3b). In the first cathodic scan, two prominent peaks were observed at around $0.6-0.7$ and $0.01-0.1\\mathrm{V}$ , respectively. The former is associated with both the conversion reaction (equation (1)) and the alloying reaction (equation (2), $\\mathrm{Na}_{x}S\\mathrm{n}$ , $x\\sim0.75\\$ ) because it is difficult to distinguish the conversion and alloying peaks especially in the first discharge process11,24. Obviously this peak also includes the contribution from solid electrolyte interphase (SEI) formation since its intensity significantly decays in the subsequent cycles. The peak at $0.01-0.1\\mathrm{V}$ is regarded as the reaction between Na and $\\mathrm{Na}_{x}\\mathrm{Sn}$ $(x\\ \\sim3.75)$ alloy due to the multi-step $\\mathsf{N a}\\mathrm{-}\\mathsf{S n}$ alloying feature11. In the anodic scan, a serial of small peaks below $1.4\\mathrm{V}$ $(\\sim0.3,\\ 0.7,\\ 1.2-1.4\\mathrm{V})$ correspond to the multi-step dealloying reaction of $\\mathrm{Na}_{x}\\mathrm{Sn}$ (ref. 24); whereas the distinct peak at $\\mathrm{\\sim}1.7\\mathrm{V}$ could be attributed to the reversible conversion reaction from Sn to SnS, which was also observed in $\\mathrm{SnS}@\\mathrm{G}^{11}$ , 3D porous interconnected $\\mathrm{{sns}}$ (ref. 25), and proved by ex situ Raman results of the electrodes after charging and discharging processes (Supplementary Fig. 8). \n\nThe first sodiation and desodiation capacities of $\\mathrm{GF-SnS~NH}$ are 1,416 and $1,147\\mathrm{mAh}\\mathbf{g}^{-1}$ , respectively, calculated based on active materials. A rather high first-cycle coulombic efficiency of $>80\\%$ is observed. A reversible capacity more than $1,100\\mathrm{mAhg}^{-1}$ could be maintained in the following cycles. We note this value is higher than all reported ones from sodium alloys, oxides, sulfides and carbonaceous anodes so far (see comprehensive comparison in Supplementary Table 2), to the best of our knowledge. Note that the pure GF contributed negligibly to the capacity: $\\sim30\\mathrm{mAhg^{-1}}$ for the first discharge process and $<10\\dot{\\mathrm{mAh}}\\dot{\\mathrm{g}}^{-1}$ in the following cycles. Compared with NH electrode, NF presents a similar behaviour due to their similar microtopography, whereas the NW one exhibits a suppressed capacity and higher polarization. More importantly, the voltage profile in NW electrode shows more obvious plateaus, which is a typical feature of diffusion-controlled charge storage of battery materials16. The improvements in the coulombic efficiency and high reversible capacity of GF–SnS NH electrode should be correlated to the reversible formation/decomposition of the polymeric film on the surface of $\\mathsf{S n S~N H}$ (refs 11,26), its distinct disorder two-dimensional structure, ultrathin-layered mesoporous $\\mathrm{\\Delta}S_{\\mathrm{n}S}$ nanocrystals, and as a result, its unique electrochemical mechanism (capacitive contribution), which is to be discussed below. The $\\mathrm{GF-SnS}$ electrodes deliver excellent capacity retention from the third cycle onwards. After 200 cycles, the capacity retains at $1,010\\mathrm{mAh}\\dot{\\bf g}^{-1}$ for the NH electrode with well-preserved microstructure (Supplementary Fig. 9). \n\nThe rate capability is a crucial indicator for large scale application of batteries, such as regenerative braking and fast recharging of electric vehicles and cellphones. The drawback of low power becomes particularly evident in high capacity (that is, high energy density) materials14. It is found that the NH electrode has the best rate capability, in addition to consistently highest capacity, among the three $\\mathrm{\\dot{G}F–S n S}$ electrodes (see Fig. 3e). For a 1,000-fold increase in current density (from 30 to $\\bar{30}\\mathrm{Ag^{-1}}\\bar{.}$ ), a discharge capacity of more than $400\\mathrm{{\\dot{m}A h\\:g^{-1}}}$ (in $1\\mathrm{min}\\dot{}$ ) could still be retained. If this electrode were used to power a cellphone system, it is estimated that the battery could be charged in 1 min and discharged in $\\sim13\\mathrm{h}$ at $30\\mathrm{mAg}^{-1}$ (Fig. 3f). On the basis of a comprehensive summary (Supplementary Table 2), this is the best rate capability among all reported anode materials for SIBs, to the best of our knowledge. The preliminary result of full-cell fabrication (see Supplementary Fig. 10, $\\mathrm{Na}_{3}(\\mathrm{VO)}_{2}(\\mathrm{PO}_{4})_{2}\\mathrm{F}$ cathode\\\\SnS anode) demonstrates the potential commercial application of our SnS electrodes to be considered as an anode material for SIBs, although further optimization is urgent to improve the skill in full-cell fabrication and cycling stability. \n\nKinetics and quantitative analysis. To explain the high-rate performance, we analysed the redox pseudocapacitance-like contribution in the $\\mathrm{\\stackrel{.}{G F-S n S}}$ electrodes by investigating the kinetics of the $\\mathrm{{sns}}$ electrodes (Fig. 4) to separate the diffusioncontrolled capacity and capacitive capacity15,27. Resulting from the stepwise sodiation mechanism, CV curves with similar shapes at various scan rates from 0.2 to $0.8\\mathrm{mVs}^{-1}$ (Supplementary Fig. 11) display two broad cathodic peaks as the scan rate increases. As cation intercalation reaction can be ruled out from our SnS electrode, we mainly consider the below three charge-storage mechanisms: the diffusion-controlled faradaic contribution from conversion and alloying reaction, the faradaic contribution from charge transfer with surface/ subsurface atoms (that is, extrinsic pseudocapacitance effect), and the non-faradaic contribution from electrical double-layer effect17,19,20. \n\nThe ratios of Na-ion capacitive contribution can be further quantitatively quantified by separating the current response $i$ at a fixed potential $V$ into capacitive effects (proportional to the scan rate $\\nu$ ) and diffusion-controlled reactions $(\\dot{k}_{2}\\nu^{1/2})$ , according to Dunn15,28: \n\n$$\ni(V)=k_{1}\\nu+k_{2}\\nu^{1/2}\n$$ \n\nBy determining both $k_{1}$ and $k_{2}$ constants, we can distinguish the fraction of the current from surface capacitance and $\\mathrm{Na}^{+}$ semiinfinite linear diffusion. Fig. 4a shows the typical voltage profile for the capacitive current (red region) in comparison with the total current. A dominating capacitive contribution $(\\sim84\\%)$ is obtained for the NH electrode. As the scan rate increases, the role of capacitive contribution further enlarges (Fig. 4b) with a maximum value of $\\sim95\\%$ at $5\\mathrm{mV}s^{-1}$ . By similar analysis, the pseudocapacitive contribution is found more than $80\\%$ for the NF electrode, but only around $60\\%$ for the NW one at $0.8\\mathrm{mVs^{-1}}$ (Supplementary Figs 12 and 13). This is unsurprising since the pseudocapacitive contribution should play a critical role for smaller particle size with high surface area $(\\sim154\\mathrm{m}^{2}\\mathrm{g}^{-1})$ and/or high porosity (mesoporous from 7 to $37\\mathrm{nm}$ , see Supplementary Fig. 14)15,18. Finally, the thin-film electric conductivity (Supplementary Fig. 15) and electrochemical impedance spectra (Supplementary Fig. 16) suggest that the NH electrode have a favourable charge transfer kinetics compared with NW electrode. \n\nComparison with Li-ion storage capability. It is widely believed that $\\bar{\\bf N}{\\bf a}^{+}$ transport and storage are more sluggish with more severe lattice expansion than the $\\mathrm{Li^{+}}$ one because of the larger radius of Na ions1,29–32. So far, the performance in SIB is generally worse than that in LIBs when the same electrode material is used, including capacity, high rate capability and polarization. Herein, we carefully compare the performance of SnS NH anode for both $\\mathrm{Na}^{+}$ and $\\mathrm{Li^{+}}$ tests. \n\nTo avoid the influence on Li uptakes in GF backbone, in our comparison experiment we used the SnS NH grown on Ni foam as the same electrode. Figure 5 shows the results. Strikingly, one can see the rate capacity for sodiation/desodiation is superior to $\\mathrm{Li^{+}}$ uptakes, particularly in the high-rate regions. At current of $30\\mathrm{Ag^{\\frac{\\cdot}{-}1}}$ , the electrode delivers a $\\bar{\\mathrm{Na}}^{+}$ discharge capacity of $\\sim$ $410\\mathrm{\\dot{mAh}g^{-1}}$ compared with $\\sim105\\mathrm{mAhg}^{-1}$ for the $\\mathrm{Li^{+}}$ electrode. In the galvanostatic charge/discharge processes (Fig. 5b), the $\\mathrm{Li^{+}}$ electrode shows two distinct plateaus at $1.2-1.4$ and $0.01-0.4\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ corresponding to their CV curves (Supplementary Fig. 17a), suggesting a lower fraction of capacitive contribution. The first discharge plateau during lithiation is attributed to the conversion reaction from $\\mathrm{SnS}\\to\\mathrm{Sn}$ and the second one is the alloying reaction-forming $\\mathrm{Li}_{15}\\mathrm{Sn}_{4}$ phase33,34. The polarization from $30\\mathrm{\\stackrel{\\smile}{m A}g^{-1}}$ to $7\\mathrm{Ag}^{-1}$ during lithiation $\\mathrm{\\hbar}\\langle\\sim340\\mathrm{mV}\\rangle$ is twice to that in sodiation $\\mathrm{\\Phi}(\\sim170\\mathrm{mV})$ . In addition, the capacitive fraction for $\\mathrm{Li^{+}}$ storage is $75\\%$ (inset in Fig. 5b), whereas $85\\%$ for the $\\mathrm{Na}^{+}$ storage of the same electrode (Supplementary Fig. 18). Similar higher $\\mathrm{Na}^{+}$ capacitive contribution than that of $\\mathrm{Li^{+}}$ had also been observed in $\\mathrm{Li}_{4}\\mathrm{Ti}_{5}\\mathrm{O}_{12}$ spinel thin film electrode but with much lower discharge capacity20. Finally, the sodiation discharge curves have more moderate and continuous operation voltage than the lithiation ones (Fig. 5b), which is favourable to achieving high energy density of full cells and avoiding dendrite growth19. \n\n![](images/abaf82940dcf0b2f87ec524d00304f816710d2c24586f535af45b92cb9366378.jpg) \nFigure 4 | Kinetics and quantitative analysis of the $\\pmb{{\\mathsf{N}}}\\mathbf{a}^{+}$ storage mechanism. (a) Capacitive (red) and diffusion-controlled (blue) contribution to charge storage of nanohoneycomb at $0.8\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . (b) Normalized contribution ratio of capacitive (red) and diffusion-controlled (blue) capacities at different scan rate. \n\n![](images/3fb74c4f7db47117b933249e27ca2b5db35794fb692a97204a7644d87d0dbdf1.jpg) \nFigure 5 | Comparison between Na-ion and Li-ion storage. (a) Rate performance comparison of the nanohoneycomb electrode at various current densities from 30 to $30,000\\mathsf{m A g}^{-1}$ . (b) Galvanostatic profiles of Na, Li electrodes at rates of $30\\mathsf{m A g}^{-1}$ and $7\\mathsf{A g}^{-1}$ after activation. Inset: capacitive (red) and diffusion-controlled (blue) contribution to charge storage at $0.8\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ during Li uptake. All of the batteries were tested in the same voltage range of $0.01-3V$ versus $\\mathsf{N a}/\\mathsf{N a}^{+}$ and ${\\mathsf{L i}}/{\\mathsf{L i}}^{+}$ for Na-ion and Li-ion batteries, respectively. \n\n# Discussion \n\nThe results presented above demonstrate sodium-ion storage with both high capacity and high rate capability rendered by tunable extrinsic pseudocapacitance in our GF-supported SnS nanosheets. The electrode architecture provides, to the best of our knowledge, the highest reported reversible capacity of $1,100\\mathrm{mAhg}^{-1}$ at $30\\mathrm{mA}\\mathbf{\\check{g}}^{-1}$ . Even at a high current density of $30\\mathrm{{Ag}^{-1}}$ (1,000-fold increase), the capacity is retained at 400 mAh g \u0002 which is higher than that of $\\mathrm{Li^{+}}$ electrode $(\\sim105\\mathrm{mAh}\\mathrm{g}^{-1}$ at $30\\mathrm{Ag^{-1}})$ . As the diffusion time of ions $\\mathbf{\\rho}(t)$ is proportional to the square of the diffusion length ( $\\zeta),t\\approx L^{2}/\\dot{D},$ a short lithium diffusion time of $\\sim0.01$ s is obtained on the basis of the ultrathin SnS architectures. As a consequence, similar to supercapacitors, the limiting factor for high rate charge/discharge is the transfer of ions and electrons to the surface of nanosheets rather than the conventional solid-state diffusion. As schematically shown in Fig. 6, the strongly solvating groups (carbonyl groups) in the organic electrolyte will arrange in an appropriate manner as a preferred solvation shell of the cations $(\\dot{\\mathrm{Li}}^{+}$ or $\\mathrm{Na}^{+}$ ) (refs 35–37), and it has been proven that sodium ion presents a weaker solvation shell with smaller de-solvation energy and lower activation barrier for sodiation transport compared with the lithium ion35,38. In additionally, higher mobility and conductivity of $\\mathrm{Na}^{+}$ solutions also contribute to the ion transfer in the electrolyte39,40. As a result, faster sodiation/desodiation kinetics are possible for SIBs as compared with LIBs35,39–41. \n\nThe surface-dominated extrinsic pseudocapacitance is identified as a major energy-storage mechanism in favour of high capacity and fast $\\mathrm{Na^{+}}$ uptakes (Fig. 6). First, the chemically bonded $\\mathrm{GF-SnS}$ hybrid demonstrates excellent structure stability and electronic/ionic conductivity through the network, which have also been shown to be a prerequisite for the extrinsic pseudocapacitance in nanosized $\\mathrm{MoO}_{2}$ (ref. 16). Moreover, the nanoscale dimension, especially thickness of the electrode materials, has been emphasized to be an important factor on the rate properties and corresponding redox capacitive contribution20,27,42,43. Compared with the SnS NW, the few layered architecture and mesoporous iso-oriented nanocrystals nature of the NH enables an interior $\\mathrm{Na}^{+}$ or electrolyte access into the van der Waals gaps of nanosheets, and thus results in both the exterior and interior parts participating in the electrochemical reaction15. This feature also facilitates ion access and shortens the ion diffusion. \n\nOur kinetics analysis verifies the surface-dominated redox reaction mechanism in the Na-ion storage process, whereas the battery-type diffusion contribution is suppressed. This is closely correlated to the engineered thin-sheet structure of $\\mathrm{\\sn{s}\\ N H}$ , and may account for the superior $\\mathrm{Na}^{+}$ storage performance (high rate capacity) of the $\\mathrm{\\sns{\\bar{N}H}}$ to its $\\mathrm{Li^{+}}$ one. This strategy renders increased power density with maintained high energy density. This encouraging result may accelerate further development of SIBs by smart nanoengineering of the electrode materials. \n\n![](images/f93362c8ac47f12bf94a57f07b4a92d9dc4f8851deabf3f31cf17ae61a7a1b55.jpg) \nFigure 6 | Schematic illustration of high-rate charge storage of SnS architecture. During transfer of ions and electrons, the solvated ${\\mathsf{N a}}^{+}$ /electron can easily enter into the open spaces between neighbouring ultrathin nanosheets on both the outside and inner surface of the graphene foam. After de-solvation of ${\\mathsf{N a}}^{+}$ on the surface of the layered SnS architecture, rapid sodiation takes place by the surface-dominated extrinsic pseudocapacitance. \n\n# Methods \n\nSynthesis and characterization. SnS nanostructures were fabricated by a facile hot bath method. First, precursors with three sets of different concentrations, namely, high, medium and low concentrations of $\\mathrm{tin}(\\mathrm{II})$ chloride dehydrate: thioacetamide, respectively for nanowall $(100{:}300\\mathrm{mM})$ , nanoflake $\\left(50{:}150\\mathrm{mM}\\right)$ and nanohoneycomb $(25{:}75\\mathrm{mM})$ , were dissolved in $50\\mathrm{ml}$ ethanol at $80^{\\circ}\\mathrm{C}$ . Then 3D $\\mathrm{GFs}(2\\times5\\mathrm{cm}^{2}$ , $\\sim0.8\\mathrm{mg}\\mathrm{cm}^{-2}$ , prepared by chemical vapour deposition method according to our previous result44) or other type of substrates such as Ni foam, carbon cloth and ITO glass were immersed into the above reaction solutions and kept for $45\\mathrm{min}$ . Finally, the samples were collected and rinsed with distilled water and ethanol in turn three times, and dried at $150^{\\circ}\\mathrm{C}$ in vacuum to obtain 3D GF-supported SnS free-standing electrodes. The SnS loading was $\\sim1.0\\mathrm{mg}\\mathrm{cm}^{-2}$ for nanoflake and nanohoneycomb electrode, and $1.2\\mathrm{mg}\\mathrm{cm}^{-2}$ for nanowall electrode. \n\nThe crystal structures of the samples were identified using X-ray diffraction (RigakuD/Max-2550 with $\\mathrm{Cu-K}\\mathfrak{a}$ radiation). Raman spectra were obtained with a WITec-CRM200 Raman system (WITec, Germany) with a laser wavelength of $532\\mathrm{nm}$ $(2.33\\mathrm{eV})$ ). The morphologies of the samples were characterized by field emission scanning electron microscopy. The structures of the samples were investigated by HRTEM(JEOL JEM-2010F at $200\\mathrm{kV},$ . The XPS measurements were performed by a VG ESCALAB 220i-XL system using a monochromatic Al Ka1 source $(1,486.6\\mathrm{eV})$ . The thin-film electric conductivity was measured by four-point probe sheet resistance. The surface area of the SnS electrode was determined by $\\Nu_{2}$ adsorption/desorption isotherms. \n\nElectrochemical measurements. Standard CR2032-type coin cells were assembled in an argon-filled glove box (Mbraun, Germany) with the as-fabricated GF-supported $\\mathrm{{sns}}$ nanoarrays as the working electrode (without any binder or additives). For SIB fabrication, the metallic sodium foil as the counter-electrode, $1\\mathrm{M}\\mathrm{NaPF}_{6}$ in ethylene carbonate (EC)–diethyl carbonate (DEC)–fluoroethylene carbonate (FEC) (1:1:0.03 in volume) as the electrolyte, and glass fibre as the separator. For the LIB case, except for the metallic lithium foil as the counterelectrode and $1\\mathrm{M}\\mathrm{LiPF}_{6}$ as the solute, the other parameters are the same with the SIB fabrication. For full-cell testing, the cathode-active material was $\\mathrm{Na}_{3}(\\mathrm{VO})_{2}(\\mathrm{PO}_{4})_{2}\\mathrm{F}$ nanoparticle. The one-time discharge/charge cycled $\\mathrm{\\sn{s}\\ N H}$ served as the anode. The weight ratio between anode and cathode active material was $\\sim0.15{:}1$ . The specific capacity was calculated based on the mass of the cathode-active material. The CV measurements were carried out using CHI660 electrochemical workstation. Electrochemical impedance spectroscopy was recorded on Solartron 1470E, the amplitude of the sine perturbation signal was $5\\mathrm{mV}$ , and the frequency was scanned from the highest $({\\mathrm{10}}\\mathrm{kHz})$ to the lowest $(5\\mathrm{mHz})$ . Galvanostatic charge discharge cycles were tested by Neware battery tester at different current densities at room temperature. \n\nData availability. The authors declare that the data supporting the findings of this study are available within the article and its Supplementary Information files. \n\n# References \n\n1. Larcher, D. & Tarascon, J. M. Towards greener and more sustainable batteries for electrical energy storage. Nat. Chem. 7, 19–29 (2015). \n2. Li, C. et al. An FeF3 \u0004 $0.5\\mathrm{H}_{2}\\mathrm{O}$ polytype: a microporous framework compound with intersecting tunnels for Li and Na batteries. J. Am. Chem. Soc. 135, 11425–11428 (2013). \n3. Yabuuchi, N. et al. P2-type $\\mathrm{Na}(\\mathrm{x})[\\mathrm{Fe}(1/2)\\mathrm{Mn}(1/2)]\\mathrm{O}2$ made from earthabundant elements for rechargeable Na batteries. Nat. Mater. 11, 512–517 (2012). \n4. Fang, Y. et al. Mesoporous amorphous $\\mathrm{FePO_{4}}$ nanospheres as highperformance cathode material for sodium-ion batteries. Nano Lett. 14, 3539–3543 (2014). \n5. Chao, D. et al. Graphene quantum dots coated $\\mathrm{VO}_{2}$ arrays for highly durable electrodes for Li and Na ion batteries. Nano Lett. 15, 565–573 (2015). \n6. Lim, S. Y. et al. Role of intermediate phase for stable cycling of $\\mathrm{Na_{7}V_{4}(P_{2}O_{7})_{4}P O_{4}}$ in sodium ion battery. Proc. Natl Acad. Sci. USA 111, 599–604 (2013). \n7. Liu, H., Xu, J., Ma, C. & Meng, Y. S. A new $\\mathrm{O}_{3}$ -type layered oxide cathode with high energy/power density for rechargeable Na batteries. Chem. Commun. 51, 4693–4696 (2015). \n8. Wu, L. et al. Electrochemical properties and morphological evolution of pitaya-like Sb@C microspheres as high-performance anode for sodium ion batteries. J. Mater. Chem. A 3, 5708–5713 (2015). \n9. Kohandehghan, A. et al. Activation with Li enables facile sodium storage in germanium. Nano Lett. 14, 5873–5882 (2014). \n10. Xie, X. et al. Sn@CNT nanopillars grown perpendicularly on carbon paper: a novel free-standing anode for sodium ion batteries. Nano Energy 13, 208–217 (2015). \n11. Zhou, T. et al. Enhanced sodium-ion battery performance by structural phase transition from two-dimensional hexagonal-SnS2 to orthorhombic-SnS. ACS Nano 8, 8323–8333 (2014). \n12. Augustyn, V., Simon, P. & Dunn, B. Pseudocapacitive oxide materials for highrate electrochemical energy storage. Energy Environ. Sci. 7, 1597–1614 (2014). \n13. Augustyn, V. et al. High-rate electrochemical energy storage through $\\operatorname{Li}+$ intercalation pseudocapacitance. Nat. Mater. 12, 518–522 (2013). \n14. Simon, P., Gogotsi, Y. & Dunn, B. Where do batteries end and supercapacitors begin? Science 343, 1210–1211 (2014). \n15. Brezesinski, T., Wang, J., Tolbert, S. H. & Dunn, B. Ordered mesoporous alphaMoO3 with iso-oriented nanocrystalline walls for thin-film pseudocapacitors. Nat. Mater. 9, 146–151 (2010). \n16. Kim, H. S., Cook, J. B., Tolbert, S. H. & Dunn, B. The development of pseudocapacitive properties in nanosized- $\\mathbf{\\cdot}\\mathbf{MoO}_{2}$ . J. Electrochem. Soc. 162, A5083–A5090 (2015). \n17. Li, S. et al. Surface capacitive contributions: towards high rate anode materials for sodium ion batteries. Nano Energy 12, 224–230 (2015). \n18. Chen, Z. et al. High-performance sodium-ion pseudocapacitors based on hierarchically porous nanowire composites. ACS Nano 6, 4319–4327 (2012). \n19. Chen, C. et al. $\\mathrm{{Na}(^{+})}$ intercalation pseudocapacitance in graphene-coupled titanium oxide enabling ultra-fast sodium storage and long-term cycling. Nat. Commun. 6, 6929 (2015). \n20. Yu, P., Li, C. & Guo, X. Sodium storage and pseudocapacitive charge in textured $\\mathrm{Li_{4}T i_{5}O_{12}}$ thin films. J. Phys. Chem. C 118, 10616–10624 (2014). \n21. Gou, X.-L., Chen, J. & Shen, P.-W. Synthesis, characterization and application of SnSx $(\\mathbf{x}=1,2^{\\cdot}$ nanoparticles. Mater. Chem. Phys. 93, 557–566 (2005). \n22. Sun, Y. et al. Direct atomic-scale confirmation of three-phase storage mechanism in $\\mathrm{Li}_{4}\\mathrm{Ti}_{5}\\mathrm{O}_{12}$ anodes for room-temperature sodium-ion batteries. Nat. Commun. 4, 1870 (2013). \n23. He, K. et al. Sodiation kinetics of metal oxide conversion electrodes: a comparative study with lithiation. Nano Lett. 15, 5755–5763 (2015). \n24. Ma, C. Z. et al. Investigating the energy storage mechanism of $\\mathrm{SnS}_{2}$ -rGO composite anode for advanced $\\mathrm{{Na}}$ -ion batteries. Chem. Mater. 27, 5633–5640 (2015). \n25. Zhu, C. B. et al. A general strategy to fabricate carbon-coated 3D porous interconnected metal sulfides: case study of SnS/C nanocomposite for highperformance lithium and sodium ion batteries. Adv. Sci. 2, 1500200 (2015). \n26. Luo, B. et al. Two dimensional graphene– ${\\cdot}\\mathrm{Sn}{\\cal S}_{2}$ hybrids with superior rate capability for lithium ion storage. Energy Environ. Sci. 5, 5226–5230 (2012). \n27. Muller, G. A., Cook, J. B., Kim, H. S., Tolbert, S. H. & Dunn, B. High performance pseudocapacitor based on 2D layered metal chalcogenide nanocrystals. Nano Lett. 15, 1911–1917 (2015). \n28. Bard, A. J. & Faulkner, L. R. Electrochemical Method: Fundamentals and Applications (John Wiley & Sons, 1980). \n29. Kim, H. et al. Aqueous rechargeable Li and Na ion batteries. Chem. Rev. 114, 11788–11827 (2014). \n30. Kundu, D., Talaie, E., Duffort, V. & Nazar, L. F. The emerging chemistry of sodium ion batteries for electrochemical energy storage. Angew. Chem. Int. Ed. Engl. 54, 3431–3448 (2015). \n31. Xu, X. et al. In situ investigation of Li and Na ion transport with single nanowire electrochemical devices. Nano Lett. 15, 3879–3884 (2015). \n32. Wang, Y. et al. A zero-strain layered metal oxide as the negative electrode for long-life sodium-ion batteries. Nat. Commun. 4, 2365 (2013). \n33. Lu, J., Nan, C., Li, L., Peng, Q. & Li, Y. Flexible SnS nanobelts: facile synthesis, formation mechanism and application in Li-ion batteries. Nano Res. 6, 55–64 (2012). \n34. Tripathi, A. M. & Mitra, S. The influence of electrode structure on the performance of an SnS anode in Li-ion batteries: effect of the electrode particle, conductive support shape and additive. RSC Adv. 5, 23671–23682 (2015). \n35. Ponrouch, A. et al. Non-aqueous electrolytes for sodium-ion batteries. J. Mater. Chem. A 3, 22–42 (2015). \n36. Ponrouch, A., Marchante, E., Courty, M., Tarascon, J. M. & Palacin, M. R. In search of an optimized electrolyte for Na-ion batteries. Energy Environ. Sci. 5, 8572–8583 (2012). \n37. Abe, T., Fukuda, H., Iriyama, Y. & Ogumi, Z. Solvated Li-ion transfer at interface between graphite and electrolyte. J. Electrochem. Soc. 151, A1120–A1123 (2004). \n38. Jonsson, E. & Johansson, P. Modern battery electrolytes: ion-ion interactions in $\\mathrm{Li^{+}/N a^{+}}$ conductors from DFT calculations. Phys. Chem. Chem. Phys. 14, 10774–10779 (2012). \n39. Yabuuchi, N., Kubota, K., Dahbi, M. & Komaba, S. Research development on sodium-ion batteries. Chem. Rev. 114, 11636–11682 (2014). \n40. Zhang, Y., Narayanan, A., Mugele, F., Cohen Stuart, M. A. & Duits, M. H. G. Charge inversion and colloidal stability of carbon black in battery electrolyte solutions. Colloids Surf. A 489, 461–468 (2016). \n41. Ong, S. P. et al. Voltage, stability and diffusion barrier differences between sodium-ion and lithium-ion intercalation materials. Energy Environ. Sci. 4, 3680–3688 (2011). \n42. Come, J. et al. Electrochemical kinetics of nanostructured ${\\mathrm{Nb}}_{2}{\\mathrm{O}}_{5}$ electrodes. J. Electrochem. Soc. 161, A718–A725 (2014). \n43. McDowell, M. T. et al. In situ observation of divergent phase transformations in individual sulfide nanocrystals. Nano Lett. 15, 1264–1271 (2015). \n44. Chao, D. et al. A $\\mathrm{V}_{2}\\mathrm{O}_{5}/$ conductive-polymer core/shell nanobelt array on three-dimensional graphite foam: a high-rate, ultrastable, and freestanding cathode for lithium-ion batteries. Adv. Mater. 26, 5794–5800 (2014). \n\n# Acknowledgements \n\nZ.X.S. acknowledge the financial supported by Ministry of Education, Tier 1 (Grant number: M4011424.110), Tier 2 (Grant number: M4020284.110); H.J.F. acknowledges the financial supported by MOE AcRF Tier 1 (RG104/14, RG98/15). We also \n\nacknowledge support from the Energy Research Institute $\\varrho\\mathrm{NTU}$ (ERI@N). We thank Professor Bruce Dunn, University of California, Los Angeles for useful discussions. \n\n# Author contributions \n\nD.L.C. and C.R.Z. conceived the experiment. D.L.C., C.R.Z., P.H.Y., X.H.X., J.L.L. and J.W. conducted the material synthesis, characterization and electrochemical measurement. X.F.F., S.V.S., J.Y.L., H.J.F. and Z.X.S. were involved in discussion on the kinetics and quantitative analysis. D.L.C., C.R.Z., H.J.F. and Z.X.S. wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Chao, D. et al. Array of nanosheets render ultrafast and high-capacity Na-ion storage by tunable pseudocapacitance. Nat. Commun. 7:12122 doi: 10.1038/ncomms12122 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2016 " + }, + { + "id": "10.1126_science.aaf9050", + "DOI": "10.1126/science.aaf9050", + "DOI Link": "http://dx.doi.org/10.1126/science.aaf9050", + "Relative Dir Path": "mds/10.1126_science.aaf9050", + "Article Title": "Ultrafine jagged platinum nullowires enable ultrahigh mass activity for the oxygen reduction reaction", + "Authors": "Li, MF; Zhao, ZP; Cheng, T; Fortunelli, A; Chen, CY; Yu, R; Zhang, QH; Gu, L; Merinov, BV; Lin, ZY; Zhu, EB; Yu, T; Jia, QY; Guo, JH; Zhang, L; Goddard, WA ; Huang, Y; Duan, XF", + "Source Title": "SCIENCE", + "Abstract": "Improving the platinum (9Pt) mass activity for the oxygen reduction reaction (ORR) requires optimization of both the specific activity and the electrochemically active surface area (ECSA). We found that solution-synthesized Pt/NiO core/shell nullowires can be converted into PtNi alloy nullowires through a thermal annealing process and then transformed into jagged Pt nullowires via electrochemical dealloying. The jagged nullowires exhibit an ECSA of 118 square meters per gram of Pt and a specific activity of 11.5 milliamperes per square centimeter for ORR 9 (at 0.9 volts versus reversible hydrogen electrode), yielding a mass activity of 13.6 amperes per milligram of Pt, nearly double previously reported best values. Reactive molecular dynamics simulations suggest that highly stressed, undercoordinated rhombus-rich surface configurations of the jagged nullowires enhance ORR activity versus more relaxed surfaces.", + "Times Cited, WoS Core": 1346, + "Times Cited, All Databases": 1413, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000390261300041", + "Markdown": "# Ultrafine jagged platinum nanowires enable ultrahigh mass activity for the oxygen reduction reaction \n\nMufan Li,1 Zipeng Zhao,2 Tao Cheng,3 Alessandro Fortunelli,3,4 Chih-Yen Chen,2 Rong Yu,5 Qinghua Zhang,6 Lin Gu,6 Boris Merinov,3 Zhaoyang Lin,1 Enbo Zhu,2 Ted Yu,3,7 Qingying Jia,8 Jinghua Guo,9 Liang Zhang,9 William A. Goddard III,3\\* Yu Huang,2,10\\* Xiangfeng Duan1,10\\* \n\n1Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA. 2Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA. 3Materials and Process Simulation Center, California Institute of Technology, Pasadena, CA 91125, USA. 4CNR-ICCOM, Consiglio Nazionale delle Ricerche, 56124 Pisa, Italy. 5National Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, P. R. China. 6Institute of Physics, Chinese Academy of Sciences, Beijing 100190, P. R. China. 7Department of Chemical Engineering, California State University, Long Beach, CA 90840, USA. 8Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA. 9Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. 10California NanoSystems Institute, University of California, Los Angeles, CA 90095, USA. \n\n\\*Corresponding author. Email: wag@wag.caltech.edu (W.A.G.); yhuang@seas.ucla.edu (Y.H.); xduan@chem.ucla.edu (X.D.) \n\nImproving the platinum (Pt) mass activity for the oxygen reduction reaction (ORR) should optimize both the specific activity and the electrochemical active surface area (ECSA). We show solution-synthesized Pt/NiO core/shell nanowires can be converted into PtNi alloy nanowires through a thermal annealing process, and then transformed into jagged Pt nanowires via an electrochemical dealloying. The jagged nanowires exhibit an ECSA of $\\mathsf{118}\\mathsf{m}^{2}$ per gram Pt and a specific activity of $11.5\\mathsf{m A}$ per square centimeter for ORR (at 0.9 V versus reversible hydrogen electrode) for a mass activity of 13.6 ampere per milligram Pt, nearly doubling previously reported best values. Reactive molecular dynamics simulations suggest that highly stressed, under-coordinated rhombohedral-rich surface configurations of the jagged nanowires enhanced ORR activity versus more relaxed surfaces. \n\nPlatinum $\\left(\\mathrm{Pt}\\right)$ represents the essential element for catalyzing the oxygen reduction reaction (ORR) (1–3). However, the catalyzed ORR rate remains sluggish that the high cost of Pt becomes the primary limiting factor preventing the widespread adoption of fuel cells $(4,5)$ , and higher Pt mass activity (the catalytic activity per given mass of $\\mathrm{Pt}{\\bf\\ddot{\\Lambda}}$ ) must be achieved. The Pt mass activity is determined by the specific activity (SA, normalized by surface area) and the electrochemically active surface area (ECSA, normalized by mass). The SA can be optimized by tuning the chemical environment, including chemical composition $(6-9)$ , exposed catalytic surface (1, 10–12), and $\\mathrm{Pt}$ coordination environment (13–16). To date, the highest SAs has generally been achieved on single crystal surfaces or well-defined nanoparticles (NPs) with specifically engineered facet structure and alloy compositions. For example, the $\\mathrm{Pt_{3}N i}$ (111) single crystal facet (1) and subsequently $\\mathrm{Pt_{3}N i}$ octahedral NPs have been shown to exhibit ORR-favorable surface structure for greatly enhanced activity (17–19), but such alloys typically suffer from insufficient stability because of electrochemical leaching of Ni during electrochemical cycling and decreased ECSA because of agglomeration of the NPs. Introduction of Mo surface dopants can mitigate such leaching processes and help maintain the ORR-favorable $\\mathrm{Pt_{3}N i}$ (111) surface for enhanced activity and stability (19). Although high SA has been achieved on these structures, the reported ECSA for these optimized structures are typically limited to $\\sim70$ $\\mathrm{m^{2}/g_{P t}}$ . On the other hand, the ECSA may be improved by tailoring the geometrical factors including creating ultrafine nanostructures (20, 21) or core/shell nanostructures with an ultrathin Pt skin (22–24) that exposes most Pt atoms on the surface. \n\nTo boost Pt mass activity and Pt utilization efficiency, an ideal catalyst should have an ORR-favorable chemical environment for high SA, optimized geometric factors for high ECSA (20–24), and a mechanism to maintain these high values for long periods of operation. We report the preparation of ultrafine jagged Pt nanowires (J-PtNWs) with rich ORR-favorable rhombic configurations to lead to an SA of $\\mathrm{11.5\\mA/cm^{2}}$ (at $0.9{\\mathrm{~V~}}$ versus RHE: reversible hydrogen electrode) and an ECSA of $118~\\mathrm{m^{2}/g_{P t}}$ . Together, these J-PtNWs deliver a mass activity of $13.6~\\mathrm{A/mg_{Pt}}$ (at $0.9{\\mathrm{~V~}}$ versus RHE), which is $\\sim50$ times higher than state-of-the-art commercial $\\mathrm{Pt/C}$ catalyst, and nearly doubles the highest previously reported mass activity values of $6.98~\\mathrm{{\\A/mg_{Pt}}}$ (19) and 5.7 $\\mathrm{{A/mg_{Pt}}}$ (23). Finally, the PtNi alloy NWs were electrochemically dealloyed to produce ultrafine pure Pt NWs with jagged surfaces. Here, Ni does not play an active electronic or structural role but is sacrificial, as it is leached entirely to form pure J-PtNWs. \n\nWe prepared $\\mathrm{Pt/NiO}$ core/shell NWs by reducing platinum (II) acetylacetonate $\\mathrm{[Pt(acac)_{2}]}$ and nickel(II) acetylacetonate $\\mathrm{[Ni(acac)_{2}]}$ in a mixture solvent of 1-octadecene (ODE) and oleylamine (OAm) (25). Transmission electron microscopy (TEM) studies show that the as-synthesized NWs exhibit an apparent core/shell structure with a contrast of darker core and lighter shell. The NWs have a typical overall diameter $\\sim5~\\mathrm{{nm}}$ or less, and a length between about 250 to ${300}~\\mathrm{{nm}}$ (Fig. 1A and fig. S1A). High-resolution TEM (HRTEM) studies confirm the core/shell structure with a typical core diameter of $2.0\\ \\mathrm{nm}\\pm\\ 0.2\\ \\mathrm{nm}$ (Fig. 1D). The shell shows well-resolved lattice fringes with the spacing of $0.24\\ \\mathrm{nm}$ , corresponding to the (111) lattice planes of facecentered cubic (fcc) NiO (Fig. 1D), and the core displays a primary lattice spacing of $0.23~\\mathrm{{nm}}$ , corresponding to Pt (111) planes (Fig. 1D). \n\nThese Pt/NiO NWs were then loaded onto carbon black and annealed in an argon/hydrogen mixture $(\\mathrm{Ar}/\\mathrm{H}_{2}\\colon97/3)$ at $450^{\\circ}\\mathrm{C}$ to produce PtNi alloy NWs. The overall morphology of the NW was maintained without obvious change in length or diameter, but the apparent core/shell contrast disappeared (Fig. 1B), suggesting the formation of uniform PtNi alloy NWs. The HRTEM image of the annealed NW confirms a uniform contrast with a well-resolved lattice spacing of $0.21{\\mathrm{nm}}$ throughout the entire NW diameter (Fig. 1E), consistent with the (111) lattice spacing of the PtNi alloy. This evolution from the initial core/shell NWs before annealing to uniform alloy NWs after annealing was also confirmed by high-angle annular dark-field scanning transmission electron microscope (HAADF-STEM) studies (fig. S1, C and D). \n\nOur energy-dispersive x-ray spectroscopy (EDS) elemental analysis shows that the overall $\\mathrm{Pt/Ni}$ ratio remains essentially the same (Pt/Ni: 15/85) before and after annealing (fig. S3, A and B). The EDS line scan profile of the asprepared NWs also confirms the core/shell structure with a Pt core (Fig. 1G) that diffuses homogenously throughout the entire NW after annealing (Fig. 1H). X-ray diffraction (XRD) studies also confirm the evolution of the initial Pt/NiO core/shell configurations into a fully alloyed PtNi NW structure (fig. S4). Furthermore, x-ray photoelectron spectroscopy (XPS) studies further demonstrate that the nickel valence state changed from $\\mathrm{Ni^{x+}}$ in the Pt/NiO core/shell NWs to mostly ${\\bf N i}^{0}$ after annealing, consistent with the formation PtNi alloy (fig. S5). \n\nWe believe that the NW geometry is essential for ensuring the thermal stability of these ultrafine NWs under high temperature annealing. For example, a similar thermal annealing process applied to ultrafine PtNi NPs led to substantial aggregation of the NPs (a size increase from $\\sim7~\\mathrm{{nm}}$ before to 10 to $30\\ \\mathrm{nm}$ ) (fig. S2), which could be partly attributed to the movement and fusion of NPs. In contrast, NWs supported on carbon black have multiple anchoring points and their mobility is much lower compared to NPs with single point contact on carbon support. \n\nAn electrochemical de-alloying (leaching) process was used to gradually remove Ni atoms from the PtNi alloy NWs, which allowed the rearrangement of Pt atoms on surface to form the J-PtNWs. We performed cyclic voltammetry (CV) in $\\mathbf{N}_{2}$ -saturated 0.1 M $\\mathrm{HClO_{4}}$ solution $_{0.05\\mathrm{~V~}}$ to $1.1\\mathrm{V}$ versus RHE) with a sweep rate of $100\\ \\mathrm{mVs^{-1}}$ (Fig. 2A). Based on the CV sweeps, the $\\mathrm{ECSA_{Hupd}}$ was derived from the $\\mathrm{H}_{\\mathrm{upd}}$ adsorption/desorption peak areas $(0.05\\mathrm{~V~<~E~<~}0.35\\mathrm{~V})$ and the total mass of the loaded Pt. The PtNi alloy NWs initially showed an essentially negligible $\\mathrm{ECSA_{Hupd}}$ during the first CV cycle. The $\\mathrm{ECSA_{Hupd}}$ increased steadily with the increasing number of CV cycles (Fig. 2B). Importantly, the NWs were fully activated in $\\sim$ 160 CV cycles to reach a stable $\\mathrm{ECSA_{Hupd}}$ up to 118 $\\mathrm{cm^{2}/m g_{P t}},$ versus previous highest reported values of $\\mathrm{\\sim}70~\\mathrm{cm^{2}/m g_{\\mathrm{pt}}}$ (Table 1). \n\nStructural and elemental studies were performed to characterize the fully activated NWs after CV cycles. Lowresolution TEM images show that the overall NW structure was well-maintained after the electrochemical de-alloying process (Fig. 1C). The HRTEM images show that the overall diameter of the NW shrank from $\\sim5.0$ to $\\sim2.2\\ \\mathrm{nm}$ after the CV cycles, with well-resolved lattice spacing of $0.23\\ \\mathrm{nm}.$ , again consistent with Pt (111) (Fig. 1F). The EDS line scan showed that Pt was the only dominant element in the resulting NWs (Fig. 1I), further confirming complete Ni leaching. In addition, the CV scan of the fully activated NWs (after 160 CV cycles) in 0.1 M KOH showed an absence of typical $\\mathrm{Ni^{2+}/N i^{3+}}$ redox signatures, in contrast to the partially activated (150 cycles) PtNi alloy NWs in which the $\\mathrm{Ni^{2+}/N i^{3+}}$ redox peaks were prominent (fig. S6). We also conducted COstripping experiment to determine the $\\mathtt{E C S A c o}$ of J-PtNWs (fig. S7). The resulting ratio of $\\mathrm{ECSA_{Hupd}}$ : $\\mathrm{ECSA_{\\mathrm{CO}}}$ is 1.00:1.05, which is in agreement with that of typical pure Pt material (10). Furthermore, TEM studies of the de-alloyed NWs also showed a highly jagged surface (Fig. 1, C and F) with rich atomic steps, in contrast to relatively smooth surface observed in typical synthetic PtNWs (fig. S1B). Based on these observations, we denote the resulting nanowires as the jagged PtNWs (J-PtNWs). \n\nThe electrocatalytic performance of the resulting NWs was compared with commercial $\\mathrm{Pt/C}$ catalyst $10\\%$ mass loading of $\\sim3$ to 5 nm Pt NPs on carbon support) and directly synthesized regular PtNWs (R-PtNWs, \\~ $1.8~\\mathrm{nm}$ diameter, fig. S1B) with relatively smooth surface (25). To assess the ORR activity, all catalysts were loaded onto glassy carbon electrodes ( $\\mathrm{\\bf{Pt}}$ mass loading: $2.2\\ \\mathrm{\\upmu{g}/c m^{2}}$ for J-PtNWs, $2.55~\\mathrm{\\upmu\\mathrm{g/cm^{2}}}$ for R-PtNWs and $7.65~\\mathrm{\\upmu\\mathrm{g/cm^{2}}}$ for $\\mathrm{Pt/C}$ catalyst). \n\nWe used CV to measure the ECSA (Fig. 2C). Overall, the JPtNWs, R-PtNWs and $\\mathrm{Pt/C}$ catalysts showed an ECSA of 118, 110, and $74~\\mathrm{m^{2}/g}_{\\mathrm{pt}},$ respectively (Table 1). The synthetic RPtNWs also exhibited a rather high ECSA that may be related to their ultrasmall diameters $(\\sim1.8\\ \\mathrm{nm})$ ). \n\nFigure 2D shows the ORR polarization curves normalized by glassy carbon electrode geometric area $\\mathrm{(0.196~cm^{2})}$ . The half-wave potential for the J-PtNWs was at $0.935\\mathrm{~V~}$ , which is considerably higher than those of the commercial Pt/C (0.86 V) and the R-PtNWs (0.90 V), suggesting excellent ORR activity of the J-PtNWs. The Koutecky-Levich equation was used to calculate the kinetic current by considering the mass-transport correction. The specific and mass activities were normalized by the ECSA or the total mass of the loaded Pt, respectively. Overall, the J-PtNWs showed a specific activity of $\\mathrm{11.5~mA/cm^{2}}$ at $0.90{\\mathrm{~V}}$ versus RHE, far higher than $0.35\\mathrm{\\mA/cm^{2}}$ for the $\\mathrm{Pt/C}$ or 1.70 $\\mathrm{\\mA/cm^{2}}$ for the R-PtNWs tested under the same conditions (Table 1). Together with their ultrahigh specific surface area, the J-PtNWs deliver a high mass activity of $13.6~\\mathrm{A/mg_{\\mathrm{pt}}}$ at $0.9{\\mathrm{~V~}}$ versus RHE, which is 52 times higher than that of the $10\\%$ wt $\\mathrm{Pt/C}$ $(0.26~\\mathrm{A/mg_{Pt}})$ , and more than 7 times higher than that of the R-PtNWs $\\left(1.76\\mathrm{\\A}/\\mathrm{mg_{Pt}}\\right)$ (Fig. 2G and Table 1). The mass activity achieved in the J-PtNWs nearly doubles the highest previously reported mass activity value of 6.98 $\\mathrm{{A/mg_{Pt}}}$ (19) and $5.7~\\mathrm{A/mg_{Pt}}$ (23). Importantly, the observed mass activity was highly reproducible and was between 10.8 and $13.8~\\mathrm{A/mg_{Pt}}$ in ${>}15$ independently tested J-PtNW electrodes. \n\nBecause the current value at $0.90{\\mathrm{~V~}}$ is already near the diffusion-limited current in ORR polarization curve, we also compared mass activity at half-wave potential of the JPtNWs $(0.935{\\mathrm{~V}})$ in Table 1. Our analysis shows that the JPtNWs still exhibit an impressive 48 times higher mass activity than that of $\\mathrm{Pt/C}$ . The specific activity Tafel plots (Fig. 2E) exhibit a slope of 51, 72 and $74\\mathrm{mV}\\mathrm{dec^{-1}}$ for J-PtNWs, RPtNWs and $\\mathrm{Pt/C_{\\mathrm{;}}}$ , respectively. A considerably smaller slope achieved in the J-PtNWs suggests significantly improved kinetics for ORR. Remarkably, the mass activity Tafel plot (Fig. 2F) shows that the J-PtNWs deliver 30 times higher mass activity than the 2017 target set by US Department of Energy $(0.44\\mathrm{\\A/mg_{Pt}}$ at $0.90{\\mathrm{~V~}}$ for MEA, highlighted by purple dash line in Fig. 2F). The J-PtNW can deliver the DOE targeted mass activity at $0.975^{}\\mathrm{~V~}$ (RHE), thus significantly reducing the over-potential by $0.075\\mathrm{V}$ . \n\nWe evaluated the durability of the J-PtNWs using accelerated deterioration tests (ADT) under a sweep rate of 100 $\\mathrm{\\mV{s}^{-1}}$ between $0.6\\mathrm{\\:V}$ and $1.0\\mathrm{V}$ in $\\mathrm{O_{2}}$ -saturated 0.1 M $\\mathrm{HClO_{4}}$ . After 6000 cycles, the ECSA dropped only by ${\\sim}7\\%$ , and the specific activity dropped by only ${\\sim}5.5\\%$ , and together the mass activity dropped by only $12\\%$ (Fig. 2H). The retention of high ECSA in J-PtNWs during ADT is in stark contrast to that of $\\mathrm{Pt/C_{\\mathrm{:}}}$ , which showed a much larger loss $(\\sim30\\%)$ in ECSA during similar ADT tests. Ultrafine nanostructures (e.g., $\\sim2\\ \\mathrm{nm},$ ) have shown severely worse stability compared to their bulk counterpart (26, 27). The unique 1D geometry of nanowires and the multipoint contacts with carbon support might also deter the Ostwald ripening process usually observed in spherical NPs (fig. S8), contributing to the excellent durability. Indeed, our TEM studies before and after ADT test showed little change in the overall morphology or size of the J-PtNWs on carbon support (fig. S9). Highresolution STEM studies showed that the jagged surface (with defective sites) was largely preserved after 6000 cycles (Fig. 2I). \n\nThe above experimental studies demonstrate that the JPtNWs exhibit ultrahigh specific surface area and specific activity, and together delivering a record-high mass activity for ORR. Notably, the J-PtNWs exhibit considerably higher specific activity and mass activity $(11.5\\mathrm{\\mA}/\\mathrm{cm^{2}}$ or 13.6 $\\mathrm{{A/mg_{Pt}}}$ at $0.9\\mathrm{V},$ than those of R-PtNWs $(1.70\\mathrm{\\mA}/\\mathrm{cm^{2}}$ or 1.87 $\\mathrm{{A/mg_{Pt}}}$ at $0.9~\\mathrm{V},$ ), despite similar ECSA values $\\mathrm{718~m^{2}/g_{P t}}$ for $2.2\\ \\mathrm{nm}$ J-PtNWs and $110\\ \\mathrm{m^{2}/g_{p t}}$ for $1.8~\\mathrm{nm}$ R-PtNWs). Compared with $\\mathrm{Pt/C_{\\mathrm{\\ell}}}$ , the J-PtNWs show a 33 times increase in specific activity at $0.90{\\mathrm{~V~}}$ vs. RHE, which suggests that the activation energy for the rate-determining step of ORR on the J-PtNWs is reduced by $0.090\\ \\mathrm{eV}$ from that of $\\mathrm{Pt/C}[\\Delta E_{\\mathrm{act}}$ $=k_{\\mathrm{B}}T\\ln(S A_{\\mathrm{J-PtNW}}/S A_{\\mathrm{Pt/C}})$ , where $\\Delta E_{\\mathrm{act}}$ is difference in activation energy, $k_{\\mathrm{B}}$ Boltzmann’s constant, $T$ temperature, $S A_{\\mathrm{J}}$ - PtNW specific activity of J-PtNWs, $S A_{\\mathrm{Pt/C}}$ specific activity of $\\mathrm{Pt/C]}$ . This decrease is plausible decrease based on our various ORR computations (16). \n\nTo gain further insight on how the J-PtNWs could deliver dramatically higher ORR activity, we conducted reactive molecular dynamics (RMD) studies using the reactive force field (ReaxFF) (28) to simulate the formation of J-PtNWs by leaching Ni atoms from an initial $\\mathrm{Pt_{15}N i_{85}}$ alloy NWs $(I6)$ , and a second-moment-approximation (SMA) tight-binding potential (29) for final local optimization and prediction of Pt-Pt distances. (25). The RMD simulation resulted in a pure Pt NW containing 7,165 Pt atoms (in a length of $\\sim46~\\mathrm{nm},$ ) with a diameter of $\\sim2.2\\ \\mathrm{nm}$ and highly jagged surface (Fig. 3A). Notably, the overall morphology of the predicted JPtNWs resembles closely the experimentally obtained JPtNWs as shown in TEM images in Fig. 1, both of which show modulating thread-like segments about $2.2\\ \\mathrm{nm}$ in diameter, containing striction regions, bending points and jagged surfaces. \n\nThe predicted radial distribution function (RDF) for the J-PtNW exhibits a well-defined first-neighbor peak at about 2.70 Å (Fig. 3D), which is ${\\sim}2.2$ to $2.5\\%$ shorter than the Pt-Pt first-neighbor distance predicted for the R-PtNWs (2.76 Å) and the bulk Pt crystal $(2.77\\mathrm{\\AA})$ , whereas the peaks associated with the second and further neighbors are much broader and more blurred, similar to those reported in nanoporous NPs (16). These predicted Pt-Pt first-neighbor distance are well confirmed by the EXAFS analysis (Fig. 3E, fig. S10, and table S1), which reveals that the first shell Pt-Pt bond length in the J-PtNWs (2.71 Å) is $\\sim1.8\\%$ shorter than that of the Pt foil (2.76 Å). \n\nNanowires with small diameters $\\cdot{\\bf-}2.2\\ \\mathrm{nm}$ in this case) inherently have ultrahigh surface area that can be further enhanced by the surface roughness of a jagged morphology. We calculated the van der Waals (vdW) surface area of the simulated J-PtNWs to be \\~ $110\\mathrm{~\\m^{2}/g_{P t}}$ (table S2), which agrees well with our experimental value derived from the ECSA $\\langle118\\ m^{2}/{\\bf g}_{\\mathrm{pt}}\\rangle$ . However, the enhancement of surface area alone cannot fully account for the observed ORR mass activity. Stressed and under coordinated crystalline-like surface rhombi can dramatically decrease the reaction barrier of the rate determining steps of ORR, thus, improving specific ORR activity $(I6)$ . Surface rhombi are an ensemble of 4 atoms arranged as two equilateral triangles sharing one edge (see the inset in Fig. 3F) and resembling the triangular tessellation of an fcc (111) surface, which we find to be superior to a square tessellation for ORR activity in the same way that the fcc (111) surface is more ORR-active than other compact fcc surfaces such as fcc (100) (1, 30). Moreover, rhombi that are stressed and under coordinated but still crystalline-like exhibit smaller overall energy barriers for ORR than those encountered on the rhombi of the fcc (111) surface, as predicted via density-functional theory (DFT) calculations (16). \n\nSeveral factors could contribute to the greatly enhanced ORR activity in the J-PtNWs. First, our analysis shows that the coordination number of surface atoms in the J-PtNWs ranges mostly between 6 and 8 (fig. S11A), indicating that these surface atoms are under-coordinated when compared to typical crystal surfaces (with coordination numbers of 8 or 9 for (100) or (111) facets, respectively). Despite the lowcoordination number and jagged feature, the crystalline-like character of surface atoms in J-PtNWs is confirmed from common neighbor analysis (CNA) (31–33). CNA result shows that the ratio of CNA [5, 5, 5] triplets (a finger print of icosahedral structure) (29, 34) to the total number of CNA triplets is rather low $84\\%$ of the atoms have a ratio below 0.0065) (Fig. 3B). Because the bonded pairs of type [5, 5, 5] are characteristic of icosahedral order, this low [5, 5, 5] ratio indicates a more crystalline-like feature (32) for our established model, which is also a crucial factor for enhancing ORR activity (16). Indeed, such crystalline-like character of simulation model is consistent with the experimental FFT images (insets in Fig. 1F and Fig. 2I) showing that the JPtNWs remain fcc-like after CV activation and repeated cycling test. Additionally, the distribution of rhombus dihedral angles (fig. S11B) shows that most of the dihedral angles formed between the two triangles of the rhombus range between $156^{\\circ}$ and $180^{\\circ}$ . Comparing with $180^{\\circ}$ for typical crystalline Pt (111) facet, this statistical analysis further confirms the high-crystallinity nature of the J-PtNWs, which is favorable for increased reactivity (16). Second, the surface atoms in the J-PtNWs exhibit rather high value of Cauchy atomic stress times atomic volume about 10 times larger than that for regular (100) or (111) facets (Fig. 3, C and F), as also confirmed by simulated and EXAFS derived Pt-Pt distances (Fig. 3, D and E). To provide further information on surface energetics, we report that the ReaxFF surface energy of the J-PtNW is $2.7\\ \\mathrm{J/m^{2}}$ that is higher than the value for the $\\mathbf{Pt}(\\mathrm{{111}})$ surface of $\\mathrm{1.7\\:J/m^{2}}$ (this latter ReaxFF value is in very good agreement with quantum mechanics and experimental values). This mechanical strain can decrease the binding energy of adsorbents on close-packed surfaces, which can make the surfaces more active (32, 35, 36), further contributing to the activity enhancement. Finally and importantly, we found that the J-PtNWs possess both a large ECSA (see table S2) and exhibit an unusually high number of the ORRfavorable rhombic structures on the surface. There are $76\\%$ rhombi per surface atom in the J-PtNW surface (table S2), considerably higher than $57\\%$ previously reported for the nanoporous $\\mathrm{\\bf{Pt}}$ -NPs (16). \n\nWe also prepared similar J-PtNWs by electrochemical dealloying PtCo NWs and achieved an ORR activity of 8.1 $\\mathrm{{A/mg_{Pt}}}$ (figs. S12 and S13), that was higher than the highest number reported previously $(6.98~\\mathrm{A/mg_{Pt}})$ . We attribute the lower mass activity compared to PtNi derived J-PtNWs to the slightly larger diameter of the resulting NWs $_{\\cdot\\sim2.5}$ vs. ${\\sim}2.2\\ \\mathrm{nm},$ ) leading to a smaller ECSA $\\mathrm{92}\\mathrm{m^{2}/g_{P t}}$ vs. $118~\\mathrm{m^{2}/g_{P t})}$ and possibly to differences in dealloying mechanism of Co with respect to Ni. These studies further demonstrate the validity and generality of our approach to derive highly ORR active J-PtNWs from alloy NWs. \n\n# REFERENCES AND NOTES \n\n1. V. R. Stamenkovic, B. Fowler, B. S. Mun, G. Wang, P. N. Ross, C. A. Lucas, N. M. Markovic, Improved oxygen reduction activity on Pt3Ni(111) via increased surface site availability. Science 315, 493–497 (2007). doi:10.1126/science.1135941 \n2. N. S. Porter, H. Wu, Z. Quan, J. Fang, Shape-control and electrocatalytic activityenhancement of Pt-based bimetallic nanocrystals. Acc. Chem. Res. 46, 1867– 1877 (2013). doi:10.1021/ar3002238 \n3. J. Wu, H. Yang, Platinum-based oxygen reduction electrocatalysts. Acc. Chem. Res. 46, 1848–1857 (2013). doi:10.1021/ar300359w \n4. Y. J. Wang, N. Zhao, B. Fang, H. Li, X. T. Bi, H. Wang, Carbon-supported Pt-based alloy electrocatalysts for the oxygen reduction reaction in polymer electrolyte membrane fuel cells: Particle size, shape, and composition manipulation and their impact to activity. Chem. Rev. 115, 3433–3467 (2015). doi:10.1021/cr500519c \n5. Z. Peng, H. Yang, Designer platinum nanoparticles: Control of shape, composition in alloy, nanostructure and electrocatalytic property. Nano Today 4, 143–164 (2009). doi:10.1016/j.nantod.2008.10.010 \n6. D. Wang, H. L. Xin, R. Hovden, H. Wang, Y. Yu, D. A. Muller, F. J. DiSalvo, H. D. Abruña, Structurally ordered intermetallic platinum-cobalt core-shell nanoparticles with enhanced activity and stability as oxygen reduction electrocatalysts. Nat. Mater. 12, 81–87 (2013). doi:10.1038/nmat3458 \n7. C. Wang, M. Chi, G. Wang, D. van der Vliet, D. Li, K. More, H.-H. Wang, J. A. Schlueter, N. M. Markovic, V. R. Stamenkovic, Correlation between surface chemistry and electrocatalytic properties of monodisperse $\\mathsf{P t}_{\\mathrm{x}}\\mathsf{N i}_{\\mathrm{1-x}}$ nanoparticles. Adv. Funct. Mater. 21, 147–152 (2011). doi:10.1002/adfm.201001138 \n8. D. F. van der Vliet, C. Wang, D. Tripkovic, D. Strmcnik, X. F. Zhang, M. K. Debe, R. T. Atanasoski, N. M. Markovic, V. R. Stamenkovic, Mesostructured thin films as electrocatalysts with tunable composition and surface morphology. Nat. Mater. 11, 1051–1058 (2012). doi:10.1038/nmat3457 \n9. V. R. Stamenkovic, B. S. Mun, M. Arenz, K. J. J. Mayrhofer, C. A. Lucas, G. Wang, P. N. Ross, N. M. Markovic, Trends in electrocatalysis on extended and nanoscale Pt-bimetallic alloy surface. Nat. Mater. 6, 241–247 (2007). doi:10.1038/nmat1840 \n10. D. F. van der Vliet, C. Wang, D. Li, A. P. Paulikas, J. Greeley, R. B. Rankin, D. Strmcnik, D. Tripkovic, N. M. Markovic, V. R. Stamenkovic, Unique electrochemical adsorption properties of Pt-skin surfaces. Angew. Chem. Int. Ed. 51, 3139–3142 (2012). doi:10.1002/anie.201107668 \n11. C. Cui, L. Gan, M. Heggen, S. Rudi, P. Strasser, Compositional segregation in shaped Pt alloy nanoparticles and their structural behavior during electrocatalysis. Nat. Mater. 12, 765–771 (2013). doi:10.1038/nmat3668 \n12. V. R. Stamenkovic, B. S. Mun, K. J. J. Mayrhofer, P. N. Ross, N. M. Marković, Effect of surface composition on electronic structure, stability, and electrocatalytic properties of Pt-transition metal alloys: Pt-skin versus Pt-skeleton surfaces. J. Am. Chem. Soc. 128, 8813–8819 (2006). doi:10.1021/ja0600476 \n13. F. Calle-Vallejo, J. I. Martínez, J. M. García-Lastra, P. Sautet, D. Loffreda, Fast prediction of adsorption properties for platinum nanocatalysts with generalized coordination numbers. Angew. Chem. Int. Ed. 53, 8316–8319 (2014). doi:10.1002/anie.201402958 \n14. F. Calle-Vallejo, J. Tymoczko, V. Colic, Q. H. Vu, M. D. Pohl, K. Morgenstern, D. Loffreda, P. Sautet, W. Schuhmann, A. S. Bandarenka, Finding optimal surface sites on heterogeneous catalysts by counting nearest neighbors. Science 350, 185–189 (2015). doi:10.1126/science.aab3501 \n15. M. Escudero-Escribano, P. Malacrida, M. H. Hansen, U. G. Vej-Hansen, A. Velazquez-Palenzuela, V. Tripkovic, J. Schiotz, J. Rossmeisl, I. E. L. Stephens, I. Chorkendorff, Tuning the activity of Pt alloy electrocatalysts by means of the lanthanide contraction. Science 352, 73–76 (2016). doi:10.1126/science.aad8892 \n16. A. Fortunelli, W. A. Goddard III, L. Sementa, G. Barcaro, F. R. Negreiros, A. Jaramillo-Botero, The atomistic origin of the extraordinary oxygen reduction activity of Pt3Ni7 fuel cell catalysts. Chem. Sci. 6, 3915–3925 (2015). doi:10.1039/C5SC00840A \n17. S. Choi, S. Xie, M. Shao, J. H. Odell, N. Lu, H.-C. Peng, L. Protsailo, S. Guerrero, J. Park, X. Xia, J. Wang, M. J. Kim, Y. Xia, Synthesis and characterization of 9 nm Pt-Ni octahedral with a record high activity of 3.3A/mgPt for the oxygen reduction reaction. Nano Lett. 13, 3420–3425 (2013). doi:10.1021/nl401881z \n18. X. Huang, Z. Zhao, Y. Chen, E. Zhu, M. Li, X. Duan, Y. Huang, A rational design of carbon-supported dispersive Pt-based octahedral as efficient oxygen reduction reaction catalysts. Energy Environ. Sci. 7, 2957–2962 (2014). doi:10.1039/C4EE01082E \n19. X. Huang, Z. Zhao, L. Cao, Y. Chen, E. Zhu, Z. Lin, M. Li, A. Yan, A. Zettl, Y. M. Wang, X. Duan, T. Mueller, Y. Huang, High-performance transition metal-doped Pt3Ni octahedral for oxygen reduction reaction. Science 348, 1230–1234 (2015). doi:10.1126/science.aaa8765 \n20. H. Zhu, S. Zhang, S. Guo, D. Su, S. Sun, Synthetic control of FePtM nanorods (M = Cu, Ni) to enhance the oxygen reduction reaction. J. Am. Chem. Soc. 135, 7130–7133 (2013). doi:10.1021/ja403041g \n21. S. Guo, D. Li, H. Zhu, S. Zhang, N. M. Markovic, V. R. Stamenkovic, S. Sun, FePt and CoPt nanowires as efficient catalysts for the oxygen reduction reaction. Angew. Chem. Int. Ed. 52, 3465–3468 (2013). doi:10.1002/anie.201209871 \n22. L. Zhang, L. T. Roling, X. Wang, M. Vara, M. Chi, J. Liu, S.-I. Choi, J. Park, J. A. Herron, Z. Xie, M. Mavrikakis, Y. Xia, Platinum-based nanocages with subnanometer-thick walls and well-defined, controllable facets. Science 349, 412–416 (2015). doi:10.1126/science.aab0801 \n23. C. Chen, Y. Kang, Z. Huo, Z. Zhu, W. Huang, H. L. Xin, J. D. Snyder, D. Li, J. A. Herron, M. Mavrikakis, M. Chi, K. L. More, Y. Li, N. M. Markovic, G. A. Somorjai, P. Yang, V. R. Stamenkovic, Highly crystalline multimetallic nanoframes with threedimensional electrocatalytic surface. Science 343, 1339–1343 (2014). doi:10.1126/science.1249061 \n24. S. Zhang, Y. Hao, D. Su, V. V. T. Doan-Nguyen, Y. Wu, J. Li, S. Sun, C. B. Murray, Monodisperse core/shell Ni/FePt nanoparticles and their conversion to Ni/Pt to catalyze oxygen reduction. J. Am. Chem. Soc. 136, 15921–15924 (2014). doi:10.1021/ja5099066 \n25. See supplementary materials on Science Online. \n26. L. Tang, B. Han, K. Persson, C. Friesen, T. He, K. Sieradzki, G. Ceder, Electrochemical stability of nanometer-scale Pt particles in acidic environments. J. Am. Chem. Soc. 132, 596–600 (2010). doi:10.1021/ja9071496 \n27. L. Tang, X. Li, R. C. Cammarata, C. Friesen, K. Sieradzki, Electrochemical stability of elemental metal nanoparticles. J. Am. Chem. Soc. 132, 11722–11726 (2010). doi:10.1021/ja104421t \n28. C. F. Sanz-Navarro, P.-O. Åstrand, D. Chen, M. Rønning, A. C. T. van Duin, T. Jacob, W. A. Goddard, Molecular dynamics simulations of the interactions between platinum clusters and carbon platelets. J. Phys. Chem. A 112, 1392– 1402 (2008). doi:10.1021/jp074806y \n29. F. Cleri, V. Rosato, Tight-binding potentials for transition metals and alloys. Phys. Rev. B 48, 22–33 (1993). doi:10.1103/PhysRevB.48.22 \n30. Y. Sha, T. H. Yu, B. V. Merinov, P. Shirvanian, W. A. Goddard III, Oxygen hydration mechanism for the oxygen reduction reaction at Pt and Pd fuel cell catalysts. J. Phys. Chem. Lett. 2, 572–576 (2011). doi:10.1021/jz101753e \n31. D. Faken, H. Jonsson, Systematic analysis of local atomic structure combined with 3D computer graphics. Comput. Mater. Sci. 2, 279–286 (1994). doi:10.1016/0927-0256(94)90109-0 \n32. S. Schnur, A. Groß, Strain and coordination effects in the adsorption properties of early transition metals: A density-functional theory study. Phys. Rev. B 81, 033402 (2010). doi:10.1103/PhysRevB.81.033402 \n33. J. D. Honeycutt, H. C. Andersen, Molecular dynamics study of melting and freezing of small Lennard-Jones clusters. J. Phys. Chem. 91, 4950–4963 (1987). doi:10.1021/j100303a014 \n34. A. Stukowski, Structure identification methods for atomistic simulations of crystalline materials. Model. Simul. Mater. Sci. Eng. 20, 045021 (2012). doi:10.1088/0965-0393/20/4/045021 \n35. M. F. Francis, W. A. Curtin, Mechanical work makes important contributions to surface chemistry at steps. Nat. Commun. 6, 6261 (2015). doi:10.1038/ncomms7261 \n36. S. Zhang, X. Zhang, G. Jiang, H. Zhu, S. Guo, D. Su, G. Lu, S. Sun, Tuning nanoparticle structure and surface strain for catalysis optimization. J. Am. Chem. Soc. 136, 7734–7739 (2014). doi:10.1021/ja5030172 \n37. V. Vitek, T. Egami, Atomic level stresses in solids and liquids. Phys. Status Solidi 144, 145–156 (1987) (b). doi:10.1002/pssb.2221440113 \n38. B. Ravel, M. Newville, ATHENA, ARTEMIS, HEPHAESTUS: Data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 12, 537–541 (2005). doi:10.1107/S0909049505012719 \n39. A. Ankudinov, B. Ravel, J. Rehr, S. Conradson, Real-space multiple-scattering calculation and interpretation of x-ray-absorption near-edge structure. Phys. Rev. B 58, 7565–7576 (1998). doi:10.1103/PhysRevB.58.7565 \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge the support from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Science and Engineering through Award DE-SC0008055 (synthesis and structural analysis). Y.H. acknowledges the support from the National Science Foundation through Award DMR-1437263 (electrochemical characterizations). The Advanced Light Source is supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. We thank Dr. Matthew A. Marcus at ALS for the support during the acquisition of XAS data, and C. Wu for help on EXAFS data analysis. R.Y. acknowledges support from the National Natural Science Foundation of China project number 51525102, 51390475, 51371102. The aberration-corrected transmission electron microscopy results were achieved (in part) using Titan 80-300 and JEM-ARM \n\n200F. In this work we used the resources of the National Center for Electron Microscopy in Beijing. A patent application on this subject has been filed. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/cgi/content/full/science.aaf9050/DC1 \nMaterials and Methods \nFigs. S1 to S13 \nTables S1 and S2 \nReferences (37–39) \n\n18 April 2016; resubmitted 25 August 2016 \nAccepted 26 October 2016 \nPublished online 17 November 2016 \n10.1126/science.aaf9050 \n\n![](images/9a64e75ee401812cbae3e0b062e9fce029742b3e55c141d383aa1704280273ae.jpg) \nFig. 1. Structure and composition characterization of different stages of the J-PtNW evolution process. (A to C) Representative TEM images and (D to F) HRTEM images of the Pt/NiO core/shell NWs, the PtNi alloy NWs and the J-PtNWs supported on carbon, respectively. The inset in (F) shows the corresponding fast Fourier transform (FFT) image. The dashed lines in (E) and (F) show the outline of the NWs, highlighting the rough surface of the J-PtNWs. (G to I) EDS line-scan profiles of the corresponding NWs show clearly the evolution from the Pt/NiO core/shell, to PtNi alloy, and then pure Pt NWs. \n\n![](images/d8781c0b16c224c3b501d967aadd20960103f8a611d0ad9b4dab9278453b976f.jpg) \nFig. 2. Electrochemical performance of the jagged PtNWs (J-PtNWs) vs. regular synthetic PtNWs (RPtNWs) and commercial Pt/C. (A) Cyclic voltammetry (CV) curves corresponding to different activation cycles of the de-alloying process, clearly indicating the increasing surface area with the increasing number of CV cycles. (B) The evolution of ECSA with the increasing CV cycles, showing that 150 cycles are sufficient to construct the J-PtNW and reach a stable ECSA. (C and D) CV and ORR polarization curves for the J-PtNWs, the R-PtNWs, and the Pt/C, respectively. (E and F) Specific activity (SA) and mass activity (MA) Tafel plot for the J-PtNWs, the R-PtNWs, and the Pt/C, respectively. The purple dash line indicates the 2017 mass activity target ( $@$ 0.90V vs. RHE) set by US Department of Energy (DOE). (G) The comparison of specific activities and mass activities of the J-PtNWs, the R-PtNWs, and the Pt/C at 0.9 V versus RHE, showing that the JPtNWs deliver 33 times higher specific activity or 52 times higher mass activity than Pt/C. (H) ORR polarization curves and mass activity Tafel plot (inset) for the J-PtNWs before and after 6000 CV cycles between 0.6 and $1.0\\vee$ versus RHE, showing little loss in activity. The scan rate for the Accelerated Durability Test (ADT) is $100\\mathrm{mVs^{-1}}$ . (I) High-resolution HAADF-STEM image of the J-PtNWs after ADT test. The circled areas indicate defective regions with missing atoms. The inset shows the corresponding FFT image. \n\n![](images/86378357f51543bdf7f6b2e9cce28fe49dbe21ac3bb902ff0e1c5e353ec9bacb.jpg) \nFig. 3. Structural analysis of the J-PtNWs obtained from ReaxFF reactive molecular dynamics and xray absorption spectroscopy. (A) Pictorial illustrations of the final structure of a Pt J-NW generated by Reactive Molecular Dynamics simulations, with an average diameter of ${\\sim}2.2$ nm and length of ${\\sim}46$ nm. (B) J-PtNW with colored atoms to show the 5-fold index. (C) J-PtNW with colored atoms to show distribution of atomic stress (in atm·nm3). (D) Pt-Pt radial distribution function (RDF) of the SMA-predicted J-PtNW (red) compared with the peaks of the RDF for the regular PtNW (black). (E) Pt L3 edge FT-EXAFS spectrum (black) collected ex situ and the corresponding first shell least-squares fit (red) for the J-PtNWs. (F) Distribution of the absolute values of the average atomic stress on surface rhombi for the R-PtNWs (black) and the J-PtNWs (red). A rhombus is an ensemble of 4 atoms arranged as two equilateral triangles sharing one edge as shown in the inset. \n\nTable 1. Electrochemically active surface area, specific activity, half-wave potential and mass activity of J-PtNWs/C, R-PtNWs/C, Pt/C catalysts, in comparison with those in several representative recent studies. \n\n\n
ECSA (m²/gpt)SA (mA/cm²) @Half-wave potential (V)Mass activity (A/mgpt) @0.90 V@ 0.935 V
J-PtNWs/C (this work)1180.90V 11.50.93513.62.87
R-PtNWs/C (this work)1101.590.8991.760.5
Pt/C (this work)740.350.8600.260.06
Octahedron Pt2.5Ni/C21NANA3.3NA
(17) Nanoframe PtNi/C (23)67.2NANA5.7NA
Mo-Pt3Ni/C (19)67.710.3NA6.98NA
DOE 2017 targetNANANA0.44NA
\n\nUltrafine jagged platinum nanowires enable ultrahigh mass activity for the oxygen reduction reaction \nMufan Li, Zipeng Zhao, Tao Cheng, Alessandro Fortunelli, Chih-Yen Chen, Rong Yu, Qinghua Zhang, Lin Gu, Boris Merinov, Zhaoyang Lin, Enbo Zhu, Ted Yu, Qingying Jia, Jinghua Guo, Liang Zhang, William A. Goddard III, Yu Huang and Xiangfeng Duan (November 17, 2016) published online November 17, 2016 \n\nThis copy is for your personal, non-commercial use only. \n\n# Article Tools \n\nVisit the online version of this article to access the personalization and article tools: http://science.sciencemag.org/content/early/2016/11/16/science.aaf9050 \n\n# Permissions \n\nObtain information about reproducing this article: http://www.sciencemag.org/about/permissions.dtl " + }, + { + "id": "10.1126_science.aaf9717", + "DOI": "10.1126/science.aaf9717", + "DOI Link": "http://dx.doi.org/10.1126/science.aaf9717", + "Relative Dir Path": "mds/10.1126_science.aaf9717", + "Article Title": "Perovskite-perovskite tandem photovoltaics with optimized band gaps", + "Authors": "Eperon, GE; Leijtens, T; Bush, KA; Prasanna, R; Green, T; Wang, JTW; McMeekin, DP; Volonakis, G; Milot, RL; May, R; Palmstrom, A; Slotcavage, DJ; Belisle, RA; Patel, JB; Parrott, ES; Sutton, RJ; Ma, W; Moghadam, F; Conings, B; Babayigit, A; Boyen, HG; Bent, S; Giustino, F; Herz, LM; Johnston, MB; McGehee, MD; Snaith, HJ", + "Source Title": "SCIENCE", + "Abstract": "We demonstrate four-and two-terminal perovskite-perovskite tandem solar cells with ideally matched band gaps. We develop an infrared-absorbing 1.2-electron volt band-gap perovskite, FA(0.75)Cs(0.25)Sn(0.5)Pb(0.5)I(3), that can deliver 14.8% efficiency. By combining this material with a wider-band gap FA(0.83)Cs(0.17)Pb(I0.5Br0.5)(3) material, we achieve monolithic two-terminal tandem efficiencies of 17.0% with > 1.65-volt open-circuit voltage. We also make mechanically stacked four-terminal tandem cells and obtain 20.3% efficiency. Notably, we find that our infrared-absorbing perovskite cells exhibit excellent thermal and atmospheric stability, not previously achieved for Sn-based perovskites. This device architecture and materials set will enable all-perovskite thin-film solar cells to reach the highest efficiencies in the long term at the lowest costs.", + "Times Cited, WoS Core": 1224, + "Times Cited, All Databases": 1316, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000388531900034", + "Markdown": "# Perovskite-perovskite tandem photovoltaics with optimized bandgaps \n\nGiles E. Eperon,1,3\\* Tomas Leijtens,2\\* Kevin A. Bush,2 Rohit Prasanna,2 Thomas Green,1 Jacob Tse-Wei Wang,1 David P. McMeekin,1 George Volonakis,4 Rebecca L. Milot,1 Richard May,2 Axel Palmstrom,2 Daniel J. Slotcavage,2 Rebecca A. Belisle,2 Jay B. Patel,1 Elizabeth S. Parrott,1 Rebecca J. Sutton,1 Wen Ma,5 Farhad Moghadam,5 Bert Conings,1,6 Aslihan Babayigit,1,6 Hans-Gerd Boyen,6 Stacey Bent,2 Feliciano Giustino,4 Laura M. Herz,1 Michael B. Johnston,1 Michael D. McGehee,2† Henry J. Snaith1† \n\n1Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK. 2Department of Materials Science, Stanford University, Lomita Mall, Stanford, CA, USA. 3Department of Chemistry, University of Washington, Seattle, WA, USA. 4Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, UK. 5SunPreme, Palomar Avenue, Sunnyvale, CA, USA. 6Institute for Materials Research, Hasselt University, Diepenbeek, Belgium. \n\n\\*These authors contributed equally to this work. \n\n†Corresponding author. Email: mmcgehee@stanford.edu (M.D.M.); henry.snaith@physics.ox.ac.uk (H.J.S.) \n\nWe demonstrate four and two-terminal perovskite-perovskite tandem solar cells with ideally matched bandgaps. We develop an infrared absorbing $\\mathtt{1.2e V}$ bandgap perovskite, $\\mathsf{F A}_{0.75}\\mathsf{C s}_{0.25}\\mathsf{S}\\mathsf{n}_{0.5}\\mathsf{P b}_{0.5}\\mathsf{l}_{3}$ , that can deliver $14.8\\%$ efficiency. By combining this material with a wider bandgap $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}(\\mathsf{I}_{0.5}\\mathsf{B r}_{0.5})_{3}$ material, we reach monolithic two terminal tandem efficiencies of $17.0\\%$ with over 1.65 volts open-circuit voltage. We also make mechanically stacked four terminal tandem cells and obtain $20.3\\%$ efficiency. Crucially, we find that our infrared absorbing perovskite cells exhibit excellent thermal and atmospheric stability, unprecedented for Sn based perovskites. This device architecture and materials set will enable “all perovskite” thin film solar cells to reach the highest efficiencies in the long term at the lowest costs. \n\nMetal halide perovskites $\\mathrm{(ABX_{3}}$ , where A is typically Cs, methylammonium (MA), or formamidinium (FA), B is Pb or Sn, and X is I, Br, or Cl) have emerged as an extremely promising photovoltaic (PV) technology due to their rapidly increasing power conversion efficiencies (PCEs) and low processing costs. Single junction perovskite devices have reached a certified $22\\%$ PCE $(I)$ , but the first commercial iterations of perovskite PVs will likely be as an “add-on” to silicon (Si) PV. In a tandem configuration, a perovskite with a band gap of ${\\sim}1.75\\ \\mathrm{eV}$ can enhance the efficiency of the silicon cell. (2) An all-perovskite tandem cell could deliver lower fabrication costs, but requires band gaps that have not yet been realized. The highest efficiency tandem devices would require a rear cell with a band gap of 0.9 to $1.2{\\mathrm{~eV}}$ and a front cell with a band gap of 1.7 to $1.9\\ \\mathrm{eV}$ . Although materials such as $\\mathrm{FA_{0.83}C s_{\\ t r}P b(I_{x}B r_{1-x})_{3}}$ deliver appropriate band gaps for the front cell (2), Pb-based materials cannot be tuned to below $1.48\\ \\mathrm{\\eV}$ for the rear cell. Completely replacing Pb with Sn can shift the band gap to ${\\sim}1.3\\mathrm{eV}$ (for $\\mathrm{{MASnI}_{3}}.$ ) (3), but the tin-based materials are notoriously airsensitive and difficult to process, and PV devices based on them have been limited to ${\\sim}6\\%$ PCE. (3, 4) An anomalous band gap bowing in mixed tin-lead perovskite systems $(\\mathbf{MAPb}_{0.5}\\mathbf{Sn}_{0.5}\\mathbf{I}_{3})$ has given band gaps of ${\\sim}1.2\\mathrm{eV}$ but mediocre performance ${\\sim}7\\%$ PCE). Very recently, PCE of over $14\\%$ has been reported with $\\mathbf{MA}_{0.5}\\mathrm{FA}_{0.5}\\mathbf{Pb}_{0.75}\\mathbf{S}\\mathbf{n}_{0.25}\\mathbf{I}_{3}$ cells, for band $\\mathrm{\\gaps\\>\\1.3\\eV}$ and all-perovskite 4 terminal tandem cells with $19\\%$ efficiency. (5) $\\left(6\\right)$ (7). Here, we demonstrate a stable $14.8\\%$ efficient perovskite solar cell based on a $1.2~\\mathrm{eV}$ bandgap $\\mathrm{FA_{0.75}C s_{0.25}P b_{0.5}S n_{0.5}I_{3}}$ absorber. We measure opencircuit voltages $\\mathrm{(V_{oc}\\mathbf{s})}$ of up to $0.83{\\mathrm{~V~}}$ in these cells, which represents a smaller voltage deficit between band gap and $\\mathrm{v_{oc}}$ than measured for the highest efficiency lead based perovskite cells. We then combined these with 1.8 eV $\\mathrm{FA}_{0.83}\\mathrm{Cs}_{0.17}\\mathrm{Pb}(\\mathrm{I}_{0.5}\\mathrm{Br}_{0.5})_{3}$ perovskite cells, to demonstrate current matched and efficient $(17.0\\%)$ monolithic allperovskite 2-terminal tandem solar cells on small areas and $13.8\\%$ on large areas, with $\\mathrm{V}_{\\mathrm{oc}}>1.65\\:\\mathrm{V}$ . Finally, we fabricated $20.3\\%$ efficient small area and $16.0\\%$ efficient $\\mathrm{{1cm^{2}}}$ allperovskite four-terminal tandems using a semitransparent 1.6eV $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.83}B r_{0.17})_{3}}$ front cell. \n\nIt has proven difficult to fabricate smooth, pinhole-free layers of tin-based perovskites on planar substrates (fig. S1). (3, 4) We developed a technique, precursor-phase antisolvent immersion (PAI), to deposit uniform layers of tincontaining perovskites, $\\mathrm{FASn_{x}P b_{\\mathrm{1-x}}I_{3}}.$ , that combines two previous methods: the use of low vapor pressure solvents to retard crystallization by forming precursor complexes and an anti-solvent bath to crystallize the film with only gentle heating. $(4,\\ 8)$ Rather than using neat dimethyl sulfoxide (DMSO) as a solvent (4), a mixture of DMSO and dimethylformamide (DMF) allowed spin-coating of a uniform transparent precursor film that was not yet fully crystallized. Immersion of the films immediately in an antisolvent bath (anisole) (fig. S2) rapidly changed the film to a deep red. (9) Subsequent annealing at $70~^{\\circ}\\mathrm{C}$ removed residual DMSO (fig. S7) to form smooth, dark, highly crystalline and uniform $\\mathrm{FASn_{x}P b_{\\mathrm{1-x}}I_{3}}$ films over the entire range of values of $\\mathbf{\\boldsymbol{x}}=\\mathbf{\\boldsymbol{0}}$ to 1 (Fig. 1A). Only the neat $\\mathrm{\\bf{Pb}}$ perovskite required heating at a higher temperature $({\\bf170}^{\\mathrm{~\\circ}}{\\bf C})$ to convert the film from the yellow room-temperature phase to the black phase. (10) \n\nPhotoluminescence (PL) spectra and absorption spectra of a range of compositions (fig. S4) allowed us to estimate the optical band gap from Tauc plots (from absorption) and the PL peak positions (Fig. 1B). (9) The band gap narrowed between the two composition endpoints, similar to the observations of Kanatzidis et al. with the MA system (5), and between 50 to $75\\%$ Sn, was almost 1.2 eV. X-ray diffraction (XRD) spectra (fig. S5) for the whole series revealed a single dominant perovskite phase (see table S1). \n\nTo understand this anomalous band gap trend, we performed first-principles calculations of band gaps as a function of the tin-lead ratio (details in the SM). (9) For a disordered solid solution with Pb and Sn in random locations, the calculated band gap decreased monotonically (fig. S8). For an ordered structure, we placed the Sn and $\\mathrm{\\sfPb}$ atoms in specific positions relative to each other within a repeating lattice unit of eight octahedra in a ‘supercell’. Here, if we took the lowest band gaps for each ratio, an anomalous bandgap trend emerges (Fig. 1C). We elucidate that for compositions with more than $>50\\%$ Sn, a specific type of short-range order in the Pb-Sn positions allowed the band gap to dip below the end points. Im et al. attributed a similar band gap trend observed for $\\mathbf{MAPb_{x}S n_{\\mathrm{1-x}}I_{3}}$ to the competition between spin-orbit coupling and distortions of the lattice $(I I)$ , but if this was the case here, we should have observed it in the random solid solution approach. The energetic difference between the various Pb-Sn configurations was on the order of $2{\\mathrm{~meV}}$ , so at room temperature the materials are likely to contain various combinations of the configurations which we show in fig. S7, but the absorption and emission onsets reflect the regions with the smallest gap. \n\nIn order to determine the diffusion length, mobility and recombination lifetimes of these materials, we performed optical pump-probe terahertz (THz spectroscopy) on $\\mathrm{FASnI_{3}}$ and $\\mathrm{FASn_{0.5}P b_{0.5}I_{3}}$ . The fluence dependence of the THz transients for $\\mathrm{FASn_{0.5}P b_{0.5}I_{3}}$ (fig. S9) exhibited faster decays at higher intensities as the result of increased bimolecular and auger recombination. (12) We calculated the recombination rate constants and the charge-carrier mobilities, which were 22 and $17\\mathrm{cm^{2}V^{-1}s^{-1}}$ for $\\mathrm{FASnI_{3}}$ and $\\mathrm{FASn}_{0.5}\\mathrm{Pb}_{0.5}\\mathrm{I}_{3},$ respectively, comparable to values for $\\mathrm{\\bf{Pb}}$ perovskite films (12, 13). In comparison, for $\\mathrm{\\mathbf{MASnI_{3}}}$ , the value was only $\\mathrm{2\\cm^{2}V^{-1}s^{-1}}$ (3, ${\\mathbf{}}I4{\\mathbf{\\Gamma}},$ ). For charge-carrier densities typical under solar illumination, charge-carrier diffusion lengths of ${\\sim}300\\mathrm{nm}$ were reached for $\\mathrm{FASn_{0.5}P b_{0.5}I_{3}}$ (details in the SM). Although lower than that for the best reported perovskite materials, it is equivalent to the typical thickness required to absorb most incident light $_{\\sim300}$ to $400\\mathrm{nm}\\cdot$ ) (15). \n\nWe fabricated a series of planar heterojunction devices in the ‘inverted’ p-i-n architecture (16) comprising ITO/Poly(3,4-ethylenedioxythiophene)- poly(styrenesulfonate) (PEDOT:PSS) $/\\mathrm{FASn_{x}P b_{1}}$ - $\\mathrm{\\mathrm{\\Omega_{x}I_{3}/C_{60}/}}$ bathcuproine (BCP) capped with an Ag or Au electrode (Fig. 2A). The current-density voltage (J-V) curves and external quantum efficiency (EQE) measurements for the whole compositional series are shown in fig. S10. The onset of the EQEs closely matched that of the absorption of the materials, with light harvested out to $\\sim1020\\mathrm{nm}$ in the $50\\%$ - $75\\%$ Sn compositions. The highest efficiencies are generated from the devices with $50\\%$ Sn, within the lowest band gap region, thus we used this material to optimize our low-gap solar cells. \n\nA small addition of Cs boosts the performance and stability of Pb based perovskites. (17–19) Substituting $25\\%$ of the FA with Cs in our films had little impact on band gap, morphology, $\\mathrm{{\\PL,}}$ crystal structure, and charge carrier diffusion lengths (Fig. 1, figs. S4 and S7), but device performance was enhanced (Fig. 2, B to D). The best $\\mathrm{FASn_{0.5}P b_{0.5}I_{3}}$ device yields $10.9\\%$ PCE, whereas the best $\\mathbf{FA}_{0.75}\\mathbf{Cs}_{0.25}\\mathbf{Sn}_{0.5}\\mathbf{Pb}_{0.5}\\mathbf{I}_{3}$ device exhibited an impressive short-circuit current of $26.7\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ , $0.74\\mathrm{~V~V~}_{\\mathrm{OC}},$ and 0.71 FF to yield $14.1\\%$ PCE. We note that the processing of each composition was optimized separately. These devices did not exhibit appreciable ratedependent hysteresis and the stabilized power output $(14.8\\%)$ matched the scanned performance well. This efficiency was comparable with the very best solutionprocessed low band gap copper-indium-gallium-diselenide (CIGS) solar cells. (20) Thus, $\\mathrm{FA_{0.75}C s_{0.25}P b_{0.5}S n_{0.5}I_{3}}$ is well suited for a rear junction in a solution processed tandem solar cell, without the need for high temperature thermal processing. \n\nWe performed UPS and XPS measurements to determine the energetic positions of the conduction and valence bands (fig. S11). The band levels for $\\mathrm{FASn_{0.5}P b_{0.5}I_{3}}$ are well matched for C60 and PEDOT:PSS as electron and hole acceptors. The Cs-containing material showed an energetically shallower valance band and mild p-type doping (21, 22). \n\nThe electronic losses in a solar cell are reflected by the difference in energy between the band gap of the absorber and $\\mathrm{v_{oc}}$ (the loss-in-potential) (23). For crystalline silicon PV cells, which generate a record $\\mathrm{v_{oc}}$ of $0.74\\mathrm{~V~}$ and have a bandgap of $1.12\\ \\mathrm{eV}$ , this loss is $0.38{\\mathrm{~V}}{}$ . (24) Some of our $\\mathrm{FA_{0.75}C s_{0.25}S n_{0.5}P b_{0.5}I_{3}}$ devices here, with a thinner active layer, displayed ${\\mathbf{V}}_{\\mathrm{oc}}{\\mathbf{S}}$ up to $0.833\\mathrm{~V~}$ (fig. S11), with a $1.22\\ \\mathrm{eV}$ bandgap, exhibiting a comparable loss in potential of 0.386 eV. \n\nTin based perovskites have previously been observed to be extremely unstable in air (25), so we carried out a simple aging test on the $\\mathrm{FASn}_{0.5}\\mathrm{Pb}_{0.5}\\mathrm{I}_{3}$ and $\\mathrm{FA_{0.75}C s_{0.25}P b_{0.5}S n_{0.5}I_{3}}$ devices. We held the devices at maximum power point under $100\\mathrm{\\mWcm^{-2}}$ illumination and measured power output over time in ambient air with a relative humidity of $50\\pm5\\%$ (Fig. 2E). The $\\mathrm{FAPbI_{3}}$ device maintains its performance relatively well with a small drop observed over the time (to $85\\%$ of initial PCE over $50\\ \\mathrm{min};$ ), possibly associated with photooxidation and hydration of the un-encapsulated perovskite layer, or a partial reversion to the yellow room-temperature phase. $(I7,\\quad26)$ Both the $\\mathrm{FASn_{0.5}P b_{0.5}I_{3}}$ and $\\mathbf{FA}_{0.75}\\mathbf{Cs}_{0.25}\\mathbf{Sn}_{0.5}\\mathbf{Pb}_{0.5}\\mathbf{I}_{3}$ showed similar or even better stability than the neat Pb material. We also subjected bare perovskite films to thermal stress, heating for 4 days at $100^{\\circ}\\mathrm{C}$ under nitrogen; there were no changes in absorption spectra, a monitor of optical quality and hence stability(Fig. 2F) (27). We also monitored the performance of full devices at $85^{\\circ}\\mathrm{C}$ over several months (fig. S13), and found that the Sn:Pb material displays similar device stability as the neat Pb material. The contribution of both Sn and Pb orbitals to the valance band minimum may reduce the propensity of $\\mathrm{Sn^{2+}}$ to oxidize to $\\mathrm{Sn^{4+}}$ . \n\nA $1.2\\mathrm{eV}$ perovskite is ideally suited as the rear cell in either monolithic two terminal (2T) tandem solar cells or mechanically stacked four terminal (4T) tandem solar cells (Fig. 3A). The subcells in a 2T tandem must be current matched to deliver optimum performance, and connected with a recombination layer. A 4T tandem operates the two cells independently, but requires an extra transparent electrode which can result in more absorption losses and higher cost. Theoretical efficiencies using a $1.2\\:\\mathrm{eV}$ rear cell (fig. S14) show that the 2T architecture requires the use of a top cell with a ${\\sim}1.75{\\cdot}1.85\\ \\mathrm{eV}$ bandgap whereas the 4T architecture has a much more relaxed requirement of 1.6 to $1.9\\mathrm{eV}$ . \n\nWe can obtain efficient and stable perovskites with appropriate wide band gaps for front cells in tandem architectures by using a mixture of FA and Cs cations (2) and control the band gap by tuning the Br:I ratio; $\\mathrm{FA}_{0.83}\\mathrm{Cs}_{0.17}\\mathrm{Pb}(\\mathrm{I}_{0.5}\\mathrm{Br}_{0.5})_{3}$ has a $1.8\\ \\mathrm{eV}$ band gap ideally suited for the 2T tandem. However, their higher losses in potential than the more commonly used $1.6~\\mathrm{eV}$ perovskites (28) make the latter more suited for the 4T tandem. We prepared both of these perovskites in the p-i-n structure depicted in Fig. 3A, using $\\mathrm{NiO_{x}}$ and phenyl-C61-butyric acid methyl ester (PCBM) as the hole and electron contacts respectively. We applied the PAI deposition route to form smooth and thick perovskite layers, obtaining efficient devices with appropriate photocurrents and voltages up to 1.1V (see fig. S14). (9) \n\nFor the recombination layer in the 2T cell, we used a layer of tin oxide coated with sputter coated indium tin oxide (ITO) (29). This ITO layer completely protects the underlying perovskite solar cell from any solvent damage (fig. S16), meaning we could fabricate the $1.2~\\mathrm{eV}$ $\\mathrm{FA_{0.75}C s_{0.25}S n_{0.5}P b_{0.5}I_{3}}$ solar cell directly on top. We plot the JV curves of the best single junction $1.2~\\mathrm{eV}$ cells, single junction $1.8~\\mathrm{eV}$ cell, and that of the best 2T tandem device in Fig. 3C. We observed good performance for the 2T tandem solar cells, in excess of either of the individual subcells and impressive considering the somewhat non-optimized $1.8\\mathrm{eV}$ top cell. The photocurrent of the tandem solar cell was $\\mathbf{14.5mAcm^{-2}}$ , voltage is an appropriate addition of the two subcells $(1.66\\mathrm{V})$ , and the fill factor is 0.70, yielding an overall performance of $16.9\\%$ via a scanned JV curve and of $17.0\\%$ when stabilized at its maximum power point. None of the devices exhibit substantial hysteresis in the JV curves (Fig. 3G and fig. S17). \n\nThe photocurrent is remarkably high when compared to the photocurrent density of the best reported monolithic perovskite-silicon tandems. (30, 31) EQE measurements (Fig. 3D) demonstrate that the two subcells are fairly well matched, with the wide gap subcell limiting the current. One benefit of a tandem architecture, that we observe here, is that the FF tends not to be limited to the lowest value of the individual subcells, due to the reduced impact of series resistance on a higher-voltage cell. (32) Furthermore, we held a 2T tandem at its maximum power point under illumination in nitrogen for more than 18 hours and it showed effectively no performance drop (fig. S18). \n\nFor a 4T tandem, we used an efficient $\\mathrm{1.6eV}$ band gap $\\mathrm{FA_{0.83}C s_{0.17}P b(I_{0.83}B r_{0.17})_{3}}$ perovskite, similar to that reported by McMeekin et al. but in p-i-n configuration (2) with a transparent ITO top contact. We obtained a $15.8\\%$ efficient solar cell with a $\\mathrm{\\DeltaV_{oc}\\sim1\\Delta V_{:}}$ , and when we use it to filter a $14.8\\%$ $\\mathrm{FA}_{0.75}\\mathrm{Cs}_{0.25}\\mathrm{Sn}_{0.5}\\mathrm{Pb}_{0.5}\\mathrm{I}_{3}$ cell, we can still extract substantial photocurrent $(7.9\\mathrm{\\mA\\cm^{-2}},$ from the low-bandgap device. We plot the JV curves and EQE spectra of the 1.6 and $1.2\\ \\mathrm{eV}$ cells in the 4T tandem in Fig. 3E and F, and show we can obtain an additional $4.5\\%$ PCE from the $1.2\\ \\mathrm{eV}$ rear cell, yielding an overall stabilized tandem efficiency of $20.3\\%$ (Fig. 3G). \n\nThe above results were for $0.2\\mathrm{cm}^{2}$ devices. We also made large-area $\\mathrm{(1cm^{2})}$ versions of the single junctions, 2T and 4T tandems and show the current-voltage characteristics in Table 2 and fig. S18, with 2T tandem $\\mathrm{{1cm^{2}}}$ devices exhibiting $13.8\\%$ stabilized PCE and 4T tandems $16.0\\%$ . The $17.0\\%$ PCE 2T and $20.3\\%$ 4T tandems, which are for devices that could be further optimized, are already far in excess of the best tandem solar cells made with other similarly low cost semiconductors, such as those made with organic small molecules (world record $13\\%$ ) or amorphous and microcrystalline silicon $(13.5\\%)$ . $(I,24)$ Notably, our results illustrate that the tandem cell should be at least 4 to $5\\%$ more efficient than the best $1.6\\ \\mathrm{eV}$ single junction perovskite cells, indicating that as the efficiency of the single junction cells increases, then the tandem approach will enable this low temperatureprocessed polycrystalline thin film technology to surpass the $30\\%$ efficiency barrier. \n\nREFERENCES AND NOTES \n1. NREL, Best Research-Cell Efficiencies, http://www.nrel.gov/ncpv/images/efficiency_chart.jpg (2016;). \n2. D. P. McMeekin, G. Sadoughi, W. Rehman, G. E. Eperon, M. Saliba, M. T. Hörantner, A. Haghighirad, N. Sakai, L. Korte, B. Rech, M. B. Johnston, L. M. Herz, H. J. Snaith, A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells. Science 351, 151–155 (2016). doi:10.1126/science.aad5845 Medline \n3. N. K. Noel, S. D. Stranks, A. Abate, C. Wehrenfennig, S. Guarnera, A.-A. Haghighirad, A. Sadhanala, G. E. Eperon, S. K. Pathak, M. B. Johnston, A. Petrozza, L. M. Herz, H. J. Snaith, Lead-free organic-inorganic tin halide perovskites for photovoltaic applications. Energy Environ. Sci. 7, 3061–3068 (2014). doi:10.1039/C4EE01076K \n4. F. Hao et al., Solvent-mediated crystallization of CH3NH3SnI 3 films for heterojunction depleted perovskite solar cells. J. Am. Chem. Soc. 137, 11445– 11452 (2015). \n5. F. Hao, C. C. Stoumpos, R. P. H. Chang, M. G. Kanatzidis, Anomalous band gap behavior in mixed Sn and Pb perovskites enables broadening of absorption spectrum in solar cells. J. Am. Chem. Soc. 136, 8094–8099 (2014). doi:10.1021/ja5033259 Medline \n6. L. Zhu, B. Yuh, S. Schoen, X. Li, M. Aldighaithir, B. J. Richardson, A. Alamer, Q. Yu, Solvent-molecule-mediated manipulation of crystalline grains for efficient planar binary lead and tin triiodide perovskite solar cells. Nanoscale 8, 7621–7630 (2016). doi:10.1039/C6NR00301J Medline \n7. Z. Yang, A. Rajagopal, C. C. Chueh, S. B. Jo, B. Liu, T. Zhao, A. K. Jen, Stable lowbandgap Pb-Sn binary perovskites for tandem solar cells. Adv. Mater. (2016). doi:10.1002/adma.201602696 Medline \n8. Y. Zhou, M. Yang, W. Wu, A. L. Vasiliev, K. Zhu, N. P. Padture, Room-temperature crystallization of hybrid-perovskite thin films via solvent-solvent extraction for high-performance solar cells. J. Mater. Chem. A Mater. Energy Sustain. 3, 8178– 8184 (2015). doi:10.1039/C5TA00477B \n9. See supplementary materials on Science Online. \n10. C. C. Stoumpos, C. D. Malliakas, M. G. Kanatzidis, Semiconducting tin and lead iodide perovskites with organic cations: Phase transitions, high mobilities, and near-infrared photoluminescent properties. Inorg. Chem. 52, 9019–9038 (2013). doi:10.1021/ic401215x Medline \n11. J. Im, C. C. Stoumpos, H. Jin, A. J. Freeman, M. G. Kanatzidis, Antagonism between spin-orbit coupling and steric effects causes anomalous band gap evolution in the perovskite photovoltaic materials $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{S n}_{1-x}\\mathsf{P b}_{x}\\mathsf{I}_{3}$ J. Phys. Chem. Lett. 6, 3503–3509 (2015). doi:10.1021/acs.jpclett.5b01738 Medline \n12. L. M. Herz, Charge-carrier dynamics in organic-inorganic metal halide perovskites. Annu. Rev. Phys. Chem. 67, 65–89 (2016). doi:10.1146/annurevphyschem-040215-112222 \n13. W. Rehman, R. L. Milot, G. E. Eperon, C. Wehrenfennig, J. L. Boland, H. J. Snaith, M. B. Johnston, L. M. Herz, Charge-carrier dynamics and mobilities in formamidinium lead mixed-halide perovskites. Adv. Mater. 27, 7938–7944 (2015). doi:10.1002/adma.201502969 Medline \n14. E. S. Parrott, R. L. Milot, T. Stergiopoulos, H. J. Snaith, M. B. Johnston, L. M. Herz, Effect of structural phase transition on charge-carrier lifetimes and defects in CH3NH3SnI3 perovskite. J. Phys. Chem. Lett. 7, 1321–1326 (2016). doi:10.1021/acs.jpclett.6b00322 Medline \n15. M. B. Johnston, L. M. Herz, Hybrid perovskites for photovoltaics: Charge-carrier recombination, diffusion, and radiative efficiencies. Acc. Chem. Res. 49, 146–154 (2016). doi:10.1021/acs.accounts.5b00411 Medline \n16. P. Docampo, J. M. Ball, M. Darwich, G. E. Eperon, H. J. Snaith, Efficient organometal trihalide perovskite planar-heterojunction solar cells on flexible polymer substrates. Nat. Commun. 4, 2761 (2013). doi:10.1038/ncomms3761 Medline \n17. Z. Li, M. Yang, J.-S. Park, S.-H. Wei, J. J. Berry, K. Zhu, Stabilizing perovskite structures by tuning tolerance factor: formation of formamidinium and cesium lead iodide solid-state alloys. Chem. Mater. 28, 284–292 (2016). doi:10.1021/acs.chemmater.5b04107 \n18. J.-W. Lee, D.-H. Kim, H.-S. Kim, S.-W. Seo, S. M. Cho, N.-G. Park, Formamidinium and cesium hybridization for photo- re-stable perovskite solar cell. Adv. Energy Mater. 5, 1501310 (2015). doi:10.1002/aenm.201501310 \n19. C. Yi et al., Entropic stabilization of mixed A-cation ABX 3 metal halide perovskites for high performance perovskite solar cells. Energy Environ. Sci. 2, 303 (2016). \n20. T. K. Todorov, O. Gunawan, T. Gokmen, D. B. Mitzi, Solution-processed Cu $(\\mathsf{I n},\\mathsf{G a})(\\mathsf{S},\\mathsf{S e})_{2}$ absorber yielding a $15.2\\%$ efficient solar cell. Prog. Photovolt. Res. Appl. 21, 82–87 (2013). doi:10.1002/pip.1253 \n21. P. Schulz, E. Edri, S. Kirmayer, G. Hodes, D. Cahen, A. Kahn, Interface energetics in organo-metal halide perovskite-based photovoltaic cells. Energy Environ. Sci. 7, 1377 (2014). doi:10.1039/c4ee00168k \n22. C. Wang, C. Wang, X. Liu, J. Kauppi, Y. Shao, Z. Xiao, C. Bi, J. Huang, Y. Gao, Electronic structure evolution of fullerene on CH3NH3PbI3. Appl. Phys. Lett. 106, 111603 (2015). doi:10.1063/1.4916079 \n23. H. J. Snaith, Estimating the maximum attainable efficiency in dye-sensitized solar cells. Adv. Funct. Mater. 20, 13–19 (2010). doi:10.1002/adfm.200901476 \n24. M. A. Green, K. Emery, Y. Hishikawa, W. Warta, E. D. Dunlop, Solar cell efficiency tables (version 45). Prog. Photovolt. Res. Appl. 23, 1–9 (2015). doi:10.1002/pip.2573 \n25. F. Hao, C. C. Stoumpos, D. H. Cao, R. P. H. Chang, M. G. Kanatzidis, Lead-free solid-state organic–inorganic halide perovskite solar cells. Nat. Photonics 8, 489–494 (2014). doi:10.1038/nphoton.2014.82 \n26. T. Leijtens, G. E. Eperon, N. K. Noel, S. N. Habisreutinger, A. Petrozza, H. J. Snaith, Stability of metal halide perovskite solar cells. Adv. Energy Mater. 5, 1500963 (2015). doi:10.1002/aenm.201500963 \n27. B. Conings, J. Drijkoningen, N. Gauquelin, A. Babayigit, J. D’Haen, L. D’Olieslaeger, A. Ethirajan, J. Verbeeck, J. Manca, E. Mosconi, F. D. Angelis, H.-G. Boyen, Intrinsic thermal instability of methylammonium lead trihalide perovskite. Adv. Energy Mater. 5, 1500477 (2015). doi:10.1002/aenm.201500477 \n28. D. Bi, W. Tress, M. I. Dar, P. Gao, J. Luo, C. Renevier, K. Schenk, A. Abate, F. Giordano, J.-P. Correa Baena, J.-D. Decoppet, S. M. Zakeeruddin, M. K. Nazeeruddin, M. Grätzel, A. Hagfeldt, Efficient luminescent solar cells based on tailored mixed-cation perovskites. Sci. Adv. 2, e1501170 (2016). doi:10.1126/sciadv.1501170 Medline \n29. K. A. Bush, C. D. Bailie, Y. Chen, A. R. Bowring, W. Wang, W. Ma, T. Leijtens, F. Moghadam, M. D. McGehee, Thermal and environmental stability of semitransparent perovskite solar cells for tandems enabled by a solution-processed nanoparticle buffer layer and sputtered ITO electrode. Adv. Mater. 28, 3937– 3943 (2016). doi:10.1002/adma.201505279 Medline \n30. J. Werner, C.-H. Weng, A. Walter, L. Fesquet, J. P. Seif, S. De Wolf, B. Niesen, C. Ballif, Efficient monolithic perovskite/silicon tandem solar cell with cell area >1 cm2. J. Phys. Chem. Lett. 7, 161–166 (2016). doi:10.1021/acs.jpclett.5b02686 Medline \n31. S. Albrecht, M. Saliba, J. P. Correa Baena, F. Lang, L. Kegelmann, M. Mews, L. Steier, A. Abate, J. Rappich, L. Korte, R. Schlatmann, M. K. Nazeeruddin, A. Hagfeldt, M. Grätzel, B. Rech, Monolithic perovskite/silicon-heterojunction tandem solar cells processed at low temperature. Energy Environ. Sci. 9, 81–88 (2015). doi:10.1039/C5EE02965A \n32. A. Hadipour, B. de Boer, J. Wildeman, F. B. Kooistra, J. C. Hummelen, M. G. R. Turbiez, M. M. Wienk, R. A. J. Janssen, P. W. M. Blom, Solution-processed organic tandem solar cells. Adv. Funct. Mater. 16, 1897–1903 (2006). doi:10.1002/adfm.200600138 \n33. D. Sabba, H. K. Mulmudi, R. R. Prabhakar, T. Krishnamoorthy, T. Baikie, P. P. Boix, S. Mhaisalkar, N. Mathews, Impact of anionic Br- substitution on open circuit voltage in lead free perovskite $(\\mathsf{C s S n l_{3\\cdot\\times}B r_{x}})$ solar cells. J. Phys. Chem. C 119, 1763–1767 (2015). doi:10.1021/jp5126624 \n34. T. M. Koh, T. Krishnamoorthy, N. Yantara, C. Shi, W. L. Leong, P. P. Boix, A. C. Grimsdale, S. G. Mhaisalkar, N. Mathews, Formamidinium tin-based perovskite with low $E_{\\mathrm{g}}$ for photovoltaic applications. J. Mater. Chem. A Mater. Energy Sustain. 3, 14996–15000 (2015). doi:10.1039/C5TA00190K \n35. P. Giannozzi, S. Baroni, N. Bonini, M. Calandra, R. Car, C. Cavazzoni, D. Ceresoli, G. L. Chiarotti, M. Cococcioni, I. Dabo, A. Dal Corso, S. de Gironcoli, S. Fabris, G. Fratesi, R. Gebauer, U. Gerstmann, C. Gougoussis, A. Kokalj, M. Lazzeri, L. Martin-Samos, N. Marzari, F. Mauri, R. Mazzarello, S. Paolini, A. Pasquarello, L. Paulatto, C. Sbraccia, S. Scandolo, G. Sclauzero, A. P. Seitsonen, A. Smogunov, P. Umari, R. M. Wentzcovitch, QUANTUM ESPRESSO: A modular and opensource software project for quantum simulations of materials. J. Phys. Condens. Matter 21, 395502 (2009). doi:10.1088/0953-8984/21/39/395502 Medline \n36. J. P. Perdew, K. Burke, M. Ernzerhof, Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). doi:10.1103/PhysRevLett.77.3865 Medline \n37. N. Troullier, J. L. Martins, Efficient pseudopotentials for plane-wave calculations. Phys. Rev. B Condens. Matter 43, 1993–2006 (1991). doi:10.1103/PhysRevB.43.1993 Medline \n38. J. P. Perdew, M. Ernzerhof, K. Burke, Rationale for mixing exact exchange with density functional approximations. J. Chem. Phys. 105, 9982 (1996). doi:10.1063/1.472933 \n39. H. J. Snaith, How should you measure your excitonic solar cells? Energy Environ. Sci. 5, 6513 (2012). doi:10.1039/c2ee03429h \n40. S. Sista, Z. Hong, M. H. Park, Z. Xu, Y. Yang, High-efficiency polymer tandem solar cells with three-terminal structure. Adv. Mater. 22, E77–E80 (2010). doi:10.1002/adma.200901624 Medline \n41. J. B. Patel, R. L. Milot, A. D. Wright, L. M. Herz, M. B. Johnston, Formation dynamics of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ perovskite following two-step layer deposition. J. Phys. Chem. Lett. 7, 96–102 (2016). Medline \n42. C. Wehrenfennig, G. E. Eperon, M. B. Johnston, H. J. Snaith, L. M. Herz, High charge carrier mobilities and lifetimes in organolead trihalide perovskites. Adv. Mater. 26, 1584–1589 (2014). doi:10.1002/adma.201305172 Medline \n43. M. R. Filip, G. E. Eperon, H. J. Snaith, F. Giustino, Steric engineering of metalhalide perovskites with tunable optical band gaps. Nat. Commun. 5, 5757 (2014). doi:10.1038/ncomms6757 Medline \n\n# ACKNOWLEDGMENTS \n\nWe thank M. T. Hörantner for performing the Shockley-Queisser calculation. The research leading to these results has received funding from the Graphene Flagship (EU FP7 grant no. 604391), the Leverhulme Trust (Grant RL-2012-001), the UK Engineering and Physical Sciences Research Council (Grant No. EP/ J009857/1 and EP/M020517/1), and the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement nos. 239578 (ALIGN) and 604032 (MESO). TL is funded by a Marie Sklodowska Curie International Fellowship under grant agreement H2O2IF-GA-2015-659225. AB is financed by IMEC (Leuven) in the framework of a joint PhD program with Hasselt University. BC is a postdoctoral research fellow of the Research Fund Flanders (FWO). We also acknowledge the Office of Naval Research USA for support. We acknowledge the use of the University of Oxford Advanced Research Computing (ARC) facility (http://dx.doi.org/10.5281/zenodo.22558) and the ARCHER UK National Super-computing Service under the “AMSEC” Leadership project. We thank the Global Climate and Energy Project (GCEP) at Stanford University. All data pertaining to the conclusions of this work is present in the main paper and the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/cgi/content/full/science.aaf9717/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S21 \nTables S1 and S2 \nReferences (33–43) \n\n27 April 2016; resubmitted 15 August 2016 \nAccepted 4 October 2016 \nPublished online 20 October 2016 \n10.1126/science.aaf9717 \n\n![](images/bede8f1f1c4786cb70464a09b114a343ecfe1134627edde45cdfbcbdffbe1123.jpg) \nFig. 1. Tin-lead alloying. (a) Scanning electron microscope (SEM) images showing the top surface of $\\mathsf{F A S n}_{\\mathrm{x}}\\mathsf{P b}_{\\mathrm{x}\\mathrm{x}}|_{3}$ films with different Sn percentages and $\\mathsf{F A}_{0.75}\\mathsf{C s}_{0.25}\\mathsf{P b}_{0.5}\\mathsf{S}\\mathsf{n}_{0.5}\\mathsf{l}_{3}$ (discussed later, and labeled here as “ $50\\%$ , $\\mathsf{F A}_{0.75}\\mathsf{C s}_{0.25}\\mathrm{\\Delta}^{\\prime\\prime})$ , fabricated with the PAI deposition technique. The $0\\%$ Sn films were annealed at $170^{\\circ}\\mathrm{C}$ , while the other films were heated at $70~^{\\circ}\\mathrm{C}$ . (b) Plot of experimentally estimated bandgap as a function of $S_{n}\\%$ , determined from absorption onset in a Tauc plot (assuming direct bandgap) of the absorption (black); PL peak positions are given in red. (c) Bandgaps for Sn-Pb perovskite alloys calculated from first principles using a supercell containing eight ${\\mathsf{B X}}_{6}$ octahedra, where the Sn and Pb atoms are ordered relative to each other (See SM for full details). Points plotted represent all possible bandgaps for a particular composition, based on all possible Sn-Pb configurations; a solid line is drawn through the lowest bandgap options as a comparison to experiment. \n\n![](images/fa92866a4e1d3ab6f404cca098b114c765e85bad58a7e0499215430ec6a5a2cd.jpg) \nFig. 2. Performance and stability of $\\mathsf{F A S n}_{0.5}\\mathsf{P b}_{0.5}|_{3}$ and $\\mathsf{F A}_{0.75}\\mathsf{C s}_{0.25}\\mathsf{S}\\mathsf{n}_{0.5}\\mathsf{P b}_{0.5}\\mathsf{I}_{3}$ perovskite solar cells. (a) Schematic of the device architecture for narrow-gap single junction perovskite solar cells. (b) Currentvoltage characteristics under AM1.5G illumination for the champion $\\mathsf{F A S n}_{0.5}\\mathsf{P b}_{0.5}|_{3}$ and $\\mathsf{F A}_{0.75}\\mathsf{C s}_{0.25}\\mathsf{S}\\mathsf{n}_{0.5}\\mathsf{P b}_{0.5}\\mathsf{I}_{3}$ devices under illumination (solid lines) and in the dark (dotted lines), measured at 0.1V/s with no pre-biasing or light soaking. (c) Champion solar cells stabilized power output, measured via a maximum power point tracking algorithm. (d) External quantum efficiency for the champion devices of each material with the integrated current shown as an inset, providing a good match to the JV scan $\\mathsf{J}_{\\mathsf{s c}}$ . (e) PCE as a function of time for three compositions of $\\mathsf{F A S n}_{\\mathrm{x}}\\mathsf{P b}_{\\mathrm{1-x}}\\mathsf{I}_{3}$ $\\scriptstyle x=0$ , 0.5, 1) as well as $\\mathsf{F A}_{0.75}\\mathsf{C s}_{0.25}\\mathsf{S}\\mathsf{n}_{0.5}\\mathsf{P b}_{0.5}\\mathsf{l}_{3}$ measured by holding the cell at maximum power point in air under AM1.5 illumination. (f) Thermal stability of $\\mathsf{F A S n}_{0.5}\\mathsf{P b}_{0.5}|_{3}$ and $\\mathsf{F A}_{0.75}\\mathsf{C s}_{0.25}\\mathsf{S}\\mathsf{n}_{0.5}\\mathsf{P b}_{0.5}\\mathsf{l}_{3}$ films, quantified by heating the samples at $100^{\\circ}\\mathrm{C}$ and monitoring their absorption at 900 nm as a function of time. \n\n![](images/fbb890675445bb9d8fc4c7f8f549fff247d2e16bac0b067686b724361a7a9822.jpg) \n\nFig. 3. Perovskite-perovskite tandems. (a) Schematics showing 2- and 4-terminal tandem perovskite solar cell concepts. In this image devices would be illuminated from below. (b) Scanning electron micrograph of the two-terminal perovskiteperovskite tandem. (c) Scanned current-voltage characteristics under AM 1.5G illumination, of the two-terminal perovskite-perovskite tandem, of the 1.2 eV solar cell, and the ITO capped 1.8 eV solar cell. (d) External quantum efficiency spectra for the sub-cells. (e) J-V curves of a $1.2\\ \\mathrm{eV}$ perovskite, of that same solar cell filtered by an ITO capped 1.6 eV perovskite solar cell, and the ITO capped 1.6 eV perovskite solar cell, used to determine the mechanically stacked tandem efficiency. (f) External quantum efficiency spectra for the mechanically stacked tandem. (g) The stabilized power output tracked over time at maximum power point for the 2T perovskite solar cell, the 1.2 eV perovskite solar cell filtered by an ITO capped 1.6 eV perovskite solar cell, the ITO capped 1.6 eV perovskite solar cell, and the mechanically stacked tandem under AM 1.5G illumination. The SPO for the 1.8 eV subcell is plotted in fig. S14 and given in Table 2. \n\nTable 1. Device parameters corresponding to the J-V curves in Fig. 2b. \n\n\n
Jsc (mA cm-2)Voc (V)FFPCE (%)SPO (%)
FASno.5Pb0.5I321.90.700.6610.210.9
FA0.75CS0.25Sn0.5Pbo.51326.70.740.7114.114.8
\n\nTable 2. Solar cell performance parameters corresponding to the J-V curves shown in Fig. 3. Cell active areas are 0.20 or $1\\mathrm{cm}^{2}$ . SP $\\c=$ stabilized power output from MPP tracking. Large area tandem data are plotted in fig. S19. \n\n\n
Jsc (mA cm-2)Voc (V)FFPCE (%)SPO (%)
1.2 eV cell26.70.740.7114.114.8
1.8 eV cell15.11.120.589.89.5
2T tandem14.51.660.7016.917.0
Filtered 1.2 eV cell7.90.740.734.44.5
ITO capped 1.6 eV cell20.30.970.7915.715.8
4T tandem20.120.3
1 cm² 2T tandem13.51.760.5613.313.8
1 cm² 4T tandem16.416.0
\n\nPerovskite-perovskite tandem photovoltaics with optimized \nbandgaps \nGiles E. Eperon, Tomas Leijtens, Kevin A. Bush, Rohit Prasanna, Thomas Green, Jacob Tse-Wei Wang, David P. McMeekin, George Volonakis, Rebecca L. Milot, Richard May, Axel Palmstrom, Daniel J. Slotcavage, Rebecca A. Belisle, Jay B. Patel, Elizabeth S. Parrott, Rebecca J. Sutton, Wen Ma, Farhad Moghadam, Bert Conings, Aslihan Babayigit, Hans-Gerd Boyen, Stacey Bent, Feliciano Giustino, Laura M. Herz, Michael B. Johnston, Michael D. McGehee and Henry J. Snaith (October 20, 2016) \npublished online October 20, 2016 \n\nEditor's Summary \n\nThis copy is for your personal, non-commercial use only. \n\n# Article Tools \n\nVisit the online version of this article to access the personalization and article tools: http://science.sciencemag.org/content/early/2016/10/19/science.aaf9717 \n\n# Permissions \n\nObtain information about reproducing this article: http://www.sciencemag.org/about/permissions.dtl " + }, + { + "id": "10.1021_acs.nullolett.5b04331", + "DOI": "10.1021/acs.nullolett.5b04331", + "DOI Link": "http://dx.doi.org/10.1021/acs.nullolett.5b04331", + "Relative Dir Path": "mds/10.1021_acs.nullolett.5b04331", + "Article Title": "Defects Engineered Monolayer MoS2 for Improved Hydrogen Evolution Reaction", + "Authors": "Ye, GL; Gong, YJ; Lin, JH; Li, B; He, YM; Pantelides, ST; Zhou, W; Vajtai, R; Ajayan, PM", + "Source Title": "nullO LETTERS", + "Abstract": "MoS2 is a promising and low-cost material for electrochemical hydrogen production due to its high activity and stability during the reaction. However, the efficiency of hydrogen production is limited by the amount of active sites, for example, edges, in MoS2. Here, we demonstrate that oxygen plasma exposure and hydrogen treatment on pristine monolayer MoS2 could introduce more active sites via the formation of defects within the monolayer, leading to a high density of exposed edges and a significant improvement of the hydrogen evolution activity. These as-fabricated defects are characterized at the scale from macroscopic continuum to discrete atoms. Our work represents a facile method to increase the hydrogen production in electrochemical reaction of MoS2 via defect engineering, and helps to understand the catalytic properties of MoS2.", + "Times Cited, WoS Core": 1073, + "Times Cited, All Databases": 1139, + "Publication Year": 2016, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000370215200042", + "Markdown": "# Defects Engineered Monolayer $M o S_{2}$ for Improved Hydrogen Evolution Reaction \n\nGonglan Ye,† Yongji Gong,\\*,‡ Junhao Lin,§,∥ Bo Li,† Yongmin He,† Sokrates T. Pantelides,§,∥ Wu Zhou,§ Robert Vajtai,\\*,† and Pulickel M. Ajayan\\*,†,‡ \n\n†Department of Materials Science and NanoEngineering, Rice University, Houston, Texas 77005, United States ‡Department of Chemistry, Rice University, Houston, Texas 77005, United States §Materials Science and Technology Division, Oak Ridge National Lab, Oak Ridge, Tennessee 37831, United States ∥Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee 37235, United States \n\nSupporting Information \n\nABSTRACT: $\\mathbf{MoS}_{2}$ is a promising and low-cost material for electrochemical hydrogen production due to its high activity and stability during the reaction. However, the efficiency of hydrogen production is limited by the amount of active sites, for example, edges, in $\\mathbf{MoS}_{2}$ . Here, we demonstrate that oxygen plasma exposure and hydrogen treatment on pristine monolayer $\\mathbf{MoS}_{2}$ could introduce more active sites via the formation of defects within the monolayer, leading to a high density of exposed edges and a significant improvement of the hydrogen evolution activity. These as-fabricated defects are characterized at the scale from macroscopic continuum to discrete atoms. \n\n![](images/209f99cd114fb21d462e68607c7876474c4d6042e74e89284bfec0b97d5eb47b.jpg) \n$\\mathsf{M o S}_{2}$ treated by $\\mathsf{O}_{2}$ plasma $\\mathsf{M o S}_{2}$ annealed by ${\\sf H}_{2}$ \n\nOur work represents a facile method to increase the hydrogen production in electrochemical reaction of $\\mathbf{MoS}_{2}$ via defect engineering, and helps to understand the catalytic properties of $\\mathbf{MoS}_{2}$ . \n\nKEYWORDS: Monolayer $M o S_{\\upsilon}$ hydrogen evolution reaction, defects, oxygen plasma, hydrogen treatment \n\nC lean, renewable and affordable energy is highly demanded nowadays because of the growing population.1−5 To replace fossil fuels, developing renewable energy technologies from renewable resources is a major trend.6,7 Among the possible alternative energy resources, hydrogen $\\left(\\operatorname{H}_{2}\\right)$ has the advantages of highest mass energy density and renewability.8−10 Water splitting is the most convenient and promising method to produce $\\mathrm{H}_{2}$ . Platinum $\\left(\\mathrm{Pt}\\right)$ , which has a slightly negative hydrogen absorption energy and minimum overpotential, is considered to be the best-known catalyst for hydrogen evolution reaction (HER).11,12 However, the scarcity and high cost of Pt largely limits its applications. Therefore, intensive efforts have been contributed to the investigation of non-noble-metal alternatives such as nickel alloys, metal sulfides, metal oxides, and so forth. \n\nMolybdenum disulfide $(\\ensuremath{\\mathrm{MoS}}_{2})$ , a hexagonally packed layered structure of transition metal dichalcogenide (TMD), has drawn significant attentions in recent years.13,14 The high activity and good stability of $\\mathbf{MoS}_{2}$ for hydrogen production makes it a potential candidate to replace Pt. The study of $\\ensuremath{\\mathbf{MoS}}_{2}$ for electrochemical hydrogen evolution can be traced back to $1970s^{15}$ but with slow progress due to the poor activity of bulk $\\mathbf{MoS}_{2}$ . However, interests were raised again due to the significant enhancement of HER activity in nanostructured $\\bar{\\mathbf{Mo}}{S_{2}}$ .16−19 Both experimental and theoretical studies demonstrated that for 2H phase $\\mathbf{MoS}_{2}$ layers only the edges have high activities for HER, while the basal plane is catalytically inert.20−24 Since then, many efforts, including phase and structure engineering, have been made to improve the performance of $\\mathbf{MoS}_{2}$ as HER catalysts.25 Compared to 2H phase, 1T phase $\\mathbf{MoS}_{2}$ is catalytically active in both basal plane and edge. As a result, lithium insertion has been developed to initiate 2H to 1T phase transition in $\\mathbf{MoS}_{2}$ which leads to an improved HER performance.16,22,26 However, the unstable nature of 1T phase $\\mathbf{MoS}_{2}$ limits its applications. On the other hand, amorphous, mesoporous, or nanosized 2H phase $\\mathbf{MoS}_{2}$ structures with more active sites have shown great improvements in HER, that is, higher turnover frequency, higher current density and lower overpotential.27,8,28,29,25,30,31 However, all of the structural engineering are performed during the synthesis of $\\mathbf{Mo}S_{2}$ . Few methods have been explored to improve the HER in pristine $\\mathbf{Mo}S_{2}$ . Furthermore, it is difficult to correlate the structural modification with the improved HER performance in the $\\mathbf{MoS}_{2}$ nanoclusters due to the difficulty in identifying their detailed HER-active structures. \n\nHere, we demonstrate the correlation between the number of defects and HER performance in $\\mathbf{MoS}_{2}$ after specific postsynthesis treatments. Pristine $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ monolayers were synthesized by chemical vapor deposition (CVD) method. Two postsynthesis strategies, oxygen plasma exposure and $\\mathrm{H}_{2}$ treatment at high temperature, have been applied to create cracks and triangular holes in monolayer $\\mathrm{MoS}_{2},$ respectively. Compared to the pristine $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2},$ these defects lead to the significant improvements of the HER performances. $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ treated by $\\mathrm{H}_{2}$ shows higher improvement than that treated by $\\mathrm{O}_{2}$ plasma because of the higher density of the exposed edges. \n\n![](images/d919def5ababfdaac409d13cb73a14304f2f046ebcaf0ac3915b94827aaac750.jpg) \nFigure 1. Morphology of monolayer $\\mathbf{MoS}_{2}$ synthesized by CVD method on $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate and transferred onto glassy carbon electrode. (A) SEM image of CVD grown triangular $\\mathbf{MoS}_{2}$ monolayers. (B) Optical microscopy image of monolayer triangles. Small bilayer domains with darker color can be observed. (C) AFM image of CVD grown $\\mathbf{MoS}_{2}$ with a thickness of ${\\sim}0.7~\\mathrm{nm}$ (inset profile), as measured along the white line. (D) STEMHAADF image of monolayer $\\mathbf{MoS}_{2}$ shows its perfect hexagonal lattice with 2H structure. (E) Photograph of working electrode used for electrochemical test. $\\mathbf{MoS}_{2}$ monolayers were transferred to the removable glassy carbon electrode for further test. (F) SEM image of monolayer $\\mathbf{MoS}_{2}$ on the glassy carbon electrode, showing the high coverage and well maintained morphology after transfer. (G) Raman intensity map at 380 $\\mathsf{c m}^{-1}$ and (H) PL intensity map at $680\\ \\mathrm{nm}$ of the $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ triangle in inset of (G) show high quality of the $\\mathbf{MoS}_{2}$ transferred onto glassy carbon electrode. \n\n![](images/7b0a52c02e5e4e6d41eb7de4250f0544fb2ef217279658fd2c6e92eb9b3e63a1.jpg) \nFigure 2. Morphology and structure characterization of CVD grown $\\ensuremath{\\mathbf{MoS}}_{2}$ with oxygen plasma treatment. SEM images $\\left(\\mathrm{A-D}\\right)$ show morphology of monolayer $\\mathbf{MoS}_{2}$ with 0, 10, 20, and $30~\\mathrm{s}$ oxygen plasma exposure, where the cracks appear in the basal plane. Both the density and width of the cracks increase with longer exposure time. STEM images (E,F) show the fresh edges inside the monolayer created by the oxygen plasma. Both Mo and $S_{2}$ terminated edges are found at these exposed edges in $\\mathrm{MoS}_{2},$ with $120^{\\circ}$ angle. (G) Raman and (H) PL spectra show the decreased intensity and shifted peaks after oxygen plasma exposure. \n\nSimilar to our previous study, the $\\mathbf{MoS}_{2}$ atomic layers are synthesized via CVD method, as shown in Figure S1.32 The CVD grown $\\mathbf{MoS}_{2}$ has a well-defined triangular shape with $10-$ $100~\\mu\\mathrm{{m}}$ in length, as shown in the scanning electron microscopy (SEM) image and the optical microscopy image in Figure 1A,B, respectively. The atomic force microscopy (AFM) image in Figure 1C shows the thickness of $\\mathbf{MoS}_{2}$ is about $0.7~\\mathrm{{nm}}$ , illustrating the CVD grown $\\mathbf{MoS}_{2}$ is dominantly monolayer. Aberration-corrected scanning transmission electron microscopy (STEM) imaging was used to study the crystal quality of the transferred $\\mathbf{MoS}_{2}$ on a TEM grid. As shown in Figure 1D, the perfect hexagonal packing of single layer $\\mathbf{MoS}_{2}$ is confirmed at the atomic scale by the high-angle annular dark field (HAADF) STEM image. Figure 1E shows a photo of the working electrode, where the glassy carbon electrode is removable, facilitating the transfer of monolayer $\\mathbf{MoS}_{2}$ . With the well-developed poly(methyl methacrylate) (PMMA)- assisted transfer technique, we are able to obtain a high quality monolayer $\\mathbf{MoS}_{2}$ /glassy carbon electrode for HER test by using a three-electrode cell setup in $0.5{\\bf M}$ sulfuric acid electrolyte. As shown in Figure 1F, the SEM image shows a high coverage of $\\ensuremath{\\mathbf{MoS}}_{2}$ atomic layers with well-maintained triangular shape. Clearly, the $\\mathbf{MoS}_{2}$ here is monolayer dominated with a little bit bilayer regions. Raman and $\\mathrm{PL}$ techniques are effective for characterization of the crystal quality of 2D material. As shown in the inset of Figure 1G, part of a $\\mathbf{MoS}_{2}$ triangle was used for Raman and PL characterization. Raman intensity map (Figure 1G) showing a uniform color distribution at the intensity of $380~\\mathrm{cm}^{-1}$ together with the uniform PL intensity map at 680 nm suggests a high homogeneity of CVD grown $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ after transfer. The above results demonstrate the nondestructive nature of the transfer process of $\\mathbf{MoS}_{2}$ . \n\nBecause of the existence of intrinsic structural defects in monolayer $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ synthesized through CVD method, there are opportunities to change the properties of $\\mathbf{MoS}_{2}$ by further tailoring the defects.33 Because the active sites of $\\ensuremath{\\mathbf{MoS}}_{2}$ are located at the edges while the basal plane is inert, introduction of defects to create active sites in basal plane is an effective way to improve the catalyst activity. \n\nOxygen plasma exposure has already been demonstrated as an effective technique to introduce defects to engineer the bandgap and PL intensity of monolayer $\\mathbf{MoS}_{2}$ .34−37 We applied the same technique to introduce defects in $\\mathbf{MoS}_{2}$ in order to study the change of the catalytic activity. CVD grown $\\mathbf{MoS}_{2}$ monolayers with high crystal quality and continuous basal plane were selected to be treated with oxygen plasma exposure, as shown in Figure 2A. Samples were exposed to oxygen plasma for 10, 20, and $^{30\\ s,}$ and the corresponding morphologies are shown in Figure $2\\mathrm{B-D},$ , respectively. After $10\\mathrm{~}s$ of oxygen plasma exposure (Figure 2B), short and isolated cracks were observed on the continuous basal plane. Angles of those connected cracks are around $120^{\\circ}$ . After $20~\\mathsf{s}$ of oxygen plasma exposure (Figure 2C), cracks became longer and were connected to each other forming continuous network. Further extending the exposure time to $30\\mathrm{s},$ the $\\mathbf{MoS}_{2}$ was decomposed into even smaller fragments with more exposed edges. The widths of cracks were further enlarged, and most of angles between the interconnected cracks were $120^{\\circ}$ , as shown in Figure 2D. Unfortunately, due to the numerous cracks after 30 s plasma exposure, transferring the sample for further morphology and electrochemical performance testing becomes extremely difficult. To identify the atomic scale structure at cracks, STEM-HAADF images of the sample with $20~\\mathsf{s}$ plasma exposure are shown in Figure 2E,F. Mo and $S_{2}$ columns can be directly identified based on their image intensity, where the bright and dark columns correspond to Mo and $\\mathbf{\\boldsymbol{S}}_{2},$ respectively. Both exposed Mo and $S_{2}$ terminated edges are found at the edges of $\\mathbf{MoS}_{2}$ (Figure 2F) and their angle is about $120^{\\circ}$ . \n\nRaman and PL spectra further illustrate the structure changes of CVD grown $\\mathbf{MoS}_{2}$ after plasma exposure. As shown in Figure 2G, the intensity of both $\\mathrm{A_{lg}}$ and $\\mathbf{E}_{2\\mathbf{g}}^{1^{-}}$ modes in Raman spectra shows a significant decrease compared to the initial monolayer $\\mathbf{MoS}_{2}$ . Furthermore, from the fresh CVD grown monolayer $\\mathbf{MoS}_{2}$ to $\\mathbf{MoS}_{2}$ with 10 and $20\\mathrm{~s~}$ plasma exposure, the peak position shifts from 383.57 to 381.62 and $38\\bar{0}.14~\\mathrm{{cm}^{-1}}$ for $\\mathrm{A_{lg}}$ mode (the out-of-plane optical vibration mode of S atoms), and from 405.85 to 407.56 and $409.26~\\mathrm{cm}^{-1}$ for $\\mathbf{E}_{2\\mathrm{g}}^{1}$ mode (the inplane optical vibration mode of $_{\\mathrm{Mo}-S}$ bond) (Figure S3). Overall, the position of $\\mathbf{A}_{\\mathrm{lg}}$ mode blue shifts about $3.43~\\mathrm{cm}^{-1}$ , while $\\mathbf{E}_{2\\mathrm{g}}^{1}$ mode red shifts about $3.41~\\mathrm{{cm}^{-1}}$ . These Raman spectra confirm the lattice distortion caused by oxygen plasma.35 In addition, the appearance of a new peak at 285 $\\bar{\\mathsf{c m}}^{-1}$ indicates the formation of $_{\\mathrm{Mo-O}}$ bonds after the oxygen bombardment.37 Furthermore, intensity of the PL peak (680 nm) also decreases while increasing the plasma exposure time, as shown in Figure 2H. Thus, the decrease of PL intensity further suggests that more defects and cracks were formed with the bombardment of oxygen.38,35,39 Overall, by increasing the exposure time, the changes of the Raman and PL spectra suggest that oxygen plasma can lower the $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ crystal symmetry and increase the lattice distortion, which can be attributed to the defects that may benefit $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ as electrochemical catalyst.36 XPS (Figure S4) is further used to confirm the formation of $_{\\mathrm{Mo-O}}$ bonds in the $\\mathbf{MoS}_{2}$ sample after $\\mathrm{O}_{2}$ plasma exposure. Although there is $_{\\mathrm{Mo-O}}$ bonding in the $\\mathrm{O}_{2}$ plasma treated sample, the newly formed edges (Figure 2F) are either S or Mo terminated edges, the same as the one in the pristine layer. This suggests that the $_{\\mathrm{Mo-O}}$ bonding is from the byproduct $\\mathbf{MoO}_{3}$ rather than in the edge of $\\mathbf{MoS}_{2}$ . $\\mathbf{MoO}_{3}$ is soluble in acid so that it will not play a role in HER. \n\nIn order to understand the effects of defects on the properties of $\\mathrm{Mo}S_{2},$ electrochemical activity of $\\ensuremath{\\mathbf{MoS}}_{2}$ monolayer before and after plasma treatment was explored for HER. The HER results of the same $\\mathbf{MoS}_{2}$ sample with oxygen plasma exposure time of 0, 10, and $20~\\mathsf{s}$ are shown in Figure 3A. The linear sweep voltammograms (LSV) were taken at $\\ensuremath{5}\\ensuremath{\\mathrm{mV}/\\ensuremath{\\mathrm{s}}}$ . The sample exposed for $20~\\mathsf{s}$ shows the smallest onset overpotential. This is expected due to the largest amount of electrochemically active sites for $\\mathbf{MoS}_{2}$ with $20~\\mathsf{s}$ plasma exposure. Furthermore, after the correction of the $j{-}V$ curve for iR losses through $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ itself the enhancement of HER activity shows a strong dependency on the duration of plasma exposure. Here, we used the surface area of the carbon electrode to estimate the current density. Twenty seconds of plasma exposed $\\mathbf{MoS}_{2}$ exhibits a significantly decreased Tafel slope of approximately $171\\ \\mathrm{mV}/$ decade, which matches well with its structure (Figure 3B). As we mentioned earlier, although $30\\mathrm{~s~}$ plasma exposed sample has wider and more cracks than 20 and 10 s plasma exposed sample, its instability during the transfer prevents it from further electrochemical characterization. This study reveals that oxygen plasma exposure can effectively introduce defects in the basal plane of monolayer $\\mathbf{MoS}_{2}$ that is beneficial for HER. We further correlated the edge length with the HER activity. As shown in Figure S5, the current density increases linearly with edge length, consistent with references.20 The relatively low HER activities of the defect engineered monolayer $\\ensuremath{\\mathbf{MoS}}_{2}$ are caused by its limited amount, which is about 4 orders of magnitude less than the amount used in literatures.24−26 \n\n![](images/33e462e9f6167154d61396f7d2424b08f106d6aefb8a27b7dc14e72e7570ed55.jpg) \nFigure 3. HER properties of $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ before and after oxygen plasma treatment. (A) LSV curves show the cathodic sweep of the first cycle. Enhanced activity is observed after oxygen plasma treatment. (B) Tafel plots show the improved electrochemical activity of the monolayer $\\ensuremath{\\mathbf{MoS}}_{2}$ catalyst with oxygen plasma treatment. \n\n![](images/3c351432181be36a30cf6b12cb55938ba367e8e28588d2b3fef029c7a3bff863.jpg) \nFigure 4. Structure characterization of CVD grown $\\mathbf{MoS}_{2}$ with hydrogen treatment at different temperatures. (A−D) SEM images of monolayer $\\mathrm{Mo}{\\cal S}_{2}$ with 400, 500, 600, and $700\\ ^{\\circ}\\mathrm{C}\\ \\mathrm{H}_{2}$ annealing, respectively, showing the appearance of small triangle holes. STEM images (E,F) show highdensity nanometer-scale holes formed inside the $\\ensuremath{\\mathbf{MoS}}_{2}$ layers with abundant exposed edges and step-edges. (G) Raman and (H) PL spectra show the decreased intensity after hydrogen annealing caused by the defects as revealed by SEM and STEM. \n\n![](images/fd6ebf621743eede877a5fd33308a1ca09a7ad60f2268912be97e676914718ec.jpg) \nFigure 5. HER property characterization of CVD grown $\\mathbf{MoS}_{2}$ with hydrogen annealing at different temperatures. (A) LSV figure shows that $\\mathbf{MoS}_{2}$ under $500~^{\\circ}\\mathrm{C}$ hydrogen annealing has better catalytic activity than 400 and $600~^{\\circ}\\mathrm{C}.$ (B) Tafel plots show hydrogen-annealed $\\ensuremath{\\mathbf{MoS}}_{2}$ has lower Tafel slope than $\\mathbf{MoS}_{2}$ without any treatment, revealing improved electrochemical activity of $\\mathbf{MoS}_{2}$ as a HER catalyst after hydrogen annealing. \n\nIn addition to oxygen plasma exposure, hydrogen annealing is also an effective method for defect engineering of 2D materials. Previously, hydrogen annealing has been used to create simple hexagonal holes or complex fractal geometric patterns in graphene, which can even form graphene nanoribbons for electronic usage.40−42 Here, the similar strategy was used to etch $\\mathbf{MoS}_{2}$ in order to expose more active sites in the basal plane of $\\mathbf{MoS}_{2}$ and to improve its catalytic activity.43 A series of SEM images of $\\mathrm{H}_{2}$ etched CVD grown $\\ensuremath{\\mathbf{MoS}}_{2}$ are shown in Figure 4A−D. When the annealing temperature was $400~^{\\circ}\\mathrm{C},$ no significant changes were observed on the $\\mathbf{MoS}_{2}$ triangles (Figure 4A). As the temperature increased to $500^{\\circ}\\mathrm{C},$ the triangles start to be etched and small triangular holes with size around $1{-}4~\\mu\\mathrm{m}$ appear. These phenomena are analogous to the morphology change of graphene when graphene was treated by hydrogen annealing with different $\\mathrm{Ar/H}_{2}$ flow rate ration. When temperature further increased to $600~^{\\circ}\\mathrm{C},$ , highdensity triangular-shaped holes became the prominent part in the original monolayer $\\mathbf{MoS}_{2}$ film, while $700~^{\\circ}\\mathrm{C}$ led to more severe sample decomposition and mass loss (Figure 4D).40 This can be explained by the decomposition of $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ when the temperature is higher than 500 °C at hydrogen atmosphere.43 Compared to defects induced by oxygen plasma, the triangular holes created by hydrogen anneal is not that uniform. Besides the microscale images observed by SEM, STEM was further used to image the morphology change of $\\ensuremath{\\mathbf{MoS}}_{2}$ at atomic level. Figure $^\\mathrm{4E,F}$ shows STEM-HAADF images of the basal plane of $\\mathbf{MoS}_{2}$ sample annealed at $500~^{\\circ}\\mathrm{C}$ High-density holes with size around $10{-}20\\ \\mathrm{nm}$ are omnipresent in the basal plane. This indicates that hydrogen annealing is an effective way to form edge enriched $\\mathbf{MoS}_{2}$ that would benefit its electrochemical performance. Similar to the oxygen plasma treatment, the decrease of the peak intensity in Raman and PL spectra is also observed here, which can further support the conclusion that hydrogen annealing could increase the defects and edges in monolayer $\\mathbf{MoS}_{2}$ . \n\nThe corresponding HER performance of $\\mathbf{MoS}_{2}$ samples with hydrogen annealing was also evaluated. The LSV measurements were taken for $\\mathbf{MoS}_{2}$ with hydrogen annealing temperature of 400, 500, and $600~^{\\circ}\\mathrm{C},$ respectively. By comparison with the fresh $\\mathbf{MoS}_{2}$ without hydrogen annealing, samples under hydrogen treatment has an obviously decreased onset overpotential and increased current density, which is shown in Figure 5A. It is noteworthy that $\\mathbf{MoS}_{2}$ annealed under $500~^{\\circ}\\mathrm{C}$ has the lowest onset overpotential $(\\sim300~\\mathrm{\\mV})$ and largest current density compared to the $400~^{\\circ}\\mathrm{C}$ $\\left({\\sim}470~\\mathrm{mV}\\right)$ and 600 $^{\\circ}\\mathrm{C}$ $\\left({\\sim}450\\ \\mathrm{mV}\\right)$ . All the $\\mathrm{H}_{2}$ annealed $\\mathbf{MoS}_{2}$ samples exhibit similar Tafel slopes, which are much lower than the pristine one (Figure 5B). These results match well with structure and morphology revealed in Figure 4 that HER performance increases with more defects. Because of the formation of large amounts of macro- and microsize triangle holes at the basal plane of $\\mathbf{MoS}_{2}$ annealed at $500~^{\\circ}\\mathrm{C},$ numerous active sites that benefit HER have been created. On the other hand, $400~^{\\circ}\\mathrm{C}$ may not be high enough to etch enough $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ to expose as many active sites as ${\\mathsf{500}}^{\\circ}\\mathrm{C}$ (Figure 4A). Meanwhile, a temperature of $600~^{\\circ}\\mathrm{C}$ is so high that most of the $\\mathbf{MoS}_{2}$ monolayer is decomposed (Figure 4C) and also the left $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ is not stable because of too many defects. These results indicate that $500~^{\\circ}\\mathrm{C}$ is an optimal hydrogen annealing temperature to balance the number of active sites and the amount of $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ left, thus showing the best HER activity. \n\nBoth oxygen plasma exposure and hydrogen annealing methods have been shown as effective strategies to expose more active sites and thus improve the catalytic property of $\\mathbf{MoS}_{2}$ . Large number of cracks with certain angles was created in $\\mathbf{MoS}_{2}$ monolayer by oxygen plasma treatment, while numerous micrometer and nanometer-scale triangular holes were formed by hydrogen annealing. For both of them, we found the formation of exposed edges is dominated. SEM images (Figures 2B and 4B) show cracks with irregular shapes are predominately formed by oxygen plasma while triangular holes are created in hydrogen annealing, respectively. Highresolution STEM images further reveal that there are small irregular holes along with the large triangular holes in the hydrogen annealed samples. The irregular shape of the cracks and holes indicates both Mo-terminated and S-terminated open edges substantially increase. Figure S6 shows high-resolution STEM images showing the comparison of the edge structures in the samples formed from the two different treatments. We also found a slight increase of sulfur vacancies in the basal plane, as shown by an atom-by-atom intensity quantification analysis in Figure S7, which may also play a role in the enhanced HER activity.44 The reason why exposed edges are dominated is that because the ideal basal plane of pristine $\\mathbf{MoS}_{2}$ is chemically inert most defects are evolved from the intrinsic sulfur vacancies. The oxygen plasma and hydrogen annealing are easier to form large cracks and holes from these reactive intrinsic vacancies rather than react with the basal plane to create new sulfur vacancies. It has been shown that the open edges in $\\mathbf{MoS}_{2}$ are very reactive in HER reactions. Thus, we believe the enhanced HER activity is mainly attributed to the increase of the exposed edges. The defects density can be easily controlled by either the exposure time or anneal temperature. Because the HER activity of 2H $\\mathbf{MoS}_{2}$ is mainly contributed by exposed edges, hydrogen annealing, which can create more edges, is more effective for improving the catalytic performance of $\\mathbf{MoS}_{2}$ than oxygen plasma exposure (Figure S8). Furthermore, we tested the stability of the resultant defective samples, which is stable after 30 days in air (Figure S9) or after 10 000 cycles in HER test (Figure S10). \n\nIn conclusion, by engineering the defects in the large-scale monolayer $\\mathbf{MoS}_{2}$ through oxygen plasma exposure and hydrogen annealing, the HER catalytic activities including the onset potential, current density, and Tafel slope can be improved effectively. More importantly, the correlation between the microscale structure changes of $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ monolayer and its macroscopic properties of HER was built for the first time utilizing an ideal observation system, $\\ensuremath{\\mathbf{MoS}}_{2}$ monolayer. Our work provides new insight of fundamental catalyst mechanism of $\\mathbf{MoS}_{2}$ . The methods developed here to introduce defects in monolayer $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ could be further applied to other forms of $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ to further improve their catalytic activities. Also, the defects created by oxygen plasma and hydrogen annealing may introduce more interesting properties, including electronics, optics, and magnetics, in monolayer $\\mathbf{MoS}_{2}$ . \n\nExperimental Section. Growth of Monolayer $M o S_{2}$ by CVD Method. CVD method has been used to synthesis monolayer $\\mathbf{MoS}_{2}$ . Sulfur (S) $(99.5\\%)$ Sigma-Aldrich) powder and molybdenum oxide $\\left(\\mathrm{MoO}_{3}\\right)$ $(99\\%$ , Sigma-Aldrich) powder were used as the S and Mo precursor, respectively. Fifty sccm argon (Ar) was used as the carrier gas during growth. The growth substrate was $\\mathrm{SiO}_{2}/\\mathrm{Si}$ wafer, which was placed face down to boat with $\\mathbf{MoO}_{3}$ powder. The boat was located at the center of the fused quartz tube. The boat with S powder was put upstream at the low-temperature zone. The furnace temperature was raised up to $750~^{\\circ}\\mathrm{C}$ in $15\\ \\mathrm{min}$ and kept stable at $750~^{\\circ}\\mathrm{C}$ for $20~\\mathrm{min}$ . After growth, the furnace was left to cool down naturally. \n\nTransfer of CVD Grown $M o S_{2}$ to Glassy Carbon for Electrochemical Characterization. The electrochemical sample was prepared through a PMMA-assisted transfer method. The $\\mathrm{MoS}_{2}/\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate was first spin-coated by a PMMA thin film. Then, 2 M KOH solution was used as the etchant to etch away the $\\mathrm{SiO}_{2}$ layer. After that, the PMMA/ $\\mathrm{\\Delta}\\mathrm{MoS}_{2}$ layer was lift off and then transferred onto a clean glassy carbon electrode. Finally, the sample was air-dried and the PMMA was washed off with acetone and 2-propanol. In our experiment, all the transfers were made after the oxygen treatment and hydrogen annealing. Thus, there is no issue from the oxidation of reduction of the carbon electrode. \n\nOxygen Plasma Treatment to the CVD Grown $M o S_{2}.$ The oxygen plasma treatment was carried out by using a SuperPlasmod 300 system with a 300 W power supply. The samples were exposed at chamber pressure of 10Torr with oxygen gas. \n\nHydrogen Annealing to the CVD Grown $M o S_{2}.$ . In hydrogen annealing experiment, high quality $\\mathbf{MoS}_{2}$ with similar size and coverage on the $\\mathrm{Si}/\\mathrm{SiO}_{2}$ was selected to be etched by $\\mathrm{H}_{2}$ . The selected $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ was put in the center of the fused quartz tube, and a gas mixture of hydrogen $(15\\%)$ and argon $(85\\%)$ flowed at a constant rate of 50 sccm. For temperaturedependent hydrogen annealing, the samples were treated at 500, 600, and $700^{\\circ}\\mathrm{C},$ respectively. The duration of each annealing was $30~\\mathrm{min}$ . \n\nElectrochemical Characterization. The electrochemical testing took place at a three-electrode electrochemical cell. Platinum was used as a counter electrode, $\\mathrm{\\sfAg/AgCl}$ was used as a reference electrode, and a glassy carbon disk that was covered by $\\mathbf{MoS}_{2}$ film was used as a working electrode. All tests were carried out in $100{-}150~\\mathrm{\\mL}$ of $0.5\\mathrm{~M~}$ sulfuric acid $\\left(\\mathrm{H}_{2}\\mathrm{SO}_{4}\\right)$ \n\nelectrolyte. The potential applied was 0 to $-0.6\\mathrm{~V~}$ and the sweep rate was $\\ensuremath{\\boldsymbol{{\\ s}}}\\mathrm{mV}/\\ensuremath{\\boldsymbol{s}}$ . \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.5b04331. \n\nAdditional information regarding growth schematics, HER performance within different $\\mathbf{MoS}_{2}$ morphology, Raman shift of CVD grown $\\mathbf{MoS}_{2}$ under oxygen plasma treatment, and electrochemical performance comparison between oxygen plasma exposure and hydrogen annealing to CVD grown $\\mathbf{MoS}_{2}$ . (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\n$^{*}\\mathrm{E}$ -mail: Yongji.Gong@rice.edu. \n\\*E-mail: Robert.Vajtai@rice.edu. \n\\*E-mail: ajayan@rice.edu. \n\n# Author Contributions \n\nG.Y. and Y.G. worked on the growth and electrochemical testing. B.L. worked on the AFM characterization. Y.H. worked on the oxygen treatment. W.Z., J.L., and S.T.P. carried out STEM experiments. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Army Research Office MURI Grant W911NF-11-1-0362 and the FAME Center, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA. This research was supported in part by U.S. DOE Grant DE-FG02- 09ER46554 (J.L. and S.T.P.), by the U.S. Department of Energy, Office of Science, Basic Energy Science, Materials Sciences and Engineering Division (W.Z.), and through a user project at ORNL’s Center for Nanophase Materials Sciences (CNMS), which is a DOE Office of Science User Facility. \n\n# REFERENCES \n\n(1) Chu, S.; Majumdar, A. Nature 2012, 488, 294−303. (2) Hertwich, E. G.; Gibon, T.; Bouman, E. A.; Arvesen, A.; Suh, S.; \nHeath, G. A.; Bergesen, J. D.; Ramirez, A.; Vega, M. I.; Shi, L. Proc. \nNatl. Acad. Sci. U. S. A. 2015, 112, 6277−6282. \n(3) Lewis, N. S.; Nocera, D. G. Proc. Natl. Acad. Sci. U. S. A. 2006, \n103, 15729−15735. \n(4) Hinnemann, B.; Moses, P. G.; Bonde, J.; Jørgensen, K. P.; \nNielsen, J. H.; Horch, S.; Chorkendorff, I.; Nørskov, J. K. J. Am. Chem. \nSoc. 2005, 127, 5308−5309. \n(5) Walter, M. G.; Warren, E. L.; McKone, J. R.; Boettcher, S. W.; Mi, \nQ.; Santori, E. A.; Lewis, N. S. Chem. Rev. 2010, 110, 6446−6473. (6) Stolley, R. M.; Helm, M. L. Nat. Chem. 2014, 6, 949−950. (7) Panwar, N. L.; Kaushik, S. C.; Kothari, S. Renewable Sustainable \nEnergy Rev. 2011, 15, 1513−1524. (8) Benck, J. D.; Hellstern, T. R.; Kibsgaard, J.; Chakthranont, P.; \nJaramillo, T. F. ACS Catal. 2014, 4, 3957−3971. \n(9) Yan, Y.; Xia, B.; Xu, Z.; Wang, X. ACS Catal. 2014, 4, 1693− \n1705. \n(10) Kibler, L. A. ChemPhysChem 2006, 7, 985−991. (11) Greeley, J.; Jaramillo, T. F.; Bonde, J.; Chorkendorff, I. B.; Nørskov, J. K. Nat. Mater. 2006, 5, 909−913. \n(12) Greeley, J.; Stephens, I. E. L.; Bondarenko, A. S.; Johansson, T. P.; Hansen, H. A.; Jaramillo, T. F.; Rossmeisl, J.; Chorkendorff, I.; Nørskov, J. K. Nat. Chem. 2009, 1, 552−556. \n(13) Rapoport, L.; Fleischer, N.; Tenne, R. J. Mater. Chem. 2005, 15, 1782. \n(14) Lin, Y.-C.; Dumcenco, D. O.; Huang, Y.-S.; Suenaga, K. Nat. Nanotechnol. 2014, 9, 391−396. \n(15) Tributsch, H.; Bennett, J. C. J. Electroanal. Chem. Interfacial Electrochem. 1977, 81, 97−111. \n(16) Voiry, D.; Salehi, M.; Silva, R.; Fujita, T.; Chen, M.; Asefa, T.; Shenoy, V. B.; Eda, G.; Chhowalla, M. Nano Lett. 2013, 13, 6222− 6227. \n(17) Laursen, A. B.; Kegnæs, S.; Dahl, S.; Chorkendorff, I. Energy Environ. Sci. 2012, 5, 5577. \n(18) Tsai, C.; Abild-Pedersen, F.; Nørskov, J. K. Nano Lett. 2014, 14, 1381−1387. \n(19) Wang, H.; Lu, Z.; Kong, D.; Sun, J.; Hymel, T. M.; Cui, Y. ACS Nano 2014, 8, 4940−4947. \n(20) Jaramillo, T. F.; Jørgensen, K. P.; Bonde, J.; Nielsen, J. H.; Horch, S.; Chorkendorff, I. Science 2007, 317, 100−102. \n(21) Raybaud, P.; Hafner, J.; Kresse, G.; Kasztelan, S.; Toulhoat, H. J. Catal. 2000, 189, 129−146. \n(22) Shi, J.; Ma, D.; Han, G.-F.; Zhang, Y.; Ji, $\\mathrm{Q.;}$ Gao, T.; Sun, J.; Song, X.; Li, C.; Zhang, Y.; Lang, X.-Y.; Zhang, Y.; Liu, Z. ACS Nano 2014, 8, 10196−10204. \n(23) Saadi, F. H.; Carim, A. I.; Velazquez, J. M.; Baricuatro, J. H.; McCrory; Charles, C. L.; Soriaga, M. P.; Lewis, N. S. ACS Catal. 2014, 4, 2866−2873. \n(24) Wang, H.; Lu, Z.; Xu, S.; Kong, D.; Cha, J. J.; Zheng, G.; Hsu, P.-C.; Yan, K.; Bradshaw, D.; Prinz, F. B.; Cui, Y. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 19701−19706. \n(25) Kibsgaard, J.; Chen, Z.; Reinecke, B. N.; Jaramillo, T. F. Nat. Mater. 2012, 11, 963−969. \n(26) Voiry, D.; Yamaguchi, H.; Li, J.; Silva, R.; Alves; Diego, C. B.; Fujita, T.; Chen, M.; Asefa, T.; Shenoy, V. B.; Eda, G.; Chhowalla, M. Nat. Mater. 2013, 12, 850−855. \n(27) Benck, J. D.; Chen, Z.; Kuritzky, L. Y.; Forman, A. J.; Jaramillo, T. F. ACS Catal. 2012, 2, 1916−1923. \n(28) Gopalakrishnan, D.; Damien, D.; Shaijumon, M. M. ACS Nano 2014, 8, 5297−5303. \n(29) Chang, K.; Mei, Z.; Wang, T.; Kang, Q.; Ouyang, S.; Ye, J. ACS Nano 2014, 8, 7078−7087. \n(30) Kibsgaard, J.; Jaramillo, T. F.; Besenbacher, F. Nat. Chem. 2014, 6, 248−253. \n(31) Xie, J.; Zhang, H.; Li, S.; Wang, R.; Sun, X.; Zhou, M.; Zhou, J.; Lou, Xiong Wen David; Xie, Y. Adv. Mater. 2013, 25, 5807−5813. (32) Gong, Y.; Lin, J.; Wang, X.; Shi, G.; Lei, S.; Lin, Z.; Zou, X.; Ye, G.; Vajtai, R.; Yakobson, B. I.; Terrones, H.; Terrones, M.; Tay, B. K.; Lou, J.; Pantelides, S. T.; Liu, Z.; Zhou, W.; Ajayan, P. M. Nat. Mater. 2014, 13, 1135−1142. \n(33) Zhou, W.; Zou, X.; Najmaei, S.; Liu, Z.; Shi, Y.; Kong, J.; Lou, J.; Ajayan, P. M.; Yakobson, B. I.; Idrobo, J.-C. Nano Lett. 2013, 13, 2615−2622. \n(34) Azizi, A.; Zou, X.; Ercius, P.; Zhang, Z.; Elías, A. L.; PereaLópez, N.; Stone, G.; Terrones, M.; Yakobson, B. I.; Alem, N. Nat. Commun. 2014, 5, 4867. \n(35) Kang, N.; Paudel, H. P.; Leuenberger, M. N.; Tetard, L.; Khondaker, S. I. J. Phys. Chem. C 2014, 118, 21258−21263. \n(36) Mouri, S.; Miyauchi, Y.; Matsuda, K. Nano Lett. 2013, 13, 5944−5948. \n(37) Nan, H.; Wang, Z.; Wang, W.; Liang, Z.; Lu, Y.; Chen, $\\mathrm{Q.;}$ He, D.; Tan, P.; Miao, F.; Wang, X.; Wang, J.; Ni, Z. ACS Nano 2014, 8, 5738−5745. \n(38) Islam, M. R.; Kang, N.; Bhanu, U.; Paudel, H. P.; Erementchouk, M.; Tetard, L.; Leuenberger, M. N.; Khondaker, S. I. Nanoscale 2014, 6, 10033−10039. (39) Yang, J.; Kim, S.; Choi, W.; Park, S. H.; Jung, Y.; Cho, M.-H.; Kim, H. ACS Appl. Mater. Interfaces 2013, 5, 4739−4744. \n(40) Geng, D.; Wu, B.; Guo, Y.; Luo, B.; Xue, Y.; Chen, J.; Yu, G.; Liu, Y. J. Am. Chem. Soc. 2013, 135, 6431−6434. \n(41) Jin, Y.; Hu, B.; Wei, Z.; Luo, Z.; Wei, D.; Xi, Y.; Zhang, Y.; Liu, Y. J. Mater. Chem. A 2014, 2, 16208−16216. \n(42) Zhang, Y.; Li, Z.; Kim, P.; Zhang, L.; Zhou, C. ACS Nano 2012, 6, 126−132. \n(43) Liu, K.-K.; Zhang, W.; Lee, Y.-H.; Lin, Y.-C.; Chang, M.-T.; Su, C.-Y.; Chang, C.-S.; Li, H.; Shi, Y.; Zhang, H.; Lai, C.-S.; Li, L.-J. Nano Lett. 2012, 12, 1538−1544. \n(44) Xie, J.; Zhang, J.; Li, S.; Grote, F.; Zhang, X.; Zhang, H.; Wang, R.; Lei, Y.; Pan, B.; Xie, Y. J. Am. Chem. Soc. 2013, 135, 17881−17888. " + }, + { + "id": "10.1038_ncomms11755", + "DOI": "10.1038/ncomms11755", + "DOI Link": "http://dx.doi.org/10.1038/ncomms11755", + "Relative Dir Path": "mds/10.1038_ncomms11755", + "Article Title": "Electron-phonon coupling in hybrid lead halide perovskites", + "Authors": "Wright, AD; Verdi, C; Milot, RL; Eperon, GE; Pérez-Osorio, MA; Snaith, HJ; Giustino, F; Johnston, MB; Herz, LM", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Phonon scattering limits charge-carrier mobilities and governs emission line broadening in hybrid metal halide perovskites. Establishing how charge carriers interact with phonons in these materials is therefore essential for the development of high-efficiency perovskite photovoltaics and low-cost lasers. Here we investigate the temperature dependence of emission line broadening in the four commonly studied formamidinium and methylammonium perovskites, HC(NH2)(2)PbI3, HC(NH2)(2)PbBr3, CH3NH3PbI3 and CH3NH3PbBr3, and discover that scattering from longitudinal optical phonons via the Frohlich interaction is the dominullt source of electron-phonon coupling near room temperature, with scattering off acoustic phonons negligible. We determine energies for the interacting longitudinal optical phonon modes to be 11.5 and 15.3 meV, and Frohlich coupling constants of similar to 40 and 60 meV for the lead iodide and bromide perovskites, respectively. Our findings correlate well with first-principles calculations based on many-body perturbation theory, which underlines the suitability of an electronic band-structure picture for describing charge carriers in hybrid perovskites.", + "Times Cited, WoS Core": 1065, + "Times Cited, All Databases": 1128, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000376674500001", + "Markdown": "# Electron–phonon coupling in hybrid lead halide perovskites \n\nAdam D. Wright1, Carla Verdi2, Rebecca L. Milot1, Giles E. Eperon1, Miguel A. P´erez-Osorio2, Henry J. Snaith1, Feliciano Giustino2, Michael B. Johnston1 & Laura M. Herz1 \n\nPhonon scattering limits charge-carrier mobilities and governs emission line broadening in hybrid metal halide perovskites. Establishing how charge carriers interact with phonons in these materials is therefore essential for the development of high-efficiency perovskite photovoltaics and low-cost lasers. Here we investigate the temperature dependence of emission line broadening in the four commonly studied formamidinium and methylammonium perovskites, $\\mathsf{H C(N H_{2})_{2}P b l_{3}},\\mathsf{H C(N H_{2})_{2}P b B r_{3}},\\mathsf{C H_{3}N H_{3}P b l_{3}}$ and ${\\mathsf{C H}}_{3}{\\mathsf{N H}}_{3}{\\mathsf{P b B r}}_{3},$ and discover that scattering from longitudinal optical phonons via the Fro¨hlich interaction is the dominant source of electron–phonon coupling near room temperature, with scattering off acoustic phonons negligible. We determine energies for the interacting longitudinal optical phonon modes to be 11.5 and $15.3\\mathsf{m e V},$ and Fr¨ohlich coupling constants of $\\sim40$ and 60 meV for the lead iodide and bromide perovskites, respectively. Our findings correlate well with first-principles calculations based on many-body perturbation theory, which underlines the suitability of an electronic band-structure picture for describing charge carriers in hybrid perovskites. \n\nybrid lead halide perovskites have attracted intense research activity following their first implementation as light absorbers in thin-film solar cells1 that now reach power conversion efficiencies (PCEs) in excess of $20\\%$ (refs 2,3). These compounds are described by the general formula $\\mathrm{ABX}_{3}$ where A is typically an organic cation such as methylammonium $\\mathrm{(CH_{3}N H_{3}^{+}}$ or $\\mathrm{MA}^{+}$ ) or formamidinium $(\\mathrm{HC}(\\mathrm{NH}_{2})_{2}^{+}$ or $\\mathrm{FA}^{+}$ ), B is a divalent metal cation (usually $\\mathrm{Pb}^{2+}$ ) and $\\mathrm{\\DeltaX}$ is a halide anion $(\\mathrm{I}^{-},\\ \\mathrm{Br}^{-}$ or $\\mathrm{Cl}^{-})^{4}$ . Such hybrid organic–inorganic materials straddle the divide between organic and inorganic semiconductors, facilitating photovoltaic devices that combine the low processing costs of the former with the high PCEs of the latter2,3,5. In addition, their structural flexibility allows a wide compositional parameter space to be explored. Although $\\mathrm{MAPbI}_{3}$ is the most commonly investigated perovskite, the currently most efficient perovskite solar cells replace $\\mathrm{\\all}^{2}$ or most3 of the $\\mathrm{\\DeltaMA^{+}}$ with $\\mathrm{FA}^{\\mp}$ . $\\mathrm{FAPbI}_{3}$ has the advantage of a smaller bandgap than $\\mathrm{MAPbI}_{3}$ (1.48 versus $1.57\\mathrm{eV},$ ), making it more suited for use in single-junction solar cells6, and furthermore shows greater resistance to heat stress6. High-performing devices have used formulations containing both FA and MA cations, to counteract the thermodynamic instability of $\\mathrm{FAPbI}_{3}$ in its perovskite phase at room temperature7–9. Meanwhile, mixed-halide perovskites incorporating both $\\mathrm{I}^{-}$ and $\\mathrm{Br^{-}}$ have been investigated for use in tandem solar cells5,6,10, as these systems allow for bandgap optimization across a wide tuning range. \n\nThe success of hybrid perovskites in photovoltaic applications has been widely attributed to their high absorption coefficients across the visible spectrum11, their low exciton binding energies4,12 facilitating charge formation and their long charge-carrier diffusion lengths enabling efficient charge extraction13,14. However, although much recent attention has been devoted towards unravelling the charge-carrier recombination mechanisms underlying these properties4,15, the interaction of charge carriers with lattice vibrations (phonons) is currently still a subject of intense debate16,17. Such electron–phonon interactions matter, because they set a fundamental intrinsic limit to charge-carrier mobilities in the absence of extrinsic scattering off impurities or interfaces18. In addition, charge-carrier cooling following non-resonant (above bandgap) photon absorption is governed by interactions between charges and phonons4. Slow charge-carrier cooling components (compared with GaAs) have been postulated for hybrid perovskites19, which may open the possibility for PCEs beyond the Shockley–Queisser limit. Furthermore, electron– phonon coupling has been shown to yield predominantly homogeneous emission line broadening in hybrid lead iodide perovskite at room temperature, making it suitable as a gain medium for short-pulse lasers20. \n\nDespite the importance of electron–phonon interactions to the optoelectronic properties of these materials, currently no clear picture has emerged of which mechanisms are active. To address this issue, a number of studies have examined the temperature dependence of the charge-carrier mobility m, which was found21–24 to scale with $T^{m}$ with $m$ in the range between $-1.4$ and \u0002 1.6. Several groups16,17,24 therefore proposed that electron–phonon coupling at room temperature is almost solely governed by deformation potential scattering with acoustic phonons, which is known18,25 to theoretically result in $\\mu\\propto T^{-3\\dot{7}2}$ . Although such behaviour may be adopted by non-polar inorganic semiconductors such as silicon or germanium18,26, it would be extremely unusual for perovskites that exhibit polar27,28 lead–iodide bonds. These findings have therefore raised the puzzling question of why such hybrid perovskites appear to evade the Fro¨hlich interactions between charge carriers and polar longitudinal optical (LO) phonon modes that normally govern polar inorganic semiconductors, such as GaAs18,29, at room temperature. \n\nHere we clarify the relative activity of different charge-carrier scattering mechanisms in hybrid lead halide perovskites by investigating charge-carrier scattering through an analysis of the photoluminescence (PL) linewidth as a function of temperature between 10 and $370\\mathrm{K}.$ By carefully examining the lowtemperature regime in which thermal energies fall below those of high-energy LO phonon modes, we are able to clearly separate competing contributions from charge-carrier interactions with acoustic and optical phonons. We are therefore able to show unambiguously that Fro¨hlich coupling to LO phonons is the predominant cause of linewidth broadening in these materials at room temperature, with scattering from acoustic phonons and impurities being a minor component. We further demonstrate excellent agreement between the experimentally determined temperature dependence of the PL linewidth and theoretical values derived from ab initio calculations for $\\mathbf{MAPbI}_{3}$ . To elucidate how charge-carrier–phonon interaction strengths depend on perovskite composition, we examine $\\mathrm{FAPbI}_{3}.$ $\\mathrm{FAPbBr}_{3}$ , $\\mathbf{MAPbI}_{3}$ and $\\bar{\\mathbf{MAPbBr}}_{3}$ , which represent a comprehensive set of the most commonly implemented organic and halide ingredients in hybrid perovskites. We show that although the choice of organic cation has relatively little effect on the Fro¨hlich interactions, bromide perovskites exhibit higher Fro¨hlich coupling than iodide perovskites as a result of their smaller high-frequency values of the dielectric function. Overall, our results conclusively demonstrate that electron–phonon coupling in hybrid lead halide perovskites follows a classic bandstructure picture for polar inorganic semiconductors, which are dominated by Fro¨hlich coupling between charge carriers and LO phonon modes in the high-temperature regime. \n\n# Results \n\nTemperature-dependent PL spectra. To conduct our analysis of electron–phonon coupling in hybrid lead halide perovskites, we recorded steady-state PL spectra of solution-processed $\\mathrm{FAPbI}_{3}$ , $\\mathrm{FAPbBr}_{3}$ , $\\mathbf{MAPbI}_{3}$ and $\\mathrm{MAPbBr}_{3}$ thin films over temperatures from 10 to $370\\mathrm{K}$ in increments of $5\\mathrm{K}$ (Fig. 1). The observed PL peak positions at room temperature are consistent with those reported previously for these material $\\ensuremath{6,30-33}$ . The colour plots in Fig. 1 exhibit abrupt shifts in PL peak energies at various temperatures that are associated with phase transitions commonly found in these relatively soft materials. For example, $\\mathbf{MAPbI}_{3}$ , $\\mathbf{MAPbBr}_{3}$ and $\\mathrm{FAPbI}_{3}$ have been reported to undergo a phase transition from an orthorhombic to a tetragonal structure between 130 and $160\\mathrm{K}$ (refs 30,33,34). A further phase transition to the cubic phase follows at higher temperatures for the MA perovskites (at $\\sim330\\mathrm{K}$ for $\\mathrm{MAPb}\\bar{\\mathrm{I}_{3}}$ (refs 30,34) and $240\\mathrm{K}$ for $\\mathbf{MAPbBr}_{3}$ (ref. 34)), whereas a transition to a trigonal phase occurs at around $200\\mathrm{K}$ for $\\mathrm{FAPbI}_{3}$ (ref. 30). The lower-temperature phase transition to the orthorhombic phase below $130{-}160\\mathrm{K}$ is generally associated with larger energetic shifts as it marks a strong reduction in the extent of rotational freedom of the organic cation34–36. Highertemperature structural changes are more subtle in this regard and therefore much harder to discern21. Apart from these discontinuities, the PL peak in all four materials shifts continuously towards higher energy with increasing temperature. This general trend is in contrast to that of typical semiconductors such as Si, Ge and GaAs, for which the bandgap decreases with temperature as a result of lattice dilation26,37. The atypical positive bandgap deformation potential of hybrid lead halide perovskites has been attributed to a stabilization of out-of-phase band-edge states as the lattice expands38. \n\nIn addition to these well-understood temperature trends, the PL spectra of MA-containing perovskites exhibit strong inhomogeneous broadening and multi-peak emission in the low-temperature orthorhombic phase. Such behaviour has been reported by ourselves21,3 9 and others24,31,40,41 on many occasions, yet a precise explanation is still outstanding. For example, the PL spectra of $\\bar{\\mathrm{MAPbI}_{3}}$ develop additional peaks at temperatures below $150\\mathrm{K}.$ , as can be seen clearly in Supplementary Fig. 1, which shows spectra from the colour plots in Fig. 1 at selected temperatures. The emerging consensus is that these are caused by additional charge or exciton trap states that are only active in the low-temperature orthorhombic phase21,24,31,39–41. It has been proposed that these traps could derive from a small fraction of inclusions of the room-temperature tetragonal phase that are populated through charge or exciton transfer from the majority orthorhombic phase39. These inclusions could be a result of strain or the proposed impossibility of a continuous structural transition from the tetragonal to orthorhombic phase in MA perovskites, as reported by Baikie et al.35. We further note that as these complicating features do not appear in the PL spectra of the equivalent FA perovskites, they are probably not intrinsic to hybrid lead halide perovskites, which re-affirms the prevailing view that they originate from trap states. Importantly, the lack of uncomplicated low-temperature spectra has to date prevented proper analysis of the linewidth broadening of MA perovskites and the associated phonon coupling to charge carriers. As we show below, such analysis requires access to a lowtemperature range over which PL spectra are dominated by intrinsic phonon broadening, rather than trap-related PL, for the contributions from acoustic and optical phonons to the clearly separated. Therefore, the discovery that the equivalent FA lead halide perovskites do not exhibit extrinsic defect-related PL in the low temperature range allows us to carry out such analysis unhindered. \n\n![](images/da4dee88774d24084166a1b0d67281d71a74309c0b14e872e95c703e9ebfbfd3.jpg) \nFigure 1 | Temperature dependence of steady-state PL. Colour plots of normalized steady-state photoluminescence spectra of (a) $\\mathsf{F A P b l}_{3},$ (b) $\\mathsf{F A P b B r}_{3},$ (c) $\\mathsf{M A P b l}_{3}$ and (d) $M A P b{\\mathsf{B}}{\\mathsf{r}}_{3}$ thin films at temperatures between 10 and $3701$ \n\nAnalysis of PL linewidth broadening. Analysis of temperaturedependent emission broadening has long been used to assess the mechanisms of electron–phonon coupling in a wide range of inorganic semiconductors42 (see Supplementary Table 1 for a literature overview of the results). We here apply these methods to hybrid lead halide perovskites by first extracting the full width at half-maximum (FWHM) of the PL spectra shown in Fig. 1 and then analysing its temperature dependence (plotted in Fig. 2). For most inorganic semiconductors, different mechanisms of scattering between charge carriers and phonons or impurities are associated with different functional dependencies of the PL linewidth $\\boldsymbol{{\\Gamma}}(\\boldsymbol{T})$ on temperature, which can be expressed as the sum over the various contributions42,43: \n\n$$\n\\begin{array}{r l}&{\\Gamma(T)=\\Gamma_{0}+{\\Gamma_{\\mathrm{ac}}}+{\\Gamma_{\\mathrm{LO}}}+{\\Gamma_{\\mathrm{imp}}}}\\\\ &{\\qquad={\\Gamma_{0}}+{\\gamma_{\\mathrm{ac}}}T+{\\gamma_{\\mathrm{LO}}}{N_{\\mathrm{LO}}}(T)+{\\gamma_{\\mathrm{imp}}}e^{-{E_{\\mathrm{b}}}/{k_{\\mathrm{B}}}T}.}\\end{array}\n$$ \n\nHere, $\\boldsymbol{{\\Gamma}}_{0}$ is a temperature-independent inhomogeneous broadening term, which arises from scattering due to disorder and imperfections42,44. The second and third terms ( $\\cdot T_{\\mathrm{ac}}$ and $\\ensuremath{{\\varGamma_{\\mathrm{LO}}}})$ are homogeneous broadening terms, which result from acoustic and LO phonon (Fro¨hlich) scatterin $\\underline{{28}},42,44$ with charge-carrier– phonon coupling strengths of $\\gamma_{\\mathrm{ac}}$ and $\\gamma_{\\mathrm{LO}},$ respectively. Electron– phonon coupling is in general proportional to the occupation numbers of the respective phonons, as given by the Bose–Einstein distribution function45,46, taken as $\\overset{\\smile}{N}_{\\mathrm{LO}}(T)=1/[e^{E_{\\mathrm{LO}}/k_{\\mathrm{B}}T}-1]$ for LO phonons, where $\\ensuremath{E_{\\mathrm{LO}}}$ is an energy representative of the frequency for the weakly dispersive LO phonon branch18,47. For acoustic phonons whose energy is much smaller than $k_{\\mathrm{B}}T$ over the typical observation range, a linear dependence on temperature is generally assumed46,48. $\\bar{A}b$ initio calculations of the relevant phonon energies and occupation numbers are shown in Supplementary Fig. 4, which confirms that the linear approximation to the acoustic phonon population used in equation (1) is appropriate. The final term, $T_{\\mathrm{imp}},$ phenomenologically accounts for scattering from ionized impurities with an average binding energy $\\boldsymbol{E_{\\mathrm{b}}}$ (ref. 43). These impurities contribute $\\gamma_{\\mathrm{imp}}$ of inhomogeneous broadening to the width when fully ionized43,45. \n\nIn general, the two major mechanisms governing the electron– phonon coupling in inorganic semiconductors are deformation potential scattering, in which distortions of the lattice change the electronic band structure, and electromechanical or piezoelectric interactions, in which lattice-related electric fields modify the electronic Hamiltonian18. Specifically, the LO phonon term in equation (1) accounts for the Fr¨ohlich interaction between LO phonons and electrons, which arises from the Coulomb interaction between the electrons and the macroscopic electric field induced by the out-of-phase displacements of oppositely charged atoms caused by the LO phonon mode18. Although both transverse optical and LO phonons interact with electrons via non-polar deformation potentials, equation (1) only accounts for LO phonons because of the dominant influence of their Fr¨ohlich interaction with electrons in polar crystals at higher temperatures49. As optical phonons in semiconductors typically have energies of the order of tens of meV (ref. 18), their population at low temperatures $(T{<}100\\mathrm{K})$ is very small; thus, homogeneous broadening in this regime predominantly results from acoustic phonons18,49. Therefore, careful examination of the low-temperature regime allows separation of the contributions from optical and acoustic modes. Long-wavelength acoustic phonons induce atomic displacements, which can correspond to macroscopic crystal deformation, affecting electronic energies via either the resultant deformation potential or a piezoelectrically induced electric field18. \n\n![](images/965e449ef7448546b5f239345e58cb3366353cfe23711cb1a32195d7af7c9880.jpg) \nFigure 2 | Temperature dependence of linewidth. FWHM of the steady-state PL spectra as a function of temperature for (a) $\\mathsf{F A P b l}_{3},$ (b) $\\mathsf{F A P b B r}_{3},$ (c) $\\mathsf{M A P b l}_{3}$ and (d) $M A P b\\mathsf{B r}_{3}$ thin films plotted as black dots. The solid red lines are fits of $\\begin{array}{r}{\\Gamma(\\tau)={\\cal{T}}_{0}+{\\cal{T}}_{\\lfloor0\\mathclose\\prime\\rfloor}}\\end{array}$ which account for contributions from inhomogeneous broadening and Fr¨ohlich coupling with LO phonons. For the perovskites containing MA, the fits are extrapolated into the low-temperature region in which the model does not hold, as indicated by dashed red lines (actual fits were carried out between 150 and $3701\\mathrm{K}$ for $\\mathsf{M A P b l}_{3},$ and between 100 and $3701\\mathrm{K}$ for $M A P b\\mathsf{B r}_{3})$ . The inset shows the functional form of the temperature dependence of the contributions to PL linewidth in semiconductors from inhomogeneous broadening $(\\boldsymbol{{\\cal T}}_{0},$ magenta), Fr¨ohlich coupling between charge carriers and LO phonons $(\\boldsymbol{{\\Gamma}}_{\\lfloor0\\right\\rangle}$ red) and acoustic phonons $\\cdot\\ensuremath{T_{\\mathrm{ac}}},$ blue), and scattering from ionized impurities $\\cdot_{\\varGamma_{\\mathrm{imp}\\prime}}$ green), as given by the terms of equation (1). An alternative presentation of the linewidths as a mutliple of the thermal energy is given in Supplementary Fig. 2. \n\nTo establish qualitatively which electron–phonon scattering mechanisms contribute in hybrid lead halide perovskites, we compare the temperature-dependent PL linewidth plotted in Fig. 2 with the functional form of the terms in equation (1). To aid comparison, the inset to Fig. 2a shows example functions for the separate components. First, we assess the possibility of electron scattering with ionized impurities playing a significant role. Comparison of the curves in the inset with the data in the main Fig. 2 makes it apparent that the shape of the ionized impurity scattering term $\\Gamma_{\\mathrm{imp}}$ could not produce the observed linear variation with $T$ of the linewidths at high temperatures. Therefore, we conclude that scattering with ionized impurities does not play any major role here, in agreement with findings based on recent analyses of the temperature-dependence of the charge-carrier mobility in this regime21–24. We therefore assume $T_{\\mathrm{imp}}{\\approx}0$ for the rest of the analysis. \n\nTo separate the contributions from acoustic and optical phonon modes, we first focus on an analysis of the PL linewidth for perovskites containing FA as the organic cation. As Fig. 2a,b show, these materials exhibit smooth variation of the linewidth, whereas for MA-containing perovskites the presence of the impurity emission discussed above leads to additional emission broadening in the low-temperature phase (Fig. 2c,d). Both $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FAPbBr}_{3}$ approach a PL linewidth of the order of $20\\mathrm{meV}$ towards $T=0$ , which can therefore be identified as the temperature-independent inhomogeneous broadening term $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{0}$ arising from disorder. To qualitatively assess the relative importance of acoustic versus optical phonon contributions, an inspection of the gradient of these curves in the low-temperature regime is essential. Although the optical phonon terms lead to a gradient of zero in the regime for which $E_{\\mathrm{LO}}{<}k_{\\mathrm{B}}T,$ the smaller energies of acoustic phonons should result in a non-zero gradient given by $\\gamma_{\\mathrm{ac}}$ here. However, visual inspection of the graphs in Fig. 2a,b shows that the gradient of the FWHM versus temperature approaches zero at low temperature, suggesting negligible acoustic phonon contribution $(\\gamma_{\\mathrm{ac}}\\approx0)$ . Indeed, we find that fits of equation (1) to these curves converge with $\\gamma_{\\mathrm{ac}}\\rightarrow0$ . This result is not surprising, given that in polar inorganic semiconductors the contribution of acoustic phonons to the broadening at room temperature is typically dwarfed by that of the LO phonons and indeed several studies ignore the contribution of acoustic phonons in such systems49. However, we may obtain an upper limit to $\\gamma_{\\mathrm{ac}}$ by careful examination of the data in the low-temperature regime in which acoustic phonons are still expected to contribute significantly. Here we may fit $\\begin{array}{r}{T(T)={\\cal{T}}_{0}+\\gamma_{\\mathrm{ac}}T}\\end{array}$ to the data in the low-temperature $(T{<}60\\mathrm{K})$ region50 or, as an alternative method, obtain the gradient of the data near $T=0\\mathrm{K}$ from differentiation. Both methods yield upper limits around $\\gamma_{\\mathrm{ac}}{=}60\\pm20\\upmu\\mathrm{eV}\\mathrm{K}^{-1}$ for $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FAPb}\\mathrm{Br}_{3}$ ; therefore, acoustic phonons will only contribute up to $\\sim18\\mathrm{meV}$ to the linewidth broadening at $300\\mathrm{K}$ Hence, our analysis illustrates that the majority of broadening in the roomtemperature regime arises from charge-carrier interactions with optical phonons, as would be expected for a polar semiconductor. To further quantify the dominant Fr¨ohlich coupling in these systems, we proceed by fitting all data including only the mechanisms based on temperature-independent inhomogeneous broadening and Fro¨hlich coupling to LO phonon modes. For perovskites containing FA cations, fits of $\\bar{\\Gamma(T)}={\\cal{T}}_{0}+{\\cal{T}}_{\\mathrm{LO}}$ to the PL linewidth data are plotted in Fig. 2a,b (red lines) and the extracted fitting parameters are presented in Table 1. Apart from Fr¨ohlich coupling strengths, we are also able to determine the energy of LO phonon modes that play the dominant role in electron–LO-phonon coupling. We find $E_{\\mathrm{{LO}}}=11.5\\mathrm{{meV}}$ for $\\mathrm{FAPbI}_{3}$ , with the value for $\\mathrm{FAPbBr}_{3}$ ( $15.3\\mathrm{meV})$ being 1.3 times larger, which is only slightly greater than the factor of 1.2 expected from a crude model of the frequency of a diatomic harmonic oscillator. These LO phonon energies of hybrid lead halide perovskites are somewhat lower than those typically measured for a range of inorganic semiconductors (see Supplementary Table 1 for an overview); however, they agree well with a recent combined experimental and density functional theory (DFT) study assigning LO phonon modes of the Pb-I lattice in $\\mathrm{MAPbI}_{3}$ with energies near $10\\mathrm{meV}$ (ref. 51) and with our present calculations (see next section). As noted above, the situation is more complex for MA perovskites, owing to the additional trap-related emission in the low-temperature orthorhombic phase that gives rise to sizeable $(>100\\mathrm{\\meV})$ additional broadening (see Fig. 2c,d). However, in the high-temperature regime, PL linewidths of the MA perovskites vary much in the same manner as that of their FA counterparts, suggesting very similar mechanisms. This may be expected, as the organic cation has relatively little influence on the vibrations of the lead-halide lattice. Hence, we model the linewidth broadening of MA perovskites in the high-temperature regime again using $\\Gamma(T)={\\cal{T}}_{0}+{\\cal{T}}_{\\mathrm{LO}}$ (solid red lines in Fig. $^{2\\mathrm{c},\\mathrm{d}},$ ), using the LO phonon energies determined previously for FA perovskites. The resultant $\\gamma_{\\mathrm{LO}}$ values are, as expected, very similar to those for the corresponding FA perovskites (Table 1). We may also extrapolate these fits down through the low-temperature regime (dashed red lines), where they do not reflect experimental reality but rather show the broadening that would be present if the additional defects in the orthorhombic phase were absent. As such, values extracted for the parameter $\\boldsymbol{{\\Gamma}}_{0}$ here mostly reflect inhomogeneous disorder present in the high-temperature phases of $\\mathrm{MAPbI}_{3}$ and $\\mathrm{M}\\mathrm{\\bar{A}P b}\\mathrm{Br}_{3}$ at temperatures above 150 and $100\\mathrm{K}$ respectively. \n\n
Table 1 | Extracted linewidth parameters.
Sample To/meVLo/meVELo/meV 11.5 ± 1.2
FAPbl3 19±1 FAPbBr3 20±1 MAPbl3 26±2 MAPbBr3 32±2 FA, formamidinium; LO, longitudinal optical; MA, methylammonium.40±5 61±7 40±2 [11.5] 58±2 [15.3]15.3±1.4
Linewidth broadening parameters extracted from fits of I(T)=Io+ILo to the PL linewidth data for the four hybrid perovskite films.Iis the inhomogeneous broadening (the linewidth at OK), Lo is the strength of the LO phonon-charge-carrier Frohlich coupling and Eo is the relevant LO phonon energy.For fits to the data from MA-containing perovskites, the values of ELo extracted previously for the FA-containing perovskites were used (hence, they are italicized and enclosed in square brackets).Because of the additional defect luminescence present in the orthorhombic phase of the MA-containing perovskites,fits were only carried out between 150 and 370K for MAPbl, and between 1OO and 37OK for MAPbBr (see solid lines in Fig. 2c,d Therefore, the extracted parameters do not reflect the lineshape broadening in the low- temperature phase of the MA-containing perovskites.
\n\nFinally, we comment on the extent to which excitonic effects may influence the coupling between charge carriers and phonons. Although the exact values for the exciton-binding energies in these systems are still a matter of debate, most reported values fall into the range of a few to a few tens of milli-electronvolts (see ref. 4 for a review). These values are compatible with numerous studies demonstrating that at room temperature, following non-resonant excitation, hybrid lead halide perovskites sustain free charge carriers as the predominant species13,14,52. Excitonic effects in the generated charge-carrier population are expected to increase as the temperature is lowered. However, we have recently examined infrared photoinduced transmission spectra for methylammonium lead iodide perovskite21 and found these to be predominantly governed by free-charge (Drude-like) features, with localization effects (for example, from excitons) only contributing at low temperature and not more than around $23\\%$ even at $8\\mathrm{K}.$ This suggests that over the temperature window we examine here, emission broadening is mostly governed by interactions between phonons and free charge carriers rather than excitons. Such predominantly free-charge behaviour of the photogenerated species may be understood, for example, in terms of the Saha equation or a low Mott density for these systems, and considering that the initial highly non-resonant excitation generates predominantly free electron–hole pairs12. We may further inspect in more detail the temperature-dependent line shapes of the emission spectra and find these to exhibit high-energy Boltzmann tails corresponding to a thermalized electron–hole density near the lattice temperature (see Supplementary Fig. 3). These overall observations are therefore compatible with the presence of a thermalized free electron–hole charge-carrier density that scatters off mostly LO phonons whose occupancy is governed by the Bose–Einstein distribution function. Analysis of how the energies of such thermalized free electrons and holes influence the precise lineshape of the PL spectra as a function of temperature could provide additional insight into the scattering mechanisms for free charge carriers. Such additional analysis is however beyond the scope of the present investigation, which is limited to considering only the extent of linewidth broadening. \n\nFirst-principles calculations. We further corroborate our analysis with first-principles calculations of the electron–phonon coupling in $\\mathbf{MAPbI}_{3}$ (see details in Methods section and in the Supplementary Note 1). In accordance with the above discussion, we separately consider the broadening arising from the interaction of phonons with free conduction-band electrons and free valence-band holes53. The combined broadening arising from both types of charge carrier is then compared with the experimentally determined emission broadening. In Fig. 3a, we present a heat-map of the imaginary part of the electron–phonon self-energy, $\\mathrm{Im}(\\Sigma)$ , projected on the quasiparticle band structure of $\\mathrm{MAPbI}_{3}$ ; $2\\ \\mathrm{Im}(\\Sigma)$ represents the linewidth of electrons and holes arising from the electron–phonon interaction before accounting for many-body effects (see Methods) and is therefore directly comparable to the experimentally determined FWHM of the PL emission linewidth. Figure 3b shows $\\mathrm{Im}(\\Sigma)$ as a function of electron energy, together with the density of electronic states. This figure indicates that the increase in the linewidth is linked to the phase-space availability for electronic transitions, that is, $\\mathrm{Im}(\\Sigma)$ increases with increasing density of electronic states, because each state can scatter into a higher number of states by absorbing or emitting a phonon. Our calculations show that the dominant contribution to the electron–phonon self-energy arises from the coupling with the LO mode at $\\omega_{\\mathrm{LO}}\\approx13\\mathrm{meV}$ , which is shown schematically in Fig. 3c. This observation is compatible with the analysis of the temperature dependence of the PL broadening, as presented in Fig. 2, yielding similar energy for the predominantly coupling LO phonon mode in $\\mathbf{MAPbI}_{3}$ . \n\nFigure 3d shows that our calculated temperature dependence of the PL broadening is in good agreement with experiment. In this figure we compared our calculations with the experimental trends obtained from the fit shown in Fig. 2 (which does not account for the anomalous broadening below $150\\mathrm{K},$ as discussed above). The blue triangles represent the data calculated based on Fermi’s golden rule, which is equivalent to using the imaginary part of the electron–phonon self-energy, $2\\ \\mathrm{Im}(\\Sigma)$ , whereas the red triangles were obtained by using Brillouin–Wigner perturbation theory54, which corresponds to scaling the self-energy by the quasiparticle renormalization factor $Z,$ that is $2\\ Z\\ \\mathrm{Im}(\\bar{\\Sigma})$ (see Methods). The comparison between calculations and experiments shows that the experimental data are most accurately described by fully taking into account the many-body renormalization of the electron lifetime. Taken together, the impressive agreement between (1) our measured and calculated characteristic phonon energy scale (11.5 and $13\\mathrm{meV}_{\\mathrm{;}}$ , respectively), (2) the magnitude of our measured and calculated linewidth broadening at room temperature (90 and $75\\mathrm{meV}_{\\mathrm{i}}$ respectively), and (3) the phonon energy scale identified here and the LO phonon identified between 10 and $13\\mathrm{meV}$ in our previous study51, strongly support the notion that the broadening of the PL spectra reflects the interaction between free carriers and LO phonons. \n\nIn addition, we may use first-principle calculations to elucidate why the lead bromide perovskites exhibit Fro¨hlich coupling constants that are larger than those of the lead iodide system by a factor of 1.5. To investigate this trend, we performed DFT calculations for $\\mathrm{MAPbBr}_{3}$ (see Supplementary Note 1) to compare the associated Born effective charges between the two systems. Our results indicate that the electron–phonon coupling in the bromide perovskite is $40\\%$ stronger than in the iodide perovskite, in excellent agreement with our measurements. We find that the increased Fr¨ohlich coupling in $\\mathbf{MAPbBr}_{3}$ is primarily connected with the smaller high-frequency value of the dielectric function compared with $\\mathbf{MAPbI}_{3}$ . \n\n![](images/e5bbcbec3bc4c7198a6a66be202060ee568ea1335ea520bf7d6eeddca0a54fd1.jpg) \nFigure 3 | Ab initio calculations of electron–phonon coupling and PL broadening in $M A P b\\mid_{3}$ . (a) Electronic band structure of orthorhombic $\\mathsf{M A P b l}_{3},$ calculated within the GW approximation as in ref. 55, combined with a heat map of the imaginary part of the electron–phonon self-energy $(\\mathsf{I m}(\\Sigma))$ at ${\\cal T}=200\\mathsf{K}$ . The zero of the energy is placed in the middle of the bandgap. In b, the imaginary part of the electron–phonon self-energy is shown together with the electronic density of states (DOS). $2\\ |m({\\boldsymbol{\\Sigma}})$ corresponds to the electron/hole linewidth arising from electron–phonon coupling (apart from the quasiparticle renormalization factor Z). (c) Ball-and-stick representation of the LO vibration responsible for the broadening of the PL peaks. The blue arrows indicate the displacements of $\\mathsf{P b}$ and I atoms, for the phonon wavevector $\\pmb{\\ q}\\rightarrow0$ along the [100] direction. This is a $\\mathsf{P b-l}$ stretching mode with $B_{3u}$ symmetry51. (d) Temperature dependence of the FWHM of the PL peak in $M A P b|_{3}$ : fit to the experimental data (dashed black line) and theoretical calculations using Fermi’s golden rule (blue triangles) and the more accurate Brillouin–Wigner perturbation theory (red triangles). The theoretical broadening is obtained as the sum of $2\\mathsf{I m}(\\Sigma)$ at the valence and conduction band edges in the case of Fermi’s golden rule, and the sum of $2\\ Z\\mathsf{I m}(\\Sigma)$ when including many-body quasiparticle renormalization, rigidly shifted by the FWHM at ${\\cal T}=0\\mathsf{K}$ $(25.72\\mathsf{m e V})$ , to account for inhomogenous broadening. The lines are guides to the eye. \n\n# Discussion \n\nOur analysis of the experimentally determined emission linewidth broadening and our first-principles calculations strongly support the notion that Fr¨ohlich coupling to LO phonons is the predominant charge-carrier scattering mechanism in hybrid lead halide perovskites. As already discussed above, such behaviour is in many ways to be expected for these materials, because the leadhalide bond is sufficiently polar (see our calculated Born effective charges in Supplementary Table 2) to lead to macroscopic polarizations from LO phonon modes that modify the electronic energies, causing electron–phonon scattering. Coupling of charge carriers to phonons with energies in the meV range has also been postulated from the signature of such modes in the roomand low-temperature photoconductivity spectra21,56. However, the predominance of Fr¨ohlich coupling appears at first sight to contradict the measured21–24 temperature dependence of the charge-carrier mobility, which has been stated16,17,24 to approach the expected form for acoustic deformation potential scattering $(\\mu\\propto T^{^{\\perp}-3/2})$ . We note, however, that although electron–phonon coupling generally leads to charge-carrier mobilities that increase with decreasing temperature, the exact functional dependence is usually a composite of many different scattering mechanisms that can be hard to attribute uniquely18. Charge-carrier scattering with low-energy acoustic phonons can relatively easily be quantified by considering the distribution function of a nondegenerate electron gas approximated by a Boltzmann distribution, which gives the probability that a particular state with energy $E_{k}$ is occupied at any temperature T. Such calculations result in predicted variations in mobility following $\\mu\\propto T^{-3/2}$ for acoustic phonon deformation potential scattering25,26 and $\\mu\\propto T^{-1/2}$ for acoustic phonon piezoelectric scattering18. For Fro¨hlich interactions between charges and LO phonons, analytical solutions are harder to establish57, but the reduction in LO phonon occupancy with decreasing temperature similarly leads to an increase in charge-carrier mobility in polar semiconductors18. Even for non-polar semiconductors such as silicon, electron– phonon interactions are found to be complex, for example, involving higher-order phonon terms and intervalley scattering58. Therefore, we conclude that although acoustic phonon deformation potential scattering may result in $\\mu\\propto T^{-\\sum/2}$ , the converse may not necessarily also hold. In addition, the rapid energy loss of electrons observed following non-resonant excitation19,59 can only sensibly be explained by a succession of high-energy optical phonon emissions60, as is typically observed in inorganic semiconductors4,61. Therefore, we conclude that Fr¨ohlich coupling to LO phonons, rather than acoustic phonon deformation potential coupling, is the dominant charge-carrier scattering mechanism at room temperature in these hybrid lead halide perovskites. Although our findings themselves do not explain the temperature dependence of the charge-carrier mobility in these materials, they support the hypothesis that the observed $\\mu\\propto T^{-3/2}$ relationship is not wholly attributable to acoustic deformation potential scattering. It is also clear that for these high-quality materials, scattering from ionized impurities is a negligible component at room temperature, with both our PL linewidth data and earlier charge-carrier mobility measurements21–23, indicating a complete absence of such contributions. \n\nIn addition, our findings give early answers to the question of how perovskite composition affects Fr¨ohlich interactions between charge carriers and phonons. Such interactions determine the maximum charge-carrier mobilities intrinsically attainable, which in turn affects charge-carrier extraction in solar cells. We show that Fro¨hlich coupling in hybrid lead bromide perovskites appears to be stronger because of the lower dielectric function in the high-frequency regime. Indeed, the THz charge-carrier mobility for $\\mathrm{FAPbBr}_{3}$ thin films has recently been shown to be somewhat lower than that for $\\mathrm{FAPbI}_{3}$ films10, which could be related to decreased momentum scattering time resulting from increased scattering with LO phonons. However, it may also be partly related to a higher propensity towards disorder in the bromide perovskites, as the inhomogeneous broadening parameter $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{0}$ appears to be somewhat higher for bromide than iodide perovskites here. Similarly, higher Urbach energies have previously been reported for $\\mathbf{MAPbBr}_{3}$ compared with $\\mathrm{\\bar{MAPbI}}_{3}$ , in accordance with larger energetic disorder in the former62. We also find that $\\boldsymbol{{\\Gamma}}_{0}$ tends to be lower for the perovskites containing FA as the organic cation, which points to larger material uniformity as one reason behind this material’s recent success in the highest efficiency perovskite solar cells2,7. \n\nWe may also compare these findings with those of other polar inorganic semiconductors for which Fro¨hlich coupling is known to be active. Supplementary Table 1 provides a detailed literature survey of values established for gLO in other inorganic semiconductors. It has been pointed out17 that charge-carrier mobilities established for lead halide perovskites (typically $\\leq100$ $c\\mathrm{m}^{2}(\\mathrm{V}~\\mathsf{s})^{-1})^{15,17}$ are relatively modest compared with those achieved in high-quality GaAs despite the effective charge-carrier masses in perovskites being only slightly elevated above those in GaAs. The values of $\\gamma_{\\mathrm{LO}}{\\approx}40\\mathrm{meV}$ and $\\gamma_{\\mathrm{LO}}{\\approx}60\\mathrm{meV}$ we extract from our data for the respective iodide and bromide perovskites (see Table 1) are somewhat higher than the range reported for GaAs (see comparison in Supplementary Table 1), which may partly explain these discrepancies. However, they are significantly lower than those typically found in highly polar materials such as GaN and $\\mathrm{znO}$ where they can be over an order of magnitude higher28. Further theoretical modelling of charge-carrier mobility in these systems based on our findings will most probably allow more quantitative explanations and predictions to be made. \n\nIn summary, we have conducted an in-depth analysis of charge-carrier–phonon interactions in hybrid lead halide perovskites, considering the four currently most implemented organic and halide components in hybrid perovskite photovoltaics, which are $\\bar{\\mathrm{FAPbI}_{3}}$ , $\\mathrm{FAPbBr}_{3},$ $\\mathbf{MAPbI}_{3}$ and $\\mathbf{\\bar{MAPb}}\\mathbf{B}\\mathbf{r}_{3}$ . Our analysis of the temperature-dependent emission linewidth of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{FAPbBr}_{3}$ allowed us to establish that the Fro¨hlich interaction between charge carriers and LO phonons provides the dominant contribution to the predominantly homogeneous linewidth broadening in these hybrid perovskites at room temperature. We successfully corroborated our findings with DFT and many-body perturbation theory calculations, which underline the suitability of an electronic bandstructure picture for describing charge carriers in perovskites. We furthermore obtained experimentally measured energies of LO phonon modes responsible for Fro¨hlich interactions in these materials and showed that Fr¨ohlich interactions are higher for bromide perovskites than iodide perovskites, providing a link between composition and electron–phonon scattering that fundamentally limits charge-carrier motion. These results lay the groundwork for more quantitative models of charge-carrier mobility values and cooling dynamics that underpin photovoltaic device operation. \n\n# Methods \n\nSample preparation. All materials, unless otherwise stated, were purchased from Sigma-Aldrich and were used as received. Methylammonium iodide, methylammonium bromide, formamidinium iodide and formamidinium bromide were purchased from Dyesol. Thin films were prepared on Z-cut quartz substrates. These were initially cleaned sequentially with acetone followed by propan-2-ol, then treated with oxygen plasma for $10\\mathrm{min}$ . \n\nMA perovskite films were deposited in a nitrogen-filled glovebox using a solvent quenching method wherein an excess of antisolvent is deposited onto the wet \n\nsubstrate while spin-coating63. A 1:1 molar ratio solution of MAX and $\\mathrm{PbX}_{2}$ $\\mathrm{{X=I}}.$ Br) was dissolved in anhydrous $N,N$ -dimethylformamide at $1\\mathbf{M}$ . This was then spin-coated onto the quartz substrates at ${5,000}\\mathrm{r.p.m}$ . for $25s$ . During spin coating, after 7 s an excess of anhydrous chlorobenzene was rapidly deposited onto the spinning film. After spin-coating, films were annealed at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . \n\nFA perovskite films were deposited using an acid-addition method to produce smooth and uniform pinhole-free $\\mathrm{{\\flms}}^{6}$ . FAX and $\\mathrm{Pb}\\mathrm{X}_{2}$ ${\\mathrm{(X=I,~Br}}$ were dissolved in anhydrous $N,N.$ -dimethylformamide in a 1:1 molar ratio at $0.55\\mathrm{M}$ . Immediately before film formation, small amounts of acid were added to the precursor solutions, to enhance the solubility of the precursors and allow smooth and uniform film formation. Thirty-eight microlitres of hydroiodic acid $57\\%$ mass/mass) was added to $\\mathrm{1ml}$ of the $0.55\\mathrm{M}\\mathrm{~FAPbI}_{3}$ precursor solution and $32\\upmu\\mathrm{l}$ of hydrobromic acid ( $48\\%$ mass/mass) was added to $\\mathrm{1ml}$ of the $0.55\\mathrm{M}$ FAPbBr3 precursor solution. Films were then spin coated from the precursor plus acid solution on warm $(85^{\\circ}\\mathrm{C})$ oxygen plasma-cleaned substrates at $2{,}000\\mathrm{r.p.m}$ . in a nitrogen-filled glovebox and subsequently annealed in air at $170^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . \n\nPL spectroscopy. Each sample was photoexcited by a $398\\mathrm{-nm}$ picosecond pulsed diode laser (PicoHarp, LDH-D-C-405M) with a repetition rate of $10\\mathrm{kHz}$ and a fluence of $490{\\mathrm{nJ}}{\\mathrm{cm}}^{\\triangleq2}$ . The resultant PL was collected and focused into a grating spectrometer (Princeton Instruments, SP-2558), which directed the spectrally dispersed PL onto an iCCD (PI-MAX4, Princeton Instruments). The sample was mounted under vacuum $(P{<}10^{-6}\\mathrm{mbar})$ in a cold-finger liquid helium cryostat (Oxford Instruments, MicrostatHe). An associated temperature controller (Oxford Instruments, ITC503) monitored the temperature at two sensors mounted on the heat exchanger of the cryostat and the end of the sample holder, respectively; the reading from the latter was taken as the sample temperature. PL measurements were taken as the sample was heated in increments of $5\\mathrm{K}$ between 10 and $370\\mathrm{K}$ \n\nComputational methods. We carried out ab initio calculations on $\\mathrm{MAPbI}_{3}$ in the orthorhombic phase using the crystallographic data in ref. 35. The ground-state electronic structure was computed within the local density approximation to DFT including spin–orbit coupling, as implemented in the Quantum ESPRESSO package64. We used norm-conserving pseudopotentials to describe the core–valence interaction, with the semicore $d$ states taken explicitly into account in the case of $\\mathrm{\\Pb}$ and I. Ground-state calculations were converged with a plane-wave cutoff of $100\\mathrm{Ry}$ and a $6\\times6\\times6$ unshifted Brillouin-zone grid. The electronic quasiparticle energies were calculated with the SS-GW method described in ref. 65 using the Yambo code66 and interpolated by means of Wannier functions as in ref. 55, using wannier90 (ref. 67). This yields bandgap and effective masses in good agreement with experiment (see Supplementary Note 1). The lattice dynamical properties were computed within density functional perturbation theory at the $\\Gamma$ point, as in ref. 51). The LO–TO splitting was included through the evaluation of the non-analytic contribution to the dynamical matrix. The electron–phonon coupling was calculated using the EPW code68,69, v.4. The electron–phonon self-energy, $\\textstyle{\\sum_{n\\mathbf{k}}},$ was calculated as: \n\n$$\n\\Sigma_{n\\mathbf{k}}=\\sum_{m\\nu\\mathbf{q}}\\big|g_{m n}^{\\nu}(\\mathbf{k,q})\\big|^{2}\\left[\\frac{n_{\\mathbf{q}\\nu}+f_{m\\mathbf{k}+\\mathbf{q}}}{\\epsilon_{n\\mathbf{k}}-\\epsilon_{m\\mathbf{k}+\\mathbf{q}}+\\omega_{\\mathbf{q}\\nu}-i\\eta}+\\frac{n_{\\mathbf{q}\\nu}+1-f_{m\\mathbf{k}+\\mathbf{q}}}{\\epsilon_{n\\mathbf{k}}-\\epsilon_{m\\mathbf{k}+\\mathbf{q}}-\\omega_{\\mathbf{q}\\nu}-i\\eta}\\right].\n$$ \n\nHere, $f_{m\\mathbf{k}+\\mathbf{q}}$ and $n_{\\mathbf{q}\\nu}$ are the Fermi–Dirac and the Bose–Einstein occupations, respectively, $\\epsilon_{n\\mathbf{k}}$ and $\\epsilon_{m\\mathbf{k}+\\mathbf{q}}$ are electron energies, $\\hbar\\omega_{\\mathbf{q}\\nu}$ is the energy of a phonon with wavevector $\\mathbf{q}$ and polarization $\\nu,$ and $\\eta$ is a small broadening ( $\\mathrm{10\\meV}$ in Fig. 3a,b; 1 meV in Fig. 3d). Only the interaction with the LO phonons was taken into account, by calculating the electron–phonon matrix element $g_{m n}^{\\nu}(\\mathbf{k},\\mathbf{q})$ as in ref. 70 (see Supplementary equation (1)). The self-energy in equation (2) was converged by using up to two million random $\\mathbf{q}$ points in the Brillouin zone. The quasiparticle renormalization factor $Z$ is defined as the frequency derivative: \n\n$$\nZ_{n\\mathbf{k}}=\\left[1-\\frac{1}{\\hbar}\\frac{\\partial\\operatorname{Re}(\\Sigma_{n\\mathbf{k}})}{\\partial\\omega}\\right]^{-1},\n$$ \n\nand is evaluated at the band edges. In the case of the conduction band edge, we find $Z=0.54$ at zero temperature. \n\nData availability. The data that support the findings of this study are available from the corresponding author on request, as is the custom Matlab code used to analyse the PL data. The Quantum ESPRESSO64, Yambo66, wannier90 (ref. 67) and EPW v.4 (ref. 69) software used to perform the first-principles calculations are open source and are accessible online. \n\n# References \n\n1. Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. \n131, 6050–6051 (2009). \n2. Yang, W. S. et al. High-performance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237 (2015). \n3. Bi, D. et al. Efficient luminescent solar cells based on tailored mixed-cation perovskites. Sci. Adv. 2, e1501170 (2016). \n4. Herz, L. M. Charge carrier dynamics in organic-inorganic metal halide perovskites. Annu. Rev. Phys. Chem. 67, doi:10.1146/annurev-physchem-040215-112222 (2016). \n5. McMeekin, D. P. et al. A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells. Science 351, 151–155 (2016). \n6. Eperon, G. E. et al. Formamidinium lead trihalide: a broadly tunable perovskite for efficient planar heterojunction solar cells. Energy Environ. Sci. 7, 982–988 (2014). \n7. Jeon, N. J. et al. Compositional engineering of perovskite materials for high-performance solar cells. Nature 517, 476–480 (2015). \n8. Binek, A., Hanusch, F. C., Docampo, P. & Bein, T. Stabilization of the trigonal high temperature phase of formamidinium lead iodide. J. Phys. Chem. Lett. 6, 1249–1253 (2015). \n9. Eperon, G. E., Beck, C. E. & Snaith, H. J. Cation exchange for thin film lead iodide perovskite interconversion. Mater. Horiz. 3, 63–71 (2015). \n10. Rehman, W. et al. Charge-carrier dynamics and mobilities in formamidinium lead mixed-halide perovskites. Adv. Mater. 27, 7938–7944 (2015). \n11. Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n12. D’Innocenzo, V. et al. Excitons versus free charges in organo-lead tri-halide perovskites. Nat. Commun. 5, 3586 (2014). \n13. Stranks, S., Eperon, G. & Grancini, G. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n14. Wehrenfennig, C., Eperon, G. E., Johnston, M. B., Snaith, H. J. & Herz, L. M. High charge carrier mobilities and lifetimes in organolead trihalide perovskites. Adv. Mater. 26, 1584–1589 (2014). \n15. Johnston, M. B. & Herz, L. M. Hybrid Perovskites for photovoltaics: chargecarrier recombination, diffusion, and radiative efficiencies. Acc. Chem. Res. 49, 146–154 (2016). \n16. Zhu, X.-Y. & Podzorov, V. Charge carriers in hybrid organic-inorganic lead halide perovskites might be protected as large polarons. J. Phys. Chem. Lett. 6, 4758–4761 (2015). \n17. Brenner, T. M. et al. Are mobilities in hybrid organic-inorganic halide perovskites actually ‘high’? J. Phys. Chem. Lett. 6, 4754–4757 (2015). \n18. Yu, P. Y. & Cardona, M. Fundamentals of Semiconductors. Graduate Texts in Physics (Springer-Verlag, 2010). \n19. Yang, Y. et al. Observation of a hot-phonon bottleneck in lead-iodide perovskites. Nature Photon. 10, 53–59 (2015). \n20. Wehrenfennig, C., Liu, M., Snaith, H. J., Johnston, M. B. & Herz, L. M. Homogeneous emission line broadening in the organo lead halide perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3-x}\\mathrm{Cl}_{x}.$ J. Phys. Chem. Lett. 5, 1300–1306 (2014). \n21. Milot, R. L., Eperon, G. E., Snaith, H. J., Johnston, M. B. & Herz, L. M. Temperature-dependent charge-carrier dynamics in $\\mathrm{CH}_{3}\\ \\mathrm{NH}_{3}\\ \\mathrm{PbI}_{3}$ perovskite thin films. Adv. Funct. Mater. 25, 6218–6227 (2015). \n22. Oga, H., Saeki, A., Ogomi, Y., Hayase, S. & Seki, S. Improved understanding of the electronic and energetic landscapes of perovskite solar cells: high local charge carrier mobility, reduced recombination, and extremely shallow traps. J. Am. Chem. Soc. 136, 13818–13825 (2014). \n23. Savenije, T. et al. Thermally activated exciton dissociation and recombination control the carrier dynamics in organometal halide perovskite. J. Phys. Chem. Lett. 5, 2189–2194 (2014). \n24. Karakus, M. et al. Phonon-electron scattering limits free charge mobility in methylammonium lead iodide perovskites. J. Phys. Chem. Lett. 6, 4991–4996 (2015). \n25. Seitz, F. On the mobility of electrons in pure non-polar insulators. Phys. Rev. 73, 549–564 (1948). \n26. Bardeen, J. & Shockley, W. Deformation potentials and mobilities in non-polar crystals. Phys. Rev. 80, 72–80 (1950). \n27. Benavides-Garcia, M. & Balasubramanian, K. Bond energies, ionization potentials, and the singlet-triplet energy separations of $\\mathrm{{SnCl}}_{2}$ , $\\operatorname{SnBr}_{2}$ , $\\mathrm{SnI}_{2}$ , $\\mathrm{Pb}{\\mathrm{Cl}}_{2}$ , $\\mathrm{Pb}\\mathrm{Br}_{2}$ , $\\mathrm{PbI}_{2}$ , and their positive ions. J. Chem. Phys. 100, 2821–2830 (1994). \n28. Viswanath, A., Lee, J., Kim, D., Lee, C. & Leem, J. Exciton-phonon interactions, exciton binding energy, and their importance in the realization of roomtemperature semiconductor lasers based on GaN. Phys. Rev. B 58, 16333–16339 (1998). \n29. Stillman, G., Wolfe, C. & Dimmock, J. Hall coefficient factor for polar mode scattering in n-type GaAs. J. Phys. Chem. Solids 31, 1199–1204 (1970). \n30. Stoumpos, C., Malliakas, C. & Kanatzidis, M. Semiconducting tin and lead iodide perovskites with organic cations: phase transitions, high mobilities, and near-infrared photoluminescent properties. Inorg. Chem. 52, 9019–9038 (2013). \n31. Fang, H.-H. et al. Photophysics of organic-inorganic hybrid lead iodide perovskite single crystals. Adv. Funct. Mater. 25, 2378–2385 (2015). nanoplatelets: towards high-performance perovskite solar cells and optoelectronic devices. Adv. Opt. Mater. 2, 838–844 (2014). \n33. Fang, H. H. et al. Photoexcitation dynamics in solution-processed formamidinium lead iodide perovskite thin films for solar cell applications. Light Sci. Appl. 5, e16056 (2016). \n34. Onoda-Yamamuro, N., Matsuo, T. & Suga, H. Calorimetric and IR spectroscopic studies of phase transitions in methylammonium trihalogenoplumbates (II). J. Phys. Chem. Solids 51, 1383–1395 (1990). \n35. Baikie, T. et al. Synthesis and crystal chemistry of the hybrid perovskite $\\mathrm{(CH_{3}N H_{3})P b I_{3}}$ for solid-state sensitised solar cell applications. J. Mater. Chem. A 1, 5628–5641 (2013). \n36. Wasylishen, R., Knop, O. & Macdonald, J. Cation rotation in methylammonium lead halides. Solid State Commun. 56, 581–582 (1985). \n37. Varshni, Y. Temperature dependence of the energy gap in semiconductors. Physica 34, 149–154 (1967). \n38. Frost, J. M. J. et al. Atomistic origins of high-performance in hybrid halide perovskite solar cells. Nano Lett. 14, 2584–2590 (2014). \n39. Wehrenfennig, C., Liu, M., Snaith, H. J., Johnston, M. B. & Herz, L. M. Charge carrier recombination channels in the low-temperature phase of organicinorganic lead halide perovskite thin films. APL Mater 2, 081513 (2014). \n40. Wu, X. et al. Trap states in lead iodide perovskites. J. Am. Chem. Soc. 137, 2089–2096 (2015). \n41. Priante, D. et al. The recombination mechanisms leading to amplified spontaneous emission at the true-green wavelength in $\\mathrm{CH_{3}N H_{3}P b B r_{3}}$ perovskites. Appl. Phys. Lett. 106, 081902 (2015). \n42. Rudin, S., Reinecke, T. L. & Segall, B. Temperature-dependent exciton linewidths in semiconductors. Phys. Rev. B 42, 11218–11231 (1990). \n43. Lee, J., Koteles, E. S. & Vassell, M. O. Luminescence linewidths of excitons in GaAs quantum wells below $150\\mathrm{K}.$ Phys. Rev. B 33, 5512–5516 (1986). \n44. Malikova, L. et al. Temperature dependence of the direct gaps of $Z\\mathrm{nSe}$ and $\\mathrm{Zn}_{0.56}\\mathrm{Cd}_{0.44}\\mathrm{Se}$ . Phys. Rev. B 54, 1819–1824 (1996). \n45. Chen, Y., Kothiyal, G., Singh, J. & Bhattacharya, P. Absorption and photoluminescence studies of the temperature dependence of exciton life time in lattice-matched and strained quantum well systems. Superlattice Microst. 3, 657–664 (1987). \n46. Bartolo, B. D. & Chen, X. Advances in Energy Transfer Processes (World Scientific, 2001). \n47. Selci, S. et al. Evaluation of electron-phonon coupling of $\\mathrm{Al}_{0.27}\\mathrm{Ga}_{0.73}\\mathrm{As}/\\mathrm{GaAs}$ quantum wells by normal incidence reflectance. Solid State Commun. 79, 561–565 (1991). \n48. Masumoto, Y. & Takagahara, T. Semiconductor Quantum Dots (SpringerVerlag, 2002). \n49. Zhang, X. B., Taliercio, T., Kolliakos, S. & Lefebvre, P. Influence of electronphonon interaction on the optical properties of III nitride semiconductors. J. Phys.: Condens. Matter 13, 7053–7074 (2001). \n50. Gammon, D., Rudin, S., Reinecke, T. L., Katzer, D. S. & Kyono, C. S. Phonon broadening of excitons in GaAs/AlGaAs quantum wells. Phys. Rev. B 51, 16785–16789 (1995). \n51. Pe´rez-Osorio, M. A. et al. Vibrational properties of the organic-inorganic halide perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ from theory and experiment: factor group analysis, first-principles calculations, and low-temperature infrared spectra. J. Phys. Chem. C 119, 25703–25718 (2015). \n52. Yamada, Y. et al. Photocarrier recombination dynamics in perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ for solar cell applications. J. Am. Chem. Soc. 136, 11610–11613 (2014). \n53. Gopalan, S., Lautenschlager, P. & Cardona, M. Temperature dependence of the shifts and broadenings of the critical points in GaAs. Phys. Rev. B 35, 5577–5584 (1987). \n54. Grimvall, G. The Electron-Phonon Interaction in Metals (North-Holland, 1981). \n55. Filip, M. R., Verdi, C. & Giustino, F. GW band structures and carrier effective masses of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and hypothetical perovskites of the type $\\mathrm{APbI}_{3}$ : $\\mathrm{A}=\\mathrm{N}\\mathrm{H}_{4},$ $\\mathrm{PH}_{4},$ $\\mathrm{AsH_{4}},$ and $\\mathrm{SbH_{4}}$ . J. Phys. Chem. C 119, 25209–25219 (2015). \n56. Wehrenfennig, C., Liu, M., Snaith, H. J., Johnston, M. B. & Herz, L. M. Charge-carrier dynamics in vapour-deposited films of the organolead halide perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3-x}\\mathrm{Cl}_{x}.$ Energy Environ. Sci. 7, 2269–2275 (2014). \n57. Petritz, R. & Scanlon, W. Mobility of electrons and holes in the polar crystal, PbS. Phys. Rev. 97, 1620–1626 (1955). \n58. Ferry, D. First-order optical and intervalley scattering in semiconductors. Phys. Rev. B 14, 1605–1609 (1976). \n59. Price, M. et al. Hot carrier cooling and photo-induced refractive index changes in organic-inorganic lead halide perovskites. Nat. Commun. 6, 8420 (2015). \n60. Kawai, H., Giorgi, G., Marini, A. & Yamashita, K. The mechanism of slow hot-hole cooling in lead-iodide perovskite: first-principle calculation on carrier lifetime from electron-phonon interaction. Nano Lett. 15, 3103–3108 (2015). \n61. von der Linde, D. & Lambrich, R. Direct measurement of hot-electron relaxation by picosecond spectroscopy. Phys. Rev. Lett. 42, 1090–1093 (1979). \n62. Sadhanala, A. et al. Preparation of single phase films of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Pb}(\\mathrm{I}_{1-x}\\mathrm{Br}_{x})_{3}$ with sharp optical band edges. J. Phys. Chem. Lett. 5, 2501–2505 (2014). \n63. Xiao, M. et al. A fast deposition-crystallization procedure for highly efficient lead iodide perovskite thin-film solar cells. Angew. Chem. Int. Ed. 126, 10056–10061 (2014). \n64. Giannozzi, P. et al. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials. J. Phys.: Condens. Matter 21, 395502 (2009). \n65. Filip, M. R. & Giustino, F. GW quasiparticle band gap of the hybrid organicinorganic perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ : Effect of spin-orbit interaction, semicore electrons, and self-consistency. Phys. Rev. B 90, 245145 (2014). \n66. Marini, A., Hogan, C., Gru¨ning, M. & Varsano, D. yambo: An ab initio tool for excited state calculations. Comp. Phys. Commun. 180, 1392–1403 (2009). \n67. Mostofi, A. A. et al. wannier90: A tool for obtaining maximally-localised Wannier functions. Comp. Phys. Commun. 178, 685–699 (2008). \n68. Giustino, F., Cohen, M. L. & Louie, S. G. Electron-phonon interaction using Wannier functions. Phys. Rev. B 76, 165108 (2007). \n69. Ponce´, S., Margine, E. R., Verdi, C. & Giustino, F. EPW: electron-phonon coupling, transport and superconducting properties using maximally localized Wannier functions. Preprint at http://arxiv.org/abs/1604.03525 (2016). \n70. Verdi, C. & Giustino, F. Fro¨hlich electron-phonon vertex from first principles. Phys. Rev. Lett. 115, 176401 (2015). \n\n# Acknowledgements \n\nThis work was supported by the Leverhulme Trust (Grant RL-2012-001), the UK Engineering and Physical Sciences Research Council (grant numbers EP/J009857/1, EP/L024667, EP/L016702/1 and EP/M020517/1) and the Graphene Flagship (EU FP7 grant number 604391). This work used the ARCHER UK National Supercomputing Service via the AMSEC Leadership project and the Advanced Research Computing (ARC) facility of the University of Oxford. \n\n# Author contributions \n\nA.D.W. performed the PL experiments, did the data analysis and participated in the experimental planning. C.V. carried out the first-principles calculations. R.L.M. gave guidance for the PL experiments. G.E.E. prepared the samples. H.J.S. gave guidance on sample preparation. M.A.P.-O. provided support with the first-principles calculations. The project was conceived, planned and supervised by F.G., M.B.J. and L.M.H. A.D.W. wrote the first version of the manuscript. All authors contributed to the discussion and preparation of the final version of the paper. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Wright, A. D. et al. Electron–phonon coupling in hybrid lead halide perovskites. Nat. Commun. 7:11755 doi: 10.1038/ncomms11755 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1002_adfm.201505328", + "DOI": "10.1002/adfm.201505328", + "DOI Link": "http://dx.doi.org/10.1002/adfm.201505328", + "Relative Dir Path": "mds/10.1002_adfm.201505328", + "Article Title": "Synthesis and Characterization of 2D Molybdenum Carbide (MXene)", + "Authors": "Halim, J; Kota, S; Lukatskaya, MR; Naguib, M; Zhao, MQ; Moon, EJ; Pitock, J; nullda, J; May, SJ; Gogotsi, Y; Barsoum, MW", + "Source Title": "ADVANCED FUNCTIONAL MATERIALS", + "Abstract": "Large scale synthesis and delamination of 2D Mo2CTx (where T is a surface termination group) has been achieved by selectively etching gallium from the recently discovered nullolaminated, ternary transition metal carbide Mo2Ga2C. Different synthesis and delamination routes result in different flake morphologies. The resistivity of free-standing Mo2CTx films increases by an order of magnitude as the temperature is reduced from 300 to 10 K, suggesting semiconductor-like behavior of this MXene, in contrast to Ti3C2Tx which exhibits metallic behavior. At 10 K, the magnetoresistance is positive. Additionally, changes in electronic transport are observed upon annealing of the films. When 2 mu m thick films are tested as electrodes in supercapacitors, capacitances as high as 700 F cm(-3) in a 1 M sulfuric acid electrolyte and high capacity retention for at least 10,000 cycles at 10 A g(-1) are obtained. Free-standing Mo2CTx films, with approximate to 8 wt% carbon nullotubes, perform well when tested as an electrode material for Li-ions, especially at high rates. At 20 and 131 C cycling rates, stable reversible capacities of 250 and 76 mAh g(-1), respectively, are achieved for over 1000 cycles.", + "Times Cited, WoS Core": 1042, + "Times Cited, All Databases": 1114, + "Publication Year": 2016, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000377591500015", + "Markdown": "# Synthesis and Characterization of 2D Molybdenum Carbide (MXene) \n\nJoseph Halim, Sankalp Kota, Maria R. Lukatskaya, Michael Naguib, Meng-Qiang Zhao, Eun Ju Moon, Jeremy Pitock, Jagjit Nanda, Steven J. May, Yury Gogotsi,\\* and Michel W. Barsoum\\* \n\nLarge scale synthesis and delamination of 2D $\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ (where T is a surface termination group) has been achieved by selectively etching gallium from the recently discovered nanolaminated, ternary transition metal carbide $M O_{2}\\mathsf{C a}_{2}\\mathsf{C}$ . Different synthesis and delamination routes result in different flake morphologies. The resistivity of free-standing $\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ films increases by an order of magnitude as the temperature is reduced from 300 to $\\mathsf{\\mathsf{10~K}},$ , suggesting semiconductor-like behavior of this MXene, in contrast to $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\bar{\\mathsf{T}}_{x}$ which exhibits metallic behavior. At $\\mathsf{\\mathsf{I}}\\boldsymbol{0}\\mathsf{K}$ , the magnetoresistance is positive. Additionally, changes in electronic transport are observed upon annealing of the films. When $2\\upmu\\mathrm{m}$ thick films are tested as electrodes in supercapacitors, capacitances as high as $700\\mathsf{F}\\mathsf{c m}^{-3}$ in a ${\\mathsf{1}}{\\mathsf{n}}$ sulfuric acid electrolyte and high capacity retention for at least 10,000 cycles at $\\mathsf{10A g^{-1}}$ are obtained. Free-standing $\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ films, with ${\\approx}8~\\mathrm{wt\\%}$ carbon nanotubes, perform well when tested as an electrode material for Li-ions, especially at high rates. At 20 and 131 C cycling rates, stable reversible capacities of 250 and $76~\\mathsf{m A h}~\\mathsf{g}^{-1}$ , respectively, are achieved for over 1000 cycles. \n\nfrom their bulk counterparts. 1–3 Recently, we discovered a new family of 2D transition metal carbides and carbonitrides, which we labeled MXenes. 4 MXenes have the general formula of $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x},$ where M stands for an early transition metal (e.g., Ti, V, Cr, and Mo), $X$ is either carbon or nitrogen, $n=1{-}3$ , and $\\mathrm{T}_{x}$ represents surface functional groups such as $-0$ , $-\\mathrm{OH}$ and/or F. 5 They are synthesized by selective etching of the “A” layers (mostly from groups 13 and 14) from layered, ternary carbides, MAX phases, using hydrofluoric acid (HF), ammonium bifluoride $\\left(\\mathrm{NH}_{4}\\mathrm{HF}_{2}\\right)$ , or a solution of lithium fluoride (LiF) and hydrochloric acid (HCl). 6–8 \n\nMXenes exhibit good electrical conductivity, hydrophilicity, and can host many different cations between their layers. 4,9 Due to these characteristics, they have been explored theoretically and experimentally for a number of applications, with par \n\n# 1. Introduction \n\nTwo-dimensional (2D) materials possess high specific surface areas and sometimes exhibit electronic properties that differ ticular attention given to energy storage applications, including electrodes for Li-, Na-, and K-ion batteries, 10–12 Li-S batteries, 13 Li-ion and aqueous supercapacitors. 8,9,14,15 They can also provide stability and durability for proton exchange membranes for fuel cells. 16 Other potential applications include water purification, 17,18 electrochemical actuators, 19 photocatalysis, 20 transparent conductive electrodes and sensors. 7,21 \n\nTypically the resistivity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films decreases with decreasing temperature from 300 down to $100~\\mathrm{K}$ , below which the resistance increases slightly. 7 At temperature $<50~\\mathrm{~K~},$ the magnetoresistance (MR) is negative and the logarithmic dependence of the resistivity on temperature suggests a weak 2D localization effect. \n\nTo date more than a dozen different MXene compositions have been reported, all of which were produced by etching the Al-layers from Al-containing MAX phases. 4,5,11,22,23 Quite recently, however, we discovered a new hexagonal ternary nanolaminated carbide, $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ , where instead of one “A” layer such as $\\mathsf{M o}_{2}\\mathsf{G a C},\\mathsf{[}24\\mathsf{]}$ two $\\mathrm{^{\\alpha}A^{\\prime\\prime}}$ layers are found between the $\\mathsf{M o}_{2}\\mathsf{C}$ layers. 25 In a subsequent paper, 26 we showed the possibility of selectively etching the Ga layers – using HF – from epitaxial ${\\mathrm{Mo}}_{2}{\\mathrm{Ga}}_{2}{\\mathrm{C}}$ thin films, producing the MXene $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ However, since the $\\mathsf{M o}_{2}\\mathsf{G a}_{2}\\mathsf{C}$ thin films were not completely converted to $\\mathrm{Mo}_{2}\\mathrm{CT}_{{\\boldsymbol x}},$ we were not able to characterize the latter’s properties. Using Boltzmann theory and first-principles electronic structure calculations, $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ terminated with F is predicted to be semiconductor with a band gap of $0.25\\mathrm{eV}$ and a high power factor. 27 \n\nCoincidentally, quite recently, $\\mathrm{\\DeltaXu}$ et al. used chemical vapor deposition to produce large-area, high-quality, $\\mathsf{M o}_{2}\\mathrm{C}$ crystals, as thin as $3.4~\\mathrm{nm}$ . 28 $\\mathrm{In}\\ 3.4\\ \\mathrm{nm}$ thick crystals, the resistivity was shown to decrease from 300 to about $50\\mathrm{K}$ ; below $50\\mathrm{K}$ the resistivity increased logarithmically suggesting – like in the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films 7 – a possible weak 2D localization effect. In crystals thicker than $3\\ \\mathrm{nm}$ , a superconducting transition was observed below ${\\approx}4~\\mathrm{K}$ . At $10~\\mathrm{K}$ , the electron mobilities of these films were reported to be $\\mathrm{\\approx}10~\\mathrm{cm}^{2}~\\mathrm{Vs}^{-1}$ \n\nHerein the large-scale synthesis and delamination of $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ flakes by the selective etching of $\\mathrm{Ga}$ from $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ powders using HF or a solution of LiF and HCl is reported. Once etched and delaminated, to produce $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ colloidal solutions, henceforth referred to as $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ free-standing “paper” was produced by filtering the $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}.$ Since this is the first report on the synthesis of $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ powder and single-layer flakes, it was important to characterize their structure and various properties. Transport measurements were carried out to evaluate the conductivity and suitability of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ for electronic applications. We also report preliminary results on the potential of using $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ in energy storage applications, such as Li-ion batteries and aqueous supercapacitors. \n\n# 2. Results and Discussion \n\n# 2.1. Material Synthesis, Structural and Chemical Characterization \n\nThe synthesis and delamination of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ flakes are schematically illustrated in Figure 1a. Both methods used for producing $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ flakes involve etching the Ga layers from $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathtt{C}$ using acidic solutions containing fluoride ions. The synthesis details of $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ , its MXene, “paper,” and composites can be found in the experimental section below. \n\nIn the first method, $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ powders were etched using a solution, containing $3\\mathrm{~M~}$ LiF and $12\\mathrm{~M~}$ HCl, producing $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ multilayered flakes with $\\mathrm{Li^{+}}$ ions between the layers. This material will henceforth be referred to as $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ –Li (more synthesis details can be found in the experimental section). To delaminate $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ –Li, $2~\\mathrm{gm}$ of the etched powder was added to $40~\\mathrm{mL}$ of deionized (DI) water and hand shaken for 5 min. The end result, after centrifuging for $^{1\\mathrm{~h~}}$ at $5000~\\mathrm{rpm}$ , was a colloidal suspension of delaminated flakes with a concentration o $\\mathrm{\\Delta\\H{\\approx}0.1\\ m g\\ m L^{-1}}$ Filtration of the latter produced films that will henceforth be referred to as $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ –Li. A comparison of the X-ray diffraction (XRD) patterns of $\\mathsf{M o}_{2}\\mathsf{G a}_{2}\\mathsf{C}$ (i./black pattern in Figure 1c,d) and $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}\\mathrm{-Li}$ etched for 16 days at $35~^{\\circ}\\mathrm{C}$ (ii./green pattern in Figure 1c,d) clearly shows that all peaks belonging to $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ are totally replaced by (000l) peaks belonging to $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}.$ –Li. As typical of all MAX to MXene transformations, the (0001) peaks broaden and shift to lower angles as a result of an increase in the $\\boldsymbol{c}$ lattice parameter (c-LP) from 18.1 to $23.1\\mathrm{{\\AA}}$ . It is worth noting that the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ –Li flakes produced after 16 days of etching contain pin-holes and other defects, as can be seen in the Transition Electron Micrographs (TEM) micrograph in Figure S2 in the Supporting Information, whereas etching for only 6 days yields higher quality flakes with little or no defects (Figure 2a). The yields after 6 days, however, are low resulting in suspensions with a concentration of ${\\approx}0.05~\\mathrm{mg~mL^{-1}}$ since only a small portion of the $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathtt{C}$ powder is converted to MXene as shown in the XRD pattern in Figure S3 in the Supporting Information. \n\n![](images/efcb417035f96a382c5232cc10a3bb851a1ee8a2d92da0a30cef60624deacd36.jpg) \nFigure 1. a) Schematic showing synthesis and delamination of ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ b) Digital photos of diluted delaminated solution and free-standing “paper” produced by filtering the delaminated solution. c) Full range XRD patterns of, i. ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ (black), ii. ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ –Li (green), iii. ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ (red), iv. ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ (blue) ntercalated with TBAOH, and v. (purple) free standing “paper” after TBAOH intercalation. d) Same as Figure $\\mathsf{c}$ but focusing on the $^{2\\Theta}$ range from 2 to $\\mathsf{10}.5^{\\circ}$ showing the shift in the 0002 peak. \n\nIn the second method, $14\\mathrm{~M~}$ aqueous HF was used as the etchant. In this case, the $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ powders were etched for 6.6 days at $55~^{\\circ}\\mathrm{C}$ . These powders will henceforth be referred to as $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ To delaminate the etched powders, the $\\mathrm{Mo}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ powders were first intercalated with tetrabutylammonium hydroxide (TBAOH) in water following the procedure, described by Naguib et al. 29 Two grams of the intercalated $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ were delaminated in $40~\\mathrm{mL}$ of DI water either by hand shaking or sonication, yielding a suspension with a concentration of ${\\approx}4~\\mathrm{mg~mL^{-1}}$ The resulting material will henceforth simply be referred to as $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ The suspension was then vacuum filtered through a nanoporous polypropylene membrane to obtain free-standing $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ “paper”. From digital images shown in Figure 1b it is apparent that the diluted delaminated suspension is brown-pink in color, whereas the films are metallic green. Scanning electron microscopy (SEM) images showing the morphologies of $\\mathsf{M o}_{2}\\mathsf{G a}_{2}\\mathsf{C}$ , $\\mathrm{Mo}_{2}\\mathrm{CT}_{{x}},$ and $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}.$ –Li powders are shown in Figure S1a–d in the Supporting Information, respectively. \n\nXRD patterns of $\\mathsf{M o}_{2}\\mathsf{G a}_{2}\\mathsf{C}$ powders after etching with HF (iii./red patterns in Figure 1c,d) resulted in the appearance of two (0002) MXene peaks in addition to a peak corresponding to the unreacted MAX phase. The first MXene peak corresponds to a $c$ -LP of $21.2\\mathrm{~\\AA~}$ , while the second, quite weak peak, corresponds to a $c$ -LP of $26.9\\mathrm{~\\AA~}$ . The difference in the interlayer spacing $(\\Delta d=\\Delta c/2)$ between them is approximately equal to the van der Waals radius of a water monolayer, viz., $\\overset{\\cdot}{2.8\\mathrm{~\\bar{A}~}}$ . 30 This suggests that some of the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ multilayers are intercalated with a monolayer of water, while others are intercalated by two layers. Water intercalation is common and has been observed in other MXenes such as $\\mathrm{Nb}_{2}\\mathrm{CT}_{{\\boldsymbol x}},$ $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\boldsymbol{x}},$ and $\\mathrm{V}_{2}\\mathrm{CT}_{x}$ 11,22 \n\nUpon intercalation with TBAOH, two (0002) peaks appeared corresponding to $\\boldsymbol{c}$ -LPs of 28.5 and $58.1\\mathring{\\mathrm{A}}$ , respectively (iv./blue patterns in Figure 1c,d). The first, small peak arises from TBA intercalated $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ . 31 The other (0002) peak with a $\\boldsymbol{c}$ -LP of $58.1\\mathrm{~\\AA~}$ has a $\\Delta d$ of $18.5\\mathrm{~\\AA~}$ (using the $d$ -spacing of the high angle 0002 peak of $\\mathrm{Mo}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ as a base line), which corresponds to the intercalation of TBA cations (the TBA cation size ranges between 8.5 and $10.5\\mathrm{~\\AA~}$ and from two to three water layers. 31 Similar behavior was reported for the intercalation of graphene oxide with TBAOH. 30 \n\nThe $\\boldsymbol{\\mathscr{c}}$ -LP of the $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ “paper” at ${\\approx}37.7\\$ Å (v./purple patterns in Figure 1c,d) is significantly shorter than the 58.1 Å of the TBA intercalated powders. Said otherwise, $\\Delta d$ compared to $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ is ${\\ \\approx}10.2\\mathrm{~\\AA~}$ , which is quite close to the size of a single TBA cation. This suggests that while water may be trapped between the multilayers, the delamination, filtration and drying steps allow the water molecules to escape leaving only TBA cations behind. A comparison of the XRD patterns of the “paper” and the multilayered powders (compare v./purple and ii. green patterns in Figure 1c and d) also reveals that the former are significantly purer as evidenced by the total absence of the (0002) peak of the $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ precursor powders at ${\\approx}9.5^{\\circ}$ . \n\nNote that the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ –Li multilayered flakes (ii./green patterns in Figure 1c,d) have a $\\boldsymbol{\\mathscr{c}}$ -LP which is $\\approx10\\%$ larger than their $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ counterparts (iii./red patterns in Figure 1c,d). This slight increase suggests the presence of $\\mathrm{Li^{+}}$ cations between the MXene layers. \n\nFigure 2a,d show, respectively, low and high magnification TEM images of a $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ –Li flake after the powders were etched for 6 days. The flake has a lateral diameter of ${\\approx}2\\upmu\\mathrm{m}$ and shows few signs of macroscopic defects, such as pores. Flakes produced after etching for 16 days (Figure S2, Supporting Information), on the other hand, are quite defective, with a large number of pores clearly visible. Not surprisingly, and as noted above, the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}.$ –Li yields, after etching for 6 days, are significantly lower than those etched for 16 days, as evidenced by the presence of $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathtt{C}$ peaks in the XRD patterns of the former (Figure S3, Supporting Information). Thus, shorter etching times result in less defective flakes but the yields are low; longer etching times, on the other hand, result in higher yields of more defective flakes. \n\n![](images/5fea1cc032c8f0e24352c7b3a6a9ba3d46b64fc7724d7379d6bb6d628787429d.jpg) \nFigure 2. Low magnification TEM images of single flakes of, a) ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ –Li powders etched for 6 days, delaminated by manual shaking in water for 5 min, b) $\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ after intercalation with TBAOH and hand shaking for 5 min and, c) Same as (b), but after sonication for $\\rceil\\mathfrak{h}$ in water. High magnification TEM images of (a), (b), and (c) are shown, respectively, in (d), (e), and (f). \n\nAlong the same lines, the $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ flakes (Figure 2b,e) are more defective than their $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}{\\mathrm{-}}\\mathrm{Li}$ counterparts (Figure 2a,d). Pores can be observed in the higher magnification TEM image (Figure 2e), which originate during the TBAOH intercalation step, since TEM images of flakes before TBAOH intercalation show no pores (Figure S5, Supporting Information). Similar behavior was reported for delaminated $\\mathrm{V}_{2}\\mathrm{CT}_{x}$ flakes after TBAOH treatment. 29 Not surprisingly, smaller sized defective flakes, with larger diameter holes, were obtained after sonication for $^{1\\mathrm{h}}$ (Figure 2c,f). However, the percentage of single flakes increased from $25\\%$ to $50\\%$ after sonication (Figure S4, Supporting Information). \n\nThese results are important because they outline several strategies that can be used to manipulate flake morphologies; from relatively defect-free to highly defective and nanoporous. The former could be used for electronic and optical applications where defect-free flakes with large lateral dimensions are needed. In contrast, the latter could be used for applications where higher accessibility and edge effects may be useful, such as in energy storage or catalysis. In the current study we focused on the characterization of the $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ produced using HF etching, which had a high yield. In the remainder of this paper, we describe experiments performed exclusively with the HF etched powders that were sonicated for $^{1\\mathrm{h}}$ . \n\nX-ray photoelectron spectroscopy (XPS) measurements performed on the $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ “paper” were used to identify and quantify the various chemical and termination species. High-resolution XPS spectra peak fittings for Mo 3d, C 1s, O 1s, and F 1s are shown in Figure 3a–d, respectively. The peak fitting results for the various species and the elemental compositions extracted from the high resolution spectra are tabulated in Tables S1 and S2 in the Supporting Information. The high-resolution XPS spectrum of the Ga 2p region confirms the absence of Ga related peaks after etching (Figure S6, Supporting Information). The high-resolution spectrum of the Mo 3d region (Figure 3a) were fitted by components corresponding to the following three species: Mo C, $\\mathrm{Mo}^{+5}$ and $\\mathrm{Mo}^{+6}$ 32,33 The latter two species – whose peaks are quite small – most probably arise from surface oxidation of the “paper” and represent ${\\approx}12\\%$ of the Mo 3d region. The binding energy (BE) of the Mo $3\\mathrm{d}_{5/2}$ for the Mo C species is at $229.2\\ \\mathrm{eV},$ which is $1.1\\ \\mathrm{eV}$ higher than the 228.1 eV BE of the $\\mathtt{M o{\\mathrm{-}}C}$ species reported for $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ . 32 This shift to higher BEs for the MXenes, compared to their parent MAX phases, is typical and is due to the replacement of the “A” element by more electronegative surface terminations species such as O, OH, and/or F. 34 \n\nFigure 3b shows the high-resolution spectrum in the C 1s region that was fitted by components corresponding to Mo C, $\\mathsf{C}{\\mathrm{-}}\\mathsf{C}$ , $\\mathrm{CH}_{x},$ C O, and COO species. The presence of all but the $\\scriptstyle{\\mathrm{Mo-C}}$ species, result from the TBAOH intercalations, and/or the exposure of this high-surface area material to the ambient during filtration and storage. The peak at a BE of $283.1\\ \\mathrm{eV}$ was assigned to the $\\scriptstyle{\\mathrm{Mo-C}}$ species and represents $10\\%$ of the C 1s region. Note that this does not imply that the amount of MXene is $10\\%$ , but rather the fact that thin carbonaceous layers form on the surfaces of the powders. Etching with Ar ions removes the latter. 34 \n\n![](images/39e7cfad0b696f89d69f2b3aac3320abba3ad0f81e7c752d58851b2d62edb7b2.jpg) \nFigure 3. XPS spectra of $d\\mathbf{\\cdot}\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ “paper” for, a) Mo 3d, b) C 1s, c) O 1s and, d) F 1s regions. Vertical lines represent the various assigned species (see Table S2 in the Supporting Information). \n\nFigure 3c plots the high-resolution spectrum in the O 1s region which was fitted by components corresponding to the following species: $\\mathrm{Mo}_{2}\\mathrm{O}_{5}$ and/or $\\mathrm{MoO}_{3}$ $\\mathrm{Mo}_{2}\\mathrm{CO}_{x},$ $\\mathrm{Mo}_{2}\\mathrm{C}(\\mathrm{OH})_{2}$ and $\\mathrm{Mo}_{2}\\mathrm{C}(\\mathrm{OH})_{x}–\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ The $\\mathbf{Mo}_{2}\\mathbf{O}_{5}$ and/or $\\mathbf{MoO}_{3}$ species arise from surface oxidation. The peaks at 531.1, 532.2, and $533.4\\ \\mathrm{eV}$ were assigned, respectively, to $\\mathrm{Mo}_{2}\\mathrm{CO}_{x}$ $_{(-0}$ terminated), $\\mathrm{Mo}_{2}\\mathrm{C}(\\mathrm{OH})_{x}$ $-\\mathrm{OH}$ terminated) and $\\mathrm{Mo}_{2}\\mathrm{C}(\\mathrm{OH})_{x}–\\mathrm{H}_{2}\\mathrm{O}_{\\mathrm{ads}}$ $_\\mathrm{(-OH}$ terminated with strongly adsorbed water). 34 The highresolution spectrum in the $\\mathrm{~F~}$ 1s region (Figure 2d) was fitted by one component at a BE of $685.5\\ \\mathrm{eV},$ which most probably corresponds to a $-\\mathrm{F}$ surface termination $(\\mathrm{Mo}_{2}\\mathrm{CF}_{x})$ . This assignment is close to that made by Park et al. who assigned a BE of $685.0\\mathrm{eV}$ to fluorine atoms bonded to Mo. 35 \n\nBased upon the atomic percentage of Mo, C, O, and F and the fraction of the species related to the MXenes, the chemical formula that best describes the “paper” is $\\mathrm{Mo_{2}C O_{0.6}(O H)_{0.4}(O H-H_{2}O)_{0.6}F_{0.1}}$ The fraction of F-terminations here is low compared to other MXenes etched by HF or LiF and HCl, 34 which is not too surprising since it has been shown that treating $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x},$ $\\mathrm{Ta}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathrm{V}_{2}\\mathrm{CT}_{x}$ with TBAOH resulted in a significant reduction in their F content. 8,29 Similar reductions in the fraction of F-terminations were reported after treating $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ with hydroxide solutions such as KOH due to the thermodynamic instability of the $_{\\mathrm{Ti-F}}$ bonds in high pH solutions. 36 It is thus reasonable to assume that the same is occurring here. Note that we were not able to identify or quantify the nitrogen associated with the TBAOH, since the N 1s region coincides with the Mo 3p region. \n\n# 2.2. Electrical Transport \n\nThe transport properties were investigated by measuring the resistivity, $\\rho$ of a $9~{\\upmu\\mathrm{m}}$ $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ “paper” before, and after, annealing at ${\\approx}120~^{\\circ}\\mathrm{C}$ in vacuum for $^{18\\mathrm{~h~}}$ As shown in Figure 4a, before annealing, $\\rho$ increases from 0.6 to $124~\\Omega$ m as the temperature is reduced from 300 to $10\\mathrm{~K~}$ (top curve in Figure 4a). After annealing, $\\rho$ increased from $2.3\\times10^{-3}$ to $33\\times10^{-3}\\Omega\\mathrm{~m~}$ (bottom curve in Figure 4a) over the same temperature range. It follows that this mild vacuum annealing reduced $\\rho$ at $300\\mathrm{~K~}$ and $10\\mathrm{~K~}$ by factors of ${\\approx}250$ and ${\\approx}3700$ , respectively. Note that in both cases, the resistivity increased with decreasing temperatures. \n\nTo shed light more light on the conduction mechanism, the resistivity data in the 10 to $50~\\mathrm{K}$ temperature range measured before and after annealing were evaluated using the logarithmic derivative method, 37,38 in which the natural logarithm of $W$ is plotted against ln $T$ where $\\displaystyle{\\mathbf{}}W=-\\frac{d(\\ln\\rho)}{d(\\ln(T)}$ (Figure 4b). The slope of such plots is the exponent $m$ (except in the case where the slope is 0) in the equation \n\n$$\n\\rho\\approx\\rho_{\\mathrm{0}}\\mathrm{exp}{\\left(\\frac{T_{\\mathrm{0}}}{T}\\right)}^{m}\n$$ \n\nwhere $\\rho_{0}$ is a prefactor. 37 The exponents $m=0.5$ , 0.33, 0.25, and 0 are consistent with the following models: Efros–Shklovskii (E–S) variable range hopping (VRH), 2D VRH, 3D VRH, and transport following a power-law (non-exponential) temperature dependence, respectively. \n\nWhile the results of the logarithmic derivative method are somewhat noisy (Figure 4b, before annealing top, after annealing bottom), some conclusions can nevertheless be drawn. The effect of annealing is to increase m from ${\\approx}0.25$ to 0.33–0.5 (compare upper and lower plots in Figure 4b). Note that the transport data before, and after, annealing - shown, respectively, in Figures S7 and S8 in the Supporting Information - poorly fit a thermally activated process or a weak localization model. The transport results also suggest a change in transport mechanism in the low-temperature regime after \n\n![](images/56b95497ab5cb8d10f700b33636109b009d513ec17d758e5ddf1b3b15ebdf55f.jpg) \nFigure 4. Dependence of the electrical behavior of $d\\mathbf{-}\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ “paper” on temperature and magnetic field. a) Resistivity versus temperature from 10 to $300~\\mathsf{K},$ before annealing, and after annealing in vacuum at ${\\mathsf{120}}^{\\circ}{\\mathsf{C}}$ . Inset showing the SEM cross section image of $d{\\cdot}\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ “paper” tested. b) Temperature-dependent resistivity evaluated from 10 to $50~\\mathsf{K}$ using a logarithmic derivative method, color codes are the same as Figure a. Slopes associated with E–S VRH $(m=0.5)$ ), 2D VRH $(m=0.33$ ), 3D VRH $m=0.25)$ , and power law $(m=0)$ , are shown for comparison. c) Magnetoresistance at $\\mathsf{\\tau}_{\\mathsf{l}0\\mathsf{K}}$ of the sample after annealing. $R_{\\mathsf{H}=0}$ refers to the $d\\mathrm{-}\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ “paper” resistance in the absence of applied magnetic field. \n\n# www.MaterialsViews.com \n\nannealing. This change may be due to the de-intercalation of the TBAOH and water after annealing. XRD patterns (Figure S9, Supporting Information) show a decrease in the $\\boldsymbol{c}$ -LP after annealing from 37.7 to $25.5\\mathrm{~\\AA~}$ , confirming the de-intercalation. These results suggest that it is possible to alter the electronic behavior of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ by simply changing the chemistry of the intercalant. Similar effects were previously observed for $\\mathrm{TaS}_{2}$ For example, Sarma et al. observed an increase in $\\rho$ , and a change in the slopes of the $\\rho$ versus $T,$ of octahedral $\\mathrm{Ta}\\mathrm{S}_{2}$ crystals when intercalated with hydrazine. In that case m decreased from 0.5 to 0.33 upon intercalation. 39,40 \n\nThe MR measured at $10~\\mathrm{~K~}$ on the annealed “paper” (Figure 4c) is positive. This result is in contrast to the recent paper by Xu et al. who reported a negative MR for a $3.4\\mathrm{nm}$ thick $\\mathsf{M o}_{2}\\mathsf{C}$ crystal, consistent with a weak localization model. 28 It is also different from the behavior we reported for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ thin films. 7 The difference in both the shape of $\\rho$ versus $T$ and the sign of the MR suggests that the dominant scattering/transport mechanisms in $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ differ from $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ but is similar to $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ 41 $\\mathrm{Mo}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ shows semiconductor-like behavior with VRH mechanism at low temperatures, unlike $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ which showed metallic behavior with weak localization at low temperatures. 7 Based on the totality of these results it is reasonable as this juncture to conclude that it is possible to change the transport properties of $\\mathrm{Mo}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ by simply varying the nature and/or presence of surface terminations. \n\n# 2.3. Electrochemical Energy Storage Properties \n\nAs demonstrated above, the room temperature (RT) resistivity of the $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ “paper” is roughly eight orders of magnitude lower than $\\mathrm{MoO}_{3}$ 42 However, the latter have been shown to be a promising electrode material for energy storage applications due to molybdenum’s ability to change its oxidation state. 43,44 Yet, their low conductivity limits the cycle-life and leads to poor rate performance. 45 This in turn encouraged us to explore the potential of the $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ free-standing “paper” as an electrode in supercapacitors and Li-ion batteries since: i) as noted above, $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ is a far better electrical conductor than Mo oxides and, ii) both materials have a similar surface chemistry; according to our XPS results, the surface of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ is terminated with O and OH. \n\n# 2.3.1. Electrochemical Performance in Supercapacitors \n\nElectrodes of $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ “paper”, $2\\ \\upmu\\mathrm{m}$ thick, were tested in a three-electrode configuration using $\\mathrm{\\sfAg/AgCl}$ as a reference electrode and an overcapacitive activated carbon as a counter electrode in a 1 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte. Figure 5a shows the cyclic voltammetry (CV) profiles collected at $20\\ \\mathrm{mV\\{s}^{-1}}$ over two different voltage windows. For the most part, testing was carried out between $-0.30$ and $0.30\\mathrm{V}$ versus $\\mathrm{\\sfAg/AgCl}$ . The non-rectangular shape of the CV loops is most probably related to the pseudocapacitive charge storage mechanism, as demonstrated for $\\mathrm{MoO}_{3-x}$ in neutral salt electrolytes and for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ in $1\\mathrm{~M~H}_{2}\\mathrm{SO}_{4}$ 44,46 \n\nThe rate performance of this $2\\upmu\\mathrm{m}$ thick “paper” is summarized in Figure 5b. At $2~\\mathrm{mV}~\\mathrm{s}^{-1}$ the gravimetric capacitance is $196\\mathrm{F}\\:\\mathrm{g}^{-1}$ while at $100\\mathrm{mVs^{-1}}$ it drops to $120\\mathrm{~F~g^{-1}}$ (left $\\gamma$ -axis in Figure 5b). The respective volumetric capacitances (right y-axis, Figure 5b) are 700 and $430\\ \\mathrm{F\\cm^{-3}}$ Figure 5c shows no degradation in performance, even after 10,000 galvanostatic charge/ discharge cycles performed at a current density of $10\\mathrm{~A~g^{-1}}$ showing almost perfectly linear charge/discharge profiles (see inset in Figure 5c). \n\nThis high specific capacitance and good rate capability can be attributed to two important features of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ a transition metal oxide/hydroxide surface chemistry as shown by XPS analysis and a conductive carbide backbone as shown by the transport measurements. Said otherwise, the transition metal oxide/hydroxide surface of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ is electrochemically active and leads to high capacitance like $\\mathrm{MoO}_{3}$ However, the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ “paper” has a good rate capability because of the relatively high intrinsic conductivity of the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ flakes and good inter-flake conductivity due to their dense stacking. However, tight re-stacking may also impede the diffusion of ions between the layers and optimization of the electrode architecture should be done before transitioning to testing thick electrodes. \n\n![](images/c98e8e30375a9fa4926c30ed2b4a14610613fe233932a52eb4f2a63719c449ba.jpg) \nFigure 5. Electrochemical performance of 2 μm thick $d\\mathbf{\\cdot}\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ “paper” in 1 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ : a) CV curves as a function of potential window. The coulombic efficiencies for different voltage windows, at $20\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ , are shown on graph. b) Gravimetric (left y-axis) and volumetric (right y-axis) rate performance on charging and discharging. c) Capacitance retention test up to 10,000 cycles at $\\mathsf{10A g^{-1}}$ . Inset shows galvanostatic cycling plot. \n\n![](images/c04f08f4bcd5d17d3223590c6708e3197290259cc0b9ef92a6a5ee70871347c0.jpg) \nFigure 6. Electrochemical performance of $d{\\cdot}\\mathsf{M o}_{2}\\mathsf{C T}_{x}{\\mathrm{-}}\\mathsf{C N T}$ “paper” as a Li anode: a) CVs at $0.2\\ m\\vee s^{-1}$ . b) Galvanostatic cycling between $5~\\mathsf{m V}$ and $3\\lor$ versus $\\mathsf{L i}/\\mathsf{L i^{+}}$ at $0.4\\mathsf{A}\\mathsf{g}^{-1}$ after first cycle at $\\mathsf{l}0\\mathsf{m}\\mathsf{A}\\mathsf{g}^{-1}$ . c) Capacity versus cycle number for cells tested at $0.4\\mathsf{A}\\mathsf{g}^{-1}$ (red), $5\\mathsf{A}\\mathsf{g}^{-1}$ (blue), $\\mathsf{10A g^{-1}}$ (orange) and the corresponding columbic efficiency (top blue curve, right y-axis) for the cell cycled at $5\\mathsf{A}\\mathsf{g}^{-1}$ . Inset is a zoom-in on the area outlined by the red dotted square focusing on the performance of the cell cycled at $0.4\\mathsf{A g}^{-1}$ . \n\n# 2.3.2. Electrochemical Performance of $d–M o_{2}C T_{x}$ –CNT as Anode in Li-ion Batteries \n\nThe CV plots of $3~{\\upmu\\mathrm{m}}$ thick $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ –CNT “paper” electrodes (Figure 6a) showed a lithiation peak around $0.1\\mathrm{\\V}$ versus $\\mathrm{{Li/Li^{+}}}$ during the first cycle. This peak shifts to $0.13~\\mathrm{V}_{:}$ , and becomes more intense, during the second cycle. With further cycling, however, the intensity of the peak decreases while its position fluctuates. After 20 cycles, the peak intensity stabilizes at ${\\approx}0.15\\mathrm{~V~}$ (Figure 6a). Another weak lithiation peak emerges after the first cycle around $1.34\\mathrm{~V~}$ and its intensity increases slightly with cycling. Its position also changes with cycling till it reaches ${\\approx}1.4\\mathrm{V}$ after 30 cycles. \n\nDuring delithiation, a similar trend of decreasing intensity and fluctuations of position was observed for the peak that initially was located at $1.5\\mathrm{~V~}$ and ended at ${\\approx}1.45\\ \\mathrm{V},$ after 30 cycles. Another delithiation peak – observed around $2.6\\mathrm{~V~}$ during the first cycle – intensifies with cycling and its position shifts to $2.64\\mathrm{V}$ after 30 cycles. In other Mo-based, systems such behavior (peaks evolutions and devolution in addition to shifting) was observed, and attributed to phase transformations between various oxides. For example, between monoclinic and orthorhombic phases during cycling. 47,48 \n\nFigure 6b shows the voltage profile for a cell cycled at $10\\ \\mathrm{mA}\\ \\mathrm{g}^{-1}$ for the first cycle and then at $0.4\\mathrm{~A~g^{-1}}$ for all subsequent ones. Voltage plateaus were observed around $0.4\\mathrm{V}$ during the first lithiation cycle and around $1.28{\\mathrm{V}}$ during the first delithiation cycle (Figure 6b). A capacity of $821\\mathrm{~mAh~g^{-1}}$ was achieved during the first lithiation cycle, but only $76\\%$ of that capacity was recovered upon delithiation. First cycle irreversibility remains a challenge for MXenes tested for LIBs. This irreversibility has been attributed to the formation of a solid electrolyte interphase (SEI), and/or the trapping of Li through irreversible reactions with either surface terminations or other species in-between the $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x}$ layers. 49 However, the first-cycle irreversibility of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ was lower compared to that reported for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and other MXenes. 10,11,50–52 Note that more than $2/3$ of the capacity is stored at voltages below $0.5~\\mathrm{V},$ which suggests that $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ could well be used as an anode material. \n\nAfter the first cycle, carried out a $10\\mathrm{\\mA\\g^{-1}}$ the capacity drops to $423\\ \\mathrm{mAh\\g^{-1}}$ Thereafter, the cycling rate was increased to 0.4 A $\\boldsymbol{\\mathrm{g}}^{-1}$ (inset in Figure 6c). At that rate, the capacity continuously increased with further cycling until it reached $560\\ \\mathrm{mAh\\{g}^{-1}}$ after 70 cycles (Figure 6c). A similar increase in capacity with cycling was reported before for $\\mathrm{MoO}_{2}/\\mathrm{Mo}_{2}\\mathrm{C}$ hetero-nanotubes and was explained by a gradual reduction of the $\\mathrm{Li}_{x}\\mathrm{MoO}_{2}$ phase relative to Mo. 48 The same argument can be used here for $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ since, as shown above, surface oxide species are present. Enhanced electrode accessibility to ions after cycling could be another reason for the observed increases in capacity. \n\nThe capacity shown by $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ is higher than the theoretical capacity of graphite anodes $(372\\ \\mathrm{mAh\\g^{-1}},$ . 53 Compared to other Mo-based systems, however, this capacity is $\\approx7\\%$ lower than what was reported for $\\mathsf{M o}_{2}\\mathrm{C}$ nanoparticles anchored on graphene $(601\\mathrm{~mAh~g^{-1}}$ at $0.4\\mathrm{~A~g^{-1}})$ at the same rate, 54 and ${\\approx}10\\%$ lower than what was reported for $\\mathrm{MoO}_{2}/\\mathrm{Mo}_{2}\\mathrm{C}$ heteronanotubes at slightly higher rates $(623\\mathrm{\\mAh\\g^{-1}}$ at $0.5\\mathrm{A}\\mathrm{g}^{-1})$ . 48 However, this is the first study on $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ MXene and it is reasonable to assume that optimization of the electrode chemistry and architecture would result in major improvements in capacity, as previously observed for other MXenes. 10,50,55 \n\nThe $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ \n\n–CNT films also showed excellent capability to handle quite high cycling rates. At 5 A $\\mathbf{g}^{-1}$ $(\\approx20~\\mathrm{C})$ a reversible capacity of ${\\approx}250\\ \\mathrm{mAh\\g^{-1}}$ with coulombic efficiency of $599\\%$ was retained after 1,000 cycles (Figure 6c). Even at $10\\mathrm{Ag^{-1}}(\\approx131\\mathrm{C})$ a stable reversible capacity of $76\\mathrm{\\mAh\\g^{-1}}$ was measured even after 1,000 cycles. This suggests $d{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ –CNT electrodes could be used as electrodes in high-power batteries or Li-ion capacitors. While the electrodes tested here are relatively thin, in future work, like for other MXenes, thicker electrodes will be tested. For example, $300\\upmu\\mathrm{m}$ thick discs $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathrm{Nb}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ were successfully tested as electrodes for LIBs. 55 Although they showed a lower gravimetric capacity compared to commercial graphite, their areal capacities were higher. 55 There is no reason to believe that similar behavior will not be observed for $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}$ \n\n# 3. Conclusions \n\nHerein we report, for the first time, on the large-scale synthesis of 2D $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ flakes via selective etching of Ga from $\\mathtt{M o}_{2}\\mathtt{G a}_{2}\\mathrm{C}$ powders using two different etchants and subsequent \n\n# www.MaterialsViews.com \n\ndelamination. The morphologies of the produced flakes depended on the etchant type and delamination method. Etching with LiF/HCl solutions produced less defective flakes as compared to those etched with HF, followed by TBAOH treatment. Furthermore, sonication tends to break the flakes into smaller sizes, but produces a higher fraction of single-layer flakes as compared to mild agitation via hand shaking alone. \n\nAnnealing the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ “paper,” drives out the TBAOH molecules present after delamination – as evidenced by a large contraction in the $\\boldsymbol{c}$ -axis lattice parameter – results in an almost three orders of magnitude decrease in resistivity at RT. The resistivity decreases with increasing temperature, and its temperature dependence changes after annealing, indicating a change in transport mechanism(s). At $10\\mathrm{~K~}$ , the magnetoresistance is positive. Based on these preliminary results we conclude that $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ exhibits semiconducting-like behavior with VRH transport mechanism at low temperatures. \n\nThe volumetric capacitance of $2~{\\upmu\\mathrm{m}}$ thick delaminated $\\mathrm{Mo}_{2}\\mathrm{CT}_{{x}}$ “paper” in 1 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ reached $700\\ \\mathrm{F}\\ \\mathrm{cm}^{-3}$ at $2\\mathrm{mVs^{-1}}$ The capacitance retention was excellent, with almost no degradation after 10,000 charge/discharge cycles. \n\nWhen a $3\\upmu\\mathrm{m}$ thick delaminated $\\mathrm{Mo}_{2}\\mathrm{CT}_{x}\\mathrm{-}\\mathrm{CNT}$ “paper” electrode was tested against Li, a reversible capacity of $560\\mathrm{mAh}\\mathrm{g}^{-1}$ was achieved at $0.4\\mathrm{~A~g^{-1}}$ with more than $2/3$ of the lithiation capacity stored at voltage below $0.5\\mathrm{~V~}$ versus $\\mathrm{Li/Li^{+}}$ As importantly, at rates of 5 and $10\\ \\mathrm{Ag^{-1}}$ reversible stable capacities of 250 and $75~\\mathrm{mAh~g^{-1}}$ were achieved, respectively, for over a 1,000 cycles, making it a promising anode material for high power batteries and Li-ion capacitors. \n\n# 4. Experimental Section \n\nSynthesis of $M o_{2}G a_{2}C$ : Powders of ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ were synthesized by a solid liquid reaction of ${\\mathsf{M o}}_{2}\\mathsf{C}$ and Ga. The details can be found in Ref. 25 . In brief, a $-325$ mesh ${\\mathsf{M o}}_{2}{\\mathsf{C}}$ powder and Ga (both from Alfa Aesar, Ward Hill, MA, both of $99.5~\\mathrm{wt\\%}$ purity) were mixed in a 1:8 molar ratio and placed in a quartz tube that was evacuated using a mechanical vacuum pump and sealed. The latter was placed in a horizontal tube furnace that was heated at a rate of $10^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ to $850~^{\\circ}\\mathsf{C},$ and held at that temperature for $48\\mathrm{~h~}$ . After furnace cooling, the lightly sintered material was crushed, using a mortar and pestle, and returned back to the quartz tube. The latter was evacuated, etc. and re-heated at a rate of $10\\ ^{\\circ}\\mathsf{C}\\ \\mathsf{m i n^{-1}}$ to $850~^{\\circ}\\mathsf{C}$ and held at temperature for $\\mathsf{16~h}$ more. Rietveld refinement of the XRD patterns for ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ (not shown) indicated that $<20\\ \\mathrm{wt\\%}$ ${\\mathsf{M o}}_{2}{\\mathsf{C}}$ was present in the powders as a secondary phase. \n\nOne gram of the lightly sintered ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ compact was immersed in a $20~\\mathsf{m L}$ of a $\\mathsf{l}2\\mathsf{\\Pi}\\mathsf{M}\\mathsf{\\Pi}\\mathsf{H}\\mathsf{C}\\mathsf{I}$ solution (technical grade, Fisher Scientific, Fair Lawn, NJ) for $^{2\\mathrm{~d~}}$ , at RT - while being stirred using a Teflon coated magnet on a stir plate - to dissolve any unreacted Ga. The powders were washed with DI water several times till a $\\mathsf{p H}$ of ${\\approx}6$ was reached, then dried by filtration using a nanoporous polypropylene membrane (3501 Coated PP, $0.064~\\upmu\\mathrm{m}$ pore size, Celgard, USA). \n\nSynthesis of 2D $M o_{2}C T_{x}$ : LiF and HCl Route: One gram of ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ powder was added to $20~\\mathsf{m L}$ of a premixed solution of $3\\mathrm{~M~}$ of LiF $(90+\\%)$ Ward Hill, MA, Alfa Aesar) and $12\\upmu$ HCl. The ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ containing mixture was placed on a magnetic stirrer hot plate in an oil bath held at $35^{\\circ}C$ for various times. Afterwards, the mixture was washed, through three cycles of $\\mathsf{\\textsf{l}}_{\\mathsf{M}}\\mathsf{H}{\\mathsf{C}}|$ solution, followed by three cycles of 1 M of aqueous LiCl (Alfa Aesar, $98+\\%$ ), and finally several cycles of DI water until the supernatant reached a pH of approximately 6. In each cycle, the washing was performed by adding $40~\\mathsf{m L}$ of the solution to the washed powders in a centrifuge tube, and the tube was hand-shaken for 1 min before centrifuging at \n\n5000 rpm for 2 min. Twenty milliliters of argon, Ar, deaerated DI water were then added to the washed powder, which was then hand shaken for 5 min., followed by centrifuging for $\\rceil\\boldsymbol{\\mathsf{h}}$ at 5000 rpm. The supernatant was collected for further investigation. The settled powder was discarded. \n\nHF and TBAOH Route: Powders of ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ were immersed, slowly, in a bottle containing $\\mathsf{l}4\\mathsf{m}\\mathsf{H}\\mathsf{F}$ solution (Fisher Scientific, Fair Lawn, NJ) in a ratio of $\\texttt{l g}$ to $40~\\mathsf{m L}$ . Afterwards the bottle was placed in an oil bath over a stirred hot plate held at $55^{\\circ}C$ for $\\mathsf{l}60\\mathsf{h}$ , while stirring using a Teflon coated magnet. The resulting suspension was washed with DI water through several cycles till a pH of ${\\approx}6$ was reached. In each cycle, the washing was performed by adding $40~\\mathrm{mL}$ of DI water to a centrifuge tube containing the sediment, and then the tube was hand-shaken for 1 min before centrifuging at 5000 rpm for $2\\min$ . \n\nThe settled powder was removed from the centrifuge tube and filtered through a nanoporous polypropylene membrane (3501 Coated PP, $0.064~\\upmu\\mathrm{m}$ pore size, Celgard, USA) for further investigation. \n\nOne gram of this filtered powder was added to a $70\\mathsf{m L}$ of an aqueous solution of $54-56~\\mathrm{wt\\%}$ TBAOH, $(C_{4}H_{9})_{4}N O H$ , (Sigma Aldrich, St. Louis, MO, USA). The mixture was stirred at RT for $^{\\dag8\\mathrm{~h~}}$ after which it was washed three times using $40~\\mathsf{m L}$ Ar-deaerated DI water each time. The sediment was then used for further characterization and delamination. \n\nGeneral Characterization Methods: The microstructures and morphologies of the various samples and powders were characterized by TEM (JEOL JEM-2100, Japan) using an accelerating voltage of $200\\ \\mathsf{k V}.$ The TEM samples were prepared by dropping several drops of the sample, diluted in DI water, onto a copper grid and dried in air. SEM was performed using Zeiss Supra 50VP (Carl Zeiss SMT AG, Oberkochen, Germany). \n\nAn XRD diffractometer (Rigaku Smartlab (Tokyo, Japan) equipped with Cu $\\mathsf{K}\\alpha$ radiation $40~\\mathsf{k V}$ and $44~\\mathsf{m A}$ ) was used for phase identification. A step scan $0.02^{\\circ}$ , time per step 2 s, $\\mathsf{10}\\times\\mathsf{10}\\mathsf{m}\\mathsf{m}^{2}$ window slit was used. \n\nXPS spectra of the $d\\mathrm{-}\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ “paper” were measured by a spectrometer (Physical Electronics, VersaProbe 5000, Chanhassen, MN) employing a $100\\upmu\\mathrm{m}$ monochromatic Al $\\mathsf{K}\\alpha$ X-ray beam to irradiate the sample surface. Photoelectrons were collected by a $\\overline{{180^{\\circ}}}$ takeoff angle between the sample surface and the path to the analyzer. Charge neutralization was performed using a dual beam charge neutralizer irradiating low-energy electrons and ion beam to avoid shift in the recorded BE. High-resolution spectra for Mo 3d, C 1s, O 1s, F 1s, and Ga 2p were taken at a pass energy of $\\mathsf{11.75~e V}$ with a step size of $0.05\\ \\mathrm{eV.}$ The binding energy scale of all XPS spectra was references to the Fermi-edge (E ), which was set to a BE of zero eV. To obtain the spectra a free-standing film was mounted on a double sided tape and was electrically grounded using a copper wire. The quantification, using the obtained core-level intensities, and peak fitting of the core-level spectra was performed using a software package (CasaXPS Version 2.3.16 RP 1.6). Prior to both the quantification and peak fitting the background contributions were subtracted using a Shirley function. The intensity ratios of the $3\\mathrm{d}_{5/2}$ and $3\\mathsf{d}_{3/2}$ peaks were constrained to be 3:2. \n\nThe temperature-dependent in-plane resistivity measurements were performed in a Physical Property Measurement System (Quantum Design, San Diego). A linear, four-point probe geometry was used. Gold wires were attached to the films using silver paint. Positive and negative currents were applied, at each temperature, to eliminate any thermal effects. The error in the resistivity values is estimated to be ${\\approx}5\\%$ , corresponding to the uncertainty in the sample thickness. The MR measurements were performed with a magnetic field, up to $\\pm9\\ T,$ applied out of the plane of the film. \n\n# Electrochemical Characterization \n\nSupercapacitors: Activated carbon electrodes were prepared by mixing activated carbon (YP-40) with $5\\mathrm{\\Delta\\wt\\%}$ polytetrafluroetylene (PTFE) in ethanol on a magnetic stirring plate for $24\\ h$ at $25^{\\circ}C$ . The powders were then kneaded, rolled, and cut into thin discs with a diameter of $9\\mathsf{m m}$ . \n\nThe $\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ electrodes were prepared from delaminated $\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ flakes obtained by HF etching of ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}_{1}$ , followed by TBAOH intercalation, as described above. After TBAOH treatment, the sediment was mixed with DI water $(\\mathsf{l}\\mathrm{~}\\mathsf{g}\\mathsf{M}\\mathsf{o}_{2}\\mathsf{C}\\mathsf{T}_{x}$ per $70~\\mathsf{m L}$ of water), deaerated using Ar gas, followed by sonication in an ice-cooled ultrasonic bath for $\\bar{1}\\ h$ . The mixture was then centrifuged for $\\texttt{l h}$ at $5000~{\\mathsf{r p m}}$ , and the supernatant, which was dark purple in color, was collected. The latter was further diluted, with deaerated DI water, to a concentration of $1\\:\\mathrm{\\mg}\\:\\mathrm{\\mL^{-1}}$ . The diluted suspension was vacuum-filtered onto nanoporous polypropylene membranes (Celgard 3501, $0.064\\ \\upmu\\mathrm{m}$ pore size, Celgard LLC) in air. The $d{\\cdot}\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ “paper” was easily separated from the membrane to obtain free-standing ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ electrodes that were ${\\approx}2~{\\upmu}{\\m m}$ thick. \n\nThe electrodes with mass loading of $0.6~\\mathsf{m g}~\\mathsf{c m}^{-2}$ were assembled in a three-electrode Swagelok cell with platinum current collectors, a polypropylene separator (Celgard 3501, Celgard LLC), and a reference electrode of $\\mathsf{A g/A g C l}$ in KCl. CV and galvanostatic cycling were performed using a potentiostat (VMP3, Biologic, France). After an initial pre-cycling step to stabilize the current–voltage characteristic, the CV scans were performed at rates ranging from 2 to $\\mathsf{l o o}\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . Galvanostatic charge– discharge tests were also performed on a two electrode Swagelok cell with an activated carbon counter electrode for 10,000 cycles using a current density of $\\mathsf{10A g^{-1}}$ . \n\nLi-Ion Electrodes: The $d{\\cdot}\\mathsf{M o}_{2}\\mathsf{C T}_{x}{\\mathrm{-}}\\mathsf{C N T}$ paper electrodes were prepared using an alternating vacuum-assisted filtration approach similar to what was described in Ref. 56 In brief, delaminated ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ in DI water $(\\approx2~{\\mathsf{m g}}$ $m\\mathsf{L}^{-1})$ and CNT dispersed in DI water $(\\approx0.2\\ \\mathrm{mg\\mL^{-1}};$ ) were alternately filtered to create a layered MXene/CNT structure. The CNT dispersion used in this study was achieved by sonicating $20~\\mathsf{m g}$ of multi-walled CNTs in $700~\\mathsf{m L}$ of DI water that contained $10\\mathrm{\\Omega}\\mathrm{wt}\\%$ sodium dodecyl sulfate $(299\\%$ , Sigma-Aldrich, St. Louis, MO, USA) for $0.5{\\mathrm{~h~}}$ . One mL of ${\\mathsf{M o}}_{2}{\\mathsf{C T}}_{x}$ suspension was filtered, first through a mixed cellulose esters membrane ( $50\\mathsf{n m}$ , MF-Millipore, EMD Millipore, Darmstadt, Germany), and then $7m L$ of CNT suspension was filtered. This alternating filtration process was repeated 10 times. At the end, another $1m L$ of the $\\mathsf{M o}_{2}\\mathsf{C T}_{x}$ suspension was filtered. The composite film were left to dry at RT in air for $\\rceil8\\mathrm{~h~}$ . Afterward, the MXene–CNT “paper” $(\\approx8\\ \\mathrm{wt\\%}$ CNT), with a thickness of ${\\approx}3~{\\upmu}{\\m m}$ , was readily peeled off the membrane and further dried under vacuum at $90^{\\circ}\\mathsf{C}$ for $\\rceil8\\mathrm{~h~}$ prior to testing. \n\nTo test the performance of this $d{\\cdot}\\mathsf{M o}_{2}\\mathsf{C T}_{x}{\\mathrm{-}}\\mathsf{C N T}$ composite electrode, stainless steel coin cells (CR-2032, Hohsen Corp., Osaka, Japan) were assembled in an Ar-filled glovebox $(\\mathsf{O}_{2}$ and ${\\sf H}_{2}{\\sf O}<{\\sf1}$ ppm) using an automatic crimping machine (Hohsen Corp., Osaka Japan). In the coin cells, Li foil was used as a counter electrode; the working electrode was the free-standing $\\mathsf{M o}_{2}\\mathsf{C T}_{x}\\mathsf{-C N T}$ paper, with a mass loading of $0.9~\\mathsf{m g}~\\mathsf{c m}^{-2}$ . The two electrodes were separated by borosilicate glass fiber paper (Whatman GF/A, Buckinghamshire, UK) that was soaked with an electrolyte of $1.2\\textsf{M}\\mathsf{L i P F}_{6}$ solution in a mixture of ethylene carbonate, EC, and dimethyl carbonate, DMC in a 1:2, respectively by weight ratio. \n\nThe CVs were recorded at a rate of $0.2\\ m\\vee\\ s^{-1}$ between $3.0~\\mathrm{V}$ and $5.0~\\mathsf{m V}$ using a potentiostat (VSP300, Biologic, Claix, France), while the galvanostatic cycling between $5.0~\\mathsf{m V}$ and $3.0\\mathrm{V}$ at different currents was conducted using a battery cycler (Series 4000 MACCOR Inc., Tulsa OK, USA). Both tests were carried out at $25^{\\circ}C$ . \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nS.K., M.R.L., and M.N. contributed equally to this work. The authors acknowledge the support from the Swedish Research Council (Project Grant No. 621-2012-4430), the Swedish Foundation for Strategic Research through the Synergy Grant FUNCASE Functional Carbides for Advanced Surface Engineering (M.W.B. and J.H.). M.N. and J.N. were supported by the Laboratory Directed Research and Development \n\nProgram of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy. E.J.M and S.J.M. acknowledge support from the U.S. Army Research Office (grant number W911NF15-1-0133). The authors also acknowledge Dr. Chunfeng Hu for his help regarding the synthesis of ${\\mathsf{M o}}_{2}{\\mathsf{G a}}_{2}{\\mathsf{C}}$ powders. \n\nReceived: December 10, 2015 \nRevised: January 14, 2016 \nPublished online: February 17, 2016 \n\n[1] K. S. Novoselov, V. I. Fal’ko, L. Colombo, P. R. Gellert, M. G. Schwab, K. Kim, Nature 2012, 490, 192. [2] M. Xu, T. Liang, M. Shi, H. Chen, Chem. Rev. 2013, 113, 3766. [3] R. Mas-Balleste, C. Gomez-Navarro, J. Gomez-Herrero, F. Zamora, Nanoscale 2011, 3, 20. [4] M. Naguib, O. Mashtalir, J. Carle, V. Presser, J. Lu, L. Hultman, Y. Gogotsi, M. W. Barsoum, ACS Nano 2012, 6, 1322. [5] M. Naguib, V. N. Mochalin, M. W. Barsoum, Y. Gogotsi, Adv. Mater. 2014, 26, 992. \n[6] M. Naguib, M. Kurtoglu, V. Presser, J. Lu, J. J. Niu, M. Heon, L. Hultman, Y. Gogotsi, M. W. Barsoum, Adv. Mater. 2011, 23, 4248. [7] J. Halim, M. R. Lukatskaya, K. M. Cook, J. Lu, C. R. Smith, L. A. Naslund, S. J. May, L. Hultman, Y. Gogotsi, P. Eklund, M. W. Barsoum, Chem. Mater. 2014, 26, 2374. \n[8] M. Ghidiu, M. R. Lukatskaya, M. Q. Zhao, Y. Gogotsi, M. W. Barsoum, Nature 2014, 516, 78. [9] M. R. Lukatskaya, O. Mashtalir, C. E. Ren, Y. Dall’Agnese, P. Rozier, P. L. Taberna, M. Naguib, P. Simon, M. W. Barsoum, Y. Gogotsi, Science 2013, 341, 1502. \n[10] D. Er, J. Li, M. Naguib, Y. Gogotsi, V. B. Shenoy, ACS Appl. Mater. Interfaces 2014, 6, 11173. \n[11] M. Naguib, J. Halim, J. Lu, K. M. Cook, L. Hultman, Y. Gogotsi, M. W. Barsoum, J. Am. Chem. Soc. 2013, 135, 15966. \n[12] Y. Xie, Y. Dall’Agnese, M. Naguib, Y. Gogotsi, M. W. Barsoum, H. L. Zhuang, P. R. Kent, ACS Nano 2014, 8, 9606. \n[13] X. Liang, A. Garsuch, N. F. Nazar, Angew. Chem. Int. Ed. 2015, 54, 3907. \n[14] O. Mashtalir, M. R. Lukatskaya, M. Q. Zhao, M. W. Barsoum, Y. Gogotsi, Adv. Mater. 2015, 27, 3501. \n[15] X. Wang, S. Kajiyama, H. Iinuma, E. Hosono, S. Oro, I. Moriguchi, M. Okubo, A. Yamada, Nat. Commun. 2015, 6, 6544. \n[16] X. Xie, S. Chen, W. Ding, Y. Nie, Z. Wei, Chem. Commun. 2013, 49, 10112. \n[17] Q. Peng, J. Guo, Q. Zhang, J. Xiang, B. Liu, A. Zhou, R. Liu, Y. Tian, J. Am. Chem. Soc. 2014, 136, 4113. \n[18] C. E. Ren, K. B. Hatzell, M. Alhabeb, Z. Ling, K. A. Mahmoud, Y. Gogotsi, J. Phys. Chem. Lett. 2015, 6, 4026. \n[19] J. Come, J. M. Black, M. R. Lukatskaya, M. Naguib, M. Beidaghi, A. J. Rondinone, S. V. Kalinin, D. J. Wesolowski, Y. Gogotsi, N. Balke, Nano Energy 2015, 17, 27. \n[20] O. Mashtalir, K. Cook, V. Mochalin, M. Crowe, M. Barsoum, Y. Gogotsi, J. Mater. Chem. A 2014, 2, 14334. \n[21] J. Chen, K. Chen, D. Tong, Y. Huang, J. Zhang, J. Xue, Q. Huang, T. Chen, Chem. Commun. 2015, 51, 314. \n[22] M. Ghidiu, M. Naguib, C. Shi, O. Mashtalir, L. M. Pan, B. Zhang, J. Yang, Y. Gogotsi, S. J. Billinge, M. W. Barsoum, Chem. Commun. 2014, 50, 9517. \n[23] B. Anasori, Y. Xie, M. Beidaghi, J. Lu, B. C. Hosler, L. Hultman, P. R. Kent, Y. Gogotsi, M. W. Barsoum, ACS Nano 2015, 9, 9507. \n[24] C. Hu, C. Li, J. Halim, S. Kota, D. J. Tallman, M. W. Barsoum, J. Am. Ceram. Soc. 2015, 98, 2713. \n[25] C. Hu, C.-C. Lai, Q. Tao, J. Lu, J. Halim, L. Sun, J. Zhang, J. Yang, B. Anasori, J. Wang, Chem. Commun. 2015, 51, 6560. \n[26] R. Meshkian, L.-Å. Näslund, J. Halim, J. Lu, M. W. Barsoum, J. Rosen, Scr. Mater. 2015, 108, 147. \n[27] M. Khazaei, M. Arai, T. Sasaki, M. Estili, Y. Sakka, Phys. Chem. Chem. Phys. 2014, 16, 7841. \n[28] C. Xu, L. Wang, Z. Liu, L. Chen, J. Guo, N. Kang, X.-L. Ma, H.-M. Cheng, W. Ren, Nat. Mater. 2015, 14, 1135. \n[29] M. Naguib, R. R. Unocic, B. L. Armstrong, J. Nanda, Dalton Trans. 2015, 44, 9353. \n[30] Z.-h. Liu, Z.-M. Wang, X. Yang, K. Ooi, Langmuir 2002, 18, 4926. \n[31] Y. Omomo, T. Sasaki, L. Wang, M. Watanabe, J. Am. Chem. Soc. 2003, 125, 3568. \n[32] C. C. Lai, R. Meshkian, M. Dahlqvist, J. Lu, L. Å. Näslund, O. Rivin, E. N. Caspi, O. Ozeri, L. Hultman, P. Eklund, M. W. Barsoum, J. Rosen, Acta Mater. 2015, 99, 157. \n[33] L. Óvári, J. Kiss, A. P. Farkas, F. Solymosi, J. Phys. Chem. B 2005, 109, 4638. \n[34] J. Halim, K. M. Cook, M. Naguib, P. Eklund, Y. Gogotsi, J. Rosen, M. W. Barsoum, Appl. Surf. Sci. 2016, 362, 406. \n[35] S. J. Park, C. P. Sun, R. Purtell, J. Vac. Sci. Technol. B 1987, 5, 1372. \n[36] Y. Dall’Agnese, M. R. Lukatskaya, K. M. Cook, P.-L. Taberna, Y. Gogotsi, P. Simon, Electrochem. Commun. 2014, 48, 118. \n[37] R. Menon, C. Yoon, D. Moses, A. Heeger, Y. Cao, Phys. Rev. B 1993, 48, 17685. \n[38] X. Zhang, M. Manno, A. Baruth, M. Johnson, E. S. Aydil, C. Leighton, ACS Nano 2013, 7, 2781. \n[39] M. Sarma, A. Beal, S. Nulsen, R. Friend, J. Phys. C: Solid State Phys. 1982, 15, 477. \n[40] N. Kobayashi, Y. Muto, Solid State Commun. 1979, 30, 337. \n[41] B. Anasori, C. Shi, E.-J. Moon, Y. Xie, C. Voigt, E. Dooryhee, P. R. C. Kent, S. J. May, S. J. L. Billinge, M. W. Barsoum, Y. Gogotsi, Nanoscale Horizons, Control of Electronic Properties of 2D Carbides (MXenes) by Manipulating Their Transition Metal Layers, 2016, n press. \n[42] N. Miyata, S. Akiyoshi, J. Appl. Phys. 1985, 58, 1651. \n[43] J. S. Chen, Y. L. Cheah, S. Madhavi, X. W. Lou, J. Phys. Chem. C 2010, 114, 8675. \n[44] X. Xiao, Z. Peng, C. Chen, C. Zhang, M. Beidaghi, Z. Yang, N. Wu, Y. Huang, L. Miao, Y. Gogotsi, J. ZhouNano Energy 2014, 9, 355. \n[45] X. Hu, W. Z. Liu, Y. Mei, Y. Huang, Chem. Soc. Rev. 2015, 44, 2376. \n[46] M. R. Lukatskaya, S. M. Bak, X. Yu, X. Q. Yang, M. W. Barsoum, Y. Gogotsi, Adv. Energy Mater. 2015, 5, 1500589. \n[47] J. R. Dahn, W. R. McKinnon, Solid State Ionics 1987, 23, 1. \n[48] H. J. Zhang, K. X. Wang, X. Y. Wu, Y. M. Jiang, Y. B. Zhai, C. Wang, X. Wei, J. S. Chen, Adv. Funct. Mater. 2014, 24, 3399. \n[49] O. Mashtalir, M. Naguib, V. N. Mochalin, Y. Dall’Agnese, M. Heon, M. W. Barsoum, Y. Gogotsi, Nat. Commun. 2013, 4, 1716. \n[50] M. Naguib, J. Come, B. Dyatkin, V. Presser, P. L. Taberna, P. Simon, M. W. Barsoum, Y. Gogotsi, Electrochem. Commun. 2012, 16, 61. \n[51] D. Sun, M. Wang, Z. Li, G. Fan, L.-Z. Fan, A. Zhou, Electrochem. Commun. 2014, 47, 80. \n[52] J. Yang, M. Naguib, M. Ghidiu, L.-M. Pan, J. Gu, J. Nanda, J. Halim, Y. Gogotsi, M. W. Barsoum, J. Am. Ceram. Soc. 2016, 99, 2, 660. \n[53] Z.-S. Wu, W. Ren, L. Wen, L. Gao, J. Zhao, Z. Chen, G. Zhou, F. Li, H.-M. Cheng, ACS Nano 2010, 4, 3187. \n[54] B. Wang, G. Wang, H. Wang, J. Mater. Chem. A 2015, 3, 17403. \n[55] S. J. Kim, M. Naguib, M. Zhao, C. Zhang, H.-T. Jung, M. W. Barsoum, Y. Gogotsi, Electrochim. Acta 2015, 163, 246. \n[56] M. Q. Zhao, C. E. Ren, Z. Ling, M. R. Lukatskaya, C. Zhang, K. L. Van Aken, M. W. Barsoum, Y. Gogotsi, Adv. Mater. 2015, 27, 339. " + }, + { + "id": "10.1126_sciadv.1501122", + "DOI": "10.1126/sciadv.1501122", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.1501122", + "Relative Dir Path": "mds/10.1126_sciadv.1501122", + "Article Title": "Identification of catalytic sites for oxygen reduction and oxygen evolution in N-doped graphene materials: Development of highly efficient metal-free bifunctional electrocatalyst", + "Authors": "Yang, HB; Miao, JW; Hung, SF; Chen, JZ; Tao, HB; Wang, XZ; Zhang, LP; Chen, R; Gao, JJ; Chen, HM; Dai, LM; Liu, B", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are critical to renewable energy conversion and storage technologies. Heteroatom-doped carbon nullomaterials have been reported to be efficient metal-free electrocatalysts for ORR in fuel cells for energy conversion, as well as ORR and OER in metal-air batteries for energy storage. We reported that metal-free three-dimensional (3D) graphene nulloribbon networks (N-GRW) doped with nitrogen exhibited superb bifunctional electrocatalytic activities for both ORR and OER, with an excellent stability in alkaline electrolytes (for example, KOH). For the first time, it was experimentally demonstrated that the electron-donating quaternary N sites were responsible for ORR, whereas the electron-withdrawing pyridinic N moieties in N-GRW served as active sites for OER. The unique 3D nulloarchitecture provided a high density of the ORR and OER active sites and facilitated the electrolyte and electron transports. As a result, the as-prepared N-GRW holds great potential as a low-cost, highly efficient air cathode in rechargeable metal-air batteries. Rechargeable zinc-air batteries with the N-GRW air electrode in a two-electrode configuration exhibited an open-circuit voltage of 1.46 V, a specific capacity of 873 mAh g(-1), and a peak power density of 65 mW cm(-2), which could be continuously charged and discharged with an excellent cycling stability. Our work should open up new avenues for the development of various carbon-based metal-free bifunctional electrocatalysts of practical significance.", + "Times Cited, WoS Core": 1086, + "Times Cited, All Databases": 1123, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000380072100008", + "Markdown": "# C H E M I S T R Y \n\n# Identification of catalytic sites for oxygen reduction and oxygen evolution in N-doped graphene materials: Development of highly efficient metal-free bifunctional electrocatalyst \n\nHong Bin Yang,1 Jianwei Miao,1 Sung-Fu Hung,2 Jiazang Chen,1 Hua Bing Tao,1 Xizu Wang,3 Liping Zhang, Rong Chen,1 Jiajian Gao,1 Hao Ming Chen,2 Liming Dai,4\\* Bin Liu1\\* \n\nOxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are critical to renewable energy conversion and storage technologies. Heteroatom-doped carbon nanomaterials have been reported to be efficient metal-free electrocatalysts for ORR in fuel cells for energy conversion, as well as ORR and OER in metal-air batteries for energy storage. We reported that metal-free three-dimensional (3D) graphene nanoribbon networks (N-GRW) doped with nitrogen exhibited superb bifunctional electrocatalytic activities for both ORR and OER, with an excellent stability in alkaline electrolytes (for example, KOH). For the first time, it was experimentally demonstrated that the electrondonating quaternary N sites were responsible for ORR, whereas the electron-withdrawing pyridinic N moieties in N-GRW served as active sites for OER. The unique 3D nanoarchitecture provided a high density of the ORR and OER active sites and facilitated the electrolyte and electron transports. As a result, the as-prepared N-GRW holds great potential as a low-cost, highly efficient air cathode in rechargeable metal-air batteries. Rechargeable zinc-air batteries with the N-GRW air electrode in a two-electrode configuration exhibited an open-circuit voltage of $\\mathsf{1.46}\\mathsf{V},$ a specific capacity of $873\\:\\mathrm{mAh}\\:\\mathfrak{g}^{-1}$ , and a peak power density of $65\\mathsf{m w}\\mathsf{c m}^{-2}.$ , which could be continuously charged and discharged with an excellent cycling stability. Our work should open up new avenues for the development of various carbon-based metal-free bifunctional electrocatalysts of practical significance. \n\n# INTRODUCTION \n\nRenewable electrochemical energy conversion and storage technologies are promising in addressing global energy and environmental challenges $(1,2)$ . Oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are two key electrochemical processes that take place in a wide range of renewable electrochemical energy conversion and storage devices, including rechargeable metal-air batteries, regenerative fuel cells, and water splitting cells (3–12). However, the overall efficiency of these devices has been severely limited by the sluggish kinetics in the electrocatalytic reduction and evolution of molecular oxygen (13–15). Therefore, noble metals and transition metal (Ni, Co, Mn, and Fe) catalysts have been widely used for electrocatalysis of ORR and OER (16, 17). Unfortunately, the scarcity, high cost, and inferior durability of these metal-based catalysts have hampered the widespread and large-scale applications of these renewable energy technologies. \n\nAlong with the extensive research and development of the noble metal-based ORR and OER catalysts (18–22), carbon nanomaterials (10), such as heteroatom-doped carbon nanotubes (CNTs) and graphene, have been studied as metal-free electrocatalysts for energy conversion and storage. Impressive experimental and theoretical results have been achieved through the molecular and/or nanoarchitecture engineering of carbon nanomaterials using various innovative strategies, including surface functionalization (23–25), geometric structuring (26–30), and heteroatom doping (17, 31–34). Among them, nitrogendoped carbon nanomaterials were demonstrated as efficient ORR (35–39) and OER (40, 41) electrocatalysts, respectively. More recently, metal-free N-, P-codoped carbon-based nanomaterials have been studied as bifunctional catalysts for both ORR and OER (42), as were N mono-doped carbon nanomaterials with unique structures (43, 44) and unknown bifunctional catalytic mechanisms. Therefore, to achieve cost-effective, high-performance, metal-free ORR and OER bifunctional electrocatalysts, it is highly desirable to gain a mechanistic understanding of metal-free electrocatalysis (particularly, OER) to guide the development of new catalytic materials with sufficient active sites. \n\nHere, we have developed a novel strategy to synthesize N-doped graphene nanoribbons with interconnected three-dimensional (3D) architecture (that is, N-GRW). The as-prepared N-GRW exhibited superior overall electrocatalytic activities for both ORR and OER with an excellent stability in alkaline media, comparable to the state-ofthe-art noble metal electrocatalysts (for example, $\\mathrm{Pt/C}$ and $\\mathrm{Ir/C})$ ). For the first time, it was experimentally found that the electronwithdrawing pyridinic N moieties in the N-GRW served as active sites for OER, whereas the electron-donating quaternary N sites were responsible for ORR. The unique 3D nanoarchitecture ensured a high density of active sites as well as excellent mass and charge transport for both ORR and OER. As a result, the as-prepared N-GRW was demonstrated to be a promising low-cost, highly efficient air cathode in rechargeable metal-air batteries. Therefore, our study on the newly developed N-GRW has provided new concepts/principles for designing bifunctional catalysts by catalytic active site and nanoarchitecture engineering, which could open up new avenues for the development of sustainable energy conversion and storage technologies based on earth-abundant, scalable, and metal-free electrocatalysts. \n\n# RESULTS \n\n# Synthesis and structure characterization of N-doped graphene catalysts \n\nIn a typical experiment, we synthesized the N-GRW by first grinding a mixture of melamine and L-cysteine with a mass ratio of 4:1 into a homogeneous precursor (Fig. 1A), followed by a two-step carbonization under argon atmosphere (fig. S2). The results from our systematic investigations on the effects of the carbonization temperature and the melamine–to–L-cysteine ratio on the structural evolution (figs. S3 to S5) are consistent with the following scenario for the N-GRW formation. Initially, melamine was polymerized to form carbon nitride, whereas the thiol groups on L-cysteine covalently bonded with the newly formed carbon nitride plane via the formation of $-C{\\mathrm{-}}{\\mathrm{S-}}{\\mathrm{C-}}$ bonds, probably through a radical mechanism, because the thiol groups on Lcysteine are highly reactive and susceptible to hydrogen extraction by free radicals. X-ray photoelectron spectroscopic (XPS) measurements, shown in fig. S6, provide evidences for the formation of $\\mathrm{C}_{3}\\mathrm{N}_{4}$ and sulfur-doped $\\mathrm{C}_{3}\\mathrm{N}_{4},$ whereas Fig. 1A indicates steric hindrances for the formation of the lateral $\\mathrm{C-N=C}$ bonds to impede the extension of the 2D carbon nitride plane due to the insertion of L-cysteine moieties. Thus, L-cysteine acted not only as a carbon source but also as a “template” to generate pores within the resultant carbon nitride. The formation of porous sulfur-doped carbon nitride was confirmed by the porous morphology (fig. S7) and larger surface area (fig. S8) observed for the sulfur-doped carbon nitride, with respect to the $\\mathrm{C}_{3}\\mathrm{N}_{4}$ sample prepared by polymerization of melamine with and without L-cysteine, respectively. As indicated by thermogravimetric analyses (TGAs) (fig. S9), subsequent thermal treatment of the sulfur-doped carbon nitride sample caused a marked mass loss over $600^{\\circ}$ to $800^{\\circ}\\mathrm{C},$ arising from pyrolysis of the sulfur-doped carbon nitride, which was accompanied by a significant reduction in the nitrogen content from 48 to 20 atomic $\\%$ (fig. S10) and an increase in the specific surface area (from 78 to $480~\\mathrm{m^{2}~g^{-1}}$ ; fig. S11). The thermal treatment could lead to the formation of 3D interconnected carbon networks (that is, N-GRW) through chemical bonding (for example, $-C{-}S{-}C{-})$ between pyrolyzed L-cysteine molecules on the same or different $\\mathrm{C}_{3}\\mathrm{N}_{4}$ planes, along with the concomitant losses of nitrogen/sulfur from the decomposed L-cysteine moieties. Because of the strong $-C{\\mathrm{-}}\\mathsf{S-}\\mathsf{C-}$ bonding, no oxidation occurred during the carbonization below $800^{\\circ}\\mathrm{C}$ (fig. S12). The resultant N-GRW had a uniformly distributed 3D interconnected porous structure (Fig. 1, B and $\\mathrm{C},$ and fig. S4) with a nitrogen content as high as 20 atomic $\\%$ (carbonized at $800^{\\circ}\\mathrm{C},$ and 6 atomic $\\%$ (carbonized at $1000^{\\circ}\\mathrm{C},$ . A higher carbonization temperature resulted in an improved graphitization degree and a reduced dopant content. The thiol group in L-cysteine was found to play critical and irreplaceable roles in controlling the structure of the N-GRW. By replacing L-cysteine with amino acids bearing other functional groups [for example, methyl (L-alanine) and hydroxyl (L-serine) groups] during the material synthesis, we could not produce N-GRW, but could only form N-doped graphene sheets with or without the porous structure (N-HGS or N-GS) (fig. S13), indicating once again the important role of the –C–S–C– bonding to the porous network formation. \n\nFigure 2A reproduces a typical SEM image of the as-synthesized N-GRW, which shows the 3D interconnected network nanoarchitecture. Transmission electron microscopy (TEM) and atomic force microscopy (AFM) analyses (Fig. 2, B to D) further affirm the uniform 3D structure of nanoribbon networks. Crumpled and entangled wrinklelike structures can be seen in Fig. 2B, a common feature typically observed in porous N-doped graphene (31). The width of the nanoribbons is less than $20\\ \\mathrm{nm}$ (typically $10\\ \\mathrm{nm}$ ), whereas the thickness measured by AFM (Fig. 2D) is less than $2.5~\\mathrm{{nm}}$ , corresponding to about eight or less layers of graphene sheets. \n\nThe measured specific surface area of the N-GRW is ${\\sim}530~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ significantly larger than that of the N-HGS $(480\\mathrm{m}^{2}\\mathrm{g}^{-1})$ and the N-GS $(460~\\mathrm{m}^{2}~\\mathrm{g}^{-1})$ (fig. S14 and table S1). Most of the pores in the N-GRW fall in the category of mesopores (Fig. 2E). The ultrahigh total pore volume of about $2.{\\dot{9}}\\operatorname{cm}^{3}\\operatorname{g}^{-1}$ for the N-GRW signifies the high porosity. The 3D porous N-GRW has abundant edges, thin walls, and conductive networks, which can facilitate fast transportation of mass and charge to facilitate electrochemical reactions. \n\n![](images/0cd5dc73012125d9fdea204594d8a525843b73423b8eb8899fab1814a9ffed37.jpg) \nFig. 1. Synthesis of N-GRW. (A) Synthesis steps: (1) polymerization at $600^{\\circ}\\mathsf C$ for 2 hours, and (2) pyrolysis and carbonization at $800^{\\circ}$ to $1000^{\\circ}\\mathsf{C}$ (B) Digita photograph of the as-synthesized N-GRW. (C) Scanning electron microscopy (SEM) image of the as-synthesized N-GRW. \n\n![](images/086357b7d31b49ac3108c813d262af41f1c1fe71f93582e73858b881b077a80a.jpg) \nFig. 2. Structure and composition of N-GRW. (A) High-resolution SEM image of the N-GRW. (B and C) Low-magnification (B) and high-magnification (C) TEM images of the N-GRW. (D) AFM image and height profile of the N-GRW on mica substrate (scale bar, $200~\\mathsf{n m}$ ). (E) Barrett-Joyner-Halenda pore size distribution and pore volume of the N-GRW calculated from ${\\sf N}_{2}$ desorption isotherm. (F) XPS spectrum of the N-GRW. Inset shows a high-resolution N1s spectrum with peaks deconvoluted into pyridinic $(397.8\\:\\mathrm{eV})$ , pyrrolic $(398.9\\:\\mathrm{eV})$ , quaternary $(400.8\\mathsf{e V})$ , and oxidized $(402.0\\ \\mathrm{eV})$ N species. a.u., arbitrary units. \n\nFigure 2F displays the XPS survey spectrum for the N-GRW, whereas fig. S15 shows the high-resolution XPS C1s, N1s, and O1s spectra for the N-GRW, N-HGS, and N-GS. The corresponding numerical results are summarized in tables S1 and S2. It is clear from these XPS results that the N-GRW contains $5.9\\%$ N and $0.10\\%$ S. The content of S is much lower than that reported (around $2\\%$ ) for other N-, S-codoped graphene materials (35, 36, 45, 46), possibly due to the different synthetic methods used and the relatively high carbonization temperature $(1000^{\\circ}\\mathrm{C})$ applied during our synthesis; this suggests that sulfur may just act as the bridge for the construction of the 3D nanoribbon networks, but without introducing any significant doping effect into the N-GRW (vide infra). The contents of N dopant in the N-HGS and N-GS are 5.4 and 6.1 atomic $\\%,$ respectively, similar to that of the N-GRW. All samples show high contents of pyridinic N and quaternary N (1.45 and 2.8 atomic $\\%$ for the N-GRW, 0.95 and 2.8 atomic $\\%$ for the N-HGS, and 1.34 and 3.0 atomic $\\%$ for the N-GS), which have been known to be active for ORR and other catalytic reactions (31, 47). \n\nWe further used x-ray diffraction (XRD) and Raman spectroscopy to investigate the crystalline structure and graphitization degree of the N-GRW, N-HGS, and N-GS samples. As shown in fig. S16, all samples exhibit similar broad diffraction patterns characteristic of the carbon (002) over $25.8^{\\circ}$ , suggesting a low degree of crystallization. According to Scherrer’s formula (48), the mean crystal size along the $\\mathbf{\\Psi}_{c}$ -direction was calculated to be $\\mathrm{\\sim}1.8~\\mathrm{nm}$ . The relatively weak peak intensity for the N-GRW, with respect to the other two samples, indicates a defectrich feature. On the other hand, Raman spectra for all of the N-doped graphene samples show two clear vibrational bands (the G band and D band). The $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratios were calculated to be 3.34, 2.34, and 2.10 for the N-GRW, N-HGS, and N-GS, respectively. A higher $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratio is usually associated with a more disordered carbon structure (46–48). $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ is inversely proportional to the in-plane coherence length $\\left(L_{\\mathrm{a}}\\right)$ , which is the mean average crystallite size of the $\\mathsf{s p}^{2}$ domains in the nano-graphite system and can be calculated from $\\bar{L}_{\\mathrm{a}}=C(\\lambda)(I_{\\mathrm{D}}/I_{\\mathrm{G}})^{-1}$ , with $\\overset{\\triangledown}{C}(\\lambda)=43.\\overset{\\triangledown}{5}\\overset{\\triangledown}{\\mathrm{\\AA}}$ for $514\\mathrm{nm}$ (49, 50). The calculated $L_{\\mathrm{a}}$ values are 1.3, 1.8, and $2.1\\ \\mathrm{nm}$ for the N-GRW, N-HGS, and N-GS, respectively, indicating that the average size of crystalline domains in the N-GRW is apparently smaller than that in the N-HGS and N-GS, which is consistent with the results obtained from the SEM and TEM images (figs. S3, S4, and S13). The smaller domain size observed for the NGRW suggests that the N-GRW sample has more edge sites, as also confirmed by its lower $\\ensuremath{\\mathrm{sp}}^{2}/\\ensuremath{\\mathrm{sp}}^{3}$ ratio deduced from the high-resolution C1s spectra (0.36, 0.58, and 0.68 for the N-GRW, N-HGS, and N-GS, respectively; fig. S15). The graphene edge sites have recently been shown to have a much faster electron transfer rate and higher electrocatalytic activity than the graphene basal plane (51, 52). This, coupled with the fast mass, as well as ionic and electronic transport, makes the N-GRW an ideal electrode for energy conversion and storage, as we should see later. \n\n# ORR and OER catalytic activity of N-doped graphene catalysts \n\nTo evaluate the electrocatalytic activities of the N-GRW, N-HGS, and N-GS toward ORR, we performed rotating ring-disc electrode (RRDE) measurements in alkaline electrolytes (figs. S17 and S18). Figure 3A reproduces the ORR polarization curves measured from the NGRW, which shows an onset potential and a half-wave potential $(E_{1/2})$ of 0.92 and $0.84\\mathrm{~V~}$ versus RHE (reversible hydrogen electrode), respectively. These values are very close to those of $\\mathrm{Pt/C}$ (0.94 and $0.85\\mathrm{V})$ , but much more positive than those of the N-HGS (0.90 and 0.81 V versus RHE) and N-GS (0.87 and $0.80\\mathrm{V}$ versus RHE). The trend for the onset potential deduced from the RRDE measurements consists well with the CV scans (fig. S19). The ring current profiles associated with the reduction of peroxide species $\\left(\\mathrm{HO}_{2}^{-}\\right)$ formed during the ORR process are shown in the upper half of Fig. 3A, from which the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield on the N-GRW was calculated to be below $5\\%$ , a value that is comparable to that of the $\\mathrm{Pt/C}$ catalyst but smaller than that of the N-HGS and N-GS catalysts. The electron transfer number per $\\mathrm{O}_{2}$ molecule was estimated to be ${\\sim}3.95$ for the N-GRW, which is obviously higher than that for the N-HGS and N-GS (fig. S20). The excellent ORR activity of the N-GRW catalyst was further confirmed by the smaller Tafel slope of $53~\\mathrm{mV}$ decade−1 at low overpotentials, as compared with that of $\\mathrm{Pt/C}$ (60 mV decade−1) and N-GS $\\mathrm{\\Delta}69\\mathrm{\\mV}$ decade−1) in 1 M KOH (fig. S21). Furthermore, the N-GRW electrode also demonstrated a good methanol tolerance, much better resistance to CO poisoning (inset of Fig. 3B and figs. S22 and S23), and superior operational durability to $\\mathrm{Pt/C}$ catalyst with only a $10\\%$ decay in ORR activity over a 12-hour continuous operation at a potential of $0.7\\mathrm{V}$ versus RHE. Figure 3C and fig. S24 show the linear sweep voltammetry (LSV) and cyclic voltammetry (CV) scans, respectively, before and after accelerated degradation test (ADT). It was found that $\\mathrm{Pt/C}$ experienced a marked loss $(35\\%)$ in electrochemical active surface area (ECSA) after 2000 consecutive cycles (fig. S24). In contrast, almost no loss in ECSA was observed for the N-GRW under the same conditions, leading to a smaller half-wave potential negative shift $\\mathrm{i}5\\mathrm{mV}$ for the N-GRW versus $35\\mathrm{mV}$ for $\\mathrm{Pt/C}\\mathrm{\\cdot}$ ) and smaller limited current variation (fig. S24). These results indicate that the N-GRW is an efficient metal-free ORR catalyst with an electrocatalytic activity comparable to that of $\\mathrm{Pt/C},$ but with a superior methanol and CO tolerance, and operational stability. These results, together with the metal-free preparation procedure (Fig. 1), indicate that the observed electrocatalytic activity can be attributed exclusively to the incorporation of nitrogen in the 3D N-GRW (vide infra). \n\nIn addition to the superb ORR performance discussed above, we also tested OER activities for the N-GRW, N-HGS, and N-GS using RDE measurements in $1\\mathbf{M}$ (Fig. 3D) and $0.1\\mathrm{{M}}$ KOH (fig. S25). As can be seen, the overpotential required to drive a $10\\mathrm{mA}\\mathrm{cm}^{-2}$ current density $\\left(\\mathfrak{n}_{10}\\right)$ for the N-GRW is $360~\\mathrm{mV}$ , which is significantly lower than that for the N-HGS and N-GS (400 and $390\\mathrm{mV}$ , respectively). Upon the application of potentials over the onset potential, the evolution of bubbles on the N-GRW electrode was evident. RRDE measurements (fig. S26) confirmed the production of oxygen bubbles with negligible ${\\mathrm{HO}}_{2}^{-}$ formation, indicating a 4e pathway for OER on the N-GRW electrode in alkaline medium. The N-GRW exhibited the smallest Tafel slope of $47\\mathrm{mV}$ decade−1 within the OER region (fig. S27) in 1 M KOH among all the electrodes tested: N-HGS $52~\\mathrm{mV}$ decade ), N-GS 1 $53\\mathrm{mV}$ decade−1), and $\\mathrm{Ir/C}$ $54\\mathrm{mV}$ decade−1). Therefore, our N-GRW catalyst is one of the best OER electrodes reported to date (table S3). CV curves of the N-GRW at different scan rates were recorded (fig. S28), showing that the contribution from double-layer capacitance of the electrode toward the measured current is negligible. Video S1 shows the gas evolution on the N-GRW–loaded carbon cloth electrode in a potential range from 1.5 to $1.8\\mathrm{V}$ versus RHE, which also shows the firm attachment of catalysts on the carbon cloth electrode. Faradaic efficiency measurements carried out at 5 and $25\\mathrm{\\mA\\cm^{-2}}$ revealed a nearly $100\\%$ Faradaic efficiency (fig. S29). Electrochemical stability of the N-GRW electrode was also tested, with the $\\mathrm{Ir/C}$ as reference, under a fixed overpotential and current loading conditions over 24-hour continued electrolysis (Fig. 3E and inset). The N-GRW catalyst showed superior durability to $\\mathrm{Ir/C}$ catalyst with $<10\\%$ decay in the OER activity over 24 hours of continuous operation, which is consistent with the LSV results before and after the stability testing, as shown in Fig. 3F. \n\n![](images/18c2a1ce037117164cba0cde9a753e8ad2c68b52d543086b82dfc23c58535698.jpg) \nFig. 3. Electrochemical performances of N-doped graphene catalysts for ORR and OER. (A) LSV curves of N-doped graphene catalysts on RRDE in ${{0}_{2}}$ -saturated 1 M KOH at a rotation speed of 1600 rpm and a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ , with a constant potential of $1.5\\mathsf{V}$ versus RHE applied on the ring. Disc current is displayed on the lower half of the graph, whereas the ring current (dotted line) is shown on the upper half. (B) Chronoamperometric (currenttime) responses of $\\mathsf{P t/C}$ and the N-GRW for ORR at $0.7\\:\\forall$ versus RHE, in 1 M KOH, at a rotation speed of 900 rpm. Inset shows the crossover effect of the N-GRW and $\\mathsf{P t/C}$ electrodes at $0.7\\:\\forall$ versus RHE, followed by introduction of methanol (3 M) in $\\mathsf{O}_{2}$ -saturated 1 M KOH. (C) LSV curves of the N-GRW before and after ADT, performed in $1M\\mathsf{K O H}$ at a scan rate of $50~\\mathrm{mV}~\\mathsf{s}^{-1}$ for the N-GRW and $\\mathsf{P t/C}$ . (D) LSV curves for OER on RDE for the N-GRW, N-HGS, and N-GS in $\\mathsf{O}_{2}$ -saturated 1 M KOH at a rotation speed of 1600 rpm and a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . (E) Chronoamperometric (current-time) responses for OER at fixed overpotential of $320~\\mathrm{mV}$ (for $\\mathsf{I r/C}$ and $360~\\mathsf{m V}$ (for the N-GRW). Inset shows chronopotentiometric (potential-time) response at a fixed current loading of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ . (F) LSV curves for OER before and after stability test for $\\mathsf{I r/C}$ and the N-GRW. \n\n# Identification of ORR and OER catalytic sites in N-doped graphene catalysts \n\nTo investigate mechanisms for the metal-free electrolysis of ORR and OER, we performed Mott-Schottky experiments to identify the doping states of the N-doped graphene catalysts. Depending on the N dopant configurations, N-doped graphene has been shown both theoretically and experimentally (53–56) to be either p-type or n-type. More specifically, n-type doping was found for quaternary/pyrrolic N and p-type doping for pyridinic N. Because the quaternary and pyridinic $\\mathrm{~N~}$ are the dominating N components in our N-doped graphene catalysts (inset of Fig. 2D and fig. S15), both n-type and p-type domains should coexist in our samples. Mott-Schottky experiments were carried out in Ar-saturated $0.1\\mathrm{~M~KOH}$ to identify doping states in the N-doped graphene catalysts. The results in the form of $\\mathrm{\\dot{C}}_{\\mathrm{scL}}{}^{-2}$ versus E given in fig. S30 show both positive and negative slopes for the N-GRW, NHGS, and N-HGS in two different potential regions, confirming the presence of both n-type and p-type domains in our N-doped graphene samples with bipolar characteristics. The slopes of Mott-Schottky plots for the N-GRW, N-HGS, and N-HGS in the n-type region (fig. S30A) are $4.2\\times10^{7}$ , $5.1\\times10^{7}$ , and ${8.1\\times10^{7}\\mathrm{C}^{-2}.\\mathrm{V}}$ , respectively. This, together with the similar trend observed in the p-type region (fig. S30B), indicates that the N-GRW electrode has the highest charge carrier density (for both n-type and p-type carriers). \n\nRecent DFT calculations have demonstrated that incorporated N itself could not act as active site for electrochemical reactions, but the adjacent C atoms have reduced energy barriers for ORR or OER due to the N-doping–induced charge redistribution in the $\\pi$ -conjugated system (57). Both experimental and theoretical studies (57–59) have indicated that quaternary N at the edge of graphene could act as the most active catalytic site for ORR by reducing the OOH intermediate adsorption energy. Figure 4A shows the similar ultraviolet photoelectron spectroscopy (UPS) spectra in valence band emission region for all samples tested. In the high-resolution valence band region, the N-doping– induced features for the N-GRW (for example, N lone pair and $\\pi_{\\mathrm{C-N}}.$ ) could be seen (fig. S31). The work function $(\\Phi)$ obtained from the UPS measurements is 4.42, 4.64, and $4.70\\:\\mathrm{eV}$ for the N-GRW, N-HGS, and N-GS, respectively. Thus, the N-GRW sample has a Fermi level $(E_{\\mathrm{f}})$ that is $0.22\\:\\mathrm{eV}$ higher than that of the N-HGS and $0.28\\:\\mathrm{eV}$ higher than that of the N-GS. Previous studies (60, 61) have shown that a catalyst with a smaller $\\Phi$ could offer a lower a energetic barrier (higher driving energy) for donating electrons from the surface of the catalyst to the adsorbed molecular oxygen, thereby facilitating the formation of the OOH species that is known to be the rate-determining step in the ORR process. Compared to the N-HGS and N-GS, the N-GRW sample has similar contents of the quaternary and pyrrolic N components for n-type doping, but much more edge sites associated with the constituent graphene nanoribbons in the 3D interconnected network. Therefore, having potentially more quaternary N edge sites and a relatively low energetic barrier for donating electrons from the surface of the catalyst to the adsorbed molecular oxygen, the N-GRW should be highly favorable for ORR with respect to the N-HGS and N-GS, as demonstrated by our experimental data (vide infra). \n\nThe correlation between the N-dopant state and OER activity is still largely lacking, though OER activities of N-doped carbon nanomaterials have been recently reported (41, 43). To elucidate the structure-performance relationship for facilitating the development of high-performance carbon-based OER catalysts, we performed x-ray absorption near-edge structure (XANES) spectroscopic measurements on carbon and nitrogen to identify the active sites for OER and ORR on the N-GRW electrode. Figure 4 (B and C) shows the evolution of carbon and nitrogen K-edge XANES spectra of the N-GRW catalyst before/ after oxygen reduction and evolution reactions. On the basis of previous reports (62–66), the peaks of carbon and nitrogen in the K-edge XANES spectra were assigned, as indicated in Fig. 4 (B and C). The increase in peak intensity related to $\\pi_{\\mathrm{~\\tiny~C-O-C,~C-N~}}^{*}$ at $287.7\\mathrm{eV}$ in Fig. 4B suggests adsorption of intermediate species $(\\mathrm{O}^{\\ast})$ on carbon atoms in both ORR and OER processes, which is consistent with the appearance of a new peak at $289.6~\\mathrm{eV}$ (adsorption of ${\\mathrm{OOH}}^{*}$ intermediates) after ORR and OER. The nitrogen K-edge XANES spectrum of the NGRW after ORR, given in Fig. 4C, shows a new peak at the lower energy side of graphitic N (that is, quaternary N) $\\left(\\sim401~\\mathrm{eV}\\right)$ , which can be ascribed to the distortion of heterocycles caused by the adsorbed ${\\cal O}^{*}$ and ${\\mathrm{OOH}}^{*}$ intermediates on carbon atoms near the graphitic N. In contrast, the peak at $398.0~\\mathrm{eV}$ related to pyridinic N was kept unchanged, with respect to the pristine N-GRW (Fig. 4C). These results indicate that the quaternary $\\mathrm{\\DeltaN}$ with $\\mathfrak{n}$ -type doping, rather than the p-type doping by pyridinic N, is responsible for the ORR on the N-GRW electrode. However, after OER, the full width at half maximum of the pyridinic N peak at ${\\sim}398.0\\mathrm{eV}$ increased from 0.8 to $1.15\\mathrm{eV}$ , together with the formation of a new peak at the higher energy side (Fig. 4C). In the meantime, other peaks, including the graphitic and pyrrolic N peaks, were kept nearly the same as those for the pristine N-GRW, indicating adsorption of ${\\mathrm{OOH}}^{*}$ and ${\\cal O}^{*}$ intermediates on carbon atoms next to the pyridinic N during OER, and hence, the pyridinic N with p-type doping is responsible for OER. As far as we are aware, this is the first experimental evidence for different $\\mathrm{\\DeltaN}$ species in the N mono-doped carbon nanomaterials for metal-free catalysis of different reactions, which could lead to various bifunctional catalysts from other heteroatom mono-doped carbon nanomaterials. \n\n![](images/bcb65799e58b3cb011bf8ef621d5a56c4dea023544d32bb7ccfe742e9e73732b.jpg) \nFig. 4. Electronic characteristics and ORR/OER active sites of N-doped graphene catalysts. (A) UPS spectra collected using an He I $(21.2\\mathsf{e V})$ radiation. Inset shows the enlarged view of the secondary electron tail threshold. (B and C) Carbon and nitrogen K-edge XANES spectra of N-GRW catalyst, acquired under ultrahigh vacuum, pristine (black line), after ORR (yellow line) and after OER (blue line). In carbon K-edge XANES spectra, A: defects, B: $\\pi_{\\mathrm{~\\tiny~C=C}}^{*}$ C: $\\pi_{\\mathrm{~C~}}^{*}$ –OH, D: $\\pi_{\\mathrm{~\\scriptstyle{C-O-C},~C-N}}^{*},$ E: $\\pi^{*}{}_{\\mathrm{C=O}},$ COOH, F: $\\upsigma_{\\mathrm{~\\tiny~C-C}}^{*}$ . (D) Schematic diagram of ORR and OER occurring at different active sites on the n- and $\\mathsf{p}$ -type domains of the NGRW catalyst. \n\nThe observed influences of the graphitic $\\mathrm{\\DeltaN}$ and pyridinic N on ORR and OER can also be understood from the doping-induced charge redistribution. As discussed above, the quaternary $\\mathrm{\\DeltaN}$ atoms in graphene could provide electrons to the $\\pi$ -conjugated system (n-type doping), leading to an increased nucleophile strength for the adjacent carbon rings $\\left[\\mathrm{C}(\\updelta-)\\right]$ to enhance the $\\mathrm{O}_{2}$ adsorption {because $\\mathrm{O}_{2}$ has high densities of $\\mathrm{o}$ lone pair electrons $[\\mathrm{O}(\\delta+)]\\}$ , and hence accelerating the ORR (67, 68). A similar scenario is applicable to the pyrrolic N atoms. As a result, carbon atoms near the quaternary N and/or pyrrolic $\\mathrm{\\DeltaN}$ are not energetically favorable for adsorption of water oxidation intermediates $\\mathrm{\\DeltaOH^{-}}$ and $\\mathrm{{OOH}^{-}},$ ) in alkaline solution, and are thereby unfavorable for OER. However, pyridinic $\\mathrm{\\DeltaN}$ (an electron-withdrawing group with the lone pair electrons involved in the resonance to delocalize electrons to make the N atoms electron-deficient) can accept electrons (p-type doping) from adjacent C atoms $(\\delta+)$ , facilitating the adsorption of water oxidation intermediates $\\mathrm{\\Delta[OH^{-}}$ , OOH−)—the rate-determining step for OER in alkaline solution (69, 70). Besides, the p-type domains of graphene can accept electrons from the adsorbed $\\mathrm{OH}^{-}$ to the catalyst surface to further accelerate the intermediate step of $\\mathrm{OH}^{-}\\rightarrow$ $\\mathrm{OH_{ads}+e^{-}}$ . A similar effect on OER has been revealed for the electronwithdrawing ketonic $\\scriptstyle{\\mathrm{C=O}}$ group (40). Because the N-GRW sample contains higher amounts of the pyridinic $\\mathrm{\\DeltaN}$ and ketonic $(\\mathrm{C=O})$ ) group (1.45 and 0.55 atomic $\\%$ ) than those of the N-HGS (0.95 and 0.28 atomic $\\%$ ) and N-GS (1.34 and 0.52 atomic $\\%$ ), the N-GRW exhibited a higher OER activity than that of the N-HGS and N-GS. Therefore, the N-GRW can act as an efficient bifunctional electrocatalyst for both ORR and OER, though detailed effects of the dopinginduced charge transfer on the catalytic mechanisms may be somewhat different under an applied potential in an electrochemical cell. On the basis of the above spectroscopic and electrochemical analyses, a schematic diagram was drawn in Fig. 4D as a working model for electrolysis of ORR and OER by the N-GRW. The turnover frequency (TOF) for the ORR and OER was calculated for the four-electron pathway, and the corresponding TOFs of N-GRW catalyst were 0.08 and $0.{\\dot{3}}3\\ \\mathbf{s}^{-1}$ for ORR and OER, respectively. As shown in Fig. 4D, the separated active sites for ORR and OER at the n- and p-type domains of the N-GRW can prevent catalyst active sites from possible cross-deactivation during the ORR and OER processes and allow for an independent optimization of the catalytic performance on each of the two different type domains. \n\nFrom the above discussions, we could conclude that the ORR activity decreased in the order of ${\\mathrm{N}{\\mathrm{-}}\\mathrm{GRW}}>{\\mathrm{N}{\\mathrm{-}}\\mathrm{HGS}}>{\\mathrm{N}{\\mathrm{-}}\\mathrm{GS}}.$ , whereas the OER activity decreased in the order of $\\mathrm{N\\mathrm{-}G R W>N\\mathrm{-}G S>N\\mathrm{-}H G S}$ (Fig. 3, A and D, and fig. S32), matching with the amounts of active sites (quaternary N, pyrrolic N for ORR and pyridinic N, $\\scriptstyle\\mathrm{C=O}$ for OER) in respective samples (table S2). To evaluate the overall ORR-OER bifunctional activities, we compared the overvoltage between OER and ORR $(\\Delta E=E_{10}-E_{1/2})$ , where $E_{10}$ is the OER potential at a current density of $10\\mathrm{\\mA\\cm}^{-2}$ and $E_{1/2}$ is the ORR half-wave potential for the catalysts investigated in this study. Smaller $\\Delta E$ corresponds to less efficiency loss and better catalyst performance as a reversible oxygen electrode. From Fig. 3 and figs. S18 and S25, we deduced a $\\Delta E$ of $0.82\\mathrm{V}$ in $0.1\\mathrm{{M}}$ KOH and $0.75\\mathrm{V}$ in 1 M KOH for the as-synthesized N-GRW, which is much lower than that of the N-HGS (0.92 and 0.82 V) and N-GS (0.92 and $0.82\\mathrm{~V~}$ ), reassuring the excellent bifunctional electrocatalytic activity for the N-GRW. As summarized in table S3, the bifunctional catalytic activity of the N-GRW is the best among recently reported high-performance bifunctional ORR/OER catalysts (6, 7, 38–44, 71, 72), including highly active metal-free carbon catalysts [for example, P-doped $\\mathrm{C}_{3}\\mathrm{N}_{4},$ $\\Delta E=0.92{\\mathrm{~V~}}$ (7), N-MWCNT (multiwalled CNT), $\\Delta E=1.05\\mathrm{~V~}$ (43), N-graphene/CNT, $\\Delta E=0.93\\mathrm{~V~}$ (44)] and even transition-metal oxide bifunctional catalysts [for example, $\\mathrm{LiCoO}_{2},$ $\\Delta E=0.97$ V (71) and $\\mathrm{Mn}_{x}\\mathrm{O}_{y}(\\mathrm{Co}_{x}\\mathrm{O}_{y})/\\mathrm{N}$ -doped carbon, $\\Delta E=0.87\\mathrm{~V~}$ (72)]. Thus, the newly developed N-GRW electrode is of practical importance. \n\n# Rechargeable zinc-air batteries in two-electrode configuration \n\nTo demonstrate potential applications for the N-GRW sample in practical energy devices, we constructed a rechargeable zinc-air battery in two-electrode configuration using a hybrid electrode based on the N-GRW–loaded carbon cloth/gas diffusion layer as the air cathode (Fig. 5A and figs. S33 and S34). Before the test of the battery performance, we evaluated the ORR and OER activities for the N-GRW air cathode in $\\mathrm{O}_{2}$ -saturated 6 M KOH (fig. S35), along with the $\\mathrm{Pt/C},\\mathrm{Ir/C},$ , and carbon cloth as references. As can be seen in fig. S35B, the overall ORR-OER activity of the N-GRW air electrode is much better than that of the noble metal catalysts [for example, $\\mathrm{Pt/C}$ $(20\\%)$ and $\\mathrm{Ir/C}$ $(20\\%)]$ . Figure S35C shows that the N-GRW–loaded carbon cloth hybrid air cathode is very stable throughout the 20-hour continuous ORR/OER cycles at $5\\mathrm{\\mA}\\mathrm{cm}^{-2}$ . Figure 5B reproduces polarization curves for the rechargeable zinc-air batteries in two-electrode configuration, which shows that the N-GRW electrode can supply a $20\\mathrm{m}\\mathrm{\\check{A}}\\mathrm{cm}^{-2}$ discharge and charge current density at 1.09 and $2.18\\mathrm{V}$ , outperformed the $\\mathrm{Pt/C}$ (1.15 and 2.53) and $\\mathrm{Ir/C}$ (0.95 and $2.05\\mathrm{V})$ ) air electrodes, and is comparable to the mixed $\\mathrm{Pt/C}+\\mathrm{Ir/C}$ (1.06 and 2.07 V) (fig. S36) air electrode. The open-circuit voltage of the two-electrode zinc-air battery with the N-GRW air electrode is $1.46\\mathrm{V}$ , which is the same as that for its counterpart with the $\\mathrm{Pt/C}$ air electrode, but higher than that of the $\\mathrm{Ir/C}$ (1.35 V) air electrode (fig. S37). The peak power density of the zinc-air battery assembled from the N-GRW air electrode is $65\\mathrm{\\mW\\cm^{-2}}$ , with a specific capacity as high as $873\\ \\mathrm{mAh\\g^{-1}}$ after being normalized to the mass of $Z\\mathrm{n}$ (Fig. 5B). The drop of voltage in discharging as shown in Fig. 5C is due to reduction in electrolyte conductivity by forming carbonate between the electrolyte (KOH) and $\\mathrm{CO}_{2}$ in the atmosphere (73). Replacing air with pure oxygen can keep the cell voltage unchanged during discharging. The rechargeability of the secondary zinc-air battery using the N-GRW air electrode was tested by galvanostatic charging and discharging at $2{\\mathrm{\\mA}}\\ {\\mathrm{cm}}^{-2}$ (Fig. 5D), showing a good cycling stability. However, as can be seen in Fig. 5, $\\mathrm{CO}_{2}$ in the atmosphere can affect the long-term stability during battery operation, and the influence of $\\mathrm{CO}_{2}$ is more severe on charging (OER) than discharging (ORR). Nevertheless, simple replenishment of the electrolyte and removal of $\\mathrm{CO}_{2}$ in air could regenerate and maintain the stable battery performance (fig. S38). Throughout more than 150 cycles of charging and discharging, the charge-discharge voltage gap of the two-electrode zinc-air battery with the N-GRW air electrode increased by only about $200~\\mathrm{mV}$ (Fig. 5D), verifying the excellent stability of the bifunctional N-GRW catalyst. Furthermore, the zinc-air battery assembled from the N-GRW air electrode could be rapidly charged and discharged at current densities as high as $20\\mathrm{m}\\mathrm{\\bar{A}}\\mathrm{cm}^{-2}$ with an outstanding stability, outperforming those devices assembled from the $\\mathrm{Pt/C,~Ir/C,}$ and mixed $\\mathrm{Pt/C}+\\mathrm{Ir/C}$ air electrodes (Fig. 5E and fig. S39). After charging, the cell was disassembled and metallic zinc was observed deposited on the metal electrode, confirming the rechargeable feature of the zinc-air battery assembled from NGRW air electrode (fig. S40). As an example for practical applications, a single zinc-air battery assembled from the N-GRW air electrode was used to power an electrolysis cell to split water into hydrogen and oxygen, as shown in Fig. 5F and video S2. Upon connecting the electrolysis cell to the zinc-air battery, the evolution of $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ was observed on the Pt/carbon cloth cathode and NiFe layer double hydroxide anode, respectively (videos S2 and S3). \n\n![](images/3895601049d21d31cc12009bd134eb66b25c97d7f438a8280d29d898daea1cab.jpg) \nFig. 5. Application of N-GRW bifunctional catalyst in rechargeable zinc-air batteries. (A) Schematic of a zinc-air battery at charging and discharging conditions. (B) Galvanodynamic charge/discharge profiles and power density curves of zinc-air batteries assembled from the N-GRW, Pt/C, Ir/C, and mixed $\\mathsf{P t/C}+\\mathsf{I r/C}$ (1:1 by weight) air electrode (fig. S36), respectively. (C) Discharge curves of zinc-air batteries assembled from the N-GRW and $\\mathsf{P t/C}$ catalysts at 5 and $20\\mathsf{m A c m}^{-2}$ discharging rate. (D) Charging/discharging cycling at a current density of $2\\mathsf{m A c m}^{-2}$ . Insets show the initial and after long time cycling testing charging/discharging curves of a zinc-air battery sembled from N-GRW as air catalyst. (E) Charging/discharging cycling curves of zinc-air batteries assembled from the N-GRW (yellow line) and mixed $\\mathsf{P t/C}+\\mathsf{I r/C}$ air electrode (blue line) at a rent density of $2\\bar{0}\\mathsf{m A}\\mathsf{c m}^{-\\bar{2}}$ (catalyst loading amount: $0.5\\mathsf{m g c m}^{-2}$ for mixed $\\mathsf{P t/C}+\\mathsf{I r/C})$ . (F) Photograph of an electrolysis cell powered by a zinc-air battery. Inset shows the bubble formation on both cathode and anode electrodes. All zinc-air batteries were tested in air at room temperature (catalyst loading amount: $0.5~\\mathsf{m g}~\\mathsf{c m}^{-2}$ for all zinc-air batteries). \n\n# DISCUSSION \n\nWe have developed a low-cost and scalable method to prepare novel 3D interconnected N-doped graphene nanoribbon network (N-GRW) architectures. The resultant N-GRW has a high density of electrondonating quaternary N favorable for ORR and high contents of electron-withdrawing functional groups (pyridinic N, $\\mathrm{C=O}$ ) attractive for OER. Moreover, the high content of nitrogen doping could modify the charge distribution in the carbon ring, leading to increased C1s binding energy and inhibition of carbon corrosion during the OER. This, together with the 3D interconnected network architecture of a high specific surface area, large pore volume, and suitable pore size distribution, provides a synergistic effect to create superb catalytic activities and stability for both ORR and OER, outperforming the reported metal-free carbon catalysts and even transition-metal oxide bifunctional catalysts. Two-electrode zinc-air batteries, based on the bifunctional N-GRW air electrode with region-specific active sides for ORR and OER, could be stably charged and discharged over 150 cycles at $2\\mathrm{\\mA}\\mathrm{cm}^{-2}$ . During discharging, the batteries exhibited an opencircuit voltage of $1.46\\mathrm{V}_{:}$ , a specific capacity of $873\\ \\mathrm{mAh\\g^{-1}}$ , and a peak power density of $65\\mathrm{mW}\\mathrm{cm}^{-2}$ . Furthermore, the rechargeable zinc-air batteries could be rapidly charged and discharged at charging and discharging current densities as high as $20\\mathrm{\\mA\\cm^{-2}}$ over 30 hours with an excellent cycling stability. Our work demonstrated the multiple independent electrocatalysis of different reactions by introducing multiple dopant states through single heteroatom doping carbon nanostructures, and for the first time, we detected different metal-free catalytic sites associated with different $\\mathrm{~N~}$ species in the N mono-doped carbon nanomaterials. This, together with the unprecedented ORR-OER bifunctional electrocatalytic activity and battery performance observed for our newly developed N-GRW metal-free catalysts, should have important implications for the development of low-cost, scalable synthetic methodology for producing various new carbon-based metal-free catalysts for a large variety of electrochemical and catalytic applications. \n\n# MATERIALS AND METHODS \n\n# Materials \n\nAll chemicals—melamine $(99\\%)$ ), L-cysteine $(98\\%)$ , L-serine $(99\\%)$ , L-alanine $(99\\%)$ , potassium hydroxide $(99\\%)$ , zinc chloride $({\\geq}98\\%)$ , and zinc foil (thickness: $0.20~\\mathrm{mm}$ , purity: $99.9\\%$ )—were purchased from Sigma-Aldrich and used without further purification. Commercial noble metal catalysts $\\mathrm{Ir/C}$ $20\\%$ Ir on Vulcan XC-72) and $\\mathrm{Pt/C}$ 1 $20\\%$ Pt on Vulcan XC-72) were purchased from Premetek. \n\n# Materials synthesis \n\nIn a typical synthesis of nitrogen-doped graphene nanoribbons (NGRW) with interconnected 3D network architecture, a mixture of melamine and L-cysteine with a mass ratio of 4:1 was first ground into a homogeneous precursor in a $\\mathrm{ZrO}_{2}$ mortar. Subsequently, the fine powder mixture underwent a pyrolysis and carbonization process in a tubular furnace (Carbolite) under argon atmosphere. Detailed temperature and time profiles for the pyrolysis and carbonization processes are shown in fig. S2. For the synthesis of holey nitrogen-doped graphene sheets (N-HGS) and nitrogen-doped graphene sheets (N-GS), the L-cysteine precursor was replaced by $\\mathrm{~L~}$ -alanine and L-serine while keeping the same molar ratio to melamine as in the synthesis of the N-GRW. \n\n# Electrochemical measurements \n\nTo prepare catalyst ink for the ORR and OER testing, $5\\mathrm{mg}$ of catalyst and $25~{\\upmu\\mathrm{l}}$ of $5\\%$ Nafion 117 solution (DuPont) were introduced into \n\n$975\\upmu\\mathrm{l}$ of 1:1 water/isopropanol solution sonicated for 3 hours. All potentials were calibrated with respect to RHE scale according to the Nernst equation $(E_{\\mathrm{RHE}}=E_{\\mathrm{Ag/AgCl}}+0.059\\times\\mathrm{pH}+0.197\\mathrm{V})$ . MottSchottky analysis was carried out at a dc potential range of 0 to $1.2\\mathrm{V}$ versus RHE (scan from 1.2 to $0\\mathrm{V}$ , anodic scan) and 1.0 to $2.0\\mathrm{V}$ versus RHE (scan from 1.0 to $2.0~\\mathrm{V}$ , cathodic scan). For the ORR test, an aliquot of $24\\upmu\\mathrm{l}$ of the catalyst ink was applied onto a glassy carbon RDE or RRDE, giving a catalyst loading of $\\mathrm{0.6~mg~cm}^{-2}$ . For the OER test, a catalyst loading of $0.3\\mathrm{mg}\\mathrm{cm}^{-2}$ was applied onto the test electrode. RRDE measurements were conducted at $25^{\\circ}\\mathrm{C}$ in an oxygen-saturated KOH solution at a scan rate of $5~\\mathrm{mV}~\\mathrm{s}^{-1}$ and a rotation speed of $1600~\\mathrm{rpm}$ . Commercial 20 wt $\\%$ Pt and 20 wt $\\%$ Ir on Vulcan carbon black $\\mathrm{\\Pt/C}$ and $\\mathrm{Ir/C}$ from Premetek) were measured for comparison. \n\n# $\\pmb{\\mathrm{x}}$ -ray absorption near-edge structure \n\nThe K-edge x-ray absorption spectra of C and N were measured in total electron yield mode at room temperature using BL-20A at the National Synchrotron Radiation Research Center (Hsinchu, Taiwan). Before XANES measurements, the samples were reacted in an $\\mathrm{O}_{2}$ - saturated $1\\mathrm{M}\\mathrm{KOH}$ for 1 hour at 0.55 and $1.65\\mathrm{~V~}$ versus RHE for ORR and OER, respectively. After ORR and OER, samples were soaked dry in vacuum and then subjected to an ultrahigh vacuum chamber 1 $\\cdot\\mathrm{i}^{\\cdot}\\times10^{-9}$ torr) for the total electron yield $\\mathbf{x}$ -ray absorption spectra (TEY-XAS) collection. For C and N K-edge absorption, the data were collected at the $6\\mathrm{-m}$ high-energy spherical grating monochromator beamline with $10\\times10{-}\\upmu\\mathrm{m}$ opening slits, corresponding to ${\\sim}0.08–\\mathrm{eV}$ energy resolution. \n\n# Rechargeable zinc-air battery \n\nRechargeable zinc-air battery in two-electrode configuration was assembled according to the following procedure: first, the air electrode was made by dipping a pretreated carbon cloth substrate $(1\\times2~\\mathrm{cm}^{2})$ ) into a bottle filled with $5\\mathrm{ml}$ of catalyst ink $(2\\mathrm{mg}\\mathrm{ml}^{-1}.$ ), gently shaking for 1 hour, followed by drying in air. This process was repeated once to reach a catalyst loading of about $0.5\\mathrm{\\mg\\cm}^{-2}$ . Subsequently, the catalyst-loaded carbon cloth was attached to a gas diffusion layer (AvCarb P75T, Fuel Cell Store) to form a carbon cloth/gas diffusion layer hybrid electrode for rechargeable zinc-air battery assembly. The electrolyte used was 6 M KOH filled with $0.2\\mathrm{M}\\mathrm{ZnCl_{2}}$ to ensure reversible zinc electrochemical reactions at the anode. \n\nfig. S16. XRD patterns and Raman spectra of the N-GRW, N-HGS, and N-GS. \nfig. S17. LSV of N-doped graphene samples at different rotation speeds in the ORR region. fig. S18. Linear sweeping voltammograms and Koutecky-Levich plots of different catalysts in the ORR region. \nfig. S19. Cyclic voltammograms of N-doped graphene catalysts and $\\mathsf{P t/C}$ $(20\\%)$ in $\\mathsf{A r-}$ and $\\mathsf{O}_{2}\\mathsf{-}$ - saturated $1M\\upkappa\\mathrm{OH}$ . \nfig. S20. Peroxide yield and electron transfer number of N-doped graphene catalysts. fig. S21. Tafel plots of N-doped graphene catalysts in ORR region. \nfig. S22. Cyclic voltammograms of $\\mathsf{P t/C}$ and the N-GRW electrode in $\\mathsf{O}_{2}$ -saturated 0.1 M KOH filled with methanol. \nfig. S23. Current-time response of $\\mathsf{P t/C}$ and N-GRW for ORR with/without introducing CO into the electrolyte. \nfig. S24. Cycling durability of $\\mathsf{P t/C}$ and N-GRW. \nfig. S25. Linear sweeping voltammograms and Tafel plots of N-doped graphene catalysts in the OER region. \nfig. S26. RRDE measurements for the detection of ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ and $\\mathsf{O}_{2}$ generated during the OER process. \nfig. S27. OER Tafel plots of N-doped graphene catalysts. \nfig. S28. Cyclic voltammograms of the N-GRW in the OER region at different scan rates. fig. S29. Faraday efficiency of OER measurement. \nfig. S30. Mott-Schottky plots of N-doped graphene catalysts in two potential regions. fig. S31. XPS valence band spectra of the N-GRW. \nfig. S32. Nyquist plots of N-doped graphene samples in the ORR and OER regions. \nfig. S33. The assembly processes for preparation of hybrid air cathode. \nfig. S34. The assembly processes for the fabrication of a rechargeable zinc-air battery. fig. S35. ORR and OER performances of air cathode tested in half-cell configuration. fig. S36. Charge/discharge profiles and power density curves of zinc-air batteries assembled from mixed $\\mathsf{P t/C}+\\mathsf{I r/C}$ air electrode. \nfig. S37. Open-circuit voltage profiles of zinc-air batteries. \nfig. S38. Charging/discharging cycling curves of the N-GRW–loaded electrode at charging/ discharging current densities of $2\\mathsf{m A}\\mathsf{c m}^{-2}$ . \nfig. S39. Charging/discharging cycling curves of $\\mathsf{P t/C}$ and $\\mathsf{I r/C}$ electrodes at charging/ discharging current densities of $20\\mathsf{m A}\\mathsf{c m}^{-2}$ . \nfig. S40. XRD patterns of materials detached from Ti foil after long time charging. \nnote S1. XPS study of C3N4 and S-doped C3N4 samples. \nnote S2. Deconvolution of C1s, N1s, and O1s XPS spectra of N-doped graphene samples. note S3. Average crystallite size of the $\\mathsf{s p}^{2}$ domains of N-doped graphene samples from Raman spectra. \nnote S4. Brief explanation of ac impedance of N-doped graphene samples. \ntable S1. Structural and compositional parameters of nitrogen-doped graphene catalysts. table S2. Surface nitrogen and oxygen species concentrations of nitrogen-doped graphene catalysts. \ntable S3. Comparison of ORR and OER performances of our N-doped graphene nanoribbon networks with the recently reported highly active bifunctional catalysts. \nvideo S1. The evolution of $\\mathsf{O}_{2}$ bubbles at potentials from 1.6 to $1.8~\\mathsf{V}$ versus RHE. \nvideos S2 and S3. The demonstration of water splitting driven by a single zinc-air battery. \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/2/4/e1501122/DC1 Experimental Section fig. S1. Molecular structures of precursors. \nfig. S2. Temperature and time profile of pyrolysis and carbonization process. \nfig. S3. FESEM images of the sample after pyrolysis at different temperatures. \nfig. S4. Low-magnification FESEM image of the N-GRW. \nfig. S5. FESEM images of samples prepared with different melamine–to–L-cysteine ratios. \nfig. S6. XPS spectra of ${C_{3}N_{4}}$ and S-doped $C_{3}N_{4}$ . \nfig. S7. TEM and FESEM images of $C_{3}N_{4}$ and S-doped $\\mathsf{C}_{3}\\mathsf{N}_{4}.$ . \nfig. S8. Nitrogen adsorption isotherms of ${C_{3}N_{4}}$ and S-doped $C_{3}N_{4}$ . \nfig. S9. TGA and heat flow curves of S-doped $C_{3}N_{4}$ . \nfig. S10. XPS spectra of S-doped $C_{3}N_{4}$ and S-doped $C_{3}N_{4}$ carbonized at $800^{\\circ}\\mathsf{C}$ . \nfig. S11. Nitrogen adsorption isotherms of S-doped $\\mathsf{C}_{3}\\mathsf{N}_{4}$ and S-doped $\\mathsf{C}_{3}\\mathsf{N}_{4}$ carbonized at $800^{\\circ}\\mathsf{C}$ . \nfig. S12. S2p core XPS spectra of S-doped $C_{3}N_{4}$ and S-doped $C_{3}N_{4}$ carbonized at $800^{\\circ}$ to $1000^{\\circ}\\mathsf C$ . \nfig. S13. FESEM and TEM images of N-HGS and N-GS. \nfig. S14. Nitrogen adsorption isotherms and pore size distribution of N-doped graphene samples. \nfig. S15. C1s, N1s, and O1s core level high-resolution XPS spectra of the N-GRW, N-HGS, and N-GS. \n\n# REFERENCES AND NOTES \n\n1. R. Schlögl, The role of chemistry in the energy challenge. ChemSusChem 3, 209–222 (2010). \n2. G. Centi, S. Perathoner, Towards solar fuels from water and ${\\mathsf{C O}}_{2}.$ ChemSusChem 3, 195–208 (2010). \n3. I. Katsounaros, S. Cherevko, A. R. Zeradjanin, K. J. Mayrhofer, Oxygen electrochemistry as a cornerstone for sustainable energy conversion. Angew. Chem. Int. Ed. 53, 102–121 (2014). \n4. A. Fujishima, K. Honda, Electrochemical Photolysis of water at a semiconductor electrode. Nature 238, 37–38 (1972). \n5. Y. Liang, Y. Li, H. Wang, J. Zhou, J. Wang, T. Regier, H. Dai, ${\\mathsf{C o}}_{3}{\\mathsf{O}}_{4}$ nanocrystals on graphene as a synergistic catalyst for oxygen reduction reaction. Nat. Mater. 10, 780–786 (2011). \n6. W. T. Hong, M. Risch, K. A. Stoerzinger, A. Grimaud, J. Suntivich, Y. Shao-Horn, Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis. Energy Environ. Sci. 8, 1404–1427 (2015). \n7. T. Y. Ma, J. Ran, S. Dai, M. Jaroniec, S. Z. Qiao, Phosphorus-doped graphitic carbon nitrides grown in situ on carbon-fiber paper: Flexible and reversible oxygen electrodes. Angew. Chem. Int. Ed. 54, 4646–4650 (2015). \n8. Y.-C. Lu, Z. Xu, H. A. Gasteiger, S. Chen, K. Hamad-Schifferli, Y. Shao-Horn, Platinum−gold nanoparticles: A highly active bifunctional electrocatalyst for rechargeable lithium−air batteries. J. Am. Chem. Soc. 132, 12170–12171 (2010). \n9. G. Wu, N. H. Mack, W. Gao, S. Ma, R. Zhong, J. Han, J. K. Baldwin, P. Zelenay, Nitrogendoped graphene-rich catalysts derived from heteroatom polymers for oxygen reduction in nonaqueous lithium– ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ battery cathodes. ACS Nano 6, 9764–9776 (2012). \n10. Q. Li, R. Cao, J. Cho, G. Wu, Nanocarbon electrocatalysts for oxygen reduction in alkaline media for advanced energy conversion and storage. Adv. Eng. Mater. 4, 1301415–1301433 (2014). \n11. S. Chen, J. Duan, M. Jaroniec, S. Z. Qiao, Three-dimensional N-doped graphene hydrogel/ NiCo double hydroxide electrocatalysts for highly efficient oxygen evolution. Angew. Chem. Int. Ed. 52, 13567–13570 (2013). \n12. S. Chen, J. Duan, J. Ran, M. Jaroniec, S. Z. Qiao, N-doped graphene film-confined nickel nanoparticles as a highly efficient three-dimensional oxygen evolution electrocatalyst. Energy Environ. Sci. 6, 3693–3699 (2013). \n13. M. K. Debe, Electrocatalyst approaches and challenges for automotive fuel cells. Nature 486, 43–51 (2012). \n14. M. Piana, S. Catanorchi, H. A. Gasteiger, Kinetics of non-platinum group metal catalysts for the oxygen reduction reaction in alkaline medium. ECS Trans. 16, 2045–2055 (2008). \n15. T. R. Cook, D. K. Dogutan, S. Y. Reece, Y. Surendranath, T. S. Teets, D. G. Nocera, Solar energy supply and storage for the legacy and nonlegacy worlds. Chem. Rev. 110, 6474–6502 (2010). \n16. Y. Jiao, Y. Zheng, M. Jaroniec, S. Z. Qiao, Design of electrocatalysts for oxygen- and hydrogeninvolving energy conversion reactions. Chem. Soc. Rev. 44, 2060–2086 (2015). \n17. J. Duan, S. Chen, M. Jaroniec, S. Z. Qiao, Heteroatom-doped graphene-based materials for energy-relevant electrocatalytic processes. ACS Catal. 5, 5207–5234 (2015). \n18. V. R. Stamenkovic, B. Fowler, B. S. Mun, G. Wang, P. N. Ross, C. A. Lucas, N. M. Marković, Improved oxygen reduction activity on $\\mathsf{P t}_{3}\\mathsf{N i}(111)$ via increased surface site availability. Science 315, 493–497 (2007). \n19. C. Chen, Y. Kang, Z. Huo, Z. Zhu, W. Huang, H. L. Xin, J. D. Snyder, D. Li, J. A. Herron, M. Mavrikakis, M. Chi, K. L. More, Y. Li, N. M. Markovic, G. A. Somorjai, P. Yang, V. R. Stamenkovic, Highly crystalline multimetallic nanoframes with three-dimensional electrocatalytic surfaces. Science 343, 1339–1343 (2014). \n20. Y. Lee, J. Suntivich, K. J. May, E. E. Perry, Y. Shao-Horn, Synthesis and activities of rutile $\\mathsf{I r O}_{2}$ and ${\\mathsf{R u O}}_{2}$ nanoparticles for oxygen evolution in acid and alkaline solutions. J. Phys. Chem. Lett. 3, 399–404 (2012). \n21. T. Nakagawa, C. A. Beasley, R. W. Murray, Efficient electro-oxidation of water near its reversible potential by a mesoporous $\\mathsf{I r O}_{x}$ nanoparticle film. J. Phys. Chem. C 113, 12958–12961 (2009). \n22. G. Wu, K. L. More, C. M. Johnston, P. Zelenay, High-performance electrocatalysts for oxygen eduction derived from polyaniline, iron, and cobalt. Science 332, 443–447 (2011). \n23. M. Steenackers, A. M. Gigler, N. Zhang, F. Deubel, M. Seifert, L. H. Hess, C. H. Y. X. Lim, K. P. Loh, J. A. Garrido, R. Jordan, M. Stutz ann, I. D. Sharp, Polymer brushes on graphene. J. Am. Chem. Soc. 133, 10490–10498 (2011). \n24. S. M. Kang, S. Park, D. Kim, S. Y. Park, R. S. Ruoff, H. Lee, Simultaneous reduction and surface functionalization of graphene oxide by mussel-inspired chemistry. Adv. Funct. Mater. 21, 108–112 (2011). \n25. T. Y. Ma, S. Dai, M. Jaroniec, S. Z. Qiao, Graphitic carbon nitride nanosheet–carbon nanotube three-dimensional porous composites as high-performance oxygen evolution electrocatalysts. Angew. Chem. Int. Ed. 53, 7281–7285 (2014). \n26. L. Jiao, X. Wang, G. Diankov, H. Wang, H. Dai, Facile synthesis of high-quality graphene nanoribbons. Nat. Nanotechnol. 5, 321–325 (2010). \n27. D. Yu, K. Goh, H. Wang, L. Wei, W. Jiang, Q. Zhang, L. Dai, Y. Chen, Scalable synthesis of hierarchically structured carbon nanotube-graphene fibres for capacitive energy storage. Nat. Nanotechnol. 9, 555–562 (2014). \n28. L. Ci, L. Song, D. Jariwala, A. L. Elias, W. Gao, M. Terrones, P. M. Ajayan, Graphene shape control by multistage cutting and transfer. Adv. Mater. 21, 4487–4491 (2009). \n29. L. Jiao, L. Zhang, X. Wang, G. Diankov, H. Dai, Narrow graphene nanoribbons from carbon nanotubes. Nature 458, 877–880 (2009). \n30. Y.-Z. Tan, B. Yang, K. Parvez, A. Narita, S. Osella, D. Beljonne, X. Feng, K. Müllen, Atomically precise edge chlorination of nanographenes and its application in graphene nanoribbons. Nat. Commun. 4, 2646–2652 (2013). \n31. X.-H. Li, M. Antonietti, Polycondensation of boron- and nitrogen-codoped holey graphene monoliths from molecules: Carbocatalysts for selective oxidation. Angew. Chem. Int. Ed. 52, 4572–4576 (2013). \n32. J. P. Paraknowitsch, A. Thomas, Doping carbons beyond nitrogen: An overview of advanced heteroatom doped carbons with boron, sulphur and phosphorus for energy applications. Energy Environ. Sci. 6, 2839–2855 (2013). \n33. X. Wang, X. Li, L. Zhang, Y. Yoon, P. K. Weber, H. Wang, J. Guo, H. Dai, N-doping of graphene through electrothermal reactions with ammonia. Science 324, 768–771 (2009). \n34. X. Wang, G. Sun, P. Routh, D.-H. Kim, W. Huang, P. Chen, Heteroatom-doped graphene materials: Syntheses, properties and applications. Chem. Soc. Rev. 43, 7067–7098 (2014). \n35. J. Liang, Y. Jiao, M. Jaroniec, S. Z. Qiao, Sulfur and nitrogen dual-doped mesoporous graphene electrocatalyst for oxygen reduction with synergistically enhanced performance. Angew. Chem. Int. Ed. 51, 11496–11500 (2012). \n36. Z. Ma, S. Dou, A. Shen, L. Tao, L. Dai, S. Wang, Sulfur-doped graphene derived from cycled lithium-sulfur batteries as a metal-free electrocatalyst for the oxygen reduction reaction. Angew. Chem. Int. Ed. 54, 1888–1892 (2015). \n37. J. Shui, M. Wang, F. Du, L. Dai, N-doped carbon nanomaterials are durable catalysts for oxygen reduction reaction in acidic fuel cells. Sci. Adv. 1, e1400129 (2015). \n38. S. Chen, J. Duan, M. Jaroniec, S. Z. Qiao, Nitrogen and oxygen dual-doped carbon hydrogel film as a substrate-free electrode for highly efficient oxygen evolution reaction. Adv. Mater. 26, 2925–2930 (2014). \n39. Y. Li, W. Zhou, H. Wang, L. Xie, Y. Liang, F. Wei, J.-C. Idrobo, S. J. Pennycook, H. Dai, An oxygen reduction electrocatalyst based on carbon nanotube–graphene complexes. Nat. Nanotechnol. 7, 394–400 (2012). \n40. X. Lu, W.-L. Yim, B. H. R. Suryanto, C. Zhao, Electrocatalytic oxygen evolution at surfacexidized multiwall carbon nanotubes. J. Am. Chem. Soc. 137, 2901–2907 (2015). \n41. Y. Zhao, R. Nakamura, K. Kamiya, S. Nakanishi, K. Hashimoto, Nitrogen-doped carbon nanomaterials as non-metal electrocatalysts for water oxidation. Nat. Commun. 4, 2390 (2013). \n42. J. Zhang, Z. Zhao, Z. Xia, L. Dai, A metal-free bifunctional electrocatalyst for oxygen reduction and oxygen evolution reactions. Nat. Nanotechnol. 10, 444–452 (2015). \n43. G.-L. Tian, Q. Zhang, B. Zhang, Y.-G. Jin, J.-Q. Huang, D. S. Su, F. Wei, Toward full exposure of “active sites”: Nanocarbon electrocatalyst with surface enriched nitrogen for superior oxygen reduction and evolution reactivity. Adv. Funct. Mater. 24, 5956–5961 (2014). \n44. G.-L. Tian, M.-Q. Zhao, D. Yu, X.-Y. Kong, J.-Q. Huang, Q. Zhang, F. Wei, Nitrogen-doped graphene/carbon nanotube hybrids: In situ formation bifunctional catalysts and thei superior electrocatalytic activity for oxygen evolution/reduction reaction. Small 10, 2251–2259 (2014). \n45. Y. Ito, W. Cong, T. Fujita, Z. Tang, M. Chen, High catalytic activity of nitrogen and sulfur codoped nanoporous graphene in the hydrogen evolution reaction. Angew. Chem. Int. Ed. 4, 2131–2136 (2015). \n46. I. Y. Jeon, S. Zhang, L. Zhang, H. J. Choi, J. M. Seo, Z. Xia, L. Dai, J. B. Baek, Edge-selectively sulfurized graphene nanoplatelets as efficient metal-free electrocatalysts for oxygen reduction reaction: The electron spin effect. Adv. Mater. 25, 6138–6145 (2013). \n47. J. Long, X. Xie, J. Xu, Q. Gu, L. Chen, X. Wang, Nitrogen-doped graphene nanosheets as metal-free catalysts for aerobic selective oxidation of benzylic alcohols. ACS Catal. 2, 622–631 (2012). \n48. A. Taylor, The study of carbon by the Debye-Scherrer method. J. Sci. Instrum. 18, 90 (1941). \n49. F. Tuinstra, J. L. Koenig, Raman spectrum of graphite. J. Chem. Phys. 53, 1126–1130 (1970). \n50. M. J. Matthews, M. A. Pimenta, G. Dresselhaus, M. S. Dresselhaus, M. Endo, Origin of disrsive effects of the Raman D band in carbon materials. Phys. Rev. B 59, R6585–R6588 (1999). \n51. A. Shen, Y. Zou, Q. Wang, R. A. W. Dryfe, X. Huang, S. Dou, L. Dai, S. Wang, Oxygen reduction reaction in a droplet on graphite: Direct evidence that the edge is more active than the basal plane. Angew. Chem. Int. Ed. 53, 10804–10808 (2014). \n52. W. Yuan, Y. Zhou, Y. Li, C. Li, H. Peng, J. Zhang, Z. Liu, L. Dai, G. Shi, The edge- and basalplane-specific electrochemistry of a single-layer graphene sheet. Sci. Rep. 3, 2248 (2013). \n53. J. Jiang, J. Turnbull, W. Lu, P. Boguslawski, J. Bernholc, The y of nitrogen doping of carbon nanoribbons: Edge effects. J. Chem. Phys. 136, 014702 (2012). \n54. D. Usachov, O. Vilkov, A. Grüneis, D. Haberer, A. Fedorov, V. K. Adamchuk, A. B. Preobrajenski, P. Dudin, A. Barinov, M. Oehzelt, C. Laubschat, D. V. Vyalikh, Nitrogendoped graphene: Efficient growth, structure, and electronic properties. Nano Lett. 11, 5401–5407 (2011). \n55. H. S. Kim, H. S. Kim, S. S. Kim, Y.-H. Kim, Atomistic mechanisms of codoping-induced p- to n-type conversion in nitrogen-doped graphene. Nanoscale 6, 14911–14918 (2014). \n56. H. Liu, Y. Liu, D. Zhu, Chemical doping of graphene. J. Mater. Chem. 21, 3335–3345 (2011). \n57. C. H. Choi, H.-K. Lim, M. W. Chung, J. C. Park, H. Shin, H. Kim, S. I. Woo, Long-range electron transfer over graphene-based catalyst for high-performing oxygen reduction reactions Importance of size, N-doping, and metallic impurities. J. Am. Chem. Soc. 136, 9070–9077 (2014). \n58. H. Kim, K. Lee, S. I. Woo, Y. Jung, On the mechanism of enhanced oxygen reduction reaction in nitrogen-doped graphene nanoribbons. Phys. Chem. Chem. Phys. 13, 17505–17510 (2011). \n59. L. Lai, J. R. Potts, D. Zhan, L. Wang, C. K. Poh, C. Tang, H. Gong, Z. Shen, J. Lin, R. S. Ruoff, Exploration of the active center structure of nitrogen-doped graphene-based catalysts for oxygen reduction reaction. Energy Environ. Sci. 5, 7936–7942 (2012). \n60. J. Y. Cheon, J. H. Kim, J. H. Kim, K. C. Goddeti, J. Y. Park, S. H. Joo, Intrinsic relationship between enhanced oxygen reduction reaction activity and nanoscale work function of doped carbons. J. Am. Chem. Soc. 136, 8875–8878 (2014). \n61. M. W. Chung, C. H. Choi, S. Y. Lee, S. I. Woo, Dimensionality-dependent oxygen reduction activity on doped graphene: Is graphene a promising substrate for electrocatalysis? Nano Energy 11, 526–532 (2015). \n62. R. Eba Medjo, B. Thiodjio Sendja, J. Mane Mane, P. Owono Ateba, A study of carbon nanotube contamination by XANES spectroscopy. Phys. Scr. 80, 045601 (2009). \n63. D. Pacilé, J. C. Meyer, A. Fraile Rodríguez, M. Papagno, C. Gómez-Navarro, R. S. Sundara M. Burghard, K. Kern, C. Carbone, U. Kaiser, Electronic properties and atomic structure of graphene oxide membranes. Carbon 49, 966–972 (2011). \n64. B. J. Schultz, C. J. Patridge, V. Lee, C. Jaye, P. S. Lysaght, C. Smith, J. Barnett, D. A. Fischer, D. Prendergast, S. Banerjee, Imaging local electronic corrugations and doped regions in graphene. Nat. Commun. 2, 372 (2011). \n65. Z. Hou, X. Wang, T. Ikeda, K. Terakura, M. Oshima, M.-A. Kakimoto, Electronic structure of N-doped graphene with native point defects. Phys. Rev. B 87, 165401 (2013). \n66. L. Mino, G. Agostini, E. Borfecchia, D. Gianolio, A. Piovano, E. Gallo, C. Lamberti, Lowdimensional systems investigated by x-ray absorption spectroscopy: A selection of 2D, \n1D and 0D cases. J. Phys. D Appl. Phys. 46, 423001–423072 (2013). \n67. Z. Luo, S. Lim, Z. Tian, J. Shang, L. Lai, B. MacDonald, C. Fu, Z. Shen, T. Yu, J. Lin, Pyridinic N doped graphene: Synthesis, electronic structure, and electrocatalytic property. J. Mater. Chem. 21, 8038–8044 (2011). \n68. Y. Okamoto, First-principles molecular dynamics simulation of $\\mathsf{O}_{2}$ reduction on nitrogendoped carbon. Appl. Surf. Sci. 256, 335–341 (2009). \n69. H. Dau, C. Limberg, T. Reier, M. Risch, S. Roggan, P. Strasser, The mechanism of water oxidation: From electrolysis via homogeneous to biological catalysis. ChemCatChem 2, 724–761 (2010). \n70. I. C. Man, H.-Y. Su, F. Calle-Vallejo, H. A. Hansen, J. I. Martínez, N. G. Inoglu, J. Kitchin, T. F. Jaramillo, J. K. Nørskov, J. Rossmeisl, Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem 3, 1159–1165 (2011). \n71. T. Maiyalagan, K. A. Jarvis, S. Therese, P. J. Ferreira, A. Manthiram, Spinel-type lithium cobalt oxide as a bifunctional electrocatalyst for the oxygen evolution and oxygen reduction reactions. Nat. Commun. 5, 3949 (2014). \n72. J. Masa, W. Xia, I. Sinev, A. Zhao, Z. Sun, S. Grutzke, P. Weide, M. Muhler, W. Schuhmann, ${M n_{x}O_{y}}/{N C}$ and $\\mathsf{C o}_{x}\\mathsf{O}_{y}{\\mathsf{N C}}$ nanoparticles embedded in a nitrogen-doped carbon matrix for high-performance bifunctional oxygen electrodes. Angew. Chem. Int. Ed. 53, 8508–8512 (2014). \n73. Y. Li, H. Dai, Recent advances in zinc-air batteries. Chem. Soc. Rev. 43, 5257–5275 (2014). \n\n# Acknowledgments \n\nFunding: This work was supported by Nanyang Technological University startup grant (M4080977.120); Singapore Ministry of Education Academic Research Fund (AcRF) Tier 1 (M4011021.120); National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) program; Air Force Office of Scientific Research (FA-9550-12-1-0037); and NSF (CMMI-1400274). Author contributions: H.B.Y., L.D., and B.L. conceived and designed the experiments. H.B.Y. carried out synthesis of the catalysts and performed the experiments on electrochemical testing. S.-F.H. and H.M.C. performed the XANES characterization. J.M., J.C., and H.B.T. contributed to the data analysis. X.W. performed the UPS study. L.Z. characterized the samples using XRD. J.G. contributed to the TGA experiments. R.C. helped on the water electrolysis studies. L.D. and B.L. supervised the entire project, and H.B.Y., L.D., and B.L. wrote the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 17 August 2015 \nAccepted 24 March 2016 \nPublished 22 April 2016 \n10.1126/sciadv.1501122 \n\nCitation: H. B. Yang, J. Miao, S.-F. Hung, J. Chen, H. B. Tao, X. Wang, L. Zhang, R. Chen, J. Gao, H. M. Chen, L. Dai, B. Liu, Identification of catalytic sites for oxygen reduction and oxygen evolution in N-doped graphene materials: Development of highly efficient metal-free bifunctional electrocatalyst. Sci. Adv. 2, e1501122 (2016). \n\n# ScienceAdvances \n\nIdentification of catalytic sites for oxygen reduction and oxygen evolution in N-doped graphene materials: Development of highly efficient metal-free bifunctional electrocatalyst \n\nHong Bin Yang, Jianwei Miao, Sung-Fu Hung, Jiazang Chen, Hua Bing Tao, Xizu Wang, Liping Zhang, Rong Chen, Jiajian Gao, Hao Ming Chen, Liming Dai and Bin Liu \n\nSci Adv 2 (4), e1501122. DOI: 10.1126/sciadv.1501122 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nhttp://advances.sciencemag.org/content/suppl/2016/04/19/2.4.e1501122.DC1 \n\nREFERENCES \n\nThis article cites 73 articles, 6 of which you can access for free http://advances.sciencemag.org/content/2/4/e1501122#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1002_anie.201508505", + "DOI": "10.1002/anie.201508505", + "DOI Link": "http://dx.doi.org/10.1002/anie.201508505", + "Relative Dir Path": "mds/10.1002_anie.201508505", + "Article Title": "Phosphorus-Doped Carbon Nitride Tubes with a Layered Micro-nullostructure for Enhanced Visible-Light Photocatalytic Hydrogen Evolution", + "Authors": "Guo, SE; Deng, ZP; Li, MX; Jiang, BJ; Tian, CG; Pan, QJ; Fu, HG", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "Phosphorus-doped hexagonal tubular carbon nitride (P-TCN) with the layered stacking structure was obtained from a hexagonal rod-like single crystal supramolecular precursor (monoclinic, C2/m). The production process of P-TCN involves two steps: 1) the precursor was prepared by self-assembly of melamine with cyanuric acid from in situ hydrolysis of melamine under phosphorous acid-assisted hydrothermal conditions; 2) the pyrolysis was initiated at the center of precursor under heating, thus giving the hexagonal P-TCN. The tubular structure favors the enhancement of light scattering and active sites. Meanwhile, the introduction of phosphorus leads to a narrow band gap and increased electric conductivity. Thus, the P-TCN exhibited a high hydrogen evolution rate of 67 mu mol.h(-1) (0.1 g catalyst, lambda > 420 nm) in the presence of sacrificial agents, and an apparent quantum efficiency of 5.68% at 420 nm, which is better than most of bulk g-C3N4 reported.", + "Times Cited, WoS Core": 1032, + "Times Cited, All Databases": 1059, + "Publication Year": 2016, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000369854000043", + "Markdown": "# Phosphorus-Doped Carbon Nitride Tubes with a Layered Micronanostructure for Enhanced Visible-Light Photocatalytic Hydrogen Evolution \n\nShien Guo, Zhaopeng Deng, Mingxia Li, Baojiang Jiang,\\* Chungui Tian, Qingjiang Pan, and Honggang Fu\\* \n\nAbstract: Phosphorus-doped hexagonal tubular carbon nitride (P-TCN) with the layered stacking structure was obtained from a hexagonal rod-like single crystal supramolecular precursor (monoclinic, C2/m). The production process of P-TCN involves two steps: 1) the precursor was prepared by self-assembly of melamine with cyanuric acid from in situ hydrolysis of melamine under phosphorous acid-assisted hydrothermal conditions; 2) the pyrolysis was initiated at the center of precursor under heating, thus giving the hexagonal $P$ - TCN. The tubular structure favors the enhancement of light scattering and active sites. Meanwhile, the introduction of phosphorus leads to a narrow band gap and increased electric conductivity. Thus, the P-TCN exhibited a high hydrogen evolution rate of 67 mmol $h^{-I}$ (0.1 g catalyst, $\\lambda>420n m$ ) in the presence of sacrificial agents, and an apparent quantum efficiency of $5.68\\%$ at 420 nm, which is better than most of bulk $g_{-}C_{3}N_{4}$ reported. \n\nGraphitic carbon nitride (g-C3N4, labeled GCN), as a metalfree organic semiconductor, has attracted increasing attention because it possesses high thermal and chemical stability and an appealing electronic structure.[1] These unique properties of GCN allow for its diverse applications, such as photocatalytic hydrogen evolution, the oxygen reduction reaction (ORR), and oxygen evolution reaction (OER).[2–4] Bulk GCN obtained by the direct thermal polymerization process generally yields relatively low surface areas and less active sites for GCN, which significantly restricts its applications.[5] Additionally, the quantum efficiency of GCN in the visible light region needs to be further improved. The fabrication of hierarchical micro-nanostructures and heterogeneous element doping for GCN are two effective methods to solve the above problems. Typically, various kinds of micro-nanostructure GCN, including porous GCN, sphere GCN, and tubular GCN, were obtained through a hard-templating approach.[6,7] Nevertheless, this type of templating is time- and costinefficient, for it requires environmentally hazardous reagents to remove the template and prohibits further functionalization. Besides that, the chemical doped GCN with foreign elements, such as phosphorus and sulfur, can tune the energy band structure and conductivity of GCN, thus enhancing the visible-light photocatalytic quantum efficiency as well as improving their surface properties of GCN.[8] This means that the GCN with novel hierarchical micro-nanostructure and simultaneous nonmetal element doping by the template-free method is highly desirable but poses challenges. \n\nTo date, self-assembled supermolecular precursors by hydrogen bonding among molecules have emerged as a potential selection to prepare specially-shaped micro-nano materials, as hydrogen bonding has strong direction and saturation.[9] The ordered and hollow GCN structures had been synthesized using the cyanuric acid-melamine complex as a starting material.[10] The GCN microspheres and microsheets were also prepared using similar method by controlling precipitation temperature and selecting proper organic solvents.[11] The supramolecular precursors mentioned above were mainly produced by the assembly of two or more components under organic solvents. Undoubtedly, use of water solvent is more beneficial to molecule self-assembly based on hydrogen bonding, forming the stable, large-sized, and regular supramolecular precursors. It is well known that melamine could be transformed into cyanuric acid at a suitable pH value.[12] It would be desirable that supramolecular precursor can be synthesized in situ from a single melamine molecular source using acidic aqueous solution like phosphorous acid. The phosphorous acid not only could adjust pH value to prompt the hydrolysis of melamine into cyanuric acid, but also provide potential P source for the P-doping on GCN. Thus, we chose melamine and phosphorous acid as starting materials to produce the P-doped carbon nitride in situ with special hierarchical micro-nanostructure. \n\nHerein, the fabrication process of phosphorus-doped hexagonal tubular carbon nitride (P-TCN) is shown as Scheme 1 (experimental details are given in the Supporting Information). Simply, melamine and phosphorous acid was dissolved in deionized water under heating. Then, under phosphorous acid assisted hydrothermal conditions $\\left(\\operatorname{pH}1-3\\right)$ , the melamine was partly hydrolyzed in situ into cyanuric acid. Then the regular and stable hexagonal cylinder precursors were finally prepared through the molecule self-assembly between melamine and cyanuric acid (for the main reactions in the synthesis, see the Supporting Information, Scheme S1). Simultaneously, the phosphorous acid molecules could adsorb on the surface of precursor. After the thermal treatment, P from phosphorous acid squeezed into the GCN skeleton and the P-TCN was formed. It exhibited enhanced visible-light photocatalytic properties owing to the hierarchical micronanostructure and the $\\mathrm{~\\bf~P~}$ doping of GCN. \n\n![](images/b1cd95adb69ef54d8f2be559e93e0ba53d8237f660b5c6eb6d485aa3a9b3ff8e.jpg) \nScheme 1. The formation process of phosphorus-doped tubular carbon nitride. \n\nAs shown in SEM images, supramolecular precursors for P-TCN (pH 1) possess a hexagonal rod structure with a length up to $300{-}500\\upmu\\mathrm{m}$ and a diameter of $60{-}100~{\\upmu\\mathrm{m}}$ (Figure 1 a). A high-magnification image (Figure 1b) reveals that the hexagonal rod precursors are composed of numbers of twodimensional sheets. Then the supramolecular complex precursor was analyzed by a single-crystal X-ray diffractometer (Supporting Information, Figure S1). The analysis results show that the melamine and cyanuric acid are held together by multiple hydrogen bonds in the same plane, yielding the hexamer, similar to previous reports.[9c] The cyanuric acid is from the partial in situ hydrolysis of melamine. The partial conversion of melamine into cyanuric acid and gradual formation of the supramolecular precursor are confirmed by FTIR spectroscopy (Supporting Information, Figures S2, S3) and XRD (Figures S4, S5). Meanwhile, the planar sheets consisting of condensed tri-s-triazine units are stacked in a perpendicular direction to the sheets via $\\pi{-}\\pi$ interactions (the interlayer space is $3.224\\mathring{\\mathrm{A}}$ ), the structure being exactly as analyzed by SEM. Furthermore, the single crystal data and structure refinement for supramolecular precursor are also shown in the Supporting Information, Table S1. It is noted that the elemental analysis mapping (Supporting Information, Figure S6) show the homogeneous distribution of C, N, O and P elements. The presence of P should be from the adsorption of P-containing species on the supramolecular structure because single-crystal data does not display any P-containing species within supramolecular framework. A series of control experiments (Supporting Information, Figures S5, S7, S8) confirm that the reaction of melamine with cyanuric acid is slow. Once the cyanuric acid is formed in situ, the remaining melamine can react with cyanuric acid to form a supramolecular structure rapidly owing to the strong interactions. The phosphorous acid cannot be incorporated into the framework because of its weak interaction with malamine; it can only adsorb on the surface of the supramolecular structure. After polycondensation at $500^{\\circ}\\mathrm{C}$ for $^{4\\mathrm{h}}$ , the transition from hexagonal rod to hexagonal tube has occurred as shown in Figure 1 c,d. It is clear that tubular external morphology of typical sample P-TCN (pH 1) is well maintained during the polycondensation, which is distinctly different from that of bulk GCN (Supporting Information, Figure S9 b). Moreover, the carbon nitride obtained from the pyrolysis of the precursor that is prepared in the absence of phosphorous also has irregular morphology (Supporting Information, Figure S9 d). These results confirm that the presence of phosphorous acid and the slow-release of cyanuric acid by the in situ hydrolyzation of melamine are very important for the formation of P-TCN. The similar tubular structures are also obtained at $\\mathrm{pH}2$ or $\\mathrm{pH}3$ (Supporting Information, Figure S10). Subsequent inestigations mainly focus on the typical sample P-TCN $\\mathrm{(pH1)}$ . In Figure 1 e,f, the TEM measurements further confirmed that the desired hexagonal tube is successfully obtained. Additionally, the structural shrinkage leads to the formation of pores of $40{-}60~\\mathrm{nm}$ embedded in the tube wall of P-TCN. It can be expected that this micro-nanostructure will enhance the accessibility of catalytic sites. To deepen understanding of the formation mechanism of P-TCN, TGA-MS was conducted (Supporting Information, Figure S11a,b). The formation of hexagonal tubes was mainly due to the release of gas, including $\\mathrm{NH}_{3}$ , $\\mathrm{NO}_{2}$ , NO, $\\mathbf{N}_{2}\\mathbf{O}/\\mathbf{CO}_{2}$ , $\\mathrm{PH}_{3}$ , and P, after pyrolysis of the supramolecular complex. These results are different from the pyrolysis of melamine (Supporting Information, Figure S12). The supramolecular precursor for carbon nitride tube was also analyzed by the TGA-MS (Supporting Information, Figure S11c,d). For the supramolecular precursor, a high density of defects probably existed at the center of the hexagonal rod because of quickly crystallizing at the early stage of hydrothermal reaction (Supporting Information, Figure S13). The phosphorous acid adsorbed on surface of precursor will also further strengthen its surface stability. Therefore, the pyrolysis or etching of precursor starts at the center of hexagonal rod, and gradually extends outward to form tube-like structure. Moreover, the speculation is also further evidenced by a series of SEM images (Supporting Information, Figure S14). \n\n![](images/493f1dc2c934361d9052388f650a7a10a8245bf9466a2b4eab2a400f6dd4da15.jpg) \nFigure 1. a), b) SEM images of supramolecular precursor, c), d) SEM images of P-TCN $(\\mathsf{P H}=\\mathsf{7})$ ), and e), f) TEM images of P-TCN (pH 1). \n\nThe TGA-MS results suggest that the release of phosphorous species during the synthesis of P-TCN, while there is still part of phosphorous species has been successfully introduced into the GCN lattice, as shown in elemental mapping images (Supporting Information, Figure S15). During the synthesis of P-TCN, phosphorous acid plays a key role like accelerating dissolution and hydrolysis of melamine, and stabilizing the precursor framework because of its acid–base interactions with melamine. Then the $\\mathrm{~\\bf~P~}$ modified precursor was further condensed under $500^{\\circ}\\mathrm{C}$ under nitrogen, resulting in the P-TCN. As XRD patterns show (Figure 2a), the (002) peak centered at $27.7^{\\circ}$ becomes broader and weaker and shifts to slightly lower scattering angles compared with the GCN, indicating the evident sizedependent properties of tube structure.[13] The specific surface area of P-TCN is $22.95\\mathrm{{m}^{2}\\mathrm{{g}^{-1}}}$ , which is about 7 times than that of GCN at $3.73\\mathrm{m}^{2}\\mathrm{g}^{-1}$ (Supporting Information, Figure S16). P-TCN with large specific surface areas could provide more surface active sites. With no doubt, the special micro-nanostructure structure and introduced P heteroatom are expected to not only change the optical and electronic band structure, but also the charge-transfer efficiency of the GCN. \n\n![](images/37453f188dfdc9fb9ce70709eedde2479d911aa84f9c1f0854550d44ddeaa4e8.jpg) \nFigure 2. a) XRD patterns and b)–d) high-resolution $\\mathsf{X P S}$ spectra of b) C 1s, c) N 1s, and d) $\\mathsf{P2p}$ that are obtained from P-TCN (pH 1). \n\nFurther detailed electronic structures and chemical environment of C, N, and $\\mathrm{~\\bf~P~}$ elements in the sample P-TCN were analyzed with $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) measurements. In the C 1s spectrum (Figure 2 b), the mainly carbon species centering at $284.6\\mathrm{eV}$ and $288.0\\mathrm{eV}$ are assigned to the graphitic carbon (C¢C) and the $\\displaystyle\\mathbf{sp}^{2}$ -hybridized carbon in the $N$ -containing aromatic ring $N{\\mathrm{-C}}{\\mathrm{=N}}$ ), respectively.[14] For the N 1s spectrum (Figure 2 c), the small peak located at $404.2\\mathrm{eV}$ is attributed to the positive charge localization in heterocycles; the big one starting from $396.4\\mathrm{eV}$ to $402.7\\mathrm{eV}$ can be deconvoluted into three peaks, including $398.4\\mathrm{eV}$ for $\\displaystyle\\mathbf{sp}^{2}$ -hybridized nitrogen in triazine rings $\\left(\\mathrm{C-N}{=}\\mathrm{C}\\right)$ , $400.0\\mathrm{eV}$ for tertiary nitrogen $N_{-}(\\mathrm{C})_{3}$ groups and $400.9\\mathrm{eV}$ for amino functions carrying hydrogen ( $\\scriptstyle(\\mathbf{C}-\\mathbf{N}-$ H). The peak of the amino carrying $\\mathbf{N}$ species $(400.9\\mathrm{eV})$ is found to be much higher than that in GCN $(401.6\\mathrm{eV}$ ; Supporting Information, Figure S17), which is attributed to the special surface structure.[15] Furthermore, the shift of peak position also suggests the electron structure change for PTCN. The peak of $\\mathrm{~P~}2\\mathrm{p}$ binding energy is centered at $133.5\\mathrm{eV},$ which is typical for $\\scriptstyle\\mathrm{P-N}$ coordination (P¢C bonding would be $1{-}2\\mathrm{eV}$ lower), indicating that P most probably replaces C in triazine rings to form $\\scriptstyle\\mathrm{P-N}$ bonds (Figure 2 d).[16] Furthermore, the NMR investigations of P-TCN on the $\\mathrm{^{31}P}$ show signals between 10 and $-20\\mathrm{ppm}$ , which further prove the P doped in framework (Supporting Information, Figure S18).[16] The structure of the P-TCN sample is also confirmed by FTIR spectra (Supporting Information, Figure S19). The sharp peak at $802~\\mathrm{cm}^{-1}$ is caused by the breathing vibration of the triazine units.[8a] One new band at around $950\\mathrm{cm}^{-1}$ is attributed to the $\\scriptstyle\\mathrm{P-N}$ stretching mode,[8b] implying a certain amount of $\\mathrm{~\\bf~P~}$ incorporation, consistent with the EDS and XPS results. Compared with the C element, the doped P element possesses more electrons which will change the band structures of GCN and improve its electric conductivity. The element content of $\\mathrm{~\\bf~P~}$ is obtained from XPS analysis (Supporting Information, Table S2) and elemental analysis (Supporting Information, Table S3). The percentage of $\\mathrm{\\bfP}$ from the elemental analysis is $1.21\\ \\mathrm{wt\\%}$ for P-TCN $\\left(\\mathrm{pH1}\\right)$ . \n\nThe optical properties and band structures of the samples were analyzed by UV/Vis light absorption spectra and XPS valence band spectra. The formation of hexagonal tube increases the light absorption of P-TCN over the entire wavelength range, which is primarily due to the multiple reflections of incident light within the micro-nanostructure tube (Figure 3a).[17] The apparent color changed from pale yellow (GCN) to brown (P-TCN) (Supporting Information, Figure S20) is ascribed to the incorporation of P element into GCN matrix. Moreover, an evident shift of photoabsorption edge from $450\\mathrm{nm}$ to $486\\mathrm{nm}$ is observed for P-TCN. The corresponding band gap energy decreases from $2.67\\mathrm{eV}$ (GCN) to $2.55\\mathrm{eV}$ (P-TCN), which is consistent with previous report.[8] Then the valence band (VB) (Figure 3b) edge potential of P-TCN and GCN were measured by the XPS valence band. The VB energy levels of P-TCN and GCN were determined to be $1.44\\mathrm{eV}$ and $1.67\\mathrm{eV}.$ respectively. Compared with that of GCN, the VB of P-TCN shifts by $0.23\\mathrm{eV}$ indicating that the electronic structure is altered owing to the P doping. Apparently, the conduction band (CB) edge of GCN and P-TCN were determined to be $-1.0\\mathrm{eV}$ and $-1.11\\mathrm{eV} $ , respectively. The CB of P-TCN shifts to more negative values can be attributed to the quantum confinement effects induced by hierarchical micro-nanostructure. The previous calculation results also show that $\\mathrm{~\\bf~P~}$ doping can increase the dispersion of the contour distribution of HOMO and LUMO, which improves the carrier mobility.[18] And this kind of electronic band structure is beneficial, for which not only possesses the thermodynamically enhanced in photocatalytic reaction, but also inhibits electron–hole recombination. It is known that photoluminescence (PL) emission is useful to disclose the efficiency of electron-hole pairs trapping, migration, and transfer in semiconductor. In Figure 3 c the photoluminescence intensity of P-TCN decreased drastically, and the decreased peak intensity further confirms a lower electron–hole recombination rate for P-TCN comparing with GCN. Then the band structure alignments of GCN and P-TCN are given in Figure 3d. \n\n![](images/4902e019c4b5c10fc6509e184c7a92c698222736b038268f0ccaf4726a521968.jpg) \nFigure 3. a) UV/Vis light absorption spectra and band gap energies (inset), b) XPS valence band spectra, c) photoluminescence spectra ( $400\\mathsf{n m}$ excitation at room temperature), and d) band structure alignments of GCN and P-TCN (pH 1), respectively. \n\nTo illustrate the separation and dynamic processes of the photogenerated charge carriers, surface photovoltage spectroscopy (SPV) was performed, and the results are shown in the Supporting Information, Figure S21. Compared with GCN, the sample P-TCN has a weak SPV response. It is assumed that the P-TCN can easily capture photoinduced electrons and inhibits the recombination of photogenerated charges, which results in low surface net charges and a weak SPV response.[19] The evolution of electronic structure for PTCN can be further revealed by the room-temperature electron paramagnetic resonance (EPR). A Lorentzian line is observed for GCN and P-TCN (Supporting Information, Figure S22), indicating the formation of unpaired electrons on $\\pi$ -conjugated CN aromatic rings.[20] However, the Lorentzian line for P-TCN can be greatly increased compared to the GCN, which is presumably due to the redistribution of electrons within P-TCN structure by the electron donation from the phosphorus species. These characterizations illustrate an encouraging result that P-TCN is favored for separation and migration of the photoinduced charge carriers, resulting in enhanced visible-light-derived hydrogen production performance. \n\nFigure 4a shows a typical time course for hydrogen production using the GCN and P-TCN (pH 1) samples under visible-light irradiation $\\lambda>420\\mathrm{nm}$ ). As presented, the average hydrogen evolution rate of the P-TCN is $67\\upmu\\mathrm{mol}\\mathrm{h}^{-1}$ , which is about seven times that of GCN $(9~\\upmu\\mathrm{mol}\\mathrm{h}^{-1})$ . No hydrogen was detected in the dark test reaction (Supporting Information, Figure S23). Meanwhile, other P-TCN samples from different $\\mathrm{pH}$ value and the TCN also exhibits high photocatalytic activity, indicating hexagonal tubes with a micro-nanostructure is beneficial for hydrogen evolution. Furthermore, the increase of P level within P-TCN could also improve its photocatalytic performance. The hydrogen production reaction was allowed to proceed for a total of 20 hours with intermittent degassing of the reaction every 4 hours (Supporting Information, Figure S24). Under the continuous hydrogen evolution, a total amount of $1.339\\mathrm{mmol}$ $\\mathrm{H}_{2}$ is produced without noticeable deterioration of the activity, which suggests the high stability of P-TCN catalyst against photocorrosion. The P-TCN catalyst demonstrates high activity for photocatalytic hydrogen evolution based on its appropriate band alignments and unique micronanostructure. Figure $\\boldsymbol{4\\mathrm{b}}$ gives the apparent quantum efficiency (AQE) values for $\\mathrm{H}_{2}$ evolution of the P-TCN catalyst under various monochromatic light irradiation conditions. As can be seen, the variation tendencies of AQE curves are similar to their UV/Vis light absorption spectra. P-TCN catalyst gives high AQE in a range of $400{\\-}450\\ \\mathrm{nm}$ and the AQE value at $420\\mathrm{nm}$ is estimated to be about $5.68\\%$ . This better photocatalytic performance for P-TCN should be attributed to the well-organized hexagonal tube frameworks; moreover, P element doping narrows the band gap and prompt the charge separation. After the photocatalytic reaction, the catalyst was recycled and then was characterized by XRD and FTIR, respectively (Supporting Information, Figure S25). Indeed, there is virtually no noticeable alternation in the structure of the catalyst before and after the reaction, again reflecting the robust nature of P-TCN. \n\n![](images/edf0d8ef8d33336ac25f9ddaf2f8f71a53c587b2cbed89572d49866c09ec22db.jpg) \nFigure 4. a) Time course of ${\\sf H}_{2}$ evolution for GCN, TCN, and P-TCN (pH 1) under visible light irradiation $(\\lambda>420\\mathsf{n m})$ , and b) wavelengthdependent AQE of ${\\sf H}_{2}$ evolution over 1 wt % Pt/P-TCN (left axis), UV/ Vis light absorption spectra of P-TCN (right axis). c) Polarization curves of GCN and P-TCN; d) the photoelectrochemical responses of GCN and P-TCN under visible light irradiation. \n\nTo further illustrate the enhanced electron transfer in the P-TCN, photoelectrochemical measurements were conducted in a typical three-electrode cell (Figure 4 c). Linear sweep voltammetry (LSV) measurements were performed under visible light irradiation. The observed cathodic current in the range of $-0.2$ to $-0.4\\:\\mathrm{V}$ versus SCE ( $-0.6$ to $-0.9{\\mathrm{V}}$ vs. RHE) can be ascribed to the hydrogen evolution reaction (HER). Compared to GCN, P-TCN shows a much higher catalytic activity. The enhanced catalytic capability was corroborated by the photocurrent measurements. Figure 4d shows a comparison of the photocurrent-time curves for the above samples with typical on–off cycles of visible light irradiation. An enhanced photocurrent response for P-TCN is generated, which is nearly three times higher than that of the pristine GCN, strongly illustrating that the mobility of the photoexcited charge carriers is promoted. Additionally, the Nyquist plots for P-TCN catalysts exhibit low charge transfer resistance as compared to those of GCN (Supporting Information, Figure S26). \n\nIn conclusion, through phosphorous acid-assisted hydrothermal method, partially hydrolysis of melamine into cyanuric acid leads to the formation of melamine–cyanuric acid supramolecular precursor. Then the hexagonal P-TCNs with the micro-nanostructure are obtained from supramolecular precursor after thermal treatment. The hexagonal tube with the layered stack structure significantly increases its specific surface area; as a result, the density of active sites is augmented. Moreover, the introduction of phosphorus decreases the band gap energy, increases the electric conductivity, and suppresses the recombination of photogenerated electron–hole pairs, thus improving the visible-light photocatalytic efficiency for the hydrogen evolution in the presence of sacrificial agents. The hexagonal carbon nitride tube structure is also good carrier material for nanocomposite with specified dimension and chemical functionality. \n\n# Acknowledgements \n\nThis work was supported by the NSFC of China (21031001, 21371053, 51372071, and 21571054), the Program for Innovative Research Team in University (IRT-1237). \n\nKeywords: carbon nitride $\\cdot\\cdot$ micro-nanostructure $\\cdot\\cdot$ nanotubes · phosphorus doping $\\mathbf{\\nabla}\\cdot\\mathbf{\\varepsilon}$ photocatalytic hydrogen evolution \n\nHow to cite: Angew. Chem. Int. Ed. 2016, 55, 1830–1834 Angew. Chem. 2016, 128, 1862–1866 \n\nZheng, J. Liu, J. Liang, M. Jaroniec, S. Z. Qiao, Energy Environ. Sci. 2012, 5, 6717 – 6774. \n[4] S. Yang, Y. Gong, J. Zhang, L. Zhan, L. Ma, Z. Fang, R. Vajtai, X. Wang, P. M. Ajayan, Adv. Mater. 2013, 25, 2452 – 2456. \n[5] a) X. Chen, S. Shen, L. Guo, S. Mao, Chem. Rev. 2010, 110, 6503 – 6570; b) A. Kudo, Y. Miseki, Chem. Soc. Rev. 2009, 38, 253 – 278. \n[6] a) J. S. Zhang, M. W. Zhang, C. Yang, X. C. Wang, Adv. Mater. 2014, 26, 4121 – 4126; b) E. Z. Lee, Y.-S. Jun, W. H. Hong, A. Thomas, M. M. Jin, Angew. Chem. Int. Ed. 2010, 49, 9706 – 9710; Angew. Chem. 2010, 122, 9900 – 9904; c) Q. Li, J. P. Yang, D. Feng, Z. X. Wu, Q. L. Wu, S. S. Park, C.-S. Ha, D. Y. Zhao, Nano Res. 2010, 3, 632 – 642. \n[7] a) Y. Y. Kang, Y. Q. Yang, L.-C. Yin, X. D. Kang, G. Liu, H.-M. Cheng, Adv. Mater. 2015, 27, 4572 – 4577; b) Y. P. Zhu, T. Z. Ren, Z. Y. Yuan, ACS Appl. Mater. Interfaces 2015, 7, 16850 – 16856; c) Q. Han, B. Wang, Y. Zhao, H. H. Cheng, L. T. Qu, Angew. Chem. Int. Ed. 2015, 54, 11433 – 11437; Angew. Chem. 2015, 127, 11595 – 11599. \n[8] a) G. Liu, P. Niu, C. H. Sun, S. C. Smith, Z. G. Chen, G. Q. Lu, H. M. Cheng, J. Am. Chem. Soc. 2010, 132, 11642 – 11648; b) T. Y. Ma, J. Ran, S. Dai, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2015, 54, 4646 – 4650; Angew. Chem. 2015, 127, 4729 – 4733. \n[9] a) G. M. Whitesides, J. P. Mathias, C. T. Seto, Science 1991, 254, 1312 – 1314; b) N. A. Wasio, R. C. Quardokus, R. P. Forrest, C. S. Lent, S. A. Corcelli, J. A. Christie, K. W. Henderson, S. A. Kandel, Nature 2014, 507, 86 – 89; c) A. Ranganathan, V. R. Pedireddi, C. N. R. Rao, J. Am. Chem. Soc. 1999, 121, 1752 – 1753; d) M. Shalom, M. Guttentag, C. Fettkenhauer, S. Inal, D. Neher, A. Llobet, M. Antonietti, Chem. Mater. 2014, 26, 5812 – 5818; e) T. Jordan, N. Fechler, J. S. Xu, T. J. K. Brenner, M. Antonietti, M. Shalom, ChemCatChem 2015, 7, 2826 – 2830; f) Y. Ishida, L. Chabanne, M. Antonietti, M. Shalom, Langmuir 2014, 30, 447 – 451. \n[10] M. Shalom, S. Inal, C. Fettkenhauer, D. Neher, M. Antonietti, J. Am. Chem. Soc. 2013, 135, 7118 – 7121. \n[11] Y.-S. Jun, J. Park, S. U. Lee, A. Thomas, W. H. Hong, G. D. Stucky, Angew. Chem. Int. Ed. 2013, 52, 11083 – 11087; Angew. Chem. 2013, 125, 11289 – 11293. \n[12] K. Jutzi, A. M. Cook, R. Huitter, Biochem. J. 1982, 208, 679 – 684. \n[13] J. H. Zhang, G. G. Zhang, X. F. Chen, S. Lin, L. Mohlmann, G. Dolega, G. Lipner, M. Antonietti, S. Blechert, X. C. Wang, Angew. Chem. Int. Ed. 2012, 51, 3183 – 3187; Angew. Chem. 2012, 124, 3237 – 3241. \n[14] J. Zhang, M. Zhang, G. Zhang, X. Wang, ACS Catal. 2012, 2, 940 – 944. \n[15] J. Zhang, F. Guo, X. Wang, Adv. Funct. Mater. 2013, 23, 3008 – 3012. \n[16] Y. J. Zhang, T. Mori, J. H. Ye, M. Antonietti, J. Am. Chem. Soc. 2010, 132, 6294 – 6295. \n[17] a) X. Wang, K. Maeda, X. Chen, K. Takanabe, K. Domen, Y. Hou, X. Fu, M. Antonietti, J. Am. Chem. Soc. 2009, 131, 1680 – 1684; b) K. Kailasam, J. D. Epping, A. Thomas, S. Losse, H. Junge, Energy Environ. Sci. 2011, 4, 4668 – 4671. \n[18] X. G. Ma, Y. H. Lv, J. Xu, Y. F. Liu, R. Q. Zhang, Y. F. Zhu, J. Phys. Chem. C 2012, 116, 23485 – 23493. \n[19] L. Q. Jing, Y. C. Qu, H. J. Su, C. H. Yao, H. G. Fu, J. Phys. Chem. C 2011, 115, 12375. \n[20] a) J. Zhang, X. Chen, K. Takanabe, K. Maeda, K. Domen, J. Epping, X. Fu, M. Antonietti, X. Wang, Angew. Chem. Int. Ed. 2010, 49, 441 – 445; Angew. Chem. 2010, 122, 451 – 454. " + }, + { + "id": "10.1038_NPHYS3867", + "DOI": "10.1038/NPHYS3867", + "DOI Link": "http://dx.doi.org/10.1038/NPHYS3867", + "Relative Dir Path": "mds/10.1038_NPHYS3867", + "Article Title": "Acoustic topological insulator and robust one-way sound transport", + "Authors": "He, C; Ni, X; Ge, H; Sun, XC; Chen, YB; Lu, MH; Liu, XP; Chen, YF", + "Source Title": "NATURE PHYSICS", + "Abstract": "Topological design of materials enables topological symmetries and facilitates unique backscattering-immune wave transport(1-26). In airborne acoustics, however, the intrinsic longitudinal nature of sound polarization makes the use of the conventional spin-orbital interaction mechanism impossible for achieving band inversion. The topological gauge flux is then typically introduced with a moving background in theoretical models(19-22). Its practical implementation is a serious challenge, though, due to inherent dynamic instabilities and noise. Here we realize the inversion of acoustic energy bands at a double Dirac cone(15,27,28) and provide an experimental demonstration of an acoustic topological insulator. By manipulating the hopping interaction of neighbouring 'atoms' in this new topological material, we successfully demonstrate the acoustic quantum spin Hall effect, characterized by robust pseudospin-dependent one-way edge sound transport. Our results are promising for the exploration of new routes for experimentally studying topological phenomena and related applications, for example, sound-noise reduction.", + "Times Cited, WoS Core": 989, + "Times Cited, All Databases": 1056, + "Publication Year": 2016, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000389133800014", + "Markdown": "# Acoustic topological insulator and robust one-way sound transport \n\nCheng He1,2, $\\mathsf{X u N i}^{1}$ , Hao $\\mathsf{G e}^{1}$ , Xiao-Chen Sun1, Yan-Bin Chen1, Ming-Hui $\\mathbf{L}\\mathbf{u}^{1,2\\star}$ , Xiao-Ping Liu1,2\\* and Yan-Feng Chen1,2\\* \n\nTopological design of materials enables topological symmetries and facilitates unique backscattering-immune wave transport1–26. In airborne acoustics, however, the intrinsic longitudinal nature of sound polarization makes the use of the conventional spin–orbital interaction mechanism impossible for achieving band inversion. The topological gauge flux is then typically introduced with a moving background in theoretical models19–22. Its practical implementation is a serious challenge, though, due to inherent dynamic instabilities and noise. Here we realize the inversion of acoustic energy bands at a double Dirac cone15,27,28 and provide an experimental demonstration of an acoustic topological insulator. By manipulating the hopping interaction of neighbouring ’atoms’ in this new topological material, we successfully demonstrate the acoustic quantum spin Hall efect, characterized by robust pseudospin-dependent one-way edge sound transport. Our results are promising for the exploration of new routes for experimentally studying topological phenomena and related applications, for example, sound-noise reduction. \n\nThe topological insulator, characterized by the quantum spin Hall effect (QSHE), originates from condensed matter. A prerequisite condition for such an effect, Kramers doublet, can be fulfilled thanks to the intrinsic spin-1/2 fermionic character of electrons. Thus, the key physics behind realizing a bosonic (for example, photonic or phononic) analogue of the electronic topological insulator is to increase the degrees of freedom so as to create a double Dirac cone, where Kramers doublet exists in the form of two two-fold states (pseudospin-up and pseudospin-down). For example, a photonic topological insulator often takes advantage of two polarizations of a spin-1 photon, which are utilized to construct the required Kramers doublet, for example, degenerate TM+TE/TM-TE states11 (TM and TE represent transverse magnetic and electric polarizations, respectively), TM/TE states29, or left/right circularly polarized states30. An acoustic system especially for longitudinal airborne sound, however, possesses intrinsic spin-0, giving rise to no such polarization-based Kramers doublet and thus hindering acoustic QSHE. To overcome this issue, Kramers doublet in the form of degenerate artificial acoustic spin-1/2 states may be constructed, for example, using clockwise and anticlockwise circulating acoustic waves23. Spin–orbital interaction may then be introduced in a time-dependent fashion24. Most recently, ref. 15 proposed a novel concept for realizing a photonic topological insulator by utilizing two pairs of degenerate Bloch modes of TM polarization (instead of two polarizations) as a result of the zone folding mechanism in a composite lattice structure15. Here, we show, other than the zone folding mechanism15, a double cone can also be accidentally formed by deliberately manipulating the filling factor of a honeycomb lattice. This straightforward yet elegant approach takes advantage of acoustic systems’ large index and impedance contrast, which unfortunately is usually absent in photonic systems (see Supplementary Information). On the basis of our novel concept, we experimentally demonstrate a completely passive or static two-dimensional acoustic topological insulator, utilizing phononic ‘graphene’ consisting of stainless-steel rods in air. In our phononic ‘graphene’, an artificial spin-1/2 is emulated through mode hybridization near the dispersion degeneracy of different energy bands. Specifically, two degenerate modes $M_{1}$ and $M_{2}$ at a given frequency can be hybridized to construct two new superimposed degenerate spin-1/2 states: spin $\\pm\\equiv M_{1}+i M_{2}/M_{1}-i M_{2}$ . Since in this scenario each spin-1/2 state corresponds to two degenerate modes, the two-fold degeneracy of the Dirac cone in a spin- $1/2$ electronic system, where the QSHE occurs, is replaced with a four-fold degeneracy or a double Dirac cone. By engineering the nearest neighbour coupling in a phononic ‘graphene’ with $C_{\\mathrm{6v}}$ symmetry, an accidental double Dirac cone can be realized27,28 (see Supplementary Information), because the $C_{\\mathrm{6v}}$ symmetry, according to group theory, possesses two two-dimensional irreducible representations, which can be leveraged to construct a double Dirac cone by forming a four-fold accidental degeneracy31. Note that similar double Dirac cones have also been reported previously in other classic wave systems, such as electromagnetic waves15,31,32 and elastic waves18. Different from all of these works27,28, we show that, in addition to the double Dirac cone, the phononic ‘graphene’ studied here undergoes a symmetry inversion in reciprocal space, causing energy band inversion, which ultimately leads to a distinct topological phase transition15. \n\nThe topological phase transition can be leveraged to form topologically protected gapless edge states inside the bulk frequency bandgap at the interface between two phononic crystals with topologically dissimilar phases, which can then be exploited to construct a topologically protected waveguide as shown in Fig. 1a. Due to topological protection, the acoustic backscattering can be largely suppressed and thus robust against various kinds of defect (including cavities, disorders and even sharp bends). To identify these topological phases, the evolution of energy band structures and their acoustic states with decreasing filling ratio are illustrated in Fig. 1b. At a high filling ratio, for example, $r/a=$ 0.45 (left panel of Fig. 1b), separated by a bandgap, two two-fold degeneracy, one for the lower bands ${p_{x}/p_{y}}$ and the other for the upper bands $d_{x^{2}-y^{2}}/d_{x y}$ , appears at the Brillouin zone centre. Spin1/2 for the bulk states can thus be achieved through hybridizing these $p/d$ states as $p_{\\pm}=(p_{x}\\pm i p_{y})/\\sqrt{2}$ and $d_{\\pm}=(d_{x^{2}-y^{2}}\\pm i d_{x y})/\\sqrt{2}$ (ref. 15). Similar to $\\boldsymbol{p}$ and $d$ orbitals of electrons, here ${p}_{x}$ obeys symmetry ${\\sigma_{x}}/{\\sigma_{y}}=-1/+1;\\ p_{y}$ obeys $\\sigma_{x}/\\sigma_{y}=+1/-1$ ; $d_{x^{2}-y^{2}}$ obeys $\\sigma_{x}/\\sigma_{y}=+1/+1$ ; and $d_{x y}$ obeys $\\sigma_{x}/\\sigma_{y}=-1/-1$ , where $\\sigma_{x,y}=+1,-1$ means the even or odd symmetry along the $x$ or $y$ axis of the unit cell, respectively (see Supplementary Information). With a deceased filling ratio of $r/a{=}0.3928$ (middle panel of Fig. 1b), the energy bandgap is eliminated, resulting in an accidental double Dirac cone with the desired four-fold degeneracy at the Dirac point. Further decreasing the filling ratio, for example, $r/a=0.3$ , destroys the four-fold degeneracy, and reopens the bandgap (right panel of Fig. 1b). In this process, the symmetry in reciprocal space is inverted, causing the energy band inversion, which is confirmed by examining the Bloch modes before the bandgap disappears and after it reappears (see Supplementary Information). The acoustic band inversion effect here is related to the fact that the velocity of a longitudinal acoustic wave in an air background is much slower than that in stainless-steel rods. The created symmetry inversion in phononic ‘graphene’ further leads to a topological transition from an ordinary phononic crystal (OPC) to a topological phononic crystal (TPC) (see Supplementary Figs 1 and 2 for details). Note that the acoustic topological insulator we proposed here is based on an accidental double Dirac cone resulting from $C_{6\\mathrm{v}}$ symmetry. In principle, other configurations, as long as they comply with the required $C_{6\\mathrm{v}}$ symmetry, can have the same phenomenon, for example, the ring-shaped components in triangle lattices28,32. \n\n![](images/6d006bc4d22b17d551f30063cf6b979691adfebfd42ad5fe196836531066b1c9.jpg) \nFigure 1 | Schematic of the acoustic insulator and band inversion process. a, A schematic of our proposed acoustic topological insulator constructed with two types of phononic ‘graphene’ with the same lattice constant $a$ but diferent ‘atom’ (stainless-steel rod) radii r. This novel design enables one-way robust spin-dependent transportation against defects such as a cavity, a lattice disorder and a bend as indicated in the figure. The inset shows a zoom-in view of our phononic ‘graphene’. b, Illustration of a band inversion process with a decreasing filling ratio. At a large filling ratio, for example, $r/a=0.45$ , the phononic crystal has two two-fold degenerate acoustic states denoted by $p_{x}/p_{y}$ and $d_{x^{2}-y^{2}}/d_{x y},$ which are separated by a bulk bandgap; at a decreased filling ratio, for example, $r/a{=}0.3928$ in our case, the bulk bandgap disappears and an accidental double Dirac cone with a four-fold degeneracy is formed; at an even smaller filling ratio, for example, $r/a=0.3$ , the bulk bandgap reappears along with two inverted two-fold degenerate acoustic states, corresponding to $d_{x^{2}-y^{2}}/d_{x y}$ and $p_{x}/p_{y}$ . In this process, a topological phase transition occurs near the double Dirac cone. Note sketches of energy bands are shown as black curves. c, Calculated projected energy bands of a supercell consisting of a topological phononic crystal $(r=0.30m$ , $a=1(11,$ ) stacked with an ordinary phononic crystal $r=0.45{\\mathrm{cm}}$ , $a=1(\\mathsf{m})$ ). The material parameters used for calculation are the density and longitudinal sound speed of $7,800\\ k g\\mathsf{m}^{-3}$ and $6,010\\mathsf{m}\\mathsf{s}^{-1}$ for stainless steel and $1.25\\mathsf{k g}\\mathsf{m}^{-3}$ and $343\\mathsf{m}\\mathsf{s}^{-1}$ . The red and blue lines represent an acoustic spin $+$ and spin− edge state that is hybridized with a symmetric edge mode (S) and anti-symmetric edge mode (A) based on $S+\\dot{I}A$ and ${\\mathsf{S}}{\\mathrm{-iA}},$ respectively. The right panel shows a representative example of the pressure field distribution at $k_{\\parallel}=0.05$ for the S and A modes. The shadow regions represent the bulk energy bands. \n\n![](images/509d8aa7e30986fd864b1a5ecb3449089c8de0eb288f7d3f006f2fbe7acfc23a.jpg) \nFigure 2 | Acoustic one-way spin-dependent transport. a, A photo of the cross-waveguide splitter sample used in our experiment. Topological phononic crystals reside in the upper and lower sections, while ordinary phononic crystals reside in the left and right sections. Four input/output ports labelled as 1, 2, 3 and 4 are located at the interface between these sections. In this test, only clockwise (anticlockwise) edge circulating propagation along the interfaces is allowed for acoustic spin $+$ (spin−) as indicated by the red (blue) circular arrow. b,c, Simulated acoustic pressure field distribution at a frequency of $19.8\\mathsf{k H z}$ (within the bulk bandgap) for the acoustic cross state with an input from port 1 and port 2, respectively. d,e, Experimental transmission spectra for acoustic spin− incidence from port 1 and for acoustic spin $^{+}$ incidence from port 2, respectively. Pij represents the acoustic transmission spectrum from port i to port j $(i=1,2$ and $j=1,2,3,4,$ ) including the in and out coupling losses. The shadow regions indicate the bulk energy bands. \n\nThe projected band structure of a TPC–OPC supercell is shown in Fig. 1c. Inside the overlapped bulk energy bandgap of the two phononic crystals, it is evident that there exists a pair of edge states (red and blue lines). These edge states are localized at the interface between the TPC and the OPC and support edge propagation of sound. Acoustic spin $\\pm$ of the edge states are obtained via hybridizing a symmetric mode (S) and an anti-symmetric mode (A) \n\nshown in the right panel of Fig. 1c as $\\mathrm{{S+iA/S-iA},}$ respectively. They can also be correlated to the spins of the bulk states in the TPC and the OPC located on either side of the interface as: $\\mathrm{S}+\\mathrm{i}\\mathrm{A}/\\mathrm{S}-\\mathrm{i}\\mathrm{A}\\equiv p_{+}+d_{+}/p_{-}+d_{-}$ (see Supplementary Information). Hence, the symmetric component S can be represented as $\\mathrm{S}=(p_{x}+d_{x^{2}-y^{2}})/\\sqrt{2}$ , while the anti-symmetric component A as $\\mathrm{A}{=}(p_{y}+d_{x y})/\\sqrt{2}$ . The two acoustic spin edge states have the same sound velocity amplitude but in opposite directions, implying the existence of spin–orbital coupling and thus one-way spin-dependent propagation. \n\nGenerally, it is very difficult to selectively excite a particular pseudospin in experiment even with multiple excitation sources. Here, we utilize a cross-waveguide splitter33, which allows us to study pseudospin-dependent transport with a very high fidelity even in the case of unknown pseudospin excitation state. As shown in Fig. 2a, the splitter is divided into four sections with the TPC residing in the upper and lower sections and the OPC residing in the left and right sections. There are four input/output ports in this splitter (labelled as 1, 2, 3 and 4). For an acoustic bar state, that is, the sound transmitting straight through from port 1 to port 3 (or from port 2 to port 4), with respect to its transmission direction, the TPC is located on the left side while the OPC is located on the right side before the acoustic wave propagates across the central region of the splitter. However, such kind of structural spatial symmetry is inverted immediately after the acoustic wave propagates across the centre (OPC on the left side and TPC on the right side). Since either pseudospin state is preserved across the centre region, the edge state is not allowed to propagate in a straight through fashion, implying that the acoustic bar state in this splitter is completely prohibited for all pseudospin edge states. Similar analysis can show that for an acoustic cross state, for example, from port 1 to port 2 or to port 4, the structural spatial symmetry is always preserved and the propagation of edge states is always allowed. In addition, the acoustic cross state is spin-dependent, which is determined by the spatial symmetry. For instance, in Fig. 2a, the acoustic cross state with input sound at port 1 or at port 3 supports only the spin $^+$ edge state while the cross state for the other two ports supports the spin− edge state. This unique effect can be explained by checking the slope of the dispersion band, that is, the group velocity, for each individual acoustic spin edge state in Fig. 1c. Clearly, because of their opposite slope across the whole Brillouin zone, the acoustic spin $+$ edge state and spin− edge state can travel only in a one-way fashion but with opposite directions, clockwise (red circular arrows) versus anticlockwise (blue circular arrows) as illustrated in Fig. 2a. Such a transport behaviour characterizes an acoustic counterpart of the QSHE. \n\n![](images/f4eb3a9b0bf2caff4a1fba930edbd3b0ba81a0a827399664c8cf43e73bfcc971.jpg) \nFigure 3 | Robust one-way sound transport. a, A photo of our experimental set-up. The green and yellow dashed lines indicate the location of an acoustic topological waveguide and an ordinary bandgap-guiding phononic crystal waveguide, respectively. b, Simulated acoustic pressure field distribution for acoustic spin− incident at $20.1\\mathsf{k H z}$ (within the bulk bandgap) in three diferent configurations, corresponding to three diferent defects, that is, a cavity, a lattice disorder and a bend. Blue, red and black arrows denote the propagation direction of acoustic spin−, spin $+$ and ordinary sound, respectively. c,d, Experimental transmission spectra for the topological waveguide and ordinary bandgap-guiding phononic crystal waveguide, respectively. The black curve corresponds to the case without any defects, while the red, blue and green curves indicate the transmission spectrum for the case with a cavity, a lattice disorder and a bend, respectively. The shadow regions correspond to the bulk energy bands. \n\nFigure $^{2\\mathrm{b},\\mathrm{c}}$ shows the simulated pressure field distribution with inputs at port 1 and at port 2 respectively for an acoustic frequency in the bulk bandgap, which resemble clearly two cross states with almost no transmission into the through port in both cases. Such an observation is consistent with our theoretical analysis above. These configurations are then experimentally studied with the resulting transmission spectra shown in Fig. 2d,e. It is found that the acoustic bar state is heavily suppressed as evidently observed from its low transmission, $<-10\\mathrm{dB}$ for the through port. The spin-dependent cross state for the two acoustic spins, however, remains with very high transmission for the two cross output ports. These experimental observations for the cross-waveguide splitter model confirmed clearly the unique one-way spin-dependent transportation in our acoustic topological insulator. \n\nThe demonstrated topological edge states are also symmetry protected with topological immunity against all non-spin-mixing defects. Different defects are intentionally introduced into our topological waveguide near the TPC/OPC interface to study the propagation robustness of our acoustic topological edge states. In comparison, a bandgap-guiding phononic crystal waveguide is also constructed with two OPCs and similar defects are introduced for a control experiment. A picture of the test sample is shown in Fig. 3a, where the location of the topological waveguide and the phononic crystal waveguide can be seen. Three different defects, including a cavity, a lattice disorder, and a bend, are implemented in the two waveguides. Note that all these three types of defect are none-spin-mixing defects by their nature, meaning that no effective ‘magnetic’ impurities are presented intentionally to break the topological characteristics15,16,18,30,34. Simulation results show that with a spin− acoustic wave incidence from the left the edge state in the topological waveguide can detour around all these defects and maintain a very high transmission (three upper panels of Fig. 3b). In contrast, the results for the bandgap-guiding phononic crystal waveguide are drastically different. The cavity in this case causes acoustic resonances, while the disorder and bend severely inhibit the acoustic forward propagation, leading to a decreased transmission or even a total reflection (three lower panels of Fig. 3b). The experimentally measured transmission spectra for these two waveguides are shown in Fig. 3d. The transmission through the topological waveguide is nearly unaffected by any of these defects especially for the spectral region near the centre of the bulk bandgap. However, their presence causes significant disturbance on the sound transportation in the bandgap-guiding phononic crystal waveguide, which could include largely reduced transmission especially on the high-frequency side of the bandgap and multiple resonance dips corresponding to the cavity resonances. Hence, the topological waveguide clearly distinguishes itself from the bandgap-guiding phononic crystal waveguide with the unparalleled advantage of robust sound transportation. \n\nIn our acoustic system, the topological property of the TPC is characterized by a non-zero spin Chern number of bulk bands (see Supplementary Information), implying that the edge states are preserved under continuous deformations. Note that a tiny gap exists between two dispersions of the edge states at the $k_{\\parallel}=0$ point (see Supplementary Information), which is originated from an imperfect cladding layer rather than the TPC itself. For instance, in our case we use the topologically trivial phononic crystal as a cladding layer but its eigen states are slightly different from those of the TPC, which gives rise to a theoretically calculated absolute bandgap of $0.095\\mathrm{kHz}$ or a relative bandgap less than $0.5\\%$ . Such a bandgap can hardly be probed in our swept frequency tests (Figs 2d,e and $^{3c,\\mathrm{d}}.$ ) even with a frequency increment of $0.01\\mathrm{kHz}$ because of the usual finite size issue for fabricated samples and the propagation loss for airborne sound. If desired, this relative bandgap can be further reduced to less than $0.02\\%$ in theory by adjusting the boundary condition35, that is, changing the filling factor of a row of cylinders to be $r/a=0.1$ (see Supplementary Information). In principle, this tiny bandgap can even be closed with a deliberately designed cladding layer, if it can support the same eigen states as those of the TPC. In reality, any fabrication imperfection could lead to a tiny gap. In this regard, the backscattering is not completely forbidden in experiment. However, the real issue is whether the experimental measurement can detect such a tiny bandgap. What we have found in our work is that the transmission through our topological waveguide is nearly unaffected (Figs 2d,e and 3c,d), suggesting that the bandgap is hardly noticeable and the backscattering is largely suppressed. \n\nThe acoustic topological states obtained here pave a new way for studying topological properties in classic wave systems without any noises resulting from dynamical modulation. This unique topological material can in principle be leveraged to explore quantum behaviour of classical waves at a high fidelity. In addition, our design principle and measurement technique demonstrated here can be easily extended to cover a large acoustic spectrum from audible sound to ultrasonic frequencies, and they can even be extended to other classic waves such as Lamb waves. Moreover, our demonstrated topological phenomenon of sound may generate considerable impact in applications in the foreseeable future. For instance, when combined with a low propagation loss substrate/background environment, the backscattering-immune sound transportation may give rise to an ultrahigh-Q acoustic resonance, which, to date, remains a challenge in the acoustic industry. \n\n# Methods \n\nMethods, including statements of data availability and any associated accession codes and references, are available in the online version of this paper. \n\n# References \n\n1. Klitzing, K. V., Dorda, G. & Pepper, M. New method for high-accuracy determination of the fine-structure constant based on quantized Hall resistance. Phys. Rev. Lett. 45, 494–497 (1980). \n2. Thouless, D. J., Kohmoto, M., Nightingale, M. P. & den Nijs, M. Quantized Hall conductance in a two-dimensional periodic potential. Phys. Rev. Lett. 49, 405–408 (1982). \n3. Hasan, M. Z. & Kane, C. L. Colloquium: topological insulators. Rev. Mod. Phys. 82, 3045–3067 (2010). \n4. Qi, X.-L. & Zhang, S.-C. Topological insulators and superconductors. Rev. Mod. Phys. 83, 1057–1110 (2011). \n5. Haldane, F. D. M. & Raghu, S. Possible realization of directional optical waveguides in photonic crystals with broken time-reversal symmetry. Phys. Rev. Lett. 100, 013904 (2008). \n6. Wang, Z., Chong, Y., Joannopoulos, J. D. & Soljacic, M. Observation of unidirectional backscattering-immune topological electromagnetic states. Nature 461, 772–775 (2009). \n7. Lu, L., Joannopoulos, J. D. & Soljacic, M. Topological photonics. Nat. Photon. 8, 821–829 (2014). \n8. Hafezi, M., Demler, E. A., Lukin, M. D. & Taylor, J. M. Robust optical delay lines with topological protection. Nat. Phys. 7, 907–912 (2011). \n9. Hafezi, M., Mittal, S., Fan, J., Migdall, A. & Taylor, J. M. Imaging topological edge states in silicon photonics. Nat. Photon. 7, 1001–1005 (2013). \n10. Rechtsman, M. C. et al. Photonic floquet topological insulators. Nature 496, 196–200 (2013). \n11. Khanikaev, A. B. et al. Photonic topological insulators. Nat. Mater. 12, 233–239 (2013). \n12. Chen, W.-J. et al. Experimental realization of photonic topological insulator in a uniaxial metacrystal waveguide. Nat. Commun. 5, 5782 (2014). \n13. Lu, L. et al. Experimental observation of Weyl points. Science 349, 622–624 (2015). \n14. Bliokh, K. Y., Smirnova, D. & Nori, F. Quantum spin Hall effect of light. Science 348, 1448–1451 (2015). \n15. Wu, L.-H. & Hu, X. Scheme for achieving a topological photonic crystal by using dielectric material. Phys. Rev. Lett. 114, 223901 (2015). \n16. Süsstrunk, R. & Huber, S. D. Observation of phononic helical edge states in a mechanical topological insulator. Science 349, 47–50 (2015). \n17. Wang, P., Lu, L. & Bertoldi, K. Topological phononic crystals with one-way elastic edge waves. Phys. Rev. Lett. 115, 104302 (2015). \n18. Mousavi, S. H., Khanikaev, A. B. & Wang, Z. Topologically protected elastic waves in phononic metamaterials. Nat. Commun. 6, 8682 (2015). \n19. Yang, Z. et al. Topological acoustics. Phys. Rev. Lett. 114, 114301 (2015). \n20. Ni, X. et al. Topologically protected one-way edge mode in networks of acoustic resonators with circulating air flow. New J. Phys. 17, 053016 (2015). \n21. Khanikaev, A. B., Fleury, R., Mousavi, S. H. & Alu, A. Topologically robust sound propagation in an angular-momentum-biased graphene-like resonator lattice. Nat. Commun. 6, 8260 (2015). \n22. Fleury, R., Sounas, D. L., Sieck, C. F., Haberman, M. R. & Alù, A. Sound isolation and giant linear nonreciprocity in a compact acoustic circulator. Science 343, 516–519 (2014). \n23. Zhu, X.-F. et al. Topologically protected acoustic helical edge states and interface states in strongly coupled metamaterial ring lattices. Preprint at http://arXiv.org/abs/1508.06243 (2015). \n24. Fleury, R., Khanikaev, A. & Alu, A. Floquet topological insulators for sound. Nat. Commun. 7, 11744 (2016). \n25. Xiao, M. et al. Geometric phase and band inversion in periodic acoustic systems. Nat. Phys. 11, 240–244 (2015). \n26. Xiao, M., Chen, W.-J., He, W.-Y. & Chan, C. T. Synthetic gauge flux and Weyl points in acoustic systems. Nat. Phys. 11, 920–924 (2015). \n27. Chen, Z.-G. et al. Accidental degeneracy of double Dirac cones in a phononic crystal. Sci. Rep. 4, 4613 (2014). \n28. Li, Y., Wu, Y. & Mei, J. Double Dirac cones in phononic crystals. Appl. Phys. Lett. 105, 014107 (2014). \n29. Ma, T., Khanikaev, A. B., Mousavi, S. H. & Shvets, G. Guiding electromagnetic waves around sharp co : topologically protected photonic transport in metawaveguides. Phys. Rev. Lett. 114, 127401 (2015). \n30. He, C. et al. Photonic topological insulator with broken time-reversal symmetry. Proc. Natl Acad. Sci. USA 113, 4924–4928 (2016). \n31. Sakoda, K. Double Dirac cones in triangular-lattice metamaterials. Opt. Express 20, 9925–9939 (2012). \n32. Li, Y. & Mei, J. Double Dirac cones in two-dimensional dielectric photonic crystals. Opt. Express 23, 12089–12099 (2015). \n33. He, C. et al. Tunable one-way cross-waveguide splitter based on gyromagnetic photonic crystal. Appl. Phys. Lett. 96, 111111 (2010). \n34. Fu, L. Topological crystalline insulators. Phys. Rev. Lett. 106, 106802 (2011). \n35. He, C., Lu, M.-H., Wan, W.-W., Li, X.-F. & Chen, Y.-F. Influence of boundary conditions on the one-way edge modes in two-dimensional magneto-optical photonic crystals. Solid State Commun. 150, 1976–1979 (2010). \n\n# Acknowledgements \n\nThe work was jointly supported by the National Basic Research Program of China (Grant No. 2012CB921503, 2013CB632904 and 2013CB632702) and the National Nature Science Foundation of China (Grant No. 11134006, No. 11474158, and No. 11404164). M.-H.L. also acknowledges the support of the Natural Science Foundation of Jiangsu Province (BK20140019) and the support from the Academic Program Development of Jiangsu Higher Education (PAPD). \n\n# Author contributions \n\nC.H., M.-H.L. and X.-P.L. conceived the idea. C.H. performed the numerical simulation and fabricated the samples. C.H., X.N. and H.G. carried out the experimental measurements. All the authors contributed to discussion of the results and manuscript \n\npreparation. M.-H.L., X.-P.L. and Y.-F.C. supervised all aspects of this work and managed this project. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to M.-H.L., X.-P.L. or Y.-F.C. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. \n\n# Methods \n\nExperiments. The phononic ‘graphene’ consists of commercial 304 stainless-steel rods with radii $r=0.3\\mathrm{cm}$ and $r=0.45\\mathrm{cm}$ , arranged in air in graphene-like lattices. The radii tolerance of these steel rods is $\\pm0.01\\mathrm{cm}$ . The height of our phononic ‘graphene’ is chosen to be $20\\mathrm{cm};$ , roughly 10 times larger than the acoustic wavelength in air at $20\\mathrm{kHz}$ to make sure that two-dimensional approximation is applicable. Experiments are conducted with a large-area acoustic transducer. The transducer excites a roughly planar acoustic field, which then will be scattered at the input facet into the appropriate spin edge state according to the symmetry of the interface. A B&K-4939-2670 microphone acts as a detector, which is placed $2\\mathrm{cm}$ away from the output port with its response acquired and analysed in B&K-3560-C. Acoustic input frequencies are swept from $18\\mathrm{kHz}$ to $22\\mathrm{kHz}$ with an increment of $0.01\\mathrm{kHz}$ . The experimentally measured transmission spectra plotted in Figs 2d,e and 3c,d are normalized to the acoustic wave transmission through the same distance in air. In theory, the transmission should be $100\\%$ (0 dB) for the topological edge states with frequencies from $19.00\\mathrm{kHz}$ to $20.53\\mathrm{kHz}$ . The deviation recorded in experiments (between 0 dB and $-5\\mathrm{dB}$ ) is primarily due to the inefficient coupling into and out of the topological waveguides. \n\nSimulations. Numerical investigations to calculate Figs 1c, $^{2\\mathrm{b},\\mathrm{c}}$ and 3b in this letter are conducted using the acoustic mode of commercial FEM software (COMSOL MULTIPHYSICS). \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding author on request. " + }, + { + "id": "10.1038_ncomms11585", + "DOI": "10.1038/ncomms11585", + "DOI Link": "http://dx.doi.org/10.1038/ncomms11585", + "Relative Dir Path": "mds/10.1038_ncomms11585", + "Article Title": "High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor", + "Authors": "Holliday, S; Ashraf, RS; Wadsworth, A; Baran, D; Yousaf, SA; Nielsen, CB; Tan, CH; Dimitrov, SD; Shang, ZR; Gasparini, N; Alamoudi, M; Laquai, F; Brabec, CJ; Salleo, A; Durrant, JR; McCulloch, I", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Solution-processed organic photovoltaics (OPV) offer the attractive prospect of low-cost, light-weight and environmentally benign solar energy production. The highest efficiency OPV at present use low-bandgap donor polymers, many of which suffer from problems with stability and synthetic scalability. They also rely on fullerene-based acceptors, which themselves have issues with cost, stability and limited spectral absorption. Here we present a new non-fullerene acceptor that has been specifically designed to give improved performance alongside the wide bandgap donor poly(3-hexylthiophene), a polymer with significantly better prospects for commercial OPV due to its relative scalability and stability. Thanks to the well-matched optoelectronic and morphological properties of these materials, efficiencies of 6.4% are achieved which is the highest reported for fullerene-free P3HT devices. In addition, dramatically improved air stability is demonstrated relative to other high-efficiency OPV, showing the excellent potential of this new material combination for future technological applications.", + "Times Cited, WoS Core": 1048, + "Times Cited, All Databases": 1120, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000377909600001", + "Markdown": "# High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor \n\nSarah Holliday1, Raja Shahid Ashraf1, Andrew Wadsworth1, Derya Baran1, Syeda Amber Yousaf2, Christian B. Nielsen1, Ching-Hong Tan1, Stoichko D. Dimitrov1, Zhengrong Shang3, Nicola Gasparini4, Maha Alamoudi5, Fr´ed´eric Laquai5, Christoph J. Brabec4, Alberto Salleo3, James R. Durrant1 & Iain McCulloch1,5 \n\nSolution-processed organic photovoltaics (OPV) offer the attractive prospect of low-cost, light-weight and environmentally benign solar energy production. The highest efficiency OPV at present use low-bandgap donor polymers, many of which suffer from problems with stability and synthetic scalability. They also rely on fullerene-based acceptors, which themselves have issues with cost, stability and limited spectral absorption. Here we present a new non-fullerene acceptor that has been specifically designed to give improved performance alongside the wide bandgap donor poly(3-hexylthiophene), a polymer with significantly better prospects for commercial OPV due to its relative scalability and stability. Thanks to the well-matched optoelectronic and morphological properties of these materials, efficiencies of $6.4\\%$ are achieved which is the highest reported for fullerene-free P3HT devices. In addition, dramatically improved air stability is demonstrated relative to other high-efficiency OPV, showing the excellent potential of this new material combination for future technological applications. \n\nhe efficiency of solution-processed organic photovoltaics (OPV) has been increasing rapidly, with the development of new high-performing benzodithiophene1–4 and difluorobenzothiadiazole5 -based donor polymers in particular that give up to $10\\%$ power conversion efficiency (PCE) combined with fullerene acceptors in single junction cells, and over $11\\%$ PCE in tandem devices6,7. Meanwhile, fullerene-free OPV has also been advancing, driven by the need to find alternative acceptors that overcome the high synthetic costs, limited optical absorption, poor bandgap tunability and morphological instability of fullerene-based acceptors such as phenyl- $\\mathrm{C}_{61}$ -butyric acid methyl ester $(\\mathrm{PC}_{60}\\mathrm{BM})$ and its $\\mathrm{C}_{71}$ analogue $\\mathrm{PC}_{70}\\mathrm{BM}$ (refs 8–10). Multiple reports of efficiencies over $6\\%$ have now been published with acceptors based on fused ring diimide11–15 and 1,1-dicyanomethylene-3-indanone16,17 structures. However, the majority of these record efficiencies are achieved with lowbandgap donor–acceptor polymers such as polythieno[3,4-b]- thiophene-alt-benzodithiophene (PTB7), which are known to present intrinsic difficulties to scale-up (thereby increasing costs) as well as suffering from issues with solubility18, device irreproducibility and photochemical instability19,20. Meanwhile, the simple homo-polymer poly(3-hexylthiophene) (P3HT), one of the most extensively used and best understood polymers in OPV research for some $\\mathrm{time}^{21-23}$ , is relatively stable24,25 and readily scalable due to its straightforward synthesis26 and compatibility with high-throughput production techniques27. Indeed, P3HT is currently one of the only polymers available in quantities over $10\\mathrm{kg}$ (ref. 23), making it one of the few feasible candidates for commercial OPV, and its use in large-area, roll-toroll printed solar cells has already been widely demonstrated28. Furthermore, the semi-crystalline nature of P3HT, compared with more amorphous polymers, is almost unique in setting an appropriate morphology lengthscale for bulk heterojunction OPV from a range of solvents and processing conditions, as well as providing it with good charge transport properties29–31. Despite this, P3HT has been somewhat marginalized in recent years since the introduction of higher efficiency donor–acceptor polymers. For $\\mathrm{P3HT:PC_{60}B M}$ devices, the average efficiency is only around $3\\%$ (ref. 21), with a maximum efficiency of $7.4\\%$ reported with the \n\nmore expensive fullerene indene- $.C_{60}$ -bisadduct (ICBA)32. We recently published a new non-fullerene acceptor called $(5Z,5^{\\prime}Z)-5$ , $5^{\\prime}$ -{(9,9-dioctyl-9H-fluorene-2,7-diyl)bis[2,1,3-benzothiadiazole-7, 4-diyl $(Z)$ methylylidene]}bis(3-ethyl-2-thioxo-1,3-thiazolidin-4-one) (FBR) that had a straightforward and scalable synthesis and gave $4.1\\%$ PCE in P3HT devices, which at the time of writing was the highest reported efficiency for a fullerene-free device with $\\mathrm{P}3\\mathrm{HT}^{33}$ . However, the short-circuit current $(J_{s c})$ in these devices was limited by recombination losses arising from the highly intermixed donor and acceptor phases, with FBR apparently unable to aggregate enough to form pure domains that would provide an appropriate charge percolation pathway. In addition, the large extent of spectral overlap of FBR with P3HT and lack of long-wavelength absorption reduced the ability to harvest photons across the spectrum, further limiting the generated photocurrent. \n\nWe now present a new acceptor derivative that has been designed to address both the spectral overlap and morphological issues with FBR via replacement of the fluorene core with an indacenodithiophene unit. This has the effect of planarizing the molecular structure and thus significantly red-shifting the absorption as well as increasing the tendency to crystallize on length scales commensurate with charge separation and extraction. We show how these properties can be further tuned via side-chain engineering, with linear ( $\\overset{\\cdot}{n}$ -octyl) alkyl chains yielding a more crystalline material with a further red-shifted absorption onset relative to branched (2-ethylhexyl) chains, resulting in higher $J_{s c}$ and PCE. Power conversion efficiencies of up to $6.4\\%$ were achieved, which is, to the best of our knowledge, the highest reported for fullerene-free P3HT solar cells. The oxidative stability of these devices is also found to be superior to the benchmark $\\mathrm{P3HT:PC_{60}B M}$ devices, as well as devices with several of the high-performance polymers tested alongside, demonstrating this to be a robust and highly promising new materials combination for OPV. \n\n# Results \n\nPhysical properties. The structure of the new IDTBR acceptors is shown in Fig. 1a. The indacenodithiophene (IDT) core was synthesized according to literature procedures34,35 and alkylated using either linear $n$ -octyl (O-IDTBR) or branched 2-ethylhexyl (EH-IDTBR) side chains as shown in Fig. 2. Stille coupling of the stannylated IDT with 7-bromo-2,1,3-benzothiadiazole-4- carboxaldehyde was then followed by Knoevenagel condensation with 3-ethylrhodanine to give O-IDTBR and EH-IDTBR in $60\\%$ and $30\\%$ final yields, respectively. The acceptors are both stable up to $350^{\\circ}\\mathrm{C}$ (Supplementary Fig. 1) and highly soluble in common organic solvents such as chloroform at room temperature, as well as non-halogenated solvents such as oxylene $(60^{\\circ}\\mathrm{C})$ , enabling facile solution processing of OPV devices. In the case of FBR, a torsional angle of $33.7^{\\circ}$ was calculated between the fluorene core and the adjacent benzothiadiazole unit by density functional theory (DFT) methods. By contrast, IDTBR was calculated to be essentially planar (Fig. 1b) due to the increased quinoidal character of the phenyl-thienyl bond compared with the phenyl–phenyl bond, and the reduced steric twisting from adjacent $d{\\mathrm{-}}C{\\mathrm{-}}\\mathrm{H}$ bonds on the coupled phenyl rings35,36. This enhanced planarity increases conjugation which, when combined with the more electron-rich thiophene-based core, acts to raise the highest occupied molecular orbital (HOMO). This is manifested in a significantly red-shifted UV–visible (UV–vis) absorption spectrum relative to that of FBR. Furthermore, whereas the lowest unoccupied molecular orbital (LUMO) of FBR was localized on the periphery of the molecule, the increased conjugation of IDTBR allows for slightly more delocalization of the LUMO across the central unit (Supplementary Fig. 2), which may be beneficial in terms of molecular oscillator strength and therefore molar absorption coefficient. However, the LUMO of IDTBR is still predominantly located on the periphery of the molecule, which was an important feature in the molecular design as it allows the energy of the highest occupied molecular orbital to be tuned by changing the central unit while preserving the relatively high-lying LUMO energy and thus maintaining a high open-circuit voltage. The molar absorption coefficient of $1\\stackrel{\\bullet}{\\times}10^{5}\\mathrm{M}^{-1}\\mathsf{c m}^{-1} $ (measured in solution) is over twice the value of FBR and demonstrates the potential of these molecules to contribute significantly more to the photocurrent relative to $\\mathrm{PC}_{60}\\mathrm{BM}$ for which the maximum extinction coefficient in the visible region $(400\\mathrm{nm})$ was measured alongside to be only $3.9\\times10^{3}\\mathrm{M}^{-1}\\mathrm{cm}^{-1}$ in $\\mathrm{CHCl}_{3}$ (Supplementary Table 1). Furthermore, IDTBR demonstrates significantly stronger absorption in the thin film relative to typical lowbandgap polymers such as PTB7 that absorb at similar wavelengths, as shown from the extinction coefficients plotted in Supplementary Fig. 3a. The absorption coefficient of IDTBR is also higher than those values reported for $\\mathrm{P3HT}^{37,38}$ .This introduces an exciting new concept in the design of active layer materials for OPV, where the acceptor can be used as the primary low-bandgap light absorber, able to donate holes on light absorption in at least an equally efficient way as donor polymers traditionally donate electrons on light absorption. \n\n![](images/feac3cf7c79912ed8e6068e73763abbd0fec2e558d06009c4f1e48c3375e784a.jpg) \nFigure 1 | Structure and UV–vis absorption of IDTBR acceptors. (a) Chemical structures of O-IDTBR and EH-IDTBR; (b) Optimized conformation of IDTBR as calculated by DFT $({\\mathsf{B}}3{\\mathsf{L Y P}}/{\\mathsf{6}}-31{\\mathsf{G}}^{\\star}).$ ) with methyl groups replacing alkyl chains for clarity; (c,d) UV–vis absorption spectra of (c) EH-IDTBR and (d) O-IDTBR in chloroform solution $(1.5\\times10^{-5}\\mathsf{m o l}|^{-1})$ , thin film (spin-coated from $10\\mathrm{mg}\\mathrm{ml}^{-1}$ chlorobenzene solution) and thin film annealed at $130^{\\circ}\\mathsf{C}$ for $10\\min$ . DFT, density functional theory. \n\nIt has been previously shown that the alkyl chain length and degree of branching can have a significant effect on the optoelectronic and aggregation properties in other IDT-BT-based systems34 and hence the investigation of both $n$ -octyl and 2-ethylhexyl chains with IDTBR. Figure 1c,d compare the UV–vis absorption spectra of the linear O-IDTBR and branched EH-IDTBR. The acceptors have very similar absorption profiles in solution with absorption maxima at $650\\mathrm{nm}$ , and evidently both materials demonstrate greater absorption in the visible region relative to $\\mathrm{PC}_{60}\\mathrm{BM}$ (Supplementary Fig. 4 and Supplementary Table 1), which further improves their ability to contribute to photocurrent through absorption. In the thin film, the absorption maximum of O-IDTBR is red-shifted by $40\\mathrm{nm}$ relative to that of EH-IDTBR, with a further bathochromic shift of $41\\mathrm{nm}$ for O-IDTBR upon annealing (above $110^{\\circ}\\mathrm{C}_{\\mathrm{;}}$ see Table 1 and Supplementary Fig. 3b). The shoulder observed at shorter wavelengths, which has been previously attributed to solid-state aggregation in IDT-BT polymers34, also becomes more pronounced with thermal annealing. By contrast, the absorption of EH-IDTBR is not affected by annealing (Table 1, Fig. 1c), indicating that the alkyl chains have a significant effect on the tendency of the material to crystallize in the thin film and this in turn strongly affects the absorption properties. \n\n![](images/370bbf1cfdf2e160d7e15ff0c54cbe824172fc92218faffe606a7cfa380e1119.jpg) \nFigure 2 | Synthesis of O-IDTBR and EH-IDTBR acceptors. The brominated indacenodithiophene core is first stannylated with trimethyltin chloride, then reacted via Stille coupling with 7-bromo-2,1,3-benzothiadiazole-4-carboxaldehyde. Knoevenagel condensation with 3-ethylrhodanine yields the final product. \n\n
Table 1 | Optoelectronic properties of O-IDTBR and EH-IDTBR acceptors.
: (104 m-1cm-1)* Amax solution (nm)*
O-IDTBR EH-IDTBR9.9 ± 0.1650amax film (nm) 690Amax ann. (nm) 731Eg opt. (eV) 1.63 ± 0.1EA (eV)s 3.88±0.05IP (eV)II 5.51± 0.05
10.3 ± 0.16506736751.68 ± 0.13.90±0.055.58±0.05
EA, electron affinity; IP, ionization potential.
Measurements were carried out in:
*CHCl solution. Thin film spin-coated from 10 mg ml-1 chlorobenzene solution.
Thin film annealed at 130 °C for 10 min.
§Cyclic voltammetry carried out on the as-cast thin film with O.1M TBAPF electrolyte in acetonitrile. lEstimated from the electrochemical EA and the optical Eg.
\n\n![](images/959051e14beaa9ce712cd992cf0c2940f498139fa592632b2efe8eef569d2c3e.jpg) \nFigure 3 | J–V characteristics and EQE of IDTBR devices with P3HT. (a) $J-V$ curves of optimized EH-IDTBR:P3HT and O-IDTBR:P3HT solar cells; (b) EQE spectra of optimized EH-IDTBR:P3HT and O-IDTBR:P3HT solar cells (solid lines) alongside normalized thin film absorption spectra of blends (dotted lines). \n\nCyclic voltammetry (CV) in the thin film shows that both EH-IDTBR and O-IDTBR have electron affinity (EA) values close to $3.9\\mathrm{eV}$ . The EA of P3HT was measured for comparison to be $3.2\\mathrm{eV}$ , allowing sufficient energetic offset for electron transfer between the donor and acceptor. The ionization potential $(I P)$ of O-IDTBR was measured to be slightly smaller than that of EH-IDTBR, which accounts for the small difference in optical bandgap (Table 1). This may be due to the enhanced planarization effect of O-IDTBR arising from the additional intermolecular interactions of the more aggregated material. The energy offset between the $I P$ of P3HT and both acceptors also appears to be suitable for efficient hole transfer. \n\nPhotovoltaic performance. Solar cells were fabricated using P3HT as the donor polymer due to the favourable energetic offsets mentioned above, as well as its widespread availability of P3HT and its potential for technological scale-up. An inverted device architecture of glass/ITO/ZnO/P3HT:IDTBR $\\mathrm{\\Delta}M_{0}\\mathrm{O}_{3}/\\mathrm{Ag}$ was chosen for its improved environmental stability relative to the conventional architecture39,40, allowing for devices to be tested under ambient conditions. The active layer blends (donorto-acceptor ratio of 1:1) were spin-coated from chlorobenzene solution under ambient conditions without the use of additives. Thermal annealing ( $10\\mathrm{min}$ at $130^{\\circ}\\mathrm{C})$ of these films was used to promote ordering of the polymer, as is typical in P3HT solar cells, as well as to induce acceptor crystallization which will be discussed later. Figure 3 and Table 2 show current density– voltage $\\left(J-V\\right)$ data for the optimized devices with an active device area of $0.045\\mathrm{cm}^{2}$ , which were measured under simulated AM1.5G illumination at $100\\mathrm{mW}\\mathrm{cm}^{-2}$ . Both acceptors yielded high open-circuit voltage $(V_{\\mathrm{oc}})$ values $(0.7\\mathrm{-}0.8\\mathrm{V})$ relative to reference devices with $\\mathrm{PC}_{60}\\mathrm{BM}$ as the acceptor, which gave $0.58\\mathrm{V}$ (Supplementary Fig. 5 and Supplementary Table 2) and this difference is accounted for by the smaller electron affinities of the IDTBR acceptors. IDTBR also generates higher short-circuit currents compared to $\\mathrm{PC}_{60}\\mathrm{BM}$ with P3HT, which may be related to the increased visible wavelength absorption, and therefore greater photocurrent generation, of these new acceptors. A higher average $J_{s c}$ of $13.9\\mathrm{mAcm}^{-2}$ is achieved from the O-IDTBR device, compared with $12.1\\mathrm{mAcm}^{-2}$ for EH-IDTBR. This can be understood, at least in part, by the broader external quantum efficiency (EQE) profile of O-IDTBR, which extends beyond ${800}\\mathrm{nm}$ due to the red-shifted absorption of the acceptor after annealing. Although the $V_{\\mathrm{oc}}$ and fill factor (FF) are both slightly lower for the linear chain analogue, this significantly larger $J_{s c}$ leads to an overall increase in average PCE from $6.0\\%$ for EH-IDTBR to $6.3\\%$ for O-IDTBR, with a maximum PCE of $6.4\\%$ for the best performing device. This is among the highest efficiencies for fullerene-free devices as well as being the highest published efficiency for non-fullerene acceptor devices with P3HT. It is also significantly higher than the reference $\\mathrm{PC}_{60}\\mathrm{BM:P3HT}$ device efficiency of $3.7\\%$ , despite the reduced active layer thickness of $75\\mathrm{nm}$ for the IDTBR devices compared with $150\\mathrm{nm}$ for the fullerene-based device. This difference in active layer thickness can also explain the increased peak EQE in the $\\mathrm{PC}_{60}\\mathrm{BM:P3HT}$ devices as shown in Supplementary Fig. 5b. To explore the compatibility of our new materials with large-area device fabrication, the dependency of $J-$ \n\n
Table 2| Photovoltaic performance of optimized EH-IDTBR:P3HT and O-IDTBR:P3HT solar cells.
Jsc (mA cm - 2)V.c (V)FFPCE (%)
O-IDTBR:P3HT13.9 ± 0.20.72 ±0.010.60 ± 0.036.30 ±0.1
EH-IDTBR:P3HT12.1± 0.10.76± 0.010.62±0.026.00±0.05
FF, fill factor; PCE, power conversion efficiency. Devi measured under simulated AM1.5G illumination at 1OO mW cm 2with average values obtained from 8 to 10 devices.
\n\n![](images/777038af79889662e6967493e80ca9f35d8d82ca29c27225aec44ca59039362a.jpg) \nFigure 4 | Morphology of acceptors and IDTBR:P3HT blends. (a) 2D GIXRD of O-IDTBR; (b) 2D GIXRD of O-IDTBR:P3HT (1:1); (c) DSC first heating cycles of O-IDTBR, P3HT and 1:1 blend; (d) 2D GIXRD of EH-IDTBR thin film; (e); 2D GIXRD of EH-IDTBR:P3HT (1:1); and (f) DSC first heating cycles of EH-IDTBR, P3HT and 1:1 blend. Thin films for GIXRD were processed using the same conditions as described for optimized devices and DSC drop-cast samples were measured at $5^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ . Thermograms are offset vertically for clarity. \n\n$V$ properties on active area was analysed for O-IDTBR:P3HT devices, as shown in Supplementary Fig. 6 and Supplementary Table 3. For active layers of $0.15\\mathrm{cm}^{2}$ , the PCE is maintained at $6.3\\%$ and for areas as large as $1.5\\mathrm{cm}^{2}$ , the PCE is still relatively high as $4.5\\%$ , owing to a slight reduction in $J_{s c}$ and FF. It should be noted that these larger area devices were prepared using procedures optimized for the $0.045\\mathrm{cm}^{2}$ cells, and that with further optimization of large-area devices their performance may be further improved, demonstrating these materials to be promising candidates for large-area, scalable OPV. \n\nCrystal packing. As discussed above, one of the limiting factors of the previously published FBR acceptor was the intimately mixed morphology with P3HT due to the amorphous nature of the acceptor, leading to charge recombination losses and limiting device performance. One of the design principles of IDTBR was therefore to increase the planarity of the backbone in order to induce crystallization and the formation of pure acceptor domains. Specular X-ray diffraction (XRD) was used to compare the crystallinity of the acceptors in films that were slightly thicker than those used in device fabrication $(280-290\\mathrm{nm})$ in order to provide enough resolution to observe crystalline reflections by this method. Supplementary Figs 7 and 8 show that, while FBR showed no sign of crystallinity in this case even with annealing, both O-IDTBR and EH-IDTBR give strong diffraction peaks. A clear increase in crystalline order is observed for O-IDTBR after annealing, in accordance with the red-shifted UV–vis absorption. From differential scanning calorimetry (DSC) measurements (Fig. 4) it is apparent that, during the first heating cycle, O-IDTBR undergoes an exothermic crystallization transition with an onset temperature of $108^{\\circ}\\mathrm{C}$ and $T_{c}$ of $115^{\\circ}\\mathrm{C}$ No such thermally induced crystallization occurs during the heating cycle of EH-IDTBR, explaining the different optical response of the acceptors to thermal annealing. DSC measurements were also carried out on drop-cast blends of the acceptors with P3HT to determine the extent of crystallization within the blend. The blend of FBR:P3HT (Supplementary Fig. 8) shows only the melting endotherm for P3HT upon heating, which has been depressed (by $20^{\\circ}\\mathrm{C})$ and broadened due to the disruption in packing caused by the acceptor; however, no transition for the acceptor is observed which indicates a lack of pure acceptor domains in this blend. By contrast, the heating cycles of O-IDTBR and EH-IDTBR blends with P3HT show the endothermic (and exothermic, in the case of O-IDTBR) transitions from the acceptor as well as the P3HT melt transition, demonstrating that these acceptors are more able to crystallize in the blend than FBR. Furthermore, the melting temperature of P3HT is only depressed by $10^{\\circ}\\mathrm{C}$ in the IDTBR blends, at the same heating rate, suggesting that the crystallization of P3HT is less disrupted by these acceptors. \n\nGrazing incidence XRD (GIXRD) was used to further investigate the formation of pure donor and acceptor domains in the thin-film blends. Figure 4 shows the GIXRD patterns of \n\nO-IDTBR and EH-IDTBR in both neat films and in 1:1 blends with P3HT, for which samples were prepared using the same conditions used for solar cells. It is evident that O-IDTBR forms a more ordered film than EH-IDTBR, with a narrow out-of-plane distribution of crystallites as given by the narrow width of the diffraction peaks. In O-IDTBR:P3HT blends, the O-IDTBR crystallites become isotropically distributed and exhibit polycrystalline rings in the diffractogram. The magnitude of the scattering wave vectors of the rings match with the diffraction peaks of neat O-IDTBR as is apparent from the peak analysis shown in Supplementary Figs 9 and 10. This suggests that the presence of P3HT may change the crystallite size and distribution of O-IDTBR but not its lattice structure. \n\nEH-IDTBR has an out-of-plane peak centred at $Q_{\\mathrm{z}}=1.69\\mathring{\\mathrm{A}}^{-1}$ , and several rings in its diffraction pattern. The peak most probably results from a portion of face-on $\\pi{-}\\pi$ stacking of EH-IDTBR aggregates. The rings indicate that besides the aggregates with face-on orientation, the film also has a considerable amorphous fraction. When EH-IDTBR is blended with P3HT, a new peak at $Q_{\\mathrm{z}}=0.48\\mathring{\\mathrm{A}}^{-1}$ appears, partly overlapping with the broad P3HT (001) alkyl peak at $0.39\\mathring{\\mathrm{A}}^{-1}$ . This peak does not correspond to any features seen in the diffraction pattern of neat EH-IDTBR, suggesting that in the presence of P3HT, EH-IDTBR crystallizes in a different orientation or a different polymorph than in neat form, although the diffraction data is not complete enough to allow us to distinguish between these two hypotheses. It should also be noted that the diffraction pattern of P3HT in the blends is the same as that of a pure P3HT $\\mathrm{{flm^{41}}}$ . \n\nCharge-carrier mobilities. It is well known that charge transport is crucial for efficient OPV devices. Carrier mobility of both donor and acceptor materials can be affected by morphology, field or carrier densities in bulk heterojunction active layers under operating conditions42,43. To get a reliable charge-carrier mobility of the blend systems, photo-induced charge-carrier extraction in a linearly increasing voltage (photo-CELIV) measurements were conducted. As these photo-CELIV measurements are conducted at 1 sun illumination on actual solar cells, they can provide important information on the transport properties in working devices44,45. In contrast to single-carrier measurements, the CELIV technique is more sensitive to the faster carrier component in the blend. The average performing EH-IDBTR:P3HT and O-IDTBR:P3HT devices were used in this experiment, having $80{-}90\\mathrm{nm}$ active layer thickness and $4\\mathrm{mm}^{2}$ active area (see Supplementary Table 4). Figure 5a shows the photo-CELIV transients of the two systems, which were recorded by applying a $2\\mathrm{V}$ per $60\\upmu\\mathrm{s}$ linearly increasing reverse bias pulse and a delay time $(t_{\\mathrm{d}})$ of $1\\upmu s$ . From the measured photocurrent transients, the charge carrier mobility $(\\mu)$ is calculated using the following equation (1): \n\n$$\n\\mu=\\frac{2d^{2}}{3A t_{\\operatorname*{max}}^{2}\\biggl[1+0.36\\frac{\\Delta j}{j(0)}\\biggr]}\\ i f\\ \\Delta j\\leq j(0),\n$$ \n\nwhere $d$ is the active layer thickness, $A$ is the voltage rise speed $\\boldsymbol{A}=\\mathrm{d}\\boldsymbol{U}/\\mathrm{d}t,\\ \\boldsymbol{U}$ is the applied voltage, $t_{\\mathrm{max}}$ is the time corresponding to the maximum of the extraction peak, and $j(0)$ is the displacement current. The photo-CELIV mobilities for the charge carriers in the O-IDTBR and EH-IDTBR blends with P3HT is found to be $5.4\\pm{0.4}\\times{10}^{-5}$ and $5.0\\pm0.3\\times10^{-5}\\mathrm{cm}^{2}\\mathrm{V}^{-1}s^{-1}$ after averaging over various delay times, respectively. The O-IDTBR:P3HT blend shows slightly higher charge-carrier density (which is the integrated area of the photo-CELIV curve at $1\\upmu\\mathrm{s}$ delay time) than the branched chain analogue system. In addition to photo-CELIV, the electron mobility of EH-IDTBR:P3HT and O-IDTBR:P3HT blends was determined by space charge-limited current (SCLC) measurements on electron-only devices as well as the hole mobility of EH-IDTBR:P3HT blends on hole-only devices. Both acceptors exhibited electron mobilities $\\sim3{-}6\\times10^{-6}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ while the hole mobility of EH-IDTBR:P3HT was found to be $\\sim3{-}7\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ (see Supplementary Fig. 11). Both methods therefore indicate relatively low electron mobilities for these blends. It is interesting to note that in spite of this rather low mobility, IDTBR:P3HT devices display FFs of up to $64\\%$ which is within the range of the majority of high-efficiency OPV devices reported in literature46. This indicates that non-geminate recombination may be severely suppressed in this system and also that charge generation is not strongly field dependent. However, a more in-depth investigation into the charge recombination dynamics would be needed to determine the exact mechanism behind these high FF values, and these studies are currently on-going. \n\nCharge extraction. Charge-carrier density $(n)$ using charge extraction $\\mathrm{(CE)^{45-47}}$ measurements were conducted for detailed investigation of the origin of reduced $V_{\\mathrm{oc}}$ in O-IDTBR solar cells compared with branched EH-IDTBR cells with P3HT. All samples were operated at $V_{\\mathrm{oc}},$ but under different background illumination intensities and then shorted in the dark to enable CE. The measured average $n$ as a function of $V_{\\mathrm{oc}}$ is depicted in Fig. 5b. It is apparent that, at equivalent charge densities, O-IDTBR devices exhibit $\\sim40\\mathrm{meV}$ lower open-circuit voltages (see shaded region, corresponding to around 1 sun irradiation) relative to EH-IDTBR. This shift in $n(V_{\\mathrm{oc}})$ indicates a $40\\mathrm{meV}$ smaller electronic bandgap for O-IDTBR devices, which is consistent with the reduced open-circuit value $(0.73{\\mathrm{V}})$ for O-IDTBR:P3HT devices compared with EH-IDTBR:P3HT solar cells (0.77 V). This reduced $\\bar{V}_{\\mathrm{oc}}$ can be explained by the more ordered microstructure of O-IDTBR:P3HT blends, as confirmed with GIXRD measurements, which results in a reduced electronic bandgap in the bulk. \n\n![](images/5cc517e1e59cfee61350c3a301e402b779d2d0b17302f77f9a6cc1baeb5ca8dc.jpg) \nFigure 5 | Charge transport and CE of IDTBR:P3HT blends. (a) Photo-CELIV of the O-IDTBR:P3HT and the EH-IDTBR:P3HT solar cells at $1\\upmu\\up s$ delay times; $t_{\\mathrm{max}}$ (the time when the extraction current reaches its maximum value) for O-IDTBR:P3HT and EH-IDTBR:P3HT is 4.7 and $4.3\\upmu\\mathsf{s}$ , respectively; (b) average charge densities measured in O-IDTBR:P3HT and EH-IDTBR:P3HT devices operating at open circuit as a function of $V_{\\mathrm{oc}}$ determined by CE for different bias light intensities. The grey area marks the data points corresponding $\\mathord{\\sim}1$ sun light intensity, and dashed lines correspond to the approximate device $V_{\\mathrm{oc}}$ values (upper line for EH-IDTBR, lower line for O-IDTBR) at 1 sun. \n\nPhotoluminescence (PL) quenching of blends. Photoluminescence (PL) studies were carried out on the EH-IDTBR:P3HT and O-IDTBR:P3HT blends relative to neat reference films of EH-IDTBR, O-IDTBR and P3HT to compare the PL quenching efficiency (PLQE) as shown in Supplementary Fig. 12. The selected range in the PL measurement is mainly focused on the emission of the acceptor. The films were excited at $680\\mathrm{nm}$ to excite selectively the IDTBR acceptors, with the PL quenching being assigned to hole transfer from IDTBR excitons to P3HT. It can be seen that the PL quenching is reasonably efficient for both systems, suggesting efficient hole transfer from acceptor excitons to the P3HT donor polymer. Qualitatively it can be seen that the PLQE is slightly larger for the linear compared with the branched chain system, which further affirms that the increased film crystallinity of O-IDTBR allows for the formation of pure acceptor domains on a lengthscale comparable to the exciton diffusion length of O-IDTBR. We note that this PL quenching contrasts with the almost quantitative acceptor PL quenching that was observed for FBR:P3HT blends, and that this is indicative of more pronounced phase segregation with both IDTBR acceptors compared with FBR33. \n\nCharge generation and recombination dynamics. The charge generation process was studied with femtosecond–nanosecond transient absorption spectroscopy (TAS). Transient spectra of EH-IDTBR and O-IDTBR blends, measured with the acceptors excited selectively at $680\\mathrm{nm}$ , are shown in Supplementary Fig. 13. The spectra of neat EH-IDTBR and O-IDTBR films were collected using the same excitation wavelength and density. Because of the spectral overlap of exciton and polaron signals, these spectra were analysed by deconvoluting the blend spectra from the neat P3HT, neat IDTBR and polaron spectra at selected time delays. Successful deconvolution of the blend spectra using the neat data allowed the temporal evolution of the polaron signal to be extracted for both blends studied herein, as shown in Fig. 6. For both blends, polaron growth kinetics were observed on a similar timescale to acceptor exciton decay. This indicates reasonably efficient charge separation from IDTBR excitons and is also consistent with the photocurrent generation from IDTBR light absorption observed in the EQE data (Fig. 3b). The rise of the polaron signal, and decay of acceptor absorption, fitted reasonably well to single exponential functions. For EH-IDTBR:P3HT, the polaron rise kinetics, and decay kinetics of EH-IDTBR exciton absorption, primarily exhibit time constants of 10–20 ps. Only a small fraction $(10-20\\%)$ of the polaron generation appears to occur within our instrument response. This contrasts with FBR:P3HT blends, where at least $50\\%$ of polaron generation was observed to be instrument response limited33, consistent with more complete phase segregation compared with FBR. Slower polaron formation and exciton decay is observed for \n\n![](images/4cbee8b8d8bfa6a25579ed9c9f3c4fb6c211a9660653249330994090145e25c8.jpg) \nFigure 6 | Charge generation and recombination dynamics of IDTBR:P3HT blends. Rise and decay of photogenerated EH-IDTBR and O-IDTBR polaron absorption, obtained by deconvolution of the ultrafast transient absorption spectra of the EH-IDTBR:P3HT and O-IDTBR:P3HT blend films excited at $680\\mathsf{n m}$ , $2\\upmu\\up c m^{-2}$ . Symbols correspond to deconvoluted polaron signals and the lines correspond to fitting of the data. \n\nO-IDTBR:P3HT $(60-120\\mathrm{ps})$ , indicating more delayed polaron generation for this blend which is consistent with our PLQE results. We have previously reported relatively slow (hundreds of picoseconds) polaron generation from acceptor excitons in polymer:PCBM blends, and correlated these with exciton diffusion within pure PCBM domains to the donor/acceptor interface47. It appears likely that the slow polaron generation kinetics we observe herein are also limited by the kinetics of exciton diffusion within pure IDTBR domains, with the slower kinetics observed for O-IDTBR being consistent with increased phase separation for this blend as discussed above. Charge recombination is also apparent in Fig. 6 as a decay of the polaron signal at longer time delays. It is apparent that these kinetics are slower for O-IDTBR compared with EH-IDTBR, again most probably associated with great phase segregation in the O-IDTBR blend. \n\nSolar cell stability. Oxidative stability is an essential consideration for the technological implentation of OPV materials24. For many of the record high efficiencies reported with low-bandgap polymers, all device fabrication and measurement must be carried out in inert conditions to maintain this performance. By contrast, the efficiencies reported herein for IDTBR:P3HT were obtained with device processing and measurement carried out in air (except for active layer annealing in a nitrogen glovebox). This improved stability is partially attributed to the inverted architecture used, which means that no encapsulation steps are needed for these devices. To further investigate the stability of IDTBR:P3HT devices to air, aging measurements were carried out alongside reference devices of $\\mathrm{PC}_{60}\\mathrm{BM}$ :P3HT as well as three of the most widely reported high-efficiency polymers PTB7, PCE-10 (PTB7-Th) and PCE-11 (PffBT4T-2OD)5,48,49 For a fair comparison, all devices were prepared in the same inverted architecture as for IDTBR devices. After the initial (stabilized PCE) measurement was taken, devices were stored in the dark under ambient conditions between measurements, which were taken at intervals over the course of $^{1,200\\mathrm{h}}$ . The corresponding PCE data is shown in Fig. 7, with normalized data given in Supplementary Fig. 14 along with the polymer structures. It is clear from this data that O-IDTBR:P3HT devices demonstrate the least degradation out of the materials studied, and that after an initial small drop in performance within the first $60\\mathrm{h}$ , the PCE remains relatively stable and still gives $73\\%$ of the initial PCE even after $^{1,200\\mathrm{h}}$ . By contrast, the efficiency of the high-performance donor polymer devices deteriorates remarkably quickly and has fallen to zero by the end of the period of study. This further demonstrates the potential of our new acceptor design for stable, scalable solar cells with practical operating lifetimes, and also gives strong support for the choice of P3HT as donor polymer in these devices. \n\n![](images/2f825887f4e66f98b9692b29f56c9bc670f4172ea6be93b486d374bffe892a3b.jpg) \nFigure 7 | Solar cell stability. Oxidative stability of O-IDTBR:P3HT device efficiencies (PCE) compared with other high-performance polymer:fullerene systems. Devices were stored in the dark under ambient conditions between measurements. \n\nIn addition to oxidative stability, the morphological stability of the O-IDTBR:P3HT blends was investigated. One of the main issues with fullerene-based acceptors like $\\mathrm{PC}_{60}\\mathrm{BM}$ is that large-scale aggregates and crystals emerge from the meta-stable blend morphology over time. This process can be monitored by polarized optical microscopy during accelerated aging of the films upon annealing29,50. To compare the thermal aging of the IDTBR blends with fullerene blends, films of O-IDTBR:P3HT and $\\mathrm{PC}_{60}\\mathrm{BM:P3HT}$ were prepared on $Z_{\\mathrm{{nO/ITO}}}$ substrates and these were subjected to annealing at $140^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . As the micrographs in Supplementary Fig. 15 show, large $(1-20\\upmu\\mathrm{m})$ aggregates appear after $^\\mathrm{1h}$ annealing of the fullerene blend, whereas the O-IDTBR blend remains smooth and featureless after annealing, suggesting that this new acceptor offers improved morphological stability over fullerene acceptors, at least in terms of lateral diffusion. \n\n# Discussion \n\nIn this work, we present a new small molecule electron acceptor IDTBR that is based on an indacenodithiophene core with benzothiadiazole and rhodanine flanking groups. IDTBR is designed to give high performance with the donor polymer P3HT, chosen for its commercial scale-up potential both in terms of cost, scalability and stability. In comparison with our previously published acceptor FBR, which had an essentially overlapping absorption profile with P3HT, this new acceptor has a significantly reduced optical bandgap owing to the more planar molecular backbone, delocalized electronic structure and push–pull molecular orbital hybridization, resulting in a UV–vis absorption profile that is now highly complementary to that of P3HT. This gives broader photon harvesting across the incident solar spectrum within the active layer, which is reflected in higher short-circuit currents and power conversion efficiencies relative to FBR:P3HT devices. Furthermore, the absorption onset of this new IDTBR acceptor can be tuned by judicial choice of solubilizing alkyl chains on the IDT unit. Linear (O-IDTBR) chains promote stronger intermolecular packing, which is particularly enhanced by thermal annealing, relative to branched (EH-IDTBR) chains. One effect of this is to further red-shift the absorption of O-IDTBR relative to the branched counterpart, which results in a broader EQE profile, higher $J_{s c}$ and an increase in PCE from 6.0 to $6.4\\%$ . CE measurements at the same light intensity reveal a reduced electronic bandgap for O-IDTBR relative to EH-IDTBR, which explains the difference in $V_{\\mathrm{oc}}$ measured for these devices. As well as affecting the optoelectronic properties, the enhanced intermolecular interactions of the linear alkyl chain also have an effect on the blend morphology. Relative to FBR, both IDTBR acceptors exhibit increased crystallinity and, crucially, formation of pure acceptor domains as evidenced by GIXRD and DSC studies. O-IDTBR in particular shows pronounced crystal packing upon annealing, which is consistent with the reduced optical bandgap. This results in greater phase segregation for the linear analogue which is manifested in reduced PL quenching of the acceptor emission, as well as a delayed polaron generation and slower recombination dynamics in the O-IDTBR:P3HT blend. Interestingly, the charge-carrier mobilities measured for the IDTBR:P3HT blends appear quite low, considering the reasonably high FFs obtained from devices (up to $64\\%$ ) and the charge recombination dynamics of these systems therefore warrant further investigation to determine whether non-geminate recombination is significantly suppressed. In addition to high efficiencies, IDTBR:P3HT devices demonstrate improved stability in ambient conditions compared with the benchmark $\\mathrm{PC}_{60}\\mathrm{BM}$ :P3HT device, as well as several systems with typical low-bandgap, high-performance polymers, which were found to degrade at a dramatic rate when exposed to air. IDTBR devices also showed improved morphological stability to fullerene devices in accelerated aging studies. These results strongly supports the use of P3HT, in conjunction with non-fullerene acceptors such as IDTBR, for high-efficiency, scalable and stable OPV for future technological applications. \n\n# Methods \n\nGeneral characterization. $^1\\mathrm{H}$ and $^{13}\\mathrm{C}$ NMR spectra were collected on a Bruker AV-400 spectrometer at $298\\mathrm{K}$ and are reported in p.p.m. UV–vis absorption spectra were recorded on a UV-1601 Shimadzu UV–vis spectrometer. DSC experiments were carried out with a Mettler Toledo DSC822 instrument at a heating rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ under nitrogen. Samples were prepared by drop-casting the materials from $\\mathrm{CHCl}_{3}$ solution directly into the DSC pan and allowing the solvent to evaporate under Ar. Specular XRD was carried out on thin films of the acceptors spin-coated from $\\mathrm{CHCl}_{3}$ solutions $(30\\mathrm{mg}\\mathrm{ml}^{-1}$ , $600\\mathrm{r.p.m.},$ ) using a PANalytical X’Pert PRO MRD diffractometer equipped with a nickel-filtered Cu-Ka1 beam and X’Celerator detector, with a current $I{=}40\\mathrm{mA}$ and accelerating voltage $U{=}40\\mathrm{kV}$ Samples for GIXRD were spin-coated on Si (100) substrates following the same spin-coating and annealing procedures as were used in fabricating solar cells. \n\nSynthesis. The compounds 1a and 1b were prepared according to literature procedure34,35, as was 7-bromo-2,1,3-benzothiadiazole-4-carboxaldehyde33. P3HT was obtained from Flexink Ltd. All other reagents and solvents were purchased from Sigma Aldrich or Acros Organics and used as received. All reactions were carried out using conventional Schlenk techniques in an inert argon atmosphere. 2a. A solution of 1a $(2.11\\mathrm{g},2.42\\mathrm{mmol})$ in anhydrous tetrahydrofuran $(200\\mathrm{ml})$ was stirred at $-78^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . $n$ -BuLi $2.42\\mathrm{ml}$ , $6.04\\mathrm{mmol}$ $2.5\\mathrm{M}$ in hexanes) was added dropwise and the solution was stirred at $-78^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ followed by $-10^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . After cooling again to $\\phantom{0}{-78^{\\circ}C,}$ trimethyltin chloride was added (7. 26 ml, 7.56 mmol, 1 M in hexanes) and the solution was allowed to return to room temperature overnight. The reaction was then poured into water and extracted with hexane, washed successively with acetonitrile to remove excess trimethyltin chloride and dried over $\\mathrm{MgSO_{4}}$ to yield 2a as a yellow oil $(2.18\\mathrm{g},86\\%)$ . $^1\\mathrm{H}$ NMR ${}^{\\prime}400\\mathrm{MHz},$ $\\mathrm{CDCl}_{3}$ ) d: 7.25 (s, 2H), 6.97 (s, 2H), 1.97–1.91 (m, 4H), 1.86–1.78 (m, 4H), 1.23–1.05 (m, 48H), 0.83–0.80 (t, 12H, $J{=}7\\mathrm{Hz}$ ), 0.39 (s, 18H); \n\n$^{13}\\mathrm{C}$ NMR ${\\bf\\Psi}_{\\mathrm{101MHz}}$ , $\\mathrm{CDCl}_{3}$ ) d: 157.15, 153.47, 147.71, 139.24, 135.31, 129.55, 113.42, 53.06, 39.20, 31.87, 30.07, 30.03, 29.31, 24.17, 22.68, 14.14 and 8.02. MS (ES-ToF): $m/z$ calculated for $\\mathrm{C_{54}H_{90}S_{2}S n}$ : 1,040.45; $m/z$ found 1,041.40 $(\\mathrm{M}+\\mathrm{H})^{+}$ . \n\n3a. A solution of 2a $\\left(1.04\\mathrm{g}\\right.$ $1.0\\mathrm{mmol}$ ) and 2,1,3-benzothiadiazole-4- carboxaldehyde $(0.73\\mathrm{g},3.0\\mathrm{mmol})$ in anhydrous toluene $\\left(40\\mathrm{ml}\\right)$ was degassed for $45\\mathrm{min}$ before $\\mathrm{Pd}(\\mathrm{PPh}_{3})_{4}$ $\\left\\langle58\\mathrm{mg},0.05\\mathrm{mmol}\\right.$ ) was added and this solution was heated at $100^{\\circ}\\mathrm{C}$ overnight. The reaction mixture was then cooled and purified by flash column chromatography on silica mixed with potassium fluoride using $\\mathrm{CHCl}_{3}$ as the eluent. Further purification by column chromatography on silica using $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}/$ /pentane (1:1) followed by precipitation from methanol yielded 3a as a dark purple solid $(0.93\\mathrm{g},90\\%$ ). $^1\\mathrm{H}$ NMR $(400\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}$ ) d: 10.72 (s, 2H), 8.27 (s, 2H), 8.25 (d, $J{=}7.7\\mathrm{Hz}$ , 2H), 8.06 (d, $J{=}7.5\\mathrm{Hz},$ 2H), 7.45 (s, 2H), 2.05 (dtd, $J{=}59.3$ , 12.9, $4.6\\mathrm{Hz}$ , 8H), 1.05–1.2 (m, 38H), 0.99–0.81 (m, 10H), 0.77 (t, $J{=}6.8\\mathrm{Hz}$ , 12H); $^{13}\\mathrm{C}$ NMR (101 MHz, $\\mathrm{CDCl}_{3}$ ) d: 188.44, 157.04, 154.02, 152.29, 147.00, 140.67, 136.44, 134.14, 132.87, 131.62, 124.87, 124.8, 122.80, 114.12, 54.43, 39.16, 31.79, 29.98, 29.29, 29.20, 24.29, 22.58, 14.04. MS (ES-ToF): m/z calculated for $\\mathrm{C}_{62}\\mathrm{H}_{78}\\mathrm{N}_{4}\\mathrm{O}_{2}\\mathrm{S}_{4}$ : 1,038.5; $m/z$ found 1,041.40. \n\nO-IDTBR. 3a $(0.40\\mathrm{g},0.39\\mathrm{mmol})$ and 3-ethylrhodanine $(186\\mathrm{mg},1.16\\mathrm{mmol})$ were dissolved in tert-butyl alcohol $(30\\mathrm{ml})$ . Two drops of piperidine were added and the solution was left to stir at $85^{\\circ}\\mathrm{C}$ overnight. The product was extracted with $\\mathrm{CHCl}_{3}$ and dried over $\\mathrm{MgSO_{4}}$ . The crude product was purified by flash column chromatography on silica in $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}$ and precipitated from methanol. The precipitate was collected and dried by vacuum filtration to afford O-IDTBR a dark blue solid $(0.40\\mathrm{g},78\\%)$ ). $\\mathrm{mp}=219-221^{\\circ}\\mathrm{C}$ . $^1\\mathrm{H}$ NMR ${'}_{400}\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}$ ) d: 8.54 (s, 2H), 8.24 (s, 2H), 8.03 (d, $J{=}8.0\\mathrm{Hz},2\\mathrm{H}$ ), 7.74 (d, $J{=}7.9\\mathrm{Hz}$ , 2H), 7.45 (s, 2H), 4.27 (q, $J{=}8.0\\mathrm{Hz}$ , 4H), 2.18–1.96 (m, 8H), 1.35 (t, $J{=}8.1\\mathrm{Hz}$ , 6H), 1.22–1.12 (m, 40H), 0.99–0.90 (m, 8H), 0.80 (m, 12H). $^{13}\\mathrm{C}$ NMR ${\\bf\\Psi}_{\\mathrm{101\\:MHz}}$ , $\\mathrm{CDCl}_{3}$ ) d: 193.04, 167.59, 157.05, 154.63, 154.22, 151.77, 146.15, 141.02, 136.41, 131.37, 130.54, 127.29, 124.49, 124.25, 124.08, 123.82, 113.97, 54.38, 39.94, 39.19, 31.82, 30.02, 29.33, 29.24, 24.30, 22.61, 14.08 and 12.35. MS (matrix-assisted laser desorption/ionization–time of flight): $m/z$ calculated for $\\mathrm{C}_{72}\\mathrm{H}_{88}\\mathrm{N}_{6}\\mathrm{O}_{2}\\mathrm{S}_{8}$ : 1,324.5; $\\mathrm{m/z}$ found 1,326.0 $(\\mathrm{M}+\\mathrm{H})^{+}$ . \n\n2b. A solution of 1b $(1.09\\mathrm{g},$ $1.25\\mathrm{mmol}$ ) in anhydrous tetrahydrofuran $(40\\mathrm{ml})$ was stirred at $-78^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . $n$ -BuLi ( $1.25\\mathrm{ml}$ , $3.12\\mathrm{mmol}$ , $2.5\\mathrm{M}$ in hexanes) was added dropwise and the solution was stirred at $-78^{\\circ}\\mathrm{C}$ for 1 h. Trimethyltin chloride was then added $3.75\\mathrm{ml}$ , 3.75 mmol, 1 M in hexanes) and the solution was allowed to return to room temperature overnight. The reaction was then poured into water and extracted with hexane, washed successively with acetonitrile to remove excess trimethyltin chloride and dried over $\\mathrm{MgSO_{4}}$ to yield 2b as a yellow oil $(1.16\\mathrm{g},89\\%)$ . $^1\\mathrm{H}$ NMR ${\\bf\\Psi}_{\\mathrm{400MHz}}$ , $\\mathrm{CDCl}_{3}$ ) d: 7.28 (s, 2H), 6.99 (s, 2H), 1.96– 1.88 $(\\mathrm{m},8\\mathrm{H})$ , 1.87–1.82 $\\left(\\mathrm{m},8\\mathrm{H}\\right)$ ), 0.99–0.46 $(\\mathrm{m},60\\mathrm{H})$ , 0.37 (s, 18H). $^{13}\\mathrm{C}$ NMR (101 MHz, $\\mathrm{CDCl}_{3}$ ) d: 157.40, 153.43, 147.51, 140.73, 135.20, 130.04, 113.95, 53.52, 43.59, 34.89, 32.20, 29.75, 28.74, 28.10, 22.67, 14.16 and 8.16. \n\n3b. A solution of 2b $(0.94\\mathrm{g},0.90\\mathrm{mmol})$ and 2,1,3-benzothiadiazole-4- carboxaldehyde $(0.53\\mathrm{g},2.17\\mathrm{mmol})$ in anhydrous toluene $(30\\mathrm{ml})$ was degassed for $45\\mathrm{min}$ before $\\mathrm{Pd}(\\mathrm{PPh}_{3})_{4}$ $\\left\\langle52\\mathrm{mg},0.05\\mathrm{mmol}\\right\\rangle$ ) was added and this solution was heated at $110^{\\circ}\\mathrm{C}$ overnight. The reaction mixture was then cooled and purified by flash column chromatography on silica mixed with potassium fluoride using $\\mathrm{CHCl}_{3}$ as the eluent. Further purification by column chromatography on silica using $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}/$ pentane (1:1) followed by precipitation from methanol yielded $\\mathbf{36}$ as a dark purple solid $(0.40\\mathrm{g},43\\%)$ . $^1\\mathrm{H}$ NMR ${\\bf\\dot{\\Psi}}_{400}\\bf{M H z}$ , $\\mathrm{CDCl}_{3}$ ) d: 10.72 (s, 2H), 8.37–8.30 (m, 2H), 8.25 (d, $J{=}7.6\\mathrm{Hz}$ , 2H), 8.03 (d, $J{=}7.5\\operatorname{Hz}$ , 2H), 7.49 (s, 2H), 2.15–2.05 (m, 8H), 1.05–0.85 $\\mathrm{{(m,40H)}}$ , 0.74–0.50 (m, 20H). MS (ES-ToF): $m/z$ calculated for $\\mathrm{C}_{62}\\mathrm{H}_{78}\\mathrm{N}_{4}\\mathrm{O}_{2}\\mathrm{S}_{4}$ : $1,038.50;m/z$ found $1,038.50~(\\mathrm{M}^{+})$ . \n\nEH-IDTBR. 3b $(0.20\\mathrm{g},0.19\\mathrm{mmol})$ and 3-ethylrhodanine $(93\\mathrm{mg},0.58\\mathrm{mmol})$ ) were dissolved in tert-butyl alcohol $(15\\mathrm{ml})$ . 1 drop of piperidine was added and the solution was left to stir at $85^{\\circ}\\mathrm{C}$ overnight. The product was extracted with $\\mathrm{CHCl}_{3}$ and dried over $\\mathrm{MgSO_{4}}$ . The crude product was purified by flash column chromatography on silica with $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}$ as the eluent followed by precipitation from methanol to yield EH-IDTBR as a dark blue solid $(0.20\\mathrm{g},80\\%)$ . $\\mathrm{mp}=218{-}220^{\\circ}\\mathrm{C}$ $^1\\mathrm{H}$ NMR ${'}_{400}\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}$ ) d: 8.53 (s, 2H), 8.27 $(\\mathrm{m},2\\mathrm{H})$ , 7.99 $(\\mathrm{m},2\\mathrm{H})$ , 7.73 (d, $J{=}8.1\\mathrm{Hz},$ 2H), 7.47 (s, 2H), 4.25 (q, $J{=}8.0\\mathrm{Hz}$ , 4H), 2.07 (m, 8H), 1.34 (t, $J{=}8.0\\mathrm{Hz}$ , 6H), 0.95–0.90 (m, 36H), 0.69–0.54 $\\mathrm{(m},24\\mathrm{H})$ . $^{13}\\dot{\\mathrm{C}}$ NMR $(101\\mathrm{MHz},$ $\\mathrm{CDCl}_{3}$ ) d: 193.07, 167.58, 156.76, 154.63, 153.93, 151.80, 146.14, 140.46, 136.38, 131.37, 130.64, 127.31, 125.08, 124.51, 124.30, 123.73, 114.82, 54.19, 39.94, 35.13, 34.16, 28.64, 28.25, 27.26, 22.86, 14.18, 12.33 and 10.60. MS (matrix-assisted laser desorption/ionization–time of flight): $m/z$ calculated for $\\mathrm{C}_{72}\\mathrm{H}_{88}\\mathrm{N}_{6}\\mathrm{O}_{2}\\mathrm{S}_{8}$ : 1,324.5; $m/z$ found 1,325.9 $(\\mathrm{M}+\\mathrm{H})^{+}$ . \n\nCyclic voltammetry. CV measurements were performed using an Autolab PGSTAT101 potentiostat. Thin films of the acceptor were spin-coated onto ITO-coated glass substrates to be used as the working electrode, alongside a platinum mesh counter electrode and $\\mathrm{\\Ag/Ag^{+}}$ reference electrode. Measurements were carried out in anhydrous and deoxygenated acetonitrile with $0.1\\mathrm{M}$ of tetrabutylammonium hexafluorophosphate (TBA $\\mathrm{PF}_{6})$ as the supporting electrolyte, and calibrated against ferrocene in solution using a cylindrical Pt working electrode. IP and EA values were calculated from the following equations: \n\n$$\nE A=(E_{\\mathrm{red}}-E_{\\mathrm{Fc}}+4.8)~\\mathrm{eV}\n$$ \n\n$$\nI P=(E_{\\mathrm{ox}}-E_{\\mathrm{Fc}}+4.8)~\\mathrm{eV}\n$$ \n\nwhere $E_{\\mathrm{red}}$ and $E_{\\mathrm{ox}}$ are taken from the onset of reduction and oxidation, respectively, and $\\scriptstyle E_{\\mathrm{Fc}}$ is taken as the half-wave potential of ferrocene. \n\nOPV devices. Bulk heterojunction solar cells were fabricated with an inverted architecture (glass/ITO/ZnO/P3HT:Acceptor $/\\mathrm{MoO}_{3}/\\mathrm{Ag})$ . Glass substrates were used with pre-patterned indium tin oxide (ITO). These were cleaned by sonication in detergent, deionized water, acetone and isopropanol, followed by oxygen plasma treatment. ZnO layers were deposited by spin-coating a zinc acetate dihydrate precursor solution ( ${\\mathrm{\\dot{6}0}}\\upmu\\mathrm{l}$ monoethanolamine in $2\\bmod{2}$ -methoxyethanol) followed by annealing at $150^{\\circ}\\mathrm{C}$ for $10{-}15\\operatorname*{min}$ , giving layers of $30\\mathrm{nm}$ . The P3HT:IDTBR (1:1 ratio by mass) active layers were deposited from $24\\mathrm{mg}\\mathrm{ml}^{-1}$ solutions in chlorobenzene by spin-coating at $2{,}000\\mathrm{r.p.m}$ , followed by annealing at $130^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . Active layer thicknesses were $75\\mathrm{nm}$ (averaged over six devices) for both acceptor blends. $\\mathrm{P3HT:PC_{60}B M}$ (1:1 ratio by mass) layers were spin-coated at $1{,}500\\mathrm{r.p.m}$ . from $40\\mathrm{mg}\\mathrm{ml}^{-1}$ solutions in o-dichlorobenzene, followed by annealing in the glovebox at $130^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ , resulting in active layer thicknesses of $148\\mathrm{nm}$ . $\\mathrm{MoO}_{3}$ $\\left(10\\mathrm{nm}\\right)$ and $\\mathrm{Ag}$ $\\cdot100\\mathrm{nm})$ layers were deposited by evaporation through a shadow mask yielding active areas of $0.045\\mathrm{cm}^{2}$ in each device. $\\left(J-V\\right)$ characteristics were measured using a Xenon lamp at AM1.5 solar illumination (Oriel Instruments) calibrated to a silicon reference cell with a Keithley 2400 source meter, correcting for spectral mismatch. Incident photon conversion efficiency was measured by a $100\\mathrm{W}$ tungsten halogen lamp (Bentham IL1 with Bentham 605 stabilized current power supply) coupled to a monochromator with computer controlled stepper motor. The photon flux of light incident on the samples was calibrated using a UV-enhanced silicon photodiode. A ${590}\\mathrm{-nm}$ long-pass glass filter was inserted into the beam at illumination wavelengths longer than $580\\mathrm{nm}$ to remove light from second-order diffraction. Measurement duration for a given wavelength was sufficient to ensure the current had stabilized. \n\nThe low-bandgap polymers PTB7, PCE-10 (PTB7-Th) and PCE-11 (PffBT4T-2OD) used in stability studies were obtained from Ossila, and the active layers for these devices were prepared as follows, with the same architecture a used for the IDTBR:P3HT devices. \n\n$\\mathsf{P T B7:P C}_{70}\\mathsf{B M}$ Active layer solutions (D:A ratio 1:1.5) were prepared in CB with $3\\mathrm{wt\\%}$ 1,8-diiodooctane (total concentration $25\\mathrm{mgml^{-1}}$ ). To completely dissolve the polymer, the active layer solution was stirred on a hot plate at $80^{\\circ}\\mathrm{C}$ for at least $^{3\\mathrm{h}}$ . Active layers were spin-coated from the warm polymer solution on preheated substrates in a nitrogen glove box at $1{,}500\\mathrm{r.p.m}$ . \n\nP $C E-10:P C_{70}B M$ Active layer solutions (D:A ratio 1:1.5) were prepared in CB with $3\\mathrm{wt\\%}$ 8-diiodooctane (total concentration $35\\mathrm{mg}\\mathrm{ml}^{-1}$ ). To completely dissolve the polymer, the active layer solution was stirred on a hot plate at $80^{\\circ}\\mathrm{C}$ for at least $^{3\\mathrm{h}}$ . Active layers were spin-coated from the warm polymer solution onto preheated substrates in a nitrogen glove box at $1{,}500\\mathrm{r.p.m}$ . \n\nPCE-11:PC $70^{8M}$ . Active layer solutions (D:A ratio 1:1.4) were prepared in $\\mathrm{CB}/\\mathrm{o}$ -DCB (1:1 volume ratio) with $3\\mathrm{wt\\%}$ 8-diiodooctane (polymer concentration: $10\\mathrm{mg}\\mathrm{ml}^{-1},$ ). To completely dissolve the polymer, the active layer solution was stirred on a hot plate at $110^{\\circ}\\mathrm{C}$ for at least $^{3\\mathrm{h}}$ . Active layers were spin-coated from the warm polymer solution onto preheated substrates in a nitrogen glove box at $1{,}000\\mathrm{r}{.}\\mathrm{p}{.}\\mathrm{m}$ . \n\nPhoto-CELIV. In photo-CELIV measurements, the devices were illuminated with a $405\\mathrm{nm}$ laser-diode. Current transients were recorded across an internal $50\\Omega$ resistor on an oscilloscope (Agilent Technologies DSO-X 2024A). A fast electrical switch was used to isolate the cell and prevent CE or sweep out during the laser pulse and the delay time. After a variable delay time, a linear extraction ramp was applied via a function generator. The ramp, which was $20\\upmu\\mathrm{s}$ long and $2\\mathrm{V}$ in amplitude, was set to start with an offset matching the $V_{\\mathrm{oc}}$ of the cell for each delay time. The geometrical capacitance is calculated as: \n\n$$\nC=\\varepsilon{\\varepsilon_{0}}A/d\n$$ \n\nwhere $A$ is the device area $(4\\:\\mathrm{mm}^{2})$ , $\\varepsilon=3$ and, $\\varepsilon_{0}=8.85\\times10^{-12}\\mathrm{F}\\mathrm{m}^{-1}$ are the relative and absolute dielectric permittivity, respectively, and $d$ is the active layer thickness $(90\\mathrm{nm})$ . $C$ is then calculated as $1\\mathrm{nF}$ Assuming $R_{\\mathrm{load}}=50\\mathrm{nm}$ , the $R C$ value is $5.9\\times10^{-8}\\mathrm{s}$ . Assuming the electrical field $(E)$ is $\\mathrm{\\hat{1}}\\times10^{5}\\mathrm{V}\\mathrm{m}^{-1}$ , the transient time (t) is calculated with the following formula: \n\n$$\nt=t_{\\operatorname*{max}}*\\sqrt{3}\\ t=t_{\\operatorname*{max}}*\\sqrt{3}=8{\\times}10^{-6}\\ s\n$$ \n\nCharge extraction. In CE measurements, the devices were illuminated in air with a $405\\mathrm{nm}$ laser diode for $200\\upmu\\mathrm{s}$ which was sufficient to reach a constant open-circuit voltage with steady state conditions. At the end of the illumination period, an analogue switch was triggered that switched the solar cell from open-circuit to short-circuit $\\left(50\\upomega\\right)$ conditions within less than $50\\mathrm{ns}$ . By adjusting the laser intensity, different open-circuit voltages were obtained which allowed a plot to be generated of charge-carrier density over voltage. As described by Shuttle et al.51, a correction was applied for the charge on the electrodes that results from the geometric capacity of the device52. \n\nSpace charge-limited current. SCLC measurements were performed on electron-only devices of the structure ITO/PEDOT:PSS/Al/P3HT:acceptor/Al and on hole-only devices of the structure ITO/PEDOT:PSS/P3HT:acceptor/Au using a Paios (FLUXiM AG) measurement system. The current–voltage characteristics were fitted by the Mott–Gurney law in the region where the current follows the square of the voltage to extract the carrier mobility. \n\nPL spectroscopy and transient absorption spectroscopy (TAS). Samples for TAS and PL spectroscopy were spin-coated onto glass using the same conditions as for solar cells. Spectra were measured using a steady state spectrofluorimeter (Horiba Jobin Yvon, Spex Fluoromax 1). The spin-coated films were excited at $680\\mathrm{nm}$ . Sub-picosecond TAS was carried out at ${800}\\mathrm{nm}$ laser pulse $(1\\mathrm{kHz},90\\mathrm{fs}$ ) by using a Solstice (Newport Corporation) Ti:sapphire regenerative amplifier. A part of the laser pulse was used to generate the pump laser at 680 nm, $2\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ with a TOPAS-Prime (light conversion) optical parametric amplifier. The other laser output was used to generate the probe light in near visible continuum $(450-800\\mathrm{nm})$ by a sapphire crystal. The spectra and decays were obtained by a HELIOS transient absorption spectrometer $(450-1,450\\mathrm{nm}$ ) and decays to 6 ns. The samples were measured in $\\Nu_{2}$ atmosphere. Deconvolution of the blend spectra was conducted by fitting the singlet EH-IDTBR exciton spectrum $\\mathrm{(S_{exciton})}$ and the P3HT:EH-IDTBR polaron spectrum $(\\mathrm{S_{polaron}})$ at 6 ns to the blend spectra for 20 different time delays using the equation: \n\n$$\n\\Delta_{\\mathrm{OD}}=A_{1}*S_{\\mathrm{exciton}}(1,150\\ \\mathrm{nm})+A_{2}*S_{\\mathrm{polaron}}(1,000\\ \\mathrm{nm})\n$$ \n\nwhere $A_{1}$ and $A_{2}$ are linear coefficients that estimate the percentage contribution of the spectra to the experimental blend spectra. $S_{\\mathrm{exciton}}$ was derived from the transient absorption spectra of the EH-IDTBR, which peaks at $1,150\\mathrm{nm}$ at selected time delays (Supplementary Fig. 13). This signal, assigned to singlet exciton absorption, disappeared at $\\sim20\\mathrm{ps}$ (Fig. 6). The polaron spectrum was derived from the TA spectra of the blend at 6 ns, where no exciton contributions are expected (Supplementary Fig. 13). Note that an exciton signal from P3HT is not expected, as supported by our PL measurements. \n\n# References \n\n1. Huang, J. et al. $10.4\\%$ Power conversion efficiency of ITO-free organic photovoltaics through enhanced light trapping configuration. Adv. Energy Mater. 5, 1500406 (2015). \n2. He, Z. et al. Enhanced power-conversion efficiency in polymer solar cells using an inverted device structure. Nat. Photon. 6, 593–597 (2012). \n3. Liao, S.-H., Jhuo, H.-J., Cheng, Y.-S. & Chen, S.-A. Fullerene derivative-doped zinc oxide nanofilm as the cathode of inverted polymer solar cells with low-bandgap polymer (PTB7-Th) for high performance. Adv. Mater. 25, 4766–4771 (2013). \n4. Ye, L., Zhang, S., Zhao, W., Yao, H. & Hou, J. Highly efficient 2D-conjugated benzodithiophene-based photovoltaic polymer with linear alkylthio side chain. Chem. Mater. 26, 3603–3605 (2014). \n5. Liu, Y. et al. Aggregation and morphology control enables multiple cases of high-efficiency polymer solar cells. Nat. Commun. 5, 5293 (2014). \n6. Zhou, H. et al. Polymer homo-tandem solar cells with best efficiency of $11.3\\%$ . Adv. Mater. 27, 1767–1773 (2015). \n7. Chen, C. C. et al. An efficient triple-junction polymer solar cell having a power conversion efficiency exceeding $11\\%$ . Adv. Mater. 26, 5670–5677 (2014). \n8. Lin, Y. & Zhan, X. Non-fullerene acceptors for organic photovoltaics: an emerging horizon. Mater. Horizons 1, 470–488 (2014). \n9. Eftaiha, A. F., Sun, J., Hill, I. G. & Welch, G. C. Recent advances of non-fullerene, small molecular acceptors for solution processed bulk heterojunction solar cells. J. Mater. Chem. A 2, 1201 (2014). \n10. Nielsen, C. B., Holliday, S., Chen, H.-Y., Cryer, S. J. & McCulloch, I. Non-fullerene electron acceptors for use in organic solar cells. Acc. Chem. Res. 48, 2803–2812 (2015). \n11. Zhong, Y. et al. Efficient organic solar cells with helical perylene diimide electron acceptors. J. Am. Chem. Soc. 136, 15215–15221 (2014). \n12. Zhang, X., Zhan, C. & Yao, J. Non-fullerene organic solar cells with $6.1\\%$ efficiency through fine-tuning parameters of the film-forming process. Chem. Mater. 27, 166–173 (2015). \n13. Zhao, J. et al. High-efficiency non-fullerene organic solar cells enabled by a difluorobenzothiadiazole-based donor polymer combined with a properly matched small molecule acceptor. Energy Environ. Sci. 8, 520–525 (2015). \n14. Li, H. et al. Fine-tuning the 3D structure of nonfullerene electron acceptors toward high-performance polymer solar cells. Adv. Mater. 27, 3266–3272 (2015). \n15. Zhong, Y. et al. Molecular helices as electron acceptors in high-performance bulk heterojunction solar cells. Nat. Commun. 6, 8242 (2015). \n16. Lin, Y. et al. An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174 (2015). efficiency. Energy Environ. Sci. 8, 610–616 (2015). \n18. Lou, S. J. et al. Effects of additives on the morphology of solution phase aggregates formed by active layer components of high-efficiency organic solar cells. J. Am. Chem. Soc. 133, 20661–20663 (2011). \n19. Soon, Y. W. et al. Correlating triplet yield, singlet oxygen generation and photochemical stability in polymer/fullerene blend films. Chem. Commun. 49, 1291–1293 (2013). \n20. Razzell-Hollis, J. et al. Photochemical stability of high efficiency PTB7:PC70BM solar cell blends. J. Mater. Chem. A 2, 20189–20195 (2014). \n21. Dang, M. T., Hirsch, L. & Wantz, G. P3HT:PCBM, best seller in polymer photovoltaic research. Adv. Mater. 23, 3597–3602 (2011). \n22. Mulligan, C. J. et al. A projection of commercial-scale organic photovoltaic module costs. Sol. Energy Mater. Sol. Cells 120, 9–17 (2014). \n23. Po, R. et al. From lab to fab: how must the polymer solar cell materials design change?—an industrial perspective. Energy Environ. Sci. 7, 925–943 (2014). \n24. Jørgensen, M. et al. Stability of polymer solar cells. Adv. Mater. 24, 580–612 (2012). \n25. Manceau, M. et al. Effects of long-term UVvisible light irradiation in the absence of oxygen on P3HT and P3HT: PCBM blend. Sol. Energy Mater. Sol. Cells 94, 1572–1577 (2010). \n26. Tremel, K. & Ludwigs, S. in P3HT Revisited—From Molecular Scale to Solar Cell Devices. (ed. Ludwigs, S.) Ch. 2 (Springer, 2014). \n27. Bannock, J. H. et al. Continuous synthesis of device-grade semiconducting polymers in droplet-based microreactors. Adv. Funct. Mater. 23, 2123–2129 (2013). \n28. Espinosa, N., Hosel, M., Jorgensen, M. & Krebs, F. C. Large scale deployment of polymer solar cells on land, on sea and in the air. Energy Environ. Sci. 7, 855–866 (2014). \n29. Campoy-Quiles, M. et al. Morphology evolution via self-organization and lateral and vertical diffusion in polymer:fullerene solar cell blends. Nat. Mater. 7, 158–164 (2008). \n30. Brabec, C. J., Heeney, M., McCulloch, I. & Nelson, J. Influence of blend microstructure on bulk heterojunction organic photovoltaic performance. Chem. Soc. Rev. 40, 1185–1199 (2011). \n31. Holliday, S., Donaghey, J. E. & McCulloch, I. Advances in charge carrier mobilities of semiconducting polymers used in organic transistors. Chem. Mater. 26, 647–663 (2014). \n32. Guo, X. et al. High efficiency polymer solar cells based on poly(3-hexylthiophene)/indene-C70 bisadduct with solvent additive. Energy Environ. Sci. 5, 7943–7949 (2012). \n33. Holliday, S. et al. A rhodanine flanked nonfullerene acceptor for solution-processed organic photovoltaics. J. Am. Chem. Soc. 137, 898–904 (2015). \n34. Bronstein, H. et al. Indacenodithiophene-co-benzothiadiazole copolymers for high performance solar cells or transistors via alkyl chain optimization. Macromolecules 44, 6649–6652 (2011). \n35. Zhang, W. et al. Indacenodithiophene semiconducting polymers for high-performance, air-stable transistors. J. Am. Chem. Soc. 132, 11437–11439 (2010). \n36. McCulloch, I. et al. Design of semiconducting indacenodithiophene polymers for high performance transistors and solar cells. Acc. Chem. Res. 45, 714–722 (2012). \n37. Zhang, M., Guo, X., Ma, W., Ade, H. & Hou, J. A polythiophene derivative with superior properties for practical application in polymer solar cells. Adv. Mater. 26, 5880–5885 (2014). \n38. Cook, S., Furube, A. & Katoh, R. Analysis of the excited states of regioregular polythiophene P3HT. Energy Environ. Sci. 1, 294–299 (2008). \n39. Sun, Y., Seo, J. H., Takacs, C. J., Seifter, J. & Heeger, A. J. Inverted polymer solar cells integrated with a low-temperature-annealed sol-gel-derived ZnO film as an electron transport layer. Adv. Mater. 23, 1679–1683 (2011). \n40. Xu, Z. et al. Vertical phase separation in poly(3-hexylthiophene): fullerene derivative blends and its advantage for inverted structure solar cells. Adv. Funct. Mater. 19, 1227–1234 (2009). \n41. Shao, M. et al. The isotopic effects of deuteration on optoelectronic properties of conducting polymers. Nat. Commun. 5, 3180 (2014). \n42. You, J. et al. A polymer tandem solar cell with $10.6\\%$ power conversion efficiency. Nat. Commun. 4, 1446 (2013). \n43. Gasparini, N. et al. Photophysics of molecular-weight-induced losses in indacenodithienothiophene-based solar cells. Adv. Funct. Mater. 25, 4898–4907 (2015). \n44. Chen, S. et al. Photo-carrier recombination in polymer solar cells based on P3HT and silole-based copolymer. Adv. Energy Mater. 1, 963–969 (2011). \n45. Clarke, T. M., Lungenschmied, C., Peet, J., Drolet, N. & Mozer, A. J. A comparison of five experimental techniques to measure charge carrier lifetime in polymer/fullerene solar cells. Adv. Energy Mater. 5, 1401345 (2015). \n46. Bartesaghi, D. et al. Competition between recombination and extraction of free charges determines the fill factor of organic solar cells. Nat. Commun. 6, 7083 (2015). \n47. Dimitrov, S. D. et al. Towards optimisation of photocurrent from fullerene excitons in organic solar cells. Energy Environ. Sci. 7, 1037–1043 (2014). \n48. Lu, L. & Yu, L. Understanding low bandgap polymer PTB7 and optimizing polymer solar cells based on it. Adv. Mater. 26, 4413–4430 (2014). \n49. He, Z. et al. Single-junction polymer solar cells with high efficiency and photovoltage. Nat. Photon. 9, 174–179 (2015). \n50. Schroeder, B. C. et al. Enhancing fullerene-based solar cell lifetimes by addition of a fullerene dumbbell. Angew. Chemie Int. Ed. 53, 12870–12875 (2014). \n51. Shuttle, C. G. et al. Experimental determination of the rate law for charge carrier decay in a polythiophene: fullerene solar cell. Appl. Phys. Lett. 92, 093311 (2008). \n52. Heumueller, T. et al. Disorder-induced open-circuit voltage losses in organic solar cells during photoinduced burn-in. Adv. Energy Mater. 5, 1500111 (2015). \n\n# Acknowledgements \n\nWe thank BASF for partial financial support, as well as EPSRC Projects EP/G037515/1 and EP/M023532/1, EC FP7 Project SC2 (610115), EC FP7 Project ArtESun (604397), EC FP7 Project POLYMED (612538), Project Synthetic carbon allotropes project SFB 953 and the King Abdullah University of Science and Technology (KAUST). George Richardson is gratefully acknowledged for his assistance with optical microscopy. M.A. thanks Z. Kan and Y. Firdaus for helpful discussions. \n\n# Author contributions \n\nS.H. and A.W. synthesized the IDTBR acceptors and carried out DSC measurements. \nS.H. and D.B. carried out optoelectronic characterization. S.H. ran DFT calculations. \nR.S.A. and S.A.Y. fabricated and characterized solar cell devices. D.B. and N.G. \n\ncarried out photo-CELIV and CE measurements. C.B.N. conducted specular XRD measurements. M.A. carried out SCLC experiments. C.-H.T. and S.D. carried out PL and TAS experiments. Z.S. carried out GIXRD measurements. S.H. prepared the manuscript with contributions from D.B., C.-H. T, Z. S. and F. L. All authors discussed the results and commented on the manuscript. F.L. supervised SCLC, C.J.B. supervised photo-CELIV and CE, A.S. supervised GIXRD and J.R.D. supervised PL and TAS and revised the manuscript. I.M. revised the manuscript and supervised and directed the project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Holliday, S. et al. High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor. Nat. Commun. 7:11585 doi: 10.1038/ncomms11585 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_NPHOTON.2015.277", + "DOI": "10.1038/NPHOTON.2015.277", + "DOI Link": "http://dx.doi.org/10.1038/NPHOTON.2015.277", + "Relative Dir Path": "mds/10.1038_NPHOTON.2015.277", + "Article Title": "Hexagonal boron nitride is an indirect bandgap semiconductor", + "Authors": "Cassabois, G; Valvin, P; Gil, B", + "Source Title": "NATURE PHOTONICS", + "Abstract": "Hexagonal boron nitride is a wide bandgap semiconductor with very high thermal and chemical stability that is used in devices operating under extreme conditions. The growth of high-purity crystals has recently revealed the potential of this material for deep ultraviolet emission, with intense emission around 215 nm. In the last few years, hexagonal boron nitride has been attracting even more attention with the emergence of two-dimensional atomic crystals and van der Waals heterostructures, initiated with the discovery of graphene. Despite this growing interest and a seemingly simple structure, the basic questions of the bandgap nature and value are still controversial. Here, we resolve this long-debated issue by demonstrating evidence for an indirect bandgap at 5.955 eV by means of optical spectroscopy. We demonstrate the existence of phonon-assisted optical transitions and we measure an exciton binding energy of about 130 meV by two-photon spectroscopy.", + "Times Cited, WoS Core": 992, + "Times Cited, All Databases": 1107, + "Publication Year": 2016, + "Research Areas": "Optics; Physics", + "UT (Unique WOS ID)": "WOS:000372978900017", + "Markdown": "# Hexagonal boron nitride is an indirect bandgap semiconductor \n\nG. Cassabois, P. Valvin and B. Gil\\* \n\nHexagonal boron nitride is a wide bandgap semiconductor with very high thermal and chemical stability that is used in devices operating under extreme conditions. The growth of high-purity crystals has recently revealed the potential of this material for deep ultraviolet emission, with intense emission around 215 nm. In the last few years, hexagonal boron nitride has been attracting even more attention with the emergence of two-dimensional atomic crystals and van der Waals heterostructures, initiated with the discovery of graphene. Despite this growing interest and a seemingly simple structure, the basic questions of the bandgap nature and value are still controversial. Here, we resolve this long-debated issue by demonstrating evidence for an indirect bandgap at 5.955 eV by means of optical spectroscopy. We demonstrate the existence of phonon-assisted optical transitions and we measure an exciton binding energy of about 130 meV by twophoton spectroscopy. \n\nexagonal boron nitride (hBN) exhibits unique electronic properties, such as a wide bandgap, low dielectric constant, high thermal conductivity and chemical inertness. In contrast to other nitride semiconductors such as GaN and $\\mathrm{AlN^{1}};$ , for which most stable crystalline phase is of the wurtzite type, the hexagonal structure of hBN makes it a prototype two-dimensional material, along with graphene and molybdene disulphide2. With a honeycomb structure based on $\\ s p^{2}$ covalent bonds similar to graphene, bulk hBN, with its atomically smooth surface, first gained a great deal of attention as an exceptional substrate for graphene. Two-dimensional hBN, or ‘white graphene’, in the form of few-layer crystals or monolayers of hBN, has since emerged as a fundamental building block for van der Waals heterostructures3. \n\nIn spite of this rising interest in hBN and the large number of studies devoted to this material, with its seemingly simple crystal structure, the very basic question of the nature of its bandgap remains controversial. There is a strong contrast between ab initio band structure calculations, which predict an indirect bandgap crystal4–8, and optical measurements, which indicate a direct bangap $^{9-11}$ . In 2004, Watanabe and colleagues demonstrated that hBN is a very promising material for light-emitting devices in the deep ultraviolet domain, with an intense luminescence peak at $5.76~\\mathrm{eV},$ supporting the direct nature of the bandgap9. The use of high-purity hBN crystals has since allowed the demonstration of lasing at $215\\mathrm{nm}$ by accelerated electron excitation9 and also the operation of field-emitter display-type devices in the deep ultraviolet12,13. \n\nHere, we demonstrate that hBN has an indirect bandgap at $5.955\\ \\mathrm{eV}$ and that the optical properties of hBN are profoundly determined by phonon-assisted transitions. By means of twophoton spectroscopy, we reveal the existence of previously unobserved lines. The weakest one lies at the highest energy $(5.955\\mathrm{eV})$ , and it corresponds to the dim emission of the indirect exciton. Each emission line appearing at lower energy consists of a phonon replica, for which we identify the corresponding phonon mode. Finally, two-photon excitation spectroscopy allows us to measure, for the first time in an indirect bandgap semiconductor, the energy splitting between the 1s and $2p$ exciton states. We obtain an estimate of the exciton binding energy of $128\\pm15\\mathrm{meV},$ showing that excitons in hBN are of a Wannier type and that the single-particle bandgap is at an energy of $6.08\\pm0.015\\mathrm{eV}$ in hBN. \n\nFigure 1a presents a photoluminescence spectrum of hBN at low temperature, in the usual configuration of one-photon excitation at $6.3\\:\\mathrm{eV}.$ . We observe the luminescence peak at $5.76\\ \\mathrm{eV}$ reported by Watanabe et al. in high-purity samples, attributed to the recombination of free excitons9. Spatially resolved cathodoluminescence measurements have confirmed this interpretation on the basis of the homogeneous spatial distribution of the emission intensity in hBN crystallites14,15 and in few-layer hBN flakes16,17. The presence of defects in hBN leads to two additional emission bands centred at $5.5\\mathrm{eV}$ and $4~\\mathrm{eV}$ (refs 13,14,18–20). In contrast to the $5.76\\mathrm{eV}$ emission line of the free exciton, these defect-related emission bands display strong localization near dislocations and boundaries in cathodoluminescence measurements14–17, with a striking spatial anticorrelation with the free exciton photoluminescence at $5.76\\mathrm{eV}_{\\mathrm{i}}$ , as recently characterized with nanometric resolution in a transmission electron microscope17. \n\nFigure 1a also shows that the $5.76\\ \\mathrm{eV}$ emission line is a multiplet with fine structures extending over $40~\\mathrm{meV}_{:}$ , accompanied by a similar satellite band at $5.86~\\mathrm{eV}$ of lower intensity15,16,21. This satellite band shows the same delocalized emission over the hBN crystals as the $5.76\\mathrm{eV}$ one, characteristic of free exciton recombination17. The different free-exciton levels observed in Fig. 1a (usually called S lines in the literature) have been tentatively attributed to dark and bright excitons with a degeneracy lifted by a Jahn–Teller effect21. Still, all theoretical calculations predict an indirect bandgap for $\\mathrm{hBN^{4-8}}$ . Moreover, our two-photon excitation scheme allows us to detect two previously unreported lines, namely a weak doublet around $5.93\\mathrm{eV}$ and an even dimmer line at $5.955\\mathrm{eV}$ (Fig. 1b), thanks to the detuning of the laser at about half the detection energy, and the subsequent suppression of the laser stray light present in one-photon spectroscopy (Fig. 1a). In the following, we will provide a comprehensive understanding of the optoelectronic properties of hBN in the deep ultraviolet, which display all the features of an indirect bandgap semiconductor. \n\n$A b$ initio calculations predict an indirect bandgap for hBN with extrema of the band structure located around the M and K points of the Brillouin zone for the conduction and valence bands, respectively4–8. Excitonic effects modify the single-particle picture of band structure calculations, whatever the direct or indirect nature of the optical transition22. As in other indirect semiconductors23, the hBN indirect exciton (iX) corresponding to the electron–hole pair built around the M and K points of the Brillouin zone is thus not coupled to light in the dipolar approximation, and phonon scattering is required to fulfil momentum conservation during photon emission or absorption24. \n\n![](images/09536339c25f111c783b2e02d4131f004497eabf5bb4f68fe14ec1040a3f4802.jpg) \nFigure 1 | Monitoring exciton thermalization in phonon replicas. a, Photoluminescence spectrum of hBN at $10~\\mathsf{K}$ for one-photon excitation at 6.3 eV. b, Photoluminescence spectrum of hBN for two-photon excitation at $3.03\\mathrm{eV}$ as a function of temperature (the spectra are shifted for clarity). Dotted lines indicate a Boltzmann law with an effective temperature of $T_{\\mathrm{e}}=145\\mathsf{K}$ superimposed on a constant baseline. c, Effective temperature $T_{\\mathrm{e}}$ (symbols) as a function of lattice temperature $T_{\\mathrm{L}}$ . Error bars indicate the standard deviations for least-squares fitting of the photoluminescence spectra with a Boltzmann law and the dashed curve is a linear regression with a slope of 1.85. d, Schematic representation of the anisotropic energy dispersion of the indirect exciton iX around the MK point of reciprocal space. The colourmap corresponds to a thermal distribution of indirect excitons, with the density decreasing from red to blue. \n\nThe first evidence for recombination assisted by phonon emission in hBN arises from the observation of a thermal distribution of excitons in the high-energy tail of the different emission lines. Figure 1b presents the photoluminescence spectrum of hBN as a function of temperature for two-photon excitation at $3.03\\mathrm{eV}$ Thanks to our background-free excitation scheme, we see that, for both the 5.76 and $5.86\\mathrm{eV}$ emission lines, the photoluminescence signal intensity falls exponentially on their high-energy side, with the slope decreasing on raising the temperature. On the contrary, on their low-energy side, these emission bands remain unchanged with temperature, except for some residual contamination by the intense redshifted neighbouring lines. To quantitatively analyse the exponential decrease in the photoluminescence signal at high energy, we fitted our data with Boltzmann distributions of the effective temperature $T_{\\mathrm{e}}$ . As shown, for instance, at $75\\mathrm{K}$ in Fig. 1b, we obtain excellent agreement, with systematically the same effective temperature for the 5.76 and $5.86~\\mathrm{eV}$ emission lines. The effective temperature $T_{\\mathrm{e}}$ is also plotted as a function of lattice temperature $T_{\\mathrm{L}}$ in Fig. 1c and, for temperatures larger than $25\\mathrm{K},$ we observe a thermalization of the excitonic system with the surrounding crystal. \n\nSuch a phenomenology is typical of semiconductor materials. Hot excitons are initially created with a large kinetic energy after electrical or optical excitation. During carrier relaxation their energy distribution converges to a thermal Boltzmann law via exciton–exciton collisions and phonon-assisted scattering processes. However, in photoluminescence experiments, the exciton thermalization cannot be observed in the so-called zero-phonon line because only excitons with wavevector close to zero can contribute to the photoluminescence signal by direct emission of photons. The population of free excitons with large wavevectors can only be monitored by studying phonon replicas, because phonon emission ensures momentum conservation in their radiative recombination. This universal effect has been observed in many different semiconductors25–28. In the specific context of exciton condensation, the transition from a Boltzmann to a Bose–Einstein distribution is investigated by a careful study of the high-energy tail of phonon replicas29. As only phonon-assisted processes can give an accurate replica of the energy distribution of excitons, we first conclude that the observation of a thermal distribution of excitons in hBN is a first piece of evidence for the nature of the 5.76 and $5.86\\mathrm{eV}$ emission lines being phonon replicas. \n\nAs far as the thermalization process is concerned, the strong structural anisotropy of hBN translates into an effective temperature $T_{\\mathrm{e}}$ of the Boltzmann law larger than the lattice temperature $T_{\\mathrm{L}},$ , as can be seen in Fig. 1c, where the linear regression (dashed curve) has a slope of 1.85. Although striking at first sight, this effect simply arises when taking into account the $k$ -dependence of the phonon energy in the phonon-assisted recombination process (Supplementary Section A). Although usually negligible in other semiconductors, leading to $T_{\\mathrm{e}}\\sim T_{\\mathrm{L}}$ (ref. 29), this correction is important in hBN because of the flatness of both the phonon and electron dispersions along the $z$ axis7,30. In fact, the corresponding large effective mass (schematically shown in Fig. 1d) leads to a huge increase in the density of exciton states, so the phonon replicas mostly monitor exciton thermalization along the $z$ axis. Such a situation is strongly analogous to the case of quantum well superlattices, where two-dimensional excitons thermalize and efficiently redistribute over the whole superlattice mini-zone31. \n\nThe 5.76 and $5.86\\mathrm{eV}$ emission lines having now been identified as phonon replicas, we now turn to the determination of the indirect exciton iX energy. In the optical response of indirect semiconductors there is a mirror symmetry between the two processes of absorption and emission assisted by phonon emission24: compared with the bandgap energy, photon emission is redshifted by the phonon energy, while photon absorption is blueshifted by the same value (see energy level schemes in Fig. 2a). We will show now that the emission line of smallest intensity, observed at $5.955\\ \\mathrm{eV}$ in Fig. 1b, corresponds to the indirect exciton iX. To check the mirror image between emission and absorption around $5.955\\ \\mathrm{eV};$ , in Fig. 2a we plot the normalized photoluminescence spectrum (red diamonds) and the normalized photoluminescence excitation (PLE) spectrum (blue open squares) in a spectral window centred at $5.955\\mathrm{eV}.$ It is essential to compare the photoluminescence spectrum of free excitons with the PLE one detected at the corresponding emission energy, as is the case in ref. 32 (Supplementary Section C), but not in previous studies reporting PLE spectroscopy for detection windows centred at defect-related lines11,19,20,33. In Fig. 2a we observe that the signal intensity is on the order of the noise around $5.955\\ \\mathrm{eV}$ in both cases, and that it increases to its maximum value by a blueshift (redshift) of $60~\\mathrm{meV}$ in the PLE (photoluminescence, respectively) spectrum. Moreover, the lines have a half-width at half-maximum (HWHM) on the order of $25\\mathrm{meV}$ in both emission and absorption spectra (see Supplementary Section C for an interpretation of the line profile in hBN). Although the rise in the PLE signal around $6.01\\ \\mathrm{eV}$ is not as steep as in the photoluminescence spectrum around $5.9\\mathrm{eV}$ (due to a poorer spectral resolution in the one-photon excitation spectroscopy in ref. 32), we will show by two-photon excitation spectroscopy (Fig. 3, inset) that the PLE signal has the same abrupt rise as the photoluminescence signal, thus confirming the mirror image of emission and absorption around $5.955\\mathrm{eV}.$ . \n\n![](images/2e11b0deffa764e9c13a9d460d1bb3a983c4700fd0255fca6ea8e70efc6b08b7.jpg) \nFigure 2 | Phonon-assisted emission and absorption in hBN. a, Normalized photoluminescence signal intensity (red diamonds) at $10\\mathsf{K}$ as a function of detection energy and normalized PLE signal intensity (blue open squares) at 11 K (from ref. 32) as a function of excitation energy. Insets: schematic representations of recombination (red double arrow) and absorption (blue double arrow) assisted by phonon emission (vertical green arrow) involving the virtual states $\\mathsf{X}_{\\mu}$ and $\\operatorname{\\mathsf{X}}_{\\mu^{\\prime}}^{\\star}$ respectively, where $\\mu$ is a phonon mode. ${\\bf b},$ Identification of the phonon modes involved in the phonon-assisted recombination lines in hBN. The scattering path in the first Brillouin zone is indicated by the green arrow, corresponding to the phonon wavevector. c, Normalized photoluminescence spectrum at $10\\mathsf{K}$ for two-photon excitation at $3.03\\mathrm{eV},$ at low excitation power for optimal observation of the fine structures. \n\nIn the simplest case of one-phonon scattering processes, momentum conservation completely determines the phonon wavevector as MK (corresponding to the green arrow in the first Brillouin zone in Fig. 2b). From simple geometrical considerations of the hexagonal Brillouin zone, one can deduce that one-phonon scattering processes involve phonons in the middle of the Brillouin zone, around $T$ points34. Consequently, the energy detuning between the phonon replicas and the indirect exciton iX reflect the energy of the different phonon modes around the $T$ points. In Fig. 2b, vertical arrows indicate the positions of the five doublet lines observed in the photoluminescence spectrum. Their energy detunings with iX are 22, 64, 95, 162 and $188\\pm1$ meV, respectively. From the complete phonon band structure characterization reported in ref. 30 we observe a perfect agreement with the phonon energy in the middle of the Brillouin zone for the ZA, TA, LA, TO and LO modes, respectively. The corresponding assignment displayed in Fig. 2b thus allows us to identify the intense emission band at $5.76\\mathrm{eV}$ as due to two optical phonon replicas, whereas the less intense emission between 5.8 and $5.94\\mathrm{eV}$ arises from three acoustic phonon replicas. This situation corresponds to the general phenomenology observed in semiconductor materials, where the electron– phonon coupling is much more efficient in the case of optical phonons for which the coupling is given by the Fröhlich interaction, while the deformation potential and piezoelectric coupling lead to less efficient scattering processes in the case of acoustic phonons24. As far as the acoustic phonon replicas are concerned, we explain the low signal intensity of the $\\mathrm{X}_{\\mathrm{ZA}}$ line as being a result of the selection rule controlling radiative recombination assisted by phonons in hBN, which is forbidden by symmetry for a ZA phonon mode in hBN in our experimental configuration (Supplementary Section B). \n\nIn light of this identification of five phonon replicas in the photoluminescence spectrum of hBN, we also interpret the varying visibility of the doublet structure in each replica as being due to the group velocity of the corresponding phonon branch. For acoustic phonons, the group velocity increases when passing from ZA to TA and LA modes30, so momentum conservation fulfilled within a given $k$ -space interval results in an increasing energy variation, thus smoothing the fine structure of the phonon replicas. This effect is more clearly observed in Fig. 2c, where the photoluminescence spectrum is plotted on a linear scale, and where the contrast of the doublet structure decreases from the ZA to TA and LA replicas. In contrast, optical phonons have a smaller group velocity than acoustic phonons30, therefore revealing with maximum contrast the fine structure of a given phonon replica (Fig. 2c). Incidentally, we note that a triplet structure develops for optical phonon replicas, and we speculate the existence of a zone-folding effect due to the presence of multilayer segments of different thickness in our sample, in analogy to the observation for multilayer graphene35. Finally, we highlight that the energy detunings $\\delta_{1}=26\\pm1$ meV and $\\dot{\\delta_{2}}=31\\pm\\dot{1}$ meV (Fig. 2c) discussed in the literature21 simply reflect the TO–LO energy splitting and the TA–LA one in the middle of the Brillouin zone. \n\nWe thus demonstrate that hBN does have an indirect bandgap, in agreement with theoretical calculations4–8. Furthermore, our estimation of $5.955\\ \\mathrm{eV}$ is fully consistent with electron energy loss spectroscopy in hBN, where electronic momentum transfer allows the excitation of indirect bandgap material, in contrast to optical spectroscopy. The bandgap of bulk hBN was found to be $5.9\\pm0.2\\ \\mathrm{eV}$ (ref. 36), and in multiwalled boron nitride nanotubes in which quantum confinement is negligible, a value of $5.8\\pm0.2\\:\\mathrm{eV}$ (ref. 37) was obtained. \n\nWith a view to further elucidate the fundamental optoelectronic properties of hBN, we performed two-photon excitation spectroscopy to determine the exciton binding energy. Two-photon spectroscopy is a powerful technique with which to access information on the bound states of exciton relative motion22, which has recently regained attention in carbon nanotubes38,39 and transition-metal dichalcogenide monolayers40,41. In the case of direct bandgap materials, the optical selection rules for two-photon absorption impose the excitation of $\\boldsymbol{p}$ -exciton states, thus providing an estimate of the $1s{-}2p$ energy splitting. The case for indirect bandgap compounds is less documented, with evidence for phonon-assisted two-photon absorption only in germanium42, to the best of our knowledge. \n\nFigure 3 presents (red circles) the two-photon excitation spectrum in hBN for detection at $5.86\\mathrm{eV}$ as a function of twice the excitation energy. The data are compared to the one-photon excitation spectrum (solid green line) from ref. 32. Below $6.02\\:\\mathrm{eV},$ the two-photon excitation does not create any carrier in the hBN sample. Beginning from $6.04~\\mathrm{eV}_{:}$ , there is an abrupt rise in the PLE signal intensity, which is at a maximum at $6.062\\mathrm{eV}$ and then decreases by one order of magnitude to an approximately constant value up to $7\\mathrm{eV}.$ . From a comparison of the one-photon and twophoton PLE spectra, we first conclude that there is a $60\\mathrm{meV}$ blueshift of the PLE maximum in the nonlinear measurements by twophoton spectroscopy. Moreover, we observe that the resonance in the two-photon PLE spectrum is very narrow, with a HWHM of only $10\\mathrm{meV}$ . This is half the value of the 5.76 and $5.86~\\mathrm{eV}$ emission lines, which consist of two phonon replicas (Fig. 2b), therefore suggesting the implication of a single phonon type in two-photon absorption. In fact, in the inset of Fig. 3 where we plot the twophoton PLE spectrum and the photoluminescence spectrum, for a same $115\\mathrm{meV}$ range but for increasing and decreasing energy, respectively, we observe that the resonance in the two-photon PLE spectrum is indeed the mirror image of a single phonon replica with the same abrupt rise followed by a smoother decrease as a function of energy (Supplementary Section C). \n\n![](images/0a7e0469898e0d62880fa5e789ad1d33a6c2f3a936fa72e9b4a0436f5c525e05.jpg) \nFigure 3 | Two-photon excitation spectroscopy in hBN. Normalized photoluminescence signal intensity at $5.76\\mathrm{eV}$ as a function of twice the excitation energy (red circles) for two-photon spectroscopy, and as a function of the excitation energy (solid green line) for one-photon spectroscopy (from ref. 32), at $1011.$ Inset: superposition of the two-photon excitation spectrum and photoluminescence spectrum for the same 115 meV range, but for increasing and decreasing energy, respectively. In contrast to phonon-assisted recombination, only one phonon mode is involved in the two-photon excitation spectrum. Scheme of two-photon excitation of the $2p_{z}$ exciton state assisted by emission of a ZA phonon. \n\nWe thus conclude that two-photon excitation is assisted by a single phonon mode in hBN. This situation contrasts with the optical response in emission, where four phonon modes (TA, LA, TO and LO) give rise to prominent replicas, the symmetry-forbidden ZA mode leading to a weak photoluminescence line. As shown in Supplementary Section B, the selection rules for phonon-assisted two-photon absorption indicate, on the contrary, that the ZA phonon mode is allowed, for excitation of the $2p_{z}$ exciton state, while the acoustic phonons of higher energy (TA and LA modes) contribute to the absorption of the $2p_{x,y}$ exciton states. Because the ZA mode corresponds to the phonon of lowest energy, we tentatively attribute the sharp line in the two-photon PLE spectrum as being assisted by a ZA phonon. Given the estimated value of $22\\pm1~\\mathrm{meV}$ for the ZA phonon energy (Fig. 2b), we obtain an energy splitting of $85\\pm1~\\mathrm{meV}$ between the 1s and $2p_{z}$ states of the indirect exciton $\\mathrm{iX}$ in hBN. This value is much smaller than the bandgap energy, and it shows that excitons in hBN are of the Wannier type, in contrast to theoretical calculations predicting Frenkel excitons7. \n\nUnder the assumption of the Rydberg series usually observed for Wannier excitons, such a splitting would lead to an exciton binding energy of $113\\mathrm{meV}$ in an isotropic material. However, because of the strong anisotropy of hBN, one has to correct this value in the framework of the theory developed for anisotropic excitons in semiconductors43,44. Depending on the value of the so-called anisotropy factor $\\gamma$ given by the ratio, for the in- and out-of-plane cases, of the dielectric constant times the effective mass, one finds a $1s\\mathrm{-}2p_{z}$ splitting ranging from 0.75 (for $\\gamma=1\\mathrm{\\AA}$ ) to 0.6 (for $\\gamma=0.1\\mathrm{\\dot{\\Omega}}$ ) in units of the excitonic Rydberg44, therefore giving an upper bound of $142~\\mathrm{meV}$ for the exciton binding energy in the limit of strong anisotropy $(\\gamma=0.1)$ . The mean value of $128\\pm15~\\mathrm{meV}$ is larger than the exciton binding energy in diamond $(70\\mathrm{meV})^{23}$ or AlN $(52~\\mathrm{meV})^{44}$ but still far from a Frenkel exciton. \n\nEventually, we estimate the single-particle bandgap of hBN at $6.08\\pm0.015\\mathrm{eV}.$ . This value indeed corresponds to the onset of the large absorption band in the one-photon PLE spectrum (Fig. 3). As a consequence, the $\\mathrm{X}_{\\mathrm{TO}}^{\\ast}$ and $\\mathrm{\\bar{X}_{L O}^{\\ast}}$ virtual states at 6.12 and $6.14\\:\\mathrm{eV}_{:}$ , respectively, are resonant with the continuum, thus preventing their observation in the one-photon PLE spectrum. It also explains a posteriori why the two-photon PLE spectrum displays only the ZA phonon mode, because the next expected one, corresponding to the TA mode, lies at $6.1\\mathrm{eV}_{:}$ , that is, already above the continuum onset. \n\nIn conclusion, we have resolved the long-debated issue of the bandgap nature of hBN by demonstrating that the bandgap is indirect with a value of $5.955\\ \\mathrm{eV}.$ We have shown that the emission spectrum of hBN in the deep ultraviolet is profoundly structured by phonon-assisted recombination, and we have identified the various phonon modes in the replicas. We have performed phonon-assisted two-photon absorption, from which we have derived an exciton binding energy of about $130\\mathrm{meV}_{:}$ , thus revealing that the indirect excitons in hBN are of the Wannier type and that the single-particle bandgap in hBN is about $6.08\\mathrm{eV}.$ . We highlight the need for theoretical calculations explaining the efficient exciton–phonon interaction in hBN. We hope our results will stimulate experiments addressing these questions, with the exciting possibility to study either the three-dimensional case in high-purity crystals or the two-dimensional one in hBN monolayers, where a transition to a direct bandgap is further expected, as in transition-metal dichalcogenide compounds. \n\n# Methods \n\nMethods and any associated references are available in the online version of the paper. \n\n# Received 3 June 2015; accepted 15 December 2015; published online 25 January 2016 \n\n# References \n\n1. Nanishi, Y. Nobel prize in physics: the birth of the blue LED. Nature Photon. 8, 884–886 (2014). \n2. Karnik, R. N. Materials science: breakthrough for protons. Nature 516, 173–175 (2014). \n3. Geim, A. K. & Grigorieva, I. V. Van der Waals heterostructures. Nature 499, 419–425 (2013). \n4. Xu, Y.-N. & Ching, W. Y. Calculation of ground-state and optical properties of boron nitrides in the hexagonal, cubic, and wurtzite structures. Phys. Rev. B 44, 7787–7798 (1991). \n5. Furthmüller, J., Hafner, J. & Kresse, G. Ab initio calculation of the structural and electronic properties of carbon and boron nitride using ultrasoft pseudopotentials. Phys. Rev. B 50, 15606–15622 (1994). \n6. Blase, X., Rubio, A., Louie, S. G. & Cohen, M. L. Quasiparticle band structure of bulk hexagonal boron nitride and related systems. Phys. Rev. B 51, 6868–6875 (1995). \n7. Arnaud, B., Lebègue, S., Rabiller, P. & Alouani, M. Huge excitonic effects in layered hexagonal boron nitride. Phys. Rev. Lett. 96, 026402 (2006). \n8. Gao, S.-P. Crystal structures and band gap characters of h-BN polytypes predicted by the dispersion corrected DFT and GW method. Solid State Commun. 152, 1817–1820 (2012). \n9. Watanabe, K., Taniguchi, T. & Kanda, H. Direct-bandgap properties and evidence for ultraviolet lasing of hexagonal boron nitride single crystal. Nature Mater. 3, 404–409 (2004). \n10. Zunger, A., Katzir, A. & Halperin, A. Optical properties of hexagonal boron nitride. Phys. Rev. B 13, 5560–5573 (1976). \n11. Evans, D. A. et al. Determination of the optical band-gap energy of cubic and hexagonal boron nitride using luminescence excitation spectroscopy. J. Phys. Condens. Matter 20, 075233 (2008). \n12. Watanabe, K., Taniguchi, T., Niiyama, T., Miya, K. & Taniguchi, M. Farultraviolet plane-emission handheld device based on hexagonal boron nitride. Nature Photon. 3, 591–594 (2009). \n13. Watanabe, K. & Taniguchi, T. Hexagonal boron nitride as a new ultraviolet luminescent material and its application. Int. J. Appl. Ceram. Technol. 8, 977–989 (2011). \n14. Jaffrennou, P. et al. Origin of the excitonic recombinations in hexagonal boron nitride by spatially resolved cathodoluminescence spectroscopy. J. Appl. Phys. 102, 116102 (2007). \n15. Watanabe, K. et al. Hexagonal boron nitride as a new ultraviolet luminescent material and its application—fluorescence properties of hBN single-crystal powder. Diam. Relat. Mater. 20, 849–852 (2011). \n16. Pierret, A. et al. Excitonic recombinations in h-BN: from bulk to exfoliated layers. Phys. Rev. B 89, 035414 (2014). \n17. Bourrellier, R. et al. Nanometric resolved luminescence in h-BN flakes: excitons and stacking order. ACS Photon. 1, 857–862 (2014). \n18. Silly, M. G. et al. Luminescence properties of hexagonal boron nitride: cathodoluminescence and photoluminescence spectroscopy measurements. Phys. Rev. B 75, 085205 (2007). \n19. Museur, L. & Kanaev, A. Near band-gap photoluminescence properties of hexagonal boron nitride. J. Appl. Phys. 103, 103520 (2008). \n20. Museur, L., Feldbach, E. & Kanaev, A. Defect-related photoluminescence of hexagonal boron nitride. Phys. Rev. B 78, 155204 (2008). \n21. Watanabe, K. & Taniguchi, T. Jahn–Teller effect on exciton states in hexagonal boron nitride single crystal. Phys. Rev. B 79, 193104 (2009). \n22. Bassani, F. & Pastori Parravicini, G. Electronic States and Optical Transitions in Solids (Pergamon, 1975). \n23. Martienssen, W. & Warlimont, H. (eds) Springer Handbook of Condensed Matter and Materials Data (Springer, 2005). \n24. Cho, K. et al. Excitons (Springer, 1979). \n25. Weisbuch, C. & Ulbrich, R. G. Spatial and spectral features of polariton fluorescence. J. Lumin. 18/19, 27–31 (1979). \n26. Snoke, D. W., Braun, D. & Cardona, M. Carrier thermalization in $\\mathrm{{Cu}_{2}\\mathrm{{O};}}$ : phonon emission by excitons. Phys. Rev. B 44, 2991 (1991). \n27. Umlauff, M. et al. Direct observation of free-exciton thermalization in quantumwell structures. Phys. Rev. B 57, 1390 (1998). \n28. Xu, S. J., Li, G. Q., Xiong, S. J. & Che, C. M. Temperature dependence of the LO phonon sidebands in the free exciton emission in GaN. J. Appl. Phys. 99, 073508 (2006). \n29. Griffin, A., Snoke, D. W. & Stringari, S. (eds) Bose–Einstein Condensation (Cambridge Univ. Press, 1995). \n30. Serrano, J. et al. Vibrational properties of hexagonal boron nitride: inelastic X-ray scattering and ab initio calculations. Phys. Rev. Lett. 98, 095503 (2007). \n31. Shtrichman, I. et al. Temporal evolution of the excitonic distribution function in GaAs/AlGaAs superlattices. Phys. Rev. B 65, 153302 (2002). \n32. Museur, L. et al. Exciton optical transitions in a hexagonal boron nitride single crystal. Phys. Status Solidi 5, 214–216 (2011). \n33. Jaffrennou, P. et al. Near-band-edge recombinations in multiwalled boron nitride nanotubes: cathodoluminescence and photoluminescence spectroscopy measurements. Phys. Rev. B 77, 235422 (2008). \n34. Reich, S. et al. Resonant Raman scattering in cubic and hexagonal boron nitride. Phys. Rev. B 71, 205201 (2005). \n35. Lui, C. H. & Heinz, T. F. Measurement of layer breathing mode vibrations in few-layer graphene. Phys. Rev. B 87, 121404 (2013). \n36. Tarrio, C. & Schnatterly, S. Interband transitions, plasmons, and dispersion in hexagonal boron nitride. Phys. Rev. B 40, 7852–7859 (1989). \n37. Arenal, R. et al. Electron energy loss spectroscopy measurement of the optical gaps on individual boron nitride single-walled and multiwalled nanotubes. Phys. Rev. Lett. 95, 127601 (2005). \n38. Wang, F., Dukovic, G., Brus, L. E. & Heinz, T. F. The optical resonances in carbon nanotubes arise from excitons. Science 308, 838–841 (2005). \n39. Maultzsch, J. et al. Exciton binding energies in carbon nanotubes from two-photon photoluminescence. Phys. Rev. B 72, 241402 (2005). \n40. Ye, Z. et al. Probing excitonic dark states in single-layer tungsten disulphide. Nature 513, 214–218 (2014). \n41. Wang, G. et al. Giant enhancement of the optical second-harmonic emission of $\\mathrm{WSe}_{2}$ monolayers by laser excitation at exciton resonances. Phys. Rev. Lett. 114, 097403 (2015). \n42. Tuncel, E. et al. Free-electron laser studies of direct and indirect two-photon absorption in germanium. Phys. Rev. Lett. 70, 4146–4149 (1993). \n43. Baldereschi, A. & Diaz, M. G. Anisotropy of excitons in semiconductors. Nuovo Cimento B 68, 217–229 (1970). \n44. Gil, B., Felbacq, D., Guizal, B. & Bouchitté, G. Excitonic states and their wave functions in anisotropic materials: a computation using the finite-element method and its application to AlN. Phys. Status Solidi B 249, 455–458 (2012). \n\n# Acknowledgements \n\nThe authors thank C. L’Henoret, D. Rosales and M. Moret for technical support, L. Tizei, O. Stephan, A. Zobelli, M. Kociak, L. Schue, J. Barjon, A. Loiseau and F. Ducastelle for discussions. This work was financially supported by the network GaNeX (ANR-11-LABX-0014). GaNeX belongs to the publicly funded Investissements d’Avenir programme managed by the French ANR agency. G.C. is a member of the ‘Institut Universitaire de France’. \n\n# Author contributions \n\nAll authors conceived and designed the experiments, which were carried out by G.C. and P.V. The data were analysed by all authors. The interpretation and writing of the manuscript were performed by G.C. and B.G. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to B.G. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. \n\n# Methods \n\nSample and experimental setup. The sample was a commercial hBN crystal from HQ Graphene (http://www.hqgraphene.com/). In the experimental setup, the sample was held on the cold finger of a closed-circle cryostat for temperaturedependent measurements from $10\\mathrm{K}$ to room temperature. Optical excitation was performed at normal incidence. In the standard configuration of one-photon excitation, the excitation beam was provided by the fourth harmonic of a continuous-wave mode-locked Ti:sapphire oscillator with a repetition rate of $82\\mathrm{MHz}$ , and in the case of two-photon excitation by the second harmonic of the Ti:sapphire oscillator. The spot diameter was on the order of $200\\ \\upmu\\mathrm{m},$ with a power of $20\\upmu\\mathrm{W}$ in one-photon excitation and $2.5\\mathrm{mW}$ in two-photon excitation spectroscopy, except for Fig. 2c, where the power was decreased by a factor of 10. An achromatic optical system coupled the emitted signal to the detection system, and was composed of an $f{=}500~\\mathrm{mm}$ Czerny–Turner monochromator, equipped with a 300 grooves/mm grating blazed at $250\\mathrm{nm}$ and a back-illuminated charge-coupled device camera (Andor Newton 920), with a quantum efficiency of $50\\%$ at $210\\mathrm{nm}.$ , operating over integration times of $1\\mathrm{min}$ . For two-photon spectroscopy, we used a band-pass filter around $200\\mathrm{nm}$ with low transmission at $400\\ \\mathrm{nm}$ in front of the spectrometer for complete laser stray light rejection. " + }, + { + "id": "10.1038_NENERGY.2016.126", + "DOI": "10.1038/NENERGY.2016.126", + "DOI Link": "http://dx.doi.org/10.1038/NENERGY.2016.126", + "Relative Dir Path": "mds/10.1038_NENERGY.2016.126", + "Article Title": "Steam generation under one sun enabled by a floating structure with thermal concentration", + "Authors": "Ni, G; Li, G; Boriskina, SV; Li, HX; Yang, WL; Zhang, TJ; Chen, G", + "Source Title": "NATURE ENERGY", + "Abstract": "Harvesting solar energy as heat has many applications, such as power generation, residential water heating, desalination, distillation and wastewater treatment. However, the solar flux is diffuse, and often requires optical concentration, a costly component, to generate the high temperatures needed for some of these applications. Here we demonstrate a floating solar receiver capable of generating 100 degrees C steam under ambient air conditions without optical concentration. The high temperatures are achieved by using thermal concentration and heat localization, which reduce the convective, conductive and radiative heat losses. This demonstration of a low-cost and scalable solar vapour generator holds the promise of significantly expanding the application domain and reducing the cost of solar thermal systems.", + "Times Cited, WoS Core": 986, + "Times Cited, All Databases": 1037, + "Publication Year": 2016, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000394184700001", + "Markdown": "# Steam generation under one sun enabled by a floating structure with thermal concentration \n\nGeorge Ni1, Gabriel Li1, Svetlana V. Boriskina1, Hongxia Li2, Weilin Yang2, TieJun Zhang2 and Gang Chen1\\* \n\nHarvesting solar energy as heat has many applications, such as power generation, residential water heating, desalination, distillation and wastewater treatment. However, the solar flux is difuse, and often requires optical concentration, a costly component, to generate the high temperatures needed for some of these applications. Here we demonstrate a floating solar receiver capable of generating $100^{\\circ}C$ steam under ambient air conditions without optical concentration. The high temperatures are achieved by using thermal concentration and heat localization, which reduce the convective, conductive and radiative heat losses. This demonstration of a low-cost and scalable solar vapour generator holds the promise of significantly expanding the application domain and reducing the cost of solar thermal systems. \n\nhe sun is a promising and abundant source of renewable energy that can potentially solve many of society’s challenges. Solar thermal technologies, that is, the conversion of the sunlight to thermal energy, are being developed for many applications, such as power generation, domestic water heating, desalination, and other industrial processes1–7. Steam and vapour generation is often desired in these applications, but the dilute solar flux $(1,000\\mathrm{W}\\mathrm{m}^{-2},$ ) does not provide enough power per unit area of the absorber to reach the required high temperatures and to compensate for the large latent heat of water vaporization. Optical concentrators, such as parabolic troughs, heliostats and lenses, can concentrate the ambient solar flux tens or even thousands of times to achieve high temperatures8–12. Plasmonic nanoparticles with absorption and scattering cross-sections exceeding their geometrical cross-sections have been recently developed and applied for direct solar steam generation13–24, but they typically require optical concentration of $10{-}1,000\\times$ for steam generation However, optical concentrators are expensive $(\\mathrm{US}\\$200\\mathrm{m}^{-2})^{25}$ , often accounting for a major portion of the capital cost of solar thermal systems8,11,26. In addition, they require support structures and access to electrical energy to track the sun. Although optical concentration is at present necessary for applications that require high temperatures, such as concentrated solar power generation, solar thermal technologies that reduce or completely eliminate the reliance on optical concentration would have better market penetration. Worldwide, the use of non-concentrated solar thermal power $(\\sim200\\mathrm{GW})^{27}$ outnumbers the use of concentrated solar thermal power $({\\sim}5\\mathrm{GW})$ . \n\nWe recently demonstrated solar steam generation under low $(\\leq10\\times)$ optical concentration using a floating graphite-based two-layer solar absorber28. This structure localized the solar heat generation to the evaporation surface of a body of water, instead of wastefully heating the entire body of water. The structure’s top layer absorbed the solar flux, while the bottom layer limited conduction of the generated heat to the underlying body of water. This resulted in very high steam generation efficiencies of up to $85\\%$ . However, to reach $100^{\\circ}\\mathrm{C}$ for steam generation, a solar flux of $10\\ensuremath{\\mathrm{kW}_{\\mathrm{m}}}^{-2}$ , 10 times the normal sun $(1,000\\mathrm{W}\\mathrm{m}^{-2}\\cdot$ ), was needed by optical concentration. Several other groups have looked into the role of surface chemistry in aiding water delivery and thermal insulation of the bottom layer20, incorporating plasmonic or carbon-based absorption layers29–33, a nd using other cheap and abundant materials34,35. These studies have achieved relatively high evaporation efficiencies, but relied on optical concentration to boost the evaporation temperatures and achieve such efficiencies. For example, Ito et al.29 used a concentration of $9\\times$ to achieve steam generation. To reach the boiling point without optical concentration, solar receivers must be designed to suppress parasitic heat losses from the absorber surface. \n\nHere, we demonstrate water boiling and steam generation under unconcentrated ambient solar flux in a receiver open to the ambient. The receiver is constructed of a variety of low-cost and commercially available materials, utilizing a combination of spectral selectivity of the solar absorber, thermal insulation, and in-plane thermal concentration. By varying the thermal concentration, the receiver can generate saturated steam at $100^{\\circ}\\mathrm{C},$ or low-temperature vapour at high efficiencies $(64\\%)$ . The ability to boil water under ambient sunlight holds promise for significant cost reduction of existing solar thermal systems while opening up new applications such as desalination, wastewater treatment, and sterilization. \n\n# Generating high-temperature vapour with low solar flux \n\nAchieving steam generation using the ambient solar flux $(1,000\\mathrm{W}\\mathrm{\\bar{m}}^{-2},$ ), or one sun, requires significant reduction of the heat losses from the receiver. Figure 1a shows the heat transfer processes involved in a floating solar steam generator, including radiative and convective heat loss to the ambient and conductive and radiative heat loss to the underlying water. The net evaporation rate $\\dot{m}$ can be expressed as \n\n$$\n\\dot{m}h_{\\mathrm{fg}}=A\\alpha q_{\\mathrm{solar}}-A\\varepsilon\\sigma\\left(T^{4}-T_{\\infty}^{4}\\right)-A h\\left(T-T_{\\infty}\\right)-A q_{\\mathrm{water}}\n$$ \n\nwhere $h_{\\mathrm{fg}}$ is the latent heat, $A$ the surface area of the absorber facing the sun, $\\alpha$ the solar absorptance, $q_{\\mathrm{solar}}$ the solar flux, $\\varepsilon$ the emittance of the absorbing surface, $\\sigma$ the Stefan–Boltzmann constant, $h$ the convection heat transfer coefficient, and $q_{\\mathrm{water}}$ the heat flux to the underlying water, including conduction and radiation. Assuming a blackbody absorber with ${\\mathrm{~\\bar{\\calT}~}}=100^{\\circ}{\\mathrm{C}},$ the minimum temperature needed for boiling water at ambient conditions, and $T_{\\infty}=20^{\\circ}\\mathrm{C},$ the radiative heat loss to the ambient is $680\\mathrm{W}\\mathrm{m}^{-2}$ . Taking a natural convection heat transfer coefficient of $10\\mathrm{W}\\mathrm{m}^{-2}\\mathrm{K},$ the convective heat loss is $800\\mathrm{W}\\mathrm{m}^{-2}$ . These two loss channels alone exceed the incoming solar flux of $1,000\\mathrm{W}\\mathrm{m}^{-2}$ , and there is additional heat loss to the underlying water by conduction and radiation. \n\n![](images/65e792b564a0c1378bf6c268b6da093bf7a18edc23877286222800f7a4d777de.jpg) \nFigure 1 | Operating principles of steam generation at one sun. a, Energy balance and heat transfer diagram for a blackbody solar receiver operating at $100^{\\circ}\\mathsf{C}$ . The 1,000 W $\\mathsf{m}^{-2}$ delivered by the ambient solar flux is not enough to sustain the heat losses, and a $100^{\\circ}\\mathsf{C}$ equilibrium temperature cannot be reached. b, Energy balance and heat transfer in the developed one-sun, ambient steam generator (OAS). c, A photograph of the OAS composed of a commercial spectrally selective coating on copper to suppress radiative losses and to thermally concentrate heat to the evaporation region. The bubble wrap cover transmits sunlight, and minimizes convective losses. Slots are cut in the bubble wrap to allow steam to escape. Thermal foam insulates the hot selective absorber from the cool underlying water, and floats the entire structure. The inset compares thermal radiative losses at $100^{\\circ}\\mathsf{C}$ from a blackbody and the spectrally selective absorber. \n\nThe large mismatch between water’s latent heat of vaporization $h_{\\mathrm{fg}}$ $(2.26\\mathrm{\\check{M}J}\\mathrm{kg}^{-1}$ at $100^{\\circ}\\mathrm{C})$ and the ambient solar flux imposes another challenge. Even without any parasitic energy losses, the maximum mass flux generated by the ambient solar flux is $\\dot{m}/A{=}q_{\\mathrm{solar}}/h_{\\mathrm{fg}}{=}4.4\\times10^{-4}\\mathrm{kg}\\mathrm{m}^{-2}\\mathrm{s}$ , according to equation (1). Our past studies28 have shown that the mass evaporation rate of water at $100^{\\circ}\\mathrm{C}$ can be an order of magnitude higher (up to $4.3\\times10^{-3}\\mathrm{kg}\\mathrm{m}^{-2}\\:s$ ). \n\nFigure 1b shows several strategies we used to overcome the above challenges to achieve continuous steam generation under one sun and even lower solar flux as shown later. First, we replace the blackbody absorber with a spectrally selective absorber, which has high solar absorptance $\\alpha$ and low thermal emittance $\\varepsilon$ (Fig. 1c). Spectrally selective absorbers strongly absorb sunlight, but emit very little radiative heat. They are already widely used in domestic solar hot water systems36,37, and allow evacuated solar hot water tubes to be heated to over $100^{\\circ}\\mathrm{C}$ under stagnation conditions38. However, these solar hot water heating systems are not designed for steam generation or evaporation from open bodies of water. Second, we use thermal insulation on both top and bottom surfaces of the absorber to reduce convective loss to air as well as conductive and radiative heat losses to the water underneath. Finally, to overcome the mismatch between the latent heat of vaporization and the ambient solar flux, we use thermal concentration, by conducting the absorbed heat into the evaporation area, which is smaller than the absorber surface area. \n\n# One-sun, ambient steam generator \n\nFigure 2 shows the lab-scale one-sun, ambient steam generator (OAS), which contains three main components. First, a spectrally selective solar absorber is used, consisting of a cermet (BlueTec eta plus) coated on a copper sheet. Second, a thermal insulator was constructed from a polystyrene foam disk. Last, a convective cover was made from a sheet of large transparent bubble wrap. We use a variety of low-cost commercial materials to construct the solar receiver, and we believe even cheaper materials can be substituted for intended applications, as discussed later; one example is using alternative selective coatings. \n\nThe spectrally selective absorber (Fig. 2a) solar absorptance 0 ${\\overset{\\prime}{\\alpha}}=0.93{\\overset{\\cdot}{3}}$ ) and emittance at $100^{\\circ}\\mathrm{C}$ ${\\mathit{\\check{\\varepsilon}}}_{\\varepsilon}=0.07{\\mathit{\\check{\\varepsilon}}}_{\\mathrm{.}}$ ) were both measured and are shown in the Supplementary Methods. The polystyrene foam shown in Fig. 2b,c serves to float the entire structure on a body of water, and is a thermal insulator $(k=\\sim0.03\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K})$ ). A channel was drilled through the foam, and a hydrophilic cotton wick threaded through. This wick used capillary forces to deliver water to the absorber. A sheet of cotton fabric (Fig. 2b) was placed above the wick on the foam to increase the evaporative area. Figure 2d shows an evaporation slot cut into a $10\\mathrm{cm}$ diameter selective absorber, to allow for water vapour to escape. The slot was varied in length ( $1\\mathrm{mm}$ width) to control the operating temperature of the receiver. For smaller thermal concentrations, 2–3 slots were made in a concentrated cluster $(\\sim5-10\\mathrm{mm}$ separation). \n\n![](images/112a3f5d49c4dc52cc4cb2948413ec3b535c873d24fccb8d865230c12183529f.jpg) \nFigure 2 | One-sun, ambient steam generator. a, The selective absorber consists of a commercially available cermet-coated copper substrate. b, The insulation foam serves to float the entire structure on a body of water, and limits the thermal conduction and radiation to the cool water underneath. The dark fabric in the centre hides a fabric wick, which tunnels through the foam to the underlying water. The fabric draws water through the foam. The clear container surrounding the foam holds water, and has a cap to prevent extraneous evaporation. c, The three layers of the OAS, from top to bottom: bubble wrap, selective absorber and thermally insulating foam. d, The evaporation slot, which reveals the dark fabric underneath. The fabric serves to deliver water, but also increases the evaporation area. The inset shows where the evaporation slot is cut. \n\nA sheet of transparent bubble wrap (Fig. 2c) was placed on top of the selective absorber to minimize the convective losses. The solar transmittance $\\tau_{\\mathrm{bubble}}$ of the bubble wrap was measured to be $80\\%$ . Though the bubble wrap reduces the solar power transmitted and absorbed by the absorber surface, it also reduces the convective heat losses. The result is a net improvement in the OAS performance. \n\n# Laboratory experiments \n\nThe lab-scale OAS performance was first characterized in a laboratory environment (Supplementary Methods). A solar simulator was used to supply solar flux $(1,000\\mathrm{W}\\mathrm{m}^{-2}),$ , and a balance was used to measure the real-time mass loss of the receiver and water supply. The selective absorber temperature and vapour temperature were measured (Fig. 3a) as a function of the thermal concentration $C_{\\mathrm{therm}}$ , the ratio of the total illumination area to the evaporation area. The vapour temperature closely tracks the selective absorber temperature. The maximum steam temperature reached was $98^{\\circ}\\mathrm{C}$ (Fig. 3b), achieved when ${\\sim}0.1\\%$ of the surface is devoted to evaporation $\\prime C_{\\mathrm{therm}}=1,300\\times\\rangle$ . The steam temperature was directly measured by the thermocouple in this case, using a small vapour chamber. The kink near $t=300s$ clearly indicates boiling limiting further temperature rise of the solar receiver, despite the measured vapour temperature not exactly reaching $100^{\\circ}\\mathrm{C}$ due to the rapid cooling of vapour. Figure 3c shows the mass change as a function of time while generating $80^{\\circ}\\mathrm{C}$ vapour. These figures show the receiver reached steady-state operation in roughly $5\\mathrm{{min}}$ , clearly demonstrating continuous steam generation under 1 sun illumination. \n\nThe solar vapour generation efficiency was defined as a ratio of enthalpy change in the generated vapour divided by the total incoming solar flux: \n\n$$\n\\eta_{\\mathrm{thermal}}=\\frac{\\dot{m}h_{\\mathrm{fg}}}{q_{\\mathrm{solar}}A}\n$$ \n\nwhere $\\dot{m}$ is the instantaneous mass change due to evaporation, $h_{\\mathrm{fg}}$ is the enthalpy change of liquid water to vapour, $q_{\\mathrm{solar}}$ is the solar flux per area, and $A$ is the total area of the receiver. Figure 3d shows the receiver efficiencies at different operating temperatures. The lines in Fig. 3d were obtained by using a heat transfer model of the OAS, which is discussed below. \n\n# Generating steam outdoors \n\nAn outdoor experiment using natural sunlight validated the ability of the OAS to generate steam in real conditions, where factors such as varying incident solar flux and wind can greatly hinder receiver performance. The OAS was placed on the roof of MIT, at noontime for all experiments. Thermocouples were used to measure the selective absorber temperature, and a thermal pyranometer used to measure the incident solar flux on a horizontal surface, known as the global horizontal irradiance. Figure 4 shows the selective absorber temperatures and solar fluxes during the two experimental runs (6 August and 17 September 2015). Based on the lab data, when the selective absorber reaches $100^{\\circ}\\mathrm{C},$ steam is generated. \n\nFigure 4a shows a measurement on a sunny day with roaming cloud cover, which caused the solar flux to vary dramatically $(\\sim200-1,000\\mathrm{W}\\mathrm{m}^{-2})$ . The temperature measurements show that the selective absorber is capable of recovering its peak operating temperature $(>95^{\\circ}\\mathrm{C})$ within minutes. Figure 4b shows a situation where the sun is more constant, but at a lower position in the sky due to seasonal variation. This lower sky position reduces the amount of solar flux incident on a horizontal surface $(\\sim750\\mathrm{W}\\mathrm{m}^{-2}.$ ). These experiments demonstrate the ability of the solar receiver to rapidly reach $100^{\\circ}\\mathrm{C}$ temperatures during periods of low and varying solar flux, such as during non-summer months and cloudy days. \n\n# Modelling \n\nWe carried out modelling to gain insights into the present experiment and future performance (Supplementary Notes 1). A key requirement for efficient thermal concentration is limiting the temperature drop along the surface of the selective absorber. A large temperature drop reduces efficiency, and indicates significant heat loss compared to the heat conduction to the evaporation region. We used a simple fin model to justify that the temperature throughout the selective absorber is nearly uniform, consistent with our measurements. We incorporate this isothermal assumption into the isothermal model. We also carried out COMSOL simulations to determine the sidewall losses in the lab-scale experimental OAS. The results are plotted in Fig. 3d. \n\nThe isothermal model is used to predict the achievable performance of a large-scale OAS where the side wall heat loss is negligible. Such a large-scale OAS is expected to have repeating patterns of evaporation slots, thus maintaining the isothermal absorber. Figure 5a shows the achievable vapour temperatures and efficiencies predicted while under $1,000\\bar{\\mathsf{W}}\\mathsf{m}^{-2}$ illumination. The maximum temperature reached was $100^{\\circ}\\mathrm{C}$ with a thermal concentration around $200\\times$ . The thermal concentration required to generate steam is higher than the optical concentration reported in previous experiments28,29, but is significantly easier to implement. Higher thermal concentration yielded lower evaporation efficiency, due to reduced evaporation area. However, once the steam generation temperature has been reached $(100^{\\circ}\\mathrm{C})$ , increasing thermal concentration does not change the efficiency much, due to phase change limiting any further temperature rise. Theoretically, superheating may occur at higher thermal concentrations, leading to increased heat losses and lower efficiency. These scenarios are not included in the model, as they are not observed in the thermal concentrations tested in this study. At low thermal concentration with large evaporation area, the efficiency of the system is higher, but the vapour temperature generated is low due to the higher evaporation rates. Based on the results of our modelling, two useful receiver configurations were identified: one for hightemperature $(100^{\\circ}\\mathrm{C})$ vapour generation, and another for highefficiency evaporation $(C_{\\mathrm{therm}}=1\\times\\dot{}$ ). \n\n![](images/279b137c93e554c5a0b976ee4dac75117448221e9aee8a05a35adc8c3f065ff2.jpg) \nFigure 3 | Vapour generation experimental results. a, Steady-state vapour and selective absorber temperatures measured as a function of the thermal concentration used. The evaporation slots were varied in size to control the operating temperature. b, Vapour and selective absorber temperatures versus time at a thermal concentration of $1,300\\times$ . The vapour temperature was directly measured with a small vapour chamber that was placed over the evaporation area. The kink in temperature rise is due to phase change. c, Mass change over time, when the produced vapour temperature is $80^{\\circ}\\mathsf{C}$ The OAS quickly reaches a steady-state condition. d, Efciency of the receiver versus thermal concentration. The dots are measurements, and the lines are computed by using the OAS heat transfer model (Supplementary Notes 1). \n\nFigure 5b shows the predicted performance of the OAS at different solar fluxes (obtained by using the model in Supplementary Notes 1, coefficients in Supplementary Notes 2) at $C_{\\mathrm{therm}}=1\\times$ and $C_{\\mathrm{therm}}=1{,}000\\times$ . This illustrates the ability of the OAS to generate steam throughout the day, when the sun is at different positions in the sky. The temperature plateau indicates phase change limiting the temperature rise of the OAS, consistent with measurements. Figure 5c shows a sensitivity analysis of the maximum operating temperature of the OAS to the transmittance of the bubble wrap and absorptance of the selective surface $(\\tau_{\\mathrm{{bubble}}}\\alpha)$ . The thermal concentration was set to $1{,}000\\times$ . The receiver can generate steam with $\\tau_{\\mathrm{bubble}}\\alpha>\\sim0.4.$ with increasing efficiency at higher $\\tau_{\\mathrm{bubble}}\\alpha$ . At lower $\\tau_{\\mathrm{{bubble}}}\\alpha$ the receiver is generating vapour via evaporation. Figure 5d shows sensitivity of the maximum operating temperature to the receiver emittance. It reveals that the OAS can generate steam even if the selective solar absorber has significantly poorer optical properties than the one used in our system. This suggests that the most expensive component, the selective absorber, can be made more cheaply than what was used in this paper. \n\n# Discussion \n\nAnother area for optimization of the receiver is the evaporation slot design. Understanding the dominating resistances in the evaporation process can give us key insights into how to improve the design. Using Schrage’s model39, an upper limit for evaporative heat transfer coefficient is estimated to be on the order of $\\mathrm{\\bar{10^{7}W}m}^{-2}\\mathrm{K}$ (Supplementary Notes 7). This is five orders of magnitude higher than the coefficients measured in this work $(\\therefore500\\mathrm{W}\\mathrm{m}^{-2}\\mathrm{K},$ Supplementary Notes 2). This suggests that the overall evaporation rate is limited by vapour diffusion through air, not vapour formation at the liquid-air interface. In support of this conclusion, the evaporation heat transfer coefficient increased ${\\sim}10\\times$ over those in a previous work28, probably due to the difference in the system geometry. The system in ref. 26 had an evaporation surface with a large planar area, resulting in one-dimensional (1D) vapour diffusion away from the liquid. In contrast, OAS evaporation areas are better approximated by lines, enabling 2D vapour diffusion, and resulting in larger evaporation heat transfer coefficients. Additional evaporation experiments were conducted to determine the size effect of evaporation areas. Smaller circular evaporation areas improved the per area evaporation rate dramatically, up to $10\\times$ increase for a $36\\times$ reduction in area (Supplementary Notes 7). Further analysis using COMSOL determined that closely space evaporation areas improved efficiency (Supplementary Notes 4). \n\n![](images/0acc3fb4fafa62cdd0e1694fc128d5b48e23767ce693c502a78d8a9431118f3c.jpg) \nFigure 4 | Outdoor performance under natural sunlight. Temperature measurements of the OAS in outdoor conditions on two separate dates: 6 August 2015 (a) and 17 September 2015 (b). Panel a demonstrates the ability of the OAS to rapidly reach peak operating temperature on cloudy days, whereas panel b demonstrates its ability to generate steam during low solar flux days (non-summer seasons). For each experiment, the thermal concentration was $1,000\\times$ . \n\n![](images/434b8d6b3b7e1715f2b3c52a08687684dec5177dfe59ce9106fbc74e2eab01df.jpg) \nFigure 5 | Analysis of a large-scale OAS performance. a, The achievable performance of the receiver using an isothermal absorber approximation (see Supplementary Notes 1). Unless otherwise stated, the OAS optical properties were $\\varepsilon=0.07,$ , $\\alpha=0.93$ and $\\tau_{\\sf b u b b l e}=0.8$ . The solar flux is $1,000\\mathsf{W}\\mathsf{m}^{-2}$ and the thermal concentration $1,000\\times$ . The open data points indicate the measured performance of a high-efciency version of the OAS with distributed holes. The lines represent the predicted achievable performance of a large OAS with negligible side losses. b, Performance at various solar fluxes for low and high thermal concentrations. c, Sensitivity of efciency and maximum temperature to the product of bubble wrap transmittance and selective surface absorptance. Thermal concentration is $1,000\\times$ . d, Sensitivity of the receiver to emittance $\\varepsilon$ , which afects radiative losses. Transmittance and absorptance have a larger efect on efciency than emittance. Absorbers with significantly poorer optical properties than our selective surface can be used to generate steam, suggesting cheaper material substitutions in future designs. \n\nEven though the present single slot configuration has a higher mass transfer coefficient than ref. 26, the mass flux is much smaller due to reduced area of evaporation. One way to improve evaporation efficiency is to distribute numerous smaller circular slots for 3D vapour diffusion, while preserving the thermal concentration ratio for the overall area. This strategy maximizes the volume of air for vapour diffusion per distributed circular slot, enhancing the overall evaporation rate. Two additional OAS were created utilizing distributed circular slots, and generated low-temperature vapour at much higher efficiencies (Fig. 5a). The highest efficiency reached was $71\\%$ at $12\\times$ thermal concentration $64\\%$ after subtracting the evaporation under dark conditions). The effective evaporation heat transfer coefficient for the total receiver area was higher than in ref. 26 $29\\mathrm{W}\\mathrm{m}^{-2}\\mathrm{K}$ versus $25\\mathrm{W}\\mathrm{m}^{-2}\\mathrm{K},$ , and the OAS achieved this with much smaller actual evaporation areas. \n\nDemonstration of continuous direct steam generation under the one-sun condition opens many potential applications, such as distillation and sterilization in remote locations. By pressurizing the system, one can potentially use the approach to generate superheated steam—for power conversion using water or other organic working fluids. The floating structure also has potential for solar desalination when the generated vapour is collected. Solar stills have been used for thousands of years, but have remained underutilized due to their low-efficiency $(30-45\\%)$ and relatively high cost40–42. The basic design of the solar still uses a blackbottomed water basin to absorb the incoming solar flux. In such a configuration, radiative losses from the hot water are the largest source of losses, and cannot be avoided. Our approach significantly reduces the radiative loss, as well as the convective losses. There are several examples of floating solar stills in the literature43,44, but these are simply basic single-effect solar stills made to float on the ocean. Hence, the cost and efficiency are expected to be similar or worse than conventional solar stills. The OAS can achieve higher efficiencies than an uncovered solar still using alternative receivers45. Furthermore, when placed in a solar still, the OAS efficiency can be higher, due to better insulation from the environment. In addition, the floating structure will enable direct deployment on water surfaces, such as over a bay, hence reducing system complexity and cost. \n\nWe have shown that thermal concentration can be a more cost-effective approach to solar steam generation than optical concentration. The OAS is estimated to cost ${\\sim}\\mathrm{US}\\$6\\mathrm{m}^{-2}$ , based on available bulk pricing of materials, and we expect the cost can be reduced down to ${\\sim}\\mathrm{US}\\$2\\mathrm{m}^{-2}$ . The manufacturing processes for final product are expected to be roll-to-roll, and should be of low cost. The cost of tracking optical concentrators can be as high as $\\mathrm{US}\\$200\\mathrm{m}^{-2}$ , and much of the prior literature on solar vapour generation has not included the optical losses due to inefficient concentration of the full solar flux, both diffuse and direct. Taking these details into account, the OAS can generate steam at ${\\sim}5\\%$ the cost of optically concentrating approaches (Supplementary Notes 5). \n\nFurther study in fouling of the OAS is needed, though the decoupling of the optical absorber from the phase change surface is an advantage. The cotton wick is a small fraction of the solar absorber, and its fouling will not affect the solar absorption. Accumulated salt may be sufficiently rejected overnight if used in an ocean. The wick is also easy to replace, being a small component. Overall, the ability of the OAS to generate high-temperature steam without relying on bulky and costly concentrating optics opens up many new possibilities for solar thermal energy harvesting. \n\n# Methods \n\nThe selective absorber’s solar absorptance was measured using an ultraviolet–visible spectrophotometer (Agilent Cary 5000) with an included integrating sphere, and the emittance was measured using a Fourier transform infrared (FTIR) spectrometer (Thermo Nicolet 5700) with a Pike Technologies mid-IR integrating sphere. \n\nThe receiver performance experiments were conducted in the lab using a solar simulator (ScienceTech, SS-1.6K) outputting simulated solar flux at $1\\mathrm{kW}\\mathrm{m}^{-2}$ (1 sun). The solar flux intensity was measured using a thermopile (Newport, 818P-001-12) connected to a power meter (Newport, 1918-C). Because the solar flux varies with the beam spot location, and the thermopile detector is smaller in area than the solar receiver, the maximum-recorded solar flux is regarded as the actual constant solar flux for the efficiency measurements. This under-reports the vapour generation efficiency up to $5\\%$ , based on the actual variation observed in solar flux. A $10\\mathrm{cm}$ aperture is used to minimize the amount of extraneous solar flux striking the receiver. The mass of the water loss is measured using a lab balance with $1\\mathrm{mg}$ resolution (A&D, FX300i), and calibrated to weights higher than the solar receiver. Before illuminating the solar receiver, the evaporation in dark conditions was measured for $10\\mathrm{min}$ . The dark-evaporation rate was subtracted from the solar-illuminated evaporation rate, which was measured for $30\\mathrm{min}$ at steady-state conditions. \n\nThe evaporation mass loss of the receiver under dark conditions was measured, and subtracted from the measured mass loss under solar illumination. Due to a low mass flux, the produced vapour quickly mixes with the surrounding air and cools. The temperature of the produced vapour was measured by touching a thermocouple to the cotton evaporation surface. For measurement of the highest temperature, a vapour chamber was constructed to collect the generated steam. In this case, the thermocouple was suspended in air to directly measure the steam temperature. The selective absorber’s temperature was measured as well via a thermocouple attached under the copper substrate. \n\nThe rooftop measurements were conducted using the A&D FX300i balance to measure water loss, and a Hukseflux LP-02 thermal pyranometer to measure the intensity of the sun. Thermocouples (Omega Engineering, K-type, 40 gauge insulated) were used to measure the temperature of the selective absorber. \n\n# Received 10 February 2016; accepted 20 July 2016; published 22 August 2016 \n\n# References \n\n1. Dalvi, V. H., Panse, S. V. & Joshi, J. B. Solar thermal technologies as a bridge from fossil fuels to renewables. Nat. Clim. Change 5, 1007–1013 (2015). \n2. Shannon, M. A. et al. Science and technology for water purification in the coming decades. Nature 452, 301–310 (2008). \n3. Narayan, G. P. et al. The potential of solar-driven humidification-dehumidification desalination for small-scale decentralized water production. Renew. Sustain. Energy Rev. 14, 1187–1201 (2010). \n4. Elimelech, M. & Phillip, W. A. The future of seawater desalination: energy, technology, and the environment. Science 333, 712–717 (2011). \n5. Li, C., Goswami, Y. & Stefanakos, E. Solar assisted sea water desalination: a review. Renew. Sustain. Energy Rev. 19, 136–163 (2013). \n6. Tiwari, G. N., Singh, H. N. & Tripathi, R. Present status of solar distillation. Sol. Energy 75, 367–373 (2003). \n7. Phelan, P., Taylor, R., Adrian, R., Prasher, R. & Otanicar, T. Nanoparticle Heat Transfer Fluid Flow (CRC Press, 2012). \n8. Weinstein, L. A. et al. Concentrating solar power. Chem. Rev. 115, 12797–12838 (2015). \n9. Boriskina, S. V. et al. Roadmap on optical energy conversion. J. Opt. 18, 073004 (2016). \n10. Jenkins, D. et al. Solar concentration of 50,000 achieved with output power approaching 1 kW. J. Sol. Energy Eng. 118, 141–145 (1996). \n11. Reif, J. H. & Alhalabi, W. Solar-thermal powered desalination: its significant challenges and potential. Renew. Sustain. Energy Rev. 48, 152–165 (2015). \n12. Montes, M. J., Abánades, A. & Martínez-Val, J. M. Performance of a direct steam generation solar thermal power plant for electricity production as a function of the solar multiple. Sol. Energy 83, 679–689 (2009). \n13. Neumann, O. et al. Solar vapor generation enabled by nanoparticles. ACS Nano 7, 29–42 (2013). \n14. Neumann, O. et al. Nanoparticle-mediated, light-induced phase separations. Nano Lett. 15, 7880–7885 (2015). \n15. Neumann, O. et al. Compact solar autoclave based on steam generation using broadband light-harvesting nanoparticles. Proc. Natl Acad. Sci. USA 110, 11677–11681 (2013). \n16. Liu, Y. et al. A bioinspired, reusable, paper-based system for high-performance large-scale evaporation. Adv. Mater. 27, 2768–2774 (2015). \n17. Wang, Z. et al. Evaporation: bio-inspired evaporation through plasmonic film of nanoparticles at the air-water interface. Small 10, 3233–3233 (2014). \n18. Boriskina, S. V., Ghasemi, H. & Chen, G. Plasmonic materials for energy: from physics to applications. Mater. Today 16, 375–386 (2013). \n19. Tian, L. et al. Plasmonic biofoam: a versatile optically active material. Nano Lett. 16, 609–616 (2015). \n20. Yu, S. et al. The impact of surface chemistry on the performance of localized solar-driven evaporation system. Sci. Rep. 5, 13600 (2015). \n21. Baffou, G., Polleux, J., Rigneault, H. & Monneret, S. Super-heating and micro-bubble generation around plasmonic nanoparticles under cw illumination. J. Phys. Chem. C 118, 4890–4898 (2014). \n22. Baral, S., Green, A. J., Livshits, M. Y., Govorov, A. O. & Richardson, H. H. Comparison of vapor formation of water at the solid/water interface to colloidal solutions using optically excited gold nanostructures. ACS Nano 8, 1439–1448 (2014). \n23. Bae, K. et al. Flexible thin-film black gold membranes with ultrabroadband plasmonic nanofocusing for efficient solar vapour generation. Nat. Commun. 6, 10103 (2015). \n24. Zhao, D. et al. Enhancing localized evaporation through separated light absorbing centers and scattering centers. Sci. Rep. 5, 17276 (2015). \n25. Ernst & Young Inc. Assessment of the Local Manufacturing Potential for Concentrated Solar Power (CSP)Projects (The World Bank, 2011). \n26. Kolb, G. J., Ho, C. K., Mancini, T. R. & Gary, J. A. Power Tower Technology Roadmap and Cost Reduction Plan (Sandia National Labs, 2011). \n27. Weiss, W., Mauthner, F. & Spork-Dur, M. Solar Heat Worldwide (Solar Heating and Cooling Programme, International Energy Agency, 2012). \n28. Ghasemi, H. et al. Solar steam generation by heat localization. Nat. Commun. 5, 4449 (2014). \n29. Ito, Y. et al. Multifunctional porous graphene for high-efficiency steam generation by heat localization. Adv. Mater. 27, 4302–4307 (2015). \n30. Liu, Y., Chen, J., Guo, D., Cao, M. & Jiang, L. Floatable, self-cleaning, and carbon-black-based superhydrophobic gauze for the solar evaporation enhancement at the air–water interface. ACS Appl. Mater. Interface 7, 13645–13652 (2015). \n31. Ni, G. et al. Volumetric solar heating of nanofluids for direct vapor generation. Nano Energy 17, 290–301 (2015). \n32. Zhou, L. et al. 3D self-assembly of aluminium nanoparticles for plasmon-enhanced solar desalination. Nat. Photon. 10, 393–398 (2016). \n33. Zhou, L. et al. Self-assembly of highly efficient, broadband plasmonic absorbers for solar steam generation. Sci. Adv. 2, e1501227 (2016). \n34. Zeng, Y. et al. Solar evaporation enhancement using floating light-absorbing magnetic particles. Energy Environ. Sci. 4, 4074–4078 (2011). \n35. Zhang, L., Tang, B., Wu, J., Li, R. & Wang, P. Hydrophobic light-to-heat conversion membranes with self-healing ability for interfacial solar heating. Adv. Mater. 27, 4889–4894 (2015). \n36. Cao, F., McEnaney, K., Chen, G. & Ren, Z. A review of cermet-based spectrally selective solar absorbers. Energy Environ. Sci. 7, 1615–1627 (2014). \n37. Harding, G. L. & Zhiqiang, Y. Thermosiphon circulation in solar water heaters incorporating evacuated tubular collectors and a novel water-in-glass manifold. Sol. Energy 34, 13–18 (1985). \n38. Budihardjo, I. & Morrison, G. L. Performance of water-in-glass evacuated tube solar water heaters. Sol. Energy 83, 49–56 (2009). \n39. Schrage, R. W. Theoretical Study of Interphase Mass Transfer (Columbia Univ., 1953). \n40. Kabeel, A. E. & El-Agouz, S. A. Review of researches and developments on solar stills. Desalination 276, 1–12 (2011). \n41. Velmurugan, V. & Srithar, K. Performance analysis of solar stills based on various factors affecting the productivity: a review. Renew. Sustain. Energy Rev. 15, 1294–1304 (2011). \n42. Cooper, P. I. The maximum efficiency of single-effect solar stills. Sol. Energy 15, 205–217 (1973). \n43. Lighter, S. Floating solar still. US patent no. US2820744 A (1958). \n44. Miller, W. H. J. Inflatable floating solar still with capillary feed. US patent no. US2412466 A. (1946). \n45. Janarthanan, B., Chandrasekaran, J. & Kumar, S. Evaporative heat loss and heat transfer for open- and closed-cycle systems of a floating tilted wick solar still. Desalination 180, 291–305 (2005). \n\n# Acknowledgements \n\nWe thank D. Kraemer with help operating the solar simulator, and T. McClure and the Center for Materials Science and Engineering for the use of the FTIR. This work was partially supported by the Cooperative Agreement between the Masdar Institute of Science and Technology (Masdar Institute), Abu Dhabi, UAE and the Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, USA—Reference 02/MI/MIT/CP/11/07633/GEN/ $\\mathrm{\\DeltaG}/00$ (for the steam generation). We gratefully acknowledge funding support from the MIT S3TEC Center, an Energy Frontier Research Center funded by the Department of Energy, Office of Science, Basic Energy Sciences under Award $\\#$ DE-FG02-09ER46577 (for the experimental facility). We also thank Z. Lu and E. Wang for their help in understanding the evaporation processes. \n\n# Author contributions \n\nG.N., S.V.B. and G.C. developed the concept. G.N. and G.L. conducted the experiments. \nG.N., H.L., W.Y. and T.Z. prepared the models. G.N., S.V.B. and G.C. wrote the paper. \nG.C. directed the overall research. \n\n# Additional information \n\nSupplementary information is available for this paper. Reprints and permissions information is available at www.nature.com/reprints. Correspondence and requests for materials should be addressed to G.C. \n\n# Competing interests \n\nThe authors have applied for a patent for this technology, but have no other competing interests. " + }, + { + "id": "10.1021_acs.chemmater.6b00602", + "DOI": "10.1021/acs.chemmater.6b00602", + "DOI Link": "http://dx.doi.org/10.1021/acs.chemmater.6b00602", + "Relative Dir Path": "mds/10.1021_acs.chemmater.6b00602", + "Article Title": "Defect Engineering: Tuning the Porosity and Composition of the Metal-Organic Framework UiO-66 via Modulated Synthesis", + "Authors": "Shearer, GC; Chavan, S; Bordiga, S; Svelle, S; Olsbye, U; Lillerud, KP", + "Source Title": "CHEMISTRY OF MATERIALS", + "Abstract": "Presented in this paper is a deep investigation into the defect chemistry of UiO-66 when synthesized in the presence of monocarboxylic acid modulators under the most commonly employed conditions. We unequivocally demonstrate that missing cluster defects are the predominullt defect and that their concentration (and thus the porosity and composition of the material) can be tuned to a remarkable extent by altering the concentration and/or acidity of the modulator. Finally, we attempt to rationalize these observations by speculating on the underlying solution chemistry.", + "Times Cited, WoS Core": 1032, + "Times Cited, All Databases": 1107, + "Publication Year": 2016, + "Research Areas": "Chemistry; Materials Science", + "UT (Unique WOS ID)": "WOS:000378016400025", + "Markdown": "# Defect Engineering: Tuning the Porosity and Composition of the Metal−Organic Framework UiO-66 via Modulated Synthesis \n\nGreig C. Shearer,† Sachin Chavan,† Silvia Bordiga,†,‡ Stian Svelle,† Unni Olsbye, and Karl Petter Lillerud\\*,† \n\n†Department of Chemistry, University of Oslo, P.O. Box 1033, N-0315 Oslo, Norway ‡Department of Chemistry, NIS and INSTM Reference Centre, University of Torino, Via G. Quarello 15, 10135 Torino, Italy \n\nSupporting Information \n\nABSTRACT: Presented in this paper is a deep investigation into the defect chemistry of UiO-66 when synthesized in the presence of monocarboxylic acid modulators under the most commonly employed conditions. We unequivocally demonstrate that missing cluster defects are the predominant defect and that their concentration (and thus the porosity and composition of the material) can be tuned to a remarkable extent by altering the concentration and/or acidity of the modulator. Finally, we attempt to rationalize these observations by speculating on the underlying solution chemistry. \n\n![](images/9e8a33c985a5453e3e0c42b3e359ce062e6ffb149815ba1e3829f2e09b72009d.jpg) \n\n# INTRODUCTION \n\nMetal−organic frameworks (MOFs) with hexanuclear $\\mathbf{Zr}_{6}$ inorganic cornerstones $(^{\\infty}\\mathrm{Zr}_{6}~\\mathrm{MOFs^{\\prime\\prime}})^{1}$ have come to recent prevalence in the literature.2−28 Their popularity can be attributed to their superior stability $2,7-10,19,\\dot{2}0,\\dot{2}3,25,28,\\dot{2}9$ and the ease with which a wide range of functionalities can be introduced.30−44 UiO-66 $\\mathrm{(Zr_{6}(O H)_{4}O_{4}(B D C)_{6},}$ BDC $\\mathbf{\\sigma}=\\mathbf{\\sigma}$ benzene-1,4-dicarboxylate) was the first $\\mathbf{Zr}_{6}$ MOF to be reported9 and is by far the most widely studied. \n\nIn 2011, Behrens and co-workers showed that relatively large and monodisperse UiO-66 crystals could be obtained by adding monocarboxylic acid “modulators” to the synthesis mixture. 45 Variants of this synthesis method have since been popularized in the literature. $^{32,36,41,46-50}$ However, recent work has shown that modulated synthesis routes promote the formation of defects,24,51−64 which can have a profound (and in some cases, positive) impact on the stability,65−68 reactivity,57 porosity, and thermomechanical behavior54 of UiO-66. Affording control over the defects thus allows MOF chemists to fine-tune the properties of the material and potentially to improve its performance in various applications. Indeed, defects have been shown to have a positive influence on UiO-66’s catalytic,58,69−72 adsorption,60,62,64,68,73 decontamination,63,74,75 and proton conductivity53 capabilities. \n\nTwo types of defects have been proposed to exist in the $\\mathrm{UiO}-6\\bar{6}$ f r a m e w o r k : “ m i s s i n g l i n k e r d e - fects”35,51,56−64,69,70,73,75−81 and “missing cluster defects” $\\cdot24,52-54,81,82$ (see Figure 1 below). Missing cluster defects were recently discovered by Goodwin and co-workers.52 In a highly convincing study, they demonstrated that using formic acid as a modulator promotes the formation of a material in which missing cluster defects exist in correlated nanoregions of the reo topology. In the defective reo phase, the clusters have reduced linker connectivity (8) with respect to ideal UiO-66 (12). This results in a charge imbalance which the authors assume to be compensated by formate anions (originating from the formic acid modulator), allowing the clusters to maintain the familiar $\\mathrm{Zr}_{6}\\mathrm{(OH)}_{6}\\mathrm{O}_{4}\\mathrm{(CO}_{2}\\mathrm{)}_{12}$ geometry. A visual depiction of the above (albeit with trifluoroacetate as the defectcompensating ligand) is shown on the left-hand side of Figure 1. \n\nThe first detailed investigation into missing linker defects was performed by the Zhou group.60 They showed that the porosity of UiO-66 tends to increase as increasing amounts of acetic acid are used in the synthesis. On the basis of this observation, they concluded that acetic acid promotes the formation of missing linker defects by acting as the defect-compensating ligand (as acetate). Similar conclusions were made by Vermoortele et al., who synthesized extremely defective UiO-66 samples using trifluoroacetic acid as a modulator.58 A hypothetical model of such a material is shown on the right-hand side of Figure 1. \n\nThe three studies discussed above each involved the use of a different monocarboxylic acid as modulator. It therefore occurred to us that the properties (particularly the acidity) of the modulator may have a strong and perhaps even logical influence on the nature and/or concentration of defects in the UiO-66 framework. This prompted us to perform a systematic investigation involving 15 UiO-66 syntheses in which only the concentration and/or acidity $\\left(\\mathrm{{p}}K_{\\mathrm{{a}}}\\right)$ of the modulator was varied (see Scheme 1). To ensure that our study is as relevant as possible, all syntheses were performed under the most widely employed reaction conditions $\\mathrm{\\ZrCl_{4}}$ as ${\\mathrm{Zr}}^{4+}$ source, 1:1 linker/ Zr ratio, DMF as solvent, crystallization temperature $=120{^\\circ}\\mathrm{C}$ ). All 15 samples were thoroughly characterized by PXRD, nitrogen sorption, dissolution/NMR, TGA-DSC, SEM/EDX, and ATR-IR. \n\n![](images/2edcd20be1109b2fa8b079630b95aa344a0ceb215a9e2221755b1d2dd1471515.jpg) \nFigure 1. Illustration depicting the structural and compositional differences between the ideal UiO-66 unit cell and those with missing cluster/ missing linker defects. Trifluoroacetate ligands compensate for the defects in the examples above; however, the compensating ligand can vary depending on the modulator used during the MOF synthesis. \n\n![](images/f60bb479a44b4de84d262574c8293df682d02d72338af21d2923d41d33b11c7b.jpg) \nScheme 1. Comparison of the Compositions of the 15 UiO-66 Synthesis Mixturesa \na(a) Similarities and b) differences between the compositions of the 15 UiO-66 synthesis mixtures. Quantities are also provided in molar equivalents (eq.) so that the molar ratios between the reagents can be easily discerned. \n\nFour of these techniques (PXRD, nitrogen adsorption, dissolution/NMR, and TGA) provide important information related to the concentration of defects in the samples, affording us the opportunity to demonstrate the incredible extent to which the defect concentration can be tuned. Moreover, quantitative data was extracted from the four techniques, allowing us to discover trends and unveil the nature of the defects. Our findings are further validated by comparing experimentally obtained nitrogen adsorption isotherms with those simulated from hypothetical defective UiO-66 structural models. Finally, we attempt to rationalize our conclusions by speculating on the underlying solution chemistry. \n\n# EXPERIMENTAL DETAILS \n\nThe compositions of the 15 UiO-66 synthesis mixtures are shown schematically in Scheme 1. The synthesis mixtures were prepared in volumetric flasks. Once all reagents had dissolved, the flasks were loosely capped and transferred to an oven set to $120{}^{\\circ}\\mathrm{C}.$ . After $^{72\\mathrm{~h~}}$ of reaction, the resulting microcrystalline powders were thoroughly washed and activated. Full details of the synthesis, washing, and activation procedures are also provided in the Supporting Information. Detailed descriptions of the characterization methods (PXRD, nitrogen sorption, dissolution/NMR, TGA-DSC, SEM, EDX, and ATR-IR), simulations (PXRD and nitrogen adsorption), and quantitative analysis methods are provided in the Supporting Information. \n\n# RESULTS AND DISCUSSION \n\nNitrogen Sorption Isotherms. The nitrogen sorption isotherms obtained on all 15 UiO-66 samples at $77~\\mathrm{~K~}$ are shown in Figure 2 below. As can be seen, the nitrogen uptake capacity (and thus porosity) of the samples varies enormously depending on the acidity and concentration of the modulator used in the MOF synthesis. Of even greater interest is the observation of two remarkably conspicuous trends: (1) The nitrogen uptake (and thus porosity) of the samples systematically increases as increasing amounts of modulator were added to the synthesis mixture. This observation holds for all four modulators. (2) The nitrogen uptake (and thus porosity) of the samples systematically increases as the acidity $\\mathsf{^{\\prime}p K_{a}}$ of the modulator was increased/decreased. \n\n![](images/3b592d10939c20c5aca1b914d680bb3b8fab5c20317577d46002cd1d61b35349.jpg) \nFigure 2. Nitrogen adsorption isotherms obtained on all 15 UiO-66 samples at $77~\\mathrm{K}$ Adsorption is represented by filled squares; desorption is represented by open squares. The same $y$ scale is applied to all four plots. \n\nThese two trends exemplify the astounding extent to which the porosity of UiO-66 may be tuned via judicious use of modulator. The only outlier is 6Trif (red curve in rightmost plot). On the basis of the second trend outlined above, one would have expected it to adsorb more nitrogen than 6Dif (red curve in second plot from the right). The surprisingly low porosity of 6Trif can be attributed to the fact that it contains an impurity phase, MIL-140,83 another zirconium terephthalate MOF which is considerably denser than UiO-66. Evidence for the presence of this impurity is presented in section 5.14 of the Supporting Information. \n\nAnother important observation is that the sample synthesized without modulator (NoMod, black curve in all four plots) is considerably less porous than all other samples. In fact, it is slightly less porous than ideal UiO-66, as determined by comparing its nitrogen adsorption isotherm with that simulated from a defect-free UiO-66 structural model (see section 5.5.1 of the Supporting Information). As one can see, using just $6~\\mathrm{mol}$ equiv of any of the four modulators (red curves) leads to a substantial increase in porosity. \n\nQuantitative data was extracted from the isotherms by calculating the BET surface areas of the samples (see section 3.3 of the Supporting Information for method and Table S15 for the numerical values). Figure 3 is the graph obtained when the BET surface areas of all 15 samples are plotted against the molar equivalents of modulator added to their syntheses. \n\nAs can be seen, the BET surface areas of the samples vary significantly, ranging from $1175~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ (NoMod) to $1777\\mathrm{m}^{2}$ $\\mathbf{g}^{-1}$ (36Trif), which is one of the highest BET surface areas ever reported for UiO-66 (the current record is $1890\\ \\mathrm{~m}^{2}\\ \\mathrm{g}^{-1})$ .64 More importantly, the trends in porosity (now quantitatively described by the BET surface area) are the same as those qualitatively observed in Figure 2, including the observation that 6Trif (blue data point at $x=6$ ) is the only outlier. \n\nPXRD. When compared over a relatively wide $2\\theta$ range $\\left(2-\\right.$ $50^{\\circ},$ ), the differences between the PXRD patterns obtained on the 15 samples are not immediately obvious (see Figure S10). However, if one looks at the $2\\theta$ region around the (111) (the strongest and ideally the first) reflection of UiO-66 (appearing at ca. ${7.4}^{\\circ}2\\theta_{.}$ ), then interesting trends emerge. This region (2θ $=2{-}12^{\\circ})$ is emphasized in Figure 4. \n\n![](images/26b343805ef151387fac26faa8631a4d0f8ecaa2c0182dc79d4401a6400b6544.jpg) \nFigure 3. Graph obtained when the BET surface areas of the 15 UiO66 samples (see Table S15) are plotted against the molar equivalents of modulator added to their syntheses. \n\nAs one can see, most of the patterns contain a very broad peak spanning a $2\\theta$ range of ca. $2{-}7^{\\circ}$ . This peak cannot be attributed to the UiO-66 phase. The assignment of this peak (hereafter simply referred to as the “broad peak”) is discussed in section 5.1.2. of the Supporting Information, where we confidently assign it to reo nanoregions that are even smaller than those previously observed by Goodwin and co-workers.52 As shown in Figure 1, the reo phase can be thought of as UiO66 with one-quarter of its clusters missing. For this reason, the terms “missing cluster defects” and “reo phase/nanodomains” are used interchangeably herein. \n\nIn their inspiring study, Goodwin and co-workers demonstrated that the intensity of the reo reflections (relative to those of UiO-66) is correlated with the concentration of missing cluster defects in the sample. With this in mind, we note two qualitative trends regarding the intensity of the broad peak when observing Figure 4: (1) It systematically increases as increasing amounts of modulator were added to the synthesis mixture. This observation holds for all four modulators. (2) It systematically increases as the acidity/ $\\mathsf{^{\\prime}p}K_{\\mathrm{a}}$ of the modulator was increased/decreased. \n\n![](images/47a7313efe6123e13ff7df81a1d2560e9349ba8ada72ed87d307b9bd198bb350.jpg) \nFigure 4. Low-angle $\\mathit{\\Omega}^{\\prime}2\\theta=2\\mathrm{-}12^{\\circ},$ region of the PXRD patterns obtained on all 15 UiO-66 samples. Samples were activated (i.e., desolvated) prior to measurement (see section 1.1 of the Supporting Information for details). The same $y$ scale is applied to all four plots. \n\nTo scrutinize these perceived trends quantitatively, we calculated the relative intensity of the broad peak $(R e l(I)_{\\mathrm{BP}})$ in each of the PXRD patterns (see section 3.1 of the Supporting Information for method). Figure 5 is the graph obtained when the $R e l(I)_{\\mathrm{BP}}$ values of all 15 samples (see Table S4) are plotted against the molar equivalents of modulator added to their syntheses. As can be seen, the trends in $R e l(I)_{\\mathrm{BP}}$ (and thus the concentration of missing cluster defects in the UiO-66 framework) are the same as those qualitatively observed upon inspection of Figure 4, with absolutely no outliers. \n\n![](images/f0db1fe7766fbeb69edb2bbcb65082f7177386d481bd03e94ff4eb2749f9dcee.jpg) \nFigure 5. Graph obtained when the $R e l(I)_{\\mathrm{BP}}$ values (see Table S4), are plotted against the molar equivalents of modulator added to the UiO66 synthesis mixture. \n\nIdentity of the Defect-Compensating Ligands. As demonstrated in Figure 1, terminal ligands are required to compensate for the defects in the UiO-66 framework (a role fulfilled by trifluoroacetate in the figure). To understand fully the defect chemistry of our samples, we need to ascertain the identity of the defect compensating ligands. To this end, three possibilities were investigated on the basis of observations and/ or speculations in previous studies: chloride,51,58,62,65,80,81,84 OH−/H O,35,53,61,63,64,70,73,74,76,77,79,85 and monocarboxylates51−60,62−64 ( i.e., deprotonated modulator molecules such as trifluoroacetate, see Figure 1). However, chloride and hydroxide were quickly ruled out on the basis of EDX (Figure S54) and ATR-IR (Figure S55) results, respectively. With the other two possibilities eliminated, dissolution/NMR (both $\\mathrm{^{1}H}$ and $^{19}\\mathrm{F}^{'}$ ) was used to investigate the possibility that monocarboxylates compensate for the defects in our samples. \n\nDissolution/NMR Spectroscopy. The dissolution/NMR technique involves the dissolution (i.e., digestion or disassembly) of the MOF in a deuterated digestion medium. The organic components (e.g., linker, modulator, and porefilling solvent) can then be identified and quantified (as a molar ratio with other organic components) by liquid NMR spectroscopy. \n\nAs a representative example of the results obtained in this work, the $\\mathrm{^{1}H}$ NMR spectra recorded on the acetic acid modulated samples after digestion in $1\\mathrm{MNaOH}$ (in $\\mathrm{D}_{2}\\mathrm{O}\\dot{},$ ) are displayed in Figure 6. The spectrum obtained on NoMod is included for comparison. See section 5.2.2 of the Supporting Information for equivalent figures and subsequent discussion of the results obtained on the formic, difluoroacetic, and trifluoroacetic acid modulated samples. \n\nLooking at the full chemical shift range of the spectra, one can see that they are exceptionally clean. There are only three signals, which have been confidently assigned to $\\dot{\\mathrm{BDC}}^{2-}$ , acetate, and formate in Figure 6. This is an early indication that monocarboxylates (both formate and acetate) do indeed compensate for the defects in these samples. However, it is of utmost importance to ascertain whether these species are actually incorporated into the UiO-66 framework or if they are simply occluded in the pores as free acids. To this end, the MOF washing and activation (i.e., desolvation) procedures are heavily scrutinized in section 5.2.1 of the Supporting Information, where we conclude that all free monocarboxylic acids (acetic, formic, difluoroacetic, or trifluoroacetic acid) were successfully removed by these treatments. We can therefore be very confident that all monocarboxylates detected after activation are indeed incorporated into the UiO-66 framework (as is the case in Figure 6). \n\n![](images/b7abdd8e8238f79a5b5da3a50bd97b3fe05d4bebfd77c91fc3acd1dee7871d06.jpg) \nFigure 6. Dissolution/ $\\mathrm{^{1}H}$ NMR spectra obtained on the acetic acid modulated samples. NoMod is included for comparison. Samples were activated (i.e., desolvated) prior to measurement (see section 1.1 of the Supporting Information for details). \n\nWith this in mind, let us return to the spectra presented in Figure 6, where one can see that the acetate signal systematically increases in intensity as increasing amounts of acetic acid were used in the synthesis. Equivalent trends are observed for the samples synthesized with the other three modulators under investigation (see section 5.2.2 of the Supporting Information). Moreover, similar trends in the intensity of bands related to the modulator can (in some cases) be seen in ATR-IR spectra (see Figures S56−S59). Both dissolution/NMR and ATR-IR results therefore show that the extent of modulator incorporation is strongly correlated with the concentration of modulator in the UiO-66 synthesis solution. \n\nA more surprising observation from Figure 6 is that all five samples contain formate, despite the fact that no formic acid was added to their synthesis mixtures. The acetic acid modulated samples are certainly not unique in this respect: formate is in fact present in the spectra obtained on all 15 samples. This is not too surprising for the formic acid modulated samples (6Form, 12Form, 36Form, and 100Form). However, intentionally added modulator cannot account for the formate observed in the 11 non formic acid modulated samples. The origin of this formate is discussed in section 5.2.1 of the Supporting Information, in which we conclude that it originates from formic acid generated by DMF hydrolysis during the MOF syntheses. \n\nThe discussion of our dissolution/NMR results has so far been limited to qualitative spectral comparisons; however, the real strength of the technique is that one can determine molar ratios between the MOF’s organic components by integration. In this work, three different molar ratios were calculated (see section 3.2 of the Supporting Information for methods): (1) the “intentionally added modulator to BDC molar ratio” (i.e., the formate/BDC, acetate/BDC, difluoroacetate/BDC, and trifluoroacetate/BDC molar ratios in the formic, acetic, difluoroacetic, and trifluoroacetic acid modulated samples, respectively). Values are presented in Table S12. (2) The formate/BDC molar ratio in the non formic acid modulated samples. Values are presented in Table S13. (3) The “total modulator to BDC ratio”. This is the sum of 1 and 2 above. Values are presented in Table S14. \n\nFollowing much discussion (section 5.2.3 of the Supporting Information), we concluded that the total modulator to BDC molar ratio, $\\frac{\\mathrm{Tot.Mod.}}{\\mathrm{BDC}}\\mathbf{m}_{R},$ is the fairest ratio to use when comparing the materials. It is essentially a quantitative descriptor for the concentration of monocarboxylate terminated defects in the UiO-66 framework. Figure 7 is the graph obtained when Tot . Mod . m values of all 15 samples are plotted against the molar equivalents of modulator added to their syntheses. \n\n![](images/906cf2af722625a003622656b2f19730658ddc97da415992e8079ff3b579d5b4.jpg) \nFigure 7. Graph obtained when the total modulator to BDC molar ratios $(\\frac{\\mathrm{Tot.Mod.}}{\\mathrm{BDC}}\\mathrm{m}_{R},$ see Table S14) are plotted against the molar equivalents of modulator added to the UiO-66 synthesis mixture. \n\nAs can be seen, an enormous range of TotB. DMCod . m values are observed in the samples. The most defective sample (36Trif) contains a huge amount of modulator: 0.76 molecules for every linker molecule. Of even greater interest is the observation of two very clear trends in the figure: (1) The total modulator/ BDC ratio (and thus the concentration of monocarboxylate terminated defects in the UiO-66 framework) systematically increases as increasing amounts of modulator were added to the synthesis mixture. This observation holds for all four modulators. (2) The total modulator/BDC ratio (and thus the concentration of monocarboxylate terminated defects in the \n\nUiO-66 framework) systematically increases as the acidity $\\mathsf{^{\\prime}p K_{a}}$ of the modulator was increased/decreased. \n\nTGA-DSC. All TGA-DSC results obtained in this work are qualitatively similar. As a representative sample of our results, the TGA-DSC traces obtained on the formic acid modulated samples are presented in Figure 8. The result obtained on \n\n![](images/e31dcae397c430c65472a719cfbe65608570566a4e4a4d4669c8e7aff1667b31.jpg) \nFigure 8. TGA-DSC results obtained on the formic acid modulated samples. NoMod is included for comparison. Samples were activated (i.e., desolvated) prior to measurement (see section 1.1 of Supporting Information for details). Solid curves, left axis, TGA trace (normalized such that end weight $=100\\%$ ). Dotted curves, right axis, DSC trace. \n\nNoMod is included for comparison. See section 5.6 of the Supporting Information for equivalent figures (and subsequent discussion) concerning the results obtained on the acetic, difluoroacetic, and trifluoroacetic acid modulated samples. \n\nThree well-resolved weight losses are observed in the TGA traces (end weight normalized to $100\\%$ ). In accordance with previous studies, the losses are assigned to the following processes: (1) Adsorbate volatilization (in this case $\\mathrm{H}_{2}\\mathrm{O}$ ). This occurs over a temperature range of ca. $25{\\mathrm{-}}100\\ ^{\\mathrm{~\\circ}}\\mathrm{C}.$ (2) Removal of monocarboxylate ligands54,58 (in this case formate) and dehydroxylation of the $\\mathrm{Zr}_{6}$ cornerstones.9,78,84,86 These two weight loss events occur over a similar temperature range (ca. $200-350~^{\\circ}\\mathrm{C})$ and are thus not well-resolved from one another. Monocarboxylate loss is accompanied by a small exothermic peak in the DSC trace (as is the case for the loss of formate in the figure). (3) Framework decomposition.54,58,78 This occurs over a temperature range of ca. $390-525\\mathrm{~~}^{\\circ}\\mathrm{C}$ and is accompanied by a very intense exothermic peak in the DSC trace. \n\nThe framework decomposition weight loss step involves the complete combustion of the BDC linkers. It is now wellestablished that the magnitude of this weight loss (when normalized as above) is inversely correlated with the defectivity of the UiO-66 sample in question.54,58,65,78 This makes sense when one compares the compositions of the structures provided in Figure 1. Therein, one can see that ideal, defectfree (and dehydroxylated) UiO-66 has a composition of $\\mathrm{Zr}_{6}\\mathrm{O}_{6}(\\mathrm{BDC})_{6},$ where each $\\mathbf{Zr}_{6}$ formula unit contains 6 BDC linkers (i.e., $(6\\times2)=12$ linkers are coordinated to each $\\mathrm{Zr}_{6}$ cluster). In contrast, there are only 4 linkers per $\\mathrm{Zr}_{6}$ formula unit in either of the hypothetical defective structural models (i.e., $(4\\times2)=8$ linkers are coordinated to their clusters). Both missing linker and missing cluster defects therefore introduce “linker deficiencies” to the UiO-66 framework. Given that the decomposition weight loss involves the loss of linkers, the magnitude of the weight loss is reduced when defects (and thus linker deficiencies) are present. However, it is impossible to distinguish between missing linker and missing cluster defects using TGA alone (see section 3.4.1. of the Supporting Information for more on this). \n\nWith all of the above in mind, let us return our attention to Figure 8, where the theoretically expected weight loss for the decomposition of ideal (dehydroxylated) UiO-66, $\\mathrm{Zr}_{6}\\mathrm{O}_{6}(\\mathrm{BDC})_{6}$ is represented by the vertical gap between the two horizontal dashed lines. To compare the samples fairly to this ideal, we need to pinpoint the stage at which everything except the BDC linkers has been lost (i.e., when the second weight loss step is complete). This point is emphasized with a vertical dashed line in Figure 8 (see section 3.4.4 in the Supporting Information for details of how this choice is made). Commencing from this point, one can see that the magnitude of the decomposition weight loss is significantly lower than that theoretically expected in all samples, indicating that they are linker deficient. More importantly, there is a clear trend among the samples: the magnitude of the decomposition weight loss systematically decreases (and thus the defectivity of the material increases) as increasing amounts of formic acid were added to the synthesis mixture. The same trend was observed for all samples except the acetic acid modulated materials (see discussion of Figure 9 later). \n\n![](images/03ae2cc47985d8e298241a7381f72e0b92ea79bbe2b52ae94baf400a067516d9.jpg) \nFigure 9. Graph obtained when the number of linker deficiencies per $\\mathbf{Zr}_{6}$ formula unit $\\scriptstyle(x,$ see Table S24) are plotted against the molar equivalents of modulator added to the UiO-66 synthesis mixture. \n\nIn order to quantitatively compare the entire series of samples, we calculated the number of linker deficiencies per $\\mathrm{Zr}_{6}$ formula unit from the TGA traces obtained on each of the 15 samples. This is the value of $x$ in the general molecular formula $\\mathrm{Zr}_{6}\\bar{\\mathrm{O}}_{6+x}(\\mathrm{BDC})_{6-x},$ which is the assumed composition of the material immediately before the decomposition weight loss step commences. The value of $x$ is correlated with the overall defectivity of the material and inversely correlated with the magnitude of the decomposition weight loss. A detailed description of the method used to calculate $x$ is provided in section 3.4 of the Supporting Information. As an interesting aside, we have used the $x$ values (in combination with the molar ratios obtained via dissolution/NMR) to attain very promising estimates for the overall (hydroxylated) composition of each of our samples. The method and results can be found in sections 3.5 and 5.8 of the Supporting Information, respectively. \n\n![](images/d6ab3d67e65c62cc56226cc7af03ea9c168e3abe3c0832c0f3ba4b0789e13888.jpg) \nFigure 10. Graphs and linear fits obtained when the relative intensity of the broad peak $(R e l(I)_{\\mathrm{BP}})$ is plotted against: left plot, the total modulator to BDC ratio ${\\left(\\frac{\\mathrm{Tot.}\\mathrm{Mod.}}{\\mathrm{BDC}}{m_{\\mathrm{R}}}\\right)}$ middle plot, the BET surface area; and right plot, the number of linker deficiencies per $\\mathrm{Zr}_{6}$ formula unit (i.e., the value of $x$ in composition $\\mathrm{Zr}_{6}\\mathrm{O}_{6+x}(\\mathrm{BDC})_{6-x})$ . Because of its aforementioned MIL-140 impurity (see section 5.14 of the Supporting Information), the data point corresponding to 6Trif has been omitted from the middle plot. \n\nFigure 9 is the graph obtained when the $x$ values of all 15 samples (see Table S24) are plotted against the molar equivalents of modulator added to their syntheses. As can be seen, the samples differ widely in their defectivity. The most defective sample in the series is once again shown to be 36Trif, which contains 2 linker deficiencies per $\\mathbf{Zr}_{6}$ formula unit, meaning that there are $(6-2)=4$ linkers in its average formula unit and only $(4\\times2)=8$ linkers coordinated to its average $\\mathrm{Zr}_{6}$ cluster. This is an astonishing level of defectivity considering that 12 linkers are coordinated to the cluster in the ideal material. More importantly, two clear trends are once again observed in the figure: (1) The number of linker deficiencies (and thus the defectivity of the material) systematically increases as increasing amounts of modulator were added to the synthesis mixture. This observation holds for all modulators except acetic acid, where the number of linker deficiencies is nearly constant unless very large amounts of modulator (100 equiv) were used. (2) The number of linker deficiencies (and thus the defectivity of the material) systematically increases as the acidity $\\mathsf{^{\\prime}p K_{a}}$ of the modulator was increased/decreased. \n\nCorrelations−The Nature of the Defects. We note that the trends observed in Figures 3, 5, 7, and 9 are qualitatively rather similar. This suggests that the parameters plotted in the graphs are correlated, which makes sense given that all four parameters are essentially quantitative descriptors for the defectivity of the samples: (1) The BET surface area of UiO66 has previously been shown to be correlated with its defectivity.60,65 (2) The relative intensity of the broad peak $(R e l(I)_{\\mathrm{BP}})$ is a quantitative descriptor for the concentration of missing cluster defects in the UiO-66 framework. (3) The total modulator to BDC molar ratio $\\left(\\frac{\\mathrm{Tot.}\\mathrm{Mod.}}{\\mathrm{BDC}}m_{\\mathrm{R}}\\right)$ is a quantitative descriptor for the concentration of monocarboxylate terminated defects in the sample. (4) The number of linker deficiencies per $\\mathbf{Zr}_{6}$ formula unit (i.e., the value of $x$ in composition $\\mathrm{Zr}_{6}\\mathrm{O}_{6+x}(\\mathrm{BDC})_{6-x})$ is an obvious descriptor for the overall defectivity of the material. \n\nTo explore the relationship between the four “defectivity descriptors”, the $R e l(I)_{\\mathrm{BP}}$ values were plotted against the other three parameters, resulting in the three graphs presented in Figure 10. For convenience, all of the data used to plot the three graphs is summarized in Table S25. As can be seen, the defectivity descriptors are indeed positively correlated with one another. Before delving deeper into these correlations, it is of utmost importance to emphasize that just 1 of the 4 defectivity descriptors (the relative intensity of the broad peak, $R e l(I)_{\\mathrm{BP}})$ is exclusively associated with only one type of defect (missing cluster defects), whereas the others could be influenced by the presence of either missing linker or missing cluster defects. This point is pivotal for attaining information on the nature of the defects. For example, the fact that there is a strong linear ( $R^{2}=$ 0.94) relationship between Rel(I)BP and Tot. Mod. m BDC R strongly suggests that the monocarboxylate ligands are incorporated almost exclusively as compensation for missing cluster defects (refer back to Figure 1 to visualize this scenario, where the monocarboxylate is trifluoroacetate). Likewise, the linear $\\scriptstyle(R^{2}=$ 0.89) relationship between $R e l(I)_{\\mathrm{BP}}$ and the number of linker deficiencies per $\\mathbf{Zr}_{6}$ formula unit $(x)$ implies that the linker deficiencies are almost exclusively due to missing cluster defects (recall that there are $(6-4)\\stackrel{.}{=}2$ linker deficiencies per $\\mathrm{Zr}_{6}$ formula unit in the pure reo phase, $\\mathrm{Zr}_{6}\\mathrm{O}_{6}(\\mathrm{BDC})_{4}(\\mathrm{\\bar{M}o d})_{4},$ where Mod is a monocarboxylate (trifluoroacetate in Figure 1)). \n\nHowever, the relationship between $R e l(I)_{\\mathrm{BP}}$ and the BET surface area is far from linear $\\left(R^{2}=0.76\\right)$ . This can be explained by the fact that four different monocarboxylate ligands (formate, acetate, difluoroacetate, or trifluoroacetate) compensate for the missing cluster defects in the samples. These four ligands have significantly different molecular weights; thus, the crystallographic densities of the samples will vary considerably. Such variations in density strongly impact the BET surface area of the material (given in meters squared per gram), an obvious point which became even more conspicuous when analyzing our simulated $\\mathbf{N}_{2}$ adsorption isotherms (see section 5.4 of the Supporting Information). Thus, the BET surface areas of the samples do not solely depend on their defectivity, resulting in the observed nonlinear relationship between BET surface area and $R e l(I)_{\\mathrm{BP}}$ . \n\nComparison of Simulated and Experimental Nitrogen Adsorption Isotherms. To scrutinize the conclusion that missing cluster defects are the predominant defect in our samples, we constructed 16 hypothetical defective UiO-66 structural models (see section 4 in the Supporting Information for details) and simulated their nitrogen adsorption isotherms. Comparing the simulated isotherms with those obtained experimentally allows us to discern the type of defect that best accounts for the porosity of our samples. \n\n![](images/0dcc796a3274a1ab179a237a78471d4e11e460a9bfdee1515de8bd2996e2a8fe.jpg) \nFigure 11. Comparison of the nitrogen adsorption isotherms experimentally obtained on the difluoroacetic acid modulated samples with those simulated from defective UiO-66 structural models with difluoroacetate terminal ligands (see section 4 of the Supporting Information). \n\nThe reliability of the simulations is validated by Figure S66, where it can be seen that the isotherm simulated from the ideal UiO-66 structural model almost exactly matches that experimentally obtained on a near-defect-free UiO-66 sample (and those simulated in previous studies).35,73 The sample, named UiO-66-Ideal (UiO-66-Ideal-Calcined in Figure S65), was obtained by an optimized version of the synthesis procedure we promoted in previous work65 (see section 1.3 of the Supporting Information for full details of the optimized method). Its near-defect-free status is evidenced by extensive characterization results presented in section 5.13 of the Supporting Information. We feel that UiO-66-Ideal should be considered as a benchmark material to which UiO-66 samples obtained by other methods are compared. \n\nGiven the above validation, our simulated and experimental isotherms can be confidently compared. The clearest example is presented in Figure 11, where the isotherms experimentally obtained on the difluoroacetic acid modulated samples are compared with those simulated from the difluoroacetate terminated defective structural models (see section 4 of the Supporting Information for details). \n\nComparing the experimental isotherms (rightmost plot) with those simulated from the missing linker structural models (leftmost plot, see section 4 of the Supporting Information for explanation of nomenclature), one can see that missing linker defects (compensated by difluoroacetate ligands) absolutely cannot account for the high porosity of our difluoroacetic acid modulated UiO-66 samples. Interestingly, the porosity of the hypothetical materials actually systematically decreases as the number of missing linker defects is increased. This surprising observation (also observed for the trifluoroacetate terminated models) is due to the increasing crystallographic density of the framework (see section 5.4.2 of the Supporting Information for in-depth discussion). \n\nIf we instead compare the experimental isotherms with that simulated from the missing cluster structural model (Reo-Dif, middle plot), then one can clearly see that the hypothetical material is only slightly more porous than our difluoroacetic acid modulated UiO-66 samples. The implications of this observation are startling. The Reo-Dif isotherm is simulated from a pure reo model in which 1 out of $4~\\mathrm{Zr}_{6}$ clusters is missing from every unit cell (the same structure as the rightmost model in Figure 1, albeit with difluoroacetate as the defect compensating ligand). The fact that our difluoroacetic acid modulated UiO-66 samples are almost as porous as ReoDif therefore suggests that there is an enormous amount of missing cluster defects in the samples. This is consistent with the observation of a relatively intense “broad peak” in the PXRD patterns obtained on the difluoroacetic acid modulated UiO-66 samples (see Figures 4 and 5). It is therefore clear that missing cluster defects are by far the most prevalent defect in the difluoroacetic acid modulated materials. Similar conclusions were afforded by comparing the simulated and experimental isotherms related to the acetic, formic, and trifluoroacetic acid modulated UiO-66 samples (see section 5.5 of the Supporting Information). However, it must be said that the assignment is not as unequivocal for the acetic or formic acid modulated materials, in which the defect concentrations are much lower than the difluoroacetic acid modulated UiO-66 samples discussed herein. \n\nIt is important to note that our findings oppose the most commonly held literature view on the defect chemistry of UiO66 samples synthesized in the presence of monocarboxylic acid modulators under the most typical conditions $\\mathrm{\\zr{Cl_{4}}}$ as ${\\mathrm{Zr}}^{4+}$ source, 1:1 BDC/Zr ratio, DMF as solvent, and crystallization temperature $=120{}^{\\circ}\\mathrm{C}{}^{\\cdot}$ ). There is a general agreement that the most prominent defects in such samples are missing linker defects compensated for by deprotonated modulator molecules (see leftmost structure in Figure 1, where trifluoroacetate is the deprotonated modulator molecule). $51,53,55-59,62-64$ However, none of the techniques most commonly used as evidence for this type of defect (TGA, dissolution/NMR, and nitrogen adsorption isotherms) can distinguish between missing linker defects and missing cluster defects terminated by monocarboxylates. The only routine method that can distinguish between the two types of defect is PXRD, and this was only discovered in $\\mathrm{mid}{-}2\\mathrm{0i}4,^{52}$ after the majority of the missing linker defect literature had already been published. We feel that it is highly likely that the PXRD “fingerprint” for missing cluster defects simply went unnoticed or was dismissed as background in earlier studies. Such a dismissal is especially tempting when it appears as a single broad peak as it does herein (refer back to Figure 4). Moreover, our comparison of simulated and experimental nitrogen adsorption isotherms is by far the most thorough study of this type in the UiO-66 defect literature. All things considered, we feel that the overall evidence for our conclusions is substantially stronger than earlier investigations. \n\nThermal Stability. In an earlier study, we showed that missing cluster defects can have a severe impact on the thermal stability of UiO-66.65 Following the discussion in the two previous sections, it is clear that the samples under study herein are also riddled with missing cluster defects. It was therefore of interest to investigate their thermal stability. To this end, we subjected five key samples (NoMod, 36Ac, 36Form, 36Dif, and 36Trif) to $^{12\\mathrm{~h~}}$ of heat treatment (in air) at 300, 350, 400, and $450~^{\\circ}\\mathrm{C}$ before measuring their PXRD patterns. The results are presented in Figure S51. \n\nSurprisingly, all five samples completely retained their crystallinity after treatment at $350\\ ^{\\circ}\\mathrm{C},$ including the incredibly defective 36Trif. However, the samples differed in their ability to handle treatment at $400~^{\\circ}\\mathrm{C}$ : The most defective samples (36Dif and 36Trif) completely collapsed, whereas the stability of the remaining materials systematically increased with decreasing defectivity (NoMod $>36\\mathrm{Ac}>36\\mathrm{Form})$ . Missing cluster defects therefore do appear to negatively affect the stability of the material. However, the range of thermal stabilities of the samples herein is far narrower than those in our previous study, many of which partially collapsed after treatment at just $250~^{\\circ}\\mathrm{C}$ .65 The poor stability of said samples was attributed to the presence of missing cluster defects. Given that missing clusters are also the predominant defect in the samples herein, it is somewhat surprising that there is such a discrepancy between the thermal stabilities of the two sets of samples. Nevertheless, we can think of two possible reasons for this: (1) The samples in the previous study contained larger domains of missing cluster defects. This is evidenced by the breadth of the forbidden reflections,52 which were much narrower (and clearly resolved from one another) in the PXRD patterns obtained in our previous work.65 It is reasonable to suggest that larger domains of missing cluster defects would be detrimental to the stability of the UiO-66 framework. (2) The identity of the defect compensating ligands. Chloride was thought to fulfill this role in the previous study,65 whereas monocarboxylates are the defect-terminating ligands herein. Compensation with monocarboxylates allows the clusters to retain the familiar $\\mathrm{Zr}_{6}\\mathrm{O}_{4}(\\mathrm{OH})_{4}(\\mathrm{CO}_{2})_{12}$ arrangement, which we imagine to be a more robust chemical environment than clusters partially terminated with $\\mathrm{Cl}^{-}$ ligands. \n\n# DISCUSSION OF OVERALL FINDINGS \n\nCombining all results presented herein, the foremost conclusions of this study are as follows: (1) Missing cluster defects are the predominant defect in UiO-66 samples synthesized in the presence of monocarboxylic acid modulators under the most typical conditions. (2) The defects are compensated by a combination of deprotonated modulator molecules and formate (originating from the in situ decomposition of DMF during the MOF synthesis). (3) The concentration of missing cluster defects in the UiO-66 framework systematically increases as increasing amounts of modulator are added to the synthesis mixture. (4) The concentration of missing cluster defects in the UiO-66 framework systematically increases as the acidity of the modulator is increased. \n\nTo understand the origin of these conclusions, one needs to understand the chemistry occurring in the MOF synthesis solution. To this end, we hypothesize that the modulator and linker compete with one another for carboxylate $\\left(\\mathrm{CO}_{2}^{-}\\right)$ sites on the $\\mathrm{Zr}_{6}\\mathrm{\\bar{(OH)}}_{4}\\mathrm{O}_{4}\\mathrm{(CO}_{2}\\mathrm{)}_{12}$ clusters in the UiO-66 product. The acids must be deprotonated before they can coordinate in this manner. To form a missing cluster defect, the deprotonated modulator needs to bind to at least 1 of the 12 sites on 12 different clusters, each in close proximity to one another. The geometry of these 12 clusters must be correlated such that the 12 monocarboxylates point toward the cavity where a cluster would ordinarily be found. This interpretation accounts for the first two conclusions above. Furthermore, it is easy to see how conclusion 3 would follow: higher concentration of modulator $\\rightarrow$ more modulator ligands for the linker to compete with $\\rightarrow$ increased probability of modulator remaining bound to the cluster in the product $\\rightarrow$ more missing cluster defects. \n\nBefore proceeding with our discussion of the fourth conclusion, it is important to declare that the literature $\\mathsf{p}K_{\\mathrm{a}}$ values presented herein were measured in aqueous conditions, and under normal circumstances, one should be wary of discussing such values in the context of MOF syntheses in DMF solutions. Nevertheless, the observed trends with modulator acidity are unequivocal, and it is difficult to imagine that they could appear by mere coincidence. \n\nWith this in mind, our working explanation for the fourth conclusion stems from the fact that the modulator must be deprotonated in order to coordinate to the clusters. We then apply the following logic: more acidic modulator $\\mid\\rightarrow\\mid$ higher concentration of deprotonated modulator in solution $\\mid\\rightarrow$ more monocarboxylate ligands for the linker to compete with $\\rightarrow$ increased probability of modulator remaining bound to cluster in product $\\rightarrow$ more missing cluster defects. An alternative explanation can be reached if one assumes that the strength of a $\\mathrm{Zr}^{\\mathsf{\\bar{4}+}}{\\mathsf{-O}_{2}\\mathsf{C}}$ bond systematically increases as the $\\mathsf{p}K_{\\mathrm{a}}$ of the carboxylate (in its acidic form) decreases. Indeed, Bennett and co-workers have previously claimed that the bond between trifluoroacetate and the $\\mathrm{Zr}_{6}$ cluster is particularly strong and attributed this to the high acidity of trifluoroacetic acid.56 However, this contradicts the generally accepted idea that the strength of a metal−ligand bond increases as the basicity of the ligand increases.87−89 If we instead assume that our working hypothesis is true, then it is interesting to imagine the dynamics of the competition between the modulator and linker and speculate on their effects in a case by case manner: (1) The $\\mathrm{p}K_{\\mathrm{a}}$ ’s of difluoroacetic (1.24) and trifluoroacetic acid (0.23) are much lower than those of $\\mathrm{H}_{2}\\mathrm{BDC}$ $\\mathrm{{'p}}K_{\\mathrm{al}}=3.51$ , $\\mathrm{p}K_{\\mathrm{a}2}=4.82,$ ). \n\nThus, when difluoroacetic or trifluoroacetic acid is used as a modulator, the synthesis solution is expected to contain many more deprotonated modulator molecules than deprotonated linker molecules. The modulator would therefore dominate the competition for carboxylate sites on the $\\mathrm{Zr}_{6}\\mathrm{(OH)}_{4}\\mathrm{O}_{4}\\mathrm{(CO}_{2}\\mathrm{)}_{12}$ clusters, resulting in samples with a very high concentration of missing cluster defects. (2) The $\\mathsf{p}K_{\\mathrm{a}}$ of formic acid (3.77) is similar to the first $\\mathsf{p}K_{\\mathrm{a}}$ of the $\\mathrm{\\bf~H}_{2}\\mathrm{\\bfBDC}$ linker (3.51). The competition between formate and the singly deprotonated linker $\\left(\\mathrm{HBDC^{-}}\\right)$ is thus expected to be fairly close. We speculate that such close competition allows formic acid to behave in a manner more similar to a modulator in the traditional sense,45,90,91 where ligand (carboxylate) exchange reactions between formate and $\\mathrm{HBDC^{-}}$ are favored, inhibiting crystal nucleation and promoting growth. This is consistent with the formation of relatively large octahedral crystals when formic acid is used as a modulator (SEM images are presented in Figure S52). However, formic acid is considerably more acidic than the singly deprotonated linker $\\left(\\mathrm{HBDC^{-}}\\right.$ , $\\mathsf{p}K_{\\mathrm{a}}=$ 4.82). The synthesis solution is therefore expected to contain many more deprotonated modulator molecules (formate) than doubly deprotonated linker molecules $\\left(\\mathrm{BDC}^{2-}\\right)$ . As a result, formate would still “win” many of the carboxylate sites on the $\\mathrm{Zr}_{6}\\mathrm{(OH)}_{4}\\mathrm{O}_{4}\\mathrm{(CO}_{2}\\mathrm{)}_{12}$ clusters, resulting in the observation of a moderate amount of missing cluster defects when formic acid is used as a modulator. (3) The $\\mathsf{p}K_{\\mathrm{a}}$ of acetic acid (4.76) is very similar to the second $\\mathsf{p}K_{\\mathrm{a}}$ of the $\\mathrm{H}_{2}\\mathrm{BDC}$ linker (4.82). The competition between acetate and the doubly deprotonated linker $\\left(\\mathrm{BDC}^{2-}\\right)$ is therefore expected to be very close. Following the same logic as in the previous case, this close competition inhibits crystal nucleation and promotes growth, resulting in the formation of large octahedral crystals when acetic acid is used as a modulator (SEM images are presented in Figure S52). Furthermore, the meager acidity of acetic acid ensures that the concentration of acetate in the synthesis solution would be rather low. Thus, only a small amount of acetate is expected to become incorporated into the material, resulting in the observation of a low concentration of missing cluster defects when acetic acid is used as a modulator. \n\n# POTENTIAL FOR SCOPE \n\nThe discussion outlined in the previous section shows that our results can be fully explained if we assume that our hypothesis, based on the competition between the modulator and linker, is true. This paper concerns only UiO-66, but we believe that our hypothesis may be applicable to $\\mathbf{Zr}_{6}$ MOFs in general. If so, then this work could greatly aid MOF chemists to make informed choices when selecting a modulator for their syntheses. For example, a general strategy for the synthesis of large crystals of relatively low defectivity could be to make the competition between the modulator and the linker as close as possible. According to our hypothesis, this can be achieved by using a monocarboxylic acid modulator whose $\\mathsf{p}K_{\\mathrm{a}}$ is similar to that of the second linker deprotonation (the equivalent of using acetic acid in the synthesis of UiO-66). If one instead wishes to purposely synthesize a highly defective (and thus more porous) material, then it is best to select a modulator that dominates its competition with the linker. According to our hypothesis, this can be achieved by using a monocarboxylic acid modulator whose $\\mathsf{p}K_{\\mathrm{a}}$ is much lower than those of the linker. This may be difficult to achieve if the linker is highly acidic, but in most cases, trifluoroacetic acid (the most acidic carboxylic acid in common use) would be an excellent choice of modulator. \n\nWhen further considering the scope of this work, we feel it is important to declare that our hypothesis surely has its limits. All of the modulators investigated herein are liquids with complete miscibility in DMF, meaning that solubility effects could be completely disregarded. This allowed us to confidently study the influence of modulator acidity in isolation. However, it is reasonable to suggest that solubility and/or steric effects will likely have a significant impact on the defect chemistry of UiO66 samples synthesized in the presence of solid modulators (e.g., benzoic acid). Such samples may not fit into the strikingly systematic acidity trends observed herein. \n\n# CONCLUSIONS \n\nWe have performed a deep investigation into the defect chemistry of UiO-66 samples synthesized in the presence of monocarboxylic acid modulators under the most typical conditions $\\mathrm{(\\dot{Z}r C l_{4}}$ as ${\\mathrm{Zr}}^{4+}$ source, $\\mathrm{BDC/Zr}$ ratio $\\mathbf{\\tau}=1{:}1$ , DMF as solvent, and crystallization temperature $=120\\mathrm{~}^{\\circ}\\mathrm{C}\\mathrm{)}$ . The concentration and acidity $\\left(\\mathfrak{p}K_{\\mathrm{a}}\\right)\\overline{{\\right.}}$ of the modulator was systematically varied in a total of 15 UiO-66 syntheses. \n\nQualitative and quantitative analysis of our multitechnique characterization data revealed that the defectivity of UiO-66 can be systematically tuned to a remarkable extent, resulting in a series of samples with a wide range of porosities and compositions. Specifically, the defectivity of the material was found to increase systematically and dramatically as the concentration and/or acidity of the modulator was increased. Our dissolution/NMR results showed that the defectcompensating ligands are a combination of deprotonated modulator molecules and formate (originating from the in situ decomposition of DMF during the MOF synthesis). \n\nFour quantitative “defectivity descriptors” were derived from PXRD, nitrogen adsorption, dissolution/NMR, and TGA data. Analysis of the correlations between these descriptors afforded the conclusion that missing clusters are the predominant defect in the samples. This conclusion was strongly supported by simulated nitrogen adsorption isotherms. \n\nTo account for these observations, we speculated on the chemistry occurring in the UiO-66 synthesis solution and formulated a simple hypothesis based on the competition between the linker and modulator (Discussion of Overall Findings). We believe that our hypothesis could be applicable to the synthesis of ${}^{\\mathfrak{a}}\\mathbf{Z}\\mathbf{r}_{6}$ MOFs” in general, allowing MOF chemists to make an informed decision when deliberating which modulator to use in their syntheses (Potential for Scope). \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.chemmater.6b00602. \n\nDetails of synthesis, characterization, and quantitative analysis methods, description of defective structural models, discussion of results from PXRD, dissolution/ NMR, TGA-DSC, ATR-IR, EDX, SEM, thermal stability tests, density measurements, and $\\mathbf{N}_{2}$ sorption (both simulated and experimental). (PDF) \n\n# AUTHOR INFORMATION \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nBoris Bouchevreau is kindly acknowledged for obtaining the SEM images. \n\n# REFERENCES \n\n(1) Mondloch, J.; Katz, M.; Planas, N.; Semrouni, D.; Gagliardi, L.; Hupp, J.; Farha, O. Are $\\mathrm{Zr}$ -6-based MOFs water stable? Linker hydrolysis vs. capillary-force-driven channel collapse. Chem. Commun. 2014, 50, 8944−8946. \n(2) Kalidindi, S.; Nayak, S.; Briggs, M.; Jansat, S.; Katsoulidis, A.; Miller, G.; Warren, J.; Antypov, D.; Cora, F.; Slater, B.; Prestly, M.; Marti-Gastaldo, C.; Rosseinsky, M. Chemical and Structural Stability of Zirconium-based Metal-Organic Frameworks with Large ThreeDimensional Pores by Linker Engineering. Angew. Chem., Int. Ed. 2015, 54, 221−226. \n(3) Feng, D.; Chung, W.; Wei, Z.; Gu, Z.; Jiang, H.; Chen, Y.; Darensbourg, D.; Zhou, H. Construction of Ultrastable Porphyrin Zr Metal-Organic Frameworks through Linker Elimination. J. Am. Chem. Soc. 2013, 135, 17105−17110. \n(4) Jiang, H.; Feng, D.; Wang, K.; Gu, Z.; Wei, Z.; Chen, Y.; Zhou, H. An Exceptionally Stable, Porphyrinic $\\mathrm{Zr}$ Metal-Organic Framework Exhibiting pH-Dependent Fluorescence. J. Am. Chem. Soc. 2013, 135, 13934−13938. \n(5) Reinsch, H.; Stassen, I.; Bueken, B.; Lieb, A.; Ameloot, R.; De Vos, D. First examples of aliphatic zirconium MOFs and the influence of inorganic anions on their crystal structures. CrystEngComm 2015, 17, 331−337. \n(6) Reinsch, H.; Bueken, B.; Vermoortele, F.; Stassen, I.; Lieb, A.; Lillerud, K.; De Vos, D. Green synthesis of zirconium-MOFs. CrystEngComm 2015, 17, 4070−4074. \n(7) Feng, D.; Gu, Z.; Chen, Y.; Park, J.; Wei, Z.; Sun, Y.; Bosch, M.; Yuan, S.; Zhou, H. A Highly Stable Porphyrinic Zirconium MetalOrganic Framework with shp-a Topology. J. Am. Chem. Soc. 2014, 136, 17714−17717. \n(8) Feng, D.; Wang, K.; Su, J.; Liu, T.; Park, J.; Wei, Z.; Bosch, M.; Yakovenko, A.; Zou, X.; Zhou, H. A Highly Stable Zeotype Mesoporous Zirconium Metal-Organic Framework with Ultralarge Pores. Angew. Chem., Int. Ed. 2015, 54, 149−154. \n(9) Cavka, J.; Jakobsen, S.; Olsbye, U.; Guillou, N.; Lamberti, C.; Bordiga, S.; Lillerud, K. A new zirconium inorganic building brick forming metal organic frameworks with exceptional stability. J. Am. Chem. Soc. 2008, 130, 13850−13851. \n(10) Schaate, A.; Roy, P.; Preusse, T.; Lohmeier, S.; Godt, A.; Behrens, P. Porous Interpenetrated Zirconium-Organic Frameworks (PIZOFs): A Chemically Versatile Family of Metal-Organic Frameworks. Chem. - Eur. J. 2011, 17, 9320−9325. \n(11) Wang, R.; Wang, Z.; Xu, Y.; Dai, F.; Zhang, L.; Sun, D. Porous Zirconium Metal-Organic Framework Constructed from 2D $_->$ 3D Interpenetration Based on a 3,6-Connected kgd Net. Inorg. Chem. 2014, 53, 7086−7088. \n(12) Ma, J.; Wong-Foy, A.; Matzger, A. The Role of Modulators in Controlling Layer Spacings in a Tritopic Linker Based Zirconium 2D Microporous Coordination Polymer. Inorg. Chem. 2015, 54, 4591− 4593. \n(13) Yuan, S.; Lu, W.; Chen, Y.; Zhang, $\\mathrm{Q.;}$ Liu, T.; Feng, D.; Wang, X.; Qin, J.; Zhou, H. Sequential Linker Installation: Precise Placement of Functional Groups in Multivariate Metal-Organic Frameworks. J. Am. Chem. Soc. 2015, 137, 3177−3180. \n(14) Zhang, M.; Chen, Y.; Bosch, M.; Gentle, T.; Wang, K.; Feng, D.; Wang, Z.; Zhou, H. Symmetry-Guided Synthesis of Highly Porous Metal-Organic Frameworks with Fluorite Topology. Angew. Chem., Int. Ed. 2014, 53, 815−818. \n(15) Morris, W.; Volosskiy, B.; Demir, S.; Gandara, F.; McGrier, P.; Furukawa, H.; Cascio, D.; Stoddart, J.; Yaghi, O. Synthesis, Structure, (16) Bon, V.; Senkovska, I.; Weiss, M.; Kaskel, S. Tailoring of network dimensionality and porosity adjustment in Zr- and Hf-based MOFs. CrystEngComm 2013, 15, 9572−9577. \n(17) Liu, T.; Feng, D.; Chen, Y.; Zou, L.; Bosch, M.; Yuan, S.; Wei, Z.; Fordham, S.; Wang, K.; Zhou, H. Topology-Guided Design and Syntheses of Highly Stable Mesoporous Porphyrinic Zirconium MetalOrganic Frameworks with High Surface Area. J. Am. Chem. Soc. 2015, 137, 413−419. \n(18) Liang, W.; Chevreau, H.; Ragon, F.; Southon, P.; Peterson, V.; D’Alessandro, D. Tuning pore size in a zirconium-tricarboxylate metalorganic framework. CrystEngComm 2014, 16, 6530−6533. \n(19) Wang, T.; Bury, W.; Gomez-Gualdron, D.; Vermeulen, N.; Mondloch, J.; Deria, P.; Zhang, K.; Moghadam, P.; Sarjeant, A.; Snurr, R.; Stoddart, J.; Hupp, J.; Farha, O. Ultrahigh Surface Area Zirconium MOFs and Insights into the Applicability of the BET Theory. J. Am. Chem. Soc. 2015, 137, 3585−3591. \n(20) Deria, P.; Gomez-Gualdron, D.; Bury, W.; Schaef, H.; Wang, T.; Thallapally, P.; Sarjeant, A.; Snurr, R.; Hupp, J.; Farha, O. Ultraporous, Water Stable, and Breathing Zirconium-Based Metal-Organic Frameworks with ftw Topology. J. Am. Chem. Soc. 2015, 137, 13183−13190. (21) Mondloch, J.; Bury, W.; Fairen-Jimenez, D.; Kwon, S.; DeMarco, E.; Weston, M.; Sarjeant, A.; Nguyen, S.; Stair, P.; Snurr, R.; Farha, O.; Hupp, J. Vapor-Phase Metalation by Atomic Layer Deposition in a Metal-Organic Framework. J. Am. Chem. Soc. 2013, 135, 10294−10297. \n(22) Furukawa, H.; Gandara, F.; Zhang, Y.; Jiang, J.; Queen, W.; Hudson, M.; Yaghi, O. Water Adsorption in Porous Metal-Organic Frameworks and Related Materials. J. Am. Chem. Soc. 2014, 136, 4369−4381. \n(23) Gutov, O.; Bury, W.; Gomez-Gualdron, D.; Krungleviciute, V.; Fairen-Jimenez, D.; Mondloch, J.; Sarjeant, A.; Al-Juaid, S.; Snurr, R.; Hupp, J.; Yildirim, T.; Farha, O. Water-Stable Zirconium-Based MetalOrganic Framework Material with High-Surface Area and Gas-Storage Capacities. Chem. - Eur. J. 2014, 20, 12389−12393. \n(24) Bueken, B.; Reinsch, H.; Reimer, N.; Stassen, I.; Vermoortele, F.; Ameloot, R.; Stock, N.; Kirschhock, C.; De Vos, D. A zirconium squarate metal-organic framework with modulator-dependent molecular sieving properties. Chem. Commun. 2014, 50, 10055−10058. (25) Feng, D.; Gu, Z.; Li, J.; Jiang, H.; Wei, Z.; Zhou, H. ZirconiumMetalloporphyrin PCN-222: Mesoporous Metal-Organic Frameworks with Ultrahigh Stability as Biomimetic Catalysts. Angew. Chem., Int. Ed. 2012, 51, 10307−10310. \n(26) Bon, V.; Senkovska, I.; Baburin, I.; Kaskel, S. Zr- and Hf-Based Metal-Organic Frameworks: Tracking Down the Polymorphism. Cryst. Growth Des. 2013, 13, 1231−1237. \n(27) Bon, V.; Senkovskyy, V.; Senkovska, I.; Kaskel, S. $\\mathrm{Zr(IV)}$ and $\\mathrm{Hf(IV)}$ based metal-organic frameworks with reo-topology. Chem. Commun. 2012, 48, 8407−8409. \n(28) Wang, B.; Lv, X.-L.; Feng, D.; Xie, L.-H.; Zhang, J.; Li, M.; Xie, Y.; Li, J.-R.; Zhou, H.-C. Highly Stable $\\mathrm{{Zr}(I V)}$ -Based Metal−Organic Frameworks for the Detection and Removal of Antibiotics and Organic Explosives in Water. J. Am. Chem. Soc. 2016, 138, 6204−6216. (29) Øien-Ødegaard, S.; Bouchevreau, B.; Hylland, K.; Wu, L.; Blom, R.; Grande, C.; Olsbye, U.; Tilset, M.; Lillerud, K. P. UiO-67-type Metal−Organic Frameworks with Enhanced Water Stability and Methane Adsorption Capacity. Inorg. Chem. 2016, 55, 1986−1991. (30) Hu, Z.; Faucher, S.; Zhuo, Y.; Sun, Y.; Wang, S.; Zhao, D. Combination of Optimization and Metalated-Ligand Exchange: An Effective Approach to Functionalize UiO-66 $\\left(\\mathrm{zr}\\right)$ MOFs for CO2 Separation. Chem. - Eur. J. 2015, 21, 17246−17255. \n(31) Yee, K.; Reimer, N.; Liu, J.; Cheng, S.; Yiu, S.; Weber, J.; Stock, N.; Xu, Z. Effective Mercury Sorption by Thiol-Laced Metal-Organic Frameworks: in Strong Acid and the Vapor Phase. J. Am. Chem. Soc. 2013, 135, 7795−7798. \n(32) Pullen, S.; Fei, H.; Orthaber, A.; Cohen, S.; Ott, S. Enhanced Photochemical Hydrogen Production by a Molecular Diiron Catalyst Incorporated into a Metal-Organic Framework. J. Am. Chem. Soc. 2013, 135, 16997−17003. \n(33) Biswas, S.; Zhang, J.; Li, Z.; Liu, Y.; Grzywa, M.; Sun, L.; Volkmer, D.; Van der Voort, P. Enhanced selectivity of CO2 over CH4 in sulphonate-, carboxylate- and iodo-functionalized UiO-66 frameworks. Dalton Trans. 2013, 42, 4730−4737. \n(34) Huang, Y.; Qin, W.; Li, Z.; Li, Y. Enhanced stability and CO2 affinity of a UiO-66 type metal-organic framework decorated with dimethyl groups. Dalton Trans. 2012, 41, 9283−9285. \n(35) Katz, M.; Brown, Z.; Colon, Y.; Siu, P.; Scheidt, K.; Snurr, R.; Hupp, J.; Farha, O. A facile synthesis of UiO-66, UiO-67 and their derivatives. Chem. Commun. 2013, 49, 9449−9451. \n(36) Biswas, S.; Van der Voort, P. A General Strategy for the Synthesis of Functionalised UiO-66 Frameworks: Characterisation, Stability and CO2 Adsorption Properties. Eur. J. Inorg. Chem. 2013, 2013, 2154−2160. \n(37) Garibay, S.; Cohen, S. Isoreticular synthesis and modification of frameworks with the UiO-66 topology. Chem. Commun. 2010, 46, 7700−7702. \n(38) Lin Foo, M.; Horike, S.; Fukushima, T.; Hijikata, Y.; Kubota, Y.; Takata, M.; Kitagawa, S. Ligand-based solid solution approach to stabilisation of sulphonic acid groups in porous coordination polymer Zr6O4(OH)(4) (BDC)(6) (UiO-66). Dalton Trans. 2012, 41, 13791−13794. \n(39) Fei, H.; Cohen, S. Metalation of a Thiocatechol-Functionalized Zr(IV)-Based Metal-Organic Framework for Selective C-H Functionalization. J. Am. Chem. Soc. 2015, 137, 2191−2194. \n(40) Jasuja, H.; Zang, J.; Sholl, D.; Walton, K. Rational Tuning of Water Vapor and CO2 Adsorption in Highly Stable $\\mathrm{Zr}$ -Based MOFs. J. Phys. Chem. C 2012, 116, 23526−23532. \n(41) Fei, H.; Shin, J.; Meng, Y.; Adelhardt, M.; Sutter, J.; Meyer, K.; Cohen, S. Reusable Oxidation Catalysis Using Metal-Monocatecholato Species in a Robust Metal-Organic Framework. J. Am. Chem. Soc. 2014, 136, 4965−4973. \n(42) Kandiah, M.; Nilsen, M.; Usseglio, S.; Jakobsen, S.; Olsbye, U.; Tilset, M.; Larabi, C.; Quadrelli, E.; Bonino, F.; Lillerud, K. Synthesis and Stability of Tagged UiO-66 Zr-MOFs. Chem. Mater. 2010, 22, 6632−6640. \n(43) Nickerl, G.; Senkovska, I.; Kaskel, S. Tetrazine functionalized zirconium MOF as an optical sensor for oxidizing gases. Chem. Commun. 2015, 51, 2280−2282. \n(44) Yang, $\\mathrm{Q.;}$ Vaesen, S.; Ragon, F.; Wiersum, A.; Wu, D.; Lago, A.; Devic, T.; Martineau, C.; Taulelle, F.; Llewellyn, P.; Jobic, H.; Zhong, C.; Serre, C.; De Weireld, G.; Maurin, G. A Water Stable MetalOrganic Framework with Optimal Features for CO2 Capture. Angew. Chem., Int. Ed. 2013, 52, 10316−10320. \n(45) Schaate, A.; Roy, P.; Godt, A.; Lippke, J.; Waltz, F.; Wiebcke, M.; Behrens, P. Modulated Synthesis of $\\mathrm{Zr}$ -Based Metal-Organic Frameworks: From Nano to Single Crystals. Chem. - Eur. J. 2011, 17, 6643−6651. \n(46) Tulig, K.; Walton, K. An alternative UiO-66 synthesis for HClsensitive nanoparticle encapsulation. RSC Adv. 2014, 4, 51080−51083. (47) Taddei, M.; Dau, P.; Cohen, S.; Ranocchiari, M.; van Bokhoven, J.; Costantino, F.; Sabatini, S.; Vivani, R. Efficient microwave assisted synthesis of metal-organic framework UiO-66: optimization and scale up. Dalton Trans. 2015, 44, 14019−14026. \n(48) Li, Y.; Liu, Y.; Gao, W.; Zhang, L.; Liu, W.; Lu, J.; Wang, Z.; Deng, Y. Microwave-assisted synthesis of UIO-66 and its adsorption performance towards dyes. CrystEngComm 2014, 16, 7037−7042. (49) Ren, J.; Langmi, H.; North, B.; Mathe, M.; Bessarabov, D. Modulated synthesis of zirconium-metal organic framework (ZrMOF) for hydrogen storage applications. Int. J. Hydrogen Energy 2014, 39, 890−895. \n(50) Anjum, M. W.; Vermoortele, F.; Khan, A. L.; Bueken, B.; De Vos, D. E.; Vankelecom, I. F. J. Modulated UiO-66-Based MixedMatrix Membranes for CO2 Separation. ACS Appl. Mater. Interfaces 2015, 7, 25193−25201. \n(51) Vandichel, M.; Hajek, J.; Vermoortele, F.; Waroquier, M.; De Vos, D.; Van Speybroeck, V. Active site engineering in UiO-66 type metal-organic frameworks by intentional creation of defects: a theoretical rationalization. CrystEngComm 2015, 17, 395−406. \n(52) Cliffe, M.; Wan, W.; Zou, X.; Chater, P.; Kleppe, A.; Tucker, M.; Wilhelm, H.; Funnell, N.; Coudert, F.; Goodwin, A. Correlated defect nanoregions in a metal-organic framework. Nat. Commun. 2014, 5, 4176. \n(53) Taylor, J.; Dekura, S.; Ikeda, R.; Kitagawa, H. Defect Control To Enhance Proton Conductivity in a Metal-Organic Framework. Chem. Mater. 2015, 27, 2286−2289. \n(54) Cliffe, M.; Hill, J.; Murray, C.; Coudert, F.; Goodwin, A. Defectdependent colossal negative thermal expansion in UiO-66(Hf) metalorganic framework. Phys. Chem. Chem. Phys. 2015, 17, 11586−11592. (55) Xydias, P.; Spanopoulos, I.; Klontzas, E.; Froudakis, G. E.; Trikalitis, P. N. Drastic enhancement of the CO2 adsorption properties in sulfone-functionalized $Z\\mathrm{{r}}.$ and Hf-UiO-67 MOFs with hierarchical mesopores. Inorg. Chem. 2014, 53, 679−81. \n(56) Van de Voorde, B.; Stassen, I.; Bueken, B.; Vermoortele, F.; De Vos, D.; Ameloot, R.; Tan, J.; Bennett, T. Improving the mechanical stability of zirconium-based metal-organic frameworks by incorporation of acidic modulators. J. Mater. Chem. A 2015, 3, 1737−1742. (57) Gutov, O.; Hevia, M.; Escudero-Adan, E.; Shafir, A. MetalOrganic Framework (MOF) Defects under Control: Insights into the Missing Linker Sites and Their Implication in the Reactivity of Zirconium-Based Frameworks. Inorg. Chem. 2015, 54, 8396−8400. (58) Vermoortele, F.; Bueken, B.; Le Bars, G.; Van de Voorde, B.; Vandichel, M.; Houthoofd, K.; Vimont, A.; Daturi, M.; Waroquier, M.; Van Speybroeck, V.; Kirschhock, C.; De Vos, D. Synthesis Modulation as a Tool To Increase the Catalytic Activity of Metal-Organic Frameworks: The Unique Case of UiO-66( $\\mathrm{{(}z r)}$ . J. Am. Chem. Soc. 2013, 135, 11465−11468. \n(59) Ren, J.; Langmi, H. W.; Musyoka, N. M.; Mathe, M.; Kang, X.; Liao, S. Tuning Defects to Facilitate Hydrogen Storage in Core-shell MIL-101(Cr)@UiO-66(Zr) Nanocrystals. Mater. Today: Proc. 2015, 2, 3964−3972. \n(60) Wu, H.; Chua, Y.; Krungleviciute, V.; Tyagi, M.; Chen, P.; Yildirim, T.; Zhou, W. Unusual and Highly Tunable Missing-Linker Defects in Zirconium Metal-Organic Framework UiO-66 and Their Important Effects on Gas Adsorption. J. Am. Chem. Soc. 2013, 135, 10525−10532. \n(61) Yang, D.; Odoh, S. O.; Borycz, J.; Wang, T. C.; Farha, O. K.; Hupp, J. T.; Cramer, C. J.; Gagliardi, L.; Gates, B. C. Tuning Zr-6 Metal-Organic Framework (MOF) Nodes as Catalyst Supports: Site Densities and Electron-Donor Properties Influence Molecular Iridium Complexes as Ethylene Conversion Catalysts. ACS Catal. 2016, 6, 235−247. \n(62) Liang, W.; Coghlan, C. J.; Ragon, F.; Rubio-Martinez, M.; D’Alessandro, D. M.; Babarao, R. Defect engineering of UiO-66 for CO2 and H2O uptake - a combined experimental and simulation study. Dalton Transactions 2016, 45, 4496−4500. \n(63) Li, B.; Zhu, X.; Hu, K.; Li, Y.; Feng, J.; Shi, J.; Gu, J. Defect creation in metal-organic frameworks for rapid and controllable decontamination of roxarsone from aqueous solution. J. Hazard. Mater. 2016, 302, 57−64. \n(64) Wang, K.; Li, C.; Liang, Y.; Han, T.; Huang, H.; Yang, $\\mathrm{Q.;}$ Liu, D.; Zhong, C. Rational construction of defects in a metal-organic framework for highly efficient adsorption and separation of dyes. Chem. Eng. J. 2016, 289, 486−493. \n(65) Shearer, G. C.; Chavan, S.; Ethiraj, J.; Vitillo, J. G.; Svelle, S.; Olsbye, U.; Lamberti, C.; Bordiga, S.; Lillerud, K. P. Tuned to Perfection: Ironing Out the Defects in Metal−Organic Framework UiO-66. Chem. Mater. 2014, 26, 4068−4071. \n(66) Piscopo, C.; Polyzoidis, A.; Schwarzer, M.; Loebbecke, S. Stability of UiO-66 under acidic treatment: Opportunities and limitations for post-synthetic modifications. Microporous Mesoporous Mater. 2015, 208, 30−35. \n(67) Bristow, J. K.; Svane, K. L.; Tiana, D.; Skelton, J. M.; Gale, J. D.; Walsh, A. Free Energy of Ligand Removal in the Metal−Organic Framework UiO-66. J. Phys. Chem. C 2016, 120, 9276. (68) Thornton, A. W.; Babarao, R.; Jain, A.; Trousselet, F.; Coudert, F. X. Defects in metal-organic frameworks: a compromise between adsorption and stability? Dalton Transactions 2016, 45, 4352−4359. (69) Vermoortele, F.; Vandichel, M.; Van de Voorde, B.; Ameloot, R.; Waroquier, M.; Van Speybroeck, V.; De Vos, D. Electronic Effects of Linker Substitution on Lewis Acid Catalysis with Metal-Organic Frameworks. Angew. Chem., Int. Ed. 2012, 51, 4887−4890. \n(70) Katz, M.; Klet, R.; Moon, S.; Mondloch, J.; Hupp, J.; Farha, O. One Step Backward Is Two Steps Forward: Enhancing the Hydrolysis Rate of UiO-66 by Decreasing [OH-]. ACS Catal. 2015, 5, 4637− 4642. \n(71) Canivet, J.; Vandichel, M.; Farrusseng, D. Origin of highly active metal-organic framework catalysts: defects? Defects! Dalton Trans. 2016, 45, 4090. \n(72) Nasalevich, M. A.; Hendon, C. H.; Santaclara, J. G.; Svane, K.; van der Linden, B.; Veber, S. L.; Fedin, M. V.; Houtepen, A. J.; van der Veen, M. A.; Kapteijn, F.; Walsh, A.; Gascon, J. Electronic origins of photocatalytic activity in d(0) metal organic frameworks. Sci. Rep. 2016, 6, 23676. \n(73) Ghosh, P.; Colon, Y.; Snurr, R. Water adsorption in UiO-66: the importance of defects. Chem. Commun. 2014, 50, 11329−11331. (74) Howarth, A.; Liu, Y.; Hupp, J.; Farha, O. Metal-organic frameworks for applications in remediation of oxyanion/cationcontaminated water. CrystEngComm 2015, 17, 7245−7253. \n(75) DeCoste, J. B.; Demasky, T. J.; Katz, M. J.; Farha, O. K.; Hupp, J. T. A UiO-66 analogue with uncoordinated carboxylic acids for the broad-spectrum removal of toxic chemicals. New J. Chem. 2015, 39, 2396−2399. \n(76) Trickett, C.; Gagnon, K.; Lee, S.; Gandara, F.; Burgi, H.; Yaghi, O. Definitive Molecular Level Characterization of Defects in UiO-66 Crystals. Angew. Chem., Int. Ed. 2015, 54, 11162−11167. \n(77) Øien, S.; Wragg, D.; Reinsch, H.; Svelle, S.; Bordiga, S.; Lamberti, C.; Lillerud, K. Detailed Structure Analysis of Atomic Positions and Defects in Zirconium Metal-Organic Frameworks. Cryst. Growth Des. 2014, 14, 5370−5372. \n(78) Valenzano, L.; Civalleri, B.; Chavan, S.; Bordiga, S.; Nilsen, M.; Jakobsen, S.; Lillerud, K.; Lamberti, C. Disclosing the Complex Structure of UiO-66 Metal Organic Framework: A Synergic Combination of Experiment and Theory. Chem. Mater. 2011, 23, 1700−1718. \n(79) Ling, S.; Slater, B. Dynamic acidity in defective UiO-66. Chemical Science 2016, DOI: 10.1039/C5SC04953A. \n(80) Han, Y.; Liu, M.; Li, K.; Zuo, Y.; Wei, Y.; Xu, S.; Zhang, G.; Song, C.; Zhang, Z.; Guo, X. Facile synthesis of morphology and sizecontrolled zirconium metal-organic framework UiO-66: the role of hydrofluoric acid in crystallization. CrystEngComm 2015, 17, 6434− 6440. \n(81) Waitschat, S.; Wharmby, M.; Stock, N. Flow-synthesis of carboxylate and phosphonate based metal-organic frameworks under non-solvothermal reaction conditions. Dalton Trans. 2015, 44, 11235− 11240. \n(82) Nouar, F.; Breeze, M.; Campo, B.; Vimont, A.; Clet, G.; Daturi, M.; Devic, T.; Walton, R.; Serre, C. Tuning the properties of the UiO66 metal organic framework by Ce substitution. Chem. Commun. 2015, 51, 14458−14461. \n(83) Guillerm, V.; Ragon, F.; Dan-Hardi, M.; Devic, T.; Vishnuvarthan, M.; Campo, B.; Vimont, A.; Gross, S.; Serre, C. A Series of Isoreticular, Highly Stable, Porous Zirconium Oxide Based Metal−Organic Frameworks. Angew. Chem., Int. Ed. 2012, 51, 9267− 9271. \n(84) Shearer, G.; Forselv, S.; Chavan, S.; Bordiga, S.; Mathisen, K.; Bjørgen, M.; Svelle, S.; Lillerud, K. In Situ Infrared Spectroscopic and Gravimetric Characterisation of the Solvent Removal and Dehydroxylation of the Metal Organic Frameworks UiO-66 and UiO-67. Top. Catal. 2013, 56, 770−782. \n(85) Lawrence, M. C.; Schneider, C.; Katz, M. J. Determining the structural stability of UiO-67 with respect to time: a solid-state NMR investigation. Chem. Commun. 2016, 52, 4971−4974. (86) Wiersum, A.; Soubeyrand-Lenoir, E.; Yang, $\\mathrm{Q.;}$ Moulin, B.; Guillerm, V.; Yahia, M. B.; Bourrelly, S.; Vimont, A.; Miller, S.; Vagner, C.; Daturi, M.; Clet, G.; Serre, C.; Maurin, G.; Llewellyn, P. An Evaluation of UiO-66 for Gas-Based Applications. Chem. - Asian J. 2011, 6, 3270−3280. \n(87) Colombo, V.; Galli, S.; Choi, H.; Han, G.; Maspero, A.; Palmisano, G.; Masciocchi, N.; Long, J. High thermal and chemical stability in pyrazolate-bridged metal-organic frameworks with exposed metal sites. Chem. Sci. 2011, 2, 1311−1319. \n(88) Nimmermark, A.; Ohrstrom, L.; Reedijk, J. Metal-ligand bond lengths and strengths: are they correlated? A detailed CSD analysis. Z. Kristallogr. - Cryst. Mater. 2013, 228, 311−317. \n(89) Bu, X.-H.; Li, N.; Xu, J.; Feng, R.; Hu, T.-L. Governing metal−organic frameworks towards high stability. Chem. Commun. 2016, DOI: 10.1039/C6CC02931K. \n(90) Bosch, M.; Zhang, M.; Zhou, H.-C. Increasing the Stability of Metal-Organic Frameworks. Adv. Chem. 2014, 2014, 182327. \n(91) Feng, D.; Wang, K.; Wei, Z.; Chen, Y.; Simon, C.; Arvapally, R.; Martin, R.; Bosch, M.; Liu, T.; Fordham, S.; Yuan, D.; Omary, M.; Haranczyk, M.; Smit, B.; Zhou, H. Kinetically tuned dimensional augmentation as a versatile synthetic route towards robust metalorganic frameworks. Nat. Commun. 2014, 5, 5723. " + }, + { + "id": "10.1080_21663831.2016.1153004", + "DOI": "10.1080/21663831.2016.1153004", + "DOI Link": "http://dx.doi.org/10.1080/21663831.2016.1153004", + "Relative Dir Path": "mds/10.1080_21663831.2016.1153004", + "Article Title": "Back stress strengthening and strain hardening in gradient structure", + "Authors": "Yang, MX; Pan, Y; Yuan, FP; Zhu, YT; Wu, XL", + "Source Title": "MATERIALS RESEARCH LETTERS", + "Abstract": "We report significant back stress strengthening and strain hardening in gradient structured (GS) interstitial-free (IF) steel. Back stress is long-range stress caused by the pileup of geometrically necessary dislocations (GNDs). A simple equation and a procedure are developed to calculate back stress basing on its formation physics from the tensile unloading-reloading hysteresis loop. The gradient structure has mechanical incompatibility due to its grain size gradient. This induces strain gradient, which needs to be accommodated by GNDs. Back stress not only raises the yield strength but also significantly enhances strain hardening to increase the ductility. [GRAPHICS] .", + "Times Cited, WoS Core": 1013, + "Times Cited, All Databases": 1054, + "Publication Year": 2016, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000385011000003", + "Markdown": "# Back stress strengthening and strain hardening in gradient structure \n\nMuxin Yang, Yue Pan, Fuping Yuan, Yuntian Zhu & Xiaolei Wu \n\nTo cite this article: Muxin Yang, Yue Pan, Fuping Yuan, Yuntian Zhu & Xiaolei Wu (2016): Back stress strengthening and strain hardening in gradient structure, Materials Research Letters, DOI: 10.1080/21663831.2016.1153004 \n\nTo link to this article: http://dx.doi.org/10.1080/21663831.2016.1153004 \n\n# Back stress strengthening and strain hardening in gradient structure \n\nMuxin Yanga, Yue Pan $^{\\mathrm{a,d}}_{.}$ , Fuping Yuana, Yuntian Zhub,c and Xiaolei Wua∗ $a$ Chinese Academy of Sciences, State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, 15 Beisihuan West Road, Beijing 100190, China; $b$ Department of Materials Science and Engineering, North Carolina State University, Campus Box 7919, Raleigh, NC 27695, USA; cSchool of Materials Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China; dIntern, from School of Aerospace Engineering and Applied Mechanics, Tongji University, No. 1239 Siping Road, Shanghai 200092, China \n\n(Received 14 January 2016; final form 8 February 2016) \n\nWe report significant back stress strengthening and strain hardening in gradient structured (GS) interstitial-free (IF) steel. Back stress is long-range stress caused by the pileup of geometrically necessary dislocations (GNDs). A simple equation and a procedure are developed to calculate back stress basing on its formation physics from the tensile unloading–reloading hysteresis loop. The gradient structure has mechanical incompatibility due to its grain size gradient. This induces strain gradient, which needs to be accommodated by GNDs. Back stress not only raises the yield strength but also significantly enhances strain hardening to increase the ductility. \n\n![](images/d932975b24f189cde73edc4e99b58c55ca204a2a0a85725f560aa930fe069aa6.jpg) \nKeywords: Back Stress, Geometrically Necessary Dislocations, Work Hardening, Ductility, Gradient Structure \n\nImpact Statement: Gradient structure leads to high back stress hardening to increase strength and ductility. A physically soun equation is derived to calculate the back stress from an unloading/reloading hysteresis loop. \n\nGradient structure in metals represents a new strategy for producing a superior combination of high strength and good ductility.[1–6] The gradient structure usually consists of a nanostructured (NS) surface layer with increasing grain size along the depth to reach coarse-grained (CG) sizes in the central layer.[2,4] \n\nGradient structure can promote ductility significantly,[2,4–9] which is measured under tensile loading. The NS layer in a gradient structure may sustain a large amount of tensile strain,[2,4] because they are constrained by the CG layer. It was reported that the gradient structured (GS) Cu derives its ductility from the confinement of the soft CG core,[2,10] and from strong grain growth in the NS layer by mechanically driven grain growth during tensile deformation. Nanostructures in high-purity copper are known to be unstable at room temperature, and mechanicaldriven grain growth in nanocrystalline metals has been extensively reported.[11–16] For GS metals with stable gradient structures, however, their high ductility is attributed to extra strain hardening due to the presence of strain gradient and the change of stress states, which generates geometrically necessary dislocations (GNDs) and promotes the generation and interaction of dislocations.[3,4,17, 18] Furthermore, the gradient structure is observed to produce an intrinsic synergetic strengthening, with its yield strength much higher than that calculated by the rule of mixture from separate gradient layers,[3] which is attributed to the macroscopic stress gradient and plastic incompatibility between layers.[3,4] \n\nThe nature of plastic deformation in the gradient structure is still not very clear.[1,2] In fact, the gradient structure can be approximately regarded as the integration of many thin layers with increasing grain sizes.[3,4] The gradient structure deforms heterogeneously due to plastic incompatibilities between neighboring layers with different flow behaviors and stresses under applied strains. As such, it is reasonable to anticipate the development of the strain gradient and internal stresses during plastic deformation, as a result of the plastic incompatibilities between different layers, similar to what happens in composites [19–21] and dual-phase structures.[22] \n\nBack stress has been reported to play a crucial role in strain hardening, strengthening and mechanical properties.[21–23] It is a type of long-range stress exerted by GNDs that are accumulated and piled up against barriers. It interacts with mobile dislocations to affect their slip.[24] The back stress reduces the effective resolved shear stress for dislocation slip because it always acts in the opposite direction of the applied resolved shear stress. In a heterogeneous structure, strain will be inhomogeneous but continuous, producing strain gradients, which needs to be accommodated by GNDs.[23,25–27] It has been observed that back stress strengthening and back stress strain-hardening are primarily responsible for unprecedented combination of strength and ductility of heterogeneous lamella Ti, which was found as strong as ultrafine-grained Ti and as ductile as CG Ti.[23] The gradient structure can be regarded as a type of heterogeneous structure. Therefore, it is reasonable to assume that significant back stress will be developed in gradient structure, which should be investigated to have a better understanding on the fundamentals of gradient structure. \n\nHere we report for the first time unambiguous experimental evidences of significant back stress hardening in GS IF steel. We will also derive an equation with sound physics to calculate back stress from an unloading–reloading stress–strain hysteresis loop during a tensile test. A detailed procedure on how to extract useful data from the hysteresis loop for calculating the back stress is presented. \n\nA $1{-}\\mathrm{mm}$ thick sheet of interstitial-free (IF) steel was used as the starting materials with the composition $(\\mathrm{wt\\%})$ ) $0.003\\%\\mathrm{C}$ , $0.08\\%$ Mn, $0.009\\%$ Si, $0.008\\%$ S, $0.011\\%$ P, $0.037\\%$ Al, $0.063\\%$ Ti, and $38\\mathrm{ppm}\\mathrm{~N~}$ . The disk of a $100\\mathrm{mm}$ diameter was cut and annealed at $1173\\mathrm{K}$ for 1 hour to obtain a homogeneous CG microstructure with a mean grain size of $35\\upmu\\mathrm{m}$ . Surface mechanical attrition treatment (SMAT) [28] was used to produce the GS sample. The SMAT duration was 5 minutes for both sides of the disk. NS layer of 120 $\\upmu\\mathrm{m}$ thick was formed, which consists of, in sequence, the nanograins (minimum grain size of $<100\\mathrm{nm}$ in the top layer), ultrafine grains, and deformed coarse grains with dislocation cells towards the central CG core. Microstructural characterization was detailed in our previous papers.[3,4] \n\nUnloading–reloading process during tensile tests was conducted using an Instron 5966 machine at a strain rate of $5\\times10^{-4}\\mathrm{s}^{-1}$ at room temperature. Tensile specimens with a gauge length of $10\\mathrm{mm}$ and a width of $2.5\\mathrm{mm}$ were cut from SMAT-processed disks. An extensometer was used to measure tensile strain. At a certain unloading strain, the specimen was unloaded in a load-control mode to $20~\\mathrm{N}$ at an unloading rate of $200\\mathrm{{Nmin^{-1}}}$ , followed by reloading to the same applied load. \n\nFigure 1(a) shows the monotonic tensile true stress– true strain $(\\sigma-\\varepsilon)$ curves in both GS and CG samples. The GS sample shows large tensile ductility comparable to that of CG, but with triple yield strength of CG, which is typical of the excellent combination of strength and ductility in GS metals.[2–8] A transient is visible soon after yielding, characterized by the presence of a short concave segment on the $\\sigma{-}\\varepsilon$ curve.[4] During the transient, the strain hardening rate $\\left(\\Theta\\right)$ sharply drops at first, which is followed by a rapid up-turn, as shown in Figure 1(b). Figure 1(c) shows the unloading and reloading test hysteresis loops measured at varying tensile strains for both CG and GS samples. \n\n![](images/78585db3da3b4d8a3a84989f3ab1bd2c8b17f9f36ed873587384b4def938b1e3.jpg) \nFigure 1. (Colour online) (a) Tensile stress–strain curves in the GS and CG IF steel samples. (b) Strain hardening rate $\\Theta=\\mathrm{d}\\sigma/\\mathrm{d}\\varepsilon$ ) vs. strain. (c) The unloading and reloading test hysteresis loops measured at varying tensile strains for both CG and GS samples. \n\nUnloading–reloading was performed at varying tensile strains to investigate the evolution of back stress during tensile test. Figure 2(a) shows schematically the unloading–reloading stress–strain hysteresis loop. As shown, the unloading starts at unloading strains $\\left(\\varepsilon_{\\mathrm{u}}\\right)$ at point A. The segment AB of the unloading curve is quasi-elastic and caused by stress relaxation [29] or viscous flow of the material.[30,31] The stress drop in this segment is called the thermal component of the flow stress.[24,29] or viscous stress.[30,31] The segment BC is the linear (elastic) part of the unloading stress with an effective unloading Young’s modulus of $E_{\\mathrm{u}}$ . The point C is called the unloading yielding point, with a stress of $\\sigma_{\\mathrm{u}}$ . Similar segments also exist for the reloading curve with EF as the linear (elastic) part of the reloading stress– strain curve with an effective reloading Young’s modulus of $E_{\\mathrm{r}}$ , which can be assumed equal to $E_{\\mathrm{u}}$ because the microstructure is assumed not changed during the unloading–reloading. The point F is called the reloading yielding point, with a stress of $\\sigma_{\\mathrm{r}}$ . Figure 2(b) is the measured hysteresis loop from a GS IF steel sample. \n\nFrom the unloading–reloading hysteresis loop, we can calculate the back stress $\\sigma_{\\boldsymbol{\\mathrm{b}}}$ , and the frictional stress $\\sigma_{\\mathrm{f}}$ . The back stress is always in the opposite direction of the applied stress, while frictional stress is always in the direction that opposes the motion of dislocations. The frictional stress consists of the Peierls stress as well as other stresses that are needed to overcome the dynamic pinning of dislocations such as solute atoms, second phase, forest dislocations, dislocation debris, dislocation jogs, etc. \n\nTo derive the equation for calculating the back stress and frictional stress, we first assume that the frictional stress $\\sigma_{\\mathrm{f}}$ is a constant during the entire unloading– reloading process. We also assume that the back stress does not change with unloading before the unloading yield point C in Figure 2(a). This assumption is reasonable because the reverse dislocation motion does not start above this point. In other words, GNDs that produce the back stress do not change their density or configuration before the unloading yield, which keeps the back stress approximately constant. This assumption is important and was also adopted by Dickson et al.[29] During the unloading, the back stress is the stress that drives the mobile dislocations to reverse their gliding direction to produce unloading yield. At the unloading yield point C (Figure 2(a)), the applied stress is low enough that the back stress starts to overcome the applied stress and the frictional stress to make dislocations glide backward, that is \n\n$$\n\\sigma_{\\mathrm{b}}=\\sigma_{\\mathrm{u}}+\\sigma_{\\mathrm{f}},\n$$ \n\nwhere $\\sigma_{\\mathrm{u}}$ is the unloading yield stress as defined in Figure 2(a). \n\nDuring the reloading, the applied stress needs to overcome the back stress and the frictional stress to drive the dislocation forward at the reloading yield point F, which can be described as \n\n$$\n\\sigma_{\\mathrm{r}}=\\sigma_{\\mathrm{b}}+\\sigma_{\\mathrm{f}},\n$$ \n\nwhere $\\sigma_{r}$ is the reloading yield stress as defined in Figure 2(a). \n\nHere again, we assume that the back stress during reloading is the same as the back stress during unloading. This is reasonable because during the unloading– reloading process, dislocation configuration can be considered reversible.[32] Solving Equations (1) and (2) yields \n\n$$\n\\sigma_{\\mathrm{b}}=\\frac{\\sigma_{\\mathrm{r}}+\\sigma_{\\mathrm{u}}}{2},\n$$ \n\nand \n\n$$\n\\sigma_{\\mathrm{f}}=\\frac{\\sigma_{\\mathrm{r}}-\\sigma_{\\mathrm{u}}}{2}.\n$$ \n\n![](images/e967963fd5428bcff7e0fe8333f21e5ada7fb2d3cfc5b4efb0477d44973b2a55.jpg) \nFigure 2. (Colour online) (a) The schematic of the unloading–reloading loop for defining the unload yielding $\\sigma_{\\mathrm{u}}$ , reload yielding $\\sigma_{\\mathrm{r}}$ , back stress $\\sigma_{\\boldsymbol{\\mathrm{b}}}$ and frictional stress $\\sigma_{\\mathrm{f}}$ , effective unloading Young’s modulus of $E_{\\mathrm{u}}$ , effective reloading Young’s modulus of $E_{\\mathrm{r}}$ (b) A measured hysteresis loop from the GS IF steel sample with $\\sigma_{\\mathrm{u}}$ and $\\sigma_{\\mathrm{r}}$ defined. \n\nEquation (3) is similar to an earlier equation proposed for cyclic loading by Cottrell [33] and KulmannWilsdorf and Laird,[32] except they used $\\sigma_{u0}$ , the initial flow stress at the beginning of the unloading, in place of the $\\sigma_{r}$ , that is \n\n$$\n\\sigma_{\\mathrm{b}}=\\frac{\\sigma_{\\mathrm{u0}}+\\sigma_{\\mathrm{u}}}{2},\n$$ \n\nwhere $\\sigma_{u0}$ is the initial unloading stress as defined in Figure 2(a). \n\nWe argue that Equation (3) is physically sounder than Equation (5) because we are defining unloading yield and reloading yield using the same criterion, that is, the same deviation of effective Young’s modulus as discussed later. It has been recognized that Equation (5) overestimates the back stress, and was later modified by Dickson et al. to include the thermal component of the flow stress:[24,29] \n\n$$\n\\sigma_{\\mathrm{b}}=\\frac{\\sigma_{\\mathrm{0}}+\\sigma_{\\mathrm{u}}}{2}-\\frac{\\sigma*}{2}\n$$ \n\nwhere $\\sigma^{*}$ is the thermal component of the flow stress as defined in Figure 2(a),[24,29] which is also called the viscous stress. [31] \n\nEquation (3) is especially suitable for hysteresis loops with positive unloading yield stresses. If the back stress is very small, the unloading yield stress may become negative, in which case $\\sigma_{\\mathrm{u}}$ cannot be measured during unloading. However, we expect Equation (3) to be valid if the applied stress is reversed to negative to measure $\\sigma_{\\mathrm{u}}$ before the reloading. As discussed later, Equation (3) derived here has an important advantage over previously published Equations (5) and (6): it produces consistent back stress values with much less scatter. In addition, Equations (5) and (6) are physically problematic because they implicitly used different criteria to define the unloading yield and reloading yield, which is physically unjustifiable. \n\nTo extract useful data from the unloading–reloading hysteresis loop, one needs to first determine the unloading yield stress $\\sigma_{\\mathrm{u}}$ and reloading yield stress $\\sigma_{\\mathrm{r}}$ . However, the real hysteresis loop (e.g. Figure 2(b)) is not as well defined as in Figure 2(a), and the practical extraction of the data is not straightforward.[31] The first step is to determine the elastic segments BC as well as its slope (the effective Young’s modulus). The unloading yield point C is usually determined by a plastic strain offset in the range of $5\\times10^{-6}$ to $10^{-3}$ , which have been used by different research groups.[24,31,34–37] These offset values are arbitrary and are not well justified. Here we propose to use the deviation of the stress–strain slope from the effective Young’s modulus as a physically sound method to determine the yield point. In this study, we choose $5\\%$ , $10\\%$ , and $15\\%$ slope reduction from the effective Young’s modulus, $E_{\\mathrm{u}}$ . If the strain hardening in the plastically deforming volume is ignored, the slope reduction should be equal to the volume fraction that is plastically deforming. For example, a $10\\%$ reduction in $E_{\\mathrm{u}}$ means $10\\%$ of the sample volume is plastically deforming. We also propose to use $E_{\\mathrm{r}}=E_{\\mathrm{u}}$ , and the same slope reduction values for determining both the unloading yield point and reloading yield point. \n\nFigure 3 compares the evolution of the unloading yield stress, reloading yield stress, and back stress of the CG and GS IF steel samples with increasing tensile strain at which the unloading was initiated. Several features can be seen from the figure. First, the unloading yield stress is affected more than the reloading yield stress by the slope reduction offset value that is used to determine them (Figure 3(a) and 3(c)). Second, using a larger slope reduction leads to lower unloading yield stress $\\sigma_{\\mathrm{u}}$ and higher reloading yield stress $\\sigma_{\\mathrm{r}}$ . Part of these variations in $\\sigma_{\\mathrm{u}}$ and $\\sigma_{\\mathrm{r}}$ caused by the choice of slope reduction cancel each other in Equation (3), which leads to smaller scatter in the calculated back stress using Equation 3 (Figure 3(b) and 3(d)). This is an advantage of Equation (3) for calculating the back stress, as compared with the previously reported Equation (6).[23, 24,29–31] Third, the back stresses in both the CG and GS samples increase with the tensile strain. However, the back stress is higher in the GS sample than in the CG sample. For example, for the $5\\%$ slope reduction, the back stress in the GS sample is $10\\text{\\textperthousand}$ higher than those in the CG sample (the red curves in Figure 3(b) and 3(d)). Fourth, Figure 3(c) and 3(d) shows that if a large slope reduction value is used, the unloading yield stresses for the GS sample at small tensile strains are negative and therefore cannot be measured in the unloading curve. This makes it advantageous to use a smaller slope reduction value in determining the back stress. \n\nFor valid and easy comparison, we propose that the slope reduction value for calculating the back stress is marked in the symbol. For example, $\\sigma_{\\ensuremath{\\mathrm{b}},5\\%}$ represents back stress calculated using $5\\%$ slope reduction from the effective Young’s modulus, as shown in Figure 3(b) and 3(d). Of course, there exist uncertainties in defining $E_{\\mathrm{u}}$ , $E_{\\mathrm{r}}$ , and the corresponding slope reductions due to the difficulties for determining the linear parts of both unloading and reloading curves; however, the consequences of these uncertainties appear to be small due to the method we used. \n\nAs shown in Figure 4(a), the frictional stress $\\sigma_{\\mathrm{f}}$ calculated using Equation (4) is very scattered. A larger slope reduction value leads to significantly higher $\\sigma_{\\mathrm{f}}.$ . For example, for the CG sample, the $\\sigma_{\\mathrm{f}}$ calculated using $20\\%$ slope reduction is many times larger than those calculated using the $5\\%$ slope reduction. This is because Equation (4) adds the absolute values of $\\sigma_{\\mathrm{u}}$ and $\\sigma_{\\mathrm{r}}$ variations together instead of making them cancel each other as in Equation (3). Therefore, the frictional stress $\\sigma_{\\mathrm{f}}$ calculated using Equation (4) is not quantitatively dependable. Nevertheless, Figure 4(a) consistently shows that for any slope reduction value, the calculated frictional stress is higher in the GS sample than in the CG sample. This is due to the higher dislocation density in the GS sample than in the CG sample.[3,4] \n\n![](images/8cf7eed2395b5eba61a268ea7602ea66a4e47fd3578943cacb14a7a1c9e9ed60.jpg) \nFigure 3. (Colour online) Evolution of (a) unloading yield stress $\\sigma_{\\mathrm{u}}$ and reloading yield stress $\\sigma_{\\mathrm{r}}$ and (b) back stress with increasing unloading strain $\\varepsilon_{\\mathrm{u}}$ for CG IF steel, and the evolution of (c) unloading/reloading yield stresses and (d) back stress with increasing $\\varepsilon_{\\mathrm{u}}$ for GS IF steel. $\\sigma_{\\ensuremath{\\mathrm{b}},5\\%}$ represents the back stress calculated using $5\\%$ slope reduction from the effective Young’s modulus. \n\nFigure $4(\\boldsymbol{\\mathrm{b}})$ shows that the GS sample has much higher back stress strain-hardening than the CG sample due to the heterogeneous microstructure, especially in the transient range that correlates to $\\Theta$ up-turn. This indicates that the back stress strain-hardening has significant contribution to the observed $\\Theta$ up-turn. The rapid back stress increase right after the yielding of the GS sample is also obvious in Figure 3(d). The observed $\\Theta$ upturn has been attributed to fast dislocation accumulation due to the back stress strain-hardening after the initial exhaustion of mobile dislocations.[4] The high back stress associated with the observed $\\Theta$ up-turn observed here suggests that a large quantity of GNDs is accumulated at this stage. Since the GNDs are associated with the strain gradient in the sample, this observation also suggests that there was a quick increase in the strain gradient at the beginning of the plastic deformation of the GS IF steel. This is understandable because this is at the deformation stage in which the NS surface layers just started to become unstable and the lateral (perpendicular to the tensile direction) stresses start to reverse their directions.[3,4] Specifically, the surface NS layers transit from compressive lateral stress to tensile laterals stress, while the central larger grained layer transits in an opposite way. Such a transition is expected to increase the strain gradient. \n\n![](images/a13b76e66a92f73c5037fe7c7ad4ebd22f330de423f566a257ccf6c599f2fcac.jpg) \nFigure 4. (Colour online) The frictional stress $\\sigma_{\\mathrm{f}}$ vs. tensile strain $\\varepsilon_{\\mathrm{true}}$ for the GS and CG IF steel samples calculated according to Equation (4). (b) The distinct back stress hardening in GS IF steel. $\\Theta_{\\mathrm{b}},5\\%^{\\mathrm{GS}}$ denotes the back stress hardening rate calculated using $5\\%$ slope reduction from the effective Young’s modulus. \n\nIn summary, it is found that the GS IF steel developed strong back stress strengthening and back stress strain-hardening during tensile testing, which arise from the plastic incompatibilities due to its microstructural heterogeneity. The high back stress near the beginning of the plastic deformation of the GS IF steel samples should have contributed to the observed synergetic strengthening,[3] while the high back stress hardening should have contributed to the observed high ductility.[4] The equation derived and the procedure proposed in this work for calculating the back stress from the unloading–reloading hysteresis loop produces more consistent back stress value than what is previously reported. \n\nAcknowledgements This work was supported by the National Natural Science Foundation of China under Grant numbers (11572328, 11072243, 11222224, 11472286, and 51471039); and 973 Projects under Grant numbers (2012CB932203, 2012CB937500, and 6138504). Y.T.Z. is funded by the US Army Research Office (W911 NF-12–1– 0009), the US National Science Foundation (DMT-1104667), and by the Jiangsu Key Laboratory of Advanced Micro&Nano Materials and Technology, Nanjing Univ of Sci and Technol. \n\nDisclosure statement No potential conflict of interest was reported by authors. \n\n# References \n\n[1] Lu K. Making strong nanomaterials ductile with gradients. Science. 2014;345(6203):1455–1456. \n[2] Fang TH, Li WL, Tao NR, Lu K. Revealing extraordinary intrinsic tensile plasticity in gradient nano-grained copper. Science. 2011;331(6024):1587–1590. \n[3] Wu XL, JIang P, Chen L,et al. Synergetic strengthening by gradient structure. Mater Res Lett. 2014;2(4): 185–191. [4] Wu XL, Jiang P, Chen L, Yuan FP, Zhu YT. Extraordinary strain hardening by gradient structure. Proc Natl Acad Sci USA. 2014;111(20):7197–7201. [5] Jerusalem A, Dickson W, Perez-Martin MJ, Dao M, Lu J, Galvez F, Grain size gradient length scale in ballistic properties optimization of functionally graded nanocrystalline steel plates. Scr Mater. 2013;69(11): 773–776. [6] Wang HT, Tao NR, Lu K. Architectured surface layer with a gradient nanotwinned structure in a Fe-Mn austenitic steel. Scr Mater. 2013;68(1):22–27. [7] Kou HN, Lu J, Li Y. High-strength and high-ductility nanostructured and amorphous metallic materials. Adv Mater. 2014;26(31):5518–5524. [8] Wei YJ, Li YQ, Zhu LC,et al. Evading the strengthductility trade-off dilemma in steel through gradient hierarchical nanotwins. Nat Comm. 2014;5: Article no. 3580. [9] Ma XL, Huang CX, Xu WZ, Zhou H, Wu XL, Zhu YT. Strain hardening and ductility in a coarsegrain/nanostructure laminate material. Scr Mater. 2015; 103:57–60. \n[10] Fang TH, Tao NR, Lu K. Tension-induced softening and hardening in gradient nanograined surface layer in copper. Scr Mater. 2014;77:17–20. \n[11] Weertman JR. Retaining the nano in nanocrystalline alloys. Science. 2012;337(6097):921–922. \n[12] Chookajorn T, Murdoch HA, Schuh CA. Design of stable nanocrystalline alloys. Science. 2012;337(6097): 951–954. \n[13] Zhang K, Weertman JR, Eastman JA. Rapid stress-driven grain coarsening in nanocrystalline Cu at ambient and cryogenic temperatures. Appl Phys Lett. 2005;87(6): Article no. 061921. \n[14] Zhang K, Weertman JR, Eastman JA. The influence of time, temperature, and grain size on indentation creep in high-purity nanocrystalline and ultrafine grain copper. Appl Phys Lett. 2004;85:5197–5199. \n[15] Legros M, Gianola DS, Hemker KJ. In situ TEM observations of fast grain-boundary motion in stressed nanocrystalline aluminum films. Acta Mater. 2008;56(14):3380– 3393. \n[16] Liao XZ, Kilmametov AR, Valiev RZ, Gao HS, Li XD, Mukherjee AK, Bingert JF, Zhu YT. Highpressure torsion-induced grain growth in electrodeposited nanocrystalline Ni. Appl Phys Lett. 2006;88: Article no. 021909. \n[17] Li WB, Yuan FP, Wu XL. Atomistic tensile deformation mechanisms of Fe with gradient nano-grained structure. AIP Advances. 2015;5(8): Article no. 087120. \n[18] Li JJ, Chen SH, Wu XL, Soh AK. A physical model revealing strong strain hardening in nano-grained metals induced by grain size gradient structure. Mater Sci Eng A. 2015;620:16–21. \n[19] Llorca J, Needleman A, Suresh S. The Bauschinger effect in whisker-reinforced metal-matrix composites. Scr Metall Mater. 1990;24(7):1203–1208. \n[20] Sinclair CW, Saada G, Embury JD. Role of internal stresses in co-deformed two-phase materials. Philos Mag. 2006;86(25–26):4081–4098. \n[21] Thilly L, Van Petegem S, Renault PO, Lecouturier F, Vidal V, Schmitt B, Van Swygenhoven H. A new criterion for elasto-plastic transition in nanomaterials: application to size and composite effects on Cu-Nb nanocomposite wires. Acta Mater. 2009;57(11):3157– 3169. \n[22] Calcagnotto M, Adachi Y, Ponge D, Raabe D. Deformation and fracture mechanisms in fine- and ultrafinegrained ferrite/martensite dual-phase steels and the effect of aging. Acta Mater. 2011;59:658–670. \n[23] Wu XL, Yang MX, Yuan FP, Wu GL, Wei YJ, Huang XX, Zhu YT. Heterogeneous lamella structure unites ultrafinegrain strength with coarse-grain ductility. Proc Natl Acad Sci USA. 2015;112(47):14501–14505. \n[24] Feaugas X. On the origin of the tensile flow stress in the stainless steel AISI 316L at $300~\\mathrm{K}$ : back stress and effective stress. Acta Mater. 1999;47(13):3617–3632. \n[25] Ashby MF. The deformation of plastically nonhomogeneous materials. Philos Mag. 1970;21(170): 399–424. \n[26] Gao H, Huang Y, Nix WD, Hutchinson JW. Mechanismbased strain gradient plasticity - I Theory. J Mech Phys Solids. 1999;47(6):1239–1263. \n[27] Gao HJ, Huang YG. Geometrically necessary dislocation and size-dependent plasticity. Scr Mater. 2003;48(2):113–118. \n[28] Lu K, Lu J. Nanostructured surface layer on metallic materials induced by surface mechanical attrition treatment. Mater Sci Eng A. 2004;375–377:38–45. \n[29] Dickson JI, Boutin J, Handfield L. A comparison of two simple methods for measuring cyclical internal and effective stresses. Mater Sci Eng. 1984;64(1):L7–L11. \n[30] Fournier B, Sauzay M, Caes C, Mottot M, Noblecourt A, Pineau A. Analysis of the hysteresis loops of a martensitic steel - Part II: study of the influence of creep and stress relaxation holding times on cyclic behaviour. Mater Sci Eng A. 2006;437:197–211. \n[31] Fournier B, Sauzay M, Caes C, Noblecourt M, Mottot M. Analysis of the hysteresis loops of a martensitic steel - Part I: study of the influence of strain amplitude and temperature under pure fatigue loadings using an enhanced stress partitioning method. Mater Sci Eng A. 2006;437:183–196. \n[32] Kuhlmann-Wilsdorf D, Laird C. Dislocation behavior in fatigue II. Friction stress and back stress as inferred from an analysis of hysteresis loops. Mater Sci Eng. 1979;37(2):111–120. \n[33] Cottrell AH. Dislocations and plastic flow in crystals. Oxford: Clarendon Press; 1953. \n[34] Delobelle P, Oytana C. The study of the laws of behavior at high-temperature, in plasticity-flow, of an austenitic stainless-steel (17–12-Sph). J Nucl Mater. 1986;139(3):204–227. \n[35] Risbet M, Feaugas X, Clavel M. Study of the cyclic softening of an under-aged gamma’-precipitated nickelbase superalloy (Waspaloy). Journal De Physique IV. 2001;11(PR4):293–301. \n[36] Guillemer-Neel C, Feaugas X, Clavel M. Mechanical behavior and damage kinetics in nodular cast iron: part II. Hardening and damage. Metall Mater Trans A. 2000;31(12):3075–3085. \n[37] Morrison DJ, Jia Y, Moosbrugger JC. Cyclic plasticity of nickel at low plastic strain amplitude: hysteresis loop shape analysis. Mater Sci Eng A. 2001;314(1):24–30. " + }, + { + "id": "10.1038_nature18593", + "DOI": "10.1038/nature18593", + "DOI Link": "http://dx.doi.org/10.1038/nature18593", + "Relative Dir Path": "mds/10.1038_nature18593", + "Article Title": "Single-layer MoS2 nullopores as nullopower generators", + "Authors": "Feng, JD; Graf, M; Liu, K; Ovchinnikov, D; Dumcenco, D; Heiranian, M; nulldigana, V; Aluru, NR; Kis, A; Radenovic, A", + "Source Title": "NATURE", + "Abstract": "Making use of the osmotic pressure difference between fresh water and seawater is an attractive, renewable and clean way to generate power and is known as 'blue energy'(1-3). Another electrokinetic phenomenon, called the streaming potential, occurs when an electrolyte is driven through narrow pores either by a pressure gradient(4) or by an osmotic potential resulting from a salt concentration gradient(5). For this task, membranes made of two-dimensional materials are expected to be the most efficient, because water transport through a membrane scales inversely with membrane thickness(5-7). Here we demonstrate the use of single-layer molybdenum disulfide (MoS2) nullopores as osmotic nullopower generators. We observe a large, osmotically induced current produced from a salt gradient with an estimated power density of up to 10(6) watts per square metre-a current that can be attributed mainly to the atomically thin membrane of MoS2. Low power requirements for nulloelectronic and optoelectric devices can be provided by a neighbouring nullogenerator that harvests energy from the local environment(8-11)-for example, a piezoelectric zinc oxide nullowire array(8) or single-layer MoS2 (ref. 12). We use our MoS2 nullopore generator to power a MoS2 transistor, thus demonstrating a self-powered nullosystem.", + "Times Cited, WoS Core": 944, + "Times Cited, All Databases": 1001, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000381472100033", + "Markdown": "# Single-layer MoS2 nanopores as nanopower generators \n\nJiandong Feng1, Michael Graf1, Ke Liu1, Dmitry Ovchinnikov2, Dumitru Dumcenco2, Mohammad Heiranian3, Vishal Nandigana3, Narayana R. Aluru3, Andras Kis2 & Aleksandra Radenovic1 \n\nMaking use of the osmotic pressure difference between fresh water and seawater is an attractive, renewable and clean way to generate power and is known as ‘blue energy’1–3. Another electrokinetic phenomenon, called the streaming potential, occurs when an electrolyte is driven through narrow pores either by a pressure gradient4 or by an osmotic potential resulting from a salt concentration gradient5. For this task, membranes made of two-dimensional materials are expected to be the most efficient, because water transport through a membrane scales inversely with membrane thickness5–7. Here we demonstrate the use of single-layer molybdenum disulfide $(\\mathbf{MoS}_{2})$ nanopores as osmotic nanopower generators. We observe a large, osmotically induced current produced from a salt gradient with an estimated power density of up to $\\mathbf{10^{6}}$ watts per square metre—a current that can be attributed mainly to the atomically thin membrane of $\\mathbf{MoS}_{2}$ . Low power requirements for nanoelectronic and optoelectric devices can be provided by a neighbouring nanogenerator that harvests energy from the local environment8–11—for example, a piezoelectric zinc oxide nanowire array8 or single-layer $\\mathbf{MoS}_{2}$ (ref. 12). We use our $\\mathbf{MoS}_{2}$ nanopore generator to power a $\\mathbf{MoS}_{2}$ transistor, thus demonstrating a self-powered nanosystem. \n\n$\\ensuremath{\\mathrm{MoS}}_{2}$ nanopores have already demonstrated better water-transport behaviour than graphene13,14 owing to the enriched hydrophilic surface sites (provided by the molybdenum) that are produced following either irradiation with transmission electron microscopy $(\\mathrm{TEM})^{15}$ or electrochemical oxidation16. The osmotic power is generated by separating two reservoirs containing potassium chloride (KCl) solutions of different concentrations with a freestanding $\\ensuremath{\\mathrm{MoS}}_{2}$ membrane, into which a single nanopore has been introduced13. A chemical potential gradient arises at the interface of these two liquids at a nanopore in a $0.65\\mathrm{-nm}$ -thick, single-layer $\\mathbf{MoS}_{2}$ membrane, and drives ions spontaneously across the nanopore, forming an osmotic ion flux towards the equilibrium state (Fig. 1a). The presence of surface charges on the pore screens the passing ions according to their charge polarity, and thus results in a net measurable osmotic current, known as reverse electrodialysis1. This cation selectivity can be better understood by analysing the concentration of each ion type (potassium and chloride) as a function of the radial distance from the centre of the pore, as we show here through molecular-dynamics simulations (Fig. 1b). \n\nWe fabricated $\\ensuremath{\\mathrm{MoS}}_{2}$ nanopores either by $\\mathrm{TEM}^{13}$ (Fig. 1c) or by the recently demonstrated electrochemical reaction (ECR) technique16. With a typical nanopore diameter in the range $2-25\\mathrm{nm}$ , a stable osmotic current can be expected, owing to the long time required for the system to reach equilibrium. We measured the osmotic current and voltage across the pore by using a pair of $\\mathrm{Ag/AgCl}$ electrodes to characterize the current–voltage $\\left(I-V\\right)$ response of the nanopore. \n\n![](images/090cb7d2c72dc5988d7b0fa01638f43581efed004dd682503c750779c4d62069.jpg) \nFigure 1 | Harvesting osmotic energy with $\\mathbf{MoS}_{2}$ nanopores. a, The experimental set-up. Salt solutions with different concentrations are separated by a $0.65\\mathrm{-nm}$ -thick $\\mathbf{MoS}_{2}$ nanopore membrane. An ion flux driven by chemical potential through the pore is screened by the negatively charged pore, forming a diffusion current composed of mostly positively charged ions. b, Top panel, a typical simulation box used in molecular-dynamics simulations, showing the nanopore membrane (in blue and yellow) and the salt (green and red) in solution. Bottom panel, molecular-dynamics-simulated potassium-ion and chloride-ion concentrations as a function of the radial distance from the centre of the pore. The region near the charged wall of the pore is representative of the electrical double layer. $C_{\\mathrm{max}},$ maximum concentration; $C_{\\mathrm{min}}\\mathrm{.}$ , minimum concentration. c, Example of a TEM-drilled $\\ensuremath{\\mathrm{MoS}}_{2}$ nanopore of diameter $5\\mathrm{nm}$ . \n\n![](images/0ffa73c36882b87da1a0a7864f8939f4b678dec38144cac6f7e2d8862cd0bb1a.jpg) \nigure 2 | Electrical conductance and chemical reactivity of the $\\mathbf{MoS}_{2}$ results to equation (1), we find the extracted surface charge values to be anopore. a, Current–voltage response of $\\ensuremath{\\mathrm{MoS}}_{2}$ nanopores with different $-0.024\\mathrm{Cm}^{-2}$ , $-0.053\\mathrm{Cm}^{-2}$ and $-0.088\\thinspace\\mathrm{Cm}^{-2}$ for a $2\\mathrm{-nm}$ , 6-nm and pore sizes (black, $2\\mathrm{nm}$ ; red, $6\\mathrm{nm}$ ; blue, $25\\mathrm{nm}$ ) in 1 M KCl at $\\mathrm{pH}5$ . $25\\mathrm{-nm}$ pore, respectively. c, Conductance as a function of pH for a KCl b, Conductance as a function of salt concentration at $\\mathrm{\\pH}5.$ By fitting the concentration of $10\\mathrm{mM}$ , for a $2\\mathrm{-nm}$ , $6\\mathrm{-nm}$ and $25\\mathrm{-nm}$ pore. \n\nTo gain a better insight into the performance of the $\\mathbf{MoS}_{2}$ nanopore power generator, we first characterized the ionic transport properties of $\\mathrm{MoS}_{2}$ nanopores under various ionic concentrations and $\\mathrm{\\pH}$ conditions, which can provide information on the surface charge of the $\\ensuremath{\\mathrm{MoS}}_{2}$ nanopore. Figure 2a shows the $I{-}V$ characteristics of $\\ensuremath{\\mathrm{MoS}}_{2}$ nano­ pores of various diameters. A large pore conductance originates from the ultrathin nature of the membrane. The conductance also depends on the salt concentration (Fig. 2b) and shows saturation at low salt concentrations—a signature of the presence of surface charge on the nanopore17,18. The predicted pore conductance $(G)$ , taking into account the contribution of the surface charge $(\\varSigma)$ , is given by19: \n\n$$\nG=\\kappa_{\\mathrm{b}}\\Bigg[\\frac{4L}{\\pi d^{2}}\\times\\frac{1}{1+4\\frac{l_{\\mathrm{Du}}}{d}}+\\frac{2}{\\alpha d+\\beta l_{\\mathrm{Du}}}\\Bigg]^{-1}\n$$ \n\nwhere $\\kappa_{\\mathrm{b}}$ is the bulk conductivity, $L$ is the pore length, $d$ is the pore diameter, $l_{\\mathrm{Du}}$ is the Dukhin length (which can be approximated by Σ /e  , where e is the elementary charge and cs is the salt concentration), $\\alpha$ is a geometrical prefactor that depends on the model used (here, $\\alpha=2)^{\\bar{1}9}$ , and $\\beta$ can also be approximated to be 2 to obtain the best fitting agreement19. From the fitting results shown in Fig. 2b, we find a surface charge value of $-0.024\\mathrm{Cm}^{-2}$ , $-0.053\\mathrm{Cm}^{-2}$ and $-0.088\\mathrm{Cm}^{-2}$ for pores of size $2\\mathrm{nm}$ , $6\\mathrm{nm}$ and $25\\mathrm{nm}$ , respectively, at $\\mathrm{pH}5$ . These values are comparable to those reported recently for graphene nano­pores $(-0.039\\mathrm{\\bar{C}}\\mathrm{m}^{-2})^{20}$ and nanotubes $(-0.\\dot{0}25\\dot{\\mathrm{C}}\\dot{\\mathrm{m}^{-2}}$ to $-0.125\\mathrm{Cm}^{-2})^{5}$ at $\\mathrm{pH}5$ . The surface charge density can be further modulated by adjusting the $\\mathrm{\\pH}$ to change the pore surface chemistry (Fig. 2c). The conductance increases with an increase in $\\mathrm{\\pH}$ , suggesting the accumulation of more negative surface charges in $\\mathrm{MoS}_{2}$ nanopores. The simulated conductance from equation (1) at $10\\mathrm{mMKCl}$ is linearly proportional to the surface charge values; thus, $\\mathsf{p H}$ changes could substantially improve the surface charge up to $0.3{-}\\mathrm{{\\dot{0}}}.8\\operatorname{Cm}^{-2}$ . The chemical reactivity of $\\mathrm{MoS}_{2}$ to $\\mathrm{\\pH}$ is also supported by measurements of zeta potential on $\\mathbf{MoS}_{2}$ (ref. 21). However we also notice that, as with other nanofluidic systems5,20, the surface charge density varies from pore to pore, which means that different pores can have disparate values of the equilibrium constant, owing to the various combinations of Mo and S atoms14 at the edge of the pores (as illuminated by molecular-dynamics simulations7). \n\nNext, we introduced a chemical potential gradient by using the KCl concentration gradient system5. The concentration gradient ratio is defined as $C_{\\mathrm{cis}}/C_{\\mathrm{trans}},$ where $C_{\\mathrm{cis}}$ is the KCl concentration in the cis chamber and $C_{\\mathrm{trans}}$ is that in the trans chamber; the concentration ranges from $1\\mathrm{mM}$ to $1\\mathrm{M}$ . The highly negatively charged surface selectively passes the ions (in this case potassium ions) according to their polarity, resulting in a net positive current. By measuring the $I{-}V$ response of the pore in the concentration gradient system (Fig. 3a), we can measure the short-circuit $(I_{s c})$ current corresponding to zero external bias, while the osmotic potential can be obtained from the open-circuit voltage $(V_{\\mathrm{oc}})$ . The pure osmotic potential, $V_{\\mathrm{{os}}}$ , and current, $I_{\\mathrm{os}},$ can then be obtained by subtracting the contribution from the electrode–solution interface at different concentrations; this contribution follows the Nernst equation5,22 (Extended Data Fig. 1). The osmotic potential is proportional to the concentration gradient ratio (Fig. 3b) and shares a similar trend with the osmotic current (Fig. 3c). \n\n![](images/266a0d40394c28c16f0029155d84ad109836184cd2eb2e179f6d0aacd7530228.jpg) \nFigure 3 | Osmotic power generation. a, Current–voltage characteristics for a $15\\mathrm{-nm}$ nanopore in a $1\\mathrm{M}/1\\mathrm{mM}$ KCl gradient. The contribution from the redox reaction on the electrodes is subtracted from the measured total current (grey line) (Extended Data Fig. 1), producing the red dashed line, which represents the pure osmotic contribution. $I_{\\mathrm{sc}}$ and $V_{\\mathrm{oc}}$ are the short-circuit current and open-circuit voltage, respectively; $I_{\\mathrm{os}}$ and $V_{\\mathrm{os}}$ are the osmotic current and potential. b, The generated osmotic potential as a function of the salt gradient. $C_{\\mathrm{cis}}$ is set to be 1 M KCl; $C_{\\mathrm{trans}}$ is tunable from $1\\mathrm{mM}$ to 1 M KCl. The solid line represents a linear fitting to equation (2). c, Osmotic current as a function of salt gradient. The solid line fits proportionally to the linear part of equation (2). d, Osmotic potential and current as a function of pore size. The dashed lines are a guide to the eye and show the trend as the pore size is changed. The error bars come from the corresponding error estimations and represent the s.e.m. (Methods). \n\n![](images/463a221be965a582a9e138063cd7cfbcd094de7faa0140906572b86c58ccb6ee.jpg) \nFigure 4 | Demonstration of a self-powered nanosystem. a, Optical image of the fabricated $\\ensuremath{\\mathrm{MoS}}_{2}$ transistor, with a designed gate, and drain and source electrodes. b, Circuit diagram for the self-powered nanosystem: the drain–source supply for the $\\ensuremath{\\mathrm{MoS}}_{2}$ transistor is provided by a $\\mathbf{MoS}_{2}$ nanopore, while a second nanopore device operates as the gate voltage source. D, drain; G, gate; S, source; $R_{\\mathrm{p}},$ pore resistance; $V_{\\mathrm{tg}},$ gate voltage; $V_{+}$ , nanopore output voltage. $R_{\\mathrm{p}}$ connected in series with $V_{\\mathrm{tg}}$ has been omitted. c, Powering all the terminals of the transistor with nanopore generators. The graph shows the modulated conductivity of the $\\mathrm{MoS}_{2}$ transistor as a function of the top gate voltage $(V_{\\mathrm{tg}})$ . Inset, current–voltage characteristics at various gate voltages $(-0.78\\mathrm{V},0\\mathrm{V}$ and $0.78\\mathrm{V}$ ). \n\nThe measured osmotic energy conversion is also $\\mathrm{\\DeltapH}$ dependent (Extended Data Fig. 2a, b). The increase in $\\mathrm{\\DeltapH}$ leads to higher gene­ rated voltage and current, suggesting the importance of surface charge to the ion-selective process. \n\nThe extracted osmotic potential is the diffusion potential and it arises from differences in the diffusive fluxes of positive and negative ions, because the pore is ion selective: cations diffuse more rapidly than anions (Fig. 1). The diffusion potential, $V_{\\mathrm{diff}},$ can be described as22: \n\n$$\nV_{\\mathrm{diff}}=S(\\varSigma)_{\\mathrm{is}}\\frac{R T}{F}\\mathrm{ln}\\Bigg[\\frac{a_{\\mathrm{KCl}}^{\\mathrm{cis}}}{a_{\\mathrm{KCl}}^{\\mathrm{trans}}}\\Bigg]\n$$ \n\nHere, $S(\\varSigma)_{\\mathrm{is}}$ is the ion selectivity23 for the $\\mathrm{MoS}_{2}$ nanopore (and equals 1 for the ideal cation-selective case, and 0 for the non-selective case); it is defined as $S(\\mathcal{D})_{\\mathrm{is}}=t_{+}-t_{-}$ , where $t_{+}$ and $t_{-}$ are the transference numbers for positively and negatively charged ions respectively. $F,R$ and $T$ are the Faraday constant, the universal gas constant, and the temperature, respectively, while $a_{\\mathrm{KCl}}^{\\mathrm{cis}}$ and $a_{\\mathrm{KCl}}^{\\mathrm{tran\\bar{s}}}$ are the activities of potassium ions in cis and trans solutions. By fitting the experimental data presented in Fig. 3b to equation (2), we find the ion-selectivity coefficient $S(\\Sigma)_{\\mathrm{is}}$ to be 0.4, suggesting efficient cation selectivity. This is because the size of our nanopores lies in the range in which the ­electrical double-layer overlap can occur inside the pore18, because the Debye length, $\\lambda_{\\mathrm{B}},$ is $10\\mathrm{nm}$ for 1 mM KCl. As shown in Extended Data Fig. 3d, with a concentration gradient of $10\\mathrm{mM/1mM}$ in a $5\\mathrm{-nm}$ pore, the ion selectivity approaches nearly 1, presenting the conditions for ideal cation selectivity23. \n\nTo test the cation-selective behaviour of the pore further, we investigated the relationship between power generation and pore size. As shown in Fig. 3d, small pores display better voltage behaviour, reflecting better performance in terms of ion selectivity. The ion selectivity, $S(\\varSigma)_{\\mathrm{is}}$ , decreases from 0.62 to 0.23 as the pore size increases. We calculated the distribution of surface potential for different pore sizes $2\\mathrm{nm}$ , $5\\mathrm{nm}$ and $25\\mathrm{nm}$ ) in order to compare the selectivity difference (Extended Data Fig. 3a–c). It has been proven that the net diffusion current stems only from the charge separation and concentration distribution within the electrical double layer24, and therefore the total current can be expected to increase more rapidly within small pores in the double-layer overlap range compared with larger pore sizes (Fig. 3d). This slight decrease in current in larger pores might be attributed to a reduced local concentration gradient, and also to probable overestimation of the redox potential subtraction. The current can be calculated using either a continuum-based Poisson–Nernst–Planck (PNP) model or molecular-dynamics simulations. The measured dependence of the osmotic potential and osmotic current as a function of the concentration ratio (Fig. 3b, c) is well captured by both computational methods (molecular dynamics, Extended Data Fig. 4, and continuum analysis, Extended Data Fig. 5a). The non-monotonic response to pore size (Fig. 3d and Extended Data Fig. 2c, d) might not only be explained by a possible depletion of the local concentration gradient in large pores, but is also predicted by the continuum-based PNP model (Extended Data Fig. 5b) because of the decrease in ion selectivity. \n\nIn order to gain further insight into the thickness scaling, we first verified the pore-conductance relation proposed in equation (1) by using molecular dynamics (Extended Data Fig. 6). We found that ion mobility also scales inversely with membrane thickness (Extended Data Fig. 7a, b), which may conform to previous observations25. We then performed molecular-dynamics simulations of multilayer membranes of $\\mathbf{MoS}_{2}$ to investigate the power generated by those membranes. We observe a strong decay in the generated power as the number of layers increases (Extended Data Fig. 7c, d), indicating that the best osmotic power generation occurs in two-dimensional membranes. The consistency between experiments and theoretical models highlights two important factors in achieving efficient power generation from a single-layer $\\mathrm{MoS}_{2}$ nanopore: atomic-scale pore thickness and surface charge. \n\nIf we have a single-layer $\\ensuremath{\\mathrm{MoS}}_{2}$ membrane with a homogeneous pore size of $10\\mathrm{nm}$ and a porosity of $30\\%$ , then, by exploiting parallelization, the estimated power density would reach $\\mathrm{\\dot{1}}0^{6}\\mathrm{\\dot{W}}\\mathrm{m}^{-\\tilde{2}}$ with a KCl salt gradient. These values exceed—by two to three orders of magnitude— the results obtained with boron nitride nanotubes5, and are a million times higher than the power density obtained by reverse electrodialysis with classical exchange membranes1 (Extended Data Table 1). \n\nAs well as using KCl concentration gradients, the nanopore power generator concept could also be applied to liquid–liquid junction systems with a chemical potential gradient, because the diffusion voltage originates from the Gibbs mixing energy of the two liquids (Supplementary Information). Thus, high-performance, nanoporebased generators based on a large number of available liquid combinations could be explored24. For example, we have shown substantial power generation based on a chemical potential gradient that uses two types of liquid (Extended Data Fig. 8d). Considerable energy could also be generated by exploiting parallelization, with multiple small pores or even a continuous porous structure within a large area of single-layer $\\mathrm{MoS}_{2}$ membrane26, which could be scaled up for mass production using the ECR pore-fabrication technique16 or plasma-based defect creation27. \n\nThe use of individual nanopores as a micro/nano power source has long been expected22. We find here that an individual osmotic generator can also serve as a nanopower source for a self-powered nanosystem, owing to its high efficiency and power density. For this self-powered nanosystem, we chose the high-performance single-layer $\\mathrm{MoS}_{2}$ transistor (Fig. 4a) because of its excellent operation at low power28. We characterized this transistor in the configuration shown in Fig. 4b, using two nanopores to apply voltages to the transistor’s drain and gate terminals. As shown in Fig. 4c, by varying the top gate voltage in the relatively narrow window of $\\pm0.78\\mathrm{V},$ we could modulate the channel conductivity by a factor of 50 to 80. Furthermore, when we fixed the gate voltage and varied the drain–source voltage $V_{\\mathrm{ds}},$ (Fig. 4c inset), we obtained a linear ${I_{\\mathrm{ds}}}\\mathrm{-}{V_{\\mathrm{ds}}}$ curve, demonstrating efficient injection of electrons into the transistor channel. Further calibration with a standard power source can be found in Extended Data Fig. 8. This system is an ideal self-powered nanosystem in which all the devices are based on single-layer $\\mathbf{MoS}_{2}$ . \n\nWe have shown that $\\mathrm{MoS}_{2}$ nanopores are promising candidates for investigating osmotic power generation as a renewable energy source. The substantial power generated in our experiments can be attributed mainly to the atomic-scale thickness of the $\\mathbf{MoS}_{2}$ membrane. Our results also provide new avenues for studying other membrane-based processes, such as water desalination7 or proton transport29. Furthermore, the nanopore generator may see application in other ultralow-power devices, such as in electronics. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# received 6 December 2015; accepted 13 May 2016. Published online 13 July 2016. \n\n1. Logan, B. E. & Elimelech, M. Membrane-based processes for sustainable power generation using water. Nature 488, 313–319 (2012). \n2. Pattle, R. Production of electric power by mixing fresh and salt water in the hydroelectric pile. Nature 174, 660 (1954). \n3. Loeb, S. Osmotic power-plants. Science 189, 654–655 (1975). \n4. van der Heyden, F. H., Stein, D. & Dekker, C. Streaming currents in a single nanofluidic channel. Phys. Rev. Lett. 95, 116104 (2005). \n5. Siria, A. et al. Giant osmotic energy conversion measured in a single transmembrane boron nitride nanotube. Nature 494, 455–458 (2013). \n6. Suk, M. E. & Aluru, N. Water transport through ultrathin graphene. J. Phys. Chem. Lett. 1, 1590–1594 (2010). \n7. Heiranian, M., Farimani, A. B. & Aluru, N. R. Water desalination with a single-layer ${\\mathsf{M o S}}_{2}$ nanopore. Nature Commun. 6, 8616 (2015). \n8. Wang, Z. L. & Song, J. Piezoelectric nanogenerators based on zinc oxide nanowire arrays. Science 312, 242–246 (2006). \n9. Wang, Z. L. Self-powered nanosensors and nanosystems. Adv. Mater. 24, \n280–285 (2012). \n10.\t Tian, B. et al. Coaxial silicon nanowires as solar cells and nanoelectronic power sources. Nature 449, 885–889 (2007). \n11.\t Xu, S. et al. Self-powered nanowire devices. Nature Nanotechnol. 5, 366–373 (2010). \n12.\t Wu, W. et al. Piezoelectricity of single-atomic-layer ${\\mathsf{M o S}}_{2}$ for energy conversio and piezotronics. Nature 514, 470–474 (2014). \n13.\t Liu, K., Feng, J., Kis, A. & Radenovic, A. Atomically thin molybdenum disulfide nanopores with high sensitivity for DNA translocation. ACS Nano 8, 2504–2511 (2014). \n14.\t Farimani, A. B., Min, K. & Aluru, N. R. DNA base detection using a single-layer MoS2. ACS Nano 8, 7914–7922 (2014). \n15.\t Liu, X. et al. Top–down fabrication of sub-nanometre semiconducting nanoribbons derived from molybdenum disulfide sheets. Nature Commun. 4, 1776 (2013). \n16.\t Feng, J. et al. Electrochemical reaction in single layer MoS2: nanopores opened atom by atom. Nano Lett. 15, 3431 (2015). \n17.\t Stein, D., Kruithof, M. & Dekker, C. Surface-charge-governed ion transport in nanofluidic channels. Phys. Rev. Lett. 93, 035901 (2004). \n18.\t Bocquet, L. & Charlaix, E. Nanofluidics, from bulk to interfaces. Chem. Soc. Rev. 39, 1073–1095 (2010). \n19.\t Lee, C. et al. Large apparent electric size of solid-state nanopores due to spatially extended surface conduction. Nano Lett. 12, 4037–4044 (2012). \n20.\t Shan, Y. et al. Surface modification of graphene nanopores for protein translocation. Nanotechnology 24, 495102 (2013). \n21.\t Ge, P. et al. Hydrogen evolution across nano-schottky junctions at carbon supported ${\\mathsf{M o S}}_{2}$ catalysts in biphasic liquid systems. Chem. Commun. 48, 6484–6486 (2012). \n22.\t Kim, D.-K., Duan, C., Chen, Y.-F. & Majumdar, A. Power generation from concentration gradient by reverse electrodialysis in ion-selective nanochannels. Microfluid. Nanofluidics 9, 1215–1224 (2010). \n23.\t Vlassiouk, I., Smirnov, S. & Siwy, Z. Ionic selectivity of single nanochannels. Nano Lett. 8, 1978–1985 (2008). \n24.\t Cao, L. et al. Towards understanding the nanofluidic reverse electrodialysis system: well matched charge selectivity and ionic composition. Energy Environ. Sci. 4, 2259–2266 (2011). \n25.\t Wu, J., Gerstandt, K., Zhang, H., Liu, J. & Hinds, B. J. Electrophoretically induced aqueous flow through single-walled carbon nanotube membranes. Nature Nanotechnol. 7, 133–139 (2012). \n26.\t Waduge, P. et al. Direct and scalable deposition of atomically thin low-noise ${\\mathsf{M o S}}_{2}$ membranes on apertures. ACS Nano 9, 7352–7359 (2015). \n27.\t Surwade, S. P. et al. Water desalination using nanoporous single-layer graphene. Nature Nanotechnol. 10, 459–464 (2015). \n28.\t Radisavljevic, B., Radenovic, A., Brivio, J., Giacometti, V. & Kis, A. Single-layer ${\\mathsf{M o S}}_{2}$ transistors. Nature Nanotechnol. 6, 147–150 (2011). \n29.\t Walker, M. I., Braeuninger-Weimer, P., Weatherup, R. S., Hofmann, S. & Keyser, U. F. Measuring the proton selectivity of graphene membranes. Appl. Phys. Lett. 107, 213104 (2015). \n\n# Supplementary Information is available in the online version of the paper. \n\nAcknowledgements This work was financially supported by the European Research Council (grant 259398, PorABEL), by a Swiss National Science Foundation (SNSF) Consolidator grant (BIONIC BSCGI0_157802), by SNSF Sinergia grant 147607, and by funding from the European Union’s Seventh Framework Programme FP7/2007-2013 under Grant Agreement 318804 (for single-nanometre lithography). We thank the Centre Interdisciplinaire de Microscopie Electronique (CIME) at the École Polytechnique fédérale de Lausanne (EPFL) for access to electron microscopes. Device fabrication was partially carried out at the EPFL Center for Micro/Nanotechnology (CMi). N.R.A. is supported by the Air Force Office of Scientific Research under grant FA9550- 12-1-0464, and by the National Science Foundation under grants 1264282, 1420882, 1506619 and1545907. We acknowledge the use of the parallel computing resource Blue Waters, provided by the University of Illinois and the National Center for Supercomputing Applications. \n\nAuthor Contributions J.F. and A.R. conceived the idea, designed all experiments, and wrote the manuscript. J.F. and M.G. performed measurements and data analysis. J.F. and K.L. fabricated the nanopore device. D.O. fabricated the ${\\mathsf{M o S}}_{2}$ transistor and D.D. performed chemical-vapour-deposition ${\\mathsf{M o S}}_{2}$ growth under A.K.’s supervision. J.F. and D.O. demonstrated the self-powering of the nanosystem. M.H., V.N., and N.R.A. built the computational nanofluidics model and interpreted the simulation results. All authors provided constructive comments on the manuscript. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Correspondence and requests for materials should be addressed to J.F. (jiandong.feng@epfl.ch) or A.R. (aleksandra.radenovic@epfl.ch). \n\nReviewer Information Nature thanks Z. Siwy and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\n# Methods \n\nNanopore fabrication. We fabricated $\\mathrm{MoS}_{2}$ nanopores either by using the atomicscale ECR technique16 or by electron irradiation under $\\mathrm{TEM}^{13}$ . Prior to nanopore fabrication, we create a freestanding $\\ensuremath{\\mathrm{MoS}}_{2}$ membrane30. Briefly, we use KOH wet etching to prepare $\\mathrm{SiN}_{x}$ membranes (of size $10\\upmu\\mathrm{m}\\times10\\upmu\\mathrm{m}$ to $50\\upmu\\mathrm{m}\\times50\\upmu\\mathrm{m};$ $20\\mathrm{nm}$ thick). We then use focused ion beam (FIB) or ebeam lithography (followed by reactive ion etching) to drill an opening of $50{-}300\\mathrm{nm}$ in the membrane. Next we suspend single-layer $\\ensuremath{\\mathrm{MoS}}_{2}$ membranes, grown by chemical-vapour deposition, on the opening by transferring them from sapphire growth substrates30. TEM irradiation can be applied to drill a single pore and image the pore. ECR is done by applying a step-like transmembrane potential to the membrane and monitoring the transmembrane ionic current with a Femto DLPCA-200 amplifier (Femto Messtechnik GmbH), with a custom-made feedback control on transmembrane conductance. Nanopores are formed when reaching the critical voltage of $\\ensuremath{\\mathrm{MoS}}_{2}$ oxidation $(>0.8\\mathrm{V})$ . We then calibrate the pore size using $I{-}V$ characteristics. \n\nNanofluidic measurements. Nanofluidic transport experiments are performed as described16. The nanopore chips are mounted in a custom-made polymethylmethacrylate chamber, and then wetted with an $\\mathrm{H}_{2}\\mathrm{O}$ :ethanol (1:1) solution. Nanofluidic measurements are carried out by taking the $I{-}V$ characteristics of the nanopore in different KCl solutions (Sigma Aldrich; the ionic concentration or pH of the solution varies), using an Axopatch 200B patch-clamp amplifier (Molecular Devices Inc.). A pair of chlorinated $\\mathrm{Ag/AgCl}$ electrodes (which have been rechlorinated regularly) is used to apply voltage and to measure the current. In addition, the electrode potential differences in solutions of different concentrations are calibrated with a saturated $\\mathrm{\\Ag/AgCl}$ reference electrode (Sigma Aldrich). \n\nTo measure osmotic power generation, we filled the reservoirs with solutions of different concentrations, ranging from $1\\mathrm{mM}$ to 1 M. Measurements are performed at various $\\mathrm{\\pH}$ conditions. We found that power generation was optimal at $\\mathrm{pH}11$ . First, we measured the $I{-}V$ response; we obtained the short-circuit current from the interception of the curve at zero voltage, and the open-circuit voltage from the interception of the curve at zero current. Next, to get the purely osmotically driven contribution, we subtracted the contribution made by the electrode potential difference that results from the redox potential in different concentrations (Extended Data Fig. 1). \n\nFor all experiments, we performed cross-checking measurements, including changing the direction of $\\mathrm{\\DeltapH}$ and concentration to make sure that the nano­pores were not substantially enlarged during the experiments. Most $\\ensuremath{\\mathrm{MoS}}_{2}$ pores were generally stable during hours of experiments owing to their high mechanical strength and stability within the $\\pm600\\mathrm{mV}$ bias range. Thus, we strongly recommend the use of small supporting FIB/ebeam-drilled opening windows (of diameter $50{-}300\\mathrm{nm}$ ) for suspended membranes. \n\nCharacterization of single-layer $\\mathbf{MoS}_{2}$ transistors. We fabricated single-layer $\\ensuremath{\\mathrm{MoS}}_{2}$ transistors using a procedure similar to that in ref. 28. \n\nFor electrical measurements we used an Agilent 5270B source-meter unit (SMU), an SR-570 low-noise current preamplifier and a Keithley 2000 digital ­multimeter (DMM; input impedance ${>}10^{10}\\Omega$ ). All measurements were performed in ambient conditions in the dark. An improved efficiency of power conversion in nanopores is obtained by using a combination of pure room-temperature ionic liquids: 1-butyl-2-methylimidazolium hexafluorophosphate $\\mathrm{Bmim}\\mathrm{PF}_{6}\\mathrm{,}$ and zinc chloride solution. \n\nWe compare the performance of the single-layer $\\ensuremath{\\mathrm{MoS}}_{2}$ transistor in two cases. First, we use two nanopores to apply $V_{\\mathrm{tg}}$ and $V_{\\mathrm{ds}},$ while using a current amplifier and voltmeter to control the current and voltage drop across the device (see Extended Data Fig. 8a). In this case, we use voltage dividers to change the source and gate voltage on the device (not shown in Fig. 4a and Extended Data Fig. 8a). Second, we use the SMU to perform standard two-contact measurements. \n\nAlthough the characteristics of our transistor are similar in both set-ups, we comment here on the difference detected in the conductivity of the ON state. We attribute it to the slow response of the device in the first case. The change in transistor resistance that occurs when applying gate voltage leads to a change in the impedance of the device and thus a change in the applied effective voltage, $V_{\\mathrm{dev}}$ (measured with a voltmeter connected in parallel). The nanopore reacts to the change in impedance with a certain stabilization time (from 10 s to 100 s). This appears to be a hysteretic effect and influences the conductivity versus gate-voltage measurements. In the second case, on the other hand, $V_{\\mathrm{dev}}=V_{\\mathrm{ds}}$ is constant. There are several secondary effects, which might in turn influence the measured values of two-probe conductivity. In relatively short channel devices, applied $V_{\\mathrm{d}s}$ might partially contribute to gating of the channel and furthermore to modification of contact resistance. This could be understood by comparing the values of $V_{\\mathrm{d}s}$ (around $100\\mathrm{mV},$ ) and $V_{\\mathrm{tg}}\\left(780\\mathrm{mV}\\right)$ . We also do not exclude the possibility of slight doping variations and hysteretic effects that occur because of the filling of trap states inside the transistor channel. However, by driving a device to the ON state and stabilizing the current for a reasonable amount of time, we obtained a very good match in drain–source ${I_{\\mathrm{ds}}}\\mathrm{-}{V_{\\mathrm{ds}}}$ characteristics (Extended Data Fig. 8c). We thus conclude that, although there are differences in performance in the two cases, these differences originate mainly from the slow response time of the nanopore. \n\nWe extracted the resistance and power of the nanopore by using the ionic liquid Bmim $\\mathrm{PF}_{6}$ . By considering the simple resistor network (Extended Data Fig. 8d, inset), we could extract the output power as a function of the load resistance, $R_{\\mathrm{load}}$ . We fit our dependence according to the following model, which assumes a constant $V_{\\mathrm{out}}$ and $R_{\\mathrm{pore}}$ : \n\n$$\n\\mathrm{Power}=\\frac{V_{\\mathrm{out}}R_{\\mathrm{load}}}{(R_{\\mathrm{p}}+R_{\\mathrm{load}})^{2}}\n$$ \n\nand found a good fit with $V_{\\mathrm{out}}{=}0.83\\mathrm{V},$ which is close to the measured $V_{\\mathrm{out}}$ of $0.78\\mathrm{V},$ and with a nanopore impedance, $R_{\\mathrm{p}},$ of $9.4\\pm2.1\\mathrm{M}\\Omega$ (Extended Data Fig. 8d). \n\nData analysis. All data analysis has been done using custom-made Matlab (R2016a) code. First, we recorded $I{-}V$ characteristics with an Axopatch 200B amplifier, by using either an automatic or a manual voltage switch. We then ­segmented the current trace into pieces of constant voltage, V. We extracted the mean, $\\mu(V)$ , and standard deviation, $\\sigma(V)$ , of the stable part of each segment and generated an $I{-}V$ plot. The error bars are the standard deviations (see Fig. 3 and Extended Data Fig. 2). All $I{-}V$ characteristics were linear. In order to propagate the error correctly, we used a linear fitting method31. Using this method, we can extract the $a$ , $b$ , $\\sigma_{a}$ and $\\sigma_{b}$ values of the first-order polynomial $I(V)=b V+a$ . The conductance is the slope, $b$ , of the $I{-}V$ curve, and a describes the offset. The height of the error bars reported for conductance measurements is $2\\sigma_{b}$ . \n\nWe report the osmotic power generation using the osmotic current, $I_{\\mathrm{os}},$ and osmotic voltage, $V_{\\mathrm{{os}}}$ . Starting from the linear-fit values of the $I{-}V$ plot, we can calculate the measured current and voltage: $I_{\\mathrm{meas}}=a$ and $V_{\\mathrm{meas}}{=}a/b$ . These measured values have to be adjusted for the electrode potential: $V_{\\mathrm{os}}=V_{\\mathrm{meas}}-V_{\\mathrm{redox}}$ and $I_{\\mathrm{os}}=(V_{\\mathrm{os}}/V_{\\mathrm{meas}})\\times I_{\\mathrm{meas}}$ Assuming an uncertainty in our estimation of redox potential, $\\sigma_{\\mathrm{redox}},$ of $5\\%$ , we can propagate the errors using the following formulas32: \n\n$$\n\\sigma_{V_{0s}}=\\sqrt{\\left(\\frac{1}{b}\\sigma_{a}\\right)^{2}+\\left(\\frac{a}{b^{2}}\\sigma_{b}\\right)^{2}+\\sigma_{\\mathrm{redox}}^{2}}\n$$ \n\n$$\n\\sigma_{I_{0s}}=\\sqrt{\\sigma_{a}^{2}+(V_{\\mathrm{redox}}\\sigma_{b})^{2}+b^{2}\\sigma_{\\mathrm{redox}}^{2}}\n$$ \n\nWe used these relations to calculate the error bars shown in plots of osmotic voltage and current (Fig. 3 and Extended Data Fig. 2). \n\nComputational simulations. Molecular-dynamics simulations. These simulations were performed using the LAMMPS package33. A $\\ensuremath{\\mathrm{MoS}}_{2}$ membrane was placed between two KCl solutions as shown in Extended Data Fig. 4a. A fixed graphene wall was placed at the end of each solution reservoir. A nanopore was drilled in $\\ensuremath{\\mathrm{MoS}}_{2}$ by removing the desired atoms. The accessible pore diameter considered in all of the molecular-dynamics simulations is $2.2\\mathrm{nm}$ with a surface charge density of $-0.04694\\mathrm{Cm}^{-2}$ . The system dimensions were $6\\mathrm{nm}\\times6\\mathrm{nm}\\times36\\mathrm{nm}$ in the $x,$ y and $z$ directions, respectively. We used the extended simple point charge (SPC/E) water model, and applied the SHAKE algorithm to maintain the rigidity of each water molecule. The Lennard Jones (LJ) parameters are tabulated in Supplementary Table 1. The LJ cut-off distance was $12{\\dot{\\mathrm{\\AA}}}$ . The long-range interactions were computed by the particle–particle particle–mesh (PPPM) method34. Periodic boundary conditions were applied in the $x$ and y directions. The system is non-periodic in the $z$ direction. For each simulation, first the energy of the system was minimized for 10,000 steps. Next, the system was equilibrated in the isothermic–isobaric (otherwise known as NPT) ensemble for 2 ns at a pressure of 1 atm and a temperature of $300\\mathrm{K}$ to reach the equilibrium density of water. Graphene and $\\ensuremath{\\mathrm{MoS}}_{2}$ atoms were held fixed in space during the simulations. Then, canonical (NVT) simulations were performed, during which the temperature was maintained at $300\\mathrm{K}$ by using the Nosè–Hoover thermostat with a time constant of 0.1 ps (refs 35, 36). Trajectories of atoms were collected every picosecond to obtain the results. For accurate mobility calculations, however, the trajectories were stored every ten femtoseconds. \n\nContinuum model. We also used the continuum–based two-dimensional Poisson– Nernst–Planck (PNP) model. We neglected the contribution of $\\mathrm{\\ddot{H}^{+}}$ and $\\mathrm{OH^{-}}$ ions in this calculation, as their concentrations are much lower compared with the bulk concentration of the other ionic species ( $\\mathrm{K^{+}}$ and $\\mathrm{Cl^{-}}$ ). Hence, water-dissociation effects are not considered in the numerical model. Further, we assumed that the ions are immobile inside the steric layer and do not contribute to the ionic current. We also did not model the Faradaic reactions occurring near the electrode. Finally, we assumed that the convective component of current originating from the fluid flow is negligible and does not contribute to the non-monotonic osmotic current observed in our experiments. We validated this assumption by performing detailed all-atom molecular-dynamics simulations and predicted the contribution of electroosmotic velocity in comparison with the drift velocity of the ions. \n\nUnder these assumptions, the total flux of each ionic species $({\\pmb{T}}_{i})$ is contributed by a diffusive component resulting from the concentration gradient, and an electrophoretic component arising from the potential gradient, as given by: \n\n$$\n\\pmb{I}_{i}=-D_{i}\\pmb{\\nabla}c_{i}-\\varOmega_{i}z_{i}F c_{i}\\pmb{\\nabla}\\phi\n$$ \n\nwhere $F$ is Faraday’s constant, $z_{i}$ is the valence of the ith species, $D_{i}$ is the diffusion coefficient, $\\varOmega_{i}$ is the ionic mobility, $c_{i}$ is the concentration and $\\phi$ is the electrical potential. Note that the ionic mobility is related to the diffusion coefficient by Einstein’s relation37, $\\begin{array}{r}{\\varOmega_{i}=\\frac{D_{i}}{R T}}\\end{array}$ , where $R$ is the ideal gas constant and $T$ is the thermodynamic temperature. The mass transport of each ionic species is: \n\n$$\n\\frac{\\mathrm{d}c_{i}}{\\mathrm{d}t}=-\\nabla\\cdot\\boldsymbol{\\Gamma_{i}}\n$$ \n\nThe individual ionic current $\\left(I_{i}\\right)$ across the reservoir and the pore is calculated by integrating their respective fluxes over the cross-sectional area, that is: \n\n$$\n\\pmb{I}_{i}=\\int z_{i}F\\pmb{I}_{i}\\mathrm{d}S\n$$ \n\nThe total ionic current at any axial location is calculated as $\\begin{array}{r}{I=\\sum_{i=1}^{m}z_{i}F T_{i}\\mathrm{d}S,}\\end{array}$ where S is the cross-sectional area corresponding to the axial location and $m$ is the number of ionic species. In order to determine the electric potential along the system, we solve the Poisson equation: \n\n$$\n\\nabla\\cdot(\\epsilon_{\\mathrm{r}}\\nabla\\phi)=-\\frac{\\rho_{\\mathrm{e}}}{\\epsilon_{0}}\n$$ \n\nwhere $\\epsilon_{0}$ is the permittivity of free space, $\\epsilon_{\\mathrm{r}}$ is the relative permittivity of the medium and $\\rho_{\\mathrm{e}}$ is the net space charge density of the ions, defined as: \n\n$$\n\\rho_{\\mathrm{e}}{=}F\\textstyle\\sum_{i=1}^{m}z_{i}c_{i}\n$$ \n\nWe provide the necessary boundary conditions for the closure of the problem. The normal flux of each ion is assumed to be zero on all the walls so that there is no leakage of current. To conserve charge on the walls of the pore, the electrostatic boundary condition is given by: \n\n$$\n{\\pmb n}\\cdot{\\pmb\\nabla}\\phi=\\frac{\\sigma}{\\epsilon_{0}\\epsilon_{\\mathrm{{r}}}}\n$$ \n\nwhere $\\pmb{n}$ denotes the unit normal vector (pointing outwards) to the wall surface and $\\sigma$ is the surface charge density of the walls. The bulk concentration of the cis reservoir is maintained at $C_{\\mathrm{max}}$ and the bulk concentration on the trans reservoir is maintained at $C_{\\mathrm{min}}$ . As we are interested in understanding the osmotic shortcircuit current, $I_{\\mathrm{sc}},$ we do not apply any voltage difference across the reservoirs. Thus, the boundary conditions at the ends of the cis and trans reservoirs are specified as: \n\n$$\n\\begin{array}{r}{c_{i}=C_{\\mathrm{max}},\\phi=0}\\\\ {c_{i}=C_{\\mathrm{min}},\\phi=0}\\end{array}\n$$ \n\nThe coupled PNP equations are numerically solved using the finite volume method in OpenFOAM (http://www.openfoam.com/). The details of solver implementation are discussed in refs 38–40. The simulated domain consisted of a $\\mathbf{MoS}_{2}$ nanopore of length, $L_{\\mathrm{n}},$ $0.6\\mathrm{nm}$ and diameter, $d_{\\mathrm{n}}$ varying from $2.2\\mathrm{nm}$ to $25\\mathrm{nm}$ . The simulated length of the reservoir was $L_{\\mathrm{cis}}=L_{\\mathrm{trans}}=11\\mathrm{nm}$ the diameter of the reservoir was $50\\mathrm{nm}$ . KCl buffer solution was used in the simulation. The bulk concentration of the cis reservoir was fixed at $1\\mathrm{M}$ and the concentration in the trans reservoir was varied systematically varied from $1\\mathrm{mM}$ to 1 M. The simulation temperature was $300\\mathrm{K}$ . The bulk diffusivities of $\\mathrm{K^{+}}$ and $\\mathrm{Cl^{-}}$ were $1.96\\times10^{-9}\\mathrm{{m}^{2}\\mathrm{{s}^{-1}}}$ and $2.03\\times10^{-9}\\mathrm{m}^{2}s^{-1}$ . The dielectric constant of the aqueous solution was assumed to be 80. We also assumed zero surface charge density on the walls of the reservoir, as the reservoir is too far away from the nanopore to have an influence on the transport. Unless otherwise stated, the charge on the walls of the $\\ensuremath{\\mathrm{MoS}}_{2}$ nanopore is assumed to be $\\sigma_{\\mathrm{n}}{=}{-}0.04694\\mathrm{Cm}^{-2}$ consistent with the surface charge calculated from our molecular-dynamics simulations. \n\n30.\t Dumcenco, D. et al. Large-area epitaxial monolayer ${\\mathsf{M o S}}_{2}$ . ACS Nano 9, 4611–4620 (2015). \n31.\t York, D., Evensen, N. M., Martınez, M. L. & Delgado, J. D. B. Unified equations for the slope, intercept, and standard errors of the best straight line. Am. J. Phys. 72, 367–375 (2004). \n32.\t Ku, H. Notes on the use of propagation of error formulas. J. Res. National Bureau Standards 70C, 263–273 (1966). \n33.\t Plimpton, S. Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117, 1–19 (1995). \n34.\t Hockney, R. W. & Eastwood, J. W. Computer Simulation Using Particles (CRC Press, 1988). \n35.\t Nosé, S. A unified formulation of the constant temperature molecular dynamics methods. J. Chem. Phys. 81, 511–519 (1984). \n36.\t Hoover, W. G. Canonical dynamics: equilibrium phase-space distributions. Phys. Rev. A 31, 1695–1697 (1985). \n37.\t Probstein, R. F. Physicochemical Hydrodynamics: An Introduction. (John Wiley & Sons, 2005). \n38.\t Nandigana, V. V. & Aluru, N. Understanding anomalous current–voltage characteristics in microchannel–nanochannel interconnect devices. J. Colloid Interface Sci. 384, 162–171 (2012). \n39.\t Nandigana, V. V. & Aluru, N. Nonlinear electrokinetic transport under combined ac and dc fields in micro/nanofluidic interface devices. J. Fluids Eng. 135, 021201 (2013). \n40.\t Nandigana, V. V. & Aluru, N. Characterization of electrochemical properties of a micro–nanochannel integrated system using computational impedance spectroscopy (cis). Electrochim. Acta 105, 514–523 (2013). \n41.\t Weinstein, J. N. & Leitz, F. B. Electric power from differences in salinity: the dialytic battery. Science 191, 557–559 (1976). \n42.\t Audinos, R. Reverse electrodialysis. Study of the electric energy obtained by mixing two solutions of different salinity. J. Power Sources 10, 203–217 (1983). \n43.\t Turek, M. & Bandura, B. Renewable energy by reverse electrodialysis. Desalination 205, 67–74 (2007). \n44.\t Suda, F., Matsuo, T. & Ushioda, D. Transient changes in the power output from the concentration difference cell (dialytic battery) between seawater and river water. Energy 32, 165–173 (2007). \n45.\t Veerman, J., De Jong, R., Saakes, M., Metz, S. & Harmsen, G. Reverse electrodialysis: comparison of six commercial membrane pairs on the thermodynamic efficiency and power density. J. Membr. Sci. 343, 7–15 (2009). \n\n![](images/a58f09fc6f07f62523e029a5c4e467629602e19e9ffed262f1962cea53292411.jpg) \n\n![](images/d5eaa0cf323647c0fe48812b30a4aa3fc865e4b9a58a1111774573d5c995f9be.jpg) \nExtended Data Figure 1 | Subtraction of the contribution made by electrodes, and stability of the nanopore generator. a, Diagram showing the contributions of different parts of the system to the overall measured current. The osmotic contribution is obtained by subtracting the contribution of the potential difference at the electrodes from the measured voltage or current. $V_{\\mathrm{{measured}}}$ is the measured voltage; $E_{\\mathrm{redox}}$ is the \n\nredox potential difference. b, Electrode contribution as a function of the salt concentration gradient: values obtained from the Nernst equation, and measured electrode redox potential differences at the reference electrode. c, The data used for the subtraction. $E_{\\mathrm{redox}},$ the redox potential at the electrodes. d, A 1-hour trace of ionic current, showing the stability of a $14\\mathrm{-nm}$ pore in $1\\mathrm{MKCl/1mM}$ KCl. Inset, the design of the fluidic cell. \n\n![](images/db085f8d55e0950922bca371847d3e28cfdead696488e86c60e6bd959d893e54.jpg) \nExtended Data Figure 2 | Dependence of osmotic power generation on $\\mathbf{pH}$ and pore size. a, b, Osmotic potential (a) and osmotic current (b) generated using a 3-nm pore under different pH conditions $\\left(\\operatorname{pH}3,5\\right.$ or 11) and in different concentration gradients. Power generation (both osmotic potential and osmotic current) at $\\mathrm{pH}3$ is very low and sometimes \nfluctuates to negative, indicating that the pore charge is relatively low. One possible explanation for the negative voltage point is that the surface charge on the pore has fluctuated to positive. c, d, Osmotic potential (c) and osmotic current (d) generated using two different pores ( $3\\mathrm{-nm}$ and $15\\mathrm{-nm}^{\\cdot}$ at $\\mathrm{pH}11$ in different concentration gradients. \n\n![](images/f31ec4c41b38988f5672a19cdd9f06b1abbdb34b8046714cdd09334aa85156ca.jpg) \n\n
Cmin/CmaxVmeasured, mVEredox, mVVos, mVIon selectivity
1mM/10mM100.646.953.70.92
10mM/100mM104.453.550.90.86
10mM/1M153.3107.246.10.78
1mM/100mM183.0100.482.60.7
100mM/1M67.353.713.60.23
\n\nExtended Data Figure 3 | Ideal cation selectivity of the pore. a–c, Calculated surface potential distribution of $\\ensuremath{\\mathrm{MoS}}_{2}$ nanopores of diameter $25\\mathrm{nm}$ (a), $5\\mathrm{nm}$ (b), and $2\\mathrm{nm}$ (c) under a fixed surface charge density. d, Ion selectivity in different salt gradients. The ion selectivity \n\nalso depends on the Debye length when the concentration gradient is fixed; with a gradient of $10\\mathrm{mM/1mM}$ and a $5\\mathrm{-nm}$ pore, the ion selectivity approaches nearly 1, indicating the ideal cation selectivity. \n\n![](images/39ea16f026c0eeaf8c9b4588824016c248cacf57d7f3fa9ebe86be892717bc8d.jpg) \nExtended Data Figure 4 | Molecular-dynamics simulations of power generation for various ratios of concentration gradients. a, A typical simulation box. b, Current as a function of the applied electric field for a single-layer $\\mathrm{MoS}_{2}.$ , at different concentration ratios. c, $\\mathrm{K^{+}}$ and $\\mathrm{Cl^{-}}$ \nconcentrations as a function of the radial distance from the centre of the pore, for different concentration ratios. d, Short-circuit current as a function of the concentration ratio. e, Open-circuit electric field as a function of the concentration ratio. \n\n![](images/78905489e6cdc94dc57ab433cfae26752b4e95061c6ca068479cab0d6abb99bc.jpg) \nExtended Data Figure 5 | Continuum-based PNP modelling of power generation. a, Short-circuit current, $I_{\\mathrm{sc}},$ as a function of the concentration gradient ratio. The diameter of the nanopore here is $2.2\\mathrm{nm}$ . b, $I_{\\mathrm{sc}}$ as a function of the nanopore diameter. The salinity concentration ratio is fixed at 1,000. The surface charge of the nanopore, $\\sigma_{\\mathrm{n}},$ is $-0.04694\\mathrm{Cm}^{-2}$ . \n\n![](images/8c5ebc2ee016b9434782cdd9ef88b669f040122627d9204040eddc650ede6b34.jpg) \nExtended Data Figure 6 | Molecular-dynamics-modelled conductance b, Conductance of the nanopore as a function of the reciprocal thickness as a function of membrane thickness. a, $I{-}V$ curves for six membranes of the membrane $(t^{-1})$ . c, Average mobility of each ion for different with a different number of $\\ensuremath{\\mathrm{MoS}}_{2}$ layers, across a symmetrical $1\\mathrm{M}$ numbers of layers of $\\ensuremath{\\mathrm{MoS}}_{2}$ membranes. KCl solution. The inset illustrates simulated multilayer membranes. \n\n![](images/0b332467a2eb38fc1520d687e7b9e9035e8d1e6d17a0cb04a8accc6237100d8a.jpg) \nExtended Data Figure 7 | Simulated power generation as a function of membrane thickness. a, $\\mathrm{K^{+}}$ and $\\mathrm{Cl^{-}}$ concentrations as a function of the radial distance from the centre of the pore for single-layer and multilayer membranes. The $\\lambda$ region, near the charged wall of the pore, is representative of the electrical double layer. b, The mobility of each \nion type within and outside the $\\lambda$ region for different layers of membranes. c, The open-circuit electric field across the membrane for different numbers of $\\ensuremath{\\mathrm{MoS}}_{2}$ layers. d, Ratio of the maximum power (P) generated by multilayer membranes to the maximum power generated by a single-layer membrane, for different numbers of layers. \n\n![](images/b53396e1d9c57eada1004a6c99820d63cafb626884f84134c9389b68e7e3d099.jpg) \nExtended Data Figure 8 | Characterization of a single-layer $\\mathbf{MoS}_{2}$ transistor with nanopores and SMU. a, Electrical measurements with two nanopores $\\cdot V_{+}$ , nanopore output voltage; $V_{\\mathrm{d}s},$ drain–source voltage; $V_{\\mathrm{tg}},$ top gate voltage). The voltage drop across the transistor channel is monitored with the voltmeter (V); current is measured with current amplifier (A). b, Comparison of nanopore measurements with \nstandard two-probe measurements made with an external source. c, $I{-}V$ characteristics at $V_{\\mathrm{tg}}{=}0.78\\mathrm{V}$ after current stabilization, measured in both set-ups. d, Output power of nanopore in Bmim $\\mathrm{PF}_{6}/$ zinc chloride as a function of load resistance, $R_{\\mathrm{load}}$ . Inset, circuit diagram for these measurements. \n\nExtended Data Table 1 | Power generation according to membrane thickness \n\n\n
Reverse electrodialysis cellsPower density (W/m²)Membrane thickness
Ref. 410.171 mm
Ref. 420.403 mm
Ref. 430.460.19 mm
Ref.440.261 mm
Ref. 450.950.2 mm
Ref. 227.70.14 mm
Ref. 540001 μm
This work1060.65 nm
Multilayer MoS2 (Simulations)300007.2 nm
\n\nThe table shows the power generated by membranes of different thickness; data from refs 5, 22, 41–45. " + }, + { + "id": "10.1126_scitranslmed.aaf2593", + "DOI": "10.1126/scitranslmed.aaf2593", + "DOI Link": "http://dx.doi.org/10.1126/scitranslmed.aaf2593", + "Relative Dir Path": "mds/10.1126_scitranslmed.aaf2593", + "Article Title": "A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat", + "Authors": "Koh, A; Kang, D; Xue, Y; Lee, S; Pielak, RM; Kim, J; Hwang, T; Min, S; Banks, A; Bastien, P; Manco, MC; Wang, L; Ammann, KR; Jang, KI; Won, P; Han, S; Ghaffari, R; Paik, U; Slepian, MJ; Balooch, G; Huang, YG; Rogers, JA", + "Source Title": "SCIENCE TRANSLATIONAL MEDICINE", + "Abstract": "Capabilities in health monitoring enabled by capture and quantitative chemical analysis of sweat could complement, or potentially obviate the need for, approaches based on sporadic assessment of blood samples. Established sweat monitoring technologies use simple fabric swatches and are limited to basic analysis in controlled laboratory or hospital settings. We present a collection of materials and device designs for soft, flexible, and stretchable microfluidic systems, including embodiments that integrate wireless communication electronics, which can intimately and robustly bond to the surface of the skin without chemical and mechanical irritation. This integration defines access points for a small set of sweat glands such that perspiration spontaneously initiates routing of sweat through a microfluidic network and set of reservoirs. Embedded chemical analyses respond in colorimetric fashion to markers such as chloride and hydronium ions, glucose, and lactate. Wireless interfaces to digital image capture hardware serve as a means for quantitation. Human studies demonstrated the functionality of this microfluidic device during fitness cycling in a controlled environment and during long-distance bicycle racing in arid, outdoor conditions. The results include quantitative values for sweat rate, total sweat loss, pH, and concentration of chloride and lactate.", + "Times Cited, WoS Core": 1001, + "Times Cited, All Databases": 1107, + "Publication Year": 2016, + "Research Areas": "Cell Biology; Research & Experimental Medicine", + "UT (Unique WOS ID)": "WOS:000389449400005", + "Markdown": "# B I O S E N S O R S \n\n# A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat \n\nAhyeon Koh,1\\* Daeshik Kang,1,2\\* Yeguang Xue,3 Seungmin Lee,1 Rafal M. Pielak,4 \nJeonghyun Kim,1,5 Taehwan Hwang,1 Seunghwan Min,1 Anthony Banks,1 Philippe Bastien,6 \nMegan C. Manco,7 Liang Wang,3,8 Kaitlyn R. Ammann,9 Kyung-In Jang,1 Phillip Won,1 \nSeungyong Han,1 Roozbeh Ghaffari,10 Ungyu Paik,5 Marvin J. Slepian,9 Guive Balooch,4 \nYonggang Huang,3 John A. Rogers1† \n\n2016 $\\circledcirc$ The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. \n\nCapabilities in health monitoring enabled by capture and quantitative chemical analysis of sweat could complement, or potentially obviate the need for, approaches based on sporadic assessment of blood samples. Established sweat monitoring technologies use simple fabric swatches and are limited to basic analysis in controlled laboratory or hospital settings. We present a collection of materials and device designs for soft, flexible, and stretchable microfluidic systems, including embodiments that integrate wireless communication electronics, which can intimately and robustly bond to the surface of the skin without chemical and mechanical irritation. This integration defines access points for a small set of sweat glands such that perspiration spontaneously initiates routing of sweat through a microfluidic network and set of reservoirs. Embedded chemical analyses respond in colorimetric fashion to markers such as chloride and hydronium ions, glucose, and lactate. Wireless interfaces to digital image capture hardware serve as a means for quantitation. Human studies demonstrated the functionality of this microfluidic device during fitness cycling in a controlled environment and during long-distance bicycle racing in arid, outdoor conditions. The results include quantitative values for sweat rate, total sweat loss, pH, and concentration of chloride and lactate. \n\n# INTRODUCTION \n\nA convergence of advances in materials, mechanics design, and specialized device architectures is beginning to establish the foundations for a next generation of wearable electronic technologies, where sensors and other functional components reside not in conventional rigid packages mounted on straps or bands but instead interface directly on the skin $(1,2)$ . Specifically, devices that combine soft, low-modulus physical properties and thin layouts allow robust, nonirritating, and long-lived interfaces with the human epidermis (2). This developing field involves innovative ideas in both organic and inorganic functional materials, where mechanical and manufacturing science play important roles. Although most devices described in the literature focus on measurement of physical characteristics such as motion, strain, stiffness, temperature, thermal conductivity, biopotential, electrical impedance, and related parameters $(l,3-l O)$ , complementary information—often with high clinical value—could be realized through capture and biochemical analysis of biofluids such as sweat $(l l,\\ l2)$ . \n\nAs a representative biofluid, sweat is of particular interest owing to its relative ease of noninvasive collection and its rich content of important biomarkers including electrolytes, small molecules, and proteins (13, 14). Despite the importance of sweat analysis in biomedicine, interpreting information from sweat can be difficult due to uncertainties in its relationship with other biofluids, such as interstitial fluid and blood, and due to the lack of biomedical appliances for direct sampling and detection of multiple biomarkers without evaporation (15). In situ quantitative analysis of sweat is nevertheless of great interest for monitoring of physiologic health status (for example, hydration state) and for the diagnosis of disease (for example, cystic fibrosis) (16, 17). Existing systems for whole-body sweat collection have been confined to the laboratory (18), where standard chemical analysis technologies (chromatography, mass spectroscopy, and electrochemical detection) can reveal the composition of collected samples (19). Recent attempts to detect and collect sweat simultaneously involve direct contact with sensors on the skin (for example, temporary tattoo) where fabric or paper substrates accumulate sweat for electrochemical and/or optical assessment (20). For instance, electrochemical sensors directly laminated on the epidermis can detect chemical components, such as sodium ions and lactate, in real time (21–23). Colorimetric responses in functionalized porous substrates can yield chemical information, such as the pH of sweat, and further enable simple quantitative assays using devices capable of capturing high-quality digital images, such as smartphones (24–26). Radio frequency identification systems, which can be integrated on top of porous materials for wireless information transfer, provide additional functionality (27, 28). These and related technologies can quantify sweat generation rate (27), but because the sweat gland density and overall areas are typically unknown, the total sweat rate and volumetric loss cannot be determined accurately. In addition, the most widely explored formats do not simultaneously reveal the concentration of multiple chemical components, nor do they offer full compatibility with the growing availability of soft, skin-mounted electronics, physical sensors, radio technologies, and energy storage devices. \n\nHere, we report a type of thin and soft, closed microfluidic system that can directly and reliably harvest sweat from pores on the surface of the skin. The device routes this sweat to different channels and reservoirs for multiparametric sensing of markers of interest, with options for wireless interfaces to external devices for image capture and analysis. This type of microfluidic technology builds substantially on recently described epidermal electronic, photonic, and optoelectronic systems $(1,29–31)$ through the addition of fluid handling and capture, and biochemical analytical capabilities. The devices can mount at multiple locations on the body without chemical or physical irritation by use of biocompatible adhesives and soft device mechanics, including flexible and stretchable properties, and watertight interfaces. These devices measure total sweat loss, pH, lactate, chloride, and glucose concentrations by colorimetric detection using wireless data transmission. Tests included two human trials: a controlled, indoor, mild sweat– inducing study, and a “real-world,” outdoor-use study conducted during a long-distance bicycling race. \n\n# RESULTS Soft epidermal microfluidic device for sweat monitoring \n\nThe soft, epidermal microfluidic device technology introduced here adheres and conforms to the skin in a manner that captures and routes sweat through a network of microchannels and reservoirs—using a combination of capillarity and action of the natural pressure $({\\sim}70\\mathrm{kPa})$ 1 associated with perspiration—for volumetric assessment and chemical analysis in situ (13). Low-modulus biocompatible materials, soft silicone elastomers $({\\sim}1\\ \\mathrm{MPa})$ , manipulated using soft lithography defined the microfluidic constructs (diameter, $3\\ \\mathrm{cm}$ ; thickness, ${\\sim}700~\\upmu\\mathrm{m})$ (Fig. 1 and fig. S1). The specific designs can retain ${\\sim}50~\\upmu\\mathrm{l}$ of sweat corresponding to an effective working time of 1 to 6 hours of exercise, depending on the rate of sweat loss and the mounting location on the body (12 to $120\\upmu\\mathrm{l/hourpercm}^{2})$ (32). Stretchable electronics technology allows direct integration of wireless sensing and data transfer capabilities into these platforms. \n\nDevices are composed of a multilayer stack of three subsystems: (i) a skin-compatible adhesive layer with micromachined openings that define the areas of sweat collection, (ii) a sealed collection of soft microfluidic channels and reservoirs filled with color-responsive materials for quantitative analysis of sweat volume and chemistry, and (iii) a magnetic loop antenna and associated near-field communication (NFC) electronics for interfacing to external wireless devices (Fig. 1A). A medical-grade acrylic adhesive film ensured stable, strong, and seamless adhesion $({\\sim}5.7~\\mathrm{N})$ of the device to the skin without irritation in a manner that offered compatibility with skin, even at regions of substantial hair coverage or in the presence of sweat (fig. S2). This adhesive exhibited about five times greater adhesion force than typical medical adhesives such as Tegaderm $(1.02\\:\\mathrm{N})$ (33). The thin geometry $(25\\upmu\\mathrm{m})$ and low modulus $({\\sim}17\\mathrm{kPa})$ of this layer provided stress release during deformation of the skin (fig. S2), facilitating comfort and longterm wearability. Openings defined the sweat harvesting areas $3\\mathrm{mm}$ diameter, corresponding to ${\\sim}10$ sweat glands) (34) through which sweat could pass into inlet regions of the overlying soft microfluidic system (Fig. 1B). The pressure that drives fluid flow arises from the action of the sweat glands themselves, assisted by capillary effects in the microchannels and the materials embedded within them. The conformal contact of the adhesive layer inhibited lateral flow of sweat from regions located outside the defined openings, ensuring that fluid issuing from the harvesting area dominated the sweat sample (fig. S3). \n\nThe microfluidic system consisted of a bottom polydimethylsiloxane (PDMS) layer (thickness, $500~{\\upmu\\mathrm{m}},$ ) embossed with appropriate relief geometry (uniform depth, $300~{\\upmu\\mathrm{m}}.$ ) and filled with reagents for colorimetric analysis (Fig. 1, A and B). A top-capping layer of PDMS served as a seal (thickness, $200~{\\upmu\\mathrm{m}})$ . Our particular layout included four circular chambers (diameter, $4~\\mathrm{mm}$ ) as independent reservoirs for analysis, preventing any cros-talk, that were surrounded by the outer perimeter by an orbicular serpentine channel. This channel and each of the reservoirs were connected by separate guiding channels to hole segments (diameter, $0.5\\mathrm{mm}$ ) that spatially aligned with openings (diameter, $3\\mathrm{mm}$ ) in the skin adhesive layer (Fig. 1, B and C). To avoid backpressure that can impede fluid flow, all channels and reservoirs interfaced to an outlet microfluidic channel (width, $100\\upmu\\mathrm{m})$ that terminated on the top-side edge of the device (Fig. 1B). Quantitative colorimetric assay reagents in the reservoirs enabled assessment of pH and the concentration of selected essential markers, including glucose, lactate, and chloride, through either enzymatic or chromogenic reactions. Hence, the colorimetric schemes embedded in the current devices did not afford real-time tracking of changes in analyte concentration. A water-responsive chromogenic reagent in the serpentine channel allowed determination of the extent of filling with sweat, which could be converted to overall sweat rate and volume. \n\nSpecially formulated variants of PDMS offer physical characteristics that are attractive for this application, including optical transparency, ease of patterning into microfluidic systems, biocompatibility, and favorable mechanics (low modulus, ${\\sim}145\\ \\mathrm{kPa}$ ; high elasticity, up to ${\\sim}200\\%$ strain at break) (35). The soft mechanics and thin geometry enabled soft, nonirritating intimate contact with the skin through principles similar to those established for epidermal electronics (2, 36). The finite element analysis (FEA) results of strain/stress distributions and corresponding optical images in Fig. 1E show deformation of a representative device under various mechanical distortions of an underlying phantom skin sample as a support (a PDMS substrate exhibiting similar mechanical properties to skin). The maximum normal and shear stresses at the device/phantom skin interface were far below the threshold for somatosensory perception of forces $(20\\mathrm{kPa})$ during ${\\sim}30\\%$ stretch of the skin (fig. S4) (37). These elastomeric microfluidic devices exhibited an effective modulus of ${\\sim}0.16~\\mathrm{MPa}$ , comparable to human skin and previously reported epidermal devices (37, 38). \n\nIntegrated electronics allow wireless interfaces to external computing and digital analysis systems using common platforms such as the smartphone. Our technology capitalized on NFC schemes to launch image capture and analysis software on such an external device and/or to read the temperature from an integrated sensor (movies S1 and S2). The overall designs allowed these stretchable electronic systems to operate under physical deformation without significantly altering the mechanical properties of the soft microfluidic structures or the overall device. FEA results demonstrated that the maximum strain in the copper layer was below the elastic limit $(0.3\\%)$ under all loading conditions (fig. S5) (39). Reference marks on the top of the device platform (Fig. 1B) included a white dot and black crosses for color balancing to allow accurate color extraction under arbitrary lighting condition (fig. S6). The crosses also helped determine the position and orientation from the images (fig. S7). \n\nOptimizing the design of the epidermal microfluidic device We optimized the materials and channel designs to collect sweat in situ, with soft, stretchable mechanics for high structural stability, low vapor permeability, and minimal backpressure (flow impedance into the channel). Figure 2A is a sketch of the channel geometry, representing the area of the outlet and the serpentine channel, used for theoretical calculation of the essential mechanics and flow properties. The blue and red dashed boxes highlight the dimensions of the serpentine and outlet channels, respectively. The outlet channels are necessary to relieve backpressure, but they also yield some sweat loss as water (sweat) vapor. The water vapor loss showed little dependence on the length of the outlet channel, whereas the backpressure was linearly proportional to this length according to calculations for a model system (fig. S8 and Fig. 2B). A short outlet channel length of $2.5~\\mathrm{mm}$ was chosen to minimize backpressure. Our calculations further indicated that the vapor loss with $100\\mathrm{-}\\upmu\\mathrm{m}$ -wide channels was ${\\sim}3.2$ -fold lower than with $800\\mathrm{-}\\upmu\\mathrm{m}$ -wide channels, whereas $25\\mathrm{-}\\upmu\\mathrm{m}$ -wide channels differed by only ${\\sim}1.1$ -fold from $100\\mathrm{-}\\upmu\\mathrm{m}$ -wide channels (Fig. 2B). For widths under $100~{\\upmu\\mathrm{m}};$ , the backpressure notably increased and bending deformation of the device was obstructed, with negligible effects on vapor loss. Considering calculated values and practical resolution limits of soft lithography, optimized outlet channel dimensions of $100\\upmu\\mathrm{m}$ in width and $2.5~\\mathrm{mm}$ in length were selected. \n\n![](images/816f1e774dcdf3dad1212a6eb0f6516d71a019fbbea2f28ffb2325b5d6d6c7f6.jpg) \nFig. 1. Schematic illustrations, optical images, and theoretical stress modeling of an epidermal microfluidic biosensor integrated with flexible electronics for swea monitoring. (A) Schematic illustration of an epidermal microfluidic sweat monitoring device and an enlarged image of the integrated near-field communication (NFC) system (inset). (B) Illustration of the top, middle, and back sides of the device. The reference color (white and black) markers are on the top side, along with the NFC electronics. The microfluidic channels with colorimetric assay reagents (water, lactate, chloride, glucose, and pH) are in the middle. The bottom side consists of a uniform layer of adhesive bonded to the bottom surfaces of the PDMS-enclosed microchannels, with openings that define sweat access and inlets that connect to these channels. (C) Cross-sectional diagrams of the cuts defined by the dashed lines (a) and (b) shown in the top side illustration in (B). (D) Optical image of a fabricated device mounted on the forearm. (E) FEA results of stress distribution associated with devices on phantom skin (PDMS) and respective optical images under various mechanical distortions: stretching at $30\\%$ strain, bending with 5 cm radius, and twisting. \n\nAs with vapor loss and backpressure, stretchability and structural stability are two other competing issues that demand careful optimization. Although thin geometries and low-modulus elastomers are key to achieving mechanical compatibility with the skin, such characteristics also yield substantial deformation or even collapse of channels by external pressure (40), either in the as-fabricated form or in states associated with natural deformations of the skin. Modeling yielded predictions for percentage changes in the volume of the serpentine channel associated with externally applied pressures between 100 and $400\\ \\mathrm{Pa}$ (Fig. 2C) comparable to those that might be associated with a gentle touch by a fingertip (41). The volume change increased with the aspect ratio (AR; width to height). For example, the volume change for AR 5 (width, $1.5~\\mathrm{mm}$ ; height, $300~{\\upmu\\mathrm{m}})$ was about fivefold greater than that for AR 3.3 (width, $1.0\\ \\mathrm{mm}$ ; height, $300~{\\upmu\\mathrm{m}},$ ). Because choices for channel geometries must also consider the total volume of sweat that can be captured and the overall size of the device, we selected a lower limit of AR 3.3. In addition, the serpentine channel layouts provided a convenient means to increase the total channel volume for a given device size (fig. S9). These considerations defined the overall design, the cross-sectional channel dimensions, and the outlet shapes illustrated in Fig. 2D. \n\n# Microfluidic sweat capture and quantitative colorimetric analysis \n\nQuantitative in vitro testing of microfluidic performance involved a simple, artificial sweat pore system (Fig. 2, E and F, and fig. S10) to mimic human eccrine sweat glands (42), consisting of a perforated PI membrane (pores with a diameter of $60~{\\upmu\\mathrm{m}}$ , ${\\sim}100$ pores per $\\mathrm{cm}^{2}$ ) mounted in a fixture with an underlying fluid reservoir connected to a syringe pump. A device $(0.07\\mathrm{cm}^{2}$ of harvesting surface area) laminated on the perforated membrane captured dyed water pumped at $5.5\\upmu\\mathrm{l/hour}$ (Fig. 2G), demonstrating the quantitative analysis of liquid uptake (movie S3). As shown in movie S3, the experimentally determined harvested liquid volume in the channel is consistent with the input volume introduced by the syringe pump and with linear hydrodynamic flow in the microfluidic channel. The experiments revealed negligible loss of water vapor and no fluid leakage under these conditions. \n\nRegarding device design, three factors determine the resolution in determination of sweat rate: (i) the rate of fluid flow into the reservoirs and the serpentine channel, (ii) the harvesting area, and (iii) the time and spatial resolution of the camera system and image analysis software. For a device layout with harvesting area $({\\sim}10\\ \\mathrm{mm}^{2})$ , human studies presented subsequently showed volumetric sweat harvesting rates of ${\\sim}1.2$ to $12~\\mathrm{\\textmul/hour}$ , corresponding to linear filling rates of ${\\sim}0.07$ to $0.7\\ \\mathrm{mm/min}$ along the serpentine channels. The reservoirs fill within ${\\sim}0.3$ to 3.2 hours at these sweating rates, with times that scale linearly with reservoir volume. Decreasing the cross-sectional area of the channel increases the filling rate proportionally. For image capture once every $5\\mathrm{min}$ , a spatial resolution of ${\\sim}0.35$ to $3.5\\mathrm{mm}$ can easily resolve changes in the positions of the fluid fronts, providing 12 data points within a ${\\sim}60\\ –\\operatorname*{min}$ timeframe (13). \n\nThe colorimetric sensing approach allowed simple, rapid quantitative assessment of the instantaneous rate and total volume of sweat loss, the $\\mathrm{\\pH}.$ , as well as the concentration of chloride, lactate, and glucose in the sweat (Fig. 3A). The first parameters relate to thermal regulation and dehydration, where continuous monitoring yields important information of relevance to electrolyte balance and rehydration (43). In the orbicular serpentine channel, cobalt (II) chloride (that is, $\\mathrm{CoCl}_{2}$ ) contained in a coating of a polyhydroxyethylmethacrylate (pHEMA) hydrogel matrix served as a colorimetric indicator. As sweat entered the channel, the anhydrous cobalt (II) chloride chelated with water to form hexahydrate cobalt chloride $(\\mathrm{CoCl}_{2}{\\bullet}6\\mathrm{H}_{2}\\mathrm{O});$ , generating a change in color from deep blue $\\langle\\lambda_{\\mathrm{max}}=657\\rangle$ ) to pale purple $\\langle\\lambda_{\\mathrm{max}}=511$ ) (Fig. 3B). The position of the leading edge that defines this color change, along with the dimensional characteristics and geometry of the channel, yields quantitative information on the sweat rate and volume. Owing to the thin layer $(\\sim25\\upmu\\mathrm{m})$ coated on the channel wall and the hydrophilic properties of the pHEMA hydrogel matrix, the hydrodynamics of the flow within the channel were not influenced during conditions of momentary flow (fig. S11, A to D). The sweat could, however, continue to travel slowly through the channel by spontaneous internal flow $(0.68\\upmu\\mathrm{l/hour})$ , with the possibility of a ${\\sim}2\\%$ reading error (fig. S11, E and F). This artifact does not occur in channels without the hydrogel; its effect could be eliminated, for practical purposes, by patterning the hydrogel into short segments (fig. S12). \n\nFour different paper-based colorimetric chemical assays resided in the central reservoirs. The cellulose matrices in each reservoir could be filled with as little as 5 to $10~\\upmu\\mathrm{l}$ of sweat sample. The color changes occurred on time scales of ${<}1\\ \\mathrm{min}$ (movie S4). The concentration of lactate in sweat is an indicator of exercise intolerance and tissue hypoxia (44, 45). Enzymatic reactions between lactate and cofactor $\\mathrm{\\bar{NAD}^{+}}$ (nicotinamide adenine dinucleotide) by lactate dehydrogenase and diaphorase induce a change in color of a chromogenic reagent (that is, formazan dyes). The formulation of enzyme and dyes in the detection cocktail solution ensured a dynamic range compatible with human sweat. The color change in the detection reservoir correlated with the concentration of lactate throughout the relevant range expected in sweat (1.5 to $100~\\mathrm{mM},$ ) (Fig. 3C) (13, 46, 47). \n\nGlucose concentration could also be analyzed by an enzymatic reaction (Fig. 3D). Glucose oxidase physically immobilized in a cellulose matrix produces hydrogen peroxide associated with oxidation of glucose and reduction of oxygen. After this reaction, iodide oxidizes to iodine by peroxidase to yield a change in color from yellow (iodide) to brown (iodine), to an extent defined by the concentration of glucose (48, 49). We note that glucose concentration in sweat is typically one order of magnitude lower than in plasma; the range of sensitivity in the reported devices could diagnose hyperglycemia, for example, limit of detection $(\\mathrm{LOD})=\\sim200\\upmu\\mathrm{M}$ (fig. S13) (50). Further development of colorimetric chemistries based on enzymatic reactions and/or enzyme-mimetic nanomaterials could improve the LODs (51, 52). Similarly, creatinine, a vital marker of hydration status and renal function, was detected in sweat using a mixture of enzymes (creatininase, creatinase, and peroxidase) and a corresponding responsive dye (4-aminophenazone) (Fig. 3E) (53). \n\n![](images/561f2abdda093eda827d1d34c3d1cba2086ce0dbba4527959306d670da84acc5.jpg) \nFig. 2. Analysis of key design features and demonstration of epidermal microfluidic devices. (A) Sketch of the channel geometry for numerical calculation. The blue and red dashed boxes highlight the dimensions of the serpentine and outlet channels, respectively. (B) Experimentally determined water vapor loss from a microfluidic channel as a function of width (w) and length (L) of the outlet channel with a fixed height of $300~{\\upmu\\mathrm{m}}$ . Inner pressure as a function of the outlet channel width was also determined from the model (red line). The orange shading highlights the optimal channel geometry. Data are presented as the average value, and error bars represent SD $\\left(n=3\\right)$ ). (C) Model prediction of the change in volume of the serpentine channel as a function of AR [ratio of width $a$ to height $h$ of the serpentine channel in (A), blue dashed box] under various pressures $(\\Delta P=100,$ 200, and $400~\\mathsf{P a}$ ). $\\Delta P$ sents press difference between the inside and outside of the serpentine channel. Dotted vertical lines show two representative ARs (10:3 and 5:1). (D) Picture of a fabricated epidermal microfluidic structure corresponding to the theoretical results and cross-sectional scanning electron microscopy (SEM) images of the outlet (red dashed box) and serpentine (blue dashed box) channels. (E) Experimental setup of the artificial sweat pore system. (F) SEM images of the polyimide (PI) membrane mimicking human sweat glands. (G) Demonstration of hydrodynamic fluid flow through the microfluidic device using the artificial sweat pore system at the rate of $5.5~\\upmu\\mathrm{l/hour}$ . \n\n![](images/80732e9c6442cfc41a2c1f438c6b556af35e0bb81c6c8d9297410e8cb23c5b90.jpg) \nFig. 3. Quantitative colorimetric analysis of markers in sweat. (A) Colorimetric detection reservoirs that enable determination of (B) total water (sweat) loss and concentrations of (C) lactate, (D) glucose, (E) creatinine, (F) pH, and (G) chloride ions in sweat. (B to G) Corresponding quantitative analysis conducted by (i) ultraviolet (UV)–visible spectroscopy and (ii) optical images as a function of analyte concentration. The presented color for (i) each spectrum corresponds to (ii) the color exhibited at the detection reservoir in the device. The insets in the spectra provide calibration curves for each of the analytes. The inset in (E) shows the response over a reduced range of concentrations. \n\nIn sweat, $\\mathrm{\\pH}$ is often considered an index of hydration state. The concentration of chloride ions serves as a marker of cystic fibrosis and altered electrolyte levels correspond to a sodium ion imbalance (17). A universal pH indicator that includes dyes such as bromothymol blue, methyl red and phenolphthalein yielded colorimetric responses over a medically relevant range $\\mathrm{\\pH}5.0$ to 7.0) (Fig. 3F). Colorimetric detection of chloride involved competitive binding between $\\mathrm{Hg}^{2+}$ and $\\mathrm{Fe}^{2+}$ with 2,4,6-tris(2-pyridyl)-s-triazine (TPTZ). In the presence of chloride ions, iron ions $(\\mathrm{Fe}^{2+})$ bind with TPTZ, whereas $\\mathrm{Hg}^{2+}$ participates as $\\mathrm{HgCl}_{2},$ thereby inducing a change in color from transparent to blue as shown in Fig. 3G. Although PDMS is known to have some permeability to water and certain small molecules, the colorimetric responses in these devices are unaffected for most practical applications due to the relevant operational time scale and the analyte chemistries used (fig. S14). \n\n# NFC interface to a smartphone and image processing \n\nRecording color changes and converting them into quantitative information were accomplished by digital image capture and analysis. Figure 4A shows frames from a video clip (movie S1) in which the proximity of a smartphone to the device initiated image capture and analysis software automatically using NFC. The user then adjusted the viewing position to the targeted spot to determine exact RGB (red, green, and blue) color in situ. The application digitized RGB color information on the screen, enabling the user to read the concentration of the marker. The previously reported ultrathin NFC electronics (39) integrated on the top of the microfluidic device enabled wireless communication to external devices, with stable operation and a soft, biocompatible set of mechanical properties, even under a $30\\%$ strain condition (39). The NFC electronics facilitated image capture, and built-in sensors provided wireless, digital data on skin temperature (fig. S15 and movie S2). \n\n![](images/b8239b857add8e1c813afb729b4ec429857bd03ad24dbcb335add3e1625f1ffa.jpg) \nFig. 4. NFC interface to a smartphone and image processing approaches. (A) Pictures demonstrating NFC between a sweat monitoring device and a smartphone to launch software for image capture and analysis. (B) Images of the epidermal microfluidic biosensor (left) before and (right) after injecting artificial sweat. (C) Location tracking of sweat accumulation with polar coordinates and their relationship to total captured volume of sweat (inset). (D) Standard calibration curves between normalized $\\%R G B$ value and concentration of markers for quantitative analysis $(n=3,$ error bars represent the SD). Each vertical colored bar represents the marker concentration determined from the corresponding reservoirs in the right image of (B) as an example. \n\nAfter wirelessly collecting the images, digital processing for assessment of color changes was achieved as shown in Fig. 4 (B to D). Reference color markers (true white and black) allowed white balancing to eliminate the dependence on lighting conditions of practical relevance (daylight, shadow, and various light sources) (fig. S6). In particular, a white dot in the middle of the device and four black crosses distributed near the center established values for $100\\%$ and $0\\%$ in $\\%{\\mathrm{RGB}}$ coordinates, respectively (Fig. 4B). The crosses further allowed rotations/translations of the images to facilitate accurate analysis of sweat rate and volume in the serpentine channel (fig. S7). After image correction, the digital color data (in $\\%{\\mathrm{RGB}}$ format) were converted into analyte concentrations using calibration curves (Fig. 4D). We could reliably measure changes of $0.5~\\mathrm{pH}$ units and 0.2, 0.3, and $0.1~\\mathrm{mM}$ of chloride, lactate, and glucose concentrations, respectively, corresponding to a $1\\%$ change in the R channel of the RGB images. The calibration curve in Fig. 4C captures the pseudo-linearities associated with the serpentine shape of the channel. The angle of the filling front (the leading edge of the color change) in the serpentine channel defined the volume of sweat collected, thereby allowing calculation of total sweat loss and, with the time interval, total sweat rate. \n\n# Human testing of the skin-mounted sweat sensor \n\nThe first demonstration involved nine human subjects with devices mounted on two different body locations (lower back and volar forearm; Fig. 5B) and with two different harvesting areas (size of the opening in the adhesive shown in Fig. 5A) during intermediatelevel activity on cycle ergometers under controlled temperature $(38^{\\circ}\\mathrm{C})$ and $50\\%$ relative humidity conditions. We compared the performance of the device in situ to conventional procedures that use absorbing pads applied onto the skin with subsequent weighing and laboratorybased analyses, such as spectrophotometry. \n\nWe quantified regional sweat rate normalized to unit area over the course of 1 hour (Fig. 5, C and D). Although the rates exhibited great variation among individual subjects, those measured on the lower back were typically ${\\sim}2.3$ -fold greater than on the volar forearm, consistent with expectations from studies using conventional techniques (54). Rates determined using devices with large harvesting areas showed agreement with those obtained using absorbing pads (Fig. 5E). Furthermore, the devices accurately captured the volume and rate information continuously, without the need for removal. Notably, the y intercept in Fig. 5E corresponds to the limit of sweat measurement with the absorbing pad due to water evaporation $(0.349~\\mathrm{g/cm}^{2}~\\mathrm{s}$ of water evaporation at $38^{\\circ}\\mathrm{C},$ $50\\%$ relative humidity) during sample collection, highlighting one of its limitations. Devices with small harvesting areas yielded somewhat higher inferred rates than those with larger harvesting areas, perhaps due to alterations in perspiration behavior caused by the physical presence of the device (Fig. 5E) (55). \n\nConcentrations of the markers chloride, glucose, lactate, and pH obtained by the colorimetric readouts demonstrated excellent agreement with conventional laboratory analysis of sweat collected from absorbing pads as shown in Fig. 5F. The glucose concentration in sweat from healthy subjects fell below the LOD for both image and laboratory analysis ( $P<0.05$ refers to differences in background noise only). Bivariate and multivariate statistical analyses, together with Pearson correlation heatmaps and Spearman rank-order statistics, quantified the correlations for all markers tested (fig. S16). The correlation between variations in marker analysis across individual subjects was only partially demonstrated because of the small sample size. \n\nTo examine the mechanical and fluidic integrity of the devices in a demanding exercise scenario, we assessed robustness in adhesion and fluidic collection and capture using devices on volunteers in a competitive long-distance outdoor bicycling race—El Tour de Tucson. Testing involved device placement on the lower back and the volar surface of the forearm of 12 volunteer riders (Fig. 6B). In all cases, the devices performed as anticipated, successfully collecting sweat with regional colorimetric change without patch detachment, even with substantial changes in temperature and humidity. Participants reported no sense of discomfort or limitation in body or arm movement during the cycling. Older subjects (ages 50 to 69 years) had greater rates of sweating in comparison to younger subjects (ages 10 to 29 years), and male subjects exhibited greater rates of sweating than females (Fig. 6E). \n\n# DISCUSSION \n\nThe epidermal microfluidic devices introduced here represent versatile platforms for evaluating athletic performance and monitoring health and disease status. The reported embodiments can detect sweat volume and rate, as well as several key markers including glucose, creatinine, lactate, chloride, and pH. Compared to previously described technologies for sweat analysis consisting of porous materials and fabrics or hydrogels as fluidic interfaces, our systems are unique in their use of fully integrated, soft microfluidics consisting of a network of functionalized channels and reservoirs for sweat capture, routing, and storage with spatially separated regions for analysis. By exploiting advanced concepts in microfluidic total analysis systems and lab-on-a-chip technologies and by integrating skin-conformal electronics, our devices have the potential to provide further quantitative modes of use beyond opportunities afforded by the embodiments reported here or by other approaches. In addition to systematic investigations of the key engineering aspects and design parameters, initial studies demonstrated practical utility through tests on nine volunteers during moderate-intensity exercise in controlled conditions, with correlation of measured results to standard methods based on absorbent pads and laboratory chemical analyses. Evaluations on 12 cyclists during high-intensity physical exertion revealed real-world performance without loss of adhesion, leakage of fluids, or other modes of failure and without discomfort or irritation at the device/skin interface. \n\nThe soft mechanical properties, biocompatible constituent materials, digitally analyzable colorimetric responses, and overall careful optimization of structural, evaporative, and fluidic properties are integral to the effectiveness of these devices and differentiate them from other sweat analysis technologies. Future opportunities could explore the use of these technologies for real-time, in situ sweat analysis and as storage vehicles for ex situ laboratory evaluation. In this latter context, it is important to note that we observed that the microfluidics structures described here can hold captured sweat for ${\\sim}125$ hours upon removal from the skin and sealing of the open channels ${\\sim}75$ hours without sealing) with negligible deterioration of colorimetric analysis. These possibilities, together with the development of on-board stretchable electronics for electrochemical biosensing, represent important directions of future research. \n\nThe limitations of the current devices are primarily in the range of chemical reagents that are available for accurate colorimetric analysis \n\nFig. 5. Human trials of sweat monitoring devices in a temperature- and humidity-controlled room $35^{\\circ}C$ at $50\\%$ relative humidity). (A) Images of two device designs used for the studies. The brown color corresponds to the adhesive layer on the back sides of the devices, with small and large harvesting areas (inlets). Absorbing pads served as reference controls. (B) Illustration indicating locations of sweat patches on the subjects (volar forearm and lower back). (C) Images of two different types of sweat patches (small and large harvesting areas) applied to the lower back and volar forearm collected at various times during the study. (D) Sweat rate determined at the lower back and volar forearm. Bars represent mean of $n=8;$ error bars represent SD. ${^{*}P}<0.05,$ , two-tailed t test. (E) Correlation of sweat rate between the epidermal microfluidic devices and the reference-absorbing pads $(n=7)$ . (F) Marker concentrations in sweat obtained by image processing of data from the device (unshaded) versus laboratory-based analysis of sweat collected from absorbing pads (shaded) $(n=7)$ ). ${^{\\ast}P}<0.05,$ , two-tailed t test. \n\nof markers at relevant ranges of concentration. Potential exists for extending colorimetric schemes to include enzymatic reactions or chromogens aimed at a broad range of possible applications for specific clinical diagnosis or for illicit drug use detection. However, the microfluidic channel/ reservoir designs reported here cannot be easily designed to provide information on time-dependent changes in marker concentration detection. Advanced electronic or nonelectronic strategies for such temporal tracking of sweat chemistry are, therefore, of interest. An alternative approach is in microfluidic designs that enable time-dependent sampling of sweat into spatially distinct reservoirs for separate analysis. In all cases, digital image capture analysis represents a simple, “wireless” means of quantitation. Direct electronic readout represents an additional possibility, where epidermal power supplies or wireless power transfer schemes could be useful. Further field studies are needed to demonstrate accuracy in realistic, demanding use scenarios. \n\n![](images/a7d80279c028bd02d08bce5d98aee9cac588b32b8be2217af324d3c82365bc37.jpg) \n\nIn addition to their use in sweat monitoring, similar systems can be used as direct capture and storage vehicles for subsequent colorimetric or conventional laboratory-based analysis for various accumulated biofluids such as tears, saliva, or discharges from wounds, especially for small sample volume collection $(<\\sim50~\\upmu\\mathrm{l})$ . The same platforms can be combined with electronic or pharmacological means to actively initiate the release of sweat or extraction of other biofluids (for example, interstitial fluids). In both active and passive collection modes, the devices could be used in athletic and military training to gain insight into critical electrolyte loss, thereby guiding earlier supplementation before symptomatic cramping and “hitting the wall” points in time at which appropriate preventative treatment is no longer effective. In this scenario, and in others of interest, data accumulated over time from individual users could serve as the basis for the development of analytic approaches for interpreting trends in marker concentrations, with the potential to provide warning signs associated with physical activities that lead to abnormal responses. The intrinsically simple, low-cost nature of the devices may facilitate rapid, broad distribution for use in these contexts. \n\n![](images/a8ea1dfab5456abf1552b4d072c9499608cc318428a00ab2245b42f88493608b.jpg) \nFig. 6. Human trials of sweat monitoring devices on cyclists competing in an outdoor race. (A) Illustration of locations of devices on the cycling subjects (volar forearm and lower back). (B) Histogram of the age distribution of the subjects. (C) Temperature and humidity during the race. (D) Elevation profile of the course. (E) Devices on the volar forearms of several subjects, imaged after ${\\sim}84~\\mathsf{k m}$ of cycling (that is, middle point of total race). (The purple ink in the lower part of the image on the right is from a marking formed on the skin using a pen before application of the device.) \n\n# MATERIALS AND METHODS Study design \n\nThe objectives of indoor and outdoor human trial studies were to investigate the feasibility of using these epidermal microfluidics devices in practical scenarios under controlled and uncontrolled environmental conditions and during moderate and vigorous exercise. Nine subjects were recruited through the Clinical Research Laboratories, LLC for indoor studies with anonymous collections of information including date of birth, gender, contraceptive status, weight, height, body mass index (BMI), blood pressure, and information from a simple survey of medical condition to ensure that all subjects were healthy. The experimental conditions, including temperature, humidity, time course of application of the device, and weight of absorbing Webril pads for sweat collection, were all controlled and documented. Results obtained from image analysis methods (described in the “Near-field communication and image processing for quantitative analysis” section in the Supplementary Materials) were compared with those from chemical laboratory analysis. For the outdoor study, 12 healthy subjects volunteered under eligibility requirements including enrollment and participation in El Tour de Tucson, a 104-km bike race. Age, height, and weight were recorded from subjects at the start of the race and used to calculate BMI and body surface area. Environmental conditions including temperature, humidity, and UV index were recorded every 2 and 3 hours from information provided by the National Weather Service. In both studies, sweat patches were placed on two different geographical body areas (volar arm and lower back), and image data were obtained by smartphone and digital single-lens reflex cameras. For full details, see the Supplementary Materials. \n\n# Fabrication of epidermal microfluidic devices with integrated electronics for colorimetric sweat analysis \n\nStandard soft lithographic techniques enabled fabrication of epidermal microfluidic devices (56). Briefly, casting and curing PDMS against lithographically prepared molds yielded solid elastomers with features of relief on their surfaces. Bonding separate pieces of PDMS formed in this manner defined sealed microfluidic channels and containment reservoirs. Mechanical punches created openings to define the inlets for sweat collection. A separate, double-sided thin adhesive layer with matching holes bonded to the bottom surface of the device on one side and to the skin on the other. As an option, separately fabricated thin electronic systems with open architectures were mounted on the top surface. For colorimetric analysis, the chromogenic reagents for detecting glucose (a mixture of glucose oxidase, horseradish peroxidase, trehalose, and potassium iodide in sodium citrate buffer solution), lactate (D-Lactase Assay Kit; Sigma-Aldrich), chloride [chloride detection reagent (Chloride Assay Kit; SigmaAldrich) titrated with $\\mathrm{Hg}(\\mathrm{SCN})_{2}]$ , and $\\mathrm{\\pH}$ [universal $\\mathrm{\\pH}$ indicator solution (Ricca Chemical Company)] were spotted onto filter paper and inserted into containment reservoirs. Cobalt chloride dissolved in pHEMA hydrogel served as a sensor of water in the serpentine channels. Complete fabrication and colorimetric analysis details are provided in the Supplementary Materials. \n\n# Statistical analysis \n\nData are presented with average values and SD unless noted in the figure caption. Pearson and Spearman correlation analyses were conducted on the patch and laboratory results (fig. S16). The matrix of bivariate correlations in analyte concentrations between the patch and laboratory analysis is displayed using a heat map representation. Blue and red denote negative and positive correlations, respectively. Bivariate correlations are described using Spearman rank-order statistics. Analyses were performed using SAS and JMP statistical software. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencetranslationalmedicine.org/cgi/content/full/8/366/366ra165/DC1 \nMaterials and Methods \nFig. S1. Fabrication procedures of the epidermal microfluidic device. \nFig. S2. Determination of adhesion forces and conformal adhesion between the device and skin. \nFig. S3. Observations of sweat at the interface between an adhesive layer and the skin. Fig. S4. Normal (A) and shear (B) stress distribution at the device/skin interface under $30\\%$ stretch. \nFig. S5. Mechanical modeling results for NFC electronics. \nFig. S6. Color balancing performed by internal calibration makers (black crosses and white circle) under various light conditions (A to F) and changes in numeric RGB representation obtained by respective images (G) before and (H) after white balance. \nFig. S7. Image processing for position calibration. Fig. S8. Cross-sectional sketch of the microfluidic channel and outlet channel geometry used, and analytical analysis of backpressure and inner pressure. \nFig. S9. Strategies and optimization of the orbicular channel design. \nFig. S10. Schematic illustration of the artificial sweat pore system. \nFig. S11. Hydrodynamic test to verify the influence of the hydrogel matrix on channel volume. Fig. S12. Assessment of the angular position of the liquid front in partially filled serpentine channels in devices with different hydrogel concentrations and segmented hydrogel patterns. \nFig. S13. Quantitative colorimetric analysis of glucose at low concentrations. \nFig. S14. Colorimetric analysis of device response as a function of time after introduction of artificial sweat. \nFig. S15. Various device configurations. \nFig. S16. Multivariate statistical analysis for correlations in marker concentrations between patch (p) and laboratory (l) analysis. \nMovie S1. NFC between an epidermal microfluidic device and a smartphone to launch software for image capture and analysis. \nMovie S2. NFC between an epidermal microfluidic device and a smartphone to launch software for temperature sensing. \nMovie S3. Hydrodynamic flow in the serpentine channel of epidermal microfluidics on the artificial pore system. \nMovie S4. Hydrodynamic flow in the detection reservoir of epidermal microfluidics on the artificial pore system. \nReferences (57, 58) \n\n# REFERENCES AND NOTES \n\n1. D.-H. Kim, N. Lu, R. Ma, Y.-S. Kim, R.-H. Kim, S. Wang, J. Wu, S. M. Won, H. Tao, A. Islam, K. J. Yu, T.-i. Kim, R. Chowdhury, M. Ying, L. Xu, M. Li, H.-J. Chung, H. Keum, M. McCormick, P. Liu, Y.-W. Zhang, F. G. Omenetto, Y. Huang, T. Coleman, J. A. Rogers, Epidermal electronics. Science 333, 838–843 (2011). \n2. J. A. Rogers, Electronics for the human body. JAMA 313, 561–562 (2015). \n3. M. Kaltenbrunner, T. Sekitani, J. Reeder, T. Yokota, K. Kuribara, T. Tokuhara, M. Drack, R. Schwödiauer, I. Graz, S. Bauer-Gogonea, S. Bauer, T. Someya, An ultra-lightweight design for imperceptible plastic electronics. Nature 499, 458–463 (2013). \n4. D. J. Lipomi, M. Vosgueritchian, B. C.-K. Tee, S. L. Hellstrom, J. A. Lee, C. H. Fox, Z. Bao, Skin-like pressure and strain sensors based on transparent elastic films of carbon nanotubes. Nat. Nanotechnol. 6, 788–792 (2011). \n5. K. Takei, T. Takahashi, J. C. Ho, H. Ko, A. G. Gillies, P. W. Leu, R. S. Fearing, A. Javey, Nanowire active-matrix circuitry for low-voltage macroscale artificial skin. Nat. Mater. 9, 821–826 (2010). \n6. D. Kang, P. V. Pikhitsa, Y. W. Choi, C. Lee, S. S. Shin, L. Piao, B. Park, K.-Y. Suh, T.-i. Kim, M. Choi, Ultrasensitive mechanical crack-based sensor inspired by the spider sensory system. Nature 516, 222–226 (2014). \n7. C. Dagdeviren, Y. Shi, P. Joe, R. Ghaffari, G. Balooch, K. Usgaonkar, O. Gur, P. L. Tran, J. R. Crosby, M. Meyer, Y. Su, R. C. Webb, A. S. Tedesco, M. J. Slepian, Y. Huang, J. A. Rogers, Conformal piezoelectric systems for clinical and experimental characterization of soft tissue biomechanics. Nat. Mater. 14, 728–736 (2015). \n8. R. C. Webb, A. P. Bonifas, A. Behnaz, Y. Zhang, K. J. Yu, H. Cheng, M. Shi, Z. Bian, Z. Liu, Y.-S. Kim, W.-H. Yeo, J. S. Park, J. Song, Y. Li, Y. Huang, A. M. Gorbach, J. A. Rogers, Ultrathin conformal devices for precise and continuous thermal characterization of human skin. Nat. Mater. 12, 938–944 (2013). \n9. J. Viventi, D.-H. Kim, L. Vigeland, E. S. Frechette, J. A. Blanco, Y.-S. Kim, A. E. Avrin, V. R. Tiruvadi, S.-W. Hwang, A. C. Vanleer, Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo. Nat. Neurosci. 14, 1599–1605 (2011). \n10. J.-W. Jeong, W.-H. Yeo, A. Akhtar, J. J. S. Norton, Y.-J. Kwack, S. Li, S.-Y. Jung, Y. Su, W. Lee, J. Xia, H. Cheng, Y. Huang, W.-S. Choi, T. Bretl, J. A. Rogers, Materials and optimized designs for human-machine interfaces via epidermal electronics. Adv. Mater. 25, 6839–6846 (2013). \n11. G. Matzeu, L. Florea, D. Diamond, Advances in wearable chemical sensor design for monitoring biological fluids. Sens. Actuators B Chem. 211, 403–418 (2015). \n12. S. R. Corrie, J. W. Coffey, J. Islam, K. A. Markey, M. A. F. Kendall, Blood, sweat, and tears: Developing clinically relevant protein biosensors for integrated body fluid analysis. Analyst 140, 4350–4364 (2015). \n13. Z. Sonner, E. Wilder, J. Heikenfeld, G. Kasting, F. Beyette, D. Swaile, F. Sherman, J. Joyce, J. Hagen, N. Kelley-Loughnane, R. Naik, The microfluidics of the eccrine sweat gland, including biomarker partitioning, transport, and biosensing implications. Biomicrofluidics 9, 031301 (2015). \n14. W. Gao, S. Emaminejad, H. Y. Y. Nyein, S. Challa, K. Chen, A. Peck, H. M. Fahad, H. Ota, H. Shiraki, D. Kiriya, D.-H. Lien, G. A. Brooks, R. W. Davis, A. Javey, Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529, 509–514 (2016). \n15. J. Heikenfeld, Non-invasive analyte access and sensing through eccrine sweat: Challenges and outlook circa 2016. Electroanalysis 28, 1242–1249 (2016). \n16. P. Salvo, F. Di Francesco, D. Costanzo, C. Ferrari, M. G. Trivella, D. De Rossi, A wearable sensor for measuring sweat rate. IEEE Sensors J. 10, 1557–1558 (2010). \n17. S. Jadoon, S. Karim, M. R. Akram, A. K. Khan, M. A. Zia, A. R. Siddiqi, G. Murtaza, Recent developments in sweat analysis and its applications. Int. J. Anal. Chem. 2015, 164974 (2015). \n18. S. M. Shirreffs, R. J. Maughan, Whole body sweat collection in humans: An improved method with preliminary data on electrolyte content. J. Appl. Physiol. 82, 336–341 (1997). \n19. V. A. LeGrys, R. Applequist, D. R. Briscoe, P. Farrell, R. Hickstein, S. F. Lo, R. Passarell, D. W. Rheinheimer, B. J. Rosenstein, J. E. Vaks, Sweat Testing: Sample Collection and Quantitative Analysis, Approved Guideline [Document C34–A3] (National Committee for Clinical Laboratory Standards, 2000). \n20. S. Coyle, K.-T. Lau, N. Moyna, D. O’Gorman, D. Diamond, F. Di Francesco, D. Costanzo, P. Salvo, M. Giovanna Trivella, D. E. De Rossi, N. Taccini, R. Paradiso, J.-A. Porchet, A. Ridolfi, J. Luprano, C. Chuzel, T. Lanier, F. Revol-Cavalier, S. Schoumacker, V. Mourier, I. Chartier, R. Convert, H. De-Moncuit, C. Bini, BIOTEX-Biosensing textiles for personalised healthcare management. IEEE Trans. Inf. Technol. Biomed. 14, 364–370 (2010). \n21. W. Jia, A. J. Bandodkar, G. Valdés-Ramírez, J. R. Windmiller, Z. Yang, J. Ramírez, G. Chan, J. Wang, Electrochemical tattoo biosensors for real-time noninvasive lactate monitoring in human perspiration. Anal. Chem. 85, 6553–6560 (2013). \n22. T. Guinovart, A. J. Bandodkar, J. R. Windmiller, F. J. Andrade, J. Wang, A potentiometric tattoo sensor for monitoring ammonium in sweat. Analyst 138, 7031–7038 (2013). \n23. A. J. Bandodkar, D. Molinnus, O. Mirza, T. Guinovart, J. R. Windmiller, G. Valdes-Ramirez, F. J. Andrade, M. J. Schöning, J. Wang, Epidermal tattoo potentiometric sodium sensors with wireless signal transduction for continuous non-invasive sweat monitoring. Biosens. Bioelectron. 54, 603–609 (2014). \n24. V. F. Curto, C. Fay, S. Coyle, R. Byrne, C. O’Toole, C. Barry, S. Hughes, N. Moyna, D. Diamond, F. Benito-Lopez, Real-time sweat pH monitoring based on a wearable chemical barcode micro-fluidic platform incorporating ionic liquids. Sens. Actuators B Chem. 171–172, 1327–1334 (2012). \n25. V. Oncescu, D. O’Dell, D. Erickson, Smartphone based health accessory for colorimetric detection of biomarkers in sweat and saliva. Lab Chip 13, 3232–3238 (2013). \n26. L. Shen, J. A. Hagen, I. Papautsky, Point-of-care colorimetric detection with a smartphone. Lab Chip 12, 4240–4243 (2012). \n27. D. P. Rose, M. E. Ratterman, D. K. Griffin, L. Hou, N. Kelley-Loughnane, R. R. Naik, J. A. Hagen, I. Papautsky, J. C. Heikenfeld, Adhesive RFID sensor patch for monitoring of sweat electrolytes. IEEE Trans. Biomed. Eng. 62, 1457–1465 (2014). \n28. X. Huang, Y. Liu, K. Chen, W.-J. Shin, C.-J. Lu, G.-W. Kong, D. Patnaik, S.-H. Lee, J. F. Cortes, J. A. Rogers, Stretchable, wireless sensors and functional substrates for epidermal characterization of sweat. Small 10, 3083–3090 (2014). \n29. L. Gao, Y. Zhang, V. Malyarchuk, L. Jia, K.-I. Jang, R. Chad Webb, H. Fu, Y. Shi, G. Zhou, L. Shi, D. Shah, X. Huang, B. Xu, C. Yu, Y. Huang, J. A. Rogers, Epidermal photonic devices for quantitative imaging of temperature and thermal transport characteristics of the skin. Nat. Commun. 5, 4938 (2014). \n30. T.-i. Kim, J. G. McCall, Y. H. Jung, X. Huang, E. R. Siuda, Y. Li, J. Song, Y. M. Song, H. A. Pao, R.-H. Kim, C. Lu, S. D. Lee, I.-S. Song, G. Shin, R. Al-Hasani, S. Kim, M. P. Tan, Y. Huang, F. G. Omenetto, J. A. Rogers, M. R. Bruchas, Injectable, cellular-scale optoelectronics with applications for wireless optogenetics. Science 340, 211–216 (2013). \n31. J.-W. Jeong, J. G. McCall, G. Shin, Y. Zhang, R. Al-Hasani, M. Kim, S. Li, J. Y. Sim, K.-I. Jang, Y. Shi, D. Y. Hong, Y. Liu, G. P. Schmitz, L. Xia, Z. He, P. Gamble, W. Z. Ray, Y. Huang, M. R. Bruchas, J. A. Rogers, Wireless optofluidic systems for programmable in vivo pharmacology and optogenetics. Cell 162, 662–674 (2015). \n32. K. Sato, F. Sato, Individual variations in structure and function of human eccrine sweat gland. Am. J. Physiol. Regul. Integr. Comp. Physiol. 245, R203–R208 (1983). \n33. J. Klode, L. Schöttler, I. Stoffels, A. Körber, D. Schadendorf, J. Dissemond, Investigation of adhesion of modern wound dressings: A comparative analysis of 56 different wound dressings. J. Eur. Acad. Dermatol. Venereol. 25, 933–939 (2011). \n34. K. Wilke, A. Martin, L. Terstegen, S. S. Biel, A short history of sweat gland biology. Int. J. Cosmet. Sci. 29, 169–179 (2007). \n35. J. N. Lee, C. Park, G. M. Whitesides, Solvent compatibility of poly (dimethylsiloxane)-based microfluidic devices. Anal. Chem. 75, 6544–6554 (2003). \n36. D.-H. Kim, R. Ghaffari, N. Lu, J. A. Rogers, Flexible and stretchable electronics for biointegrated devices. Annu. Rev. Biomed. Eng. 14, 113–128 (2012). \n37. C. H. Lee, Y. Ma, K.-I. Jang, A. Banks, T. Pan, X. Feng, J. S. Kim, D. Kang, M. S. Raj, B. L. McGrane, B. Morey, X. Wang, R. Ghaffari, Y. Huang, J. A. Rogers, Soft core/shell packages for stretchable electronics. Adv. Funct. Mater. 25, 3698–3704 (2015). \n38. X. Liang, S. A. Boppart, Biomechanical properties of in vivo human skin from dynamic optical coherence elastography. IEEE Trans. Biomed. Eng. 57, 953–959 (2010). \n39. J. Kim, A. Banks, H. Cheng, Z. Xie, S. Xu, K.-I. Jang, J. W. Lee, Z. Liu, P. Gutruf, X. Huang, P. Wei, F. Liu, K. Li, M. Dalal, R. Ghaffari, X. Feng, Y. Huang, S. Gupta, U. Paik, J. A. Rogers, Epidermal electronics with advanced capabilities in near-field communication. Small 11, 906–912 (2015). \n40. Y. Y. Huang, W. Zhou, K. J. Hsia, E. Menard, J.-U. Park, J. A. Rogers, A. G. Alleyne, Stamp collapse in soft lithography. Langmuir 21, 8058–8068 (2005). \n41. C. Pang, G.-Y. Lee, T.-i. Kim, S. M. Kim, H. N. Kim, S.-H. Ahn, K.-Y. Suh, A flexible and highly sensitive strain-gauge sensor using reversible interlocking of nanofibres. Nat. Mater. 11, 795–801 (2012). \n42. L. Hou, J. Hagen, X. Wang, I. Papautsky, R. Naik, N. Kelley-Loughnane, J. Heikenfeld, Artificial microfluidic skin for in vitro perspiration simulation and testing. Lab Chip 13, 1868–1875 (2013). \n43. N. A. Taylor, C. A. Machado-Moreira, Regional variations in transepidermal water loss, eccrine sweat gland density, sweat secretion rates and electrolyte composition in resting and exercising humans. Extreme Physiol. Med. 2, 4 (2013). \n44. A. Polliack, R. Taylor, D. Bader, Sweat analysis following pressure ischaemia in a group of debilitated subjects. J. Rehabil. Res. Dev. 34, 303–308 (1997). \n45. S. Biagi, S. Ghimenti, M. Onor, E. Bramanti, Simultaneous determination of lactate and pyruvate in human sweat using reversed-phase high-performance liquid chromatography: A noninvasive approach. Biomed. Chromatogr. 26, 1408–1415 (2012). \n46. I. Alvear-Ordenes, D. García-López, J. A. De Paz, J. González-Gallego, Sweat lactate, ammonia, and urea in rugby players. Int. J. Sports Med. 26, 632–637 (2005). \n47. L. S. Lamont, Sweat lactate secretion during exercise in relation to women’s aerobic capacity. J. Appl. Physiol. 62, 194–198 (1987). \n48. A. W. Martinez, S. T. Phillips, M. J. Butte, G. M. Whitesides, Patterned paper as a platform for inexpensive, low-volume, portable bioassays. Angew. Chem. Int. Ed. 46, 1318–1320 (2007). \n49. A. W. Martinez, S. T. Phillips, E. Carrilho, S. W. Thomas, H. Sindi, G. M. Whitesides, Simple telemedicine for developing regions: Camera phones and paper-based microfluidic devices for real-time, off-site diagnosis. Anal. Chem. 80, 3699–3707 (2008). \n50. T. C. Boysen, S. Yanagawa, F. Sato, K. Sato, A modified anaerobic method of sweat collection. J. Appl. Physiol. 56, 1302–1307 (1984). \n51. H. Wei, E. Wang, $\\mathsf{F e}_{3}\\mathsf{O}_{4}$ magnetic nanoparticles as peroxidase mimetics and their applications in ${\\sf H}_{2}{\\sf O}_{2}$ and glucose detection. Anal. Chem. 80, 2250–2254 (2008). \n52. Y. Song, K. Qu, C. Zhao, J. Ren, X. Qu, Graphene oxide: Intrinsic peroxidase catalytic activity and its application to glucose detection. Adv. Mater. 22, 2206–2210 (2010). \n53. H. Crocker, M. D. S. Shephard, G. H. White, Evaluation of an enzymatic method for determining creatinine in plasma. J. Clin. Pathol. 41, 576–581 (1988). \n54. C. J. Smith, G. Havenith, Body mapping of sweating patterns in male athletes in mild exercise-induced hyperthermia. Eur. J. Appl. Physiol. 111, 1391–1404 (2011). \n55. P. B. Licht, H. K. Pilegaard, Severity of compensatory sweating after thoracoscopic sympathectomy. Ann. Thorac. Surg. 78, 427–431 (2004). \n56. Y. Fainman, L. Lee, D. Psaltis, C. Yang, Optofluidics: Fundamentals, Devices, and Applications (McGraw-Hill Education, 2009). \n57. E. Ventsel, T. Krauthammer, Thin Plates and Shells: Theory: Analysis, and Applications (CRC Press, 2001). \n58. F. M. White, Fluid Mechanics (McGraw-Hill Higher Education, ed. 7, 2010). \n\nFunding: This work was supported by L’Oréal and the Frederick Seitz Materials Research Laboratory at the University of Illinois at Urbana-Champaign. J.K. and U.P. acknowledges the support from the Global Research Laboratory Program (K20704000003TA050000310) through the National Research Foundation of Korea funded by the Ministry of Science. Y.H. acknowledges NIH grant R01EB019337. Author contributions: D.K., A.K., and J.A.R. led the development of the concepts, designed the experiments, interpreted results, and wrote the paper. D.K. and A.K. led the experimental works, with support from S.L., R.M.P., J.K., T.H., S.M., A.B., P.B., M.C.M., K.R.A., K.-I.J., P.W., R.G., and S.H. Y.X., L.W., and Y.H. performed mechanical modeling and simulations. S.L. contributed to the image analysis, and R.M.P., P.B., M.C.M., K.R.A., M.J.S., and G.B. contributed to the organization and design of the human test and provided in-depth discussion. R.M.P., P.B., and G.B. performed statistical analysis. M.J.S., R.M.P., Y.H., and J.A.R. provided technical guidance. All authors contributed to proofreading the manuscript. Competing interests: J.A.R, A.K., and D.K. are inventors on PCT Patent Application PCT/US2015/044638 submitted by The Board of Trustees of the University of Illinois that covers “Devices and related methods for epidermal characterization of biofluids.” The authors declare that they have no competing financial interests. Data and materials availability: All data needed to evaluate the conclusions are present in the paper and/or in the Supplementary Materials. Additional data and materials related to this paper may be requested from J.A.R. \n\nSubmitted 14 January 2016 \nAccepted 28 October 2016 \nPublished 23 November 2016 \n10.1126/scitranslmed.aaf2593 \n\nCitation: A. Koh, D. Kang, Y. Xue, S. Lee, R. M. Pielak, J. Kim, T. Hwang, S. Min, A. Banks, P. Bastien, M. C. Manco, L. Wang, K. R. Ammann, K.-I. Jang, P. Won, S. Han, R. Ghaffari, U. Paik, M. J. Slepian, G. Balooch, Y. Huang, J. A. Rogers, A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat. Sci. Transl. Med. 8, 366ra165 (2016). \n\n# Science Translational Medicine \n\n# A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat \n\nAhyeon Koh, Daeshik Kang, Yeguang Xue, Seungmin Lee, Rafal M. Pielak, Jeonghyun Kim, Taehwan Hwang, Seunghwan Min, Anthony Banks, Philippe Bastien, Megan C. Manco, Liang Wang, Kaitlyn R. Ammann, Kyung-In Jang, Phillip Won, Seungyong Han, Roozbeh Ghaffari, Ungyu Paik, Marvin J. Slepian, Guive Balooch, Yonggang Huang and John A. Rogers \n\nSci Transl Med 8, 366ra165366ra165. DOI: 10.1126/scitranslmed.aaf2593 \n\n# Better health? Prepare to sweat \n\nWearable technology is a popular way many people monitor their general health and fitness, tracking heart rate, calories, and steps. Koh et al. now take wearable technology one step further. They have developed and tested a flexible microfluidic device that adheres to human skin. This device collects and analyzes sweat during exercise. Using colorimetric biochemical assays and integrating smartphone image capture analysis, the device detected lactate, glucose, and chloride ion concentrations in sweat as well as sweat pH while stuck to the skin of individuals during a controlled cycling test. Colorimetric readouts showed comparable results to conventional analyses, and the sweat patches remained intact and functional even when used during an outdoor endurance bicycle race. The authors suggest that microfluidic devices could be used during athletic or military training and could be adapted to test other bodily fluids such as tears or saliva. \n\nARTICLE TOOLS \n\nhttp://stm.sciencemag.org/content/8/366/366ra165 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://stm.sciencemag.org/content/suppl/2016/11/21/8.366.366ra165.DC1 \n\nRELATED CONTENT \n\nhttp://stm.sciencemag.org/content/scitransmed/9/381/eaaf9209.full http://stm.sciencemag.org/content/scitransmed/10/435/eaan4950.full http://stm.sciencemag.org/content/scitransmed/10/465/eaat8437.full http://stm.sciencemag.org/content/scitransmed/10/470/eaau1643.full \n\nREFERENCES \n\nThis article cites 54 articles, 3 of which you can access for free http://stm.sciencemag.org/content/8/366/366ra165#BIBL \n\nPERMISSIONS \n\nhttp://www.sciencemag.org/help/reprints-and-permissions \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1137_15M1054183", + "DOI": "10.1137/15M1054183", + "DOI Link": "http://dx.doi.org/10.1137/15M1054183", + "Relative Dir Path": "mds/10.1137_15M1054183", + "Article Title": "MOMENT TENSOR POTENTIALS: A CLASS OF SYSTEMATICALLY IMPROVABLE INTERATOMIC POTENTIALS", + "Authors": "Shapeev, AV", + "Source Title": "MULTISCALE MODELING & SIMULATION", + "Abstract": "Density functional theory offers a very accurate way of computing materials properties from first principles. However, it is too expensive for modeling large-scale molecular systems whose properties are, in contrast, computed using interatomic potentials. The present paper considers, from a mathematical point of view, the problem of constructing interatomic potentials that approximate a given quantum-mechanical interaction model. In particular, a new class of systematically improvable potentials is proposed, analyzed, and tested on an existing quantum-mechanical database.", + "Times Cited, WoS Core": 944, + "Times Cited, All Databases": 1033, + "Publication Year": 2016, + "Research Areas": "Mathematics; Physics", + "UT (Unique WOS ID)": "WOS:000388444300008", + "Markdown": "# MOMENT TENSOR POTENTIALS: A CLASS OF SYSTEMATICALLY IMPROVABLE INTER ATOMIC POTENTIALS∗ \n\nALEXANDER V. SHAPEEV† \n\nAbstract. Density functional theory offers a very accurate way of computing materials properties from first principles. However, it is too expensive for modeling large-scale molecular systems whose properties are, in contrast, computed using interatomic potentials. The present paper considers, from a mathematical point of view, the problem of constructing interatomic potentials that approximate a given quantum-mechanical interaction model. In particular, a new class of systematically improvable potentials is proposed, analyzed, and tested on an existing quantum-mechanical database. \n\nKey words. machine learning, interatomic potentials, moment tensor potentials \n\nAMS subject classifications. 70G10, 68Q32 \n\nDOI. 10.1137/15M1054183 \n\n1. Introduction. Molecular modeling is an increasingly popular tool in biology, chemistry, physics, and materials science [15]. The success of molecular modeling largely depends on the accuracy and efficiency of calculating the interatomic forces. The two major approaches to computing interatomic forces are (1) quantum mechanics (QM) calculations [10, 14] and (2) using empirical interatomic potentials. In the first approach, first the electronic structure is computed and then the forces on the atoms (more precisely, on their nuclei) are deduced. QM calculations are therefore rather computationally demanding but can yield a high quantitative accuracy. On the other hand, the accuracy and transferability of empirical interatomic potentials is limited, but they are orders of magnitude less computationally demanding. With interatomic potentials, typically, the forces on atoms derive from the energy of interaction of each atom with its atomic neighborhood (typically consisting of tens to hundreds of atoms). \n\nThis hence makes it very attractive to design a combined approach whose efficiency would be comparable to interatomic potentials, yet the accuracy is similar to the one obtained with ab initio simulations. Moreover, the scaling of computational complexity of using the interatomic potentials is $O(N)$ , where $N$ is the number of atoms, whereas, for instance, standard Kohn–Sham density functional theory calculations scale like $O(N^{3})$ —which implies that the need in such combined approaches is even higher for large numbers of atoms. \n\nOne way of achieving this is designing accurate interatomic potentials. With this goal in mind, we categorize all potentials into two groups, following the regression analysis terminology of [3]. The first group is the parametric potentials with a fixed number of numerical or functional parameters. All empirical potentials known to the author are parametric, which is their disadvantage—their accuracy cannot be systematically improved. As a result, if the class of problems is sufficiently large and the required accuracy is sufficiently high (say, close to that of ab initio calculations), then the standard parametric potentials are not sufficient and one needs to employ nonparametric potentials. In theory, the accuracy of these potentials can be systematically improved. In practice, however, increasing the accuracy is done at a cost of higher computational complexity (which is nevertheless orders of magnitude less than that of the QM calculations), and the accuracy is still imited by that of the available QM model the potential is fitted to. Also, it should be noted that, typically, such fitted potentials do not perform well for the situations that they were not fitted to (i.e., they exhibit little or no transferability). \n\nEach nonparametric potential has two major components: (1) a representation (also referred to as “descriptors”) of atomic environments and (2) a regression model which is a function of the representation. It should be emphasized that finding a good representation of atomic environments is not a trivial task, as the representation is required to satisfy certain restrictions, namely, invariance with respect to Euclidean transformations (translations, rotations, and reflections) and permutation of chemically equivalent atoms, smoothness with respect to distant atoms coming to and leaving the boundary of the atomic environment, as well as completeness (for more details see the discussion in [3, 6, 13]). The latter restriction means that the representation should contain all the information to unambiguously reconstruct the atomic environment. \n\nIn this context, one common approach to constructing nonparametric potentials, called the neural networks potentials (NNP) [7, 8], is using artificial NNs as the regression model and a family of descriptors first proposed by Behler and Parrinello [8]. These descriptors have a form of radial functions applied to and summed over atomic distances to the central atom of the environment, augmented with similar functions with angular dependence summed over all pairs of atoms. Another approach, called Gaussian approximation potentials (GAP) [4, 27], uses Gaussian process regression and a cleverly designed set of descriptors that are evaluated by expanding smoothened density field of atoms into a spherical harmonics basis [3]. \n\nOther recent approaches include [28], which employs the bispectrum components of the atomic density, as proposed in an earlier version of GAP [4], and uses a linear regression model to fit the QM data. Also, [21] uses Gaussian process regression of a force-based model rather than the potential energy-based model. Additionally, in a recent work [19] the authors put forward an approach of regressing the interatomic interaction energy together with the electron density. \n\nIt is worthwhile to mention a related field of research, namely, the development of nonreactive interatomic potentials. Such potentials assume a fixed underlying atomistic structure (fixed interatomic bonds or fixed lattice sites that atoms are bound to). The works developing nonparametric versions of such potentials include [1, 17, 24]. \n\nIn the present paper we propose a new approach to constructing nonparametric potentials based on linear regression and invariant po ynomials. The main feature of this approach is that the proposed form of the potential can provably approximate any regular function satisfying all the needed symmetries (see Theorems 3.1 and 3.2), while being computationally efficient. The building block of the proposed potentials is what we call the moment tensors—similar to inertia tensors of atomic environments. Hence we call this approach the moment tensor potentials (MTP). \n\nThe manuscript is structured as follows. Section 2 gives an overview of interatomic potentials. Section 3 introduces MTP and then formulates and proves the two main theorems. The practical implementation of MTP is discussed in section 4. Section 5 reports the accuracy and computational efficiency (i.e., the CPU time) of MTP and compares MTP with GAP. \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\n2. Interatomic potentials. Consider a system consisting of $N_{\\mathrm{tot}}$ atoms with positions $x\\in(\\mathbb{R}^{d})^{N_{\\mathrm{tot}}}$ (more precisely, with positions of their nuclei to be $x$ ), where $d$ is the number of physical dimensions, taken as $d=3$ in most of applications. These atoms have a certain energy of interaction, $E^{\\mathrm{q}}(x)$ , typ cally given by some QM model that we aim to approximate. For simplicity, we assume that all atoms are chemically equivalent. \n\nWe make the assumption that $E^{\\mathrm{q}}(x)$ can be well approximated by a sum of energies of atomic environments of the individual atoms. We denote the atomic environment of atom $k$ by $D x_{k}$ and let it equal to a tuple \n\n$$\nD x_{k}:=(x_{i}-x_{k})_{1\\leq i\\leq N_{\\mathrm{tot}},0<|x_{i}-x_{k}|\\leq R_{\\mathrm{cut}}},\n$$ \n\nwhere $R_{\\mathrm{cut}}$ is the cut-off radius, in practical calculations typically taken to be between 5 and $\\mathrm{10\\AA}$ . In other words, $D x_{k}$ is the collection of vectors joining atom $k$ with all other atoms located at distance $R_{\\mathrm{cut}}$ or closer. Thus, we are looking for an approximant of the form \n\n$$\nE(\\boldsymbol{x}):=\\sum_{k=1}^{N_{\\mathrm{tot}}}V(D\\boldsymbol{x}_{k}),\n$$ \n\nwhere $V$ is called the interatomic potential. This assumption is true in most systems with short-range interactions (as opposed to, e.g., Coulomb interaction in charged or polarized systems); refer to recent works [11, 12, 23] for rigorous proofs of this statement for simple QM models. \n\nMathematically, since $D x_{k}$ can be a tuple of any size (in practice limited by the maximal density of atoms), $V$ can be understood as a amily of functions each having a different number of arguments. For convenience, however, we will still refer to $V$ as a “function.” \n\nThe function $V=V(u_{1},\\ldots,u_{n})$ is required to satisfy the following restrictions: (R1) Permutation invariance: \n\n$$\nV(u_{1},\\dots,u_{n})=V(u_{\\sigma_{1}},\\dots,u_{\\sigma_{n}})\\qquad{\\mathrm{for~any~}}\\sigma\\in S_{n},\n$$ \n\nwhere $S_{n}$ denotes the set of permutations of $(1,\\ldots,n)$ . \n\n(R2) Rotation and reflection invariance: \n\n$$\nV(u_{1},\\dots,u_{n})=V(Q u_{1},\\dots,Q u_{n})\\qquad\\mathrm{for~any~}Q\\in O(d),\n$$ \n\nwhere $O(d)$ is the orthogonal group in $\\mathbb{R}^{d}$ . For simplicity in what follows we will denote $Q u:=(Q u_{1},\\ldots,Q u_{n})$ . \n\n(R3) Smoothness with respect to the number of atoms (more precisely, with respect to atoms leaving and entering the interaction neighborhood): \n\n$V:\\mathbb{R}^{d\\times n}\\rightarrow\\mathbb{R}$ is a smooth function, \n\n$$\nV(u_{1},\\ldots,u_{n})=V(u_{1},\\ldots,u_{n},u_{n+1})\\qquad{\\mathrm{whenever~}}|u_{n+1}|\\geq R_{\\mathrm{cut}}.\n$$ \n\nIn most of the works performing practical calculations, including [6, 7, 8, 26, 27, 28], the interatomic potentials are chosen such that the energy and forces are continuous. There are, however, exceptions including [4] that require the second derivatives of energy to be continuous, and [20] proposing exponential decay of the potential with no strict cut-off radius. \n\nNote that $E$ is translation symmetric by definition. \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\n2.1. Empirical interatomic potentials. For the purpose of illustration, we will briefly present two popular classes of empirical interatomic potentials. The first class is pair potentials (also known as two-body potentials), \n\n$$\nV^{\\mathrm{pair}}(u)=\\sum_{i}\\varphi(|u_{i}|),\n$$ \n\nwhere by $u$ we denote the collection of the relative coordinates, $\\boldsymbol{u}=(u_{i})_{i=1}^{n}$ . It is clear that this potential satisfies (R1) and (R2), while if we take $\\varphi(r)=0$ for $r\\geq R_{\\mathrm{cut}}$ (as is done in most practical calculations), then it also satisfies (R3). The second potential is the embedded atom model, \n\n$$\nV^{\\mathrm{eam}}(u)=\\sum_{i}\\varphi(|u_{i}|)+F\\Bigl(\\sum_{i}\\rho\\bigl(|u_{i}|\\bigr)\\Bigr),\n$$ \n\nwhere if $\\varphi(r)$ and $\\rho(r)$ are chosen to vanish for $r~\\geq~R_{\\mathrm{cut}}$ , then it also satisfies (R1)–(R3). \n\nBoth potentials can be viewed to have descriptors of the form \n\n$$\nR_{\\nu}(u)=\\sum_{i}f_{\\nu}(|u_{i}|),\n$$ \n\nwhere $f_{\\nu}$ are chosen such that their linear combination can approximate any smooth function (e.g., $f_{\\nu}(r)=r^{\\nu}(R_{\\mathrm{cut}}-r)^{{\\scriptscriptstyle2}}$ for $r\\leq R_{\\mathrm{cut}}$ and $\\begin{array}{r}{f_{\\nu}(r)=0}\\end{array}$ for $r>R_{\\mathrm{cut}}$ , where $\\nu=0,1,\\ldots{}$ ; the term $(R_{\\mathrm{cut}}-r)^{2}$ ensures continuous energy and forces). Then, we can approximate $\\begin{array}{r}{\\varphi(\\boldsymbol{r})\\approx\\sum_{\\nu}c_{\\nu}f_{\\nu}(\\boldsymbol{r})}\\end{array}$ (the sum is taken over some finite set of $\\nu$ ), and hence \n\n$$\nV^{\\mathrm{pair}}(u)\\approx\\sum_{\\nu}c_{\\nu}R_{\\nu}(u).\n$$ \n\nLikewise one can approximate $V^{\\mathrm{eam}}$ with the exception that it will not be, in general, a linear function of $R_{\\nu}(u)$ . \n\nThis set of descriptors is not complete, because it is based only on the distances to the central atom, but is insensitive to bond angles. \n\n2.2. Nonempirical interatomic potentials. Next, we review a number of nonempirical interatomic potentials proposed recently as a more accurate alternative to the empirical ones. \n\nWe start with the NNPs [6, 7, 8]. In addition to the descriptors given by (2.3) they also employ the descriptors of the form \n\n$$\n\\sum_{i=1}^{n}\\sum_{j=1\\atop j\\neq i}^{n}f(|u_{i}|,|u_{j}|,u_{i}\\cdot u_{j}).\n$$ \n\n(Note that NN can be, in principle, used with any set of descriptors. If these descriptors are complete, then such NNP is systematically improvable.) Typically, 50 to 100 descriptors of the form (2.3) and (2.4) are chosen as an input to an NN, while its output yields the function $V$ [7]. In practice, this approach gives convincing results; however, it is an open question whether these descriptors are complete. \n\nThe GAP [4, 27] uses a different idea, consisting of (1) forming a smoothened atomic density function \n\n$$\n\\sum_{i=1}^{n}\\exp\\big({-\\frac{|u_{i}-u|^{2}}{2\\sigma^{2}}}\\big),\n$$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\n(2) approximating it through spherical harmonics, and (3) constructing functionals applied to the spherical harmonics coefficients that satisfy all needed symmetries. One can prove mathematically that this approach can approximate any regular symmetric function (i.e., a function that satisfies (R1)–(R3)). However, expanding functions in a spherical harmonics basis can be computationally expensive. \n\nSeveral other nonempirical potentials have been proposed recently. A method using a representation based on expanding the atom c density function in spherical harmonics together with linear regression was used in [28]. In [21] the authors use Gaussian process regression to train a model that predicts forces on atoms directly (as opposed to a model that fits the energy). \n\n# 3. Moment tensor potentials. \n\n3.1. Representation with invariant polynomials. In the present paper we propose an alternative approach based on invariant po ynomials. The idea is that any given potential $V^{*}(u)$ , if it is smooth enough, can be approximated by a polynomial $p(u)\\approx V^{*}(u)$ —we will analyze the error of such an approximation in section 3.2. The approximant can always be chosen symmetric. Indeed, given $p(u)$ , one can consider the symmetrized polynomial \n\n$$\np^{\\mathrm{sym}}(u_{1},\\ldots,u_{n})=\\frac1{n!}\\sum_{\\sigma\\in{\\cal S}_{n}}p(u_{\\sigma_{1}},\\ldots,u_{\\sigma_{n}}),\n$$ \n\nand then $V^{*}(u)\\approx p^{\\mathrm{sym}}(u)$ . Similarly, one can symmetrize $p^{\\mathrm{sym}}$ with respect to rotations and reflections. Hence, theoretically, one can construct a basis of such polynomials $b_{\\nu}(u)$ and choose \n\n$$\nV^{*}(u)\\approx V(u):=\\sum_{\\nu}c_{\\nu}b_{\\nu}(u).\n$$ \n\nThis approach is implemented for small systems of up to 10 atoms [9]; however, generalizations of this approach require a more efficient way of generating the invariant polynomials. The main difficulty is related to the fact that the number of permutations in a system of $n$ atoms is $n!$ , which grows too fast in order to, for instance, calculate the right-hand side of (3.1). \n\nIn the present paper we propose a basis for the set of all polynomials invariant with respect to permutation, rotation, and reflection. The main feature of the proposed basis is that the computational complexity of computing these polynomials scales like $O(n)$ . Moreover, one can easily construct such bases to also satisfy the (R3) property (refer to section 4), making it a promising candidate for efficient nonparametric interatomic potentials. \n\nThe $M$ polynomials. The building blocks of the basis functions for the approximation (representation) of $V=V(u)$ are the “moment” polynomials $M=M_{\\bullet,\\bullet}(u)$ defined as follows. \n\nFor integer $\\mu,\\nu\\geq0$ we let \n\n$$\nM_{\\mu,\\nu}(u):=\\sum_{i=1}^{n}|u_{i}|^{2\\mu}u_{i}^{\\otimes\\nu},\n$$ \n\nwhere $w^{\\otimes\\nu}:=w\\otimes\\cdot\\cdot\\cdot\\otimes w$ is the Kronecker product o $\\nu$ copies of the vector $w\\in\\mathbb{R}^{d}$ . Thus, $M_{\\mu,\\nu}(u)\\in(\\mathbb{R}^{d})^{\\nu}$ (i.e., an $\\nu$ -dimensional tensor) or each $u$ . Computing $M_{\\mu,\\nu}(u)$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nrequires linear time in $n$ , but exponential in $\\nu$ . This means that if the maximal value of $\\nu$ is bounded, then computing $M_{\\mu,\\nu}$ can be done efficiently. \n\nThere is a mechanical interpretation of $M_{\\mu,\\nu}(u)$ Consider $\\mu=0$ ; then $M_{0,0}$ simply gives the number of atoms at the distance of $R_{\\mathrm{cut}}$ or less (this can also be understood as the “mass” of these atoms), $M_{0,1}$ is the center of mass of such atoms (scaled by the mass), $M_{0,2}$ is the tensor of second moments of inertia, etc. For $\\mu>0$ , $M_{\\mu,\\nu}$ can be interpreted as weighted moments of inertia, with the $i$ th atom’s weight being $|u_{i}|^{2\\mu}$ . \n\nThe basis polynomials $B_{\\alpha}$ . The basis polynomials are indexed by $k\\in\\mathbb N$ , $k\\leq n$ , where our definition for $\\mathbb{N}$ is \n\n$$\n\\mathbb{N}=\\{0,1,\\ldots\\},\n$$ \n\nand a $k\\times k$ symmetric matrix $\\alpha$ of integers $\\alpha_{i,j}\\geq0$ $(i,j\\in\\{1,\\dots,k\\})$ . For such matrices, by $\\alpha_{i}^{\\prime}$ we define the sum of the off-diagonal elements of the $\\textit{\\textbf{\\i}}$ th row, \n\n$$\n\\alpha_{i}^{\\prime}=\\sum_{j=1\\atop j\\neq i}^{k}\\alpha_{i,j}.\n$$ \n\nNext, we define a contraction operator (product) of tensors $T^{(i)}\\in(\\mathbb{R}^{d})^{\\alpha_{i}^{\\prime}}$ by \n\n$$\n\\prod_{i=1}^{\\infty}T^{(i)}:=\\sum_{\\beta}\\prod_{i=1}^{k}T_{\\beta^{(1,i)}...\\beta^{(i-1,i)}\\beta^{(i,i+1)}...\\beta^{(i,k)}}^{(i)},\n$$ \n\nwhere each $\\beta$ is a collection of multi-indices $\\beta=\\left(\\beta^{(i,j)}\\right)_{1\\leq i0$ is the Boltzmann constant, and $T>0$ is the electronic temperature, and we take the chemical potential to be zero. \n\nNext, we let $R>0$ and $\\delta_{0}>0$ , allow $u_{i}$ to vary in $\\mathcal{V}_{\\delta_{0}}$ , where \n\n$$\n\\mathcal{V}_{\\delta}:=\\{\\zeta\\in\\mathbb{C}:\\operatorname{Re}(\\zeta)\\in[-R-\\delta,R+\\delta]^{d},\\operatorname{Im}(\\zeta)\\in[-\\delta,\\delta]^{d}\\},\n$$ \n\nand assume that $\\varphi(v)$ is analytically extended to $\\upnu_{\\delta_{0}}$ . We note that in many models $\\varphi(\\zeta)$ has a singularity at $\\zeta=0$ (for example, $\\varphi(\\zeta)=\\beta_{0}\\exp(-q|\\zeta|)$ for some $\\beta_{0}$ , $q>0$ [14, equation (7.24)]); therefore by assuming analytical extensibility of $\\varphi$ onto $\\upnu_{\\delta_{0}}$ we implicitly assume some approximation of such irregular $\\varphi$ with a function that is regular around $\\zeta=0$ . For example, one could use the Hermite functions basis, $e^{-|\\zeta|^{2}/2}H_{n_{1}}(\\zeta_{1})H_{n_{2}}(\\zeta_{2})\\ldots H_{n_{d}}(\\zeta_{d})$ [25], to approximate $\\varphi(\\zeta)$ away from $\\zeta=0$ . \n\nTheorem 3.2. There exist $C>0$ and $\\rho>1$ , both depending only on $n$ , $\\delta_{0}$ , $M_{\\delta_{0}}$ and $k_{\\mathrm{B}}T$ , such that for any $m\\in\\mathbb{N}$ there exists $p_{m}\\in\\mathbb{P}_{\\mathrm{perm}}\\cap\\mathbb{P}_{\\mathrm{rot}}$ of degree $m$ such that \n\n$$\n\\operatorname*{sup}_{u:\\operatorname*{max}_{i}|u_{i}|\\leq R}|V^{\\mathrm{q}}(u)-p_{m}(u)|1$ , \n\n$$\n\\mathcal{E}_{\\rho}^{(j)}:=[-1,1]^{j-1}\\times\\mathcal{E}_{\\rho}\\times[-1,1]^{n-j-1},\n$$ \n\n$f=f(z_{1},\\ldots,z_{n})$ defined on the union of all $\\mathcal{E}_{\\rho}^{(j)}$ , and \n\n$$\nM_{\\rho}(f):=\\operatorname*{max}_{1\\leq j\\leq n}\\operatorname*{sup}_{z\\in\\mathscr{E}_{\\rho}^{(j)}}|f(z)|.\n$$ \n\nLet $p=p(z_{1},\\ldots,z_{n})$ be the polynomial interpolant of $f$ of degree m on the Chebyshev– Gauss–Lobatto nodes in $[-1,1]^{n}$ . Then \n\n$$\n\\operatorname*{sup}_{\\operatorname*{max}_{i}\\mid z_{i}\\mid\\leq1}\\left\\vert f(z)-p(z)\\right\\vert\\leq2(1+2\\pi^{-1}\\log(n))^{m}M_{\\rho}(f)\\frac{\\rho^{-m}}{\\rho-1}.\n$$ \n\nAn illustration of $\\xi_{\\rho}$ and $\\upnu_{\\delta}$ is given in Figure 3.1 \n\nProof of Theorem 3.2. The plan of the proof is to, after an auxiliary step (Step 1), successively obtain bounds on $\\varphi$ (Step 2), on $H(u)$ (Step 3), and on the interpolating polynomial (Step 4), and then symmetrize this interpolating polynomial (Step 5). \n\nStep 1. First, we define $M_{\\delta}:=\\operatorname*{sup}_{\\zeta\\in\\mathcal{V}_{\\delta}}\\varphi(\\zeta)$ and note that by the Cauchy integral formula one can bound \n\n$$\n|\\varphi^{\\prime}(z)|\\leq\\left|\\oint_{\\partial\\nu_{2\\delta}}{\\frac{\\varphi(\\zeta)\\mathrm{d}\\zeta}{(\\zeta-z)^{2}}}\\right|={\\frac{(2R+8\\delta)M_{2\\delta}}{\\delta^{2}}}=:M_{\\delta}^{\\prime}\\qquad\\forall z:|z|\\leq\\delta.\n$$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\n![](images/601d3d60f1f5348ccc27f3a45cca993f3375d46b87e9f498270262e127e62418.jpg) \nFig. 3.1. Illustration of $\\upnu_{\\delta}$ (black square) and $\\ensuremath{\\varepsilon}_{\\rho}$ (blue ellipse) on the complex plane for $R=1$ , $\\delta=0.4$ , $\\rho=1.4$ . Both regions contain [–1,1] (red line) and for this choice of parameters $\\varepsilon_{\\rho}\\subset\\mathcal{V}_{\\delta}$ . \n\nThis is valid for any $\\delta\\leq\\delta_{0}/2$ . \n\nStep 2. Next we let $\\delta\\in(0,\\delta_{0}/2]$ , which will be fixed later, and note that if $z\\in\\mathcal{V}_{\\delta}$ , then $|\\mathrm{Im}(\\varphi(z))|\\leq\\mathrm{Im}(\\varphi(\\mathrm{Re}(z)))+M_{\\delta_{0}}^{\\prime}\\mathrm{Im}(z)\\leq M_{\\delta_{0}}^{\\prime}\\delta$ thanks to the intermediate value theorem. \n\nStep 3. Next, following Proposition 3.3, define \n\n$$\n\\mathcal{U}_{\\delta}:=\\cup_{i=1}^{n}\\mathcal{V}_{0}^{i-1}\\times\\mathcal{V}_{\\delta}\\times\\mathcal{V}_{0}^{n-i-1}.\n$$ \n\nHence note that for $u\\in\\mathcal{U}_{\\delta}$ , $H(u)$ is symmetric (possib y non-Hermitian) with at most $2n$ elements being nonreal, which makes it easy to estimate using the Frobenius norm: \n\n$$\n\\Vert\\mathrm{Im}(H(u))\\Vert\\leq\\sqrt{2n}M_{\\delta}^{\\prime}\\delta.\n$$ \n\nBy a spectrum perturbation argument (namely, the Bauer–Fike theorem [5]) we have the corresponding bound on the spectrum: \n\n$$\n|\\mathrm{Im}(\\mathrm{Sp}(H(u)))|\\leq\\sqrt{2n}M_{\\delta}^{\\prime}\\delta.\n$$ \n\nThe real part of the spectrum can be estimated directly through the norm: \n\n$$\n|\\mathrm{Re}(\\mathrm{Sp}(H(u)))|\\leq\\|H(u)\\|\\leq n M_{\\delta_{0}}.\n$$ \n\nStep 4. We next bound $V^{\\mathrm{q}}(u)$ for $u\\in\\mathcal{U}_{\\delta}$ . If needed we decrease $\\delta$ such that $\\begin{array}{r}{\\sqrt{2n}M_{\\delta}^{\\prime}\\delta<\\frac{\\pi}{3}k_{\\mathrm{B}}T}\\end{array}$ and use the following representation [11, 18]: \n\n$$\nV^{\\mathrm{q}}(u)=-\\frac{1}{2\\pi\\mathrm{i}}\\oint_{\\gamma}f^{\\mathrm{q}}(z)\\big((H(u)-z I)^{-1}\\big)_{0,0}\\mathrm{d}z,\n$$ \n\nwhere we take $\\gamma:=\\partial\\Omega$ , where $\\begin{array}{r}{\\Omega=\\{z\\in\\mathbb{C}:|\\mathrm{Re}(z)|\\leq n M_{\\delta_{0}}+\\frac{\\pi}{3}k_{\\mathrm{B}}T.}\\end{array}$ , $|\\mathrm{Im}(z)|\\leq$ $\\textstyle{\\frac{2\\pi}{3}}k_{\\mathrm{B}}T\\}$ . The choice of the region $\\Omega$ is such that any point $z\\in\\gamma$ is separated from any eigenvalue $\\lambda$ of $H(u)$ by the distance $\\begin{array}{r}{|z-\\lambda|\\ge\\frac{\\pi}{3}k_{\\mathrm{B}}T}\\end{array}$ , and at the same time $f^{\\mathrm{q}}(z)$ is regular on $\\Omega$ . This allows us to estimate, for $z\\in\\gamma$ , \n\n$$\n\\begin{array}{r}{\\|(H(u)-z I)^{-1}\\|\\leq\\left(\\frac{\\pi}{3}k_{\\mathrm{B}}T\\right)^{-1}}\\end{array}\n$$ \n\nand hence \n\n$$\n\\operatorname*{sup}_{u\\in\\mathcal{U}_{\\delta}}\\vert V^{\\mathrm{q}}(u)\\vert\\le\\operatorname*{sup}_{z\\in\\Omega}\\vert f^{\\mathrm{q}}(z)\\vert\\vert\\gamma\\vert\\left(\\frac{\\pi}{3}k_{\\mathrm{B}}T\\right)^{-1}\\le C,\n$$ \n\nwhere $C$ is a generic constant that depends only on $n$ , $\\delta_{0}$ , $M_{\\delta_{0}}$ , and $k_{\\mathrm{B}}T$ . It now remains to notice that there exists $\\rho>1$ that depends on $\\delta$ such that \n\n$$\n\\{z\\in\\mathbb{C}:|z/R-1|+|z/R+1|\\le\\rho+\\rho^{-1}\\}\\subset\\mathcal{V}_{\\delta}.\n$$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nHence Proposition 3.3 applies to the function $f(z)=V^{\\mathrm{q}}(R z)$ and yields the interpolating polynomial $\\tilde{p}_{m}(u)$ such that \n\n$$\n\\operatorname*{sup}_{\\substack{u\\colon\\operatorname*{max}_{i}|u_{i}|\\le R}}|V^{\\mathrm{q}}(u)-\\tilde{p}_{m}(u)|\\le\\operatorname*{sup}_{\\substack{u\\colon\\operatorname*{max}_{i}|u_{i}|_{\\infty}\\le R}}|V^{\\mathrm{q}}(u)-\\tilde{p}_{m}(u)|\\le C\\rho^{-m}.\n$$ \n\nBy construction $\\tilde{p}_{m}\\in\\ensuremath{\\mathbb{P}}_{\\mathrm{perm}}$ . Indeed, the function $f(z)~=~V^{\\mathrm{q}}(R z)$ is symmetric with respect to permutation of variables, and so is the Chebyshev–Gauss–Lobatto interpolation nodes on the domain $[-1,1]^{n}$ . Hence, uniqueness of interpolation yields permutation symmetry of $\\ddot{p}_{m}$ . \n\nStep 5. We define \n\n$$\np_{m}(u):=\\frac{\\int_{Q\\in O(d)}\\tilde{p}_{m}(Q u)\\mathrm{d}Q}{\\int_{Q\\in O(d)}\\mathrm{d}Q}\\in\\mathbb{P}_{\\mathrm{perm}}\\cap\\mathbb{P}_{\\mathrm{rot}}\n$$ \n\n(where $\\mathrm{d}Q$ denotes the Haar measure) and thanks to the rotation invariance of $V^{\\mathrm{q}}$ we recover (3.5). \n\nIt is worth noting that the integration with respect to rotation was used only as a technical tool in the proof. If we directly constructed an approximation $V(u)=$ $\\textstyle\\sum_{\\alpha}c_{\\alpha}B_{\\alpha}(u)$ to $V^{\\mathrm{q}}(u)$ , rather than using the Chebyshev–Gauss–Lobatto interpolation as an intermediate step, then $V(u)$ would be rotationally invariant by construction. \n\n3.3. Proof of Theorem 3.1. We start with stating the first fundamental theorem for the orthogonal group ${\\mathrm{O}}(d)$ [30]. \n\nTheorem 3.4. $p\\in\\mathbb{P}$ is rotation invariant if and only if it can be represented as a polynomial of $n(n+1)/2$ scalar variables of the form $r_{i j}(u):=u_{i}\\cdot u_{j}$ , where $1\\leq i\\leq j\\leq n$ . \n\nWe hence can identify a polynomial $p=p(u)\\in\\mathbb{P}_{\\mathrm{rot}}$ with the respective polynomial $q=q(r)\\in\\mathbb{Q}$ , where $\\mathbb{Q}$ is the set of polynomials of $n(n+1)$ scalar variables $r=(r_{i j})_{1\\leq i,j\\leq n}$ (we lift the requirement $i\\leq j$ for ease of notation in what follows). \n\nIn order to proceed, we introduce the notation of composition of tuples: (3.6) \n\n$$\na_{b}:=(a_{b_{1}},\\dotsc,a_{b_{m}})\\qquad{\\mathrm{for}}\\enspace b=(b_{1},\\dotsc,b_{m})\\subset\\{1,\\dotsc,n\\}^{m}{\\mathrm{and}}\\ a=(a_{1},\\dotsc,a_{n}).\n$$ \n\nHence define \n\n$$\n\\mathbb{Q}_{\\mathrm{perm}}:=\\left\\{q\\in\\mathbb{Q}:q(r)\\equiv q(r_{\\sigma\\sigma})\\ \\forall\\sigma\\in S_{n}\\right\\}\n$$ \n\nthat corresponds to $\\mathbb{P}_{\\mathrm{perm}}$ , where we likewise let $r_{\\sigma\\sigma}:=(r_{\\sigma_{i}\\sigma_{j}})_{1\\le i,j\\le n}$ . \n\nWe next formulate a rather intuitive result, essentially stating that $\\mathbb{Q}_{\\mathrm{perm}}$ can be spanned by symmetrizing all monomials of $r$ . \n\nLemma 3.5. \n\n$$\n\\mathbb{Q}_{\\mathrm{perm}}=\\mathrm{Span}\\Bigg\\{\\sum_{\\sigma\\in S_{n}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\sigma_{i}\\sigma_{j}})^{\\alpha_{i j}}:m\\in\\mathbb{N},\\ m\\leq n,\\ \\alpha\\in\\mathbb{N}^{m\\times m}\\Bigg\\}.\n$$ \n\nProof. If $q\\in\\mathbb{Q}_{\\mathrm{perm}}$ , then \n\n$$\n{\\frac{1}{n!}}\\sum_{\\sigma\\in S_{n}}q(r_{\\sigma\\sigma})={\\frac{1}{n!}}\\sum_{\\sigma\\in S_{n}}q(r)=q(r).\n$$ \n\nIt remains to apply this identity to all monomials $\\begin{array}{r}{q(r)=\\prod_{i=1}^{m}\\prod_{j=i}^{m}r_{i j}^{\\alpha_{i j}}}\\end{array}$ to obtain the stated result. \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nThe next step toward proving the main result is the following lemma, where we denote $\\mathcal{N}:=\\{1,\\ldots,n\\}$ . \n\nLemma 3.6. For $m\\in\\mathbb{N}$ , $m\\leq n$ , and $\\alpha\\in\\mathbb{N}^{m\\times m}$ , \n\n$$\nB_{\\alpha}(u)=\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(u_{\\gamma_{i}}\\cdot u_{\\gamma_{j}})^{\\alpha_{i j}}.\n$$ \n\nProof. Before commencing with the proof, we note that we will use the distributive law of addition and multiplication in the following form: \n\n$$\n\\prod_{j=1}^{m}\\sum_{i\\in\\mathcal{I}}f(i,j)=\\sum_{\\gamma\\in\\mathcal{T}^{m}}\\prod_{j=1}^{m}f(\\gamma_{j},j).\n$$ \n\nThen \n\n$$\n\\begin{array}{r}{T_{\\beta^{(1,i)}\\dots\\beta^{(i-1,i)}\\beta^{(i,i+1)}\\dots\\beta^{(i,m)}}^{(i)}(u)=\\displaystyle\\sum_{\\gamma\\in\\mathcal{N}}\\vert u_{\\gamma}\\vert^{2\\alpha_{i i}}\\left(\\displaystyle\\prod_{j=1}^{i-1}\\big(u_{\\gamma}^{\\otimes\\alpha_{j i}}\\big)_{\\beta^{(j,i)}}\\right)\\left(\\displaystyle\\prod_{j=i+1}^{m}\\big(u_{\\gamma}^{\\otimes\\alpha_{i j}}\\big)_{\\beta^{(i,j)}}\\right)}\\\\ {=\\displaystyle\\sum_{\\gamma\\in\\mathcal{N}}\\vert u_{\\gamma}\\vert^{2\\alpha_{i i}}\\left(\\displaystyle\\prod_{j=1}^{i-1}\\displaystyle\\prod_{\\ell=1}^{\\alpha_{j i}}u_{\\gamma,\\beta_{\\ell}^{(j,i)}}\\right)\\left(\\displaystyle\\prod_{j=i+1}^{m}\\displaystyle\\prod_{\\ell=1}^{\\alpha_{i j}}u_{\\gamma,\\beta_{\\ell}^{(i,j)}}\\right).}\\end{array}\n$$ \n\nWe recall the notation $\\alpha_{i}^{\\prime}$ and $\\boldsymbol{B}$ , introduced in (3.2) and (3.3), respectively, and hence express \n\n$$\n\\begin{array}{r l}{\\frac{\\sqrt{1}}{2\\pi}\\mathbb{E}_{\\alpha\\times\\alpha}\\left(\\left[\\hat{\\mathbf{J}}_{\\alpha}^{\\dagger}\\right]+\\sum_{k\\in\\mathcal{N}_{\\alpha}}^{\\dagger}\\left[\\hat{\\mathbf{J}}_{\\alpha}^{\\dagger}\\right]\\right)}&{=\\alpha\\ln\\left(\\alpha+\\beta\\right),}\\\\ &{\\quad-\\frac{\\sqrt{1}}{2\\pi}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\left(\\frac{\\sqrt{1}}{2}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\right)\\Bigg(\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\right)\\Bigg(\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\Bigg)}\\\\ &{\\quad-\\sum_{k\\in\\mathcal{N}_{\\alpha}}^{\\dagger}\\frac{\\sqrt{1}}{2\\pi}\\prod_{i=1}^{N}\\exp^{\\alpha}\\left(\\frac{\\sqrt{1}}{2}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\right)\\Bigg(\\prod_{i=1}^{N}\\frac{\\sqrt{1}}{2}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\Bigg)}\\\\ &{\\quad-\\sum_{k\\in\\mathcal{N}_{\\alpha}}^{\\dagger}\\frac{\\sqrt{1}}{2\\pi}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\left(\\frac{\\sqrt{1}}{2}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\right)\\Bigg)}\\\\ &{=\\frac{\\sqrt{1}}{2\\pi}\\frac{\\sqrt{1}}{2\\pi}\\sum_{k\\in\\mathcal{N}_{\\alpha}}^{\\dagger}\\frac{\\sqrt{1}}{2}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\Bigg[\\prod_{i=1}^{N}\\exp^{\\alpha}\\alpha\\Bigg]\\ln\\left(\\exp^{-\\alpha}\\alpha\\right)}\\\\ &{\\quad-\\sum_{k\\in\\mathcal{N}_{\\alpha}}^{\\dagger}\\frac{\\sqrt{1}}{2}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\Bigg[\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\Bigg]}\\\\ &{=\\sum_{k\\in\\mathcal{N}_{\\alpha}}^{\\dagger}\\frac{\\sqrt{1}}{2}\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\Bigg[\\prod_{i=1}^{N}\\exp^{-\\alpha}\\alpha\\Bigg]\\ln\\left(\\exp^{-\\alpha}\\alpha\\right)\\Bigg(\\prod_{i=1}^{N}\\exp^{-\\alpha}\\\n$$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nProof of Theorem 3.1. In view of the previous lemma, we can denote \n\n$$\n\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}=\\mathrm{Span}\\Bigg\\{\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\gamma_{i}\\gamma_{j}})^{\\alpha_{i j}}:m\\in\\mathbb{N},\\ m\\leq n,\\ \\alpha\\in\\mathbb{N}^{m\\times m}\\Bigg\\}\n$$ \n\nand, applying the earlier lemmas, formulate the statement of Theorem 3.1 as $\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}=$ $\\mathbb{Q}_{\\mathrm{perm}}$ . The latter is an immediate corollary of the following more specialized result. \n\nLemma 3.7. For $m\\in\\mathbb{N}$ , $m\\leq n$ , denote \n\n$$\n\\begin{array}{l l}{\\displaystyle\\mathbb{Q}_{\\mathrm{perm}}^{(m)}:=\\mathrm{Span}\\Bigg\\{\\sum_{\\sigma\\in S_{n}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\sigma_{i}\\sigma_{j}})^{\\alpha_{i j}}:\\alpha\\in\\mathbb{N}^{m\\times m}\\Bigg\\}}&{\\ a n d}\\\\ {\\displaystyle\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(m)}:=\\mathrm{Span}\\Bigg\\{\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\gamma_{i}\\gamma_{j}})^{\\alpha_{i j}}:\\alpha\\in\\mathbb{N}^{m\\times m}\\Bigg\\}.}&\\end{array}\n$$ \n\nThen Q˜ (m) $\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(m)}=\\mathbb{Q}_{\\mathrm{perm}}^{(m)}$ \n\nBefore we prove this lemma, we give two auxiliary results. \n\nLemma 3.8. We equip ${\\mathcal{N}}^{m}$ with the lexicographical order and hence denote by $\\Gamma:=\\{\\gamma\\in\\mathcal{N}^{m}:\\gamma=\\operatorname*{min}\\{\\sigma_{\\gamma}:\\sigma\\in\\mathcal{S}_{n}\\}\\}$ the set o representatives of equivalence classes $\\{\\sigma_{\\gamma}:\\sigma\\in S_{n}\\}$ , where $\\sigma_{\\gamma}$ is understood as composition of tuples (3.6). Also let $C_{\\gamma}=\\#\\{\\sigma_{\\gamma}:\\sigma\\in S_{n}\\}$ , where $\\#$ denotes the number of elements in a set. Then \n\n$$\n\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\gamma_{i}\\gamma_{j}})^{\\alpha_{i j}}=\\sum_{\\gamma\\in\\Gamma}\\frac{C_{\\gamma}}{n!}\\sum_{\\sigma\\in S_{n}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\sigma_{\\gamma_{i}}\\sigma_{\\gamma_{j}}})^{\\alpha_{i j}}.\n$$ \n\nProof. Any $\\sigma\\in S_{n}$ induces a one-to-one mapping $\\gamma\\mapsto\\sigma_{\\gamma}$ on ${\\mathcal{N}}^{m}$ . Hence \n\n$$\n\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\gamma_{i}\\gamma_{j}})^{\\alpha_{i j}}=\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\sigma_{\\gamma_{i}}\\sigma_{\\gamma_{j}}})^{\\alpha_{i j}}\\qquad\\forall\\sigma\\in\\mathcal{S}_{n},\n$$ \n\ntherefore \n\n$$\n\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\gamma_{i}\\gamma_{j}})^{\\alpha_{i j}}=\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\frac{1}{n!}\\sum_{\\sigma\\in\\mathcal{S}_{n}}\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\sigma_{\\gamma_{i}}\\sigma_{\\gamma_{j}}})^{\\alpha_{i j}}.\n$$ \n\nIt remains to group up the terms for which $\\sigma_{\\gamma}$ is the same. \n\nThe next auxiliary result is proved by a trivial combinatorial argument, essentially expressing that all elements of $\\Gamma$ other than $(1,\\ldots,m)\\in\\Gamma$ have repeated values. \n\nProposition 3.9. Let $m\\geq1$ . Then $\\Gamma=\\{(1,\\ldots,m)\\}\\cup\\Gamma^{\\prime}$ , where $\\Gamma^{\\prime}:=\\{\\gamma\\in\\Gamma$ : $\\operatorname*{max}_{i}\\gamma_{i}\\leq m-1\\}$ . \n\nProof of Lemma 3.7. We argue by induction over $m$ . For $m=0$ the statement is obvious since Q(p0e)rm $\\mathbb{Q}_{\\mathrm{perm}}^{(0)}=\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(0)}=\\operatorname{Span}\\{1\\}$ ; therefore we only need to prove the induction step. \n\nNow, for $m\\in\\mathbb{N}$ , $m\\leq n$ , we choose an arbitrary $\\alpha$ and let \n\n$$\n\\begin{array}{r}{q(r):=\\displaystyle\\sum_{\\sigma\\in S_{n}}\\prod_{j,k=1}^{m}(r_{\\sigma_{j}\\sigma_{k}})^{\\alpha_{j k}}\\in\\mathbb{Q}_{\\mathrm{perm}}\\qquad\\mathrm{and}}\\\\ {\\tilde{q}(r):=\\frac{n!}{C_{\\{1,\\dots,m\\}}}\\displaystyle\\sum_{\\gamma\\in\\mathcal{N}^{m}}\\prod_{j,k=1}^{m}(r_{\\gamma_{j}\\gamma_{k}})^{\\alpha_{j k}}\\in\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}.}\\end{array}\n$$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nThese $q(r)$ and $\\tilde{q}(r)$ span $\\mathbb{Q}_{\\mathrm{perm}}^{(m)}$ and $\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(m)}$ , respective y. We aim to show that $q(r)-$ $\\Tilde{q}(r)\\in\\mathbb{Q}_{\\mathrm{perm}}^{(m-1)}=\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(m-1)}$ .rove the result considering that, by definition, $\\mathbb{Q}_{\\mathrm{perm}}^{(m-1)}\\subseteq\\mathbb{Q}_{\\mathrm{perm}}^{(m)}$ $\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(m-1)}\\subseteq\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(m)}$ \n\nIndeed, in view of the two previous results, recall the definition $\\Gamma^{\\prime}:=\\{\\gamma\\in\\Gamma$ : $\\operatorname*{max}_{i}\\gamma_{i}\\leq m-1\\}$ and write \n\n$$\n\\begin{array}{l}{\\displaystyle\\tilde{q}(\\boldsymbol{r})-q(\\boldsymbol{r})=\\frac{n!}{C_{\\{1,\\dots,m\\}}}\\sum_{\\gamma\\in\\Gamma}\\frac{C_{\\gamma}}{n!}\\sum_{\\sigma\\in S_{n}}\\displaystyle\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\sigma\\gamma_{i}}\\sigma_{\\gamma_{j}})^{\\alpha_{i j}}-\\sum_{\\sigma\\in S_{n}}\\displaystyle\\prod_{i=1}^{m}\\prod_{j=i}^{m}(r_{\\sigma_{i}\\sigma_{j}})^{\\alpha_{i j}}}\\\\ {=\\sum_{\\gamma\\in\\Gamma^{\\prime}}\\frac{C_{\\gamma}}{C_{\\{1,\\dots,m\\}}}\\sum_{\\sigma\\in S_{n}}\\displaystyle\\prod_{i=i}^{m}\\prod_{j=i}^{m}(r_{\\sigma\\gamma_{i}}\\sigma_{\\gamma_{j}})^{\\alpha_{i j}}.}\\end{array}\n$$ \n\nNext, we denote \n\n$$\n\\alpha_{k\\ell}^{(\\gamma)}:=\\sum_{{\\bf\\Phi}_{1\\leq i\\leq j\\leq m\\atop\\gamma_{i}=k,~\\gamma_{j}=\\ell}}\\alpha_{i j}\n$$ \n\nand hence express \n\n$$\n\\tilde{q}(r)-q(r)=\\sum_{\\gamma\\in\\Gamma^{\\prime}}\\frac{C_{\\gamma}}{C_{\\{1,\\dots,m\\}}}\\sum_{\\sigma\\in S_{n}}\\prod_{k=1}^{m-1}\\prod_{\\ell=i}^{m-1}(r_{\\sigma_{k}\\sigma_{\\ell}})^{\\alpha_{k\\ell}^{(\\gamma)}}.\n$$ \n\nNote that the upper limit of both products is $m-1$ thanks to the definition of $\\Gamma^{\\prime}$ (and, of course, Proposition 3.9). Also, note that we used the fact that, from the definition of $\\alpha^{(\\gamma)}$ , $\\alpha_{k\\ell}^{(\\gamma)}=0$ whenever $k>\\ell$ . Since $\\begin{array}{r}{\\sum_{\\sigma\\in S_{n}}\\prod_{k=1}^{m-1}\\prod_{\\ell=i}^{m-1}(r_{\\sigma_{k}\\sigma_{\\ell}})^{\\alpha_{k\\ell}^{(\\gamma)}}}\\end{array}$ by definition belongs to $\\mathbb{Q}_{\\mathrm{perm}}^{(m-1)}$ for each $\\gamma$ , we finally derive that \n\n$$\n\\begin{array}{r}{\\tilde{q}(r)-q(r)\\in\\mathbb{Q}_{\\mathrm{perm}}^{(m-1)}=\\tilde{\\mathbb{Q}}_{\\mathrm{perm}}^{(m-1)}.}\\end{array}\n$$ \n\nThis concludes the proof of the induction step. \n\n4. Practical implementation. The representat on of the interatomic potential through polynomials, outlined in section 3.1, does not satisfy the (R3) property needed for the practical implementation. Hence, as the next step we modify the interatomic potential to satisfy this property. After this, in section 4.1 we discuss the steps needed to compute $B_{\\alpha}(\\boldsymbol{u})$ , and in section 4.2 we describe the algorithms we used for fitting the potentials. \n\nFirst, notice that for a fixed $\\nu$ , a linear combinat on of moment tensors $M_{\\mu,\\nu}(u)$ is a polynomial of $|u_{i}|^{2}$ multiplied by $u_{i}^{\\otimes\\nu}$ . The space of polynomials of $|u_{i}|^{2}$ can be substituted with any other space of functions (which, for generality, can be made dependent on $\\nu$ ), provided that they can represent any regular function of $|u|$ , i.e., \n\n$$\n\\tilde{M}_{\\mu,\\nu}(u):=\\sum_{i=1}^{n}f_{\\mu,\\nu}(|u_{i}|)u_{i}^{\\otimes\\nu},\n$$ \n\nwhere, e.g., $f_{\\mu,\\nu}(r)=r^{-\\mu-\\nu}f_{\\mathrm{cut}}(r)$ or $f_{\\mu}(r)=e^{-k_{\\mu}r}f_{\\mathrm{cut}}(r)$ , $k_{\\mu}>0$ is some sequence of real numbers, and $\\ensuremath{f_{\\mathrm{cut}}}(r)$ is some cut-off function such that $\\begin{array}{r l}{f_{\\mathrm{cut}}(r)=0}\\end{array}$ for $r\\geq R_{\\mathrm{cut}}$ . Here $f_{\\mu,\\nu}(r)$ plays essentially the same role as the “radial symmetry functions” in the NNP [7] or the radial basis functions in [3]. We then let \n\n$$\n\\tilde{B}_{\\alpha}(u):=\\prod_{i=1}^{k}\\tilde{M}_{\\alpha_{i i},\\alpha_{i}^{\\prime}}(u)\n$$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\n(cf. (3.4)) and define the interatomic potential by \n\n$$\nV(u)=\\sum_{\\alpha\\in A}c_{\\alpha}\\tilde{B}_{\\alpha}(u),\n$$ \n\nwhere $A$ is a set of matrix-valued indices fixed a priori and $c_{\\alpha}$ is the set of coefficients found in the training stage. For the rest of the paper we will omit tildes in $\\tilde{M}_{\\bullet,\\bullet}$ and ${\\tilde{B}}_{\\bullet}$ . \n\n4.1. Computing the energy and forces. Next, we discuss the steps needed to compute the interatomic potential and its derivatives for a given neighborhood $u$ . The computation consists of two parts, the precomputation (offline) step and the evaluation (online) step. The precomputation step accepts the set $A$ of values of $\\alpha$ as an input and generates the data for the next step, which is the efficient calculation of $B_{\\alpha}(\\boldsymbol{u})$ for a given neighborhood $u$ . \n\nBefore we proceed, we make two observations. \n\n1. The elements of the tensors $M_{\\mu,\\nu}$ are the “moments” of the form \n\n$$\nm_{\\mu,\\beta}(\\boldsymbol{u}):=\\sum_{i=1}^{n}f_{\\mu,\\nu}(|\\boldsymbol{u}_{i}|)\\prod_{j=1}^{d}u_{i,j}^{\\beta_{j}},\n$$ \n\nwhere $\\beta$ is a multi-index such that $|\\beta|=\\nu$ . The higher the dimension is, the more repeated moments each $M_{\\mu,\\nu}$ contains (e.g., each matrix $M_{\\mu,2}$ has nine elements, out of which at most six may be different due to the symmetricity of $M_{\\mu,2}$ ). \n\n2. The scalar functions $B_{\\alpha}$ consist of products of $M_{\\mu,\\nu}$ (which means that the elements of $B_{\\alpha}$ are linear combinations of products of ${m}_{\\mu,\\beta}$ ). Differentiating products of two terms is easier than differentiating products of three or more terms. Hence it will be helpful to have a representation of $B_{\\alpha}$ as a product of two tensors. \n\nTo that end, we extend the definition of the product $\\mathrm{\\Delta}^{\\alpha}\\Pi$ by allowing the result to be a tensor of nonzero dimension: \n\n$$\n\\left(\\prod_{i=1}^{k}T^{(i)}\\right)_{\\beta^{(1,1)}\\ldots\\beta^{(k,k)}}:=\\sum_{\\beta\\in B}\\prod_{i=1}^{k}T_{\\beta^{(i,1)}\\ldots\\beta^{(i,k)}}^{(i)},\n$$ \n\nwhere each $T^{(i)}$ is a tensor of dimension $\\textstyle\\sum_{j=1}^{k}\\alpha_{i j}$ (here we let $\\alpha_{i j}=\\alpha_{j i}$ ), $\\boldsymbol{B}$ is defined in (3.3), and we make a convention that $\\beta^{(i,j)}:=\\beta^{(j,i)}$ for $i>j$ . Hence we define \n\n$$\n\\hat{B}_{\\bar{\\alpha},\\alpha}(u):=\\prod_{i=1}^{\\alpha}M_{\\bar{\\alpha}_{i},\\sum_{j=1}^{k}\\alpha_{i j}}(u),\n$$ \n\nparametrized by $k\\in\\mathbb N$ , $\\bar{\\alpha}\\in\\ensuremath{\\mathbb{N}}^{k}$ , and a symmetric matrix $\\alpha\\in\\mathbb{N}^{k\\times k}$ . $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ is a tensor of dimension $\\textstyle\\sum_{i=1}^{k}\\alpha_{i i}$ . Clearly if $\\bar{\\alpha}_{i}=\\alpha_{i i}$ for all $i$ , then $\\hat{B}_{\\bar{\\alpha},\\alpha}=B_{\\alpha}$ , which makes the collection of tensors $\\hat{B}_{\\bar{\\alpha},\\alpha}$ a generalization of $B_{\\alpha}$ . Next, consider $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ for some $\\bar{\\alpha}\\in\\mathbb{N}^{k}$ and $\\alpha\\in\\mathbb{N}^{k\\times k}$ , fix $1\\leq I\\leq k$ , and denote $\\beta=(\\bar{\\alpha}_{1},\\dots,\\bar{\\alpha}_{I})$ , $\\Bar{\\gamma}=\\left(\\Bar{\\alpha}_{I+1},\\ldots,\\Bar{\\alpha}_{k}\\right)$ , \n\n$$\n\\beta:=\\left(\\begin{array}{c c c c c}{\\alpha_{11}+\\sum_{i=I+1}^{k}\\alpha_{i1}}&{\\alpha_{12}}&{\\cdots}&{\\alpha_{1I}}\\\\ {\\alpha_{12}}&{\\alpha_{22}+\\sum_{i=I+1}^{k}\\alpha_{i2}}&{\\cdots}&{\\alpha_{2I}}\\\\ {\\vdots}&{\\vdots}&{\\ddots}&{\\vdots}\\\\ {\\alpha_{1I}}&{\\alpha_{2I}}&{\\cdots}&{\\alpha_{I I}+\\sum_{i=I+1}^{k}\\alpha_{i I}}\\end{array}\\right),\n$$ \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nand \n\n$$\n\\gamma:=\\left(\\begin{array}{c c c c c}{\\alpha_{I+1,I+1}+\\sum_{i=1}^{I}\\alpha_{i,I+1}}&{\\alpha_{I+1,I+2}}&{\\hdots}&{\\alpha_{I+1,k}}\\\\ {\\alpha_{I+1,I+2}}&{\\alpha_{I+2,I+2}+\\sum_{i=1}^{I}\\alpha_{i,I+2}}&{\\hdots}&{\\alpha_{I+2,k}}\\\\ {\\vdots}&{\\hdots}&{\\vdots}&{\\ddots}&{\\vdots}\\\\ {\\alpha_{I+1,k}}&{\\alpha_{I+2,k}}&{\\hdots}&{\\alpha_{k k}+\\sum_{i=1}^{I}\\alpha_{i,k}}\\end{array}\\right).\n$$ \n\nOne can then express the elements of $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ through products of elements of $\\hat{B}_{\\bar{\\beta},\\beta}(u)$ and $\\hat{B}_{\\bar{\\gamma},\\gamma}(u)$ . Note that by reordering the rows and columns of $\\alpha$ and $\\beta$ , one can generate many different ways of representing $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ . When doing computations, one should exercise this freedom in such a way that the resulting tensors are of minimal dimension so that the total computation cost is reduced. \n\nFinally, note that even if $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ was scalar-valued, $\\hat{B}_{\\bar{\\beta},\\beta}(u)$ and $\\hat{B}_{\\bar{\\gamma},\\gamma}(u)$ do not have to be scalar-valued—this motivates the need to introduce the tensor-valued basis functions $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ . \n\nPrecomputation. The precomputation step is hence as follows (we keep the argument $u$ of, e.g., in $B_{\\alpha}(\\boldsymbol{u})$ to match the above notation; however, the particular values of $u$ never enter the precomputation step): \n\nStarting with the set of tensors $B_{\\alpha}(\\boldsymbol{u})$ (indexed by $\\alpha\\in A$ ), establish their correspondence to $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ and recursively represent each $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ through some $\\hat{B}_{\\bar{\\beta},\\beta}(u)$ and $\\hat{B}_{\\bar{\\gamma},\\gamma}(u)$ as described above. In each case, out of all such products choose the one with the minimal sum of the number of dimensions of these two tensors. \n• Enumerate all the elements of all the tensors $\\hat{B}_{\\bar{\\alpha},\\alpha}(u)$ as $b_{i}(u)$ ( $i$ is the ordinal number of the corresponding element). \n• Represent each $b_{i}(u)$ as either $b_{i}(u){=}m_{\\mu_{i},\\beta_{i}}(u)$ or $\\begin{array}{r}{b_{i}(u)=\\sum_{j=1}^{J_{i}}c_{j}b_{\\ell_{j}}(u)b_{k_{j}}(u)}\\end{array}$ . \n• Output the resulting (1) correspondence of $B_{\\alpha}(\\boldsymbol{u})$ to $b_{i}(u)$ , (2) $\\mu_{i}$ and $\\beta_{i}$ , and (3) tuples of $(i,c,\\ell,k)$ corresponding to $\\begin{array}{r}{b_{i}(u)=\\sum_{j=1}^{J_{i}}c_{j}b_{\\ell_{j}}(u)b_{k_{j}}(u)}\\end{array}$ . \n\nEvaluation. The evaluation step, as written out below, accepts $u$ as an input and evaluates $B_{\\alpha}(\\boldsymbol{u})$ using the precomputed data (described above). \n\n1. For a given $u$ , calculate all $m_{\\mu_{i},\\beta_{i}}(u)$ . \n2. Then calculate all other $b_{i}(u)$ using the tuples of $(i,c,\\ell,k)$ . \n3. Finally, pick those $b_{i}(u)$ that correspond to scalar $B_{\\alpha}(\\boldsymbol{u})$ (as opposed to nonscalar $\\hat{B}_{\\bar{\\alpha},\\alpha}$ ). \n\nIt remains to form the linear combination of $B_{\\alpha}(\\boldsymbol{u})$ with the coefficients obtained from a linear regression (training), and then sum up all these linear combinations for all atomic environments to obtain the interatomic interaction energy of a given atomistic system. The forces are computed by reverse-mode differentiation of the energy with respect to the atomic positions [22]. \n\n4.2. Training. Once the set $A$ of values of $\\alpha$ s fixed, we need to determine the coefficients $c_{\\alpha}$ . This is done with the regularized (to avoid overfitting [2]) linear regression in the following way. \n\nLet a database of atomic configurations $X=\\{x^{(k)}:k=1,\\ldots,K\\}$ , where $x^{(k)}$ is of size $N^{(k)}$ , be given together with their reference energies and forces, $E^{\\mathrm{q}}(x^{(k)})=E^{(k)}$ and $-\\nabla E^{\\mathrm{q}}(x^{(k)})=f^{(k)}$ . We form an overdetermined system of linear equations on $c_{\\alpha}$ , \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\n$$\n\\begin{array}{r}{\\displaystyle\\sum_{i=1}^{N^{(k)}}\\sum_{\\alpha\\in A}c_{\\alpha}B(D x_{i}^{(k)})=E^{(k)},}\\\\ {\\displaystyle\\frac{\\partial}{\\partial x_{j}^{(k)}}\\sum_{i=1}^{N^{(k)}}\\sum_{\\alpha\\in A}c_{\\alpha}B(D x_{i}^{(k)})=-f_{j}^{(k)}}\\end{array}\n$$ \n\n(cf. (2.1) and (2.2)), which we write in the matrix form $X c=g$ . These equations may be ill-conditioned, hence a regularization must be used. We tried three versions of regularization, namely, the $\\ell_{p}$ regularization with $p\\in\\{0,1,2\\}$ , all described below. All three can be written as \n\n$$\n\\mathrm{~{\\mathrm{~\\find~}}~}\\operatorname*{min}_{c}\\|X c-g\\|^{2}\\quad{\\mathrm{~subject~to~}}\\quad\\|c\\|_{\\ell_{p}}^{2}\\leq t,\n$$ \n\nwhere $t$ is the regularization parameter and $\\|c\\|_{\\ell_{0}}$ is defined as the number of nonzero entires in $c$ . For $p\\geq1$ this can be equivalently rewritten as \n\n$$\n\\mathrm{~\\find~}\\quad\\operatorname*{min}_{c}\\|X c-g\\|^{2}+\\gamma\\|c\\|_{\\ell_{p}}^{2},\n$$ \n\nwhere $\\gamma$ is an alternative regularization parameter. \n\n4.2.1. $\\ell_{2}$ regularization. For the solution of the overdetermined linear equations $X c=g$ we take \n\n$$\nc=(X^{T}X+\\gamma\\operatorname{diag}(X^{T}X))^{-1}X^{T}g,\n$$ \n\nwhere $\\operatorname{diag}(A)$ denotes the diagonal matrix whose d agonal elements are the same as in $A$ . The penalization matrix was chosen as $\\mathrm{diag}(X^{I^{\\prime}}X)$ instead of the identity matrix so that its scaling with respect to the database size and the scale of the basis functions $B_{\\alpha}$ , is compatible with that of the covariance matrix $X^{T}X$ . The regularization parameter $\\gamma$ was determined from the 16-fold cross-validation scheme [2] as described in the next paragraph. \n\nTo perform the 16-fold cross-validation, we split the database $X$ evenly into 16 nonoverlapping databases $\\tilde{X}_{1},\\ldots,\\tilde{X}_{16}$ . We then train 16 different models, each on the database $X\\setminus{\\tilde{X}}_{i}$ , and find the root mean square (RMS) error when tested on ${\\tilde{X}}_{i}$ . The parameter $\\gamma$ is then chosen such that the cross-validation RMS error averaged over these 16 models is minimal. \n\n4.2.2. $\\ell_{0}$ regularization. The advantage of the $\\ell_{0}$ regularization is that it produces sparse solutions $c$ , whereas the $\\ell_{2}$ regularization does not. We note that the $\\ell_{1}$ regularization also produces sparse solutions [29], but our numerical experiments show that the $\\ell_{0}$ regularization produces significantly more sparse solutions (however, at a cost of a larger precomputation time). \n\nWe thus solve a sequence of problems, parametrized by an integer parameter $N_{\\mathrm{nz}}$ (number of nonzeros) as follows: \n\n$$\n\\mathrm{\\find\\min}\\ ||X c-g||\\ \\mathrm{subject\\to}\\ ||c||_{\\ell_{0}}=N_{\\mathrm{nz}}.\n$$ \n\nand choose the minimal $N_{\\mathrm{nz}}$ such that $\\|X c-g\\|$ reaches the accuracy goal. \n\nTo describe the algorithm, it is convenient to rewrite the problem as follows. Let $\\pmb{A}$ be the set of all indices $\\alpha$ (earlier denoted as $A$ ). \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nThis is essentially a compressed sensing problem [31]. In order to solve it we take a standard greedy algorithm (similar to the matching pursuit from the compressed sensing literature) and turn it into a genetic algorithm by adding the local search and crossover steps. The main variable in this algorithm is the family (population) of the sets $A$ which is denoted by $\\mathcal{A}$ . The cap on the population size is set to be $N_{\\mathrm{cap}}>1$ . The algorithm is as follows: \n\n1. Let ${\\mathcal{A}}=\\{\\emptyset\\}$ as the solution for $N_{\\mathrm{nz}}=0$ . \n2. For each $A\\in{\\mathcal{A}}$ find $i\\not\\in A$ , such that $c$ corresponding to $A\\cup\\{i\\}$ is the best (i.e., minimizing $\\|X c-g\\|,$ ). Then replace $A$ with $A\\cup\\{i\\}$ . \n3. “Crossover”: If $|{\\mathcal{A}}|>1$ , then do the following. For each pair of sets, $A,A^{\\prime}\\in$ $\\mathcal{A}$ , divide randomly these sets into two nonintersecting subsets, $A=A_{1}\\cup A_{2}$ and $A^{\\prime}=A_{1}^{\\prime}\\cup A_{2}^{\\prime}$ , and generate new sets $A_{1}\\cup A_{2}^{\\prime}$ and $A_{1}^{\\prime}\\cup A_{2}$ . To generate such splittings of the sets, first sample uniformly an integer $m\\in\\{1,\\ldots,|A\\setminus$ $A^{\\prime}|\\}$ and then form $A_{2}$ and $A_{2}^{\\prime}$ by uniformly sampling $m$ distinct elements from $A$ and $A^{\\prime}$ , respectively. Then replace al the sets in $\\mathcal{A}$ with the newly generated sets. (Note that if $|\\mathcal{A}|=N_{\\mathrm{{cap}}}$ , then up to $N_{\\mathrm{cap}}(N_{\\mathrm{cap}}-1)$ sets will be generated—two sets from each of $\\binom{N_{\\mathrm{cap}}}{2}$ pairs.) \n4. “Local search”: 4.1. For each $A\\in{\\mathcal{A}}$ find $j\\in A$ such that $c$ corresponding to $A\\backslash\\{j\\}$ is the best. 4.2. Then find $i\\not\\in A\\setminus\\{j\\}$ such that $c$ corresponding to $(A\\setminus\\{j\\})\\cup\\{i\\}$ is the best. 4.3. If $i\\neq j$ , then 4.3a. include $(A\\setminus\\{j\\})\\cup\\{i\\}$ , into $\\mathcal{A}$ 4.3b. if $|\\mathcal{A}|>N_{\\mathrm{cap}}$ , then exclude $A$ from $\\mathcal{A}$ , and 4.3c. go to step 4.1. \n\n5. Remove all but $N_{\\mathrm{cap}}$ best sets in $\\mathcal{A}$ . \n\n6. Repeat steps 2–5 until the accuracy goal on $\\|X c-g\\|$ is reached. Then take the best set $A\\in{\\mathcal{A}}$ and compute the corresponding $c$ . \n\nWe note that whenever $A$ is fixed, then finding $c$ corresponding to $A$ is easy: $c=((X^{T}X)_{A A})^{-1}(X^{T}g)_{A}$ , where $\\bullet_{A}$ and ${\\bullet}_{A A}$ are the operations of extracting a subset of rows and columns corresponding to $A\\subset A$ . \n\n5. Numerical experiments. Our next goal is to understand how MTP performs compared to other interatomic potentials. Unfortunately, there are no existing works performing quantitative comparison between different machine learning potentials in terms of their accuracy and computational efficiency. In the present work we compare the performance of MTP with that of GAP for tungsten [26, 27] on the QM database published at www.libatoms.org together with the GAP code. We test MTP by fitting it on the database of 9693 configurations of tungsten, with nearly 150,000 individual atomic environments, and compare it to the analogously fitted GAP, namely, the one tagged as GAP $_6$ in [27] or as the iterative-SOAP-GAP or I-S-GAP in [26]. We note that this is a database of the Kohn–Sham DFT calculations (as opposed to a tight-binding model used in the analysis) for an electronic temperature of 1000◦K. We did not prove algebraic convergence of MTP to this model; however, we will observe it numerically. \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\nWe choose $R_{\\mathrm{cut}}=4.9\\AA$ and also set the minimal distance parameter to be $R_{\\mathrm{min}}:=$ $1.9\\mathring\\mathrm{A}$ . For the radial functions we choose \n\n$$\n\\hat{f}_{\\mu,\\nu}(r):=\\left\\{\\begin{array}{l l}{r^{-\\nu-2}r^{\\mu}(R_{\\mathrm{cut}}-r)^{2},}&{r
PotentialGAPMTP1MTP2
CPU time/atom [ms] basis functions134.2±2.6 100002.9 ±0.5 111330.8 ±0.2 760
Fit errors
force RMS error [eV/A]0.06330.04270.0633
[%]4.2%2.8%4.2%
regularization parameter force RMS error[eV/A]Cross-validation errors3:10=90
0.05110.0642
[%]3.4%4.3%
\n\nThe data from the conducted efficiency and accuracy tests are summarized in Table 5.1. The RMS force (more precisely, RMS of all force components over all non-single-atom configurations) is $1.505~\\mathrm{eV}/\\mathrm{\\AA}$ , which s used to compute the relative RMS error. The errors relative to this RMS force are also presented in the table. The GAP error is calculated based on the data from [26]. The CPU times do not include the initialization (precomputation) or constructing the atomistic neighborhoods. \n\nOne can see that MTP $^{\\perp}$ has about the same number of fitting parameters as GAP, while its fitting accuracy is about 1.5 times better and the computation time is 40 times smaller. MTP $_2$ was constructed such that its fitting accuracy is the same as GAP, but it uses many fewer parameters for fitting and its computation is more than two orders of magnitude faster. \n\nAlso included in the table is the 16-fold cross-validation error. It shows that MTP $^2$ is not overfitted on the given database, whereas MTP $^{\\perp}$ needs regularization to avoid overfitting. We anticipate, however, that by significantly increasing the database size, the cross-validation error of MTP $^{1}$ would go down and reach the current fitting error of MTP $^{\\perp}$ , since the fitting error follows closely the a gebraic decay (see Figure 5.1) and is not expected to deteriorate with increasing the database size. \n\n6. Conclusion. The present paper considers the problem of approximating a QM interaction model with interatomic potentials from a mathematical point of view. In particular, (1) a new class of nonparametric (i.e., systematically improvable) potentials satisfying all the required symmetries has been proposed and advantages in terms of accuracy and performance over the existing schemes have been discussed and (2) an algebraic convergence of fitting with these potentials in a simple setting has been proved and it was then confirmed with the numerical experiments. \n\nThis work is done under the assumption that all atoms are chemically equivalent. A straightforward extension to multicomponent systems would be to let the radial functions depend not only on the positions of atoms $x_{i}$ but also on the types of atoms $t_{i}$ Thus, the expression for the moments for atom $i$ could be \n\n$$\nM_{\\mu,\\nu}=\\sum_{j}f_{\\mu,\\nu}(|x_{j}-x_{i}|,t_{i},t_{j})(x_{j}-x_{i})^{\\otimes\\nu},\n$$ \n\nwhere the summation is over the neighborhood of atom $i$ . We leave exploring this path to future publications. \n\nAcknowledgments. The author is grateful to G´abor Cs´anyi for igniting the interest in this topic and for valuable discussions as a part of our ongoing collaboration. Also, the author thanks Albert Bart´ok-P´artay for his help with implementation of MTP in the QUIP software (available at http://www.libatoms.org/Home/LibAtoms QUIP), which was used to compare the performance of MTP with GAP. Finally, the author thanks the anonymous referees for many suggestions that led to improvement of the paper. \n\n# REFERENCES \n\n[1] X. Ai, Y. Chen, and C. A. Marianetti, Slave mode expansion for obtaining ab initio interatomic potentials, Phys. Rev. B, 90 (2014), 014308. [2] E. Alpaydin, Introduction to Machine Learning, MIT Press, Cambridge, MA, 2014. \n[3] A. P. Bart´ok, R. Kondor, and G. Cs´anyi, On representing chemical environments, Phys. Rev. B, 87 (2013), 184115. \n[4] A. P. Bart´ok, M. C. Payne, R. Kondor, and G. Cs´anyi Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons, Phys. Rev. Lett., 104 (2010), 136403. \n[5] F. L. Bauer and C. T. Fike, Norms and exclusion theorems, Numer. Math., 2 (1960), pp. 137– 141. [6] J. Behler, Atom-centered symmetry functions for constructing high-dimensional neural network potentials, J. Chemical Phys., 134 (2011), 074106. \n[7] J. Behler, Representing potential energy surfaces by high-dimensional neural network potentials, J. Phys. Condensed Matter, 26 (2014), 183001. [8] J. Behler and M. Parrinello, Generalized neural-network representation of high-dimensional potential-energy surfaces, Phys. Rev. Lett., 98 (2007) 146401. \n[9] B. J. Braams and J. M. Bowman, Permutationally invar ant potential energy surfaces in high dimensionality, Internat. Rev. Phys. Chemistry, 28 (2009), pp. 577–606. \n[10] E. Cances, M. Defranceschi, W. Kutzelnigg, C. Le Bris, and Y. Maday, Computational quantum chemistry: A primer, in Computational Chemistry, Handb. Numer. Anal., 10, P. G. Ciarlet and C. L. Bris, Eds., Elsevier, Amsterdam 2003, pp. 3–270. \n[11] H. Chen and C. Ortner, QM/MM methods for crystal ine defects. Part 1: Locality of the tight binding model, Multiscale Model. Simul., 14 (2016), pp. 232–264. \n[12] H. Chen and C. Ortner, QM/MM Methods for Crystalline Defects. Part 2: Consistent Energy and Force-Mixing, preprint, arXiv:1509.06627, 2015. \n[13] G. Ferre´, J.-B. Maillet, and G. Stoltz, Permutation-invariant distance between atomic configurations, J. Chemical Phys., 143 (2015), 104114. \n[14] M. Finnis, Interatomic Forces in Condensed Matter, Vol. 1, Oxford University Press, Oxford, UK, 2003. \n[15] M. Griebel, S. Knapek, and G. Zumbusch, Numerical Simulation in Molecular Dynamics: Numerics, Algorithms, Parallelization, Applications, Vol. 5, Springer Science & Business Media, New York, 2007. \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. \n\n[16] W. Hackbusch and B. N. Khoromskij, Towards $\\mathcal{H}$ -matrix approximation of the linear complexity, in Problems and Methods in Mathematical Physics, Oper. Theory Adv. Appl. 121, Birkh¨auser Verlag, Basel, 2001, pp. 194–220. \n[17] O. Hellman, P. Steneteg, I. A. Abrikosov, and S. I. Simak, Temperature dependent effective potential method for accurate free energy calculations of solids, Phys. Rev. B, 87 (2013), 104111. \n[18] N. J. Higham, Functions of Matrices: Theory and Computation, SIAM, Philadelphia, 2008. \n[19] M. Hirn, N. Poilvert, and S. Mallat, Quantum Energy Regression Using Scattering Transforms, preprint, arXiv:1502.02077, 2015. \n[20] J. Jalkanen and M. H. M¨user, Systematic analysis and modification of embedded-atom potentials: Case study of copper, Model. Simul. Materials Sci. Eng., 23 (2015), 074001. \n[21] Z. Li, J. R. Kermode, and A. De Vita, Molecular dynamics with on-the-fly machine learning of quantum-mechanical forces, Phys. Rev. lett., 114 (2015), 096405. \n[22] S. Linnainmaa, Taylor expansion of the accumulated rounding error, BIT, 16 (1976), pp. 146– 160. \n[23] F. Q. Nazar and C. Ortner, Locality of the Thomas-Fermi-von Weizs¨acker Equations, preprint, arXiv:1509.06753, 2015. \n[24] L. J. Nelson, V. Ozoli¸nsˇ, C. S. Reese, F. Zhou, and G. L. W. Hart, Cluster expansion made easy with Bayesian compressive sensing, Phys. Rev. B, 88 (2013), 155105. \n[25] G. Szeg¨o, Orthogonal Polynomials, Vol. 23, AMS, Providence, RI, 1939. \n[26] W. J. Szlachta, First Principles Interatomic Potential for Tungsten Based on Gaussian Process Regression, preprint, arXiv:1403.3291, 2014. \n[27] W. J. Szlachta, A. P. Bart´ok, and G. Cs´anyi, Accuracy and transferability of Gaussian approximation potential models for tungsten, Phys. Rev. B, 90 (2014), 104108. \n[28] A. P. Thompson, L. P. Swiler, C. R. Trott, S. M. Foiles, and G. J. Tucker, SNAP: Automated generation of quantum-accurate interatomic potentials, J. Comput. Phys., 285 (2015), pp. 316–330. \n[29] R. Tibshirani, Regression shrinkage and selection via the lasso, J. R. Stat. Soc. Ser. B Methodol., 58 (1996), pp. 267–288. \n[30] H. Weyl, The Classical Groups: Their Invariants and Representations, Princeton Landmarks in Mathematics and Physics, Princeton University Press, Princeton, NJ, 1997. \n[31] Y. Zhang, Theory of compressive sensing via $\\ell_{1}$ -minimization: A non-rip analysis and extensions, J. Oper. Res. Soc. China, 1 (2013), pp. 79–105 \n\nCopyright $\\circledcirc$ by SIAM. Unauthorized reproduction of this article is prohibited. " + }, + { + "id": "10.1002_aenm.201501590", + "DOI": "10.1002/aenm.201501590", + "DOI Link": "http://dx.doi.org/10.1002/aenm.201501590", + "Relative Dir Path": "mds/10.1002_aenm.201501590", + "Article Title": "Electrochemical Stability of Li10GeP2S12 and Li7La3Zr2O12 Solid Electrolytes", + "Authors": "Han, FD; Zhu, YZ; He, XF; Mo, YF; Wang, CS", + "Source Title": "ADVANCED ENERGY MATERIALS", + "Abstract": "The electrochemical stability window of solid electrolyte is overestimated by the conventional experimental method using a Li/electrolyte/inert metal semiblocking electrode because of the limited contact area between solid electrolyte and inert metal. Since the battery is cycled in the overestimated stability window, the decomposition of the solid electrolyte at the interfaces occurs but has been ignored as a cause for high interfacial resistances in previous studies, limiting the performance improvement of the bulk-type solid-state battery despite the decades of research efforts. Thus, there is an urgent need to identify the intrinsic stability window of the solid electrolyte. The thermodynamic electrochemical stability window of solid electrolytes is calculated using first principles computation methods, and an experimental method is developed to measure the intrinsic electrochemical stability window of solid electrolytes using a Li/electrolyte/electrolyte-carbon cell. The most promising solid electrolytes, Li10GeP2S12 and cubic Li-garnet Li7La3Zr2O12, are chosen as the model materials for sulfide and oxide solid electrolytes, respectively. The results provide valuable insights to address the most challenging problems of the interfacial stability and resistance in high-performance solid-state batteries.", + "Times Cited, WoS Core": 911, + "Times Cited, All Databases": 988, + "Publication Year": 2016, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000374703900002", + "Markdown": "# Electrochemical Stability of Li10GeP2S12 and Li7La3Zr2O12 Solid Electrolytes \n\nFudong Han, Yizhou Zhu, Xingfeng He, Yifei Mo,\\* and Chunsheng Wang\\* \n\nThe electrochemical stability window of solid electrolyte is overestimated by the conventional experimental method using a Li/electrolyte/inert metal semiblocking electrode because of the limited contact area between solid electrolyte and inert metal. Since the battery is cycled in the overestimated stability window, the decomposition of the solid electrolyte at the interfaces occurs but has been ignored as a cause for high interfacial resistances in previous studies, limiting the performance improvement of the bulk-type solid-state battery despite the decades of research efforts. Thus, there is an urgent need to identify the intrinsic stability window of the solid electrolyte. The thermodynamic electrochemical stability window of solid electrolytes is calculated using first principles computation methods, and an experimental method is developed to measure the intrinsic electrochemical stability window of solid electrolytes using a Li/electrolyte/electrolyte-carbon cell. The most promising solid electrolytes, $\\mathsf{L i}_{10}\\mathsf{G e P}_{2}\\mathsf{S}_{12}$ and cubic Li-garnet $\\begin{array}{r}{\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12},}\\end{array}$ are chosen as the model materials for sulfide and oxide solid electrolytes, respectively. The results provide valuable insights to address the most challenging problems of the interfacial stability and resistance in high-performance solid-state batteries. \n\n# 1. Introduction \n\nThe safety issue of Li-ion batteries has resulted in fire incidences for electric vehicles and airplanes. The use of flammable organic electrolytes in commercial Li-ion batteries is often blamed. Replacing the organic electrolyte with inorganic, ceramic solid electrolytes, which are intrinsically nonflammable, to assemble all-solid-state Li-ion batteries has the promise to ultimately resolve the safety issue of Li-ion batteries. Similar to an organic liquid electrolyte, a solid electrolyte has also to satisfy three critical requirements: (1) high Li ionic conductivity of $>10^{-3}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1}$ and low electronic conductivity, (2) wide electrochemical stability window, and (3) chemical compatibility with the anode and cathode. In the past few years, major advances have been achieved in increasing the Li ionic conductivity of the solid electrolytes. The state-of-the-art solid electrolyte materials, such as Li-garnet $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ (LLZO) and $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ (LGPS) have achieved an ionic conductivity of $10^{-3}$ to $10^{-2}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1}$ 1,2 which are comparable to commercial organic liquid electrolytes. The high ionic conductivity in solid electrolytes has ignited the research of all-solid-state Li-ion batteries. After achieving adequate Li ionic conductivity in the solid electrolyte materials, current research efforts turned to enhancing the electrochemical stability of the solid electrolytes and chemical compatibility between the solid electrolytes and electrodes, so that Li metal anode and high voltage cathode materials can achieve higher energy density in all-solid-state Li-ion batteries. \n\nTo enable the highest voltage output of the solid-state battery by coupling a lithium metal anode with a high voltage cathode material, a very wide electrochemical stability window (0.0–5.0 V) is desired for an ideal solid electrolyte. The electrochemical stability window of solid electrolyte was typically obtained by applying the linear polarization on the Li/solid electrolyte/ inert metal (e.g., Pt) semiblocking electrode. Tested by this method, very wide electrochemical stability windows of 0.0 to $5.0\\mathrm{V}$ were reported for both LGPS and LLZO. 2,3 However, the electrochemical performances of the bulk-type all-solid-state battery batteries assembled with these solid electrolytes 2,4 are far worse than the liquid-electrolyte based batteries even though the solid electrolyte has a comparable ionic conductivity to the liquid electrolyte. The high interfacial resistance is often blamed as the main limiting factor for the performance of the solid state battery. 5 The origin of the interfacial resistance, though still not fully understood, is often attributed to the poor physical interfacial contact, the formation of space charge layers, 6 and/or the formation of interphase layers due to the chemical reactions between the electrolyte and electrode. 7 Although a variety of interfacial processing techniques, such as dynamic pressing, 8 nanosizing, 9 cosintering, 10 screen printing, 11 surface coatings 12,13 have been attempted to engineer the interfaces between the electrodes and electrolytes, the performances of the solid-state battery are still much lower than the liquidelectrolyte based batteries. The limited electrochemical stability of the solid electrolyte is rarely thought to be an issue, since the batteries are cycled within the “wide” stability window of electrolytes measured using the semiblocking electrode. 14 \n\nHowever, recent studies have challenged the claimed stability of the solid electrolyte materials. For example, LiPON, a solid electrolyte demonstrated to be compatible with Li metal anode, has recently been shown to decompose against Li metal. 15 In addition, our first principles computational and experimental study demonstrated the reversible reduction and oxidization of the LGPS solid electrolyte materials at $_{0-1.7\\mathrm{~V~}}$ and $2{-}2.5\\mathrm{~V},$ respectively, 5 which indicated a true electrochemical window of the LGPS significantly narrower than the $0.0{-}5.0\\mathrm{~V~}$ window obtained using the semiblocking electrode. 5,16 These results suggest that the electrochemical window measurements based on the semiblocking electrodes significantly overestimated the true electrochemical window governed by the intrinsic thermodynamics of the material. The overestimated electrochemical stability of solid electrolytes is caused by the slow kinetics of the decomposition reactions due to the small contact area between LGPS and current collectors. 5 However, in the bulk-type allsolid-state battery, a large amount of carbon and solid electrolyte are mixed together with the active materials to form the composite electrode. 9,10 As a result, the reduction or oxidation kinetics of the solid electrolyte in the composite electrode is significantly accelerated because of the significantly-increased contact area between the solid electrolyte and electronic conductive additives. The electrochemical stability window of the electrolyte in the carbon-electrolyte-active material electrode composite cannot be properly captured by the semiblock electrodes, which may be only more suitable for the cell configurations in thin-film solid-state batteries. 17 Therefore, a proper cell design is needed to evaluate the electrochemical window of the solid electrolyte in the bulk-type all-solid-state batteries. \n\nMore importantly, the limited stability of the solid electrolyte materials, though still neglected by battery community, has significantly restricted the performance of all-solid-state Li-ion batteries. At the cycling voltages beyond the stability window of the solid electrolyte, the decomposition products of the solid electrolyte would form as an interphase at the interfaces between solid electrolyte and electronic conductive additives. Depending on the properties of the decomposition products, the interphase may lead to an increase in interfacial resistances and a decrease in the performance of the bulk-type solid-state battery. Unfortunately, the interfacial resistance arising from the decomposition of solid electrolytes has been ignored so far due to the overestimated stability window from the semiblocking electrode measurements. The intrinsic (true) electrochemical stability window of solid electrolytes is critical in understanding the origins of high interfacial resistance in the bulk-type solid-state Li-ion batteries. However, only few theoretical studies have examined the electrochemical stability of solid electrolytes, and no existing experimental technique can measure the true stability window of the solid electrolytes. \n\nIn this study, we challenge the claimed stability of the solid electrolyte materials and the use of semiblock electrode design for evaluating the electrochemical window for solid electrolyte materials. The most promising solid electrolytes, $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ and cubic Li-garnet $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ were chosen as the model materials for sulfide and oxide solid electrolytes, respectively. \n\nFirst principles calculations were performed to obtain the intrinsic thermodynamic electrochemical stability windows. A new Li/electrolyte/electrolyte-carbon cell was proposed to replace current Li/electrolyte/Pt semiblocking electrode for the measurement of the true electrochemical stability window of solid electrolytes. The first principles computation and experimental results are in good agreement, indicating that both of these solid electrolyte materials have narrower electrochemical window than what was previously claimed. The understanding of the intrinsic thermodynamics about the solid electrolyte materials at different voltages during the battery cycling provides invaluable guidance for the development of the bulk-type all-solid-state battery. \n\n# 2. Results \n\n# 2.1. Electrochemical Stability of Li10GeP2S12 \n\nLithium sulfide-based solid electrolytes exhibit high ionic conductivity, low grain boundary resistance, and the excellent mechanical property, which allows forming a good interfacial contact with the electrode by cold-pressing without high temperature sintering. 18,19 In this study, $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ (LGPS) is chosen as a typical example of sulfide electrolytes. LGPS was reported to have the highest room-temperature ionic conductivity $({\\approx}10^{-2}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1})^{[2]}$ among all solid electrolyte materials and a wide “apparent” electrochemical stability window of $0.0{-}5.0\\mathrm{V}$ determined by cyclic voltammetry of a Li/LGPS/Pt semiblock electrode. 2 \n\nHowever, the first principles computation using Li grand potential phase diagram demonstrated that the intrinsic stability window is much narrower than 0.0–5.0 V. 16 The Li grand potential phase diagram identifies the phase equilibria at different potentials and the most thermodynamically favorable reactions at the given potential, assuming the full thermodynamic equilibrium and no kinetic limitation in the reaction and transportation. The same computation scheme has been used in the calculations of voltages and reaction energies in the lithiation/delithiation of battery materials. Figure 1 shows the calculated voltage profile and phase equilibria of LGPS upon lithiation and delithiation, confirming that LGPS has a much narrower electrochemical window than $5.0~\\mathrm{V}.^{[2]}$ The reduction of the LGPS starts at 1.71 V, where LGPS is lithiated and turns into $\\mathrm{Li}_{4}\\mathrm{GeS}_{4}$ P, and $\\mathrm{Li}_{2}\\mathrm{S}$ . With further decrease of the potential, there are multiple thermodynamic voltage plateaus corresponding to the Li-P and Li-Ge alloying processes upon lithiation. Our calculations predicted the reduction products of LGPS to be $\\mathrm{Li}_{2}\\mathrm{S}$ , $\\mathrm{Li}_{15}\\mathrm{Ge}_{4}$ $\\mathrm{Li}_{3}\\mathrm{P}$ at $0\\mathrm{V},$ which have been confirmed by the experimental results. 5 On the other hand, the oxidization of the LGPS to $\\mathrm{Li}_{3}\\mathrm{PS}_{4}$ S, and ${\\mathrm{GeS}}_{2}$ starts at only $2.14~\\mathrm{V},$ and the formed $\\mathrm{Li}_{3}\\mathrm{PS}_{4}$ is further oxidized into S and $\\mathrm{P}_{2}\\mathrm{S}_{5}$ at $2.31\\mathrm{V}.$ In summary, our calculation results have shown that the LGPS has a limited electrochemical stability window from 1.7 to $2.1\\mathrm{V}.$ \n\nCyclic voltammetry (CV) was used to experimentally evaluate the electrochemical stability of LGPS. Using the conventional Li/LGPS/Pt semiblocking electrode (voltage range: $-0.6$ to 5.0 V), the decomposition current within the voltage window of 0.0 to $5.0\\mathrm{~V~}$ cannot be observed from the CV of LGPS. 2,5 \n\n![](images/654214ffbe1f6379b5d8551f1b365cc3ab46a4e67334f0d7c88548d85f68835f.jpg) \nFigure 1. The first principles calculation results of the voltage profile and phase equilibria of LGPS solid electrolyte upon lithiation and delithiation. \n\nThe “wide” electrochemical stability window of $0.0{-}5.0\\mathrm{~V~}$ is because the decomposition current is very small and is underestimated by the huge Li deposition/dissolution peaks. 20 To avoid the huge Li deposition/dissolution peaks, the conventional Li/LGPS/Pt semiblocking electrode was scanned within restricted voltage windows $(0.0{-}2.5\\mathrm{V}$ and 2.5–4.0 V). As shown in Figure S1 (Supporting Information), apparent current due to the decomposition of LGPS could be clearly observed in the linear scan of the Li/LGPS/Pt although the reaction current is still very low due to the limited interfacial contact between LGPS and Pt in the Li/LGPS/Pt cell. In this regard, we propose a novel experimental method to measure the electrochemical stability window of LGPS using a Li/LGPS/LGPS-C/Pt cell. A large amount of carbon (graphite, KS-4) was mixed into LGPS (weight ratio of LGPS to carbon is 75:25) to form the electrode. The increased contact between LGPS and carbon would significantly improve the kinetics of the decomposition reaction due to the facile electron transport as well as the significantly increased active area for charge-transfer reaction. Thus, the intrinsic stability window of LGPS is expected to be obtained from the CV scan of the Li/LGPS/LGPS-C/Pt cell. Since the electrochemical decomposition and the lithiation/delithiation of the LGPS are essentially the same process but described from two different perspectives, the reversible decomposition of LGPS electrolyte had been demonstrated using the same $\\operatorname{Li}/$ LGPS/LGPS-C/Pt cell in Figure S2 in the Supporting Information 5 of our previous work. The result indicates that the reduction of LGPS starts at $1.7\\mathrm{~V~}$ while the oxidation of LGPS starts at $2.1~\\mathrm{V}.$ This electrochemical behavior agrees very well with the computational results, and both computational and experimental results indicate the true electrochemical stability window of 1.7 to $2.1\\mathrm{~V~}$ for LGPS. Additionally, the oxidation of S at high potentials and the formation of Li-Ge and Li-P alloys at the low potentials were also confirmed by the X-ray photoelectron spectrum results. 5 The main function of carbon in the LGPS-C composite is to increase the electronic conductivity of LGPS so that the decomposition kinetics could be improved. In this regard, carbon is not the only option for the electronic-conductive additive. To exclude the potential interactions between carbon and LGPS, we replaced carbon with the inert metal powder (Pt black), i.e., $25\\mathrm{wt\\%}$ Pt black and mixed Pt with LGPS to form the LGPS-Pt composite electrode. The CV curves of the \n\nLi/LGPS/LGPS-Pt/Pt cell are shown in Figure S2 (Supporting Information). Both the oxidation and reduction peaks could be observed at similar voltages in the CV curves of the Li/LGPS/ LGPS-C/Pt cell. The result implies that the redox peaks in Li/ LGPS/LGPS-C/Pt cell is not induced by the reaction between carbon and LGPS but the decomposition of LGPS itself. These results demonstrated that the thermodynamic electrochemical stability window of LGPS can be accurately calculated using our computation scheme, and that Li/LGPS/LGPS-C/Pt cell can be used to measure the true electrochemical stability of LGPS. \n\nTherefore, our proposed method of measuring the electrochemical stability of the electrolyte in Li/electrolyte/electrolyteC cell is demonstrated to obtain the “true” electrochemical stability window based on the intrinsic thermodynamics of the solid electrolyte. The Li/electrolyte/electrolyte-C cell provides improved kinetics from large and continuous physical contacts between solid electrolyte and carbon to facilitate the thermodynamically favorable decomposition reactions of the solid electrolyte. The kinetics of these reactions is limited in the semiblocking electrode, which yields overestimated electrochemical stability. Moreover, the use of the Li/electrolyte/electrolyte-C cell mimics the cell configuration in the bulk-type solid-state battery and represents the real microstructural architectures in the solid-state electrode composite, where carbon and solid electrolyte are mixed with the active material. It should be noted that in this work we mainly focused on the thermodynamic electrochemical stability of the solid electrolyte materials. The degree (extent) of the decomposition of a solid electrolyte depends on the kinetics of decomposition reaction. The particle size of solid electrolyte, the electronic and ionic conductivities of electrolytecarbon composite, the electronic and ionic conductivities of decomposition products, and the applied current (or CV scan rate) all change the reaction kinetics, thus the degree of decomposition of solid electrolyte. The passivation from the electronic insulating decomposition products may also prevent further decomposition of solid electrolyte. These indicate that the decomposition of the solid electrolyte in the real all-solid-state cell may not be as severe as that in the Li/electrolyte/electrolyte-C cell because of the low content of carbon in the electrode composite. However, even a slight amount of decomposition of the solid electrolyte may cause a huge interfacial resistance in the real cell, which was always ignored and will be discussed in detail in Section 3. Therefore, the measurements based on the Li/electrolyte/electrolyte-C cell could help to understand the electrochemical interfacial behavior of the solid electrolyte in the real bulk-type solid-state battery. \n\nIn addition, we calculated the electrochemical stability of other sulfide electrolytes, such as $\\mathrm{Li}_{3.25}\\mathrm{Ge}_{0.25}\\mathrm{P}_{0.75}\\mathrm{S}_{4}$ $\\mathrm{Li}_{3}\\mathrm{PS}_{4}$ $\\mathrm{Li}_{4}\\mathrm{GeS}_{4}$ $\\mathrm{Li}_{6}\\mathrm{PS}_{5}\\mathrm{Cl}$ , and $\\mathrm{Li_{7}P_{2}S_{8}I}$ , using the same computation scheme. 21 The thermodynamically intrinsic electrochemical stability windows and the decomposition phase equilibria beyond their stability window are very similar to those of LGPS. The cathodic limit is around $1.6{-}1.7\\mathrm{V}$ for the reduction of Ge or $\\mathrm{\\DeltaP}$ contained in the sulfide electrolytes, and the anodic limit is usually around $2.1{-}2.3\\mathrm{~V~}$ corresponding to the oxidization of S. Doping halogen elements, such as Cl and I, into the materials increases the the potential to fully delithiate the materials. 22–24 The results indicate that the narrow electrochemical stability window is originated from the reduction of P/Ge and the oxidization of S. \n\n# 2.2. Electrochemical Stability of $\\ L i_{7}\\ L a_{3}Z r_{2}O_{72}$ \n\nDespite the high ionic conductivity, most of the sulfide electrolytes are sensitive to moisture and/or oxygen in the ambient environment. The oxide-based solid electrolytes, which have better stability in air, therefore attract a lot of interests. In particular, cubic Li-stuffed garnet (i.e., $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}\\big)$ ) reported with a wide electrochemical stability window of $0.0{-}6.0\\ \\mathrm{V}^{[3,25]}$ and a high ionic conductivity of $10^{-4}–10^{-3}\\mathrm{~S~cm^{-1},}^{!}$ 1 is considered as one of the most promising oxide solid electrolytes. In this section, the same research methodology was applied to study the electrochemical stability window of lithium oxide-based solid electrolyte, especially LLZO. \n\nThe voltage profile of LLZO upon lithiation/delithiation and the detailed phase equilibria of LLZO at different voltages were calculated using the first principles method (Figure 2). The results show that the thermodynamic electrochemical stability window of LLZO is also smaller than the reported value of $0.0{-}6.0\\ \\mathrm{V}.^{[3]}$ The oxidation decomposition of LLZO occurs at as low as $2.91\\mathrm{~V~}$ to form $\\mathrm{Li}_{2}\\mathrm O_{2}$ $\\mathrm{Li}_{6}\\mathrm{Zr}_{2}\\mathrm{O}_{7}$ and $\\mathrm{La}_{2}\\mathrm{O}_{3}$ As the voltage increases above $3.3~\\mathrm{V},$ $\\mathrm{O}_{2}$ is generated from the oxidation of $\\mathrm{Li}_{2}\\mathrm O_{2}$ (Figure 2). At below $0.05\\mathrm{~V},$ LLZO is lithiated and reduced into $\\mathrm{Li}_{2}\\mathrm O$ , $\\mathrm{Zr}_{3}\\mathrm{O}$ , and $\\mathrm{La}_{2}\\mathrm{O}_{3}$ , and $\\mathrm{Zr}_{3}\\mathrm{O}$ may be further reduced into $\\mathrm{zr}$ metal at below 0.004 V (Figure 2). The thermodynamic results based on the energetics of DFT calculations indicate LLZO is not thermodynamically stable against Li metal. However, the reduction potential of LLZO (0.05 V) is very close to Li metal deposition potential (0 V), the thermodynamic driving force for the reduction is very small. Since these values of energy and voltage (0.004 V) for the further reduction of $\\mathrm{Zr}_{3}\\mathrm{O}$ are as small as the potential errors of typical DFT calculations and the approximations in our calculation scheme, the exact potential to reduce $\\mathrm{Zr}_{3}\\mathrm{O}$ into $\\mathrm{zr}$ may be below or above $0\\ \\mathrm{V}.$ However, if the potential is significantly lower than $0\\mathrm{~V~},$ the formation of $\\mathrm{zr}$ would be thermodynamically favorable. In addition, we also evaluated the electrochemical stability of the garnet phases doped by the cation dopants, such as Ta, Nb, and Al (Tables S1–S3, Supporting Information), which are commonly applied to stabilize the cubic phase of LLZO and to increase the Li ionic conductivity. The calculations indicate that a small amount of dopants, such as Ta, Al, Nb, which may be reduced at a slightly higher reduction potential, does not have a large effect on the reduction/oxidation of the host elements in LLZO (Tables S1–S3, Supporting Information). At $0.0\\mathrm{V},$ the doped cations Ta and Nb are reduced into metallic states, and Al is reduced into $\\mathrm{Zr{\\cdot}A l}$ alloys. Considering the low amount of dopants in LLZO, the effects of dopants on the stability window are small. Given the low reduction potentials for the garnet reduction, the good stability of the garnet LLZO may be explained by the formation of surface passivation after decomposition, such as $\\mathrm{Li}_{2}\\mathrm O$ , $\\mathrm{La}_{2}\\mathrm{O}_{3}$ and other oxides. In addition, the formation of $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ surface layers due to reaction of LLZO with the $\\mathrm{CO}_{2}$ in the air may also help passivating the LLZO. 26,27 These results may explain why LLZO was widely observed to be stable with Li at room temperature in many studies. 25,28 \n\n![](images/ce24e1b309474bc51d1f9d0a1acba9170076a2fcef1452c1e0d9cb24951c4f0e.jpg) \nFigure 2. The first principles calculation results of the voltage profile of LLZO solid electrolyte upon lithiation and delithiation. \n\nThe CV of the Li/LLZO/LLZO-C/Pt cell was used to measure the electrochemical stability window of LLZO, which was doped with a small amount of Ta to stabilize the cubic phase of LLZO. 29 To increase the contact area between the LLZO and carbon, the as-obtained LLZO powder was ground using a high-energy ball mill to reduce its particle size below $1\\upmu\\mathrm{m}$ , and then a thin-layer of carbon was coated on LLZO, as shown in Figure S3 (Supporting Information). The carbon-coated LLZO was then mixed with carbon black (weight ratio is 40:60) to make the LLZO-C composite electrode. All these processes were done in an Ar atmosphere to protect the LLZO from the slow reaction with the $_{\\mathrm{H}_{2}\\mathrm{O}/\\mathrm{CO}_{2}}$ in air. 26,27 The XRD test (Figure S4, Supporting Information) confirmed that the LLZO structure remained after grinding and carbon-coating processing. The same $\\ensuremath{\\mathrm{Zr}}3d$ spectra of LLZO before and after carbon coating (Figure S5, Supporting Information) indicates that LLZO is stable upon high-temperature carbonization process and no apparent carbothermal reduction of $\\mathrm{zr}$ could be observed. The thermodynamic oxidation stability of the LLZO was examined by the CV scan of the Li/LLZO/LLZO-C cell within the voltage range of $2.6\\mathrm{-}10.0\\ \\mathrm{V}.$ As can be observed from Figure 3 the apparent oxidation of LLZO starts at about $4.0\\mathrm{V},$ which is much lower than the reported value of $6.0{\\mathrm{V}}.$ The subsequent cathodic scan indicates the oxidation reaction is not reversible, and no oxidation peak can be observed in the second cycle. The maximum current of ${\\approx}5~{\\upmu}\\mathrm{A}$ in Figure 3 indicates that only a small amount of LLZO was oxidized. It should also be noted that the small oxidation current could also come from the insufficient ionic conduction in the LLZO-C composite because of the large amount of carbon additives as well as the large grain boundary resistance between LLZO particles. A larger current would be expected if a continuous ionic pathway through LLZO was formed in the LLZO-C composite (e.g., from co-sintering of LLZO solid electrolyte and LLZO-C electrode. 10 ) The higher voltage (4.0 V) compared with the calculation result (2.91 V) can be explained by the large over-potential for the oxidation of LLZO. It should be noted that the CV scan of Li/LLZO/ LLZO-C/Pt cell was tested in an Ar-filled glovebox and similar results were obtained when graphite was used as the electronic conductive additive, excluding the oxidation of carbon additives if LLZO is stable. Since the reduction potential of the LLZO at $0.05\\mathrm{~V~}$ is very close to the voltage of Li metal, it is difficult to distinguish the reduction of LLZO from the Li deposition in the CV scan and to quantify the reduction potential of LLZO. \n\nX-ray photoelectron spectroscopy (XPS) was used to identify the reduction and oxidation products of LLZO beyond its stability window. In order to increase the yields of decomposition products for characterization, the LLZO-C composite electrode was cycled against Li metal in a liquid electrolyte, which provided faster reaction kinetics. A 5-V class liquid electrolyte, $1\\mathrm{~M~LiPF}_{6}$ in a mixed solvent of FEC, FEMC, and HFE (volume ratio is 2:6:2), was used to minimize the oxidation from the liquid electrolyte. The Li/LLZO half-cells were charged to $4.5~\\mathrm{V}$ or discharged to $0\\mathrm{~V~}$ at a current density of $10\\mathrm{\\mA\\g^{-1}}$ and were then maintained at the voltages for $^{72\\mathrm{~h~}}$ . The charge and discharge curves of the LLZO-C composite electrodes are provided in the Supporting Information (Figure S6, Supporting Information). However, it is impossible to conclude the decomposition of the LLZO simply from the charge/discharge curve of the LLZO-C electrode in Figure S7 (Supporting Information) because carbon in the LLZO-C electrode will also reacts with lithium and solid-electrolyte-interphase (SEI) is also formed on carbon. \n\n![](images/9fbe9c7f045b8600c1f9dd61874ff83f07bc73d28fd12b9ca5adc4839e3d1698.jpg) \nFigure 3. Cyclic voltammetry of Li/LLZO/LLZO-C/Pt cell within the voltage range of $2.6\\mathrm{-}10.0\\ V.$ . \n\nTherefore, XPS was used to characterize the decomposition of LLZO. Figure 4a shows the XPS survey of the fresh and charged LLZO electrodes. The atomic percentages of the O and $\\mathrm{zr}$ derived from the survey (Table 1) indicates the atomic ratio of O to $\\mathrm{zr}$ decreases from 7.6:1 to 4.9:1 after LLZO was charged to $4.5~\\mathrm{V}.$ It should be noted that 2h $\\mathrm{Ar^{+}}$ sputtering was performed on the surface of the charged LLZO before collecting the atomic concentrations of O and $\\mathrm{zr}$ in order to completely remove the surface layers caused by the decomposition of the liquid electrolyte at a high potential. The complete removal of SEI after sputtering is confirmed by the XPS spectra of C 1s of the LLZO-C samples upon different sputtering times (Figure S7, Supporting Information). Multiple peaks above 284.6 eV (carbon black) could be observed for the charged LLZO before sputtering, indicating that several carbon-containing species are present at the surface. These carbon-containing species are most likely attributed to the decomposition products of the liquid electrolyte. However, after $^\\textrm{\\scriptsize1h}$ sputtering, only one peak at $284.6\\ \\mathrm{eV}$ corresponding to the carbon black in the LLZO-C electrode could be observed in the sample, which means that all the SEI species were removed. One more hour sputtering was performed in order to completely remove the surface layer. This result confirms that $\\mathrm{O}_{2}$ was released from the charged LLZO, which is consistent with our computation result (Figure 2). No obvious binding energy shift can be observed for Li, La, Zr, O elements after the LLZO was charged. On the other hand, Figure 4b compares the high-resolution spectra of $\\textstyle\\operatorname{Zr}3d$ of LLZO electrodes at the fresh and discharged states. All $\\textstyle\\operatorname{Zr}3d$ spectra exhibit a doublet with a fixed difference of $2.43\\ \\mathrm{eV}$ because of the spinsplit coupling between $3d_{5/2}$ and $3d_{3/2}$ For the fresh LLZO electrode, two different chemical environments of the $\\mathrm{zr}$ can be observed. The main peak of Zr $3d_{5/2}$ located at the $181.8\\mathrm{eV}$ corresponds to the $\\mathrm{zr}$ in the cubic garnet, 26 while the side peak of the $\\mathrm{Zr~}3d_{5/2}$ at the $179.7\\ \\mathrm{eV}$ may be ascribed to the oxide impurities (e.g., $\\mathrm{La}_{2}\\mathrm{Zr}_{2}\\mathrm{O}_{7}$ ) at the surface of the sample though the amount of the impurities is too small to be detected in the XRD test. 30,31 Both $\\mathrm{zr}$ peaks remained with the increased relative intensity of the side peak at $179.7\\ \\mathrm{eV},$ after the LLZO was discharged to $0\\mathrm{V}.$ In addition, another peak at a lower binding energy of $178.2\\ \\mathrm{eV}$ also appears for the discharged LLZO. It is known that various $\\mathrm{zr}$ suboxides exist and their binding energy will shift to a lower value as the oxidation state of $\\mathrm{zr}$ decreases. 32 The increase in the relative intensity of side peak at $179.7\\ \\mathrm{eV}$ as well as the appearance of a new peak at a lower binding energy $(178.2\\ \\mathrm{eV},$ ascribed to $\\mathrm{Zr}_{3}\\mathrm{O}$ herein) confirmed the reduction of $\\mathrm{zr}$ in the discharged LLZO, which agrees with the calculation result. It should be noted that the main peak at $181.8\\ \\mathrm{eV}$ of $\\mathrm{zr}$ still remained after the LLZO was discharged to $0\\mathrm{V},$ indicating that only the surface of the LLZO was reduced and most of LLZO was still stable. Nevertheless, our results demonstrated that the electrochemical stability window of garnet is not as wide as previously reported, and the reduction of $\\mathrm{zr}$ and the oxidation of O contained in LLZO occur beyond the stability window of LLZO. \n\n![](images/70eea5dd12c6b0c44f8c7e82e362cc2ed22c0fcc580ca87f3a32e21281e56ddc.jpg) \nFigure 4. a) The XPS survey spectrum of the fresh and charged LLZO. The atomic percentage of O and $Z\\boldsymbol{\\mathsf{r}}$ in the sample is obtained from the area of $\\textsf{O}$ 1s and $Z r3d$ peak, respectively. b) High resolution $Z r3d$ core XPS spectra of fresh and discharged LLZO. The curve fits were obtained using fixed spin splits $(3d_{3/2}-3d_{5/2}=2.43\\ \\mathrm{eV})$ . \n\nTable 1. XPS analysis-derived O and Zr elements atomic concerntrations. \n\n\n
SamplesO content [at%]Zr content [at%]O/Zr ratio
Fresh6.640.877.6:1
Charged to 4.5 V2.120.434.9:1
\n\nOur computation and experimental results provide a new mechanism for the short-circuiting across the Li/LLZO/Li cell during Li striping/plating test at a high overpotential. 33–35 It was reported that the Li dendrite growth across the LLZO electrolyte layer is responsible for the short circuiting of $\\mathrm{Li}/$ LLZO/Li electrolyte cell. However, the growth of soft, ductile Li dendrite through the hard, dense layer of the LLZO is not understood. Here, we propose an alternative mechanism on the basis of the reduction of LLZO at very large overpotentials. As a result of the cation reduction, the formation of metallic states at the interfaces of the Li-LLZO and of the LLZO grain boundaries facilitates the electronic conduction at these interfaces. The electronic conduction would facilitate the deposition of Li in the materials from the Li electrode or the Li ions in the garnet materials. In addition, the coloration of the LLZO surface from tan white to gray black was observed after LLZO was immersed in molten Li $(300~^{\\circ}\\mathrm{C})$ for $168\\mathrm{~h~}$ . 36 We believe that the coloration is related to the reduction of $\\mathrm{zr}$ and/or the dopant (Al) in LLZO. The undetected oxidation change of $\\mathrm{zr}$ in their XPS result 36 may be caused by the re-oxidation of the top-surface of the sample stored in dry room, since the surface of $\\mathrm{zr}$ is very sensitive to oxygen and will be gradually oxidized to $\\mathrm{ZrO}_{2}$ after long time exposure of air. 32 \n\nThe thermodynamic electrochemical stability windows and the decomposition phase equilibria at different voltages of other common oxide solid electrolytes were also calculated. 21 The oxide solid electrolytes generally have a wider stability window than sulfides. The stability window of oxide solid electrolyte varies significantly from one material to another. Ligarnet LLZO has the lowest cathodic limit of $0.05\\mathrm{V},$ suggesting the best resistance to reduction. The NASICON-type materials, $\\mathrm{Li}_{1.3}\\mathrm{Al}_{0.3}\\mathrm{Ti}_{1.7}(\\mathrm{PO}_{4})_{3}$ (LATP) and $\\mathrm{Li}_{1.5}\\mathrm{Al}_{0.5}\\mathrm{Ge}_{1.5}(\\mathrm{PO}_{4})_{3}$ (LAGP), have the highest reduction potential of 1.7 and $2.2~\\mathrm{V},$ respectively, and also have the highest oxidization potential of ${\\approx}4.2~\\mathrm{V}.$ We found that the anodic limit of the electrolyte is related with the oxidation of the O in the compounds. The reduction of Ge, \n\nTi, P, Zn, and Al elements contained in the solid electrolytes is generally responsible for the cathodic limit. \n\n# 3. Discussions \n\nOur first principles computation and experimental results indicate most solid electrolytes, especially sulfides, have an intrinsically narrower electrochemical stability window than the “apparent” window obtained from the linear scan of semiblocking electrode. No solid electrolyte is thermodynamically stable over the wide range from 0.0 to $5.0~\\mathrm{V}.$ Therefore, most electrolytes are not stable within the cycling voltage range of typical Li-ion battery cells based on the lithium anode and $\\mathrm{LiCoO}_{2}$ cathode. The main problem for operating the solid electrolyte beyond the limited thermodynamic stability window is the formation of new interphases due to the decomposition at the active material-electrolyte and carbon-electrolyte interfaces. The decomposition interphases, which likely have poorer Li ion conductivity than the solid electrolyte, would impede the Li transport between the solid electrolyte and the active materials and would increase the interfacial resistance. Therefore, the performance of the bulk-type solid-state battery is greatly affected, depending on the properties of the decomposition interphases, such as ionic conductivity, electronic conductivity, and electrochemical reversibility. \n\nThe most desired properties of the interphases are electrochemically irreversible, highly ionic conducting but electronic insulating. The interphase with such properties is essentially the SEI, which kinetically inhibit further decompositions of solid electrolyte and extend the electrochemical window. The formation of the SEI layer is similar to that on the graphite electrode in the commercialized lithium ion battery, which enabled the liquid electrolyte to be used beyond its stability window. 14 For example, the decomposition products of $\\mathrm{Li}_{2}\\mathrm O$ $\\mathrm{Li}_{3}\\mathrm{N}$ , and $\\mathrm{Li}_{3}\\mathrm{P}$ formed at the reduction and lithiation of LiPON serve as an excellent SEI, 15 enabling its stability with Li metal for extremely long charge/discharge cycles. 17 In addition, $\\mathrm{Li}_{3}\\mathrm{N}$ and $\\mathrm{Li}_{3}\\mathrm{P}$ are good Li ionic conductor materials, which lower the interfacial resistance. 37,38 However, it is more likely to have the interphase with lower Li ionic conductivity than the original electrolyte, causing high interfacial resistance at the interface. Even worse, the interphase would be highly detrimental if the decomposition products have sufficient electronic conductivity. In this case, the decomposition of the solid electrolyte would continue into the bulk of the solid electrolyte, eventually causing short circuiting of the battery. For example, the wellknown reduction of the LLTO is due to the high electronic conductivity of LLTO after the reduction of Ti at low potentials. 39 The formation of metals or metal alloys at reduction, which is typical for the solid electrolytes containing certain cations, such as Ge, Ti, Zn, and Al, prevents the formation of SEI layers. For such solid electrolyte materials, an artificial SEI layer is required to be inserted at the electrode/electrolyte interface to passivate the solid electrolyte and to suppress the decomposition of the solid electrolyte beyond its stability window. \n\nIn addition, it is highly undesired to have reversible or partially reversible decomposition reactions during lithiation/ delithiation, which make the electrolyte essentially an active \n\n# www.MaterialsViews.com \n\nelectrode. 39,40 The decomposition of the electrolyte at the interfaces would reduce the electrolyte content in the electrode composite, and the repeated volume changes during the cycling may lead to the poor physical contacts at the interfaces of the electrolyte. For example, the oxidation products of sulfide electrolytes at high voltages contain S, which is a well-known cathode material in Li-S batteries. The lithiation/delithiation of S at the interfaces of LGPS-cathode and LGPS-carbon interfaces generates a large volume change of up to $180\\%$ at the interface. 41 In addition, the changes of electronic and ionic conductivities in the interphase upon lithiation/delithiation would also affect the interfacial resistances and performance of the solid state batteries during cycling. The EIS test of the Li/LGPS/LGPS-C cells at different voltages (Figures S8 and S9, Supporting Information) confirmed that oxidation and reduction decomposition of LGPS will increase the interfacial resistance of the cells. \n\nTo avoid the undesirable decompositions of the solid electrolyte, one strategy is to limit the voltage of the battery to suppress the formation of detrimental decomposition products. For example, the decomposition of LLZO will be intrinsically avoided if we use Li-In alloy as an anode (0.6 V) and S as a cathode (2.3 V). In addition, Li-In anode is widely used for the sulfide solid electrolytes, because the Li-In alloying potential higher than the reduction of Ge suppresses the Li-Ge alloying and further decompositions in the sulfide solid electrolytes. However, the use of Li-In anode significantly decreases the capacity and voltage of the battery. Another strategy to extend the stability of the solid electrolyte is to apply the coating layers at the electrolyte–electrode interfaces, since the choice of the materials is very limited to simultaneously satisfy all battery criteria (e.g., voltage, capacity, and chemical compatibility). 21 For example, the artificial coating layer, such as $\\mathrm{Li}_{4}\\mathrm{Ti}_{5}\\mathrm{O}_{12}$ and ${\\mathrm{LiNb}}O_{3}$ has been applied at the interface between the sulfide solid electrolyte and cathode materials. 12,42 These coating layers are found to suppress the interfacial mutual diffusion and to reduce the interfacial resistance. In addition, the formation of $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ on the surface of LLZO after exposing to air 26,27 can be considered as a SEI, which protects the reduction of LLZO against Li. At the anode side, Polyplus has applied the coating layers to stabilize the LATP materials against Li metal anode. 43 The above examples suggest the formation and coating of the SEI-like layers is an effective strategy to extend the stability window of the solid electrolyte and to improve the performance of all-solid-state batteries. \n\nOn the basis of our new understanding, we provide specific recommendations for the engineering of sulfides and oxides solid electrolyte materials in the all-solid-state batteries. Since LGPS has a limited electrochemical stability window with a reduction potential of $1.7\\mathrm{V}$ and an oxidization potential of $2.1\\mathrm{V},$ the anode materials, such as In, with the lithiation potential higher than Li-Ge alloying is recommended for LGPS electrolyte to avoid the formation of highly electronic conductive Li-Ge alloys. The problems of the LGPS solid electrolyte at the cathode side is that the oxidation products, $\\mathrm{P}_{2}\\mathrm{S}_{5}$ S, and ${\\mathrm{GeS}}_{2}$ are neither electronic nor ionic conductive, and that the oxidation product S is electrochemically reversible if mixed with carbon. Therefore, applying an artificial SEI layer is recommended at the interface between the high voltage cathode and LGPS to provide good battery performance. LLZO has a wider electrochemical window than LGPS. In particular, LLZO holds great promises for the application with lithium metal anode, because the stability of LLZO against Li metal can be easily circumvented by kinetic protections, given the very small thermodynamic driving force for the reduction of LLZO at 0 V. Such kinetic protections should be able to sustain large current densities and high temperatures, which would facilitate the Li reduction of LLZO, during the operation of the LLZO-based batteries. At the cathode side, the stability of the LLZO may not be an issue as the oxidation products consisting electronic insulating $\\mathrm{La}_{2}\\mathrm{Zr}_{2}\\mathrm{O}_{7}$ and $\\mathrm{La}_{2}\\mathrm{O}_{3}$ can provide good passivation. However, these decomposition phases are poor ionic conductors, which give rise to high interfacial resistance. Therefore, the application of coating layers is also recommended between LLZO and the cathode to reduce interfacial resistance. The introduction of Nb oxides at cathode interfaces is recently demonstrated to effectively reduce the interfacial resistance. 42,44 \n\nIn addition to the electrochemical decomposition of the solid electrolyte itself at the interfaces with electronically conductive additives (e.g., carbon), the presence of the active material in a real all-solid-state cell may also induce the electrochemical decomposition of the solid electrolyte. Therefore, the effect of the active material on the thermodynamic electrochemical stability of solid electrolytes should also be considered. Given the conventional understanding about that the high interfacial resistance caused by the chemical incompatibility between solid electrolyte and active material during high-temperature sintering process and/or room-temperature charge/discharge processes, our work provides unprecedented insight for the understanding of the interfacial resistances in all-solid-state lithium ion batteries. \n\n# 4. Conclusion \n\nIn summary, the thermodynamic stability windows and decomposition phase equilibria of LGPS and LLZO were calculated using the first principles computation method. A Li/electrolyte/ electrolyte-carbon cell was proposed to replace current Li/electrolyte/Pt semiblocking electrode to obtain the intrinsic stability window of the solid electrolytes. The reduction and oxidation of both LGPS and LLZO are confirmed by the new CV scans and the XPS results. The results indicate that both solid electrolytes have significantly narrower electrochemical window than previously reported apparent window based on the semiblocking electrode. Therefore, the high interfacial resistances arising from the decomposition of solid electrolyte should be addressed by stabilizing the solid electrolyte. Extending the stability window of the solid electrolytes through the spontaneous formation or artificial application of SEI layers is the key to good performance of the bulk-type all-solid-state lithium ion batteries. \n\n# 5. Experimental Section \n\nSynthesis: Polycrystalline $\\mathsf{L i}_{10}\\mathsf{G e P}_{2}\\mathsf{S}_{12}$ powder was prepared with the same method reported elsewhere. 2 A Ta-doped cubic garnet compound with the composition of $\\mathsf{L i}_{6.75}\\mathsf{L a}_{3}\\mathsf{Z r}_{1.75}\\mathsf{T a}_{0.25}\\mathsf{O}_{12}$ was prepared through solid state reaction. Starting materials of $L i O H\\cdot H_{2}O$ $99.995\\%$ , Sigma \n\n# www.MaterialsViews.com \n\nAldrich), $L a(O H)_{3}$ $(99.9\\%$ , Sigma Aldrich), $Z\\mathsf{r O}_{2}$ $(99.99\\%$ , Sigma Aldrich), $\\mathsf{T a}_{2}\\mathsf{O}_{5}$ $(99.99\\%$ , Sigma Aldrich), were weighed and mixed based on the stoichiometric ratio. $10\\%$ excess $\\mathsf{L i O H}.\\mathsf{H}_{2}\\mathsf{O}$ was used to compensate the Li loss during high-temperature calcinations and sintering. The mixture was ball-milled (PM 100, Retsch) in 2-propanol for $24\\mathrm{~h~}$ with zirconia balls in a zirconia vial, and then dried, heated in air at $950^{\\circ}\\mathsf C$ for $\\mathsf{12h}$ . The ball-milling and heating were repeated once to enhance purity. The collected powder samples were pressed into pellets under isostatic pressure $(720\\ M\\mathsf{P a})$ . The pellet was fully covered with powder with the same composition and sintered in air at $1230^{\\circ}\\mathsf C$ for $\\mathsf{l}2\\mathsf{h}$ in a ${\\mathsf{M g O}}$ crucible. The residual powder samples were transferred to the Ar-filled glovebox to protect its slow reaction with the ${\\sf H}_{2}{\\sf O}/{\\sf C}{\\sf O}_{2}$ in air. For the preparation of the carbon-coated LLZO particles, the as-prepared LLZO powder was ground using a high-energy vibrating mill (SPEX SamplePrep\\* 8000M Mixer/Mill) for $\\texttt{l h}$ (to reduce its particle size), dispersed into a solution of polyvinylpyrrlidone ( $70\\mathrm{\\ut\\%}$ in ethanol), and then vigorously stirred for $30~\\mathrm{min}$ . The product was then dried and sintered at $700^{\\circ}\\mathsf C$ for $\\rceil\\mathfrak{h}$ in argon flow to enable carbon coating. \n\nCharacterization: Powder X-ray diffraction patterns were obtained with a D8 Advance with LynxEye and SolX (Bruker AXS, WI, USA) using $\\mathsf{C u}$ $\\mathsf{K}\\alpha$ radiation. The morphologies of the sample were examined using a Hitachi a SU-70 field-emission scanning electron microscope and JEOL 2100F field emission transmission electron microscope (TEM). The surface chemistry of the samples was examined by X-ray photoelectron spectroscopy (XPS) using a Kratos Axis 165 spectrometer. To prepare the sample for XPS test, LLZO electrodes were charged or discharged to a certain voltage in a liquid electrolyte using a Swagelok cell, and held at that voltage for $24\\mathrm{~h~}$ . The electrodes were then taken out from the cell, and rinsed by dimethyl carbonate (DMC) inside the glove box for three times. All samples were dried under vacuum overnight, placed in a sealed bag, and then transferred into the XPS chamber under inert conditions in a nitrogen-filled glove bag. $\\mathsf{A r}^{+}$ sputtering was performed for $2\\ h$ ( $0.5\\mathrm{~h~}$ per step) until the carbon and/or SEI layer on the surface of the LLZO electrodes are removed. XPS data were collected using a monochromated Al $\\mathsf{K}\\alpha$ X-ray source $(7486.7\\ \\mathrm{eV})$ . The working pressure of the chamber was lower than $6.6\\times10^{-9}$ Pa. All reported binding energy values are calibrated to the C 1s peak at $284.8\\ \\mathrm{eV}.$ \n\nElectrochemistry: $\\boldsymbol{120}\\:\\mathrm{~mg}$ LGPS powder was pressed into a pellet (diameter $13m m$ ; thickness $2\\mathsf{m m}$ ) under isostatic pressure $(\\mathsf{l}20\\mathsf{M P a})$ in an Ar atmosphere. It was then sputtered with Pt on one side and attached with Li metal on the other side to make the Li/LGPS/Pt cell. To make the Li/LGPS/LGPS-C cell, $10\\mathrm{\\mg\\LGPS{\\cdot}C}$ powder (LGPS: graphite is 75:25 in weight) was put on the top of 120 LGPS powder and then cold-pressed together under $360~\\mathsf{M P a}$ , while Li metal was attached on the other side of LGPS pellet. The cyclic voltammograms of the Li/ LGPS/Pt and Li/LGPS/LGPS-C cells were measured with a scan rate of $0.7\\ m\\vee s^{-1}$ . The LLZO electrodes were prepared by mixing the carboncoated LLZO and carbon black (weight ratio of carbon-coated LLZO to carbon is 40:60) by hand-grinding in the mortar, and mixing with $10\\mathrm{~wt\\%~}$ polyvinylidene fluoride (PVDF) and n-methylpyrrolidinone (NMP) to make the electrode slurry. The electrodes were prepared by casting the electrode slurry onto copper or aluminum foils and dried at $120^{\\circ}\\mathsf C$ overnight. The loading of the active material on each electrode is about $\\textsf{l m g}$ . The charge/discharge tests of the LLZO electrodes were carried out in Swagelok cells using Li metal as the counter electrode and 1M $\\mathsf{L i P F}_{6}$ in a mixed solvent of FEC, HFE, and FEMC (volume ratio is 2:6:2) as the liquid electrolyte. To make the Li/LLZO/LLZO-C cell for the electrochemical stability window test, the LLZO electrode slurry was coated on the top surface of LLZO pellet, dried at ${\\mathsf{120}}\\ {\\mathsf{^{o}C}}$ overnight, and then sputtered with Pt to improve the electrical contact. After that, Li metal was attached on the other side of the pellet and cured at $200^{\\circ}\\mathsf{C}$ to enhance the interfacial contact between Li and LLZO. The cyclic voltammogram of the Li/LLZO/LLZO-C cell was tested with a scan rate of $0.01\\ m\\vee\\mathsf{s}^{-1}$ . The charge/discharge behavior was tested using an Arbin BT2000 workstation at room temperature. The cyclic voltammetry measurements were carried on an electrochemistry workstation (Solartron 1287/1260). \n\nFirst Principles Computation Methods: All density functional theory (DFT) calculations in the work were performed using the Vienna Ab initio Simulation Package (VASP) within the projector augmented-wave approach, and the Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA) functional was used. The DFT parameters were consistent with the parameters used in Materials Project (MP). 45 The crystal structures of LGPS and LLZO were obtained from the ICSD database and ordered using pymatgen if the material has disordering sites. The electrochemical stability of the solid electrolyte materials was studied using the grand potential phase diagrams constructed using pymatgen, 46 which identify the phase equilibria of the material in equilibrium with an opening Li reservoir of Li chemical potential $\\mu_{\\mathrm{Li}}$ . As in the previous studies, 16,47 the applied potential $\\phi$ was considered in the Li chemical potential $\\mu_{\\mathrm{Li}}$ as \n\n$$\n\\mu_{\\mathrm{Li}}(\\phi)=\\mu_{\\mathrm{Li}}^{0}-e\\phi\n$$ \n\nwhere $\\mu_{\\mathrm{Li}}^{0}$ is the chemical potential of Li metal, and the potential $\\phi$ is referenced to Li metal. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nF.H. and Y.Z. contributed equally to this work. The authors thank Dr. Karen J. Gaskell at the Surface Analysis Center of University of Maryland for the help on the XPS data analysis. The authors thank Dr. Kang Xu at the U.S. Army Research Laboratory for providing the high-voltage liquid electrolyte. C.W. and F.H. thank the support from National Science Foundation under Award No. 1235719 and Army Research Office (Program Manager: Dr. Robert Mantz), under Award No. W911NF1510187. Y.M. and Y.Z. thank the support from U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, under Award No. DE-EE0006860, and the computational facilities from the University of Maryland supercomputing resources and from the Extreme Science and Engineering Discovery Environment (XSEDE) supported by National Science Foundation Award No. TG-DMR130142. \n\nReceived: August 9, 2015 \nRevised: December 21, 2015 \nPublished online: January 21, 2016 \n\n[10] A. Aboulaich, R. Bouchet, G. Delaizir, V. Seznec, L. Tortet, M. Morcrette, P. Rozier, J. M. Tarascon, V. Viallet, M. Dolle, Adv. Energy Mater. 2011, 1, 179. \n[11] S. Ohta, S. Komagata, J. Seki, T. Saeki, S. Morishita, T. Asaoka, J. Power Sources 2013, 238, 53. \n[12] N. Ohta, K. Takada, L. Q. Zhang, R. Z. Ma, M. Osada, T. Sasaki, Adv. Mater. 2006, 18, 2226. \n[13] R. B. Cervera, N. Suzuki, T. Ohnishi, M. Osada, K. Mitsuishi, T. Kambara, K. Takada, Energy Environ. Sci. 2014, 7, 662. \n[14] J. B. Goodenough, Y. Kim, Chem. Mater. 2009, 22, 587. \n[15] A. Schwöbel, R. Hausbrand, W. Jaegermann, Solid State Ionics 2015, 273, 51. \n[16] Y. Mo, S. P. Ong, G. Ceder, Chem. Mater. 2012, 24, 15. \n[17] J. B. Bates, N. J. Dudney, B. Neudecker, A. Ueda, C. D. Evans, Solid State Ionics 2000, 135, 33. \n[18] M. Tatsumisago, F. Mizuno, A. Hayashi, J. Power Sources 2006, 159, 193. \n[19] M. Tatsumisago, A. Hayashi, Solid State Ionics 2012, 225, 342. \n[20] B. R. Shin, Y. J. Nam, D. Y. Oh, D. H. Kim, J. W. Kim, Y. S. Jung, Electrochim. Acta 2014, 146, 395. \n[21] Y. Zhu, X. He, Y. Mo, ACS Appl. Mater. Interfaces 2015, 7, 23685. \n[22] E. Rangasamy, Z. Liu, M. Gobet, K. Pilar, G. Sahu, W. Zhou, H. Wu, S. Greenbaum, C. Liang, J. Am. Chem. Soc. 2015, 137, 1384. \n[23] S. Ujiie, A. Hayashi, M. Tatsumisago, Solid State Ionics 2012, 211, 42. \n[24] H. M. Chen, C. Maohua, S. Adams, Phys. Chem. Chem. Phys. 2015, 17, 16494. \n[25] V. Thangadurai, D. Pinzaru, S. Narayanan, A. K. Baral, J. Phys. Chem. Lett. 2015, 6, 292. \n[26] L. Cheng, E. J. Crumlin, W. Chen, R. Qiao, H. Hou, S. Franz Lux, V. Zorba, R. Russo, R. Kostecki, Z. Liu, K. Persson, W. Yang, J. Cabana, T. Richardson, G. Chen, M. Doeff, Phys. Chem. Chem. Phys. 2014, 16, 18294. \n[27] Y. Wang, W. Lai, J. Power Sources 2015, 275, 612. \n[28] M. Kotobuki, H. Munakata, K. Kanamura, Y. Sato, T. Yoshida, J. Electrochem. Soc. 2010, 157, A1076. \n[29] Y. Wang, A. Huq, W. Lai, Solid State Ionics 2014, 255, 39. \n[30] S. Toda, K. Ishiguro, Y. Shimonishi, A. Hirano, Y. Takeda, O. Yamamoto, N. Imanishi, Solid State Ionics 2013, 233, 102. \n[31] F. Tietz, T. Wegener, M. T. Gerhards, M. Giarola, G. Mariotto, Solid State Ionics 2013, 230, 77. \n[32] I. Bespalov, M. Datler, S. Buhr, W. Drachsel, G. Rupprechter, Y. Suchorski, Ultramicroscopy 2015, 159, 147. \n[33] K. Ishiguro, Y. Nakata, M. Matsui, I. Uechi, Y. Takeda, O. Yamamoto, N. Imanishi, J. Electrochem. Soc. 2013, 160, A1690. \n[34] R. Sudo, Y. Nakata, K. Ishiguro, M. Matsui, A. Hirano, Y. Takeda, O. Yamamoto, N. Imanishi, Solid State Ionics 2014, 262, 151. \n[35] L. Cheng, W. Chen, M. Kunz, K. Persson, N. Tamura, G. Chen, M. Doeff, ACS Appl. Mater. Interfaces 2015, 7, 2073. \n[36] J. Wolfenstine, J. L. Allen, J. Read, J. Sakamoto, J. Mater. Sci. 2013, 48, 5846. \n[37] U. v. Alpen, A. Rabenau, G. H. Talat, Appl. Phys. Lett. 1977, 30, 621. \n[38] G. Nazri, Solid State Ionics 1989, 34, 97. \n[39] S. Wenzel, T. Leichtweiss, D. Krüger, J. Sann, J. Janek, Solid State Ionics 2015, 278, 98. \n[40] P. Hartmann, T. Leichtweiss, M. R. Busche, M. Schneider, M. Reich, J. Sann, P. Adelhelm, J. Janek, J. Phys. Chem. C 2013, 117, 21064. \n[41] Y. Yang, G. Zheng, Y. Cui, Chem. Soc. Rev. 2013, 42, 3018. \n[42] N. Ohta, K. Takada, I. Sakaguchi, L. Zhang, R. Ma, K. Fukuda, M. Osada, T. Sasaki, Electrochem. Commun. 2007, 9, 1486. \n[43] S. Visco, Y. Nimon, B. Katz, L. De Jonghe, N. Goncharenko, V. Loginova, WO Patent 2,013,074,772, 2013. \n[44] T. Kato, T. Hamanaka, K. Yamamoto, T. Hirayama, F. Sagane, M. Motoyama, Y. Iriyama, J. Power Sources 2014, 260, 292. \n[45] A. Jain, G. Hautier, C. J. Moore, S. Ping Ong, C. C. Fischer, T. Mueller, K. A. Persson, G. Ceder, Comput. Mater. Sci. 2011, 50, 2295. \n[46] S. P. Ong, L. Wang, B. Kang, G. Ceder, Chem. Mater. 2008, 20, 1798. \n[47] S. P. Ong, Y. Mo, W. D. Richards, L. Miara, H. S. Lee, G. Ceder, Energy Environ. Sci. 2013, 6, 148. " + }, + { + "id": "10.1021_acsnullo.6b00181", + "DOI": "10.1021/acsnullo.6b00181", + "DOI Link": "http://dx.doi.org/10.1021/acsnullo.6b00181", + "Relative Dir Path": "mds/10.1021_acsnullo.6b00181", + "Article Title": "Antibacterial Activity of Ti3C2Tx MXene", + "Authors": "Rasool, K; Helal, M; Ali, A; Ren, CE; Gogotsi, Y; Mahmoud, KA", + "Source Title": "ACS nullO", + "Abstract": "MXenes are a family of atomically thin, two-dimensional (2D) transition metal carbides and carbonitrides with many attractive properties. Two-dimensional Ti3C2TX (MXene) has been recently explored for applications in water desalination/purification membranes. A. major success indicator for any water treatment membrane is the resistance to biofouling. To validate this and to understand better the health and environmental impacts of the new 2D carbides, we investigated the antibacterial properties of single- and few-Iayer Ti3C2TX MXene flakes in colloidal solution. The antibacterial properties of Ti3C2TX were tested against Escherichia coli (E.,coli) and Bacillus subtilis (B. subtilis) by using bacterial growth curves based on optical densities (OD) and colonies growth on agar nutritive plates. Ti3C2T shows a higher antibacterial efficiency toward both Gram-negative E. coli and Gram-positive. B. subtilis compared with graphene oxide (GO), which has been widely reported as an antibacterial agent. Concentration dependent antibacterial activity was observed and more than 98% bacterial cell viability loss was found at 200 jzg/mL Ti3C2TX for both bacterial cells within 4 h of exposure, as confirmed by colony forming unit (CFU) and regrowth curve. Antibacterial mechanism investigation by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) coupled with lactate dehydrogenase (LDH) release assay indicated the damage to the cell membrane, which resulted in release of cytoplasmic materials from the bacterial cells. Reactive oxygen species (ROS) dependent and independent stress induction by Ti3C2TX was investigated in two separate abiotic assays. MXenes are expected to be resistant to biofouling and offer bactericidal properties.", + "Times Cited, WoS Core": 1013, + "Times Cited, All Databases": 1055, + "Publication Year": 2016, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000372855400072", + "Markdown": "# ACSNANO \n\n# Antibacterial Activity of T $\\mathsf{i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ MXene \n\nKashif Rasool,† Mohamed Helal,† Adnan Ali,† Chang E. Ren,‡ Yury Gogotsi,\\*,‡ and Khaled A. Mahmoud\\*,† \n\n†Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University (HBKU), P.O. Box 5825, Doha, Qatar ‡Department of Materials Science and Engineering and A.J. Drexel Nanomaterials Institute, Drexel University, Philadelphia, Pennsylvania 19104, United States \n\nSupporting Information \n\nABSTRACT: MXenes are a family of atomically thin, twodimensional (2D) transition metal carbides and carbonitrides with many attractive properties. Two-dimensional $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ (MXene) has been recently explored for applications in water desalination/purification membranes. A major success indicator for any water treatment membrane is the resistance to biofouling. To validate this and to understand better the health and environmental impacts of the new 2D carbides, we investigated the antibacterial properties of single- and few-layer $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ MXene flakes in colloidal solution. The antibacterial properties of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ were tested against Escherichia coli $\\left(\\boldsymbol{E}.\\ c o l i\\right)$ and Bacillus subtilis (B. subtilis) by using bacterial growth curves based on optical densities (OD) and colonies growth on agar nutritive plates. $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ shows a higher antibacterial efficiency toward both Gram-negative $E$ . coli and Gram-positive B. subtilis compared with graphene oxide (GO), which has been widely reported as an antibacterial agent. Concentration dependent antibacterial activity was observed and more than $98\\%$ bacterial cell viability loss was found at ${\\bf200~}\\mu\\mathbf{g}/\\mathbf{m}\\mathbf{L}$ $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ for both bacterial cells within $^\\textrm{\\scriptsize4h}$ of exposure, as confirmed by colony forming unit (CFU) and regrowth curve. Antibacterial mechanism investigation by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) coupled with lactate dehydrogenase (LDH) release assay indicated the damage to the cell membrane, which resulted in release of cytoplasmic materials from the bacterial cells. Reactive oxygen species (ROS) dependent and independent stress induction by $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ was investigated in two separate abiotic assays. MXenes are expected to be resistant to biofouling and offer bactericidal properties. \n\n![](images/b4a8f9b93f62f41a6a0ef11de05632142da462fc4c11e5e8e4708236c504cb63.jpg) \nLiveB.Subtilis Dead B. Subtilis \n\nKEYWORDS: MXene, $T_{{i_{3}}}C_{2}T_{{s}{}},$ antibacterial, B. subtilis, E. coli, membrane, oxidative stress \n\nR ebTcyheians yan,regtweh fraomuiliply ofof 2rDlDymtramtaaentrseiiartlisaolnsh shmabest lbnecaeaurnb lmdaebsne.t1le−d6 “MXenes”, where $\\mathbf{M}$ is an early transition metal and X is carbon and/or nitrogen. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ (T is standing for the surface termination, such as $-\\mathrm{O}_{\\mathrm{i}}$ , $-\\mathrm{OH}$ , or $\\mathrm{-F},$ ) is the most studied MXene, and recently, we reported the selective ion sieving through micrometer-thick $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ membranes.7 The hydrophilic nature of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ together with the hydrated interlayer spacing, promotes ultrafast water flux and differential sieving toward single-, double-, and triple-charged metal cations of different sizes. ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ outperformed graphene oxide (GO) membranes in the separation of higher charge cations. However, antibacterial characteristics of MXenes have never been studied. It is important to investigate the antibacterial properties of MXenes for their potential use as a biocide in water treatment and biomedical applications. \n\nSeveral studies have compared the antibacterial activity of 2D graphene-based materials (graphite oxide, ${\\mathrm{GO}},$ and reduced GO (rGO)) against Gram-negative $\\left(\\mathrm{Gram~}\\left(-\\right)\\right)$ and Grampositive (Gram $\\displaystyle{\\bigl(+\\bigr)^{j}}$ ) bacteria through direct contact.8−14 The antibacterial activity of metal and metal oxide nanoparticles (e.g., $\\mathrm{Ag,ZnO_{\\it3}}$ , and $\\mathrm{TiO}_{2}$ ) have also been well documented by a sizable number of studies.15,16 Antibacterial activity of these nanoparticles has been associated with production of reactive oxygen species (ROS) and direct contact with bacteria membrane, penetrating into the bacteria and interacting with sulfur-containing proteins as well as phosphorus-containing DNA, leading to bacterial cell death.17−21 Similarly, the antimicrobial activities of graphene have been found to be the synergy of both “chemical” and “physical” effects.14,19 Most of the studies have attributed the antibacterial activity of GO and rGO to oxidative and physical stress induced by sharp edges of graphene nanosheets, which may result in mechanical damage of cell membranes, leading to a loss of their integrity.14,22−24 Moreover, several mechanisms have been proposed to explain the antimicrobial properties of composite films based on carbon nanotubes (CNT) including inhibition of electron transports, leakage and penetration of cell membrane and generation of ROS.25−29 Despite antimicrobial properties of MXenes have never been examined before, it is reasonable to assume that at least some of those mechanisms may work in MXenes, which were shown to destroy dye molecules in solution.9 Therefore, investigations of the mechanism of MXene’s interaction with bacterial cell membranes and its bactericidal activity are needed to determine the range of potential applications of these new materials.30,31 \n\n![](images/07a091501bfb617c66415c3845700310e5ae3706ac48674c1577c7d1df14d68c.jpg) \nFigure 1. SEM images of $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (A) and $\\mathbf{ML-Ti_{3}C_{2}T}_{x}$ (B) and $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ nanosheets on an alumina filter (C), and their corresponding photographs showing $\\mathrm{\\bfTi}_{3}\\mathrm{\\bfAlC}_{2},$ $\\mathbf{ML-Ti_{3}C_{2}T}_{x},$ and $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ solution, respectively. (D) TEM image of the pristine $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ flake. (E) Typical XRD pattern of air-dried $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ film. \n\nHere, we present for the first time a report on the antibacterial behavior of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene in the colloidal suspension. To better understand the health and environmental impacts of the new 2D carbides, the antibacterial activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene toward two bacterial models, Escherichia coli (E. coli) and Bacillus subtilis (B. subtilis), was studied and compared with GO. The concentration dependent antibacterial activities were evaluated by cell viability assays together with scanning electron microscopy (SEM), transmission electron microscopy (TEM), and lactate dehydrogenase (LDH) release assay. On the basis of these results, we introduce MXenes as a new family of 2D antimicrobial nanomaterials. This will open a door for MXenes in the antibacterial applications and water purification industry. \n\n# RESULTS AND DISCUSSION \n\nSynthesis and Characterization of $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\bar{\\mathsf{T}}_{x}.$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ suspension was prepared from multilayer (ML) $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\vphantom{\\mathrm{T}}x}$ “clay” by ultrasonication under a flow of argon $\\left(\\operatorname{Ar}\\right)$ gas as described in the experimental section. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ synthesis was described in details elsewhere.32 GO was also synthesized by oxidizing natural graphite powders using $\\mathrm{H}_{2}S\\mathrm{O}_{4}$ and $\\mathrm{KMnO}_{4}$ according to the modified Hummers method and was used as a reference in this study.33 Figure 1 shows SEM images of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (Figure 1A), $\\mathbf{ML}–\\mathrm{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ (Figure 1B), and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (Figure 1C) nanosheets dried on alumina wafer and photographs of their corresponding colloidal suspensions in water. The images clearly show the different appearance of the three materials after 10 min sonication. Both $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and asproduced M $\\mathrm{L}{\\mathrm{-}}\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ show opaque gray color and their particles precipitated after $^\\mathrm{~1~h~}$ and the SEM revealed well stacked nanosheets. On the other hand, delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ formed dark green colloidal solution and the stacked layers were delaminated as observed from SEM (Figure 1C). The TEM micrograph in (Figure 1D) revealed thin, transparent flakes of delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets. Fluorine and oxygen were confirmed by energy-dispersive spectroscopy (EDS), suggesting $0\\cdot$ and F-containing surface terminations. Delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ has highly exfoliated and smaller sheets, which are expected to provide a significantly higher surface area than $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and ML $-\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and an improved antimicrobial performance.4,24 A typical XRD pattern of air-dried $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film is shown in Figure 1E. The presence of peaks corresponding to basal-plane reflections (00l) with $\\mathbf{\\Psi}_{c}$ lattice parameter of $27-28\\mathrm{~\\AA~}$ suggests the presence of water, and possibly Li ions, between the hydrophilic and negatively charged $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ MXene nanosheets.32 The sharp and intense peak (002) at $6.4^{\\circ}$ is at a much lower angle that typical of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ produced by etching in HF, having layers of water or solvated ions between MXene sheets. Peaks from 20 to $40^{\\circ}$ are still observed, which suggests a good periodicity between the stacked MXene layers. \n\nAntibacterial Activity. In order to investigate the effect of delamination on the antibacterial efficiency of MXene, the inhibition effect of three materials $(\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (MAX), asproduced ML-MXene, and delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathfrak{x}}$ nanosheets) were examined against both E. coli and B. subtilis. The bacterial growth inhibition was determined by the colony counting method. Figure S1A (Supporting Information) shows the photographs of agar plates onto which control and bacterial cells were recultivated after treatment for $^\\textrm{\\scriptsize4h}$ with the same concentration of $100\\:\\:\\mu\\mathrm{g/mL}$ of nanomaterial. Figure S1B (Supporting Information) depicts the percentage growth inhibition of both bacterial strains exposed to the materials under study. MAX dispersion showed growth inhibition of only $14.39\\pm1.43\\%$ and $18.34\\pm1.59\\%$ for $E.$ . coli and B. subtilis, respectively. The ML- ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ dispersion showed a little higher antibacterial activity compared with MAX with $E.$ coli and B. subtilis growth inhibition of $30.55\\pm2.56\\%$ and $33.60\\pm2.89\\%_{;}$ , respectively. Whereas for the cells exposed to the colloidal solution of delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene, the loss of $E.$ coli and B. subtilis cells viability increases to $97.70\\pm2.87\\%$ and $97.04\\pm$ $2.91\\%$ , respectively, exhibiting much stronger inhibition. The three materials showed significant differences in their antibacterial activities against both bacterial strains. In particular, delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene has a much more pronounced antibacterial activity compared with those of MAX and ML- $\\mathrm{\\cdotTi}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ MXene and was used for further studies. \n\nConcentration Dependent Antibacterial Activity of $\\bar{\\Pi}_{3}\\mathsf{C}_{2}\\bar{\\Pi}_{x}.$ The antibacterial activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ against Gram $\\left(+\\right)$ B. subtilis and Gram $\\left(-\\right)E.$ . coli was evaluated by measuring the growth curve and the cell viability after exposure of the bacteria to increasing concentrations of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ colloidal solutions. The optical density (OD) was monitored spectrophotometrically at $600\\ \\mathrm{nm}$ for pristine bacteria and bacteria treated with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ over different time intervals from lag phase (when individual bacteria are adjusting to the environment) to stationary phase (when their growth and death rates are equivalent). Bacteria (at $10^{7}$ colony forming units $\\mathrm{(CFU)/mL}$ ) were treated with different concentrations of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ for $^{4\\mathrm{h},}$ recultivated on agar plates, and evaluated by using the bacteria counting method. Figure 2 shows the typical photographs of $E_{\\rightleftarrows}$ coli or B. subtilis bacteria colonies after treatment with various concentrations of bacteria. As can be seen from both panels, the number of colonies significantly decreases with increasing concentration of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}.$ . The obtained results indicate the dose-dependent antimicrobial activity of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}.$ \n\nFigure 3 shows the bacterial cells viability exposed to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and GO concentrations in the range of $2{-}200\\ \\mu\\mathrm{g/mL}$ for $^\\textrm{\\scriptsize4h}$ . $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ showed excellent antimicrobial activity for both Gram $\\left(+\\right)$ and Gram $(-)$ bacteria. The bacterial cell loss gradually ascended with the increasing concentration of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{{\\boldsymbol{x}}}.$ E. coli and B. subtilis showed $92.53\\%$ and $93.96\\%$ survival rate, respectively, at the lowest $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ concentration of $2~\\mu\\mathrm{g/mL}$ . By increasing the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene concentration from 2 $:\\mu\\mathrm{g/mL}$ to $20~\\mu\\mathrm{g/mL},$ , the survival rate of $E$ . coli and B. subtilis was decreased to $35.31\\%$ and $28.21\\%$ , respectively. More than $96\\%$ bacterial viability loss for both bacterial strains was observed at $100\\:\\mu\\mathrm{g/mL}$ of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ and bacterial inhibition was increased to more than $99\\%$ at $200~\\mu\\mathrm{g/mL}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ (Figure 3). Additionally, the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ dispersions revealed a stronger influence on B. subtilis than E. coli at lower concentrations. \n\n![](images/a613011091f2210ff07a470a20ab06b0234a51296c780e50242651f74fcb152b.jpg) \nFigure 2. Concentration dependent antibacterial activities of the $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ in aqueous suspensions: Photographs of agar plates onto which E. coli (top panel) and $B.$ subtilis (bottom panel) bacterial cells were recultivated after treatment for $\\mathbf{4h}$ with ${\\bf0}\\mu{\\bf g}/{\\bf m L}$ (A), 10 ${\\mu}\\mathbf{g}/\\mathbf{m}\\mathbf{L}$ (B), ${\\bf20~}\\mu\\bf{g/m L}$ (C), $\\mathbf{50~}\\mu\\mathbf{g}/\\mathbf{mL}$ $\\mathbf{\\tau}(\\mathbf{D})$ , $\\mathbf{100}~\\mu\\mathbf{g}/\\mathrm{mL}$ (E), and ${\\bf200~}\\mu\\mathbf{g}/\\mathbf{mL}$ (D) of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x},$ respectively. Bacterial suspensions in deionized water without $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ MXene material were used as control. \n\nThe obtained results are in agreement with previously reported data, where several nanomaterials showed a higher antibacterial activity against Gram $\\left(+\\right)$ bacterial strains than Gram $(-)$ bacteria and differences of the cell wall structure of two bacterial strains were reported as a possible reason for different sensitivities.9,34 Gram $(-)$ E. coli cells have negatively charged cellular membranes, as a function of the isoelectric point $\\mathrm{\\left(pI\\right)}=4{-}5$ . For the Gram $\\left(+\\right)$ B. subtilis cells, the pI value of the membranes can reach 7, which produces a more negatively charged surface in culture medium.35,36 Therefore, the higher negative charges of $E$ . coli cells at $\\mathrm{pH}7$ could explain their higher resistance against the direct exposure to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ substrate than B. subtilis cells in aqueous suspensions at $\\mathrm{pH}7$ . This could be attributed to the observed difference in the antimicrobial activity against Gram $(-)$ E. coli and ${\\mathrm{Gram~}}(+)\\ B.$ subtilis. Recently, graphene-based materials were reported to show unique antibacterial properties and have become one of the most popular research subjects.10,37,38 Moreover, E. coli, as Gram $(-\\bar{)}$ bacteria, are covered by a much thinner layer of peptidoglycan (thickness of $7{-}8~\\mathrm{nm}$ ) but have an external protective lipid membrane,39 whereas Gram $\\left(+\\right)$ B. subtilis lacks the external lipid membrane, but its thicker peptidoglycan cell walls are in the range of $20{-}80~\\mathrm{nm}$ . It was reported that the cell membrane of Gram $\\left(+\\right)$ bacteria lacking the outer membrane were more easily damaged by direct contact with graphene nanowalls, as compared to the Gram $\\left(-\\right)E.$ . coli with the outer membrane.10,39 The hydrophilic $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ could effectively attach to bacteria, facilitating their inactivation by direct contact interaction. \n\n![](images/485f63eb98fd7224d31df71e14129c276f5efbf8bf809e54c125ee2d792d5a70.jpg) \nFigure 3. Cell viability measurements of (A) E. coli and (B) B. subtilis treated with $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ and graphene oxide (GO) in aqueous suspension. Bacterial suspensions $\\mathbf{(10^{7}~C F U/m L)}$ were incubated with different $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ and GO concentrations $\\left(0-200\\mu\\mathrm{g/mL}\\right)$ at $35~^{\\circ}\\mathbf{C}$ for ${\\bf4}{\\bf h}$ at 150 rpm shaking speed. Survival rates were obtained by the colony forming count method. Gentamicin at concentration of $\\scriptstyle50\\mu_{\\mathrm{{g}}}/\\mathrm{{mL}}$ was used as positive control. Error bars represent the standard deviation. \n\n![](images/5fbca0396d5108bb040f86cd1fedd034ab2abb836bb7226d5b8ed4f29fc454c4.jpg) \nFigure 4. Bacterial suspensions exposed to different $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ concentrations at $35~^{\\circ}\\mathbf{C}$ for ${\\bf4}{\\bf h}$ and the reaction mixture then transferred to 15 mL tubes, each containing $\\mathbf{10\\mL}$ of LB medium. The tubes were inoculated on a shaking incubator at $\\bf{150~r p m}$ and $35^{\\circ}\\mathbf{C}$ and at bacterial cell density measured at specific time intervals. OD regrowth curves of (A) E. coli and (B) B. subtilis in LB broth at $35~^{\\circ}\\mathbf{C}$ after the cells were treated with different concentrations of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x},$ in DI water for $\\textbf{4h}$ . Controls were cells untreated with $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}.$ \n\nIn order to compare antibacterial activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ with GO, both bacterial strains were treated with different concentrations of GO under the same experimental conditions. Figure 3 shows the viability of both E. coli and B. subtilis bacteria in control, which was taken as $100\\%$ and exposed to $0{-}200~\\mu\\mathrm{g/mL}$ of GO. For both bacterial strains, there were substantial differences in bacteria colonies on agar plates, indicating that the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene has a higher antibacterial activity as compared to GO in our experimental setup. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ showed more than $98\\%$ cell inactivation to both bacterial strains at $200~\\mu\\mathrm{g/mL}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ whereas GO induces about $90\\%$ inactivation at the same concentration (Figure 3). \n\nTo further evaluate the bactericidal properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene, the antibacterial activity is reported in terms of log reduction. The plate count experiments showed $\\log2.43$ and log 2.21 reductions of viable E. coli and B. subtilis bacteria, respectively, as compared to the initial concentration of bacteria $(1\\bar{0}^{7}\\:\\mathrm{\\CFU/mL})$ (Figure S2, Supporting Information). GO suspensions showed a log reduction of 1.02 and 0.97 for E. coli and B. subtilis, respectively, being less effective than $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}.$ \n\nTo evaluate the antibacterial activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ MXene in growth media, both bacterial strains were exposed to $200~\\mu\\mathrm{g}/\\$ mL of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ in LB media for $^\\textrm{\\scriptsize4h}$ . Figure S3 (Supporting Information) depicts the growth of bacterial cells in LB media in the presence of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ . Figure S3A shows a significant decrease in log of bacterial growth when exposed to ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ The viable cells count in growth media were $33.32\\%$ and $27.34\\%$ for $E_{\\rightleftarrows}$ . coli and B. subtilis, respectively, in the presence of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ as compared to that of control (see Figure S3B). \n\nThe effect of contact time on bactericidal activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\vphantom{\\mathrm{T}}x}$ $\\left(200\\ \\mu\\mathrm{g/mL}\\right)$ was further examined during the $^{4\\mathrm{~h~}}$ incubation period. Figure S4 (Supporting Information) shows the kinetics of antibacterial activity in terms of cell viability and log reduction. The antibacterial activity increased with increasing contact time and cell viability decreased to $50\\%$ within $^{2\\mathrm{~h~}}$ of contact time and more than $98\\%$ cells viability loss was observed after $^{4\\mathrm{h}}$ . This relatively short contact time might also be advantageous for the application of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ as antibacterial agent. \n\nTable 1. Specific Growth Constant and Doubling Time Obtained in the Batch Growth Tests for E. coli and B. subtilis Cells Treated with Different $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ Concentrations \n\n\n
TiCTx (μg/mL)
substrateconstant021020 50100200
E.coliμe (h-1)0.2770.2710.2610.2390.1680.0870.068
B. subtilisTa (h)2.52.5502.652.94.127.9210.11
μb (h-1)0.3470.3190.3060.2640.2400.1900.134
Ta (h)2.02.2512.2592.6172.8783.6295.16
\n\n![](images/d8a551d710d6d1584fe945671d52e00ce4b03e284faf6bc6ca75eb39b354e7f6.jpg) \nFigure 5. SEM images of the E. coli (top panel) and B. subtilis (bottom panel) treated with ${\\bf0}\\mu_{\\mathrm{g}}/\\mathrm{mL}$ [control] (A), ${\\bf50}\\mu\\mathrm{g/mL}$ (B), and $\\bf{100}\\mu\\ g/$ mL (C) of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x},$ at low and high magnification, respectively. Control bacterial cells were viable with no observed membrane damage or cell death and the higher magnification shows that the bacterium is protected by intact cytoplasmic membrane (panel A). At 50 and $\\mathbf{100}\\mu\\mathbf{g}/\\mathbf{mL}$ of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x},$ both bacteria suffered from prevalent cell lysis indicated by a severe membrane disruption and cytoplasm leakage (see the red circles at high magnification in panel C). \n\nThe antimicrobial activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets was further confirmed by bacterial regrowth curves using a second assay. Figure 4 shows the OD growth curves of $E_{\\rightleftarrows}$ coli and B. subtilis cells incubated with different concentrations of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{{\\boldsymbol{x}}}.$ It was found that inhibition of both bacterial strains growth was dose dependent and the bactericidal activity increased with increasing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ concentration, which was in line with the number of colonies grown on the LB plates. Growth kinetics constants for both bacterial strains were evaluated and are given in Table 1. It was found that the specific growth constant for $E_{\\rightleftarrows}$ . coli, $\\left(\\mu_{\\mathrm{e}}\\right)$ decreased from $0.277{\\mathrm{h}}^{-\\hat{1}}$ to $0.0\\bar{6}8\\mathrm{h}^{-1}$ with increasing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\vphantom{\\mathrm{T}}x}$ concentration from 0 to $200~\\mu\\mathrm{g/mL}$ . For $B$ . subtilis, a decrease in the growth rate constants $\\left(\\mu_{\\mathrm{b}}\\right)$ from $0.347~\\mathrm{h}^{-1}$ to $0.134\\mathrm{h}^{-1}$ was observed with increasing ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ concentration. With increasing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ concentration from 0 to $200~\\mu\\mathrm{g/mL},$ bacterial doubling time $\\left(T_{\\mathrm{d}}\\right)$ was increased from 2.5 to $10.11\\mathrm{~h~}$ and 2.0 to $5.16\\mathrm{h}$ for $E_{\\rightleftarrows}$ . coli and B. subtilis, respectively, showing a strong bactericidal effect. \n\nBacterial Membrane Morphology Changes. To understand the antibacterial effect of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ MXene, changes of morphology and membrane integrity of E. coli and B. subtilis cells due to the interaction with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ were further evaluated by SEM and TEM. As depicted by SEM images in Figure 5A, bacterial cells of both $E.$ . coli and B. subtilis cultured in the absence of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ were viable with no observed membrane damage or cell death. The higher magnification in lower panels shows that the bacterium is protected by intact cytoplasmic membrane.40 On the other hand, most bacterial cell suffered from a prevalent membrane damage and cytoplasm leakage in the presence of $50\\mu\\mathrm{g/mL}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x},$ which is clearly observed at high magnifications (Figure 5B). Some bacterial cells still maintained the membrane integrity, but they were deformed. At $100\\:\\:\\mu\\mathrm{g/mL}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ both bacteria suffered from prevalent cell lysis indicated by a severe membrane disruption and cytoplasm leakage (see the red circles at high magnification in Figure 5C). \n\nSignificant morphological changes in the cell structure could be attributed to detachment of the cytoplasmic membrane from the cell wall as confirmed by LDH release assay. The SEM observations were consistent with the bacteria colonies numbers in Figure 3. It is suggested that with increasing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ concentration both E. coli and B. subtilis were trapped or wrapped by the thin sheets of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and subsequently formed agglomerates. This has been confirmed by spot EDS analysis on the surface of the bacterium (see Figure S5, Supporting Information). Similar observations were reported for graphene, GO, and CNTs, where the death of both the Gram $\\bar{(-)}$ and the Gram $\\left(+\\right)$ cells was ascribed to the disruption of their membranes and the leakage of their cytoplasm content after direct contact with graphene-based material.8,14,26,40 Liu et al. suggested that different aggregation/ dispersion behavior of GO and rGO may have distinct effect in their antimicrobial activities.14 \n\nAdditionally, TEM images (Figure 6) were utilized to observe the cell wall and membrane damage, as well as the change of inner structure of the cells. TEM analysis of E. coli and B. subtilis before and after being exposed to $200~\\mu\\mathrm{g/mL}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ showed a decrease in the number of bacterial cells in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathfrak{x}}$ treated groups comparing to the control. As Figure 6 shows, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets were tightly adsorbed around the cells and even entered the cells (Figure 6, arrows a,c). \n\n![](images/d3a2f42f9b019e667f91e27c5bebbcfba7a44cb0aa3b10006461abc696f4702f.jpg) \nFigure 6. TEM images of E. coli $(\\mathbf{A},\\mathbf{B})$ and B. subtilis $(\\mathbf{C},\\mathbf{D})$ treated with ${\\bf200~}\\mu\\bf{g/m L}$ of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ for $^\\textrm{\\scriptsize4h}$ at low (A, C) and high magnifications (B, D). The cell wall stripped down after exposure to $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ nanosheets (arrows $\\mathbf{b},\\mathbf{d})$ , $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ nanosheets tightly adsorbed around the cells and entered into the cells (arrows a, c). The intracellular densities of both cells decreased and $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ attached to the cellular membrane of both bacteria (arrows $\\mathbf{b},{\\mathbf{d}},$ ). \n\nMeanwhile, the intracellular densities of both $E.$ . coli and B. subtilis decreased, revealing that they lost some intracellular substance. The attachment of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ MXene to the cellular membrane of both bacteria is clearly demonstrated by presence of the highly crystalline $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ layers observed from the high resolution TEM (HRTEM) and the corresponding selected area electron diffraction (SAED) patterns, as well as the spot EDS analysis showing Ti signal on the surface of the treated bacteria (see Figures S6 and S7). In both $E.$ coli and B. subtilis, the cell wall was stripped down after exposure to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets (Figure 6, arrows b, d). Significant inner cell structure leakage was observed due to cell wall and membrane damage. \n\nLDH release assay was used to quantitatively determine the extent of cell damage. Figure 7 shows the LDH activity in the supernatants after $^{4\\mathrm{h}}$ of incubation. Concentration dependent LDH release was observed as bacterial cells were exposed to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets dispersions (Figure 7). The bacterial cells exposed to 2 and $10~\\mu\\mathrm{g/L}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\vphantom{\\mathrm{T}}x}$ exhibited minimal LDH release for both E. coli and B. subtilis. However, LDH release increased significantly when bacterial cells were exposed to 200 $\\mu\\mathrm{g/L}$ solution of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x},$ which showed cytotoxicity of $38.41\\%$ and $55.24\\%$ for $E$ . coli and B. subtilis, respectively. This dosedependent cytotoxicity shows that both the walls and the inner contents of the cell were damaged, suggesting that membrane disruption might be a major cell inhibitory mechanism. \n\n![](images/32eb422155fbd45383d55e0e1b8ffd9d85e6e2e4751ea6c163e48af8eb21d2d1.jpg) \nFigure 7. $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ cytotoxicity measured by LDH release from the bacterial cells exposed to different concentrations of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ for 4 h. \n\nOxidative-Stress and Antimicrobial Activity of $\\bar{\\Pi}_{3}\\mathsf C_{2}\\bar{\\Pi}_{x}$ MXene. Some earlier studies have proposed oxidative stress as a common mechanism of antibacterial activity of several metal-, metal-oxide-, and carbon-based nanomaterials.8,14,17,41 Oxidative stress occurs when cells are exposed to elevated levels of ROS such as free radicals, $\\mathrm{O}_{2}^{\\bullet-}$ , •OH and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . In particular, many previous studies have explored the generation of ROS on the surface of carbon, metal, and metal-oxide NPs like graphene, Ag, $\\mathrm{TiO}_{2},$ and $\\mathrm{ZnO.}^{\\mathrm{16-18}}$ Although an agreement on the ROS production of different nanomaterials was difficult to reach among various studies, almost all engineered NPs including nonoxide nanomaterials appear to produce ROS under certain circumstances.20,21,42 For example, some studies detected ROS in $\\mathrm{TiO}_{2}$ nanoparticles suspensions under dark conditions,43,44 whereas other studies did not.45 A similar mechanism has been thought for antibacterial activity of iron oxide nanoparticles in which reduced iron species $(\\mathrm{Fe}^{3+}/\\mathrm{Fe}^{2+})$ reacted with oxygen to create ROS.46 \n\n![](images/66e0361a378206ad6b58d490abe3e0747af46dd20553615a546e9ac5c4f0fdff.jpg) \nFigure 8. $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ nanosheets reaction with glutathione in colloidal suspensions. Bicarbonate buffer ( $\\bf{\\50m M}$ at $\\mathbf{pH8.}5\\mathrm{.}$ ) without $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ was used as a negative control. $\\mathbf{H}_{2}\\mathbf{O}_{2}$ ( $\\mathbf{\\hat{l}m M})$ was used as a positive control: (A) Time-dependent glutathione $(\\mathbf{0.4\\mM})$ loss after incubation for 4 h with $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ $\\mathbf{(200\\mug/mL)}$ . (B) Glutathione depletion exposed to different $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ concentrations (at 2, 10, 20, 50, 100, and ${\\bf2000}\\mu\\mathrm{g/mL}$ ) and incubated for $\\textbf{4h}$ . \n\nTo identify if cellular oxidative stress may be induced by $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ ROS dependent and independent oxidative stress was investigated in two separate abiotic assays. First, the production of superoxide anion $(\\bar{\\mathrm{O}}_{2}^{\\bullet-})$ at different $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ concentrations was monitored using XTT assay. As shown in the Figure S8 (Supporting Information), no noticeable absorption was detected at different $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ concentrations revealing that MXene mediated no or negligible superoxide anion production and their role in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ antibacterial activity could be minimal. However, the production and impact of ROS other than superoxide anion needs to be discretely examined in future studies. \n\nSecond, oxidative stress mediated by $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ was examined using glutathione oxidation assay. Glutathione is a tripeptide with a thiol group, which serves as one of the major cellular antioxidant enzymes in bacteria. It is involved in the intracellular oxidative balance and protects the cells against external electrophilic compounds. The oxidation of glutathione has been widely used as an indicator of the oxidative stress induced by different nanomaterials. Thiol groups $(-\\mathrm{{SH})}$ in glutathione can be oxidized to disulfide converting glutathione to glutathione disulfide. Moreover, direct contact of glutathione with nanoparticle surface also logically could lead to loss of glutathione by adsorption, or binding.47 In this study, glutathione was exposed to increasing concentrations of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ in a bicarbonate buffer and incubated for $^{4\\ \\mathrm{h},}$ after which the concentration of thiol groups was quantified by Ellman’s assay. \n\nAs shown in Figure 8, glutathione depletion was dependent on both $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ concentration and incubation time. Although negligible glutathione loss was observed for the control samples in the absence of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x},$ glutathione concentration was reduced from $97.5\\%$ to $61.7\\%$ when $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ concentration was increased from 2 to $200~\\mu\\mathrm{g/mL},$ respectively (Figure 8B). It is unlikely that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene itself can work as an oxidant for glutathione, but $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ has reactive $\\mathrm{Ti-F}$ groups on its surface, which are not stable at high $\\mathrm{\\tt{pH}},$ , and also $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ possesses a high negative surface charge, as shown by its $-30$ to $-40~\\mathrm{mV}$ zeta-potential in aqueous solutions.48 Thus, both chemical reactions and physisorption are potentially possible. However, at the moment, there is no published data on interaction of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ with thiols. \n\nIt is important to note that MXenes also have good conductivity $(>2000~\\mathrm{\\S/cm}$ measured on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films48), similar to or exceeding that of rGO. The mechanism in this case could be explained by formation of a conductive bridge over the insulating lipid bilayer, mediating electron transfer from bacterial intracellular components to the external environment and resulting in cell death.8,49 \n\nProposed Inhibition Mechanism of $\\bar{\\Pi}_{3}\\mathsf C_{2}\\bar{\\mathsf T}_{x}$ MXene. Strong antibacterial property of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ may be partially attributed to the anionic nature of its surface. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets have negatively charged surfaces. In addition, its high hydrophilicity may enhance bacterial contact to membrane surface resulting in inactivation of adhered microorganisms according to direct contact-killing mechanism. Morover, hydrogen bonding between oxygenate groups of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene and the lipopolysaccharide strings of the cell membrane could result in bacterial inhibition by preventing nutrient intake as recently proposed for GO nanosheets.10,50 It is important to understand the interaction of MXene with cell membranes for the evaluation of MXene’s health and environmental impacts and to utilize it as biocide in disinfection industry. We have found the interesting antibacterial activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}};$ however, still the interaction between MXene and bacterial cell membrane has to be investigated and fully understood. From the above LDH release assay, SEM, and TEM images, as well as glutathione oxidation assays, the antimicrobial mechanism of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\vphantom{\\mathrm{T}}x}$ MXene nanosheets can be explained as follows: First of all, delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ nanosheets with sharp edges have the capacity of adsorbing on the surface of microorganisms. It is also suggested that with increasing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ concentration, both E. coli and B. subtilis were trapped or wrapped by the nanometer-thin sheets of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ and subsequently formed agglomerates. Moreover, exposure of bacterial cells to sharp edges of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x},$ as shown by the TEM image in Figure 1A, may induce membrane damage. The water contact angle on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films was found to be $37^{\\circ}$ and its hydrophilicity may result in effective attachment of bacteria to $\\mathrm{Ti}_{3}\\mathrm{\\bar{C}}_{2}\\mathrm{T}_{x}.$ 1 The antibacterial effects may also be attributed to strong reducing activity of MXene and its reactive surfaces.52 The smallest $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\vphantom{\\mathrm{A}}x}$ nanosheets could permeate into the microorganism cell through direct physical penetration or via endocytosis. Finally, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ may also react with some molecules in the cell wall and cytoplasm of microorganism, disrupting the cell structure and leading to the death of the microorganism. Recently, several studies investigating the effects of carbonbased nanomaterials, such as graphene, GO, CNT, and fullerene, proposed a similar three-step antibacterial mechanism causing physicochemical damage to cell membranes depending upon the size of nanoparticles.10,12,14,23,41 \n\n$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ has been used as a representative MXene in this study. However, there are now close to 20 members of MXene family that should be similarly screened for their potential use as antibacterial agents. Taking into account that other MXenes have different transition metals, such as Nb, Mo, V, and so forth,2,53−55 exposed on their surface, we can expect different chemical behavior as a function of the MXene composition and the surface termination (OH, O, F, etc.). Even Ti-based MXenes can differ in chemical reactivity. For example, ${\\mathrm{Ti}}_{2}{\\mathrm{CT}}_{\\boldsymbol{x}}$ oxidizes easier in the presence of oxygen and water than $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}.^{52}\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ produced by different methods has different functional groups on its surface, with more $\\mathrm{~F~}$ on the surface of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ produced by etching in concentrated HF compared to that synthesized by extracting Al in diluted HF or LiF-HCl solution.56,57 Difference in surface chemistry may affect toxicity and antibacterial activity of MXenes. This study is the first step toward understanding interactions of MXenes with living matter and it is expected to open the door for extensive studies on other 2D carbides and nitrides of transition metals. Fine tuning of MXene surface functional groups, flake size, and conductivity, both in colloidal and membrane forms, may open a wide window for MXenes’ application in the antimicrobial coatings and water purification membranes. \n\n# CONCLUSIONS \n\nOur studies demonstrate that ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ in aqueous colloidal solution can stimulate antibacterial activity against Gram $(-)E$ . coli and Gram $\\left(+\\right)$ B. subtilis bacteria. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ antibacterial activity was dose dependent and exceeded that of GO. Direct contact with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene can disrupt cellular membranes leading to cell damage and eventual death. We have focused this first study on the antibacterial properties of MXenes, but the cellular uptake and cytotoxicity of MXene should be studied to understand the health and environmental impact of MXenes. On the basis of these results, we introduce MXenes as a new family of 2D antimicrobial nanomaterials for their potential use in water treatment and biomedical applications. \n\n# MATERIALS AND METHODS \n\nSynthesis, Delamination, and Dispersion of $\\pmb{\\operatorname{Ti}}_{3}\\pmb{\\operatorname{C}}_{2}\\pmb{\\operatorname{T}}_{x}.$ A colloidal solution of single- and few-layer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ particles was obtained by delaminating $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ powders by ultrasonication, after etching $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ with LiF/HCl solution (Sigma-Aldrich) as described previously32 with minor modifications in the process. Briefly, the obtained M $\\mathrm{\\partial_{\\Omega}}_{\\mathrm{-}}\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it{x}}$ powder was dispersed in deaerated water with a weight ratio of ML${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ :water of 1:250. The suspension was probe sonicated at $60\\%$ amplitude for 30 minutes (450 watts) while 3 sec pulse on and 1 sec off under flow of argon, and then centrifuged for $^\\textrm{\\scriptsize1h}$ at $3000~\\mathrm{rpm}$ to obtain the supernatant containing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ flakes. TEM, SEM, EDX, and XRD were used to study the structure, composition and morphology of the flakes. \n\nCell Preparation. The antibacterial properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ and GO colloids were evaluated using $E_{\\rightleftarrows}$ . coli and B. subtilis as the model Gram $(-)$ and Gram $\\bar{(+)}$ bacteria, respectively. Glycerol stocks were used to inoculate defined overnight cultures in LB medium at $35~^{\\circ}\\mathrm{C}.$ . Following that, $1\\mathrm{mL}$ volumes of cell suspensions were subcultured and harvested at the exponential growth phase. Cultures were centrifuged at 5000 rpm for $\\textsf{S m i n}$ and pellets obtained were washed three times with phosphate buffered saline (PBS, Sigma-Aldrich) $\\left(\\mathrm{pH}\\ 7.2\\right)$ to remove residual macromolecules and other growth medium constituents. The cell pellets collected by centrifugation were resuspended in sterilized deionized water (DI) and diluted to approximate cell concentration of $10^{7}\\mathrm{\\CFU/mL}$ . Gentamicin $\\mathbf{(50~\\mug/mL)}$ ) was used as positive control. Water was used to replace PBS buffer for the antibacterial studies to prevent the aggregation of MXene in PBS during experiments. Figure S9, (Supporting Information) showed that cell viability of $E$ . coli and B. subtilis was similar in DI and PBS during $^\\mathrm{~4~h~}$ of incubation time. \n\nAntibacterial Activity of $\\bar{\\Pi}_{3}\\mathsf C_{2}\\bar{\\mathsf T}_{x}$ (MXene) Nanosheets Dispersions. Antibacterial activity against each strain was determined by the colony count method and the measurement of OD. Batch assays were performed to compare the antibacterial activity of delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ in colloidal solution with that of dispersions of ML- $\\mathrm{\\cdotTi}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ and $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Delaminated ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{{\\boldsymbol{x}},{\\boldsymbol{\\mathbf{\\mathit{x}}}}}$ $\\mathbf{ML}–\\mathrm{Ti}_{3}\\mathbf{C}_{2}\\mathrm{T}_{x},$ and $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ concentrations of $100~\\mu\\mathrm{g/mL}$ were applied to both E. coli and B. subtilis and cell survival rate was counted by $\\mathrm{CFU/mL}$ . \n\nA second set of antibacterial activity tests was conducted by spread plate CFU counting. The bacteria (about $10^{7}\\:\\mathrm{CFU/mi}$ were incubated with different concentrations $\\left(2{-}200~\\mu\\mathrm{g/mL}\\right)$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene for $^\\textrm{\\scriptsize4h}$ . Aliquots of the samples were withdrawn and CFU were counted by plating $40\\mu\\mathrm{L}$ of 10-fold serial dilutions onto LB agar plates. Colonies were counted after incubation at $35~^{\\circ}\\mathrm{{C}}$ and the cell survival rate was expressed as the percentage of the control and $\\log$ reduction. The following equation was used to represent relative viability of cells: \n\n$$\n{\\mathrm{relative~cells~availability}}=\\left({\\frac{N_{\\mathrm{c}}}{N_{\\mathrm{m}}}}\\right)\\times100\n$$ \n\nwhere $N_{\\mathrm{c}}$ is bacterial colonies of the control sample and $N_{\\mathrm{m}}$ are colonies for cells treated with ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{{\\boldsymbol{x}}}$ . \n\nThe log reduction was calculated using the following equation: \n\n$$\n\\mathrm{logreduction}=\\mathrm{log}_{10}\\bigg(\\frac{N_{\\mathrm{c}}}{N_{\\mathrm{m}}}\\bigg)\n$$ \n\nTo examine the effect of MXene on bacterial regrowth, the batch assays were subjected to 2, 10, 20, 50, 100, and $200~\\mu\\mathrm{g}/\\$ mL $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ . The batch assays were subjected to continuous shaking at $150~\\mathrm{rpm}$ and constant mesophilic temperature of 35 $^{\\circ}\\mathrm{C}$ for $\\mathrm{{4h}}$ . For controls, DI was added instead of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ . The reaction mixture was then transferred to $15~\\mathrm{mL}$ tubes, each containing $10~\\mathrm{\\mL}$ of LB medium, and the tubes were inoculated on a shaking incubator at $150\\ \\mathrm{\\rpm}$ and $35~^{\\circ}\\mathrm{C}$ . Aliquots of the samples were withdrawn at specific time intervals and the value of OD at a wavelength of $600\\ \\mathrm{nm}$ was measured on a UV−vis spectrometer (Novaspec Plus). Bacterial regrowth curves were created by plotting OD values versus time and bacterial growth kinetics were studied. All experiments were performed as triplicates and average values were reported. \n\nAntibacterial activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ in LB growth media was assessed by exposing the bacteria (about $10^{5}\\mathrm{CFU/mL}$ to 200 $\\mu\\mathrm{g/mL}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene for $^{4\\mathrm{h}}$ . Aliquots of the samples were withdrawn and CFU were counted as described earlier. \n\nLactase Dehydrogenase Release Assay. LDH release assay was used to determine the cell membrane activity of \n\nMXene treated bacterial cells in colloidal solution using cytotoxicity detection kit (Roche Applied Science). The standard protocol assay was performed according to the manufacturer’s instructions. Briefly, $E.$ . coli and B. subtilis cells were treated with 2, 10, 20, 50, 100, and $200\\mu\\mathrm{g/mL}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ in DI for $^{4\\mathrm{~h~}}$ . Following $^\\textrm{\\scriptsize4h}$ exposure to MXene, $50~\\mu\\mathrm{L}$ of cell culture supernatant was transferred into sterile $1~\\mathrm{mL}$ centrifuge tubes. Then, $50~\\mu\\mathrm{L}$ substrate mix was added and tubes were incubated at room temperature in the dark for $^{\\textrm{1h}}$ . The reaction was stopped by the addition of $50~\\mu\\mathrm{L}$ of stop solution. LDH release was quantified by measuring absorbance at $490~\\mathrm{nm}$ . \n\nSuperoxide Radical $(0^{2\\bullet-})$ Assay. The hypothetical possibility of superoxide radical anion $(\\dot{\\mathrm{O}}^{2\\bullet-})$ production was evaluated by monitoring the absorption of XTT (2,3-bis (2- methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide, Fluka). XTT can be reduced by superoxide radical anion $(\\mathrm{O}^{2\\bullet-})$ to form water-soluble XTT-formazan with the maximum absorption at $470~\\mathrm{\\nm}$ . XTT $\\left(0.4~\\mathrm{\\mM}\\right)$ were dissolved in PBS solution at $\\mathrm{pH}~7.0$ . Bacterial dispersions treated with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ at different concentrations $(1~\\mathrm{mL})$ in DI were mixed with $1\\ \\mathrm{mL}$ of $0.4\\mathrm{\\mM}$ XTT. The mixture was incubated in dark for $s\\mathrm{~h~}_{\\cdot}$ ; afterward, the mixture was filtered through a $0.45\\mu\\mathrm{m}$ polyethersulfone (PES) filter (Whatman) to remove $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}.$ The changes in absorbance at $470\\ \\mathrm{nm}$ were monitored with a UV−vis spectrophotometer. \n\nAbiotic Thiol Oxidation and Quantification. The $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (MXene)-mediated abiotic oxidation of glutathione was studied by quantifying thiol concentration following Ellman’s assay as described earlier.49 Briefly, $0.4~\\mathrm{\\mM}$ glutathione was prepared in a $50~\\mathrm{mM}$ bicarbonate buffer $\\mathrm{\\langlepH}$ 8.6) at a total volume of $250~\\mu\\mathrm{L}$ in microcentrifuge tubes, and the reaction was initiated by spiking the solution with various $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ concentrations. The tubes were then placed in a shaker incubator at room temperature $(22-23{\\ }^{\\circ}\\mathrm{C})$ and covered with aluminum foil to prevent any photochemical reactions. A $90\\mu\\mathrm{L}$ aliquot of the reaction solution was mixed with $157\\mu\\mathrm{L}$ of Tris− HCl $\\mathrm{\\Phi_{pH}}8.3$ , Fluka) and $3~\\mu\\mathrm{L}$ of $100\\mathrm{\\mM\\}5{,}5^{\\prime}$ -dithio-bis(2- nitrobenzoic acid) (DTNB, Invitrogen). The assayed aliquots were then filtered through a $0.45\\ \\mu\\mathrm{m}$ PES filter to remove $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and eliminate any background absorbance and/or scattering. The filtered aliquot absorbance at $412\\ \\mathrm{nm}$ was measured by a UV−vis spectrophotometer (SPECTRA max 340PC). The concentration of thiol was calculated using the absorbance at $412\\ \\mathrm{nm},$ , a path length of $1\\ \\mathrm{cm}$ , and a molar extinction coefficient of $14150\\mathrm{~\\ensuremath~{~M^{-1}~}~c m^{-1}}$ . Glutathione oxidation by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ ( $1\\mathrm{mM}$ and $10~\\mathrm{mM}$ ) was used as a positive control. \n\nCell Morphology Observation with SEM and TEM. SEM analysis was performed to observe the effect of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ MXene on morphology and surface structure of the bacterial cells using FEI-Nova Nano SEM 650. SEM imaging of samples was accomplished using the following procedures: after the experiments, cells from the treated samples were fixed with $2.5\\%$ glutaraldehyde (Sigma-Aldrich) overnight at $4^{\\circ}\\mathrm{C},$ followed by washing with 0.1 M PBS $\\mathrm{(pH7.4)}$ and dehydration with a graded ethanol series (25, 50, 80, $100\\%$ ). For SEM, samples were allowed to dry completely at room temperature and then coated with gold by sputtering $(5\\ \\mathrm{nm})$ . \n\nThe ultrastructure of the bacteria was examined by TEM. The bacteria were pelleted and fixed overnight with a $4\\%$ formaldehyde $-1\\%$ glutaraldehyde fixative. Following a wash with $s$ -collidine buffer, the samples were postfixed with $1\\%$ osmium tetroxide for $^\\textrm{\\scriptsize1h},$ , dehydrated in graded concentrations of ethanol, and embedded in epoxy resin. The resin embedded tissue was polymerized at $60~^{\\circ}\\mathrm{C}$ overnight. Thick $1-2\\mu\\mathrm{m}$ and thin $90~\\mathrm{{\\nm}}$ sections were cut using a Leica EM UC6 ultramicrotome. Grids were stained with uranyl acetate and lead citrate stains. Ultrathin $90\\mathrm{nm}$ sections were examined with a JEOL JEM-1230 transmission electron microscope operated at $80~\\mathrm{kV}$ . Digital images were acquired using an AMT digital camera system. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.6b00181. \n\nPhotographs of agar plates and results of inhibition studies, detailed cell viability and log reduction graphs, detailed TEM and EDS analysis. (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\n$^{*}\\mathrm{E}$ -mail: kmahmoud@qf.org.qa. Fax: +974 44541528. \n$^{*}\\mathrm{E}$ -mail: gogotsi@drexel.edu. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nK.R. is grateful to the Maersk Oil Research & Technology Centre at Qatar for the financial support. C.R. was supported by the Chinese Scholarship Council (CSC). Y.G. acknowledges the support from the NOMAD project funded by British Council. FESEM analysis was performed at the Central Lab Unit, Qatar University. The authors would like to thank C. Johnson and S. Koutzaki at the Centralized Research Facilities and Pathology Department, College of Medicine, of Drexel University for the TEM analyses. The authors are grateful to Department of Biological and Environmental Sciences, Qatar University for their support and providing bacteria strains and Dr. Susan Sandeman of Brighton University for the helpful discussions. \n\n# REFERENCES \n\n(1) Lei, J.-C.; Zhang, X.; Zhou, Z. Recent advances in MXene: Preparation, Properties, and Applications. Front. Phys. 2015, 10, 276− 286. (2) Naguib, M.; Mashtalir, O.; Carle, J.; Presser, V.; Lu, J.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Transition Metal Carbides. ACS Nano 2012, 6, 1322−1331. (3) Naguib, M.; Kurtoglu, M.; Presser, V.; Lu, J.; Niu, J.; Heon, M.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Nanocrystals Produced by Exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 2011, 23, 4248−4253. (4) Mashtalir, O.; Naguib, M.; Mochalin, V. N.; Dall’Agnese, Y.; Heon, M.; Barsoum, M. W.; Gogotsi, Y. Intercalation and Delamination of Layered Carbides and Carbonitrides. Nat. Commun. 2013, 4, 1716. (5) Naguib, M.; Mochalin, V. N.; Barsoum, M. W.; Gogotsi, Y. 25th anniversary article: MXenes: A New Family of Two-Dimensional Materials. Adv. Mater. 2014, 26, 992−1005. (6) Naguib, M.; Gogotsi, Y. Synthesis of Two-Dimensional Materials by Selective Extraction. Acc. Chem. Res. 2015, 48, 128−135. (7) Ren, C. E.; Hatzell, K. B.; Alhabeb, M.; Ling, Z.; Mahmoud, K. A.; Gogotsi, Y. Charge- and Size-Selective Ion Sieving Through $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene Membranes. J. Phys. Chem. Lett. 2015, 6, 4026−4031. \n\n(8) Li, J.; Wang, G.; Zhu, H.; Zhang, M.; Zheng, X.; Di, Z.; Liu, X.; Wang, X. Antibacterial Activity of Large-area Monolayer Graphene Film Manipulated by Charge Transfer. Sci. Rep. 2014, 4, 4359. (9) Hu, W.; Peng, C.; Luo, W.; Lv, M.; Li, X.; Li, D.; Huang, $\\mathrm{Q.;}$ Fan, C. Graphene-Based Antibacterial Paper. ACS Nano 2010, 4, 4317− 4323. \n(10) Akhavan, O.; Ghaderi, E. Toxicity of Graphene and Graphene Oxide Nanowalls Against Bacteria. ACS Nano 2010, 4, 5731−5736. (11) Salas, E. C.; Sun, Z.; Lüttge, A.; Tour, J. M. Reduction of Graphene Oxide via Bacterial Respiration. ACS Nano 2010, 4, 4852− 4856. \n(12) Tu, Y.; Lv, M.; Xiu, P.; Huynh, T.; Zhang, M.; Castelli, M.; Liu, Z.; Huang, $\\mathrm{Q.;}$ Fan, C.; Fang, H.; Zhou, R. Destructive Extraction of Phospholipids from Escherichia Coli Membranes by Graphene Nanosheets. Nat. Nanotechnol. 2013, 8, 594−601. \n(13) Kim, I. Y.; Park, S.; Kim, H.; Park, S.; Ruoff, R. S.; Hwang, S.-J. Strongly-Coupled Freestanding Hybrid Films of Graphene and Layered Titanate Nanosheets: An Effective Way to Tailor the Physicochemical and Antibacterial Properties of Graphene Film. Adv. Funct. Mater. 2014, 24, 2288−2294. \n(14) Liu, S.; Zeng, T. H.; Hofmann, M.; Burcombe, E.; Wei, J.; Jiang, R.; Kong, J.; Chen, Y. Antibacterial Activity of Graphite, Graphite Oxide, Graphene Oxide, and Reduced Graphene Oxide: Membrane and Oxidative Stress. ACS Nano 2011, 5, 6971−6980. \n(15) Chernousova, S.; Epple, M. Silver as Antibacterial Agent: Ion, Nanoparticle, and Metal. Angew. Chem., Int. Ed. 2013, 52, 1636−1653. (16) Lemire, J. A.; Harrison, J. J.; Turner, R. J. Antimicrobial Activity of Metals: Mechanisms, Molecular Targets and Applications. Nat. Rev. Microbiol. 2013, 11, 371−384. \n(17) Li, Y.; Zhang, W.; Niu, J.; Chen, Y. Mechanism of Photogenerated Reactive Oxygen Species and Correlation with the Antibacterial Properties of Engineered Metal-Oxide Nanoparticles. ACS Nano 2012, 6, 5164−5173. \n(18) Lakshmi Prasanna, V.; Vijayaraghavan, R. Insight into the Mechanism of Antibacterial Activity of ZnO: Surface Defects Mediated Reactive Oxygen Species Even in the Dark. Langmuir 2015, 31, 9155− 9162. \n(19) Wang, Y.-W.; Cao, A.; Jiang, Y.; Zhang, X.; Liu, J.-H.; Liu, Y.; Wang, H. Superior Antibacterial Activity of Zinc Oxide/Graphene Oxide Composites Originating from High Zinc Concentration Localized around Bacteria. ACS Appl. Mater. Interfaces 2014, 6, 2791−2798. \n(20) Zhang, W.; Li, Y.; Niu, J.; Chen, Y. Photogeneration of Reactive Oxygen Species on Uncoated Silver, Gold, Nickel, and Silicon Nanoparticles and Their Antibacterial Effects. Langmuir 2013, 29, 4647−4651. \n(21) Choi, O.; Hu, Z. Size Dependent and Reactive Oxygen Species Related Nanosilver Toxicity to Nitrifying Bacteria. Environ. Sci. Technol. 2008, 42, 4583−4588. \n(22) Wu, L.; Zeng, L.; Jiang, X. Revealing the Nature of Interaction between Graphene Oxide and Lipid Membrane by Surface-Enhanced Infrared Absorption Spectroscopy. J. Am. Chem. Soc. 2015, 137, 10052−10055. \n(23) Romero-Vargas Castrillón, S.; Perreault, F.; de Faria, A. F.; Elimelech, M. Interaction of Graphene Oxide with Bacterial Cell Membranes: Insights from Force Spectroscopy. Environ. Sci. Technol. Lett. 2015, 2, 112−117. \n(24) Perreault, F.; de Faria, A. F.; Nejati, S.; Elimelech, M. Antimicrobial Properties of Graphene Oxide Nanosheets: Why Size Matters. ACS Nano 2015, 9, 7226−7236. \n(25) Li, $\\mathrm{Q.;}$ Mahendra, S.; Lyon, D. Y.; Brunet, L.; Liga, M. V.; Li, D.; Alvarez, P. J. J. Antimicrobial Nanomaterials for Water Disinfection and Microbial Control: Potential applications and implications. Water Res. 2008, 42, 4591−4602. \n(26) Kang, S.; Pinault, M.; Pfefferle, L. D.; Elimelech, M. SingleWalled Carbon Nanotubes Exhibit Strong Antimicrobial Activity. Langmuir 2007, 23, 8670−8673. \n\n(27) Guo, L.; Morris, D. G.; Liu, X.; Vaslet, C.; Hurt, R. H.; Kane, A. B. Iron Bioavailability and Redox Activity in Diverse Carbon Nanotube Samples. Chem. Mater. 2007, 19, 3472−3478. (28) Pulskamp, K.; Diabaté, S.; Krug, H. F. Carbon Nanotubes Show no Sign of Acute Toxicity but Induce Intracellular Reactive Oxygen Species in Dependence on Contaminants. Toxicol. Lett. 2007, 168, 58−74. (29) Narayan, R. J.; Berry, C. J.; Brigmon, R. L. Structural and Biological Properties of Carbon nanotube Composite Films. Mater. Sci. Eng., B 2005, 123, 123−129. (30) Kostarelos, K.; Novoselov, K. S. Exploring the Interface of Graphene and Biology. Science 2014, 344, 261−263. (31) Dellieu, L.; Lawarée, E.; Reckinger, N.; Didembourg, C.; Letesson, J. J.; Sarrazin, M.; Deparis, O.; Matroule, J. Y.; Colomer, J. F. Do CVD Grown Graphene Films have Antibacterial Activity on Metallic Substrates? Carbon 2015, 84, 310−316. (32) Ghidiu, M.; Lukatskaya, M. R.; Zhao, M.- $\\mathrm{.Q.;}$ Gogotsi, Y.; Barsoum, M. W. Conductive Two-Dimensional Titanium Carbide ‘Clay’ with High Volumetric Capacitance. Nature 2014, 516, 78−81. (33) Hummers, W. S.; Offeman, R. E. Preparation of Graphitic Oxide. J. Am. Chem. Soc. 1958, 80, 1339−1339. (34) Fu, F.; Li, L.; Liu, L.; Cai, J.; Zhang, Y.; Zhou, J.; Zhang, L. Construction of Cellulose Based ZnO Nanocomposite Films with Antibacterial Properties through One-Step Coagulation. ACS Appl. Mater. Interfaces 2015, 7, 2597−2606. (35) Brock, T. D. Milestones in Microbiology; Prentice Hall: Upper Saddle River, NJ, 1961; Vol. 36, p 847. (36) Büttner, K.; Bernhardt, J.; Scharf, C.; Schmid, R.; Mäder, U.; Eymann, C.; Antelmann, H.; Völker, A.; Völker, U.; Hecker, M. A Comprehensive Two-Dimensional Map of Cytosolic Proteins of Bacillus subtilis. Electrophoresis 2001, 22, 2908−2935. (37) Kholmanov, I. N.; Stoller, M. D.; Edgeworth, J.; Lee, W. H.; Li, H.; Lee, J.; Barnhart, C.; Potts, J. R.; Piner, R.; Akinwande, D.; Barrick, J. E.; Ruoff, R. S. Nanostructured Hybrid Transparent Conductive Films with Antibacterial Properties. ACS Nano 2012, 6, 5157−5163. (38) Ocsoy, I.; Paret, M. L.; Ocsoy, M. A.; Kunwar, S.; Chen, T.; You, M.; Tan, W. Nanotechnology in Plant Disease Management: DNA-Directed Silver Nanoparticles on Graphene Oxide as an Antibacterial against Xanthomonas perforans. ACS Nano 2013, 7, 8972−8980. (39) Eaton, P.; Fernandes, J. C.; Pereira, E.; Pintado, M. E.; Xavier Malcata, F. Atomic Force Microscopy Study of the Antibacterial Effects of Chitosans on Escherichia coli and Staphylococcus aureus. Ultramicroscopy 2008, 108, 1128−1134. (40) Chen, J.; Peng, H.; Wang, X.; Shao, F.; Yuan, Z.; Han, H. Graphene Oxide Exhibits Broad-Spectrum Antimicrobial Activity against Bacterial Phytopathogens and Fungal Conidia by Intertwining and Membrane Perturbation. Nanoscale 2014, 6, 1879−1889. (41) Zhang, Y.; Ali, S. F.; Dervishi, E.; Xu, Y.; Li, Z.; Casciano, D.; Biris, A. S. Cytotoxicity Effects of Graphene and Single-Wall Carbon Nanotubes in Neural Phaeochromocytoma-Derived PC12 Cells. ACS Nano 2010, 4, 3181−3186. (42) Yong, K.-T.; Law, W.-C.; Hu, R.; Ye, L.; Liu, L.; Swihart, M. T.; Prasad, P. N. Nanotoxicity Assessment of Quantum Dots: from Cellular to Primate Studies. Chem. Soc. Rev. 2013, 42, 1236−1250. (43) Long, T. C.; Saleh, N.; Tilton, R. D.; Lowry, G. V.; Veronesi, B. Titanium Dioxide (P25) Produces Reactive Oxygen Species in Immortalized Brain Microglia (BV2): Implications for Nanoparticle Neurotoxicity. Environ. Sci. Technol. 2006, 40, 4346−4352. (44) Long, T. C.; Tajuba, J.; Sama, P.; Saleh, N.; Swartz, C.; Parker, J.; Hester, S.; Lowry, G. V.; Veronesi, B. Nanosize Titanium Dioxide Stimulates Reactive Oxygen Species in Brain Microglia and Damages Neurons. in Vitro. Environ. Health Persp. 2007, 115, 1631−1637. (45) Xia, T.; Kovochich, M.; Brant, J.; Hotze, M.; Sempf, J.; Oberley, T.; Sioutas, C.; Yeh, J. I.; Wiesner, M. R.; Nel, A. E. Comparison of the Abilities of Ambient and Manufactured Nanoparticles To Induce Cellular Toxicity According to an Oxidative Stress Paradigm. Nano Lett. 2006, 6, 1794−1807. \n\n(46) Ismail, R. A.; Sulaiman, G. M.; Abdulrahman, S. A.; Marzoog, T. R. Antibacterial Activity of Magnetic Iron Oxide Nanoparticles Ssynthesized by Laser Ablation in Liquid. Mater. Sci. Eng., C 2015, 53, 286−297. \n(47) Carmel-Harel, O.; Storz, G. Roles of the Glutathione- and Thioredoxin-Dependent Reduction Systems in the Escherichia coli and Saccharomyces Cerevisiae Responses to Oxidative Stress. Annu. Rev. Microbiol. 2000, 54, 439−461. \n(48) Ling, Z.; Ren, C. E.; Zhao, $\\mathrm{M.}\\mathrm{-}\\mathrm{Q.};$ Yang, J.; Giammarco, J. M.; Qiu, J.; Barsoum, M. W.; Gogotsi, Y. Flexible and conductive MXene Films and Nanocomposites with High Capacitance. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 16676−16681. \n(49) Vecitis, C. D.; Zodrow, K. R.; Kang, S.; Elimelech, M. Electronic-Structure-Dependent Bacterial Cytotoxicity of SingleWalled Carbon Nanotubes. ACS Nano 2010, 4, 5471−5479. \n(50) Liu, S.; Hu, M.; Zeng, T. H.; Wu, R.; Jiang, R.; Wei, J.; Wang, L.; Kong, J.; Chen, Y. Lateral Dimension-Dependent Antibacterial Activity of Graphene Oxide Sheets. Langmuir 2012, 28, 12364−12372. (51) Tian, T.; Shi, X.; Cheng, L.; Luo, Y.; Dong, Z.; Gong, H.; Xu, L.; Zhong, Z.; Peng, R.; Liu, Z. Graphene-Based Nanocomposite As an Effective, Multifunctional, and Recyclable Antibacterial Agent. ACS Appl. Mater. Interfaces 2014, 6, 8542−8548. \n(52) Mashtalir, O.; Cook, K. M.; Mochalin, V. N.; Crowe, M.; Barsoum, M. W.; Gogotsi, Y. Dye Adsorption and Decomposition on Two-Dimensional Titanium Carbide in Aqueous Media. J. Mater. Chem. A 2014, 2, 14334−14338. \n(53) Naguib, M.; Halim, J.; Lu, J.; Cook, K. M.; Hultman, L.; Gogotsi, ${\\mathrm{Y}}_{\\cdot{\\mathrm{;}}}$ Barsoum, M. W. New Two-Dimensional Niobium and Vanadium Carbides as Promising Materials for Li-Ion Batteries. J. Am. Chem. Soc. 2013, 135, 15966−15969. \n(54) Anasori, B.; Xie, Y.; Beidaghi, M.; Lu, J.; Hosler, B. C.; Hultman, L.; Kent, P. R. C.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional, Ordered, Double Transition Metals Carbides (MXenes). ACS Nano 2015, 9, 9507−9516. \n(55) Mashtalir, O.; Lukatskaya, M. R.; Zhao, $\\mathrm{M.}\\mathrm{\\-Q.};$ Barsoum, M. W.; Gogotsi, Y. Amine-Assisted Delamination of $\\mathsf{N b}_{2}\\mathsf{C}$ MXene for Li-Ion Energy Storage Devices. Adv. Mater. 2015, 27, 3501−3506. \n(56) Halim, J.; Cook, K. M.; Naguib, M.; Eklund, P.; Gogotsi, Y.; Rosen, J.; Barsoum, M. W. X-ray Photoelectron Spectroscopy of Select Multi-Layered Transition Metal Carbides (MXenes). Appl. Surf. Sci. 2016, 362, 406−417. \n(57) Wang, H.-W.; Naguib, M.; Page, K.; Wesolowski, D. J.; Gogotsi, Y. Resolving the Structure of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXenes through Multilevel Structural Modeling of the Atomic Pair Distribution Function. Chem. Mater. 2016, 28, 349−359. " + }, + { + "id": "10.1021_jacs.6b11291", + "DOI": "10.1021/jacs.6b11291", + "DOI Link": "http://dx.doi.org/10.1021/jacs.6b11291", + "Relative Dir Path": "mds/10.1021_jacs.6b11291", + "Article Title": "High Electrocatalytic Hydrogen Evolution Activity of an Anomalous Ruthenium Catalyst", + "Authors": "Zheng, Y; Jiao, Y; Zhu, YH; Li, LH; Han, Y; Chen, Y; Jaroniec, M; Qiao, SZ", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Hydrogen evolution reaction (HER) is a critical process due to its fundamental role in electrocatalysis. Practically, the development of high-performance electrocatalysts for HER in alkaline media is of great importance for the conversion of renewable energy to hydrogen fuel via photoelectrochemical water splitting. However, both mechanistic exploration and materials development for HER under alkaline conditions are very limited. Precious. Pt metal, which still serves as the state-of-the-art catalyst for HER, is unable to guarantee a sustainable hydrogen supply. Here we report an anomalously structured Ru catalyst that shows 2.5 times higher hydrogen generation rate than Pt and is among the most active HER electrocatalysts yet reported in alkaline solutions. The identification of new face-centered cubic crystallographic structure of Ru nulloparticles was investigated by high-resolution transmission electron microscopy imaging, and its formation mechanism was revealed by spectroscopic characterization and theoretical analysis. For the first time, it is found that the Ru nullo catalyst showed a pronounced effect of the crystal structure on the electrocatalytic activity tested under different conditions. The combination of electrochemical reaction rate measurements and density functional theory computation shows that the high activity of anomalous Ru catalyst in alkaline solution originates from its suitable adsorption energies to some key reaction intermediates and reaction kinetics in the HER process.", + "Times Cited, WoS Core": 918, + "Times Cited, All Databases": 941, + "Publication Year": 2016, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000389962800057", + "Markdown": "# High Electrocatalytic Hydrogen Evolution Activity of an Anomalous Ruthenium Catalyst \n\nYao Zheng, Yan Jiao, Yihan Zhu, Lu Hua Li, Yu Han, Ying Chen, Mietek Jaroniec, and Shi Zhang Qiao J. Am. Chem. Soc., Just Accepted Manuscript $\\cdot$ DOI: 10.1021/jacs.6b11291 $\\cdot$ Publication Date (Web): 28 Nov 2016 Downloaded from http://pubs.acs.org on November 28, 2016 \n\n# Just Accepted \n\n“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier $(\\mathsf{D O}|\\oplus)$ . “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts. \n\n# High Electrocatalytic Hydrogen Evolution Activity of an Anomalous Ruthenium Catalyst \n\nYao Zheng1‡, Yan Jiao1‡, Yihan $\\mathrm{Zhu}^{2\\ddagger}$ , Lu Hua $\\mathrm{Li}^{3}$ , Yu Han2, Ying Chen3, Mietek Jaroniec4, Shi-Zhang Qiao1\\* \n\n1 School of Chemical Engineering, University of Adelaide, Adelaide, SA 5005, Australia \n2 King Abdullah University of Science and Technology, Advanced Membranes and Porous Materials Center, Physical Sciences and \nEngineering Division, Imaging and Characterization Core Lab, Thuwal 23955-6900, Saudi Arabia \n3 Institute for Frontier Materials, Deakin University, Waurn Ponds, VIC 3216, Australia \n4 Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44242, USA \n\nABSTRACT: Hydrogen evolution reaction (HER) is a critical process due to its fundamental role in electrocatalysis. Practically, the development of high-performance electrocatalysts for HER in alkaline media is of great importance for the conversion of renewable energy to hydrogen fuel via photoelectrochemical water splitting. However, both mechanistic exploration and materials development for HER under alkaline conditions are very limited. Precious Pt metal, which still serves as the state-of-the-art catalyst for $\\mathrm{HER},$ is unable to guarantee a sustainable hydrogen supply. Here we report an anomalously structured Ru catalyst that shows 2.5 times higher hydrogen generation rate than Pt and is among the most active HER electrocatalysts yet reported in alkaline solutions. The identification of new face-centered-cubic crystallographic structure of Ru nanoparticles was investigated by high resolution transmission electron microscopy imaging and its formation mechanism was revealed by spectroscopic characterization and theoretical analysis. For the first time, it is found that the Ru nanocatalyst showed a pronounced effect of the crystal structure on the electrocatalytic activity tested under different conditions. The combination of electrochemical reaction rate measurements and density functional theory computation shows that the high activity of anomalous Ru catalyst in alkaline solution originates from its suitable adsorption energies to some key reaction intermediates and reaction kinetics in HER process. \n\n# INTRODUCTION \n\nSearch for suitable catalysts with maximum mass-specific reactivity yet long-term stability has been an everlasting but still formidable challenging topic in catalysis research. Generally, the apparent rate of a surface reaction occurring on a heterogeneous catalyst is strongly dependent on its geometric properties (size, conformation, crystallinity, etc.) and electronic structure (d-band centre position, work functions, etc.), which act together in determining adsorption of intermediates, activation energies and energy barriers for this reaction.1-7 This complexity hinders the design and selection of the most appropriate catalyst for a specific catalytic reaction. For instance, one catalyst’s geometric structure sensitivity can significantly affect its activity toward a specific heterogeneous reaction like the ammonia synthesis over certain iron crystal faces,5 crystallographic dependence of Fischer–Tropsch process over cobalt catalysts,6 and nanogold’s size dependence of carbon monoxide oxidation.7 \n\nDue to the enormous advances in modern physical chemistry and computational quantum chemistry, an in-depth understanding of the macroscopic reaction kinetics of catalytic processes at the atomic level can be achieved by correlating reaction rate measurements, spectroscopic characterization, and theoretical calculations.3, 8-10 The importance of this correlation lies in its ability to reveal the nature of the solid catalysts and the origin of their reactivity toward specific catalytic processes. 11-14 Therefore, one can engineer potential catalysts with desired performance by tailoring their chemical composition and/or physical structure. \n\nHydrogen evolution $\\mathrm{^{\\prime}}2\\mathrm{H^{+}}+2\\mathrm{e^{-}}\\rightarrow\\mathrm{H}_{2},$ HER) is an ideal model reaction for introducing the aforementioned advanced methodology to the field of electrocatalysis. HER generates solely the desired product and is being considered as a cornerstone reaction in exploring the mechanism of more complex multielectron transfer processes.15-16 Practically, HER is also an essential reaction in the photoelectrochemical (PEC) water splitting for hydrogen production.17-18 In contrast to the traditional steam reforming of natural gas, the generation of clean hydrogen fuel from water is a potential route toward a sustainable energy future. Although commercial technologies of alkaline electrolysis offer mild conditions and higher system efficiency than acidic proton exchange membrane electrolysis, the reaction rate of HER in alkaline solutions is \\~two to three orders of magnitude lower than that in acidic solutions.19 More importantly, in the promising PEC water splitting technology, the best oxygen evolution reaction (OER) electrocatalysts used as counter electrodes work well only in basic or neutral media.18, 20-21 Therefore, the development of HER catalysts suitable for alkaline solutions is crucial. \n\nCurrently, the fundamental studies of HER are mainly conducted under acidic conditions due to its relative simple reaction pathway. The activity origin and trend for a wide variety of metallic electrocatalysts has been successfully constructed.14, 16, 22-23 However, the overall comprehension of the HER process in alkaline solutions is very limited, mainly on monocrystalline and polycrystalline Pt surfaces19, 24-25. As a result, the molecular design and practical development of efficient electrocatalysts for this key but sluggish process has been largely hindered. Evidently, Pt shows an “incomparable” HER activity in alkaline solutions while all welldeveloped cost-effective alternatives, including high-surface area \n\nRaney Ni and nickel molybdenum alloy, still cannot match the activity of Pt.26-27 However, its scarcity and high cost cannot afford a sustainable hydrogen generation. \n\nHerein we present the identification of an anomalously structured Ru catalyst, with one-twenty fifth (1/25) price of Pt metal, that shows 2.5 times higher hydrogen evolution turnover frequency (TOF) under alkaline conditions than the state-of-the-art $\\mathrm{Pt/C}$ catalyst. Density functional theory (DFT) computation and electrochemical reaction rate measurements were conducted to evaluate the newly developed Ru catalyst by linking its extrinsic crystalline structure with intrinsic reaction energetics in hydrogen evolution process. Based on the elucidation of poorly known nature of HER in alkaline media, here we reveal for the first time the origin of highest HER activity of this cost-effective catalyst in comparison to all previously reported precious metals, non-precious metals, and non-metallic materials. \n\n# EXPERIMENTAL AND COMPUTIONAL METHODS \n\nMaterials synthesis. Firstly, a specified amount of diluted $\\mathrm{RuCl}_{3}$ aqueous solution (0.005 M) was mixed with dicyandiamide (DCDA) to make a homogeneous solution; namely, $80\\mathrm{mL}$ of $\\mathrm{\\RuCl_{3}}$ aqueous solution and $_\\textrm{1g}$ of DCDA solid were used to achieve the resultant Ru-graphitic carbon nitride complex supported on carbon $\\left(\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}\\right)$ containing ${\\sim}20$ wt. $\\%$ of metallic $\\mathtt{R u}$ (confirmed by thermogravimetric analysis as shown in Figure S1), which is comparable with 20 wt. $\\%$ of metallic $\\mathrm{Pt}$ in commercial $\\mathrm{Pt/C}$ benchmark. Then the mixture was concentrated using rotary evaporator and dried using freeze dryer. The collected dark powder was then annealed under argon atmosphere at $600^{\\circ}\\mathrm{C}$ for $^\\textrm{\\scriptsize1h}$ at a heating rate of $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{\\cdot1}$ . In the presence of Ru catalyst, most of the DCDA precursor did not follow the rational reaction path of polycondensation to obtain periodic $\\mathrm{g-C_{3}N_{4}}$ matrix but was converted to nitrogen doped carbon, as confirmed by the carbon Kedge near edge X-Ray absorption fine structure (NEXAFS) results. \n\nPure Ru supported on carbon $\\mathrm{(Ru/C)}$ was prepared by mixing 0.005 $\\mathrm{\\bfMRuCl}_{3}$ aqueous solution with oxidized commercial carbon black. Then, the mixture was dried and annealed using the same procedure as in the synthesis of $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C},$ and used as a control sample. Commercial platinum carbon ( $\\mathrm{Pt/C}$ with 20 wt. $\\%\\ \\mathrm{Pt}\\$ ), iridium carbon $\\mathrm{{Ir/C}}$ with $20\\mathrm{wt.}\\%\\mathrm{Ir}$ , palladium carbon $\\mathrm{Pd}/\\mathrm{C}$ with 20 wt. $\\%$ Pd), gold carbon $\\mathrm{\\Au/C}$ with 20 wt. $\\%$ Au) catalysts were purchased from Fuel Cell Store without any further treatment. \n\nMaterial Characterization. Scanning transmission electron microscopy (STEM) and transmission electron microscopy (TEM) images and electron diffraction patterns were collected on a cubed Titan G2 80-300 Field-Emission-Gun Electron Microscope equipped with a Fischione model 3000 High-Angle-Annular-DarkField (HAADF) detector and a CEOS GmbH double-hexapole spherical-aberration corrector operating at $300\\mathrm{kV}.$ . A probe semiconvergence angle of 24.9 mrad was used for STEM imaging. Some raw HAADF-STEM images were processed by masking diffraction spots in the fast-Fourier transforms of the original images and then back-transforming using Gatan Digital Micrograph. \n\nThe NEXAFS measurements were carried out in an ultrahigh vacuum chamber $(\\sim10^{-10}$ mbar) of the undulator soft X-ray spectroscopy beamline at the Australian Synchrotron. The samples were dispersed in deionized water and then deposited and dried on Au plates. The raw NEXAFS data were normalized to the photoelectron current of the photon beam, measured on an Au grid. The C K-edge spectra were double-corrected to remove the influence from adsorbed carbon on the optics and detector. \n\nElectrochemical Testing Setup. The as-prepared powder was first ultrasonically dispersed in distilled water (Milli-Q) containing 0.05 wt. $\\%$ of Nafion. $20~\\upmu\\mathrm{L}$ of aqueous dispersion of the catalyst (2.0 $\\mathrm{mg/mL}$ ) were then transferred onto the glassy carbon rotating disk electrode (RDE, $0.196\\mathrm{cm}^{2}$ , Pine Research Instrumentation) serving as a working electrode. The reference electrode was an $\\mathrm{Ag/AgCl}$ in $4\\mathrm{MKCl}$ solution and the counter electrode was a graphite rod. All potentials were referenced to reversible hydrogen electrode (RHE) by using pure hydrogen calibration and all polarization curves were corrected for the iR contribution within the cell. During experiments a flow of $\\mathrm{\\bfN}_{2}$ was maintained over the electrolytes used: $0.5\\mathrm{MH}_{2}\\mathrm{SO}_{4},$ , or 0.1 M KOH solution. The working electrode was rotated at $^{1,600}$ rpm to remove hydrogen gas bubbles formed at the catalyst surface. \n\nComputational Methods and Models. The electronic structure computation was conducted by using VASP code.28-31 To describe the electron-core interaction, the projector-augmented wave (PAW) method was utilized within the frozen-core approximations for Ru and $\\mathrm{Pt.}^{32\\cdot33}$ For electron exchange-correlation, the PerdewBurke-Ernzerhof (PBE) functional within the generalized-gradient approximation (GGA) range was applied.34-35 The cut-off energies for plane waves were chosen to be $400\\mathrm{eV}$ based on the convergence test on $\\mathtt{R u}_{\\mathtt{h c p}}3\\times3$ supercell and $5\\times5~\\mathrm{Ru}+\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ supercell. The convergence tolerance of force on each atom during structure relaxation was set to be $0.01\\ \\mathrm{eV}/\\mathrm{\\AA}$ and all atoms were allowed to relax. Spin-polarization effect was considered in all cases. To better describe the dispersion interaction within water adsorption systems, vdW correction was considered by adopting the Grimme’s D2 scheme.36 The parameters for ${\\mathrm{Ru,O,}}$ and H are the default values given by VASP 5.3, and those for $\\mathrm{Pt}$ are $C_{6}=4.43$ J $\\cdot\\mathrm{nm}^{6}{\\cdot}\\mathrm{mol}^{-1}$ and ${\\mathrm{R}}_{0}$ $=1.772\\mathring{\\mathrm{A}}^{37}$ The cut-off radius (Å) for pair interactions among D2 scheme is set to be $20\\textup{\\AA}$ to avoid interactions between different layers, with global scaling factor set to be $0.750\\mathrm{\\AA}.$ The optimized lattice parameters for hexagonal-close-packed Ru $\\left(\\mathbf{a}=\\mathbf{b}=2.73\\mathrm{\\AA},\\mathrm{c}\\right.$ $=4.31\\mathring{\\mathrm{A}},$ ), face centered cubic $\\mathrm{Ru}\\left(3.82\\AA\\AA\\right)$ , and face centered cubic Pt (3.97 Å) structures agree well with previous computation studies.38-41 The K-point for all three metal $\\left(1\\times1\\right)$ single cell, $({\\sqrt{3}}\\times$ $\\sqrt{3})$ reconstructed surface, $(1\\times1$ ) $\\mathrm{g-C_{3}N_{4},}$ and $(5\\times5)$ metal with (2 $\\times2$ ) $\\mathrm{g-C_{3}N_{4}}$ was set to be $15\\times15\\times15,9\\times9\\times1,$ , $5\\times5\\times1$ , and $1\\times$ $1\\times1$ , respectively. \n\nThe calculation of adhesion energy between Ru and $\\mathrm{g-C_{3}N_{4}}$ was modelled for three layers of Ru slab, one layer of $\\mathsf{g}–\\mathsf{C}_{3}\\mathrm{N}_{4},$ and a $16\\mathrm{\\AA}$ vacuum layer to separate the interaction between periodic images. This supercell structure contains a $(5{\\times}5)$ lattice of $\\mathrm{Ru}_{\\mathrm{hcp}}(0001)$ or $\\mathrm{Ru}_{\\mathrm{fcc}}(111)$ primitive cells matched to $(2{\\times}2)$ lattice of repeating $g_{^{-}}$ $\\mathrm{C_{3}N_{4}}$ primitive cells. Three configurations with different relative position between metals and $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ were investigated, i.e., FCC, HCP, and TOP positions, according to the position of $\\mathrm{{C}_{6}\\mathrm{{N}_{7}}}$ rings in $\\mathrm{g-C_{3}N_{4}}$ matrix on the top layer of Ru atoms. The calculation of adhesion energy between $\\mathtt{R u}$ and carbon was modelled by three layers of $(1\\times1)$ $\\mathrm{Ru}_{\\mathrm{hcp}}(0001)$ or $\\mathrm{Ru}_{\\mathrm{fcc}}(111)$ and one layer of $(1\\times1)$ graphene to represent carbon black. Similarly, three relative configurations were studied due to the lattice mismatch between $\\mathtt{R u}$ and graphene, as in the previous work.42 More computational details about free energy diagram, water dissociation pathway, and $\\mathrm{H}_{2}$ recombination pathway can be found in supporting information. \n\n# RESULTS AND DISCUSSION \n\nStructural identification. The as-synthesized $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ product shows a homogeneous dispersion of $\\mathtt{R u}$ nanoparticles with an average size of $2\\mathrm{nm}$ on the $\\mathrm{g{-}C_{3}N_{4}/C}$ support (Figure S2). Note that we did not carry out the conventional synthesis of precious metal nanoparticles involving bulky capping, structure-directing, or reducing agents etc. The formation of homogeneous particle size of Ru was achieved by taking advantage of strong interaction (discussed later) between Ru metal and $\\mathrm{g-C_{3}N_{4}}$ support that has a periodically regular molecular structure. The HAADF-STEM images provide more structural information about these Ru nanoparticles (Figure 1a, c, e). Normally, the majority of metals show only its most stable crystalline structure: either a face centered cubic $\\left(\\mathit{t c c}\\right)$ , a body centered cubic $(b c c)$ , or a hexagonal close packed $\\left(h c p\\right)$ structure. The structure transition can only be achieved under some extreme conditions e.g. temperature and/or pressure and may lead to some unique electrical, magnetic and catalytic properties as compared with the most stable structures under ambient conditions.43-45 Ru as a 4d transition metal possesses an hcp structure, as reported in most experimental and theoretical studies.46- 48 \n\n![](images/a9ec6d97e98563c8adc57eb3eb05a98e26f4316cef6f9588df2cbda0fbedc468.jpg) \nFigure 1. (a, c, e) HAADF-STEM images and the $(\\boldsymbol{\\mathrm{b}},\\boldsymbol{\\mathrm{d}},\\boldsymbol{\\mathrm{f}})$ corresponding FFT patterns of Ru nanoparticles showing (a) fc ; (c) mixed $\\mathit{t c c}/h c p;$ and (e) hcpstructure. The red and blue dots in panels a, c, e mark the typical atomic arrangements of $f c c$ and hcpstructures along different zone axes. The green circles in panel d inset indicate the shared diffraction plans of thefc andhcpstructures. \n\nInterestingly, the typical atomic resolution HAADF-STEM images of individual Ru nanoparticles in $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ catalyst were used to unambiguously identify a typical [100]f oriented fc mono-phase, a $[110]_{\\mathrm{f}}/[11\\overline{{2}}0]_{\\mathrm{h}}$ oriented intergrown hcp/fc phase sharing the $(0001)_{\\mathrm{h}}/(111)_{\\mathrm{f}}$ interface, and a $[0001]_{\\mathrm{h}}$ oriented hcpmono-phase, respectively. These results are further supported by the indexed fast Fourier transform (FFT) diffractograms (Figure 1b, d, f) and high resolution TEM images (Figure S3). In addition, in comparison with $\\mathrm{Ru/C}$ control sample that only demonstrates hcpRu crystal on the electron diffraction patterns (Figure S4), $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ shows extra intensity at $\\sim7.3\\ \\mathrm{nm^{-1}}$ that can be assigned to the (022) reflection of the $\\scriptstyle f c c\\mathrm{{Ru}}$ crystal. Given the difference between two materials is the existence of $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{4},{}^{49}$ we assume that $\\mathrm{g-C_{3}N_{4}}$ as the support allows for the growth of anomalous face-centered-cubic Ru lattice structure. Similarly to Kitagawa et al. report on the formation of multiply-twinned Ru particles based on the “nanosize” effect,46 our study shows clearly that the anomalous Ru structures exist in the case of small nanosized particles confined by the $\\mathrm{g-C_{3}N_{4}}$ phase. \n\nAdhesion energy calculation. To validate the above assumption, the DFT calculated adhesion energies $\\left(\\Delta\\mathrm{E_{adh}}\\right)$ between two specific Ru nanostructures and $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ substrate were used to quantitatively describe the formation mechanism of anomalous Ru crystalline structure (Figure 2a, Figure S5, Table S1). For comparison purposes, the values of $\\Delta\\mathrm{E}_{\\mathrm{adh}}$ between Ru and pure carbon layer represented by graphene were also computed (Figure S6, Table S1). For standalone Ru slabs, thehcpstructure is more stable than the $f c c$ one with an energy difference of $0.06\\ \\mathrm{eV}$ per Ru atom, which is in good agreement with previous experimental observations.46-48 Conversely, as shown in Figure 2b (dashed bars), the $\\Delta\\mathrm{E_{adh}}$ calculated for $f c c$ structured Ru $\\left(\\mathrm{Ru}_{\\mathrm{fcc}}\\right)$ on the $\\mathrm{g-C_{3}N_{4}}$ substrate is nearly $4\\mathrm{eV}$ ( $0.15\\mathrm{eV}$ per Ru atom on the top layer) higher than that of hcpstructured Ru $\\mathrm{\\langleRu_{hcp}\\rangle}$ , confirming the stabilizing effect of $g_{^{-}}$ $\\mathrm{C_{3}N_{4}}$ toward formation of $\\mathrm{Ru}_{\\mathrm{fcc}}$ achieved by enhanced metalsubstrate interactions. On the other hand, such tendency was not observed in the case of a carbon substrate, on which the ${\\mathrm{Ru}}_{\\mathrm{hcp}}$ structure is more energetically favourable than $\\mathrm{Ru}_{\\mathrm{fcc}}$ as indicated by larger $\\Delta\\mathrm{E_{adh}}$ (Figure 2b solid bars). Thus, $\\mathrm{g-C_{3}N_{4}}$ acts as a promoter that can facilitate the formation of anomalous $f c c$ crystalline Ru structure. This theoretically predicted result agrees with the experimental data \n\n![](images/9fd55f824e9c4537c102b8e1d49104aab9012cb079f414c030237ad39ec7980b.jpg) \nFigure 2. (a) Atomic configurations (tops) and side views of the electron difference (bottoms) of $\\mathrm{g-C_{3}N_{4}}$ $(2{\\times}2)$ and Ru $(5{\\times}5)$ layers with $f c c$ structure. Colour codes: Deep blue, light blue and pink denote the top, middle and bottom layer of $\\mathtt{R u}$ atoms, respectively; green and yellow denote carbon and nitrogen atoms in $\\mathrm{g-C_{3}N_{4}}$ layer, respectively. (b) \n\nComparison of the adhesion energy between carbon $\\mathrm{'g-C_{3}N_{4}}$ and Ru layers with fc orhcpstructure. \n\nshowing that there is a certain amount of $f c c$ crystalline Ru in the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ composite while only solehcpphase exists in the $\\mathrm{Ru}/\\mathrm{C}$ control sample (Figure S4). Besides crystalline, the rich functional groups in $\\mathrm{g-C_{3}N_{4}}$ molecular skeleton (e.g., triazine, amine, etc.) may also modulate the growth of Ru nanoparticles, resulting in a more uniform distribution and smaller size than those grown on clean carbon surfaces (Figure S2). \n\nChemical characteristics of $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ . NEXAFS spectroscopy was used to precisely detect intramolecular interactions between Ru and $\\mathrm{g-C_{3}N_{4}}$ as demonstrated by the DFT calculations. In the C Kedge region (Figure 3a), the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ catalyst mainly shows the characteristic resonances of $\\pi^{*}{\\bf{\\Psi}}_{\\mathrm{C-N-C}},$ and $\\pi^{*}{\\mathrm{c}}{=}\\mathrm{C},\\pi^{*}{\\mathrm{c}}{\\mathrm{-}}\\mathrm{N}$ originating from $\\mathrm{g-C_{3}N_{4}}$ and nitrogen-doped carbon (N-carbon) supports (the identification of each characteristic resonance can be referred to Figure 3 caption). This not only confirms the existence of N-carbon in $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ composite but also indicates that Ru has no noticeable effect on the chemical environment of carbon. In the N K-edge region (Figure 3b), besides expected pyridinic and graphitic nitrogen species’ resonances from N-carbon individual component, the C–N–C coordination in $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ was preserved while the original bridging N resonance in $\\mathrm{g-C_{3}N_{4}}$ was weakened and accompanied by a group of new peaks in the lower photon energy zone (the identification of each characteristic resonance can be referred to Figure 3b caption). These new nitrogen resonances can be assigned to the interaction of Ru with bridging N–3C species of $\\mathrm{g-C_{3}N_{4}}$ with different coordination. As a result, nitrogen atoms accept extra charges from Ru atom, resulting in a negative shift in its photon energy profile. \n\n![](images/d398dc607b71fafd699246b45b8cc9b7764ca8a0f382fa3df54af1c2c012f396.jpg) \nFigure 3. C K-edge and N K-edge NEXAFS spectra of $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ electrocatalyst, pure $\\mathrm{g-C_{3}N_{4}}$ and N-carbon reference samples. In C Kedge, defects at ${\\sim}283~\\mathrm{eV}$ in all three materials are assigned to lowcoordinated carbon atoms at the edges of $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ and N-carbon moieties. The resonances of $\\overleftarrow{\\pi}^{*}$ at $288.2\\mathrm{eV}$ are assigned to C-N-C species in $\\mathsf{g}–\\mathsf{C}_{3}\\mathrm{N}_{4}$ while the resonances of $\\pi^{*}$ at $285.0\\mathrm{eV}$ and $\\pi^{*}$ at $288.7\\mathrm{eV}$ are assigned to $C{=}C$ and C-N species in N-carbon. In N K-edge, the resonances of $\\pi^{*}$ at $398.6~\\mathrm{eV}$ and $401.5\\ \\mathrm{eV}$ are assigned to nitrogen species in the form of pyridine $\\left(\\mathrm{C}{\\cdot}\\mathrm{N}(\\mathfrak{p})\\right)$ and graphite $\\left(\\mathrm{C}\\mathrm{-}\\mathrm{N}(\\mathbf{g})\\right)$ structures in N-carbon. The resonances of $\\pi^{*}$ at $399.7\\mathrm{eV}$ and $402.6\\mathrm{eV}$ are assigned to the aromatic C–N–C coordination of tri-s-triazine and the $_{\\mathrm{N}-3\\mathrm{C}}$ bridging among three tri-s-triazine moieties $\\left(\\mathbf{C}\\mathbf{-}\\mathbf{N}(\\mathbf{b})\\right)$ in $g_{^-}$ $\\mathrm{C}_{3}\\mathrm{N}_{4}$ . \n\nElectrocatalytic activity comparison. The electrocatalytic properties of the newly identified $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ electrocatalyst were evaluated and compared to the conventional $\\mathrm{Ru/C}$ and the state-of-the-art $\\mathrm{Pt/C}$ electrocatalysts under alkaline conditions. The polarization curves of three electrocatalysts recorded in $0.1\\mathrm{~M~}$ KOH solution show an increase in the HER activity (on the overpotential basis) in the following order: $\\mathrm{Ru}/\\mathrm{C}<\\mathrm{Pt}/\\mathrm{C}<\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ (Figure $4\\mathrm{a}$ ). The normalized (with respect to the electrode’s geometrical area) exchange current density $\\left(j_{0}\\right)$ values obtained from Tafel plots also follow the same trend (Figure 4b). As read from Figure $4\\mathrm{a}$ , a small overpotential of $79~\\mathrm{mV}$ was required for achieving a $10\\mathrm{\\mA\\cm^{-2}}$ cathodic current density (such current density was chosen as a metrics for the comparison with solar hydrogen production) by the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ sample. This value is not only much smaller than that for some non-precious metal HER electrocatalysts like WC, ${}^{50}\\mathrm{Ni}_{2}\\mathrm{P},{}^{5}$ 1 $\\mathbf{Mo}_{2}\\mathbf{C},^{52}$ but, more strikingly, superior as compared to the values obtained for all reported pure and nanostructured precious metals like $\\mathrm{Pt},^{53}\\mathrm{Au},^{53-54}\\mathrm{Ir},^{53}\\mathrm{Pd},^{54}$ and Ru itself 53 under the same conditions (Figure $_{4c}$ , Figure $S7a$ ). We note that the performances of individual metal-free components $\\mathrm{g-C_{3}N_{4},}$ N-carbon and their hybrid are ignorable as compared with Ru-containing catalyst, $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ (Figure S8); therefore, a significant enhancement in its activity in comparison to that of the $\\mathrm{Ru/C}$ control sample can be solely attributed to the presence of anomalous $\\mathit{f c c}$ crystalline Ru nanoparticles. \n\n![](images/918e90756cc7f98164c0db3f75482b046225c799fa611fc2237495986e305d03.jpg) \nFigure 4. (a) HER polarization curves and (b) corresponding Tafel plots of the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C},$ conventional $\\mathrm{Ru}/\\mathrm{C}$ and commercial $\\mathrm{Pt/C}$ electrocatalysts recorded in $\\mathbf{N}_{2}$ -purged $0.1\\mathrm{~M~}$ KOH solutions. The dashed lines in panel is a guide for the eye to calculate j0 by the linear fitting of Tafel plots. In panel a, the underpotential hydrogen adsorption effect in the case of precious metals and the capacitance effect in the case of nanocarbons make that the current start points are not zero. (c) \n\nComparison of the overpotential values required to achieve a $10\\mathrm{mAcm^{.}}$ 2 cathodic current densities and (d) TOF values at $100\\mathrm{mV}$ overpotential in alkaline solutions for various nanostructured precious metal electrocatalysts on carbon support. (e) The relationship between TOF and the measured potentials for the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ and commercial $\\mathrm{Pt/C}$ electrocatalysts in 0.1 M KOH solutions. The benchmark was accorded to the metallurgically prepared commercial Ni−Mo alloys.27 (f) Currenttime (i-t) chronoamperometric response of $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ electrocatalyst at overpotential of $50~\\mathrm{mV}.$ Inset represents HER polarization curves recorded before and after 1,000 potential sweeps ( $_{+0.2}$ to $-0.6\\mathrm{V}$ versus RHE) in 0.1 M KOH solution. \n\nTOF analysis. To eliminate the contributions originating from different particle sizes and surface areas of electrocatalysts to the measured HER activity, we calibrated the electrochemically active surface area (ECSA) of the newly developed $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ and a series of precious metal electrocatalysts by well-established cyclic voltammetry method (Figure S9), which has been successfully validated on Ru electrodes surfaces.55-56 Afterwards, the turnover frequency (TOF), the best figure-of-merit used for comparative evaluation of the catalytic activities of different catalysts, can be explicitly calculated based on the current density obtained from the polarization curve. As expected, TOF value increases with the overpotential following the Tafel behaviour for all samples. As shown in Figure 4d, at an overpotential of $100\\mathrm{mV},$ , the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ electrocatalyst exhibits an extremely high TOF of $4.2\\ \\mathrm{s^{-1}}$ , which is larger than that of most commercial precious metal/carbon nanocomposites. Note that the price of Ru metal is at least 10 times cheaper than other precious metals, which is advantageous for the large scale commercialization in future (Table S2). Moreover, the TOF value obtained for $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ was also compared with other benchmarked electrocatalysts: it is 60 times larger than that on $\\mathrm{Ni}_{5}\\mathrm{P}_{4}$ catalyst $(0.06s^{-1}),^{57}80$ times larger than that on Ni-Mo catalyst (0.05 $s^{-1}),\\AA^{27}$ and most importantly, 2.5 times larger than that on currently the most active $\\mathrm{Pt/C}$ catalyst under the same conditions (Figure 4e). \n\nAdditionally, the strong interactions of Ru nanoparticles with $g_{^{-}}$ $\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ support as confirmed by both experimental and theoretical studies prevent its aggregation during long term reaction. This assures high HER operational stability of the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ electrocatalyst in alkaline solutions with a very slow attenuation after 50 hours (Figure 4f). The accelerated durability test (ADT) also revealed its reliable stability with a very small negative shift of the HER polarization after 1,000 continuous potential cycles (Figure 4f inset). \n\nCrystal structure sensitivity in electrocatalysis under different conditions. As shown in Figure 5a, the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ also is applicable under acidic conditions, in which the activity is higher than in alkaline solutions. This trend also agrees with other reports on $\\mathrm{Pt/C}$ materials.21, 24 The activity differences in acid and alkaline solutions can be attributed to the nature of reaction pathway in each type of solution, which will be discussed in details later. Additionally, the TOF values of $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ are always higher than that of the $\\mathrm{Ru/C}$ control sample under the same conditions (Figure 5a, b). This trend is more obvious at high $\\mathsf{p H}$ values than at low $\\mathrm{\\ttpH}$ values. For example, the TOF difference between $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ and $\\mathrm{Ru/C}$ in acidic solutions is $0.38\\ \\mathrm{s^{-1}}$ at an overpotential of $100\\mathrm{mV}$ ( $\\cdot0.05\\ s^{-1}$ at an overpotential of $50~\\mathrm{mV}$ ), while this value is as large as $2.25~\\mathrm{s^{-1}}$ at an overpotential of $100\\mathrm{mV}$ ( $0.45\\ \\mathrm{s^{-1}}$ at an overpotential of $50~\\mathrm{mV}$ ) in alkaline solutions. Given that the most noticeable difference between these two kinds of catalysts is the crystalline structure of Ru (after ECSA normalization), we attribute the observed difference in the catalytic activities to the Ru crystal structure sensitivity under different testing conditions. \n\nSuch the lattice structure-induced enhancement in the catalytic activity under specific conditions is also reflected between $\\mathrm{Pt/C}$ and $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ samples. Judged from both overpotential and TOF bases, $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ shows smaller HER activity than that of $\\mathrm{Pt/C}$ under acid conditions while reversely shows better activity under alkaline conditions (Figure 5c,d). As can be also seen the activity differences for $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ electrocatalyst in acid and alkaline solutions are small, which is rarely observed on other electrocatalysts because the reaction rate of HER in alkaline solutions is usually ${\\sim}2$ to 3 orders of magnitude lower than that in acidic solutions (for example, on Pt surface).21 Therefore, we assume the reversible activity trend in acid and alkaline solutions should be attributed to some critical but unknown factor(s) that govern the overall reaction rate on each electrocatalyst surface. \n\n![](images/ca4ef52f8604d522c5c94d2c3643406c4d1f3d9118c64627bd82ecc40afc3e87.jpg) \nFigure 5. $(\\mathbf{a},\\mathbf{b}),$ The relationship between TOF values and the measured potentials for $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ and conventional $\\mathrm{Ru}/\\mathrm{C}$ electrocatalysts under various conditions. (c) Polarization curves and (d) the relationship between TOF values and the measured potentials for the $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ and $\\mathrm{Pt/C}$ electrocatalysts under various conditions. \n\nOrigin of the enhanced activity of $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ We performed DFT computations related to the thermodynamics and kinetics of HER on different metal surfaces to reveal the observed activity difference and the origin of the superior activity of $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ in alkaline solutions (Figure 6). Ru slabs with both $\\mathrm{Ru_{hcp}}$ (0001) and $\\mathrm{Ru}_{\\mathrm{fcc}}$ (111) planes were modelled to represent conventional $\\mathtt{R u}$ in $\\mathrm{Ru}/\\mathrm{C}$ and the newly identified anomalous $\\mathtt{R u}$ in $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ sample, respectively; Pt slab with (111) plane that represents the $\\mathrm{Pt/C}$ sample was also studied for the purpose of comparison.13, 47 Even though the computed structured surfaces cannot fully represent the experimentally synthesized metal nanoparticles with various facets, corners, and edges, these specific planes were selected because they are among the most commonly observed and most respective ones in both experiments and theoretical modelling studies.14, 47, 58 \n\nOn all selected metal surfaces, we constructed the reaction pathway for HER including bilayer adsorption of $_\\mathrm{H_{2}O}$ , dissociation of water to form adsorbed H $\\left(\\mathrm{H}^{*}\\right)$ , combination of $\\boldsymbol{\\mathrm{H^{*}}}$ with proton from adjacent $_\\mathrm{H_{2}O}$ to form adsorbed $\\mathrm{H}_{2},$ and desorption of $\\mathrm{H}_{2}$ from the surface. 21 As shown in Figure 6a, among all three metal surfaces, Pt shows the optimal level for H adsorption step with a free energy $(\\Delta\\mathrm{G}_{\\mathrm{~\\tiny~H^{*}}}^{\\mathrm{Pt}})$ value of $-0.02\\mathrm{eV},$ , while $\\mathrm{Ru}_{\\mathrm{hcp}}$ and $\\mathrm{Ru}_{\\mathrm{fcc}}$ surface exhibit more negative values with $\\Delta\\mathrm{G}^{\\mathrm{Ru\\mathrm{-}h c p}}\\mathrm{_H\\mathrm{*}}=-0.83\\mathrm{\\eV}$ and $\\Delta\\mathrm{G^{\\mathrm{Ru\\cdotfcc}}}_{\\mathrm{H^{*}}}=-0.48\\mathrm{eV},$ respectively. Therefore, from the thermodynamic point of view, Pt should demonstrate the best hydrogen evolution activity among these three metal structures. The calculated $\\Delta G_{\\mathrm{H^{*}}}$ values on the respective metal surfaces can be correlated with their electronic structures via the d-band centre theory to reveal the origin of their reactivity (Figure S10).59 The general trend is that with a low position d-band such as in the case of Pt, the hydrogen adsorption is weak; while for a metal with a higher d-band position, such as ${\\mathrm{Ru}}_{\\mathrm{hcp}},$ the hydrogen binding is strong thus resulting in more negative $\\Delta G_{\\mathrm{H^{*}}}$ and is not thermodynamically favourable for $\\mathrm{H^{*}}$ desorption process in the Heyrovsky step. \n\nHowever, the above theoretical investigation based only on adsorption energetics can hardly meet with the experimental observation: comparing with $\\mathrm{Pt/C}$ , a larger j0 value was observed on $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ sample, which is represented by the ${\\mathrm{Ru}}_{\\mathrm{fcc}}$ slab with a relatively stronger $\\boldsymbol{\\mathrm{H^{*}}}$ adsorption (Figure 6b).When the kinetics of water dissociation from the Volmer step is considered, as shown in Figure 6a (curved lines), the Pt surface exhibits a significant energy barrier $\\mathrm{'}\\Delta G_{\\mathrm{B}}=0.94\\ \\mathrm{eV},$ , substantively higher than that on $\\mathrm{Ru}_{\\mathrm{fcc}}$ $\\langle\\Delta\\mathrm{GB}=0.41~\\mathrm{eV}\\rangle$ and $\\mathrm{Ru}_{\\mathrm{hcp}}$ $\\mathrm{'}\\Delta\\mathrm{GB}=0.51\\ \\mathrm{eV},$ (Table 3, Figure S11, 12). Therefore, from the kinetic viewpoint, conversely, Pt demonstrates the most sluggish water dissociation among the three metal structures studied. Note that this water dissociation issue does not exist under acidic conditions;14 therefore Pt shows an extremely high activity in acid solutions, owing to its optimal $\\Delta\\mathrm{G}_{\\mathrm{H}},$ value. \n\nWe conducted further computation work to obtain energy barrier values for the following $\\mathrm{H}_{2}$ formation process by Heyrovsky mechanism on Ru surfaces. As shown in Figure S13, the energy barrier for Heyrovsky step on $\\mathrm{Ru}_{\\mathrm{fcc}}$ is $0.48\\mathrm{eV}$ while that on $\\mathrm{Ru}_{\\mathrm{hcp}}$ is $0.40\\ \\mathrm{eV}$ (Figure S13). These easily surmountable barrier values indicate that the Heyrovsky step is kinetically viable and not serve as the limiting step for the overall reaction. \n\n![](images/04d5bf54b889643153222e5f7ba0213228dc5d63ee1d48e210c0e6aeb465e844.jpg) \nFigure 6. (a) Gibbs free energy diagram of HER on different surfaces including reactant initial state, intermediate state, final state, and an additional transition state representing water dissociation. $\\Delta G_{\\mathrm{H^{\\prime}}}$ indicates hydrogen adsorption free energy; $\\Delta G_{\\mathrm{B}}$ indicates water dissociation free energy barrier. (b) The relationship between the computed $\\Delta\\mathrm{G}_{\\mathrm{H^{*}}}$ or $\\Delta G_{\\mathrm{B}}$ values and the measured $j o$ values on various metal surfaces. (c) Atomic configurations of water dissociation step on the surface of Rufcc. Colour codes: deep blue, light blue and pink represent top, middle and bottom layer of Ru. Red and white represent oxygen and hydrogen atoms in single water molecule. Yellow represents the dissociated H atom that adsorbs on the metal surface. \n\nRegarding the overall HER rate, it is generally accepted that $\\Delta\\mathrm{G}_{\\mathrm{H^{*}}}$ could be employed to obtain the HER rate in acidic solutions based on the micro-kinetic model.14 This has also been validated by our computation done for selected models and by measurements performed on the synthesized electrocatalysts (Figure S14). However, with the identification of large energy barrier like water dissociation on Pt surface, the $\\Delta\\mathrm{G}_{\\mathrm{H^{*}}}$ value alone is hardly sufficient to describe the apparent HER activity in alkaline solutions. In this case, besides the formation of $\\mathrm{H^{*}}$ state, the water dissociation kinetics would also affect the overall reaction rate leading to the experimentally observed activity trend (Figure 6b). At this stage, association of the classical micro-kinetic model (applying $\\Delta G_{\\mathrm{H^{*}}}$ as an activity descriptor) with the newly considered transition state theory (applying ∆GB as an activity descriptor) gives a qualitative confirmation of the sluggish kinetics of hydrogen evolution in alkaline solutions on $\\mathrm{Pt/C}$ electrocatalyst, and more importantly, explains the underlying mechanism of the better catalytic activity of $\\mathrm{Ru}_{\\mathrm{fcc}}$ present in $\\mathrm{Ru}/\\mathrm{C}_{3}\\mathrm{N}_{4}/\\mathrm{C}$ electrocatalyst. \n\n# CONCLUSION \n\nUsing hydrogen evolution as a probe reaction, we correlated the apparent catalytic activity of a cost-effective but highly efficient Ru electrocatalyst with its anomalous crystalline structure and inherent reaction energetics. By identifying significant influence of water dissociation on the overall HER activity of different metal surfaces, we elucidated the poorly studied HER process in alkaline media through the association of the classical micro-kinetic model with the transition state theory. Both experimental data and theoretical computation demonstrate that a special kind of carbon-based material (e.g., $\\mathrm{g-C_{3}N_{4}},$ ) can induce an anomalous crystalline structure of a transition metal $(\\mathrm{e.g.,\\Ru)}$ with having very high catalytic activity. Therefore, this study opens a new avenue for the design of a wide variety of solid catalysts for broader heterogeneousand electrocatalytic applications. \n\n# ASSOCIATED CONTENT \n\nSupporting Information. More materials characterization, electrochemical measurements, computational results. This material is available free of charge via the Internet at http://pubs.acs.org. \n\n# AUTHOR INFORMATION \n\nCorresponding Author \\* s.qiao@adelaide.edu.au \n\n# Author Contributions \n\n‡These authors contributed equally. \n\n# Notes \n\nThe authors declare no competing financial interests. \n\n# ACKNOWLEDGMENT \n\nThe authors gratefully acknowledge financial support by the Australian Research Council (ARC) through the Discovery Project programs (DP160104866, DP140104062, DP130104459 and DE160101163). NEXAFS measurements were performed on the soft X-ray beamline at Australian Synchrotron. DFT calculations were carried out using the NCI National Facility systems through the National Computational Merit Allocation Scheme. \n\n# REFERENCE \n\n1. Nørskov, J. K.; Studt, F.; Abild-Pedersen, F.; Bligaard, T., Catalyst Structure. In FundamentalConceptsinHeterogeneousCatalysis, John Wiley & Sons, Inc: 2014; pp 138-149. \n2. Calle-Vallejo, F.; Loffreda, D.; KoperMarc, T. M.; Sautet, P., NatChem 2015, 7, 403-410. \n3. Norskov, J. K.; Bligaard, T.; Rossmeisl, J.; Christensen, C. H., NatChem 2009, 1, 37-46. \n4. Stamenkovic, V. R.; Fowler, B.; Mun, B. S.; Wang, G.; Ross, P. N.; Lucas, C. A.; Marković, N. M., Science2007, 315, 493-497. \n5. Somorjai, G. A.; Materer, N., Top.Catal.1994, 1, 215-231. \n6. Liu, J.-X.; Su, H.-Y.; Sun, D.-P.; Zhang, B.-Y.; Li, W.-X.,J.Am.Chem.Soc. 2013, 135, 16284-16287. \n7. Haruta, M.; Yamada, N.; Kobayashi, T.; Iijima, S.,J.Catal.1989,1 5, 301- 309. \n8. Medford, A. J.; Wellendorff, J.; Vojvodic, A.; Studt, F.; Abild-Pedersen, F.; Jacobsen, K. W.; Bligaard, T.; Nørskov, J. K., Science2014, 345, 197-200. 9. Behrens, M.; Studt, F.; Kasatkin, I.; Kühl, S.; Hävecker, M.; AbildPedersen, F.; Zander, S.; Girgsdies, F.; Kurr, P.; Kniep, B.-L.; Tovar, M.; Fischer, R. W.; Nørskov, J. K.; Schlögl, R., Science2012, 3 6, 893-897. 10. Jiao, Y.; Zheng, Y.; Jaroniec, M.; Qiao, S. Z.,J.Am.Chem.Soc.2014,136, 4394-4403. \n11. Jiao, Y.; Zheng, Y.; Jaroniec, M.; Qiao, S. Z., Chem.Soc.Rev.2015, 4 , 2060-2086. \n12. Marković, N. M.; Ross Jr, P. N., Surf.Sci.Rep.2002, 45, 117-229. 13. Nørskov, J. K.; Rossmeisl, J.; Logadottir, A.; Lindqvist, L.; Kitchin, J. R.; Bligaard, T.; Jónsson, H., J.Phys.Chem.B2004, 108, 17886-17892. \n14. Nørskov, J. K.; Bligaard, T.; Logadottir, A.; Kitchin, J. R.; Chen, J. G.; Pandelov, S.; Stimming, U., J.Electrochem.Soc.2005, 152, J23-J26. \n15. Conway, B. E.; Tilak, B. V., Electrochim.Acta2002, 47, 3571-3594. 16. Zheng, Y.; Jiao, Y.; Jaroniec, M.; Qiao, S. Z., Angew.Chem.Int.Ed.2015, 54, 52-65. \n17. Cook, T. R.; Dogutan, D. K.; Reece, S. Y.; Surendranath, Y.; Teets, T. S.; Nocera, D. G., Chem.Rev.2010, 1 0, 6474-6502. \n18. Walter, M. G.; Warren, E. L.; McKone, J. R.; Boettcher, S. W.; Mi, $\\mathrm{Q.;}$ Santori, E. A.; Lewis, N. S., Chem.Rev.2010, 1 0, 6446-6473. \n19. Rheinländer, P. J.; Herranz, J.; Durst, J.; Gasteiger, H. A.,J.Electrochem. Soc.2014, 161, F1448-F1457. \n20. Lewis, N. S.; Nocera, D. G., Proc.Natl.Acad.Sci.2006, 103, 15729- 15735. \n21. Durst, J.; Siebel, A.; Simon, C.; Hasche, F.; Herranz, J.; Gasteiger, H. A., Energ.Environ.Sci.2014, 7, 2255-2260. 22. Greeley, J.; Jaramillo, T. F.; Bonde, J.; Chorkendorff, I.; Norskov, J. K., NatMater2006, 5, 909-913. \n23. Tsai, C.; Chan, K.; Nørskov, J. K.; Abild-Pedersen, F., Surf.Sci.2015, 640, 133-140. \n24. Sheng, W.; Zhuang, Z.; Gao, M.; Zheng, J.; Chen, J. G.; Yan, Y., Nat Com un2015, 6, 5848. \n25. Markovica, N. M.; Sarraf, S. T.; Gasteiger, H. A.; Ross, P. N., J.Chem. Soc.,FaradayTrans.1996, 92, 3719-3725. \n26. Birry, L.; Lasia, A., J.Ap l.Electrochem.2004, 34, 735-749. \n27. McKone, J. R.; Sadtler, B. F.; Werlang, C. A.; Lewis, N. S.; Gray, H. B., ACSCatalysis2013, 3, 166-169. \n28. Kresse, G.; Furthmüller, J., Comp.Mater.Sci.1996, 6, 15-50. \n29. Kresse, G.; Hafner, J., Phys.Rev.B1993, 47, 558-561. \n30. Kresse, G.; Hafner, J., Phys.Rev.B1994, 49, 14251-14269. \n31. Kresse, G.; Furthmüller, J., Phys.Rev.B1996, 54, 11169-11186. \n32. Blöchl, P. E., Phys.Rev.B1994, 50, 17953-17979. \n33. Kresse, G.; Joubert, D., Phys.Rev.B1999, 59, 1758-1775. \n34. Perdew, J. P.; Burke, K.; Ernzerhof, M., Phys.Rev.Let.1996, 7 , 3865- 3868. \n35. Perdew, J. P.; Burke, K.; Ernzerhof, M., Phys.Rev.Let.1997, 78, 1396- 1396. \n36. Grimme, S., J.Comput.Chem.2006, 27, 1787-1799. \n37. Duverger, E.; Gharbi, T.; Delabrousse, E.; Picaud, F., PC P2014, 16, 18425-18432. \n38. Zheng, Y.; Jiao, Y.; Zhu, Y. H.; Li, L. H.; Han, Y.; Chen, Y.; Du, A. J.; Jaroniec, M.; Qiao, S. Z., Nat.Com un.2014, 5, 3783. \n39. Jiang, D.-E.; Du, M.-H.; Dai, S., J.Chem.Phys.2009, 130, 074705. 40. Radmilovic, V.; Gasteiger, H. A.; Ross, P. N.,J.Catal.1995, 154, 98-106. 41. Kitchin, J. R.; Nørskov, J. K.; Barteau, M. A.; Chen, J. G., J.Chem.Phys. 2004, 120, 10240-10246. \n42. Stradi, D.; Barja, S.; Diaz, C.; Garnica, M.; Borca, B.; Hinarejos, J. J.; Sanchez-Portal, D.; Alcami, M.; Arnau, A.; de Parga, A. L. V.; Miranda, R.; Martin, F., Phys.Rev.B2013, 8 , 245401 . \n43. Jacobs, K.; Zaziski, D.; Scher, E. C.; Herhold, A. B.; Paul Alivisatos, A., Science2001, 293, 1803-1806. \n44. Sun, S.; Murray, C. B.; Weller, D.; Folks, L.; Moser, A.,Science2000,287, 1989-1992. \n45. Kim, J.; Lee, Y.; Sun, S., J.Am.Chem.Soc.2010, 132, 4996-4997. 46. Kusada, K.; Kobayashi, H.; Yamamoto, T.; Matsumura, S.; Sumi, N.; Sato, K.; Nagaoka, K.; Kubota, Y.; Kitagawa, H., J.Am.Chem.Soc.2013, 135, 5493-5496. \n47. Feibelman, P. J., Science2002, 295, 99-102. \n48. Chen, G.; Zhang, J.; Gupta, A.; Rosei, F.; Ma, D.,NewJ.Chem.2014,38, 1827-1833. \n49. Thomas, A.; Fischer, A.; Goettmann, F.; Antonietti, M.; Muller, J.-O.; Schlogl, R.; Carlsson, J. M., J.Mater.Chem.2008, 18, 4893-4908. \n50. Fan, X.; Zhou, H.; Guo, X., ACSNano2015, 9, 5125-5134. \n51. Feng, L.; Vrubel, H.; Bensimon, M.; Hu, X., Phys.Chem.Chem.Phys. 2014, 16, 5917-5921. \n52. Ma, L.; Ting, L. R. L.; Molinari, V.; Giordano, C.; Yeo, B. S., J.Mater. Chem.A2015, 3, 8361-8368. \n53. Danilovic, N.; Subbaraman, R.; Strmcnik, D.; Chang, K.-C.; Paulikas, A. P.; Stamenkovic, V. R.; Markovic, N. M., Angew.Chem.Int.Ed.2012, 51, 12495-12498. \n54. Sheng, W.; Myint, M.; Chen, J. G.; Yan, Y., Energ.Environ.Sci.2013, 6, 1509-1512. \n55. Colmenares, L.; Jusys, Z.; Behm, R. J., Langmuir2006,2 , 10437-10445. 56. Green, C. L.; Kucernak, A., J.Phys.Chem.B2002, 106, 1036-1047. 57. Laursen, A. B.; Patraju, K. R.; Whitaker, M. J.; Retuerto, M.; Sarkar, T.; Yao, N.; Ramanujachary, K. V.; Greenblatt, M.; Dismukes, G. C., Energ. Environ.Sci. 015, $^{\\mathbf{\\alpha}}\\mathbf{\\mathcal{S}},$ 1027-1034. \n58. Wolfschmidt, H.; Paschos, O.; Stimming, U., Hydrogen Reactions on Nanostructured Surfaces. In FuelCel Science, John Wiley & Sons, Inc.: 2010; pp 1-70. \n59. Hammer, B.; Nørskov, J. K., Theoretical surface science and catalysis— calculations and concepts. In AdvancesinCatalysis, Academic Press: 2000; Vol. Volume 45, pp 71-129. \n\n![](images/9d1b56c2cd0958809f22e729016ecfdd8d3153954fca3cac5456c5429367a0c4.jpg) " + }, + { + "id": "10.1038_NMAT4463", + "DOI": "10.1038/NMAT4463", + "DOI Link": "http://dx.doi.org/10.1038/NMAT4463", + "Relative Dir Path": "mds/10.1038_NMAT4463", + "Article Title": "Tough bonding of hydrogels to diverse non-porous surfaces", + "Authors": "Yuk, H; Zhang, T; Lin, ST; Parada, GA; Zhao, XH", + "Source Title": "NATURE MATERIALS", + "Abstract": "In many animals, the bonding of tendon and cartilage to bone is extremely tough (for example, interfacial toughness similar to 800 J m(-2); refs 1,2), yet such tough interfaces have not been achieved between synthetic hydrogels and non-porous surfaces of engineered solids(3-9). Here, we report a strategy to design tough transparent and conductive bonding of synthetic hydrogels containing 90% water to non-porous surfaces of diverse solids, including glass, silicon, ceramics, titanium and aluminium. The design strategy is to anchor the long-chain polymer networks of tough hydrogels covalently to non-porous solid surfaces, which can be achieved by the silanation of such surfaces. Compared with physical interactions, the chemical anchorage results in a higher intrinsic work of adhesion and in significant energy dissipation of bulk hydrogel during detachment, which lead to interfacial toughness values over 1,000 J m(-2). We also demonstrate applications of robust hydrogel-solid hybrids, including hydrogel superglues, mechanically protective hydrogel coatings, hydrogel joints for robotic structures and robust hydrogel-metal conductors.", + "Times Cited, WoS Core": 912, + "Times Cited, All Databases": 986, + "Publication Year": 2016, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000368766100023", + "Markdown": "# Tough bonding of hydrogels to diverse non-porous surfaces \n\nHyunwoo $\\mathsf{Y u k}^{1},$ , Teng Zhang1, Shaoting Lin1, German Alberto Parada1,2 and Xuanhe Zhao1,3\\* \n\nIn many animals, the bonding of tendon and cartilage to bone is extremely tough (for example, interfacial toughness $\\sim800\\mathrm{J}\\mathrm{m}^{-2}$ ; refs 1,2), yet such tough interfaces have not been achieved between synthetic hydrogels and non-porous surfaces of engineered solids3–9. Here, we report a strategy to design tough transparent and conductive bonding of synthetic hydrogels containing $90\\%$ water to non-porous surfaces of diverse solids, including glass, silicon, ceramics, titanium and aluminium. The design strategy is to anchor the long-chain polymer networks of tough hydrogels covalently to non-porous solid surfaces, which can be achieved by the silanation of such surfaces. Compared with physical interactions, the chemical anchorage results in a higher intrinsic work of adhesion and in significant energy dissipation of bulk hydrogel during detachment, which lead to interfacial toughness values over $\\mathbf{1},\\mathbf{000}\\mathbf{1}\\mathbf{m}^{-2}$ . We also demonstrate applications of robust hydrogel–solid hybrids, including hydrogel superglues, mechanically protective hydrogel coatings, hydrogel joints for robotic structures and robust hydrogel–metal conductors. \n\nHybrid combinations of hydrogels and solid materials, including metals, ceramics, glass, silicon and polymers, are used in areas as diverse as biomedicine10,11, adaptive and responsive materials12, antifouling13, actuators for optics14 and fluidics15, soft electronics16 and machines17. Although hydrogels with extraordinary physical properties have been recently developed3–9, the weak and brittle bonding between hydrogels and solid materials often severely hampers their integration and function in devices and systems. Whereas intense efforts have been devoted to the development of tough hydrogel–solid interfaces, previous works are generally limited to special cases with porous solid substrates18. Robust adhesion of dry elastomers to non-porous solids has been achieved19–22, but such adhesion is not applicable to hydrogels that contain significant amounts of water23. The need for general strategies and practical methods for the design and fabrication of tough hydrogel bonding to diverse solid materials has remained a central challenge for the field. \n\nHere, we report a design strategy and a set of simple fabrication methods to give extremely tough and functional bonding between hydrogels and diverse solids, including glass, silicon, ceramics, titanium and aluminium, to achieve interfacial toughness values over $1,000{\\mathrm{J}}\\mathrm{m}^{-2}$ . The new design strategy and fabrication methods do not require porous or topographically patterned surfaces of the solids, and allow the hydrogels to contain over $90\\mathrm{wt\\%}$ of water. The resultant tough bonding is also optically transparent and electrically conductive. In addition, we demonstrate novel functions of hydrogel–solid hybrids uniquely enabled by the tough bonding, including tough hydrogel superglues, hydrogel coatings that are mechanically protective, hydrogel joints for robotic structures and robust hydrogel–metal conductors. The design strategy and simple yet versatile method open new avenues not only to addressing fundamental questions on hydrogel–solid interfaces in biology, physics, chemistry and materials science, but also to practical applications of robust hydrogel–solid hybrids in diverse areas10–17,24. \n\nThe proposed strategy to design tough hydrogel–solid bonding is illustrated in Fig. 1. As interfacial cracks can kink and propagate in relatively brittle hydrogel matrices (see Supplementary Movie 1, for example), the design of tough hydrogel–solid bonding first requires high fracture toughness of the constituent hydrogels18. Whereas tough hydrogels generally consist of covalently crosslinked longchain polymer networks that are highly stretchable and other components that dissipate mechanical energy under deformation25,26, it is impractical to chemically bond all components of the hydrogels on solid surfaces. We propose that it is sufficient to achieve relatively tough hydrogel–solid bonding by chemically anchoring the longchain polymer network of a tough hydrogel on solid surfaces, as illustrated in Fig. 1a. When such a chemically anchored tough hydrogel is detached from a solid, the scission of the anchored layer of polymer chains gives the intrinsic work of adhesion $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{0}$ (ref. 27; Fig. 1b). Meanwhile, the tough hydrogel around the interface will be highly deformed and thus dissipate a significant amount of mechanical energy20–22,28, which further contributes to the interfacial toughness by $\\ensuremath{{\\cal T}}_{\\mathrm{D}}$ (Fig. 1b). Neglecting contributions from mechanical dissipation in the solid and friction on the interface, we can express the total interfacial toughness of the hydrogel–solid bonding as \n\n$$\n\\Gamma={\\Gamma_{0}}+{\\Gamma_{\\mathrm{D}}}\n$$ \n\nIn equation (1), $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{0}$ may be much lower than $\\ensuremath{{\\cal T}}_{\\mathrm{D}}$ for tough hydrogel– solid bonding, but it is still critical to chemically anchor long-chain polymer networks of tough hydrogels on the solids’ surfaces. This is because the chemical anchorage gives a relatively high intrinsic work of adhesion $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{0}$ (compared with physically attached cases), which maintains cohesion of the hydrogel–solid interface while allowing large deformation and mechanical dissipation to be developed in the bulk hydrogel to give high values of $\\ensuremath{{\\cal T}_{\\mathrm{D}}}$ (Fig. 1b). \n\nTo test the proposed design strategy, we use a functional silane, 3-(trimethoxysilyl) propyl methacrylate (TMSPMA), to modify the surfaces of glass, silicon wafer, titanium, aluminium and mica ceramic (Fig. 2a)29. We then covalently crosslink the longchain polymer network of polyacrylamide (PAAm) or polyethylene glycol diacrylate (PEGDA) to the silanes on the modified surfaces of various solids. (See Methods and Supplementary Fig. 1a for details on the modification and anchoring process.) To form tough hydrogels, the long-chain polymer network is interpenetrated with a reversibly crosslinked network of alginate, chitosan or hyaluronan6,26, in which the reversible crosslinking and chain scission dissipate mechanical energy, as illustrated in Fig. 1a,b. (See Methods for details on the formula and procedures to make various hydrogels.) As control samples, we chemically anchor a pure PAAm or PEGDA hydrogel on silanized solid surfaces, and physically attach the pure PAAm or PEGDA hydrogel and corresponding tough hydrogels on untreated solid surfaces, as illustrated in Fig. 1c. The shear moduli of all hydrogels in the as-prepared states are set to be at the same level, ${\\sim}30\\mathrm{kPa}$ , by controlling the crosslinking densities in the hydrogels. \n\n![](images/c24f0165236772d57ee43724fe5974cfa3e0d79cb2b96d6066be07ee0558d0f4.jpg) \nFigure 1 | A design strategy for tough bonding of hydrogels to diverse solids. a, The tough bonding first requires high fracture toughness of the constituent hydrogels. Whereas tough hydrogels generally consist of long-chain polymer networks and mechanically dissipative components, it is sufcient to achieve tough bonding by chemically anchoring the long-chain networks on solid surfaces. b, The chemical anchoring gives a relatively high intrinsic work of adhesion $\\begin{array}{r}{{\\cal{T}}_{0},}\\end{array}$ , which maintains cohesion of the hydrogel–solid interface and allows large deformation and mechanical dissipation to be developed in the hydrogel during detachment. The dissipation further contributes to the total interfacial toughness by $\\boldsymbol{{\\Gamma}}_{\\mathsf{D}}$ . c, Schematics of various types of hydrogel–solid interfaces to be tested in the current study to validate the proposed design strategy (from left to right): common and tough hydrogels physically attached on solids, and common and tough hydrogels chemically anchored on solids. \n\nThe samples of tough (for example, PAAm-alginate) and common (for example, PAAm) hydrogels chemically anchored and physically attached on glass substrates all look identical, as they are transparent with transmittance over $95\\%$ . We demonstrate the transparency of a sample in Fig. 2b by placing it above the ‘MIT MECHE’ colour logo. We then carry out a standard 90-degree peeling test with a peeling rate of $50\\mathrm{mm}\\mathrm{min}^{-1}$ to measure the interfacial toughness between hydrogel sheets with a thickness of $3\\mathrm{mm}$ and the glass substrates. A thin $(\\sim25\\upmu\\mathrm{m}$ thick) and rigid glass film backing is attached to the other surface of the hydrogel sheet to prevent its elongation along the peeling direction. Thus, the measured interfacial toughness is equal to the steady-state peeling force per width of the hydrogel sheet30. (See Methods and Supplementary Fig. 2 for details of the peeling test.) Supplementary Movie 1 and Fig. 2c–e demonstrate the peeling process of the common hydrogel chemically anchored on the glass substrate. It can be seen that a crack initiates at the hydrogel–solid interface, kinks into the brittle hydrogel, and then propagates forward. The measured interfacial toughness is $24\\mathrm{J}\\mathrm{m}^{-2}$ (Fig. 2i), limited by the hydrogel’s fracture toughness, validating that tough hydrogels are indeed critical in the design of tough hydrogel–solid interfaces. Supplementary Movie 2 and Supplementary Fig. 3 demonstrate a typical peeling process of a tough or common hydrogel physically attached on the glass substrate. Different from the previous process shown in Supplementary Movie 1 and Fig. 2c–e, the crack can easily propagate along the interface without kinking or significantly deforming the hydrogel, giving a very low interfacial toughness of $8\\mathrm{J}\\mathrm{m}^{-2}$ (Fig. 2i). Supplementary Movie 3 and Fig. $2\\mathrm{f-h}$ demonstrate the peeling process of the tough hydrogel with its long-chain network chemically anchored on the glass substrate. As the peeling force increases, the hydrogel around the interfacial crack front becomes highly deformed and subsequently unstable31,32, developing a pattern of fingers before the interfacial crack can propagate. When the peeling force reaches a critical value, the crack begins to propagate along the hydrogel–solid interface (Fig. 2g). During crack propagation, the fingers coarsen with increasing amplitude and wavelength, and then detach from the substrate (Fig. 2h). The measured interfacial toughness is over $1{,}500\\operatorname{J}\\mathrm{m}^{-2}$ (Fig. 2i), superior to natural counterparts such as tendon and cartilage on bones. As control cases, we vary the thickness of the tough hydrogel sheet from $1.5\\mathrm{mm}$ to $6\\mathrm{mm}$ , and obtain similar values of interfacial toughness (Supplementary Fig. 4). We further vary the peeling rate of the test from $200\\mathrm{{mm}\\mathrm{{min}^{-1}}}$ to $5\\mathrm{{mm}\\mathrm{{min}^{-1}}}$ , and find that the measured interfacial toughness decreases from $3,100\\mathrm{J}\\mathrm{m}^{-2}$ to $1{,}500\\mathrm{J}\\mathrm{m}^{-2}$ accordingly (Supplementary Fig. 5). It is evident that the measured interfacial toughness of chemically anchored PAAm-alginate hydrogel is rate-dependent, possibly owing to viscoelasticity of the hydrogel (Supplementary Fig. 5). Furthermore, the peeling rate used in the current study $(50\\mathrm{mm}\\mathrm{min}^{-1}$ ) gives an interfacial toughness around the lower asymptote, which reflects the effects of intrinsic work of adhesion and rate-independent dissipation, such as the Mullins effect33. \n\nTo understand the phenomena described above and the interfacial toughening mechanism, we develop a finite-element model to simulate the peeling process of a hydrogel sheet from a rigid substrate under a plane-strain condition. In the model, the intrinsic work of adhesion $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{0}$ is characterized by a layer of cohesive elements and the dissipative property of the PAAm-alginate hydrogel is characterized by the Mullins effect33. (See Supplementary Information and Supplementary Figs 13–19 and Supplementary Movies 8 and 9 for details of the model.) Figure 2j gives the calculated relation between the intrinsic work of adhesion $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{0}$ and the interfacial toughness $\\boldsymbol{{\\cal T}}$ . It is evident that the interfacial toughness increases monotonically with the intrinsic work of adhesion, which is effectively augmented by a factor determined by the dissipative properties of the hydrogel. We also vary the thickness of the tough hydrogel in the model from 0.8 to $6\\mathrm{mm}$ and find that the calculated interfacial toughness is approximately the same, consistent with the experimental observation (Supplementary Figs 4 and 19). As a control case, we model the peeling test of a hydrogel with no Mullins effect (that is, no dissipation) but otherwise the same mechanical properties as the tough hydrogel. From Fig. 2j, it is evident that the calculated interfacial toughness for the control case is approximately the same as the prescribed intrinsic work of adhesion. Although the current finite-element model does not account for the effects of fingering instability or viscoelasticity on mechanical dissipation, it clearly demonstrates that high values of the intrinsic work of adhesion and significant mechanical dissipation of the bulk hydrogels are key factors in designing tough bonding of hydrogels on solids (Fig. 2j). \n\n![](images/9d426ad11a906477bf252397e9c255f33c478a660509086248eb8ac00ec12045.jpg) \nFigure 2 | Experimental and modelling results on various types of hydrogel–solid bonding. a, The chemical anchoring of long-chain polymer networks is achieved by crosslinking the networks to functional silanes grafted on the surfaces of various solids. b, The high transparency of the hydrogel–solid bonding is demonstrated by a colourful logo ‘MIT MECHE’ behind a hydrogel–glass hybrid. c–e, Photos of the peeling process of a common hydrogel chemically anchored on a glass substrate. f–h, Photos of the peeling process of a tough hydrogel with its long-chain network chemically anchored on a glass substrate. (Note that blue and red food dyes are added into the common and tough hydrogels, respectively, to enhance the contrast of the interfaces.) i, Curves of the peeling force per width of hydrogel sheet versus displacement for various types of hydrogel–solid bonding. j, Calculated interfacial fracture toughness $\\boldsymbol{\\Gamma}$ as a function of the prescribed intrinsic work of adhesion ${\\varGamma}_{0}$ in finite-element models for the tough hydrogel (red line) and a pure elastic hydrogel with no mechanical dissipation but otherwise the same properties as the tough hydrogel (blue line). The contours in the inset figures indicate mechanical energy dissipated per unit area. \n\n![](images/0bc223041f29dd7fd1da1d887017d945461c2107129d990e6fa0863432ae051e.jpg) \nFigure 3 | Performance of the tough bonding of hydrogels to various solids. a, Measured interfacial toughness values of PAAm-alginate hydrogel bonded on glass, silicon wafer, ceramic, titanium and aluminium are consistently high, over $1,000\\mathrm{J}\\mathsf{m}^{-2}$ , in both the as-prepared and swollen states. In contrast, the interfacial toughness values of the control samples are very low, $8{-}20\\mathrm{J}\\mathsf{m}^{-2}.$ , in the as-prepared state. (As the control samples debond from solids in the fully swollen state, the interfacial toughness is not measured.) b, Comparison of interfacial toughness of PAAm-alginate hydrogel bonded on diverse solids and other hydrogel–solid bonding commonly used in engineering applications as functions of the water concentration in the hydrogels. DOPA in b represents 3,4-dihydroxyphenyl-L-alanine. Values in a represent the mean and the standard deviation ( $\\cdot n{=}3{-}5\\rangle$ . \n\nThe proposed design strategy and fabrication methods for tough hydrogel–solid bonding is applicable to multiple types of non-porous solid materials. Figure 3a shows that the measured interfacial toughness is consistently high for the PAAm-alginate tough hydrogel chemically anchored on glass $(1,500\\mathrm{J}\\mathrm{m}^{-2},$ , silicon $(1,500\\mathrm{{J}}\\mathrm{{m}}^{-2})$ ), aluminium $(1,200\\mathrm{J}\\mathrm{m}^{-2}),$ ), titanium $(1,250\\mathrm{J}\\mathrm{m}^{-2})$ and ceramics $(1,300\\mathrm{J}\\mathrm{m}^{-2},$ . Replacing the PAAm-alginate with other types of tough hydrogels, including PAAm-hyaluronan, PAAm-chitosan, PEGDA-alginate and PEGDA-hyaluronan, still yields relatively high interfacial toughness values, $148{-}820\\operatorname{J}\\mathrm{m}^{-2}$ , compared with the interfacial toughness in controlled cases, $4.4\\mathrm{-}16\\mathrm{J}\\mathrm{m}^{-2}$ (Supplementary Fig. 6). (See Methods for details on other hydrogel–solid bonding.) To explain the difference in interfacial toughness of different tough hydrogels with long-chain networks chemically anchored on substrates, we measure the maximum dissipative capacity and fracture toughness of these hydrogels (Supplementary Fig. 7). It can be seen that, for tough hydrogels with the same chemically anchored long-chain networks (that is, PAAm-based or PEGDA-based tough hydrogels), both the interfacial toughness and fracture toughness increase with the maximum dissipative capacity of the hydrogels (Supplementary Fig. 7). These results validate that significant energy dissipation in bulk hydrogels is critical to achieving high interfacial toughness. \n\nAs hydrogels are commonly used in wet environments, we further immerse the PAAm-alginate hydrogels with PAAm networks anchored on various solid substrates in water for $24\\mathrm{h}$ to allow the hydrogels to swell to equilibrium states. We find that the anchored hydrogels do not detach from the solid substrates in the swollen state. The interfacial toughness of the swollen samples is measured using the 90-degree-peeling test. From Supplementary Movie 4, it can be seen that the detaching process of the swollen hydrogel is similar to that of the same hydrogel in the as-prepared state (that is, Fig. $2\\mathrm{f-h}$ and Supplementary Movie 3). As shown in Supplementary Fig. 8b and Fig. 3a, the measured interfacial toughness values for swollen hydrogels bonded on glass $(1,123\\mathrm{J}\\mathrm{m}^{-2},$ , silicon $(1,210\\mathrm{J}\\mathrm{m}^{-2})$ , aluminium $(1,046\\mathrm{J}\\mathrm{m}^{-2})$ , titanium $(1,113\\mathrm{J}\\mathrm{m}^{-2}),$ and ceramics $(1,091\\mathrm{J}\\mathrm{m}^{-2})$ are consistently high, indicating that the design strategy and fabrication methods can give tough bonding of hydrogels to diverse solids in a wet environment. The slight decrease in interfacial toughness from as-prepared to swollen hydrogels may be due to the decrease of dissipative capability of hydrogels34 and/or the residual stress generated in the hydrogels during swelling. \n\nThe above results prove that chemically anchoring the longchain networks of tough hydrogels on solid substrates can lead to tough hydrogel–solid bonding. As the tough hydrogels used in the current study are composed of covalently crosslinked long-chain networks and reversibly crosslinked dissipative networks, it is also important to know the effects of chemically anchoring dissipative networks on the resultant interfacial toughness. We chemically anchor the dissipative networks (that is, alginate or hyaluronan) in PAAm-alginate, PEGDA-alginate and PEGDA-hyaluronan hydrogels on glass substrates using EDC–Sulfo-NHS chemistry, and then measure the interfacial toughness of resultant samples (see Supplementary Fig. $^{1\\mathrm{b},\\mathrm{c}}$ and Methods for details on anchoring alginate and hyaluronan). As shown in Supplementary Fig. $^{9_{\\mathrm{a,b}},}$ the measured interfacial toughness for PEGDA-alginate and PEGDA-hyaluronan hydrogels with dissipative networks anchored on substrates is $13\\mathrm{J}\\mathrm{m}^{-2}$ and $16\\mathrm{J}\\mathrm{m}^{-2}$ respectively—much lower than the values of the same hydrogels with long-chain networks anchored on substrates $\\left(365\\mathrm{J}\\mathrm{m}^{-2}\\right.$ and $148\\mathrm{J}\\mathrm{m}^{-2}$ respectively). On the other hand, the interfacial toughness for PAAm-alginate hydrogel with alginate anchored on the substrate is $1{,}450{\\mathrm{~}}{\\mathrm{J}}\\cdot{\\mathrm{m}}^{-2}$ (Supplementary Fig. 9c), similar to the value for PAAm-alginate hydrogel with PAAm anchored on the substrate $(1,500\\mathrm{J}\\mathrm{m}^{-2})$ . It is evident that anchoring either long-chain or dissipative networks gives similar interfacial toughness in PAAm-alginate hydrogel but very different values in PEGDA-alginate (or PEGDA-hyaluronan) hydrogel (Supplementary Fig. 9). The different results obtained in PAAm-alginate and PEGDA-alginate (or PEGDA-hyaluronan) hydrogels may be due to much stronger interactions between long-chain and dissipative networks in PAAm-alginate hydrogel than in PEGDA-alginate and PEGDA-hyaluronan hydrogels6,35. \n\nTo compare our results with existing works in the field, we summarize the interfacial toughness of various hydrogel–solid bonding commonly used in engineering applications versus water concentration in those hydrogels in Fig. 3b. (See Supplementary Methods and Supplementary Fig. 10 for detailed references.) Whereas our approach allows the PAAm-alginate tough hydrogels to contain $90\\mathrm{wt\\%}$ of water and does not require porous or topographically patterned surfaces of the solids, it can achieve extremely high interfacial toughness values up to $1{,}500{\\mathrm{J}}\\mathrm{m}^{-2}$ . In comparison, most of synthetic hydrogel bonding has relatively low interfacial toughness, below $10\\dot{0}\\mathrm{J}\\mathrm{m}^{-2}$ . Although previous work on hydrogels and animal skin tissues impregnated in porous substrates gave interfacial toughness values up to $1,000\\mathrm{J}\\mathrm{m}^{-2}$ , the hydrogels and tissues contains $60{-}80\\mathrm{wt\\%}$ water and the requirement of porous solids significantly limits their applications18. Further notably, our fabrication methods for tough hydrogel bonding are relatively simple compared with previous methods, as well as being generally applicable to a wide range of hydrogels and solid materials. \n\nOwing to its simplicity and versatility, the design strategy and fabrication methods for tough hydrogel–solid bonding can potentially enable a set of unprecedented functions of hydrogel–solid hybrids. For example, the tough hydrogels may be used as soft (for example, $30\\mathrm{kPa}$ ), wet (for example, with $90\\%$ water) and biocompatible36 superglues for glass, ceramics and Ti, which have been used in biomedical applications. (See Methods and Supplementary Fig. 12 for details on biocompatibility of tough hydrogels bonded on solid surfaces.) Figure 4a demonstrates that two glass plates bonded by the tough hydrogel superglue (dimension, $5\\mathrm{cm}\\times5\\mathrm{cm}\\times1.5\\mathrm{mm})$ are transparent, and can readily sustain a weight of $25\\mathrm{kg}$ (See Methods for details on fabrication of hydrogel superglue.) As another example, the tough hydrogel–solid bonding can re-define the functions and capabilities of commonly used hydrogel coatings, which are usually mechanically fragile and susceptible to debonding failure. Supplementary Movie 5 and Fig. 4b demonstrate the process of shattering and consequently deforming a silicon wafer coated with a layer of chemically anchored tough hydrogel. Thanks to the high toughness of the hydrogel and interface, the new coating prevents detachment of the shattered pieces of silicon wafer and maintains integrity of the hydrogel–solid hybrid even under a high stretch of three times, demonstrating the hydrogel coating’s new capability for mechanical protection and support. (See Methods for details on fabrication of mechanically protective hydrogel coating.) The tough hydrogel bonding can also be used as compliant joints in mechanical and robotic structures. Supplementary Movie 6 and Fig. 4c demonstrate an example of four ceramic bars bonded with the chemically anchored tough hydrogels. The compliance of the hydrogel combined with high toughness of the bonding enables versatile modes of deformation of the structure. (See Methods for details on fabrication of hydrogel joints.) In addition, the tough hydrogel bonding is electrically conductive and thus can provide a robust interface between hydrogel ionic conductors and metal electrodes16. Existing hydrogel–metal interfaces usually rely on conductive copper tapes whose robustness is uncertain. Supplementary Movie 7 and Fig. 4d demonstrate that the hybrid combination of a tough hydrogel chemically anchored on two titanium electrodes is conductive enough to power a LED light, even when the hydrogel is under a high stretch of 4.5 times. In addition, the conductivity of the hydrogel–metal hybrid remains almost the same even after 1,000 cycles of high stretch up to four times. (See Methods and Supplementary Fig. 11 for details on the fabrication of robust hydrogel–metal conductors and measurements of the electrical conductivity.) \n\nIn summary, we demonstrate that the chemical anchorage of long-chain polymer networks of tough hydrogels on solid surfaces represents a general strategy to design tough and functional bonding between hydrogels and diverse solids. Following the design strategy, we use simple methods such as silane modification and EDC chemistry to achieve tough, transparent and conductive bonding of hydrogels to glass, ceramic, silicon wafer, aluminium and titanium with interfacial toughness values over $1,000\\mathrm{J}\\mathrm{m}^{-2}$ —superior to the toughness of tendon–bone and cartilage–bone interfaces. High values of the intrinsic work of adhesion and significant mechanical dissipation of the bulk hydrogels are key factors that lead to the tough bonding. The ability to fabricate extremely robust hydrogel– solid hybrids makes a number of future research directions and applications possible. For example, electronic devices robustly embedded in (or attached on) tough hydrogels may lead to a new class of stretchable hydrogel electronics, which are softer, wetter and more biocompatible than existing ones based on dry elastomer matrices. New microfluidic systems based on tough hydrogels bonded on non-porous substrates may be able to sustain high flow rates, high pressure and large deformation to better approximate physiological environments than existing microfluidics based on weak or brittle hydrogels. Neural probes coated with tough and biocompatible hydrogels with reduced rigidity34 may be used to better match the mechanical and physiological properties of the brain, spinal cord and peripheral nervous systems. \n\n# Methods \n\nMethods and any associated references are available in the online version of the paper. \n\nReceived 28 May 2015; accepted 25 September 2015; published online 9 November 2015 \n\n![](images/afcb9af92631f6359a80b0ca6bcd9a56c21c3b5b807608399ce02b5a2350c1fd.jpg) \nFigure 4 | Novel applications of hydrogel–solid hybrids enabled by the tough bonding. a, Two glass plates bonded by the hydrogel superglue (dimension, $5\\mathsf{c m}\\times5\\mathsf{c m}\\times1.5\\mathsf{m m})$ are transparent, and can readily sustain a weight of $25\\mathsf{k g}$ . b, The tough bonding of hydrogel to a silicon wafer gives a new coating that is mechanically protective. Shattered silicon chips still attach tightly to the hydrogel coating even under high stretches. c, The tough hydrogel bonding acts as flexible but robust joints between four ceramic bars, which can be deformed into diferent configurations. d, The tough bonding of an ion-containing hydrogel on two titanium electrodes is conductive enough to power a LED light, even when the hydrogel is under a high stretch of 4.5 times. The conductivity of the hydrogel–metal hybrid remains almost the same even after 1,000 cycles of a high stretch up to four times. \n\n# References \n\n1. Bobyn, J., Wilson, G., MacGregor, D., Pilliar, R. & Weatherly, G. Effect of pore size on the peel strength of attachment of fibrous tissue to porous-surfaced implants. J. Biomed. Mater. Res. 16, 571–584 (1982). \n2. Moretti, M. et al. Structural characterization and reliable biomechanical assessment of integrative cartilage repair. J. Biomech. 38, 1846–1854 (2005). \n3. Gong, J. P., Katsuyama, Y., Kurokawa, T. & Osada, Y. Double-network hydrogels with extremely high mechanical strength. Adv. Mater. 15, 1155–1158 (2003). \n4. Wang, Q. et al. High-water-content mouldable hydrogels by mixing clay and a dendritic molecular binder. Nature 463, 339–343 (2010). \n5. Henderson, K. J., Zhou, T. C., Otim, K. J. & Shull, K. R. Ionically cross-linked triblock copolymer hydrogels with high strength. Macromolecules 43, 6193–6201 (2010). \n6. Sun, J.-Y. et al. Highly stretchable and tough hydrogels. Nature 489, 133–136 (2012). \n7. Sun, T. L. et al. Physical hydrogels composed of polyampholytes demonstrate high toughness and viscoelasticity. Nature Mater. 12, 932–937 (2013). \n8. Kamata, H., Akagi, Y., Kayasuga-Kariya, Y., Chung, U.-i. & Sakai, T. ‘‘Nonswellable’’ hydrogel without mechanical hysteresis. Science 343, 873–875 (2014). \n9. Liu, M. et al. An anisotropic hydrogel with electrostatic repulsion between cofacially aligned nanosheets. Nature 517, 68–72 (2015). \n10. Peppas, N. A., Hilt, J. Z., Khademhosseini, A. & Langer, R. Hydrogels in biology and medicine: From molecular principles to bionanotechnology. Adv. Mater. 18, 1345–1360 (2006). \n11. Lee, K. Y. & Mooney, D. J. Hydrogels for tissue engineering. Chem. Rev. 101, 1869–1880 (2001). \n12. Sidorenko, A., Krupenkin, T., Taylor, A., Fratzl, P. & Aizenberg, J. Reversible switching of hydrogel-actuated nanostructures into complex micropatterns. Science 315, 487–490 (2007). \n13. Banerjee, I., Pangule, R. C. & Kane, R. S. Antifouling coatings: Recent developments in the design of surfaces that prevent fouling by proteins, bacteria, and marine organisms. Adv. Mater. 23, 690–718 (2011). \n14. Dong, L., Agarwal, A. K., Beebe, D. J. & Jiang, H. Adaptive liquid microlenses activated by stimuli-responsive hydrogels. Nature 442, 551–554 (2006). \n15. Beebe, D. J. et al. Functional hydrogel structures for autonomous flow control inside microfluidic channels. Nature 404, 588–590 (2000). \n16. Keplinger, C. et al. Stretchable, transparent, ionic conductors. Science 341, 984–987 (2013). \n17. Yu, C. et al. Electronically programmable, reversible shape change in two-and three-dimensional hydrogel structures. Adv. Mater. 25, 1541–1546 (2013). \n18. Kurokawa, T., Furukawa, H., Wang, W., Tanaka, Y. & Gong, J. P. Formation of a strong hydrogel–porous solid interface via the double-network principle. Acta Biomater. 6, 1353–1359 (2010). \n19. Ahagon, A. & Gent, A. Effect of interfacial bonding on the strength of adhesion. J. Polym. Sci. 13, 1285–1300 (1975). \n20. Gent, A. Adhesion and strength of viscoelastic solids. Is there a relationship between adhesion and bulk properties? Langmuir 12, 4492–4496 (1996). \n21. Kaelble, D. Peel adhesion: Influence of surface energies and adhesive rheology. J. Adhes. 1, 102–123 (1969). \n22. Derail, C., Allal, A., Marin, G. & Tordjeman, P. Relationship between viscoelastic and peeling properties of model adhesives. Part 1. Cohesive fracture. J. Adhes. 61, 123–157 (1997). \n23. Sudre, G., Olanier, L., Tran, Y., Hourdet, D. & Creton, C. Reversible adhesion between a hydrogel and a polymer brush. Soft Matter 8, 8184–8193 (2012). \n24. Weissman, J. M., Sunkara, H. B., Albert, S. T. & Asher, S. A. Thermally switchable periodicities and diffraction from mesoscopically ordered materials. Science 274, 959–963 (1996). \n25. Gong, J. P. Why are double network hydrogels so tough? Soft Matter 6, 2583–2590 (2010). \n26. Zhao, X. Multi-scale multi-mechanism design of tough hydrogels: Building dissipation into stretchy networks. Soft Matter 10, 672–687 (2014). \n27. Lake, G. J. & Thomas, A. G. Strength of highly elastic materials. Proc. R. Soc. Lond. Ser. A 300, 108–119 (1967). \n28. Webber, R. E., Creton, C., Brown, H. R. & Gong, J. P. Large strain hysteresis and Mullins effect of tough double-network hydrogels. Macromolecules 40, 2919–2927 (2007). \n29. Tegelström, H. & Wyöni, P. I. Silanization of supporting glass plates avoiding fixation of polyacrylamide gels to glass cover plates. Electrophoresis 7, 99 (1986). \n30. Kendall, K. Thin-film peeling-the elastic term. J. Phys. D 8, 1449–1452 (1975). \n31. Ghatak, A., Chaudhury, M. K., Shenoy, V. & Sharma, A. Meniscus instability in a thin elastic film. Phys. Rev. Lett. 85, 4329–4332 (2000). \n32. Biggins, J. S., Saintyves, B., Wei, Z., Bouchaud, E. & Mahadevan, L. Digital instability of a confined elastic meniscus. Proc. Natl Acad. Sci. USA 110, 12545–12548 (2013). \n33. Ogden, R. & Roxburgh, D. A pseudo–elastic model for the Mullins effect in filled rubber. Proc. R. Soc. Lond. Ser. A 455, 2861–2877 (1999). \n34. Lin, S., Zhou, Y. & Zhao, X. Designing extremely resilient and tough hydrogels via delayed dissipation. Extreme Mech. Lett. 1, 70–75 (2014). \n35. Hong, S. et al. 3D printing of highly stretchable and tough hydrogels into complex, cellularized structures. Adv. Mater. 27, 4035–4040 (2015). \n36. Darnell, M. C. et al. Performance and biocompatibility of extremely tough alginate/polyacrylamide hydrogels. Biomaterials 34, 8042–8048 (2013). \n\n# Acknowledgements \n\nThe authors thank A. Wang and L. Griffith for their help on the cell viability test. This work is supported by ONR (No. N00014-14-1-0528), MIT Institute for Soldier Nanotechnologies and NSF (No. CMMI-1253495). H.Y. acknowledges the financial support from Samsung Scholarship. X.Z. acknowledges the supports from NIH (No. UH3TR000505) and MIT Materials Research Science and Engineering Center. \n\n# Author contributions \n\nX.Z. and H.Y. conceived the idea. H.Y., T.Z., S.L., G.A.P. and X.Z. designed the research. H.Y., S.L. and G.A.P. carried out the experiments and T.Z. performed the numerical simulation. H.Y., T.Z., S.L., G.A.P. and X.Z. analysed and interpreted the results. X.Z. drafted the manuscript and all authors contributed to the writing of the manuscript. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to X.Z. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. \n\n# Methods \n\nMaterials. Unless otherwise specified, the chemicals used in the current work were purchased from Sigma-Aldrich and used without further purification. For the long-chain polymer networks in the hydrogels, acrylamide (AAm; Sigma-Aldrich A8887) was the monomer used for the polyacrylamide (PAAm) networks, and $20\\mathrm{kDa}$ polyethylene glycol diacrylate (PEGDA) was the macromonomer used for the PEGDA networks. The PEGDA macromonomers were synthesized based on a previously reported protocol37 using polyethylene glycol (PEG; Sigma-Aldrich 81300), acryloyl chloride (Sigma-Aldrich 549797), triethylamine (TEA; Sigma-Aldrich 471283), dichloromethane (Sigma-Aldrich 270997), sodium bicarbonate (Sigma-Aldrich S6014), magnesium sulphate (Sigma-Aldrich M7506) and diethyl ether (Sigma-Aldrich 346136). For the polyacrylamide (PAAm) hydrogel, $N,N$ -methylenebisacrylamide (MBAA; Sigma-Aldrich 146072) was used as crosslinker, ammonium persulphate (APS; Sigma-Aldrich A3678) as thermal initiator and $N,N,N^{\\prime},N^{\\prime}$ -tetramethylethylenediamine (TEMED; Sigma-Aldrich T9281) as crosslinking accelerator. For the PEGDA hydrogel, 2-hydroxy- $4^{\\prime}$ -(2-hydroxyethoxy)-2-methylpropiophenone (Irgacure 2959; Sigma-Aldrich 410896) was used as photo initiator. For the dissipative polymer networks in tough hydrogels, a number of ionically crosslinkable biopolymers were used, including sodium alginate (Sigma-Aldrich A2033) ionically crosslinked with calcium sulphate (Sigma-Alginate C3771), chitosan (Sigma-Aldrich 740500) ionically crosslinked with sodium tripolyphosphate (TPP; Sigma-Aldrich 238503), and sodium hyaluronan (HA; Sigma-Aldrich H5542) ionically crosslinked with iron chloride (Sigma-Aldrich 157740). For chemical modification of various solid materials, functional silane 3-(trimethoxysilyl) propyl methacrylate (TMSPMA; Sigma-Aldrich 440159) and acetic acid (Sigma-Aldrich 27225) were used. For anchoring alginate and hyaluronan on solid substrates, (3-aminopropyl) triethoxysilane (APTES, Sigma-Aldrich 440140), $N$ -hydroxysulphosuccinimide (Sulfo-NHS, Sigma-Aldrich 56485), $N$ -(3-dimethylaminopropyl)- $.N^{\\prime}$ ethylcarbodiimide (EDC, Sigma-Aldrich 39391), 2-(N -morpholino)ethanesulphonic acid (MES, Sigma-Aldrich M3671) and sodium chloride (Sigma-Aldrich 746398) were used. \n\nIn the 90-degree peeling experiments, borosilicate glass (McMaster Carr), silicon wafers with a thermal oxidized layer (UniversityWafer), non-porous glass mica ceramic (McMaster Carr), anodized aluminium (Inventables) and titanium (McMaster Carr) plates were used as the solid substrates. As a stiff backing for the hydrogel sheet, ultrathin glass films $25\\upmu\\mathrm{{m};}$ Schott Advanced Optics) were used together with transparent Scotch tape (3 M). In the conductive hydrogel–metal bonding experiments, sodium chloride solution was used as an electrolyte. \n\nSynthesis of various tough hydrogels. The PAAm-alginate tough hydrogel was synthesized by mixing $10\\mathrm{ml}$ of a carefully degassed aqueous precursor solution $12.05\\mathrm{wt\\%}$ AAm, $1.95\\mathrm{wt\\%}$ sodium alginate, $0.017\\mathrm{wt\\%}$ MBAA and $0.043\\mathrm{wt\\%}$ APS) with calcium sulphate slurry (0.1328 times the weight of sodium alginate) and TEMED (0.0025 times the weight of AAm; ref. 6). The mixture was mixed quickly and poured into a laser-cut Plexiglass acrylic mould. The lid of the mould included an opening for the functionalized substrates to be in contact with hydrogel precursor solution. The gel was crosslinked by ultraviolet light irradiation for an hour $254\\mathrm{nm}$ exposure with $6.0\\mathrm{mW}\\mathrm{cm}^{-2}$ average intensity; Spectrolinker XL-1500). \n\nThe PAAm-hyaluronan tough hydrogel was synthesized by mixing $10\\mathrm{ml}$ of degassed precursor solution $18\\mathrm{wt\\%}$ AAm, $2\\mathrm{wt\\%}$ HA, $0.026\\mathrm{wt\\%}$ MBAA and $0.06\\mathrm{wt\\%}$ APS) with $60\\upmu\\mathrm{l}$ of iron chloride solution $(0.05\\mathrm{M})$ and TEMED (0.0025 times the weight of AAm). The PAAm-chitosan tough hydrogel was synthesized by mixing $10\\mathrm{ml}$ of degassed precursor solution $24\\mathrm{wt\\%}$ AAm, $2\\mathrm{wt\\%}$ chitosan, $0.034\\mathrm{wt\\%}$ MBAA and $0.084\\mathrm{wt\\%}$ APS) with $60\\upmu\\mathrm{l}$ of TPP solution $(0.05\\mathrm{M})$ and TEMED (0.0025 times the weight of AAm). The PEGDA-alginate tough hydrogel was synthesized by mixing $10\\mathrm{ml}$ of a degassed precursor solution $20\\mathrm{wt\\%}$ PEGDA and $2.5\\mathrm{wt\\%}$ sodium alginate) with calcium sulphate slurry (0.068 times the weight of sodium alginate) and Irgacure 2959 (0.0018 the weight of PEGDA). The PEGDA-hyaluronan tough hydrogel was synthesized by mixing $10\\mathrm{ml}$ of a degassed precursor solution $20\\mathrm{wt\\%}$ PEGDA and $2\\mathrm{wt\\%}$ HA) with $60\\upmu\\mathrm{l}$ of iron chloride solution $(0.05\\mathrm{M})$ and Irgacure 2959 (0.0018 the weight of PEGDA). The curing procedure was identical to that used for the PAAm-alginate tough hydrogel. \n\nCommon PAAm hydrogel was synthesized by mixing $10\\mathrm{ml}$ of degassed precursor solution $23\\mathrm{wt\\%}$ AAm, $0.051\\mathrm{wt\\%}$ MBAA and $0.043\\mathrm{wt\\%}$ APS) and TEMED (0.0025 times the weight of AAm). The curing procedure was identical to that used for the PAAm-alginate tough hydrogel. Note that the modulus of the common PAAm hydrogel was tuned to match the PAAm-alginate tough hydrogel’s modulus $(30\\mathrm{kPa})$ based on the previously reported data6. \n\nChemically anchoring PAAm and PEGDA on various solid surfaces. The surface of various solids was functionalized by grafting functional silane TMSPMA. Solid substrates were thoroughly cleaned with acetone, ethanol and deionized water in that order, and completely dried before the next step. Cleaned substrates were treated by oxygen plasma $30\\mathrm{W}$ at a pressure of 200 mtorr; Harrick Plasma PDC-001) for $5\\mathrm{min}$ . Immediately after the plasma treatment, the substrate surface was covered with $5\\mathrm{ml}$ of the silane solution ( $\\mathrm{100ml}$ deionized water, $10\\upmu\\mathrm{l}$ of acetic acid with $\\mathrm{pH}3.5$ and $2\\mathrm{wt\\%}$ of TMSPMA) and incubated for $^{2\\mathrm{h}}$ at room temperature. Substrates were washed with ethanol and completely dried. Functionalized substrates were stored in low-humidity conditions before being used for experiments. \n\nDuring oxygen plasma treatment of the solids, oxide layers on the surfaces of the solids (silicon oxide on glass and silicon wafer, aluminium oxide on aluminium, titanium oxide on titanium, and metal oxides on ceramics) react to hydrophilic hydroxyl groups by oxygen radicals produced by the oxygen plasma. These hydroxyl groups on the oxide layer readily form hydrogen bonds with silanes in the functionalization solution, generating a self-assembled layer of silanes on the oxide layers38. Notably, the methoxy groups in TMSPMA are readily hydroxylated in an acidic aqueous environment and formed silanes. These hydrogen bonds between surface oxides and silanes become chemically stable siloxane bonds on the removal of water, forming strongly grafted TMSPMA onto oxide layers on various solids39. \n\nGrafted TMSPMA has a methacrylate terminal group which can copolymerize with the acrylate groups in either AAm or PEGDA under a free radical polymerization process, generating chemically anchored long-chain polymer networks onto various solid surfaces40. Because the long-chain polymer networks in hydrogels are chemically anchored onto solid surfaces via strong and stable covalent bonds, the interfaces can achieve a higher intrinsic work of adhesion than physically attached hydrogels. The silane functionalization chemistry is summarized in Supplementary Fig. 1a. \n\nChemically anchoring alginate and hyaluronan on various solid surfaces. We anchored alginate and hyaluronan via EDC–Sulfo-NHS chemistry following previously reported protocols41,42 (Supplementary Fig. $^{\\mathrm{1b,c}}$ ). Glass substrates were cleaned and treated with oxygen plasma following the above-mentioned procedures and covered with $5\\mathrm{ml}$ of the amino-silane solution ( $\\mathrm{100ml}$ deionized water, $2\\mathrm{wt\\%}$ of APTES), then incubated for $^{2\\mathrm{h}}$ at room temperature. Substrates were washed with ethanol and completely dried. The amino-silane functionalized glass substrates were further incubated in either alginate anchoring solution or hyaluronan anchoring solution ( $\\mathrm{100ml}$ of aqueous MES buffer (0.1 M MES and $50\\mathrm{mM}$ sodium chloride), $1\\mathrm{wt\\%}$ alginate or hyaluronan, Sulfo-NHS (molar ratio of 30:1 to either alginate or hyaluronan) and EDC (molar ratio of 25:1 to either alginate or hyaluronan)) for $24\\mathrm{h}$ . Incubated glass substrates were finally washed with deionized water and completely dried before use. \n\nInterfacial toughness measurement. All tests were conducted in ambient air at room temperature. The hydrogels and hydrogel–solid interfaces maintain consistent properties over the time of the tests (that is, $\\sim$ a few minutes), during which the effect of dehydration is not significant. Whereas long-term dehydration will significantly affect the properties of hydrogels, adding highly hydratable salts into the hydrogels can enhance their water retention capacity43. The interfacial toughness of various hydrogel–solid bondings was measured using the standard 90-degree peeling test (ASTM D 2861) with a mechanical testing machine (2 kN load cell; Zwick/Roell Z2.5) and a 90-degree peeling fixture (TestResources, G50). All rigid substrates were prepared with dimensions $7.62\\mathrm{cm}$ in width, $12.7\\mathrm{cm}$ in length and $0.32\\mathrm{cm}$ in thickness. Hydrogels were cured on the solid substrates in a Plexiglass acrylic mould with a size of $110\\mathrm{mm}\\times30\\mathrm{mm}\\times6\\mathrm{mm}$ . As a stiff backing for the hydrogel, TMSPMA-grafted ultrathin glass film was used with an additional protective layer of transparent Scotch tape (3 M) on top of the glass film. Prepared samples were tested with the standard 90-degree peeling test set-up (Supplementary Fig. 2). All 90-degree peeling tests were performed with a constant peeling speed of $50\\mathrm{mm}\\mathrm{min}^{-1}$ . The measured force reached a plateau as the peeling process entered the steady state, and this plateau force was calculated by averaging the measured force values in the steady-state region with common data processing software (Supplementary Fig. 8a). The interfacial toughness $\\boldsymbol{{\\cal T}}$ was determined by dividing the plateau force $F$ by the width of the hydrogel sheet W . To test the dependence of interfacial toughness on hydrogel thickness, we carried out a set of 90-degree peeling tests on PAAm-alginate hydrogels with different thicknesses $(1.5\\sim6\\mathrm{mm}$ ) chemically anchored on glass substrates (Supplementary Fig. 4a). For interfacial toughness measurements of fully swollen samples, each peeling test sample was immersed in deionized water for $24\\mathrm{h}$ and tested by the standard 90-degree peeling test (Supplementary Fig. 8b). \n\nTo demonstrate the peeling rate dependency of the measured interfacial toughness, we performed a set of 90-degree peeling tests on PAAm-alginate hydrogels chemically anchored on glass substrates with various peeling rates from $5\\mathrm{mm}\\mathrm{min}^{-1}$ (lowest) to $200\\mathrm{mm}\\mathrm{min}^{-1}$ (highest; Supplementary Fig. 5). \n\nTo demonstrate that the proposed strategy and method is generally applicable to multiple types of hydrogels, we also performed standard 90-degree peeling tests on various types of tough hydrogels, including PAAm-hyaluronan, PAAm-chitosan, PEGDA-alginate and PEGDA-hyaluronan hydrogels chemically anchored on glass substrates (Supplementary Fig. 6a). The measured interfacial toughness for these tough hydrogels $(148-820\\mathrm{J}\\mathrm{m}^{-2}$ , Supplementary Fig. 6b) was consistently much higher than the interfacial toughness of the control cases $(4.4\\mathrm{-}16\\mathrm{J}\\mathrm{m}^{-2}$ , Supplementary Fig. 6b). \n\nPreparation of hydrogel superglue, coating and joints. For the hydrogel superglue, two TMSPMA-grafted glass plates $5\\mathrm{cm}\\times12\\mathrm{cm}\\times2\\mathrm{cm})$ ) were connected by thin tough hydrogel $(5\\mathrm{cm}\\times5\\mathrm{cm}\\times1.5\\mathrm{mm})$ and subjected to weights up to $25\\mathrm{kg}$ . Weight was applied by hanging metal pieces of known weight with metal wires. Hydrogel joints were fabricated by curing tough hydrogel using a Plexiglass acrylic mould between four TMSPMA-grafted non-porous glass mica ceramic rods ( $75\\mathrm{mm}$ length with $10\\mathrm{mm}$ diameter), forming an interconnected square structure. To test the robustness of these hydrogel joints, each joint was twisted and rotated to large angles. The hydrogel coating was fabricated by curing a thin $\\mathrm{{(1mm}}^{\\cdot}$ ) tough hydrogel layer onto the TMSPMA-grafted thermal oxide silicon wafer $100\\upmu\\mathrm{m}$ thickness with $50.8\\mathrm{mm}$ diameter). To test the hydrogel coating’s protective capability, we shattered the wafer with a metal hammer and stretched the hydrogel-coated wafer by hand up to three times its original diameter. In the preparation of samples, we used the PAAm-alginate tough hydrogel. The grafting of TMSPMA on various solids was conducted as discussed in the previous section. \n\nElectrically conductive hydrogel interface. Ionic tough hydrogel was prepared by curing tough PAAm-alginate hydrogel on two TMSPMA-grafted titanium slabs and then soaking in sodium chloride solution (3 M) for $^{6\\mathrm{h}}$ . The electric resistance of the ionic hydrogel–titanium hybrid was measured using the four-point method44. The ionic hydrogel–titanium hybrid was connected in series with a function generator and galvanometer, and the voltage between the titanium slabs was measured with a voltmeter connected in parallel (Supplementary Fig. 11a). The ratio of the measured voltage to the measured current gave the electrical resistance of the ionic hydrogel–titanium hybrid. The resistivity was then calculated using the relation $R{=}\\rho L/A$ for a given geometry of the ionic hydrogel in the test where $\\rho$ is the resistivity, $L$ is the length of the gel and $A$ is the cross-sectional area. The rate of stretch was kept constant at $100\\mathrm{mm}\\mathrm{min}^{-1}$ using a mechanical testing machine. All electrical connections other than the ionic tough hydrogel–titanium interface were established using conductive aluminium tape. Cyclic extension of the ionic tough hydrogel was done by a mechanical testing machine based on a predetermined number of cycles. The ionic tough hydrogel’s ability to transmit power was tested by lighting up LEDs using an a.c. power source ( $1\\mathrm{kHz}5\\mathrm{V}$ peak-to-peak sinusoidal). Supplementary Fig. 11b illustrates the test set-up. \n\nBiocompatibility of tough hydrogel bonding. The biocompatibility of tough hydrogels, including PAAm-alginate and PEGDA-alginate hydrogels, has been validated in previous studies35,36. In the current study, the biocompatibility of PAAm-alginate hydrogel bonded on silane-grafted glass was tested in vitro with a live/dead viability assay of hTERT-immortalized human mesenchymal stem cells (MSCs; Supplementary Fig. 12). A hydrogel disk was chemically anchored on a glass slide following the above-mentioned procedure using TMSPMA and then swelled in PBS for two days. To focus on the biocompatibility of the hydrogel–solid interface, the hydrogel was peeled off from the glass slide to expose the previously bonded interface. Thereafter, both the hydrogel and the glass slide were placed in 24-well plates with the exposed interfaces facing up (Supplementary Fig. 12a). MSCs were seeded at a density of 25,000 cells/well on the exposed interfaces of the hydrogel and glass, and incubated for seven days at $37^{\\circ}\\mathrm{C}$ and $5\\%\\mathrm{CO}_{2}$ in complete cell culture media (high-glucose DMEM with $10\\%$ FBS, $1\\mathrm{mM}$ sodium pyruvate, $1\\times$ MEM (non-essential amino acids), $2\\mathrm{mM}$ glutamax, and $100\\mathrm{Uml^{-1}}$ penicillin–streptomycin) from Life Technologies. \n\nA live/dead staining was performed using the LIVE/DEAD kit for mammalian cells (Life Technologies) according to the manufacturer’s instructions, and fluorescent images were obtained using a Leica DMI 6000 microscope with Oasis Surveyor software. As seen in Supplementary Fig. 12c, the MSCs proliferated and survived on the exposed interface of the glass slide. On the exposed interface of the hydrogel, there were fewer cells as the MSCs did not attach well to the hydrogel, but most cells that attached were alive, consistent with previous report36 (Supplementary Fig. 12b). In both cases, the percentage of viable MSCs on the exposed interfaces is over $95\\%$ after seven days of incubation. (It should be noted that although the formed tough hydrogel–glass interface is biocompatible, the bonding process is not, as the AAm monomers used in the process are toxic.) \n\n# References \n\n37. Nemir, S., Hayenga, H. N. & West, J. L. PEGDA hydrogels with patterned elasticity: Novel tools for the study of cell response to substrate rigidity. Biotechnol. Bioeng. 105, 636–644 (2010). \n38. Dugas, V. & Chevalier, Y. Surface hydroxylation and silane grafting on fumed and thermal silica. J. Colloid Interface Sci. 264, 354–361 (2003). \n39. Yoshida, W., Castro, R. P., Jou, J.-D. & Cohen, Y. Multilayer alkoxysilane silylation of oxide surfaces. Langmuir 17, 5882–5888 (2001). \n40. Muir, B. V., Myung, D., Knoll, W. & Frank, C. W. Grafting of cross-linked hydrogel networks to titanium surfaces. ACS Appl. Mater. Interfaces 6, \n958–966 (2014). \n41. Cha, C. et al. Tailoring hydrogel adhesion to polydimethylsiloxane substrates using polysaccharide glue. Angew. Chem. Int. Ed. 52, 6949–6952 (2013). \n42. Stile, R. A., Barber, T. A., Castner, D. G. & Healy, K. E. Sequential robust design methodology and X-ray photoelectron spectroscopy to analyze the grafting of hyaluronic acid to glass substrates. J. Biomed. Mater. Res. 61, 391–398 (2002). \n43. Bai, Y. et al. Transparent hydrogel with enhanced water retention capacity by introducing highly hydratable salt. Appl. Phys. Lett. 105, 151903 (2014). \n44. Yang, C. H. et al. Ionic cable. Extreme Mech. Lett. 3, 59–65 (2015). " + }, + { + "id": "10.1038_ncomms12032", + "DOI": "10.1038/ncomms12032", + "DOI Link": "http://dx.doi.org/10.1038/ncomms12032", + "Relative Dir Path": "mds/10.1038_ncomms12032", + "Article Title": "Superconcentrated electrolytes for a high-voltage lithium-ion battery", + "Authors": "Wang, JH; Yamada, Y; Sodeyama, K; Chiang, CH; Tateyama, Y; Yamada, A", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Finding a viable electrolyte for next-generation 5V-class lithium-ion batteries is of primary importance. A long-standing obstacle has been metal-ion dissolution at high voltages. The LiPF6 salt in conventional electrolytes is chemically unstable, which accelerates transition metal dissolution of the electrode material, yet beneficially suppresses oxidative dissolution of the aluminium current collector; replacing LiPF6 with more stable lithium salts may diminish transition metal dissolution but unfortunately encounters severe aluminium oxidation. Here we report an electrolyte design that can solve this dilemma. By mixing a stable lithium salt LiN(SO2F)(2) with dimethyl carbonate solvent at extremely high concentrations, we obtain an unusual liquid showing a three-dimensional network of anions and solvent molecules that coordinate strongly to Li+ ions. This simple formulation of superconcentrated LiN(SO2F)(2)/dimethyl carbonate electrolyte inhibits the dissolution of both aluminium and transition metal at around 5V, and realizes a high-voltage LiNi0.5Mn1.5O4/graphite battery that exhibits excellent cycling durability, high rate capability and enhanced safety.", + "Times Cited, WoS Core": 905, + "Times Cited, All Databases": 966, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000379110300001", + "Markdown": "# Superconcentrated electrolytes for a high-voltage lithium-ion battery \n\nJianhui Wang1,\\*, Yuki Yamada1,2,\\*, Keitaro Sodeyama2,3,4, Ching Hua Chiang1, Yoshitaka Tateyama2,4 \n& Atsuo Yamada1,2 \n\nFinding a viable electrolyte for next-generation $5\\lor\\cdot$ -class lithium-ion batteries is of primary importance. A long-standing obstacle has been metal-ion dissolution at high voltages. The $\\mathsf{L i P F}_{6}$ salt in conventional electrolytes is chemically unstable, which accelerates transition metal dissolution of the electrode material, yet beneficially suppresses oxidative dissolution of the aluminium current collector; replacing $\\mathsf{L i P F}_{6}$ with more stable lithium salts may diminish transition metal dissolution but unfortunately encounters severe aluminium oxidation. Here we report an electrolyte design that can solve this dilemma. By mixing a stable lithium salt $\\mathsf{L i N}(\\mathsf{S O}_{2}\\mathsf{F})_{2}$ with dimethyl carbonate solvent at extremely high concentrations, we obtain an unusual liquid showing a three-dimensional network of anions and solvent molecules that coordinate strongly to ${\\mathsf{L i}}^{+}$ ions. This simple formulation of superconcentrated LiN $({\\mathsf{S O}}_{2}{\\mathsf{F}})_{2}/$ dimethyl carbonate electrolyte inhibits the dissolution of both aluminium and transition metal at around $5\\mathsf{V},$ and realizes a high-voltage $\\mathsf{L i N i}_{0.5}\\mathsf{M n}_{1.5}\\mathsf{O}_{4}/\\varepsilon$ raphite battery that exhibits excellent cycling durability, high rate capability and enhanced safety. \n\nithium-ion batteries, having received great commercial success in the portable power source market, are being aimed for large-scale energy-storage application in electric vehicles1–3. To approach the high energy-density requirements for automobiles, a pragmatic approach is to elevate the operating voltage of batteries, from the present $4\\mathrm{V}$ to around $5\\mathrm{V}$ (refs 4,5). This allows the direct application of the mature fabrication technology of $4\\mathrm{V}$ -class lithium-ion batteries, the well-developed negative electrodes (for example, graphite and graphite/silicon), and high-voltage positive electrodes (for example, spinel $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ and some layered oxides). However, new challenges—which mainly arise from the electrolyte—hinder the practical application of the next-generation $5\\mathrm{V}$ -class battery. \n\nOne major problem is metal dissolution from the positive electrode at high voltages, which poses a serious dilemma in designing an electrolyte. In state-of-the-art lithium-ion electrolyte, chemically unstable $\\mathrm{LiPF}_{6}$ is an essential component to suppress anodic (oxidative) dissolution of an aluminium current collector because its hydrolysis product of hydrofluoric acid (HF) contributes to an insoluble ${\\mathrm{AlF}}_{3}$ passivation $\\mathrm{\\hat{\\tlm}}^{6,7}$ . However, the generated HF accelerates the dissolution of transition metals from the active electrode materials, which causes severe capacity decay upon cycling, especially at high voltages and elevated temperatures8,9. Using $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ as an example, the dissolved $\\mathrm{Mn}^{2+}$ and $\\mathrm{Ni}^{2+}$ ions, albeit $<1\\%$ of the total amount, deposit on the surface of the graphite negative electrode, which thicken the solid electrolyte interphase (SEI) by catalysing the reductive decomposition of the electrolyte, and consume the limited lithium reserve in the battery to result in a $>50\\%$ capacity loss in 100 charge/discharge cycles10,11. Diversified functional additives and/or alternative solvents have been explored12–17 but improvements are still unsatisfactory. Efforts have tried more stable salts (less tendency to generate HF) to replace $\\mathrm{LiPF}_{6}.$ , such as lithium perfluorosulfonylamide (shortened to ‘amide’)18. However, the chemically stable amide does not participate in the reaction with Al to form a stable passivation film, thus causing severe anodic dissolution of the Al current collector at ${>}4\\mathrm{V}$ (refs 19–22). As a result, it remains a dilemma for electrolyte design to suppress both the Al dissolution (requiring an unstable salt) and transition metal dissolution (avoiding an unstable salt). Recently, increasing the concentration of amide salts was reported to alleviate anodic Al dissolution23–25, but the operating voltage of a half-cell is still limited below $4.3\\mathrm{V}$ , presumably owing to some or all of the following reasons: insufficient salt concentration23, too low ionic conductivity24 and too low oxidative stability of the solvent26. \n\nIn this work, we report an electrolyte system to resolve the dilemma. We select stable yet dissociative lithium bis(fluorosulfonyl)amide (LiFSA) as the salt and oxidation-stable carbonate esters as the solvent. We demonstrate an unusual liquid with a peculiar three-dimensional structural network obtained at extremely high salt concentrations. The superconcentrated electrolyte not only effectively suppresses the anodic Al dissolution but also remarkably inhibits the transition metal dissolution and, thus, realizes a safe, stable and fast-rate high-voltage $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}|$ graphite battery. \n\n# Results \n\nPhysicochemical properties. LiFSA salt was dissolved at various concentrations into three different carbonate ester solvents: dimethyl carbonate (DMC), ethylene carbonate (EC) and mixed EC:DMC. All the mixtures are transparent liquids at room temperature (see Fig. 1a as an example). Their basic physicochemical properties are presented in Supplementary Table 1. Figure 1b shows their viscosity as a function of salt concentration. \n\nIndependent of the solvents used, the viscosity increases exponentially with increasing the LiFSA mole fraction $(X_{\\mathrm{LiFSA}})$ . Among the three groups of solutions, the group with DMC as the solvent shows the lowest viscosity because pure DMC has a lower viscosity than pure EC or mixed EC:DMC. For electrolytes with similar solvation radiuses of mobile ions, the ionic conductivity is proportional to the number of mobile ions and inversely proportional to the viscosity of the medium18. As shown in Fig. 1c, at dilute concentrations of $X_{\\mathrm{LiFSA}}{<}0.14$ (below $1.5\\mathrm{mol}\\mathrm{dm}^{-3},$ ), the use of the EC:DMC mixture shows the highest ionic conductivity owing to a synergistic effect: the high-dielectric-constant EC increases the mobile ion number by promoting salt dissociation; the low-viscosity DMC increases the ion mobility by decreasing the solution viscosity. This is why the mixed solvents of EC and linear carbonates are generally adopted in conventional electrolytes of the lithium-ion battery18. However, when XLiFSA is above 0.14, the solution with DMC as the sole solvent shows an even higher ionic conductivity than that with EC:DMC, which should result from the much lower viscosity of the former at high concentrations. This result suggests that the viscosity becomes the decisive factor on the ionic conductivity for a concentrated solution, wherein intensive ionic association exists independent of the solvents used, showing a distinct departure from the conventional electrolyte design strategy on the basis of dilute concentrations. For the LiFSA/DMC solution, a commercially acceptable ionic conductivity of $1.12\\mathrm{mS}\\mathrm{cm}^{-1}\\left(\\ddagger\\right.$ $(30^{\\circ}\\mathrm{C})$ is obtained even at a ‘super-high’ concentration with salt-to-solvent molar ratio of 1:1.1 despite a high viscosity of $238.9\\mathrm{mPas}$ . Although the ionic conductivity is lower than that of the commercial dilute electrolyte, it does not compromise the rate capability of the battery (shown later). \n\nOn the other hand, the drawbacks of the high volatility and high flammability of linear carbonate solvents can be overcome to a large degree owing to the much lower content of organic solvents in the concentrated solutions. Thermogravimetry measurements (Supplementary Fig. 1) show that the weight loss of the superconcentrated 1:1.1 LiFSA/DMC solution is only $1.5\\mathrm{wt\\%}$ after elevating the temperature to ${100}^{\\circ}\\mathrm{C},$ which is considerably lower than those of a dilute 1:10.8 LiFSA/DMC solution $(65.5\\mathrm{wt\\%}$ , corresponding to $1.0\\mathrm{mol}\\mathrm{dm}^{-3}$ ) and a commercial electrolyte $(28.7\\mathrm{wt\\%})$ . As demonstrated in the flame tests (Fig. 1d,e), the 1:1.1 LiFSA/DMC solution does not burn as fiercely as the commercial dilute electrolyte. The superior thermal stability and flame retardant ability of the concentrated electrolytes contribute to the remarkably improved safety properties as compared with the dilute electrolytes. \n\nReversible reaction of a ${}_{5\\thinspace\\mathrm{~V~}}$ -class electrode. Anodic dissolution of the Al current collector and/or oxidative decomposition of solvent may be encountered in the high-voltage application of amide-based electrolytes. To exclude the possible influence of the anodic Al dissolution, we initially used platinum foil as the current collector for the $\\mathrm{LiNi}_{0.5}\\mathrm{Mn}_{1.5}\\mathrm{O}_{4}$ electrode in a threeelectrode cell (Supplementary Fig. 2). The results showed that both dilute (1:10.8) and superconcentrated (1:1.1) LiFSA/DMC electrolytes enabled a reversible $\\mathrm{Li^{+}}$ de-intercalation/intercalation on the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}|P t}$ electrode, indicating a reasonably good compatibility between the present electrolyte system and $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ material at $\\sim5\\mathrm{V}$ . \n\nHowever, when applied in a coin cell using the conventional Al current collector, low concentrations of LiFSA/DMC electrolytes encountered problems, confirming the critical drawback of anodic Al dissolution for the amide-based electrolytes. As shown in Fig. 2a, the first charge on the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}|A l}$ electrode is impossible in the dilute 1:10.8 LiFSA/DMC electrolyte owing to the continuous Al dissolution at $4.3\\mathrm{V}.$ . In the concentrated 1:1.9 LiFSA/DMC electrolyte (Fig. 2b), the charge/discharge cycling becomes possible up to the cutoff voltage of $4.9\\mathrm{V}$ , but the large irreversible capacity indicates the parasitic Al dissolution remains. The Al dissolution subsequently deteriorates the electrical contacts between the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ material and the Al current collector, and results in a fast capacity decay (Fig. 2d). Actually, the poor cycling performance on the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ electrode was generally observed in other concentrated 1:2 LiFSA/ carbonate ester electrolytes, such as LiFSA in EC, propylene carbonate (PC), ethyl methyl carbonate (EMC) and diethyl carbonate (DEC; Supplementary Fig. 3), indicating this concentration is not sufficient to fully inhibit Al dissolution at $_{5\\mathrm{V}}$ . \n\n![](images/ed3fdfae0d3e42cb26e5c59070a89b931029e744e7c17ddf8e248dc4e90bc87f.jpg) \nFigure 1 | Physicochemical properties dependent on solution concentration. (a) Images of various salt-to-solvent molar ratios of LiFSA/DMC solutions. Viscosity (b) and ionic conductivity (c) for solutions of LiFSA in DMC, EC and EC:DMC (1:1 by mol.) at $30^{\\circ}\\mathsf{C}$ . The $X_{\\mathsf{L i F S A}}$ mole fraction is the molar amount of LiFSA salt divided by the total molar amount of the salt and solvents. The LiFSA-to-solvent molar ratios of the solutions are shown on the upper axis. (d) Flame tests of a commercial dilute electrolyte of $1.0\\mathsf{m o l}\\mathsf{d m}^{-3}$ LiPF6/EC:DMC (1:1 by vol.) and (e) the lab-made superconcentrated electrolyte of 1:1.1 LiFSA/DMC. \n\nIn contrast, the superconcentrated 1:1.1 LiFSA/DMC electrolyte enables a reversible $\\mathrm{Li^{+}}$ de-intercalation/intercalation reaction on the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ electrode even at a high voltage of $5.2\\mathrm{V}$ (Fig. 2c). In a charge/discharge cycling test, the capacity retention after 100 cycles was over $95\\%$ (Fig. 2d), and the coulombic efficiency was close to $100\\%$ (Supplementary Fig. 4), evidencing an effective inhibition of anodic Al dissolution. Similarly, using the super-high concentration of 1:1.3, all the LiFSA/carbonate electrolytes enabled stable charging/discharging cycling of the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ electrode (see Fig. 2e for example). Especially, the electrolytes using low-dielectric-constant and lowviscosity linear carbonate solvents (for example, DMC, EMC and DEC) showed a faster rate capability as compared with those using high-dielectric-constant and high-viscosity cyclic carbonate solvents (for example, EC, PC and their corresponding mixtures), which is at least partly owing to the much higher ionic conductivity of the former. These results demonstrate that the salt-superconcentrated strategy is a simple, effective and fruitful approach to various safe and stable high-voltage electrolytes. To the best of our knowledge, this is the first time that stable and fast charge/discharge cycling of a $5\\mathrm{V}$ -class electrode using amide salt-based organic electrolytes has been achieved. \n\nThe progressive inhibition of anodic Al dissolution with increasing salt concentration is further proved by linear sweep voltammetry (LSV) of an Al electrode and the subsequent scanning electron microscopy observation on the polarized Al surface (see Fig. 3 for details). This notable concentration effect was recently reported but with a debate on whether a stable surface film on Al (ref. 23) or the elimination of uncoordinated (free) solvents of electrolyte24,25 plays the key role. We conducted a surface analysis of the Al electrodes polarized in various concentrations of LiFSA/DMC electrolytes by $\\mathrm{\\DeltaX}$ -ray photoemission spectroscopy (XPS) as well as a comparative LSV study between fresh and polarized Al electrodes (see Supplementary Figs 5 and 6 for details). We were unable to obtain any essential evidence to support the existence of a stronger surface film generated in the concentrated electrolyte. Instead, we found that the LiFSA salt readily decomposes and produces LiF upon $\\mathrm{Ar^{+}}$ etching (Supplementary Fig. 7). The previous observation in ref. $23-\\mathtt{a}$ much thicker surface film of LiF produced in a higher concentration of electrolyte—is likely to arise from the decomposition of un-rinsed amide salt induced by $\\mathrm{Ar^{+}}$ etching in the XPS measurement. \n\n![](images/790db469119fedc193d7c7e95b9c3928a6e410808dd3af71ceb99f8a0fbc581e.jpg) \nFigure 2 | Performance of 5 V-class $\\pm\\mathrm{i}\\mathsf{N i_{0.5}}\\mathsf{M n_{1.5}}\\mathsf{O}_{4}$ electrode in a half-cell. Charge–discharge voltage curves of $\\mathsf{L i N i}_{0.5}\\mathsf{M n}_{1.5}\\mathsf{O}_{4}$ lithium metal half-cells using (a) dilute 1:10.8, $(\\pmb{\\ b})$ moderately concentrated 1:1.9 and $\\mathbf{\\eta}(\\bullet)$ superconcentrated 1:1.1 LiFSA/DMC electrolytes at a C/5 rate. Some/all curves of 1st, 2nd, 10th, 50th and 100th cycles are shown. (d) Discharge $(\\mathsf{L i}^{+}$ intercalation) capacity retention of the half-cells using different concentrations of LiFSA/DMC electrolytes at a C/5 rate. (e) Rate capacity and subsequent cycling retention of the half-cells using 1:1.3 LiFSA-based electrolytes with different carbonate solvents. Charge–discharge tests were conducted at $25^{\\circ}C$ with a cutoff voltage of $3.5\\substack{-4.9V}$ and a maximum-time restriction of $10\\mathsf{h}$ except for that using the 1:1.1 LiFSA/DMC electrolyte whose cutoff voltage was $3.5\\substack{-5.2\\vee}$ The 1C-rate corresponds to $147\\mathsf{m A g}^{-1}$ on the weight basis of the $\\mathsf{L i N i}_{0.5}M\\mathsf{n}_{1.5}{\\mathsf{O}}_{4}$ electrode. \n\nWe now study the solution structure of the electrolytes using Raman spectroscopy observation and density functional theory molecular dynamics simulation (DFT-MD). As shown in the Raman spectra (Fig. 4b left), a free DMC molecule exhibits an ${\\mathrm{O-CH}}_{3}$ stretching vibration band at $910\\mathrm{cm}^{-1}$ (ref. 27). This band shifts up to $930{-}935\\mathrm{cm}^{-1}$ when DMC participates in $\\mathrm{Li^{+}}$ solvation. In dilute 1:10.8 LiFSA/DMC, the majority of DMC molecules exist in a free state because the solvent-to-salt molar ratio (10.8) is much larger than a typical four- or fivefold coordination of $\\mathrm{Li^{+}}$ in aprotic solvents. As the LiFSA concentration increases, the population of free DMC decreases and that of $\\mathrm{Li^{+}}$ -coordinated DMC increases; the $\\mathrm{Li^{+}{\\mathrm{-}F S A^{-}}}$ association simultaneously intensifies through the formation of contact ion pairs (CIPs, FSA \u0002 coordinating to one $\\mathrm{Li^{+}}$ ) and aggregate clusters (AGGs, $\\mathrm{FSA}^{-}$ coordinating to two or more $\\bar{\\mathrm{Li}^{+}}$ ). The latter is evidenced from a remarkable upshift of the $\\mathrm{FSA}^{-}$ band $\\left(700-780\\thinspace\\mathrm{cm}^{-1}\\right.$ , Fig. 4b right), which is typically observed in the amide-based concentrated solutions24,25,28–31. For the moderately concentrated 1:2 LiFSA/DMC solution, the Raman band corresponding to free DMC is remarkably weakened, suggesting that the majority of DMC are solvating to $\\mathrm{Li^{+}}$ . This is consistent with the DFT-MD simulation, which shows ca. $90\\%$ DMC are coordinating to $\\mathrm{Li^{+}}$ with the rest as free solvent (marked as light blue in Fig. 4d). Moreover, the simulation illustrates that all $\\mathrm{FSA}^{-}$ anions are coordinating to $\\mathrm{Li^{+}}$ with ca. $20\\%$ as CIPs and ca. $80\\%$ as AGGs (marked as orange and dark blue in Fig. 4d, respectively). The coordination environment is shown in Supplementary Fig. 8. For the superconcentrated 1:1.1 LiFSA/DMC solution, both DMC and $\\mathrm{FSA}^{-}$ bands further upshift substantially, indicating both $\\mathrm{Li^{+}}$ - DMC and $\\mathrm{Li^{+}{\\mathrm{-}F S A}^{-}}$ interactions enhanced compared with those in 1:2 LiFSA/DMC. The DFT-MD simulation reveals that all DMC molecules, together with all $\\mathrm{FSA}^{-}$ anions, are coordinating to $\\mathrm{Li^{+}}$ (no free solvent or anion). Interestingly, besides oxygen, significant amount of nitrogen on $\\mathrm{FSA}^{-}$ anions also participate in the coordination with $\\bar{\\mathrm{Li^{+}}}$ , which is hardly observed at the lower concentrations. The contribution of nitrogen coordinating to $\\mathrm{Li^{+}}$ is shown in Supplementary Fig. 8. More importantly, almost all $\\mathrm{FSA}^{-}$ anions remain in AGG states during the whole DFT-MD simulation time $\\left(0.1\\mathrm{fs}\\times100,000\\right.$ steps), and a CIP state is rarely observed, demonstrating the unusual solution structural feature with AGG clusters as the predominant components in the superconcentrated LiFSA/DMC solution. It is noteworthy that each $\\mathrm{FSA}^{-}$ anion coordinates to $2{-}3\\ \\mathrm{Li}^{+}$ and each $\\mathrm{Li^{+}}$ is coordinated by $2{-}3\\operatorname{FSA}^{-}$ in 1:1.1 LiFSA/DMC. Hence, $\\mathrm{FSA}^{-}$ anions in the superconcentrated solution connect with each other through the intensive association with $\\mathrm{Li^{+}}$ , leading to a reinforced three-dimensional network (shown in Fig. 4e). This feature is different from the less concentrated solutions, wherein significant amount of CIPs and free solvents divide the solution structure into relatively small-size parts. \n\n![](images/83fbd301fe52d949d03e9025d17817cff89ca00cb7329ac484dd0d42f4d01bf3.jpg) \nFigure 3 | Oxidation stability of an aluminium electrode. LSV of an aluminium electrode in various concentrations of LiFSA/DMC electrolytes in a three-electrode cell. The scan rate was $1.0\\:\\mathrm{mVs}^{-1}$ . The insets are scanning electron microscopy images of the Al surface polarized in the dilute 1:10.8 (left of panel) and superconcentrated 1:1.1 (right of panel) electrolytes. Many corroding pits cover the surface of the Al electrode polarized in the dilute electrolyte, showing a severe anodic Al dissolution. In contrast, no corroding pits appear on the surface of the Al electrode polarized in the superconcentrated electrolyte, indicating a good inhibition of anodic Al dissolution. The white scale bar represents $20\\upmu\\mathrm{m}$ . \n\nGenerally, the anodic metal dissolution requires three steps: first, oxidation of the metal to a metal cation; second, coordination of the metal cation by solvents or anions; and finally, the diffusion of the solvated metal cation to the bulk electrolyte32. At high voltages of $\\sim5\\mathrm{V}$ , the first step proceeds more rapidly and extensively than at the conventional operating voltage of $4\\mathrm{V}$ . Thereby, the subsequent coordination and diffusion must be strongly inhibited by the nature of electrolyte solutions to suppress the metal ion dissolution. In the moderately concentrated 1:2 LiFSA/carbonate electrolytes, the presence of significant free solvents and CIPs (with two or more coordination sites remaining vacant) could coordinate to Al cations and fail to inhibit Al dissolution completely at $5\\mathrm{V}$ . In contrast, the superconcentrated 1:1.1 LiFSA/DMC electrolyte effectively inhibits Al dissolution even over $5\\mathrm{V}$ , which can be ascribed to its peculiar AGGs-predominant solution structure: (i) all DMC solvents and all $\\mathrm{FS}\\bar{\\mathrm{A}}^{-}$ anions strongly coordinate to $\\mathrm{Li^{+}}$ cations and thus have a much lower probability of coordinating to other metal cations; (ii) the resulting reinforced three-dimensional network further retards the diffusion rate of the metal cations, particularly, those with multiple charge. \n\nStable cycling of a 4.6 V $\\mathbf{LiNi_{0.5}M n_{1.5}O_{4}}|$ graphite battery. In addition to the excellent performance achieved on the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ -positive electrode, the superconcentrated 1:1.1 LiFSA/DMC electrolyte also realized ultra-stable charge/discharge cycling on the natural graphite-negative electrode despite the absence of conventional SEI-forming agent of EC (Supplementary Fig. 9): the application in a graphite|Li half-cell exhibits a capacity retention of $99.6\\%$ after 100 cycles with coulombic efficiency of $\\sim99.8\\%$ , and with rate capability comparable with that using a commercial dilute electrolyte. Accordingly, the superconcentrated electrolyte was further applied in the high-voltage $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}|$ graphite full cell, a much harsher condition than in the half-cell, because the active lithium resource is limited and a new underlying problem arises from the transition metal dissolution from the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ especially at high voltages and elevated temperatures. Figure 5a,b shows charge/discharge voltage profiles of $\\mathrm{LiNi}_{0.5}\\mathrm{Mn}_{1.5}\\mathrm{O}_{4}|$ natural graphite full cells at $40^{\\circ}\\mathrm{C}$ using a state-of-the-art commercial electrolyte and the lab-made superconcentrated electrolyte, respectively. The cell with the commercial electrolyte suffers from a severe capacity decay during cycling, that is, only $18\\%$ of the initial capacity left after 100 cycles (Fig. 5a,c), which is consistent with previous reports11,33. In contrast, the capacity retention using the 1:1.1 LiFSA/DMC electrolyte is over $90\\%$ after 100 cycles, exhibiting a remarkably improved cycling durability (Fig. $^{5\\mathrm{b,c}}$ and Supplementary Figs 10 and 11). Notably, the superiority of the superconcentrated electrolyte becomes even more marked at $55^{\\circ}\\mathrm{C}$ (Supplementary Fig. 12). It is generally accepted that the poor cycling performance of the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ graphite battery originates from the dissolution of transition metals from $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ into the electrolyte, as introduced at the beginning of this article. Indeed, energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) observation shows a much lower content of Mn and Ni on the graphite electrode of the full cell cycled in the superconcentrated electrolyte than that in the commercial electrolyte, which provides evidence for the effective inhibition of transition metal dissolution in the former. There are two main reasons for the improved performance: (i) LiFSA is less reactive to produce HF as compared with $\\mathrm{LiPF}_{6},$ which alleviates the corrosion of $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ and, thus, reduces the formation of soluble $\\mathrm{Mn}^{2+}$ and $\\mathrm{Ni}^{2+}$ ; (ii) even if some $\\mathrm{Mn}^{2+}$ and $\\mathrm{Ni}^{2+}$ are formed on the surface of $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ , they can hardly dissolve in and transport through the AGGs-predominant superconcentrated electrolyte owing to the same functional manner for the inhibition of Al dissolution. Moreover, it is worth noting that the rate performance of the full cell using the superconcentrated 1:1.1 LiFSA/DMC is comparable with that using the commercial electrolyte (Fig. 5d), although the former shows an ionic conductivity one-order lower than the latter. The mechanistic understanding on the high-rate capability of the superconcentrated electrolyte is underway in our laboratory. To the best of our knowledge, this is the first case that, an electrolyte with such an ultra-simple formulation—a single salt and a single solvent without any additive—realizes stable cycling of a highvoltage lithium-ion battery. \n\n![](images/e0fe3c7a44fe92aac0e0bf9a3d1d8f4dee762718bbf9fdc995f6cf6641f72faf.jpg) \nFigure 4 | Li salt solvent coordination structure dependent on salt concentration. (a) The several main species in the LiFSA/DMC solutions. (b) Raman spectra of LiFSA/DMC solutions with various salt-to-solvent molar ratios in the range of $890{-}900{\\mathsf{c m}}^{-1}$ $({\\mathsf{O}}\\mathrm{-}{\\mathsf{C}}{\\mathsf{H}}_{3}$ stretching mode of the DMC solvent) and $700-780{\\mathsf{c m}}^{-1}$ (S-N stretching mode of the $\\mathsf{F S A}^{-}$ anion). Snapshots of typical equilibrium trajectories obtained by DFT-MD simulations: (c) dilute solution (1 LiFSA/25 DMC, $<1\\mathsf{m o l}\\mathsf{d m}^{-3})$ , (d) moderately concentrated solution (12 LiFSA/24 DMC, ca. $4\\mathsf{m o l}\\mathsf{d}\\mathsf{m}^{-3},$ , and (e) superconcentrated solution (10 LiFSA/11 DMC, ca. $5.5\\mathsf{m o l}\\mathsf{d m}^{-3},$ ). The coordination of $\\mathsf{L i}^{+}-\\mathsf{D M C}$ and $\\mathsf{L i}^{+}-\\mathsf{F S A}^{-}$ is supposed to build up when the involved atoms locate within $2.5\\mathring{\\mathsf{A}}$ from ${\\mathsf{L i}}^{+}$ . The coordination numbers of solvents and anions to $\\mathsf{L i}^{+}$ are shown in Supplementary Fig. 8. Li cations are marked in purple. Free and coordinated DMC molecules are marked in light blue and grey, respectively. Free, CIP and AGG states of $\\mathsf{F S A}^{-}$ anions are marked in red, orange and dark blue, respectively. Hydrogen atoms are not shown. \n\n# Discussion \n\nThe conventional dilute $\\mathrm{LiPF}_{6}/\\mathrm{EC}$ -based electrolytes have dominated the electrolyte market of $4\\mathrm{V}$ -class lithium-ion batteries over the past 25 years; however, they show difficulties in satisfying the requirements of next-generation $_{5\\mathrm{V}}$ -class batteries in terms of both safety and stability. Our work demonstrates a number of electrolytes with a reinforced three-dimensional network that are obtained by simple mixing of a stable salt with a conventional carbonate solvent at ‘super-high’ concentrations. Owing to its peculiar structural characteristics, the superconcentrated electrolytes overcomes the longstanding challenge faced by the unstable $\\mathrm{LiPF}_{6}$ -based electrolytes at high voltages (passivating the Al current collector versus accelerating the transition metal dissolution of the active material), thus, enables a stable operation of a $5\\mathrm{V}$ -class battery. Emphasis is on the fact that the peculiar solution structure and functionalities are unique to such superhigh concentrations (solvent/salt $\\approx1.1\\$ ), and cannot be achieved in moderately high concentrations (solvent/salt $>1.8$ ) as in previous reports $24,30,31,34,35$ . Besides the positive electrode side, the superconcentrated electrolytes also show a good compatibility with the natural graphite-negative electrode even in the absence of EC. It breaks through the limitation of a general requirement of EC for a SEI formation for a lithium-ion electrolyte, and diversifies the electrolyte formulation towards various EC-free electrolytes. Different from the conventional electrolyte design that requires a high-dielectric-constant (usually high-viscosity) solvent, the superconcentrated electrolyte prefers a low-viscosity solvent. Although the ionic conductivity of the superconcentrated electrolyte is lower than that of the conventional dilute electrolyte, it does not necessarily compromise the rate capability of the battery. Clarification of the corresponding mechanism would be enlightening for developing novel high-power batteries. Furthermore, the superconcentrated electrolytes show superior thermal stability and flame retardant ability, alleviating the safety risk for a high-voltage battery using conventional dilute electrolytes. Finally, it is noteworthy that our reported superconcentrated electrolytes do not contain any additives, signifying the potential to further enhance the performance. These desirable features above outperform the conventional dilute electrolytes; meanwhile, the wide-temperature window of the liquid state (ensuring a good contact with the electrode materials), as well as the convenience of the approach, surpass the solid-state electrolytes. Therefore, the superconcentrated electrolytes might offer opportunities to build safe and stable high-voltage batteries that are not limited to the lithium-ion. \n\n![](images/d0e22bc56be1a237fc3ee6feba9b923392e4d81c137bb3c24dbb3ffde752f6f5.jpg) \nFigure 5 | Performance of a high-voltage $\\pm\\mathsf{I i N i}_{0.5}\\mathsf{M n}_{1.5}\\mathsf{O}_{4}|$ natural graphite battery. Charge–discharge voltage curves of $\\mathsf{L i N i}_{0.5}M\\mathsf{n}_{1.5}{\\mathsf{O}}_{4}$ graphite full cells using (a) a commercial $1.0\\mathsf{m o l}\\mathsf{d m}^{-3}$ LiPF $\\dot{}_{6}$ EC:DMC (1:1 by vol.) electrolyte and (b) lab-made superconcentrated 1:1.1 LiFSA/DMC electrolyte at a $C/5$ rate and $40^{\\circ}\\mathsf{C}$ . The curves of 2nd, 10th, 50th and 100th cycle are shown. (c) Discharge capacity retention of the full cells at a $C/5$ rate. The inset shows EDS spectra on the graphite electrode surface $(200\\times200\\upmu\\mathrm{m}^{2}$ area) after 8-day cycling tests, which is equivalent to the operating time of 100 and 20 cycles for the battery using the commercial and superconcentrated electrolytes, respectively. (d) Discharge capacity of the full cell at various C-rates and $25^{\\circ}\\mathsf{C}$ . All charge-discharge cycling tests were conducted with a cutoff voltage of $3.5\\substack{-4.8\\vee}.$ 1C-rate corresponds to $147\\mathsf{m A g}^{-1}$ on the weight basis of the $\\mathsf{L i N i}_{0.5}M\\mathsf{n}_{1.5}{\\mathsf{O}}_{4}$ electrode. \n\n# Methods \n\nPreparation of electrolytes and electrodes. LiFSA (Nippon shokubai) and all solvents (DMC, DEC, EMC, EC and PC, Kishida Chemical Co. Ltd) were lithium battery grade and used without purification. Electrolyte solutions were prepared by mixing a given amount of LiFSA with solvents in an Ar-filled glove box. The commercial electrolyte of $1.0\\mathrm{mol}\\mathrm{dm}^{-3}$ $_{\\mathrm{LiPF}_{6}/\\mathrm{EC:DMC}}$ (1:1 by vol) was purchased from Kishida Chemical Co. Ltd and used as the reference. Both the lab-made LiFSA-based electrolytes and as-received commercial $\\mathrm{LiPF}_{6}$ -based electrolyte were dried by molecular sieve before tests. The water content was less than $2\\mathrm{p.p.m}$ ., as detected by a coulometric Karl Fischer Titrator. \n\nThe electrodes were fabricated by first well mixing the active materials of $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ (Hosen Corp., mean particle size ${\\hat{\\mathrm{R}}}=5\\upmu\\mathrm{m}.$ no surface treatment) and natural graphite (SEC Carbon Ltd., $\\hat{\\mathrm{R}}=10\\upmu\\mathrm{m}\\mathrm{,}$ , polyvinylidene difluoride (PVdF) and/or Denka black (AB, HS-100) in $N$ -methylpyrrolidone with weight ratios of 80:10:10 $\\mathrm{(LiNi_{0.5}M n_{1.5}O_{4};P V}$ dF:AB) and 90:10 (graphite:PVdF). The resultant slurry was cast on the Al or Pt foil ${\\mathrm{20}}\\upmu\\mathrm{m}$ thickness) for the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ electrode and on the Cu foil ( ${\\mathrm{.10}}\\upmu\\mathrm{m}$ thickness) for the graphite electrode using a $50\\upmu\\mathrm{m}$ doctor blade. All those electrodes were dried at $120^{\\circ}\\mathrm{C}$ under vacuum for $^{12\\mathrm{h}}$ . The active material mass loading was $0.7{-}2\\operatorname*{mgcm}^{-2}$ with a thickness of $\\sim15\\mathrm{-}20\\upmu\\mathrm{m}$ , unless otherwise mentioned. The use of relatively low mass loading was to spotlight the critical issue of anodic Al dissolution as the content ratio of metallic Al components (Al current collector and Al positive cap) to the active electrode material becomes much higher in a coin cell. Nevertheless, thick electrodes with a high mass loading of $\\sim10\\mathrm{mgcm}^{-2}$ were also tested. The results are shown in Supplementary Figs 11 and 12. \n\nElectrochemical measurements. LSV was performed by VMP-3 (BioLogic) in a beaker cell with an Al belt $(1\\times4\\mathrm{cm}^{2}$ , $0.6\\mathrm{cm}$ soaked in the electrolyte) as a working electrode and lithium metal as the reference and counter electrodes (shown in Supplementary Fig. 5 inset). $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}|L i}$ half-cells and $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}|$ - graphite full cells were assembled in the standard 2032-type coin cell hardware in an Ar-filled glove box. A combined separator, composed of cellulose separator (Nippon Kodoshi, placed on the positive electrode side) and glass fibre separator (Advantec GB-50, placed on the negative electrode side), was used. The amount of electrolyte in a coin cell was ca $160\\upmu\\mathrm{l}$ to fully wet the separators and electrodes. In the full cells, the weight ratio of $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ :graphite was $\\sim2{:}1$ , which corresponds to $\\sim1{:}1.3$ of their theoretical capacity ratio. Galvanostatic charge/ discharge cycling and rate capability tests were conducted on a charge/discharge unit (TOSCAT). Charge and discharge were conducted at the same C-rate without using a constant-voltage mode at both ends of the charge and discharge. \n\nCharacterization. The density and viscosity of solution samples were evaluated with a DMA 35 density meter and a Lovis $2000\\mathrm{M}$ viscometer, respectively. The ionic conductivity was measured by AC impedance spectroscopy at $1\\mathrm{kHz}$ (Solartron 147055BEC) in a symmetric cell $\\mathrm{(Pt|}$ electrolyte|Pt). The flammability was tested on an electrolyte-soaked glass fibre filter (Advantec GB-100). \n\nThe solution structure was studied by a Raman spectroscopy with an exciting laser of $514\\mathrm{nm}$ (NRS-5100). The samples were sealed in a quartz cell in the glove box to avoid any contamination from the air. \n\nThe morphology of Al electrodes after LSV tests were observed by a fieldemission scanning electron microscopy at $2.0\\mathrm{kV}$ . The transition metals deposited on the graphite electrode in the $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ graphite full cells after charge/ discharge cycling were estimated by an EDS. The cells were disassembled in the glove box. The obtained electrodes were rinsed in DMC and dried in the glove box. The sample was exposed in air for $<1\\mathrm{{min}}$ at sample loading. \n\nThe experimental details for thermogravimetric analysis and XPS measurements are shown in Supplementary Fig. 1 legend and Supplementary Methods, respectively. \n\nSimulations. Car-Parrinello type DFT-MD simulations were carried out using CPMD code36. LiFSA/DMC solutions with salt-to-solvent molar ratios of 1:25, 1:2 and 1:1.1 were calculated in cubic supercells with 15.05, 17.03 and $14.34\\mathrm{\\AA}$ linear dimensions, respectively. A fictitious electric mass of 500 a.u. and a time step of 4 a.u. (0.10 fs) were chosen. The temperature was controlled using a Nose´ thermostat with a target temperature of $30^{\\circ}\\mathrm{C}$ . After 5 ps equilibration steps, statistical averages were computed from trajectories of at least $10\\mathrm{ps}$ in length. The electronic wave function was quenched to the Born-Oppenheimer surface approximately every 1 ps to maintain adiabaticity. The energy cutoff of the plane wave basis is set to $90\\mathrm{Ry}$ Goedecker–Teter–Hutter type norm-conserving pseudopotentials for C, H, O, N, S, F and Li were used37. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon request. \n\n# References \n\n1. Goodenough, J. B. & Kim, Y. Challenges for rechargeable Li batteries. Chem. Mater. 22, 587–603 (2010). \n2. Etacheri, V., Marom, R., Elazari, R., Salitra, G. & Aurbach, D. Challenges in the development of advanced Li-ion batteries: a review. Energy Environ. Sci. 4, \n3243–3262 (2011). \n3. Amine, K., Kanno, R. & Tzeng, Y. Rechargeable lithium batteries and beyond: Progress, challenges, and future directions. MRS Bull. 39, 395–401 (2014). \n4. Patoux, S. et al. High voltage spinel oxides for Li-ion batteries: From the material research to the application. J. Power Sources 189, 344–352 (2009). \n5. Croy, J. R., Abouimrane, A. & Zhang, Z. Next-generation lithium-ion batteries: the promise of near-term advancements. MRS Bull. 39, 407–415 (2014). \n6. Myung, S.-T., Sasaki, Y., Sakurada, S., Sun, Y.-K. & Yashiro, H. Electrochemical behavior of current collectors for lithium batteries in non-aqueous alkyl carbonate solution and surface analysis by ToF-SIMS. Electrochim. Acta 55, 288–297 (2009). \n7. Zhang, X. & Devine, T. M. Identity of passive film formed on aluminum in Liion battery electrolytes with LiPF6. J. Electrochem. Soc. 153, B344–B351 (2006). \n8. Aurbach, D. et al. Review on electrode–electrolyte solution interactions, related to cathode materials for Li-ion batteries. J. Power Sources 165, 491–499 (2007). \n9. Zhan, C. et al. $\\mathrm{{Mn}(I I)}$ deposition on anodes and its effects on capacity fade in spinel lithium manganate-carbon systems. Nat. Commun. 4, 2437 (2013). \n10. Kim, J.-H. et al. Understanding the capacity fading mechanism in $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}/$ /graphite Li-ion batteries. Electrochim. Acta 90, 556–562 (2013). \n11. Pieczonka, N. P. W. et al. Understanding transition-metal dissolution behavior in $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ high-voltage spinel for lithium ion batteries. J. Phys. Chem. C 117, 15947–15957 (2013). \n12. Zhang, Z. et al. Fluorinated electrolytes for $5\\mathrm{~V~}$ lithium-ion battery chemistry. Energy Environ. Sci. 6, 1806–1810 (2013). \n13. Hu, L., Zhang, Z. & Amine, K. Fluorinated electrolytes for Li-ion battery: An FEC-based electrolyte for high voltage $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}/$ graphite couple. Electrochem. Commun. 35, 76–79 (2013). \n14. Pieczonka, N. P. W. et al. Impact of lithium bis(oxalate)borate electrolyte additive on the performance of high-voltage spinel/graphite Li-ion batteries. J. Phys. Chem. C 117, 22603–22612 (2013). \n15. Song, Y.-M., Han, J.-G., Park, S., Lee, K. T. & Choi, N.-S. A multifunctional phosphite-containing electrolyte for 5 V-class $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ cathodes with superior electrochemical performance. J. Mater. Chem. A 2, 9506–9513 (2014). \n16. Xu, M. et al. Improved performance of high voltage graphite $/\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ batteries with added lithium tetramethyl borate. ECS Electrochem. Lett. 4, A83–A86 (2015). \n17. Xu, K. Electrolytes and Interphases in Li-Ion Batteries and Beyond. Chem. Rev. 114, 11503–11618 (2014). \n18. Xu, K. Nonaqueous liquid electrolytes for lithium-based rechargeable batteries. Chem. Rev. 104, 4303–4417 (2004). \n19. Krause, L. J. et al. Corrosion of aluminum at high voltages in non-aqueous electrolytes containing perfluoroalkylsulfonyl imides; new lithium salts for lithium-ion cells. J. Power Sources 68, 320–325 (1997). \n20. Wang, X., Yasukawa, E. & Mori, S. Inhibition of anodic corrosion of aluminum cathode current collector on recharging in lithium imide electrolytes. Electrochim. Acta 45, 2677–2684 (2000). \n21. Li, L. et al. Transport and electrochemical properties and spectral features of non-aqueous electrolytes containing LiFSI in linear carbonate solvents. J. Electrochem. Soc. 158, A74–A82 (2011). \n22. Kramer, E. et al. Mechanism of anodic dissolution of the aluminum current collector in 1 M LiTFSI EC:DEC 3:7 in rechargeable lithium batteries. J. Electrochem. Soc. 160, A356–A360 (2013). \n23. Matsumoto, K. et al. Suppression of aluminum corrosion by using high concentration LiTFSI electrolyte. J. Power Sources 231, 234–238 (2013). \n24. McOwen, D. W. et al. Concentrated electrolytes: decrypting electrolyte properties and reassessing Al corrosion mechanisms. Energy Environ. Sci. 7, 416–426 (2014). \n25. Moon, H. et al. Solvent activity in electrolyte solutions controls electrochemical reactions in Li-ion and Li-sulfur batteries. J. Phys. Chem. C 119, 3957–3970 (2015). \n26. Yoshida, K. et al. Oxidative-stability enhancement and charge transport mechanism in glyme-lithium salt equimolar complexes. J. Am. Chem. Soc. 133, 13121–13129 (2011). \n27. Katon, J. E. & Cohen, M. D. The vibrational spectra and structure of dimethyl carbonate and its conformational behavior. Can. J. Chem. 53, 1378–1386 (1975). \n28. Seo, D. M., Borodin, O., Han, S.-D., Boyle, P. D. & Henderson, W.A. Electrolyte solvation and ionic association II. Acetonitrile-lithium salt mixtures: highly dissociated salts. J. Electrochem. Soc. 159, A1489–A1500 (2012). \n29. Yamada, Y., Yaegashi, M., Abe, T. & Yamada, A. A superconcentrated ether electrolyte for fast-charging Li-ion batteries. Chem. Commun. 49, 11194–11196 (2013). \n30. Yamada, Y. et al. Unusual stability of acetonitrile-based superconcentrated electrolytes for fast-charging lithium-ion batteries. J. Am. Chem. Soc. 136, 5039–5046 (2014). \n31. Yamada, Y. & Yamada, A. Review-Superconcentrated electrolytes for lithium batteries. J. Electrochem. Soc. 162, A2406–A2423 (2015). \n32. Yamada, Y. et al. Corrosion prevention mechanism of aluminum metal in superconcentrated electrolytes. ChemElectroChem 2, 1687–1694 (2015). \n33. Glatthaar, S., Dorit, N., Binder, J. R. & Andres, H. Evidence of loss of active lithium in titanium-doped $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}/$ graphite cells. J. Power Sources 274, 1267–1275 (2015). \n34. Jeong, S.-K., Inaba, M., Iriyama, Y., Abe, T. & Ogumi, Z. Electrochemical intercalation of lithium ion within graphite from propylene carbonate solutions. Electrochem. Solid State Lett. 6, A13–A15 (2003). \n35. Suo, L., Hu, Y.-S., Li, H., Armand, M. & Chen, L. A new class of solvent-in-salt electrolyte for high-energy rechargeable metallic lithium batteries. Nat. Commun. 4, 1481 (2013). \n36. CPMD. http://www.cpmd.org:81/manual/node4.html, Copyright IBM Corp (1990-2015), Copyright MPI fu¨r Fesko¨rperforschung Stuttgart (1997-2001). \n37. Goedecker, S., Teter, M. & Hutter, J. Separable dual-space Gaussian pseudopotentials. Phys. Rev. B 54, 1703–1710 (1996). \n\n# Acknowledgements \n\nThis work was partially supported by JSPS Grant-in-Aid for Young Scientists (A) (No. 26708030) and JSPS Specially Promoted Research (No. 15H05701). The calculations were carried out at the super-computer centres of National Institute for Materials Science, the University of Tokyo, and the K computer at the RIKEN through the HPCI \n\nSystem Research Projects (hp150209). We thank Keisuke Kikuchi, Reiko Kawakami and Dr Kouhei Okitsu for their assistance in the experiments, and specially thank Dr Sai-Cheong Chung for his valuable suggestions on the manuscript. \n\n# Author contributions \n\nJ.W. and Y.Y. contributed equally to this work. Y.Y. and A.Y. proposed the concept. J.W. and Y.Y. designed the experiments. J.W. and C.H.C. carried out the experiments and analysed the data. K.S. and Y.T. designed and conducted the theoretical calculations. J.W., Y.Y. and A.Y. wrote the manuscript. A.Y. supervised the whole project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Wang, J. et al. Superconcentrated electrolytes for a high-voltage lithium-ion battery. Nat. Commun. 7:12032 doi: 10.1038/ncomms12032 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms12967", + "DOI": "10.1038/ncomms12967", + "DOI Link": "http://dx.doi.org/10.1038/ncomms12967", + "Relative Dir Path": "mds/10.1038_ncomms12967", + "Article Title": "Biodegradable black phosphorus-based nullospheres for in vivo photothermal cancer therapy", + "Authors": "Shao, JD; Xie, HH; Huang, H; Li, ZB; Sun, ZB; Xu, YH; Xiao, QL; Yu, XF; Zhao, YT; Zhang, H; Wang, HY; Chu, PK", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Photothermal therapy (PTT) offers many advantages such as high efficiency and minimal invasiveness, but clinical adoption of PTT nulloagents have been stifled by unresolved concerns such as the biodegradability as well as long-term toxicity. Herein, poly (lactic-co-glycolic acid) (PLGA) loaded with black phosphorus quantum dots (BPQDs) is processed by an emulsion method to produce biodegradable BPQDs/PLGA nullospheres. The hydrophobic PLGA not only isolates the interior BPQDs from oxygen and water to enhance the photothermal stability, but also control the degradation rate of the BPQDs. The in vitro and in vivo experiments demonstrate that the BPQDs/PLGA nullospheres have inappreciable toxicity and good biocompatibility, and possess excellent PTT efficiency and tumour targeting ability as evidenced by highly efficient tumour ablation under near infrared (NIR) laser illumination. These BP-based nullospheres combine biodegradability and biocompatibility with high PTT efficiency, thus promising high clinical potential.", + "Times Cited, WoS Core": 892, + "Times Cited, All Databases": 934, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000385456600001", + "Markdown": "# Biodegradable black phosphorus-based nanospheres for in vivo photothermal cancer therapy \n\nJundong Shao1,2, Hanhan Xie1, Hao Huang1, Zhibin Li1, Zhengbo Sun2, Yanhua Xu2, Quanlan Xiao2, Xue-Feng $\\upgamma_{\\mathsf{U}}\\mathsf{1}$ , Yuetao Zhao1, Han Zhang2, Huaiyu Wang1 & Paul K. Chu3 \n\nPhotothermal therapy (PTT) offers many advantages such as high efficiency and minimal invasiveness, but clinical adoption of PTT nanoagents have been stifled by unresolved concerns such as the biodegradability as well as long-term toxicity. Herein, poly (lactic-co-glycolic acid) (PLGA) loaded with black phosphorus quantum dots (BPQDs) is processed by an emulsion method to produce biodegradable BPQDs/PLGA nanospheres. The hydrophobic PLGA not only isolates the interior BPQDs from oxygen and water to enhance the photothermal stability, but also control the degradation rate of the BPQDs. The in vitro and in vivo experiments demonstrate that the BPQDs/PLGA nanospheres have inappreciable toxicity and good biocompatibility, and possess excellent PTT efficiency and tumour targeting ability as evidenced by highly efficient tumour ablation under near infrared (NIR) laser illumination. These BP-based nanospheres combine biodegradability and biocompatibility with high PTT efficiency, thus promising high clinical potential. \n\nevelopment of novel nanomaterials and advanced nanotechnology for cancer treatment has attracted much interest1. As a promising alternative or supplement to traditional cancer therapy, photothermal therapy (PTT) based on the interaction between tissues and near infrared (NIR) radiation offers many advantages such as high efficiency and minimal invasiveness2–5. Owing to the excellent NIR optical performance, nanomaterials such as metallic nanostructures, metal-based semiconductor nanoparticles and carbon nanomaterials have been explored and employed as PTT agents or drug release systems in in vivo cancer therapy6–15. Nanomaterials with a size range between 20 and $200\\mathrm{nm}$ circumvent rapid renal filtration enabling passive accumulation in tumours at high concentrations for a longer time than organic molecules via the enhanced permeability and retention (EPR) effect that can hardly be achieved by other molecular agents16–19. However, unlike other small biodegradable molecules, inorganic nanoparticles generally have poor biodegradability and stay in the body for a long period of time accentuating the risk of deleterious effects. Hence, clinical adoption of nanomaterials hinges on the proper control of biodegradability as well as long-term toxicity of the materials and by-products20,21. It has recently been reported that ultrasmall nanoparticles ( $<10\\mathrm{nm})$ undergo rapid renal filtration22 but suffer from a short blood circulation half-life, attenuated EPR effects, as well as reduced tumour accumulation and retention. Therefore, it is highly desirable to develop new PTT agents which have not only the proper size enabling efficient tumour targeting, but also good biocompatibility and biodegradability ensuring that the nanoparticles can be discharged harmlessly from the body in a reasonable period of time after completion of the designed therapeutic functions. \n\nAs a new member of 2D materials, atomically thin black phosphorus (BP) has many potential applications in electronics and optoelectronics23–31. Being a metal-free layered semiconductor, BP has a layer-dependent direct bandgap varying from $0.3\\mathrm{eV}$ for the bulk materials to $2.0\\mathrm{eV}$ for phosphorene (monolayered BP), thereby allowing broad absorption across the ultraviolet and infrared regions25. Liquid exfoliation methods are commonly utilized to prepare BP nanosheets with different thicknesses and sizes32–36 for bioimaging and phototherapy37–39. In particular, ultrasmall BP nanosheets (also called BP quantum dots, BPQDs) with a size of $\\sim3\\mathrm{nm}$ have a large NIR extinction coefficient, high photothermal conversion efficiency and little cytotoxicity39. As an inorganic nanoagent, BP is attractive due to its inherent biocompatibility and furthermore, as one of the vital elements, $P$ is a benign element making up $\\sim1\\%$ of the total body weight as a bone constituent in the human body40–42. Recent experiments have shown that BP nanosheets, especially ones with a small thickness and size, have high reactivity with oxygen and water43–46 and can degrade in aqueous media. Moreover, the final degradation products are nontoxic phosphate and phosphonate45–47, both of which exist in and are well tolerated by the human body41,42. Therefore, ultrasmall BPQDs with good photothermal performance and biocompatibility are potential therapeutic agents. However, their actual clinical application in vivo still suffers from rapid renal excretion and degradation of the optical properties during circulation in the body. \n\nIn this work, to accomplish high therapeutic efficacy and desirable biodegradation, poly (lactic-co-glycolic acid) (PLGA) loaded with $3\\mathrm{nm}$ BPQDs is processed by an oil-in-water emulsion solvent evaporation method to produce $\\sim100\\mathrm{nm}$ BPQDs/PLGA nanospheres (NSs). PLGA, a well known biodegradable and biocompatible polymer approved by the Food and Drug Administration (FDA), is widely used as a vehicle in the delivery of drugs and nanomaterials48–51. In general, the degradation period of PLGA spans several months and its degradation rate can be controlled by adjusting the chemical composition such as the monomer ratio and molecular weight52. Herein, the hydrophobic PLGA not only isolates the interior BPQDs from oxygen and water to enhance the photothermal stability, but also controls the degradation rate of the BPQDs in the physiological medium. The BPQDs/PLGA NSs with the optimal size enable prolonged blood circulation and effective accumulation in tumours based on the EPR effect. Furthermore, in vitro and in vivo experiments are performed systematically to evaluate the performance of the BPQDs/PLGA NSs as biodegradable and biocompatible PTT agents in cancer therapy. \n\n# Results \n\nMorphology and characterization. The ultrasmall BPQDs were prepared by a modified liquid exfoliation technique according to the method reported by our group previously39. The transmission electron microscopy (TEM) image in Fig. 1a reveals the uniform morphology of the BPQDs and the high-resolution TEM image in Fig. 1b discloses lattice fringes of $0.34\\mathrm{nm}$ ascribed to the (021) plane of the BP crystal33. The average lateral size of $3.1\\pm1.8\\mathrm{{nm}}$ (Fig. 1c) is obtained according to the statistical TEM analysis of 200 BPQDs. The atomic force microscopy (AFM) image in Fig. 1d shows the topographic morphology of the BPQDs and the thickness is determined by the cross-sectional analysis. The measured heights of $2.4,\\sim1.8$ and $1.3\\mathrm{nm}$ (Fig. 1e) correspond to BPQDs with $\\sim4$ , 3 and 2 quintuple layers, respectively. Statistical analysis of the AFM data from 200 BPQDs yields an average thickness of $1.8\\pm0.6\\mathrm{nm}$ corresponding to a stack of $3\\pm1$ quintuple layers of BP. \n\nThe BPQDs/PLGA NSs were synthesized by an oil-in-water emulsion solvent evaporation method. As shown in Fig. 1f, the scanning electron microscopy (SEM) image provides evidence of high-yield synthesis of the BPQDs/PLGA NSs. The highmagnification SEM image in Fig. 1g confirms the uniform spherical shape with a smooth surface and the statistical analysis (Fig. 1h) of $200~\\mathrm{NSs}$ discloses an average size of $102.8\\pm35.7\\mathrm{{nm}}$ . The average hydrodynamic size of the BPQDs/PLGA NSs is $\\sim127.6\\pm\\bar{4}3.8\\mathrm{{nm}}$ (Supplementary Fig. 1), which is slightly larger than that determined by SEM and hence, the size of the BPQDs/PLGA NSs is within the accepted range enabling efficient uptake by tumours based on the EPR effect53,54. The TEM images in Fig. 1i and inset depict the internal structure of the BPQDs/PLGA NSs. Many BPQDs are incorporated into each NS and most of them are located inside and protected by the PLGA shells. The loading efficiency and encapsulation efficiency are 12.9 and $83.8\\%$ as determined by energy dispersive X-ray spectroscopy (Fig. 1j) and inductively coupled plasma atomic emission spectroscopy. Raman scattering is further performed to characterize the BPQDs and BPQDs/PLGA NSs (Supplementary Fig. 2). Both samples exhibit three prominent Raman peaks at 359.7, 436.2 and $463.5\\mathrm{cm}^{-1}$ which can be assigned to one out-of-plane phonon mode $(\\mathbf{A}_{\\mathrm{~g~}}^{1})$ and two in-plane modes $\\left(\\mathrm{B}_{2\\mathrm{g}}\\right.$ and $\\mathrm{A}_{\\mathrm{\\scriptsize~g}}^{2},$ ) of BP, respectively, confirming the introduction of BPQDs into PLGA NSs. \n\nStability evaluation under ambient conditions. To evaluate the influence of PLGA encapsulation on the BPQDs stablity, the BPQDs and BPQDs/PLGA NSs with the same amount of BPQDs (20 p.p.m.) were dispersed in water and exposed to air for 8 days and then their optical properties were examined at predetermined time intervals (0, 2, 4, 6 and 8 days). As shown in Fig. 2a, the colour of the solution containing the bare BPQDs become lighter during dispersion, while the BPQDs/PLGA NSs solution retains the colour quite well. The inset photographs in Fig. $^{2\\mathrm{b},\\mathrm{c}}$ show that both dispersions are stable without visible aggregation or sedimentation and it can be confirmed by the Tyndall effect for diluted suspensions. The corresponding absorption spectra are displayed in Fig. $^{2\\mathrm{b},\\mathrm{c}}$ . During initial dispersion, both the BPQDs and BPQDs/PLGA NSs exhibit a typical broad absorption band spanning the ultraviolet and NIR regions. However, the absorbance intensity of the BPQDs in water decreases with dispersion time. The inset spectra in Fig. 2b show the variation in the absorption ratios at $808\\mathrm{nm}$ and the intensity $(A)$ decreases by $27.5\\%$ compared with the original value $\\left(A_{0}\\right)$ after 2 days and $62.5\\%$ after 8 days. In contrast, the absorbance of the BPQDs/ PLGA NSs is more stable as shown in Fig. 2c and the absorbance intensity only drops by $9.7\\%$ after 8 days. Degradation of BP in water is caused by the irreversible reaction with oxygen and water forming oxidized phosphorus species $(\\mathrm{P}\\to\\mathrm{P_{x}}\\mathrm{O}_{\\mathrm{v}})$ followed by conversion of $\\mathrm{P_{x}O_{y}}$ to the final anions (that is, $\\mathrm{PO}_{4}^{3-})^{45}$ . Hence, the absorbance decreases because of the degradation of the bare BPQDs. In contrast, the BPQDs/PLGA NSs show stronger absorption than the BPQDs due to the contribution of the PLGA shells and the larger size of the whole particle. Owing to the strong hydrophobicity of PLGA, the BPQDs are adequately protected from oxygen and water leading to the enhanced stability of the BPQDs/PLGA NSs in water under ambient conditions. Furthermore, comparing with obvious blue-shift of the Raman spectra of the BPQDs after dispersion in water for 8 days (Fig. 2d), no significant change is observed from that of the BPQDs/PLGA NSs (Fig. 2e), confirming their better stability55,56. \n\n![](images/516978237db69ff4c49c48f251ff83392b3add8e2b1eff806cc52217b62c888a.jpg) \nFigure 1 | Morphology and characterization. (a) TEM (scale bar, $20{\\mathsf{n m}}.$ ) and (b) high-resolution TEM images of the BPQDs (scale bar, 1 nm). (c) Statistical analysis of the size of 200 BPQDs based on the TEM images. (d) AFM image of the BPQDs (scale bar, $200\\mathsf{n m},$ . (e) Height profiles along the white lines in d. (f,g) SEM images of the BPQDs/PLGA NSs (scale bar, f: $1\\upmu\\mathrm{m};$ g: 100 nm). (h) Statistical analysis of the size of 200 BPQDs/PLGA NSs according to the SEM images. (i) TEM image of the BPQDs/PLGA NSs (scale bar, $200\\mathsf{n m}.$ ) with the inset displaying the magnified TEM image of a BPQDs/PLGA NS. (j) Energy dispersive X-ray spectroscopy analysis of the BPQDs/PLGA NSs. \n\nThe stability of the photothermal performance of the BPQDs and BPQDs/PLGA NSs in water is further examined (Fig. $2\\mathrm{f,g},$ ). In the beginning, the temperature of the BPQDs solution increases by $19.{\\overset{-}{3}}{\\overset{\\circ}{\\mathrm{C}}}$ after $808\\mathrm{nm}$ laser irradiation $(1.{\\overset{-}{0}}\\mathrm{W}\\mathrm{cm}^{-2})$ for $10\\mathrm{min}$ but after 8 days, the temperature rise is only $8.7^{\\circ}\\mathrm{C}$ due to the BP degradation. In comparison, after 8 days, the temperature of the \n\nBPQDs/PLGA NSs solution increases by $19.9^{\\circ}\\mathrm{C}$ after irradiation for $10\\mathrm{min}$ and it is very close to the initial one of $21.1^{\\circ}\\mathrm{C}$ . It indicates that PLGA encapsulation can effectively prevent the degradation of BPQDs and maintain the photothermal characteristics in water. However, $\\sim10\\%$ loss in the absorbance and photothermal performance is observed from the BPQDs/PLGA NSs after dispersion in water for 8 days due to the biodegradable nature of PLGA in water48–51 consequently exposing a small amount of the BPQDs to water. Nonetheless, since PLGA almost does not degrade in air, the BPQDs/PLGA NSs can be stored as powders for at least 3 months (Supplementary Fig. 3). \n\n# Biodegradation behaviour of the BPQDs and BPQDs/PLGA NSs. \n\nThe biodegradation behaviour of the BPQDs and BPQDs/PLGA NSs in the phosphate-buffered saline (PBS; pH 7.4) is investigated in a horizontal shaker at $37^{\\circ}\\mathrm{C}$ PBS is a suitable medium to study biodegradation in vitro57. Compared with natural dispersion in water, the bare BPQDs in PBS subjected to agitation degrade faster giving rise to greater absorption and photothermal loss during $24\\mathrm{h}$ (Supplementary Fig. 4). In contrast, the BPQDs/PLGA NSs maintain the stability and performance during the initial $24\\mathrm{h}$ (Fig. 3a,b). \n\nThe long-term biodegradability of the BPQDs/PLGA NSs in PBS is further assessed. As shown in Fig. $^{3\\mathrm{a},\\mathrm{b}}$ , the absorption and photothermal performance of the BPQDs/PLGA NSs deteriorates after 8 weeks due to the biodegradability of PLGA. The residual weights of the BPQDs/PLGA NSs during degradation are measured and the residual weight percentage is determined by the following formula: residual weight $\\dot{(\\%)}=W r\\times100/W o,$ where Wr is the dry weight of the sample after degradation and \n\n![](images/a9647607fe1aeaf42925bdf7ae56ff87a775ec2ecb7cc5e0af6bdd531468cfa9.jpg) \nFigure 2 | Stability evaluation under ambient conditions. (a) Photographs and (b,c) Absorption spectra of the BPQDs and BPQDs/PLGA NSs with the same amount of BPQDs (20 p.p.m.) after storing in water for different periods of time. Insets in (b,c): tyndall effect and variation of the absorption ratios $(A/A_{0})$ at $808\\mathsf{n m}$ . (d,e) Raman scattering spectra acquired from the BPQDs and BPQDs/PLGA NSs, respectively, after storing in water for 0 and 8 days. $\\mathbf{\\Gamma}(\\mathbf{f},\\mathbf{g})$ Photothermal heating curves of the BPQDs and BPQDs/PLGA NSs, respectively, after storing in water for different periods of time and being irradiated with the $808{\\mathsf{n m}}$ laser $(1\\mathsf{W}\\mathsf{c m}^{-2})$ for 10 min. \n\nWo is the initial weight of the sample. As shown in Fig. 3c, the residual weight of the BPQDs/PLGA NSs exhibits a downward trend with a small degradation rate during the first week but it accelerates showing nearly $80\\%$ loss after 8 weeks. Figure 3d shows the corresponding SEM and TEM images. After 1 week, the NSs maintain the integrity generally with only slight morphological changes (arrow indicated). After 4 weeks, degradation is visible as indicated by the shape change and after 8 weeks, the morphology of the NSs is completely disrupted and very few residues of the BPQDs can be observed (arrow indicated). The influence of laser irradiation on the degradation of the BPQDs/PLGA NSs is further assessed (Supplementary Fig. 5). After laser illumination $(808\\mathrm{nm},1\\mathrm{W}\\mathrm{cm}^{-2})$ for $10\\mathrm{min}$ , no evident morphological change and influence on the degradation rate can be found from the NSs suggesting that the photothermal treatment does not affect the biodegradability of the NSs significantly. \n\n![](images/308c5cdcb140ab8409165f3afae6a4c4e8125e091135a877710443955175cf4f.jpg) \nFigure 3 | Biodegradation performance. (a) Absorbance spectra of the BPQDs/PLGA NSs (internal BPQDs concentration is 10 p.p.m.) dispersed in PBS for $\\mathsf{0}\\mathsf{h}.$ , 24 h and 8 weeks with the inset showing the corresponding photographs. (b) Photothermal heating curves of the BPQDs/PLGA NSs dispersed in PBS for $0\\mathfrak{h}$ , $24\\mathsf{h}$ and 8 weeks and irradiated with the $808\\mathsf{n m}$ laser $(1\\mathsf{W}\\mathsf{c m}^{-2})$ for $10\\min$ . (c) Residual weight of the BPQDs/PLGA NSs after degradation in PBS as a function of time $_{\\cdot n=5}$ ; $^{\\star}P<0.05$ , $^{\\star\\star}P<0.01$ , $P{<}0.001$ ; ANOVA). (d) SEM images (scale bars, $500\\mathsf{n m}.$ ) of the BPQDs/PLGA NSs after degradation in PBS for 1, 4 and 8 weeks together with the corresponding TEM image (scale bar, $200\\mathsf{n m})$ of the NSs after degradation for 8 weeks. (e) Schematic representation of the degradation process of the BPQDs/PLGA NSs in the physiological environment. \n\nThe degradation process is illustrated in Fig. 3e. When the BPQDs/PLGA NSs are in the physiological environment, the external PLGA shells degrade gradually due to hydrolysis of the ester linkage into segments (reduced molecular weight), oligomers and monomers, and finally carbon dioxide and water52,58. Degradation of PLGA disrupts the NSs and triggers release of the interior BPQDs which degrade rapidly if they are not protected by PLGA. The final degradation products from the BPQDs are nontoxic phosphate and phosphonate45–47, both of which are commonly found in the human body41,42. In in vivo applications, the unique biodegradability of the BPQDs/PLGA NSs not only circumvents rapid degradation of the optical performance, but also enables harmless clearance from the body in a reasonable period of time after fulfilling their therapeutic functions. \n\nIn vitro cytotoxicity assays and photothermal experiments. The possible cytotoxicity of the BPQDs/PLGA NSs towards normal and tumour cells is probed (Fig. 4a). The relative viability of the human skin fibroblast, MCF7 (human breast cancer cells) and B16 (melanoma cells) cells incubated with the BPQDs/PLGA NSs (internal BPQDs concentration is 0, 2, 5, 10, 20, 50 and $100{\\mathrm{p.p.m.}})$ for $48\\mathrm{h}$ was determined by the cell counting kit-8 (CCK-8) assay. No significant cytotoxicity can be observed from all types of cells even at the concentration of BPQDs as high as $100{\\mathrm{p.p.m}}$ ., which far surpasses that used in the following photothermal experiments. \n\nThe photothermal ability of the BPQDs/PLGA NSs for killing cancer cells is further investigated. After incubation with the NSs for $^{4\\mathrm{h}}$ , the MCF7 and B16 cells were irradiated with the $808\\mathrm{nm}$ laser $(1\\mathrm{W}\\mathrm{cm}^{-2})$ for $10\\mathrm{min}$ and the cell viability was quantitatively assessed by the CCK-8 assay (Fig. 4b). A dosedependent PTT effect can be observed. Almost all of the cancer cells are killed after incubating with the NSs containing only 10 p.p.m. of BPQDs and exposure to the NIR laser but on the contrary, direct irradiation of the cells in the absence of the NSs does not compromise the cell viability. Similar results can be observed from the fluorescence micrographs (Fig. 4c) of the cells co-stained by calcein AM (live cells, green fluorescence) and propidium iodide (PI, dead cells, red fluorescence) after the PTT treatment. The results demonstrate the good PTT efficiency of the BPQDs/PLGA NSs in sterilizing cancer cells. \n\n![](images/e8e62ad40fd36d09686129a4b2969b6fdba2a609f924f2f7fb29a338025e1a23.jpg) \nFigure 4 | Cell experiments. (a) Relative viability of the human skin fibroblast normal cells, MCF7 cancer cells and B16 melanoma cells after incubation with BPQDs/PLGA NSs (internal BPQDs concentrations of 0, 2, 5, 10, 20, 50 and 100 p.p.m.) for $48\\mathsf{h}$ . (b) Relative viability of the MCF7 and B16 cells after incubation with BPQDs/PLGA NSs (internal BPQDs concentrations of 0, 2, 5, 10 and 20 p.p.m.) for $4h$ after irradiation with the $808\\mathsf{n m}$ laser $(1\\mathsf{W}\\mathsf{c m}^{-2},$ ) for 10 min. (c) Corresponding fluorescence images (scale bars, $100\\upmu\\mathrm{m}$ for all panels) of the cells stained with calcein AM (live cells, green fluorescence) and PI (dead cells, red fluorescence). \n\nIn the next step, the PTT efficiency of the BPQDs/PLGA NSs was compared with that of gold nanorods (AuNRs), one of the common photothermal agents. On account of the large NIR extinction coefficient and high photothermal conversion efficiency of the BPQDs (ref. 39), the BPQDs/PLGA NSs are more efficient in increasing the solution temperature than the AuNRs (Supplementary Fig. 6). In the cell photothermal experiments, both of the NSs (containing only 10 p.p.m. of BPQDs) and AuNRs $(72.4\\mathrm{p.p.m.})$ can kill the cancer cells almost completely, but it is clear that less BPQDs are needed. These results confirm the suitability of BPQDs/PLGA NSs as an efficient PTT agent. \n\nIn vivo toxicity. The in vivo toxicology of the BPQDs/PLGA NSs is investigated systematically. Sixty healthy female $\\mathrm{Balb/c}$ mice (6 weeks old) were randomly divided into 4 groups and subjected to variable conditions, including: (1) control group without any treatment, (2) NSs directly intravenously injected into the mice, (3) NSs intravenously injected into the mice after $808\\mathrm{nm}$ laser irradiation for $10\\mathrm{min}$ and (4) NSs intravenously injected into the mice which are then exposed to artificial daylight for $24\\mathrm{h}$ . The injection dose of the NSs is $\\sim10\\mathrm{mg}\\mathrm{BP}\\mathrm{kg}^{-1}$ and haematological, blood biochemical and histological analyses were performed at time points of 1, 7 and 28 days post-injection. \n\nThe standard haematology markers including the white blood cells, red blood cells, haemoglobin, mean corpuscular volume, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, platelets and haematocrit were measured (Fig. 5a). Compared with the control group, all the parameters in the three NSs-treated groups at all time points appear to be normal and the differences between are not statistically significant 1 $P$ value $>0.05$ ). These results indicate that the BPQDs/PLGA NSs do not cause obvious infection and inflammation in the treated mice59. \n\nBlood biochemical analysises were carried out and various parameters including alanine transaminase, aspartate transaminase, total protein, globulin, total bilirubin, blood urea nitrogen, creatinine and albumin were examined (Fig. 5b). Compared with the control group, no meaningful difference can be observed from the three NSs-treated groups at all time points. Hence, the NSs treatment does not affect the blood chemistry of mice. Furthermore, since alanine transaminase, aspartate transaminase and creatinine are closely related to the functions of the liver and kidney of mice59, the results demonstrate that the NSs induce no obvious hepatic and kidney toxicity in mice. \n\nFinally, the corresponding histological changes of organs were checked by immunohistochemistry using major organs including the liver, spleen, kidney, heart and lung collected and sliced for haematoxylin and eosin staining (Fig. 5c). No noticeable signal of organ damage can be observed during the whole-treatment period from all the groups suggesting no apparent histological abnormalities or lesions in the NSs-treated groups for the test dose. \n\n![](images/182164f01b04ad679c50cb556d5a4a9641f95d519836574bcc84907744ea9e2b.jpg) \nFigure 5 | In vivo toxicity. (a) Haematological data of the mice intravenously injected with the BPQDs/PLGA NSs at 1, 7 and 28 days post-injection. The terms are following: white blood cells, red blood cells, haemoglobin, mean corpuscular volume, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, platelets and haematocrit. (b) Blood biochemical analysis of the NSs-treated mice at 1, 7 and 28 days post-injection. The results show the mean and s.d. of aminotransferase, aminotransferase, total protein, globulin, total bilirubin, blood urea nitrogen, creatinine and albumin (AL B). (c) Histological data (haematoxylin and eosin stained images) obtained from the liver, spleen, kidney, heart and lung of the NSs-treated mice at 1, 7 and 28 days post-injection (scale bars, $100\\upmu\\mathrm{m}$ for all panels). \n\nAccording to above analyses, inappreciable toxicity is observed from the BPQDs/PLGA NSs regardless of NIR laser irradiation. Even if the NSs-treated mice are under artificial daylight illumination for $24\\mathrm{h}$ , no significant toxic side effects can be found, indicating that the NSs induce no evident phototoxicity which has generally been observed from many photosensitizer molecules60. These results demonstrate the good biocompatibility of the BPQDs/PLGA NSs. \n\nIn vivo biodistribution. Since significant amounts of $P$ exist in the animal body, it is very difficult to direct obtain biodistribution information of the BP-based materials (Supplementary Fig. 7). Therefore, to study the in vivo behaviour of the BPQDs/PLGA \n\nNSs, Cy5.5, a commonly used NIR fluorescent dye61 was utilized to label the BPQDs/PLGA NSs by entrapping it into the NSs using the oil-in-water emulsion solvent evaporation method mentioned above. The synthesized $\\mathrm{Cy}5.5$ -labelled BPQDs/PLGA NSs with similar size of the BPQDs/PLGA NSs exhibit bright and stable fluorescence at about $695\\mathrm{nm}$ (Supplementary Fig. 8) enabling non-invasive monitoring and quantitative examination of the NSs biodistribution in the mice. Hence, the Balb/c nude mice bearing MCF7 breast tumours are intravenously injected with the $\\mathrm{Cy}5.5$ -labelled BPQDs/PLGA NSs $(100\\upmu\\mathrm{l}$ of $\\mathrm{1\\mg}$ BP $\\mathrm{ml}^{-1}$ for each mouse) for the biodistribution examinations. \n\nThe pharmacokinetics profile of the $\\mathrm{Cy}5.5$ -labelled $\\mathrm{BPQDs}/$ PLGA NSs was examined by fluorometry to determine the concentrations in blood at different time intervals post-injection (Fig. 6a). Blood circulation of the NSs obeys the typical two compartment model. After the first phase (distribution phase, with a rapid decline) with a half-life of only $1.50\\pm0.21\\mathrm{h}$ , the NSs in circulating blood exhibit a long second phase (elimination phase, the predominant process for NSs clearance) with a half-life of $22.66\\pm3.65\\mathrm{h}$ . The volume of distribution $(V)$ is measured to be $2.31\\pm0.72\\mathrm{ml}$ and the area under curve (AUC) is $0.65\\pm0.11\\mathrm{mghml^{-1}}$ . The long blood circulation of the NSs delays the macrophage clearance in reticuloendothelial systems62, favouring enhanced tumour targeting by the EPR effect. \n\n![](images/abb97d31023ad2f004df4eb8209a8cf0565507fb031d665a582de2b81d0a4dbf.jpg) \nFigure 6 | Pharmacokinetic and biodistribution analysis. (a) Blood circulation curve of the ${\\mathsf{C y}}5.5$ -labelled BPQDs/PLGA NSs determined by measuring the ${\\mathsf{C y}}5.5$ fluorescence intensity in the blood of the MCF7 tumour-bearing Balb/c mice at different time points post-injection of the NSs. The pharmacokinetics obeys a typical two compartment model (as shown by the fitted curve). (b) In vivo fluorescence images of the NSs-treated mice at different time points post-injection. (c) $\\boldsymbol{{\\cal E}}\\boldsymbol{x}$ vivo fluorescence images of the tumour and major organs from the NSs-treated mice at $24\\mathsf{h}$ post-injection. H, heart; I, intestine; K, kidney; Lu, lung; Li, liver; Sp, spleen; St, stomach; T, tumour. (d) Fluorescence microscopy images of the tumour sections at macroorganizational level (scale bars, 1 mm) and micro-organizational level (scale bars, $50\\upmu\\mathrm{m})$ from the NSs-treated mice. The NSs are shown in red and the nuclei are shown in blue by staining with DAPI. (e) Quantitative biodistribution analysis of the NSs in mice by measuring the ${\\mathsf{C y}}5.5$ fluorescence intensity in the tumours and major organs at different time points post-injection. \n\nThe biodistribution of the $\\mathrm{Cy}\\bar{5}.5$ -labelled BPQDs/PLGA NSs in the mice is directly observed by fluorescence imaging. As shown in Fig. 6b, considerable fluorescence can be observed from the tumour at $^\\mathrm{1h}$ post-injection and the subcutaneous tumour can be definitely delineated from the other tissues. The fluorescence intensity in the tumour gradually increases up to $24\\mathrm{h}$ indicating that the NSs can continuously accumulate at the tumour site. At $48\\mathrm{h}$ post-injection, the tumour still maintains strong fluorescence, suggesting good retention of the NSs in the tumour. Figure 6c shows the ex vivo fluorescence images obtained at $24\\mathrm{h}$ post-injection, in which bright fluorescence can be observed from the tumour and some organs including the liver, spleen and kidney. Macro-organizational examination of a tumour $(\\sim50\\mathrm{mm}^{2})$ in Fig. 6d (up) shows that the NSs are distributed throughout the entire tumour section. Moreover, Fig. 6d highlights the significant colocalization of the nuclei (DAPI staining, shown in blue) and NSs (shown in red) in the tumour section, confirming efficient penetration of the NSs within the tumour. \n\nA quantitative biodistribution analysis of the $\\mathrm{Cy}5.5$ -labelled BPQDs/PLGA NSs in mice is conducted (Fig. 6e). The tumour and major organs were collected from the mice, weighed and solubilized by a lysis buffer at different time intervals post-injection. The homogenized tissue lysates were diluted and measured by fluorometry to quantitatively determine the NSs concentrations. At $24\\mathrm{h}$ post-injection, large NSs concentrations can be found from not only the tumour, but also organs including the liver, spleen and kidney as consistent with the above ex vivo fluorescence examination. Uptake of the NSs by the liver and spleen may be due to reticuloendothelial system absorption62, while the kidney uptake can be associated with possible renal excretion63. Even so, considerable uptake of the NSs by the tumour can be achieved on account of the EPR effect21. \n\nSince the NSs in the physiological medium can maintain their integrity (Fig. 3c,d) without causing evident fluorescence decrease of the entrapped $\\mathrm{Cy}5.5$ (Supplementary Fig. 8) for 7 days, the fluorescence examinations were further used to estimate the time-dependent residual amounts of the NSs in mice during the 7 days post-injection. The residual ratios were calculated by normalizing the total residual amounts in these organs and tissues to initial total amounts. It can be calculated that the residual ratio of the NSs decreases from $90.1\\%\\mathrm{ID}\\mathrm{g}^{-1}$ at day 1 $(24\\mathrm{h})$ to only $29.9\\%\\mathrm{ID}{\\bf g}^{-1}$ at day 7, suggesting the possibility of the NSs to be partially metabolized. It is known that such nanoparticles is generally difficult to be completely metabolized and excreted from the body directly. However, the aforementioned biodegradability of the NSs enables harmless clearance from the body in a reasonable period of time (for example, several months). \n\n![](images/0800d1b3a738eb1d1514d16e1a1b1d90ab25dab668c88e3ec3b87a910ff3749d.jpg) \nFigure 7 | In vivo photothermal cancer therapy. (a) Infrared thermographic maps and (b) Time-dependent temperature increase in the MCF7 breast tumour-bearing nude mice irradiated by the $808\\mathsf{n m}$ laser $(1\\mathsf{W}\\mathsf{c m}^{-2})$ at $24\\mathsf{h}$ after separate intravenous injection with $100\\upmu\\upiota$ of PBS, PLGA NSs, BPQDs $(1\\mathsf{m g}\\mathsf{m}!^{-1})$ and BPQDs/PLGA NSs $(1\\mathsf{m g}\\mathsf{B P}\\mathsf{m}|^{-1})$ with the colour bar referring to the relative temperature. (c) Growth curves of MCF7 breast tumour in different groups of nude mice treated with PBS, PLGA NSs, BPQDs $(1\\mathsf{m g}\\mathsf{m}!^{-1})$ and BPQDs/PLGA NSs ( $1\\mathsf{m g}\\mathsf{B P}\\mathsf{m}|^{-1};$ with the NIR laser irradiation. \n\nIn vivo photothermal cancer therapy. To evaluate the potential of the BPQDs/PLGA NSs in cancer PTT in vivo, MCF7 breast tumours were established in situ in the Balb/c nude mice. After the tumour volume has reached $\\sim200\\mathrm{mm}^{3}$ , 20 mice were randomly divided into four groups and aliquots $(100\\upmu\\mathrm{l})$ of PBS, PLGA NSs, BPQDs $(1\\mathrm{mg}\\mathrm{ml}^{\\cdot-1},$ ) and BPQDs/PLGA NSs $(1\\mathrm{mg}\\mathrm{BP}\\mathrm{ml}^{-1}, $ were injected separately via the tail vein. At $24\\mathrm{h}$ post-injection, the mice were anaesthetized and the entire region of the tumour was irradiated with the $808\\mathrm{nm}$ laser $(1\\mathrm{W}\\mathrm{cm}^{-2},$ ) for $10\\mathrm{min}$ . To monitor the photothermal effects in vivo, the infrared thermographic maps and changes in the tumour temperature were recorded by an infrared thermal imaging camera simultaneously (Fig. 7a,b). Under NIR laser irradiation, the tumour temperature of the mice injected with the bare BPQDs increases by only $10.8^{\\circ}\\mathrm{C}$ which is just slightly higher than that of two other control groups of mice injected with the PLGA NSs $(7.8^{\\circ}\\mathrm{C})$ and PBS $(6.2^{\\circ}\\mathrm{C})$ . In contrast, with regard to the mice injected with the BPQDs/PLGA NSs, the tumour temperature rises rapidly by $26.3^{\\circ}\\mathrm{C}$ within $10\\mathrm{min}$ of the NIR laser irradiation and the maximum temperature reaches ${58.8^{\\circ}\\mathrm{C}},$ which is high enough for tumour ablation64. The AuNRs were employed as a positive control in the photothermal experiments (Supplementary Fig. 9). Under the same irradiation condition, the tumour temperature of the mice injected with $100\\upmu\\mathrm{l}$ of the AuNRs $(3.62\\mathrm{mg}\\mathrm{ml}^{-1})_{,}$ ) increases to $54.{\\dot{4}}^{\\circ}\\mathrm{C},$ which is lower than that induced by the NSs. These results indicate the high efficiency of the BPQDs/PLGA NSs as a PTT agent for in vivo tumour ablation. \n\nTo further evaluate the influence of PLGA encapsulation on the in vivo PTT efficiency of the BPQDs, the BPQDs and BPQDs/PLGA NSs with different concentrations (0.5, 1, 2 and $3\\mathrm{mg~BPml^{-1}}.$ ) were injected intravenously into the tumourbearing nude mice, which were irradiated with the NIR laser at different times (1, 4, 8, 12, 24 and $48\\mathrm{h}$ ) post-injection. As shown in Supplementary Fig. 10, the BPQDs/PLGA NSs produce larger tumour temperature increase than the bare BPQDs under all conditions. The better in vivo PTT efficiency of the BPQDs/PLGA NSs than bare BPQDs pertaining to tumour ablation can be attributed to two factors. First, the BPQDs/PLGA NSs have better stability than the bare BPQDs and so can maintain the photothermal performance during circulation in the body. Second, compared with the ultrasmall BPQDs with a size of $\\sim3\\mathrm{nm}$ (ref. 16), the size of the BPQDs/PLGA NSs of $\\sim100\\mathrm{nm}$ is more appropriate for efficient tumour targeting and retension during the long blood circulation in the body. \n\nAfter the above photothermal treatments with different samples, the tumour size was measured every 2 days after the treatment (Supplementary Table 1) and no obvious sign of toxic side effects such as abnormal body weight, activity, eating, drinking or neurological issues could be observed from all the experimental groups. The tumour volume variations determined from the different groups are consistent with those of temperature (Fig. 7c). The mice injected with the BPQDs/PLGA NSs and irradiated by the NIR laser, their tumours shrink gradually, are obliterated only leaving black scars, and then are completely cured in $\\sim16$ days. More importantly, not even a single case of recurrence is observed. With regard to the mice treated with the bare BPQDs, the tumour growth is not inhibited effectively and so are the mice treated with the PLGA NSs or PBS alone. The mice treated with the BPQDs/PLGA NSs are tumourfree after the treatment and all survive for over 40 days until killed. In contrast, the mice in the other groups have a life span of 18–26 days and the tumour volume is as large as $1{,}600\\mathrm{\\mm}^{3}$ These results demonstrate the excellent efficacy of the NSs for photothermal cancer therapy of the BALB/c nude mice which have a deficient immune system. To further demonstrate the applicability of the NSs-mediated PTT, BALB/c mice, with a competent immune system, were employed as another animal model in the photothermal treatments. As shown in Supplementary Fig. 11, the BPQDs/PLGA NSs also exhibit excellent photothermal efficacy to kill the melanoma tumour in the $\\mathrm{{\\bar{B}A L B/c}}$ mice without causing obvious toxic side effects. The results demonstrate that the NSs-mediated PTT is suitable for such two kinds of animals with different immune systems. \n\nThe anticancer efficiency is further analysed by a terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end-labelling (TUNEL) assay, which is generally utilized to detect the intratumoral levels of apoptosis. As shown in Supplementary Fig. 12, no or few TUNEL-positive cells (shown in green) are observed from the PBS, PLGA and BPQDs groups, while significant colocalization of nuclei (DAPI staining, shown in blue) and TUNEL-positive apoptotic cells (shown in green) can be observed from the BPQDs/PLGA NSs group. Moreover, the apoptosis examination at macro-organizational level $\\mathrm{\\Omega}^{\\prime}\\sim10\\mathrm{mm}^{2\\cdot}$ ) shows that the TUNEL-positive apoptotic cells are distributed throughout the tumour section (Supplementary Fig. 13). These results indicate that the NSs-mediated PTT can induce cancer cell death by activating apoptosis in the tumour. \n\nThe depth of photothermal damage is investigated in the tumour-bearing nude mice with the tumour volume as large as $1,000\\mathrm{mm}^{3}$ . After the photothermal treatment, intratumoral apoptosis of the tumour sections at different depths was detected by a TUNEL assay (Supplementary Fig. 14). Most cancer cells undergo apoptosis in the tumour sections at depths of no more than $6\\mathrm{mm}$ . Although evident depth-dependent decay of the PTT efficiency is observed when the depth is over $6\\mathrm{mm}$ , significant apoptosis of cells can still be found from the section at the depth of $10\\mathrm{mm}$ . The considerable photothermal damage to deep tissues stems from the excellent PTT efficiency of the NSs and high tissue penetration ability of NIR light. It should be noted that although the penetration depth of NIR light is limited to be no more than $10\\mathrm{mm}$ (ref. 21), clinical photothermal treatment of deep tumours is still achievable with the aid of specialized medical devices such as endoscopic ones in combination with optical fibres as well as implanted NIR devices65,66. \n\n# Discussion \n\nBPQDs/PLGA NSs with highly efficient photothermal performance are fabricated using PLGA loaded with $3\\mathrm{nm}$ BPQDs by an oil-in-water emulsion solvent evaporation method. Owing to the strong hydrophobicity of PLGA, rapid degradation of the BPQDs is prevented so that the photothermal performance of the BPQDs/PLGA NSs in the physiological environment is improved significantly. No appreciable toxicity and good biocompatibility are observed from the BPQDs/PLGA NSs based on the haematological, blood biochemical and histological analyses. Boasting long blood circulation in the body, the NSs after intravenous injection show efficient tumour accumulation by the EPR effect. By activating apoptosis of cancer cells even in the deep tumour tissues, the NSs give rise to highly efficient tumour ablation under NIR laser irradiation, and the NSs-mediated PTT is proven to be suitable for two kinds of animals with different immune systems. \n\nCompared with previously reported nanoagents, these $\\mathrm{\\BPQDs}/$ PLGA NSs are especially attractive due to the unique biodegradability (as illustrated in Supplementary Fig. 15). PLGA, which is FDA-approved degrades by hydrolysis forming carbon dioxide and water eventually in a reasonable time (for example, several months). After intravenous administration into the body, the BPQDs/PLGA NSs with size of $\\sim100\\mathrm{nm}$ can circumvent rapid degradation of the BPQDs in the optical performance during long-time circulation (for example, $24\\mathrm{h}$ ), and ensure sufficient tumour accumulation for highly efficient photothermal cancer therapy. After fulfilling their therapeutic functions, degradation of PLGA disrupts the NSs causing the release of the BPQDs. The BPQDs then degrade to form nontoxic phosphate and phosphonate enabling harmless clearance from the body. In addition, such slow degradation of the BPQDs circumvents the local imbalance of phosphorus in vivo. Therefore, such BP-based PTT agent with the unique combination of biodegradability and biocompatibility has immense clinical potential. \n\n# Methods \n\nMaterials. The BP crystals were purchased from a commercial supplier (Smart-Elements) and stored in a dark Ar glovebox and N-methyl-2-pyrrolidone (NMP) $(99.5\\%$ , anhydrous) was obtained from Aladdin Reagents. The PLGA (50:50, MW: 40,000–70,000), polyvinyl alcohol (MW: 9,000–10,000), and dichloromethane (DCM) were purchased from Sigma-Aldrich (Santa Barbara, USA). The PBS $\\mathrm{(pH7.4)}$ , foetal bovine serum, H-DMEM, trypsin-EDTA, Calcein AM and PI were obtained from Gibco Life Technologies (AG, Switzerland). The Cy5.5 NIR fluorescence dye was purchased from Lumiprobe (US). All the chemicals used in this study were analytical reagent grade and used without further purification. \n\nSynthesis of BPQDs. The BPQDs were prepared by a simple liquid exfoliation technique described in the literature39. In brief, $20\\mathrm{mg}$ of the bulk BP powders were dispersed in $20\\mathrm{ml}$ of NMP and sonicated with a sonic tip (ultrasonic frequency: $19{-}25\\mathrm{kHz})$ for $^{4\\mathrm{h}}$ (period of 2 s with the interval of 4 s) using a power of $^{1,200\\mathrm{W}}$ . The mixture was sonicated overnight in an ice bath using a power of $300\\mathrm{W}$ . The dispersion was centrifuged for $20\\mathrm{min}$ at $7{,}000\\mathrm{r.p.m}$ . and the supernatant containing the BPQDs was decanted gently. \n\nPreparation of BPQDs/PLGA NSs. The BPQDs/PLGA NSs were prepared by an oil-in-water emulsion solvent evaporation method. IN brief, $10\\mathrm{ml}$ of the BPQDs suspension in NMP $(200\\ \\mathrm{p.p.m.})$ were centrifuged for $20\\mathrm{min}$ at $12,000{\\mathrm{r.p.m}}$ . and the precipitate was redispersed in $\\mathrm{1ml}$ of the PLGA solution in DCM with a concentration of $10\\mathrm{mg}\\dot{\\mathrm{ml}}^{-1}$ . After probe sonication for $5\\mathrm{min}$ , the mixture was dispersed in $10\\mathrm{ml}$ of $0.5\\%$ (w/v) polyvinyl alcohol aqueous solution and sonicated for another $5\\mathrm{{min}}$ . The emulsion was stirred overnight at room temperature to evaporate the residual DCM. Finally, the NS suspension was centrifuged at $7{,}000\\mathrm{r.p.m}$ . for $15\\mathrm{min}$ , washed twice with deionized water to remove dissociated BPQDs, and re-suspended in the aqueous solution. \n\nMorphology and characterization. The TEM images were acquired on the JEOL JEM-2010 TEM at an acceleration voltage of $200\\mathrm{kV}$ and AFM was performed on an MFP-3D-S AFM (Asylum Research, USA) using the tapping mode in air (NanoSensors SSS-NCH probe with the tip radius as small as $2\\mathrm{nm}$ ). The BP concentration was determined by inductively coupled plasma atomic emission spectroscopy (IRIS Intrepid II XSP, thermo Electron Corporation, USA). The SEM images were obtained on the field-emission SEM (NOVA NANOSEM430, FEI, Netherlands) at $5{\\mathrm{-}}10\\mathrm{kV}$ after gold coating for 120s (EM-SCD500, Leica, Germany). The energy dispersive X-ray spectroscopy was conducted on the Oxford INCA 300 equipped on the SEM. The Raman scattering was performed on the Horiba Jobin-Yvon Lab Ram HR VIS high-resolution confocal Raman microscope with the $633\\mathrm{nm}$ laser as the excitation source. The ultraviolet–visibleNIR absorption spectra were acquired on a TU-1810 ultraviolet–visible spectrophotometer (Purkinje General Instrument Co. Ltd. Beijing, China) using QS-grade quartz cuvettes at room temperature. \n\nNIR laser-induced heat conversion. A fiber-coupled continuous semiconductor diode laser $\\cdot808\\mathrm{nm}$ , KS-810F-8000, Kai Site Electronic Technology Co., Ltd. Shaanxi, China) was employed in the experiments. Sample $(1\\mathrm{ml})$ in a 1-cm path length quartz cuvette was irradiated by the laser with a power density of $1\\mathrm{W}\\mathrm{cm}^{-2}$ for $\\mathrm{{10}m i n}$ . The laser spot was adjusted to cover the entire surface of the sample. Real-time thermal imaging was performed and the maximum temperature was recorded by the Fluke Ti27 infrared thermal imaging camera (USA). \n\nIn vitro degradation. The BPQDs and the $\\mathrm{BPQDs},$ PLGA NSs with the same amount of BPQDs (10 p.p.m.) were dispersed in PBS $\\mathrm{(pH~7.4)}$ , kept in closed sample vials and maintained in a horizontal shaker at $37^{\\circ}\\mathrm{C}$ . At predetermined time intervals, the BPQDs/PLGA NSs were centrifuged at $7{,}000\\mathrm{r.p.m}$ . and dried under vacuum. The residual weight percentages of the sample for different degradation time (0–8 weeks) were determined by the following formula: residual weight $(\\%)=W r\\times100/W o$ , where $W r$ is the dry weight of the sample after degradation and $W o$ is the initial weight of the sample. Degradation of the BPQDs/PLGA NSs after $808\\mathrm{nm}$ laser $(1\\mathrm{W}\\mathrm{cm}^{-2}$ ) illumination for $10\\mathrm{min}$ was also evaluated by the above method. \n\nIn vitro cytotoxicity assays. The human skin fibroblast, MCF7 human breast cancer cells and B16 melanoma cells were purchased from China Type Culture Collection (CTCC) obtained from the American Type Culture Collection (ATCC). Cells were routinely tested for mycoplasma contamination using MycoSET Mycoplasma real-time PCR detection Kit (Life Technologies, Foster City, CA, USA). These cells were seeded on a 96-well plate $(1\\times10^{4}$ cells per well) with $200\\upmu\\mathrm{l}$ of H-DMEM (Gibco BRL) supplemented with $10\\%$ $\\scriptstyle\\left(\\mathbf{v}/\\mathbf{v}\\right)$ foetal bovine serum and maintained in an incubator at $37^{\\circ}\\mathrm{C}$ in a humidified atmosphere consisting of $5\\%\\mathrm{CO}_{2}$ . After culturing for $12\\mathrm{h}$ , the cell culture medium was replaced with $200\\upmu\\mathrm{l}$ of the H-DMEM medium containing different concentrations of BPQDs/PLGA NSs (internal BPQDs concentrations of 0, 2, 5, 10, 20, 50 and $100{\\mathrm{p.p.m}}$ ., respectively). Five multiple holes were set for every sample. The cell viability was quantitatively determined using the CCK-8 assay. The absorbance at $450\\mathrm{nm}$ was determined on a microplate spectrophotometer (Varioskan Flash 4.00.53, Finland) as an indicator of viable cells. The cell viability was normalized to the control group without any treatment and the following formula was used to calculate cell growth inhibition: cell viability $(\\%)=$ (mean of Abs. value of treatment group/mean Abs. value of control) $\\times100\\%$ . \n\nIn vitro photothermal experiments. The MCF7 and B16 cells $(1\\times10^{4}$ cells per well) were seeded on 96-well plates and incubated overnight in an incubator at $37^{\\circ}\\mathrm{C}$ . After rinsing with PBS, the MCF7 and B16 cells were incubated with BPQDs/PLGA NSs (internal BPQDs concentrations of 0, 2, 5, 10 and $20{\\mathrm{p.p.m.}}$ ) for $^{4\\mathrm{h}}$ at $37^{\\circ}\\mathrm{C}$ and then illuminated with the $808\\mathrm{nm}$ laser $(1\\mathrm{W}\\mathrm{cm}^{-2},$ ) for $10\\mathrm{min}$ . The laser spot was adjusted to fully cover the area of each well. After irradiation, the cells were incubation for $12\\mathrm{h}$ , rinsed with PBS, and co-stained with Calcein AM and PI for $30\\mathrm{min}$ . Afterwards, the cells of the experimental group were rinsed with PBS and examined by an Olympus IX71 inverted fluorescence microscope. The cell viability was determined quantitatively by the CCK-8 assay and compared with the control group which did not undergo any treatment. \n\nThe AuNRs were employed as a positive control in the in vitro photothermal experiments. The MCF7 cells was incubated with AuNRs (concentrations of 0, 7.2, 18.1, 36.2 and $72.4\\:\\mathsf{p.p.m.})$ for $\\mathrm{4h}$ at $37^{\\circ}\\mathrm{C}$ and then irradiated with the $808\\mathrm{nm}$ laser $(1\\mathrm{W}\\mathrm{cm}^{-2})$ for $10\\mathrm{min}$ . The corresponding fluorescence images of the cells and cell viability were assessed by the above method. \n\nIn vivo toxicity. Sixty healthy female Balb/c mice (6 weeks old) were obtained from Slac Laboratory Animal Co. Ltd (Hunan, China) and all the in vivo experiments followed the protocols approved by the Animal Care and Use Committee of the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. Aliquots $(200\\upmu\\mathrm{l})$ of the BPQDs/PLGA NSs $(1\\mathrm{mg}\\mathrm{BP}\\mathrm{ml}^{-1}),$ ) were injected separately into the mice via the tail vein. The mice were randomly divided into 4 groups and subjected to variable conditions. This include: (1) control group without any treatment, (2) NSs directly intravenously injected into the mice, (3) NSs intravenously injected into the mice after $808\\mathrm{nm}$ laser irradiation for $10\\mathrm{min}$ and (4) NSs intravenously injected into the mice which are then exposed to artificial daylight for $24\\mathrm{h}$ . The mice were killed at various time points after injection (1, 7 and 28 days, five mice per group at each time point). About $0.8\\mathrm{ml}$ of blood were collected from each mouse to conduct complete blood panel analysis and serum biochemistry assay at the Shanghai Research Center for Biomodel Organism. The major organs (liver, spleen, kidney, heart and lung) were harvested, fixed in $10\\%$ neutral buffered formalin, processed routinely into paraffin, sectioned at $8\\upmu\\mathrm{m}$ , stained with haematoxylin and eosin, and examined by digital microscopy. \n\nPharmacokinetic and biodistribution analysis. In the biodistribution and pharmacokinetic analysis, fluorescent labelled BPQDs/PLGA NSs were prepared by adding $0.1\\mathrm{mg}\\mathrm{ml}^{-1}$ of $\\mathrm{Cy}5.5$ to the BPQDs/PLGA solution in DCM followed by oil-in-water emulsion solvent evaporation described above. The excess dye molecules were removed by centrifugation and washed away with water more than 5 times until no noticeable colour change was observed from the supernatant fluids followed by resuspension in PBS. \n\nThe female Balb/c nude mice (6 weeks old) were purchased from Slac Laboratory Animal Co.Ltd (Hunan, China). In the pharmacokinetic analysis, blood circulation was assessed by drawing $10\\upmu\\mathrm{l}$ of blood from the tail veins of the Balb/c nude mice at certain time intervals post-injection of the $\\mathrm{Cy}5.5$ -labelled BPQDs/PLGA NSs. Each blood sample was dissolved in $\\mathrm{1ml}$ of the lysis buffer (the same as the above used) and the concentration of the NSs in the blood was determined from the fluorescence spectrum acquired on a Fluoromax 4 fluorometer (Horiba Jobin Yvon, France). A series of dilutions were performed to obtain a standard calibration curve. The blank blood sample without injection was measured to determine the blood auto-fluorescence level, which was subtracted from the fluorescence intensities of injected samples during concentration calculation. The pharmacokinetic parameters such as half-life $(t_{I/2})$ , $V$ and AUC were determined using a Microsoft add-in tool, PKSolver67. \n\nIn the in vivo fluorescence imaging experiments, the Balb/c nude mice bearing MCF7 breast tumours were intravenously injected with the $\\mathrm{Cy}5.5$ -labelled $\\mathrm{\\DeltaBPQDs}/$ PLGA NSs $100\\upmu\\mathrm{l}$ of $1\\mathrm{mg}\\mathrm{BP}\\mathrm{ml}^{-1}$ for each mouse) and examined by a fluorescence (Xenogen IVIS-Spectrum) imaging system as a function of time for up to $48\\mathrm{h}$ . NIR light with a peak wavelength of $675\\mathrm{nm}$ was used as the excitation source and in vivo spectral imaging with the $\\mathrm{Cy}5.5$ bandpass emission filter $(680-720\\mathrm{nm})$ was carried out for an exposure time of $200\\mathrm{{ms}}$ for each image frame. All the images were captured using identical system settings and auto-fluorescence was removed using the spectral unmixing software. \n\nIn the ex vivo fluorescence imaging experiments, the NSs-treated mice were killed by cervical dislocation and the corresponding major organs and tissues including the liver, spleen, kidney, heart, stomach, lung, intestine and tumour were collected and imaged immediately afterwards. The tumours were fixed in $10\\%$ neutral buffered formalin and embedded in paraffin. Sections of whole tumour were stained using DAPI (shown in blue) to label all nuclei of tumour cells. The fluorescence images of the tumour sections were acquired on the Leica DM4000B fluorescence microscope (Leica, Nussloch, Germany). \n\nIn the quantitative biodistribution analysis, the NSs-treated mice were killed and the organs/tissues were weighed and solubilized by a lysis buffer $(1\\%$ SDS, $1\\%$ Triton X-100, $40\\mathrm{mM}$ Tris Acetate) using a PowerGen homogenizer (Fisher Scientific). The clear homogeneous tissue lysates were diluted 100 times to avoid light scattering and self-quenching during fluorescence measurement. The fluorescence intensities of both the standard samples and real tissues were adjusted to be in the linear range by appropriate dilution and subjected to fluorometry to quantitatively determine the NSs concentrations. The organs and tissues from a control mouse without injection of the NSs were collected and used as controls to subtract the auto-fluorescence background in various tissues. The samples were measured in triplicate to ensure reproducibility and accuracy. The biodistribution of the NSs in the various organs of the mice was calculated and presented as the percentage of injected dose per gram of tissue $\\left(\\%\\mathrm{ID}{\\mathrm{~g~}^{-1}}\\right),$ ). \n\nIn vivo photothermal experiments. To establish the MCF7 breast tumours in situ in the $\\mathrm{Balb/c}$ nude mice, $1\\times10^{7}$ MCF7 cells in $100\\upmu\\mathrm{l}$ PBS were subcutaneously injected into the left foreleg armpit of each mouse. When the tumour volume reached $200\\mathrm{mm}^{3}$ , the mice were randomly divided into 4 groups $\\stackrel{\\prime}{n}=5$ per group) and aliquots $(100\\upmu\\mathrm{l})$ of PBS, PLGA NSs, BPQDs $(1\\mathrm{mg}\\mathrm{m}\\mathbf{\\bar{l}}^{-1},$ ) and BPQDs/PLGA NSs $\\mathrm{^{\\prime}1m g~B P~m l^{-1}},$ ) were injected separately into the nude mice via the tail vein. At $24\\mathrm{h}$ post-injection, the mice were anaesthetized and the entire region of the tumour was irradiated with the $808\\mathrm{nm}$ NIR laser $(1\\mathrm{W}\\mathrm{cm}^{-2})$ for $10\\mathrm{min}$ . The temperature of the tumours and infrared thermographic maps were monitored by an infrared thermal imaging camera (Ti27, Fluke, USA) simultaneously. The AuNRs $100\\upmu\\mathrm{l}.$ , $3.62\\mathrm{mg}\\mathrm{\\bar{ml}}^{-1}$ ) were employed as a positive control in the photothermal experiments. After laser irradiation, the tumour size was measured by a caliper every other day according to the formula: volume $(V)=$ (tumour $\\mathrm{length})\\stackrel{\\cdot}{\\times}(\\mathrm{tumour~width})^{2}/2$ , and no mice died during the course of therapy. The same observer performed all tumour measurements in this study. The relative tumour volume was calculated as $V/V_{0}$ with $V_{0}$ being the initial tumour volume at the start of the treatment. Daily clinical observations including weekends and holidays were performed to monitor the animals for signs of distress. When the tumour size reached $20\\mathrm{mm}$ in any direction or the mice displayed restriction, inability to access food and water, pressure on internal organs or sensitive regions of the body, the mice were euthanized. To further compare the photothermal effects between the BPQDs and BPQDs/PLGA NSs in details, photothermal experiments with different injection concentrations (0.5, 1, 2 and $3\\mathrm{mg~BP~ml^{-1}},$ ) and irradiation time (1, 4, 8, 12, 24 and $48\\mathrm{h}$ post-injection) were performed. The temperature of the tumours and infrared thermographic maps were obtained by the infrared thermal imaging camera. \n\nAnother tumour model with competent immune system was established in situ in the Balb/c mice by subcutaneously injection of $1\\times10^{7}$ B16 melanoma cells in PBS to the left rear flank of each mouse. When the tumour volume reached $100\\mathrm{mm}^{3}$ , aliquots $(100\\upmu\\mathrm{l})$ of PBS, PLGA NSs, BPQDs $(1\\mathrm{mg}\\mathrm{ml}^{-1}),$ , and $\\mathrm{\\DeltaBPQDs}/$ PLGA NSs $\\mathrm{^{'1}m g B P m l^{-1}}.$ ) were injected separately into the mice via the tail vein. At $24\\mathrm{h}$ post-injection, in vivo photothermal experiments were conducted as described above. \n\nApoptosis detection. The tumours were collected from the $\\mathrm{Balb}/c$ nude mice treated with PBS, PLGA NSs, BPQDs and BPQDs/PLGA NSs $24\\mathrm{h}$ after the treatment. The individual tumours were fixed in $10\\%$ neutral buffered formalin, embedded in paraffin, sectioned at 5 micrometres and stained using the TUNEL technique using the In Situ Cell Death Detection Kit (Roche Applied Science, Germany). The experimental procedures were in accordance with the manufacturer’s instructions. DAPI was used to stain the sections in the absence of light to label the apoptotic cells and cellular DNA. The fluorescence images were taken on the Leica DM4000B fluorescence microscope (Leica, Nussloch, Germany). To further investigate the depth of the photothermal damage, the tumour-bearing nude mice with a tumour volume as large as $1,000\\mathrm{mm}^{3}$ was illuminated with the $808\\mathrm{nm}$ NIR laser $(1\\mathrm{W}\\mathrm{cm}^{-2})$ for $10\\mathrm{min}$ . Intratumoral apoptosis of the tumour sections was monitored at different depths (2, 4, 6, 8 and $10\\mathrm{mm}$ ) by the TUNEL assay. \n\nStatistical analysis. All the data were presented as means $\\pm$ s.d. To test the significance of the observed differences between the study groups, analysis by variance statistics was applied and a value of $P{<}0.05$ was considered to be statistically significant. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# References \n\n1. Chen, Y., Tan, C., Zhang, H. & Wang, L. Two-dimensional graphene analogues for biomedical applications. Chem. Soc. Rev. 44, 2681–2701 (2015). \n2. Tian, Q. et al. Hydrophilic flower-like CuS superstructures as an efficient 980 nm laser-driven photothermal agent for ablation of cancer cells. Adv. Mater. 23, 3542–3547 (2011). \n3. Yang, K. et al. Multimodal imaging guided photothermal therapy using functionalized graphene nanosheets anchored with magnetic nanoparticles. Adv. Mater. 24, 1868–1872 (2012). \n4. Sang, Y. et al. From UV to near-infrared, $\\mathrm{WS}_{2}$ nanosheet: a novel photocatalyst for full solar light spectrum photodegradation. Adv. Mater. 27, 363–369 (2015). \n5. Zhu, C. et al. Stabilizing two classical antiaromatic frameworks: demonstration of photoacoustic imaging and the photothermal effect in metalla-aromatics. Angew. Chem. Int. Ed. 127, 6279–6283 (2015). \n6. Hirsch, L. R. et al. Nanoshell-mediated near-infrared thermal therapy of tumors under magnetic resonance guidance. Proc. Natl Acad. Sci. USA 100, 13549–13554 (2003). \n7. Hauck, T. S., Jennings, T. L., Yatsenko, T., Kumaradas, J. C. & Chan, W. C. W. Enhancing the toxicity of cancer chemotherapeutics with gold nanorod hyperthermia. Adv. Mater. 20, 3832–3838 (2008). \n8. Dong, K., Liu, Z., Li, Z., Ren, J. & Qu, X. Hydrophobic anticancer drug delivery by a $980~\\mathrm{nm}$ laser-driven photothermal vehicle for efficient synergistic therapy of cancer cells in vivo. Adv. Mater. 25, 4452–4458 (2013). \n9. Yin, W. et al. High-throughput synthesis of single-layer $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets as a near-infrared photothermal-triggered drug delivery for effective cancer therapy. ACS Nano 8, 6922–6933 (2014). \n10. Kam, N. W. S., O’Connell, M., Wisdom, J. A. & Dai, H. Carbon nanotubes as multifunctional biological transporters and near-infrared agents for selective cancer cell destruction. Proc. Natl Acad. Sci. USA 102, 11600–11605 (2005). \n11. Li, M., Yang, X., Ren, J., Qu, K. & Qu, X. Using graphene oxide high nearinfrared absorbance for photothermal treatment of Alzheimer’s disease. Adv. Mater. 24, 1722–1728 (2012). \n12. Li, B. et al. Photothermal theragnosis synergistic therapy based on bimetal sulphide nanocrystals rather than nanocomposites. Adv. Mater. 27, 1339–1345 (2015). \n13. Huang, X., Neretina, S. & El-Sayed, M. A. Gold nanorods: from synthesis and properties to biological and biomedical applications. Adv. Mater. 21, 4880–4910 (2009). \n14. Liu, H., Du, Y., Deng, Y. & Peide, D. Y. Semiconducting black phosphorus: synthesis, transport properties and electronic applications. Chem. Soc. Rev. 44, 2732–2743 (2015). \n15. Yavuz, M. S. et al. Gold nanocages covered by smart polymers for controlled release with near-infrared light. Nat. Mater. 8, 935–939 (2009). \n16. Park, J. H. et al. Biodegradable luminescent porous silicon nanoparticles for in vivo applications. Nat. Mater. 8, 331–336 (2009). \n17. Yang, K., Feng, L., Shi, X. & Liu, Z. Nano-graphene in biomedicine: theranostic applications. Chem. Soc. Rev. 42, 530–547 (2013). \n18. Song, G. et al. Degradable molybdenum oxide nanosheets with rapid clearance and efficient tumor homing capabilities as a therapeutic nanoplatform. Angew. Chem. Int. Ed. 55, 2122–2126 (2016). \n19. Liu, J. et al. Passive tumor targeting of renal-clearable luminescent gold nanoparticles: long tumor retention and fast normal tissue clearance. J. Am. Chem. Soc. 135, 4978–4981 (2013). \n20. Guo, L. et al. A comparative study of hollow copper sulfide nanoparticles and hollow gold nanospheres on degradability and toxicity. ACS Nano 7, 8780–8793 (2013). \n21. Cheng, L., Wang, C., Feng, L., Yang, K. & Liu, Z. Functional nanomaterials for phototherapies of cancer. Chem. Rev. 114, 10869–10939 (2014). \n22. Choi, H. S. et al. Renal clearance of quantum dots. Nat. Biotechnol. 25, 1165–1170 (2007). \n23. Churchill, H. O. H. & Jarillo-Herrero, P. Two-dimensional crystals: phosphorus joins the family. Nat. Nanotechnol. 9, 330–331 (2014). \n24. Li, L. et al. Black phosphorus field-effect transistors. Nat. Nanotechnol. 9, 372–377 (2014). \n25. Liu, H. et al. Phosphorene: an unexplored 2D semiconductor with a high hole mobility. ACS Nano 8, 4033–4041 (2014). \n26. Qiao, J., Kong, X., Hu, Z. X., Yang, F. & Ji, W. High-mobility transport anisotropy and linear dichroism in few-layer black phosphorus. Nat. Commun. 5, 4475 (2014). \n27. Xiang, D. et al. Surface transfer doping induced effective modulation on ambipolar characteristics of few-layer black phosphorus. Nat. Commun. 6, 6485 (2015). \n28. Wang, X. et al. Highly anisotropic and robust excitons in monolayer black phosphorus. Nat. Nanotechnol. 10, 517–521 (2015). orientation of black phosphorus using angle-resolved polarized Raman spectroscopy. Angew. Chem. Int. Ed. 54, 2396–2399 (2015). \n30. Doganov, R. A. et al. Transport properties of pristine few-layer black phosphorus by van der Waals passivation in an inert atmosphere. Nat. Commun. 6, 6647 (2015). \n31. Zhang, S. et al. Extraordinary photoluminescence and strong temperature/ angle-dependent Raman responses in few-layer phosphorene. ACS Nano 8, 9590–9596 (2014). \n32. Brent, J. R. et al. Production of few-layer phosphorene by liquid exfoliation of black phosphorus. Chem. Commun. 50, 13338–13341 (2014). \n33. Yasaei, P. et al. High-quality black phosphorus atomic layers by liquid-phase exfoliation. Adv. Mater. 27, 1887–1892 (2015). \n34. Kang, J. et al. Solvent exfoliation of electronic-grade, two-dimensional black phosphorus. ACS Nano 9, 3596–3604 (2015). \n35. Woomer, A. H. et al. Phosphorene: synthesis, scale-up, and quantitative optical spectroscopy. ACS Nano 9, 8869–8884 (2015). \n36. Zhang, X. et al. Black phosphorus quantum dots. Angew. Chem. Int. Ed. 54, 3653–3657 (2015). \n37. Lee, H. U. et al. Black phosphorus (BP) nanodots for potential biomedical applications. Small 12, 214–219 (2016). \n38. Wang, H. et al. Ultrathin black phosphorus nanosheets for efficient singlet oxygen generation. J. Am. Chem. Soc. 137, 11376–11382 (2015). \n39. Sun, Z. et al. Ultrasmall black phosphorus quantum dots: synthesis and use as photothermal agents. Angew. Chem. Int. Ed. 127, 11688–11692 (2015). \n40. Comber, S., Gardner, M., Georges, K., Blackwood, D. & Gilmour, D. Domestic source of phosphorus to sewage treatment works. Environ. Technol. 34, 1349–1358 (2013). \n41. Childers, D. L., Corman, J., Edwards, M. & Elser, J. J. Sustainability challenges of phosphorus and food: solutions from closing the human phosphorus cycle. BioScience 61, 117–124 (2011). \n42. Pravst, I. Risking public health by approving some health claims?–The case of phosphorus. Food Policy 36, 726–728 (2011). \n43. Castellanos-Gomez, A. et al. Isolation and characterization of few-layer black phosphorus. 2D Materials 1, 025001 (2014). \n44. Island, J. O., Steele, G. A., van der Zant, H. S. & Castellanos-Gomez, A. Environmental instability of few-layer black phosphorus. 2D Materials 2, 011002 (2015). \n45. Huang, Y. et al.Degradation of black phosphorus (BP): the role of oxygen and water. Preprint at http://arxiv.org/abs/1511.09201 (2015). \n46. Wang, G., Slough, W. J., Pandey, R. & Karna, S. P. Theoretical study of stability of phosphorene in air. Preprint at http://arxiv.org/abs/1508.07461 (2015). \n47. Ling, X., Wang, H., Huang, S., Xia, F. & Dresselhaus, M. S. The renaissance of black phosphorus. Proc. Natl Acad. Sci. USA 112, 4523–4530 (2015). \n48. Song, J. et al. Ultrasmall gold nanorod vesicles with enhanced tumor accumulation and fast excretion from the body for cancer therapy. Adv. Mater. 27, 4910–4917 (2015). \n49. Song, J. et al. Sequential drug release and enhanced photothermal and photoacoustic effect of hybrid reduced graphene oxide-loaded ultrasmall gold nanorod vesicles for cancer therapy. ACS Nano 9, 9199–9209 (2015). \n50. Ye, F. et al. Biodegradable polymeric vesicles containing magnetic nanoparticles, quantum dots and anticancer drugs for drug delivery and imaging. Biomaterials 35, 3885–3894 (2014). \n51. Zhang, X. et al. The effect of autophagy inhibitors on drug delivery using biodegradable polymer nanoparticles in cancer treatment. Biomaterials 35, 1932–1943 (2014). \n52. Anderson, J. M. & Shive, M. S. Biodegradation and biocompatibility of PLA and PLGA microspheres. Adv. Drug Deliv. Rev. 64, 72–82 (2012). \n53. Altinog˘lu, E. I. et al. Near-infrared emitting fluorophore-doped calcium phosphate nanoparticles for in vivo imaging of human breast cancer. ACS Nano 2, 2075–2084 (2008). \n54. Kim, J. S. et al. In vivo NIR imaging with CdTe/CdSe quantum dots entrapped in PLGA nanospheres. J. Colloid Interface Sci. 353, 363–371 (2011). \n55. Favron, A. et al. Photooxidation and quantum confinement effects in exfoliated black phosphorus. Nat. Mater. 14, 826–832 (2015). \n56. Gan, Z. X. et al. Tunable photoluminescence from sheet-like black phosphorus crystal by electrochemical oxidation. Appl. Phys. Lett. 107, 021901 (2015). \n57. Liu, B. et al. Silk structure and degradation. Colloids Surf. B Biointerfaces 131, 122–128 (2015). \n58. Avgoustakis, K. et al. PLGA–mPEG nanoparticles of cisplatin: in vitro nanoparticle degradation, in vitro drug release and in vivo drug residence in blood properties. J. Control. Release 79, 123–135 (2002). \n59. Zhang, X. D. et al. Metabolizable ${\\mathrm{Bi}}_{2}{\\mathrm{Se}}_{3}$ nanoplates: biodistribution, toxicity, and uses for cancer radiation therapy and imaging. Adv. Funct. Mater. 24, 1718–1729 (2014). \n60. Allison, R. R. et al. Photosensitizers in clinical PDT. Photodiagnosis Photodyn. Ther. 1, 27–42 (2004). \n61. Shin, T. H., Choi, Y., Kim, S. & Cheon, J. Recent advances in magnetic nanoparticle-based multi-modal imaging. Chem. Soc. Rev. 44, 4501–4516 (2015). \n62. Huynh, N. T., Roger, E., Lautram, N., Benoıˆt, J. P. & Passirani, C. The rise and rise of stealth nanocarriers for cancer therapy: passive versus active targeting. Nanomedicine 5, 1415–1433 (2010). \n63. Yang, K. et al. In vivo pharmacokinetics, long-term biodistribution, and toxicology of PEGylated graphene in mice. ACS Nano 5, 516–522 ð2010Þ: \n64. Li, Z. et al. Small gold nanorods laden macrophages for enhanced tumor coverage in photothermal therapy. Biomaterials 74, 144–154 (2016). \n65. Jaque, D. et al. Nanoparticles for photothermal therapies. Nanoscale 6, 9494–9530 (2014). \n66. Bagley, A. F., Hill, S., Rogers, G. S. & Bhatia, S. N. Plasmonic photothermal heating of intraperitoneal tumors through the use of an implanted nearinfrared source. ACS Nano 7, 8089–8097 (2013). \n67. Zhang, Y., Huo, M., Zhou, J. & Xie, S. PKSolver: An add-in program for pharmacokinetic and pharmacodynamic data analysis in Microsoft Excel. Comput. Methods Programs Biomed. 99, 306–314 (2010). \n\n# Acknowledgements \n\nWe acknowledge financial support from the National Natural Science Foundation of China (51372175, 61435010), Leading Talents of Guangdong province Program (00201520), Science and Technology Innovation Commission of Shenzhen (KQTD2015032416270385, JCYJ20160229195124187), as well as Hong Kong Research Grants Council (RGC) General Research Funds (GRF) No. CityU 11301215. \n\n# Author contributions \n\nX.F.Y., H.Z. and P.K.C. conceived the idea and designed the experiments. J.S. and H.X. performed mainly the syntheses, experimental measurements and data analysis. H.H., Z.L., Z.S., Y.X., Q.X. and Y.Z. assisted with data analysis and interpretation. J.S. drafted the paper and X.F.Y., H.W., H.Z. and P.K.C. provided revisions. All authors approved the final version of the paper for submission. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Shao, J. et al. Biodegradable black phosphorus-based nanospheres for in vivo photothermal cancer therapy. Nat. Commun. 7, 12967 doi: 10.1038/ncomms12967 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms13651", + "DOI": "10.1038/ncomms13651", + "DOI Link": "http://dx.doi.org/10.1038/ncomms13651", + "Relative Dir Path": "mds/10.1038_ncomms13651", + "Article Title": "11.4% Efficiency non-fullerene polymer solar cells with trialkylsilyl substituted 2D-conjugated polymer as donor", + "Authors": "Bin, HJ; Gao, L; Zhang, ZG; Yang, YK; Zhang, YD; Zhang, CF; Chen, SS; Xue, LW; Yang, C; Xiao, M; Li, YF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Simutaneously high open circuit voltage and high short circuit current density is a big challenge for achieving high efficiency polymer solar cells due to the excitonic nature of organic semdonductors. Herein, we developed a trialkylsilyl substituted 2D-conjugated polymer with the highest occupied molecular orbital level down-shifted by Si-C bond interaction. The polymer solar cells obtained by pairing this polymer with a non-fullerene acceptor demonstrated a high power conversion efficiency of 11.41% with both high open circuit voltage of 0.94 V and high short circuit current density of 17.32 mA cm(-2) benefitted from the complementary absorption of the donor and acceptor, and the high hole transfer efficiency from acceptor to donor although the highest occupied molecular orbital level difference between the donor and acceptor is only 0.11 eV. The results indicate that the alkylsilyl substitution is an effective way in designing high performance conjugated polymer photovoltaic materials.", + "Times Cited, WoS Core": 935, + "Times Cited, All Databases": 970, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000389651800001", + "Markdown": "# 11.4% Efficiency non-fullerene polymer solar cells with trialkylsilyl substituted 2D-conjugated polymer as donor \n\nHaijun $\\mathsf{B i n}^{1,2,\\star},$ Liang $\\mathsf{G a o}^{1,2,\\star}$ , Zhi-Guo Zhang1, Yankang Yang1,2, Yindong Zhang3,4, Chunfeng Zhang3,4, Shanshan Chen5, Lingwei Xue1, Changduk Yang5, Min Xiao3,4 & Yongfang Li1,2,6 \n\nSimutaneously high open circuit voltage and high short circuit current density is a big challenge for achieving high efficiency polymer solar cells due to the excitonic nature of organic semdonductors. Herein, we developed a trialkylsilyl substituted 2D-conjugated polymer with the highest occupied molecular orbital level down-shifted by Si–C bond interaction. The polymer solar cells obtained by pairing this polymer with a non-fullerene acceptor demonstrated a high power conversion efficiency of $11.41\\%$ with both high open circuit voltage of $0.94\\mathrm{V}$ and high short circuit current density of $17.32\\mathsf{m A c m}^{-2}$ benefitted from the complementary absorption of the donor and acceptor, and the high hole transfer efficiency from acceptor to donor although the highest occupied molecular orbital level difference between the donor and acceptor is only $0.11\\mathrm{eV}.$ The results indicate that the alkylsilyl substitution is an effective way in designing high performance conjugated polymer photovoltaic materials. \n\nBoulske-dhoetfearobjluencdt aocnt vpe yaymeerrofsoal $\\boldsymbol{p}$ cyeplels (oPnjSuCgsa) adrepocloymper$n$ -type semiconductor as acceptor sandwiched between an anode and a cathode where at least one of the two electrodes should be transparent1–3. The $n$ -type semiconductors used as acceptor in the PSCs include fullerene derivatives4, $n$ -type conjugated polymers5–12 and $n$ -type organic semiconductors $(n\\mathrm{-OS})^{1\\mathrm{{3}-23}}$ . Among the acceptors, $n$ -OS acceptors show distinguished advantages of easy tuning of absorption and electronic energy levels, strong absorbance, good morphology stability and more suitable for flexible devices. Therefore, the non-fullerene PSCs with $n{\\mathrm{-}}\\mathrm{OS}$ as acceptor have attracted great attention recently, and their power conversion efficiency (PCE) has rapidly increased to $9-11\\%$ (refs 24–26). \n\nIn PSCs, due to the low dielectric permittivity and relatively large excitons binding energy of organic semdonductor, polymer donor and acceptor with cascading enegy levels (the lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) levels of the conjugated polymer donor should be higher than the correponding LUMO and HOMO levels of the acceptor) are specially required to provide a driving force for excitons dissociation at the heterojunction interface27–30. In this cascade model, it is generally accepted that the LUMO/HOMO energy levels differences between the donor and acceptor $(\\Delta E_{\\mathrm{LUMO}}$ and $\\Delta E_{\\mathrm{HOMO}})$ should be larger than $0.3\\mathrm{eV}$ for efficient excitons dissociation to overcome binding energy (usually $0.3\\mathrm{-}0.5\\mathrm{eV})$ of the excitons produced in the donor and acceptor phases by absorbing photons27,30–32. One crucial issue of the PSCs is their relatively large photon energy loss $(E_{\\mathrm{loss}})$ at 1 sun illuminaiton which is defined as $E_{\\mathrm{loss}}=E_{\\mathrm{g}}–\\mathrm{e}V_{\\mathrm{oc}},$ where $E_{\\mathrm{g}}$ is the lowest optical bandgap of the donor and acceptor components $^{27,33-35}$ . The reported $\\boldsymbol{E_{\\mathrm{loss}}}$ in the most efficient fullerene-based PSCs is typically $0.7\\mathrm{-}1.0\\mathrm{eV}$ . The larger $\\boldsymbol{E_{\\mathrm{loss}}}$ is associated with the larger driving force for excitons dissociation and the relative large non-radiative recombinations27,28,36,37, thus creating a great challenge to simultaneously obtain a large open circuit voltage $(V_{\\mathrm{oc}})$ and a high short circuit current density $\\bar{(\\boldsymbol{J}_{s c})}$ in the PSCs. \n\nIn the non-fullerene PSCs, medium bandgap polymer donor– low bandgap n-OS acceptor pairs are particular interesting due to their complementary absorption in the visible-near infrared region, providing an effective approch for getting a high $J_{\\mathrm{sc}}$ . In these systems, another interesting feature is the easy energy level matching to get higher $V_{\\mathrm{oc}}$ with lower $\\boldsymbol{E_{\\mathrm{loss}}}$ of $0.6\\mathrm{-}0.7\\mathrm{eV}$ (refs 21,25,26,38). For example, the non-fullerene PSCs based on a medium bandgap D-A copolymer PffT2-FTAZ-2DT as donor and a low bandgap n-OS IEIC (ref. 19) ( $\\cdot E_{\\mathrm{g}}$ of $1.59\\mathrm{eV},$ as acceptor with a $\\Delta E_{\\mathrm{HOMO}}$ of $0.17\\mathrm{eV}$ showed a PCE of $7.3\\%$ with a $V_{\\mathrm{oc}}$ of $0.998\\mathrm{V}$ and a $E_{\\mathrm{loss}}$ of ca. $0.60\\mathrm{eV}$ (ref. 38). The device based on a 2D-conjugated D-A copolymer PBDB-T as donor and a low bandgap $n$ -OS ITIC (ref. 20) $(E_{\\mathrm{g}}$ of $1.59\\mathrm{eV})$ as acceptor with a $\\Delta E_{\\mathrm{HOMO}}$ of $0.18\\mathrm{eV}$ demonstrated a PCE of $11.21\\%$ with a $V_{\\mathrm{oc}}$ of $0.899\\mathrm{V}$ and a $E_{\\mathrm{loss}}$ of $0.64\\mathrm{eV}$ (ref. 26). Notably, the lower $E_{\\mathrm{loss}}$ was attained with a relatively low $\\Delta E_{\\mathrm{HOMO}},$ suggesting a low driving force needed for excitons dissociation in this system. These encouraging results provide a plausible approach to well remove the trade-off between the $V_{\\mathrm{oc}}$ and $J_{s c}$ . Recently, we developed a series medium bandgap 2D-conjugated D-A copolymers based on bithienyl-benzodithiophene (BDTT) donor unit and fluorine-substituted benzotriazole (FBTA) acceptor unit25,39, which showed good photovoltaic performance in the PSCs with the polymers as donor and $\\mathtt{n-O S}$ as acceptors11,25. Among the polymers, J61 as donor blending with the $n$ -OS ITIC as acceptor with a $\\Delta E_{\\mathrm{HOMO}}$ of $0.16\\mathrm{eV}$ in the nonfullerene PSCs displayed a high PCE of $9.53\\%$ with a $V_{\\mathrm{oc}}$ of $0.89\\mathrm{V}$ and a $\\boldsymbol{E_{\\mathrm{loss}}}$ of $0.68\\mathrm{eV}$ (ref. 25). The high photovoltaic performance of the non-fullerene PSCs with the small $\\Delta E_{\\mathrm{HOMO}}$ between donor and acceptor is a very important phenomenon for the development of high performance PSCs by increasing $V_{\\mathrm{oc}}$ and decreasing Eloss. \n\nTo probe the possiblity of further increasing the $V_{\\mathrm{oc}}$ and PCE of the non-fullerene PSCs with smaller $\\Delta E_{\\mathrm{HOMO}}$ value, herein we try to further decrease HOMO energy level of the BDTT-FBTAbased 2D-conjugated D-A copolymers by introducing trialkylsilyl substituents on BDTT unit. The trialkylsilyl substituents instead of alkyl side chains make HOMO energy level of the synthesized polymer J71 down-shifted to $-5.40\\mathrm{eV}$ and its absorbance enhanced in comparison with its analogue polymer J52 with alkyl side chains25. Very interestingly, the non-fullerene PSC based on J71 as donor and ITIC as acceptor with a smal $\\Delta E_{\\mathrm{HOMO}}$ of $0.11\\mathrm{eV}$ demonstrates a high PCE of $11.41\\%$ with high $V_{\\mathrm{oc}}$ of $0.94\\mathrm{V}$ , high $J_{\\mathrm{sc}}$ of $17.32\\mathrm{mA}\\mathrm{cm}^{-2}$ and a low $E_{\\mathrm{loss}}$ of $0.63\\mathrm{-}0.65\\mathrm{eV}$ The PCE of $11.41\\%$ is one of the highest efficiency of the single junction PSCs reported in literatures till now. The results indicate that the alkylsilyl substitution is an effective way in designing high performance conjugated polymer photovoltaic materials. \n\n# Results \n\nDesign and synthesis of J71. In the molecular design of conjugated polymer donor materials for PSCs, the main chain engineering (such as alternative donor (D)-acceptor (A) copolymerization)40,41 and side chain engineering (such as conjugated side chains and electron-withdrawing substituents)30,42 are widely used strategy to tune absorption spectra and electronic energy levels of the conjugated polymers. Silicon (Si)-containing fused rings, such as dibenzosilole and dithienosilole, are representative donor units in the high performance D-A copolymer donor materials. Silicon bridging atom in the Si-containing fused rings plays an important role in improving the planarity of the backbone and modifying the electronic properties of the polymers43–46. The effect of the Si-atom on the electronic properties are mostly related to the bond interaction of the low-lying $\\sigma^{*}$ orbital of the Si atom with the $\\pi^{*}$ orbital of the aromatic units, which results in stabilization of the LUMO energy level and lowering of HOMO energy level47. For example, Si-bridged bithiophene (dithienosilole, DTS) has lower HOMO and LUMO energy levels compared with those of its C-bridged counterpart $(\\mathrm{CD}\\mathbf{\\ddot{T}})^{47}$ . In addition, the Si-bridging atom also showed a significant effect on the crystallinity of the polymer due to the longer C–Si bond length compared with the C–C bond, leading to stronger $\\pi{-}\\pi$ stacking. Inspired by the special-function of the Si-atom connecting with conjugated system, herein we designed another BDTT-FBTA-based D-A copolymer J71 by introducing alkylsilyl substituents on thiophene conjugated side chains of BDTT unit for down-shifting HOMO energy level and strengthening interchain interaction of the polymers by the $\\sigma^{*}$ (Si)– $\\cdot\\pi^{*}(\\mathbf{C})$ bond interaction. \n\nThe polymer J71 was synthesized by Stille-coupling polycondensation between M1 (BDTT-Si) and M2 (FTAZ-based mononmer)48, as shown in Fig. 1a. The structure of BDTT-Si obtained by X-ray crystallography was also shown in Fig. 1a, and the crystallographic data of BDTT-Si (CCDC number: 1478875) are listed in Supplementary Table 1 and Supplementary Table 2. To better understand the effect of alkylsilyl substitution on the electronic properties of the monomer and polymer, we compared the absorption spectra and electronic energy levels of BDTT-Si with the alkylsilyl substituents and BDTT-C with alkyl substituents on the thiophene conjugated side chains of the BDTT units, as shown in Fig. 1b. It can be seen that the absorption maximum $(\\lambda_{\\operatorname*{max}})$ of BDTT-Si is at $380\\mathrm{nm}$ which is \n\n![](images/6985a14ea63451f88d7df78611fdab44057b0acf0801ac29f6513e368de3bfe2.jpg) \nFigure 1 | Synthetic route of J71 and the effect of the alkylsilyl substitution on the physicochemical properties of the monomers. (a) Synthetic route of J71 with the structure of BDTT-Si obtained by $\\mathsf{X}$ -ray crystallography. (b) Absorption spectra of the monomers BDTT-Si and BDTT-C chloroform solutions with concentration of $1\\times10^{-5}\\mathsf{m o l}|^{-1}$ . (c) Cyclic voltammograms of BDTT-Si and BDTT-C in $0.1\\mathsf{m o l}|^{-1}\\mathsf{B u}_{4}\\mathsf{N P F}_{6}$ acetonitrile solution at a scan rate of $20\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ , the ferrocene/ferrocenium $(\\mathsf{F C}/\\mathsf{F C}^{+}\\bar{}$ ) couple was also provided for an internal reference. (d) Energy level diagrams of BDTT-Si and BDTT-C. \n\n$5\\mathrm{nm}$ red-shifted than that $(375\\mathrm{nm})$ of BDTT-C. And the absorption coefficient of BDTT-Si is higher than that of BDTT-C, indicating that alkylsilyl substitution affords not only broader but also stronger absorption. HOMO energy levels of the two monomers were measured by cyclic voltammetry. The onset oxidation potentials $(\\varphi_{\\mathrm{ox}})$ of BDTT-Si and BDTT-C are 0.99 and $0.90\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ (Fig. 1c), and the HOMO energy levels $(E_{\\mathrm{HOMO}})$ were calculated to be $-5.35\\mathrm{eV}$ for BDTT-Si and $-5.26\\mathrm{eV}$ for BDTT-C (the calculation equation will be discussed below in the section on the electronic energy level measurements of J71). The LUMO levels of BDTT-Si and BDTT-C, estimated from their absorption edges and HOMO levels, are $-3.40$ and $-3.27\\mathrm{eV}$ respectively. Clearly, alkylsilyl substituted BDTT-Si has lower HOMO and LUMO enrgy levels compared with those of its alkyl substituted counterpart BDTT-C (Fig. 1d). The results suggest that the alkylsilyl side chain engineering can afford the similar effect of the $\\mathrm{Si\\mathrm{-}C}$ bond interaction as that in Si-bridged aromatic compounds47, while the alkylsilyl side chain approach developed in this work is more simple and convenient in downshifting the HOMO energy level and strengthening the absorption. To further understand the effect of the alkylsilyl side chains on the electronic energy levels of the monomers, we performed the theoretical calculation by the DFT method on the molecules at the DFT B3LYP/6-31G(d) level with the Gaussian 03 program package. The calculated HOMO and LUMO energy levels of BDTT-Si are lower than those of BDTT-C (Supplementary Fig. 1), which is consistent with the experimental results mentioned above. \n\nThe synthesis details of J71 were described in the Method section. J71 exhibits good solubility in many chlorinated solvents, such as chloroform, chlorobenzene and dichlorobenzene. The number average molecular weight $(M_{\\mathrm{n}})$ of J71 is $23.5\\mathrm{kDa}$ with a polydispersity index of 2.0, which was measured by high temperature Gel permeation chromatography (GPC). Thermogravimetric analysis (TGA) demonstrated a good thermal stability of the polymer with a $5\\%$ weight-loss temperature at $354^{\\circ}\\mathrm{C},$ as shown in Supplementary Fig. 2. \n\nAbsorption spectra and electronic energy levels. Figure 2a shows the molecular structures of the polymer J71 and the n-OS ITIC acceptor, and Fig. 2b displays the absorption spectra of J71 solution and film together with the film absorpiton of ITIC for comparison. In solution, J71 shows defined absorption profile with two peaks at about 528 and $573\\mathrm{nm}$ , which can be ascribed to the vibronic bands associated with the (0-1) and (0-0) transitions respectively. The emergence of these features is believed to be associated with the partial aggregation of the fluorinated polymer chains. The absorption of J71 film is red-shifted by about $14\\mathrm{nm}$ along with a stronger (0-0) transition peak in the long wavelength range. The red-shift of its absorption in the solid film indicates more ordered structure and stronger $\\pi{-}\\pi$ stacking interaction, which should benefit higher hole mobility and better photovoltaic performance of the polymer. The absorption edge of J71 film is at $632\\mathrm{nm}$ , which correponds to an optical bandgap of $1.96\\mathrm{eV}$ The film maximum extinction coefficient of J71 is $\\stackrel{\\cdot}{0.96}\\times10^{5}\\ \\mathrm{cm}^{-1}$ , which is higher than its polymer analogue J52 with alkyl chain $(0.73\\times10^{5}\\mathrm{~cm}^{-1})^{25}$ . In addition, as one of the series of BDTTFBTA-based copolymers11,25,39, J71 also demonstrates well complementary absorption with that of ITIC $\\mathrm{\\n-OS{}}$ acceptor in the wavelength range of $400{-}800\\mathrm{nm}$ , which is beneficial for light harvesting in the non-fullerene PSCs. \n\n![](images/b8d722c6785e02f93713affca68b6f104edd94be17e5a702f11ea7fffb7f06c7.jpg) \nFigure 2 | Chemical structure and physicochemical properties of J71. (a) Chemical structures of J71 polymer donor and ITIC n-OS acceptor. (b) Absorption spectra of J71 and ITIC. (c) Cyclic voltammogram of J71 polymer film on a platinum electrode measured in $0.1\\mathsf{m o l}|^{-1}\\mathsf{B u}_{4}\\mathsf{N P F}_{6}$ acetonitrile solutions at a scan rate of $20\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ , the inser figure (blue line) shows the Cyclic voltammogram of ferrocene/ferrocenium $(\\mathsf{F c}/\\mathsf{F c}^{+})$ couple used as an internal reference. (d) Energy level diagram of J71 and ITIC. \n\nThe HOMO and LUMO energy levels of J71 were measured by electrochemical cyclic voltammetry49,50, for investigating the effect of the tripropylsilyl substitution on the electronic energy levels of the 2D-conjugated polymers. The HOMO/LUMO energy levels $(E_{\\mathrm{HOMO}}/E_{\\mathrm{LUMO}})$ can be calculated from onset oxidation/reduction potentials $(\\varphi_{\\mathrm{ox}}/\\varphi_{\\mathrm{red}})$ in the cyclic voltammograms according to the equations of $E_{\\mathrm{HOMO}}/E_{\\mathrm{LUMO}}=-\\mathrm{~e~}$ $(\\varphi_{\\mathrm{ox}}/\\bar{\\varphi}_{\\mathrm{red}}+4.8-\\bar{\\varphi}_{\\mathrm{Fc}/\\mathrm{Fc}^{+}})$ $\\mathrm{(eV)}^{\\mathrm{49,50}}$ where $\\varphi_{\\mathrm{Fc/Fc}}+$ is the redox potential of ferrocene/ferrocenium $(\\mathrm{Fc/Fc^{+}})$ couple in the electrochemical measurement system, and the evergy level of $\\mathrm{Fc/Fc^{+}}$ was taken as $4.8\\mathrm{eV}$ below vacuum. The electrochemical measurement was performed in a $0.1\\mathrm{M}$ acetonitrile solution of tetrabutylammonium hexafluorophosphate $\\mathrm{(n-Bu_{4}N P F_{6})}$ with the sample (J71 or ITIC) film deposited on Pt disc electrode as working electrode, $\\mathrm{Ag/AgCl}$ as reference electrode. $\\varphi_{\\mathrm{Fc/Fc}}+$ was measured to be $0.44\\mathrm{V}$ versus $\\mathrm{\\Ag/AgCl}$ in this measurement system, and then the calculation equations are $E_{\\mathrm{HOMO}}/E_{\\mathrm{LUMO}}=-\\mathrm{~e~}$ $\\langle\\varphi_{\\mathrm{ox}}/\\varphi_{\\mathrm{red}}+4.36\\rangle$ (eV). \n\nFigure 2c shows the cyclic voltammegram of J71 film, from which the onset oxidation potential $(\\varphi_{\\mathrm{ox}})$ and onset reduction potential $(\\varphi_{\\mathrm{red}})$ of J71 were measured to be 1.04 and $-1.10\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ respectively (Supplementary Fig. 3). The HOMO energy level $(E_{\\mathrm{HOMO}})$ and LUMO energy level $(E_{\\mathrm{LUMO}})$ of J71 were calculated to be $-5.40$ and $-3.24\\mathrm{eV}$ respectively (see Fig. 2d), according to the Equations mentioned above. Under the same experimental conditions, the $E_{\\mathrm{HOMO}}$ and $E_{\\mathrm{LUMO}}$ of ITIC were measured to be $-5.51$ and $-3.84\\mathrm{eV}$ respectively (see Fig. 2d and Supplementary Fig. 3b). \n\nIt should be noted that the $E_{\\mathrm{HOMO}}$ of J71 is 0.19 and $0.08\\mathrm{eV}$ deeper than that of its polymer analogue J52 with alkyl substituent $(E_{\\mathrm{HOMO}}=-5.21\\mathrm{eV},$ , see Supplementary Fig. 4) and J61 with alkylthio substituent $(E_{\\mathrm{HOMO}}=-5.32\\mathrm{eV})$ respectively25. The results indicate that the alkylsilyl substitution (with $\\sigma^{*}$ (Si)– $\\pi^{*}(\\mathbf{C})$ bond interaction) is effective in lowering the HOMO energy level of the 2D-conjugated polymers. It should be mentioned that the electrochemical bandgap $(E_{\\mathrm{LUMO}}-E_{\\mathrm{HOMO}})$ of J71 is $2.16\\mathrm{eV}$ , which is $0.2\\mathrm{eV}$ larger than that $(1.96\\mathrm{eV})$ of its optical bandgap. The larger electrochemical bandgap is a common phenomenon for the conjugated polymers and is reasonable in considering the energy barriers needed for the charge transfer in electrochemical oxidation and reduction reactions on the electrode. \n\nPhotovoltaic properties. PSCs were fabricated with a traditional device structure of ITO (indium tin oxide) /PEDOT: PSS (poly (3, 4-ethylenedioxythiophene): poly (styrene-sulfonate)) /J71: ITIC (1:1, w/w) $/\\mathrm{P}\\dot{\\mathrm{D}}\\mathrm{IN}\\dot{\\mathrm{O}}^{51}$ (perylene diimide functionalized with amino $N$ -oxide)/Al, where PDINO was chosen as the cathode interlayer for lowering the work funciton of $\\mathsf{A l}^{51}$ . The weight ratio of J71 donor: ITIC acceptor is 1: 1 according to our recent work in the studies of non-fullerene PSCs based on J61:ITIC25, considering the similar chemical structure of J71 with J61. The active layers with a thickness of about $100\\mathrm{nm}$ were prepared by spin-coating the J71: ITIC blend solution with a total blend concentration of $1\\dot{2}\\mathrm{mg}\\mathrm{ml}^{-1}$ in chloroform at $3000{\\mathrm{r.p.m}}$ . \n\n![](images/bdd69d4ad6883769506662f2fea571e39cbf06e07d96997e6ab74b385a162fa1.jpg) \nFigure 3 | Photovoltaic performance of the PSCs based on J71:ITIC without (open circles) and with (filled circles) thermal annealing at $\\yen02$ for $\\pmb{10}\\mathbf{min}$ . (a) $J-V$ curves of the champion PSCs, under the illumination of AM $1.56$ , $100\\mathsf{m w c m}^{-2}$ , (b) IPCE spectra of the corresponding ${\\mathsf{P S C s}};$ (c) Light intensity dependence of $J_{\\mathsf{s c}}$ of the ${\\mathsf{P S C s}};$ (d) dark currents of the PSCs, the inset shows the equivalent circuit of the PSCs. \n\n
Table1|Photovoltaicperformance parametersof thePSCsbasedonJ71:ITICunder theilluminationof AM1.5G,mWcm2.
DevicesV.c (V)Jsc (mA cm - 2)FF (%)PCE (%)Rs Ω cm²Rsh kΩ2 cm²μh 10-4cm²v-1s-1μe μh/Me 10-4cm²V -1s-1
As- prepared0.9614.8163.639.03 8.94± 0.2410.380.572.080.96 2.17
0.96± 0.004*14.55 ± 0.5663.85 ±0.51
Thermal- annealed0.94 0.94± 0.00317.32 17.40 ± 0.3769.77 68.09 ± 1.1211.41 11.2 ± 0.291.13 1.93.783.071.23
\n\n\\*Average values with standard deviation were obtained from 30 devices. wThermal annealing at $150^{\\circ}\\mathsf C$ for $10\\min$ . \n\nFigure 3a shows the current density–voltage $\\left(J-V\\right)$ curves, and the corresponding incident photon to converted current efficiency (IPCE) spectra are shown in Fig. 3b. For a clear comparison, the detailed photovoltaic performance data are listed in Table 1. The as-prepared PSCs based on J71: ITIC showed a PCE of $9.03\\%$ with a high $V_{\\mathrm{oc}}$ of $0.96\\mathrm{V}$ , a $J_{s c}$ of $14.81\\mathrm{mA}\\mathrm{cm}^{-2}$ and a FF of $63.63\\%$ . After thermal annealing at $150^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ , the PCE of the PSC was further improved to $11.41\\%$ with a high $V_{\\mathrm{oc}}$ of $0.94\\mathrm{V}$ , a high $J_{\\mathrm{sc}}$ of $17.32\\mathrm{m}\\mathrm{\\dot{A}}\\mathrm{cm}^{-2}$ and a FF of $69.77\\%$ . The PCE of $11.41\\%$ is one of the highest efficiency for the single junction PSCs reported in literatures so far. And very importantly, both high $V_{\\mathrm{oc}}$ and high $J_{\\mathrm{sc}}$ were achieved in the J71:ITIC-based PSCs, which is a big challenge for the high performance PSCs. \n\nIt can be seen that the PSCs based on J71: ITIC exhibited high $V_{\\mathrm{oc}}$ in the range of $0.94\\mathrm{-}0.96\\mathrm{V} $ , which is certainly benefitted from the low-lying HOMO energy level of the alkylsilyl substituted J71. As mentioned in the Introduction part, a crucial issue in the studies of PSCs is to minimize the device photon energy loss $(E_{\\mathrm{loss}})$ which is defined as $E_{\\mathrm{loss}}=E_{\\mathrm{g}}–\\mathrm{e}V_{\\mathrm{oc}},$ where $E_{\\mathrm{g}}$ is the lowest optical band gap among the donor and acceptor components33–35. In the present PSCs based on J71: ITIC, the lowest $E_{\\mathrm{g}}$ is $1.59\\mathrm{eV}$ for the ITIC acceptor with onset absorption at \n\n$782\\mathrm{nm}$ (see Supplementary Fig. 5b). Therefore the $V_{\\mathrm{oc}}$ of $0.94\\substack{-0.96\\mathrm{V}}$ results in a low $\\boldsymbol{E_{\\mathrm{loss}}}$ of $0.63\\substack{-0.65\\mathrm{eV}}$ , which is smaller than that of most PSCs and approaching the empirically low threshold of $0.6\\mathrm{eV}$ . It should be mentioned that using the onset absorption to determine $E_{\\mathrm{g}}$ is the commonly accepted and wide used method by different groups33–35,52,53. And this method can provide a straight forward comparison of our results with those results previously reported (see Supplementary Table 3). Recently, Scharber et al. proposed a more accurate method to measure the $E_{\\mathrm{g}}$ value of the active layer (blend of donor and acceptor) of the PSCs from IPCE spectrum36. With this method, we obtained a $E_{\\mathrm{g}}$ of $1.58\\mathrm{eV}$ from the onset of IPCE spectrum of the PSC based on J71:ITIC (as shown in Supplementary Fig. 6) which is consistent with the $E_{\\mathrm{g}}$ value of $\\bar{1}.59\\mathrm{eV}$ from the absorption edge of ITIC mentioned above. \n\nThe plot of $\\mathrm{e}V_{\\mathrm{OC}}$ against $E_{\\mathrm{g}},$ and the plots of PCE and $\\mathrm{IPCE}_{\\operatorname*{max}}$ against $\\boldsymbol{E_{\\mathrm{loss}}}$ for the PSCs reported in literatures are provided in Supplementary Fig. 7, and the detailed data of the corresponding devices are listed in Supplementary Table 3 for a clear comparison. It should be noted that the PCE and the $\\mathrm{IPCE}_{\\operatorname*{max}}$ $(76.5\\%)$ of the PSC based on J71/ITIC are in fact the highest values among the fullerene and non-fullerene PSCs reported in literatures with $\\boldsymbol{E_{\\mathrm{loss}}}$ less than $0.65\\mathrm{eV}$ . Such small $\\boldsymbol{E_{\\mathrm{loss}}}$ is benefitted from the small $\\Delta E_{\\mathrm{HOMO}}$ of $0.11\\mathrm{eV}$ in the PSCs based on J71/ITIC. \n\nThe IPCE spectra of the PSCs based on J71: ITIC (Fig. 3b) demonstrate broad and high photo-response from 300 to $790\\mathrm{nm}$ , which indicates high photo-conversion efficiency for the absorptions of both J71 polymer donor and ITIC acceptor. The IPCE spectra in the wavelength range of $650\\mathrm{-}790\\mathrm{nm}$ are corresponding to the excitons dissociation of the ITIC acceptor with the hole transfer from the HOMO of ITIC to that of J71. The high IPCE values in this range confirm that efficient hole transfer process did occour even though the $\\Delta E_{\\mathrm{HOMO}}$ between J71 donor and ITIC acceptor is only 0.11 eV. The $J_{s c}$ values integrated from the IPCE spectra are $\\mathrm{i}6.564\\mathrm{mAcm}^{-2}$ for the thermal annealed device and $14.688\\mathrm{mAcm}^{-2}$ for the as-prepared device, which agrees well with those values obtained from the $J{-}V$ curves within $5\\%$ mismatch (Table 1). It should be noted that the low $\\Delta E_{\\mathrm{HOMO}}$ request can provide big chance in the molecular design of photovoltaic materials, such as for the polymer donor to further downshift its $E_{\\mathrm{HOMO}}$ toward a larger $V_{\\mathrm{oc}},$ thus it will be promising to address the big challenge of PSCs for maximizing $V_{\\mathrm{oc}}$ and $J_{s c}$ at the same time and ultimately getting a highefficiency. \n\nWe also tried to fabricate the inverted PSCs with a device structure of $\\mathrm{ITO/ZnO}$ /J71: ITIC (1:1, w/w) $/\\mathrm{MoO}_{3}/\\mathrm{Al}$ . The inverted PSC with thermal annealing at $150^{\\circ}\\mathrm{C}$ for $10\\mathrm{{min}}$ showed a PCE of $10.7\\%$ with a $V_{\\mathrm{oc}}$ of $0.93\\mathrm{V}$ , a $J_{\\mathrm{sc}}$ of $17.36\\mathrm{mAcm}^{-2}$ and a FF of $66.05\\%$ , as shown in Supplementary Fig. 8. The slightly lower PCE of the inverted device could be due to the electrode buffer layer materials used in the inverted PSCs, and the optimization of the inverted PSCs is underway. \n\nThe charge carrier mobilities of the PSCs were measured by space-charge-limited current (SCLC) method to investigate the effect of thermal annealing. The plots of the current density versus voltage of the devices for the mobility measurements are shown in Supplementary Fig. 9. For the as-cast blend film, their hole mobility $\\mu_{\\mathrm{h}}$ and electron mobility $\\mu_{\\mathrm{e}}$ are estimated to be $\\phantom{-}2.08\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}s^{-1}$ and $0.96\\times\\dot{1}0^{-4}\\dot{\\mathrm{cm}}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ respectively with $\\mu_{\\mathrm{h}}/\\mu_{\\mathrm{e}}$ of 2.17, while after thermal annealing the $\\mu_{\\mathrm{h}}$ and $\\mu_{\\mathrm{e}}$ values were increased to $3.78\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ and $\\mathrm{\\dot{3}.07}\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ respectively with the improved $\\mu_{\\mathrm{h}}/\\mu_{\\mathrm{e}}$ ratio of 1.23. The improved photovoltaic performance of the PSCs with thermal annealing could be ascribed to the higher and more-balanced charge carrier mobilities of the thermal-treated J71: ITIC film. Figure 3c shows the dependance of $J_{s c}$ values on the light-intensity $(P_{\\mathrm{light}})$ which reflects the charge recombination behaviour of the devices. In general, the relationship between $J_{\\mathrm{sc}}$ and $P_{\\mathrm{light}}$ can be described as $J_{\\mathrm{sc}}\\propto P_{\\mathrm{light}}^{\\alpha}$ . If the bimolecular recombination of the charge carriers is negligible, the power-law exponent $\\alpha$ should be unity. The values of $\\alpha$ for the as-prepared and thermal treated devices are 0.922 and 0.986, respectively (Fig. 3c). The higher $\\alpha$ value of the thermal-treated device suggests the reduced charge recombination in its device, which correlates well with the balanced charge carrier mobilities of the devices mentioned above. \n\nThe effect of thermal annealing on the device performance was further studied by analysing the series resistance $(R_{s})$ and shunt resistance $(R_{\\mathrm{sh}})$ of the devices from their dark $J{-}V$ curves (Fig. 3d), and the $R_{s}$ and $R_{\\mathrm{sh}}$ values are also listed in Table 1. The $R_{s}$ and $R_{\\mathrm{sh}}$ values of the as-prepared device are $10.38\\Omega\\mathrm{cm}^{2}$ and $0.57\\mathrm{k}\\Omega\\mathrm{cm}^{2}$ respectively, while after thermal annealing, $R_{s}$ was decreased to $1.{\\dot{1}}3\\Omega\\mathrm{cm}^{2}$ and $R_{\\mathrm{sh}}$ was increased to $1.9\\mathrm{k}\\Omega\\mathrm{cm}^{2}$ , suggesting the better overall diode characteristics after the thermal annealing, which is also reflected in the lower ideality factor $n$ (1.51 for the thermal-annealed device in comparison with 1.92 for the as-prepared device) and lowest dark saturation current density $J_{\\mathrm{o}}$ $(1.89\\times10^{-10}\\mathrm{mA}\\mathrm{cm}^{-2}$ for the thermal-annealed device while it is $1.44\\times10^{-8}\\mathrm{mAcm}^{-2}$ for the as-prepared device). \n\nMorphological characterization. For non-fullerene PSCs, morphology can be a determining factor governing the devcie performance54,55. Here, the microstructural features and surface morphologies of the neat J71 and ITIC films as well as their blend films with or wihtout thermal annealing were investigated by grazing incident wide-angle X-ray diffraction (GIWAXS) plots56 and tapping-mode atomic force microscopy (AFM). Figure 4 shows the plots and images of the GIWAXS measurements. Strong diffraction peaks of the neat J71 film, as shown in Fig. 4b, reveal the semicrystalline structure and strong preference for faceon orientation in the polymer film. In addition, characteristic of the long range order and crystallinity in the film was observed in the in-plane direction. The high crystallinity is largely benefitted from its proper side chain42 and fluorination effect48. For neat ITIC film, its lamellar (100) peak is located at $0.360\\mathring{\\mathrm{A}}^{-1}$ and $\\pi{-}\\pi$ stacking (010) peak is at $1.{\\dot{7}}5{\\mathring{\\mathrm{A}}}^{-1}$ (Fig. 4a,e), corresponding to lamellar distance of $17.44\\mathring{\\mathrm{A}}$ and a $\\pi{-}\\pi$ stacking distance of $3.58\\mathrm{\\AA}$ . Its large azimuthal distribution of the diffraction peaks suggests randomly oriented crystallites, which is related to the steric effect of its tetrahexylphenyl substituents. \n\nFor the blend films, the GIWAXS plots demonstrated microstructural features with the diffraction patterns contributed from individual components (Fig. 4c,g). After thermal annealing, the J71: ITIC blend film is more prone to adopt a prominent faceon orientation (Fig. 4d,h) as evidenced by the small azimuthal distribution of the (010) p-p stacking in the out-of-plane direction. Further looking into diffraction patterns, it can be found that, the peak intensities become significantly stronger accompanied by their narrower peak widths $(\\mathrm{Fig.4d,h})$ . Furthermore, a $3.85\\mathring{\\mathrm{A}}$ p-p-stacking distance $(q=1.63\\mathring\\mathrm{A}^{-1})$ is seen in the thermal treated blend films, which is slighltly smaller than that of the as-cast J71: ITIC film $(3.88\\mathring{\\mathrm{A}}$ , $q=1.62\\mathring{\\mathrm{A}}^{-1})$ . All the behaviour is related to the higher crystalline characteristics of the thermal treated blend film, and the combination of the preferred face-on orientation and the tight $\\pi{-}\\pi$ -stacking of the polymer backbone is known to assist intermolecular charge transport and suppress the charge carrier recombination, which eventually improves the photovoltaic performance. \n\nThe AFM images, as shown in Supplementary Fig. 10, reveal that the blend films have relatively smooth surface with a rootmean-square (RMS) roughness of $0.722\\mathrm{nm}$ for the as-cast J71: ITIC blend film and $0.741\\mathrm{nm}$ for the thermal annealed blend film, indicating the good miscibility between the alkylsilyl substituted J71 polymer donor and ITIC acceptor. From the AFM phase images in Supplementary Fig. 10d, it can be seen that with the thermal annealing, enhanced crystalline domains with nano-networks around $20\\mathrm{nm}$ are visualized. This highly intercrystalline morphology asross the active layer enhances the polymer donor domain connectivity and thereby improves the hole transport, which correlates well with its superior device performance. \n\nHole transfer and charge separation dynamics. As mentioned above, it is likely that hole transfer from ITIC to J71 is highly efficient, despite the energy difference between HOMO levels $(\\Delta E_{\\mathrm{HOMO}})$ of ITIC and J71 is only $0.11\\mathrm{eV}$ which is much smaller than the empirical threshold of $0.3\\mathrm{eV}$ for effective exciton dissociation. To confirm the assessment, we performed transient absorption spectroscopy measurement to investigate the charge transfer dynamics of photo-induced carriers in the blend film of J71: ITIC. The primary absorption peaks for J71 and ITIC are well separated in spectral domain (Fig. 2b), so we can extract the spectral and temporal characteristics of hole transfer dynamics with selected excitation. The pump wavelengths of 540 and $710\\mathrm{nm}$ were selected to excite J71 and ITIC, respectively. The excitation density is kept in a weak regime below $1\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ to avoid the effect of exciton-exciton annihilation. The pump-probe experiments measure the pump-induced differential change of the probe transmission, $\\Delta\\bar{T}/T=(T_{\\mathrm{pump-on}}-T_{\\mathrm{pump-off}})/T_{\\mathrm{pump}}$ -off. \n\n![](images/e6ce90f0d8220f65337cfe4bdd11d373df106cbd72d0d45e0ac887b4a9474afb.jpg) \nFigure 4 | Plots and images of the GIWAXS measurements. Line cuts of the GIWAXS images of (a) neat ITIC film and $(\\pmb{6})$ neat J71 film, (c) as cast J71: ITIC blend films and (d) thermal annealed J71: ITIC blend films. GIWAXS images of (e) the neat ITIC film, (f) neat J71 film, $\\mathbf{\\sigma}(\\mathbf{g})$ as acst J71: ITIC film and ${\\bf\\Pi}({\\bf h})$ thermal annealed J71: ITIC film. \n\nFigure 5 shows the results of transient absorption spectroscopy with excitation wavelength at $710\\mathrm{nm}$ . At this pump wavelength, only ITIC is excited as confirmed by the absence of transient absorption signal from the neat sample of J71 (Supplementary Fig. 11). A bleaching signal peaked at $710\\mathrm{nm}$ appears in both neat ITIC and the blend (Fig. 5a,b). This signal at the absorption peak of ITIC can be naturally ascribed to the ground state bleaching (GSB) of the transition in ITIC. In addition, clear bleaching peaks at 540 and $590\\mathrm{nm}$ appear in the transient absorption spectrum of blend (Fig. 5b). These wavelengths are exactly the absorption peaks of J71 (Fig. 2b). The spectral feature is also consistent with the GSB signal from J71 observed with resonant excitation at $540\\mathrm{nm}$ (Supplementary Fig. 11). Figure 5c compares the transient absorption spectra from the blend sample at different time delays with the initial GSB spectra observed in J71 and ITIC under resonant excitations. Basically, the bleaching signals at 540 and $590\\mathrm{nm}$ are built up with the decays of bleaching signal at $710\\mathrm{nm}$ , suggesting the transfer of excitations from ITIC to J71. The excitation photon energy (at $710\\mathrm{nm},$ ) is much smaller than that required for exciton absorption of the polymer, therefore, the bleaching signals (540 and $590\\mathrm{nm},$ ) cannot be ascribed to energy transfer process. Notably, the bleaching signals at about $540\\mathrm{nm}$ and about $590\\mathrm{nm}$ appear simultaneously with the decay of the GSB signals of ITIC at about $710\\mathrm{nm}$ (Fig. 5c), such excitation transfer can be naturally assigned to the hole transfer since the LUMO level of ITIC is much lower than that of J71. \n\nFigure 5d compares the dynamics probed at $710\\mathrm{nm}$ for the films of neat ITIC and blend J71:ITIC in a normalized scale. For the early stage at less than $20\\mathrm{ps}$ , the relaxation rate becomes dramatically faster in the blend film with respect to the neat ITIC, indicating the presence of additional relaxation channel of hole transfer in the blend film. We quantify the early-stage kinetics with a bi-exponetial decay function (Supplementary Fig. 12). The lifetime parameters for the two components are about $0.72\\mathrm{ps}$ and about 15.0 ps respectively for the neat ITIC which decreases to about $0.29\\mathrm{ps}$ and about 4.5 ps in the blends. Correspondingly, the buildup of signals probed at 540 and $590\\mathrm{nm}$ in blend film is different from the abrupt rises observed in J71 excited at $570\\mathrm{nm}$ (Supplementary Fig. 11). The onset shows two exponential growth components with lifetime parameters of about $0.3{\\mathrm p s}$ and about $4.8\\mathrm{ps}$ respectively (Fig. 5e), confirming the hole transfer is the primary origin of the GSB signal at the absorption band of J71. With these results, we briefly summarize the dynamics in Fig. 5f where the hole transfer from ITIC is quite efficient with rate up to $3\\mathrm{p}\\mathrm{s}^{-1}$ . Moreover, it is worthy noting that the GSB signals at 540, 590 and $710\\mathrm{nm}$ in the blend film persist to nanosecond scale which is much longer than those in neat samples of J71 and ITIC. The results suggest the existence of the long-lived dissociated excitons in the blend which is beneficial for electricity generation. \n\n![](images/7c44cfd797e7187fa7566d23e1d6e3b59460ddb772e62349b26e0df133654c46.jpg) \nFigure 5 | Transient absorption measurements for the study of hole transfer dynamics. transient absorption signal recorded from the films of (a) neat ITIC and (b) J71: ITIC (1:1, w/w) blend excited by $710\\mathsf{n m}$ . (c) Transient absorption spectra from the blend film exicted by $710\\mathsf{n m}$ (orange line) at different time delays. The lower panel shows the transient absorption spectra recorded at 1 ps from ITIC excited by $710\\mathsf{n m}$ and J71 excited by $540\\mathsf{n m}$ (blue line), respectively. (d) Dynamics probed at $710\\mathsf{n m}$ recorded from the films of neat ITIC and blend J71: ITIC (1:1, w/w). (e) Dynamic curves probed at 540 and $590\\mathsf{n m}$ recorded from the film of blend. (f) A schematic digram of the hole transfer in the film of J71: ITIC (1:1, w/w) blend. \n\n# Discussion \n\nIn conclusion, another BDTT-FBTA-based 2D-conjugated D-A copolymer J71 with tripropylsilyl substituents on thiophene conjugated side-chain of BDTT unit, was synthesized. J71 possesses a low-lying HOMO energy level at $-5.40\\mathrm{eV}$ and high film absorption extinction coefficients which is benefitted from the $\\sigma^{*}\\left(\\mathrm{Si}\\right){-}\\pi^{*}(\\mathrm{C})$ bond interaction with the trialkylsilyl substitution. Non-fullerene PSCs were fabricated with J71 as donor and a narrow bandgap n-OS ITIC as acceptor, and the PCE of the PSCs based on J71/ITIC (1:1, w/w) with thermal annealing at $150^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ reached $11.41\\%$ with simultaneously high $V_{\\mathrm{oc}}$ of $0.94\\mathrm{V}$ and a high $J_{\\mathrm{sc}}$ of $17.32\\mathrm{mA}\\mathrm{cm}^{-2}$ . The PCE of $11.41\\%$ is one of the highest efficiencies of the single-junction PSCs reported in literatures till now. The high $V_{\\mathrm{oc}},$ which results in a low $E_{\\mathrm{loss}}$ of $0.63\\mathrm{-}0.65\\mathrm{eV}$ for the PSC, is benefitted from the low-lying HOMO level of the J71 donor. The high $J_{\\mathrm{sc}}$ should be ascribed to the extraordinarily high exciton charge separation efficiency even though the HOMO energy difference between the donor and acceptor is quite small (only $0.11\\mathrm{eV})$ . And the high hole transfer efficiency from ITIC to J71 was confirmed by transient absorption spectra. The results indicate that the alkylsilyl substitution is an effective way in designing high performance conjugated polymer photovoltaic materials and the driving force for the hole transfer from the acceptor to donor could be quite small in the non-fullerene PSCs with the $\\mathrm{\\Omega_{n-}}\\mathrm{OS}$ as acceptor. \n\n# Methods \n\nMaterials and synthesis. ITIC was purchased from Solarmer Materials Inc. The other chemicals and solvents were purchased from J&K, Alfa Aesar or TCI Chemical Co. The monomers and polymer J71 were synthesized according to Scheme 1. The Benzo[1,2-b:4,5-b0]dithiophene-4,8-dione and M2 was synthesized according to the procedure reported in the literatures39. \n\nMonomer 1 was synthesized as follows: Under protection of argon, to a solution of thiophene $(8.4\\mathrm{g},100\\mathrm{mmol}$ ) in THF $(100\\mathrm{ml})$ at $-78^{\\circ}\\mathrm{C}$ was added $n$ -BuLi ( $40\\mathrm{ml}$ , $2.5\\mathrm{M}$ in hexane) slowly, the mixture was kept at $-78^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ and warmed slowly to room temperature. Then, chlorotripropylsilane $(19.2\\mathrm{g},$ $100\\mathrm{mmol}.$ ) was added, and the mixture stirred overnight. The mixture was extracted by diethyl ether twice, washed by water and brine. Further purification was carried out by column chromatography using hexane as eluent to obtain pure tripropyl(thiophen-2-yl)silane (1). as a colourless liquid. $(22.3\\mathrm{g},93\\%$ yield). $\\mathrm{^1HNMR}(400\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3},$ ), d (p.p.m.): 7.57-7.56 (d, 1H), 7.22 (d, 1H), 7.16-7.15(t, 1H), 1.40-1.32 (m, 6H), 0.96-0.92(m, 9H), 0.80-0.75(m, 6H). \n\nMonomer BDTT-Si was synthesized as follows: Under protection of argon, to a solution of compound 1 $(7.2\\mathrm{g},30\\mathrm{mmol})$ in THF $\\mathrm{30ml})$ at $0{}^{\\circ}\\mathrm{C}$ was added $n$ -BuLi ( $12\\mathrm{ml}$ , 2.5 M in hexane), the mixture was kept at $0^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ and heated to $50^{\\circ}\\mathrm{C}$ and strirred for $^{2\\mathrm{h}}$ . Then, Benzo[1,2-b:4,5-b0]dithiophene- $^{.4,8}$ -dione $2.2\\mathrm{g},10\\mathrm{mmol},$ ) was added quickly, and the mixture stirred for 2 h. After cooling down to the room temperature, $\\mathrm{SnCl}_{2}\\cdot2\\mathrm{H}_{2}\\mathrm{O}$ $\\mathrm{(189,80mmol)}$ in $10\\%$ HCl $(35\\mathrm{ml})$ was added, and the mixture was stirred for 3 h. The mixture was extracted by diethyl ether twice, washed by water and brine. The crude product purified with column chromatography using petroleum ether as eluent to obtain pure 4,8-bis (5-(tripropylsilyl)thiophen-2-yl)benzo[1,2-b:4,5-b0]dithiophene (BDTT-Si) as a light yellow solid. $2.8\\:\\mathrm{g}\\mathrm{.}$ , $42\\%$ yield). $^1\\mathrm{H}$ NMR ${\\bf\\dot{400}M H z}$ $\\mathrm{CDCl}_{3}$ ), d (p.p.m.): 7.65-7.64(d, 2H), 7.57-7.56 (d, 2H), 7.47-7.45 (d, 2H), 7.36-7.35(d, 2H), 1.53-1.42(m, 12H), 1.05-1.00(m, 18H), 0.92-0.86 (m, 12H). $^{13}\\mathrm{C}$ NMR $(100\\mathrm{MHz},$ $\\mathrm{CDCl}_{3})$ , d (p.p.m.):145.0, 139.3, 139.1, 136.6, 134.9, 129.3, 127.7, 124.2, 123.6, 18.6, 17.6, 16.5. \n\nMonomer M1 was synthesized as follows: To a solution of BDTT-Si $(1.332{\\mathrm{g}},$ $2\\mathrm{mmol},$ ) in THF $(20\\mathrm{ml})$ at $-78^{\\circ}\\mathrm{C}$ was added $n$ -BuLi $(2\\mathrm{ml},2.5\\mathrm{M}$ in hexane). After the addition, the mixture was kept at $\\cdot78^{\\circ}\\mathrm{C}$ for $40\\mathrm{{min};}$ trimethyltin chloride (6 ml, 1 M in THF) was added dropwise. The resulting mixture was stirred for $^{2\\mathrm{h}}$ at room temperature. Then, it was poured into water and extracted with diethyl ether, washed by water and brine and after drying over $\\mathrm{MgSO_{4}}$ , the solvent was removed and the residue was recrystallized with methanol to afford a yellow crystal $^{\\cdot}5,5^{\\prime}$ -(2,6-bis(trimethylstannyl)benzo(1,2-b:4,5-b0)dithiophene-4, 8-diyl)bis(thiophene-5,2-diyl))bis(tripropylsilane) (M1) $(1.56\\:\\mathrm{g},$ $78.8\\%$ yield). $^1\\mathrm{H}$ NMR ${'}_{400}\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}.$ ), d $(\\mathrm{p.p.m.})$ : 7.74-7.67(t, 2H), 7.60–7.59(d, 2H), 7.36(d, 2H), 1.53–1.45(m, 12H), 1.04–0.97 $\\mathrm{{;m,18H}}$ , 0.91–0.87(m, 12H), 0.46-0.32(t, 18H). $^{13}\\mathrm{C}$ NMR ${100}\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}$ ), d (p.p.m.):205.9, 144.9, 142.3, 141.4, 137.8, 136.5, 133.9, 130.4, 128.0, 121.5, 30.0, 17.6, 16.6, 15.3, \u0002 7.4, \u0002 7.5, $-9.3,\\ -11.0,\\ -11.1.$ \n\nPolymer J71 was synthesized as follows: M1 (248 mg, $0.25\\mathrm{mmol}$ ) and M2 (175 mg, 0.25 mmol) and dry toluene $(10\\mathrm{ml})$ were added to a $25\\mathrm{ml}$ double-neck round-bottom flask. The reaction container was purged with argon for $20\\mathrm{min}$ , and then $\\mathrm{Pd}(\\mathrm{PPh}_{3})_{4}$ ( $\\mathrm{\\Delta\\cdot10\\mg)}$ was added. After another flushing with argon for $20\\mathrm{min}$ , the reactant was heated to reflux for $12\\mathrm{h}$ . The reactant was cooled down to room temperature and poured into MeOH $(200\\mathrm{ml})$ , then filtered through a Soxhlet thimble, which was then subjected to Soxhlet extraction with methanol, hexane, and chloroform. The polymer J71 of $275\\mathrm{mg}$ (Yield $91\\%$ ) was recovered as solid from the chloroform fraction by precipitation from methanol, and was dried under vacuum. GPC: $M_{\\mathrm{n}}{=}23.5\\mathrm{kDa}$ ; $M_{\\mathrm{w}}/M_{\\mathrm{n}}=2.0$ . Anal. Calcd for $\\mathrm{C}_{66}\\mathrm{H}_{85}\\mathrm{F}_{2}\\mathrm{N}_{3}\\mathrm{S}_{6}\\mathrm{Si}_{2}$ $(\\%)$ : C, 65.68; H, 7.10; N, 3.48. Found $\\scriptstyle(\\%):{\\mathcal{C}}$ , 64.79; H, 7.06; N, 3.55. $^1\\mathrm{H}$ NMR $(\\mathrm{CDCl}_{3}$ , $\\boldsymbol{400}\\mathrm{MHz},$ ): d (p.p.m.) 8.15–8.12 (br, 2H), 8.01–7.45 (br, 6H), 7.20–6.90 (br, 2H), 4.69 (br, 2H), 2.24–0.83 (br, 73H). \n\nGeneral characterization. $\\mathrm{{}^{1}H\\ N M R}$ spectra were measured on a Bruker DMX–400 spectrometer with $d-$ chloroform as the solvent and trimethylsilane as the internal reference. Ultraviolet–visible absorption spectra were measured on a Hitachi U–3010 Ultraviolet–vis spectrophotometer. Mass spectra were recorded on a Shimadzu spectrometer. Elemental analyses were carried out on a flash EA 1112 elemental analyser. Thermogravimetric analysis (TGA) was conducted on a Perkin–Elmer TGA–7 thermogravimetric analyser at a heating rate of $20^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ under a nitrogen flow rate of $\\mathbf{\\dot{1}}00\\mathbf{m}\\mathbf{l}\\operatorname*{min}^{-1}$ . Gel permeation chromatography (GPC) measurements was performed on Agilent PL-GPC 220 instrument with high temperature chromatograph, using $^{1,2,4}$ -trichlorobenzene as the eluent at $160^{\\circ}\\mathrm{C}$ Photoluminescience (PL) spectra were measured with a Shimadzu RF-5301PC fluorescence spectrophotometer. Electrochemical cyclic voltammetry was performed on a Zahner IM6e Electrochemical Workstation under a nitrogen atmosphere. The cyclic voltammograms of J71 polymer film and ITIC film on a Pt disk electrode (working electrode) were measured with a potential scan rate of $20\\mathrm{mVs}^{-1}$ in an acetonitrile solution of $0.1\\mathrm{M}$ tetrabutylammonium hexafluorophosphate $\\mathrm{(n-Bu_{4}N P F_{6})}$ with a $\\mathrm{\\Ag/AgCl}$ reference electrode and a platinum wire counter electrode. The ferrocene/ferrocenium $(\\mathrm{Fc/Fc}^{+}$ ) couple was used as an internal reference. Thin films of J71 or ITIC were prepared by drop-casting $1.0\\upmu\\mathrm{l}$ of their chloroform solutions (analytical reagent, $1\\mathrm{{mg}}\\mathrm{{ml}}^{-1}$ ) onto the working electrode and then dried in the air. The J71 or ITIC film and J71:ITIC blend film for morphology measurements were prepared by spin-coating the corresponding solution in chloroform with a concentration of $\\mathrm{i0ingml^{-1}}$ on indium tin oxide (ITO) glass at $^{3,000\\mathrm{rpm}}$ for $30s$ . The film morphology was measured using an atomic force microscope (AFM, SPA-400) using the tapping mode. \n\nHole and electron mobilities were measured using the the space charge limited current (SCLC) method, with the hole-only device of ITO/PEDOT:PSS/J71: ITIC(1:1, w/w) /Au for hole mobility measurement and electron-only device of $\\mathrm{ITO/ZnO/J71}$ : ITIC (1: 1, w/w) /PDINO/Al for electron mobility measurement. The SCLC mobilities were calculated by MOTT-Gurney equation:57,58 \n\n$$\nJ={\\frac{9\\varepsilon_{\\mathrm{{r}}}\\varepsilon_{0}\\mu V^{2}}{8L^{3}}}\n$$ \n\nWhere J is the current density, $\\scriptstyle{\\varepsilon_{r}}$ is the relative dieletiric constant of active layer material usually 2–4 for organic semiconductor, herein we use a relative dielectric constant of 4, $\\scriptstyle{\\varepsilon_{O}}$ is the permittivity of empty space, $\\upmu$ is the mobility of hole or electron and L is the thickness of the active layer, $V$ is the internal voltage in the device, and $V=V_{\\mathrm{app}}–V_{\\mathrm{bi}},$ where $V_{\\mathrm{app}}$ is the voltage applied to the device, and $V_{\\mathrm{bi}}$ is the built-in voltage resulting from the relative work function difference between the two electrodes (in the hole-only and the electron-only devices, the $V_{\\mathrm{bi}}$ values are 0.2 and $0\\mathrm{V}$ respectively). \n\nGrazing-incidence wide-angle X-ray scattering (GIWAXS) measurements were conducted at PLS-II 9A USAXS beam line of the Pohang Accelerator Laboratory in Korea. X-rays coming from the in-vacuum undulator (IVU) were monochromated (wavelength $\\lambda{=}1.1\\mathrm{0}\\mathrm{\\dot{9}}~94\\mathrm{\\AA}$ ) using a double crystal monochromator and focused both horizontally and vertically $(450~\\mathrm{(H)}\\times60~\\mathrm{(V)}\\upmu\\mathrm{m}^{2}$ in fwhm at sample position) using K-B type mirrors. The GIWAXS sample stage was equipped with a 7-axis motorized stage for the fine alignment of sample, and the incidence angle of X-ray beam was set to be $0.13\\substack{-0.135^{\\circ}}$ for polymer films, ITIC film and their bend films. GIWAXS patterns were recorded with a 2D CCD detector (Rayonix SX165), and X-ray irradiation time was $6{-}9s,$ dependent on the saturation level of the detector. Diffraction angles were calibrated using a sucrose standard (monoclinic, P21, $a=10.8631\\mathrm{\\AA}$ , $\\overset{\\prime}{b}=8.7044\\overset{\\circ}{\\mathrm{A}}$ , $c=7.7624\\mathrm{\\AA}$ , $\\beta=102.938^{\\circ})$ , and the sample-todetector distance was $\\sim231\\mathrm{mm}$ . \n\nFor transient absorption spectroscopy, pump pulses with tunable wavelength were from an optical parametric amplifier pumped by a regenerative amplifier (Libra, Coherent, $1\\mathrm{k}\\mathrm{\\bar{H}z},90\\mathrm{fs},$ ). The carrier dynamics was probed by a broadband supercontinuum light source that was generated by focusing a small portion of the beam of the amplifier onto a sapphire plate. The chirp of the probe supercontinuum was corrected with error to be less than 100 fs over the whole spectral range. The transient absorption signal was then analysed by a high speed charge-coupled device (S11071-1104, Hamamatsu) with a monochromater (Acton 2358, Princeton Instrument) at 1 kHz enabled by a custom-built board from Entwicklungsbuero Stresing. The angle between the polarizations of pump and probe beam was set at the magic angle. \n\nDevice fabrication and characterization. The PSCs were fabricated with a structure of ITO/PEDOT: PSS $(40\\mathrm{nm})$ /active layer/PDINO/Al. A thin layer of PEDOT: PSS was deposited through spin-coating on precleaned ITO-coated glass from a PEDOT: PSS aqueous solution (Baytron P VP AI 4083 from H. C. Starck) at $2{,}000\\mathrm{rpm}$ and dried subsequently at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ in air. Then the device was transferred to a nitrogen glove box, where the active blend layer of J71 and ITIC was spin-coated from its chloroform solution onto the PEDOT: PSS layer under a spin-coating rate of ${3,000}\\mathrm{r.p.m}$ . After spin-coating, the active layers were annealed at $150^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ for the devices with thermal annealing treatment. The thickness of the active layers is about $100\\mathrm{nm}$ . Then methanol solution of PDINO at a concentration of $1.0\\mathrm{mg}\\mathrm{ml}^{-1}$ was deposited atop the active layer at ${3,000}\\mathrm{r.p.m}$ . for $30s$ to afford a PDINO cathode buffer layer with thickness of about $10\\mathrm{nm}$ . Finally, top Al electrode was deposited in vacuum onto the cathode buffer layer at a pressure of about $5.0\\times10^{-5}\\mathrm{Pa}$ . The active area of the devices was $4.{\\dot{7}}\\mathrm{mm}^{2}$ . Optical microscope (Olympus BX51) was used to define the active area of the devices. The current density–voltage $\\left(J-V\\right)$ characteristics of the PSCs were measured in a nitrogen glovebox $(\\mathrm{O}_{2}<0.1\\$ p.p.m., $\\mathrm{H}_{2}\\mathrm{O}{<}0.1$ p.p.m.) on a computer-controlled Keithley 2450 Source-Measure Unit. The voltage scan is from $-1.5$ to $1.5\\mathrm{V}$ with voltage step of $10\\mathrm{mV}$ and delay time of $1\\mathrm{ms}$ . Oriel Sol3A Class AAA Solar Simulator (model, Newport 94023A) with a 450W xenon lamp and an air mass (AM) 1.5 filter was used as the light source. The light intensity was calibrated to $100\\mathrm{mW}\\mathrm{cm}^{-2}$ by a Newport Oriel 91150V reference cell. Masks made by laser beam cutting technology with a well-defined area of $2.2\\mathrm{mm}^{2}$ were used to define the effective area for accurate measurement of the photovoltaic performance. All the measurements with mask or without mask gave consistent results with relative errors within $0.5\\%$ . Actually, the measurement with mask give a slightly higher PCE mainly due to its slightly higher FF. The PCE results in the manuscript are from the measurement without mask. PCE statistics were obtained using 30 individual devices fabricated under the same conditions. The input photon to converted current efficiency (IPCE) was measured by Solar Cell Spectral Response Measurement System QE-R3-011 (Enli Technology Co., Ltd., Taiwan). The light intensity at each wavelength was calibrated with a standard single-crystal Si photovoltaic cell. \n\nData availability. The data that support the findings of this study are available from the corresponding author on request. \n\n# References \n\n1. Yu, G., Gao, J., Hummelen, J. C., Wudl, F. & Heeger, A. J. Polymer photovoltaic cells: enhanced efficiencies via a network of internal donor-acceptor heterojunctions. Science 270, 1789–1791 (1995). \n2. Thompson, B. C. & Fre´chet, J. M. J. Polymer-fullerene composite solar cells. Angew. Chem. Int. Ed. 47, 58–77 (2008). \n3. Li, G., Zhu, R. & Yang, Y. Polymer solar cells. Nat. Photon. 6, 153–161 (2012). \n4. He, Y. & Li, Y. Fullerene derivative acceptors for high performance polymer solar cells. Phys. Chem. Chem. Phys. 13, 1970–1983 (2011). \n5. Zhan, X. et al. A high-mobility electron-transport polymer with broad absorption and its use in field-effect transistors and all-polymer solar cells. J. Am. Chem. Soc. 129, 7246–7247 (2007). \n6. Zhou, E. et al. All-polymer solar cells from perylene diimide based copolymers: material design and phase separation control. Angew. Chem. Int. Ed. 50, 2799–2803 (2011). \n7. Facchetti, A. Polymer donor-polymer acceptor (all-polymer) solar cells. Mater. Today 16, 123–132 (2013). \n8. Kim, T. et al. Flexible, highly efficient all-polymer solar cells. Nat. Commun. 6, 8547 (2015). \n9. Jung, J. W. et al. Fluoro-substituted n-type conjugated polymers for additivefree all-polymer bulk heterojunction solar cells with high power conversion efficiency of $6.71\\%$ . Adv. Mater. 27, 3310–3317 (2015). \n10. Hwang, Y.-J., Courtright, B. A. E., Ferreira, A. S., Tolbert, S. H. & Jenekhe, S. A. $7.7\\%$ Efficient All-Polymer Solar Cells. Adv. Mater. 27, 4578–4584 (2015). \n11. Gao, L. et al. All-polymer solar cells based on absorption-complementary polymer donor and acceptor with high power conversion efficiency of $8.27\\%$ . Adv. Mater. 28, 1884–1890 (2016). \n12. Benten, H., Mori, D., Ohkita, H. & Ito, S. Recent research progress of polymer donor/polymer acceptor blend solar cells. J. Mater. Chem. A 4, 5340–5365 (2016). \n13. Holliday, S. et al. High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor. Nat. Commun. 7, 11585 (2016). \n14. Nielsen, C. B., Holliday, S., Chen, H.-Y., Cryer, S. J. & McCulloch, I. Nonfullerene electron acceptors for use in organic solar cells. Acc. Chem. Res. 48, 2803–2812 (2015). \n15. Hwang, Y.-J., Li, H., Courtright, B. A. E., Subramaniyan, S. & Jenekhe, S. A. Nonfullerene polymer solar cells with $8.5\\%$ efficiency enabled by a new highly twisted electron acceptor dimer. Adv. Mater. 28, 124–131 (2016). \n16. Zhong, Y. et al. Molecular helices as electron acceptors in high-performance bulk heterojunction solar cells. Nat. Commun. 6, 9242 (2015). \n17. Zhang, X. et al. A potential perylene diimide dimer-based acceptor material for highly efficient solution-processed non-fullerene organic solar cells with $4.03\\%$ efficiency. Adv. Mater. 25, 5791–5797 (2013). \n18. Hartnett, P. E. et al. Ring-fusion as a perylenediimide dimer design concept for high-performance non-fullerene organic photovoltaic acceptors. Chem. Sci. 7, 3543–3555 (2016). \n19. Lin, Y. et al. High-performance fullerene-free polymer solar cells with $6.31\\%$ efficiency. Energy Environ. Sci. 8, 610–616 (2015). \n20. Lin, Y. et al. An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174 (2015). \n21. Li, Y. et al. Non-fullerene acceptor with low energy loss and high external quantum efficiency: towards high performance polymer solar cells. J. Mater. Chem. A 4, 5890–5897 (2016). \n22. Lin, Y. et al. High-performance electron acceptor with thienyl side chains for organic photovoltaics. J. Am. Chem. Soc. 138, 4955–4961 (2016). solar cells based on selenophene-containing perylene bisimide acceptor. J. Am. Chem. Soc. 138, 375–380 (2016). \n24. Liu, J. et al. Fast charge separation in a non-fullerene organic solar cell with a small driving force. Nat. Energy 1, 16089 (2016). \n25. Bin, H. et al. Non-fullerene polymer solar cells based on alkylthio and fluorine substituted 2D-conjugated polymers reach $9.5\\%$ efficiency. J. Am. Chem. Soc. 138, 4657–4664 (2016). \n26. Zhao, W. et al. Fullerene-free polymer solar cells with over $11\\%$ efficiency and excellent thermal stability. Adv. Mater. 28, 4734–4739 (2016). \n27. Ran, N. A. et al. Harvesting the full potential of photons with organic solar cells. Adv. Mater. 28, 1482–1488 (2016). \n28. Janssen, R. A. J. & Nelson, J. Factors limiting device efficiency in organic photovoltaics. Adv. Mater. 25, 1847–1858 (2013). \n29. Coakley, K. M. & McGehee, M. D. Conjugated polymer photovoltaic cells. Chem. Mater. 16, 4533–4542 (2004). \n30. Li, Y. Molecular design of photovoltaic materials for polymer solar cells: toward suitable electronic energy levels and broad absorption. Acc. Chem. Res. 45, 723–733 (2012). \n31. Dennler, G., Scharber, M. C. & Brabec, C. J. Polymer-fullerene bulkheterojunction solar cells. Adv. Mater. 21, 1323–1338 (2009). \n32. Scharber, M. C. & Sariciftci, N. S. Efficiency of bulk-heterojunction organic solar cells. Prog. Polym. Sci. 38, 1929–1940 (2013). \n33. Veldman, D., Meskers, S. C. J. & Janssen, R. A. J. The energy of charge-transfer states in electron donor–acceptor blends: insight into the energy losses in organic solar cells. Adv. Funct. Mater. 19, 1939–1948 (2009). \n34. Faist, M. A. et al. Competition between the charge transfer state and the singlet states of donor or acceptor limiting the efficiency in polymer:fullerene solar cells. J. Am. Chem. Soc. 134, 685–692 (2012). \n35. Kawashima, K., Tamai, Y., Ohkita, H., Osaka, I. & Takimiya, K. High-efficiency polymer solar cells with small photon energy loss. Nat. Commun. 6, 10085 (2015). \n36. Scharber, M. C. On the efficiency limit of conjugated polymer:fullerene-based bulk heterojunction solar cells. Adv. Mater. 28, 1994–2001 (2016). \n37. Burke, T. M., Sweetnam, S., Vandewal, K. & McGehee, M. D. Beyond Langevin recombination: how equilibrium between free carriers and charge transfer states determines the open-circuit voltage of organic solar cells. Adv. Energ. Mater 5, 1500123 (2015). \n38. Lin, H. et al. High-performance non-fullerene polymer solar cells based on a pair of donor–acceptor materials with complementary absorption properties. Adv. Mater. 27, 7299–7304 (2015). \n39. Min, J., Zhang, Z.-G., Zhang, S. & Li, Y. Conjugated Side-Chain-Isolated D–A Copolymers Based on Benzo[1,2-b:4,5-b0]dithiophene-altdithienylbenzotriazole: Synthesis and Photovoltaic Properties. Chem. Mater. 24, 3247–3254 (2012). \n40. Chen, J. & Cao, Y. Development of novel conjugated donor polymers for highefficiency bulk-heterojunction photovoltaic devices. Acc. Chem. Res. 42, 1709–1718 (2009). \n41. Zhou, H., Yang, L. & You, W. Rational design of high performance conjugated polymers for organic solar cells. Macromolecules 45, 607–632 (2012). \n42. Zhang, Z.-G. & Li, Y. F. Side-chain engineering of high-efficiency conjugated polymer photovoltaic materials. Sci. China: Chem. 58, 192–209 (2015). \n43. Wang, J.-Y. et al. Benzobis(silolothiophene)-based low bandgap polymers for efficient polymer solar cells. Chem. Mater. 23, 765–767 (2011). \n44. Ashraf, R. S. et al. Silaindacenodithiophene semiconducting polymers for efficient solar cells and high-mobility ambipolar transistors. Chem. Mater. 23, 768–770 (2011). \n45. Love, J. A. et al. Silaindacenodithiophene-based molecular donor: morphological features and use in the fabrication of compositionally tolerant, high-efficiency bulk heterojunction solar cells. J. Am. Chem. Soc. 136, 3597–3606 (2014). \n46. Wu, J.-S., Cheng, S.-W., Cheng, Y.-J. & Hsu, C.-S. Donor-acceptor conjugated polymers based on multifused ladder-type arenes for organic solar cells. Chem. Soc. Rev. 44, 1113–1154 (2015). \n47. Ohshita, J. Conjugated oligomers and polymers containing dithienosilole units. Macromol. Chem. Phys. 210, 1360–1370 (2009). \n48. Price, S. C., Stuart, A. C., Yang, L., Zhou, H. & You, W. Fluorine substituted conjugated polymer of medium band gap yields $7\\%$ efficiency in polymerfullerene solar cells. J. Am. Chem. Soc. 133, 4625–4631 (2011). \n49. Eckhardt, H., Shacklette, L. W., Jen, K. Y. & Elsenbaumer, R. L. The electronic and electrochemical properties of poly(phenylene vinylenes) and poly(thienylene vinylenes): An experimental and theoretical study. J. Chem. Phys 91, 1303–1315 (1989). \n50. Sun, Q., Wang, H., Yang, C. & Li, Y. Synthesis and electroluminescence of novel copolymers containing crown ether spacers. J. Mater. Chem. 13, 800–806 (2003). \n51. Zhang, Z.-G. et al. Perylene diimides: a thickness-insensitive cathode interlayer for high performance polymer solar cells. Energy Environ. Sci. 7, 1966–1973 (2014). \n52. Wang, C. et al. Low band gap polymer solar cells with minimal voltage losses. Adv. Energy Mater. 6, 1600148 (2016). \n53. Li, W., Hendriks, K. H., Furlan, A., Wienk, M. M. & Janssen, R. A. J. High quantum efficiencies in polymer solar cells at energy losses below 0.6 eV. J. Am. Chem. Soc. 137, 2231–2234 (2015). \n54. Liu, F. et al. Characterization of the morphology of solution-processed bulk heterojunction organic photovoltaics. Prog. Polym. Sci. 38, 1990–2052 (2013). \n55. Tumbleston, J. R. et al. The influence of molecular orientation on organic bulk heterojunction solar cells. Nat. Photon. 8, 385–391 (2014). \n56. Rivnay, J., Mannsfeld, S. C. B., Miller, C. E., Salleo, A. & Toney, M. F. Quantitative determination of organic semiconductor microstructure from the molecular to device scale. Chem. Rev. 112, 5488–5519 (2012). \n57. Blom, P. W. M., de Jong, M. J. M. & van Munster, M. G. Electric-field and temperature dependence of the hole mobility in poly(p-phenylene vinylene). Phys. Rev. B 55, R656–R659 (1997). \n58. Malliaras, G. G., Salem, J. R., Brock, P. J. & Scott, C. Electrical characteristics and efficiency of single-layer organic light-emitting diodes. Phys. Rev. B 58, R13411–R13414 (1998). \n\n# Acknowledgements \n\nThis work was supported by the Ministry of Science and Technology of China (973 project, no. 2014CB643501), NSFC (nos. 91433117, 91333204 and 21374124) and the Strategic Priority Research Program of the Chinese Academy of Sciences (no. XDB12030200). The authors would like to thank Dr Dan Deng and Prof. Zhixiang Wei for their help in measuring photovoltaic performance of the inverted structured PSCs \n\n# Author contributions \n\nH.B., $Z.$ -G.Z. and Y.L. designed the polymer J71, H.B. synthesized and characterized J71. L.G., Y.Y. and Z.-G.Z. carried out the device fabrication and characterization, L.X. provide \n\nthe cathode buffer layer material. S.C. and C.Y. measured the GIWAXS diffraction patterns. Y.Z., C.Z. and M.X. measured TA spectra. Y.L. and Z.-G.Z. supervised the project and wrote the paper. The first two authors contributed equally to this work. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Bin, H. et al. $11.4\\%$ Efficiency non-fullerene polymer solar cells with trialkylsilyl substituted 2D-conjugated polymer as donor. Nat. Commun. 7, 13651 doi: 10.1038/ncomms13651 (2016). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2016 " + }, + { + "id": "10.1038_srep37946", + "DOI": "10.1038/srep37946", + "DOI Link": "http://dx.doi.org/10.1038/srep37946", + "Relative Dir Path": "mds/10.1038_srep37946", + "Article Title": "High-Entropy Metal Diborides: A New Class of High-Entropy Materials and a New Type of Ultrahigh Temperature Ceramics", + "Authors": "Gild, J; Zhang, Y; Harrington, T; Jiang, S; Hu, T; Quinn, MC; Mellor, WM; Zhou, N; Vecchio, K; Luo, J", + "Source Title": "SCIENTIFIC REPORTS", + "Abstract": "Seven equimolar, five-component, metal diborides were fabricated via high-energy ball milling and spark plasma sintering. Six of them, including (Hf0.2Zr0.2Ta0.2Nb0.2Ti0.2)B-2, (Hf0.2Zr0.2Ta0.2Mo0.2Ti0.2)B-2, (Hf0.2Zr0.2Mo0.2Nb0.2Ti0.2)B-2, (Hf0.2Mo0.2Ta0.2Nb0.2Ti0.2)B-2, (Mo0.2Zr0.2Ta0.2Nb0.2Ti0.2)B-2, and (Hf0.2Zr0.2Ta0.2Cr0.2Ti0.2)B-2, possess virtually one solid-solution boride phase of the hexagonal AlB2 structure. Revised Hume-Rothery size-difference factors are used to rationalize the formation of high-entropy solid solutions in these metal diborides. Greater than 92% of the theoretical densities have been generally achieved with largely uniform compositions from nulloscale to microscale. Aberration-corrected scanning transmission electron microscopy (AC STEM), with high-angle annular dark-field and annular bright-field (HAADF and ABF) imaging and nulloscale compositional mapping, has been conducted to confirm the formation of 2-D high-entropy metal layers, separated by rigid 2-D boron nets, without any detectable layered segregation along the c-axis. These materials represent a new type of ultra-high temperature ceramics (UHTCs) as well as a new class of high-entropy materials, which not only exemplify the first high-entropy non-oxide ceramics (borides) fabricated but also possess a unique non-cubic (hexagonal) and layered (quasi-2D) high-entropy crystal structure that markedly differs from all those reported in prior studies. Initial property assessments show that both the hardness and the oxidation resistance of these high-entropy metal diborides are generally higher/better than the average performances of five individual metal diborides made by identical fabrication processing.", + "Times Cited, WoS Core": 901, + "Times Cited, All Databases": 985, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000388791700001", + "Markdown": "# SCIENTIFIC REPORTS \n\n# OPEN \n\n# High-Entropy Metal Diborides: A New Class of High-Entropy Materials and a New Type of Ultrahigh Temperature Ceramics \n\nreceived: 13 July 2016 \naccepted: 31 October 2016 \nPublished: 29 November 2016 \n\nJoshua Gild1, Yuanyao Zhang1, Tyler Harrington1, Sicong Jiang1, Tao ${\\mathsf{H}}{\\mathsf{U}}^{2}$ , Matthew C. Quinn2, William M. Mellor2, Naixie Zhou1, Kenneth Vecchio1,2 & Jian Luo1,2 \n\nSeven equimolar, five-component, metal diborides were fabricated via high-energy ball milling and spark plasma sintering. Six of them, including $(\\mathsf{H f}_{0.2}\\mathsf{Z r}_{0.2}\\mathsf{T a}_{0.2}\\mathsf{N b}_{0.2}\\mathsf{T i}_{0.2})\\mathsf{B}_{2},$ $(\\mathsf{H f}_{0.2}\\mathsf{Z r}_{0.2}\\mathsf{T a}_{0.2}\\mathsf{M o}_{0.2}\\mathsf{T i}_{0.2})$ $\\mathsf{B}_{2},$ $\\mathbf{\\chi}_{\\prime}(\\mathsf{H f}_{0.2}\\mathsf{Z r}_{0.2}\\mathsf{M o}_{0.2}\\mathsf{N}\\mathsf{b}_{0.2}\\mathsf{T i}_{0.2})\\mathsf{B}_{2}{}_{\\prime}$ $(\\mathsf{H f}_{0.2}\\mathsf{M o}_{0.2}\\mathsf{T a}_{0.2}\\mathsf{N b}_{0.2}\\mathsf{T i}_{0.2})\\mathsf{B}_{2{\\boldsymbol{r}}}(\\mathsf{M o}_{0.2}\\mathsf{Z r}_{0.2}\\mathsf{T a}_{0.2}\\mathsf{N b}_{0.2}\\mathsf{T i}_{0.2})\\mathsf{B}_{2{\\boldsymbol{r}}}$ and $(\\mathsf{H f}_{0.2}\\mathsf{Z r}_{0.2}\\mathsf{T a}_{0.2}\\mathsf{C r}_{0.2}\\mathsf{T i}_{0.2})\\mathsf{B}_{2},$ possess virtually one solid-solution boride phase of the hexagonal $\\mathsf{A l B}_{2}$ structure. Revised Hume-Rothery size-difference factors are used to rationalize the formation of highentropy solid solutions in these metal diborides. Greater than $92\\%$ of the theoretical densities have been generally achieved with largely uniform compositions from nanoscale to microscale. Aberrationcorrected scanning transmission electron microscopy (AC STEM), with high-angle annular dark-field and annular bright-field (HAADF and ABF) imaging and nanoscale compositional mapping, has been conducted to confirm the formation of 2-D high-entropy metal layers, separated by rigid 2-D boron nets, without any detectable layered segregation along the $\\pmb{c}$ -axis. These materials represent a new type of ultra-high temperature ceramics (UHTCs) as well as a new class of high-entropy materials, which not only exemplify the first high-entropy non-oxide ceramics (borides) fabricated but also possess a unique non-cubic (hexagonal) and layered (quasi-2D) high-entropy crystal structure that markedly differs from all those reported in prior studies. Initial property assessments show that both the hardness and the oxidation resistance of these high-entropy metal diborides are generally higher/better than the average performances of five individual metal diborides made by identical fabrication processing. \n\nRecently, the fabrication and properties of metallic high entropy alloys (HEAs) have attracted significant research interests1,2. In an HEA, the configurational entropy of a solid-solution phase is maximized to stabilize it against the formation of intermetallics. Typically, five or more elements can be mixed in a HEA in equimolar concentrations to produce a maximum molar configurational entropy of $\\Delta S_{\\mathrm{mix}}{=}R\\mathrm{ln}N$ , where $N$ is the number of equimolar components and $R$ is the gas constant1,2. HEAs have shown superior mechanical and physical properties1–3; specially, a series of recent studies fabricated a class of refractory, metallic HEAs and demonstrated their excellent wear resistance and strength, including (especially) exceptional high-temperature properties4–8. Since the minimization of Gibbs free energy ( $\\scriptstyle{G=H-T S}$ , where $H$ is enthalpy, S is entropy, and $T$ is temperature) dictates the thermodynamic stability of a material at a constant pressure, a high-entropy material (with large S) can be thermodynamically more stable (particularly) at high temperatures, motivating this study to explore the phase stability and fabrication feasibility of high-entropy metal diborides, as a new type of high-entropy materials as well as a new class of ultra-high temperature ceramics (UHTCs). \n\nMost prior studies of crystalline high-entropy materials have been conducted for metallic HEAs of mostly simple face- and body-centered cubic (FCC and BCC), as well as occasionally hexagonal close packing (HCP), crystal structures1,2; much less studies have been done for making crystalline high-entropy ceramics (albeit that glasses can be considered high-entropy materials in a broad definition), particularly those with more complex, non-cubic, crystal structures. Most recently, Rost et al. successfully fabricated an entropy-stabilized oxide, $(\\mathrm{Mg_{0.2}C o_{0.2}N i_{0.2}C u_{0.2}Z n_{0.2}})\\mathrm{O}$ that possessed a single-phase rocksalt (which is also a FCC) structure when it was \n\n1Program of Materials Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0448, USA. 2Department of NanoEngineering, University of California, San Diego, La Jolla, CA 92093-0448, USA. Correspondence and requests for materials should be addressed to J.L. (email: jluo@alum.mit.edu) \n\nTable 1.  Summary of the seven metal diboride systems studied. For the lattice parameters ( $\\mathbf{\\Phi}_{.}^{\\cdot}\\mathbf{\\Phi}_{a}$ and $c_{,\\-}$ ), the “average” values represent the means of five individual metal diborides while the $\\ensuremath{\\mathrm{^{*}X R D^{*}}}$ values represent the actual lattice parameters of the high-entropy solutions measured by XRD. See Supplementary Table S-I for additional data. \n\n\n
CompositionSingle Boride Phase?8a8a(A)c(A)Relative Density
AverageXRDAverageXRD
HEB#1(Hfo.2Zro.2Tao.2Nbo.2Tio.2)BYes1.4%3.9%3.1103.1013.3463.36192.4%
HEB#2(Hfo.ZroTaMoo2)BYes1.7%5.2%3.0933.0803.3073.31692.4%
HEB #3(HfoZroMoNbT)BYes1.7%5.2%3.1013.0923.3113.34592.3%
HEB#4(Hfo.2Moo.2Tao.Nbo.2Tio.2)BYes1.3%4.0%3.0843.0823.2533.27992.2%
HEB#5(M00.2Zro.2Tao.2Nbo.Tio.2)BYes1.6%4.6%3.0903.0753.2653.25392.1%
HEB#6(Hfo.2Zro.Wo.2M0.2Ti0.2)BNo2.0%6.2%3.0823.268
HEB #7(Hfo.2Zr0o.2Ta0.2Cro.2Tio.2)BYes2.3%5.2%3.0813.0793.3073.33692.2%
\n\n![](images/294df669e1b34077ec0d06f169c53c754ea1d7f1e8c859830e1747707b59d2ce.jpg) \nFigure 1.  Schematic illustration of the atomic structure of the high-entropy metal diborides. Here, $\\mathbf{M}_{1},\\mathbf{M}_{2}$ , $\\mathbf{M}_{3}$ , $\\mathrm{{\\bfM}}_{4},$ and $\\mathbf{M}_{5}$ represent five different transition metals (selected from Zr, Hf, Ti, Ta, Nb, W, and Mo). This new class of high-entropy materials and new type of UHTCs have a unique layered hexagonal crystal structure with alternating rigid 2D boron nets and high-entropy 2D layers of metal cations (as essentially a class of quasi-2D high-entropy materials), with mixed ionic and covalent (M-B) bonds between the metals and boron. \n\nquenched from a sufficiently high temperature9; subsequent studies revealed that this entropy-stabilized oxide and its derivatives, $(\\mathrm{Mg_{0.2}C o_{0.2}N i_{0.2}C u_{0.2}Z n_{0.2}})_{1-x-y}\\mathrm{Ga}_{y}A_{x}\\mathrm{O}$ (where $A=\\operatorname{Li}$ , Na, or K), have colossal dielectric constants10 and superionic conductivities11. To the best of our knowledge, this class of entropy-stabilized oxides and its derivatives represent the first and only crystalline high-entropy ceramics that have been reported to date. \n\nThis study further extended the state of the art for the crystalline high-entropy ceramics via successfully synthesizing a new class of high-entropy metal diborides, including $(\\mathrm{Hf_{0.2}}\\mathrm{Zr_{0.2}T a_{0.2}N b_{0.2}T i_{0.2}})\\mathrm{B}_{2}.$ $(\\mathrm{Hf}_{0.2}\\mathrm{Zr}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Mo}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2}.$ $(\\mathrm{Hf}_{0.2}\\mathrm{Zr}_{0.2}\\bar{\\mathrm{Mo}}_{0.2}\\mathrm{Nb}_{0.2}\\bar{\\mathrm{Ti}}_{0.2})\\mathrm{B}_{2},$ $(\\mathrm{Hf_{0.2}M o_{0.2}T a_{0.2}N b_{0.2}T i_{0.2}})\\mathrm{B}_{2}.$ $(\\mathrm{Mo_{0.2}Z r_{0.2}T a_{0.2}N b_{0.2}T i_{0.2}})$ $\\mathbf{B}_{2},$ and $(\\mathrm{Hf_{0.2}}\\mathrm{Zr_{0.2}T a_{0.2}C r_{0.2}T i_{0.2}})\\mathrm{B}_{2}$ (Table 1). This work has greatly extended the knowledge of high-entropy materials, not only since it is the first time crystalline high-entropy non-oxide ceramics (specifically borides) have been synthesized, but also because these high-entropy metal diborides exhibit a unique layered hexagonal crystal structure with alternating rigid two-dimensional (2D) boron nets and high-entropy $2D$ layers of metal cations (as essentially a class of quasi-2D high-entropy materials), as schematically shown in Fig. 1, which distinctly differs from any other high-entropy crystalline phases reported to date. \n\n# Results \n\nPhase Evolution and Formation of High-Entropy Ceramic Phases.  To synthesize high-entropy metal diborides, five commercial metal diboride powders of equimolar amounts were mixed and mechanically alloyed via high energy ball milling (HEBM) for six hours; subsequently, the HEBM powders were compacted into disks of $20\\mathrm{-mm}$ diameter and densified utilizing spark plasmas sintering (SPS) at $2000^{\\circ}\\mathrm{C}$ for 5 minutes under a pressure of $30\\mathrm{MPa}$ . The detailed synthesis procedure was described in the “Methods” section. Seven high-entropy metal diboride compositions were tested in this study, which are sometimes referred as HEB $\\#1\\#7$ (as listed in Table 1 and Supplementary Table S-I. Representative X-ray diffraction (XRD) patterns shown in Fig. 2 and Supplementary Figs S1–S7 illustrate the phase evolution during the HEBM and SPS fabrication process. The initial mixture of powder displayed XRD peaks for five individual metal diboride phases (although some peaks overlap for most compositions), which broadened and merged (due to the particle size reduction and mechanical alloying effects during HEBM); eventually, a single, high-entropy, phase of the hexagonal ${\\mathrm{AlB}}_{2}$ structure formed after SPS at $2000^{\\circ}\\mathrm{C}$ (Fig. 2; Supplementary Figs S1–S7). Full-range XRD patterns of the SPS specimens are displayed in Fig. 3 (and in expanded views in Supplementary Figs S1–S7), where six of them, i.e., $(\\mathrm{Hf_{0.2}}\\mathrm{Zr_{0.2}T a_{0.2}N b_{0.2}T i_{0.2}})\\mathrm{B}_{2}.$ , $\\begin{array}{r}{(\\mathrm{Hf}_{0.2}\\mathrm{Zr}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Mo}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2},}\\end{array}$ $(\\mathrm{Hf_{0.2}}Z\\mathrm{r_{0.2}M o_{0.2}N b_{0.2}T i_{0.2}})\\mathrm{B}_{2}.$ , $(\\mathrm{Hf_{0.2}M o_{0.2}T a_{0.2}N b_{0.2}T i_{0.2}})\\mathrm{B}_{2}.$ $(\\mathrm{Mo_{0.2}Z r_{0.2}T a_{0.2}N b_{0.2}T i_{0.2}})\\mathrm{B}_{2}$ , and $\\begin{array}{r}{(\\mathrm{Hf}_{0.2}\\mathrm{Zr}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Cr}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2},}\\end{array}$ exhibit largely a single hexagonal phase, albeit the presence of minor secondary $(\\mathrm{Zr},\\mathrm{Hf}){\\mathrm{O}}_{2}$ phases; these secondary oxide phases are represented by the low-intensity peaks that are evident in Figs 2 and 3, which are not indexed in Figs 2 and 3 for the figure clarity, but indicated by the solid dots in Supplementary Figs S1–S7. The formation of minor amounts of secondary oxide $(\\mathrm{ZrO}_{2}$ or $\\mathrm{HfO}_{2},$ ) phases is commonly observed in sintered $\\mathrm{ZrB}_{2}$ and $\\mathrm{HfB}_{2}$ specimens, which are native oxides that are difficult to remove (because of the extreme stabilities of native oxides of $\\mathrm{ZrO}_{2}$ and $\\mathrm{HfO}_{2},$ . As the only special case, a secondary boride phase was observed in HEB $\\#6$ , $\\begin{array}{r}{(\\mathrm{Hf}_{0.2}Z\\mathrm{r}_{0.2}\\mathrm{W}_{0.2}\\mathrm{M}\\mathbf{o}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2},}\\end{array}$ with XRD peaks matching those of the $(\\mathrm{Ti}_{1.6}\\mathrm{W}_{2.4})\\mathrm{B}_{4}$ compound, while the major XRD peaks still represent a hexagonal metal diboride solid-solution phase (Fig. 3 and Supplementary Fig. S6). \n\n![](images/a0145549c7c7e4829f49691ae9942eb986ef79844fdfbe951183a7c7ad09e892.jpg) \nFigure 2.  XRD patterns showing the phase evolution during the HEBM and SPS fabrication processes in (a) HEB $\\#2$ as an examplar in an expanded scale and (b) six other specimens. Only the first three peaks of the high-entropy hexagonal ${\\mathrm{AlB}}_{2}$ phases are shown here for figure clarity; full-range XRD patterns (of $2\\time20^{\\circ}-100^{\\circ}$ , showing eleven XRD peaks of the high-entropy hexagonal phases) are documented in the Supplementary Figs S1–S7. \n\n![](images/11ba8154d29a013e1c3d2f8e29ae0774b17c1e9d4b1d3ee680597433511e4fcc.jpg) \nFigure 3.  XRD patterns of all seven specimens after SPS at $2{\\bf000}^{\\circ}{\\bf C},$ where the peaks of the primary hexagonal phase are indexed. Six of seven specimens (except for HEB $\\#6$ ) exhibit largely a single hexagonal phase of the $\\mathrm{AlB}_{2}$ structure, albeit the presence of minor secondary $(\\mathrm{Zr},\\mathrm{Hf}){\\mathrm O}_{2}$ (native oxides), which are represented by the low-intensity peaks that are not indexed here the figure clarity (but indicated by the solid dots in Supplementary Figs S1–S7). As the only special case, a secondary boride phase was observed in HEB $\\#6$ , with XRD peaks matching those of the $(\\mathrm{Ti}_{1.6}^{\\cdot}\\bar{\\mathsf{W}}_{2.4})\\mathbf{B}_{4}$ compound, while the major XRD peaks still represent a hexagonal metal diboride solid-solution phase. \n\nCompositional Uniformity.  Cross-sectional scanning electron microscopy (SEM) images and the corresponding energy dispersive X-ray (EDX) spectroscopy compositional maps of three selected specimens (after \n\n![](images/145ba5b7ce9c1a5055bc9625b01a79f21d779c503f92a7eae528b4c9f2750142.jpg) \nFigure 4.  Cross-sectional SEM image and the corresponding EDX compositional maps of three selected specimens after SPS, showing the formation of largely homogeneous high-entropy solid-solution phases except for the HEB $\\#6$ shown in (c). The compositions are largely uniform albeit the presence of minor $(\\mathrm{Zr},\\mathrm{Hf}){\\mathrm{O}}_{2}$ based native oxides, e.g., in (a), and some Nb clustering in four Nb-containing specimens, e.g., in (b). The formation of a secondary boride phase was observed only in $\\mathrm{HEB}\\#6 $ as shown in (c). Additional EDX compositional maps (in expanded views) of all seven specimens are documented in the Supplementary Figs S1–S7. \n\nSPS at $2000^{\\circ}\\mathrm{C}$ ) are shown in Fig. 4 (additional EDX compositional maps of all seven specimens are documented in the Supplementary Figs S1–S7). The compositions of all specimens are largely uniform, albeit the presence of uniformly-distributed minor secondary $(\\mathrm{Zr},\\mathrm{Hf})\\mathrm{O}_{2}$ phases (to different extents in different specimens), as well as the $(\\mathrm{Ti}_{1.6}\\mathrm{W}_{2.4})\\mathrm{B}_{4}$ secondary phase in HEB $\\#6$ (only). Less than 1 at. $\\%$ W (tungsten) is present in Specimens $\\#1\\#5$ and $\\#7$ as contamination from the WC-based milling media used in HEBM. EDX mapping operating at $20\\mathrm{kV}$ also found micrometer-scale Nb (niobium) localization in Specimens #1 and $\\#3\\substack{-\\#5}$ , with occasional Zr and Mo clustering occurring concurrently in the same regions. This is somewhat surprising considering the fact that $\\mathrm{Nb}{\\tt B}_{2}$ generally forms continuous solid solutions with other metal diborides12. Presumably, the Nb localization is due to kinetic effects and can be homogenized with annealing for a prolonged time or at higher temperatures. In general, the compositional homogeneities are largely satisfactory, as shown in Fig. 4 (and in expanded views in Supplementary Figs S1–S7 for all seven specimens); they are significantly more homogenous than the typical (BCC) refractory HEAs made by casting, which usually form dendrite structures with severe compositional segregations7. \n\nAtomic-Resolution Structural Characterization.  AC STEM HAADF and ABF imaging has been conducted to confirm the formation of uniform solid solution at nanometer and atomic scales, particularly the formation 2-D high-entropy metal layers (separated by the rigid 2-D boron nets in the (0001) basal planes) without any significant layer-to-layer variation (or layered segregation) of different metal atoms in different (0001) planes perpendicular to the $\\boldsymbol{\\mathscr{c}}$ -axis. The STEM-ABF and STEM-HAADF images in Fig. 5(a) and (b) show a homogeneous solid solution phase in the $\\mathrm{HEB}\\#2$ , $(\\mathrm{Hf_{0.2}}\\mathrm{Zr_{0.2}T i_{0.2}M o_{0.2}T a_{0.2}})\\mathrm{B}_{2}$ . STEM ABF and HAADF images with higher magnification showed the atomic configuration of atoms in the view of[0110] zone axis. The atomic planes (0001) and (0110) were indicated in Fig. 5(c). The mean spacing between two (0001) planes is about $3.449\\mathring\\mathrm{A}$ , which is close to $3.{\\overset{\\cdot}{3}}16{\\overset{\\cdot}{\\mathrm{A}}}$ measured by XRD. In Fig. 5(c), the metallic atoms were highlighted by red circles on (0001) plane. Light element B can be visualized via ABF imaging. The highlighted green dots in Fig. 5(c) indicated the B atoms, which are located between two basal planes (0001). The observed atomic configuration is consistent with the unit cell model depicted in Fig. 1. The same atomic configuration and homogeneity were also observed in different locations (Figs S8 and S9) and a different specimen (Fig. S10). A careful digital image analysis (Fig. S11) revealed that the measured standard deviations of lattice spacings between the basal (0001) planes are only ${\\sim}0.6\\%$ of the average measured $\\boldsymbol{\\mathscr{c}}$ lattice parameter or the measured variations from STEM ABF and HAADF images are ${\\sim}0.02\\mathrm{\\bar{A}}$ , which directly confirmed the formation 2-D high-entropy metal layers without a layered segregation of different metal specimens in different (0001) basal planes, where these 2-D metal layers are well separated by the rigid 2-D boron nets in between (Fig. 1). Thus, these high-entropy metal diborides can be considered as (layered) quasi-2D high-entropy materials, as schematically illustrated in Fig. 1. \n\nNanoscale Compositional Mapping.  The compositional homogeneity at nanoscale for the HEB $\\#2$ , $\\begin{array}{r l}{\\lefteqn{(\\mathrm{Hf}_{0.2}Z\\mathbf{r}_{0.2}\\mathrm{Ti}_{0.2}\\mathrm{Mo}_{0.2}\\mathrm{Ta}_{0.2})\\mathbf{B}_{2}.}\\end{array}$ , was confirmed by EDX maps for different metallic elements. Figure 6 showed that Hf, Zr, Ta, Mo and Ti were uniformly distributed at nanoscale. No segregation or aggregation was found throughout the scanned area. Since these compositional maps were also taken with the electron beam being parallel to the [0110] zone axis, they also confirmed no layered segregation along the $\\boldsymbol{c}$ -axis in (0001) basal planes; thus, this is indeed a quasi-2D high-entropy material as illustrated in Fig. 1. Additional EDX mapping at a different location was also conducted and documented in Fig. S11. \n\n![](images/f46c7083520e0e877a371a28eae4c8c724d2040c5d807da7eb8ad5260c570e23.jpg) \nFigure 5.  Atomic-resolution STEM ABF and HAADF images of HEB $\\#2$ $(\\mathbf{Hf_{0.2}}\\mathbf{Zr_{0.2}}\\mathbf{Ta_{0.2}M o_{0.2}T i_{0.2}})\\mathbf{B}_{2}$ . (a) and (b): ABF and HAADF images at a low magnification, showing the homogeneity of the solid-solution phase. (c) and (d): ABF and HAADF images at a higher magnification, showing atomic configuration. The electron beam is parallel to the[01 0] zone axis of hexagonal structure. (0001) and (01 ) planes are indexed in (c). The red circles highlight the columns of transition metal atoms (Hf, Zr, Ta, Mo and Ti). The green dots indicate the B atoms. Additional STEM images from different regions and a different specimen are documented in the Supplementary Figs S8–S10; a further digital analysis of HAADF and ABF images in Supplementary Fig. S11 shows that the standard variations in the (0001) lattice spacings are only ${\\sim}0.6\\%$ or ${\\sim}0.0\\dot{2}\\dot{\\mathrm{A}}$ , indicating homogenous mixing of five metal atoms (Hf, Zr, Ta, Mo and Ti) within the 2-D metal layers in (0001) planes. \n\nDensification and Lattice Parameters.  In general, greater than $92\\%$ of theoretical densities has been achieved by SPS at $2000^{\\circ}\\mathrm{C}$ (Table 1; see Supplementary Table S-I for the actual measured densities, along with the theoretical densities calculated using the lattice parameters measured by XRD). The lattice parameters were measured from XRD and listed in Table 1. Typically, the measured lattice parameters are within $<1\\%$ of those calculated by the rule of mixtures (Table 1), which, along with the narrow XRD peaks (where the peak widths are much narrower than the mean differences among the five peaks of individual metal diborides, as shown in Fig. 2 and Supplementary Figs S1–S7), indicates the formation of disordered solid solutions for all high-entropy metal diborides made in this study (consistent with the direct STEM HAADF/ABF imaging and nanoscale compositional mapping as shown in Figs 5 and 6). \n\nHardness and Oxidation Resistance.  Initial property assessments indicated that both the hardness and the oxidation resistance of these high-entropy metal diborides are generally greater or better than the average performances of the individual (conventional) metal diborides made by the identical HEBM and SPS fabrication processing. We understand that both hardness and oxidation resistance should critically depend on microstructures; the presence of porosity and oxide inclusion, as a consequence of the HEBM procedure that we adopted for promoting the homogenization of high-entropy solid solutions, adversely affected the hardness and oxidation resistance. To conduct a fair assessment of the relative performance of high-entropy and conventional metal diborides, we measured six single-phase high-entropy diborides, along with a controlled group of $\\mathrm{HfB}_{2}$ , $\\mathrm{ZrB}_{2}$ , $\\begin{array}{r}{\\mathrm{{TaB}}_{2},}\\end{array}$ $\\mathrm{Nb}{\\tt B}_{2}$ , $\\mathrm{TiB}_{2},$ and $\\mathrm{CrB}_{2}$ specimens made by the identical HEBM and SPS fabrication processing using the same processing parameters (except for $\\mathrm{CrB}_{2}$ ; see “Methods” section for explanation). Figure 7 displays the measured hardness of six high-entropy metal diborides (with the actual measured data being listed in Supplementary Table S-III), which are generally greater than the averages of the hardness values measured from individual metal diborides fabricated via the same route. Because $\\mathrm{MoB}_{2}$ is not an equilibrium bulk phase below $1500^{\\circ}\\mathrm{C}$ , the averages for HEB#2-HEB#5 that contains $20\\%$ $\\mathrm{MoB}_{2}$ were calculated without $\\mathrm{MoB}_{2}$ . Yet, it is well established that $\\mathrm{MoB}_{2}$ has a lower melting temperature and theoretical hardness than all the other metal diborides in HEB#2-HEB#5 $\\left(\\mathrm{HfB}_{2};\\right.$ $\\mathrm{ZrB}_{2}$ , $\\mathrm{TaB}_{2}$ , $\\mathrm{Nb}\\mathbf{\\bar{B}}_{2}$ , and $\\mathrm{TiB}_{2}$ ) so that the actual averages from the “rule of mixtures,” if we could make and measure $\\mathrm{MoB}_{2}$ via the same procedure, should be even lower. Furthermore, results from an initial oxidation resistance measurement of these high-entropy and individual metal diborides made by the identical fabrication processing are shown in Fig. 8, with additional data and images documented in Supplementary S13–S15. Taking $\\mathrm{HEB}\\#1$ $(\\mathrm{Hf_{0.2}}\\mathrm{Zr_{0.2}T a_{0.2}N\\bar{b}_{0.2}T i_{0.2}})\\mathrm{B}_{2}$ as an example (which is a good case for considering because none of its oxides is volatile in this temperature range so that the weight gains shown in Fig. 8 and Fig. S13 are easier to interpret), Figs 8, S13 and S14 show that $\\mathrm{HEB}\\#1$ performs better than most of its individual components made with the same procedure $(\\mathrm{ZrB}_{2},\\mathrm{TaB}_{2},\\mathrm{NbB}_{2}$ , and $\\mathrm{TiB}_{2}^{\\cdot}$ ) except for $\\mathrm{HfB}_{2}$ ; it certainly performs better than the “average” performance of these five individual metal diborides. Consistently, both HEB $\\#1$ and HEB $\\#7$ maintained their shapes even at $1500^{\\circ}\\mathrm{C},$ while the majority of the respective individual metal diborides (except for $\\mathrm{HfB}_{2}$ ) that were fabricated via the same HEBM and SPS route oxidized more severely. For example, the $\\mathrm{TiB}_{2}$ specimen, which represents one most widely-used metal diboride today, pulverized completely at $1500^{\\circ}\\mathrm{C}$ (Supplementary Fig. S14). Finally, the four $\\mathrm{MoB}_{2}$ -containing high-entropy diborides (HEB#2-HEB#5) exhibited interesting and diverse, oxidation behaviors because $\\mathbf{MoO}_{3}$ is volatile. Despite this, some of them still perform better than many conventional metal diborides that do not have volatile native oxides (Figs S13 and S15). \n\n![](images/de9cb8ad74d4cb70755bf4825492949499344f0018c3c00295a17c402fe1d328.jpg) \nFigure 6.  STEM-HAADF image and the corresponding EDS compositional maps for HEB #2 $\\begin{array}{r l}{{\\bf(\\bar{H f}_{0.2}Z r_{0.2}T a_{0.2}M o_{0.2}T i_{0.2})B}_{2}}&{{}}\\end{array}$ showing the homogeneous chemical distribution at nanoscale. These compositional maps were taken when the electron beam is parallel to the[01 0] zone axis, showing no significant layer-to-layer variations of metal composition in different basal (0001) planes. Additional EDX compositional maps obtained from a different region are documented in the Supplementary Fig. S12. \n\n![](images/bc7c77f6abebe75282ec628116eb8238c1a860b260ff6768e762a5616cae384b.jpg) \nFigure 7.  Measured hardness of six single-phase high-entropy metal diborides, which are generally greater than the “rule-of-mixtures” averages of the hardness values measured from individual metal diborides that were fabricated via the same HEBM and SPS route. Since $\\mathrm{MoB}_{2}$ is not an equilibrium bulk phase below $1500^{\\circ}\\mathrm{C}$ , the averages for HEB#2-HEB#5 were calculated without $\\mathrm{MoB}_{2}$ . However, $\\mathrm{MoB}_{2}$ has a lower melting temperature and theoretical hardness than all other five other metal diborides in question; thus, the actual rule-of-mixtures averages should be even lower. It is also important to note that the hardness can be affected by porosity and oxide inclusions so that fully-dense and oxide-free metal diborides should have greater hardness than these measured values. We choose to compare the measured hardness values of high-entropy and conventional metal diborides fabricated by the same method to allow a fair assessment of relative values. \n\n# Discussion \n\nThe formation of (metallic) HEAs are often predicted by using the atomic-size effect $(\\delta)$ and the enthalpy of mixing $(\\Delta H_{\\mathrm{mix}})$ as the two main criteria1,2. The enthalpy of mixing is difficult to quantify for the current case, so attention is focused on analyzing the atomic-size effect. The original Hume-Rothery solid-solution rule suggests that $(r_{\\mathrm{solute}}-r_{\\mathrm{solvent}})/r_{\\mathrm{solvent}}\\leq15\\%$ is one of the necessary conditions for forming a binary solid solution. Following the same concept, the average atomic-size difference $(\\delta)$ can be defined for a multicomponent HEA alloy1,2, as: \n\n$$\n\\delta\\equiv\\sqrt{\\sum_{i=1}^{N}X_{i}\\Bigg[1-r_{i}/\\Bigg(\\sum_{i=1}^{N}X_{i}r_{i}\\Bigg)\\Bigg]^{2}}\n$$ \n\n![](images/5542721474062c062637d57b5d6627a645a3d35004e350fe6e9ebc94e604b8e3.jpg) \nFigure 8.  A snapshot of the relative oxidation performance of various high-entropy and individual metal diborides fabricated and tested with the same conditions. This figure displays percentage weight gain vs. oxidation temperature curves during annealing in flowing dry air at $1000^{\\circ}\\mathrm{C},$ , $1100^{\\circ}\\mathrm{C},$ and $1200^{\\circ}\\mathrm{C}$ (for one hour each) sequentially for six single-phase high-entropy metal diborides [HEB $\\#1=(\\mathrm{Hf}_{0.2}Z\\mathrm{r}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Nb}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2},$ HEB $\\#2=(\\mathrm{Hf}_{0.2}\\mathrm{Zr}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Mo}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2}$ , $\\mathrm{HEB\\#3}=(\\mathrm{Hf}_{0.2}Z\\mathrm{r}_{0.2}\\mathrm{Mo}_{0.2}\\mathrm{Nb}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2},$ $\\mathrm{IEB\\#4}=(\\mathrm{Hf}_{0.2}\\mathrm{Mo}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Nb}_{0.2}\\mathrm{Ti}_{0.2})$ $\\mathbf{B}_{2}$ , H $:\\mathrm{B}\\#5=(\\mathrm{Mo}_{0.2}\\mathrm{Zr}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Nb}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2}$ , and HEB $\\#7=(\\mathrm{Hf}_{0.2}Z\\mathrm{r}_{0.2}\\mathrm{Ta}_{0.2}\\mathrm{Cr}_{0.2}\\mathrm{Ti}_{0.2})\\mathrm{B}_{2}],$ along with six individual metal diborides fabricated via the same HEBM and SPS route. See the “Methods” section for the experimental procedure and Supplementary Figs S13–S15 for additional results, including weight gain per surface area plots, weight percentage gains at higher temperatures, and images of all specimens after oxidation at different temperatures. In this figure (and Supplementary Fig. S13), solid lines represent the high-entropy metal diborides and dashed lines represent the individual (conventional) metal diborides made by the same fabrication route. \n\nwhere $r_{\\mathrm{i}}$ and $X_{\\mathrm{i}}$ are the atomic radius and molar content, respectively, of the $i$ -th component. Prior studies suggested, mostly based on empirical observations, that a necessary (but not sufficient) criterion for forming a single-phase (disordered) HEA is that the computed $\\delta$ of the solid solution should be sufficiently small: $\\delta\\le\\delta_{\\mathrm{max}}\\approx4\\%^{1}$ or $4.3\\%^{2}$ . By simply plugging the values of metallic or covalent radii of the metals, and the computed $\\delta$ values are in the range of $3.5\\%$ to ${\\sim}8\\%$ (Table S-I in the Supplementary Material); specifically, HEB $\\#7$ has the highest $\\delta\\approx8\\%$ ; yet, it still forms single-phase, high-entropy, solid solution. In reality, metal diborides $[\\mathbf{M}^{2+}(\\mathbf{B}^{-})_{2}]$ form a highly anisotropic layered structure (i.e., the hexagonal ${\\mathrm{AlB}}_{2}$ structure13), where each metal atom donates two electrons and the M-B bonds (between the metal and B layers) have mixed ionic and covalent characteristics (see Fig. 1). Within the 2D metal layers, M-M bonds are strained significantly by the more rigid boron net (Fig. 1). Thus, none of the available (metallic, covalent or ionic) radii can effectively represent the actual bond lengths in the metal diborides in the ${\\mathrm{AlB}}_{2}$ structure (Fig. 1)13. \n\nAlternatively, we propose to calculate the average size difference for a high-entropy metal diboride using the lattice constants of individual metal diborides (measured lattice parameters $a_{\\mathrm{i}}$ and $c_{\\mathrm{i}}$ for the $i$ -th $\\begin{array}{r}{\\mathbf{M}\\mathbf{B}_{2},}\\end{array}$ as summarized in ref. 14, instead of the atomic radii of metals), as: \n\n$$\n\\delta_{a}=\\sqrt{\\sum_{i=1}^{N}X_{i}\\biggl[1-a_{i}\\biggl/\\sum_{i=1}^{N}X_{i}a_{i}\\biggr]\\biggr]^{2}}\n$$ \n\nand \n\n$$\n\\delta_{c}=\\sqrt{\\sum_{i=1}^{N}X_{i}\\bigg[1-c_{i}/\\Bigg(\\sum_{i=1}^{N}X_{i}c_{i}\\Bigg)\\bigg]^{2}}\n$$ \n\nSubsequently, the values of $\\delta_{a}$ and $\\delta_{c}$ have been computed for the seven specimens and listed in Table 1 and Supplementary Table S-I. Interestingly, the computed $\\delta_{a}$ values are small (in the range of $1.3\\%$ to $2.3\\%$ for all seven specimens) because the M-M bonds are strained by the rigid boron net (that can deform metal cations and M-M bond lengths towards an ideal “strain-free” value dictated by stronger B-B bonds13; Fig. 1). Thus, the computed $\\delta_{c}$ values may better represent the average size difference because of less constraint along the $c$ -axis. Coincidentally, Specimens $\\#1\\#5$ and $\\#7$ , for which single-phase, high-entropy, solid solutions did form, all have computed $\\delta_{c}$ values in the range of $3.9\\%$ to $5.2\\%$ , whereas HEB $\\#6$ , for which single-phase did not form, has the largest computed $\\delta_{c}$ value of ${\\sim}6.2\\%$ . It is interesting to further note that HEB $\\#7$ (with a simple high-entropy phase) has a greater $\\delta_{a}$ but smaller $\\delta_{c}$ than those of HEB $\\#6$ (with two boride phases), suggesting that a smaller $\\delta_{c}$ may be more important than a smaller $\\delta_{a}$ . \n\nHowever, we should emphasize that small differences in lattice parameters (measured by small $\\delta_{a}$ and $\\delta_{c,}$ ) are only one necessary, but not essential, condition for forming high-entropy solutions. A very small $\\delta$ value is certainly not a guarantee for forming a single-phase, high-entropy, solid solution. For example, the precipitation of the secondary $(\\mathrm{Ti}_{1.6}\\mathrm{W}_{2.4})\\mathrm{B}_{4}$ phase in HEB $\\#6$ may be related to the facts that this $(\\mathrm{Ti}_{1.6}\\mathrm{W}_{1.4})\\mathrm{B}_{4}$ phase is extremely stable or $\\mathrm{WB}_{2}$ is not stable by itself; further investigation is needed here to clarify the most important reason for the precipitation of $(\\mathrm{Ti}_{1.6}\\mathrm{W}_{2.4})\\mathrm{B}_{4}$ in HEB $\\#6$ . \n\nMoreover, the average size differences are certainly not the only factors that determine the ability to form a single high-entropy phase. For example, it is known13 that an average lattice parameter $a$ of ${\\sim}3.04\\mathring\\mathrm{A}$ would produce “strain-free” metal layers that match the rigid boron net, thereby being favored; this may also be a factor for HEB $\\#7$ to exhibit single high-entropy phase since its average $a$ (of ${\\bf\\tilde{\\Omega}}{\\bf\\Delta}{\\bf\\tilde{\\Omega}}^{3.081\\tilde{\\mathrm{A}}},$ has the closest match to the ideal strain-free value (Supplementary Table S-I; despite that this factor also favors HEB $\\#6$ , where the largest $\\delta_{c}$ may be a determining factor). In addition to the several size factors discussed above, the mixing enthalpy, as well as the valence electron concentration, may also play an important role in determining whether a single high-entropy phase forms1,2. \n\nIt is worth making a few additional notes regarding the observed phase stabilities. First, perhaps the most interesting observation is the formation of a single-phase, high-entropy solution in HEB $\\#7$ , $(\\mathrm{Hf_{0.2}}\\mathrm{Zr_{0.2}T i_{0.2}C r_{0.2}T a_{0.2}})$ $\\mathbf{B}_{2}.$ despite the limited solid solubilities of $\\mathrm{CrB}_{2}$ in both $\\mathrm{\\dot{H}f B}_{2}$ and $\\bar{\\mathrm{ZrB}}_{2}^{12,15}$ . Second, $\\mathrm{MoB}_{2}$ is believed to be metastable at room temperature, but the hexagonal $\\mathrm{MoB}_{2}$ phase could be retained in the SPS specimens16; in this study, four $20\\%$ -Mo-containing high-entropy metal diborides have been made. Third, the starting powder ${\\bf W}_{2}{\\bf B}_{5}$ (since $\\mathrm{WB}_{2}$ is not commercially available) possessed a different structure and it has limited solubilities in all diborides except for $\\mathrm{TiB}_{2}^{17-19}$ , which can be another reason that HEB $\\#6$ did not possess a single solid-solution phase (in addition to the largest $\\delta_{c}$ of ${\\sim}6.2\\%$ ). \n\nIt is important to emphasize that both the hardness and oxidation resistance can be affected by the microstructure, e.g., the porosity and oxide inclusions, significantly. Thus, we choose to compare the high-entropy and individual metal diborides fabricated using the same method to allow a fair assessment of relative hardness and oxidation resistance (even if our specimens have high levels of porosity and oxidation inclusions due to HEBM than those fully-dense and oxide-free specimens prepared by other fabrication routes). We expect that fully-dense and oxide-free specimens should have higher hardness and better oxidation resistance. \n\nAlthough the high-entropy metal diborides do appear to exhibit greater hardness and better oxidization resistance than the average performances of the individual metal diborides (provided that they are made with the same fabrication route), perhaps a more important advantage for adopting high-entropy materials is a large compositional design space to allow tuning of properties. This will be particularly important for improving oxidation resistance, which depends on many (often kinetic) factors; thus, there is perhaps no simple answer on whether high-entropy metal diborides are good or bad for oxidation resistance (and some other properties). A large compositional design space is useful for designing better protective oxide scales (with additives or in composites, which are often necessary for real applications), representing a complex material engineering problem beyond the scope of this study. Further systematic investigation of hardness, oxidation resistance, and other properties of the high-entropy metal diborides, which often critically depend on the microstructure and therefore the processing optimization, is important but beyond the scope of this study that focuses on the formation, structure, microstructure, and thermodynamic stability of this new class of high-entropy materials. \n\nIn summary, this study has successfully synthesized six single-phase, high-entropy, metal diborides via mechanical alloying and SPS. In general, metal diboride-based UHTCs have ultrahigh melting points, as well as excellent thermal and electrical conductivities, hardness, and wear and oxidation resistances13,15,20–23; thus, they have potential structural applications in extreme environments. In addition, with a unique, layered hexagonal $(\\mathrm{AlB}_{2}),$ ) crystal structure, with alternating metal and boron layers, some metal diborides also exhibit exotic functionality, e.g., $\\mathrm{MgB}_{2}$ is a well-known superconductor. While extensive future research has to be conducted to investigate their mechanical, chemical (oxidation), and physical properties, these high-entropy metal diborides represent a new class of UHTCs, as well as a new type of high-entropy materials that can have unique compositions and structures that differ distinctly from any other existing materials, as well as great possibilities of tailoring their properties via an extremely-large compositional engineering space. \n\n# Methods \n\nSynthesis of High-Entropy Metal Diboride Specimens.  To synthesize high-entropy metal diborides, powders of $\\mathrm{HfB}_{2}$ , $\\mathrm{ZrB}_{2}$ , $\\mathrm{Nb}{\\bf B}_{2}$ , $\\mathrm{TiB}_{2}$ , ${\\bf W}_{2}{\\bf B}_{5}$ (to substitute $\\mathrm{WB}_{2}$ that is not commercially available), $\\mathrm{CrB}_{2}$ ( $99.5\\%$ purity; purchased from Alfa Aesar, MA, USA), $\\mathrm{TaB}_{2}.$ and $\\mathrm{MoB}_{2}$ $99\\%$ purity; purchased from Goodfellow, PA, USA) were utilized as starting materials. Appropriate amounts of five powders were utilized to fabricate specimens of each composition (with the stoichiometry being calculated on the metal basis). The seven compositions are listed in Table 1 and referred to as HEB $\\#1$ to $\\#7$ in the text. The raw powders were mechanically alloyed via high energy ball milling (HEBM) using a Spex 8000D mill (SpexCertPrep, NJ, USA) for six hours in WC media. To prevent overheating, the HEBM was stopped every 60 minutes to allow cooling for five minutes. The powders were then hand ground in an agate mortar to a 325 mesh; subsequently, they were compacted into disks of $20\\mathrm{-mm}$ diameter and densified utilizing spark plasma sintering (SPS, Thermal Technologies, CA, USA) in vacuum $(10^{-2}$ Torr) at $2000^{\\circ}\\mathrm{C}$ for 5 minutes under a pressure of $30\\mathrm{MPa}$ , with a heating ramp rate of $100^{\\circ}\\mathrm{C}/\\mathrm{min}$ . The inside of the graphite die was lined with a $25\\upmu\\mathrm{m}$ -thick molybdenum foil to prevent reactions between the graphite and the diboride specimen. The molybdenum foil was then lined with a layer of $125\\upmu\\mathrm{m}$ -thick graphite paper to minimize reactions between the foil and the outer die. \n\nCharacterization.  The specimens were characterized by X-ray diffraction (XRD) using a Rigaku diffractometer with Cu $\\operatorname{Ka}$ ​radiation and scanning electron microscopy (SEM) in conjunction with energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDX). The specimen densities were measured via the Archimedes method to an accuracy of $\\pm0.0\\mathrm{{ig/cm^{2}}}$ and the relative densities were calculated via using theoretical densities that were determined by the ideal stoichiometry and lattice parameters measured by XRD. The atomic and nanoscale characterization was conducted using aberration-corrected scanning transmission electron microscopy (AC STEM); STEM high-angle annular dark-field (HAADF) images, medium-angle annular dark-field (MAADF), and annular bright-field (ABF) images were taken by using a $200\\mathrm{kV}$ STEM (ARM-200F, JEOL) equipped with a probe Cs corrector (CEOS Gmbh), which offers an unprecedented opportunity to probe structures with a sub-Ångström resolution. For HAADF imaging, we adopted a probe convergence angle of ${\\sim}22$ mrad and a detector with inner semi-angle of ${>}60$ mrad. The ABF images were taken with a detector of 12–23 mrad, while MAADF images were taken with a detector of 23–50 mrad. The energy dispersion X-ray (EDX) spectroscopy was employed to map the chemical composition at nanoscale. The TEM samples were prepared by dual-beam FIB/SEM system (Scios, FEI). \n\nHardness and Oxidation Measurements.  Hardness and oxidation measurements were conducted using all six single-phase high-entropy diborides (HEB $\\#1\\#5$ and $\\#7$ ) and six individual metal diboride benchmarking specimens $\\left(\\mathrm{HfB}_{2}\\right.$ , $\\mathrm{ZrB}_{2}$ , $\\mathrm{TaB}_{2}$ , $\\mathrm{Nb}{\\tt B}_{2}$ , $\\mathrm{TiB}_{2}$ , and $\\mathrm{CrB}_{2}$ ) that were made by the same HEBM and SPS fabrication method using the same processing parameters, with one exception that $\\mathrm{CrB}_{2}$ was sintered at lower temperature of $1800^{\\circ}\\mathrm{C}$ because its substantially lower melting (and therefore sintering) temperature. $\\mathrm{MoB}_{2}$ was not examined because it is not a thermodynamically stable phase (and will decompose to MoB and ${\\bf M o}_{2}{\\bf B}_{5}$ ) below $1500^{\\circ}\\mathrm{C}$ . Hardness measurements were performed with a Vickers’ diamond indenter at $200\\mathrm{kgf}/\\mathrm{mm}^{2}$ with a hold time of 15 seconds. The indentations were examined for conformation with the ASTM C1327. The indentations averaged $20{-}25\\upmu\\mathrm{m}$ in width during the testing. Multiple measurements were performed at different locations of each specimen; the mean and standard deviation are reported. The density and hardness are generally uniform at different locations for HEB specimens $\\#1\\#5$ and all six individual metal diboride specimens; however, HEB $\\#7$ has a denser outside shell and less dense inner core with different average hardness values (due to the effect of low-melting $\\mathrm{CrB}_{2}$ that promotes rapid densification near the surface); thus, the hardness values were measured at both regions and reported in Supplementary Table S-III but only the overall mean and standard deviation were used in comparison. The oxidation experiments were conducted in a tube furnace under flowing dry air. The specimens were annealed at $800^{\\circ}\\mathrm{C}_{:}$ , $900^{\\circ}\\mathrm{C}$ . $1000^{\\circ}\\mathrm{C},$ $1100^{\\circ}\\mathrm{C}$ , $1200^{\\circ}\\mathrm{C},$ $1300^{\\circ}\\mathrm{C}$ , $1400^{\\circ}\\mathrm{C},$ , and $1500^{\\circ}\\mathrm{C}$ sequentially. Each annealing step included a one-hour isothermal oxidation at the desired temperature with a heating ramp rate of $10^{\\circ}\\mathrm{C}/\\mathrm{min}$ ; after the isothermal annealing, the specimens were cooled in the furnace with uncontrolled cooling rates on the order of $100^{\\circ}\\mathrm{C}/\\mathrm{min}$ . After each annealing step, the specimens were removed from the furnace and weighted. At low annealing temperatures, specimens were weighted directly. At high temperatures (typically1 $300^{\\circ}\\mathrm{C}$ and above), many specimens reacted with the alumina crucibles so that the specimens were weighted in the crucibles to obtain the net weight gains/losses. We found the measured weights are generally accurate for the oxidization temperatures of $1000{-}1200^{\\circ}\\mathrm{C}$ (from direct weighting of specimens) and for the annealing temperatures of 1400 and $1500^{\\circ}\\mathrm{C},$ where the weight changes were sufficiently large to allow to be weighted accurately in crucibles. Outside these two temperature windows, the weight gains/losses were typically on the same order of magnitude as the measurement errors; thus, those data are not reported. \n\n# References \n\n1.\t Zhang, Y., Zuo, T. T., Tang, Z., Gao, M. C., Dahmen, K. A., Liaw, P. K. & Lu, Z. P. Microstructures and properties of high-entropy alloys. Prog. Mater. Sci. 61, 1–93 (2014). \n2.\t Tsai, M.-H. & Yeh, J.-W. High-Entropy Alloys: A Critical Review. Mater. Res. Lett. 2, 107–123 (2014). \n3.\t Gludovatz, B., Hohenwarter, A., Catoor, D., Chang, E. H., George, E. P. & Ritchie, R. O. A fracture-resistant high-entropy alloy for cryogenic applications. Science 345, 1153–1158 (2014). \n4.\t Poulia, A., Georgatis, E., Lekatou, A. & Karantzalis, A. Microstructure and wear behavior of a refractory high entropy alloy. Int. J. Refractory Met. Hard Mater. 57, 50–63 (2016). \n5.\t Fazakas, E., Zadorozhnyy, V., Varga, L., Inoue, A., Louzguine-Luzgin, D., Tian, F. & Vitos, L. Experimental and theoretical study of $\\mathrm{Ti}_{20}\\mathrm{Zr}_{20}\\mathrm{Hf}_{20}\\mathrm{Nb}_{20}\\mathrm{X}_{20}$ ( $\\mathbf{\\tilde{X}}=\\mathbf{\\tilde{V}}$ or $\\mathrm{Cr}$ ) refractory high-entropy alloys. Int. J. Refractory Met. Hard Mater. 47, 131–138 (2014). \n6.\t Senkov, O., Scott, J., Senkova, S., Miracle, D. & Woodward, C. Microstructure and room temperature properties of a high-entropy TaNbHfZrTi alloy. J. Alloys Compounds 509, 6043–6048 (2011). \n7.\t Gao, M., Carney, C., Doğan, Ö., Jablonksi, P., Hawk, J. & Alman, D. Design of Refractory High-Entropy Alloys. JOM 67, 2653–2669 (2015). \n8.\t Senkov, O. N., Wilks, G. B., Miracle, D. B., Chuang, C. P. & Liaw, P. K. Refractory high-entropy alloys. Intermetallics 18, 1758–1765 (2010). \n9.\t Rost, C. M., Sachet, E., Borman, T., Moballegh, A., Dickey, E. C., Hou, D., Jones, J. L., Curtarolo, S. & Maria, J.-P. Entropy-stabilized oxides. Nature Comm. 6, 8485 (2015). \n10.\t Bérardan, D., Franger, S., Dragoe, D., Meena, A. K. & Dragoe, N. Colossal dielectric constant in high entropy oxides. Phys. Status Solidi RRL 10, 328–333 (2016). \n11.\t Bérardan, D., Franger, S., Meena, A. & Dragoe, N. Room temperature lithium superionic conductivity in high entropy oxides. J. Mater. Chem. A 4, 9536–9541 (2016). \n12.\t Post, B., Glaser, F. W. & Moskowitz, D. Transition metal diborides. Acta Metall. 2, 20–25 (1954). \n13.\t Fahrenholtz, W. G., Hilmas, G. E., Talmy, I. G. & Zaykoski, J. A. Refractory diborides of zirconium and hafnium. J. Am. Ceram. Soc. 90, 1347–1364 (2007). \n14.\t Zhou, Y., Xiang, H., Feng, Z. & Li, Z. General Trends in Electronic Structure, Stability, Chemical Bonding and Mechanical Properties of Ultrahigh Temperature Ceramics TMB2 (TM $\\c=$ transition metal). J. Mater. Sci. Tech. 31, 285–294 (2015). \n15.\t Matkovich, V. I. Boron and Refractory Borides. (Springer Berlin Heidelberg, 1977). \n16.\t Klesnar, H., Aselage, T., Morosin, B. & Kwei, G. The diboride compounds of molybdenum: $\\mathbf{MoB}_{2-x}$ and $\\mathbf{Mo}_{2}\\mathbf{B}_{5-y}$ . J. Alloys Compounds 241, 180–186 (1996). \n17.\t Telle, R., Fendler, E. & Pettsov, G. The quasiternary TiB 2-W 2 B 5-CrB 2 system and its possibilities in evolution of ceramic hard materials. Powder Metall. Metal Ceram. 32, 240–248 (1993). \n18.\t Kuz’ma, Y. B., Lakh, V., Stadnyk, B. & Kovalyk, D. Systems hafnium-tungsten-boron, hafnium-rhenium-boron, and niobiumrhenium-boron. Powder Metall. Metal Ceram. 9, 1003–1006 (1970). \n19.\t Shibuya, M., Kawata, M., Ohyanagi, M. & Munir, Z. A. Titanium Diboride–Tungsten Diboride Solid Solutions Formed by Induction‐Field‐Activated Combustion Synthesis. J. Am. Ceram. Soc. 86, 706–710 (2003). \n20.\t Zhang, G.-J., Guo, W.-M., Ni, D.-W. & Kan, Y.-M. Ultrahigh temperature ceramics (UHTCs) based on $\\mathrm{ZrB}_{2}$ and $\\mathrm{HfB}_{2}$ systems: powder synthesis, densification and mechanical properties. J. Phys. 176, 012041 (2009). \n21.\t Fahrenholtz, W. & Hilmas, G. Oxidation of ultra-high temperature transition metal diboride ceramics. Int. Mater. Rev. 57, 61–72 (2012). \n22.\t Fahrenholtz, W. G., Wuchina, E. J., Lee, W. E. & Zhou, Y. Ultra-high temperature ceramics: materials for extreme environment applications. (John Wiley & Sons, 2014). \n23.\t Fahrenholtz, W. G., Binner, J. & Zou, J. Synthesis of ultra-refractory transition metal diboride compounds. J. Mater. Res. FirstView, 10.1557/jmr.2016.1210 (2016). \n\n# Acknowledgements \n\nWe acknowledge the financial support from an Office of Naval Research MURI program (grant No. N00014-15- 1-2863) and we thank our Program Mangers Dr. Kenny Lipkowitz and Dr. Eric Wuchina, Principle Investigator Prof. Donald Brenner, and all other MURI colleagues for guidance, encouragement, and helpful scientific discussion. We thank Prof. Elizabeth J. Opila for helpful discussion about the oxidation experiments. T.H., N.Z. and J.L. also acknowledge partial support from a Vannevar Bush Faculty Fellowship (ONR N00014-16-1-2569) for the STEM work. \n\n# Author Contributions \n\nJ.L. conceived the idea and designed the experiments. Y.Z. conducted the initial experiments of composition $\\#1$ before J.G. started to work on this project. J.G. conducted the most of the other experiments in a close collaboration with of T.H. (Harrington) in the lab. All authors analyzed the data and discussed the results. T.H. (Hu) conducted the STEM characterization and N.Z. conducted important digital analysis of the STEM HAADF/ABF images. S.J., Y.Z., and J.G. conducted the oxidation experiments. M.C.Q. and W.M.M. conducted the hardness measurements. J.G. and J.L. wrote the initial version of this paper; J.L., K.V., Y.Z. and T.H. revised the manuscript critically. J.L. supervised this study. \n\n# Additional Information \n\nSupplementary information accompanies this paper at http://www.nature.com/srep \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nHow to cite this article: Gild, J. et al. High-Entropy Metal Diborides: A New Class of High-Entropy Materials and a New Type of Ultrahigh Temperature Ceramics. Sci. Rep. 6, 37946; doi: 10.1038/srep37946 (2016). \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\circledcirc$ The Author(s) 2016 " + }, + { + "id": "10.1126_science.aaf3961", + "DOI": "10.1126/science.aaf3961", + "DOI Link": "http://dx.doi.org/10.1126/science.aaf3961", + "Relative Dir Path": "mds/10.1126_science.aaf3961", + "Article Title": "Majorana bound state in a coupled quantum-dot hybrid-nullowire system", + "Authors": "Deng, MT; Vaitiekenas, S; Hansen, EB; Danon, J; Leijnse, M; Flensberg, K; Nygård, J; Krogstrup, P; Marcus, CM", + "Source Title": "SCIENCE", + "Abstract": "Hybrid nullowires combining semiconductor and superconductor materials appear well suited for the creation, detection, and control of Majorana bound states (MBSs). We demonstrate the emergence of MBSs from coalescing Andreev bound states (ABSs) in a hybrid InAs nullowire with epitaxial Al, using a quantum dot at the end of the nullowire as a spectrometer. Electrostatic gating tuned the nullowire density to a regime of one or a few ABSs. In an applied axial magnetic field, a topological phase emerges in which ABSs move to zero energy and remain there, forming MBSs. We observed hybridization of the MBS with the end-dot bound state, which is in agreement with a numerical model. The ABS/MBS spectra provide parameters that are useful for understanding topological superconductivity in this system.", + "Times Cited, WoS Core": 863, + "Times Cited, All Databases": 928, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000390254300045", + "Markdown": "part from the Excellence Initiative of the German Federal and State Governments provided via the Freie Universität Berlin, the Deutsche Forschungsgemeinschaft (DFG) through the Collaborative Research Center SFB1078 project C4, as well as computing time from the Freie Universität Berlin and from the North-German Supercomputing Alliance (HLRN). M.M. acknowledges financial support from the Exploratory Research for Advanced Technology of the JST. Author contributions: S.I., R.N., and E.N. conceived the research; T.T., T.A., A.Y., J.K., R.T., E.N., P.N., and J.S. prepared microcrystals; S.M., S.K., and M.M. prepared purple membrane; E.N., C.S., R.N., M.K., and K.T. designed the experimental setup; M.K., T.Ki., T.No., S.O., and J.D. contributed the pump laser setup; E.N., T.T., R.T., T.A., A.Y., J.K., T.Ho., E.M., \n\nP.N., M.S., C.S., D.N., R.D., Y.K., T.S., D.I., T.F., Y.Y., B.J., T.Ni., K.O., M.F., C.W., R.A., C.S., P.B., J.S., and R.N. performed data collection; M.K., T.Ki., and T.No. performed time-resolved visible absorption spectroscopy; C.W. and R.N. analyzed the spectral data; T.Na. and O.N. performed data processing; A.R. and E.N. refined the intermediate structures; A.-N.B. performed computations; K.T., C.S., T.Ka., T.Ha., Y.J., and M.Y. developed the SFX systems at SACLA; and R.N., C.W., E.N., A.R., M.K., and T.Na. wrote the paper with input from all authors. Coordinates and structure factors have been deposited in the Protein Data Bank with IDs 5B6V (bR resting state), 5B6W $\\Delta t=16$ ns), 5H2H $\\Delta t=40$ ns), 5H2I $(\\Delta t=110$ ns), 5H2J $\\Delta t=290$ ns), 5B6X $\\Delta t=760$ ns), 5H2K $(\\Delta t=2\\upmu\\mathrm{s})$ , 5H2L $(\\Delta t=5.25~\\upmu\\mathrm{s})^{\\cdot}$ ), 5H2M $(\\Delta t=13.8~\\upmu\\up s^{\\prime}$ ), 5B6Y $(\\Delta t=36.2\\upmu\\mathrm{s}$ ), 5H2N $(\\Delta t=95.2~\\upmu\\up s^{\\cdot}$ ), 5H2O $\\prime_{\\Delta t}=250~\\upmu\\mathrm{s},$ ), 5H2P $'\\Delta t=657~\\upmu\\mathrm{s})$ \n\nand 5B6Z $\\langle\\Delta t=1.725~\\mathrm{ms}^{\\cdot}$ ). Raw diffraction images have been deposited in the Coherent X-ray Imaging Data Bank (accession ID 53). \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/354/6319/1552/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S9 \nTables S1 and S2 \nReferences (43–76) \nMovies S1 to S3 \n\n28 June 2016; accepted 21 November 2016 \n10.1126/science.aah3497 \n\n# TOPOLOGICAL MATTER \n\n# Majorana bound state in a coupled quantum-dot hybrid-nanowire system \n\nM. T. Deng,1,2 S. Vaitiekėnas,1,3 E. B. Hansen,1 J. Danon,1,4 M. Leijnse,1,5 K. Flensberg,1 J. Nygård,1 P. Krogstrup,1 C. M. Marcus1\\* \n\nHybrid nanowires combining semiconductor and superconductor materials appear well suited for the creation, detection, and control of Majorana bound states (MBSs). We demonstrate the emergence of MBSs from coalescing Andreev bound states (ABSs) in a hybrid InAs nanowire with epitaxial Al, using a quantum dot at the end of the nanowire as a spectrometer. Electrostatic gating tuned the nanowire density to a regime of one or a few ABSs. In an applied axial magnetic field, a topological phase emerges in which ABSs move to zero energy and remain there, forming MBSs. We observed hybridization of the MBS with the end-dot bound state, which is in agreement with a numerical model. The ABS/MBS spectra provide parameters that are useful for understanding topological superconductivity in this system. \n\nto refer to the regime in which MBS appears. The similarities between trivial ABS zero-energy crossings and MBS in a finite-length wire can be subtle (13, 15, 16, 30, 31). Several obstacles have prevented a detailed experimental study of the ABS-MBS relation to date, including a soft proximity-induced gap (18), the difficulty of tuning the chemical potential of the hybrid nanowire, and disorder in the wire and tunneling barrier. \n\nIn this work, we investigated MBSs and their emergence from coalescing ABSs, using tunneling spectroscopy through quantum dots at the end of epitaxial hybrid Sm-S nanowires. We observed gate-controlled hybridization of the MBSs with the bound state in the end dot, finding excellent agreement between experiment and numerical models. The epitaxial Sm-S interface induces a hard superconducting gap (32, 33), whereas the partial coverage by the epitaxial superconductor allows tuning of the chemical potential and yields a high critical field (34), both crucial for realizing MBSs. \n\n# Hybrid nanowire with end dot \n\ns condensed-matter analogs of Majorana A fermions—particles that are their own antiparticles $(I)$ —Majorana bound states (MBSs) H carheanagnetisctiaptiastteicds,topreoxvihdiibnitgnaobna-sAisbfeoliranaetuxrally fault-tolerant topological quantum computing (2–7). In the past two decades, the list of potential realizations of MBSs has grown from evendenominator fractional quantum Hall states (8) and $p$ -wave superconductors (9) to topological insulator-superconductor hybrid systems (10), semiconductor-superconductor (Sm-S) hybrid nanowire systems (11–21), and artificially engineered Kitaev chains (22–24). Sm-S hybrid systems have received particular attention because of ease of realization and a high degree of experimental control. Experimental signatures of MBS in Sm-S systems have been reported (25–29), \n\ntypically consisting of zero-bias conductance peaks in tunneling spectra appearing at finite magnetic field. \n\nIn a confined normal conductor-superconductor system, Andreev reflection will give rise to discrete electron-hole states below the superconducting gap—Andreev bound states (ABSs). Given the connection between superconducting proximity effect and ABSs, zero-energy MBSs in Sm-S hybrid nanowires can be understood as a robust merging of ABSs at zero energy, thanks in part to the presence of strong spin-orbit interaction (SOI) (11–13, 15, 16). However, not all zero-energy ABSs are MBSs. For instance, in the nontopological or trivial phase, ABSs can move to zero energy at a particular Zeeman field, giving rise to a zerobias conductance peak, and then split again at higher fields, indicating a switch of fermion parity (30). On the other hand, zero-energy MBSs in short wires may also split as a function of chemical potential or Zeeman field (14). In this case, the difference between topological MBSs in a finite-length wire and trivial ABSs is whether the states are localized at the wire ends or not (17). We will use the term “MBSs” to refer to ABSs that are to a large degree localized at the wire ends and would evolve into true topological MBSs as the wire becomes longer. We also will use the term “topological phase in a finite-length wire” \n\nOur devices were made of epitaxial InAs/Al nanowires (Fig. 1A) (32). Wurtzite InAs nanowires were first grown to a length of 5 to $10~\\upmu\\mathrm{m}$ by means of molecular beam epitaxy, followed by low-temperature epitaxial growth of Al. Two or three facets of the hexagonal InAs core were covered by Al (Fig. 1B) (32). The nanowires were then deposited onto a degenerately doped silicon/ silicon oxide substrate. Transene-D Al etch was used to selectively remove the Al from the end of the wire, which was then contacted by titanium/ gold (Ti/Au, $5/100~\\mathrm{nm}$ ), forming a normal (nonsuperconducting) metal lead. Five devices were investigated. Data from four devices, denoted 1 to 4, are reported in the main text, and data from a fifth device, denoted 5, are reported in (35). For device 1, the unetched end of the nanowire section was contacted by titanium/ aluminum/vanadium $(\\mathrm{Ti}/\\mathrm{Al}/\\mathrm{V},5/20/70~\\mathrm{nm})$ , and global back gate and local side gates were used to control the electron density in the wire. A quantum dot was formed in the $\\mathsf{150–n m}$ bare InAs wire segment between the Ti/Au normal contact and the epitaxial Al shell, owing to disorder or band-bending (33). Fabrication details for the other devices, each slightly different, are given in (35). Micrographs of all devices accompany transport data. Except where noted, the magnetic field $B$ was applied parallel to the quasiparticle continuum appears. The value of $\\Delta^{*}$ for device 1 is found to be $220~\\mathrm{\\upmueV}$ (for devices 2, 3, and 4, $\\Delta^{*}\\sim250$ to $270\\upmu\\mathrm{eV})$ , which is somewhat larger than measured previously in either epitaxial (33) or evaporated hybrid devices (27, 37). The measured gap is consistent with values for evaporated ultrathin Al films in the literature (38). \n\n![](images/ce027b01ad20406f61a1c38e139eb79513b3846cc0a0f477e05884996d8b4210.jpg) \nFig. 1. Epitaxial hybrid nanowire with end dot. (A) Scanning electron micrograph (SEM) of device 1, with false color representing different materials. The white brace indicates the location of a natively formed quantum dot. (B) Schematic cross-sectional view of the nanowire. The epitaxial Al shell (dark blue) was grown on two facets of the hexagonal InAs core (light blue), with a thickness of ${\\sim}10~\\mathsf{n m}$ . The applied magnetic field is parallel to the nanowire in most cases. (C) Differential conductance measured for device 1 as a function of applied source-drain bias voltage, $V_{\\mathrm{sd}}^{}$ , and the voltage $V_{\\mathrm{g1}}$ on gate g1. A Coulomb diamond pattern and a low-conductance gap through the valleys can be seen. (D) Linecuts of the conductance, taken from (C), indicated by red and black lines. (E and F) Schematic views of two different dot-wire configurations of the device. (E) illustrates the elastic cotunneling process in the Coulomb-blockade regime, whereas (F) shows how a quantum-dot level can hybridize with the subgap states in the nanowire when it is tuned to resonance. \n\nTunneling conductance $(d I/d V_{\\mathrm{sd}})$ for device 1, as a function of $V_{\\mathrm{g1}}$ and $V_{\\mathrm{sd}},$ spanning three Coulomb blockade valleys is shown in Fig. 2 for two values of back-gate voltage $V_{\\mathrm{bg}},$ which is applied uniformly to the device by using a conductive Si substrate separated by a $200\\mathrm{-nm}$ oxide layer. To compensate the effect of $V_{\\mathrm{bg}}$ on the conductance of the end dot, the voltage $V_{\\mathrm{g1}},$ on the gate near the end dot is simultaneously swept by a small amount during the back-gate sweep. Other gates are grounded. At less negative back-gate voltage $\\mathbf{\\tilde{\\rho}}_{V_{\\mathrm{bg}}}=-2.5\\:\\mathrm{V})$ , several subgap conductance peaks are seen at $B=1$ T, including one at zero bias. We attribute these peaks, which run through consecutive Coulomb valleys, to ABSs in the finite-length wire. The magnetic field dependence of the spectrum is shown in Fig. 2, C and D: subgap states lie close to the superconducting gap at zero field and move to lower energies as $B$ increases. Some of the lower-energy subgap states merge at zero energy, forming a narrow zero-bias peak spanning the range from 1 to $2\\mathrm{T}$ . At more negative back-gate voltage, $V_{\\mathrm{bg}}=-7~\\mathrm{V}$ , dot-independent subgap structure is absent (Fig. 2, E to H); only a hard superconducting gap is seen throughout the field range of 0 to $2\\mathrm{~T~}$ . The back-gate dependence on the number of ABSs in the gap demonstrates that the chemical potential of the wire can be controlled with the superconductor shell present. \n\nThe zero-field effective gap $\\Delta^{*}$ in the regime with high ABS density is ${\\sim}200~\\upmu\\mathrm{eV}$ , which is distinctly smaller than the $220\\mathrm{-}\\upmu\\mathrm{eV}$ gap seen in the no-ABS regime. This is because the phenomenological $\\Delta^{*}$ in the high-ABS density regime is mainly determined by the energy of the cluster of ABSs, yielding what is usually referred to as the induced gap $\\Delta_{\\mathrm{ind}}$ . When there are no states in the wire, $\\Delta^{*}$ is set by the gap of the Al shell, denoted $\\Delta$ . \n\nnanowire axis by using a three-axis vector magnet. Transport measurements were performed by using standard ac lock-in techniques in a dilution refrigerator, with a base temperature of $20~\\mathrm{mK}$ . \n\nDifferential conductance measured for device 1 is shown in Fig. 1C as a function of source-drain voltage, $V_{\\mathrm{sd}}$ , between the normal and superconducting leads, and the voltage, $V_{\\mathrm{g1}},$ on gate g1. The height (in $V_{\\mathrm{sd},}$ of the Coulomb-blockade diamond yields an end-dot charging energy $E_{\\mathrm{c}}\\sim$ $6\\ \\mathrm{meV}$ . Because $E_{\\mathrm{c}}$ is larger than the superconductor gap, single-electron cotunneling dominates transport in Coulomb-blockade valleys. In this regime, the dot acts effectively as a single barrier and can be used as a tunneling spectrometer for the wire (Fig. 1E). On the other hand, when the dot is tuned onto a Coulomb peak (Fig. 1F), hybridization occurs between the dot and wire states (36). We first discuss cotunneling spectra away from resonance then investigate dot-wire interaction when the dot is on resonance with ABSs and MBSs in the wire. \n\n# Weak dot-wire coupling \n\nA hard proximity-induced superconducting gap, marked by vanishing conductance below coherence peaks, can be seen in cotunneling transport through Coulomb blockade valleys of the end dot (Fig. 1D). The width of the gap in bias voltage is given by $2\\Delta^{*}/e$ , where $\\Delta^{*}$ is the effective superconducting gap, defined phenomenologically by the bias voltage at which the \n\nBetween the regimes of high ABS density and zero ABS density, one can find, by adjusting back and local gates, a low-density ABS regime in which only one or a few subgap modes are present. In this intermediate density regime, ABSs can be readily probed with tunneling spectroscopy, without softening the gap with numerous quasicontinuous subgap states. To prevent end-dot states from mixing with ABSs in the wire, two gate voltages, one at the junction and one along the wire, were swept together so as to compensate for capacitive cross-coupling (Fig. 3A). In this way, either the end-dot chemical potential $\\upmu_{\\mathrm{dot}}$ or the wire chemical potential $\\upmu_{\\mathrm{wire}}$ could be swept, with the other held fixed. A two-dimensional plot of zero-bias conductance as a function of $V_{\\mathrm{g1}}$ and $V_{\\mathrm{g2},\\mathrm{g3}}$ (fixing $V_{\\mathrm{g2}}=V_{\\mathrm{g3}})$ in Fig. 3B shows isopotential lines for the end dot as a diagonal Coulomb blockade peak-ridge (red arrows). The slope of this ridge determines how to compensate the wire gates $(V_{\\mathrm{g2,g3}})$ with the junction gate $(V_{\\mathrm{g1}})$ . Data can then be taken in the cotunneling regime for an effectively constant $\\upmu_{\\mathrm{dot}}.$ . Tunneling spectra measured along the red line in Fig. 3B at various fields are shown in Fig. 3, C to F. A pair of ABSs that moves with $\\upmu_{\\mathrm{wire}}$ can be seen at $B=0$ (Fig. 3C). The spectrum is symmetric around zero $V_{\\mathrm{sd}},$ reflecting particlehole symmetry. The minimum energy of the ABS is $\\zeta=130~\\upmu\\mathrm{eV}$ , which is smaller than the effective gap $\\Delta^{*}=220~\\mathrm{\\upmueV}$ . The pair of ABSs splits into two pairs when the applied magnetic field lifts the spin degeneracy, visible above $B=0.4$ T (Fig. 3D). The low field splitting corresponds to an effective g-factor, $\\mathrm{g}^{\\ast}\\sim4$ (the $\\mathbf{g}^{*}$ -factor estimated from the ABS-energy/ magnetic field slope may differ considerably from the intrinsic $\\mathbf{g}^{*}$ -factor). At higher magnetic fields, the inward ABSs cross at zero and reopen, forming a characteristic oscillatory pattern (Fig. 3, E and F). The gap reopening at more positive $V_{\\mathrm{g2},\\mathrm{g3}}$ is relatively slow, leading to a single zero-bias peak in the range of $V_{\\mathrm{g2},\\mathrm{g3}}$ $\\sim5.8$ to $_{7\\mathrm{~V~}}$ (Fig. 3F). \n\nThe magnetic field dependence of the ABS spectrum near the ABS energy minimum is shown in Fig. 3G. The evolution of the ABSs can be clearly followed: They split at low field, the inner ABSs merge around $B=1\\mathrm{~T~}$ , they split again at higher fields, and the resplit ABSs merge with the higher-energy ABSs above $B=$ $1.7\\:\\mathrm{T}$ . Here, the emergence of a zero-bias peak and its splitting is qualitatively similar to the observations reported in (27, 30). However, the $B$ -dependent ABS spectrum at more positive gate voltage (Fig. 3H) shows a merging-splittingmerging behavior, giving rise to an eye-shaped loop between 1 and 2 T. At even more positive gate voltage (Fig. 3I), the spectrum displays an unsplit zero-bias peak from 1.1 to $2\\mathrm{T}$ . The first excited ABSs in Fig. 3, G to I, are still visible at a high magnetic field—for instance, as marked at $B=1.2\\mathrm{~T~}$ in Fig. 3, H and I. Qualitatively, the lowest-energy ABSs in Fig. 3, H and I, tend to split after crossing but are pushed back by the first excited ABSs, resulting in either a narrow splitting or an unsplit zero-bias peak. The measurements in Fig. 3, C to I, were taken in an even Coulomb valley of the end dot, but the qualitative behavior does not depend on enddot parity. Similar results measured in an odd valley of the end dot are provided in (35). \n\nThe different field dependences of the subgap states—either crossing zero or sticking at zero— can be understood as reflecting a transition from ABS to MBS (14, 17). For the ABSs in the regime of $V_{\\mathrm{g2},\\mathrm{g3}}<5.8\\:\\mathrm{V}_{\\mathrm{i}}$ , their crossing in Zeeman field is a signature of parity switching, similar to ABSs in a quantum dot, such as investigated in (30). In contrast, behavior in the range of $V_{\\mathrm{g2},\\mathrm{g3}}\\sim5.8$ to $_{\\mathrm{~7~V~}}$ indicates that the system is in the topologically nontrivial regime, with MBS levels that stick to zero as the magnetic field increases. In a finite-size wire, SOI induces anticrossings between discrete ABSs, thus pushing levels to zero, preventing further splitting. We ascribe the differences in the qualitative behavior in Fig. 3, G to I, to state-dependent SOI-induced anticrossings, which depend on gate voltage. The excited ABS in Fig. 3G and the ones in Fig. 3, H and I, are presumably not the same state, but belong to different subgap modes [investigated in detail in (35)]. \n\nFor a long wire, the topological phase transition is marked by a complete closing and reopening of a gap to the continuum, with a single discrete state remaining at zero energy after the reopening. For a finite wire, the continuum is replaced by a set of discrete ABSs, and at the transition where a single state becomes pinned near zero energy, there remains a finite gap d to the first discrete excited state. At this transition point (where the gap of the corresponding infinite system would close and its spectrum would be linear), $E_{k}=R\\mathsf{{a}}|k|$ , where $R$ is a renormalization factor due to the strong coupling between the semiconducting wire and its superconducting shell (35), $\\mathfrak{a}$ is the spin-orbit coupling strength, and $k$ is the electron wave vector. From this relation, we can connect d to the ratio $L/\\xi$ as $L/\\xi\\approx\\mathbb{R}\\pi\\Delta^{\\prime}/\\delta$ , where $L$ is the separation between Majoranas (the wire length in the clean limit), $\\xi$ is the effective superconducting coherence length near the topological oscillation amplitude and $\\updelta E_{0}$ is a prefactor. If we take the value $\\updelta E_{0}~\\sim~150~\\upmu\\mathrm{eV}$ based on Coulomb peak motion in (40), we obtain a value $L/\\xi\\sim1.3$ by using the subgap state splitting energy $\\delta E\\sim40~\\ensuremath{\\upmu\\mathrm{eV}}$ at $\\mathrm{~B~}\\sim1.3\\mathrm{~T~}$ from Fig. 3H. We speculate that the discrepancy in estimates of $L/\\xi$ may be attributed to a smaller value of $\\updelta E_{0}$ in (40) as compared with the $\\updelta E_{0}$ in this device, perhaps arising from differences in gatetuned electron density compared with the Coulomb blockade devices in (40). \n\n![](images/6403d39b31719eeba414bf8f58c32b335750f6db27d9da76d09177ee9918fa44.jpg) \nFig. 2. Tunneling spectra for large and zero ABS density. (A) Differential conductance measured for device 1 as a function of $V_{\\mathrm{sd}}$ and $V_{\\mathrm{g1}}$ , measured at $B=0.5\\intercal$ and $V_{\\mathrm{bg}}=-2.5\\:\\Vdash$ , $V_{\\mathrm{g}2,\\mathrm{g}3}=-10$ V. The white arrows indicate Zeeman split dot levels. (B) The same as (A), but at $B=1$ T. ABSs can be clearly identified below the superconducting gap. (C) Differential conductance as a function of $V_{\\mathrm{sd}}$ and $B$ $[B-V_{\\mathrm{sd}}$ sweep), measured at the gate voltage indicated by the white lines in (A) and (B). The triangle and square indicate at which fields (A) and (B) are measured, respectively. Blurring of data in narrow $B<0$ range is due to heating caused by sweeping field away from zero. (D) Line-cut \ntaken from (C) at various $B$ values. Lines are offset by 0.01 $e^{2}/h$ each for clarity. The conductance peaks below the superconducting gap indicate that the wire is in a subgap-state–rich regime. A well-defined zero-bias peak can be seen at high field. (E to $\\boldsymbol{\\mathsf{H}}$ ) Similar to (A) to (D), but measured at $V_{\\mathrm{bg}}=-7\\:\\mathrm{V}$ and $V_{\\mathrm{g2},\\mathrm{g3}}=-10~\\mathsf{V},$ , and with (G) measured at the gate voltage indicated by the black lines in (E) and (F). The diamond and circle indicate at which fields (E) and (F) are measured, respectively. Here, a hard superconducting gap is clearly seen, with a critical magnetic field $\\boldsymbol{B}_{\\mathrm{c}}$ up to ${\\sim}2.2~\\top.$ No subgap structure is observed across the full range of field, 0 to $2\\intercal$ . \n\n![](images/26026c9f98be3250ce54737a9db9f32978c3f38e786efea7f7a6cb81a0445b2e.jpg) \nFig. 3. Tunneling spectra for intermediate density in few-ABS regime. (A) A schematic of device 1 showing the gating configuration for a combined gate voltage sweep. g1 and $^{\\mathrm{g2},\\mathrm{g3}}$ are capacitively coupled to both the dot and the nanowire. (B) Conductance measured at $V_{\\mathrm{sd}}=0~\\mathrm{mV},$ , $V_{\\mathrm{bg}}=-7V$ , and $B=0$ , as a function of $V_{\\mathrm{g1}}$ and $V_{\\mathrm{g2,g3}}$ (the gate map). g2 and $g3$ are connected to the same voltage source. The high-conductance lines indicated by red arrows are the resonant levels in the end dot. The dot can be used as a cotunneling spectrometer if the gate sweeping is kept inside the Coulomb blockade valley and parallel to the resonant level. (C to F) Tunneling spectra at various \nmagnetic fields as a function of the combined gate voltage, measured along the red line in (B). The energy of the ABSs is strongly dependent on gate voltages. (G to I) $B\\mathrm{-}V_{\\mathrm{sd}}$ sweeps at different gate voltages, corresponding to the triangle, square, and circle in (C) to (F), respectively. Depending on gate voltages, the ABSs in the wire show different magnetic field evolution, from a splitting behavior (G) to nonsplitting behavior (I). Arrows in (G) to (I) indicate the first excited ABSs, and d in (H) is defined as the residual gap—the energy of the first excited state around topological phase transition, caused by the finite-size effect. \n\n![](images/07f32432e37ccc0aae2ceb193b34029645dbe6f06e320f32b68b42092257d8ff.jpg) \nFig. 4. Stable zero-energy states measured on other devices. (A) SEM (B) is measured at $V_{\\mathrm{g1}}=-600\\mathsf{m V},$ $V_{\\mathrm{g}2}=-1840\\mathrm{mV},$ and $V_{\\mathrm{g3}}=5$ V, and (E) is images of device 2, in which local bottom gates are used. The hybrid wire measured at $V_{\\mathrm{g1}}=3720~\\mathrm{mV}$ , $V_{\\mathrm{g}2}=V_{\\mathrm{g}3}=-5850\\mathrm{mV}.$ , and $V_{\\mathrm{bg}}=-8\\ V.$ . (C and section is $1.5~{\\upmu\\mathrm{m}}$ long. (D) SEM image of device 3, with the hybrid wire F) Gate voltage–dependence measurements of subgap states for device 2 section length around $2~{\\upmu\\mathrm{m}}$ long. (B and E) Subgap states evolution in and device 3, respectively. Both measurements are taken by following the magnetic field, measured on device 2 and device 3, respectively. In both isopotential lines of the hybrid wires in one of their end-dot Coulomb plots, stable zero-energy states arising from a pair of ABSs can be seen. blockade valleys. \n\n![](images/16124201272045aa0a4fabbd373f820d840a66a5e9ec30f2a9e625d97cbf8353.jpg) \nFig. 5. Resonant coupling of wire subgap states and dot states. (A) A gate map similar to Fig. 3B, but taken at $B=1.2{\\:}{\\top}$ . The blue dashed arrows denote the dot isopotential sweeping direction, and the red dashed arrow denotes the wire isopotential sweeping direction. (B to D) Differential conductance measured across one of the resonant dot levels, along the solid red line in (A), at $B=0$ , 0.8, and $\\begin{array}{r}{1.2\\top.}\\end{array}$ The dashed circle in (C) indicates an anticrossing between the dot state and a wire state. In (D), there is a pronounced zero-bias peak-splitting at the dot resonance. (E and F) Simulated differential conductance through a dot-hybrid wire system, as a function of bias voltage and dot chemical potential $\\upmu_{\\mathrm{dot}}$ , for different Zeeman splittings in the wire. The zero-bias peak splitting at the dot resonance also appears in (F). (G) SEM image of device 4. (H) Normalized conductance in the MBS-dot hybridization region of device 4. Again, the zero-energy MBS state is split when it crosses the end-dot resonant level. \n\nSubgap-state evolution in applied magnetic field and gate voltage for devices 2 and 3 are shown in Fig. 4. For device 2, which has a device length of ${\\sim}1.5~\\upmu\\mathrm{m},$ subgap state reaches zero energy at ${\\sim}0.9\\mathrm{~T~}$ and persists to $2\\mathrm{T}$ . Using the finite-size gap near the phase transition point in Fig. 4B, we can extract $L/\\xi\\sim1.7(\\S\\sim\\Delta^{\\prime}\\sim170\\upmu\\mathrm{eV},$ , $R\\sim0.56)$ . For device 3, with a ${\\sim}2\\upmu\\mathrm{m}$ hybrid nanowire, rigid zero energy states are shown in both magnetic field and gate voltage–dependence measurements. Here, a value of $L/\\xi\\sim3.4(\\Delta^{\\prime}\\sim230\\upmu\\mathrm{eV},$ , $\\S\\sim100\\ \\upmu\\mathrm{eV}$ , and $R\\sim0.47\\$ can be estimated from Fig. 4E. \n\nThe obtained values for $L/\\xi$ evidently do not reflect the lithographic device length. For instance, taking $\\xi\\sim260~\\mathrm{nm}$ from (40) (where $\\xi$ is fit from the wire-length dependence by using similar nanowires), yields lengths of 0.6, 0.45, and $0.9\\upmu\\mathrm{m}$ for devices 1, 2, and 3, resepectively, in each case shorter than the lithographic length. This discrepancy is presumably the result of disorder or material defects that create a topological region shorter than the full wire. \n\n# Resonant dot-MBS coupling \n\nWe next examined the interaction of wire states with bound states in the end dot. For all data above, the wire states were probed via cotunneling through the end dot (Fig. 1E), actively keeping the end dot in the middle of a Coulomb valley. By separately controlling $\\upmu_{\\mathrm{dot}}$ and $\\upmu_{\\mathrm{wire}},$ we can also tune the local gates so that a wire state is at resonance with a Coulomb peak of the dot (Fig. 1F). As seen in the gate map for device 1 shown in Fig. 5A, besides the dot resonant level, there is a MBS-induced blurred trace (Fig. 5A, red dashed arrow). Tunneling spectra at various magnetic fields where the MBS and end-dot state align are shown in Fig. 5, B to D [traces with a larger range are provided in (35)]. The gate sweep is now along a wire isopotential (Fig. 5A, red solid line) as opposed to an end-dot isopotential as in Fig. 3. The dot state crosses zero energy around $V_{\\mathrm{g2},\\mathrm{g3}}=5.66\\mathrm{V}$ , at which the dot switches its fermion parity. At $B=0$ (Fig. 5B) and at $B=0.8$ T (Fig. 5C), we clearly see this crossing in the spectrum. There is a pronounced anticrossing between the dot state and the wire state in Fig. 5C (indicated by the dashed circle). Figure 5D looks qualitatively different: A zero-bias peak is visible when the dot is off resonance (which is extended from the MBS in Fig. 3H), and this peak splits when the dot level comes close to zero. In this case, no zero-crossing is observed. \n\nphase transition, and $\\Delta^{\\prime}$ is the effective gap near the phase transition point [the derivation and more details are available in (35, 39)]. The ratio $L/\\xi$ is the dimensionless length of the topological wire segment. We estimate from Fig. \n\n$3\\mathrm{H}\\ \\updelta\\ \\sim\\ 100\\ \\upmu\\mathrm{eV}_{;}$ $\\Delta^{\\prime}\\sim180~\\mathrm{\\mueV};$ and $R\\sim0.4$ , yielding $L/\\xi\\sim2.3$ . We then take values at the field where the ABS reaches zero energy. We can independently estimate $L/\\xi$ from the relation $\\updelta E~\\approx~\\Bar{\\updelta}E_{0}e^{-L/\\upxi}$ (14, 17), where $\\delta E$ is MBS \n\n![](images/1fb7c5c999f2d17f321969766e0e064a6a32f61718f8b16f77956e071d5db3a7.jpg) \nFig. 6. Tunneling spectrum for resonant dot-wire coupling. (A) $B{-}V_{\\mathrm{sd}}$ sweep at $V_{\\mathrm{bg}}=-8.5$ V, $V_{\\mathrm{g1}}=$ $22\\vee,$ , and $V_{\\mathrm{g}2}=V_{\\mathrm{g}3}=-10~\\backslash$ . (B) Differential conductance line-cut plots taken from (A) at various $B$ values. At this gate configuration, a pronounced zero-bias conductance peak emerges around $B=$ 0.75 T and persists above $B=2$ T, without splitting. The intensity of the zero-bias peak is higher than other finite-energy ABSs and even higher than the Al superconducting coherence peaks. The background conductance is almost zero even at $B=1{\\:}\\mathsf{T}$ , indicating that the induced gap is still a hard gap after the phase transition. \n\nThe dot-wire interaction observed in Fig. 5D can be understood in terms of leakage of the MBS into the dot when the dot is on resonance (41). The energy splitting of a pair of MBSs is given by $\\updelta E^{\\propto}|\\sin(k_{\\mathrm{F}}L)e^{-L/\\upxi}|$ (where $k_{\\mathrm{{F}}}$ is the effective Fermi wave vector). In Fig. 5D, this splitting is initially small, when the dot is off resonance and coupling of the MBSs to the dot states is suppressed by Coulomb blockade. For a finitesize wire, this implies that $\\sin(k_{\\mathrm{F}}L)\\sim0$ at that particular tuning. As the dot level comes closer to the resonant point, the nearby MBS partially leaks into the dot, which changes the details of the MBSs wave function [the numerical study on the wave-function distribution is provided in (35)]. This can change the effective $k_{\\mathrm{{F}}}L$ in $\\delta E,$ , which causes the zero-bias peak to split at resonance. Numerical simulations of the conductance spectrum of the coupled dot-MBS (Fig. 5, E and F) show good qualitative agreement with the experimental data, both in the trivial superconducting regime (Fig. 5, C and E) and in the topological superconducting phase (Fig. 5, D and F). Similar zero-bias peak splitting in another coupled dot-MBS device (device 4) is shown in Fig. 5H. To enhance image visibility, conductance values in Fig. 5H are normalized by the conductance at $V_{\\mathrm{sd}}=0.2~\\mathrm{mV}$ at the corresponding gate voltage. \n\nLast, we examined the magnetic field evolution of the subgap states in the strong dotwire coupling regime, in which dot and wire states cannot be separated. Shown in Fig. 6 is the evolution with field of the spectral features of the dot-wire system measured for device 1, with two ABSs merging at $B=0.75\\mathrm{~T~}$ into a stable zero-bias peak that remains up to $B=2$ T. The effective $g^{*}$ -factor that can be deduced from the inward ABS branches is ${\\sim}6$ . The conductance at the base of the zero-bias peak is almost zero even at $B=1$ T, indicating a hard superconducting gap also after the topological phase \n\nThe long field range and intensity of the zerobias peak in Fig. 6 can be understood as arising from the hybridization of the MBS with the enddot state. In the strong coupling regime, MBS can partially reside at the end dot, making the effective length of the wire longer than in Fig. 3I. The MBS wave function has larger amplitude at the wire end, where the dot couples, than either finite-energy ABSs or states in the Al shell. This leads to a relatively higher conductance peak at zero energy and makes the excited states and the Al shell superconducting coherence peaks almost invisible (13). The long field range of the zero-bias peak in Fig. 6 (also Fig. 3I) may also be enhanced by electrostatic effects that depend on magnetic field (14, 19). \n\ntransition. Related measurements are shown in (35). \n\nOur measurements have revealed how the ABSs in a hybrid superconductor-semiconductor nanowire evolve into MBSs as a function of field and gate voltage. \n\n# REFERENCES AND NOTES \n\n1. E. Majorana, Nuovo Cim. 14, 171–184 (1937). \n2. A. Y. Kitaev, Phys. Uspekhi 131, 130–136 (2001). \n3. C. Nayak, S. H. Simon, A. Stern, M. Freedman, S. Das Sarma, Rev. Mod. Phys. 80, 1083–1159 (2008). \n4. B. van Heck, A. R. Akhmerov, F. Hassler, M. Burrello, C. W. J. Beenakker, New J. Phys. 14, 035019 (2012). \n5. T. Hyart et al., Phys. Rev. B 88, 035121 (2013). \n6. L. A. Landau et al., Phys. Rev. Lett. 116, 050501 (2016). \n7. D. Aasen et al., Phys. Rev. X 6, 031016 (2016). \n8. G. Moore, N. Read, Nucl. Phys. B 360, 362–396 (1991). \n9. N. Read, D. Green, Phys. Rev. B 61, 10267–10297 (2000). \n10. L. Fu, C. L. Kane, Phys. Rev. Lett. 100, 096407 (2008). \n11. R. M. Lutchyn, J. D. Sau, S. Das Sarma, Phys. Rev. Lett. 10 077001 (2010). \n12. Y. Oreg, G. Refael, F. von Oppen, Phys. Rev. Lett. 105, 177002 (2010). \n13. T. D. Stanescu, S. Tewari, J. D. Sau, S. D. Sarma, Phys. Rev. Lett. 109, 266402 (2012). \n14. S. Das Sarma, J. D. Sau, T. D. Stanescu, Phys. Rev. B 86, 220506 (2012). \n15. D. Chevallier, P. Simon, C. Bena, Phys. Rev. B 88, 165401 (2013). \n16. D. Rainis, L. Trifunovic, J. Klinovaja, D. Loss, Phys. Rev. B 87, 024515 (2013). \n17. T. D. Stanescu, R. M. Lutchyn, S. Das Sarma, Phys. Rev. B 87, 094518 (2013). \n18. S. Takei, B. M. Fregoso, H.-Y. Hui, A. M. Lobos, S. Das Sarma, Phys. Rev. Lett. 110, 186803 (2013). \n19. A. Vuik, D. Eeltink, A. R. Akhmerov, M. Wimmer, New J. Phys. 18, 033013 (2016). \n20. J. D. Sau, R. M. Lutchyn, S. Tewari, S. Das Sarma, Phys. Rev. Lett. 104, 040502 (2010). \n21. J. Alicea, Phys. Rev. B 81, 125318 (2010). \n22. S. Nadj-Perge, I. K. Drozdov, B. A. Bernevig, A. Yazdani, Phys. Rev. B 88, 020407 (2013). \n23. M. M. Vazifeh, M. Franz, Phys. Rev. Lett. 111, 206802 (2013). \n24. S. Nadj-Perge et al., Science 346, 602–607 (2014). \n25. V. Mourik et al., Science 336, 1003–1007 (2012). \n26. M. T. Deng et al., Nano Lett. 12, 6414–6419 (2012). \n27. A. Das et al., Nat. Phys. 8, 887–895 (2012). \n28. H. O. H. Churchill et al., Phys. Rev. B 87, 241401 (2013). \n29. M. T. Deng et al., Sci. Rep. 4, 7261 (2014). \n30. E. J. H. Lee et al., Nat. Nanotechnol. 9, 79–84 (2014). \n31. R. Žitko, J. S. Lim, R. López, R. Aguado, Phys. Rev. B 91, 045441 (2015). \n32. P. Krogstrup et al., Nat. Mater. 14, 400–406 (2015). \n33. W. Chang et al., Nat. Nanotechnol. 10, 232–236 (2015). \n34. R. Meservey, D. H. Douglass Jr., Phys. Rev. 135, A25 (1964). \n35. Supplementary materials are available on Science Online. \n36. M. Leijnse, K. Flensberg, Phys. Rev. B 84, 140501 (2011). \n37. W. Chang, V. E. Manucharyan, T. S. Jespersen, J. Nygård, C. M. Marcus, Phys. Rev. Lett. 110, 217005 (2013). \n38. P. N. Chubov, V. V. Eremenko, Y. A. Pilipenko, Sov. Phys. JETP 28, 389–395 (1969). \n39. B. van Heck, R. Lutchyn, L. I. Glazman, Phys. Rev. B 93, 235431 (2016). \n40. S. M. Albrecht et al., Nature 531, 206–209 (2016). \n41. E. Vernek, P. H. Penteado, C. A. Seridonio, J. C. Egues, Phys. Rev. B 89, 165314 (2014). \n\n# ACKNOWLEDGMENTS \n\nWe thank R. Aguado, S. Albrecht, J. Alicea, L. Glazman, A. Higginbotham, B. van Heck, T. Sand Jespersen, F. Kuemmeth, R. Lutchyn, and J. Paaske for valuable discussions and V. Kirsebom, S. Moore, M. Ravn, D. Sherman, C. Sørensen, G. Ungaretti, and S. Upadhyay for contributions to growth, fabrication, and analysis. This research was supported by Microsoft Research, Project Q, the Danish National Research Foundation, the Villum Foundation, and the European Commission. M.L. acknowledges the Crafoord Foundation and the Swedish Research Council (VR). P.K., J.N., and C.M.M. are co-inventors on patent application PCT/EP2015/065110, submitted by the University of Copenhagen, covering epitaxial semiconductorsuperconductor nanowires. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/354/6319/1557/suppl/DC1 \nSupplementary Text \nFigs. S1 to S11 \nReferences (42–46) \n3 February 2016; accepted 16 November 2016 \n10.1126/science.aaf3961 \n\n# Science \n\n# Majorana bound state in a coupled quantum-dot hybrid-nanowire system \n\nM. T. Deng, S. Vaitiekenas, E. B. Hansen, J. Danon, M. Leijnse, K. Flensberg, J. Nygård, P. Krogstrup and C. M. Marcus \n\nScience 354 (6319), 1557-1562. DOI: 10.1126/science.aaf3961 \n\n# Watching Majorana bound states form \n\nMajorana bound states (MBSs) are peculiar quasiparticles that may one day become the cornerstone of topological quantum computing. To engineer these states, physicists have used semiconductor nanowires in contact with a superconductor. Although many of the observed properties align with theoretical predictions, a closer look into the creation of MBSs is desirable. Deng et al. fabricated nanowires with a quantum dot at one end that served as a spectrometer for the states that formed inside the superconducting gap of the nanowire. Using this setup, topologically trivial bound states were seen to coalesce into MBSs as the magnetic field was varied. \n\nScience, this issue p. 1557 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_ncomms11053", + "DOI": "10.1038/ncomms11053", + "DOI Link": "http://dx.doi.org/10.1038/ncomms11053", + "Relative Dir Path": "mds/10.1038_ncomms11053", + "Article Title": "Water electrolysis on La1-xSrxCoO3-δ perovskite electrocatalysts", + "Authors": "Mefford, JT; Rong, X; Abakumov, AM; Hardin, WG; Dai, S; Kolpak, AM; Johnston, KP; Stevenson, KJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Perovskite oxides are attractive candidates as catalysts for the electrolysis of water in alkaline energy storage and conversion systems. However, the rational design of active catalysts has been hampered by the lack of understanding of the mechanism of water electrolysis on perovskite surfaces. Key parameters that have been overlooked include the role of oxygen vacancies, B-O bond covalency, and redox activity of lattice oxygen species. Here we present a series of cobaltite perovskites where the covalency of the Co-O bond and the concentration of oxygen vacancies are controlled through Sr2+ substitution into La1 - xSrxCoO3 - delta. We attempt to rationalize the high activities of La1 - xSrxCoO3 - delta through the electronic structure and participation of lattice oxygen in the mechanism of water electrolysis as revealed through ab initio modelling. Using this approach, we report a material, SrCoO2.7, with a high, room temperature-specific activity and mass activity towards alkaline water electrolysis.", + "Times Cited, WoS Core": 919, + "Times Cited, All Databases": 966, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000372721700001", + "Markdown": "# Water electrolysis on La1 xSrxCoO3 d perovskite electrocatalysts \n\nJ. Tyler Mefford1, Xi Rong2, Artem M. Abakumov3,4, William G. Hardin5, Sheng Dai6, Alexie M. Kolpak2, Keith P. Johnston5,7 & Keith J. Stevenson1,3,5,8 \n\nPerovskite oxides are attractive candidates as catalysts for the electrolysis of water in alkaline energy storage and conversion systems. However, the rational design of active catalysts has been hampered by the lack of understanding of the mechanism of water electrolysis on perovskite surfaces. Key parameters that have been overlooked include the role of oxygen vacancies, B–O bond covalency, and redox activity of lattice oxygen species. Here we present a series of cobaltite perovskites where the covalency of the ${\\mathsf{C o}}{\\mathsf{-O}}$ bond and the concentration of oxygen vacancies are controlled through $\\mathsf{S r}^{2+}$ substitution into $\\mathsf{L a}_{1-x}\\mathsf{S r}_{x}\\mathsf{C o O}_{3-\\delta}$ . We attempt to rationalize the high activities of $\\mathsf{L a}_{1-x}\\mathsf{S r}_{x}\\mathsf{C o O}_{3-\\delta}$ through the electronic structure and participation of lattice oxygen in the mechanism of water electrolysis as revealed through ab initio modelling. Using this approach, we report a material, $\\mathsf{S r C o O}_{2.7},$ with a high, room temperature-specific activity and mass activity towards alkaline water electrolysis. \n\nT thee ceanrvcirtoynomf efnotsasli afunedl gaenodpotlhiteicianl rperaosibnlegmaswarsesonceisas eodf with their use have encouraged significant efforts towards the development of advanced energy storage and conversion systems using materials that are cheap, abundant and environmentally benign. A major thrust in the field of renewable energy has been to develop higher power and more energy-dense storage devices, including low-temperature regenerative fuel cells and rechargeable metal–air batteries that function through the electrocatalysis of oxygen. Inherent to these systems are the electrolysis of water $(2\\mathrm{H}_{2}\\mathrm{O}\\to\\mathrm{O}_{2}+4\\mathrm{H}^{+}+\\dot{4}\\mathrm{e}^{-}$ ; oxygen evolution reaction (OER)) and the reduction of molecular oxygen $(\\mathrm{O}_{2}+4\\mathrm{H}^{+}+4\\mathrm{e}^{-}\\rightarrow2\\mathrm{H}_{2}\\mathrm{O};$ oxygen reduction reaction (ORR)), both of which require the use of an electrocatalyst due to their slow reaction kinetics. The most active catalysts for the ORR are $\\mathrm{\\Pt}$ -alloys and other precious metals, Ir, Ru and $\\mathrm{Pd}^{1-3}$ . However, while the $\\mathrm{Pt}$ group metals perform well for the ORR, the formation of an oxide surface film at high potentials, especially in the case of $\\mathrm{Pt,}$ decreases their ability to catalyse the $\\mathrm{OER^{4}}$ . This problem, coupled with the $\\mathrm{Pt}$ group metal scarcity and restrictive cost represent major roadblocks to mass adoption of fuel cells and metal–air batteries in renewable energy technologies. \n\nUsing alkaline electrolytes opens up the possibility to use transition metal oxides as catalysts due to their structural stability, resistance to electrolytic corrosion and their high activities for both the OER and $\\dot{\\mathrm{{ORR}^{5-7}}}$ . Among the wide variety of metal oxides available, the crystal family of perovskite oxides $\\mathrm{ABO}_{3\\pm\\delta}.$ of which A is a rare-earth or alkaline earth element and B is a transition metal, are attractive candidates due to their high ionic and electronic conductivities, structural stability, and the ability to substitute into the A and B sites elements of varying valency, electronegativity or ionic size to tune the structural, physical and electronic properties of the catalyst. Even though the electrolysis of water to oxygen is one of the most extensively studied reactions, predating even the fields of catalysis and electrochemistry, the lack of a conclusive mechanism for metal oxides in alkaline electrolyte remains a significant limitation in the rational design of electrocatalysts for the OER8. Thus, much of the research on perovskites for the OER and ORR has been focused on identifying descriptors for the activities of perovskites based on the electronic and structural properties of the surface or bulk9–11. Since the initial discovery of $\\mathrm{La}_{0.8}\\mathrm{Sr}_{0.2}\\mathrm{CoO}_{3}$ as an active ORR catalyst, many mechanistic theories have been put forward over the past 40 years12. A recent review summarizes the current understanding of mechanistic processes for the $\\mathrm{OER},$ specifically highlighting correlations between bulk and surface properties of metal oxides and their electrocatalytic activities13. Notably, the idea that the $e_{\\mathrm{g}}$ filling of the transition metal in the $\\mathrm{ABO}_{3}$ perovskite controls the intermediates binding strength and thus the electrocatalytic activity has recently gained significant credence14,15. However, we have observed that among a series of perovskites with a nominal $\\boldsymbol{\\mathrm{e_{g}}}$ filling of $\\sim1$ $\\mathrm{(LaBO_{3},}$ where ${\\bf B}={\\bf M}{\\bf n}$ , $\\scriptstyle{\\mathrm{Co}},$ Ni, or $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25})$ , there exists significant differences in their activities for both the ORR and the OER, indicating that the surface chemistry may not be adequately rationalized by bulk electronic descriptions16,17. \n\nA previously overlooked parameter concerns the role of oxygen vacancy defects, which allows for crystalline oxygen to be mobile at the surface of perovskites. It is well-known that the stoichiometry of oxygen in the crystal structure of perovskites often differs from the nominal value of 3 for the formula $\\mathrm{ABO}_{3}$ , affecting both the lability of surface oxygen and reflecting the underlying electronic structure of these materials18–20. The degree of vacancy formation reflects the relative positions of the transition metal 3d bands compared with the oxygen 2p band in the crystal, with more covalent systems exhibiting higher vacancy concentrations as shown in Fig. 1. In addition, it is well-documented that the concentrations of oxygen vacancies in perovskite electrodes can be controlled through an applied electrical potential, with room temperature diffusion coefficients of lattice oxygen for a number of perovskites in the range of $10^{-14}$ to $\\stackrel{\\sim}{10}^{-11}\\mathtt{c m}^{2}s^{-1}$ (refs 21–26). In a previous paper, we demonstrated that this effect could be used as a means of pseudocapacitive energy storage in an oxygen-deficient $\\bar{\\mathrm{LaMnO}_{2.91}}$ electrode27. We have previously hypothesized the role of lattice oxygen and vacancy exchange in the OER mechanism on $\\mathrm{LaNiO}_{3}$ refs 16,17. We now revisit this idea to investigate the role of mobile lattice oxygen in the electrolysis of water by examining the system $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta},$ $0\\leq x\\leq1$ . Through substitution of the lower valence $\\mathrm{Sr}^{2+}$ ion for $\\mathrm{La}^{3+}$ , the amount of oxygen vacancy defects and the oxidation state of cobalt can be tuned through the relation28: \n\n$$\n\\begin{array}{l}{{\\mathrm{LaCo}^{3+}\\mathrm{O}_{3}+x\\mathrm{Sr}^{2+}-x\\mathrm{La}^{3+}}}\\\\ {{\\qquad\\mathrm{O}_{1-}^{\\phantom{3+}}\\mathrm{O}_{3}+x\\mathrm{Sr}_{x}^{2+}\\mathrm{Co}_{1-}^{3+}\\mathrm{O}_{3-\\delta}+\\displaystyle\\frac{\\delta}{2}\\mathrm{O}_{2}}}\\end{array}\n$$ \n\nwhere, $\\delta$ is the oxygen non-stoichiometry parameter, $x$ is the amount of $\\operatorname{Sr}^{2\\mp}$ , and $y$ is the amount of ${\\mathrm{Co}}^{3+}$ in $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ , hereafter referred to as $\\operatorname{LSCO}(1-x)x$ (that is, LSCO28 for $\\mathrm{La}_{0.2}\\mathrm{Sr}_{0.8}\\mathrm{CoO}_{3-\\delta})$ . \n\nHerein, we describe the intrinsic activities of $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ for the OER across the full series from $0\\leq x\\leq1$ , including the previously unreported perovskite phase $\\mathrm{SrCoO}_{2.7}$ with the layered ordering of oxygen vacancies. The controlled substitution of $\\operatorname{Sr}^{2+}$ for $\\mathrm{La}^{3+}$ across the full phase space of the LSCO system while maintaining the perovskite structure allows us to probe the effects of covalency, vacancy defects and oxygen exchange on the electrocatalysis of the OER. The high activities for materials with $x>0.4$ are rationalized through the high oxygen ion diffusivity and the covalency of the Co 3d and O 2p bonding in these materials allowing access to a newly hypothesized lattice oxygen-based mechanism as predicted through DFT modelling. \n\n# Results \n\nCrystallographic characterization. LCO, LSCO and SCO samples were synthesized using our previously developed reversephase hydrolysis scheme, using a $950^{\\circ}\\mathrm{C}$ calcination temperature instead of $700^{\\circ}\\mathrm{C}$ to ensure that the correct phase was synthesized16,17,27. Figure 2a shows the powder X-ray diffraction patterns for the system, demonstrating the successful synthesis of the perovskite phases across the whole-composition range. The only minor admixture found in the LCO and LSCO samples was $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ . The crystal structures of all compositions have been verified using a combination of powder $\\mathrm{\\DeltaX}$ -ray diffraction and transmission electron microscopy. The unit cell parameters and space groups of the respective materials are given in Supplementary Table 1. The powder X-ray diffraction and selected area electron diffraction (SAED) patterns of the $x=0{-}0.4$ compositions are characteristic of the perovskite $R\\bar{3}c$ structure with the $a^{-}a^{-}a^{-}$ tilting distortion of the octahedral framework (Fig. $^{2\\mathrm{b},\\mathrm{e})}$ ). The monoclinic distortion due to orbital ordering reported for this compositional range was not detected being beyond resolution of our powder $\\mathrm{\\DeltaX}$ -ray diffraction experiment29–31. The LSCO46 composition crystallizes in a cubic $P m\\bar{3}m$ perovskite structure. In the crystal structures of LSCO28 and SCO ordering of oxygen vacancies becomes obvious from both SAED patterns and high-angle annular dark-field scanning transmission electron microcopy (HAADF-STEM) images (Fig. $\\textstyle2c,\\mathrm{d},\\mathrm{f},\\mathrm{g})$ . Oxygen vacancies reside in the $(\\mathrm{CoO}_{2-\\delta})$ anion-deficient perovskite layers alternating with the complete $\\mathrm{(CoO}_{2}\\mathrm{)}$ ) layers that results in a tetragonal $a_{\\mathrm{p}}\\times a_{\\mathrm{p}}\\times2a_{\\mathrm{p}}$ \n\n![](images/58e43c3d69f9073c62999adb600f4d887e244ae2ee66fa926fe9c19a50937f55.jpg) \nFigure 1 | Relationship between oxygen vacancy concentration and Co–O bond covalency. As the oxidation state of Co is increased through $\\mathsf{S r}^{2+}$ substitution, the C $\\cdot\\circ3\\mathsf{d}/\\mathsf{O}2\\mathsf{p}$ band overlap is increased (covalency increases) and the Fermi level decreases into the $\\mathsf{C o3d}/\\mathsf{O2p}\\pi^{\\star}$ band, creating ligand holes. Oxygen is released from the system resulting in oxygen vacancies and pinning the Fermi level at the top of the Co $\\mathsf{,3d/O2p}\\pi^{\\star}$ band61. \n\n1 $(a_{P}$ indicates the parameter of the perovskite subcell) supercell in LSCO28. The anion-deficient layers manifest themselves as faintly darker stripes in the HAADF-STEM images (marked with arrowheads in Fig. 2f,g), which according to Kim et al.32 is related to the structural relaxation in these planes. The anion-deficient layers form nanoscale-twinned patterns in both the LSCO28 and SCO samples (Fig. 2f,g). In general, the crystallographic observations on the LCO and LSCO samples are in agreement with the $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ phase diagram33. However, in contrast to the earlier reported $\\mathrm{Sr}_{2}\\mathrm{Co}_{2}\\mathrm{O}_{5}$ brownmillerite or hexagonal $\\mathrm{Sr}_{6}\\mathrm{Co}_{5}\\mathrm{O}_{15}$ phases34,35, the SCO sample demonstrates another type of oxygen vacancy ordering. The $[010]_{\\mathrm{p}}$ SAED pattern of SCO (Fig. 2d, top) is strongly reminiscent to that of the $L n_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ ( $\\mathrm{'}L n=\\mathrm{Sm\\mathrm{-}Y b},$ Y) perovskites with the $\\boldsymbol{I4/}$ mm \u0002m $2a_{\\mathrm{p}}\\times2a_{\\mathrm{p}}\\times4a_{\\mathrm{p}}$ supercell33,36,37. A detailed deconvolution of this SAED pattern into contributions from the twinned domains is presented in Supplementary Fig. 1. This supercell also allows complete indexing of the powder X-ray diffraction pattern of SCO (Supplementary Fig. 2). The layered ordering of the oxygen vacancies in the LSCO28 and SCO samples was directly visualized using annular bright-field STEM (ABF-STEM) imaging (Fig. 3a,b). In both structures the anion-complete $(\\mathrm{CoO}_{2})$ and anion-deficient $(\\mathrm{CoO}_{2-\\delta})$ layers can be clearly distinguished, alternating along the $c$ -axis of the tetragonal supercells. However, establishing the exact ordering patterns of the oxygen atoms and vacancies in these $\\left(\\mathrm{CoO}_{2-\\delta}\\right)$ layers requires more detailed neutron powder diffraction investigation. \n\n![](images/0d019a42eae2e8421828fd4a1b1df375b6069140470af1d3d0daced5f0b818c4.jpg) \nFigure 2 | Structural characterization of $\\mathbf{La}_{1-x}\\pmb{\\mathbb{S}}\\mathbf{r}_{x}\\mathbf{CoO}_{3-\\delta}$ . (a) Powder $\\mathsf{X}$ -ray diffraction patterns for $\\mathsf{L a}_{1-x}\\mathsf{S r}_{x}\\mathsf{C o O}_{3-\\delta}$ $\\quad0\\leq x\\leq1)$ . The reflection from ${\\mathsf{C o}}_{3}{\\mathsf{O}}_{4}$ is marked with an asterisk. $(b-d)$ SAED patterns of LSCO82 (b), LSCO28 (c) and SCO (d). The reflections of the basic perovskite structure are indexed. The $[\\bar{1}10]_{\\mathsf{p}}$ SAED pattern of LSCO82 shows weak $\\mathsf{G}_{\\mathsf{p}}\\pm1/2<111>\\mathsf{\\Lambda}_{\\mathsf{p}}$ -type reflections ( $\\mathsf{G}_{\\mathsf{p}}$ —reciprocal lattice vector of the perovskite structure) characteristic of the $a^{-}a^{-}a^{-}$ octahedral tilting distortion of the perovskite structure. The $[010]_{\\mathsf{p}}$ SAED pattern of LSCO28 demonstrates the orientationally twinned $\\mathsf{G}_{\\mathsf{p}}\\pm1/2<001>\\mathsf{\\Omega}_{\\mathsf{p}}$ superlattice reflections resulting in the P4/mmm $a_{\\mathsf{p}}\\times a_{\\mathsf{p}}\\times2a_{\\mathsf{p}}$ supercell. The superstructure in the $[010]_{\\mathsf{p}}$ SAED pattern of SCO can be described with the $\\mathsf{G}_{\\mathsf{p}}\\pm n/4<201>\\mathsf{\\Omega}_{\\mathsf{p}}$ (n—integer) and $\\mathsf{G}_{\\mathsf{p}}\\pm1/2<110>_{\\mathsf{p}}$ superstructure vectors corresponding to the orientationally twinned I4/mmm $2a_{\\mathsf{p}}\\times2a_{\\mathsf{p}}\\times4a_{\\mathsf{p}}$ supercell (see details in Supplementary Fig. 1). Note that the $\\mathsf{G}_{\\mathsf{p}}\\pm1/2<110>_{\\mathsf{p}}$ superlattice reflections are barely visible in the $[\\bar{1}10]_{\\mathsf{p}}$ SAED patterns of SCO, but the intensity profile (shown as insert in d) along the area marked with the white rectangle demonstrates their presence undoubtedly. (e–g) $[010]_{\\mathsf{p}}$ HAADF-STEM images of LSCO82 (e), LSCO28 $(\\pmb{\\uparrow})$ and SCO $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ . The image of LSCO82 shows uniform perovskite structure, whereas the images of LSCO28 and SCO show faint darker stripes spaced by $2a_{\\mathsf{p}}$ (marked by arrowheads) indicating nanoscale-twinned arrangement of the alternating $(\\mathsf{C o O}_{2})$ perovskite layers and $(\\mathsf{C o O}_{2-\\delta})$ anion-deficient layers. Scale bars are $5\\mathsf{n m}$ . \n\n![](images/36d6145e57268fa40a26a3f493fc3062e93cfab16076fe2ba5d2a4c57ef25f1c.jpg) \nFigure 3 | ABF-STEM imaging of oxygen vacancy ordering in $\\mathbf{La}_{1-x}\\mathbf{Sr}_{x}\\mathbf{CoO}_{3-\\delta}$ ${\\bf(}x=0.8$ , 1.0). (a) $[001]_{\\mathsf{p}}$ ABF-STEM image of LSCO28 showing the cation and anion sublattices. The contrast is inverted in comparison with the HAADF-STEM images. The assignment of the atomic columns is shown in the enlargement at the top right corner. Half of the perovskite $(\\mathsf{C o O}_{2})$ layers appear brighter indicating oxygen deficiency (marked with white arrowheads). The complete $(\\mathsf{C o O}_{2})$ layers and anion-deficient $(\\mathsf{C o O}_{2-\\delta})$ layer alternate (see the ABF intensity profile below, the anion-deficient layers are marked with black arrowheads) resulting in doubling of the perovskite lattice parameter in the direction perpendicular to the layers. (b) $[001]_{\\mathsf{P}}$ ABF-STEM image of SCO showing layered anion-vacancy ordering. The $(\\mathsf{C o O}_{2-\\delta})$ layers are marked with the white arrowheads and demonstrate the contrast clearly distinct from that of the $\\mathrm{(}\\mathsf{O O}_{2})$ layers. The assignment of the atomic columns is shown in the enlarged part at the bottom left. \n\nIn order to understand the effects of $\\operatorname{Sr}^{2+}$ substitution on oxygen vacancy concentrations in $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta},$ , iodometric titrations were performed. It should be noted that processing conditions affect the oxygen content and oxidation state of cobalt significantly through equation 1. The results of the iodometric titrations are presented in Table 1. As can be seen, there is both an increase in the bulk oxidation state of Co as well as an increase in the concentration of oxygen vacancies as lower valence $\\operatorname{Sr}^{2+}$ is substituted for $\\mathrm{La}^{3+}$ . The high concentration of oxygen vacancies in $\\mathrm{SrCoO}_{2.7}$ corroborates their pronounced layered ordering. \n\nMicrostructural characterization. The overall morphology of the LSCO series was investigated with bright-field TEM images, presented in Supplementary Fig. 3. The samples consist of highly agglomerated and partially sintered nanoparticles with size ranging from $20{-}50\\mathrm{nm}$ to few hundred nanometres. The LCO and SCO materials demonstrate somewhat larger and more sintered crystallites compared with those of the mixed LSCO samples. HAADF-STEM and ABF-STEM images of the surface structure of LCO and SCO are shown in Supplementary Fig. 4, where the particles remain crystalline at the surface and for SCO the anion-deficient layers, evident through the nanoscale-twinned domain columns, extend to the surface. Brunauer–Emmett–Teller surface areas measured through $\\Nu_{2}$ adsorption showed similar surface areas for all samples of $3.1\\mathrm{\\bar{-}}4.5\\mathrm{m}^{2}\\mathrm{g}^{-1}$ (Supplementary Table 2). This surface area is approximately half the surface area of the materials reported in our previous studies, which results from the higher calcination temperatures used for the LSCO series than the previously investigated $\\mathrm{LaCoO}_{3}.$ , ${\\mathrm{LaNiO}}_{3}$ , $\\mathrm{LaMnO}_{3}$ and $\\mathrm{LaNi}_{0.75}\\mathrm{Fe}_{0.25}\\mathrm{O}_{3}$ . \n\n
Table 1 | Oxygen vacancy concentration, S, and cobalt oxidation state, y.
x in La1-xSrxCoO3-88y
0 0.2 0.4 0.6 0.8-0.01±0.01 3.01±0.01
0.01±0.01 3.18 ± 0.02
0.05 ± 0.04 3.30 ±0.08
0.09 ± 0.01 3.43 ± 0.01 0.16 ± 0.01 3.48 ± 0.02
0.30±0.03 3.40 ±0.06
1.0 Error is based on the s.d. of triplicate measurements.
\n\nElectrochemical characterization. In order to better understand the role of oxygen vacancies in $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ during electrochemical applications, the intercalation of oxygen in LSCO was studied using cyclic voltammetry in Ar saturated $1\\mathrm{M}\\ \\mathrm{KOH}$ solutions. The insertion and removal of oxygen ions appear as redox peaks in Fig. 4a. It is apparent that an increase in the oxygen vacancy concentration as $\\mathrm{\\hat{S}r}^{2+}$ is substituted for $\\mathrm{La}^{3+}$ in LSCO increases the tendency for oxygen intercalation as indicated through the high current densities measured in the intercalation region. In addition, it is interesting to note that the position of the intercalation redox peaks shifts to higher potentials with increased oxygen vacancies which can be described through the common pseudocapacitive Nernst Equation: \n\n$$\n{\\cal E}={\\cal E}^{0}+{\\frac{R T}{n{\\cal F}}}\\mathrm{ln}{\\frac{\\sigma}{1-\\sigma}}\n$$ \n\nwhere, $E$ represents the measured potential for oxygen intercalation, $\\ {\\overset{\\bullet}{\\boldsymbol{E}}}{}^{0}$ represents the standard potential for oxygen intercalation, $R$ is the universal gas constant $(8.3145\\mathrm{J}\\dot{\\mathrm{K}}^{-1}$ $\\mathrm{mol}^{-1}$ ), $T$ is the temperature during the measurement, $F$ is \n\n![](images/57142aac58dd997fbee857435b38924f3bdd27c6b0222a0c71b062e18c034679.jpg) \nFigure 4 | Electrochemical oxygen intercalation into $\\mathbf{La}_{1-x}\\pmb{S}\\mathbf{r}_{x}\\mathbf{C}\\mathbf{o}\\mathbf{O}_{3-\\delta}.$ (a) Cyclic voltammetry at $20\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ for each member of LSCO in Ar saturated $1M\\mathsf{K O H}$ . The redox peaks, indicative of the insertion and removal of oxygen from the crystal, shift to higher potentials with increasing $\\mathsf{S r}^{2+}$ and oxygen vacancy concentrations. (b) Oxygen diffusion rates measured at $25^{\\circ}C$ chronoamperometrically. The diffusion rate increases with $\\mathsf{S r}^{2+}$ and oxygen vacancy concentrations as well. Error bars represent the standard deviation of triplicate measurements. \n\nFaraday’s constant $(96,485{\\mathrm{Cmol}}^{-1})$ , and $\\sigma$ is the occupancy fraction of accessible lattice vacancy sites38 for the reaction: \n\n$$\n\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}+2\\sigma\\mathrm{OH}^{-}\\rightleftharpoons\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta+\\sigma}+\\sigma\\mathrm{H}_{2}\\mathrm{O}+2\\sigma\\mathrm{e}^{-\\delta}\n$$ \n\nThis type of Nernst Equation is commonly associated with pseudocapacitive-type intercalation mechanisms, indicative of facile oxygen ion diffusion. \n\nThe diffusion rates of oxygen ions in LSCO were measured chronoamperometrically based on a bounded 3D solid-state diffusion model with a rotating disk electrode (RRDE) rotating at 1,600 r.p.m. in Ar saturated 1 M KOH39–41. These results are presented in Fig. 4b, and a more detailed description of the theory behind the model is included as Supplementary Fig. 5. It was found that SCO, with a vacancy concentration of $\\delta=0.30\\pm0.03$ , had a diffusion rate of $\\mathrm{D}{=}1.2{\\pm}0.1\\times10^{-12}\\mathrm{cm}^{2}\\mathrm{s}^{-1}$ at room temperature, which is $\\sim40\\times$ faster than for LCO, with a complete oxygen sublattice and a diffusion rate of $\\mathrm{D}{=}3\\pm1\\times10^{-14}\\mathrm{cm}^{2}s^{-1}$ . As a general comment, diffusion coefficients in the range of $10^{^{\\circ}-9}$ to $10^{-14}\\mathrm{cm}^{2}s^{-1}$ have been found as usual values for the short circuit diffusion of oxygen along high-diffusivity pathways, including grain boundaries24. Although it is unclear whether the measured diffusion rates are from bulk diffusion or along grain boundaries, isotope tracer studies have shown that diffusion rates trend in the order of surface oxygen $>$ oxygen at grain boundaries $>$ bulk oxygen in perovskite systems, and thus the fast diffusion rates found in this study represent the lower boundary on the mobility of oxygen at the surface42. Further, the crystallite size and density of grain boundaries is relatively consistent across the LSCO series due to the similar synthetic conditions, indicating that the diffusion rates can at least be compared against each other. The results indicate that the diffusion rates scale with $\\mathrm{{Sr}}$ concentration because of the correlation with vacancies and $\\mathrm{{Sr}}$ content. The results highlight the benefit of substitution of a lower valence ion into the A-site as an effective means of increasing the mobility of oxygen in perovskite oxide electrodes. \n\nThe electrolysis of water. The OER activities for LSCO and for a commercial $\\mathrm{IrO}_{2}$ sample were quantified through cyclic voltammetry in $\\mathrm{O}_{2}$ saturated $0.1\\mathrm{M}\\mathrm{\\KOH}$ at $1,600~\\mathrm{r.p.m}$ , as shown in Fig. 5a. Each material was mixed at a mass loading of $30\\mathrm{wt\\%}$ perovskite on a mesoporous nitrogen-doped carbon (NC) or onto Vulcan Carbon XC-72 (VC) for stability measurements. An evaluation of the carbon loading and total mass loading is presented in Supplementary Fig. 6, Supplementary Table 5 and the Supplementary Discussion. There is a shift towards more active Tafel slopes with increasing $\\operatorname{sr}$ content, with LCO and $\\mathrm{IrO}_{2}$ having similar Tafel slopes of $\\partial V/\\partial\\ln i=58\\mathrm{mV}\\mathrm{dec}^{-1}$ $(\\approx2R T/F)$ which decreases towards SCO with a Tafel slope of $\\partial V/\\partial\\ln i{=}31\\mathrm{mV}\\mathrm{dec}^{-1}\\left(\\approx R T/F\\right)$ . This shift of Tafel slope for the OER may be indicative of the facile surface kinetics for oxygen exchange with increasing vacancy content, whereby OER kinetics that are limited by high-coverage Langmuir like behaviour where surface oxygen is not exchanged rapidly $(\\theta\\to1)$ ) show Tafel slopes of $2R T/F.$ . In contrast, those materials showing more rapid surface oxygen exchange in the intermediate coverage Temkin condition range $(0.2<\\theta<0.8)$ have slopes of ${\\cal R}T/{\\cal F}^{9}$ . The specific activities at an overpotential of $400\\mathrm{mV}$ , based on perovskite surface area from BET, are presented in Fig. 5b. It is clear that substitution of $\\mathrm{Sr}^{2+}$ for $\\mathrm{La}^{3+}$ in LSCO, and thereby the creation of oxygen vacancies, is beneficial to the OER, with the fully substituted $\\mathrm{SrCoO}_{2.7}$ at $28.4\\mathrm{mA}\\mathrm{cm}^{-2}\\mathrm{_{ox}^{}}$ which is $\\sim6\\times$ more active than $\\mathrm{LaCoO}_{3.005}$ $(4.3\\operatorname{mA}\\operatorname{cm}^{-2}\\operatorname{\\omega}_{\\mathrm{ox}})$ , $\\sim23\\times$ more active than the commercial $\\mathrm{IrO}_{2}$ sample $(1.2\\mathrm{mA}\\mathrm{cm}^{-2}\\mathrm{_{ox}^{})}$ , and $\\sim1.5\\times$ more active than previously reported high-vacancy concentration cobaltite perovskites $(\\mathrm{Ba}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{Co}_{0.8}\\mathrm{Fe}_{0.2}\\mathrm{O}_{2.6}$ : $\\stackrel{\\cdot}{\\sim}20\\mathrm{mAcm}^{-2}\\mathrm{ox};$ $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{2.85}$ : $\\sim20\\mathrm{mA}\\mathrm{cm}^{-2}\\mathrm{_{ox}^{}})$ (refs 14,43). In addition, due to the small particle size from the reverse-phase hydrolysis synthesis, $\\mathrm{SrCoO}_{2.7}$ $(3.6\\mathrm{m}^{2}\\mathrm{g}^{-1})$ had a mass activity of $1,020\\pm20\\mathrm{mAmg^{-1}\\mathrm{_{ox}^{}}}$ at $+1.63\\mathrm{V}$ versus the reversible hydrogen electrode (RHE), which is $\\mathord{\\sim}2\\times$ more active than BSCF with a similar surface area $(\\sim500\\mathrm{mA}\\mathrm{mg}^{-1}\\mathrm{_{ox}},3.9\\mathrm{m}^{2}\\mathrm{g}^{-1})$ (ref. 14). To verify that the measured current was due only to the OER, and not to side-reactions or corrosion of the electrode material, rotating-ring-disk (RRDE) cyclic voltammetry was performed with a Pt ring poised at $+0.4\\mathrm{V}$ versus RHE, whereby $\\mathrm{O}_{2}$ generated at the disk from the OER is collected and reduced at the ring. The results for $\\mathrm{SrCoO}_{2.7}/\\mathrm{NC}$ and $\\mathrm{IrO}_{2}/$ NC are shown in Fig. 5c. The collection efficiency for both $\\mathrm{SrCoO}_{2.7}/\\mathrm{NC}$ and $\\mathrm{IrO}_{2}/\\mathrm{NC}$ was $37\\%$ , which was equal to the collection efficiency measured during calibration of the RRDE for the oxidation of $\\mathbf{0.3\\:mM}$ ferrocene-methanol in $0.1\\mathrm{M}$ KCl. Therefore, we can confirm that the current is exclusively due to the generation of oxygen on the SCO or the $\\mathrm{IrO}_{2}$ surface within the precision of the RRDE measurements. \n\nThe stability of $\\mathrm{SrCoO}_{2.7}$ and of the carbon supports under OER conditions were tested galvanostatically at $10\\mathrm{\\dot{A}g^{-1}}_{\\mathrm{ox}}$ ox and $1{,}600\\ \\mathrm{r.p.m}$ ., shown in Fig. 5d. As is readily apparent, both the \n\n![](images/8ad5b8ba7a6c34ed1ea8dc9b9691506799fa2b212bfe27fce8719079116caedf.jpg) \nFigure 5 | Electrochemical characterization of $\\mathbf{La}_{1-x}\\pmb{\\mathbb{S}}\\mathbf{r}_{x}\\mathbf{CoO}_{3-\\delta}$ for the OER. (a) Capacitance corrected specific OER current densities in $\\mathsf{O}_{2}$ saturated 0.1 M KOH, a scan rate of $10\\mathrm{mVs}^{-1}$ , and $\\omega=1,600$ r.p.m., for $30\\mathrm{wt\\%}$ $\\mathsf{L a}_{1-x}\\mathsf{S r}_{x}\\mathsf{C o O}_{3-\\delta}$ supported on 2 at. $\\%N C$ . The performance of $30\\mathrm{wt\\%}$ $\\mathsf{I r O}_{2}$ supported on 2 at. $\\%N C$ is included as a reference. (b) Specific activities of $\\mathsf{L a}_{1-x}\\mathsf{S r}_{x}\\mathsf{C o O}_{3-\\delta}$ and $\\mathsf{I r O}_{2}$ at a $400\\mathsf{m V}$ overpotential for the OER $(1.63\\vee$ versus RHE). (c) Confirmation of oxygen generation using a RRDE. The disk has a thin layer of either $30\\mathrm{wt\\%}$ $\\mathsf{S r C o O}_{2.7}/\\mathsf{N C}$ or $30\\mathsf{w t\\%}\\mathsf{l r O}_{2}/\\mathsf{N C}$ and the ring is Pt. $\\mathsf{O}_{2}$ is generated at the disk then reduced back to $\\mathsf{O H}^{-}$ at the ring which is poised at $+0.4\\vee$ versus RHE. The collection efficiency of the RRDE was found to be $37\\%$ . (d) Galvanostatic stability at $10\\mathsf{A}\\mathsf{g}^{-1}\\mathsf{\\Gamma}_{\\mathsf{o}\\mathsf{x}}$ and $\\omega=1,600$ r.p.m. of $\\mathsf{S r C o O}_{2.7}$ and $\\mathsf{I r O}_{2}$ supported on two different carbons, $2a t\\%$ nitrogendoped NC and non-nitrogen doped VC. It is evident that both carbons are unstable at the anodic potentials of the OER, with rapid degradation occurring for all samples once the potential is $>1.65\\lor$ versus RHE. The high activity and stability of $\\mathsf{S r C o O}_{2.7}$ on NC allows the electrode to generate $10\\mathsf{A}\\mathsf{g}^{-1}\\mathsf{\\Gamma}_{\\mathsf{o}\\mathsf{x}}$ of current without reaching this potential, which results in a relatively stable catalyst for $24\\mathsf{h}$ of operation. For all electrochemical studies the mass loading of the electrode was $51\\upmu\\mathrm{g}_{\\mathrm{tot}}\\mathsf{c m}^{-2}\\mathsf{g e o m}$ Error bars represent the standard deviation of triplicate measurements. \n\nNC and VC are not stable carbon supports for the OER, and we hypothesize that this dominates the mechanism of failure for the composite electrodes at potentials $\\mathrm{~>~+~}1.65\\mathrm{~V~}$ versus RHE. However, other variables may be responsible for the failure of the electrodes, including the degradation of the Nafion binder due to the oxidative conditions and the rapid rotation of the electrode. $\\mathrm{SrCoO}_{2.7},$ however, appears to be active enough to sustain the OER for $24\\mathrm{h}$ at $10\\mathrm{\\dot{A}g^{-1}}_{\\mathrm{ox}}$ without reaching the potential where rapid carbon corrosion occurs. Further studies are needed in order to better understand the variables that influence catalyst stability, however, it is clear that carbon may not be the optimal catalyst support under the OER conditions. In addition, it should be noted that $\\mathrm{IrO}_{2}$ which has become the benchmark comparison for OER catalysts is not stable under the anodic conditions of the OER, forming the soluble complex anion $\\mathrm{IrO}_{4}^{2-}$ in alkaline environments44. This is demonstrated in the stability plot in Fig. 5d, where even the unsupported $\\mathrm{IrO}_{2}$ electrode failed after $\\sim14\\mathrm{h}$ . \n\nThe catalytic activity towards the OER was found to strongly correlate with the oxygen diffusion rate and the vacancy concentration, $\\delta_{:}$ , presented in Fig. 6c,d. On the basis of these correlations, we hypothesize a new OER mechanism in Fig. 6a based on the exchange of lattice oxygen species that takes into account the role of surface oxygen vacancies and B–O bond covalency (lattice oxygen-mediated OER, LOM). In contrast to the general adsorbate evolution mechanism (AEM) which considers only the redox activity of the transition metal B-site, we find a better electronic explanation arises when the covalency of the $\\mathrm{M-O}$ bond is considered, indicative of the overlap of the $\\mathrm{Co}\\ 3\\mathrm{d}$ and O $2{\\mathfrak{p}}$ bands in the crystal, as first proposed by Matsumoto et al.14,45. As the oxidation state of $\\scriptstyle{\\mathrm{Co}}$ is increased, the d orbitals of the Co ion have a greater overlap with the s, p orbitals of the $\\mathrm{O}^{2-}$ ion, leading to the formation of $\\pi^{*}$ and $\\sigma^{*}$ bands, as described through Fig. 1 and in the partial density of states (PDOS) diagrams in Fig. 6a and refs 11,13,22,43. When the overlap is great enough, ligand holes (oxygen vacancies) are formed and the metal $\\operatorname{\\bar{3}d}\\ \\pi^{\\bar{*}}$ band can no longer be treated as isolated in energy from the oxygen O ${\\mathfrak{2}}{\\mathfrak{p}}\\ \\pi^{*}$ band. At this point, the surface of the crystal and bound intermediates can be treated as a single energy surface, where the Fermi energy can be modulated through the hybridized $\\mathrm{Co}\\ 3\\mathrm{d-O}\\ 2\\mathrm{p}\\ \\pi^{*}$ band with applied electrical potential, opening up the possibility for lattice oxygen redox activity46. A recent in situ ambient pressure XPS study has confirmed the validity of this model in perovskites and other oxides47,48. In addition, oxygen redox activity has been observed in LSCO with high $\\mathrm{Sr}^{2\\mp}$ content in the regime of oxygen intercalation, which occurs approximately at the onset potentials of the OER in these materials49–51. \n\nTo test the validity of this lattice oxygen-mediated mechanism (LOM) and identify the rate-determining step, we modelled the reaction pathway using density functional theory52. Supplementary Fig. 7a shows that $\\mathrm{OH}^{-}(\\mathrm{aq})$ tends to electrochemically fill the surface O vacancies of LSCO under the operational electrode potential of OER, as described through reaction 3 and LOM 1 in Fig. 6a, leading to an in situ surface–layer stoichiometry close to that of stoichiometric bulk $\\mathrm{ABO}_{3}$ . Consequently, we begin by constructing the [001] $\\mathrm{BO}_{2}$ terminated surfaces (Supplementary Fig. 8a) with $\\textstyle{\\frac{1}{4}}$ ML OER intermediate adsorbates52 based on the $2\\times2\\times2$ cubic stoichiometric bulk LSCO for the initial identification of the reactivity trend and reaction mechanism53. We subsequently investigated more realistic bulk phases with oxygen vacancies and various surface structures, which we find do not alter the preference of LOM over AEM; further details of these computations are provided in the Supplementary Methods. \n\n![](images/3fa9315fde11dec40644a968c0231fbc8a3341052f5a59c30238d65ab37db269.jpg) \nFigure 6 | Oxygen evolution mechanisms on $\\mathbf{La}_{1-x}\\pmb{S}\\mathbf{r}_{x}\\mathbf{C}\\mathbf{o}\\mathbf{O}_{3-\\delta}$ and activity correlations. (a) $\\mathsf{A E M}^{14,62}$ . In the AEM, the transition metal 3d bands are significantly higher in energy than the $\\textsf{O}2\\mathsf{p}$ band in the lattice as shown qualitatively in the PDOS diagram below the mechanism. Because of this, all intermediates during the reaction originate from the electrolyte and Co in the active-site undergoes the catalytic redox reactions. This allows Co to access a higher oxidation state of ${\\mathsf{C o}}^{4+}$ in Step 1 (a) AEM. As the covalency of the material increases, the transition metal 3d bands are lowered into the $\\mathtt{O2p}$ band in the lattice, where the Fermi energy is pinned at the top of the $02\\mathsf{p}$ band through generation of oxygen vacancies61. In contrast, in Step 1 (b) of the LOM, applying an anodic potential oxidizes a ligand hole in the $\\textsf{O}2\\mathsf{p}$ band allowing for exchange of lattice oxygen to the adsorbed intermediate to yield the superoxide ion $\\mathsf{O}_{2}^{-}$ rather than oxidizing Co to ${\\mathsf{C o}}^{4+}$ . This is shown qualitatively in the PDOS diagram below the mechanism where Step 1 of the LOM is separated into an electrochemical (1E) step in which the ligand hole is generated and a chemical step (1C) in which the lattice oxygen is exchanged into the adsorbed intermediate. For both (a,b) lattice species are shown in red and electrolyte species are shown in blue. In the PDOS diagrams, the electrolyte species are shown to the left of the energy axis and the crystal PDOS are shown to the right. (c) Correlation of oxygen evolution activity with the vacancy parameter $\\delta.$ The vacancy parameter is indicative of the underlying electronic structure where vacancies are generated when there is significant Co 3d and $\\textsf{O}2\\mathsf{p}$ band overlap. (d) Correlation of oxygen evolution activity with the oxygen ion diffusion rate, indicating that increased surface exchange kinetics trend with increased OER activity. Error bars represent standard deviation of triplicate measurements. \n\nOur results show that Step 1 differentiates the LOM, involving the intermediate with adsorbed –OO and lattice O vacancies 1 $\\mathrm{{\\tilde{{I}}}_{1}}$ in Figs 6a and 7a), from the AEM, involving the generally proposed adsorbed $^{-0}$ $\\mathrm{{\\tilde{L}}_{0}}$ in Figs 6a and $7\\mathrm{a}$ ). Therefore, the relative stabilities (free energy difference, $\\Delta G$ ) between these two isomeric intermediates are key to identifying if OER proceeds via the LOM or AEM for a given LSCO composition. This identification approach has been successfully used to demonstrate the preference of LOM on ${\\mathrm{LaNiO}}_{3}$ (ref. 52). The computed values of $\\bar{\\Delta\\mathrm{G}}$ are shown as a function of LSCO composition in Fig. 7b, which illustrates two key points. First, increasing $x$ in $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ reduces the O vacancy formation energy and therefore bulk stability. Second, $\\Delta G$ decreases with the decreased bulk stability, becoming negative between $0.25}3+$ . In the LOM step 1, the transfer of a surface $\\mathrm{~O~}$ to form a surface O vacancy and the single-bonded –OO adsorbate decreases the nominal valence charge on the $\\scriptstyle{\\mathrm{Co}}$ to $^{3+}$ . Thus, the LOM pathway has higher stability than the AEM pathway, particularly for those LSCO with large $x$ . The relative stability of $\\mathrm{I}_{1}$ to $\\mathrm{I}_{0}$ is also apparent in the projected density of states of the d-band for the active surface $\\scriptstyle{\\mathrm{Co}}$ and the overall $\\mathfrak{p}$ -band for its ligand O (Fig. 7c). The overlap of the peaks in these two bands indicates the orbital hybridization and ${\\mathrm{Co-O}}$ binding. For the AEM intermediate on $\\mathrm{LaCoO}_{3}$ $\\left(\\mathrm{I}_{0}\\right)$ , the strong overlap of peaks in the spin-up (down) bands centred around $\\mathrm{~\\bar{~}{~-~}1{\\mathrm{eV}}~}(\\mathrm{0}.5\\mathrm{eV})$ indicates the strong ${\\mathrm{Co-O}}$ covalent bonding state. These overlaps, however, are significantly weakened for $\\mathrm{I}_{1}\\mathrm{:}$ , consistent with the stability. The reverse is true for the LSCO with low stability. Compared with $\\mathrm{I}_{0}$ for $\\mathsf{S r C o O}_{3}$ , $\\mathrm{I}_{1}$ preserves a significant overlap of spin-up state around $-1\\mathrm{eV}$ , but has negligible overlap of the unoccupied spin-down states, which are anti-bonding in character, indicating the greater stability of $\\mathrm{I}_{1}$ . \n\n![](images/09567b80cbf1b278c34640fc1e1db0a3d0a32f026550b6761db7d84e4bafc522.jpg) \nFigure 7 | Density functional theory modelling of vacancy-mediated oxygen evolution on $\\mathbf{La}_{1-x}\\pmb{\\mathbb{S}}\\mathbf{r}_{x}\\mathbf{Co0}_{3-\\delta}$ (a) Surface configurations of the intermediate after AEM Step 1 $(\\mathsf{I}_{0})$ and the one after LOM Step 1 (I1). (b) The free energy change of $\\mathsf{I}_{1}$ over $\\mathsf{I}_{0}$ versus the O vacancy formation enthalpy in the bulk, for the cubic $\\mathsf{L a}_{1-x}\\mathsf{S r}_{x}\\mathsf{C o O}_{3-\\delta}$ (black mark), where $x=0$ , 0.25, 0.5, 0.75 and 1, with the rhombohedral $\\mathsf{L a C o O}_{3}$ and optimized $\\mathsf{S r C o O}_{2.75}$ phases; for $x=0.25$ and 0.75, the most energetic favourable vacancy site is selected; the O vacancy formation energy is calculated at the concentration of 1 per $2\\times2\\times2$ unit cell with respect to ${\\sf H}_{2}\\mathrm{O}(\\mathrm{g})$ and ${\\sf H}_{2}({\\bf g})$ at standard condition; using $\\mathsf{O}_{2}(\\mathsf{g})$ as the reference will shift the O vacancy formation enthalpy around $+2.5\\mathsf{e V}$ larger. (c) The density of states of d-band for the active surface Co and the overall $\\mathsf{p}$ -band for its ligand ${\\mathsf{O}},$ for $\\mathsf{L a C o O}_{3}$ and $\\mathsf{S r C o O}_{3}$ before and after the lattice oxygen exchange. (d) The OER free energy changes of LOM and AEM on $\\mathsf{S r C o O}_{3}$ at the concentration of ${\\frac{1}{4}}\\ M L,$ with indicated intermediates structures and potential-determining steps. \n\nTo understand the phase and stoichiometry effects on the relative stability of $\\mathrm{I}_{1}$ to $\\mathrm{I}_{0}$ , we perform the analogous calculations on the rhombohedral $\\mathrm{LaCoO}_{3}$ and the nonstoichiometric $\\mathrm{SrCoO}_{2.7}$ phases. The rhombohedral $\\mathrm{LaCoO}_{3}$ phase is modelled by optimizing an initial $2\\times2\\times2$ orthorhombic cell with octahedral rotation; the optimized structure exhibits a $_{\\mathrm{Co-O-Co}}$ angle of $162^{\\circ}$ and a $\\scriptstyle{\\mathrm{Co-O}}$ distance of $1.96\\mathring{\\mathrm{A}}$ , consistent with experimental measurements. The $\\mathrm{SrCoO}_{2.7}$ phase is approximated as $\\mathrm{SrCoO}_{2.75}$ , which can be modelled by relaxing the cubic $2\\times2\\times2\\ \\mathrm{SrCoO}_{3}$ structure with two oxygen vacancies. By comprehensively searching the vacancy ordering, we identify the most stable configuration as the presence of the two vacancies surrounding one $\\mathrm{Co}$ , which therefore leads to the formation of a tetrahedral $\\mathrm{CoO_{4}}$ linked to two tetragonal pyramidal $\\mathrm{CoO}_{5}$ units (Supplementary Fig. 8b). The lattice constant of this optimized $\\mathrm{SrCoO}_{2.75}$ is within $1.1\\%$ difference from that of the derived pseudocubic $\\mathrm{SrCoO}_{2.7}$ (Supplementary Table 1). This configuration is further validated by introducing two more vacancies to form $\\mathrm{SrCoO}_{2.5}$ in the same way, so as to maximize the number of tetrahedral $\\mathrm{CoO_{4}}$ . The relaxed $\\mathrm{SrCoO}_{2.5}$ shows alternating octahedral $(\\mathrm{CoO}_{2})$ and tetrahedral zigzag-like $(\\mathrm{CoO})$ layers with respect to the (001) direction of the reference cubic phase (Supplementary Fig. 8b), in full agreement with experimental observations. The $\\mathrm{SrCoO}_{2.75}$ slab is subsequently constructed by exposing the $(\\mathrm{CoO}_{2-\\delta})$ layer (Supplementary Fig. 8c), but with added oxygen anions to attain the correct stoichiometry (Supplementary Fig. 8d) to simulate the intercalation phenomenon as described by Supplementary Fig. 7a and LOM Step 3. As Fig. 7b shows, the octahedral rotation stabilizes the rhombohedral $\\mathrm{LaCoO}_{3}$ , leading to a slight increase in the oxygen vacancy formation energy and $\\Delta G$ . In the case of $\\mathrm{SrCoO}_{2.75}$ , the existing oxygen deficiency increases the oxygen vacancy formation energy by $0.33\\mathrm{eV}$ , while slightly stabilizing $\\mathrm{I}_{1}$ relative to ${\\mathrm{I}}_{0},$ compared with $\\mathrm{SrCoO}_{3}$ . The lattice constant of the predicted $\\mathrm{SrCoO}_{2.75}$ is $0.7\\%$ larger than that of $\\mathrm{SrCoO}_{3}$ leading to the slightly weaker adsorption strength and lower stability of $\\mathrm{I}_{0}$ (ref. 54). However, the small magnitude of this change indicates the similar reactivity of $\\mathsf{S r C o O}_{3}$ to that of the intercalated $\\mathrm{SrCoO}_{2.7}$ surface under OER conditions. From the above analysis, we conclude that neither the phase nor the non-stoichiometry alters the qualitative stability of $\\mathrm{I}_{1}$ to ${\\mathrm{I}}_{0},$ although it leads to a horizontal shift in the overall trend of bulk vacancy formation to higher energetic cost. \n\nWe also compute the free energy of electrochemical OER on $\\mathsf{S r C o O}_{3}$ to demonstrate the switch in the reaction mechanism due to the relative change in $\\mathrm{I}_{1}$ -to- $\\cdot\\mathrm{I}_{0}$ stability on $\\mathrm{SrCoO}_{2.7}$ . In accordance with the procedure in ref. 53 the free energy of each reaction step is determined by $\\varDelta G_{R}=E+\\varDelta Z P E-T\\varDelta\\bar{S}-e U_{\\mathrm{RHE}}$ at $U_{\\mathrm{RHE}}=\\bar{+}1.23\\mathrm{V}$ , where $\\varDelta E$ is the DFT-computed enthalpy change for $\\begin{array}{l l}{{\\frac{1}{4}}}&{{\\mathrm{ML}}}\\end{array}$ of intermediates relative to $_{\\mathrm{H}_{2}\\mathrm{O}}$ and $\\mathrm{H}_{2}$ molecules (Supplementary Table 3) and $\\angles{1}{Z P E-T}\\angles{S}$ gives the corrections for zero-point energy and entropy of both adsorbates and $\\mathrm{H}_{2}(\\mathbf{g})$ and $\\mathrm{H}_{2}\\mathrm{O}$ (l) under OER conditions (Supplementary Table 4) (refs 53,54). The largest free energy is the estimated overpotential, $\\eta$ . As $\\varDelta G_{R}$ is independent of the initial OER intermediate considered, we—in practice—start from the stoichiometric hydroxylated surface (the surface before LOM 1). Figure 7d shows that the first step $(-\\mathrm{OH}$ to $\\mathrm{I}_{0}^{\\ }$ ) of AEM is the potential-determining step, with $\\eta=0.4\\:\\mathrm{V}$ . However, it becomes remarkably energetically favourable to follow LOM 1, forming the superoxide-like –OO $(V_{\\mathrm{O}})$ adsorbates $\\left(\\mathrm{I}_{1}\\right)$ with an O-to-O bond length of $1.28\\mathring{\\mathrm{A}}$ . Therefore, LOM is the relevant mechanism for $\\mathrm{SrCoO}_{2.7}$ . Once $\\mathrm{I}_{1}$ forms, it requires small energetically uphill and downhill reactions, respectively, to evolve back to $-\\mathrm{OH}\\ \\bar{(}V_{\\mathrm{O}})$ and electrochemically fill the vacancy by $\\mathrm{OH^{-}}$ (aq) in Step 2 and 3 of the LOM. This electrochemical surface hydroxylation during Step 3 occurs concomitantly with an electron transfer to leave the surface in a neutral state. The subsequent step of electrochemical deprotonation is identified as the potential-determining step, similar to the results for ${\\mathrm{LaNiO}}_{3}$ (ref. 52). Further, the computed overpotential of $0.22\\mathrm{V}$ is fully consistent with experiments. \n\nWe note that consideration of modified surface configurations, which may occur under operating conditions, could lead to different values of $\\Delta G$ . For example, full surface hydroxylation can further decrease the value of $\\Delta G$ due to oxidation of the surface Co, making the LOM more favourable, while moderate protonation of surface oxygen can increase $\\Delta G$ by donating electrons to the surface. In addition, the O-to-O overbinding effects in the superoxide formation $\\left(\\mathrm{I}_{1}\\right)$ by RPBE can increase $\\bar{\\Delta}\\mathsf{G}$ by $-0.3\\mathrm{eV}$ (ref. 55), while the use of $\\mathrm{GGA}+U_{\\mathrm{eff}}$ can lead to the weaker adsorption strength of $\\mathrm{I}_{0}\\mathrm{:}$ , decreasing $\\Delta G$ by $>0.3\\mathrm{eV}$ (ref. 56). Nevertheless, the behaviour of the model surfaces expected to be qualitatively correct for these systems, and also independent of exchange correlation functional, as demonstrated for $\\mathrm{LaNiO}_{3}$ . \n\nInterestingly, significant oxygen deficiencies of the LSCO series begin to appear at $x=0.4$ , matching well with the predicted transition from the AEM to LOM at $0.25}0.4$ from that when $x{<}0.4$ . Our work thus provides a strong theoretical framework, consistent with experiments, to describe the transition of the OER mechanism as a function of bulk stability. Further discussion about the applicability of this mechanism to other metal oxide catalysts is included in Supplementary Fig. 9 and in the Supplementary Discussion. \n\n# Discussion \n\nWe have demonstrated that oxygen vacancy defects are a crucial parameter in improving the electrocatalysis of oxygen on metal oxide surfaces, whereby they may control the physical parameters of ionic diffusion rates and reflect the underlying electronic structure of the catalyst. The vacancy-mediated mechanism proposed offers insight into the design of highly active OER catalysts, and allows for the rationalization of the electrolysis of water using surface chemistry parameters, as described through the modulation of the Fermi energy through transition metal 3d and oxygen 2p partial density of states at the surface. As such, the role of oxygen vacancy defects cannot be ignored, and should be a critical component in the benchmarking of metal oxide oxygen electrocatalysts and the advancement of the mechanistic theory behind the OER. \n\n# Methods \n\nGeneral. All chemicals were used as received. Anhydrous ethanol and $5\\mathrm{wt\\%}$ Nafion solution in lower alcohols were purchased from Sigma-Aldrich. Lanthanum (III) nitrate hexahydrate $(99.999\\%^{\\cdot}$ , strontium (II) nitrate hexahydrate $(99.9\\%)$ , cobalt (II) nitrate hexahydrate $(99.9\\%)$ , tetrapropylammonium bromide $(98\\%)$ , tetramethylammonium hydroxide (TMAH) pentahydrate $(99\\%)$ , 2-propanol, potassium hydroxide, potassium iodide $(\\geq99\\%)$ , sodium thiosulfate (0.1 N), potassium iodate $(0.1\\mathrm{N})$ and hydrochloric acid were obtained from Fisher Scientific. Absolute ethanol (200 proof) was obtained from Aaper alcohol. The commercial $\\mathrm{IrO}_{2}$ sample was obtained from Strem Chemicals. Oxygen $(99.999\\%)$ and argon $(99.999\\%)$ ) gases were obtained from Praxair. VC was obtained from Cabot Corporation and the NC was prepared as reported elsewhere57. \n\nSynthesis of $\\mathbf{La}_{1-x}\\pmb{\\mathbb{S}}\\mathbf{r}_{x}\\mathbf{Co0}_{3-\\delta},$ $\\pmb{0}\\le\\pmb{x}\\le\\pmb{0.8}$ . $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ was synthesized following our previously reported reverse-phase hydrolysis approach16,17,27. Mixed metal hydroxides were prepared by reverse-phase hydrolysis of La, Sr and Co nitrates in the presence of an equimolar amount of tetraproprylammonium bromide (TPAB) dissolved in $1\\mathrm{wt\\%}$ TMAH. An $\\sim10\\mathrm{mM}$ solution of mixed metal nitrates of the appropriate stoichiometry was added dropwise at $\\sim1{-}2\\mathrm{ml}\\mathrm{min}^{-1}$ to $200\\mathrm{ml}$ of the $1\\mathrm{wt\\%}$ TMAH solution containing TPAB. The resulting precipitated mixed metal hydroxide nanoparticles were collected by centrifugation and washed with deionized water, followed by re-suspension in deionized water through probe sonication. The solution was frozen as a thin film on a rotating steel drum at cryogenic temperatures $(-79^{\\circ}\\mathrm{C})$ , and then lyophilized at $-10^{\\circ}\\mathrm{C}$ at a fixed pressure of $\\sim50$ mTorr for $20\\mathrm{h}$ . The lyophilized powder was calcined in a tube furnace under dehumidified air at a flow rate of $1\\dot{5}0\\mathrm{ml}\\mathrm{min}^{-1}$ for $^{5\\mathrm{h}}$ at $950^{\\circ}\\mathrm{C}$ . The resulting perovskites are then washed with ethanol followed by water and allowed to dry in an oven at $80^{\\circ}\\mathrm{C}$ overnight. \n\nSynthesis of $\\sin C00_{2.7}$ . Synthesis of $\\mathrm{SrCoO}_{2.7}$ followed a similar procedure to the one used above, but used a slower addition rate of metal nitrate solution to TMAH/ TPAB of $<0.5\\mathrm{ml}\\mathrm{min}^{-1}$ . In addition, the hydrolysis reaction was allowed to \n\nproceed for 5 days before collection by centrifugation. Finally, the flow rate of dehumidified air during calcination was adjusted to $20\\mathrm{ml}\\mathrm{min}^{-1}$ . \n\nMaterials characterization. Bulk crystal structures were determined through wide-angle X-ray diffraction (Rigaku Spider, Cu $\\operatorname{K}\\mathfrak{a}$ radiation, $\\lambda=1.5418\\mathrm{\\AA}$ ) and analysed with JANA2006 software58. The TEM samples were prepared by crushing the crystals in a mortar in ethanol and depositing drops of suspension onto holey carbon grid. Electron diffraction patterns, TEM images, HAADF-STEM images, ABF-STEM images and energy dispersive X-ray spectra were obtained with an aberration-corrected Titan $\\mathrm{\\bfG}^{\\bar{3}}$ electron microscope operated at $200\\mathrm{kV}$ using a convergence semi-angle of 21.6 mrad. The HAADF and ABF inner collection semiangles were 70 mrad and 10 mrad, respectively. Iodometric titrations were performed according to the referenced procedure19. In short, $3\\mathrm{ml}$ of deoxygenated $2\\mathrm{MKI}$ solution was added to a flask containing $15{-}20\\mathrm{mg}$ of perovskite under an Ar atmosphere and allowed to disperse for three minutes. After a few minutes $25\\mathrm{ml}$ of $1\\mathrm{M}\\mathrm{HCl}$ is added and the perovskite is allowed to dissolve. This solution is then titrated to a faint golden colour with a solution of $\\sim40\\upmu\\mathrm{M}$ solution of $\\mathrm{Na}_{2}\\mathrm{S}_{2}\\mathrm{O}_{3}$ that has been pre-standardized with $0.1\\mathrm{N}\\mathrm{KIO}_{3}$ . Starch indicator is then added and the solution is titrated until clear, marking the end point. BET surface area measurements were performed through nitrogen sorption on a Quantachrome Instruments NOVA 2000 high-speed surface area BET analyser at a temperature of $77\\mathrm{K},$ using 7 points from the linear region of the adsorption isotherm to determine the surface area. \n\nElectrode preparation. All $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ nanopowders and the commercial $\\mathrm{IrO}_{2}$ sample were loaded onto carbon through ball milling with a Wig-L-Bug ball mill. For rotating disk electrode (RDE) and for the RRDE measurements the LSCO nanopowders were loaded at a mass loading of $\\sim30\\mathrm{wt\\%}$ onto NC. For the galvanostatic stability tests, LSCO nanopowders and $\\mathrm{IrO}_{2}$ were also loaded onto VC (XC-72, Cabot Corporation) at a mass loading of $\\sim30\\mathrm{wt\\%}$ . The LSCO/carbon mixtures were dispersed in ethanol containing $0.05\\mathrm{wt\\%}$ Na-substituted Nafion at a ratio of $1\\mathrm{mg}\\mathrm{ml}^{-1}$ and sonicated for $45\\mathrm{{min}}$ . This solution was spuncast onto a glassy carbon RDE $(0.196\\mathrm{cm}_{\\mathrm{~geom}}^{2}$ , Pine Instruments) and for the RRDE (Glassy Carbon Disk: $0.2472\\mathrm{cm}_{\\mathrm{\\geom}}^{2};$ $\\mathrm{\\check{P}t}$ ring: $0.1859\\mathrm{cm}_{\\mathrm{\\geom}}^{2},$ 2geom, Pine Instruments) at a total mass loading of $51.0\\upmu\\mathrm{g}\\mathrm{cm}^{-2}\\mathrm{geom},\\mathrm{disk}$ (LSCO loading: $15.3\\upmu\\mathrm{gcm}^{-2}\\mathrm{geom})$ 2geom). The synthesis of the NC is described elsewhere57. For the oxygen intercalation cyclic voltammetry studies the LSCO nanopowders were loaded at a mass loading of $85\\mathrm{wt\\%}$ on VC (Cabot Corporation). The LSCO/carbon mixtures were dispersed in ethanol containing $0.1\\mathrm{wt\\%}$ Na-substituted Nafion at a ratio of $2\\mathrm{mg}\\mathrm{ml}^{-1}$ and sonicated for $45\\mathrm{{min}}$ . This solution was spun cast onto the glassy carbon RDE at a total mass loading of $102.0\\upmu\\mathrm{g}\\mathrm{cm}^{-2}\\mathrm{geom}$ (LSCO loading $86.7\\upmu\\mathrm{g}c\\mathrm{m}^{-2}\\mathrm{geom})$ . The electrodes were cleaned before spin casting by sonication in a 1:1 deionized water:ethanol solution. The electrodes were then polished using $50\\mathrm{nm}$ alumina powder, sonicated in a fresh deionized water:ethanol solution and dried under a scintillation vial in ambient air. \n\nElectrochemical testing. Electrochemical testing was performed on a CH Instruments CHI832a potentiostat or a Metrohm Autolab PGSTAT302N potentiostat, both equipped with high-speed rotators from Pine Instruments. For the OER studies, the testing was done at room temperature in $\\mathrm{O}_{2}$ saturated $0.1\\mathrm{{M}}$ KOH (measured $\\mathrm{pH}\\approx12.6)$ . The current interrupt and positive-feedback methods were used to determine electrolyte resistance $(50\\Omega)$ and all data was iR compensated after testing. Each measurement was performed in a standard three-electrode cell using a $\\mathrm{Hg/HgO}$ (1 M KOH) reference electrode, a $\\mathrm{Pt}$ wire counter electrode, and a film of catalyst ink on the glassy carbon working electrode. All OER testing was performed on a new electrode that had not undergone previous testing. Cyclic voltammetry was performed from $+0.9$ to $+1.943\\mathrm{V}$ at $\\mathrm{\\dot{1}0\\mathrm{mV}s^{-1}}$ with a rotation rate of $1{,}600\\ \\mathrm{r.p.m}$ . To compensate for capacitive effects, the currents were averaged for the forward and backwards scans (Supplementary Fig. 10) The current at $+1.63\\mathrm{V}$ was selected from the polarization curves to compare the OER activities. For the rotating-ring-disk studies, the same parameters were used for the disk and the Pt ring electrode was held at a constant potential of $+0.4\\mathrm{V}$ versus RHE for the reduction of $\\mathrm{O}_{2}$ to $\\mathrm{OH^{-}}$ . The Pt ring of the RRDE was electrochemically cleaned before testing by cyclic voltammetry on only the polished electrode in $0.1\\mathrm{M}\\mathrm{KOH}$ through the hydrogen reduction potential regime at $5\\mathrm{mVs}^{-1}$ for 20 cycles. The collection efficiency of the RRDE was measured as $N=0.37$ through calibration in $0.3\\mathrm{mM}$ Ferrocene-methanol in $0.1\\mathrm{M}$ KCl electrolyte (Supplementary Fig. 11). Stability tests were performed galvanostatically at a current density of $10\\mathrm{{Ag}^{-1}\\mathrm{{ox}}}$ and a rotation rate of $1{,}600\\ \\mathrm{r.p.m}$ . for $24\\mathrm{h}$ for $\\mathrm{SrCoO}_{2.7}$ and $\\mathrm{IrO}_{2}$ supported on either NC or on VC. A cutoff potential of $+1.75\\mathrm{V}$ versus RHE was used to stop the test to preserve the integrity of the glassy carbon electrode supports. All potential are reported versus the RHE, which was measured as $\\mathrm{E_{RHE}=E_{H g/H g O}+0.8456V}$ through the reduction of hydrogen in 1 atm $\\mathrm{H}_{2}$ saturated 0.1 M KOH (Supplementary Fig. 12). \n\nOxygen intercalation and diffusion rate measurements. The reversible intercalation of oxygen into LSCO was measured using cyclic voltammetry in an Ar saturated 1 M KOH electrolyte at $20\\mathrm{mVs}^{-1}$ in a standard 3-electrode cell, using a $\\mathrm{Hg/HgO}$ (1 M KOH) reference electrode, a Pt wire counter electrode, and a \n\nworking electrode of a thin film of LSCO/VC on a glassy carbon electrode as described above. The electrodes were stationary during testing and cycled twice. The data shown is from the second cycle. Following this, the diffusion rates of oxygen in the crystal were measured based on an adaptation of the procedure given in refs 39–41. In short, following the cyclic voltammetry oxygen intercalation measurements, the $\\mathrm{E}_{1/2}$ of the intercalation redox peaks was determined as the potential half way between the peak currents for intercalation and de-intercalation. The same electrodes were tested chronoamperometrically by applying a potential $50\\mathrm{mV}$ more anodic of the $E_{1/2}$ . The electrodes were rotated at $1{,}600\\ \\mathrm{r.p.m}$ . to get rid of electrolyte based mass-transfer effects, and the current was measured as a function of time for $\\boldsymbol{4}\\mathrm{h}$ . The current was plotted versus $t^{-1/2}$ and the linear section of the curve was fit to find the intercept with the $t^{-1/2}$ axis. Using a bounded 3-dimensional solid-state diffusion model, this intersect is indicative of the diffusion rate of oxygen according to the relation $\\begin{array}{r}{\\lambda=\\frac{a}{\\sqrt{D t}},}\\\\ {\\quad\\cdot\\quad.\\sqrt{D t}^{}}\\end{array}$ pa , where, l is a shape factor for the particles (in this case $\\lambda=2$ for rounded paralelipffiiffiffiffipeds), $a$ is the radius of the particle (in this case $150\\mathrm{nm}$ was used for all LSCO samples), $t^{-1/2}$ is determined from the intersection with the $t^{-1/2}$ axis, and $D$ is the diffusion rate of oxygen ions in the crystal measured at room temperature. \n\nDensity function theory calculations and surface models. DFT calculations55,59,60 are performed using VASP with PAW pseudopotentials and the RPBE-GGA functional. More details are provided in the Supplementary Methods. \n\n# References \n\n1. Cui, C., Gan, L., Heggen, M., Rudi, S. & Strasser, P. Compositional segregation in shaped Pt alloy nanoparticles and their structural behaviour during electrocatalysis. Nat. Mater. 12, 765–771 (2013). \n2. Slanac, D. A., Hardin, W. G., Johnston, K. P. & Stevenson, K. J. Atomic ensemble and electronic effects in Ag-rich AgPd nanoalloy catalysts for oxygen reduction in alkaline media. J. Am. Chem. Soc. 134, 9812–9819 (2012). \n3. Gupta, G. et al. Highly stable and active $\\mathrm{Pt}-\\mathrm{Cu}$ oxygen reduction electrocatalysts based on mesoporous graphitic carbon supports. Chem. Mater. 21, 4515–4526 (2009). \n4. James Patrick, H. The Electrochemistry of Oxygen (Interscience Publishers, 1968). \n5. McCrory, C. C. L., Jung, S., Peters, J. C. & Jaramillo, T. F. Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 135, 16977–16987 (2013). \n6. Gorlin, Y. & Jaramillo, T. F. A bifunctional nonprecious metal catalyst for oxygen reduction and water oxidation. J. Am. Chem. Soc. 132, 13612–13614 (2010). \n7. Jasem, S. M. & Tseung, A. C. C. A potentiostatic pulse study of oxygen evolution on teflon–bonded nickel–cobalt oxide electrodes. J. Electrochem. Soc. 126, 1353–1360 (1979). \n8. Dau, H. et al. The mechanism of water oxidation: from electrolysis via homogeneous to biological catalysis. ChemCatChem 2, 724–761 (2010). \n9. Otagawa, T. & Bockris, J. O. Oxygen evolution on perovskites. J. Phys. Chem. 87, 2960–2971 (1983). \n10. Bockris, J. O. & Otagawa, T. The electrocatalysis of oxygen evolution on perovskites. J. Electrochem. Soc. 131, 290–302 (1984). \n11. Matsumoto, Y. & Sato, E. Electrocatalytic properties of transition metal oxides for oxygen evolution reaction. Mater. Chem. Phys. 14, 397–426 (1986). \n12. Meadowcroft, D. B. Low-cost Oxygen electrode material. Nature 226, 847–848 (1970). \n13. Hong, W. T. et al. Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis. Energy Env. Sci. 8, 1404–1427 (2015). \n14. Suntivich, J., May, K. J., Gasteiger, H. A., Goodenough, J. B. & Shao-Horn, Y. A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles. Science 334, 1383–1385 (2011). \n15. Suntivich, J. et al. Design principles for oxygen-reduction activity on perovskite oxide catalysts for fuel cells and metal-air batteries. Nat. Chem. 3, 546–550 (2011). \n16. Hardin, W. G. et al. Highly active, nonprecious metal perovskite electrocatalysts for bifunctional metal–air battery electrodes. J. Phys. Chem. Lett. 4, 1254–1259 (2013). \n17. Hardin, W. G. et al. Tuning the electrocatalytic activity of perovskites through active site variation and support interactions. Chem. Mater. 26, 3368–3376 (2014). \n18. Pen˜a, M. a. & Fierro, J. L. Chemical structures and performance of perovskite oxides. Chem. Rev. 101, 1981–2017 (2001). \n19. Conder, K., Pomjakushina, E., Soldatov, A. & Mitberg, E. Oxygen content determination in perovskite-type cobaltates. Mater. Res. Bull. 40, 257–263 (2005). \n20. Takeda, Y. et al. Phase relation and oxygen-non-stoichiometry of perovskitelike compound $\\mathrm{SrCoO_{x}}$ $(2.29<\\mathbf{x}<2.80\\$ ). Z. Anorg. Allg. Chem. 540/541, 259–270 (1986). \n21. Kudo, T., Obayashi, H. & Gejo, T. Electrochemical behavior of the perovskite–type $\\mathrm{Nd_{1-x}S r_{x}C o O_{3}}$ in an aqueous alkaline solution. J. Electrochem. Soc. 122, 159–163 (1975). \n22. Wattiaux, A., Grenier, J. C., Pouchard, M. & Hagenmuller, P. Electrolytic oxygen evolution in alkaline medium on $\\mathrm{La}_{\\mathrm{1-x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{FeO}_{3\\mathrm{-y}}$ perovskite-related ferrites II. Influence of bulk properties. J. Electrochem. Soc. 134, 1718–1724 (1987). \n23. Nemudry, A., Rudolf, P. & Scho¨llhorn, R. Topotactic electrochemical redox reactions of the defect perovskite $\\mathrm{SrCoO}_{2.5+\\mathbf{x}}.$ . Chem. Mater. 8, 2232–2238 (1996). \n24. Nemudry, A., Goldberg, E. L., Aguirre, M. & Alario-Franco, M. A´ . Electrochemical topotactic oxidation of nonstoichiometric perovskites at ambient temperature. Solid State Sci. 4, 677–690 (2002). \n25. Jeen, H. et al. Reversible redox reactions in an epitaxially stabilized $\\mathrm{SrCoO_{x}}$ oxygen sponge. Nat. Mater. 12, 1057–1063 (2013). \n26. Jeen, H. et al. Topotactic phase transformation of the brownmillerite $\\mathrm{SrCoO}_{2.5}$ to the perovskite $\\mathrm{SrCoO}_{3-\\delta}$ . Adv. Mater. 25, 3651–3656 (2013). \n27. Mefford, J. T., Hardin, W. G., Dai, S., Johnston, K. P. & Stevenson, K. J. Anion charge storage through oxygen intercalation in $\\mathrm{LaMnO}_{3}$ perovskite pseudocapacitor electrodes. Nat. Mater. 13, 726–732 (2014). \n28. Mastin, J., Einarsrud, M.-A. & Grande, T. Structural and thermal properties of $\\mathrm{La}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3-\\delta}$ . Chem. Mater. 18, 6047–6053 (2006). \n29. Maris, G. et al. Evidence for orbital ordering in $\\mathrm{LaCoO}_{3}$ . Phys. Rev. B 67, 224423 (2003). \n30. Takami, T., Zhou, J.-S., Goodenough, J. B. & Ikuta, H. Correlation between the structure and the spin state in $\\mathrm{R}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3}$ $\\mathrm{\\tilde{R}=L a}$ , Pr, and Nd). Phys. Rev. B 76, 144116 (2007). \n31. Wang, Y. et al. Correlation between the structural distortions and thermoelectric characteristics in $\\mathrm{La}_{1-\\mathrm{x}}\\mathrm{A}_{\\mathrm{x}}\\mathrm{CoO}_{3}$ ( $\\mathrm{\\ddot{A}=C a}$ and Sr). Inorg. Chem. 49, 3216–3223 (2010). \n32. Kim, Y.-M. et al. Probing oxygen vacancy concentration and homogeneity in solid-oxide fuel-cell cathode materials on the subunit-cell level. Nat. Mater. 11, 888–894 (2012). \n33. James, M. et al. Orthorhombic superstructures within the rare earth strontium-doped cobaltate perovskites: $\\mathrm{Ln}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3-\\delta}$ ${\\mathrm{(Ln}}={\\mathrm{Y}}^{3+}$ , $\\mathrm{Dy}^{3+}\\mathrm{-Yb}^{3+}$ ; $0.750\\leqslant\\mathbf{x}\\leqslant0.875$ ). J. Solid St a\u0002te Chem. 1 \u000280, 2233–2247 (2007). \n34. Grimaud, A. et al. Oxygen evolution activity and stability of $\\mathrm{Ba}_{6}\\mathrm{Mn}_{5}\\mathrm{O}_{16},$ $\\mathrm{Sr_{4}M n_{2}C o O_{9}}$ , and $\\mathrm{Sr}_{6}\\mathrm{Co}_{5}\\mathrm{O}_{15}$ : the influence of transition metal coordination. J. Phys. Chem. C 117, 25926–25932 (2013). \n35. Takeda, Y. et al. Properties of $\\mathrm{SrMO}_{3\\mathrm{-}\\mathrm{d}}$ $\\mathrm{T}\\mathrm{R}=\\mathrm{Fe},$ Co) as oxygen electrodes in alkaline solution. J. Appl. Electrochem. 12, 275–280 (1982). \n36. Lindberg, F. et al. Synthesis and characterization of $\\mathrm{Sr}_{0.75}\\mathrm{Y}_{0.25}\\mathrm{Co}_{1-\\mathrm{x}}\\mathrm{M}_{\\mathrm{x}}\\mathrm{O}$ $2.625+\\delta$ $\\mathbf{\\dot{M}}=\\mathbf{Ga}$ , $0.125\\leqslant\\mathbf{x}\\leqslant0.500$ and $\\mathbf{M}=\\mathrm{Fe}$ , $0.125\\leqslant\\mathbf{x}\\leqslant0.875$ ). J. Solid State Chem. 179, 1434–1444 (2006). \n37. Withers, R. L., James, M. & Goossens, D. J. Atomic ordering in the doped rare earth cobaltates $\\mathrm{Ln}_{0.33}\\mathrm{Sr}_{0.67}\\mathrm{CoO}_{3-\\delta}$ ${\\mathrm{(Ln=Y^{3+}}}$ , ${\\mathrm{Ho}}^{3+}$ and $\\mathrm{Dy}^{3+}$ ). J. Solid State Chem. 174, 198–208 (2003). \n38. Conway, B. E. Electrochemical Supercapacitors (Springer, 1999). \n39. Van Buren, F. R., Broers, G. H. J., Bouman, A. J. & Boesveld, C. An electrochemical method for the determination of oxygen ion diffusion coefficients in $\\mathrm{La}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3-\\mathrm{y}}$ compounds: theoretical aspects. J. Electroanal. Chem. Interfacial Electrochem. 87, 389–394 (1978). \n40. Van Buren, F. R., Broers, G. H. J., Bouman, A. J. & Boesveld, C. The electrochemical determination of oxygen ion diffusion coefficients in $\\mathrm{La}_{0.50}\\mathrm{Sr}_{0.50}\\mathrm{CoO}_{3-\\mathrm{y}}$ : experimental results and related properties. J. Electroanal. Chem. Interfacial Electrochem. 88, 353–361 (1978). \n41. Kobussen, A. G. C., van Buren, F. R. & Broers, G. H. J. The influence of the particle size distribution on the measurement of oxygen ion diffusion coefficients in $\\mathrm{La}_{0.50}\\mathrm{Sr}_{0.50}\\mathrm{CoO}_{3-\\mathrm{y}}.$ J. Electroanal. Chem. Interfacial Electrochem. 91, 211–217 (1978). \n42. Royer, S., Duprez, D. & Kaliaguine, S. Oxygen mobility in $\\mathrm{LaCoO}_{3}$ Perovskites. Catal. Today 112, 99–102 (2006). \n43. Grimaud, A. et al. Double perovskites as a family of highly active catalysts for oxygen evolution in alkaline solution. Nat. Commun. 4, 2439 (2013). \n44. Minguzzi, A., Fan, F.-R. F., Vertova, A., Rondinini, S. & Bard, A. J. Dynamic potential–pH diagrams application to electrocatalysts for water oxidation. Chem. Sci. 3, 217–229 (2011). \n45. Matsumoto, Y., Yoneyama, H. & Tamura, H. Influence of the nature of the conduction band of transition metal oxides on catalytic activity for oxygen reduction. J. Electroanal. Chem. Interfacial Electrochem. 83, 237–243 (1977). \n46. Goodenough, J. B. Covalency criterion for localized vs collective electrons in oxides with the perovskite structure. J. Appl. Phys. 37, 1415–1422 (1966). \n47. Mueller, D. N., Machala, M. L., Bluhm, H. & Chueh, W. C. Redox activity of surface oxygen anions in oxygen-deficient perovskite oxides during electrochemical reactions. Nat. Commun. 6, 6097 (2015). \n48. Sathiya, M. et al. Reversible anionic redox chemistry in high-capacity layeredoxide electrodes. Nat. Mater. 12, 827–835 (2013). \n49. Imamura, M., Matsubayashi, N. & Shimada, H. Catalytically active oxygen species in $\\mathrm{La}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3-\\delta}$ studied by XPS and XAFS spectroscopy. J. Phys. Chem. B 104, 7348–7353 (2000). \n50. Sunstrom, IV J. E., Ramanujachary, K. V., Greenblatt, M. & Croft, M. The synthesis and properties of the chemically oxidized perovskite, $\\mathrm{La}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3-\\delta}$ ( $0.5\\le\\mathbf{x}\\le0.9,$ ). J. Solid State Chem. 139, 388–397 (1998). \n51. Le Toquin, R., Paulus, W., Cousson, A., Prestipino, C. & Lamberti, C. Time-resolved in situ studies of oxygen intercalation into $\\mathrm{SrCoO}_{2.5},$ performed by neutron diffraction and $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy. J. Am. Chem. Soc. 128, 13161–13174 (2006). \n52. Rong, X., Parolin, J. & Kolpak, A. M. A fundamental relationship between reaction mechanism and stability in metal oxide catalysts for oxygen evolution. ACS Catal. 6, 1153–1158 (2016). \n53. Man, I. C. et al. Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem 3, 1159–1165 (2011). \n54. Akhade, S. A. & Kitchin, J. R. Effects of strain, d-band filling, and oxidation state on the surface electronic structure and reactivity of 3d perovskite surfaces. J. Chem. Phys. 137, 084703 (2012). \n55. Hammer, B., Hansen, L. B. & Nørskov, J. K. Improved adsorption energetics within density-functional theory using revised Perdew-Burke-Ernzerhof functionals. Phys. Rev. B 59, 7413–7421 (1999). \n56. Lee, Y.-L., Kleis, J., Rossmeisl, J. & Morgan, D. Ab initio energetics of $\\mathrm{LaBO}_{3}$ ( $\\mathbf{\\ddot{B}}=\\mathbf{M}\\mathbf{\\dot{n}}$ , Fe, Co, and Ni) for solid oxide fuel cell cathodes. Phys. Rev. B 80, 224101 (2009). \n57. Wang, X. et al. Ammonia-treated ordered mesoporous carbons as catalytic materials for oxygen reduction reaction. Chem. Mater. 22, 2178–2180 (2010). \n58. Petrˇı´cˇek, V., Dusˇek, M. & Palatinus, L. Crystallographic computing system JANA2006: general features. Z. Fu¨r. Krist. 229, 345–352 (2014). \n59. Kresse, G. & Furthmu¨ller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n60. Blo¨chl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n61. Maiyalagan, T., Jarvis, K. A., Therese, S., Ferreira, P. J. & Manthiram, A. Spinel-type lithium cobalt oxide as a bifunctional electrocatalyst for the oxygen evolution and oxygen reduction reactions. Nat. Commun. 5, 3949 (2014). \n62. Goodenough, J. B. & Cushing, B. L. in Handbook of Fuel Cells—Fundamentals, Technology and Applications 2, 520–533 (Wiley, 2003). \n\n# Acknowledgements \n\nFinancial support for this work was provided by the R.A. Welch Foundation (grants F-1529 and F-1319). X.R. and A.M.K. acknowledge support from the Skoltech-MIT Center for Electrochemical Energy Storage. Computations were performed using computational resources from XSEDE and NERSC. S.D. was supported as part of the Fluid Interface Reactions, Structures and Transport (FIRST) Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, and Office of Basic Energy Sciences. We thank D.W. Redman for help with the RHE measurements. \n\n# Author contributions \n\nJ.T.M. and W.G.H. performed the synthesis. J.T.M. performed the X-ray diffraction, and electrochemical characterization. X.R. and A.M.K. performed the DFT modelling. A.M.A. performed the SAED, HAAFD-STEM, ABF-STEM, energy dispersive X-ray measurements and crystallographic analysis. S.D. contributed the carbon support. J.T.M., K.P.J. and K.J.S. planned the experiment and analysed the data. All authors contributed to the writing of the paper. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interest. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Mefford, J. T. et al. Water electrolysis on $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ perovskite electrocatalysts. Nat. Commun. 7:11053 doi: 10.1038/ncomms11053 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms12357", + "DOI": "10.1038/ncomms12357", + "DOI Link": "http://dx.doi.org/10.1038/ncomms12357", + "Relative Dir Path": "mds/10.1038_ncomms12357", + "Article Title": "Room-temperature ferroelectricity in CuInP2S6 ultrathin flakes", + "Authors": "Liu, FC; You, L; Seyler, KL; Li, XB; Yu, P; Lin, JH; Wang, XW; Zhou, JD; Wang, H; He, HY; Pantelides, ST; Zhou, W; Sharma, P; Xu, XD; Ajayan, PM; Wang, JL; Liu, Z", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Two-dimensional (2D) materials have emerged as promising candidates for various optoelectronic applications based on their diverse electronic properties, ranging from insulating to superconducting. However, cooperative phenomena such as ferroelectricity in the 2D limit have not been well explored. Here, we report room-temperature ferroelectricity in 2D CuInP2S6 (CIPS) with a transition temperature of similar to 320 K. Switchable polarization is observed in thin CIPS of similar to 4 nm. To demonstrate the potential of this 2D ferroelectric material, we prepare a van der Waals (vdW) ferroelectric diode formed by CIPS/Si heterostructure, which shows good memory behaviour with on/off ratio of similar to 100. The addition of ferroelectricity to the 2D family opens up possibilities for numerous novel applications, including sensors, actuators, non-volatile memory devices, and various vdW heterostructures based on 2D ferroelectricity.", + "Times Cited, WoS Core": 856, + "Times Cited, All Databases": 920, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000381525200001", + "Markdown": "# Room-temperature ferroelectricity in CuInP2S6 ultrathin flakes \n\nFucai Liu1,\\*, Lu You2,\\*, Kyle L. Seyler3, Xiaobao Li4, Peng $\\mathsf{Y u}^{1}$ , Junhao $\\mathsf{L i n}^{5,6,\\dagger}$ , Xuewen Wang1, Jiadong Zhou1, Hong Wang1, Haiyong He1, Sokrates T. Pantelides5,6, Wu Zhou6, Pradeep Sharma7, Xiaodong ${\\sf X}{\\sf u}^{3}.$ , Pulickel M. Ajayan8, Junling Wang2 & Zheng Liu1,9,10 \n\nTwo-dimensional (2D) materials have emerged as promising candidates for various optoelectronic applications based on their diverse electronic properties, ranging from insulating to superconducting. However, cooperative phenomena such as ferroelectricity in the 2D limit have not been well explored. Here, we report room-temperature ferroelectricity in $2\\mathsf{D}\\mathsf{C u l n P}_{2}\\mathsf{S}_{6}$ (CIPS) with a transition temperature of $\\sim320\\mathsf{K}$ Switchable polarization is observed in thin CIPS of $\\sim4\\mathsf{n m}$ . To demonstrate the potential of this 2D ferroelectric material, we prepare a van der Waals (vdW) ferroelectric diode formed by CIPS/Si heterostructure, which shows good memory behaviour with on/off ratio of $\\sim100$ . The addition of ferroelectricity to the 2D family opens up possibilities for numerous novel applications, including sensors, actuators, non-volatile memory devices, and various vdW heterostructures based on 2D ferroelectricity. \n\nFeowrhrdioecerhlie gtmrioacfcrteoylseicstorapicico liplpeoclltaiervsiezapntirdonpc rnatryibseosf wfeirrtotcamhie spmboayn eteraxitnaelrsoniuansl electric field. Most technologically important ferroelectrics are perovskite oxides with strong covalent/ionic bonds, such as ${\\bar{\\mathrm{PbTiO}}}_{3}$ and $\\mathrm{BaTiO}_{3}$ , which have been widely applied in electronic and optoelectronic devices1–3. Due to the three-dimensional nature of the ferroelectric oxide lattices, epitaxial growth of high-quality films requires the careful selection of substrates with small lattice mismatch4. This severely limits the possible materials that can be utilized in ferroelectric heterostructure devices. In addition, prevalent dangling bonds and defects at the interface drastically deteriorate the electronic coupling between ferroelectric and graphene like two-dimensional (2D) materials5, due to the complex interface reconstruction and defect chemistry6. Studying weakly bonded non-oxide ferroelectric compounds is thus both fundamentally and practically rewarding. Meanwhile, the groundbreaking work on graphene has triggered an intense search for other 2D materials with intriguing physical properties7–9. However, ferroelectricity has so far remained elusive to the 2D material library. Currently the reported critical thickness for ferroelectricity in layered materials is relatively large (above $50\\mathrm{nm}$ thick)10, far from the ultrathin limit. \n\nHere, we report the experimental observation of switchable polarization in $\\mathrm{CuInP}_{2}\\mathrm{S}_{6}$ (CIPS) films down to $4\\mathrm{nm}$ at room temperature. Second-harmonic generation (SHG) measurements show the transition from ferroelectric to paraelectric accompanies the structural change from inversion asymmetric to symmetric. Finally, we demonstrate a non-volatile memory device with on/off ratio of $\\sim100$ in a CIPS/Si ferroelectric diode. \n\n# Results \n\nCharacterization of $\\mathbf{CuInP}_{2}\\mathbf{S}_{6}$ . CIPS is one of the few layered compounds which exhibits room-temperature ferroelectricity11. The atomic structure of CIPS contains of a sulfur framework with the octahedral voids filled by the Cu, In and $\\mathrm{{\\sfP-P}}$ triangular patterns. Bulk crystals are composed of vertically stacked, weakly interacting layers packed by van der Waals interactions (Fig. 1a,b)12. Owing to the site exchange between Cu and P–P pair from one layer to another, a complete unit cell consists of two adjacent monolayers to fully describe the material’s symmetry. It is a collinear two-sublattice ferrielectric system with $T_{c}$ of about $315\\mathrm{K}$ (ref. 11). When the temperature drops below $T_{c},$ due to the off-centre ordering in the Cu sublattice and the displacement of cations from the centrosymmetric positions in the In sublattice (symmetry changes from $\\mathrm{C}_{2/\\mathrm{c}}$ to $\\textstyle\\mathrm{C}_{\\mathrm{c}}.$ , spontaneous polarization emerges in the ferrielectric phase with polar axis normal to the layer plane13. For simplicity, CIPS will be referred as ferroelectric because ferrielectric materials exhibit the same macroscopic properties as ferroelectrics: namely, a spontaneous and switchable net electric polarization. To verify the ferroelectricity of the bulk sample, polarization versus out-of-plane electric field curve was measured on a $4\\mathrm{-}\\upmu\\mathrm{m}$ -thick CIPS flake using a commercial ferroelectric analyzer, where the clear hysteresis loop is direct evidence of ferroelectricity13. Details of the ferroelectric and dielectric measurements as well as the temperature dependence are shown in Supplementary Note 1 and Supplementary Figs 1 and 2. The weak interlayer vdW interaction in CIPS allows us to exfoliate ultrathin flakes from a single crystal and study the ferroelectric properties with reduced dimension. Flakes with different thicknesses were mechanically exfoliated on heavily doped Si substrate with or without $\\mathrm{SiO}_{2}$ depending on the purpose of the measurement. They were identified by optical contrast in a microscope and the thickness was subsequently measured using an atomic force microscopy (AFM). Figure 1c shows a typical AFM image of CIPS flakes with different thicknesses on a Si substrate covered with $285\\mathrm{nm\\SiO}_{2}$ . In the height profile (Fig. 1d) along the line in Fig. 1c, flakes from two to five layers thick and clear monolayer steps are observed. The atomic structure and high quality of the CIPS crystal is also confirmed by high-resolution scanning transmission electron microscopy (STEM) imaging (Supplementary Fig. 3) and Raman spectroscopy (Supplementary Fig. 4). \n\nPiezoresponse force microscopy measurement. To verify the thin-film ferroelectricity, CIPS flakes with various thicknesses were investigated using piezoresponse force microscopy (PFM) under both resonant and non-resonant modes (see Methods). The PFM amplitude reflects the absolute magnitude of the local piezoelectric response, while the phase indicates the polarization direction in each individual domain14. Figure 2a–c shows the typical domain evolution of CIPS flakes with thickness ranging from $100\\mathrm{nm}$ down to sub- $10\\mathrm{nm}$ . With reduced flake thickness (Fig. 2a), the PFM amplitude signal also decreases (Fig. 2b). Similar behaviour is commonly observed in conventional ferroelectric films due to the enhanced depolarization effect in thinner films15 as well as the nonuniform electric field of the AFM tip16. However, the amplitude signal above the background persists down to the lowest thickness $\\left(7\\mathrm{nm}\\right)$ . The PFM phase image (Fig. 2c) is characterized by two-colour tones with a contrast of $180^{\\circ}$ , corresponding to the two opposite polarization directions perpendicular to the layer surface. To confirm the polarization is confined in vertical direction, thickness-dependent vector (vertical and lateral) PFM is conducted on flakes with thickness ranging from sub-10 to $100\\mathrm{nm}$ (Supplementary Figs 5 and 6 and Supplementary Note 2). Persistent noise-level in-plane piezoresponse signal suggests negligible effect of possible residual strain on the polarization orientation17, thanks to the quasi-freestanding nature of the specimen. The domain patterns evolve from fractal in thinner flakes towards dendrite-like in thicker ones, together with an increase in domain size. The piezoresponse amplitude reduces with the layer thickness, consistent with a finite depolarization effect commonly found in ferroelectric thin films18,19. These observations imply that CIPS ultrathin flakes remain ferroelectric down to a few nanometre thick. Piezoelectric response was also obtained from a bilayer $(\\sim1.6\\mathrm{nm})$ CIPS flake (Fig. $2\\mathrm{d-g)}$ , benefiting from the absence of surface/interface reconstructions in 2D materials. To further examine the ferroelectric polarization in ultrathin CIPS, we calculated the structure and polarization of CIPS by the density functional theory (DFT) calculation, and found that the ferrielectric phase can be stabilized in bilayer CIPS (see Methods and Supplementary Note 3 and Supplementary Fig. 7 for details). \n\n![](images/539001a83bad1f72917301f5063eadd64f63052b9bca5cd9cacdab8463a3f91f.jpg) \nFigure 1 | Crystal structure and characterization of CIPS. (a,b) The side view (a) and side view $(\\pmb{6})$ for the crystal structure of CIPS with vdW gap between the layers. Within a layer, the $\\mathsf{C u},$ In and P–P form separate triangular networks. The polarization direction is indicated in by the arrow. (b) The ferroelectric hysteresis loop of a $4-upmu\\mathrm{m}$ -thick CIPS flake. (c) AFM image of the CIPS flakes with different thicknesses. Scale bar, $2\\upmu\\mathrm{m}$ (d) The height profile along the line shown in c. Clear step height of $0.7\\mathsf{n m}$ corresponding to single layer thickness of CIPS can be observed. $\\mathsf{L},$ Layers. \n\n![](images/416f21390276d333897c0732aa83ed98f6decfb9ee72a9488bad68d58999b5a7.jpg) \nFigure 2 | AFM and piezoresponse images of CIPS with different thicknesses. (a–c) AFM topography (a) PFM amplitude (b) and PFM phase (c) for CIPS flakes ranging from 100 to 7 nm thick, on doped Si substrate. Scale bar in a, $1\\upmu\\mathrm{m}$ . (d,e) AFM topography (d) PFM amplitude (e) and phase (f) of 2–4 layer thick CIPS on Au coated $\\mathsf{S i O}_{2}/\\mathsf{S i}$ substrate. Scale bar in d, $500\\mathsf{n m}$ . $\\mathbf{\\sigma}(\\mathbf{g})$ the height (black) and PFM amplitude (blue) profile along the lines shown in d and e, respectively. L, Layers. \n\nFerroelectric switching. By definition, a ferroelectric material should possess spontaneous polarization that is switchable. Although hysteresis loops have been obtained in thick CIPS flakes, it does not warrant switchable polarization in thinner samples, as conventional ultrathin ferroelectric films are notorious for their deteriorated ferroelectric performance owing to the depolarization effect18, interface/surface polarization pinning20, or, more generally, the ‘dead layer’ effect21. Hence, we carried out local switching tests by applying a bias between the conductive PFM tip and the heavily doped Si substrate. Figure 3a–c displays the PFM phase images of 400, 30 and $4\\mathrm{nm}$ thick CIPS flakes after writing box-in-box patterns with reversed DC bias in the centre (see Supplementary Figs 8–12 and Supplementary Note 4 for detailed results). Clear reversal of phase contrast confirms the switching of polarization in CIPS down to $\\sim4\\mathrm{nm}$ . Meanwhile, there are no obvious changes in the corresponding surface morphologies as previously reported10. Furthermore, the CIPS flakes exhibit superior ferroelectric retention despite the relatively low ferroelectric Curie temperature (Supplementary Fig. 13). The written domain patterns are still discernible after several weeks in ambient condition. These observations clearly rule out the possible contribution of PFM signal from the electrochemical phenomena $^{22,-24}$ . The corresponding switching spectroscopic loops were also recorded under resonance-enhanced PFM mode by applying an AC electric field superimposing on a DC triangle saw-tooth waveform (Supplementary Fig. 14). The well-defined butterfly loops of the PFM amplitude signals and the distinct $180^{\\circ}$ switching of the phase signals further corroborate the robust ferroelectric polarization in CIPS ultrathin flakes (Fig. 3d–f). Furthermore, the longitudinal piezoelectric coefficient of the CIPS flakes were quantitatively determined using off-resonant PFM (Supplementary Note 5 and Supplementary Figs 15 and 16). \n\nSecond-harmonic generation measurement. To probe the structural phase change accompanying the ferroelectric to paraelectric transition, we utilized SHG microscopy, which is a sensitive probe of broken inversion symmetry and an excellent tool for the investigation of ferroelectric order25,26. We first explored the structural symmetry through polarization-resolved SHG at $300\\mathrm{K}$ under normal incidence excitation (see Methods and Supplementary Information for details of the measurement). Figure 4a illustrates the SHG intensity dependence on excitation polarization for fixed detection along the horizontal $\\mathrm{(H)}$ or vertical (V) direction (laboratory coordinates), which are fit well (solid lines) using the allowed in-plane second-order susceptibility elements for point group m (ref. 27; see Supplementary Note 6 and Supplementary Fig. 17). The nonzero SHG directly reveals the broken inversion symmetry that generates the ferroelectricity. This is clearly seen in the approximate sixfold rotational symmetry of the co-linearly polarized SHG (Supplementary Fig. 5), which reflects hexagonal ordering of the displaced Cu and In sublattices in the ferroelectric phase. We further investigated the SHG intensity as a function of temperature for CIPS flakes with thicknesses from 100 to $\\sim10\\mathrm{nm}$ . Figure 4b shows the normalized intensity plotted as a function of temperature. All flakes follow the same trend: below $T_{c},$ there is significant SHG signal, but as the temperature increases, the SHG intensity decreases gradually, and almost vanishes at high temperature. This is a strong indication of the ferroelectric to paraelectric phase transition around $T_{c},$ which involves a structural change from noncentrosymmetric $\\mathrm{(m)}$ to centrosymmetric $(2/\\mathrm{m})$ . \n\n![](images/2c0ef791180fcac48d2f03a1cecbdcd534e31f8217f83c3ff49884d1abb53fcf.jpg) \nFigure 3 | Ferroelectric polarization switching by PFM for CIPS flakes with different thicknesses. (a–c) The PFM phase images for $400\\mathsf{n m}$ (a) $30\\mathsf{n m}$ (b) and $4\\mathsf{n m}$ (c) thick CIPS flakes with written box-in-box patterns with reverse DC bias. Scale bar, $1\\upmu\\mathrm{m}$ . (d–f) The corresponding PFM amplitude (black) and phase (blue) hysteresis loops during the switching process for $400\\mathsf{n m}$ (d) $30\\mathsf{n m}$ (e) and $4\\mathsf{n m}$ $\\mathbf{\\eta}(\\bullet)$ thick CIPS flakes. \n\n![](images/7a1b8994cfb14bf2a50ad943a37588e9561068744356382a8ad2828c00a9dc07.jpg) \nFigure 4 | Thicknesses-dependent second-harmonic generation (SHG). (a) Polar plots of the SHG intensity in H and V directions (laboratory coordinates) as a function of the excitation laser linear polarization for a $100\\mathsf{n m}$ thick CIPS flake. (b) Temperature dependence of the SHG intensity for CIPS flakes with thickness of 100, 50, 30 and $10\\mathsf{n m}$ , respectively. The SHG intensity of each thickness is normalized to its intensity at $300\\mathsf{K}.$ \n\nFerroelectric diode based on CIPS/Si heterostructure. All the above evidence unambiguously establishes the existence of ferroelectric order in 2D layers of CIPS, making it a promising non-volatile element in vdW heterostructures. We test its applications in a prototype ferroelectric diode (inset of Fig. 5a). The vdW heterojunction was fabricated by exfoliating the CIPS flakes $\\left(30\\mathrm{nm}\\right)$ on to a Si substrate and followed by patterning the top electrodes (see Methods). Electrical contact to the top electrode was made using an AFM conductive tip. Figure 5a shows the current change by sweeping the bias from $\\bar{2.5\\mathrm{V}}$ to $-2.5\\mathrm{V}$ , and back to $2.5\\mathrm{V}$ . Figure 5b shows the resistance calculated at a bias of $-1.3\\mathrm{V}$ while sweeping the switching pulse. A clear large hysteresis and resistive switching are observed. The ON and OFF states, which correspond to the low- and high-resistance states, respectively, can be assigned. The resistive switching and resulting memory effect is due to the polarization switching of the ferroelectric CIPS layer, as evidenced from the piezoelectric switching measurement of the same device (Fig. 5c). The coercive voltage coincides minima in the amplitude loop as well as the switching bias in the phase signal coincides with the bias, at which resistive switching takes place. This strongly suggests that the ferroelectric polarization reversal is the origin of the resistive switching in the vdW diode. The on/off ratio of about 100 is comparable to that observed in tunnel junctions based on conventional ferroelectric oxide28. These results, although obtained on unoptimized devices, constitute a proof of concept for novel non-volatile memories based on ferroelectric 2D materials. \n\n# Discussion \n\nIn summary, we have unambiguously established roomtemperature ferroelectricity in ultrathin CIPS flakes of $\\sim4\\mathrm{nm}$ thick as well as piezoelectric response in bilayer CIPS. A simple vdW CIPS/Si ferroelectric diode exhibits non-volatile memory behaviour with on/off ratio of $\\sim100$ , exhibiting the capability of integration with well-established Si-based platforms. Our discovery greatly enriches the functionalities of the 2D material family and opens new possibilities for novel devices based on vdW heterostructures. \n\n# Methods \n\nSample preparation and characterization. High-quality single crystals of CIPS were synthesized by solid state reaction as previously reported12. The thin flakes were obtained by mechanical exfoliation from synthetic bulk crystals onto heavily doped silicon substrates with or without a $285\\mathrm{nm}\\mathrm{SiO}_{2}$ layer on top. The thickness of the flakes was identified from their optical contrast and AFM. Raman spectrum was carried out using a confocal Raman system (WITec) with the $532\\mathrm{nm}$ laser excitation. SHG measurements were performed in reflection geometry with 100 fs pulses at $786\\mathrm{nm}$ and a repetition rate of $76\\mathrm{MHz}$ , which were focused to a spot size of $\\sim1\\upmu\\mathrm{m}$ by a $40\\times\\ 0.6$ NA objective lens (Olympus). TEM sample was prepared by dropcasting the solution, which contains exfoliated thin flakes after sonication of the thick CIPS crystal, onto a lacy carbon TEM grid. Z-contrast STEM imaging was performed on a Nion UltraSTEM-100, equipped with a fifth order aberration corrector, operated at $60\\mathrm{kV}$ . The convergence angle is set to be $\\sim30$ mrad. All Z-contrast STEM images were acquired from the $\\sim86-200$ mrad range. \n\nPFM and ferroelectric polarization measurement. PFM measurement was carried out on a commercial atomic force microscope (Asylum Research MFP-3D) under both resonance-enhanced and off-resonance modes. In resonance-enhanced mode, a soft tip with a spring constant of $\\sim2\\mathrm{N}\\mathrm{m}^{-1}$ was driven with an ac voltage $\\mathrm{\\DeltaVac}=0.5{-1\\mathrm{V}};$ under the tip-sample contact resonant frequency $(\\sim300\\mathrm{kHz})$ . In off-resonance mode, a stiff tip with a spring constant of ${\\sim}40\\mathrm{N}\\mathrm{m}^{-1}$ was driven at $10\\mathrm{kHz}$ . The inverse optical lever sensitivity (InvOLS, $\\mathrm{nm/V}$ was calibrated beforehand to obtain quantitative piezoelectric displacement data. Vector PFM was performed by imaging both the out-of-plane and in-plane PFM at different azimuth angles between the sample and AFM cantilever. Ferroelectric polarization measurements were carried out using a commercial ferroelectric \n\n![](images/54073dddcccf9802eaf534cfe7dcc5c4ee63a806b213d11205849d7ab8b458e0.jpg) \nFigure 5 | Electric characterization of the vdW CIPS/Si diode. (a) The I–V curves from the typical vdW CIPS/Si diode with $30\\mathsf{n m}$ thick CIPS, by sweeping the bias from 2.5 to $-2.5V,$ and then back to $2.5\\mathsf{V}.$ Inset is the schematic of the device. (b) Resistance-switching voltage hysteresis loop of the diode measured at a bias voltage of $-1.3\\vee$ . The schematic representations of the ON and OFF states with respect to the polarization direction are shown in the bottom-left and top-right insets, respectively. (c) Out-of-plane PFM amplitude (black) and phase (blue) measurements on the same diode device shown in a. \n\ntester (Radiant Technologies) and a pulse generator (Keithley 3,401). Dielectric permittivity was characterized using a commercial LCR metre (Agilent E4980A). \n\nDevice fabrication and measurement. The ferroelectric diode was fabricated by exfoliating the thin flakes of CIPS onto heavily doped silicon substrates. The top electrodes are defined using standard photolithography process followed by thermal evaporation of the $\\mathrm{Ti/Au}$ 1 $\\mathrm{{(1nm/10nm})}$ metal, and lift-off process. Electrical measurements were performed using a commercial AFM (Asylum Research MFP-3D) integrated with a pA metre/direct current (d.c.) voltage source (Hewlett Package 4140B). \n\nComputational method. The quantum calculations are based on the density functional theory (DFT) as implemented in the Quantum-Espresso computational package29 (http://www.quantum-espresso.org/). The PAW pseudopotentials with PBE exchange correlation functional from Quantum-Espresso pseudopotential database are used for each element in CIPS (http://www.quantum-espresso.org/ pseudopotentials/). The $4\\times8\\times1$ k-point grid by Monkhorst-Pack scheme was selected for the calculations. The energy cutoff for wave function and charge density are set as $50~\\mathrm{Ry}$ and 400 Ry respectively. A vacuum region of $20\\textup{\\AA}$ is set in the direction perpendicular to the layer to avoid the interaction between the periodic images. The polarization calculation is performed using Berry-phase method30 embedded in the Quantum-Espresso package. In this method, the total polarization includes two contributions: ionic and electronic. More $k$ -point (for example, 9) has been used in the polarization calculation direction. All the calculations are done at $0\\mathrm{K}$ \n\nData availability. The data that support the findings of this study are available from the corresponding author upon request. \n\n# References \n\n1. Ahn, C., Rabe, K. & Triscone, J.-M. Ferroelectricity at the nanoscale: local polarization in oxide thin films and heterostructures. Science 303, 488–491 (2004). \n2. Garcia, V. & Bibes, M. Ferroelectric tunnel junctions for information storage and processing. Nat. Commun. 5, 4289 (2014). \n3. Dawber, M., Rabe, K. & Scott, J. Physics of thin-film ferroelectric oxides. Rev. Mod. Phys. 77, 1083–1130 (2005). \n4. Schlom, D. G. et al. Strain tuning of ferroelectric thin films. Annu. Rev. Mater. Res. 37, 589–626 (2007). \n5. Yusuf, M. H., Nielsen, B., Dawber, M. & Du, X. Extrinsic and intrinsic charge trapping at the graphene/ferroelectric interface. Nano Lett. 14, 5437–5444 (2014). \n6. Zubko, P., Gariglio, S., Gabay, M., Ghosez, P. & Triscone, J.-M. Interface physics in complex oxide heterostructures. Annu. Rev. Condens. Matter Phys. 2, 141–165 (2011). \n7. Xi, X. et al. Strongly enhanced charge-density-wave order in monolayer $\\mathrm{Nb}{\\mathsf{S e}}_{2}$ . Nat. Nanotech. 10, 765–769 (2015). \n8. Keum, D. H. et al. Bandgap opening in few-layered monoclinic $\\mathrm{MoT}e_{2}$ . Nat. Phys. 11, 482–486 (2015). \n9. Li, L. et al. Black phosphorus field-effect transistors. Nat. Nanotech. 9, 372–377 (2014). \n10. Belianinov, A. et al. $\\mathrm{CuInP}_{2}\\mathrm{S}_{6}$ -room temperature layered ferroelectric. Nano Lett. 15, 3808–3814 (2015). \n11. Simon, A., Ravez, J., Maisonneuve, V., Payen, C. & Cajipe, V. Paraelectricferroelectric transition in the lamellar thiophosphate $\\mathrm{CuInP}_{2}\\mathrm{S}_{6}$ . Chem. Mater. 6, 1575–1580 (1994). \n12. Maisonneuve, V., Evain, M., Payen, C., Cajipe, V. & Molinie, P. Roomtemperature crystal structure of the layered phase $\\mathrm{Cu}^{\\mathrm{II}}\\mathrm{n}^{\\mathrm{III}}\\mathrm{P}_{2}\\mathrm{S}_{6}$ . J. Alloy Compd. 218, 157–164 (1995). \n13. Maisonneuve, V., Cajipe, V., Simon, A., Von Der Muhll, R. & Ravez, J. Ferrielectric ordering in lamellar $\\mathrm{CuInP}_{2}\\mathrm{S}_{6}$ . Phys. Rev. B 56, 10860–10868 (1997). \n14. Gruverman, A. & Kalinin, S. V. Piezoresponse force microscopy and recent advances in nanoscale studies of ferroelectrics. J. Mater. Sci. 41, 107–116 (2006). \n15. Nagarajan, V. et al. Scaling of structure and electrical properties in ultrathin epitaxial ferroelectric heterostructures. J. Appl. Phys. 100, 051609 (2006). \n16. Morozovska, A. N., Eliseev, E. A. & Kalinin, S. V. The piezoresponse force microscopy of surface layers and thin films: Effective response and resolution function. J. Appl. Phys. 102, 074105 (2007). \n17. Catalan, G. et al. Flexoelectric rotation of polarization in ferroelectric thin films. Nat. Mater. 10, 963–967 (2011). \n18. Junquera, J. & Ghosez, P. Critical thickness for ferroelectricity in perovskite ultrathin films. Nature 422, 506–509 (2003). \n19. Maksymovych, P. et al. Ultrathin limit and dead-layer effects in local polarization switching of ${\\mathrm{BiFeO}}_{3}$ . Phys. Rev. B 85, 014119 (2012). \n20. Han, M.-G. et al. Interface-induced nonswitchable domains in ferroelectric thin films. Nat. Commun. 5, 4693 (2014). \n21. Stengel, M. & Spaldin, N. A. Origin of the dielectric dead layer in nanoscale capacitors. Nature 443, 679–682 (2006). \n22. Kalinin, S. V., Jesse, S., Tselev, A., Baddorf, A. P. & Balke, N. The role of electrochemical phenomena in scanning probe microscopy of ferroelectric thin films. ACS Nano 5, 5683–5691 (2011). \n23. Bark, C. et al. Switchable induced polarization in LaAlO3/SrTiO3 heterostructures. Nano Lett. 12, 1765–1771 (2012). \n24. Kumar, A. et al. Probing surface and bulk electrochemical processes on the $\\mathrm{LaAlO}_{3}–\\mathrm{SrTiO}_{3}$ interface. ACS Nano 6, 3841–3852 (2012). \n25. Denev, S. A., Lummen, T. T., Barnes, E., Kumar, A. & Gopalan, V. Probing ferroelectrics using optical second harmonic generation. J. Am. Ceram. Soc. 94, 2699–2727 (2011). \n26. Misuryaev, T. et al. Second harmonic generation in the lamellar ferrielectric $\\mathrm{CuInP}_{2}\\mathrm{S}_{6}$ . Solid State Commun. 115, 605–608 (2000). \n27. Boyd, R. W. Nonlinear Optics (Academic press, 2008). \n28. Chanthbouala, A. et al. Solid-state memories based on ferroelectric tunnel junctions. Nat. Nanotech. 7, 101–104 (2012). \n29. Giannozzi, P. et al. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials. J. Phys.: Condens. Matter 21, 395502 (2009). \n30. King-Smith, R. & Vanderbilt, D. Theory of polarization of crystalline solids. Phys. Rev. B 47, 1651–1654 (1993). \n\n# Acknowledgements \n\nThis work was financially supported by the Singapore National Research Foundation under NRF RF Award No. NRF-RF2013-08, the start-up funding from Nanyang Technological University (M4081137.070). J.W. acknowledges the support from the Ministry of Education Singapore under grant No. MOE2013-T2-1-052, MOE2014-T2-1-099 and RG126/14. K.S. and X.X are supported by Department of Energy Office of Basic Energy Sciences (DoE BES, DE-SC0008145 and SC0012509). J.L. and S.T.P. acknowledge the support from U.S. Department of Energy grant DE-FG02-09ER46554. W.Z. was supported by the U.S. Department of Energy, Office of Science, Basic Energy Science, Materials Sciences and Engineering Division, and through a user project at ORNL’s Centre for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. P.S. was funded by NSF CMMI grant 1463205. \n\n# Author contributions \n\nF.L., L.Y., J.W. and Z.L. conceived and designed the research. L.Y. and F.L. prepared the sample and device, performed the PFM measurement and electric characterization. K.S. and X.X. conducted the SHG measurement. X.L. and P.S. performed the theoretical calculation. P.Y., X.W., J.Z. and H.W. carried out the characterization of single crystal sample. J.L., H.H., S.T.P. and W.Z. performed the TEM characterization. X.X., P.M.A., J.W. and Z.L. conducted the data analysis. F.L. and L.Y. co-wrote the manuscript with input from all authors. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Liu, F. et al. Room-temperature ferroelectricity in $\\mathrm{CuInP}_{2}\\mathrm{S}_{6}$ ultrathin flakes. Nat. Commun. 7:12357 doi: 10.1038/ncomms12357 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms10437", + "DOI": "10.1038/ncomms10437", + "DOI Link": "http://dx.doi.org/10.1038/ncomms10437", + "Relative Dir Path": "mds/10.1038_ncomms10437", + "Article Title": "Temperature-feedback upconversion nullocomposite for accurate photothermal therapy at facile temperature", + "Authors": "Zhu, XJ; Feng, W; Chang, J; Tan, YW; Li, JC; Chen, M; Sun, Y; Li, FY", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Photothermal therapy (PTT) at present, following the temperature definition for conventional thermal therapy, usually keeps the temperature of lesions at 42-45 degrees C or even higher. Such high temperature kills cancer cells but also increases the damage of normal tissues near lesions through heat conduction and thus brings about more side effects and inhibits therapeutic accuracy. Here we use temperature-feedback upconversion nulloparticle combined with photothermal material for real-time monitoring of microscopic temperature in PTT. We observe that microscopic temperature of photothermal material upon illumination is high enough to kill cancer cells when the temperature of lesions is still low enough to prevent damage to normal tissue. On the basis of the above phenomenon, we further realize high spatial resolution photothermal ablation of labelled tumour with minimal damage to normal tissues in vivo. Our work points to a method for investigating photothermal properties at nulloscale, and for the development of new generation of PTT strategy.", + "Times Cited, WoS Core": 892, + "Times Cited, All Databases": 940, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000371011500001", + "Markdown": "# Temperature-feedback upconversion nanocomposite for accurate photothermal therapy at facile temperature \n\nXingjun $Z\\mathsf{h u}^{1,\\star}$ , Wei Feng2,\\*, Jian Chang3, Yan-Wen Tan3, Jiachang ${\\mathsf{L i}}^{2}$ , Min Chen2, Yun Sun2 & Fuyou Li1,2,4 \n\nPhotothermal therapy (PTT) at present, following the temperature definition for conventional thermal therapy, usually keeps the temperature of lesions at $42-45^{\\circ}C$ or even higher. Such high temperature kills cancer cells but also increases the damage of normal tissues near lesions through heat conduction and thus brings about more side effects and inhibits therapeutic accuracy. Here we use temperature-feedback upconversion nanoparticle combined with photothermal material for real-time monitoring of microscopic temperature in PTT. We observe that microscopic temperature of photothermal material upon illumination is high enough to kill cancer cells when the temperature of lesions is still low enough to prevent damage to normal tissue. On the basis of the above phenomenon, we further realize high spatial resolution photothermal ablation of labelled tumour with minimal damage to normal tissues in vivo. Our work points to a method for investigating photothermal properties at nanoscale, and for the development of new generation of PTT strategy. \n\nhe past few decades have witnessed significant efforts in the treatment of cancer1,2. Among the existing treatment methods, thermal therapy has become an important treatment modality3. Conventional approaches including radiofrequency or microwave ablation have been widely used in clinic4,5. However, these approaches relying on macroscopic heat sources have a relatively large destruction range causing normal tissue damages and even some serious systemic side effects6,7. Photothermal therapy (PTT), using photoabsorbing molecules or nanoparticles as microscopic heat sources, is expected to improve the therapeutic accuracy and reduce injury to normal tissues8–13. However, the current method to monitor PTT regards the entire lesion containing PTT agents as a macroscopic heat source and keep the overall temperature of the lesion (here defined as apparent temperature) at high level in line with the temperature definition for conventional thermal therapy (usually 42–45 \u0002C)14,15. In some cases, the temperature is even higher16,17. Such a high apparent temperature can damage normal tissues adjacent to the lesions due to massive heat transfer, therefore, leading to more side effect and inhibiting the therapeutic accuracy of PTT. In our view, distinguished from traditional thermal therapy methods using macroscopic heat source and requiring apparent temperature as reference, PTT uses heat source at nanoscale, so correspondingly the temperature of those nanoparticles (here defined as the eigen temperature) during photothermal process should be the prerequisite to determine the temperature threshold for effective and minimally harmful PTT. Although some previous studies have referred to the measurement of the eigen temperature of gold nanostructures18,19, to date, no data were reported to utilize the eigen temperature during PTT in a real biosystem to achieve therapeutic effect with high spatial resolution under facile apparent temperature. It still remains unsolved to seek for an adequate thermal-sensitive system that is stable and not affected by the complex biological condition to report the eigen temperature of photothermal agents, thus determining the temperature threshold for accurate and facile therapy. If there exists a suitable way to monitor the eigen temperature during PTT, then it will not only open a window to learn the temperature of PTT agents at microscopic level, but also innovate the PTT strategy for better therapeutic efficacy. \n\nTo monitor the eigen temperature of PTT agents in biological systems, temperature-sensing luminescent materials are appropriate options as the optical signals provide high resolution and sensitivity. A series of luminescent temperaturesensing probes have been developed including organic dyes, polymers, QDs and lanthanide-based upconversion nanophosphors $(\\mathrm{Ln-}\\bar{\\mathrm{UCNPs}})^{20-25}$ . Among those, Ln-UCNPs which allow the conversion of lower-energy light in the near-infrared (NIR) region into higher energy emissions have many advantages to be served as imaging or therapy agents such as superior photostability, non-blinking, absence of autofluorescence of biological tissue and low-energy NIR radiation26–43. On the basis of the above merits, Ln-UCNPs are ideal probes to real-time sensing the eigen temperature of PTT agents in biological system. Here we build a carbon-coated core-shell upconversion nanocomposite NaLuF4:Yb,Er@NaLuF $_4\\textcircled{\\theta}$ Carbon $({\\bar{\\mathrm{csUCNP@{\\mathrm{C}}}}})$ to investigate the possible difference between the apparent and eigen temperature and evaluate the therapeutic effect of implementing photothermal therapy at low apparent temperature, but a much higher eigen temperature in real biosystems. Moreover, this kind of nanocomposite can also be served as theranostic agents as the upconversion core and carbon shell endorse it with a good imaging quality and PTT efficacy. \n\n# Results \n\nCharacterization of temperature-feedback $\\mathbf{csUCNP}@\\mathbf{C}$ The synthetic procedure of ${\\mathsf{c s U C N P@C}}$ is shown in Supplementary Fig. 1. The carbon shell generated heat under $730\\mathrm{-nm}$ irradiation and the core of NaLuF $_4$ :Yb,Er provided thermal-sensitive upconversion luminescence (UCL) emission under $980\\mathrm{-nm}$ excitation (Fig. 1). As shown by transmission electron microscopy (TEM), the NaLuF4:Yb,Er nanoparticles (UCNPs, the core) were uniform in morphology with a diameter of $\\sim25\\mathrm{nm}$ (Fig. 2b). After coating with a non-doping $\\mathrm{\\DeltaNaLuF_{4}}$ layer, the shape of the formed nanoparticles was changed to rod-like and the size was increased to $\\sim50\\mathrm{nm}$ in length and $\\sim40\\mathrm{nm}$ in width (Fig. 2b), indicating the formation of the core-shell nanoparticles NaLuF $_4$ $:\\mathrm{Yb,Er@NaLuF_{4}}$ (csUCNPs). X-ray powder diffraction (Supplementary Fig. 2c) patterns of UCNPs and csUCNPs were indexed as the hexagonal phase of $\\mathrm{\\DeltaNaLuF_{4}}$ . The as-prepared oleate-capped csUCNPs were transformed into the aqueous phase using an acid-based ligand removal method reported by Capobianco et al.44 To coat the shell layer of carbon, a glucose solution $(0.4\\mathrm{mmol}\\mathrm{ml}^{-1}$ ) containing hydrophilic csUCNPs $(2\\mathrm{mg}\\mathrm{ml}^{-1})$ ) was hydrothermally treated at $160^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ . Fourier-transform infrared spectroscopy indicated that the oleate species on csUCNPs were totally removed after acid treatment (Supplementary Fig. 4a) and a carbon layer was successfully coated on csUCNPs after the hydrothermal treatment, as the stretching bands referred to as $\\mathrm{C}-\\mathrm{H}$ and $\\mathrm{C}=\\mathrm{C}$ bonds appeared. A new coating layer was also visible in the TEM images (Fig. 2b; Supplementary Fig. 2b) and the monodispersity of the nanoparticles kept good (Supplementary Fig. 3). In particular, Raman spectra confirmed the dominance of an ordered conjugated $\\pi$ -bond structure in the outside shell layer, as the intensity ratio of the peaks of graphitic carbon and amorphous carbon reached 4.3 (Supplementary Fig. 4c). The highly graphitic components in the carbon shell, inducing effective $\\pi$ -plasmon, accounted for the broad absorption from visible to NIR region of ${\\mathsf{c s U C N P@C}}$ (Fig. 2d; Supplementary Fig. 5). Thus, the colour of the nanocomposites turned from white of csUCNP to deep brown (Fig. 2d inset). After carbon coating, the average hydrodynamic diameter was increased from 56.5 to $77.0\\mathrm{nm}$ (Supplementary Fig. 6b), and the weight percentage $(\\mathrm{wt\\%})$ of the organic components was enhanced from $\\sim0.5$ to $\\sim3.7\\mathrm{wt\\%}$ (Supplementary Fig. 4d). These factors indicated that a carbon layer was successfully coated on the surface of csUCNPs by hydrothermal treatment. The as synthesized c $s\\mathrm{UCNP}@{\\mathrm{C}}$ can be easily dispersed in water and other buffers because polymerization of glucose occurred before carbonization and the hydrophilic polymer chains located at the outer layer of ${\\mathsf{c s U C N P@C}},$ which make the nanoparticles very stable in aqueous phase45. Dynamic light scattering (DLS) data showed that the colloidal suspensions can be preserved for 2 weeks without any aggregation (Supplementary Fig. 7). \n\n![](images/61b9b22abe40fe53b040cc5fcc2473c3960537c8c68b193792fe4bb10f34b8ba.jpg) \nFigure 1 | Schematic of csUCNP $@.$ for accurate PTT at facile temperature. The ${\\mathsf{c s U C N P}}({\\mathsf{a}}){\\mathsf{C}}$ exhibit both UCL emission and photothermal effect. With temperature-sensitive UCL emission, csUCNP $@{\\mathsf{C}}$ was used to monitor the change in microscopic temperature of the photoabsorber (carbon shell) under $730-\\mathsf{n m}$ irradiation. The eigen temperature of ${\\mathsf{c s U C N P}}{\\widehat{\\underline{{a}}}}{\\mathsf{C}}$ was much higher than the apparent temperature observed macroscopically, indicating that ${\\mathsf{c s U C N P}}({\\mathsf{a}}){\\mathsf{C}}$ acted as a nano-hotspot at the microscopic level. By utilizing the high eigen temperature during photothermal process, accurate PTT, which prevent the damage to normal tissues can be realized. \n\n![](images/0a066a9d8eb3f34ce7cf94d75e184069fa1a752e8a2c74dd4ee5e33bbd4125c6.jpg) \n\nImportantly, the insertion of a non-doping $\\mathrm{NaLuF_{4}}$ interlayer $\\mathrm{\\hbar}\\sim7.5{\\cdot}\\mathrm{nm}$ thick) between the carbon shell and upconversion core of $\\mathrm{NaLuF_{4}};$ Yb,Er can both enhance the UCL emission and prevent luminescent quenching by the carbon shell. When the concentration of the luminescence centre of $\\mathrm{Er}^{3+}$ was consistent, csUCNPs emitted stronger UCL at $540\\mathrm{nm}$ (increased 4.9-fold) compared with UCNPs. The control $_{\\mathrm{NaLuF}_{4}:\\mathrm{Yb},\\mathrm{Er@Carbon}}$ $\\mathsf{(U C N P@C)}$ without a $\\mathrm{\\DeltaNaLuF_{4}}$ protective layer displayed an $83\\%$ decrease in UCL intensity, whereas ${\\mathsf{c s U C N P@C}}$ with a protective layer maintained $82\\%$ of the UCL intensity (Fig. 2c). Thus, the introduction of $\\mathrm{NaLuF_{4}}$ is necessary for fabricating the temperature-feedback PTT agent. \n\nPhotothermal properties of ${\\mathsf{c s U C N P@C}}$ were also evaluated by measuring the photothermal conversion efficiency under $730\\mathrm{-nm}$ laser irradiation $(1\\mathrm{W}\\mathrm{cm}^{-2})$ . Detailed data are shown in Supplementary Information (Supplementary Figs 8 and 9). The final heat-generation efficiency $(\\eta)$ is $38.1\\ \\%$ that is higher than those widely studied PTT agents such as gold nanorods $(21\\%)$ and nanoshells $(13\\%)$ , $\\mathrm{Cu}_{2}\\mathrm{-}x^{\\mathrm{Se}}$ $(22\\%)$ and $\\mathrm{Cu}_{9}\\mathrm{S}_{5}$ $(25.7\\%)^{46,47}$ . The high heat-generation efficiency indicated that the carbon shell of ${\\mathsf{c s U C N P@C}}$ is a kind of excellent PTT agent to realize the therapeutic temperature at even lower laser-irradiation dosage. It should be noted that the 2-in-1 design that combined temperature-sensitive upconversion luminescence with photothermal carbon shell can realize both good temperature-sensing property and photothermal effect. Although other carbon materials such as carbon dots also exhibit special luminescent property that is marked by tunable emission wavelength and broad excitation spectra48,49, their \n\nFigure 2 | Characterization and temperature-sensing properties of csUCNP@C. (a) Schematic diagram of the detection of the eigen temperature of csUCNP $@{\\mathsf{C}}$ . (b) TEM images of UCNPs (left), csUCNPs (middle) and ${\\mathsf{c s U C N P}}({\\mathsf{a}}){\\mathsf{C}}$ (right). Scale bar, $50\\mathsf{n m}$ . (c) UCL emission spectra of UCNPs, UCNPs $@{\\mathsf{C}},$ csUCNPs and ${\\mathsf{c s U C N P}}{\\widehat{\\underline{{a}}}}{\\mathsf{C}}$ in the aqueous dispersion with the same concentration of luminescence centre $\\mathsf{E r}^{3+}$ . (d) Powder absorption spectra of csUCNPs and ${\\mathsf{c s U C N P}}{\\mathcal{Q}}{\\mathsf{C}}$ (e) UCL emission spectra of $\\mathsf{E r}^{3+}$ -doping csUCNP $@{\\mathsf{C}}$ at different temperatures by external heating. The peaks were normalized at $528.5\\mathsf{n m}$ . (f) A plot of $\\ln(I_{525}/I_{545})$ versus $1/T$ to calibrate the thermometric scale for ${\\mathsf{c s U C N P}}{\\bmod{\\mathsf{C}}}$ . $1_{525}$ and $1_{545}$ indicate the UCL emission of the $^2\\mathsf{H}_{11/2}\\to^{4}\\mathsf{I}_{15/2}$ and $^4\\mathsf{S}_{3/2}\\to$ $4|_{15/2}$ transitions, respectively. Average values of $I_{525}/I_{545}$ under different temperature were given to fit the calibration curve based on three times measurements of UCL spectrum. Error bars were defined as s.d. $\\mathbf{\\sigma}(\\mathbf{g})$ Elevation of apparent temperature (A.T.) and eigen temperature (E.T.) of csUCNP $\\mathtt{\\Pi}_{\\mathtt{(a)}}\\mathtt{(}$ $(1\\mathrm{mg}\\mathrm{ml}^{-1})$ in aqueous dispersion under irradiation with a $730-\\mathsf{n m}$ laser at 0.8 and $0.3\\mathsf{W}\\mathsf{c m}^{-2}$ . Average value of A.T. and E.T. under different time points were given based on three times measurements. Error bars were defined as s.d. ${\\bf\\Pi}({\\bf h})$ Finite element method (FEM) simulation of the heat conduction of a single ${\\mathsf{c s U C N P}}{\\widehat{\\underline{{a}}}}{\\mathsf{C}}$ nanoparticle induced by the photothermal process. Scale bar, $100\\mathsf{n m}$ . \n\nabsorption spectrum usually located in ultraviolet to blue region and their photothermal effect under NIR laser irradiation has not been proved yet. Also, the temperature-sensing properties of carbon dots have not been clarified. \n\nObservation of the eigen temperature of $\\mathbf{csUCNP}@\\mathbf{C}$ . In the $\\mathrm{Er}^{3+}$ -doped upconversion system, $^2\\mathrm{H}_{11/2}\\to{^4}\\mathrm{I}_{15/2}$ (UCL emission centred at $525\\mathrm{nm}$ ) and $^{2}\\mathrm{\\dot{S}}_{3/2}\\ \\rightarrow\\ ^{4}\\mathrm{I}_{15/2}$ (centred at $545\\mathrm{nm}$ transitions were in close proximity to a thermal equilibrium ruled by the Boltzmann factor (equation $1)^{24}$ : \n\n$$\n(I_{525})/(I_{545})=C\\exp(-\\Delta E/k T),\n$$ \n\nwhere $I_{525}$ and $I_{545}$ are the UCL emission of the $^2\\mathrm{H}_{11/2}\\rightarrow^{4}\\mathrm{I}_{15/2}$ and $^{4}\\mathrm{S}_{3/2}\\quad\\rightarrow\\quad^{4}\\mathrm{I}_{15/2}$ transitions, respectively; $C$ is a constant determined by the degeneracy, spontaneous emission rate and photon energies of the emitting states in the host materials; $\\Delta E$ is the energy gap separating the two excited states; $k$ is the Boltzmann constant; $T$ is temperature using the Kelvin scale. The changes in the UCL intensities as a function of temperature make it possible to quantitatively monitor the eigen temperature fluctuation of ${\\mathsf{c s U C N P@C}}$ when irradiated. \n\nTo simultaneously measure the apparent temperature and upconversion emission spectrum of the aqueous solution containing ${\\mathsf{c s U C N P@C}}.$ we designed and set-up a system by introducing a thermometer and upconversion emission spectroscope, as shown in Fig. 2a. First, we obtained a calibration curve to determine the relationship between UCL intensity and temperature. By heating the solution of $\\mathsf{c s U C N P@C}$ with a temperature controller (Supplementary Fig. 10), the UCL emission at $525\\mathrm{nm}$ was correspondingly enhanced (Fig. 2e). The dependence of $\\ln(I_{525}/I_{545})$ on the inverse temperature $(1/T)$ , which showed a linear behaviour (Fig. 2f), was well fitted as $\\ln(I_{525}/I_{545})=1.085-0.838\\times(1/T)$ ( $T$ given in K). Judging from the signal changes of UCL intensity changes, $\\mathtt{c s U C N P@C}$ is a good optical nanothermometer with a relatively high sensitivity of $1\\%$ signal change $\\mathrm{K}^{-1}$ around $35\\mathrm{-}40^{\\circ}\\mathrm{C}$ and a high temperature resolution of about $0.5\\mathrm{K}$ . Although some previous works have reported other methods for intracellular thermometry with excellent temperature resolution and sensitivity50–52, those thermometry methods rely on single band emission without an internal ratiometric. Hence, the accuracy of temperature sensing will be strongly affected by other environmental factors, which can change the emission intensity such as absorption, scattering, tissue motions, autofluorescence and quenching centres. Moreover, their combination with photothermal therapy have not been exploited and the advantages of marked local temperature changes of PTT agents have not been fully recognized to improve PTT. The optical temperature sensor in ${\\mathsf{c s U C N P@C}},$ $\\mathrm{NaLuF_{4}}$ :Yb,Er, has a couple of temperature-sensitive emission bands (centred at 525 and $545\\mathrm{nm}$ ) for ratiometric thermometry, which is insusceptible to disturbance of environmental factors. The closely combined structure of temperature sensor and photothermal component in ${\\mathsf{c s U C N P@C}}$ is indispensable to monitor local temperature elevation of PTT agents during photothermal process and thus give us the chance to explore a new strategy of photothermal therapy with much less normal tissue damage. \n\nTo observe the difference of eigen and apparent temperature, ${\\mathsf{c s U C N P@C}}$ solution under $730\\mathrm{-nm}$ irradiation at various time points were recorded using the thermometer (Fig. 2a) to compare the eigen temperature of ${\\mathsf{c s U C N P@C}}$ and the apparent temperature. As shown in Fig. 2g, the eigen temperature of ${\\mathsf{c s U C N P@C}}$ was much higher than the apparent temperature at each time point, with a significant difference of $\\sim34\\mathrm{K}$ at equilibrium with a power density of $0.8\\mathrm{W}\\mathrm{cm}^{-2}$ at $730\\mathrm{-nm}$ irradiation. Under low-power illumination at $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ for \n\n$8\\mathrm{min}$ , the apparent temperature of the solution was ${36.6^{\\circ}\\mathrm{C}},$ whereas the eigen temperature of ${\\mathsf{c s U C N P@C}}$ soared to $65.5^{\\circ}\\mathrm{C}$ by determining the ratio of UCL emission at 525 to $545\\mathrm{nm}$ . Even when irradiated for $2\\mathrm{min}$ , the eigen temperature of ${\\mathsf{c s U C N P@C}}$ reached ${59.7^{\\circ}\\mathrm{C}},$ whereas the apparent temperature of the solution was $31.6^{\\circ}\\mathrm{C}.$ . To the best of our knowledge, this is the first time such a significant difference between eigen temperature of the PTT agent and apparent temperature of its surrounding system has been reported. It should be noted that $\\mathrm{NaLuF_{4};\\bar{Y}b,\\bar{E}r}$ as temperature sensor has a temperature resolution of $0.5^{\\circ}\\mathrm{C}$ and sensitivity of $1\\%$ signal change per degree, which can be perfectly qualified for differentiating the remarkable temperature elevation (for example, eigen temperature elevation is $30.0^{\\circ}\\mathrm{C}$ with $730\\mathrm{-nm}$ irradiation at $0.3\\dot{\\mathrm{W}}\\mathrm{cm}^{-2}$ for $2\\mathrm{min}$ ) of PTT agents in microscopic state. \n\nTo shed light on the temperature distribution at the microscopic level, we used a single-particle model to simulate the possible temperature distribution around the nanoparticles (heating centre) in solution. As shown in Fig. 2h, the temperature of the nanoparticles was kept at $80^{\\circ}\\mathrm{C}$ (in accordance with the highest eigen temperature in our experiment). Water was chosen as the ambient condition for the nanoparticles and the external boundary was kept at $35^{\\circ}\\mathrm{C}$ . The model simulated a steady state with heat conduction mode (see Methods). The simulation showed that the temperature of water declined with increasing distance from the nanoparticles, below the lethal temperature to cancer cells $(39^{\\circ}\\mathrm{C})$ at $\\sim360\\mathrm{nm}$ in diameter (Fig. 2h). Therefore, it is reasoned that under $730\\mathrm{-nm}$ laser irradiation, ${\\mathsf{c s U C N P@C}}$ in the aqueous phase become localized hot spots whose eigen temperature is much higher than the ambient temperature, and thus their effective range for killing cancer cells by PTT is in the nanoscale. Therefore, it was theoretically proved that PTT can be performed at low apparent temperature and high spatial accuracy. \n\nFacile and high-accuracy PTT in vitro. To confirm that PTT is effective at low apparent temperature, experiments at the macroscopic level were carried out. First, non-labelled HeLa cells were irradiated by a $730\\mathrm{-nm}$ laser $(0.3\\mathrm{W}\\mathrm{cm}^{-2},$ ) to figure out the laser-induced heating effect and the final apparent temperature elevation in the laser spot, $T_{0}$ $35.6^{\\circ}\\mathrm{C},$ Supplementary Fig. 13b), was set as a benchmark. $\\Delta T$ shown in Fig. 3b was the temperature increment subtracting $\\mathrm{T}_{0}$ after photothermal process or external heating. Calcein acetoxymethyl ester (Calcein AM) and propidium iodide (PI) double staining were used to confirm the state (live or dead) of cells. When csUCNP $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ -incubated HeLa cells were irradiated under $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ for less than $3\\mathrm{min}$ , Calcein AM/PI staining indicated that $\\mathsf{c s U C N P@C}$ -incubated cells were dead when $\\Delta T$ was $1.4^{\\circ}\\mathrm{C}$ . Non-labelled cells with external heating holder indicated that cells were alive when $\\Delta T$ was $1.4^{\\circ}\\mathrm{C}$ and were dead only when $\\Delta T$ reached $3.6^{\\circ}\\mathrm{C}$ . These results suggest that the photothermal effect of ${\\mathsf{c s U C N P@C}}$ can effectively kill the cells without heating the surrounding solution to a high apparent temperature. \n\nAs proof of concept experiments to investigate the accuracy of PTT, we mixed csUCNP $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ -labelled HeLa cells with non-labelled cells together and let them adhere to the culture dish. In our designed PTT system (Fig. 3a), two lasers, one at $980\\mathrm{nm}$ and the other at $730\\mathrm{nm}$ , were used to generate upconversion emission and the photothermal effect of ${\\mathsf{c s U C N P}}\\ @{\\mathsf{C}},$ respectively. Before $730\\mathrm{-nm}$ irradiation, csUCNP $\\boldsymbol{\\mathcal{Q}}\\mathbf{C}$ -treated cells (incubating dosage, $200\\upmu\\mathrm{g}\\mathrm{ml}^{-1},$ ), which have a relatively wide distribution of ${\\mathsf{c s U C N P@C}}$ in cytoplasm with a uptake of $4.4\\mathrm{\\pg\\csUCNP{@C}}$ per cell, could be stained with Calcein AM (Supplementary Fig. 11a–d) showing they were all alive. Methyl thiazolyl tetrazolium (MTT) assays also confirmed that csUCNP $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ have no toxic effect on cells under this incubating dosage (Supplementary Fig. 11e,f). A low-power density $(0.3\\mathrm{\\breve{W}}\\mathrm{cm}^{-2},$ of $730\\mathrm{-nm}$ laser was adopted for photothermal cell ablation. Determined by UCL intensity changes on the csUCNP $\\boldsymbol{@}\\mathrm{C}$ - labelled HeLa cells (Supplementary Fig. 14), a huge eigen temperature elevation was observed after $730\\mathrm{-nm}$ laser irradiation from $37^{\\circ}\\mathrm{C}$ to nearly $60^{\\circ}\\mathrm{C}$ (Supplementary Fig. 15). Such a high eigen temperature reflects enormous localized heat which is very critical in killing the cancer cells. As shown in Fig. 3c, only the cells with upconversion emission displayed red fluorescence from PI $(\\lambda_{\\mathrm{ex}}=633\\mathrm{nm})$ ), whereas the others without upconversion signals showed the fluorescence signal from Calcein AM (cyan, $\\lambda_{\\mathrm{ex}}=488\\mathrm{nm}$ ). The results indicated that, after $730\\mathrm{-nm}$ irradiation, the ${\\mathsf{c s U C N P@C}}$ -labelled cells were dead and the free cells were still alive. Bright-field image of the ${\\mathsf{c s U C N P@C}}$ -labelled cells showed membrane damage and leakage of the cytoplasm. Moreover, laser irradiation of $\\mathsf{c s U C N P@C}.$ -labelled HeLa cells and non-labelled C2C12 cells indicated that photothermal effect can only occurred in the cancer cells without damaging normal cells (Supplementary Fig. 12). MTT assays also confirmed these results by a remarkable decrease in cell viability after $730\\mathrm{-nm}$ irradiation (Supplementary Fig. 10f). By further decreasing the power density of the $730\\mathrm{-nm}$ laser to $0.2\\dot{\\mathrm{W}}\\mathrm{cm}^{-2}$ , early stage cell apoptosis was observed only in csUCNP $\\boldsymbol{\\mathcal{Q}}$ C-labelled cells (Supplementary Fig. 13a), using the Annexin V-FITC/PI double staining method. On the basis of the cell selective ablation experiment (Fig. $^{3\\mathrm{b},\\mathrm{c};}$ Supplementary Fig. 15), we can conclude that high temperature of a limited space is enough to kill cells, while the overall temperature changes little. In other words, with the microscopic temperature monitoring technology, there is no longer a need to use overall temperature to monitor PTT. The usage of overall temperature of cells for PTT, which only involves the average value of high-temperature region containing $\\mathsf{c s U C N P@C}$ and low-temperature region without ${\\mathsf{c s U C N P@C}},$ will neglect the significance of localized high temperature in killing the cancer cells and obviously restrict the therapeutic accuracy. It is worth noting that the distance between PTT-affected cells and unaffected cells in the confocal image (Fig. 3c,d) was at the micrometre level and the minimum distance was only $0.9\\upmu\\mathrm{m}$ , that is, the photothermal ablation under a low apparent temperature was proved to have very high spatial resolution at the microscopic level. \n\n![](images/f5cbf42c65abc492816aa57b67dc5335658218caf9e177de1d7b81ba5c1eca55.jpg) \nFigure 3 | csUCNP@C for high-accuracy PTT at cell level. (a) Schematic diagram of PTT in cells. (b) Thermal images and Calcein AM and PI doublestained images of HeLa cells treated with photothermal ablation or external heating. Non-labelled cells were irradiated by $730-\\mathsf{n m}$ laser $(0.3\\mathsf{W}\\mathsf{c m}^{-2})$ and the final apparent temperature elevation in the laser spot ( $T_{0}=35.6^{\\circ}\\mathsf C)$ was set as a benchmark. DT was the difference between apparent temperature and $T_{0}$ . In external heating, cells were alive when $\\Delta T=1.4^{\\circ}\\mathsf{C}$ and dead when $\\Delta T=3.6^{\\circ}C$ . With $730–\\mathsf{n m}$ laser irradiation, ${\\mathsf{c s U C N P}}{\\mathcal{Q}}{\\mathsf{C}}$ labelled cells were dead when $\\Delta T=1.4^{\\circ}C$ indicating that the eigen temperature of ${\\mathsf{c s U C N P}}({\\mathsf{a}}){\\mathsf{C}}$ had reached to a lethal temperature to the cells even though the apparent temperature was still safe. Scale bar, $50\\upmu\\mathrm{m}$ . (c) Photothermal therapy of HeLa cells under $730-\\mathsf{n m}$ laser irradiation at $0.3\\mathsf{W}\\mathsf{c m}^{-2}$ for 5 min. Cells labelled with ${\\mathsf{c s U C N P}}({\\mathsf{a}}){\\mathsf{C}}$ showed a strong UCL signal in the cytoplasm (green). The signal is collected in the wavelength region of $520-550\\mathrm{nm}$ . After $730-\\mathsf{n m}$ irradiation, dead cells showed conspicuous cytoplasm leakage which labelled with black arrows. Calcein AM (cyan) and PI (red) double-staining showed that only the cells labelled with csUCNP $@{\\mathsf{C}}$ were dead. Scale bar, $30\\upmu\\mathrm{m}$ . (d) Amplified image of the luminescent cell images in c. The distance between the adjacent live and dead cells was measured. The minimum distance was $\\sim0.9\\upmu\\mathrm{m}$ . Scale bar, $30\\upmu\\mathrm{m}$ . \n\nFacile and high-accuracy PTT in vivo. To further confirm the feasibility of photothermal therapy at low apparent temperature and investigate the heat-conduction process in the living body, it is crucial to know about the eigen temperature fluctuations of ${\\mathsf{c s U C N P@C}}$ under laser irradiation in biological tissue. As it is difficult to obtain the temperature calibration curve and to investigate the heat conduction process in living animals due to some limiting factors in instruments, tissue phantoms were used to simulate the temperature elevation of ${\\mathsf{c s U C N P@C}}$ in biological tissue (Fig. 4a). The tissue phantom is consisted of gelatin and a certain amount of haemoglobin and intralipid to simulate the absorption and scattering properties of real tissue (see Supplementary Methods for the synthesis of tissue phantom). The temperature calibration curve (from 0 to $100^{\\circ}\\mathrm{C}\\cdot$ ) obtained in a single-layer phantom containing ${\\mathsf{c s U C N P@C}}$ showed a linear behaviour $[\\ln(I_{525}/I_{545})=0.924-0.687\\times(1/T)]$ $T$ given in K, Fig. 4b), which was similar to that detected in solution (Fig. 2f). A double-layer phantom where the lower layer of the phantom containing ${\\mathsf{c s U C N P@C}}$ (Layer 1, $\\sim10–\\mathrm{mm}$ thick) simulating the tumour area for therapy and the upper layer without ${\\mathsf{c s U C N P@C}}$ (Layer 2, $\\sim4\\ –\\mathrm{mm}$ thick) simulating normal tissue (Fig. 4a) was used to investigate the heat conduction in facile and excessive photothermal process. The photothermal effect of ${\\mathsf{c s U C N P@C}}$ in the phantom tissues was triggered by $730\\mathrm{-nm}$ irradiation at 0.3 or $0.8\\dot{\\mathrm{W}}\\mathrm{cm}^{-2}$ . The apparent temperatures of layer 1 (‘tumour’) and layer 2 (‘normal tissue’) were recorded using a thermal camera, and the eigen temperature of ${\\mathsf{c s U C N P@C}}$ in layer 1 was calculated by the upconversion emission spectrum (Fig. 4a). Following $0.{\\dot{8}}\\mathrm{W}\\mathrm{cm}{\\dot{^{-2}}}$ irradiation for $8\\mathrm{min}$ , layer 1 was heated to $44.5^{\\circ}\\mathrm{C}$ (apparent temperature) and layer 2 also underwent an obvious temperature elevation to $43.3\\mathrm{{}^{\\circ}C}$ due to massive heat conduction, that is, the overheating photothermal effect. However, following mild laser irradiation at $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ , the apparent temperature of layer 1 was moderate at $37.3^{\\circ}\\mathrm{C}$ and layer 2 only showed slight heat conduction $(35.2^{\\circ}\\mathrm{C})$ , as shown in Fig. 4c. Meanwhile, the eigen temperature of ${\\mathsf{c s U C N P@C}}$ within the phantom obtained by the UCL spectrum was $56.7^{\\circ}\\mathrm{C},$ which is sufficient to kill cancer cells (Fig. 4d). Therefore, it can be safely concluded that c ${\\mathsf{s U C N P@C}}$ as a PTT agent can take effect under mild apparent temperature elevation, while excessive laser power aggravates injury of normal tissue. It should be noted that in previous publications on PTT, an overheating effect existed during the therapy process due to the absence of a temperaturefeedback unit in the photothermal agent. \n\nThe above-mentioned results encouraged us to further assess the therapeutic effect of ${\\mathsf{c s U C N P@C}}$ in small living animals. The $\\mathsf{c s U C N P@C}$ -incubated ( $\\cdot4.4\\mathrm{pg}$ per cell) HeLa cells $(1\\times10^{7}$ cells) were subcutaneously transplanted into nude mice for tumour growth. Fourteen days after transplantation, a tumour with a diameter of $\\sim0.6\\mathrm{cm}$ was observed and displayed strong UCL signals collected by a $720–\\mathrm{nm}$ short pass filter (Fig. 4f; Supplementary Fig. 19a). The apparent temperature in the tumour area was recorded by an infrared thermal imaging device. The eigen temperature in the tumour area was calculated by upconversion luminescence of ${\\mathsf{c s U C N P@C}}$ . On the basis of the therapeutic data and the heat conduction behaviour under two sets of $730\\mathrm{-nm}$ laser power density (0.3 and $0.8\\mathrm{W}\\mathrm{cm}^{-2},$ ) in Fig. 4c, we have summarized and proposed a model of temperature-feedback photothermal treatment system and make a demonstration of this feedback treatment with the strategies given in this work (Supplementary Fig. 18). In this model, controller (in this work, controller is experimenter) will make decision on the treatment strategy. Strategy box stores a series of photothermal therapy strategies for selection (in this work, strategies are $1\\#$ and $2\\#$ with $730\\mathrm{-nm}$ laser at 0.3 and 0.8 W cm \u0002 2, respectively.). csUCNP@C receives the strategy output and is served as photothermal agent and eigen temperature reporter for feedback signal input. Eigen temperature of $\\mathtt{c s U C N P@C}$ with different power density of $730\\mathrm{-nm}$ laser irradiation reported by UCL spectra (Supplementary Fig. 17) \n\nshowed that both sets of power density can result in an enough high eigen temperature to ablate cancer cells $(61.5^{\\circ}\\mathrm{C}$ with $0.{\\overset{\\smile}{3}}\\operatorname{W}\\operatorname{cm}^{-2}$ and $73.1^{\\circ}\\mathrm{C}$ with $0.8\\mathrm{W}\\mathrm{cm}^{-2}.$ ). The temperature elevation through heat conduction in layer 2 (‘normal tissue’) is \n\n![](images/90d099064260500c85724b1ca5be3ecd7cbdbd5a1c8b8542f62c3d7726cfbe2e.jpg) \n\nFigure 4 | csUCNP@C for high-accuracy PTT in vivo. (a) Schematic diagram of the feasibility of PTT in vivo using a tissue phantom. (b) A plot of $\\ln(I_{525}/I_{545})$ versus 1/T to calibrate the thermometric scale for csUCNP $@{\\mathsf{C}}$ in the tissue phantom. (c) Apparent temperature versus the thickness of the tissue phantom (from layer 1 to layer 2) under 730-nm irradiation at two different power densities (left panel). Thermal images of longitudinal sections of the phantom within two irradiation power densities to show the heat conduction process. The white dashed line separates the simulated ‘tumour’ and ‘normal tissue’ (right panel). (d) Elevation of apparent temperature (A.T.) and eigen temperature (E.T.) of csUCNP $\\mathtt{\\Pi}_{\\mathtt{(a)C}}$ in the tissue phantom under irradiation with $730-\\mathsf{n m}$ laser at 0.8 and $0.3\\mathsf{W}\\mathsf{c m}^{-2}$ . Average values of A.T. and E.T. under different time points were given based on three times measurement. Error bars were defined as s.d. (e) Thermal images of nude mice with (left panel) and without (right panel) csUCNP $\\textstyle{\\mathcal{Q}}C$ - labelled HeLa cell tumours under 730-nm irradiation $(0.3\\mathsf{W}\\mathsf{c m}^{-2};$ . (f) Representative photos of nude mice transplanted with csUCNP $\\ @{\\mathsf C}$ -labelled HeLa cells under $730–\\mathsf{n m}$ irradiation $(0.3\\mathsf{W}\\mathsf{c m}^{-2})$ . $\\mathbf{\\sigma}(\\mathbf{g})$ H&E histologic section of the border of tumour and normal fat tissue. The tumour region (Tu) and the adipocytes (Ad) in normal fat tissue of the mice without 730- nm irradiation (left, control) is compact and the tumour cells are stretched. Following photothermal treatment (middle, Facile PTT), the tumour region became loose and fragile and the tumour cells are atrophic. The adipocytes (Ad) in normal fat tissue are intact with minimal damage. However, following high-power irradiation with the $730–\\mathsf{n m}$ laser $(0.8\\mathsf{W}\\mathsf{c m}^{-2},$ , both Tu and Ad suffered extreme damage (right, Over irradiated). \n\nconfined within $2^{\\circ}\\mathrm{C}$ under $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ irradiation. Considering that the body temperature is $37^{\\circ}\\mathrm{C}$ and $2^{\\circ}\\mathrm{C}$ elevation will not exceed $40^{\\circ}\\mathrm{C}$ that cause protein denaturation53, treatment strategy $^{1\\#}$ with a power density of $730\\mathrm{-nm}$ laser at $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ was chosen for therapy. Tumour-bearing mice with ${\\mathsf{c s U C N P@C}}$ -labelled were exposed to a $730\\mathrm{-nm}$ laser $(0.3\\mathrm{W}\\mathrm{cm}^{-2})$ for $3\\mathrm{min}$ and the difference between final apparent temperature (at $3\\mathrm{min}\\dot{}$ ) and the initial temperature (at $0\\mathrm{min}\\dot{}$ ) was controlled at $\\sim1.5\\mathrm{K}$ (Fig. 4e). The tumourbearing mice without $\\mathtt{c s U C N P@C}$ treatment (control) under $0.3\\mathrm{W}\\mathrm{cm}^{-2}730\\mathrm{-nm}$ laser irradiation showed a slight increase in apparent temperature (Fig. 4e). The tumour in each mouse in the treatment group was exposed to the $730\\mathrm{-nm}$ laser every day. Five days later, the tumours in the treatment group shrank and were finally eliminated without any regrowth (Supplementary Figs 19b and 21; Supplementary Table 1). In contrast, neither csUCNP $@^{\\zeta}$ - treatment nor laser irradiation affected tumour growth and the tumour size increased rapidly. Reference groups (including untreated mice, mice exposed to the $730\\mathrm{-nm}$ laser only, and $\\mathsf{c s U C N P@C}$ -treated mice without $730\\mathrm{-nm}$ irradiation) showed an average lifespan for tumour-bearing mice of $\\sim22$ days, while the mice in the PTT experimental group survived for over 40 days without mortality (Supplementary Fig. $^{19\\mathrm{b},\\mathrm{c}},$ ). Hematoxylin and eosin (H&E) histopathological analysis indicated that malignant cells at the tumour site $\\left(\\mathrm{Tu}\\right)$ in the facile PTT treatment group 1 $^{\\prime}730\\mathrm{-nm}$ laser, $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ ) showed obvious shrinkage and fragmented nuclei (Fig. 4g), whereas the control group showed no conspicuous necrosis (Fig. $\\ensuremath{4\\mathrm{g}})$ . Furthermore, the adjacent subcutaneous adipocytes (Ad) showed intact morphology in the control group and in the facile PTT treatment group $(0.3\\mathrm{W}\\mathrm{cm}^{-2},$ ), while both Tu and Ad sites in the $730\\mathrm{-nm}$ over-irradiated group $(0.8\\mathrm{W}\\mathrm{cm}^{-2},$ that had a high apparent temperature (Supplementary Fig. 16) were severely damaged (Fig. 4g). Hence, by using ${\\mathsf{c s U C N P@C}}$ as a photothermal agent, PTT at a mild apparent temperature is successfully achieved in living animals without damaging normal tissue. \n\nFurthermore, using folic-acid-modified ${\\mathsf{c s U C N P@C}}$ $\\left(\\mathrm{FA-csUCNP}@\\mathrm{C}\\right)$ as the photothermal agent, targeting PTT of the HeLa tumour-bearing balb/c mice under mild apparent temperature was investigated. After intravenous injection of FA-csUCNP $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ $2\\mathrm{mg}\\mathrm{ml}^{-1}$ , $200\\upmu\\mathrm{l})$ for $2\\mathrm{h}$ , strong UCL signals were detected in tumour region (Supplementary Fig. 22a). Ex vivo UCL imaging indicated the biodistribution of ${\\mathsf{c s U C N P@C}}$ in other organs (Heart, Liver, Spleen, Lung, Kidney and Tumour) (Supplementary Fig. 22b). Histological and serum biochemistry assays suggested no evident toxic effects in vivo within one week of FA- $-c s{\\bar{\\mathrm{UCNP}}}\\varrho{\\mathrm{C}}$ administration when compared with the untreated group (Supplementary Fig. 20; Supplementary Methods for detailed experimental procedures). After $730–\\mathrm{nm}$ irradiation $(0.3\\mathrm{W}\\mathrm{cm}^{-2})$ for $3\\mathrm{min}$ three times per day for 6 days, the tumours shrank and were finally eliminated (Supplementary Figs 22c and 23; Supplementary Table 2), and the PTT-treated mice survived for over 2 months without mortality (Supplementary Fig. 22d). Thus, we have successfully proved that FA-csUCNP $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ can be used as a theranostic agent in vivo. \n\n# Discussion \n\nWe demonstrated carbon-coated core-shell upconversion nanocomposite NaLuF $_4$ :Yb,Er@NaLuF $_4\\textcircled{\\theta}$ Carbon $({\\mathsf{c s U C N P@C}})$ for monitoring of microscopic temperature in photothermal process. Under laser irradiation at $730\\mathrm{nm}$ , the carbon shell serves as an excellent photothermal agent for cancer therapy and simultaneously heats up the nanocomposite. By analysing upconversion luminescence emitted from the NaLuF $_{\\mathrm{~4~}}^{\\prime}$ :Yb,Er core of csUCNP $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ during the photothermal process, microscopic temperature of photothermal agent was detected and found to be much greater than the temperature at macroscopic level. By utilizing this phenomenon, we selectively ablated $\\scriptstyle\\mathrm{\\overrightarrow{csUCNP@C-}}$ labelled cancer cells under mild apparent temperature without harming adjacent non-labelled cells. The minimum separation between ablated cell and ambient preserved cell is $0.9\\upmu\\mathrm{m}$ . High spatial resolution photothermal ablation in vivo of tumour with minimal damage to normal tissues was also realized at low apparent temperature. In stark contrast to the existing principle of PTT focusing on elevating the apparent temperature to overheating level, which can cause severe adverse effects in normal tissues near the tumour area, our approach relying on ${\\mathsf{c s U C N P@C}}$ as a temperature-feedback photothermal agent indicated that an effective photothermal treatment with high accuracy can be realized under moderate conditions. This point proves that the strategy to ensure enough heating of the photothermal agent to ablate the labelled cancer cell and to simultaneously circumvent heat conduction to non-labelled normal tissues is possible. The indispensable advantage of this work is to use a microscopic temperature-feedback system to point out an optimized irradiation dose for facile photothermal therapy, which is different from the common understanding and cannot be achieved by previous macroscopic temperature measuring method. If automatic controlling device with automatic spectrum analysing and laser power controlling abilities is integrated, then the strategies of temperature-feedback photothermal therapy will be more diversified and can be conducted more conveniently. It is reasonable to presume that PTT possessing high therapeutic accuracy and mild treatment conditions can do more sophisticated operations such as precise lymphadenectomy, embolization of tumour microvessels and low-injury intervention treatment around vital organs. Our work presented a powerful tool to give an insight into the photothermal process at microscopic level. By utilizing the merits of the presented temperature-feedback upconversion nanocomposite, the mode and concept of PTT will be changed profoundly. \n\n# Methods \n\nSynthesis of oleate-coating NaLuF4:Yb,Er/Tm nanoparticles. Spherical-like oleate-coating $\\mathrm{NaLuF_{4}}$ :Yb,Er nanoparticles (OA-UCNPs) were synthesized via a modified solvothermal method54. In a typical procedure, 1 mmol lanthanide chloride $78\\%$ mol Lu, $20\\%$ mol Yb and $2\\%$ mol Er) were mixed with $6\\mathrm{ml}$ oleic acid (OA) and $17\\mathrm{ml}1$ -octadecene in a $\\scriptstyle100-{\\mathrm{ml}}$ three-necked flask. The resulting mixture was degassed at $90^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ , and then heated to $160^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ to form a transparent solution. After that, the solution was cooled to room temperature. Then $2.5\\mathrm{mmol\\NaOH}$ and 4 mmol $\\mathrm{NH}_{4}\\mathrm{F}$ dissolved in $5\\mathrm{ml}$ methanol were added and the mixture was degassed for another $30\\mathrm{min}$ at $90^{\\circ}\\mathrm{C}$ . Thereafter, the solution was heated to $300^{\\circ}\\mathrm{C}$ as quickly as possible and the temperature was maintained for $^{\\textrm{1h}}$ under an argon atmosphere. When the reaction was complete, an excess amount of ethanol was poured into the solution at room temperature. Nanoparticles were collected by centrifugation and washed three times with ethanol/cyclohexane $(1{:}1\\ \\mathrm{v}/\\mathrm{v})$ . The as-obtained nanoparticles OA-UCNPs were dispersed in $5\\mathrm{ml}$ cyclohexane for the following synthesis. \n\nSynthesis of NaLu $\\mathsf{I F}_{4}\\colon\\mathsf{Y b},\\mathsf{E r}@\\mathsf{N a L u F}_{4}$ nanoparticles. Rod-like oleate-coating $_{\\mathrm{NaLuF}_{4}:\\mathrm{Yb},\\mathrm{Er}@\\mathrm{NaLuF}_{4}}$ nanoparticles (OA-csUCNPs) were prepared by epitaxial growth on OA-UCNPs via a similar solvothermal method. One millimole of $\\mathrm{LuCl}_{3}$ was mixed with $12\\mathrm{ml}$ oleic acid and $15\\mathrm{ml}$ 1-octadecene in a $\\scriptstyle100-{\\mathrm{ml}}$ three-necked flask. Analogous to the procedure in synthesizing OA-UCNPs, the resulting mixture was degassed at $90^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ , and then heated to $160^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ to form a transparent solution and then cooled to room temperature. After that, $5\\mathrm{ml}$ cyclohexane solution containing OA-UCNPs was added into the system dropwise. The system was kept at $80^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ to evaporate cyclohexane. Then $2.5\\mathrm{mmol}$ NaOH and 4 mmol $\\mathrm{NH_{4}F}$ dissolved in $5\\mathrm{ml}$ methanol were added into the mixture, degassed at $90^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ , and finally maintained at $300^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . OA-csUCNPs were collected by centrifugation, washed three times with ethanol/cyclohexane (1:1, $\\mathbf{v}/\\mathbf{v})$ ), subsequently washed with acetone and isolated by centrifugation. The products were dried and stored for further use. \n\nSynthesis of carbon-coated csUCNPs. The OA-csUCNPs underwent a ligand-exchange process to make them water-soluble according to a reported method44. Briefly, OA-csUCNPs were dispersed in $10\\mathrm{ml}$ aqueous solution $\\mathrm{(pH=4)}$ by adding $0.1\\mathrm{mol}1^{-1}\\mathrm{HCl}$ and stirring for $^{2\\mathrm{h}}$ . Diethyl ether was used to extract oleic acid yielded from the protonated oleate ligand. After extraction was carried out three times, the products in the water layer were collected by centrifugation and washed three times with deionized water. The resulting ligand-free csUCNPs were easily dispersed in water. Then a certain amount of ligand-free csUCNPs were added into $0.4\\mathbf{M}$ glucose aqueous solution and were redispersed by sonication. The concentration of nanoparticles was kept at $2\\mathrm{mg}\\mathrm{ml}^{-1}$ . The solution was transferred to a $50\\mathrm{-ml}$ autoclave, sealed and hydrothermally treated at $160^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ . Finally, the system was allowed to cool to room temperature and carbon-coated csUCNPs $(\\mathsf{c s U C N P}@{\\mathsf{C}})$ were collected by centrifugation and washed three times with deionized water. \n\nSynthesis of folic acid-conjugated csUCNP $\\boldsymbol{\\Subset}$ . To synthesize FA functionalized $\\mathsf{c s U C N P@C}.$ $10\\mathrm{mg}$ FA was mixed with $10\\mathrm{mg4}$ -dimethylaminopyridine and $20\\mathrm{mg}$ $\\mathsf{c s U C N P@C}$ in $2\\mathrm{ml}$ anhydrous dimethylformamide under a $\\Nu_{2}$ atmosphere. sixteen milligrams of $N,N^{\\prime}$ -dicyclohexylcarbodiimide and $20\\upmu\\mathrm{l}$ triethylamine was then added into the mixture and stirred for $24\\mathrm{h}$ . An excess of diethyl ether was added to precipitate FA-conjugated csUCNP@C (FA-csUCNP $\\mathcal{\\varpi}\\mathrm{C}$ ). The as obtained FA- ${\\mathsf{c s U C N P@C}}$ were washed with methanol once and washed with ethanol twice and finally redispersed in deionized water. \n\nSimulation of temperature distribution in one-nanoparticle system. Here we used a finite element method to simulate the heat conduction process of a single nanoparticle in the aqueous phase. An ellipse with a long axis of $50\\mathrm{nm}$ and short axis of $40\\mathrm{nm}$ was set as the nanoparticle. A circle with a diameter of $1\\upmu\\mathrm{m}$ was set as the water surroundings. The temperature of the nanoparticle was set at $80^{\\circ}\\mathrm{C}$ and the external boundary of water was set at $35^{\\circ}\\mathrm{C}$ . The model only considered the heat-transfer process in the static condition. The temperature distribution presented is the final equilibrium state. The initial temperature was set at $35^{\\circ}\\mathrm{C}.$ . \n\nCalculation of the photothermal conversion efficiency. According to the method described in the literature, the total energy conservation for the system can be expressed by equation 2. \n\n$$\n\\sum_{i}m_{i}C_{\\mathrm{p},i}\\frac{\\mathrm{d}T}{\\mathrm{d}t}=Q_{\\mathrm{cs}}+Q_{\\mathrm{B}}-Q_{\\mathrm{sur}},\n$$ \n\nwhere $m$ and $C_{\\mathrm{p}}$ are the mass and heat capacity of water, respectively, $T$ is the solution temperature, $Q_{c s}$ is the energy induced by carbon shell of $\\operatorname{\\cdotsUCNP}@\\operatorname{C},$ $Q_{\\mathrm{B}}$ is the baseline energy induced by the sample cell, and $Q_{\\mathrm{sur}}$ is heat conduction away from the surface by air. \n\n$Q_{\\mathrm{{cs}}}$ is caused by the $\\pi$ -plasmon of the carbon shell under irradiation of $730\\mathrm{-nm}$ laser: \n\n$$\nQ_{c s}=I{\\left(1-10^{-A_{730}}\\right)}\\eta,\n$$ \n\nwhere $I$ is the laser power, $\\eta$ is the conversion efficiency from incident laser energy to thermal energy, and $A_{730}$ is the absorbance of carbon shell of ${\\mathsf{c s U C N P@C}}$ at wavelength of $730\\mathrm{nm}$ . On the other hand, $Q_{B},$ expressing heat dissipated from light absorbed by the sample cell, was measured independently to be $28.4\\mathrm{mW}$ using a quartz cuvette containing pure water without $\\mathsf{c s U C N P@C}$ . Moreover, $Q_{s u r}$ is in proportion to temperature for the outgoing thermal energy, as given by equation 4: \n\n$$\nQ_{\\mathrm{sur}}=h S(T-T_{\\mathrm{amb}}),\n$$ \n\nwhere $h$ is heat transfer coefficient, $s$ is the surface area of the container, and $T_{\\mathrm{amb}}$ is ambient temperature of the surroundings. \n\nAccording to equation 4, when the system temperature will reach a maximum, the heat input is equal to heat output: \n\n$$\nQ_{\\mathrm{CS}}+Q_{\\mathrm{B}}=h S(T_{\\mathrm{max}}-T_{\\mathrm{amb}}),\n$$ \n\nwhere $T_{\\mathrm{max}}$ is the equilibrium temperature. The $730\\mathrm{-nm}$ laser heat-conversion efficiency $(\\eta)$ can be determined by substituting equation 3 for $Q_{\\mathrm{{cs}}}$ into equation 5 and rearranging to get \n\n$$\n\\eta=\\frac{h S(T_{\\mathrm{max}}-T_{\\mathrm{amb}})-Q_{\\mathrm{B}}}{I(1-10^{-A_{730}})},\n$$ \n\nwhere $Q_{\\mathrm{B}}$ was measured independently to be $28.4\\mathrm{mW}$ , the $(T_{\\mathrm{max}}-T_{\\mathrm{amb}})$ was $22.3^{\\circ}\\mathrm{C}$ according to Supplementary Fig. 8a, $I$ is $1\\mathrm{W}\\mathrm{cm}^{-2}$ , $A_{730}$ is the absorbance (1.254) of $c s\\mathrm{UCNP}@C$ at $730\\mathrm{nm}$ (Supplementary Fig. 9). Here $h S$ is calculated by introducing $\\theta$ , is defined as the expression below: \n\n$$\n\\theta=\\frac{T-T_{\\mathrm{amb}}}{T_{\\mathrm{max}}-T_{\\mathrm{amb}}},\n$$ \n\nand a sample system time constant $\\tau_{s}$ \n\n$$\n\\tau_{s}=\\frac{\\sum_{i}m_{i}C_{p,i}}{h S},\n$$ \n\nwhich is substituted into equation 5 and rearranged to yield \n\n$$\n\\frac{\\mathrm{d}\\theta}{\\mathrm{d}t}=\\frac{1}{\\tau_{s}}\\left[\\frac{Q_{\\mathrm{cs}}+Q_{\\mathrm{B}}}{h S(T_{\\mathrm{max}}-T_{\\mathrm{amb}})}-\\theta\\right],\n$$ \n\nAt the cooling stage of the aqueous dispersion of the csUCNP $\\textstyle{\\mathcal{Q}}\\mathrm{C}$ , the light source was shut off, the $Q_{\\mathrm{cs}}+Q_{\\mathrm{B}}=0$ , reducing the equation 10: \n\n$$\n\\mathrm{d}t=-\\tau_{s}\\frac{\\mathrm{d}\\theta}{\\theta},\n$$ \n\nand integrating, giving the expression: \n\n$$\nt=-\\tau_{s}\\mathrm{ln}\\theta,\n$$ \n\nTherefore, time constant for heat transfer from the system is determined to be $\\tau_{s}=120.5s$ by applying the linear time data from the cooling period (after $400s)$ 1 versus negative natural logarithm of $\\theta$ (Supplementary Fig. 8b). In addition, the $m$ is $0.5{\\mathrm{g}}$ and the $C$ is $4.2\\:\\mathrm{Jg}^{-1}$ . Thus, according to equation 11, the $h S$ is deduced to be $17.4\\mathrm{mW}^{\\circ}\\mathrm{C}^{-1}$ . Substituting $17.4\\mathrm{mW}^{\\circ}\\mathrm{C}^{\\simeq1}$ into the $h S$ into equation 6, the $730\\mathrm{-nm}$ laser heat conversion efficiency $(\\eta)$ of $\\mathsf{c s U C N P@C}$ can be calculated to be $38.1\\%$ . \n\nEigen temperature measurement of csUCNP $@.$ in solution. To obtain temperature-upconversion luminescence calibration curve in solution (Apparatus diagram is shown in Supplementary Fig. 10.), a quartz cuvette containing $\\mathsf{c s U C N P@C}$ aqueous dispersion ( $2\\mathrm{{iml},\\bar{0}.5\\mathrm{{mgml}^{-1}}}$ ) was placed in Edinburgh FLS-920 fluorescence spectrometer with an external temperature controller. Aqueous solution was heated to different temperature from 5 to $100^{\\circ}\\mathrm{C}$ and the corresponding UCL from 500 to $580\\mathrm{nm}$ was recorded with excitation of a continuous wave (CW) 980-nm laser $(50\\mathrm{mW}\\mathrm{cm}^{-2},$ . The evolutions of the ratio of UCL emission peaks centred at 525 and $545\\mathrm{nm}$ as function of temperature are used as calibration curve for eigen temperature monitoring. To evaluate the photothermal process of $\\mathsf{c s U C N P@C}$ (Apparatus diagram is shown in Fig. 2a.), a quartz cuvette containing an aqueous dispersion $(2\\mathrm{ml})$ of $\\mathsf{c s U C N P@C}$ $(\\mathsf{0.5m g m l^{-1}})$ was irradiated with an optical fibre coupled $730\\mathrm{-nm}$ diode-laser (Weining Technology Development Co., Ltd. China) for $8\\mathrm{min}$ at a laser power of 0.3 and $\\breve{0}.8\\mathrm{W}\\mathrm{cm}^{-\\breve{2}}$ . A CW $980\\mathrm{-nm}$ laser was used to generate the upconversion luminescence. UCL spectra, from 500 to $580\\mathrm{nm}$ , were collected by Edinburgh FLS920 fluorescence spectrometer at different time intervals (0, 40, 120, 240, 360 and 480 s). The eigen temperature of $\\mathsf{c s U C N P@C}$ was determined from the ratio of the luminescence peaks which centred at $525\\mathrm{nm}$ and $545\\mathrm{nm}$ . Apparent temperature changes of the solution were recorded by a thermocouple thermometer. \n\nCell culture and confocal UCL imaging in vitro. HeLa cells and C2C12 myoblasts were provided by the Institute of Biochemistry and Cell Biology, SIBS, CAS (China). The cell lines used in this work (HeLa cells and C2C12 myoblasts) do not appear in the list of mis-identified cell lines made by International Cell Line Authentication Committee (ICLAC). Cells were grown in RPMI 1640 (Roswell Park Memorial Institute medium) supplemented with $10\\%$ fetal bovine serum at $37^{\\circ}\\mathrm{C}$ and $5\\%$ $\\mathrm{CO}_{2}$ . Cells $(5\\times10^{8}1^{-1})$ were plated on $14\\mathrm{-mm}$ glass coverslips under $100\\%$ humidity and allowed to adhere for $24\\mathrm{h}$ . After washing with PBS, the cells were incubated in a serum-free medium containing $200\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ csUCNP@C at $37^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ under $5\\%$ $\\mathrm{CO}_{2}$ and then washed with PBS three times to get rid of excess nanoparticles. Confocal UCL imaging was performed on our designed laser scanning UCL microscope with an Olympus FV1000 scanning unit. The set-ups of the confocal UCL microscopy and upconversion luminescence in vivo imaging system are detailed in ref. 55,56, respectively. The cells were excited by a CW laser operating at $980\\mathrm{nm}$ (Connet Fiber Optics, China) with the focused power of $\\mathrm{\\sim}19\\mathrm{mW}$ . A $60\\times$ oil-immersion objective lens was used and luminescence signals were detected in the wavelength region of $500{-}580\\mathrm{nm}$ . To qualitatively assess the photothermal effect in vitro, cells were irradiated with a $730\\mathrm{-nm}$ laser at a power density of $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ for $5\\mathrm{{min}}$ , and then stained with PI (propidium iodide) and calcein AM. PI signals were collected at $600{-}680\\mathrm{nm}$ excited with a CW $543\\mathrm{nm}$ laser. Calcein AM signals were collected at $500{-}580\\mathrm{nm}$ excited with a CW 488-nm laser. To assess the apoptosis promoting effect of $\\mathsf{c s U C N P@C}$ in vitro, cells were irradiated with a $730\\mathrm{-nm}$ laser at a low-power density of $0.2\\mathrm{W}\\mathrm{cm}^{-2}$ for $5\\mathrm{min}$ , and then stained with PI and Annexin V-FITC. Annexin V-FITC signals were collected at $500{-}550\\mathrm{nm}$ excited with a CW 488-nm laser. \n\nTemperature mapping of $\\mathsf{c s u c N P}@\\mathsf{C}$ labelled cells. For eigen temperature monitoring in cell, confocal UCL imaging was performed on our designed laser scanning UCL microscope with an Olympus FV1000 scanning unit. The HeLa cells were incubated in a serum-free medium containing $200\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ $\\mathsf{\\Pi}_{:S}\\mathsf{U C N P}@{\\mathsf{C}}$ at $37^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ under $5\\%$ $\\mathrm{CO}_{2}$ , and then washed with PBS three times to get rid of excess nanoparticles. Then $\\mathsf{c s U C N P@C}$ labelled HeLa cells were excited by a CW laser operating at $980\\mathrm{nm}$ (Connet Fiber Optics, China) with the focused power of $\\mathrm{\\sim}19\\mathrm{mW}$ . A $60\\times$ oil-immersion objective lens was used and luminescence signals were detected in the wavelength region of $540{-}570\\mathrm{nm}$ $(I_{545})$ and $515\\mathrm{-}535\\mathrm{nm}$ $(I_{525})$ , respectively. Eigen temperature mapping of csUCNP $@\\mathrm{C}$ labelled cells before and after $730\\mathrm{-nm}$ irradiation ( $0.3\\mathrm{W}\\mathrm{cm}^{-\\frac{3}{2}}$ for $5\\mathrm{{min}}$ ) was achieved by determining the ratio of $I_{545}$ and $I_{525}$ in confocal images based on calibration formula $((I_{545})/$ $(I_{525})=C$ exp $(-\\Delta E/k T)\\rangle$ . \n\nIn vitro photothermal cytotoxicity of csUCNP $@.$ . In vitro quantitative photothermal cytotoxicity of $\\mathsf{c s U C N P@C}$ was measured by performing MTT assays on HeLa cells. Cells were seeded into a 96-well cell culture plate at $5\\times10^{4}$ per well, under $100\\%$ humidity, and were cultured at $37^{\\circ}\\mathrm{C}$ and $5\\%$ $\\mathrm{CO}_{2}$ for $24\\mathrm{h}$ different concentrations of ${\\mathsf{c s U C N P@C}}$ (0, 50, 100, 150, 200, 300 and $400\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ , diluted in RPMI 1640) were then added to the wells. The cells were subsequently incubated for $^{3\\mathrm{h}}$ at $37^{\\circ}\\mathrm{C}$ under $5\\%$ $\\mathrm{CO}_{2}$ . Thereafter, the cells were exposed to an NIR laser $730\\mathrm{nm}$ , $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ ) for 0 and $5\\mathrm{{min}.}$ , respectively, and then incubated for another $24\\mathrm{h}$ . After that, MTT (5 ml; $5\\mathrm{mg}\\mathrm{ml}^{-1}.$ ) was added to each well and the plate was incubated for an additional $^{4\\mathrm{h}}$ at $37^{\\circ}\\mathrm{C}$ under $5\\%$ $\\mathrm{CO}_{2}$ . Following the addition of $10\\%$ SDS $(50\\upmu\\mathrm{l}$ per well), the assay plate was allowed to stand at room temperature for $12\\mathrm{{h}}$ . The optical density $\\mathrm{OD}_{570}$ value $(A b s.)$ of each well, with background subtraction at $690\\mathrm{nm}$ , was measured by means of a Tecan Infinite M200 monochromator-based multifunction microplate reader. The following formula was used to calculate the inhibition of cell growth: \n\nCell viability $\\left(\\%\\right)=$ mean of $A b s$ : value of treatment group/mean Abs: value of controlÞ $100\\%$ \n\nTemperature monitoring in tissue phantom. Apparatus configuration and the measurement of UCL-temperature calibration curve are similar to that in aqueous solution, but the aqueous solution of $c s\\mathrm{UCNP}@\\mathrm{C}$ was replaced by tissue phantom (see Supplementary Methods for the synthesis of tissue phantom). To evaluate the photothermal process of $\\mathsf{c s U C N P@C}$ in tissue phantom, a double-layer phantom where the lower layer of the phantom containing $\\mathsf{c s U C N P@C}$ (Layer 1, $\\mathrm{\\sim10–mm}$ thick) simulating the tumour area for therapy and the upper layer without $\\mathsf{c s U C N P@C}$ (Layer 2, $\\sim4\\mathrm{-mm}$ thick) simulating normal tissue was prepared. Schematic diagram of temperature monitoring in tissue phantom is shown in Fig. 4a. Tissue phantom was irradiated with an optical fibre-coupled $730\\mathrm{-nm}$ diode-laser (Weining Technology Development Co., Ltd. China) for $8\\mathrm{min}$ at a laser power of 0.3 and $0.8\\mathrm{W}\\mathrm{cm}^{-2}$ . A CW $980\\mathrm{-nm}$ laser was used to generate the UCL. UCL spectra, from 500 to $580\\mathrm{nm}$ , were collected by fibre-optic spectrometer $({\\mathrm{PG}}2000{\\mathrm{Pro}}$ , Ideaoptics, China) at different time intervals (0, 40, 120, 240, 360 and $480s)$ for the calculation of eigen temperature. Thermal camera (FLIR E40) was used to record the apparent temperature. Investigation of heat conduction from layer 1 to layer 2 was also carried out by reading the temperature value in every other millimetre around the borderline of layer 1 and layer 2 from the thermal images. \n\nTumour xenografts. Animal procedures were in agreement with the guidelines of the Institutional Animal Care and Use Committee, School of Pharmacy, Fudan University. For in vivo photothermal therapy with ${\\mathsf{c s U C N P@C}}$ pre-labelled tumour, HeLa cells were incubated in a serum-free medium containing $200\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ ${\\mathsf{c s U C N P@C}}$ at $37^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ under $5\\%$ $\\mathrm{CO}_{2}$ , and then washed with PBS three times to get rid of excess nanoparticles. After that, HeLa cells were collected by incubation with $0.05\\%$ trypsin-EDTA. Cells were collected by centrifugation and resuspended in sterile PBS. Cells ( $\\mathrm{10^{7}}$ cells per site) were subcutaneously implanted into 4-week-old male athymic nude mice. Photothermal therapy was performed when the tumours reached an average diameter of $0.6\\mathrm{cm}$ . For in vivo photothermal therapy, HeLa cells were collected by incubation with $0.05\\%$ trypsin-EDTA. Cells were collected by centrifugation and resuspended in sterile PBS. Cells $\\mathrm{10^{8}}$ cells per site) were subcutaneously implanted into 4-weekold female athymic Balb/c mice. Photothermal therapy was performed when the tumours reached an average diameter of $0.6~\\mathrm{cm}$ . \n\nUCL bioimaging in vivo. UCL imaging in vivo was performed with an in vivo imaging system designed by our group, using two external $0\\sim5\\mathrm{W}$ adjustable CW $980\\mathrm{-nm}$ lasers (Connet Fiber Optics Co., China) as the excited source and an Andor DU897 EMCCD as the signal collector. Excitation was provided by the CW laser at $980\\mathrm{nm}$ and UCL signals were collected using a $720–\\mathrm{nm}$ short-pass filter. In the case of $\\mathsf{c s U C N P@C}$ -labelled HeLa cells transplantation, UCL imaging was performed when the tumour reached an average diameter of $0.6\\mathrm{cm}$ . In the case of in vivo targeting imaging, FA-csUCNP@C were intravenously injected into HeLa cell tumour-bearing athymic Balb/c mice. Whole-body imaging of the nude mice was performed 1 h after the injection. \n\nEigen temperature monitoring in vivo. Eigen temperature monitoring in vivo was conducted in $\\mathsf{c s U C N P@C}$ labelled HeLa tumour-bearing nude mice. 0–5 W adjustable CW $980\\mathrm{-nm}$ lasers was chosen as the excitation source of UCL and an optical fibre-coupled $730\\mathrm{-nm}$ diode-laser was used for photothermal excitation. Fibre-optic spectrometer was used to collect the UCL signals and a $720\\mathrm{-nm}$ shortpass filter was installed in front of the probe of the spectrometer. Under $730\\mathrm{-nm}$ laser irradiation at 0, 0.3 and $0.8\\mathrm{W}\\mathrm{cm}^{-2}$ for $3\\mathrm{min}$ , upconversion emission spectra were collected by fibre-optic spectrometer and the eigen temperature under different laser-power density were calculated by the luminescence spectra with the temperature calibration curve got from the tissue phantom. \n\nPhotothermal therapy in vivo. An optical fibre-coupled $730\\mathrm{-nm}$ diode-laser (Weining Technology Development Co., Ltd. China) was used to irradiate tumours during the experiments. For photothermal treatment, the $730\\mathrm{-nm}$ laser beam with a diameter of $\\sim10\\mathrm{mm}$ was focused on the tumour area at the power density of $0.3\\mathrm{W}\\mathrm{cm}^{-2}$ for $3\\mathrm{min}$ . Infrared thermal images were taken by an FLIR E40 thermal imaging camera. Tumour sizes of treatment group ( $\\operatorname{\\'}_{C S}\\operatorname{UCNP}_{C}\\varnothing\\operatorname{C}$ -labelled tumour with $730\\mathrm{-nm}$ irradiation in $\\mathsf{c s U C N P@C}$ -labelled HeLa cells transplantation and FA-csUCNP $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ targeted tumour with $730–\\mathrm{nm}$ irradiation in targeting photothermal therapy in vivo) and reference groups (untreated mice, mice exposed to the $730\\mathrm{-nm}$ laser only, and $\\mathsf{c s U C N P@C}.$ -treated mice without $730\\mathrm{-nm}$ irradiation) were measured every day after treatment. Each group contained five mice for relatively rational evaluation. The tumour sizes were measured using a caliper and calculated as volume $=(\\mathrm{tumour~length})\\times(\\mathrm{tumour~width})^{2}/2$ . Relative tumour volumes were normalized and were calculated as $V/V_{0}$ ( $\\cdot V_{0}$ is the tumour volume when the treatment was initiated). According to the guidelines of Institutional Animal Care and Use Committee, School of Pharmacy, Fudan University, the maximum permitted tumour size is $20\\mathrm{mm}$ in an average diameter for mice. The tumours’ size in this work is confined within this criterion. \n\n# References \n\n1. Neidle, S. & Thurston, D. E. Chemical approaches to the discovery and development of cancer therapies. Nat. Rev. Cancer 5, 285–296 (2005). \n2. Davis, M. E., Chen, Z. & Shin, D. M. Nanoparticle therapeutics: An emerging treatment modality for cancer. Nat. Rev. Drug Discov. 7, 771–782 (2008). \n3. Chu, K. F. & Dupuy, D. E. Thermal ablation of tumours: biological mechanisms and advances in therapy. Nat. Rev. Cancer 14, 199–208 (2014). \n4. Gillams, A. R. The use of radiofrequency in cancer. Br. J. Cancer 92, 1825–1829 (2005). \n5. Simon, C. J., Dupuy, D. E. & Mayo-Smith, W. W. Microwave ablation: Principles and applications. Radiographics 25, S69–S83 (2005). \n6. Shinohara, K. Thermal ablation of prostate diseases: Advantages and limitations. Int. J. Hyperther. 20, 679–697 (2004). \n7. Jansen, M. C. et al. Adverse effects of radiofrequency ablation of liver tumours in the netherlands. Br. J. Surg. 92, 1248–1254 (2005). \n8. Hirsch, L. R. et al. Nanoshell-mediated near-infrared thermal therapy of tumors under magnetic resonance guidance. Proc. Natl Acad. Sci. USA 100, 13549–13554 (2003). \n9. Huang, X., El-Sayed, I. H., Qian, W. & El-Sayed, M. A. Cancer cell imaging and photothermal therapy in the near-infrared region by using gold nanorods. J. Am. Chem. Soc. 128, 2115–2120 (2006). \n10. Kam, N. W. S., O’Connell, M., Wisdom, J. A. & Dai, H. Carbon nanotubes as multifunctional biological transporters and near-infrared agents for selective cancer cell destruction. Proc. Natl Acad. Sci. USA 102, 11600–11605 (2005). \n11. Seo, W. S. et al. FeCo/graphitic-shell nanocrystals as advanced magneticresonance-imaging and near-infrared agents. Nat. Mater. 5, 971–976 (2006). \n12. Yang, K. et al. Graphene in mice: Ultrahigh in vivo tumor uptake and efficient photothermal therapy. Nano Lett. 10, 3318–3323 (2010). \n13. Robinson, J. T. et al. Ultrasmall reduced graphene oxide with high nearinfrared absorbance for photothermal therapy. J. Am. Chem. Soc. 133, 6825–6831 (2011). \n14. Huang, X. et al. Freestanding palladium nanosheets with plasmonic and catalytic properties. Nat. Nano 6, 28–32 (2011). \n15. Tian, Q. et al. Sub- $\\cdot10\\ \\mathrm{nm}$ $\\mathrm{Fe}_{3}\\mathrm{O}_{4}@\\mathrm{Cu}_{2-\\mathrm{x}}\\mathrm{S}$ core–shell nanoparticles for dualmodal imaging and photothermal therapy. J. Am. Chem. Soc. 135, 8571–8577 (2013). \n16. Lovell, J. F. et al. Porphysome nanovesicles generated by porphyrin bilayers for use as multimodal biophotonic contrast agents. Nat. Mater. 10, 324–332 (2011). \n17. Cheng, L. et al. PEGylated $\\mathrm{WS}_{2}$ nanosheets as a multifunctional theranostic agent for in vivo dual-modal CT/photoacoustic imaging guided photothermal therapy. Adv. Mater. 26, 1886–1893 (2014). \n18. Kyrsting, A., Bendix, P. M., Stamou, D. G. & Oddershede, L. B. Heat profiling of three-dimensionally optically trapped gold nanoparticles using vesicle cargo release. Nano Lett. 11, 888–892 (2010). \n19. Freddi, S. et al. A molecular thermometer for nanoparticles for optical hyperthermia. Nano Lett. 13, 2004–2010 (2013). \n20. Wang, X.-D., Wolfbeis, O. S. & Meier, R. J. Luminescent probes and sensors for temperature. Chem. Soc. Rev. 42, 7834–7869 (2013). \n21. Lo¨w, P., Kim, B., Takama, N. & Bergaud, C. High-spatial-resolution surfacetemperature mapping using fluorescent thermometry. Small 4, 908–914 (2008). \n22. Okabe, K. et al. Intracellular temperature mapping with a fluorescent polymeric thermometer and fluorescence lifetime imaging microscopy. Nat. Commun. 3, 705 (2012). \n23. Vlaskin, V. A., Janssen, N., van Rijssel, J., Beaulac, R. M. & Gamelin, D. R. Tunable dual emission in doped semiconductor nanocrystals. Nano Lett. 10, 3670–3674 (2010). \n24. Vetrone, F. et al. Temperature sensing using fluorescent nanothermometers. ACS Nano 4, 3254–3258 (2010). \n25. Sedlmeier, A., Achatz, D. E., Fischer, L. H., Gorris, H. H. & Wolfbeis, O. S. Photon upconverting nanoparticles for luminescent sensing of temperature. Nanoscale 4, 7090–7096 (2012). \n26. Wang, J. et al. Enhancing multiphoton upconversion through energy clustering at sublattice level. Nat. Mater. 13, 157–162 (2014). \n27. B¨unzli, J.-C. G. Lanthanide luminescence for biomedical analyses and imaging. Chem. Rev. 110, 2729–2755 (2010). \n28. Idris, N. M. et al. In vivo photodynamic therapy using upconversion nanoparticles as remote-controlled nanotransducers. Nat. Med. 18, 1580–1585 (2012). \n29. Jayakumar, M. K. G., Idris, N. M. & Zhang, Y. Remote activation of biomolecules in deep tissues using near-infrared-to-UV upconversion nanotransducers. Proc. Natl Acad. Sci. USA 109, 8483–8488 (2012). \n30. Park, Y. I. et al. Theranostic probe based on lanthanide-doped nanoparticles for simultaneous in vivo dual-modal imaging and photodynamic therapy. Adv. Mater. 24, 5755–5761 (2012). \n31. Wang, Y.-F. et al. ${\\mathrm{Nd}}^{3+}$ -sensitized upconversion nanophosphors: Efficient in vivo bioimaging probes with minimized heating effect. ACS Nano 7, 7200–7206 (2013). \n32. Huang, P. et al. Lanthanide-doped $\\mathrm{LiLuF_{4}}$ upconversion nanoprobes for the detection of disease biomarkers. Angew. Chem. Int. Ed. 53, 1252–1257 (2014). \n33. Tang, Q. et al. Color tuning and white light emission via in situ doping of luminescent lanthanide metal–organic frameworks. Inorg. Chem. 53, 289–293 (2013). \n34. Lu, Y. et al. Tunable lifetime multiplexing using luminescent nanocrystals. Nat. Photon. 8, 32–36 (2014). \n35. Johnson, N. J. J., Korinek, A., Dong, C. & van Veggel, F. C. J. M. Self-focusing by ostwald ripening: A strategy for layer-by-layer epitaxial growth on upconverting nanocrystals. J. Am. Chem. Soc. 134, 11068–11071 (2012). \n36. Yi, G. S. & Chow, G. M. Synthesis of hexagonal-phase $\\mathrm{NaYF_{4};Y b,E r}$ and $\\mathrm{\\DeltaNaYF_{4}}$ :Yb,Tm nanocrystals with efficient up-conversion fluorescence. Adv. Funct. Mater. 16, 2324–2329 (2006). \n37. Fan, W. et al. Rattle-structured multifunctional nanotheranostics for synergetic chemo-/radiotherapy and simultaneous magnetic/luminescent dual-mode imaging. J. Am. Chem. Soc. 135, 6494–6503 (2013). \n38. Ma, P. et al. Rational design of multifunctional upconversion nanocrystals/ polymer nanocomposites for cisplatin (IV) delivery and biomedical imaging. Adv. Mater. 25, 4898–4905 (2013). \n39. Shen, J., Zhao, L. & Han, G. Lanthanide-doped upconverting luminescent nanoparticle platforms for optical imaging-guided drug delivery and therapy. Adv. Drug Deliver. Rev. 65, 744–755 (2013). \n40. Chen, G., Qiu, H., Prasad, P. N. & Chen, X. Upconversion nanoparticles: design, nanochemistry, and applications in theranostics. Chem. Rev. 114, 5161–5214 (2014). \n41. Shan, G. B., Weissleder, R. & Hilderbrand, S. A. Upconverting organic dye doped core-shell nano-composites for dual-modality NIR imaging and photothermal therapy. Theranostics 3, 267–274 (2013). \n42. Dong, B. et al. Multifunctional $\\mathrm{NaYF_{4}:Y b^{3}+,E r^{3}+\\ @A g}$ core/shell nanocomposites: Integration of upconversion imaging and photothermal therapy. J. Mater. Chem. 21, 6193–6200 (2011). \n43. Zhou, J., Liu, Z. & Li, F. Upconversion nanophosphors for small-animal imaging. Chem. Soc. Rev. 41, 1323–1349 (2012). \n44. Bogdan, N., Vetrone, F., Ozin, G. A. & Capobianco, J. A. Synthesis of ligandfree colloidally stable water dispersible brightly luminescent lanthanide-doped upconverting nanoparticles. Nano Lett. 11, 835–840 (2011). \n45. Sun, X. & Li, Y. Colloidal carbon spheres and their core/shell structures with noble-metal nanoparticles. Angew. Chem. Int. Ed. 43, 597–601 (2004). \n46. Hessel, C. M. et al. Copper selenide nanocrystals for photothermal therapy. Nano Lett. 11, 2560–2566 (2011). \n47. Tian, Q. et al. Hydrophilic $\\mathrm{Cu}_{9}\\mathrm{S}_{5}$ nanocrystals: A photothermal agent with a $25.7\\%$ heat conversion efficiency for photothermal ablation of cancer cells in vivo. ACS Nano 5, 9761–9771 (2011). \n48. Liu, C. et al. One-step synthesis of surface passivated carbon nanodots by microwave assisted pyrolysis for enhanced multicolor photoluminescence and bioimaging. J. Mater. Chem. 21, 13163–13167 (2011). \n49. Liu, C. et al. Nano-carrier for gene delivery and bioimaging based on carbon dots with PEI-passivation enhanced fluorescence. Biomaterials 33, 3604–3613 (2012). \n50. Kucsko, G. et al. Nanometre-scale thermometry in a living cell. Nature 500, \n54–58 (2013). \n51. Shang, L., Stockmar, F., Azadfar, N. & Nienhaus, G. U. Intracellular thermometry by using fluorescent gold nanoclusters. Angew. Chem. Int. Ed. 52, \n11154–11157 (2013). \n52. Arai, S., Lee, S.-C., Zhai, D., Suzuki, M. & Chang, Y. T. A molecular fluorescent probe for targeted visualization of temperature at the endoplasmic reticulum. Sci. Rep. 4, 6701 (2014). \n53. Dewey, W. C. Arrhenius relationships from the molecule and cell to the clinic. Int. J. Hyperther. 25, 3–20 (2009). \n54. Li, Z. & Zhang, Y. An efficient and user-friendly method for the synthesis of hexagonal-phase $_{\\mathrm{NaYF_{4}:Y b,E r/T m}}$ nanocrystals with controllable shape and upconversion fluorescence. Nanotechnology 19, 345606 (2008). \n55. Yu, M. et al. Laser scanning up-conversion luminescence microscopy for imaging cells labeled with rare-earth nanophosphors. Anal. Chem. 81, 930–935 (2009). \n56. Xiong, L. et al. High contrast upconversion luminescence targeted imaging in vivo using peptide-labeled nanophosphors. Anal. Chem. 81, 8687–8694 (2009). \n\n# Acknowledgements \n\nWe thank National Basic Research Program of China (2015CB931800, 2013CB733700), National Natural Science Foundation of China (21527801, 21231004) and the CAS/ SAFEA International Partnership Program for Creative Research Teams for financial support. \n\n# Author contributions \n\nThe manuscript was written by X.Z, W.F. and F.L. The experiment and analysis were carried out by X.Z., W.F., J.C., J.L., M.C. and Y.S. The experimental work and the manuscript were supervised by Y.-W.T., W.F. and F.L. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Zhu, X. et al. Temperature-feedback upconversion nanocomposite for accurate photothermal therapy at facile temperature. Nat. Commun. 7:10437 doi: 10.1038/ncomms10437 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_srep31110", + "DOI": "10.1038/srep31110", + "DOI Link": "http://dx.doi.org/10.1038/srep31110", + "Relative Dir Path": "mds/10.1038_srep31110", + "Article Title": "Multimaterial 4D Printing with Tailorable Shape Memory Polymers", + "Authors": "Ge, Q; Sakhaei, AH; Lee, H; Dunn, CK; Fang, NX; Dunn, ML", + "Source Title": "SCIENTIFIC REPORTS", + "Abstract": "We present a new 4D printing approach that can create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures. The approach is based on high resolution projection microstereolithography (P mu SL) and uses a family of photo-curable methacrylate based copolymer networks. We designed the constituents and compositions to exhibit desired thermomechanical behavior (including rubbery modulus, glass transition temperature and failure strain which is more than 300% and larger than any existing printable materials) to enable controlled shape memory behavior. We used a high resolution, high contrast digital micro display to ensure high resolution of photo-curing methacrylate based SMPs that requires higher exposure energy than more common acrylate based polymers. An automated material exchange process enables the manufacture of 3D composite architectures from multiple photo-curable SMPs. In order to understand the behavior of the 3D composite microarchitectures, we carry out high fidelity computational simulations of their complex nonlinear, time-dependent behavior and study important design considerations including local deformation, shape fixity and free recovery rate. Simulations are in good agreement with experiments for a series of single and multimaterial components and can be used to facilitate the design of SMP 3D structures.", + "Times Cited, WoS Core": 839, + "Times Cited, All Databases": 934, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000392100600001", + "Markdown": "# SCIENTIFIC REPORTS \n\n# OPEN \n\n# Multimaterial 4D Printing with Tailorable Shape Memory Polymers \n\nreceived: 01 April 2016 \naccepted: 14 July 2016 \nPublished: 08 August 2016 \n\nQi Ge1,2, Amir Hosein Sakhaei1, Howon Lee2, Conner K. Dunn3, Nicholas X. Fang2 & Martin L. Dunn1 \n\nWe present a new 4D printing approach that can create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures. The approach is based on high resolution projection microstereolithography $(\\mathsf{P}\\mu\\mathsf{S}\\mathsf{L})$ and uses a family of photo-curable methacrylate based copolymer networks. We designed the constituents and compositions to exhibit desired thermomechanical behavior (including rubbery modulus, glass transition temperature and failure strain which is more than $300\\%$ and larger than any existing printable materials) to enable controlled shape memory behavior. We used a high resolution, high contrast digital micro display to ensure high resolution of photo-curing methacrylate based SMPs that requires higher exposure energy than more common acrylate based polymers. An automated material exchange process enables the manufacture of 3D composite architectures from multiple photo-curable SMPs. In order to understand the behavior of the 3D composite microarchitectures, we carry out high fidelity computational simulations of their complex nonlinear, time-dependent behavior and study important design considerations including local deformation, shape fixity and free recovery rate. Simulations are in good agreement with experiments for a series of single and multimaterial components and can be used to facilitate the design of SMP 3D structures. \n\nThree-dimension (3D) printing technology allows the creation of complex geometries with precisely prescribed microarchitectures that enable new functionality or improved and even optimal performance. While 3D printing has largely emphasized manufacturing with a single material, recent advances in multimaterial printing enable the creation of heterogeneous structures or composites that have myriad scientific and technological applications1–5. Commercial printing systems with these capabilities have been used in many innovative applications, but are limited because their development has largely proceeded with objectives of creating printed components with reliable mechanical properties, and applications have generally emphasized linear elastic behavior with small deformations where the innovation arises from the sophisticated geometry. Independently, soft active materials (SAMs) as a class of emerging materials with the capability of exhibiting large elastic deformation in response to environmental stimuli such as heat6,7, light8,9, and electricity10,11, are enabling the creation of functional active components. SAMs including shape memory polymers (SMPs), hydrogels, dielectric elastomers have been used to fabricate biomedical devices7,12,13, wearable devices14,15, artificial muscles10,11 and other smart products16–18. However, applications of SAMs are limited by the current manufacturing approaches which constrain active structures and devices to simple geometries, often created with a single material, and they have yet to broadly exploit the potential of tailored microarchitectures. \n\nThis picture is changing as 3D printing and SAMs are being integrated. The most notable example is the recently developed $\\ensuremath{{}^{\\circ}}4\\ensuremath{\\mathrm{D}}$ printing” technology2,3 in which the printed 3D structures are able to actively transform configurations over time in response to environmental stimuli. There are two types of SAMs mainly used to realize 4D printing: hydrogels that swell when solvent molecules diffuse into polymer network and shape memory polymers (SMPs) that are capable of fixing temporary shapes and recovering to the permanent shape upon heating. The examples of the hydrogel-based 4D printing include complex self-evolving structures actuated by multilayer joints5, active valves made of thermally sensitive hydrogel19, pattern transformation realized by heat-shrinkable polymer20, and biominic 4D printing achieved by anisotropic hydrogel composites with cellulose fibrils21. However, the low modulus of hydrogels ranging from ${\\sim}\\mathrm{kPa}$ to $\\bar{\\sim}100\\dot{\\mathrm{kPa}}^{15,21}$ , and the solvent diffusion based slow response rates in the time scale of a few ten minutes, hours, and even days5,21,22 make the hydrogel based 4D printing not suitable for structural and actuation applications. Compared to hydrogels, SMPs have higher modulus ranging ${\\sim}\\mathrm{MPa}$ to ${\\sim}\\mathrm{GPa}^{7,23}$ and faster response rates (in the scale of seconds to minutes depending on actuation temperature)24,25. The examples of the SMP based 4D printing include printed active composites where precisely prescribed SMP fibers were used to activate the complex shape change2,3, sequential self-folding structured where SMP hinges with different responding rates were deliberately placed at different positions4, and multi-shape active composites where two SMP fibers with different glass transition temperatures26. To date, the SMP based 4D printing were mainly realized by commercial Polyjet 3D printer (Stratasys, Objet) which create materials with properties ranging between rigid and elastomeric by mixing the two base resins. The fact that users are not allowed to freely tune the thermomechanical properties beyond the realm of available resins impedes this 4D printing technology to advance to a wider range of applications. For example, the capability of 4D printed actuation is limited as the printed digital materials break at $10-25\\%^{27}$ ; the printed structures could not be used in high temperature applications as the highest glass transition temperature of the available resin is about ${\\sim}70^{\\circ}\\mathrm{C^{4}}$ . In addition, this technology is not suitable for microscale applications as the lateral printing resolution is up to $200\\mu\\mathrm{m}$ inherently limited by the Polyjet printing method28. \n\nIn this paper we report a new approach that enables high resolution multimaterial 4D printing by printing highly tailorable SMPs on a projection microstereolithography $(\\mathrm{P}\\mu\\mathrm{SL})$ based additive manufacturing system. We synthesize photo-curable methacrylate based copolymer networks using commercially-available materials. By tuning the material constituents and compositions, the flexibility of the methacrylate based copolymer networks enables highly tailorable SMP thermomechanical properties including rubbery modulus (from ${\\sim}\\mathrm{MPa}$ to ${\\sim}100\\mathrm{MPa}$ ), glass transition temperature (from $\\sim-50^{\\circ}\\mathrm{C}$ to ${\\sim}180^{\\circ}\\mathrm{C}$ , and the failure strain (up to $\\sim300\\%$ ). Methacrylate based SMPs with different constituents or compositions form strong interface bonds with each other and enable fabrication of 3D structures made of multiple SMPs that can exhibit new functionality resulting from their dynamic thermomechanical properties. The $\\mathrm{P}\\mu\\mathrm{SL}$ based additive manufacturing system with high lateral resolution up to ${\\sim}1\\mu\\mathrm{m}$ exploits a digital micro-display device as a dynamic photo mask to dynamically generate and reconfigure light patterns, which then converts liquid monomer resin into solid via photo-polymerization in a layer-by-layer fashion29–31. A high resolution, high contrast digital micro-display device ensures high resolution structure made of methacrylate based SMPs that require higher exposure energy than acrylate based polymers which have been frequently used for 3D printing but do not have SM effect. Multimaterial manufacturing is achieved via an automatic material exchanging mechanism integrated into the $\\mathrm{P}\\mu\\mathrm{SL}$ additive manufacturing system. In addition, a highly fidelity computational tool based on the understanding of the shape memory behavior is used to facilitate the design of SMP 3D structures by simulating important design considerations including local deformation, shape fixity and free recovery rate. We believe this novel approach will translate the SMP based 4D printing into a wide variety of practical applications, including biomedical devices12,13,32,33, deployable aerospace structures34,35, shopping bags36,37, and shape changing photovoltaic solar cells38,39. \n\n# Results \n\nMultimaterial additive manufacturing system.  We fabricate high resolution multimaterial shape memory structures on an additive manufacturing apparatus based on projection microstereolithography $(\\mathrm{P}\\bar{\\mu}\\mathrm{SL})^{29-31}$ . As shown schematically in Fig. 1a, a computer aid design (CAD) model is first sliced into a series of closely spaced horizontal two-dimension (2D) digital images. Then, these 2D images are transmitted to a digital micro display which works as a dynamic photo-mask30. Ultraviolet (UV) light produced from a light emitting diode (LED) array is spatially modulated with the patterns of the corresponding 2D images, and illuminated onto the surface of photo-curable polymer solution. Once the material in the exposed area is solidified to form a layer, the substrate on which the fabricated structure rests is lowered by a translational stage, followed by projection of the next image to polymerize a new layer on top of the preceding one. This process proceeds iteratively until the entire structure is fabricated. In the current setup, the projection area is about $3.2\\mathrm{cm}\\times2.4\\mathrm{cm}$ resulting in a pixel size of ${\\sim}30\\mu\\mathrm{m}\\times30\\mu\\mathrm{m}$ . The lateral resolution can be further improved up to as high as ${\\sim}1\\mu\\mathrm{m}$ if a projection lens with high optical magnification is used29. The step-and-repeat method can be employed to extend printing area without compromising lateral resolution30. Multimaterial fabrication is enabled by automating polymer solution exchange during the printing process. Although many efforts40–42 have been made to develop multimaterial fabrication systems by adding the automated polymer solution exchanging mechanisms into the “top-down” fabrication system (as shown schematically in Fig. 1a) where the modulated UV light projected downwards to the polymer resin, the multimaterial fabrication system developed based on the “bottom-up” approach making the depth of transparent polymer solution containers independent of the part height helps to significantly reduce material contamination and improve efficiency of material use43, but requires precise control of the oxygen concentration to separate the printed parts from the transparent polymer solution containers without damaging them43,44. \n\nWe fabricate shape memory structures using photo-curable methacrylate copolymers that form polymer networks via free radical photo-polymerization45–47. To understand the thermomechanical properties and shape memory (SM) effects of the materials and structures, we prepared polymer resins by using a mono-functional monomer, Benzyl methacrylate (BMA) as linear chain builder (LCB), and difunctional oligomers, Poly (ethylene glycol) dimethacrylate (PEGDMA), Bisphenol A ethoxylate dimethacrylate (BPA), and Di(ethylene glycol) dimethacrylate (DEGDMA) as crosslinkers that connect the linear chains to form a cross-linked network (shown in Fig. 1b). Details about polymer resin preparations can be founded in Methods. More selections of LCBs and crosslinkers are suggested by Safranski and Gall48. \n\nExperimental Characterization.  The photo-curable methacrylate networks provide high tailorability of thermomechanical properties of printed SMPs. Among them, the glass transition temperature $(T_{g})$ , the rubbery modulus $(E_{r})$ and the failure strain $(\\varepsilon_{f})$ are the most critical properties for the design of active components as they dictate the shape recovery temperature and rate, constrained recovery stress, and capability of shape change and/ or actuation, respectively $^{24,48-51}$ . Figure 2a–c demonstrates that these thermomechanical properties can be tailored over wide ranges and still printed, by either controlling the concentration of crosslinker or using different crosslinkers. In Fig. 2a, for instance, for the copolymer network system consisting of BMA and crosslinker PEGDMA with molecular weight of $550{\\mathrm{g/mole}}$ (denoted as $\\mathsf{B}+\\mathsf{P}550\\rangle$ , the $T_{g}$ starts from ${\\sim}65^{\\circ}\\mathrm{C}$ where the copolymer network system consists of pure BMA, and then decreases with increase in the crosslinker concentration (See Supplementary Materials S1.1 I and Fig. S1a). The $T_{g}$ of the copolymer networks consisting of the crosslinker PEGDMA with molecular weight of $750\\mathrm{g/mole}$ (denoted as $\\mathrm{B}+\\mathrm{P}750\\mathrm{,}$ and the crosslinker BPA with molecular weight of $1700\\mathrm{g/mole}$ (denoted as $\\mathrm{B+BPA}_{\\mathrm{\\ell}}^{\\mathrm{\\prime}}$ follows the same trend of the $\\mathrm{B}+\\mathrm{P}550$ copolymer networks (Fig. $\\mathrm{s}1\\mathrm{b},\\mathrm{c},$ ), while the $T_{g}$ increases with increase in the crosslinker concentration of the copolymer network consisting of BMA and DEGDMA (denoted as $\\mathrm{B}+\\mathrm{DEG}$ , Fig. S1d). The Couchman equation52 can be used to guide material design with a desired $T_{g}$ by mixing the LCB and crosslinker with prescribed ratios: $\\Breve{1}/T_{_{g}}=M_{1}/T_{g}^{1}+M_{2}/T_{g}^{1}$ . Here, $T_{g_{\\star}}^{1}$ and ${\\boldsymbol{T}}_{\\boldsymbol{g}}^{1}$ are the glass transition temperatures of the respective pure-components, and $\\mathcal{M}_{1}$ and $\\hat{M}_{2}$ are the corresponding mass fractions. In Fig. 2a, using the current LCB monomer, namely BMA, and crosslinkers, namely PEGDMA, BPA and DEGDMA allows us to adjust $T_{g}$ from $\\sim-50^{\\circ}\\mathrm{C}$ to ${\\sim}180^{\\circ}\\mathrm{C}.$ , while more flexibility can be obtained by choosing different LCB monomers and crosslinkers48 or even mixing more than one LCB monomers and crosslinkers to prepare the polymer resin53. \n\n![](images/605a83068833e36de890fc5e3b9de96167b0a8103ffd465b90a60a74e92a35e4.jpg) \nFigure 1.  Schematics of multimaterial additive manufacture system. (a) A workflow illustrates the process of fabricating a multimaterial structure based on $\\mathrm{P}\\mu\\mathrm{SL}$ (b) Photo-curable shape memory polymer network is constructed by mono-functional monomer, Benzyl methacrylate (BMA) as linear chain builder (LCB), and multi-functional oligomers, Poly (ethylene glycol) dimethacrylate (PEGDMA), Bisphenol A ethoxylate dimethacrylate (BPA), and Di(ethylene glycol) dimethacrylate (DEGDMA) as crosslinkers. \n\n![](images/9bbb6f3f7eff106ebf0438fdf13decff02e07a7611ecc3d43ac313bf2ccc0a24.jpg) \nFigure 2.  Experimental characterization of methacrylate SMP networks. Highly tailorable glass transition temperature (a), rubbery modulus ${\\bf(b)}$ , and failure strain (c) are controlled by either changing the mixing LCB/ crosslinker ratio or using different crosslinkers. (d) The temperature effect on the failure strain of the SMP consisting of $90\\%$ BMA and $10\\%$ BPA. (e) The normalized exposure energy to cure a thin layer varies with the crosslinker concentration as well as the molecular weight of crosslinker. (f) The investigation on the interface bonding of a printed composite with two components arranged in series (inset). \n\nFigure 2b shows that the rubbery modulus $E_{r}$ of the copolymer networks increases with increase in crosslinker concentration (see Supplementary Materials S1.2, Fig. S2 and Table S1), as expected from entropic elasticity54, $E_{r}=(3\\rho R T)/M_{c};$ here, $R$ is the gas constant, $T$ is absolute temperature, $\\rho$ is polymer density, and $M_{c}$ is average molecular weight between crosslinks. The ratio $\\rho/M_{c}$ is the crosslinking density of the polymer network which is affected by crosslinker concentration as well as the molecular weight of the crosslinker. Comparing the four network systems, the $\\mathtt{B}+\\mathtt{D E G}$ network has the highest rubbery modulus at the same mass fraction of crosslinker, as the highest molar weight of DEGDMA leads to the highest crosslinking density (See Supplementary Materials S1.3 and Table S2) and the highest $E_{r}.$ \n\nThe effect of crosslinker on failure strain $\\varepsilon_{f}$ is shown in Fig. 2c; these results were obtained from uniaxial tensile tests at temperatures $30^{\\circ}\\mathrm{C}$ above each sample’s $T_{g}$ where sample stays the rubbery state to eliminate the effect of viscoelasticity (see Supplementary Materials S1.2, Fig. S2 and Table S1). The results shown in Fig. 2c suggest that in the SMP system consisting of the same LCB and crosslinker, the lower crosslinker concentration gives higher stretchability. Figure 2c also shows that the copolymer network system formed with a higher molecular weight crosslinker has higher stretchability. For example, for the copolymer systems consisting of $10\\%$ crosslinkers, the stretchability can be increased from ${\\sim}45\\%$ to ${\\sim}100\\%$ at $30^{\\circ}\\mathrm{C}$ above sample’s $T_{g}$ by increase the molecular weight from $242.3\\mathrm{g}/\\mathrm{mol}$ (DEGDMA) to $1700\\mathrm{g/mol}$ (BPA) (See Supplementary Materials S1.2, Fig. S2 and Table S1). Figure 2d shows the temperature effect on the failure strain of an SMP sample consisting of $90\\%$ BMP and $10\\%$ BPA (See Supplementary Materials S1.4 and Fig. S3). The stretchability of this copolymer network is increased by decreasing the stretching temperatures, and finally reaches the maximum of ${\\sim}330\\%$ at $40^{\\circ}\\mathrm{C}$ where the temperature is close to the peak of the loss modulus indicating the highest energy dissipation. A more stretchable network can be achieved by further reducing the crosslinker concentration of BPA or replacing BPA with a crosslinker having higher molecular weight. \n\nNot only does the chemical composition affect the thermomechanical properties of the printed SMP systems, it also affects the photo-polymerization kinetics that determines the build rate during manufacturing. As shown in Fig. 2e, at a given UV light intensity, less exposure energy (time) is required to cure a layer of the same thickness when the crosslinker concentration increases (See Supplementary Materials S1.5 and Fig. S4a). This is mainly attributed to the reaction diffusion-controlled termination during the polymerization of the methacrylate based copolymer system55–57. With more crosslinker, the crosslinking density of the polymer increases, which limits the propagation of free radicals that would otherwise reach each other to terminate the polymerization57. Figure 2e also shows that the copolymer network consisting of a lower molecular weight crosslinker (P550) requires less exposure energy (time) to polymerize a same thickness layer. This is primarily because the low molecular weight crosslinker (P550) contains more unreacted double bonds per unit mass than the high molecular weight crosslinker (P750) does. In addition, the increase of photo initiator reduces the exposure energy (time) to cure a same thickness layer (See Supplementary Materials S1.5 and Fig. S4b). Moreover, it is necessary to note that under the same condition methacrylate based SMP has comparatively lower reactivity57 than those acrylate based materials such as poly(ethylene glycol) diacrylate (PEGDA) and hexanediol diacrylate which have been frequently used to print 3D structure $\\yen123,44,58,59$ . This comparatively slow but conversion-dependent57 photo-polymerization kinetics makes the methacrylate based SMPs require higher (longer) exposure energy (time) to cure a layer of the same thickness than the acrylate based materials (See Supplementary Materials S1.5 and Fig. S4c). Therefore, a high contrast digital micro display with moderate intensity of UV light is needed to avoid any unwanted curing on the unintended parts (Details about the digital micro display are described in Materials). \n\nIn a printed component that consists of more than one material, the interface bonding between them significantly impacts the mechanical performance of the composite. In Fig. 2f, we investigated the interfacial bonding by uniaxially stretching a composite with two components arranged in series (Component A: $50\\%$ $\\mathrm{B}+50\\%$ P550 with $T_{g}=31^{\\circ}\\mathrm{C}$ and Component B: $90\\%$ $\\mathrm{B}+10\\%$ BPA $T_{g}=56^{\\circ}\\mathrm{C})$ at a temperature $30^{\\circ}\\mathrm{C}$ higher than $T_{g}$ of Component B, where the both components are in their rubbery state (See Supplementary Materials S1.6 and Fig. S5). The fact that the composite breaks at Component A which has a lower failure strain rather than at the interface indicates a strong interface bonding. The comparison of uniaxial tensile tests between the composite and the two components in Fig. 2e reveals that Components A and B form a strong covalently boned interface through which the composite transfers stress completely between the two components. Generally speaking, this strong interface bonding forms between the methacrylate based SMPs made of different compositions and constitutes. \n\nShape Memory Behavior.  Two key attributes of SMPs are their ability to fix a temporary programmed shape (fixity) and to subsequently recover the original shape upon activation by a stimulus (recovery). Figure 3a shows a typical temperature-strain-time shape memory (SM) cycle that we used to investigate the fixity and recovery of SMP samples synthesized from different LCBs and crosslinkers that result in different $T_{g}$ s. Figure 3b presents representative strain-time curves of a SMP strip sample made of $80\\%$ $\\mathrm{BMA}+20\\%$ P750. The SMP was first stretched to a target strain $e_{\\mathrm{max}}(20\\%)$ with a constant loading rate $e\\left(0.001{\\bf s}^{-1}\\right)$ at a programming temperature $T_{D}\\left(63^{\\circ}\\mathrm{C}\\right)$ , and then the temperature was decreased to a $T_{L}$ $_L^{\\prime}\\left(T_{L}=25^{\\circ}\\mathrm{C}\\right)$ with a cooling rate $2.5^{\\circ}\\mathrm{C}/\\mathrm{min}$ . Once $T_{L}$ was reached, the specimen was held for 2 minutes, and then the tensile force was removed. In the free recovery step, the temperature was increased to a recovery temperature $T_{R}$ (in Fig. 3b, $T_{R}=35^{\\circ}\\mathrm{C},$ , $40^{\\circ}\\mathrm{C}$ $50^{\\circ}\\mathrm{C}$ and $60^{\\circ}\\mathrm{C},$ respectively) at the same rate of cooling and subsequently stabilized for another $20\\mathrm{min}$ . (Details about the SM behavior testing are presented in Supplementary Material in S2.1 and Fig. S6). \n\n![](images/2f2885e905428b7f03c6421d31be2aca3b7f7e6e1bc65ef6c239ec9be4faf826.jpg) \nFigure 3.  SM behavior of the (meth)acrylate based copolymer SMP network. (a) The SM behavior has been investigated by following a typical SM cycle: at Step I, a sample is deformed by $e_{\\mathrm{max}}$ at a programming temperature $T_{D};$ at Step II, the temperature is decreased from $T_{D}$ to $T_{L}$ while keeping the sample deformed by $e_{\\mathrm{max}}\\mathrm{:}$ at Step III, after unloading, there is a deformation bounce back $\\Delta e_{\\mathrm{i}}$ ; at Step IV, the free recovery is performed by heating the sample to a recovery temperature $T_{R}$ . (b) The representative SMP strain-time curves achieved by stretching a SMP sample ( $80\\%$ BMA and $20\\%$ P750) at $63^{\\circ}\\mathrm{C},$ unloading at $25^{\\circ}\\mathrm{C}$ , and heating to $63^{\\circ}\\mathrm{C}$ , $50^{\\circ}\\mathrm{C},$ , $40^{\\circ}\\mathrm{C}$ and $35^{\\circ}\\mathrm{C},$ respectively. (c) Shape fixity as a function of programming temperature. (d) Shape recovery time $(t_{0.95})$ as a function of recovery temperature. \n\nAs shown in Fig. 3a,b, we use the small strain bounce back, $\\Delta e$ , of the SMP after unloading to define the shape fixity, i.e., $R_{f}=(e_{\\operatorname*{max}}-\\Delta e)/e_{\\operatorname*{max}}.$ Figure 3c shows that the shape fixity is a function of the programming temperature $T_{D}$ (Details about $T_{D}$ are listed in Supplementary Material Table S4): the SMP keeps a high shape fixity $(>90\\%)$ when $T_{D}$ is above or near the SMP’s $T_{g},$ and the shape fixity starts to drop dramatically when $T_{D}$ is $20^{\\circ}\\mathrm{C}$ lower than the SMP’s $T_{\\mathrm{g}}.$ The phenomenon that the shape fixity is a function of $T_{D}$ agrees the previous study24, and can be simulated by the recently developed multi-branch model which consists of an equilibrium branch corresponding to entropic elasticity and several thermoviscoelastic nonequilibrium branches to represent the multiple relaxation processes of the polymer24,60 (Details about the multi-branch model are presented in Supplementary Material S2.2–2.3). The model predictions agree with the experiments well and provide underlying understanding of the effect of the programming temperature $T_{D}$ on the shape fixity $R_{f}$ (Details about model predictions are presented in Supplementary Material S2.4 and Figure S9). When $T_{D}$ is higher or near the $T_{g},$ an SMP has a high shape fixity $R_{f}$ as the time requires to relax all the nonequilibrium stresses is shorter than the time used for loading at $T_{D}$ and cooling to $T_{L}$ . When $T_{D}$ is decreased to a lower temperature the shape fixity $R_{f}$ decreases as the nonequilibrium stresses do not have sufficient time to relax. For example, in Fig. 3c, the simulation indicates that for the SMP of $90\\%$ $\\mathrm{BMA}+10\\%$ BPA with $T_{g}=56^{\\circ}\\mathrm{C}$ , $R_{f}$ is decreased to nearly zero when $T_{D}$ is $25^{\\circ}\\mathrm{C}$ where the polymer chain mobility is significantly reduced and the unrelaxed nonequilibrium stresses are stored as elastic energy. \n\nFigure 3d indicates that the free shape recovery is a function of recovery temperature (Details about how to achieve the free recovery curve are presented in S2.1). We define the shape recovery ratio as $R_{r}{=}1{-}e(t)/(e_{\\operatorname*{max}}{-}\\Delta e)$ . We use the recovery time $t_{0.95}$ that corresponds to a $95\\%$ shape recovery ratio to measure the shape recovery rate at different recovery temperatures $T_{R}{}^{24}$ . Within the lab scale experiment time (an hour), the SMP samples were able to realize the $95\\%$ shape recovery only at the recovery temperature $T_{R}$ more than $10^{\\circ}\\mathrm{C}$ higher than the SMP’s $T_{g}$ (the measured $t_{0.95}$ are listed in Table S5). The multi-branch model is also used to simulate the free recovery at different recovery temperatures $T_{R}$ and predict the recovery time $t_{0.95}$ at different $T_{R}$ s (See Supplementary Material S2.4). \n\n![](images/c74e5797cbcbaf601ffde42aef64bbc87514a61b9b73022fc26abb650157424c.jpg) \nFigure 4.  3D printed shape memory structures with single material. (a) A 3D printed shape memory spring (I) was programmed to a straight strand temporary configuration (II), and then recovered to its original shape upon heating (III–V). (b) Experimental characterization and FE simulation were performed to investigate the nonlinear deformation. (c) Experiments and simulations of the free recovery at different temperatures. (d) 3D printed SM Eiffel tower. (e) 3D printed SM stents. \n\nOverall, $t_{0.95}$ increases exponentially with a decreasing $T_{R},$ and for different SMPs, at the same $T_{R}$ , the one with a higher $T_{g}$ requires a longer recovery time. \n\nThree dimensional printed structures with a single SMP.  Figure 4 shows the ability of our additive manufacturing system to create complex 3D structures that exhibit nonlinear large deformation SM behavior. As shown in Fig. 4aI, a spring was fabricated using a SMP with $T_{g}=43^{\\circ}\\mathrm{C}$ ( $0\\%\\mathrm{~B+20\\%~}$ P750). We demonstrated the SM effect of the spring by stretching it to a straight strand at $60^{\\circ}\\mathrm{C}$ The straight strand configuration was fixed (Fig. 4aII) after removing the external load at $20^{\\circ}\\mathrm{C}$ . It recovered the original spring shape (Fig. 4aII–V) after heating back to $60^{\\circ}\\mathrm{C}$ . The complicated nonlinear large deformation SM behavior of the spring was investigated by following the typical SM cycle for a spring with a representative segment (See Supplementary Material S3.3). Figure 4b shows the force-displacement relation when the spring was stretched at $60^{\\circ}\\mathrm{C}$ . The spring becomes extremely stiff as it approaches to its fully unfolded state. The finite element (FE) simulations present the deformation contours in the progress of stretching the spring. Regardless of the maximum deformation on the two ends, the highest principle engineering strain on the main body of the spring was in the range from $70\\mathrm{-}100\\%$ which is about two to three times higher than the failure strain of previously reported SMPs used for 4D printing2, indicating the enhanced mechanical performance which is a necessity for active structures. In $\\ensuremath{{}^{\\infty}}4\\ensuremath{\\mathrm{D}}$ printing” \n\n![](images/001f38db3f2aee7b47878f955a064f30dfc6ecdc47e7afc5d9b4b02b550bc50f.jpg) \nFigure 5.  3D printed multimaterial grippers. (a) Multimaterial grippers were fabricated with different designs. (b) The demonstration of the transition between as printed shape and temporary shape of multimaterial grippers. (c) The snapshots of the process of grabbing an object. \n\nwhere the fourth dimension is “time”, a key desire is to control of the actuation rate. For the printed shape memory structures, the actuation rate can be controlled by the recovery temperature24,49. Figure 4c shows the recovery ratio of the stretched spring at different recovery temperatures. Here, the recovery ratio of the SM spring is defined as $R_{r}^{s}=1-d(t)/(d_{\\operatorname*{max}}-\\Delta d).$ , where $\\mathbf{}d(t)$ is the end-to-end displacement during heating, $d_{\\mathrm{max}}$ is the maximum displacement before unloading at $20^{\\circ}\\mathrm{C},$ , and $\\Delta d$ is the bounce back displacement after unloading. As seen in Fig. 4c, $\\boldsymbol{R}_{r}^{s}$ is highly dependent on the recovery temperature. At $60^{\\circ}\\mathrm{C},$ , the spring was fully recovered into the initial shape within 3 mins. The recovery rate was significantly slower at $35^{\\circ}\\mathrm{C}$ where only about $10\\%$ recovery took place after 20 mins holding. The SM behavior including the free recovery at different temperatures of the 3D printed spring can be simulated by implementing the multi-branch model into FE software ABAQUS (Simulia, Providence, RI, USA). In Fig. 4c, the FE simulation reproduced the free recovery behavior at different recovery temperatures, indicating that the multi-branch model can be used to design complex 4D printed structures that are made of SMPs and exhibit complex nonlinear large deformation thermomechanical behaviors. Details about FE simulation of SM behavior of this printed spring are described in Supplementary Material S3.3 and Supplementary Movies 1a–d. \n\nFigure 4d shows a more refined and complex 3D printed structure Eiffel Tower standing on a Singapore dollar. It was printed with the SMP made of $80\\%$ $\\mathrm{B}+20\\%$ P750 too. Following the SM cycle, a temporary bent shape (Fig. 4dI) was achieved by bending the Eiffel tower at $60^{\\circ}\\mathrm{C}$ and removing the external load after cooling to $25^{\\circ}\\mathrm{C}$ . After heating back to $60^{\\circ}\\mathrm{C},$ the bent Eiffel tower gradually recovered its original straight shape (Fig. 4d, Supplementary Movie 2). Figure 4e demonstrates one of the most notable applications of SMPs — cardiovascular stent. Although there have been various efforts directed at fabrication12,32, material and structural characterization12,61,62 and simulations $^{32,63-65}$ , the design of the stents has been limited primarily by fabrication methods because traditional manufacturing approaches are usually complex, consisting of multiple time-consuming steps, to achieve the geometric complexity and resolution necessary for stents12,32. Our additive manufacturing system offers the ability to fabricate high resolution 3D shape memory structures with hardly any restriction of geometric complexity. Figure 4eI shows an array of stents printed in one batch with different geometric parameters including the height and the diameter of a stent, the number of joints, the diameter of ligaments and the angle between ligaments. In Fig. 4eII, a 3D printed stent was programmed into the temporary shape with a smaller diameter for minimally invasive surgery. After heating, the stent was recovered into the original shape with a larger diameter used to expand a narrowed artery. The finite element (FE) simulation shown in Fig. 4eII gives an insight into the local large deformation that occurs in the temporary shape, and renders existing additive manufacturing systems and materials infeasible. The simulations provide a guide for the material selection based on the understanding of the thermomechanical properties from Fig. 2. \n\n![](images/1524edaa735653a603a2e8e0512c0ca49b581d1029857d0064794ceae627a756.jpg) \nFigure 6.  The sequential recovery of a multimaterial flower. The multimaterial flower in the original shape (c) was first programmed into the temporary bud state at $20^{\\circ}\\mathrm{C}$ (a). The outer petals opened first after heating to $50^{\\circ}\\mathrm{C}$ (b) and then, the flower fully bloomed at $70^{\\circ}\\mathrm{C}$ (c). (d)–(f) represent the FE simulations of the corresponding flower blooming process. \n\nThree dimensional printed structures with multiple SMPs.  Figure 5 demonstrates the printing of a 3D printed structure with multiple SMPs - multimaterial grippers that have the potential to function as microgrippers13 that can grab objects, or drug delivery devices33,66 that can release objects. Figure 5aI shows a number of multimaterial grippers with different designs including different sizes and numbers of digits (comparing Fig. 5aII and III), multiple materials placing at different positions (Fig. 5aIII and IV), and different mechanisms of the grippers to enable different functionalities (the closed grippers in Fig. 5aIII for grabbing objects and the open gripper in Fig. 5bV for releasing objects). In Fig. 5b, an as-printed closed (open) gripper was opened (closed) after programming and the functionality of grabbing (releasing) objects was triggered upon heating. Figure 5c shows time-lapsed images of a gripper grabbing an object (Supplementary Movies 3). \n\nCompared to contemporary manufacturing approaches13,33,66 that essentially realized the gripper deformation of folding or unfolding by creating strain mismatches between layers of a thin multilayer hinge with thickness from a few microns to a few hundred nanometers which is about 1000 times smaller than the size of the entire structure13,33,66, our approach is simple and straightforward enabling stiffer grippers with thick joints made of SMPs. Additionally, the capability of multimaterial fabrication enables us to print the tips of the grippers with the materials different from the SMPs constructing the joints, and to design the stiffness of the tips based on that of the object to realize a safe contact. Details about material selections of the 3D printed grippers are described in Supplementary Material S4.1. \n\nFinally, by controlling the dynamic properties of the different SMPs as investigated in Fig. 3d, we are able to design the time dependent sequential shape recovery4,67 of a structure fabricated with multiple SMPs. In Fig. 6, we demonstrate sequential shape recovery by printing a multimaterial flower whose inner and outer petals have different $T_{g}\\mathbf{s}$ (inners petal made of $90\\%\\mathrm{B}+10\\%$ BPA with $T_{g}=56^{\\circ}\\mathrm{C}$ and outer petals made of $80\\%$ $\\%\\mathrm{B}+20\\%$ P750 with $T_{g}=43^{\\circ}\\mathrm{C})$ . We first closed all the petals at $70^{\\circ}\\mathrm{C}.$ and then decreased the temperature to $20^{\\circ}\\mathrm{C}$ After removal of the external constraint, the flower was fixed at the temporary bud state (Fig. 6a) where both the inner and outer petals stayed closed. The sequential recovery was triggered by raising the temperature first to $50^{\\circ}\\mathrm{C}$ at which only the outer petals opened. The inner petals with $T_{g}$ of $56^{\\circ}\\mathrm{C}$ opened later after temperature was raised to $70^{\\circ}\\mathrm{C},$ , completing the full shape recovery of the flower to its original blooming state (Fig. 6c). In Fig. 6d–f, a FE simulation (details can be founded in Supplementary Material S4.2) predicts this flower blooming process indicating that the multi-branch model can be used to design complex 4D printed structures that are made of multiple SMPs and exhibit sequential shape. \n\n# Methods \n\nDevelopment of multimaterial fabrication system.  To develop a high resolution multimaterial system based on $\\mathrm{P}\\mu\\mathrm{SL},$ a CEL5500 LED light engine purchased from Digital Light Innovation (Austin, Taxes, USA) was used to work as the digital micro-display, a translation stage (LTS300) with $0.1\\mu\\mathrm{m}$ minimum achievable incremental movement and $2\\mu\\mathrm m$ backlash purchased from Thorlabs (Newton, New Jersey, USA) was used to work as the elevator, a stepper motor purchased from SparkFun Electornics (Niwot, Colorado, USA) controlled by Arduino UNO board works as a shaft to build the automated material exchange system. A custom LabView code was developed to control all the electronic components and automate the printing process. \n\nMaterial synthesis.  All the chemicals including the methacrylate based monomers and crosslinkers, photo initiator, and photo absorbers were purchased from Sigma Aldrich (St. Louis, MO, USA) and used as received. Phenylbis (2, 4, 6-trimethylbenzoyl) phosphine oxide works as photo initiator mixed into the methacrylate based polymer resolution at the concentration of $5\\%$ by weight. Sudan I and Rhodamine B works as photo absorber fixed at concentration of $0.05\\%$ and $1\\%$ by weight, respectively. \n\nPrinting and post-processing.  The designed 3D structures were first sliced into layers with a prescribed layer thickness (most structures here were sliced with $50\\mu\\mathrm{m}$ per layer). The custom LabVIEW with printing parameters which specify layer thickness, light intensity, exposure time, sends the sliced 2D images in order to digital micro display and controls the light irradiation of the digital micro displace, and translational stage motion. Once the 3D structures were printed, they were rinsed by the ethanol solution to remove the extra unreacted polymer solution. After that, the 3D structures were placed into a UV oven (UVP, Ultraviolet Crosslinkers, Upland, CA, USA) for $10\\mathrm{min}$ post-curing. \n\n# References \n\n1.\t Bartlett, N. W. et al. A 3D-printed, functionally graded soft robot powered by combustion. Science 349, 161–165, 10.1126/science. aab0129 (2015). \n2.\t Ge, Q., Dunn, C. K., Qi, H. J. & Dunn, M. L. Active origami by 4D printing. Smart Materials and Structures 23, doi: 10.1088/0964- 1726/23/9/094007 (2014). \n3.\t Ge, Q., Qi, H. J. & Dunn, M. L. Active materials by four-dimension printing. Applied Physics Letters 103, doi: dx.doi. org/10.1063/1.4819837 (2013). \n4.\t Mao, Y. et al. Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers. Scientific Reports 5, 13616, doi: 10.1038/srep13616 (2015). \n5.\t Raviv, D. et al. Active printed materials for complex self-evolving deformations. Scientific Reports 4, 7422, doi: 10.1038/srep07422 (2014). \n6.\t Lendlein, A. & Kelch, S. Shape-memory polymers. Angewandte Chemie International Edition in English 41, 2035–2057 (2002). \n7.\t Lendlein, A. & Kelch, S. Shape-memory polymers as stimuli-sensitive implant materials. Clinical Hemorheology and Microcirculation 32, 105–116 (2005). \n8.\t Long, K. N., Scott, T. F., Qi, H. J., Bowman, C. N. & Dunn, M. L. Photomechanics of light-activated polymers. Journal of the Mechanics and Physics of Solids 57, 1103–1121, doi: 10.1016/j.jmps.2009.03.003 (2009). \n9.\t Ryu, J. et al. Photo-origami-Bending and folding polymers with light. Applied Physics Letters 100, 161908, doi: 10.1063/1.3700719 (2012). \n10.\t Keplinger, C. et al. Stretchable, Transparent, Ionic Conductors. Science 341, 984–987, doi: 10.1126/science.1240228 (2013). \n11.\t Wang, Q. M., Gossweiler, G. R., Craig, S. L. & Zhao, X. H. Cephalopod-inspired design of electro-mechano-chemically responsive elastomers for on-demand fluorescent patterning. Nature Communications 5, doi: 10.1038/Ncomms5899 (2014). \n12.\t Yakacki, C. M. et al. Unconstrained recovery characterization of shape-memory polymer networks for cardiovascular applications. Biomaterials 28, 2255–2263, doi: 10.1016/j.biomaterials.2007.01.030 (2007). \n13.\t Leong, T. G. et al. Tetherless thermobiochemically actuated microgrippers. Proc Natl Acad Sci USA 106, 703–708, doi: 10.1073/ pnas.0807698106 (2009). \n14.\t Mosadegh, B. et al. Pneumatic Networks for Soft Robotics that Actuate Rapidly. Advanced Functional Materials 24, 2163–2170, doi: 10.1002/adfm.201303288 (2014). \n15.\t Kramer, R. K., Majidi, C. & Wood, R. J. In Robotics and Automation (ICRA), 2011 IEEE International Conference on. 1103–1107. \n16.\t Song, Y. M. et al. Digital cameras with designs inspired by the arthropod eye. Nature 497, 95–99, doi: 10.1038/Nature12083 (2013). \n17.\t Westbrook, K. K. et al. Two-way reversible shape memory effects in a free-standing polymer composite. Smart Materials & Structures 20, doi: 10.1088/0964-1726/20/6/065010 (2011). \n18.\t Yamano, I. & Maeno, T. Five-fingered robot hand using ultrasonic motors and elastic elements. 2005 IEEE International Conference on Robotics and Automation (ICRA), Vols 1–4, 2673–26782005). \n19.\t Bakarich, S. E., Gorkin, R., Panhuis, M. i. h. & Spinks, G. M. 4D Printing with Mechanically Robust, Thermally Actuating Hydrogels. Macromolecular Rapid Communications 36, 1211–1217, doi: 10.1002/marc.201500079 (2015). \n20.\t Zhang, Q., Yan, D., Zhang, K. & Hu, G. Pattern Transformation of Heat-Shrinkable Polymer by Three-Dimensional (3D) Printing Technique. Scientific Reports 5, 8936, doi: 10.1038/srep08936 (2015). \n21.\t Sydney Gladman, A., Matsumoto, E. A., Nuzzo, R. G., Mahadevan, L. & Lewis, J. A. Biomimetic 4D printing. Nature Materials. 15, 413–418, doi: 10.1038/nmat4544 (2016). \n22.\t Mao, Y. et al. 3D Printed Reversible Shape Changing Components with Stimuli Responsive Materials. Scientific Reports 6, 24761, doi: 10.1038/srep24761 (2016). \n23.\t Lendlein, A. & Kelch, S. Shape-memory polymers. Angew Chem Int Ed Engl 41, 2035–2057 (2002). \n24.\t Yu, K., Ge, Q. & Qi, H. J. Reduced Time as a Unified Parameter Determining Fixity and Free Recovery of Shape Memory Polymers. Nature Communication 5, 3066 (2014). \n25.\t Castro, F., Westbrook, K. K., Long, K. N., Shandas, R. & Qi, H. J. Effects of thermal rates on the thermomechanical behaviors of amorphous shape memory polymers. Mechanics of Time-Dependent Materials 14, 219–241, doi: 10.1007/s11043-010-9109-6 (2010). \n26.\t Wu, J. et al. Multi-shape active composites by 3D printing of digital shape memory polymers. Scientific Reports 6, 24224, doi: 10.1038/srep24224 (2016). \n27.\t Stratasys. Digital Materials Data Sheet http://usglobalimages.stratasys.com/Main/Files/Material_Spec_Sheets/MSS_PJ_ DigitalMaterialsDataSheet.pdf (2015), Date of access: 5/6/2016. \n28.\t Stratasys. Specifications of Stratasys J750, the ultimate full-color, multi-material 3D printer, http://www.stratasys.com/3d-printers/ production-series/stratasys-j750 (2016), Date of access: 5/6/2016. 29.\t Sun, C., N., Wu, D. M. & Zhang, sors and Actuators a-Physical 121, 113–120, doi: 10.1016/j.sna.2004.12.011 (2005). \n30.\t Zheng, X. et al. Design and optimization of a light-emitting diode projection micro-stereolithography three-dimensional manufacturing system. Review of Scientific Instruments 83, 125001, doi: dx.doi.org/10.1063/1.4769050 (2012). \n31.\t Zheng, X. Y. et al. Ultralight, Ultrastiff Mechanical Metamaterials. Science 344, 1373–1377, doi: 10.1126/science.1252291 (2014). \n32.\t Srivastava, V., Chester, S. A. & Anand, L. Thermally actuated shape-memory polymers: Experiments, theory, and numerical simulations. Journal of the Mechanics and Physics of Solids 58, 1100–1124, doi: 10.1016/j.jmps.2010.04.004 (2010). \n33.\t Yoon, C. et al. Functional stimuli responsive hydrogel devices by self-folding. Smart Materials and Structures 23, doi: 10.1088/0964- 1726/23/9/094008 (2014). \n34.\t Gall, K., Mikulas, M., Munshi, N. A., Beavers, F. & Tupper, M. Carbon Fiber Reinforced Shape Memory Polymer Composites. Journal of Intelligent Material Systems and Structures 11, 877–886, 10.1106/ejgr-ewnm-6clx-3x2m (2000). \n35.\t Xin, L. et al. Fiber reinforced shape-memory polymer composite and its application in a deployable hinge. Smart Materials and Structures 18, 024002 (2009). \n36.\t Merali, Z. Profile: Zhong You - ‘Origami Engineer’ Flexes to Create Stronger, More Agile Materials. Science 332, 1376–1377 (2011). \n37.\t Wu, W. N. & You, Z. A solution for folding rigid tall shopping bags. P Roy Soc a-Math Phy 467, 2561–2574, doi: 10.1098/ rspa.2011.0120 (2011). \n38.\t Guo, X. Y. et al. Two- and three-dimensional folding of thin film single-crystalline silicon for photovoltaic power applications. P Natl Acad Sci USA 106, 20149–20154, doi: 10.1073/pnas.0907390106 (2009). \n39.\t Myers, B., Bernardi, M. & Grossman, J. C. Three-dimensional photovoltaics. Applied Physics Letters 96, 071902, doi: dx.doi. org/10.1063/1.3308490 (2010). \n40.\t Chan, V. et al. Multi-material bio-fabrication of hydrogel cantilevers and actuators with stereolithography. Lab on a Chip 12, 88–98, doi: 10.1039/c1lc20688e (2012). \n41.\t Choi, J.-W., Kim, H.-C. & Wicker, R. Multi-material stereolithography. Journal of Materials Processing Technology 211, 318–328, doi: dx.doi.org/10.1016/j.jmatprotec.2010.10.003 (2011). \n42.\t Wicker, R. B. & MacDonald, E. W. Multi-material, multi-technology stereolithography. Virtual and Physical Prototyping 7, 181–194, doi: 10.1080/17452759.2012.721119 (2012). \n43.\t Zhou, C., Chen, Y., Yang, Z. G. & Khoshnevis, B. Digital material fabrication using mask-image-projection-based stereolithography. Rapid Prototyping Journal 19, 153–165, doi: 10.1108/13552541311312148 (2013). \n44.\t Tumbleston, J. R. et al. Continuous liquid interface production of 3D objects. Science 347, 1349–1352, doi: 10.1126/science.aaa2397 (2015) \n45.\t Anseth, K. S., Wang, C. M. & Bowman, C. N. Reaction behaviour and kinetic constants for photopolymerizations of multi(meth) acrylate monomers. Polymer 35, 3243–3250, doi: dx.doi.org/10.1016/0032-3861(94)90129-5 (1994). \n46.\t Bowman, C. N., Carver, A. L., Kennett, S. N., Williams, M. M. & Peppas, N. A. Polymers for information storage systems III. Crosslinked structure of polydimethacrylates. Polymer 31, 135–139, doi: dx.doi.org/10.1016/0032-3861(90)90364-5 (1990). \n47.\t Kannurpatti, A. R. & Bowman, C. N. Structural evolution of dimethacrylate networks studied by dielectric spectroscopy. Macromolecules 31, 3311–3316, doi: 10.1021/Ma970721r (1998). \n48.\t Safranski, D. L. & Gall, K. Effect of chemical structure and crosslinking density on the thermo-mechanical properties and toughness of (meth)acrylate shape memory polymer networks. Polymer 49, 4446–4455, doi: dx.doi.org/10.1016/j.polymer.2008.07.060 (2008). \n49.\t Ge, Q., Yu, K., Ding, Y. F. & Qi, H. J. Prediction of temperature-dependent free recovery behaviors of amorphous shape memory polymers. Soft Matter 8, 11098–11105, doi: 10.1039/C2sm26249e (2012). \n50.\t Nguyen, T. D., Qi, H. J., Castro, F. & Long, K. N. A thermoviscoelastic model for amorphous shape memory polymers: Incorporating structural and stress relaxation. Journal of the Mechanics and Physics of Solids 56, 2792–2814, doi: 10.1016/j.jmps.2008.04.007 (2008). \n51.\t Qi, H. J., Nguyen, T. D., Castro, F., Yakacki, C. M. & Shandas, R. Finite deformation thermo-mechanical behavior of thermally induced shape memory polymers. Journal of the Mechanics and Physics of Solids 56, 1730–1751, doi: 10.1016/j.jmps.2007.12.002 (2008). \n52.\t Couchman, P. R. Compositional Variation of Glass-Transition Temperatures. 2. Application of the Thermodynamic Theory to Compatible Polymer Blends. Macromolecules 11, 1156–1161, doi: 10.1021/ma60066a018 (1978). \n53.\t Voit, W. et al. High-Strain Shape-Memory Polymers. Advanced Functional Materials 20, 162–171, 10.1002/adfm.200901409 (2010). \n54.\t Treloar, L. R. G. The physics of rubber elasticity. 2d edn, (Clarendon Press, 1958). \n55.\t Anseth, K. S., Decker, C. & Bowman, C. N. Real-Time Infrared Characterization of Reaction Diffusion during Multifunctional Monomer Polymerizations. Macromolecules 28, 4040–4043, doi: 10.1021/ma00115a045 (1995). \n56.\t Lovell, L. G., Stansbury, J. W., Syrpes, D. C. & Bowman, C. N. Effects of Composition and Reactivity on the Reaction Kinetics of Dimethacrylate/Dimethacrylate Copolymerizations. Macromolecules 32, 3913–3921, doi: 10.1021/ma990258d (1999). \n57.\t Young, J. S. & Bowman, C. N. Effect of Polymerization Temperature and Cross-Linker Concentration on Reaction Diffusion Controlled Termination. Macromolecules 32, 6073–6081, doi: 10.1021/ma9902955 (1999). \n58.\t Lee, H., Xia, C. & Fang, N. X. First jump of microgel; actuation speed enhancement by elastic instability. Soft Matter 6, 4342–4345, doi: 10.1039/c0sm00092b (2010). \n59.\t Lee, H., Zhang, J., Jiang, H. & Fang, N. X. Prescribed Pattern Transformation in Swelling Gel Tubes by Elastic Instability. Physical Review Letters 108, 214304 (2012). \n60.\t Westbrook, K. K., Kao, P. H., Castro, F., Ding, Y. F. & Qi, H. J. A 3D finite deformation constitutive model for amorphous shape memory polymers: A multi-branch modeling approach for nonequilibrium relaxation processes. Mechanics of Materials 43, 853–869, doi: 10.1016/j.mechmat.2011.09.004 (2011). \n61.\t Yakacki, C. M. et al. Strong, tailored, biocompatible shape-memory polymer networks. Advanced Functional Materials 18, 2428–2435, doi: 10.1002/adfm.200701049 (2008). \n62.\t Gall, K. et al. Thermomechanics of the shape memory effect in polymers for biomedical applications. Journal of Biomedical Materials Research Part A 73A, 339–348, doi: 10.1002/jbm.a.30296 (2005). \n63.\t Ames, N. M., Srivastava, V., Chester, S. A. & Arland, L. A thermo-mechanically coupled theory for large deformations of amorphous polymers. Part II: Applications. International Journal of Plasticity 25, 1495–1539, doi: 10.1016/j.ijplas.2008.11.005 (2009). \n64.\t Anand, L., Ames, N. M., Srivastava, V. & Chester, S. A. A thermo-mechanically coupled theory for large deformations of amorphous polymers. Part I: Formulation. International Journal of Plasticity 25, 1474–1494, doi: 10.1016/j.ijplas.2008.11.004 (2009). \n65.\t Srivastava, V., Chester, S. A., Ames, N. M. & Anand, L. A thermo-mechanically-coupled large-deformation theory for amorphous polymers in a temperature range which spans their glass transition. International Journal of Plasticity 26, 1138–1182, doi: 10.1016/j. ijplas.2010.01.004 (2010). \n66.\t Malachowski, K. et al. Stimuli-Responsive Theragrippers for Chemomechanical Controlled Release. Angewandte ChemieInternational Edition 53, 8045–8049, doi: 10.1002/anie.201311047 (2014). \n67.\t Yu, K., Ritchie, A., Mao, Y., Dunn, M. L. & Qi, H. J. Controlled Sequential Shape Changing Components by 3D Printing of Shape Memory Polymer Multimaterials. Procedia IUTAM 12, 193–203, doi: dx.doi.org/10.1016/j.piutam.2014.12.021 (2015). \n\n# Acknowledgements \n\nQ.G., A.H.S. and M.L.D. gratefully acknowledge support from SUTD Digital Manufacturing and Design Centre (DManD), supported by the Singapore National Research Foundation. Q.G. and N.X.F. acknowledge the SUTDMIT joint postdoctoral programme. Q.G. acknowledges SUTD Start-up Research Grant, and LNM Open Fund supported by State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Science. \n\n# Author Contributions \n\nQ.G. developed the multimaterial 3D printing system, prepared photo-curable polymer resins, fabricated the multimaterial shape memory structures, conducted experiments, and prepared the manuscript. A.H.S. conducted FEA simulations. H.L. conducted the preliminary experiments, and contributed to the development of multimaterial 3D printing system and manuscript preparation. C.K.D. contributed to the development of multimaterial 3D printing system. N.X.F and M.L.D. contributed to the concept development and manuscript. All authors reviewed the manuscript. \n\n# Additional Information \n\nSupplementary information accompanies this paper at http://www.nature.com/srep \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nHow to cite this article: Ge, Q. et al. Multimaterial 4D Printing with Tailorable Shape Memory Polymers. Sci. \nRep. 6, 31110; doi: 10.1038/srep31110 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\circledcirc$ The Author(s) 2016 " + }, + { + "id": "10.1038_ncomms11981", + "DOI": "10.1038/ncomms11981", + "DOI Link": "http://dx.doi.org/10.1038/ncomms11981", + "Relative Dir Path": "mds/10.1038_ncomms11981", + "Article Title": "Nickel-vanadium monolayer double hydroxide for efficient electrochemical water oxidation", + "Authors": "Fan, K; Chen, H; Ji, YF; Huang, H; Claesson, PM; Daniel, Q; Philippe, B; Rensmo, H; Li, FS; Luo, Y; Sun, LC", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Highly active and low-cost electrocatalysts for water oxidation are required due to the demands on sustainable solar fuels; however, developing highly efficient catalysts to meet industrial requirements remains a challenge. Herein, we report a monolayer of nickel-vanadium-layered double hydroxide that shows a current density of 27 mA cm(-2) (57 mA cm(-2) after ohmic-drop correction) at an overpotential of 350 mV for water oxidation. Such performance is comparable to those of the best-performing nickel-iron-layered double hydroxides for water oxidation in alkaline media. Mechanistic studies indicate that the nickel-vanadium-layered double hydroxides can provide high intrinsic catalytic activity, mainly due to enhanced conductivity, facile electron transfer and abundant active sites. This work may expand the scope of cost-effective electrocatalysts for water splitting.", + "Times Cited, WoS Core": 900, + "Times Cited, All Databases": 925, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000378815100001", + "Markdown": "# Nickel–vanadium monolayer double hydroxide for efficient electrochemical water oxidation \n\nKe Fan1,2, Hong Chen1, Yongfei Ji3, Hui Huang4, Per Martin Claesson4, Quentin Daniel1, Bertrand Philippe5, Håkan Rensmo5, Fusheng Li1, Yi Luo3 & Licheng Sun1,6 \n\nHighly active and low-cost electrocatalysts for water oxidation are required due to the demands on sustainable solar fuels; however, developing highly efficient catalysts to meet industrial requirements remains a challenge. Herein, we report a monolayer of nickel–vanadium-layered double hydroxide that shows a current density of $27\\mathsf{m A c m}^{-2}$ $(57\\mathsf{m A}\\mathsf{c m}^{-2}$ after ohmic-drop correction) at an overpotential of $350\\mathsf{m V}$ for water oxidation. Such performance is comparable to those of the best-performing nickel–iron-layered double hydroxides for water oxidation in alkaline media. Mechanistic studies indicate that the nickel–vanadium-layered double hydroxides can provide high intrinsic catalytic activity, mainly due to enhanced conductivity, facile electron transfer and abundant active sites. This work may expand the scope of cost-effective electrocatalysts for water splitting. \n\nW ater splitting is considered one of the most promising strategies to produce chemical fuels such as hydrogen. The half reaction of the water splitting process, water oxidation, remains the bottleneck of the whole process at present. Therefore, developing highly efficient water oxidation catalysts is crucial. Some precious metal-based electrocatalysts, such as $\\mathrm{IrO}_{2}$ and ${\\mathrm{RuO}}_{2}$ , have shown excellent performance for water oxidation; however, they suffer from high-cost and relative scarcity of precious metals, which limits their applications. Although some first-row transition metal oxides (for example, $\\mathrm{NiO_{x}},$ $\\mathrm{NiFeO_{x},}$ $\\mathrm{CoO_{x}}$ and $\\mathrm{{MnO}_{\\mathrm{{x}}}},$ ) had been developed as low-cost electrocatalysts for water oxidation, most of them still cannot compete with $\\mathrm{IrO}_{2}$ and $\\mathrm{RuO}_{2}{}^{1,2}$ . Recently, the earth-abundant Ni–Fe double-layered hydroxide (NiFe-LDH) catalysts have attracted attention3–7. From being first reported as an advanced electrocatalyst coupled with carbon nanotubes for water oxidation8, it is nowadays known as one of the most active catalysts with a low overpotential and high electrolysis current. Since, then tremendous efforts have been devoted to further improve the activity of NiFe-LDH, such as exfoliation9 and hybridization6,8,10,11, to the extent that LDH catalysts can now outperform $\\mathrm{IrO}_{2}$ in alkaline media6,8,9; however, the aforementioned methods are still too complicated for large-scale applications. \n\nIt is already known that Fe(III) incorporated in Ni(II)-based LDH is the key aspect for the high catalytic performance, although the role of Fe in LDH is still ambiguous5,6,12. Besides ${\\mathrm{Fe}}(\\mathrm{III})$ , cobalt is also commonly incorporated in nickel hydroxides to construct NiCo-LDHs for water oxidation13–16, and the resulting NiCo-LDHs show promising catalytic activities; however, the performance is relatively low compared with the reported NiFe-LDHs under identical conditions9. Besides, more earth-abundant metal elements have been incorporated into $\\mathrm{Ni(OH)}_{2}$ to explore novel LDHs for water oxidation, for example, recently Koper and co-workers17 investigated a series of Ni-based double hydroxides with $\\mathrm{Cr}.$ , Mn, Fe, Co, Cu and $Z\\mathrm{n}$ for water oxidation, and among these candidates NiFe-LDH still appears as the most promising and shows the best activity. Up until now, there has been no reported earth-abundant metal element that can outperform Fe incorporated Ni-based LDHs. Searching for an earth-abundant metal to form efficient Ni-based LDH comparable to NiFe-LDH is still the state-of-the-art in this area of energy research. \n\nIn this work, we incorporate another earth-abundant element into ${\\mathrm{Ni}}(\\mathrm{OH})_{2}$ : vanadium, and succeed in forming NiV-LDH as an efficient catalyst for the water oxidation reaction. A simple one-step hydrothermal method is employed to synthesize NiV-LDH. Without need for exfoliation or hybridization with other materials, the resulting monolayer NiV-LDH catalyst exhibits comparable activity to the best-performing NiFe-LDH for water oxidation in alkaline electrolyte. \n\n# Results \n\nMonolayer of $\\mathbf{Ni_{0.75}V_{0.25}–L D H}$ . Figure 1a shows the typical X-ray diffraction patterns of pure $\\mathrm{Ni(OH)}_{2}$ and $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{\\bar{LDH}}$ As can be seen, pure $\\mathrm{Ni(OH)}_{2}$ was successfully synthesized in the simple hydrothermal system without addition of $\\mathrm{v}$ sources, and the X-ray diffraction pattern supports the formation of pure hexagonal $\\mathsf{\\alpha{-}N i}(\\mathrm{OH})_{2}$ (JCPDS 380715), which exhibits a layered structure constructed from $\\mathrm{[NiO_{6}]}$ coordinated octahedra connected by sharing their edges. After incorporation of $\\mathrm{\\DeltaV}$ into the structure of $\\mathsf{\\{-\\mathrm{Ni}(O H)_{2}}}$ , no obvious change can be observed in the X-ray diffraction spectrum, indicating $\\mathrm{\\bar{Ni}_{0.75}V_{0.25}–L D H}$ is the isomorphous compound as $\\mathsf{\\alpha{-}N i}(\\mathrm{OH})_{2}$ with the layered structure. The $\\mathrm{\\DeltaX}$ -ray diffraction pattern of prepared bare $\\mathrm{v}$ -based hydroxide without Ni source (Supplementary Fig. 1) shows very low crystallinity that is significantly different from those of the above Ni-based materials. Figure $16\\mathrm{-}\\mathrm{\\dot{d}}$ shows the Ni $2p$ , V $2p$ and O 1s X-ray photoelectron spectroscopy (XPS) core-level spectra of the $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH powder. The Ni $2p$ spectrum presents two main structures, resulting from the spin–orbit splitting of the $\\boldsymbol{p}$ orbital that are assigned as Ni $2p_{3/2}$ $850-870\\mathrm{eV}$ region) and Ni $2p_{1/2}$ $(870-890\\mathrm{eV}$ region). The binding energy difference between the $3/2$ and $1/2$ components is $\\sim17.4\\mathrm{eV}$ . Ni $2p_{3/2}$ presents a main peak at $\\sim855.4\\mathrm{eV}$ with an intense satellite structure at $\\mathrm{\\sim}861.2\\mathrm{eV}$ , $(\\sim872.8$ and $\\sim879.6\\mathrm{eV}$ , respectively, for $\\mathrm{Ni}2p_{1/2})$ , this signature is characteristic of $\\mathrm{Ni}^{2+}$ (refs 18–21). The spectra of $\\mathrm{~O~}$ 1s and $\\mathrm{~V~}2p$ are presented in Fig. 1c, the O 1s signal originates from $\\mathrm{Ni_{0.75}V_{0.25}–L D H}$ , but its main contributions is from the fluorine doped tin oxide (FTO) glass substrate used with an O1s-binding energy ${\\sim}530\\mathrm{eV}$ . The V $2p$ core-level spectrum is also decomposed into $\\mathrm{~V~}2p_{3/2}$ and V $2{p}_{1/2}$ due to the spin–orbit splitting that are separated by $\\sim7.5\\mathrm{eV}$ . A closer view on the V $2p_{3/2}$ region is shown in Fig. 1d. Three components can be distinguished at $\\sim515.4\\mathrm{eV}$ (in blue), $\\sim516.3\\mathrm{eV}$ (in light grey) and $\\mathrm{\\sim}517.5\\mathrm{eV}$ (in grey) and are in good agreement with respectively $\\mathrm{V}^{3+},~\\mathrm{V}^{\\tilde{4}+}$ and $\\mathrm{V}^{5+}$ (refs 22–24). This result indicates that $\\mathrm{V}^{3+}$ was partially oxidized by oxygen to $\\mathrm{V}^{4+}$ and $\\mathrm{V}^{5+}$ during the synthesis. \n\nTypical transmission electron microscopy (TEM) images of $\\boldsymbol{\\alpha}{-}\\mathrm{Ni}(\\mathrm{OH})_{2}$ and $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ are shown in Fig. 2. Interestingly, as shown in Fig. $^{2\\mathrm{a},\\mathrm{b}}$ , the pure $\\scriptstyle\\alpha-\\mathrm{Ni}(\\mathrm{OH})_{2}$ shows a narrow nanosheet morphology with the size of few tens of nanometre. Aggregated by these nanosheet crystals, a porous sphere structure with the diameter of few micrometres was obtained, as observed by scanning electron microscopy (SEM; Supplementary Fig. 2a). After adding the vanadium source to the initial solution for hydrothermal reaction, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH presents a threedimensional morphology assembled by ultrathin nanosheets as shown in Fig. 2c,d. Selected area electron diffraction pattern in the inset of Fig. 2d confirms the hexagonal phase of $\\bar{\\mathrm{Ni}}_{0.75}\\mathrm{V}_{0.25^{-}}$ LDH. The atomic force microscopy (AFM) and height profile of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ in Fig. 2e,f show that the nanosheet is ultrathin with thickness of $\\sim0.9\\mathrm{nm}$ , indicating the obtained nanosheet is monolayered. To make a comparison, $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ was also prepared by a similar protocol in the literature25 and the SEM image of the products obtained is shown in Supplementary Fig. 2b and c. Some large aggregation plates in $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ can be observed, showing that the size of aggregations by nanosheets in $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ is bigger than $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH. However, the TEM, AFM images and height profile of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH in Supplementary Fig. 2d–f exhibit that the nanosheet of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}\\mathrm{-LDH}$ is also ultrathin with thickness of $\\sim1.2\\mathrm{nm}$ . Meanwhile, differing from the above nanosheet-based structure, the bare V-based and Fe-based hydroxides $(\\beta{\\mathrm{-FeOOH}})$ without Ni content show mainly ‘nanostick’ morphologies after the hydrothermal processes (Supplementary Fig. 3). \n\nOxygen evolution catalysis. It is known that the composition can affect the water oxidation performance of the catalysts significantly. First, we investigated the electrocatalytic activities of NiV-LDHs and NiFe-LDHs on glassy carbon (GC) electrodes with different Ni content to optimize the composition (the measurements were carried out without ohmic-drop correction unless noted otherwise). All the amount of catalyst loadings on GC electrodes were $0.143\\mathrm{mg}\\mathrm{cm}^{-2}$ . As shown in Supplementary Fig. 4, the Ni content plays an essential role for the catalytic activity in this study (the electrocatalytic activities of pure $\\mathrm{Ni(OH)}_{2}.$ , bare $\\mathrm{v}$ -based and Fe-based hydroxides are very low, so they are not shown here for clarity). When the molar ratio of $\\mathrm{\\DeltaNi/X}$ ( $\\mathbf{\\boldsymbol{X}}=\\mathbf{\\boldsymbol{V}}$ or Fe) is 3:1, that is, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ and $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH, the best water oxidation performances are achieved with the highest catalytic current density (Supplementary Fig. 4a–c) and turnover frequency (TOF) (Supplementary Fig. 4d), and the lowest required overpotential (Supplementary Fig. 4e) in NiV-LDH and NiFe-LDH series, respectively (note that for NiFe-LDH, this optimized molar ratio of Ni/Fe is in a good agreement with the literature reported previously6). Either a lower or higher mole ratio of the two metal elements will decrease the catalytic performances of LDHs. The atomic percentage of Ni, V and Fe in $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ and $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH has been measured by energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS; Supplementary Fig. 5), showing the molar ratios of $\\mathrm{Ni/V}$ (3.29) and Ni/Fe (2.93) are close to 3:1 that was used in the corresponding solution stoichiometries. The catalytic performances of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH and $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ are very reproducible (Supplementary Fig. 6) and compared in Fig. 3. A sharp onset catalytic current density can be observed at low overpotential $\\eta\\sim250$ and $300\\mathrm{mV}$ for $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH and $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}–\\mathrm{LDH}$ , respectively. It is apparent that $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}.$ LDH exhibits a better catalytic activity than $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ , suggesting that substituting Fe entirely by $\\mathrm{v}$ in Ni-based LDH can improve the water oxidation performance in our case. The improved catalytic activity of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ is not only shown via the higher catalytic current density of linear scan voltammogram (LSV) curves, but also reflected in its lower Tafel slope (Fig. 3b). $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH catalyst exhibits a Tafel slope of $\\sim50\\mathrm{mV}\\mathrm{dec}^{-1}$ which is smaller than that of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}–\\mathrm{LDH}$ catalyst $(\\sim64\\:\\mathrm{mV}\\:\\mathrm{dec}^{-1}),$ ). Tafel slopes can be influenced by mass transport and electron transport26,27. Different scan rate ranging from 1 to $5\\mathrm{mV}s^{-1}$ for LSV have been done, which resulted in negligible change of current densities for $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ and $\\mathrm{\\tilde{Ni}}_{0.75}\\mathrm{V}_{0.25}$ -LDH catalysts, indicating sufficiently fast mass transport for both $\\mathrm{LDHs}^{26,27}$ . Therefore, it is reasonable to conclude that the lower Tafel slope of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ is likely ascribed to the facile electron transport through the layers of the catalyst. \n\n![](images/5b6e78bf5f29d1745718980210043ace4b8b4b8927967842239f55c36901f56b.jpg) \nFigure 1 | X-ray diffraction and XPS. (a) X-ray diffraction patterns of $(x-N i(0H)_{2}$ and $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH. XPS measurements $(h\\upnu=1,486.6\\mathsf{e V})$ on the $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH powder deposited on a FTO conductive glass: (b) Ni $2p$ (c) O 1s and V $2p$ core-level spectra, and (d) zoom on the $\\textsf{V}2p$ core-level spectrum. \n\nAt $\\eta$ of $350\\mathrm{mV}$ , $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH can achieve current density of $27.0\\pm1.6\\operatorname*{mA}{\\mathrm{cm}^{-2}};$ which is more than twice higher than the one of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}–\\mathrm{LDH}$ $(11.7\\pm1.5\\mathrm{mAcm}^{-2}.$ ). TOF was also calculated at an overpotential of $350\\mathrm{mV}$ in $1\\mathrm{M}\\mathrm{KOH}$ , assuming all the metal sites were electrochemically active in the water oxidation reaction. $\\mathrm{Ni}_{0.25}\\mathrm{V}_{0.25}–\\mathrm{LDH}$ also shows the better TOF of $0.054\\pm0.003s^{-1}$ compare with $0.021\\pm0.003\\mathrm{s}^{-1}$ for $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH. It is worth noting that the above TOFs in this study are obviously underestimated, since some of the metal sites are electrochemically non-accessible. Meanwhile, the overpotential $\\eta$ required to achieve $10\\mathrm{mA}\\mathrm{cm}^{-2}$ current density, which is approximately the current expected at the anode in a $10\\%$ efficient solar water splitting device under 1-sun illumination28, was also evaluated. $\\mathrm{\\bar{Ni}}_{0.75}\\mathrm{Fe}_{0.25}\\mathrm{-LDH}$ and $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH show required overpotential $0.347\\pm0.002$ and $0.318\\pm0.003\\mathrm{V}_{:}$ respectively, exhibiting the lower required overpotential of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH. \n\nIn addition, we compared the durability of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ and $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ in $1\\mathrm{M}\\ \\mathrm{KOH}$ (Fig. 4). When biased galvanostatically at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , both of $\\mathrm{\\bar{Ni}}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ and $\\mathrm{\\bar{Ni}}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ electrodes show considerable stability, the slightly decrease of the required potential for $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ electrode may be due to the amorphazation during the anodic conditioning process26,29. Obviously, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ electrode requires less overpotential than $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}–\\mathrm{LDH}$ , showing its comparable stability and catalytic performance to $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{\\bar{L}D H}$ for water splitting. \n\n# Discussion \n\nTo understand the reason behind the high catalytic performance of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH for water splitting, electrochemical active surface areas (ECSA) of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH and $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ were obtained from cyclic voltammetry (CV) curves in 1 M KOH and compared. Figure 5a shows typical CV curves of $\\mathrm{Ni}_{0.75}$ $\\mathrm{V}_{0.25}$ -LDH with different scan rates. By plotting the $\\Delta J=\\left(J_{\\mathrm{a}}{-}J_{c}\\right)$ at $0.25\\mathrm{V}$ versus $\\mathrm{\\Ag/AgCl}$ against the scan rate, the linear slope that is twice the double layer capacitance $(C_{\\mathrm{dl}})$ can be obtained, and is normally used to represent the corresponding $\\mathrm{ECSA}^{1,9,11,26}$ . \n\n![](images/21945efdf96e2e539d5b25f8d9755ed876b06bb197e0f971cda3c68307424ce9.jpg) \nFigure 2 | TEM and AFM. (a,b) TEM images of $(x-N i(0H)_{2}$ . Scale bar, $1\\upmu\\mathrm{m}$ $\\mathbf{\\eta}(\\mathbf{a})$ ; $200\\mathsf{n m}$ $(\\pmb{\\ b})$ ; (c,d) TEM images of $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH (inset of d: selected area electron diffraction pattern). Scale bar, $200\\mathsf{n m}$ $(\\bullet)_{}^{}$ $100\\mathsf{n m}$ $(\\blacktriangleleft)$ ; (e) AFM image and (f) height profile of $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH nanosheets. \n\nActive surface area is a very important factor for catalysts in water oxidation reaction, as it is well known that an increase of active surface area often leads to enhancement of the catalytic activity. The linear slope (ECSA) of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ is $\\dot{0}.199\\pm0.0\\dot{1}8\\mathrm{mF}\\mathrm{cm}^{-2}$ , while $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH has a higher linear slope of $0.270\\pm0.030\\mathrm{mFcm}^{-2}$ , which means $\\mathrm{Ni}_{0.75}$ $\\bar{\\mathrm{V}_{0.25}}$ -LDH has a more electroactive surface than $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH (Fig. 5b). The bigger ECSA should be attributed to the smaller size of aggregations by nanosheets in $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH (as shown in Supplementary Fig. 2). This can contribute to partial enhancement of water oxidation reaction presented here. Nevertheless, it is important to note that comparing to $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}–\\mathrm{LDH}$ has just slightly $\\sim36\\%$ higher ECSA due to the similar nanostructure, with such small increase of ECSA, more than twofold of current density at $\\eta=350\\mathrm{mV}$ can be achieved. This improvement of the catalytic activity cannot be merely ascribed to the slightly increased surface area of the catalysts. This result suggests that $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH may have higher intrinsic catalytic activity for water oxidation reaction. \n\nTo verify this point, the ECSAs of NiV-LDH with different Ni content were further examined in details, as shown in Fig. 6a–c. The slopes (ECSA) of $\\mathrm{Ni}_{0.25}\\mathrm{V}_{0.75^{-}}$ , $\\mathrm{Ni}_{0.5}\\mathrm{V}_{0.5^{-}}$ , $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}.$ - and $\\mathrm{Ni}_{0.83}\\mathrm{V}_{0.17}$ -LDH electrodes were $0.123\\pm0.009$ , $0.166\\pm0.012$ , $0.270\\pm0.030$ and $0.144\\pm0.015$ $\\mathrm{mFcm}^{-2}$ , respectively, in Fig. 6a. Obviously, the largest ECSA can be achieved when the Ni content was 0.75 in NiV-LDHs, as shown in Fig. 6b as well. The relationship of ECSA with the current density of different NiV-LDHs is exhibited in Fig. 6c. One can see that the current density of NiV-LDH increases with ECSA, further confirming the active surface area of catalyst is an important contributor for the enhancement of water oxidation reaction. However, investigating this result carefully, the ECSA has more than twofold increase from $\\sim0.123$ to $0.270\\mathrm{mFcm}^{-2}$ , while the corresponding current density increases from $\\sim4.0$ to $27.0\\mathrm{mAcm}^{-2}$ showing significantly almost seven times improvement. This is a strong clue that incorporating $\\mathrm{\\DeltaV}$ into Ni hydroxide can not only change the active surface area, but also enhance the intrinsic catalytic property. As a comparison, we also investigated current density-dependent ECSA of different NiFe-LDHs in Fig. 6d. \n\n![](images/4697000faf0dd8a4ae81060781014040379e6d5ed7a23653eaef5969fb214edb.jpg) \nFigure 3 | Linear scan voltammogram (LSV) curves and Tafel plots. (a) LSV curves and $(\\pmb{6})$ Tafel plots (with ohmic-drop correction) of $\\mathsf{N i}_{0.75}\\mathsf{F e}_{0.25}$ -LDH and $N i_{0.75}\\lor_{0.25}{-\\downarrow\\mathsf{D}\\mathsf{H}}$ . \n\n![](images/26d81490312372174ac91ede14dd5c8dfdb09b23b1e9ccfeaf8ab02a2cec42cd.jpg) \nFigure 4 | Long-term stability. Chronopotentiometry curves at current density of $10\\mathsf{m A c m}^{-2}$ of Ni0.75Fe0.25-LDH and $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH. \n\nFor NiFe-LDHs, the current density increases with ECSA as well; however, comparing with the significantly enhanced current density of NiV-LDH, the current density of NiFe-LDH just almost linearly increases to 1.6-fold (from $\\sim7.45$ to $\\mathrm{11.76}\\mathrm{mAcm}^{-2})$ with 1.3-fold increase of ECSA (from $\\sim0.157$ to $0.199\\mathrm{\\mF}\\mathrm{cm}^{-2}$ ). This linear correlation indeed indicates that the improvement of catalytic activity of NiFe-LDHs is mainly due to the increase of actively accessible surface area. We attempted to make a comparison of the catalytic activities between NiFe-LDH and NiV-LDH with the same ECSA value. The linear correlation in Fig. 6d for NiFe-LDH is used to predict the current density of NiFe-LDH with $0.270\\ \\mathrm{mFcm}^{-2}$ of ECSA (the blue solid square in Fig. 6d), which is supposed to have the same ECSA with $\\mathrm{Ni_{0.75}\\mathrm{\\bar{V}}_{0.25}\\mathrm{-LDH}}$ catalyst (the red solid circle in Fig. 6d). The expected current density of NiFe-LDH described above $({\\stackrel{\\cdot}{\\sim}}20.0\\operatorname*{mA}\\operatorname{cm}^{-2})$ is still lower than $\\mathrm{Ni_{0.75}V_{0.25^{-}L D H}}$ $(\\sim27.0\\mathrm{mAcm}^{-2})$ , although they have been estimated to have the same ECSA value. These results suggest in addition to the increased accessible surface area, probably the $\\mathrm{\\DeltaV}$ in the Ni-based LDHs can also lead to the increased intrinsic catalytic activity than NiFe-LDHs in our case. \n\nAlthough it is difficult to correctly normalize the catalytic current to the number of active sites in the LDH electrocatalysts to compare the intrinsic catalytic performances accurately, the kinetic parameters of the Tafel slope and onset potential can be selected to reflect the intrinsic activity of catalysts30,31. Thus, we investigated the Tafel slopes and onset potentials of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ and $\\mathrm{Ni_{0.75}V_{0.25^{-}}L D\\bar{H}}$ in Fig. 3 again. The Tafel slope is only affected by the kinetics of the reaction, which involves the type of active sites but not its quantity, surface area, morphology or electrical resistance30. Therefore, the lower Tafel slope of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH $(\\sim50\\mathrm{mV}\\mathrm{dec}^{-1})_{,}$ ) than that of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ $\\mathrm{^{'}{\\sim}64m V\\ d e c^{-1}},$ indicates the higher catalytic activity and superior type of the active sites in $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH. In addition, $\\mathrm{Ni_{0.75}V_{0.25}–L D H}$ also shows lower onset potential $(\\sim250\\mathrm{mV}$ overpotential) than that of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}^{-}$ -LDH 1 $\\mathrm{\\hbar}\\sim300\\mathrm{mV}$ overpotential), implying the facile kinetics of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ for the water oxidation reaction, which is consistent with the Tafel slope investigation. These results indicate that $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ possesses superior intrinsic catalytic activity in our case. \n\n![](images/bc90f57663a526a247e98ca49a1b049bbcdb27199c7a038b1183ef0f0d847ef0.jpg) \nFigure 5 | ECSA of $\\mathsf{N i}_{0.75}\\mathsf{F e}_{0.25}$ -LDH and $\\ensuremath{\\mathbf{N}}\\ensuremath{\\mathbf{i}}_{0.75}\\ensuremath{\\mathbf{V}}_{0.25}$ -LDH. (a) Typical cyclic voltammetry curves of $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}–\\mathsf{L D H}$ electrode in 1 M KOH with different scan rates; (b) $\\Delta J~(=J_{a}-J_{c})$ of $\\mathsf{N i}_{0.75}\\mathsf{F e}_{0.25}–\\mathsf{L D H}$ and $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH plotted against scan rates. All the error bars represent the ${\\sf s.d.^{\\prime}s}$ of three replicate measurements. The slopes $\\cdot2C_{\\mathrm{dl}})$ were used to represent ECSA. The unit of slopes is $\\mathsf{m F c m}^{-2}$ . \n\n![](images/fbb1b3b59350a5c6bfdaa8fcce693429f0a982bc26c11a96f8cb7503bbc9b204.jpg) \nFigure 6 | ECSA of LDHs. (a) $\\Delta J~(=J_{\\mathrm{a}}-J_{\\mathrm{c}})$ of NiV-LDH with different Ni contents plotted against scan rates. The unit of slopes is $\\mathsf{m F c m}^{-2}$ (b) ECSA $(2C_{\\mathrm{dl}})$ of NiV-LDH with different Ni contents; $\\mathbf{\\eta}(\\bullet)$ current density at $350\\mathsf{m V}$ overpotential plotted against ECSA $(2C_{\\mathrm{dl}})$ of NiV-LDH with different Ni contents; and $({\\pmb d})$ current density at $350\\mathsf{m V}$ overpotential plotted against ECSA $(2C_{\\mathrm{dl}})$ of NiFe-LDH with different Ni contents (black open squares), estimated the activity of NiFe-LDH (blue solid square) with the same ECSA of $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH (red solid circle). All the error bars represent the s.d.’s of three replicate measurements. \n\nThe higher intrinsic catalytic activity of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH may be due to the higher conductivity than $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ . To test the conductivity, electrochemical impedance spectroscopies (EIS) of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH and $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}–\\mathrm{LDH}$ electrodes were carried out in the three-electrode configuration in $1\\mathrm{M}$ KOH. The Nyquist diagrams of both electrodes show an apparent semicircle in the high frequency range (Fig. 7a), which should be mainly associated with charge transfer resistance $(R_{\\mathrm{ct}})$ in the LDH catalysts32,33. The diameter of the semicircle in Nyquist diagram of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH decreases comparing to that of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}\\mathrm{-LDH},$ indicating lower charge transfer resistance, that is, improved conductivity in LDH catalysts. A reported electrical analogue was used to fit the EIS data32, and the $R_{\\mathrm{{ct}}}$ of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH is estimated to be $\\sim62\\Omega\\mathrm{cm}^{2};$ , lower than that of $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH $(\\sim94\\Omega\\mathrm{cm}^{2})$ . This is also reflected in the Bode plots in Fig. 7b, where $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ shows smaller resistance than $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25}$ -LDH. It is known that the LDHs suffer from their low conductivity, in the current case, the higher electron conductivity of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH benefits the charge transfer efficiently, which is also in a good agreement with the lower Tafel slope in Fig. 3b. \n\nOn the other hand, comparing to the relatively planar structure in $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ , the slightly more three-dimensional structured $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ can expose more edges of the nanosheets to the electrolyte (see TEM images in Fig. $^{2\\mathrm{c},\\mathrm{d}}$ and Supplementary Fig. 2). The edges are expected to contain open coordination sites that can be the active sites for water oxidation. Therefore, from this point, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH exposes more active sites than $\\mathrm{Ni}_{0.75}\\mathrm{Fe}_{0.25^{-}}\\mathrm{LDH}$ in electrolyte, while maintaining a similar active surface area. This may be another important factor contributing to the highly catalytic activity of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH. Meanwhile, investigating Fig. 6c again, it is also noted that the increases in ECSA produce large changes in current density up to $\\mathrm{ECSA}=0.17$ $(2C_{\\mathrm{dl}})$ , but after that the trend is much less pronounced. This change of trend of the activity dependent on ECSA for NiV-LDHs indicates that there should be other factors that can influence the activity of NiV-LDHs besides ECSA. It was reported that the catalytic performance of the layered catalyst for water splitting more strongly depends on the edge-state length than ECSA. The catalytic activity can be linear to the edge-state length34. Therefore, as shown in Fig. 6c, a plausible explanation is that it can be speculated that at small ECSA ( $_{<0.17}$ in our case), the active sites on the edge-state length can be exposed to the electrolyte sufficiently, increasing with ECSA, and dominate the catalytic activity, so the modest increases in ECSA can produce large changes in current density by the edge-state length. However, when the ECSA increases to a large value, due to the aggregation, ESCA will cover numerous edges of the nanosheets from the electrolyte, which makes ECSA show more significant effect than the edge-state length, resulting in a slower increase rate. This result also indicates the important role that the edge state of LDHs plays in the catalytic activity. More investigations into the detailed mechanism are in progress. \n\n![](images/0035e29ff3c24027b4a5f2981f0ca682492122ffd018a7ab035c73dcf5abd360.jpg) \nFigure 7 | EIS measurements. (a) Nyquist diagram and (b) Bode plots of Ni0.75Fe0.25-LDH and $\\mathsf{N i}_{0.75}\\mathsf{V}_{0.25}$ -LDH with bias of $350\\mathsf{m V}$ overpotential. \n\nTo further understand the advantages of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}.$ density functional theory (DFT) calculations were performed based on the following mechanism for water oxidation: \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}+*\\rightarrow*\\mathrm{OH}_{2}\n$$ \n\n$$\n{}_{\\ *\\mathrm{OH}_{2}}\\longrightarrow{*\\mathrm{OH}}+\\mathrm{H}^{+}+e\n$$ \n\n$$\n\\mathrm{*OH}\\longrightarrow\\mathrm{*O+H^{+}}+e\n$$ \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}+\\ast\\mathrm{O}\\rightarrow\\ast\\mathrm{OOH}+\\mathrm{H}^{+}+e\n$$ \n\n$$\n\\mathrm{*OOH}\\longrightarrow\\mathrm{O}_{2}+\\ast+\\mathrm{H}^{+}+e\n$$ \n\nHere ‘\\*’ presents the adsorption site that is usually on the top of the doping element. The calculation of the reaction free energy with the zero-point energy and entropy corrections followed the same procedure in ref. 35. Reaction free energies of reaction 1–5 are denoted as $\\Delta G_{1}–\\Delta G_{5}$ , $\\Delta G_{5}$ is defined as $\\bar{4.92\\mathrm{eV}}{-\\Delta G_{1}}{-\\Delta G_{2}}{-}$ $\\Delta G_{3}–\\Delta G_{4}$ to avoid the calculation of the energy of $\\mathrm{O}_{2}$ molecule. The overpotential $\\eta$ is defined in equation (1): \n\n$$\n\\eta=\\operatorname*{max}\\{\\Delta G_{2},\\Delta G_{3},\\Delta G_{4},\\Delta G_{5}\\}/e-1.23\\mathrm{V}\n$$ \n\nThe optimized structures of the intermediates in the free-energy landscape are shown in Fig. 8. The intermediate $^{*}\\mathrm{OH}$ and $^{*}\\mathrm{OOH}$ bind to the surface through oxygen with a single bond. The difference of their binding energies has been shown to be a constant $(3.2\\pm0.2\\mathrm{eV})$ for various materials, such as metals and oxides36. In our case, the constant is calculated to be $3.22\\mathrm{eV}$ Because this binding energy difference equals to the sum of the reaction free energies of reaction 3 and 4 $(\\Delta G_{3}+\\Delta G_{4})^{35,37}$ , the rate-limiting step is either the formation of $^{*}\\mathrm{O}$ from $^{*}\\mathrm{OH}$ $(\\Delta G_{3})$ or formation of $^{*}\\mathrm{OOH}$ from $^*\\mathrm{O}$ $(\\Delta G_{4})$ . The calculated free-energy landscape shows that the rate-limiting step is the formation of $^{*}\\mathrm{OOH}$ when the sample is doped with $\\mathrm{\\DeltaV}$ with $\\eta=0.62\\:\\mathrm{V}$ , whereas the rate-limiting step becomes the formation of $^{*}\\mathrm{O}$ when the sample is doped with Fe with $\\eta=1.28\\:\\mathrm{V}$ . Because $\\Delta G_{3}+\\Delta G_{4}=3.22\\mathrm{eV}_{\\mathrm{;}}$ , the lower limit of the $\\eta$ can be reached when $\\Delta G_{3}=\\Delta G_{4}=1/2\\times3.22\\mathrm{eV}=1.61\\mathrm{eV}$ if a proper element was doped. Then $\\eta=1.61-1.23=0.38\\mathrm{V}$ , which suggests it has a large space to further optimize the activity of Ni-based LDH by doping with other elements. \n\nBesides being better than the prepared NiFe-LDH in our case, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH shows superior catalytic performance than other reported LDHs as well, to the best of our knowledge. Supplementary Table 1 compares the activity of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH with recently reported state-of-the-art LDH catalysts without exfoliation or coupling with other materials, which were loaded on GC electrodes for water splitting, including NiFe-, NiCo-, ZnCo-, CoCo- and MnCo-LDHs. Although the catalytic performances of LDH electrodes are strongly dependent on the preparation methods in literatures, to make a general overview, the current density at $350\\mathrm{mV}$ overpotential and the corresponding mass activity $\\dot{(\\mathrm{A}\\mathrm{g}^{-1})}$ are still used to compare the intrinsic activities between different LDH catalysts. To make the comparison more reasonable, ohmic-drop correction was also performed for $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ , as most of the literature has done (Supplementary Fig. 7)8,9,26,29,38. In our case, without ohmicdrop correction, at $350\\mathrm{mV}$ overpotential, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH can achieve $\\sim27\\mathrm{mAcm}^{-2}$ current density with $\\sim190\\mathrm{Ag}^{-1}$ mass activity. After ohmic-drop correction, the current density and mass activity can be as high as $\\sim57\\mathrm{mAcm}^{-2}$ and $\\sim400\\dot{\\mathrm{Ag}}^{-1}$ , respectively. Those results are even better than some exfoliated NiFe-, NiCo- and CoCo-LDHs. It is worthy to note that $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}–\\mathrm{LDH}$ shows even higher activity than MnCo-LDH $(\\sim43\\mathrm{mAcm}^{-2}$ and $\\sim301\\mathrm{Ag^{-1}}\\overset{\\cdot}{\\underset{.}{\\mathrm{\\Omega}}},$ ) before long-term anodic conditioning that was reported as one of the most active LDH catalyst for water oxidation26. \n\nIt is worth pointing out that although $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ outperforms $\\mathrm{Ni_{0.75}F e_{0.25}–L D H}$ in our case, we cannot claim $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ has higher catalytic activity than all the NiFe-LDHs in the literature. For instance, Louie and Bell reported NiFe-LDH that requires $<300\\mathrm{mV}$ overpotential to deliver current densities of $1\\dot{0}\\mathrm{mA}\\mathrm{cm}^{-2}$ with a Tafel slope of ${\\sim}40\\mathrm{mV}\\mathrm{dec}^{-1}$ (with ohmic-drop correction), which outperforms our $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ probably due to the different preparation method12. Nevertheless, from Supplementary Table 1, our $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ is still highly efficient among the listed catalysts, and comparable to the best-performing NiFe-LDHs12, which indicates our $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH is one of the best water oxidation catalysts. \n\n![](images/d8499d30dbfef05b4fdf6e7c503e5ecdc8a4e0d511a40f205eb653deb002704e.jpg) \nFigure 8 | DFT calculation. Adsorption geometries of the intermediates ${\\sf H}_{2}{\\sf O},$ , $^{\\star}\\mathsf{O}\\mathsf{H}.$ , $^{\\star}\\mathrm{O}$ and $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ in $\\widehat{\\mathbf{a}},\\mathbf{b},\\mathbf{c}$ and $\\mathbf{d},$ respectively. The red, blue, white, grey atoms represent the O, Ni, H and V atoms, respectively. The adsorption structures are similar to these when one Ni is substituted by Fe instead of V; (e) the free-energy landscape. \n\nTo confirm the $\\mathrm{O}_{2}$ evolution and Faradaic efficiency of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH electrode, the experimental and theoretical $\\mathrm{O}_{2}$ evolution amount by $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH at a constant oxidative current of $1\\mathrm{mA}$ in $1\\mathrm{M}\\ \\mathrm{KOH}$ were performed as shown in Supplementary Fig. 8. The experimental $\\mathrm{O}_{2}$ evolution determined by gas chromatography exhibited $101\\pm7\\%$ Faradaic efficiency, when the electrolysis time was $60\\mathrm{min}$ . Moreover, to further explore the highly catalytic activity of $\\mathrm{Ni_{0.75}V_{0.25^{-}}L D H}$ we drop-casted $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ suspension onto Ni foam as well, which can supply excellent conductivity and very high surface area for the electrode, and tested the catalytic activity of resulted electrode in $1\\mathrm{M}\\mathrm{KOH}$ for water oxidation. The $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH on Ni foam exhibits the promising activity for practical applications, with $\\sim44\\mathrm{mAcm}^{-2}$ at $350\\mathrm{mV}$ overpotential, and just $\\sim300\\mathrm{mV}$ overpotential required to reach $10\\mathrm{mA}\\mathrm{cm}^{-2}$ (Supplementary Fig. 9) without ohmic-drop correction. Such catalytic activities of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ on Ni foam indicate attractive prospects for large-scale and practical applications. \n\nIn summary, $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ has been prepared by a simple hydrothermal method, which is monolayered and shows high catalytic activity for the water oxidation reaction comparable to the best-performing NiFe-LDHs. The high intrinsic catalytic activity of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ is mainly due to the good conductivity, facile electron transfer and abundant active sites in the nanolayers of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH, showing potential to be one of the most effective Ni-based LDH electrocatalysts. Our study reveals the promising catalytic properties of vanadium incorporated Ni-based LDHs, and expands the scope of non-precious metal catalysts with the highly intrinsic activity for the water oxidation reaction. \n\n# Methods \n\nPreparation of NiV- and NiFe-LDHs. A one-step hydrothermal method was employed to synthesize the bulk LDHs. In brief, for preparation of NiV-LDH, different mole ratios of $\\mathrm{Ni}/\\mathrm{V}$ solution (1:0, 5:1, 3:1, 1:1, 1:3 and 0:1 for the synthesis of pure $\\mathrm{Ni}(\\mathrm{OH})_{2}$ , $\\mathrm{Ni_{0.83}V_{0.17^{-}L D H}}$ , $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25}$ -LDH, $\\mathrm{Ni}_{0.5}\\mathrm{V}_{0.5}$ -LDH, $\\mathrm{Ni}_{0.25}\\mathrm{V}_{0.75}$ -LDH and bare V-based hydroxide, respectively) was obtained by mixing $\\mathrm{NiCl}_{2}$ and $\\mathrm{VCl}_{3}$ in $80\\mathrm{ml}\\mathrm{H}_{2}\\mathrm{O}$ , while the total amount of metal ions $(\\mathrm{Ni}^{2+}+\\mathrm{V}^{3+})$ was kept to $3.2\\mathrm{mmol}$ . Afterwards, $0.3\\mathrm{g}$ of urea was added, and the above mixture solution was transferred to a stainless-steel Teflon-lined autoclave, and heated in an oven at $120^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ . After cooling the autoclave to room temperature, the resulting powder was washed by deionized water and ethanol three times, collected and then dried at $70^{\\circ}\\mathrm{C}$ overnight. As a reference, for preparation of NiFe-LDH, the same processes were followed except $\\mathrm{FeCl}_{3}$ was used as iron source instead of ${\\mathrm{VCl}}_{3}$ , which was analogous to the literature25. \n\nElectrode preparation. A measure of $5\\mathrm{mg}$ of the obtained LDH powders were dispersed in the mixture solution of 1 ml $\\mathrm{H}_{2}\\mathrm{O}$ , $0.25\\mathrm{ml}\\mathrm{\\Omega}$ -propanol and $10\\upmu\\mathrm{l}\\ 5\\%$ Nafion (ethanol solution) by sonication for $>1\\mathrm{h}$ . A measure of $2.5\\upmu\\mathrm{l}$ of the above suspension were drop-casted to a pre-polished GC electrode (diameter: $3\\mathrm{mm}$ ), and dried at $50^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ to evaporate the solvent. \n\nStructure and surface characterization. X-ray diffraction measurements were carried out on Bruker X-ray diffraction diffractometer D5000 with Cu $\\operatorname{K}\\alpha$ radiation. SEM images were taken on JEOL JSM-7000F instrument with energydispersive X-ray spectroscopy (EDS). TEM images were taken on JEOL JEM2100 TEM. Tapping mode AFM was performed to examine the surface morphology by a Dimension Icon AFM (Bruker, Santa Barbara, USA) on silicon wafer. Rectangular cantilevers with approximate dimensions of $125\\upmu\\mathrm{m}$ in length and $40\\upmu\\mathrm{m}$ in width (BudgetSensors Tap300Al-G) were used to perform the tapping mode experiments. The NanoScope Analysis software (version 1.50, Bruker) was used to analyse the recorded AFM data. A first-order polynomial-flattening algorithm was employed to remove surface tilt from height images. XPS measurements were conducted with an in-house spectrometer (PHI 5500) using monochromatized Al $\\operatorname{K}\\alpha$ radiation \n\n$(1,486.6\\mathrm{eV})$ . The pressure in the analysis chamber was $\\sim5\\times10^{-9}$ mbar during the measurement. Core peaks were analysed using a nonlinear Shirley-type background. The peak positions and areas were optimized by a weighted least-squares fitting method using $70\\%$ Gaussian $130\\%$ Lorentzian lineshapes. The powder was grinded and deposited on a conductive FTO glass. An electron flood gun was used to compensate the charging effects. The XPS spectra were energy calibrated by setting the adventitious carbon peak to $285\\mathrm{eV}$ . \n\nElectrochemical measurements. Electrolysis experiments were carried out in a polytetrafluoroethylene cell with an Autolab potentiostat with GPES electrochemical interface (Eco Chemie) in a standard three-electrode configuration, which was composed of working electrode (LDHs deposited on GC electrodes), counter electrode (Pt net) and reference electrode $\\mathrm{(Ag/AgCl)}$ . The electrolyte was $1\\mathrm{M}\\mathrm{KOH}$ , and the applied potentials were converted with respect to reversible hydrogen electrode (RHE), $E_{\\mathrm{RHE}}=E_{\\mathrm{Ag/AgCl}}+0.059~\\mathrm{pH}+0.197\\mathrm{V}$ and overpotential $\\eta{=}E_{\\mathrm{RHE}}{-}1.23\\mathrm{V}$ . \n\nFirst, before all the electrochemical measurements, a galvanostatic measurement at a fixed current density of $5\\mathrm{mAcm}^{-2}$ was performed until a stable potential was obtained. Then LSV were measured from 0.2 to $0.7\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ with a slow scan rate of $2\\mathrm{m}\\mathrm{V}\\mathrm{s}^{-1}$ . By plotting overpotential $\\eta$ against $\\log{(J)}$ from LSV curves, Tafel slopes can be obtained. To test the stability of LDHs, a galvanostatic measurement at a fixed current density $(J)$ of $10^{\\cdot}\\mathrm{mAcm}^{-2}$ was performed. ECSA were measured by CV at the potential window $0.2\\mathrm{-}0.3\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ , with different scan rates of 20, 40, 60, 80, 100 and $120\\mathrm{mVs}^{-1}$ . By plotting the $\\Delta J=\\left(J_{\\mathrm{a}}-J_{\\mathrm{c}}\\right)$ at $0.25\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ against the scan rate, the linear slope that is twice of the double layer capacitance $(C_{\\mathrm{dl}})$ is used to represent ECSA. All the above measurements were carried out without ohmic-drop correction unless noted otherwise. \n\nTurnover frequency. The TOF of LDH catalysts were calculated according to the following equation ${\\overset{\\cdot}{(2)}}^{9}$ , \n\n$$\nT O F=\\frac{J A}{4F m}\n$$ \n\nwhere $J$ is the current density at a given overpotential, for example, in our cases $\\eta=350\\mathrm{mV}$ , A is the surface area of the electrode $(0.07\\mathrm{cm}^{2})$ , $F$ is Faraday constant $(96,485s\\mathrm{Amol}^{-1}\\mathrm{\\AA},$ and $m$ is the number of moles of the metal on the electrodes. In our cases, we assumed all the metal sites were actively involved in the electrochemical reaction. \n\nTo compare the conductivities of LDHs, EISs were carried out in 1 M KOH with a three-electrode configuration, the frequency ranged from 0.1 to $10^{5}\\mathrm{Hz}.$ with an a.c. amplitude of $10\\mathrm{mV}$ and overpotential bias of $350\\mathrm{mV}$ . \n\nThe measurements of $\\mathrm{O}_{2}$ were performed in an air-tight H shape cell, which was divided by a glass frit to two chambers. The working electrode, the $\\mathrm{Ag/AgCl}$ reference electrode and a magnetic stirring bar were inserted in one chamber of the cell, the Pt counter electrode was inserted in the other chamber. The cell was filled with 1 M KOH and degassed with helium for $\\mathrm{{>}1h}$ . The headspace of the compartment containing the working electrode was $23.6\\mathrm{ml}$ . The electrolysis was carried out with a constant oxidation current of 1 mA for $60\\mathrm{{min}}$ . A measure of $500\\upmu\\mathrm{l}$ of the gas sample in the compartment containing the working electrode was transferred by a specific syringe to the gas chromatography, (Shimadzu) where the amount of $\\mathrm{O}_{2}$ evolution was determined. The Faradaic efficiency was determined from the total amount of charge Q (C) passed through the cell and the total amount of the produced $\\mathrm{O}_{2}\\ n_{\\mathrm{O}2}$ (mol): Faradaic efficiency $\\dot{\\bf\\omega}=4F\\times n_{\\mathrm{O}2}/Q,$ where $F$ is the Faraday constant, assuming the four electrons are needed to produce one oxygen molecule. \n\nDFT calculation. Calculations were carried out with DFT implanted in the Vienna Ab initio Simulation Package $(\\mathrm{VASP})^{39-42}$ to give a better understanding for the superior activity of $\\mathrm{Ni}_{0.75}\\mathrm{V}_{0.25^{-}}\\mathrm{LDH}$ . Perdew-Burke-Ernzerhof (PBE)43 exchangecorrelation functional and projector augmented-wave $\\mathrm{(PAW)^{44}}$ pseudo-potential were adopted. An energy cutoff of $400\\mathrm{eV}$ was applied for the plane-wave basis set. A $2\\times2$ supercell was used with one of the Ni atom substituted by Fe or V. A $7\\times7$ Monkhorst–Pack K-point grid was applied for the sampling of Brillouin zone. To describe the transition metal elements, DFT $+\\mathrm{U}^{45}$ method have been used with the $\\mathrm{~U~}$ values from ref. 35, $\\mathrm{U-J}=3.8\\mathrm{eV}$ for $\\mathrm{Ni}^{2+}$ and $\\mathrm{U}-\\mathrm{J}=4.3\\:\\mathrm{eV}$ for $\\mathrm{Fe}^{3+}$ and $\\mathrm{U-J}=3.4\\mathrm{eV}$ for $\\mathrm{V}^{3+}$ species. One proton of the material is removed to create the metal ion at $^{3+}$ oxidation state. The structures were optimized until the maxima force on the atoms was smaller than $0.02\\mathrm{eV}/\\mathrm{\\AA}$ . \n\nData availability. The data that support the findings of this study are available from the corresponding author upon request. \n\n# References \n\n1. McCrory, C. C. L., Jung, S., Peters, J. C. & Jaramillo, T. F. Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 135, 16977–16987 (2013). \n\n2. Gala´n-Mascaro´s, J. R. Water oxidation at electrodes modified with earth-abundant transition-metal catalysts. ChemElectroChem. 2, 37–50 (2015). \n3. Chen, G. et al. Interfacial effects in iron-nickel hydroxide–platinum nanoparticles enhance catalytic oxidation. Science 344, 495–499 (2014). \n4. Lu, Z. et al. Three-dimensional NiFe layered double hydroxide film for high-efficiency oxygen evolution reaction. Chem. Commun. 50, 6479–6482 (2014). \n5. Trotochaud, L., Young, S. L., Ranney, J. K. & Boettcher, S. W. Nickel–iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation. J. Am. Chem. Soc. 136, 6744–6753 (2014). \n6. Friebel, D. et al. Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting. J. Am. Chem. Soc. 137, 1305–1313 (2015). \n7. Gong, M. & Dai, H. A mini review of NiFe-based materials as highly active oxygen evolution reaction electrocatalysts. Nano Res. 8, 23–39 (2015). \n8. Gong, M. et al. An advanced Ni–Fe layered double hydroxide electrocatalyst for water oxidation. J. Am. Chem. Soc. 135, 8452–8455 (2013). \n9. Song, F. & Hu, X. Exfoliation of layered double hydroxides for enhanced oxygen evolution catalysis. Nat. Commun. 5, 4477 (2014). \n10. Long, X. et al. A strongly coupled graphene and FeNi double hydroxide hybrid as an excellent electrocatalyst for the oxygen evolution reaction. Angew. Chem. Int. Ed. 53, 7584–7588 (2014). \n11. Ma, W. et al. A superlattice of alternately stacked Ni–Fe hydroxide nanosheets and graphene for efficient splitting of water. ACS Nano 9, 1977–1984 (2015). \n12. Louie, M. W. & Bell, A. T. An investigation of thin-film Ni–Fe oxide catalysts for the electrochemical evolution of oxygen. J. Am. Chem. Soc. 135, 12329– 12337 (2013). \n13. Valdez, R., Grotjahn, D. B., Smith, D. K., Quintana, J. M. & Olivas, A. Nanosheets of Co-(Ni and Fe) layered double hydroxides for electrocatalytic water oxidation reaction. Int. J. Electrochem. Sci. 10, 909–918 (2015). \n14. Liang, H. et al. Hydrothermal continuous flow synthesis and exfoliation of NiCo layered double hydroxide nanosheets for enhanced oxygen evolution catalysis. Nano Lett. 15, 1421–1427 (2015). \n15. Burke, M. S., Kast, M. G., Trotochaud, L., Smith, A. M. & Boettcher, S. W. Cobalt-iron (oxy)hydroxide oxygen evolution electrocatalysts: the role of structure and composition on activity, stability, and mechanism. J. Am. Chem. Soc. 137, 3638–3648 (2015). \n16. Liang, J. et al. Topochemical synthesis, anion exchange, and exfoliation of Co–Ni layered double hydroxides: a route to positively charged Co–Ni hydroxide nanosheets with tunable composition. Chem. Mater. 22, 371–378 (2010). \n17. Diaz-Morales, O., Ledezma-Yanez, I., Koper, M. T. M. & Calle-Vallejo, F. Guidelines for the rational design of Ni-based double hydroxide electrocatalysts for the oxygen evolution reaction. ACS Catal. 5, 5380–5387 (2015). \n18. Tan, Z. A. et al. Solution-processed nickel acetate as hole collection layer for polymer solar cells. Phys. Chem. Chem. Phys. 14, 14217–14223 (2012). \n19. De Jesus, J. C., Gonza´lez, I., Quevedo, A. & Puerta, T. Thermal decomposition of nickel acetate tetrahydrate: an integrated study by TGA, QMS and XPS techniques. J. Mol. Catal. A: Chem. 228, 283–291 (2005). \n20. Mansour, A. N. Characterization of NiO by XPS. Surf. Sci. Spectra 3, 231–238 (1994). \n21. Biesinger, M. C. et al. Resolving surface chemical states in XPS analysis of first row transition metals, oxides and hydroxides: Cr, Mn, Fe, Co and Ni. Appl. Surf. Sci. 257, 2717–2730 (2011). \n22. Chen, H. et al. 3D open-framework vanadoborate as a highly effective heterogeneous pre-catalyst for the oxidation of alkylbenzenes. Chem. Mater. 25, 5031–5036 (2013). \n23. Biesinger, M. C., Lau, L. W. M., Gerson, A. R. & Smart, R. S. C. Resolving surface chemical states in XPS analysis of first row transition metals, oxides and hydroxides: Sc, Ti, V, Cu and Zn. Appl. Surf. Sci. 257, 887–898 (2010). \n24. Silversmit, G., Depla, D., Poelman, H., Marin, G. B. & De Gryse, R. Determination of the V2p XPS binding energies for different vanadium oxidation states $\\mathrm{N}^{5+}$ to $\\mathrm{\\dot{V}^{0+}}$ ). J. Electron Spectrosc. 135, 167–175 (2004). \n25. Luo, J. et al. Water photolysis at $12.3\\%$ efficiency via perovskite photovoltaics and Earth-abundant catalysts. Science 345, 1593–1596 (2014). \n26. Song, F. & Hu, X. Ultrathin cobalt–manganese layered double hydroxide is an efficient oxygen evolution catalyst. J. Am. Chem. Soc. 136, 16481–16484 (2014). \n27. Ma, T. Y., Dai, S., Jaroniec, M. & Qiao, S. Z. Graphitic carbon nitride nanosheet–carbon nanotube three-dimensional porous composites as highperformance oxygen evolution electrocatalysts. Angew. Chem. Int. Ed. 53, 7281–7285 (2014). \n28. Walter, M. G. et al. Solar water splitting cells. Chem. Rev. 110, 6446–6473 (2010). \n29. Nai, J. et al. Efficient electrocatalytic water oxidation by using amorphous Ni-Co double hydroxides nanocages. Adv. Energy. Mater. 5, 1401880 (2015). \n30. Huynh, M., Shi, C., Billinge, S. J. L. & Nocera, D. G. Nature of activated manganese oxide for oxygen evolution. J. Am. Chem. Soc. 137, 14887–14904 (2015). \n31. Smith, R. D. L., Pre´vot, M. S., Fagan, R. D., Trudel, S. & Berlinguette, C. P. Water oxidation catalysis: electrocatalytic response to metal stoichiometry in amorphous metal oxide films containing iron, cobalt, and nickel. J. Am. Chem. Soc. 135, 11580–11586 (2013). \n32. Lopes, T., Andrade, L., Ribeiro, H. A. & Mendes, A. Characterization of photoelectrochemical cells for water splitting by electrochemical impedance spectroscopy. Int. J. Hydrogen Energ. 35, 11601–11608 (2010). \n33. Long, X., Xiao, S., Wang, Z., Zheng, X. & Yang, S. Co intake mediated formation of ultrathin nanosheets of transition metal LDH-an advanced electrocatalyst for oxygen evolution reaction. Chem. Commun. 51, 1120–1123 (2015). \n34. Jaramillo, T. F. et al. Identification of active edge sites for electrochemical H2 evolution from $\\ensuremath{\\mathbf{MoS}}_{2}$ nanocatalysts. Science 317, 100–102 (2007). \n35. Liao, P., Keith, J. A. & Carter, E. A. Water oxidation on pure and doped hematite (0001) surfaces: prediction of Co and Ni as effective dopants for electrocatalysis. J. Am. Chem. Soc. 134, 13296–13309 (2012). \n36. Man, I. C. et al. Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem. 3, 1159–1165 (2011). \n37. Calle-Vallejo, F. & Koper, M. T. M. First-principles computational electrochemistry: achievements and challenges. Electrochim. Acta 84, 3–11 (2012). \n38. Li, Y., Zhang, L., Xiang, X., Yan, D. & Li, F. Engineering of ZnCo-layered double hydroxide nanowalls toward high-efficiency electrochemical water oxidation. J. Mater. Chem. A 2, 13250–13258 (2014). \n39. Kresse, G. & Hafner, J. Abinitio molecular-dynamics for liquid-metals. Phys. Rev. B 47, 558–561 (1993). \n40. Kresse, G. & Hafner, J. Ab-initio molecular-dynamics simulation of the liquid-metal amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251–14269 (1994). \n41. Kresse, G. & Furthmuller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n42. Kresse, G. & Furthmuller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comp. Mat. Sci. 6, 15–50 (1996). \n43. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n44. Blo¨chl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n45. Dudarev, S. L., Botton, G. A., Savrasov, S. Y., Humphreys, C. J. & Sutton, A. P. Electron-energy-loss spectra and the structural stability of nickel oxide: an LSDA $+\\mathrm{U}$ study. Phys. Rev. B 57, 1505–1509 (1998). \n\n# Acknowledgements \n\nWe thank Beatrice Johansson from KTH, Dr Valentina Leandri, Chao Xu and Sareh Ahmed from Uppsala University for their help in characterizations of materials. We acknowledge the financial support of this work by Swedish Energy Agency, the Knut and Alice Wallenberg Foundation, the Swedish Research Council, the National Natural Science Foundation of China (21120102036, 91233201) and the National Basic Research Program of China (973 program, 2014CB239402). \n\n# Author contributions \n\nK.F. and H.C. contributed equally to this paper. K.F. designed the experiments, fabricated and measured the devices, and wrote the paper. H.C. carried out the X-ray diffraction, SEM and TEM characterization, analysed the data and helped to revise the paper. Y.J. and Y.L. did the DFT calculation; H.H. and P.C. carried out the AFM measurement; and B.P. and H.R. carried out and analysed the XPS measurements. Q.D. and F.L. contributed to the discussion of the paper. L.S. supervised the project and wrote the paper. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Fan, K. et al. Nickel–vanadium monolayer double hydroxide for efficient electrochemical water oxidation. Nat. Commun. 7:11981 doi: 10.1038/ncomms11981 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1021_acs.jpclett.5b02597", + "DOI": "10.1021/acs.jpclett.5b02597", + "DOI Link": "http://dx.doi.org/10.1021/acs.jpclett.5b02597", + "Relative Dir Path": "mds/10.1021_acs.jpclett.5b02597", + "Article Title": "Cesium Enhances Long-Term Stability of Lead Bromide Perovskite-Based Solar Cells", + "Authors": "Kulbak, M; Gupta, S; Kedem, N; Levine, I; Bendikov, T; Hodes, G; Cahen, D", + "Source Title": "JOURNAL OF PHYSICAL CHEMISTRY LETTERS", + "Abstract": "Direct comparison between perovskite-structured hybrid organic inorganic methylammonium lead bromide (MAPbBr(3)) and all-inorganic cesium lead bromide (CsPbBr3), allows identifying possible fundamental differences in their structural, thermal and electronic characteristics. Both materials possess a similar direct optical band gap, but CsPbBr3 demonstrates a higher thermal stability than MAPbBr(3). In order to compare device properties, we fabricated solar cells, with similarly synthesized MAPbBr(3) or CsPbBr3, over mesoporous titania scaffolds. Both cell types demonstrated comparable photovoltaic performances under AM1.5 illumination, reaching power conversion efficiencies of similar to 6% with a poly aryl amine-based derivative as hole transport material. Further analysis shows that Cs-based devices are as efficient as, and more stable than methylammonium-based ones, after aging (storing the cells for 2 weeks in a dry (relative humidity 15-20%) air atmosphere in the dark) for 2 weeks, under constant illumination (at maximum power), and under electron beam irradiation.", + "Times Cited, WoS Core": 879, + "Times Cited, All Databases": 936, + "Publication Year": 2016, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000367968700029", + "Markdown": "# Cesium Enhances Long-Term Stability of Lead Bromide PerovskiteBased Solar Cells \n\nMichael Kulbak,†,§ Satyajit Gupta,†,§ Nir Kedem,† Igal Levine,† Tatyana Bendikov,‡ Gary Hodes,\\*,† and David Cahen\\*,† \n\n†Department of Materials & Interfaces and ‡Department of Chemical Research Support, Weizmann Institute of Science, Rehovot, 76100, Israel \n\n# Supporting Information \n\nABSTRACT: Direct comparison between perovskite-structured hybrid organic−inorganic methylammonium lead bromide $\\left(\\mathbf{MAPbBr}_{3}\\right),$ ) and all-inorganic cesium lead bromide $(\\cos\\mathrm{PbBr}_{3})$ , allows identifying possible fundamental differences in their structural, thermal and electronic characteristics. Both materials possess a similar direct optical band gap, but $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ demonstrates a higher thermal stability than $\\mathbf{MAPbBr}_{3}$ . In order to compare device properties, we fabricated solar cells, with similarly synthesized $\\mathbf{MAPbBr}_{3}$ or $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ over mesoporous titania scaffolds. Both cell types demonstrated comparable photovoltaic performances under AM1.5 illumination, reaching power conversion efficiencies of ${\\sim}6\\%$ with a \n\n![](images/f729d8ce802c87c6950acb061e636daf0185823e9f93cd0f1f2754724cde0a06.jpg) \n\npoly aryl amine-based derivative as hole transport material. Further analysis shows that Cs-based devices are as efficient as, and more stable than methylammonium-based ones, after aging (storing the cells for 2 weeks in a dry (relative humidity $15\\mathrm{-}20\\%)$ air atmosphere in the dark) for 2 weeks, under constant illumination (at maximum power), and under electron beam irradiation. \n\n$\\mathbf{O}\\left(\\mathrm{HOIPs}\\right)$ wbiatshetdheogn nheyrbicr sd ourcgtaurnailc ionromruglan $\\mathbf{AMX}_{3}$ o(vwskhietrees A is an organic cation, M is the metal center, and X is a halide) have shown rapidly increasing efficiencies1,2 if methylammonium (MA) or formamidinium $\\left(\\mathrm{FA}\\right)^{3}$ is the organic monovalent cation in the $\\mathbf{\\dot{A}}^{\\prime}$ site (which has a permanent dipole moment), $\\mathbf{M}=\\mathrm{lead~}(\\mathbf{Pb}^{2+})$ and $\\mathbf{X}=\\mathbf{a}$ monovalent halide anion.4−6 Most efforts focus on iodide-based materials, which show the highest efficiencies. Cells made with the higher band gap bromide-based perovskites generate an open circuit voltage $(V_{\\mathrm{OC}})$ of up to ${\\sim}1.\\hat{S}\\mathrm{V}.^{7-9}$ Such cells are of interest for possible use in tandem or spectral splitting systems and for photoelectrochemistry to generate energy-storing chemicals by, e.g., water splitting and carbon dioxide $\\left(\\mathrm{CO}_{2}\\right)$ reduction, provided they are stable. \n\nRecently we showed that replacing the organic cation by cesium, ${\\bf C}s^{+}.$ , to form cesium lead bromide $\\left(\\mathrm{CsPbBr}_{3}\\right)$ , with a completely inorganic perovskite structure at standard temperature and pressure, resulted in photovoltaic (photovoltaic) devices with efficiencies as high as those of the analogous HOIP ones.10 That result calls for a direct comparison of the allinorganic to the methylammonium lead bromide $\\left(\\mathbf{MAPbBr}_{3}\\right),$ - based cells both in terms of PV performance and stability, using perovskites that are prepared in the same manner. Here we report such comparison between the $\\mathrm{Cs^{+}}.$ - and MA-based leadhalide perovskites in terms of thermal properties, and the corresponding photovoltaic device performance and stability. \n\nIn our earlier work the active $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ perovskite layer of the cell was deposited in two steps and processing was carried out in ambient atmosphere,10 while the $\\mathbf{MAPbB{r}}_{3}$ was deposited with a one-step process.8 In this report, in contrast, in order to be able to compare the materials and devices made with them, the two materials were prepared under as identical processing conditions as possible (using the two-step process) and the same holds for devices made with them, including materials and thickness of the electron transport material (ETM), mesoporous layer, and hole transport material (HTM). The results of such comparison show that the all-inorganic material and device performance are more stable than those made with the HOIPs, under both operational and storage conditions. \n\nThe structural, electronic and thermal properties of $\\mathbf{MAPbBr}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ were characterized using X-ray diffraction (XRD), UV−visible spectroscopy, ultraviolet photoelectron spectroscopy (UPS), contact potential difference (CPD) measurements and thermogravimetric analysis (TGA). The XRD patterns of the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ (Supporting Information Figure S1A) and $\\mathbf{MAPbBr}_{3}$ (Figure S1B), deposited on mesoporous titania $\\left(\\mathrm{mp-TiO}_{2}\\right)$ -coated FTO slides correspond to previously published patterns of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ and $\\mathbf{MAPbB{r}}_{3}^{-}$ .11,12 Optical absorption/bandgap measurements also agree with previously published data with a direct bandgap for $\\mathbf{MAPbB{r}_{3}}$ of $2.32~\\mathrm{eV}^{8}$ and a direct bandgap of $2.36~\\mathrm{eV}$ possibly preceded by an indirect gap of ${\\sim}2.3\\mathrm{eV}$ for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ (the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ spectrum and bandgap were discussed in ref 10). \n\nValues of work function and ionization energy/valence band energies of the two perovskites deposited on FTO\\dense (d)- $\\mathrm{TiO}_{2}$ were measured by UPS. For $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ the values were 3.95 and $5.75\\ \\mathrm{eV},$ respectively, and for $\\mathbf{MAPbBr}_{3}$ , 4.15 and $6.1~\\mathrm{eV}$ . The work functions of the materials were also obtained from CPD (using the Kelvin-Probe technique) in vacuum (Table S1) and agree well with the UPS measurements. These studies show that the differences in surface energetics between the materials are not large. \n\nA significant difference between the materials was observed in terms of real-time thermal stability, as shown by TGA analysis. Figure 1 shows TGA weight loss on heating the two perovskites and the various constituents making up these perovskites (MABr, CsBr and $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}.$ ). The very large temperature difference between the MABr (onset $200~^{\\circ}\\bar{\\bf C},$ ) and CsBr $(650~^{\\circ}\\mathrm{C})$ evaporation/decomposition sets the stage for the differences in the associated perovskites. $\\mathbf{MAPbB}\\mathbf{r}_{3}$ (first onset ${\\sim}220\\ ^{\\circ}\\mathrm{C}\\ ,$ ) has previously been shown to decompose in two steps: loss of MABr and loss of $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ .13 Qualitatively we see a similar behavior here, although the loss of MABr is about $50\\%$ of what is expected (we will return to that issue below). In the case of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ (onset ${\\sim}580~^{\\circ}\\mathrm{C},$ ), CsBr is more stable (with respect to evaporation or decomposition) than $\\mathrm{Pb}{\\bf B}{\\bf r}_{2},$ and in this case, the latter is lost first. In fact, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ is somewhat more thermally stable than $\\mathrm{Pb}{\\bf B}{\\bf r}_{2}$ itself. This difference in stability of $\\mathbf{MAPbBr}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ (and MA- vs Cs-based perovskites in general) had been predicted by firstprinciples calculations.14 \n\n![](images/5f29c36161a503679502a733546410b728e31a59f9d69f3be00f40d2f01a8f37.jpg) \nFigure 1. Thermogravimetric analyses of methylammonium bromide (MABr), methylammonium lead bromide $\\left(\\mathbf{MAPbBr}_{3}\\right)$ , lead bromide $(\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2})$ , cesium lead bromide $\\left(\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}\\right)$ and cesium bromide (CsBr), showing the higher thermal stability of the inorganic perovskite compared to the hybrid organic−inorganic perovskite. \n\nThe small temperature shift between $\\mathrm{Pb}{\\mathrm{Br}_{2}}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ can be explained, as for the $\\mathbf{MAPbBr}_{3}^{13}$ by greater stability of the first phase to leave when combined in the perovskite compound. The fact that we do not see an intermediate plateau for the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ as in the $\\mathbf{MAPbBr}_{3}$ is probably due to evaporation of CsBr before all the $\\mathrm{Pb}{\\mathbf{B}}{\\mathbf{r}}_{2}$ has been lost. \n\nThere are two aspects of the $\\mathbf{MAPbBr}_{3}$ that are different from the results given in ref 13. One is the first weight loss feature (onset at ${\\sim}220~^{\\circ}\\mathrm{C},$ ): If this loss were purely MABr, we would expect a greater weight loss. Our results are closer to those obtained for $\\mathbf{MAPbI}_{3},$ where this corresponding weight loss feature is sometimes due to loss of both MAI and also $\\mathrm{CH}_{3}\\mathrm{NH}_{2}$ $+\\ \\mathrm{HI}$ lost at a somewhat higher temperature.13,15 We also note the apparently incomplete loss of $\\mathbf{MAPbBr}_{3}$ (it is not completely lost even at high temperatures). This may be due to partial formation of an intermediate ${\\mathrm{Pb}}{\\mathrm{Br}}_{2}{\\mathrm{-Pb}}{\\mathrm{O}}$ compound16 or even $\\mathrm{PbO}$ (while our TGA is carried out under $\\mathbf{N}_{2}$ flow, there is almost certainly a small amount of $\\mathrm{O}_{2}$ present). Both these features of the $\\mathbf{MAPbBp}_{3}$ TGA are reproducible although the quantitative weight loss varies considerably from one measurement to another, particularly for the second weight loss feature, as might be expected if partial oxidation is occurring. \n\nTo study the photovoltaic behavior of $\\mathbf{MAPbBr}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ devices with a configuration $\\mathrm{FTO/d\\mathrm{-}T i O_{2}/m p\\mathrm{-}}$ $\\mathrm{TiO}_{2}$ /perovskite/HTM/Au were fabricated, using PTAA $(\\mathrm{HOMO}\\sim5.2~\\mathrm{eV})$ as HTM. The Cs- and MA-based devices demonstrated comparable performance under AM 1.5 illumination, and the $J{-}V$ results for the best performing cells (in the dark and illuminated) are given in Figure 2. The distributions in various photovoltaic parameters for $\\mathbf{MAPbBr}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}.$ - based cells are shown in Figures S2 and S3, respectively. Average values of the various parameters calculated from these cells are as follows: For $\\mathbf{MAPbBr}_{3}$ -based cells: $V_{\\mathrm{OC}}=1.37\\mathrm{V},J_{\\mathrm{SC}}$ $={\\begin{array}{l}{5.9}\\end{array}}\\mathrm{mA}/\\mathrm{cm}^{2}.$ , fill factor $=71\\%$ , efficiency $=~5.8\\%$ . For $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ -based cells: $V_{\\mathrm{OC}}=1.26\\mathrm{V},J_{\\mathrm{SC}}=6.2\\mathrm{mA}/\\mathrm{cm}^{2},$ fill factor $=74\\%$ and efficiency $\\mathit{\\Theta}=\\ 5.8\\%$ . The $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ cells gave a somewhat lower $V_{\\mathrm{OC}}$ but this was compensated by a higher $J_{\\mathrm{SC}}$ and fill factor. The spectral responses of the two cells are shown in Figure S4. \n\n![](images/2fe08e4cd1d72557938106ba93a59b7d071d02963395233e5c0ab9c1b5101c02.jpg) \nFigure 2. $J{-}V$ characteristics of the best performing $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}.$ and $\\mathbf{MAPbBr}_{3}$ -based cells in the dark and under illumination, demonstrating comparable device performances and tabulated values of their PV parameters (bottom). [PCE: power conversion efficiency; FWD: forward; REV: reverse]. \n\nThe lower $V_{\\mathrm{OC}}$ of the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ -based cells is of particular interest. In principle, it could be due to the deeper valence band of the $\\mathbf{MAPbBr}_{3},$ 6.1 eV compared to $5.75~\\mathrm{eV}$ for the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ although both are much deeper than the (separately measured) valence band edge of the HTM $(5.2~\\mathrm{eV})$ and thus, based on a simple, and probably unrealistic, consideration of energy band alignments, no difference is expected for this reason. In contrast, the smaller electron affinity of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ than of $\\mathbf{MAPbB}\\mathbf{r}_{3}$ could explain the lower $V_{\\mathrm{OC}}$ due to greater energy loss at the perovskite/ $\\mathrm{TiO}_{2}$ interface. This $V_{\\mathrm{OC}}$ difference is presently under investigation. \n\nThe operational stabilities of the cells were monitored by measuring the photocurrent densities at an applied bias close to the initial maximum power point $\\mathrm{\\mathit{\\check{V}}_{m p}}\\sim1.04\\:\\mathrm{V}$ for $\\mathbf{MAPbBp}_{3}$ and ${\\sim}1\\mathrm{v}$ for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ ) as a function of time for both cell types (Figure 3). During a $s\\mathrm{h}$ illumination period, the $\\mathbf{MAPbBp}_{3}$ cell shows a strong decay ( $\\sim55\\%$ loss, compared to the maximum value) in photocurrent density as a function of time, while $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ shows a much slower and smaller decay $(\\sim13\\%)$ in the photocurrent density in the same time frame. Note that all cells in this study were not encapsulated. We assume the initial increase in current of the $\\mathbf{MAPbBr}_{3}$ device is caused by light soaking due to charge accumulation in the perovskite and particularly at the interfaces with the electron and hole extraction layers. While this property is known for planar and not mesoporous cells,17 we do not know of any report showing it for mesoscopic cells. However, there are not many operational stability studies in the literature, and this should be further studied. \n\n![](images/137c300809674d921836f68abe55af4d9a85cbb7a20ad9eee5144ea1a0bb563a.jpg) \nFigure 3. Current density measured at an applied bias close to the initial maximum power point versus time under $100\\mathrm{\\mW/cm^{2}}$ AMI.5 illumination for $\\mathbf{MAPbBr}_{3}.$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ -based cells. \n\nAnother significant difference in device parameters between $\\mathbf{MAPbBr}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ was observed during aging studies, presented in Figure 4. The measurements were carried out in ambient air under relative humidity (RH) of $60-70\\%$ , every couple of days for 2 weeks. Between measurements, the devices were kept in a dry air atmosphere (in the dark) with a RH of ${\\sim}15{-}20\\%$ . $\\mathbf{MAPbBr}_{3}$ -based devices showed a steady decay in all device parameters, leading to an average loss of ${\\sim}85\\%$ in efficiency, $\\sim25\\%$ in open circuit voltage, $\\sim71\\%$ in current density, and ${\\sim}35\\%$ in the fill factor, while $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ -based cells showed no significant decay $(J-V$ curves of the devices are shown in Figure S5). One possible reason is the much higher volatility of MABr compared to CsBr; decomposition of the perovskites with water vapor results in MABr that can gradually volatilize away, while this happens much slower, if at all, with CsBr. Thus, while liquid water can both decompose and remove (some of) the decomposition products of both perovskites rather rapidly, water vapor is expected to have a much smaller effect on the Cs than on the MA perovskite. It may also be that the polar organic MA cation makes $\\mathbf{MAPbB}\\mathbf{r}_{3}$ more hydrophilic in character than $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ and thus allows water molecules to permeate faster through the edges of the devices, increasing the decomposition rate. In any case, higher device stability is critical for long-term practical device applications. \n\nThe devices were further analyzed using electron beaminduced current (EBIC) analysis. Figure 5A,B show crosssectional scanning electron microscopy images of the devices. The top row (A) is for a $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ -based device, while the bottom row (B) is for a $\\mathbf{MAPbBr}_{3}$ one. The extreme left images of the collage are secondary electron (SE) ones (marked as $^{\\omega}\\mathrm{SE}$ image”). Sequential scanning images using EBIC analysis are displayed from left to right (marked as “scan $1^{\\prime\\prime}$ to “scan $\\boldsymbol{5}^{\\prime\\prime}$ in the images of the collage). In brief, EBIC uses an electron beam to act as a light source equivalent, generating electron−hole pairs in the junction area as depicted in Figure S6. These pairs separate into free carriers, which are collected at the contacts. The EBIC signal is acquired pixel by pixel in parallel to the SE image acquisition. For the purpose of tracking beam-induced changes in the EBIC signal, a dose on the order of $5\\times10^{15}{\\mathrm{e}}/$ $\\mathsf{c m}^{2}$ per scan was used. During sequential scans, between measurements, the sample is kept unexposed to the e-beam for 1 min. \n\nThe current originating from the charge collection is observed in real time, and a current collection efficiency image can be drawn. In a mesoporous structure, a fixed collection efficiency is expected throughout the device due to the short collection distance. The EBIC signal in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ - based cells (Figure 5A) is stable from the FTO/ $\\mathbf{d}{\\cdot}\\mathrm{TiO}_{2}$ interface through the mesoporous and capping perovskite layer. There is no apparent loss in charge collection when scanning the same cross sectional area multiple times, suggesting $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ remains stable and does not degrade under the electron beam. For the $\\mathbf{MAPbBr}_{3}$ -based cells, the first EBIC image (Figure 5B) indicates efficient charge collection at the $\\mathrm{FTO}/\\mathrm{d}{-}\\mathrm{TiO}_{2}$ interface, similar to what we reported earlier.18 Although the image drifts while repeating the EBIC scans, it is clear that the EBIC signal decays as the number of scans increases, meaning a decrease in collection efficiency. We attribute this to severe beam damage of the $\\mathbf{MAPbBr}_{3}$ due to extensive local heating at the beam point of entrance. \n\nIt is likely that the thermal stability observed in TGA for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ is associated with the total device stability, as well as its efficient collection efficiency under the electron beam, during EBIC analysis. We suggest that due to its relatively hightemperature, single-phase degradation process, the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}.$ - based devices are less prone to environmental degradation, and their lifetime is prolonged compared to that of $\\mathbf{MAPbBr}_{3}$ -based devices. As the inclusion of chloride in $\\mathbf{MAPbBp}_{3}$ was reported to increase its stability as well,7,19 we are now studying the effects of chloride addition to $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ . \n\n![](images/d52207eeee4bfe141ee8e2141d7a4334b4567a2d2ee305f14d800e3fbb4056f4.jpg) \nFigure 4. Aging analysis of $\\mathbf{MAPbBr}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ cells. Figures show the cell parameters (A) $V_{\\mathrm{OC}},$ (B) $J_{\\mathrm{SC}},$ (C) fill factor, and (D) efficiency, as a function of time, demonstrating the much greater stability of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ -based cells with aging. \n\n![](images/c3091e40d4da4c2ee0dc13878e4c5242dc581b404bd4111a66cff02df0d8211c.jpg) \nFigure 5. Repetitive sequential EBIC responses of cross sections of (A) a $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ cell indicating a stable electron beam-induced current generation whereas (B) the $\\mathbf{MAPbBr}_{3}$ cell, shows a steady decay in current under same conditions (“Scan $1^{\\prime\\prime}$ to “Scan $\\boldsymbol{5}^{\\prime\\prime}$ indicate the sequence of the scans) \n\nIn conclusion, we have shown that replacing the common organic $\\mathrm{\\cdot}_{\\mathrm{A}^{\\prime}}$ site of $\\mathbf{AMX}_{3}$ halide perovskites by an inorganic one forms a more thermally stable perovskite structure, as indicated by TGA analysis. The optoelectronic properties for both materials were investigated using UPS and CPD analysis together with $J{-}V$ characterization, with specific emphasis on the stability of the devices. Devices fabricated with $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ demonstrated photovoltaic performance, comparable to that of $\\mathbf{MAPbBr}_{3}$ -based ones but with much improved solar cell stability as shown in device aging studies. These results indicate that $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ a completely inorganic perovskite, is to be preferred as an $\\mathrm{ABX}_{3}$ absorber over $\\mathbf{MAPbBr}_{3}$ for long-term stable device operation. Further investigation is needed to understand the lower $V_{\\mathrm{OC}}$ (and to increase this parameter) and also the (modestly but reproducibly) higher $J_{\\mathrm{SC}}$ and fill factor obtained for cells with all-inorganic absorbers compared to cells with hybrid absorbers. \n\n# EXPERIMENTAL SECTION \n\nDevice Fabrication. F-doped tin oxide (FTO) transparent conducting substrates (Xinyan Technology TCO-XY15) were cut and cleaned by sequential $15~\\mathrm{\\min}$ sonication in warm aqueous alconox solution, deionized water, acetone, and ethanol, followed by drying under $\\mathbf{N}_{2}$ stream. After an oxygen plasma treatment for $10\\ \\mathrm{min},$ , a compact $\\sim60\\ \\mathrm{nm}$ thin $\\mathrm{TiO}_{2}$ layer was applied to the clean substrate by spray pyrolysis of a $30\\mathrm{\\mM}$ titanium diisopropoxide bis(acetylacetonate) (SigmaAldrich) solution in isopropanol using air as the carrier gas on a hot plate set to $450\\ ^{\\circ}\\mathrm{C},$ followed by a two-step annealing procedure at 160 and $500~^{\\circ}\\mathrm{C},$ each for $^\\textrm{\\scriptsize1h}$ in air. \n\nA $450~\\mathrm{nm}$ -thick mesoporous $\\mathrm{TiO}_{2}$ scaffold was deposited by spin-coating a $\\mathrm{TiO}_{2}$ paste onto the dense $\\mathrm{TiO}_{2}$ -coated substrates. A $\\mathrm{TiO}_{2}$ paste $(\\mathrm{DYESOL},$ DSL 18NR-T) and ethanol were mixed in a ratio of 2:7 by weight and sonicated until all the paste dissolved. The paste was spin-coated for 5 s at $500~\\mathrm{rpm}$ and $30~\\mathsf{s}$ at $2000~\\mathrm{rpm}.$ , twice, followed by a two-step annealing procedure at 160 and $500~^{\\circ}\\mathrm{C},$ each for $^\\textrm{\\scriptsize1h}$ in air. \n\nThe $\\mathbf{MAPbB}\\mathbf{r}_{3}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ films were prepared by a twostep sequential deposition technique. For both cases, $^\\mathrm{~1~M~}$ of $\\mathrm{Pb}{\\bf B}{\\bf r}_{2}$ (Sigma-Aldrich) in DMF was stirred on a hot plate at 75 $^{\\circ}\\mathrm{C}$ for $20~\\mathrm{min}$ . It was then filtered using a $0.2\\ \\mu\\mathrm{m}$ pore size PTFE filter and immediately used. The solution was kept at 75 $^{\\circ}\\mathrm{C}$ during the spin-coating process. For preparation of the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ film, the solution was spin-coated on preheated (75 $^{\\circ}\\mathrm{C})$ ) substrates for $30~\\mathsf{s}$ at $2500~\\mathrm{rpm}$ and was then dried on a hot plate at $70~^{\\circ}\\mathrm{C}$ for $30~\\mathrm{min}$ . After drying, the substrates were dipped for $10~\\mathrm{min}$ in a heated $(50~^{\\circ}\\mathrm{C})$ solution of $17~\\mathrm{mg/mL}$ CsBr (Sigma-Aldrich) in methanol for $10~\\mathrm{{min},}$ , washed with 2- propanol, dried under ${\\bf N}_{2}$ stream and annealed for $10\\ \\mathrm{min}$ at $250~^{\\circ}\\mathrm{C}$ . For $\\mathbf{MAPbBr}_{3},$ the solution was spin-coated over unheated substrates for $20~\\mathsf{s}$ at $3000~\\mathrm{rpm}_{\\cdot}$ , and was dried on a hot plate at $70~^{\\circ}\\mathrm{C}$ for $30~\\mathrm{min}$ . After drying, the substrates were dipped for $40\\textrm{s}$ in a $10~\\mathrm{mg/mL}$ MABr in isopropanol, washed with isopropanol, and then dried under $\\mathrm{N}_{2}$ stream and annealed for $15\\ \\mathrm{min}$ at $100~^{\\circ}\\mathrm{C}.$ . All procedures were carried out in an a m b i e n t a t m o s p h e r e . P o l y [ b i s ( 4 - p h e n y l ) ( 2 , 4 , 6 - trimethylphenyl)amine] (PTAA − Lumtec) was applied by spin-coating 5 s at $500~\\mathrm{rpm}$ followed by $40\\ s$ at $2000~\\mathrm{rpm}$ . For $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3},$ the PTAA solution contained $15\\mathrm{\\mg}$ in $1\\ \\mathrm{mL}$ of chlorobenzene, mixed with $7.5~\\mu\\mathrm{L}$ of tert-butylpyridine (TBP) and $7.5\\mu\\mathrm{L}$ of $\\mathrm{170mg/mL}$ LiTFSI [bis(trifluoromethane)- sulfonamide (in acetonitrile)], while for $\\mathbf{MAPbBr}_{3}$ the PTAA solution contained $30~\\mathrm{mg}$ in $1~\\mathrm{mL}$ of chlorobenzene, mixed with $15\\ \\mu\\mathrm{L}$ of tert-butylpyridine and $15\\ \\mu\\mathrm{L}$ of $\\mathrm{170~mg/mL}$ LiTFSI. The samples were left overnight in the dark in dry air before ${\\sim}100~\\mathrm{nm}$ gold contacts were thermally evaporated on the back through a shadow mask with $0.24~\\mathrm{cm}^{2}$ rectangular holes. \n\nCharacterization. The thermogravimetric analyses was carried out using TA Instruments, at a heating rate of $20~\\mathrm{{^circC/min}}$ (using alumina crucibles) under $\\mathbf{N}_{2}$ flow. XRD measurements were conducted on a Rigaku ULTIMA III operated with a $\\mathtt{C u}$ anode at $40\\ \\mathrm{kV}$ and $40\\ \\mathrm{mA}.$ The measurements were taken using a Bragg−Brentano configuration through a $10~\\mathrm{mm}$ slit, a convergence Soller $5^{\\circ}$ slit and a $^{\\omega}\\mathrm{Ni}^{\\omega}$ filter. A Jasco V-570 spectrophotometer with an integrating sphere was used for measuring reflectance-corrected transmission. The $J{-}V$ characteristics were measured with a Keithley 2400-LV SourceMeter and controlled with a Labview-based, in-house written program. A solar simulator (ScienceTech SF-150; with a 300 W xenon short arc lamp from USHIO Inc., Japan) equipped with an AM1.5 filter and calibrated with a Si solar cell IXOLARTM High Efficiency SolarBIT (IXYS XOB17-12x1) was used for illumination. The devices were characterized through a 0.16 $\\mathrm{cm}^{2}$ mask. The $J{-}V$ characteristics were taken after light soaking for $10\\mathrm{~s~}$ at open circuit and at a scan rate of $0.06\\mathrm{\\:V/s}$ (unless otherwise stated). UPS measurements were carried out using a Kratos AXIS ULTRA system, with a concentric hemispherical analyzer for photoexcited electron detection. UPS was measured with a helium discharge lamp, using He I $(21.22\\ \\mathrm{eV})$ and He II $(40.8\\ \\mathrm{eV})$ radiation lines. All UPS spectra were measured with a $-10\\mathrm{~V~}$ bias applied to the sample to observe photoemission onset at low kinetic energies. The total energy resolution was better than $100\\mathrm{meV},$ as determined from the Fermi edge of gold $\\left(\\mathrm{Au}\\right)$ reference. A Kelvin probe located in a controlled atmosphere station (McAllister Technical Services) was used to measure CPD between the probe and the sample surface, under a vacuum of ${\\sim}10^{-3}$ mbar. EBIC analysis was done in a Zeiss-Supra SEM using beam current of ${\\mathfrak{s}}_{\\mathrm{\\pA}}$ and beam energy of $3\\mathrm{\\keV}.$ . Current was collected and amplified using Stanford Research Systems SR570 preamplifier. The device cross section was exposed by mechanical cleaving immediately (up to $2~\\mathrm{min}$ ) before transferring the sample into the SEM vacuum chamber $(10^{-5}~\\mathrm{mbar})$ ). \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpclett.5b02597. \n\nX-ray diffractograms, work function values, statistics of cell parameters, IPCE curves, $J{-}V$ curves taken during device aging, and a schematic explaining the EBIC analysis (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Authors $^{*}\\mathrm{E}$ -mail: gary.hodes@weizmann.ac.il. $^{*}\\mathrm{E}$ -mail: david.cahen@weizmann.ac.il. \n\nAuthor Contributions \nContributed equally. \nNotes \nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis research work was supported by the Israel Ministry of Science’s Tashtiot, Israel−China and India−Israel programs, the Israel National Nanoinitiative, and the Sidney E. Frank Foundation through the Israel Science Foundation. D.C. holds the Sylvia and Rowland Schaefer Chair in Energy Research. \n\n# REFERENCES \n\n(1) Jeon, N. J.; Noh, J. H.; Yang, W. S.; Kim, Y. C.; Ryu, S.; Seo, J.; Seok, S. I. Compositional Engineering of Perovskite Materials for High-Performance Solar Cells. Nature 2015, 517, 476−480. \n(2) Burschka, J.; Pellet, N.; Moon, S.-J.; Humphry-Baker, R.; Gao, P.; Nazeeruddin, M. K.; Grätzel, M. Sequential Deposition as a Route to High-Performance Perovskite-Sensitized Solar Cells. Nature 2013, 499, 316−319. \n(3) Eperon, G. E.; Stranks, S. D.; Menelaou, C.; Johnston, M. B.; Herz, L. M.; Snaith, H. J. Formamidinium Lead Trihalide: A Broadly Tunable Perovskite for Efficient Planar Heterojunction Solar Cells. Energy Environ. Sci. 2014, 7, 982−988. \n(4) Berry, J.; Buonassisi, T.; Egger, D. A.; Hodes, G.; Kronik, L.; Loo, Y.-L.; Lubomirsky, I.; Marder, S. R.; Mastai, Y.; Miller, J. S.; et al. Hybrid Organic-Inorganic Perovskites (HOIPs): Opportunities and Challenges. Adv. Mater. 2015, 27, 5102−5112. \n(5) Green, M. A.; Ho-Baillie, A.; Snaith, H. J. The Emergence of Perovskite Solar Cells. Nat. Photonics 2014, 8, 506−514. \n(6) Hodes, G.; Cahen, D. Photovoltaics: Perovskite Cells Roll Forward. Nat. Photonics 2014, 8, 87−88. \n(7) Edri, E.; Kirmayer, S.; Kulbak, M.; Hodes, G.; Cahen, D. Chloride Inclusion and Hole Transport Material Doping to Improve Methyl Ammonium Lead Bromide Perovskite-Based High Open-Circuit Voltage Solar Cells. J. Phys. Chem. Lett. 2014, 5, 429−433. \n(8) Edri, E.; Kirmayer, S.; Cahen, D.; Hodes, G. High Open-Circuit Voltage Solar Cells Based on Organic−Inorganic Lead Bromide Perovskite. J. Phys. Chem. Lett. 2013, 4, 897−902. \n(9) Ryu, S.; Noh, J. H.; Jeon, N. J.; Chan Kim, Y.; Yang, W. S.; Seo, J.; Seok, S. I. Voltage Output of Efficient Perovskite Solar Cells with High Open-Circuit Voltage and Fill Factor. Energy Environ. Sci. 2014, 7, 2614−2618. \n(10) Kulbak, M.; Cahen, D.; Hodes, G. How Important Is the Organic Part of Lead Halide Perovskite Photovoltaic Cells? Efficient $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ Cells. J. Phys. Chem. Lett. 2015, 6, 2452−2456. \n(11) Tidhar, Y.; Edri, E.; Weissman, H.; Zohar, D.; Hodes, G.; Cahen, D.; Rybtchinski, B.; Kirmayer, S. Crystallization of Methyl Ammonium Lead Halide Perovskites: Implications for Photovoltaic Applications. J. Am. Chem. Soc. 2014, 136, 13249−13256. \n(12) Stoumpos, C. C.; Malliakas, C. D.; Peters, J. A.; Liu, Z.; Sebastian, M.; Im, J.; Chasapis, T. C.; Wibowo, A. C.; Chung, D. Y.; Freeman, A. J.; et al. Crystal Growth of the Perovskite Semiconductor $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ : A New Material for High-Energy Radiation Detection. Cryst. Growth Des. 2013, 13, 2722−2727. \n(13) Liu, Y.; Yang, Z.; Cui, D.; Ren, X.; Sun, J.; Liu, X.; Zhang, J.; Wei, $\\textsc{Q}.$ ; Fan, H.; $\\mathrm{Yu,}$ F.; et al. Two-Inch-Sized Perovskite $\\mathrm{CH_{3}N H_{3}P b}X_{3}$ $\\mathrm{\\nabla{X}=C l,}$ Br, I) Crystals: Growth and Characterization. Adv. Mater. 2015, 27, 5176−5183. \n(14) Zhang, Y.-Y.; Chen, S.; Xu, P.; Xiang, H.; Gong, X.-G.; Walsh, A.; Wei, S.-H. Intrinsic Instability of the Hybrid Halide Perovskite Semiconductor $\\mathrm{CH_{3}N H_{3}P b I_{3}};$ arXiv:1506.01301v1, 2015. \n(15) Dualeh, A.; Gao, P.; Seok, S. I.; Nazeeruddin, M. K.; Grätzel, M. Thermal Behavior of Methylammonium Lead-Trihalide Perovskite Photovlotaic Light Harvesters. Chem. Mater. 2014, 26, 6160−6164. (16) Knowles, L. M. Thermal Analysis of the System $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ -PbO. J. Chem. Phys. 1951, 19, 1128−1130. \n(17) Zhao, C.; Chen, B.; Qiao, X.; Luan, L.; Lu, K.; Hu, B. Revealing Underlying Processes Involved in Light Soaking Effects and Hysteresis Phenomena in Perovskite Solar Cells. Adv. Energy Mater. 2015, 5, 1500279. \n(18) Kedem, N.; Brenner, T. M.; Kulbak, M.; Schaefer, N.; Levcenko, S.; Levine, I.; Abou-Ras, D.; Hodes, G.; Cahen, D. Light-Induced Increase of Electron Diffusion Length in a $\\mathtt{p-n}$ Junction Type $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ Perovskite Solar Cell. J. Phys. Chem. Lett. 2015, 6, 2469−2476. \n(19) Das, J.; Bhaskar Kanth Siram, R.; Cahen, D.; Rybtchinski, B.; Hodes, G. Thiophene-Modified Perylenediimide as Hole Transporting Material in Hybrid Lead Bromide Perovskite Solar Cells. J. Mater. Chem. A 2015, 3, 20305−20312. " + }, + { + "id": "10.1038_ncomms11204", + "DOI": "10.1038/ncomms11204", + "DOI Link": "http://dx.doi.org/10.1038/ncomms11204", + "Relative Dir Path": "mds/10.1038_ncomms11204", + "Article Title": "Coupled molybdenum carbide and reduced graphene oxide electrocatalysts for efficient hydrogen evolution", + "Authors": "Li, JS; Wang, Y; Liu, CH; Li, SL; Wang, YG; Dong, LZ; Dai, ZH; Li, YF; Lan, YQ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electrochemical water splitting is one of the most economical and sustainable methods for large-scale hydrogen production. However, the development of low-cost and earth-abundant non-noble-metal catalysts for the hydrogen evolution reaction remains a challenge. Here we report a two-dimensional coupled hybrid of molybdenum carbide and reduced graphene oxide with a ternary polyoxometalate-polypyrrole/reduced graphene oxide nullocomposite as a precursor. The hybrid exhibits outstanding electrocatalytic activity for the hydrogen evolution reaction and excellent stability in acidic media, which is, to the best of our knowledge, the best among these reported non-noble-metal catalysts. Theoretical calculations on the basis of density functional theory reveal that the active sites for hydrogen evolution stem from the pyridinic nitrogens, as well as the carbon atoms, in the graphene. In a proof-of-concept trial, an electrocatalyst for hydrogen evolution is fabricated, which may open new avenues for the design of nullomaterials utilizing POMs/conducting polymer/reduced-graphene oxide nullocomposites.", + "Times Cited, WoS Core": 950, + "Times Cited, All Databases": 983, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000373478700001", + "Markdown": "# Coupled molybdenum carbide and reduced graphene oxide electrocatalysts for efficient hydrogen evolution \n\nJi-Sen Li1,2,\\*, Yu Wang1,\\*, Chun-Hui Liu1, Shun-Li Li1, Yu-Guang Wang2, Long-Zhang Dong1, Zhi-Hui Dai1, Ya-Fei Li1 & Ya-Qian Lan1 \n\nElectrochemical water splitting is one of the most economical and sustainable methods for large-scale hydrogen production. However, the development of low-cost and earth-abundant non-noble-metal catalysts for the hydrogen evolution reaction remains a challenge. Here we report a two-dimensional coupled hybrid of molybdenum carbide and reduced graphene oxide with a ternary polyoxometalate-polypyrrole/reduced graphene oxide nanocomposite as a precursor. The hybrid exhibits outstanding electrocatalytic activity for the hydrogen evolution reaction and excellent stability in acidic media, which is, to the best of our knowledge, the best among these reported non-noble-metal catalysts. Theoretical calculations on the basis of density functional theory reveal that the active sites for hydrogen evolution stem from the pyridinic nitrogens, as well as the carbon atoms, in the graphene. In a proof-of-concept trial, an electrocatalyst for hydrogen evolution is fabricated, which may open new avenues for the design of nanomaterials utilizing POMs/conducting polymer/ reduced-graphene oxide nanocomposites. \n\nTcaototanedtnadtirmoeisn toihoenh,e rererosgeyeanrc ihasei p hdmaviaseimnegdl oavrlotateteredne icvoiernostinodmefreoansbtslaiel fuels. Electrochemical water splitting to produce hydrogen, or the hydrogen evolution reaction (HER), is the most economical and sustainable method for large-scale hydrogen production. Achieving this goal requires inexpensive electrocatalysts with high efficiency for the $\\mathrm{HER}^{\\mathrm{i},2}$ . Although the best electrocatalysts are $\\mathrm{Pt}$ or $\\mathrm{Pt}$ -based materials, their high cost and low abundance substantially hamper their large-scale utilization3–5. Thus, the development of low-cost and earth-abundant non-noble-metal catalysts to replace $\\mathrm{Pt}$ is an important and urgently needed for practical applications. \n\nBecause of their Pt-like catalytic behaviours6, Mo-based compounds, such as $\\mathbf{Mo}_{2}\\mathbf{C}^{7-10}$ , $\\mathrm{MoN}^{11-13}$ , $\\ensuremath{\\mathrm{MoS}}_{2}$ (refs 14–17), and others18–20 have attracted substantial interest as a new class of electrocatalysts. To further enhance the HER activity, Mo-based compounds have been anchored onto conductive supports, such as carbon nanosheets $(\\mathrm{NSs})^{21-23}$ and carbon nanotubes $(\\mathrm{CNTs})^{11,24,25}$ , which not only prevent Mo-based compounds from aggregating but also increase the dispersion of active sites. Among these conductive supports, reduced graphene oxide (RGO), particularly nitrogen (N)-doped RGO, has garnered much attention because of its excellent electron transport properties and chemical stability26,27. Therefore, RGO-supported Mo-based compounds appear to be highly active and stable electrocatalysts11,25,28–30. However, carbonization at high-reaction temperature during synthesis procedures leads to the sintering and aggregation of Mo-based-compound nanoparticles (NPs), thus reducing their number of exposed active sites and their specific surface area8,19. In addition, due to its strong $\\pi$ -stacking and hydrophobic interactions, RGO NSs usually aggregate, which hinders their practical application31,32. Preventing the RGO from re-stacking and the Mo-based compound NPs from aggregating during the synthesis of a porous uniform thin layer RGOsupported Mo-based electrocatalysts is critical to enhancing their catalytic performance. \n\nWe developed a new approach to integrate polyoxometalates (POMs) and pyrrole (Py) on graphene substrates via a ‘‘one-pot’’ method to obtain ternary POMs–polypyrrole/RGO (POMs–PPy/ RGO) nanohybrid sheets with a uniform distribution. As an important family of transition-metal oxide clusters with excellent redox features33,34, POMs provided an essential oxidizing medium for the oxidative polymerization of $\\mathrm{Py}^{35}$ , and the POMs finally were converted into ‘‘heteropoly blue’’36. Heteropoly blue can be used as a highly localized reducing agent and can further react with graphene oxide (GO) to restore the original POMs. With the polymerization of the Py monomers, POMs were dispersed into the PPy framework. Meanwhile, RGO was homogeneously dispersed and segregated by both the POMs and PPy during the synthesis of POMs–PPy/RGO. Thus, RGO-supported Mo-based catalysts prepared with POMs–PPy/RGO as a precursor may efficiently hinder the Mo sources and graphene from aggregating during the process of forming the RGO-supported NPs. To the best of our knowledge, reports on POMs, PPy and RGO ternary hybrids by a green and one-pot redox relay reaction are rare. More importantly, the coupled hybrid with both $\\mathrm{Mo}_{2}\\mathrm{C}$ and RGO has not been previously prepared with a ternary hybrid as the precursor. \n\nIn this work, we carefully design and fabricate a two-dimensional (2D) coupled hybrid consisting of $\\mathrm{Mo}_{2}\\mathrm{C}$ encapsulated by N, phosphorus (P)-codoped carbon shells and N, P-codoped RGO (denoted as $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGO)}$ using a $\\mathrm{PMo}_{12}$ $\\mathrm{(H_{3}P M o_{12}O_{40})}$ –PPy/RGO nanocomposite as the precursor. Notably, the entire polymerization and the reductive reactions are triggered by $\\mathrm{PMo}_{12}$ without any additional oxidants or reductants, leading to a synthetic process that is green, efficient and economical. PPy was used as both the carbon and nitrogen sources as well as the reducing agent for GO. Three main advantages of this method are attributed to the $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO hybrid: (1) due to the unique structure of $\\mathrm{PMo}_{12}\\mathrm{-PPy/}$ RGO, the $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs are nanosized and uniformly embedded in the carbon matrix without aggregation; (2) the $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs are coated with carbon shells, which effectively prevent $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs from aggregating or oxidizing and impart them with fast electron transfer ability; and (3) owing to the heteroatom dopants (N, P), a large number of active sites are exposed. Overall, taking advantage of the synergistic catalytic effects, the $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO catalyst exhibits excellent electrocatalytic activity for the HER, with a low onset overpotential of $0\\mathrm{mV}$ (vs reversible hydrogen electrode (RHE)), a small Tafel slope of $33.6\\mathrm{mV}\\mathrm{dec}^{-1}$ , and excellent stability in acidic media. Its HER catalytic activity, which is comparable to that of commercial $\\mathrm{Pt-C}$ catalyst, even superior to those of the best reported non-noble-metal catalysts. In addition, we further investigate the nature of catalytically active sites for the HER using density functional theory (DFT). This approach provides a perspective for designing 2D nanohybrids with transition-metal carbides and RGO as HER catalysts. \n\n# Results \n\nCatalyst synthesis and characterization. $\\mathrm{Mo}_{2}\\mathrm{C@NPC/N}$ PRGO was synthesized as follows: (1) the $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ nanocomposite was synthesized via a green one-pot redox relay reaction. The nanocomposite was then carbonized under a flow of ultrapure $\\mathrm{N}_{2}$ at $900^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ at a heating rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ . Finally, the obtained samples were acid etched in 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ for $24\\mathrm{h}$ with continuous agitation at $80^{\\circ}\\mathrm{C}$ to remove unstable and inactive species. The etched samples were thoroughly washed with deionized water until the $\\mathsf{p H}$ of the wash water was neutral (Fig. 1). \n\nFigure 2a shows a scanning electron microscopy (SEM) image of $\\mathrm{P\\bar{M}o_{12}\\mathrm{-}P P y/R G O}$ The rough surfaces and wrinkled edges on the sheet-like structures were due to the intercalation and polymerization of Py. A transmission electron microscopy (TEM) image of $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ revealed that a large amount of PPy $\\mathrm{\\Delta}^{\\prime}\\mathrm{PMo}_{12}$ NPs were homogeneously coated onto the RGO NSs and that voids were present (Fig. 2b). As evident in Fig. 2c and d, the morphologies of $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO were similar to that of $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ after carbonization. The nanosized $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs with diameters of $\\sim2\\ –5\\mathrm{nm}$ were uniformly decorated on the RGO sheets at a high density, which was attributed to the distinct porous structure of $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}.$ The high-resolution TEM (HRTEM) image exhibited clear lattice fringes with an interplanar distance of $0.238\\mathrm{nm}$ , corresponding to the (111) planes of $\\mathsf{M o}_{2}\\mathrm{C}$ (Fig. 2e)37. Notably, the $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs were embedded in the carbon shells, which can efficiently prevent the aggregation and/or excessive growth of $\\mathrm{Mo}_{2}\\mathrm{C}\\ \\mathrm{NPs}^{\\hat{2}2}$ . Figure 2f shows the scanning TEM (STEM) and corresponding energy dispersive X-ray spectroscopy (EDX) elemental mapping images, which confirmed that C, Mo, $\\mathrm{~N~}$ and $\\mathrm{~\\bf~P~}$ were distributed on the $\\mathrm{Mo_{2}C@N P C/N P R G O}$ surface, consistent with the EDX spectrum (Supplementary Fig. 1). These results confirm the successful synthesis of the $\\mathrm{Mo_{2}C@N P C/N P R G C}$ nanocomposite. \n\n![](images/68110fd7dd7e279c5e346801229482f21728447c8701bbf651babc36854f5f86.jpg) \nFigure 1 | Schematic illustration of the synthetic process of $M O_{2}C(\\Delta q)\\Delta p C$ /NPRGO. (a) Synthesis of $\\mathsf{P M o}_{12}$ –PPy/RGO via a green one-pot redox relay reaction. (b) Formation of ${M O}_{2}{\\mathsf{C}}_{\\varepsilon}$ NPC/NPRGO after carbonizing at $900^{\\circ}\\mathsf{C}$ . \n\n![](images/86060ce9297f6a4684cd26f88b3e0cfbfcf9509343d80fd2c0b9a8db4ad1db66.jpg) \nFigure 2 | Characterization of the $\\mathsf{P M o}_{12}$ –PPy/RGO and $M O_{2}\\mathsf{C}\\ @\\mathsf{N P C}/$ NPRGO hybrids. (a) SEM and (b) TEM images of $\\mathsf{P M o}_{12}\\mathrm{-PPy/RGO}$ . (c) SEM, (d) TEM, (e) HRTEM and (f) STEM images and EDX elemental mapping of C, N, P and Mo of ${M o}_{2}{\\mathsf{C}}_{\\varepsilon}$ NPC/NPRGO. Scale bar: a,b,c ( $200\\mathsf{n m})$ ; d $(100\\mathsf{n m})$ ; e $\\cdot5\\mathsf{n m})$ and f $(50\\mathsf{n m})$ ). \n\nFor comparison, the nanohybrid of $\\mathtt{M o}_{2}\\mathrm{C}$ encapsulated by N, P-codoped carbon (defined as $\\mathrm{Mo}_{2}\\mathrm{C@NPC})$ was also synthesized through a similar preparation procedure without GO. Supplementary Fig. 2a shows aggregation of $\\mathrm{PPy}/\\mathrm{PMo}_{12}$ NPs. \n\nSupplementary Fig. 2b and c reveals that $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs tended to agglomerate during the heat treatment to form large NPs, which decreased the exposed active surface. Supplementary Fig. 2d demonstrates the STEM and EDX elemental mapping images of $\\mathrm{Mo}_{2}\\mathrm{C@NPC}$ . These data verified that the $\\mathsf{M o}_{2}\\mathsf{C@N P C}$ material contained C, N, P and Mo elements, consistent with the EDX results (Supplementary Fig. 1b). Hence, these results sufficiently confirm that the presence of GO plays an important role in the generation of highly dispersed and nanosized $\\mathrm{\\overline{{Mo}}}_{2}\\mathrm{C}$ NPs. \n\nSupplementary Fig. 3 shows the powder X-ray diffraction patterns of $\\mathrm{Mo}_{2}\\mathrm{C}_{\\mathscr{Q}\\mathrm{NPC}}$ and $\\mathrm{Mo_{2}C@N P C/N P R G O}$ . The broad peak at $\\sim25^{\\circ}$ was ascribed to carbon38,39. The other peaks located at 37.9, 43.7, 61.6 and $75.6^{\\circ}$ were indexed to the (111), (200), (220) and (311) planes of $\\mathtt{M o}_{2}\\mathrm{C}$ (JCPDS, No. 15-0457), respectively; these peaks were broad and exhibited low intensity because of the smaller crystallites of $\\mathrm{Mo}_{2}\\mathrm{C}$ or $\\mathrm{Mo}_{2}\\mathrm{C}$ coated with amorphous carbon21,40,41. Beside, the degrees of graphitization of the two catalysts were analyzed by Raman spectra (Supplementary Fig. 4). As is well-known, the ratio between the D $(\\dot{1},\\dot{3}50\\mathsf{c m}^{-1})$ and G band $(1,580\\mathsf{c m}^{-1})$ intensities $(I_{\\mathrm{D}}/I_{\\mathrm{G}})$ is an important criterion to judge the degree of the graphitization9,28. Compared to $\\begin{array}{r}{\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{NPC},}\\end{array}$ the $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ of $\\mathrm{\\DeltaMo_{2}C@N P C/N P R G C}$ is higher, implying that more defects formed on the RGO sheets, thus favoring the accessibility of more active sites and enhancing the electrocatalytic performance. The Brunauer–Emmett–Teller (BET) surface areas of $\\mathrm{Mo}_{2}\\mathrm{C}_{\\mathscr{Q}\\mathrm{NPC}}$ and $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRG}$ O calculated by the $\\Nu_{2}$ sorption isotherms were 55 and $190\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , respectively (Supplementary Fig. 5a). $\\mathrm{Mo}_{2}\\mathrm{C}_{\\mathscr{O}\\mathrm{NPC}}$ showed a microporous structure, with pore sizes mainly in the range from 1 to $2\\mathrm{nm}$ (Supplementary Fig. 5b), whereas the corresponding pore size distribution of $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGC}$ was mainly concentrated in the range from 1 to $10\\mathrm{nm}$ , which was characteristic of a microporous and mesoporous structure (Supplementary Fig. 5c). Overall, the large surface area and enriched porous structures efficiently facilitate electrolyte penetration and charge transfer9. \n\n$\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) analyses of $\\mathrm{Mo}_{2}C@\\mathrm{NPC/NF}$ RGO catalysts were carried out to elucidate their valence states and compositions. As observed, the XPS spectrum of $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGO}$ (Supplementary Fig. 6) indicated the presence of C, N, O, P and Mo in the catalyst. The deconvoluted C1s spectrum is shown in Fig. 3a, and the main peak at $284.6\\mathrm{eV}$ implies that the graphite carbon is the majority species22. The deconvolution of N1s energy level signals for $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO revealed the peaks at 398.6 and $401.3\\mathrm{eV}$ , which were assigned to pyridinic and graphitic N (Fig. 3b), respectively21,27. From Fig. 3c, it can be seen that the $\\mathrm{P}2p$ peaks at about 133.5, and $134.8\\mathrm{eV}$ were attributed to P–C and P–O bonding, respectively18,28. Besides, the high-resolution Mo $3d$ XPS revealed that the peak at $228.8\\mathrm{eV}$ was attributable to $\\mathrm{Mo}^{2+}$ , stemming from $\\mathtt{M o}_{2}\\mathrm{C}$ . In parallel, as a consequence of surface oxidation, the peaks at 232.05 and 235.2 were attributable to $\\mathrm{MoO}_{3}$ and that at $232.7\\mathrm{eV}$ was assignable to $\\mathrm{MoO}_{2}$ (refs 8,21); both of these species are inactive toward the HER (Fig. 3d). For comparison, $\\mathrm{Mo}_{2}\\mathrm{C@NPC}$ is shown in Supplementary Fig. 7. All of these data were similar to those for $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{NPC}$ /NPRGO. The corresponding atomic percentages of the different catalysts measured by XPS are listed in Supplementary Table 1. \n\nElectrocatalytic HER performance. A three-electrode system was adopted to evaluate the electrocatalytic activities of $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO toward the HER in $0.5\\mathrm{M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ at $100\\mathrm{mVs}^{-1}$ . For comparison, $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{NPC}$ and commercial $\\mathrm{Pt-C}$ $20\\mathrm{wt\\%}$ Pt on carbon black from Johnson Matthey) were also assessed. The corresponding polarization curves without IR compensation are shown in Fig. 4a. All potentials in this work are reported vs RHE. As expected, the commercial $\\mathrm{Pt-C}$ displayed the highest electrocatalytic activity, with an onset overpotential of nearly zero30. The $\\mathrm{Mo}_{2}\\mathrm{C@NPC}$ catalyst exhibited far inferior HER activity. Impressively, $\\mathbf{Mo}_{2}\\mathbf{C}\\boldsymbol{@}$ NPC/NPRGO exhibited the lowest onset overpotential of $0\\mathrm{mV}$ , approaching the performance of commercial Pt–C. Moreover, it was clearly observed that the cathodic current rose sharply with more negative potentials. Generally, the potential value for a current density of $10\\mathrm{mA}\\mathrm{cim}^{-2}$ is an important reference because solar-lightcoupled HER apparatuses usually operate at 10–20 mA cm \u0002 2 under standard conditions (1 sun, AM 1.5)4. To achieve this current density, $\\mathrm{Mo}_{2}\\mathrm{C}\\ @\\mathrm{NPC}$ requires an overpotential of $260\\mathrm{mV}$ . Strikingly, $\\mathrm{Mo_{2}C@N P C/N P R G O}$ required only $\\sim34\\mathrm{mV}$ to achieve a $10\\mathrm{mA}\\mathrm{cm}^{-2}$ current density, even superior to commercial $\\mathrm{Pt-C}$ $(40\\mathrm{mV})$ (Table 1). To the best of our knowledge, this overpotential is superior to those of all previously reported non-noble-metal electrocatalysts for the HER, such as $\\mathrm{MoS}_{2}/\\mathrm{CoSe}_{2}$ (ref. 15), $\\mathrm{MoO}_{2}$ (ref. 18), $\\dot{\\mathrm{Mo}}_{2}\\mathrm{C}/\\mathrm{CNT}^{24}$ and $\\mathrm{CoNi@NC^{40}}$ (Supplementary Table 2). \n\n![](images/8c92aba835b2bb789a84587cffdcc1de1f1b6729f3909221dbd2d5fd1c5a2f3b.jpg) \nFigure 3 | Compositional characterization of the $M O_{2}\\C(O)$ NPC/NPRGO. $\\mathsf{X P S}$ high-resolution scans of (a) C 1s, (b) N 1s, (c) $\\textsf{P}2p$ and $(\\blacktriangleleft)$ Mo 3d electrons of $M O_{2}\\mathsf{C}_{\\mathcal{Q}}$ NPC/NPRGO. \n\n![](images/88a6aba2921abe7fea543a7f372710e143096fc6522a57a5da8d00cce5514748.jpg) \nFigure 4 | HER activity characterization. (a,b) Polarization curves and Tafe plots of ${\\cal M}\\circ_{2}{\\mathsf{C}}_{\\ @{\\mathsf{N P C}}},$ , $M O_{2}C@$ NPC/NPRGO and Pt–C. (inset: the production of ${\\sf H}_{2}$ bubbles on the surface of $\\mathsf{M o}_{2}\\mathsf{C}_{@\\mathsf{N P C/N P R G O}})$ (c) CVs of $M O_{2}C@N P C/N P R G O$ with different rates from 20 to $200\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . Inset: The capacitive current at $0.32\\mathrm{V}$ as a function of scan rate for $\\mathsf{M o}_{2}\\mathsf{C@N P C/N P R G O.}$ (d) Polarization curves of $\\mathsf{M o}_{2}\\mathsf{C}\\ @\\mathsf{N P C}/\\mathsf{N P R}$ GO initially and after 1,000 CV cycles. Inset: Time-dependent current density curve of ${\\cal M}\\circ_{2}{\\cal C}(\\varpi)$ NPC/NPRGO under a static overpotential of $48\\mathsf{m V}$ for $10\\mathsf{h}$ . \n\n
Table 1 | Comparison of catalytic parameters of different HER catalysts.
CatalystOnset potential (mV vs RHE) Overpotential at 10 mA cm -2 (mV vs RHE) jo (mA cm-2) Tafel slope (mV dec-1)
MoC@NPC1372603.16 ×10-3126.4
MoC@NPC/NPRGO0341.0933.6
Pt-C0400.3930
HER,Hevolutionreaction; Pt-C,2Owt%PtoncarbonlackfromJohnson-Matthey; RHE,reversiblehydrogenelectrode. jo represents exchange current density that was calculated from Tafel curves using extrapolation method.
\n\nTo elucidate the HER mechanism, Tafel Plots were fitted to Tafel equation (that is, $\\eta=b\\log\\left(j\\right)+a,$ where $b$ is the Tafel slope, and $j$ is the current density), as shown Fig. 4b. The Tafel slope of commercial $\\mathrm{Pt-C}$ was ${\\sim}\\dot{3}0\\mathrm{mV}\\mathrm{dec}^{-1}$ , which was in agreement with the reported value, thus supporting the validity of our electrochemical measurements30. The Tafel slope of $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO was $33.6\\mathrm{mV}\\mathrm{dec}^{-1}$ , which indicated higher performance than that of $\\mathrm{Mo}_{2}\\mathrm{C}_{\\mathscr{Q}\\mathrm{NPC}}$ $\\mathrm{^{'}126.4m V d e c^{-1}}$ ). Meanwhile, the Tafel slope of $\\mathrm{Mo}_{2}\\mathrm{C@NPC/N}$ PRGO suggested that hydrogen evolution on the $\\mathrm{Mo}_{2}C@\\mathrm{NPC/NI}$ PRGO electrode probably proceeds via a Volmer–Tafel mechanism, where the recombination is the ratelimiting step17. The exchange current density $(j_{0})$ was extrapolated from the Tafel plots. Notably, $\\mathrm{Mo_{2}C@N P C/N P R G O}$ displayed the largest $j_{0}$ of $1\\dot{.}9\\times10^{-3}\\mathrm{Acm}^{-2}$ , which was nearly three times larger than the $j_{0}$ of $\\mathrm{Pt-C}$ $(0.39\\times10^{-3}\\mathrm{Acm}^{-2})$ (Table 1) and was substantially greater than those of other recently reported nonnoble-metal catalysts (Supplementary Table 2). This performance of $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGO}$ demonstrates favourable HER kinetics at the $\\mathrm{Mo_{2}C@N P C/N P R G O/}$ electrolyte interface. \n\nThe electrochemical double-layer capacitance (EDLC, $C_{\\mathrm{dll}})$ was measured to investigate the electrochemically active surface area. Cyclic voltammetry (CV) was performed in the region from 0.27 to $0.37\\mathrm{V}$ at rates varying from 20 to $200\\mathrm{mVs^{-\\breve{1}}}$ (Fig. 4c and Supplementary Fig. 8). The $C_{\\mathrm{dll}}$ of $\\mathrm{Mo_{2}C@N P C/N P R G O}$ $(1\\dot{7}.\\dot{9}\\mathrm{mFcm}^{-2})$ was $\\sim195$ times larger than that of $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{NPC}$ $(0.092\\mathrm{mF}\\mathrm{cm}^{-2},$ ). Thus, the large $j_{0}$ value of $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO may benefit from both its large BET surface area and its large EDLC. \n\nTo gain further insight into the electrocatalytic activity of $\\mathrm{Mo_{2}C@N P C/N P R G O}$ for the HER, we performed electrochemical impedance spectroscopy (EIS). The Nyquist plots of the EIS responses are shown in Supplementary Fig. 9. Compared with the Nyquist plot of $\\begin{array}{r}{\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{NPC},}\\end{array}$ that of $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO showed a much smaller semicircle, suggesting that $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGO}$ has lower impedance. This result proves that the catalyst affords markedly faster HER kinetics due to the presence of the RGO support. \n\nLong-term stability is also critical for HER catalysts. To probe the durability of the $\\mathrm{Mo_{2}C@N P C/N P R G O}$ catalyst, continuous CV was performed between $-0.2$ and $0.2\\mathrm{V}$ at a $100\\mathrm{mVs}^{-1}$ scan rate in $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution (Fig. 4d). As observed, the polarization curve for $\\mathrm{Mo}_{2}C@\\mathrm{NPC/NPRC}$ O remained almost the same after 1,000 cycles. In addition, the durability of $\\mathrm{Mo}_{2}C@\\mathrm{NPC/NPRG}$ O was also examined by electrolysis at a static overpotential of $48\\mathrm{mV}$ . The inset of Fig. 4d shows that the current density experienced a negligible loss at B20 mA cm \u0002 2 for $\\mathrm{10h}$ . For comparison, the durability of the $\\mathrm{Mo}_{2}\\mathrm{C}\\ @\\mathrm{NPC}$ catalyst was examined by the same methods (Supplementary Fig. 10). This is reconfirming that $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{NPC}$ and $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO are stable electrocatalysts in acidic solutions. \n\nIn control experiments, we investigated the effect of the $\\mathrm{PMo}_{12}$ content on electrocatalytic performance. Two other catalysts with different $\\mathrm{PMo}_{12}$ contents (1.1 and $3.3\\mathrm{g})$ were synthesized (denoted as $\\mathrm{Mo_{2}C@N P C/N P R G O–1.1}$ and $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO-3.3). The morphology, structure and composition of these two catalysts were studied by SEM, TEM, HRTEM, STEM, EDX, elemental mapping, powder X-ray diffraction patterns and XPS in detail (Supplementary Figs 11–16). The HER activities of $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGO-1.1}$ and -3.3 were also evaluated using the same measurements. As seen from Fig. $^{5\\mathrm{a,b}}$ , $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO showed the lowest onset overpotential and the smallest Tafel slope among the three samples. We speculate that these results are likely related to the amount and distribution of active sites. Because of the lower amount of $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs in $\\mathrm{Mo}_{2}\\mathrm{C@NPC}/$ NPRGO-1.1, the corresponding electrocatalytic activity was poorer than that of $\\mathrm{Mo_{2}C@N P C/N P R G O}$ . In contrast, a larger number of $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs in $\\mathrm{Mo_{2}C@N P C/N P R G O-3.3}$ aggregated together, which is also unfavourable for the HER. These results demonstrate that the amount of $\\mathrm{PMo}_{12}$ substantially influences the HER performance. \n\nWe subsequently studied the influence of carbonization temperature under the given conditions. Supplementary Figs 17–22 show the morphology, structure and composition of the two samples carbonized at 700 and $1,100^{\\circ}\\mathrm{C}$ (defined as $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO-}700$ and $\\mathrm{Mo_{2}C@N P C/N P R G O-1100})$ , respectively. The onset overpotentials of $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO-}700$ and $\\mathrm{Mo_{2}C@N P C/N P R G O-1100}$ were 20 and $27\\mathrm{mV}$ , respectively, and the Tafel slopes were 48.4 and $70.1\\:\\mathrm{mV}\\:\\mathrm{dec}^{-1}$ , respectively (Fig. 5c and d). Among these catalysts, the $\\mathrm{Mo}_{2}\\mathrm{C@NPC/1}$ NPRGO catalyst exhibited the optimal HER activity, possibly because active sites of $\\mathrm{Mo}_{2}\\mathrm{C}$ were not produced when $\\bar{\\mathrm{PMo}}_{12}\\mathrm{-PPy/RGO}$ is carbonized at $700^{\\circ}\\mathrm{C}$ ; the high–carbonization temperature led to substantial sintering and aggregation of $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs, which further reduced the density of highly active sites. Meanwhile, the N content decreased with increasing carbonization temperature (Supplementary Table 1). All of these results were consistent with the SEM, TEM, XRD, thermogravimetric analysis and XPS results (Supplementary Figs 17–22). Therefore, in this work, the selection of the correct $\\mathrm{PMo}_{12}$ content and carbonization temperature was critical to forming high-HER active sites. \n\nTheoretical investigation. The aforementioned experimental results demonstrated that the $\\mathbf{Mo}_{2}\\mathbf{C}\\mathbf{\\mathcal{Q}}$ NPC/NPRGO composite exhibits excellent electrocatalytic activity toward the HER because of the synergistic effects of $\\mathtt{M o}_{2}\\mathrm{C}$ and NPC/NPRGO. To elucidate the mechanism underlying the superior HER activity of the $\\mathrm{Mo}_{2}\\mathrm{C@NPC}_{I}$ NPRGO composite, we performed a series of DFT calculations (Supplementary Fig. 23 and Supplementary Table 3). Theoretically, the HER pathway can be depicted as a three-state diagram containing an initial state of $\\mathrm{H}^{+}+e^{-}$ , an intermediate state of adsorbed $\\mathrm{H}$ ( $\\mathrm{^{H^{*}}}$ , where \\* denotes an adsorption site), and a final state of 1/2 the $\\mathrm{H}_{2}$ product5,22. Generally, a good hydrogen evolution catalyst should have a free energy of adsorbed H of approximately zero $(\\Delta G_{\\mathrm{H^{*}}}\\approx0)$ , which can provide a fast proton/electron-transfer step as well as a fast hydrogen release process42. Because only trace amounts of $\\mathrm{\\DeltaP}$ were present in the $\\mathbf{Mo}_{2}\\mathbf{C}\\boldsymbol{@}$ NPC/NPRGO hybrid compared to the $\\mathrm{~N~}$ content, we investigated only the effect of $\\mathrm{~N~}$ doping (graphitic $\\mathrm{~N~}$ and pyridinic N) on the catalytic effect of the hybrids. Figure 6 shows the calculated free energy diagram for the HER in various studied systems. \n\n![](images/6b2e8f486b19e56a2a84c2a2d44e4231ec3bebec86bf0f56d6828c6d2a4f52f4.jpg) \nFigure 5 | Comparison of the HER performance of different electrocatalysts. (a,b) Polarization curves and Tafe plots of ${\\mathsf{M o}}_{2}{\\mathsf{C}}_{\\ @{\\mathsf{N P C}}}$ /NPRGO with different mass of $\\mathsf{P M o}_{12}$ (1.1, 2.2 and $_{3.3\\mathrm{g}}\\mathrm{,}$ ). (c,d) Polarization curves and Tafe plots of Mo2C@NPC/NPRGO $(2.2\\ g)$ at different carbonization temperature. \n\nAccording to our computational results, pristine graphene had an endothermic $\\Delta G_{\\mathrm{H^{*}}}$ of $1.82\\mathrm{eV}$ , implying an energetically unfavourable interaction with hydrogen. Therefore, the HER can barely proceed on pristine graphene because of the slow proton/ electron transfer. On the other hand, the (001) surface of $\\mathrm{Mo}_{2}\\mathrm{C}$ had a strong interaction with $\\mathrm{H},$ , as indicated by the exothermic $\\Delta G_{\\mathrm{H^{*}}}$ of $-\\dot{0}.82\\mathrm{eV}$ , which would subsequently lead to poor HER performance because of the foreseeable difficulty of hydrogen release. Moreover, N-doped graphene exhibited low catalytic activity toward the HER. Specifically, the $\\Delta G_{\\mathrm{H^{*}}}$ values for graphitic-N- and pyridinic-N-doped graphene were 0.89 and $-2.04\\mathrm{eV}$ , respectively. \n\nHowever, the catalytic activity of graphene and N-doped graphene were substantially improved when they were anchored to the surface of $\\mathrm{Mo}_{2}\\mathrm{C}$ . For example, the $\\Delta G_{\\mathrm{H^{*}}}$ values for $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{C}$ and $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{C}$ -graphitic $\\bar{\\bf N}$ were 0.41 and $0.69\\mathrm{eV}$ , respectively, which were much lower than those of suspended graphene $(1.82\\mathrm{eV})$ and N-doped graphene $(0.89\\mathrm{eV})$ . The $\\Delta G_{\\mathrm{H^{*}}}$ of $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{C}$ (0.41 eV) indicated that the graphene C atoms in the hybrid also play an important role in the HER activity. In particular, due to the synergistic effect between $\\mathsf{M o}_{2}\\mathrm{C}$ and C-pyridinic $\\mathrm{\\DeltaN}$ , $\\mathbf{Mo}_{2}\\mathbf{C}@\\mathbf{C}$ -pyridinic $\\mathrm{\\DeltaN}$ had a favourable $\\Delta G_{\\mathrm{H^{*}}}$ $(-0.22\\mathrm{eV})$ for the adsorption and desorption of hydrogen. Therefore, the active sites for the HER should be composed mainly of pyridinic $\\mathrm{\\DeltaN}$ atoms and C atoms of graphene rather than graphitic N atoms. We note here that, according to the results of XPS analysis, the major type of N in $\\mathrm{Mo_{2}C@N P C/N P R G O}$ was pyridinic $\\mathrm{\\DeltaN},$ which means that $\\mathrm{Mo}_{2}\\mathrm{C}@\\mathrm{NPC}_{I}$ NPRGO would manifest a high density of active sites and would consequently present a high-current density at a low overpotential for the HER. Overall, the experimental and theoretical results verified that as-synthesized $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGO}$ is an unexpected and highly efficient HER electrocatalyst. \n\n![](images/9001b2f7c6bd4eed6efda99727bb5ad79b19351d184e6cdaea7546b8d02276e0.jpg) \nFigure 6 | DFT-calculated HER activities. Calculated free energy diagram for HER on various studied system. \n\n# Discussion \n\nIn view of the aforementioned considerations, the amazing HER activities of the $\\mathrm{Mo_{2}C@N P C/N P R G O}$ are postulated to originate from the following reasons: (1) the small size of $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs favors the exposure of an abundance of available active sites, which may enhance the catalytic activity for the HER7,21,28; (2) the introduction of heteroatoms (N, P) into the carbon structure results in charge density distribution and asymmetry spin, thus enhancing the interaction with $\\mathrm{H^{+}}$ (refs 18,27). Especially, pyridinic $\\mathrm{\\DeltaN}$ is favourable for highly efficient catalytic performance43,44; (3) as an advanced support, RGO can increase the dispersion of $\\mathrm{PMo}_{12}$ to further obtain highly dispersed $\\mathrm{Mo}_{2}\\mathrm{C}$ during the carbonization process. Meanwhile, the outstanding electrical conductivity of RGO facilitates charge transfer in the catalyst11,25; (4) the robust conjugation between $\\mathrm{Mo}_{2}\\mathrm{C}$ and NPC/ NPRGO provides a resistance-less path favourable for fast electron transfer. The carbon shells may hamper the aggregation of $\\mathrm{Mo}_{2}\\mathrm{C}~\\mathrm{NPs}^{21}$ and promote electron penetration from $\\mathrm{\\bar{Mo}}_{2}\\mathrm{C}$ to $\\mathrm{RGO}^{22}$ . Furthermore, the geometric confinement of $\\mathtt{M o}_{2}\\mathrm{C}$ inside the carbon shells can also enhance the catalytic activity for the $\\mathrm{HER^{40}}$ and (5) the unique structure of $\\mathrm{Mo_{2}C_{\\mathcal{Q}}N P C/N P R G O}$ is favourable for the fast mass transport of reactants and facilitates electron transfer26,39. Because of the synergistic catalytic effects of the aforementioned factors, the $\\mathrm{Mo_{2}C@N P C/N P R G O}$ catalyst exhibits potent HER activity. \n\nIn summary, we designed and developed a novel architecture that is composed of $\\mathrm{Mo}_{2}\\mathrm{\\bar{C}}$ NPs, NPC and NPRGO by simply carbonizing a ternary $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ nanocomposite. The effect of the $\\mathrm{PMo}_{12}$ content and carbonization temperature on the HER activity was investigated in detail. The RGO-supported Mo-based catalysts prepared with $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ as the precursor may efficiently hinder Mo sources and graphene from aggregating during the formation of RGO-supported $\\mathrm{Mo}_{2}\\mathrm{C}$ NPs. The obtained $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRG(}$ nanocomposite exhibits the best HER performance and high stability as an electrocatalyst in an acidic electrolyte reported to date. Theoretical studies demonstrated that the synergistic effect between $\\mathrm{Mo}_{2}\\mathrm{C}$ and C-pyridinic N contributes to the excellent HER activity of the $\\mathrm{Mo}_{2}C@\\mathrm{NPC/NPRG}$ O nanocomposite, in accordance with the experimental results. This proof-of-concept study not only offers novel hydrogen-evolving electrocatalysts with excellent activity but also opens new avenues for the development of other 2D coupled nanohybrids with transition-metal carbides and RGO using POMs/conducting polymer/RGO as a precursor. These catalysts can also be explored as highly efficient electrocatalysts for oxygen reduction reaction (ORR), HER and lithium batteries. \n\n# Methods \n\nSynthesis of $\\scriptstyle\\mathsf{P M o}_{12}-\\mathsf{P P y}/\\mathsf{R G O}$ and $M O_{2}C(O N P C$ /NPRGO hybrids. In a typical synthesis, GO NSs were pre-synthesized by chemical oxidation exfoliation of natural graphite flakes using a modified Hummers method45. The obtained GO NSs were dispersed in de-ionized water by ultrasonication to form a suspension with the concentration of $1\\mathrm{mg}\\mathrm{ml}^{-1}$ . Around $12.5\\mathrm{ml}$ of such GO suspension and $150\\mathrm{ml}$ of $2\\mathrm{mM}$ $\\mathrm{PMo}_{12}$ solution were added into a clean three-necked flask, respectively, and mixed uniformly under a strong ultrasonication bath. Subsequently, Py monomer solution by dispersing $230\\upmu\\mathrm{l}$ of Py in $15\\mathrm{ml}$ de-ionized water, was slowly dropped into the above mixed $\\mathrm{PMo}_{12}/\\mathrm{GO}$ suspension. With the addition of $\\mathrm{Py}$ monomer solution, the reaction system gradually turned from yellow-brown to deep blue and a black precipitate began to generate after about $5\\mathrm{{min}}$ . Finally, the reactor was transferred to an oil bath and allowed to react for $30\\mathrm{h}$ at $50^{\\circ}\\mathrm{C}$ under vigorously magnetic stirring. After separated by centrifugation and washed with deionized water and anhydrous ethanol for several times, the black $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ ternary nanohybrids were obtained, which were dried in vacuum at $50^{\\circ}\\mathrm{C}$ In control experiments, $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ (1.1) and $\\mathrm{PMo}_{12}$ –PPy/ RGO (3.3) were synthesized by identical condition except that the amount of $\\mathrm{PMo}_{12}$ is 1.1 and $3.3\\:\\mathrm{g},$ respectively. \n\nTo prepare the $\\mathrm{Mo}_{2}\\mathrm{C@NPC/NPRGC}$ nanocomposite, $2\\mathrm{g}$ of $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ was carbonized in a flow of ultrapure $\\Nu_{2}$ at $900^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ with the heating rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ . The obtained samples were acid etched in $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ (0.5 M) for $24\\mathrm{h}$ with continuous agitation at $80~^{\\circ}\\mathrm{C}$ to remove unstable and inactive species. The etched samples were then thoroughly washed with de-ionized water until reaching a neutral $\\mathrm{\\boldmath~\\pH,}$ and defined as Mo2C@NPC/NPRGO, $\\mathbf{Mo}_{2}\\mathbf{C}\\boldsymbol{@}$ NPC/NPRGO-1.1 and -3.3, respectively. \n\nSynthesis of $\\mathsf{P M o}_{12}\\mathrm{-PPy}$ and $M O_{2}C(\\Delta)N P C$ composites. The synthetic procedure is very similar to $\\mathrm{PMo}_{12}\\mathrm{-PPy/RGO}$ without GO. Likewise, the preparation of $\\mathrm{Mo}_{2}\\mathrm{C}\\ @\\mathrm{NPC}$ composite is identical with that of $\\mathbf{Mo}_{2}\\mathbf{C}\\boldsymbol{@}$ NPC/NPRGO. \n\nCharacterization. The TEM and HRTEM images were recorded on JEOL-2100F apparatus at an accelerating voltage of $200\\mathrm{kV}$ Surface morphologies of the carbon materials were examined by a SEM (JSM-7600F) at an acceleration voltage of $10\\mathrm{kV}$ . The EDX was taken on JSM-5160LV-Vantage-typed energy spectrometer. The XRD patterns were recorded on a $\\mathrm{D}/\\mathrm{max}~2500\\mathrm{VL}/\\mathrm{PC}$ diffractometer (Japan) equipped with graphite monochromatized $\\mathrm{Cu}\\ \\mathrm{K}\\mathfrak{a}$ radiation $\\left(\\lambda=1.54060\\mathrm{\\AA}\\right.$ ). Corresponding work voltage and current is $40\\mathrm{kV}$ and $100\\mathrm{mA}$ , respectively. XPS was recorded by a scanning X-ray microprobe (PHI 5000 Verasa, ULAC-PHI, Inc.) using Al $\\operatorname{K}\\upalpha$ radiation and the C1s peak at $284.8\\mathrm{eV}$ as internal standard. The Raman spectra of dried samples were obtained on Lab-RAM HR800 with excitation by an argon ion laser $(514.5\\mathrm{nm})$ ). The nitrogen adsorption–desorption experiments were operated at $77\\mathrm{K}$ on a Micromeritics ASAP 2050 system. BET surface areas were determined over a relative pressure range of 0.05–0.3, during which the BET plot is linear. The pore size distributions were measured by using the nonlocalized density functional theory method. Before the measurement, the samples were degassed at $150^{\\circ}\\mathrm{C}$ for $^{10\\mathrm{h}}$ . \n\nElectrochemical measurements. All electrochemical experiments were conducted on a CHI 760D electrochemical station (Shanghai Chenhua Co., China) in a standard three electrode cell in 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at room temperature. A glassy carbon electrode $3\\mathrm{mm}$ in diameter), an $\\mathrm{Ag/AgCl}$ with saturated KCl, and a Pt wire were used as the working electrode, reference and counter electrode, respectively. A total of $4\\mathrm{mg}$ of the catalysts were dispersed in $2\\mathrm{ml}$ of $9{:}1\\ \\mathrm{v/v}$ water/Nafion by sonication to form a homogeneous ink. Typically, ${5\\upmu\\mathrm{l}}$ well-dispersed catalysts were covered on the glassy carbon electrode and then dried in an ambient environment for measurements. The electrocatalyst was prepared with a catalyst loading of $0.14\\mathrm{mg}\\mathrm{cm}^{-2}$ . Commercial $20\\%$ Pt–C catalyst was also used as a reference sample. Linear sweep voltammetry was tested with a scan rate of $5\\mathrm{mVs}^{-1}$ . EIS measurements were carried out from $1{,}000\\mathrm{kHz}$ to $100\\mathrm{mHz}$ with an amplitude of $10\\mathrm{mV}$ at the open-circuit voltage. The electrochemical stability of the catalyst was conducted by cycling the potential between $-0.3$ and $0.3\\mathrm{V}$ vs RHE at a scan rate of $100\\mathrm{mVs}^{2}$ . The Chronoamperometry were tested at an overpotential of $-0.12\\mathrm{V}$ vs RHE after equilibrium. To estimate the electrochemical active surface areas of the catalysts, CV was tested by measuring EDLC under the potential window of 0.19–0.39 vs RHE with various scan rate (20, 40, 60, 80, 100, 120, 140, 160, 180 and $200\\mathrm{mVs^{-1}}_{.}$ ). A flow of $\\Nu_{2}$ was maintained over the electrolyte during the experiment to eliminate dissolved oxygen. The potential vs RHE was converted to RHE via the Nernst equation: $E_{\\mathrm{RHE}}{=}\\breve{E}_{\\mathrm{Ag/AgCl}}{+}0.059\\mathrm{pH}+E_{\\mathrm{~Ag/AgCl}}^{\\uptheta}$ . I $\\mathrm{~n~}0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4},E_{\\mathrm{RHE}}{=}0.21\\mathrm{V}+E_{\\mathrm{Ag/AgCl}}$ . \n\nComputational details. DFT calculations were performed using the plane-wave technique implemented in the Vienna $a b$ initio Simulation package46. The ion–electron interaction was treated within the projector-augmented plane wave pseudopotentials47,48. The generalized gradient approximation expressed by Perdew \u0002 Burke \u0002 Ernzerhof functional49 and a plane-wave cutoff energy of $360\\mathrm{eV}$ were used in all computations. The electronic structure calculations were employed with a Fermi-level smearing of $0.1\\mathrm{eV}$ for all surface calculations and $0.01\\mathrm{eV}$ for all gas-phase species. The Brillouin zone was sampled with $3\\times3\\times1$ $k$ -points. The convergence of energy and forces were set to $1\\times10^{-5}\\mathrm{eV}$ and $\\dot{0}.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ , respectively. A vacuum region of around $12\\mathrm{\\AA}$ was set along the $z$ direction to avoid the interaction between periodic images. More computational details are provided in Supplementary Note 1. \n\n# References \n\n1. Turner, J. A. Sustainable hydrogen production. Science 305, 972–974 (2004). \n2. Wang, J. et al. Recent progress in cobalt-based heterogeneous catalysts for electrochemical water splitting. Adv. Mater. 28, 215–230 (2016). \n3. Stamenkovic, V. R. et al. Trends in electrocatalysis on extended and nanoscale Pt-bimetallic alloy surfaces. Nat. Mater. 6, 241–247 (2007). \n4. Walter, M. G. et al. Solar water splitting cells. Chem. Rev. 110, 6446–6473 (2010). \n5. Zheng, Y. et al. Hydrogen evolution by a metal-free electrocatalyst. Nat. Commun. 5, 3783 (2014). \n6. Levy, R. B. & Boudart, M. Platinum-like behavior of tungsten carbide in surface catalysis. Science 181, 547–549 (1973). \n7. Wu, H. B., Xia, B. Y., Yu, L., Yu, X. Y. & Lou, X. W. Porous molybdenum carbide nano-octahedrons synthesized via confined carburization in metalorganic frameworks for efficient hydrogen production. Nat. Commun. 6, 6512 (2015). \n8. Zhao, Y., Kamiya, K., Hashimoto, K. & Nakanishi, S. In situ $\\mathrm{CO}_{2}$ -emission assisted synthesis of molybdenum carbonitride nanomaterial as hydrogen evolution electrocatalyst. J. Am. Chem. Soc. 137, 110–113 (2015). \n9. Ma, F. X., Wu, H. B., Xia, B. Y., Xu, C.Y. & Lou, X. W. Hierarchical ${\\upbeta}{\\mathrm{-}}{\\mathrm{M}}{\\mathbf{o}}_{2}{\\mathrm{C}}$ nanotubes organized by ultrathin nanosheets as a highly efficient electrocatalyst for hydrogen production. Angew. Chem. Int. Ed. 54, 15395–15399 (2015). \n10. Liao, L. et al. A nanoporous molybdenum carbide nanowire as an electrocatalyst for hydrogen evolution reaction. Energy Environ. Sci. 7, 387–392 (2014). based on molybdenum compounds on carbon nanotube–graphene hybrid support. ACS Nano 8, 5164–5173 (2014). \n12. Chen, W. F. et al. Biomass-derived electrocatalytic composites for hydrogen evolution. Energy Environ. Sci. 6, 1818–1826 (2013). \n13. Ma, L., Ting, L. R. L., Molinari, V., Giordano, C. & Yeo, B. S. Efficient hydrogen evolution reaction catalyzed by molybdenum carbide and molybdenum nitride nanocatalysts synthesized via the urea glass route. J. Mater. Chem. A 3, 8361–8368 (2015). \n14. Wang, H. et al. Transition-metal doped edge sites in vertically aligned $\\mathbf{MoS}_{2}$ catalysts for enhanced hydrogen evolution. Nano Res. 8, 566–575 (2015). \n15. Gao, M. R. et al. An efficient molybdenum disulfide/cobalt diselenide hybrid catalyst for electrochemical hydrogen generation. Nat. Commun. 6, 5982 (2015). \n16. Merki, D. & Hu, X. Recent developments of molybdenum and tungsten sulfides as hydrogen evolution catalysts. Energy Environ. Sci. 4, 3878–3888 (2011). \n17. Jaramillo, T. F. et al. Identification of active edge sites for electrochemical $\\mathrm{H}_{2}$ evolution from $\\ensuremath{\\mathrm{MoS}}_{2}$ nanocatalysts. Science 317, 100–102 (2007). \n18. Tang, Y. J. et al. Porous molybdenum-based hybrid catalysts for highly efficient hydrogen evolution. Angew. Chem. Int. Ed. 54, 12928–12932 (2015). \n19. Vrubel, H. & Hu, X. Molybdenum boride and carbide catalyze hydrogen evolution in both acidic and basic solutions. Angew. Chem. Int. Ed. 51, 12703–12706 (2012). \n20. Faber, M. S. & Jin, S. Earth-abundant inorganic electrocatalysts and their nanostructures for energy conversion applications. Energy Environ. Sci. 7, 3519–3542 (2014). \n21. Ma, R. et al. Ultrafine molybdenum carbide nanoparticles composited with carbon as a highly active hydrogen-evolution electrocatalyst. Angew. Chem. Int. Ed. 54, 14723–14727 (2015). \n22. Liu, Y. et al. Coupling $\\mathrm{Mo}_{2}\\mathrm{C}$ with nitrogen-rich nanocarbon leads to efficient hydrogen-evolution electrocatalytic sites. Angew. Chem. Int. Ed. 54, 10752–10757 (2015). \n23. Cui, W. et al. $\\mathsf{M o}_{2}\\mathrm{C}$ nanoparticles decorated graphitic carbon sheets: biopolymer-derived solid-state synthesis and application as an efficient electrocatalyst for hydrogen generation. ACS Catal. 4, 2658–2661 (2014). \n24. Chen, W. F. et al. Highly active and durable nanostructured molybdenum carbide electrocatalysts for hydrogen production. Energy Environ. Sci. 6, 943–951 (2013). \n25. Seol, M. et al. Mo-compound/CNT-graphene composites as efficient catalytic electrodes for quantum-dot-sensitized solar cells. Adv. Energy Mater. 4, 1300775 (2014). \n26. Duan, J., Chen, S., Chambers, B. A., Andersson, G. G. & Qiao, S. Z. 3D $\\mathrm{WS}_{2}$ nanolayers@heteroatom-doped graphene films as hydrogen evolution catalyst electrodes. Adv. Mater. 27, 4234–4241 (2015). \n27. Duan, J., Chen, S., Jaroniec, M. & Qiao, S. Z. Porous $\\mathrm{C}_{3}\\mathrm{N}_{4}$ nanolayers@Ngraphene films as catalyst electrodes for highly efficient hydrogen evolution. ACS Nano 9, 931–940 (2015). \n28. Yan, H. et al. Phosphorus-modified tungsten nitride/reduced graphene oxide as a high-performance, non-noble-metal electrocatalyst for the hydrogen evolution reaction. Angew. Chem. Int. Ed. 54, 6325–6329 (2015). \n29. He, C. & Tao, J. Synthesis of nanostructured clean surface molybdenum carbides on graphene sheets as efficient and stable hydrogen evolution reaction catalysts. Chem. Commun. 51, 8323–8325 (2015). \n30. Li, Y. et al. $\\ensuremath{\\mathbf{MoS}}_{2}$ nanoparticles grown on graphene: an advanced catalyst for the hydrogen evolution reaction. J. Am. Chem. Soc. 133, 7296–7299 (2011). \n31. Kamat, P. V. Graphene-based nanoarchitectures. anchoring semiconductor and metal nanoparticles on a two-dimensional carbon support. J. Phys. Chem. Lett. 1, 520–527 (2009). \n32. Huang, C., Li, C. & Shi, G. Graphene based catalysts. Energy Environ. Sci. 5, 8848–8868 (2012). \n33. Du, D. Y., Qin, J. S., Li, S. L., Su, Z. M. & Lan, Y. Q. Recent advances in porous polyoxometalate-based metal-organic framework materials. Chem. Soc. Rev. 43, 4615–4632 (2014). \n34. Cronin, L. & Mu¨ller, A. From serendipity to design of polyoxometalates at the nanoscale, aesthetic beauty and applications. Chem. Soc. Rev. 41, 7333–7334 (2012). \n35. Wang, T. et al. Electrochemically fabricated polypyrrole and $\\mathrm{MoS}_{x}$ copolymer films as a highly active hydrogen evolution electrocatalyst. Adv. Mater. 26, 3761–3766 (2014). \n36. Zhou, D. & Han, B. H. Graphene-based nanoporous materials assembled by mediation of polyoxometalate nanoparticles. Adv. Funct. Mater. 20, 2717–2722 (2010). \n37. Ma, R., Hao, W., Ma, X., Tian, Y. & Li, Y. Catalytic ethanolysis of kraft lignin into high-value small-molecular chemicals over a nanostructured $\\textsf{\\textsf{Q}}$ - molybdenum carbide catalyst. Angew. Chem. Int. Ed. 53, 7310–7315 (2014). \n38. Zhou, W. et al. N-doped carbon-wrapped cobalt nanoparticles on $N$ -doped graphene nanosheets for high-efficiency hydrogen production. Chem. Mater. 27, 2026–2032 (2015). \n39. Wu, R., Zhang, J., Shi, Y., Liu, D. & Zhang, B. Metallic $\\mathrm{WO}_{2}$ –carbon mesoporous nanowires as highly efficient electrocatalysts for hydrogen evolution reaction. J. Am. Chem. Soc. 137, 6983–6986 (2015). \n40. Deng, J., Ren, P., Deng, D. & Bao, X. Enhanced electron penetration through an ultrathin graphene layer for highly efficient catalysis of the hydrogen evolution reaction. Angew. Chem. Int. Ed. 54, 2100–2104 (2015). \n41. Zheng, W. et al. Experimental and theoretical investigation of molybdenum carbide and nitride as catalysts for ammonia decomposition. J. Am. Chem. Soc. 135, 3458–3464 (2013). \n42. Hinnemann, B. et al. Biomimetic hydrogen evolution: $\\ensuremath{\\mathbf{MoS}}_{2}$ nanoparticles as catalyst for hydrogen evolution. J. Am. Chem. Soc. 127, 5308–5309 (2005). \n43. Lai, L. et al. Exploration of the active center structure of nitrogen-doped graphene-based catalysts for oxygen reduction reaction. Energy Environ. Sci. 5, 7936–7942 (2012). \n44. Rao, C. V., Cabrera, C. R. & Ishikawa, Y. In search of the active site in nitrogendoped carbon nanotube electrodes for the oxygen reduction reaction. J. Phys. Chem. Lett. 1, 2622–2627 (2010). \n45. Lee, J. H. et al. Restacking-inhibited 3D reduced graphene oxide for high performance supercapacitor electrodes. ACS Nano 7, 9366–9374 (2013). \n46. Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993). \n47. Blo¨chl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n48. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n49. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n\n# Acknowledgements \n\nThis work was financially supported by the National Natural Science Foundation of China (No. 21371099, 21522305 and 21471080), the NSF of Jiangsu Province of China (No. BK20130043 and BK20141445), the Natural Science Foundation of Shandong Province (No. ZR2014BQ037), the Youths Science Foundation of Jining University (No. 2014QNKJ08), the Priority Academic Program Development of Jiangsu Higher Education Institutions and the Foundation of Jiangsu Collaborative Innovation Center of Biomedical Functional Materials. \n\n# Author contributions \n\nY.-Q.L. and J.-S.L. conceived the idea. J.-S.L., C.-H.L., Y.-G.W. and L.-Z.D. designed the experiments, collected and analysed the data. Y.-F.L. and Y.W. performed the DFT calculations. S.-L.L. and. Z.-H.D. assisted with the experiments and characterizations. J.-S.L. and Y.-Q.L. co-wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Li, J.-S. et al. Coupled Molybdenum Carbide and Reduced Graphene Oxide Electrocatalysts for Efficient Hydrogen Evolution. Nat. Commun. 7:11204 doi: 10.1038/ncomms11204 (2016). \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1073_pnas.1600422113", + "DOI": "10.1073/pnas.1600422113", + "DOI Link": "http://dx.doi.org/10.1073/pnas.1600422113", + "Relative Dir Path": "mds/10.1073_pnas.1600422113", + "Article Title": "Flexible, solid-state, ion-conducting membrane with 3D garnet nullofiber networks for lithium batteries", + "Authors": "Fu, K; Gong, YH; Dai, JQ; Gong, A; Han, XG; Yao, YG; Wang, CW; Wang, YB; Chen, YN; Yan, CY; Li, YJ; Wachsman, ED; Hu, LB", + "Source Title": "PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA", + "Abstract": "Beyond state-of-the-art lithium-ion battery (LIB) technology with metallic lithium anodes to replace conventional ion intercalation anode materials is highly desirable because of lithium's highest specific capacity (3,860 mA/g) and lowest negative electrochemical potential (similar to 3.040 V vs. the standard hydrogen electrode). In this work, we report for the first time, to our knowledge, a 3D lithium-ion-conducting ceramic network based on garnet-type Li6.4La3Zr2Al0.2O12 (LLZO) lithium-ion conductor to provide continuous Li+ transfer channels in a polyethylene oxide (PEO)-based composite. This composite structure further provides structural reinforcement to enhance the mechanical properties of the polymer matrix. The flexible solid-state electrolyte composite membrane exhibited an ionic conductivity of 2.5 x 10(-4) S/cm at room temperature. The membrane can effectively block dendrites in a symmetric Li vertical bar electrolyte vertical bar Li cell during repeated lithium stripping/plating at room temperature, with a current density of 0.2 mA/cm(2) for around 500 h and a current density of 0.5 mA/cm(2) for over 300 h. These results provide an all solid ion-conducting membrane that can be applied to flexible LIBs and other electrochemical energy storage systems, such as lithium-sulfur batteries.", + "Times Cited, WoS Core": 801, + "Times Cited, All Databases": 906, + "Publication Year": 2016, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000379033400047", + "Markdown": "# Flexible, solid-state, ion-conducting membrane with 3D garnet nanofiber networks for lithium batteries \n\nKun (Kelvin) $\\mathsf{F u}^{\\mathsf{a},\\mathsf{b},\\mathsf{1}}$ , Yunhui Gonga,1, Jiaqi Daib, Amy Gonga,b, Xiaogang Hana,b, Yonggang Yaob, Chengwei Wanga,b, Yibo Wangb, Yanan Chenb, Chaoyi Yanb, Yiju Lib, Eric D. Wachsmana,b,2, and Liangbing $\\mathsf{H u}^{\\mathsf{a},\\mathsf{b},2}$ \n\naUniversity of Maryland Energy Research Center, University of Maryland, College Park, MD 20742; and bDepartment of Materials Science and Engineering University of Maryland, College Park, MD 20742 \n\ndited by Yi Cui, Stanford University, Stanford, CA, and accepted by Editorial Board Member Tobin J. Marks May 4, 2016 (received for review January 10, 2016 \n\nBeyond state-of-the-art lithium-ion battery (LIB) technology with metallic lithium anodes to replace conventional ion intercalation anode materials is highly desirable because of lithium’s highest specific capacity $(3,860~\\mathsf{m A/g})$ and lowest negative electrochemical potential $\\left(\\sim3.040\\ v$ vs. the standard hydrogen electrode). In this work, we report for the first time, to our knowledge, a 3D lithium-ion–conducting ceramic network based on garnet-type $\\begin{array}{r}{\\mathsf{L i}_{6.4}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{A l}_{0.2}\\mathsf{O}_{12}}\\end{array}$ (LLZO) lithium-ion conductor to provide continuous ${\\mathbf{L}}{\\mathbf{i}}^{+}$ transfer channels in a polyethylene oxide (PEO)-based composite. This composite structure further provides structural reinforcement to enhance the mechanical properties of the polymer matrix. The flexible solid-state electrolyte composite membrane exhibited an ionic conductivity of $2.5\\times10^{-4}\\:\\mathsf{S}/\\mathsf{c m}$ at room temperature. The membrane can effectively block dendrites in a symmetric Li j electrolyte j Li cell during repeated lithium stripping/plating at room temperature, with a current density of $0.2\\ m\\mathsf{A}/\\mathsf{c m}^{2}$ for around ${\\pmb500\\mathrm{~h~}}$ and a current density of $0.5~\\mathsf{m A}/\\mathsf{c m}^{2}$ for over $300\\ h$ . These results provide an all solid ion-conducting membrane that can be applied to flexible LIBs and other electrochemical energy storage systems, such as lithium–sulfur batteries. \n\nsolid-state electrolyte | 3D garnet nanofibers | polyethylene oxide | ionic conductor | flexible membrane \n\nHimghosct pi amcpitoyr, ahingt kseayf fya,ctaonrds oton dliefveslpoapninag rtehcrheaergoefatbhle lithium batteries for applications in portable electronics, transportation (e.g., electrical vehicles), and large-scale energy storage systems (1–5). Based on state-of-the-art lithium-ion battery (LIB) technology, metallic lithium anode is preferable to replace conventional ion intercalation anode materials because of the highest specific capacity $(3,860\\mathrm{mAh/g})$ of lithium and the lowest negative electrochemical potential $(\\sim3.040\\mathrm{~V~}$ vs. the standard hydrogen electrode), which can maximize the capacity density and voltage window for increased battery energy density (1). Moreover, the success of beyond LIBs, such as lithium–sulfur and lithium–oxygen, will strongly rely on lithium metal anode designs with good stability to achieve their targeted goals of high energy density and long cycle life. \n\nUsing lithium metal in organic liquid electrolyte systems faces many challenges in terms of battery performance and safety. For example, lithium–sulfur batteries suffer from the dissolution of intermediate polysulfides in the organic electrolyte that causes severe parasitic reactions on lithium metal surfaces, leading to lithium metal degradation and low lithium cycling efficiency (6). Lithium–oxygen batteries have the challenge of chemically instable liquid electrolytes on the oxygen electrode that cause limited battery cycling (7). All of these challenges are associated with the use of lithium metal in liquid electrolyte battery systems. Another major associated challenge is lithium dendrite growth on lithium metal anodes, which causes internal short circuits after lithium dendrites penetrate through the separator and touch the cathode. In addition, solid–electrolyte interphase (SEI) formation during the uneven lithium deposition will continuously consume Li metal and dry up the electrolyte, leading to an increase of cell resistance and decrease of cell Coulombic efficiency (1, 8). Although extensive studies have been performed to address these challenges, Li dendrite and SEI formation are inevitable and mainly caused by the intrinsic problems of the thermodynamically unstable Li with low-molecular weight organic solvents and the poor strength of formed SEI layers (1). \n\nA fundamental strategy to address Li dendrite penetration and SEI formation is to develop a solid-state electrolyte to mechanically suppress the lithium dendrite and intrinsically eliminate SEI formation (9–14). Among the different types of solid-state electrolytes (inorganic oxides/nonoxides and Li salt-contained polymers), solid-state polymer electrolytes have been the most extensively studied (15–21). Polyethylene oxide (PEO)-based composite electrolytes have attracted the most interest (22, 23). In PEO-based composite, powders are incorporated into a host PEO polymer matrix to influence the recrystallization kinetics of the PEO polymer chains to promote local amorphous regions, thereby increasing the Li salt– polymer system’s ionic conductivity (15). The addition of powders will also improve the electrochemical stability and enhance the mechanical strength. As studied in previous work, the fillers can be either non– $\\bar{-}\\bar{\\mathrm{Li}^{+}}$ -conductive nanoparticles, such as ${\\bf A l}_{2}{\\bf O}_{3}$ (15), $\\mathrm{SiO}_{2}$ (24), $\\mathrm{TiO}_{2}$ (25), $\\boldsymbol{Z}\\mathrm{r}\\mathbf{O}_{2}$ (26), and organic polymer spheres (23), or ${\\mathrm{Li}^{+}}$ -conductive nanoparticles, such as $\\mathrm{Li}_{0.33}\\mathrm{La}_{0.557}.$ $\\bar{\\mathrm{TiO}}_{3}$ (22), tetragonal $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ (27), and $\\mathrm{Li_{1.3}A l_{0.3}T i_{1.7}(P O_{4})_{3}}$ (28). Developing nanostructured fillers is an essential approach to increase the ionic conductivity of polymer composite electrolytes because of the increased surface area of the amorphous region and improved interface between fillers and polymers. Typically, 1D \n\n# Significance \n\nThis work describes a flexible, solid-state, lithium-ion–conducting membrane based on a 3D ion-conducting network and polymer electrolyte for lithium batteries. The 3D ion-conducting network is based on percolative garnet-type $\\mathsf{L i}_{6.4}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{A l}_{0.2}\\mathsf{O}_{12}$ solid-state electrolyte nanofibers, which enhance the ionic conductivity of the solid-state electrolyte membrane at room temperature and improve the mechanical strength of the polymer electrolyte. The membrane has shown superior electrochemical stability to high voltage and high mechanical stability to effectively block lithium dendrites. This work represents a significant breakthrough to enable high performance of lithium batteries. \n\nAuthor contributions: K.(K.)F., Y.G., E.D.W., and L.H. designed research; K.(K.)F., Y.G., J.D., A.G., and Y.W. performed research; K.(K.)F., Y.G., X.H., Y.Y., C.W., Y.C., C.Y., Y.L., E.D.W., and L.H. analyzed data; and K.(K.)F. and Y.G. wrote the paper. \n\nnanowire fillers, based on perovskite-type lithium-ion–conducting $\\mathrm{Li_{0.33}L a_{0.557}T i O_{3}}$ material, were shown by Cui and coworkers (22) to enhance the ionic conductivity of the polymer composite electrolyte. This enhanced ionic conductivity was because the nanowire fillers provide extended ionic transport pathways in the polymer matrix instead of an isolated distribution of nanoparticle fillers in the polymer electrolyte (22). However, the agglomeration of ceramic fillers may remain, and it will become a challenge for its mixing with polymer to fabricate uniform solid polymer electrolyte on a large scale. To solve this challenge, in situ synthesis of ceramic filler particles with high monodispersity in polymer electrolyte was recently reported (29). By in situ synthesizing nanosized $\\mathrm{SiO}_{2}$ particles into PEO–Li salt polymer, the reported solid polymer electrolyte exhibited an ionic conductivity of $4.4\\times\\dot{1}0^{-5}\\mathrm{{S/cm}}$ at $30~^{\\circ}\\mathrm{C},$ which needs additional improvement to achieve a higher ionic conductivity at room temperature. Based on our understanding, therefore, creating a continuous nanosized network with interconnected long-range ion transport and controlling a minimum/nonfiller agglomeration are the main directions to design high ionic-conductive polymer composite electrolytes. \n\nIn this work, we have successfully developed a 3D ceramic network based on garnet-type $\\mathrm{Li}_{6.4}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{Al}_{0.2}\\mathrm{O}_{12}$ (LLZO) nanofibers to provide continuous $\\mathrm{Li^{+}}$ transfer channels in PEO-based composite electrolytes as all solid ion-conducting membranes for lithium batteries. Here, we select garnet-type lithium-ion–conducting ceramic as the inorganic component because of several desired physical and chemical properties, including $(i)$ high ionic conductivity approaching $\\stackrel{\\cdot}{10^{-3}}\\mathrm{S/cm}$ at room temperature with optimized element substitution, $(i i)$ good chemical stability against lithium metal, and $(i i i)$ good chemical stability against air and moisture (11, 30, 31). Fig. 1 shows the schematic structure of the 3D LLZO–polymer composite membrane. The LLZO porous structure consists of randomly distributed and interconnected nanofibers, creating a continuous lithium-ion–conducting network. The Li salt–PEO polymer is then filled into the porous 3D ceramic networks, forming the 3D garnet–polymer composite membrane. Different from conventional methods to prepare polymer electrolytes, the 3D garnet–polymer composite membrane does not need to mechanically mix fillers with polymers; instead, we can directly soak a preformed 3D ceramic structure into Li salt–polymer solutions to get the desired polymer composite electrolyte hybrid structure, thus simplifying fabrication process and avoiding the agglomeration of fillers. \n\n![](images/dd7e5218e614fc46a60803dbdb4596c3bb4e79d89209052fa81dbe254e606f2e.jpg) \nFig. 1. Schematic of the hybrid solid-state composite electrolyte, where ceramic garnet nanofibers function as the reinforcement and lithium-ion– conducting polymer functions as the matrix. The interwelded garnet nanofiber network provides a continuous ion-conducting pathway in the electrolyte membrane. \n\n# Results and Discussion \n\nFig. 2 schematically shows the procedure to synthesize flexible solid-state garnet LLZO nanofiber-reinforced polymer composite electrolytes. As shown in Fig. 2A, garnet LLZO nanofibers were prepared by electrospinning of polyvinylpyrrolidone (PVP) polymer mixed with relevant garnet LLZO salts followed by the calcination of the as-prepared nanofibers at $800^{\\circ}\\mathrm{C}$ in air for $^{2\\mathrm{h}}$ . On the drum collector of the electrospinning setup, a thin nonwoven fabric was covered to collect the nanofibers. \n\nThe schematic fabrication of fiber-reinforced polymer composite (FRPC) lithium-ion–conducting membrane using the 3D porous garnet nanofiber network is shown in Fig. 2B. A PEO polymer mixture with Li salt, such as bis(trifluoromethane)sulfonimide lithium salt (LiTFSI), is prepared. Then, the Li salt–PEO polymer is reinforced by the 3D nanofibers to form a composite electrolyte, which can be called FRPC electrolyte membrane. Compared with filler-containing polymer electrolyte, the FRPC electrolyte membrane maintains the framework of 3D garnet nanofiber networks and is believed to have a better mechanical property because of the continuous nanofiber structure that enhances the integrity of polymer electrolyte. \n\nMorphologies of the as-spun PVP–garnet salt nanofibers and calcinated garnet nanofibers were characterized by SEM as shown in Fig. $2C$ and $E$ . Before calcination, the PVP–garnet salt nanofibers have smooth surfaces, and nanofibers have a diameter of $256\\ \\mathrm{nm}$ on average. The corresponding diameter distribution is shown in Fig. $2D$ . After the calcination at $800^{\\circ}\\mathrm{C}$ in air, PVP polymers were removed, and garnet LLZO nanofibers were obtained. The average diameter of the nanofibers decreased to $138~\\mathrm{nm}$ . Their diameter distribution is given in Fig. $2F$ . We can see that, after annealing, garnet nanofibers were “interwelded” with each other, forming cross-linked 3D garnet nanofiber networks. The large volume of interspace between nanofibers can facilitate Li salt–polymer infiltration to form the composite membrane. The flexibility of the membrane is shown in Fig. $2G$ . The bendable electrolyte membrane can then be used to construct flexible solid-state lithium batteries. Note that the design of flexible 3D ion-conducting networks mainly depends on ceramic garnet nanofibers, which require a thin and mechanically stable structure for good ionic conductivity and feasible battery fabrication. To achieve a thinner polymer composite electrolyte while maintaining a good mechanical stability, some key parameters need to be considered, which include electrospinning process (collecting time, drum rotating speed, and syringe moving speed), precursor solution preparation (garnet salt concentration, polymer concentration, polymer molecular weight, and solvent selection), and thermal annealing optimization (heating rate, temperature, time, and cooling rate). Therefore, we believe that additional development of 3D ceramic nanofiber networks as well as polymer–salt optimization become important and necessary in the future understanding of mechanical properties and electrochemical performance of the 3D ion-conducting network-based solid-state electrolyte for lithium batteries and beyond. \n\nFig. 3 shows the morphological characterization of the garnet nanofibers and resulting FRPC electrolyte. As shown in Fig. 3A, garnet nanofibers were bonded together at their intersection points, forming a cross-linked network. These interconnected garnet nanofibers offer a continuous ion-conducting pathway because of the extended long-range lithium transport channels, which should be superior to the isolated particle fillers that are distributed in typical polymer matrixes (22). Fig. $3B$ and $C$ shows the transmission electron microscopy (TEM) images of the garnet nanofibers. The garnet nanofiber has a polycrystalline structure consisting of interconnected small crystallites to form the long, continuous nanofiber (Fig. 3B). Fig. S1 shows the magnified TEM image of a garnet nanofiber with an average grain size of $20\\ \\mathrm{nm}$ in diameter. Fig. $3C$ indicates the highly crystalized structure of the garnet grain. \n\n![](images/086bbc722db4363d042870a381392a72d3647a87887cdcab5c0fc8b6a5d9a79e.jpg) \nFig. 2. Fabrication of the flexible solid-state FRPC electrolyte. (A) Schematic setup of electrospinning garnet–PVP nanofibers. (B) Schematic procedure to fabricate the FRPC lithium-ion–conducting membrane. (C) SEM image of the as-spun nanofiber network. (D) Diameter distribution of the as-spun nanofibers. (E) SEM image of the garnet nanofiber network. $(F)$ Diameter distribution of the garnet nanofibers. (G) Photo image to show the flexible and bendable FRPC lithium-ion–conducting membrane. \n\nThe morphologies of FRPC electrolyte were examined by SEM (Fig. 3 $D/-F$ ). The FRPC electrolyte exhibited a smooth surface, which came from the PEO–LiTFSI polymer (Fig. 3D). Inside of the FRPC electrolyte, we can see that the 3D porous garnet nanofiber network supported the main structure of the composite and that the PEO–LiTFSI polymer was infiltrated into the porous garnet membrane and filled the interspace between garnet nanofibers. The cross-section image of the FRPC electrolyte showed a thickness of $40{-}50~\\upmu\\mathrm{m}$ (Fig. $3E$ ). To increase interphase contact between garnet nanofibers and PEO– LiTFSI polymer, the FRPC electrolyte was thermally treated at $60~^{\\circ}\\mathrm{C}$ , which is slightly above the polymer melting temperature $(T_{\\mathrm{m}})$ , to enable the melted PEO–LiTFSI polymer to fully infiltrate the 3D porous garnet nanofiber network. As shown in Fig. $3F$ , after thermal treatment, PEO–LiTFSI polymer was fully embedded with garnet nanofibers. We can see that garnet nanofibers increased to an average diameter of $500\\ \\mathrm{nm}$ because of the PEO–LiTFSI polymer coating. The interconnected pores were filled with polymer to maintain good lithium-ion transfer. The FRPC electrolyte membrane is proposed to have three ionconducting pathways: the first one is the interwelded ceramic garnet nanofiber network, the second one is the continuous garnet fiber–polymer interface, and the third one is the Li salt-containing polymer matrix. Because of the higher ionic conductivity of garnet-type electrolytes than that of Li salt-containing polymer electrolyte, we believe that the former two ion-conducting pathways are the dominant factors to provide improved ionic conductivity to the electrolyte membrane. \n\n![](images/41f903586be2035a6d4d31e4268c3177f5dd2fe47ad4a1ce5d0ba290a02671d1.jpg) \nFig. 3. Morphological characterizations of garnet nanofiber reinforcement and the solid-state FRPC electrolyte. (A) SEM image showing the interwelded garnet nanofibers. (B) TEM image of polycrystalline garnet nanofiber. (C) High-resolution TEM image of an individual garnet nanofiber. (D) SEM image of FRPC electrolyte membrane surface. (E) Cross-sectional SEM image of the membrane. (F) Magnified SEM image of the cross-section morphology. The free space of garnet 3D porous structure was filled with polymer. \n\nFu et al. \n\n![](images/bddacac8981db968b3e65a0d25b15a633232e28b0991964e34814a4a80ef6bea.jpg) \nFig. 4. Thermal properties and flammability tests of the solid-state FRPC electrolyte. (A) TGA curve of the as-spun nanofibers. (B) TGA curves of Li salt–PEO polymer and FRPC electrolyte membrane. (C) Flammability test of Li salt–PEO polymer mixed with garnet nanoparticles. (D) Flammability test of FRPC electrolyte membrane. \n\nThermogravimetric analysis (TGA) was used to study the garnet nanofiber formation during the calcination process. The TGA was carried out under airflow with a rapid heating rate of $10~\\mathrm{{^circC/min}}$ . Fig. 4A shows the TGA profile of the as-spun nanofibers containing PVP polymer and garnet precursor. The result shows that, above $750~^{\\circ}\\mathrm{C}.$ , the weight became stable, indicating that stable garnet nanofibers were formed. Fig. $^{4B}$ compares the TGA profiles of the PEO–LiTFSI and the FRPC electrolyte. Both electrolytes were thermally stable to around $200~^{\\circ}\\mathrm{C}$ . In the rapid heating process, polymers began to decompose above $200~^{\\circ}\\mathrm{C}$ and showed a significant weight loss at around $400~^{\\circ}\\mathrm{C}$ because of the almost complete decomposition of the polymer. The slope at $400^{\\circ}\\mathrm{C}$ was the decomposition of LiTFSI. For the FRPC electrolyte, the weight was stable at $500~^{\\circ}\\mathrm{C}$ , and the remaining was the garnet nanofiber membrane caused by the superior stability of garnet material in air. For the polymer electrolyte, the weight was stable at $650~^{\\circ}\\mathrm{C},$ leaving with decomposed LiTFSI salt. \n\nThermal stability is an important consideration for using solidstate electrolytes, especially polymer electrolyte. Traditional liquid electrolytes, such as carbonate electrolytes, tend to cause thermal runaway when batteries are under extreme conditions of short circuits, overcharge, and high temperature (19). Because of its relatively high thermal stability, polymer electrolyte becomes a safer choice compared with liquid electrolyte. Because traditional polymer electrolytes are built on their own polymer structure and fillers cannot offer sufficient mechanical support for the electrolyte, the polymer electrolyte inevitably melts and shrinks at high temperature, especially above the polymer thermal decomposition temperature, which may cause direct contact between cathode and anode and is a significant safety concern. The FRPC electrolyte is able to address this concern, because the garnet nanofiber membrane within the polymer electrolyte provides a ceramic barrier to physically block cathode and anode contact, even after loss of the polymer. \n\nFig. $4C$ and $D$ compares the combustion tests of a traditional polymer electrolyte and the FRPC electrolyte developed in this work. The traditional polymer electrolyte was prepared using the same recipe used to prepare the PEO–LTFSI polymer but using garnet nanopowders (vs. the 3D garnet network) as fillers. The mass ratio of polymer and filler was controlled at 4:1. In Fig. 4C, the polymer electrolyte caught fire instantly when it came close to the ignited lighter and was quickly burned off into ashes. This high flammability indicates poor thermal stability of the polymer electrolyte. In comparison, the FRPC electrolyte exhibited an outstanding thermal stability; although the polymer component was gone, the garnet nanofiber membrane still retained its3 structure (Fig. $4D$ ). This low-flammability FRPC electrolyte can provide enhanced safety for all lithium metal and LIBs. \n\nPowder X-ray diffraction (XRD) patterns of LLZO garnet nanofibers that were calcined at $800^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ are shown in Fig. 5A. Almost all of the diffraction peaks match very well with those of cubic-phase garnet $\\mathrm{Li}_{5}\\mathrm{La}_{3}\\mathrm{Nb}_{2}\\mathrm{O}_{12}$ (Joint Committee on Powder Diffraction Standards card 80-0457). $\\mathrm{Li}_{5}\\mathrm{La}_{3}\\mathrm{M}_{2}\\mathrm{O}_{5}$ $\\mathbf{M}=\\mathbf{Nb}$ , Ta) is the first example, to our knowledge, of a fast lithium-ion– conductive processing garnet-like structure, which is the typical structure that has been widely used as a model to study the garnet structure of LLZO material. Here, we use the standard $\\mathrm{Li}_{5}\\mathrm{La}_{3}\\mathrm{Nb}_{2}\\mathrm{O}_{12}$ XRD profile to identify the synthesized garnet nanofiber structure. A small amount of $\\mathrm{La}_{2}\\mathrm{Zr}_{2}\\mathrm{O}_{7}$ was identified, but other impurities were below detection limit. According to the thermogravimetric results, decomposition of precursors to oxide was completed at ${\\sim}750^{\\circ}\\mathrm{C}$ . Additional heating at $800^{\\circ}\\mathrm{C}$ resulted in reaction of the oxides and formation of cubic-phase LLZO garnet structure. However, the small amount of $\\mathrm{La}_{2}\\mathrm{Zr}_{2}\\mathrm{O}_{7}$ phase could also be formed by lithium loss at elevated temperature. \n\nThe total lithium-ion conductivity of FRPC electrolyte was characterized by electrochemical impedance spectroscopy (EIS). Fig. $5B$ shows the typical Nyquist plots of FRPC electrolyte sandwiched between stainless steel blocking electrodes in the frequency range from $1~\\mathrm{Hz}$ to 1MHz. Each impedance profile shows a real axis intercept at high frequency, a semicircle at intermediate frequency, and an inclined straight tail at low frequency. The intercept of the extended semicircle on the real axis and the semicircle in the high- and intermediate-frequency range represent the bulk relaxation of FRPC electrolyte. The low-frequency tail is caused by the migration of lithium ions and the surface inhomogeneity of the blocking electrodes. Fig. $5C$ shows the Arrhenius plot of the FRPC electrolyte. Lithium-ion conductivity was calculated based on the thickness of FRPC electrolyte and diameter of stainless electrodes. As reported, lithium-ion conductivity of the cubic-phase LLZO garnet pellet would reach as high as $\\mathrm{10^{-3}}\\mathrm{S/cm}$ , whereas lithium salt-stuffed PEO is generally on the order of $\\mathrm{{10^{-6}{-}10^{-9}\\ S/c m}}$ at room temperature (15, 22). Our FRPC electrolyte combining conductive cubic LLZO garnet and lithium–PEO could exhibit reasonably high ionic conductivity of $2.5\\times10^{-4}\\mathrm{S}/\\mathrm{cm}$ at room temperature. \n\n![](images/9d4a70592b1caf9ec02fed58ed4af8b7c227bb63d170f075cd23216c412be075.jpg) \nFig. 5. Phase structure of garnet fiber and electrical properties of solidstate FRPC electrolyte. (A) XRD pattern of the garnet nanofibers and the powder diffraction file (PDF) of $\\mathsf{L i}_{5}\\mathsf{L a}_{2}\\mathsf{N b}_{2}\\mathsf{O}_{12}$ . (B) EIS profiles of the FRPC electrolyte membrane at different temperatures $(25^{\\circ}\\mathsf{C},$ $40^{\\circ}\\mathsf C,$ , and $90^{\\circ}\\mathsf{C})$ . (C ) Arrhenius plot of the FRPC electrolyte membrane at elevated temperatures (from $20^{\\circ}\\mathsf C$ to $90~^{\\circ}\\mathsf{C}$ and record every $10^{\\circ}\\mathsf{C}$ increase). (D) LSV curve of the FRPC electrolyte membrane to show the electrochemical stability window in the range of $_{0-6\\vee}$ . OCV, open-circuit voltage. \n\nA large electrochemical window is another key factor to determine the polymer electrolyte application for high-voltage lithium batteries. Fig. $5D$ shows the result of the linear sweep voltammetry (LSV) profile of the FRPC electrolyte using lithium metal as the counter and reference electrode and stainless steel as the working electrode. The FRPC electrolyte exhibits a stable voltage window up to $6.0\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ , indicating that this ion-conducting membrane can satisfy the requirement of most high-voltage lithium batteries. \n\nThe mechanical stability of the FRPC electrolyte membrane against Li dendrites was evaluated by using a symmetric Li j FRPC electrolyte Li cell. During charge and discharge processes at a constant current, lithium ions are plating/stripping the lithium metal electrode to mimic the operation of charging and discharging lithium metal batteries. Fig. 6A represents the schematic of the symmetric cell setup. The FRPC electrolyte membrane was sandwiched between two lithium metal foils and sealed in coin cell. Fig. $6B$ shows the time-dependent voltage profile of the cell with FRPC electrolyte membrane cycled over $230\\mathrm{~h~}$ at a constant current density of $0.2\\ \\mathrm{mA}/\\mathrm{cm}^{2}$ and a temperature of $15~^{\\circ}\\mathrm{C}$ . The symmetric cell was periodically charged and discharged for $0.5\\mathrm{h}$ . The positive voltage is the Li stripping, and the negative voltage value refers to the Li plating process. In the first $70\\mathrm{{\\bar{h}}}$ , the cell’s voltage slightly increased from 0.3 to $0.4\\mathrm{~V~}$ and then, stabilized at $0.4\\mathrm{\\:V}$ . \n\n![](images/d288da522144ad2709fa86cc145690c9bfb9f35ca4e1bff89d1e8ec136be9a32.jpg) \nFig. 6. Electrochemical performance of the FRPC electrolyte membrane measured in the symmetric Li FRPC electrolyte Li cell. $(A)$ Schematic of the symmetric cell for the lithium plating/stripping experiment. (B) Voltage profile of the lithium plating/striping cycling with a current density of $0.2\\ m\\mathsf{A}/\\mathsf{c m}^{2}$ at $15^{\\circ}\\mathsf C$ . (C) Voltage profile of the continued lithium plating/ stripping cycling with a current density of $0.2\\ m\\mathsf{A}/\\mathsf{c m}^{2}$ at $25^{\\circ}\\mathsf{C}$ . (D) The impedance spectra of the symmetric cell measured at different cycle times (300, 500, and $700~\\mathrm{h};$ ). (E) Magnified EIS spectra in the high-frequency region. $(F)$ Voltage profile of the continued lithium plating/stripping cycling with a current density of $0.5~\\mathsf{m A}/\\mathsf{c m}^{2}$ at $25^{\\circ}\\mathsf{C}$ . \n\nWhen the testing temperature increased to $25~^{\\circ}\\mathrm{C}$ , the voltage dropped to $0.3{\\mathrm{~V}}$ because of the improved ionic conductivity at elevated temperature as shown in Fig. 6C. In the following longtime cycles, the voltage kept decreasing to $0.2\\mathrm{V}$ with increasing cycle time to $700\\mathrm{~h~}$ (Fig. S2). The fluctuation of voltage was caused by the surrounding environmental temperature change. Two voltage profiles of the symmetric cell at two different stripping/plating process times were compared as shown in Fig. S3. The voltage hysteresis apparently decreased with increase of cycle time. This decrease in voltage is quite different from the liquid electrolyte system, in which the voltage normally increases with the increase of time and is mainly ascribed to the nonuniform Li deposition and severe electrolyte decomposition that cause impedance increase (32). Similar voltage decrease has been observed in recent polymer electrolyte studies, but the reason why voltage keeps decreasing with the increasing cycle time has not yet been explained (23, 33). Based on our understanding, the decrease in voltage might be because of the improved interface between the electrolyte membrane and lithium metal during the repeated Li electrodeposition, which is confirmed by the EIS spectra of the symmetric cell measured at 300, 500, and 700 h (Fig. $6D^{\\cdot}$ ). The depressed semicircles at lower frequency indicate decreased interfacial impedance between electrolyte membrane and lithium metal during cycling. At high frequency (Fig. $6E{\\ddot{}}$ ), the semicircle also decreased with the increased cycle time, indicating the decreased bulk impedance of the electrolyte membrane. When the current density increased to $0.5\\mathrm{\\mA}/\\mathrm{cm}^{2}$ , the voltage increased to $0.3{\\mathrm{~V~}}$ , and the cell also exhibited slight decrease in voltage with increasing time to $^{1,000\\mathrm{h}}$ (Fig. $6F$ ), showing good cycling stability with long cycle life. \n\n# Conclusion \n\nIn conclusion, all solid ion-conducting membranes of 3D garnet– polymer composite were synthesized for lithium batteries. 3D garnet nanofiber networks were prepared by electrospinning and high-temperature annealing. The garnet nanofibers constructed an interwelded 3D structure that provides long-range lithium-ion transfer pathways and further provides structural reinforcement to enhance the polymer matrix. This flexible solid-state electrolyte composite membrane exhibited an ionic conductivity of $2.5\\times$ $\\mathrm{i0^{-4}~S/c m}$ at room temperature. The membrane can effectively block dendrites in a symmetric Li j electrolyte j Li cell during repeated lithium stripping/plating at room temperature, with a current density of $0.2\\mathrm{\\mA}/\\mathrm{cm}^{2}$ around $500\\mathrm{{h}}$ and a current density of $0.5\\mathrm{mA}/\\mathrm{cm}^{2}$ over $300\\mathrm{h}$ . The decrease of voltage with increasing cycle time is observed for the symmetric cell, which is possibly because of the improved interfaces during repeated lithium electrodeposition. Our work is the first report, to our knowledge, of the development of 3D lithium-ion–conducting ceramic materials in solid-state electrolytes, which can be potentially applied to flexible LIBs and other electrochemical energy storage systems, such as lithium–sulfur batteries. \n\nACKNOWLEDGMENTS. This work was supported by EERE, which is funded by the US Department of Energy. We acknowledge the support of the Maryland NanoCenter and its FabLab and NispLab. \n\n1. Xu W, et al. (2014) Lithium metal anodes for rechargeable batteries. Energy Environ Sci 7(2):513–537. \n2. Xu K (2014) Electrolytes and interphases in Li-ion batteries and beyond. Chem Rev 114(23):11503–11618. \n3. Bruce PG, Freunberger SA, Hardwick LJ, Tarascon JM (2011) Li-O2 and Li-S batteries with high energy storage. Nat Mater 11(1):19–29. \n4. Yin Y-X, Xin S, Guo Y-G, Wan L-J (2013) Lithium-sulfur batteries: Electrochemistry, materials, and prospects. Angew Chem Int Ed Engl 52(50):13186–13200. \n5. Dunn B, Kamath H, Tarascon J-M (2011) Electrical energy storage for the grid: A battery of choices. Science 334(6058):928–935. \n6. Manthiram A, Fu Y, Chung SH, Zu C, Su YS (2014) Rechargeable lithium-sulfur batteries. Chem Rev 114(23):11751–11787. \n7. Jung H-G, Hassoun J, Park J-B, Sun Y-K, Scrosati B (2012) An improved high-performance lithium-air battery. Nat Chem 4(7):579–585. \n8. Cheng X-B, et al. (2015) A review of solid electrolyte interphases on lithium metal anode. Adv Sci 3(3):1500213. \n9. Quartarone E, Mustarelli P (2011) Electrolytes for solid-state lithium rechargeable batteries: Recent advances and perspectives. Chem Soc Rev 40(5):2525–2540. \n10. Takada K (2013) Progress and prospective of solid-state lithium batteries. Acta Mater 61(3):759–770. \n11. Thangadurai V, Narayanan S, Pinzaru D (2014) Garnet-type solid-state fast Li ion conductors for Li batteries: Critical review. Chem Soc Rev 43(13):4714–4727. \n12. Luntz AC, Voss J, Reuter K (2015) Interfacial challenges in solid-state Li ion batteries. J Phys Chem Lett 6(22):4599–4604. \n13. Wang Y, et al. (2015) Design principles for solid-state lithium superionic conductors. Nat Mater 14(10):1026–1031. \n14. Tan G, et al. (2016) Solid-state li-ion batteries using fast, stable, glassy nanocomposite electrolytes for good safety and long cycle-life. Nano Lett 16(3):1960–1968. \n15. Croce F, Appetecchi GB, Persi L, Scrosati B (1998) Nanocomposite polymer electrolytes for lithium batteries. Nature 394(6692):456–458. \n16. Gadjourova Z, Andreev YG, Tunstall DP, Bruce PG (2001) Ionic conductivity in crystalline polymer electrolytes. Nature 412(6846):520–523. \n17. Christie AM, Lilley SJ, Staunton E, Andreev YG, Bruce PG (2005) Increasing the conductivity of crystalline polymer electrolytes. Nature 433(7021):50–53. \n18. Aetukuri NB, et al. (2015) Flexible ion-conducting composite membranes for lithium batteries. Adv Energy Mater 5(14):1500265. \n19. Zhou D, et al. (2015) In situ synthesis of a hierarchical all-solid-state electrolyte based on nitrile materials for high-performance lithium-ion batteries. Adv Energy Mater 5(15):1500353. \n20. Pan $\\scriptstyle{\\mathsf{Q}},$ Smith DM, Qi H, Wang S, Li CY (2015) Hybrid electrolytes with controlled network structures for lithium metal batteries. Adv Mater 27(39):5995–6001. \n21. Zhang J, et al. (2015) Safety-reinforced poly(propylene carbonate)-based all-solidstate polymer electrolyte for ambient-temperature solid polymer lithium batteries. Adv Energy Mater 5(24):1501082. \n22. Liu W, et al. (2015) Ionic conductivity enhancement of polymer electrolytes with ceramic nanowire fillers. Nano Lett 15(4):2740–2745. \n23. Zhou W, Gao H, Goodenough JB (2016) Low-cost hollow mesoporous polymer spheres and all-solid-state lithium, sodium batteries. Adv Energy Mater 6(1):1501802. \n24. Liu S, et al. (2010) Effect of nano-silica filler in polymer electrolyte on Li dendrite formation in Li/poly(ethylene oxide)–Li(CF3SO2)2N/Li. J Power Sources 195(19): 6847–6853. \n25. Gurevitch I, et al. (2013) Nanocomposites of titanium dioxide and polystyrenepoly(ethylene oxide) block copolymer as solid-state electrolytes for lithium metal batteries. J Electrochem Soc 160(9):A1611–A1617. \n26. Damen L, Hassoun J, Mastragostino M, Scrosati B (2010) Solid-state, rechargeable Li/ LiFePO4 polymer battery for electric vehicle application. J Power Sources 195(19): 6902–6904. \n27. Choi JH, Lee CH, Yu JH, Doh CH, Lee SM (2015) Enhancement of ionic conductivity of composite membranes for all-solid-state lithium rechargeable batteries incorporating tetragonal Li7La3Zr2O12 into a polyethylene oxide matrix. J Power Sources 274: 458–463. \n28. Wang Y-J, Pan Y, Kim D (2006) Conductivity studies on ceramic Li1.3Al0.3Ti1.7(PO4)3- filled PEO-based solid composite polymer electrolytes. J Power Sources 159(1): 690–701. \n29. Lin D, et al. (2016) High ionic conductivity of composite solid polymer electrolyte via in situ synthesis of monodispersed SiO2 nanospheres in poly(ethylene oxide). Nano Lett 16(1):459–465. \n30. Teng S, Tan J, Tiwari A (2014) Recent developments in garnet based solid state electrolytes for thin film batteries. Curr Opin Solid State Mater Sci 18(1):29–38. \n31. Du F, et al. (2015) All solid state lithium batteries based on lamellar garnet-type ceramic electrolytes. J Power Sources 300:24–28. \n32. Liang Z, et al. (2015) Polymer nanofiber-guided uniform lithium deposition for battery electrodes. Nano Lett 15(5):2910–2916. \n33. Choudhury S, Mangal R, Agrawal A, Archer LA (2015) A highly reversible roomtemperature lithium metal battery based on crosslinked hairy nanoparticles. Nat Commun 6:10101. \n34. Rangasamya E, Wolfenstineb J, Sakamoto J (2012) The role of Al and Li concentration on the formation of cubic garnet solid electrolyte of nominal composition Li7La3Zr2O12. Solid State Ionics 206:28–32. " + }, + { + "id": "10.1088_1361-648X_aa8f79", + "DOI": "10.1088/1361-648X/aa8f79", + "DOI Link": "http://dx.doi.org/10.1088/1361-648X/aa8f79", + "Relative Dir Path": "mds/10.1088_1361-648X_aa8f79", + "Article Title": "Advanced capabilities for materials modelling with QUANTUM ESPRESSO", + "Authors": "Giannozzi, P; Andreussi, O; Brumme, T; Bunau, O; Nardelli, MB; Calandra, M; Car, R; Cavazzoni, C; Ceresoli, D; Cococcioni, M; Colonna, N; Carnimeo, I; Dal Corso, A; de Gironcoli, S; Delugas, P; DiStasio, RA; Ferretti, A; Floris, A; Fratesi, G; Fugallo, G; Gebauer, R; Gerstmann, U; Giustino, F; Gorni, T; Jia, J; Kawamura, M; Ko, HY; Kokalj, A; Küçükbenli, E; Lazzeri, M; Marsili, M; Marzari, N; Mauri, F; Nguyen, NL; Nguyen, HV; Otero-de-la-Roza, A; Paulatto, L; Poncé, S; Rocca, D; Sabatini, R; Santra, B; Schlipf, M; Seitsonen, AP; Smogunov, A; Timrov, I; Thonhauser, T; Umari, P; Vast, N; Wu, X; Baroni, S", + "Source Title": "JOURNAL OF PHYSICS-CONDENSED MATTER", + "Abstract": "QUANTUM ESPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the-art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudopotential and projector-augmented-wave approaches. QUANTUM ESPRESSO owes its popularity to the wide variety of properties and processes it allows to simulate, to its performance on an increasingly broad array of hardware architectures, and to a community of researchers that rely on its capabilities as a core open-source development platform to implement their ideas. In this paper we describe recent extensions and improvements, covering new methodologies and property calculators, improved parallelization, code modularization, and extended interoperability both within the distribution and with external software.", + "Times Cited, WoS Core": 6474, + "Times Cited, All Databases": 6784, + "Publication Year": 2017, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000413705400001", + "Markdown": "PAPER \n\n# Related content \n\n# Advanced capabilities for materials modelling with Quantum ESPRESSO \n\n- QUANTUM ESPRESSO: a modular and open-source software project for quantumsimulations of materials Paolo Giannozzi, Stefano Baroni, Nicola Bonini et al. \n\nTo cite this article: P Giannozzi et al 2017 J. Phys.: Condens. Matter 29 465901 \n\n- Electronic structure calculations with GPAW: a real-space implementation of the projectoraugmented-wave method J Enkovaara, C Rostgaard, J J Mortensen et al. \n\nView the article online for updates and enhancements. \n\n- exciting: a full-potential all-electron package implementing density-functional theory and many-body perturbation theory Andris Gulans, Stefan Kontur, Christian Meisenbichler et al. \n\n# Advanced capabilities for materials modelling with Quantum ESPRESSO \n\nP Giannozzi $^1\\textcircled{\\circ}$ , O Andreussi2,9, T Brumme3, O Bunau4, M Buongiorno Nardelli5, M Calandra4, R Car6, C Cavazzoni7, D Ceresoli8, M Cococcioni9, N Colonna9, I Carnimeo1, A Dal Corso10,32, S de Gironcoli10,32, P Delugas10, R A DiStasio Jr 11, A Ferretti12, A Floris13, G Fratesi $14\\textcircled{\\mathbb{P}}$ , G Fugallo15, R Gebauer16, U Gerstmann17, F Giustino18, T Gorni4,10, J Jia11, M Kawamura $19_{\\textcircled{\\mathbb{D}}}$ , H-Y $\\mathsf{K o}^{6}$ , A Kokalj20, E Küçükbenli10, M Lazzeri4, M Marsili21, N Marzari9, F Mauri22, N L Nguyen9, H-V Nguyen23, A Otero-de-la-Roza24, L Paulatto4, S Poncé18, D Rocca25,26, R Sabatini27, B Santra $6\\textcircled{\\textcircled{\\circ}}$ , M Schlipf18, A P Seitsonen28,29, A Smogunov30, I Timrov9 , T Thonhauser31, P Umari21,32, N Vast33, X Wu34 and S Baroni $10_{\\textcircled{\\textcircled{10}}}$ \n\n1  Department of Mathematics, Computer Science, and Physics, University of Udine, via delle Scienze \n206, I-33100 Udine, Italy \n2  Institute of Computational Sciences, Università della Svizzera Italiana, Lugano, Switzerland \n3  Wilhelm-Ostwald-Institute of Physical and Theoretical Chemistry, Leipzig University, Linnéstr. 2, \nD-04103 Leipzig, Germany \n4  IMPMC, UMR CNRS 7590, Sorbonne Universités-UPMC University Paris 06, MNHN, IRD, 4 Place \nJussieu, F-75005 Paris, France \n5  Department of Physics and Department of Chemistry, University of North Texas, Denton, TX, \nUnited States of America \n6  Department of Chemistry, Princeton University, Princeton, NJ 08544, United States of America \n7  CINECA—Via Magnanelli 6/3, I-40033 Casalecchio di Reno, Bologna, Italy \n8  Institute of Molecular Science and Technologies (ISTM), National Research Council (CNR), I-20133 \nMilano, Italy \n9  Theory and Simulation of Materials (THEOS), and National Centre for Computational Design \nand Discovery of Novel Materials (MARVEL), Ecole Polytechnique Fédérale de Lausanne, CH-1015 \nLausanne, Switzerland \n10  SISSA-Scuola Internazionale Superiore di Studi Avanzati, via Bonomea 265, I-34136 Trieste, Italy \n11  Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, \nUnited States of America \n12  CNR Istituto Nanoscienze, I-42125 Modena, Italy \n13  School of Mathematics and Physics, College of Science, University of Lincoln, United Kingdom \n14  Dipartimento di Fisica, Università degli Studi di Milano, via Celoria 16, I-20133 Milano, Italy \n15  ETSF, Laboratoire des Solides Irradiés, Ecole Polytechnique, F-91128 Palaiseau cedex, France \n16  The Abdus Salam International Centre for Theoretical Physics (ICTP), Strada Costiera 11, I-34151 \nTrieste, Italy \n17  Department Physik, Universität Paderborn, D-33098 Paderborn, Germany \n18  Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, United Kingdom \n19  The Institute for Solid State Physics, Kashiwa, Japan \n20  Department of Physical and Organic Chemistry, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, \nSlovenia \n21  Dipartimento di Fisica e Astronomia, Università di Padova, via Marzolo 8, I-35131 Padova, Italy \n22  Dipartimento di Fisica, Università di Roma La Sapienza, Piazzale Aldo Moro 5, I-00185 Roma, Italy \n23  Institute of Physics, Vietnam Academy of Science and Technology, 10 Dao Tan, Hanoi, Vietnam \n24  Department of Chemistry, University of British Columbia, Okanagan, Kelowna BC V1V 1V7, Canad \n25  Université de Lorraine, $\\dot{\\mathrm{CRM}}^{2}$ , UMR 7036, F-54506 Vandoeuvre-lès-Nancy, France \n26  CNRS, $\\mathbf{CRM}^{2}$ , UMR 7036, F-54506 Vandoeuvre-lès-Nancy, France \n27  Orionis Biosciences, Newton, MA 02466, United States of America \n28  Institut für Chimie, Universität Zurich, CH-8057 Zürich, Switzerland \n29  Département de Chimie, École Normale Supérieure, F-75005 Paris, France \n30  SPEC, CEA, CNRS, Université Paris-Saclay, F-91191 Gif-Sur-Yvette, France \n31  Department of Physics, Wake Forest University, Winston-Salem, NC 27109, United States of America \n\n32  CNR-IOM DEMOCRITOS, Istituto Officina dei Materiali, Consiglio Nazionale delle Ricerche, Italy 33  Laboratoire des Solides Irradiés, École Polytechnique, CEA-DRF-IRAMIS, CNRS UMR 7642, Université Paris-Saclay, F-91120 Palaiseau, France 34  Department of Physics, Temple University, Philadelphia, PA 19122-1801, United States of America \n\nE-mail: paolo.giannozzi@uniud.it \n\nReceived 5 July 2017, revised 23 September 2017 \nAccepted for publication 27 September 2017 \nPublished 24 October 2017 \n\n![](images/36cb9e159752d0b39df0e591b4daa3813eccfa0ffe5193a55a1a5118300f3f09.jpg) \n\n# Abstract \n\nQuantum ESPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the-art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudopotential and projector-augmented-wave approaches. Quantum ESPRESSO owes its popularity to the wide variety of properties and processes it allows to simulate, to its performance on an increasingly broad array of hardware architectures, and to a community of researchers that rely on its capabilities as a core open-source development platform to implement their ideas. In this paper we describe recent extensions and improvements, covering new methodologies and property calculators, improved parallelization, code modularization, and extended interoperability both within the distribution and with external software. \n\nKeywords: density-functional theory, density-functional perturbation theory, many-body perturbation theory, first-principles simulations \n\n(Some figures may appear in colour only in the online journal) \n\n# 1.  Introduction \n\nNumerical simulations based on density-functional theory (DFT) [1, 2] have become a powerful and widely used tool for the study of materials properties. Many such simulations are based upon the ‘plane-wave pseudopotential method’, often using ultrasoft pseudopotentials [3] or the projector augmented wave method (PAW) [4] (in the following, all of these modern developments will be referred to under the generic name of ‘pseudopotentials’). An important role in the diffusion of DFT-based techniques has been played by the availability of robust and efficient software implementations [5], as is the case for Quantum ESPRESSO, which is an open-source software distribution—i.e. an integrated suite of codes—for electronic-structure calculations based on DFT or many-body perturbation theory, and using plane-wave basis sets and pseudo­potentials [6]. \n\nThe core philosophy of Quantum ESPRESSO can be summarized in four keywords: openness, modularity, efficiency, and innovation. The distribution is based on two core packages, PWscf and CP, performing self-consistent and molecular-dynamics calculations respectively, and on additional packages for more advanced calculations. Among these we quote in particular: PHonon, for linear-response calculations of vibrational properties; PostProc, for data analysis and postprocessing; atomic, for pseudopotential generation; XSpectra, for the calculation of $\\mathbf{\\boldsymbol{x}}$ -ray absorption spectra; GIPAW, for nuclear magnetic resonance and electron paramagn­etic resonance calculations. \n\nIn this paper we describe and document the novel or improved capabilities of Quantum ESPRESSO up to and including version 6.2. We do not cover features already present in v.4.1 and described in [6], to which we refer for further details. The list of enhancements includes theoretical and methodological extensions but also performance enhancements for current parallel machines and modularization and extended interoperability with other software. \n\nAmong the theoretical and methodological extensions, we mention in particular: \n\n•\tFast implementations of exact (Fock) exchange for hybrid functionals [7, 42–44]; implementation of non-local van der Waals functionals [9] and of explicit corrections for van der Waals interactions [10–13]; improvement and extensions of Hubbard-corrected functionals [14, 15]. \n•\tExcited-state calculations within time-dependent densityfunctional and many-body perturbation theories. \n•\tRelativistic extension of the PAW formalism, including spin–orbit interactions in density-functional theory [16, 17]. \n•\tContinuum embedding environments (dielectric solvation models, electronic enthalpy, electronic surface tension, periodic boundary corrections) via the Environ module [18, 19] and its time-dependent generalization [20]. \n\nSeveral new packages, implementing the calculation of new properties, have been added to Quantum ESPRESSO. We quote in particular: \n\n•\tturboTDDFT [21–24] and turboEELS [25, 26], for excited-state calculations within time-dependent DFT (TDDFT), without computing virtual orbitals, also interfaced with the Environ module (see above). \n•\tQE-GIPAW, replacing the old GIPAW package, for nuclear magnetic resonance and electron paramagnetic resonance calculations. \n•\tEPW, for electron–phonon calculations using Wannierfunction interpolation [27]. \n•\tGWL and SternheimerGW for quasi-particle and excited-state calculations within many-body perturbation theory, without computing any virtual orbitals, using the Lanczos bi-orthogonalization [28, 29] and multi-shift conjugate-gradient methods [30], respectively. \n•\tthermo_pw, for computing thermodynamical properties in the quasi-harmonic approximation, also featuring an advanced master-slave distributed computing scheme, applicable to generic high-throughput calculations [31]. \n• $\\mathtt{d}3\\mathtt{q}$ and thermal2, for the calculation of anharmonic 3-body interatomic force constants, phonon-phonon interaction and thermal transport [32, 33]. \n\nImproved parallelization is crucial to enhance performance and to fully exploit the power of modern parallel architectures. A careful removal of memory bottlenecks and of scalar sections  of code is a pre-requisite for better and extending scaling. Significant improvements have been achieved, in par­ ticular for hybrid functionals [34, 35]. \n\nComplementary to this, a complete pseudopotential library, pslibrary, including fully-relativistic pseudopotentials, has been generated [36, 37].A curation effort [38] on all the pseudo­ potential libraries available for Quantum ESPRESSO has led to the identification of optimal pseudopotentials for efficiency or for accuracy in the calculations, the latter delivering an agreement comparable to any of the best all-electron codes [5]. Finally, a significant effort has been dedicated to modularization and to enhanced interoperability with other software. The structure of the distribution has been revised, the code base has been re-organized, the format of data files re-designed in line with modern standards. As notable examples of interoperability with other software, we mention in particular the interfaces with the LAMMPS molecular dynamics (MD) code [39] used as molecular-mechanics ‘engine’ in the Quantum ESPRESSO implementation of the QM–MM methodology [40], and with the i PI MD driver [41], also featuring path-integral MD. \n\nAll advances and extensions that have not been documented elsewhere are described in the next sections. For more details on new packages we refer to the respective references. \n\nThe paper is organized as follows. Section  2 contains a description of new theoretical and methodological developments and of new packages distributed together with Quantum ESPRESSO. Section  3 contains a description of improvements of parallelization, updated information on the philosophy and general organization of Quantum ESPRESSO, notably in the field of modularization and interoperability. Section 4 contains an outlook of future directions and our conclusions. \n\n# 2. Theoretical, algorithmic, and methodological extensions \n\nIn the following, CGS units are used, unless noted otherwise. \n\n# 2.1.  Advanced functionals \n\n2.1.1.  Advanced implementation of exact (Fock) exchange and hybrid functionals.  Hybrid functionals are already the de facto standard in quantum chemistry and are quickly gaining popularity in the condensed-matter physics and computational materials science communities. Hybrid functionals reduce the self-interaction error that plagues lower-rung exchange-correlation functionals, thus achieving more accurate and reliable predictive capabilities. This is of particular importance in the calculation of orbital energies, which are an essential ingredient in the treatment of band alignment and charge transfer in heterogeneous systems, as well as the input for higher-level electronic-structure calculations based on many-body perturbation theory. However, the widespread use of hybrid functionals is hampered by the often prohibitive computational requirements of the exact-exchange (Fock) contribution, especially when working with a plane-wave basis set. The basic ingredient here is the action $(\\hat{V}_{x}\\phi_{i})(\\mathbf{r})$ of the Fock operator $\\hat{V}_{x}$ onto a (single-particle) electronic state $\\phi_{i}$ , requiring a sum over all occupied Kohn–Sham (KS) states $\\{\\psi_{j}\\}$ . For spinunpolarized systems, one has: \n\n$$\n(\\hat{V}_{x}\\phi_{i})(\\mathbf{r})=-e^{2}\\sum_{j}\\psi_{j}(\\mathbf{r})\\int\\mathrm{d}\\mathbf{r}^{\\prime}\\frac{\\psi_{j}^{*}(\\mathbf{r}^{\\prime})\\phi_{i}(\\mathbf{r}^{\\prime})}{|\\mathbf{r}-\\mathbf{r}^{\\prime}|},\n$$ \n\nwhere $-e$ is the charge of the electron. In the original algorithm [6] implemented in PWscf, self-consistency is achieved via a double loop: in the inner one the $\\psi^{\\dagger}$ s entering the definition of the Fock operator in equation  (1) are kept fixed, while the outer one cycles until the Fock operator converges to within a given threshold. In the inner loop, the integrals appearing in equation (1): \n\n$$\nv_{i j}(\\mathbf{r})=\\int{\\mathrm{d}\\mathbf{r}^{\\prime}}\\frac{\\rho_{i j}(\\mathbf{r}^{\\prime})}{|\\mathbf{r}-\\mathbf{r}^{\\prime}|},\\qquad\\rho_{i j}(\\mathbf{r})=\\psi_{i}^{*}(\\mathbf{r})\\phi_{j}(\\mathbf{r}),\n$$ \n\nare computed by solving the Poisson equation  in reciprocal space using fast Fourier transforms (FFT). This algorithm is straightforward but slow, requiring $\\mathcal{O}\\big((N_{b}N_{k})^{2}\\big)$ FFTs, where $N_{b}$ is the number of electronic states (‘bands’ in solid-state parlance) and $N_{k}$ the number of $\\mathbf{k}$ points in the Brillouin zone (BZ). While feasible in relatively small cells, this unfavorable scaling with the system size makes calculations with hybrid functionals challenging if the unit cell contains more than a few dozen atoms. \n\nTo enable exact-exchange calculations in the condensed phase, various ideas have been conceived and implemented in recent Quantum ESPRESSO versions. Code improvements aimed at either optimizing or better parallelizing the standard algorithm are described in section  3.1. In this section we describe two important algorithmic developments in Quantum ESPRESSO, both entailing a significant reduction in the computational effort: the adaptively compressed exchange (ACE) concept [7] and a linear-scaling $(\\mathcal{O}(N_{b}))$ framework for performing hybrid-functional ab initio molecular dynamics using maximally localized Wannier functions (MLWF) [42–44]. \n\n2.1.1.1. Adaptively compressed exchange.  The simple formal derivation of ACE allows for a robust implementation, which applies straightforwardly both to isolated or aperiodic systems $\\mathrm{{T-}}$ only sampling of the BZ, that is, $\\mathbf{k}=0$ ) and to periodic ones (requiring sums over a grid of $\\mathbf{k}$ points in the BZ); to norm conserving and ultrasoft pseudopotentials or PAW; to spin-unpolarized or polarized cases or to non-collinear magnetization. Furthermore, ACE is compatible with, and takes advantage of, all available parallelization levels implemented in Quantum ESPRESSO: over plane waves, over $\\mathbf{k}$ points, and over bands. \n\nWith ACE, the action of the exchange operator is rewritten as \n\n$$\n|\\hat{V}_{x}\\phi_{i}\\rangle\\simeq\\sum_{j m}|\\xi_{j}\\rangle(M^{-1})_{j m}\\langle\\xi_{m}|\\phi_{i}\\rangle,\n$$ \n\nwhere $|\\xi_{i}\\rangle=\\hat{V}_{x}|\\psi_{i}\\rangle$ and $M_{j m}=\\langle\\psi_{j}|\\xi_{m}\\rangle$ . At self-consistency, ACE becomes exact for $\\phi_{i}$ ’s in the occupied manifold of KS states. It is straightforward to implement ACE in the doubleloop structure of PWscf. The new algorithm is significantly faster while not introducing any loss of accuracy at conv­ ergence. Benchmark tests on a single processor show a $3\\times$ to $4\\times$ speedup for typical calculations in molecules, up to $6\\times$ in extended systems [45]. \n\nAn additional speedup may be achieved by using a reduced FFT cutoff in the solution of Poisson equations. In equation  (1), the exact FFT algorithm requires a FFT grid containing $G$ -vectors up to a modulus $G_{\\mathrm{max}}=2G_{c}$ , where $G_{c}$ is the largest modulus of $G$ -vectors in the plane-wave basis used to expand $\\psi_{i}$ and $\\phi_{j}.$ , or, in terms of kinetic energy cutoff, up to a cutoff $E_{x}=4E_{c}$ , where $E_{c}$ is the plane-wave cutoff. The presence of a $1/{G}^{2}$ factor in the reciprocal space expression suggests, and experience confirms, that this condition can be relaxed to $E_{x}\\sim2E_{c}$ with little loss of precision, down to $E_{x}=E_{c}$ at the price of increasing somewhat this loss [46]. The kinetic-energy cutoff for Fock-exchange computations can be tuned by specifying the keyword ecutfock in input. \n\nHybrid functionals have also been extended to the case of ultrasoft pseudopotentials and to PAW, following the method of [47]. A large number of integrals involving augmentation charges $q_{l m}$ are needed in this case, thus offsetting the advantage of a smaller plane-wave basis set. Better performances are obtained by exploiting the localization of the $q_{l m}$ and computing the related terms in real space, at the price of small aliasing errors. \n\nThese improvements allow to significantly speed up a calcul­ation, or to execute it on a larger number of processors, thus extending the reach of calculations with hybrid functionals. The bottleneck represented by the sum over bands and by the FFT in equation (1) is however still present: ACE just reduces the number of such expensive calculations, but does not eliminate them. In order to achieve a real breakthrough, one has to get rid of delocalized bands and FFTs, moving to a representation of the electronic structure in terms of localized orbitals. Work along this line using the selected column density matrix localization scheme [48, 49] is ongoing. In the next section we describe a different approach, implemented in the CP code, based on maximally localized Wannier functions (MLWF). \n\n2.1.1.2. Ab initio molecular dynamics using maximally localized Wannier functions.  The CP code can now perform highly efficient hybrid-functional ab initio MD using MLWFs [50] $\\big\\{\\overline{{\\varphi}}_{i}\\big\\}$ to represent the occupied space, instead of the canonical KS orbitals $\\{\\psi_{i}\\}$ , which are typically delocalized over the entire simulation cell. The MLWF localization procedure can be written as a unitary transformation, $\\begin{array}{r}{\\overline{{\\varphi}}_{i}({\\bf r})=\\sum_{j}U_{i j}\\psi_{j}({\\bf r}).}\\end{array}$ where $U_{i j}$ is computed at each MD time step by minimizing the total spread of the orbitals via a second-order damped dynamics scheme, starting with the converged $U_{i j}$ from the previous time step as initial guesses [51]. \n\nThe natural sparsity of the exchange interaction provided by a localized representation of the occupied orbitals (at least in systems with a finite band gap) is efficiently exploited during the evaluation of exact-exchange based applications (e.g. hybrid DFT functionals). This is accomplished by computing each of the required pair-exchange potentials $\\overline{{v}}_{i j}(\\mathbf{r})$ (corresponding to a given localized pair-density $\\overline{{\\rho}}_{i j}(\\mathbf{r}))$ through the numerical solution of the Poisson equation: \n\n$$\n\\nabla^{2}\\overline{{v}}_{i j}(\\mathbf{r})=-4\\pi\\overline{{\\rho}}_{i j}(\\mathbf{r}),\\qquad\\overline{{\\rho}}_{i j}(\\mathbf{r})=\\overline{{\\varphi}}_{i}^{*}(\\mathbf{r})\\overline{{\\varphi}}_{j}(\\mathbf{r})\n$$ \n\nusing finite differences on the real-space grid. Discretizing the Laplacian operator $(\\nabla^{2})$ using a 19-point central-difference stencil (with an associated $\\mathcal{O}(h^{6})$ accuracy in the grid spacing $h$ ), the resulting sparse linear system of equations is solved using the conjugate-gradient technique subject to the boundary conditions imposed by a multipolar expansion of $\\overline{{v}}_{i j}(\\mathbf{r})$ : \n\n$$\n\\overline{{v}}_{i j}(\\mathbf{r})=4\\pi\\sum_{l m}\\frac{Q_{l m}}{2l+1}\\frac{Y_{l m}(\\theta,\\phi)}{r^{l+1}},\\qquadQ_{l m}=\\int\\mathrm{d}\\mathbf{r}Y_{l m}^{*}(\\theta,\\phi)r^{l}\\overline{{\\rho}}_{i j}(\\mathbf{r})\n$$ \n\nin which the $Q_{l m}$ are the multipoles describing $\\overline{{\\rho}}_{i j}(\\mathbf{r})$ [42–44]. \n\nSince $\\overline{{v}}_{i j}(\\mathbf{r})$ only needs to be evaluated for overlapping pairs of MLWFs, the number of Poisson equations that need to be solved is substantially decreased from $\\mathcal{O}(N_{b}^{2})$ to $\\mathcal{O}(N_{b})$ . In addition, $\\overline{{v}}_{i j}(\\mathbf{r})$ only needs to be solved on a subset of the real-space grid (that is in general of fixed size) that encompasses the overlap between a given pair of MLWFs. This further reduces the overall computational effort required to evaluate exact-exchange related quantities and results in a linear-scaling $(\\mathcal{O}(N_{b}))$ algorithm. As such, this framework for performing exact-exchange calculations is most efficient for non-metallic systems (i.e. systems with a finite band gap) in which the occupied KS orbitals can be efficiently localized. \n\nThe MLWF representation not only yields the exactexchange energy $E_{\\mathrm{xx}}$ , \n\n$$\nE_{\\mathrm{xx}}=-e^{2}\\sum_{i j}\\int\\mathrm{d}\\mathbf{r}\\overline{{\\rho}}_{i j}(\\mathbf{r})\\overline{{v}}_{i j}(\\mathbf{r}),\n$$ \n\nat a significantly reduced computational cost, but it also provides an amenable way of computing the exactexchange contributions to the (MLWF) wavefunction forces, $\\begin{array}{r}{\\overline{{D}}_{x x}^{i}({\\bf r})=e^{2}\\sum_{j}\\overline{{v}}_{i j}({\\bf r})\\overline{{\\varphi}}_{j}({\\bf r}).}\\end{array}$ , which serve as the central quanti­ ties in Car–Parrinello MD simulations [53]. Moreover, the exact-exchange contributions to the stress tensor are readily available, thereby providing a general code base which enables hybrid DFT based simulations in the NVE, NVT, and NPT ensembles for simulation cells of any shape [44]. We note in passing that applications of the current implementation of this MLWF-based exact-exchange algorithm are limited to $\\Gamma$ -point calculations employing norm-conserving pseudo-potentials. \n\nThe MLWF-based exact-exchange algorithm in CP employs a hybrid MPI/OpenMP parallelization strategy that has been extensively optimized for use on large-scale massively-parallel (super-) computer architectures. The required set of Poisson equations—each one treated as an independent task—are distributed across a large number of MPI ranks/ processes using a task distribution scheme designed to minimize the communication and to balance computational workload. Performance profiling demonstrates excellent scaling up to 30 720 cores (for the $\\alpha$ -glycine molecular crystal, see figure 1) and up to 65 536 cores (for $\\left(\\mathrm{H}_{2}\\mathrm{O}\\right)_{256}$ , see [43]) on Mira (BG/Q) with extremely promising efficiency. In fact, this algorithm has already been successfully applied to the study of long-time MD simulations of large-scale condensed-phase systems such as $\\mathrm{(H}_{2}\\mathrm{O})_{128}$ [43, 52]. For more details on the performance and implementation of this exact-exchange algorithm, we refer the reader to [44]. \n\n2.1.2.  Dispersion interactions.  Dispersion, or van der Waals, interactions arise from dynamical correlations among charge fluctuations occurring in widely separated regions of space. The resulting attraction is a non-local correlation effect that cannot be reliably captured by any local (such as local density approximation, LDA) or semi-local (generalized gradient approximation, GGA) functional of the electron density [54]. Such interactions can be either accounted for by a truly non-local exchange-correlation (XC) functional, or modeled by effective interactions amongst atoms, whose parameters are either computed from first principles or estimated semiempirically. In Quantum ESPRESSO both approaches are implemented. Non-local XC functionals are activated by selecting them in the input_dft variable, while explicit interactions are turned on with the vdw_corr option. From the latter group, DFT-D2 [10], Tkatchenko–Scheffler [11], and exchange-hole dipole moment models [12, 13] are cur­ rently implemented (DFT-D3 [55] and the many-body dispersion (MBD) [56–58] approaches are already available in a development version). \n\n2.1.2.1. Non-local van der Waals density functionals.  A fully non-local correlation functional able to account for van der Waals interactions for general geometries was first developed in 2004 and named vdW-DF [59]. Its development is firmly rooted in many-body theory, where the so-called adiabatic connection fluctuation-dissipation theorem (ACFD) \n\n[60] provides a formally exact expression for the XC energy through a coupling constant integration over the response function—see section 2.1.4. A detailed review of the vdW-DF formalism is provided in [9]. The overall XC energy given by the ACFD theorem—as a functional of the electron density $n$ —is then split in vdW-DF into a GGA-type XC part $E_{\\mathrm{xc}}^{0}[n]$ and a truly non-local correlation part $E_{\\mathrm{c}}^{\\mathrm{nl}}[n].$ i.e. \n\n$$\nE_{\\mathrm{xc}}[n]=E_{\\mathrm{xc}}^{0}[n]+E_{\\mathrm{c}}^{\\mathrm{nl}}[n],\n$$ \n\nwhere the non-local part is responsible for the van der Waals forces. Through a second-order expansion in the plasmonresponse expression used to approximate the response function, the non-local part turns into a computationally tractable form involving a universal kernel $\\Phi(\\mathbf{r},\\mathbf{r}^{\\prime})$ , \n\n$$\nE_{\\mathrm{c}}^{\\mathrm{nl}}[n]=\\frac{1}{2}\\int\\mathrm{d}\\mathbf{r}\\mathrm{d}\\mathbf{r}^{\\prime}n(\\mathbf{r})\\Phi(\\mathbf{r},\\mathbf{r}^{\\prime})n(\\mathbf{r}^{\\prime}).\n$$ \n\nThe kernel $\\Phi(\\mathbf{r},\\mathbf{r}^{\\prime})$ depends on $\\mathbf{r}$ and $\\mathbf{r}^{\\prime}$ only through $q_{0}(\\mathbf{r})|\\mathbf{r}-\\mathbf{r}^{\\prime}|$ and $q_{0}(\\mathbf{r}^{\\prime})|\\mathbf{r}-\\mathbf{r}^{\\prime}|$ , where $q_{0}(\\mathbf{r})$ is a function of $n(\\mathbf{r})$ and $\\nabla n(\\mathbf{r})$ . As such, the kernel can be pre-calculated, tabulated, and stored in some external file. To make the scheme self-consistent, the XC potential $V_{\\mathrm{c}}^{\\mathrm{nl}}({\\bf r})={\\delta E_{\\mathrm{c}}^{\\mathrm{nl}}[n]}/{\\delta n({\\bf r})}$ also needs to be computed [61]. The evaluation of $E_{\\mathrm{c}}^{\\mathrm{nl}}[n]$ in equation  (8) is computationally expensive. In addition, the evaluation of the corresponding potential $V_{\\mathrm{c}}^{\\mathrm{nl}}(\\mathbf{r})$ requires one spatial integral for each point r. A significant speedup can be achieved by writing the kernel in terms of splines [62] \n\n$$\n\\begin{array}{l}{\\displaystyle\\Phi(\\mathbf{r},\\mathbf{r}^{\\prime})=\\Phi\\big(q_{0}(\\mathbf{r}),q_{0}(\\mathbf{r}^{\\prime}),|\\mathbf{r}-\\mathbf{r}^{\\prime}|\\big)}\\\\ {\\approx\\displaystyle\\sum_{\\alpha\\beta}\\Phi\\big(q_{\\alpha},q_{\\beta},|\\mathbf{r}-\\mathbf{r}^{\\prime}|\\big)p_{\\alpha}\\big(q_{0}(\\mathbf{r})\\big)p_{\\beta}\\big(q_{0}(\\mathbf{r}^{\\prime})\\big),}\\end{array}\n$$ \n\nwhere $q_{\\alpha}$ are fixed values and $p_{\\alpha}$ are cubic splines. Equation (8) then becomes a convolution that can be simplified to \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\cal E}_{\\mathrm{c}}^{\\mathrm{nl}}[n]=\\frac{1}{2}\\sum_{\\alpha\\beta}\\int\\mathrm{d}{\\bf r}\\mathrm{d}{\\bf r}^{\\prime}\\theta_{\\alpha}({\\bf r})\\Phi_{\\alpha\\beta}(|{\\bf r}-{\\bf r}^{\\prime}|)\\theta_{\\beta}({\\bf r}^{\\prime})}}\\\\ {{\\displaystyle~=\\frac{1}{2}\\sum_{\\alpha\\beta}\\int\\mathrm{d}{\\bf k}\\theta_{\\alpha}^{*}({\\bf k})\\Phi_{\\alpha\\beta}(k)\\theta_{\\beta}({\\bf k}).}}\\end{array}\n$$ \n\nHere $\\theta_{\\alpha}(\\mathbf{r})=n(\\mathbf{r})p_{\\alpha}{\\big(}q_{0}(\\mathbf{r}){\\big)}$ and $\\theta_{\\alpha}(\\mathbf{k})$ is its Fourier transform. Accordingly, $\\Phi_{\\alpha\\beta}(k)$ is the Fourier transform of the original kernel $\\Phi_{\\alpha\\beta}(r)=\\Phi(q_{\\alpha},q_{\\beta},|\\mathbf{r}-\\mathbf{r}^{\\prime}|)$ . Thus, two spatial integrals are replaced by one integral over Fourier transformed quantities, resulting in a considerable speedup. This approach also provides a convenient evaluation for $V_{\\mathrm{c}}^{\\mathrm{nl}}(\\mathbf{r})$ . \n\nThe vdW-DF functional was implemented in Quantum ESPRESSO version 4.3, following equation  (10). As a result, in large systems, compute times in vdW-DF calculations are only insignificantly longer than for standard GGA functionals. The implementation uses a tabulation of the Fourier transformed kernel $\\Phi_{\\alpha\\beta}(k)$ from equation  (10) that is computed by an auxiliary code, generate_vdW_kernel_table.x, and stored in the external file vdW_kernel_table. The file then has to be placed either in the directory where the calculation is run or in the directory where the corresponding pseudopotentials reside. The formalism for vdW-DF stress was derived and implemented in [63]. The proper spin extension of vdW-DF, termed svdW-DF [64], was implemented in Quantum ESPRESSO version 5.2.1. \n\n![](images/6dc32e909093b4944a9db836051e88f3160276bbccbc1f63b86a61cc3d50882d.jpg) \nFigure 1.  Strong (left) and weak (right) scaling plots on Mira (BG/Q) for hybrid-DFT simulations of the $\\alpha$ -glycine molecular crystal polymorph using the linear-scaling exact-exchange algorithm in CP. In these plots, unit cells containing 16–64 glycine molecules (160–640 atoms, 240–960 bands) were considered as a function of $z$ , the number of MPI ranks per band $(z=0.5-2)$ . On Mira, 30 720 cores (1920 MPI ranks $\\times16$ OpenMP threads/rank $\\times1$ core/OpenMP thread) were utilized for the largest system (gly064, $z=2$ ), retaining over $88\\%$ (strong scaling) and $80\\%$ (weak scaling) of the ideal efficiencies (dashed lines). Deviations from ideal scaling are primarily due to the FFT (which scales non-linearly) required to provide the MLWFs in real space. \n\nAlthough the ACFD theorem provides guidelines for the total XC functional in equation  (7), in practice $E_{\\mathrm{xc}}^{0}[n]$ is approximated by simple GGA-type functional forms. This has been used to improve vdW-DF—and correct the often too large binding separations found in its original form—by optimizing the exchange contribution to $E_{\\mathrm{xc}}^{0}[n]$ . The naming convention for the resulting variants is that the extension should describe the exchange functional used. In this context, the functionals vdW-DF-C09 [65], vdW-DF-obk8 [66], vdW-DF-ob86 [67], and vdW-DF-cx [68] have been developed and implemented in Quantum ESPRESSO. While all of these variants use the same kernel to evaluate $E_{\\mathrm{c}}^{\\mathrm{nl}}[n].$ , advances have also been made in slightly adjusting the kernel form, which is referred to and implemented as vdW-DF2 [69]. A corresponding variant, i.e. vdW-DF2-b86r [70], is also implemented. Note that vdWDF2 uses the same kernel file as vdW-DF. \n\nThe functional VV10 [71] is related to vdW-DF, but adheres to fewer exact constraints and follows a very different design philosophy. It is implemented in Quantum ESPRESSO in a form called rVV10 [72] and uses a different kernel and kernel file that can be generated by running the auxiliary code generate_vdW_kernel_table.x. \n\n2.1.2.2. Interatomic pairwise dispersion corrections.  An alternative approach to accounting for dispersion forces is to add to the XC energy $E_{\\mathrm{xc}}^{0}$ a dispersion energy, $E_{\\mathrm{disp}}$ , written as a damped asymptotic pairwise expression: \n\n$$\nE_{\\mathrm{xc}}=E_{\\mathrm{xc}}^{0}+E_{\\mathrm{disp}},\\qquadE_{\\mathrm{disp}}=-{\\frac{1}{2}}\\sum_{n=6,8,10}\\sum_{I\\ne J}{\\frac{C_{I J}^{(n)}f_{n}(R_{I J})}{R_{I J}^{n}}}\n$$ \n\nwhere $I$ and $J$ run over atoms, $R_{I J}=|\\mathbf{R}_{I}-\\mathbf{R}_{J}|$ is the interatomic distance between atoms $I$ and $J$ , and $f_{n}(R)$ is a suitable damping function. The interatomic dispersion coefficients $C_{I J}^{(n)}$ can be derived from fits, as in DFT-D2 [10], or calculated non-empirically, as in the Tkatchenko–Scheffler (TS-vdW) [11] and exchange-hole dipole moment (XDM) models [12, 13]. \n\nIn XDM, the $C_{I J}^{(n)}$ coefficients are calculated assuming that dispersion interactions arise from the electrostatic attraction between the electron-plus-exchange-hole distributions on different atoms [12, 13]. In this way, XDM retains the simplicity of a pairwise dispersion correction, like in DFT-D2, but derives the $C_{I J}^{(n)}$ coefficients from the electronic properties of the system under study. The damping functions $f_{n}$ in equation  (11) suppress the dispersion interaction at short distances, and serve the purpose of making the link between the short-range correlation (provided by the XC functional) and the long-range dispersion energy, as well as mitigating erroneous behavior from the exchange functional in the representation of intermolecular repulsion [13]. The damping functions contain two adjustable parameters, available online [73] for a number of popular density functionals. Although any functional for which damping parameters are available can be used, the functionals showing best performance when combined with XDM appear to be B86bPBE [74, 75] and PW86PBE [75, 76], thanks to their accurate modeling of Pauli repulsion [13]. Both functionals have been implemented in Quantum ESPRESSO since version 5.0. \n\nIn the canonical XDM implementation, recently included in Quantum ESPRESSO and described in detail elsewhere [77], the dispersion coefficients are calculated from the electron density, its derivatives, and the kinetic energy density, and assigned to the different atoms in the system using a Hirshfeld atomic partition scheme [78]. This means that XDM is effectively a meta-GGA functional of the dispersion energy whose evaluation cost is small relative to the rest of the self-consistent calculation. Despite the conceptual and computational simplicity of XDM, and because the dispersion coefficients depend upon the atomic environment in a physically meaningful way, the XDM dispersion correction offers good performance in the calculation of diverse properties, such as lattice energies, crystal geometries, and surface adsorption energies. XDM is especially good for modeling organic crystals and organic/inorganic interfaces. For a recent review, see [13]. \n\nThe XDM dispersion calculation is turned on by specifying vdw_corr $\\scriptstyle\\gamma=\\prime\\ \\_{\\mathrm{XClm}}\\prime$ and optionally selecting appropriate damping function parameters (with the xdm_a1 and xdm_a2 keywords). Because the reconstructed all-electron densities are required during self-consistency, XDM can be used only in combination with a PAW approach. The XDM contribution to forces and stress is not entirely consistent with the energies because the current implementation neglects the change in the dispersion coefficients. Work is ongoing to remove this limitation, as well as to make XDM available for Car–Parrinello MD, in future Quantum ESPRESSO releases. \n\nIn the TS-vdW approach $(\\mathrm{vdw\\_corr}\\mathrm{r}\\mathrm{=}^{\\prime}\\mathrm{t}\\mathrm{s}\\mathrm{-}\\mathrm{vdw}^{\\prime})$ , all vdW parameters (which include the atomic dipole polarizabilities, $\\alpha_{I}$ , vdW radii, $R_{I}^{0}$ , and interatomic $C_{I J}^{(6)}$ dispersion coefficients) are functionals of the electron density and computed using the Hirshfeld partitioning scheme [78] to account for the unique chemical environment surrounding each atom. This approach is firmly based on a fluctuating quantum harmonic oscillator (QHO) model and results in highly accurate $C_{I J}^{(6)}$ coefficients with an associated error of approximately $5.5\\%$ [11]. The TS-vdW approach requires a single empirical range-separation parameter based on the underlying XC functional and is recommended in conjunction with non-empirical DFT functionals such as PBE and PBE0. For a recent review of the TS-vdW approach and several other vdW/dispersion corrections, please see [79]. \n\nThe implementation of the density-dependent TS-vdW correction in Quantum ESPRESSO is fully self-consistent [80] and currently available for use with norm-conserving pseudo-potentials. An efficient linear-scaling implementation of the TS-vdW contribution to the ionic forces and stress tensor allows for Born–Oppenheimer and Car–Parrinello MD simulations at the DFT $+$ TS-vdW level of theory; this approach has already been successfully employed in longtime MD simulations of large-scale condensed-phase systems such as $\\mathrm{(H}_{2}\\mathrm{O})_{128}$ [43, 52]. We note in passing that the Quantum ESPRESSO implementation of the TS-vdW correction also includes analytical derivatives of the Hirshfeld weights, thereby completely reflecting the change in all TS-vdW parameters during geometry/cell optimizations and MD simulations. \n\n2.1.3.  Hubbard-corrected functionals: DFT+U.  Most approximate XC functionals used in modern DFT codes fail quite spectacularly on systems with atoms whose ground-state electronic structure features partially occupied, strongly localized orbitals (typically of the $d$ or $f$ kind), that suffer from strong self-interaction effects and a poor description of electronic correlations. In these circumstances, $\\tt D F T+U$ is often, although not always, an efficient remedy. This method is based on the addition to the DFT energy functional $E_{\\mathrm{DFT}}$ of a correction $E_{U}$ , shaped on a Hubbard model Hamiltonian: $E_{\\mathrm{DFT+}U}=E_{\\mathrm{DFT}}+E_{U}$ . The original implementation in \n\nQuantum ESPRESSO, extensively described in [81, 82], is based on the simplest rotationally invariant formulation of $E_{U}$ , due to Dudarev and coworkers [83]: \n\n$$\nE_{U}=\\frac{1}{2}\\sum_{I}U^{I}\\sum_{m,\\sigma}\\left\\{n_{m m}^{I\\sigma}-\\sum_{m^{\\prime}}n_{m m^{\\prime}}^{I\\sigma}n_{m^{\\prime}m}^{I\\sigma}\\right\\},\n$$ \n\nwhere \n\n$$\nn_{m m^{\\prime}}^{I\\sigma}=\\sum_{\\mathbf{k},\\nu}f_{\\mathbf{k}\\nu}^{\\sigma}\\langle\\psi_{\\mathbf{k}\\nu}^{\\sigma}\\vert\\phi_{m}^{I}\\rangle\\langle\\phi_{m^{\\prime}}^{I}\\vert\\psi_{\\mathbf{k}\\nu}^{\\sigma}\\rangle,\n$$ \n\n$|\\psi_{{\\bf k}\\nu}^{\\sigma}\\rangle$ is the valence electronic wave function for state $\\mathbf{k}\\nu$ of spin $\\sigma$ , $f_{{\\bf k}\\nu}^{\\sigma}$ is the corresponding occupation number, $\\vert\\phi_{m}^{I}\\rangle$ is the chosen Hubbard manifold of atomic orbitals, centered on atomic site $I$ , that may be orthogonalized or not. The presence of the Hubbard functional results in extra terms in energy derivatives such as forces, stresses, elastic constants, or forceconstant (dynamical) matrices. For instance, the additional term in forces is \n\n$$\n\\mathbf{F}_{I\\alpha}^{U}=-\\frac{1}{2}\\sum_{I,m,m^{\\prime},\\sigma}U^{I}\\left(\\delta_{m m^{\\prime}}-2n_{m m^{\\prime}}^{I\\sigma}\\right)\\frac{\\partial n_{m m^{\\prime}}^{I\\sigma}}{\\partial R_{I\\alpha}}\n$$ \n\nwhere $R_{I\\alpha}$ is the $\\alpha$ component of position for atom $I$ in the unit cell, \n\n$$\n\\begin{array}{c}{\\displaystyle\\frac{\\partial n_{m m^{\\prime}}^{I\\sigma}}{\\partial R_{I\\alpha}}=\\sum_{\\mathbf{k},\\nu}f_{\\mathbf{k}\\nu}^{\\sigma}\\left(\\left\\langle\\psi_{\\mathbf{k}\\nu}^{\\sigma}\\left\\vert\\frac{\\partial\\phi_{m}^{I}}{\\partial R_{I\\alpha}}\\right\\rangle\\langle\\phi_{m^{\\prime}}^{I}\\vert\\psi_{\\mathbf{k}\\nu}^{\\sigma}\\rangle\\right.\\right.}\\\\ {\\displaystyle\\left.\\left.+\\langle\\psi_{\\mathbf{k}\\nu}^{\\sigma}\\vert\\phi_{m}^{I}\\rangle\\left\\langle\\frac{\\partial\\phi_{m^{\\prime}}^{I}}{\\partial R_{I\\alpha}}\\right\\vert\\psi_{\\mathbf{k}\\nu}^{\\sigma}\\right\\rangle\\right).}\\end{array}\n$$ \n\n2.1.3.1. Recent extensions of the formulation.  As a correction to the total energy, the Hubbard functional naturally contributes an extra term to the total potential that enters the KS equations. An alternative formulation [14] of the $\\mathrm{DFT+U}$ method, recently introduced and implemented in Quantum ESPRESSO for transport calculations, eliminates the need of extra terms in the potential by incorporating the Hubbard correction directly into the (PAW) pseudopotentials through a renormalization of the coefficients of their nonlocal terms. \n\nA simple extension to the Dudarev functional, $\\mathrm{\\DeltaDFT+U+J0}$ , was proposed in [15] and used to capture the insulating ground state of $\\mathrm{CuO}$ . In $\\mathtt{C u O}$ the localization of holes on the $d$ states of $\\mathrm{cu}$ and the consequent on-set of a magnetic ground state can only be stabilized against a competing tendency to hybridize with oxygen $p$ states when on-site exchange interactions are precisely accounted for. A simplified functional, depending upon the on-site (screened) Coulomb interaction $U$ and the Hund’s coupling $J$ , can be obtained from the full second-quantization formulation of the electronic interaction potential by keeping only on-site terms that describe the interaction between up to two orbitals and by approximating on-site effective interactions with the (orbital-independent) atomic averages of Coulomb and exchange terms: \n\n$$\nE_{U+J}=\\sum_{I,\\sigma}\\frac{U^{I}-J^{I}}{2}\\operatorname{Tr}\\Big[\\mathbf{n}^{I\\sigma}\\left(\\mathbf{1}-\\mathbf{n}^{I\\sigma}\\right)\\Big]+\\sum_{I,\\sigma}\\frac{J^{I}}{2}\\operatorname{Tr}\\Big[\\mathbf{n}^{I\\sigma}\\mathbf{n}^{I-\\sigma}\\Big].\n$$ \n\nThe on-site exchange coupling $J^{I}$ not only reduces the effective Coulomb repulsion between like-spin electrons as in the simpler Dudarev functional (first term of the right-hand side), but also contributes a second term that acts as an extra penalty for the simultaneous presence of anti-aligned spins on the same atomic site and further stabilizes ferromagnetic ground states. \n\nThe fully rotationally invariant scheme of Liechtenstein et al [84], generalized to non-collinear magnetism and twocomponent spinor wave-functions, is also implemented in the current version of Quantum ESPRESSO. The corrective energy term for each correlated atom can be quite generally written as: \n\n$$\n\\begin{array}{r l}{\\displaystyle}&{E_{U}^{\\mathrm{full}}=\\frac{1}{2}\\sum_{\\alpha\\beta\\gamma\\delta}U_{\\alpha\\beta\\gamma\\delta}\\langle c_{\\alpha}^{\\dagger}c_{\\beta}^{\\dagger}c_{\\delta}c_{\\gamma}\\rangle_{\\mathrm{DFT}}}\\\\ {\\displaystyle}&{=\\frac{1}{2}\\sum_{\\alpha\\beta\\gamma\\delta}\\big(U_{\\alpha\\beta\\gamma\\delta}-U_{\\alpha\\beta\\delta\\gamma}\\big)n_{\\alpha\\gamma}n_{\\beta\\delta},}\\end{array}\n$$ \n\nwhere the average is taken over the DFT Slater determinant, $U_{\\alpha\\beta\\gamma\\delta}$ are Coulomb integrals, and some set of orthonormal spin-space atomic functions, $\\{\\alpha\\}$ , is used to calculate the occupation matrix, $n_{\\alpha\\beta}$ , via equation (13). These basis functions could be spinor wave functions of total angular momentum $j=l\\pm1/2$ , originated from spherical harmonics of orbital momentum $l$ , which is a natural choice in the presence of spin–orbit coupling. Another choice, adopted in our implementation, is to use the standard basis of separable atomic functions, $R_{l}(r)Y_{l m}(\\theta,\\phi)\\chi(\\sigma)$ , where $\\chi(\\sigma)$ are spin up/down projectors and the radial function, $R_{l}(r)$ , is an eigenfunction of the pseudo-atom. In the presence of spin–orbit coupling, the radial function is constructed by averaging between the two radial functions $R_{l\\pm1/2}$ . These radial functions are read from the file containing the pseudopotential, in this case a fully-relativistic one. In this conventional basis, the corrective functional takes the form: \n\n$$\nE_{U}^{\\mathrm{{full}}}=\\frac{1}{2}\\sum_{i j k l,\\sigma\\sigma^{\\prime}}U_{i j k l}n_{i k}^{\\sigma\\sigma}n_{j l}^{\\sigma^{\\prime}\\sigma^{\\prime}}-\\frac{1}{2}\\sum_{i j k l,\\sigma\\sigma^{\\prime}}U_{i j l k}n_{i k}^{\\sigma\\sigma^{\\prime}}n_{j l}^{\\sigma^{\\prime}\\sigma},\n$$ \n\nwhere $\\{i j k l\\}$ run over azimuthal quantum number $m$ . The second term contains a spin-flip contribution if $\\sigma^{\\prime}\\neq\\sigma$ . For collinear magnetism, when $n_{i j}^{\\sigma\\sigma^{\\prime}}=\\delta_{\\sigma\\sigma^{\\prime}}n_{i j}^{\\sigma}$ , the present form­ ulation reduces to the scheme of Liechtenstein et al [84]. All Coulomb integrals, $U_{i j k l}$ , can be parameterized by few input parameters such as $U$ (s-shell); $U$ and $J$ $\\overset{\\cdot}{p}$ -shell); $U,J$ and $B$ ( $\\mathit{\\Pi}_{M}$ -shell); $U,J,E_{2}$ , and $E_{3}$ $f$ -shell), and so on. We note that if all parameters but $U$ are set to zero, the Dudarev functional is recovered. \n\n2.1.3.2. Calculation of Hubbard parameters.  The Hubbard corrective functional $E_{U}$ depends linearly upon the effective on-site interactions, $U^{I}$ . Therefore, using a proper value for these interaction parameters is crucial to obtain quantitatively reliable results from $\\mathrm{\\DeltaDFT+U}$ calculations. The Quantum ESPRESSO implementation of $\\tt D F T+U$ has also been the basis to develop a method for the calcul­ation of $U$ [81], based on linear-response theory. This method is fully ab initio and provides values of the effective interactions that are consistent with the system and with the ground state that the Hubbard functional aims at correcting. A comparative analysis of this method with other approaches proposed in the literature to compute the Hubbard interactions has been initiated in [82] and will be further refined in forthcoming publications by the same authors. \n\nWithin linear-response theory, the Hubbard interactions are the elements of an effective interaction matrix, computed as the difference between bare and screened inverse susceptibilities [81]: \n\n$$\nU^{I}=\\big(\\chi_{0}^{-1}-\\chi^{-1}\\big)_{I I}.\n$$ \n\nIn equation  (19) the susceptibilities $\\chi$ and $\\chi_{0}$ measure the response of atomic occupations to shifts in the potential acting on the states of single atoms in the system. In particular, $\\chi$ is defined as $\\begin{array}{r}{\\chi_{I J}=\\sum_{m\\sigma}\\left(d n_{m m}^{I\\sigma}/d\\alpha^{J}\\right)}\\end{array}$ and is evaluated at self consistency, while $\\chi_{0}$ has a similar definition but is computed before the self-consistent re-adjustment of the Hartree and XC potentials. In the current implementation these susceptibilities are computed from a series of self-consistent total energy calculations (varying the strength $\\alpha$ of the perturbing potential over a range of values) performed on supercells of sufficient size for the perturbations to be isolated from their periodic replicas. While easy to implement, this approach is quite cumbersome to use, requiring multiple calculations, expensive convergence tests of the resulting parameters and complex post-processing tools. \n\nThese difficulties can be overcome by using density-functional perturbation theory (DFpT) to automatize the calcul­ ation of the Hubbard parameters. The basic idea is to recast the entries of the susceptibility matrices into sums over the BZ: \n\n$$\n\\frac{\\mathrm{d}n_{m m^{\\prime}}^{I\\sigma}}{\\mathrm{d}\\alpha^{J}}=\\frac{1}{N_{\\mathbf{q}}}\\sum_{\\mathbf{q}}^{N_{\\mathbf{q}}}\\mathrm{e}^{\\mathrm{i}\\mathbf{q}\\cdot\\left(\\mathbf{R}_{l}-\\mathbf{R}_{l^{\\prime}}\\right)}\\Delta_{\\mathbf{q}}^{s^{\\prime}}n_{m m^{\\prime}}^{s\\sigma},\n$$ \n\nwhere $I\\equiv(l,s)$ and $J\\equiv(l^{\\prime},s^{\\prime})$ , $l$ and $l^{\\prime}$ label unit cells, $s$ and $s^{\\prime}$ label atoms in the unit cell, $\\mathbf{R}_{l}$ and $\\mathbf{R}_{l^{\\prime}}$ are Bravais lattice vectors, and $\\Delta_{\\mathbf{q}}^{s^{\\prime}}n_{m m^{\\prime}}^{s\\sigma}$ represent the (lattice-periodic) response of atomic occupations to monochromatic perturbations constructed by modulating the shift to the potential of all the periodic replicas of a given atom by a wave-vector $\\mathbf{q}$ . This quantity is evaluated within DFpT (see section  2.2), using linear-response routines contained in LR_Modules (see section  3.4.3). This approach eliminates the need for supercell calculations in periodic systems (along with the cubic scaling of their computational cost) and automatizes complex postprocessing operations needed to extract $U$ from the output of calculations. The use of DFpT also offers the perspective to directly evaluate inverse susceptibilities, thus avoiding the matrix inversions of equation  (19), and to calculate the Hubbard parameters for closed-shell systems, a notorious problem for schemes based on perturbations to the potential. Full details about this implementation will be provided in a forthcoming publication [85] and the corresponding code will be made available in one of the next Quantum ESPRESSO releases. \n\n2.1.4.  Adiabatic-connection fluctuation-dissipation theory.  In the quest for better approximations for the unknown XC energy functional in KS-DFT, the approach based on the adiabatic connection fluctuation-dissipation (ACFD) theorem [60] has received considerable interest in recent years. This is largely due to some attractive features: (i) a formally exact expression for the XC energy in term of density linear response functions can be derived providing a promising way for a systematic improvement of the XC functional; (ii) the method treats the exchange energy exactly, thus canceling out the spurious selfinteraction error present in the Hartree energy; (iii) the correlation energy is fully non local and automatically includes long-range van der Waals interactions (see section 2.1.2.1). \n\nWithin the ACFD framework a formally exact expression for the XC energy $E_{\\mathrm{xc}}$ of an electronic system can be derived: \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\cal E}_{\\mathrm{xc}}=-\\frac{\\hbar}{2\\pi}\\int_{0}^{1}\\mathrm{d}\\lambda\\int\\mathrm{d}{\\bf r}\\mathrm{d}{\\bf r}^{\\prime}\\frac{e^{2}}{\\left|{\\bf r}-{\\bf r}^{\\prime}\\right|}}\\ ~}\\\\ {{\\displaystyle~\\times\\left[\\int_{0}^{\\infty}\\chi_{\\lambda}({\\bf r},{\\bf r}^{\\prime},\\mathrm{i}u)\\mathrm{d}u+\\delta({\\bf r}-{\\bf r}^{\\prime})n({\\bf r})\\right]},}\\end{array}\n$$ \n\nwhere $\\hbar=h/2\\pi$ and $h$ is the Planck constant, $\\chi_{\\lambda}(\\mathbf{r},\\mathbf{r}^{\\prime};\\mathrm{i}u)$ is the density response function at imaginary frequency iu of a system whose electrons interact via a scaled Coulomb interaction, i.e. $\\lambda e^{2}/|\\mathbf{r}-\\mathbf{r}^{\\prime}|,$ and are subject to a local potential such that the electronic density $n(\\mathbf{r})$ is independent of $\\lambda$ , and is thus equal to the ground-state density of the fully interacting system ( $\\langle\\lambda=1$ ). The XC energy, equation (21), can be further separated into a KS exact-exchange energy $E_{\\mathrm{xx}}$ , equation (6), and a correlation energy $E_{\\mathrm{c}}$ . The former is routinely evaluated as in any hybrid functional calculation (see section 2.1.1). Using a matrix notation, the latter can be expressed in a compact form in terms of the Coulomb interaction, $v_{c}=e^{2}/|\\mathbf{r}-\\mathbf{r}^{\\prime}|$ , and of the density response functions: \n\n$$\nE_{\\mathrm{c}}=-\\frac{\\hbar}{2\\pi}\\int_{0}^{1}\\mathrm{d}\\lambda\\int_{0}^{\\infty}\\mathrm{d}u\\mathrm{tr}\\big[v_{c}[\\chi_{\\lambda}(\\mathrm{i}u)-\\chi_{0}(\\mathrm{i}u)]\\big].\n$$ \n\nFor $\\lambda>0$ , $\\chi_{\\lambda}$ can be related to the noninteracting density response function $\\chi_{0}$ via a Dyson equation  obtained from TDDFT: \n\n$$\n\\chi_{\\lambda}(\\mathbf{i}u)=\\chi_{0}(\\mathbf{i}u)+\\chi_{0}(\\mathbf{i}u)\\left[\\lambda v_{c}+f_{\\mathrm{xc}}^{\\lambda}(\\mathbf{i}u)\\right]\\chi_{\\lambda}(\\mathbf{i}u).\n$$ \n\nThe exact expression of the XC kernel $f_{\\mathrm{xc}}$ is unknown, and in practical applications one needs to approximate it. In the ACFDT package, the random phase approximation (RPA), obtained by setting $f_{\\mathrm{xc}}^{\\lambda}=0$ , and the RPA plus exact-exchange kernel (RPAx), obtained by setting $f_{\\mathrm{xc}}^{\\lambda}=\\lambda f_{\\mathrm{x}}$ , are implemented. The evaluation of the RPA and RPAx correlation energies is based on an eigenvalue decomposition of the noninteracting response functions and of its first-order correction in the limit of vanishing electron-electron interaction [86–88]. \n\nSince only a small number of these eigenvalues are relevant for the calculation of the correlation energy, an efficient iterative scheme can be used to compute the low-lying modes of the RPA/RPAx density response functions. \n\nThe basic operation required for the eigenvalue decomposition is a number of loosely coupled DFpT calculations for different imaginary frequencies and trial potentials. Although the global scaling of the iterative approach is the same as for implementations based on the evaluation of the full response matrices $(N^{4})$ , the number of operation involved is 100 to 1000 times smaller [87], thus largely reducing the global scaling pre-factor. Moreover, the calculation can be parallelized very efficiently by distributing different trial potentials on different processors or groups of processors. \n\nIn addition, the local EXX and RPA-correlation potentials can be computed through an optimized effective potential (OEP) scheme fully compatible with the eigenvalue decomposition strategy adopted for the evaluation of the EXX/RPA energy. Iterating the energy and the OEP calculations and using an effective mixing scheme to update the KS potential, a self-consistent minimization of the EXX/RPA functional can be achieved [89]. \n\n# 2.2.  Linear response and excited states without virtual orbitals \n\nOne of the key features of modern DFT implementations is that they do not require the calculation of virtual (unoccupied) orbitals. This idea, first pioneered by Car and Parrinello in their landmark 1985 paper [53] and later adopted by many groups world-wide, found its way in the computation of excited-state properties with the advent of density-functional perturbation theory (DFpT) [90–93]. DFpT is designed to deal with static perturbations and its use is therefore restricted to those excitations that can be described in the Born–Oppenheimer approx­ imation, such as lattice vibrations. The main idea underlying DFpT is to represent the linear response of KS orbitals to an external perturbation as generic orbitals satisfying an orthogonality constraint with respect to the occupied-state manifold and a self-consistent Sternheimer equation  [94, 95], rather than as linear combinations of virtual orbitals (which would require the computation of all, or a large number, of them). \n\nSubstantial progress has been made over the past decade, allowing one to extend DFpT to the dynamical regime, and thus simulate sizable portions of the optical and loss spectra of complex molecular and extended systems, without making any explicit reference to their virtual states. Although the Sternheimer approach can be easily extended to timedependent perturbations [96–98], its use is hampered in practice by the fact that a different Sternheimer equation has to be solved for each different value of the frequency of the perturbation. When the perturbation acting on the system vanishes, the frequency-dependent Sternheimer equation  becomes a non-Hermitian eigenvalue equation, whose eigenvalues are the excitation energies of the system. In the TDDFT community, this equation is known as the Casida equation [99, 100], which is the immediate translation to the DFT parlance of the timedependent Hartree–Fock equation  [101]. This approach to excited states is optimal in those cases where one is interested in a few excitations only, but can hardly be extended to continuous spectra, such as those arising in extended systems or above the ionization threshold of even finite ones. In those cases where extended portions of a continuous spectrum is required, a new method has been developed, based on the Lanczos bi-orthogonalization algorithm, and dubbed the Liouville– Lanczos approach to time-dependent density-functional perturbation theory (TDDFpT). This method allows one to reuse intermediate products of an iterative process, essentially identical to that used for static perturbations, to build dynamical response functions from which spectral properties can be computed for a whole wide spectral range at once [21, 22]. A similar approach to linear optical spectroscopy was proposed later, based on the multi-shift conjugate gradient algorithm [102], instead of Lanczos. This powerful idea has been generalized to the solution of the Bethe–Salpeter equation, which is formally very similar to the eigenvalue equations arising in TDDFpT [103–105], and to the computation of the polarization propagator and self-energy operator appearing in the $G W$ equations  [28, 29, 106]. It is presently exploited in several components of the Quantum ESPRESSO distribution, as well as in other advanced implementations of many-body perturbation theory [106]. \n\n2.2.1.  Static perturbations and vibrational spectroscopy.  The computation of vibrational properties in extended systems is one of the traditional fields of application of DFpT, as thoroughly described, e.g. in [93]. The latest releases of Quantum ESPRESSO feature the linear-response implementation of several new functionals in the van der Waals and DFT+U families. Explicit expressions of the XC kernel, implementation details, and a thorough benchmark are reported in [107] for the first case. As for the latter, DFpT $+\\mathrm{U}$ has been implemented for both the Dudarev [83] and $\\mathrm{\\DeltaDFT+U+J0}$ functionals [15], allowing one to account for electronic localization effects acting selectively on specific phonon modes at arbitrary wave-vectors, thus substantially improving the description of the vibrational properties of strongly correlated systems with respect to ‘standard’ LDA/GGA functionals. The current implementation allows for both norm-conserving and ultrasoft pseudopotentials, insulators and metals alike, also including the spin-polarized case. The implementation of $\\mathrm{\\DeltaDFpT+U}$ requires two main additional ingredients with respect to standard DFpT [108]. First, the dynamical matrix contains an additional term coming from the second derivative of the Hubbard term $E_{U}$ with respect to the atomic positions (denoted $\\lambda$ or $\\mu_{\\mathrm{-}}$ ), namely: \n\n$$\n\\begin{array}{l}{{\\displaystyle\\Delta^{\\mu}(\\partial^{\\lambda}E_{U})=\\sum_{I\\sigma m m^{\\prime}}U^{I}\\left[\\frac{\\delta_{m m^{\\prime}}}{2}-n_{m m^{\\prime}}^{I\\sigma}\\right]\\Delta^{\\mu}\\left(\\partial^{\\lambda}n_{m m^{\\prime}}^{I\\sigma}\\right)}}\\\\ {{-\\sum_{I\\sigma m m^{\\prime}}U^{I}\\Delta^{\\mu}n_{m m^{\\prime}}^{I\\sigma}\\partial^{\\lambda}n_{m m^{\\prime}}^{I\\sigma},}}\\end{array}\n$$ \n\nwhere the notations are the same as in equation  (12). The symbols $\\partial$ and $\\Delta$ indicate, respectively, a bare derivative (leaving the KS wavefunctions unperturbed) and a total derivative (including also linear-response contributions). Second, in order to obtain a consistent electronic density response to the atomic displacements from the $\\mathrm{\\DeltaDFT+U}$ ground state, the perturbed KS potential $\\Delta V_{S C F}$ in the Sternheimer equation is augmented with the perturbed Hubbard potential $\\Delta^{\\lambda}V_{U}$ : \n\n$$\n\\begin{array}{r}{\\begin{array}{r}{\\Delta^{\\lambda}V_{U}=\\displaystyle\\sum_{I\\sigma m m^{\\prime}}U^{I}\\left[\\frac{\\delta_{m m^{\\prime}}}{2}-n_{m m^{\\prime}}^{I\\sigma}\\right]\\times\\left[|\\Delta^{\\lambda}\\phi_{m^{\\prime}}^{I}\\rangle\\langle\\phi_{m}^{I}|+|\\phi_{m^{\\prime}}^{I}\\rangle\\langle\\Delta^{\\lambda}\\phi_{m}^{I}|\\right]}\\\\ {-\\displaystyle\\sum_{I\\sigma m m^{\\prime}}U^{I}\\Delta^{\\lambda}n_{m m^{\\prime}}^{I\\sigma}|\\phi_{m^{\\prime}}^{I}\\rangle\\langle\\phi_{m}^{I}|,}\\end{array}}\\end{array}\n$$ \n\nwhere the notations are the same as in equation  (13). The unperturbed Hamiltonian in the Sternheimer equation  is the $\\tt D F T+U$ Hamiltonian (including the Hubbard potential $V_{U,}$ . More implementation details will be given in a forthcoming publication [109]. \n\nApplications of $\\mathrm{\\DeltaDFpT+U}$ include the calculation of the vibrational spectra of transition-metal monoxides like MnO and NiO [108], investigations of properties of materials of geophysical interest like goethite [110, 111], iron-bearing [112, 113] and aluminum-bearing bridgmanite [114]. These results feature a significantly better agreement with experiment of the predictions of various lattice-dynamical properties, including the LO-TO and magnetically-induced TO splittings, as compared with standard LDA/GGA calculations. \n\n2.2.2.  Dynamic perturbations: optical, electron energy loss, and magnetic spectroscopies.  Electronic excitations can be described in terms of the dynamical charge- and spin-density susceptibilities, which are accessible to TDDFT [115, 116]. In the linear regime the TDDFT equations can be solved using first-order perturbation theory. The time Fourier transform of the charge-density response, $\\tilde{n}^{\\prime}(\\mathbf{r},\\omega)$ , is determined by the projection over the unoccupied-state manifold of the Fourier transforms of the first-order corrections to the one-electron orbitals, $\\tilde{\\psi}_{{\\bf k}\\nu}^{\\prime}({\\bf r},\\omega)$ , [21–24, 117]. For each band index $\\mathbf{k}\\nu$ , two response orbitals $x_{\\mathbf{k}\\nu}$ and $y_{\\mathbf{k}\\nu}$ can be defined as \n\n$$\nx_{\\mathbf{k}\\nu}(\\mathbf{r})=\\frac{1}{2}\\hat{Q}\\left(\\tilde{\\psi}_{\\mathbf{k}\\nu}^{\\prime}(\\mathbf{r},\\omega)+\\tilde{\\psi}_{-\\mathbf{k}\\nu}^{\\prime*}(\\mathbf{r},-\\omega)\\right)\n$$ \n\n$$\ny_{\\mathbf{k}\\nu}(\\mathbf{r})=\\frac{1}{2}\\hat{Q}\\left(\\tilde{\\psi}_{\\mathbf{k}\\nu}(\\mathbf{r},\\omega)-\\tilde{\\psi}_{-\\mathbf{k}\\nu}^{\\prime*}(\\mathbf{r},-\\omega)\\right),\n$$ \n\nwhere $\\hat{\\boldsymbol{Q}}$ is the projector on the unoccupied-state manifold. The response orbitals $x_{\\mathbf{k}\\nu}$ and $y_{\\mathbf{k}\\nu}$ can be collected in socalled batches $X=\\left\\{x_{\\mathbf{k}\\nu}\\right\\}$ and $Y=\\{y_{{\\bf k}\\nu}\\}$ , which uniquely determine the response density matrix. In a similar way, the perturbing potential $\\hat{V}^{\\prime}$ can be represented by the batch $Z=\\{z_{{\\bf k}\\nu}\\}=\\{\\hat{Q}\\hat{V}^{\\prime}\\psi_{{\\bf k}\\nu}\\}$ . Using these definitions, the linearresponse equations of TDDFpT take the simple form: \n\n$$\n\\left(\\hbar\\omega-\\hat{\\mathcal{L}}\\right)\\cdot\\binom{X}{Y}=\\binom{0}{Z},\\qquad\\hat{\\mathcal{L}}=\\left(\\begin{array}{l l}{0}&{\\hat{D}}\\\\ {\\hat{D}+\\hat{K}}&{0}\\end{array}\\right),\n$$ \n\nwhere the super-operators $\\hat{D}$ and $\\hat{K}$ , which enter the definition of the Liouvillian super-operator, $\\hat{\\mathcal{L}}$ , are defined in terms of the unperturbed Hamiltonian and of the perturbed Hartreeplus-XC potential [21–24, 117]. This implies that a Liouvillian build costs roughly twice as much as a single iteration in time-independent DFpT. It is important to note that $\\hat{D}$ and $\\hat{K}$ , and therefore $\\hat{\\mathcal{L}}$ , do not depend on the frequency $\\omega$ . For this reason, when in equation  (28) the vector on the right-hand side, $(0,Z)^{\\top}$ , is set to zero, a linear eigenvalue equation  is obtained (Casida’s equation). \n\nThe quantum Liouville equation  (28) can be seen as the equation  for the response density matrix operator $\\hat{\\rho}^{\\prime}(\\omega)$ , namely $(\\hbar\\omega-\\hat{\\mathcal{L}})\\cdot\\hat{\\rho}^{\\prime}(\\omega)=[\\hat{V}^{\\prime},\\hat{\\rho}^{\\circ}],$ , where $[\\cdot,\\cdot]$ is the commutator and $\\hat{\\rho}^{\\circ}$ is the ground-state density matrix operator. With this at hand, we can define a generalized susceptibility $\\chi_{A V}(\\omega)$ , which characterizes the response of an arbitrary one-electron Hermitian operator $\\hat{\\boldsymbol A}$ to the external perturbation $\\hat{V}^{\\prime}$ as \n\n$$\n\\chi_{A V}(\\omega)=\\mathrm{Tr}\\left[\\hat{A}\\hat{\\rho}^{\\prime}(\\omega)\\right]=\\left\\langle\\hat{A}\\ \\right|(\\hbar\\omega-\\hat{\\mathcal{L}})^{-1}\\cdot[\\hat{V}^{\\prime},\\hat{\\rho}^{0}]\\right\\rangle,\n$$ \n\nwhere $\\langle\\cdot|\\cdot\\rangle$ denotes a scalar product in operator space. For instance, when both $\\hat{\\boldsymbol A}$ and $\\hat{V^{\\prime}}$ are one of the three Cartesian components of the dipole (position) operator, equation  (29) gives the dipole polarizability of the system, describing optical absorption spectroscopy [21, 22]; setting $\\hat{\\boldsymbol A}$ and $\\hat{V}^{\\prime}$ to one of the space Fourier components of the electron charge-density operator would correspond to the simulation of electron energy loss or inelastic $\\mathbf{\\boldsymbol{x}}$ -ray scattering spectroscopies, giving access to plasmon and exciton excitations in extended systems [25, 26]; two different Cartesian components of the Fourier transform of the spin polarization would give access to spectroscopies probing magnetic excitations (e.g. inelastic neutron scattering or spin-polarized electron energy loss) [118], and so on. When dealing with macroscopic electric fields, the dipole operator in periodic boundary conditions is treated using the standard DFpT prescription, as explained in [119, 120]. \n\nThe Quantum ESPRESSO distribution contains several codes to solve the Casida’s equation or to directly compute generalized susceptibilities according to equation  (29) and by solving equation (28) using different approaches for different pairs of $\\hat{A}/\\hat{V}^{\\prime}$ , corresponding to different spectroscopies. In particular, equation (28) can be solved iteratively using the Lanczos recursion algorithm, which allows one to avoid computationally expensive inversion of the Liouvillian. The basic principle of how matrix elements of the resolvent of an operator can be calculated using a Lanczos recursion chain has been worked out by Haydock et al [121, 122] for the case of Hermitian operators and diagonal matrix elements. The quantity of interest can be written as \n\n$$\ng_{v}(\\omega)=\\left\\langle v\\left|(\\hbar\\omega-\\hat{L})^{-1}v\\right\\rangle.\n$$ \n\nA chain of vectors is defined by \n\n$$\n\\begin{array}{r l}&{\\left|q_{0}\\right\\rangle=0}\\\\ &{\\left|q_{1}\\right\\rangle=\\left|v\\right\\rangle}\\\\ &{\\quad\\alpha_{n}=\\left\\langle q_{n}\\right|\\hat{L}q_{n}\\right\\rangle}\\\\ &{\\quad\\beta_{n+1}\\left|q_{n+1}\\right\\rangle=\\left(\\hat{L}-\\alpha_{n}\\right)\\left|q_{n}\\right\\rangle-\\beta_{n}\\left|q_{n-1}\\right\\rangle,}\\end{array}\n$$ \n\nwhere $\\beta_{n+1}$ is given by the condition $\\langle q_{n+1}|q_{n+1}\\rangle=1$ . The vectors $\\left|q_{n}\\right\\rangle$ created by this recursive chain are orthonormal. \n\nFurthermore, the operator $\\hat{L}$ , written in the basis of these vectors, is tridiagonal. If one limits the chain to the $M$ first vectors $\\vert q_{0}\\rangle,\\vert q_{1}\\rangle,\\cdot\\cdot\\cdot,\\vert q_{M}\\rangle$ , then the resulting representation of $\\hat{L}$ is a $M\\times M$ square matrix $T_{M}$ which reads \n\n$$\nT_{M}=\\left(\\begin{array}{c c c c c c}{{\\alpha_{1}}}&{{\\beta_{2}}}&{{0}}&{{\\cdots}}&{{0}}\\\\ {{}}&{{}}&{{}}&{{}}&{{}}\\\\ {{\\beta_{2}}}&{{\\alpha_{2}}}&{{\\beta_{3}}}&{{\\ddots}}&{{}}&{{\\vdots}}\\\\ {{}}&{{}}&{{}}&{{\\ddots}}&{{\\ddots}}&{{}}\\\\ {{0}}&{{\\beta_{3}}}&{{\\ddots}}&{{\\ddots}}&{{}}&{{0}}\\\\ {{\\vdots}}&{{\\ddots}}&{{\\ddots}}&{{\\ddots}}&{{\\alpha_{M-1}}}&{{\\beta_{M}}}\\\\ {{}}&{{}}&{{\\cdots}}&{{0}}&{{\\beta_{M}}}&{{\\alpha_{M}}}\\end{array}\\right).\n$$ \n\nUsing such a truncated representation of $\\hat{L}$ , the resolvent in equation (30) can be approximated as \n\n$$\ng_{v}(\\omega)\\approx\\left\\langle v\\left|\\left(\\hbar\\omega-T_{M}\\right)^{-1}v\\right\\rangle.\n$$ \n\nThanks to the tridiagonal form of $T_{M}.$ the approximate resolvent can finally be written as a continued fraction \n\n$$\ng_{v}(\\omega)\\approx\\frac{1}{\\hbar\\omega-\\alpha_{1}+\\frac{\\beta_{2}^{2}}{\\hbar\\omega-\\alpha_{2}+...}}.\n$$ \n\nNote that performing the recursion (31)–(34) is the computational bottleneck of this algorithm, while evaluating the continued fraction in equation (37) is very fast. The recursion being independent of the frequency $\\omega$ , a single recursion chain yields information about any desired number of frequencies, at negligible additional computational cost. It is also important to note that at any stage of the recursion chain, only three vectors need to be kept in memory, namely $|q_{n-1}\\rangle,|q_{n}\\rangle$ and $\\left|q_{n+1}\\right>$ . This is a considerable advantage with respect to the direct calculation of $N$ eigenvectors of $\\bar{L}$ where all $N$ vectors need to be kept in memory in order to enforce orthogonality. \n\nThe Liouvillian $\\hat{\\mathcal{L}}$ in equation (28) is not a Hermitian operator. For this reason, the Lanczos algorithm presented above cannot be directly applied to the calculation of the generalized susceptibility (29). There are two distinct algorithms that can be applied in the non-Hermitian case. The non-Hermitian Lanczos bi-orthogonalization algorithm [22, 23] amounts to recursively applying the operator $\\hat{\\mathcal{L}}$ and its Hermitian conjugate $\\hat{\\mathcal{L}}^{\\dagger}$ to two Lanczos vectors $\\left|v_{n}\\right\\rangle$ and $\\left|w_{n}\\right\\rangle$ . In this way, a pair of bi-orthogonal basis sets is created. The operator $\\hat{\\mathcal{L}}$ can then be represented in this basis as a tridiagonal matrix, similarly to the Hermitian case, equation (35). The Liouvillian $\\hat{\\mathcal{L}}$ of TDDFpT belongs to a special class of non-Hermitian operators which are called pseudo-Hermitian [24, 123]. For such operators, there exists a second recursive algorithm to compute the resolvent— pseudo-Hermitian Lanczos algorithm— which is numerically more stable and requires only half the number of operations per Lanczos step [24, 123]. Both algorithms have been implemented in Quantum ESPRESSO. Because of its speed and numerical stability, the use of the pseudo-Hermitian method is recommended. \n\nThis methodology has also been extended—presently only in the case of absorption spectroscopy—to employ hybrid functionals [24, 103, 104] (see section  2.1.1). In this case the calculation requires the evaluation of the linear response of the non-local Fock potential, which is readily available from the response density matrix, represented by the batches of response orbitals. The corresponding hybrid-functional Liouvillian features additional terms with respect to the definition in equation  (28), but presents a similar structure and similar mathematical properties. Accordingly, semi-local and hybrid-functional TDDFpT employ the same numerical algorithms in practical calculations. \n\n2.2.2.1.  Optical absorption spectroscopy.  The turbo_ lanczos.x [23, 24] and turbo_davidson.x [24] codes are designed to simulate the optical response of molecules and clusters. turbo_lanczos.x computes the dynamical dipole polarizability (see equation (29)) of finite systems over extended frequency ranges without ever computing any eigenpairs of the Casida equation. This goal is achieved by applying a recursive non-Hermitian or pseudo-Hermitian Lanczos algorithm. The two flavours of the Lanczos algorithm implemented in turbo_lanczos.x are particularly suited in those cases where one is interested in the spectrum over a wide frequency range comprising a large number of individual excitations. In turbo_davidson.x a Davidson-like algorithm [124] is used to selectively compute a few eigenvalues and eigenvectors of $\\hat{\\mathcal{L}}$ . This is useful when very few low-lying excited states are needed and/or when the excitation eigenvector is explicitly needed, e.g. to compute ionic forces on excited potential energy surfaces, a feature that will be implemented in one of the forthcoming releases. Both turbo_lanczos.x and turbo_davidson.x are interfaced with the Environ module [18], to simulate the absorption spectra of complex molecules in solution using the self-consistent continuum solvation model [20] (see section 2.5.1). \n\n2.2.2.2.  Electron energy loss spectroscopy.  The turbo_ eels.x code [26] computes the response of extended systems to an incoming beam of electrons or $\\mathrm{\\Delta}X$ rays, aimed at simulating electron energy loss (EEL) or inelastic $\\mathbf{\\boldsymbol{x}}$ -ray scattering (IXS) spectroscopies, sensitive to collective chargefluctuation excitations, such as plasmons. Similarly to the description of vibrational modes in a lattice by the PHonon package, here the perturbation can be represented as a sum of monochromatic components corresponding to different momenta, q, and energy transferred from the incoming electrons to electrons of the sample. The quantum Liouville equation  (28) in the batch representation can be formulated for individual $\\mathbf{q}$ components of the perturbation, which can be solved independently [25]. The recursive Lanczos algorithm is used to solve iteratively the quantum Liouville equation, much like in the case of absorption spectroscopy. The entire EEL/IXS spectrum is obtained in an arbitrarily wide energy range (up to the core-loss region) with only one Lanczos chain. Such a numerical algorithm allows one to compute directly the diagonal element of the charge-density susceptibility, see equation (29), by avoiding computationally expensive matrix inversions and multiplications characteristic of standard methods based on the solution of the Dyson equation [125]. \n\nThe current version of turbo_eels.x allows to explicitly account for spin–orbit coupling effects [126]. \n\n2.2.2.3. Magnetic spectroscopy.  The response of the system to a magnetic perturbation is described by a spin-density susceptibility matrix, see equation (29), labeled by the Cartesian components of the perturbing magnetic field and magnetization response, whose poles characterize spin-wave (magnon) and Stoner excitations. The methodology implemented in turbo_eels.x to deal with charge-density fluctuations has been generalized to spin-density fluctuations so as to deal with magnetic (spin-polarized neutron and electron) spectroscopies in extended systems. In the spin-polarized formulation of TDDFpT the time-dependent KS wave functions are two-component spinors $\\{\\psi_{{\\bf k}\\nu}^{\\sigma}({\\bf r},t)\\}$ ( $\\overrightharpoon{\\boldsymbol{\\sigma}}$ is the spin index), which satisfy a time-dependent Pauli-type KS equations  and describe a time-dependent spin-charge-density, $\\begin{array}{r}{n_{\\sigma\\sigma^{\\prime}}(\\mathbf{r},t)=\\sum_{\\mathbf{k}\\nu}\\psi_{\\mathbf{k}\\nu}^{\\sigma*}(\\mathbf{r},t)\\psi_{\\mathbf{k}\\nu}^{\\sigma^{\\prime}}(\\mathbf{r},t)}\\end{array}$ . Instead of using the latter quantity it is convenient to change variables and use the charge density $\\begin{array}{r}{n(\\mathbf{r},t)=\\sum_{\\sigma}n_{\\sigma\\sigma}(\\mathbf{r},t)}\\end{array}$ and the spin density $\\begin{array}{r}{\\mathbf{m}(\\mathbf{r},t)=\\mu_{\\mathrm{B}}\\sum_{\\sigma\\sigma^{\\prime}}\\pmb{\\sigma}_{\\sigma\\sigma^{\\prime}}n_{\\sigma^{\\prime}\\sigma}(\\mathbf{r},t)}\\end{array}$ , where $\\mu_{\\mathrm{B}}$ is the Bohr magneton and $\\sigma$ is the vector of Pauli matrices. In the linearresponse regime, the charge- and spin-density response $n^{\\prime}(\\mathbf{r},t)$ and $\\mathbf{m}^{\\prime}(\\mathbf{r},t)$ are coupled via the scalar and magnetic XC response potentials $V_{\\mathrm{xc}}^{\\prime}(\\mathbf{r},t)$ and $\\mathbf{B}_{\\mathrm{xc}}^{\\prime}(\\mathbf{r},t)$ , which are treated on a par with the Hartree response potential $V_{\\mathrm{H}}^{\\prime}(\\mathbf{r},t)$ depending only on $n^{\\prime}(\\mathbf{r},t)$ , and which all enter the linear-response time-dependent Pauli-type KS equations. The lack of timereversal symmetry in the ground state means that the TDDFpT equations have to be generalized to treat KS spinors at $\\mathbf{k}$ and $-\\mathbf{k}$ and various combinations with the $\\mathbf{q}$ vector. Moreover, this also implies that no rotation of batches is possible, as in equations (26) and (27), and a generalization of the Lanczos algorithm to complex arithmetics is required. At variance with the cumbersome Dyson’s equation approach, which requires the separate calculation and coupling of charge-charge, spinspin, and charge-spin independent-electron polarizabilities, in our approach the coupling between spin and charge fluctuations is naturally accounted for via Lanczos chains for the spinor KS response orbitals. The current implementation supports general non-collinear spin-density distributions, which allows us to account for spin–orbit interaction and magnetic anisotropy. All the details about the present formalism will be given in a forthcoming publication [118] and the corre­ sponding code will be made available in one of the next Quantum ESPRESSO releases. \n\n# 2.2.3.  Many-body perturbation theory. \n\nMany-body perturbation theory refers to a set of computational methods, based on quantum field theory, that are designed to calculate electronic and optical excitations beyond standard DFT [125]. The most popular among such methods are the $G W$ approximation and the Bethe–Salpeter equation  (BSE) approach. The former is intended to calculate accurate quasiparticle excitations, e.g. ionization energies and electron affinities in molecules, band structures in solids, and accurate band gaps in semiconductor and insulators. The latter is employed to study optical excitations by including electron–hole interactions. \n\nIn the GW method the XC potential of DFT is corrected using a many-body self-energy consisting of the product of the electron Green’s function $G$ and the screened Coulomb interaction W [127, 128], which represents the lowest-order term in the diagrammatic expansion of the exact electron self-energy. In the vast majority of $G W$ implementations, the evaluation of $G$ and $W$ requires the calculation of both occupied and unoccupied KS eigenstates. The convergence of the resulting self-energy correction with respect to the number of unoccupied states is rather slow, and in many cases it constitutes the main bottleneck in the calculations. During the past decade there has been a growing interest in alternative techniques which only require the calculation of occupied electronic states, and several computational strategies have been developed [29, 129–131]. The common denominator to all these strategies is that they rely on linear-response DFpT and the Sternheimer equation, as in the PHonon package. \n\nIn Quantum ESPRESSO the GW approximation is realized based on a DFpT representation of response and selfenergy operators, thus avoiding any explicit reference to unoccupied states. There are two different implementations: the GWL (GW-Lanczos) package [28, 29] and the SternheimerGW package [30]. The former focuses on efficient GW calcul­ ations for large systems (including disordered solids, liquids, and interfaces), and also supports the calculations of optical spectra via the Bethe–Salpeter approach [105]. The latter focuses on high-accuracy calculations of band structures, frequency-dependent self-energies, and quasi-particle spectral functions for crystalline solids. In addition to these, the WEST code [106], not part of the Quantum ESPRESSO distribution, relies on Quantum ESPRESSO as an external library to perform similar tasks and to achieve similar goals. \n\n2.2.3.1. GWL.  The GWL package consists of four different codes. The pw4gww.x code reads the KS wave-functions and charge density previously calculated by PWscf and prepares a set of data which are used by code gww.x to perform the actual $G W$ calculation. While pw4gww.x uses the plane-wave representation of orbitals and charges and the same Quantum ESPRESSO environment as all other linear response codes, gww.x does not rely on any specific representation of the orbitals. Its parallelization strategy is based on the distribution of frequencies. Only a few basic routines, such as the MPI drivers, are common with the rest of Quantum ESPRESSO. \n\nGWL supports three different basis sets for representing polarisability operators: (i) plane wave-basis set, defined by an energy cutoff; (ii) the basis set formed by the most important eigenvectors (i.e. corresponding to the highest eigenvalues) of the actual irreducible polarisability operator at zero frequency calculated through linear response; (iii) the basis set formed by the most important eigenvectors of an approximated polarisability operator. The last choice permits the control of the balance between accuracy and dimension of the basis. The GW scheme requires the calculation of products in real space of KS orbitals with vectors of the polarisability basis. These are represented in GWL through dedicated additional basis sets of reduced dimensions. \n\nGWL supports only the $\\Gamma\\cdot$ point sampling of the BZ and considers only real wave-functions. However, ordinary $\\mathbf{k}$ -point sampling of the BZ can be used for the long-range part of the (symmetrized) dielectric matrix. These terms are calculated by the head.x code. In this way reliable calcul­ ations for extended materials can be performed using quite small simulation cells (with cell edges of the order of 20 Bohr). Self-consistency is implemented in GWL, although limited to the quasi-particle energies; the so-called vertex term, arising in the diagrammatic expansion of the self-energy, is not yet implemented. \n\nUsually ordinary $G W$ calculations for transition elements require the explicit inclusion of semicore orbitals in the valence manifold, resulting in a significantly higher computational cost. To cope with this issue, an approximate treatment of semicore orbitals has been introduced in GWL as described in [132]. In addition to collinear spin polarization, GWL provides a fully relativistic non collinear implementation relying on the scalar relativistic calculation of the screened Coulomb interactions [133]. \n\nThe bse.x code of the GWL package performs BSE calcul­ ations and permits to evaluate either the entire frequencydependent complex dielectric function through the Lanczos algorithm or a discrete set of excited states and their energies through a conjugate gradient minimization. In contrast to ordinary implementations, bse.x scales as $N^{3}$ instead of $N^{4}$ with respect to the system size $N$ (e.g. the number of atoms) thanks to the use of maximally localized Wannier functions for representing the valence manifold [105]. The bse.x code, apart from reading the screened Coulomb interaction at zero frequency from a gww.x calculation, works as a separate code and uses the Quantum ESPRESSO environ­ ment. Therefore it could be easily be interfaced with other GW codes. \n\n2.2.3.2. SternheimerGW.  The SternheimerGW package calculates the frequency-dependent GW self-energy and the corresponding quasiparticle corrections at arbitrary $\\mathbf{k}$ -points in the BZ. This feature enables accurate calculations of band structures and effective masses without resorting to interpolation. The availability of the complete $G W$ self-energy (as opposed to the quasiparticle shifts) makes it possible to calculate spectral functions, for example including plasmon satellites [134]. The spectral function can be directly compared to angle-resolved photoelectron spectroscopy (ARPES) experiments. In SternheimerGW the screened Coulomb interaction W is evaluated for wave-vectors in the irreducible BZ by exploiting crystal symmetries. Calculations of $G$ and $W$ for multiple frequencies $\\omega$ rely on the use of multishift linear system solvers that construct solutions for all frequencies from the solution of a single linear system [131, 135]. This method is closely related to the Lanczos approach. The convolution in the frequency domain required to obtain the self energy from $G$ and $W$ can be performed either on the real axis or the imaginary axis. Padé functions are employed to perform approximate analytic continuations from the imaginary to the real frequency axis; the standard Godby-Needs plasmon pole model is also available to compare with literature results. The stability and portability of the SternheimerGW package are verified via a test-suite and a Buildbot test-farm (see section 3.6). \n\n# 2.3.  Other spectroscopies \n\n2.3.1.  QE-GIPAW: nuclear magnetic and electron paramagn­ etic resonance.  The QE-GIPAW package allows for the calcul­ation of various physical parameters measured in nuclear magnetic resonance (NMR) and electron paramagn­ etic resonance (EPR) spectroscopies. These encompass (i) NMR chemical shift tensors and magnetic susceptibility, (ii) electric field gradient (EFG) tensors, (iii) EPR $\\mathrm{\\bf{g}}$ -tensor, and (iv) hyperfine coupling tensor. \n\nIn QE-GIPAW, the NMR and EPR parameters are obtained from the orbital linear response to an external uniform magn­ etic field. The response depends critically upon the exact shape of the electronic wavefunctions near the nuclei. Thus, all-electron wavefunctions are reconstructed from the pseudo-wavefunctions in a gauge- and translationally invariant way using the gauge-including projector augmented-wave (GIPAW) method [136]. The description of a uniform magnetic field within periodic boundary conditions is achieved by the longwavelength limit $(q\\ll1)$ of a sinusoidally modulated field in real space. In practice, for each $\\mathbf{k}$ point, we calculate the first order change of the wavefunctions at $\\mathbf{k}+\\mathbf{q}$ , where q runs over a star of 6 points. The magnetic susceptibility and the induced orbital currents are then evaluated by finite differences, in the limit of small $q$ . The induced magnetic field at the nucleus, which is the central quantity in NMR, is obtained from the induced current via the Biot–Savart law. In QE-GIPAW, the NMR orbital chemical shifts and magnetic susceptibility can be calculated both for insulators [34] and for metals [137] (the additional contribution for metals coming from the spinpolarization of valence electrons, namely the Knight shift, can also be computed but it is not yet ready for production at the time of writing). Similarly to the NMR chemical shift, the EPR g-tensor is calculated as the cross product of the induced current with the spin–orbit operator [138]. \n\nFor the quantities defined in zero magnetic field, namely the EFG, Mössbauer and relativistic hyperfine tensors, the usual PAW reconstruction of the wavefunctions is sufficient and these are computed as described in [139, 140]. The hyperfine Fermi contact term, proportional to the spin density evaluated at the nuclear coordinates, however requires the relaxation of the core electrons in response to the magnetization of valence electrons. We implemented the core relaxation in perturbation theory, according to [141]. Basically we compute the spherically averaged PAW spin density around each atom. Then we compute the change of the XC potential, $\\Delta V_{\\mathrm{XC}}$ , on a radial grid, and compute in perturbation theory the core radial wavefunction, both for spin up and spin down. This provides an extra contribution to the Fermi contact, in most cases opposite in sign to and as large as that of valence electrons. \n\nBy combining the quadrupole coupling constants derived from EFG tensors and hyperfine splittings, electron nuclear double resonance (ENDOR) frequencies can be calculated. Applications highlighting all these features of the QE-GIPAW package can be found in [142]. These quantities are also needed to compute NMR shifts in paramagnetic systems, like novel cathode materials for Li batteries [143]. Previously restricted to norm-conserving pseudopotentials only, all features are now applicable using any kind of pseudization scheme and to PAW, following the theory described in [144]. The use of smooth pseudopotentials allows for the calcul­ation of chemical shifts in systems with several hundreds of atoms [145]. \n\nThe starting point of all QE-GIPAW calculations is a previous calculation of KS orbitals via PWscf. Hence, much like other linear response routines, the QE-GIPAW code uses many subroutines of PWscf and of the linear response module. As usually done in linear response methods, the response of the unoccupied states is calculated using the completeness relation between occupied and unoccupied manifolds [146]. As a result, for insulating as well as metallic systems, the linear response of the system is efficiently obtained without the need to include virtual orbitals. \n\nAs an alternative to linear response method, the theory of orbital magnetization via Berry curvature [147, 148] can be used to calculate the NMR [149] and EPR parameters [150]. Specifically, it can be shown that the variation of the orbital magnetization $M^{\\mathrm{{orb}}}$ with respect to spin flip is directly $\\mathrm{g}$ einsstohr:e $\\begin{array}{r}{g_{\\mu\\nu}=g_{e}-\\frac{2}{\\alpha S}\\mathbf{e}_{\\mu}\\cdot\\mathbf{M}^{\\mathrm{orb}}(\\mathbf{e}_{\\nu})}\\end{array}$ ,hewthoetrael $g_{e}=2.002319$ $\\alpha$ $S$ spin, e are Cartesian unit vectors, provided that the spin–orbit interaction is explicitly considered in the Hamiltonian. This converse method of calculating the g-tensor has been implemented in an older version of QE-GIPAW. It is especially useful in critical cases where linear response is not appropriate, e.g. systems with quasi-degenerate HOMO-LUMO levels. A demonstration of this method applied to delocalized conduction band electrons can be found in [151]. \n\nThe converse method will be shortly ported into the current QE-GIPAW and we will explore the possibility of computing in a converse way the Knight shift as the response to a small nuclear magnetic dipole. The present version of the code allows for parameter-free calculations of g-tensors, hyperfine splittings, and ENDOR frequencies also for systems with total spin $S>1/2$ . Such triplet or even higher-spin states give rise to additional spin-spin interactions, that can be calculated within the magnetic dipole-dipole interaction approximation. This interaction results in a fine structure which can be measured in zero magnetic field. This so-called zero-field splitting is being implemented following the methodology described in [152]. \n\n2.3.2.  XSpectra: L2,3 x-ray absorption edges.  The XSpectra code [153, 154] has been extended to the calcul­ ation of $\\mathbf{\\boldsymbol{X}}$ -ray absorption spectra at the $L_{2,3}$ -edges [155]. The XSpectra code uses the self-consistent charge density produced by PWscf and acts as a post processing tool [153, 154, 156]. The spectra are calculated for the $L_{2}$ edge, while the $L_{3}$ edge is obtained by multiplying by two (single-particle statistical branching ratio) the $L_{2}$ edge spectrum and by shifting it by the value of the spin–orbit splitting of the $2p_{1/2}$ core levels of the absorbing atom. The latter can be taken either from a DFT relativistic all-electron calculation on the isolated atom, or from experiments. \n\nIn practice, the $L_{3}$ edge is obtained from the $L_{2}$ with the spectra_correction.x tool. Such tool contains a table  of experimental $2p$ spin–orbit splittings for all the elements. In addition to computing $L_{3}$ edges, spectra_correction.x allows one to remove states from the spectrum below a certain energy, and to convolute the calculated spectrum with more elaborate broadenings. These operations can be applied to any edge. \n\nTo evaluate the x-ray absorption spectrum for a system containing various atoms of the same species but in different chemical environments, one has to sum the contribution by each atom. This could be the case, for example of an organic molecule containing various C atoms in inequivalent sites. Such individual contributions can be computed separately by XSpectra, and the tool molecularnexafs.x allows one to perform their weighted sum taking into account the proper energy reference (initial and final state effects) [157, 158]. One should in fact notice that the reference for initial state effects will depend upon the environment (e.g. the vacuum level for gas phase molecules, or the Fermi level for molecules adsorbed on a metal). \n\n# 2.4.  Other lattice-dynamical and thermal properties \n\n2.4.1.  thermo_pw: thermal properties from the quasi-harmonic approximation.  thermo_pw [31] is a collection of codes aimed at computing various thermodynamical quantities in the quasi-harmonic approximation. The key ingredient is the vibrational contribution, $F_{\\mathrm{ph}}$ , to the Helmholtz free energy at temperature $T$ : \n\n$$\nF_{\\mathrm{ph}}=k_{\\mathrm{B}}T\\sum_{\\mathbf{q},\\nu}\\ln\\left[2\\sinh\\left(\\frac{\\hbar\\omega_{\\mathbf{q}\\nu}}{2k_{\\mathrm{B}}T}\\right)\\right],\n$$ \n\nwhere $\\omega_{\\mathbf{q},\\nu}$ are phonon frequencies at wave-vector ${\\bf q},k_{\\mathrm{B}}$ is the Boltzmann constant. thermo_pw works by calling Quantum ESPRESSO routines from PWscf and PHonon, that perform one of the following tasks: (i) compute the DFT total energy and possibly the stress for a given crystal structure; (ii) compute for the same system the electronic band structure along a specified path; (iii) compute for the same system phonon frequencies at specified wave-vectors. Using such quantities, thermo_pw can calculate numerically the derivatives of the free energy with respect to the external parameters (e.g. different volumes). Several calls to such routines, with slightly different geometries, are typically needed in a run. All such tasks can be independently performed on different groups of processors (called images). \n\nWhen the tasks carried out by different images require approximately the same time, or when the amount of numer­ ical work needed to accomplish each task is easy to estimate $a$ priori, it would be possible to statically assign tasks to images at the beginning of the run so that images do not need to communicate during the run. However, such conditions are seldom met in thermo_pw and therefore it would be impossible to obtain a good load balancing between images. thermo_pw takes advantage of an engine that controls these different tasks in an asynchronous way, dynamically assigning tasks to the images at run time. \n\nAt the core of thermo_pw there is a module mp_asyn, based on MPI routines, that allows for asynchronous communication between different images. One of the images is the ‘master’ and assigns tasks to the other images (the ‘slaves’) as soon as they communicate that they have accomplished the previously assigned task. The master image also accomplishes some tasks but once in a while, with negligible overhead, it checks if there is an image available to do some work; if so, it assigns to it the next task to do. The code stops when the master recognizes that all the tasks have been done and communicates this information to the slaves. The routines of this communication module are quite independent of the thermo_pw variables and in principle can be used in conjunction with other codes to set up complex workflows to be executed in a massively parallel environment. It is assumed that each processor of each image reads the same input and that the only information that the image needs to synchronize with the other images is which tasks to do. The design of thermo_pw makes it easily extensible to the calculation of new properties in an incremental way. \n\n2.4.2.  thermal2: phonon–phonon interaction and thermal transport.  Phonon–phonon interaction (ph–ph) plays a role in different physical phenomena: phonon lifetime (and its inverse, the linewidth), phonon-driven thermal transport in insulators or semi-metals, thermal expansion of mat­erials. Ph–ph is possible because the harmonic Hamiltonian of ionic motion, of which phonons are stationary states, is only approximate. At first order in perturbation theory we have the third derivative of the total energy with respect to three phonon perturbations, which we compute ab initio. This calcul­ ation is performed by the d3q code via the $2n+1$ theorem [32, 159]. The d3q code is an extension of the old D3 code, which only allowed the calculation of zone-centered phonon lifetimes and of thermal expansion. The current version can compute the three-phonon matrix element of arbitrary wavevectors $D^{(3)}(\\mathbf{q}_{1},\\mathbf{q}_{2},\\mathbf{q}_{3})=\\partial^{3}E/\\partial u_{\\mathbf{q}_{1}}\\partial u_{\\mathbf{q}_{2}}\\partial u_{\\mathbf{q}_{3}}.$ where $u$ are the phonon displacement patterns, the momentum conservation rule imposes ${\\bf q}_{1}+{\\bf q}_{2}+{\\bf q}_{3}=0$ . The current version of the code can treat any kind of crystal geometry, metals and insulators, both local density and gradient-corrected functionals, and multi-projector norm-conserving pseudopotentials. Ultrasoft pseudopotentials, PAW, spin polarization and noncollinear magnetization are not implemented. Higher order derivative of effective charges [160] are not implemented. \n\nThe ph–ph matrix elements, computed from linear response, can be transformed, via a generalized Fourier transform, to the real-space three-body force constants which could be computed in a supercell by finite difference derivation: \n\n$$\nD^{(3)}(\\P_{1},\\P_{2},\\P_{3})=\\sum_{\\mathbf{R}^{\\prime},\\mathbf{R}^{\\prime\\prime}}\\mathrm{e}^{-2\\mathrm{i}\\pi(\\mathbf{R}^{\\prime}\\cdot\\mathbf{q}_{2}+\\mathbf{R}^{\\prime\\prime}\\cdot\\mathbf{q}_{3})}F^{(3)}(\\mathbf{0},\\mathbf{R}^{\\prime},\\mathbf{R}^{\\prime\\prime}),\n$$ \n\nwhere $F^{3}({\\bf0},{\\bf R}^{\\prime},{\\bf R}^{\\prime\\prime})=\\partial^{3}E/\\partial\\tau\\partial(\\tau^{\\prime}+{\\bf R}^{\\prime})\\partial(\\tau^{\\prime\\prime}+{\\bf R}^{\\prime\\prime})$ is the derivative of the total energy w.r.t. nuclear positions of ions with basis $\\tau,\\tau^{\\prime}$ , $\\tau^{\\prime\\prime}$ from the unit cells identified by direct lattice vectors 0 (the origin), $\\mathbf{R}^{\\prime}$ and $\\mathbf{R}^{\\prime\\prime}$ . The sum over $\\ensuremath{\\mathbf{R}}^{\\prime}$ and $\\mathbf{R}^{\\prime\\prime}$ runs, in principle, over all unit cells, however the terms of the sum quickly decay as the size of the triangle $\\mathbf{0}-\\mathbf{R}^{\\prime}-\\mathbf{R}^{\\prime\\prime}$ increases. The real-space finite-difference calculation, performed by some external softwares [168], has some advantages: it is easier to implement and it can readily include all the capabilities of the self-consistent code; on the other hand it is much more computationally expensive than the linearresponse method we use, its cost scaling with the cube of the supercell volume, or the $9_{\\mathrm{th}}$ power of the number of side units of an isotropic system. We use the real-space formalism to apply the sum rule corresponding to translational invariance to the matrix elements. This is done with an iterative method that alternatively enforces the sum rule on the first matrix index and restores the invariance on the order of the derivations. We also use the real-space force constants to Fourierinterpolate the ph–ph matrices on a finer grid, assuming that the contrib­ution from triangles $\\mathbf{0}-\\mathbf{R}^{\\prime}-\\mathbf{R}^{\\prime\\prime}$ which we have not computed is zero; it is important in this stage to consider the periodicity of the system. \n\nFrom many-body theory we get the first-order phonon linewidth [161] $(\\gamma_{\\nu})$ of mode $\\nu$ at $\\mathbf{q}$ , which is a sum over all the possible $N_{\\mathbf{q}}$ ’s final and initial states $(\\mathbf{q}^{\\prime},\\nu^{\\prime},\\nu^{\\prime\\prime})$ with conservation of energy $(\\hbar\\omega)$ and momentum $(\\mathbf{q}^{\\prime\\prime}=-\\mathbf{q}-\\mathbf{q}^{\\prime})$ , BoseEinstein occupations $(n(\\mathbf{q},\\nu)=(\\exp(\\hbar\\omega_{\\mathbf{q},\\nu}/k_{\\mathrm{B}}T)-1)^{-1})$ and an amplitude $V^{(3)}$ , proportional to the ${\\cal D}^{(3)}$ matrix element but renormalized with phonon energies and ion masses: \n\n$$\n\\begin{array}{l}{{\\displaystyle\\gamma_{\\mathbf{q},\\nu}=\\frac{\\pi}{\\hbar^{2}N_{\\mathbf{q}}}\\sum_{\\mathbf{q}^{\\prime},\\nu^{\\prime},\\nu^{\\prime\\prime}}\\left\\vert V^{(3)}(\\mathbf{q}\\nu,\\mathbf{q}^{\\prime}\\nu^{\\prime},\\mathbf{q}^{\\prime\\prime}\\nu^{\\prime\\prime})\\right\\vert}}\\\\ {{\\displaystyle\\qquad\\times\\left[(1+n_{\\mathbf{q}^{\\prime},\\nu^{\\prime}}+n_{\\mathbf{q}^{\\prime\\prime},\\nu^{\\prime\\prime}})\\delta(\\omega_{\\mathbf{q},\\nu}-\\omega_{\\mathbf{q}^{\\prime},\\nu^{\\prime}}-\\omega_{\\mathbf{q}^{\\prime\\prime},\\nu^{\\prime\\prime}})\\right.}}\\\\ {{\\displaystyle\\qquad\\left.+2(n_{\\mathbf{q}^{\\prime},\\nu^{\\prime}}-n_{\\mathbf{q}^{\\prime\\prime},\\nu^{\\prime\\prime}})\\delta(\\omega_{\\mathbf{q},\\nu}+\\omega_{\\mathbf{q}^{\\prime},\\nu^{\\prime}}-\\omega_{\\mathbf{q}^{\\prime\\prime},\\nu^{\\prime\\prime}})\\right].}}\\end{array}\n$$ \n\nThis sum is computed in the thermal2 suite, which is bundled with d3q. A similar expression can be written for the phonon scattering probability which appears in the Boltzmann transport equation. In order to properly converge the integral of the Dirac delta function, we express it as finite-width Gaussian function and use an interpolation grid. This equation can be solved either exactly or in the single mode approximation (SMA) [162]. The SMA is a good tool at temperatures comparable to or larger than the Debye temperature, but is known to be inadequate at low temperatures [163, 164] or in the case of 2D materials [165–167]. The exact solution is computed using a variational form, minimized via a preconditioned conjugate gradient algorithm, which is guaranteed to converge, usually in less than 10 iterations [33]. \n\naddition to using our force constants from DFpT, the code supports importing 3-body force constants computed via finite differences with the thirdorder.py code [168]. Parallelization is implemented with both MPI (with great scalability up to thousand of CPUs) and OpenMP (optimal for memory reduction). \n\n2.4.3.  EPW: electron–phonon coefficients from Wannier i­nterpolation.  The electron–phonon-Wannier (EPW) package is designed to calculate electron–phonon coupling using an ultra-fine sampling of the BZ by means of Wannier interpolation. EPW employs the relation between the electron–phonon matrix elements in the Bloch representation $g_{m n\\nu}(\\mathbf{k,q})$ , and in the Wannier representation, $g_{i j\\kappa\\alpha}(\\mathbf{R},\\mathbf{R}^{\\prime})$ [169], \n\n$$\ng_{m n}(\\mathbf{k},\\mathbf{q})=\\sum_{\\mathbf{R},\\mathbf{R}^{\\prime}}\\mathrm{e}^{\\mathrm{i}\\left(\\mathbf{k}\\cdot\\mathbf{R}+\\mathbf{q}\\cdot\\mathbf{R}^{\\prime}\\right)}\\sum_{i j\\kappa\\alpha}U_{m i\\mathbf{k}+\\mathbf{q}}g_{i j\\kappa\\alpha}(\\mathbf{R},\\mathbf{R}^{\\prime})U_{j n\\mathbf{k}}^{\\dagger}u_{\\kappa\\alpha,\\mathbf{q}\\nu},\n$$ \n\nin order to interpolate from coarse $\\mathbf{k}$ -point and $\\mathbf{q}$ -point grids into dense meshes. In the above expression $\\mathbf{k}$ and $\\mathbf{q}$ represent the electron and phonon wave-vector, respectively, the indices $m,n$ and $i,j$ refer to Bloch states and Wannier states, respectively, and $\\mathbf{R},\\mathbf{R}^{\\prime}$ are direct lattice vectors. The matrices $U_{m i\\mathbf{k}}$ are unitary transformations and the vector $u_{\\kappa\\alpha,\\mathbf{q}\\nu}$ is the displacements of the atom $\\kappa$ along the Cartesian direction $\\alpha$ for the phonon of wavevector $\\mathbf{q}$ and branch $\\nu$ . The interpolation is performed with ab initio accuracy by relying on the localization of maximally-localized Wannier functions [170]. During its execution EPW invokes the Wannier90 software [171] in library mode in order to determine the matrices $U_{m i\\mathbf{k}}$ on the coarse $\\mathbf{k}$ -point grid. \n\nEPW can be used to compute the following physical properties: the electron and phonon linewidths arising from electron–phonon interactions; the scattering rates of electrons by phonons; the total, averaged electron–phonon coupling strength; the electrical resistivity of metals, see figure 2(b); the critical temperature of electron–phonon superconductors; the anisotropic superconducting gap within the Eliashberg theory, see figure  2(c); the Eliashberg spectral function, transport spectral function, see figure 2(d) and the nesting function. The calculation of carrier mobilities using the Boltzmann transport equation in semiconductors is under development. \n\nThe epw.x code exploits crystal symmetry operations (including time reversal) in order to limit the number of phonon calculations to be performed using PHonon to the irreducible wedge of the BZ. The code supports calculations of electron–phonon couplings in the presence of spin–orbit coupling. The current version does not support spin-polarized calculations, ultrasoft pseudopotentials nor the PAW method. As shown in figure 2(a), epw.x scales reasonably up to 2000 cores using MPI. A test farm (see section 3.6) was set up to ensure portability of the code on many architecture and compilers. Detailed information about the EPW package can be found in [27]. \n\nOn top of intrinsic ph–ph events, the thermal2 codes can also treat isotopic disorder and substitution effects and finite transverse dimension using the Casimir formalism. In \n\n2.4.4.  Non-perturbative approaches to vibrational spectroscopies.  Although DFpT is in many ways the state of the art in the simulation of vibrational spectroscopies in extended systems, and in fact one of defining features of Quantum ESPRESSO, it is sometimes convenient to compute lattice-dynamical properties, the response to macroscopic electric fields, or combinations thereof (such as e.g. the infrared or Raman activities), using non-perturbative methods. This is so because DFpT requires the design of dedicated codes, which have to be updated and maintained separately, and which therefore not always follow the pace of the implementation of new features, methods, and functionals (such as e.g. DFT $+\\mathrm{U}$ , vdW-DF, hybrid functionals, or ACBN0 [172]) in their ground-state counterparts. Such a non-perturbative approach is followed in the FD package, which implements the ‘frozen-phonon’ method for the computation of phonons and vibrational spectra: the interatomic Force Constants (IFCs) and electronic dielectric constant are computed as finite differences of forces and polarizations, with respect to finite atomic displacements or external electric fields, respectively [173, 174]. IFC’s are computed in two steps: first, code fd.x generates the symmetry-independent displacements in an appropriate supercell; after the calculations for the various displacements are completed, code fd_ifc.x reads the forces and generates IFC’s. These are further processed in matdyn.x, where non-analytical long-ranged dipolar terms are subtracted out from the IFCs following the recipe of [175]. The calculation of dielectric tensor and of the Born effective charges proceeds from the evaluation of the electronic susceptibility following the method proposed by Umari and Pasquarello [174], where the introduction of a non local energy functional $E_{\\mathrm{tot}}^{\\pmb{\\mathscr{E}}}[\\psi]=E^{0}[\\psi]-\\pmb{\\mathscr{E}}\\cdot(\\mathbf{P}^{\\mathrm{ion}}+\\mathbf{P}^{\\mathrm{el}}[\\psi])$ allows to compute the electronic structure for periodic systems under finite homogeneous electric fields. $E^{0}$ is the ground state total energy in the absence of external electric fields; $\\mathbf{P}^{\\mathrm{ion}}$ is the usual ionic polarization, and $\\mathbf{P}^{\\mathrm{el}}$ is given as a Berry phase of the manifold of the occupied bands [176]. The high-frequency dielectric tensor $\\epsilon^{\\infty}$ is then computed as $\\epsilon_{i j}^{\\infty}=\\delta_{i,j}+4\\pi\\chi_{i j}$ , while Born effective-charge tensors $Z_{I,i j}^{*}$ are obtained as the polarization induced along the direction $i$ by a unit displacement of the Ith atom in the $j$ direction; alternatively, as the force induced on atom $I$ by an applied electric field, $\\varepsilon$ . \n\n![](images/89817fd2d07675c5c860ec9ef67ddd85b14de9b9622748f2827ba09d83216060.jpg) \nFigure 2.  Examples of calculations that can be performed using EPW. (a) Parallel scaling of EPW on ARCHER Cray XC30. This example corresponds to the calculation of electron–phonon couplings for wurtzite GaN. The parallelization is performed over $\\mathbf{k}$ -points using MPI. (b) Calculated temperature-dependent resistivity of Pb by including/neglecting spin–orbit coupling. (c) Calculated superconducting gap function of $\\mathbf{MgB}_{2}$ , color-coded on the Fermi surface. (d) Eliashberg spectral function $\\alpha^{2}{\\cal F}$ and transport spectral function $\\alpha^{2}F_{\\mathrm{tr}}$ of $\\mathrm{Pb}$ . (b)–(d) Reprinted from [27], Copyright 2016, with permission from Elsevier. \n\nThe calculation of the Raman spectra proceeds along similar lines. Within the finite-field approach, the Raman tensor is evaluated in terms of finite differences of atomic forces in the presence of two electric fields [177]. In practice, the tensor $\\chi_{i j I k}^{(1)}$ is obtained from a set of calculations combining finite electric fields along different Cartesian directions. $\\chi_{i j I k}^{(1)}$ is then symmetrized to recover the full symmetry of the structure under study. \n\n# 2.5.  Multi-scale modeling \n\n2.5.1.  Environ: self-consistent continuum solvation embedding model.  Continuum models are among the most popular multiscale approaches to treat solvation effects in the quantumchemistry community [178]. In this class of models, the degrees of freedom of solvent molecules are effectively integrated out and their statistically-averaged effects on the solute are mimicked by those of a continuous medium surrounding a cavity in which the solute is thought to dwell. The most important interaction usually handled with continuum models is the electrostatic one, in which the solvent is described as a dielectric continuum characterized by its experimental dielectric permittivity. \n\nFollowing the original work of Fattebert and Gygi [179] , a new class of continuum models was designed, in which a smooth transition from the QM-solute region to the continuumenvironment region of space is introduced and defined in terms of the electronic density of the solute. The corresponding free energy functional is optimized using a fully variational approach, leading to a generalized Poisson equation  that is solved via a multi-grid solver [179]. This approach, ideally suited for plane-wave basis sets and tailored for MD simulations, has been featured in the Quantum ESPRESSO distribution since v. 4.1. This approach was recently revised [18], by defining an optimally smooth QM/continuum transition, reformulated in terms of iterative solvers [180] and extended to handle in a compact and effective way non-electrostatic interactions [18]. The resulting self-consistent continuum solvation (SCCS) model, based on a very limited number of physically justified parameters, allows one to reproduce experimental solvation energies for aqueous solutions of neutral [18] and charged [181] species with accuracies comparable to or higher than state-of-the-art quantum-chemistry packages. \n\nThe SCCS model involves different embedding terms, each representing a specific interaction with an external continuum environment and contributing to the total energy, KS potential, and interatomic forces of the embedded QM system. Every contribution may depend explicitly on the ionic (rigid schemes) and/or electronic (self-consistent or soft schemes) degrees of freedom of the embedded system. All the different terms are collected in the stand-alone Environ module [182]. The present discussion refers to release 0.2 of Environ, which is compatible with Quantum ESPRESSO starting from versions 5.1. The module requires a separate input file with the specifications of the environment interactions to be included and of the numerical parameters required to compute their effects. Fully parameterized and tuned SCCS environ­ ments, e.g. corresponding to water solutions for neutral and charged species, are directly available to the users. Otherwise individual embedding terms can be switched on and tuned to the specific physical conditions of the required environ­ ment. Namely, the following terms are currently featured in Environ: \n\n•\tSmooth continuum dielectric, with the associated generalized Poisson problem solved via a direct iterative approach or through a preconditioned conjugate gradient algorithm [180]. \n•\tElectronic enthalpy functional, introducing an energy term proportional to the quantum-volume of the system and able to describe finite systems under the effect of an applied external pressure [183]. \n•\tElectronic cavitation functional, introducing an energy term proportional to the quantum-surface able to describe free energies of cavitation and other surface-related interaction terms [184]. \n•\tParabolic corrections for periodic boundary conditions in aperiodic and partially periodic (slab) systems [19, 185]. \n•\tFixed dielectric regions, allowing for the modelling of complex inhomogenous dielectric environments. \n\n•\tFixed Gaussian-smoothed distributions of charges, allowing for a simplified modelling of countercharge distributions, e.g. in electrochemical setups. \n\nDifferent packages of the Quantum ESPRESSO distribution have been interfaced with the Environ module, including PWscf, CP, PWneb, and turboTDDFT, the latter featuring a linear-response implementation of the SCCS model (see section  2.2.2). Moreover, continuum environ­ ment effects are fully compatible with the main features of Quantum ESPRESSO, and in particular, with reciprocal space integration and smearing for metallic systems, with both norm-conserving and ultrasoft pseudopotentials and PAW, with all XC functionals. \n\n2.5.2.  QM–MM.  QM–MM was implemented in v.5.0.2 using the method documented in [40]. Such methodology accounts for both mechanical and electrostatic coupling between the QM (quantum-mechanical) and MM (molecular-mechanics) regions, but not for bonding interactions (i.e. bonds between the QM and MM regions). In practice, we need to run two different codes, Quantum ESPRESSO for the QM region and a classical force-field code for the MM region, that communicate atomic positions, forces, electrostatic potentials. \n\nLAMMPS [39] is the software chosen to deal with the classical (MM) degrees of freedom. This is a well-known and well-maintained package, released under an opensource license that allows redistribution together with Quantum ESPRESSO. The communications between the QM and MM regions use a ‘shared memory’ approach: the MM code runs on a master node, communicates directly via the memory with the QM code, which is typically running on a massively parallel machine. Such approach has some advantages: the MM part is typically much faster than the QM one and can be run in serial execution, wasting no time on the HPC machine; there is a clear and neat separation between the two codes, and very small code changes in either codes are needed. It has however also a few drawbacks, namely: the serial computation of the MM part may become a bottleneck if the MM region contains many atoms; direct access to memory is often restricted for security reasons on HPC machines. \n\nAn alternative approach has been implemented in v.5.4. A single (parallel) executable runs both the MM and the QM codes. The two codes exchange data and communicate via MPI. This approach is less elegant than the previous one and requires a little bit more coding, but its implementation is quite straightforward thanks also to the changes in the logic of parallelization mentioned in section 3.4. The coupling of the two codes has required some modifications also to the qmmm library inside LAMMPS and to the related fix qmmm (a ‘fix’ in LAMMPS is any operation that is applied to the system during the MD run). In particular, electrostatic coupling has been introduced, following the approach described in [186]. The great advantage of this approach is that its performance on HPC machines is as good as the separate performances of the QM and MM codes. Since LAMMPS is very well parallelized, this is a significant advantage if the MM region contains many atoms. Moreover, it can be run without restrictions on any parallel machine. This new QM–MM implementation is an integral part of the Quantum ESPRESSO distribution and will soon be included into LAMMPS as well (the ‘fix’ is currently under testing) and it is straightforward to compile and execute it. \n\n# 2.6.  Miscellaneous feature enhancements and additions \n\n2.6.1.  Fully relativistic projector augmented-wave method.  By applying the PAW formalism to the equations  of relativistic spin density functional theory [187, 188], it is possible to obtain the fully relativistic PAW equations  for four-comp­ onent spinor pseudo-wavefunctions [16]. In this formalism the pseudo-wavefunctions can be written in terms of large $|\\tilde{\\Psi}_{i,\\sigma}^{A}\\rangle$ and small $|\\tilde{\\Psi}_{i,\\sigma}^{B}\\rangle$ components, both two-component spinors (the index $\\sigma$ runs over the two spin components). The latter is of order $\\textstyle{\\frac{v}{c}}$ of the former, where $\\nu$ is of the order of the velocity of the electron and $c$ is the speed of light. These equations can be simplified introducing errors of the order of the transferability error of the pseudopotential or of order $1/c^{2}$ , depending on which is the largest. In the final equations only the large components of the pseudo-wavefunctions appear. The non relativistic kinetic energy $\\ensuremath{\\mathbf{p}}^{2}/2m$ ( $\\dot{m}$ is the electron mass) acts on the large component of the pseudo-wavefunctions $|\\tilde{\\Psi}_{i,\\sigma}^{A}\\rangle$ in the mesh defined by the FFT grid and the same kinetic energy is used to calculate the expectation values of the Hamiltonian between partial pseudo-waves $\\big|\\Phi_{n,\\sigma}^{I,P S,A}\\big\\rangle$ . The Dirac kinetic energy is used instead to calculate the expectation values of the Hamiltonian between all-electron partial waves $\\vert\\Phi_{n,\\eta}^{I,A E}\\rangle$ (η is a four-component index). In this manner, relativistic effects are hidden in the coefficients of the non-local pseudopotential. The equations are formally very similar to the equations of the scalar-relativistic case: \n\n$$\n\\begin{array}{r l r}{\\lefteqn{\\sum_{\\sigma_{2}}\\left[\\frac{{\\bf p}^{2}}{2m}\\delta^{\\sigma_{1},\\sigma_{2}}+\\sum_{\\eta_{1},\\eta_{2}}\\int\\mathrm{d}{\\bf r}\\tilde{V}_{\\mathrm{LOC}}^{\\eta_{1},\\eta_{2}}({\\bf r})\\tilde{K}({\\bf r})_{\\sigma_{1},\\sigma_{2}}^{\\eta_{1},\\eta_{2}}-\\varepsilon_{i}S^{\\sigma_{1},\\sigma_{2}}\\right.}}\\\\ &{}&{\\left.+\\sum_{I,m n}(D_{I,m n}^{1}-\\tilde{D}_{I,m n}^{1})|\\beta_{m,\\sigma_{1}}^{I,A}\\rangle\\langle\\beta_{n,\\sigma_{2}}^{I,A}|\\right]|\\tilde{\\Psi}_{i,\\sigma_{2}}^{A}\\rangle=0,}\\end{array}\n$$ \n\nwhere $D_{I,m n}^{1}$ and ${\\tilde{D}}_{I,m n}^{1}$ are calculated inside the PAW spheres: \n\n$$\nD_{I,m n}^{1}=\\sum_{\\eta_{1},\\eta_{2}}\\langle\\Phi_{m,\\eta_{1}}^{I,A E}|T_{D}^{\\eta_{1},\\eta_{2}}+V_{\\mathrm{LOC}}^{I,\\eta_{1},\\eta_{2}}|\\Phi_{n,\\eta_{2}}^{I,A E}\\rangle,\n$$ \n\n$$\n\\begin{array}{l}{{\\displaystyle\\tilde{D}_{I,m n}^{1}=\\sum_{\\sigma_{1},\\sigma_{2}}\\langle\\Phi_{m,\\sigma_{1}}^{I,P S,{A}}\\vert\\frac{\\mathbf{p}^{2}}{2m}\\delta^{\\sigma_{1},\\sigma_{2}}+\\tilde{V}_{\\mathrm{LOC}}^{I,\\sigma_{1},\\sigma_{2}}\\vert\\Phi_{n,\\sigma_{2}}^{I,P S,{A}}\\rangle}}\\\\ {{\\displaystyle\\qquad+\\sum_{\\eta_{1},\\eta_{2}}\\int_{\\Omega_{I}}\\mathrm{d}\\mathbf{r}\\hat{Q}_{m n,\\eta_{1},\\eta_{2}}^{I}(\\mathbf{r})\\tilde{V}_{\\mathrm{LOC}}^{I,\\eta_{1},\\eta_{2}}(\\mathbf{r}).}}\\end{array}\n$$ \n\nHere $T_{D}$ is the Dirac kinetic energy: \n\n$$\nT_{D}=c{\\pmb\\alpha}\\cdot{\\bf p}+(\\beta-{\\bf1}_{4\\times4})m c^{2},\n$$ \n\nwritten in terms of the $4\\times4$ Hermitian matrices $\\alpha$ and $\\beta$ and $V_{\\mathrm{LOC}}^{\\eta_{1},\\eta_{2}}$ is the sum of the local, Hartree, and XC potential $(V_{\\mathrm{eff}})$ together, in magnetic systems, with the contribution of the XC magnetic field: \n\n$V_{\\mathrm{LOC}}^{\\eta_{1},\\eta_{2}}(\\mathbf{r})=V_{\\mathrm{eff}}(\\mathbf{r})\\delta^{\\eta_{1},\\eta_{2}}-\\mu_{\\mathrm{B}}\\mathbf{B}_{\\mathrm{xc}}(\\mathbf{r})\\cdot(\\boldsymbol{\\beta}\\pmb{\\Sigma})^{\\eta_{1},\\eta_{2}}$ . We refer to [16] for a detailed definition of the partial waves $\\vert\\Phi_{n,\\eta}^{I,A E}\\rangle$ , $\\big|\\Phi_{n,\\sigma}^{I,P S,A}\\big\\rangle$ dapnrdo $\\vert\\beta_{m,\\sigma}^{I,A}\\rangle$ , of tthe oavuerglmapenmtatiroixn iaonds $\\hat{Q}_{m n,\\eta_{1},\\eta_{2}}^{I}(\\mathbf{r})$ $\\tilde{K}(\\mathbf{r})_{\\sigma_{1},\\sigma_{2}}^{\\eta_{1},\\eta_{2}}$ $S^{\\sigma_{1},\\sigma_{2}}$ for their rewriting in terms of projector functions that contain only spherical harmonics. Solving these equations  it is possible to include spin–orbit coupling effects in electronic structure calculations. In Quantum ESPRESSO these equations  are used when input variables noncolin and lspinorb are both.TRUE.and the PAW data sets are fully relativistic, as those available with the pslibrary project. \n\n2.6.2.  Electronic and structural properties in field-effect ­configuration.  Since Quantum ESPRESSO v.6.0 it is possible to compute the electronic structure under a fieldeffect transistor (FET) setup in periodic boundary conditions [189]. In physical FETs, a voltage is applied to a gate electrode, accumulating charges at the interface between the gate di­electric and a semiconducting system (see figure  3). The gate electrode is simulated with a charged plate, henceforth referred to as the gate. Since the interaction of this charged plate with its periodic image generates a spurious nonphysical electric field, a dipolar correction, equivalent to two planes of opposite charge, is added [190], canceling out the field on the left side of the gate. In order to prevent electrons from spilling towards the gate for large electron doping [191], a potential barrier can be added to the electrostatic potential, mimicking the effect of the gate dielectric. \n\nThe setup for a system in FET configuration is shown in figure 3. The gate has a charge $n_{\\mathrm{dop}}A$ and the system has opposite charge. Here $n_{\\mathrm{dop}}$ is the number of doping electrons per unit area (i.e. negative for hole doping), $A$ is the area of the unit cell parallel to the surface. In practice the gate is represented by an external potential \n\n$$\nV_{\\mathrm{gate}}(\\mathbf{r})=-2\\pi n_{\\mathrm{dop}}\\left(-|\\overline{{\\mathbf{z}}}|+\\frac{\\overline{{\\mathbf{z}}}^{2}}{L}+\\frac{L}{6}\\right).\n$$ \n\nHere ${\\overline{{\\mathsf{z}}}}=z-z_{\\mathrm{gate}}$ with $\\overline{{\\mathbf{z}}}\\in\\left[-L/2;L/2\\right]$ measures the distance from the gate (see figure 3). The dipole of the charged system plus the gate is canceled by an electric dipole generated by two planes of opposite charge [190, 192, 193], placed at $z_{\\mathrm{dip}}-d_{\\mathrm{dip}}/2$ and $z_{\\mathrm{dip}}+d_{\\mathrm{dip}}/2$ , in the vacuum region next to the gate ( $\\ensuremath{V_{\\mathrm{dip}}}$ in figure 3). Additionally one may include a potential barrier to avoid charge spilling towards the gate, or as a substitute for the gate dielectric. $V_{b}({\\bf r})$ is a periodic function of $z$ defined on the interval $z\\in[0,L]$ as equal to a constant $V_{b}$ for $z_{1}
ATOMIC_POSITIONS sg
Cla
C8gX
C24mXy
C48nXy
C
\n\nFor some crystal systems there are alternate descriptions in the ITA, so additional input parameters may be needed to select the desired one. For the monoclinic system the $\\mathrm{{^\\circc}}$ -unique’ orientation is the default and bunique $\\c=$ .TRUE.must be specified in input if the ‘b-unique’ orientation is desired. For some space groups there are two possible choices of the origin. The origin appearing first in the ITA is chosen by default, unless origin_choice $:=2$ is specified in input. Finally, for trigonal space groups the atomic coordinates can be referred to the rhombohedral or to the hexagonal Bravais lattices. The default is the rhombohedral lattice, so rhombohedral $\\c=$ .FALSE. must be specified in input to use the hexagonal lattice. \n\nA final comment for centered Bravais lattices: in the crystallographic literature, the conventional unit cell is usually assumed. Quantum ESPRESSO however assumes the primitive unit cell, having a smaller volume and a smaller number of atoms, and discards atoms outside the primitive cell. Auxiliary code supercell.x, available in thermo_pw (see section  2.4.1), prints all atoms in the conventional cell when necessary. \n\n# 3.  Parallelization, modularization, interoperability and stability \n\n# 3.1.  New parallelization levels \n\nThe basic modules of Quantum ESPRESSO are characterized by a hierarchy of parallelization levels, described in [6]. Processors are divided into groups, labeled by a MPI communicator. Each group of processors distributes a specific subset of computations. The growing diffusion of HPC machines based on nodes with many cores (32 and more) makes however pure MPI parallelization not always ideal: running one MPI process per core has a high overhead, limiting performances. It is often convenient to use mixed MPI-OpenMP parallelization, in which a small number of MPI processes per node use OpenMP threads, either explicitly (i.e. with compiler directives) or implicitly (i.e. via calls to OpenMP-aware library). Explicit OpenMP parallelization, originally confined to computationally intensive FFTs, has been extended to many more parts of the code. \n\nOne of the challenges presented by a massively parallel machine is to get rid of both memory and CPU time bottlenecks, caused respectively by arrays that are not distributed across processors and by non-parallelized sections  of code. It is especially important to distribute all arrays and parallelize all computations whose size/complexity increases with the dimensions of the unit cell or of the basis set. Nonparallelized computations hamper ‘weak’ scalability, that is, parallel performance while increasing both the system size and the amount of computational resources, while non-distributed arrays may become an unavoidable RAM bottleneck with increasing problem size. ‘Strong’ scalability (that is, at fixed problem size and increasing number of CPUs) is even more elusive than weak scalability in electronic-structure calcul­ations, requiring, in addition to systematic distribution of computations, to keep to the minimum the ratio between time spent in communications and in computation, and to have a nearly perfect load balancing. In order to achieve strong scalability, the key is to add more parallelization levels and to use algorithms that permit to overlap communications and computations. \n\nFor what concerns memory, notable offenders are arrays of scalar products between KS states $\\psi_{i}$ : $O_{i j}=\\langle\\psi_{i}|\\widehat{O}|\\psi_{j}\\rangle$ , where $\\hat{o}$ can be either the Hamiltonian or an overlap m\u001fatrix; and sca\u001flar products between KS states and pseudopotential projectors $\\beta$ , $p_{i j}=\\langle\\psi_{i}|\\beta_{j}\\rangle$ . The size of such arrays grows as the square of the size of the cell. Almost all of them are now distributed across processors of the ‘linear-algebra group’, that is, the group of processors taking care of linear-algebra operations on matrices. The most expensive of such operations are subspace diagonalization (used in PWscf in the iterative diagonalization) and iterative orthonormalization (used by CP). In both cases, a parallel dense-matrix diagonalization on distributed matrix is needed. In addition to ScaLAPACK, Quantum ESPRESSO can now take advantage of newer ELPA libraries [200], leading to significant performance improvements. \n\nThe array containing the plane-wave representation, $c_{\\mathbf{k},n}(\\mathbf{G})$ , of KS orbitals is typically the largest array, or one of the largest. While plane waves are already distributed across processors of the ‘plane-wave group’ as defined in [6], it is now possible to distribute KS orbitals as well. Such a parallelization level is located between the $\\mathbf{k}$ -point and the plane-wave parallelization levels. The corresponding MPI communicator defines a subgroup of the $\\mathbf{\\hat{\\mu}}_{\\mathbf{k}}$ -point group’ of processors and is called ‘band group communicator’. In the CP package, band parallelization is implemented for almost all available calcul­ ations. Its usefulness is better appreciated in simulations of large cells—several hundreds of atoms and more—where the number of processors required by memory distribution would be too large to get good scalability from plane-wave parallelization only. \n\nIn PWscf, band parallelization is implemented for calcul­ ations using hybrid functionals. The standard algorithm to compute Hartree–Fock exchange in a plane-wave basis set (see section 2.1.1) contains a double loop on bands that is by far the heaviest part of computation. A first form of parallelization, described in [34], was implemented in v.5.0. In the latest version, this has been superseded by parallelization of pairs of bands, [35]. Such algorithm is compatible with the ‘task-group’ parallelization level (that is: over KS states in the calculation of $V\\psi_{i}$ products) described in [6]. \n\nIn addition to the above-mentioned groups, that are globally defined and in principle usable in all routines, there are a few additional parallelization levels that are local to specific routines. Their goal is to reduce the amount of non-parallel computations that may become significant for many-atom systems. An example is the calculation of $\\tt D F T+U$ (section 2.1.3) terms in energy and forces, equations  (12) and (14) respectively. In all these expressions, the calculation of the scalar products between valence and atomic wave functions is in principle the most expensive step: for $N_{b}$ bands and $N_{p w}$ plane waves, $\\mathcal{O}(N_{p w}N_{b})$ floating-point operations are required (typically, $N_{p w}\\gg N_{b})$ . The calculation of these terms is however easily and effectively parallelized, using standard matrix-matrix multiplication routines and summing over MPI processes with a mpi_reduce operation on the plane-wave group. The sum over $\\mathbf{k}$ -points can be parallelized on the $\\mathbf{k}$ -point group. The remaining sums over band indices $\\nu$ and Hubbard orbitals $I,m$ may however require a significant amount of non-parallelized computation if the number of atoms with a Hubbard $U$ term is not small. The sum over band indices is thus parallelized by simply distributing bands over the plane-wave group. This is a convenient choice because all processors of the plane-wave group are available once the scalar products are calculated. The addition of band parallelization speeds up the computation of such terms by a significant factor. This is especially important for Car–Parrinello dynamics, requiring the calculation of forces at each time step, when a sizable number of Hubbard manifolds is present. \n\n# 3.2.  Aspects of interoperability \n\nOne of the original goals of Quantum ESPRESSO was to assemble different pieces of rather similar software into an integrated software suite. The choice was made to focus on the following four aspects: input data formats, output data files, installation mechanism, and a common base of code. While work on the first three aspects is basically completed, it is still ongoing on the fourth. It was however realized that a different form of integration—interoperability, i.e. the possibility to run Quantum ESPRESSO along with other software—was more useful to the community of users than tight integration. There are several reasons for this, all rooted in new or recent trends in computational materials science. We mention in par­ ticular the usefulness of interoperability for \n\n1.\texcited-states calculations using many-body perturbation theory, at various levels of sophistication: GW, TDDFT, BSE (e.g. yambo [201], SaX [202], or BerkeleyGW [203]); \n2.\tcalculations using quantum Monte Carlo methods; \n3.\tconfiguration-space sampling, using such algorithms as nudged elastic band (NEB), genetic/evolutionary algorithms, meta-dynamics; \n4.\tinclusion of quantum effects on nuclei via path-integral Monte Carlo; \n5.\tmulti-scale simulations, requiring different theoretical approaches, each valid in a given range of time and length scale, to be used together; \n6.\thigh-throughput, or ‘exhaustive’, calculations (e.g. AiiDA [204, 205] and $\\operatorname{AFLOW}\\pi$ [206]) requiring automated submission, analysis, retrieval of a large number of jobs; \n7.\t‘steering’, i.e. controlling the computation in real time using either a graphical user interface (GUI) or an interface in a high-level interpreted language (e.g. python). \n\nIt is in principle possible, and done in some cases, to implement all of the above into Quantum ESPRESSO, but this is not always the best practice. A better option is to use Quantum ESPRESSO in conjunction with external software performing other tasks. \n\nCases 1 and 2 mentioned above typically use as starting step the self-consistent solution of KS equations, so that what is needed is the possibility for external software to read data files produced by the main Quantum ESPRESSO codes, notably the self-consistent code PWscf and the molecular dynamics code CP. \n\nCases 3 and 4 typically require many self-consistent calcul­ ations at different atomic configurations, so that what is needed is the possibility to use the main Quantum ESPRESSO codes as ‘computational engine’, i.e. to call PWscf or CP from an external software, using atomic configurations supplied by the calling code. \n\nThe paradigmatic case 5 is QM–MM (section 2.5.2), requiring an exchange of data, notably: atomic positions, forces, and some information on the electrostatic potential, between Quantum ESPRESSO and the MM code—typically a classical MD code. \n\nCase 6 requires easy access to output data from one simulation, and easy on-the-fly generation of input data files as well. This is also needed for case 7, which however may also require a finer-grained control over computations performed by Quantum ESPRESSO routines: in the most sophisticated scenario, the GUI or python interface should be able to perform specific operations ‘on the fly’, not just running an entire self-consistent calculation. This scenario relies upon the existence of a set of application programming interfaces (API’s) for calls to basic computational tasks. \n\n# 3.3.  Input/Output and data file format \n\nOn modern machines, characterized by fast CPU’s and large RAM’s, disk input/output (I/O) may become a bottleneck and should be kept to a strict minimum. Since v.5.3 both PWscf and CP do not perform by default any I/O at run time, except for the ordinary text output (printout), for checkpointing if required or needed, and for saving data at the end of the run. The same is being gradually extended to all codes. In the following, we discuss the case of the final data writing. \n\nThe original organization of output data files (or more exactly, of the output data directory) was based on a formatted ‘head’ file, with a XML-like syntax, containing general information on the run, and on binary data files containing the KS orbitals and the charge density. We consider the basic idea of such approach still valid, but some improvements were needed. On one hand, the original head file format had a number of small issues—inconsistencies, missing pieces of relevant information—and used a non-standard syntax, lacking a XML ‘schema’ for validation. On the other hand, data files suffered from the lack of portability of Fortran binary files and had to be transformed into text files, sometimes very large ones, in order to become usable on a different machine. \n\n3.3.1.  XML files with schema.  Since v.6.0, the ‘head’ file is a true XML file using a consistent syntax, described by a XML schema, that can be easily parsed with standard XML tools. It also contains complete information on the run, including all data needed to reproduce the results, and on the correct execution and exit status. This aspect is very useful for highthroughput applications, for databasing of results and for verification and validation purposes. \n\nThe XML file contains an input section  and can thus be used as input file, alternative to the still existing text-based input. It supersedes the previous XML-based input, introduced several years ago, that had a non-standard syntax, different from and incompatible with the one of the original head file. Implementing a different input is made easy by the clear separation existing between the reading and initialization phases: input data is read, stored in a separate module, copied to internal variables. \n\nThe current XML file can be easily parsed and generated using standard XML tools and is especially valuable in conjunction with GUI’s. The schema can be found at the URL: www.quantum-espresso.org/ns/qes/qes-1.0.xsd. \n\n3.3.2.  Large-record data file format.  Although not as I/Obound as other kinds of calculations, electronic-structure simulations may produce a sizable amount of data, either intermediate or needed for further processing. The largest array typically contains the plane-wave representation of KS orbitals; other sizable arrays contain the charge and spin density, either in reciprocal or in real space. In parallel execution using MPI, large arrays are distributed across processors, so one has two possibilities: let each MPI process write its own slice of the data (‘distributed’ I/O), or collect the entire array on a single processor before writing it (‘collected’ I/O). In distributed I/O, coding is straightforward and efficient, minimizing file size and achieving some sort of I/O parallelization. A global file system, accessible to all MPI processes, is needed. The data is spread into many files that are directly usable only by a code using exactly the same distribution of arrays, that is, exactly the same kind of parallelization. In collected I/O, the coding is less straightforward. In order to ensure portability, some reference ordering, independent upon the number of processors and the details of the parallelization, must be provided. For large simulations, memory usage and communication pattern must be carefully optimized when a distributed array is collected into a large array on a single processor. \n\nIn the original I/O format, KS orbitals were saved in reciprocal space, in either distributed or collected format. For the latter, a reproducible ordering of plane waves (including the ordering within shells of plane waves with the same module), independent upon parallelization details and machine-independent, ensures data portability. Charge and spin density were instead saved in real space and in collected format. In the new I/O scheme, available since v.6.0, the output directory is simplified, containing only the XML data file, one file per $\\mathbf{k}$ -point with KS orbitals, one file for the charge and spin density. Both files are in collected format and both quantities are stored in reciprocal space. In addition to Fortran binary, it is possible to write data files in HDF5 format [207]. HDF5 offers the possibility to write structured record and portability across architectures, without significant loss in performances; it has an excellent support and is the standard for I/O in other fields of scientific computing. Distributed I/O is kept only for checkpointing or as a last-resort alternative. \n\nIn spite of its advantages, such a solution has still a bottleneck in large-scale computations on massively parallel machines: a single processor must read and write large files. Only in the case of parallelization over $\\mathbf{k}$ -points is I/O parallelized in a straightforward way. More general solutions to implement parallel I/O using parallel extensions of HDF5 are currently under examination in view of enabling Quantum ESPRESSO towards ‘exascale’ computing (that is: towards $\\mathcal{O}(10^{18})$ floating-point operations per second). \n\n# 3.4.  Organization of the distribution \n\nCodes contained in Quantum ESPRESSO have evolved from a small set of original codes, born with rather restricted goals, into a much larger distribution via continuous additions and extensions. Such a process—presumably common to most if not all scientific software projects—can easily lead to uncoordinated growth and to bad decisions that negatively affect maintainability. \n\n# 3.4.1.  Package re-organization and modularization.  In order to make the distribution easier to maintain, extend and debug, the distribution has been split into \n\na.\tbase distribution, containing common libraries, tools and utilities, core packages PWscf, CP, PostProc, plus some commonly used additional packages, currently: atomic, PWgui, PWneb, PHonon, XSpectra, turboTDDFT, turboEELS, GWL, EPW; b.\texternal packages such as SaX [202], yambo [201], Wannier90 [171], WanT [208, 209], that are automatically downloaded and installed on demand. \n\nThe directory structure now explicitly reflects the structure of Quantum ESPRESSO as a ‘federation’ of packages rather than a monolithic one: a common base distribution plus additional packages, each of which fully contained into a subdirectory. \n\nIn the reorganization process, the implementation of the NEB algorithm was completely rewritten, following the paradigm sketched in section 3.2. PWneb is now a separate package that implements the NEB algorithm, using PWscf as the computational engine. The separation between the NEB algorithm and the self-consistency algorithm is quite complete: PWneb could be adapted to work in conjunction with a different computational engine with a minor effort. \n\nThe implementation of meta-dynamics has also been reconsidered. Given the existence of a very sophisticated and well-maintained package [210] Plumed for all kinds of metadynamics calculations, the PWscf and CP packages have been adapted to work in conjunction with Plumed v.1.x, removing the old internal meta-dynamics code. In order to activate meta-dynamics, a patching process is needed, in which a few specific ‘hook’ routines are modified so that they call routines from Plumed. \n\n3.4.2.  Modular parallelism.  The logic of parallelism has also evolved towards a more modular approach. It is now possible to have all Quantum ESPRESSO routines working inside a MPI communicator, passed as argument to an initialization routine. This allows in particular the calling code to have its own parallelization level, invisible to Quantum ESPRESSO routines; the latter can thus perform independent calculations, to be subsequently processed by the calling code. For instance: the ‘image’ parallelization level, used by NEB calculations, is now entirely managed by PWneb and no longer in the called PWscf routines. Such a feature is very useful for coupling external codes to Quantum ESPRESSO routines. To this end, a general-purpose library for calling PWscf or CP from external codes (either Fortran or $_{\\mathrm{C/C++}}$ using the Fortran 2003 ISO C binding standard) is provided in the directory COUPLE/. \n\n3.4.3.  Reorganization of linear-response codes.  All linearresponse codes described in sections  2.2 and 2.1.4 share as basic computational step the self-consistent solution of linear systems $A x=b$ for different perturbations $b$ , where the operator $A$ is derived from the KS Hamiltonian $H$ and the linearresponse potential. Both the perturbations and the methods of solution differ by subtle details, leading to a plethora of routines, customized to solve slightly different versions of the same problem. Ideally, one should be able to solve any linearresponse problem by using a suitable library of existing code. To this end, a major restructuring of linear-response codes has been started. Several routines have been unified, generalized and extended. They have been collected into the same subdirectory, LR_Modules, that will be the container of ‘generic’ linear-response routines. Linear-response-related packages now contain only code that is specific to a given perturbation or property calculation. \n\n# 3.5.  Quantum ESPRESSO and scripting languages \n\nA desirable feature of electronic-structure codes is the ability to be called from a high-level interpreted scripting language. Among the various alternatives, python has emerged in the last years due to its simple and powerful syntax and to the availability of numerical extensions (NumPy). Since v.6.0, an interface between PWscf and the path integral MD driver i-PI [41] is available and distributed together with \n\n![](images/cdada522bfbec079887ab060c8a351916be890606e54e7bc1ad84bba5580c7bd.jpg) \nFigure 4.  A simple AiiDA directed acyclic graph for a Quantum ESPRESSO calculation using PWscf (square), with all the input nodes (data, circles; code executable, diamond) and all the output nodes that the daemon creates and connects automatically. \n\nQuantum ESPRESSO. Various implementations of an interface between Quantum ESPRESSO codes and the atomic simulation environment (ASE) [211] are also available. In the following we briefly highlight the integration of Quantum ESPRESSO with AiiDA, the pwtk toolkit for PWscf, and the QE-emacs-modes package for userfriendly editing of Quantum ESPRESSO with the Emacs editor [212]. \n\n3.5.1.  AiiDA: a python materials’ informatics infrastructure.  AiiDA [204] is a comprehensive python infrastructure aimed at accelerating, simplifying, and organizing major efforts in computational science, and in particular computational materials science, with a close integration with the Quantum ESPRESSO distribution. AiiDA is structured around the four pillars of the ADES model (Automation, Data, Environment, and Sharing, [204])), and provides a practical and efficient implementation of all four. In particular, it aims at relieving the work of a computational scientist from the tedious and error-prone tasks of running, overseeing, and storing hundreds or more of calculations daily (Automation pillar), while ensuring that strict protocols are in place to store these calculations in an appropriately structured database that preserves the provenance of all computational steps (Data pillar). This way, the effort of a computational scientist can become focused on developing, curating, or exploiting complex workflows (Environment pillar) that calculate in a robust manner e.g. the desired materials properties of a given input structure, recording expertise in reproducible sequences that can be progressively perfected, while being able to share freely both the workflows and the data generated with public or private common repositories (Sharing). AiiDA is built using an agnostic structure that allows to interface it with any given code—through plugins and a plugin repository— or with different queuing systems, transports to remote HPC resources, and property calculators. In addition, it allows to use arbitrary object-relational mappers (ORMs) as backends (currently, Django and SQLAlchemy are supported). These ORMs map the AiiDA objects (‘Codes’, ‘Calculations’ and ‘Data’) onto python classes, and lead to the representation of calculations through Directed Acyclic Graphs (DAGs) connecting all objects with directional arrows; this ensures both provenance and reproducibility of a calculation. As an example, in figure 4 we present a simple DAG representing a PWscf calculation on ${\\bf B a T i O}_{3}$ . \n\n3.5.2.  Pwtk: a toolkit for PWscf.  The pwtk, standing for PWscfToolKit, is a Tcl scripting interface for PWscf set of programs contained in the Quantum ESPRESSO distribution. It aims at providing a flexible and productive framework. The basic philosophy of pwtk is to lower the learning curve by using syntax that closely matches the input syntax of Quantum ESPRESSO. Pwtk features include: (i) assignment of default values of input variables on a project basis, (ii) reassignment of input variables on the fly, (iii) stacking of input data, (iv) math-parser, (v) extensible and hierarchical configuration (global, project-based, local), (vi) data retrieval functions (i.e. either loading the data from pre-existing input files or retrieving the data from output files), and (vii) a few predefined higher-level tasks, that consist of several seamlessly integrated calculations. Pwtk allows to easily automate large number of calculations and to glue together different computational tasks, where output data of preceding calcul­ ations serve as input for subsequent calculations. Pwtk and related documentation can be downloaded from http://pwtk. quantum-espresso.org. \n\n![](images/f64a19b568f22fb8d5cd2963d81e35e3975400dfc40d652901dab06b27fd736e.jpg) \nFigure 5.  (a) pw.x input file opened in Emacs with pw-mode highlighting the following elements: namelists and their variables (blue and brown), cards and their options (purple and green), comments (red), string and logical variable values (burgundy and cyan, respectively). A mistyped variable (i.e. ibrv instead of ibrav) is not highlighted. (b) An excerpt from the INPUT_PW.html file, which describes the pw.x input file syntax. Both the QE-emacs-modes and the INPUT_PW.html are automatically generated from the Quantum ESPRESSO’s internal definition of the input file syntax. \n\n3.5.3.  QE-emacs-modes.  The QE-emacs-modes package is an open-source collection of Emacs major-modes for making the editing of Quantum ESPRESSO input files easier and more comfortable with Emacs. The package provides syntax highlighting (see figure  5(a)), auto-indentation, auto-completion, and a few utility commands, such as $\\mathtt{M}\\mathrm{-}\\mathtt{x}$ prog−insert template that inserts a respective input file template for the prog program (e.g. pw, neb, pp, projwfc, dos, bands). The QE-emacs-modes are aware of all namelists, variables, cards, and options that are explicitly documented in the INPUT_PROG.html files, which describe the respective input file syntax (see figure  5(b)), where PROG stands for the uppercase name of a given program of Quantum ESPRESSO. The reason for this is that both INPUT_PROG.html files and QE-emacs-modes are automatically generated by the internal helpdoc utility of Quantum ESPRESSO. \n\n# 3.6.  Continuous integration and testing \n\nThe modularization of Quantum ESPRESSO reduces the extent of code duplication, thus improving code maintainability, but it also creates interdependencies between the modules so that changes to one part of the code may impact other parts. In order to monitor and mitigate these side effects we developed a test-suite for non-regression testing. Its purpose is to increase code stability by identifying and correcting those changes that break established functionalities. The test-suite relies on a modified version of python script testcode [213]. \n\n![](images/1d0231085ac008188e408b2b595a44ff0fa476d962aab45ba96ee94b09f03cf0.jpg) \nFigure 6.  Layout of the Quantum ESPRESSO test-suite. The program testcode runs Quantum ESPRESSO executables, extracts numerical values from the output files, and compares the results with reference data. If the difference between these data exceeds a specified threshold, testcode issues an error indicating that a recent commit might have introduced a bug in parts of the code. \n\nThe layout of the test-suite is illustrated in figure  6. The suite is invoked via a Makefile that accepts several options to run sequential or parallel tests or to test one particular feature of the code. The test-suite runs the various executables of Quantum ESPRESSO, extracts the numerical data of interest, compares them to reference data, and decides whether the test is successful using specified thresholds. At the moment, the test-suite contains 181 tests for PW, 14 for PH, 17 for CP, 43 for EPW, and 6 for TDDFpT covering $43\\%$ , $30\\%$ , $29\\%$ , $63\\%$ and $25\\%$ of the blocks, respectively. Moreover, $60\\%$ , $44\\%$ , $47\\%$ , $76\\%$ and $32\\%$ of the subroutines in each of these codes are tested, respectively. \n\nThe test-suite also contains the logic to automatically create reference data by running the relevant executables and storing the output in a benchmark file. These benchmarks are updated only when new tests are added or bugfixes modify the previous behavior. \n\nThe test-suite enables automatic testing of the code using several Buildbot test farms. The test farms monitor the code repository continuously, and trigger daily builds in the night after every new commit. Several compilers (Intel, GFortran, PGI) are tested both in serial and in parallel (openmpi, mpich, Intel mpi and mvapich2) execution with different mathematical libraries (LAPACK, BLAS, ScaLAPACK, FFTW3, MKL, OpenBlas). More information can be found at testfarm.quantum-espresso.org. \n\nThe official mirror of the development version of Quantum ESPRESSO (https://github.com/QEF/q-e) employs a subset of the test-suite to run TravisCI. This tool rapidly identifies erroneous commits and can be used to assist code review during a pull request. \n\ncodes makes a rewrite for new architectures a challenging choice, and a risky one given the fast evolution of computer architectures. \n\nWe think that the main directions followed until now in the development of Quantum ESPRESSO are still valid, not only for new methodologies, but also for adapting to new computer architectures and future ‘exascale’ machines. Namely, we will continue pushing towards code reusability by removing duplicated code and/or replacing it with routines performing well-defined tasks, by identifying the time-intensive sections of the code for machine-dependent optimization, by having documented APIs with predictable behavior and with limited dependency upon global variables, and we will continue to optimize performance and reliability. Finally, we will push towards extended interoperability with other software, also in view of its usefulness for data exchange and for cross-verification, or to satisfy the needs of high-throughput calculations. \n\nStill, the investment in the development and maintenance of state-of-the-art scientific software has historically lagged behind compared to the investment in the applications that use such software, and one wonders is this the correct or even forward-looking approach given the strategic importance of such tools, their impact, their powerful contribution to open science, and their full and complete availability to the entire community. In all of this, the future of materials simulations appear ever more bright [214], and the usefulness and relevance of such tools to accelerating invention and discovery in science and technology is reflected in its massive uptake by the community at large. \n\n# 4.  Outlook and conclusions \n\nThis paper describes the core methodological developments and extensions of Quantum ESPRESSO that have become available, or are about to be released, after [6] appeared. The main goal of Quantum ESPRESSO to provide an efficient and extensible framework to perform simulations with well-established approaches and to develop new methods remains firm, and it has nurtured an ever growing community of developers and contributors. \n\nAchieving such a goal, however, becomes increasingly challenging. On one hand, computational methods become ever more complex and sophisticated, making it harder not only to implement them on a computer but also to verify the correctness of the implementation (for a much needed initial effort on verification of electronic-structure codes based on DFT, see [5]). On the other hand, exploiting the current technological innovations in computer hardware can require massive changes to software and even algorithms. This is especially true for the case of ‘accelerated’ architectures (GPUs and the like), whose exceptional performance can translate to actual calculations only after heavy restructuring and optimization. The complexity of existing \n\n# Acknowledgments \n\nThis work has been partially funded by the European Union through the MaX Centre of Excellence (Grant No. 676598) and by the Quantum ESPRESSO Foundation. SdG acknowledges support from the EU Centre of Excellence E CAM (Grant No. 676531). OA, MC, NC, NM, NLN, and IT acknowledge support from the SNSF National Centre of Competence in Research MARVEL, and from the PASC Platform for Advanced Scientific Computing. TT acknowledges support from NSF Grant No. DMR-1145968. SP, MS, and FG are supported by the Leverhulme Trust (Grant RL-2012-001). MBN acknowledges support by DOD-ONR (N00014-13-1-0635, N00014-11-1-0136, N00014-15-1- 2863) and the Texas Advanced Computing Center at the University of Texas, Austin. RD acknowledges partial support from Cornell University through start-up funding and the Cornell Center for Materials Research (CCMR) with funding from the NSF MRSEC program (DMR-1120296). MK acknowledges support by Building of Consortia for the Development of Human Resources in Science and Technology from the MEXT of Japan. AK acknowledges support from the Slovenian Research Agency (Grant No. P2-0393). This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-06CH11357. This research also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. \n\n# ORCID iDs \n\nP Giannozzi $\\textcircled{1}$ https://orcid.org/0000-0002-9635-3227 \nG Fratesi $\\circledcirc$ https://orcid.org/0000-0003-1077-7596 \nM Kawamura $\\circledcirc$ https://orcid.org/0000-0003-3261-1968 \nH-Y Ko $\\textcircled{1}$ https://orcid.org/0000-0003-1619-6514 \nB Santra $\\circledcirc$ https://orcid.org/0000-0003-3609-2106 \nI Timrov $\\textcircled{1}$ https://orcid.org/0000-0002-6531-9966 \nS Baroni $\\textcircled{1}$ https://orcid.org/0000-0002-3508-6663 \n\n# References \n\n[1] Hohenberg P and Kohn W 1964 Phys. Rev. 136 B864 [2] Kohn W and Sham L J 1965 Phys. Rev. 140 A1133 [3] Vanderbilt D 1990 Phys. Rev. B 41 7892 [4] Blöchl P E 1994 Phys. Rev. B 50 17953 [5] Lejaeghere K et al 2016 Science 351 aad3000 \n[6] Giannozzi P et al 2009 J. Phys.: Condens. Matter 21 395502 [7] Lin L 2016 J. Chem. Theory Comput. 12 2242 [8] Jia J, Vazquez-Mayagoitia A and DiStasio R A Jr private communication [9] Berland K, Cooper V R, Lee K, Schröder E, Thonhauser T, Hyldgaard P and Lundqvist B I 2015 Rep. Prog. Phys. 78 066501 \n[10] Grimme S 2006 J. Comput. Chem. 27 1787 \n[11] Tkatchenko A and Scheffler M 2009 Phys. Rev. Lett. 102 073005 \n[12] Becke A D and Johnson E R 2007 J. Chem. Phys. 127 154108 \n[13] Johnson E R 2017 Non-covalent Interactions in Quantum Chemistry and Physics ed A Otero-de-la-Roza and G DiLabio (Amsterdam: Elsevier) pp 215–48 \n[14] Sclauzero G and Dal Corso A 2013 Phys. Rev. B 87 085108 \n[15] Himmetoglu B, Wentzcovitch R M and Cococcioni M 2011 Phys. Rev. B 84 115108 \n[16] Dal Corso A 2010 Phys. Rev. B 82 075116 \n[17] Dal Corso A 2012 Phys. Rev. B 86 085135 \n[18] Andreussi O, Dabo I and Marzari N 2012 J. Chem. Phys. 136 064102 \n[19] Andreussi O and Marzari N 2014 Phys. Rev. B 90 245101 \n[20] Timrov I, Andreussi O, Biancardi A, Marzari N and Baroni S 2015 J. Chem. Phys. 142 034111 \n[21] Walker B, Saitta A M, Gebauer R and Baroni S 2006 Phys. Rev. Lett. 96 113001 \n[22] Rocca D, Gebauer R, Saad Y and Baroni S 2008 J. Chem. Phys. 128 154105 \n[23] Malcioğlu O B, Gebauer R, Rocca D and Baroni S 2011 Comput. Phys. Commun. 182 1744 \n[24] Ge X, Binnie S, Rocca D, Gebauer R and Baroni S 2014 Comput. Phys. Commun. 185 2080 \n[25] Timrov I, Vast N, Gebauer R and Baroni S 2013 Phys. Rev. B 88 064301 Timrov I, Vast N, Gebauer R and Baroni S 2015 Phys. Rev. B 91 139901 \n[26] Timrov I, Vast N, Gebauer R and Baroni S 2015 Comput. Phys. Commun. 196 460 \n[27] Poncé S, Margine E, Verdi C and Giustino F 2016 Comput. Phys. Commun. 209 116 \n[28] Umari P, Stenuit G and Baroni S 2009 Phys. Rev. B 79 201104 \n[29] Umari P, Stenuit G and Baroni S 2010 Phys. Rev. B 81 115104 \n[30] Schlipf M, Lambert H, Zibouche N and Giustino F 2017 SternheimerGW https://github.com/QEF/SternheimerGW \n[31] Dal Corso A https://github.com/dalcorso/thermo_pw \n[32] Paulatto L, Mauri F and Lazzeri M 2013 Phys. Rev. B 87 214303 \n[33] Fugallo G, Lazzeri M, Paulatto L and Mauri F 2013 Phys. Rev. B 88 045430 \n[34] Varini N, Ceresoli D, Martin-Samos L, Girotto I and Cavazzoni C 2013 Comput. Phys. Commun. 184 1827 \n[35] Barnes T, Kurth T, Carrier P, Wichmann N, Prendergast D, Kent P R C and Deslippe J 2017 Comput. Phys. Commun. 241 52 \n[36] Dal Corso A http://pslibrary.quantum-espresso.org \n[37] Dal Corso A 2015 Comput. Mater. Sci. 95 337 \n[38] Castelli I, Prandini G, Marrazzo A, Mounet N and Marzari N http://materialscloud.org/sssp/ \n[39] Plimpton S 1995 J. Comput. Phys. 117 1 \n[40] Ma C, Martin-Samos L, Fabris S, Laio A and Piccinin S 2015 Comput. Phys. Commun. 195 191 \n[41] Ceriotti M, More J and Manolopoulos D E 2014 Comput. Phys. Commun. 185 1019 \n[42] Wu X, Selloni A and Car R 2009 Phys. Rev. B 79 085102 \n[43] DiStasio R A Jr, Santra B, Li Z, Wu X and Car R 2014 J. Chem. Phys. 141 084502 \n[44] Ko H Y, Jia J, Santra B, Wu X, Car R and DiStasio R A Jr J. Chem. Theory Comput. submitted \n[45] Carnimeo I, Giannozzi P and Baroni S in preparation \n[46] Marsili M and Umari P 2013 Phys. Rev. B 87 205110 \n[47] Paier J, Hirschl R, Marsman M and Kresse G 2005 J. Chem. Phys. 122 234102 \n[48] Damle A, Lin L and Ying L 2015 J. Chem. Theory Comput. 11 1463 \n[49] Damle A, Lin L and Ying L 2017 SIAM J. Sci. Comput. in preparation \n[50] Marzari N and Vanderbilt D 1997 Phys. Rev. B 56 12847 \n[51] Sharma M, Wu Y and Car R 2003 Int. J. Quantum Chem. 95 821 \n[52] Santra B, DiStasio R A Jr, Martelli F and Car R 2015 Mol. Phys. 113 2829 \n[53] Car R and Parrinello M 1985 Phys. Rev. Lett. 55 2471 \n[54] French R H et al 2010 Rev. Mod. Phys. 82 1887 \n[55] Grimme S, Antony J, Ehrlich S and Krieg S 2010 J. Chem. Phys. 132 154104 \n[56] Tkatchenko A, DiStasio R A Jr, Car R and Scheffler M 2012 Phys. Rev. Lett. 108 236402 \n[57] Ambrosetti A, Reilly A M, DiStasio R A Jr and Tkatchenko A 2014 J. Chem. Phys. 140 18A508 \n[58] Blood-Forsythe M A, Markovich T, DiStasio R A Jr, Car R and Aspuru-Guzik A 2016 Chem. Sci. 7 1712 \n[59] Dion M, Rydberg H, Schröder E, Langreth D C and Lundqvist B I 2004 Phys. Rev. Lett. 92 246401 \n[60] Langreth D C and Perdew J P 1977 Phys. Rev. B 15 2884 \n[61] Thonhauser T, Cooper V R, Li S, Puzder A, Hyldgaard P and Langreth D C 2007 Phys. Rev. B 76 125112 \n[62] Román-Pérez G and Soler J M 2009 Phys. Rev. Lett. 103 096102 \n[63] Sabatini R, Küçükbenli E, Kolb B, Thonhauser T and de Gironcoli S 2012 J. Phys. Condens. Matter 24 424209 \n[64] Thonhauser T, Zuluaga S, Arter C A, Berland K, Schröder E and Hyldgaard P 2015 Phys. Rev. Lett. 115 136402 \n[65] Cooper V R 2010 Phys. Rev. B 81 161104 \n[66] Klimeš J, Bowler D R and Michaelides A 2010 J. Phys. Condens. Matter 22 022201 \n[67] Klimeš J, Bowler D R and Michaelides A 2011 Phys. Rev. B 83 195131 \n[68] Berland K and Hyldgaard P 2014 Phys. Rev. B 89 035412 \n[69] Lee K, Murray E D, Kong L, Lundqvist B I and Langreth D C 2010 Phys. Rev. B 82 081101 \n[70] Hamada I and Otani M 2010 Phys. Rev. B 82 153412 \n[71] Vydrov O A and Van Voorhis T 2010 J. Chem. Phys. 133 244103 \n[72] Sabatini R, Gorni T and de Gironcoli S 2013 Phys. Rev. B 87 041108 \n[73] http://schooner.chem.dal.ca \n[74] Becke A 1986 J. Chem. Phys. 85 7184 \n[75] Perdew J, Burke K and Ernzerhof M 1996 Phys. Rev. Lett. 77 3865 \n[76] Perdew J and Yue W 1986 Phys. Rev. B 33 8800 \n[77] Otero-de-la-Roza A and Johnson E R 2012 J. Chem. Phys. 136 174109 \n[78] Hirshfeld F L 1977 Theor. Chim. Acta 44 129 \n[79] Hermann J, DiStasio R A Jr and Tkatchenko A 2017 Chem. Rev. 117 4714 \n[80] Ferri N, DiStasio R A Jr, Ambrosetti A, Car R and Tkatchenko A 2015 Phys. Rev. Lett. 114 176802 \n[81] Cococcioni M and de Gironcoli S 2005 Phys. Rev. B 71 035105 \n[82] Himmetoglu B, Floris A, de Gironcoli S and Cococcioni M 2014 Int. J. Quantum Chem. 114 14 \n[83] Dudarev S L, Botton G A, Savrasov S Y, Humphreys C J and Sutton A P 1998 Phys. Rev. B 57 1505 \n[84] Liechtenstein A I, Anisimov V I and Zaanen J 1995 Phys. Rev. B 52 R5467 \n[85] Timrov I, Cococcioni M and Marzari N in preparation \n[86] Wilson H F, Gygi F and Galli G 2008 Phys. Rev. B 78 113303 \n[87] Nguyen H V and de Gironcoli S 2009 Phys. Rev. B 79 205114 \n[88] Colonna N, Hellgren M and de Gironcoli S 2014 Phys. Rev. B 90 125150 \n[89] Nguyen N L, Colonna N and de Gironcoli S 2014 Phys. Rev. B 90 045138 \n[90] Baroni S, Giannozzi P and Testa A 1987 Phys. Rev. Lett. 58 1861 \n[91] Giannozzi P, de Gironcoli S, Pavone P and Baroni S 1991 Phys. Rev. B 43 7231 \n[92] Gonze X 1995 Phys. Rev. A 52 1096 \n[93] Baroni S, de Gironcoli S, Dal Corso A and Giannozzi P 2001 Rev. Mod. Phys. 73 515 \n[94] Sternheimer R M 1954 Phys. Rev. 96 951 \n[95] Mahan G D 1980 Phys. Rev. A 22 1780 \n[96] Schwartz C and Tiemann J 1959 Ann. Phys. 2 178 \n[97] Zernik W 1964 Phys. Rev. 135 A51 \n[98] Baroni S and Quattropani A 1985 Il Nuovo Cimento D 5 89 \n[99] Casida M 1996 Recent Developments and Applications of Modern Density Functional Theory ed J Seminario (Amsterdam: Elsevier) p 391 \n[100] Jamorski C, Casida M E and Salahub D R 1996 J. Chem. Phys. 104 5134 \n[101] McLachlan A D and Ball M A 1964 Rev. Mod. Phys. 36 844 \n[102] Hübener H and Giustino F 2014 J. Chem. Phys. 141 044117 \n[103] Rocca D, Lu D and Galli G 2010 J. Chem. Phys. 133 164109 \n[104] Rocca D, Ping Y, Gebauer R and Galli G 2012 Phys. Rev. B 85 045116 \n[105] Marsili M, Mosconi E, De Angelis F and Umari P 2017 Phys. Rev. B 95 075415 \n[106] Govoni M and Galli G 2015 J. Chem. Theory Comput. 11 2680 \n[107] Sabatini R, Küçükbenli E, Pham C H and de Gironcoli S 2016 Phys. Rev. B 93 235120 \n[108] Floris A, de Gironcoli S, Gross E K U and Cococcioni M 2011 Phys. Rev. B 84 161102 \n[109] Floris A, Timrov I, Marzari N, de Gironcoli S and Cococcioni M private communication \n[110] Blanchard M, Balan E, Giura P, Beneut K, Yi H, Morin G, Pinilla C, Lazzeri M and Floris A 2014 Phys. Chem. Miner. 41 289 \n[111] Blanchard M et al 2014 Geochim. Cosmochim. Acta 151 19 \n[112] Shukla G, Wu Z, Hsu H, Floris A, Cococcioni M and Wentzcovitch R M 2015 Geophys. Res. Lett. 42 1741 \n[113] Shukla G and Wentzcovitch R M 2016 Phys. Earth Planet. Interior. 260 53 \n[114] Shukla G, Cococcioni M and Wentzcovitch R M 2016 Geophys. Res. Lett. 43 5661 \n[115] Runge E and Gross E 1984 Phys. Rev. Lett. 52 997 \n[116] Marques M A L, Maitra N T, Nogueira F M S, Gross E K U and Rubio A (ed) 2012 Fundamentals of Time-Dependent Density Functional Theory (Lecture Notes in Physics vol 837) (Berlin: Springer) \n[117] Baroni S and Gebauer R The Liouville–Lanczos Approach to Time-Dependent Density-Functional (Perturbation) Theory in Lecture Notes in Physics, vol 837 (Springer, Berlin, 2012) ch 19, pp 375–90 \n[118] Gorni T, Timrov I and Baroni S private communication \n[119] Baroni S and Resta R 1986 Phys. Rev. B 33 7017 \n[120] Tobik J and Dal Corso A 2004 J. Chem. Phys. 120 9934 \n[121] Haydock R, Heine V and Kelly M J 1972 J. Phys. C: Solid State Phys. 5 2845 \n[122] Haydock R, Heine V and Kelly M J 1975 J. Phys. C: Solid State Phys. 8 2591 \n[123] Grüning M, Marini A and Gonze X 2011 Comput. Mater. Sci. 50 2148 \n[124] Davidson E R 1975 J. Comput. Phys. 17 87 \n[125] Onida G, Reining L and Rubio A 2002 Rev. Mod. Phys. 74 601 \n[126] Timrov I, Markov M, Gorni T, Raynaud M, Motornyi O, Gebauer R, Baroni S and Vast N 2017 Phys. Rev. B 95 094301 \n[127] Hedin L 1965 Phys. Rev. 139 A796 \n[128] Hybertsen M S and Louie S G 1985 Phys. Rev. Lett. 55 1418 \n[129] Reining L, Onida G and Godby R W 1997 Phys. Rev. B 56 R4301 \n[130] Wilson H F, Lu D, Gygi F and Galli G 2009 Phys. Rev. B 79 245106 \n[131] Giustino F, Cohen M L and Louie S G 2010 Phys. Rev. B 81 115105 \n[132] Umari P and Fabris S 2012 J. Chem. Phys. 136 174310 \n[133] Umari P, Mosconi E and De Angelis F 2014 Sci. Rep. 4 4467 \n[134] Caruso F, Lambert H and Giustino F 2015 Phys. Rev. Lett. 114 146404 \n[135] Lambert H and Giustino F 2013 Phys. Rev. B 88 075117 \n[136] Pickard C J and Mauri F 2001 Phys. Rev. B 63 245101 \n[137] d’Avezac M, Marzari N and Mauri F 2007 Phys. Rev. B 76 165122 \n[138] Pickard C J and Mauri F 2002 Phys. Rev. Lett. 88 086403 \n[139] Petrilli H M, Blöchl P E, Blaha P and Schwarz K 1998 Phys. Rev. B 57 14690 \n[140] Zwanziger J W 2009 J. Phys.: Condens. Matter 21 195501 \n[141] Bahramy M S, Sluiter M H F and Kawazoe Y 2007 Phys. Rev. B 76 035124 \n[142] von Bardeleben H J, Cantin J L, Vrielinck H, Callens F, Binet L, Rauls E and Gerstmann U 2014 Phys. Rev. B 90 085203 \n[143] Pigliapochi R, Pell A J, Seymour I D, Grey C P, Ceresoli D and Kaupp M 2017 Phys. Rev. B 95 054412 \n[144] Yates J R, Pickard C J and Mauri F 2007 Phys. Rev. B 76 024401 \n[145] Küçükbenli E, Sonkar K, Sinha N and de Gironcoli S 2012 J. Phys. Chem. A 116 3765 \n[146] de Gironcoli S 1995 Phys. Rev. B 51 6773 \n[147] Xiao D, Shi J and Niu Q 2005 Phys. Rev. Lett. 95 137204 \n[148] Thonhauser T, Ceresoli D, Vanderbilt D and Resta R 2005 Phys. Rev. Lett. 95 137205 \n[149] Thonhauser T, Ceresoli D, Mostofi A A, Marzari N, Resta R and Vanderbilt D 2009 J. Chem. Phys. 131 101101 \n[150] Ceresoli D, Gerstmann U, Seitsonen A P and Mauri F 2010 Phys. Rev. B 81 060409 \n[151] George B M et al 2013 Phys. Rev. Lett. 110 136803 \n[152] Bodrog Z and Gali A 2014 J. Phys.: Condens. Matter 26 015305 \n[153] Gougoussis C, Calandra M, Seitsonen A P and Mauri F 2009 Phys. Rev. B 80 075102 \n[154] Gougoussis C, Calandra M, Seitsonen A, Brouder C, Shukla A and Mauri F 2009 Phys. Rev. B 79 045118 \n[155] Bunău O and Calandra M 2013 Phys. Rev. B 87 205105 \n[156] Taillefumier M, Cabaret D, Flank A M and Mauri F 2002 Phys. Rev. B 66 195107 \n[157] Fratesi G, Lanzilotto V, Floreano L and Brivio G P 2013 J. Phys. Chem. C 117 6632 \n[158] Fratesi G, Lanzilotto V, Stranges S, Alagia M, Brivio G P and Floreano L 2014 Phys. Chem. Chem. Phys. 16 14834 \n[159] Lazzeri M and de Gironcoli S 2002 Phys. Rev. B 65 245402 \n[160] Deinzer G, Birner G and Strauch D 2003 Phys. Rev. B 67 144304 \n[161] Calandra M, Lazzeri M and Mauri F 2007 Physica C 456 38 \n[162] Callaway J 1959 Phys. Rev. 113 1046 \n[163] Markov M, Sjakste J, Fugallo G, Paulatto L, Lazzeri M, Mauri F and Vast N 2016 Phys. Rev. B 93 064301 \n[164] Markov M, Sjakste J, Fugallo G, Paulatto L, Lazzeri M, Mauri F and Vast N 2017 Phys. Rev. Lett. submitted \n[165] Ward A, Broido D A, Stewart D A and Deinzer G 2009 Phys. Rev. B 80 125203 \n[166] Fugallo G, Cepellotti A, Paulatto L, Lazzeri M, Marzari N and Mauri F 2014 Nano Lett. 14 6109 \n[167] Cepellotti A, Fugallo G, Paulatto L, Lazzeri M, Mauri F and Marzari N 2015 Nat. Commun. 6 \n[168] Li W, Carrete J, Katcho N A and Mingo N 2014 Comp. Phys. Commun. 185 1747–58 \n[169] Giustino F 2017 Rev. Mod. Phys. 89 015003 \n[170] Marzari N, Mostofi A A, Yates J R, Souza I and Vanderbilt D 2012 Rev. Mod. Phys. 84 1419 \n[171] Mostofi A A, Yates J R, Pizzi G, Lee Y S, Souza I, Vanderbilt D and Marzari N 2014 Comput. Phys. Commun. 185 2309 \n[172] Agapito L A, Curtarolo S and Buongiorno Nardelli M 2015 Phys. Rev. X 5 011006 \n[173] Calzolari A and Buongiorno Nardelli M 2013 Sci. Rep. 3 \n[174] Umari P and Pasquarello A 2002 Phys. Rev. Lett. 89 157602 \n[175] Wang Y, Shang S, Liu Z K and Chen L Q 2012 Phys. Rev. B 85 224303 \n[176] King-Smith R and Vanderbilt D 1993 Phys. Rev. B 47 1651 \n[177] Umari P, Gonze X and Pasquarello A 2003 Phys. Rev. Lett. 90 027401 \n[178] Tomasi J, Mennucci B and Cammi R 2005 Chem. Rev. 105 2999 \n[179] Fattebert J L and Gygi F 2002 J. Comput. Chem. 23 662 \n[180] Fisicaro G, Genovese L, Andreussi O, Marzari N and Goedecker S 2016 J. Chem. Phys. 144 014103 \n[181] Dupont C, Andreussi O and Marzari N 2013 J. Chem. Phys. 139 214110 \n[182] Andreussi O, Dabo I, Fisicaro G, Goedecker S, Timrov I, Baroni S and Marzari N 2016 Environ 0.2: a library for environment effect in first-principles simulations of materials www.quantum-environ.org \n[183] Cococcioni M, Mauri F, Ceder G and Marzari N 2005 Phys. Rev. Lett. 94 145501 \n[184] Scherlis D A, Fattebert J L, Gygi F, Cococcioni M and Marzari N 2006 J. Chem. Phys. 124 074103 \n[185] Dabo I, Kozinsky B, Singh-Miller N E and Marzari N 2008 Phys. Rev. B 77 115139 \n[186] Laio A, VandeVondele J and Rothlisberger U 2002 J. Chem. Phys. 116 6941 \n[187] MacDonald A H and Vosko S H 1979 J. Phys. C: Solid State Phys. 12 2977 \n[188] Rajagopal A K and Callaway J 1973 Phys. Rev. B 7 1912 \n[189] Brumme T, Calandra M and Mauri F 2014 Phys. Rev. B 89 245406 \n[190] Bengtsson L 1999 Phys. Rev. B 59 12301 \n[191] Topsakal M and Ciraci S 2012 Phys. Rev. B 85 045121 \n[192] Neugebauer J and Scheffler M 1992 Phys. Rev. B 46 16067 \n[193] Meyer B and Vanderbilt D 2001 Phys. Rev. B 63 205426 \n[194] Štich I, Car R, Parrinello M and Baroni S 1989 Phys. Rev. B 39 4997 \n[195] Jepsen O and Andersen O K 1971 Solid State Commun. 9 1763 \n[196] Blöchl P E, Jepsen O and Andersen O K 1994 Phys. Rev. B 49 16223 \n[197] Kawamura M, Gohda Y and Tsuneyuki S 2014 Phys. Rev. B 89 094515 \n[198] Zadra F and Dal Corso A private communication \n[199] Hahn T (ed) 2005 International Tables for Crystallography Volume A: Space-Group Symmetry (New York: Springer) \n[200] Marek A, Blum V, Johanni R, Havu V, Lang B, Auckenthaler T, Heinecke A, Bungartz H J and Lederer H 2014 J. Phys.: Condens. Matter 26 213201 \n[201] Marini A, Hogan C, Grüning M and Varsano D 2009 Comput. Phys. Commun. 180 1392 \n[202] Martin-Samos L and Bussi G 2009 Comput. Phys. Commun. 180 1416 \n[203] Deslippe J, Samsonidze G, Strubbe D A, Jain M, Cohen M L and Louie S G 2012 Comput. Phys. Commun. 183 1269 \n[204] Pizzi G, Cepellotti A, Sabatini R, Marzari N and Kozinsky B 2016 Comput. Mater. Sci. 111 218 \n[205] Mounet N, Gibertini M, Schwaller P, Merkys A, Castelli I E, Cepellotti A, Pizzi G and Marzari N 2016 arXiv:1611.05234 \n[206] Supka A R et al 2017 Comput. Mater. Sci. 136 76 \n[207] The HDF Group 2000–2010 Hierarchical data format version 5 www.hdfgroup.org/HDF5 \n[208] Calzolari A, Souza I, Marzari N and Buongiorno Nardelli M 2004 Phys. Rev. B 69 035108 \n[209] Ferretti A, Calzolari A, Bonferroni B and Di Felice R 2007 J. Phys.: Condens. Matter 19 036215 \n[210] Bonomi M et al 2009 Comput. Phys. Commun. 180 1961 \n[211] Bahn S R and Jacobsen K W 2002 Comput. Sci. Eng. 4 56 \n[212] Moon D A et al 2017 EMACS: The Extensible and Customizable Display Editor www.gnu.org/software/ emacs/ \n[213] Spencer J 2017 Testcode https://github.com/jsspencer/ testcode \n[214] Marzari N 2016 Nat. Mater. 15 381 " + }, + { + "id": "10.1038_nature22391", + "DOI": "10.1038/nature22391", + "DOI Link": "http://dx.doi.org/10.1038/nature22391", + "Relative Dir Path": "mds/10.1038_nature22391", + "Article Title": "Layer-dependent ferromagnetism in a van der Waals crystal down to the monolayer limit", + "Authors": "Huang, B; Clark, G; Navarro-Moratalla, E; Klein, DR; Cheng, R; Seyler, KL; Zhong, D; Schmidgall, E; McGuire, MA; Cobden, DH; Yao, W; Xiao, D; Jarillo-Herrero, P; Xu, XD", + "Source Title": "NATURE", + "Abstract": "Since the discovery of graphene(1), the family of two-dimensional materials has grown, displaying a broad range of electronic properties. Recent additions include semiconductors with spin-valley coupling(2), Ising superconductors(3-5) that can be tuned into a quantum metal(6), possible Mott insulators with tunable charge-density waves(7), and topological semimetals with edge transport(8,9). However, no two-dimensional crystal with intrinsic magnetism has yet been discovered(10-14); such a crystal would be useful in many technologies from sensing to data storage(15). Theoretically, magnetic order is prohibited in the two-dimensional isotropic Heisenberg model at finite temperatures by the Mermin-Wagner theorem(16). Magnetic anisotropy removes this restriction, however, and enables, for instance, the occurrence of two-dimensional Ising ferromagnetism. Here we use magneto-optical Kerr effect microscopy to demonstrate that monolayer chromium triiodide (CrI3) is an Ising ferromagnet with out-of-plane spin orientation. Its Curie temperature of 45 kelvin is only slightly lower than that of the bulk crystal, 61 kelvin, which is consistent with a weak interlayer coupling. Moreover, our studies suggest a layer-dependent magnetic phase, highlighting thickness-dependent physical properties typical of van der Waals crystals(17-19). Remarkably, bilayer CrI3 displays suppressed magnetization with a metamagnetic effect(20), whereas in trilayer CrI3 the interlayer ferromagnetism observed in the bulk crystal is restored. This work creates opportunities for studying magnetism by harnessing the unusual features of atomically thin materials, such as electrical control for realizing magnetoelectronics(12), and van der Waals engineering to produce interface phenomena(15).", + "Times Cited, WoS Core": 4484, + "Times Cited, All Databases": 4790, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000402823400033", + "Markdown": "# Layer-dependent ferromagnetism in a van der Waals crystal down to the monolayer limit \n\nBevin Huang1\\*, Genevieve Clark2\\*, Efrén Navarro-Moratalla3\\*, Dahlia R. Klein3, Ran Cheng4, Kyle L. Seyler1, Ding Zhong1, Emma Schmidgall1, Michael A. McGuire5, David H. Cobden1, Wang ${\\mathrm{Yao}}^{6}$ , Di Xiao4, Pablo Jarillo-Herrero3 & Xiaodong $\\mathrm{{Xu^{\\bar{1},2}}}$ \n\nSince the discovery of graphene1, the family of two-dimensional materials has grown, displaying a broad range of electronic properties. Recent additions include semiconductors with spin– valley coupling2, Ising superconductors3–5 that can be tuned into a quantum metal6, possible Mott insulators with tunable chargedensity waves7, and topological semimetals with edge transport8,9. However, no two-dimensional crystal with intrinsic magnetism has yet been discovered10–14; such a crystal would be useful in many technologies from sensing to data storage15. Theoretically, magnetic order is prohibited in the two-dimensional isotropic Heisenberg model at finite temperatures by the Mermin–Wagner theorem16. Magnetic anisotropy removes this restriction, however, and enables, for instance, the occurrence of two-dimensional Ising ferromagnetism. Here we use magneto-optical Kerr effect microscopy to demonstrate that monolayer chromium triiodide $\\left(\\mathbf{CrI}_{3}\\right)$ is an Ising ferromagnet with out-of-plane spin orientation. Its Curie temperature of 45 kelvin is only slightly lower than that of the bulk crystal, 61 kelvin, which is consistent with a weak interlayer coupling. Moreover, our studies suggest a layer-dependent magnetic phase, highlighting thickness-dependent physical properties typical of van der Waals crystals17–19. Remarkably, bilayer $\\mathbf{CrI}_{3}$ displays suppressed magnetization with a metamagnetic effect20, whereas in trilayer $\\mathbf{CrI}_{3}$ the interlayer ferromagnetism observed in the bulk crystal is restored. This work creates opportunities for studying magnetism by harnessing the unusual features of atomically thin materials, such as electrical control for realizing magnetoelectronics12, and van der Waals engineering to produce interface phenomena15. \n\nMagnetic anisotropy is an important requirement for ­realizing two-dimensional (2D) magnetism. In ultrathin metallic films, whether an easy axis can originate from symmetry reduction at the interface or surface is dependent on substrate properties and interface ­quality21–23. In contrast, most van der Waals magnets have an intrinsic magnetocrystalline anisotropy owing to the reduced crystal symmetry of their layered structures. Several layered magnets exhibit effective 2D magnetic interactions even in their bulk crystal form24,25. This implies that it might be possible to retain a magnetic ground state in a ­monolayer. In addition to enabling the study of magnetism in naturally formed crystals in the true 2D limit, layered magnets provide a platform for studying the thickness dependence of magnetism in isolated single crystals where the interaction with the underlying substrate is weak. These covalently bonded van der Waals layers prevent complex magnetization reorientations induced by epitaxial lattice reconstruction and strain23. For layered materials, these advantages come at a low fabrication cost, since the micromechanical exfoliation technique is much simpler than conventional approaches requiring sputtering or sophisticated molecular beam epitaxy. \n\nA variety of layered magnetic compounds have recently been investigated to determine whether their magnetic properties can be retained down to monolayer thickness12–14,26. Recent Raman studies suggest ferromagnetic ordering in few-layer ${\\mathrm{Cr}}_{2}{\\mathrm{Ge}}_{2}{\\mathrm{Te}}_{6}$ and antiferromagnetic ordering in monolayer $\\mathrm{FePS}_{3}{}^{27,28}$ . However, no evidence yet exists for ferromagnetism persisting down to the monolayer limit. One promising candidate is bulk crystalline $\\mathrm{CrI}_{3}$ . It shows layered Ising ferromagnetism below a Curie temperature $(T_{\\mathrm{C}})$ of $61\\mathrm{K}$ with an out-of-plane easy axis (Fig. 1a and b, Extended Data Fig. 1)10,29. Given its van der Waals nature, we expect magnetocrystalline anisotropy, which could possibly lift the Mermin–Wagner restriction to stabilize long-range ­ferromagnetic ordering even in a monolayer. \n\nIn our experiment, we obtained atomically thin $\\mathrm{CrI}_{3}$ flakes by mechanical exfoliation of bulk crystals onto oxidized silicon substrates (see Methods for $\\mathrm{CrI}_{3}$ crystal growth10 and fabrication details). Given the reactivity of $\\mathrm{CrI}_{3}$ flakes, sample preparation was carried out in a glove box under an inert atmosphere. We mainly employed optical ­contrast based on the pixel red–green–blue (RGB) value to index the number of layers in a flake (see Methods for quantitative ­optical microscopy in $\\mathrm{CrI}_{3}$ and Extended Data Figs 2–4). Figure 1c is an ­optical micrograph of a typical multi-step $\\mathrm{CrI}_{3}$ flake on a $2\\bar{8}\\bar{5}{\\cdot}\\mathrm{nm}\\bar{\\mathrm{SiO}}_{2}/$ Si ­substrate, showing regions ranging from 1 to 6 layers in thickness. Figure 1d shows an optical contrast map of the same region illuminated by 631-nm-filtered light. The extracted optical contrast as a function of layer thickness is in good agreement with models based on the Fresnel equations (Fig. 1e). To accurately determine the correspondence between optical contrast and flake thickness, we also measured the thickness of $\\mathrm{CrI}_{3}$ flakes by atomic force microscopy, determined to be $0.7\\mathrm{nm}$ per layer, after encapsulation with few-layer graphene (see Extended Data Fig. 5). \n\nTo probe the magnetic order, we employed polar magneto-optical Kerr effect (MOKE) measurements as a function of applied external magnetic field perpendicular to the sample plane (Faraday geometry). This design is sensitive to out-of-plane magnetization, and can detect small Kerr rotations, $\\theta_{\\mathrm{K}},$ of linearly polarized light down to $100\\upmu\\mathrm{rad}$ using an alternating-current polarization modulation technique as laid out in Extended Data Fig. 6. All optical measurements were carried out using a $633\\mathrm{-nm}$ HeNe laser and at a temperature of $15\\mathrm{K}$ , unless otherwise specified. Figure 1f illustrates the MOKE signal from a thin bulk flake of $\\mathrm{CrI}_{3}$ . The observed hysteresis curve and remanent $\\theta_{\\mathrm{K}}$ at zero magnetic field $\\mu_{\\mathrm{o}}H{=}0$ T (where $\\mu_{\\mathrm{o}}$ is the magnetic constant) are hallmarks of ferromagnetic ordering, consistent with its bulk ferromagnetism with out-of-plane magnetization. The negative remanent $\\theta_{\\mathrm{K}}$ when approaching zero field from a positive external field is a consequence of thin-film interference from reflections at the ${\\mathrm{CrI}}_{3}{\\mathrm{-}}{\\mathrm{SiO}}_{2}$ and $\\mathrm{SiO}_{2}–\\mathrm{Si}$ interfaces (see Methods for thin-film interference and Extended Data Fig. 7). \n\n![](images/20b76d820443b2e9106ff9a5feae9ab4c8341d2d8f37cb36508af6e59e2aa30e.jpg) \nFigure 1 | Crystal structure, layer thickness identification, and MOKE representative $\\mathrm{CrI}_{3}$ flake. d, Calculated optical contrast map of the same of bulk $\\mathbf{CrI}_{3}$ . a, View of the in-plane atomic lattice of a single $\\mathrm{CrI}_{3}$ layer. flake with a 631-nm optical filter. The scale bar in c is $3\\upmu\\mathrm{m}$ . e, Averaged Grey and purple balls represent Cr and I atoms, respectively. The $\\mathrm{Cr}^{\\dot{3}+}$ ions optical contrast of the steps of the sample with different numbers of layers are coordinated to six $\\mathrm{I}^{-}$ ions to form edge-sharing octahedra arranged (circles) fitted by a model based on Fresnel’s equations (solid line). f, Polar in a hexagonal honeycomb lattice. b, Out-of-plane view of the same $\\mathrm{CrI}_{3}$ MOKE signal of a thin bulk $\\mathrm{CrI}_{3}$ crystal. structure depicting the Ising spin orientation. c, Optical micrograph of a \n\nRemarkably, the ferromagnetic ordering remains in the monolayer limit. Figure 2a shows $\\theta_{\\mathrm{K}}$ as a function of $\\mu_{\\mathrm{o}}H$ for a monolayer $\\mathrm{CrI}_{3}$ flake (inset to Fig. 2a). A single hysteresis loop in $\\theta_{\\mathrm{K}}$ centred around $\\mu_{\\mathrm{o}}H{=}0\\mathrm{T},$ with a non-zero remanent Kerr rotation, demonstrates out-of-plane spin polarization. This implies Ising ferromagnetism in ­monolayer $\\mathrm{CrI}_{3}$ . As expected, $\\theta_{\\mathrm{K}}$ is independent of the excitation power (Fig. 2b). In the following, all data are taken with an excitation power of $10\\upmu\\mathrm{W}.$ We have measured a total of 12 monolayer samples, which show similar MOKE behaviour with consistent remanent $\\theta_{\\mathrm{K}}$ values of about $5\\pm2$ mrad at $\\mu_{\\mathrm{o}}H{=}0$ T (Extended Data Fig. 8a). The coercive field $(\\mu_{\\mathrm{o}}H_{\\mathrm{c}})$ , which is approximately $50\\mathrm{mT}$ for the sample in Fig. 2a, can vary between samples owing to the formation of domain structures in some samples. \n\nFigure 2c shows spatial maps of $\\theta_{\\mathrm{K}}$ for another monolayer, taken at selected magnetic field values. After cooling the sample from above $T_{\\mathrm{C}}$ at $\\mu_{\\mathrm{o}}H{=}0$ T, the entire monolayer is spontaneously magnetized (in blue, defined as spin down). As the field is increased to $0.15\\mathrm{T}_{:}$ the magnetization in the upper half of the flake switches direction (now spin up, in red). As the field is further increased to $0.3\\mathrm{T}_{:}$ , the lower half of the monolayer flips and the entire flake becomes spin up, parallel to $\\mu_{\\mathrm{o}}H$ . This observation of micrometre-scale lateral domains suggests ­different values of coercivity in each domain. Indeed, magnetic field sweeps $\\mathrm{\\dot{\\theta}_{K}}$ versus $\\mu_{\\mathrm{o}}H)$ taken at discrete points ranging across both domains (Fig. 2d) show the difference in coercive field between the upper and lower half of the monolayer. Sweeps taken only on the upper domain (marked by a blue circle) show a much narrower hysteresis loop (about $50\\mathrm{mT}$ ) than sweeps from spots on the lower domain (orange and ­purple circles, about $200\\mathrm{mT}$ ). When the beam spot is centred between the two domains, contributions from both can be seen in the resulting hysteresis loop (green circle), a consequence of the approximately $1\\mathrm{-}\\upmu\\mathrm{m}$ beam spot illuminating both domains. \n\n![](images/74cdbe65cae6f89178b5f1f93fef6852261a5414aa533356d9b77bbdf14e859d.jpg) \nFigure 2 | MOKE measurements of monolayer $\\mathbf{CrI}_{3}$ . a, Polar MOKE monolayer. The scale bar is $1\\upmu\\mathrm{m}$ . d, $\\theta_{\\mathrm{K}}$ versus $\\mu_{0}H$ sweeps taken at four signal for a $\\mathrm{CrI}_{3}$ monolayer. The inset shows an optical image of an points marked by dots on the $\\mu_{\\mathrm{o}}H=0.3\\mathrm{T}$ map in c. e, Temperature isolated monolayer (the scale bar is $2\\upmu\\mathrm{m}$ ). b, Power dependence of the dependence of MOKE signal with the sample initially cooled at $\\mu_{\\mathrm{o}}H=0$ T MOKE signal taken at incident powers of $3\\upmu\\mathrm{W}$ (blue), $10\\upmu\\mathrm{W}$ (pink), and (blue) and $0.15\\mathrm{T}$ (red). $30\\upmu\\mathrm{W}$ (red). c, MOKE maps at $\\mu_{\\mathrm{o}}H=0$ T, $0.15\\mathrm{T}$ and $0.3\\mathrm{T}$ on a different \n\nTo determine the monolayer $T_{\\mathrm{C}},$ we perform an analysis of the ­irreversible field-cooled and zero-field-cooled Kerr signal. Zero-fieldcooled sweeps were performed by measuring $\\theta_{\\mathrm{K}}$ while cooling the sample in zero field. After warming up to a temperature well above $T_{\\mathrm{C}}\\left(90\\mathrm{K}\\right)$ , the field-cooled measurement is taken upon cooling down in the presence of a small external magnetic field ( $\\langle\\mu_{\\mathrm{o}}H=0.15\\mathrm{T}\\rangle$ . Thermomagnetic irreversibility can be observed below $T_{\\mathrm{C}},$ at which point the zero-field-cooled sweep and the field-cooled sweep diverge as illustrated in Fig. 2e. We measured the average $T_{\\mathrm{C}}$ for the monolayer samples to be $45\\mathrm{K},$ slightly lower than the value (61 K) for bulk samples. \n\nThe layered structure of $\\mathrm{CrI}_{3}$ provides a unique opportunity to investigate ferromagnetism as a function of layer thickness. ­Figure $3\\mathrm{a-c}$ shows $\\theta_{\\mathrm{K}}$ versus $\\mu_{\\mathrm{o}}H$ for representative 1–3-layer $\\mathrm{CrI}_{3}$ samples. All measured monolayer and trilayer samples consistently show ferromagnetic behaviour with a single hysteresis loop centred at $\\mu_{\\mathrm{o}}H{=}0$ T (Fig. 3a and c and Extended Data Fig. 8). Both remanent and saturation values of $\\theta_{\\mathrm{K}}$ for trilayers are about $50\\pm10$ mrad, which is an order of magnitude larger than for monolayers. This drastic change in $\\theta_{\\mathrm{K}}$ on moving from monolayer to trilayer may be due to a layer-­dependent electronic structure, leading to weaker optical resonance effects at $633\\mathrm{nm}$ for the monolayer than for the trilayer (see Extended Data Fig. 9 and Methods for thin-film interference and MOKE signal in $\\mathrm{CrI}_{3}.$ ). We find that for trilayers and thin bulk samples, $T_{\\mathrm{C}}$ is consistent with the bulk value of $61\\mathrm{K}$ . The relatively small decrease of $T_{\\mathrm{C}}$ from bulk to few-layer and monolayer samples suggests that interlayer interactions do not dominate the ferromagnetic ordering in $\\mathrm{CrI}_{3}$ . Compared with metallic magnetic thin films whose magnetic properties strongly depend on the underlying substrate30, the weak layer-dependent $T_{\\mathrm{C}}$ also implies a negligible substrate effect on the ferromagnetic phenomena in atomically thin $\\mathrm{CrI}_{3}$ . As such, exfoliated $\\mathrm{CrI}_{3}$ of all thicknesses can be regarded as isolated single crystals. \n\nA further observation is that bilayer $\\mathrm{CrI}_{3}$ shows a markedly different magnetic behaviour from the monolayer (Fig. 3b). For all ten bilayer samples measured, the MOKE signal is strongly suppressed, with $\\theta_{\\mathrm{K}}$ approaching zero (subject to slight variation between samples, see Extended Data Fig. 8b) at field values $\\pm0.65\\mathrm{T}$ . This observation implies a compensation for the out-of-plane magnetization. Upon crossing a critical field, $\\theta_{\\mathrm{K}}$ shows a sharp jump, depicting a sudden recovery of the out-of-plane co-parallel orientation of the spins. This new magnetic state has a saturation $\\theta_{\\mathrm{{K}}}$ $\\mathrm{:(40\\pm10mrad)}$ an order of magnitude larger than that of monolayer samples, and slightly smaller than for trilayers. \n\nThe suppression of the Kerr signal at zero magnetic field demonstrates that the ground state has zero out-of-plane magnetization. The plateau behaviour of the magnetization curve—showing three horizontal regimes between magnetic field values of $-1.1\\mathrm{T}$ and $1.1\\mathrm{T}$ (Fig. 3b)—further implies that there are no in-plane spin components; otherwise, one would expect a gradual increase of the MOKE signal with increasing perpendicular magnetic field. Rather, our observation suggests that each individual layer is ferromagnetically ordered (out-of-plane) while the interlayer coupling is antiferromagnetic. In this case, the strength of the interlayer coupling determines the field at which jumps between different plateaus occur, $\\pm0.65\\mathrm{T}$ Although the detailed mechanism of this coupling remains unclear, the different magnetic phases observed in bilayers and trilayers emphasizes the strong layer-dependent interplay between different mechanisms that stabilize magnetic ordering in the atomically thin limit. \n\n![](images/1b7e6c3da9901dcfb71120bb6b211a8ad4819f27e19b91241d4f379a780d0d8b.jpg) \nFigure 3 | Layer-dependent magnetic ordering in atomically-thin $\\mathbf{CrI}_{3}$ . a, MOKE signal on a monolayer (1L) $\\mathrm{CrI}_{3}$ flake, showing hysteresis in the Kerr rotation as a function of applied magnetic field, indicative of ferromagnetic behaviour. b, MOKE signal from a bilayer $\\mathrm{CrI}_{3}$ showing vanishing Kerr rotation for applied fields $\\pm0.65\\mathrm{T},$ suggesting antiferromagnetic behaviour. Insets depict bilayer (2L) magnetic ground states for different applied fields. c, MOKE signal on a trilayer (3L) flake, showing a return to ferromagnetic behaviour. \n\nAnother bilayer feature distinct from those of monolayers is the ­vanishingly small hysteresis around the jumps, suggesting negligible net perpendicular anisotropy. A possible interpretation is that the shape anisotropy (which prefers in-plane spin orientation) nearly compensates for the intrinsic magnetocrystalline anisotropy (which prefers outof-plane spin orientation) so that the overall anisotropy is close to zero. \n\nThe insets in Fig. 3b display the layer-by-layer switching behaviour that leads to plausible magnetic ground states of bilayer $\\mathrm{CrI}_{3}$ . When the magnetic field is $\\pm0.65\\mathrm{T}_{:}$ the magnetization of the two layers are oppositely oriented to one another. Thus, the net magnetization vanishes and bilayer $\\mathrm{CrI}_{3}$ behaves as an antiferromagnet with an exchange field of about $0.65\\mathrm{T}.$ . When $\\left|\\mu_{\\mathrm{o}}H\\right|{>}0.65\\mathrm{T}$ magnetization in one layer flips to align with the external magnetic field and restores out-of-plane magnetization, giving rise to the large MOKE signal. At around $|\\mu_{\\mathrm{o}}H|=0.65\\mathrm{T}$ , the MOKE signal sharply increases from near zero to its saturation value within about $100\\mathrm{mT},$ suggesting an abrupt increase of out-of-plane magnetization triggered by a small change of magnetic field. Such behaviour is indicative of metamagnetism, the magnetic-field-driven transition from antiferromagnetic ordering to a fully spin-polarized state20. \n\nIn summary, here we demonstrated 2D ferromagnetism in exfoliated monolayer $\\mathrm{CrI}_{3}$ . The observed monolayer $T_{\\mathrm{C}}$ suggests that these 2D magnets are weakly coupled to their substrates and can be regarded as isolated magnets. This is in distinct contrast with conventional metallic monolayer films, whose magnetism is strongly affected by substrate coupling. We also observed strong evidence for layer-­dependent ­magnetic phases, from ferromagnetism in the monolayer, to antiferromagnetism in the bilayer, and back to ferromagnetism in the trilayer and bulk. We envision that the demonstration of intrinsic ferromagnetism in monolayer $\\mathrm{CrI}_{3}$ as well as its layer-dependent magnetic behaviour will provide opportunities for the investigation of quantum phenomena, such as topological effects in hybrid superconducting– ferromagnetic van der Waals heterostructures as well as the engineering of new magneto-optoelectronic devices at low temperature, such as ferromagnetic light emitters. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# received 12 January; accepted 20 April 2017. \n\n1. Novoselov, K. S. et al. Electric field effect in atomically thin carbon films. Science 306, 666–669 (2004). \n2. Xu, X., Yao, W., Xiao, D. & Heinz, T. F. Spin and pseudospins in layered transition metal dichalcogenides. Nat. Phys. 10, 343–350 (2015). \n3. Saito, Y. et al. Superconductivity protected by spin-valley locking in ion-gated MoS2. Nat. Phys. 12, 144–149 (2016). \n4. Lu, J. M. et al. Evidence for two-dimensional Ising superconductivity in gated MoS2. Science 350, 1353–1357 (2015). \n5. Xi, X. et al. Ising pairing in superconducting NbSe2 atomic layers. Nat. Phys. 12, 139–143 (2015). \n6. Tsen, A. W. et al. Nature of the quantum metal in a two-dimensional crystalline superconductor. Nat. Phys. 12, 208–212 (2015). \n7. Yu, Y. et al. Gate-tunable phase transitions in thin flakes of 1T-TaS2. Nat. Nanotechnol. 10, 270–276 (2015). \n8. Fei, Z. et al. Topological insulator behavior in monolayer $\\mathsf{W T e}_{2}$ Preprint at https://arxiv.org/abs/1610.07924 (2016). \n9. Qian, X., Liu, J., Fu, L. & Li, J. Quantum spin Hall effect in two-dimensional transition metal dichalcogenides. Science 346, 1344–1347 (2014). \n10.\t McGuire, M. A., Dixit, H., Cooper, V. R. & Sales, B. C. Coupling of crystal structure and magnetism in the layered, ferromagnetic insulator CrI3. Chem. Mater. 27, 612–620 (2015). \n11.\t Li, X. & Yang, J. CrXTe3 $\\langle\\mathsf{X}=\\mathsf{S}\\mathsf{i}$ , Ge) nanosheets: two dimensional intrinsic ferromagnetic semiconductors. J. Mater. Chem. C 2, 7071–7076 (2014). \n12.\t Zhang, W.-B., Qu, Q., Zhu, P. & Lam, C.-H. Robust intrinsic ferromagnetism and half semiconductivity in stable two-dimensional single-layer chromium trihalides. J. Mater. Chem. C 3, 12457–12468 (2015). \n13.\t Lin, M.-W. et al. Ultrathin nanosheets of CrSiTe3: a semiconducting twodimensional ferromagnetic material. J. Mater. Chem. C 4, 315–322 (2016). \n14.\t Sivadas, N., Daniels, M. W., Swendsen, R. H., Okamoto, S. & Xiao, D. Magnetic ground state of semiconducting transition-metal trichalcogenide monolayers. Phys. Rev. B 91, 235425 (2015). \n15.\t Soumyanarayanan, A., Reyren, N., Fert, A. & Panagopoulos, C. Emergent phenomena induced by spin–orbit coupling at surfaces and interfaces. Nature 539, 509–517 (2016). \n16.\t Mermin, N. D. & Wagner, H. Absence of ferromagnetism or antiferromagnetism in one- or two-dimensional isotropic Heisenberg models. Phys. Rev. Lett. 17, 1133–1136 (1966). \n17.\t Novoselov, K. S. et al. Unconventional quantum Hall effect and Berry’s phase of $2\\pi$ ​in bilayer graphene. Nat. Phys. 2, 177–180 (2006). \n18.\t Mak, K. F., Lee, C., Hone, J., Shan, J. & Heinz, T. F. Atomically thin ${\\mathsf{M o S}}_{2}$ : a new direct-gap semiconductor. Phys. Rev. Lett. 105, 136805 (2010). \n19.\t Splendiani, A. et al. Emerging photoluminescence in monolayer ${\\mathsf{M o S}}_{2}$ . Nano Lett. 10, 1271–1275 (2010). \n20.\t Stryjewski, E. & Giordano, N. Metamagnetism. Adv. Phys. 26, 487–650 (1977). \n21.\t Huang, F., Kief, M. T., Mankey, G. J. & Willis, R. F. Magnetism in the fewmonolayers limit: a surface magneto-optic Kerr-effect study of the magnetic behavior of ultrathin films of Co, Ni, and Co-Ni alloys on Cu(100) and $\\mathsf{C u}(111)$ . Phys. Rev. B 49, 3962–3971 (1994). \n22.\t Back, C. H. et al. Experimental confirmation of universality for a phase transition in two dimensions. Nature 378, 597–600 (1995). \n23.\t Elmers, H.-J., Hauschild, J. & Gradmann, U. Critical behavior of the uniaxial ferromagnetic monolayer Fe(110) on W(110). Phys. Rev. B 54, 15224–15233 (1996). \n24.\t De Jongh, L. J. & Miedema, A. R. Experiments on simple magnetic model systems. Adv. Phys. 50, 947–1170 (1974). \n25.\t Carteaux, V., Moussa, F. & Spiesser, M. 2D Ising-like ferromagnetic behaviour for the lamellar $\\mathsf{C r}_{2}\\mathsf{S i}_{2}\\mathsf{T e}_{6}$ compound: a neutron scattering investigation. Europhys. Lett. 29, 251 (1995). \n26.\t Sachs, B., Wehling, T. O., Novoselov, K. S., Lichtenstein, A. I. & Katsnelson, M. I. Ferromagnetic two-dimensional crystals: single layers of K2CuF4. Phys. Rev. B 88, 201402 (2013). \n27.\t Wang, X. et al. Raman spectroscopy of atomically thin two-dimensional magnetic iron phosphorus trisulfide $(\\mathsf{F e P S}_{3})$ crystals. 2D Mater. 3, 031009 (2016). \n28.\t Tian, Y., Gray, M. J., Ji, H., Cava, R. J. & Burch, K. S. Magneto-elastic coupling in a potential ferromagnetic 2D atomic crystal. 2D Mater. 3, 025035 (2016). \n29.\t Dillon, J. F. Jr & Olson, C. E. Magnetization, resonance, and optical properties of the ferromagnet CrI3. J. Appl. Phys. 36, 1259 (1965). \n30.\t Sander, D. The magnetic anisotropy and spin reorientation of nanostructures and nanoscale films. J. Phys. Condens. Matter 16, R603 (2004). \n\nAcknowledgements Work at the University of Washington was mainly supported by the Department of Energy, Basic Energy Sciences, Materials Sciences and Engineering Division (DE-SC0008145 and SC0012509), and a University of Washington Innovation Award. Work at the Massachusetts Institute of Technology was supported by the Center for Integrated Quantum Materials under NSF grant DMR-1231319 as well as the Gordon and Betty Moore Foundation’s EPiQS Initiative (grant GBMF4541 to P.J.-H.). Device fabrication was supported in part by the Center for Excitonics, an Energy Frontier Research Center funded by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences under Award Number DESC0001088. D.H.C.’s contribution is supported by DE-SC0002197. Work at Carnegie Mellon University is supported by DOE BES DE-SC0012509. W.Y. is supported by the Croucher Foundation (Croucher Innovation Award), the RGC of Hong Kong (HKU17305914P), and the HKU ORA. Work at Oak Ridge National Laboratory (M.A.M.) was supported by the US Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. X.X. and D.X. acknowledge the support of a Cottrell Scholar Award. X.X. acknowledges the support from the Clean Energy Institute (funded by the State of Washington) and from a Boeing Distinguished Professorship in Physics. \n\nAuthor Contributions X.X. and P.J.-H. supervised the project. E.N.-M. and M.A.M. synthesized and characterized the bulk $\\mathsf{C r l}_{3}$ crystal. E.N.-M. and D.R.K. fabricated the samples and analysed the layer thickness, assisted by G.C. and B.H. B.H. built the MOKE setup with help from E.S. and D.Z. G.C. and B.H. performed the MOKE measurements, assisted by K.L.S. and E.N.-M. R.C., D.X. and W.Y. provided theoretical support. B.H., G.C., E.N.-M., X.X., P.J.-H., D.X. and D.H.C. wrote the paper with input from all authors. All authors discussed the results. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Correspondence and requests for materials should be addressed to X.X. (xuxd@uw.edu) and P.J.-H. (pjarillo@mit.edu). \n\n# Methods \n\nGrowth of chromium $\\mathbf{\\Pi}(\\mathbf{III})$ iodide bulk crystals. Chromium powder $(99.5\\%$ , Sigma-Aldrich) and anhydrous iodine beads $(99.999\\%$ , Sigma-Aldrich) were mixed in a 1:3 ratio inside a glove box with an argon atmosphere. $1.5\\mathrm{g}$ of the mixture was then loaded in a silica ampoule ( $16\\mathrm{mm}$ of inner diameter, $19\\mathrm{mm}$ of outer diameter and $550\\mathrm{mm}$ in length). The ampoule was extracted from the glove box and immediately evacuated to a pressure of approximately $10^{-4}$ torr. Once at that pressure, the closed end was dipped in liquid nitrogen to prevent the sublimation of the iodine beads. The ampoule was then flame-sealed under dynamic vacuum and placed inside a three-zone furnace. A three-zone furnace provides the best control over the growth process by reducing nucleation, leading to the growth of large-size single isolated crystals. Following an inverted gradient step of several hours, the crystals were grown over a period of 7 days with source zone at $650^{\\circ}\\mathrm{C}$ (containing the solid mixture), middle growth zone at $550^{\\circ}\\mathrm{C}$ and third zone at $600^{\\circ}\\mathrm{C}$ . Crystals formed both in the source (lustrous hexagonal platelets of several millimetres in size) and the middle (millimetre-long ribbon-like flakes) zones. The crystals were extracted from the ampoule in an argon atmosphere and stored in anhydrous conditions. The I:Cr elemental ratio was verified to be $2.8\\pm0.2$ in several crystals by energy-dispersive X-ray microanalysis performed on individual crystals in a Zeiss Merlin high-resolution scanning electron microscope equipped with an electron dispersive spectroscopy probe. To confirm the crystallographic phase of the material, a few single crystals were ground, loaded into a $0.3\\mathrm{-mm}$ outer-diameter capillary and mounted on a Rigaku Smartlab Multipurpose Diffractometer setup in converging beam configuration with a D/teX detector. The room-temperature X-ray diffraction patterns of both the ribbon-like and hexagonal platelets were identical and consistent with the high-temperature monoclinic $\\mathrm{AlCl}_{3}$ -type structure $(C2/m)$ reported for $\\mathrm{CrI}_{3}$ , with indexed unit cell ­parameters of $a=\\dot{6.87}35(2)\\mathring{\\mathrm{A}},b=11.8859\\mathring{(3)}\\mathring{\\mathrm{A}},c=6.9944(1)\\mathring{\\mathrm{A}}$ and $\\beta=108.535(2)^{\\circ}$ (Le-Bail refinement, $R_{\\mathrm{Bragg}}{=}5.27\\%$ ). SQUID magnetometry performed on the single ­crystals depicts a $T_{\\mathrm{C}}$ of 61 K and a saturation magnetization of $3\\mu_{\\mathrm{{B}}}$ per $\\mathrm{Cr}$ atom, also in agreement with the values reported in the literature10. \n\nEncapsulation of samples for atomic force microscopy. $\\mathrm{CrI}_{3}$ samples exfoliated under an inert atmosphere were encapsulated to preserve the $\\mathrm{CrI}_{3}$ flakes during atomic force microscopy (AFM) studies under ambient conditions. Using an alldry viscoelastic stamping technique inside the glovebox, $\\mathrm{CrI}_{3}$ flakes were sandwiched between two layers of approximately $5\\mathrm{-nm}$ graphite to prevent reaction with oxygen and moisture. Encapsulated $\\mathrm{CrI}_{3}$ flakes could then be safely removed from the glove box for further study. AFM of graphite-encapsulated $\\mathrm{CrI}_{3}$ flakes was measured using a Bruker Dimension Edge atomic force microscope in tapping mode. Extended Data Fig. 5 shows AFM results for bilayer and trilayer $\\mathrm{CrI}_{3}$ flakes encapsulated in approximately 5-nm graphite layers. Their corresponding MOKE data are consistent with bare samples. \n\nMOKE. Power-stabilized light from a $633\\mathrm{-nm}$ HeNe laser source was linearly polarized at $45^{\\circ}$ to the photoelastic modulator (PEM) slow axis (Extended Data Fig. 6)31. Transmitting through the PEM, the light was sinusoidally phasemodulated at $50.1\\mathrm{kHz}$ , with a maximum retardance of $\\lambda/4$ . Upon phase ­modulation, the light was focused down onto the sample at normal incidence using an aspheric lens. At any point in time when the light was not circularly polarized, reflection off a magnetic sample would rotate the polarization axis (the major axis for elliptically polarized light) by what we define as the Kerr rotation, $\\theta_{\\mathrm{K}}$ . This reflection was then separated from the incidence path via a laser line nonpolarizing beamsplitter cube and projected onto the PEM slow axis using a second polarizer. For $\\theta_{\\mathrm{K}}=0$ , the slow-axis component remains constant for all polarizations and hence is not time-dependent. With a non-zero $\\theta_{\\mathrm{K}},$ however, the slow-axis component depends on the polarization and oscillates at twice the ­modulation frequency, $100.2\\mathrm{kHz}$ , with an amplitude that is proportional to the Kerr rotation. Therefore, to obtain $\\theta_{\\mathrm{K}},$ the reflection was detected using an amplified photodiode and two lock-in amplifiers: one tuned at $100.2\\mathrm{kHz}$ to detect the Kerr rotation, and one tuned at the chopper frequency, $800\\mathrm{Hz},$ to normalize the Kerr signal to laser intensity fluctuations and the reflectivity of the sample. \n\nQuantitative optical microscopy in $\\mathbf{CrI}_{3}$ . Optical microscopy images were taken using a Nikon Eclipse LV-CH 150NA optical microscope with a DS-Ri2 full-frame camera. The setup was located inside a glove box (argon atmosphere) to prevent sample degradation. The quantitative optical contrast analysis required that images were captured with a $100\\times$ objective under monochromatic illumination at ­normal incidence. In practice, $10\\mathrm{-nm}$ full-width at half-maximum (FWHM) filters were used (Andover Corp.) to filter the light coming from a halogen lamp. The ­thickness of the flakes was determined by contact-mode AFM under ambient conditions. Given the extreme sensitivity of the samples to atmospheric moisture, the $\\mathrm{CrI}_{3}$ flakes were encapsulated between two pieces of few-layer graphite (typically $5\\mathrm{nm}$ in thickness) before being extracted from the glove box. For each opticalmicroscopy-filtered image, individual RGB values were extracted and averaged over each flake and substrate region to give the reflected intensities of the flake and substrate. The intensity was chosen to be exclusively the value of the channel with the highest number of counts. The experimental optical contrast value was then calculated according to the following expression (1). \n\n$$\nC(d,\\lambda)={\\frac{I_{\\mathrm{flake}}-I_{\\mathrm{substrate}}}{I_{\\mathrm{flake}}+I_{\\mathrm{substrate}}}}\n$$ \n\nEquation (1) expresses the relationship between the optical contrast $C$ between each flake and the substrate using the reflected intensities from the flake $\\left(I_{\\mathrm{flake}}\\right)$ and the substrate $(I_{\\mathrm{substrate}})$ . Extended Data Fig. 1 shows an example of a contrast map of a multi-step $\\mathrm{CrI}_{3}$ flake extracted from its optical micrograph. \n\nFor flakes that have been exfoliated on a $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate, $C$ depends on the thickness of the flake and on the illumination wavelength32,33. Following the quantitative microscopy analysis proposed for graphene on $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrates34, $C$ can be computed for any kind of flake by using a model based on Fresnel’s equations shown in equations (2a) and (2b): \n\n$$\nI_{\\mathrm{substrate}}(\\lambda)=\\left|\\frac{r_{02}+r_{23}{\\mathrm e}^{-2i\\phi_{2}}}{1+r_{02}r_{23}{\\mathrm e}^{-2i\\phi_{2}}}\\right|^{2}\n$$ \n\n$$\n\\begin{array}{r l}&{I_{\\mathrm{flake}}(\\lambda)}\\\\ &{\\qquad=\\left|\\frac{r_{02}\\mathrm{e}^{i(\\phi_{1}+\\phi_{2})}+r_{12}\\mathrm{e}^{-i(\\phi_{1}-\\phi_{2})}+r_{23}\\mathrm{e}^{-i(\\phi_{1}+\\phi_{2})}+r_{01}r_{12}r_{23}\\mathrm{e}^{i(\\phi_{1}-\\phi_{2})}}{\\mathrm{e}^{i(\\phi_{1}+\\phi_{2})}+r_{01}r_{12}\\mathrm{e}^{-i(\\phi_{1}-\\phi_{2})}+r_{01}r_{23}\\mathrm{e}^{-i(\\phi_{1}+\\phi_{2})}+r_{12}r_{23}\\mathrm{e}^{i(\\phi_{1}-\\phi_{2})}}\\right|^{2}}\\end{array}\n$$ \n\nIn this calculation, the subscripts 0, 1, 2 and 3 refer to air (treated as vacuum), $\\mathrm{CrI}_{3}$ , $\\mathrm{SiO}_{2}$ and Si, respectively. The amplitude of the reflected path at the interface between media $j$ and $k$ is given by $r_{j k}$ in equation (3b) and is calculated from the complex refractive indices defined in equation (3a). $\\varPhi_{j}$ is the phase shift introduced by the interaction between light of wavelength $\\lambda$ and medium $j$ with thickness $d_{j}$ shown in equation (3c). \n\n$$\n\\tilde{n}_{j}(\\lambda)=n_{j}-i\\kappa_{j}\n$$ \n\n$$\nr_{j k}=\\frac{\\tilde{n}_{j}-\\tilde{n}_{k}}{\\tilde{n}_{j}+\\tilde{n}_{k}}\n$$ \n\n$$\n\\varPhi_{j}=\\frac{2\\pi\\tilde{n}_{j}d_{j}}{\\lambda}\n$$ \n\nAs can be noted from the previous expressions, if one wants to model $C$ using the Fresnel equations, the complex index of refraction of the material under study must be known. The reflectivity of $\\mathrm{CrI}_{3}$ measured in vacuum at $300\\mathrm{K}$ at normal ­incidence of a single-crystal platelet of $\\mathrm{CrI}_{3}$ has been previously reported35. This data was used to calculate the phase of the amplitude reflection coefficient $\\theta$ at energies in the visible range by numerical integration, according to the Kramers– Kronig relation (4a). The refractive index $n$ and extinction coefficient $\\kappa$ of $\\mathrm{CrI}_{3}$ were then obtained throughout the visible range by combining equations (4b) and (4c) at each energy value. The results are plotted in Extended Data Fig. 3. \n\n$$\n\\theta(E)=-\\frac{E}{\\pi}\\int_{0}^{\\infty}\\frac{\\ln[R(E^{\\prime})]}{(E^{\\prime})^{2}-E^{2}}\\mathrm{d}E^{\\prime}\n$$ \n\n$$\nr(E)=\\sqrt{R(E)}{\\mathrm e}^{i\\theta(E)}\n$$ \n\n$$\nr(E)=\\frac{n(E)-1+i\\kappa(E)}{n(E)+1+i\\kappa(E)}\n$$ \n\nSubstituting for the complex indices of refraction36 of $\\mathrm{CrI}_{3}$ , Si and $\\mathrm{SiO}_{2}$ in equations (2a) and (2b), we can calculate the expected value of $C$ for flakes of different thicknesses as a function of the illumination wavelength. Extended Data Fig. 4a shows the contrast map for $\\mathrm{CrI}_{3}$ considering a fixed thickness of $285\\mathrm{nm}$ of the $\\mathrm{SiO}_{2}$ layer in the $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate. We also present a line cut of that plot at an illumination wavelength of $635\\mathrm{nm}$ in Extended Data Fig. 4b. It can be seen that the experimental data points closely follow the trend predicted by the model. Given that the method is non-destructive and can be performed inside a glove box for many different illumination wavelengths, the error in the determination of the number of layers can be reduced. This provides a fast and reliable method for the characterization of few-layer $\\mathrm{CrI}_{3}$ flakes. \n\nThin-film interferometry and the MOKE signal in $\\mathbf{CrI}_{3}$ . Linearly polarized light is an equal superposition of right-circularly and left-circularly polarized light (RCP, \n\nLCP respectively). When a phase difference accrues between the RCP and LCP components, the polarization axis of the linearly polarized light rotates. This ­rotation can be observed in any material that exhibits circular birefringence. In magnetic samples, such as $\\mathrm{CrI}_{3}$ , this birefringence arises from a non-zero ­magnetization, $M_{;}$ , and is known as the magneto-optical Kerr effect (MOKE) when detected in reflection geometry. A MOKE measurement then detects changes in $M$ by exploiting the functional dependence of the Kerr rotation on the magnetization, $\\theta_{\\mathrm{K}}(M)$ . Additional interference terms must be accounted for, however, when we discuss the Kerr rotation of a thin-film material, because reflections from the material–substrate $\\mathrm{(CrI_{3}-S i O_{2})}$ interface will superimpose with the reflection off the magnetic sample (Extended Data Fig. 7). As such, this motivates a model that uses the Fresnel equations (the same formalism as in Methods subsection ‘Quantitative microscopy on $\\mathrm{Crl}_{3}^{\\prime}$ ) to calculate the reflection coefficients for RCP $(\\widetilde{r}_{+})$ and for LCP $(\\widetilde{r}_{-})$ light. The phase difference between $\\widetilde{r}_{+}$ and $\\widetilde{r}_{-}$ then, is the Kerr rotation: \n\n$$\n\\theta_{\\mathrm{K}}=\\arg(\\widetilde{r}_{+})-\\arg(\\widetilde{r}_{-})\n$$ \n\nTo obtain the index of refraction for $\\mathrm{CrI}_{3}$ when fully spin polarized, we work in Cartesian coordinates and use a dielectric tensor of the form37: \n\n$$\n\\varepsilon=\\left[-i Q M\\begin{array}{c c c}{{\\widetilde{\\varepsilon}_{x x}}}&{{i Q M}}&{{0}}\\\\ {{-i Q M}}&{{\\widetilde{\\varepsilon}_{x x}}}&{{0}}\\\\ {{0}}&{{0}}&{{\\widetilde{\\varepsilon}_{z z}}}\\end{array}\\right]\n$$ \n\nwhere $Q$ is the complex Voigt constant and $M$ is the out-of-plane (parallel to the $z$ -axis) component of the magnetization, which we assume is constant for all $\\mathrm{CrI}_{3}$ thicknesses when fully spin-polarized. This form of the dielectric tensor for a magnetic sample is valid assuming (1) that the crystal exhibits at least threefold symmetry; (2) that $M$ is parallel to the axis of rotation that gives rise to the threefold symmetry; and (3) that the axis of rotation is chosen to be the $z$ axis. Solving for the normal modes, we obtain the eigenvalues: \n\n$$\n\\tilde{n}_{\\pm}=\\sqrt{\\tilde{\\varepsilon}_{x x}\\pm Q M}\n$$ \n\nand the eigenvectors: \n\n$$\n\\pmb{{\\cal D}}_{\\pm}=(E_{x}\\pm i E_{y})\\hat{z}\n$$ \n\nwhere $\\tilde{n}_{+}$ and $D_{+}$ denote the eigenvalue and eigenvector respectively of RCP light and $\\tilde{n}_{-}$ and ${\\cal D}_{-}$ denote the eigenvalue and eigenvector respectively of LCP light in $\\mathrm{CrI}_{3}$ . The complex dielectric component $\\tilde{\\varepsilon}_{x x}$ , when related to the $\\tilde{n}$ defined in ­equation (3a), is: \n\n$$\n\\tilde{\\varepsilon}_{x x}=n^{2}-\\kappa^{2}-2i n\\kappa\n$$ \n\nwhere the value of $\\tilde{\\varepsilon}_{x x}$ was derived from the $n$ and $\\kappa$ values at about $1.96\\mathrm{eV}$ (modelled in Extended Data Fig. 3). It is apparent from equation (7) that we should not expect $\\theta_{\\mathrm{K}}$ to depend linearly on $M$ and layer number. In addition, interference from reflections off the ${\\mathrm{CrI}}_{3}{\\mathrm{-SiO}}_{2}$ interface will give rise to a non-trivial functional form of $\\theta_{\\mathrm{K}}$ with respect to layer thickness. There is no determination of $Q$ in the literature for $\\mathrm{CrI}_{3}$ , so we varied $Q$ as a complex parameter and constrained it to a small range that fitted experimental $\\theta_{\\mathrm{K}}$ values from our MOKE measurements on trilayer and bulk $\\mathrm{CrI}_{3}$ . These calculations qualitatively describe the large increase in $\\theta_{\\mathrm{K}}$ moving from monolayer to trilayer, as well as the negative $\\theta_{\\mathrm{K}}$ seen at positive $\\mu_{0}H$ for bulk flakes. However, this simple model does not incorporate layerdependent electronic structure changes, seen in other atomically thin van der Waals materials such $\\mathsf{a s}^{18}\\mathrm{MoS}_{2}$ , and evident in this system as a change in magnetic ground states from monolayer to bilayer. \n\nData availability. The data sets generated during and analysed during this study are available from the corresponding author upon reasonable request. \n\n![](images/2f1c4da1b542e21731a68df7068c6f0b28c173e75f1e35d969ade05e81f3b297.jpg) \nExtended Data Figure 1 | SQUID magnetometry in bulk $\\mathbf{CrI}_{3}$ . a, Zerofield-cooled/field-cooled temperature dependence of the magnetization of a $\\mathrm{CrI}_{3}$ bulk crystal with an applied magnetic field of $10\\mathrm{G}$ perpendicular to the basal plane of the sample. The black line is a criticality fit \n\n![](images/17277eca20924369578caead5f60987d4e7e106843318da7c8ca7207eb5b5011.jpg) \n$(M=\\alpha(1-T_{\\mathrm{{C}}}/T)^{\\beta})$ of the data with $T_{\\mathrm{C}}{=}61\\mathrm{K}$ and $\\beta=0.125$ (Ising universality class). b, Hysteresis loops of the same sample with the external magnetic field in perpendicular and parallel orientations with respect to the $\\mathrm{CrI}_{3}$ layers. (emu, electromagnetic units.) \n\n![](images/024ab0bdd4df460f9a19fb9591b31267d94ffcce7f9aa24bedbafc4479091379.jpg) \nExtended Data Figure 2 | Thickness dependence of the optical contrast of the $\\mathbf{CrI}_{3}$ flakes. Optical micrographs of a $\\mathrm{CrI}_{3}$ flake illuminated with white light (a) and with $631\\mathrm{-nm}$ -( $\\mathrm{10-nm}$ FWHM bandpass)-filtered light (b). \nc, AFM topography image of the same sample. d, Optical contrast map extracted from the $631\\mathrm{-nm}$ micrograph in b. Scale bars are $5\\upmu\\mathrm{m}$ . \n\n![](images/e87b469ecde36cd3743fbb29a3e9e87c98d924ee39845f5e296ed7a6f3b973a6.jpg) \nExtended Data Figure 3 | Computed index of refraction of bulk $\\mathbf{CrI}_{3}$ . Real $(n)$ and imaginary $(\\kappa)$ components are plotted as a function of photon energy in the visible range. \n\n![](images/875de929022b539b208f84c570e037ba5802cee9f21391c4175d61a8bc57ce77.jpg) \nExtended Data Figure 4 | Fresnel model for the optical contrast $c$ of $\\mathbf{CrI}_{3}$ flakes on $\\mathbf{Si}/285\\mathbf{nm}\\mathbf{SiO}_{2}$ substrates. a, Dependence of $C$ with the number of layers for a $\\mathrm{CrI}_{3}$ flake as a function of the illumination wavelength. b, Comparison of the experimental data with the computed \nthickness dependence of $C$ for a red-light-illuminated sample (line cut at $631\\mathrm{nm}$ as shown by the dashed line in a). The different shape markers indicate data coming from different exfoliated samples. \n\n![](images/defa0cbe79c7e5f43a9697ec7e791df26bed7161a7fe0f4a917700a98eb287d0.jpg) \nExtended Data Figure 5 | AFM and MOKE measurements of graphiteencapsulated few-layer $\\mathbf{CrI}_{3}$ . a, Optical microscope image of a bilayer $\\mathrm{CrI}_{3}$ flake on $285\\mathrm{-nm}$ -thick $\\mathrm{SiO}_{2}$ . b, AFM data for the $\\mathrm{CrI}_{3}$ flake in a encapsulated in graphite, showing a line cut across the flake with a step height of $1.5\\mathrm{nm}$ . c, Optical microscope image of a trilayer $\\mathrm{CrI}_{3}$ \nflake on $285\\mathrm{-nm}$ -thick $\\mathrm{SiO}_{2}$ . d, AFM data for the $\\mathrm{CrI}_{3}$ flake shown in c encapsulated in graphite. A line cut taken across the flake shows a step height of $2.2\\mathrm{nm}$ . Both scale bars are $2\\upmu\\mathrm{m}$ . e and f show the MOKE signal as a function of applied magnetic field for the encapsulated bilayer in b and the encapsulated trilayer in $\\mathbf{d}$ respectively. \n\n![](images/3a9f0bdbc5cdb3888c067d4aac8260b5bcd992d366cea3d266ecfc8936c8b698.jpg) \nExtended Data Figure 6 | Magneto-optical Kerr effect experimental setup. Schematic of the optical setup used to measure the MOKE effect in $\\mathrm{CrI}_{3}$ samples. $633\\mathrm{nm}$ optical excitation is provided by a power-stabilized HeNe laser. A mechanical chopper and photoelastic modulator provide intensity and polarization modulation, respectively. The modulated beam is directed through a polarizing beam splitter to the sample, housed in \n\na closed-cycle cryostat at $15\\mathrm{K}$ . A magnetic field is applied at the sample using a 7-T solenoidal superconducting magnet in Faraday geometry. The reflected beam passes through an analyser onto a photodiode, where lock-in detection measures the reflected intensity $(\\mathrm{at}f_{\\mathrm{C}})$ as well as the Kerr rotation (at fPEM). \n\n![](images/1c5d36d5d24811d6f8646058e64aa974e5c42370c013aebd1720b63123315d35.jpg) \nExtended Data Figure 7 | Thin-film interference ray diagram of $\\mathbf{CrI}_{3}$ on a silicon oxide/silicon substrate. Light incident on $\\mathrm{CrI}_{3}$ undergoes reflections at the ${\\mathrm{CrI}}_{3}{\\mathrm{-SiO}}_{2}$ interface (green–blue boundary) as well as the $\\mathrm{SiO}_{2}–\\mathrm{Si}$ interface (blue–grey boundary). These reflections interfere with the initial reflection off the $\\mathrm{CrI}_{3}$ flake to produce thin-film interference that depends on the $\\mathrm{CrI}_{3}$ layer thickness, $d_{1}$ , as well as the $\\mathrm{SiO}_{2}$ thickness, $d_{2}$ . The underlying silicon wafer is assumed to be semiinfinite. The indices of refraction for $\\mathrm{CrI}_{3}$ , $\\mathrm{SiO}_{2}$ , and Si are $n_{1},n_{2}$ and $n_{3}$ respectively. \n\n![](images/122e8d79dad55ee85fe85c84cec0f16656595a5734654402123ab40cb9c31b53.jpg) \nExtended Data Figure 8 | Additional data for 1–3-layer samples showing Kerr rotation as a function of the applied magnetic field. The insets show optical microscope images of the $\\mathrm{CrI}_{3}$ flakes at $100\\times$ ​magnification. a, Additional monolayer data showing ferromagnetic hysteresis and remanent Kerr signal as a function of applied magnetic field. b, Additional bilayer data showing field-dependent behaviour consistent with an antiferromagnetic ground state. c, Additional trilayer data showing field-dependent behaviour consistent with a ferromagnetic ground state, as well as a larger remanent Kerr signal than the monolayer in a. All scale bars are ${5\\upmu\\mathrm{m}}$ . \n\n![](images/2aaeedf3fe0a379a121ff58602fc1e892a56fcd3f88b7cf40f3494b471144255.jpg) \nExtended Data Figure 9 | Additional data for monolayer and bilayer samples under ${780-}\\mathbf{n}\\mathbf{m}$ excitation and ${\\bf633-n m}$ excitation. Insets show optical microscope images of the $\\mathrm{CrI}_{3}$ flakes at $100\\times$ ​magnification. \na, Kerr rotation as a function of applied magnetic field for a monolayer a (or $\\mathbf{c}_{\\mathcal{\\kappa}}^{\\dagger}$ , and a bilayer b (or $\\mathbf{d}$ ) under $780\\mathrm{-nm}$ (or $633\\mathrm{-nm}$ ) excitation. All scale bars are $4\\upmu\\mathrm{m}$ . " + }, + { + "id": "10.1038_nenergy.2017.105", + "DOI": "10.1038/nenergy.2017.105", + "DOI Link": "http://dx.doi.org/10.1038/nenergy.2017.105", + "Relative Dir Path": "mds/10.1038_nenergy.2017.105", + "Article Title": "Ultra-high-rate pseudocapacitive energy storage in two-dimensional transition metal carbides", + "Authors": "Lukatskaya, MR; Kota, S; Lin, ZF; Zhao, MQ; Shpigel, N; Levi, MD; Halim, J; Taberna, PL; Barsoum, M; Simon, P; Gogotsi, Y", + "Source Title": "NATURE ENERGY", + "Abstract": "The use of fast surface redox storage (pseudocapacitive) mechanisms can enable devices that store much more energy than electrical double-layer capacitors (EDLCs) and, unlike batteries, can do so quite rapidly. Yet, few pseudocapacitive transition metal oxides can provide a high power capability due to their low intrinsic electronic and ionic conductivity. Here we demonstrate that two-dimensional transition metal carbides (MXenes) can operate at rates exceeding those of conventional EDLCs, but still provide higher volumetric and areal capacitance than carbon, electrically conducting polymers or transition metal oxides. We applied two distinct designs for MXene electrode architectures with improved ion accessibility to redox-active sites. A macroporous Ti(3)C(2)Tx MXene film delivered up to 210 F g(-1) at scan rates of 10Vs(-1), surpassing the best carbon supercapacitors known. In contrast, we show that MXene hydrogels are able to deliver volumetric capacitance of similar to 1,500 F cm(-3) reaching the previously unmatched volumetric performance of RuO2.", + "Times Cited, WoS Core": 1847, + "Times Cited, All Databases": 1936, + "Publication Year": 2017, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000411264300015", + "Markdown": "# Ultra-high-rate pseudocapacitive energy storage in two-dimensional transition metal carbides \n\nMaria R. Lukatskaya1,2†‡, Sankalp Kota2‡, Zifeng $\\mathsf{L i n}^{3,4\\ddagger}$ , Meng-Qiang Zhao1,2, Netanel Shpigel5, Mikhael D. Levi5, Joseph Halim1,2, Pierre-Louis Taberna3,4, Michel W. Barsoum2, Patrice Simon3,4\\* and Yury Gogotsi1,2\\* \n\nThe use of fast surface redox storage (pseudocapacitive) mechanisms can enable devices that store much more energy than electrical double-layer capacitors (EDLCs) and, unlike batteries, can do so quite rapidly. Yet, few pseudocapacitive transition metal oxides can provide a high power capability due to their low intrinsic electronic and ionic conductivity. Here we demonstrate that two-dimensional transition metal carbides (MXenes) can operate at rates exceeding those of conventional EDLCs, but still provide higher volumetric and areal capacitance than carbon, electrically conducting polymers or transition metal oxides. We applied two distinct designs for MXene electrode architectures with improved ion accessibility to redox-active sites. A macroporous $\\begin{array}{r}{\\pmb{\\Tilde{\\Pi}_{3}\\pmb{C}_{2}\\pmb{\\Tilde{\\Pi}_{x}}}}\\end{array}$ MXene film delivered up to $210\\mathsf{F g}^{-1}$ at scan rates of $\\mathbf{\\bar{10}}\\mathbf{\\boldsymbol{v}}\\mathbf{5}^{-1}$ , surpassing the best carbon supercapacitors known. In contrast, we show that MXene hydrogels are able to deliver volumetric capacitance of $\\sim1.500\\mathrm{F}\\mathrm{cm}^{-3}$ reaching the previously unmatched volumetric performance of $\\pmb{\\mathrm{RuO}_{2}}$ . \n\nypical commercial batteries require prolonged charging and therefore are limiting mobility of users. Systems that are capable of delivering high energy densities at relatively high charge/discharge rates are classified as pseudocapacitors and characterized by absence of phase transformations during operation1–3. Pseudocapacitors are a sub-class of supercapacitors that are differentiated from electrical double-layer capacitors (EDLCs) on the basis of charge storage mechanism. EDLCs store charge via formation of the electrical double layer at the electrode/electrolyte interface and, naturally, their capacitance is proportional to the electrode’s specific surface area available for electrosorption of ions. Pseudocapacitors, on the other hand, utilize fast redox reactions and therefore can potentially provide higher energy densities due to charge transfer. \n\nSince the discovery of high specific capacitances in $\\mathrm{RuO}_{2}$ (refs 4–7), research on other pseudocapacitive materials (for example, $\\mathrm{{MnO}}_{2}$ (ref. 8), $\\mathrm{MoO}_{3}$ (ref. 9), $\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ (refs 10,11), VN (ref. 12)) has attracted much attention, but the limited electronic conductivity of most pseudocapacitive oxides leads to high electrode resistance and, consequently, lower power densities compared with EDLCs and electrolytic capacitors. Conductive coatings on electrochemically active materials10 and hybrids of active materials and conductive phases6,11 enhance charge transfer, but rapid transport of ions and electrons to all active sites remains a challenge, especially when the electrode thickness exceeds a few micrometres. Synthesis of materials with large, open channels (for example, $\\mathrm{T}{\\cdot}\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ (ref. 12)) allowed rapid ion access and significantly improved rate capability over existing high-rate redox materials, such as $\\mathrm{Li_{4}T i_{5}O_{12}}$ , but the issue of low electronic conductivity remained. Therefore, pseudocapacitors usually operate at rates that are between those of batteries and double-layer capacitors3. \n\nMXenes are a class of two-dimensional materials13, usually produced by selective etching of layered ternary transition metal carbides called MAX phases in acidic fluoride containing solutions, such as lithium fluoride (LiF) solution in hydrochloric acid $\\mathrm{(HCl)^{14}}$ . MXenes have a general formula $\\textstyle\\mathrm{{M}}_{n+1}\\mathrm{{X}}_{n}\\mathrm{{T}}_{x},$ , where $\\mathbf{\\dot{M}}^{\\mathbf{\\alpha}}$ is a transition metal, X is C and/or N, $n$ is an integer between 1 and 3, and $\\mathrm{T}_{x}$ represent surface functional groups13. As depicted in Fig. 1a, MXenes’ unique structure renders them particularly attractive for energy storage applications because: a conductive inner transition metal carbide layer enables fast electron supply to electrochemically active sites; a transition metal oxide-like surface generated during the synthesis15 is redox active; a two-dimensional morphology and pre-intercalated water14 enable fast ion transport. Previously, high volumetric capacitances of freestanding MXene electrodes of ${\\sim}900$ and $700\\mathrm{Fcm}^{-3}$ were demonstrated for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (ref. 14) and $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ (ref. 16), respectively, yet their charging at rates above $100\\mathrm{mVs}^{-1}$ remained largely unexplored. Herein, we probe the limits of pseudocapacitive charge storage in terms of rate, capacitance and voltage window using $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ and demonstrate how effective electrode design strategies allow energy storage and delivery at ultrahigh rates. We demonstrate how highly accessible macroporous electrode architectures enable exceptional high-rate performance with capacitance over $200\\mathrm{Fg}^{-1}$ at $10\\mathrm{{V}}\\thinspace s^{-1}$ rate. We also show using MXene hydrogel that in situ incorporation of the $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte in between MXene layers enables volumetric capacitance of $\\sim\\mathrm{i},500\\mathrm{Fcm}^{-3}$ . \n\n# Theoretical capacitance and voltage window \n\nPreviously, we demonstrated that the mechanism of charge storage in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ in one molar sulfuric acid, 1 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ , is pseudocapacitive; that is, changes in electrode potential correlate almost linearly to changes in the titanium oxidation state17. It was also demonstrated that change in titanium oxidation state is accompanied by protonation of oxygen functional groups18. In a simplified view, the electrochemical reaction can be presented as: \n\n![](images/c096a1362dc0740c1c285bc5e9ed7c636fe076b7c07f77a64f4210e5a0bc69be.jpg) \nFigure 1 | MXene electrodes. a, Schematic illustration of MXene structure. MXenes possess excellent conductivity owing to a conductive carbide core along with transition metal oxide-like surfaces. Intercalated water molecules enable high accessibility of protons to the redox-active sites. b, SEM image of ${\\mathsf{T i}}_{3}{\\mathsf{C}}_{2}{\\mathsf{T}}_{x}$ MXene hydrogel cross-section. c, SEM image of macroporous templated $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ electrode cross-section. Scale bars, $5\\upmu\\mathrm{m}$ . Insets in b and c show schematically the ionic current pathway in electrodes of diferent architectures. \n\n$$\n\\mathrm{Ti_{3}C_{2}O_{\\boldsymbol{x}}(O H)_{\\boldsymbol{y}}F_{\\boldsymbol{z}}}+\\delta\\boldsymbol{\\bar{e}}+\\delta\\mathrm{H}^{+}\\to\\mathrm{Ti_{3}C_{2}O_{\\boldsymbol{x}-\\delta}(O H)_{\\boldsymbol{y}+\\delta}F_{\\boldsymbol{z}}}\n$$ \n\nSo far, the most promising electrochemical performance was demonstrated by MXenes produced via etching the MAX phase in LiF–HCl (ref. 14). According to NMR analysis, these synthetic conditions result in the following chemistry: $\\mathrm{Ti_{3}C_{2}O_{0.84(6)}(O H)_{0.06(2)}F_{0.25(8)}}$ (ref. 15). Assuming this chemical formula and $0.85\\ \\bar{\\mathrm{e}}$ redox reaction as per equation (1), the maximum theoretical capacity for the noted surface chemistry can be estimated using Faraday’s law to be ${\\sim}615\\mathrm{Cg}^{-1}$ . Yet the maximum experimental values reported to date are $245\\mathrm{Fg}^{-1}$ or ${\\sim}135\\mathrm{Cg}^{-\\bar{1}}$ for a voltage window of $0.55\\mathrm{V}$ (refs 14,17). \n\nTo analyse this discrepancy between theory and experiment, we performed electrochemical testing of a $90\\mathrm{-nm}$ -thick MXene film coating to minimize ion transport limitations stemming from the electrode architecture. In previous reports, testing of the capacitive performance was performed using platinum or gold current collectors14,19, which can introduce limitations by catalysing water splitting within the potential range of interest. In the current work, glassy carbon electrodes were used as current collectors, instead. The advantage of the latter is their exceptional overpotential for hydrogen evolution reaction, which allows probing the intrinsic ability of different materials towards hydrogen evolution, making glassy carbon electrodes a primary current collector in the catalysis field20. When the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene electrodes were tested in this configuration, the operation potential window was extended to $1\\mathrm{V}$ $\\cdot-1.1$ to $-0.1\\mathrm{V}$ versus ${\\mathrm{Hg/Hg_{2}S O_{4}}},$ ) (Fig. 2a). Study of a $90\\mathrm{-nm}$ - thick electrodes revealed capacitance up to $450\\mathrm{Fg}^{-1}$ along with exceptional rate performance (Fig. $^{2\\mathrm{b},\\mathrm{d})}$ : capacitance decays only $27\\%$ following a $10^{4}$ -fold scan rate increase from 10 to $100,\\dot{0}00\\dot{\\mathrm{mV}}s^{-1}$ (Fig. 2c). Another characteristic feature of the charge storage process in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ is a small cathodic and anodic peak potential separation, $\\Delta E_{\\mathrm{{p}}}$ (less than $50\\mathrm{mV}$ for the scan rates up to $1,000\\mathrm{\\bar{m}V s^{-1}}.$ ), indicating a highly reversible redox process at peak potential with a clear domain of quasi-equilibrium2 (Fig. 2c); this is also confirmed by matching the capacitance extracted from voltammetry (CV) and electrochemical impedance spectroscopy (EIS) data for intercalation and deintercalation at the same potentials indicating the equilibrium nature of the process (Supplementary Fig. 1a,b). \n\nIt is important to note that, when $3\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ was used as electrolyte in the current study, the higher concentration of protons resulted in slightly larger capacitance values and superior rate performance (Supplementary Fig. 1c–e), probably because conductivity of 3 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ exceeds that of $1\\mathrm{M}$ solution used in previous studies by almost an order of magnitude21. \n\nIt is worth noting that although capacitive performance of $90\\mathrm{-nm}$ -thick film demonstrates an extent to which performance of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ can be improved, it has limited practical importance unless the noted above electrochemical response translates well for thicker practical electrodes22. We address realization of the enhanced electrochemical performance for the thick electrodes in the sections below. \n\n# Electrode design for high volumetric performance \n\nA comparison of the performance of the $90\\mathrm{nm}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film with thicker $(5\\upmu\\mathrm{m})$ electrodes14 (Fig. 2d) shows a factor of two difference and suggests a decreasing accessibility of electrochemically active sites to ions with increasing thickness of planar electrodes. To test this conjecture, we prepared hydrogel electrodes23 that provide delivery of electrolyte species in between MXene sheets (Supplementary Fig. 2). This approach was previously used to enhance performance of graphene in aqueous electrolytes24 and also to enable access of bulky ionic liquid ions to electrochemically active sites of MXene23. As a result, a dramatic increase in gravimetric and volumetric performance over previous reports14 was observed: capacitance of $380\\mathrm{Fg}^{-1}$ or $1{,}500\\mathrm{\\bar{F}}\\mathrm{cm}^{-3}$ was measured at $2\\mathrm{mVs}^{-1}$ for 1 ${\\mathfrak{a}}3\\upmu\\mathrm{m}\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ hydrogel electrode $(1.2\\mathrm{mg}\\mathrm{cm}^{-2}$ loading) over a potential window of 1 V. This translates to specific charge of $380\\mathrm{Cg}^{-1}$ , which is more than 3 times higher than our previous results14 and corresponds to ${\\sim}65\\%$ from theoretical capacity. More importantly, these outstanding values translated well (for scan rates ranging from 2 to $20\\mathrm{mVs}^{-1}$ ) following increasing electrodes’ mass loadings to practical ones of 5.3 and even $11.{\\overset{-}{3}}\\operatorname*{mgcm}^{-2}$ . For instance, capacitance of $370\\mathrm{Fg}^{-1}$ or $1,500\\mathrm{Fcm}^{-3}$ was measured for a $13\\upmu\\mathrm{m}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ hydrogel film electrode $(5.3\\mathrm{mg}\\mathrm{cm}^{-2},$ at $2\\mathrm{mVs}^{-1}$ (Fig. 2e and Fig. 3e and Supplementary Fig. 3b). These electrodes retained more than $90\\%$ of their capacitance after 10,000 cycles (Fig. 2f). \n\nTypical EIS results are shown in Fig. 2g. The Nyquist plots collected at different applied reducing potentials are in a good agreement with the CV data (Fig. 2b and Supplementary Fig. 3). The Nyquist plots at potentials of $-0.3\\mathrm{V}$ and $-0.5\\mathrm{V}$ tend to overlap and are characterized by a low ion transport resistance and a sharp (almost vertical) rise of the imaginary component of impedance at low frequencies, demonstrating the capacitive behaviour of the electrode. As can be seen from both EIS (Fig. 2g) and CV profiles collected at different scan rates (Fig. 2b and Supplementary Fig. 3), this potential region corresponds to a relatively low capacitance originating from non-diffusion-limited processes. A slight increase of the 45-degree linear part (related to ion transport resistance) and a less steep slope of the Nyquist plot in the low-frequency range at $-0.7\\mathrm{V}$ were followed by a large increase of the 45-degree linear part at $-0.9\\mathrm{V}$ and $-1.1\\mathrm{V}.$ This correlates with the appearance of redox peaks in the CVs (Fig. 2b and Supplementary Fig. 3b) associated with a pseudocapacitive mechanism. There are clear diffusion limitations that translate into substantial capacitance decrease at potentials below $-0.4\\mathrm{V}$ with increasing scan rate (Supplementary Fig. 3). Further increase in ion transport resistance for EIS collected at $-1.1\\mathrm{V}$ may originate from the onset of hydrogen evolution during exposure for $30\\mathrm{min}$ (see the $\\mathrm{H}_{2}$ evolution ‘tail’ features in the CVs in Fig. 2a and Supplementary Fig. 3a). \n\n![](images/322a3d1762c8190ec7a8fe3c0e8f64ab764e26596b5f6816052109a22cf83d1b.jpg) \nFigure 2 | Electrochemical performance of planar MXene electrodes. a, Cyclic voltammetry profiles for $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ electrode collected at $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in $3M$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at diferent potential windows on a glassy carbon current collector. b, Cyclic voltammetry data collected at scan rates from 10 to $100,000\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ for a 90-nm-thick $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ MXene. c, Peak separation, $\\Delta E_{\\mathsf{p}}$ , for diferent scan rates extracted from CV analysis of $90\\mathsf{n m}$ MXene film. The blue dashed line indicates the domain of the quasi-equilibrium. d, Gravimetric rate performance of a $90\\mathsf{n m}$ $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ film on glassy carbon current collector (black circles), and a 3- $\\cdot\\upmu\\mathrm{m}$ -thick hydrogel film electrode (blue stars), compared with the performance from ref. 14 of 5- $\\upmu\\mathrm{m}$ -thick ‘clay’ electrode (grey spheres). e, Volumetric capacitance of 3-µm-thick (blue stars), 13- $\\cdot\\upmu\\mathsf{m}$ -thick (dark blue squares) and 40-µm-thick (gold triangles) hydrogel film electrode (mass loadings of $1.2\\mathsf{m g c m}^{-2}$ , $5.3\\mathsf{m g c m}^{-2}$ and 1 $1.3\\mathsf{m g c m}^{-2}$ accordingly) in 3 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ compared with the performance from ref. 14 of 5- $\\upmu\\mathrm{m}$ -thick ‘clay’ electrode (grey spheres) in 1 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ . The inset shows the ionic current pathway in a planar MXene electrode. f, Capacitance retention test of a $13\\upmu\\mathrm{m}$ hydrogel film performed by galvanostatic cycling at ${10\\mathsf{A}\\mathsf{g}^{-1}}$ . The inset depicts galvanostatic cycling profiles collected at 1, 2, 5 and $\\mathsf{10A g^{-1}}$ . $\\scriptstyle\\mathbf{g},$ Electrochemical impedance spectroscopy data collected at diferent potentials for a vacuum-filtered $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ hydrogel film (mass loading of $4.6\\mathsf{m g c m}^{-2})$ . The inset shows the high-frequency range. \n\n# Electrode design for high-rate performance \n\nPseudocapacitive materials are usually tested at moderate charge– discharge rates, namely between those of batteries and EDLCs. The electrochemical performance of MXenes at high rates remained unexplored, but previous reports demonstrated good rate handling ability up to $10\\bar{0}\\mathrm{mV}s^{-1}$ for electrodes having areal density in the range from 1 to $5\\mathrm{mg}\\mathrm{cm}^{-2}$ (refs 14,16,25). As shown in Fig. 2d, thin $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films deliver an exceptionally high-rate performance, yet when the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ hydrogel electrode was subjected to charging rates above $200\\mathrm{mVs^{-1}}$ , a rapid decrease in gravimetric and volumetric capacitance was observed. \n\nThe planar ‘paper’ electrode architecture with horizontal alignment of MXene flakes, which is formed during vacuumassisted filtration of the colloidal solution (Fig. 1b), results in electrode density approaching $4\\mathrm{gcm}^{-3}$ . This leads to a high volumetric capacitance, but limits high-rate charge transfer and impedes ion transport towards redox-active sites (Fig. 2g). \n\nElectrode architectures with macroporosity26,27 as well as decreased pore tortuosity28 were shown to be efficient to address this problem. Herein, we used templating with polymethyl methacrylate (PMMA) microspheres29 to create electrodes with open structure (Fig. 1c). In these electrodes—characterized by $1{-}2{\\cdot}\\upmu\\mathrm{m}$ -diameter macropores with submicrometre MXene wall thicknesses—the ion transport lengths are greatly reduced. X-ray diffraction data suggested less ordering of flakes in macroporous MXene (MPMXene) electrodes with only the (0002) peak appearing, in contrast to a set of (000l) peaks for MXene paper with well-aligned sheets (Supplementary Fig. 4). Transmission electron microscopy (TEM) analysis of the edge of an individual $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flake confirmed the presence of single-layer flakes (Supplementary Fig. 5a). Supplementary Fig. 5b shows the connection point of two $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ hollow spheres. Each sphere consists of a few monolayers with some flakes shared between each of them, providing a good connection and mechanical robustness (Supplementary Figs 5b and 6). \n\n![](images/c7a84730d13f790452faaef0c59765ca530f86235ba57d800a22fe3565d1c3b9.jpg) \nFigure 3 | Electrochemical performance of macroporous $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\bar{\\mathsf{T}}_{x}$ electrodes. a, Cyclic voltammetry profiles of a macroporous 13-µm-thick film with a $0.43\\mathsf{m g c m}^{-2}$ loading collected in 3 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at scan rates from 20 to $10,000\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . The inset shows schematically macroporous electrode architecture and ionic current pathways in it. b, Determination of the slope, $b,$ for the logarithm of anodic (open symbols) and cathodic (filled symbols) peak current versus logarithm of scan rate for macroporous films with diferent mass loadings from 0.45 to $4.5\\mathsf{m g c m}^{-2}$ . Capacitive storage is indicated by $b=1$ while $b=0.5$ is characteristic for difusion-limited processes. c, Electrochemical impedance spectroscopy data collected at diferent potentials for a macroporous film $(3.7\\mathsf{m g}\\mathsf{c m}^{-2}$ loading). d, Comparison of ion transport resistance for hydrogel (black squares) and macroporous (yellow circles) electrodes extracted from EIS collected at diferent applied potentials. The insets show schematically the ionic current pathway in hydrogel (top) and macroporous (bottom) electrodes. e,f, Rate performance of MXene films with diferent preparation methods and mass loadings represented in gravimetric (e) and areal (f) capacitance. \n\nElectrochemical studies of these macroporous electrodes revealed exceptional rate handling ability for a pseudocapacitive material (Fig. 3a,e), with gravimetric capacitance of $310\\mathrm{Fg}^{-1}$ at a scan rate of $\\mathrm{10mVs^{-1}}$ $(0.135\\mathrm{F}\\mathsf{c m}^{-2})$ ; $\\bar{210}\\mathrm{Fg}^{-1}$ $(0.090\\mathrm{F}\\mathrm{cm}^{-2}),$ at $10\\mathrm{V}\\mathrm{{s}^{-1}}$ and $100\\mathrm{Fg}^{-1}$ $0.043\\mathrm{F}\\mathsf{c m}^{-2})$ at $40\\mathrm{V}\\thinspace s^{-1}$ for a $13\\mathrm{-}\\upmu\\mathrm{m}$ -thick film, surpassing some of the best reported results30,31. To shed light on the charge storage kinetics, an analysis of peak current dependence on the scan rate was carried out. Assuming power-law dependence of the current, $i,$ on scan rate, $\\nu$ : \n\n$$\ni_{\\mathrm{p}}=a\\nu^{b}\n$$ \n\nwhere $^a$ and $b$ are variables, and a plot of $\\log{i}$ versus $\\log\\nu$ should result in a straight line with a slope equal to $b$ (Fig. 3b). The $b$ -value provides important information on the charge storage kinetics: $b\\ =\\ 1$ indicates capacitive storage, while $b~=~0.5$ is characteristic for diffusion-limited processes32. Herein for the $13\\upmu\\mathrm{m}$ macroporous film, $b$ was ${\\approx}1$ up to scan rates of $3\\mathrm{V}\\mathrm{~s}^{-1}$ (light blue symbols in Fig. 3b). For a $25\\mathrm{-}\\upmu\\mathrm{m}$ -thick macroporous electrode $b$ was ${\\approx}1$ up to scan rates of $2\\mathrm{V}\\mathsf{s}^{-1}$ (Fig. 3b), which reflected in excellent rate performance of the sample with capacitance of $280\\mathrm{Fg}^{-1}$ $(0.23\\mathrm{F}\\bar{\\mathrm{cm}}^{-2})$ ) at $1\\mathrm{V}\\mathsf{s}^{-1}$ and $12\\bar{0}\\mathrm{Fg}^{-1}$ $(0.1\\bar{0}\\mathrm{F}\\mathrm{cm}^{-2})$ at $10\\mathrm{V}\\thinspace\\mathsf{s}^{-1}$ . Even a $180\\mathrm{-}\\upmu\\mathrm{m}$ -thick film demonstrated capacitance of $125\\mathrm{Fg}^{-1}$ $(0.54\\mathrm{F}\\mathrm{cm}^{-2})$ at $1\\mathrm{V}\\mathsf{s}^{-1}$ and $32\\mathrm{Fg}^{-1}$ $(0.1\\dot{4}\\mathrm{F}\\mathrm{cm}^{-2})$ at $10\\mathrm{V}\\thinspace\\mathsf{s}^{-1}$ (Fig. 3b,e,f). Corresponding CV profiles for $25\\upmu\\mathrm{m}$ and $180\\upmu\\mathrm{m}$ samples collected at different scan rates are shown in Supplementary Fig. $^{7\\mathrm{a},\\mathrm{b},}$ respectively. EIS data collected at different potentials for the thick macroporous electrode with $3.7\\mathrm{mg}\\mathrm{cm}^{-2}$ weight loading revealed a significant decrease in ion transport resistance of $\\mathsf{\\bar{0}}.04\\Omega\\mathrm{cm}^{2}$ across all potentials for this electrode architecture when compared with hydrogel samples of comparable weight loading (Fig. 3c,d). It is important to mention that the open structure of the MP electrodes results in a lower electrode density $(\\sim0.35\\mathrm{gcm}^{-3})$ and therefore hydrogel-type electrodes should be used for high volumetric performance, since they possess a high density $(\\sim\\bar{4}\\mathrm{gcm}^{-3\\cdot},$ . \n\nIt is worth noting that exceptional high-rate performance is not unique to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene. As shown in Supplementary Fig. 8, only slight distortions of the CVs with increased scan rate are observed for a $30\\mathrm{-}\\upmu\\mathrm{m}$ -thick macroporous $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ electrode, with a capacitance of $100\\mathrm{Fg}^{-1}$ at $10\\mathrm{\\bar{V}}\\:s^{-1}$ . Given that more than 15 MXenes have been reported in the literature13 and the large compositional variability of the MAX phase33 precursors, it is reasonable to expect that other MXenes may perform equally well as, or better than, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ . Moreover, these design strategies also enabled exceptional areal capacitances; that is, for $40\\mathrm{-}\\upmu\\mathrm{m}$ -thick hydrogel electrodes $4\\mathrm{Fcm}^{-2}$ is achieved at $5\\mathrm{mVs}^{-1}$ (Fig. 3e); for a macroporous electrode with mass loading of $4.3\\mathrm{mg}\\mathrm{cm}^{=_{2}}$ , areal capacitance above $0.5\\mathrm{Fcm}^{-2}$ was maintained at scan rates up to $1\\mathrm{V}\\bar{\\mathsf{s}}^{\\bar{-}1}$ \n\n# Conclusions \n\nIn summary, we have demonstrated how different electrode design strategies can push MXene capacitance closer to its theoretical limit. Using glassy carbon current collectors, the working potential window was extended to $1\\mathrm{V}$ in 3 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte. We also show that the extended voltage window is not unique to glassy carbon, but is also achieved when other current collectors, such as graphite (Supplementary Fig. 9b) or Ti foil (Supplementary Fig. $9c$ ), are used. Macroporous electrode architectures enabled outstanding capacitance retention even at charge–discharge rates above $1\\mathrm{V}\\bar{\\mathsf{s}}^{-1}$ : $210\\mathrm{Fg}^{-1}$ at $10\\mathrm{V}\\thinspace\\mathsf{s}^{-1}$ and $100{\\overline{{\\mathrm{F}}}}{\\mathrm{g}}^{-1}$ at $\\bar{40}\\mathrm{V}\\thinspace s^{-1}$ , surpassing the best carbon supercapacitors known34. Hydrogel electrodes demonstrated exceptional volumetric capacitance up to $1{,}500\\mathrm{Fcm}^{-3}$ and areal capacitance up to $4\\mathrm{F}\\mathrm{cm}^{-2}$ , exceeding stateof-the-art supercapacitor materials30,31,34–37. This study shows that pseudocapacitive materials can be used for energy harvesting and storage at rates exceeding $10\\mathrm{V}\\mathrm{{s}^{-1}}$ , and probably higher rates can be achieved after further optimization of material composition and architecture, opening new exciting opportunities in the fields of electrochemical energy harvesting, conversion and storage. \n\n# Methods \n\nSynthesis of $\\mathbf{T}\\mathbf{i}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ . A mixture of hydrochloric acid (HCl) and lithium fluoride (LiF) was used to synthesize multilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ from $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ , which were synthesized similarly to a previous report14. Specifically, $2\\mathrm{g}$ of LiF was added to $40\\mathrm{ml}$ of $9\\mathrm{M}\\mathrm{HCl}$ (Fisher, Technical), followed by the slow addition of $2\\mathrm{g}$ of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (ice bath). After etching for $24\\mathrm{h}$ at $35^{\\circ}\\mathrm{C}$ , the multilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ was washed and centrifuged with deionized water until the supernatant reached a pH value ${\\approx}6$ . Next, the MXene powders were again mixed with deionized water and bath sonicated for $^{\\textrm{\\scriptsize1h}}$ , while bubbling Ar gas through the mixture. The sonication bath water with cooled with ice. Afterwards, the mixture was centrifuged for $^{\\textrm{1h}}$ at $^{3,500\\mathrm{r.p.m}}$ . $(2,301g)$ ). The resultant dark supernatant was a colloidal suspension of few-layer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ used to fabricate various $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ electrodes (see below). \n\nSynthesis of $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ . Molybdenum carbide MXene $(\\mathrm{Mo}_{2}\\mathrm{CT}_{x})$ ) was synthesized by immersing $\\mathrm{Mo}_{2}\\mathrm{Ga}_{2}\\mathrm{C}$ in hydrofluoric acid (HF), according to a recent paper16. The multilayer $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ powders were washed with deionized water and centrifuged repeatedly to neutral $\\mathrm{\\DeltapH}$ . The powders were then mixed with tetrabutylammonium hydroxide (TBAOH; Acros Organics, $40\\mathrm{wt\\%}$ in water), for $^{2\\mathrm{h}}$ under continuous stirring at room temperature. The mixture was centrifuged for $5\\mathrm{min}$ at $5,000\\mathrm{r.p.m}$ . $(4,696g)$ ), and the supernatant was decanted. The intercalated $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ sediment was rinsed with deionized water three times to remove residual TBAOH. The sediment was then mixed with deionized water and vigorously shaken in a vortex mixer to delaminate the $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ into few-layer $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ . After centrifugation for $^{\\textrm{1h}}$ at $5,000\\mathrm{r.p.m}$ . $(4,696g)$ ), the supernatant was separated from the sediment and used without further preparation to make various $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ electrodes (see below). \n\nPreparation of $\\mathbf{T}\\mathbf{i}_{3}\\mathbf{C}_{2}$ ‘paper’ electrodes. A $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ colloidal solution was vacuum-filtered through nanoporous polypropylene membrane (Celgard 3501, Celgard LLC) to make MXene ‘paper’ electrodes (VF-MXene). Once all of the water passed through the filter, the films were air-dried for several hours, before being peeled off the membrane and then used for electrochemical testing. Resulting electrode density values fall in the range from 3.7 to $4\\mathrm{gcm}^{-3}$ . \n\nPreparation of macroporous MXene electrodes. To synthesize hollow MXene spheres we first fabricated poly(methyl methacrylate) (PMMA) spheres following the process described in ref. 38. In short, a radical initiator, azoisobutyronitrile (Sigma-Aldrich), and a stabilizer, poly(vinyl pyrrolidone) (Sigma-Aldrich), were dissolved in methanol with a concentration of 0.1 and $4.0\\mathrm{wt\\%}$ , respectively, at room temperature. The solution was purged with Ar for $10\\mathrm{min}$ to remove oxygen. After that, methyl methacrylate monomer (MMA, Sigma-Aldrich) was added, at a concentration of $10\\mathrm{{wt\\%}}$ . The mixture was stirred at $55^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . Then, the white PMMA spheres were collected by centrifugation and washed with methanol. A colloidal solution of PMMA spheres was prepared by dispersing PMMA spheres in ethanol by sonication, at a concentration of $10\\mathrm{mg}\\mathrm{ml}^{-1}$ . Colloidal solutions of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ $2\\mathrm{mg}\\mathrm{ml}^{-1},$ and PMMA spheres $(10\\mathrm{mg}\\mathrm{ml}^{-1}.$ ) were mixed together while stirring. The mass ratio of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ to PMMA spheres was controlled at 1:4. The mixture was sonicated for $10\\mathrm{min}$ to ensure the uniform dispersion of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes and PMMA spheres in the solution. The mixture was filtered through a polypropylene membrane (3501 Coated PP, Celgard LL) to yield a film. This film was dried in air at room temperature for $10\\mathrm{min}$ and peeled off from the polypropylene membrane, yielding a flexible freestanding $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}/\\mathrm{PMMA}$ composite film. This composite film was annealed at $400^{\\circ}\\mathrm{C}$ under flowing Ar for $^{\\textrm{1h}}$ to burn out the PMMA spheres, leaving a macroporous $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film. The film thickness was controlled by varying the amount of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes used. Macroporous $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ films were prepared in a similar \n\nmanner. Resulting electrode density values fall in the range from 0.25 to $0.4\\mathrm{gcm}^{-3}$ . Density of 0.35 to $0.4\\mathrm{gcm}^{-3}$ was characteristic of electrodes with small to intermediate thickness $(<30\\upmu\\mathrm{m})$ , while thicker electrodes $(150-200\\upmu\\mathrm{m})$ possessed the density of 0.25 to $0.3\\mathrm{gcm}^{-3}$ . \n\nPreparation of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ hydrogels. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ hydrogel films were prepared by vacuum filtration of a delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ colloidal solution. It should be noted that the vacuum was disconnected immediately once there was no free $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ colloidal solution on the filtrate. Afterwards, the obtained hydrogel film was immersed in acetone and carefully peeled off from the filter membrane. After immersing in the electrolyte for $72\\mathrm{h}$ , the hydrogel film was then used for electrochemical characterizations directly. Resulting electrode density values fall in the range from 2.8 to $4.3\\mathrm{gcm}^{-3}$ . Thinner electrodes (1 to $15\\upmu\\mathrm{m}$ thick) possessed the highest density of ${\\sim}4\\mathrm{gcm}^{-3}$ , while thicker ones $({\\sim}40\\upmu\\mathrm{m})$ showed the lowest density of $\\sim2.8\\mathrm{gcm}^{-3}$ . This can be explained by better alignment of MXene flakes in thinner electrodes. \n\nElectrochemical measurements. All electrochemical tests were performed using a VMP3 potentiostat (Biologic). Cyclic voltammetry was conducted in three-electrode plastic Swagelok cells. MXene electrode on glassy carbon current collector was used as a working electrode and overcapacitive activated carbon was used as a counter electrode. The reference electrodes were either $\\mathrm{Hg/Hg_{2}S O_{4}}$ in saturated $\\mathrm{K}_{2}\\mathrm{SO}_{4}$ or $\\mathrm{\\Ag/AgCl}$ in $1\\mathrm{M}\\mathrm{KCl}$ After initially pre-cycling the electrodes at $20\\mathrm{mVs^{-1}}$ the cells were tested from scan rates of $2\\mathrm{mVs}^{-1}$ to $\\mathrm{100,000mVs^{-1}}$ . Galvanostatic cycling was performed at current densities from 1 to $100\\mathrm{Ag^{-1}}$ . The same 3-electrode cell configuration described above was used for electrochemical impedance spectroscopy (EIS) in the $100\\mathrm{mHz}$ to $100\\mathrm{kHz}$ range using a potential amplitude of $10\\mathrm{mV}.$ EIS spectra were collected at various potentials and were recorded versus $\\mathrm{Hg/Hg_{2}S O_{4}}$ reference electrode after holding at each potential for $0.5\\mathrm{h}$ (Fig. 3a). For thick hydrogel samples, the ESR (equivalent series resistance) was subtracted from the real part resistance as shown on the $x$ axis, to eliminate the effect of resistance originating from the $\\mathrm{Hg/Hg_{2}S O_{4}}$ reference electrode, which may also vary with the potential. The ion transport resistance at each potential was then calculated from the difference of the knee frequency resistance and the $\\mathrm{ESR},$ and plotted versus potential (Fig. 3d). \n\nCapacitance calculations. The capacitance was calculated by integration of current with respect to time: \n\n$$\nC=\\frac{\\int_{0}^{V/s}\\left|j\\right|\\mathrm{d}t}{V}\n$$ \n\nwhere $C$ is the gravimetric capacitance $(\\mathrm{F}\\mathfrak{g}^{-1}),j$ is the gravimetric current density $\\left(\\mathrm{A}\\mathbf{g}^{-1}\\right)$ , $s$ is the scan rate $\\ensuremath{(\\mathrm{V}\\mathrm{~s}^{-1})}$ , and $V$ is the potential window (V). To calculate the volumetric and areal capacitances, the gravimetric capacitance was multiplied by the volumetric $(\\mathrm{gcm}^{-3})$ or areal $(\\mathbf{g}\\thinspace\\mathrm{cm}^{-2})$ ) density of the electrode. \n\nCharacterization of structure and properties. X-ray diffraction (XRD) patterns of MXene films were obtained using a powder diffractometer (SmartLab, Rigaku Corp. or D4 ENDEAVOR, Bruker) using $\\mathrm{Cu\\Ka_{1}}$ radiation. A scanning electron microscope, (SEM; Zeiss Supra 50VP, Carl Zeiss SMT AG or JSM-6510LV, JEOL), equipped with an energy-dispersive X-ray spectroscope (Oxford EDS), was used to characterize the microstructure and measure the electrode thicknesses. A JEM-2100 (JEOL) transmission electron microscope (TEM) was used to analyse the MXene flakes using an accelerating voltage of $200\\mathrm{kV}.$ Samples for TEM observation were prepared by dropping two drops of the MXene dispersion in water onto a lacey carbon-coated copper grid (Electron Microscopy Sciences) and air-dried. \n\nCharacterization of macroporous electrodes. Synthesis of the PMMA resulted in spherical particles $1.7\\pm0.3{\\upmu\\mathrm{m}}$ in diameter, as shown in Supplementary Fig. 5a. When the PMMA spheres were mixed with colloidal $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ flakes, the former acted as templates for the latter to wrap around into a MXene/PMMA composite. After heating the composite at $400^{\\circ}\\mathrm{C}$ under Ar flow, the PMMA spheres evaporated, resulting in hollow $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ spheres of roughly the same size as the PMMA particles (Supplementary Fig. 5b). The same method was used to produce $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ hollow spheres of the same size. Micrographs of the macroporous $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ films’ cross-sections are shown in Supplementary Fig. 5c,d. The XRD patterns of a vacuum-filtered $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film (Supplementary Fig. 4a) show only the broad (000l) MXene peaks, confirming that the synthesis was successful. The $d_{0002}$ peak at $6.6^{\\circ}~2\\theta$ corresponds to a $\\boldsymbol{\\mathbf{\\mathit{c}}}$ -lattice parameter of $26.8\\mathring\\mathrm{A}$ , which is close to typical values found in the literature39. After annealing the $\\mathrm{PMMA}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ mixture at $400^{\\circ}\\mathrm{C},$ , the $\\boldsymbol{c}$ -lattice parameter remained unchanged, but all (000l) peaks become significantly broader such that the higher order basal reflections were longer visible. More importantly, the absence of reflections corresponding to PMMA at $13^{\\circ}$ and $30^{\\circ}2\\theta$ in the XRD pattern38 of the macroporous films confirmed their full removal. Similarly, the XRD pattern of a vacuum-filtered $\\mathbf{Mo}_{2}\\mathbf{CT}_{x}$ film (Supplementary Fig. 4b) shows broad (000l) \n\npeaks, in agreement with previous reports16. After annealing away the PMMA spheres however, the (0002) peak experiences significant broadening and a slight upshift in angle. These observations may reflect the vaporization and deintercalation of residual tetrabutylammonium cations. \n\nProcessing control for hydrogel films. The thicknesses and mass loadings of the hydrogel films were controlled by starting with different volumes of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ colloidal solutions during vacuum filtration. However, as mentioned above, the water from the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ colloidal solutions was not completely removed following drying. Therefore, the mass loadings and thicknesses of the hydrogel films were only precisely measured after the electrochemical tests. Specifically, the tested films were washed with deionized water and ethanol to remove the electrolyte, and then dried in a vacuum oven for more than $24\\mathrm{h}$ . Lastly, the mass and thicknesses of the dried films were measured with a microbalance and SEM, respectively. \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding authors on request. \n\n# Received 1 February 2017; accepted 31 May 2017; published 10 July 2017 \n\n# References \n\n1. Lukatskaya, M. R., Dunn, B. & Gogotsi, Y. Multidimensional materials and device architectures for future hybrid energy storage. Nat. Commun. 7, 12647 (2016). \n2. Conway, B. Electrochemical Supercapacitors: Scientific Fundamentals and Technological Applications (Kluwer Academic/Plenum, 1999). \n3. Simon, P. & Gogotsi, Y. Materials for electrochemical capacitors. Nat. Mater. 7, 845–854 (2008). \n4. Sugimoto, W., Iwata, H., Yokoshima, K., Murakami, Y. & Takasu, Y. Proton and electron conductivity in hydrous ruthenium oxides evaluated by electrochemical impedance spectroscopy: the origin of large capacitance. J. Phys. Chem. B 109, 7330–7338 (2005). \n5. Zheng, J. P., Cygan, P. J. & Jow, T. R. Hydrous ruthenium oxide as an electrode material for electrochemical capacitors. J. Electrochem. Soc. 142, 2699–2703 (1995). \n6. Sassoye, C. et al. Block-copolymer-templated synthesis of electroactive $\\mathrm{RuO}_{2}$ -based mesoporous thin films. Adv. Funct. Mater. 19, 1922–1929 (2009). \n7. Hu, C.-C., Chang, K.-H., Lin, M.-C. & Wu, Y.-T. Design and tailoring of the nanotubular arrayed architecture of hydrous $\\mathrm{RuO}_{2}$ for next generation supercapacitors. Nano Lett. 6, 2690–2695 (2006). \n8. Toupin, M., Brousse, T. & Bélanger, D. Charge storage mechanism of $\\mathrm{MnO}_{2}$ electrode used in aqueous electrochemical capacitor. Chem. Mater. 16, 3184–3190 (2004). \n9. Brezesinski, T., Wang, J., Tolbert, S. H. & Dunn, B. Ordered mesoporous [alpha]- $\\mathrm{MoO}_{3}$ with iso-oriented nanocrystalline walls for thin-film pseudocapacitors. Nat. Mater. 9, 146–151 (2010). \n10. Come, J. et al. Electrochemical kinetics of nanostructured $\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ electrodes. J. Electrochem. Soc. 161, A718–A725 (2014). \n11. Augustyn, V. et al. High-rate electrochemical energy storage through Li+ intercalation pseudocapacitance. Nat. Mater. 12, 518–522 (2013). \n12. Choi, D., Blomgren, G. E. & Kumta, P. N. Fast and reversible surface redox reaction in nanocrystalline vanadium nitride supercapacitors. Adv. Mater. 18, 1178–1182 (2006). \n13. Naguib, M., Mochalin, V. N., Barsoum, M. W. & Gogotsi, Y. MXenes: a new family of two-dimensional materials. Adv. Mater. 26, 992–1004 (2014). \n14. Ghidiu, M., Lukatskaya, M. R., Zhao, M.-Q., Gogotsi, Y. & Barsoum, M. W. Conductive two-dimensional titanium carbide ‘clay’ with high volumetric capacitance. Nature 516, 78–81 (2014). \n15. Hope, M. A. et al. NMR reveals the surface functionalisation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene. Phys. Chem. Chem. Phys. 18, 5099–5102 (2016). \n16. Halim, J. et al. Synthesis and characterization of 2D molybdenum carbide (MXene). Adv. Funct. Mater. 26, 3118–3127 (2016). \n17. Lukatskaya, M. R. et al. Probing the mechanism of high capacitance in 2D titanium carbide using in situ X-ray absorption spectroscopy. Adv. Energy Mater. 5, 1500589 (2015). \n18. Hu, M. et al. High-capacitance mechanism for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ MXene by in situ electrochemical raman spectroscopy investigation. ACS Nano 10, 11344–11350 (2016). \n19. Lukatskaya, M. R. et al. Cation intercalation and high volumetric capacitance of two-dimensional titanium carbide. Science 341, 1502–1505 (2013). \n20. Benck, J. D., Pinaud, B. A., Gorlin, Y. & Jaramillo, T. F. Substrate selection for fundamental studies of electrocatalysts and photoelectrodes: inert potential windows in acidic, neutral, and basic electrolyte. PLoS ONE 9, e107942 (2014) \n21. Darling, H. E. Conductivity of sulfuric acid solutions. J. Chem. Eng. Data 9, 421–426 (1964). \n22. Gogotsi, Y. & Simon, P. True performance metrics in electrochemical energy storage. Science 334, 917–918 (2011). \n23. Lin, Z. et al. Capacitance of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene in ionic liquid electrolyte. J. Power Sources 326, 575–579 (2016). \n24. Yang, X., Cheng, C., Wang, Y., Qiu, L. & Li, D. Liquid-mediated dense integration of graphene materials for compact capacitive energy storage. Science 341, 534–537 (2013). \n25. Mashtalir, O. et al. The effect of hydrazine intercalation on structure and capacitance of 2D titanium carbide (MXene). Nanoscale 8, 9128–9133 (2016). \n26. Li, Y. et al. Synthesis of hierarchically porous sandwich-like carbon materials for high-performance supercapacitors. Chem. Eur. J. 22, 16863–16871 (2016). \n27. Zhu, C. et al. Supercapacitors based on three-dimensional hierarchical graphene aerogels with periodic macropores. Nano Lett. 16, 3448–3456 (2016). \n28. Yoo, J. J. et al. Ultrathin planar graphene supercapacitors. Nano Lett. 11, 1423–1427 (2011). \n29. Chen, C.-M. et al. Macroporous ‘bubble’ graphene film via template-directed ordered-assembly for high rate supercapacitors. Chem. Commun. 48, 7149–7151 (2012). \n30. Lang, X.-Y. et al. Ultrahigh-power pseudocapacitors based on ordered porous heterostructures of electron-correlated oxides. Adv. Sci. 3, 1500319 (2016). \n31. El-Kady, M. F. et al. Engineering three-dimensional hybrid supercapacitors and microsupercapacitors for high-performance integrated energy storage. Proc. Natl Acad. Sci. USA 112, 4233–4238 (2015). \n32. Lindström, H. et al. ${\\mathrm{Li}}^{+}$ ion insertion in $\\mathrm{TiO}_{2}$ (Anatase). 2. Voltammetry on nanoporous films. J. Phys. Chem. B 101, 7717–7722 (1997). \n33. Barsoum, M. W. The $\\mathrm{M}_{N+1}\\mathrm{AX}_{N}$ phases: a new class of solids: thermodynamically stable nanolaminates. Prog. Solid State Chem. 28, 201–281 (2000). \n34. Pech, D. et al. Ultrahigh-power micrometre-sized supercapacitors based on onion-like carbon. Nat. Nanotech. 5, 651–654 (2010). \n35. Acerce, M., Voiry, D. & Chhowalla, M. Metallic 1T phase $\\mathrm{MoS}_{2}$ nanosheets as supercapacitor electrode materials. Nat. Nanotech. 10, 313–318 (2015). \n36. Zhu, M. et al. Highly flexible, freestanding supercapacitor electrode with enhanced performance obtained by hybridizing polypyrrole chains with MXene. Adv. Energy Mater. 6, 1600969 (2016). \n37. Zhao, X. et al. Incorporation of manganese dioxide within ultraporous activated graphene for high-performance electrochemical capacitors. ACS Nano 6, 5404–5412 (2012). \n38. Shen, S., Sudol, E. D. & El-Aasser, M. S. Control of particle size in dispersion polymerization of methyl methacrylate. J. Polym. Sci. A 31, 1393–1402 (1993). \n39. Ling, Z. et al. Flexible and conductive MXene films and nanocomposites with high capacitance. Proc. Natl Acad. Sci. USA 111, 16676–16681 (2014). \n\n# Acknowledgements \n\nWe thank C.(E.) Ren for help with material synthesis. XRD, SEM and TEM investigations were performed at the Core Research Facilities (CRF) at Drexel University. Y.G., M.R.L. and M.-Q.Z. were supported by the Fluid Interface Reactions, Structures and Transport (FIRST) Center, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, and Office of Basic Energy Sciences. S.K. was supported by the US National Science Foundation under grant number DMR-1310245. Z.-F. Lin was supported by China Scholarship Council (No. 201304490006). P.S. and P.-L.T. thank the ANR (LABEX STAEX) and RS2E for financial support. M.L. and N.S. acknowledge funding from the Binational Science Foundation (BSF) USA-Israel via Research Grant Agreement 2014083/2016. \n\n# Author contributions \n\nM.R.L. and Y.G. planned the study. S.K., M.R.L., Z.L. and N.S. conducted electrochemical testing. Z.L. and S.K. performed XRD and SEM analysis. M.-Q.Z., Z.L. and J.H. synthesized MXenes and fabricated electrodes. M.-Q.Z. performed TEM analysis. Y.G., P.S., M.R.L., M.D.L., P.-L.T. and M.W.B. supervised the research and discussed the results. \n\n# Additional information \n\nSupplementary information is available for this paper. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\n# Correspondence and requests for materials should be addressed to P.S. or Y.G. \n\nHow to cite this article: Lukatskaya, M. R. et al. Ultra-high-rate pseudocapacitive energy storage in two-dimensional transition metal carbides. Nat. Energy 2, 17105 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Competing interests \n\nThe authors declare no competing financial interests. " + }, + { + "id": "10.1038_NCHEM.2695", + "DOI": "10.1038/NCHEM.2695", + "DOI Link": "http://dx.doi.org/10.1038/NCHEM.2695", + "Relative Dir Path": "mds/10.1038_NCHEM.2695", + "Article Title": "Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution", + "Authors": "Grimaud, A; Diaz-Morales, O; Han, BH; Hong, WT; Lee, YL; Giordano, L; Stoerzinger, KA; Koper, MTM; Shao-Horn, Y", + "Source Title": "NATURE CHEMISTRY", + "Abstract": "Understanding how materials that catalyse the oxygen evolution reaction (OER) function is essential for the development of efficient energy-storage technologies. The traditional understanding of the OER mechanism on metal oxides involves four concerted proton-electron transfer steps on metal-ion centres at their surface and product oxygen molecules derived from water. Here, using in situ O-18 isotope labelling mass spectrometry, we provide direct experimental evidence that the O-2 generated during the OER on some highly active oxides can come from lattice oxygen. The oxides capable of lattice-oxygen oxidation also exhibit pH-dependent OER activity on the reversible hydrogen electrode scale, indicating non-concerted proton-electron transfers in the OER mechanism. Based on our experimental data and density functional theory calculations, we discuss mechanisms that are fundamentally different from the conventional scheme and show that increasing the covalency of metal-oxygen bonds is critical to trigger lattice-oxygen oxidation and enable non-concerted proton-electron transfers during OER.", + "Times Cited, WoS Core": 1718, + "Times Cited, All Databases": 1786, + "Publication Year": 2017, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000399785500013", + "Markdown": "# Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution \n\nAlexis Grimaud1†‡, Oscar Diaz-Morales2‡, Binghong Han3‡, Wesley T. Hong3, Yueh-Lin Lee1,4, Livia Giordano4,5, Kelsey A. Stoerzinger3, Marc T. M. Koper2 and Yang Shao-Horn1,3,4\\* \n\nUnderstanding how materials that catalyse the oxygen evolution reaction (OER) function is essential for the development of efficient energy-storage technologies. The traditional understanding of the OER mechanism on metal oxides involves four concerted proton–electron transfer steps on metal-ion centres at their surface and product oxygen molecules derived from water. Here, using in situ $\\mathfrak{r}\\mathfrak{s}_{\\pmb{0}}$ isotope labelling mass spectrometry, we provide direct experimental evidence that the $\\bullet_{2}$ generated during the OER on some highly active oxides can come from lattice oxygen. The oxides capable of latticeoxygen oxidation also exhibit pH-dependent OER activity on the reversible hydrogen electrode scale, indicating nonconcerted proton–electron transfers in the OER mechanism. Based on our experimental data and density functional theory calculations, we discuss mechanisms that are fundamentally different from the conventional scheme and show that increasing the covalency of metal–oxygen bonds is critical to trigger lattice-oxygen oxidation and enable non-concerted proton–electron transfers during OER. \n\nctivating the anionic redox chemistry of oxygen in metal oxides, on the surface and in bulk, can provide exciting opportunities for the design of materials in clean-energy and environmental applications. Such chemistry, which involves the formation of bulk peroxo-like $(\\mathrm{O}_{2})^{n-}$ species1, has been shown to be important in applications such as catalysing the oxygen evolution reaction (OER) in photoelectrochemical water splitting2–6, regenerative fuel cells7,8, rechargeable metal–air batteries and storing energy in lithium-ion battery materials9,10. In this Article we demonstrate that enabling the oxidation of lattice oxygen in highly covalent metal oxides during the OER can enhance OER activity and trigger non-concerted proton– electron transfer. \n\nThe current understanding of the OER mechanism on metal oxides11,12, which is largely drawn from studies on metal surfaces13, involves four concerted proton–electron transfer steps on surface metal-ion centres, yielding $\\mathrm{\\pH}$ -independent activity on the reversible hydrogen electrode (RHE) scale14. With this mechanism, high OER activities can be obtained by optimizing the binding strength of reaction intermediates on surfaces (neither too strong nor too weak)11,12, and this is supported by experimental findings that the OER activities of oxides in basic solution (the $\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}$ couple: $4\\mathrm{OH}^{-}\\rightarrow\\mathrm{O}_{2}+2\\mathrm{H}_{2}\\mathrm{O}+4\\mathrm{e}^{-})$ correlate with oxide electronic structure parameters such as the estimated $e_{\\mathrm{g}}$ occupancy of surface transitionmetal ions15. However, this conventional mechanism—centred on the redox chemistry of the metal cation—has been challenged by a few observations in recent years. First, some highly active oxides exhibit pH-dependent OER activity on the RHE scale16–18, suggesting that non-concerted proton–electron transfers participate in catalysing the $\\mathrm{OER^{14}}$ . Second, changing the bulk oxide electronic structure, for example, increasing the oxygen $2p$ -band centre (defined relative to the Fermi level)19,20 and metal–oxygen hybridization15,21, has been correlated with enhanced OER activities in perovskites, highlighting the role of bulk electronic structure in catalysing OER kinetics19,22,23. Third, mass spectrometry measurements of oxides stable in bulk during OER, such as $\\mathrm{NiCo}_{2}\\mathrm{O}_{4}$ in basic solution24, $\\mathrm{IrO}_{2}$ (ref. 25) and ${\\mathrm{RuO}}_{2}$ (ref. 26,27) in acid, and Co-Pi (ref. 28) in neutral solutions, reveal that the evolved oxygen molecules can come not only from water molecules but also from the oxide29–31. \n\nIn this study, we provide, for the first time, direct experimental evidence for the involvement of lattice oxygen redox chemistry in the OER mechanisms within the perovskite family. On-line electrochemical mass spectrometry (OLEMS) measurements of $^{18}\\mathrm{O}$ -labelled perovskites reveal that the oxidation of lattice oxygen occurs during the OER for highly covalent oxides such as $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ , for which up to 37 monolayers of oxides $({\\sim}14~\\mathrm{nm})$ can be involved during the OER process, but not for the less covalent $\\mathrm{LaCoO}_{3}$ . Moreover, highly covalent oxides exhibit $\\mathrm{\\pH}$ -dependent OER activities (on the RHE scale), whereas $\\mathrm{LaCoO}_{3}$ shows the $\\mathrm{\\pH}$ -independent OER activity expected from the conventional OER mechanism. In light of these findings, we discuss potential OER mechanisms that are fundamentally different from the conventional scheme, which involve redox reactions of lattice oxygen and non-concerted proton–electron transfer steps to explain the lattice oxygen oxidation and the $\\mathrm{\\tt{pH}}$ -dependent OER activity observed with highly covalent and active catalysts. \n\n# Results and discussion \n\nEvidence of lattice oxygen oxidation during OER. Here, we compare the participation of lattice oxygen oxidation in the OER among $\\mathrm{LaCoO}_{3}$ , $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ (that is, double perovskite $\\mathrm{PrBaCo}_{2}\\mathrm{O}_{5+\\delta})$ and $\\mathrm{SrCoO}_{3-\\delta}$ . It is of particular interest to examine the role of metal–oxygen covalency on the participation of lattice oxygen oxidation in the OER. Density functional theory (DFT) studies19,20 have shown that substituting trivalent ions such as ${\\mathrm{La}}^{3+}$ with divalent ions such as $\\operatorname{Sr}^{2+}$ on the A-site of the perovskite structure $(\\mathrm{ABO}_{3})$ moves the Fermi level closer to the computed O $2p$ -band centre, which is accompanied by a reduced energy gap between the metal $3d$ and O $2p$ -band centres (Fig. 1a), in agreement with work by Cheng and co-authors32. As the Fermi level moves down in energy and closer to the O $2p$ states from $\\mathrm{LaCoO}_{3}$ to $\\mathrm{SrCoO}_{3}$ , the antibonding states below the Fermi level exhibit greater oxygen character, indicative of greater covalency of the metal–oxygen bond33. Similar hybridization has been reported for layered metal chalcogenides34, perovskite-like cuprates35 and layered ${\\mathrm{Li}}_{x}{\\mathrm{CoO}}_{2}$ $(x=\\sim\\bar{0})^{36}$ . The oxidation of lattice oxygen in the perovskites becomes thermodynamically favourable when O $2p$ states at the perovskite Fermi level lie above the redox energy of the $\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}$ couple, as shown in Fig. 1b. Lattice oxygen oxidation is fundamentally different from oxygen intercalation (oxygen vacancy filling via $\\mathrm{ACoO}_{3-\\delta}+2\\delta\\mathrm{OH}^{-}\\rightarrow\\mathrm{ACoO}_{3}+\\delta\\mathrm{H}_{2}\\mathrm{O}+2\\delta\\mathrm{e}^{-})$ upon the oxidation of oxygen-deficient perovskites in an alkaline electrolyte37–39, which is driven by the energy difference between the $\\mathrm{H}_{2}\\mathrm{O}/\\mathrm{H}_{2}$ redox couple and the $\\mathrm{Co}\\quad3d$ states at the Fermi level of oxides (Fig. 1b). \n\n![](images/2f29f8f2eb2f1bc329607bacfb44e67ab1a4a8af22c50095bb6f4aad9f613990.jpg) \nFigure 1 | Electronic structures of Co-containing perovskite oxides. a, Difference between the Co $3d\\cdot$ -band centre and the $\\textsf{O}2p$ -band centre versus the O $2p$ -band centre relative to the Fermi level for stoichiometric ${\\mathsf{A C o O}}_{3}$ perovskites. Details of the computational approaches are provided in the Supplementary Information. b, Schematic rigid band diagrams of $\\mathsf{L a C o O}_{3}$ and $\\mathsf{S r C o O}_{3}$ . The position of the $0_{2}/\\mathsf{H}_{2}\\mathsf{O}$ redox couple at pH 14 $\\langle40\\mathsf{H}^{-}\\to0_{2}+2\\mathsf{H}_{2}\\mathsf{O}+4\\mathsf{e}^{-}\\rangle$ is 1.23 V versus RHE, as shown schematically on the right. The relationship between voltages under the RHE and standard hydrogen electrode (SHE) scale is $\\varepsilon_{\\mathsf{R H E}}=\\varepsilon_{\\mathsf{S H E}}+59\\mathsf{m V}\\times\\mathsf{p H}.$ \n\nOLEMS was used to detect the participation of lattice oxygen oxidation in the OER catalysed by these Co-based perovskites with different metal–oxygen covalency. $\\mathrm{LaCoO}_{3}$ , $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ were prepared by conventional solid-state synthesis (see Methods). These oxides are stable in bulk during OER, in contrast to $\\mathrm{Ba_{0.5}S r_{0.5}C o_{0.8}F e_{0.2}O_{3-\\delta}}$ , which becomes amorphous during $\\mathrm{OER^{40,41}}$ . In this work, we assert that oxides are not stable in bulk during OER, when considerable amorphization and loss of metal ions for oxide particles following OER are clearly discernable using transmission electron microscopy and associated spectroscopy, as reported previously40,41. This definition is different from the thermodynamic instability of oxides described in previous work42, which indicates that oxides are formally unstable when interfacing with aqueous electrolytes free of metal cations. Here, the oxide particles were dispersed on a gold disk electrode and labelled with $^{18}\\mathrm{O}$ by potentiostatic holding at $1.6\\mathrm{V}$ versus Au in $\\mathrm{H}_{2}^{\\ 18}\\mathrm{O}$ -labelled 0.1 M KOH solution for $10\\mathrm{min}$ (see Methods and Supplementary Fig. 19). After rinsing with $^{16}\\mathrm{O}$ water to remove $\\mathrm{H}_{2}^{\\mathrm{~18}}\\mathrm{\\dot{O}}$ , OLEMS measurements were performed on these oxide electrodes in a $0.1\\mathrm{{M}}$ KOH solution of $\\mathrm{~{~H~}}_{2}^{16}\\mathrm{{O}}$ using cyclic voltammetry (CV). The OER activities of these oxides on \n\nAu during OLEMS (Supplementary Fig. 1) were found to be similar to those measured by rotating disk electrode (RDE) measurements on glassy carbon (Supplementary Fig. 2), which are also consistent with those reported previously19,40,41. Oxygen gas of different molecular weights generated during OER was measured in situ by mass spectroscopy, where the signal for mass-to-charge ratio $m/z=32$ represents $^{32}\\mathrm{O}_{2}$ $\\overset{(16}{\\mathrm{O}}^{16}\\mathrm{O})$ , $m/z=34$ represents $^{34}\\mathrm{O}_{2}$ $^{\\cdot16}\\mathrm{O}^{18}\\mathrm{O})$ and $m/z=36$ represents $^{36}\\mathrm{O}_{2}$ $^{\\prime18}\\mathrm{O}^{18}\\mathrm{O})$ . The signal of $m/z=34$ was normalized by the signal of $m/z=32$ to account for natural isotopic abundance $(\\sim0.2\\%)$ . This normalized signal of $m/z=34$ to $m/z=32$ and the mass signal of $m/z=36$ collected from the OER in the first cycle are shown in Fig. 2a and b, respectively. As the signals of $m/z=32$ detected by OLEMS include both molecular oxygen formed during the OER and oxygen from ambient air, the ratio of OER current involving $m/z=34$ and $m/z=36$ to that with $m/z=32$ could not be quantified in this study. \n\nNeither normalized $m/z=34$ (Fig. 2a) nor $m/z=36$ (Fig. 2b) was detected during the OER for $\\mathrm{LaCoO}_{3}$ , indicating there was no oxygen from the $\\mathrm{LaCoO}_{3}$ lattice in the molecular oxygen evolved. For $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , the normalized $m/z=34$ rose slightly above the natural abundance of $^{18}\\mathrm{O}$ (Fig. 2a), and small signals of $m/z=36$ were detected at $1.6\\mathrm{V}$ versus RHE and above (Fig. 2b), indicating successful $^{18}\\mathrm{O}$ labelling and the involvement of lattice oxygen in the OER. Of significance, lattice oxygen oxidation during the OER measured from $\\mathrm{SrCoO}_{3-\\delta}$ was more pronounced than that for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}.$ , as both the normalized $m/z=34$ and $m/z=36$ signals detected from $\\mathrm{SrCoO}_{3-\\delta}$ were greater, with lower onset voltages $_{1.5\\mathrm{V}}$ versus RHE and greater), as shown in Fig. 2. The detection of $^{16}\\mathrm{O}^{18}\\mathrm{O}$ during the OER (one oxygen from the electrolyte and the other from the oxide lattice) as well as $^{18}\\mathrm{O}^{18}\\mathrm{O}$ (two oxygens from the oxide lattice) requires the oxidation of lattice oxygen from metal oxides and the formation of oxygen vacancies during the OER. The release of $^{16}\\mathrm{O}^{16}\\mathrm{O}$ , $^{16}\\mathrm{O}^{18}\\mathrm{O}$ and $^{18}\\mathrm{O}^{18}\\mathrm{O}$ for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ , which are stable in bulk during OER, differs from those for catalysts that are amorphized in bulk under OER, such as $\\mathrm{Ba_{0.5}S r_{0.5}C o_{0.8}F e_{0.2}O_{3-\\delta}}$ (refs 40,41), where $^{16}\\mathrm{O}^{16}\\mathrm{O}$ and $^{18}\\mathrm{O}^{18}\\mathrm{O}$ are released independently of the potential in the negative sweep (Supplementary Figs 1 and 3). The amount of $^{18}\\mathrm{O}$ detected during the OER was used to estimate the number of monolayers, or thickness normal to the (001) surface, in the cubic perovskite structure involved in the OER for $\\mathrm{LaCoO}_{3}$ , $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ (Supplementary Table 3 and Supplementary Fig. 4). The minimum oxide thickness involved during OER was estimated to be ${\\sim}0.5\\ \\mathrm{nm}$ for $\\mathrm{LaCoO}_{3}$ , indicating a surface OER process. In contrast, the minimum thicknesses estimated for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ were ${\\sim}0.7$ , 1.5 and $14\\mathrm{nm}$ , respectively, demonstrating the participation of oxygen from the oxides in the OER. Having considerable oxygen originating from oxides participating in the OER is not surprising, considering that the bulk diffusion of oxygen ions at room temperature can be large (for example, $\\tilde{D}_{O}\\approx\\mathrm{i}0^{-11}\\mathrm{cm}^{2}s^{-1}$ for $\\mathrm{SrCoO}_{3-\\delta})^{38}$ . The physical origin of the oxidation of lattice oxygen can be attributed to a shift of the Fermi level deeper into the O $2p$ band. When the $\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}$ redox potential aligns with the energy corresponding to the O $2p$ states of the oxide, holes are created in the oxygen band, which can allow oxidized oxygen ions to form $(\\mathrm{O}_{2})^{\\dot{n}-}$ species, analogous to anionic redox of chalcogenides34 and/or molecular oxygen33 (leaving oxygen vacancies behind). The more $\\mathrm{O}_{2}$ generated during OER, the greater the value for $^{18}\\mathrm{O}/^{16}\\mathrm{O}$ (Supplementary Fig. 5), indicating that the amount of lattice oxygen detected during the OER process depends on the position of the O $2p$ states relative to the Fermi level and correlates with the OER activity for this family of oxides. \n\n![](images/e6c889a1b7de9a0fe57079127f4caa03f59edb8a991d8d5f78e0f03ee1712394.jpg) \nFigure 2 | Direct evidence of lattice oxygen oxidation involved in the OER of $^{18}0$ -labelled perovskites. Data were measured in 0.1 M KOH by OLEMS at a scan rate of $2{\\mathsf{m}}{\\mathsf{V}}{\\mathsf{s}}^{-1}$ (no gas bubbling). a, $^{34}\\mathrm{O}_{2}/{}^{32}\\mathrm{O}_{2}$ ratios, where the straight lines correspond to the natural abundance of $^{18}\\mathrm{O}$ of $0.2\\%$ . The arrows indicate forward and backward scans. b, $^{36}\\mathrm{O}_{2}$ signal. All data were taken from the first cycle (data from the second cycle are provided in Supplementary Fig. 1). $^{34}\\mathsf{O}_{2}$ but not $^{36}\\mathsf{O}_{2}$ was detected in the cathodic sweep at potentials where there is no OER activity. The origin of this is not understood. We speculate that chemical processes triggered by OER with lattice oxygen participation might be responsible for the evolution of $^{34}\\mathsf{O}_{2}$ in the cathodic sweep, but further studies are needed. \n\nThe participation of lattice oxygen oxidation in the OER for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ highlights a fundamental mechanistic shift from the conventional OER mechanism involving four concerted proton–electron-transfer steps on surface metal ions11,12. The lattice oxygen oxidation found in the OER in this study is distinct from the participation of active vacancy sites in the $\\dot{\\mathrm{OER}}^{43}$ or the oxygen intercalation reaction in oxygendeficient oxides37–39, which largely involve the redox of the cation and do not form $_{\\mathrm{O-O}}$ bonds involving metal oxide lattice oxygen. As previous work shows that $\\mathrm{La}_{0.8}\\mathrm{Sr}_{0.2}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{La}_{0.6}\\mathrm{Sr}_{0.4}\\mathrm{CoO}_{3-\\delta}$ exhibit pH-dependent OER activity on the RHE scale16,17, we investigate in the following whether the participation of lattice oxygen oxidation in the OER is associated with non-concerted proton–electron transfer processes14, giving rise to $\\mathrm{\\pH}$ -dependent OER activity. \n\npH-dependent OER kinetics. Oxides that exhibited the oxidation of lattice oxygen during the OER (that is, $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta};$ Fig. 2) were found to have pH-dependent OER kinetics on the RHE scale (Fig. 3 and \n\n![](images/11a293f12df2f94c0ca302cd1e725442157941e8a44d73e41dea6a457176418a.jpg) \nFigure 3 | pH-dependent OER activity on the RHE scale. a, CV measurements from $\\mathsf{O}_{2}$ -saturated 0.03 M KOH $\\cdot\\mathsf{p H}12.5)$ to 1 M KOH (pH 14) recorded at $\\mathsf{10}\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . ${\\big\\vert}\\mathbf{b},$ Specific OER activity (current normalized by oxide BET surface area) at $\\ensuremath{\\uparrow.55\\mathrm{V}}$ versus RHE after $i R$ correction as a function of pH. The nominal oxide loading is $0.25\\mathrm{mg}_{\\mathrm{oxide}}\\mathrm{cm}_{\\mathrm{disk}}^{-2}.$ Error bars represent standard deviation of three measurement results. \n\nSupplementary Figs 6,7,8), while $\\mathrm{LaCoO}_{3}$ without any lattice oxygen oxidation exhibited pH-independent OER kinetics. RHE was used as the reference electrode to ensure that the OER overpotential with respect to the equilibrium $\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}$ redox potential remained identical across different values of $\\mathrm{\\pH}$ (ref. 17). The pH dependence of OER activity on the RHE scale indicates the presence of non-concerted proton–electron transfer steps during the OER, where the rate-limiting step is either a proton transfer step or preceded by acid/base equilibrium14,17. OER currents from CV measurements were found to increase with increasing $\\mathrm{pH}$ for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ , but remained unchanged for $\\mathrm{LaCoO}_{3}$ , as shown in Fig. 3a. The intrinsic OER activities of $\\mathrm{LaCoO}_{3}$ , $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ , as estimated by either the surface-area-normalized current at $1.55\\mathrm{V}$ versus RHE (Fig. 3b) or the OER potential at $0.2\\ \\mathrm{mA}\\ \\mathrm{cm}_{\\mathrm{oxide}}^{-2}$ (Supplementary Fig. 6) from CV and galvanostatic measurements, are compared as a function of $\\mathsf{p H}$ . The specific OER activities of these oxides, with error bars, are presented in Supplementary Figs 7 and 8. Greater metal–oxygen covalency (Fig. 1) and lattice oxygen oxidation (Fig. 2) correlates with increasing OER activity, which is most evident at $\\mathrm{pH}14$ (Fig. 3b). Significantly, $\\mathrm{SrCoO}_{3-\\delta}$ was found to have OER activity approximately three times greater than that of $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ (ref. 19), one of the most active and stable oxides previously reported for the OER. \n\nBoth CV and galvanostatic measurements show that the intrinsic OER activity of $\\mathrm{LaCoO}_{3}$ is independent of $\\mathrm{\\pH}$ , while those for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ are pHdependent (increasing the pH from 12.5 to 14 led to greater intrinsic OER activities by one order of magnitude). Interestingly, the specific OER currents measured from CV can be consistently higher than those from galvanostatic measurements. This difference can be attributed to the contribution from oxygen intercalation following the oxidation of ${\\mathrm{Co}}^{3+}$ ions (as evidenced by the redox peak at ${\\sim}1.2\\mathrm{V}$ versus RHE in Supplementary Fig. 9) in oxygen-deficient perovskites37–39 to the OER current measured from CV (measured over minutes), which is negligible in galvanostatic measurements (with much lower rates, measured over hours). This argument is further supported by the fact that the difference in the OER activity between CV and galvanostatic measurements increases with increasing charge associated with oxygen vacancy filling of the oxides before OER (Fig. 3 and Supplementary Fig. 10). Therefore, galvanostatic measurements provide a more accurate measure of OER activity than CV. \n\nOER mechanisms with lattice oxygen oxidation. The conventional OER mechanism11,12 on surface metal sites (Fig. 4a and Supplementary Fig. 11) catalyses OER on the oxide surface, which cannot evolve more than ${\\sim}0.4~\\mathrm{nm}$ of $^{18}\\mathrm{O}$ during OER after $^{18}\\mathrm{O}$ -labelling. The observed $^{18}\\mathrm{O}$ released in the OER for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ can be attributed to oxide lattice participation greater than ${\\sim}0.4\\ \\mathrm{nm}$ , which cannot be explained by the traditional OER mechanism. In addition, this traditional mechanism with concerted proton–electron transfer cannot explain the pH-dependent OER activity on the above oxides. Therefore, mechanisms that are fundamentally different from the conventional scheme11,12 are needed to explain the involvement of lattice oxygen oxidation $\\binom{34}{\\phantom{^{34}\\mathrm{O}_{2}}}$ and/or $^{36}\\mathrm{O}_{2}\\qquad$ detected) in the OER for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , and $\\mathrm{SrCoO}_{3-\\delta},$ as well as their $\\mathrm{pH}$ -dependent OER kinetics. Conversely, given the absence of lattice oxygen oxidation and $\\mathrm{\\pH}$ -independent OER kinetics observed for $\\mathrm{LaCoO}_{3}$ , the OER kinetics on $\\mathrm{LaCoO}_{3}$ can be explained by the conventional concerted proton–electron transfer mechanism on surface cobalt sites (Fig. 4a)11,12. Considering the cobalt sites of the (001) $\\mathrm{CoO}_{2}$ surface, the computed free energies of concerted proton–electron transfer steps show that the $_{\\mathrm{O-O}}$ bond formation (step 2 in Fig. 4a) is rate-limiting for $\\mathrm{LaCoO}_{3}$ , in agreement with previous works11,44. Increasing metal–oxygen covalency from $\\mathrm{LaCoO}_{3}$ to $\\mathsf{S r C o O}_{3}$ was found to promote OER kinetics on the metal sites in this concerted mechanism (Fig. 4b), as indicated by the lowered potential needed for all steps becoming thermodynamically downhill. \n\n![](images/213c37e49f54a221311323f5f16672e33b618fbdaced1d430f4d4c378bc4a625.jpg) \nFigure 4 | OER mechanisms with concerted and non-concerted proton–electron transfer. a, Conventional OER mechanism involving concerted proton– electron transfers on surface metal sites12,58,59, with oxygen from the electrolyte in blue and from the oxide lattice in red. c,e, Possible OER mechanisms involving concerted proton–electron transfer on surface oxygen sites to yield $^{16}\\mathrm{O}^{18}\\mathrm{O}\\ (^{34}\\mathrm{O}_{2})$ and $^{18}\\mathrm{O}^{18}\\mathrm{O}$ $^{(36}\\mathsf{O}_{2})_{\\cdot}$ , respectively. b,d, Computed free energies (ΔG) of coupled proton–electron transfer OER steps on the metal $(\\pmb{\\ b})$ and oxygen $(\\pmb{\\mathsf{d}})$ sites of the (001) $M O_{2}$ surface to form $^{32}\\mathsf{O}_{2}$ , respectively, where all the steps are thermodynamically downhill. f, The computed $\\Delta G$ of (001) $M O_{2}$ shows that the formation of the $_{0-0}$ bond is energetically favourable for surface oxygen sites of $\\mathsf{S r C o O}_{3}$ but not for $\\mathsf{L a C o O}_{3}$ . g,h, Possible non-concerted proton–electron transfer OER mechanisms that evolve $^{34}\\mathsf{O}_{2}\\left(\\pmb{\\mathsf{g}}\\right)$ and $^{36}{\\mathsf O}_{2}({\\mathsf h})$ with pH-dependent OER activity, with electron-transfer steps in yellow, proton-transfer steps in green and charged intermediates accommodated by metal ion valence changes. \n\nWe next discuss reaction schemes involving the oxidation of lattice oxygen and concerted proton–electron transfers to explain the detection of $^{34}\\mathrm{O}_{2}$ and $^{36}\\mathrm{O}_{2}$ , which will be further modified to include decoupled proton–electron transfers to explain the observed pH-dependent OER activities. The formation of $^{34}\\mathrm{O}_{2}$ can be explained by charge transfer steps on surface oxygen sites. One likely mechanism is shown in Fig. 4c, though other possibilities may exist. The first three steps on surface oxygen sites are concerted proton–electron transfers analogous to those on metal sites in Fig. 4a; these are followed by a chemical step to produce molecular $^{34}\\mathrm{O}_{2}\\:(^{16}\\mathrm{O}^{18}\\mathrm{O})$ and an oxygen vacancy, and a subsequent concerted proton–electron transfer step to regenerate the O–M–OH surface. Increasing metal–oxygen covalency from $\\mathrm{LaCoO}_{3}$ to $\\mathsf{S r C o O}_{3}$ promotes OER activity for the surface oxygen sites, as is evident from the lower computed potential necessary for all reaction steps to become thermodynamically favourable (Fig. 4d). The computed thermodynamic OER potential on surface oxygen sites of $\\mathsf{S r C o O}_{3}$ is comparable to that on surface Co sites (Fig. 4b), suggesting that both can be active for OER. In contrast, surface Co sites (Fig. 4b) of $\\mathrm{LaCoO}_{3}$ are more active than surface oxygen sites, suggesting that surface Co sites govern the OER activity. Note that the ratelimiting step of OER on $\\mathrm{LaCoO}_{3}$ was found to be different from that for $\\mathrm{SrCoO}_{3}$ , where $_{\\mathrm{O-O}}$ bond formation on surface metal and oxygen sites (step 2 in Fig. $^{4\\mathrm{a},\\mathrm{c}}$ ) and $\\mathrm{OH^{-}}$ adsorption onto surface metal and oxygen sites (step 1 in Fig. $\\mathrm{4a,c}$ ) limits the OER kinetics of $\\mathrm{LaCoO}_{3}$ and $\\mathrm{SrCoO}_{3}$ , respectively (Fig. 4d). Increasing $_{\\mathrm{Co-O}}$ covalency from $\\mathrm{LaCoO}_{3}$ to $\\mathrm{SrCoO}_{3}$ is associated with moving the oxide Fermi level below the $\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}$ redox energy (Fig. 1b); the oxide surface becomes more negatively charged when equilibrated with the electrolyte and preferentially acts as a Brønsted base, making deprotonation by $\\mathrm{OH^{-}}$ more difficult for $\\mathrm{sr}$ -substituted $\\mathrm{LaCoO}_{3}$ (ref. 45). \n\n![](images/e31afe9fb0ca0dd144f1c81a5b2cf920286431b8e84b5796bf9e6e1522eccf79.jpg) \nFigure 5 | Electrochemical oxygen intercalation into brownmillerite $\\mathsf{S r C o o}_{3-\\delta}$ followed by the OER. Galvanostatic charging (iR-corrected) of $\\mathsf{S r C o O}_{3-\\delta}$ in $\\mathsf{O}_{2}$ -saturated (solid line) and $\\mathsf{A r}$ -saturated (dotted line) 1 M KOH as a function of charge passed at $7\\mathrm{mA}\\mathrm{g}_{\\mathrm{oxide}}^{-1}$ . The oxide loading was $0.25\\mathsf{m g_{o x i d e}c m_{d i s k}^{-2}}$ mixed with a carbon loading of $0.05\\mathsf{m g_{c a r b o n}c m_{d i s k}^{-2}}$ . Inset scheme: relationship between the measured voltage of oxygen intercalation at ${\\mathsf{p H}}14$ (unit activity for $\\mathsf{O H}^{-})$ and oxide band structure. \n\nThe formation of $^{36}\\mathrm{O}_{2}$ , most pronounced for $\\mathrm{SrCoO}_{3-\\delta}$ , requires the formation of an $^{18}\\mathrm{O}-^{18}\\mathrm{O}$ bond from two surface oxygen ions of the oxide. Although other possibilities may exist (Supplementary Fig. 12), a likely mechanism is shown in Fig. 4e. The mechanism consists of two chemical steps, which create an O–O bond, then a molecular oxygen from lattice oxygen sites via the formation of two oxygen vacancies (steps 2 and 3 in Fig. 4e). The remaining steps of the mechanism involve four concerted proton–electron transfers—two for regenerating the surface oxygen sites and two associated with deprotonating surface oxygen ions. DFT calculations show that the chemical step to form an $_{\\mathrm{O-O}}$ bond and an oxygen vacancy from surface oxygen ions of $\\mathsf{S r C o O}_{3}$ is thermodynamically favourable (Fig. 4f and Supplementary Fig. 13). On the other hand, the $_{\\mathrm{O-O}}$ bond formation from two surface oxygen ions of $\\mathrm{LaCoO}_{3}$ is energetically unfavourable (Fig. 4f ), which is consistent with previous findings that the energy penalty associated with oxygen vacancy formation increases with moving the Fermi level away from the O $2p$ -band centre20 (Supplementary Fig. 14) and the absence of lattice oxygen oxidation on $\\mathrm{LaCoO}_{3}$ . \n\nThe $\\mathrm{\\pH}$ -dependent OER activities on the RHE scale observed for $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ require the decoupling of some proton transfers from electron transfers in the reaction schemes in Fig. 4c,e. Two likely reaction schemes are proposed in Fig. $^{4\\mathrm{g},\\mathrm{h}}$ . It is postulated here that the rate-limiting step in the concerted mechanism (Fig. 4c,e)—deprotonation of hydroxyl groups $\\mathrm{O-M}^{n+}-\\mathbf{O}\\mathbf{H}+\\mathrm{O}\\mathbf{\\bar{H}}^{-}\\to\\mathrm{O-M}^{(n-1)+}-\\mathbf{O}+\\mathrm{H}_{2}\\mathbf{O}$ (highlighted in green)—has become non-concerted and decoupled from subsequent electron transfer during the evolution of molecular oxygen, $\\bar{\\mathrm{{O-M}}}^{(n-1)+}{\\bf-O}{\\bf O}\\to\\mathrm{O-M}^{n+}{\\bf-}\\breve{\\bigsqcup}+{\\bf O}_{2}+\\mathrm{e}^{-}$ (highlighted in yellow). Nevertheless, we emphasize that decoupling of proton and electron transfers can also occur in other reaction steps in these OER mechanisms, and, ultimately, the $\\mathsf{p}K_{\\mathrm{a}}$ of such surface deprotonation determines the step that is responsible for the overall pH-dependent kinetics14,46. \n\nThe proposed rate-limiting step for the OER kinetics of oxides with strong covalency, that is, the deprotonation of surface hydroxyl groups, is supported by the remarkably different kinetics of galvanostatic oxidation of brownmillerite $\\mathrm{SrCoO}_{3-\\delta}$ $(\\mathrm{SrCoO}_{3-\\delta}+2\\delta\\mathrm{OH}^{-}\\rightarrow$ $\\mathrm{SrCoO}_{3}+\\delta\\mathrm{H}_{2}\\mathrm{O}+2\\delta\\mathrm{e}^{-})$ in Ar-saturated and $\\mathrm{O}_{2}$ -saturated $^{1\\mathrm{{M}}}$ KOH, as shown in Fig. 5. Galvanostatic oxidation of brownmillerite $\\mathrm{SrCoO}_{3-\\delta}$ in $\\mathrm{O}_{2}$ -saturated 1 M KOH led to the well-known plateau47 of oxygen intercalation, whereas oxidation with Ar saturation exhibited no clear plateau of oxygen intercalation. Oxygen vacancy filling into $\\mathrm{SrCoO}_{3-\\delta}$ is driven by the energy difference between the $\\mathrm{H}_{2}\\mathrm{O}/$ $\\mathrm{H}_{2}$ redox couple and the $\\mathrm{Co}\\ 3d$ states at the Fermi level of oxides (Fig. 5, inset), which should not be influenced by Ar or $\\mathrm{O}_{2}$ saturation in the electrolyte. The kinetics of the oxygen filling of $\\mathrm{SrCoO}_{3-\\delta}$ oxygen vacancies in Ar-saturated electrolyte can be attributed to the slow deprotonation kinetics of surface hydroxyl groups, which is needed to intercalate oxygen ions into the oxide lattice. As our DFT calculations show that filling vacancies with ${{\\mathrm{O^{*}}}}$ is more favourable than filling with ${\\mathrm{OH}}^{*}$ on the Co-terminated (001) surface of brownmillerite $(-0.82\\mathrm{eV}$ per ${{\\cal O}^{*}}$ and $-0.40\\ \\mathrm{eV}$ per $\\mathrm{OH^{*}})$ at $1.23{\\mathrm{V}}$ versus RHE (Supplementary Fig. 15), surface oxygen vacancies in the $\\mathrm{O}_{2}$ -saturated electrolyte are filled preferentially by $\\mathrm{O}_{2}$ rather than by $\\mathrm{OH^{-}}$ . The filling of surface vacancies with ${{\\mathrm{O}}^{*}}$ rather than $\\mathrm{OH^{*}}$ allows the oxygen intercalation to proceed through an ${\\bf O-M-O O H}$ intermediate rather than O–M– OH (step 3 instead of step 1 in Fig. $^{4\\mathrm{b},\\mathrm{d})}$ ), rendering the faster kinetics observed in the $\\mathrm{O}_{2}$ -saturated electrolyte. Further support for the deprotonation being decoupled from electron transfer comes from the observation that the oxygen intercalation kinetics become more sluggish in the $\\mathrm{O}_{2}$ -saturated electrolyte when decreasing the $\\mathrm{\\pH}$ from 14 to 13 (Supplementary Fig. 16). \n\nThe proposed OER mechanisms in Fig. 4g,h used to explain lattice oxygen oxidation and the pH-dependent OER kinetics of highly covalent oxides bridge between the conventional OER mechanism11,12,14,15 of metal oxides and those reported for electrodeposited oxide $\\mathrm{\\flms^{17,28,48}}$ . Oxygen exchange is shown to participate in the OER of ${\\mathrm{Co-Pi}}$ films electrodeposited in ${\\bf\\dot{C}}{\\bf0}^{2+}$ -phosphate-containing electrolytes under neutral conditions via $^{18}\\mathrm{O}$ -isotopic labelling28,48, while no pH-dependence of OER kinetics on the RHE scale is noted17,28, where proton-acceptor phosphate species governs the kinetics of surface deprotonation28 to enable high OER activity. Recent mechanistic studies of these catalysts move beyond charge transfer steps on metal sites and propose the involvement of oxygen redox chemistry mediated by oxygen holes (that is, ${\\mathrm{Co}}^{4+}$ described as ${\\mathrm{Co}}^{3+}$ and a hole in the O states30 promotes O–O bond formation) in OER kinetics, similar to the mechanisms proposed here28,30,48. Further support for the synergy in the OER mechanisms comes from the pH-dependent OER kinetics on the RHE scale in basic solution reported for electrodeposited (Ni,Fe) OOH film18, which has been attributed to deprotonation leading to the formation of a negatively charged oxygenated intermediate (‘active oxygen’) participating in the OER, as suggested by surface-enhanced Raman spectroscopy18. Further studies are required to understand the role of non-concerted proton–electron transfer steps on the OER kinetics of electrodeposited oxide films and highly covalent oxides and the nature of surface oxygen participating in O–O bond formation (for example, terminal oxygen, as proposed for electrodeposited films28,30,48, versus bridging oxygen, for covalent oxides in this study). \n\nIn summary, by combining electrochemical characterization with DFT studies, we have demonstrated that the bulk electronic structure of transition-metal oxides, namely the metal–oxygen covalency, not only governs the OER activity but also the reaction mechanism. Specifically, we have shown that lattice oxygen can be activated for the OER and promote new reaction pathways, in addition to the classically studied mechanism on surface metal sites. The OER on oxygen sites can be triggered when the Fermi level becomes pinned to the top of the O $2p$ band for highly covalent oxides, resulting in electronic states near the Fermi level with substantial O $2p$ character. Moreover, OER activities on the RHE scale for perovskites with strong metal–oxygen covalency become higher with increasing $\\mathrm{\\pH_{\\mathrm{\\cdot}}}$ indicating that non-concerted proton– electron transfer steps are coupled to the activation of lattice oxygen redox reactions. These new insights open new possibilities for developing highly active catalysts using lattice oxygen redox processes and non-concerted proton–electron transfer steps, bypassing the design limitations of engineering catalysts under the conventional mechanism, which involves only concerted proton–electron transfer steps on surface metal ion sites. \n\ndetermined using Brunauer, Emmet and Teller (BET) analysis on a Quantachrome ChemBET Pulsar from single-point BET analysis performed after $12\\mathrm{{h}}$ outgassing at $150^{\\circ}\\mathrm{C}$ (Supplementary Table 2). More details are provided in the Supplementary Information. \n\nElectrochemical measurements of OER activities. Electrodes used for CV and galvanostatic measurements were prepared by drop-casting ink containing oxide catalyst powder on a glassy carbon electrode (GCE), as described previously49. The glassy carbon electrode surface $5\\mathrm{mm}$ diameter) was loaded with $0.25\\mathrm{~mg}_{\\mathrm{oxide}}\\mathrm{cm}_{\\mathrm{disk}}^{-2}$ and a mass ratio of 5:1:1 of oxide catalyst:acetylene black carbon: Nafion. We used an oxide:carbon mass ratio of 5:1 for the OER measurements, as the specific OER activity estimated for oxide particles from such measurements agrees well with that measured from well-defined epitaxial oxide thin-film surfaces of comparable oxide chemistry48. Electrochemical measurements were performed with a rotating disk electrode set-up using a glass electrochemical cell with $\\mathrm{Ag/AgCl}$ reference electrode and Pt counter electrode. The potential was controlled using a Biologic VSP-300 potentiostat. Ohmic losses were corrected by subtracting the ohmic voltage drop from the measured potential, using the electrolyte resistance determined by high-frequency a.c. impedance, where $i R$ -corrected potentials are denoted as $E-i R$ (i as the current and $R$ as the electrolyte resistance). Rotating ring disk electrode (RRDE) measurements were performed on a GCE disk and a Pt ring held at $0.4\\mathrm{V}$ versus RHE. RRDE measurements of $\\mathrm{SrCoO}_{3-\\delta}$ in Ar-saturated 1 M KOH (Supplementary Fig. 17) revealed that oxygen was detected only at potentials higher than ${\\sim}1.5\\mathrm{V}$ versus RHE and thus the currents measured at lower potentials are not related to OER but rather to oxygen intercalation upon oxidation of $\\mathrm{SrCoO}_{3-\\delta}$ (that is, filling of oxygen vacancies in the oxide). More details are provided in the Supplementary Information. \n\nOnline electrochemical mass spectroscopy. OLEMS experiments50 were performed using an EvoLution mass spectrometer system (European Spectrometry Systems). Volatile reaction products were collected from the electrode interface by a small inlet tip positioned close $(\\sim10~\\upmu\\mathrm{m})$ to the electrode surface using a micrometric screw system and a camera. More details are provided in the Supplementary Information. The electrochemical cell used for these experiments is a two-compartment cell with three electrodes, with a gold wire as counter electrode and a reversible hydrogen electrode as the reference electrode. The working electrode was prepared in a comparable manner to that used for OER activity measurements but on a gold disk electrode ( $4.6\\ \\mathrm{mm}$ diameter) and with an oxide loading of $0.25\\mathrm{mg_{oxide}}\\mathrm{cm}_{\\mathrm{disk}}^{-2}$ with no carbon. We used oxide-only electrodes on Au in the OLEMS measurements to avoid any corrosion currents associated with carbon such as oxidization of carbon to form CO and $\\mathrm{CO}_{2}$ , as shown previously51,52. The OER activities measured for OLEMS measurements without iR correction were in good agreement with those from RDE measurements with $i R$ correction (Supplementary Fig. 2). Moreover, the gold electrode was shown to have no OER activity within the potential range used for the OLEMS measurements (Supplementary Fig. 18). Pristine electrodes were oxidized for $10\\mathrm{min}$ in 0.1 M KOH made with $^{\\mathrm{{\\small~\\cdot~}}_{18}}\\mathrm{{O}}$ -labelled water (GMP standard from CMR, $98\\%^{18}\\mathrm{O})$ at $1.6\\mathrm{V}$ versus gold counter electrode (no gas bubbling), to label them with $^{18}\\mathrm{O}$ ( $^{18}\\mathrm{O}$ labelling currents are provided in Supplementary Fig. 19). Electrodes were then rinsed with $^{16}\\mathrm{O}$ water to remove $\\mathrm{H}_{2}^{\\ 18}\\mathrm{O}$ and measured in $0.1\\mathrm{~M~}$ KOH solution of $\\mathrm{H}_{2}^{16}\\mathrm{O}$ at $2\\mathrm{mVs}^{-1}$ for two cycles (no gas bubbling). Because samples were rinsed with $^{16}\\mathrm{O}$ water after $^{18}\\mathrm{O}$ -labelling, it is unlikely that $^{18}\\mathrm{O}$ species (for example, ${\\mathrm{OH^{*}}}$ or $\\mathrm{H}_{2}\\mathrm{O})$ ) adsorbed on the oxide surface contributed substantially to the observed $^{16}\\mathrm{O}^{18}\\mathrm{O}$ or $^{18}\\mathrm{O}^{18}\\mathrm{O}$ signal, especially for oxides with a high Co oxidation state. $\\mathrm{Ba}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{Co}_{0.8}\\mathrm{Fe}_{0.2}\\mathrm{O}_{3-\\delta}$ , which transforms amorphous cobalt–ironcontaining oxyhydroxides in bulk during $\\mathrm{OER}^{36,37}$ , had markedly different OLEMS data (Supplementary Fig. 1) from $\\mathrm{LaCoO}_{3}$ , $\\mathrm{La}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{CoO}_{3-\\delta}$ , $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ and $\\mathrm{SrCoO}_{3-\\delta}$ particles, which remained stable upon OER19,40. $\\mathrm{Ba}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{Co}_{0.8}\\mathrm{Fe}_{0.2}\\mathrm{O}_{3-\\delta}$ had monotonically increasing lattice oxygen $\\mathrm{\\dot{(}^{18}O^{18}O)}$ signals in the positive-going and negative-going scans, confirming bulk oxide decomposition. Moreover, the tip in the open OLEMS set-up used in this study detects $^{32}\\mathrm{\\dot{O}}_{2}$ not only from OER but also from the atmosphere. This contribution from the atmosphere in the $^{32}\\mathrm{O}_{2}$ detected is evident from Supplementary Table 3, where the amount of $^{32}\\mathrm{O}_{2}$ is nearly identical for all four oxides studied. We therefore chose not to include $^{32}\\mathrm{O}_{2}$ data in Fig. 2. Each oxide was examined by OLEMS measurements of two to four different electrodes, and the results of different electrodes were comparable, generating error bars for OLEMS data analysis such as the $^{18}\\mathrm{O}/^{16}\\mathrm{O}$ ratio in Supplementary Figs 4 and 5 and Supplementary Table 3. Multiple OLEMS measurements of $\\mathrm{SrCoO}_{3-\\delta}$ (Supplementary Fig. 20) and $\\mathrm{Ba_{0.5}S r_{0.5}C o_{0.8}F e_{0.2}O_{3-\\delta}}$ (Supplementary Fig. 3) are provided in the Supplementary Information as examples. \n\n# Methods \n\nSynthesis and bulk characterization. Perovskite $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ ( $x=0$ , 0.5 and 1) and $\\mathrm{Pr}_{0.5}\\mathrm{Ba}_{0.5}\\mathrm{CoO}_{3-\\delta}$ were synthesized by a conventional solid-state route15,19. All catalysts reported in this study are single-phase, as analysed by X-ray diffraction (XRD), with lattice parameters consistent with those reported previously (Supplementary Table 1). XRD measurements were performed using a PANalytical X’Pert Pro powder diffractometer in the Bragg-Brentano geometry using copper $\\mathrm{K}_{\\upalpha}$ radiation, and data were collected using the X’Celerator detector in the $8\\mathrm{-}80^{\\circ}$ window in the 2θ range. The specific surface area of each oxide sample was \n\nDFT studies. DFT calculations with Hubbard U $\\cdot U_{\\mathrm{eff}}=3.3\\ \\mathrm{eV},$ ) correction20,53 for the Co 3d electrons were performed with the Vienna $\\mathbf{\\nabla}_{A b}$ -initio Simulation Package $(\\mathrm{VASP})^{54,55}$ using the projector-augmented plane-wave method56. Exchangecorrelation was treated in the Perdew-Wang-91 generalized gradient approximation $(\\mathrm{GGA})^{57}$ . Fully relaxed stoichiometric bulk perovskite calculations were simulated with $2\\times2\\times2$ perovskite supercells. The double perovskites were simulated based on the reported ordered structures within the $2\\times2\\times2$ perovskite supercell. Both O $2p$ -band and metal $_{3d.}$ -band centres were determined by taking the weighted mean energy of the projected density of states of O 2p and metal $3d$ states (both occupied and unoccupied states) relative to the Fermi level. We used a symmetric slab cut along the (001) direction as a model for the (001) $\\mathrm{MO}_{2}$ terminated surface and $(2\\times2)$ surface supercells. The thermodynamic approaches for calculating the OER free energy profiles are described in ref. 44. For more details see Supplementary Information. \n\nData availability. The original data for Figs 1– 5 in this manuscript are available from https://figshare.com/s/286742731dfc47a8f1c1. Other data sets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. \n\n# Received 3 August 2016; accepted 14 November 2016; published online 9 January 2017 \n\n# References \n\n1. Grimaud, A., Hong, W. T., Shao-Horn, Y. & Tarascon, J. M. Anionic redox processes for electrochemical devices. Nat. Mater. 15, 121–126 (2016). \n2. Lewis, N. S. & Nocera, D. G. Powering the planet: chemical challenges in solar energy utilization. Proc. Natl Acad. Sci. USA 103, 15729–15735 (2006). \n3. Gray, H. B. Powering the planet with solar fuel. Nat. Chem. 1, 7 (2009). \n4. Seger, B. et al. 2-Photon tandem device for water splitting: comparing photocathode first versus photoanode first designs. Energy Environ. Sci. 7, \n2397–2413 (2014). \n5. Hansen, O., Seger, B., Vesborg, P. C. K. & Chorkendorff, I. A quick look at how photoelectrodes work. Science 350, 1030–1031 (2015). \n6. Castelli, I. E. et al. New cubic perovskites for one- and two-photon water splitting using the computational materials repository. Energy Environ. Sci. \n5, 9034–9043 (2012). \n7. Risch, M. et al. $\\mathrm{La}_{0.8}\\mathrm{Sr}_{0.2}\\mathrm{MnO}_{3-\\delta}$ decorated with $\\mathrm{Ba_{0.5}S r_{0.5}C o_{0.8}F e_{0.2}O_{3-\\delta}}$ : a bifunctional surface for oxygen electrocatalysis with enhanced stability and activity. J. Am. Chem. Soc. 136, 5229–5232 (2014). \n8. Jung, J.-I. et al. Optimizing nanoparticle perovskite for bifunctional oxygen electrocatalysis. Energy Environ. Sci. 9, 176–183 (2016). \n9. McCalla, E. et al. Visualization of O–O peroxo-like dimers in high-capacity layered oxides for Li-ion batteries. Science 350, 1516–1521 (2015). \n10. Sathiya, M. et al. Reversible anionic redox chemistry in high-capacity layered-oxide electrodes. Nat. Mater. 12, 827–835 (2013). \n11. Man, I. C. et al. Universality in oxygen evolution electrocatalysis on oxide surfaces. Chem. Catal. Chem. 3, 1159–1165 (2011). \n12. Rossmeisl, J., Qu, Z. W., Zhu, H., Kroes, G. J. & Nørskov, J. K. Electrolysis of water on oxide surfaces. J. Electroanal. Chem. 607, 83–89 (2007). \n13. Nørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n14. Koper, M. T. M. Theory of multiple proton–electron transfer reactions and its implications for electrocatalysis. Chem. Sci. 4, 2710–2723 (2013). \n15. Suntivich, J., May, K. J., Gasteiger, H. A., Goodenough, J. B. & Shao-Horn, Y. A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles. Science 334, 1383–1385 (2011). \n16. Matsumoto, Y., Manabe, H. & Sato, E. Oxygen evolution on $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3}$ electrodes in alkaline solutions. J. Electrochem. Soc. 127, 811–814 (1980). \n17. Giordano, L. et al. pH dependence of OER activity of oxides: current and future perspectives. Catal. Today 262, 2–10 (2016). \n18. Trześniewski, B. J. et al. In situ observation of active oxygen species in Fe-containing Ni-based oxygen evolution catalysts: the effect of pH on electrochemical activity. J. Am. Chem. Soc. 137, 15112–15121 (2015). \n19. Grimaud, A. et al. Double perovskites as a family of highly active catalysts for oxygen evolution in alkaline solution. Nat. Commun. 4, 2439 (2013). \n20. Lee, Y.-L., Kleis, J., Rossmeisl, J., Shao-Horn, Y. & Morgan, D. Prediction of solid oxide fuel cell cathode activity with first-principles descriptors. Energy Environ. Sci. 4, 3966–3970 (2011). \n21. Suntivich, J. et al. Estimating hybridization of transition metal and oxygen states in perovskites from O K-edge X-ray absorption spectroscopy. J. Phys. Chem. C \n118, 1856–1863 (2014). \n22. Calle-Vallejo, F., Díaz-Morales, O. A., Kolb, M. J. & Koper, M. T. M. Why is bulk thermochemistry a good descriptor for the electrocatalytic activity of transition metal oxides? ACS Catal. 5, 869–873 (2015). \n23. Rong, X., Parolin, J. & Kolpak, A. M. A fundamental relationship between reaction mechanism and stability in metal oxide catalysts for oxygen evolution. ACS Catal. 6, 1153–1158 (2016). \n24. Hibbert, D. B. & Churchill, C. R. Kinetics of the electrochemical evolution of isotopically enriched gases. Part $2.-\\ ^{18}\\mathrm{O}^{16}\\mathrm{O}$ evolution on $\\mathrm{NiCo}_{2}\\mathrm{O}_{4}$ and $\\mathrm{Li}_{\\mathrm{x}}\\mathrm{Co}_{3-x}\\mathrm{O}_{4}$ in alkaline solution. J. Chem. Soc. Faraday Trans. I 80, \n1965–1975 (1984). \n25. Fierro, S., Nagel, T., Baltruschat, H. & Comninellis, C. Investigation of the oxygen evolution reaction on $\\mathrm{Ti}/\\mathrm{IrO}_{2}$ electrodes using isotope labelling and on-line mass spectrometry. Electrochem. Commun. 9, 1969–1974 (2007). \n26. Macounova, K., Makarova, M. & Krtil, P. Oxygen evolution on nanocrystalline $\\mathrm{RuO}_{2}$ and $\\mathrm{Ru}_{0.9}\\mathrm{Ni}_{0.1}\\mathrm{O}_{2-\\delta}$ electrodes—DEMS approach to reaction mechanism determination. Electrochem. Commun. 11, 1865–1868 (2009). \n27. Wohlfahrt-Mehrens, M. & Heitbaum, J. Oxygen evolution on Ru and $\\mathrm{RuO}_{2}$ electrodes studied using isotope labelling and on-line mass spectrometry. J. Electroanal. Chem. Interf. Electrochem. 237, 251–260 (1987). \n28. Surendranath, Y., Kanan, M. W. & Nocera, D. G. Mechanistic studies of the oxygen evolution reaction by a cobalt-phosphate catalyst at neutral pH. J. Am. Chem. Soc. 132, 16501–16509 (2010). \n29. Mavros, M. G. et al. What can density functional theory tell us about artificial catalytic water splitting? Inorg. Chem. 53, 6386–6397 (2014). \n30. Wang, L.-P. & Van Voorhis, T. Direct-coupling $\\mathrm{O}_{2}$ bond forming a pathway in cobalt oxide water oxidation catalysts. J. Phys. Chem. Lett. 2, 2200–2204 (2011). \n31. Betley, T. A., Wu, Q., Van Voorhis, T. & Nocera, D. G. Electronic design criteria for O−O bond formation via metal−oxo complexes. Inorg. Chem. 47, 1849–1861 (2008). \n32. Cheng, X. et al. Oxygen evolution reaction on $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3}$ perovskites: a combined experimental and theoretical study of their structural, electronic, and electrochemical properties. Chem. Mater. 27, 7662–7672 (2015). \n33. Goodenough, J. B. Perspective on engineering transition-metal oxides. Chem. Mater. 26, 820–829 (2014). \n34. Rouxel, J. Anion–cation redox competition and the formation of new compounds in highly covalent systems. Chem. Eur. J. 2, 1053–1059 (1996). \n35. Nücker, N., Fink, J., Fuggle, J. C., Durham, P. J. & Temmerman, W. M. Evidence for holes on oxygen sites in the high- $T_{\\mathrm{c}}$ superconductors $\\mathrm{La}_{2-x}\\mathrm{Sr}_{x}\\mathrm{CuO}_{4}$ and $\\mathrm{YBa}_{2}\\mathrm{Cu}_{3}\\mathrm{O}_{7-y}$ . Phys. Rev. B 37, 5158–5163 (1988). \n36. Amatucci, G. G., Tarascon, J. M. & Klein, L. C. $\\mathrm{CoO}_{2}$ , the end member of the ${\\mathrm{LixCoO}}_{2}$ solid solution. J. Electrochem. Soc. 143, 1114–1123 (1996). \n37. Mefford, J. T., Hardin, W. G., Dai, S., Johnston, K. P. & Stevenson, K. J. Anion charge storage through oxygen intercalation in $\\mathrm{LaMnO}_{3}$ perovskite pseudocapacitor electrodes. Nat. Mater. 13, 726–732 (2014). \n38. Nemudry, A., Goldberg, E. L., Aguirre, M. & Alario-Franco, M. A. Electrochemical topotactic oxidation of nonstoichiometric perovskites at ambient temperature. Solid State Sci. 4, 677–690 (2002). \n39. Grenier, J. C. et al. Electrochemical oxygen intercalation into oxide networks. J. Solid State Chem. 96, 20–30 (1992). \n40. May, K. J. et al. Influence of oxygen evolution during water oxidation on the surface of perovskite oxide catalysts. J. Phys. Chem. Lett 3, 3264–3270 (2012). \n41. Risch, M. et al. Structural changes of cobalt-based perovskites upon water oxidation investigated by EXAFS. J. Phys. Chem. C 117, 8628–8635 (2013). \n42. Binninger, T. et al. Thermodynamic explanation of the universal correlation between oxygen evolution activity and corrosion of oxide catalysts. Sci. Rep. 5, 12167 (2015). \n43. Kim, J., Yin, X., Tsao, K.-C., Fang, S. & Yang, H. $\\mathrm{Ca}_{2}\\mathrm{Mn}_{2}\\mathrm{O}_{5}$ as oxygen-deficient perovskite ellectrocatalyst for oxygen evolution reaction. J. Am. Chem. Soc. 136, 14646–14649 (2014). \n44. Lee, Y.-L., Gadre, M. J., Shao-Horn, Y. & Morgan, D. Ab initio $\\mathrm{GGA+U}$ study of oxygen evolution and oxygen reduction electrocatalysis on the (001) surfaces of lanthanum transition metal perovskites $\\mathrm{LaBO}_{3}$ ( $\\scriptstyle\\mathrm{B=Cr}$ , Mn, Fe, Co and Ni). Phys. Chem. Chem. Phys. 17, 21643–21663 (2015). \n45. Bockris, J. O. M. & Otagawa, T. The electrocatalysis of oxygen evolution on perovskites. J. Electrochem. Soc. 131, 290–302 (1984). \n46. Koper, M. M. Volcano activity relationships for proton-coupled electron transfer reactions in electrocatalysis. Top. Catal. 58, 1153–1158 (2015). \n47. Nemudry, A., Rudolf, P. & Schöllhorn, R. Topotactic electrochemical redox reactions of the defect perovskite $\\mathrm{SrCoO}_{2.5+x}.$ Chem. Mater. 8, 2232–2238 (1996). \n48. Koroidov, S., Anderlund, M. F., Styring, S., Thapper, A. & Messinger, J. First turnover analysis of water-oxidation catalyzed by Co-oxide nanoparticles. Energy Environ. Sci. 8, 2492–2503 (2015). \n49. Suntivich, J., Gasteiger, H. A., Yabuuchi, N. & Shao-Horn, Y. Electrocatalytic measurement methodology of oxide catalysts using a thin-film rotating disk electrode. J. Electrochem. Soc. 157, B1263–B1268 (2010). \n50. Wonders, A. H., Housmans, T. H. M., Rosca, V. & Koper, M. T. M. On-line mass spectrometry system for measurements at single-crystal electrodes in hanging meniscus configuration. J. Appl. Electrochem. 36, 1215–1221 (2006). \n51. Meyers, J. P. & Darling, R. M. Model of carbon corrosion in PEM fuel cells. J. Electrochem. Soc. 153, A1432–A1442 (2006). \n52. He, M., Fic, K., Frckowiak, E., Novak, P. & Berg, E. J. Ageing phenomena in high-voltage aqueous supercapacitors investigated by in situ gas analysis. Energy Environ. Sci. 9, 623–633 (2016). \n53. Lee, Y.-L., Kleis, J., Rossmeisl, J. & Morgan, D. Ab initio energetics of $\\mathrm{LaBO}_{3}(001)$ ${\\mathrm{(B}}{=}{\\mathrm{Mn}},$ Fe, Co, and Ni) for solid oxide fuel cell cathodes. Phys. Rev. B 80, 224101 (2009). \n54. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n55. Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993). \n56. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n57. Perdew, J. P. & Wang, Y. Accurate and simple analytic representation of the electron-gas correlation energy. Phys. Rev. B 45, 13244–13249 (1992). \n58. Rossmeisl, J., Logadottir, A. & Nørskov, J. K. Electrolysis of water on (oxidized) metal surfaces. Chem. Phys. 319, 178–184 (2005). \n59. Goodenough, J. B., Manoharan, R. & Paranthaman, M. Surface protonation and electrochemical activity of oxides in aqueous solution. J. Am. Chem. Soc. 112, 2076–2082 (1990). \n\n# Acknowledgements \n\nThis work was supported in part by the Skoltech-MIT Center for Electrochemical Energy, the SMART programme, and the Department of Energy (DOE) and National Energy Technology Laboratory (NETL), Solid State Energy Conversion Alliance (SECA) Core Technology Program (Funding Opportunity Number DEFE0009435). This work is also supported in part by the Netherlands Organization for Scientific Research (NWO) within the research programme of BioSolar Cells, co-financed by the Dutch Ministry of Economic Affairs, Agriculture and Innovation. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the US Department of Energy (contract no. DE-AC02-05CH11231). \n\nThe authors would like to acknowledge Dane Morgan and Jean-Marie Tarascon for fruitful discussion. \n\n# Author contributions \n\nY.S.-H. and A.G. designed the experiments. A.G. and W.T.H. carried out the synthesis, structural and chemical analysis. A.G. and B.H. performed the electrochemical measurements. O.D.-M. and M.T.M.K. conducted the OLEMS measurements. Y.-L.L and L.G. carried out the DFT calculations. Y.S.-H. wrote the manuscript and all authors edited the manuscript. \n\n# Additional information \n\nSupplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to Y.S.H. \n\n# Competing financial interests \n\nThe authors declare no competing financial interests. " + }, + { + "id": "10.1002_adma.201605148", + "DOI": "10.1002/adma.201605148", + "DOI Link": "http://dx.doi.org/10.1002/adma.201605148", + "Relative Dir Path": "mds/10.1002_adma.201605148", + "Article Title": "Alkali-Assisted Synthesis of Nitrogen Deficient Graphitic Carbon Nitride with Tunable Band Structures for Efficient Visible-Light-Driven Hydrogen Evolution", + "Authors": "Yu, HJ; Shi, R; Zhao, YX; Bian, T; Zhao, YF; Zhou, C; Waterhouse, GIN; Wu, LZ; Tung, CH; Zhang, TR", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "A facile synthetic strategy for nitrogen-deficient graphitic carbon nitride (g-C3Nx) is established, involving a simple alkali-assisted thermal polymerization of urea, melamine, or thiourea. In situ introduced nitrogen vacancies significantly red-shift the absorption edge of g-C3Nx, with the defect concentration depending on the alkali to nitrogen precursor ratio. The g-C3Nx products show superior visible-light photocatalytic performance compared to pristine g-C3N4.", + "Times Cited, WoS Core": 1900, + "Times Cited, All Databases": 1950, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000400024500015", + "Markdown": "# Alkali-Assisted Synthesis of Nitrogen Deficient Graphitic Carbon Nitride with Tunable Band Structures for Efficient Visible-Light-Driven Hydrogen Evolution \n\nHuijun Yu, Run Shi, Yunxuan Zhao, Tong Bian, Yufei Zhao, Chao Zhou, Geoffrey I. N. Waterhouse, Li-Zhu Wu, Chen-Ho Tung, and Tierui Zhang\\* \n\nGraphitic carbon nitride $(\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4})$ has recently attracted widespread attention owing to its excellent photocatalytic activity for $\\mathrm{H}_{2}$ production,[1] water oxidation,[2] organic pollutant degradation,[3] artificial photosynthesis,[4] and $\\mathrm{CO}_{2}$ reduction.[5] The facile synthesis by thermal polymerization of urea, melamine, dicyanamide, or thiourea, together with its high thermal, chemical, and photostability, are further desirable attributes.[1a] However, pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ has a limited visible-light absorption range and also suffers from a high recombination rate of photo­ excited charge carriers, resulting in low photocatalytic activity. Various strategies have been developed to overcome these problems, such as doping with heteroatoms (e.g., C,[6] B,[7] O,[8] S,[9] P,[10] $\\mathrm{Br},^{[11]}$ I,[12] V,[13] and $\\mathrm{Fe^{[14]}}$ ), nanostructuring[2e,15] or crystal$\\mathrm{lizing^{[16]}}$ the $\\mathrm{g-C}_{3}\\mathrm{N}_{4}.$ , sensitization with dyes,[17] delamination to a few layers thickness,[18] and coupling with other semiconductors[19] or conductors.[20] The introduction of nitrogen defects into the $\\mathrm{g-C_{3}N_{4}}$ framework was recently shown to significantly enhance the photocatalytic activity of $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ under visible excitation on account of the narrower band gaps obtained.[21] Approaches used to date for the synthesis of nitrogen defective $\\mathtt{g}\\mathrm{-C}_{3}\\mathrm{N}_{x}$ include thermal polymerization at high temperature,[21a] hydrothermal routes,[21b] and hydrogen reduction.[21c] Each of these approaches has inherent limitations and affords limited control over the type and abundance of nitrogen defect that they can introduce. Therefore, it is desirable to discover a facile approach for introducing nitrogen defects into $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ during its synthesis, thereby allowing a systematic and tunable redshift in the $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ absorption edge and thus an enhanced visiblelight photocatalytic response. \n\nIn this work, we describe a novel one step KOH-assisted route to prepare nitrogen defective $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x},$ wherein two types of nitrogen defects were selectively introduced in situ during the thermal polymerization of urea or other nitrogen-rich precursors (such as melamine and thiourea). The introduction of nitrogen defects redshifted the $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ absorption edge, with the size of the shift being dependent on the amount of nitrogen defects which can be easily tuned by the KOH:urea ratio. Furthermore, similar results can also be achieved using other alkali compounds (such as NaOH and $\\mathrm{Ba}(\\mathrm{OH})_{2})$ , highlighting the versatility of the method. Due to enhanced visible-light absorption and improved charge carrier separation, the $\\mathtt{g}\\mathrm{-C}_{3}\\mathrm{N}_{x}$ products displayed superior photocatalytic hydrogen performance compared to pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ under visible light. The synthetic strategy introduced here thus represents a simple and effective way of synergistically optimizing the chemical composition, optical response, and photocatalytic properties of $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ -based materials. \n\nThe chemical structure of pristine $\\mathrm{g-C_{3}N_{4}}$ and a series of ${\\tt g}–{\\sf C}_{3}\\mathrm{N}_{x}–M$ powders ( $M$ represents the KOH amount $\\mathbf{\\tau}(\\mathbf{g})$ , ranging from 0.005 to 1.0) were first characterized by X-ray diffraction (XRD) patterns and Fourier transform infrared (FTIR) spectroscopy. As shown in Figure 1A,B, the XRD patterns and FTIR spectra of $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ were very similar to that of pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ confirming that the general structure of $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ was preserved with KOH addition. The XRD pattern for pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ (Figure 1A, top line) showed two characteristic peaks at $13.0^{\\circ}$ and $27.4^{\\circ}$ , which can be assigned to the (100) and (002) crystal planes of $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ , representing in-plane packing and interfacial stacking of $\\mathrm{g-C_{3}N_{4}}$ sheets, respectively.[22] It is obvious that the lateral peak shifts to higher $2\\theta$ angles with increasing KOH usage, indicating a progressively smaller stacking distance between nanosheets. In addition, both peaks broadened and gradually weakened with KOH usage, suggesting that KOH could react with $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ (or its molecular precursors) during the thermal-polymerization process, causing the loss of ordered structures within the framework. The FTIR spectrum for pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ (Figure 1B, top spectrum) showed a peak at $810\\mathrm{cm}^{-1}$ typical for the out-of-plane bending mode of heptazine rings, whilst peaks locked between 900 and $1800~\\mathrm{cm}^{-1}$ originate from $N{\\mathrm{-}}C{\\mathrm{=}}\\mathrm{N}$ heterorings in the “melon” framework. Multiple broad peaks in the $3000{-}3500~\\mathrm{cm}^{-1}$ region correspond to $_\\mathrm{N-H}$ stretching vibrations. For the $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ samples, two distinct changes can be observed in the FTIR spectra with increasing KOH usage, highlighted by the yellow shaded regions in Figure 1B. The first was a progressive decrease in the intensity of the $\\mathsf{N}{\\mathrm{-}}\\mathsf{H}$ stretching peaks between 3000 and $3300{\\mathrm{cm}}^{-1}$ . The other change was the development of a new peak at $2177\\mathrm{cm}^{-1}$ , corresponding to an asymmetric stretching vibration of cyano groups $(-C\\equiv\\mathrm{N})$ .[23] The results suggest KOH addition during the synthesis of $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ decreases the concentration of $\\mathsf{N}{\\mathrm{-}}\\mathsf{H}$ groups and introduces $-C{\\equiv}\\mathrm{N}$ groups. It should be noted that KOH melts at $360~^{\\circ}\\mathrm{C}$ , and thus $\\mathrm{OH^{-}}$ released upon melting may react with amine groups of urea-derived intermediates during the thermal-polymerization process, thus generating cyano groups.[24] Solid-state $^{13}\\mathrm{C}$ magic angle spinning (MAS) NMR measurements provided further insight about the newly formed cyano groups (Figure 1C). The NMR spectra of all samples showed two strong peaks at 156.4 and 164.5 ppm corresponding to the chemical shifts of $\\mathrm{C}_{3\\mathrm{N}}$ (1) and $\\mathrm{C}_{2\\mathrm{N}-\\mathrm{N}\\mathrm{H}x}$ (2) in the heptazine units, respectively.[25] Two new peaks at 123.8 and 171.0 ppm can be clearly observed for $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–0.5$ , which can be ascribed to carbon atom (3) in cyano groups and the neighbor C atom (4), respectively.[26] Peak (1) at 156.4 ppm is associated with $\\mathrm{C}_{2\\mathrm{N}-\\mathrm{N}\\mathrm{H}x}$ lost intensity with increasing KOH usage during synthesis of $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ . Thus, based on the NMR results, it would appear that the cyano groups may be located at one apex of the melon structure of $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x},$ with the cyano groups originated from deprotonation of ${\\mathrm{-C-NH}}_{2}$ . \n\n![](images/98657cb9aed15dd15fdceeb65f8480649029cfb4372a2d37c2e00658f7117599.jpg) \nFigure 1.  A) XRD patterns and B) FTIR spectra of ${\\tt g}{\\cdot}{\\sf C}_{3}\\mathsf{N}_{4}$ and $\\mathsf{g}\\mathrm{-}\\mathsf{C}_{3}\\mathsf{N}_{x}.$ $\\mathsf{a}{-}\\mathsf{g}$ represent $\\mathsf{g}{\\mathsf{-}}\\mathsf{C}_{3}\\mathsf{N}_{4},$ , $\\mathtt{g}_{\\mathtt{-}}\\mathsf{C}_{3,}\\mathsf{N}_{x}{\\mathsf{-}}0.005$ , $\\mathtt{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}–0.0\\mathsf{l}$ , $\\mathtt{g}_{\\mathtt{-}}\\mathsf{C}_{3}\\mathsf{N}_{x}{\\mathtt{-}}0.05$ , $\\mathtt{g}\\ –\\mathsf{C}_{3}\\mathsf{N}_{x}.0.1$ , ${\\tt g}{\\cdot}{\\sf C}_{3}\\mathsf{N}_{x}{\\cdot}$ 0.5, and ${\\tt g}–{\\mathsf{C}}_{3}\\mathsf{N}_{x}–\\mathsf{l}.0$ , respectively. C) Solid-state $^{13}{\\mathsf{C}}$ MAS NMR spectra of (I) $\\mathsf{g}{\\mathsf{-}}\\mathsf{C}_{3}\\mathsf{N}_{4}$ , (II) $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}–0.05$ , and (III) ${\\tt g}–{\\mathsf{C}}_{3}\\mathsf{N}_{x}–0.5$ , and proposed structure changes in heptazine units before and after introducing cyano groups. D) C1s and N1s XPS spectra of (i) $\\mathsf{g-C}_{3}\\mathsf{N}_{4},$ (ii) $\\mathtt{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}–0.0\\mathsf{l}$ , (iii) ${\\tt g}–{\\mathsf{C}}_{3}\\mathsf{N}_{x}–0.7$ , and (iv) ${\\tt g}–{\\mathsf{C}}_{3}\\mathsf{N}_{x}–\\mathsf{l}.0$ . \n\nTo further investigate the effects of KOH treatment on the bulk and surface elemental composition of $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{x},$ organic elemental analysis (OEA) and X-ray photoelectron spectroscopy (XPS) measurements were performed, respectively. $\\mathrm{N}/\\mathrm{C}$ and $\\mathrm{{{O/C}}}$ atomic ratios for pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ and $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ determined from the two methods are listed in Table S1 (Supporting \n\nInformation). Only trace amounts of oxygen were detected by OEA, which excluded the possibility that hydroxyl groups were introduced by KOH treatment. The very small O1s peaks in the XPS survey spectra were likely due to surface adsorbed adventitious oxygen-containing species (Figure S1, Supporting Information).[27] The $\\mathrm{N}/\\mathrm{C}$ atomic ratios for pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ obtained from OEA and XPS were 1.457 and 1.35, respectively, close to the theoretical value for $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ .[28] The OEA data confirmed that the bulk $\\mathrm{N}/\\mathrm{C}$ ratio for all ${\\tt g}–{\\sf C}_{3}\\mathrm{N}_{x}$ samples was similar. It should be noted here that the formation of cyano groups does not result in N loss in the bulk. However, the XPS data showed a progressive decrease in the $\\mathrm{N}/\\mathrm{C}$ ratio (from 1.35 to 0.85) on the surface of $\\mathsf{g}{\\mathsf{-C}}_{3}\\mathrm{N}_{x}$ with increasing KOH usage, suggesting the introduction of surface $\\mathrm{~N~}$ defects. To further confirm the introduction of surface N defects, narrow scan C1s and N1s XPS spectra for pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ and the $\\mathtt{g}\\mathrm{-C}_{3}\\mathrm{N}_{x}$ samples were collected and deconvoluted into their components (Figure 1D). The C1s XPS spectra for $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{x}$ contained three components located at 288.2, 286.4, and $284.8\\ \\mathrm{eV}$ corresponding to ${\\mathrm{N-C}}{\\mathrm{=N}}$ coordination in the framework of $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ $\\mathrm{C}{\\cdot}\\mathrm{N}\\mathrm{H}_{x}$ $\\left\\langle x=1,2\\right\\rangle$ ) on the edges of heptazine units and adventitious hydrocarbons, respectively. Interestingly, the $286.4\\ \\mathrm{eV}$ signal of $\\mathrm{g-C_{3}N_{4}}{-1.0}$ was intensified compared to the same feature for pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ (Figure 1D, bottom), which can be taken as additional evidence for the formation of cyano groups (as seen by FTIR and solid-state $^{13}\\mathrm{C}$ NMR) since $\\mathrm{C}\\equiv\\mathrm{N}$ groups possess similar C1s binding energies to $\\mathrm{C-NH}_{x}$ .[29] The N1s XPS spectrum for pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ contained three components at 398.6, 400.0, and $401.0\\ \\mathrm{~eV},$ corresponding to bicoordinated $\\left(\\mathrm{N}_{2\\mathrm{C}}\\right)$ and tricoordinated $(\\mathrm{N}_{3\\mathrm{C}})$ \n\nnitrogen atoms and $\\mathrm{NH}_{x}$ groups in the heptazine framework, respectively. With increasing KOH usage during thermal polymerization, the $\\mathrm{N}_{3\\mathrm{c}}$ peak exhibited a small shift to lower binding energy, which could be due to the generation of cyano groups whose N 1s binding energy are intermediate between those of $\\Nu_{2\\mathrm{C}}$ and $\\Nu_{3\\mathrm C}$ (Table S2, Supporting Information).[29] Further, the intensity of $\\Nu_{2\\mathrm{C}}$ decreases $\\mathrm{(N_{2C}/C}$ atomic ratios dropped from 1.10 to 0.51), strong evidence that $\\Nu_{2\\mathrm{C}}$ vacancies were formed on the surface of $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}.$ \n\n$\\mathrm{N}_{2}$ physisorption measurements at 77 K were used to examine the effect of KOH addition on the specific surface area and pore structure of samples. Pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ had a Brunauer–Emmett–Teller (BET) specific surface area of $81.5~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ and a well-defined mesopore distribution (Table S3 and Figure S3, Supporting Information), displaying characteristic adsorption–desorption hysteresis (Figure S2, Supporting Information). The BET specific surface area of the $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ samples decreased progressively on going from $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–0.005$ to $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–1.0$ , reflecting a corresponding loss in the well-defined mesoporous structure seen for pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ . Scanning electron microscopy (Figures S4 and S5, Supporting Information) confirmed that $\\mathrm{g-C_{3}N_{4}}$ and the $\\mathsf{g}{\\mathsf{-C}}_{3}\\mathrm{N}_{x}$ samples all possessed sheet-like structures, with the possible exception being the $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–1.0$ sample. Thus, it can be concluded that KOH addition modifies the chemical composition and mesoporosity of $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ , whilst largely preserving the characteristic sheet structure of the compound. \n\n$\\mathrm{~N~}$ defects introduced into $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ by KOH addition during the thermal polymerization of urea dramatically alter their optical properties and light harvesting ability of the samples. It is evident that as the KOH usage increased, the $\\mathtt{g}\\mathrm{-C}_{3}\\mathrm{N}_{x}$ powders became a progressively darker yellow and then finally orange when the amount of KOH used was increased to $\\boldsymbol{1.0\\ \\mathrm{g}}$ (Inset in Figure 1A). Figure 2A,B shows UV–vis diffuse reflectance spectra (DRS) and calculated bandgaps for pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ and $\\mathsf{g}{\\mathrm{-}}\\mathsf{C}_{3}\\mathsf{N}_{x}$ samples prepared with different amounts of KOH. A progressive redshift in the absorption edge was achieved with increasing KOH usage, indicating a homogeneous distribution of N defects in the bulk. Bandgaps of the samples determined from the transformed Kubelka–Munk function progressively narrowed from 2.68 to $2.36~\\mathrm{eV}.$ Furthermore, $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ prepared by other precursors (melamine or thiourea) and alkalis (NaOH or $\\mathrm{Ba}(\\mathrm{OH})_{2})$ showed similar trends of a narrowed bandgap was formed compared with pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ , confirming the versatility of this alkali-assisted synthesis approach (Figure 2C,D and Figure S6, Supporting Information). \n\nTo explain the narrower bandgap in the $\\mathsf{g}{\\mathsf{-C}}_{3}\\mathrm{N}_{x}$ powders, valence band (VB) XPS spectra were collected (Figure S7, Supporting Information). The VB maximum was similar for both pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ and $\\mathsf{g}{\\mathsf{-C}}_{3}\\mathrm{N}_{x}$ $(\\approx2.07\\ \\mathrm{eV}$ ). The contact potential difference between the samples and the analyzer was estimated to be $_{\\approx1.51\\mathrm{~V~}}$ versus normal hydrogen electrode (NHE) at $\\mathrm{pH}7$ using the formula $E_{\\mathrm{NHE}}/V=\\Phi+2.07\\:\\mathrm{eV}-4.44$ ( $E_{\\mathrm{NHE}}$ : potential of normal hydrogen electrode; $\\Phi$ of $3.88~\\mathrm{eV};$ the electron work function of the analyzer).[21b,30] The data suggest that the VB position was largely unaffected by the introduction of nitrogen defects into $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ . Therefore, in combination with the DRS results above, the narrower bandgap of the $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ powders must originate from a decrease in the conduction band (CB) position compared to that of $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4},$ with the band alignments shown in Figure 3. \n\n![](images/8cec03c621eb290cc48949664ba1aadca41bb382f04787d4ac161a3151105ecd.jpg) \nFigure 2.  A) UV–vis DRS and B) Plots of transformed Kubelka–Munk function versus photon energy for $g{-}C_{3}\\mathsf{N}_{4}$ and ${\\tt g}{\\cdot}{\\mathsf{C}}_{3}\\mathsf{N}_{x}$ prepared using urea as precursor and different amounts of KOH (ranging from 0 to $\\mathsf{1.0}\\mathsf{g})$ . Inset in (A) shows a digital photograph of samples prepared with different amounts of KOH (ranging from 0 to $\\mathsf{1.0~g}$ , from left to right). C) UV–vis DRS spectra of $\\mathsf{g}{\\mathsf{-}}\\mathsf{C}_{3}\\mathsf{N}_{4}$ and ${\\tt g}–{\\mathsf{C}}_{3}\\mathsf{N}_{x}$ prepared with melamine as precursor and $\\boldsymbol{\\mathsf{1.0\\mathrm{g}}}$ of KOH. Inset in bottom-left corner shows a digital photograph of samples ${\\tt g}{\\cdot}{\\sf C}_{3}\\mathsf{N}_{4}$ (left) and ${\\tt g}–{\\mathsf{C}}_{3}\\mathsf{N}_{x}$ (right). D) UV–vis DRS spectra of $\\mathsf{g}{\\mathsf{-}}\\mathsf{C}_{3}\\mathsf{N}_{4}$ and ${\\tt g}{\\tt c}_{3}\\mathsf{N}_{x}$ prepared with urea as precursor and $\\boldsymbol{\\mathsf{1.0\\mathrm{~g~}}}$ of NaOH or $B a(O H)_{2}$ . Inset in left bottom in (D) shows a digital photograph of samples $\\mathsf{g}{\\mathsf{-}}\\mathsf{C}_{3}\\mathsf{N}_{4}$ (left), ${\\tt g}{\\tt c}_{3}\\mathsf{N}_{x}$ prepared with NaOH (middle), and ${\\tt g}{\\tt c}_{3}\\mathsf{N}_{x}$ prepared with $B a(O H)_{2}$ (right). Insets in upper-right corner in (C) and (D) show plots of transformed Kubelka–Munk function versus photon energy for corresponding samples. \n\n![](images/1780cfad71e2ee084f798a678c2c12fb941a206d76e84353d7bba05b7420aae5.jpg) \nFigure 3.  Band structure alignments for pristine $\\mathsf{g}{\\mathsf{-}}\\mathsf{C}_{3}\\mathsf{N}_{4}$ and $\\mathtt{g}\\mathtt{-C}_{3}\\mathsf{N}_{x}.$ \n\nIn order to understand the relationship between N defects and the narrowed bandgaps of $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x},$ density-functionaltheory calculations of the band structure and partial density of states (PDOS) for $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ and $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ were performed (Figure 4). The calculations show that after introducing a cyano group and $\\mathrm{~N~}$ vacancy into the unit cell of $\\mathrm{g-C_{3}N_{4}}$ , the bandgap energy of $\\mathtt{g}\\mathrm{-C}_{3}\\mathrm{N}_{x}$ decreases from 2.67 to $2.17\\ \\mathrm{eV},$ , which agreed well with the general trend seen in the DRS data above. Both C2p and N2p orbitals contribute to the CB of $\\mathrm{g-C}_{3}\\mathrm{N}_{4},$ while the VB is mainly composed of $\\mathsf{N2p}$ orbitals, consistent with previously reported results.[31] Further, a defect energy level composed of both $\\mathtt{C2p}$ and $\\mathtt{N2p}$ orbitals appears about $1.52\\ \\mathrm{eV}$ above the VB, coinciding with the increasing absorption tail seen for the $\\mathsf{g}{\\mathsf{-C}}_{3}\\mathrm{N}_{x}$ samples in Figure 2A. Another unit cell of $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ containing only one cyano group was also built to better understand the contributions of the two types of $\\mathrm{~N~}$ defects toward the final band structure (Figure S8, Supporting Information). The bandgap becomes $2.32\\ \\mathrm{eV}$ due to a lowering of the CB minimum by $0.35\\ \\mathrm{eV}$ whilst no defect energy level appears. Detailed simulated band structure alignments are given in Figure S9 (Supporting Information). These results confirmed that the narrowed bandgap of $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ compared to pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ is due to the coexistence of cyano groups and N vacancies. \n\nIn addition to the effect on the bandgap structure, N defects in $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ are also expected to influence the separation of photoexcited charge carriers, which can be investigated by photoluminescence (PL) spectroscopy and transient surface photovoltage (TS-SPV) techniques. PL data for pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ under visible-light irradiation $(\\lambda>420\\ \\mathrm{nm})$ showed an intense fluorescence signal (Figure 5A). This signal progressively lost intensity and redshifted on adding KOH during the thermalpolymerization process and completely disappeared when KOH usage was $0.5\\mathrm{\\g}$ or higher, confirming that KOH addition during synthesis is highly beneficial for the separation of photoexcited charge carriers in $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x},$ which was further corroborated by TS-SPV measurements (Figure 5B). It can be seen that both the fast component $(<10^{-5}\\ \\mathrm{s})$ and slow component $(>10^{-4}$ s) corresponding to the separation and diffusion of electron–hole pairs, respectively, were more intense for $\\mathsf{g}{\\mathsf{-C}}_{3}\\mathrm{N}_{x}$ samples compared to pristine $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ . Further, these features intensified as more N defects were introduced (with the exception being $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–1.0$ which may be caused by its poor crystallinity).[32] \n\n![](images/c349fad02b52fef4c9439b5eb10d8a3248a2c9726a116bd8e14c9f89e08ce082.jpg) \nFigure 4.  A,D) Structure models of ${\\tt g}{\\cdot}{\\sf C}_{3}\\mathsf{N}_{4}$ and ${\\tt g}{\\cdot}{\\mathsf{C}}_{3}\\mathsf{N}_{x}$ with N defects (including $-C=N$ group and N vacancy). B,E) Calculated band structures and C,F) corresponding PDOS for $\\mathtt{g-C}_{3}\\mathsf{N}_{4}$ and $\\mathsf{g}\\mathrm{-}\\mathsf{C}_{3}\\mathsf{N}_{x},$ respectively. \n\n![](images/3bcd946ec1b75efad6dead3480adf833e4ef1a427ebc2462727e033663b9f545.jpg) \nFigure 5.  A) Photoluminescence spectra for ${\\tt g}{\\cdot}{\\sf C}_{3}\\mathsf{N}_{4}$ and ${\\tt g}–{\\mathsf{C}}_{3}\\mathsf{N}_{x}–M$ ( $M$ from 0.005 to 1.0). B) TS-SPV spectra of $\\mathsf{\\bar{g}}\\mathsf{-C}_{3}\\mathsf{N}_{4}$ prepared with different amounts of KOH under $355\\ \\mathsf{n m}$ excitation. Photocatalytic hydrogen evolution rates over bare (C) and (D) 1 wt% Pt-loaded $g{-}C_{3}\\mathsf{N}_{4}$ and ${\\tt g}{\\tt c}_{3}\\mathsf{N}_{x}$ photocatalysts in $25\\ \\mathrm{vol\\%}$ aqueous lactic acid solution under visible-light irradiation $(\\lambda>420\\mathsf{n m})$ . $\\boldsymbol{\\mathsf{10}}\\mathrm{mg}$ photocatalysts were used for all experiments. E) Transient photocurrent response of ${\\tt g}{\\cdot}{\\sf C}_{3}\\mathsf{N}_{4}$ and $\\mathtt{g}\\mathrm{-}\\mathsf{C}_{3}\\mathsf{N}_{x}\\mathrm{-}0.01$ under visible-light illumination $\\lambda>420\\ \\mathsf{n m}_{\\mathrm{,}}$ ). F) Time course of hydrogen evolution over $\\mathsf{\\Delta}\\mathsf{l}0\\mathsf{h}$ for $1~\\mathrm{wt\\%}~\\mathsf{P t/g–C}_{3}\\mathsf{N}_{4}$ and $1\\mathrm{\\Omega}\\mathrm{wt}\\%$ $\\mathsf{P t}/\\mathsf{g}\\mathsf{-C}_{3}\\mathsf{N}_{x}\\mathsf{-}0.01$ in $25\\ \\mathrm{vol\\%}$ aqueous lactic acid solution under visible-light irradiation $(\\lambda>420\\mathsf{n m})$ . \n\nThe photocatalytic performance of the $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ and the $\\mathrm{g-C_{3}N_{4}}$ powders was evaluated using $\\mathrm{H}_{2}$ evolution under visible-light irradiation in an aqueous lactic acid solution at room temperature (Figure 5C,D). First, in the absence of Pt cocatalysts, $\\mathrm{H}_{2}$ evolution could be detected for all samples with the highest $\\mathrm{H}_{2}$ evolution rate of $4.40~\\upmu\\mathrm{mol}~\\mathrm{h}^{-1}$ (0.440 mmol $\\begin{array}{r}{\\mathbf{g}^{-1}\\mathbf{\\Lambda}\\mathrm{h}^{-1}.}\\end{array}$ observed for $\\mathrm{g{\\cdotC_{3}N}}_{x}{\\cdot0.01}$ (about twice as active as pristine $\\mathrm{g-C_{3}N_{4,}}$ ). The superior activities of $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–0.005$ and $\\mathrm{g{\\cdotC_{3}N}}_{x}{\\cdot0.01}$ can be attributed to their enhanced visible-light absorption and better charge separation efficiencies caused by N defects. The activity of $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–0.05$ and more N deficient samples were very low compared to $\\mathrm{g{\\cdotC_{3}N}}_{x}{\\cdot0.01}$ , which could be due to their lower CB positions, resulting in decreased reduction driving force for hydrogen evolution (Figure 3). In addition, the abundance of surface N vacancies on $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–0.05$ and the more N deficient samples created defect energy levels in their bandgaps. The defect energy levels with very low reduction driving force for $\\mathrm{H}_{2}$ evolution may trap a portion of the photogenerated electrons, thereby further decreasing the $\\mathrm{H}_{2}$ evolution activity.[33] Results suggest that there might be an optimum level of N-deficiency in $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{x}$ for achieving high photocatalytic $\\mathrm{H}_{2}$ production rates. Following loading with a $\\mathrm{Pt}$ cocatalyst, the rates of $\\mathrm{H}_{2}$ production increased significantly for all samples due to platinum’s high conductivity, negligible overpotential for $\\mathrm{H}_{2}$ evolution, and excellent electron transport kinetic. Again, the $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–0.01$ sample was the most active, affording a $\\mathrm{H}_{2}$ evolution rate of $69.0\\pm2~\\upmu\\mathrm{mol}~\\mathrm{h}^{-1}$ (6.9 mmol $\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ ) which was approximately twice that of pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ $(29.7\\pm2\\ \\upmu\\mathrm{mol}\\ \\mathrm{h}^{-1}$ or $2.97\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1})$ .[1a] Transient photocurrent measurements for pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ and $\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{x}–0.01$ revealed that both samples exhibited a sensitive photocurrent response during $\\mathsf{o n}/$ off irradiation cycles under visible light (Figure 5E). The photo­ current values were ${\\approx}0.13$ and $0.06\\mathrm{\\mA\\cm^{-2}}$ for $\\mathrm{g{\\cdotC_{3}N}}_{x}{\\cdot0.01}$ and $\\mathrm{g-C_{3}N_{4}}.$ respectively, which is consistent with the trend seen in their photocatalytic hydrogen evolution activities. The much higher photocurrent measured for $\\mathrm{g{\\cdotC_{3}N}}_{x}{\\cdot0.01}$ reflects a better visible-light response and more efficient photoexcited charge separation compared with pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ . The $\\mathrm{H}_{2}$ evolution rates for the Pt loaded $\\mathsf{g}{\\mathrm{-}}\\mathsf{C}_{3}\\mathsf{N}_{x}$ and $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ photocatalysts remained stable over $^{10\\mathrm{~h~}}$ of testing, confirming good operational stability even after introducing N defects into the $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ structure (Figure 5F). \n\nIn summary, nitrogen defects were successfully introduced into $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ via adding an alkali compound such as KOH during the thermal polymerization of urea, melamine, or thiourea. The obtained $\\mathsf{g}–\\mathsf{C}_{3}\\mathsf{N}_{x}$ products possess tunable band structures controlled by cyano groups in the bulk and surface N vacancies and are able to harvest visible light and separate photo­ excited charge carries more efficiently than pristine $\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}$ . Importantly, the alkali-assisted route allows the facile synthesis of carbon nitrides with tailored optical and photocatalytic properties. We hypothesize that the simple and highly effective strategy adopted here could be used to tune the band structures of other nitrogen-based semiconductors for improved solar energy capture and conversion. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThe authors are grateful for financial support from the Ministry of Science and Technology of China (2014CB239402 and 2013CB834505), the National Key Projects for Fundamental Research and Development of China (2016YFB0600900), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB17030300), the National Natural Science Foundation of China (21401206, 51322213, 21301183, 51572270, and 21401207), the Beijing Natural Science Foundation (2152033 and 2154058), and the National Program for Support of Top-notch Young Professionals. \n\nReceived: September 23, 2016 Revised: December 8, 2016 Published online: \n\n[1]\t a) X. C.  Wang, K.  Maeda, A.  Thomas, K.  Takanabe, G.  Xin, J. M.  Carlsson, K.  Domen, M.  Antonietti, Nat. Mater. 2009, 8, 76; b) J. Liu, Y. liu, N. Y. Liu, Y. Z. Han, X. Zhang, H. Huang, Y. Lifshitz, S.-T. Lee, J. Zhong, Z. H. Kang, Science 2015, 347, 970. \n[2]\t a) J. S.  Zhang, M.  Grzelczak, Y. D.  Hou, K.  Maeda, K.  Domen, X. Z.  Fu, M.  Antonietti, X. C.  Wang, Chem. Sci. 2012, 3, 443; b) K. Maeda, X. Wang, Y. Nishihara, D. Lu, M. Antonietti, K. Domen, J. Phys. Chem. C 2009, 113, 4940; c) A. B.  Jorge, D. J.  Martin, M. T. S.  Dhanoa, A. S.  Rahman, N.  Makwana, J.  Tang, A.  Sella, F.  Cora, S.  Firth, J. A.  Darr, P. F.  McMillan, J. Phys. Chem. C 2013, 117, 7178; d) Y.  Shiraishi, S.  Kanazawa, Y.  Kofuji, H.  Sakamoto, S.  Ichikawa, S.  Tanaka, T.  Hirai, Angew. Chem. Int. Ed. 2014, 53, 13454; e) Y. Zheng, L. Lin, X. Ye, F. Guo, X. Wang, Angew. Chem. Int. Ed. 2014, 53, 11926. \n[3]\t Y.  Cui, Z.  Ding, P.  Liu, M.  Antonietti, X.  Fu, X.  Wang, Phys. Chem. Chem. Phys. 2012, 14, 1455. \n[4]\t a) F. Su, S. C. Mathew, G. Lipner, X. Fu, M. Antonietti, S. Blechert, X. Wang, J. Am. Chem. Soc. 2010, 132, 16299; b) Y. Wang, X. Wang, M.  Antonietti, Angew. Chem. Int. Ed. 2012, 51, 68; c) B.  Long, Z. Ding, X. Wang, ChemSusChem 2013, 6, 2024. \n[5]\t a) R.  Kuriki, K.  Sekizawa, O.  Ishitani, K.  Maeda, Angew. Chem. Int. Ed. 2015, 54, 1; b) W.-J. Ong, L.-L. Tan, S.-P. Chai, S.-T. Yong, Chem. Commun. 2015, 51, 858; c) K.  Maeda, K.  Sekizawa, O.  Ishitani, Chem. Commun. 2013, 49, 10127; d) J.  Lin, Z.  Pan, X.  Wang, ACS Sustainable Chem. Eng. 2014, 2, 353; e) K.  Maeda, R.  Kuriki, M. Zhang, X. Wang, O. Ishitani, J. Mater. Chem. A 2014, 2, 15146; f ) H.  Zhou, P.  Li, J.  Liu, Z. P.  Chen, L. Q.  Liu, D.  Dontsova, R. Y. Yan, T. X. Fan, D. Zhang, J. H. Ye, Nano Energy 2016, 25, 128; g) G. P.  Gao, Y.  Jiao, E. R.  Waclawik, A. J.  Du, J. Am. Chem. Soc. 2016, 138, 6292. \n[6]\t G. Dong, K. Zhao, L. Zhang, Chem. Commun. 2012, 48, 6178. \n[7]\t a) S. C.  Yan, Z. S.  Li, Z. G.  Zou, Langmuir 2010, 26, 3894; b) Y.  Wang, J. S.  Zhang, X. C.  Wang, M.  Antonietti, H. R.  Li, Angew. Chem. Int. Ed. 2010, 49, 3356; c) Y.  Wang, H. R.  Li, J.  Yao, X. C. Wang, M. Antonietti, Chem. Sci. 2011, 2, 446. \n[8]\t J.  Li, B.  Shen, Z.  Hong, B.  Lin, B.  Gao, Y.  Chen, Chem. Commun. 2012, 48, 12017. \n[9]\t a) J. S. Zhang, J. H. Sun, K. Maeda, K. Domen, P. Liu, M. Antonietti, X. Z.  Fu, X. C.  Wang, Energy Environ. Sci. 2011, 4, 675; b) G.  Liu, P. Niu, C. H. Sun, S. C. Smith, Z. G. Chen, G. Q. Lu, H. M. Cheng, J. Am. Chem. Soc. 2010, 132, 11642. \n[10]\t a) J. R. Ran, T. Y. Ma, G. P. Gao, X. W. Du, S. Z. Qiao, Energy Environ. Sci. 2015, 8, 3708; b) S. E.  Guo, Z. P.  Deng, M. X.  Li, B. J.  Jiang, C. G.  Tian, Q. J.  Pan, H. G.  Fu, Angew. Chem. Int. Ed. 2016, 55, 1830. \n[11]\t Z. A. Lan, G. G. Zhang, X. C. Wang, Appl. Catal. B 2016, 192, 116. \n[12]\t G.  Zhang, M.  Zhang, X.  Ye, X.  Qiu, S.  Lin, X.  Wang, Adv. Mater. 2014, 26, 805. \n[13]\t G. Ding, W. Wang, T. Jiang, B. Han, H. Fan, G. Yang, ChemCatChem 2013, 5, 192. \n[14]\t a) X. Chen, J. Zhang, X. Fu, A. Markus, X. Wang, J. Am. Chem. Soc. 2009, 131, 11658; b) X. Ye, Y. Cui, X. Wang, ChemSusChem 2014, 7, 738. \n[15]\t a) J.  Sun, J.  Zhang, M.  Zhang, M.  Antonietti, X.  Fu, X.  Wang, Nat. Commun. 2012, 3, 1139; b) X. Bai, L. Wang, R. Zong, Y. Zhu, J. Phys. Chem. C 2013, 117, 9952; c) Y. S. Jun, J. Park, S. U. Lee, A. Thomas, W. H.  Hong, G. D.  Stucky, Angew. Chem. Int. Ed. 2013, 52, 11083; d) Y.-S.  Jun, E. Z.  Lee, X.  Wang, W. H.  Hong, G. D.  Stucky, A.  Thomas, Adv. Funct. Mater. 2013, 23, 3661; e) J.  Xu, Y.  Wang, Y.  Zhu, Langmuir 2013, 29, 10566; f) M.  Tahir, C.  Cao, F. K.  Butt, S.  Butt, F.  Idrees, Z.  Ali, I.  Aslam, M.  Tanveer, A.  Mahmood, N.  Mahmood, CrystEngComm 2014, 16, 1825; g) J.  Zhang, M.  Zhang, C.  Yang, X.  Wang, Adv. Mater. 2014, 26, 4121; h) X. C.  Wang, K.  Maeda, X. F.  Chen, K.  Takanabe, K.  Domen, Y. D. Hou, X. Z. Fu, M. Antonietti, J. Am. Chem. Soc. 2009, 131, 1680; i) M.  Shalom, S.  Inal, C.  Fettkenhauer, D.  Neher, M.  Antonietti, J. Am. Chem. Soc. 2013, 135, 7118; j) K. Zhang, L. Wang, X. W. Sheng, M.  Ma, M. S.  Jung, W.  Kim, H.  Lee, J. H.  Park, Adv. Energy Mater. 2016, 6, 1502352; k) Q. Han, B. Wang, J. Gao, Z. H. Cheng, Y. Zhao, Z. P. Zhang, L. T. Qu, ACS Nano 2016, 10, 2745. \n[16]\t a) Y. Y. Kang, Y. Q. Yang, L. C. Yin, X. D. Kang, G. Liu, H. M. Cheng, Adv. Mater. 2015, 27, 4572; b) V. W. H.  Lau, M. B.  Mesch, V. Duppel, V. Blum, J. Senker, B. V. Lotsch, J. Am. Chem. Soc. 2015, 137, 1064. \n[17]\t a) X.  Zhang, L.  Yu, R.  Li, T.  Peng, X.  Li, Catal. Sci. Technol. 2014, 4, 3251; b) J. Xu, Y. Li, S. Peng, G. Lu, S. Li, Phys. Chem. Chem. Phys. 2013, 15, 7657; c) X. Zhang, L. Yu, C. Zhuang, T. Peng, R. Li, X. Li, ACS Catal. 2013, 4, 162; d) Y. Wang, J. Hong, W. Zhang, R. Xu, Catal. Sci. Technol. 2013, 3, 1703; e) S. Min, G. Lu, J. Phys. Chem. C 2012, 116, 19644; f) K.  Takanabe, K.  Kamata, X.  Wang, M.  Antonietti, J. Kubota, K. Domen, Phys. Chem. Chem. Phys. 2010, 12, 13020. \n[18]\t a) K.  Schwinghammer, M. B.  Mesch, V.  Duppel, C.  Ziegler, J. Senker, B. V. Lotsch, J. Am. Chem. Soc. 2014, 136, 1730; b) P. Niu, L.  Zhang, G.  Liu, H.-M.  Cheng, Adv. Funct. Mater. 2012, 22, 4763; c) S. B. Yang, Y. J. Gong, J. S. Zhang, L. Zhan, L. L. Ma, Z. Y. Fang, R.  Vajtai, X. C.  Wang, P. M.  Ajayan, Adv. Mater. 2013, 25, 2452; d) Q.  Han, F.  Zhao, C. G.  Hu, L. X.  Lv, Z. P.  Zhang, N.  Chen, L. T. Qu, Nano Res. 2015, 8, 1718; e) M. Wu, J.-M. Yan, X.-N. Tang, M. Zhao, Q. Jiang, ChemSusChem 2014, 7, 2654. \n[19]\t a) L.  Ge, C.  Han, J.  Liu, Appl. Catal. B 2011, 108, 100; b) H.  Xu, J.  Yan, Y.  Xu, Y.  Song, H.  Li, J.  Xia, C.  Huang, H.  Wan, Appl. Catal. B 2013, 129, 182; c) J.  Fu, B.  Chang, Y.  Tian, F.  Xi, X.  Dong, J. Mater. Chem. A 2013, 1, 3083; d) S. Kumar, T. Surendar, A. Baruah, V. Shanker, J. Mater. Chem. A 2013, 1, 5333; e) C. Han, Y. D. Wang, Y. P. Lei, B. Wang, N. Wu, Q. Shi, Q. Li, Nano Res. 2015, 8, 1199. \n[20]\t a) L.  Ge, C.  Han, Appl. Catal. B 2012, 117, 268; b) L.  Ge, C.  Han, J.  Liu, J. Mater. Chem. 2012, 22, 11843; c) A.  Du, S.  Sanvito, Z.  Li, D.  Wang, Y.  Jiao, T.  Liao, Q.  Sun, Y. H.  Ng, Z.  Zhu, R.  Amal, S. C. Smith, J. Am. Chem. Soc. 2012, 134, 4393. \n[21]\t a) P. Niu, G. Liu, H.-M. Cheng, J. Phys. Chem. C 2012, 116, 11013; b) Z.  Hong, B.  Shen, Y.  Chen, B.  Lin, B.  Gao, J. Mater. Chem. A 2013, 1, 11754; c) P. Niu, L. C. Yin, Y. Q. Yang, G. Liu, H. M. Cheng, Adv. Mater. 2014, 26, 8046. \n[22]\t A.  Thomas, A.  Fischer, F.  Goettmann, M.  Antonietti, J.-O.  Müller, R. Schlögl, J. M. Carlsson, J. Mater. Chem. 2008, 18, 4893. \n[23]\t a) E.  Irran, B.  Jürgens, W.  Schnick, Solid State Sci. 2002, 4, 1305; b) W.  Lei, D.  Portehault, R.  Dimova, M.  Antonietti, J. Am. Chem. Soc. 2011, 133, 7121; c) Y.  Cui, Z.  Ding, X.  Fu, X.  Wang, Angew. Chem. Int. Ed. 2012, 51, 11814. \n[24]\t H. Gao, S. Yan, J. Wang, Y. A. Huang, P. Wang, Z. Li, Z. Zou, Phys. Chem. Chem. Phys. 2013, 15, 18077. \n[25]\t B. Jürgens, E. Irran, J. Senker, P. Kroll, H. Müller, W. Schnick, J. Am. Chem. Soc. 2003, 125, 10288. \n[26]\t V. W.  Lau, I.  Moudrakovski, T.  Botari, S.  Weinberger, M. B. Mesch, V. Duppel, J. Senker, V. Blum, B. V. Lotsch, Nat. Commun. 2016, 7, 12165. \n[27]\t a) J.  Liu, T.  Zhang, Z.  Wang, G.  Dawson, W.  Chen, J. Mater. Chem. 2011, 21, 14398; b) F.  Dong, Z.  Zhao, T.  Xiong, Z.  Ni, W.  Zhang, Y.  Sun, W.-K.  Ho, ACS Appl. Mater. Interfaces 2013, 5, 11392. \n[28]\t T. Sano, S. Tsutsui, K. Koike, T. Hirakawa, Y. Teramoto, N. Negishi, K. Takeuchi, J. Mater. Chem. A 2013, 1, 6489. \n[29]\t H. L.  Gao, S. C.  Yan, J. J.  Wang, Y. A.  Huang, P.  Wang, Z. S.  Li, Z. G. Zou, Phys. Chem. Chem. Phys. 2013, 15, 18077. \n[30]\t S. Trasatti, Pure Appl. Chem. 1986, 58, 955. \n[31]\t G. Dong, K. Zhao, L. Zhang, Chem. Commun. 2012, 48, 6178. \n[32]\t M.  Xie, X.  Fu, L.  Jing, P.  Luan, Y.  Feng, H.  Fu, Adv. Energy Mater. 2014, 4, 1300995. \n[33]\t a) E. M.  Samsudin, S. B. A.  Hamid, J. C.  Juan, W. J.  Basirun, A. E.  Kandjani, Appl. Surf. Sci. 2015, 359, 883; b) S.  Li, L.  Zhang, T.  Jiang, L.  Chen, Y.  Lin, D.  Wang, T.  Xie, Chem. Eur. J. 2014, 20, 311. " + }, + { + "id": "10.1038_ncomms13907", + "DOI": "10.1038/ncomms13907", + "DOI Link": "http://dx.doi.org/10.1038/ncomms13907", + "Relative Dir Path": "mds/10.1038_ncomms13907", + "Article Title": "Ti3C2 MXene co-catalyst on metal sulfide photo-absorbers for enhanced visible-light photocatalytic hydrogen production", + "Authors": "Ran, JR; Gao, GP; Li, FT; Ma, TY; Du, AJ; Qiao, SZ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Scalable and sustainable solar hydrogen production through photocatalytic water splitting requires highly active and stable earth-abundant co-catalysts to replace expensive and rare platinum. Here we employ density functional theory calculations to direct atomic-level exploration, design and fabrication of a MXene material, Ti3C2 nulloparticles, as a highly efficient co-catalyst. Ti3C2 nulloparticles are rationally integrated with cadmium sulfide via a hydrothermal strategy to induce a super high visible-light photocatalytic hydrogen production activity of 14,342 mu mol h(-1) g(-1) and an apparent quantum efficiency of 40.1% at 420 nm. This high performance arises from the favourable Fermi level position, electrical conductivity and hydrogen evolution capacity of Ti3C2 nulloparticles. Furthermore, Ti3C2 nulloparticles also serve as an efficient co-catalyst on ZnS or ZnxCd1-xS. This work demonstrates the potential of earth-abundant MXene family materials to construct numerous high performance and low-cost photocatalysts/photoelectrodes.", + "Times Cited, WoS Core": 1707, + "Times Cited, All Databases": 1770, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000391020200001", + "Markdown": "# Ti3C2 MXene co-catalyst on metal sulfide photo-absorbers for enhanced visible-light photocatalytic hydrogen production \n\nJingrun Ran1,\\*, Guoping ${\\mathsf{G a o}}^{2,\\star}.$ , Fa-Tang Li1,3, Tian-Yi Ma1, Aijun ${\\mathsf{D}}{\\mathsf{u}}^{2}$ & Shi-Zhang Qiao1 \n\nScalable and sustainable solar hydrogen production through photocatalytic water splitting requires highly active and stable earth-abundant co-catalysts to replace expensive and rare platinum. Here we employ density functional theory calculations to direct atomic-level exploration, design and fabrication of a MXene material, $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ nanoparticles, as a highly efficient co-catalyst. $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ nanoparticles are rationally integrated with cadmium sulfide via a hydrothermal strategy to induce a super high visible-light photocatalytic hydrogen production activity of $14,342{\\upmu\\mathrm{mol}}{\\hslash}-1{\\upmu}^{-1} $ and an apparent quantum efficiency of $40.1\\%$ at $420\\mathsf{n m}$ . This high performance arises from the favourable Fermi level position, electrical conductivity and hydrogen evolution capacity of $\\bar{\\mathsf{T}}\\mathsf{i}_{3}\\mathsf{C}_{2}$ nanoparticles. Furthermore, $\\bar{\\mathsf{T}}\\mathsf{i}_{3}\\mathsf{C}_{2}$ nanoparticles also serve as an efficient co-catalyst on $Z n S$ or $Z n_{x}C d_{1-x}S$ . This work demonstrates the potential of earth-abundant MXene family materials to construct numerous high performance and lowcost photocatalysts/photoelectrodes. \n\nTeghlneobrgagely iersn iroegny dpf doh ladesrmoags1 –np $\\left(\\operatorname{H}_{2}\\right)$ fnircgomsat lawyt,a pyr fouotsroi sagtoalslvoyiltnaigcr energy is regarded as a, promising strategy for solving global energy problemsl-3. Particularly, photocatalytic water splitting by utilizing semiconductor photocatalysts has demonstrated huge potential as a clean, low-cost and sustainable approach for solar $\\mathrm{H}_{2}$ production. However, despite tremendous achievement in this area during the past decades1,4,5, it is still a great challenge to develop highly efficient, cost-effective and robust photocatalysts driven by sunlight. In recent years, cocatalysts have shown great success in boosting both the activity and stability of photocatalysts6–9. Unfortunately, the high price and extreme scarcity of the most active $\\mathrm{H}_{2}$ evolution co-catalyst, $\\mathrm{Pt},$ restricts the commercialization of current photocatalysts. Therefore, seeking an inexpensive and highly active co-catalyst to replace $\\mathrm{Pt}$ is of paramount significance for achieving large-scale solar $\\mathrm{H}_{2}$ production in the future. \n\nTo date, although enormous progress has been made in developing earth-abundant co-catalysts, several major problems, arising from the intrinsic properties of current co-catalysts, still exist: (i) lack of abundant surface functionalities to establish strong connection with photocatalysts, for fast interfacial charge transfer and long-term stability; (ii) inefficient electron shuttling within co-catalysts due to their poor semiconducting/ insulating conductivity10 or destruction of $\\pi$ -conjugated system (for example, graphene oxide)11; (iii) undesirable Gibbs free energy for $\\mathrm{H}_{2}$ evolution; (iv) insufficient contact with water molecules due to lack of hydrophilic functionalities; and (v) instability and/or requirement of non-aqueous environment (for example, hydrogenases and their mimics)12,13. Therefore, it is highly desirable to seek a brand-new family of materials as the next generation co-catalysts that can overcome these drawbacks. MXene, a new family of over 60 two-dimensional (2D) metal carbides, nitrides or carbonitrides14,15, has shown great potential as electrodes in (Li)-ion batteries16 and supercapacitors17. Notably, their distinguished characteristics render them highly promising for solving the above problems as: (i) MXene possesses numerous hydrophilic functionalities (–OH and $^{-0}$ ) on its surface, enabling it to easily construct strong connection with various semiconductors; (ii) the excellent metallic conductivity of MXene assures efficient charge-carrier transfer; (iii) the exposed terminal metal sites (for example, Ti, Nb or V) on MXene might lead to much stronger redox reactivity than that of the carbon materials18; (iv) the presence of numerous hydrophilic functionalities on MXene promotes its strong interaction with water molecules; and (v) MXene can stably function in aqueous solutions. Considering the above outstanding properties of the MXene family, it is anticipated that MXene will be a promising material to be employed in photocatalysis. However, to the best of our knowledge, there is no report on exploring MXene as a co-catalyst for photocatalysis. \n\nHerein, we utilize density functional theory (DFT) calculations to explore the potential of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene as a $\\mathrm{H}_{2}$ evolution co-catalyst. On the basis of theoretical studies, we report a rational design and synthesis of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ nanoparticles (NPs) and merge them with a chosen photocatalyst, CdS, to successfully achieve a super high visible-light photocatalytic $\\mathrm{H}_{2}$ -production activity. The origin of this high activity is studied by both experimental techniques and theoretical investigations. Moreover, the general function of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs as an active co-catalyst for other photocatalysts is also confirmed, illustrating the considerable potential of MXene family materials to replace rare and costly $\\mathrm{Pt}$ in photocatalysis/photoelectrocatalysis. \n\n# Results \n\nTheoretical exploration of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ MXene as a co-catalyst. To explore the possibility of using $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene as a highly efficient and low-priced co-catalyst to promote $\\mathrm{H}_{2}$ production, we have conducted a series of theoretical investigations based on DFT calculations. A highly active co-catalyst can not only rapidly extract photo-induced electrons from a photocatalyst to its surface, but also efficiently catalyse the $\\mathrm{H}_{2}$ evolution on its surface, by using those electrons6. Herein, we first focus on the $\\mathrm{H}_{2}$ evolution activity to evaluate whether $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ is an excellent candidate. Usually, the overall $\\mathrm{H}_{2}$ evolution reaction (HER) pathway can be summarized by a three-state diagram, composed of an initial state $\\mathrm{H}^{+}+e^{-}$ , an intermediate adsorbed $\\mathrm{H^{*}}$ , and a final product $\\boldsymbol{\\mathscr{z}}_{2}\\mathbf{H}_{2}$ (refs 19,20). The Gibbs free energy of the intermediate state, $|\\Delta G_{\\mathrm{H^{*}}}|,$ is regarded as a major indicator of the HER activity for various catalysts. The most desirable value for $|\\Delta G_{\\mathrm{H^{*}}}|$ should be zero20. For example, the highly active and well-known HER catalyst, Pt, shows a near-zero value of $\\Delta G_{\\mathrm{H^{*}}}\\approx-0.09\\mathrm{eV}$ (refs 21,22). Thus, we performed DFT studies to calculate $\\Delta G_{\\mathrm{H^{*}}}$ for atomic $\\mathrm{~H~}$ adsorption on the surface of O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , respectively. Their structural models are displayed in Fig. 1a and Supplementary Figs 1,2, respectively. Pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ exhibits a largely negative $\\Delta G_{\\mathrm{H^{*}}}=-0.927\\:\\mathrm{eV}$ (Supplementary Fig. 3a), suggesting too strong chemical adsorption of $\\mathrm{H^{*}}$ on its surface. Meanwhile, a largely positive $\\Delta G_{\\mathrm{H^{*}}}=1.995\\mathrm{eV}$ is observed for F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (Supplementary Fig. 3b), indicating very weak $\\mathrm{H^{*}}$ adsorption and easy product desorption. Unfortunately, both conditions are unfavourable for HER. Surprisingly, O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ shows a near-zero value of $|\\Delta\\bar{G_{\\mathrm{H^{*}}}}|=\\bar{0}.00283\\mathrm{eV}$ at its optimal $\\mathrm{H^{*}}$ coverage $\\left(\\theta=1/2\\right)$ (Fig. 1b; Supplementary Table 1). This value is even much lower than that of $\\mathrm{Pt}$ or highly active earth-abundant HER catalysts (Fig. 1c), for example, $\\ensuremath{\\mathrm{MoS}}_{2}$ $(\\Delta G_{\\mathrm{H^{*}}}=0.08\\mathrm{eV})^{23}$ or $\\mathrm{WS}_{2}$ ( $\\Delta G_{\\mathrm{H^{*}}}=0.22\\mathrm{eV})^{23}$ , clearly indicating the remarkable HER activity of O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ from the viewpoint of thermodynamics. \n\nApart from extraordinary HER activity, a highly active cocatalyst must efficiently extract the photo-induced electrons from photocatalysts and deliver them to its surface, which requires appropriate electronic band structure and excellent conductivity. Hence, we employ DFT calculations to determine the band structures of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}.$ , F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , respectively. As shown in Supplementary Fig. $^{4\\mathrm{a},\\mathrm{b}}$ , pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ exhibits metallic characteristics with substantial electronic states crossing the Fermi level. In comparison, F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (Supplementary Fig. 4c,d) and O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (Fig. 1d,e) exhibit decreased numbers of states at the Fermi level, indicating their lower conductivities. Nevertheless, the continuous electronic states crossing Fermi level for $\\mathrm{~F~}$ -terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ indicate that their conductivities are still good. Hence, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ retains its outstanding electrical conductivity, even after decoration with numerous functionalities, implying its exceptional capability to transport electrons. We believe this unique merit of MXene renders it a superior co-catalyst outperforming its counterparts, such as graphene and carbon nanotubes, which suffer obvious conductivity loss after their termination with $-\\mathrm{O}_{\\mathrm{i}}$ , –OH and $-\\mathrm{COO^{-}}$ (ref. 11). Furthermore, the Fermi levels $(E_{\\mathrm{F}})$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ are calculated to be $-0.05\\mathrm{V}$ , $1.88\\mathrm{V}$ and $0.15\\mathrm{V}$ versus SHE, respectively. Among them, O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ displays the most positive value of $E_{\\mathrm{F}},$ implying its strongest capacity to accept photo-induced electrons from semiconductor photocatalysts. \n\nOn the basis of the above theoretical explorations, it can be concluded that both pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{~F~}$ -terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ are not eligible candidates due to their inefficient HER activity and unfavourable $E_{\\mathrm{F}}$ . In contrast, O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ is predicted to be a highly promising co-catalyst, given its outstanding HER activity, excellent metallic conductivity and desirable $E_{\\mathrm{F}}$ . \n\n![](images/34fd1d588b4d13f72dd165a16a35e1bb6f94f4631df6c7744e9c38ac3e7c3bd8.jpg) \nFigure 1 | Density function theory calculation studies of O-terminated $\\pmb{\\Tilde{\\mathbf{I}}\\Tilde{\\mathbf{I}}_{3}\\pmb{\\ C}_{2}}.$ (a) The side and top views of the structure model for a $4\\times4\\times1$ O-terminated $T_{{\\dot{1}}_{3}}C_{2}$ supercell. Grey, red and cyan spheres denote C, O and $\\bar{\\mathsf{T i}}$ atoms, respectively. (b) The calculated free-energy diagram of HER at the equilibrium potential $\\langle U=0\\vee,$ ) on the surface of a $2\\times2\\times1$ O-terminated $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ supercell at different $\\mathsf{H}^{\\star}$ coverage $(1/8,1/4,3/8,1/2,5/8$ and $3/4$ ) conditions (the side and top views of a $2\\times2\\times1$ O-terminated $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ supercell at $\\mathsf{1/2H^{\\star}}$ coverage are shown in the inset). (c) The calculated free-energy diagram of HER at the equilibrium potential $\\left(\\mathsf{U}=0\\mathsf{V}\\right)$ on the surface of a $2\\times2\\times1$ O-terminated $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ supercell at $1/2{\\mathsf{H}}^{\\star}$ coverage, and the referenced Pt (ref. 21,22) ${M o S}_{2}$ (ref. 23), and ${\\sf W S}_{2}$ (ref. 23). (d) The calculated band structure of O-terminated $T i_{3}C_{2}$ . (e) The total density of states (TDOS) and partial density of states (PDOS) for $\\textsf{O}$ -terminated $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ . \n\nDesign and synthesis of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ -incorporated CdS. The above theoretical investigations provide clear guidance to synthesize $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ co-catalyst and couple it with photocatalysts. Firstly, we need to obtain $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ terminated with abundant functionalities instead of pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . Then, we should minimize and maximize the number of $-\\mathrm{F}$ and $^{-0}$ terminations on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , respectively. To achieve this goal, as presented in Supplementary Fig. 5, $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (MAX phase) powders were firstly etched by HF to remove Al species, producing exfoliated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ ( $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -E) with an accordion-like architecture (Supplementary Fig. 6a). During the etching process, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -E was spontaneously decorated with substantial functionalities ( $-\\mathrm{OH}$ , $\\mathrm{-F}$ and $-\\mathrm{O}$ on its surface, giving rise to its exceptional hydrophilicity. The transformation from $\\mathrm{\\bar{Ti}}_{3}\\mathrm{AlC}_{2}$ to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ is firmly evidenced by the obvious shift of the (002) and (004) X-ray diffraction (XRD) peaks to lower degrees, and the disappearance of the strongest diffraction peak of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ at $39^{\\circ}$ (Supplementary Fig. 7)24. To further increase the surface area and functionalities of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{-E}$ was added to de-ionized water and subjected to strong ultra-sonication, during which many large $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{-}\\mathrm{E}$ sheets were cut into small pieces of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs. The resulting suspension was centrifuged at $10,000{\\mathrm{r.p.m}}$ . to remove the large $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ sheets and particles, leaving the small $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs in the supernatant (Supplementary Fig. 8a). The successful formation of $\\bar{\\mathrm{Ti}}_{3}\\mathrm{C}_{2}$ NPs is supported by the XRD pattern (Supplementary Fig. 7; Supplementary Note 1), high-angle annular dark-field (HAADF) image (Supplementary Fig. 8b), energy-dispersive X-ray spectra (EDX) elemental mapping images (Supplementary Fig. 8c–f), X-ray photoelectron spectroscopy (XPS) survey spectrum (Supplementary Fig. 9a), and high-resolution XPS spectra of Ti $2p$ , O 1s and F 1s (Supplementary Fig. ${\\mathfrak{g}}{\\mathfrak{b}},{\\mathfrak{c}},{\\bar{\\mathbf{d}}},$ ). The presence of abundant hydrophilic functionalities (–O, –OH and $\\mathrm{-F},$ ) on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs is supported by the high-resolution XPS spectrum of O 1s and F 1s (Supplementary Fig. $^{9\\mathrm{c},\\mathrm{d})}$ . Meanwhile, the ‘black’ colloid dispersion of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ exhibits a typical Tyndall effect (Supplementary Fig. 8a, inset), reasonably suggesting the formation of a homogeneous dispersion of $\\mathrm{Ti}_{3}\\bar{\\mathrm{C}}_{2}^{\\bar{}}$ NPs. The engineering of three-dimensional (3D) $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{-}\\mathrm{E}$ into zerodimensional (0D) $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs dramatically increased their surface area and functionalities, thus greatly favoring their intimate coupling with photocatalysts. \n\nThen, CdS was selected as the photocatalyst to couple with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}.$ , since its reported conduction band (CB) potential $\\bar{(}-0.7\\mathrm{V}$ versus $\\mathrm{SHE})^{25}$ is much more negative than the $E_{\\mathrm{{F}}}$ of O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ $\\mathrm{1.88V}$ versus SHE). Besides, to obtain the desired functionalities on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , a hydrothermal strategy is applied to integrate CdS with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs. So the $\\mathrm{-F}$ terminations can be replaced by $^{-0}$ or $-\\mathrm{OH}$ in the aqueous environment during hydrothermal treatment. The synthesis process is shown in Supplementary Fig. 10. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs were firstly introduced into $\\operatorname{Cd}(\\operatorname{Ac})_{2}$ aqueous solution, in which $\\operatorname{Cd}^{2+}$ cations were easily adsorbed on numerous -O terminations. Then, an organic sulfur source, thiourea, was added into the above suspension and coordinated with $\\operatorname{Cd}^{2+}$ . Finally, the resulting suspension was subjected to hydrothermal treatment. During this process, most of the $\\mathrm{-F}$ terminations on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs were replaced by $-\\mathrm{O}/\\mathrm{-OH}$ terminations, and thiourea molecules decomposed to gradually release $\\mathsf{S}^{2-}$ anions into the solution. These $\\mathsf{S}^{2-}$ anions were combined with the $\\operatorname{Cd}^{2+}$ cations adsorbed on the surface of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs, leading to the heterogeneous nucleation and growth of CdS NPs on $\\mathrm{\\bar{Ti}}_{3}\\mathrm{C}_{2}$ NPs. Meanwhile, the excessive $\\operatorname{Cd}^{2+}$ cations were also combined with these $S^{2-}$ anions, resulting in the homogeneous nucleation and growth of pure CdS NPs. Then both $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ nanocomposites and CdS NPs self-assembled to form a large cauliflower-structured $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ sub-microsphere (SMS), with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs intimately coupled. The nominal mass ratios of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ to CdS were 0, 0.05, 0.1, 2.5, 5 and $7.5\\mathrm{wt.\\%}$ , and the resulting samples were labelled as CT0, CT0.05, CT0.1, CT2.5, CT5 and CT7.5, respectively. The actual mass ratios of the synthesized samples were determined by inductively coupled plasma atomic emission spectrometry (ICP-AES) (Supplementary Table 2). \n\nChemical composition and morphology. The chemical composition and morphology of the as-prepared samples were thoroughly investigated. Firstly, their crystal structures were characterized by XRD. The XRD patterns (Supplementary Fig. 11a) confirm that all the samples are composed of hexagonal wurtzite-structured phase CdS (JCPDS No. 77-2306). A combination of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs with CdS did not affect the crystal structure of CdS, suggesting that the remarkable increase in photocatalytic activity is not caused by any crystal structure alteration in CdS. Instead, it should be attributed to the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs deposited on its surface. However, no diffraction peaks for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ are observed in Supplementary Fig. 11a, probably due to the low loading and high dispersion of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs on the surface of CdS. \n\nThe morphology and composition of the as-synthesized CT2.5 were further investigated by HAADF, EDX, high-resolution (HR)TEM, SEM and XPS techniques. The HAADF image of CT2.5 in Fig. 2a show that several NPs are deposited on the surface of CdS SMS, which is quite different from the smooth surface of pure CdS SMS (CT0) displayed in Supplementary Fig. $^{12\\mathrm{a},\\mathrm{b}}$ . The composition of these NPs was in situ studied by EDX and HRTEM. Firstly, three points of $\\mathrm{O}_{2}$ , $\\mathrm{O}_{3}$ and $\\mathrm{O}_{4}$ at these NPs were selected for EDX analysis, respectively. The results in Fig. 2b and Supplementary Fig. $^{13\\mathrm{b},\\mathrm{c}}$ exhibit that Ti peaks were found, while no Cd or S peaks were observed at $\\mathrm{O}_{2}$ , $\\mathrm{O}_{3}$ and $\\mathrm{O}_{4}$ , suggesting that these NPs are not CdS but Ti-containing material. The HRTEM image near the $\\mathrm{O}_{3}$ point (Fig. 2c) shows a heterointerface with lattice spacings of 1 and $0.36\\mathrm{nm}$ , which are assigned to the (002) plane of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (ref. 24) and (100) plane of CdS26, respectively. This result confirms the formation of $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ hetero-junction. Furthermore, the SEM image of $\\mathrm{CT}2.5$ in Fig. 2d shows a uniform SMS structure of $\\mathrm{CdS}/\\mathrm{\\bar{T}i}_{3}\\mathrm{C}_{2}$ with sizes of ca. $400{-}500\\mathrm{nm}$ . A detailed observation in Fig. 2d suggests that $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ SMS has a cauliflower-structured morphology created by the self-assembly of many $\\mathrm{NPs}^{27}$ . The corresponding EDX spectrum in Fig. 2e indicates that CT2.5 contains Cd, S, Ti and C, which is consistent with the HRTEM image and EDX spectra. The above results support the establishment of intimate coupling between $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and CdS, implying the efficient interfacial photo-induced charge diffusion on visible-light irradiation7,28. Moreover, the high-resolution XPS spectrum of Ti $2p$ exhibits four deconvoluted peaks in Fig. 2f, corresponding to Ti–O $2p$ and Ti–C $2p^{24}$ , in agreement with the above HRTEM and EDX results. It should be noted that numerous $^{-0}$ terminations are present in CT2.5 (Fig. 2g), while the F content is negligible for CT2.5 (Fig. 2h), suggesting the successful replacement of $\\mathrm{-F}$ by $-\\mathrm{O}/\\mathrm{-OH}$ on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs after hydrothermal treatment. Thus, the ratio of $\\mathrm{~F~}$ to $\\mathrm{~O~}$ in $\\mathrm{CT}2.5$ is zero. \n\nSuper high photocatalytic $\\mathbf{H}_{2}$ -production performance. The photocatalytic $\\mathrm{H}_{2}$ -production activity of all the as-prepared samples was examined in $18\\ \\mathrm{vol}.\\%$ lactic acid aqueous solution under visible-light irradiation $(\\lambda\\ge420\\mathrm{nm})$ . Excitingly, the coupling of $\\mathrm{Ti}_{3}\\bar{\\mathrm{C}}_{2}$ NPs with CdS indeed leads to a remarkable enhancement in the photocatalytic activity. As displayed in Fig. 3a, pristine CdS (CT0) shows a very low photocatalytic activity of $105\\upmu\\mathrm{molh}^{-1}\\mathbf{g}^{-1}$ . In contrast, the loading of a small amount of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs $(0.05\\mathrm{wt.\\%})$ obviously improves the photocatalytic activity of $\\mathrm{CT0.05}$ to $993\\upmu\\mathrm{molh}^{-1}\\mathbf{g}^{-1}$ With increasing amount of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs, the photocatalytic activity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -loaded CdS is gradually enhanced. Surprisingly, a super high photocatalytic $\\mathrm{H}_{2}$ -production activity of $1\\breve{4,342}\\upmu\\mathrm{mol}\\mathrm{\\hat{h}}^{-1}\\mathrm{g}^{-1}$ is achieved on CT2.5, exceeding that of CT0 by an amazing factor of 136.6. In comparison, for the same loading $(2.5\\mathrm{wt.\\%})$ and experimental conditions, NiS, Ni and $\\ensuremath{\\mathrm{MoS}}_{2}$ -loaded CdS SMS (NiS–CdS, Ni–CdS and $\\mathrm{MoS}_{2}\\mathrm{-CdS})$ exhibit lower photocatalytic activities of 12,953, 8,649 and $6,183\\upmu{\\mathrm{mol}}\\mathrm{h}^{-1}{\\overset{.}{\\mathbf{g}}}^{-1}$ , respectively (Fig. 3a). Besides, CT2.5 also shows higher quantum efficiency $(40.1\\%$ at $420\\mathrm{nm}$ ) than the other noble-metal-free CdS-based photocatalysts reported to date, such as: Ni/CdS, $\\mathrm{Ni(OH)}_{2}/\\mathrm{CdS}.$ $\\mathrm{\\bar{Ni}}_{2}\\mathrm{P/CdS}.$ , CoP/CdS, graphene oxide/CdS and $\\mathrm{MoS}_{2}/\\mathrm{CdS}$ (Supplementary Table 3). On the basis of the above experimental data and literature, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs have proven to be one of the most active earth-abundant co-catalysts. Furthermore, $\\mathrm{CT}2.5$ even displays higher activity than $2.5\\mathrm{wt.\\%}$ Pt loaded CdS SMS (Pt–CdS, $10\\mathrm{,978\\upmumolh^{-1}g^{-1}}$ , even though Pt is widely accepted as the most active co-catalyst promoting $\\mathrm{H}_{2}$ production. The HAADF image, EDX elemental mapping images, TEM and HRTEM images of $\\mathrm{\\bar{P}t-C d S}$ (Supplementary Fig. 14a–f) imply that Pt is homogeneously decorated on CdS in the form of clusters (Supplementary Note 2). The size of $\\mathrm{Pt}$ in $\\mathrm{Pt\\mathrm{-}C d S}$ is much smaller than that of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ in CT2.5, suggesting more active sites exposed on $\\mathrm{Pt}$ than those on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ for the same loading. In this case, the superior activity of CT2.5 should be ascribed to the much stronger combination between CdS and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ established during hydrothermal treatment, which greatly facilitates the rapid interfacial charge transfer7,28. This result also highlights the huge potential of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs as a high performance and low-cost cocatalyst to replace Pt. However, further increase in the loading of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs leads to the drastic deterioration of photocatalytic activity as reported in previous works6,7,28,29. This is due to the excessive $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs covering the surface active sites and impeding the light absorption of CdS. Nevertheless, CT7.5 still retains a photocatalytic activity of $2{,}707\\upmu\\mathrm{molh}^{-1}\\mathbf{g}^{-1}$ , much higher than that of CT0. In addition, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs show no activity toward $\\mathrm{H}_{2}$ production under visible-light irradiation, further supporting its role as a co-catalyst rather than a photocatalyst. \n\n![](images/ba2b6abf560bb0ca02fd1c3bebd52848baea46dcaee837c49b61799f99725af8.jpg) \nFigure 2 | Morphology and chemical composition of CT2.5. (a) A typical high-angle annular dark-field (HAADF) image of CT2.5 and the six different points $(\\mathsf{O}_{1},\\mathsf{O}_{2},\\mathsf{O}_{3},\\mathsf{O}_{4},\\mathsf{O}_{\\sharp}$ and $\\mathsf{\\Omega}_{0_{6}})$ for EDX analysis. (b) The EDX spectrum at $\\mathsf{O}_{3}$ point in a. (c) The high-resolution TEM image near ${{\\mathrm O}_{3}}$ point in a. (d,e) A typical SEM image of CT2.5 and its corresponding EDX spectrum. (f–h) The high-resolution XPS spectra of Ti $2p$ , O 1s and F 1s for CT2.5. Scale bars, $200\\mathsf{n m}$ (a), $2{\\mathsf{n m}}$ (c) and $500\\mathsf{n m}$ (d). \n\nThe stability of the optimized CT2.5 was further evaluated by performing the photocatalytic experiments under the same reaction conditions for seven cycles. No significant deterioration of photocatalytic activity was observed for CT2.5 during seven successive cycling tests for $\\mathrm{H}_{2}$ production (Supplementary Fig. 15a). A comparison of the crystalline phase (Supplementary Fig. 11a), morphology and size (Fig. 2a and \n\n![](images/853a3a4441593700fb91789ee47d1f179a021a33453afb9ae651f9d5a3e954cb.jpg) \nFigure 3 | Photocatalytic performance and spectroscopy/(photo)electrochemical characterization. (a) A comparison of the photocatalytic ${\\sf H}_{2}$ -production activities of CT0, CT0.05, CT0.1, CT2.5, CT5, CT7.5, $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ NPs, Pt–CdS, NiS–CdS, Ni–CdS and ${M o S}_{2}$ –CdS. The error bars are defined as s.d. (b) Ultraviolet-visible diffuse reflectance spectra of CT0, CT2.5 and $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ -E. The insets show the colours of all the samples as well as the ultraviolet-visible absorbance spectrum and picture of the $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ NPs aqueous solution. (c) Time-resolved PL spectra of CT0 and CT2.5. (d) EIS Nyquist plots of CT0 and CT2.5 electrodes measured under the open-circle potential and visible-light irradiation in $0.5{\\ensuremath{M}}$ potassium phosphate buffer $\\langle\\mathsf{p H}=7\\rangle$ solution. The inset shows the transient photocurrent responses of CT0 and CT2.5 electrodes in $0.2M$ $\\mathsf{N a}_{2}\\mathsf{S}+0.04\\mathsf{M}$ ${\\mathsf N}{\\mathsf a}_{2}{\\mathsf S}{\\mathsf O}_{3}$ mixed aqueous solution under visible-light irradiation. \n\nSupplementary Fig. 15b) between the original and used CT2.5 (CT2.5-A) shows no apparent alterations in CT2.5-A, which is in accordance to its repeated high activity. \n\nLight-harvesting capability. To investigate the origin of the remarkable activity of CT2.5, its properties governing the three major processes in photocatalytic reactions (that is, light absorption, charge separation and transfer, and surface redox reactions $^{1,4-6}$ ) were thoroughly characterized. Firstly, the lightharvesting capability of $\\mathrm{CT}2.5$ was measured by the ultravioletvisible diffuse reflectance spectra. As displayed in Fig. 3b, the light absorption of CT2.5 is obviously increased throughout the entire region of $350\\mathrm{-}800\\mathrm{nm}$ , due to the black colour of loaded $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs (Fig. 3b, inset). Similar phenomenon is also observed for CT0.05, CT0.1, CT5 and CT7.5 (Supplementary Fig. 11b). The ultraviolet-visible absorbance spectrum of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs aqueous solution shows no obvious absorption edge in the $250\\mathrm{-}800\\mathrm{nm}$ region, implying the metallic nature of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs. Furthermore, no apparent shift in the absorption edge of CT2.5 is observed, indicating that Ti, C, F or O element is not doped into the crystal structure of CdS, which is in agreement with the above XRD data. To investigate whether the increased visible-light absorption originating from $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs enhanced the photocatalytic activity of CT2.5, a $560\\mathrm{nm}$ light filter was employed to cutoff any irradiation light with wavelength shorter than $557\\mathrm{nm}$ (the onset absorption edge of CdS in CT2.5), while other experimental conditions were kept identical. Under such conditions, CT2.5 shows no activity for $\\mathrm{H}_{2}$ production, indicating that the enhanced visible-light absorption arising from $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs is unlikely to promote the activity enhancement observed for CT2.5. \n\nCharge separation and transfer. To study the charge-carrier separation and transfer efficiency in CT2.5, a series of characterization techniques including time-resolved and steady-state photoluminescence (PL) spectra, electrochemical impedance spectra (EIS) and transient photocurrent (TPC) response were used. As shown in Fig. 3c, in comparison to CT0, CT2.5 shows an increased short $(\\tau_{1})$ , long $(\\tau_{2})$ and intensity-average $\\mathbf{\\eta}(\\tau)$ PL lifetimes, indicating that the deposition of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ on CdS can effectively suppress the charge recombination and elongate the lifetime of charge carriers. The enhanced charge separation efficiency is further confirmed by the quenched emission peak around $560\\mathrm{nm}$ for CT2.5 (Supplementary Fig. 16). Furthermore, the surface and bulk charge-transfer efficiencies were investigated by the EIS and TPC density measurements, respectively. As indicated in Fig. 3d, CT2.5 shows a much smaller semicircle diameter and a much lower interfacial charge-transfer resistance than those of CT0 in potassium phosphate buffer solution $(\\mathrm{pH}=7)$ under visible-light irradiation, suggesting the apparent enhancement of interfacial charge-carrier transfer on the surface of $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . On the other hand, to study the bulk charge transfer in CT0 and CT2.5, the TPC density measurements were conducted. $\\mathrm{Na}_{2}\\mathrm{S}$ and ${\\ N a}_{2}{\\ S}{\\ O}_{3}$ were applied as electrolytes to rapidly capture the photo-induced holes on the surface of CT0 and CT2.5. Thus, these hole scavengers were supposed to eliminate the surface charge recombination on $\\mathrm{CT}0$ and CT2.5. In such a case, the observed enhancement in the TPC density on loading of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (Fig. 3d, inset) directly reflects an improved charge separation efficiency in the bulk of $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . \n\nTo gain further insights into the charge separation and transfer mechanism in CT2.5, the CB and valence band (VB) potentials of CdS in CT2.5 were determined to be $-0.79\\mathrm{V}$ and $1.54\\mathrm{V}$ versus SHE, respectively, by a combination of Mott-Schottky and Tauc plots (Supplementary Fig. 17a,b). Hence, on light irradiation, the photo-induced electrons on the CB of CdS $\\mathrm{\\Delta}^{\\prime}E_{\\mathrm{CB}}=-0.79\\mathrm{\\DeltaV}$ versus SHE) in CT2.5 can promptly migrate to O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs, which rapidly shuttle these photoinduced electrons to their surface active sites, because of their low $E_{\\mathrm{{F}}}$ position and excellent conductivity. Therefore, in the case of CT2.5, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ can serve as an electron trapping and shuttling site not only to suppress the charge recombination on the surface of CdS, but also to promote the charge separation and transfer in the bulk of CdS, which is consistent with the above results. \n\nSurface catalytic redox reactions. Following the charge separation and transfer, the last step in photocatalytic $\\mathrm{H}_{2}$ production includes the surface redox reactions catalysed by the reactive sites on CT2.5. Therefore, to study the efficiency of the last step, we determined the specific surface area and pore volume of all the samples by $\\Nu_{2}$ sorption analysis (Supplementary Fig. 18a,b). As shown in Supplementary Table 2, an initial increase in the loading of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs up to $1.89\\mathrm{wt.\\%}$ (CT0.05, CT0.1 and CT2.5) caused a gradual enlargement in the specific surface area of the $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ composites. However, further increase in the loading of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs resulted in a noticeable decrease in surface area to 3.8 and $\\overline{{3.7}}\\mathrm{m}^{2}\\mathrm{g}^{-1}$ for CT5 and CT7.5, respectively, despite that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs exhibit a large surface area of $120.1\\mathrm{{m}}^{2}\\mathrm{{g}}^{-1}$ (Supplementary Table 4). This decrease is observed at higher loadings of $\\mathrm{Ti}_{3}\\mathrm{\\dot{C}}_{2}$ NPs because of their tendency to aggregate on the surface of CdS SMS. Hence, the highest surface area of $\\mathrm{CT}2.5$ among all the $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ composites suggests the existence of abundant active sites on its surface, which greatly promote the surface redox catalytic reactions. Moreover, the polarization curves of CT0, CT2.5 and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs (Supplementary Fig. 19) indicate that the presence of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs on the surface of CdS can greatly improve the HER activity of CT2.5, and consequently, contribute to its enhanced photocatalytic $\\mathrm{H}_{2}$ production. \n\nTo further reveal the differences in HER mechanistic behaviour between $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and other state-of-the-art earth-abundant HER catalysts, for example, $\\mathrm{MoS}_{2}$ and $\\mathrm{WS}_{2}.$ , DFT calculations were conducted to study the effect of $\\mathrm{H}_{2}$ coverage on $\\Delta G_{\\mathrm{H^{\\ast}}}$ for O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . Fig. 1b shows that one O-terminated $\\mathrm{Ti}_{3}\\mathrm C_{2}$ unit cell tends to allow for adsorption of four $\\mathrm{H^{*}}$ due to its smallest $|\\Delta G_{\\mathrm{H}^{*}}|$ (Supplementary Note 3), corresponding to the unsaturated $\\mathrm{H^{*}}$ coverage of $\\theta\\overset{\\cdot}{=}1/2$ . The $|\\Delta G_{\\mathrm{H}^{*}}|$ values for the adsorption of $\\mathrm{H^{*}}$ on O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ at $\\theta$ values below $1/2$ (that is, $\\theta=1/8$ , 1/4 and $3/8$ ) are relatively low (Supplementary Table 1). However, the further increase of $\\mathrm{H^{*}}$ coverage results in a rapid increase of $|\\Delta G_{\\mathrm{H}^{*}}|$ and deterioration of HER activity (Fig. 1b; Supplementary Table 1). Nevertheless, O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ still possesses a relatively large number of HER active sites considering its large surface with numerous active sites. In comparison, the HER active sites of well-known $\\mathbf{MoS}_{2}$ and $\\mathrm{WS}_{2}$ are only located at the edge positions, while all the sites in the basal plane are inactive30, suggesting the superiority of this newly developed O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . \n\nPhotocatalytic $\\mathbf{H}_{2}$ -production mechanism and discussion. To gain an insight into the influence of intrinsic properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ on the photocatalytic activity of the $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ composite, a series of experiments were designed and conducted. Firstly, the effect of co-catalyst’s surface area on the activity was studied. Co-catalysts $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -E, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}{-}5000$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs with different sizes (Supplementary Figs 6a, 8a and 20) and corresponding surface areas (Supplementary Table 4) were respectively coupled with CdS at the same loading $(2.5\\mathrm{wt.\\%})$ under identical hydrothermal conditions. As shown in Fig. 4a, loading $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -E, $\\mathrm{Ti}_{3}\\mathrm{\\dot{C}}_{2}$ -5000 and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs with increasing surface area leads to gradually enhanced photocatalytic activities. This is because the smaller size and larger number of exposed active sites of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ not only result in stronger coupling with CdS, but also assure better access to reactants. Secondly, the influence of functionalities of co-catalyst on the activity of $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ was investigated. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs were subjected to a hydrothermal treatment to reduce the number of $\\mathrm{-F}$ terminations. The surface atomic ratio of F to $\\mathrm{~O~}$ , estimated by XPS analysis, for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs and hydrothermally treated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs (HT- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs) are $20.6\\%$ and $8.0\\%$ , respectively. This implies that a large number of the -F terminations were exchanged into $-\\mathrm{O}/\\mathrm{-OH}$ terminations for HT- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs during hydrothermal treatment. Then $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs and $\\mathrm{HT}{\\cdot}\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs were mechanically mixed with CT0 at the same loading $(2.5\\mathrm{wt.\\%})$ , respectively. Figure 4b displays that HT- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ ${\\mathrm{NPs}}$ induce a higher photocatalytic activity of $1,527\\upmu\\mathrm{molh}^{-1}\\mathbf{g}^{-1}$ than $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs $(\\mathbf{\\dot{l}},105\\upmu\\mathrm{molh}^{-1}\\mathbf{g}^{-1})$ , even though the surface area of HT- $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs $(56.7\\mathrm{m}^{2}\\mathrm{g}^{-1}) $ is much lower than that of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs $(1\\bar{2}0.\\bar{1}\\mathrm{m}^{2}\\mathrm{g}^{-1})$ as shown in Supplementary Table 4. The reason for this is that the replacement of $\\mathrm{-F}$ by $-\\mathrm{O}/\\mathrm{-OH}$ on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs increases the density of effective active sites 1 $_\\mathrm{-O}$ terminations), despite the decreased surface area after hydrothermal treatment. This result coincides with the above DFT calculation data of $\\Delta G_{\\mathrm{H^{*}}}$ on O-terminated and F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . \n\nOn the basis of the above experimental results and theoretical calculations, a photocatalytic mechanism illustrating the surprisingly high photocatalytic $\\mathrm{H}_{2}$ -production activity of $\\mathrm{CT}2.{\\bar{5}}$ is proposed in Fig. 4c,d. Since the original $E_{\\mathrm{F}}$ of $n$ -type CdS (slightly lower than its CB position of $-0.91\\mathrm{V}$ versus SHE) is much more negative than the original $E_{\\mathrm{{F}}}$ of O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ $\\mathrm{1.88V}$ versus SHE), the intimate contact between CdS and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ in $\\mathrm{CT}2.5$ leads to the electron transfer from CdS to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (Supplementary Note 4), accompanied by the rise of $E_{\\mathrm{F}}$ for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ above the hydrogen evolution potential $(0.00\\mathrm{V}$ versus SHE) and the equilibrium of $E_{\\mathrm{{F}}}$ in $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ system. The similar phenomenon was reported by Jakob et al.31. Moreover, the CB position of CdS in $\\mathrm{CT}2.5$ is also lowered to $-0.79\\mathrm{V}$ versus SHE as confirmed in Supplementary Fig. 17a. Meanwhile, the immobilized positive charges remain in CdS near the $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ interface, where a space charge layer is formed, and the CB and VB of CdS are bent ‘upward’. Hence, a Schottky junction is formed between $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and CdS. On visible-light $(\\lambda\\ge420\\mathrm{nm})$ irradiation, the electrons are excited from the VB to the CB of CdS. Due to the reduced space charge layer thickness in nano-sized CdS primary particles, the ‘upward’ bending of the CB and VB for CdS is also limited (Fig. 4c)32. Hence, the photoinduced electrons in the CB can still migrate across the ‘upward’ bent CB to the Fermi level of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , leaving the photo-induced holes in the VB of CdS. As a result, the Schottky junction can serve as an electron trap to efficiently capture the photo-induced electrons, without impeding the electron transfer from CdS to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}.$ , as reported in previous works33–35. After being transferred to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , the photo-induced electrons are further rapidly shuttled to its surface, due to the excellent metallic conductivity. Finally, thanks to the outstanding HER capacity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , the protons in the aqueous solution are efficiently reduced by the photo-induced electrons at the abundant $^{-0}$ terminations on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ to evolve $\\mathrm{H}_{2}$ gas. Therefore, through tuning the number and type of surface functionalities on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , one can achieve the desirable $E_{\\mathrm{{F}}}$ and optimize the HER activity for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , which imposes a pronounced synergetic enhancement effect on the photocatalytic activity of the $\\mathrm{Cd}\\mathrm{{S}/T i_{3}C_{2}}$ system. \n\n![](images/ed513e8adb89ff194c7ef6e1b49ed383860837af314a1fd790488a6e9f9604d3.jpg) \nFigure 4 | Origin and mechanism of the enhanced photocatalytic performance in $\\mathbf{CdS}/\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ system. (a) The influence of the co-catalyst’s surface area on the photocatalytic activity. The error bars are defined as s.d. (b) The influence of the co-catalyst’s surface F to O atomic ratio on the photocatalytic activity. The error bars are defined as s.d. (c) The charge separation and transfer in the $\\mathsf{C d S}/\\mathsf{T i}_{3}\\mathsf{C}_{2}$ system under visible-light irradiation. Red and blue spheres denote photo-induced electrons and holes, respectively. (d) Proposed mechanism for photocatalytic ${\\sf H}_{2}$ production in the $\\mathsf{C d S}/\\mathsf{T i}_{3}\\mathsf{C}_{2}$ system under visible-light illumination. Green sphere denotes $\\mathsf{H}^{+}$ . White, grey, red, yellow, cyan and gold spheres denote H, C, O, S, Ti and Cd atoms, respectively. \n\nThe potential of this newly developed co-catalyst can be further exploited by a co-loading strategy. For instance, a $\\boldsymbol{p}$ -type semiconductor NiS could be simultaneously loaded with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs on CdS SMS. Surprisingly, the photocatalytic activity of $\\mathrm{CdS}/1\\mathrm{mol.}\\%\\mathrm{NiS}/2.5\\mathrm{wt.}\\%\\mathrm{Ti}_{3}\\dot{\\mathrm{C}}_{2}$ (CNT2.5) was further increased to $18,560\\upmu{\\mathrm{molh}}^{-1}{\\mathrm{g}}^{-1}$ as presented in Supplementary Fig. 21a. This is because the combination of $\\boldsymbol{p}$ -type NiS with $n$ -type CdS results in the formation of a $p{-}n$ junction, which promotes the transfer of photo-induced holes from CdS to NiS. Meanwhile, the photo-induced electrons are rapidly extracted from CdS to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ \n\nNPs for $\\mathrm{H}_{2}$ evolution. Therefore, the co-loading strategy imposes a strong synergistic effect on the charge separation and transfer in CNT2.5, which is confirmed by combined techniques of PL spectra (Supplementary Fig. 22a) and TPC response (Supplementary Fig. 22b). These results demonstrate the great potential of co-loading $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ with other co-catalysts to achieve synergetic enhancement of photocatalytic activity. \n\n$\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ as a versatile HER co-catalyst. To verify that the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs can act as a versatile HER co-catalyst on different photocatalysts, we mechanically mixed $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs with $\\mathrm{Zn}_{x}\\mathrm{Cd}_{1-}\\mathrm{\\bar{\\Omega}}_{X}$ and $Z\\mathrm{nS}$ respectively, and tested the photocatalytic $\\mathrm{H}_{2}$ -production activity of the resultant mixtures. As shown in Supplementary Figs 23a and $24\\mathsf{a}$ , a simple mechanical mixing of $\\mathrm{\\bar{Z}n_{0.8}C d_{0.2}\\bar{S}}$ (ZCS) and $Z\\mathrm{nS}$ with 1 wt. $\\%$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs increased the photocatalytic activities of the formed composites $\\mathrm{ZCS/Ti_{3}C_{2}}$ and $\\mathrm{ZnS/Ti}_{3}\\mathrm{C}_{2}$ by 386 and $217\\%$ , respectively, as compared with that of pristine ZCS and $Z\\mathrm{nS}$ . This exciting finding clearly shows an enormous potential in coupling $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs with a wide variety of semiconductor photocatalysts/photoelectrodes. \n\n# Discussion \n\nThis work demonstrates the great advantage of using modern theoretical tools for the design and synthesis of a novel MXene material, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs, as a highly active co-catalyst. On the basis of the theoretical predictions, we rationally employed the hydrothermal treatment to replace the $\\mathrm{-F}$ terminations on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ by $-\\mathrm{O}/\\mathrm{-OH}$ terminations, and coupled the pretreated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ with CdS to prepare a highly fused $\\mathrm{CdS}/\\mathrm{\\bar{T}i}_{3}\\mathrm{C}_{2}$ composite photocatalyst. Remarkably, this composite photocatalyst exhibited both super high visible-light photocatalytic activity $(14,342\\upmu\\mathrm{molh}^{-1}\\dot{\\bf g}^{-1})$ and apparent quantum efficiency 1 $40.1\\%$ at $420\\mathrm{nm}$ ), rendering it as one of the best noble-metalfree metal-sulfides photocatalysts. By combining the firstprinciple calculations and experimental methodology, we found that this unusual activity can be attributed to the synergetic effect of the highly efficient charge separation and migration from CdS to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs and the rapid $\\mathrm{H}_{2}$ evolution on numerous $^{-0}$ terminations present on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs. Successful application of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs as an efficient co-catalyst on $Z\\mathrm{n}S$ or ZCS excitingly confirms the versatile nature of this newly developed co-catalyst. This study opens a new area of utilizing this new generation of co-catalytic materials, MXene, to achieve highly efficient, steady and cost-effective solar water splitting based on semiconductor photocatalysts/photoelectrodes. \n\n# Methods \n\nMaterials synthesis. $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (MAX phase: $\\mathbf{M}_{n+1}\\mathbf{AX}_{n},$ where M indicates early transition metal, A indicates III A or IV A group element, and X indicates C or N) was synthesized following the approach reported by Peng et al.36. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -E was prepared by immersing $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ in HF solution. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs were fabricated by ultra-sonication of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -E in de-ionized water. The detailed synthesis procedures of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ , $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{-E}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs are described in Supplementary Methods. The $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ composites were fabricated by a one-step hydrothermal method summarized in Supplementary Methods. Pt–CdS was synthesized by in situ photodeposition of $2.5\\mathrm{wt.}\\%$ Pt on CT0 using $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ aqueous solution. Pt NPs loaded CT0 (Pt–CdS-1) was synthesized by mixing $2.5\\mathrm{wt\\%}$ Pt NPs with CT0 in ultrasonication followed by washing with ethanol and dried at $60^{\\circ}\\mathrm{C}$ . The morphology (Supplementary Fig. 25a) and photocatalytic activity (Supplementary Fig. 26) of Pt–CdS-1 are discussed in Supplementary Note 5. The above Pt NPs (Supplementary Fig. 27) was synthesized by a chemical-reduction method summarized in Supplementary Methods. NiS–CdS was synthesized following the previosuly reported method37 using CT0 as the substrate with $2.5\\mathrm{wt\\%}$ loading of NiS. Ni–CdS was synthesized by in situ photo-deposition of $2.5\\mathrm{wt\\%}$ Ni on CT0 using $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}$ aqueous solution. $\\mathbf{MoS}_{2}$ –CdS was synthesized by the previously reported method38 using CT0 as the substrate with $2.5\\mathrm{wt\\%}$ loading of $\\mathbf{MoS}_{2}$ . $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -5000 was synthesized following the preparation method of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs except that the final product was obtained by centrifugation at ${5,000}\\mathrm{r.p.m}$ . CT2.5-5000 was prepared following the preparation method of CT2.5 except that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -5000 was used instead of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs. HT- $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs were synthesized following the hydrothermal method for preparation of CT2.5 except that no $\\operatorname{Cd}(\\operatorname{Ac})_{2}$ was added. CT2.5-A was acquired after the repeated photocatalytic reaction of CT2.5 for $28\\mathrm{h}$ . Overall, $1\\mathrm{mol}\\%$ NiS loaded CT0 (CN) was synthezised by following the previously reported method39. CNT2.5 was synthesized by a one-step hydrothermal method as summarized in Supplementary Methods. The phase structures (Supplementary Fig. 21b) and optical properties (Supplementary Fig. 21c) of CN and CNT2.5 are discussed in Supplementary Note 6. ZCS was synthesized by the previously reported method39. $\\mathrm{ZCS/Ti_{3}C_{2}}$ was synthesized by mechanical mixing of the as-synthesized ZCS with $1\\mathrm{wt.\\%}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs. The phase structures (Supplementary Fig. 23b) and optical properties (Supplementary Fig. 23c) of ZCS and $\\mathrm{ZCS/Ti_{3}C_{2}}$ are discussed in Supplementary Note 7. ZnS was prepared by a hydrothermal approach as summarized in Supplementary Methods. $\\mathrm{ZnS/Ti}_{3}\\mathrm{C}_{2}$ was prepared by mechanical mixing of the as-synthesized $Z\\mathrm{n}S$ with $1\\mathrm{wt.\\%}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ NPs. The phase structures (Supplementary Fig. 24b) and optical properties (Supplementary Fig. 24c) of $Z\\mathrm{n}S$ and $\\mathrm{ZnS/Ti_{3}C_{2}}$ are discussed in Supplementary Note 8. \n\nPhysicochemical characterization. XRD patterns were acquired on a powder X-ray diffractometer (Miniflex, Rigaku) using $\\mathrm{Cu-K}\\mathfrak{a}$ radiation at $40\\mathrm{kV}$ and $15\\mathrm{mA}$ . SEM images and EDX spectra were collected on FEI Quanta 450 at an accelerating voltage of $10\\mathrm{kV}$ . HAADF, TEM, HRTEM images and EDX were performed by utilizing a JEM-2100F electron microscope (JEOL, Japan). XPS measurements were conducted using an Axis Ultra (Kratos Analytical, UK) XPS spectrometer equipped with an Al $\\mathtt{K}\\upalpha$ source $\\cdot1,486.6\\mathrm{eV},$ ). The F/O atomic ratios in all the $\\mathrm{CdS}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ composites were examined by XPS technique (Supplementary Fig. 28) and discussed in Supplementary Note 9. The Brunauer–Emmett–Teller specific surface areas $(S_{\\mathrm{BET}})$ and pore volume (PV) of the samples were evaluated by $\\Nu_{2}$ adsorption on a Tristar II 3020 gas adsorption apparatus (Micromeritics, USA). Ultraviolet-visible diffuse reflectance spectra were collected for the drypressed disk samples with an ultraviolet-visible spectrophotometer (UV2600, Shimadzu, Japan) using $\\mathrm{BaSO_{4}}$ as the reflectance standard. PL spectra were \n\nrecorded on a RF-5301PC spectrofluorophotometer (Shimadzu, Japan) at room temperature. Time-resolved PL decay curves were obtained on a FLS920 fluorescence lifetime spectrophotometer (Edinburgh Instruments, UK) under the excitation of $365\\mathrm{nm}$ and probed at $460\\mathrm{nm}$ . The actual chemical compositions of the assynthesized samples were measured by ICP-AES using an Optima 4300 DV spectrometer (PerkinElmer) (Supplementary Table 2). \n\nTheoretical calculations. The DFT calculations were carried out by using the Vienna ab initio simulation package $(\\mathrm{VASP})^{40,41}$ . The exchange-correlation interaction is described by generalized gradient approximation (GGA) with the Perdew–Burke–Ernzerhof (PBE) functional42. Van der Waals correction was applied in all calculations. The energy cutoff was set to $500\\mathrm{eV}$ . The Brillouin zone was sampled by a Monkhorst-Pack $9\\times9\\times1$ K-point grid. The fully relaxed lattice constants of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ monolayers are 3.08, 3.01 and $3.0\\dot{2}\\mathring{\\mathrm{A}}$ respectively. The models of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ , O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ or F-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ in $2\\times2\\times1$ supercells with a $k$ -point of $5\\times5\\times1$ grid in reciprocal space are used to identify the HER activity sites. HSE06 calculations43,44 employing VASP are performed to get the exact band structures. The band gap is zero. The further calculation details of the Gibbs free energy of the absorption of atomic H, the Fermi level positions and the surface Pourbaix diagrams can be found in Supplementary Methods. The surface Pourbaix diagram (Supplementary Fig. 29) of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ is analysed and discussed in Supplementary Note 10. The excellent conductivity of O-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ at different $\\mathrm{~H~}$ coverages (Supplementary Fig. 30) is confirmed in Supplementary Note 11. \n\nPhotocatalytic $H_{2}$ -production test. The experimental measurements of photocatalytic $\\mathrm{H}_{2}$ production were carried out in a $100~\\mathrm{ml}$ Pyrex flask (openings sealed with silicone rubber septum) at room temperature and atmospheric pressure. A 300 W Xenon arc lamp with an ultraviolet-cutoff filter ( $\\lambda\\geq420\\mathrm{nm})$ was utilized as a visible-light source to trigger the photocatalytic reaction. The focused intensity on the flask was ca. $80\\mathrm{mW}\\mathrm{cm}^{-2}$ . Typically, $20\\mathrm{mg}$ of the photocatalyst was suspended by constant stirring in $80\\mathrm{ml}$ of mixed aqueous solution containing $20\\mathrm{ml}$ of lactic acid $(88\\mathrm{\\vol\\%})$ ) and $\\dot{6}0\\mathrm{ml}$ of water. Before irradiation, the suspension was purged with Argon for $0.5\\mathrm{h}$ to remove any dissolved air and keep the reaction system under anaerobic conditions. Next, $0.2{\\mathrm{ml}}$ gas was intermittently sampled through the septum, and $\\mathrm{H}_{2}$ content was analysed by gas chromatograph (Clarus 480, PerkinElmer, USA, TCD, Ar as a carrier gas and $\\mathbf{\\dot{5}}\\mathbf{\\dot{A}}$ molecular sieve column). Before the experiment, all glassware was rinsed carefully with de-ionized water. The apparent quantum efficiency (QE) was measured under the identical photocatalytic reactions. Four low power $420\\mathrm{-nm}$ LEDs (3 W, Shenzhen LAMPLIC Science Co Ltd. China) were employed as the light sources to trigger the photocatalytic reactions. The focused intensity for every $420\\mathrm{-nm}$ LED was ca. $6\\mathrm{mW}\\mathrm{cm}^{-2}$ . The QE was calculated according to the following equation (1): \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\mathrm{QE}}(\\%{\\it\\Psi})=\\frac{\\mathrm{Number~of~reacted~electrons}}{\\mathrm{Number~of~incident~photons}}\\times100\\ ~}}\\\\ {{\\displaystyle~=\\frac{\\mathrm{Number~of~evolved~H_2molecules}\\times2}{\\mathrm{Number~of~incident~photons}}\\times100}}\\end{array}\n$$ \n\nElectrochemical and photoelectrochemical measurements. EIS measurements were performed on an electrochemical analyser (CHI650D instruments) in a standard three-electrode system utilizing the synthesized samples as the working electrodes, $\\mathrm{\\Ag/AgCl}$ (saturated KCl) as a reference electrode, and a Pt wire as the counter electrode. The polarization curves were recorded in the above-mentioned three-electrode system and the bias sweep range was from $-1.5$ to $-0.8\\mathrm{V}$ versus $\\mathrm{\\Ag/AgCl}$ with a step size of $0.005\\mathrm{V}.0.5\\mathrm{MNa}_{2}\\mathrm{SO}_{4}$ aqueous solution was utilized as the electrolyte. The Mott-Schottky plots were also measured using the same threeelectrode system over an alternating current (AC) frequency of $^{1,200\\mathrm{Hz}}$ in $0.5\\mathbf{M}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ aqueous solution. The EIS were recorded over a range from 1 to $2\\times10^{5}\\mathrm{Hz}$ with an AC amplitude of 0.02 V. $0.5\\mathrm{M}$ potassium phosphate buffer solution was used as the electrolyte. Photocurrent was measured in the same three-electrode system. A $300\\mathrm{W}$ Xenon light with an ultraviolet-cutoff filter $(\\lambda\\ge420\\mathrm{nm})$ was applied as the light source. $\\mathsf{0}.2\\mathrm{M}\\mathrm{Na}_{2}\\mathrm{S}$ and $0.04\\mathrm{M}\\mathrm{Na}_{2}\\mathrm{SO}_{3}$ mixed aqueous solution was used as the electrolyte. The working electrodes were synthesized as follows: $0.1\\mathrm{g}$ sample and $\\boldsymbol{0.03\\mathrm{g}}$ polyethylene glycol (PEG; molecular weight: 20,000) were ground with $0.5\\mathrm{ml}$ of ethanol to make a slurry. Then the slurry was coated onto a $2\\mathsf{c m}\\times1.5\\mathsf{c m}$ FTO glass electrode by the doctor blade approach. The obtained electrode was dried in an oven and heated at $623\\mathrm{K}$ for $0.5\\mathrm{h}$ under flowing $\\Nu_{2}$ . All working electrodes studied were kept at a similar film thickness of about $10{-}11\\upmu\\mathrm{m}$ . \n\nData availability. The data that support the findings of this study are available from the corresponding author on request. \n\n# References \n\n1. Hisatomi, T., Kubota, J. & Domen, K. Recent advances in semiconductors for photocatalytic and photoelectrochemical water splitting. Chem. Soc. Rev. 43, 7520–7535 (2014). \n\nsynergistically enhanced visible-light photocatalytic $\\mathrm{H}_{2}$ production. Energy Environ. Sci. 8, 3708–3717 (2015). \n3. Fujishima, A. & Honda, K. Electrochemical photolysis of water at a semiconductor electrode. Nature 238, 37–38 (1972). \n4. Chen, X., Shen, S., Guo, L. & Mao, S. S. Semiconductor-based photocatalytic hydrogen generation. Chem. Rev. 110, 6503–6570 (2010). \n5. Kudo, A. & Miseki, Y. Heterogeneous photocatalyst materials for water splitting. Chem. Soc. Rev. 38, 253–278 (2009). \n6. Ran, J. et al. Earth-abundant cocatalysts for semiconductor-based photocatalytic water splitting. Chem. Soc. Rev. 43, 7787–7812 (2014). \n7. Zong, X. et al. Enhancement of photocatalytic $\\mathrm{H}_{2}$ evolution on CdS by loading $\\ensuremath{\\mathrm{MoS}}_{2}$ as cocatalyst under visible light irradiation. J. Am. Chem. Soc. 130, 7176–7177 (2008). \n8. Hou, Y. et al. Bioinspired molecular co-catalysts bonded to a silicon photocathode for solar hydrogen evolution. Nat. Mater. 10, 434–438 (2011). \n9. Bi, W. et al. Molecular co-catalyst accelerating hole transfer for enhanced photocatalytic $\\mathrm{H}_{2}$ evolution. Nat. Commun. 6, 8647 (2015). \n10. Mahler, B., Hoepfner, V., Liao, K. & Ozin, G. A. Colloidal synthesis of 1T- $\\mathrm{WS}_{2}$ and $2\\mathrm{H}\\mathrm{-}\\mathrm{W}\\mathrm{S}_{2}$ nanosheets: applications for photocatalytic hydrogen evolution. J. Am. Chem. Soc. 136, 14121–14127 (2014). \n11. Hernandez, Y. et al. High-yield production of graphene by liquid-phase exfoliation of graphite. Nat. Nanotechnol. 3, 563–568 (2008). \n12. Brown, K. A. et al. Characterization of photochemical processes for $\\mathrm{H}_{2}$ production by CdS nanorod-[FeFe] hydrogenase complexes. J. Am. Chem. Soc. 134, 5627–5636 (2012). \n13. Wang, F. et al. A highly efficient photocatalytic system for hydrogen production by a robust hydrogenase mimic in an aqueous solution. Angew Chem. Int. Ed. 50, 3193–3197 (2011). \n14. Khazaei, M. et al. Novel electronic and magnetic properties of two-dimensional transition metal carbides and nitrides. Adv. Funct. Mater. 23, 2185–2192 (2013). \n15. Gao, Y. et al. Hydrothermal synthesis of $\\mathrm{TiO}_{2}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ nanocomposites with enhanced photocatalytic activity. Mater. Lett. 150, 62–64 (2015). \n16. Naguib, M. et al. New two-dimensional niobium and vanadium carbides as promising materials for Li-ion batteries. J. Am. Chem. Soc. 135, 15966–15969 (2013). \n17. Lukatskaya, M. R. et al. Cation intercalation and high volumetric capacitance of two-dimensional titanium carbide. Science 341, 1502–1505 (2013). \n18. Ghidiu, M. et al. Conductive two-dimensional titanium carbide ‘clay’ with high volumetric capacitance. Nature 516, 78–81 (2014). \n19. Nørskov, J. K., Bligaard, T., Rossmeisl, J. & Christensen, C. H. Towards the computational design of solid catalysts. Nat. Chem. 1, 37–46 (2009). \n20. Jiao, Y., Zheng, Y., Jaroniec, M. & Qiao, S. Z. Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions. Chem. Soc. Rev. 44, 2060–2086 (2015). \n21. Nørskov, J. K. et al. Trends in the exchange current for hydrogen evolution J. Electrochem. Soc. 152, J23–J26 (2005). \n22. Hinnemann, B. et al. Biomimetic hydrogen evolution: $\\ensuremath{\\mathrm{MoS}}_{2}$ nanoparticles as catalyst for hydrogen evolution. J. Am. Chem. Soc. 127, 5308–5309 (2005). \n23. Bonde, J. et al. Hydrogen evolution on nano-particulate transition metal sulfides. Farad. Discuss. 140, 219–231 (2009). \n24. Ma, T. Y., Cao, J. L., Jaroniec, M. & Qiao, S. Z. Interacting carbon nitride and titanium carbide nanosheets for high-performance oxygen evolution. Angew Chem. Int. Ed. 55, 1138–1142 (2016). \n25. Ran, J., Yu, J. & Jaroniec, M. $\\mathrm{Ni(OH)}_{2}$ modified CdS nanorods for highly efficient visible-light-driven photocatalytic $\\mathrm{H}_{2}$ generation. Green Chem. 13, 2708–2713 (2011). \n26. Chauhan, H. et al. Photoinduced ultrafast charge separation in colloidal 2-dimensional CdSe/CdS–Au hybrid nanoplatelets and corresponding application in photocatalysis. Nanoscale 8, 15802–15812 (2016). \n27. Rengaraj, S. et al. Cauliflower-like CdS microspheres composed of nanocrystals and their physicochemical properties. Langmuir 27, 352–358 (2011). \n28. Xiang, Q., Yu, J. & Jaroniec, M. Synergetic effect of $\\ensuremath{\\mathbf{MoS}}_{2}$ and graphene as cocatalysts for enhanced photocatalytic $\\mathrm{H}_{2}$ production activity of $\\mathrm{TiO}_{2}$ nanoparticles. J. Am. Chem. Soc. 134, 6575–6578 (2012). \n29. Chang, K. et al. $\\ensuremath{\\mathrm{MoS}}_{2^{\\prime}}$ /graphene cocatalyst for efficient photocatalytic $\\mathrm{H}_{2}$ evolution under visible light irradiation. ACS Nano 8, 7078–7087 (2014). \n30. Jaramillo, T. F. et al. Identification of active edge sites for electrochemical $\\mathrm{H}_{2}$ evolution from $\\mathbf{MoS}_{2}$ nanocatalysts. Science 317, 100–102 (2007). \n31. Jakob, M., Levanon, H. & Kamat, P. V. Charge distribution between UV-irradiated $\\mathrm{TiO}_{2}$ and gold nanoparticles: determination of shift in the Fermi level. Nano Lett. 3, 353–358 (2003). \n32. Osterloh, F. E. Inorganic nanostructures for photoelectrochemical and photocatalytic water splitting. Chem. Soc. Rev. 42, 2294–2320 (2013). \n33. Leung, D. Y. C. et al. Hydrogen production over titania-based photocatalysts. ChemSusChem. 3, 681–694 (2010). \n34. Yan, H. et al. Visible-light-driven hydrogen production with extremely high quantum efficiency on Pt-PdS/CdS photocatalyst. J. Catal. 266, 165–168 (2009). \n35. Yang, J., Wang, D., Han, H. & Li, C. Roles of cocatalysts in photocatalysis and photoelectrocatalysis. Acc. Chem. Res. 46, 1900–1909 (2013). \n36. Peng, Q. et al. Unique lead adsorption behavior of activated hydroxyl group in two-dimensional titanium carbide. J. Am. Chem. Soc. 136, 4113–4116 (2014). \n37. Zhang, J., Qiao, S. Z., Qi, L. & $\\mathrm{Yu,}$ J. Fabrication of NiS modified CdS nanorod $p{-}n$ junction photocatalysts with enhanced visible-light photocatalytic $\\mathrm{H}_{2}$ -production activity. Phys. Chem. Chem. Phys. 15, 12088–12094 (2013). \n38. Lang, D., Shen, T. & Xiang, Q. Roles of $\\mathbf{MoS}_{2}$ and graphene as cocatalysts in the enhanced visible-light photocatalytic $\\mathrm{H}_{2}$ production activity of multiarmed CdS nanorods. ChemCatChem. 7, 943–951 (2015). \n39. Ran, J., Zhang, J., Yu, J. & Qiao, S. Z. Enhanced visible-light photocatalytic $\\mathrm{H}_{2}$ production by $\\mathrm{Zn}_{x}\\mathrm{Cd}_{1-x}\\mathrm{S}$ modified with earth-abundant nickel-based cocatalysts. ChemSusChem. 7, 3426–3434 (2014). \n40. Kresse, G. & Furthmu¨ller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n41. Kresse, G. & Furthmu¨ller, J. Efficiency of $a b$ -initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comp. Mater. Sci. 6, 15–50 (1996). \n42. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n43. Paier, J. et al. Screened hybrid density functionals applied to solids. J. Chem. Phys. 124, 154709 (2006). \n44. Paier, J. et al. Erratum: Screened hybrid density functionals applied to solids. J. Chem. Phys. 125, 249901 (2006). \n\n# Acknowledgements \n\nThis work was supported financially by the Australian Research Council (ARC) through the Discovery Project programme (DP160104866, DP140104062 and DP130104459). \n\n# Author contributions \n\nJ.R. and G.G. contributed equally to this work. S.-Z.Q., F.-T.L. and J.R. conceived and designed the research. J.R. synthesized photocatalysts, conducted all the experiments and wrote the paper. T.-Y.M. gave suggestions on the synthesis of photocatalysts. G.G. performed the DFT calculations, assisted by A.D. All authors discussed and analysed the data. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Ran, J. et al. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene co-catalyst on metal sulfide photo-absorbers for enhanced visible-light photocatalytic hydrogen production. Nat. Commun. 8, 13907 doi: 10.1038/ncomms13907 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1016_j.mattod.2016.12.001", + "DOI": "10.1016/j.mattod.2016.12.001", + "DOI Link": "http://dx.doi.org/10.1016/j.mattod.2016.12.001", + "Relative Dir Path": "mds/10.1016_j.mattod.2016.12.001", + "Article Title": "On Maxwell's displacement current for energy and sensors: the origin of nullogenerators", + "Authors": "Wang, ZL", + "Source Title": "MATERIALS TODAY", + "Abstract": "Self-powered system is a system that can sustainably operate without an external power supply for sensing, detection, data processing and data transmission. nullogenerators were first developed for self-powered systems based on piezoelectric effect and triboelectrification effect for converting tiny mechanical energy into electricity, which have applications in internet of things, environmental/infrastructural monitoring, medical science and security. In this paper, we present the fundamental theory of the nullogenerators starting from the Maxwell equations. In the Maxwell's displacement current, the first term epsilon(0) partial derivative E/partial derivative t gives the birth of electromagnetic wave, which is the foundation of wireless communication, radar and later the information technology. Our study indicates that the second term partial derivative P/partial derivative t in the Maxwell's displacement current is directly related to the output electric current of the nullogenerator, meaning that our nullogenerators are the applications of Maxwell's displacement current in energy and sensors. By contrast, electromagnetic generators are built based on Lorentz force driven flow of free electrons in a conductor. This study presents the similarity and differences between pieozoelectric nullogenerator and triboelectric nullogenerator, as well as the classical electromagnetic generator, so that the impact and uniqueness of the nullogenerators can be clearly understood. We also present the three major applications of nullogenerators as micro/nullo-power source, self-powered sensors and blue energy.", + "Times Cited, WoS Core": 1592, + "Times Cited, All Databases": 1610, + "Publication Year": 2017, + "Research Areas": "Materials Science", + "UT (Unique WOS ID)": "WOS:000398895800016", + "Markdown": "# On Maxwell’s displacement current for energy and sensors: the origin of nanogenerators \n\nZhong Lin Wang1,2 \n\n1 School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0245, United States \n2 Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100083, China \n\nSelf-powered system is a system that can sustainably operate without an external power supply for sensing, detection, data processing and data transmission. Nanogenerators were first developed for selfpowered systems based on piezoelectric effect and triboelectrification effect for converting tiny mechanical energy into electricity, which have applications in internet of things, environmental/ infrastructural monitoring, medical science and security. In this paper, we present the fundamental theory of the nanogenerators starting from the Maxwell equations. In the Maxwell’s displacement current, the first term $\\epsilon_{\\mathbf{0}}\\frac{\\partial\\pmb{E}}{\\partial t}$ gives the birth of electromagnetic wave, which is the foundation of wireless communication, radar an@td later the information technology. Our study indicates that the second term $\\textstyle{\\frac{\\partial P}{\\partial t}}$ in the Maxwell’s displacement current is directly related to the output electric current of the nanogenerator, meaning that our nanogenerators are the applications of Maxwell’s displacement current in energy and sensors. By contrast, electromagnetic generators are built based on Lorentz force driven flow of free electrons in a conductor. This study presents the similarity and differences between pieozoelectric nanogenerator and triboelectric nanogenerator, as well as the classical electromagnetic generator, so that the impact and uniqueness of the nanogenerators can be clearly understood. We also present the three major applications of nanogenerators as micro/nano-power source, self-powered sensors and blue energy. \n\n# Self-powering \n\nInternet of things (IoT) is a technological drive that link moving things or any things around world on internet, such as shipping objects, cargo carriers and people etc. IoT needs widely distributed sensors for health monitoring, medical care, environmental protection, infrastructure monitoring and security. The power for driving each sensor is small, but the number of such units can be huge in the order of billions to trillions. The most conventional technology is using batteries, which may not be the solution for IoT with considering the limited life time, wide distribution, high maintenance cost and environmental issues. Most of the IoT would be impossible without making the devices self-powered by harvesting energy from the working environment so that the devices can operate sustainably. This was the original motivation for developing nanogenerators based self-powering systems [1,2]. \n\nIn the last half century, the road map of electronics has been focusing on miniaturization following the Moore’s law, for example, the number of devices on a chip doubles every 18 months, which is a commercial drive rather than a nature physics law. Solid state electronics has made it possible to integrate many components on a single chip. Integrated circuits set the foundation for improving the reliability, reducing size, increasing calculation speed, reducing power consumption and more. Secondly, the next revolutionary advance is the development of wireless/mobile communication technology. By conjunction with optical fiber based information transfer and computer science, the development of internet has changed every corner of the world. Thirdly, in the last decades, adding functionality to mobile devices has closely \n\n![](images/641247a1e897171b60732ec9efd5778cfd4bfafce9b4acf8d49300294ec83d51.jpg) \nFIGURE 1 \n\nA summary about the major development stages of microelectronics and communication technologies as well as newly arising fields. \n\nlinked to medical science and medical care of every one, so that one can fully utilize modern sensor technology for living in a more security and healthy world. But all of these advances can be hugely impacted if we can make the mobile electronics self-powered so that the systems can operate suitably and continuously without interruption. This is desperately needed for IoT because we mostly care about mobile objects. Regarding whatever technology, one thing is true, no electronics works without electric power! Therefore, the last huge drive is to make devices self-powered. The above discussions are thus classified and summarized in Fig. 1 as four major technological drives toward systems with: miniaturized integratebility; wireless portability, functionality, and self-powerbility. The self-powering serves as the base of the other three fields. This is what I projected future areas of exploration. \n\n# Nanogenerators \n\nWe first proposed the idea of self-powering in 2006 as a result of discovery of piezoelectric nanogenerators (PENGs) [3–5], which utilizes piezoelectric effect of nanowires for converting tiny mechanical energy into electricity. This study inspires the field of nanoenergy. The triboelectric nanogenerator (TENG) was first invented in 2012 [6–9]. Using the electrostatic charges created on the surfaces of two dissimilar materials when they are brought into physical contact, the contact induced triboelectric charges can generate a potential drop when the two surfaces are separated by a mechanical force, which can drive electrons to flow between the two electrodes built on the top and bottom surfaces of the two materials. Research in nanogenerators has inspired a worldwide interest because of its importance not only as a power source, but also self-powered sensors with applications ranging from IoT, environmental monitoring, health care, medical science, infrastructure monitoring and security [9]. \n\nThere are a few important forms of energy that can be harvested from our living environment for self-powered system, including solar, thermal, mechanical and biochemical. Each of these energies offers its own uniqueness, potentials and limitations, as summarized in Fig. 2. In some cases, a device that can simultaneously harvesting multiple types of energies is desirable, so called hybrid energy technology [10,11]. Our current article mainly focus on mechanical energy harvesting, which can be accomplished using effects such as electromagnetic induction, electrostatic, piezoelectric and triboelectric. Each of these effects has its own uniqueness and applications, as summarized and compared in Fig. 3. The goal of this article is about the fundamental physics for energy harvesting using piezoelectric and triboelectric effect. We will explore the relationship between nanogenerator’s output and the Maxwell’s displacement current so that a clear understanding is offered about the difference between nanogenerators from classical electromagnetic generator (EMG). Finally, some key application fields of the nanogenerators will be briefly reviewed. \n\n# Maxwell’s displacement current for understanding nanogenerators \n\nOur discussion starts from the fundamental Maxwell’s equations that unify electromagnetism: \n\n$$\n\\nabla{\\cdot}\\pmb{D}=\\rho_{f}\\quad(\\mathrm{Gauss^{\\prime}s\\ L a w})\n$$ \n\n$$\n\\nabla\\times\\mathbf{E}=-{\\frac{\\partial\\mathbf{B}}{\\partial t}}\\quad{\\mathrm{(Faraday's~law)}}\n$$ \n\n$$\n\\nabla\\times\\pmb{H}=\\pmb{J}_{f}+\\frac{\\partial\\pmb{D}}{\\partial t}\n$$ \n\nAmp\\`ere’s circuital law with Maxwell’s addition \n\nwhere the electric field $\\mathbf{E};$ the magnetic field $\\mathbf{B}$ ; magnetizing field $\\mathbf{H}_{\\cdot}$ ; the free electric charge density $\\rho\\B{\\prime}$ the free electric current density $J_{f{\\big/}}$ displacement field $\\mathbf{D}$ , \n\n$$\n\\pmb{{\\cal D}}=\\epsilon_{0}\\pmb{{\\cal E}}+\\pmb{{\\cal P}}\n$$ \n\nand polarization field $\\mathbf{P},$ and permittivity in vacuum $\\epsilon_{0}$ . As for an isotropic media, $\\mathbf{{\\boldsymbol{D}}}=\\epsilon\\mathbf{{\\boldsymbol{E}}} $ , where e is the permittivity of the dielectrics. \n\nIn Eq. (1.4), the second term is the Maxwell’s displacement current defined as \n\n$$\n\\pmb{J}_{D}=\\frac{\\partial\\pmb{D}}{\\partial t}=\\epsilon_{0}\\frac{\\partial\\pmb{E}}{\\partial t}+\\frac{\\partial\\pmb{P}}{\\partial t}\n$$ \n\nThe displacement current was first postulated by Maxwell in 1861 [12], and it was introduced on consistency consideration between Amp\\`ere’s law for the magnetic field and the continuity equation for electric charges. The displacement current is not an electric current of moving free charges, but a time-varying electric field (vacuum or media), plus a contribution from the slight motion of charges bound in atoms, dielectric polarization in materials. In Eq. (3), the firs component $\\epsilon_{0}\\frac{\\partial\\pmb{E}}{\\partial t}$ in the displacement current gives the birth of electromagnetic wave, which later being taken as the approach for developing radio, radar, TV and long distance wireless communication. We now present the relationship between the second term in the displacement current and the output signal from nanogenerators, and show the contribution of displacement current to energy and sensors in the near future. \n\nFIGURE 2 \n\n\n
Energy sourceSolarThermalMechanicalBiochemical
Harvesting PrinciplePhotovoltaicThermoelectricElectromagnetic/Electro static/ PiezoelectricBiochemical reactions
Approximate power density5-30 mWcm-20.01-0.1 mWcm-210-100 mWcm-20.1-1 mWcm-2
ProsMicrofabrication compatible mature technology, long lifetime, DC & high power outputNo moving parts required, long lifetime, high reliability, DC outputUbiquitous and abundant in the ambient, broad frequency and power ranges, high outputBiocompatible/degrada ble, clean energy, environmentally friendly, abundant in biological entities
ConsLimited by environmental conditions, not available at nightLow efficiency, large size, a large and sustained thermal gradient is requiredAC output, not continuous outputLow power output, poor reliability, limited lifetime
Potential ApplicationsRemote sensing and environmental MonitoringStructural-health monitoring for Engines and machines, wearable Biomedical devicesRemote sensing and monitoring, wearable systems, blue energy, internet of thingsIn vivo applications, environmental Monitoring/sensing, biocompatible application
\n\ncomparison about the harvesting of energy from solar, thermal, mechanical and biochemical for illustrating their merits and possible practical limitations. \n\n\n
Mechanical energy harvestingElectromagneticElectrostaticPiezoelectricTriboelectric
Harvesting principleElectromagnetic inductionElectrostatic inductionPiezoelectric effect & Electrostatic inductionContact electrification & Electrostatic induction
Impedance typeResistiveCapacitiveCapacitiveCapacitive
ProsHigh efficiency, easy to scale upLight weightEasy to scale down to nanoscaleLarge output power, high efficiency, low weight, cost effective materials, simple fabrication
ConsHeavy magnet required, low output for small-scale devicesPrecharge required, low output, high matched impedanceLow output & low efficiency, pulsed output, high matched impedancePulsed output, high matched impedance
\n\ncomparison about the harvesting of mechanical energy using electromagnetic, electrostatic, piezoelectric and triboelectric effect for illustrating their merit nd possible practical limitations. \n\n# FIGURE 3 \n\n# Piezoelectric nanogenerator \n\nThe working principle of a piezoelectric nanogenerator (PENG) is illustrated in Fig. 4a-i. An insulator piezoelectric material is covered by a top and bottom electrodes on its two surfaces. A vertical mechanical deformation results in the generation of piezoelectric polarization charges at the two ends of the material (Fig. 4a-ii). An increase of the applied force results in higher polarization charge density (Fig. 4a-iii). The electrostatic potential created by the polarization charges is balanced by the flow of electrons from one electrode to the other through an external load. This is the process of converting mechanical energy into electric power. If the density of the piezoelectric polarization charges on the surface is $\\sigma_{p}(z)$ , and the corresponding charge density of free electrons in the electrode is $\\sigma(x)$ , which is a function of the thickness of the piezoelectric material z with considering the strain introduced by applied force. \n\nAs for a piezoelectric material that is usually anisotropic, the piezoelectric equation and constituter equations under a small uniform mechanical strain are given by [13–15]: \n\n$$\n\\begin{array}{l}{P_{i}=(\\pmb{e})_{i j k}(\\pmb{s})_{j k}}\\\\ {\\left\\{\\begin{array}{l l}{\\pmb{T}=\\pmb{c}_{E}\\pmb{s}-\\pmb{e}^{T}\\pmb{E}}\\\\ {\\pmb{D}=\\pmb{e}\\pmb{s}+\\pmb{k}\\pmb{E}}\\end{array}\\right.}\\end{array}\n$$ \n\nwhere $\\textbf{s}$ is the mechanical strain; the third order tensor $({\\pmb e})_{i j k}$ is the piezoelectric tensor; ${\\bf T}$ and $\\scriptstyle\\mathbf{c}_{E}$ are the stress tensor and the elasticity tensor, respectively; $\\pmb{k}$ is the dielectric tensor. The displacement current from the media polarization is: \n\n$$\nJ_{D i}=\\frac{\\partial P_{i}}{\\partial t}=(\\pmb{e})_{i j k}\\left(\\frac{\\partial\\pmb{s}}{\\partial t}\\right)_{j k}\n$$ \n\nEq. (5) means that the changing rate of the applied strain is proportional to the output current density of the PENG. \n\n# (a) Piezoelectric nanogenerator \n\n![](images/dc7fa67b9f8a9ef73888577d6b881e5b4df7aaff63bd1ab292d49257f34b58d2.jpg) \n\n# FIGURE 4 \n\nIllustrations about the working mechanisms of (a) piezoelectric nanogenerator with the increase of the applied stress, and (b) triboelectric nanogenerator with the increase of contact cycles. \n\nFor a case there is no external electric field applied as show in Fig. 4a and the polarization is along the $z$ -axis, the displacement field is the polarization vector, $D_{z}=P_{z}=\\sigma_{p}(z)$ in the media, so that the displacement current is \n\n$$\nJ_{D z}=\\frac{\\partial P_{z}}{\\partial t}=\\frac{\\partial\\sigma_{p}(z)}{\\partial t}\n$$ \n\nEq. (6) means that the changing rate of the surface polarization charges is the observed output current for a PENG. The magnitude of the open circuit voltage for PENG is \n\n$$\nV_{o c}=z\\sigma_{p}(z)/\\epsilon\n$$ \n\nWith considering the presence of an external load $R$ as shown in Fig. 4a-ii, the current transport equation for PENG is \n\n$$\nR A\\frac{d\\sigma}{d t}=z[\\sigma_{p}(z)-\\sigma(z)]/\\epsilon\n$$ \n\nwhere $A$ is the area of the electrode. In a case that the applied strain is a relatively slow process, so that $z$ is a function of time $t.$ The output characteristics of a PENG can be derived from Eq. (8). In analogy, the output of a pyroelectric nanogenerator can also be described accordingly. \n\n# Triboelectric nanogenerator \n\nWe start from the very basic model of the TENG for illustrating its theory. Starting from a four layer TENG in contact-separation mode, with two dielectrics with permittivity of $\\epsilon_{1}$ and $\\epsilon_{2}$ and thicknesses $d_{1}$ and $d_{2},$ respectively (Fig. 4b-i). Once the two dielectrics are driven to be in physical contact, electrostatic charges are transferred to the surfaces of the two owing to the contact electrification effect (triboelectricity). The surface is partially charged and the charges are non-mobile static charges (Fig. 4b-ii), and surface charge density $\\sigma_{c},$ builds up as a number of contacts between the two dielectric media and finally reaches a saturation, and it is independent of the gap distance $z$ . The electrostatic field built by the triboelectric charges drives electrons to flow through the external load, resulting in an accumulation of free electrons in the electrode, $\\sigma_{I}(z,t)$ , which is a function of the gap distance $z(t)$ between the two dielectrics. This is the process of converting mechanical energy into electricity. \n\nAs shown in Fig. 4b-iii, the electric field in dielectric 1 and 2 are $E_{z}=\\sigma_{I}(z,t)/\\epsilon_{1}$ and $E_{z}=\\sigma_{I}(z,t)/\\epsilon_{2},$ respectively. In the gap, $E_{z}=(\\sigma_{I}(z,t)$ $-\\sigma_{c})/\\epsilon_{0}$ . The relative voltage drop between the two electrodes is \n\n$$\nV=\\sigma_{I}(z,t)[d_{1}/\\epsilon_{1}+d_{2}/\\epsilon_{2}]+z[\\sigma_{I}(z,t)-\\sigma_{c}]/\\epsilon_{0}\n$$ \n\nUnder short-circuit condition, $V=0$ , \n\n$$\n\\sigma_{I}(z,t)=\\frac{z\\sigma_{c}}{d_{1}\\epsilon_{0}/\\epsilon_{1}+d_{2}\\epsilon_{0}/\\epsilon_{2}+z}\n$$ \n\nFrom Eq. (4), the corresponding displacement current density is \n\n$$\nJ_{D}=\\frac{\\partial D_{z}}{\\partial t}=\\frac{\\partial\\sigma_{I}(z,t)}{\\partial t}=\\sigma_{c}\\frac{d z}{d t}\\frac{d_{1}\\epsilon_{0}/\\epsilon_{1}+d_{2}\\epsilon_{0}/\\epsilon_{2}}{\\left[d_{1}\\epsilon_{0}/\\epsilon_{1}+d_{2}\\epsilon_{0}/\\epsilon_{2}+z\\right]^{2}}\n$$ \n\nThis equation means that the displacement current density is proportional to the charge density on the dielectric surface and the speed at which the two dielectrics are being separated or contacted. This is the output characteristics of the TENG. \n\nWith considering the presence of an external load $R$ as shown in Fig. 4a-ii, the current transport equation for TENG is \n\n$$\nR A\\frac{d\\sigma_{I}(z,t)}{d t}=z\\sigma_{c}/\\epsilon_{0}-\\sigma_{I}(z,t)[d_{1}/\\epsilon_{1}+d_{2}/\\epsilon_{2}+z/\\epsilon_{0}]\n$$ \n\nwhere z is a function of time $t$ depending on the dynamic process that the force is applied. Starting from Eq. (12), we have systematically established the theories for all of the four modes for TENG once it is connected with a load, regarding to the power output, the optimization of the experimental parameters [16–20]. \n\n# Capacitive model \n\nBoth piezoelectric and triboelectric nanogenerators are referred to as the capacitive conduction, in which the displacement current is the only conduction mechanism for electricity transport. The power is transmitted not via flow of free charges across the electrodes of the capacitor, but via electromagnetic wave and induction. Based on a capacitor model, the output current of a nanogenerator can be represented by \n\n$$\nI={\\frac{d Q}{d t}}=C{\\frac{d V}{d t}}+V{\\frac{d C}{d t}}\n$$ \n\nwhere $Q$ is the stored charges in the capacitor, the first term is the current introduced by a change in the applied voltage; the second term is the current introduced by the variation in capacitance. \n\nAs for a PENG, the change in capacitance is rather small because the strain induced change in crystal size/thickness is extremely small, so that the current is mainly due the change in strain induced voltage \n\n$$\nI\\approx C\\frac{d V}{d t}=\\left(\\epsilon\\frac{A}{z}\\right)\\frac{d}{d t}\\left(\\frac{\\sigma z}{\\epsilon}\\right)\\approx A\\frac{d\\sigma}{d t},\n$$ \n\nwhere $A$ is the area of the electrode. Under short circuit condition, $\\sigma=\\sigma_{p}(z)$ , the result from Eq. (14) is just the result derived from the displacement current in Eq. (6). \n\n$$\nI=A{\\frac{d\\sigma_{p}}{d t}}=A{\\frac{d\\sigma_{p}}{d z}}{\\frac{d z}{d t}},\n$$ \n\nAs for TENG, since the change in gap distance is rather large, so that both terms in Eq. (13) contribute to the observed output current, \n\n$$\nI={\\frac{d Q}{d t}}=A{\\frac{d\\sigma_{I}}{d t}}\n$$ \n\nwhich will lead to the same result as for displacement current in Eq. (11). Therefore, the foundation of the capacitive model is the Maxwell’s displacement current. Our study proves the equivalence of the different models. Using Eq. (16), in conjunction with $\\mathrm{{Ohm^{\\prime}s}}$ law, we have systematically established the theories for all of the four modes for TENG once it is connected with a load, regarding to the power output, the optimization of the experimental parameters [16–20]. \n\n# Electromagnetic generators \n\nIn Maxwell Eq. (1.4), the first term ${\\bf J}_{f}$ is the current density as a result of free electron flow. As for EMG, the Lorentz force induced electron flow in a conductor is the power generation process \n\n$$\n\\pmb{F}=-e\\pmb{\\nu}\\pmb{\\times}\\pmb{B},\n$$ \n\nwhere $\\nu$ is the moving speed of the conductor across the electric field. The motion of the electrons is accelerated by the magnetic field, but the related resistance due to inelastic collisions with atoms and electrons limits their flow, reaching a steady state current. This means that the EMG is a resistive conduction. \n\n# Four fundamental working modes of TENG \n\nEver since the first report of the TENG in 2012 by Wang et al., TENG’s output area power density reaches $500\\mathrm{W}/\\mathrm{m}^{2}$ [21], an instantaneous conversion efficiency of ${\\sim}50\\%$ have been demonstrated [22]. TENG is effective for harvesting energy from human motion, walking, vibration, mechanical triggering, rotating tire, wind, flowing water and more. A TENG can also be used as a selfpowered sensor for actively detecting the static and dynamic processes arising from mechanical agitation using the voltage and current output signals of the TENG, respectively, with potential applications as mechanical sensors and for touch pad and smart skin technologies. We now present the four basic working modes of a TENG (Fig. 5) [7,8]. The contact-separation mode uses the polarization in vertical direction. The lateral sliding mode uses the polarization in lateral direction as a result of relative sliding between two dielectrics [23,24]. The single electrode mode was introduced for harvesting energy from a freely moving object without attaching a conduction line [25]. The Freestanding triboelectric-layer mode is designed for power generation using electrostatic induction between a pair of electrode [26]. In many cases, two or more modes can work in conjunction. \n\n# Vertical contact-separation mode \n\nA physical contact between the two dielectric films with distinct electron affinity (at least one is insulator) creates oppositely charged surfaces. Once the two surfaces are separated by a gap, a potential drop is created between electrodes deposited on the top and the bottom surfaces of two dielectric films, as demonstrated in Fig. 5a. If the two electrodes are electrically connected by a load, free electrons in one electrode would flow to the other electrode in order to balance the electrostatic field. Once the gap is closed, the potential drop created by the triboelectric charges disappears, the induced electrons will flow back. A periodic contact and separation between the two materials drives the induced electrons to flow back and forth between the two electrodes, resulting in an AC output in the external circuit [6,26]. This mode is the basic mode of TENG and it can be easily achieved in practice. \n\n# In-plane sliding mode \n\nWhen two materials with opposite triboelectric polarities are brought into contact, surface charge transfer takes place due to \n\n![](images/8eaa8cd4c4536ea6111969686c40dbd847d276797afc245d1d90bfe5d8aa5cbb.jpg) \n\n# FIGURE 5 \n\nThe four fundamental working modes of the triboelectric nanogenerators. (a) The vertical contact-separation mode. (b) The lateral sliding mode. (c) The single-electrode mode. (d) The free-standing mode. \n\nthe triboelectrification effect (Fig. 5b) [27]. When the two surfaces are fully matched there is no current flow, because the positive charges at one side are fully compensated by the negative ones. Once a relative displacement is introduced by an externally applied force in the direction parallel to the interface, triboelectric charges are not fully compensated at the displaced/mismatched areas, resulting in the creation of an effective dipole polarization in parallel to the direction of the displacement. Therefore, a potential difference across the two electrodes is generated. The sliding mode can be made into fully packaged and even in rotation mode so that it can operate in vacuum. \n\n# Single-electrode mode \n\nFor a dielectric and metal plate, as shown in Fig. 5c, induction current is created in the metal plate if the charged dielectric approaches it to balance the field. Once the dielectric moves away from the metal plate, the current flows back to the ground. This mode works in a way that relies on the charge exchange between ground and metal plate [25]. This mode is most useful for utilizing the energy from a moving object without attaching an electric connection, such as human walking, moving car, finger typing and more. \n\n# Free-standing triboelectric-layer mode \n\nIf we make a pair of symmetric electrodes underneath a dielectric layer and the size of the electrodes are of the same order as the size of the moving object, and there is a small gap between the object and the electrode, the object’s approaching to and/or departing from the electrodes create an asymmetric charge distribution via induction in the media, provided the object was prior-charged by a triboelectric process, which causes the electrons to flow between the two electrodes to balance the local potential distribution (Fig. 5d) [28]. The oscillation of the electrons between the paired electrodes in responding to the back and forth motion of the object produces an AC current output. This mode carries the advantages of harvesting the energy from a moving object but with the entire system mobile without grounding. \n\n# Major applications of TENG \n\nTo provide a comparison, Fig. 6 gives a comparison between EMG and TENG, through which one can see the distinction differences between the TENG and EMG. The major applications of TENG are in three directions (Fig. 7): as sustainable nano/micro-power source for small devices to achieve self-powering; as active sensors for medical, infrastructure, human–machine, environmental monitoring and security; and as basic networks units for harvesting water motion energy at low frequency toward the dream of blue energy [9]. \n\n# TENGs as sustainable nano/micro-power source for self-powered systems \n\nThe ultimate goal of nanogenerators is to build up self-powered systems (Fig. 8), in which multifunctional electronic devices can be powered up by the nanogenerators through collecting ambient mechanical energies [29]. TENGs can convert irregular and mostly low-frequency energy from almost any mechanical motion from human, machine to nature into electricity. Such pulsed energy cannot be directly used to drive conventional electronics that \n\nFIGURE 6 \n\n\n
Electromagnetic generatorTriboelectric nanogenerator
MechanismElectromagnetic induction; Resistive free electron conduction driven by Lorentz forceContact electrification and electrostatic induction; Capacitive displacement current arising from time-dependent electrostatic induction and slight motion of bonded electrostatic charges
ProsHigh current, low voltage; High efficiency at high frequency; High durability, long lifeHigh voltage,low current; High efficiency atlow frequency; Low cost, low density,low weight; Multiple working modes; Diverse choice of materials; Diverse use of fields; Broad use as sensors
Cons●Lowimpedance; Heavy, high density; )Highcost●High impedance; Low durability
\n\nA comparison about the electromagnetic generator and triboelectric nanogenerator in mechanisms, advantages and disadvantages. \n\nrequire a continuous and constant input. A new power management system is required for lowering the output voltage but without scarifying energy, so that the generated electricity can be directly stored as electrochemical energy by a battery or capacitor [30]. Such a power management cannot be accomplished by a classical transformer, which usually has a very low efficiency at low-frequency. An integration of a TENG, power management circuit and storage unit form a self-charging power unit. This unit can be used as a sustainable power source for powering any electronics as long as the power output is sufficient. This is the first major applications of TENG. \n\n# TENGs as self-powered active sensors \n\nTENG is a technology for converting mechanical energy into electricity. Reversely, the electric output signals of the TENG directly reflect the impact of the mechanical triggering, so that TENG can be used as an active sensor in responding to external excitation [31]. From Eq. (7), the output voltage is a direct measurement of the gap distance z, while the output current represents the impact speed, dz/dt. The TENG based sensor is different from the conventional sensor that has to be driven by a power, otherwise there is no output signal. In contrast, the TENG sensor gives an output electric signal itself without applying a power to the sensor tip. TENG based sensor can be used for sensing of motion, vibration, human triggering and object contacts. \n\nWe use keyboard based TENG as an example [32]. Keyboard is an indispensable input component for many personal electronics like computers and cell phones. We recently invented an intelligent and self-powered keyboard as an advanced security safeguard against unauthorized access to computers. Based on the triboelectric effect between human fingers and keys, the intelligent keyboard (IKB) could convert typing motions into localized electric signals that could be identified as personalized physiological information. The core part of the IKB was composed of multilayered transparent thin film materials to form a typical singleelectrode TENG. Fig. 9a shows the schematic structure and a photograph of a fully-assembled IKB with the same size as a commercial keyboard. The working principle of the IKB as an \n\n![](images/81b58fe77ced8fb3f77739269e2ca70afd37a18730cf4cddbc9acbe529e77198.jpg) \n\n# FIGURE 7 \n\nA summary about the three major application fields of nanogenerators as micro-/nano-energy source, for blue energy and self-powered sensors. The photos around the three directions are the ones we have demonstrated in our experiments in the last few years. \n\n![](images/2c5bb14d03153da24dc76009aefef5487541b90eb61d6563ebc27992345f49bb.jpg) \nself-powered system by integrating a nanogenerator, power management circuit and energy storage unit as a self-charging power cell. \n\n# FIGURE 8 \n\n![](images/fe11d17c9d108a49bafd0409d6f83fbb47e29514c2df2f90e696a7d9813c36c3.jpg) \nRESEARCH \n\n# FIGURE 9 \n\nenergy harvester was similar with the single-electrode TENG. A finger movement during typing would then induce change of the potential difference between the pair of ITO electrodes, driving electrons flow through the external load or data collection system. The electric signals generated by three people by typing the same phrase or words are completely different, which can be used to identify the user of the computer for system protection (Fig. 9b). \n\n# TENGs as basic units for large-scale blue energy \n\nOur earth is largely covered by water. Energy offered by ocean can be huge, but harvesting such energy is extremely challenging because the low efficiency of electromagnetic generators, especially at low frequency [33]. TENG is much more effective than EMG for harvesting energy in the frequency range of $<5\\mathrm{Hz},$ which is ideally suited for our daily life and in nature (not EMG works only effective at relatively high frequency such a $s{>}s\\operatorname{Hz}$ ). More importantly, the EMGs are heavy and high cost, and they are not easily to be installed in sea floor or at water surface for collecting the water wave energy. I proposed the idea of using TENG networks for harvesting water motion energy at a large scale in 2014 [34]. The idea is that the TENG is made of mostly organic materials and it is partially filled up with air, so that the network made of millions of TENGs as fishing net would flow at the vicinity of the water surface (Fig. 10). Any wave motion would drive the TENG to perform contact-separation and sliding motions, so that the mechanical energy can be collected. Our initial estimation indicates that the power can be generated on average is $1\\mathrm{MW/km}^{2}$ , which could be improved for at least 10 times based on near future progress in materials and structure design [35] The advantage offered by TENG networks is low-cost, occupy no land, no natural disaster, independent of day, night or even weather, and there is no big security concern. I believe that this blue energy dream will offer a new energy path for human kind. \n\n![](images/365fe486244e07a3d9c5f030ebc764a921e9bb308057b27d9ade2480f262fe0a.jpg) \nPersonalized keystroke dynamics for self-powered human-machine interfacing. (a) Schematic illustrations of the keyboard. (b) Evaluation of the performance of the biometric authentication system using triboelectrification enabled keystroke dynamics by repeatedly typing the same phase of words by three different people. The output electric signals are completely different from one person to the other, but each person’s pattern is self-reproducible. \nFIGURE 10 \n\nA blue energy dream by networking millions of spherical balls based triboelectric nanogenerators for harvesting low-frequency water wave energy. The inset is the designed spherical TENG. The lower-right corner is an imaginary structure of the networks. \n\n# Summary \n\nThe goal of this review article is to present the linkage between the Maxwell’s displacement current and the output of nanogenerators, so that the differences between EMG and PENG/TENG are clearly elaborated. The displacement current has two components (Fig. 11). The first component $\\epsilon_{0}\\frac{\\partial\\pmb{E}}{\\partial t}$ represents the electricity to magnetism induction effect, so that it represents the existence of electromagnetic waves and the theory of light. As a result, it is the foundation of antenna, telegram, radio, TV, and most recently wireless communication technology. It means that the first component of displacement current is the foundation of today’s wireless information technology, which has driven the development of the world for the last 50 years. \n\nIn parallel, the second term $\\textstyle{\\frac{\\partial{\\pmb P}}{\\partial t}}$ in the displacement current is related to the polarization of media, from which the fundamental characteristics of piezoelectric nanogenerator and triboelectric nanogenerator can all be derived. Besides the applications in capacitors, the second term gives the birth of new energy technology and self-powered sensors, for example, our nanogenerators, which could have extensive applications in IoT, sensor networks, blue energy and even big data. The industry as generated by the second component of the displacement current could possibly drive the development of the world in energy and sensors in the next 50 years at least! \n\nOur study indicates that the second term $\\textstyle{\\frac{\\partial P}{\\partial t}}$ in the displacement current is directly related to the output electric current of the nanogenerator. In other words, the applications of displacement current in energy and sensors are our nanogenerators. Based on this future prediction, we like to emphasize here is a lacking of \n\n![](images/80b6bb9cc83efc2d59d3ada18d7b4fe78c1f0605c60063e995c41d047708c2b2.jpg) \n\n# FIGURE 11 \n\nMajor fundamental science, technologies and practical impacts that have been derived from the two components of the Maxwell’s displacement current. The left hand-side column is the electromagnetic wave that has impacted the development of the world in the last century in communication; the right-hand side is the new technologies derived from displacement current for energy and sensors that are likely to impact the world for the future. \n\nfundamental understanding about the phenomenon of triboelectrification. Although this phenomenon is known for over thousands years, its basic physics interpretation is unclear. Why? I believe that there was not enough study devoted to it because triboelectricity has been attributed as a negative effect, so people would think that it is not important or rather difficult to understand. However, as now, triboelectric nanogenerator finds the true applications of contact electrification and it is time to study this phenomenon and explore the core physics, for example, the physics each and every one of us experiences every day! We now have the urgency and practical implication for studying charging effect at dielectric surfaces. Once a clear physical picture is presented, developing effective triboelectrification process and structure would hugely impact the technological development of nanogenerators and their commercial products. \n\n# Acknowledgements \n\nResearch was supported by the Hightower Chair foundation, and the ‘thousands talents’ program for pioneer researcher and his innovation team, China, the National Key R&D Project from Minister of Science and Technology (2016YFA0202704). \n\n# References \n\n[1] Z.L. Wang, Sci. Am. 298 (2008) 82–87. [2] S. Xu, et al. Nat. Nanotechnol. 5 (2010) 366–373. [3] Z.L. Wang, J. Song, Science 312 (2006) 242–246. [4] R. Yang, et al. Nat. Nanotechnol. 4 (2009) 34–39. \n[5] Z.L. Wang, Nanogenerators for Self-Powered Devices and Systems, Georgia Institute of Technology, 2011 http://smartech.gatech.edu/handle/1853/39262. [6] F.-R. Fan, Z.-Q. Tian, Z.L. Wang, Nano Energy 1 (2012) 328–334. [7] Z.L. Wang, ACS Nano 7 (2013) 9533–9557. [8] Z.L. Wang, J. Chen, L. Lin, Energy Environ. Sci. 8 (2015) 2250–2282. [9] Z.L. Wang, et al., Triboelectric Nanogenerators, Springer, 2016 http://www. springer.com/us/book/9783319400389. \n[10] C. Xu, X. Wang, Z.L. Wang, J. Am. Chem. Soc. 131 (2009) 5866–5872. \n[11] C. Xu, Z.L. Wang, Adv. Mater. 23 (2011) 873–877. \n[12] J.C. Maxwell, Philosophical Magazine and Journal of Science, London, Edinburg and Dubline, Fourth series, p. 161. \n[13] T. Ikeda, Fundamentals of Piezoelectricity, Oxford University Press, Oxford, UK, 1996. \n[14] G.A. Maugin, Continuum Mechanics of Electromagnetic Solids, Amsterdam, North-Holland, 1988. \n[15] R.W. Soutas-Little, Elasticity, XVI, 431, Dover Publications, Mineola, NY, 1999. \n[16] S. Niu, et al. Energy Environ. Sci. 6 (2013) 3576–3583. \n[17] S. Niu, et al. Adv. Mater. 25 (2013) 6184–6193. \n[18] S. Niu, et al. Nano Energy 12 (2015) 760–774. \n[19] S. Niu, et al. Energy Environ. Sci. 7 (2014) 2339–2349. \n[20] S. Niu, et al. IEEE Trans. Electron Devices 62 (2015) 641–647. \n[21] G. Zhu, et al. Adv. Mater. 26 (2014) 3788–3796. \n[22] Y. Xie, et al. Adv. Mater. 26 (2014) 6599–6607. \n[23] J. Yang, et al. ACS Nano 8 (2014) 2649–2657. \n[24] G. Zhu, et al. Nano Lett. 13 (2013) 2282–2289. \n[25] Y. Yang, et al. ACS Nano 7 (2013) 7342–7351. \n[26] G. Zhu, et al. Nano Lett. 12 (2012) 4960–4965. \n[27] G. Zhu, et al. Nano Lett. 13 (2013) 847–853. \n[28] S. Wang, et al. Adv. Mater. 26 (2014) 2818–2824. \n[29] Z.L. Wang, W. Wu, Angew. Chem. 51 (2012) 11700–11721. \n[30] S. Niu, et al. Nat. Commun. 6 (2015) 8975. \n[31] S. Wang, L. Lin, Z.L. Wang, Nano Energy 11 (2015) 436–462. \n[32] J. Chen, et al. ACS Nano 9 (2015) 105–116. \n[33] Y. Zi, et al. ACS Nano 10 (2016) 4797–4805. \n[34] Z.L. Wang, Faraday Discuss. 176 (2014) 447–451. \n[35] J. Chen, et al. ACS Nano 9 (2015) 3324–3331. " + }, + { + "id": "10.1002_adfm.201701264", + "DOI": "10.1002/adfm.201701264", + "DOI Link": "http://dx.doi.org/10.1002/adfm.201701264", + "Relative Dir Path": "mds/10.1002_adfm.201701264", + "Article Title": "Flexible MXene/Graphene Films for Ultrafast Supercapacitors with Outstanding Volumetric Capacitance", + "Authors": "Yan, J; Ren, CE; Maleski, K; Hatter, CB; Anasori, B; Urbankowski, P; Sarycheva, A; Gogotsi, Y", + "Source Title": "ADVANCED FUNCTIONAL MATERIALS", + "Abstract": "A strategy to prepare flexible and conductive MXene/graphene (reduced graphene oxide, rGO) supercapacitor electrodes by using electrostatic self-assembly between positively charged rGO modified with poly(diallyldimethylammonium chloride) and negatively charged titanium carbide MXene nullosheets is presented. After electrostatic assembly, rGO nullosheets are inserted in-between MXene layers. As a result, the self-restacking of MXene nullosheets is effectively prevented, leading to a considerably increased interlayer spacing. Accelerated diffusion of electrolyte ions enables more electroactive sites to become accessible. The freestanding MXene/rGO-5 wt% electrode displays a volumetric capacitance of 1040 F cm(-3) at a scan rate of 2 mV s(-1), an impressive rate capability with 61% capacitance retention at 1 V s(-1) and long cycle life. Moreover, the fabricated binder-free symmetric supercapacitor shows an ultrahigh volumetric energy density of 32.6 Wh L-1, which is among the highest values reported for carbon and MXene based materials in aqueous electrolytes. This work provides fundamental insight into the effect of interlayer spacing on the electrochemical performance of 2D hybrid materials and sheds light on the design of next-generation flexible, portable and highly integrated supercapacitors with high volumetric and rate performances.", + "Times Cited, WoS Core": 1561, + "Times Cited, All Databases": 1625, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000407261700011", + "Markdown": "# Flexible MXene/Graphene Films for Ultrafast Supercapacitors with Outstanding Volumetric Capacitance \n\nJun Yan, Chang E. Ren, Kathleen Maleski, Christine B. Hatter, Babak Anasori, Patrick Urbankowski, Asya Sarycheva, and Yury Gogotsi\\* \n\nA strategy to prepare flexible and conductive MXene/graphene (reduced graphene oxide, rGO) supercapacitor electrodes by using electrostatic self-assembly between positively charged rGO modified with poly(diallyldimethylammonium chloride) and negatively charged titanium carbide MXene nanosheets is presented. After electrostatic assembly, rGO nanosheets are inserted in-between MXene layers. As a result, the self-restacking of MXene nanosheets is effectively prevented, leading to a considerably increased interlayer spacing. Accelerated diffusion of electrolyte ions enables more electroactive sites to become accessible. The freestanding MXene $r\\Delta0.5~\\mathrm{wt\\%}$ electrode displays a volumetric capacitance of $\\mathtt{l o40}\\mathtt{F}\\mathtt{c m}^{-3}$ at a scan rate of $2{\\mathsf{m}}{\\mathsf{v}}{\\mathsf{s}}^{-1}$ , an impressive rate capability with $67\\%$ capacitance retention at $\\mathsf{I}\\mathsf{V}\\mathsf{s}^{-1}$ and long cycle life. Moreover, the fabricated binder-free symmetric supercapacitor shows an ultrahigh volumetric energy density of $32.6~\\mathsf{W h\\mathsf{L}^{-1}}$ , which is among the highest values reported for carbon and MXene based materials in aqueous electrolytes. This work provides fundamental insight into the effect of interlayer spacing on the electrochemical performance of 2D hybrid materials and sheds light on the design of next-generation flexible, portable and highly integrated supercapacitors with high volumetric and rate performances. \n\n# 1. Introduction \n\nTwo-dimensional (2D) nanomaterials, such as graphene,[1] transition metal oxides/hydroxides,[2] transition metal dichalcogenides,[3] and MXenes,[4] have been extensively investigated recently as active materials in energy storage applications, because they allow the development of binder-free electrodes with improved capacitance.[5,6] \n\nMXenes are an emerging family of 2D transition metal carbides and nitrides with a general formula of $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x},$ where M is an early transition metal, X represents C and/or N, $\\mathrm{T}_{x}$ denotes surface functional groups, and $n=1$ , 2, or 3. MXenes are generally produced by selective etching of the A-group (generally, group III A or IV A) element layers from MAX phase precursors $(\\mathbf{M}_{n+1}\\mathbf{AX}_{n})$ , which comprise a ${>}70$ -membered family of layered, hexagonal early-transition-metal carbides and nitrides.[7] Since their discovery in 2011,[8] MXenes have attracted attention from the scientific community for various applications including supercapacitors,[4,9] Li-ion and Na-ion batteries,[10,11] electromagnetic interference shielding,[12] selective ion sieving[13] as well as cellular imaging.[14] Due to their metallic conductivity, high density, and hydrophilic nature, MXenes have proven to be promising candidates for supercapacitors with high \nvolumetric capacitance exceeding most previously reported \nmaterials.[4,15] For instance, titanium carbide $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x})$ clay \nfilms exhibited high volumetric capacitance up to $900\\ \\mathrm{F}\\ \\mathrm{cm}^{-3}$ \nwith excellent cyclability and rate performance.[4] However, the \ngravimetric capacitance was about $245\\mathrm{~F~g^{-1}}$ and still needed \nto be enhanced. Generally, electrodes made of layered materials \nsuffer from limited electrolyte-accessible surface area due to the \nrestacking of the 2D sheets. This problem can be circumvented \nby constructing more open structures of layered materials that \nmay provide more gallery space for storage and transport of \n\nelectrolyte ions. \n\nSimilar to graphene, aggregation and face-to-face selfrestacking of MXene nanosheets are usually inevitable during drying and electrode fabrication processes owing to the strong van der Waals interaction between adjacent nanosheets. Selfrestacking of MXene nanosheets has been demonstrated to significantly decrease the electrochemical utilization ratio, deteriorate the intrinsic performance and accessibility to electrolyte ions.[16] In order to effectively prevent the self-restacking and improve the performance, various materials such as polypyrrole,[15,17] nickel–aluminum-layered double hydroxides,[18] $\\mathrm{{MnO}}_{2}.$ ,[19] and carbon nanotubes (CNTs)[16,20] have been to eliminate the self-restacking of both graphene and MXene through the formation of a structure with alternating MXene/graphene layers, one can expect to obtain improved performances. Recently, Feng and co-workers demonstrated MXene/graphene flexible films through vacuum-filtrating an MXene/ graphene suspension.[22] These composite electrodes were assembled into flexible allsolid-state supercapacitors, which exhibited a volumetric capacitance of $216~\\mathrm{~F~}\\mathrm{cm}^{-3}$ .[22] However, the MXene nanosheets used in that study were relatively small in size $(\\approx200\\ \\mathrm{nm})$ , greatly increasing the internal resistance due to the contact resistance among the sheets. Most importantly, the random physical mixing between MXene and graphene did not efficiently prevent their self-restacking since both graphene and MXene have negatively charged surfaces. Although that work, as well as other studies,[16] demonstrated the possibility of MXene/graphene supercapacitor electrodes, the performances could be further improved by alternative assembly approaches. \n\n![](images/a9f8f1867b5d199440d7eade1077d428844a871be78f7b2354f95f0455ea5522.jpg) \nFigure 1.  a) Schematic illustration for the synthesis of the MXene/rGO hybrids. b) Digital photo­graphs of G-PDDA, MXene suspension, and $M/C-5\\%$ hybrid. c) Zeta potential of MXene, G-PDDA, and self-assembled $M/C.5\\%$ hybrid. d,e) Digital photographs showing flexible, freestanding MXene/rGO hybrid films $(M/C.5\\%)$ . The film in panel (e) is wrapped around a glass rod. \n\nintroduced to hybridize with MXenes in recent years. However, pseudocapacitive materials like polypyrrole, $\\mathrm{MnO}_{2}$ , and hydroxides usually have low electrical conductivity, thus decreasing the electrical conductivity of the electrodes, and consequently resulting in low power delivery.[18,19] Additionally, pseudocapacitive materials commonly display serious volume changes during the fast charge/discharge processes, resulting in overall decrease in rate capability and cyclability. Alternatively, in an effort to produce films yielding a higher volumetric capacitance, better rate capability and cycling performance than pristine MXene, our group produced sandwiched MXene/CNT flexible films through alternating filtration.[16] One-dimensional (1D) CNTs played an important role to act as electrically conductive spacers, facilitating accessibility of MXene sheets to the electrolyte and greatly shortening the transportation and diffusion distance of electrolyte ions. Although CNTs have excellent electrical conductivity, the density of the film decreased greatly due to the open structure, leading to lower volumetric performance. To this end, efficiently preventing the self-restacking of MXene nanosheets while retaining the intrinsic high electrical conductivity and high volumetric performance is a pressing challenge for materials scientists wishing to obtain MXene electrodes that can perform well in all aspects. \n\nGraphene has been widely used as an electrode material for supercapacitors.[1,21] If graphene with high electrical conductivity is controllably introduced in between MXene nanosheets \n\nIn this work, we demonstrate the fabrication of flexible and highly conductive MXene/reduced graphene oxide (rGO) films through electrostatic self-assembly of negatively charged MXene nanosheets and positively charged $\\mathtt{r G O}$ nanosheets for ultrafast supercapacitors. The resultant MXene/ rGO composite efficiently alleviates the selfrestacking of both rGO and MXene, maintaining ultrahigh electrical conductivity $(2261\\ \\mathrm{S\\cm^{-1}},$ ) and high density $(3.1\\ \\mathrm{g}\\ \\mathrm{cm}^{-3}),$ . In addition, the rGO nanosheets present in between MXene nanosheets can act as conductive spacers while increasing the interlayer spacing of MXene, providing unimpeded channels for electrolyte ions and ensuring high-rate performance. As a consequence, the flexible film delivers unparalleled volumetric capacitance up to $1040\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ at $2\\ \\mathrm{mV}\\ \\mathrm{s}^{-1}$ with $61\\%$ capacitance retention at $1\\mathrm{V}\\mathrm{s}^{-1}$ , much higher than that of pure MXene $(28\\%)$ . Additionally, the resultant composite exhibits excellent cyclability with almost no capacitance degradation after 20 000 cycles. Moreover, the symmetric supercapacitor can yield an outstanding volumetric energy density of 32.6 Wh $\\mathrm{L}^{-1}$ and an ultrahigh volumetric power density of $74.4\\mathrm{~kW~L^{-1}}$ . \n\n# 2. Results and Discussion \n\nFigure 1a schematically illustrates the fabrication of the flexible MXene/rGO composite films through electrostatic selfassembly. First, rGO nanosheets were prepared through hydrazine reduction of graphene oxide at $90~^{\\circ}\\mathrm{C}$ for $24\\mathrm{~h~}$ .[23] Due to the presence of numerous residual oxygen-containing functional groups, the negatively charged $\\mathtt{r G O}$ nanosheets were dispersed into cationic polymer poly(diallyldimethylammonium chloride) (PDDA) solution $(0.01~\\mathrm{wt\\%})$ by probe sonication to obtain a stable suspension with a concentration of $0.5~\\mathrm{mg~mL^{-1}}$ (Figure 1b, left vial). In order to confirm the modification, the zeta potential of PDDA-modified rGO (G-PDDA) was measured to be $+63.0\\ \\mathrm{mV}$ (Figure 1c). Then, MXene $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x})$ was obtained through etching $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ in a mixture of lithium fluoride (LiF) and hydrochloric acid followed by delamination through sonication. Because of the surface functional groups (e.g., $-0_{:}$ $-\\mathrm{OH}$ , and $-\\mathrm{F})$ , the as-prepared MXene is negatively charged with a zeta potential of $-39.5\\mathrm{\\mV}$ (Figure 1c). Owing to the hydrophilicity and electrostatic repulsion between neighboring nanosheets, the MXene colloidal solution is very stable in water (Figure  1b, middle vial). When positively charged G-PDDA was added into the negatively charged MXene solution, rGO nanosheets attached the surface of MXene nanosheets. After several minutes, large agglomerates appeared and settled down to the bottom of the container to form precipitates leaving a clear supernatant (Figure 1b, right vial), indicating the electrostatic self-assembly between MXene and rGO. Notably, as opposed to random physical mixing, strong interactions are established between MXene and rGO nanosheets through electrostatic attraction, which can effectively prevent the selfrestacking of rGO or MXene nanosheets. Finally, the flexible freestanding composite films with 1, 5, or $10\\mathrm{\\Omega}\\mathrm{wt}\\%$ of rGO were obtained through vacuum-assisted filtration (Figure  1d and Table 1). The composite films are denoted as \n\n$\\mathrm{M}/\\mathrm{G}{\\cdot}x,$ where $x$ is the weight percent of rGO nanosheets in the composites. These obtained MXene/rGO films could be readily wrapped around a glass rod without any visible damage to their structure, indicating their flexibility and durability (Figure 1e). \n\n![](images/3da379fe685cbd3dd175024d505d7895c79a285aec8c24b0aa0df0db0c0b38ee.jpg) \nFigure 2.  a,b) Top-view and c,d) cross-sectional SEM images of a,b) the pure MXene and b,d) $M/C.5\\%$ hybrid, insets are higher magnification SEM images. e) TEM images of the $M/C-5\\%$ hybrid. f) XRD patterns of the prepared MXene and MXene/rGO hybrids. \n\nScanning electron microscopye(SEM) and transmission electron microscopy eTEM) were employed to observe the morphology and microstructure of the MXene/rGO hybrid films. Figure 2 shows the SEM and TEM images of MXene and $M/G{-}5\\%$ composite films. From the top-view SEM images, similar morphology with considerable wrinkles can be found on the surfaces of both pure MXene and MXene/rGO hybrid films (Figure 2a,b; Figure S1a,b, Supporting Information). The cross-sectional SEM image of the pure MXene shows a wellaligned, layered structure (Figure 2c). After the introduction of rGO nanosheets, the MXene/rGO hybrid films maintain the same layered structure of pure MXene film without any visible change, as shown in Figure 2d and Figure S1c,d (Supporting Information). Cross-sectional TEM images of the $M/G{-}5\\%$ hybrid film show the alternating single layers of MXene and rGO (Figure 2e; Figure S1e, Supporting Information), demonstrating the assembly of nanosheets and confirming the minimal self-restacking of MXene nanosheets. The line profile analysis across the red line in Figure S1e (Supporting Information) indicates that the interlayer spacing between MXene layers of $M/G{-}5\\%$ hybrid is $1.5\\ \\mathrm{nm}$ (Figure S1f, Supporting Information), much larger than that of pure MXene ( $\\mathrm{1.3~nm}$ , the inset of Figure S1h of the Supporting Information), certifying the formation of alternating MXene and rGO nanosheet layers. The increased interlayer spacing is favorable for the diffusion and transport of electrolyte ions during rapid charge/discharge processes and improves the accessibility of MXene nanosheets to electrolyte ions.[16] The mitigative restacking and increased exposed surface area can be verified by the $\\mathrm{N}_{2}$ adsorption/desorption test (Figure S1j, Supporting Information). The specific surface area of the $M/G.5\\%$ hybrid is about $68.1\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}$ , about 3.5 times that of pure $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene $(19.6~\\mathrm{m}^{2}~\\mathrm{g}^{-1})$ , indicating the increased exposed surface area of MXene nanosheets. \n\nTable 1.  Composition and properties of the materials under study. \n\n\n
SampleTiCTx content [wt%]rGO content [wt%]Density [g cm-3]Conductivity [S cm-1]
MXene10003.74556
M/G-1%9913.43326
M/G-5%9553.12261
M/G-10%90102.71231
\n\nIn order to confirm that the change of interlayer spacing observed in TEM is statistically significant, X-ray diffraction (XRD) measurements were performed for pure MXene and \n\nMXene/rGO hybrids (Figure 2f). The pure MXene exhibits a strong (002) diffraction peak at $6.7^{\\circ}$ , corresponding to an interlayer spacing of $1.31\\ \\mathrm{nm}$ , which is typical for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene with water between the layers.[24] The (002) diffraction peak shifts from $6.7^{\\circ}$ for pure MXene to $5.2^{\\circ}$ for $M/\\mathrm{G}{\\cdot}10\\%$ hybrid with an increase of $\\mathrm{rGO}$ content from 0 to $10~\\mathrm{wt\\%}$ . This corresponds to an increased interlayer spacing from 1.31 to $1.67\\mathrm{nm}$ , indicating that rGO nanosheets and possibly PDDA molecules interleave MXene layers.[25] For $M/G.5\\%$ , the interlayer spacing of (002) diffraction peak is $1.51\\ \\mathrm{nm}$ , which is in good agreement with the TEM observation (Figure 2e). In addition, the intensity of (002) peaks decreases with the increase of rGO content, indicating a decrease in the degree of stacking order of MXene layers due to hybridization with rGO. This may result in the decrease of material density and electrical conductivity. The pure MXene film has a density of $3.7\\ \\mathrm{g\\cm^{-3}}$ with an electrical conductivity of $4556\\ \\mathrm{S\\cm^{-1}}$ (Table 1). However, with the increase of $\\mathrm{rGO}$ content in the hybrids, both the density and electrical conductivity decrease gradually due to the decreased degree of stacking order in addition to the lower density and electrical conductivity of rGO $(72\\ \\mathrm{~S~}\\ \\mathrm{cm}^{-1}.$ ) compared with MXene.[26] Particularly, the $M/G{-}5\\%$ hybrid exhibits a high density of $3.1\\ \\mathrm{g\\cm^{-3}}$ while keeping the excellent electrical conductivity up to 2261 $\\mathrm{{\\calS}}\\mathrm{cm}^{-1}$ , ensuring a high power output during the fast charging and discharging processes. \n\nFigure 3a shows Raman spectra of the as-prepared pure MXene and $M/G.5\\%$ hybrid. For the Raman shift range from 150 to $750\\mathrm{cm}^{-1}$ , pure MXene and $M/\\mathrm{G}{\\cdot}5\\%$ hybrid exhibit similar Raman spectra. Specifically, the modes at 198 $(\\omega_{2})$ and $717\\mathrm{cm}^{-1}$ $(\\omega_{3})$ are $\\mathrm{A_{1g}}$ symmetry out-of-plane vibrations of Ti and C atoms, respectively, while the modes at 284 $(\\omega_{5})$ , 366 $(\\omega_{5})$ , and $624~\\mathrm{cm}^{-1}$ $(\\omega_{4})$ are the $\\operatorname{E}_{\\mathrm{g}}$ group vibrations, including in-plane (shear) \n\nmodes of Ti, C, and surface functional group atoms.[27] After the incorporation of $\\mathtt{r G O}$ nanosheets, two broad bands appear at ${\\approx}1312$ and $1588~\\mathrm{cm}^{-1}$ for the $M/G{-}5\\%$ hybrid, which are the characteristics for the $D$ and $G$ bands of graphitic carbon, confirming the presence of $\\mathrm{\\Upsilon{r}G O}$ nanosheets in the hybrid. Compared with those of pure rGO nanosheets, the G band redshifts by $16\\mathrm{cm}^{-1}$ , which is probably caused by the interaction between MXene and $\\mathtt{r G O}$ layers. In order to confirm the interaction between MXene and rGO layers, X-ray photoelectron spectroscopy (XPS) was employed to examine the chemical composition and surface electronic states. The XPS survey spectra as shown in Figure 3b indicate that the samples are mainly composed of C, Ti, O, and F. High-resolution XPS spectra of $\\mathrm{Ti}\\ 2\\mathrm{p}$ and C 1s core levels of pure MXene and $M/G{-}5\\%$ samples are shown in Figure 3c,d, respectively. The Ti $2\\mathrm{p}$ core level can be fitted with three doublets $\\mathrm{(Ti}2\\mathrm{p}_{3/2}\\mathrm{-Ti}2\\mathrm{p}_{1/2}\\mathrm{)}$ .[28,29] The Ti $2\\mathrm{p}_{3/2}$ components located at 455.1, 456.1, and $458.3\\ \\mathrm{eV}$ correspond to $\\mathrm{Ti-C}$ Ti (II), and $\\mathrm{Ti}{-}\\mathrm{O}$ bonds, respectively.[28] The C 1s core level could be fitted with five components centered at 281.8, 282.3, 284.8, 286.2, and $288.1\\ \\mathrm{eV},$ which could be assigned to $\\mathrm{{C-Ti}}$ TiCO, CC, $\\scriptstyle{\\mathrm{C-O}}$ and $scriptstyle{\\mathrm{O=C-O}}$ bonds, respectively.[28] The atomic percentage of $\\mathrm{{C-Ti}}$ in all fitted components increases from $7.12\\%$ for $M/\\mathrm{G}{\\cdot}1\\%$ to $10.05\\%$ for $M/\\mathrm{G}{\\cdot}10\\%$ , confirming the interaction between MXene layers and rGO layers. \n\nMXene/rGO hybrid films show self-assembled unique structures with excellent flexibility, significantly increased interlayer spacing, high density, and superior electrical conductivity. Consequently, they are expected to possess greatly improved electrolyte accessibility, high volumetric capacitance, high rate capability, and volumetric energy output, rendering them a potential candidate for flexible supercapacitors. The electrochemical performances of the as-prepared samples were first evaluated in a three-electrode configuration in $3~\\mathrm{~M~}$ sulfuric acid $\\mathrm{(H}_{2}\\mathrm{SO}_{4})$ aqueous electrolyte. The acidic electrolyte was chosen because of its excellent ionic conductivity and small size of protons, favorable for surface redox reaction and intercalation contributing to pseudocapacitance.[4] Figure 4a shows the cyclic voltammetry (CV) curves of pure MXene and MXene/rGO hybrid electrodes at a scan rate of $20~\\mathrm{mV~s^{-1}}$ . A pair of broad and symmetric redox peaks with cathodic peaks at about $-0.37\\mathrm{~V~}$ (vs $\\mathrm{\\sfAg/AgCl}_{\\mathrm{\\ell}}^{\\prime}$ ) and anodic peaks around $-0.31$ V (vs $\\mathrm{\\sfAg/AgCl}_{\\mathrm{\\ell}}^{\\mathrm{\\sf1}}$ can be clearly found in all the CV curves, indicating that the capacitance mainly comes from the pseudocapacitance associated with reversible intercalation/deintercalation of protons along with the change of Ti oxidation state.[30] The slightly larger integral area of CV curves for $M/G{-}5\\%$ electrode demonstrates higher specific capacitance than pure MXene and the other two hybrid electrodes. Additionally, with an increase of scan rate to $500\\ \\mathrm{mV\\s^{-1}}$ and even $1\\mathrm{~V~s~}^{-1}$ , the CV curves of $M/G{-}5\\%$ electrode still maintain similar shapes with a slight shift of the anodic and cathodic peaks, indicating an excellent rate capability and low internal resistance of the electrode (Figure 4b; Figure S3a, Supporting Information).[2] Generally, the relationship between current $(i)$ and scan rates $(\\nu)$ obeys the power law[31] \n\n![](images/804e9f6d755f536cba062847f06988f68997f1a6582bbf9f04c17ed1bfb892bf.jpg) \nFigure 3.  a) Raman spectra of MXene, rGO, and $M/C.5\\%$ hybrid $(\\lambda=633\\ \\mathsf{n m})$ . b) XPS survey spectrum, high-resolution c) Ti 2p and d) C 1s spectra of MXene and $M/\\mathsf{G}\\cdot5\\%$ hybrid. \n\n![](images/6d1ee4642fe070d63cd613943ab90a8dec1e1e408ca5e878e4884077c43596ed.jpg) \nFigure 4.  a) CV curves of MXene and MXene/rGO hybrids at a scan rate of $20\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in $3\\mathrm{~M~}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ electrolyte. b) CV curves of the $M/C-5\\%$ electrode at different scan rates. c) The relationship between peak current and scan rates from 2 to $50\\mathrm{mV}\\mathsf{s}^{-1}$ for the $M/C-5\\%$ electrode. d) Galvanostatic charge/ discharge curves of the $M/C-5\\%$ electrode at different current densities. e) Gravimetric and f) volumetric capacitances of MXene and MXene/rGO hybrids at different scan rates, compared with some previously reported MXene-based materials, such as MXene clay,[4] MXene,[9] MXene/polypyrrole,[15] MXene/CNTs,[16] and MXene/polyvinyl alcohol.[25] \n\n$$\ni=a\\nu^{b}\n$$ \n\nwhere $a$ and $b$ are appropriate values. The electrochemical process is a diffusion-controlled process for a $b$ -value of 0.5, while it corresponds to a nondiffusion-controlled behavior for a value of 1.[31] Thus, the nondiffusion-controlled capacitive effect and the diffusion-controlled insertion process can be well distinguished depending on the value of $b$ . In order to confirm the charge storage mechanism, the plot of $\\log(i)$ versus $\\log(\\nu)$ from 2 to $50~\\mathrm{mV}~\\mathrm{s}^{-1}$ for the anodic and cathodic peaks is shown in Figure $4\\mathsf{c}$ . The $b$ -values of 1.00 and 0.91 are obtained for the anodic and cathodic peaks, respectively, indicating that the charge storage process is predominantly nondiffusion limited,[31] thus providing superior rate capability. \n\nFigure 4d represents the galvanostatic charge/discharge curves of the $M/G{-}5\\%$ electrode between $-0.7$ and $0.3\\mathrm{V}$ (vs $\\mathrm{Ag/}$ $\\mathsf{A g C l})$ at different current densities from 0.5 to $5\\mathrm{~A~g^{-1}}$ . It can be found that these charge/discharge curves are nonlinear and deviate from the triangular shape, which is a typical characteristic of electric double-layer capacitors, indicating the pseudocapacitive nature of MXene electrodes. The potential plateaus around $-0.32\\mathrm{~V~}$ (vs $\\mathrm{\\Ag/AgCl}_{\\mathrm{\\ell}}^{\\mathrm{\\ell}}$ ) during charging and −0.37 V (vs $\\mathrm{\\sfAg/AgCl}]$ during discharging are in good agreement with the CV curves (Figure 4b). The gravimetric capacitance is calculated from the CV curves and shown in Figure 4e. Among these electrodes, the $M/G.5\\%$ electrode exhibits the highest specific capacitance of $335.4\\mathrm{~F~g}^{-1}$ at a scan rate of $2~\\mathrm{mV}~\\mathrm{s}^{-1}$ , slightly higher than those of pure MXene $(330.2\\mathrm{~F~g}^{-1})$ , $M/\\mathrm{G}{\\cdot}1\\%$ $(308.0\\mathrm{~F~g}^{-1})$ , and $M/\\mathrm{G}{\\cdot}10\\%$ $(329.9\\mathrm{~F~g}^{-1})$ . It is worth noting that the $M/G{-}5\\%$ electrode could still maintain a very high specific capacitance of $100\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{g}}^{-1}$ with an unparalleled rate performance $30\\%$ at $10\\mathrm{~V~s~}^{-1}$ , Figure 4e), much higher than those of pure MXene $(6\\%)$ , $M/\\mathrm{G}{\\cdot}1\\%$ $(7\\%)$ , and $M/\\mathrm{G}{\\cdot}10\\%$ $(16\\%)$ , as well as previously reported MXene-based materials (Table S2, Supporting Information).[4,9,15,16,25] The rate capability of $M/G{-}5\\%$ can be attributed to the increased interlayer spacing caused by the incorporation of $\\mathrm{rGO}$ nanosheets in between MXene layers, while keeping its good conductivity. These characteristics further improve the diffusion and transportation of electrolyte ions and increase the surface area accessible to the electrolyte ions. $M/\\mathrm{G}{\\cdot}10\\%$ has the largest interlayer spacing of $1.67\\ \\mathrm{nm}$ among all the samples; however, the rate capability is much worse than that of $M/G{-}5\\%$ , which is probably due to the poor electrical conductivity (Table 1) and hydrophobic surface of rGO nanosheets.[26] Figure 4f shows the volumetric capacitance of pure MXene and the MXene/rGO electrodes. A high volumetric capacitance up to $1222\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ can be obtained for the pure MXene electrode at a scan rate of $2~\\mathrm{mV~s^{-1}}$ . To the best of our knowledge, this is the highest value for MXene-based electrodes reported up to now. Despite its much lower density $(3.1\\ \\mathrm{g}\\ \\mathrm{cm}^{-3})$ compared with pure MXene $(3.7\\ \\mathrm{g\\cm^{-3}})$ due to the incorporation of $\\mathtt{r G O}$ nanosheets, $M/G{-}5\\%$ hybrid can deliver a volumetric capacitance of $1040\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ at $2~\\mathrm{mV}~\\mathrm{s}^{-1}$ and can maintain 777 and $634~\\mathrm{F~cm}^{-3}$ at $100\\mathrm{mVs^{-1}}$ and $1\\mathrm{V}\\mathrm{s}^{-1}$ , respectively. The ultrahigh volumetric capacitance is highly comparable with, or in some cases much higher than, those of previously reported MXene-based materials (Figure 4f; Table S2, Supporting Information), such as MXene clay $(900\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3},$ ),[4] MXene/polypyrrole $(1000~\\mathrm{~F~}\\mathrm{cm}^{-3})$ ,[15] MXene $(340\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3},$ ),[9] MXene/CNTs $(390\\mathrm{~\\textit~{~F~}~}\\mathrm{cm}^{-3})$ ,[16] MXene/polyvinyl alcohol $(528\\ \\mathrm{F}\\ \\mathrm{cm}^{-3})$ ,[25] and MXene/graphene $(216\\ \\mathrm{F}\\ \\mathrm{cm}^{-3})$ ).[22] \n\nIn order to further investigate the nature of the charge storage process, the electrochemical kinetics of the $M/G{-}5\\%$ sample were evaluated through the Trasatti analysis method to quantify stored charges (q) at the straightforwardly ionaccessible outer surface $(q_{\\mathrm{o}})$ and the less easily accessible inner surface $(q_{\\mathrm{i}})$ during this process.[32] The total amount of stored charge $(q_{\\mathrm{T}})$ is composed of both outer and inner surface charges as follows[32] \n\n$$\nq_{\\mathrm{T}}=q_{\\mathrm{i}}+q_{\\mathrm{o}}\n$$ \n\nThe charge storage at the outer surface is independent of scan rates and non-diffusion-controlled, while the charge storage at the inner surface is a diffusion-controlled process. Thus, the total measured voltammetric charge $[q(\\nu)]$ could be expressed as a function of scan rates (v) through the following equation[32] \n\n$$\nq(\\nu)=q_{\\infty}+k\\nu^{-1/2}\n$$ \n\nwhere $k\\nu^{-1/2}$ represents the charge storage related to semi-infinite diffusion, $k$ is a constant, and $q_{\\infty}$ is the charge stored at a high scan rate $(\\nu\\to\\infty)$ equaling to $q_{\\mathrm{o}}$ . The dependence of $q$ on $\\nu^{-1/2}$ and $1/q$ on $\\nu^{1/2}$ is shown in Figure 5. The extrapolation of $q$ to $\\nu=0$ in Figure 5a gives the total charge $(q_{\\mathrm{T}})$ while extrapolation of $q$ to $\\nu\\to\\infty$ in Figure 5b can obtain the outer charge $(q_{\\mathrm{o}})$ . \n\nAs a consequence, the outer and total charges are calculated to be 239 and $373{\\mathrm{~C~g}}^{-1}$ , respectively. At a scan rate of $2~\\mathrm{mV~s^{-1}}$ , the practical charge storage is $335.4\\mathrm{~C~g^{-1}}$ , which accounts for $90\\%$ of the total charge, indicating high electrochemical utilization ratio of MXene during the charge/discharge process.[32] This means that most of the surfaces are fully accessible to electrolyte ions during the charge/discharge processes due to the increased interlayer spacing of MXene layers resulting from the prevention of face-to-face self-restacking of MXene layers in the hybrids. \n\nIn order to further verify the hypothesis of the increased interlayer spacing favorable for the rapid diffusion and transportation of ions, the impedance behaviors of the electrodes were studied by the complex model of capacitance $[C(\\omega)]$ .[33,34] The normalized $C^{\\prime}(\\omega)$ and $C^{\\prime\\prime}(\\omega)$ as a function of frequency for pure MXene and $M/G{-}5\\%$ electrodes are shown in Figure 5c,d. The $C^{\\prime}(\\omega)$ of $M/G{-}5\\%$ electrode decreases much slower than the pure MXene electrode with the increase of frequency, indicating the fast diffusion and transportation of electrolyte ions in the $M/G{-}5\\%$ electrode. This can be confirmed by the minimal characteristic relaxation time constant $\\tau_{0}$ of $192~\\mathrm{ms}$ (the minimum time needed to discharge all the energy with an efficiency of ${>}50\\%$ ), which is much smaller than those of pure MXene (4.4 s; Figure 5c), $M/\\mathrm{G}{\\cdot}1\\%$ (2 s; Figure S3b, Supporting Information), and $M/\\mathrm{G}{\\cdot}10\\%$ $(621~\\mathrm{ms}$ ; Figure S3c, Supporting Information) electrodes. Additionally, from the relationship between $Z^{\\prime}$ and $\\omega$ $(\\omega=2\\pi f)$ in the low-frequency region, as shown in Figure 5e, the $M/G.5\\%$ electrode presents the lowest slope among all the electrodes, demonstrating the smallest charge transfer resistance and best ion diffusion/transportation kinetics.[35] Therefore, $M/G{-}5\\%$ has the potential to deliver high power. The long-term cycling stability of $M/G{-}5\\%$ hybrid was further evaluated by repeating the CV test at $100\\ \\mathrm{mV\\s^{-1}}$ for $20\\ 000$ cycles. The $M/\\mathrm{G}{\\cdot}5\\%$ electrode exhibits excellent cycling stability with almost no capacitance deterioration after $20~000$ cycles (Figure 5f), which is highly comparable with the previously reported MXene-based materials.[4,9,16,25,36,37] \n\nIn order to evaluate the practical application of $M/G{-}5\\%$ hybrid, a symmetric supercapacitor was fabricated in $3~\\mathrm{~M~}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ aqueous electrolyte. Figure 6a shows the CV curves of $M/G{-}5\\%$ -based symmetric supercapacitors at different scan rates. It can be seen that all the CV curves exhibit a pair of redox peaks, which are in accordance with the CV curves measured in the three-electrode system (Figure 4b). In addition, all the CV curves maintain similar shapes without any obvious distortion when the scan rates increase from 2 to $100\\ \\mathrm{mV\\s^{-1}}$ , indicating promising rate capabilities. Figure 6b displays the specific capacitance of MXene- and $M/G{-}5\\%$ -based symmetric supercapacitors at different scan rates. Although the $M/G{-}5\\%$ - based symmetric supercapacitor delivers a specific capacitance of $80.3\\mathrm{~F~g}^{-1}$ (based on the total weight of electrodes), slightly lower than those of the MXene-based symmetric supercapacitor $(85.5\\mathrm{~F~}\\mathrm{g}^{-1})$ , it exhibits a specific capacitance up to $24\\mathrm{~F~g^{-1}}$ at $2\\mathrm{~V~s~}^{-1}$ (Figure 6b), more than twice that of the MXene-based symmetric supercapacitor $(10.1\\mathrm{~F~g^{-1}})$ . Ragone plots of the assembled symmetric supercapacitors are shown in Figure  6c,d. The $M/G{-}5\\%$ symmetric supercapacitor could deliver a maximum energy density of $10.5~\\mathrm{Wh~kg^{-1}}$ at a power density of $80.3~\\mathrm{W~kg^{-1}}$ , and performs with an energy density of \n\n![](images/d556d8dc75059cbcb381a76cba3a3e2d5d29fb379c85f0130a34bbb324a3e733.jpg) \nFigure 5.  a) Inverse of stored charge (q) versus square root of the scan rate (v). b) Stored charge versus inverse of the square root of the scan rate Normalized real and imaginary capacitances of the ${\\mathsf c})$ MXene and d) $M/C.5\\%$ electrodes. e) Linear fit showing the relationship between $Z^{\\prime}$ and $\\omega^{-1/2}$ in the low-frequency region. f) Cycling stability of the $M/\\mathsf{G}{\\cdot}5\\%$ electrode measured at $\\mathsf{100}\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-\\mathsf{I}}$ . \n\n$3.3\\mathrm{\\Wh\\kg^{-1}}$ when the power density is increased to $24\\ensuremath{\\mathrm{kW}}\\ensuremath{\\mathrm{kg}^{-1}}$ (Figure 6c). Due to the high density, $M/G{-}5\\%$ -based symmetric supercapacitors could achieve an ultrahigh volumetric energy of $32.6~\\mathrm{Wh~L^{-1}}$ and retain $10.3\\mathrm{\\Wh\\L^{-1}}$ at an ultrahigh volumetric power density of $74.4~\\mathrm{\\kW}~\\mathrm{L}^{-1}$ . The maximum volumetric energy density is highly comparable with, and even much higher than, those of previously reported carbon-based symmetric supercapacitors in organic electrolytes (Figure 6d), such as N-enriched carbon $(19.6~\\mathrm{Wh}~\\mathrm{L}^{-1})$ ,[38] graphene/activated carbon $(22.3\\mathrm{\\Wh\\L^{-1}})$ ),[39] carbide-derived carbon $(7.49\\mathrm{~Wh~L^{-1}})$ ), and activated graphene (43 Wh $\\mathrm{L}^{-1}$ ).[40] In addition, the energy density of our $M/G{-}5\\%$ -based symmetric supercapacitor decreases gradually compared with MXene-based symmetric supercapacitors, indicating the advantage of $M/G.5\\%$ hybrid. Since the weight of active materials is about $30\\%$ of the total weight of the packaged commercial supercapacitor, a factor of 3–4 is frequently used to extrapolate the energy density of the device from the performance of the electrode material.[41] Therefore, the energy density of $10.5~\\mathrm{Wh~kg^{-1}}$ of $M/G.5\\%$ will translate into $2.6~\\mathrm{Wh~kg^{-1}}$ for the device. However, this is just an estimate, and real devices must be tested to determine the correct values. \n\nIn order to further investigate the effect of the structure on the electrochemical performances, we calculated the layer ratio of MXene $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x})$ to rGO in the hybrid electrodes (detailed calculation process is given in the Supporting Information). For $M/\\mathrm{G}{\\cdot}1\\%$ hybrid, the layer ratio of MXene to rGO is about 18.2:1, meaning that every 18 or 19 layers of MXene correspond to 1 layer of rGO (Figure 7a). Thus, the face-to-face restacking of MXene nanosheets cannot be effectively prohibited, and this hybrid is relatively dense and has high electrical conductivity $(3326\\ \\mathrm{S\\cm^{-1}},$ ). However, the interlayer spacing of MXene is very small $(1.46\\mathrm{nm})$ ), unfavorable for the rapid diffusion and transportation of electrolyte ions during fast charging/discharging process, leading to moderate rate capability. With regard to $M/\\mathrm{G}{\\cdot}10\\%$ hybrid, the layer ratio of MXene to rGO is calculated to be 1.7:1. That is to say, every one or two layers of MXene correspond to one layer of rGO (Figure 7c). In this manner, the restacking of MXene is effectively prevented; thus, this hybrid has a very large interlayer spacing of MXene $\\left[1.67\\ \\mathrm{nm}\\right]$ ). Nevertheless, the electrical conductivity is significantly deteriorated $(1231\\ \\mathrm{S\\cm^{-1}},$ , which is detrimental to the rapid electron transfer. In sharp contrast, for $M/\\mathrm{G}{\\cdot}5\\%$ hybrid, the layer ratio of MXene to $\\mathrm{rGO}$ is about 3.5:1, indicating that every three or four layers of MXene correspond to one layer of rGO (Figure 7b). Thus, this hybrid has relatively high density $(3.1\\ \\mathrm{g}\\ \\mathrm{cm}^{-3})$ and electrical conductivity $(2261\\ \\mathrm{S\\cm^{-1}}$ ). Additionally, the restacking of MXene is greatly mitigated, resulting in relatively larger interlayer spacing $(1.51\\ \\mathrm{nm})$ , which is conducive to the rapid transport and diffusion of electrolyte ions and transfer of electrons during fast charge/ discharge processes. As a consequence, the $M/G{-}5\\%$ hybrid displays high specific capacitance and excellent rate capability. \n\n![](images/1e62b04037ff57f4d90f3eb077a05a939c9d4ddd6c0db4a8f91b4dfe66d596fd.jpg) \nFigure 6.  a) CV curves and b) gravimetric capacitance of MXene and M/ $6.5\\%$ -based symmetric supercapacitors at different scan rates. c) Gravimetric and d) volumetric energy and power densities for our MXene- and $M/C-5\\%$ -based symmetric supercapacitors, compared with those of previously reported carbon-based symmetric supercapacitors in organic electrolytes, such as N-enriched carbon,[38] graphene/activated carbon,[39] and carbide-derived carbon.[42] \n\n![](images/e5421bf756716953b53315daefadf591c7e377984254d822d5bf444e25f1057f.jpg) \nFigure 7.  Schematic illustration of MXene/rGO hybrids showing the layer ratios of rGO to $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ MXene: a) 1:18 or 1:19 for M/G-1%, b) 1:3 or 1:4 for $M/C-5\\%$ , and c) 1:1 or 1:2 for $M/\\mathsf{G}\\cdot\\mathsf{l}0\\%$ . \n\nThe electrochemical performances such as high volumetric capacitance and energy density as well as improved rate capability can be attributed to the following aspects: (i) insertion of $\\mathrm{rGO}$ nanosheets in between MXene layers could not only effectively inhibit the selfrestacking of MXene layers, but also greatly increase the interlayer spacing of MXene layers to form well-aligned alternating ordered structures. This could significantly enhance the surface accessibility to electrolyte ions, and facilitate the rapid diffusion and transportation of electrolyte ions during the charge/discharge processes, consequently leading to enhanced electrochemical utilization of MXene and high rate capability. (ii) The electrical conductivity is favorable for the rapid transfer of ions during the charge/discharge process, effectively decreasing the internal resistance and ensuring high power delivery. (iii) The high density of the electrodes allows for the achievement of high volumetric performances. \n\n# 3. Conclusions \n\nIn summary, we have demonstrated a simple method to prepare MXene/rGO flexible films through electrostatic self-assembly of negatively charged MXene and positively charged chemically reduced graphene oxide. rGO nanosheets are inserted in between the MXene layers to form a well-aligned ordered structure, which effectively prevents the self-restacking of MXene layers, resulting in an increase in interlayer spacing and facilitating the rapid diffusion and transporn of electrolyte ions. When employed as electrode materials for supercapacitors, the resultant freestanding $M/G{-}5\\%$ film with superior electrical conductivity exhibits an outstanding volumetric capacitance of $1040~\\mathrm{~F~}~\\mathrm{cm}^{-3}$ at a scan rate of $2\\ \\mathrm{mV}\\ \\mathrm{s}^{-1}$ and spectacular rate capability with $61\\%$ capacitance retention at $1\\ \\mathrm{~V~}\\ \\mathrm{s}^{-1}$ . Additionally, the film electrode possesses excellent cycling stability with almost no capacitance decay after $20~000$ cycles. Our fabricated symmetric supercapacitor displays an ultrahigh volumetric energy density of $32.6~\\mathrm{{Wh}~\\mathrm{{L^{-1}}}}$ and a maximum volumetric power density up to $74.4\\mathrm{~kW~L^{-1}}$ , much higher than those previously reported carbon- and MXenebased materials in aqueous electrolytes. Due to the improvement in electrochemical performance and hybrid structure, we firmly believe that this work may pave the way for design and development of flexible MXene-based materials in future applications which require ultrahigh volumetric capacitances and high rate performances such as portable and microsized integrated energy storage devices. \n\n# 4. Experimental Section \n\nPreparation of Delaminated $\\overline{{T}}\\slash_{3}C_{2}\\overline{{T}}_{x}$ MXene Solution: Multilayered $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ was synthesized through etching of $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ powders, which were prepared as described elsewhere.[4] Typically, $\\rceil\\textrm{g}$ of LiF (Alfa Aesar, $98.5\\%)$ ) was dissolved in $70~\\mathrm{mL}$ of $9\\mathrm{~M~HCl}$ . Then $\\rceil\\textrm{g}$ of $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ powders was added into the above mixture solution and kept at $35^{\\circ}\\mathsf{C}$ for $24\\ h$ while stirring. Afterward, the solid residue was washed with deionized water and then centrifuged until the $\\mathsf{p H}$ of the supernatant was above 5, followed by vacuum filtration and drying under vacuum to obtain multilayered $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ powders. \n\nAbout $\\mathsf{\\Omega}_{\\mathsf{g}}$ of the obtained multilayered $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ powders was dispersed in $250~\\mathsf{m L}$ of deionized water and bath sonicated for $60~\\mathsf{m i n}$ under Ar flow. After centrifugation at 3500 rpm for $60~\\mathrm{{min}}$ , the dark green supernatant was collected to obtain the delaminated MXene suspension, whose concentration was determined by filtering a known volume of the suspension and measuring the weight of the film after vacuum drying. \n\nFabrication of Flexible MXene/rGO Hybrid Films: rGO nanosheets were prepared through hydrazine reduction of GO,[23] which were then dispersed in the PDDA (average molecular weight: 100 000–200 000) solution by probe sonication to yield a suspension with a concentration of $0.5~\\mathsf{m g}\\mathsf{m}\\mathsf{L}^{-1}$ . \n\nMXene/rGO hybrid electrode films were prepared through an electrostatic self-assembly process. Typically, the G-PDDA suspension was added into $20~\\mathsf{m L}$ of MXene suspension $(0.5\\mathrm{\\mg\\mL^{-1}})$ drop by drop under stirring. Then the mixture was subjected to probe sonication for $10~\\mathsf{m i n}$ , filtered using a polypropylene membrane with copious deionized water, and then dried in a vacuum hood for $12\\mathrm{~h~}$ to obtain the flexible and freestanding MXene/rGO films (denoted as ${\\mathsf{M}}/{\\mathsf{G}}{\\cdot}x,$ where $x$ is the mass ratio of rGO in the hybrid). $M/\\mathrm{G}.7\\%$ , $M/\\mathsf{G}{\\cdot}5\\%$ , and $M/{\\sf C}\\cdot10\\%$ could be obtained through changing the volume of G-PDDA suspension with 0.2, 1, and $2.2~\\mathsf{m L}$ , respectively. For comparison, pure MXene film was prepared without the presence of rGO. \n\nMaterial Characterizations: The morphology of MXene and MXene/ rGO hybrids was observed using a SEM (Zeiss Surra 50VP, Germany) and a TEM (JEOL JEM-2100, Japan) using an accelerating voltage of $200\\ \\mathsf{k V}.$ XRD patterns were measured by a powder diffractometer (Rigaku Smart Lab, Japan) with $\\mathsf{C u}\\ \\mathsf{K}\\alpha$ radiation $(\\lambda=1.54\\mathrm{~\\AA}$ at a step size of $0.02^{\\circ}$ with 0.5 s dwelling time. Raman spectra were recorded on an inVia Renishaw confocal spectrometer with a $633\\ n m$ laser as an excitation source. The laser power used in the measurements was $10\\%$ and spectra were recorded during $\\boldsymbol{120\\ s}$ . Chemical compositions of the samples were further analyzed by high-resolution $\\mathsf{X P S}$ recorded with a Physical Electronics VersaProbe 5000 instrument equipped with a monochromatic Al $\\mathsf{K}\\alpha$ X-ray source ( $h\\nu=1486.6$ eV). Peak fitting was carried out using CasaXPS version 2.3.17PR1.1. Zeta potential was measured using a Malvern Zetasizer Nano ZS (Malvern Instruments, USA). The electrical conductivity of the films was measured using a four-point probe instrument (ResTest v1, Jandel Engineering, UK) by repeating the test in at least six different positions. The thickness of the films was measured using a high-accuracy submicrometer digimatic micrometer (293-130, Mitutoyo) with a resolution of $0.1~{\\upmu\\mathrm{m}}$ . Nitrogen adsorption–desorption isotherms were measured on a Micromeritics ASAP 2020 gas adsorption analyzer at $77~\\mathsf{K}.$ . \n\nElectrochemical Measurements: The electrochemical performances were first measured in a three-electrode configuration, in which the prepared flexible films, overcapacitive activated carbon, and $\\mathsf{A g/A g C l}$ in $\\rceil\\bowtie\\mathsf{K C l}$ were used as the working, counter, and reference electrodes, respectively. The symmetric supercapacitors were assembled with two flexible films with the exactly same size separated by two Celgard membranes used as separators. All the electrochemical tests were carried out using a VMP3 (Biologic, France) electrochemical station in $3\\mathrm{~\\textmu~}\\mathsf{H}_{2}\\mathsf{S}\\mathsf{O}_{4}$ at room temperature. Cycling stability was measured by repeating the CV test for 20 000 cycles at $100\\:\\mathrm{mVs^{-1}}$ . The electrochemical impedance spectroscopy was performed at open circuit potential within a frequency range from $700~\\mathsf{k H z}$ to $10~\\mathsf{m H z}$ at an amplitude of $5~\\mathsf{m V}.$ \n\nGravimetric specific capacitance $(C_{\\mathrm{g}})$ was calculated through the following equation \n\n$$\nC_{_{\\mathtt{g}}}=\\frac{\\rceil}{\\Delta V m\\nu}\\int i\\mathrm{d}V\n$$ \n\nwhere $i$ is the current density, $V$ is the potential window, $\\nu$ is the potential scan rate, and $m$ is the mass of the electrodes. The volumetric capacitance $(C_{\\vee})$ was calculated according to the following equation \n\n$$\nC_{\\mathrm{v}}=\\rho C_{\\mathrm{g}}\n$$ \n\nwhere $\\rho$ is the apparent density of the films, which was measured according to the following formula \n\n$$\n\\rho=m/S d\n$$ \n\nwhere m (g) is the mass of the dried calendared electrode, S $(\\mathsf{c m}^{2})$ and d (cm) are the area and thickness of the film electrode, respectively. The gravimetric and volumetric energy densities $(E_{\\mathrm{g}},\\ E_{\\mathrm{v}})$ as well as power density $(P_{\\mathrm{g}},P_{\\mathrm{v}})$ were calculated according to the following equations \n\n$$\n\\begin{array}{r l}&{E_{\\mathrm{g}}=\\int V I d t}\\\\ &{P_{\\mathrm{g}}=E_{\\mathrm{g}}/\\Delta t}\\\\ &{E_{\\mathrm{v}}=\\rho E_{\\mathrm{g}}}\\\\ &{P_{\\mathrm{v}}=\\rho P_{\\mathrm{g}}}\\end{array}\n$$ \n\nwhere $\\Delta t$ is the discharge time, and $M$ is the total weight of electrode materials. The real $C^{\\prime}(\\omega)$ and imaginary part $C^{\\prime\\prime}(\\omega)$ capacitances can be calculated through the following equations \n\n$$\n\\begin{array}{r}{C^{\\prime}(\\omega)=\\frac{-Z^{\\prime\\prime}(\\omega)}{\\omega\\left|Z(\\omega)\\right|^{2}}}\\\\ {C^{\\prime\\prime}(\\omega)=\\frac{Z^{\\prime}(\\omega)}{\\omega\\left|Z(\\omega)\\right|^{2}}}\\end{array}\n$$ \n\nwhere $Z^{\\prime}(\\omega),Z^{\\prime\\prime}(\\omega)$ and $\\omega$ are the respective real and imaginary parts of the complex impedance $Z\\left(\\omega\\right)$ and angular frequency given by $\\omega=2\\pi f.$ \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nJ.Y. acknowledges the financial support from National Natural Science Foundation of China (21571040) and China Scholarship Council (CSC). Dr. Narendra Kurra is thanked for the helpful discussion on the electrochemical results. The electrochemistry work at Drexel University was supported by the Fluid Interface Reactions, Structures & Transport, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\nenergy density, graphene, MXene, supercapacitors, volumetric performance \n\nReceived: March 8, 2017 \nRevised: April 8, 2017 \nPublished online: June 30, 2017 \n\n[1]\t M. F.  El-Kady, V.  Strong, S.  Dubin, R. B.  Kaner, Science 2012, 335, 1326. \n[2]\t D.  Shan, J.  Yang, W.  Liu, J.  Yan, Z.  Fan, J. Mater. Chem. A 2016, 4, 13589. \n[3]\t M. Acerce, D. Voiry, M. Chhowalla, Nat. Nanotechnol. 2015, 10, 313. \n[4]\t M. Ghidiu, M. R. Lukatskaya, M.-Q. Zhao, Y. Gogotsi, M. W. Barsoum, Nature 2014, 516, 78. \n[5]\t B. Mendoza-Sánchez, Y. Gogotsi, Adv. Mater. 2016, 28, 6104. \n[6]\t Q. Wang, J. Yan, Z. Fan, Energy Environ. Sci. 2016, 9, 729. \n[7]\t B. Anasori, M. R. Lukatskaya, Y. Gogotsi, Nat. Rev. Mater. 2017, 2, 16098. \n[8]\t M.  Naguib, M.  Kurtoglu, V.  Presser, J.  Lu, J.  Niu, M.  Heon, L. Hultman, Y. Gogotsi, M. W. Barsoum, Adv. Mater. 2011, 23, 4248. \n[9]\t M. R. Lukatskaya, O. Mashtalir, C. E. Ren, Y. Dall’Agnese, P. Rozier, P. L.  Taberna, M.  Naguib, P.  Simon, M. W.  Barsoum, Y.  Gogotsi, Science 2013, 341, 1502. \n[10]\t O.  Mashtalir, M. R.  Lukatskaya, M.-Q.  Zhao, M. W.  Barsoum, Y. Gogotsi, Adv. Mater. 2015, 27, 3501. \n[11]\t S.  Kajiyama, L.  Szabova, K.  Sodeyama, H.  Iinuma, R.  Morita, K. Gotoh, Y. Tateyama, M. Okubo, A. Yamada, ACS Nano 2016, 10, 3334. \n[12]\t F.  Shahzad, M.  Alhabeb, C. B.  Hatter, B.  Anasori, S.  Man Hong, C. M. Koo, Y. Gogotsi, Science 2016, 353, 1137. \n[13]\t C. E.  Ren, K. B.  Hatzell, M.  Alhabeb, Z.  Ling, K. A.  Mahmoud, Y. Gogotsi, J. Phys. Chem. Lett. 2015, 6, 4026. \n[14]\t Q.  Xue, H.  Zhang, M.  Zhu, Z.  Pei, H.  Li, Z.  Wang, Y.  Huang, Y.  Huang, Q.  Deng, J.  Zhou, S.  Du, Q.  Huang, C.  Zhi, Adv. Mater. 2017, 29, 1604847. \n[15]\t M.  Boota, B.  Anasori, C.  Voigt, M.-Q.  Zhao, M. W.  Barsoum, Y. Gogotsi, Adv. Mater. 2016, 28, 1517. \n[16]\t M.-Q.  Zhao, C. E.  Ren, Z.  Ling, M. R.  Lukatskaya, C.  Zhang, K. L.  Van Aken, M. W.  Barsoum, Y.  Gogotsi, Adv. Mater. 2015, 27, 339. \n[17]\t M.  Zhu, Y.  Huang, Q.  Deng, J.  Zhou, Z.  Pei, Q.  Xue, Y.  Huang, Z.  Wang, H.  Li, Q.  Huang, C.  Zhi, Adv. Energy Mater. 2016, 6, 1600969. \n[18]\t Y. Wang, H. Dou, J. Wang, B. Ding, Y. Xu, Z. Chang, X. Hao, J. Power Sources 2016, 327, 221. \n[19]\t R. B.  Rakhi, B.  Ahmed, D. H.  Anjum, H. N.  Alshareef, ACS Appl. Mater. Interfaces 2016, 8, 18806. \n[20]\t Y.  Dall’Agnese, P.  Rozier, P.-L.  Taberna, Y.  Gogotsi, P.  Simon, J. Power Sources 2016, 306, 510. \n[21]\t W.-Y.  Tsai, R.  Lin, S.  Murali, L.  Li Zhang, J. K.  McDonough, R. S. Ruoff, P.-L. Taberna, Y. Gogotsi, P. Simon, Nano Energy 2013, 2, 403. \n[22]\t H.  Li, Y.  Hou, F.  Wang, M. R.  Lohe, X.  Zhuang, L.  Niu, X.  Feng, Adv. Energy Mater. 2017, 7, 1601847. \n[23]\t J.  Yan, Z.  Fan, T.  Wei, W.  Qian, M.  Zhang, F.  Wei, Carbon 2010, 48, 3825. \n[24]\t J.  Halim, S.  Kota, M. R.  Lukatskaya, M.  Naguib, M.-Q.  Zhao, E. J. Moon, J. Pitock, J. Nanda, S. J. May, Y. Gogotsi, M. W. Barsoum, Adv. Funct. Mater. 2016, 26, 3118. \n[25]\t Z. Ling, C. E. Ren, M. Q. Zhao, J. Yang, J. M. Giammarco, J. S. Qiu, M. W. Barsoum, Y. Gogotsi, Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 16676. \n[26]\t D.  Li, M. B.  Muller, S.  Gilje, R. B.  Kaner, G. G.  Wallace, Nat. Nanotechnol. 2008, 3, 101. \n[27]\t M. Hu, Z. Li, T. Hu, S. Zhu, C. Zhang, X. Wang, ACS Nano 2016, 10, 11344. \n[28]\t M.  Ghidiu, J.  Halim, S.  Kota, D.  Bish, Y.  Gogotsi, M. W.  Barsoum, Chem. Mater. 2016, 28, 3507. \n[29]\t R. B. Rakhi, B. Ahmed, M. N. Hedhili, D. H. Anjum, H. N. Alshareef, Chem. Mater. 2015, 27, 5314. \n[30]\t M. R.  Lukatskaya, S.-M.  Bak, X.  Yu, X.-Q.  Yang, M. W.  Barsoum, Y. Gogotsi, Adv. Energy Mater. 2015, 5, 1500589. \n[31]\t V.  Augustyn, J.  Come, M. A.  Lowe, J. W.  Kim, P. L.  Taberna, S. H.  Tolbert, H. D.  Abruna, P.  Simon, B.  Dunn, Nat. Mater. 2013, 12, 518. \n[32]\t S. Ardizzone, G. Fregonara, S. Trasatti, Electrochim. Acta 1990, 35, 263. \n[33]\t D.  Pech, M.  Brunet, H.  Durou, P. H.  Huang, V.  Mochalin, Y. Gogotsi, P. L. Taberna, P. Simon, Nat. Nanotechnol. 2010, 5, 651. \n[34]\t X. Yang, C. Cheng, Y. Wang, L. Qiu, D. Li, Science 2013, 341, 534. \n[35]\t M.  Fan, Y.  Chen, Y.  Xie, T.  Yang, X.  Shen, N.  Xu, H.  Yu, C.  Yan, Adv. Funct. Mater. 2016, 26, 5019. \n[36]\t P. T.  Yan, R. J.  Zhang, J.  Jia, C.  Wu, A. G.  Zhou, J.  Xu, X. S.  Zhang, J. Power Sources 2015, 284, 38. \n[37]\t M. M.  Hu, Z. J.  Li, H.  Zhang, T.  Hu, C.  Zhang, Z.  Wu, X. H.  Wang, Chem. Commun. 2015, 51, 13531. \n[38]\t Y. J.  Kim, Y.  Abe, T.  Yanagiura, K. C.  Park, M.  Shimizu, T.  Iwazaki, S. Nakagawa, M. Endo, M. S. Dresselhaus, Carbon 2007, 45, 2116. \n[39]\t C. Zheng, X. Zhou, H. Cao, G. Wang, Z. Liu, J. Power Sources 2014, 258, 290. \n[40]\t T.  Kim, G.  Jung, S.  Yoo, K. S.  Suh, R. S.  Ruoff, ACS Nano 2013, 7, 6899. \n[41]\t Y. Gogotsi, P. Simon, Science 2011, 334, 917. \n[42]\t M.  Arulepp, J.  Leis, M.  Latt, F.  Miller, K.  Rumma, E.  Lust, A. F. Burke, J. Power Sources 2006, 162, 1460. " + }, + { + "id": "10.1126_sciadv.1602076", + "DOI": "10.1126/sciadv.1602076", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.1602076", + "Relative Dir Path": "mds/10.1126_sciadv.1602076", + "Article Title": "A highly stretchable, transparent, and conductive polymer", + "Authors": "Wang, Y; Zhu, CX; Pfattner, R; Yan, HP; Jin, LH; Chen, SC; Molina-Lopez, F; Lissel, F; Liu, J; Rabiah, NI; Chen, Z; Chung, JW; Linder, C; Toney, MF; Murmann, B; Bao, Z", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Previous breakthroughs in stretchable electronics stem from strain engineering and nullocomposite approaches. Routes toward intrinsically stretchable molecular materials remain scarce but, if successful, will enable simpler fabrication processes, such as direct printing and coating, mechanically robust devices, and more intimate contact with objects. We report a highly stretchable conducting polymer, realized with a range of enhancers that serve a dual function: (i) they change morphology and (ii) they act as conductivity-enhancing dopants in poly(3,4-ethylene-dioxythiophene): poly(styrenesulfonate) (PEDOT: PSS). The polymer films exhibit conductivities comparable to the best reported values for PEDOT: PSS, with over 3100 S/cm under 0% strain and over 4100 S/cm under 100% strain-among the highest for reported stretchable conductors. It is highly durable under cyclic loading, with the conductivity maintained at 3600 S/cm even after 1000 cycles to 100% strain. The conductivity remained above 100 S/cmunder 600% strain, with a fracture strain of 800%, which is superior to even the best silver nullowire-or carbon nullotube-based stretchable conductor films. The combination of excellent electrical and mechanical properties allowed it to serve as interconnects for field-effect transistor arrays with a device density that is five times higher than typical lithographically patterned wavy interconnects.", + "Times Cited, WoS Core": 1260, + "Times Cited, All Databases": 1384, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000397044000024", + "Markdown": "# A P P L I E D S C I E N C E S A N D E N G I N E E R I N G \n\n# A highly stretchable, transparent, and conductive polymer \n\n2017 $\\circledcirc$ The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\nYue Wang,1 Chenxin Zhu,2 Raphael Pfattner,1 Hongping Yan,3 Lihua Jin,1,4 Shucheng Chen,1 Francisco Molina-Lopez,1 Franziska Lissel,1 Jia Liu,1 Noelle I. Rabiah,1 Zheng Chen,1 Jong Won Chung,1,5 Christian Linder,4 Michael F. Toney,3 Boris Murmann,2 Zhenan Bao1\\* \n\nPrevious breakthroughs in stretchable electronics stem from strain engineering and nanocomposite approaches. Routes toward intrinsically stretchable molecular materials remain scarce but, if successful, will enable simpler fabrication processes, such as direct printing and coating, mechanically robust devices, and more intimate contact with objects. We report a highly stretchable conducting polymer, realized with a range of enhancers that serve a dual function: (i) they change morphology and (ii) they act as conductivity-enhancing dopants in poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). The polymer films exhibit conductivities comparable to the best reported values for PEDOT:PSS, with over $3100~5/{\\mathrm{cm}}$ under $0\\%$ strain and over $4100\\mathsf{S}/\\mathsf{c m}$ under $100\\%$ strain— among the highest for reported stretchable conductors. It is highly durable under cyclic loading, with the conductivity maintained at $3600\\mathsf{S}/\\mathsf{c m}$ even after 1000 cycles to $100\\%$ strain. The conductivity remained above $100\\mathsf{S}/\\mathsf{c m}$ under $600\\%$ strain, with a fracture strain of $800\\%$ , which is superior to even the best silver nanowire– or carbon nanotube– based stretchable conductor films. The combination of excellent electrical and mechanical properties allowed it to serve as interconnects for field-effect transistor arrays with a device density that is five times higher than typical lithographically patterned wavy interconnects. \n\n# INTRODUCTION \n\nRecent advancements in stretchable electronics have blurred the interfaces between human and machine $(\\boldsymbol{l},\\boldsymbol{2})$ . Devices such as epidermal electronics, implantable sensors, and hemispherical eye cameras all rely on the intimate contact between devices and curvilinear surfaces of various biological systems while operating with stability under up to $100\\%$ strain (3–5). The most successful concept leading to such devices builds on linking rigid islands of active components [that is, transistors, lightemitting diodes (LEDs), or photovoltaics] with stretchable interconnects $(1,3,6,7)$ . Hence, developing conductors that can retain good electrical performance under high mechanical strain is paramount. \n\nStretchable conductors have been fabricated via two main routes: strain engineering and nanocomposites (1, 8, 9). In the first approach, nonstretchable inorganic materials, such as metals, are geometrically patterned into wavy lines that can be extended when the underneath elastomer substrate is stretched (10). Alternatively, depositing a thin layer of conducting materials such as metals, carbon nanotubes, or graphene on a prestrained substrate leads to the formation of periodic buckles upon the release of the strain, which allows the material to accommodate further cycles of stretching up to the initial prestrained value (5). A kirigami design or microcracks have also been applied to sheets of flexible materials to enable macroscopic stretching motion (11–13). These methods demonstrate the possibility of transforming virtually any rigid materials into stretchable materials while maintaining their electrical properties. However, the fabrication methods involved are usually complicated, and it is challenging to achieve high device density owing to the large geometric patterns required for high stretchability. In addition, the buckling and kirigami methods lead to out-of-plane patterns, which could be difficult to encapsulate and disadvantageous for devices that require planar interfaces or lower profiles. \n\nEmbedding a conductive filler in an insulating elastomeric matrix to form a nanocomposite is the second major route toward stretchable conductors (8, 14). Typically, one-dimensional materials such as carbon nanotubes (CNTs) and silver nanowires are chosen as the conductive fillers because of their high aspect ratios (15–17). Metal nanoparticles or flakes have also been shown to be good filler materials under specific conditions because of their ability to self-organize upon stretching (7, 18). Despite the versatility and large number of material choices, the percolationdependent conductivity is highly strain-sensitive and remains a hurdle for device miniaturization and cycling stability (8). \n\nTo achieve a highly stretchable and highly conductive material that is readily solution-processable and patternable, an intrinsically stretchable conductor is desirable. Conducting polymers are good candidates because of the flexibility in tuning the molecular structures and electrical and mechanical properties. Their solution processability offers additional advantages for large-scale production of flexible electronics. Unfortunately, high conductivity and high stretchability have not been achieved simultaneously for conducting polymers (19–21). \n\nIn general, to achieve high conductivity, high crystallinity and low insulating content are required. However, to render a polymer film stretchable, a high degree of disorder with chain folding is advantageous to create a large free volume for polymer chain movement and unfolding when being stretched (22, 23). Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) has the highest reported conductivity among solutionprocessed polymers but has a fracture strain of as low as ${\\sim}5\\%$ (20). Previous efforts enabled the stretching of PEDOT:PSS by incorporating plasticizers such as Zonyl or Triton (19–21). However, the enhanced stretchability often results in much lower conductivities, and the value further decreases with the application of strain. As yet, the best reported value is $550\\mathrm{S}/\\mathrm{cm}$ under $0\\%$ strain and a conductivity of $13\\mathrm{S}/\\mathrm{cm}$ under a fracture strain of $188\\%$ (20). Hence, these materials have generally been used as pressure or strain sensors where a large change in electrical signal upon strain is desirable, but they fail to serve as interconnects. \n\nInterconnects for various rigid electrical components in circuits require an intrinsically stretchable conducting polymer with conductivity $>1000~\\mathrm{S/cm}$ at ${>}100\\%$ strain and minimal temperature dependence. \n\nHere, we demonstrate a method for creating highly stretchable and conductive PEDOT films with high cycling stability by incorporating ionic additives–assisted stretchability and electrical conductivity (STEC) enhancers (Fig. 1, A and B). The resulting PEDOT:PSS films are both highly conductive and stretchable (higher than $4100\\ \\mathrm{S}/\\mathrm{cm}$ under $100\\%$ strain), giving rise to transistor arrays up to five times higher in island-to-interconnect ratio as compared to those using wavy metal interconnects. \n\n# RESULTS Selection of STEC enhancers \n\nWe rationalized that high stretchability requires polymer films with both hard and soft domains, typically seen with hydrogenated styrene ethylene butylene styrene (SEBS) block copolymers or polyurethane elastomers (23). Unfortunately, both PEDOT and PSS are semicrystalline polymers with no observable glass transition temperatures (24). Therefore, the STEC enhancers need to partially soften polymer chains to create soft domains in order to achieve high fracture strain. To promote high conductivity, it is important to have good connectivity between PEDOT-rich domains, which requires a weakened electrostatic interaction between PEDOT and PSS to allow PEDOT to partially aggregate to form a “hard” conductive network inside a soft PSS matrix (Fig. 1D). Previous studies reported various additives used to promote some of the effects (20, 21, 25). However, either solely improved conductivity or solely improved stretchability was reported. Here, we introduce a new approach, in which STEC enhancers soften the PSS domains and promote better connectivity and higher crystallinity in PEDOT regions while further enhancing electrical conductivity through doping. \n\nWe identified a number of effective STEC enhancers, including ionic compounds such as dioctyl sulfosuccinate sodium salt, sodium dodecylbenzenesulfonate, dodecylbenzenesulfonic acid, and ionic liquids (table S1 and fig. S1). All these molecules have sulfonate or sulfonimide anions, which are effective dopants for conducting polymers, including PEDOT (26). We focus our study on the ionic liquids because of the large number of commercially available varieties. These compounds not only effectively reduce Young’s moduli of PEDOT:PSS bulk film by as much as 50 times and render it highly extensible, but also preserve or increase the conductivity (table S1 and fig. S1). \n\nWe found that a synergistic effect on both conductivity and stretchability can be achieved when the STEC enhancers satisfy the following two characteristics: (i) good solubility in water and the PEDOT:PSS matrix and (ii) highly acidic anions that can act as effective dopants \n\n![](images/b511b4d1436bcb8ea2b05bffb7d0b9b7150eaaef8ab775aa9ade5f800b001d5b.jpg) \nFig. 1. Chemical structures and schematic representation. (A and B) Chemical structures of PEDOT:PSS (A) and representative STEC enhancers (B) (see complete list in the Supplementary Materials). (C and D) Schematic diagram representing the morphology of a typical PEDOT:PSS film (C) versus that of a stretchable PEDOT film with STEC enhancers (D). (E) Photograph showing a freestanding PEDOT/STEC film being stretched. (F and G) Stress/strain (F) and strain cycling behavior (G) of freestanding PEDOT/STEC films. \n\nWang et al., Sci. Adv. 2017; 3 : e1602076 10 March 2017 for PEDOT. Through the evaluation of electrical and mechanical properties of freestanding PEDOT/STEC films, we found that STEC enhancers 1 to 3 (Fig. 1A) lead to both high conductivity and good stretchability (Fig. 1, E and F, and sections S1 and S2). Even with as high as 40 to 50 weight $\\%$ (wt $\\%$ ) incorporation of STEC enhancers, the rheological characteristics of the bulk films are similar to those of viscoelastic solids (Fig. 1G and sections S1 and S2). Therefore, we chose these systems for further investigations. \n\n# Highly conductive and stretchable PEDOT film supported on elastic substrates \n\nStretchable PEDOT is characterized using thin films directly coated onto SEBS elastic substrates to evaluate their electrical behavior as transparent, thin-film electronic components. When stretched, an initial increase in conductivity by almost three times to up to $3390~\\mathrm{S/cm}$ under $100\\%$ strain was observed along the stretching direction $(\\upsigma_{||})$ , but it decreased in the perpendicular direction $(\\upsigma_{\\bot})$ (Fig. 2, A and B). A high degree of PEDOT chain alignment was confirmed by polarized ultravioletvisible (UV-vis) measurement (Fig. 2G). The dichroic ratios $(A_{||}/A_{\\perp})$ calculated using the absorption of the $785\\mathrm{-nm}$ peak and the free-carrier tail at $1100~\\mathrm{{nm}}$ both showed a monotonic increase from 1 under $0\\%$ strain to ${\\sim}3.2$ under $125\\%$ strain, which is indicative of chain alignment along the parallel direction to stretching (Fig. 2G). This agrees with the increase in conductivity along this direction (Fig. 2A). \n\nFollowed by the initial increase at lower strains, $\\upsigma_{\\parallel}$ then decreased consistently under ${>}100\\%$ strain until the substrate ruptured. We obtained the best performance for films with STEC enhancer 1, where the conductivity remained above $1000\\mathrm{S}/\\mathrm{cm}$ between 0 and $100\\%$ strain, with the highest value at $3390{\\mathrm{S}}/{\\mathrm{cm}}$ under $100\\%$ strain, above $100\\mathrm{S}/\\mathrm{cm}$ up to $600\\%$ strain, and a final conductivity of $56~\\mathrm{S/cm}$ even when stretched to a record $800\\%$ strain, beyond which point the substrate ruptured. Optical microscope images of the stretchable PEDOT films held under strain show that cracks do not form until $\\sim150\\%$ (section S5). Even under strains as high as $550\\%$ with a much higher crack density, the films have morphologies of an interconnected network, which could account for the reasonably high conductivity under high strain. Compared to most reported stretchable conductors (Fig. 2B), our material not only has a higher initial conductivity and a slower drop in conductivity under tensile strain but also sustains the highest maximum tensile strain. Note that, although a maximum $100\\%$ strain is necessary for wearable or epidermal electronics, a higher stretchability is required when these materials are used as interconnects for rigidisland device arrays shown later. In addition, the ability for a material to be elongated to several times its original length greatly broadens its applications to robotics and biomechanical systems under extreme conditions. \n\n![](images/b6cf824c020ca1b4f8a949057e754229b78e0e48a2610b0e74e341c9cb0d97cd.jpg) \nFig. 2. Electrical and optical properties of stretchable PEDOT under strain. (A) Conductivity under various strains for PEDOT with different STEC enhancers. Film thicknesses are around 600 to $800~\\mathsf{n m}$ (B) Conductivities under various strain presented in this work compared to representative stretchable conductors reported in literature. PU, polyurethane. (C and D) Cycling stability of PEDOT/STEC1 under $50\\%$ strain (C) and $100\\%$ strain (D). $G,$ conductance; $\\circ,$ conductivity; a.u., arbitrary units. (E and F) AFM images of a PEDOT/STEC1 film under different magnifications under $0\\%$ strain after it was cycled for 1000 times to $100\\%$ strain. The vertical profile across the line on the image is shown below the corresponding image. The deep folds have an amplitude of $\\mathord{\\sim}100\\mathsf{n m}$ and a periodicity of ${\\sim}1.5\\upmu\\mathrm{m}.$ , whereas those for the wrinkles are ${\\sim}20\\mathsf{n m}$ and ${\\sim}0.25\\upmu\\mathrm{m},$ respectively. (G) Dichroic ratio of the PEDOT/STEC1 films under different strains calculated at 785 and $1100\\mathsf{n m}$ for the 1st and the 1000th cycle. There is no change in dichroic ratio from 0 to $100\\%$ strain after 1000 cycles, potentially because of the folds formed in the film and a steady concentration of STEC enhancers being reached. \n\nThe stretchable PEDOT films show high cycling stability. The film conductance $G$ (reflects change in resistance) retained $92\\%$ of the original value under $50\\%$ strain after 1000 cycles and $71\\%$ when the cycling strain was $100\\%$ (Fig. 2, C and D). The conductivity $(\\upsigma_{||})$ of these films increased with strain as a result of the chain alignment phenomenon. After 1000 cycles, the films still exhibited a 2.1- and 2.8-fold increase in conductivity under 50 and $100\\%$ strains, respectively, as compared to the unstrained films (Fig. 2, C and D). Note that the conductivity exhibited an increase during approximately the first 100 cycles but then stabilized at a more constant value. At the end of 1000 cycles to $100\\%$ strain, no visible cracks formed on films when inspected under an optical microscope (section S4) and an atomic force microscope (AFM) (Fig. 2, E and F). The darker lines visible in optical microscope images were revealed to be deep folds by AFM analysis (Fig. 2, E and F), demonstrating the excellent durability of the PEDOT/STEC films under repeated strain. \n\n# Stretchable PEDOT film morphological characterizations \n\nWe found that the STEC enhancers (such as 1 to 3) play a number of roles in PEDOT:PSS in terms of charge transfer doping, crystallinity, and morphology. First, it has been documented that small ionic species can have a charge screening effect that weakens the Coulombic interactions between the polyelectrolytes PEDOT and PSS (25, 27–29). The charge screening effect was previously found to result in higher crystallinity of the PEDOT-rich domains (25, 28). We observed larger colloidal particle sizes in solution with the addition of STEC by dynamic light scattering analysis (fig. S3, B and C). In addition, more distinct nanofibrous structures were seen in dried films by AFM (Fig. 3, H to $\\mathbb{K},$ and fig. S4). In thin films, we observed that $\\mathrm{C_{\\mathrm{{\\scriptsized}}}=C_{\\mathrm{{\\scriptsize\\beta}}}}$ vibration peaks $(\\sim144\\bar{5}\\mathrm{cm}^{-1},$ ) in Raman spectroscopy red-shifted and were narrower in width in the PEDOT/STEC films compared to the pure PEDOT:PSS control (Fig. 3A). This indicates that a higher proportion of the benzoid moieties in PEDOT are converted to the quinoid structure from oxidative charge transfer doping, which results in a more planar backbone (25, 30, 31). This planarity may contribute to more efficient charge delocalization and a higher packing order (28). The charge delocalization effect is further confirmed by UV-vis–near-infrared (NIR) spectra (Fig. 3B) (32) because the ${\\sim}800\\mathrm{-}\\mathrm{nm}$ peak became less well defined and a more intense free-carrier tail extending into the NIR was observed when STEC1, STEC2, and STEC3 were incorporated into PEDOT:PSS. \n\n![](images/761d0ffa6802d1b510632f881e813eb5341e92f6a281de00e971f43e91bf90c2.jpg) \nFig. 3. Chemical and crystallographic characterization of stretchable PEDOT. (A) Raman spectra illustrating the $\\mathsf C_{\\mathrm{a}}=\\mathsf C_{\\upbeta}$ peak position shift for the different films. The dashed line indicates the peak position for the PEDOT control film without any STEC. (B) UV-vis-NIR spectra showing the doping effect of STEC on PEDOT, as evidenced by increased absorption intensity from bipolaron delocalization at ${>}1000\\mathsf{n m}$ . (C) Near out-of-plane intensity plot of PEDOT:PSS films with various amounts of STEC2 additives extracted from GIWAXS patterns of PEDOT:PSS films with no STEC (D) and 45.5 wt $\\%$ of STEC1 (E), STEC2 (F), and STEC8 (G) (see also section S3). For the standard PEDOT film without any STEC additives, three peaks were observed along $q_{z}\\colon q_{z}=0.57\\mathring{\\mathsf{A}}^{-1}$ $(d=11.2\\mathring{\\mathsf{A}})$ , $1.33\\mathring{\\mathsf{A}}^{-1}$ $(d=4.9\\mathring{\\mathsf{A}})$ , and $1.87\\mathring{\\mathsf{A}}^{-1}$ $\\left(d=3.4\\mathring{\\mathsf{A}}\\right)$ , which can be indexed as PEDOT (200), PSS amorphous scattering, and PEDOT (010), respectively (40, 45). $\\mathbf{\\Delta}\\mathbf{H}$ to $\\pmb{\\kappa}$ ) AFM phase images of regular PEDOT:PSS (H) compared to PEDOT with high stretchability by incorporating STEC1 (I), STEC2 (J), and STEC3 (K). \n\nGrazing-incidence wide-angle $\\mathbf{x}$ -ray scattering (GIWAXS) patterns indicate that the ordering in the semicrystalline PEDOT:PSS films was improved with the addition of STEC (Fig. 3, C to G, and fig. S5). Specifically, the (200) d-spacing increases with increased STEC contents in the films, which is accompanied by a slight decrease in d-spacing for the (010) peak (from 3.4 to $3.3{\\mathrm{\\AA}}$ ) (33–35). Meanwhile, with the addition of STEC, a new peak emerges at $q_{\\mathrm{z}}={\\sim}0.89\\ \\mathring{\\mathrm{A}}^{-1}$ $\\begin{array}{r}{\\dot{\\mathopen{}\\mathclose\\bgroup\\left(d=-6.8\\mathrm{\\AA}\\aftergroup\\egroup\\right.}\\end{array}$ ), which was previously reported and assigned to PEDOT, but no definitive indexing was reported (33, 34). In addition, we observed this peak in the ${\\mathrm{PEDOT:PF}}_{6}$ system without PSS (fig. S6), further confirming that it arises from PEDOT scattering. \n\nCombining the above evidences, we propose a schematic representation of the composition and morphology of the PEDOT/STEC films (Fig. 1D): The charge screening effect of the ionic STEC additives results in a morphological change to form more crystalline and more interconnected PEDOT nanofibrillar structures. Because the PEDOT phase becomes more crystalline with the addition of STEC, we suspect that it is likely that the STEC molecules mostly reside in the more disordered regions, which further softens the material. This gives rise to a nanofiber network embedded in a soft matrix, which is a desirable morphology for high stretchability. Such morphology is also advantageous for high conductivity because of the higher crystallinity of the PEDOT domains and the improved connectivity. \n\nFilms with the highest conductivity values were obtained with the above morphological improvement and an additional STEC washing of the films (Materials and Methods and figs. S15 to 17). X-ray photoelectron spectroscopy (XPS) sputtering experiments indicate that the surface of the as-spun PEDOT/STEC film has a higher $\\mathrm{PSS}+\\mathrm{STEC-}$ to–PEDOT ratio than the interior of the film (Fig. 4B and fig. S17). Rinsing with an STEC aqueous solution after annealing removes the excess PSS from the film surface, leading to a thinner film with a higher PEDOT content, thus further improving the conductivity (figs. S16 and S17). Treating the films with water led to a similar effect in terms of conductivity enhancement, but STEC solutions are used here to minimize the loss of STEC plasticizers that are necessary for stretchability. The conductivity for PEDOT/STEC systems increased rapidly as the STEC concentration increased until ${\\sim}45\\mathrm{wt}\\%$ (Fig. 4A and figs. S15 to 17). It then remained nearly constant upon further addition. The highest conductivity values achieved were 2588, 3102, and $2544~\\mathrm{S/cm}$ at 71 wt $\\%$ of STEC1, STEC2, and STEC3, respectively, versus $4\\:\\mathrm{S}/\\mathrm{cm}$ without these additives. \n\n# Temperature dependence of conductivity \n\nThe chemical composition and morphology of materials have direct impact on the temperature dependence of the electrical conductivity, which provides insights into transport properties. Aiming at applications where highly stretchable materials are used as interconnects between different electronic components, possible temperature drifts have to be minimized. The temperature dependence of PEDOT thin films between 340 and 75 K were measured in a cryostat using a four-probe dc current method (Fig. 4C). All samples exhibited reversible temperature dependence with low hysteresis, indicating high stability. An empirical relation has been used to extract the temperature resistance coefficients of first and second order (section S6). PEDOT with dimethyl sulfoxide as the additive exhibited a very high linear temperature resistance coefficient of about $\\begin{array}{r}{\\upalpha=0.35\\%/\\mathrm{K},}\\end{array}$ whereas PEDOT/STEC enhancers 1 and 2 showed much lower values of $3.8\\times{{10}^{-7}}$ and $7.6\\times10^{-3}\\%/\\mathrm{K},$ respectively. \n\nA widely used model to describe the temperature behavior of disordered polymeric systems assumes that the charge transport is dominated by interchain hopping probability (36–38). The temperature dependence of these materials follows a non-Arrhenius quadratic expression originating from a Gaussian disorder and has been reported to describe systems with low charge carrier densities well. On the other hand, at high charge carrier densities, a universal Arrhenius-like temperature dependence has been observed for disordered conjugated polymers (39). Our stretchable PEDOT/STEC materials exhibited a clear temperature-activated behavior following the Arrhenius law (Fig. 4D). The activation energy extracted for PEDOT/STEC1 and PEDOT/STEC2 was found to be only about 3 and $4.1\\mathrm{meV}$ , respectively. These values are much lower compared to typical PEDOT films, which have an activation energy of $15.2\\mathrm{meV}.$ These results agree with the stronger free-carrier tails observed in UV-vis-NIR spectra (Fig. 3B), which suggest that STEC enhancers also act as “secondary” dopants for PEDOT. The doping effect increases the charge carrier density and shifts the Fermi level $E_{\\mathrm{f}}$ above the equilibrium level $E_{\\mathrm{q}},$ which is represented by the maximum of the density of occupied states (39). The lowest activation energy of PEDOT/STEC1 remains in agreement with the highest room temperature conductivity and the lowest linear temperature resistance coefficient of $3.8\\times10^{-7}\\%/\\dot{\\mathrm{K}}.$ \n\n# Applications and patterning of stretchable PEDOT \n\nBecause the conductivity of the stretchable PEDOT remains well above $1000\\mathrm{S}/\\mathrm{cm}$ even under $100\\%$ strain, only a thin layer is needed to achieve low resistance, rendering it a good transparent stretchable conductor. Figure 4E depicts the relationship between film transmittance and sheet resistance. A sheet resistance of 59 ohms/sq was obtained for a film with $96\\%$ transmittance (with substrate absorbance subtracted). This is among the highest values reported for PEDOT transparent electrodes, whereas none of the previously reported highly conductive ones were stretchable (25, 34, 40). The resistance decreased as the film thickness is increased, and it reached ${\\sim}10$ ohms/sq with a $75\\%$ film transmittance at $550\\mathrm{nm}$ . The film with $96\\%$ transmittance has a figure of merit (FoM) of 142, which surpasses the previous highest value from spin-casted PEDOT films and transparent CNT electrodes (27, 34, 40, 41). \n\nLarger patterns (that is, $>500\\upmu\\mathrm{m}\\ '$ (Fig. 4F) can be readily obtained by screen printing or etching through a shadow mask and are stretchable when printed on an elastic substrate such as SEBS. Complex patterns with resolution down to $40\\upmu\\mathrm{m}$ can be obtained through inkjet printing (Fig. 4, G to I). \n\nTo demonstrate the application of stretchable PEDOT as interconnects, we used it to connect rigid LEDs (Fig. 5A). Negligible change in LED light intensity was observed even under high strain conditions, such as twisting while stretching or poking the interconnect with a sharp object (Fig. 5, B and C, and videos S1 and S2), due to the small change in resistance upon tensile strain. \n\nOne distinct advantage of an intrinsically stretchable conductor as interconnects for rigid-island matrices is that it can lead to a much higher surface filling ratio $(f)$ (42) for active devices (islands) compared to the wavy interconnects, where a large amount of space between the rigid islands needs to be reserved for the wavy metal ribbons (4, 6). To demonstrate the potential of PEDOT/STEC as interconnects in high-density circuits, we connected multiple rigid islands with field-effect transistor (FET) devices by lines of PEDOT (Fig. 5, F to H). \n\n![](images/b5ed3955be562975933eaa773ff30083341b0f932ccfd2479ad15c1abab5dbd1.jpg) \nFig. 4. Electrical properties and patterning of the stretchable PEDOT/STEC (STEC content is 45.5 wt % for all). (A) Conductivity of the PEDOT films via spin coating followed by various STEC aqueous solution treatments. (B) $\\mathsf{X P S C}_{60}$ ion gun sputtering depth profile of a stretchable PEDOT/STEC film. (C) Temperature dependence of the conductivity and (D) Arrhenius fitting for conventional PEDOT compared to those with STEC additives. (E) Sheet resistance of the PEDOT/STEC1 films in relation to their transparency. Transmittance values are extracted at $550\\mathsf{n m}.$ . (F) Patterned PEDOT/STEC film on SEBS (top) and the film being stretched (bottom). The line width is 1 mm. (G and H) Photograph (G) and optical microscope image (H) showing micrometer-scale patterns produced by inkjet-printing the PEDOT/STEC. (I) Illustration of the control of feature size, with a line width as small as $40\\upmu\\mathrm{m}$ printed on a SEBS substrate. \n\nA rigid island-to-interconnect width of 1:1 $(f=50\\%)$ is typically required for wavy interconnects to reach stable performances under $100\\%$ strain (42). The actual length of the stretched interconnect is much longer than the spacing between rigid islands (for example, up to ${>}12$ times if straightened) (6). In our case, for unidirectional stretching, a rigid island-to-interconnect ratio of as high as 5:1 $(f=78\\%)$ can still lead to identical transistor current and threshold voltage characteristics from 0 to $150\\%$ strain for the linear array (fig. S29), which inflicts ${>}530\\%$ strain on the PEDOT region based on finite element simulations (Fig. 5, D and E). \n\nTo demonstrate the feasibility of multidimensional stretching, we fabricated $3\\times3$ arrays with $f$ of $78\\%$ and uniformly stretched them in all directions. Figure S30 and table S2 show the transfer curves for the nine transistors under 0 and $125\\%$ strains for overall device structure. The mobility variation for all the transistors is within $\\pm10\\%$ (Fig. 5I). This strain is well beyond the $100\\%$ strain requirement for wearable and epidermal electronics, illustrating the excellent stretchability and the stable electrical performances of the PEDOT interconnects under strain. This array is especially suitable for stable performance on curved objects (Fig. 5H, fig. S31, and video S3). \n\n![](images/3d6533bca149f08a9f191bb48e4e1b4e688f1abc2bbd39341c603b1308067d41.jpg) \nFig. 5. Stretchable PEDOT/STEC as interconnects for LED and FET devices. (A) Schematic representation of an LED device bridged by PEDOT wires to the power source. (B and C) Photographs illustrating the minimal change in LED brightness as the device is stretched under twisting and poked with a sharp object, respectively. (D) Finite element simulation showing the cross-sectional strain distribution of the rigid-island arrays under $0\\%$ (top) and $100\\%$ (bottom) strains. (E) Plot summarizing the relationship between array density and strain on PEDOT interconnects when stretching the array to $100\\%$ from the simulation results. (F) Schematic diagram of the rigid-island FET array with stretchable PEDOT interconnects. (G and H) Photographs showing the FET array being stretched in all directions on a flat surface and spherical object, respectively. (I) Normalized mobility of individual transistors when the array is stretched to different strains. \n\nproper selection of anions. The resulting materials show record-high stretchability and conductivity, the coexistence of which is rare for conducting polymers. High-density FET arrays connected using the stretchable PEDOT films show stable performance under ${>}100\\%$ strain. This material synergistically combines high electrical conductivity, exceptional mechanical ductility, and patternability by printing, thus opening many new avenues toward next-generation wearable and epidermal electronics and bioelectronics. \n\n# DISCUSSION \n\nWe have demonstrated a highly stretchable and conductive PEDOT polymer by incorporating ionic additive–assisted STEC enhancers that result in a morphology that is beneficial for both high stretchability and conductivity. A further boost in conductivity is achieved through a \n\n# MATERIALS AND METHODS Material preparation \n\nPEDOT:PSS (PH1000) was obtained from Clevios, and the STEC ionic additives were obtained from Sigma-Aldrich and Santa Cruz Biotechnology, \n\nInc. SEBS with $20\\%$ styrene content (Tuftec H1052) was supplied by AK Elastomer. HiPco single-walled CNT (SWCNT) was sorted via a previously reported method (43) using poly(3-dodecylthiophene2,5-diyl) (P3DDT) to obtain semiconducting SWCNT for transistor fabrication. \n\nIn a typical experiment, STEC of 10 to 71 wt $\\%$ was added to the PEDOT:PSS aqueous dispersion (1.1 to $1.3\\mathrm{wt}\\%$ ) and stirred vigorously for $15\\mathrm{min}$ . Thick films were acquired by drying the mixture overnight in a Teflon mold and then annealing at $130^{\\circ}\\mathrm{C}$ for $15~\\mathrm{min}$ . Thin films were processed onto glass, $\\mathrm{SiO}_{2}/\\mathrm{Si},$ or SEBS substrates by spin coating at $1000~\\mathrm{rpm}$ for $1\\mathrm{min}$ under ambient conditions, followed by a 10-min annealing at $130^{\\circ}\\mathrm{C}.$ A postdeposition washing step was then carried out by dropping an aqueous solution containing $10~\\mathrm{mg/ml}$ of the corresponding STEC on the PEDOT films, waiting for 1 min, and removing the liquid by spinning the samples at $3000\\mathrm{rpm}$ for 1 min. Glass or $\\mathrm{SiO}_{2}/\\mathrm{Si}$ was treated with oxygen plasma at $150\\mathrm{W}$ for $30\\mathrm{s},$ and SEBS was treated with UV ozone for $30\\mathrm{min}$ or with oxygen plasma for $10\\mathrm{{s}}(150\\mathrm{{W})}$ before PEDOT deposition via spin coating $1000~\\mathrm{rpm}$ for $1\\mathrm{min}$ , followed by annealing at $70^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ ). The SEBS substrates were prepared from a toluene solution $(200\\mathrm{mg/ml})$ casted onto a glass slide. \n\n# Electrical property \n\nConductivity measurements were carried out using a four-point geometry. Electrodes were deposited by applying silver paste or EGaIn or by evaporating gold. A minimum of three to five measurements were obtained for an average value. Low temperature–dependent measurements were performed in a LakeShore cryostat under ${{10}^{-5}}$ mbar vacuum. A bottom gold contact geometry was used to ensure stable electrical contacts under thermal cycling. A slow cooling and heating rate of about $1.4~\\mathrm{K/min}$ assured the stabilization at each temperature. \n\n# Mixed ion-electron conductivity \n\nMixed ion-electron conductivity was studied using impedance measurements. The PEDOT films with STEC enhancers were cut into round tablets (diameter, $3.5~\\mathrm{mm}$ ; thickness, ca. $100\\upmu\\mathrm{m}\\cdot$ ). Two glassy carbon electrodes (diameter, $3\\mathrm{mm}$ ) were used to sandwich the tablet to form an electrical contact for the impedance measurement. The impedance data as functions of frequency were acquired by a Bio-Logic VSP-300 workstation with a sine wave signal amplitude of $10\\mathrm{mV}$ . Resistances from the ionic versus electronic components were calculated using previously reported procedures (44). \n\n# Mechanical property \n\nMechanical properties of freestanding films around $200\\upmu\\mathrm{m}$ in thickness were studied using Instron 5565 with a 100-N loading cell using dumbbell film geometry. The storage, loss moduli, and stress relaxation tests were carried out on a dynamic mechanical analysis (TA Instruments Q800). \n\n# Morphological and chemical characterization \n\nMicroscopy was performed on a FEI XL30 Sirion scanning electron microscope. AFM images were recorded in tapping mode using a Veeco Multimode AFM. UV-vis-NIR spectra were collected on an Agilent Cary 6000i model. Dynamic light scattering experiments were carried out using 100-fold diluted PEDOT/STEC dispersions on a Brookhaven Instrument 90. XPS was performed on a PHI VersaProbe Scanning XPS Microprobe. Sputtering was carried out at $10\\mathrm{kV}$ and $20\\mathrm{mA}$ with a $\\mathrm{C}_{60}$ ion sputtering gun to preserve the chemical information in the polymer films. Film thickness values were measured using a contact probe Dektak 150 profilometer and averaged from a minimum of three areas. \n\n# Grazing-incidence $\\pmb{\\ x}$ -ray scattering \n\nGIWAXS measurements were carried out at the Stanford Synchrotron Radiation Lightsource at beamline 11-3, with a photon energy of $12.735\\mathrm{KeV}$ and a sample-to-detector distance of $320~\\mathrm{mm}$ . The incident angle was fixed at $0.14^{\\circ}$ to probe the entire film with reduced substrate scattering. \n\n# Patterning \n\nPatterned films [feature size, $>500~{\\upmu\\mathrm{m}}$ (such as for the LED or FET arrays)] were obtained by repeating the spin coating and washing steps three times for PEDOT on SEBS, followed by oxygen plasma etching $\\mathrm{~\\small~\\displaystyle~}^{\\cdot}150\\mathrm{~W~}$ for 5 to $10~\\mathrm{min}$ ) through a shadow mask until the exposed PEDOT films were completely removed. \n\nMicrometer-sized patterns of the stretchable PEDOT/STEC were achieved through inkjet printing using a fourfold diluted dispersion. The dispersion was passed through a glass fiber syringe filter with a pore size of $0.7\\upmu\\mathrm{m}$ and degassed for a few minutes to remove trapped air bubbles before it was loaded into a cartridge. A Dimatix Fujifilm DMP 2800 inkjet printer with 10-pl drop volume cartridges was used to print this ink on different substrates, such as $\\mathrm{SiO}_{2}/\\mathrm{Si},$ , SEBS, or photo paper. The optimal printing parameters for plasma-treated SEBS substrate (150 W for 10 s) were as follows: drop-to-drop spacing of $30\\upmu\\mathrm{m};$ ; a jet speed and a frequency of $5\\mathrm{m}/s$ and $1.5\\mathrm{kHz}$ , respectively; a cartridge temperature of $28^{\\circ}\\mathrm{C},$ and a substrate temperature of $30^{\\circ}\\mathrm{C}.$ . \n\n# Stretchable rigid-island transistor arrays \n\nTransistors on rigid Si islands in our arrays were fabricated by first patterning the $\\mathrm{Cr/Au}$ $(5/40~\\mathrm{nm})$ ) source and drain electrodes through a shadow mask on a $\\mathrm{SiO}_{2}/\\mathrm{n}^{++}{-}\\mathrm{Si}$ wafer (Si and $\\mathrm{SiO}_{2}$ serve as the back gate and dielectric layer, respectively). Each FET device has a channel width of $1000\\upmu\\mathrm{m}$ and a channel length of $200\\upmu\\mathrm{m}$ . The sorted SWCNT dispersion $\\mathrm{(0.7ml)}$ (43) was spin-coated on the patterned substrates $(2\\operatorname{in}\\times2$ in) at $2000\\mathrm{rpm}$ for $90s.$ . The sample was then soaked in toluene at $90^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ to remove the P3DDT, dried with nitrogen flow, and annealed at $120^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ under ambient conditions. Polydimethylsiloxane shadow masks were aligned on the devices to protect the active device areas. The SWCNTs between devices were then etched away by oxygen plasma $\\mathrm{~\\i{50W}}$ for $10\\mathrm{min}$ ). Single rigid-island devices were obtained by dividing the whole piece into $5\\mathrm{-}\\mathsf{c m}\\times5$ -cm chips along the CNTfree spaces. The $3\\times3$ stretchable organic transistor active matrices were fabricated by immobilizing the individual islands using silver epoxy onto a SEBS substrate and linked together using patterned PEDOT/STEC1, creating a common back gate (Fig. 5F). Under ambient conditions, the transistor performance was characterized using a Keithley 4200 SC semiconductor analyzer under different strains for each rigid island while applying common gate voltages through the PEDOT interconnects. \n\n# Finite element simulation \n\nFinite element analysis for simulating the strain distributions in the FET arrays was carried out using the software Abaqus. \n\n# SUPPLEMETARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ \ncontent/full/3/3/e1602076/DC1 \nsection S1. Selection of STEC enhancers \nsection S2. Mechanical characterization of bulk freestanding films \nsection S3. Effect of STEC on PEDOT:PSS \nsection S4. Morphology of PEDOT/STEC film interior \nsection S5. Microscopy study of the effect of tensile strain on PEDOT/STEC films \nsection S6. Electrical properties of PEDOT/STEC films section S7. Composition of PEDOT/STEC films \nsection S8. Low-temperature measurements \nsection S9. FoM for transparent conductors \nsection S10. Testing geometry for PEDOT films under tensile strain \nsection S11. Polarized UV-vis-NIR spectra for PEDOT films under tensile strain \nsection S12. Cycling stability and morphological change of PEDOT with STEC additives section S13. Mixed ion-electron conductivity \nsection S14. PEDOT/STEC as interconnects for FET arrays \ntable S1. Summary of STEC structures and their effects on the electrical and mechanical properties of freestanding PEDOT:PSS films (thickness range, 150 to $200~{\\upmu\\mathrm{m}})$ with 45.5 wt $\\%$ of STEC. table S2. Summary of mobility and threshold voltage shift for the $3\\times3$ transistor arrays under 0 and $125\\%$ strain. \nfig. S1. Plot summarizing the conductivity, maximum tensile strain, and Young’s modulus for freestanding PEDOT:PSS films $(\\sim150\\ \\upmu\\mathrm{m}$ in thickness) with all additives investigated in this paper. fig. S2. Mechanical characterization of bulk freestanding films. \nfig. S3. Mechanism behind STEC-induced morphology change for PEDOT:PSS films. \nfig. S4. AFM phase images of PEDOT with various additives. \nfig. S5. GIWAXS analyses of PEDOT films. \nfig. S6. Diffraction data for PSS and insoluble PEDOT control samples. \nfig. S7. Plasticizing effect of STEC on PEDOT and $N a P S S$ individually. \nfig. S8. SEM characterization of the cross section of a stretchable PEDOT film. \nfig. S9. Optical microscope images of a PEDOT/STEC1 film supported on a SEBS substrate under various strains. \nfig. S10. Optical microscope images of a PEDOT/STEC1 film supported on a SEBS substrate after being stretched to various strains and returned to its original length. \nfig. S11. Surface profile analyses of PEDOT films after stretching. \nfig. S12. Optical microscope images of a PEDOT/STEC1 film upon unloading from $100\\%$ strain. fig. S13. Optical microscope images of a PEDOT/STEC2 film held under various tensile strains. fig. S14. Optical microscope images of a PEDOT/STEC2 film upon stretching to various tensile strains. fig. S15. Conductivity values of PEDOT/STEC films processed under different conditions. fig. S16. Conductivity of PEDOT/STEC films with various STEC weight $\\%$ before and after further STEC solution treatment. \nfig. S17. Effect of further doping using STEC solution on spin-coated films. \nfig. S18. Chemical composition of PEDOT/STEC films. \nfig. S19. Temperature-dependent conductivity and first- and second-order temperature coefficients for PEDOT films. \nfig. S20. Arrhenius plots for temperature dependent conductivity. \nfig. S21. Schematic diagrams of tensile testing and conductivity measurement geometries. fig. S22. Tension-induced chain-alignment behavior of PEDOT/STEC films. \nfig. S23. XPS analysis of film surfaces under $0\\%$ versus $100\\%$ strain, after returning from $100\\%$ to $0\\%$ strain, and after 1000 stretching cycles to $100\\%$ strain. \nfig. S24. Cycling stability of PEDOT/STEC1 films. \nfig. S25. Cycling stability of PEDOT/STEC2 films. \nfig. S26. Mixed ion-electron conductivity measurements. \nfig. S27. Schematic showing the cross-sectional view of a linear rigid-island array connected with stretchable PEDOT. \nfig. S28. Schematic diagrams illustrating strain calculation for rigid-island devices. \nfig. S29. Schematic and transfer characteristics for a $3\\times1$ FET array. \nfig. S30. Schematic and transfer characteristics for a $3\\times3$ FET array. \nfig. S31. A $3\\times3$ FET array being stretched on a spherical object. \nvideo S1. A stretchable LED device poked with a sharp object. \nvideo S2. Twisting and stretching of a stretchable LED device. \nvideo S3. A $3\\times3$ FET array stretched on a spherical object. \n\n# REFERENCES AND NOTES \n\n1. S. Wagner, S. Bauer, Materials for stretchable electronics. MRS Bull. 37, 207–213 (2012). \n2. M. L. Hammock, A. Chortos, B. C.-K. Tee, J. B.-H. Tok, Z. Bao, The evolution of electronic skin (E-skin): A brief history, design considerations, and recent progress. Adv. Mater. 25, \n5997–6038 (2013). \n3. I. Jung, J. Xiao, V. Malyarchuk, C. Lu, M. Li, Z. Liu, J. Yoon, Y. Huang, J. A. Rogers, Dynamically tunable hemispherical electronic eye camera system with adjustable zoom capability. Proc. Natl. Acad. Sci. U.S.A. 108, 1788–1793 (2011). \n4. D.-H. Kim, J.-H. Ahn, W. Mook Choi, H.-S. Kim, T.-H. Kim, J. Song, Y. Y. Huang, Z. Liu, C. Lu, J. A. Rogers, Stretchable and foldable silicon integrated circuits. Science 320, 507–511 (2008). \n5. D. J. Lipomi, M. Vosgueritchian, B. C. Tee, S. L. Hellstrom, J. A. Lee, C. H. Fox, Z. Bao, Skinlike pressure and strain sensors based on transparent elastic films of carbon nanotubes. Nat. Nanotechnol. 6, 788–792 (2011). \n6. X. Hu, P. Krull, B. de Graff, K. Dowling, J. A. Rogers, W. J. Arora, Stretchable inorganicsemiconductor electronic systems. Adv. Mater. 23, 2933–2936 (2011). \n7. T. Sekitani, Y. Noguchi, K. Hata, T. Fukushima, T. Aida, T. Someya, A rubberlike stretchable active matrix using elastic conductors. Science 321, 1468–1472 (2008). \n8. S. Yao, Y. Zhu, Nanomaterial-enabled stretchable conductors: Strategies, materials and devices. Adv. Mater. 27, 1480–1511 (2015). \n9. D.-H. Kim, J. A. Rogers, Stretchable electronics: Materials strategies and devices. Adv. Mater. 20, 4887–4892 (2008). \n10. C. Yan, P. S. Lee, Stretchable energy storage and conversion devices. Small 10, 3443–3460 (2014). \n11. T. C. Shyu, P. F. Damasceno, P. M. Dodd, A. Lamoureux, L. Xu, M. Shlian, M. Shtein, S. C. Glotzer, N. A. Kotov, A kirigami approach to engineering elasticity in nanocomposites through patterned defects. Nat. Mater. 14, 785–789 (2015). \n12. H. Vandeparre, Q. Liu, I. R. Minev, Z. Suo, S. P. Lacour, Localization of folds and cracks in thin metal films coated on flexible elastomer foams. Adv. Mater. 25, 3117–3121 (2013). \n13. A. Chortos, J. Lim, J. W. F. To, M. Vosgueritchian, T. J. Dusseault, T.-H. Kim, S. Hwang, Z. Bao, Highly stretchable transistors using a microcracked organic semiconductor. Adv. Mater. 26, 4253–4259 (2014). \n14. T. S. Hansen, K. West, O. Hassager, N. B. Larsen, Highly stretchable and conductive polymer material made from poly(3,4-ethylenedioxythiophene) and polyurethane elastomers. Adv. Funct. Mater. 17, 3069–3073 (2007). \n15. K.-Y. Chun, Y. Oh, J. Rho, J.-H. Ahn, Y.-J. Kim, H. Ryeol Choi, S. Baik, Highly conductive, printable and stretchable composite films of carbon nanotubes and silver. Nat. Nanotechnol. 5, 853–857 (2010). \n16. N. Matsuhisa, M. Kaltenbrunner, T. Yokota, H. Jinno, K. Kuribara, T. Sekitani, T. Someya, Printable elastic conductors with a high conductivity for electronic textile applications. Nat. Commun. 6, 7461 (2015). \n17. K. Tybrandt, J. Vörös, Fast and efficient fabrication of intrinsically stretchable multilayer circuit boards by wax pattern assisted filtration. Small 12, 180–184 (2016). \n18. Y. Kim, J. Zhu, B. Yeom, M. Di Prima, X. Su, J.-G. Kim, S. J. Yoo, C. Uher, N. A. Kotov, Stretchable nanoparticle conductors with self-organized conductive pathways. Nature 500, 59–63 (2013). \n19. S. Savagatrup, E. Chan, S. M. Renteria-Garcia, A. D. Printz, A. V. Zaretski, T. F. O’Connor, D. Rodriquez, E. Valle, D. J. Lipomi, Plasticization of PEDOT:PSS by common additives for mechanically robust organic solar cells and wearable sensors. Adv. Funct. Mater. 25, 427–436 (2015). \n20. D. J. Lipomi, J. A. Lee, M. Vosgueritchian, B. C.-K. Tee, J. A. Bolander, Z. Bao, Electronic properties of transparent conductive films of PEDOT:PSS on stretchable substrates. Chem. Mater. 24, 373–382 (2012). \n21. J. Y. Oh, S. Kim, H.-K. Baik, U. Jeong, Conducting polymer dough for deformable electronics. Adv. Mater. 28, 4455–4461 (2016). \n22. S. Savagatrup, A. D. Printz, T. F. O’Connor, A. V. Zaretski, D. J. Lipomi, Molecularly stretchable electronics. Chem. Mater. 26, 3028–3041 (2014). \n23. R. J. Young, P. A. Lovell, Introduction to Polymers (CRC Press, ed. 3, 2011). \n24. D. Liu, R. Osuna Orozco, T. Wang, Deviations of the glass transition temperature in amorphous conjugated polymer thin films. Phys. Rev. E 88, 022601 (2013). \n25. J. Ouyang, “Secondary doping” methods to significantly enhance the conductivity of PEDOT:PSS for its application as transparent electrode of optoelectronic devices. Displays 34, 423–436 (2013). \n26. A. Elschner, S. Kirchmeyer, W. Lovenich, U. Merker, K. Reuter, PEDOT: Principles and Applications of an Intrinsically Conductive Polymer (CRC Press, ed. 1, 2010). \n27. Y. Hyun Kim, C. Sachse, M. L. Machala, C. May, L. Müller-Meskamp, K. Leo, Highly conductive PEDOT:PSS electrode with optimized solvent and thermal post-treatment for ITO-free organic solar cells. Adv. Funct. Mater. 21, 1076–1081 (2011). \n28. J. Ouyang, C.-W. Chu, F.-C. Chen, Q. Xu, Y. Yang, High-conductivity poly(3,4- ethylenedioxythiophene):poly(styrene sulfonate) film and its application in polymer optoelectronic devices. Adv. Funct. Mater. 15, 203–208 (2005). \n29. Y. Xia, J. Ouyang, Salt-induced charge screening and significant conductivity enhancement of conducting poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate). Macromolecules 42, 4141–4147 (2009). \n30. S. Garreau, J. L. Duvail, G. Louarn, Spectroelectrochemical studies of poly(3,4- ethylenedioxythiophene) in aqueous medium. Synth. Met. 125, 325–329 (2001). \n31. S. Garreau, G. Louarn, J. P. Buisson, G. Froyer, S. Lefrant, In situ spectroelectrochemical Raman studies of poly(3,4-ethylenedioxythiophene) (PEDT). Macromolecules 32, 6807–6812 (1999). \n32. M. Łapkowski, A. Proń, Electrochemical oxidation of poly(3,4-ethylenedioxythiophene)— “In situ” conductivity and spectroscopic investigations. Synth. Met. 110, 79–83 (2000). \n33. N. Kim, B. Hoon Lee, D. Choi, G. Kim, H. Kim, J.-R. Kim, J. Lee, Y. H. Kahng, K. Lee, Role of interchain coupling in the metallic state of conducting polymers. Phys. Rev. Lett. 109, 106405 (2012). \n34. N. Kim, S. Kee, S. Ho Lee, B. H. Lee, Y. H. Kahng, Y.-R. Jo, B.-J. Kim, K. Lee, Highly conductive PEDOT:PSS nanofibrils induced by solution-processed crystallization. Adv. Mater. 26, 2268–2272 (2014). \n35. C. M. Palumbiny, F. Liu, T. P. Russell, A. Hexemer, C. Wang, P. Müller-Buschbaum, The crystallization of PEDOT:PSS polymeric electrodes probed in situ during printing. Adv. Mater. 27, 3391–3397 (2015). \n36. H. Bässler, Charge transport in disordered organic photoconductors a Monte Carlo simulation study. Phys. Status Solidi B 175, 15–56 (1993). \n37. S. D. Baranovskii, H. Cordes, F. Hensel, G. Leising, Charge-carrier transport in disordered organic solids. Phys. Rev. B 62, 7934–7938 (2000). \n38. R. Coehoorn, W. F. Pasveer, P. A. Bobbert, M. A. J. Michels, Charge-carrier concentration dependence of the hopping mobility in organic materials with Gaussian disorder. Phys. Rev. B 72, 155206 (2005). \n39. N. I. Craciun, J. Wildeman, P. W. M. Blom, Universal Arrhenius temperature activated charge transport in diodes from disordered organic semiconductors. Phys. Rev. Lett. 100, \n056601 (2008). \n40. B. J. Worfolk, S. C. Andrews, S. Park, J. Reinspach, N. Liu, M. F. Toney, S. C. B. Mannsfeld, Z. Bao, Ultrahigh electrical conductivity in solution-sheared polymeric transparent films. Proc. Natl. Acad. Sci. U.S.A. 112, 14138–14143 (2015). \n41. B. Dan, G. C. Irvin, M. Pasquali, Continuous and scalable fabrication of transparent conducting carbon nanotube films. ACS Nano 3, 835–843 (2009). \n42. H. R. Fu, S. Xu, R. X. Xu, J. Q. Jiang, Y. H. Zhang, J. A. Rogers, Y. G. Huang, Lateral buckling and mechanical stretchability of fractal interconnects partially bonded onto an elastomeric substrate. Appl. Phys. Lett. 106, 091902 (2015). \n43. H. Wang, B. Cobb, A. van Breemen, G. Gelinck, Z. Bao, Highly stable carbon nanotube top-gate transistors with tunable threshold voltage. Adv. Mater. 26, 4588–4593 (2014). \n44. C. Wang, J. Hong, Ionic/electronic conducting characteristics of LiFe $\\mathrm{{}^{\\circ}}\\mathrm{{O}}_{4}$ cathode materials: The determining factors for high rate performance. Electrochem. Solid State Lett. 10, A65–A69 (2007). \n45. K. E. Aasmundtveit, E. J. Samuelsen, O. Inganäs, L. A. A. Pettersson, T. Johansson, S. Ferrer, Structural aspects of electrochemical doping and dedoping of poly(3,4-ethylenedioxythiophene). Synth. Met. 113, 93–97 (2000). \n\nAcknowledgments: We thank H.-H. Chou for helpful discussions and M. Nalamachu for assistance in preparation of LED devices. Funding: This work was supported by Samsung Electronics and Air Force Office of Scientific Research (grant no. FA9550-15-1-0106). R.P. acknowledges support from the Marie Curie Cofund, Beatriu de Pinós fellowship (Agència de Gestió d’Ajuts Universitaris i de Recerca, 2014 BP-A 00094). F.L. and F.M-L. thank the Swiss National Science Foundation for an Early Mobility Postdoc grant. N.I.R. thanks the Stanford Graduate Fellowship and the NSF Graduate Research Fellowship Program. C.L. gratefully acknowledges additional support of the NSF through grant CMMI-1553638. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under contract no. DE-AC02-76SF00515. Author contributions: Y.W. and Z.B. conceived the concept. Y.W. carried out material preparation, characterization, and measurements. C.Z. fabricated FET arrays. R.P. performed low-temperature measurements. H.Y. performed GIWAXS data collection and analysis. L.J. simulated the strain distribution inrigid-island arrays. S.C. carried out XPS measurements. F.M.-L. inkjet-printed micrometer-sized patterns. F.L. and Y.W. performed AFM analyses. J.L. carried out mixed ion-electron conductivity measurements. N.I.R. helped with material preparation. Z.C. aided with the experimental design. J.W.C., C.L., M.F.T., B.M., and Z.B. supervised the project. All authors participated in data analysis and manuscript preparation. Competing interests: Y.W. and Z.B. applied for a patent related to the work (US 62/279,561) through Stanford University. All other authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 30 August 2016 \nAccepted 16 February 2017 \nPublished 10 March 2017 \n10.1126/sciadv.1602076 \n\nCitation: Y. Wang, C. Zhu, R. Pfattner, H. Yan, L. Jin, S. Chen, F. Molina-Lopez, F. Lissel, J. Liu, N. I. Rabiah, Z. Chen, J. W. Chung, C. Linder, M. F. Toney, B. Murmann, Z. Bao, A highly stretchable, transparent, and conductive polymer. Sci. Adv. 3, e1602076 (2017). \n\nA highly stretchable, transparent, and conductive polymer Yue Wang, Chenxin Zhu, Raphael Pfattner, Hongping Yan, Lihua Jin, Shucheng Chen, Francisco Molina-Lopez, Franziska Lissel, Jia Liu, Noelle I. Rabiah, Zheng Chen, Jong Won Chung, Christian Linder, Michael F. Toney, Boris Murmann and Zhenan Bao (March 10, 2017) \nSci Adv 2017, 3:. \ndoi: 10.1126/sciadv.1602076 \n\nThis article is publisher under a Creative Commons license. The specific license under which this article is published is noted on the first page. \n\nFor articles published under CC BY licenses, you may freely distribute, adapt, or reuse the article, including for commercial purposes, provided you give proper attribution. \n\nFor articles published under CC BY-NC licenses, you may distribute, adapt, or reuse the article for non-commerical purposes. Commercial use requires prior permission from the American Association for the Advancement of Science (AAAS). You may request permission by clicking here. \n\nThe following resources related to this article are available online at http://advances.sciencemag.org. (This information is current as of March 10, 2017): \n\nUpdated information and services, including high-resolution figures, can be found in the \nonline version of this article at: \nhttp://advances.sciencemag.org/content/3/3/e1602076.full \n\nSupporting Online Material can be found at: http://advances.sciencemag.org/content/suppl/2017/03/06/3.3.e1602076.DC1 \n\nThis article cites 43 articles, 4 of which you can access for free at: http://advances.sciencemag.org/content/3/3/e1602076#BIBL " + }, + { + "id": "10.1016_j.jpowsour.2016.12.011", + "DOI": "10.1016/j.jpowsour.2016.12.011", + "DOI Link": "http://dx.doi.org/10.1016/j.jpowsour.2016.12.011", + "Relative Dir Path": "mds/10.1016_j.jpowsour.2016.12.011", + "Article Title": "Degradation diagnostics for lithium ion cells", + "Authors": "Birkl, CR; Roberts, MR; McTurk, E; Bruce, PG; Howey, DA", + "Source Title": "JOURNAL OF POWER SOURCES", + "Abstract": "Degradation in lithium ion (Li-ion) battery cells is the result of a complex interplay of a host of different physical and chemical mechanisms. The measurable, physical effects of these degradation mechanisms on the cell can be summarised in terms of three degradation modes, namely loss of lithium inventory, loss of active positive electrode material and loss of active negative electrode material. The different degradation modes are assumed to have unique and measurable effects on the open circuit voltage (OCV) of Li-ion cells and electrodes. The presumptive nature and extent of these effects has so far been based on logical arguments rather than experimental proof. This work presents, for the first time, experimental evidence supporting the widely reported degradation modes by means of tests conducted on coin cells, engineered to include different, known amounts of lithium inventory and active electrode material. Moreover, the general theory behind the effects of degradation modes on the OCV of cells and electrodes is refined and a diagnostic algorithm is devised, which allows the identification and quantification of the nature and extent of each degradation mode in Li-ion cells at any point in their service lives, by fitting the cells' OCV. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).", + "Times Cited, WoS Core": 1116, + "Times Cited, All Databases": 1220, + "Publication Year": 2017, + "Research Areas": "Chemistry; Electrochemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000393003400044", + "Markdown": "# Degradation diagnostics for lithium ion cells \n\nChristoph R. Birkl a, Matthew R. Roberts b, Euan McTurk b, c, Peter G. Bruce b, David A. Howey a, \\* \n\na Department of Engineering Science, University of Oxford, OX1 3PJ, Oxford, UK b Department of Materials, University of Oxford, OX1 3PH, Oxford, UK c Warwick Manufacturing Group, University of Warwick, Warwick, CV4 7AL, UK \n\n# h i g h l i g h t s \n\nA diagnostic algorithm to identify and quantify degradation modes in Li-ion cells. \nExperimental proof for effects of degradation modes on the open circuit voltage. \nState of health estimations for commercial cells by fitting open circuit voltages. \n\n# g r a p h i c a l a b s t r a c t \n\n![](images/e4df4857dac3336d6705ef92ff1881857a5660ee6d8bbddac6b52c6cb23da19d.jpg) \n\n# a r t i c l e i n f o \n\nArticle history: Received 12 July 2016 Received in revised form 15 November 2016 Accepted 4 December 2016 \n\nKeywords: \nLithium ion \nDegradation \nState of health \nDiagnostic \nOpen circuit voltage \nBattery management system \n\n# a b s t r a c t \n\nDegradation in lithium ion (Li-ion) battery cells is the result of a complex interplay of a host of different physical and chemical mechanisms. The measurable, physical effects of these degradation mechanisms on the cell can be summarised in terms of three degradation modes, namely loss of lithium inventory, loss of active positive electrode material and loss of active negative electrode material. The different degradation modes are assumed to have unique and measurable effects on the open circuit voltage (OCV) of Li-ion cells and electrodes. The presumptive nature and extent of these effects has so far been based on logical arguments rather than experimental proof. This work presents, for the first time, experimental evidence supporting the widely reported degradation modes by means of tests conducted on coin cells, engineered to include different, known amounts of lithium inventory and active electrode material. Moreover, the general theory behind the effects of degradation modes on the OCV of cells and electrodes is refined and a diagnostic algorithm is devised, which allows the identification and quantification of the nature and extent of each degradation mode in Li-ion cells at any point in their service lives, by fitting the cells' OCV. \n\n$\\circledcirc$ 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). \n\n# 1. Introduction \n\nLithium ion (Li-ion) cells degrade as a result of their usage and exposure to environmental conditions [1e4]. This degradation affects the cells' ability to store energy, meet power demands and, ultimately, leads to their end of life. Any system employing Li-ion cells as its power source must be informed of the amount of energy that can be stored and the power that can be provided by the battery at any point in time. Since the rates of capacity and power fade cannot be easily inferred from operational data in a practical system, methods and models are required which utilise available parameters and measurements to generate estimates and predictions of current and future energy storage capacity and power capability. \n\nDegradation in Li-ion cells is caused by a large number of physical and chemical mechanisms, which affect the different components of the cells: the electrodes, the electrolyte, the separator and the current collectors [5e10]. Fig. 1 illustrates some of the most commonly reported degradation mechanisms in Li-ion cells. The different causes, rates and inter-dependencies of these degradation mechanisms make them extremely challenging to model, which is why most physics-based models focus only on the most dominant mechanisms, such as the formation and growth of the solid electrolyte interphase (SEI) [11,12] or electronic contact loss through particle cracking [13,14]. \n\nPhysics-based models generally capture degradation at the micro scale, i.e. on a particle or even molecular level [13e15]. However, evidence suggests that meso and macro scale features, such as inhomogeneities in the structure of the electrodes, have a significant effect on cell degradation as a whole [16,17]. Structural nonuniformity can lead to inhomogeneous distributions of current densities and degrees of lithiation inside the electrode material, which in turn causes inhomogeneous degradation of the electrode. Evidence of such inhomogeneities has also been observed in the course of a post-mortem analysis of commercial Kokam pouch cells (described in detail in Section 2.1), which are the subject of this work. After low current rate (C/25) capacity tests, five cells were opened in an argon filled glove box and their electrode sheets visually inspected. Each cell consists of 20 sheets of positive (PE) and negative (NE) electrodes. Some of the investigated cells were fully charged, i.e. their negative graphite electrodes fully lithiated. Lithiated graphite has a golden color as opposed to the black color of delithiated graphite. Fig. 2 illustrates the difference in lithiation of graphite electrode sheets extracted from the same, fully charged cell. Whereas most NE sheets appeared to be uniformly lithiated (Fig. 2 a)), one NE sheet was clearly non-uniformly lithiated, as shown in Fig. 2 b). The cell was charged according to the test procedure specified in Table 3, with $100\\%$ SoC at the end of test. The standard deviation between the capacities of the five investigated pouch cells was less than $0.2\\%$ and the cell with one non-uniformly lithiated graphite sheet actually exhibited the highest capacity. This illustrates that meso- and macro-scale inhomogeneities can not easily be identified in commercial Li-ion cells but they may have long term effects on degradation. Bottom-up physics-based models may not be able to capture such inhomogeneities on a micro-scale. \n\n![](images/8f07251d9f79e00da69ec35f84fa2e1e0a339ef5f77684535a251acf8163b703.jpg) \nFig. 2. Graphite negative electrodes extracted from a fully charged Kokam pouch cell; a) uniformly lithiated, b) non-uniformly lithiated. \n\n![](images/b22d994816fdb9e27e72faeaf2c68a6038c58b5cd1e4ab26891e71c3c14fb6f2.jpg) \nFig. 1. Degradation mechanisms in Li-ion cells. \n\nAs an alternative, we propose to rely more heavily on a diagnostic approach, built on frequent cell characterisations using available measurements which include information on the state of health (SoH) of the cell. One such measurement is the cell's open circuit voltage (OCV). Since the OCV is the difference between the cathode and the anode voltage, it provides a thermodynamic fingerprint of the electrodes at any point in time. Changes in this fingerprint can offer valuable information on path-dependent degradation of both the individual electrodes and the cell as a whole. Not every degradation mechanism leaves a unique fingerprint in the cell's OCV but sets of mechanisms can be clustered into so-called degradation modes, which have a measurable effect on the OCV of the cell and the electrodes [18e21]. There are three commonly reported degradation modes: \n\n1 Loss of lithium inventory (LLI): lithium ions are consumed by parasitic reactions, such as surface film formation (e.g. SEI growth), decomposition reactions, lithium plating, etc. and are no longer available for cycling between the positive and negative electrode, leading to capacity fade. Surface films may also cause power fade. Lithium ions can also be lost if they are trapped inside electrically isolated particles of the active materials. \n\n2 Loss of active material of the NE $(\\mathbf{LAM_{NE}})$ : active mass of the NE (or anode) is no longer available for the insertion of lithium due to particle cracking and loss of electrical contact or blocking of active sites by resistive surface layers. These processes can lead to both capacity and power fade. \n\n3 Loss of active material of the PE $\\mathbf{(LAM_{PE})}$ : active mass of the PE (or cathode) is no longer available for the insertion of lithium due to structural disordering, particle cracking or loss of electrical contact. These processes can lead to both capacity and power fade. \n\nA more comprehensive list of degradation mechanisms, their causes, effects and links to degradation modes is provided in Fig. 3. Note that Fig. 3 only lists the effects of degradation mechanisms and modes on the cell's thermodynamic (i.e. its OCV), not its kinetic behaviour. The primary effect of degradation on the cell's kinetics is an increase in internal resistance or cell impedance, which is easily measured by the voltage drop in response to a load. It should be noted that an increase in resistance can also lead to a decrease in useful cell capacity under load, since the lower voltage cut-off of the cell is reached sooner in a cell with a higher internal resistance. Equivalently, the higher voltage cut-off is reached sooner during charging. Methods to estimate internal cell resistance are widely reported [22e24] and not the subject of the presented work. \n\nThe assumed links between the OCV and degradation modes have been used for SoH estimation in the literature [19,25,26]. However, to the best of our knowledge, the existence of the proposed degradation modes has never been proven experimentally and unambiguously but only in simulation. Moreover, methods for estimating degradation modes and inferring the SoH of Li-ion cells are typically based on derivatives of OCV or cell capacity, so called incremental capacity analysis (ICA) [27] or differential voltage analysis (DVA) [28]. Differentiating measurements amplifies the noise in the signal and makes it more difficult to use the resulting data for processing. This is especially problematic in practical applications where voltage measurements may be noisier than in a laboratory environment. In response to these open questions and challenges, two primary objectives were defined for this work: \n\n1. The design and execution of experiments to verify the manifestations of LLI, $\\mathsf{L A M}_{\\mathrm{NE}}$ and $\\mathrm{\\DeltaLAM_{PE}}$ on the OCV of Li-ion cells. \n2. The creation of a diagnostic algorithm capable of identifying and quantifying the nature and extent of degradation modes present \n\n![](images/c89287b4f5dcc5e1f349202144e1f07d5db8da76472b31989440f275f0130d91.jpg) \nFig. 3. Cause and effect of degradation mechanisms and associated degradation modes. \n\nin a Li-ion cell based exclusively on the cell's OCV without performing derivative operations on the measurements. \n\n# 2. Experimental \n\n# 2.1. Material preparation \n\nCoin cells were constructed with known amounts of lithium inventory and active electrode materials in order to emulate the different degradation modes. All coin cells were manufactured from electrodes harvested from commercial Kokam $740\\mathrm{mAh}$ pouch cells. The NE material of the Kokam pouch cells is graphite and the PE material is a blend of lithium cobalt oxide (LCO) and lithium nickel cobalt oxide (NCO). \n\nThe pouch cells were opened in an argon filled glove box using a ceramic scalpel. The electrode sheets were extracted, rinsed with dimethyl carbonate and dried under vacuum for $20~\\mathrm{{min}}$ . The NE sheets consist of copper foil current collectors coated on both sides with graphite, and the PE sheets of aluminium foil current collectors coated on both sides with LCO/NCO. In order to improve electronic conductivity between the current collectors and the coin cell contacts, active material was removed from one side of the electrode sheets using $N\\cdot$ -methyl-2-pyrrolidone. The exposed $\\mathsf{C u/A l}$ surfaces were cleaned with dimethyl carbonate and the electrode disks were cut to size using hole punches. The coin cells were assembled using Celgard separators whetted with LP30 electrolyte ${\\mathrm{~}}1.0{\\mathrm{~M~LiPF}}_{6}$ solution in ethylene carbonate (EC) and dimethyl carbonate (DMC); $\\mathsf{E C/D M C}=50/50\\$ . \n\nFive reference cells were assembled with electrodes extracted from discharged $(0\\%S_{0}C)$ and fully charged ( $100\\%$ SoC) cells. Both positive and NE disks were cut to a diameter of $15~\\mathrm{mm}$ and the separator to $20~\\mathrm{mm}$ , as illustrated in Fig. 4 a). The reference cells served as a baseline against which the degradation modes were compared, and provided a measure for the reproducibility of the coin cell manufacturing process. \n\nTwo half-cells, one with positive and one with NE material, with $15\\mathrm{mm}$ electrode disks were made in the same way as the full cells except with lithium foil as counter electrodes (see Table 1). The half-cells served to parametrize the OCV model, as described in Section 3.2. The reference cells and half-cells used in the experiments are listed in Table 1 along with the SoC of the electrodes at the time of assembly and the electrode disk diameters. The SoC of the electrodes refers to the degree of lithiation of the respective electrode at the time of assembly. For example, in a fully charged cell, the SoC of the PE is $0\\%$ and the SoC of the NE is $100\\%$ . \n\nLoss of lithium inventory (LLI) was created by combining the PE of a pouch cell discharged to a higher SoC with the NE of a pouch cell discharged to a lower SoC. For example, combining a PE from a cell discharged to $25\\%$ SoC with a NE from a cell discharged to $0\\%$ creates a cell with $25\\%$ LLI, since the NE is the limiting electrode during discharge and once it has reached its upper voltage limit (the lower voltage limit of the cell), no more lithium can be extracted. In coin cells with emulated LLI, both electrode disks were $15~\\mathrm{mm}$ in diameter. \n\nLoss of active electrode material was created by reducing the diameter of the respective electrode disk. The commercial electrodes extracted from the Kokam cells were very uniformly coated with active material, so the useful capacity of the electrodes was assumed to be proportional to their surface area. Loss of NE material $(\\mathrm{LAM_{NE}})$ was created by combining a larger PE disk with a smaller NE disk. Fig. 4 b) illustrates a cell with $36\\%\\mathrm{LAM_{NE}}$ , where the NE (anode) disk is $12~\\mathrm{mm}$ in diameter and the PE (cathode) disk is $15~\\mathrm{mm}$ in diameter. Loss of PE material $\\left(\\mathrm{LAM_{PE}}\\right)$ was created by combining a larger NE disk with a smaller PE disk. Fig. 4 c) shows a cell with $36\\%$ $\\mathsf{L A M}_{\\mathrm{PE}}$ , where the PE (cathode) disk is $12\\mathrm{mm}$ in diameter and the NE (anode) disk is $15~\\mathrm{mm}$ in diameter. Theoretically, active electrode material can be lost in lithiated, delithiated and partially lithiated states. Loss of lithiated NE material $(\\mathrm{LAM_{NE,li}})$ was emulated by combining a $12\\mathrm{mm}\\mathrm{NE}$ disk with a $15\\mathrm{mm}\\mathrm{PE}$ disk, both harvested from a fully charged pouch cell $\\mathsf{T o C}=100\\%$ . Equivalently, loss of delithiated NE material $\\mathsf{L A M}_{\\mathrm{NE,de}}$ was emulated by combining a $12\\mathrm{mm}\\mathrm{NE}$ disk with a $15~\\mathrm{mm}$ PE disk, both harvested from a fully discharged pouch cell $S0C=0\\%$ . The same principle was used to create loss of lithiated PE material $(\\mathrm{LAM_{PE,li}})$ . A limitation of this experimental approach to simulate the loss of active material is the fact that lithium insertion/extraction in the overhang region of the larger electrode is limited by the lateral diffusion of lithium in the active material. The simulation of LAM using this method is therefore only valid for very slow C-rates. For this reason, a very low pseudo-OCV C-rate of $C/25$ is used in this work. \n\n![](images/08f29b2069110a64cd191ce4561c5cc8eee89ec15cba27a0a98d3df54b539aa0.jpg) \nFig. 4. Sizes of electrode disks and separators used in coin cells for a) reference cells and cells with LLI, b) cells with $36\\%$ $\\mathrm{LAM_{NE}}$ and c) cells with $36\\%$ $\\mathrm{\\DeltaLAM_{PE}}$ . \n\nA combination of LLI and $\\mathsf{L A M}_{\\mathrm{PE,li}}$ was created by combining a $14~\\mathrm{mm}$ PE disk harvested from a pouch cell previously discharged to $25\\%$ SoC with a $15\\ \\mathrm{mm}\\ \\mathrm{NE}$ disk harvested from a pouch cell previously discharged to $0\\%$ SoC. \n\nTable 1 Baseline cell and half-cell electrodes. \n\n\n
Reference cellsCoin cell IDSoC PESoC NEDiameter PEDiameter NE
Full cellsRef 1100%0%15 mm15 mm
Ref 2100%0%15 mm15 mm
Ref 3100%0%15 mm15 mm
Ref 40%100%15 mm15 mm
Half-cellsRef 50%100%15 mm15 mm
HCPE100%15 mm
HCNE0%15 mm
\n\nTable 2 Test cell electrodes. \n\n\n
Deg.modeCoin cell IDSoC PESoC NEDiameter PEDiameter NE
25% LLILLI2575%0%20 mm20 mm
50% LLILLI5050%0%20 mm20 mm
36% LAMNE.iLAMNE,i0%100%15 mm12 mm
36% LAMNE,deLAMNE,de100%0%15 mm12 mm
36% LAMPE.liLAMPE.li100%0%12 mm15 mm
25% LLI+13% LAMPE,liLLI + LAMPE75%0%14 mm15 mm
\n\nTable 3 Test procedure for pouch cell preparation. \n\n\n
SoC at end of testTest stepCurrentlimits
0%CC charge29.6mAVcell > 4.2V
100%CC discharge29.6 mAVcell <2.7V
CC charge29.6 mAVcell > 4.2V
CC discharge29.6 mAVcell <2.7V
50%CC charge29.6mAVcell > 4.2V
CC charge29.6 mAVcell > 4.2V
CC discharge29.6mAVcell<2.7V
CC charge29.6 mAVcell > 4.2V
25%Rest0 mAtime>10min
CC discharge29.6 mAQdch > 0.5 ×Qmeas
CC charge29.6 mAVcell > 4.2V
CC discharge29.6mAVcell <2.7V
CC charge29.6 mAVcell > 4.2V
Rest CC discharge0 mA 29.6mAtime>10min Qdch > 0.75 ×Qmeas
\n\nTable 2 provides a list of all the coin cells manufactured to emulate the different degradation modes, including the SoC of the electrodes and the diameter of the electrode disks. \n\n# 2.2. Cell testing \n\nAll cell tests were conducted in thermal chambers at $30^{\\circ}\\mathsf C$ using BioLogic potentiostats of type MPG-205 and SP-150. Before the start of tests, pouch cells and coin cells were stored in the thermal chambers for $^{3\\mathrm{~h~}}$ for thermal equilibration. The pouch cells from which the electrodes were extracted for the coin cell manufacturing were prepared according to the test schedule listed in Table 3. Firstly, the capacities of the pouch cells $\\left(\\mathrm{Q}_{\\mathrm{meas}}\\right)$ were measured during a C/25 ( $29.6\\ \\mathrm{\\mA})$ discharge following a $C/25$ charge. Secondly, following another C/25 charge, the SoC of the pouch cells was adjusted by a $C/25$ discharge to the levels required for the respective coin cells, based on the initial capacity measurements. \n\nThe reference coin cells (full cells and PE/NE half-cells) and the coin cells with induced degradation modes were tested according to the test schedule in Table 4, which consisted primarily of one cycle at C/2 and one cycle at $C/25$ . Partial charges/discharges served to adjust the cells' SoC in preparation for the full cycles, as listed in Table 4. The $C/2$ cycle served to assess the general performance of the cells, based on which under-performing cells were discarded, and the $C/25$ cycle served as pseudo-OCV measurement. \n\nAt a current rate of C/25, the voltage drop in the coin cells was measured to be on the order of $9\\times10^{-4}\\mathrm{mV}$ , which was considered negligible and any voltage measurements recorded at a current rate of $C/25$ were treated as pseudo-OCV. These pseudo-OCV measurements were used in the degradation model to estimate the degradation modes. The expected capacities of the coin cells were calculated based on the active surface areas of the electrodes. The total electrode surface area of the pouch cells was $600~\\mathrm{cm}^{2}$ and their average capacity measured at $C/25$ was $759~\\mathrm{\\mAh}$ with a standard deviation of $<0.2\\%$ Given a surface area of $1.767\\mathrm{cm}^{2}$ in all coin cells with electrode diameters of $1.5\\mathrm{cm}$ , the expected nominal coin cell capacity is $2.236\\ \\mathrm{\\mAh}$ , which gives a $C/25$ current of $0.089\\mathrm{mA}$ and a $C/2$ current of $1.118~\\mathrm{{mA}}$ The standard deviation of the capacities of all five reference coin cells measured at a $c/2$ current rate was $5.4\\%$ , which served as the measure of uncertainty for the estimation of degradation modes. \n\nTable 4 Test procedure for coin cells. \n\n\n
Test IDTest stepCurrentLimits
Full cellsPart. chargeCC charge1.118 mAVcell > 4.2V
C/2 cycleCC discharge1.118 mAVcell<2.7V
CC charge1.118mAVcell > 4.2V
Part. dischargeCC discharge1.118 mAVcell<3.75V
Part. chargeCC charge0.089mAVcell> 4.2V
C/25 cycleCC discharge0.089mAVcell<2.7V
PE half-cellCC charge0.089mAVcell > 4.2V
Part. chargeCC charge1.118 mAVcell > 4.5V
C/2 cycleCC discharge1.118 mAVcell<3.5V
Part. dischargeCC charge1.118 mAVcell >4.5V
CC discharge1.118 mAVcell<4.0V
Part. chargeCC charge0.089mAVcell >4.5V
C/25 cycleCC discharge0.089mAVcell<3.5V
NE half-cellCC charge0.089mAVcell > 4.5V
Part. dischargeCC discharge1.118 mAVcell <0.001V
C/2 cycleCC charge1.118 mAVcell>1.3V
CC discharge1.118 mAVcell<0.001V
Part. chargeCC charge1.118 mAVcell >0.1V
Part. chargeCC charge0.089mAVcell >1.3V
C/25 cycleCC discharge0.089mAVcell<0.001V
CC charge0.089mAVcell > 1.3V
\n\n# 3. Model development \n\n# 3.1. Theory \n\nThe theory underlying the proposed degradation modes and their effects on the OCV of cells and electrodes is well documented in the literature [19,26,29]. This section explains the approach and the extensions of the presented work. \n\nIn Li-ion cells, the end of charge (EoC; $100\\%$ SoC) and the end of discharge (EoD; $0\\%$ SoC) are defined by a corresponding maximum and minimum cell voltage, in order to ensure safe operation. The lithium cycled within these limits constitutes the cell's useful capacity. During charge, the PE is limiting, since its rising voltage, resulting from delithiation, triggers the cell's EoC voltage limit (in this case $4.2\\mathrm{~V~}$ ). Analogously, the NE is limiting during discharge, triggering the EoD voltage limit (in this case $2.7\\:\\mathrm{V}$ . \n\nFig. 5 a) shows the base case of a pristine cell. The bars on the left symbolise the anode (NE, in red) and the cathode (PE, blue). The areas of the bars represent the electrode capacities, not to scale. The golden area represents the cyclable lithium, which corresponds to the cell capacity, in this case intercalated in the NE in a fully charged cell. In commercial Li-ion cells, there is generally an excess of NE material, which is illustrated by the larger NE bar. The misalignment of the two bars indicates which electrode is limiting at $100\\%$ SoC and $0\\%$ SoC, respectively. The plot on the right of Fig. 5 a) depicts the OCV curves of the PE in blue, the NE in red and the cell in grey, as functions of the cell's normalised capacity, denoted as $S o C_{\\mathrm{Cell}}$ in $\\%$ . The horizontal dash/dot lines highlight the upper and lower voltage limits of the cell at $4.2\\:\\mathrm{V}$ and $2.7\\mathrm{V}.$ , respectively, and the vertical dash/dot lines highlight the corresponding maximum and minimum SoC of the whole cell. The points on the OCV of the PE and NE that correspond to the cell's upper and lower voltage limits are indicated by circular markers on the respective OCV curves. As LLI, $\\mathsf{L A M}_{\\mathrm{NE}}$ and $\\mathrm{\\DeltaLAM_{PE}}$ come into effect, the utilised portions of the electrodes change, which is reflected in their OCVs. This means that the OCV of the electrodes at EoC and EoD may also change accordingly. The EoC and EoD OCVs of the electrodes are further affected by maintaining constant upper and lower cell voltage limits of $4.2~\\mathrm{V}$ and $2.7~\\mathrm{V}$ , respectively. Imposing these voltage limits can lead to a stoichiometric offset between the electrodes, which has not been addressed in the literature but is an important addition of this work. The effects of these offsets are discussed individually for each degradation mode. \n\n![](images/7f1ab5981f57a39a9dea48468975f22d50d59eb9b4086bf88cd33100b5d6149f.jpg) \nFig. 5. Examples of the different degradation modes. The bars in the left column illustrate the utilisation of the electrodes as a result of the degradation modes, compared to the base case (not to scale). The plots on the right show the corresponding OCV of the electrodes and the cell. \n\nIf cyclable lithium is lost a smaller fraction of the electrodes' capacities is used, due to the increased offset between the positive and negative electrode. The example of $30\\%$ LLI is illustrated by both the shift of the bars on the left of Fig. 5 b) and the shift of the negative electrode's OCV curve in the plot on the right. The OCV curves of the base case are depicted for comparison as broken lines. The yellow areas in the plots on the right of Fig. 5 indicate lost cell capacity. The OCVs of the electrodes at the EoC and EoD are also affected by the stoichiometric offset due to the imposed cell voltage limits. When a cell which has lost $30\\%$ of its lithium inventory approaches its EoD $(0\\%S_{0}C)$ , the PE voltage is significantly higher than it would be in a pristine cell at EoD (compare the two circular blue markers on the PE OCV curve at the EoD in Fig. 5 b)). If the cut-off voltage of the NE remained unchanged, the minimum cell voltage of $2.7\\:\\mathrm{V}$ could not be reached. In reality, as the cell approaches its EoD and the cell voltage is driven towards $2.7\\mathrm{V}.$ , more lithium is extracted from the NE and inserted into the positive electrode, leading to a steep rise in the NE voltage, ultimately reaching the minimum cell voltage of $2.7~\\mathrm{V}$ (compare the two circular red markers on the NE OCV curves at the EoD in Fig. 5 b)). Equivalently, as a cell with $30\\%$ LLI approaches its EoC, the NE voltage is higher than in a pristine cell. Therefore, as the cell is driven toward its upper voltage limit of $4.2\\:\\mathrm{V}$ , more lithium is extracted from the PE and inserted into the negative electrode, until the rise in PE voltage triggers the upper cut-off condition of the cell (compare the two circular blue markers on the PE voltage curve at the EoC in Fig. 5 b). In the case of $30\\%$ LLI, this stoichiometric offset causes a noticeable increase in cell capacity, on the order of $2\\%$ , as indicated by the green area in the OCV plot of Fig. 5 b). Driving the PE to ever higher voltages can destabilize the structure and, in the worst case, the delithiated cathode material reacts exothermically with the electrolyte, triggering thermal runaway [30]. \n\nThe loss of lithiated active material in the NE $(\\mathrm{LAM_{NE,li}})$ can occur as a result of particle cracking or electronic contact loss between particles of the active electrode material or between the active material and the current collector. The lithium trapped inside the isolated graphite particles and can no longer be cycled, leading to a decrease in the cell's capacity. This capacity loss is illustrated by a shortened red/golden NE bar on the left of Fig. 5 c) and the yellow area in the OCV plot on the right of the figure. Less NE material remains to receive and release lithium, which is manifested in a shrinkage of the OCV curve of the NE, as shown in Fig. 5 c). Less NE material means that the current density on the remaining material is increased during cycling, which could in turn lead to accelerated aging of the NE and, in the worst case, to lithium plating on the surface if the charging rates exceed the rates of lithium diffusion into graphite. In the event that only fully lithiated NE material is lost, the EoC voltage of the NE remains the same (as indicated by the padlock symbol in the plot of Fig. 5 c). The EoD voltage of the positive and negative electrodes change in the same manner as they would in the case of LLI (indicated by the circular markers). \n\nThe loss of delithiated NE material $\\left(\\mathrm{LAM}_{\\mathrm{NE,de}}\\right)$ initially only has a small effect on the capacity of the cell, since there is an excess of NE material and the OCV of the NE at the EoD remains constant (see Fig. 5 d)). However, the OCV of the NE at the EoC gradually decreases as a result of the loss of active material, which limits the PE to a lower OCV at the EoC thus extracting less lithium. Once the remaining capacity of the NE is smaller than the original cell capacity, the cell loses capacity at the same rate as it loses active NE material. The capacity loss is equivalent to the portion of lithium inventory that remains trapped in the PE at higher voltages, which is indicated by the blue/gold striped area in the PE bar of Fig. 5 d). The example of $30\\%$ LAMNE,de illustrated in Fig. 5 d), effectively leads to a capacity loss of $12\\%$ . Moreover, since the cell is still driven to its upper voltage limit of $4.2\\:\\mathrm{V}$ the NE can be forced to negative voltages, which initiates lithium plating. This is a mechanism that must be prevented in practical applications, since it can lead to dendrite formation and internal short-circuits, which in turn cause catastrophic cell failure [31,32]. \n\nThe loss of lithiated PE material $(\\mathrm{LAM_{PE,li}})$ is analogous to $\\mathsf{L A M}_{\\mathrm{NE,li}}$ ; it is a result of electronic contact loss to lithiated PE particles. An example of $30\\%\\mathrm{LAM_{PE,li}}$ is given in Fig. 5 e). The OCV curve of the PE shrinks compared to its original extent, since a smaller amount of active material contains less lithium and is discharged faster. At the cell's EoC, this means that less lithium is inserted into the NE, leaving it at a higher OCV, which must be matched by a higher OCV of the PE in order to reach the cell's upper voltage limit of $4.2\\mathrm{V}.$ A similar scenario arises as discussed for the case of LLI - increasing $\\mathsf{L A M}_{\\mathrm{PE,li}}$ leads to ever higher PE voltages, potentially destabilizing the PE material. \n\nA loss of delithiated PE material $\\left(\\mathrm{LAM}_{\\mathrm{PE,de}}\\right)$ can potentially affect the cell capacity at early stages, since there is only a smaller buffer of PE material compared to that in the negative electrode. A scenario of $30\\%\\ \\mathrm{LAM_{PE,de}}$ is illustrated in Fig. 5 f). The OCV of both electrodes at the cell's EoC remains constant but the OCV of the PE at the cell's EoD decreases as the OCV curve of the PE shrinks compared to its original extent. In the case of commercial LCO/NCO material, there can be a steep drop in OCV below $\\sim3.4\\mathsf{V}.$ Such a drop leads to an equivalently lower OCV of the NE at the cell's EoD (indicated by the circular markers in the OCV plot of Fig. 5 f)). The lithium inserted in the NE at higher NE voltages can no longer be accessed for cycling (illustrated by the red/gold striped pattern in the NE bar of Fig. 5 f)), which causes the observed capacity loss of $24\\%$ . \n\n# 3.2. The OCV model \n\nIn previous work, we developed a parametric OCV model which can be used as a functional expression of the OCV of both the electrodes and the cell [33]. This OCV model is used as the basis for modelling and estimating the degradation modes discussed in this work. A brief account of the application of the OCV model is provided as follows. For a more detailed description, the reader is referred to [33]. \n\nThe normalised capacity of an electrode can be expressed as the ratio $x$ of occupied to available lattice sites in a host structure, ranging from 0 to 1. In solid multi-phase intercalation materials, $x$ can be calculated as a function of the open circuit voltage $E^{O C}$ by \n\n$$\nx\\Big(E^{O C}\\Big)=\\sum_{i=1}^{N}\\frac{\\Delta x_{i}}{1+\\exp^{\\left(E^{O C}-E_{0,i}\\right)a_{i}e/k T}}\n$$ \n\nwhere $N$ is the number of phases in the material, $i=\\{1,2,...N\\},\\Delta x_{i}$ is the fraction of material attributed to phase i, $E_{0,i}$ is the energy of lattice sites in phase i, $a_{i}$ is an approximation of the interaction energy between intercalated ions, $e$ is the elementary charge, $k$ is the Boltzmann constant and $T$ the temperature in Kelvin. \n\nIn the first step of the OCV model parametrization, Equation (1) was fitted to the pseudo-OCV measurements of the PE and NE halfcells. In previous work, a minimum of four phases were identified in both the PE and NE material for this particular cell chemistry [33]. In this work, high qualities of fit of electrode OCVs are paramount in order to achieve accurate estimates of degradation modes. For this reason, an additional phase was added to the OCV model in order to improve the fit qualities from a root mean squared error (RMSE) of $7\\mathrm{mV}$ for the PE and $12{\\mathrm{~mV}}$ for the NE [33] to $<3\\mathrm{mV}$ for both electrodes in this work, as demonstrated in Fig. 6. Equation (1) can not be expressed explicitly as $E^{O C}(x)$ for multiple phases $N$ and is therefore solved iteratively during the optimisation. The objective function used for the optimisation is \n\n$$\n\\mathrm{arg}_{\\theta}\\mathrm{min}\\mathrm{RMSE}=\\sqrt{\\frac{\\sum_{i}^{n}\\left(\\widehat{E}_{i}^{0C}(\\theta)-E_{i}^{0C}\\right)^{2}}{n}}\n$$ \n\nwhere $n$ is the number of OCV measurements and $\\widehat{E}_{i}^{O C}$ is the fitted electrode OCV. $\\theta$ are the model parameters obtbained for each electrode, summarised by \n\n$$\n\\theta=\\left[{\\begin{array}{c c c}{E_{0,1}}&{\\Delta x_{1}}&{a_{1}}\\\\ {E_{0,2}}&{\\Delta x_{2}}&{a_{2}}\\\\ {\\vdots}&{\\vdots}&{\\vdots}\\\\ {E_{0,5}}&{\\Delta x_{5}}&{a_{5}}\\end{array}}\\right].\n$$ \n\nIn the second step of the OCV model parametrization, the OCVs of the electrodes were fitted simultaneously with the OCV of the cell - using pseudo-OCV measurements recorded on a full cell - using parameters $\\theta$ of each electrode as an initial guess. The OCV of the cell was calculated by \n\n![](images/1bf5280d09eddf4fcd9ffab1da573a02cffa7f7a9e11be89c54bbc0c8f785281.jpg) \nFig. 6. OCV model fitting results. \n\nThe objective function used for the second optimisation was \n\n$$\n\\arg_{\\theta_{\\mathrm{cell}}}\\operatorname*{min}{\\mathrm{RMSE}}=\\sqrt{\\frac{\\sum_{i}^{n}\\left(\\widehat{E}_{C e l l,i}^{O C}(\\theta_{C e l l})-E_{C e l l,i}^{O C}\\right)^{2}}{n}}\n$$ \n\n$$\n+\\sqrt{\\frac{\\displaystyle{\\sum_{i}^{n}\\left(\\widehat{E}_{P E,i}^{O C}\\left(\\theta_{C e l l,P E}\\right)-E_{P E,i}^{O C}\\right)^{2}}}{n}}\n$$ \n\n$$\n+\\sqrt{\\frac{\\displaystyle\\sum_{i}^{n}\\left(\\widehat{E}_{N E,i}^{O C}\\big(\\theta_{C e l l,N E}\\big)-E_{N E,i}^{O C}\\right)^{2}}{n}}.\n$$ \n\nParameters $\\theta_{C e l l}$ can be summarised by \n\n$$\n\\theta_{C e l l}=\\left[\\begin{array}{c c c c c c c}{E_{0,P E,1}}&{\\Delta x_{P E,1}}&{a_{P E,1}}&{E_{0,N E,1}}&{\\Delta x_{N E,1}}&{a_{N E,1}}\\\\ {E_{0,P E,2}}&{\\Delta x_{P E,2}}&{a_{P E,2}}&{E_{0,N E,2}}&{\\Delta x_{N E,2}}&{a_{N E,2}}\\\\ {\\vdots}&{\\vdots}&{\\vdots}&{\\vdots}&{\\vdots}&{\\vdots}&{\\vdots}\\\\ {E_{0,P E,5}}&{\\Delta x_{P E,5}}&{a_{P E,5}}&{E_{0,N E,5}}&{\\Delta x_{N E,5}}&{a_{N E,5}}\\end{array}\\right].\n$$ \n\n$\\theta_{C e l l,P E}$ and $\\theta_{C e l l,N E}$ in Equation (5) include the electrode parameters as detailed in Equation (3). Using the parameters $\\theta_{C e l l}$ , Equations (1) and (4) are applied in the degradation model to compute the OCVs and normalised capacities of electrodes and cells for the base case, i.e. a pristine cell without any signs of degradation. It is important to emphasize that the OCV model is only parameterized in this fashion once for the base case. Fitting the OCV of degraded cells, thus identifying the degradation modes, is achieved using the degradation model described below. This is based on the assumption that the degradation does not impact the individual phases of the electrode materials in different ways. \n\n# 3.3. The degradation model \n\nThe degradation model is designed to estimate three parameters only; the degradation modes LLI, $\\mathsf{L A M}_{\\mathrm{NE}}$ and $\\mathrm{\\DeltaLAM_{PE}}$ . The objective of the model is to estimate the extent of the different degradation modes at any point in a cell's life by fitting the cell's OCV. Only the full cell's OCV measurement is required for this. The parameters of the OCV model described in Section 3.2 remain unaltered. \n\nThe degradation modes affect the electrodes' capacity ranges in terms of (i) their offset, increased by LLI, (ii) their scaling, affected by $\\mathsf{L A M}_{\\mathrm{NE}}$ and $\\mathrm{\\DeltaLAM_{PE}}$ and (iii) the stoichiometric offset, at EoC $(\\Delta x_{E O C})$ and EoD $(\\Delta x_{E O D})$ due to the constant upper and lower cell voltage limits. \n\nEquations (7)e(10) describe how LLI, $\\mathrm{LAM_{PE}}$ , $\\mathsf{L A M}_{\\mathrm{NE}}$ , $\\Delta x_{E O C}$ and $\\Delta x_{E O D}$ affect the normalised capacity of the PE at the cell's EoC $(x_{P E,E O C})$ and EoD $\\left({{x}_{P E,E O D}}\\right)$ and the normalised capacity of the NE at the cell's EoC $(x_{N E,E o C})$ and EoD $(x_{N E,E o D})$ . \n\n$$\nx_{P E,E o C}=\\frac{\\Delta x_{E o C}}{1-\\mathrm{LAM_{PE}}}\n$$ \n\n$$\nx_{P E,E o D}=\\frac{\\Delta x_{E o D}+1-\\mathrm{LLI}+\\mathrm{LAM_{PE}}}{1-\\mathrm{LAM_{PE}}}\n$$ \n\n$$\nx_{N E,E o C}=\\frac{\\Delta x_{E o C}+\\mathrm{LLI}-\\mathrm{LAM_{NE}}}{1-\\mathrm{LAM_{NE}}}\n$$ \n\n$$\nE_{C e l l}^{O C}=E_{P E}^{O C}-E_{N E}^{O C}.\n$$ \n\n$$\nx_{N E,E o D}=\\frac{\\Delta x_{E o D}}{1-\\mathrm{LAM}_{\\mathrm{NE}}}\n$$ \n\nLLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ in Equations (7)e(10) range from 0 to 1, where 1 is equivalent to the cell's original capacity; e.g. $\\mathrm{LLI}=0.1$ means that the loss of lithium inventory is equivalent to $10\\%$ of the cell's original capacity. LAMPE and $\\mathsf{L A M}_{\\mathrm{NE}}$ refer to the loss of active material as a fraction of the active material originally utilised within the capacity range of the full cell. The normalised capacities of the positive and negative electrodes at EoC and EoD are linked through the cell's upper and lower voltage limits, denoted as ECOeCll;high and ECOeCll;low, respectively, according to \n\n$$\nE_{C e l l,h i g h}^{O C}-\\widehat{E}_{P E,E o C}^{O C}\\left(x_{P E,E o C}\\right)+\\widehat{E}_{N E,E o C}^{O C}\\left(x_{N E,E o C}\\right)=0\n$$ \n\nand \n\n$$\nE_{C e l l,l o w}^{O C}-\\widehat{E}_{P E,E o D}^{O C}\\left(x_{P E,E o D}\\right)+\\widehat{E}_{N E,E o D}^{O C}\\left(x_{N E,E o D}\\right)=0.\n$$ \n\nEquations (11) and (12) define the OCV of electrodes and cell at $100\\%$ SoC and $0\\%$ SoC, respectively, when upper and lower cell voltage limits are imposed. The respective points on the OCV curves of cell and electrodes are marked by the vertical, dash/dotted lines in Fig. 5. ECell;high and ECOeCll;low have predefined values, in this case $4.2\\mathrm{~V~}$ and $2.7~\\mathrm{V}$ , respectively. $\\widehat{\\boldsymbol{E}}_{P E/N E,E o C}^{O C}$ and $\\widehat{E}_{P E/N E,E o D}^{O C}$ are the modelled OCV of the PE and N bat the EoC andbEoD, respectively. The OCVs of the electrodes at the cell's EoC and EoD in Equations (11) and (12) $(\\widehat{\\boldsymbol{E}}_{P E,E o C}^{O C},\\widehat{\\boldsymbol{E}}_{N E,E o C}^{O C},\\widehat{\\boldsymbol{E}}_{P E,E o D}^{O C},E_{N E,E o D}^{O C})$ are calculated using Equation (1). $\\Delta x_{E O C}$ and $\\Delta x_{E o D}$ can be calculated by substituting Equations (7)e(10) into Equations (11) and (12) and solving the linear system of equations. The estimated LLI, $\\mathrm{\\DeltaLAM_{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ are inserted into Equations (7)e(10) during the optimisation described below. \n\nThe normalised capacity ranges of the electrodes in a degraded cell are defined by vectors of discrete values limited by the normalised capacities at the EoC and EoD according to Equations (13) and (14). The number of elements in the vectors depends on the number of sampling points obtained for the pseudo-OCV measurements. \n\n$$\n\\begin{array}{r l}&{\\widehat{\\mathbf{x}}_{\\mathbf{PE}}=\\big\\{x_{P E,E o C},...x_{P E,E o D}\\big\\}}\\\\ &{}\\\\ &{\\widehat{\\mathbf{x}}_{\\mathbf{NE}}=\\big\\{x_{N E,E o C},...x_{N E,E o D}\\big\\}}\\end{array}\n$$ \n\nThe OCVs of the electrodes in a degraded cell $(\\widehat{E}_{P E}^{O C},\\widehat{E}_{N E}^{O C})$ can thus be calculated by numerically solving Equation (b1) fobr $E^{O C}$ of the respective electrode, using the normalised electrode capacity ranges $\\widehat{\\mathbf{x}}_{\\mathbf{PE}}$ and $\\widehat{\\mathbf{x}}_{\\mathbf{NE}}$ . \n\nAt thbe cell levbel, the normalised cell capacity at EoC and EoD is calculated using Equations (15) and (16). \n\n$$\n\\begin{array}{l}{x_{C e l l,E o C}=\\Delta x_{E o C}}\\\\ {\\qquad\\ }\\\\ {x_{C e l l,E o D}=1-\\mathrm{LLI}+\\Delta x_{E o D}}\\end{array}\n$$ \n\nIn a pristine cell $100\\%$ SoC is equivalent to $x_{C e l l,E o C}=0$ and $0\\%$ SoC to $x_{C e l l,E o D}=1$ . The cell's original capacity is normalised, so that $x_{C e l l,E o D}-x_{C e l l,E o C}=1$ . The difference between $x_{C e l l,E o D}$ and xCell;EoC in a degraded cell corresponds to the cell's normalised capacity as a fraction of its original capacity, e.g. $x_{C e l l,E o D}-x_{C e l l,E o C}=0.9$ means that the cell has lost $10\\%$ of its original capacity. The normalised capacity range of the cell is defined by a vector of discrete values limited by $x_{C e l l,E o C}$ and $x_{C e l l,E o D}$ according to \n\n$$\n\\widehat{\\mathbf{x}}_{\\mathbf{Cell}}=\\big\\{x_{C e l l,E o C},...x_{C e l l,E o D}\\big\\}.\n$$ \n\nFinally, the OCV of the degraded cell, $\\widehat{\\boldsymbol{E}}_{C e l l,d e g}^{O C}$ , is caOlCculated fOoCr capacity range $\\widehat{\\mathbf{x}}_{\\mathbf{cell}}$ , by solving Equationb(2) using $\\widehat{E}_{P E}^{0\\mathfrak{C}}$ and $\\widehat{E}_{N E}^{\\cup\\mathfrak{c}}$ . Parameters LLI, $\\mathsf{L A M}_{\\mathrm{NE}}$ and $\\mathrm{\\DeltaLAM_{PE}}$ are estimated by mibnimisingbthe objective function \n\n$$\n{\\arg}{\\theta_{\\mathrm{deg}}\\operatorname*{min}\\mathrm{RMSE}}=\\sqrt{\\frac{\\displaystyle{\\sum_{i}^{n}\\left(\\widehat{E}_{C e l l,d e g}^{O C}\\left(\\theta_{d e g}\\right)-E_{C e l l,d e g}^{O C}\\right)^{2}}}{n}}\n$$ \n\nwhere $\\widehat{\\boldsymbol{E}}_{C e l l,d e g}^{O C}$ is the calculated OCV of the degraded cell, ECell;deg is the meabsured pseudo-OCV of the degraded cell, $n$ is the number of measurements and $\\theta_{d e g}$ are the parameters \n\n$$\n\\begin{array}{r}{\\theta_{d e g}=[\\mathrm{LLI},\\mathrm{LAM}_{\\mathrm{PE}},\\mathrm{LAM}_{\\mathrm{NE}}].}\\end{array}\n$$ \n\nThe fitting procedure is carried out in Matlab, using the activeset algorithm in Matlab's fmincon optimisation function. In order to ensure convergence to the global minimum, the optimisation is run repeatedly (100 times) from different starting points using Matlab's global optimisation function multistart. \n\nSince the cell's OCV drops off rapidly near the EoD, errors calculated at low OCV are generally greater than errors at higher OCV where the OCV curve is flat. In order to avoid a bias of the fit toward the lower end of the OCV curve, the calculation of the RMSE as described in Equation (18) was confined to the part of the OCV curve with a gradient of $\\frac{\\Delta E_{C e l l,d e g}^{O C}}{\\Delta{\\sf S o C}}<0.1$ \n\n# 4. Results and discussion \n\n# 4.1. OCV model fitting \n\nThe OCV model described in Section 3.2 and [33] was fitted to the pseudo-OCV measurements recorded on the electrode halfcells and a reference coin cell in order to obtain the OCV model parameters. High qualities of fit were achieved for both the OCV of the electrodes and the cell with root mean squared errors (RMSE) $<3\\mathrm{mV}$ (see Fig. 6). The solid lines in Fig. 6 show the fitted OCV results of the cell and the electrodes over the SoC range of the pristine cell. The high fitting accuracy is essential for the degradation model since any deviation from the actual OCV makes it more difficult to identify degradation modes, which may only have very slight effects on the OCV of a degraded cell. The estimated OCV model parameters - $\\boldsymbol{E}_{0,i},\\boldsymbol{a}_{i}$ and $\\Delta x_{i}$ - for each of the phases $i=\\{1...5\\}$ of the PE and the NE are listed in Table 5. \n\n# 4.2. Test of the diagnostic algorithm using synthesized data \n\nWith the OCV model parameterized, the degradation model described in Section 3.3 was used in ‘forward mode’ to create a number of scenarios of cells with known amounts of LLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ . The OCVs of the hypothetical degraded cells were subsequently used to test the ability of the diagnostic algorithm to identify the different degradation modes. It is important to point out that the model estimates the total amounts of lost active materials $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ , both lithitated and delithiated. Any lithium contained in lost active electrode material is included in the estimate of the total LLI; i.e. the total estimated LLI includes both the lithium lost through pure LLI (e.g. by SEI build up) and the lithium lost in lithiated active material $(\\mathrm{LAM_{PE,li}}$ and $\\mathsf{L A M}_{\\mathrm{NE,li}}.$ . For example, $10\\%$ of pure LLI and $5\\%$ of $\\mathsf{L A M}_{\\mathrm{NE,li}}$ gives a total of $15\\%$ LLI. The reason for the diagnostic algorithm to be designed in this manner is that a combination of e.g. LLI and $\\mathsf{L A M}_{\\mathrm{NE,de}}$ creates the same OCV signature as an equal amount of $\\mathsf{L A M}_{\\mathrm{NE,li}}$ . The same holds true for combinations of LLI and $\\mathsf{L A M}_{\\mathrm{PE}}$ . The fractions of lithiated and delithiated LAM can therefore not be uniquely identified if the assumption is that LLI can occur simultaneously, resulting from a different mechanism. An exceptional case would be one where LAM is detected but no LLI. In such a case, the respective LAM could be uniquely identified as loss of delithiated active material. In realworld scenarios of Li-ion cell degradation, there is no reason to assume that the loss of active electrode material occurs exclusively in lithiated or delithiated states - it is likely to occur over a range of different stages of lithiation. The approach to separate the loss of lithium contained in lost active electrode material from the loss of the active electrode material itself allows to account for these more realistic scenarios. \n\nTable 5 Estimated OCV model parameters. \n\n\n
NE
Eo,PE,i [V]apE,i [1]△XpE,i [1]Eo,NE,i [V]aNE,i [1]△XNE,i [1]
P15.0381.7530.0210.226-18.0720.025
P24.0790.1780.5230.219-0.1650.112
P33.9360.6810.1240.173-1.1880.243
P43.9003.0740.1360.132-14.7730.254
P53.6880.4700.1780.094-6.6900.365
\n\nThree artificial scenarios were created to test the diagnostic algorithm by running the degradation model in ‘forward mode’. The scenarios are listed in Table 6. The values in Table 6 are given as percentage of the cell's original capacity. Values of LAM refer to the loss of active material as a fraction of the active material originally utilised within the capacity range of the full cell. \n\nThe diagnostic algorithm was used to fit the degradation model to the synthetically generated cell OCVs, thereby identifying the amounts of total LLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ . The fitting results are depicted in Fig. 7, which shows the fitted cell and electrode OCVs on the left (Fig. 7 a), c) and d)) and the amounts of real and estimated LLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ on the right (Fig. 7 b), d) and f)). The dash/ dotted horizontal lines in the OCV plots of Fig. 7 indicate the cell's upper and lower voltage limits and the vertical lines indicate the corresponding relative capacity. The broken lines show the OCVs of the electrodes and cell of the reference (pristine) cell. Areas filled with yellow indicate capacity loss. For all three scenarios, perfect fits were obtained and all degradation modes accurately identified, which proves the ability of the diagnostic algorithm to uniquely identify the three different degradation modes by fitting the OCV of a degraded cell. \n\n# 4.3. Validation of the diagnostic algorithm using coin cell data \n\nThe diagnostic algorithm was used to estimate the degradation modes engineered by means of the customised coin cells (described in Section 2.1). The degradation model was fitted to the pseudoOCV measurements recorded on the coin cells and the results are displayed in Fig. 8; OCV fitting results on the left and the extent of real and estimated degradation modes on the right. The broken lines in the OCV plots on the left of the figure show the cell and electrode OCV of the reference (pristine) cell. The filled areas at the EoC and EoD indicate capacity loss (in yellow) or capacity gain (in green) of the respective cell as a result of degradation. Capacity gain refers to the extraction of additional lithium from the PE as a result of the imposed upper cell voltage limit, leading to a stoichiometric offset. This can be detrimental to the cell, since the PE is driven to higher voltages, which may accelerate its degradation. The capacity gain at the EoC is never greater than the accompanying capacity loss at the EoD but it can slightly reduce the overall capacity loss. The RMSE values displayed in the OCV plots were calculated from the measured and the fitted cell voltages for the entire cell voltage window of $2.7\\:\\mathrm{V}{-4.2\\:\\mathrm{V}}.$ The error bars on the bar charts on the right of Fig. 8 are based on the standard deviation of the capacities of the reference coin cells $(5.4\\%)$ , as described in Section 2.2. It should be emphasized that the uncertainty of $5.4\\%$ reflects the reproducibility of the coin cell manufacturing. For applications on commercial cells, high accuracies can be expected for estimations of degradation modes, as demonstrated in Section 4.2. The results are discussed individually for each degradation scenario. \n\nTable 6 Scenarios for synthetic OCV data. \n\n\n
ScenarioLLI (pure)LAMNE,liLAMNE,deLAMPE,liLAMPE,deLLI (total)
12%0%23%6%0%18%
II21%4%0%0%7%25%
III9%0%14%0%11%9%
\n\n# 4.3.1. $25\\%$ LLI \n\nThe fitted OCV and estimated degradation mode of cell LLI25 ( $25\\%$ LLI) are shown in Fig. 8 a) and b), respectively. The diagnostic algorithm accurately estimated the extent of LLI within the margin of error (see Fig. 8 b)). The coin cell's OCV was fitted with a RMSE of $6.7~\\mathrm{mV}.$ The $25\\%$ LLI led to the expected increased offset between the positive and negative electrode's OCV, illustrated by a left-shift of the negative electrode's OCV in Fig. 8 a), which directly translates into capacity loss of the cell. The offset and imposed upper cell voltage limit forced the PE to a slightly higher OCV, extracting a small amount of additional lithium at the EoC, offsetting $\\sim1\\%$ of the overall capacity loss. This is indicated by the dash/dotted vertical lines at the cell's EoC and the circular markers on the positive and negative electrode's OCV in Fig. 8 a). \n\n# 4.3.2. $50\\%$ LLI \n\nFig. 8 c) and d) show the fitted OCV and estimated degradation mode of cell LLI50 ( $50\\%$ LLI). $50\\%$ LLI was accurately estimated and other degradation modes were found to be negligible within the margin of error. The RMSE of the OCV fit was $11.9~\\mathrm{mV}$ . The same trends were observed as for cell LLI25, albeit to a greater extent; a large offset between the positive and NE and a noticeably higher PE OCV at EoC, extracting an additional $\\sim2\\%$ of lithium from the positive electrode. The results obtained for cells LLI25 and LLI50 confirm the theory of LLI discussed in Section 3.1. \n\n# 4.3.3. 36% LAMNE,li \n\nFig. 8 e) and f) show the fitted OCV and estimated degradation mode of cell $\\mathsf{L A M}_{\\mathrm{NE,li}}$ $(36\\%\\ \\mathrm{LAM_{NE,li}})$ . $\\mathsf{L A M}_{\\mathrm{NE}}$ was successfully identified as a major degradation mode, although to a slightly smaller extent than expected, exceeding the margin of error by $\\sim4\\%$ . Against expectations, a small amount of $\\mathrm{\\DeltaLAM_{PE}}$ was detected by the diagnostic algorithm, exceeding the margin of error by $\\sim5\\%$ This discrepancy could be explained as an artifact of the coin cell manufacturing technique. The hole punch used to cut the $12~\\mathrm{mm}$ electrode disks slightly crimped the disks around the edge, causing a small rim which was bent away from the interface of electrode and separator. A rim of merely $0.3~\\mathrm{mm}$ around a $12~\\mathrm{mm}$ disk constains an additional $5\\%$ of the electrode's capacity. Due to the lack of contact between the rim around the NE disk (which was cut in a fully lithiated state) and the separator, the lithium contained in the NE could not be fully extracted during the pseudo-OCV discharge of the cell, which would appear as a loss of PE material. The fact that the extent of $\\mathsf{L A M}_{\\mathrm{NE}}$ was underestimated by roughly the same amount as the $\\mathrm{\\DeltaLAM_{PE}}$ was overestimated, namely between $4\\%$ and \n\n![](images/65c9c8876f78fe3960c936b088471af30943955ef43401fdbd2c6faa8ea37f44.jpg) \nFig. 7. Estimation of known amounts of LLI, $\\mathrm{\\DeltaLAM_{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ ; a) and b) Scenario I: $12\\%$ (pure) LLI, $23\\%$ $\\mathrm{LAM}_{\\mathrm{NE,de}},$ $6\\%$ $\\mathsf{L A M}_{\\mathrm{PE,li}},$ c) and d) Scenario II: $21\\%$ (pure) LLI, $4\\%$ $\\mathsf{L A M}_{\\mathrm{NE,li}}$ $7\\%$ $\\mathrm{LAM_{PE,de}}$ , e) and f) Scenario III: $9\\%$ (pure) LLI, $14\\%$ $\\mathsf{L A M}_{\\mathrm{NE,de}}$ , $11\\%$ $\\mathrm{LAM}_{\\mathrm{PE,de}}$ . \n\n$5\\%$ , supports this theory. The lithium contained within the lost active NE material (LLI) was also slightly underestimated - to a similar degree as the $\\mathsf{L A M}_{\\mathrm{NE}}$ , within the margin of error. Overall, the predominant degradation modes were correctly identified - LLI and $\\mathsf{L A M}_{\\mathrm{NE}}$ . In this scenario, all of the lost litihium was contained in the lithiated negative electrode. The diagnostic algorithm correctly identified equal amounts of LLI and $\\mathsf{L A M}_{\\mathrm{NE}}$ , suggesting that the prevalent mechanism was $\\mathsf{L A M}_{\\mathrm{NE,li}}$ . \n\n# 4.3.4. 36% LAMNE,de \n\nThe diagnostic results for cell $\\mathsf{L A M}_{\\mathrm{NE,de}}$ are displayed in Fig. $8\\:\\mathrm{g}^{\\cdot}$ ) and h) - fitted OCV and estimated degradation modes, respectively. Since a $36\\%$ loss of delithiated NE material exceeds the additional NE capacity buffer, lithium plating on the NE was expected in this scenario during charging. The onset of lithium plating occurs once the NE voltage drops below $0{\\:}\\mathsf{V}.$ . The cells used in this work have a NE capacity buffer of $\\sim25\\%$ , which can be inferred from the OCV of the reference cell's negative electrode, shown as broken red line in the plots on the left of Fig. 8. The amount of $\\mathsf{L A M}_{\\mathrm{NE,de}}$ required to consume all of the NE buffer and reach the onset of lithium plating $\\left(\\mathrm{LAM}_{\\mathrm{NE,pl}}\\right)$ can be calculated as follows. Firstly, the normalised capacity of the NE at $E_{N E}^{O C}=0\\mathsf{V}$ , scaled with respect to the normalised cell capacity $(x_{N E,C e l l,p l})$ , is calculated. $x_{N E,C e l l,p l}$ is equivalent to the normalised and scaled capacity of the positive electrode, where $E_{P E}^{O C}=4.2\\mathrm{V}.$ The latter can be calculated using Equation (1) for the PE with $4.2\\mathrm{V}$ plugged in as $E_{P E}^{O C}$ , multiplying the result by the ratio of cell capacity to PE capacity and adding the offset between the normalised cell capacity and the normalised PE capacity, which is equivalent to $x_{P E}$ at $E_{C e l l}^{O C}=4.2\\mathrm{V}$ (as obtained by the OCV model). Now $\\mathsf{L A M}_{\\mathrm{NE,pl}}$ can be calculated using Equation (20). \n\n$$\n\\mathsf{L A M}_{\\mathrm{NE,pl}}=1-\\frac{x_{N E,c e l l,p l}}{x_{N E,C e l l,m a x}}\n$$ \n\nwhere $x_{N E,m a x}=1.25$ is the maximum of the normalised capacity of the negative electrode, scaled with respect to the cell capacity, in the reference cell. Equation (20) yields $\\mathrm{LAM_{NE,pl}}=26.4\\%$ , which means that any loss of delithiated NE material exceeding $26.4\\%$ causes the onset of lithium plating on the NE and leads to further capacity loss due to irreversible deposition of metallic lithium. Although some of the lithium plated during charging may be recovered by stripping during discharging [34], the assumption in this work is that the amount of stripped lithium is negligible and any plated lithium leads to LLI. The amount of LLI resulting from plating can be approximated by calculating the difference between $\\mathsf{L A M}_{\\mathrm{NE,de}}$ and $\\mathsf{L A M}_{\\mathrm{NE,pl}}$ , in this case amounting to $9.6\\%$ LLI. The diagnostic algorithm accurately identified both the amount of $\\mathsf{L A M}_{\\mathrm{NE}}$ and LLI within the margin of error, as shown in Fig. 8 h). The capacity loss attributed to $\\mathsf{L A M}_{\\mathrm{NE,de}}$ is illustrated by the yellow area at the cell's EoC in Fig. 8 g). Note that capacity lost due to lithium trapped inside the PE (yellow area in Fig. $\\mathbf{8\\cdotg}^{\\cdot}$ ) at the cell's EoC), as a result of $\\mathsf{L A M}_{\\mathrm{NE,de}}$ , is not included in the total amount of LLI. The capacity lost as a result of lithium plating is marked by the yellow area at the cell's EoD in Fig. $\\mathbf{8\\cdotg}^{\\cdot}$ ). The small amount of $\\mathrm{LAM_{PE}}$ which was also identified exceeds the margin of error by only $\\sim1\\%$ and is therefore considered negligible. \n\n![](images/fdd79bcf18e1d4ac8c356854843aa75c757248d93941f9f5a4a079f96c77cb09.jpg) \nFig. 8. Results of degradation diagnostics; fitted cell OCVs (left column) and estimated degradation mode (right column). a) and b): cell LLI25, c) and d): cell LLI50, e) and f): cell $\\mathsf{L A M}_{\\mathrm{NE,li}},\\mathsf{g})$ and $\\mathbf{h}$ ): cell $\\mathrm{LAM_{NE,de},i)}$ and j): cell $\\mathsf{L A M}_{\\mathrm{PE,li}},\\mathsf{k}$ ) and l): cell $\\mathrm{LLI}+\\mathrm{LAM}_{\\mathrm{PE,li}}$ . \n\n# 4.3.5. 36% LAMPE,li \n\nFig. 8 i) and j) display the fitted OCV and estimated degradation mode of cell $\\mathsf{L A M}_{\\mathrm{PE,li}}$ $36\\%$ of $\\mathsf{L A M}_{\\mathrm{PE},\\mathrm{li}}\\cdot$ ). Fig. 8 i) illustrates the effect of lost lithiated PE material on the cell's capacity, which is significantly reduced at the EoC. The correct amounts of $\\mathsf{L A M}_{\\mathrm{PE}}$ and LLI contained in the lost electrode material were estimated using the diagnostic algorithm. \n\n# 4.3.6. $25\\%L L I+13\\%L A M_{P E,l i}$ \n\nFig. $\\boldsymbol{8\\mathrm{~k~}}$ ) and l) show the fitted OCV and estimated degradation mode of cell $\\mathrm{LLI}+\\mathrm{LAM}_{\\mathrm{PE,li}}$ ( $25\\%$ of LLI and $13\\%$ of $\\mathsf{L A M}_{\\mathrm{PE,li}},$ . In this case, two degradation modes were combined. The total amount of LLI $(38\\%)$ includes the pure LLI $(25\\%)$ and the lithium lost inside the active PE material $(13\\%)$ . The yellow area at the EoC in Fig. $8\\mathrm{~k~}$ ) represents the capacity loss due to $\\mathsf{L A M}_{\\mathrm{PE,li}}$ and the yellow area at the EoD the capacity loss due to pure LLI. As shown in Fig. 8 l), the total amount of LLI was accurately estimated and the $\\mathbf{LAM_{PE}}$ was slightly overestimated, exceeding the margin of error by $1.6\\%.$ A small amount of $\\mathsf{L A M}_{\\mathrm{NE}}$ was detected, exceeding the margin of error by $\\sim1\\%.$ . This could be due to the same effect as described for cell $\\mathsf{L A M}_{\\mathrm{NE,li}}$ . Overall, the predominant degradation modes were successfully identified, even in the presence of two independent degradation modes. \n\n# 5. Conclusions \n\nThis work has built on the theory of degradation modes in Li-ion cells as a manifestation of a host of different physical and chemical mechanisms. The general theory behind the degradation modes LLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ has been expanded to account for the effects of imposed upper and lower cell voltage limits on the different degradation modes. This expanded theory was used to create a diagnostic algorithm to identify and quantify LLI, $\\mathrm{\\DeltaLAM_{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ using only pseudo-OCV measurements of full cells. The diagnostic algorithm was validated using test cells with known amounts of LLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ . The results led to three key findings: \n\nExperimental proof of the effects of LLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ on the cell's OCV. \nA diagnostic algorithm has been demonstrated to successfully identify and quantify LLI, LAMPE and $\\mathsf{L A M}_{\\mathrm{NE}}$ . \n\u0001 The diagnostic algorithm can identify the onset of potentially dangerous processes such as excessively high voltages on the PE and lithium plating on the NE. \n\nExperimental evidence has been presented to prove, for the first time, that the OCV of Li-ion cells can be used to provide accurate estimates of LLI, $\\mathsf{L A M}_{\\mathrm{PE}}$ and $\\mathsf{L A M}_{\\mathrm{NE}}$ . The diagnostic algorithm was evaluated for six different scenarios of degradation modes. Once the OCV model has been parameterized, the diagnostic algorithm requires only pseudo-OCV measurements. Since the algorithm uses the pseudo-OCV measurements as a direct input, rather than the derivative of voltage or capacity, it is less sensitive to noise compared to other techniques proposed in the literature. These attributes, combined with the low computational complexity of the diagnostic algorithm, make it ideal for BMS applications in order to keep track of the cells' SoH and to maintain safe operation. \n\nTheoretically, the presented diagnostic technique can be applied to any Li-ion cell chemistry. This possibility will be investigated in future work. Further work also includes the identification and quantification of degradation modes in commercial Li-ion cells aged in a variety of use cases and throughout their service life. This should enable projections of the end-of-life for commercial Li-ion cells. \n\nFinancial support of EPSRC UK (EP/K504518/1) and Jaguar Land Rover is gratefully acknowledged. \n\n# Acknowledgements \n\n# References \n\n[1] S.S. Choi, H.S. Lim, Factors that affect cycle-life and possible degradation mechanisms of a Li-ion cell based on LiCoO2, J. Power Sources 111 (1) (2002) 130e136, http://dx.doi.org/10.1016/S0378-7753(02)00305-1. \n[2] M. Broussely, P. Biensan, F. Bonhomme, P. Blanchard, S. Herreyre, K. Nechev, R. Staniewicz, Main aging mechanisms in Li ion batteries, J. Power Sources 146 (1e2) (2005) 90e96, http://dx.doi.org/10.1016/j.jpowsour.2005.03.172. \n[3] K. Jalkanen, J. Karppinen, L. Skogstro€m, T. Laurila, M. Nisula, K. Vuorilehto, Cycle aging of commercial NMC/graphite pouch cells at different temperatures, Appl. Energy 154 (2015) 160e172, http://dx.doi.org/10.1016/j.apenergy.2015.04.110. URL, http://linkinghub.elsevier.com/retrieve/pii/ S0306261915005735. \n[4] I. Bloom, B. Cole, J. Sohn, S. Jones, E. Polzin, V. Battaglia, G. Henriksen, C. Motloch, R. Richardson, T. Unkelhaeuser, D. Ingersoll, H. Case, An accelerated calendar and cycle life study of Li-ion cells, J. Power Sources 101 (2) (2001) 238e247, http://dx.doi.org/10.1016/S0378-7753(01)00783-2. URL, http://linkinghub.elsevier.com/retrieve/pii/S0378775301007832. [5] J. Vetter, P. Nova\u0002k, M.R. Wagner, C. Veit, K.-C. M€oller, J.O. Besenhard, M. Winter, M. Wohlfahrt-Mehrens, C. Vogler, A. Hammouche, Ageing mechanisms in lithium-ion batteries, J. Power Sources 147 (1e2) (2005) 269e281, http://dx.doi.org/10.1016/j.jpowsour.2005.01.006. [6] D. Aurbach, B. Markovsky, I. Weissman, E. Levi, Y. Ein-Eli, On the correlation between surface chemistry and performance of graphite negative electrodes for Li ion batteries, Electrochim. Acta 45 (1e2) (1999) 67e86, http:// dx.doi.org/10.1016/S0013-4686(99)00194-2. URL, http://linkinghub.elsevier. com/retrieve/pii/S0013468699001942. \n[7] V. Agubra, J. Fergus, Lithium ion battery anode aging mechanisms, Materials 6 (4) (2013) 1310e1325, http://dx.doi.org/10.3390/ma6041310. \n[8] S.-K. Jung, H. Gwon, J. Hong, K.-Y. Park, D.-H. Seo, H. Kim, J. Hyun, W. Yang, K. Kang, Understanding the degradation mechanisms of LiNi0.5Co0.2Mn0.3O2 cathode material in lithium ion batteries, Adv. Energy Mater. (2013), http:// dx.doi.org/10.1002/aenm.201300787 $\\mathtt{n/a\\mathrm{-}\\boldsymbol{n/\\mathsf{a}}}$ . \n[9] P. Nov\u0002ak, F. Joho, M. Lanz, B. Rykart, J.-C. Panitz, D. Alliata, R. Ko€tz, O. Haas, The complex electrochemistry of graphite electrodes in lithium-ion batteries, J. Power Sources 97e98 (2001) 39e46, http://dx.doi.org/10.1016/S0378- 7753(01)00586-9. \n[10] P. Verma, P. Maire, P. Nova\u0002k, A review of the features and analyses of the solid electrolyte interphase in Li-ion batteries, Electrochim. Acta 55 (22) (2010) 6332e6341, http://dx.doi.org/10.1016/j.electacta.2010.05.072. \n[11] M.B. Pinson, M.Z. Bazant, Theory of SEI formation in rechargeable batteries: capacity fade, accelerated aging and lifetime prediction, J. Electrochem. Soc. 160 (2) (2012) A243eA250, http://dx.doi.org/10.1149/2.044302jes. \n[12] E. Prada, D. Di Domenico, Y. Creff, J. Bernard, V. Sauvant-Moynot, F. Huet, A simplified electrochemical and thermal aging model of LiFePO4-graphite Liion batteries: power and capacity fade simulations, J. Electrochem. Soc. 160 (4) (2013) A616eA628, http://dx.doi.org/10.1149/2.053304jes. \n[13] J. Christensen, J. Newman, Stress Generation and Fracture in Lithium Insertion Materials, 2006, pp. 293e319, http://dx.doi.org/10.1007/s10008-006-0095-1. \n[14] R. Deshpande, M. Verbrugge, Y.-T. Cheng, J. Wang, P. Liu, Battery cycle life prediction with coupled chemical degradation and fatigue mechanics, J. Electrochem. Soc. 159 (10) (2012) A1730eA1738, http://dx.doi.org/10.1149/ 2.049210jes. \n[15] M. Safari, M. Morcrette, A. Teyssot, C. Delacourt, Multimodal physics-based aging model for life prediction of Li-Ion batteries, J. Electrochem. Soc. 156 (3) (2009) A145, http://dx.doi.org/10.1149/1.3043429. \n[16] S.J. Harris, P. Lu, Effects of inhomogeneities - nanoscale to mesoscale - on the durability of Li-Ion batteries, J. Phys. Chem. C 117 (2013) 6481e6492. \n[17] T.C. Bach, S.F. Schuster, E. Fleder, J. Müller, M.J. Brand, H. Lorrmann, A. Jossen, G. Sextl, Nonlinear aging of cylindrical lithium-ion cells linked to heterogeneous compression, J. Energy Storage 5 (2016) 212e223, http://dx.doi.org/ 10.1016/j.est.2016.01.003. \n[18] V. Pop, H.J. Bergveld, P.P.L. Regtien, J.H.G. Op het Veld, D. Danilov, P.H.L. Notten, Battery aging and its Influence on the electromotive force, J. Electrochem. Soc. 154 (8) (2007) A744, http://dx.doi.org/10.1149/1.2742296. \n[19] M. Dubarry, C. Truchot, B.Y. Liaw, Synthesize battery degradation modes via a diagnostic and prognostic model, J. Power Sources 219 (2012) 204e216, http://dx.doi.org/10.1016/j.jpowsour.2012.07.016. URL, http://linkinghub. elsevier.com/retrieve/pii/S0378775312011330. \n[20] K. Striebel, J. Shim, A. Sierra, H. Yang, X. Song, R. Kostecki, K. McCarthy, The development of low cost lifepo 4-based high power lithium-ion batteries, J. Power Sources 146 (1) (2005) 33e38. \n[21] E. Sarasketa-Zabala, F. Aguesse, I. Villarreal, L. Rodriguez-Martinez, C. Lo\u0002pez, P. Kubiak, Understanding lithium inventory loss and sudden performance fade in cylindrical cells during cycling with deep-discharge steps, J. Phys. Chem. C 119 (2) (2014) 896e906. \n[22] G.L. Plett, Extended Kalman filtering for battery management systems of LiPBbased HEV battery packs. Part 3. State and parameter estimation, J. Power Sources 134 (2) (2004) 277e292, http://dx.doi.org/10.1016/j.jpowsour.2004.02.033. URL, http://linkinghub.elsevier.com/retrieve/pii/ S0378775304003611. \n[23] J. Remmlinger, M. Buchholz, M. Meiler, P. Bernreuter, K. Dietmayer, State-ofhealth monitoring of lithium-ion batteries in electric vehicles by on-board internal resistance estimation, J. Power Sources 196 (12) (2011) 5357e5363, http://dx.doi.org/10.1016/j.jpowsour.2010.08.035. \n[24] M.A. Roscher, O.S. Bohlen, D.U. Sauer, Reliable state estimation of multicell Lithium-ion battery systems, IEEE Trans. Energy Convers. 26 (3) (2011) 737e743, http://dx.doi.org/10.1109/TEC.2011.2155657. \n[25] H.M. Dahn, A.J. Smith, J.C. Burns, D.A. Stevens, J.R. Dahn, User-friendly differential voltage analysis freeware for the analysis of degradation mechanisms in Li-Ion batteries, J. Electrochem. Soc. 159 (9) (2012) A1405eA1409, http://dx.doi.org/10.1149/2.013209jes. \n[26] A. Marongiu, N. Nlandi, Y. Rong, D.U. Sauer, On-board capacity estimation of lithium iron phosphate batteries by means of half-cell curves, J. Power Sources 324 (2016) 158e169, http://dx.doi.org/10.1016/j.jpowsour.2016.05.041. URL, http://www.sciencedirect.com/science/article/pii/S0378775316305778. \n[27] M. Dubarry, V. Svoboda, R. Hwu, B. Yann Liaw, Incremental capacity analysis and close-to-equilibrium OCV measurements to quantify capacity fade in commercial rechargeable lithium batteries, Electrochem. Solid-State Lett. 9 (10) (2006) A454eA457, http://dx.doi.org/10.1149/1.2221767. URL, http://esl. \n[28] I. Bloom, A.N. Jansen, D.P. Abraham, J. Knuth, S.A. Jones, V.S. Battaglia, G.L. Henriksen, Differential voltage analyses of high-power, lithium-ion cells 1. Technique and application, J. Power Sources 139 (1e2) (2005) 295e303, http://dx.doi.org/10.1016/j.jpowsour.2004.07.021. \n[29] X. Han, M. Ouyang, L. Lu, J. Li, Y. Zheng, Z. Li, A comparative study of commercial lithium ion battery cycle life in electrical vehicle: aging mechanism identification, J. Power Sources 251 (2014) 38e54, http://dx.doi.org/10.1016/ j.jpowsour.2013.11.029. URL, http://linkinghub.elsevier.com/retrieve/pii/ S0378775313018569. \n[30] T. Ohsaki, T. Kishi, T. Kuboki, N. Takami, N. Shimura, Y. Sato, M. Sekino, A. Satoh, Overcharge reaction of lithium-ion batteries, J. Power Sources 146 (1-2) (2005) 97e100, http://dx.doi.org/10.1016/j.jpowsour.2005.03.105. \n[31] F. Orsini, A. Du Pasquier, B. Beaudoin, J. Tarascon, M. Trentin, N. Langenhuizen, E. De Beer, P. Notten, In situ Scanning Electron Microscopy (SEM) observation of interfaces within plastic lithium batteries, J. Power Sources 76 (1998) 19e29, http://dx.doi.org/10.1016/S0378-7753(98)00128-1. \n[32] S. Santhanagopalan, P. Ramadass, J.Z. Zhang, Analysis of internal short-circuit in a lithium ion cell, J. Power Sources 194 (1) (2009) 550e557, http:// dx.doi.org/10.1016/j.jpowsour.2009.05.002. URL, http://linkinghub.elsevier. com/retrieve/pii/S037877530900843X. \n[33] C.R. Birkl, E. McTurk, M.R. Roberts, P.G. Bruce, D.A. Howey, A parametric open circuit voltage model for lithium ion batteries, J. Electrochem. Soc. 162 (12) (2015) A2271eA2280, http://dx.doi.org/10.1149/2.0331512jes. URL, http:// jes.ecsdl.org/content/162/12/A2271.abstract. \n[34] M. Petzl, M.A. Danzer, Nondestructive detection, characterization, and quantification of lithium plating in commercial lithium-ion batteries, J. Power Sources 254 (2014) 80e87, http://dx.doi.org/10.1016/j.jpowsour.2013.12.060. " + }, + { + "id": "10.1021_acsnullo.7b03186", + "DOI": "10.1021/acsnullo.7b03186", + "DOI Link": "http://dx.doi.org/10.1021/acsnullo.7b03186", + "Relative Dir Path": "mds/10.1021_acsnullo.7b03186", + "Article Title": "Janus Monolayer Transition-Metal Dichalcogenides", + "Authors": "Zhang, J; Jia, S; Kholmanov, I; Dong, L; Er, DQ; Chen, WB; Guo, H; Jin, ZH; Shenoy, VB; Shi, L; Lou, J", + "Source Title": "ACS nullO", + "Abstract": "The crystal configuration of sandwiched S-Mo-Se structure (Janus SMoSe) at the monolayer limit has been synthesized and carefully characterized in this work. By controlled sulfurization of monolayer MoSe2, the top layer of selenium atoms is substituted by sulfur atoms, while the bottom selenium layer remains intact. The structure of this material is systematically investigated by Raman, photoluminescence, transmission electron microscopy, and X-ray photoelectron spectroscopy and confirmed by time-of-flight secondary ion mass spectrometry. Density functional theory (DFT) calculations are performed to better understand the Raman vibration modes and electronic structures of the Janus SMoSe monolayer, which are found to correlate well with corresponding experimental results. Finally, high basal plane hydrogen evolution reaction activity is discovered for the Janus monolayer, and DFT calculation implies that the activity originates from the synergistic effect of the intrinsic defects and structural strain inherent in the Janus structure.", + "Times Cited, WoS Core": 1206, + "Times Cited, All Databases": 1260, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000408520900069", + "Markdown": "# Janus Monolayer Transition-Metal Dichalcogenides \n\nJing Zhang,†,∥ Shuai Jia,†,∥ Iskandar Kholmanov,‡ Liang Dong,§ Dequan Er,§ Weibing Chen,† Hua Guo, Zehua Jin,† Vivek B. Shenoy, Li Shi,‡ and Jun Lou\\*,† \n\n†Department of Materials Science and Nanoengineering, Rice University, Houston, Texas 77005, United States ‡Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States §Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States \n\nSupporting Information \n\nABSTRACT: The crystal configuration of sandwiched $\\mathbf{s-}$ Mo−Se structure (Janus SMoSe) at the monolayer limit has been synthesized and carefully characterized in this work. By controlled sulfurization of monolayer $\\mathbf{MoSe}_{2},$ the top layer of selenium atoms is substituted by sulfur atoms, while the bottom selenium layer remains intact. The structure of this material is systematically investigated by Raman, photoluminescence, transmission electron microscopy, and X-ray photoelectron spectroscopy and confirmed by time-of-flight secondary ion mass spectrometry. Density functional theory (DFT) calculations are performed to better understand the Raman vibration modes and \n\n![](images/c42fbe712d339089c97247523f5ddb88465c792d41f68fce79f84c00ad25d212.jpg) \n\nelectronic structures of the Janus SMoSe monolayer, which are found to correlate well with corresponding experimental results. Finally, high basal plane hydrogen evolution reaction activity is discovered for the Janus monolayer, and DFT calculation implies that the activity originates from the synergistic effect of the intrinsic defects and structural strain inherent in the Janus structure. \n\nKEYWORDS: Janus SMoSe, sulfurization, Raman, TOF-SIMS, HER \n\nS i(n2cDe)thmeadtiesrciaolvserhyavoef gbreaepnheatnteraicnt $2004,^{1}$ rtewaosi-ndigmaettnesniotinoanl (2D) materials have been attracting increasing attention due to the many interesting properties originating from the bulk to monolayer transition. Among the 2D family, transition-metal dichalcogenides (TMDs) have been most widely studied; $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}\\ensuremath{\\mathbf{S}}_{2}$ as the representative TMD material, its electrical,2 optical3 as well as other physical properties4,5 are well understood. By controlling the stoichiometric ratio of chemical vapor deposition grown ${\\mathrm{MoS}}_{x}{\\mathrm{Se}}_{2-x}{}^{6}{\\mathrm{WS}}_{x}{\\mathrm{Se}}_{2-x}{}^{7}$ and $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathbf{o}}_{x}\\ensuremath{\\mathbf{W}}_{1-x}\\ensuremath{\\mathbf{S}}_{2}^{\\phantom{\\dagger}}$ alloys, the optical and electrical properties of the monolayers can be tuned. Various combinations of out-of-plane TMD heterojunctions have been prepared by transfer methods. $\\mathrm{MoS}_{2}/\\mathrm{WS}_{2},^{\\mathrm{g}}$ $\\mathbf{MoS}_{2}/\\mathbf{MoSe}_{2},$ 0 $\\hat{\\bf M}\\mathrm{o}\\hat{\\bf S}_{2}/\\mathrm{W}{\\bf S}\\mathrm{e}_{2},^{\\mathrm{~\\tiny~11~}}$ and $\\mathbf{MoSe}_{2}/$ $\\mathrm{WSe}_{2}^{12}$ out-of-plane and in-plane heterojunctions have also been grown by the CVD method. The heterojunctions, especially the in-plane ones, exhibit interesting physical properties due to the presence of an atomically sharp interface.13 In this work we demonstrate a type of TMD structure possessing an unconventional asymmetry sandwich construction that is distinctively different from both types of heterojunctions. As shown in Figure 1b and Figure $^{2\\mathrm{a},}$ the socalled “Janus” SMoSe consists of three layers of atoms, namely, sulfur, molybdenum, and selenium from the top to the bottom. \n\nUnlike the randomly alloyed SMoSe, the Janus SMoSe is highly asymmetric along the $c$ -axis direction. The polarized chemical construction potentially derives an intrinsic electric field inside the crystal and physical properties such as the Zeeman-type spin splitting.1 4 \n\nWe have managed to reproducibly obtain monolayer Janus SMoSe flakes by well-controlled sulfurization of monolayer $\\mathbf{MoSe}_{2}$ . The monolayer $\\mathbf{MoSe}_{2}$ flakes were first grown by the CVD method.15 Briefly, $\\mathbf{MoO}_{3}$ powder as the Mo source was placed in a porcelain boat at the center of the heating zone. Sulfur powder as the S source was placed upstream of the heating zone. Monolayer $\\mathbf{MoSe}_{2}$ flakes started to crystallize and grow at around $800^{\\circ}\\mathrm{C}$ on a $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate facing the $\\mathbf{MoO}_{3}$ powder under the protection of ultrahigh purity argon. The asgrown monolayer $\\mathbf{MoSe}_{2}$ exhibits typical Raman and high photoluminescence $\\mathrm{(PL)}^{16,17}$ signals as shown in Figure 1c and d. The sulfurization of the top layer Se was realized by a controlled substitutional reaction with vaporized sulfur in a typical CVD setup (Figure 1a). Briefly, the monolayer $\\mathbf{MoSe}_{2}$ sample was placed in the center of the heating zone and heated to $800~^{\\circ}\\mathrm{C}.$ . Sulfur powder was heated to $150~^{\\circ}\\mathrm{C}$ by a heating belt. The sulfur gas was carried to the center of the heating zone by ultrahigh-purity argon. The sulfurization process was kept for $30~\\mathrm{min}$ before the furnace was naturally cooled down to room temperature. \n\n![](images/176282bc9fd89e88b58f15c288617943aa548b1900b95a3fe08d6e460b91a9e0.jpg) \nFigure 1. Reactions under different growth temperature. (a) Schematic illustration of the reaction setup. (b) Proposed reaction mechanism for the sulfurization of monolayer $\\mathbf{MoSe}_{2}$ on a $\\mathbf{SiO}_{2}/\\mathbf{Si}$ substrate at different temperatures. Between the monolayer and the substrate is the van der Waal interaction. $(\\mathbf{c},\\mathbf{d})$ Raman and PL (under ${\\pmb532}\\mathbf{nm}$ diode laser excitation) spectra of $\\mathbf{MoSe}_{2},$ Janus SMoSe, and $\\mathbf{MoS}_{2}$ corresponding to the diagram in (b). \n\n![](images/c2636ed0306c7b5d5f45f0b70c4f68774e85ef67b59d8dfaccea4b45a337d6ea.jpg) \nFigure 2. Monolayer Janus SMoSe characterizations. (a) Off-angle top view and side view of an eight-unit-cell Janus SMoSe monolayer. The purple, yellow, and green spheres represent molybdenum, sulfur, and selenium atoms, respectively. (b) Optical image of a Janus SMoSe triangle. The purple and the central island with high contrast is the monolayer and bulk crystal region, respectively. (c, d) Raman and PL peak intensity mappings of the Janus SMoSe triangle in (b). The mapping shows uniform distribution of the identical Raman peak at $\\bar{2}87~\\mathrm{cm}^{-1}$ and PL peak at $\\mathbf{1.68\\eV}.$ . (e) AFM topography image of the Janus SMoSe triangle. The profile shows that the thickness of the flake is $\\mathbf{<1\\nm}$ . (f) HRTEM image of the Janus SMoSe lattice. The atom arrangement indicates the 2H structure of the monolayer. $\\mathbf{\\sigma}(\\mathbf{g})$ Corresponding selected area electron diffraction pattern of the monolayer. $({\\bf h}{\\bf-j})$ XPS spectra of the Mo 3d, Se 3d, and $\\mathbf{s}_{2\\mathbf{p}}$ core level peaks for the Janus SMoSe monolayer. \n\nAs shown in Figure 1b, the top and bottom layer Se atoms of monolayer $\\mathbf{MoSe}_{2}$ on $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate are located under different chemical environments, namely, under atmosphere pressure and in the van der Waals gap, respectively. While the gaseous sulfur molecules (mainly ${\\cal S}_{8},$ possibly pyrolyse to smaller molecules) approach, the top layer Se atoms are in direct contact with sulfur and could be quickly substituted once the thermal driving force overcomes the thermodynamic barrier. However, in order to substitute the bottom layer Se atoms, the gaseous sulfur molecules have to diffuse into the van der Waals gap first. Once a selenium atom is substituted, it has to diffuse out to facilitate further sulfurization. Assuming the sulfur partial pressure is identical, the diffusion process becomes the rate-limiting step, and the temperature directly determines the reaction rate. We have shown in Figure 1b that below 750 $^{\\circ}\\mathrm{C}$ and over $850~^{\\circ}\\mathrm{C}$ the Raman peaks are similar to $\\mathbf{MoSe}_{2}$ and $\\mathrm{Mo}S_{2},$ respectively, indicating that sulfur does not substitute selenium below a certain temperature and is able to diffuse into the van der Waals gap once the temperature is high enough. Similar observation has been made on the sulfurization of monolayer $\\mathbf{WSe}_{2}$ as depicted in Figure S2. The tendency to form the Janus structure has been shown in similar sulfurization processes but under high-vacuum conditions.7,18,19 The high vacuum potentially lowers the diffusion energy barrier of sulfur and facilitates the sulfurization process, resulting in a reduced temperature required for complete sulfurization of the selenides $({\\sim}700~^{\\circ}\\mathrm{C})$ . We attribute our reproducible synthesis of the Janus SMoSe to the fact that atmosphere pressure is maintained during the reaction. The atmospheric pressure significantly enlarges the stable temperature window for the top layer atom substitution reaction. The sulfurization time, on the other hand, did not lead to the selenium substitution in the bottom layer, implying that only temperature and pressure played crucial roles in this selective sulfurization process. \n\nThe Janus SMoSe triangular flake looks identical to $\\mathbf{MoSe}_{2}$ when observed under the optical microscope (Figure 2b). The morphology of the flake was checked by atomic force microscopy (AFM), and the profile shows the flake thickness was $<1\\ \\mathrm{nm}$ (Figure 2e), implying that after sulfurization it is still in the monolayer configuration. To interpret the trilayer-atom structure, we first examined the Raman spectra of the Janus SMoSe flakes. As shown in Figure 1c, the spectrum for the asgrown $\\mathbf{MoSe}_{2}$ has the typical $\\mathbf{A}_{\\mathrm{lg}}$ mode $(240~\\mathrm{cm}^{-1})$ and $\\mathbf{E}_{2\\mathrm{g}}^{1}$ mode $\\left(287~\\mathrm{cm}^{-1}\\right),$ ) peaks.17,20 After the sulfurization reaction, several major changes appeared in the spectrum. First of all, the $\\mathbf{A}_{\\mathrm{lg}}$ peak completely vanished, indicating the out-of-plane vibration of the symmetric $_{S e-M o-S e}$ structure has been disrupted by the sulfur substitution to selenium. Second, a new peak with strong intensity appeared at $290~\\mathrm{{\\cm}^{-1}}$ , not overlapping with the $\\mathbf{MoSe}_{2}\\dot{\\mathbf{E}}_{2\\mathbf{g}}^{1}$ peak $\\left(287~\\mathrm{cm}^{-1}\\right),$ ). We suspect the peak accounts for the out-of-plane $S{\\mathrm{-}}\\mathrm{Mo}{\\mathrm{-}}\\mathrm{Se}$ vibration mode. At the same time, another distinct peak that we assign for the in-plane $_{S-\\mathrm{Mo-Se}}$ vibration mode at $350.8~\\mathrm{{\\cm}^{-1}}$ appeared. In the end, compared to the $\\ensuremath{\\mathrm{MoS}}_{x}\\ensuremath{\\mathrm{Se}}_{2-x}$ alloy spectrum, which consists of the $\\mathbf{MoS}_{2}$ and $\\mathbf{MoSe}_{2}$ major Raman peaks as long as $0~SMoSe~\\approx~MoSe_{2}~>~M o S_{2},}$ in general agreement with the experimental results of $\\mathrm{SeMoS}>\\mathrm{SMoSe}>$ $\\mathbf{MoSe}_{2}>\\mathbf{MoS}_{2}$ . The only exception is the relative efficiencies of SMoSe and $\\mathbf{MoSe}_{2}$ . Theoretical results show that they have similar HER efficiencies, while experimentally SMoSe has a better efficiency. The discrepancy may arise from the densities of single S- and Se-vacancies, which affect the electronic and catalytic properties of TMD monolayers. In the supercells we simulate, a universal vacancy density of $6.25\\%$ in an S or Se atomic layer is used, regardless of the materials. However, under experimental conditions, the single S- and Se-vacancies may vary in $\\mathrm{MoS}_{2},$ SMoSe (SeMoS), and $\\mathbf{MoSe}_{2}$ . Therefore, a further experimental investigation on the defect microstructure of the TMD samples is needed to address this discrepancy. \n\n![](images/67d3bd22b985bb5c238a1aefac398e68ec222f3ea9825a57efc52f8e1b3a568b.jpg) \nFigure 5. Experimental and computational evaluation on the HER activity of the Janus monolayer. (a) HER polarization curves of monolayer $\\mathbf{MoS}_{2}$ , $\\mathbf{MoSe}_{2},$ SMoSe, and SeMoS. (b) (Left) DFT calculated hydrogen adsorption free energy $\\Delta G_{\\mathrm{H}}$ for $\\mathbf{MoS}_{2}$ and SMoSe (which have a single S-vacancy) and for $\\mathbf{MoSe}_{2}$ and SeMoS (which have a single Se-vacancy). The insets show a side view of the truncated supercell structure where the $\\mathbf{H}$ atom is absorbed in the vacancies. (Right) Top view of the $4\\times4\\times1$ supercell with the location of the single S- (or Se-) vacancy circled in red. \n\nIn conclusion, a 2D monolayer with an asymmetric structure, Janus SMoSe, has been synthesized by a controlled sulfurization process. The $_{S-\\mathrm{Mo-Se}}$ trilayer atomic structure exhibits unique Raman vibration peaks that can be distinguished from pure $\\mathbf{MoS}_{2}$ and $\\mathbf{MoSe}_{2}$ and randomly alloyed $\\mathrm{MoS}_{x}\\mathrm{Se}_{2-x}$ . The experimental characteristic Raman peaks agree well with predictions of DFT simulations. TOF-SIMS analysis further confirms that the Janus SMoSe is composed of the $_{S-\\mathrm{Mo-Se}}$ trilayer structure. Both Raman mapping and TOF-SIMS element mapping/XPS profile analysis indicate that the monolayer is uniformly sulfurized and the asymmetric structure distributes all over the Janus monolayer. DFT simulation was used to predict the bandgap of the Janus SMoSe, and the value is consistent with the experimental results derived from the PL spectroscopy. It is also suggested that an intrinsic electric field potentially exists perpendicular to the inplanar direction. High basal plane HER catalytic activity is discovered for the Janus structures, and DFT calculation implies that the activity may originate from the synergistic effects of the intrinsic defects and structural strain in the Janus structure. \n\n# MATERIALS AND METHODS \n\nExperimental Details. All the chemicals are purchased from Sigma-Aldrich and used as received without further purification. The CVD procedures are carried out using a MTI tube furnace. The Raman and PL spectra are collected with Renishaw inVia confocal Raman microscope. The TEM images are taken with JEOL 2100F microscope. The XPS spectra are collected with PHI Quantera instrument. The devices are fabricated with FEI Quanta 400 SEM. The TOF-SIMS data are collected with a IONTOF TOF.SIMS.5 instrument. \n\nThe electronic properties of such asymmetric 2D monolayer is investigated by measuring the field-effect transistor (FET) based on it. FET devices on Janus SMoSe monolayers were fabricated using an ebeam lithography method. The fabricated device (inset in Figure S6) has a channel length of $6\\mu\\mathrm{m}$ and width of $3.6~\\mu\\mathrm{m}$ . At positive backgate voltage $(V_{\\mathrm{g}})$ region, the output characteristics (increased drain current $\\left(\\bar{I_{\\mathrm{d}}}\\right)$ vs $\\breve{V}_{\\mathrm{g}})$ indicates the $\\mathbf{n}$ -type behavior of the Janus SMoSe monolayer. The mobility of the device is calculated (see details in Supporting Information) to be $6.2\\times10^{-2}\\ \\mathrm{cm}^{-2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-\\mathrm{i}}$ , and the on/ off ratio is $\\mathrm{\\bar{10}}^{2}$ . The low mobility of the Janus SMoSe can potentially be attributed to the heat treatment accompanying the sulfurization reaction. During the process, the residual oxygen in the CVD environment often lead to the creation of vacancies on the monolayer structure24,25 and reduction in the carrier mobility.26 \n\nThe basal plane HER polarization curves of the monolayer TMDs were collected using a modified three-electrode method (Figure S9). \n\nThe TMD monolayers were electrically connected by depositing gold electrodes on them. To exclude the edge sites contribution of the monolayers to the HER measurements, a layer of PMMA was coated onto a typical HER device and patterned with an e-beam lithography method so that only a basal plane region with controlled area was exposed for the HER measurement. \n\nComputational Details. The DFT calculations are performed using the Vienna ab initio simulation package (VASP) code.27 Projector augmented wave pseudopotentials28 are used with a cutoff energy of $520~\\mathrm{{\\eV}}$ for plane-wave expansions. The exchange− correlation functional was treated within the Perdew−Burke− Ernzerhof (PBE) generalized gradient approximations (GGA).29 The unit cell structures of monolayer SMoSe, $\\ensuremath{\\mathbf{MoS}}_{\\upsilon}$ and $\\mathrm{MoSe}_{2}$ are relaxed with a $\\Gamma$ -centered $k$ -point mesh of $18\\times18\\times1$ in the first Brillouin zone, with the total energy converged to below $10^{-8}~\\mathrm{eV}.$ . The in-plane lattice parameters of $\\mathrm{MoSe}_{2},$ SMoSe, and $\\ensuremath{\\mathbf{MoS}}_{2}$ monolayers are calculated to be 3.322, 3.252, and $3.185\\mathrm{~\\AA~},$ respectively. The atomic positions of the unit cells are optimized until all components of the forces on each atom are reduced to values below $\\begin{array}{r}{\\bar{0}.001\\ \\mathrm{~eV}/\\bar{\\mathrm{A}}.}\\end{array}$ A vacuum region of $16\\mathrm{~\\AA~}$ thickness was used to prevent interactions between the adjacent periodic images of the monolayer. To simulate the Raman activity of these materials, their dielectric susceptibility tensor and zone-centered (Γ point) vibrational frequencies are computed with the density functional perturbation theory as implanted in VASP. Raman intensities are estimated by the derivative of the dielectric susceptibility tensor with respect to the normal mode,30 using the vasp_raman.py package.31 \n\nTo correctly address the chemisorption energies of $\\mathrm{~H~}$ atoms on the surfaces of SMoSe, we use the Bayesian error estimation exchange− correlation functional with van der Waals interactions (BEEF-vdW)32 as implemented in VASP with spin-polarized calculations. Other sets of parameters remain the same as in previous calculations for the structural relaxations. The in-plane lattice parameters of $\\mathrm{MoSe}_{2},$ SMoSe, and $\\ensuremath{\\mathbf{MoS}}_{2}$ monolayers obtained by the BEEF-vdW functional are 3.335, 3.263, and $3.18\\bar{5}\\bar{\\mathrm{A}},$ respectively. The $4\\times4\\times1$ supercells of these materials (see right panel of Figure 5) are constructed with a single S- or Se-vacancy to investigate their effect on the HER catalytic efficiency. Such vacancies are most energetically favored among all types of structural defects in TMDs and are hence mostly commonly observed in CVD-grown TMD sample.26 Our calculations show that the single S- and Se-vacancies are the most energetically stable H absorption site on the surfaces of the supercells (see insets of the left panel of Figure 5). The vibrational frequencies of the absorbed H atom are calculated using the finite displacement method. The calculated $\\Delta E_{\\mathrm{{ZPE}}}$ for $\\mathrm{~H~}$ in a single S- and Se-vacancies in $\\mathrm{MoSe}_{2},$ SMoSe, and $\\mathbf{MoS}_{2}$ are 5.6 and $-0.8\\ \\mathrm{meV}$ , respectively. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.7b03186. \n\nDescriptor of the HER efficiency by DFT calculation; HER device fabrication and measurement details; survey XPS of Janus SMoSe; Raman and PL spectra of $\\mathbf{WSe}_{2}$ sulfurization; Raman spectra of $\\mathbf{MoSe}_{2}$ with increasing layer numbers with and without sulfurization; Raman vibration modes of SMoSe; charge density distribution of SMoSe; TOF-SIMS of $\\mathrm{MoSe}_{2},$ ; XPS profile analysis of the SMoSe; FET device performance of SMoSe; images of a typical HER measurement device; PL of SMoSe before and after annealing; preparation of SeMoS configuration from SMoSe; experimental and theoretical Raman peaks of $\\mathrm{MoSe}_{2},$ SMoSe, and $\\mathbf{MoS}_{2}$ monolayers (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author $^{*}\\mathrm{E}$ -mail: jlou@rice.edu. \n\nORCID Jing Zhang: 0000-0002-4706-8630 Li Shi: 0000-0002-5401-6839 \n\n# Author Contributions \n\n∥These authors contributed equally. \n\nNotes The authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nJ.L. gratefully acknowledges the support from the AFOSR grant FA9550-14-1-0268, the Welch Foundation grant C-1716, and the Army Research Office grant W911NF-16-1-0447. L.S. acknowledges the support from the NSF award EFRI-1433467. The theoretical work is supported primarily by contract W911NF-16-1-0447 from the Army Research Office (V.B.S.) and also by grants EFMA-542879 (D.E) and CMMI-1363203 (L.D.) from the U.S. National Science Foundation. We appreciate the great help from Dr. B. Chen with the XPS measurements and analysis. \n\n# REFERENCES \n\n(1) Novoselov, K. S.; Geim, A. ${\\mathrm{K}}.{\\mathrm{}}$ Morozov, S. V.; Jiang, D.; Zhang, Y.; Dubonos, S. V.; Grigorieva, I. V.; Firsov, A. A. Electric Field Effect in Atomically Thin Carbon Films. Science 2004, 306, 666−669. (2) Radisavljevic, B.; Radenovic, A.; Brivio, J.; Giacometti, V.; Kis, A. Single-Layer $\\mathbf{MoS}_{2}$ Transistors. Nat. Nanotechnol. 2011, 6, 147−150. (3) Splendiani, A.; Sun, L.; Zhang, Y. B.; Li, T. S.; Kim, J.; Chim, C. Y.; Galli, G.; Wang, F. Emerging Photoluminescence in Monolayer $\\mathbf{Mo}S_{2}$ . Nano Lett. 2010, 10, 1271−1275. \n(4) Cai, L.; He, J. F.; Liu, Q. H.; Yao, T.; Chen, L.; Yan, W. S.; Hu, F. C.; Jiang, Y.; Zhao, Y. D.; Hu, T. D.; Sun, Z. H.; Wei, S. Q. VacancyInduced Ferromagnetism of $\\mathbf{MoS}_{2}$ Nanosheets. J. Am. Chem. Soc. 2015, 137, 2622−2627. \n(5) Zeng, H. L.; Dai, J. F.; Yao, W.; Xiao, D.; Cui, X. D. Valley Polarization in $\\mathbf{MoS}_{2}$ Monolayers by Optical Pumping. Nat. Nanotechnol. 2012, 7, 490−493. \n(6) Gong, Y. J.; Liu, Z.; Lupini, A. R.; Shi, G.; Lin, J. H.; Najmaei, S.; Lin, Z.; Elias, A. L.; Berkdemir, A.; You, G.; Terrones, H.; Terrones, M.; Vajtai, R.; Pantelides, S. T.; Pennycook, S. J.; Lou, J.; Zhou, W.; Ajayan, P. M. Band Gap Engineering and Layer-by-Layer Mapping of Selenium-Doped Molybdenum Disulfide. Nano Lett. 2014, 14, 442− 449. \n(7) Duan, X. D.; Wang, C.; Fan, Z.; Hao, G. L.; Kou, L. Z.; Halim, U.; Li, H. L.; Wu, X. P.; Wang, Y. C.; Jiang, J. H.; Pan, A. L.; Huang, Y.; Yu, R. $\\mathrm{Q.;}$ Duan, X. F. Synthesis of $\\mathbf{WS}_{2\\mathbf{x}}S\\mathbf{e}_{2-2\\mathbf{x}}$ Alloy Nanosheets with Composition-Tunable Electronic Properties. Nano Lett. 2016, 16, 264−269. \n(8) Lin, Z.; Thee, M. T.; Elías, A. L.; Feng, S.; Zhou, C.; Fujisawa, K.; Perea-López, N.; Carozo, V.; Terrones, H.; Terrones, M. Facile Synthesis of $\\mathbf{MoS}_{2}$ and $\\mathbf{Mo}_{\\mathbf{x}}\\mathbf{W}_{1-\\mathbf{x}}\\mathbf{S}_{2}$ Triangular Monolayers. APL Mater. 2014, 2, 092514. \n(9) Gong, Y. J.; Lin, J. H.; Wang, X. L.; Shi, G.; Lei, S. D.; Lin, Z.; Zou, X. L.; Ye, G. L.; Vajtai, R.; Yakobson, B. I.; Terrones, H.; Terrones, M.; Tay, B. K.; Lou, J.; Pantelides, S. T.; Liu, Z.; Zhou, W.; Ajayan, P. M. Vertical and in-Plane Heterostructures from ${\\mathrm{WS}_{2}}/{\\mathrm{MoS}_{2}}$ Monolayers. Nat. Mater. 2014, 13, 1135−1142. \n(10) Duan, X. D.; Wang, C.; Shaw, J. C.; Cheng, R.; Chen, Y.; Li, H. L.; Wu, X. P.; Tang, Y.; Zhang, Q. L.; Pan, A. L.; Jiang, J. H.; Yu, R. $\\mathrm{Q.;}$ Huang, Y.; Duan, X. F. Lateral Epitaxial Growth of Two-Dimensional Layered Semiconductor Heterojunctions. Nat. Nanotechnol. 2014, 9, 1024−1030. \n(11) Li, M. Y.; Shi, Y. M.; Cheng, C. C.; Lu, L. S.; Lin, Y. C.; Tang, H. L.; Tsai, M. L.; Chu, C. W.; Wei, K. H.; He, J. H.; Chang, W. H.; Suenaga, K.; Li, L. J. Epitaxial Growth of a Monolayer ${\\mathrm{WSe}}_{2}–{\\mathrm{MoS}}_{2}$ Lateral P-N Junction with an Atomically Sharp Interface. Science 2015, 349, 524−528. \n\n(12) Gong, Y. J.; Lei, S. D.; Ye, G. L.; Li, B.; He, Y. M.; Keyshar, K.; Zhang, X.; Wang, Q. Z.; Lou, J.; Liu, Z.; Vajtai, R.; Zhou, W.; Ajayan, P. M. Two-Step Growth of Two-Dimensional $\\mathbf{WSe}_{2}/\\mathbf{MoSe}_{2}$ Heterostructures. Nano Lett. 2015, 15, 6135−6141. (13) Pant, A.; Mutlu, Z.; Wickramaratne, D.; Cai, H.; Lake, R. K.; Ozkan, C.; Tongay, S. Fundamentals of Lateral and Vertical Heterojunctions of Atomically Thin Materials. Nanoscale 2016, 8, 3870−3887. (14) Yuan, H. T.; Bahramy, M. S.; Morimoto, K.; Wu, S. F.; Nomura, K.; Yang, B. J.; Shimotani, H.; Suzuki, R.; Toh, M.; Kloc, C.; Xu, X. D.; Arita, R.; Nagaosa, N.; Iwasa, Y. Zeeman-Type Spin Splitting Controlled by an Electric Field. Nat. Phys. 2013, 9, 563−569. (15) Najmaei, S.; Liu, Z.; Zhou, W.; Zou, X. L.; Shi, G.; Lei, S. D.; Yakobson, B. I.; Idrobo, J. C.; Ajayan, P. M.; Lou, J. Vapour Phase Growth and Grain Boundary Structure of Molybdenum Disulphide Atomic Layers. Nat. Mater. 2013, 12, 754−759. (16) Tonndorf, P.; Schmidt, R.; Bottger, P.; Zhang, X.; Borner, J.; Liebig, A.; Albrecht, M.; Kloc, C.; Gordan, O.; Zahn, D. R. T.; de Vasconcellos, S. M.; Bratschitsch, R. Photoluminescence Emission and Raman Response of Monolayer $\\mathrm{MoS}_{2},$ $\\mathrm{MoSe}_{2},$ and ${\\mathrm{WSe}}_{2}$ . Opt. Express 2013, 21, 4908−4916. (17) Lu, X.; Utama, M. I. B.; Lin, J. H.; Gong, X.; Zhang, J.; Zhao, Y. Y.; Pantelides, S. T.; Wang, J. X.; Dong, Z. L.; Liu, Z.; Zhou, W.; Xiong, $\\mathsf{Q}.$ H. Large-Area Synthesis of Monolayer and Few-Layer $\\mathbf{MoSe}_{2}$ Films on $\\mathrm{SiO}_{2}$ Substrates. Nano Lett. 2014, 14, 2419−2425. (18) Mahjouri-Samani, M.; Lin, M. W.; Wang, K.; Lupini, A. R.; Lee, J.; Basile, L.; Boulesbaa, A.; Rouleau, C. M.; Puretzky, A. A.; Ivanov, I. N.; Xiao, K.; Yoon, M.; Geohegan, D. B. Patterned Arrays of Lateral Heterojunctions within Monolayer Two-Dimensional Semiconductors. Nat. Commun. 2015, 6, 7749. (19) Su, S. H.; Hsu, Y. T.; Chang, Y. H.; Chiu, M. H.; Hsu, C. L.; Hsu, W. T.; Chang, W. H.; He, H., Jr; Li, L. J. Band Gap-Tunable Molybdenum Sulfide Selenide Monolayer Alloy. Small 2014, 10, 2589−2594. (20) Nam, D.; Lee, J. U.; Cheong, H. Excitation Energy Dependent Raman Spectrum of $\\mathbf{MoSe}_{2}$ . Sci. Rep. 2015, 5, 17113. (21) Moulder, J. F.; Chastain, J. Handbook of X-Ray Photoelectron Spectroscopy: A Reference Book of Standard Spectra for Identification and Interpretation of XPS Data; Physical Electronics Division, Perkin-Elmer Corporation: Waltham, MA, 1992. (22) Buscema, M.; Steele, G. A.; van der Zant, H. S.; CastellanosGomez, A. The Effect of the Substrate on the Raman and Photoluminescence Emission of Single-Layer $\\mathbf{Mo}S_{2}$ . Nano Res. 2014, 7, 561−571. (23) Voiry, D.; Fullon, R.; Yang, J.; e Silva, C. d. C. C.; Kappera, R.; Bozkurt, I.; Kaplan, D.; Lagos, M. J.; Batson, P. E.; Gupta, G.; et al. The Role of Electronic Coupling between Substrate and 2D $\\ensuremath{\\mathbf{MoS}}_{2}$ Nanosheets in Electrocatalytic Production of Hydrogen. Nat. Mater. 2016, 15, 1003. (24) Nan, H. Y.; Wang, Z. L.; Wang, W. H.; Liang, Z.; Lu, Y.; Chen, $\\mathrm{Q.;}$ He, D. W.; Tan, P. H.; Miao, F.; Wang, X. R.; Wang, J. L.; Ni, Z. H. Strong Photoluminescence Enhancement of $\\ensuremath{\\mathbf{MoS}}_{2}$ through Defect Engineering and Oxygen Bonding. ACS Nano 2014, 8, 5738−5745. (25) Tongay, S.; Suh, J.; Ataca, C.; Fan, W.; Luce, A.; Kang, J. S.; Liu, J.; Ko, C.; Raghunathanan, R.; Zhou, J.; Ogletree, F.; Li, J. B.; Grossman, J. C.; Wu, J. Q. Defects Activated Photoluminescence in Two-Dimensional Semiconductors: Interplay between Bound, Charged, and Free Excitons. Sci. Rep. 2013, 3, 2657. (26) Hong, J. H.; Hu, Z. X.; Probert, M.; Li, K.; Lv, D. H.; Yang, X. N.; Gu, L.; Mao, N. N.; Feng, Q. L.; Xie, L. M.; Zhang, J.; Wu, D. Z.; Zhang, Z. Y.; Jin, C. H.; Ji, W.; Zhang, X. X.; Yuan, J.; Zhang, Z. Exploring Atomic Defects in Molybdenum Disulphide Monolayers. Nat. Commun. 2015, 6, 6293. (27) Kresse, G.; Furthmüller, J. Efficient Iterative Schemes for ab initio Total-Energy Calculations Using a Plane-Wave Basis Set. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 11169. (28) Blöchl, P. E. Projector Augmented-Wave Method. Phys. Rev. B: Condens. Matter Mater. Phys. 1994, 50, 17953. \n\n(29) Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865. (30) Porezag, D.; Pederson, M. R. Infrared Intensities and RamanScattering Activities within Density-Functional Theory. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 7830. (31) Fonari, A.; Stauffer, S.VASP_Raman.py. https://github.com/ raman-sc/VASP/, Accessed September 2013. (32) Wellendorff, J.; Lundgaard, K. T.; Møgelhøj, A.; Petzold, V.; Landis, D. D.; Nørskov, J. K.; Bligaard, T.; Jacobsen, K. W. Density Functionals for Surface Science: Exchange-Correlation Model Development with Bayesian Error Estimation. Phys. Rev. B: Condens. Matter Mater. Phys. 2012, 85, 235149. " + }, + { + "id": "10.1038_ncomms14675", + "DOI": "10.1038/ncomms14675", + "DOI Link": "http://dx.doi.org/10.1038/ncomms14675", + "Relative Dir Path": "mds/10.1038_ncomms14675", + "Article Title": "Highly selective and active CO2 reduction electro-catalysts based on cobalt phthalocyanine/carbon nullotube hybrid structures", + "Authors": "Zhang, X; Wu, ZS; Zhang, X; Li, LW; Li, YY; Xu, HM; Li, XX; Yu, XL; Zhang, ZS; Liang, YY; Wang, HL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electrochemical reduction of carbon dioxide with renewable energy is a sustainable way of producing carbon-neutral fuels. However, developing active, selective and stable electrocatalysts is challenging and entails material structure design and tailoring across a range of length scales. Here we report a cobalt-phthalocyanine-based high-performance carbon dioxide reduction electrocatalyst material developed with a combined nulloscale and molecular approach. On the nulloscale, cobalt phthalocyanine (CoPc) molecules are uniformly anchored on carbon nullotubes to afford substantially increased current density, improved selectivity for carbon monoxide, and enhanced durability. On the molecular level, the catalytic performance is further enhanced by introducing cyano groups to the CoPc molecule. The resulting hybrid catalyst exhibits 495% Faradaic efficiency for carbon monoxide production in a wide potential range and extraordinary catalytic activity with a current density of 15.0mAcm(-2) and a turnover frequency of 4.1 s(-1) at the overpotential of 0.52V in a near-neutral aqueous solution.", + "Times Cited, WoS Core": 1195, + "Times Cited, All Databases": 1246, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000395727800001", + "Markdown": "# Highly selective and active CO2 reduction electrocatalysts based on cobalt phthalocyanine/carbon nanotube hybrid structures \n\nXing Zhang1,\\*, Zishan Wu2,3,\\*, Xiao Zhang1,\\*, Liewu $\\mathsf{L i}^{1,\\star}$ , Yanyan Li1, Haomin $\\mathsf{X}\\mathsf{u}^{1},$ , Xiaoxiao Li1, Xiaolu Yu1, Zisheng Zhang1, Yongye Liang1 & Hailiang Wang2,3 \n\nElectrochemical reduction of carbon dioxide with renewable energy is a sustainable way of producing carbon-neutral fuels. However, developing active, selective and stable electrocatalysts is challenging and entails material structure design and tailoring across a range of length scales. Here we report a cobalt-phthalocyanine-based high-performance carbon dioxide reduction electrocatalyst material developed with a combined nanoscale and molecular approach. On the nanoscale, cobalt phthalocyanine (CoPc) molecules are uniformly anchored on carbon nanotubes to afford substantially increased current density, improved selectivity for carbon monoxide, and enhanced durability. On the molecular level, the catalytic performance is further enhanced by introducing cyano groups to the CoPc molecule. The resulting hybrid catalyst exhibits $595\\%$ Faradaic efficiency for carbon monoxide production in a wide potential range and extraordinary catalytic activity with a current density of $15.0\\mathsf{m A c m}^{-2}$ and a turnover frequency of $4.1\\mathsf{s}^{-1}$ at the overpotential of $0.52\\mathrm{V}$ in a near-neutral aqueous solution. \n\nonverting carbon dioxide $\\left(\\mathrm{CO}_{2}\\right)$ to useful products is an attractive paradigm to mitigate the environmental problems associated with atmospheric $\\mathrm{CO}_{2}$ concentration increase and to simultaneously benefit energy storage and chemical production1–4. Electrocatalytic $\\mathrm{CO}_{2}$ reduction is of particular interest as it can work under ambient conditions in aqueous media and is compatible with utilization of renewable energy sources such as wind and solar energy5. However, the efficiency and practicality of $\\mathrm{CO}_{2}$ electroreduction is currently hindered by the lack of cost-effective electrocatalysts with high catalytic activity, selectivity and durability6. \n\nA range of materials including metals, oxides, chalcogenides, nitrogen-doped carbons and molecular complexes have been explored for catalysing $\\mathrm{CO}_{2}$ electroreduction7–27. Among them, metal porphyrins and metal phthalocyanines constitute an attractive class of materials with distinct advantages in easy accessibility, chemical stability and structural tunability at molecular level28–32. Recently, a covalent organic framework (COF) based on cobalt-porphyrin has been reported for efficiently reducing $\\mathrm{CO}_{2}$ to CO in aqueous electrolyte. The catalyst exhibits a Faradaic efficiency (FE) of $90\\%$ together with an optimized initial turnover frequency (TOF) as high as $3s^{-1}$ at an overpotential of $0.55\\mathrm{V}$ (ref. 14). In another case, iron-porphyrin derivative molecules immobilized on a carbon nanotube (CNT) electrode exhibited a TOF of $\\mathrm{144h^{-1}}$ and an FE of $93\\%$ in converting $\\mathrm{CO}_{2}$ to CO at an overpotential of $0.48\\mathrm{V}$ (ref. 16). Cobalt phthalocyanine (CoPc) molecules absorbed on graphite electrode are also capable to reduce $\\mathrm{CO}_{2}$ to CO, but the activity and selectivity are modest13. By modification with poly-4-vinylpridine (P4VP), the catalytic performance could be enhanced33,34. A current density of $\\mathbf{\\dot{2}.0}\\mathbf{m}\\mathbf{A}\\mathbf{cm}^{-2}$ and a TOF of $4.8\\:s^{-1}$ with an FE of $89\\%$ for CO have been demonstrated for a CoPc-P4VP system at an overpotential of $0.64\\mathrm{V}$ (ref. 34). Despite these progresses, better electrocatalyst materials are still deserved to be developed. \n\nHere, we report a combined nanoscale and molecular approach to construct CoPc-based hybrid materials as efficient electrocatalysts for $\\mathrm{CO}_{2}$ reduction to CO. On the nanoscale, CoPc molecules are uniformly anchored on CNTs. At an overpotential $(E^{\\circ}_{\\mathrm{{CO2/CO}}}=-0.11\\:\\mathrm{V}$ versus the reversible hydrogen electrode (versus RHE))15 of $0.52\\mathrm{V}$ in $0.1\\mathrm{M}\\mathrm{KHCO}_{3}$ aqueous solution, the $\\mathrm{CoPc/CNT}$ hybrid catalyst shows a high and stable current density of over $10\\mathrm{mA}\\mathrm{cim}^{-2}$ with a FE of over $90\\%$ for $\\mathrm{CO}_{2}$ reduction to CO, corresponding to a TOF of $2.7{\\mathrm{s}}^{-1}$ . We find that the hybridization with CNTs significantly improves not only the catalytic activity but also the product selectivity and catalytic stability as well. The catalyst material is further upgraded with molecular level structure optimization. By introducing cyano groups to the CoPc molecular structure, we realize a superior CoPc-CN/CNT hybrid catalyst which reduces $\\mathrm{CO}_{2}$ to CO with a TOF of $4.1\\:s^{-1}$ and a FE of $96\\%$ at an overpotential of $0.52\\mathrm{V}$ representing to the best of our knowledge the most active and selective molecular-based electrocatalyst for $\\mathrm{CO}_{2}$ reduction to CO so far. \n\n# Results \n\nSynthesis and characterization of $\\mathbf{CoPc/CNT}$ . The $\\mathrm{CoPc/CNT}$ hybrid was prepared by interacting CoPc and multi-walled CNTs in $N,N.$ -dimethyl formamide (DMF) with the assistance of sonication and magnetic stirring (see Methods for experimental details). DMF is a good solvent for dispersing CoPc and CNTs, allowing for effective anchoring of CoPc molecules on CNTs via strong $\\pi{-}\\pi$ interactions35. Transmission electron microscopy (TEM) reveals that the morphology of the CoPc/CNT (Fig. 1a,b) resembles that of the original CNTs (Supplementary Fig. 1a,b) as nanotubular structures with an average diameter of $\\sim20\\mathrm{nm}$ . No aggregated CoPc particles were observed. The scanning TEM image and the corresponding energy dispersive X-ray spectroscopy maps show that the distributions of C and N elements overlap and match the nanotube structures (Fig. 1c), which confirms that the CoPc molecules are uniformly dispersed on the sidewalls of the CNTs. The Co map overlaps partially with the C or N map, possibly due to the low atomic content of Co in the hybrid material. It should be pointed out that no Co signals could be detected in the original CNT sample (Supplementary Fig. 1c). \n\nInductively coupled plasma mass spectrometry (ICP-MS) was employed to determine the Co amount and to derive the CoPc content in the hybrid material. The Co amount was found to be $0.63\\mathrm{wt\\%}$ , corresponding to $6.0\\mathrm{wt\\%}$ of CoPc in the hybrid (denoted as $\\mathrm{CoPc/CNT(\\bar{6}\\%)}$ hereafter). Raman spectroscopy was further used to characterize the $\\mathrm{CoPc/CNT}$ hybrid (Fig. 1d). Signature vibrational peaks of CNT and CoPc can be discerned in the spectrum. It is noted that some of the CoPc vibrational features are not observed for the hybrid material, suggesting strong CoPc-CNT electronic interactions that prohibit some of the vibrational modes of the CoPc molecules on CNT. The CoPc content in the hybrid was adjusted in the range from 26 to $0.50\\mathrm{wt\\%}$ (Supplementary Table 1). The TEM and Raman spectroscopy results of the corresponding materials are shown in Supplementary Figs 2–4. With a CoPc content of $26\\mathrm{wt\\%}$ , wrinkled layers are clearly observed on the sidewalls of the CNTs (Supplementary Fig. 2) and the Raman spectrum shows most of the CoPc vibrational features (Supplementary Fig. 4), suggesting that CoPc aggregates have formed with such a high loading. With a CoPc loading of $2.5\\mathrm{wt\\%}$ or lower, the CNT sidewalls appear smooth (Supplementary Fig. 3), indicating that CoPc is possibly dispersed on CNTs at molecular level. \n\nElectrocatalytic performance of $\\mathbf{CoPc/CNT}$ . The catalyst materials were loaded on carbon fibre paper (CFP) substrates (catalyst loading is $0.4\\mathrm{mg}\\mathrm{cm}^{-2}$ unless otherwise mentioned). Cyclic voltammetry was first performed in a phosphate buffer solution $(0.2\\mathrm{M},\\mathrm{pH}7.2)$ saturated with Ar or $\\mathrm{CO}_{2}$ (Supplementary Fig. 5). The $\\mathrm{CoPc/CNT(6\\%)}$ hybrid under Ar exhibited considerable cathodic current density at potentials $<-0.35\\mathrm{V}$ versus RHE, which was ascribed to hydrogen evolution reaction because hydrogen was detected as the only product with a high FE. When the solution was saturated with $\\mathrm{CO}_{2}$ , significant current increase was observed and $\\mathrm{CO}_{2}$ reduction products were detected (Supplementary Fig. 5a). In contrast, the CFP without catalyst showed much smaller current density (Supplementary Fig. 5b). These results suggest that the $\\mathrm{CoPc/CNT}$ hybrid has significant catalytic activity for reducing $\\mathrm{CO}_{2}$ . Control experiments further reveal that the $\\mathrm{CoPc/CNT}$ hybrid has much higher catalytic activity than CoPc or CNTs alone (Supplementary Fig. 5a,b). CoPc/CNT hybrids with different CoPc contents were also studied (Supplementary Fig. 6). It is found that the reduction current increases with the CoPc percentage but starts to saturate when the CoPc percentage goes over $2.5\\mathrm{wt\\%}$ . Therefore, we focus on the $\\mathrm{CoPc/CNT}(2.5\\%)$ hybrid (the cobalt content is $0.26\\mathrm{wt\\%}$ ) in the following studies. \n\nElectrochemical $\\mathrm{CO}_{2}$ reduction in a 0.1 M ${\\mathrm{KHCO}}_{3}$ aqueous solution saturated with $\\mathrm{CO}_{2}$ $\\mathrm{(pH~6.8)}$ was performed under controlled electrode potentials. Figure 2a shows the chronoamperograms of $\\mathrm{CoPc/CNT}(2.5\\%)$ at different potentials. Little current decay $(<5\\%)$ after $^\\mathrm{1h}$ was observed at each potential. The CoPc molecular structure remains intact over the electrolysis (Supplementary Fig. 7). A high current density of $>10\\mathrm{mAcm}^{'-2}$ was achieved at $-0.63\\mathrm{V}$ versus RHE. Gas chromatography (GC) and nuclear magnetic resonance spectroscopy were used to analyse the gas and liquid products respectively. $\\mathrm{H}_{2}$ and CO were the major gas products and no liquid products could be detected (Fig. 2b). The product distribution was found to be dependent on the applied potential. At a low potential of $-0.46\\mathrm{V}$ versus RHE, the FE for CO production $\\scriptstyle(\\mathrm{FE}(\\mathrm{CO})),$ ) was determined to be $59\\pm3.4\\%$ . The $\\mathrm{FE}(\\mathrm{CO})$ increased with larger overpotential applied, and reached over $92\\%$ at $-0.59$ and $-0.63\\mathrm{V}$ versus RHE. In contrast, CoPc directly loaded on CFP showed significantly lower current density and faster decay (Supplementary Fig. 8). The FE(CO) was only around $68\\%$ at $-0.59$ and $-0.63\\mathrm{V}$ versus RHE (Fig. 2b). For pure CNTs, the reduction current density at $-0.63\\mathrm{V}$ versus RHE was smaller than $0.10\\mathrm{mA}\\mathrm{cm}^{-2}$ (Supplementary Fig. 8a), and only $\\mathrm{H}_{2}$ could be detected as the reduction product at this potential. Figure 2c shows the partial current densities of the reduction products over the $\\mathrm{CoPc/CNT}(2.5\\%)$ and $\\mathrm{CoPc}$ catalysts at various potentials. The CO production rate over the $\\mathrm{CoPc/CNT}$ is much higher than that over the CoPc directly loaded on CFP. These results indicate that $\\mathrm{CoPc/CNT}$ exhibits not only higher catalytic activity, but also enhanced stability and product selectivity. \n\n![](images/c49ea421c87b8412baa9743aeb52a2ea59ff30c1165d73bbc5c1f6ae61fdc52a.jpg) \nFigure 1 | Morphological and structural characterizations of the CoPc/CNT hybrid. (a,b) TEM images of the $\\mathsf{C o P c/C N T(6\\%)}$ hybrid. Inset in b shows a schematic representation of the CoPc/CNT hybrid. (c) STEM image of the $\\mathsf{C o P c/C N T(6\\%)}$ material and the corresponding EDS maps of C, N and Co in the blue dash area. (d) Raman spectra of pure CoPc, the $\\mathsf{C o P c/C N T(6\\%)}$ hybrid and pure CNTs. Scale bars, $100\\mathsf{n m}$ (a); $20\\mathsf{n m}$ (b); and $200\\mathsf{n m}$ (c). EDS, energy dispersive X-ray spectroscopy; STEM, scanning transmission electron microscopy. \n\n![](images/9a12a7402ffb1cb8b8ef045f2d6a987e03cb48c8834b8a5f51a3123465f658ce.jpg) \nFigure 2 | $\\pmb{\\mathrm{co}}_{2}$ electroreduction catalysed by the CoPc/CNT hybrid. (a) Representative chronoamperograms of ${\\mathsf{C O}}_{2}$ electroreduction catalysed by the $\\mathsf{C o P c/C N T}(2.5\\%)$ hybrid for 1 h at various potentials in 0.1 M $K{\\mathsf{H C O}}_{3}$ aqueous solution. (b) Faradaic efficiencies of ${\\mathsf{C O}}_{2}$ reduction products in the gas phase for $\\mathsf{C o P c/C N T}(2.5\\%)$ (red) and CoPc (blue) at various potentials. (c) Partial current densities of ${\\mathsf{C O}}_{2}$ reduction products in the gas phase for CoPc/ $C N T(2.5\\%)$ (red) and CoPc (blue) at different potentials. The average values and error bars in (b,c) are based on six measurements during three reaction runs (two product analysis measurements were performed in each run). The error bars represent s.d. of six measurements. (d) Long-term stability of the $\\mathsf{C o P c/C N T}(2.5\\%)$ hybrid catalyst for ${\\mathsf{C O}}_{2}$ reduction operated at $\\_{0.63\\vee}$ versus RHE for $10\\mathsf{h}$ . The data are all $i R$ corrected. \n\nA long-term operation was conducted at $-0.63\\mathrm{V}$ versus RHE for the $\\mathrm{CoPc/CNT}$ catalyst. The initial current density of $\\sim10\\mathrm{mAcm}^{-2}$ was maintained for $\\mathrm{10h}$ and the FE(CO) was over $90\\%$ during the entire period (Fig. 2d), corresponding to a remarkable turnover number of 97,000 for $\\mathrm{CO}_{2}$ conversion to CO. The quantity of CO molecules generated is $\\sim3\\small{,}000$ times more than the total number of $\\mathrm{~C~}$ atoms contained in all the CoPc molecules of the $\\mathrm{CoPc/CNT}$ catalyst. Combined with the observation that no CO or other $\\mathrm{CO}_{2}$ reduction products are detected when either CNTs or bare CFP is used as catalyst, the result unambiguously confirms that the produced CO originates from $\\mathrm{CO}_{2}$ . \n\nCoPc hybridized with other forms of nano-carbons including reduced graphene oxide (RGO) and carbon black (CB) was also studied (Supplementary Table 1). Compared with $\\mathrm{CoPc}/$ $\\mathrm{CNT}(2.5\\%)$ , $\\mathrm{CoPc/RGO}(2.2\\%)$ and $\\mathrm{CoPc/CB}(3.3\\%)$ showed less than 1/3 of the current density at $-0.59\\mathrm{V}$ versus RHE with $\\sim10\\%$ lower $\\mathrm{FE}(\\mathrm{CO})$ and inferior catalytic stability (Fig. 3). The results clearly reflect the advantage of CNTs in enhancing the catalytic performance. The CNT has a higher graphitic degree than either RGO or CB and is thus likely to afford better $\\pi{-}\\pi$ interactions with CoPc and higher electron conduction36. We also measured a $\\mathrm{Pc/CNT}$ hybrid and observed much smaller reduction current density (Fig. 3b) with a much lower FE(CO) of only $19\\%$ (Fig. 3c), indicating that the Co centres in the $\\mathrm{CoPc/CNT}$ are the catalytically active sites. The low but non-zero conversion of $\\mathrm{CO}_{2}$ to CO on $\\dot{\\mathrm{Pc}}/\\mathrm{CNT}$ is attributed to the catalytic activity of Pc itself. Recent experimental and theoretical studies have found that nitrogen dopants such as pyridinic, pyrrolic and graphitic nitrogen atoms in carbon materials can catalyse $\\mathrm{CO}_{2}$ electroreduction to CO (refs 12,37). Thus, it is reasonable that the nitrogen-containing Pc supported on CNTs could reduce $\\mathrm{CO}_{2}$ to CO with certain activity. \n\nCyano-substituted CoPc hybrid. We further explored the potential of tuning the CoPc molecular structure for optimizing catalytic performance. Inspired by previous reports that electronwithdrawing substituents on metal phthalocyanine structures can increase the electrocatalytic performance for $\\mathrm{CO}_{2}$ reduction to CO (refs 38–40), we synthesized cobalt-2,3,7,8,12,13,17, 18-octacyano-phthalocyanine $(\\mathrm{CoPc-CN})$ and prepared a CoPcCN/CNT hybrid containing $3.5\\mathrm{wt\\%}$ of $\\mathrm{CoPc\\mathrm{-}C N}$ (the cobalt content is $0.27\\mathrm{wt\\%}$ , similar to that of $\\mathrm{CoPc/CNT}(2.5\\%))$ (Supplementary Fig. 9). In 0.1 M ${\\mathrm{KHCO}}_{3}$ , the CoPc-CN/CNT hybrid exhibits even larger reduction current density than the previous $\\mathrm{CoPc/CNT}$ hybrid (Supplementary Fig. 10 and Fig. 4a). More impressively, higher selectivity for $\\scriptstyle{\\mathrm{CO}}$ production at low overpotentials can be achieved with the CoPc-CN/CNT catalyst. The FE(CO) is already over $90\\%$ at $-0.46\\mathrm{V}$ versus RHE (Fig. 4b), compared with only $59\\%$ for the $\\mathrm{CoPc/CNT}$ at the same potential. The FE(CO) maintains over $95\\%$ from $-0.53\\mathrm{V}$ to $-0.63\\mathrm{V}$ versus RHE (Fig. 4b). We also tested the CoPcCN/CNT hybrid catalyst in $0.5\\mathrm{M}\\mathrm{\\KHCO}_{3}$ aqueous solution. At $-0.46\\mathrm{V}$ versus RHE, a high current density of $5.6\\operatorname{mA}\\mathrm{cm}^{-2}$ with a $\\mathrm{FE}(\\mathrm{CO})$ of $88\\%$ could be obtained (Supplementary Fig. 11). \n\n![](images/3a92fd5aee8e2a2d9980aed53b2d4a7c3955b4cb37e16f5f574b093c0cd37106.jpg) \nFigure 3 | Comparison of various hybrid materials for catalysing $\\pmb{\\mathrm{co}}_{2}$ electroreduction. (a) Cyclic voltammograms at $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ , (b) chronoamperograms at $-0.59\\vee$ versus RHE, (c) Faradaic efficiencies of ${\\mathsf{C O}}_{2}$ reduction products, and (d) partial current densities of ${\\mathsf{C O}}_{2}$ reduction products for Pc/CNT, ${\\mathsf{C o P c}}/$ RGO and ${\\mathsf{C o P c/C B}}$ in comparison with ${\\mathsf{C o P c/C N T}}$ in 0.1 M ${\\mathsf{K H C O}}_{3}$ solution. The average values and error bars in (c,d) are based on six measurements during three reaction runs (two product analysis measurements were performed in each run). The error bars represent s.d. of six measurements. The data are all $i R$ corrected. \n\n![](images/71da7326d7a62f58b7cdfbce30da24efc833958a469362f5be4bec5bbd49b7e9.jpg) \nFigure 4 | Introduction of cyano groups to CoPc enhances catalytic performance. (a) Chronoamperograms and $(\\pmb{6})$ Faradaic efficiencies of reduction products at different potentials for CoPc-CN/CNT (solid line) in comparison with ${\\mathsf{C o P c/C N T}}$ (dotted line). Inset in $(\\pmb{6})$ shows the molecular structure of ${\\mathsf{C o P c-C N}},$ which is anchored on CNT. The average values and error bars in b are based on six measurements during three reaction runs (two product analysis measurements were performed in each run). The error bars represent s.d. of six measurements. The data are all $i R$ corrected. \n\n
Table1|Comparison of the CoPc/CNTand CoPc-CN/CNT hybridcatalysts with reported state-of-the-art high-performance CO-selective COz reduction electrocatalysts working in aqueous media.
j(mA cm -2)Vversus RHEElectrolyte (pH)Main productsTOF (CO)s-1
Catalyst CoPc/CNT (2.5%)~10.0-0.630.1M KHCO3 (6.8)CO (92%),H (6.4%)2.7 (±0.0)Ref.
CoPc-CN/CNT (3.5%)~15.0-0.630.1M KHCO3 (6.8)CO (98%), Hz (3.3%)4.1 (±0.1)This study
CoPc-CN/CNT (3.5%)-0.460.5 M KHCO3 (7.2)CO (88%),H (13%)1.4 (±0.0)This study
Perfluorinated CoPc~5.6 ~ 4.410.80.5 M KHCO3 (7.2)CO(93%), H (6%)1.6This_study 39
CoPc-P4VP2.0-0.730.1M NaHPO4 (4.7)CO (89%), H (5%)4.834
COF-367-Co3.3-0.670.5 M KHCO3 (7.3)CO (91%),Hz (20%)0.5314
COF-367-Co(1%)0.45- 0.670.5 M KHCO3 (7.3)CO (53%),H (62%)2.614
CATpyr/CNT0.24-0.590.5 M KHCO3 (7.3)CO (93%), H (4%)0.0416
FeTPP-WSCAT~1.0-0.520.1MKCI+0.5MKHCO3 (7.3)CO (~ 92%)N/A49
Au NWs8.16-0.350.5 M KHCO3 (7.2)CO (94%)0.0250
Pd NPs~9.76-0.890.1M KHCO (6.8)CO (91%)~ 0.1619
Nanoporous Ag~8.7-0.50.5 M KHCO3 (7.2)CO (92%)~0.00251
\n\nAbbreviations: CoPc, cobalt phthalocyanine; CNT, carbon nanotube; RHE, reversible hydrogen electrode; TOF, turnover frequency. \n\n# Discussion \n\nThe CoPc-CN/CNT hybrid material demonstrates outstanding catalytic performance for $\\mathrm{CO}_{2}$ electroreduction to CO. At $-0.{\\dot{6}}3\\mathrm{V}$ versus RHE in $0.1\\mathrm{M}\\mathrm{\\KHCO_{3}}$ , the catalyst delivers a reduction current density as high as $15.{\\overset{-}{0}}\\operatorname*{mA}\\operatorname{cm}^{-2}$ , with $98\\%$ of the electrons devoted to CO production. Assuming all the loaded CoPc-CN molecules are catalytically active (the electrochemically active coverage of the molecules could not be readily determined from the broad CV peaks), the TOF value for CO production is calculated to be $4.1\\:s^{\\dot{-}1}$ , representing the lower limit of the actual TOF. The calculated TOF is slightly higher than that of other CO-selective electrocatalysts based on molecular catalytic sites (Table 1). Furthermore, our hybrid catalysts deliver much higher geometric current densities than other molecular-based catalysts under similar conditions (Table 1). At $-0.46\\mathrm{V}$ versus RHE in $0.5\\mathrm{M}$ ${\\mathrm{KHCO}}_{3}.$ , our CoPc-CN/CNT catalyst reaches $5.6\\operatorname{mA}\\mathrm{cm}^{-2}$ with a FE(CO) of $88\\%$ (corresponding to a TOF of $1.4\\:s^{-1}\\$ ), which is already comparable to the most-active noble metal-based electrocatalysts for $\\mathrm{CO}_{2}$ reduction to CO (Table 1). We note that the catalyst shows higher catalytic activity in $0.5\\mathrm{M}$ ${\\mathrm{KHCO}}_{3}$ than in $0.1\\dot{\\mathrm{~M~KHCO_{3}}}$ (Supplementary Fig. 11), which is possibly due to improved mass transport of CO2 to the catalytic sites41. \n\nA clear advantage of our $\\mathrm{CoPc/CNT}$ and $\\mathrm{CoPc-CN/CNT}$ hybrid materials is that they can deliver high geometrical catalytic current densities comparable to the best heterogeneous catalysts while maintaining good per-site activity comparable to the best molecular systems for $\\mathrm{CO}_{2}$ electroreduction to $\\mathrm{CO}^{42}$ . The efficient molecule/CNT hybridization strategy allows us to realize one order of magnitude larger catalyst molecule loading $(\\sim1.8\\times10^{-8}\\mathrm{mol}\\mathrm{cm}^{-\\sharp}$ for CoPc or CoPc-CN) without compromising per-molecule activity, leading to one order of magnitude increase in catalytic current density compared with the previously reported CoPc-P4VP loaded on edge-plane graphite with similar $\\mathrm{TOF}^{34}$ . For hybrid materials with higher CoPc contents, lower TOFs were expectedly observed due to aggregation of molecules (Supplementary Table 2). \n\nThe exceptional catalytic performance (activity, selectivity and durability) originates from the CNT hybridization on the nanoscale and the cyano substitution on the molecular level. The strong interactions between $\\mathrm{CoPc\\mathrm{-}C N}$ (or CoPc) and CNTs allow for uniform distribution of the molecules on the highly conductive carbon support and thus enable a high degree of catalytic site exposure, beneficial for achieving high catalytic current densities. Rapid electron transfer from electrode to surface CoPc-CN (or CoPc) molecules anchored on CNTs facilitates fast repetitive cycling between $\\operatorname{Co}(\\operatorname{II})$ and $\\mathrm{Co(I)}$ to support $\\mathrm{CO}_{2}$ conversion to CO during the electrocatalytic process. Moreover, uniform coverage of CNTs by CoPc molecules in the $\\mathrm{CoPc/CNT}$ catalyst material structure also minimizes exposure of carbon surface which may catalyse hydrogen evolution reaction but not $\\mathrm{CO}_{2}$ reduction. All these contribute to the high selectivity of $\\mathrm{CO}_{2}$ reduction over proton reduction of our hybrid catalysts43. Attachment to CNTs could also lower the possibility of molecule detachment from electrode and thus enhance catalytic durability. \n\nIt should be noted that our solution-phase hybridization strategy distinguishes from previous approaches where metal porphyrin or metal phthalocyanine molecules are drop-dried or dip-coated on electrodes pre-loaded with $\\mathrm{CNTs}^{16,38}$ . Such directdrying methods may generate molecular aggregates, which harms catalytic site exposure and impedes efficient electron delivery from electrode to catalyst surface. To prove this concept, we used SEM to check the morphology of the CoPc loaded on CFP by drop-drying its ethanol dispersion, and observed obvious CoPc aggregates (Supplementary Fig. 12a). Replacing the ethanol with DMF is able to reduce the aggregation (Supplementary Fig. 12b), likely due to the improved CoPc solubility and higher boiling point of DMF, and thus increases the $\\mathrm{CO}_{2}$ reduction current density (Supplementary Fig. 13). However, the catalytic performance is still substantially inferior to that of the $\\mathrm{CoPc}/$ CNT hybrid. For the CoPc catalysts, electrons have to go through the less-conductive aggregate bulk to reach the surface molecules, which could hamper the reduction of $\\operatorname{Co}(\\operatorname{II})$ to $\\mathrm{Co(I)}$ . A smaller fraction of $\\operatorname{Co}(\\operatorname{I})$ sites on the CoPc surface and/or slower redox cycling between $\\operatorname{Co}(\\operatorname{II})$ and $\\operatorname{Co}(\\operatorname{I})$ can explain the observed lower product selectivity compared with the CoPc/CNT catalyst. \n\nThe cyano substituent on the phthalocyanine ligand is another essential contributor. The electron-withdrawing cyano groups can facilitate the formation of $\\mathrm{Co(I)}$ which is considered as the active sites for reducing $\\mathrm{CO}_{2}$ (ref. 44). This is supported by the more significant $\\mathrm{Co(II)/Co(I)}$ redox transition observed at more positive potential for the CoPc-CN/CNT as compared with the $\\mathrm{\\bar{C}o P c/C N T}$ (Supplementary Fig. 10b). Even though the cyano substituents may make the $\\operatorname{Co}(\\operatorname{I})$ sites less nucleophilic and thus bind $\\mathrm{CO}_{2}$ less strongly, the positive shift of the $\\mathrm{Co(\\bar{I}I)/C o(\\bar{I})}$ redox potential renders a higher fraction of $\\operatorname{Co}(\\operatorname{I})$ sites in the CoPcCN/CNT catalyst than in the $\\mathrm{CoPc/CNT}$ at low overpotentials. In the potential range $(-0.46$ to $-0.63\\mathrm{V})$ we examined, the $\\mathrm{CoPc/CNT}$ is only partially reduced to $\\operatorname{Co}(\\operatorname{I})$ (Supplementary Fig. 10b). This explains the higher current density and thus higher TOF (based on all the molecules loaded on the electrode) for the CoPc-CN/CNT hybrid catalyst. It can also be responsible for the observed higher CO selectivity for the CoPc-CN/CNT catalyst at low overpotentials. The electron-withdrawing substituents can also reduce the affinity of the cobalt centre to CO (ref. 39), which can accelerate product removal and catalytic turnover45. As a result, cyano substitution further enhances the catalytic performance on the basis of the $\\mathrm{CoPc}/$ CNT hybrid material, which itself is already remarkably active and selective. \n\nIn conclusion, we have devised a combined nanoscale and molecular-level approach to construct easily accessible cobaltphthalocyanine/CNT hybrid materials which catalyse electroreduction of $\\mathrm{CO}_{2}$ to CO with remarkable activity, selectivity and durability in aqueous solution. The CoPc-CN/CNT shows unprecedented electrocatalytic performance, owing to the stacked effects of CNT hybridization and cyano-group substitution in the molecular structure. With the molecularly tunable phthalocyanine unit and the structurally engineerable nano-carbon support, these molecule/CNT hybrid materials represent an attractive class of electrocatalysts for converting $\\mathrm{CO}_{2}$ emissions to sustainable fuels. \n\n# Methods \n\nChemicals. Chemicals were purchased from commercial sources and used without further purification unless otherwise noted. CoPc-CN was synthesized based on a reported method46. All aqueous solutions were prepared with Millipore water $(18.2\\mathrm{M}\\Omega\\mathrm{cm})$ . Organic solvents used were analytical grade. The CNTs were purchased from C-Nano (FT 9000). The purification of CNTs was done by calcining the CNTs at $500^{\\circ}\\mathrm{C}$ in air for $^{5\\mathrm{h}}$ . After cooling down to room temperature, the CNTs were transferred into a $5\\mathrm{wt\\%}$ HCl aqueous solution and sonicated for $30\\mathrm{min}$ . The purified CNTs were collected by filtration and washed with ultrapure water for over 10 times. The quality of the CNTs was evaluated by Raman, SEM and TEM. \n\nPreparation of the hybrid materials. $30\\mathrm{mg}$ of purified CNTs were dispersed in $30\\mathrm{ml}$ of DMF with the assistance of sonication for $^{\\textrm{1h}}$ . Then, a calculated amount of CoPc or CoPc-CN dissolved in DMF was added to the CNT suspension followed by $30\\mathrm{min}$ of sonication to obtain a well-mixed suspension. The mixed suspension was further stirred at room temperature for $20\\mathrm{h}$ . Subsequently, the mixture was centrifuged and the precipitate was washed with DMF for three times and ethanol twice. Finally, the precipitate was lyophilized to yield the final product. Other CoPc/nano-carbon hybrids were prepared \nby the same method. RGO was synthesized following a previously reported method.47,48 \n\nMaterial characterizations. TEM and energy dispersive X-ray spectroscopy were performed on a FEI Tecnai G2 F30 transmission electron microscope. Raman spectra were taken with Horiba LabRAM HR Evolution and Jobin Yvon LabRAM Aramis Raman spectrometers. ICP-MS was performed on an Agilent Technologies 7,700 series instrument. \n\nElectrochemical measurements. All electrochemical measurements were conducted using a CHI 660E Potentiostat in three-electrode configuration. Catalyst ink was prepared by dispersing $2\\mathrm{mg}$ of catalyst material in a mixture of $130\\upmu\\mathrm{l}$ of $0.25\\mathrm{wt\\%}$ Nafion solution and $870\\upmu\\mathrm{l}$ of ethanol with the assistance of sonication. The working electrodes were prepared by drop-drying $100\\upmu\\mathrm{l}$ of catalyst ink onto carbon fibre paper (AvCarb MGL190 from Fuel Cell Store) to cover an area of $0.5\\mathrm{cm}^{2}$ (loading: $0.4\\mathrm{mg}\\mathrm{cm}^{-2}$ ). The loading of other catalysts on CFP was $0.4\\mathrm{mg}\\mathrm{cm}^{-2}$ unless otherwise mentioned. The cyclic voltammetry and chronoamperometry measurements were performed in a gas-tight two-compartment electrochemical cell with a piece of glass frit as the separator (Supplementary Fig. 14). A $1\\mathrm{cm}^{2}$ piece of platinum gauze was used as the counter electrode. Unless otherwise stated, the electrolyte was 0.1 or $0.5\\mathrm{M}\\mathrm{KHCO}_{3}$ solution saturated with $\\mathrm{CO}_{2}$ $\\mathrm{\\Phi_{pH}}6.8$ or 7.2). All potentials were measured against an $\\mathrm{\\Ag/AgCl}$ reference electrode and converted to RHE scale based on Nernst equation. In the electrochemical measurements, $i R$ corrections were made to assess the activity and selectivity of the catalyst under actual electrode potentials, so that the catalytic performance of different catalyst materials could be compared on the same bias42. The uncorrected potentials are listed in Supplementary Table 3. During constantpotential electrolysis, high-purity $\\mathrm{CO}_{2}$ gas $(99.999\\%)$ was delivered into the cathodic compartment at a flow rate of 5 s.c.c.m. to convey the gas products into the gas-sampling loop of a gas chromatograph (GC, SRI Instruments) for analysing the gas products. The reported TOFs and Faradaic efficiencies are average values based on three reaction runs with each containing two GC measurements (a GC measurement was initiated every $30\\mathrm{min}$ ). The reported cyclic voltammograms and chronoamperograms are representative data for these runs. The GC was equipped with a packed Molecular Sieve 5 A capillary column and a packed HaySep D column. Helium $(99.999\\%)$ was used as the carrier gas. A helium ionization detector (HID) was used to quantify $\\mathrm{H}_{2}$ and $\\scriptstyle{\\mathrm{CO}}$ concentrations. The partial current density of CO production was calculated from the GC peak area as follows: \n\n$$\nj_{\\mathrm{CO}}\\mathrm{=}\\mathrm{(peak\\area/}\\alpha\\mathrm{)}\\times\\mathrm{flow\\rate}\\times\\left(2F p/R T\\right)\\times\\left(\\mathrm{electrode\\area}\\right)^{\\mathrm{-1}}\n$$ \n\n$$\nj_{\\mathrm{H_{2}}}\\mathrm{=(peak\\area/}\\beta){\\times}\\mathrm{flow\\rate}{\\times}\\left(2F p/R T\\right){\\times}\\left(\\mathrm{electrode\\area}\\right)^{\\mathrm{-1}}\n$$ \n\nwhere $\\alpha$ and $\\beta$ are conversion factors for CO and $\\mathrm{H}_{2}$ , respectively, determined from the calibration of the GC with standard samples, $p{=}1.013$ bar and $T=293.15\\mathrm{K}$ . \n\nData availability. The data that support the findings of this study are available within the paper and its Supplementary Information file or are available from the corresponding authors upon request. \n\n# References \n\n1. Aresta, M. & Dibenedetto, A. Utilisation of $\\mathrm{CO}_{2}$ as a chemical feedstock: opportunities and challenges. Dalton Trans. 36, 2975–2992 (2007). \n\nprimary driver of early Cenozoic climate. Nature 533, 380–384 (2016). \n3. Sakakura, T., Choi, J.-C. & Yasuda, H. Transformation of carbon dioxide. Chem. Rev. 107, 2365–2387 (2007). \n4. Williamson, P. Scrutinize $\\mathrm{CO}_{2}$ removal methods. Nature 530, 153–155 ð2016Þ: \n5. Kuhl, K. P. et al. Electrocatalytic conversion of carbon dioxide to methane and methanol on transition metal surfaces. J. Am. Chem. Soc. 136, 14107–14113 (2014). \n6. Jones, J. P., Prakash, G. & Olah, G. A. Electrochemical $\\mathrm{CO}_{2}$ reduction: recent advances and current trends. Isr. J. Chem. 54, 1451–1466 (2014). \n7. Qiao, J., Liu, Y., Hong, F. & Zhang, J. A review of catalysts for the electroreduction of carbon dioxide to produce low-carbon fuels. Chem. Soc. Rev. 43, 631–675 (2014). \n8. Zhu, C. & Dong, S. Recent progress in graphene-based nanomaterials as advanced electrocatalysts towards oxygen reduction reaction. Nanoscale 5, 1753–1767 (2013). \n9. Kim, C. et al. Achieving selective and efficient electrocatalytic activity for $\\mathrm{CO}_{2}$ reduction using immobilized silver nanoparticles. J. Am. Chem. Soc. 137, 13844–13850 (2015). \n10. Sarfraz, S., Garcia-Esparza, A. T., Jedidi, A., Cavallo, L. & Takanabe, K. Cu–Sn bimetallic catalyst for selective aqueous electroreduction of $\\mathrm{CO}_{2}$ to CO. ACS Catal. 6, 2842–2851 (2016). \n11. Chen, Y., Li, C. W. & Kanan, M. W. Aqueous $\\mathrm{CO}_{2}$ reduction at very low overpotential on oxide-derived Au nanoparticles. J. Am. Chem. Soc. 134, 19969–19972 (2012). \n12. Wu, J. et al. Achieving highly efficient, selective, and stable $\\mathrm{CO}_{2}$ reduction on nitrogen-doped carbon nanotubes. ACS Nano 9, 5364–5371 (2015). \n13. Lieber, C. M. & Lewis, N. S. Catalytic reduction of carbon dioxide at carbon electrodes modified with cobalt phthalocyanine. J. Am. Chem. Soc. 106, 5033–5034 (1984). \n14. Lin, S. et al. Covalent organic frameworks comprising cobalt porphyrins for catalytic $\\mathrm{CO}_{2}$ reduction in water. Science 349, 1208–1213 (2015). \n15. Asadi, M. et al. Nanostructured transition metal dichalcogenide electrocatalysts for $\\mathrm{CO}_{2}$ reduction in ionic liquid. Science 353, 467–470 (2016). \n16. Maurin, A. & Robert, M. Noncovalent immobilization of a molecular ironbased electrocatalyst on carbon electrodes for selective, efficient $\\mathrm{CO}_{2}$ -to-CO conversion in water. J. Am. Chem. Soc. 138, 2492–2495 (2016). \n17. Li, C. W. & Kanan, M. W. $\\mathrm{CO}_{2}$ reduction at low overpotential on Cu electrodes resulting from the reduction of thick $\\mathrm{Cu}_{2}\\mathrm{O}$ films. J. Am. Chem. Soc. 134, 7231–7234 (2012). \n18. Rosen, J. et al. Electrodeposited $Z\\mathrm{n}$ dendrites with enhanced CO selectivity for electrocatalytic $\\mathrm{CO}_{2}$ reduction. ACS Catal. 5, 4586–4591 (2015). \n19. Gao, D. et al. Size-dependent electrocatalytic reduction of $\\mathrm{CO}_{2}$ over Pd nanoparticles. J. Am. Chem. Soc. 137, 4288–4291 (2015). \n20. Asadi, M. et al. Robust carbon dioxide reduction on molybdenum disulphide edges. Nat. Commun. 5, 4470 (2014). \n21. Varela, A. S. et al. Metal-doped nitrogenated carbon as an efficient catalyst for direct $\\mathrm{CO}_{2}$ electroreduction to CO and hydrocarbons. Angew Chem. Int. Ed. Engl. 54, 10758–10762 (2015). \n22. Kumar, B. et al. Renewable and metal-free carbon nanofibre catalysts for carbon dioxide reduction. Nat. Commun. 4, 2819 (2013). \n23. Studt, F. et al. Discovery of a Ni-Ga catalyst for carbon dioxide reduction to methanol. Nat. Chem. 6, 320–324 (2014). \n24. Torelli, D. A. et al. Nickel-gallium-catalyzed electrochemical reduction of $\\mathrm{CO}_{2}$ to highly reduced products at low overpotentials. ACS Catal. 6, 2100–2104 (2016). \n25. Kas, R. et al. Three-dimensional porous hollow fibre copper electrodes for efficient and high-rate electrochemical carbon dioxide reduction. Nat. Commun. 7, 10748 (2016). \n26. Shen, J. et al. Electrocatalytic reduction of carbon dioxide to carbon monoxide and methane at an immobilized cobalt protoporphyrin. Nat. Commun. 6, 8177 (2015). \n27. Kim, D., Resasco, J., Yu, Y., Asiri, A. M. & Yang, P. Synergistic geometric and electronic effects for electrochemical reduction of carbon dioxide using gold–copper bimetallic nanoparticles. Nat. Commun. 5, 4948 (2014). \n28. Takahashi, K., Hiratsuka, K., Sasaki, H. & Toshima, S. Electrocatalytic behavior of metal porphyrins in the reduction of carbon dioxide. Chem. Lett. 8, 305–308 (1979). \n29. Meshitsuka, S., Ichikawa, M. & Tamaru, K. Electrocatalysis by metal phthalocyanines in the reduction of carbon dioxide. J. Chem. Soc. Chem. Commun. 5, 158–159 (1974). \n30. Kornienko, N. et al. Metal–organic frameworks for electrocatalytic reduction of carbon dioxide. J. Am. Chem. Soc. 137, 14129–14135 (2015). \n31. Costentin, C., Drouet, S., Robert, M. & Save´ant, J.-M. A local proton source enhances $\\mathrm{CO}_{2}$ electroreduction to CO by a molecular Fe catalyst. Science 338, 90–94 (2012). \n32. Weng, Z. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction to hydrocarbons on a heterogeneous molecular Cu catalyst in aqueous solution. J. Am. Chem. Soc. 138, 8076–8079 (2016). \n33. Yoshida, T. et al. Selective electrocatalysis for $\\mathrm{CO}_{2}$ reduction in the aqueousphase using cobalt phthalocyanine/poly-4-vinylpyridine modified electrodes. J. Electroanal. Chem. 385, 209–225 (1995). \n34. Kramer, W. W. & McCrory, C. C. L. Polymer coordination promotes selective $\\mathrm{CO}_{2}$ reduction by cobalt phthalocyanine. Chem. Sci. 7, 2506–2515 (2016). \n35. Tasis, D., Tagmatarchis, N., Bianco, A. & Prato, M. Chemistry of carbon nanotubes. Chem. Rev. 106, 1105–1136 (2006). \n36. Liang, Y., Li, Y., Wang, H. & Dai, H. Strongly coupled inorganic/nanocarbon hybrid materials for advanced electrocatalysis. J. Am. Chem. Soc. 135, 2013–2036 (2013). \n37. Sharma, P. P. et al. Nitrogen-doped carbon nanotube arrays for high-efficiency electrochemical reduction of $\\mathrm{CO}_{2}$ on the understanding of defects, defect Density, and selectivity. Angew Chem. Int. Ed. Engl. 54, 13701–13705 (2015). \n38. Manbeck, G. F. & Fujita, E. A review of iron and cobalt porphyrins, phthalocyanines and related complexes for electrochemical and photochemical reduction of carbon dioxide. J. Porphyrins Phthalocyanines 19, 45–64 (2015). \n39. Morlane´s, N., Takanabe, K. & Rodionov, V. Simultaneous reduction of $\\mathrm{CO}_{2}$ and splitting of $\\mathrm{H}_{2}\\mathrm{O}$ by a single immobilized cobalt phthalocyanine electrocatalyst. ACS Catal 6, 3092–3095 (2016). \n40. Abe, T. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction catalysed by cobalt octacyanophthalocyanine and its mechanism. J. Porphyrins Phthalocyanines 1, 315–321 (1997). \n41. Min, X. & Kanan, M. W. Pd-catalyzed electrohydrogenation of carbon dioxide to formate: High mass activity at low overpotential and identification of the deactivation pathway. J. Am. Chem. Soc. 137, 4701–4708 (2015). \n42. Stevens, M. B. et al. Measurement techniques for the study of thin film heterogeneous water oxidation electrocatalysts. Chem. Mater. 29, 120–140 (2016). \n43. Hod, I., Farha, O. K. & Hupp, J. T. Electrocatalysis powered by porphyrin packing. Nat. Mater. 14, 1192–1193 (2015). \n44. Leung, K., Nielsen, I. M. B., Sai, N., Medforth, C. & Shelnutt, J. A. Cobalt porphyrin catalyzed electrochemical reduction of carbon dioxide in water. 2. Mechanism from first principles. J. Phys. Chem. A 114, 10174–10184 (2010). \n45. Froehlich, J. D. & Kubiak, C. P. The homogeneous reduction of $\\mathrm{CO}_{2}$ by $\\mathrm{[Ni(cyclam)]^{+}}$ : increased catalytic rates with the addition of a CO scavenger. J. Am. Chem. Soc. 137, 3565–3573 (2015). \n46. Kim, S. J., Matsumoto, M. & Shigehara, K. Synthesis and electrical properties of one-dimensional octacyanometallophthalocyanine $\\mathrm{\\Delta}\\mathrm{M}{\\equiv}\\mathrm{Fe}$ Co) polymers. J. Porphyrins Phthalocyanines 4, 136–144 (2000). \n47. Liang, Y. Y. et al. $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocrystals on graphene as a synergistic catalyst for oxygen reduction reaction. Nat. Mater. 10, 780–786 (2011). \n48. Jiang, Y. Y. et al. Enhanced catalytic performance of Pt-free iron phthalocyanine by graphene support for efficient oxygen reduction reaction. ACS Catal 3, 1263–1271 (2013). \n49. Tatin, A. et al. Efficient electrolyzer for $\\mathrm{CO}_{2}$ splitting in neutral water using earth-abundant materials. Proc. Natl Acad. Sci. USA 113, 5526–5529 (2016). \n50. Zhu, W. et al. Active and selective conversion of $\\mathrm{CO}_{2}$ to CO on ultrathin Au nanowires. J. Am. Chem. Soc. 136, 16132–16135 (2014). \n51. Lu, Q. et al. A selective and efficient electrocatalyst for carbon dioxide reduction. Nat. Commun. 5, 3242 (2014). \n\n# Acknowledgements \n\nZ.W. and H.W. acknowledge funding support from Yale University and the Global Innovation Initiative from Institute of International Education. Y.L. acknowledges financial supports from ‘The Recruitment Program of Global Youth Experts of China’, Shenzhen fundamental research funding (JCYJ20160608140827794), Shenzhen Key Lab funding (ZDSYS201505291525382) and Peacock Plan (KQTD20140630160825828). \n\n# Author contributions \n\nY.L. and H.W. conceived the project and designed the experiments. Xing Z., Z.W., L.L., Xiao Z., Y.Li., H.X., X.Li., X.Y., Z.Z. carried out the synthesis, material characterizations and electrocatalytic measurements. Y.L., H.W., Xing Z. and L.L. analysed the data and wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Zhang, X. et al. Highly selective and active $\\mathrm{CO}_{2}$ reduction electrocatalysts based on cobalt phthalocyanine/carbon nanotube hybrid structures. Nat. Commun. 8, 14675 doi: 10.1038/ncomms14675 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2017 " + }, + { + "id": "10.1126_science.aam5655", + "DOI": "10.1126/science.aam5655", + "DOI Link": "http://dx.doi.org/10.1126/science.aam5655", + "Relative Dir Path": "mds/10.1126_science.aam5655", + "Article Title": "Perovskite solar cells with CuSCN hole extraction layers yield stabilized efficiencies greater than 20%", + "Authors": "Arora, N; Dar, MI; Hinderhofer, A; Pellet, N; Schreiber, F; Zakeeruddin, SM; Grätzel, M", + "Source Title": "SCIENCE", + "Abstract": "Perovskite solar cells (PSCs) with efficiencies greater than 20% have been realized only with expensive organic hole-transporting materials. We demonstrate PSCs that achieve stabilized efficiencies exceeding 20% with copper(I) thiocyanate (CuSCN) as the hole extraction layer. A fast solvent removal method enabled the creation of compact, highly conformal CuSCN layers that facilitate rapid carrier extraction and collection. The PSCs showed high thermal stability under long-term heating, although their operational stability was poor. This instability originated from potential-induced degradation of the CuSCN/Au contact. The addition of a conductive reduced graphene oxide spacer layer between CuSCN and gold allowed PSCs to retain >95% of their initial efficiency after aging at a maximum power point for 1000 hours under full solar intensity at 60 degrees C. Under both continuous full-sun illumination and thermal stress, CuSCN-based devices surpassed the stability of spiro-OMeTAD-based PSCs.", + "Times Cited, WoS Core": 1299, + "Times Cited, All Databases": 1382, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000414847100040", + "Markdown": "# SOLAR CELLS \n\n# Perovskite solar cells with CuSCN hole extraction layers yield stabilized efficiencies greater than 20% \n\nNeha Arora,1\\* M. Ibrahim Dar, $^{1*}\\dag$ Alexander Hinderhofer,2 Norman Pellet,1 Frank Schreiber,2 Shaik Mohammed Zakeeruddin,1 Michael Grätzel1† \n\nPerovskite solar cells (PSCs) with efficiencies greater than $20\\%$ have been realized only with expensive organic hole-transporting materials. We demonstrate PSCs that achieve stabilized efficiencies exceeding $20\\%$ with copper(I) thiocyanate (CuSCN) as the hole extraction layer. A fast solvent removal method enabled the creation of compact, highly conformal CuSCN layers that facilitate rapid carrier extraction and collection. The PSCs showed high thermal stability under long-term heating, although their operational stability was poor. This instability originated from potential-induced degradation of the CuSCN/Au contact. The addition of a conductive reduced graphene oxide spacer layer between CuSCN and gold allowed PSCs to retain $>95\\%$ of their initial efficiency after aging at a maximum power point for 1000 hours under full solar intensity at $60^{\\circ}\\mathsf{C}$ . Under both continuous full-sun illumination and thermal stress, CuSCN-based devices surpassed the stability of spiro-OMeTAD–based PSCs. \n\nhe tailoring of the formation and composi1 tion of the absorber layer in organic-inorganic perovskite solar cells (PSCs) has resulted in certified power conversion efficiencies (PCEs) exceeding $20\\%$ (1, 2). These PCEs have been obtained while retaining the electron-selective $\\mathrm{TiO_{2}}$ layer and by using either spiro-OMeTAD [2,2′,7,7′- tetrakis(N,N-di-p-methoxyphenyl-amine)9,9′-spirobifluorene] or a polymer-based poly(triarylamine) (PTAA) as the hole-transporting material (HTM) (2, 3). However, the cost of these HTMs is prohibitively high for large-scale applications, and the archetype organic HTMs or their ingredients apparently are a factor in the long-term operational and thermal instability of the PSCs that use them (4). One strategy to combat these issues of cost and instability could be the use of inexpensive inorganic hole extraction layers, similar to the use of $\\mathrm{TiO}_{2}$ as an electron-transporting material $(5)$ . However, obtaining stable PCEs of ${>}20\\%$ with PSCs that use inorganic HTMs (such as NiO, CuI, $\\mathrm{Cs_{2}S n I_{6}}.$ and CuSCN) when subjected to light soaking under realistic operational conditions (i.e., at maximum power point and $60^{\\circ}\\mathrm{C}$ ) has remained a challenge (6–9). \n\nThe realization of efficiencies of ${>}20\\%$ from PSCs using inorganic HTMs remains a key goal that would foster the large-scale deployment of PSCs. Among various inorganic HTMs, CuSCN is an extremely cheap, abundant p-type semiconductor that exhibits high hole mobility, good thermal stability, and a well-aligned work function (10). It is intrinsically p-doped and transmits light across the entire visible and near-infrared spectral region, so it is also attractive for tandem cell applications where the PSC is placed on top of a semiconductor with a lower band gap (11). However, the stabilized PCE values reported with CuSCN lag far behind devices based on the standard spiro-OMeTAD. CuSCN deposition methods including doctor blading, electrodeposition, spin coating, and spray coating have been tried (9, 12–16). Of these, the solution-based bottom-up approaches are more facile; however, a critical issue associated with them is that most of the solvents in which CuSCN shows high solubility degrade the perovskite layer $(I7)$ . Because of the dearth of solvents that readily dissolve CuSCN but not the perovskites, an inverted device architecture has been used, albeit with moderate success (12). \n\nTo retain the mesoscopic $\\mathrm{TiO_{2}}$ -based normal device architecture, we developed a simple dynamic deposition method. Typically, we deposited a thin and uniform CuSCN layer on top of a $\\mathrm{CsFAMAPbI_{3-x}B r}_{x}$ $\\mathrm{{[FA=\\CH(NH_{2})_{2}^{+}}}$ , $\\mathrm{\\MA}\\ =\\$ $\\mathrm{CH_{3}N H_{3}}^{+}]$ perovskite layer. To do so without compromising the quality of the perovskite layer, we drop-cast a defined volume of CuSCN dissolved in diethyl sulfide (DES, $35~\\mathrm{mg/ml},$ ) in 2 to $3\\mathrm{~s~}$ while spinning the substrate at $5000~\\mathrm{rpm}$ (18). The structural features of this CuSCN layer were investigated by x-ray diffraction (XRD). CuSCN crystallizes generally in two polymorphs, $\\mathfrak{a}$ -CuSCN (19) and $\\upbeta$ -CuSCN (20, 21), where the latter exhibits polytypism (i.e., variation in layer stacking order). A comparison of the calculated powder XRD spectra and grazing incidence XRD data of CuSCN (Fig. 1A) shows that the dynamic deposition method yielded $\\upbeta$ -CuSCN. A broad reflection at $q=1.9\\textup{\\AA}^{-1}$ established the presence of different polytypes of $\\upbeta$ -CuSCN, predominantly 2H and 3R. Coherently scattering island sizes of 17 and $18~\\mathrm{nm}$ were estimated from the peak width of the (002) reflection of CuSCN deposited, respectively, on the glass and the perovskite film. To determine the domain orientation, we acquired grazing incidence wide-angle x-ray scattering (GIWAXS) data from CuSCN and CuSCN/perovskite films (Fig. 1, B and C). The intensity distribution of the (002) $\\upbeta$ -CuSCN ring (fig. S1) reveals that the CuSCN domains have preferential orientation, with the long unit cell axis parallel to the substrate (Fig. 1, D and E). \n\nScanning electron microscopy (SEM) images of the perovskite film acquired before (Fig. 2A) and after (Fig. 2B) the deposition of a CuSCN layer revealed the homogeneous coverage of the perovskite overlayer with the CuSCN layer. By comparison, for a spiro-OMeTAD layer deposited via the conventional spin-coating method, the presence of pinholes was evident (fig. S2), which could be detrimental to performance (22). To evaluate the thickness of various layers, we acquired a crosssectional SEM image (Fig. 2C) of the complete device, which established the formation of a thin CuSCN layer $(\\sim60\\mathrm{nm}),$ ) sandwiched between a perovskite overlayer and a gold layer. Because DES is a strong solvent, it could damage the underlying perovskite layer (fig. S3). Thus, we used a dynamic deposition approach in which the solvent evaporated more rapidly than in conventional deposition. \n\nTo investigate the charge carrier dynamics in pristine and HTM-containing perovskite films, we used steady-state photoluminescence (PL) and time-correlated single-photon counting (TCSPC) spectroscopy. The pristine perovskite film exhibited an intense PL emission centered around $773~\\mathrm{nm}$ with a linewidth of $44\\ \\mathrm{nm}$ (Fig. 2D). In the presence of a charge extraction layer, the PL of the pristine perovskite film was strongly quenched, from which very rapid extraction of electrons or holes across the interfaces could be inferred (23). We used TCSPC spectroscopy to estimate the dynamics of charge carriers quantitatively (Fig. 2E). The long lifetime of the charge carriers $(\\uptau_{10}=390~\\mathrm{ns}^{\\cdot}$ ) is indicative of the high electronic quality of the pristine perovskite film $\\scriptstyle\\cdot_{10}$ is the time at which the initial PL intensity decreases by a factor of 10) (24). In agreement with the steady-state PL, the charge carrier lifetime decreased sharply in the perovskite films containing $\\mathrm{TiO}_{2}$ $\\dot{\\tau}_{10}=49$ ns) as the electron extraction layer and spiro-OMeTAD ( $\\mathrm{\\tilde{\\it{r}}_{10}=22}$ ns) or CuSCN $_{\\tau_{10}}=16$ ns) as the hole extraction layer (25 ). In comparison, the hole injection from the valence band of perovskite into the highest occupied molecular orbital (HOMO) or valence band of HTM was more rapid than the electron injection from the conduction band of perovskite into that of $\\mathrm{TiO_{2}}$ (26). In addition, TCSPC spectroscopy showed that the hole transfer was faster across the perovskite-CuSCN junction relative to the perovskite–spiro-OMeTAD interface, although the thermodynamic driving force (difference between the two energy levels) is lower at the perovskite-CuSCN interface (27 ). This difference could be explained by considering that there are stronger interfacial interactions between the perovskite and CuSCN than between the perovskite and the organic layer. \n\n![](images/29257f366517a12c567b81f72e16e930937459b243e44108fd7944dd20fbfc26.jpg) \nFig. 1. Structural characterization of CuSCN films coated on glass or pe- data obtained from a CuSCN film coated on a glass substrate. (C) GIWAXS data rovskite. (A) Grazing incidence XRD data acquired from a pure CuSCN film obtained from a CuSCN film coated on a perovskite layer. In (C), the (002) coated on glass, CuSCN coated on perovskite $\\bar{\\mathsf{T i O}}_{2},$ /fluorine-doped tin oxide reflection is visible; other reflections are superimposed with more intense (FTO), and bare perovskite/ $\\mathsf{T i O}_{2}$ /FTO. At the bottom, calculated powder reflections from the perovskite film. (D and E) The preferential out-of-plane diffraction data from CuSCN are shown for comparison. Indexing of the CuSCN orientation of CuSCN (the in-plane orientation is rotated by $90^{\\circ}.$ ). Color code: red, pattern is performed according to the CuSCN 2H $\\upbeta$ -structure. (B) GIWAXS copper atoms; yellow, sulfur atoms; gray, carbon atoms; blue, nitrogen atoms. \n\n![](images/e3bc79bec91732baeccff4d22c859c1c89de7dc6098e051e1c422acc23ca32be.jpg) \nFig. 2. Morphological characterization and steady-state and time-resolved photoluminescence studies. (A) Top-view SEM image of the perovskite film deposited onto mesoporous $\\mathsf{T i O}_{2}$ ; perovskite grains are visible. (B) Top-view SEM image showing the formation of a uniform CuSCN layer deposited onto the perovskite film. (C) Cross-sectional SEM image displaying the thickness of different layers of the complete device. (D) Steady-state PL spectra showing strong quenching of intense PL exhibited by the pristine perovskite film. (E) TCSPC spectra showing long-lasting charge carriers in the pristine perovskite film and the very rapid injection of charges from the perovskite film into the electron and hole extraction layers. Color code is the same as in (D). \n\n![](images/a2b5f2094c268de85519882578bc0ba35d022f10c0fcd2861678e8a19384656e.jpg) \n\nApart from injection, the transport of charges through the HTM layer is another critical process that strongly influences overall device performance. In fully assembled devices, hole mobilities of $1.4\\times10^{-6}\\mathrm{cm^{2}V^{-1}s^{-1}}$ and $1.2\\times10^{-3}\\mathrm{cm^{2}V^{-1}s^{-1}}$ were assessed for spiro-OMeTAD and CuSCN, respectively, by using photo charge extraction and linearly increasing voltage. With similar charge separation and recombination dynamics in the perovskite, CuSCN’s higher hole mobility (by about three orders of magnitude) and thinner layer offer a distinct advantage over spiro-OMeTAD, enabling CuSCN to be effective in its pristine form, whereas spiro-OMeTAD requires a high concentration of p-dopant and other additives (such as organic lithium salt and 4-tert-butylpyridine) to reach its peak performance (28). \n\n![](images/b5e2b384fddd16ef5fb8acf77d7c2c99b480ae04ee4bc28f772799ed73511ba6.jpg) \nFig. 3. Photovoltaic characterization of devices based on spiro-OMeTAD and CuSCN holetransporting layers. (A) $J-V$ curve of the spiro-OMeTAD–based device recorded at a scan rate of $0.01\\lor{\\mathsf{s}}^{-1}$ ; the inset shows the open-circuit voltage $V_{\\mathrm{OC}}$ as a function of illumination intensity with an ideality factor of 1.46. (B) $J-V$ curve of the CuSCN-based device recorded at a scan rate of $0.01\\lor\\mathsf{s}^{-1}$ ; the inset shows the $V_{\\mathrm{OC}}$ as a function of illumination intensity with an ideality factor of 1.50. (C) $J-V$ metrics for 20 independent devices based on spiro-OMeTAD and CuSCN with an illumination area of $0.16~\\mathsf{c m}^{2}$ . $J_{\\mathsf{S C}}$ , short-circuit current; FF, fill factor; PCE, power conversion efficiency. (D) Maximum power point tracking for $60~\\mathsf{s}$ , yielding stabilized efficiencies of $20.5\\%$ and $20.2\\%$ , respectively, for spiro-OMeTAD–based and CuSCN-based devices. (E) EQE as a function of monochromatic wavelength recorded for spiro-OMeTAD–based and CuSCN-based devices; also shown are integrated current densities obtained from the respective EQE spectra. (F) Operational stability of an unencapsulated CuSCN-based device with and without a thin layer of rGO (as a spacer layer between CuSCN and gold layers), examined at a maximum power point under continuous full-sun illumination at $60^{\\circ}\\mathrm{C}$ in a nitrogen atmosphere. \n\nAfter the successful deposition of the thin and conformal $\\upbeta$ -CuSCN layer, we investigated the photovoltaic (PV) characteristics of the devices. The PV parameters extracted from the currentvoltage $(J{-}V)$ curve (Fig. 3A) of the spiro-OMeTAD– based device yielded a short-circuit current $J_{\\mathrm{SC}}={}$ \n\n$23.35~\\mathrm{mA~cm^{-2}}$ , an open-circuit voltage $V_{\\mathrm{OC}}=$ $\\mathrm{{1137mV}_{\\mathrm{{i}}}}$ , and a fill factor $\\mathrm{FF}=77.5\\%$ , resulting in a PCE of $20.8\\%$ . The device with CuSCN as HTM and reduced graphene oxide (rGO) as a spacer layer yielded $J_{\\mathrm{SC}}=23.24\\mathrm{mAcm^{-2}}$ , $V_{\\mathrm{OC}}=1112\\ensuremath{\\mathrm{mV}}_{;}$ , and $\\mathrm{FF=78.2\\%}$ , resulting in a PCE of $20.4\\%$ (Fig. 3B) (the role of rGO is discussed below). As evident from the hysteresis index values, a hysteresis effect was discernable for spiro-OMeTAD by comparing the forward and backward $J_{-}V$ scan, but it was negligible for CuSCN (Fig. 3C) (29). Figure 3, A and B, shows that the $V_{\\mathrm{OC}}$ yielded by CuSCN-based devices was slightly lower than that yielded by spiro-OMeTAD–based devices. To understand the cause of the $V_{\\mathrm{OC}}$ deficit in CuSCNbased devices, we estimated the ideality factor $(n)$ , which is an indicator of the dominant recombination mechanism occurring within a working device (30). By fitting the intensity dependence of the $V_{\\mathrm{OC}}$ curves (Fig. 3, A and B, insets) [(18), equation S1], we estimated $n=1.46$ and 1.50, respectively, for the spiro-OMeTAD–based and CuSCN-based devices, which indicates that the difference in the $V_{\\mathrm{OC}}$ stemmed from marginally higher monomolecular recombination occurring within the CuSCN-based devices. $J_{\\mathrm{SC}}$ showed linear behavior with illumination intensity in both PSCs (fig. S4). \n\nFigure 3C summarizes the statistical analysis of PV parameters extracted from the $J_{-}V$ curves of 20 independent devices. The high PCEs were reproducible for both spiro-OMeTAD–based and CuSCN-based PSCs. For the CuSCN-based devices, we observed an average $J_{\\mathrm{SC}}=22.65\\pm0.60\\mathrm{mAcm^{-2}}$ , $V_{\\mathrm{OC}}=1090~\\pm~14~\\mathrm{mV}_{;}$ , and $\\mathrm{FF}=0.75\\pm0.02$ , resulting in an average PCE of $19.22~\\pm~0.84\\%$ . Similarly, for the spiro-OMeTAD–based devices, we observed an average $J_{\\mathrm{SC}}=22.6\\pm0.55\\mathrm{mAcm^{-2}}$ , $V_{\\mathrm{OC}}=1115\\pm15~\\mathrm{mV}_{;}$ , and $\\mathrm{FF}=0.75\\pm0.02$ , resulting in an average PCE of $19.6\\pm0.77\\%$ . To determine the stabilized (scan speed–independent) PCEs, we probed the solar cells at their maximum power point under full-sun illumination (Fig. 3D). We recorded a stabilized output power corresponding to a PCE of $20.5\\%$ and $20.2\\%$ for spiro-OMeTAD–based and CuSCN-based devices, respectively, in close agreement with the $J_{-}V$ measurements. The integrated photocurrent densities obtained from the external quantum efficiency (EQE) spectra of spiroOMeTAD–based and CuSCN-based devices agreed closely with those obtained from the $J_{-}V$ curves (Fig. 3E), indicating that any spectral mismatch between our simulator and AM-1.5 standard solar radiation was negligible. \n\nThe long-term thermal stability of devices at high temperature has become a key problem, primarily because the diffusion of metal through a spiro-OMeTAD layer at higher temperatures leads to the degradation of the devices (22). We examined the thermal stability of CuSCN-based devices coated with a thin layer of poly(methyl methacrylate) polymer (18) at $85^{\\circ}\\mathrm{C}$ in ambient conditions in the dark. After 1000 hours, the CuSCN-based devices retained ${>}85\\%$ of their initial efficiency (fig. S5). The formation of a uniform CuSCN film, as evident from morphological analysis, blocked the metal diffusion (22). Long-term operational stability is a crucial requirement for future exploitations of PSC-based technology (31). Under fullsun illumination at their maximum power point, the CuSCN devices (fig. S6) showed poor photostability, losing ${>}50\\%$ of their initial efficiency within 24 hours (Fig. 3F, red trace). Such instability of PSCs has been associated with the degradation of the CuSCN/perovskite interface $(I4)$ , but atomic layer deposition of an insulating $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ layer $\\cdot{\\sim}2\\ \\mathrm{nm})$ between the perovskite and CuSCN layers did not mitigate the initial degradation (fig. S7). Instead, we introduced a thin conductive rGO spacer layer (fig. S8) between the CuSCN and gold layers, leading to excellent operational stability under full-sun illumination at $60^{\\circ}\\mathrm{C}$ . The resulting PSCs retained ${>}95\\%$ of their initial efficiency after aging for 1000 hours, apparently surpassing the stability of spiro-OMeTAD devices recorded under similar conditions (fig. S9). \n\nWe traced the photoeffect back to the positive electrical polarization imposed on the gold when the CuSCN device is illuminated at its maximum power point or under open circuit conditions. We confirmed the occurrence of potential-induced degradation by applying a positive bias of $0.8\\mathrm{V}$ to the Au contact of a CuSCN device in the dark. The results (fig. S10) illustrate the severe loss in PV performance under these conditions. When no electrical bias was applied to the cell during aging in the dark, no appreciable degradation was observed even after prolonged heating of the CuSCN devices at $85^{\\circ}\\mathrm{C}$ (fig. S5). Thus, we identify the cause of the degradation to be an electrical potential–induced reaction of gold with the thiocyanate anions forming an undesired barrier, which is different from the degradation occurring at the interfaces between perovskite and selective contacts (32). Using x-ray photoelectron spectroscopy (XPS), we confirmed the oxidation of gold (fig. S11) upon subjecting the CuSCN devices to the light soaking test over extended time periods. We conclude that the instability of PSCs is not associated with the degradation of CuSCN/perovskite interface, as is generally believed, but rather originates mainly from the CuSCN/Au contact. The CuSCN film did not require any additives to function as an effective HTM, in contrast to PTAA and spiroOMeTAD, which can reach their peak performance only in the presence of organic lithium salt and 4-tert-butylpyridine and, for the latter, also a Co(III) complex that acts as a p-dopant (4); these additives readily cross into the photoactive PSC layer and adversely affect PV performance. Our results show that PSCs using all-inorganic charge extraction layers (i.e., mesoporous $\\mathrm{TiO_{2}}$ and CuSCN) display high PCE values combined with remarkable operational and thermal stability, offering the potential for large-scale deployment. \n\n# REFERENCES AND NOTES \n\n1. A. Kojima, K. Teshima, Y. Shirai, T. Miyasaka, J. Am. Chem. Soc. 131, 6050–6051 (2009). \n2. W. S. Yang et al., Science 356, 1376–1379 (2017). \n3. H. Tan et al., Science 355, 722–726 (2017). \n4. J. Liu et al., Energy Environ. Sci. 7, 2963–2967 (2014). \n5. H.-S. Kim et al., Sci. Rep. 2, 591 (2012). \n6. W. Chen et al., Science 350, 944–948 (2015). \n7. J. A. Christians, R. C. M. Fung, P. V. Kamat, J. Am. Chem. Soc. 136, 758–764 (2014). \n8. I. Chung, B. Lee, J. He, R. P. H. Chang, M. G. Kanatzidis, Nature 485, 486–489 (2012). \n9. P. Qin et al., Nat. Commun. 5, 3834 (2014). \n10. J. E. Jaffe et al., J. Phys. Chem. C 114, 9111–9117 (2010). \n11. J. W. Jung, C.-C. Chueh, A. K. Y. Jen, Adv. Energy Mater. 5, 1500486 (2015). \n12. S. Ye et al., Nano Lett. 15, 3723–3728 (2015). \n13. M. Jung et al., ChemSusChem 9, 2592–2596 (2016). \n14. J. Liu et al., Adv. Mater. Interfaces 3, 1600571 (2016). \n15. S. Ye et al., Adv. Mater. 28, 9648–9654 (2016). \n16. V. E. Madhavan et al., ACS Energy Lett. 1, 1112–1117 (2016). \n17. N. Yaacobi-Gross et al., Adv. Energy Mater. 5, 1401529 (2015). \n18. See supplementary materials. \n19. M. Kabešová, M. Dunaj-jurčo, M. Serator, J. Gažo, J. Garaj, Inorg. Chim. Acta 17, 161–165 (1976). \n20. D. L. Smith, V. I. Saunders, Acta Crystallogr. B 37, 1807–1812 (1981). \n21. D. L. Smith, V. I. Saunders, Acta Crystallogr. B 38, 907–909 (1982). \n22. Y. Han et al., J. Mater. Chem. A 3, 8139–8147 (2015). \n23. S. D. Stranks et al., Science 342, 341–344 (2013). \n24. L. Kong et al., Proc. Natl. Acad. Sci. U.S.A. 113, 8910–8915 (2016). \n25. M. I. Dar et al., Sci. Adv. 2, e1601156 (2016). \n26. G. Xing et al., Science 342, 344–347 (2013). \n27. K. Pydzińska et al., ChemSusChem 9, 1647–1659 (2016). \n28. W. H. Nguyen, C. D. Bailie, E. L. Unger, M. D. McGehee, J. Am. Chem. Soc. 136, 10996–11001 (2014). \n29. H.-S. Kim, N.-G. Park, J. Phys. Chem. Lett. 5, 2927–2934 (2014). \n30. K. Tvingstedt et al., Sci. Rep. 4, 6071 (2014). \n31. F. Bella et al., Science 354, 203–206 (2016). \n32. J. Carrillo et al., Adv. Energy Mater. 6, 1502246 (2016). \n\n# ACKNOWLEDGMENTS \n\nAuthor contributions: N.A., M.I.D., and M.G. conceived the idea of the work; N.A. and M.I.D. designed the project and fabricated and characterized devices; M.I.D. and N.A. performed PL and SEM analysis; N.A., M.I.D., and A.H. performed the XRD measurements; A.H. and F.S. analyzed and discussed the XRD data; N.P. carried out hole mobility experiments; N.P. and M.I.D. performed light soaking measurements; M.I.D. wrote the manuscript; all the authors contributed toward finalizing the draft; S.M.Z. coordinated the project; and M.G. directed and supervised the research. Supported by Greatcell Solar SA (N.A.) and by the European Union’s Horizon 2020 program through a Future Emerging Technologies (FET)–Open Research and Innovation action under grant agreement 687008 and Graphene Flagship Core1 under grant agreement 696656 (M.I.D., S.M.Z., and M.G.). We thank the European Synchrotron Radiation Facility for provision of synchrotron radiation, A. Chumakov and F. Zontone for assistance in using beamline ID10, J. Hagenlocher for assistance with XRD analysis, M. Mayer for assistance with ALD, F. Giordano and P. Yadav for helpful discussions, and P. Mettraux (Molecular and Hybrid Materials Characterization Center, EPFL) for carrying out XPS measurements. All results are presented in the main paper and supplement. We have applied for a patent on inorganic hole conductor–based PSCs with high operational stability. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/358/6364/768/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S11 \nTable S1 \nReferences (33, 34) \n\n16 December 2016; resubmitted 4 August 2017 \nAccepted 14 September 2017 \nPublished online 28 September 2017 \n10.1126/science.aam5655 \n\n# Science \n\n# Perovskite solar cells with CuSCN hole extraction layers yield stabilized efficiencies greate than $20\\%$ \n\nNeha Arora, M. Ibrahim Dar, Alexander Hinderhofer, Norman Pellet, Frank Schreiber, Shaik Mohammed Zakeeruddin and Michael Grätzel \n\nScience 358 (6364), 768-771. DOI: 10.1126/science.aam5655originally published online September 28, 2017 \n\n# Transporter layers improve stability \n\nAlthough perovskite solar cells can have power conversion efficiencies exceeding $20\\%$ , they can have limited thermal and ultraviolet irradiation stability. This is in part because of the materials used to extract the charge carriers (electrons and holes) from the active layer. Arora et al. replaced organic hole transporter layers with CuCSN to improve thermal stability. Device lifetime was enhanced when a conducting reduced graphene oxide spacer was added between the CuSCN layer and the gold electrode. \n\nScience, this issue p. 768 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/358/6364/768 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2017/09/27/science.aam5655.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/358/6364/732.full http://science.sciencemag.org/content/sci/358/6364/734.full http://science.sciencemag.org/content/sci/358/6364/739.full http://science.sciencemag.org/content/sci/358/6364/745.full http://science.sciencemag.org/content/sci/358/6364/751.full http://science.sciencemag.org/content/sci/358/6367/1192.full \n\nREFERENCES \n\nThis article cites 33 articles, 8 of which you can access for free http://science.sciencemag.org/content/358/6364/768#BIBL \n\nPERMISSIONS \n\nhttp://www.sciencemag.org/help/reprints-and-permissions \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41467-017-01050-0", + "DOI": "10.1038/s41467-017-01050-0", + "DOI Link": "http://dx.doi.org/10.1038/s41467-017-01050-0", + "Relative Dir Path": "mds/10.1038_s41467-017-01050-0", + "Article Title": "Hollow MnO2 as a tumor-microenvironment-responsive biodegradable nullo-platform for combination therapy favoring antitumor immune responses", + "Authors": "Yang, GB; Xu, LG; Chao, Y; Xu, J; Sun, XQ; Wu, YF; Peng, R; Liu, Z", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Herein, an intelligent biodegradable hollow manganese dioxide (H-MnO2) nullo-platform is developed for not only tumor microenvironment (TME)-specific imaging and on-demand drug release, but also modulation of hypoxic TME to enhance cancer therapy, resulting in comprehensive effects favoring anti-tumor immune responses. With hollow structures, H-MnO2 nulloshells post modification with polyethylene glycol (PEG) could be co-loaded with a photodynamic agent chlorine e6 (Ce6), and a chemotherapy drug doxorubicin (DOX). The obtained H-MnO2-PEG/C&D would be dissociated under reduced pH within TME to release loaded therapeutic molecules, and in the meantime induce decomposition of tumor endogenous H2O2 to relieve tumor hypoxia. As a result, a remarkable in vivo synergistic therapeutic effect is achieved through the combined chemo-photodynamic therapy, which simultaneously triggers a series of anti-tumor immune responses. Its further combination with checkpoint-blockade therapy would lead to inhibition of tumors at distant sites, promising for tumor metastasis treatment.", + "Times Cited, WoS Core": 1240, + "Times Cited, All Databases": 1274, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000412860100002", + "Markdown": "# Hollow MnO2 as a tumor-microenvironmentresponsive biodegradable nano-platform for combination therapy favoring antitumor immune responses \n\nGuangbao Yang1, Ligeng $\\mathsf{X}\\mathsf{u}^{1}$ , Yu Chao1, Jun $\\mathsf{X}\\mathsf{u}^{1}$ , Xiaoqi Sun1, Yifan Wu1, Rui Peng1 & Zhuang Liu \n\nHerein, an intelligent biodegradable hollow manganese dioxide $\\left(\\mathsf{H}-\\mathsf{M}\\mathsf{n}\\mathsf{O}_{2}\\right)$ ) nano-platform is developed for not only tumor microenvironment (TME)-specific imaging and on-demand drug release, but also modulation of hypoxic TME to enhance cancer therapy, resulting in comprehensive effects favoring anti-tumor immune responses. With hollow structures, ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ nanoshells post modification with polyethylene glycol (PEG) could be co-loaded with a photodynamic agent chlorine e6 (Ce6), and a chemotherapy drug doxorubicin (DOX). The obtained H-MnO2-PEG/C&D would be dissociated under reduced pH within TME to release loaded therapeutic molecules, and in the meantime induce decomposition of tumor endogenous $H_{2}O_{2}$ to relieve tumor hypoxia. As a result, a remarkable in vivo synergistic therapeutic effect is achieved through the combined chemo-photodynamic therapy, which simultaneously triggers a series of anti-tumor immune responses. Its further combination with checkpoint-blockade therapy would lead to inhibition of tumors at distant sites, promising for tumor metastasis treatment. \n\nTtchuoer etdudmweoiptrhivmvaiatcisorconue,lnlrvoiarwb tured with vascular abnormalities, high lactate levels, glu- mnvata (tuiTesM, Eha)in,gdhwlhaiyctphaotxiesale1o–vft5e,eln,i g auan$\\mathsf{p H}$ important factor that largely affects the therapeutic outcomes in many conventional cancer therapies6–11. Moreover, it also been discovered that the unique features of TME may greatly limit the killing functions of cytotoxic T lymphocytes and promote the immunosuppression by multiple kinds of cells like myeloidderived suppressor cells (MDSC), M2 tumor-associated macrophages (TAM), and regulatory T cells (Treg) within tumors, all of which are unfavorable for cancer treatment12, 13. Hence, designing nanoscale drug delivery systems (nano-DDSs) that are able to be responsive to the inherent features of TME has been proposed to be a promising approach to realized tumor-specific cancer treatment14–16. For instance, many smart nano-DDSs are able to release their payloads, or show reduced sizes/converted charges under TME conditions (e.g., reduced pH, hypoxia, tumor-specific enzymes, etc.), so as to realize improved therapeutic specificity and efficacy17–19. On the other hand, it has been proposed that by modulating the TME inside solid tumors, the therapeutic responses of those tumors to various types of cancer therapies may be significantly enhanced20–22. Therefore, designing TMEresponsive and TME-modulating nano-DDSs may be of great interests for new generations of cancer combination therapies. \n\nIn recent years, $\\mathrm{MnO}_{2}$ nanostructures have attracted substantial attention as a unique type of TME-responsive theranostic agents23, 24. It has been found that $\\mathrm{MnO}_{2}$ nanostructures would be decomposed by reaction with either $\\mathrm{H^{+}}$ or glutathione (GSH) existing within the TME, generating $\\mathrm{Mn}^{2+}$ ions that are able to significantly enhance T1-magnetic resonance (MR) imaging contrast for tumor-specific imaging and detection25–28. Meanwhile, $\\mathrm{MnO}_{2}$ nanostructures are able to trigger the decomposition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ existing in the TME into water and oxygen, so as to relieve tumor hypoxia29–31. Such an effect has been found to be able to enhance a number of cancer therapies such as radiotherapy and photodynamic therapy (PDT) in which oxygen is actively involved in the treatment process23, 28, 29, 32, 33. Moreover, as $\\mathrm{MnO}_{2}$ nanoparticles could be decomposed to harmless water-soluble $\\bar{{\\bf M}}{\\bf n}^{2+}$ ions that are rapidly excreted by kidneys, there should be no long-term toxicity concerns for $\\mathrm{MnO}_{2}$ nanostructures when they are used for in vivo applications, unlike many other non-biodegradable inorganic nanomaterials23, 29. However, most of previously reported $\\mathrm{MnO}_{2}$ nanostructures are nanoparticles, nanosheets, or nanocomposites incorporated with other types of nanoparticles, and may not be ideal to realize the most effective drug loading as well as precisely controlled release of therapeutic payloads32, 34. Hollow nanostructures with mesoporous shells (e.g., hollow mesoporous silica) and large cavities have been demonstrated to be excellent drug loading/delivery systems to load high quantities of therapeutic agents, whose release may be precisely controlled by tuning the shell structures or coatings35, 36. However, hollow $\\mathrm{MnO}_{2}$ nanostructures as smart DDs have not yet been reported to our best knowledge. \n\nHerein, we therefore for the first time design an intelligent theranostic platform based on hollow mesoporous $\\mathrm{MnO}_{2}$ (H$\\mathrm{MnO}_{2}^{\\cdot}$ ) nanoshells for tumor-targeted drug delivery, ultrasensitive pH-triggered controllable release, and TME-responsive generation of oxygen to overcome tumor hypoxia, so as to achieve tumor-specific enhanced combination therapy under the guidance of $\\mathrm{\\pH}$ -responsive MR imaging. In this system, mesoporous $\\mathrm{MnO}_{2}$ shells were grown on silica nanoparticles, which were then removed by gentle etching. The obtained $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ with hollow structures are functionalized with polyethylene glycol (PEG), yielding $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG nanoparticle with great physiological stability. A photosensitizer, chlorine e6 (Ce6), and an anti-cancer drug, doxorubicin (DOX), can be co-loaded into this hollow $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG nano-platform with high loading capacities (H$\\mathrm{MnO}_{2}$ -PEG/C&D). Under acidic $\\mathsf{p H}$ the fast break-up of $\\mathrm{MnO}_{2}$ nanoshells would lead to release of loaded drugs, and simultaneously result in significantly enhanced T1-contrast under MR imaging. After systemic injection of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D into tumor-bearing mice, strong Ce6 fluorescence and T1-weighted MR signals appear in both tumors and kidneys, suggesting efficient passive tumor homing of those nanoparticles, as well as their rapid renal filtration after being decomposed. Meanwhile, owing to $\\mathrm{MnO}_{2}$ -triggered in-situ generation of oxygen from tumor endogenous $\\mathrm{H}_{2}\\mathrm{O}_{2}.$ , the tumor oxygenation level is greatly improved. Great in vivo synergistic therapeutic effect is then achieved after combining chemotherapy and PDT with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG/C&D by a single treatment using a rather low dose. In addition, it is further discovered that combination therapy with this novel agent also could effectively induce anti-tumor immunities, which with the help of programmed death-ligand 1 (PD-L1) checkpoint blockade37 could inhibit tumor growth at distant sites spared from light exposure via a remarkable abscopal effect. Our work highlights the great promise of modulating TME with smart nano-systems to enhance the efficacies of various types of therapies to achieve a comprehensive effect in fighting cancers. \n\n# Results \n\nSynthesis and characterization of $\\mathbf{H}\\mathbf{-}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ -PEG. The procedure for the synthesis of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D is illustrated in Fig. 1a. Firstly, monodispersed silica nanoparticles were synthesized by hydrolyzation of tetraethyl orthosilicate (TEOS) and then utilized immediately as the hard template. A uniform layer of mesoporous $\\mathrm{MnO}_{2}$ was grown on the surface of as-made silica nanoparticles by simply mixing them with manganese permanganate $\\mathrm{(KMnO_{4})}$ , which was reduced by unreacted organosilica existing on those freshly prepared silica nanoparticles. The hollow mesoporous $\\mathrm{MnO}_{2}^{\\cdot}$ $\\bar{(\\mathrm{H}\\mathrm{-}\\mathrm{MnO}_{2})},$ nanoshells were obtained after incubating $\\mathrm{MnO}_{2}@\\mathrm{SiO}_{2}$ nanoparticles with a ${\\mathrm{Na}}_{2}{\\mathrm{CO}}_{3}$ solution to dissolve silica. To enhance their water solubility and physiological stability, $\\mathrm{\\mathrm{H}}{\\mathrm{-MnO}}_{2}$ nanoshells were modified with PEG through a layer-by-layer (LBL) polymer-coating method. In this process, asmade $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ nanoshells with negative charges were coated subsequently with a cationic polymer poly (allylamine hydrochloride) (PAH), and then an anionic polymer poly (acrylic acid) (PAA) through electrostatic interactions. Amino-terminated PEG 1 $\\mathrm{NH}_{2}$ -PEG) was then conjugated to the surface of PAA-coated H$\\mathrm{MnO}_{2}$ nanoshells via amide formation, producing $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG nanoshells. Lastly, the photosensitizer chlorine e6 (Ce6) and anticancer drug doxorubicin (DOX) were simultaneously loaded into the hollow structure of $_{\\mathrm{H-MnO}_{2}}$ -PEG nanoshells, yielding H$\\mathrm{MnO}_{2}$ -PEG/C&D, which was used for further experiments. \n\nTransmission electron microscope (TEM) images of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG nanoshells clearly revealed the spherical morphology and the hollow structure of our product (Fig. 1b). The thickness of such $\\mathrm{MnO}_{2}$ shell was measured to be ${\\sim}15\\mathrm{nm}$ (Fig. 1c). The hollow structure of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG nanoshells was further confirmed by the high-angle annular dark-field scanning TEM (HHAADF-STEM)-based elemental mapping (Fig. 1d). In the process of surface functionalization, the step-wise altered zeta potentials indicated successful LBL coating of polymers on those nanoparticles (Supplementary Fig. 1). With surface PEG coating, $_{\\mathrm{H-MnO}_{2}}$ -PEG could be dispersed in different physiological buffers without any aggregation over time (Supplementary Fig. 2). Such a strategy could be scaled-up for gram-scale production of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ nanoshells with high quality in one reaction batch (Fig. 1e–g). \n\npH-dependent nanoparticle decomposition and drug behaviors. Manganese dioxide $(\\mathrm{MnO}_{2})$ is known to be stable under neutral and basic $\\mathsf{p H}$ , but can be decomposed into $\\mathrm{Mn}^{2+}$ under reduced $\\mathsf{p H}$ values38. Therefore, TEM images of $_{\\mathrm{H-MnO}_{2}}$ -PEG after incubation in phosphate-buffered saline (PBS) with different $\\mathrm{\\DeltapH}$ values (7.4 and 5.5) for various treated time were recorded (Fig. 2a). The morphology of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG nanoshells showed no significant change in $\\mathrm{pH}7.4$ solution after $^{8\\mathrm{h}}$ , indicating that $_{\\mathrm{H-MnO}_{2}}$ -PEG nanoshells were stable in the neutral environment. However, $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG exhibited time-dependent degradation behavior in acidic solutions due to the decomposition of $\\mathrm{MnO}_{2}$ into $\\mathrm{Mn}^{2+}$ ions. The degradation rates could be determined by the decrease of $\\mathrm{MnO}_{2}$ -characteristic absorbance band (Fig. 2b; Supplementary Fig. 3), which appeared to be stable under $\\mathrm{pH}7.4$ but decreased rapidly under $\\mathrm{pH}~6.5$ and 5.5, further demonstrating the ultrasensitive pH-responsive degradation behavior of H$\\mathrm{MnO}_{2}$ -PEG. \n\nThe surface area and average pore diameter of $_\\mathrm{H-MnO}_{2}$ -PEG were determined to be $360\\mathrm{m}^{2}\\mathrm{g}^{-1}$ and $3.94\\mathrm{nm}$ , respectively, by Brunauer–Emmett–Teller (BET) measurement (Fig. 2c). The hollow structure of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG with mesoporous shells is expected to be ideal for efficient drug loading. To employ $\\mathrm{MnO}_{2}$ nanoshells for PDT application, the photosensitizer Ce6 was loaded into $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG by incubating those nanoshells with different concentrations of free Ce6 under ultrasonication and stirring at room temperature. After removal of excess Ce6, UV–vis spectra were recorded to determine the Ce6-loading capacities. At the feeding weight ratio $(\\mathrm{Ce}6\\colon\\mathrm{MnO}_{2})$ of 3:1, the $\\mathrm{Ce}6$ loading researched a rather high ratio of $88.9\\%$ (Ce6: $\\mathrm{MnO}_{2}^{\\cdot}$ ) (Fig. 2d). In this system, DOX, a commonly anti-cancer drug was also loaded into the hollow structure of nanoshells. For DOX loading, $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG was mixed with different concentrations of DOX in dark for $12\\mathrm{h}$ . The DOX loading increased with increasing added DOX and achieved the maximal level at $86.1\\%$ . Lastly, Ce6 and DOX also could simultaneously loaded into the hollow structure of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG nanoshells, obtaining dualdrug co-loaded $\\mathrm{\\mathrm{H}}{\\mathrm{-}}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D nanoparticles for combination therapy (Fig. 2e). \n\nThe drug release behaviors of Ce6 and DOX from $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG/C&D were then studied in solutions at different $\\mathrm{\\pH}$ values (Fig. 2f). Compared with the slow drug-release profiles of $\\mathrm{~H~}$ - $\\mathrm{MnO}_{2}$ -PEG/C&D at $\\mathrm{pH}7.4$ , the release speeds of both Ce6 and DOX were found to be much faster in mild acidic solutions at pH 6.5 and $\\mathrm{pH}5.5$ , owing to the acidic triggered decomposition of H$\\mathrm{MnO}_{2}$ nanocarriers into $\\mathrm{Mn}^{2+}$ ions. \n\nIn vitro experiments with $\\mathbf{H}\\mathbf{-}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ -PEG/C&D. As uncovered in many previous studies, the hypoxic TME is responsible for the limited PDT efficacy for treatment of solid tumors as oxygen is an essential element in the process of $\\mathrm{PDT}^{39}$ , 40. Considering the existence of endogenous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ with concentrations in the range of $10{-}100\\upmu\\mathrm{M}$ inside most types of solid tumors41, we then tested the ability of our $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ as a catalyst to trigger the decomposition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ by using an oxygen probe to measure the dissolved $\\mathrm{O}_{2}$ after different concentrations of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG were added into $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solutions $(100\\upmu\\mathrm{M})$ . Although the dissolved $\\mathrm{O}_{2}$ level was stable in the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution without adding $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG nanoshells, we found that $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG could effectively trigger the fast production of $\\mathrm{O}_{2}$ from $\\mathrm{H}_{2}\\mathrm{O}_{2}$ by a $\\mathrm{MnO}_{2}$ concentration-dependent manner (Fig. 3b). \n\nThe singlet oxygen (SO) generated from Ce6 and $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG/C under $660–\\mathrm{nm}$ light irradiation in the presence of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was then monitored by a SO sensor green (SOSG) probe (Supplementary Fig. 4). As expected, no appreciable difference in SO production by free Ce6 under light exposure was observed regardless of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ addition $(100\\upmu\\mathrm{M})$ . Interestingly, after addition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , the light-triggered SO production of H$\\mathrm{MnO}_{2}–\\mathrm{PEG}/\\mathrm{C}$ was remarkably accelerated. Therefore, Ce6-loaded $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG is expected to be a more effective PDT agent under TME conditions with low oxygen and high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ contents23. \n\n![](images/93fb534f7cd4aaa9e82ce285d9734168c4528f550d448f5f332618d3c280e582.jpg) \nFig. 1 Synthesis and characterization of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG. a A scheme indicating the step-by-step synthesis of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG nanoparticles and the subsequent dual-drug loading. b, c A TEM image (b) and a magnified TEM image (c) of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG. d HAADF-STEM image and elemental mapping for ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ PEG. e A photo of the $500~\\mathrm{mL}$ reaction vessel for preparation of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ in a large scale. f Digital picture showing the gram-scale production of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ nanoshells in one reaction. g A representative TEM image of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ nanoshells prepared in the gram-scale \n\nNext, we ought to study the efficacy of $_{\\mathrm{H-MnO}_{2}}$ -PEG as a multifunctional DDS at the in vitro level (Fig. 3a). We firstly tested the cytotoxicity of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG in the dark (Supplementary Fig. 5). The standard methyl thiazolyl tetrazolium (MTT) assay indicated that $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG exhibited no obvious toxicity to 4T1 murine breast cancer cells even at high concentrations of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ up to $100\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ . \n\nTo evaluate the PDT efficiency of Ce6-loaded $_{\\mathrm{H-MnO}_{2}}$ -PEG, 4T1 cells were incubated with $\\mathrm{H}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}{\\cdot}\\mathrm{PEG}/\\mathrm{C}$ or free Ce6 in either $\\Nu_{2}$ or $\\mathrm{O}_{2}$ environment for $^{2\\mathrm{h}}$ . Those cells were then treated with $660\\mathrm{nm}$ light $(5\\mathrm{mW}\\mathrm{cm}^{-2}$ , $30\\mathrm{min}$ ). Twenty-four hours later, their relative viabilities were determined by the MTT assay (Fig. 3c). Both free Ce6 and H-MnO2-PEG/C showed high phototoxicity to cells within the oxygen atmosphere. In contrast, although the PDT-induced cell killing by free Ce6 under the nitrogen atmosphere was found to be much less effective, the light-triggered cancer cell-destruction efficiency of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG/C remained at high levels even under this hypoxic condition, likely owing to the additional supply of oxygen by $\\mathrm{MnO}_{2}$ -trigged decomposition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generated in situ by cancer cells. Therefore, different from conventional PDT, which is effective only under normoxic conditions, Ce6-loaded $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG could serve as an effective PDT agent even within the hypoxic environment. \n\nWe next used DOX and Ce6 co-loaded $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG $\\mathrm{\\RnO}_{2}$ -PEG/C&D) for in vitro combination treatment. 4T1 cells incubated with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D for different periods of time were then imaged by a confocal fluorescence microscope (Fig. 3d). Both DOX and Ce6 fluorescence inside cells significantly enhanced with prolonging of incubation time. Interestingly, although Ce6 fluorescence mostly maintained in the cells cytoplasm after incubation for $12\\mathrm{{h}},$ obvious accumulation of DOX inside cell nuclei was found over time, indicating the gradual intracellular DOX release from $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D after the break-up of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ nanocarriers within acidic lysosomes after cellular uptake of those nanoparticles. \n\nThe combined PDT and chemotherapy based on $\\mathrm{{H}}{\\cdot}\\mathrm{{MnO}}_{2}$ - PEG/C&D was then demonstrated by treating 4T1 cells with H$\\mathrm{MnO}_{2}$ -PEG/C plus light irradiation, $\\mathrm{H}{-}\\mathrm{Mn}\\mathrm{O}_{2}{\\mathrm{-}}\\mathrm{PEG}/\\mathrm{C}\\&\\mathrm{D}$ in dark, or $_{\\mathrm{H-MnO}_{2}}$ -PEG/C&D plus light. Cells for PDT treatment were exposed to the $660–\\mathrm{nm}$ light for $30\\mathrm{min}$ $\\mathrm{\\Omega}^{\\prime}5\\mathrm{mW}\\mathrm{cm}^{-2}.$ ) after they were incubated with nanoparticles for $^{2\\mathrm{h}}$ . The cell viabilities were determined by the MTT assay after incubation for another $24\\mathrm{h}$ (Fig. 3e). Compared with PDT alone $\\mathrm{(H}\\mathrm{-}\\ensuremath{\\mathrm{MnO}}_{2}$ -PEG/C plus light) or chemotherapy alone $\\mathrm{\\bf\\ddot{H}}{\\bf-M}{\\bf\\ddot{n}}{\\bf O}_{2}$ -PEG/C&D in dark), the combination therapy ( $_{\\mathrm{H-MnO}_{2}}$ -PEG/C&D plus light) was found to be the most effective in killing cancer cells by a synergistic manner under different drug concentrations. \n\nIn vivo and ex vivo imaging with $\\mathbf{H}\\mathbf{-}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ -PEG/C&D. After demonstrating the combination therapy function of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ - PEG/C&D in our in vitro experiments, we thus would like to test $_\\mathrm{H-MnO}_{2}$ -PEG/C&D in the animal tumor model. We firstly used in vivo fluorescence imaging to track those nanoparticles in 4T1 tumor-bearing Balb/c mice after intravenous (i.v.) injection of $_\\mathrm{H-MnO}_{2}$ -PEG/C&D (dose of $\\mathrm{MnO}_{2}=10\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{C}\\mathrm{\\dot{e}6=4.7m g\\mathrm{kg}^{-1}}$ , and $\\mathrm{DOX}=4.5\\mathrm{mg}\\mathrm{kg}^{-1};$ (Fig. 4a). The Ce6 fluorescence signals in the tumor region increased and reached a peak level at $\\textup{\\^{8h}}$ post injection, indicating the efficient tumor accumulation of those $_{\\mathrm{H-MnO}_{2}}$ -PEG/C&D. Semi-quantitative biodistribution based on ex vivo imaging of major organs and tumor collected from $24\\mathrm{h}$ post injection indicated the hightumor uptake of $_{\\mathrm{H-MnO}_{2}}$ -PEG/C&D (Fig. 4b, c). Notably, strong fluorescence of Ce6 found in kidneys of mice after injection of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D illustrated rapid renal clearance of Ce6 after decomposition of those nanoshells. \n\n![](images/2ec2e46b89724ad7a769a1a0289c67ce186b5b177fd581811a706f68c27a6ce8.jpg) \nFig. 2 pH-dependent nanoparticle decomposition and drug behaviors of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D. a TEM images of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG after incubation in buffers with different pHs (7.4 and 5.5) for various periods of time. b The degradation behavior of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG dispersed in different pH values (7.4, 6.5 and 5.5) determined by the absorbance of $\\mathsf{M n O}_{2}$ . c Pore-size distribution curve and ${\\sf N}_{2}$ adsorption/desorption isotherms (inset) of the ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG sample. d Ce6 and DOX-loading weight ratios in ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D at different feeding drug: $\\mathsf{M n O}_{2}$ ratios. e UV–vis-NIR spectra of free Ce6, DOX, ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG, and ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D. f Percentages of released Ce6 and DOX from ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D over time in the presence of $10\\%$ fetal bovine serum (FBS) at different pH values (7.4, 6.5, and 5.5). Date are presented as means $\\pm$ standard deviation (s.d.) $\\left(n=3\\right)$ \n\n![](images/effcb4c9d2b8f405d8e920b6d16c9fb13c91f01e7079fe125ab4c55949190861.jpg) \nFig. 3 In vitro experiments with ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D. a A scheme illustration of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D for pH-responsive drug delivery and oxygen-elevated PDT. b The $\\mathsf{O}_{2}$ concentration changes in $H_{2}O_{2}$ solutions ${\\mathrm{\\Omega}}^{\\mathrm{\\Omega}}(100\\upmu\\mathrm{{M}})$ after various concentrations of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D were added. c In vitro PDT treatment of 4T1 cells by free Ce6 or H ${\\tt-}M{\\tt n}{\\tt O}_{2}$ -PEG/C under 660-nm light irradiation $(5\\mathsf{m}\\mathsf{W}\\mathsf{c m}^{-2}$ for $30\\mathrm{min}$ ) in ${\\sf N}_{2}$ or $\\mathsf{O}_{2}$ atmospheres. d Confocal images of 4T1 cells treated with ${\\mathsf{H}}{\\cdot}{\\mathsf{M n O}}_{2}{\\cdot}{\\mathsf{P E G}}/{\\mathsf{C}}\\&{\\mathsf{D}}$ at different times points. Blue, green, and red represent DAPI, Ce6, and DOX fluorescence, respectively. e Relative viabilities of 4T1 cells after incubation with ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C with light irradiation, or ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D with or without 660-nm light irradiation $(5\\mathsf{m}\\mathsf{W}\\mathsf{c m}^{-2}$ , $30\\mathsf{m i n}\\dot{}$ ). Date are presented as means $\\pm\\thinspace s.0$ . $\\left(n=5\\right)$ ) \n\nIt is known that $\\mathrm{MnO}_{2}$ nanoparticles were stable under neutral and basic $\\mathsf{p H}$ , but would be decomposed into $\\mathrm{Mn}^{2+}$ and $\\mathrm{O}_{2}$ under acidic environment. As $\\mathrm{Mn}^{2\\mathrm{\\hat{+}}}$ with five unpaired $3d$ electrons is known to be a T1-shortening agent in MR imaging42, MR imaging of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D incubated in buffer solutions with different pHs (6 and 7.4) for $6\\mathrm{h}$ was conducted. The significant concentration-dependent brightening effect of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D samples were found in T1-MR images at $\\mathrm{\\pH}6$ , whereas the signals of nanoparticles in the neutral buffer solution appeared to be much weaker (Fig. 4d). Importantly, the r1 value (in terms of the molar concentration of Mn) was remarkably enhanced from the initial value of $0.051\\dot{\\mathrm{mM}}^{-1}s^{-1}$ at $\\mathrm{pH}\\ 7.4$ to $8.743\\mathrm{mM}^{-1}s^{-1}$ after incubation in $\\mathrm{pH}6$ buffer for $6\\mathrm{h}$ , owing the decomposition of $\\mathrm{MnO}_{2}$ nanoshells into paramagnetic $\\mathrm{Mn}^{2+}$ . To demonstrate the use of such $\\mathrm{MnO}_{2}$ nanoshells for tumor-specific imaging, $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D was directly injected into the tumor and the muscle on the opposite side for MR imaging (Fig. 4e). Interestingly, because of the acidic $\\mathrm{TME}^{29}$ , the tumor area exhibited significantly enhanced T1-MR contrast after injection of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D, whereas the muscle area with the same amount of nanoparticles injected showed much less T1 signal enhancement (Fig. 4f). This phenomenon gives the direct evidence that $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ with ultrasensitive pH-responsive T1-MR contrasting performance is particularly useful for tumor-specific imaging. \n\n![](images/be641a9bd7bb24550a32135b3697141a7b38a048c9934d7e801c7ff80e40b773.jpg) \nFig. 4 In vivo and ex vivo imaging with ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D. a In vivo fluorescence images of 4T1 tumor-bearing mice taken at different time points post i.v. injection of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D (three mice per group). b $\\mathsf{E x}$ vivo fluorescence images of major organs and tumor dissected from mice at $24\\mathsf{h}$ p.i. Sp, Ki, H, Lu, In, Li, and Tu stood for spleen, kidney, heart, lung, intestine, liver, and tumor, respectively. c Semi-quantitative analysis of ex vivo fluorescence images in different organs in $(\\pmb{6})$ . d T1-weighted MR images of the ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D recorded using 3T MR scanner at different pH values (6 and 7.4). The transverse relativities (r1) were 8.743 and $0.051\\mathsf{m}\\mathsf{M}^{-1}\\mathsf{s}^{-1}$ for ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D at ${\\mathsf{p H}}6$ and 7.4, respectively. e T1-MR images of 4T1 tumor-bearing mice before and after local injection of H- $\\cdot\\mathsf{M n O}_{2}$ -PEG/C&D within normal and tumor subcutaneous tissues (three mice per group). f Quantified T1-MR signals in muscle and tumor before and after injection of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D based on images in (e). g, h In vivo T1-MR images of a mouse taken before and $24\\mathsf{h}$ post i.v. injection of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D shown in cross section $\\mathbf{\\sigma}(\\mathbf{g})$ and longitudinal section ${\\bf\\Pi}({\\bf h})$ . i Quantification analysis of T1-MR signals in liver, kidney, and tumor, before and $24\\mathsf{h}$ post i.v. injection or ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D nanoparticles. Date are presented as means $\\pm{\\sf s.d}$ . ( $\\overset{\\cdot}{\\boldsymbol{n}}=3$ mice per group) \n\nMR imaging was then conducted to image 4T1 tumor-bearing mice after i.v. injection of H- $\\cdot\\mathrm{MnO}_{2}$ -PEG/C&D (Fig. 4g). At $24\\mathrm{h}$ post injection of nanoparticles, the T1-MR signals showed twofold-positive enhancement in the tumor (Fig. 4i), demonstrating high-tumor accumulation of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D, consistent to the in vivo fluorescence imaging results. Moreover, strong T1 signals were also found in kidneys of those mice (Fig. 4h, i), suggesting fast renal clearance of $\\mathrm{Mn^{2+}}$ ions decomposed from H$\\mathrm{MnO}_{2}$ -PEG/C&D. Therefore, both fluorescence and MR imaging reveal that our PEGylated hollow $\\mathrm{MnO}_{2}$ nanoshells with drug loading on one hand exhibit efficient passive tumor homing after systemic administration via the enhanced permeability and retention (EPR) effect, on the hand other could be gradually decomposed into free ions and molecules with rapid renal excretion. \n\nIn vivo combined chemo-PDT treatment with $\\mathbf{H}\\mathbf{-}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ -PEG/ C&D. It is known that cancer cells inside tumors are able to constitutively produce $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , whose level has been reported to be in the range of $10{-}100\\upmu\\mathrm{M}$ in many types of solid tumors41. $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D nanoparticles thus might be able to trigger the decomposition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generated by cancer cells, producing $\\mathrm{O}_{2}$ in situ to relieve tumor hypoxia. Therefore, a hypoxyprobe (pimonidazole) immunofluorescence assay was conducted to examine tumor slices extracted at different time points post i.v. injection of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D. The cell nuclei, blood vessels, and hypoxic areas were stained with 2-(4-amidinophenyl)-6- indolecarbamidine dihydrochloride (DAPI, blue), anti-CD31 antibody (red), and anti-pimonidazole antibody (green), respectively. Compared with the control group, tumor slices from mice treated with H- ${\\mathrm{-}}\\mathrm{MnO}_{2}$ -PEG/C&D collected at different time points showed obviously reduced green fluorescence, indicating that the decomposition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ into $\\mathrm{O}_{2}$ triggered by $\\mathrm{MnO}_{2}$ accumulated in the tumor was able to greatly reduce the tumor hypoxia (Fig. 5a). Semi-quantitative analysis of hypoxia positive areas recorded from more than 15 confocal images per group further evidenced that i.v. injected $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D could significantly reduce tumor hypoxia (Fig. 5b). Furthermore, it was found that $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG without drug loading also could markedly decrease the tumor hypoxia signals (Supplementary Fig. 6). In contrast, for mice treated with ${\\mathrm{H}}{\\mathrm{-}}{\\mathrm{SiO}}_{2}$ -PEG, large hypoxia areas remained in their tumors (Supplementary Fig. 6). \n\n![](images/40bf042ee59cc9d983e5d103acc15a27c5c50f09f658f612c579558f5e23d658.jpg) \nFig. 5 In vivo combined chemo-PDT treatment with ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D. a Representative immunofluorescence images of 4T1 tumor slices collected from untreated control mice and mice 6 h and $12\\mathsf{h}$ post i.v. injection with $-1-M n O_{2}$ -PEG/C&D. The nuclei, blood vessels, and hypoxic areas were stained with DAPI (blue), anti-CD31 antibody (red), and anti-pimonidazole antibody (green), respectively (three mice per group). b Quantification of hypoxia areas in tumors at different time points post injection of our nanoparticles. c Tumor growth curves of different groups of mice after various treatments indicated. Error bars were based on standard errors of the mean (SEM) (six mice per group). d Average weight of tumors collected from mice at day 14th post initiation of various treatments. The predicted addictive effect was calculated by multiplying the tumor growth inhibition ratios of group 4 (PDT alone) and group 5 (chemotherapy alone). e H&E-stained tumor slices collected from mice post various treatments indicated. $p$ values in (c) and (d) were calculated by Tukey’s post-test $^{\\prime\\star\\star\\star}p<0.001$ , $^{\\star\\star}p<0.01$ , or $^{\\star}p<0.05^{\\cdot}$ ) \n\nNext, the efficacy of $\\mathrm{H-MnO_{2}\\mathrm{-PEG/C\\&D}}$ for enhanced PDT and chemotherapy was studied with the 4T1 mouse tumor model. As an inert control to $\\mathrm{MnO}_{2}$ carriers, hollow mesoporous silica $\\left(\\mathrm{H}{-}\\mathrm{SiO}_{2}\\right) $ ) nanoshells were used to replace $\\mathrm{MnO}_{2}$ . Such $\\mathrm{H}{\\cdot}\\mathrm{SiO}_{2}$ nanoshells with similar sizes to $_\\mathrm{H-MnO}_{2}$ after PEGylation also showed efficient co-loading of Ce6 and DOX, but no catalytic activity to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (Supplementary Fig. 7). In our in vivo treatment experiments, Balb/c mice bearing 4T1 tumors were divided into seven groups: untreated (group 1), free $\\mathrm{Ce}6+\\mathrm{DOX}$ with $660\\mathrm{-nm}$ light irradiation (group 2, $\\mathrm{Ce}6+\\mathrm{DOX}+\\mathrm{L},$ ), $_{\\mathrm{H-MnO}_{2}}$ -PEG (group 3), $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C with $660–\\mathrm{nm}$ light irradiation (group 4, H$\\mathrm{MnO}_{2}–\\mathrm{PEG}/\\mathrm{C}+\\mathrm{L};$ ), $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D (group 5), $\\mathrm{H}{\\cdot}\\mathrm{SiO}_{2}$ -PEG/ \n\nC&D with $660–\\mathrm{nm}$ light irradiation (group 6, ${\\mathrm{H}}{\\mathrm{-}}{\\mathrm{SiO}}_{2}$ -PEG/C&D $+\\mathrm{L})$ , and $_{\\mathrm{H-MnO}_{2}}$ -PEG/C&D with $660–\\mathrm{nm}$ light irradiation (Group 7, $H\\mathrm{-}\\mathrm{Mn}{\\mathrm{O}_{2}}\\mathrm{-}\\mathrm{PEG}/\\mathrm{C}\\&\\mathrm{D}+\\mathrm{L}\\rangle$ . At $^{12\\mathrm{h}}$ post i.v. injection of those therapeutic agents (dose of $\\mathrm{MnO}_{2}{=}\\mathrm{\\bar{1}}0\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{SiO}_{2}=$ $25\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{Ce6=4.7mgkg^{-1}}$ , and $\\mathrm{DOX}=4.5\\mathrm{mg}\\mathrm{kg}^{-1}$ ), mice in group 2, 4, 6, and 7 were exposed to the $660–\\mathrm{nm}$ light for $^{\\textrm{1h}}$ $\\mathbf{\\bar{(}}5\\operatorname*{min}\\mathrm{{cm}^{-2}},$ ). \n\nThe tumor sizes and mice body weights were measured in following 2 weeks (Fig. 5c; Supplementary Fig. 8). At day 14, the tumors of all mice were collected and weighted. Free drugs plus ${660\\mathrm{-nm}}$ laser irradiation (group 2) showed no appreciable effect on tumor growth, likely owing to the insufficient tumor retention of free Ce6 and DOX at such low doses. $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG without laser irradiation showed no obvious suppressive effect on the tumor growth (group 3). For tumors on mice treated by H$\\mathrm{MnO}_{2}$ -PEG/C exposed to $660–\\mathrm{nm}$ light irradiation (group 4, PDT alone), or $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\bar{\\mathrm{O}}}_{2}$ -PEG/C&D without light irradiation (group 5, chemotherapy only), their growth was partially delayed. Combination therapy with H- $\\mathrm{Si}\\mathrm{\\bar{O}}_{2}$ -PEG/C&D plus light irradiation offered more significant tumor growth-inhibition effect (group 6). Notably, in the combination treatment group of H $\\cdot{\\mathrm{-}}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ -PEG/ C&D with $660\\mathrm{-nm}$ light, the tumors showed the slowest growth speed and smallest volumes at the end of treatment. Importantly, the therapeutic efficacy of our combination therapy with H$\\mathrm{MnO}_{2}$ -PEG/C&D was obviously stronger than the predicted addictive effect (Fig. 5d), indicating the significant synergistic effect by the combined PDT and chemotherapy delivered by H$\\mathrm{MnO}_{2}$ -PEG/C&D. Furthermore, hematoxylin and eosin (H&E) staining of tumor slices also showed that the majority of tumor cells were severely damaged in the group of $_\\mathrm{H-MnO}_{2}$ -PEG/C&D with $660–\\mathrm{nm}$ light (Fig. 5e). After 14 days, H&E-stained images of major organs from the combination therapy group suggested that our $_\\mathrm{H-MnO}_{2}$ -PEG/C&D induced no obvious toxic side effects to mice (Supplementary Fig. 9). \n\n![](images/4e3837a9f01a89714ac067a69aad536d39ac09576e8b058f6982f121874cb7eb.jpg) \nFig. 6 Immunological responses after combined chemo-PDT with ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D. a Macrophages infiltration and polarization within tumors post various treatments. CD11b $^{+}C D206^{+}$ cells were defined as M2 phenotype macrophages (six mice per group). The total number of macrophages infiltrated in tumors markedly increased post the combined chemo-PDT, which also resulted in polarization of M2 phenotype TAM towards M1 TAM. b, c The levels of IL-10 (b) and IL-12p40 (c) in the supernatant of tumors post various treatments. d, e Representative flow cytometry data of cytotoxic T lymphocytes (CTL) infiltration in tumors. ${\\mathsf{C D3^{+}C D8^{+}}}$ cells were defined as CTLs. f The production of $\\vert F N-\\gamma$ in sera of mice post various treatments. $p$ values were calculated by Tukey’s post-test between group 5 $(H-M n\\mathsf{O}_{2}\\mathsf{-P E G/C G D+L})$ and group 1 (untreated) $({}^{\\star\\star\\star}p<0.001$ , $^{\\star\\star}p<0.01$ , or $^{\\star}p<0.05\\$ (compared with untreated). Date are presented as means $\\pm\\thinspace s.0$ . $(n=6)$ ) \n\nImmunological responses after the combined chemo-PDT. In recent years, extensive evidences have highlighted the pivotal roles of TME in effective cancer immunotherapy43. For instance, M2 type TAM and regulatory T cells (Treg) are immunosuppressive cells that can promote tumor progression via inhibiting anti-tumor immunities44, 45. It has been uncovered that the hypoxic TME could promote the recruitment of Treg into tumors12 and tune TAM into M2-like phenotype cells12, 13, 46. Considering the ability of our nanoparticles to relieve tumor hypoxia, we thus worked whether combination treatment with such $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D would have any effect to the tumor immunology. The changes of TAM and Treg at day 5 post treatments in tumors were firstly examined using flow cytometry assay. Interestingly, compared with the untreated group, tumors on mice with i.v. injection of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D after light exposure (combined chemo-PDT) showed significantly enhanced macrophages infiltration within tumor from $0.8\\%$ to $8\\%$ , together with largely reduced population of M2 phenotype TAMs from $40\\%$ to $9.5\\%$ among total TAM (Fig. 6a). Consistent to a previous report47, injection of $\\mathrm{MnO}_{2}$ by itself could also induce a certain level of TAM polarization, although to be much less extend as found in our work. In contrast, no significant change of TAM phenotypes was observed in tumor after combination treatment with ${\\mathrm{H}}{\\mathrm{-}}{\\mathrm{SiO}}_{2}$ -based nano-platform. Meanwhile, the secretion of IL-10 (predominant cytokine secreted by M2 macrophages) in the supernatant of tumor lysates also significantly decreased by 3.77 times for the $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D-injected mice plus light irradiation (Fig. 6b), whereas the secretion of IL-12 (predominant cytokine secreted by M1 macrophages) in tumor showing significant upregulation (Fig. 6c), both indicating significant M2 to M1 polarization for TAM within tumors post chemo-PDT with $_\\mathrm{H-MnO}_{2}$ -PEG/C&D. \n\nIn the meanwhile, we also checked the populations of different sub-groups of T cells in tumors post various types of treatment by flow cytometry. It was found that there were more cytotoxic T lymphocytes (CTL) infiltrated in the tumor after treatment with $_\\mathrm{H-MnO}_{2}$ -PEG/C&D plus light irradiation (Fig. 6d, e). The high expression of interferon gamma (IFN-γ) in the serum confirmed the CTL-mediated cellular immunity induced by such treatment (Fig. 6f)48. Moreover, it was also observed that such treatment with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D could slightly reduce the population of immunosuppressive Treg within tumors (Supplementary Fig. 10). In contrast, treatment with $\\mathrm{H}{\\cdot}\\mathrm{SiO}_{2}$ -PEG/C&D (plus light irradiation) without the hypoxia modulating ability exerted no obvious effect to the sub-populations of T cells. These distinguished effects may be attributed to the TME modulation capacity of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -based nano-platform and the subsequently enhanced chemo-PDT treatment to induce the release of tumorassociated antigens49, 50, which would activate dendritic cells and then the recruitment of effector T cells into tumors. Furthermore, extensive evidences51 have demonstrated that PDT treatment could induce the release of heat shock proteins to facilitate the antigen cross-presentation and finally activate CTL-mediated cellular immunity (e.g., IFN- $\\boldsymbol{\\cdot}\\boldsymbol{\\gamma}$ expression). In other words, besides killing tumor cells, the combined chemo-PDT treatment with our $\\mathrm{H}{\\mathrm{-}}\\mathrm{Mn}\\mathrm{O}_{2}$ -PEG/C&D nano-platform could simultaneously induce CTL-mediated anti-tumor immunities and moderate the immunosuppressive microenvironment inside tumors, favorable for immune killing of tumor cells, which have survived after the first round of treatment by chemo-PDT. \n\n![](images/9ed6b86b6a46396c21a5bd8636891997d3661c0e1e6b55433dfbd977a6d6dbb2.jpg) \nFig. 7 The abscopal effect of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D in combination with anti-PD-L1 ( $\\overset{\\cdot}{\\underset{\\cdot}{\\propto}}\\overset{\\cdot}{\\underset{\\cdot}{\\propto}}$ -PD-L1) checkpoint blockade. a Schematic illustration of ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/ C&D and anti-PD-L1 combination therapy. b, d Primary $(\\pmb{\\ b})$ and distant (d) tumors growth curves of different groups of mice after various treatments indicated. Error bars are based on SEM (six mice per group). The arrows represent the time points of anti-PD-L1 administration. c, e Average weights of primary (c) and distant (e) tumors collected from mice 18 days after initiation of various treatments. f CTL infiltration in distant tumors. ${\\mathsf{C D3^{+}C D8^{+}}}$ cells were defined as CTLs. g The production of TNF- $\\mathbf{\\sigma}\\cdot\\mathbf{\\alpha}\\mathbf{\\cdot}\\mathbf{\\alpha}\\mathbf{\\cdot}\\mathbf{\\alpha}\\mathbf{\\cdot}\\mathbf{\\alpha}$ in sera of mice determined on the 9th day post various treatments. h The proposed mechanism of anti-tumor immune responses induced by ${\\mathsf{H}}{\\mathsf{-}}{\\mathsf{M}}{\\mathsf{n}}{\\mathsf{O}}_{2}$ -PEG/C&D in combination with anti-PD-L1 therapy. p values were calculated by Tukey’s post-test $({}^{\\star\\star\\star}p<0.001$ , $^{\\star\\star}p<0.01$ , or $^{\\star}p<0.05^{\\cdot}$ ) \n\n$\\mathbf{H}\\mathbf{-}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ -PEG/C&D plus anti-PD-L1 checkpoint blockade. It is well known that tumor cells themselves could induce the CTL exhaustion through PD-L1 signaling pathway for immune evasion45. Recently, PD-1/PD-L1 checkpoint-blockade strategies approved by the U.S. Food and Drug Administration (FDA) to promote anti-tumor immunities by inhibiting CTL exhaustion has demonstrated to be a promising cancer immunotherapy method with exciting clinical results in cancer treatment52 Encouraged by the robust cellular immunity induced by the combined chemo-PDT with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D, we hypothesized that such a novel TME-responsive/modulating treatment strategy might have a synergistic effect with PD-L1 checkpoint blockade. In the following study, a bilateral breast tumor model was developed by subcutaneously injecting 4T1 cells into both the left and right flank regions of mice (Fig. 7a). The left and right tumors were designated as the primary and distant tumors, respectively. When those tumors reached $80\\mathrm{mm}^{3}$ , mice were randomly divided into five groups ${\\mathrm{\\Delta}n}=6$ per group): (1) PBS (untreated); (2) $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D injection; (3) $_\\mathrm{H-MnO}_{2}$ - PEG/C&D injection plus anti-PD-L1 treatment; (4) $_{\\mathrm{H-MnO}_{2}}$ - PEG/C&D injection followed by light irradiation ( $\\mathrm{\\bf\\ddot{H}}{\\bf-M}{\\bf\\ddot{n}}{\\bf O}_{2}$ -PEG/ $\\mathrm{C}\\&\\mathrm{D+L})$ ); (5) $\\mathrm{\\mathrm{^{*}H}\\mathrm{-}M n O_{2}\\mathrm{-}P E G/C8\\mathrm{\\bar{c}D+L^{3}}}$ treatment together with anti-PD-L1 treatment. Light irradiation for group 4 and 5 was conducted only on the left tumors (primary tumors) using the $660–\\mathrm{nm}$ LED light for 1 h $(5\\mathrm{mW}\\mathrm{cm}^{-2}.$ ), whereas the right distant tumors were spared from light-induced PDT. PD-L1 blockade therapy was adopted at day 1, 3, 5, and 7 post chemo-PDT treatment by i.v. injection of anti-PD-L1 $(\\mathrm{d{\\dot{o}s e}=750\\upmu g\\mathrm{kg^{-1}}},$ (Fig. 7a). \n\nAs expected, $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D-based chemo-PDT treatment showed further improved therapeutic efficacy in combating the primary tumor progression (the left tumor with light exposure) when combining with PD-L1 blockade, in comparison to chemo-PDT alone with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D (Fig. 7b, c). Most notably, for tumors on the right side (distant tumors) without light exposure, the chemo-PDT with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D on primary tumors together with PD-L1 blockade could also effectively delay their growth, whereas the growth of distant tumors in all other control groups were not significantly affected (Fig. 7d, e). Therefore, such chemo-PDT treatment with H$\\mathrm{MnO}_{2}$ -PEG/C&D in combination with PD-L1 blockade could not only effectively kill primary tumor cells with direct light exposure, but also inhibit the growth of distant tumors (e.g., tumors located deeply inside the body, or too small to be detected before treatment) spared from light exposure. \n\nTo understand such phenomenon, CTL infiltration in distant tumors without PDT treatment was then examined. Interestingly, the CTL recruitment within the distant tumor for the combination treatment group (group 5) increased remarkably. In marked contrast, the CTL infiltration levels within distant tumors in other control groups, including chemo-PDT with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D (no PD-L1 blockade) and $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D injection plus anti-PD-L1 (no light irradiation on the primary tumor), were not significantly affected (Fig. 7f; Supplementary Fig. 11). Furthermore, we also checked the level of TNF- $\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}\\mathbf{\\alpha}_{\\cdot\\mathbf{\\alpha}}$ , an important indicator of anti-tumor systemic immune responses, in sera of mice at day 9th post the irradiation of primary tumors. It was shown that the chemo-PDT with $_\\mathrm{H-MnO}_{2}$ -PEG/C&D together with PD-L1 blockade could induce the highest level of TNF- $\\upalpha$ secretion in serum in comparison to all other control groups (Fig. $\\bf{7g}$ . All these interesting results indicate that although TME-modulating treatment with $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D could reverse the immunosuppressive microenvironment inside tumors and trigger CTLmediated anti-tumor immunities, the PD-L1 blockade could further potentiate the generation of tumor antigen-specific CTL effector cells, which are then migrated into the distant tumors to kill tumor cells there. \n\nSubsequently, we also conducted T cell blocking experiments to confirm the involvement of $\\mathrm{\\DeltaT}$ cells in the efficient abscopal response. 4T1 tumor-bearing mice were treated with $\\mathrm{H}{\\cdot}\\mathrm{Mn}\\bar{\\mathrm{O}}_{2}$ - PEG/C&D $^+$ anti-PD-L1 $^+$ light irradiation as described before, and then received i.p. injection of anti-CD4, anti-CD8, or mouse IgG (as the control) at a dose of $200~{\\upmu\\mathrm{g}}$ per mouse on day 0 and 5. As expected, mouse IgG injection did not affect the therapeutic outcomes of our combination treatment in inhibiting both primary and distant tumors. In marked contrast, blocking of either $\\mathrm{\\dot{C}D4^{+}}$ T cells or $\\mathrm{CD8^{+}}$ T cells greatly impaired the capability of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D (with light) $^+$ anti-PD-L1 treatment in inhibiting both primary and distant tumors, particularly at later time points post treatment (Supplementary Fig. 12). Our results indicate that both $\\mathrm{CD4^{+}}$ and $\\bar{\\mathrm{CD8^{+}}}$ T cells are essential not only to the abscopal effect in inhibiting distant tumors, but also important to the growth inhibition of primary tumors after the combined chemo-PDT-immunotherapy. \n\n# Discussion \n\nAs depicted in Fig. 7h, our developed novel $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D nano-platform with efficient tumor-homing capacity could effectively release the chemotherapeutic drug and photodynamic agent upon responsive to tumor acidic microenvironment. Meanwhile, this novel nano-platform could also relieve the hypoxic condition via inducing decomposition of endogenous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ inside the tumor to further promote photodynamic cancer cell killing. More significantly, the combined chemo-PDT with H$\\mathrm{MnO}_{2}$ -PEG/C&D would result in a number of immunological consequences: (1) The TME modulation capacity of $\\mathrm{H}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ - PEG-based nano-platform could effectively shape the immunosuppressive microenvironment to favor anti-tumor immunities (e.g., TAM polarization from M2 to M1). (2) Besides eliminating primary tumor cells, the enhanced chemo-PDT treatment may generate tumor-associated antigens released from the apoptotic or necrotic tumor cells50, which would be engulfed by antigen presenting cells like dendritic cells to induce anti-tumor cellular immunities (e.g., CTL infiltration in tumors). (3) Furthermore, the above mentioned effects would greatly facilitate the synergistic effect between chemo-PDT treatment and PD-L1 checkpoint blockade. In such comprehensive treatment strategy, the tumor-killing CTL effector cells generated after the chemoPDT treatment plus PD-L1 blockade would migrate into other distant tumors and destruct those tumor cells expressing the same type of tumor-associated antigens, promising for effectively killing of tumor cells that cannot be directly irradiated by light during PDT, as well as for tumor metastasis inhibition. \n\nIn summary, we have fabricated hollow mesoporous $\\mathrm{MnO}_{2}$ nanoshells with PEG coating and dual-drug loading $\\mathrm{\\left(H\\mathrm{-}M n O_{2}\\right.}$ - PEG/C&D) as a multifunctional theranostic platform that is responsive to TME and be able to modulate TME, for enhanced cancer combination chemo-PDT therapy, which further favors anti-tumor immunities to promote cancer immunotherapy. Compared with previously reported $\\mathrm{MnO}_{2}$ nanostructures, hollow mesoporous $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ nanoshells developed here show advantages in highly effective drug loading as well as precisely controlled drug release. The ultrasensitive $\\mathrm{\\pH}$ responsiveness of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D enables tumor-specific MR imaging as well as efficient drug release under acidic TME $\\mathrm{\\DeltapH}$ . The relieved tumor hypoxia by $\\mathrm{MnO}_{2}$ -triggered decomposition of endogenous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ inside tumors offered remarkable benefits not only for improving the efficacy of chemo-PDT, but also for reversing the immunosuppressive TME to favor anti-tumor immunities post treatment. Further combination of $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D-based chemo-PDT with PD-L1 checkpoint blockade offers an abscopal effect to inhibit the growth of not only primary tumors but also distant tumors without light exposure likely through the CTL migration. Subsequent T-cells depletion experiments demonstrate that this combinational chemo-PDT-immunotherapy strategy would inhibit tumor growth mainly through modulating T cellsmediated immunities. With inherent biodegradability, our H$\\mathrm{MnO}_{2}$ -based theranostic nano-platform may indeed find significant potential in clinical translation to allow the combination of chemotherapy, PDT, and cancer immunotherapy, which acting together after modulation of TME could offer a synergistic comprehensive effect in battling cancer. \n\n# Methods \n\nMaterials. Treaethyl orthosilicate (TEOS), poly(allylamine hydrochloride) (PAH, $\\begin{array}{r}{\\mathrm{MW}\\approx15,000\\mathrm{\\rangle}}\\end{array}$ ), and polyacrylic acid (PAA, $\\begin{array}{r}{\\mathrm{MW}\\approx1800^{\\circ},}\\end{array}$ were purchased from Sigma-Aldrich. Potassium permanganate $\\left(\\mathrm{KMnO_{4}}\\right)$ and sodium carbonate $\\left(\\mathrm{Na}_{2}\\mathrm{CO}_{3}\\right)$ were obtained from Sinopharm Chemical Reagent CO., Ltd. (China). Hydrogen peroxide $\\mathrm{(H}_{2}\\mathrm{O}_{2})$ $30\\mathrm{wt\\%}$ solution and Chlorin e6 (Ce6) were purchased from J&K chemical CO. SOSG reagent was purchased from Molecular Probes (Eugenr, OR). DOX was purchased from Beijing HuaFeng United Technology Co. Ltd. PEG polymers were obtained from JiaXingBoMei, China. \n\nSynthesis of H- $\\sin\\cap\\mathsf{O}_{2}$ -PEG/C&D. Solid silica nanoparticles $(\\mathrm{sSiO}_{2})$ were synthesized following the reported method53. Then an aqueous solution of $\\mathrm{KMnO}_{4}$ $(300~\\mathrm{mg})$ ) was dropwise added into the suspension of $\\mathrm{sSiO}_{2}$ ( $\\mathrm{^{40}m g},\\$ under ultrasonication. After $^{6\\mathrm{h}}$ , the precipitate was obtained by centrifugation at $14{,}800\\ \\mathrm{rpm}$ The as-prepared mesoporous $\\mathrm{MnO}_{2}$ -coated $\\mathrm{\\sSiO}_{2}$ was dissolved in 2 M ${\\bf N a}_{2}{\\bf C O}_{3}$ aqueous solution at $60^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . The obtained hollow mesoporous $\\mathrm{MnO}_{2}$ nanoshells $\\left(\\mathrm{H}\\mathrm{-}\\mathrm{Mn}\\mathrm{O}_{2}\\right).$ ) were centrifuged and washed with water several times. Overall, $5\\mathrm{mL}\\mathrm{\\:H}{\\cdot}\\mathrm{MnO}_{2}$ solution $(2\\mathrm{\\bar{mg}m L^{-1}},$ ) was then added to $10\\mathrm{mL}$ PAH solution $(5\\mathrm{mg}\\mathrm{mL}^{-1})$ under ultrasonication. After stirring for $^{2\\mathrm{h}}$ , the above solution was centrifuged and washed with water. The obtained $_\\mathrm{H-MnO}_{2}$ /PAH solution was dropwisely added into $10\\mathrm{mL}$ PAA $(5\\mathrm{mg}\\mathrm{mL}^{-1}\\mathrm{\\Omega}$ ) under ultrasonication. After $^{2\\mathrm{h}}$ of stirring, the above solution was centrifuged and washed with water, before it was mixed with $50\\mathrm{mg\\mPEG{-}}5\\mathrm{K{-}N H_{2}}$ under ultrasonication for $30\\mathrm{min}$ . After adding $15\\mathrm{mg}$ EDC and stirring for $12\\mathrm{h}$ , the prepared $\\mathrm{{H}}{\\mathrm{{-MnO}}_{2}}$ -PEG was collected by centrifugation and washed with water for three times. For Ce6 and DOX loading, the $\\mathrm{\\bfH}{\\mathrm{-}}\\mathrm{\\bfM}\\mathrm{\\bfn}{\\mathrm{O}}_{2}$ -PEG solution $(0.2\\mathrm{mg}\\mathrm{mL}^{-1},\\$ ) was mixed with different concentrations of Ce6 and DOX for $^{12\\mathrm{h}}$ . Ce6 and DOX were co-loaded into H$\\mathrm{MnO}_{2}$ -PEG with appropriate concentrations, yielding $\\mathrm{H}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ -PEG/C&D which was used for further experiments. \n\nCharacterizations. Transmission electron microscopy (TEM, FEI Tecnai F20, acceleration voltage $=200\\mathrm{KV}$ ) was applied to characterize the morphology of nanoparticles. UV–vis spectra were measured with a PerkinElmer Lambda 750 UV–vis-NIR spectrophotometer. The sizes and zeta potentials of nanoparticles were determined by a Malvern zetasizer (ZEN3690, Malvern, UK). Surface area and pore size were measured by Surface Area and Porosity Analyzer (Micromeritics Instrument Corp. ASAP2050). The dissolved $\\mathrm{O}_{2}$ was measured with an oxygen probe (JPBJ-608 portable Dissolved Oxygen Meters, Shanghai REX Instrument Factory). \n\nDegradation and drug release studies. $\\mathrm{H}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ -PEG was incubated with different pH values of PBS (5.5, 6.5, and 7.4) for different durations. At the given time points, the solution was measured by TEM and UV–vis spectrometer for characterizations. To study the Ce6 and DOX release, a solution of H- $\\mathrm{MnO}_{2}$ -PEG/C&D was dialyzed against PBS with different pH values (5.5, 6.5, and 7.4) under room temperature. The amounts of Ce6 and DOX release at different time points were measured by UV–vis spectra. \n\nDetection of SO. SOSG, which is super-sensitive to produced SO, can be employed for SO detection54. Free Ce6 and $\\mathrm{\\ddot{H}{-}M n O}_{2}$ -PEG/C with or without $\\mathrm{H}_{2}\\mathrm{O}_{2}$ added were incubated with SOSG $(2.5\\upmu\\mathrm{M})$ , and then irradiated under $660–\\mathrm{nm}$ light with various periods of time in $\\Nu_{2}$ atmosphere $(5\\mathrm{mW}\\mathrm{cm}^{-2}$ ). The generated SO was determined by the recovered SOSG fluorescence under $_{494-\\mathrm{nm}}$ excitation. \n\nIn vitro cell experiments. 4T1 murine breast cancer cell line was originally obtained from American Type Culture Collection (ATCC) and then incubated under $37^{\\circ}\\mathrm{C}$ within $5\\%$ $\\mathrm{CO}_{2}$ atmosphere. For cell toxicity assay, cells were seeded into 96-well plates $(1\\times10^{4}$ per well) until adherent and then incubated with series concentrations of H- $\\mathbf{\\mathrm{MnO}}_{2}$ -PEG. The standard thiazolyl tetrazolium (MTT, SigmaAldrich) test was applied to measure the cell viabilities relative to untreated cells. \n\nFor confocal fluorescence imaging, 4T1 cells were cultured in 24-well plates containing $\\mathrm{H}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ -PEG/C&D $\\mathrm{\\'{Ce}}6=10\\upmu\\mathrm{M}$ , $\\mathrm{DOX}=5.7\\upmu\\mathrm{g}\\mathrm{mL}^{-1},$ ) in the dark for different incubation time (1, 4, 8, and $^{12\\mathrm{h}}$ ). After washing with PBS for three times, the cells were labeled with 4′, 6-diamidino-2-phenylindole (DAPI) and imaged by a laser scanning confocal fluorescence microscope (Leica SP5). \n\nFor PDT, 4T1 cells were cultured in 96-well plates and incubated with H$\\mathrm{MnO}_{2}–\\mathrm{PEG}/\\mathrm{C}$ or free Ce6 with various concentrations. The 96-well plates were moved to a transparent box ventilated with either oxygen or nitrogen in advance for $^{2\\mathrm{h}}$ . Afterwards, cells were exposed to the $660\\mathrm{-nm}$ light for $30\\mathrm{min}$ $(5\\mathrm{mW}\\mathrm{cm}^{-2},$ ) within either oxygen or nitrogen atmosphere. Cells were then replaced with fresh media and incubated for another $24\\mathrm{h}$ . The cells viabilities were determined by the MTT assay. \n\nFor in vitro combination therapy, 4T1 cells seeded in 96-well plates were incubated with different concentrations of H- $\\cdot\\mathrm{MnO}_{2}$ -PEG/C or $_\\mathrm{H-MnO}_{2}$ -PEG/ C&D for $^{2\\mathrm{h}}$ and then treated with or without $660–\\mathrm{m}$ light irradiation $(5\\mathrm{mW}\\mathrm{cm}^{-2}$ , $30\\mathrm{min}^{\\cdot}$ ). After incubation for another $^{2\\mathrm{h}}$ , the cells were transferred into fresh media and incubated for another $24\\mathrm{h}$ before the MTT assay to measure relative cell viabilities. \n\nAnimal models. Female Balb/c mice (6–8 weeks) were purchased from Nanjing Peng Sheng Biological Technology Co.Ltd, and then implemented in accordance with protocols approved by Soochow University Laboratory Animal Center. 4T1 cells $(5\\times10^{\\dot{6}})$ suspended in $30\\upmu\\mathrm{L}$ of PBS were subcutaneously injected into the back of mouse. The mice bearing 4T1 tumors were treated when the volume of tumor reached about $\\sim60\\mathrm{mm}^{3}$ . \n\nIn vivo imaging. In vivo fluorescence imaging was performed using the Maestro in vivo fluorescence imaging system (Cri inc.). MR imaging was conducted under a $3.0\\mathrm{-T}$ clinical MRI scanner (GE healthcare, USA) with a special coil for small animal imaging. \n\nImmunohistochemistry. 4T1 tumor-bearing mice were i.v. injected with PBS or $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D. At 6 or $^{12\\mathrm{h}}$ post injection, tumors were surgically excised $90\\mathrm{min}$ after intraperitoneal injection with pimonidazole hydrochloride $(60\\mathrm{mg}\\mathrm{kg}^{-1}),$ (Hypoxyprobe-1 plus kit, Hypoxyprobe Inc.), which was reductively activated in hypoxic cells and formed stable adducts with thiol groups in proteins. For immunofluorescence staining, OCT compound (Sakura Finetek) was employed to prepare frozen sections of the tumors. For detection of pimonidazole, the tumor sections were treated with mouse anti-pimonidazole primary antibody (dilution 1:200, Hypoxyprobe Inc.) and Alex 488-conjugated goat anti-mouse secondary antibody (dilution 1:200, Jackson Inc.) following the kit’s instructions. Tumor blood vessels were stained by rat anti-CD31 mouse monoclonal antibody (dilution 1:200, Biolegend) and Rhodamine-conjugated donkey anti-rat secondary antibody (dilution 1:200, Jackson), subsequently. Cell nuclei were stained with DAPI (dilution 1:5000, Invitrogen). The obtained slices were observed by a confocal microscopy (Leica SP5). \n\nIn vivo cancer treatment. 4T1 tumor-bearing mice were i.v. injected with $200\\upmu\\mathrm{L}$ of PBS, free $\\mathrm{Ce}6+\\mathrm{DOX}$ , $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C, ${\\mathrm{H}}{\\mathrm{-}}{\\mathrm{SiO}}_{2}$ -PEG-C&D, or $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/ C&D (dose of $\\mathrm{MnO}_{2}=10\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{SiO}_{2}=25\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{Ce6=4.7\\mg{kg}^{-1}}$ , and $\\mathrm{DOX}=4.5\\mathrm{mg}\\mathrm{kg}^{-1}.$ ), respectively. The 660-nm light irradiation was conducted at $^{12\\mathrm{h}}$ post injection $(5\\mathrm{m}\\mathrm{\\dot{W}}\\mathrm{cm}^{-2},1\\mathrm{h}$ . Tumor sizes and body weights were \n\nmonitored every 2 days for 2 weeks. The tumor volume was calculated following the formula: volume $\\dot{=}\\mathrm{width}^{2}\\times\\mathrm{length}/2$ . The tissue and tumor slices were stained by H&E following the standard protocol. \n\nTo evaluate the immunological effects of chemo-PDT combination treatment, 4T1 tumor-bearing mice were randomly divided into 5 groups and i.v. injected with $200\\upmu\\mathrm{L}$ of PBS, $\\mathrm{H}{\\cdot}\\mathrm{SiO}_{2}$ -PEG/C&D (with or without laser irradiation), or H$\\mathrm{{MnO}}_{2}$ -PEG/C&D (with or without laser irradiation, dose of $\\mathrm{MnO}_{2}=10\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{SiO}_{2}=25\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{Ce6=4.7\\mgkg^{-1}}$ , and $\\mathrm{DOX}=4.5\\mathrm{mg}\\mathrm{kg}^{-1}$ ). The $660–\\mathrm{nm}$ light irradiation was conducted at $^{12\\mathrm{h}}$ $\\mathrm{^{\\prime}}5\\mathrm{mW}\\mathrm{cm}^{-2}$ , 1 h) post injection. At day 5 post irradiation, mice were sacrificed and tumors were collected for the immunological evaluations. Briefly, tumor tissues were cut into small pieces and put into a glass homogenizer containing PBS solution $\\mathrm{\\Phi(pH=7.4)}$ ). Then, the single cell suspension was prepared by gentle pressure with the homogenizer without addition of digestive enzyme55. Finally, the supernatant of tumors were collected to determine IL-10 and IL-12p40 levels using ELISA assay (eBioscience). Meanwhile, cells were stained with fluorescence-labeled antibodies after the removal of red blood cells (RBC) using the RBC lysis buffer. For macrophage polarization, cells were stained with anti-CD206-FITC, anti-CD11b-PE and anti-F4/80-AlexaFluor 647 (eBioscience) antibodies according to the manufacturer’s protocols. $\\mathrm{CD11b^{+}F4/80^{+}}$ and $\\mathrm{CD11b^{+}F4/80^{+}C D206^{+}}$ cells were defined as macrophages and M2 phenotype macrophages, respectively. For regulatory T cells (Treg) evaluation, cells were stained with anti-CD3-FITC, anti-FoxP3-PE, anti-CD4-PerCP, and anti-CD8-APC (eBioscience) antibodies according to the manufacturer’s protocols. Meanwhile, cells were stained with anti-CD3-APC (BD Biosciences) and anti-CD8-PE (BD Biosciences) for evaluating cytotoxic T lymphocytes (CTL) infiltration. $\\mathrm{CD}3^{+}\\mathrm{CD}4^{+}\\mathrm{FoxP}3^{+}$ and $\\mathrm{CD3^{+}C D8^{+}}$ cells were defined as Treg and CTL, respectively. In addition, interferon gamma $(\\mathrm{IFN-}\\gamma)$ and tumor necrosis factor alpha (TNF-α) in the sera of mice were also determined using ELISA assay (eBioscience). \n\nTo develop the bilateral tumor model, 4T1 cells were subcutaneously injected into left (primary tumor) and right (distant tumor) flank. After one week, those mice were i.v. injected with $200\\upmu\\mathrm{L}$ of PBS, $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D (dose of $\\mathrm{{MnO}}_{2}=$ $10\\mathrm{mg}\\mathrm{kg}^{-1}$ , $\\mathrm{Ce6{=}4.7\\ m g{k g^{-1}}}$ , and $\\mathrm{DOX}=4.5\\mathrm{mg}\\mathrm{kg}^{-1},$ ), or $\\mathrm{H}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ -PEG/C&D $^+$ anti-PD-L1, respectively. Twelve hours after injection, the primary tumors were irradiated with a $660\\mathrm{-nm}$ light $(5\\mathrm{mW}\\mathrm{cm}^{-2}$ , $\\mathrm{1h}^{\\cdot}$ . Then, mice were i.v. injected with anti-PD-L1 antibody at a dose of $750\\upmu\\mathrm{g}\\mathrm{kg}^{-1}$ at day 1, 3, 5, and 7 post irradiation. Primary and distant tumor sizes and body weights were monitored every 2 days. At day 9 post irradiation, the sera of mice were collected using orbital sinus blood sampling to determine TNF- $\\upalpha$ . Meanwhile, T cells infiltration within bilateral tumors were evaluated using flow cytometry assay. \n\nThe abscopal therapeutic effect of H $\\mathrm{I}{\\mathrm{-}}\\mathrm{Mn}\\mathrm{O}_{2}$ -PEG/C&D $^+$ anti-PD-L1 was evaluated on 4T1 tumor-bearing mice with $\\mathrm{CD4^{+}}$ T cell or $\\mathrm{CD8^{+}}$ T cell depletion. When the tumors reached ${\\sim}100\\mathrm{mm}^{3}$ , mice were i.v. injected with H- $\\mathbf{\\mathrm{MnO}}_{2}$ -PEG/ C&D ${\\mathrm{dose}}=200\\upmu\\mathrm{g}$ per mouse) and exposed to the $660\\mathrm{-nm}$ light $(5\\mathrm{mW}\\mathrm{cm}^{-2}$ , $\\mathrm{1h}^{\\cdot}$ at $^{12\\mathrm{h}}$ post injection. Then, mice were i.v. injected with anti-PD-L1 antibody at a dose of $\\dot{7}50\\upmu\\mathrm{g}\\dot{\\mathrm{kg}}^{-1}$ at day 1, 3, 5, and 7 post irradiation. Anti-CD4 (for $\\mathrm{CD4^{+}}$ T cell depletion, GK1.5, BioXcell), anti-CD8 (for $\\mathrm{CD8^{+}}$ T cell depletion, 2.43, BioXcell) or mouse IgG (Control, SouthernBiotech) were intraperitoneally injected to the mice $200\\upmu\\mathrm{g}$ per mouse) on day 0 and 5 post the treatment. Primary and distant tumor sizes and body weights were measured every 2 days. Tumor volumes were calculated as width $^2\\times$ length/2 \n\nData availability. All other remaining data are available within the article and supplementary files, or available from the authors upon request. \n\nReceived: 2 December 2016 Accepted: 15 August 2017 \nPublished online: 12 October 2017 \n\n# References \n\n1. Chang, C.-H. et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 162, 1229–1241 (2015). \n2. Swartz, M. A. et al. Tumor microenvironment complexity: emerging roles in cancer therapy. Cancer Res. 72, 2473–2480 (2012). \n3. Miao, L., Wang, Y. & Huang, L. Tumor microenvironment and nanodrug delivery. Nanomed. Nanotechnol. Biol. Med. 12, 452 (2016). \n4. Chung, M.-F., Liu, H.-Y., Lin, K.-J., Chia, W.-T. & Sung, H.-W. A pHresponsive carrier system that generates NO bubbles to trigger drug release and reverse P-glycoprotein-mediated multidrug resistance. Angew Chem. 127, 10028–10031 (2015). \n5. Pan, W.-Y. et al. Localized sequence-specific release of a chemopreventive agent and an anticancer drug in a time-controllable manner to enhance therapeutic efficacy. Biomaterials 101, 241–250 (2016). \n6. Yang, G. et al. Mesoporous silica nanorods intrinsically doped with photosensitizers as a multifunctional drug carrier for combination therapy of cancer. Nano Res. 8, 751–764 (2015). and metastasis. Nat. Med. 19, 1423–1437 (2013). \n8. Allinen, M. et al. Molecular characterization of the tumor microenvironment in breast cancer. Cancer Cell 6, 17–32 (2004). \n9. Yang, G. et al. Two-dimensional magnetic ${\\mathrm{WS}}2@{\\mathrm{Fe}}_{3}{\\mathrm{O}}_{4}$ nanocomposite with mesoporous silica coating for drug delivery and imaging-guided therapy of cancer. Biomaterials 60, 62–71 (2015). \n10. Chen, W.-H., Lecaros, R. L. G., Tseng, Y.-C., Huang, L. & Hsu, Y.-C. Nanoparticle delivery of HIF1α siRNA combined with photodynamic therapy as a potential treatment strategy for head-and-neck cancer. Cancer Lett. 359, 65–74 (2015). \n11. Hu, Q. et al. Tumor microenvironment-mediated construction and deconstruction of extracellular drug-delivery depots. Nano Lett. 16, 1118–1126 (2016). \n12. Facciabene, A. et al. Tumour hypoxia promotes tolerance and angiogenesis via CCL28 and Treg cells. Nature 475, 226–230 (2011). \n13. Laoui, D. et al. Tumor hypoxia does not drive differentiation of tumorassociated macrophages but rather fine-tunes the M2-like macrophage population. Cancer Res. 74, 24–30 (2014). \n14. Cheng, R., Meng, F., Deng, C., Klok, H.-A. & Zhong, Z. Dual and multi-stimuli responsive polymeric nanoparticles for programmed site-specific drug delivery. Biomaterials 34, 3647–3657 (2013). \n15. Yang, Y. et al. Near-infrared light-activated cancer cell targeting and drug delivery with aptamer-modified nanostructures. Nano Res. 9, 139–148 (2016). \n16. Qian, C. et al. Light-activated hypoxia-responsive nanocarriers for enhanced anticancer therapy. Adv. Mater. 28, 3313–3320 (2016). \n17. Zhao, Z. et al. A controlled-release nanocarrier with extracellular pH value driven tumor targeting and translocation for drug delivery. Angew Chem. Int. Ed. 52, 7487–7491 (2013). \n18. Hu, Q., Katti, P. S. & Gu, Z. Enzyme-responsive nanomaterials for controlled drug delivery. Nanoscale 6, 12273–12286 (2014). \n19. Min, K. H. et al. pH-controlled gas-generating mineralized nanoparticles: a theranostic agent for ultrasound imaging and therapy of cancers. ACS Nano 9, 134–145 (2015). \n20. Kostic, A. D. et al. Fusobacterium nucleatum potentiates intestinal tumorigenesis and modulates the tumor-immune microenvironment. Cell Host Microbe 14, 207–215 (2013). \n21. Devaud, C., John, L. B., Westwood, J. A., Darcy, P. K. & Kershaw, M. H. Immune modulation of the tumor microenvironment for enhancing cancer immunotherapy. OncoImmunology 2, e25961 (2013). \n22. Liu, Z. & Chen, X. Simple bioconjugate chemistry serves great clinical advances: albumin as a versatile platform for diagnosis and precision therapy. Chem. Soc. Rev. 45, 1432–1456 (2016). \n23. Zhu, W. et al. Modulation of hypoxia in solid tumor microenvironment with $\\mathrm{MnO}_{2}$ nanoparticles to enhance photodynamic therapy. Adv. Funct. Mater. 26, 5490–5498 (2016). \n24. Chen, Y. et al. Manganese oxide-based multifunctionalized mesoporous silica nanoparticles for pH-responsive MRI, ultrasonography and circumvention of MDR in cancer cells. Biomaterials 33, 7126–7137 (2012). \n25. Zhang, M. et al. Manganese doped iron oxide theranostic nanoparticles for combined T1 magnetic resonance imaging and photothermal therapy. ACS Appl. Mater. Inter. 7, 4650–4658 (2015). \n26. Fan, W. et al. Intelligent $\\mathrm{MnO}_{2}$ nanosheets anchored with upconversion nanoprobes for concurrent pH- $\\mathrm{\\cdot/H}_{2}\\mathrm{O}_{2}$ -responsive UCL imaging and oxygenelevated synergetic therapy. Adv. Mater. 27, 4155–4161 (2015). \n27. Zhao, Z. et al. Activatable fluorescence/MRI bimodal platform for tumor cell imaging via $\\mathrm{MnO}_{2}$ nanosheet–aptamer nanoprobe. J. Am. Chem. Soc. 136, 11220–11223 (2014). \n28. Fan, H. et al. Inside back cover: a smart photosensitizer–manganese dioxide nanosystem for enhanced photodynamic therapy by reducing glutathione levels in cancer cells. Angew Chem. Int. Ed. 55, 5611–5611 (2016). \n29. Chen, Q. et al. Intelligent albumin– $\\cdot\\mathrm{MnO}_{2}$ nanoparticles as $\\mathrm{\\pH}{-}/\\mathrm{H}_{2}\\mathrm{O}_{2}$ - responsive dissociable nanocarriers to modulate tumor hypoxia for effective combination therapy. Adv. Mater. 28, 7129–7136 (2016). \n30. Gordijo, C. R. et al. Hybrid nanoparticles: design of hybrid $\\mathrm{MnO}_{2}$ -polymerlipid nanoparticles with tunable oxygen generation rates and tumor accumulation for cancer treatment. Adv. Funct. Mater. 25, 1857–1587 (2015). \n31. Fan, H. et al. A smart photosensitizer–manganese dioxide nanosystem for enhanced photodynamic therapy by reducing glutathione levels in cancer cells. Angew Chem. 128, 5567–5572 (2016). \n32. Prasad, P. et al. Multifunctional albumin– $\\cdot\\mathrm{MnO}_{2}$ nanoparticles modulate solid tumor microenvironment by attenuating hypoxia, acidosis, vascular endothelial growth factor and enhance radiation response. ACS Nano 8, 3202–3212 (2014). \n33. Song, M., Liu, T., Shi, C., Zhang, X. & Chen, X. Bioconjugated manganese dioxide nanoparticles enhance chemotherapy response by priming tumorassociated macrophages toward M1-like phenotype and attenuating tumor hypoxia. ACS Nano 10, 633–647 (2016). \n34. Abbasi, A. Z. et al. Manganese oxide and docetaxel co-loaded fluorescent polymer nanoparticles for dual modal imaging and chemotherapy of breast cancer. J. Control. Release 209, 186–196 (2015). \n35. Chen, Y. et al. Hollow mesoporous organosilica nanoparticles: a generic intelligent framework-hybridization approach for biomedicine. J. Am. Chem. Soc. 136, 16326–16334 (2014). \n36. Li, Y. & Shi, J. Hollow-structured mesoporous materials: chemical synthesis, functionalization and applications. Adv. Mater. 26, 3176–3205 (2014). \n37. Wherry, E. J. T cell exhaustion. Nat. Immunol. 12, 492–499 (2011). \n38. Wang, X. et al. Iron oxide/manganese oxide co-loaded hybrid nanogels as pHresponsive magnetic resonance contrast agents. Biomaterials 53, 349–357 (2015). \n39. Kim, Y., Lin, Q., Glazer, P. M. & Yun, Z. Hypoxic tumor microenvironment and cancer cell differentiation. Curr. Mol. Med. 9, 425–434 (2009). \n40. Lunt, S. J., Chaudary, N. & Hill, R. P. The tumor microenvironment and metastatic disease. Clin. Exp. Metastasis 26, 19–34 (2009). \n41. Szatrowski, T. P. & Nathan, C. F. Production of large amounts of hydrogen peroxide by human tumor cells. Cancer Res. 51, 794–798 (1991). \n42. Platas-Iglesias, C., Esteban-Gómez, D., Helm, L. & Regueiro-Figueroa, M. Transient versus static electron spin relaxation in $\\mathrm{Mn}^{\\tilde{2+}}$ complexes relevant as MRI contrast agents. J. Phys. Chem. A 120, 6467–6476 (2016). \n43. Tang, H., Qiao, J. & Fu, Y.-X. Immunotherapy and tumor microenvironment. Cancer Lett. 370, 85–90 (2016). \n44. Pollard, J. W. Tumour-educated macrophages promote tumour progression and metastasis. Nat. Rev. Cancer 4, 71–78 (2004). \n45. Pardoll, D. M. The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer 12, 252–264 (2012). \n46. Sitkovsky, M. V., Kjaergaard, J., Lukashev, D. & Ohta, A. Hypoxiaadenosinergic immunosuppression: tumor protection by T regulatory cells and cancerous tissue hypoxia. Clin. Cancer Res. 14, 5947 (2008). \n47. Song, M., Liu, T., Shi, C., Zhang, X. & Chen, X. Correction to bioconjugated manganese dioxide nanoparticles enhance chemotherapy response by priming tumor-associated macrophages toward M1-like phenotype and attenuating tumor hypoxia. ACS Nano 10, 3872–3872 (2016). \n48. Dranoff, G. Cytokines in cancer pathogenesis and cancer therapy. Nat. Rev. Cancer 4, 11–22 (2004). \n49. Vanneman, M. & Dranoff, G. Combining immunotherapy and targeted therapies in cancer treatment. Nat. Rev. Cancer 12, 237–251 (2012). \n50. Kabingu, E., Oseroff, A. R., Wilding, G. E. & Gollnick, S. O. Enhanced systemic immune reactivity to a basal cell carcinoma associated antigen following photodynamic therapy. Clin. Cancer Res. 15, 4460–4466 (2009). \n51. Castano, A. P., Mroz, P. & Hamblin, M. R. Photodynamic therapy and antitumour immunity. Nat. Rev. Cancer 6, 535–545 (2006). \n52. Brahmer, J. R. et al. Safety and activity of anti–PD-L1 antibody in patients with advanced cancer. N. Engl. J. Med. 366, 2455–2465 (2012). \n53. Huang, P. et al. Folic acid-conjugated silica-modified gold nanorods for X-ray/ CT imaging-guided dual-mode radiation and photo-thermal therapy. Biomaterials 32, 9796–9809 (2011). \n54. Yang, G., Sun, X., Liu, J., Feng, L. & Liu, Z. Light-responsive, singlet oxygentriggered on-demand drug release from photosensitizer-doped mesoporous silica nanorods for cancer combination therapy. Adv. Funct. Mater. 26, 4722–4732 (2016). \n55. Takahashi, K. et al. Morphological interactions of interdigitating dendritic cells with B and T cells in human mesenteric lymph nodes. Am. J. Pathol. 159, 131–138 (2001). \n\n# Acknowledgements \n\nThis work was partially supported by the National Research Programs from Ministry of Science and Technology (MOST) of China (2016YFA0201200), the National Natural Science Foundation of China (51525203, 81403120, and 31300824), Collaborative Innovation Center of Suzhou Nano Science and Technology, a ‘111’ program from the Ministry of Education (MOE) of China, and a Project Funded by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions. \n\n# Author contributions \n\nG.Y. and L.X. contributed equally to this work. G.Y. and Z.L. conceived the project. G.Y., L.X., Y.C., J.X., X.S. and Y.W. performed the experiments and analyzed the results. R.P. provided useful suggestions to this work. G.Y., L.X. and Z.L. wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at doi:10.1038/s41467-017-01050-0. \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2017 " + }, + { + "id": "10.1021_acs.nullolett.6b04755", + "DOI": "10.1021/acs.nullolett.6b04755", + "DOI Link": "http://dx.doi.org/10.1021/acs.nullolett.6b04755", + "Relative Dir Path": "mds/10.1021_acs.nullolett.6b04755", + "Article Title": "nulloscale Nucleation and Growth of Electrodeposited Lithium Metal", + "Authors": "Pei, A; Zheng, GY; Shi, FF; Li, YZ; Cui, Y", + "Source Title": "nullO LETTERS", + "Abstract": "Lithium metal has re-emerged as an exciting anode for high energy lithium-ion batteries due to its high specific capacity of 3860 mAh g(-1) and lowest electrochemical potential of all known materials. However, lithium has been plagued by the issues of dendrite formation, high chemical reactivity with electrolyte, and infinite relative volume expansion during plating and stripping, which present safety hazards and low cycling efficiency in batteries with lithium metal electrodes. There have been a lot of recent studies on Li metal although little work has focused on the initial nucleation and growth behavior of Li metal, neglecting a critical fundamental scientific foundation of Li plating. Here, we study experimentally the morphology of lithium in the early stages of nucleation and growth on planar copper electrodes in liquid organic electrolyte. We elucidate the dependence of lithium nuclei size, shape, and areal density on current rate, consistent with classical nucleation and growth theory. We found that the nuclei size is proportional to the inverse of overpotential and the number density of nuclei is proportional to the cubic power of overpotential. Based on this understanding, we propose a strategy to increase the uniformity of electrodeposited lithium on the electrode surface.", + "Times Cited, WoS Core": 1287, + "Times Cited, All Databases": 1380, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000393848800075", + "Markdown": "# Nanoscale Nucleation and Growth of Electrodeposited Lithium Metal \n\nAllen Pei,† Guangyuan Zheng,† Feifei Shi,† Yuzhang Li,† and Yi Cui\\*,†,‡ †Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States ‡Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States \n\nSupporting Information \n\nABSTRACT: Lithium metal has re-emerged as an exciting anode for high energy lithium-ion batteries due to its high specific capacity of $38\\check{6}0\\ \\mathrm{mAh}\\ \\mathrm{g}^{-1}$ and lowest electrochemical potential of all known materials. However, lithium has been plagued by the issues of dendrite formation, high chemical reactivity with electrolyte, and infinite relative volume expansion during plating and stripping, which present safety hazards and low cycling efficiency in batteries with lithium metal electrodes. There have been a lot of recent studies on Li metal although little work has focused on the initial nucleation and growth behavior of Li metal, neglecting a critical fundamental scientific foundation of Li plating. Here, we study experimentally the morphology of lithium in the early stages of nucleation and growth on planar copper electrodes in liquid organic electrolyte. We elucidate the dependence of lithium nuclei size, shape, and areal density on current rate, consistent with classical nucleation and growth theory. We found that the nuclei size is proportional to the inverse of overpotential and the number density of nuclei is proportional to the cubic power of overpotential. Based on this understanding, we propose a strategy to increase the uniformity of electrodeposited lithium on the electrode surface. \n\n![](images/a0049f687f7e4ce01076eb4b9457c794b469afde6225b1de80e53ccb14f0c702.jpg) \n\nKEYWORDS: Lithium metal anode, electrodeposition, nucleation and growth, anode-less, anode-free, copper $\\mathbf{C}$ idgenviefilcoapnmt nret eofa lcith iunmtermeset has beneng idvevoetlecdt tdo tfhoer rechargeable batteries since the $1970s.^{1,2}$ Lithium (Li), with its high theoretical specific capacity $\\left(3860\\mathrm{\\mA}\\mathrm{~h~g~}^{-1}\\right),$ and lowest electrochemical potential $-3.04\\mathrm{~V~}$ vs SHE), has since been recognized as an attractive negative electrode material for high energy batteries.2−5 However, the industrial deployment of Li metal batteries has been impeded by the critical problems of battery safety and poor cycling lifetime and efficiency, all which stem from fundamental issues with the Li plating and stripping process. The intrinsic reactivity of Li metal with electrolyte at low potentials causes their rapid consumption and promotes irreversible solid−electrolyte interphase (SEI) formation. Furthermore, mechanical instability of the SEI due to large electrode volumetric changes from repeated Li deposition and stripping generates nonuniformities at the Li-SEI surface in the form of Li dendrites and filaments, excessively thick SEI layers, or disconnected Li, all of which ultimately give rise to safety hazards and low Coulombic efficiency. 6−12 \n\nTo address these issues, there has been significant recent progress in nanoscale interfacial materials design,13−17 engineering of stable hosts for Li metal deposition,18−23 s earching for new liquid electrolytes and additive s,24−29 solid electrolyte development,30−32 and new tools for studying Li metal platin g.33−37 In many studies, the bulk morphology of the Li metal electrode is often employed as qualitative metric; lack of mossy and filamentary Li after deposition are commonly shown as evidence of improvement of the Li plating process. However, it is also of equal importance to understand the immediate and intermediate states of Li metal electrodes as deposition occurs. \n\nThe final bulk morphology of the Li metal after plating does not give a complete picture of its development during growth. By studying the morphology and distribution of Li nuclei and developing a more fundamental understanding of the initial stages of nucleation and growth, a more comprehensive picture of the Li deposition process can be obtained, which may lead to the development of new strategies for enabling lithium metal batteries. \n\nHere, we approached the problems of Li deposition by first understanding the essential principles underlying Li nucleation and correlating them with experimental results. This study provides further fundamental understanding of lithium nucleation and growth directly relevant to the anodeless lithium metal electrode platform12,38 and other lithium−metal based electrodes and expands upon previous qualitative studies of Li nucleation using ionic liquid and solid electrolytes.39,40 The empirical data on Li particle size, density, and growth behavior presented here can also provide insight for the design and fabrication of nanostructured electrodes and host-type structures for next-generation Li metal anodes. Using classical nucleation theory as a starting point, it is well-known that the nucleation of a new solid phase has an associated free energy barrier related to the thermodynamic costs of forming a critical cluster of atoms.41 For electrodeposition, this nucleation barrier can effectively be adjusted by changing the electrochemical supersaturation at the working electrode through tuning the overpotential of the reduction reaction (Figure 1a). Traditionally, the driving force for the electrocrystallization process can be divided into the reaction overpotential, charge transfer overpotential, diffusion overpotential, and crystallization overpotential.41,42 However, as it is difficult to deconvolute each source of electrode polarization, we will refer to two important characteristic overpotentials observed during galvanostatic Li electrodeposition: (1) the nucleation overpotential $(\\eta_{\\mathrm{n}})_{\\mathrm{\\ell}}$ , which is the magnitude of the voltage spike at the onset of Li deposition, and (2) the plateau overpotential $(\\eta_{\\mathtt{p}})$ present after nucleation occurs and Li growth continues (Figure 1b). Specifically, due to the process of galvanostatic Li electrocrystallization occurring at variable supersaturation (overpotential varying over time),43 $\\eta_{\\mathrm{n}}$ and $\\eta_{\\mathrm{p}}$ are chosen for their ease of extractability from experimental data and relevance as important parameters describing nucleation and growth. At the start of the galvanostatic Li deposition process, the potential of the working electrode drops below $0\\mathrm{~V~}$ vs $\\mathrm{Li/Li^{+}}$ to $-\\eta_{\\mathrm{n}}$ at which the electrochemical overpotential is sufficient to drive the nucleation of Li embryos. After initial nucleation occurs, the overpotential rises to $-\\eta_{\\mathrm{p}},$ which is still negative vs $\\mathrm{Li/Li^{+}}$ , and Li nuclei growth proceeds since electrode polarization is lower for Li growth as compared to that for the nucleation step. This is because the addition of a Li adatom to an existing Li nuclei is more favorable and has a lower energy barrier than forming a stable cluster (embryo) of Li atoms.40 From Figure 1b, a parallel can be readily drawn between the voltage profiles of galvanostatic electrodeposition and double-pulse potentiostatic electrodeposition techniques to support the delineation between nucleation and growth regions; a high fixed polarization nucleation pulse of potential $\\eta_{\\mathrm{n}}$ is applied to the working electrode to spontaneously generate nuclei seeds followed by a subsequent extended low polarization pulse of potential $\\eta_{\\mathrm{p}}$ to grow the existing nuclei.44 Classical equations for homogeneous nucleation can briefly be used to understand the dependence of the sizes of electrodeposited Li nuclei on the electrodeposition overpotential and applied current density.41,45,46 The Gibbs energy $\\left(\\Delta G_{\\mathrm{nucleation}}\\right)$ for forming a spherical nuclei of radius $r$ is the sum of its bulk free energy and surface free energy: \n\n![](images/84ecf22a10af200f1d9ae28eff07d27b897350317fd6791acb62ac7c91aace72.jpg) \nFigure 1. Fundamentals of lithium nucleation and growth. (a) Free energy schematic showing the effects of increasing overpotential on the nucleation energy barrier. (b) Schematic plot comparing the typical voltage profiles of galvanostatic Li deposition (black) and double pulse potentiostatic Li deposition (red). (c) Schematic plot of the dependence of critical Li nuclei radius and areal nuclei density on the overpotential of Li deposition. (d) Experimental voltage profiles of Li deposition on $\\mathtt{C u}$ at different current densities for a total capacity of $0.3\\mathrm{\\mA}$ h $\\mathrm{cm}^{-2}$ . (e) Schematic illustrating the size and density of Li nuclei deposited on Cu at varying overpotentials. \n\n$$\n\\Delta G_{\\mathrm{nucleation}}=-4/3\\pi r^{3}\\Delta G_{\\mathrm{V}}+4\\pi r^{2}\\Upsilon\n$$ \n\nwhere $\\Delta G_{\\mathrm{V}}$ is the free energy change per volume and $r$ is the surface energy of the Li-electrolyte interface. The deposition overpotential, $\\eta,$ is related to $\\Delta G_{\\mathrm{V}}$ by \n\n$$\n\\Delta G_{\\mathrm{V}}=F|\\eta|/V_{\\mathrm{m}}\n$$ \n\nwhere $F$ is Faraday’s constant and $V_{\\mathrm{m}}$ is the molar volume of Li. The critical radius is thus as follows:41,47 \n\n$$\nr_{\\mathrm{crit}}=2\\Upsilon V_{\\mathrm{m}}/F|\\eta_{\\mathrm{n}}|\n$$ \n\nFor heterogeneous nucleation, such as for Li deposited on an electrode surface, the energy barrier for forming a critical nucleus is decreased, but the expression for the critical nuclei size remains the same as in eq $3.^{^{\\mathbf{^{\\lambda_{39,47}}}}}$ Immediately, the inverse relationship between nuclei size and electrochemical overpotential is apparent, and the cubic relationship between areal nuclei density and overpotential follows for spherical nuclei (Figure 1c). Figure 1d shows characteristic voltage profiles for the deposition of $0.3\\mathrm{\\mA}$ $\\textrm{h c m}^{-2}$ of Li on a $\\mathtt{C u}$ substrate at different current densities after $i R$ -compensation. The nucleation barrier (overpotential spike) and steady-state Li growth plateau are seen to increase with increasing current density, as predicted by the Butler−Volmer electrode kinetics relationship between current density and electrode potential. The nucleation overpotential $(\\eta_{\\mathrm{n}})$ increases from around $38~\\mathrm{{\\mV}}$ at a current density of $0.1\\mathrm{\\mA\\cm^{-2}}$ to $380~\\mathrm{mV}$ at $\\mathsf{S\\ m A\\ c m}^{-2}$ . Similarly, the plateau overpotential $(\\eta_{\\mathfrak{p}})$ increases from $25~\\mathrm{mV}$ at $0.1\\dot{\\mathrm{\\mA}}\\mathrm{\\cm}^{-2}$ to $137~\\mathrm{mV}$ at $5\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ . Note that $\\eta_{\\mathrm{p}}$ is smaller than $\\eta_{\\mathrm{n}},$ supporting that it is more favorable for Li to deposit on existing nuclei than for new embryos to form. Thus, at low current densities, Li domains are expected to be relatively large and sparsely dispersed, whereas smaller, more densely distributed Li nuclei are expected to grow at higher current densities (Figure 1e). It should be noted that extra amounts of charge are required to complete the nucleation step at lower current densities (e.g., $0.1\\mathrm{\\:\\:\\dot{\\mA}\\:\\:c m^{-2}})$ due to the simultaneous formation of SEI and deposition of Li. Supporting Figure S1 shows that the amount of charge capacity required to reach the nucleation overpotential spike increases drastically with lower current rates. \n\n![](images/15bf8d72777d18eb84400e7f2647af43c1d4decf9d650888b709dd266ad9c435.jpg) \nFigure 2. Lithium nuclei deposited at different current densities. $\\left(\\mathsf{a}\\mathrm{-}\\mathsf{j}\\right)$ Ex situ SEM images of Li nuclei deposited on Cu at current densities of 0.025, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 1, 5, and $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively, for a total areal capacity of $0.1\\mathrm{mA}$ h $\\mathrm{cm}^{-2}$ . At lower current densities, the $\\mathtt{C u}$ substrate is visible underneath the sparsely distributed Li nuclei. \n\nTo investigate the size evolution of Li nuclei during electrodeposition, Cu electrodes were observed after fixed amounts of Li $\\left(0.025{-}0.3~\\mathrm{mA}\\mathrm{h}~\\mathrm{cm}^{-2}\\right)$ , equivalent to $125~\\mathrm{nm}$ to $1.5\\ \\mu\\mathrm{m}$ of Li metal film) was galvanostatically deposited at various current densities $\\left(0.1{-}5\\mathrm{~\\mA~\\}\\mathrm{cm}^{-2}\\right)$ . Here, 1,3- dioxolane/1,2-dimethoxyethane $\\mathrm{\\left(DOL/DME,\\1{:}1\\ {v}/{v}\\right)}$ with 1 M lithium bis(trifluoromethylsulfonyl)imide (LiTFSI) with 1 wt $\\%\\mathrm{LiNO}_{3}$ as an additive was used as the electrolyte for these studies due to the well-defined, nearly circular morphology typical of Li grown in this electrolyte. This DOL/DME etherbased electrolyte is common for sulfur/Li metal batteries, and $\\mathrm{LiNO}_{3}$ is frequently used as a shuttle-effect inhibitor and helps to improve the passivation and surface chemistry of the Li metal surface. $26,4\\dot{8}-50$ Compared to Li deposited in carbonatebased electrolytes which are typically filamentary or wire-like and difficult to characterize (Supporting Figure S2), the Li nuclei grown here are uniform and smooth, and whisker-like or dendritic growth is avoided. Individual Li particles sampled from randomly selected locations near the center of the electrode were measured for each combination of deposition capacity and current density. The electrode edges experience an inhomogeneity effect from cell construction26 and are not used in these sampling studies. Figure 2 shows ex situ SEM images of the typical morphology of Li metal growths deposited in etherbased electrolyte at various current densities ranging from 0.025 to $10\\ \\mathrm{mA\\cm}^{-2}$ with a total charge of $0.1\\ \\mathrm{mAh}\\ \\mathrm{{cm}}^{-2}$ . This low areal capacity is equivalent to a thin Li metal film of ${\\sim}500~\\mathrm{nm}$ and allows us to see the initial stages of deposition. Extra ex situ SEM images of all current density and capacity conditions used in statistical analysis are available in Supporting Figure S3. At low current densities of 0.025 and $0.{\\bar{0}}{\\bar{5}}0{\\mathrm{~mA~}}{\\mathrm{cm}}^{-2}$ (Figure $|2\\mathrm{a},\\mathrm{b}_{\\cdot}^{\\cdot}$ , Li growths are large and sparsely distributed on the Cu electrode surface. The particles are observed to form island-like morphologies, and many particles are noncircular in shape, possibly due to fusing of multiple nuclei at these low growth rates. The nonuniformity of these particles makes it difficult to measure their size and number, so the lower current densities are not represented in the following statistical data. As we increase the current density from 0.1 to $10\\mathrm{\\mA\\cm}^{-2}$ (Figure $\\mathsf{2c-j})$ for a fixed amount of Li, the deposited Li nuclei decrease in size and become more closely packed, as expected. The dimpled shape of the particles likely arises due to the brief exposure to ambient atmosphere during sample transfer to the SEM chamber. For current densities above $\\bar{1}\\mathrm{mA}\\mathrm{cm}^{-2}.$ , the Li nuclei are in contact and closely packed together, and the underlying bare $\\mathtt{C u}$ substrate is nearly unable to be seen. \n\nFigure 3a indicates that the Li particle sizes clearly decrease with increased current density and increased overpotential. A linear relationship appears when particle size is plotted versus inverse overpotential, as expected from eq 3 (Figure 3b). Furthermore, within each current density stratum, the Li particle size increases as the amount of Li deposited is increased. This effect is most pronounced with low current density deposition due to the relatively low particle density which causes individual particles to grow significantly with increasing Li capacity. Figure 3c,d and Supporting Figure S4 are color-coded in parallel with the plot in Figure 3a; each set of histograms corresponds to a different amount of Li deposited (areal capacity in mA h $\\mathrm{cm}^{-2}$ ). These histograms more clearly elucidate the distributions of Li particle sizes deposited at different current densities for Li capacities of $0.025\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}$ (red), $0.05\\mathrm{\\mA}\\mathrm{h}\\mathrm{\\cm}^{-2}$ (orange), $0.1\\ \\mathrm{mA}$ h $\\mathsf{c m}^{-2}$ (green), 0.2 mA h $\\mathrm{cm}^{-2}$ (blue), and $0.3\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}$ (purple). Interestingly, the sizes of the particles are approximately Gaussian distributed, whereas the log-normal distribution is expected from particles undergoing classical Kolmogorov−Avrami−Mehl−Johnson (KAMJ) random nucleation and growth processes.51 The KAMJ model assumes progressive nucleation of particles throughout the entire deposition process and nuclei size independent growth rates.52 The expected log-normal size distribution arises from small recently nucleated particles making up a large fraction of the population, while the fewer earliest nucleated particles grow much larger, skewing the distribution to the right. However, here for Li metal, an initial fixed population of instantaneously nucleated critical nuclei would be expected to grow at equivalent rates and all have the same size. Fluctuations within the system, such as the development of diffusion-limited zones around clustered nuclei, cause slight polydispersity in particle sizes,53 generating the Gaussian distribution observed in this study. The effects of interparticle diffusion coupling, the most important mechanism governing broadening of particle size distributions,53 can significantly affect the sizes of densely distributed Li particles which have many neighbors clustered nearby.54 Furthermore, the clear distinction between the nucleation overpotential and the growth overpotential as seen in Figure 1d suggests that the Li nucleation event is instantaneous instead of progressive. Broader size distributions are expected at lower current densities and lower overpotentials, while the sizes of particles grown at high current densities should have a tighter spread.44 Here, the sizes of Li particles deposited for $0.02{\\bar{5}}{\\mathrm{~mA}}{\\mathrm{~h~}}{\\mathrm{{cm}}}^{-2}$ at $0.1\\mathrm{\\mA}\\mathrm{cm}^{-2}$ have a higher relative standard deviation (RSD) of $20.4\\%$ compared to an R.SD of $15.7\\%$ for deposition at $\\mathrm{\\Delta}5\\mathrm{\\mA}$ $\\mathrm{cm}^{-2}$ . Even after extended Li deposition to $0.3\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}.$ , the RSDs for the sizes of particles grown at all current densities remain below $21\\%$ , indicating that the growth process proceeds relatively uniformly. \n\n![](images/2a6e45cab84cbcb1b9fe8b4669e1d1d26d80cc5eba65bbe9e1949979024bd63c.jpg) \nFigure 3. Size distribution study of Li nuclei grown on $\\mathtt{C u}$ in $^{1\\mathrm{~M~}}$ LiTFSI in DOL/DME with $1\\%\\mathrm{LiNO}_{3}$ additive. (a) Plot of Li particle size versus applied areal current density for different amounts of Li deposition. (b) Plot of Li particle size versus inverse overpotential of Li deposition $(\\eta_{\\mathtt{p}})$ . The red line shows linear fit. Current densities range from 0.05 to $5\\mathrm{\\mA\\cm^{-2}}.$ , and the capacity is $0.1\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}$ . $(\\mathrm{c,d})$ Histograms of Li particle sizes after (c) $0.025~\\mathrm{mA}$ h $\\mathrm{cm}^{-2}$ and (d) $0.3\\mathrm{\\mA}$ h $\\dot{\\mathrm{cm}}^{-2}$ of Li deposition. The five histograms in c and d correspond to current densities of 5, 1, 0.5, 0.3, and $0.1\\mathrm{\\mA\\cm^{-2}}$ from top to bottom. Histograms of other capacities are in Supporting Information.. \n\n![](images/791dbea3f92959bebde4c9fe2a2676f483bc4b249e2ef7baf8aab41cd1470fa6.jpg) \nFigure 4. Nuclei density study of Li deposited on Cu foil. (a) Plot of nuclei density versus amount of Li deposition for different applied current densities. A log−ln plot (log scale for nuclei density) is used to clearly represent the 3 orders of magnitude range of nuclei density. $(\\mathrm{b-d})$ Ex situ SEM images of Li deposited at $\\mathsf{S\\ m A\\ c m}^{-2}$ for a total capacity of (b) $0.{\\dot{1}}\\operatorname*{ma}{\\mathrm{h}}\\ c{\\mathrm{m}}^{-2}.$ , (c) $0.2\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{=_{2}}$ , and (d) $\\bar{0}.3\\mathrm{mAhcm}^{-2}$ . The multiple layers of near-spherical Li particles are clearly visible. \n\nTo further understand the progression of Li deposition, the areal number density of Li particles on the Cu foil was measured at various amounts of deposition and plotted in Figure 4a. Random areas near the center of each electrode were selected, and the number of particles visible was counted from ex situ SEM images to find the particle density on the electrode surface. At $0.02{\\breve{5}}\\mathrm{\\mA}\\mathrm{\\h\\cm}^{-2},$ the earliest stage of deposition measured, the density of nuclei is slightly greater than densities observed at higher deposition amounts. After further growth, the nuclear density decreases and then plateaus from 0.1 to 0.3 mA h $\\mathrm{cm}^{-2}$ . For potentiostatic deposition experiments, the nuclei density would be expected to increase over time due to the application of a fixed overpotential which generates a constant nucleation rate.52,55 However, for this case of galvanostatic Li deposition, there seems to be an instantaneous nucleation event followed by continuous growth of the nuclei as previously discussed, resulting in a relatively static nuclei density. For all current densities studied, the nuclei density is initially high due to the high driving force (overpotential) for nucleation but subsequently drops and plateaus. This decrease in overpotential increases the minimum size of nuclei that can exist, and so any Li embryos that are not larger than the critical size cannot survive. Additionally, due to the small size of the Li nuclei and freshly formed SEI passivation at these low capacities, it is possible that nuclei in close proximity can fuse together upon further Li deposition, resulting in a decreased nuclei density. The nuclei density after deposition of $0.3\\mathrm{\\mAl}$ h $\\mathsf{c m}^{-2}$ of Li at the tested current densities was found to be proportional to the cube of nucleation overpotential, as expected (Supporting Figure S5). \n\nAt low current densities, the initial nuclei are sparsely spread out on the working electrode surface and eventually expand to form a more densely packed arrangement as more charge is passed, forming an island-like morphology (Supporting Figure S6). In these cases, although the areal coverage of the Li growths increases over time, the actual particle density is relatively constant over a large range of deposition, indicating that the initial Li nuclei greatly expand and no new nucleation events occur. Interestingly, for high current density $\\zeta\\ \\mathrm{mA}$ $\\mathsf{c m}^{-2},$ , the morphology of the deposit is quite different from that of lower current density deposition. After $0.1{-}0.3\\ \\mathrm{mA}\\ \\mathrm{h}$ $\\mathsf{c m}^{-2}$ of Li deposition at $5\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2},$ , the Li particles in some areas are seen to overlap and stack in a vertical direction, forming a multilayered particle structure (Figure $\\mathrm{4b-d},$ . This particle stacking-induced decrease in apparent nuclei density at high currents (i.e., $S\\mathrm{\\mA\\cm^{-2}},$ ) explains the deviation from the cubic dependence of nuclei density on overpotential followed by particles deposited at lower current rates (Supporting Figure S5). Intuitively, growing a multilayered structure requires new nuclei to be formed on top of existing Li growths during the deposition process. Note that the voltage profile for Li deposition at $5\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ does not show an immediate drop in overpotential after nucleation to a flat growth plateau as do those for lower current densities (Figure 1d); instead, the overpotential remains relatively high and gradually decreases. With the high overpotential during the growth region at $\\mathrm{\\Delta}5\\mathrm{\\mA}$ $\\mathrm{cm}^{-2}$ , the formation of new nuclei on top of the existing Li surface seems to have occurred, causing the observed stackedparticle structure. This could be due to a relatively lower overpotential requirement for Li nucleation on a Li surface compared to nucleation on Cu. Some multilayer Li particle regions were observed at $1\\mathrm{\\mA}\\mathrm{cm}^{-2}$ , but the overall electrode morphology consisted mainly of a single layer of particles. This suggests that at higher overpotentials, due to the decreased nucleation Gibbs free energy, the increased nucleation frequency per active site causes additional nucleation events to occur due to the greatly increased driving force.42 Due to the high nuclei density and nearly complete coverage of the $\\mathtt{C u}$ working electrode, additional Li nuclei are formed on top of pre-existing Li particles, creating three-dimensional stacked growths. Although the total number of nuclei increased volumetrically, the areal nuclei density at high current rates remained constant with increased Li deposition, since some nuclei underneath the top layer of the 3D nuclei structure were not visible from above. \n\n![](images/448b465b6776dcdfa0a99a262c50dbe2da4893c682635642c981d1b63fe0d2fc.jpg) \nFigure 5. Effect of Li seed layer on Li nuclei size and particle density. (a) $0.1\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}$ of Li deposited at $0.05\\mathrm{mAcm}^{-2}$ . The particles are large and sparsely distributed. (b) $0.1\\mathrm{\\dot{~mA}}\\mathrm{~h~cm}^{-2}$ of Li deposited at $0.05\\mathrm{\\mA\\cm^{-2}}$ on top of a Li nuclei seed layer showing increased particle density. (c) Higher magnification image of the same electrode in b. (d) $0.3\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}$ of Li deposited at $0.05\\mathrm{\\mA}\\mathrm{cm}^{-2}$ on top of a Li seed layer. The number density of Li particles is seen to increase, and seed particles slightly increase in size. The Li nuclei seed layer is generated by depositing $0.02~\\mathrm{mA}$ h $\\mathrm{cm}^{-2}$ of Li at $10\\mathrm{\\mA\\cm}^{-2}$ onto Cu foil. \n\nKnowing that dense arrays of Li particles can be instantaneously nucleated at high current rates, we tested the effects of a highly dense Li embryo-covered working electrode on the morphology of further deposited Li. Figure 5a shows Li particles on $\\mathtt{C u}$ foil after deposition of $0.1\\mathrm{\\mA}\\mathrm{\\bar{h}}\\mathrm{cm}^{-2}$ of Li at a low current rate of $0.05\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ . The particles are sparsely distributed on the surface, and bare Cu is visible underneath the Li. To try to improve the Li particle density and uniformity on the whole electrode, a layer of Li nuclei was generated on the Cu foil at the beginning of the experiment by depositing 0.02 mA h $\\mathrm{cm}^{-2}$ of Li at a high current of $10~\\mathrm{\\mA}~\\mathrm{cm}^{-2}$ . This generated an initial seed layer upon which $0.1\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}$ of Li at $0.05\\mathrm{\\mA\\cm^{-2}}$ was further deposited for comparison with Li deposited without the seed layer. Figure 5b shows a significant increase in the density and coverage of the electrode area by Li particles on the electrode with the Li seeds. With the seed layer, the areal particle density increases from 0.019 particles $\\mu\\mathrm{m}^{-\\dot{2}}$ to 0.051 particles $\\mu\\mathrm{m}^{-2}$ , while the average particle size decreases from 4.55 to $3.49~\\mu\\mathrm{m}$ . The high polarization from the high current pulse generates significantly more nuclei than naturally occurs galvanostatically at $0.05~\\mathrm{\\mA}~\\mathrm{cm}^{-2}$ , providing more discrete predefined locations at which Li can grow. However, the higher magnification image of the preseeded electrode after Li deposition in Figure 5c indicates that, even though the $\\mathtt{C u}$ surface is densely covered by Li nuclei, many of the initial nuclei do not grow into larger particles after $0.{\\dot{1}}\\ \\mathrm{mA}\\ \\mathrm{h}\\ \\mathrm{cm}^{-2}$ of deposition. Upon increasing the deposition amount to $0.3\\mathrm{\\mA}$ $\\mathrm{h}\\mathrm{cm}^{-2}$ in Figure 5d, the Li particles are approximately the same size, but the particle density has significantly increased, indicating that additional seed nuclei have grown larger after additional deposition. Smaller Li particles are seen growing in clusters near larger particles, and the seed nuclei on the Cu surface have become visibly larger. \n\nInspection of the voltage profile of the deposition process reveals that there is no voltage spike present upon decreasing the current from $10\\mathrm{\\mA\\cm^{-2}}$ to initiate growth, indicating that no new nucleation events occur (Supporting Figure S7). Thus, during low current deposition, the growth proceeds by selective enlargement of individual pre-existing nuclei seeds. The sparse morphology of large Li particles could be due to the presence of diffusion zones that form around growing particles, depleting $\\mathrm{Li}^{+}$ around them and preventing growth of immediate surrounding nuclei.41 Further investigation is required to understand the nature of Li growth from a seeded layer. \n\nThese results suggest an interesting technique to generate more uniform Li metal morphologies during the galvanostatic cycling of Li metal batteries by utilizing an initial nuclei seed layer for Li deposition. Dendritic and mossy Li growths are intrinsically localized nonuniformities that arise during Li metal deposition. Thus, improving the areal density of Li metal deposits on the working electrode during intermediate steps of deposition can be expected to reduce the heterogeneity of the Li metal surface. For anodeless batteries featuring a lithiumcontaining cathode and bare Cu anode, it may prove beneficial to initialize the anode with a short Li seeding process. However, nuclei seeds and smaller Li morphologies can cause increased electrolyte consumption and SEI formation due to the increased surface area. Ultimately, preserving a more uniform and stable Li surface will better maintain the integrity of the native SEI and any engineered protective structures or coatings, all while enhancing electrode performance and safety. \n\nIn summary, the nucleation of Li metal on Cu substrates for Li metal battery electrodes was studied via ex situ SEM. We demonstrate the dependence of lithium nuclei size, shape, and areal density on current rate, consistent with trends from classical nucleation and growth theory. We found that the Li nuclei size is proportional to the inverse of overpotential and the number density of nuclei is proportional to the cubic power of overpotential. Based upon this understanding, the instantaneous nucleation of Li during galvanostatic electrodeposition was utilized in a strategy to improve the uniformity and particle density of deposited Li metal. These results are relevant to promising anodeless batteries utilizing bare Cu current collectors or low-capacity Li foils as negative electrodes. Additional studies on the nucleation and growth of Li metal in different electrolytes and on other relevant materials such as Li metal itself are paramount to understanding the initial behavior of Li metal deposition. Finally, future potentiostatic experiments which hold the overpotential of Li deposition constant will be critical for determining and extracting fundamental values relevant to the Li nucleation mechanism. These studies can guide the design of nanostructured Li metal electrodes and provide further much-needed insight toward fundamental aspects of high energy density, high performance Li metal batteries. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.6b04755. \n\nSEM images of Li deposited on Cu in various common electrolytes, SEM images of Li deposited on Cu from DOL/DME electrolyte at various capacities and current densities, statistics of Li nuclei size and number density versus overpotential of deposition, SEM images of islandlike Li growths, and electrochemical data on Li nuclei seeding and growth and a description of materials and methods (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author $^{*}\\mathrm{E}$ -mail: yicui@stanford.edu. ORCID \n\nAllen Pei: 0000-0001-8930-2125 \n\n# Present Address \n\nG.Z.: Institute of Materials Research and Engineering, 2 Fusionopolis Way, Innovis $\\#08–03$ , Singapore, 138634. \n\nNotes The authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nA.P. acknowledges support by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program and support by the Stanford Graduate Fellowship. The work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the US Department of Energy under the Battery 500 Consortium program. \n\n# REFERENCES \n\n(1) Whittingham, M. S. Science 1976, 192, 1126−1127. \n(2) Xu, W.; Wang, J.; Ding, F.; Chen, X.; Nasybulin, E.; Zhang, Y.; Zhang, J.-G. Energy Environ. Sci. 2014, 7, 513. \n(3) Tarascon, J. M.; Armand, M. Nature 2001, 414, 359−367. (4) Armand, M.; Tarascon, J.-M. Nature 2008, 451, 652−657. (5) Bruce, P. G.; Freunberger, S. A.; Hardwick, L. J.; Tarascon, J.-M. Nat. Mater. 2011, 11, 19−29. \n(6) Xu, K. Chem. Rev. 2004, 104, 4303−4417. \n(7) Aurbach, D.; Zinigrad, E.; Teller, H.; Cohen, Y.; Salitra, G.; Yamin, H.; Dan, P.; Elster, E. J. Electrochem. Soc. 2002, 149, A1267− A1277. \n(8) Aurbach, D. Electrochim. Acta 2003, 48, 599. \n(9) Kim, H.; Jeong, G.; Kim, Y.-U.; Kim, J.-H.; Park, C.-M.; Sohn, H.- J. Chem. Soc. Rev. 2013, 42, 9011−9034. \n(10) Lu, D.; Shao, Y.; Lozano, T.; Bennett, W. D.; Graff, G. L.; Polzin, B.; Zhang, J.; Engelhard, M. H.; Saenz, N. T.; Henderson, W. a.; Bhattacharya, P.; Liu, J.; Xiao, J. Adv. Energy Mater. 2015, 5, 1400993. \n(11) Cheng, X.-B.; Zhang, R.; Zhao, C.-Z.; Wei, F.; Zhang, J.-G.; Zhang, Q. Adv. Sci. 2016, 3, 1500213. \n(12) Tikekar, M. D.; Choudhury, S.; Tu, Z.; Archer, L. A. Nat. Energy 2016, 1, 16114. \n(13) Zheng, G.; Lee, S. W.; Liang, Z.; Lee, H.-W.; Yan, K.; Yao, H.; Wang, H.; Li, W.; Chu, S.; Cui, Y. Nat. Nanotechnol. 2014, 9, 618−623. (14) Yan, K.; Lee, H.-W.; Gao, T.; Zheng, G.; Yao, H.; Wang, H.; Lu, Z.; Zhou, Y.; Liang, Z.; Liu, Z.; Chu, S.; Cui, Y. Nano Lett. 2014, 14, 6016−6022. \n(15) Kozen, A. C.; Lin, C.-F.; Pearse, A. J.; Schroeder, M. A.; Han, X.; Hu, L.; Lee, S. B.; Rubloff, G. W.; Noked, M. ACS Nano 2015, 9, 5884−5892. \n(16) Kazyak, E.; Wood, K. N.; Dasgupta, N. P. Chem. Mater. 2015, 27, 6457−6462. \n(17) Sun, Y.; Liu, N.; Cui, Y. Nat. Energy 2016, 1, 16071. \n(18) Liang, Z.; Zheng, G.; Liu, C.; Liu, N.; Li, W.; Yan, K.; Yao, H.; Hsu, P.-C.; Chu, S.; Cui, Y. Nano Lett. 2015, 15, 2910−2916. \n(19) Yang, C.-P.; Yin, Y.-X.; Zhang, S.-F.; Li, N.-W.; Guo, Y.-G. Nat. Commun. 2015, 6, 8058. \n(20) Lin, D.; Liu, Y.; Liang, Z.; Lee, H.-W.; Sun, J.; Wang, H.; Yan, K.; Xie, J.; Cui, Y. Nat. Nanotechnol. 2016, 11, 626−632. \n(21) Liu, Y.; Lin, D.; Liang, Z.; Zhao, J.; Yan, K.; Cui, Y. Nat. Commun. 2016, 7, 10992. \n(22) Liang, Z.; Lin, D.; Zhao, J.; Lu, Z.; Liu, Y.; Liu, C.; Lu, Y.; Wang, H.; Yan, K.; Tao, X.; Cui, Y. Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 2862−2867. \n(23) Yan, K.; Lu, Z.; Lee, H.-W.; Xiong, F.; Hsu, P.-C.; Li, Y.; Zhao, J.; Chu, S.; Cui, Y. Nat. Energy 2016, 1, 16010. \n(24) Qian, J.; Henderson, W. a.; Xu, W.; Bhattacharya, P.; Engelhard, M.; Borodin, O.; Zhang, J.-G. Nat. Commun. 2015, 6, 6362. \n(25) Lu, Y.; Tu, Z.; Archer, L. a. Nat. Mater. 2014, 13, 961−969. (26) Li, W.; Yao, H.; Yan, K.; Zheng, G.; Liang, Z.; Chiang, Y.-M.; Cui, Y. Nat. Commun. 2015, 6, 7436. \n(27) Qian, J.; Xu, W.; Bhattacharya, P.; Engelhard, M.; Henderson, W. a.; Zhang, Y.; Zhang, J.-G. Nano Energy 2015, 15, 135−144. (28) Zhang, Y.; Qian, J.; Xu, W.; Russell, S. M.; Chen, X.; Nasybulin, E.; Bhattacharya, P.; Engelhard, M. H.; Mei, D.; Cao, R.; Ding, F.; Cresce, A. V.; Xu, K.; Zhang, J. Nano Lett. 2014, 14, 6889−6896. (29) Ding, F.; Xu, W.; Graff, G. L.; Zhang, J.; Sushko, M. L.; Chen, X.; Shao, Y.; Engelhard, M. H.; Nie, Z.; Xiao, J.; Liu, X.; Sushko, P. V.; Liu, J.; Zhang, J.-G. J. Am. Chem. Soc. 2013, 135, 4450−4456. \n(30) Khurana, R.; Schaefer, J. L.; Archer, L. A.; Coates, G. W. J. Am. Chem. Soc. 2014, 136, 7395−7402. \n(31) Zhang, J.; Bai, Y.; Sun, X.-G.; Li, Y.; Guo, B.; Chen, J.; Veith, G. M.; Hensley, D. K.; Paranthaman, M. P.; Goodenough, J. B.; Dai, S. Nano Lett. 2015, 15, 3398−3402. \n(32) Rangasamy, E.; Liu, Z.; Gobet, M.; Pilar, K.; Sahu, G.; Zhou, W.; Wu, H.; Greenbaum, S.; Liang, C. J. Am. Chem. Soc. 2015, 137, 1384− 1387. \n(33) Bhattacharyya, R.; Key, B.; Chen, H.; Best, A. S.; Hollenkamp, A. F.; Grey, C. P. Nat. Mater. 2010, 9, 504−510. \n(34) Cheng, H.; Zhu, C. B.; Lu, M.; Yang, Y. J. Power Sources 2007, 174, 1027−1031. \n(35) Chandrashekar, S.; Trease, N. M.; Chang, H. J.; Du, L.-S.; Grey, C. P.; Jerschow, A. Nat. Mater. 2012, 11, 311−315. \n(36) Chang, H. J.; Ilott, A. J.; Trease, N. M.; Mohammadi, M.; Jerschow, A.; Grey, C. P. J. Am. Chem. Soc. 2015, 137, 15209−15216. (37) Devaux, D.; Harry, K. J.; Parkinson, D. Y.; Yuan, R.; Hallinan, D. T.; MacDowell, A. A.; Balsara, N. P. J. Electrochem. Soc. 2015, 162, A1301−A1309. \n(38) Qian, J.; Adams, B. D.; Zheng, J.; Xu, W.; Henderson, W. A.; Wang, J.; Bowden, M. E.; Xu, S.; Hu, J.; Zhang, J.-G. Adv. Funct. Mater. 2016, 26, 7094−7102. \n(39) Sano, H.; Sakaebe, H.; Senoh, H.; Matsumoto, H. J. Electrochem. Soc. 2014, 161, A1236−A1240. \n(40) Sagane, F.; Ikeda, K.; Okita, K.; Sano, H.; Sakaebe, H.; Iriyama, Y. J. Power Sources 2013, 233, 34−42. \n(41) Plieth, W. Electrochemistry for Materials Science; Elsevier: Amsterdam, 2008. \n(42) Winand, R. J. Appl. Electrochem. 1991, 21, 377−385. \n(43) Milchev, A.; Irene Montenegro, M. J. Electroanal. Chem. 1992, 333, 93−102. \n(44) Ueda, M.; Dietz, H.; Anders, A.; Kneppe, H.; Meixner, A.; Plieth, W. Electrochim. Acta 2002, 48, 377−386. \n(45) Kashchiev, D. J. Chem. Phys. 1982, 76, 5098−5102. \n(46) Oxtoby, D. W.; Kashchiev, D. J. Chem. Phys. 1994, 100, 7665. (47) Ely, D. R.; Garcia, R. E. J. Electrochem. Soc. 2013, 160, A662− A668. \n(48) Aurbach, D.; Pollak, E.; Elazari, R.; Salitra, G.; Kelley, C. S.; Affinito, J. J. Electrochem. Soc. 2009, 156, A694. \n(49) Zhang, S. S. Electrochim. Acta 2012, 70, 344−348. \n(50) Rosenman, a.; Elazari, R.; Salitra, G.; Markevich, E.; Aurbach, D.; Garsuch, a. J. Electrochem. Soc. 2015, 162, A470−A473. \n(51) Teran, A. V.; Bill, A.; Bergmann, R. B. Phys. Rev. B: Condens. Matter Mater. Phys. 2010, 81, 10−15. \n(52) Stark, J. K.; Ding, Y.; Kohl, P. A. J. Electrochem. Soc. 2013, 160, D337−D342. \n(53) Penner, R. M. J. Phys. Chem. B 2002, 106, 3339−3353. \n(54) Fransaer, J. L.; Penner, R. M. J. Phys. Chem. B 1999, 103, 7643− 7653. \n(55) Eliaz, N.; Eliyahu, M. J. Biomed. Mater. Res., Part A 2007, 80, 621−634. " + }, + { + "id": "10.1126_science.aah6362", + "DOI": "10.1126/science.aah6362", + "DOI Link": "http://dx.doi.org/10.1126/science.aah6362", + "Relative Dir Path": "mds/10.1126_science.aah6362", + "Article Title": "Tough adhesives for diverse wet surfaces", + "Authors": "Li, J; Celiz, AD; Yang, J; Yang, Q; Wamala, I; Whyte, W; Seo, BR; Vasilyev, NV; Vlassak, JJ; Suo, Z; Mooney, DJ", + "Source Title": "SCIENCE", + "Abstract": "Adhesion to wet and dynamic surfaces, including biological tissues, is important in many fields but has proven to be extremely challenging. Existing adhesives are cytotoxic, adhere weakly to tissues, or cannot be used in wet environments. We report a bioinspired design for adhesives consisting of two layers: an adhesive surface and a dissipative matrix. The former adheres to the substrate by electrostatic interactions, covalent bonds, and physical interpenetration. The latter amplifies energy dissipation through hysteresis. The two layers synergistically lead to higher adhesion energies on wet surfaces as compared with those of existing adhesives. Adhesion occurs within minutes, independent of blood exposure and compatible with in vivo dynamic movements. This family of adhesives may be useful in many areas of application, including tissue adhesives, wound dressings, and tissue repair.", + "Times Cited, WoS Core": 1214, + "Times Cited, All Databases": 1304, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000406362300039", + "Markdown": "# ADHESIVES \n\n# Tough adhesives for diverse wet surfaces \n\nJ. Li,1,2,3 A. D. Celiz, $^{2,4\\ast}\\dag$ J. Yang,1,5\\* Q. Yang,1,5,6 I. Wamala,7 W. Whyte,1,2,8 B. R. Seo,1,2 N. V. Vasilyev,7 J. J. Vlassak,1 Z. Suo,1,5 D. J. Mooney1,2‡ \n\nAdhesion to wet and dynamic surfaces, including biological tissues, is important in many fields but has proven to be extremely challenging. Existing adhesives are cytotoxic, adhere weakly to tissues, or cannot be used in wet environments. We report a bioinspired design for adhesives consisting of two layers: an adhesive surface and a dissipative matrix. The former adheres to the substrate by electrostatic interactions, covalent bonds, and physical interpenetration. The latter amplifies energy dissipation through hysteresis. The two layers synergistically lead to higher adhesion energies on wet surfaces as compared with those of existing adhesives. Adhesion occurs within minutes, independent of blood exposure and compatible with in vivo dynamic movements. This family of adhesives may be useful in many areas of application, including tissue adhesives, wound dressings, and tissue repair. \n\nsive. The second criterion is satisfied by using a hydrogel capable of dissipating energy as the dissipative matrix. For instance, alginate-polyacrylamide (Alg-PAAm) hydrogels effectively dissipate energy under deformation (20). We hypothesize that by combining the interfacial bridging and the background hysteresis, the TAs could form strong adhesion on wet surfaces. \n\ndhesives that can bond strongly to biological tissues would have broad applications ranging from tissue repair (1, 2) and drug delivery (3, 4) to wound dressings (5, 6) . and biomedical devices (7, 8). However, existing tissue adhesives are far from ideal. Cyanoacrylate (Super Glue) is the strongest class of tissue adhesive (9) but is cytotoxic; is incompatible with wet surfaces, as it solidifies immediately upon exposure to water; and forms rigid plastics that cannot accommodate dynamic movements of tissues (10). Nanoparticle $(I I)$ and musselinspired adhesives (12) adhere weakly to tissues, as their adhesion mainly relies on relatively weak physical interactions, typically leading to low adhesion energies of 1 to $\\mathbf{10~J~m^{-2}}$ . Commercial adhesives, such as the fibrin glue TISSEEL (Baxter) (13) and polyethylene glycol–based adhesives $(I4)$ like COSEAL (Baxter) and DURASEAL (Confluent Surgical), can form covalent bonds with tissues. However, their matrix toughness and adhesion energies are on the order of $\\ensuremath{\\mathrm{10~J~m^{-2}}}$ (15). Such brittle adhesives are vulnerable to debonding because of cohesive failure in the adhesive matrix. For comparison, cartilage constitutes a matrix of high toughness $(\\mathrm{{1000}J m^{-2}}.$ ) and bonds to bones with an adhesion energy of $800\\mathrm{J\\m^{-2}}$ (16). \n\nAchieving high adhesion energy requires the synergy of two effects. First, the adhesive should form strong bonds with the substrate. Second, materials inside either the adhesive or the substrate (or both) should dissipate energy by hysteresis. Tissue adhesives must also show compatibility with body fluids, as well as with cells and tissues. Here we report the design of a family of tough adhesives (TAs) for biological applications to meet those requirements. The design is inspired by a defensive mucus secreted by slugs (Arion subfuscus) that strongly adheres to wet surfaces (17). This slug adhesive consists of a tough matrix with interpenetrating positively charged proteins (18). Our TAs are made up of two layers: (i) an adhesive surface containing an interpenetrating positively charged polymer and (ii) a dissipative matrix (Fig. 1A). The adhesive surface can bond to the substrate through electrostatic interactions, covalent bonds, and physical interpenetration, whereas the matrix dissipates energy through hysteresis under deformation. \n\nThe TAs were designed on the basis of two criteria: (i) The adhesive surface must wet negatively charged surfaces of tissues and cells and must form covalent bonds across the interface while being compliant to the dynamic movements of tissues. (ii) The dissipative matrix must be tough and capable of dissipating energy effectively when the interface is stressed. To satisfy the first criterion, we employed a bridging polymer that bears positively charged primary amine groups under physiological conditions. The primary amine found in the slug adhesive is believed to play a major role in its mechanics and adhesion (19). Such a polymer can be absorbed to the tissue surface via electrostatic attractions, enabling primary amine groups to bind covalently with carboxylic acid groups from the hydrogel matrix and the tissue surface (Fig. 1A). If the target surface is permeable, the bridging polymer can also penetrate into the target surface, forming physical entanglements, and chemically anchor the adhe \n\nWith the use of these design principles, we fabricated a family of TAs that can adhere to wet surfaces. We chose porcine skin as the first model tissue, as it closely resembles human skin and is robust, ensuring that ultimate adhesive failure occurs at the interface. To identify an appropriate bridging polymer, we tested five polymers: chitosan, polyallylamine (PAA), polyethylenimine, collagen, and gelatin. The bridging polymer penetrated rapidly into the hydrogel matrix (fig. S1), forming a positively charged surface (fig. S2). Two coupling reagents, 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide and $N_{\\mathbf{\\ell}}$ -hydroxysulfosuccinimide, were applied to facilitate covalent bond formation (21, 22). Other coupling reagents or enzymes, such as transglutaminase, can also enable the formation of interface-bridging covalent bonds (23). Our TAs were then applied on the epidermis of porcine skin with compression, and the resulting adhesion was quantified by the adhesion energy (fig. S3) (24). Among the tested polymers, PAA and chitosan led to adhesion energies $>1000\\mathrm{J}\\mathrm{m}^{-2}$ (Fig. 1B and fig. S4), probably due to the high concentration of primary amines present on these polymers. In comparison, use of the coupling reagents or the bridging polymer alone yielded adhesion energies of $14\\mathrm{J~m}^{-2}$ and $303\\mathrm{~J~m~}^{-2}$ , respectively (fig. S5). Adhesion energy was sensitive to the concentration but not the molecular weight of the bridging polymer (fig. S6). \n\nWe next examined the importance of the synergy between interfacial bridging and background hysteresis. Our TAs were compared with adhesives formed with either Alg or PAAm singlenetwork hydrogels, as these do not dissipate energy as effectively as the Alg-PAAm hydrogels (20). The coupling reagents and chitosan were again applied for interfacial bridging. The Alg hydrogel led to weak adhesion, as it is vulnerable to rupture and lacks effective energy-dissipating mechanisms to toughen the interface. The PAAm hydrogel resulted in higher adhesion, but not as high as the tough matrix of the Alg-PAAm hydrogel, which enables TAs to integrate high adhesion energy and high matrix toughness simultaneously (Fig. 1C and fig. S4). This specific combination cannot be found among existing tissue adhesives (Fig. 1D and fig. S7), including cyanoacrylate (CA), COSEAL, and a nanoparticlebased adhesive. Commercial adhesives are either formed with a brittle matrix such as COSEAL or lack strong interaction with tissues, as in the case of adhesive bandages (24). This finding is also echoed in many studies on adhesion between hard materials and rubbers (25, 26), as well as adhesion between hydrogels and inorganic oxidized surfaces (27). \n\nTough adhesives are applicable to a wide variety of wet surfaces, including tissues and hydrogels. \n\nOur TAs adhered strongly to porcine skin, cartilage, heart, artery, and liver (Fig. 2A). Their adhesion energies on hydrogels are higher than those of the nanoparticle-based adhesives (1 to $10\\mathrm{~J~m~}^{-2}.$ ) that were recently developed to glue hydrogels (Fig. 2B) (11). Unlike tissues, certain hydrogels, such as poly(hydroxyethyl methacrylate), lack the functional groups (amine or carboxylic acid) that we used to form interfacial covalent bonds, but these hydrogels still adhere well to TAs (figs. S8 and S9). Although the bridging polymer was found to interpenetrate into a variety of substrates, the penetration depth in a given time depended on the substrate permeability. Because hydrogels are more permeable than tissues, the penetration depth of fluorescein isothiocyanate– labeled chitosan (FITC-chitosan) in hydrogels was greater than that found in skin or muscle (Fig. 2C and fig. S10) and likely underlies the strong adhesion of TAs to even chemically inert hydrogels. \n\nWe next evaluated the capacity of our TAs as tissue adhesives, particularly compared with that of the widely used CA. Our TAs exhibited a rapid increase in adhesion energy to porcine skin over time (Fig. 3A). This rapid but not immediate adhesion is likely to aid clinical translation and adoption of these tissue adhesives, as it allows the material to be applied in a facile manner. In contrast, CA solidifies upon contact with tissues, which makes handling and repositioning difficult (28). The formation of tissue adhesion is often complicated in vivo because of exposure to blood and dynamic movements. To simulate this in vitro, the porcine skin was first covered with blood before the application of a TA (fig. S11 and movie S2). The adhesion energy was found to be 1116 $\\mathrm{J}\\mathrm{m}^{-2}$ , which indicates strong adhesion even with blood exposure. In contrast, the adhesion provided by CA deteriorates significantly upon exposure to blood (Fig. 3B and fig. S12). Our TAs were further tested on a beating porcine heart in vivo (Fig. 3C). Freshly drawn blood was spread on the heart surface at the site of application, followed by application of a TA and peeling tests (movie S3). A strong adhesion was formed on the dynamic curved surface with a peak strength of $83\\pm31\\mathrm{{kPa}}$ , which exceeds that of commercially available tissue adhesives (typically ${\\sim}\\mathrm{10~kPa},$ (29). Our TAs were found to maintain strong adhesion $(600\\mathrm{~J~m~}^{-2})$ after being implanted into rats for 2 weeks (fig. S13). They also exhibited excellent biocompatibility: In an in vitro cell study, human dermal fibroblasts were able to maintain full viability after 24-hour culture in a TAconditioned medium, while the cells cultured in a CA-conditioned medium were unable to spread and exhibited low viability (Fig. 3D and fig. S14). The in vivo biocompatibility of our TAs was evaluated with subcutaneous implantation and myocardium attachment in rats (24). After performing a histological assessment, we concluded that the degree of inflammatory reaction produced by our TAs was lower than that produced by CA; additionally, our TAs were comparable to COSEAL in this category (Fig. 3E and fig. S15). \n\nThe design of TAs can potentially enable many applications, including the gluing of tissues and attaching devices in vivo, tissue repair, and attaining hemostasis. TAs can readily adhere to liver tissue (Fig. 4A). Tensile testing demonstrated that a TA remained highly stretchable and sustained 14 times its initial length before debonding from the liver. The combination of strong adhesion and large deformability is vital when interfacing tissues and deformable devices, whereas existing adhesives hardly accommodate large deformation. For example, our TAs managed to anchor an actuator, recently developed to support heart function, onto myocardium surfaces (fig. S16). TAs are also potentially useful as a dressing for skin wounds. TAs adhered strongly to the epidermis of mice and readily accommodated dynamic movements of this tissue on the living animal (fig. S17 and movie S4). \n\n![](images/29f29095400980f6d15508030dc73c6076e5850674089159689d30794565a12e.jpg) \nFig. 1. Design of tough adhesives (TAs). (A) TAs consist of a dissipative matrix (light blue square), made of a hydrogel containing both ionically (calcium; red circles) cross-linked and covalently cross-linked polymers (black and blue lines), and an adhesive surface that contains a bridging polymer with primary amines (green lines). The bridging polymer penetrates into the TA and the substrate (light green region). When a crack approaches, a process zone (orange area) dissipates significant \namounts of energy as ionic bonds between alginate chains and calcium ions break. (B) Adhesion energy on porcine skin was measured using different bridging polymers. PAA, polyallylamine; PEI, polyethylenimine. (C) Adhesion energy varies with the hydrogel matrix. Alg, alginate; PAAm, polyacrylamide. (D) Comparison between our TAs and other adhesives. CA, cyanoacrylate; NPs, nanoparticles. Error bars indicate SD; $N=4$ samples. \n\n![](images/58e741df699802e5950d4f9433d042af25e0464b7bb1bd0547a1cca5f512dcdf.jpg) \nFig. 2. Adhesion on diverse wet surfaces. TAs adhere to a variety of (A) and alginate-polyacrylamide (Alg-PAAm) hydrogels. (C) Penetration depth of ssue surfaces and (B) hydrogels, including poly(hydroxyethyl methacrylate) fluorescein isothiocyanate–labeled chitosan (FITC-chitosan) into PAAm (PHEMA), poly(N′-isopropylacrylamide) (PNIPAm), polyacrylamide (PAAm), hydrogels, skin, and muscle. Error bars indicate SD; $N=4$ . \n\n![](images/f8c24e6f1d51f1f64eb8fc9ab2d0eccc780208d57c34869bc785aea91fbe32a7.jpg) \nFig. 3. Adhesion performance and biocompatibility. (A) Adhesion kinetics $N=4$ . (E) In vivo biocompatibility was evaluated by using subcutaneous of TAs to porcine skin. (B) Comparison of TA versus CA placed on porcine implantation in rats. The degree of inflammation was determined by a skin with and without exposure to blood. $N=4$ to 6. (C) In vivo test on pathologist $\\mathrm{\\DeltaO=}$ normal, $1=$ very mild, $2=$ mild, $3=$ moderate, $4=$ severe, a beating porcine heart with blood exposure. (D) In vitro cell compatibility $5=$ very severe). Error bars indicate SD; $N=4$ to 6. $P$ values were determined was compared by quantifying the viability of human dermal fibroblasts. by a Student’s $t$ test; $^{\\ast}P\\leq0.05$ ; $\\ast\\ast\\ast\\ast P\\leq0.0001$ ; ns, not significant. \n\nA TA can be used for tissue repair as either a preformed patch or an injectable solution. We first tested a TA as a sealant to close a large defect in a porcine heart (Fig. 4B). Our TA was compliant and conformed closely to the geometry of the myocardium. While the heart was being inflated, the sealant expanded with the deformation, and no leakage was observed under strain up to $100\\%$ . A perfect seal was maintained after tens of thousands of cycles of inflationdeflation (fig. S18 and movie S5). The measured burst pressures of the TA sealant without and with a plastic backing were $206\\mathrm{mmHg}$ and $367\\mathrm{mmHg},$ , respectively (Fig. 4C); these values exceed normal arterial blood pressure in humans (80 to $\\begin{array}{r}{\\mathbf{120\\mmHg},}\\end{array}$ and the performance of commercially available surgical sealants (24, 30). Notably, the TA sealant malfunctioned due to cohesive failure, which is indicative of a strong adhesion interface (fig. S18 and movie S6). We also developed an injectable TA based on an Alg–polyethylene glycol hydrogel (24). It can be injected via syringe into a defect site and can form a tough matrix upon exposure to ultraviolet light (fig. S19). As a proof of concept, the injectable TA was used to repair a cylindrical defect in explanted cartilage discs, resulting in recovery of the compressive properties (fig. S20). \n\nTough adhesives can be used as a hemostatic dressing because of their compatibility with blood exposure, as shown in a hepatic hemorrhage model. A circular laceration was used to produce heavy bleeding on the left lobe of the liver in rats (24). Animals were treated immediately with the TA or with a commercial hemostat [SURGIFLO (Ethicon)] as a positive control or were left untreated as a negative control (Fig. 4D). The blood loss was significantly reduced by the application of the TA versus the negative control, and the TA’s performance was comparable to that of SURGIFLO (Fig. 4E). All animals survived for the experimental period of 2 weeks without secondary hemorrhage. However, substantial adhesions were found at the lesion site when untreated or treated with SURGIFLO; necrosis occurred in the livers of untreated animals (fig. S21). Neither of these were found in the animals treated with the TA. \n\nWe report design principles of biocompatible TAs that combine chemical and physical processes at the interface and in the bulk of the adhesive to achieve high adhesion energy on various wet and dynamic surfaces. The mechanical performance and compatibility with cells and tissues allow these materials to meet key requirements for nextgeneration tissue adhesives. \n\n![](images/7bb74d45e911c5f35a9b4e70edce112b550be8629fcea961cbc444559eb2a230.jpg) \nFig. 4. Application enabled by TAs. (A) TAs were used as tissue adhesives. A TA adhered to the liver and sustained 14 times its initial length (l) before debonding. Scale bars, $20~\\mathsf{m m}$ . (B) TAs served as heart sealants. The TA sealant prevented liquid (red) leakage as the porcine heart was inflated. $\\Delta\\mathsf{P},$ change in pressure. Scale bars, $10~\\mathsf{m m}$ . (C) Burst pressures of the TA sealant were measured without (TA) and with plastic \nbacking (TA-B). (D) Use of a TA as a hemostatic dressing. A deep wound was created on rat liver and then sealed with a TA to stop the blood flow (labeled with red arrows). (E) Blood loss with the treatment of TA, SURGIFLO hemostat, and control (without treatment). Error bars indicate SD; $N=4$ . $P$ values were determined by a Student’s t test; ${\\ast\\ast\\ast P}\\leq0.001$ ; ns, not significant. \n\n# REFERENCES AND NOTES \n\n1. S. Duflo, S. L. Thibeault, W. Li, X. Z. Shu, G. D. Prestwich, Tissue Eng. 12, 2171–2180 (2006). \n2. B. Sharma et al., Sci. Transl. Med. 5, 167ra6 (2013). \n3. M. R. Prausnitz, R. Langer, Nat. Biotechnol. 26, 1261–1268 (2008). \n4. J. Li, D. J. Mooney, Nat. Rev. Mater. 1, 16071 (2016). \n5. C. Ghobril, K. Charoen, E. K. Rodriguez, A. Nazarian, M. W. Grinstaff, Angew. Chem. Int. Ed. 52, 14070–14074 (2013). \n6. M. W. Grinstaff, Biomaterials 28, 5205–5214 (2007). \n7. E. T. Roche et al., Adv. Mater. 26, 1200–1206 (2014). \n8. R. Feiner et al., Nat. Mater. 15, 679–685 (2016). \n9. K. A. Vakalopoulos et al., Ann. Surg. 261, 323–331 (2015). \n10. H. V. Vinters, K. A. Galil, M. J. Lundie, J. C. Kaufmann, Neuroradiology 27, 279–291 (1985). \n11. S. Rose et al., Nature 505, 382–385 (2014). \n12. D. G. Barrett, G. G. Bushnell, P. B. Messersmith, Adv. Healthc. Mater. 2, 745–755 (2013). \n13. D. H. Sierra, J. Biomater. Appl. 7, 309–352 (1993). \n14. D. G. Wallace et al., J. Biomed. Mater. Res. 58, 545–555 (2001). \n15. A. K. Dastjerdi, M. Pagano, M. T. Kaartinen, M. D. McKee, F. Barthelat, Acta Biomater. 8, 3349–3359 (2012). \n16. M. Moretti et al., J. Biomech. 38, 1846–1854 (2005). \n17. J. M. Pawlicki et al., J. Exp. Biol. 207, 1127–1135 (2004). \n18. A. M. Wilks, S. R. Rabice, H. S. Garbacz, C. C. Harro, A. M. Smith, J. Exp. Biol. 218, 3128–3137 (2015). \n19. M. Braun, M. Menges, F. Opoku, A. M. Smith, J. Exp. Biol. 216, 1475–1483 (2013). \n20. J. Y. Sun et al., Nature 489, 133–136 (2012). \n21. N. Nakajima, Y. Ikada, Bioconjug. Chem. 6, 123–130 (1995). \n22. M. A. Gilles, A. Q. Hudson, C. L. Borders Jr., Anal. Biochem. 184, 244–248 (1990). \n23. J. G. Fernandez et al., Tissue Eng. Part A 23, 135–142 (2017). \n24. Materials and methods are available as supplementary materials. \n25. A. N. Gent, Langmuir 12, 4492–4496 (1996). \n26. J. W. Hutchinson, Z. Suo, Adv. Appl. Mech. 29, 63–191 (1992). \n27. H. Yuk, T. Zhang, S. Lin, G. A. Parada, X. Zhao, Nat. Mater. 15, 190–196 (2016). \n28. T. Stefanov, B. Ryan, A. Ivanković, N. Murphy, Int. J. Adhes. Adhes. 68, 142–155 (2016). \n29. N. Lang et al., Sci. Transl. Med. 6, 218ra6 (2014). \n30. P. K. Campbell, S. L. Bennett, A. Driscoll, A. S. Sawhney, “Evaluation of absorbable surgical sealants: In vitro testing” \n\n(Covidien, 2005); www.covidien.com/imageServer.aspx/ doc179399.pdf?contentID=14109&contenttype=application/pdf. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the NIH under award R01DE0130333 and was performed, in part, at the Center for Nanoscale Systems at Harvard University. A.D.C. acknowledges support from a Marie Curie International Outgoing Fellowship funded by the European Commission (agreement 629320). W.W. acknowledges support from Science Foundation Ireland under grant SFI/12/RC/2278. Q.Y. acknowledges a scholarship from Tsinghua University. Z.S. and J.J.V. acknowledge support from the NSF under award CMMI-1404653. Z.S., J.J.V., and D.J.M. acknowledge support from the Harvard University Materials Research Science and Engineering Center (grant DMR-1420570). J.L., A.D.C., and D.J.M. are inventors on U.S. patent applications (US 62/311,646, US 62/356,939, and PCT/US2017/023538) submitted by Harvard University that cover the design of TAs. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/357/6349/378/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S21 \nReferences (31–49) \nMovies S1 to S6 \n25 July 2016; resubmitted 27 April 2017 \nAccepted 22 June 2017 \n10.1126/science.aah6362 \n\n# Science \n\n# Tough adhesives for diverse wet surfaces \n\nJ. Li, A. D. Celiz, J. Yang, Q. Yang, I. Wamala, W. Whyte, B. R. Seo, N. V. Vasilyev, J. J. Vlassak, Z. Suo and D. J. Mooney \n\nScience 357 (6349), 378-381. DOI: 10.1126/science.aah6362 \n\n# Sticky even when wet \n\nTissue adhesives are used as an alternative to stitches or staples and can be less damaging to the healthy tissues. But they can suffer from low biocompatibility and poor matching of the mechanical properties with the tissues. Li et al. combined an adhesive surface with a flexible matrix to develop an adhesive that has the right level of stick but moves with the surrounding tissues. The adhesive is effective in the presence of blood and thus might work during wound repair. \n\nScience, this issue p. 378 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_ncomms14627", + "DOI": "10.1038/ncomms14627", + "DOI Link": "http://dx.doi.org/10.1038/ncomms14627", + "Relative Dir Path": "mds/10.1038_ncomms14627", + "Article Title": "Conductive porous vanadium nitride/graphene composite as chemical anchor of polysulfides for lithium-sulfur batteries", + "Authors": "Sun, ZH; Zhang, JQ; Yin, LC; Hu, GJ; Fang, RP; Cheng, HM; Li, F", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Although the rechargeable lithium-sulfur battery is an advanced energy storage system, its practical implementation has been impeded by many issues, in particular the shuttle effect causing rapid capacity fade and low Coulombic efficiency. Herein, we report a conductive porous vanadium nitride nulloribbon/graphene composite accommodating the catholyte as the cathode of a lithium-sulfur battery. The vanadium nitride/graphene composite provides strong anchoring for polysulfides and fast polysulfide conversion. The anchoring effect of vanadium nitride is confirmed by experimental and theoretical results. Owing to the high conductivity of vanadium nitride, the composite cathode exhibits lower polarization and faster redox reaction kinetics than a reduced graphene oxide cathode, showing good rate and cycling performances. The initial capacity reaches 1,471mAhg(-1) and the capacity after 100 cycles is 1,252 mAhg(-1) at 0.2 C, a loss of only 15%, offering a potential for use in high energy lithium-sulfur batteries.", + "Times Cited, WoS Core": 1068, + "Times Cited, All Databases": 1134, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000395280000001", + "Markdown": "# Conductive porous vanadium nitride/graphene composite as chemical anchor of polysulfides for lithium-sulfur batteries \n\nZhenhua Sun1, Jingqi Zhang1, Lichang Yin1, Guangjian ${\\mathsf{H}}{\\mathsf{u}}^{1}.$ , Ruopian Fang1, Hui-Ming Cheng1,2 & Feng Li1 \n\nAlthough the rechargeable lithium–sulfur battery is an advanced energy storage system, its practical implementation has been impeded by many issues, in particular the shuttle effect causing rapid capacity fade and low Coulombic efficiency. Herein, we report a conductive porous vanadium nitride nanoribbon/graphene composite accommodating the catholyte as the cathode of a lithium–sulfur battery. The vanadium nitride/graphene composite provides strong anchoring for polysulfides and fast polysulfide conversion. The anchoring effect of vanadium nitride is confirmed by experimental and theoretical results. Owing to the high conductivity of vanadium nitride, the composite cathode exhibits lower polarization and faster redox reaction kinetics than a reduced graphene oxide cathode, showing good rate and cycling performances. The initial capacity reaches $1,471\\mathsf{m A h g}^{-1}$ and the capacity after 100 cycles is $1,252\\mathsf{m A h g}^{-1}$ at $0.2\\mathsf{C},$ a loss of only $15\\%$ , offering a potential for use in high energy lithium–sulfur batteries. \n\narge-scale electrical energy storage involves transportation and stationary applications ranging from plug-in hybrid electric vehicles and full electric vehicles to the widespread use of intermittent renewable energy in the modern electrical grid, all of which require advanced battery systems1. The high capacity and low cost of lithium–sulfur $(\\operatorname{Li-}S)$ batteries are essential for achieving practical applications2,3. These batteries possess high specific energy of $2{,}50\\dot{0}\\dot{\\mathrm{Wh}}\\mathrm{kg}^{-1}$ and $2,800\\mathrm{Whl^{-1}}$ and although their average working voltage is as low as $2.15\\mathrm{V}$ their high theoretical specific capacity of $1,672\\mathrm{mAhg}^{-1}$ can compensate for this limitation4. The practical energy density for packaged Li–S batteries may reach as high as $500{-}600\\mathrm{Wh}\\dot{\\mathrm{kg}}^{-1}\\mathrm{ol}$ r $500{-}600\\mathrm{Whl^{-1}}$ , which is sufficient for driving an electric vehicle 500 km5–7. \n\nDespite these attractive properties, one of the major issues with Li–S batteries is their sluggish reaction kinetics stemming from the high electronic resistivity of sulfur and lithium sulfides. As the resistivity of sulfur is as high as $10^{24}\\Omega\\mathrm{cm},$ it is necessary to be combined with conductive materials8. In addition, the resistivity of $\\mathrm{Li}_{2}S$ is $>10^{14}\\Omega\\ \\mathrm{cm}$ and the Li ion diffusivity in $\\mathrm{Li}_{2}\\mathrm S$ is $\\mathrm{low}^{\\mathrm{\\mathcal{G}}}$ . Once an insoluble insulation layer composed of $\\mathrm{Li}_{2}\\mathrm{S}_{2}$ and/or $\\mathrm{Li}_{2}S$ is plated on the electrode, it would increase the internal resistance, resulting in polarization that decreases energy efficiency. Moreover, the $79\\%$ volume expansion of sulfur upon cycling induces the pulverization of active materials, which often results in poor contact with current collectors to further slow reaction kinetics10. The other major issue is polysulfides $\\left(\\mathrm{Li}_{2}\\mathrm{S}_{4}–\\mathrm{Li}_{2}\\mathrm{S}_{8}\\right)$ dissolving in the electrolyte and migrating between the anode and the cathode, which causes the so-called ‘shuttle effect’ in a process in which polysulfides participate in reduction reactions with lithium and re-oxidation reactions at the cathode11,12. Despite the fact that the shuttle effect provides an overcharge protection, it causes low discharge energy capacity, thermal effects, self-discharge and low Coulombic efficiency13,14. \n\nPorous carbon-based materials used as barriers and hosts have been demonstrated to be a simple approach to suppress the polysulfide shuttle effect15–18. Owing to the large specific surface area, macropores and mesopores can encapsulate a large amount of sulfur and facilitate fast ion transport19. A microporous sulfur/carbon composite has been produced that had an unusual capacity between 1.5 and $2\\mathrm{V}$ , indicating a mixture of the two elements at the atomic level20. Nevertheless, because of the distinct non-polarity of carbon and the polarity of the $\\mathrm{Li}_{2}\\mathsf{S}_{n}$ species, the confinement of polysulfides inside the pores is mainly a result of weak physical interactions21. Some advantages of porous carbon are conflicting; for instance, a large surface area of $\\bar{\\mathrm{Li}}_{2}\\mathrm{S}_{2}$ and $\\mathrm{Li}_{2}\\mathrm{S}$ deposition is prone to cause an open structure and lead to ineffective trapping of polysulfides22, but a small pore volume limits the sulfur loading23,24. Functionalized graphene materials, such as graphene oxide obtained by the hydrothermal method, are decorated with hydroxyl and epoxide functional groups, and have chemical interactions with polysulfides25. Functional groups containing nitrogen and/or sulfur also show strong binding and are capable of anchoring polysulfides26,27. However, these functional groups are often unstable and it is difficult to control their contents28. Because of this, many groups have used polar oxides for chemically adsorbing polysulfides. For instance, $\\mathrm{MnO}_{2}$ nanosheets were used to spatially locate and control the deposition of both $\\mathrm{Li}_{2}\\mathrm{S}/\\mathrm{Li}_{2}\\mathrm{S}_{2}$ and sulfur by offering an active interface via the thiosulfate intermediate29. Silica has also been used as a polysulfide adsorbent, because of its excellent stability and high specific surface area. In conjunction with a polyethylene oxide coating on a separator, self-discharge was increased due to the strong polysulfide-silica interactions causing polysulfide diffusion from the cathode30. Nonetheless, insulating oxides ultimately impede electron transport and interrupt paths for Li ion movement, thus leading to low sulfur utilization and rate capability. It is worth noting that introducing highly conductive polar materials into the sulfur electrode is an effective means of alleviating the above issues. For example, the surface of added metallic $\\mathrm{Ti}_{4}\\mathrm{O}_{7}$ triggers the reduction of sulfur and oxidation of $\\mathrm{Li}_{2}\\mathrm{S}$ by forming an excellent interface with polysulfides31. Similarly, the addition of MXene phase $\\mathrm{Ti}_{2}\\mathrm{\\bar{C}}$ introduces exposed terminal metal sites that bond with sulfur as a result of an interface-mediated reduction32. Metal nitrides with a high electrical conductivity can be an ideal anchoring material. A generalized gradient approximation and local density approximation analysis of a series of transition metal nitrides (TiN, VN, CrN, ZrN and NbN) indicate the metallic behaviour of these materials with no resolved band $\\mathrm{gap}^{33}$ . Among metal nitrides, vanadium nitride (VN) has a number of desirable properties for a potential host materials for sulfur including the following: (1) a strong chemical adsorption for polysulfides that can effectively inhibit the shuttle effect, (2) a high electrical conductivity $(1.17\\times10^{6}\\mathrm{Sm}^{-1}$ at room temperature) (Supplementary Table 1) that is conducive to the electrochemical conversion of adsorbed sulfur species on the surface and (3) catalytic properties similar to the precious metals that may facilitate redox reaction kinetics. \n\n![](images/c4f69275e991ad5bf3b74140de40718c739712260efea50818f1858ff019050e.jpg) \nFigure 1 | Schematic of fabrication process of VN/G composite and cell assembly. Schematic of the fabrication of a porous VN/G composite and the cell assembly with corresponding optical images of the material obtained. Scale bar, $500\\mathsf{n m}$ . \n\n![](images/3ac5c0d563204793769edadef285d235bd4848cdea8d5092e74428c7dde43897.jpg) \nFigure 2 | Morphology and structural characterization of the VN/G composite. (a) Low-magnification SEM image, (b) high-magnification SEM image, (c) high-angle annular dark-field (HAADF) STEM image and (d,e) TEM images of the as-prepared porous VN/G composite. (f) High-resolution TEM (HRTEM) image, with inset showing the fast Fourier transform (FFT) pattern. Scale bars, (a) $100\\upmu\\mathrm{m};$ (b) $2\\upmu\\mathrm{m};$ (c) $500\\mathsf{n m}.$ ; (d) $500\\mathsf{n m};$ (e) $50\\mathsf{n m}$ ; (f) 5 nm. \n\nHere we report a highly conductive porous VN nanoribbon/ graphene (VN/G) composite accommodating a suitable amount of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte as the cathode of Li–S batteries without using carbon black and binder. The free-standing three-dimensional (3D) interconnected network of the graphene facilitates the transportation of electrons and lithium ions, and the VN not only shows strong chemical anchoring of the polysulfides, but also accelerates the redox reaction kinetics. The anchoring of polysulfides by VN is investigated in a dissolved polysulfide system and further verified by theoretical calculations. The VN/G cathode delivers a high specific capacity of $1,461\\mathrm{mAhg}^{-1}$ at $0.2\\mathrm{C}$ , a Coulombic efficiency approaching $100\\%$ , and a highrate performance of $956\\mathrm{mAh}\\dot{\\mathrm{g}}^{-1}$ at $2\\mathrm{C}$ \n\n![](images/1d5da896bb493fb7446f0eba0f2de3dd25cc5e111a323cc2accc481ea367fe51.jpg) \nFigure 3 | Compositional information of the VN/G composite. (a) X-ray diffraction (XRD) pattern and (b) thermogravimetric-differential scanning calorimetry (TG-DSC) curve of the $V N/G$ composite. \n\n# Results \n\nSynthesis and characterization of VN/G composite. As illustrated in Fig. 1, the synthesis of a porous VN/G composite involves two steps. We first obtained a vanadium oxide/graphene $\\mathrm{(VO_{\\itx}/G)}$ hydrogel by a hydrothermal method using graphene oxide and $\\mathrm{NH_{4}V O_{3}}$ as precursors. $\\mathrm{VO}_{x}$ was grown in situ on the surface of the graphene oxide and simultaneously assembled into a 3D foam. After immersion in deionized water, the product was subjected to freeze-drying and a $\\mathrm{VO}_{x}/\\mathrm{G}$ macrostructure was formed. After annealing in a $\\mathrm{NH}_{3}$ atmosphere, the free-standing VN/G composite was obtained. The final product can be cut and pressed into plates for direct use as Li–S battery electrodes without a metal current collector, binder and conductive additive. \n\nThe morphology and microstructure of the VN/G composite were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) as shown in Fig. 2. SEM images reveal that 3D interconnected network of VN nanoribbons and reduced graphene oxide (RGO) sheets. Numerous voids, several micrometres in size, are able to hold a large amount of sulfur and provide good penetration of electrolyte (Fig. 2a,b). This skeleton structure not only enhances the electron and lithium ion transportation but also accommodates the volume expansion of sulfur. The elemental mappings of vanadium, nitrogen, carbon and oxygen further reveal the hybrid structure of the VN/G composite (Supplementary Fig. 1). To see this more clearly, we then characterized the structure using a high-angle annular dark-field scanning TEM (STEM) and TEM in Fig. 2c–e. The VN nanoribbons are typically $50\\mathrm{-}100\\mathrm{nm}$ wide and $1{-}2\\upmu\\mathrm{m}$ long. Compared with the product before annealing in $\\mathrm{NH}_{3}$ (Supplementary Fig. 2), VN nanoribbons contains a large number of mesopores ranging from 10 to $30\\mathrm{nm}$ in diameter, which are beneficial for both the ion transportation and the adsorption of polysulfides in the electrochemical process. A representative high-resolution TEM image and the fast Fourier transform pattern are also shown in Fig. 2f, revealing lattice fringes with a spacing of $0.20\\mathrm{nm}$ , which is in agreement with spacing of the (200) plane of VN. The graphene in the VN/G composite provides a supporting framework to prevent the aggregation of the VN nanoribbons. \n\nThe crystal structure of the 3D VN/G composite was further examined by X-ray diffraction (Fig. 3a). The major peaks are assigned to cubic VN (JCPDS card number 73-0528) with a wide peak around $26^{\\circ}$ corresponding to graphene stacking. Thermogravimetric-differential scanning calorimetry analysis suggested that the VN content was $30\\%$ (Fig. 3b). The specific surface area of the VN/G was $37\\mathrm{m}^{2}\\mathrm{g}^{-1}$ with mesopores $18\\mathrm{nm}$ in diameter (Supplementary Fig. 3), which is consistent with the TEM observation. In contrast, the specific surface area of the RGO was as high as $296\\mathrm{m}^{2}\\mathrm{g}^{-1}$ (Supplementary Fig. 4). \n\nThe electrochemical performance of VN/G cathodes. A series of electrochemical measurements were carried out to evaluate the performance of the VN/G cathode. In the cell assembly process, $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte was directly added to VN/G (Fig. 1). The final areal sulfur loading of the electrode was $3\\mathrm{mg}\\mathrm{cm}^{-2}$ . Typical cyclic voltammetry (CV) profiles for the RGO and VN/G electrodes were obtained within a potential window of $1.7{-}2.8\\mathrm{V}$ at a scan rate of $0.1\\mathrm{mVs}^{-1}$ (Fig. 4a), both showing two cathodic peaks and two anodic peaks. The two representative cathodic peaks can be attributed to the reduction of sulfur to long-chain lithium polysulfides $(\\mathrm{Li}_{2}\\mathrm{S}_{x},3\\leq x\\leq8)$ at the higher potential and the formation of insoluble short-chain $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ at the lower potential. When scanning back, the anodic peaks corresponded to the oxidation of $\\mathrm{Li}_{2}\\mathrm{S}/\\mathrm{Li}_{2}\\bar{\\mathrm{S}}_{2}$ to polysulfides and then to sulfur. It is interesting to note that the reduction peaks with the VN/G cathode (2.0 and $2.35\\mathrm{V}.$ ) appeared at higher potentials than those with the RGO cathode (1.88 and $2.24\\mathrm{V}$ ). The distinguishable positive shift in the reduction peaks and negative shift in the oxidation peaks of the VN/G cathode indicate the improved polysulfide redox kinetics by VN. According to recent reports, $\\mathrm{Pt}$ as an electrocatalyst can help to convert polysulfide deposits back to soluble long-chain polysulfide and hence enhance reaction kinetics and retain high Coulombic efficiency, and the catalytic activities of VN resemble those of noble metal $\\mathrm{Pt}^{34,35}$ . These results suggest that VN has similar catalytic activity to that of precious metals, which can improve the redox reaction kinetics. Galvanostatic charge/discharge tests (Fig. 4b) were further performed at a constant current rate of $0.2\\mathrm{C}$ (based on the mass of sulfur in the cell, $1{\\mathrm{C}}=1{,}675{\\mathrm{mAg}}^{-1}{\\mathrm{,}}$ ). The charge– discharge profiles of VN/G consist of two discharge plateaus at 2.35 and $2.05\\mathrm{V}_{:}$ , and two charge plateaus between 2.2 and $2.45\\mathrm{V}$ respectively, which are in agreement with the CV curves. The plateaus were longer and flatter with a higher capacity and a lower polarization than those using the RGO electrode, suggesting a kinetically efficient reaction process. Figure 4c shows the cycling performance of the VN/G and RGO cathodes. The VN/G cathode delivered an excellent initial discharge capacity of $1{,}471\\mathrm{mAhg}^{-1}$ and, more importantly, it was able to maintain a stable cycling performance with a Coulombic efficiency above $99.5\\%$ for 100 charge–discharge cycles at $0.2\\mathrm{C}_{:}$ indicating that dissolution of polysulfides into the organic electrolyte was effectively mitigated in the VN/G electrode. The $\\mathrm{LiNO}_{3}$ additive in the electrolyte also has a positive effect on the Coulomb efficiency and cyclic performance of Li–S batteries36. It was also confirmed that the VN/G host contributed almost nothing to the measured capacity (Supplementary Fig. 5). In contrast, the RGO cathode showed a lower discharge capacity of $1,070\\mathrm{mAhg}^{-1}$ in the initial cycle and rapid capacity decay with a capacity retention of $47\\%$ after 100 cycles, implying low sulfur utilization with severe polysulfide dissolution into the electrolyte. In the electrochemical impedance spectroscopy measurements (Supplementary Fig. 6), the Nyquist plots obtained consist of two parts, a semicircle in the high-frequency region representing the charge transfer resistance and a straight line in the low-frequency region associated with the mass transfer process. The VN/G cathode has a smaller resistance $(28\\Omega)$ than that of the RGO cathode $(95\\Omega)$ , which can be explained by enhanced interfacial affinity between VN and polysulfides, and the high electrical conductivity of metal nitrides comparable to their metal counterparts, as shown in Supplementary Table 1. In addition, the VN/G composite also exhibits an electrical conductivity of $\\approx1,150\\mathrm{Sm}^{-1}$ measured by the four-point probe method, which is over four times larger than that of RGO (about $240\\mathrm{Sm}^{-1}.$ , even though RGO contains doping nitrogen (about $4.6\\%$ ) after $\\mathrm{NH}_{3}$ annealing (Supplementary Fig. 7). Although N-doped graphene can improve the performance of Li–S batteries, but the electrochemical performance of VN/G composite electrode was much better than that of RGO electrode in the same condition. As shown in Fig. 4d, when the electrode was cycled at different rates of $0.2\\mathrm{C},0.5\\mathrm{C},1\\mathrm{C},2\\mathrm{C}$ and $3\\mathrm{C}_{:}$ , the cell was able to deliver discharge capacities of 1,447, 1,241, 1,131, 953 and $701\\mathrm{{mAh}\\ g^{-1}}$ , respectively. In contrast, the RGO electrode exhibited lower discharge capacity and poorer stability under the same conditions. Moreover, a stable discharge capacity of $1,148\\mathrm{mAhg}^{-1}$ was recovered as soon as the current density was restored to 1 C. Figure 4e shows the long-term cyclability of VN/ G electrode at ${\\mathrm{~1~C~}}_{:}$ indicating an excellent cycling stability. The initial capacity was as high as $1,128\\mathrm{mAhg^{-1}}$ and retained $81\\%$ of the initial capacity $(917\\mathrm{mAh}\\mathrm{g}^{-1}\\dot{}\\mathrm{~,~}$ ) after 200 cycles. Although higher polarization occurred in the electrodes at higher rates due to slower dynamics of sulfur, the charge–discharge profiles still consist of two plateaus even at a very high current density (Supplementary Fig. 8). In contrast, the $\\mathrm{VO}_{x}/\\mathrm{G}$ electrode displayed rapid capacity decay and low Coulombic efficiency (about $93\\%$ after 100 cycles), which probably resulted from the low conversion efficiency of polysulfides adsorbed on non-conductive $\\mathrm{VO}_{x}$ surfaces (Supplementary Fig. 9). The excellent electrochemical performance of the VN/G cathode can be attributed to the following factors. First, the porous VN host provides a polar surface and a strong chemical interaction with polysulfides, effectively inhibiting the shuttle effect. Second, the high electrical conductivity of VN enhances redox electron transfer and reduces interfacial impedance, and accelerates the polysulfide conversion. Third, VN has similar catalytic activity to that of the precious metals, which improves the redox reaction kinetics. \n\n![](images/40873a2780aa9454cb2d54fbd02252cecbe89dca34988a9dbdfaa6596c4951a6.jpg) \nFigure 4 | Electrochemical performances of VN/G and RGO cathodes. (a) CV profiles of the VN/G and RGO cathodes at a scan rate of $0.1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in a potential window from 1.7 to $2.8{\\sf V}.$ (b) Galvanostatic charge–discharge profiles of the VN/G and RGO cathodes at $_{0.2\\mathsf{C}}$ $\\mathbf{\\eta}(\\bullet)$ Cycling performance and Coulombic efficiency of the VN/G and RGO cathodes at $_{0.2\\mathsf{C}}$ for 100 cycles. (d) Rate performance of the VN/G and RGO cathodes at different current densities. (e) Cycling stability of the $V N/G$ cathode at 1 C for 200 cycles. \n\n![](images/4ad57998f55aa2572d0803fa4cc59c61d40a6e627c6fec2b0ff281fe433226e8.jpg) \nFigure 5 | Demonstration of the strong interaction of VN/G composite with polysulfides. (a) Ultraviolet/visible absorption spectra of a $\\mathsf{L i}_{2}\\mathsf{S}_{6}$ solution before and after the addition of RGO and VN/G. Inset image shows a photograph of a ${\\mathsf{L i}}_{2}{\\mathsf{S}}_{6}$ solution before and an $2h$ after the addition of graphene and VN/G. (b) Side view of a ${\\mathsf{L i}}_{2}{\\mathsf{S}}_{6}$ molecule on a nitrogen-doped graphene surface, the binding energy between $\\mathsf{L i}_{2}\\mathsf{S}_{6}$ and pyridinic N-doped graphene is calculated to be $1.07\\mathrm{eV.}$ (c) Side view of a ${\\mathsf{L i}}_{2}{\\mathsf{S}}_{6}$ molecule on VN (200) surface, the binding energy between ${\\mathsf{L i}}_{2}{\\mathsf{S}}_{6}$ and VN is calculated to be $3.75\\mathrm{eV.}$ \n\n# Discussion \n\nTo verify the strong anchoring of VN for polysulfides, as shown in Fig. 5a, we compared the polysulfide adsorption ability of \n\nRGO and the VN/G composite, after adding $20\\mathrm{mg}$ of their powders to $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution for $2\\mathrm{h}$ . The VN/G completely decoloured the polysulfide solution, whereas the solution containing RGO remained the same bright yellow colour. Ultraviolet/visible absorption measurements were also made to investigate the concentration changes of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solutions after adding RGO or VN/G. It can be clearly seen that the absorption peak of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ in the visible light range apparently disappeared after adding VN/G, but remained after adding RGO (Fig. 5a). This difference suggests strong adsorption of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ molecules to polar VN, owing to ionic bonding of V–S. The surface compositions of VN/G composite were measured by $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy survey spectra indicates that the surface of the VN also contains small amounts of $_{\\mathrm{V-N-O}}$ and $_{\\mathrm{V-O}}$ bonds, which have a high affinity for polysulfides (Supplementary $\\mathrm{Fig.}\\ 10)^{37}$ . The strong interaction between VN and lithium polysulfides was further verified by an evaluation of the binding energies between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and VN based on density functional theory calculations (Supplementary Note 1). As shown in the Supplementary Fig. 7, the pyridinic-N is the dominant dopant in N-doped graphene synthesized in this work. For comparison, the binding energy between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and pyridinic N-doped graphene was considered, and it has been reported to be $1.0\\dot{7}\\mathrm{eV}^{3\\8}$ . In contrast, the binding energy between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and VN was calculated to be much larger $(3.75\\mathrm{eV})$ . This is mainly due to the much stronger polar–polar interactions between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and VN than those between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and pyridinic N-doped graphene. In comparison with the case of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ on pyridinic N-doped graphene (Fig. 5b), the strong polar– polar interaction between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and VN results in an obvious deformation of the $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ molecule (Fig. 5c), forming three $_{\\mathrm{{S-V}}}$ and one Li–N bonds. The bond lengths of these S–V $(2.49{-}2.61\\mathring\\mathrm{A})$ and Li–N $(2.08\\mathring\\mathrm{A})$ bonds are very close to the corresponding bond lengths in bulk VS $(2.42\\mathring\\mathrm{A})$ and $\\mathrm{LiNH}_{2}$ $(2.06\\mathring\\mathrm{A})$ , respectively39,40. These results clearly show the good affinity and strong chemical anchoring of polar VN for polysulfides. In addition, the non-polarity of graphene in the VN/G composite can also be beneficial for the redeposition of the charging product sulfur. The hetero-polar VN/G electrodes provide both polar (VN) and non-polar (graphene) platforms to facilitate the binding of solid $\\operatorname{Li}_{x}S$ and sulfur species to the electrodes. STEM elemental mapping was performed to track the sulfur distribution in the VN nanoribbons after cycling. The high-angle annular dark-field STEM image and corresponding elemental maps of vanadium, nitrogen and sulfur show that the sulfur species were uniformly distributed and strongly adsorbed on the surface of the VN nanoribbons (Fig. 6). This result verifies the experimental observations and corresponding theoretical calculations. \n\nIn summary, we have used a 3D highly conductive porous VN/G composite to solve the shuttle effect in Li–S batteries. This composite combines the advantages of both graphene and VN. The 3D free-standing structure composed of a graphene network facilitates electron and ion transportation, but is also beneficial to electrolyte absorption. In addition, VN showed a strong anchoring effect for polysulfides and its high conductivity also accelerated the polysulfide conversion. The VN/G electrode exhibited excellent specific capacity with a Coulombic efficiency reaching $599\\%$ compared with the RGO electrodes. We believe that other highly conductive metal nitrides can also be used for high-energy Li–S batteries and our design opens a new direction of the electrochemical use of transition metal nitrides for energy storage. \n\n# Methods \n\nPreparation of a 3D porous VN/G composite. The VN/G composites were prepared using hydrothermal method, according to the previously reported procedure41. Specifically, $0.05\\mathrm{g}\\mathrm{NH}_{4}\\mathrm{VO}_{3}$ was dissolved in a mixture of $45\\mathrm{ml}$ water and $5\\mathrm{ml}$ ethanol, followed by slowly adding drops of HCl (2 M) to adjust the $\\mathsf{p H}$ of the solution to 2–3. Next, $30\\mathrm{ml}$ of a graphene oxide suspension $(5\\mathrm{{mg}\\mathrm{{ml}^{-1})}}$ was added to the solution under continuous stirring. The mixture was then transferred to a $100\\mathrm{ml}$ Teflon-lined autoclave, which was heated to $180^{\\circ}\\mathrm{C}$ where it was maintained for $24\\mathrm{h}$ . The as-prepared sample was rinsed with deionized water several times followed by freeze-drying for 2 days. Finally, the obtained product was heated at $550^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ in an $\\mathrm{NH}_{3}$ (30 s.c.c.m.) atmosphere. For comparison, a 3D RGO structure was prepared following the same procedure. The 3D porous $\\mathrm{VO}_{x}/\\mathrm{G}$ composite was also synthesized using a process similar to that for the synthesis of VN/G composite, except that the atmosphere of the heat treatment was changed from ammonia to argon. \n\n![](images/4711b4e4e9e5846ec8b9b00558601d6595f12edfcc97c0e25c4435718665e645.jpg) \nFigure 6 | Sulfur distribution in the VN nanoribbons after cycling. (a) STEM image of a VN nanoribbon after cycling with the corresponding elemental maps of (b) vanadium, (c) nitrogen and (d) sulfur. Scale bars, $100\\mathsf{n m}$ . \n\nPreparation of the $\\mathbf{Li}_{2}\\mathcal{S}_{6}$ solution. Sulfur and $\\mathrm{Li}_{2}\\mathrm S$ at a molar ratio of 5:1 were added to an appropriate amount of 1,2-dimethoxyethane and 1,3-dioxolane by vigorous magnetic stirring at $50^{\\circ}\\mathrm{C}$ until the sulfur was fully dissolved. \n\nPolysulfide adsorption test. A solution with a $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ concentration of $50\\mathrm{\\dot{m}m o l l^{-1}}$ (calculated based on sulfur content) was used. Twenty milligrams of VN/G and RGO powder were separately added to $2.0\\mathrm{ml}$ of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution and the mixtures were stirred to obtain thorough adsorption. A blank glass vial was also filled with the same $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution as a comparison. \n\nPreparation of sulfur electrodes. A VN/G composite was cut and compressed into $1.5\\mathrm{mg}\\mathrm{VN/G}$ electrode. Next, inside an Argon-filled glovebox, $30\\upmu\\mathrm{l}\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte equal to $1.92\\mathrm{mg}$ of sulfur and $60\\upmu\\mathrm{l}$ of electrolyte was used to form the sulfur electrode. The final areal sulfur loading of the electrode was determined about $3\\mathrm{mg}\\mathrm{cm}^{-2}$ . \n\nMaterials characterization. The morphology and structure of the materials were characterized using a SEM (FEI Nova NanoSEM 450, 15 kV). TEM imaging was performed on a FEI CM120 microscope. High-resolution TEM images, STEM images and energy dispersive X-ray spectroscopy (EDX) elemental maps were obtained on a FEI Tecnai F20 microscope equipped with an Oxford EDX analysis system with an acceleration voltage of $200\\mathrm{kV}$ . X-ray diffraction patterns were obtained on a Rigaku diffractometer (Cu $\\begin{array}{r}{{\\ K}_{\\infty},}\\end{array}$ $\\lambda=0.154056\\mathrm{nm},$ . Thermogravimetric-differential scanning calorimetry analysis (TGA) was performed with a NETZSCH STA 449 C thermo balance in air with a heating rate of $10^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ from room temperature to $1,000^{\\circ}\\mathrm{C}$ . The X-ray photoelectron spectroscopy measurements were carried out in an ultra-high vacuum ESCALAB 250 set-up equipped with a monochromatic Al $\\mathsf{K}\\mathsf{\\mathfrak{x}}$ X-ray source $(1486.6\\mathrm{eV};$ anode operating at $15\\mathrm{kV}$ and $20\\mathrm{mA}$ ). Ultraviolet/visible absorption spectroscopy analysis (Cary 5000) was performed to evaluate the polysulfide adsorption capability of RGO and VN/G. The electrical conductivities were measured by a standard four-point-probe resistivity measurement system (RTS-9, Guangzhou, China). $\\Nu_{2}$ adsorption/ desorption isotherms were determined using a Micromeritics ASAP2020M instrument. Before the measurements, the samples were degassed at $200^{\\circ}\\mathrm{C}$ until a manifold pressure of $2\\mathrm{mmHg}$ was reached. The surface area and pore size distribution were determined based on the Barrett–Joyner–Halenda method. \n\nElectrochemical measurements. Stainless steel coin cells (2,032-type) were assembled inside an Ar-filled glovebox. The electrolyte was lithium bis-trifluoromethaesulphonylimide $(99\\%$ , Acros Organics, 1 M) dissolved in 1,3-dioxolane $(99.5\\%$ , Alfa Asea) and 1,2-dimethoxyethane $(99.5\\%$ , Alfa Aesar) (1:1 ratio by volume) with $0.2\\ensuremath{\\mathrm{M}}$ lithium nitrate $\\mathrm{(LiNO_{3}}$ $99.9\\%$ , Alfa Aesar) as the additive. Lithium metal foil was used as the anode and Celgard 2400 as the separator. A Landian multichannel battery tester was used to perform electrochemical measurements. The charge-discharge voltage range was $1.7{-}2.8\\mathrm{V}$ The CV and the electrochemical impedance spectroscopy measurements were performed on a VSP-300 multichannel workstation. \n\nData availability. The authors declare that the data supporting the findings of this study are available within the article and its Supplementary Information files. All other relevant data supporting the findings of this study are available from the corresponding author on request. \n\n# References \n\n1. Armand, M. & Tarascon, J. M. Building better batteries. Nature 451, 652–657 (2008). \n2. Larcher, D. & Tarascon, J. M. Towards greener and more sustainable batteries for electrical energy storage. Nat. Chem. 7, 19–29 (2015). \n3. Goodenough, J. B. Energy storage materials: a perspective. Energy Storage Mater. 1, 158–161 (2015). \n4. Ji, X. & Nazar, L. F. Advances in Li–S batteries. J. Mater. Chem. 20, 9821–9826 (2010). \n5. Bruce, P. G., Freunberger, S. A., Hardwick, L. J. & Tarascon, J.-M. Li- ${\\bf\\cal O}_{2}$ and Li-S batteries with high energy storage. Nat. Mater. 11, 19–29 (2012). \n6. Fang, X. & Peng, H. S. A revolution in electrodes: recent progress in rechargeable lithium–sulfur batteries. Small 11, 1488–1511 (2015). \n7. Liang, J., Sun, Z. H., Li, F. & Cheng, H.-M. Carbon materials for Li–S batteries: functional evolution and performance improvement. Energy Storage Mater. 2, 76–106 (2016). \n8. Ji, L. et al. Graphene oxide as a sulfur immobilizer in high performance lithium/sulfur cells. J. Am. Chem. Soc. 133, 18522–18525 (2011). \n9. Yang, Y. et al. High-capacity micrometer-sized $\\mathrm{Li}_{2}\\mathrm{S}$ particles as cathode materials for advanced rechargeable lithium-ion batteries. J. Am. Chem. Soc. 134, 15387–15394 (2012). \n10. Wei Seh, Z. et al. Sulphur– $\\cdot\\mathrm{TiO}_{2}$ yolk–shell nanoarchitecture with internal void space for long-cycle lithium–sulphur batteries. Nat. Commun. 4, 1331 (2013). \n11. Nazar, L. F., Cuisinier, M. & Pang, Q. Lithium-sulfur batteries. MRS Bull. 39, 436–442 (2014). \n12. Busche, M. R. et al. Systematical electrochemical study on the parasitic shuttleeffect in lithium-sulfur-cells at different temperatures and different rates. J. Power Sources 259, 289–299 (2014). \n13. Bruce, P. G., Hardwick, L. J. & Abraham, K. M. Lithium-air and lithium-sulfur batteries. MRS Bull. 36, 506–512 (2011). \n14. Manthiram, A., Fu, Y., Chung, S.-H., Zu, C. & Su, Y.-S. Rechargeable lithium– sulfur batteries. Chem. Rev. 114, 11751–11787 (2014). \n15. Schuster, J. et al. Spherical ordered mesoporous carbon nanoparticles with high porosity for lithium–sulfur batteries. Angew. Chem. Int. Ed. 51, 3591–3595 (2012). \n16. Zheng, G., Yang, Y., Cha, J. J., Hong, S. S. & Cui, Y. Hollow carbon nanofiberencapsulated sulfur cathodes for high specific capacity rechargeable lithium batteries. Nano Lett. 11, 4462–4467 (2011). \n17. Elazari, R., Salitra, G., Garsuch, A., Panchenko, A. & Aurbach, D. Sulfurimpregnated activated carbon fiber cloth as a binder-free cathode for rechargeable Li-S batteries. Adv. Mater. 23, 5641–5644 (2011). \n18. Huang, J. Q., Zhang, Q. & Wei, F. Multi-functional separator/interlayer system for high-stable lithium-sulfur batteries: progress and prospects. Energy Storage Mater. 1, 127–145 (2015). \n19. Wang, D.-W. et al. Carbon–sulfur composites for Li–S batteries: status and prospects. J. Mater. Chem. A 1, 9382–9394 (2013). \n20. Zhang, B., Qin, X., Li, G. R. & Gao, X. P. Enhancement of long stability of sulfur cathode by encapsulating sulfur into micropores of carbon spheres. Energy Environ. Sci. 3, 1531–1537 (2010). \n21. Zhang, Q. et al. Understanding the anchoring effect of two-dimensional layered materials for lithium–sulfur batteries. Nano Lett. 15, 3780–3786 (2015). \n22. Yang, Y., Zheng, G. & Cui, Y. Nanostructured sulfur cathodes. Chem. Soc. Rev. 42, 3018–3032 (2013). \n23. Zhang, S. S. Liquid electrolyte lithium/sulfur battery: fundamental chemistry, problems, and solutions. J. Power Sources 231, 153–162 (2013). \n24. Jia, X. et al. Evolution of the effect of sulfur confinement in graphene-based porous carbons for use in Li–S batteries. Nanoscale 8, 4447–4451 (2016). \n25. Zhou, G. M. et al. Fibrous hybrid of graphene and sulfur nanocrystals for highperformance lithium–sulfur batteries. ACS Nano 7, 5367–5375 (2013). \n26. Zhou, G. M., Paek, E., Hwang, G. S. & Manthiram, A. Long-life Li/polysulphide batteries with high sulphur loading enabled by lightweight three-dimensional nitrogen/sulphur-codoped graphene sponge. Nat. Commun. 6, 7760 (2015). \n27. Qiu, Y. et al. High-rate, ultralong cycle-life lithium/sulfur batteries enabled by nitrogen-doped graphene. Nano Lett. 14, 4821–4827 (2014). \n28. Song, M.-K., Zhang, Y. & Cairns, E. J. A long-life, high-rate lithium/sulfur cell: a multifaceted approach to enhancing cell performance. Nano Lett. 13, 5891–5899 (2013). \n29. Liang, X. et al. A highly efficient polysulfide mediator for lithium–sulfur batteries. Nat. Commun. 6, 5682 (2015). \n30. Zhang, S. S. A concept for making poly (ethylene oxide) based composite gel polymer electrolyte lithium/sulfur battery. J. Electrochem. Soc. 160, A1421–A1424 (2013). \n31. Pang, Q., Kundu, D., Cuisinier, M. & Nazar, L. F. Surface-enhanced redox chemistry of polysulphides on a metallic and polar host for lithium-sulphur batteries. Nat. Commun. 5, 4759 (2014). \n32. Liang, X., Garsuch, A. & Nazar, L. F. Sulfur cathodes based on conductive MXene nanosheets for high-performance lithium-sulfur batteries. Angew. Chem. Int. Ed. 54, 3907–3911 (2015). \n33. Brik, M. G. & Ma, C. G. First-principles studies of the electronic and elastic properties of metal nitrides XN $(\\mathrm{X}=\\mathrm{S}\\mathrm{c}_{\\mathrm{:}}$ , Ti, V, Cr, Zr, Nb). Comput. Mater. Sci. 51, 380–388 (2012). \n34. Al Salem, H., Babu, G., Rao, C. V. & Arava, L. M. R. Electrocatalytic polysulfide traps for controlling redox shuttle process of Li-S batteries. J. Am. Chem. Soc. 137, 11542–11545 (2015). \n35. Huang, K. et al. Novel VN/C nanocomposites as methanol-tolerant oxygen reduction electrocatalyst in alkaline electrolyte. Sci. Rep. 5, 11351 (2015). \n36. Aurbach, A. et al. On the surface chemical aspects of very high energy density, rechargeable Li–sulfur batteries. J. Electrochem. Soc. 160, A694–A702 (2009). \n37. Liang, X. et al. Tuning transition metal oxide–sulfur interactions for long life lithium sulfur batteries: the ‘Goldilocks’ principle. Adv. Energy Mater. 6, 1501636 (2016). \n38. Yin, L. C. et al. Understanding the interactions between lithium polysulfides and N-doped graphene using density functional theory calculations. Nano Energy 25, 203–210 (2016). \n39. Wyckoff, R. W. G. in Crystal Structures 2nd edn (Interscience Publishers, 1963). \n40. Jacobs, H. & Juza, R. Redefinition of the crystal structure of the lithiumamids. Anorg. Allg. Chem. 391, 271–279 (1972). \n41. Wang, R. T. et al. Fast and large lithium storage in 3D porous VN nanowiresgraphene composite as a superior anode toward high-performanc hybrid supercapacitors. Adv. Funct. Mater. 25, 2270–2278 (2015). \n\n# Acknowledgements \n\nWe acknowledge financial support from MOST (2016YFA0200100, 2014CB932402 and 2016YFB0100100) and the National Science Foundation of China (numbers 51525206, 51521091, 51472249, 51372253, 51272051 and U1401243), Youth Innovation Promotion Association of the Chinese Academy of Sciences (number 2015150), the Natural Science Foundation of Liaoning province (number 2015021012), the Institute of Metal Research (number 2015-PY03) and ‘Strategic Priority Research Program’ of the Chinese Academy of Sciences (XDA09010104), the Key Research Program of the Chinese Academy of Sciences (grant number KGZD-EW-T06) and the CAS/SAFEA International Partnership Program for Creative Research Teams. The theoretical calculations were performed on TianHe-1(A) of National Suercomputer Center in Tianjin. We thank Dr Wei Lv and Professor Quanhong Yang for helping in experiments. \n\n# Author contributions \n\nZ.S. and F.L. designed the research. Z.S. conducted the electrochemical experiments and characterization of materials, and J.Z. prepared the materials. L.Y. performed density functional theory calculations. G.H. and R.F. contributed to the discussion of the results. Z.S., J.Z., H.-M.C. and F.L. wrote the paper. All the authors commented on and revised the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Sun, Z. et al. Conductive porous vanadium nitride/graphene composite as chemical anchor of polysulfides for lithium-sulfur batteries. Nat. Commun. 8, 14627 doi: 10.1038/ncomms14627 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1021_acsnullo.6b08415", + "DOI": "10.1021/acsnullo.6b08415", + "DOI Link": "http://dx.doi.org/10.1021/acsnullo.6b08415", + "Relative Dir Path": "mds/10.1021_acsnullo.6b08415", + "Article Title": "MXene Ti3C2: An Effective 2D Light-to-Heat Conversion Material", + "Authors": "Li, RY; Zhang, LB; Shi, L; Wang, P", + "Source Title": "ACS nullO", + "Abstract": "MXene, a new series of 2D material, has been steadily advancing its applications to a variety of fields, such as catalysis, supercapacitor, molecular separation, electromagnetic wave interference shielding. This work reports a carefully designed aqueous droplet light heating system along with a thorough mathematical procedure, which combined leads to a precise determination of internal light-to-heat conversion efficiency of a variety of nullomaterials. The internal light-to-heat conversion efficiency of MXene, more specifically Ti3C2, was measured to be 100%, indicating a perfect energy conversion. Furthermore, a self-floating MXene thin membrane was prepared by simple vacuum filtration and the membrane, in the presence of a rationally chosen heat barrier, produced a light-to-water evaporation efficiency of 84% under one sun irradiation, which is among the state of art energy efficiency for similar photothermal evaporation system. The outstanding internal light-to-heat conversion efficiency and great light-to-water evaporation efficiency reported in this work suggest that MXene is a very promising light-to-heat conversion material and thus deserves more research attention toward practical applications.", + "Times Cited, WoS Core": 1392, + "Times Cited, All Databases": 1451, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000400233200033", + "Markdown": "# MXene Ti3C2: An Effective 2D Light-to-Heat Conversion Material \n\nRenyuan Li,† Lianbin Zhang,‡ Le Shi,† and Peng Wang\\*,† †Water Desalination and Reuse Center, Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia ‡Key Laboratory of Materials Chemistry for Energy Conversion and Storage of Ministry of Education, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China \n\nSupporting Information \n\nABSTRACT: MXene, a new series of 2D material, has been steadily advancing its applications to a variety of fields, such as catalysis, supercapacitor, molecular separation, electromagnetic wave interference shielding. This work reports a carefully designed aqueous droplet light heating system along with a thorough mathematical procedure, which combined leads to a precise determination of internal light-to-heat conversion efficiency of a variety of nanomaterials. The internal light-toheat conversion efficiency of MXene, more specifically ${\\bf T i}_{3}{\\bf C}_{2},$ was measured to be $100\\%$ , indicating a perfect energy conversion. Furthermore, a self-floating MXene thin membrane was prepared by simple vacuum filtration and the membrane, in the presence of a rationally chosen heat barrier, produced a light-to-waterevaporation efficiency of $84\\%$ under one sun irradiation, which is among the state of art energy efficiency for similar photothermal evaporation system. The outstanding internal light-to-heat conversion efficiency and great light-to-water evaporation efficiency reported in this work suggest that MXene is a very promising light-to-heat conversion material and thus deserves more research attention toward practical applications. \n\n![](images/b4f717ed70aeca3ff28aa4da7a4a2953e723331392ea0841974b4c9bf0ab9c48.jpg) \n\nKEYWORDS: MXene, $T i_{3}C_{2},$ light-to-heat conversion, photothermal, water evaporation \n\nM aeXanerdln g annenrsiaetlilwonspermioedtsu lcoefcda bDiydesmsealatencrtdia/vloesl oaertmcbphoionsigtediodeuostf the A layers from $\\mathbf{M}_{n+1}\\mathbf{A}\\mathbf{X}_{n}$ phases, where M is an early transition metal, A is mainly a group IIIA or IVA (i.e., group 13 or 14) element, X is C and/or N, and $n=1,2,$ or $3,^{1}$ was first introduced by Gogotsi’s group in 2011 and has since been growing its family steadily and finding itself many exciting applications,2 including catalysis,3,4 battery,5,6 supercapacitor s,7,8 molecular separation,9 etc. \n\nVery recently, it has been reported that MXene and MXenepolymer composite films produced a record-breaking electromagnetic interference shielding effect, which is a direct result of excellent electromagnetic wave absorption property by pristine MXene and its composites. Furthermore, as a top-of-the-line electromagnetic interference shielding material, MXene allows negligible electromagnetic wave emission and the ultimate fate of the absorbed waves is to dissipate in the form of heat within the material.10 The discovery is thought-provoking and inspires us to look into MXene’s interaction with more ubiquitous electromagnetic waves present in our daily life: sunlight. Although there exists no prior art, we believe MXene’s excellent electromagnetic wave absorption and subsequent heat generation put it on the way to be an excellent light-to-heat conversion material. \n\nLight-to-heat, also known as photothermal conversion, a seemingly primitive and ancient means of utilizing solar energy involves harvesting and converting solar irradiation by photothermal materials into heat as terminal energy for beneficial usage.11−13 Due to its operation simplicity, wide variety of materials of choice, and more importantly extremely high energy conversion efficiency compared to other means of solar energy harvesting (e.g., photovoltaic and photocatalysis),14−16 light-to-heat conversion has gained renewed research interest in the past decade and found itself certain niche applications, including steam generation, water desalination, cancer therapy, etc.17−23 \n\nThe pool of photothermal material is big and keeps growing and the popular nanosized photothermal materials with desirable performance include carbon black, carbon nanotubes,24,25 graphene,26,27 gold nanoparticle,28,29 aluminum nanoparticles,30 black $\\mathrm{TiO_{2}}^{31}$ $\\mathrm{Ti}_{2}\\mathrm{O}_{3},^{32}$ etc. A recent report rationally devised hollow bimetallic plasmonic mesoporous nanoshells and the sophisticated structure of the material significantly enhances light absorption and facilitates light-towater-vapor generation.33 The aim of this work is to push MXene, more specifically ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2},$ into the pool of photothermal materials to invite further scientific investigations. Very recently, Xuan et al. and Lin et al. both investigated MXene’s application to phototherapy under near-infrared and their results show outstanding in vitro/in vivo photothermal ablation performance of MXene on tumor cells.20,34 In this report, we measured, with carefully designed systems, the light-to-heat conversion efficiency of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ via means of droplet laser heating process and photothermal water evaporation efficiency by stacked MXene membranes. Our results confirmed that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ had an outstanding internal light-to-heat conversion efficiency (i.e., $100\\%$ ) and the MXene membrane with an underlying heat barrier achieved $84\\%$ light-to-water-evaporation efficiency under 1 sun light illumination $\\left(1\\mathrm{~kW}/\\mathrm{m}^{2}\\right)$ , which is among the state of the art of such a system. This work demonstrates that MXene is a promising solar photothermal material and inspires more research efforts in the application of MXene for practical solar energy utilization. \n\n# RESULTS AND DISCUSSION \n\nMXene Preparation. In this project, $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ layered MAX phase was chosen as a raw material. The Al layers were etched by hydrofluoric acid (HF) aqueous solution. When the asprepared HF treated MAX phase was immersed into DMSO in the presence of sonication, exfoliated single/few layered MXene flakes were formed. Figure 1a shows a SEM image of the HF treated MAX-phase powder. Clearly, after the aluminum layer removal from ${\\mathrm{Ti}}_{3}{\\mathrm{AlC}}_{2},$ an opened interspace was formed and the layered structure could be obviously observed. Figure 1b presents a SEM image of typical exfoliated MXene flakes whose size were $500~\\mathrm{{nm}}$ . The HRTEM image in Figure 1c shows the single crystallinity of the MXene sheet. From selective area electron diffraction pattern (SAED) pattern in Figure 1d, one can see that the prepared MXene in this work has a hexagonal symmetry and exfoliated MXene flake has single crystallinity, as demonstrated by the HRTEM image.35,36 \n\n![](images/f2e00f4e7564364056fb6c65252c045a872caae2bba392b5ee5b35155e028711.jpg) \nFigure 1. (a) SEM image of as-made $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ MAX phase powder after Al removal by HF. (b) $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ MXene sheet after exfoliation. (c) HRTEM image of the exfoliated $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ MXene. (d) Selected area electron diffraction (SAED) pattern of the exfoliated $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ MXene. \n\nMeasurement and Calculation of Light to Heat Conversion. Figure 2a presents the UV−vis-NIR absorption spectra $\\left(300{-}1300\\ \\ \\mathrm{\\nm}\\right)$ of MXene and CNT aqueous suspensions with the same mass concentration of $0.1~\\mathrm{mg/mL}$ . As can be seen, CNT absorbs broad spectrum from 300 to $1300\\ \\mathrm{nm}$ without any distinct absorption peak while MXene exhibits a basic absorption much higher than CNT material with an absorption peak around $800\\ \\mathrm{nm}$ . According to the solution to Maxwell equation, a higher conductivity of a material will generally lead to a higher extinction coefficient and thus to a better electro-magnetic wave absorption.37 It has been reported that MXene materials possess higher electric conductivity than CNT and reduced graphene oxide materials,1 two popular and effective photothermal materials in literature, which may help explain the MXene’s consistently higher light absorption than CNT (Figure 2a) in the entire wavelength range. This encouraging result inspired us to move on to measure the light-to-heat conversion efficiency of MXene. \n\nTo precisely evaluate the light-to-heat conversion efficiency of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene, a droplet-based light absorption and heat measurement system was carefully established based on literature with certain modification and the system setup is schematically presented in Figure 3a. Briefly, an aqueous solution droplet with a known volume $(9.0\\mu\\mathrm{L})$ and containing MXene is hung at the tip of a one-end-sealed PTFE pipet. The selection of PTFE pipet is based on its hydrophobicity, which prevents the droplet from entering into the pipet, and on its poor heat conduction property due to its hollow structure. A single wavelength laser beam (i.e., 473 or $785\\mathrm{nm}$ in this study), with power density of $82{\\mathrm{~mW}}$ and spot size of $0.85\\ \\mathrm{mm}$ in diameter, is shone right in the center of the droplet. The selection of the laser as the light source is because it is a perfect parallel light source and of its stable light power density. The laser light is partially adsorbed by MXene existing in the optical path of the laser beam inside the droplet (Figure 3b), which is a circular column with length of $2.6\\ \\mathrm{mm}$ and diameter of 0.85 mm. The adsorbed laser light energy by MXene is converted to heat and consequently temperature of the droplet increases (Figure S1). The droplet temperature is real-time recorded by a precalibrated IR camera. More details regarding the system setup can be found in Supporting Information. \n\nFigure 2b shows the total temperature profile of the droplet in response to photothermal heating and subsequently natural cooling. As can be seen, there was a sharp temperature rise of the droplet soon as the laser was turned on, which is an indicator of instantaneous heat convection within the droplet. Figure S1 presents the IR photo of the droplet after $10~\\mathsf{s}$ of laser illumination. Upon the arrival of the equilibrium temperature of the droplet $(35~^{\\circ}\\mathrm{C})$ , which was determined when the droplet temperature fluctuation was less than $2~^{\\circ}\\mathrm{C},$ , the laser was shut down and cooling process was initialized. \n\nDuring the laser light induced heating process, part of the light energy was adsorbed and converted into heat energy by MXene sheets with a light-to-heat conversion efficiency $(\\eta)$ , which is to be investigated in this experiment. Some of the gained heat energy is converted to the internal energy of the droplet system, indicated by a temperature increase of the droplet before an equilibrium state is achieved. Other heat energy gets dissipated to the environment once the temperature of the droplet is higher than the environment. Therefore, the general governing energy balance of this system is described as eq 1: \n\n![](images/357044dd58a58b3ff5ff8e623db5d0e66882b311ff08efb35f84f07cb4bc841c.jpg) \nFigure 2. (a) UV−vis-NIR absorption spectrum of MXene and CNT solution with the same mass concentration of ${\\bf0.1\\ m g/m L}$ . (b) Time course of temperature profile of the droplet containing 0. One $\\mathbf{mg/mL}$ MXene in the light-to-heat conversion experiment under two separate laser irradiation. Plots of $\\mathbf{ln}\\frac{T_{\\mathrm{t}}-T_{0}}{T_{\\mathrm{max}}-T_{0}}$ versus $\\mathbf{\\delta}_{t,\\tiny{1}}$ tested with (c) ${\\bf473n m}$ laser and (d) $785\\ \\mathbf{nm}$ laser, respectively. The slopes were calculated based on linear regression. \n\n![](images/0f219f96919e3114ce4a78b66204c8567f55159495af1bf07df5dbb8f3ad5447.jpg) \nFigure 3. (a) Experimental set up for droplet-based light-to-heat conversion experiment. (b) Schematic of droplet with laser irradiation. \n\n$$\nP\\eta={\\frac{d Q_{\\mathrm{{i}}}}{d t}}=m C_{\\mathrm{{p}}}{\\frac{d T}{d t}}+{\\frac{d Q_{\\mathrm{{ext}}}}{d t}}\n$$ \n\nWhere $P$ is the light power that is adsorbed by the droplet and $\\boldsymbol{Q}_{\\mathrm{i}}$ is the heat energy gained by the droplet from the absorbed light energy, and $\\eta$ is the light-to-heat conversion efficiency of the MXene. $m$ , $C_{\\mathrm{p}},$ and $T$ are mass, heat capacity, and temperature of the droplet, respectively. $Q_{\\mathrm{ext}}$ is the heat dissipated into the environment external to the droplet. \n\nThe absorbed light power $P$ is evaluated from the difference between power of the incident laser beam $\\mathrm{\\Delta}P_{\\mathrm{in}},$ constant at 82 mW) and the outgoing light $(P_{\\mathrm{out}})$ , which is calculated by using MXene light absorbance $\\left({{A_{\\lambda}}}\\right)$ (eq 2). \n\n$$\nP=P_{\\mathrm{in}}-P_{\\mathrm{out}}=P_{\\mathrm{in}}(1-10^{-A_{\\lambda}})\n$$ \n\nThe determination of $A_{\\lambda}$ is based on Beer−Lambert law (eq 3). \n\n$$\nA_{\\lambda}=K L C=-\\mathrm{log}_{10}(P_{\\mathrm{out}}/P_{\\mathrm{in}})\n$$ \n\nWhere $L$ is optical path length of the incident laser light in the droplet, $2.6\\ \\mathrm{mm}$ in this case (Figure 2b), $C$ is the MXene concentration in the droplet, and $K$ is MXene’s extinction coefficient. Hence, the determination of $K$ is a key to this calculation. It is important to notice that, the extinction coefficient of $\\mathrm{\\DeltaAl(OH)_{4}^{-}}$ containing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene at $808~\\mathrm{nm}$ in the work by Xuan et al. is $29.1\\mathrm{~L~g}^{-1}\\mathrm{cm}^{-1}$ , which is quite comparable to the state of art NIR photothermal material.20 However, many factors that influence MXene’s extinction coefficient should be considered. According to Xuan et al.’s report, the calculated distinction coefficient difference between MXene obtained from TMAOH method and HF-DMSO method can be as high as 5.7 times, which they proposed to be attributable to the Al(OH) $_4^{-}$ functionalization of their MXene flakes. Thus, presumably due to the different size and surface functional groups, among others, of the MXene flakes in this work, the extinction coefficient in the current study is different than the literature value. \n\nExisting in the literature is a similar single droplet experiment conducted by Richardson et al. in 2009 in an effort to investigate the light-to-heat conversion efficiency of monodispersed $20~\\mathrm{{\\nm}}$ spherical gold nanoparticles.38 In this pioneering case, $A_{\\lambda}$ by the gold nanoparticles was theoretically calculated based on the estimated number of the gold nanoparticles in the light path of the solution and $K$ of a literature value for individual gold nanoparticles. However, directly applying the method reported by Richardson et al. to our system is deemed inappropriate as there is no existing $K$ value for a specified occasion available in literature for MXene, an emerging material only recently discovered. \n\nInstead, in this work, $K$ was measured on a UV−vis-NIR spectrophotometer using cuvette for each sample with known MXene concentration. With $A_{\\lambda}$ being measured directly on the spectrophotometer for any specific wavelength and $L$ and $C$ known, $K$ is then calculated for each sample at both wavelength of the laser beams (eq 3). \n\nWith $K$ being known now, $A_{\\lambda}$ in the single droplet experiment can then be calculated accordingly for various MXene concentrations as shown in Table 1. As can be seen, our method of calculating $A_{\\lambda}$ saves the trouble of having prior knowledge of number of particles and literature values of $K$ for photothermal materials. Given the fact that the majority of photothermal materials are neither spherical in shape nor monodispersed in size, our method is a more universal process for light-to-heat efficiency evaluations for all kinds of materials irrespective of their shapes and size distributions. In addition, with the $K$ and thus $A_{\\lambda}$ can be measured at the same particle concentration on a spectrophotometer as in the droplet experiment, the uncertainty in these parameters can be considerably reduced. In this work, the outgoing laser intensity behind the droplet was also monitored by a photometer. For comparison, the recorded outgoing light intensity was used to calculate $A_{\\lambda}$ and similar values were generated to the ones calculated using the above-described procedure, which proves the credibility of our method. \n\nTable 1. Light-to-Heat Conversion Efficiency Calculation Results \n\n\n
785 nm wavelength laser
Antime to achieve Teq (s)F (x10-3 J/(s °C))n
0.10 mg/mL0.3915.035.1253.3301.027
0.075 mg/mL0.2814.433.2352.8490.976
0.0500.1914.631.5352.3510.932
mg/mL 0.025 mg/mL0.1116.929.2402.1221.039
473 nm wavelength laser
0.100 mg/mL0.4818.536.525 3.4401.038
0.075 mg/mL0.3316.934.5273.213
0.050 mg/mL19.21.074
0.2531.130 3.3911.054
0.025 mg/mL0.1421.528.240 2.7421.017
CNT 785 nm wavelength laser
0.100 mg/mL0.124.627.9302.3741.045
\n\nWhen the laser beam is turn off, energy input becomes zero and the temperature of the droplet instantaneously starts to decline due to the heat dissipation from the droplet to its surrounding. In this cooling stage, the energy balance equation is described by eq 4. \n\n$$\nm C_{\\mathrm{p}}\\frac{d T}{d t}+\\frac{d Q_{\\mathrm{ext}}}{d t}=0\n$$ \n\nGenerally, the heat dissipation $Q_{\\mathrm{ext}}$ of an object to its surrounding is proportional to the temperature difference between them, and therefore it can be expressed as the following: \n\n$$\n\\frac{d Q_{\\mathrm{ext}}}{d t}=F(T-T_{0})\n$$ \n\nWhere $F$ is the proportional coefficient that describes heat loss process, $T$ and $T_{0}$ are the temperature of the droplet and its surrounding, in this case, ambient air. \n\nAssuming $T_{\\mathrm{eq}}$ is the maximum droplet temperature achieved when the equilibrium state is reached during the test, which is also the starting droplet temperature at the time when the laser is shut, we can deduce the expression for the temperature of the droplet $(T)$ in this cooling stage from eqs 5 and 6 as follows (eq 6): \n\n$$\nT=T_{0}+\\:\\big(T_{\\mathrm{eq}}-T_{0}\\big)\\mathrm{exp}\\Bigg(-\\frac{F}{m C_{\\mathrm{p}}}t\\Bigg)\n$$ \n\nThe eq 6 can be further reorganized into eq 7, by which the $F$ value can be calculated from the data collected in the cooling stage, namely the stage when the laser light irradiation is off (Figure 2b). \n\n$$\nF=-{\\frac{\\ln{\\frac{T_{\\mathrm{t}}-T_{0}}{T_{\\mathrm{eq}}-T_{0}}}}{t}}m C_{\\mathrm{p}} \n$$ \n\nFigure 2c,d presents $\\mathrm{ln}\\big(\\big(T_{\\mathrm{t}}{-}\\mathrm{T}_{0}\\big)/\\big(T_{\\mathrm{eq}}{-}T_{0}\\big)\\big)$ as a function of time $\\mathbf{\\eta}(t)$ for MXene aqueous droplet. A clearly linear correlation implies the $F$ and $m C_{\\mathfrak{p}}$ can be regarded as constant in the small temperature range $(20-40~^{\\circ}\\bar{\\mathbf{C}})$ in our experiments. The calculated $F$ values are listed in Table 1. Since the MXene concentrations in the tests are very low (i.e., 0.025, 0.05, 0.075, and $0.1~\\mathrm{mg/mL}$ ) and thus it is believed that the MXene does not significantly contribute to the heat capacity of the droplet, therefore the mass and heat capacity of the droplets are calculated based on the volume of the droplets, the density $\\left(0.996~\\mathrm{g/mL}\\right)$ and heat capacity $\\left(4.2\\mathrm{J/g}\\right)$ of pure water from literature. It is worth mentioning that, in a typical test, due to water evaporation the droplet volume shrinkage did happen but to a very small extent. First, the effect of droplet size shrinkage on light absorption path is minor (less than $0.2~\\mathrm{mm}$ ). Second, in our calculation, the water evaporation induced heat loss is implicitly incorporated in the term F. So no special treatment is given to the water evaporation induced size change of the droplet in the calculation. \n\nAt the equilibrium, the heat energy gained by the droplet is equal to energy output from the droplet by heat energy dissipation, and thus the temperature of the droplet remains constant. In this case, the energy balance equation can be described as \n\n$$\nP\\eta={\\frac{d Q_{\\mathrm{i}}}{d t}}={\\frac{d Q_{\\mathrm{ext}}}{d t}}\n$$ \n\nCombining eq 8 with eqs 2 and 5 leads to eq 9, which can be further reorganized into eq 10 for the calculation of light-toheat conversion efficiency $\\bar{(\\eta)}$ , which is the ultimate goal of the calculations. \n\n![](images/4a14f4a02bdea2702a08597c7d9e47247c69216adf11d14a2fb8ad01c9c9534b.jpg) \nFigure 4. (a) Diffuse reflection spectrum of PVDF membrane, PDMS modified PVDF membrane, and MXene membranes with different mass loading. Inset in (a) compares digital image of PVDF membrane and PVDF-MXene membrane. The mass loading of MXene on top of PVDF membrane was $\\mathbf{10~mg}$ . (b) Temperature time course of PDMS modified PVDF membrane and MXene-PVDF membrane in air under one sun illumination, insert (b) is IR photo of PDMS modified PVDF membrane and MXene, respectively. Both batches were irradiated for $30\\mathrm{min}$ to achieve water steam generation equilibrium at one sun. (c) Temperature depth profile of PDMS-MXene-PVDF membrane for photothermalbased steam generation. In this measurement, a glass bottle was used to prevent shielding of IR irradiation. (d) Time-dependent water evaporation rate under one sun light irradiation by the MXene membranes with different MXene mass loadings. \n\n$$\nP_{\\mathrm{in}}(1-10^{-A_{\\lambda}})\\eta=F(T_{\\mathrm{eq}}-T_{0})\n$$ \n\n$$\n\\eta={\\frac{F\\big(T_{\\mathrm{eq}}-T_{0}\\big)}{P_{\\mathrm{in}}\\big(1-10^{-A_{\\lambda}}\\big)}}\n$$ \n\nThus, as one can see, in our method, the temperature profile of the droplet in the cooling stage is used to derive the $F$ value, which is constant across all temperatures from 20 to $40~^{\\circ}\\mathrm{C}$ and is in turn used at the equilibrium stage in calculating $\\eta$ . By following the procedure described above, light-to-heat conversion efficiency $(\\eta)$ were calculated for all tested concentrations and the calculated $\\eta$ in this work are listed in Table 1. \n\nIt has to be mentioned that, light scattering did exist both in the $A_{\\lambda}$ measurement and droplet heating experiments and were not explicitly counted in our calculations. (1) In the case of $A_{\\lambda}$ measurement, the scattered light was counted toward the measured absorbance. However, $A_{\\lambda}$ measurement is widely used in determining the extinction coefficient values of nanostructures because light scattering is quite weak therein.20,34 (2) In the case of droplet heating measurement, the irradiated laser beam passed through the center of droplet and the scattered light was partially absorbed by MXene in the surrounding area that was not directly irradiated by the laser beam. Thus, the light energy loss due to scattering can be very limited in this case. \n\nClearly, in all cases, the $\\eta$ of MXene is all close to unity $(100\\%)$ , indicating perfect light-to-heat conversion, no matter the wavelength of the laser source is 473 or $785\\mathrm{nm}$ . In order to estimate the margin of error of our droplet heating system in estimating light-to-heat conversion efficiency, the experiment was repeated four times using $0.05~\\mathrm{mg/mL}$ MXene dispersion. By calculating light-to-heat conversion efficiency from the four batches, an error range was estimated to be at $5\\%$ . Therefore, our results demonstrate that MXene is a very promising photothermal material and more scientific efforts are justified to explore its further applications. \n\nIn parallel with the use of single wavelength laser sources, full visible spectrum laser and Vis plus NIR spectrum laser were also applied to the droplets and Figure S4 presents the time course of temperature profiles of CNT and MXene droplets with the same mass concentration under illumination of these two wide spectrum laser beams. It is clear that under both laser source illumination the droplet containing MXene showed consistently higher equilibrium temperature than the one containing CNTs. The result corroborates that MXene is an excellent photothermal material. Given the outstanding light-toheat conversion efficiency of both CNT and MXene (Table 1), the lower equilibrium temperature of the CNT droplet is presumably due to its lower light absorbance than MXene (Figure 3a). \n\nPhotothermal Water Steam Generation Under One Sun. Having confirmed that MXene has an outstanding internal light-to-heat conversion efficiency with excellent light absorption capability, we moved on to test the efficiency of stacked MXene thin membrane for interfacial water steam generation. In this part, a simple vacuum-assisted filtration method, was utilized to fabricate stacked MXene membrane.39 Hydrophilic PVDF membrane with a pore size of $0.22\\mu\\mathrm{m}$ was selected as a substrate for filtration due to its suitable pore size, flexibility and chemical inertia. MXene sheets in the filtrating solution were retained and stacked to form stacked MXene membrane directly on the PVDF substrate. Although the prepared MXene membranes could be peeled off from the PVDF substrate to form self-standing ones, the MXene membranes were kept together with the supporting PVDF substrates to increase the mechanical strength and stability in the following tests. \n\nDue to the hydrophilicity of the MXene membrane and PVDF substrate,40 the as-prepared MXene membrane sank in water. Therefore, poly(dimethylsiloxane) (PDMS) was grafted onto the membrane surface to decreases the surface energy. After this modification, the MXene-PVDF membrane is still wetted by water but able to self-float on top of water. Thanks to high transparency of PDMS, the PDMS modification shows negligible effect on the light absorption and reflection of the membranes (Figure 4a). \n\nTo optimize the thickness of MXene layer toward water evaporation performance, MXene membranes with different thickness were prepared by varying loading amount of MXene from 1.0 to 2.0, 3.0, 4.0, 5.0, and $10.0\\ \\mathrm{\\mg}$ in the filtrating solutions. Roughly, $1.0~\\mathrm{mg}$ MXene corresponded to $0.75\\ \\mu\\mathrm{{m}}$ thickness for the MXene layer according to the SEM observation (Figure S5). The MXene-PVDF membranes with 1.0 and $2.0\\ \\mathrm{mg}$ MXene loading amount show relatively high diffuse reflection in the visible light range as revealed in Figure $^{4\\mathrm{a},}$ which can be explained by the insufficient covering and thus incomplete MXene layers in these two cases cause by small MXene loading. \n\nFigure $\\boldsymbol{4\\mathrm{b}}$ presents temperature time course of MXene-PVDF membrane versus PDVF substrate alone, both under one sun illumination. In a sharp comparison and as expected, the MXene-PVDF membrane achieved an equilibrium temperature around $75~^{\\circ}\\mathrm{C}$ while the PVDF substrate had only $30~^{\\circ}\\mathrm{C}$ at equilibrium. Figure $\\scriptstyle4c$ is the water temperature profile as a function of depth with the MXene-PVDF membrane selffloating on top of water bottle, which shows a sharp and clear high temperature zone $(35.4~^{\\circ}\\mathrm{C})$ at the air/water interface (inset) and thus provides a proof to efficient interfacial water heating by the self-floating MXene-PVDF membrane. \n\nFigure 4d presents mass of water evaporated as a function of time for the MXene-PVDF membranes with varying MXene mass loading. It is clear that with the MXene mass loadings tested, the water evaporation is faster with increasing MXene mass. The light-to-water evaporation efficiency was calculated after light irradiation for $^\\textrm{\\scriptsize1h}$ when the evaporation rate was stable. The MXene-PVDF membrane with $10~\\mathrm{mg}$ MXene mass loading led to a light to water evaporation efficiency (EF) of $74\\%$ which compares very favorable against the water evaporation under light irradiation but without the membrane $(30\\%)$ (Figure S7, Table S1). \n\nIt is known that, in addition to material’s intrinsic light-toheat conversion efficiency, photothermal performance can be significantly enhanced by rationally designing surface structure to maximize light capture and employing suitable heat barrier to minimize heat loss to bulk water, among others.22,24,26,28,30,33 To achieve better EF of the system, a nonporous heat barrier of polystyrene foam was used and attached onto the back side of the MXene-PVDF membrane. The selection of the polystyrene foam is rational as it contains no water channel and thus blocks heat from transferring down to the bulk water while allowing water supply up to the photothermal material from the peripheral side of the foam. The design further concentrates the heat at the interfacial water region and thus can improve the water evaporation efficiency.26 Not surprisingly, with the rationally designed heat barrier, the light to water evaporation efficiency of $10~\\mathrm{mg}$ MXene−PVDF-PS membrane was boosted to $84\\%$ (Figure S8), which makes it one of the top \n\nperformances in literature with similar testing system 22,41−44 \nsetup. \n\n# CONCLUSION \n\nIn conclusion, in this work, a general procedure was developed based on a previously reported method to measure light-to-heat conversion efficiency of MXene with a droplet light heating system. The results showed that MXene had an outstanding internal light-to-heat conversion efficiency $(\\sim100\\%)$ , and MXene shows higher light absorption capability than CNTs. Exfoliated MXene was further made into self-floating thin membrane, which, in the presence of a heat barrier, produced a light-to-water evaporation efficiency $84\\%$ , comparable to the state of art photothermal evaporation system. This work thus demonstrates that MXene is a promising photothermal material. \n\n# EXPERIMENTS AND METHODS \n\nSynthesis of $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}$ . The synthesis of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ was conducted using the method reported in previous literature.1,34,45,46 Briefly, an aliquot of $\\mathfrak{s}.00\\ \\mathrm{g}$ MAX phase $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ power (VWR chemicals, $97\\%$ purity) was immersed in $50~\\mathrm{mL}$ of $50\\ \\mathrm{wt\\%}$ hydrofluoric acid (HF, VWR chemicals) at room temperature along with magnetic stirring for $^{18\\mathrm{~h~}}$ to obtain a stable suspension. The suspension was then centrifuged, followed by washing with DI water until $\\mathrm{\\pH}>5$ . The obtained $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ powder was dried under vacuum at $60~^{\\circ}\\mathrm{C}$ overnight. The delamination of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ was conducted using dimethyl sulfoxide (DMSO, SigmaAldrich). Briefly, $\\mathbf{1.00\\g}$ of the previously obtained $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ dry powder was stir-mixed with $20~\\mathrm{mL}$ DMSO for $^{18\\mathrm{~h~}}$ at room temperature, followed by centrifugation at $3500~\\mathrm{rpm}$ for 5 min to collect the solid. The collected powder was dispersed in DI water at a mass ratio of 1:300, subsequently sonicated for $300\\ \\mathrm{\\min}$ with argon gas being continuously bubbled through the DI water during the sonication, and finally centrifuged at $3500~\\mathrm{rpm}$ for $30\\ \\mathrm{min}$ to remove unexfoilated particles. \n\nPretreatment of Carbon Nanotube. An aliquot of $6.0\\mathrm{~g~}$ of multiwalled carbon nanotube (Sigma-Aldrich, $6{-}9\\ \\mathrm{nm}\\times5\\ \\mathrm{um}$ ) was dispersed in a mixture of $70\\%$ nitric acid $(60~\\mathrm{mL})$ and $97\\%$ sulfuric acid $\\mathrm{180~mL}$ . The dispersion was then refluxed for $^\\textrm{\\scriptsize4h}$ at $70~^{\\circ}\\mathrm{C}$ followed by $^{2\\mathrm{~h~}}$ sonication. The as-treated dispersion was filtrated and washed by DI water thoroughly before its use. \n\nCharacterization. Transmission electron microscopy (TEM) images were taken on a FEI-Titan CT microscope operated at 300 kV. Scanning electron microscopy (SEM) images were obtained on a FEI Nova Nano 630s microscope. The diffuse reflectance and UV/vis absorption spectra were determined by Shimadazu UV 2550 spectrophotometer. The UV−vis-NIR spectrum was conducted on an Agilent Cary 5000 UV−vis-NIR spectrophotometer. Single wavelength laser sources utilized for light-to-heat conversion efficiency test were BWF-785−450 laser source $(785\\ \\mathrm{nm})$ ) and MBL-N-473B laser source $(473\\ \\mathrm{nm})$ . Single wavelength photometer for transmitted laser energy detection was Newport 7936-R photometer. Broad spectrum white laser and IR laser for temperature profile comparison was conducted by a NKT superK EXTREME supercontinuum lasers equipped with a SuperK SPLIT spectral supercontinuum splitter. IR images were captured by a FLIR A655 infrared camera for temperature determination. \n\nThe emissivity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ powder was experimentally measured in this work. Briefly, MXene powder was scribbled on the surface of the hot plate whose temperature was maintained constant at $70~^{\\circ}\\mathrm{C}$ . Surface temperature of the MXene powder was read by both a thermal couple and IR camera, and the emissivity of the MXene was calculated based on the temperatures read from the thermal couple and the IR camera. The emissivity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ powder was measured to be 0.942 in this work. \n\nLight-to-Heat conversion efficiency measurement. Light to heat conversion efficiency of MXene was measured by utilizing a droplet of MXene aqueous solution based on a literature method reported by Richardson et al.38 with some modification. Figure 3a shows the experimental setup. Briefly, a $9.0~\\mu\\mathrm{L}$ $\\mathbf{\\Pi}(\\mathrm{uL})$ droplet of water (with a diameter of $2.6~\\mathrm{mm}$ ) with varying concentrations of MXene (i.e., 0.100, $0.075,$ , 0.050, and $0.025\\mathrm{\\mg/mL}$ ) was moved from a patterned superhydrophobic surface onto a one-end-sealed PTFE plastic pipet tip and hung there. \n\nA laser beam with wavelength at 785 or $473\\ \\mathrm{nm}$ and incident power of $82~\\mathrm{mW}$ was shone right onto the center of the water droplet. Part of the light was adsorbed by the MXene sheets located in the light path, which led to the temperature increase of the entire droplet. A precalibrated infrared (IR) camera was employed to monitor the temperature change of the droplet during heat and later cooling processes. Upon the droplet temperature achieving its steady state, the laser was turned off and the droplet cooled down naturally due to heat dissipation. For the purpose of comparison, the measurement was also conducted with a droplet with CNT (Sigma-Aldrich, multiwalled carbon nanotube) concentration at $0.100~\\mathrm{mg/mL}$ . \n\nFabrication of MXene Thin Membrane. Vacuum assisted filtration method was used to fabricate MXene thin membranes with different thickness. Briefly, MXene aqueous suspension containing known mass of exfoliated MXene (i.e., $1,2,3,4,5,$ and $10~\\mathrm{mg}$ ) was filtrated through a commercial hydrophilic PVDF membrane (Merck Millipore, GVWP, $0.22\\mu\\mathrm{m}\\dot{}$ ). A thin MXene layer with stacked MXene sheets was formed on top of the PVDF substrate. The MXene thin membranes were first tested by directly shining simulated solar light (Oriel solar simulator) with intensity adjusted to one sun $\\cdot1000\\ \\mathrm{W}/\\$ $\\mathbf{m}^{2}.$ ) on top of the MXene membrane in air and the temperature of the membranes was recorded by IR camera. \n\nWater Evaporation Performance Under One Sun. For photothermal water evaporation performance testing, a self-floating MXene-PVDF photothermal membrane was fabricated by modifying the previously prepared MXene thin membrane with PDMS functional groups. In more details, the MXene thin membrane along with PVDF substrate was moved to a $0.25~\\mathrm{wt\\%}$ PDMS hexane solution for $2\\:s$ for surface modification, followed by $60~^{\\circ}\\mathrm{C}$ heat treatment for $30~\\mathrm{min}$ . \n\nDI water was placed in a cylindrical polypropylene (PP) container with a mouth diameter of $3.2~\\mathrm{cm}$ , and the MXene membrane with matching size was put and self-floated on the top of water. One sun solar light irradiation was illuminated from the top and onto the surface of the MXene membrane vertically. The distance between light source and membrane surface was $17.5~\\mathrm{cm}$ . The mass of the water evaporated was real time monitored by a digital balance (Mettler Toledo, $\\begin{array}{r}{d=0.0001\\ \\mathrm{g},}\\end{array}$ connected to a PC. The water evaporation rate was calculated by the following equation: \n\n$$\n\\nu=\\frac{d m}{s\\times d t}\n$$ \n\nWhere $m$ is the mass of evaporated water, $s$ is the illuminated area, t is time, and $\\nu$ is evaporation rate. \n\nIn the end, a polystyrene heat barrier was physically attached onto the bottom of the MXene membrane $\\left(10~\\mathrm{mg}\\right)$ by two-side scotch tape and they together were tested for water evaporation rate using the otherwise same experimental conditions. \n\nLight to water evaporation efficiency (EF) was calculated based on following equation: \n\n$$\n\\begin{array}{l}{{\\displaystyle Q_{\\mathrm{e}}=\\frac{d m\\times H_{\\mathrm{e}}}{d t}=\\nu\\times H_{\\mathrm{e}}}}\\\\ {{\\displaystyle}}\\\\ {{\\displaystyle\\mathrm{EF}=\\frac{Q_{\\mathrm{e}}}{Q_{\\mathrm{s}}}}}\\end{array}\n$$ \n\nWhere $Q_{\\mathrm{e}}$ is energy consumed for water evaporation, $\\boldsymbol{Q}_{s}$ is the incident simulated solar light power $\\left(1000\\mathrm{W/m}^{2}\\right)$ , $m$ is the mass of evaporated water recorded by the balance, and $H_{\\mathrm{e}}$ is the enthalpy of vaporization of water $\\left(2266~\\mathrm{KJ/kg}\\right)$ . \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.6b08415. \n\nOptical path length calibration, IR images, temperature profiles of the aqueous droplets, SEM images, and EDX spectrum (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author \n\\*peng.wang@kaust.edu.sa. \nORCID \nLianbin Zhang: 0000-0002-8548-1506 \nPeng Wang: 0000-0003-0856-0865 \nNotes \nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThe authors are grateful to KAUST for very generous financial support. Professor Peng Wang would like to thank the anonymous reviewers for their comments and suggestions which significantly improved the quality of the manuscript. \n\n# REFERENCES \n\n(1) Ling, Z.; Ren, C. E.; Zhao, M.-Q.; Yang, J.; Giammarco, J. M.; Qiu, J.; Barsoum, M. W.; Gogotsi, Y. Flexible and Conductive MXene Films and Nanocomposites with High Capacitance. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 16676−16681. (2) Butler, S. Z.; Hollen, S. M.; Cao, L.; Cui, Y.; Gupta, J. A.; Gutiérrez, H. R.; Heinz, T. F.; Hong, S. S.; Huang, J.; Ismach, A. F.; Johnston-Halperin, E.; Kuno, M.; Plashnitsa, V. V.; Robinson, R. D.; Ruoff, R. S.; Salahuddin, S.; Shan, J.; Shi, L.; Spencer, M. G.; Terrones, M.; Windl, W.; Goldberger, J. E. Progress, Challenges, and Opportunities in Two-Dimensional Materials Beyond Graphene. ACS Nano 2013, 7, 2898−2926. (3) Seh, Z. W.; Fredrickson, K. D.; Anasori, B.; Kibsgaard, J.; Strickler, A. L.; Lukatskaya, M. R.; Gogotsi, Y.; Jaramillo, T. F.; Vojvodic, A. Two-Dimensional Molybdenum Carbide (MXene) as An Efficient Electrocatalyst for Hydrogen Evolution. ACS Energy Lett. 2016, 1, 589−594. (4) Zhang, X.; Lei, J.; Wu, D.; Zhao, X.; Jing, Y.; Zhou, Z. A Tianchored $\\mathrm{Ti}_{2}\\mathrm{CO}_{2}$ Monolayer (MXene) as a Single-atom Catalyst for CO Oxidation. J. Mater. Chem. A 2016, 4, 4871−4876. (5) Naguib, M.; Come, J.; Dyatkin, B.; Presser, V.; Taberna, P.-L.; Simon, P.; Barsoum, M. W.; Gogotsi, Y. MXene: A Promising Transition Metal Carbide Anode for Lithium-ion Batteries. Electrochem. Commun. 2012, 16, 61−64. (6) Liang, X.; Garsuch, A.; Nazar, L. F. Sulfur Cathodes Based on Conductive MXene Nanosheets for High-Performance Lithium− Sulfur Batteries. Angew. Chem., Int. Ed. 2015, 54, 3907−3911. (7) Dall’Agnese, Y.; Taberna, P.-L.; Gogotsi, Y.; Simon, P. TwoDimensional Vanadium Carbide (MXene) as Positive Electrode for Sodium-Ion Capacitors. J. Phys. Chem. Lett. 2015, 6, 2305−2309. (8) Wang, X.; Kajiyama, S.; Iinuma, H.; Hosono, E.; Oro, S.; Moriguchi, I.; Okubo, M.; Yamada, A. Pseudocapacitance of MXene Nanosheets for High-power Sodium-ion Hybrid Capacitors. Nat. Commun. 2015, 6, 6544−6550. (9) Ren, C. E.; Hatzell, K. B.; Alhabeb, M.; Ling, Z.; Mahmoud, K. A.; Gogotsi, Y. Charge- and Size-Selective Ion Sieving Through $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Tx}$ MXene Membranes. J. Phys. Chem. Lett. 2015, 6, 4026−4031. (10) Shahzad, F.; Alhabeb, M.; Hatter, C. B.; Anasori, B.; Man Hong, S.; Koo, C. M.; Gogotsi, Y. Electromagnetic Interference Shielding with 2D Transition Metal Carbides (MXenes). Science 2016, 353, 1137−1140. \n\n(11) Kabeel, A. E.; El-Agouz, S. A. Review of Researches and Developments on Solar Stills. Desalination 2011, 276, 1−12. \n(12) Velmurugan, V.; Srithar, K. Prospects and Scopes of Solar Pond: A Detailed Review. Renewable Sustainable Energy Rev. 2008, 12, 2253− 2263. \n(13) Jackson, R. D.; Van Bavel, C. H. M. Solar Distillation of Water from Soil and Plant Materials: A Simple Desert Survival Technique. Science 1965, 149, 1377−1379. \n(14) Stranks, S. D.; Snaith, H. J. Metal-halide Perovskites for Photovoltaic and Light-emitting Devices. Nat. Nanotechnol. 2015, 10, 391−402. \n(15) Tong, H.; Ouyang, S.; Bi, Y.; Umezawa, N.; Oshikiri, M.; Ye, J. Nano-photocatalytic Materials: Possibilities and Challenges. Adv. Mater. 2012, 24, 229−251. \n(16) Chen, X.; Shen, S.; Guo, L.; Mao, S. S. Semiconductor-based Photocatalytic Hydrogen Generation. Chem. Rev. 2010, 110, 6503− 6570. \n(17) Huang, X.; El-Sayed, I. H.; Qian, W.; El-Sayed, M. A. Cancer Cell Imaging and Photothermal Therapy in the Near-Infrared Region by Using Gold Nanorods. J. Am. Chem. Soc. 2006, 128, 2115−2120. (18) Boyer, D.; Tamarat, P.; Maali, A.; Lounis, B.; Orrit, M. Photothermal Imaging of Nanometer-Sized Metal Particles among Scatterers. Science 2002, 297, 1160−1163. \n(19) Neumann, O.; Urban, A. S.; Day, J.; Lal, S.; Nordlander, P.; Halas, N. J. Solar Vapor Generation Enabled by Nanoparticles. ACS Nano 2013, 7, 42−49. \n(20) Xuan, J.; Wang, Z.; Chen, Y.; Liang, D.; Cheng, L.; Yang, X.; Liu, Z.; Ma, R.; Sasaki, T.; Geng, F. Organic-Base-Driven Intercalation and Delamination for the Production of Functionalized Titanium Carbide Nanosheets with Superior Photothermal Therapeutic Performance. Angew. Chem., Int. Ed. 2016, 55, 14569−14574. \n(21) Jaque, D.; Martinez Maestro, L.; del Rosal, B.; Haro-Gonzalez, P.; Benayas, A.; Plaza, J. L.; Martin Rodriguez, E.; Garcia Sole, J. Nanoparticles for Photothermal Therapies. Nanoscale 2014, 6, 9494− 9530. \n(22) Liu, Y.; Yu, S.; Feng, R.; Bernard, A.; Liu, Y.; Zhang, Y.; Duan, H.; Shang, W.; Tao, P.; Song, C.; Deng, T. A Bioinspired, Reusable, Paper-Based System for High-Performance Large-Scale Evaporation. Adv. Mater. 2015, 27, 2768−2774. \n(23) Li, R.; Zhang, L.; Wang, P. Rational Design of Nanomaterials for Water Treatment. Nanoscale 2015, 7, 17167−17194. \n(24) Wang, Y.; Zhang, L.; Wang, P. Self-Floating Carbon Nanotube Membrane on Macroporous Silica Substrate for Highly Efficient SolarDriven Interfacial Water Evaporation. ACS Sustainable Chem. Eng. 2016, 4, 1223−1230. \n(25) Panagiotopoulos, N. T.; Diamanti, E. K.; Koutsokeras, L. E.; Baikousi, M.; Kordatos, E.; Matikas, T. E.; Gournis, D.; Patsalas, P. Nanocomposite Catalysts Producing Durable, Super-Black Carbon Nanotube Systems: Applications in Solar Thermal Harvesting. ACS Nano 2012, 6, 10475−10485. \n(26) Li, X.; Xu, W.; Tang, M.; Zhou, L.; Zhu, B.; Zhu, S.; Zhu, J. Graphene Oxide-based Efficient and Scalable Solar Desalination Under one Sun with A Confined 2D Water Path. Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 13953−13958. \n(27) Ito, Y.; Tanabe, Y.; Han, J.; Fujita, T.; Tanigaki, K.; Chen, M. Multifunctional Porous Graphene for High-Efficiency Steam Generation by Heat Localization. Adv. Mater. 2015, 27, 4302−4307. (28) Zhou, L.; Tan, Y.; Ji, D.; Zhu, B.; Zhang, P.; Xu, J.; Gan, Q.; Yu, Z.; Zhu, J. Self-assembly of Highly Efficient, Broadband Plasmonic Absorbers for Solar Steam Generation. Sci. Adv. 2016, 2, e1501227. (29) Wang, Z.; Liu, Y.; Tao, P.; Shen, $\\mathrm{Q.;}$ Yi, N.; Zhang, F.; Liu, $\\mathrm{Q.;}$ Song, C.; Zhang, D.; Shang, W.; Deng, T. Bio-Inspired Evaporation Through Plasmonic Film of Nanoparticles at the Air−Water Interface. Small 2014, 10, 3234−3239. \n(30) Zhou, L.; Tan, Y.; Wang, J.; Xu, W.; Yuan, Y.; Cai, W.; Zhu, S.; Zhu, J. 3D Self-assembly of Aluminium Nanoparticles for Plasmonenhanced Solar Desalination. Nat. Photonics 2016, 10, 393−398. (31) Ren, W.; Yan, Y.; Zeng, L.; Shi, Z.; Gong, A.; Schaaf, P.; Wang, D.; Zhao, J.; Zou, B.; Yu, H.; Chen, G.; Brown, E. M. B.; Wu, A. A Near Infrared Light Triggered Hydrogenated Black $\\mathrm{TiO}_{2}$ for Cancer Photothermal Therapy. Adv. Healthcare Mater. 2015, 4, 1526−1536. (32) Wang, J.; Li, Y.; Deng, L.; Wei, N.; Weng, Y.; Dong, S.; Qi, D.; Qiu, J.; Chen, X.; Wu, T. High-Performance Photothermal Conversion of Narrow-Bandgap $\\mathrm{Ti}_{2}\\mathrm{O}_{3}$ Nanoparticles. Adv. Mater. 2017, 29, 1603730. \n(33) Zielinski, M. S.; Choi, J.-W.; La Grange, T.; Modestino, M.; Hashemi, S. M. H.; Pu, Y.; Birkhold, S.; Hubbell, J. A.; Psaltis, D. Hollow Mesoporous Plasmonic Nanoshells for Enhanced Solar Vapor Generation. Nano Lett. 2016, 16, 2159−2167. \n(34) Lin, H.; Wang, X.; Yu, L.; Chen, Y.; Shi, J. Two-Dimensional Ultrathin MXene Ceramic Nanosheets for Photothermal Conversion. Nano Lett. 2017, 17, 384. \n(35) Naguib, M.; Kurtoglu, M.; Presser, V.; Lu, J.; Niu, J.; Heon, M.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Nanocrystals Produced by Exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 2011, 23, 4248−4253. \n(36) Mashtalir, O.; Naguib, M.; Mochalin, V. N.; Dall’Agnese, Y.; Heon, M.; Barsoum, M. W.; Gogotsi, Y. Intercalation and Delamination of Layered Carbides and Carbonitrides. Nat. Commun. 2013, 4, 1716−1723. \n(37) Electrodynamic Fields- Time Varying Fields and Maxwell’s Equations. In Electromagnetic Wave Theory; Bakshi, U. A., Bakshi, A. V.; 2009; pp 9−12−9−19. \n(38) Richardson, H. H.; Carlson, M. T.; Tandler, P. J.; Hernandez, P.; Govorov, A. O. Experimental and Theoretical Studies of Light-toHeat Conversion and Collective Heating Effects in Metal Nanoparticle Solutions. Nano Lett. 2009, 9, 1139−1146. \n(39) Tang, B.; Zhang, L.; Li, R.; Wu, J.; Hedhili, N. M.; Wang, P. Are Vacuum Filtrated Reduced Graphene Oxide Membranes Symmetric? Nanoscale 2016, 8, 1108−1116. \n(40) Naguib, M.; Mochalin, V. N.; Barsoum, M. W.; Gogotsi, Y. 25th Anniversary Article: MXenes: A New Family of Two-Dimensional Materials. Adv. Mater. 2014, 26, 992−1005. \n(41) Ni, G.; Li, G.; Boriskina, S. V.; Li, H.; Yang, W.; Zhang, T.; Chen, G. Steam Generation under One Sun Enabled by A Floating Structure with Thermal Concentration. Nat. Energy 2016, 1, 16126− 16133. \n(42) Ghasemi, H.; Ni, G.; Marconnet, A. M.; Loomis, J.; Yerci, S.; Miljkovic, N.; Chen, G. Solar Steam Generation by Heat Localization. Nat. Commun. 2014, 5, 4449−4456. \n(43) Zhang, L.; Tang, B.; Wu, J.; Li, R.; Wang, P. Hydrophobic Lightto-Heat Conversion Membranes with Self-Healing Ability for Interfacial Solar Heating. Adv. Mater. 2015, 27, 4889−4894. \n(44) Shi, L.; Wang, Y.; Zhang, L.; Wang, P. Rational Design of a BiLayered Reduced Graphene Oxide Film on Polystyrene Foam for Solar-Driven Interfacial Water Evaporation. J. Mater. Chem. A 2017, DOI: 10.1039/C6TA09810J. \n(45) Ding, L.; Wei, Y.; Wang, Y.; Chen, H.; Caro, J.; Wang, H. A Two-Dimensional Lamellar Membrane: MXene Nanosheet Stacks. Angew. Chem., Int. Ed. 2017, 56, 1825. \n(46) Zhao, M.- $\\mathrm{.Q.;}$ Ren, C. E.; Ling, Z.; Lukatskaya, M. R.; Zhang, C.; Van Aken, K. L.; Barsoum, M. W.; Gogotsi, Y. Flexible MXene/ Carbon Nanotube Composite Paper with High Volumetric Capacitance. Adv. Mater. 2015, 27, 339−345. " + }, + { + "id": "10.1038_ncomms15684", + "DOI": "10.1038/ncomms15684", + "DOI Link": "http://dx.doi.org/10.1038/ncomms15684", + "Relative Dir Path": "mds/10.1038_ncomms15684", + "Article Title": "One-Year stable perovskite solar cells by 2D/3D interface engineering", + "Authors": "Grancini, G; Roldán-Carmona, C; Zimmermann, I; Mosconi, E; Lee, X; Martineau, D; Narbey, S; Oswald, F; De Angelis, F; Graetzel, M; Nazeeruddin, MK", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Despite the impressive photovoltaic performances with power conversion efficiency beyond 22%, perovskite solar cells are poorly stable under operation, failing by far the market requirements. Various technological approaches have been proposed to overcome the instability problem, which, while delivering appreciable incremental improvements, are still far from a market-proof solution. Here we show one-year stable perovskite devices by engineering an ultra-stable 2D/3D (HOOC(CH2)(4)NH3)(2)PbI4/CH3NH3PbI3 perovskite junction. The 2D/3D forms an exceptional gradually-organized multi-dimensional interface that yields up to 12.9% efficiency in a carbon-based architecture, and 14.6% in standard mesoporous solar cells. To demonstrate the up-scale potential of our technology, we fabricate 10 x 10 cm(2) solar modules by a fully printable industrial-scale process, delivering 11.2% efficiency stable for >10,000 h with zero loss in performances measured under controlled standard conditions. This innovative stable and low-cost architecture will enable the timely commercialization of perovskite solar cells.", + "Times Cited, WoS Core": 1255, + "Times Cited, All Databases": 1262, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000402524300001", + "Markdown": "# One-Year stable perovskite solar cells by 2D/3D interface engineering \n\nG. Grancini1, C. Rolda´n-Carmona1, I. Zimmermann1, E. Mosconi2,3, X. Lee4, D. Martineau5, S. Narbey5, F. Oswald5, F. De Angelis2,3, M. Graetzel4 & Mohammad Khaja Nazeeruddin1 \n\nDespite the impressive photovoltaic performances with power conversion efficiency beyond $22\\%$ , perovskite solar cells are poorly stable under operation, failing by far the market requirements. Various technological approaches have been proposed to overcome the instability problem, which, while delivering appreciable incremental improvements, are still far from a market-proof solution. Here we show one-year stable perovskite devices by engineering an ultra-stable 2D/3D $(H O O C(C H_{2})_{4}N H_{3})_{2}P b|_{4}/C H_{3}N H_{3}P b|_{3}$ perovskite junction. The 2D/3D forms an exceptional gradually-organized multi-dimensional interface that yields up to $12.9\\%$ efficiency in a carbon-based architecture, and $14.6\\%$ in standard mesoporous solar cells. To demonstrate the up-scale potential of our technology, we fabricate $10\\times10\\mathsf{c m}^{2}$ solar modules by a fully printable industrial-scale process, delivering $11.2\\%$ efficiency stable for $>10,000\\mathsf{h}$ with zero loss in performances measured under controlled standard conditions. This innovative stable and low-cost architecture will enable the timely commercialization of perovskite solar cells. \n\nW ith power conversion efficiencies (PCE) beyond $22\\%$ , comparable to silicon solar cells at half of the price1–3, organo lead-halide perovskite solar cells (PSC) are leading the photovoltaic research scene. However, despite the big excitement, the unacceptably low-device stability under operative conditions currently represents an apparently unbearable barrier for their market uptake4,5. Notably, a marketable product requires a warranty for 20–25 years with $<10\\%$ drop in performances. This corresponds, on standard accelerated aging tests, to having $<10\\%$ drop in PCE for at least $^{1,000\\mathrm{h}}$ . Hybrid perovskite solar cells are still struggling to reach this goal. Perovskite are sensitive to water and moisture, ultraviolet light and thermal stress6–8. When exposed to moisture, the perovskite structure tend to hydrolyse6, undergoing irreversible degradation and decomposing back into the precursors, for example, the highly hygroscopic $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{X}$ and $\\bar{\\mathrm{CH}}(\\mathrm{NH}_{2})_{2}\\mathrm{X}$ salts and $\\mathrm{\\bar{Pb}X}_{2}$ , with $\\mathrm{X=}$ halide, a process that can be dramatically accelerated by heat, electric field and ultraviolet exposure7,8. Material instability can be controlled to a certain extent using cross-linking additives9 or by compositional engineering10, that is, adding a combination of $\\mathrm{Pb}(\\mathrm{CH}_{3}\\mathrm{CO}_{2})_{2}\\cdot3\\mathrm{H}_{2}\\mathrm{O}$ and ${\\mathrm{PbCl}}_{2}$ in the precursors11 or using cation cascade, including Cs and $\\mathbb{R}\\mathrm{b}$ cations, as recently demonstrated2,3, to reduce the material photo-instability and/or optimize the film morphology. However, solar cell \n\ndegradation is not only due by the poor stability of the perovskite layers, but can be also accelerated by the instability of the other layers of the solar cell stack. For instance, the organic hole transporting material (HTM) is unstable when in contact with water. This can be partially limited by proper device encapsulation12–14 using buffer layers between perovskite and $\\mathrm{HTM}^{15}$ or moisture-blocking $\\mathrm{HTM}^{16}$ such as $\\mathrm{NiO}_{x}$ (ref. 17) delivering, in this case, up to $^{1,000\\mathrm{h}}$ stability at room temperature. However, this approach increases the device complexity, and the cost of materials and processing. It is also worth to mention that most of the device stability measurements reported in literature are often done under arbitrary conditions far from the required standards18 such as not performed under continuous light illumination17, measured at an undefined temperature, or leaving the device under uncontrolled light and humidity conditions19. This makes a proper comparison among the different strategies used challenging. On the other hand, two-dimensional (2D) perovskites have recently attracted a substantial interest due to their superior stability and water resistance, far above their three-dimensional (3D) counterpart14,20,21. In this respect, solar cells based on the quasi-2D $(\\mathrm{B}\\mathrm{A})_{2}(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ ( $\\mathrm{BA}=\\mathrm{n}$ -butylammonium) perovskite have recently shown $12\\%$ efficiency21. However, their performances drop by $30\\%$ after running for $^{2,250\\mathrm{h}}$ in ambient conditions. \n\n![](images/7599a1595158718f06b4a15ff71502d581210473c8d0dc56d9ac29adda2dfe0c.jpg) \nFigure 1 | Optical and Structural characterization. (a) Absorption spectra of the $({\\mathsf{H O O C}}(\\mathsf{C H}_{2})_{4}{\\mathsf{N H}}_{3})_{2}\\mathsf{P b l}_{4}$ (blue dashed line), 3D $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ (black line) and 2D/3D (red line) using $3\\%$ of $H_{ Ḋ }{\\sf Ḋ }{0}\\mathsf{C}(\\mathsf{C}\\mathsf{H}_{2})_{4}\\mathsf{N}\\mathsf{H}_{3}\\mathsf{I}$ , AVAI hereafter. In the inset the intensity of the peak at $420\\mathsf{n m}$ with increasing the percentage of AVAI to $\\mathsf{P b l}_{2}$ . (b) Raman spectra for $100\\%\\mathsf{A V A l}$ (panel I.), $3\\%A V A I$ (panel II) and $0\\%\\mathsf{A V A l}$ (panel III) perovskites. Solid lines represent the fit from multi-gaussian peaks fitting procedure (Supplementary Fig. 3 for details). For 3D perovskite main peak at: 78, 109 and $250\\mathsf{c m}^{-1},$ for 2D at: 73, 109, 143, $171\\mathsf{c m}^{-1}$ and for 2D/3D at: 62, 87, 112, 143, $169\\ c m^{-1}$ ; (c) $\\mathsf{X}$ Ray diffraction pattern of $100\\%\\mathsf{A V A l}$ (panel I); $3\\%A V A I$ (panel II) and $0\\%A V A l$ (panel III) perovskite. Peaks denoted with a star originate from the $F\\mathsf{T O}/\\mathsf{T i O}_{2}$ substrate. (d) Zoom of the $\\mathsf{X}$ -ray diffraction pattern comparing the $3\\%$ AVAI with the pure $0\\%\\mathsf{A V A l}$ perovskites at selected angles. Substrate: mesoporous $\\mathsf{T i O}_{2}$ . \n\nHere we develop an innovative concept by engineering a multidimensional junction made of 2D/3D perovskites. This 2D/3D interface brings together the enhanced stability of 2D perovskite with the panchromatic absorption and excellent charge transport of the 3D ones, enabling the fabrication of efficient and ultra-stable solar cells, an important proof of concept for further device optimization and up-scaling. In particular, we develop HTM-free solar cells and modules substituting the HTM with hydrophobic carbon electrodes22,23. Within this configuration we demonstrate, for the first time, a remarkable long-term stability of $>10,000\\mathrm{h}$ , corresponding to $>400$ days with zero loss in efficiency over a large-area, fully printable, low-cost and high-efficient solar module of $10\\breve{0}\\mathrm{cm}^{2}$ (active area of around $50\\mathrm{cm}^{2}.$ ) measured under controlled standard conditions and in the presence of oxygen and moisture. \n\n# Results \n\nStructural and optoelectronic characterization. Inspired by the concept of crystal engineering and supramolecular synthons in 2D layered perovskite24,25, we have first realized a lowdimensional perovskite using the protonated salt of aminovaleric acid iodide $(\\mathrm{HOOC(CH_{2})_{4}N H_{3}I},$ AVAI hereafter), as the organic precursor mixed with $\\mathrm{PbI}_{2}$ (see Supplementary Information for details), following the procedure of the previous work of few of $\\mathrm{u}s^{23,26}$ . The deposition results in the formation of a low-dimensional perovskite possibly arranging into a $(\\mathrm{HOOC}(\\mathrm{CH_{2}})_{4}\\mathrm{NH_{3}})_{2}\\mathrm{PbI_{4}}$ structure. A yellowish film containing needle-like crystallites is formed (Supplementary Fig. 1). As shown in Fig. 1a, the absorption spectra of the film shows a clear band edge at $450\\mathrm{nm}$ and an excitonic peak at $425\\mathrm{nm}^{24,25}$ . Band edge emission at $453\\mathrm{nm}$ is observed in the photoluminescence (PL) spectrum (Supplementary Fig. 2). The structural properties of the $\\mathrm{(HOOC(CH_{2})_{4}N H_{3})_{2}P b I_{4}}$ are investigated by Raman spectroscopy and X-ray diffraction. The Raman spectra of the $100\\%\\mathrm{AVAI}$ sample is compared with the one collected from the 3D perovskite $(0\\%\\mathrm{{AVAI})}$ and to the mixed $3\\%$ AVAI, as shown in Fig. 1b (panels I–III). For the $100\\%\\mathrm{AVAI}$ perovskite sharper peaks in the $50{-}200\\mathrm{cm}^{-1}$ range are observed. More in details, the peaks at 87, 112 and $169\\mathrm{cm}^{-1}$ are related to $P b\\ –I$ stretching and bending modes27–29, while the modes at 62 and at $143\\mathrm{cm}^{-\\dagger}$ are associated to the rotation and libration of the organic cations, leading to an overall spectra very similar in shape to that of $\\mathrm{PbI}_{2}$ intercalated with ammonia molecules27–29. The $\\mathrm{\\DeltaX}$ -ray diffraction measurement of the $100\\%\\mathrm{AVAI}$ perovskite, Fig. 1c (panel I), collected on an extended range down to $3^{\\circ}$ , exhibits a rich diffraction pattern at low angles with a strong dominant peak at $4.7^{\\circ}$ along with two lateral peaks at 4.2 and $5.2^{\\circ}$ . The data provide evidence of the formation of a low-dimensional perovskite with a possible much more complex crystal structure as evident by the multiple reflections at low angles $(2\\theta<10^{\\mathrm{o}})^{24,25,30}$ . As the second step, we engineer the 2D/3D composite by mixing the $(\\mathrm{A}\\bar{\\mathrm{V}}\\mathrm{AI}{:}\\mathrm{PbI}_{2})$ and $\\left(\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}{:}\\mathrm{PbI}_{2}\\right)$ precursors at different molar ratios $(0-3-5-10-20-50\\%)$ as described in Supplementary Information). The mixed solution is infiltrated in the mesoporous oxide scaffold by a single-step deposition followed by a slow drying-process, allowing the reorganization of the components in the film before solidification. The mixed films obtained by varying the precursors ratio absorb across the whole visible region with an edge at $760\\mathrm{nm}$ and a peak around $430\\mathrm{nm}$ , see Fig. 1a and Supplementary Fig. 4. Figure 1a shows the results for the film obtained by $3\\%$ AVAI, representing the optimized concentration for the best performing device (see below). The absorption band edge matches with that of 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite, while the peak at $430\\mathrm{nm}$ , which linearly gains intensity upon increasing the $\\mathrm{AVAI\\%}$ (see inset in Fig. 1a and Supplementary Fig. 4), resembles the absorption peak of the 2D perovskite, although partially red-shifted. The addition of $3\\%$ AVAI thus induces the formation of a mixed 2D/3D composite, partly retaining the features of its 2D and 3D constituents. Figure 1b compares the Raman spectrum of the $100\\%\\mathrm{AVAI}$ sample with those from the $0\\%\\mathrm{{AVAI}}$ and the optimized $3\\%$ AVAI sample. Additional data at different AVAI concentration are reported in Supplementary Figs 5 and 6. The spectrum of the 2D/3D $3\\%\\mathrm{AVAI}$ composite shows well-defined Raman lines spectrally matching the 2D peaks and standing out of a broader band that is characteristic of the modes of the inorganic lattice of the 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ (refs 28,29). In the $3\\%$ AVAI sample, sharp Raman features with reduced broadening are identified, suggesting an overall more ordered crystal rearrangement of the 2D/3D film compared with the pure 3D phase. The $\\mathrm{\\DeltaX}$ -ray diffraction pattern of the $\\mathrm{{2D/3D}}$ is reported in Fig. 1c–e and Supplementary Figs 7 and 8 for the different AVAI content. The most prominent peak is observed at $14.13^{\\circ}$ related to the (110) direction of the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ tetragonal phase30. More in details, as revealed by the zoom in Fig. $^{\\mathrm{1d,e}}$ , the 2D/3D film shows a remarkable change in intensity of the (00l) and $(\\mathrm{hk0})$ peaks compared with the pattern of the 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite. With $3\\%$ AVAI both (002) and (004) decrease in intensity, while the intensity of the (110) and (220) reflections are increased, speaking in favour for a preferred orientation along the ${\\tt{}}$ direction23. On the other side, no clear evidence of the peaks related to the 2D phase is observed for $3\\%$ AVAI, while they appear if the AVAI percentage exceeds $10\\%$ (Supplementary Figs 7 and 8). We can rationalize these results suggesting that the 2D/3D perovskite film with $3\\%$ AVAI is constituted by a thin layer (possibly a monolayer) of 2D perovskite; an oriented interface where the 3D phase has a marked preferential growth direction, and a pure 3D perovskite arranging in the tetragonal phase on top. To further elucidate the properties of the 2D/3D interface, we measure the steady-state PL spectra and timeresolved PL dynamics, see Fig. 2. \n\n![](images/3f130898c999065712ec5212d27469ff78f2f3055bcc48d63063f001f37ec12a.jpg) \nFigure 2 | Emission Properties. (a) PL spectra, excitation at $400\\mathsf{n m}$ , for the $100\\%$ ${\\mathsf{H O O C}}({\\mathsf{C H}}_{2})_{4}{\\mathsf{N H}}_{3}{\\mathsf{I}},$ AVAI hereafter and $20/30$ at $3\\%A V A l$ exciting from the $\\mathsf{T i O}_{2}$ side, where perovskite is infiltrated within the mesoporous scaffold. $(\\pmb{\\ b})$ Normalized PL spectra, excitation at $600\\mathsf{n m}$ , for the 2D/3D at $3\\%$ AVAI exciting from the top perovskite layer and from the $\\mathsf{T i O}_{2}$ side, where perovskite is infiltrated within the mesoporous scaffold compared to 3D $0\\%\\mathsf{A V A l}$ exciting from the mesoporous side (solid line). Since the light penetration depth is $<100\\mathsf{n m}$ at $600\\mathsf{n m}$ , excitation of the perovskite film from the oxide side (scaffold thickness of around $1\\upmu\\mathrm{m})$ interrogates the perovskite nano-crystallites grown within the scaffold, while excitation from the perovskite top layer probes the intrinsic properties of the bulk perovskite growing on top. (c) PL dynamics of the bulk perovskite (exciting from the top layer) at $760\\mathsf{n m}$ and from the oxide side at $730\\mathsf{n m}$ of the $3\\%$ AVAI deposited on the insulating $Z\\mathsf{r O}_{2}$ mesoporous substrate. \n\nIn particular, we measure the 2D/3D perovskite infiltrated into an inert $\\mathrm{ZrO}_{2}$ scaffold by varying the excitation side to selectively interrogate the perovskite crystals within the oxide or the top bulk perovskite layer, Fig. 2a. The PL measured when exciting from the oxide side reveals a weak emission around $450\\mathrm{nm}$ , matching with the one of $\\mathrm{(HOOC(CH_{2})_{4}N H_{3})_{2}P b I_{4}}$ (Supplementary Figs 2 and 10a). This suggests the presence of a 2D phase mostly retained at the interface with the oxide due to the favourable anchoring of the carboxylic acid group of the AVAI ligand to the $\\mathrm{TiO}_{2}$ scaffold31. Monitoring a more extended spectral window, Fig. 2b, excitation of the bulk top layer results in a single PL peak at $760\\mathrm{nm}$ as one would expect, while excitation from the oxide side leads to a peak at $730\\mathrm{nm}$ along with a shoulder at $760\\mathrm{nm}$ . The emission at $730\\mathrm{nm}$ suggests that a different perovskite phase with a larger band-gap (of $1.69\\mathrm{eV})$ is formed within the oxide scaffold, but only in the presence of the AVAI precursor. Interestingly, a similar higher energy emission has been found at low-temperature, for the 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite, but was never observed at room temperature32,33. If we deposit a thicker oxide scaffold, avoiding the formation of the bulk $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite capping layer, only the peak at $730\\mathrm{nm}$ appears (Supplementary Figs 9, 10), confirming that the emission at $760\\mathrm{nm}$ comes from the bulk perovskite. Notably, the pristine 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ excited from the oxide side does not show such blueshifted emission. Figure 2c compares the PL dynamics probing the temporal decay of the two different peaks. At $760\\mathrm{nm}$ , the PL shows a long-lived decay (extending out of our temporal window) typically assigned to electron-hole recombination at the band $\\mathrm{edges}^{32,33}$ , while at $730\\mathrm{nm}$ a fast component with a time constant $\\tau=2$ ns dominates, see Supplementary Table 1. Interestingly, such faster decay has been lobwsetrevemdpienrathuere3m2,o3r3e, oproisesnitbelyd d3uDe $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ etdhuacteadpepleacrtrson-lhyolaet lifetime34. Note that we intentionally use the insulating $\\mathrm{ZrO}_{2}$ substrate to highlight the intrinsic behaviour of the two phases, however a relative shortening of the lifetime is also observed on $\\mathrm{TiO}_{2}$ (Supplementary Fig. 11). \n\nOverall, our analysis demonstrates the unique role of the 2D perovskite, anchored on the oxide network, in templating the growth of a biphasic 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ : an oriented wider bandgap phase within the oxide scaffold and a standard tetragonal phase on top of it. It is important to remark the fundamental role of the oxide in templating the graded 2D/3D interface. Indeed, if the $3\\%$ AVAI perovskite is deposited on a compact glass substrate the blue-shifted emission peak at $730\\mathrm{nm}$ is not observed, while only the emission at around $760\\mathrm{nm}$ is visible, independently from the excitation side (see Supplementary Figs 12,13 and the discussion in Supplementary Information). \n\nSimulation of the 2D/3D interface. To check the impact of the suggested 2D/3D perovskite interface on the composite electronic properties, we carried out first principles simulations of the 2D/ 3D interface, Fig. 3. We built periodic (in the direction orthogonal to the interface) slabs of the 2D and 3D perovskites ensuring a lattice mismatch within $<1\\%$ . The methylammonium cations of the 3D perovskite layer contacting the 2D slab were replaced by AVA cations from the 2D slab and, employing the cell parameters of the 3D perovskite, we relaxed the atomic positions of the overall system by means of scalar-relativistic plane-wave/pseudopotential density functional theory calculations employing the PBE functional. As seen in Fig. 3a, there is a $0.14\\mathrm{eV}$ CB upshift at the 2D/3D interface compared to the bulk of the 3D perovskite, which induces a $0.09\\mathrm{eV}$ larger interface gap compared to the 3D bulk. This is clearly consistent with the PL blue shift experimentally observed $(0.13\\mathrm{eV})$ when probing the system from the oxide side. Notably, only a small shift (around $0.02\\mathrm{eV})$ of opposite sign was found at the MAPbI3/TiO2 interface35. \n\n# Discussion \n\nThese results suggest that the 2D/3D interaction widens the 3D perovskite band-gap in the interface region. Additionally, the thin 2D layer does not constitute a barrier to electron injection to $\\mathrm{TiO}_{2}$ , but it rather constitutes a barrier towards electron recombination, since the 2D conduction band is found at lower energy than that of the 3D CB. This result is confirmed also in the presence of spin-orbit-coupling, see PDOS in Fig. 3c and Supplementary Fig. 14. The results indicate that the 2D/3D perovskite organizes in a gradual multi-dimensional structure retaining the individual 2D and 3D phases, but, importantly also templating the formation of a novel oriented $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ phase stabilized at the 2D/3D interface. \n\n![](images/7a44880820ef6f798fdafc19b63f6cb5676d99d263889eb23baaef96840baa5d.jpg) \nFigure 3 | First principles simulations of the 2D/3D interface. (a) Local density of state (DOS) of the 3D/2D interface and (b) interface structure with the 2D phase contacting the $\\mathsf{T i O}_{2}$ surface. (c) Partial DOS summed on the 2D and 3D fragments calculated by including spin-orbit-coupling (SOC, inset) and without it. Notice the favourable alignment of conduction band states for electron injection into the 2D perovskite and possibly further into $\\mathsf{T i O}_{2}$ . \n\nWe have then fabricated solar cells with the 2D/3D perovskite optimizing the $\\mathrm{AVAI\\%}$ using both an architecture with an organic HTM and Au electrode, and a fully printable HTM-free configuration, where the HTM and gold are substituted with a carbon matrix23, and a $\\mathrm{TiO}_{2}$ mesoporous layer as electron transporting layer36, as depicted in the cartoon in Fig. 4a. $J{-}V$ characteristic of the 2D/3D perovskite solar cell using an optimal $3\\%$ AVAI composition and Spiro-OMeTAD/Au is shown in Fig. 4b. The solar cell delivers a champion efficiency of $14.6\\%$ (see also Table in the inset of Fig. 4c, Supplementary Fig. 15 and device statistics in the inset and in Supplementary Figs 16,17). Importantly, it shows a much better trend in the device stability with respect to pure 3D $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ cell (delivering an average efficiency above $13\\%$ in the same cell architecture), as shown in Fig. 4c. This represents an important proof of concept that paves the way to further stabilize the high efficiency (beyond $21\\%$ ) mesoporous solar cells based on a mixed halide composition2,37,38. Using the 2D/3D perovskite compared to the standard 3D $\\mathrm{CH}_{3}\\mathrm{\\bar{N}H}_{3}\\mathrm{PbI}_{3}$ , the efficiency is maintained up to $60\\%$ of the initial value after $300\\mathrm{h}$ continuous illumination under argon atmosphere, more stable than the standard 3D perovskite (Fig. 4c). \n\nOn the other side, based on the pioneering work by Mei et al.23 we developed HTM-free solar cells, being at present the cheapest, fully printable low-cost deposition process. It presents the most attractive photovoltaic solution, being a simple monolithic architecture without the use of the instable and expensive organic HTM and without the additional barrier layers17. We have developed small area cells $(0.64\\mathrm{cm}^{2})$ and large area $10\\times10\\mathrm{cm}^{2}$ solar modules as shown in Fig. 5a,b reporting the average $J{-}V$ curve of the cell and the module, as well as the device statistics in the inset. The modules were prepared with a total size of $10\\times10\\mathrm{cm}^{2}$ , with a geometric fill factor (GFF), the ratio between the active area and the total area of the module, of $46.7\\%$ . This leads to an active area of $47.6\\mathrm{cm}^{2}$ per module, which is the area considered to calculate the device efficiency. In addition, to avoid any mechanical damage of the cells, the devices were protected with a glass slide via a very simple sealing method under air conditions (see details in Supplementary Information), not under any inert or humidity controlled atmosphere as usually reported in literature, further confirming the higher robustness of our devices. The champion cell and module deliver an efficiency of $12.71\\%$ and $11.2\\%$ , respectively, among the highest reported so far ranging from 7 to $14\\%$ (refs 39–42), as shown in Supplementary Table 2 (ref. 22). It is worth mentioning that a fair comparison among the majority of reported module efficiencies is challenging because the GFF and the geometric shape of the devices are most of the times not indicated. In our work, the modules consist of 8 cells of $85\\times7\\mathrm{mm}^{2}$ , which leads to an active area of $5.95\\mathrm{cm}^{2}$ per cell and $47.60\\mathrm{cm}^{2}$ per module. In this module design, both the interconnect distance (around $3\\mathrm{mm}$ ) and the margins around the module aperture are admittedly large, implying an important loss in the area (which is included in the total area considered for the module). Further optimizations could be done by reducing the interconnect distance between cells, which will probably have two different impacts: less area will be lost, increasing the efficiency per total area in the module and the ohmic losses at the FTO between the interconnect gap will be reduced, improving the efficiency per active area. In addition, producing larger modules will not significantly increase the area for the margins, which would also have a positive impact on the final module performance. We have tested the modules under different conditions under simulated AM $1.5\\mathrm{~G~}$ solar illumination at $1000\\mathrm{W}\\mathrm{m}^{-2}$ and cycling of temperature up to $90^{\\circ}\\mathrm{C}$ under ambient conditions, in agreements with the standards (Supplementary Fig. 17). The results, in Fig. 5c, show an extraordinary long-term stability of $>10,000\\mathrm{h}$ and excellent response at elevated temperature (Supplementary Fig. 17), reported here for the first time. It is fair to notice that an initial increase is detected in Fig. 5c in the first $500\\mathrm{{h}}$ of the stability test. This can be due to concomitant effects such as light or field induced ion movement with the associated structural rearrangement, light-induced trap formation, or interfacial charge accumulation that can alter the device buenhdaevrioiunr (nasned aclrsuo ncay3u7s,e4 t4h4.e Sduevpipcle mheynstaereysisF),i .at p8resaendt Supplementary Table 4 report the comparison of the $J{-}V$ characteristic and parameters, when the device is measured in forward and back scan direction. As mentioned above, it is fair noticing that these devices show a not negligible hysteresis that is subject of ongoing investigation. Remarkably, the long stability here reported is at present the highest record value obtained for perovskite photovoltaics, surpassing with a gigantic step the results obtained so far. \n\n![](images/832edac017ce6da54e42d82999304642cb950146247a3b4b673bc899845d7d80.jpg) \nFigure 4 | 2D/3D Mesoporous Solar cell characteristics and stability. (a) Device cartoon of the Hole transporting Material (HTM)-free solar cell and of the standard HTM-based solar cell. (b) Current density voltage $(J-V)$ curve using the $20/30$ perovskite with $3\\%$ $\\mathrm{\\Delta}/\\mathrm{\\Delta}/\\mathsf{H O O C}(\\mathsf{C H}_{2})_{4}\\mathsf{N H}_{3}\\mathsf{I},$ AVAI hereafter, in a standard mesoporous configuration using $2,2^{\\prime},7,7^{\\prime}$ -tetrakis(N,N-di- $\\cdot\\mathsf{p}$ -methoxyphenylamine)- ${\\cdot9,9^{\\prime}}$ -spirobifluorene (spiro-OMeTAD)/Au (devise statistics and picture of the cell in the inset). (c) Stability curve of the Spiro-OMeTAD/Au cell comparing standard 3D with the mixed 2D/3D perovskite at maximum power point under AM 1.5G illumination, argon atmosphere and stabilized temperature of $45^{\\circ}\\mathsf{C}$ . Solid line represent the linear fit. In the inset the champion device parameters are listed. \n\n![](images/bca8fae2e5b7af3614f0746424f0b3e200f851941be06bce251f56cc443d2074.jpg) \nFigure 5 | 2D/3D Carbon based Solar cell characteristics and stability. (a) $J-V$ curve using the 2D/3D perovskite with $3\\%A V A|$ in HTM-free solar cell measured under Air Mass (AM) 1.5G illumination (device statistics and picture in the inset). (b) $J-V$ curve using the $20/30$ perovskite with $3\\%A V A l$ in a HTM-free $10\\times10\\mathsf{c m}^{2}$ module (device statistics and picture in the inset). (c) Typical module stability test under 1 sun AM $1.5\\mathsf{G}$ conditions at stabilized temperature of $55^{\\circ}$ and at short circuit conditions. Stability measurements done according to the standard aging conditions. In the inset device parameters of the devices represented in a and b. Champions devices reported in Supplementary Table 2. \n\nIn conclusion, we interface engineering a built-in 2D/3D perovskite which grows forming a peculiar bottom-up phasesegregated graded structure. The unique combination of the 2D layer acting as a protective window against moisture, preserving the 3D perovskite and of the efficient 3D one provides the hint for the development of a stable perovskite technology, paving the way for the realization of near term high efficient and stable perovskite solar cells for widespread deployment. \n\n# Methods \n\nMaterials development. $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ (MAI), $\\mathrm{{HOOC}(C H_{2})_{4}N H_{3}I}$ (AVAI) and $\\mathrm{TiO}_{2}$ paste (30 NR-D) have been purchased from Dyesol Company. $\\mathrm{PbI}_{2}$ was purchased from TCI Europe. All chemicals were used as received without further purification. \n\nFabrication of Spiro-OMeTAD based solar cells. The solar cells were prepared on fluorine-doped tin oxide coated glass (NSG10) substrates. Before the deposition of the different layers, the substrates were cleaned by sequentially sonicating them during $15\\mathrm{min}$ in hellmanex solution $(2\\mathrm{vol\\%})$ , 5 min in distilled water and finally $5\\mathrm{{min}}$ more in isopropanol, followed by $15\\mathrm{min}$ of ultraviolet-ozone treatment. A 30 nm thick $\\mathrm{TiO}_{2}$ blocking layer was deposited by spray pyrolysis from a solution containing $600\\upmu\\mathrm{l}$ Titanium diisopropoxide bis(acetylacetonate) $75\\%$ from Sigma Aldrich in $9\\mathrm{ml}$ of isopropanol. After sintering at $450^{\\circ}\\mathrm{C}$ the mesoporous $\\mathrm{TiO}_{2}$ layer was spin-coated from a $400\\mathrm{mg}\\mathrm{ml}^{-1}$ solution of 30NRD Dyesol paste in EtOH at 1,000 r.p.m. for 10 s and annealed at $500^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . Once the substrates were cooled down, $40\\upmu\\mathrm{l}$ of a solution containing 1.25 M $\\mathrm{PbI}_{2}$ /MAI (1:1) in DMSO was spin-coated on top through a two-step process: the first step consisting of $1{,}000\\mathrm{r.p.m}$ . during 10 s (preconditioning of the layer) and the second step at $4{,}500\\mathrm{r.p.m}$ . during $30\\mathrm{s}$ . Ten seconds before the end of the program, $100\\mathrm{ml}$ of chlorobenzene were spin-coated on top of the perovskite layer, according to the antisolvent method previously described in literature38, and finally the perovskite films were sintered at $100^{\\circ}\\mathrm{C}$ during $^{\\textrm{1h}}$ . Different compositions of 2D–3D perovskite were also tested by mixing different amounts of $1.1\\ \\mathrm{M}$ solution of $\\operatorname{AVAI:PbI}_{2}$ (2:1) with the $\\operatorname{MAI:PbI}_{2}$ precursor solution (0, 3 and $5\\%$ molar ratio). After the annealing time, Spiro-OMeTAD was spin-coated at 4,000 r.p.m., $20\\mathrm{s}$ from a chlorobenzene solution $(28.9\\mathrm{mg}$ in $400\\upmu\\mathrm{l}$ , $60\\mathrm{mmol}$ ) containing Li-TFSI ( $7.0\\upmu\\mathrm{l}$ from a $520\\mathrm{mg}\\mathrm{ml}^{-1}$ stock solution in acetonitrile), TBP $(11.5\\upmu\\mathrm{l})$ and $\\mathrm{Co(II)TFSI}$ ( $10\\mathrm{mol\\%}$ , $8.8\\upmu\\mathrm{l}$ from a $40\\mathrm{mg}\\mathrm{ml}^{-1}$ stock solution) as dopants. Finally, a $100\\mathrm{nm}$ gold electrode was evaporated. \n\nFabrication of carbon-based mesoscopic solar cells. The FTO glass was first etched to form two separated electrodes before being cleaned ultrasonically with ethanol. Then, the patterned substrates were coated by a compact $\\mathrm{TiO}_{2}$ layer by aerosol spray pyrolysis, and a $1\\upmu\\mathrm{m}$ nanoporous $\\mathrm{TiO}_{2}$ layer was deposited by screen-printing of a $\\mathrm{TiO}_{2}$ slurry, which was prepared as reported previously23. After being sintered at $450^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ , a $2\\upmu\\mathrm{m}Z\\mathrm{rO}_{2}$ spacer layer was printed on the top of the nanoporous $\\mathrm{TiO}_{2}$ layer using a $\\mathrm{ZrO}_{2}$ slurry, which acts as an insulating layer to prevent electrons from reaching the back contact. Finally, a carbon black/graphite counter electrode with a thickness of about $10\\upmu\\mathrm{m}$ was coated on top of the $\\mathrm{ZrO}_{2}$ layer by printing a carbon black/graphite composite slurry, and sintering at $400^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . After cooling down to room temperature, the perovskite precursor solution was infiltrated through a semi-continuous printing process from the top of the carbon counter electrode by drop casting. The complete printing process was carried out in air conditions. After drying at $50^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ , the mesoscopic solar cells containing perovskite was obtained. The perovskite precursor solution was prepared as follows: for the 3D precursor solution, $1.2\\ensuremath{\\mathrm{M}}$ of MAI and $1.2\\ensuremath{\\mathrm{M}}$ of $\\mathrm{PbI}_{2}$ were dissolved in $\\gamma$ -butyrolactone, and then stirred at $60^{\\circ}\\mathrm{C}$ overnight. For the 2D perovskite $1.2\\mathrm{M}$ of AVAI and $1.2\\mathrm{M}$ of $\\mathrm{PbI}_{2}$ were dissolved in $\\gamma$ -butyrolactone and then stirred at $60^{\\circ}\\mathrm{C}$ overnight. The $(\\mathrm{AVA})_{x}(\\mathrm{MA})1{\\cdot}\\mathrm{xPbI}_{3}$ precursor solution was prepared in the same manner except that a mixture of $(\\mathrm{AVAI:PbI}_{2},$ ) and $\\left(\\mathrm{MAI:PbI}_{2}\\right)$ with 3, 10, 20, $50\\mathrm{vol\\%}$ (that is, $\\mathrm{(AVAI{:}P b I_{2})/((A V A I{:}P b I_{2})+(M A I{:}P b I_{2}))})$ was used. All the cells were encapsulated in ambient atmosphere to protect the cell from mechanical damage, with no special control on the humidity and oxygen content. The encapsulation was performed by covering the cells with a thin glass and sealing the edges using DuPont Surlyn polymer. In the case of the modules, the same process was carried out but adding an extra ring of epoxy glue around the cell as a second protection. \n\nX-ray diffraction measurements. X-ray diffraction measurements were done on thin films using a D8 Advance diffractometer from Bruker (Bragg–Brentano geometry). Perovskite layers grown on top of mesoporous titania, as well as mesoporous zirconia and were analysed on addition of various amounts of AVAI. \n\nSolar cells and module characterization. For Spiro-based solar cells, photocurrent density voltage $\\left(J-V\\right)$ curves were characterized with a Keithley 2400 source/metre and a Newport solar simulator (model 91192) giving light with AM 1.5G spectral distribution. A black mask with an aperture $(0.\\bar{1}6\\mathrm{cm}^{2})$ smaller than the active area of the square solar cell $(0.5\\mathrm{cm}^{2})\\$ was applied on top of the cell. The measured $J_{\\mathrm{sc}}$ did not change using a mask. \n\nCells with HTM-free ( $\\mathrm{\\Delta}0.64\\mathrm{cm}^{2}$ large) were measured in air, but sealed with the glass slide and Surlyn polymer, the cell temperature during the measurements reaches $60^{\\circ}$ . Current–voltage characteristics of cells were measured under AM 1.5 simulated sunlight (class AAA solar simulator from Newport equipped with a 1000 W Xenon lamp) with a potentiostat (Keithley). The light intensity was measured for calibration with an NREL certified KG5 filtered Si reference diode. Light source used is a solar simulator equipped with a discharge Xe lamp, properly calibrated using a reference Si solar cell. Same cell are also measured with an inhouse developed AAA class simulator using a plasma lamp with a spectrum that exactly superimposes to the standard. No preconditioning protocol is used. Each cell is measured five times and the last one is taken as defined protocol, no differences are observed, no average of the scans are made. The module has been sealed with a back glass sheet and the stability tests were carried out in ambient air. The HTM-free cells used an adhesive mask with square aperture which is $\\mathbf{8\\times8}\\mathrm{mm}^{2}$ in aperture to avoid external rays. For the module no mask is used, as the active area is the size of the glass. The total active area for each $10\\times10\\mathrm{cm}^{2}$ module is $46.7\\mathrm{cm}^{2}$ . The overall GFF for the module that is the ratio between the active area and the total area of the module is then $46.7\\%$ , standing within the range observed for fully printed organic photovoltaic modules. \n\nSolar cells reproducibility. Spiro-OMeTAD solar cells: batch of 16 devices has been produced twice. HTM-free: 1 batch is $10\\times10$ glass with 18 cell, in total 9 batch have been continuously produced so far. For the modules, $>10$ at paper submission time, $20~\\mathrm{so}$ far. Data are reproducible comparing batch to batch. \n\nStability measurements. Spiro-OMeTAD based solar cells. The cells are placed in a sealed cell holder with a glass cover that is flushed with a flow of argon of $30\\mathrm{ml}\\mathrm{min}^{-1}$ . The holder is therefore exempt of water and oxygen, avoiding the need of sealing and improving the reproducibility. IV curves were characterized by an electronic system using 22 bits delta-sigma analogic to digital converter. For IV curves measurement, a scan rate of $25\\mathrm{mVs}^{-1}$ with a step of $5\\mathrm{mV}$ was used, maintaining the temperature of the holder to $35^{\\circ}\\mathrm{C}$ while the temperature of the cells was measured around $45^{\\circ}\\mathrm{C}$ . The system comprises a set of $I{-}V$ curves at different light intensities (dark current, 10 and $100\\mathrm{\\mW}\\mathrm{cm}^{-2},$ ). Between each measurement the cells are maintained at the maximum power point using a MPPT algorithm under $100\\mathrm{mW}\\mathrm{cm}^{-2}$ . A reference Si-photodiode is placed in the holder to verify the stability of the light. \n\nCarbon-based mesoscopic solar cells. The cells are prepared and sealed with a glass cover under ambient atmosphere as previously described. For the stability the cells are at $55^{\\circ}$ temperature, 1sun illumination for $24\\mathrm{h}$ per day, sealed under ambient atmosphere. An ultraviolet filter up to $390\\mathrm{nm}$ is on top of all over the samples. Solar simulator class A $1.5\\mathrm{M}$ at full sun under short circuit condition. Stability measurements done according to the ISOS standard conditions. \n\nSample for spectroscopy. The FTO glass was first etched to form two separated electrodes before being cleaned ultrasonically with ethanol. The patterned substrates were coated by a compact $\\mathrm{TiO}_{2}$ layer by aerosol spray pyrolysis, and $1\\upmu\\mathrm{m}$ nanoporous $\\mathrm{TiO}_{2}$ or $\\mathrm{ZrO}_{2}$ layer were deposited by screen-printing and sintered at $450^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ , as described previously. After cooling down to room temperature, the perovskite precursor solution was infiltrated by drop casting and let it drying at $50^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . The perovskite infiltrates in the mesoporous scaffold forming a capping layer of around $1\\upmu\\mathrm{m}$ thick. All the samples were encapsulated with a microscope glass to prevent any interaction with oxygen and moisture. \n\nAbsorption and photoluminescence. The absorption spectra have been registered with a ultraviolet–vis-infrared spectrophotometer (PerkinElmer Instrument). Photoluminescence (PL) Measurements: CW and time-resolved PL experiments were performed with a spectrophotometer (Gilden Photonics) using the lamp or a pulsed source at $460\\mathrm{nm}$ $\\mathrm{\\DeltaPs}$ diode lasers BDS-SM, pulse with ${<}100\\mathrm{ps}$ , from Photonic Solutions, $20\\mathrm{MHz}$ repetition rate, $\\sim500\\upmu\\mathrm{m}$ spot radius), respectively. The excitation density is around few $\\mathrm{nJ}\\mathrm{cm}^{-2}$ . The steady-state spectra and the time-resolved signal were recorded by a photomultiplier tube, and by a Time Correlated Single Photon Counting detection technique with a time resolution of 1 ns, respectively. A monoexponential and bi-exponential fitting were used to analyse the background-corrected PL decay signal. \n\nRaman spectroscopy. The micro-Raman system is based on an optical microscope (Renishaw microscope, equipped with $\\times5,\\times20,\\times50$ and $\\times100$ short and long working distance microscope objectives) used to focus the excitation light and collect it in a back scattering configuration, a monochromator, notch filters system and a charge coupled detector. The sample is mounted on a translation stage of a Leica microscope. The excitation used consists of a laser diode at $532\\mathrm{nm}$ . The system has been calibrated against the $520.5\\mathrm{cm}^{-1}$ line of an internal silicon wafer. The spectra have been registered in the $50{-}250\\mathrm{cm}^{-1}$ range, particularly sensitive the Pb-I modes. The final data have been averaged over 50 accumulations in order to maximize the signal to noise ratio. The measurements were conducted at room temperature on encapsulated samples using the $\\times100$ long working distance objective. To prevent sample degradation or thermal effects the laser power intensity is kept below $50\\upmu\\mathrm{W}$ . \n\nComputational details. DFT calculations within periodic boundary conditions have been performed within the planewave/pseudopotential formalism, as implemented in the PWSCF package of Quantum-Espresso45. For the geometry optimization we used the PBE exchange-correlation functional46 along with ultrasoft47, scalar relativistic pseudopotentials for all the atoms. Electrons from I 5s, 5p; O, N and C 2s, 2p; H 1s; Pb 6s, 6p, 5d shells explicitly included in the calculations. Spin-orbit coupling was included in the calculations of the DOS of Fig. 3. \n\nThe cutoffs for the wave function and the electronic density expansions were set to 25 and $200\\mathrm{Ry}$ cutoffs, respectively. \n\nOur model system for the 3D system is made by I-terminated $\\mathrm{MAPbI}_{3}2\\times2\\times3$ tetragonal perovskite slab exposing the 001 surfaces. The 2D slab was obtained by using the experimental X-ray data reported for $\\mathrm{(HOOC(CH_{2})_{3}N H_{3})P b I_{4}}$ in ref. 25 To model the 2D/3D interface we deposit the $2\\times2\\times1$ 2D perovskite slab exposing the 001 surfaces onto the 3D slab, replacing one $\\mathrm{MA}+$ layers from the top of the 3D slab with one $\\mathrm{HOOC}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3}$ layer, see Supplementary Fig. 12. \n\nThe experimental $\\mathbf{MAPbI}_{3}$ cell parameters $\\overset{\\prime}{a}=b=8.8556\\overset{\\cdot}{_{\\cdot}}$ are employed to build a periodic supercell in the $x$ and $y$ directions of twice the unit cell size $\\overset{\\prime}{a}={b}=17.7112$ ), leaving $10\\mathrm{\\AA}$ vacuum along the $z$ direction. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon request. \n\n# \n\nReferences \n1. National Renewable Energy Laboratory, N.R.E.L. http://www.nrel.gov/ncpv/ images/efficiency_chart.png. Accessed 20 December 2016. \n2. Saliba, M. et al. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). \n3. Saliba, M. et al. Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency. Energy Environ. Sci. 9, 1989–1997 (2016). \n4. Wang, D., Wright, M., Elumalai, N. K. & Uddin, A. Stability of perovskite solar cells. Sol. Energy Mater. Sol. Cells 147, 255–275 (2016). \n5. Berhe, T. A. et al. Organometal halide perovskite solar cells: degradation and stability. Energy Environ. Sci. 9, 323–356 (2016). \n6. Leguy, A. M. A. et al. Reversible Hydration of CH3NH3PbI3 in Films, Single Crystals, and Solar Cells. Chem. Mater. 27, 3397–3407 (2015). \n7. Sutton, R. J. et al. Bandgap-tunable cesium lead halide perovskites with high thermal stability for efficient solar cells. Adv. Energy Mater. 5, 1502458 (2016). \n8. Conings, B. et al. Intrinsic thermal instability of methylammonium lead trihalide perovskite. Adv. Energy Mater. 5, 1500477 (2016). \n9. Li, X. et al. Improved performance and stability of perovskite solar cells by crystal crosslinking with alkylphosphonic acid o-ammonium chlorides. Nat. Chem. 7, 703–711 (2015). \n10. Yang, Z. et al. Stabilized wide bandgap perovskite solar cells by tin substitution. Nano Lett. 16, 7739–7747 (2016). \n11. Qiu, W. et al. Pinhole-free perovskite films for efficient solar modules. Energy Environ. Sci. 9, 484–489 (2016). \n12. Kaltenbrunner, M. et al. Flexible high power-per-weight perovskite solar cells with chromium oxide-metal contacts for improved stability in air. Nat. Mater. 14, 1032–1039 (2015). \n13. Han, Y. et al. Degradation observations of encapsulated planar CH3NH3PbI3 perovskite solar cells at high temperatures and humidity. J. Mater. Chem. A 3, 8139–8147 (2015). \n14. Smith, I. C. et al. Hybrid perovskite solar-cell absorber with enhanced moisture stability. Angew. Chem. 126, 11414–11417 (2014). \n15. Domanski, K. et al. Not all that glitters is gold: metal-migration-induced degradation in perovskite solar cells. ACS Nano. 10, 6306–6314 (2016). \n16. Habisreutinger, S. N. et al. Carbon nanotube/polymer composites as a highly stable hole collection layer in perovskite solar cells. Nano Lett. 14, 5561–5568 (2014). \n17. You, J. et al. Improved air stability of perovskite solar cells via solutionprocessed metal oxide transport layers. Nat. Nanotechnol. 11, 75–81 (2016). \n18. IEC 61646. Thin Film Terrestrial Photovoltaic (PV) Modules—Design Qualification and Type Approval (IEC Central Office, 2008). \n19. Bella, F. et al. Improving efficiency and stability of perovskite solar cells with photocurable fluoropolymers. Science 354, 203–206 (2016). \n20. Cao, D. H., Stoumpos, C. C., Farha, O. K., Hupp, J. T. & Kanatzidis, M. G. 2D Homologous perovskites as light-absorbing materials for solar cell applications. J. Am. Chem. Soc. 137, 7843–7850 (2015). \n21. Tsai, H. et al. High-efficiency two-dimensional Ruddlesden–Popper perovskite solar cells. Nature 536, 312–316 (2016). \n22. Hambsch, M., Lin, Q., Armin, A., Burn, P. L. & Meredith, P. Efficient, monolithic large area organohalide perovskite solar cells. J. Mater. Chem. A 4, 13830–13836 (2016). \n23. Mei, A. et al. A hole-conductor–free, fully printable mesoscopic perovskite solar cell with high stability. Science 345, 295–298 (2014). \n24. Mercier, N., Poiroux, S., Riou, A. & Batail, P. Unique hydrogen bonding correlating with a reduced band gap and phase transition in the hybrid perovskites $\\mathrm{(HO(CH_{2})2N H_{3})2P b X_{4}}$ $\\mathrm{X}=\\mathrm{I}$ , Br). Inorg. Chem. 43, 8361–8366 (2004). \n25. Mercier, N. $\\mathrm{(HO_{2}C(C H_{2})3N H_{3})2(C H_{3}N H_{3})P b_{2}I_{7}}$ a predicted noncentrosymmetrical structure built up from carboxylic acid supramolecular synthons and bilayer perovskite sheets. Cryst. Eng. Commun. 7, 429–432 (2005). \n26. Li, X. et al. Outdoor performance and stability under elevated temperatures and long-term light soaking of triple-layer mesoporous perovskite photovoltaics. Energy Technol. 3, 551–555 (2015). \n27. Preda, N., Mihut, L., Baibarac, M., Baltog, I. & Lefrant, S. A distinctive signature in the Raman and photoluminescence spectra of intercalated $\\mathrm{PbI}_{2}$ . J. Phys. Condens. Matter 18, 8899 (2006). \n28. Quarti, C. et al. The Raman spectrum of the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ hybrid perovskite: interplay of theory and experiment. J. Phys. Chem. Lett. 5, 279–284 (2014). \n29. Grancini, G. et al. The impact of the crystallization processes on the structural and optical properties of hybrid perovskite films for photovoltaics. J. Phys. Chem. Lett. 5, 3836–3842 (2014). \n30. Mitzi, D. B. in Progress in Inorganic Chemistry (ed. Karlin, K. D.) 1–121 (John Wiley & Sons, Inc., 1999) http://onlinelibrary.wiley.com/doi/10.1002/ \n9780470166499.ch1/summary. \n31. Prajongtat, P. & Dittrich, T. Precipitation of $\\mathrm{CH_{3}N H_{3}P b C l_{3}}$ in CH3NH3PbI3 and Its Impact on Modulated Charge Separation. J. Phys. Chem. C. 119, \n9926–9933 (2015). \n32. Wehrenfennig, C., Liu, M., Snaith, H. J., Johnston, M. B. & Herz, L. M. Charge carrier recombination channels in the low-temperature phase of organicinorganic lead halide perovskite thin films. APL Mater. 2, 81513 (2014). \n33. Fang, H.-H. et al. Photophysics of organic–inorganic hybrid lead iodide perovskite single crystals. Adv. Funct. Mater. 25, 2378–2385 (2015). \n34. Leijtens, T. et al. Modulating the electron–hole interaction in a hybrid lead halide perovskite with an electric field. J. Am. Chem. Soc. 137, 15451–15459 (2015). \n35. Mosconi, E., Ronca, E. & De Angelis, F. First-principles investigation of the $\\mathrm{TiO}_{2}/$ organohalide perovskites interface: the role of interfacial chlorine. J. Phys. Chem. Lett. 5, 2619–2625 (2014). \n36. Rolda´n-Carmona, C. et al. High efficiency methylammonium lead triiodide perovskite solar cells: the relevance of non-stoichiometric precursors. Energy Environ. Sci. 8, 3550–3556 (2015). \n37. Gratia, P. et al. Intrinsic halide segregation at nanometer scale determines the high efficiency of mixed cation/mixed halide perovskite solar cells. J. Am. Chem. Soc. 138, 15821–15824 (2016). \n38. Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n39. Hambsch, M., Lin, Q., Armin, A., Burn, P. L. & Meredith, P. Efficient, monolithic large area organohalide perovskite solar cells. J. Mater. Chem. A 4, \n13830–1386 (2016). \n40. Liao, H.-C. et al. Enhanced efficiency of hot-cast large-area planar perovskite solar cells/modules having controlled chloride incorporation. Adv. Energy Mater. 7, 1601660 (2017). \n41. Di Giacomo, F. et al. Flexible perovskite photovoltaic modules and solar cells based on atomic layer deposited compact layers and UV-irradiated $\\mathrm{TiO}_{2}$ scaffolds on plastic substrates. Adv. Energy Mater. 5, 1401808 (2015). \n42. Qiu, w. et al. Pinhole-free perovskite films for efficient solar modules. Energy Environ. Sci. 9, 484–489 (2016). \n43. Liao, W.-Q. et al. A lead-halide perovskite molecular ferroelectric. Nat. Commun. 6, 7338 (2015). \n44. Saparov, B. & Mitzi, D. B. Organic-inorganic perovskites: structural versatility for functional materials design. Chem. Rev. 116, 4558–4596 (2016). \n45. Giannozzi, P. et al. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials. J. Phys. Condens. Matter \n21, 395502 (2009). \n46. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n47. Vanderbilt, D. Soft self-consistent pseudopotentials in a generalized eigenvalue formalism. Phys. Rev. B 41, 7892–7895 (1990). \n\n# Acknowledgements \n\nG.G. is supported by the co-funded Marie Skłodowska Curie fellowship, H2020 Grant agreement no. 665667 and fund number 588072. We acknowledge funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604032 of the MESO project. We thank Manuel Tschumi for the assistance in the stability measurements and Dr Toby Meyer for the valuable discussion. \n\n# Author contributions \n\nG.G. performed absorption, Raman and PL measurements; C.R.-C., I.Z., X.L., S.N. and F.O. prepared and characterized the solar cell; E.M. and F.D.A. performed the theoretical simulations; all the authors contributed in data analysis and in editing the manuscript; G.G., M.G. and M.K.N. conceived the idea, M.K.N. supervised the research project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Grancini, G. et al. One-Year stable perovskite solar cells by 2D/3D interface engineering. Nat. Commun. 8, 15684 doi: 10.1038/ncomms15684 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2017 " + }, + { + "id": "10.1038_s41467-017-00467-x", + "DOI": "10.1038/s41467-017-00467-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-017-00467-x", + "Relative Dir Path": "mds/10.1038_s41467-017-00467-x", + "Article Title": "Rechargeable aqueous zinc-manganese dioxide batteries with high energy and power densities", + "Authors": "Zhang, N; Cheng, FY; Liu, JX; Wang, LB; Long, XH; Liu, XS; Li, FJ; Chen, J", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Although alkaline zinc-manganese dioxide batteries have dominated the primary battery applications, it is challenging to make them rechargeable. Here we report a high-performance rechargeable zinc-manganese dioxide system with an aqueous mild-acidic zinc triflate electrolyte. We demonstrate that the tunnel structured manganese dioxide polymorphs undergo a phase transition to layered zinc-buserite on first discharging, thus allowing subsequent intercalation of zinc cations in the latter structure. Based on this electrode mechanism, we formulate an aqueous zinc/manganese triflate electrolyte that enables the formation of a protective porous manganese oxide layer. The cathode exhibits a high reversible capacity of 225 mAh g(-1) and long-term cyclability with 94% capacity retention over 2000 cycles. Remarkably, the pouch zinc-manganese dioxide battery delivers a total energy density of 75.2 Wh kg(-1). As a result of the superior battery performance, the high safety of aqueous electrolyte, the facile cell assembly and the cost benefit of the source materials, this zinc-manganese dioxide system is believed to be promising for large-scale energy storage applications.", + "Times Cited, WoS Core": 1138, + "Times Cited, All Databases": 1170, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000408820700005", + "Markdown": "# Rechargeable aqueous zinc-manganese dioxide batteries with high energy and power densities \n\nNing Zhang $\\textcircled{1}$ 1, Fangyi Cheng 1,2, Junxiang Liu1, Liubin Wang1, Xinghui Long3, Xiaosong Liu3, Fujun Li 1 & Jun Chen1,2 \n\nAlthough alkaline zinc-manganese dioxide batteries have dominated the primary battery applications, it is challenging to make them rechargeable. Here we report a high-performance rechargeable zinc-manganese dioxide system with an aqueous mild-acidic zinc triflate electrolyte. We demonstrate that the tunnel structured manganese dioxide polymorphs undergo a phase transition to layered zinc-buserite on first discharging, thus allowing subsequent intercalation of zinc cations in the latter structure. Based on this electrode mechanism, we formulate an aqueous zinc/manganese triflate electrolyte that enables the formation of a protective porous manganese oxide layer. The cathode exhibits a high reversible capacity of $225\\mathsf{m A h g}^{-1}$ and long-term cyclability with $94\\%$ capacity retention over 2000 cycles. Remarkably, the pouch zinc-manganese dioxide battery delivers a total energy density of $75.2\\mathsf{W h}\\mathsf{k g}^{-1}$ . As a result of the superior battery performance, the high safety of aqueous electrolyte, the facile cell assembly and the cost benefit of the source materials, this zinc-manganese dioxide system is believed to be promising for large-scale energy storage applications. \n\nTphneorlretoagibisees welirtehcinrhcoirgneihacssis,n eltdeyectamrniafidneld wvfecahodiscvtlaefnso,c adanpbdpa rtceartniyeowtneascbihlneenergy storage1–7. Although lithium-ion batteries have gained great improvement in energy/power density and life span, the safety issues associated with flammable organic electrolytes and the growing concerns of the price and availability of Li resources impede their large-scale deployment. Battery chemistries based on electrochemical intercalation/storage of $\\dot{\\mathrm{Na}}^{+},\\mathrm{K^{+}},\\mathrm{Mg^{2+}}$ , and $Z\\mathrm{n}^{2+}$ in aqueous electrolytes have been considered as promising alternatives, because of high safety, materials abundance, and environmental friendliness8–19. Rechargeable Zn-ion batteries (ZIBs) are particularly attractive as zinc features higher water compatibility and stability than alkaline metals, allows multivalent charge transport carriers, and can be produced and recycled with mature industrial process20–25. \n\nZinc-manganese dioxide $\\scriptstyle(Z{\\mathrm{n-MnO}}_{2},$ batteries have dominated the primary battery market because of low cost, high safety, and easy manufacturing26–28. It is highly intriguing to develop rechargeable $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries. Nevertheless, previous attempts are plagued by poor cycling performance due to the formation of irreversible discharged species (e.g., $\\mathrm{Mn}(\\mathrm{OH})_{2}$ and $\\mathrm{znO}$ at cathode and anode, respectively) in alkaline electrolytes29–31. Although alkaline $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries (Fig. 1a) were shown rechargeable for extended cycles, the delivered capacity is limited at shallow depth of discharge $(\\sim10\\%)^{32}$ . Recently, the rechargeability of aqueous $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries has been improved by using mild acidic electrolyte (e.g., aqueous $\\mathrm{ZnSO_{4}}$ solution) $33-37$ . However, the reaction mechanism of $\\mathrm{MnO}_{2}$ polymorphs remains elusive and controversial. For example, electrochemical $Z\\mathrm{n}$ -insertion in $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathrm{{\\alpha}}\\mathbf{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{\\alpha}\\mathrm{{\\alpha}}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm\\mathrm{\\alpha\\mathrm}{\\alpha\\mathrm}\\mathrm{\\alpha\\mathrm}\\mathrm{\\mathrm\\alpha\\mathrm{}\\mathrm\\alpha\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\mathrm}\\mathrm\\mathrm\\mathrm{\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\$ is shown to undergo phase transition from tunneled structure to spinel $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}{}^{33}$ , layered $Z\\mathrm{n}$ -buserite36, or birnessite38, most of which collapse upon cycling. A different mechanism was referred to the conversion reaction between $\\ensuremath{\\mathbf{\\alpha}}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}$ and $\\mathrm{MnOOH}^{35}$ . For $\\scriptstyle\\gamma-\\mathrm{MnO}_{2}.$ , complex mutiple-phase transformation was proposed on discharge, involving spinel-type $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ , tunnel-type $\\gamma{\\mathrm{-}}Z{\\mathrm{n}}_{x}{\\mathrm{MnO}}_{2}$ , and layered-type $\\mathrm{L}{-}\\dot{\\mathrm{Zn}_{x}}\\mathrm{MnO}_{2}{^{34}}$ . Additionally, the Zn-insertion properties in aqueous $\\mathrm{ZnSO_{4}}$ electrolyte are found to vary among polymorphs: $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathrm{{\\alpha}}\\mathbf{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{\\alpha}\\mathrm{}\\mathrm{{\\alpha}}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm\\mathrm{}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm\\mathrm{\\mathrm}\\mathrm{\\alpha\\alpha}\\mathrm{\\mathrm}\\mathrm\\mathrm{\\alpha\\mathrm}\\mathrm{\\alpha}\\mathrm\\mathrm{\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm{\\mathrm\\mathrm\\alpha}\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm}\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\mathrm}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\mathrm\\mathrm\\mathrm}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm}\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm}\\mathrm $ featuring $(2\\times2)+(1\\times1)$ tunnel structure39 and $\\mathsf{\\chi}_{\\mathsf{Y}^{-}}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ with $(1\\times2)+(1\\times1)$ tunnels exhibit high capacity (150‒300 mAh $\\mathbf{g}^{-1})_{..}^{34,36}$ , whereas the most stable $(1\\times1)$ tunneled $\\mathsf{\\beta{-}M n O}_{2}$ phase40, 41 hardly incorporates $Z\\mathrm{n}^{2+}$ ions33 due to narrow tunnels42. Furthermore, in the widely investigated $\\mathrm{ZnSO_{4}}$ electrolyte, $\\mathrm{MnO}_{2}$ generally suffers from capacity loss due to the dissolution of $\\mathrm{\\breve{M}n}^{2+}$ from $\\mathrm{Mn}^{3+}$ disproportionation34, 35. Pre-addition of $\\mathrm{Mn}^{2+}$ salt is proposed to improve capacity retention35 but the underneath mechanism remains unclear. Our previous study indicates that the use of zinc salt with bulky anion (e.g., $\\mathrm{CF}_{3}\\mathrm{\\dot{S}O_{3}}^{-}\\mathrm{\\dot{\\Omega}}$ benefits reactivity and stability of $Z\\mathrm{n}$ anode and spinel $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ cathode24. Therefore, elucidating the electrode reactions of $\\mathrm{MnO}_{2}$ and exploiting compatible electrolyte are desirable in developing rechargeable aqueous $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries. \n\nHerein, we report high-performance rechargeable aqueous $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cells based on $\\mathrm{MnO}_{2}$ cathode, Zn anode, and $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte with $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ additive. For the widely investigated $\\upalpha\\mathrm{-},\\upbeta\\mathrm{-}$ , and $\\mathsf{\\Omega}\\gamma{-}\\mathrm{MnO}_{2}$ polymorphs, we elucidate a common electrode reaction mechanism, by combining electrochemical measurements, $\\mathrm{\\DeltaX}$ -ray diffraction analysis (XRD), elemental analysis, transmission electron microscopy (TEM), and synchrotron $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy (XAS). Interestingly, in the exemplified $_{\\beta-\\mathrm{MnO}_{2}}$ that has been previously demonstrated unfavorable for Zn intercalation, a layer-type phase (i.e., Zn-buserite $\\mathrm{B}{-}\\mathrm{Zn}_{x}\\mathrm{MnO}_{2}{\\cdot}n\\mathrm{H}_{2}\\mathrm{O})$ is generated during the initial discharge, followed by reversible insertion/extraction of $Z\\mathrm{n}^{2+}$ ions in the layered structure (Fig. 1b). Up to $\\sim0.5~\\mathrm{Zn}$ per molecular $\\mathrm{MnO}_{2}$ is accommodated on discharging, along with disproportionated Mn dissolution and capacity fade. We significantly improve the cycling stability of $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cell by employing concentrated $\\mathrm{\\tilde{Z}n}(\\mathrm{C}\\mathrm{\\bar{F}}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte and Mn $(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ additive (Fig. 1c). The pre-added $\\mathrm{M}\\mathrm{\\ddot{n}(C F}_{3}\\mathrm{SO}_{3})_{2}$ is found to suppress $\\mathrm{Mn}^{2+}$ dissolution and result in the formation of a uniform porous $\\mathrm{MnO}_{x}$ nanosheet layer on the cathode surface, which helps to maintain the electrode integrity. Remarkably, $\\mathsf{\\beta{-}M n O}_{2}$ exhibits high reversible capacity, high rate capability, and stable cyclability. We further demonstate a soft-packed $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ full cell that delivers a reversible capacity of $1550\\mathrm{mAh}$ with a total energy density of $75.2\\mathrm{Wh}\\log^{-1}$ after 50 cycles. \n\n# Results \n\nMaterials synthesis and characterization. We selected pyrolusite $\\mathsf{\\beta{-}M n O}_{2}$ as a model polymorph, which has been previously demonstrated to exhibit extremely poor electrochemical activity33 and was prepared by a simple hydrothermal route in this study (detailedly described in experimental section). X-ray diffraction patterns (XRD, Supplementary Fig. 1a) reveals high purity of the formed tetragonal phase (JCPDS no. 24-735) with $\\mathrm{P42/mnm}$ space group. Scanning electron microscope (SEM, Supplementary Fig. 1b) of the sample displays nanorod morphology with average length of $2\\upmu\\mathrm{m}$ and width of $100{-}200\\mathrm{nm}$ . Polymorphs of $\\mathbf{\\alpha}_{\\mathrm{{(-}\\mathrm{{MnO}}}_{2}}$ and $\\mathsf{\\chi}_{\\mathsf{I}^{-}}\\mathrm{MnO}_{2}$ nanorods were also synthesized via hydrothermal technique (Supplementary Fig. 2; Supplementary Methods). Commerical $\\mathsf{\\beta{-}M n O}_{2}$ powders with large particle size of $\\sim2\\upmu\\mathrm{m}$ (Supplementary Fig. 3) were employed for comparison. \n\n![](images/ac8d2bcb36157bb5f328dce3da477045e8895d86460e61e3b1a87f37381ab9c0.jpg) \nFig. 1 $Z n-M n O_{2}$ battery chemistry. Schematic illustration of a the primary alkaline $Z n-M n O_{2}$ battery using KOH electrolyte and b the rechargeable $Z n-M n O_{2}$ cell using ${\\mathsf{C F}}_{3}{\\mathsf{S O}}_{3}{}^{-}$ -based electrolyte. c Comparison of the cycling performance of $Z_{n-M{\\mathsf{n O}}_{2}}$ cells with electrolytes of 45wt.% KOH (at $0.32\\mathsf{C})$ , 3 M $Z n S O_{4},$ 3 M $Z\\mathsf{n}(\\mathsf{C F}_{3}\\mathsf{S O}_{3})_{2},$ and 3 M $Z\\mathsf{n}(\\mathsf{C F}_{3}\\mathsf{S O}_{3})_{2}$ with 0.1 M $\\mathsf{M n}(\\mathsf{C F}_{3}\\mathsf{S O}_{3})_{2}$ additive at 0.65 C. nC equals the rate to charge/discharge the thereotical capacity $(308\\mathsf{m A h}\\mathsf{g}^{-1})$ of $\\mathsf{M n O}_{2}$ in $1/n$ hours \n\n![](images/ae0b04cb62d50dc935cf4721a123b28b578fdb1a4581abba2e0a278512fec8a4.jpg) \nFig. 2 Electrochemical and structural evolution of ${\\beta\\mathrm{-}M\\mathsf{n}O_{2}}$ in $Z_{n-M{\\mathsf{n O}}_{2}}$ cell. a Cyclic voltammograms of ${\\beta\\mathrm{-}M\\mathrm{n}O_{2}}$ electrode at a scan rate of $0.1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ from 0.8 to $1.9\\lor$ . b Typical charge/discharge curves for the initial two cycles at $0.32\\mathsf{C}$ in 3 M $\\mathsf{1}Z\\mathsf{n}(\\mathsf{C F}_{3}\\mathsf{S O}_{3})_{2}$ aqueous electrolyte. The points A–J marked the states where data were collected for XRD analysis. c $x_{R}\\mathsf{D}$ patterns of ${\\beta\\mathrm{-}M\\mathsf{n}O_{2}}$ electrode at selected states during the first and second cycles \n\nElectrode reaction mechanism. Figure 2a shows the cyclic voltammograms (CVs) of $\\mathsf{\\beta{-}M n O}_{2}$ in aqueous $3\\mathrm{M}\\ Z\\mathrm{n}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte. A sharp peak at around $1.06\\mathrm{V}$ is observed during the first cathodic sweeping. In the following cycles, the CV curves are well repeated with two cathodic peaks located at 1.35 and $1.17\\mathrm{V}$ and an overlapped anodic peak at $1.6/1.65\\mathrm{V}$ . The significant difference in CV profiles between the initial and subsequent cycles suggests phase transition. Figure $2\\mathrm{b}$ shows the typical galvanostatic profiles of $\\mathsf{\\beta{-}M n O}_{2}$ at $0.32\\mathrm{C}$ . The first discharge curve displays a flat plateau at around $1.08\\mathrm{V}$ while the second cycle presents two slopping discharge plateaus, in line with the CV results. Notably, the initial discharge capacity reaches $307\\mathrm{mAhg^{-1}}$ , which approaches the theoretical capacity of $308\\mathrm{mAh}\\bar{\\mathrm{g}}^{-1}$ (based on $\\mathrm{MnO}_{2}^{\\cdot}$ ) and corresponds to $0.5\\:\\mathrm{Zn}^{2\\dag}$ per $\\mathrm{MnO}_{2}$ . The evolution of CV profiles and discharge plateaus indicates different mechanism of $Z\\mathrm{n}^{2+}$ intercalation in $\\mathrm{MnO}_{2}$ electrode36, 43, as discussed below. \n\nTo probe the structural evolution of ${\\upbeta}{\\mathrm{-MnO}}_{2}$ in the discharge/ charge process, ex-situ XRD patterns (Fig. 2c) were recorded at the selected states (marked points in Fig. 2b). On first discharging $\\mathrm{(A\\toD)}$ ), the characteristic peaks of $_{\\beta-\\mathrm{MnO}_{2}}$ are gradually weakened and new phase arises. Besides the peaks designated to the $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ salt, new peaks emerge at 6.47, 13.00, 19.58, 26.28, and $32.93^{\\circ}$ , which could be assigned to reflections from the (001)–(005) crystallographic planes of a layered $Z\\mathrm{n}$ -buserite phase, respectively. The electrolyte salt is precipitated on the surface of both $\\mathrm{MnO}_{2}$ cathode and $Z\\mathrm{n}$ anode but can be easily removed by immersing and rinsing with water (Supplementary Fig. $\\scriptstyle4\\mathsf{a}-\\mathsf{c})$ . Notably, the XRD pattern of the rinsed cathode differs from that of previously reported species (e.g., $\\mathrm{MnOOH}^{35}$ , spinel $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}{}^{33}$ , birnessite38, tunneled $\\gamma{-}Z{\\mathrm{nMnO}_{2}}^{34}$ , and layered $\\mathrm{L}–\\mathrm{Zn}_{x}\\mathrm{MnO}_{2}^{34},$ ) in discharged $\\mathrm{MnO}_{2}$ electrodes (Supplementary Fig. 4d). Rietveld refinement of the XRD data of the discharged electrode suggests the formation of $Z\\mathrm{n}$ -buserite phase (Supplementary Fig. 4e). The exact structural motif of $Z\\mathrm{n}$ -buserite is not determined yet, but will be further investigated in the future.The $Z\\mathrm{n}$ -buserite phase, commonly found in layered Mn oxide mineral44–46, contains $\\mathrm{H}_{2}\\mathrm{O}$ layers in the channels between two $\\mathrm{MnO}_{6}$ octohedron slabs (Fig. 1b), featuring a similar structure with Ca-buserite44 (JCPDS No.50-0015). $\\mathsf{Z n}^{2+}$ cations reside above and below the Mn vacant sites and are coordinated with three O atoms adjacent to the vacancies and three O atoms from interlayer $\\mathrm{H}_{2}\\mathrm{O}^{36,^{\\circ}44-46}$ . The presence of $\\mathrm{H}_{2}\\mathrm{O}$ in the discharged species was validated using thermal gravimetric analysis (TGA), indicating a composition of $\\sim2.28$ molecular $_{\\mathrm{H}_{2}\\mathrm{O}}$ per formula of $Z\\mathrm{n}$ -buserite (Supplementary Fig. 5). In the followed charging process $(\\mathrm{D\\toF})$ , the intensity of characteristic peaks for the layered phase was gradually weakened upon extraction of $Z\\mathrm{n}$ ions. This peak attenuation could be explained by the decrease of scattering atom concentration in unit cell and the weakening of $Z\\mathrm{n-O}$ interaction due to Zn egress. Similar intensity variation of (00l) reflection has been observed on layered intercalation electrodes such as vanadium oxides9, 47. In the second cycle, the signals of layered compound were reversibly strengthened/ weakened upon $Z\\mathrm{n}^{2+}$ insertion/extraction. The presence of $\\mathsf{\\beta{-}M n O}_{2}$ can be observed in the initial several cycles but is not discernable after 10 cycles (Supplementary Fig. 6). We investigated the structural evolution of $\\scriptstyle\\mathbf{\\alpha}\\mathbf{-}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ and $\\mathsf{\\Omega}\\gamma\\mathrm{-MnO}_{2}$ cathodes as well. Interestingly, these two polymorphs undergo phase transformation to layered $Z\\mathrm{n}$ -buserite upon first discharging and reversible $Z\\mathrm{n}$ intercalation in the layered structure on subsequent cycling (Supplementary Figs. 7 and 8), resembling the case of ${\\upbeta\\mathrm{-}\\mathrm{MnO}_{2}}$ . The results suggest common electrode reaction mechanism in tunneled polymorphs of $\\mathrm{MnO}_{2}$ , which to the best of our knowlege, is first elucidated in mild acidic electrolytes. \n\nThe structural evolution of $\\mathsf{\\beta{-}M n O}_{2}$ electrode was further investigated by ex-situ TEM analysis. Figure 3a, b displays the TEM and high-resolution TEM (HRTEM) images at the initial state, where the lattice fringes can be indexed to the (110) plane of $\\mathsf{\\beta{-}M n O}_{2}$ . The annular bright field-scanning TEM (ABF-STEM) image (Fig. 3c) clearly shows the atomic arrangement within the tunnel-like framework, as schematically viewed along the [100] direction of the lattice (Fig. 3d). After fully discharging, the one-dimensional nanorod shape is maintained, while the surface of electrode becomes rough with the formation of aggregated nanoparticles (Fig. 3e), which is ascribed to the structural distortion in the phase-conversion process. The observed lattice fringes with interplanar distances of 0.45, 0.64, and $1.29\\mathrm{nm}$ correspond to the (003), (002), and (001) planes of $Z\\mathrm{n}$ -buserite (Fig. 3f and Supplementary Fig. 9a), respectively, consistent with the XRD analysis. \n\n![](images/743c2abd059a17a411bfa204b877c0ea8415f9b36ec1780b77a68d15e479dfdd.jpg) \nFig. 3 Microstructural and compositional analysis of $\\mathsf{M n O}_{2}$ . a TEM image, b HRTEM image, c ABF-STEM image, and d schematic atomic model (viewed from the [100] zone axis) at the initial state. e TEM image, f HRTEM image, g EDS line scanning profiles in TEM, and h XPS spectra of the first fully discharged electrode. Scale bars, 50 nm a, $\\mathbf{e};$ 5 nm b, f; and 1 nm c, respectively \n\nTo eliminate the impact of precipitated electrolyte salt, the discharged electrode was rinsed with water for elemental dispersive spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) analysis. The line scanning profile in TEM (Fig. 3g) and elemental mapping (Supplementary Fig. 9b) in STEM of the discharged electrode reveal the uniform distribution of $Z\\mathrm{n}$ , Mn and O, whereas S and $\\mathrm{~F~}$ from electrolyte are not detectable (Fig. 3g). In XPS spectra, the energy splitting $(\\Delta E)$ of $\\mathtt{M n}\\ 3\\mathtt{s}$ doublet peaks is 4.7 and $5.0\\mathrm{eV}$ for pristine and discharged electrodes, respectively, indicating reduced Mn valence after $Z\\mathrm{n}$ insertion (Fig. 3h). At discharged state, a new $\\mathrm{Zn}3\\mathrm{p}$ peak appears at $92.0\\mathrm{eV}$ , which is lower than that of $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}^{-}$ $(92.7\\mathrm{eV})$ and could be assigned to the intercalated Zn. These results confirm the presence of $Z\\mathrm{n}^{2+}$ ions into the layered manganese oxide host and rule out the possibility of electrode reactions associated with $\\mathrm{CF}_{3}\\mathrm{SO}_{3}{}^{-}$ anions. Furthermore, the TEM images of $\\mathsf{\\beta{-}M n O}_{2}$ electrode after different cycles (Supplementary Fig. 10) indicate expansion and exfoliation of nanorods, which is attributed to the phase transition, Mn dissolution and repeated $Z\\mathrm{n}^{2+}$ intercalation, and would incur capacity loss during cycling. \n\nTo gain insight into the variation of Mn oxidation state and electronic structure during the (de)intercalation process, we performed the synchrotron XAS characterization, which has been demonstrated useful to analyze manganese oxides48–52. Figure 4a shows the normalized Mn K-edge XANES (X-ray near edge absorption structure) profiles of $\\mathsf{\\bar{\\boldsymbol{\\beta}}}–\\mathbf{M}\\mathbf{n}\\mathsf{O}_{2}$ electrode at selected states in the initial two cycles. The nominal Mn valence was plotted vs. excitation energy of reference manganese oxides to establish fitted linear correlation (Fig. 4b). On discharging, the entire edge shifts toward lower energy, indicating a decrease of the average Mn oxidation state. The mean Mn valence at fully discharged state is estimated to be 3.6. During first charging, the edge position slightly shifts back to higher energy, while it remains almost unchanged in the second cycle. The interesting point is that the Mn valence should increase/decrease with $Z\\mathrm{n}^{2+}$ intercalation/deintercalation and would approach 3 for the fully discharged electrode, as anticipated from the discharged capacity (Fig. 2b). We postulate that such unexpected observation could be ascribed to the disproportional dissolution of trivalent Mn species $(\\mathrm{Mn}^{3+}{}_{\\mathrm{s}}\\to\\mathrm{Mn}^{4+}{}_{\\mathrm{s}}+\\mathrm{Mn}^{\\mathrm{\\bullet}}{}_{\\mathrm{aq}})^{38,}$ 53. Analysis of Mn by inductively coupled plasma atomic emission spectrometer (ICP-AES) evidences the change of Mn concentration in the electrolyte (Supplementary Fig. 11; Supplementary Note 1). On discharging, the amount of dissolved Mn increases and corresponds to $\\sim8.9\\%$ of the total manganese at full discharge. The partial dissolution of Mn in electrolyte is a feasible attribution to the noticeable capacity loss on cycling. \n\nFigure $\\mathtt{4c}$ shows the EXAFS (extended X-ray absorption fine structure) spectra of $\\mathsf{\\beta{-}M n O_{2}}$ electrode at selected Zn (de) intercalation stages. The strongest peak located at $1.5\\mathring\\mathrm{A}$ is attributed to the closest oxygen (Mn-O) in the $\\mathrm{MnO}_{6}$ octahedra. The peaks at 2.5 and $3.0\\mathring\\mathrm{A}$ are assigned to Mn in the edge-sharing $\\left(\\mathrm{Mn-Mn}_{\\mathrm{edge}}\\right)$ and corner-sharing $\\left(\\mathrm{Mn-Mn}_{\\mathrm{corner}}\\right)$ $\\mathrm{MnO}_{6}$ octahedra (Fig. 4d), respectively51, 54. When the elcctrode was fully discharged, the relative intensity of the $\\mathrm{Mn-Mn}_{\\mathrm{corner}}$ peak decreased to a much larger extent than that of Mn-O and $\\mathrm{Mn-Mn_{\\mathrm{edge}}}$ signals (Supplementary Fig. 12). This result is indicative of the breakage of the corner-shared $\\mathrm{MnO}_{6}$ octahedra. Furthermore, the $3.0\\mathring\\mathrm{A}$ peak broadens and slightly shifts to larger distance, which is related to the formation of Mn-O-Zn energy-absorbing path between the layered $\\mathrm{MnO}_{6}$ octohedron slabs and inserted $Z\\mathrm{n}$ ions. A comparison of the crystallographic structure between $_{\\mathrm{{\\beta-MnO}}_{2}}$ and $Z\\mathrm{n}$ -buserite suggests that the co-insertion of $Z\\mathrm{n}^{2+}$ and $_\\mathrm{H}_{2}\\mathrm{O}$ and the dissolution of Mn distort the pyrolusite framework, leaving Mn vacancies in the upper/underlying layers and generating layered $Z\\mathrm{n}$ -buserite. This tunnel-to-layer phase transition is irreversible, as indicated by the absence of EXAFS spectra recovery on first recharge. Meanwhile, the broadened $3.0\\mathring\\mathrm{A}$ peak is not fully recovered after second charging, which can be attritubed to the capacity loss (Fig. 2b). Notably, XAS analysis of $\\scriptstyle\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}$ and $\\mathsf{\\Omega}\\gamma\\mathrm{-MnO}_{2}$ electrodes (Supplementary Fig. 13) reveals similar behavior with that of $\\upbeta$ - $\\mathrm{MnO}_{2},$ again suggesting common electrode reaction mechanism among different tunneled $\\mathrm{MnO}_{2}$ polymorphs. \n\n![](images/47aa1c4eb79ef4fe88141b2438faa74b1f590b572eaed0a180d6ecb5949cabc0.jpg) \nFig. 4 XAS characterization of ${\\beta\\mathrm{-}M\\mathsf{n}O_{2}}$ electrode. a $M_{n-K}$ edge XANES curves at selected discharge/charge states, with reference to standard MnO, $\\mathsf{M n}_{2}\\mathsf{O}_{3},$ and $\\scriptstyle{\\mathsf{M n}}_{3}{\\mathsf{O}}_{4}$ . b Fitted linear relationship between the photon energy and oxidation state of Mn element. c The EXAFS spectra. d Schematic depiction of the unit cell of ${\\beta\\mathrm{-}}\\mathsf{M n O}_{2}$ \n\n![](images/a8643d824de309f8d1c1a0e86e4acc94388449f55d060c358e509a5021fccc7b.jpg) \nFig. 5 Electrochemical performance of $Z_{n-M{\\mathsf{n O}}_{2}}$ cells in 3 M $Z\\mathsf{n}(\\mathsf{C F}_{3}\\mathsf{S O}_{3})_{2}$ electrolyte with $0.1\\mathsf{M}\\mathsf{M n}(\\mathsf{C F}_{3}\\mathsf{S O}_{3})_{2}$ additive. a Discharge/charge profiles at varying C rates. b The Ragone plots of $Z n-M n O_{2}$ battery and ZIBs with other reported cathode materials. Values are based on the total active mass of both cathode and anode. c Long-cycle performance at rate of $6.5\\mathsf{C}$ . Inset shows the capacity evolution at the initial 19 cycles \n\n![](images/a88632e6231295c8e7e9e8009ae2dfabd6030a1e0c0bf2c16b7eba36468fc3bc.jpg) \nFig. 6 Function of pre-added $\\mathsf{M n}^{2+}$ in electrolyte. a, b, c, e SEM, d TEM images, and f, g three-electrode-cell EIS analysis of re-obtained cathodes after ten cycles in 3 M $Z\\mathsf{n}(\\mathsf{C F}_{3}\\mathsf{S O}_{3})_{2}$ electrolyte a–d, f with and e, g without 0 $.1M\\ M n(C F_{3}S O_{3})_{2}$ additive. Insets of c, d show elemental mapping and SAED pattern, respectively. Insets of f, g show the equivalent circuit to fit the EIS data, where $R_{{\\mathsf{s}}},$ $R_{\\mathrm{i}},$ $R_{\\mathrm{{ct}}},$ CPE, and $Z_{\\mathrm{w}}$ represent series resistance, interface resistance between electrolyte and deposited layer, charge-transfer resistance, constant-phase element, and Warburg diffusion process, respectively. Scale bars, $5\\upmu\\mathrm{m}$ a, e; $1\\upmu\\mathrm{m}\\ \\mathsf{b};10\\upmu\\mathrm{m}\\ \\mathsf{c};100\\mathsf{n m}\\ \\mathsf{d};$ and $51/\\mathsf{n m}$ (inset of d), respectively \n\nElectrochemical performance. To evaluate the electrochemical performance, coin-type $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cell was assembled in ambient air by using $_{\\beta-\\mathrm{MnO}_{2}}$ nanorod cathode, Zn foil anode, filter paper separator, and aqueous $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte. The concentrated $3\\mathrm{~M~}\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{\\bar{S}O}_{3})_{2}$ results in better cyclic stability than diluted electrolyte (e.g., 1 M) (Supplementary Fig. 14), which is ascribed to the decrease of water activity and water-induced side reactions4, 24, 55. As shown in Fig. 1c, the cells based on mild acidic electrolye $\\mathrm{3\\M\\ZnSO_{4}},$ $\\mathrm{pH}\\sim3.4$ ; $3\\mathrm{M}\\ Z\\mathrm{n}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2},$ $\\mathrm{pH}\\sim3.6)\\$ show much better cycling performance as compared with that employing KOH electolyte. Meanwhile, the cell using $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte delivers much higher initial discharge capacity than that of $\\mathrm{ZnSO_{4}}$ (275 vs. $120\\mathrm{mAhg^{-1}};$ ) at $0.65\\dot{\\mathrm{C}}$ . However, similar capacity deterioration is observed upon cycling, due to the loss of active mass. To address this issue, we pre-added $\\mathrm{Mn}^{2+}$ salts into the electrolyte to accommodate the dissolution equilibrium of $\\mathrm{Mn}^{2+}$ from $\\mathrm{MnO}_{2}$ electrode. By eliminating the anion effect, we selected $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ as the electrolyte additive, with concentration from diluted $0.01\\mathrm{M}$ to the saturated $0.1\\mathbf{M}$ . The optimized electrolyte composition was found to be 3 M $\\mathrm{Zn(CF_{3}S O_{3})_{2}+0.1M}$ $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2},$ which results in the highest Coulombic efficiency and ionic conductivity as well as high capacity of $225\\mathrm{mAhg^{-1}}$ after 100 cycles (Supplementary Figs. 15 and 16). \n\nFigure 5a shows the charge/discharge profiles of $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cells at different current densities. Discharge capacities of 258, 213, 188, 151, and $115\\mathrm{mAhg^{-1}}$ were recorded at rates of 0.65, 1.62, 3.25, 6.50, and $16.20\\mathrm{C},$ respectively. Even at a high rate of $32.50\\mathrm{C},$ a reversible capacity of $100\\dot{\\mathrm{mAh}}\\mathrm{g}^{-1}$ could be obtained. In addition, when the rate shifted back to $0.65\\mathrm{C}_{:}$ , the capacity recovered to $246\\mathrm{mAhg^{-1}}$ , showing a strong tolerance to the rapid $Z\\mathrm{n}^{2+}$ ions insertion/extraction (Supplementary Fig. 17). The superior rate performance can be further viewed from the Ragone plots (specific energy vs. specific power) by comparing the $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ system to reported $\\ensuremath{\\alpha}{\\mathrm{-}}\\ensuremath{\\mathrm{MnO}_{2}}^{33}$ , ${{\\delta\\mathrm{-}}\\mathrm{Mn}{{\\mathrm{O}}_{2}}^{56}}$ $\\mathrm{Zn}_{0.25}\\mathrm{V}_{2}\\mathrm{O}_{5}{\\cdot}\\mathrm{nH}_{2}\\mathrm{O}^{9}$ , $\\mathrm{Zn_{1.86}M n_{2}O_{4}}^{24}$ , todorokite37, $\\mathrm{KCuFe(CN)}_{6}$ (CuHCF)21, and $\\mathrm{Zn}_{3}[\\mathrm{Fe}(\\mathrm{CN})_{6}]_{2}$ $(Z\\mathrm{nHCF})^{57}$ cathodes for aqueous ZIBs (Fig. 5b). High-specific energy and specific power $(\\dot{25}4\\mathrm{Wh}\\mathrm{kg}^{-1}$ at $\\mathrm{\\overline{{197}}W\\ k g^{\\mathrm{-1}}}$ ; $\\dot{1}10\\mathrm{Wh}\\mathrm{kg}^{-1}$ at $5910^{\\circ}\\mathrm{W}\\mathrm{kg}^{-1}\\mathrm{\\Omega},$ can be simultaneously achieved, which is promising for energy storage applications. The $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cell was galvanostatically discharged/charged at $6.50\\mathrm{C}$ (Fig. 5c) to evaluate the long-term cycling stability. Remarkably, the reversible capacity sustains $1\\dot{3}5\\mathrm{mAh}\\mathrm{g}^{-1}$ with a capacity retention of $94\\%$ over 2000 cycles and Coulombic efficiency approaching $100\\%$ . \n\nWe also investigated the $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cells with $3\\mathrm{MZnSO_{4}}+0.1\\mathrm{M}$ $\\mathrm{MnSO_{4}}$ and $3\\mathrm{M}\\mathrm{~Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}+0.1\\mathrm{M}\\mathrm{~MnSO}_{4}$ electrolytes, which delivered initial discharge capacity of 110 and $20\\dot{5}\\mathrm{mAh}\\mathrm{g}^{-1}$ respectively (Supplementary Fig. 18). In $\\mathrm{SO_{4}}^{2-}$ -based electrolyte, an increase of capacity was observed within the first several cycles, which was attributed to the activation process that has been similarly found in reported ${\\upalpha}{-}/{\\upgamma}{-}\\mathrm{MnO}_{2}$ cathodes34–36. Interestingly, the $\\mathrm{CF}_{3}\\mathrm{\\dot{S}O}_{3}{}^{-}$ -based electrolyte endows much higher initial discharge capacity $(275\\mathrm{mAhg^{-1}}$ at $0.65\\mathrm{C})$ and results in capacity stabilization after $\\sim10$ cycles. The different behaviors could be ascribed to the $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ solution that not only features higher ionic conductivity (Supplementary Fig. 19) but also enables faster kinetics and higher stability of $Z\\mathrm{n}$ plating/stripping as compared with sulfate and alkaline electrolytes (Supplementary Fig. 20; Supplementary Note 2). Besides, the bulky $\\bar{\\mathrm{CF}_{3}}\\mathrm{SO}_{3}{}^{-}$ anion (vs. $\\mathrm{SO_{4}}^{2-}$ with double charge) could decrease the number of water molecules surrounding $Z\\mathrm{n}^{2\\mathrm{+}}$ cations and reduce the solvation effect24, thus facilitating $Z\\mathrm{n}^{2\\mp}$ ions transportation and charge transfer. \n\nAlthough the pre-addition of $\\mathrm{Mn}^{2+}$ in electrolyte has been demonstrated to enhance the cyclability of $\\mathrm{MnO}_{2}$ electrode35, the underneath mechanism remains unclear. To further understand the functions of pre-added $\\mathrm{Mn}^{2+}$ , we have carried out a series of analytical studies, including electrochemical measurements, XRD, Raman, XPS, XANES, and SEM/TEM. In acidic electrolyte, manganese oxides $(\\mathrm{MnO}_{x})$ such as $\\mathrm{MnO}_{2}$ or $\\mathrm{Mn}_{2}\\mathrm{O}_{3}$ can be generated from electrolysis of $\\mathrm{Mn}^{2+}$ -containing solution32 based on the following reactions: \n\n![](images/bb4718d70f4bd5ecef45ced0f5d4997bae872868289309642c7efa49286543ba.jpg) \nFig. 7 Electrochemical performance of pouch-type $Z n-M n O_{2}$ battery. a Schematic illustration of the cell configuration with anode—separator—cathode stacks. b A digital photo of the soft-package battery powering a series of LED lights. c Cycling performance in the voltage range of 0.8–1.9 V at constan current of 0.72 A \n\n$$\n\\begin{array}{c}{{\\mathrm{MnO_{2}}+4\\mathrm{H}^{+}+2e^{-}=\\mathrm{Mn}^{2+}+2\\mathrm{H}_{2}\\mathrm{O}}}\\\\ {{E^{\\ominus}=2.01\\mathrm{V}\\big(\\mathrm{vs.~}\\mathrm{Zn}^{2+}/\\mathrm{Zn}\\big)}}\\end{array}\n$$ \n\n$$\n\\begin{array}{c}{{\\mathrm{Mn}_{2}\\mathrm{O}_{3}+6\\mathrm{H}^{+}+2\\mathrm{e}^{-}=2\\mathrm{Mn}^{2+}+3\\mathrm{H}_{2}\\mathrm{O}}}\\\\ {{E^{6}=2.26\\mathrm{V}\\mathrm{(vs.~}\\mathrm{Zn}^{2+}/\\mathrm{Zn}\\mathrm{)}}}\\end{array}\n$$ \n\nAccording to Nernst equation, the required theoretical potentials to form $\\mathrm{MnO}_{2}$ and $\\mathrm{Mn}_{2}\\mathrm{O}_{3}$ in $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ $(0.1\\mathrm{M}$ , $\\mathrm{pH}6.0\\right)$ solution are 1.35 and $1.26\\mathrm{V}$ (vs. $Z\\mathrm{n}^{2+}/\\mathrm{Zn}^{\\cdot}$ , respectively; the corresponding values are 1.60 and $1.64\\mathrm{V}$ in $3\\mathrm{M}\\mathrm{Zn}(\\mathrm{\\bar{C}F}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte containing $0.1\\mathrm{M}\\mathrm{~}\\mathrm{Mn}^{2+}$ $\\mathrm{(pH}~3.8)$ . This estimation is consistent with the voltammetry results of three-electrode measurements (Supplementary Fig. 21; Supplementary Note 3), which also reveals that $\\mathrm{Mn}^{2+}$ is not reduced within the investigated potential windows. After charging in $3\\mathrm{M}$ Zn $(\\mathrm{CF}_{3}\\mathrm{S}\\bar{\\mathrm{O}}_{3})_{2}+\\bar{0.1}\\mathrm{M}\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte, brown deposit layer was observed on the electrode. The layer is composed of manganese oxide with Mn oxidation state between $+3$ and $+4$ , and features nanosheet morphology and poor crystallinity, as analyzed by SEM, XRD, Raman, XPS, and XAENS (Supplementary Fig. 22). \n\nIn post-mortem analysis of $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cell using 3 M Zn $(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}+0.11$ M $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte, we also observed an interconnected porous $\\mathrm{MnO}_{x}$ layer on the cathode surface after charging (Fig. 6a, b). The cross-sectional SEM image and elemental mapping images (Fig. 6c) evidence the presence of a uniform layer with thickness around $10\\upmu\\mathrm{m}$ . TEM imaging and selected area electron diffraction (SAED) analysis reveal porous nanosheet microstructure and amorphous character of the deposited layer (Fig. 6d), which would facilitate mass diffusion. In contrast, the integrity of $\\mathsf{\\beta{-}M n O}_{2}$ electrode was seriously destroyed with the formation of cracks in 3 M $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte without $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ additive (Fig. 6e). The electrode pulverization would break the electronic conducting network and increase electrode polarization, further aggravating the capacity decay. Electrochemical impedance spectroscopy (EIS) was performed in a three-electrode cell, using the dismantled cathode after ten cycles as the working electrode, platinum plate as the counter electrode, and saturated calomel electrode (SCE) as the reference electrode. The cycled electrode in $\\mathrm{Mn}^{2+}$ -added electrolyte displays two depressed semicircles in high frequency area and one line in low frequency region (Fig. 6f). Fitting the EIS data (Supplementary Table 1) gives a series resistance $(R_{s},4.5\\Omega)$ , an interface resistance $(R_{\\mathrm{i}},6.0\\Omega)$ between electrolyte and deposited layer, a charge-transfer resistance $(R_{\\mathrm{ct}},~25\\Omega)$ and a Warburg diffusion impedance $(Z_{\\mathrm{w}},124.7\\Omega)$ . In comparison, the cell without electrolyte additive shows higher $R_{s}~(8.0\\Omega),R_{\\mathrm{ct}}~(350\\Omega)$ , and $Z_{\\mathrm{w}}$ $(1200\\Omega)$ , in the absence of the apparent interface component (Fig. 6g). \n\nBased on the above results, we propose three merits of the $\\mathrm{Mn}^{2+}$ electrolyte additive for the $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ battery: (1) accommodating and compensating $\\mathrm{Mn}^{2+}$ dissolution from the electrode, (2) improving initial Coulombic efficiency and ionic conductivity of the electrolyte and (3) generating a uniform porous nanostructured $\\mathrm{MnO}_{x}$ film on the cathode surface, which helps to maintain the electrode integrity and favor charge transfer. Note that the generated $\\mathrm{MnO}_{x}^{\\mathrm{-}}$ layer itself contributes to nearly $2.4\\%$ of the capacity delivered by the active material (Supplementary Fig. 23). The $\\mathrm{Zn(CF_{3}S O_{3})_{2}+M n(C F_{3}S O_{3})_{2}}$ electrolyte is also applicable to improve the cycling stability of nanostructured $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathrm{{\\alpha}}\\mathbf{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}\\mathrm{{\\alpha}}$ and $\\mathsf{\\Omega}\\gamma\\mathrm{-MnO}_{2}$ cathodes (Supplementary Fig. 24a, b). Furthermore, commercial $_{\\beta-\\mathrm{MnO}_{2}}$ powders with irregular shape and micrometer particle size (Supplementary Fig. 3) also exhibit considerable capacity $(132\\mathrm{mAh}\\mathrm{g}^{-1}$ at $0.65\\dot{\\mathrm{C}},\\$ ) and cyclability (200 cycles) in this electrolyte (Supplementary Fig. 24c, d). \n\nThe Zn anode was also investigated to understand the high-performing $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cell chemistry (Supplementary Figs. 25–28). Post-mortem analysis of cycled Zn in threeelectrode cell with $3\\mathrm{M}$ $\\mathrm{Zn(CF_{3}S O_{3})_{2}+0.1\\Delta M}$ $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte reveals a dense and dendrite-free surface morphology after $280\\mathrm{h}$ of repeated $Z\\mathrm{n}$ plating/stripping (Supplementary Fig. 25). In a $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ full cell, neither dendritic morphology nor formation of byproducts such as $\\mathrm{{}}Z\\mathrm{{nO}}$ or $\\bar{Z}\\mathrm{n(OH)}_{2}$ was evidenced after rate test (Supplementary Fig. 26), favoring the cyclic stability of $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries. In contrast, in $3\\mathrm{M}$ $\\mathrm{ZnSO_{4}}+0.1\\:\\mathrm{N}$ $\\mathrm{MnSO_{4}}$ electrolyte, Zn plate with lots of cracks formed on the zinc surface, while $\\mathrm{znO}$ nanorods were observed in KOH electrolyte, which would deter the cyclability of Zn (Supplementary Figs. 25 and 27). Furthermore, the EDS analysis indicates that there is no detectable Mn in $Z\\mathrm{n}$ anode (Supplementary Fig. 28). \n\n# Discussion \n\nThe exceptional performance of $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ coin-type batteries has motivated us to further assess soft-packed full cells, which were facilely assembled in ambient air negating complicated procedures or extra protection (Supplementary Methods). Figure 7a schematically shows the battery configuration consisting of six anode—separator—cathode stacks. A typical assembled pouch-type cell lightens a $^{\\mathrm{e}}Z\\mathrm{n-Mn}^{\\mathrm{3}}$ —shape indicator containing 44 LEDs (Fig. 7b). A stable discharge capacity of $1550\\mathrm{mAh}$ can be obtained after 50 repeated cycles with an average potential of $1.35\\mathrm{V}$ (Fig. 7c). The full cell delivers an energy density of 158.5 $\\mathrm{Wh}\\mathrm{kg^{-1}}$ based on the total weight of the active materials (including both cathode and anode). This value far exceeds that of other aqueous Li-ion batteries (50–90 Wh kg−1)3, 4, 58 and aqueous Na-ion batteries $(\\sim33\\mathrm{Wh}\\mathrm{kg}^{-1})^{\\xi}$ 8, 16, 59. Remarkably, a total energy density of $75.2\\mathrm{Wh}\\mathrm{kg}^{-\\Gamma}$ is obtained according to the mass of whole battery mass, much higher than that of commercial $\\mathrm{Pb}$ -acid $(\\sim30\\mathrm{Wh}\\mathrm{kg}^{-1},$ ) and Ni-Cd technologies $(\\sim50\\mathrm{Wh}\\mathrm{kg}^{-1})^{26}$ . We note that the higher price of anhydrous $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ salt relative to $\\mathrm{ZnSO_{4}}$ and KOH would inevitably increase the practical cost of this aqueous $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ battery system, even though $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ merely serves as charge carrier and is not consumed during battery operation. Fortunately, considering the abundant, cheap precursors (i.e., triflic acid and $Z\\mathrm{nCO}_{3})^{60}$ and the direct usage of hydrateform salt in aqueous solution, the cost of $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte could be expected to drop with the development of synthetic technique and market demand. \n\nIn conclusion, we demonstrate a high-performing rechargeable $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ battery system based on zinc anode, $\\mathsf{\\beta{-}M n O}_{2}$ cathode, and mild acidic aqueous electrolyte. We elucidate the $Z\\mathrm{n}$ -insertion mechanism and structural evolution of $\\mathrm{MnO}_{2}$ cathode by combining electrochemical investigations, XRD, TEM, ICP, and XANES/EXAFS analysis. A phase transition from tunneled to layered structure ( $\\mathrm{\\cdot}\\mathrm{Zn}$ -buserite) occurs during the first discharge of $\\mathrm{MnO}_{2},$ followed by reversible $Z\\mathrm{n}^{2+}$ (de)intercalation in the $_{\\mathrm{H}_{2}\\mathrm{O}}$ -containing $Z\\mathrm{n}$ -buserite framework. Unlike previous reports, this electrode mechanism is common in polymorphs of $\\scriptstyle\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}(\\mathbf{\\alpha}_{2}$ , $\\mathsf{\\gamma}\\gamma\\mathrm{-}\\mathrm{MnO}_{2}$ , and $\\mathsf{\\beta{-}M n O}_{2}$ . The phase tranformation, Mn dissolution and electode pulverization incur capacity fade of $\\mathrm{MnO}_{2}$ . By formulating an aqueous $3\\mathrm{M}\\mathrm{Zn(CF_{3}S O_{3})_{2}+0.1M\\mathrm{Mn}}$ $(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte, the $\\mathrm{\\dot{M}n}^{2+}$ dissolution can be effectively accommodated and the electrode integrity can be maintained because of the in-situ generated amorphous $\\mathrm{MnO}_{x}$ layer. As a result, $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ cell exhibits high capacity $(225\\mathrm{mA}\\dot{\\mathrm{h}}\\mathrm{g}^{-1}$ at $0.65\\mathrm{C})$ , high rate capability $(100\\mathrm{{mAhg}^{-1}}$ at $32.50\\mathrm{C})$ and longterm cycling stability $94\\%$ capacity retention after 2000 cycles at $6.50\\mathrm{C})$ . Furthermore, the assembled soft-packed $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ battery can deliver a high reversible capacity of $1550\\mathrm{mAh}$ with a total energy density of $75.2\\mathrm{Wh}\\mathrm{kg^{-f}}$ , among the highest value achieved in aqueous battery technologies. The present $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ system holds great promise for potential applications in largescale energy storage, in view of the remarkable electrochemical performance and other advantages such as low materials cost, easy manufacturing, high safety, and environmental friendliness. \n\n# Methods \n\nSynthesis. $\\mathsf{\\beta{-}M n O}_{2}$ nanorods were synthesized by a hydrothermal method. In a typical synthesis, 30 ml $\\mathrm{KMnO}_{4}$ ( $0.1\\mathrm{M})$ and 30 ml $\\mathrm{MnSO_{4}{\\cdot}H_{2}O}$ $(0.6\\mathbf{M})$ were mixed under continuous stirring for $30\\mathrm{min}$ at room temperature. The mixture was loaded into a $100\\mathrm{ml}$ Teflon-lined autoclave and maintained at $140^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . The obtained product was centrifuged, washed thoroughly using water and absolute ethyl alcohol, and dried at $80^{\\circ}\\mathrm{C}$ for $^{10\\mathrm{h}}$ . Bulk $\\mathsf{\\beta{-}M n O}_{2}$ powders was purchased from Alfa Aesar. $\\mathbf{\\alpha}_{\\mathrm{{(\\alpha-MnO_{2}}}}$ and $\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma\\left.\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma\\left[\\frac{\\gamma}{\\mathsf{\\gamma}\\mathsf{\\gamma}\\cdot\\mathsf{\\gamma}\\mathsf{\\left[\\gamma\\frac{\\gamma}\\mathsf{\\gamma\\left[\\frac{\\gamma\\alpha}\\mathsf{\\beta}\\right]}}\\right]}}$ nanorods were synthesized via hydrothermal technique following previously reported procedures61. \n\nCharacterization. Powder XRD patterns were collected on a Rigaku X-ray diffractometer (MiniFlex600) with Cu Kα radiation. SEM images were obtained on Field-emission JEOL JSM-7500F microscope. TEM and HRTEM images were taken on Philips Tecnai G2 F20. ABF-STEM was performed on Titan Cubed Themis $G2~300$ (FEI) at an acceleration voltage of $200\\mathrm{kV}$ . The XAS data were collected on BL14W1 beamline of Shanghai Synchrotron Radiation Facility and analyzed with software of Ifeffit Athena62. ICP-AES measurements were conducted on a PerkinElmer Optima 8300. XPS was tested on a Perkin Elmer PHI 1600 ESCA system. Raman spectra were obtained on confocal Thermo-Fisher Scientific DXR microscope using $532\\mathrm{nm}$ excitation. TGA was measured by a Netzsch STA 449 F3 Jupiter analyzer. \n\nElectrochemical test. Electrochemical performance was tested using CR2032 coin-type cells. The working electrode was fabricated by blending $\\mathrm{MnO}_{2}$ powder, Super P carbon and polyvinylidene fluoride in a weight ratio of 8:1:1 using $N.$ -methyl-2-pyrrolidone as solvent. The obtained slurry was pasted onto a Ti foil and vacuum-dried at $100^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . The loading mass of active material was $\\sim2~\\mathrm{mg}\\mathrm{cm}^{-2}$ . Filter paper and zinc foil were employed as the separator and anode, respectively. A 3 M $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ with/without 0.1 M $\\mathrm{Mn}(\\mathrm{CF}_{3}\\mathrm{\\bar{SO}}_{3})_{2}$ aqueous solution was used as the electrolyte. The assembled cells were galvanostatically cycled between 0.8 and $1.9\\mathrm{V}$ using the LAND-CT2001A battery-testing instrument. Calculation of specific capacities was based on the mass of initial $\\mathrm{{MnO}}_{2}$ . CVs were measured on a Parstat 263 A electrochemical workstation (AMETEK). EIS was performed on a Parstat 2273 electrochemical workstation (AMETEK). The AC perturbation signal was $\\pm10\\mathrm{mV}$ and the frequency ranged from $100\\mathrm{kHz}$ to $100\\mathrm{mHz}$ . The electrochemical behaviors of $\\mathrm{Mn}^{2+}$ additive in electrolyte were characterized using three-electrode cells (Ti foil as working electrode, platinum plate or $Z\\mathrm{n}$ foil as counter electrode, and SCE as reference electrode). \n\nData availability. The authors declare that all the relevant data are available within the paper and its Supplementary Information file or from the corresponding author upon reasonable request. \n\nReceived: 6 January 2017 Accepted: 27 June 2017 \nPublished online: 01 September 2017 \n\n# References \n\n1. Armand, M. & Tarascon, J. M. Building better batteries. Nature 451, 652–657 (2008). \n2. Choi, J. W. & Aurbach, D. Promise and reality of post-lithium-ion batteries with high energy densities. Nat. Rev. Mater. 1, 16013 (2016). \n3. Li, W., Dahn, J. R. & Wainwright, D. S. Rechargeable lithium batteries with aqueous electrolytes. Science 264, 1115–1118 (1994). \n4. Suo, L. et al. “Water-in-salt” electrolyte enables high-voltage aqueous lithiumion chemistries. Science 350, 938–943 (2015). \n5. Lin, M. C. et al. An ultrafast rechargeable aluminium-ion battery. Nature 520, 325–328 (2015). \n6. Ponrouch, A., Frontera, C., Barde, F. & Palacin, M. R. Towards a calcium-based rechargeable battery. Nat. Mater. 15, 169 (2015). \n7. Hassoun, J., Lee, K. S., Sun, Y. K. & Scrosati, B. An advanced lithium ion battery based on high performance electrode materials. J. Am. Chem. Soc. 133, 3139–3143 (2011). \n8. Kim, H. et al. Aqueous rechargeable Li and Na ion batteries. Chem. Rev. 114, 11788–11827 (2014). \n9. Kundu, D. et al. A high-capacity and long-life aqueous rechargeable zinc battery using a metal oxide intercalation cathode. Nat. Energy 1, 16119 (2016). \n10. Pasta, M. et al. Full open-framework batteries for stationary energy storage. Nat. Commun. 5, 3007 (2014). \n11. Pasta, M., Wessells, C. D., Huggins, R. A. & Cui, Y. A high-rate and long cycle life aqueous electrolyte battery for grid-scale energy storage. Nat. Commun. 3, 1149 (2012). \n12. Lu, Y., Goodenough, J. B. & Kim, Y. Aqueous cathode for next-generation alkali-ion batteries. J. Am. Chem. Soc. 133, 5756–5759 (2011). \n13. Wang, Y. et al. Ti-substituted tunnel-type $\\mathrm{Na}_{0.44}\\mathrm{MnO}_{2}$ oxide as a negative electrode for aqueous sodium-ion batteries. Nat. Commun. 6, 6401 (2015). \n14. Yabuuchi, N., Kubota, K., Dahbi, M. & Komaba, S. Research development on sodium-ion batteries. Chem. Rev. 114, 11636–11682 (2014). \n15. Su, D., McDonagh, A., Qiao, S. Z. & Wang, G. High-capacity aqueous potassium-ion batteries for large-scale energy storage. Adv. Mater. 29, 1604007 (2017). \n16. Shan, X. et al. Bivalence $\\mathrm{Mn}_{5}\\mathrm{O}_{8}$ with hydroxylated interphase for high-voltage aqueous sodium-ion storage. Nat. Commun. 7, 13370 (2016). \n17. Häupler, B. et al. Aqueous zinc-organic polymer battery with a high rate performance and long lifetime. NPG Asia Mater. 8, e283 (2016). \n18. Sun, X. et al. Investigation of the mechanism of Mg insertion in birnessite in nonaqueous and aqueous rechargeable mg-ion batteries. Chem. Mater. 28, 534–542 (2016). \n19. Bucur, C. B., Gregory, T., Oliver, A. G. & Muldoon, J. Confession of a magnesium battery. J. Phys. Chem. Lett. 6, 3578–3591 (2015). \n20. González, M. A. et al. Layered double hydroxides as a suitable substrate to improve the efficiency of $Z\\mathrm{n}$ anode in neutral pH Zn-ion batteries. Electrochem. Commun. 68, 1–4 (2016). \n21. Trócoli, R. & La Mantia, F. An aqueous zinc-ion battery based on copper hexacyanoferrate. ChemSusChem. 8, 481–485 (2015). \n22. Tahil, W. The zinc air battery and the zinc economy: A virutuous circle. Available at: www.meridian-int-res.com/Projects/The_Zinc_Air_Solution.pdf (Meridian International Research, 2007). \n23. Chamoun, M. et al. Hyper-dendritic nanoporous zinc foam anodes. NPG Asia Mater 7, e178 (2015). \n24. Zhang, N. et al. Cation-deficient spinel $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ cathode in $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte for rechargeable aqueous $Z\\mathrm{n}$ -ion battery. J. Am. Chem. Soc. 138, 12894–12901 (2016). \n25. Cheng, Y. et al. Highly reversible zinc-ion intercalation into chevrel phase $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ nanocubes and applications for advanced zinc-ion batteries. ACS Appl. Mater. Interfaces 8, 13673–13677 (2016). \n26. Linden, D. & Reddy, T. Handbook of Batteries 3rd edn (McGraw-Hill, 2002). \n27. Winter, M. & Brodd, R. J. What are batteries, fuel cells, and supercapacitors? Chem. Rev. 104, 4245–4270 (2004). \n28. Cheng, F. Y., Chen, J., Gou, X. L. & Shen, P. W. High-power alkaline $\\mathrm{Zn}{-}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries using $\\scriptstyle\\gamma-\\mathrm{MnO}_{2}$ nanowires/nanotubes and electrolytic zinc powder. Adv. Mater. 17, 2753–2756 (2005). \n29. Kannan, A. M. et al. Characterization of the bismuth-modified manganese dioxide cathodes in rechargeable alkaline cells. J. Electrochem. Soc. 149, A483 (2002). \n30. McLarnon, F. R. & Cairns, E. J. The secondary alkaline zinc electrode. J. Electrochem. Soc. 138, 645–656 (1991). \n31. Shen, Y. & Kordesch, K. The mechanism of capacity fade of rechargeable alkaline manganese dioxide zinc cells. J. Power Sources 87, 162–166 (2000). \n32. Gibson, A. J. et al. Dynamic electrodeposition of manganese dioxide: Temporal variation in the electrodeposition mechanism. J. Electrochem. Soc. 163, H305–H312 (2016). \n33. Xu, C., Li, B., Du, H. & Kang, F. Energetic zinc ion chemistry: The rechargeable zinc ion battery. Angew. Chem. Int. Ed. 51, 933–935 (2012). \n34. Alfaruqi, M. H. et al. Electrochemically induced structural transformation in a $\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma\\left.\\mathsf{\\gamma}\\mathsf{\\gamma}\\mathsf{\\gamma\\left[\\frac{\\gamma\\mathsf{\\gamma}\\mathsf{\\gamma}\\cdot\\mathsf{\\gamma}\\mathsf{\\gamma\\left[\\frac{\\gamma\\gamma}\\mathsf{\\gamma\\left[\\frac\\gamma\\mathsf{\\gamma}\\right]}}{\\mathsf\\gamma\\left[\\frac{\\gamma\\left.\\mathsf{\\gamma\\left[\\gamma\\left.\\mathsf\\gamma\\right]}\\right]}\\right.\\mathsf\\quad}\\quad\\mathsf{\\gamma}\\left.\\mathsf\\mathsf{\\gamma\\left[\\frac\\gamma\\left.\\mathsf\\mathrm{\\gamma\\left.\\gamma\\left[\\frac\\gamma\\right]\\left.\\mathrm\\gamma\\left.\\mathrm\\gamma\\right.\\left.\\quad\\frac\\gamma\\quad\\quad\\gamma\\left.\\quad\\frac\\gamma\\right.\\quad\\quad\\gamma\\left.\\quad\\frac\\gamma\\right.\\quad\\quad\\gamma\\left.\\left.\\frac\\quad\\frac\\gamma\\right.\\left.\\quad\\quad\\gamma\\left.\\right.\\left.\\frac\\gamma\\right.\\left.\\right.\\left.\\quad\\left.\\frac\\quad\\gamma\\left.\\left.\\right.\\left.\\left.\\left.\\right.$ cathode of a high capacity zinc-ion battery system. Chem. Mater. 27, 3609–3620 (2015). \n35. Pan, H. et al. Reversible aqueous zinc/manganese oxide energy storage from conversion reactions. Nat. Energy 1, 16039 (2016). \n36. Lee, B. et al. Elucidating the intercalation mechanism of zinc ions into small alpha- $\\cdot\\mathrm{MnO}_{2}$ for rechargeable zinc batteries. Chem. Commun. 51, 9265–9268 (2015). \n37. Lee, J. et al. Todorokite-type $\\mathrm{MnO}_{2}$ as a zinc-ion intercalating material. Electrochim. Acta 112, 138–143 (2013). \n38. Lee, B. et al. Electrochemically-induced reversible transition from the tunneled to layered polymorphs of manganese dioxide. Sci. Rep. 4, 6066 (2014). \n39. Yuan, Y. et al. The influence of large cations on the electrochemical properties of tunnel-structured metal oxides. Nat. Commun. 7, 13374 (2016). \n40. Jiao, F. & Bruce, P. G. Mesoporous crystalline $\\mathsf{\\beta{-}M n O}_{2}$ –a reversible positive electrode for rechargeable lithium batteries. Adv. Mater. 19, 657–660 (2007). \n41. Tompsett, D. A., Parker, S. C. & Islam, M. S. Rutile $\\left({\\beta-}\\right)\\mathrm{MnO}_{2}$ surfaces and vacancy formation for high electrochemical and catalytic performance. J. Am. Chem. Soc. 136, 1418–1426 (2014). \n42. Wei, C. et al. Preparation and characterization of manganese dioxides with nano-sized tunnel structures for zinc ion storage. J. Phys. Chem. Solids 73, 1487–1491 (2012). \n43. Yamada, A. et al. Room-temperature miscibility gap in $\\mathrm{Li_{x}F e P O_{4}}$ . Nat. Mater. 5, 357–360 (2006). \n44. Luo, J. et al. Double-aging method for preparation of stabilized Na−buserite and transformations to todorokites incorporated with various metals. Inorg. Chem. 38, 6106–6113 (1999). \n45. Post, J. E. Manganese oxide minerals: Crystal structures and economic and environmental significance. Proc. Natl Acad. Sci. 96, 3447–3454 (1999). \n46. Golden, D. C., Chen, C. C. & Dixon, J. B. Transformation of birnessite to buserite, todorokite, and manganite under mild hydrothermal treatment. Clays Clay Miner 35, 271–280 (1987). \n47. Tepavcevic, S. et al. Nanostructured bilayered vanadium oxide electrodes for rechargeable sodium-ion batteries. ACS Nano 6, 530–538 (2012). \n48. Hu, Y. Y. et al. Origin of additional capacities in metal oxide lithium-ion battery electrodes. Nat. Mater. 12, 1130–1136 (2013). \n49. Lu, J. et al. Effectively suppressing dissolution of manganese from spinel lithium manganate via a nanoscale surface-doping approach. Nat. Commun. 5, 5693 (2014). \n50. Kim, C. et al. Direct observation of reversible magnesium ion intercalation into a spinel oxide host. Adv. Mater. 27, 3377–3384 (2015). \n51. Zhang, R. et al. $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{(}\\mathbf{{\\alpha}}\\mathbf{{)}}\\mathbf{{\\alpha}}}}}}}}}}}}\\mathrm{~}$ as a cathode material for rechargeable $\\mathbf{\\mathrm{{Mg}}}$ batteries. Electrochem. Commun. 23, 110–113 (2012). \n52. Li, C. et al. Phase and composition controllable synthesis of cobalt manganese spinel nanoparticles towards efficient oxygen electrocatalysis. Nat. Commun. 6, 7345 (2015). \n53. Thackeray, M. M. et al. Structural fatigue in spinel electrodes in high voltage (4 V) Li / $\\mathrm{Li_{x}M n_{2}O_{4}}$ cells. Electrochem. Solid-State Lett. 1, 7–9 (1998). \n54. Nam, K. W., Kim, M. G. & Kim, K. B. In situ Mn K-edge x-ray absorption spectroscopy studies of electrodeposited manganese oxide films for electrochemical capacitors. J. Phys. Chem. C 111, 749–758 (2007). \n55. Alfaruqi, M. H. et al. A layered $_{{\\delta-}\\mathrm{Mn}\\mathrm{O}_{2}}$ nanoflake cathode with high zincstorage capacities for eco-friendly battery applications. Electrochem. Commun. 60, 121–125 (2015). \n56. Ramanujapuram, A. et al. Degradation and stabilization of lithium cobalt oxide in aqueous electrolytes. Energy Environ. Sci. 9, 1841–1848 (2016). \n57. Zhang, L., Chen, L., Zhou, X. & Liu, Z. Towards high-voltage aqueous metalion batteries beyond $1.5\\mathrm{V}$ The zinc/zinc hexacyanoferrate system. Adv. Energy Mater. 5, 1400930 (2015). \n58. Luo, J. Y., Cui, W. J., He, P. & Xia, Y. Y. Raising the cycling stability of aqueous lithium-ion batteries by eliminating oxygen in the electrolyte. Nat. Chem. 2, 760–765 (2010). \n59. Li, Z. et al. Towards high power high energy aqueous sodium-ion batteries: The $\\mathrm{NaTi}_{2}(\\mathrm{PO}_{4})_{3}/\\mathrm{Na}_{0.44}\\mathrm{MnO}_{2}$ system. Adv. Energy Mater 3, 290–294 (2013). \n60. Chandak, H., Sarode, P. & Bahekar, S. $\\mathrm{Zn}(\\mathrm{OTf})_{2}$ -mediated expeditious and solvent-free synthesis of propargylamines via C–H activation of phenylacetylene. Synlett 27, 2209–2212 (2016). \n61. Cheng, F. et al. Facile controlled synthesis of $\\mathrm{MnO}_{2}$ nanostructures of novel shapes and their application in batteries. Inorg. Chem. 45, 2038–2044 (2006). \n62. Yu, H. et al. The XAFS beamline of SSRF. Nucl. Sci. Tech. 26, 050102 (2015). \n\n# Acknowledgements \n\nThis work was supported by MOST (2016YFA0202500 and 2017YFA0206702), NSFC (21231005, 21473235, and 11227902) and MOE (B12015, ACET-13-0296, and IRT13R30). \n\n# Author contributions \n\nN.Z., J.L., and L.W. conducted the synthesis. N.Z. carried out the characterization and the electrochemical measurements. N.Z., F.C., and J.C. co-wrote the manuscript. N.Z., F.C., and X.L. analyzed the results of synchrotron X-ray absorption spectroscopy. All authors discussed the data and commented on the manuscript. F.C. and J.C. directed the research. \n\n# Additional information \n\nSupplementary Information accompanies this paper at doi:10.1038/s41467-017-00467-x. \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2017 " + }, + { + "id": "10.1073_pnas.1615837114", + "DOI": "10.1073/pnas.1615837114", + "DOI Link": "http://dx.doi.org/10.1073/pnas.1615837114", + "Relative Dir Path": "mds/10.1073_pnas.1615837114", + "Article Title": "Catalytic oxidation of Li2S on the surface of metal sulfides for Li-S batteries", + "Authors": "Zhou, GM; Tian, HZ; Jin, Y; Tao, XY; Liu, BF; Zhang, RF; Seh, ZW; Zhuo, D; Liu, YY; Sun, J; Zhao, J; Zu, CX; Wu, DS; Zhang, QF; Cui, Y", + "Source Title": "PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA", + "Abstract": "Polysulfide binding and trapping to prevent dissolution into the electrolyte by a variety of materials has been well studied in Li-S batteries. Here we discover that some of those materials can play an important role as an activation catalyst to facilitate oxidation of the discharge product, Li2S, back to the charge product, sulfur. Combining theoretical calculations and experimental design, we select a series of metal sulfides as a model system to identify the key parameters in determining the energy barrier for Li2S oxidation and polysulfide adsorption. We demonstrate that the Li2S decomposition energy barrier is associated with the binding between isolated Li ions and the sulfur in sulfides; this is the main reason that sulfide materials can induce lower overpotential compared with commonly used carbon materials. Fundamental understanding of this reaction process is a crucial step toward rational design and screening of materials to achieve high reversible capacity and long cycle life in Li-S batteries.", + "Times Cited, WoS Core": 1097, + "Times Cited, All Databases": 1149, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000393196300042", + "Markdown": "# Catalytic oxidation of Li S on the surface of metal sulfides for Li−S batteries \n\nGuangmin Zhoua,1, Hongzhen Tianb,1, Yang Jina,1, Xinyong Taoa, Bofei Liua, Rufan Zhanga, Zhi Wei Sehc, Denys Zhuoa, Yayuan Liua, Jie Suna, Jie Zhaoa, Chenxi $z\\mathbf{u}^{\\mathsf{a}}$ , David Sichen $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{\\mathsf{a}}$ , Qianfan Zhangb,2, and Yi Cuia,d,2 \n\naDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305; bSchool of Materials Science and Engineering, Beihang University, Beijing 100191, People’s Republic of China; cInstitute of Materials Research and Engineering, Agency for Science, Technology and Research, Singapore 138634; and dStanford Institute for Materials and Energy Sciences, Stanford Linear Accelerator Center National Accelerator Laboratory, Menlo Park, CA 94025 \n\nEdited by Thomas E. Mallouk, The Pennsylvania State University, University Park, PA, and approved December 6, 2016 (received for review September 22, 2016) \n\nPolysulfide binding and trapping to prevent dissolution into the electrolyte by a variety of materials has been well studied in Li−S batteries. Here we discover that some of those materials can play an important role as an activation catalyst to facilitate oxidation of the discharge product, $\\mathsf{L i}_{2}\\mathsf{S},$ , back to the charge product, sulfur. Combining theoretical calculations and experimental design, we select a series of metal sulfides as a model system to identify the key parameters in determining the energy barrier for $\\ L i_{2}S$ oxidation and polysulfide adsorption. We demonstrate that the $\\mathbf{Li}_{2}\\mathsf{S}$ decomposition energy barrier is associated with the binding between isolated Li ions and the sulfur in sulfides; this is the main reason that sulfide materials can induce lower overpotential compared with commonly used carbon materials. Fundamental understanding of this reaction process is a crucial step toward rational design and screening of materials to achieve high reversible capacity and long cycle life in Li−S batteries. \n\nlithium−sulfur batteries | catalytic oxidation | metal sulfides | graphene | polysulfide adsorption \n\nhigh energy density, low material cost, and long cycle life has driven the development of new battery systems beyond the currently dominant lithium ion batteries (LIBs) (1). Among alternative battery chemistries, lithium−sulfur $(\\mathrm{Li}{-}\\mathrm{S})$ batteries have attracted remarkable attention due to their high theoretical energy density of 2,600 watt hours per kilogram, 5 times higher than those of state-of-the-art LIBs (2–4). In addition, sulfur, as a byproduct of the petroleum refining process, is naturally abundant, inexpensive, and environmentally friendly (5). However, the practical application of $\\mathrm{Li}{-}\\mathrm{S}$ batteries is still plagued with numerous challenges. For example, the insulating nature of sulfur and discharge products $\\mathrm{Li}_{2}\\mathrm{S}/\\mathrm{Li}_{2}\\mathrm{S}_{2}$ leads to low active material utilization. In addition, the easy dissolution of lithium polysulfides (LiPSs) into the electrolyte causes LiPSs shuttling between cathode and anode and uncontrollable deposition of sulfide species on the lithium metal anode, inducing fast capacity fading and low coulombic efficiency (2, 6). \n\nTremendous efforts have been taken to circumvent these concerns, with the nanostructuring of electrodes as one of the most effective approaches to overcoming the issues facing highcapacity electrode materials (2, 7). For example, the integration of nanostructured carbon materials with sulfur is one of the primary strategies for improving the electrical conductivity of the composites and suppression of polysulfide shuttling through physical confinement (8–14). However, it was first recognized by Zheng et al. (11) that the weak interaction between nonpolar carbon-based materials and polar $\\mathrm{LiPSs}/\\mathrm{Li}_{2}\\mathrm{S}$ species leads to weak confinement and easy detachment of LiPSs from the carbon surface, with further diffusion into the electrolyte causing capacity decay and poor rate performance. Therefore, the introduction of heteroatoms into carbonaceous materials (such as nitrogen, oxygen, boron, phosphorous, sulfur, or codoping) for the generation of polar functional groups was adopted to enhance the interaction and immobilization of LiPS species in the electrode (15). For instance, nitrogen- or sulfur-doped mesoporous carbons (16, 17), boron-doped carbons (18), oxygen- or nitrogenfunctionalized carbon nanotubes and graphenes (19, 20), aminofunctionalized reduced graphene oxides (21), and nitrogen/ sulfur-codoped graphene sponges (22) have shown great promise in trapping LiPSs due to the strong anchoring sites induced by heteroatom doping. In addition to carbon, a wide variety of anchoring materials (AM) have been introduced with polysulfide binding and trapping abilities (23–25). Patterning of carbon- and tin-doped indium oxide for sulfur species deposition, as an example, offers a clear demonstration of the polysulfide binding effect (26). Various metal oxides (27, 28), metal sulfides (29–31), metal nitrides (32), metal carbides (33), and metal organic frameworks (34) have been proposed to overcome the above-mentioned problems and improve cycling stability based on their similar polar interaction with LiPSs or Lewis acid−base interaction. \n\nStudy in the past several years has indicated that polysulfide binding and trapping is one of the most important strategies for improving $\\mathrm{Li}{-}\\mathrm{S}$ battery performance. Here we discover a catalytic effect: that electrode materials previously designed for polysulfide binding and trapping can play a critical role in catalyzing the oxidation of $\\mathrm{Li}_{2}\\mathrm{S}$ back to sulfur during battery charging. The recent mechanism study has clarified that there are both \n\n# Significance \n\nA series of metal sulfides were systematically investigated as polar hosts to reveal the key parameters correlated to the energy barriers and polysulfide adsorption capability in Li−S batteries. The investigation demonstrates that the catalyzing oxidation capability of metal sulfides is critical in reducing the energy barrier and contributing to the remarkably improved battery performance. Density functional theory simulation allows us to identify the mechanism for how binding energy and polysulfides trapping dominate the $\\mathsf{L i}_{2}\\mathsf{S}$ decomposition process and overall battery performance. The understanding can serve as a general guiding principle for the rational design and screening of advanced materials for high-energy Li−S batteries. \n\nAuthor contributions: G.Z., Y.J., Q.Z., and Y.C. designed research; G.Z., H.T., Y.J., and Q.Z. performed research; G.Z., H.T., Y.J., X.T., B.L., R.Z., Z.W.S., Y.L., J.S., J.Z., C.Z., D.S.W., Q.Z., and Y.C. contributed new reagents/analytic tools; G.Z., H.T., Y.J., X.T., B.L., R.Z., Z.W.S., D.Z., Y.L., J.S., J.Z., C.Z., D.S.W., Q.Z., and Y.C. analyzed data; and G.Z., D.Z., Q.Z., and Y.C. wrote the paper. \n\nThe authors declare no conflict of interest. \n\nThis article is a PNAS Direct Submission. \n\n$^1{\\sf G}.2$ ., H.T., and Y.J. contributed equally to this work. \n\n2To whom correspondence may be addressed. Email: yicui@stanford.edu or qianfan@ buaa.edu.cn. \n\nThis article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. \n1073/pnas.1615837114/-/DCSupplemental. \n\n![](images/2a7a1c6fdbfe667f1b5e2a6de487cd4a54c30309c3c1ce61b9b1f58b36eb551a.jpg) \nFig. 1. Schematic illustration of the sulfur conversion process and the $\\mathsf{L i}_{2}\\mathsf{S}$ catalytic oxidation on the surface of the substrate. (A) Sulfur adsorbs on the surface of carbon and polar host and transforms to $\\mathsf{L i}_{2}\\mathsf{S}_{\\mathsf{x}},$ which is strongly bonded with the polar host while weakly adsorbed by nonpolar carbon (step 1). $\\mathsf{L i}_{2}\\mathsf{S}_{\\mathsf{x}}$ transforms to $\\mathsf{L i}_{2}\\mathsf{S}$ and is mainly captured by the polar host while isolated islands are deposited on the carbon surface (step 2). (B) The substrate catalyzes $\\mathsf{L i}_{2}\\mathsf{S}$ decomposition and favors the oxidization of $\\mathsf{L i}_{2}\\mathsf{S}$ to $\\mathsf{L i}_{2}\\mathsf{S}_{\\mathsf{x}}$ near the substrate surface, and finally to sulfur (steps 3 and 4 in A). \n\nelectrochemical and chemical pathways during battery cycling (35). That is, polysulfides can be electrochemically deposited to form $\\mathrm{Li}_{2}\\mathrm{S}$ , or chemically disproportionated to form $\\mathrm{Li}_{2}\\mathrm S$ , suggesting that the catalytic oxidation of $\\mathrm{Li}_{2}\\mathrm S$ is of crucial importance in achieving high reversible capacity and long cycling life. Typically, the conversion reaction process in $\\operatorname{Li}{-\\mathsf{S}}$ batteries can be divided into four main steps, as illustrated in Fig. 1. Most of the research work has emphasized the physical/chemical adsorption of sulfur species on the surface of carbon and polar hosts (strong affinity to $\\mathrm{LiPSs}/\\mathrm{Li}_{2}\\mathrm{S}$ , step 1, Fig. 1A). For insulating materials with poor electronic conductivity, the polysulfide redox mechanism is hampered. Our group has recently demonstrated the importance of balancing sulfide species adsorption and diffusion on nonconductive metal oxides (27) with better surface diffusion, leading to higher $\\mathrm{Li}_{2}\\mathrm{S}$ deposition efficiency (step 2, Fig. 1A). In the reverse reaction process, catalysis of the decomposition of $\\mathrm{Li}_{2}\\mathrm{S}$ and oxidization of $\\mathrm{Li}_{2}\\mathrm S$ to $\\mathrm{Li}_{2}\\mathrm{S}_{\\mathrm{x}}$ and finally to sulfur (Fig. $1B$ and steps 3 and 4 in Fig. 1A) near the surface of the substrate are crucial steps to realizing high capacity and Columbic efficiency, yet have been relatively neglected in the $\\mathrm{Li}{-}\\mathrm{S}$ chemistry. In this respect, a systematic consideration of the substrates that are capable of catalyzing $\\mathrm{Li}_{2}\\mathrm{S}$ decomposition is critical to the development of advanced Li−S batteries. \n\nHerein, a series of metal sulfides have been systematically investigated as model systems to identify the key parameters in determining the energy barrier for $\\mathrm{Li}_{2}\\mathrm S$ oxidation and polysulfide adsorption capability in $\\mathrm{Li}{-}\\mathsf{S}$ batteries. The experimental results show that $\\mathrm{V}\\bar{\\mathrm{S}_{2}}.$ , $\\mathrm{TiS}_{2}.$ -, and $\\mathrm{CoS}_{2}$ -based cathodes exhibit higher binding energy and lower diffusion and activation energy barriers, resulting in improved capacity and cycling stability. By combining first-principles calculations, we demonstrate that the strongly coupled interactions between LiPS species and metal sulfides and the energy barrier of $\\mathrm{Li}_{2}\\mathrm S$ decomposition is correlated with the binding between isolated Li ions and the sulfur in sulfides. This strong interaction is favorable for lowering the overpotential and improving energy efficiency compared with weakly bonded carbon materials. These findings provide insight into a fundamental understanding of sulfur conversion chemistry and guidance for the future design and screening of new materials with $\\mathrm{Li}_{2}\\mathrm S$ catalytic activity toward achieving highperformance $\\operatorname{Li}{-\\mathsf{S}}$ batteries. \n\n# Results and Discussion \n\nInitial Activation Energy Barrier on Various Metal Sulfides. To understand the role of metal sulfides in catalytic decomposition of $\\mathrm{Li}_{2}\\mathrm{S}$ , we systematically investigated the effect of six kinds of metal sulfides, including $\\mathrm{VS}_{2}$ , $\\mathrm{CoS}_{2}$ , $\\mathrm{TiS}_{2}$ , FeS, $\\mathrm{SnS}_{2}$ , and $\\mathrm{Ni}_{2}\\mathrm{S}_{3}$ , on tuning the decomposition energy barrier. According to our simulation of electronic band structures ( $S I$ Appendix, Fig. S1), $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , FeS, and $\\mathrm{CoS}_{2}$ are metallic materials and $\\mathrm{VS}_{2}$ and $\\mathrm{TiS}_{2}$ are semimetallic, which means that they are all materials with good electrical conductivities, whereas $\\mathrm{SnS}_{2}$ is a semiconductor with a band gap of $2.2\\mathrm{eV}$ . Carbon materials [a graphene/carbon nanotube hybrid $(\\mathbf{G}/\\mathbf{CNT})$ (36) was used in this work] were chosen for comparison due to their common use as conductive coating materials in sulfur- or $\\mathrm{Li}_{2}\\mathrm S$ -based cathodes. The cathode consists of a commercial $\\mathrm{Li}_{2}\\mathrm S$ cathode material mixed uniformly with various metal sulfides, carbon black, and polyvinylidene fluoride binder. The detailed synthesis procedures are described in $S I$ Appendix, Materials and Methods. Coin cells were assembled with lithium metal as anode and reference electrode. $\\mathrm{Li}_{2}\\mathrm S$ suffers from a low electrical conductivity, high charge transfer resistance, and low lithium ion diffusivity, which leads to a high overpotential at the initial charging to overcome the energy barrier. The initial charge voltage profiles from open-circuit voltage to $4.0\\mathrm{V}$ to delithiate $\\mathrm{Li}_{2}\\mathrm S$ is shown in $S I$ Appendix, Fig. S2. The red rectangular area was magnified in Fig. 2A to clearly show the activation barrier. The $\\mathrm{G}/\\bar{\\mathrm{CNT-Li_{2}S}}$ cathode without the addition of metal sulfide exhibits a high potential barrier at about $3.41~\\mathrm{V}$ in the initial charging process, indicating a sluggish activation process with high charge transfer resistance. The $\\bar{\\bf S}\\mathrm{nS}_{2}\\mathrm{-}\\mathrm{Li}_{2}\\mathrm{S}$ cathode shows a clear voltage jump with a potential barrier of $3.53\\mathrm{~V~}$ during the activation process due to the semiconducting nature of $\\mathrm{SnS}_{2}$ . The charge voltage plateaus after the short voltage jump represent the phase conversion reaction from $\\mathrm{Li}_{2}\\mathrm S$ to low-order LiPSs, high-order LiPSs, and sulfur. A similar charging phenomenon is observed for ${\\bf N i}_{3}{\\bf S}_{2}\\mathrm{-}{\\bf L i}_{2}{\\bf S}$ and ${\\mathrm{FeS}}{\\mathrm{-Li}}_{2}{\\mathrm{S}}$ electrodes with high potential barriers of 3.47 and $3.25\\mathrm{~V~}$ even though both are metallic. However, the addition of $\\mathrm{CoS}_{2}$ , $\\mathrm{VS}_{2}$ , and $\\mathrm{TiS}_{2}$ significantly reduces the height of the potential barrier to 3.01, 2.91, and $\\dot{2}.88\\mathrm{~V~}$ , respectively (Fig. 2A). These results are consistent with the cyclic voltammetry (CV) measurements (SI Appendix, Fig. S3). The lower potential barrier and longer voltage plateau of the $\\mathrm{CoS}_{2^{-}}$ , $\\mathrm{VS}_{2^{-}}$ , and $\\mathrm{TiS}_{2}$ -based electrodes compared with other metal sulfides indicate improved conductivity and reduced charge transfer resistance. \n\nTo attain an in-depth understanding of the function of these metal sulfides, we use the climbing-image nudged elastic band (CI-NEB) method (37) to calculate the barrier for $\\mathrm{Li}_{2}\\mathrm{S}$ decomposition to evaluate the delithiation reaction kinetics on the surface of different metal sulfides. Here, we consider the decomposition process from an intact $\\mathrm{Li}_{2}\\mathrm S$ molecule into an LiS cluster and a single Li ion $\\mathrm{(Li_{2}S{\\to}L i S+L i^{+}+e^{-})}$ . The main evolution is composed of the Li ion moving far away from the S atom in the $\\mathrm{Li}_{2}\\mathrm S$ molecule, which is accompanied by breaking of the $\\mathrm{Li}{-}\\mathrm{S}$ bond. The energy profiles for the decomposition processes on different sulfides are shown in Fig. $2B$ , and the barrier heights are listed in $S I$ Appendix, Table S1. The $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ decomposition barrier is as high as $1.03\\ \\mathrm{eV}$ , much larger than the other five cases, and is consistent with the large initial voltage barrier for $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ -added $\\mathrm{Li}_{2}\\mathrm{S}$ cathode. The barriers for FeS, $\\mathrm{CoS}_{2}$ , $\\mathrm{VS}_{2}$ , and $\\mathrm{Ti}\\mathsf{S}_{2}$ are 0.63, 0.56, 0.31, and $0.30~\\mathrm{eV}$ , respectively, and qualitatively agree with the voltage magnitudes measured experimentally. For $\\mathrm{SnS}_{2}$ , the calculated barrier for decomposition is as low as $0.32\\mathrm{eV}$ , but experimentally exhibits a very large initial charge potential. This can be probably attributed to the insulating nature of $\\mathrm{SnS}_{2}$ and the electron−ion recombination process, which is the rate-determining step for the delithiation process, but not the Li decomposition process. Fig. $2\\ C{-}H$ illustrates the decomposition pathway for one Li ion departing from the LiS cluster on the surface of six kinds of sulfides. It can be clearly seen that the decomposition process is associated with the binding between the isolated Li ion and the sulfur in sulfides. This is the dominant reason that the sulfide anchor can induce a lower decomposition barrier compared with carbon materials. For graphene, the chemical interaction between the Li ion and carbon is much weaker, and, therefore, the decomposition process should have a very large activation energy barrier (Fig. 2I, 1.81 eV according to our simulation). \n\n![](images/52e6a07772b32b1f292ccd19b09d584bac0a3de73f3342f584cc1d21db93836f.jpg) \nFig. 2. Electrochemical activation and $\\mathsf{L i}_{2}\\mathsf{S}$ decomposition mechanism on the surface of various metal sulfides and graphene. (A) First cycle charge voltage profiles of $\\mathsf{N i}_{3}\\mathsf{S}_{2}\\mathsf{-L i}_{2}\\mathsf{S}_{}$ , $S_{n S_{2}-\\mathsf{L i}_{2}S_{4}}$ , ${\\mathsf{F e S-L i}}_{2}\\mathsf{S},$ , ${\\mathsf{C o S}}_{2}{\\mathsf{-L i}}_{2}{\\mathsf{S}}_{}$ , ${\\mathsf{V S}}_{2}{\\mathrm{-Li}}_{2}{\\mathsf{S}},$ , $\\bar{\\mathsf{T i S}}_{2}-$ ${\\mathsf{L i}}_{2}{\\mathsf{S}},$ and $\\mathsf{G}/\\mathsf{C N T}-\\mathsf{L i}_{2}\\mathsf{S}$ electrodes. (B) Energy profiles for the decomposition of $\\mathsf{L i}_{2}\\mathsf{S}$ cluster on $N i_{3}S_{2},$ $\\mathsf{S n S}_{2},$ FeS, $\\mathsf{C o S}_{2}$ , $\\mathsf{V S}_{2},$ $\\bar{\\mathsf{T i S}}_{2},$ and graphene. Top view schematic representations of the corresponding decomposition pathways for (C) $\\mathsf{N i}_{3}\\mathsf{S}_{2},\\left(D\\right)\\mathsf{S n S}_{2},$ (E) FeS, (F) $\\mathsf{C o S}_{2}$ , (G) $\\mathsf{V S}_{2},$ , $(H)$ $\\bar{\\mathsf{T i S}}_{2},$ and $(1)$ graphene. Here, green, yellow, gray, purple, brown, blue, red, cyan, and beige balls symbolize lithium, sulfur, nickel, tin, iron, cobalt, vanadium, titanium, and carbon atoms, respectively. $\\mathsf{S}_{\\mathsf{m}}$ represents the sulfur atom in the $\\mathsf{L i}_{2}\\mathsf{S}$ cluster. \n\nInteraction Between Polysulfides and Various Metal Sulfides. The discovery that $\\mathrm{Li}_{2}\\mathrm S$ decomposition is related to Li ion binding with the host material propels us to understand the binding between metal sulfides and LiPSs. Therefore, polysulfide adsorption tests and X-ray photoelectron spectroscopy (XPS) studies were carried out to provide detailed information on the interaction between polysulfides and various metal sulfides. To probe the polysulfide adsorptivity, $0.005\\mathrm{~M~Li_{2}S_{6}~}$ was prepared by chemically reacting sulfur with $\\mathrm{Li}_{2}\\mathrm S$ in 1,3-dioxolane/1,2- dimethoxyethane solution (DOL/DME, 1:1 by volume). Different masses of metal sulfides and $\\mathbf{G}/\\mathbf{CNT}$ with equivalent total surface area were added into the above solution for comparison. Unsurprisingly, after prolonged contact with $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ , nonpolar G/CNT has no observable effect on adsorbing polysulfides as the color of the solution remains the same as the control sample shown in Fig. 3A, indicating weak physical adsorption. FeS and $\\mathrm{SnS}_{2}$ demonstrate higher adsorption capability of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ compared with $\\mathbf{\\Pi}_{\\mathbf{G/CNT}}$ , whereas $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ exhibits lower adsorption capability as demonstrated by the lack of any significant color change. In contrast, the originally yellow-colored polysulfide solution becomes colorless after the addition of $\\mathrm{TiS}_{2}$ or $\\mathrm{VS}_{2}$ , and becomes much lighter in color for $\\mathrm{CoS}_{2}$ , suggesting a strong interaction between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and these sulfide hosts. \n\nXPS analysis of the samples retrieved after the adsorption test provides additional evidence for the interaction between LiPSs and metal sulfides or $\\mathbf{\\Pi}_{\\mathbf{G/CNT}}$ . Here we take $\\mathrm{VS}_{2}$ , $\\mathrm{CoS}_{2}$ , and $\\mathbf{G}/\\mathbf{CNT}$ as examples. The $\\mathtt{V2p}$ spectra of $\\mathrm{VS}_{2}$ and ${\\mathrm{VS}}_{2}{\\mathrm{-Li}}_{2}{\\mathrm{S}}_{6}$ are shown in $S I$ Appendix, Fig. S4A, in which two peaks located at 517.3 and ${524.8~\\mathrm{eV}}$ with an energy separation of $7.5~\\mathrm{eV}$ are attributed to the V $2\\mathsf{p}_{3/2}$ and V $2\\mathsf{p}_{1/2}$ spin-orbit levels of $\\mathrm{VS}_{2}$ (38). Upon contact with $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ , both peaks shift about $0.8\\mathrm{eV}$ to $1.0\\mathrm{eV}$ toward lower binding energy. The Li 1s spectrum of pristine $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ exhibits an $\\operatorname{Li}{-\\mathsf{S}}$ peak at around ${56.3\\mathrm{e}\\bar{\\mathrm{V}}}$ $\\cdot_{S I}$ Appendix, Fig. S4B), which shifts to $5\\bar{6}.1\\mathrm{eV}$ after contact with $\\mathrm{\\DeltaVS}_{2}$ . Both of the peak shifts in $\\textsf{V}2\\mathsf{p}$ and Li 1s suggest the formation of chemical bonds between $\\mathrm{VS}_{2}$ and $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ . A similar shift trend was observed in the $\\mathrm{CoS}_{2}\\mathrm{-Li}_{2}\\mathrm{S}_{6}$ system (SI Appendix, Fig. $\\mathrm{~S4~}C$ and $D$ ). In contrast, almost no signal can be detected in the Li 1s spectrum of the $\\mathrm{G}/\\mathrm{CNT-Li_{2}S_{6}}$ sample, confirming the poor adsorption capability of nonpolar G/CNT with the polar $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ molecule ( $S I$ Appendix, Fig. S5). \n\n![](images/d0c94afa6f241dfbe3629d1503f30109d1931baf995e4331d439e9f05b48fd11.jpg) \nFig. 3. Lithium polysulfide $(\\mathsf{L i}_{2}\\mathsf{S}_{6})$ adsorption by carbon and metal sulfides and corresponding simulation of $\\mathsf{L i}_{2}\\mathsf{S}_{6}$ adsorbed on the surface of metal sulfides. (A) Digital image of the $\\mathsf{L i}_{2}\\mathsf{S}_{6}$ (0.005 M) captured by carbon and metal sulfides in DOL/DME solution. Atomic conformations and binding energy for $\\mathsf{L i}_{2}\\mathsf{S}_{6}$ species adsorption on (B) $N i_{3}S_{2}$ , (C ) $\\mathsf{S n S}_{2}$ , $(D)$ FeS, (E ) $\\mathsf{C o S}_{2}$ , (F ) ${\\mathsf{V S}}_{2},$ and (G) $\\bar{\\mathsf{T i S}}_{2}$ . Here, green, yellow, gray, purple, brown, blue, red, and cyan balls represent lithium, sulfur, nickel, tin, iron, cobalt, vanadium, and titanium atoms, respectively. \n\nTo study the interaction between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and sulfide materials, first-principle simulations are applied. Fig. 3 $B{-}G$ shows the adsorption conformations for $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ on various sulfides. It can be clearly seen that the chemical interaction is dominated by the bond formed between the Li ion in $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and the sulfur ion in the sulfide, congruent with the previous discussion and the adsorption mechanism described in our previous work (39). The binding energy, $\\mathrm{E_{b}}$ , is computed to measure the binding strength between the $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ species and the AM; it is defined as the energy difference between the ${\\mathrm{Li}}_{2}{\\mathrm{S}}_{6}{\\mathrm{-}}{\\mathrm{AM}}$ adsorbed system $\\left(\\mathrm{E}_{\\mathrm{Li2S6+AM}}\\right)$ and the summation of pure $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ $\\mathrm{(E_{Li2S6})}$ and pure AM $\\mathbf{(E_{AM})}$ , which can be expressed as $\\mathrm{E_{b}=E_{L i2S6}+E_{A M}-E_{L i2S6+A M}}$ (positive binding energy indicates the binding interaction is favored and the larger the value, the stronger the anchoring effect). According to the simulation, the binding strengths between $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , $\\mathrm{SnS}_{2}$ , FeS, $\\mathrm{CoS}_{2}$ , $\\mathrm{VS}_{2}$ , and $\\mathrm{TiS}_{2}$ are 0.72, 0.80, 0.87, 1.01, 1.04, and $1.02\\ \\mathrm{eV}$ , respectively. The calculated magnitudes of $\\mathrm{E_{b}}$ are in good agreement with our experimentally measured $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ adsorption capability and also indicate that stronger interactions can induce a better anchoring effect. Furthermore, all of the sulfide anchors in our study can induce greater binding strength than graphene $\\mathrm{(0.67eV)}$ , which exhibits weak chemical binding to $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ as adsorption is dominated by physical van der Waals interaction $S I$ Appendix, Fig. S6); this explains why these sulfides can mitigate polysulfide dissolution and suppress shuttle effect, leading to better performance than commonly adopted $\\displaystyle\\mathbf{sp}^{2}$ carbon materials in Li−S batteries. \n\nFabrication of Sulfur-Infiltrated Metal Sulfides@G/CNT Electrodes. To better disperse the metal sulfides $(\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}})$ in the sulfur cathode and reduce the weight of the whole cathode, a $\\mathbf{G}/\\mathbf{CNT}$ hybrid was prepared and served as the substrate to support $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ particles (SI Appendix, Fig. S7). The G/CNT and various commercial $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ particles were mixed, ground, and ball-milled for $^\\textrm{\\scriptsize1h}$ to disperse $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ on the surface of the $\\mathbf{G}/\\mathbf{CNT}$ and obtain $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/$ CNT hybrids (SI Appendix, Fig. S8). Sulfur was then infused through a melt diffusion method into the $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ hybrids by heating at $155~^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{~h~}}$ to form the $\\mathbf{S}{-}\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ composites. Here sulfur-infiltrated $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ instead of $\\mathrm{Li}_{2}\\mathrm{S}$ -based composites were used as cathodes because the cost of sulfur is much lower than that of $\\mathrm{Li}_{2}\\mathrm{S}$ , and sulfur is easier to handle compared with $\\mathrm{Li}_{2}\\mathrm{S}$ , as $\\mathrm{Li}_{2}\\mathrm S$ is sensitive to water and oxygen. The intrinsically conductive $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ in the electrode is intended to serve several important functions, including as a polar feature that can bind strongly to LiPSs, spatially localize the deposition of the sulfide species, and promote surface redox chemistry (SI Appendix, Fig. S8). The as-prepared $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/$ CNT composites were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), as shown in $S I$ Appendix, Fig. S9. These composites exhibit a cloud-like, rough surface with various ${\\bf\\cal M}_{\\mathrm{x}}\\S_{\\mathrm{y}}$ particles well decorated inside or on the surface of the $\\mathbf{G}/\\mathbf{CNT}$ (SI Appendix, Fig. S9 $\\scriptstyle|A-F)$ . The microstructure was further investigated by TEM. The $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ particles, with particle size in the range of $200~\\mathrm{nm}$ to $400\\ \\mathrm{nm}$ , are homogeneously distributed in the $\\mathbf{G}/\\mathbf{CNT}$ hybrid without obvious agglomeration (SI Appendix, Fig. $_{{\\cal S}9}\\cal{G}\\mathrm{-}{\\cal L}$ ). It can be noted that the $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ particles are firmly adhered to the $\\mathbf{G}/\\mathbf{CNT}$ even after ultrasonic dispersion for TEM characterization, indicating good contact between them. The high-resolution TEM images show lattice spacings of 0.573, 0.568, 0.248, 0.298, 0.278, and $0.408\\mathrm{nm}$ , which are ascribed to the (001), (001), (210), (110), (101), and (101) planes of $\\mathrm{VS}_{2}$ , $\\mathrm{TiS}_{2}$ , $\\mathrm{CoS}_{2}$ , FeS, $\\mathrm{SnS}_{2}$ , and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , respectively $S I$ Appendix, Fig. $S9\\ M{-}R$ ). After the infusion of sulfur, the typical structure of the corresponding $\\mathbf{S}\\mathbf{-}\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{\\alpha}$ $\\mathbf{G}/\\mathbf{CNT}$ composites was characterized by SEM (energy-dispersive X-ray spectroscopy elemental analysis and mapping) and X-ray diffraction, as shown in $S I$ Appendix, Figs. S10 and S11. The microstructure of the $\\mathbf{S}{-}\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ composite is similar to the $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ composite in which the graphene and CNTs can still be sparsely observed. The surface of the $\\mathbf{S}{-}\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ composite is smoother after sulfur impregnation, suggesting a homogeneous sulfur coating on the surface of the $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ hybrids. \n\nLithium Ion Diffusion Mechanism. The lithium ion diffusion coefficient can serve as a good descriptor to verify whether $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ can propel the polysulfide redox reaction process, as fast lithium ion diffusion facilitates the sulfur transformation chemistry at the $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ interface. CV was used to investigate electrode kinetics with respect to the lithium ion diffusion coefficient (27). Taking the $\\mathbf{S}\\mathrm{-}\\bar{\\mathbf{V}}\\bar{\\mathbf{S}}_{2}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathrm{T}$ electrode as a representative example, Fig. 4A shows the CV curves of the electrode measured under different scanning rates ranging from $0.2\\ \\mathrm{mV}{\\cdot}\\mathrm{s}^{-1}$ to $0.5\\ \\mathrm{mV\\cdots^{-1}}$ between $1.5\\mathrm{V}$ and $2.8\\mathrm{V}$ (vs. $\\mathrm{\\bar{L1}/L i^{+}}$ ). At all scan rates, there are two cathodic peaks at around $2.30\\mathrm{~V~}(\\mathrm{I_{C1}})$ and $1.95\\mathrm{~V~}$ $\\left(\\operatorname{I}_{\\mathbf{C}2}\\right)$ , corresponding to the reduction of elemental sulfur $\\mathrm{(S_{8})}$ to longchain lithium polysulfides and the subsequent formation of short-chain $\\mathrm{Li}_{2}\\bar{\\mathrm{S}}_{2}/\\bar{\\mathrm{Li}}_{2}\\mathrm{S}$ (12). The anodic peak at around $2.50\\mathrm{V}$ in the anodic sweep results from the transition of $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ to polysulfides and elemental sulfur $\\mathrm{(I_{A})}$ . The cathodic and anodic current peaks $(\\mathrm{I_{C1}},\\mathrm{I_{C2}},\\mathrm{I_{A}})$ of all of the $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ -containing electrodes have a linear relationship with the square root of scanning rates (Fig. $4B/-D)$ ), indicative of the diffusion-limited process. Therefore, the classical Randles−Sevcik equation can be applied to describe the lithium diffusion process (27): $\\mathrm{{I_{p}}}=(2.69\\times^{10^{5}})$ $n^{1.5}S D_{\\mathrm{Li^{+}}}{}^{0.5}C_{\\mathrm{Li}}\\nu^{0.5}$ , where $\\mathrm{I_{P}}$ is the peak current, $n$ is the charge transfer number, $s$ is the geometric area of the active electrode, $D_{\\mathrm{Li+}}$ is the lithium ion diffusion coefficient, $C_{\\mathrm{Li}}$ is the concentration of lithium ions in the cathode, and $\\nu$ is the potential scan rate. The slope of the curve $(\\mathrm{I_{p}}/\\nu^{0.5})$ represents the lithium ion diffusion rate as $n,S$ , and $C_{\\mathrm{Li}}$ are unchanged. It can be clearly seen that the $\\operatorname{S}\\textcircled{a}\\operatorname{G}/\\operatorname{CNT}$ electrode exhibits the lowest lithium ion diffusivity, which mainly arises from the weak LiPSs adsorption and $\\mathrm{Li}_{2}\\mathrm{\\dot{S}}$ catalyzing conversion capability, induced high LiPSs viscosity in the electrolyte, or deposition of a thick insulating layer on the electrode, as discussed previously. In contrast, the $\\mathrm{S}{-}\\mathrm{VS}_{2}@\\mathrm{G}/\\mathrm{CNT}$ , $\\mathrm{S}{-}\\mathrm{CoS}_{2}@\\mathrm{G}/\\mathrm{CNT}$ , and $\\mathbf{S}\\mathbf{-}\\mathbf{\\Tilde{IiS}}_{2}\\mathbf{\\textcircled{\\omega}}\\mathbf{G/CNT}$ electrodes demonstrate much faster diffusion compared with the $\\mathbf{S}\\textcircled{a}\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ electrode and better reaction kinetics than the $\\mathrm{S}{-}\\mathrm{Ni}_{3}\\mathrm{S}_{2}@$ G/CNT, $\\mathrm{S}{-}\\mathrm{SnS}_{2}@\\mathrm{G}/\\mathrm{CNT}$ , and $\\mathbf{S}{-}\\mathbf{FeS}\\textcircled{a}\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ electrodes, indicating that the introduction of polar $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ hosts enables highly efficient catalyzing conversion of sulfur redox. \n\n![](images/d95a83bd4e315bd9fcd665b3977e75cbded456ee03b0380722c43706bfe2b617.jpg) \nFig. 4. Lithium ion diffusion properties on the surface of graphene and various metal sulfides with mechanism analysis. (A) CV curves of the ${\\mathsf{S}}{-}{\\mathsf{V S}}_{2}@{\\mathsf{G}}/{\\mathsf{C N T}}$ electrode at various scan rates. Plots of CV peak current for the (B) first cathodic reduction process $(\\mathsf{I}_{\\mathsf{C}1}\\colon\\mathsf{S}_{8}\\to\\mathsf{L}\\mathsf{i}_{2}\\mathsf{S}_{\\mathsf{x}})$ , (C) second cathodic reduction process (I $_{\\mathsf{C}2}\\colon\\mathsf{L i}_{2}\\mathsf{S}_{\\mathsf{x}}{\\rightarrow}\\mathsf{L i}_{2}\\mathsf{S}_{2}/\\mathsf{L i}_{2}\\mathsf{S})$ , and $(D)$ anodic oxidation process $(\\mathsf{I}_{\\mathsf{A}}\\colon\\mathsf{L}\\mathsf{i}_{2}\\mathsf{S}_{2}/\\mathsf{L}\\mathsf{i}_{2}\\mathsf{S}\\to\\mathsf{S}_{8})$ versus the square root of the scan rates. (E) Energy profiles for diffusion processes of Li ion on $N i_{3}S_{2}$ , $\\mathsf{S n S}_{2}$ , FeS, ${\\mathsf{C o S}}_{2}$ , $\\mathsf{V S}_{2}$ , $\\mathsf{T i S}_{2}$ and graphene. Top view schematic representations of corresponding diffusion pathways for (F) graphene, (G $)\\mathsf{N i}_{3}\\mathsf{S}_{2},(H)\\mathsf{S n S}_{2},($ $(1)$ FeS, $\\begin{array}{r}{\\left(J\\right)\\mathsf{C o S}_{2},\\left(K\\right)\\mathsf{V o}_{2},}\\end{array}$ and (L) $\\bar{\\mathsf{T i S}}_{2}$ . Here, green, yellow, gray, purple, brown, blue, red, cyan, and beige balls represent lithium, sulfur, nickel, tin, iron, cobalt, vanadium, titanium, and carbon atoms, respectively. \n\nTo validate the above-mentioned points, we simulate the diffusion barriers for Li ion on graphene and six kinds of sulfides using CI-NEB calculations (37). The energy profiles along the diffusion coordinate for these AM are shown in Fig. $4E$ . The magnitudes of the barriers lie in the region of $0.12\\mathrm{eV}$ to $0.26\\mathrm{eV}$ (listed in $S I$ Appendix, Table S2), all of which are smaller than the diffusion barrier on graphene, which is $0.30\\mathrm{eV}$ according to our simulations and is consistent with the experimental results showing that Li ions diffuse faster on sulfide materials. The diffusion barriers for $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , $\\mathrm{SnS}_{2}$ , and FeS are $\\mathrm{\\sim}0.1\\ \\mathrm{eV}$ larger than those for $\\mathrm{CoS}_{2}$ , $\\mathrm{VS}_{2}$ , and $\\mathrm{TiS}_{2}$ which is also in qualitative agreement with our experimental observations. This finding likely explains why $\\mathrm{CoS}_{2}$ , $\\mathrm{VS}_{2}$ , and $\\mathrm{TiS}_{2}$ added electrodes have better reaction kinetics compared with the other three; a lower barrier can lead to an increase in the diffusion rate according to the exponential rule, and faster diffusion on the surface of the AM can promote the reaction between lithium and sulfur. In Fig. 4 $_{F-L}$ , the diffusion pathways on the surface of graphene and sulfides are illustrated. For $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , FeS, $\\mathrm{CoS}_{2}$ , and graphene, the diffusion follows the arc curves from one stable point to the other, with the saddle point located in the middle of the pathway. In contrast, for hexagonal $\\mathrm{SnS}_{2}$ , $\\mathrm{VS}_{2}$ , and $\\mathrm{TiS}_{2}$ , the diffusion follows a polyline, from one stable hollow site to the metastable hollow site and then to another stable hollow site. Therefore, the diffusions in these three kinds of sulfides have double-peak profiles. \n\nElectrochemical Performance of the $\\mathbf{S}\\mathbf{-}\\mathbf{M}_{\\mathbf{x}}\\mathbf{S}_{\\mathbf{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{M}\\boldsymbol{\\mathsf{T}}$ Electrodes. Fig. 5A and $S I$ Appendix, Fig. S12 show the galvanostatic discharge/ charge voltage profiles of $\\mathbf{S}{-}\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ and $\\mathbf{S}\\textcircled{a}\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ electrodes at various current rates from $0.2\\mathrm{C}$ ( $1{\\mathrm{C}}=1675{\\mathrm{~mA}}{\\cdot}{\\mathrm{g}}^{-1})$ ) to $4\\mathrm{C}$ in the potential range of $1.5\\mathrm{V}$ to $2.8\\mathrm{V}$ . The $\\mathrm{S}{-}\\mathrm{VS}_{2}@\\mathrm{G}/\\mathrm{CNT}$ cathode exhibits excellent rate performance consisting of two discharge plateaus even at a very high current rate of $4\\mathrm{{\\bar{C}}}$ (Fig. 5A), which can be ascribed to the reduction of ${\\bf S}_{8}$ to high-order lithium polysulfides at $2.3{\\mathrm{~V}}$ to $2.4\\mathrm{V}$ and the transformation to low-order $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ at $1.9\\mathrm{V}$ to $2.1\\mathrm{V}$ (2). In the reverse reaction, two plateaus in the charge curve represent the backward reaction from lithium sulfides to polysulfides and finally to sulfur (12). These results are in good agreement with the reduction and oxidation processes established in the CV curves (Fig. 4A). Based on the discharge curves at $0.2~\\mathrm{C}_{:}$ , the sulfur electrodes containing $\\mathbf{G}/\\mathbf{CNT}$ , $\\mathrm{SnS}_{2}$ , $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , FeS, $\\mathrm{TiS}_{2}$ , $\\mathrm{CoS}_{2}$ , and $\\mathrm{VS}_{2}$ exhibit average discharge capacities of 685, 836, 845, 900, 1,008, 1,033, and $1{\\cdot}093\\ \\mathrm{mA}{\\cdot}\\mathrm{h}{\\cdot}\\mathrm{g}^{-1}$ , respectively (Fig. 5B). The higher discharge capacities of $\\mathrm{TiS}_{2}.$ , $\\mathrm{Co}\\mathrm{S}_{2}\\mathrm{-}$ , and $\\mathrm{VS}_{2}$ - containing cathodes indicate the high utilization of sulfur due to the strong interaction between LiPSs and these sulfides. There are distinct differences in the voltage hysteresis and length of the voltage plateaus, which are related to the redox reaction kinetics and the reversibility of the system (Fig. $5B$ and $S I$ Appendix, Fig. S12). \n\nThe $\\mathrm{TiS}_{2}$ -, $\\mathrm{CoS}_{2}\\mathrm{-}$ , and $\\mathrm{VS}_{2}$ -containing cathodes display flat and stable plateaus with relatively small polarizations of 177, 177, and $172\\mathrm{mV}$ at ${\\bar{0}}.2~\\mathrm{C},$ , much lower than ${\\mathrm{~G}}/{\\mathrm{CNT}}.$ -, $\\mathrm{SnS}_{2}.$ -, $\\mathrm{Ni}_{3}\\mathrm{S}_{2}\\mathrm{-}$ , and FeS-containing cathodes with values of 272, 244, 259, and $217~\\mathrm{mV}$ . This finding suggests a kinetically efficient reaction process with a smaller energy barrier promoted by the $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ $\\mathrm{\\Delta[_{X}S_{y}\\left(T i S_{2},C o\\right)}$ $\\mathrm{CoS}_{2}$ , and $\\mathrm{VS}_{2}$ ) catalyzing process discussed previously. A similar trend was confirmed when the cells were subjected to higher rates of $0.5\\mathrm{C}$ and 1 C (SI Appendix, Figs. S12 and S13). The charge/discharge plateaus obviously shift or even disappear for ${\\mathrm{~G/CNT}}.$ , $\\mathrm{SnS}_{2}-$ , and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ -containing electrodes at high current rates, indicating high polarization and slow redox reaction kinetics with inferior reversibility, which is consistent with the decomposition energy barrier analysis (Fig. 2). \n\n![](images/8d0cbb9dda0dee03afc1c4c640688f786837b05d71259c9ab85ec2befe9978c7.jpg) \nFig. 5. Electrochemical performance of the $\\mathsf{S}{-}\\mathsf{M}_{\\times}\\mathsf{S}_{\\mathsf{y}}@\\mathsf{G}/\\mathsf{C N T}$ composite electrodes. $\\left(A\\right)$ Galvanostatic charge/discharge voltage profiles of the ${\\mathsf{S}}{-}{\\mathsf{V}}{\\mathsf{S}}_{2}@{\\mathsf{G}}/$ CNT composite electrodes at different current densities within a potential window of $1.5\\:\\mathsf{V}$ to ${\\sim}2.8\\ V$ vs. $\\mathsf{L i}^{+}/\\mathsf{L i}^{0}$ . (B) Comparison of the specific capacity and polarization voltage between the charge and discharge plateaus at $\\textstyle0.2\\textsf{C}$ for different composite electrodes. (C) Cycling performance and coulombic efficiency of the different composite electrodes at $\\textstyle0.5{\\textsf{C}}$ for 300 cycles. \n\nLong-term cycling stability with high capacity retention is crucial for the practical application of Li−S batteries. Fig. $5C$ shows the cycling performance of the $\\operatorname{S}@\\operatorname{G}/\\operatorname{CNT}$ and $\\mathbf{S}{\\mathbf{-M}}_{\\mathrm{x}}\\mathbf{\\bar{S_{y}}}@\\mathbf{G}/$ CNT electrodes at $0.5\\mathrm{C}$ for 300 cycles after the rate capability test. The $\\mathrm{S}{-}\\mathrm{VS}_{2}@\\mathrm{G}/\\mathrm{CNT}$ electrode delivers a high initial reversible capacity of $\\mathrm{\\bar{8}30m A\\cdot h{\\cdot}g^{-1}}$ , and the capacity remains at $701\\mathrm{mA}{\\cdot}\\mathrm{h}{\\cdot}\\mathrm{g}^{-1}$ after 300 cycles with stabilized coulombic efficiency above $99.5\\%$ , corresponding to a capacity retention of $84.5\\%$ and slow capacity decay rate of $0.052\\%$ per cycle. The high LiPSs adsorbing capability and good catalytic conversion of sulfur species alleviate the shuttle effect and improve the coulombic efficiency. The $\\mathrm{S}{-}\\mathrm{CoS}_{2}@\\mathrm{G}/\\mathrm{CNT}$ and $\\mathbf{S}{-}\\mathrm{TiS}_{2}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ electrodes also retain reversible capacities of 581 and $546\\ \\mathrm{mA\\cdoth{\\cdotg}^{-1}}$ , respectively, accounting for $85.3\\%$ and $78.2\\%$ of their initial capacities, with low capacity fading rates of $0.049\\%$ and $0.073\\%$ per cycle. Even at a high charge/discharge rate of $2\\mathrm{~C~}$ , the $\\mathrm{VS}_{2}.$ -, $\\mathrm{Co}{\\mathbf{S}}_{2}.$ -, and $\\mathrm{TiS}_{2}$ - based electrodes still demonstrate excellent cycling stability, with capacity retentions of $79.1\\%$ , $74.7\\%$ , and $73.7\\%$ , and low capacity decay rates of $0.070\\%$ , $0.084\\%$ , and $0.088\\%$ per cycle, respectively $S I$ Appendix, Fig. S14). The remarkable improvements in cycling stability and coulombic efficiency can be ascribed to the immobilization of soluble polysulfide species through a strong chemical binding and facile redox reaction propelled by these metal sulfides. As for the $\\mathbf{S}@\\mathbf{G}/\\mathbf{CNT}$ electrode, it only delivers an initial reversible capacity of $386\\ \\mathrm{mA\\cdoth\\cdotg^{-1}}$ at $0.5~\\mathrm{C}$ rate and the capacity rapidly decreases to $218\\ \\mathrm{mA}{\\cdot}\\mathrm{h}{\\cdot}\\mathrm{g}^{-1}$ after 300 cycles, with a capacity retention of $56.5\\%$ and fast capacity decay rate of $0.145\\%$ per cycle. This finding suggests a weak affinity with LiPSs that cannot retard their diffusion into the electrolyte and prevent active material loss. Compared with $\\mathrm{TiS}_{2}\\mathrm{-}$ , $\\mathrm{Co}\\dot{\\mathrm{S}}_{2}\\mathrm{-}$ , and $\\bar{\\mathbf{V}}\\mathbf{S}_{2}$ -containing electrodes, the sulfur cathodes containing FeS $(33{\\bar{4}}\\ \\mathrm{mA}{\\cdot}\\mathrm{h}{\\cdot}\\mathrm{g}^{-1}$ , $47.4\\%$ capacity retention), $\\mathrm{SnS}_{2}$ $(191\\ \\mathrm{mA}{\\cdot}\\mathrm{\\bar{h}}{\\cdot}\\mathrm{g}^{-1}\\ )$ , $31.3\\%$ capacity retention), and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ $\\mathrm{^{153}\\ m A{\\cdot}h{\\cdot}g^{-1}}$ , $29.1\\%$ capacity retention) demonstrate inferior cycling stability at $0.5~\\mathrm{C}_{:}$ , with quick capacity degradation and unstable coulombic efficiency around $96\\%$ . The capacity fading rates reach $0.175\\%$ , $0.229\\%$ , and $0.236\\%$ per cycle for FeS-, $\\mathrm{SnS}_{2}.$ , and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ -containing electrodes, respectively, much higher than the other three metal sulfides. These results imply that the selection of suitable polar hosts in the cathode that can $(i)$ strongly interact with LiPSs, $(\\ddot{u})$ rationally control $\\mathrm{Li}_{2}\\mathrm S$ deposition, $(i i i)$ enable fast lithium ion diffusion, $({\\dot{\\imath}}\\nu)$ effectively transform sulfur to $\\mathrm{LiPSs}/\\mathrm{Li}_{2}\\mathrm{S}$ , and $(\\nu)$ catalytically reverse the reaction process is crucial and could significantly decrease polarization, improve sulfur utilization, and enhance rate performance and long-term cycling stability. \n\nPostmortem Analysis of the Electrodes After Cycling. Postcycling SEM characterization provides additional evidence to demonstrate the strong chemisorption between $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ and polysulfides in restricting LiPSs dissolution $S I$ Appendix, Figs. S15–S17). After 100 cycles, the morphologies of the $\\mathbf{S}{-}\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ electrodes display a relatively uniform and smooth surface with few aggregates observed on the surface $S I$ Appendix, Fig. S15). In contrast, large numbers of agglomerates covered the surfaces of the $\\mathbf{S}@\\mathbf{G}/\\mathbf{CNT}$ electrode (SI Appendix, Fig. $\\mathsf{S}16A$ and $B$ ), indicating uncontrolled diffusion of polysulfide intermediates that cause fast capacity decay during cycling. Some small cracks can be observed on the $\\mathbf{S}{-}\\mathbf{Ni}_{3}\\mathbf{S}_{2}@\\mathbf{G}/\\mathbf{C}\\mathbf{N}\\mathbf{T}$ , $\\mathrm{\\bar{S}-S n S_{2}@G/C N T}$ , and $\\mathrm{S-FeS}@\\mathrm{G/CNT}$ electrodes (SI Appendix, Fig. S15 $A{-}C)$ ), whereas the microstructures of the $\\dot{\\bf S}{-}\\dot{\\bf V}\\bar{\\bf S}_{2}\\bar{\\bf(}\\underline{{{a}}}\\mathrm{G}/\\mathrm{CNT}$ , ${\\bf S}{-}{\\bf C o S}_{2}@{\\bf G}/{\\bf C N T}$ , and $\\mathbf{S}\\mathbf{-}\\mathbf{TiS}_{2}@\\mathbf{G}/\\mathbf{CNT}$ electrodes (SI Appendix, Fig. S15 $D{-}F_{-}$ ) remained relatively unchanged, indicating their effective suppression of polysulfide shuttling. The microstructure evolution of lithium metal anode after cycling further supports the inhibition of the LiPSs shuttle effect and effective conversion of sulfur redox promoted by $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ . A rough passivation layer with many cracks is observed on the Li anode surface of the $\\operatorname{s}@\\operatorname{G}/\\operatorname{CNT}$ electrode due to the reaction of migrated sulfur species with the metallic lithium anode $(S I A p\\ –$ pendix, Fig. S16C), whereas the Li anode surface of $\\mathbf{S}{\\mathbf{-M}}_{\\mathbf{x}}\\mathbf{S}_{\\mathbf{y}}@\\mathbf{G}/$ CNT electrodes is much smoother (SI Appendix, Fig. S17). Due to the strong chemical binding of $\\mathrm{CoS}_{2}$ , $\\mathrm{VS}_{2}$ , and $\\mathrm{TiS}_{2}$ to polysulfides (which significantly alleviates polysulfide shuttling) as well as the catalytic conversion of $\\mathrm{Li}_{2}\\mathrm{S}/\\mathrm{Li}_{2}\\mathrm{S}_{2}$ deposition, the passivation layers in the $S I$ Appendix, Fig. S17 $D{-}F$ are more intact and compact, elucidating the more stable cycling exhibited by $\\mathrm{S}{-}\\mathrm{CoS}_{2}@\\mathrm{G}/\\bar{\\mathrm{CNT}}$ , $\\mathrm{S}{-}\\mathrm{VS}_{2}@\\bar{\\mathbf{G}}/\\mathrm{CNT}$ , and $\\mathbf{S}\\mathbf{-}\\mathrm{TiS}_{2}@\\mathbf{G}/\\mathbf{CNT}$ electrodes. \n\n# Conclusions \n\nWe have systematically investigated a series of metal sulfides as polar hosts to reveal the key parameters correlated to the energy barriers and polysulfide adsorption capability in $\\mathrm{Li}{-}\\mathsf{S}$ batteries. Our results indicate that $\\mathrm{VS}_{2^{-}}$ , $\\mathrm{TiS}_{2}.$ , and $\\mathrm{CoS}_{2}$ -based cathodes \n\n1. Bruce PG, Freunberger SA, Hardwick LJ, Tarascon J-M (2011) $L i-O_{2}$ and Li-S batteries with high energy storage. Nat Mater 11(1):19–29. \n2. Yang Y, Zheng G, Cui Y (2013) Nanostructured sulfur cathodes. Chem Soc Rev 42(7): 3018–3032. \n3. Manthiram A, Fu Y, Chung S-H, Zu C, Su Y-S (2014) Rechargeable lithium-sulfur batteries. Chem Rev 114(23):11751–11787. \n4. Evers S, Nazar LF (2013) New approaches for high energy density lithium-sulfur battery cathodes. Acc Chem Res 46(5):1135–1143. \n5. Chung WJ, et al. (2013) The use of elemental sulfur as an alternative feedstock for polymeric materials. Nat Chem 5(6):518–524. \n6. Manthiram A, Chung S-H, Zu C (2015) Lithium-sulfur batteries: Progress and prospects. Adv Mater 27(12):1980–2006. \n7. Sun Y, Liu N, Cui Y (2016) Promises and challenges of nanomaterials for lithium-based rechargeable batteries. Nat Energy 1:16071. \n8. Wang D-W, et al. (2013) Carbon-sulfur composites for Li-S batteries: Status and prospects. J Mater Chem A 1(33):9382–9394. \n9. Ji X, Lee KT, Nazar LF (2009) A highly ordered nanostructured carbon-sulphur cathode for lithium-sulphur batteries. Nat Mater 8(6):500–506. \n10. Yang Y, et al. (2010) New nanostructured $\\mathsf{L i}_{2}\\mathsf{S}$ /silicon rechargeable battery with high specific energy. Nano Lett 10(4):1486–1491. \n11. Zheng G, et al. (2013) Amphiphilic surface modification of hollow carbon nanofibers for improved cycle life of lithium sulfur batteries. Nano Lett 13(3):1265–1270. \n12. Zhou G, et al. (2013) Fibrous hybrid of graphene and sulfur nanocrystals for highperformance lithium-sulfur batteries. ACS Nano 7(6):5367–5375. \n13. Jayaprakash N, Shen J, Moganty SS, Corona A, Archer LA (2011) Porous hollow carbon@sulfur composites for high-power lithium-sulfur batteries. Angew Chem Int Ed Engl 50(26):5904–5908. \n14. Xin S, et al. (2012) Smaller sulfur molecules promise better lithium-sulfur batteries. J Am Chem Soc 134(45):18510–18513. \n15. Zhang SS (2015) Heteroatom-doped carbons: Synthesis, chemistry and application in lithium/sulphur batteries. Inorg Chem Front 2(12):1059–1069. \n16. Song J, et al. (2014) Nitrogen-doped mesoporous carbon promoted chemical adsorption of sulfur and fabrication of high-areal-capacity sulfur cathode with exceptional cycling stability for lithium-sulfur batteries. Adv Funct Mater 24(9):1243–1250. \n17. See KA, et al. (2014) Sulfur-functionalized mesoporous carbons as sulfur hosts in Li-S batteries: Increasing the affinity of polysulfide intermediates to enhance performance. ACS Appl Mater Interfaces 6(14):10908–10916. \n18. Yang C-P, et al. (2014) Insight into the effect of boron doping on sulfur/carbon cathode in lithium-sulfur batteries. ACS Appl Mater Interfaces 6(11):8789–8795. \n19. Peng H-J, et al. (2014) Strongly coupled interfaces between a heterogeneous carbon host and a sulfur-containing guest for highly stable lithium-sulfur batteries: Mechanistic insight into capacity degradation. Adv Mater Interfaces 1(7):1400227. \n20. Ji L, et al. (2011) Graphene oxide as a sulfur immobilizer in high performance lithium/ sulfur cells. J Am Chem Soc 133(46):18522–18525. \n\nexhibit higher capacity, lower overpotential, and better cycling stability compared with pure carbon materials and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}\\mathrm{-}$ , $\\mathrm{SnS}_{2}\\mathrm{-}$ , and FeS-added electrodes. It is demonstrated that the inherent metallic conductivity, strong interaction with LiPSs, facilitated Li ion transport, controlled $\\mathrm{Li}_{2}\\mathrm{S}$ precipitation, accelerated surfacemediated redox reaction, and catalyzing reduction/oxidation capability of $\\mathbf{M}_{\\mathrm{x}}\\mathbf{S}_{\\mathrm{y}}$ are critical in reducing the energy barrier and contributing to the remarkably improved battery performance. More importantly, our density functional theory simulation results are in good agreement with our experiments measuring the activation barrier, polysulfide adsorption, lithium diffusion rate, and electrochemical behavior, which allows us to identify the mechanism for how binding energy and LiPSs trapping dominate the $\\mathrm{Li}_{2}\\mathrm{S}$ decomposition process and overall battery performance. This understanding can serve as a general guiding principle for the rational design and screening of advanced materials for practical Li−S batteries with high energy density and long cycle life. \n\n# Materials and Methods \n\nMaterials and methods can be found in SI Appendix. \n\nACKNOWLEDGMENTS. Y.C. acknowledges support from the Assistant Secretary for Energy Efficiency and Renewable Energy, the Office of Vehicle Technologies, and the Battery Materials Research Program of the US Department of Energy. Q.Z. is supported by the National Natural Science Foundation of China (Grant 11404017), the Technology Foundation for Selected Overseas Chinese Scholar, the Ministry of Human Resources and Social Security of China, and the program for New Century Excellent Talents in University (Grant NCET-12-0033). \n\n21. Wang Z, et al. (2014) Enhancing lithium-sulphur battery performance by strongly binding the discharge products on amino-functionalized reduced graphene oxide. Nat Commun 5:5002. \n22. Zhou G, Paek E, Hwang GS, Manthiram A (2015) Long-life Li/polysulphide batteries with high sulphur loading enabled by lightweight three-dimensional nitrogen/sulphur-codoped graphene sponge. Nat Commun 6:7760. \n23. Wang JL, Yang J, Xie JY, Xu NX (2002) A novel conductive polymer-sulfur composite cathode material for rechargeable lithium batteries. Adv Mater 14(13-14):963–965. \n24. Xiao L, et al. (2012) A soft approach to encapsulate sulfur: Polyaniline nanotubes for lithium-sulfur batteries with long cycle life. Adv Mater 24(9):1176–1181. \n25. Chen H, et al. (2013) Ultrafine sulfur nanoparticles in conducting polymer shell as cathode materials for high performance lithium/sulfur batteries. Sci Rep 3:1910. \n26. Yao H, et al. (2014) Improving lithium-sulphur batteries through spatial control of sulphur species deposition on a hybrid electrode surface. Nat Commun 5:3943. \n27. Tao $\\mathsf{x,}$ et al. (2016) Balancing surface adsorption and diffusion of lithium-polysulfides on nonconductive oxides for lithium-sulfur battery design. Nat Commun 7:11203. \n28. Pang Q, Kundu D, Cuisinier M, Nazar LF (2014) Surface-enhanced redox chemistry of polysulphides on a metallic and polar host for lithium-sulphur batteries. Nat Commun 5:4759. \n29. Seh ZW, et al. (2014) Two-dimensional layered transition metal disulphides for effective encapsulation of high-capacity lithium sulphide cathodes. Nat Commun 5:5017. \n30. Pang Q, Kundu D, Nazar LF (2016) A graphene-like metallic cathode host for long-life and high-loading lithium-sulfur batteries. Mater Horiz 3(2):130–136. \n31. Yuan Z, et al. (2016) Powering lithium-sulfur battery performance by propelling polysulfide redox at sulfiphilic hosts. Nano Lett 16(1):519–527. \n32. Cui Z, Zu C, Zhou W, Manthiram A, Goodenough JB (2016) Mesoporous titanium nitride-enabled highly stable lithium-sulfur batteries. Adv Mater 28(32):6926–6931. \n33. Liang X, Garsuch A, Nazar LF (2015) Sulfur cathodes based on conductive MXene nanosheets for high-performance lithium-sulfur batteries. Angew Chem Int Ed Engl 54(13):3907–3911. \n34. Demir-Cakan R, et al. (2011) Cathode composites for Li-S batteries via the use of oxygenated porous architectures. J Am Chem Soc 133(40):16154–16160. \n35. Xiao J, et al. (2015) Following the transient reactions in lithium-sulfur batteries using an in situ nuclear magnetic resonance technique. Nano Lett 15(5):3309–3316. \n36. Zhao M-Q, et al. (2012) Graphene/single-walled carbon nanotube hybrids: One-step catalytic growth and applications for high-rate Li-S batteries. ACS Nano 6(12): 10759–10769. \n37. Henkelman G, Uberuaga BP, Jonsson H (2000) A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J Chem Phys 113(22): 9901–9904. \n38. Rout CS, et al. (2013) Synthesis and characterization of patronite form of vanadium sulfide on graphitic layer. J Am Chem Soc 135(23):8720–8725. \n39. Zhang $\\scriptstyle{\\mathsf{Q}},$ et al. (2015) Understanding the anchoring effect of two-dimensional layered materials for lithium-sulfur batteries. Nano Lett 15(6):3780–3786. " + }, + { + "id": "10.1126_sciadv.1700015", + "DOI": "10.1126/sciadv.1700015", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.1700015", + "Relative Dir Path": "mds/10.1126_sciadv.1700015", + "Article Title": "Ultrastretchable, transparent triboelectric nullogenerator as electronic skin for biomechanical energy harvesting and tactile sensing", + "Authors": "Pu, X; Liu, MM; Chen, XY; Sun, JM; Du, CH; Zhang, Y; Zhai, JY; Hu, WG; Wang, ZL", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Rapid advancements in stretchable and multifunctional electronics impose the challenge on corresponding power devices that they should have comparable stretchability and functionality. We report a soft skin-like triboelectric nullogenerator (STENG) that enables both biomechanical energy harvesting and tactile sensing by hybridizing elastomer and ionic hydrogel as the electrification layer and electrode, respectively. For the first time, ultrahigh stretchability (uniaxial strain, 1160%) and transparency (average transmittance, 96.2% for visible light) are achieved simultaneously for an energy-harvesting device. The soft TENG is capable of outputting alternative electricity with an instantaneous peak power density of 35 mW m(-2) and driving wearable electronics (for example, an electronic watch) with energy converted from human motions, whereas the STENG is pressuresensitive, enabling its application as artificial electronic skin for touch/pressure perception. Our work provides new opportunities for multifunctional power sources and potential applications in soft/wearable electronics.", + "Times Cited, WoS Core": 1103, + "Times Cited, All Databases": 1164, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000419752300014", + "Markdown": "# A L T E R N A T I V E E N E R G Y \n\n# Ultrastretchable, transparent triboelectric nanogenerator as electronic skin for biomechanical energy harvesting and tactile sensing \n\n2017 $\\circledcirc$ The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\nXiong $\\mathsf{P u},^{1*}$ Mengmeng Liu,1\\* Xiangyu Chen,1 Jiangman Sun,1 Chunhua Du,1 Yang Zhang,1 Junyi Zhai,1 Weiguo Hu,1† Zhong Lin Wang1,2† \n\nRapid advancements in stretchable and multifunctional electronics impose the challenge on corresponding power devices that they should have comparable stretchability and functionality. We report a soft skin-like triboelectric nanogenerator (STENG) that enables both biomechanical energy harvesting and tactile sensing by hybridizing elastomer and ionic hydrogel as the electrification layer and electrode, respectively. For the first time, ultrahigh stretchability (uniaxial strain, $1160\\%$ ) and transparency (average transmittance, $96.2\\%$ for visible light) are achieved simultaneously for an energy-harvesting device. The soft TENG is capable of outputting alternative electricity with an instantaneous peak power density of $35\\mathrm{\\mw\\}\\mathrm{m}^{-2}$ and driving wearable electronics (for example, an electronic watch) with energy converted from human motions, whereas the STENG is pressuresensitive, enabling its application as artificial electronic skin for touch/pressure perception. Our work provides new opportunities for multifunctional power sources and potential applications in soft/wearable electronics. \n\n# INTRODUCTION \n\nThe past decade has witnessed the rapid growth of flexible/stretchable electronics, with the advent of various revolutionary multifunctional devices ranging from flexible transistors $(\\boldsymbol{{l}},2)$ and integrated circuits (3, 4), stretchable luminescence devices $(5,6)$ , and roll-up displays (7) to smart sensor-integrated electronic skins (8–10). These advancements impose the challenge on corresponding power devices that they should have comparable flexibility/stretchability. For example, stretchable and transparent actuator $(l I)$ and touch panel (12) have been recently demonstrated, but no reported energy device can simultaneously achieve the high transparence and stretchability. Meanwhile, the growing wearable consumer electronics, either integrated in clothes/wears or attached on or implanted in curved human body, rely on power devices that are stretchable, shapeadaptive, and biocompatible. \n\nBecause of the intrinsic energy conversion mechanism, it is hard for some energy harvesters to achieve high stretchability, for example, the strong magnetic field required for conventional electromagnetic generator; on the contrary, the recently developed triboelectric nanogenerator (TENG) is naturally flexible and has potential for high stretchability (13–16). The TENG, converting mechanical energy into electricity based on the coupling effect of contact electrification and electrostatic induction, has been demonstrated to be versatile in harvesting different types of energies and has the advantages of simple structure, vast material choice, and low cost (17–22). Several stretchable TENGs have been recently reported (23–28) with similar strategy as most reported stretchable devices, which are enabled by anchoring percolated networks of conductive materials (carbon nanotubes, graphene, carbon paste, silver nanowires, etc.) on prestrained elastomer substrates. However, the stretchability or ultimate strain $(\\varepsilon_{\\mathrm{ult}})$ for this strategy is limited, typically below the ultimate strain of the elastomer (for example, 400 to $700\\%$ for silicones), due to the markedly increased sheet resistance when being stretched and the loss of percolation at large strain. Another recently reported stretchable TENG achieved ${\\sim}300\\%$ tensile strain by using water or ionic liquid as the electrode, but its application is limited by the use of liquid materials (29). \n\nHydrogels, composed of hydrophilic polymer networks swollen with water or ionic aqueous solution, are in solid form, soft, stretchable $(\\varepsilon_{\\mathrm{ult}},\\sim2000\\%)$ , and biocompatible (30). Some hydrogels are transparent in full visible spectrum $(l l)$ . Meanwhile, the increments of their resistivity with strain are orders of magnitude lower than those of percolated conductive networks $(l l)$ . Many stretchable functional devices have been demonstrated with ionic hydrogels as the electrode conductors, such as strain sensors (31), loudspeakers $(l I)$ , and electroluminescent devices (32). \n\nHere, we report a soft skin-like TENG (STENG) that enables both biomechanical energy harvesting and touch sensing by using elastomer and ionic hydrogel as the electrification layer and electrode, respectively. Different from previously reported TENGs using electrical conductors as the electrode, this soft STENG uses ionic conductors as the electrode. Polyacrylamide (PAAm) hydrogel containing lithium chloride (LiCl) is used as the ionic hydrogel (PAAm-LiCl hydrogel), and two commonly used elastomers, that is, polydimethylsiloxane (PDMS) Sylgard 184 and 3M VHB 9469, are adopted. For the first time, ultrahigh stretchability (ultimate stretch $\\lambda$ of up to 12.6 or strain e of $1160\\%$ ) and high transparency (up to $96.2\\%$ ) are achieved simultaneously for an energy device because all engaged materials are stretchable and transparent. These soft skin-like generators are capable of outputting an open-circuit voltage of up to $145\\mathrm{V}$ and an instantaneous areal power density of $35\\mathrm{mW}\\mathrm{\\stackrel{\\sim}{m}}^{-2}$ . Meanwhile, the STENG-based electronic skin can sense pressure of as low as $1.3\\mathrm{kPa}$ . The current study presents an energy harvester that is superstretchable, biocompatible, and transparent for the first time, allowing energy generation and touch sensing without interference of optical information’s delivering and could thus have potential in smart artificial skins, soft robots, functional displays, wearable electronics, etc. \n\n# RESULTS \n\nA sandwich-like architecture was adopted for the design of the STENG, as illustrated in Fig. 1A. The PAAm-LiCl hydrogel was sealed between two elastomer films, and an Al belt or a Cu wire was attached to the hydrogel for electrical connection. Commercial PDMS or VHB was used as the elastomer film, denoted as PDMS-STENG and VHBSTENG, respectively. For the convenience of handling, the thickness of the hydrogel film is controlled to be about $2~\\mathrm{mm}$ ; the thickness of PDMS and VHB is about 90 and $130\\upmu\\mathrm{m}$ , respectively. The final devices can be of arbitrary two-dimensional shapes. Figure 1B shows an image of a circular PDMS-STENG that is highly transparent to all visible colors. Because all engaged elastomers and PAAm-LiCl hydrogel are stretchable, the final device is ultrastretchable as well, as confirmed by the image (Fig. 1C) of a VHB-STENG at initial state (stretch $\\lambda=L/$ $L_{\\mathrm{o}}=1$ ) and after being uniaxially stretched for 11 times (stretch $\\lambda=11$ or strain $\\begin{array}{r}{\\mathbf{\\varepsilon}\\mathbf{\\varepsilon}=1000\\%\\mathbf{\\varepsilon}}\\end{array}$ ). The images of a PDMS-STENG with uniaxial stretch $\\lambda=4$ and a PAAm-LiCl hydrogel with stretch $\\lambda=15$ are also shown in fig. S1. \n\n![](images/eb595be91576fea342217087b58a99041784ec61ae2517e66f7f855ed6238d00.jpg) \nFig. 1. The design of transparent and superstretchable STENG. (A) Scheme of the STENG with sandwich structure. (B) A circular STENG that is transparent to full visible colors. (C) VHB-STENG (indicated by arrows) at initial state (stretch $\\lambda=1$ ) and stretched state $(\\lambda=11$ or strain $\\mathbf{\\varepsilon}\\mathbf{{E}}=1000\\%)$ . (D) Transmittance in the visible range and (E) uniaxial tensile test of the PAAm-LiCl hydrogel, PDMS-STENG, and VHB-STENG. Scale bars, $5c m$ (B) and $15~\\mathsf{m m}$ (C). \n\nThe $2\\mathrm{-mm}$ -thick PAAm-LiCl hydrogel achieves an average transmittance of $98.2\\%$ (Fig. 1D) in the visible range (wavelength, 400 to $800\\mathrm{nm}\\cdot$ ), which is less transparent than that of the previously reported $11\\mathrm{-mm}$ -thick PAAm-NaCl hydrogel $(98.9\\%)$ due to the higher salt concentration in the current study (8 M) $(l l)$ . The PDMS-STENG and VHB-STENG show average transmittances of 96.2 and $91.9\\%$ , respectively, both much higher than those of previously reported transparent TENG using graphene or indium tin oxide (ITO) (33–36). Uniaxial tensile tests are performed to evaluate the mechanical properties of the hydrogels and STENGs (Fig. 1E). The PAAm-LiCl hydrogel shows an ultimate stress of $75.8\\mathrm{kPa}$ at a stretch of $\\lambda=16.2$ ; whereas the VHBSTENG ruptures at a stress of $152.4\\mathrm{~kPa}$ and a stretch of 12.6, the PDMS-STENG ruptures at a stress of $446.2\\mathrm{\\kPa}$ and a stretch of 4.5. \n\nIt therefore can be suggested that the stretchability and strength of the STENGs are tunable by selecting appropriate elastomer/hydrogel combinations for specific requirements and that ultrahigh stretchability and transparency have been achieved simultaneously. \n\nThere are generally four types of working modes for a TENG, that is, contact-separation mode, sliding mode, freestanding mode, and singleelectrode mode (37). If the PAAm-LiCl hydrogel is connected to the ground by a metal wire through the external load, the STENG will work in the single-electrode mode (Fig. 2A). Once an object (typically dielectric materials different from the elastomer) contacts with the elastomer film of the STENG, electrification occurs at the interface and generates the same amount of charges with opposite polarities at the surface of the dielectric film and the elastomer, respectively (Fig. 2A, i). Because the two opposite charges coincide at almost the same plane, there is practically no electrical potential difference between the two surfaces. When the two surfaces are separating and moving away, the static charges on the surface of the insulating elastomer will induce the movement of the ions in the ionic hydrogel to balance the static charges, forming a layer of excessive ions (positive in the example in Fig. 2A, ii) at the interface. Meanwhile, the electrical double layer formed at the metal/electrolyte (that is, ionic hydrogel) interface will be polarized, forming the same amount of excessive negative ions at the interface and positive charges in the metal wire (Fig. 2A, v). To achieve this double layer, electrons flow from the metal wires to the ground through the external circuits until all the static charges in the elastomer film are screened (Fig. 2A, iii). If the moving dielectric film is approaching back to the elastomer film, the whole process will be reversed and an electron flux with the opposite direction will transfer from the ground to the metal/hydrogel interface through the external load (Fig. 2A, iv). By repeating the contact-separation movement between the dielectric object and the STENG, an alternative current will be generated. \n\n![](images/2311f0c5b842ed7a083df7ec769607bffc5c155cf15260b303af1aa3ff5579d2.jpg) \nFig. 2. The working principles and output characteristics of the STENG at single-electrode mode. (A) Scheme of the working mechanism of the STENG. (B) Opencircuit voltage $V_{\\mathrm{OC}}$ (B), (C) short-circuit charge quantity $\\scriptstyle Q_{5C},$ and (D) short-circuit current $I_{S C}$ of a PDMS-STENG. (E) Variation of the output current density and power density with the external loading resistance. \n\nThe electrical double layer formed at the metal/hydrogel interface has a thickness typically in the nanometer range, which leads to a high capacitance $\\dot{c}_{\\mathrm{EDL}}$ is in the order of $0.1\\mathrm{F}\\mathrm{m}^{-2}.$ ) $(l l,38)$ . The contacting area $(A_{\\mathrm{EDL}})$ of the metal wire and the hydrogel is in the order of $\\sim10\\mathrm{mm}^{\\frac{\\dag}{2}}$ , and the quantity of transferred charges (Q) is in the order of ${\\sim}10\\mathrm{nC}$ (the data will be presented in later discussions). Then, the voltage across the electrical double layer $(V_{\\mathrm{EDL}}=Q/A c_{\\mathrm{EDL}})$ is in the order of ${\\sim}10^{-2}\\mathrm{~V~}$ . Therefore, the metal/hydrogel interface is stable, and no electrochemical reaction will happen because the voltage is well below 1 V (11). \n\nSTENG fundamentally has inherent capacitive behavior because it is an electrostatic system, and it can be equivalent to a circuit consisting of a series of capacitors, as shown in fig. S2. The output voltage under open-circuit condition $(V_{\\mathrm{OC}})$ and the transferred charges under shortcircuit condition $(Q_{\\mathrm{SC}})$ have a relationship of (37, 39) \n\n$$\nQ_{\\mathrm{SC}}=V_{\\mathrm{OC}}C_{\\mathrm{o}}\n$$ \n\nwhere $C_{\\mathrm{o}}$ is the capacitance of the STENG. When the moving dielectric film is in contact with the elastomer, $V_{\\mathrm{OC}}$ and $Q_{\\mathrm{SC}}$ are both 0. When the dielectric film is moving far away, $V_{\\mathrm{OC}}$ and $Q_{\\mathrm{SC}}$ can be derived as (see detailed explanations in fig. S2) (37, 39) \n\n$$\nV_{\\mathrm{OC}}=-\\upsigma A/2C_{\\mathrm{o}}\n$$ \n\n$$\nQ_{\\mathrm{SC}}=-{\\upsigma}A/2\n$$ \n\nwhere $\\upsigma$ is the density of electrostatic charges generated at the surface of the elastomer film and $A$ is the contacting area between the dielectric film and the elastomer film. \n\nTo measure the output of the STENG, we used a commercial Nylon film to have contact-separation movement relative to a PDMS-STENG (area, $3\\times4~\\mathrm{cm}$ ). Other than mentioned, the frequency $(1.5\\ \\mathrm{Hz})$ and speed $(0.2\\mathrm{~m~}s^{-1}\\mathrm{~.~}$ ) of the contact-separation motion and the pressure $({\\sim}100\\ \\mathrm{kPa})$ between the two contacting films are all controlled to be the same by a stepping motor for all following tests. The peak $V_{\\mathrm{OC}}$ and the peak $Q_{\\mathrm{SC}}$ are about $145\\mathrm{V}$ (Fig. 2B) and $47{\\mathrm{nC}}$ (Fig. 2C), respectively. Under short-circuit conditions, an alternative current was measured with a peak value of ${\\sim}1.5~\\upmu\\mathrm{A}$ (Fig. 2D). By varying the external resistance, the maximum output areal power density was measured to be ${\\sim}35\\mathrm{mW}\\mathrm{m}^{-2}$ at a matched resistance of ${\\sim}70$ megohm (Fig. 2E). Similar output characteristics were obtained for the VHB-STENG (fig. S5). \n\nThe STENG can also work at a two-electrode contact-separation mode, as shown in fig. S6. Different from the single-electrode mode, the moving dielectric film is replaced with a second metal electrode that is connected to the PAAm-LiCl hydrogel through the external circuit (fig. S6A). When Al foil was used as the second electrode, the generated peak $V_{\\mathrm{OC}}$ and peak $Q_{\\mathrm{SC}}$ are about $182\\mathrm{V}$ (fig. S6B) and $130\\mathrm{nC}$ (fig. S6C), respectively. The instantaneous peak value of the ac current is around ${\\sim}20\\upmu\\mathrm{A}$ (fig. S6D), and a maximum areal power density of ${\\sim}328\\mathrm{mW}\\mathrm{m}^{-2}$ can be reached at a loading resistance of ${\\sim}7\\$ megohm (fig. S6E). \n\nBecause of the universality of contact electrification between any two different materials, the STENG can generate voltage/current outputs from the relative motion between the STENG and many other materials. A series of materials were used to have contact-separation motion relative to the STENG in single-electrode mode, and corresponding opencircuit voltages were recorded (Fig. 3A and fig. S7). The amplitude and polarization of $V_{\\mathrm{OC}}$ depend on the relative ability of a material to lose or gain electrons when contacting with the elastomer. Compared with VHB (typically acrylate polymers), all of Nylon (polyamide), latex, silk, paper, Al, cotton, and polyester (PET) are tending to lose electrons and therefore are more tribo-positive, whereas Kapton (polyimide) and PDMS are more tribo-negative and the polarization of the $V_{\\mathrm{OC}}$ is reversed (Fig. 3, A and B), coincident with the well-established tribo-series table (18, 40). The larger the difference in the ability of losing/gaining electrons between the two contacting materials, the more electrostatic charges generated at the interface and thus the higher output $V_{\\mathrm{OC}}$ . Nylon and \n\n![](images/ab078a3f4ac5da18f4366adaa96c32cd6ba6bf1bfac60591d20b37b0e02b590c.jpg) \nFig. 3. The material choices and durability of the STENG. (A) Summarized peak amplitude (A) of $V_{\\mathrm{OC}}$ and (B) three representative $V_{\\mathrm{OC}}$ profiles (B) of a VHB-STENG with relative contact-separation motion to different materials. (C) Output $V_{\\mathrm{OC}}$ and $\\boldsymbol{Q}_{\\mathsf{S C}}$ of a PDMS-STENG using PAAm-LiCl hydrogel with different LiCl concentrations. (D) Normalized weight retention of the PAAm-LiCl hydrogel, VHB-STENG, and PDMS-STENG kept at a dry environment with an RH of $30\\%$ at $30^{\\circ}\\mathsf C.$ (E) Comparison of the $V_{\\mathrm{{oc}}}$ of the PDMSSTENG before and after storing in the dry environment for 30 days. (F) $I_{S C}$ of a PDMS-STENG that lasted for $\\mathord{\\sim}5000$ cycles of contact-separation motions (1 hour). \n\nPDMS are the most tribo-positive and tribo-negative among tested materials, respectively. Consistent results are also obtained when using PDMS as the elastomer film for the PDMS-STENG (fig. S7), where all tested materials are more tribo-positive than PDMS. Because PDMS is more tribo-negative than VHB, the PDMS-STENG has relatively larger output than that of VHB-STENG when the same materials were used for the contact-separation motion. Human skin can also be used to have contact separation with the STENG. As shown in fig. S8, current can be generated when using a hand to tap a PDMS-STENG with or without a latex glove. The viability of the STENG in relative motion to different materials can make it suitable and applicable for energy harvesting in various applications. \n\nThe concentration of the LiCl in the PAAm-LiCl hydrogel was also varied to see its effect on the output performances, but the $V_{\\mathrm{OC}}$ and $Q_{\\mathrm{SC}}$ were found to have little dependence on the LiCl concentration (Fig. 3C of a PDMS-STENG). This is easy to understand as far as Eqs. 2 and 3 are considered because the $V_{\\mathrm{OC}}$ and $Q_{\\mathrm{SC}}$ are majorly dependent on the generated electrostatic charges, and the concentration of the ionic hydrogel (or electrolyte) will not significantly vary the capacitance of the STENG. \n\nOne major concern about hydrogel is the dehydration along with time, which can deteriorate its ionic conductivity and mechanical elasticity. When kept in an environment of an average relative humidity (RH) of ${\\sim}30\\%$ at $30^{\\circ}\\mathrm{C},$ the PAAm-LiCl hydrogel loses water content quickly in the first 3 days $7.1\\%$ loss) but stabilizes in the following 27 days, yielding weight retention of $89.8\\%$ over a month (Fig. 3D). Whereas the dehydration is greatly alleviated when the PAAm-LiCl hydrogel is sandwiched or sealed with the elastomer films of PDMS and VHB, which have the weight retention of 95.0 and $94.6\\%$ after a month in the same environment, respectively, the improved antidehydration capability is mainly because the thin elastomer films can prevent the water evaporation. Despite the slight loss of water content of the PDMSTENG over a month, the output performances show no noticeable degradation, as confirmed by the comparison between the $V_{\\mathrm{OC}}$ of the as-made PDMS-STENG in relative motion to a Nylon film and that after storage at an RH of ${\\sim}30\\%$ at $30^{\\circ}\\mathrm{C}$ for a month (Fig. 3E). This demonstrated antidehydration performance of the STENG ensures its applicability in many harsh environments. \n\nBecause the hydrogel contains large amount of LiCl solution, the STENG can only be applicable in the temperature range between the freezing and boiling point of LiCl solution. Beyond this temperature range, the STENG may be damaged. We tested the performances of the STENG at temperatures ranging from $0^{\\circ}$ to $80^{\\circ}\\mathrm{C}.$ . On the basis of our measurements, the $V_{\\mathrm{OC}}$ and $Q_{\\mathrm{SC}}$ are stable, other than the small decrease at high temperature at around ${60}^{\\circ}$ to $80^{\\circ}\\mathrm{C}$ (fig. S9). This is accordant with the previous study that the variation of output is small in the temperature range of 270 to $380\\mathrm{K}$ (41). To confirm the thermal durability of the STENG, we further stored the PDMS-STENG, VHB-STENG, and bare hydrogel at different temperatures $(0^{\\circ},20^{\\circ},40^{\\circ},$ $60^{\\circ}$ , and $80^{\\circ}\\mathrm{C})$ for $30\\mathrm{min}$ consecutively. The weight of bare hydrogel decreases significantly when the temperature is more than $40^{\\circ}\\mathrm{C},$ and the shrinkage of the sample can be observed after storing at $60^{\\circ}$ and $80^{\\circ}\\mathrm{C}$ (fig. S10). The weight retention of the hydrogel is only about $68.6\\%$ after the test due to the severe water loss at high temperature. However, the hydrogels inside the PDMS-STENG and VHB-STENG can maintain weight retentions of 95.6 and $98.5\\%$ , respectively, even after storing at $80^{\\circ}\\mathrm{C}$ (fig. S10A), whereas water vapor bubbles inside the PDMS-STENG and VHBSTENG can be observed when the temperature is $80^{\\circ}\\mathrm{C}$ . Hence, although the PDMS and VHB films are believed to alleviate the water evaporation of hydrogels, the STENG is believed to be better when used in the temperature range of $0^{\\circ}$ to $60^{\\circ}\\mathrm{C}$ . \n\nHumidity has large effect on the output performances of the STENG (fig. S11). By increasing the humidity, the $V_{\\mathrm{OC}}$ of both the PDMSSTENG and VHB-STENG decreases significantly. When the RH is about $70\\%$ , the $V_{\\mathrm{OC}}s$ of the PDMS-STENG and VHB-STENG are 20 and $43\\mathrm{V}$ , respectively. In a humid environment, the adsorption of the water molecules will neutralize the surface electrostatic charges so that the output performances of the STENG will be degraded (17). \n\nThe durability of the STENG was also tested over long-term motion cycles. After $\\mathord{\\sim}5000$ cycles (for 1 hour) of repeated contact-separation motion of a PDMS-STENG relative to a Nylon film, the short-circuit current shows no obvious degradation (Fig. 3F and fig. S12). An elongated test over ${\\sim}20000$ cycles (for 4 hours) was also conducted to confirm the durability (fig. S12). \n\nOne major advantage of hybridizing the elastomer and hydrogel is the high stretchability, as shown in above discussions. The viability of the energy harvesting of the STENG at stretched states was further evaluated. A VHB-STENG $3\\mathrm{cm}\\times3\\mathrm{cm})$ was uniaxially stretched for different stretches or strains (Fig. 4A), and corresponding electrical outputs (Fig. 4B) were recorded when having contact-separation motion relative to a dielectric film (that is, a latex film). During the test, the latex film was always maintained to have the similar shape and size as the VHB-STENG. Compared with the initial state without strain $\\left(\\lambda=1\\right)$ ), the open-circuit voltage of the STENG (Fig. 4B) is greatly improved from ${\\sim}110$ to ${\\sim}180$ and ${\\sim}210\\mathrm{V}$ after being stretched for $\\lambda=3$ and 8, respectively. Similar \n\n![](images/c331a0b7990fdd6978b495f002fcff701de209915a0d64f28a6486cde414f2f0.jpg) \nFig. 4. The stretchability of the STENG. (A) Images of a VHB-STENG at initial state and different stretched states and (B) its corresponding output $V_{\\mathrm{OC}}$ (B) when having contact-separation motion to a latex film. \n\nPu et al., Sci. Adv. 2017; 3 : e1700015 31 May 2017 increases in the electrical outputs at stretched states were also observed previously (23, 29). This increment in $V_{\\mathrm{OC}}$ is attributed to the increase of the surface area of the elastomer film and thus the contacting area for the electrification at stretched states. On the basis of our rough estimation, the area of the STENG is almost doubled after being stretched to $\\lambda=3$ . According to Eqs. 2 and 3, both the $V_{\\mathrm{OC}}$ and $Q_{\\mathrm{SC}}$ increase when the contacting area $A$ increases. This can also be confirmed by the larger $Q_{\\mathrm{SC}}$ at stretched states (fig. S13). After recovering from the stretched states, the electrical output is comparable with that at initial state, suggesting no degradation of the device. \n\nFor most stretchable devices using percolated networks of carbonaceous materials or metal nanowires, degradation in performances at stretched states is almost inevitable due to the significantly elongated electron transfer paths or even the loss of percolation at large strain. In contrast, the increment in resistance of hydrogel is several orders lower $(l I)$ . Our devices show no degradation but even improvement in the performances at stretched states. Ideally, our devices will work until the mechanical break or fracture of the hydrogel/elastomer; in contrast, the loss of percolation of conductive networks usually happens before the mechanical failure of the substrates. Furthermore, another drawback of the percolated networks is the possible fatigue failure after elongated stretching cycles due to the loss of electrical connection at the network joints. Nevertheless, the STENG with ionic hydrogel as the conductor shows no mechanical fatigue or degradation in electrical output after being stretched for strain $\\varepsilon=200\\%$ $\\left(\\lambda=3\\right)$ for 1000 cycles (fig. S14). However, note that interface bonding between the PAAm-LiCl hydrogel and the elastomer films is weak because hydrogel is hydrophilic and elastomers are typically hydrophobic. This could be a disadvantage comparing with conductive additive-filled nanocomposites (42). For our STENG, the hydrogel is wrapped or sealed inside the elastomer film; it still works after cycles of stretching, but the enhancement in the bonding force can further improve the mechanical durability of the devices. Several recent progresses showed potential approaches to addressing this issue (43, 44). \n\nThe STENG can be used for scavenging mechanical energy, especially the energy of human motions. When tapping a transparent VHBSTENG with a hand (with thes human body as the reference electrode or grounding) both at initial and stretched states, 20 green light-emitting diodes (LEDs) connected in series can be easily lighted up (Fig. 5, A and B, and movies S1 and S2). Because the STENG is highly transparent, a VHB-STENG is attached onto a liquid crystal display (LCD) screen, which converts the energy of finger pressing into electricity and powers the screen (Fig. 5C and movie S3). Furthermore, the output of a STENG can be regulated to charge energy storage devices (capacitors or batteries) for powering different portable electronics, as shown by the equivalent circuit in Fig. 5E. For demonstration, a PDMS-STENG was attached on the human skin of the left hand and tapped by the right hand to charge a $2.2\\mathrm{-}\\upmu\\mathrm{F}$ capacitor and to power an electronic watch (Fig. 5D). The tapping frequency is about 1 to $2\\mathrm{Hz}$ . In ${\\sim}160s,$ the voltage of the capacitor reaches $4.5\\mathrm{V}$ and can later power the watch for about $15\\:s$ (Fig. 5F and movie S4). Subsequently, the capacitor can be charged back to $4.5\\mathrm{V}$ in about 110 to 140 s and can power the watch repeatedly (Fig. 5F). Meanwhile, the STENG, working in two-electrode mode, can charge a Li-ion battery $\\mathrm{LiCoO}_{2}$ as cathode and Li metal as anode) to $3.83\\mathrm{V}$ in 4 hours, which later can be discharged at a constant current of $1\\upmu\\mathrm{A}$ for $45\\mathrm{min}$ (fig. S15). Note that the transparent TENG is soft, biocompatible, capable of adapting to the curvy surface of supporting objects in any irregular shape and has no interference of the communication of optical information and therefore has high potential in soft robots, foldable touch screens, artificial skins, wearable electronics, etc. \n\n![](images/2c4b087b2f34c6ac295a002c8a55e2f01e66288f73dec2b2d6cf396efac005dc.jpg) \nFig. 5. Biomechanical energy harvesting by the STENG. An image of 20 green LEDs lightened by the VHB-STENG (A) at initial state and (B) stretched state when being tapped slightly by a hand. (C) An image of an LCD screen powered by a transparent VHB-STENG, which covers the screen and converts the energy of finger pressing into electricity. (D) An image and (E) the equivalent circuit of a self-charging system that uses the energy harvested from the STENG to power electronics (for example, an electronic watch). (F) Voltage profile of a $2.2\\J{\\cdot}\\mu\\ F$ capacitor being charged by the STENG and used to power the electronic watch. \n\nThe output of the STENG is also found to be pressure-sensitive in this study and in several previous reports (45, 46). Because the surfaces of the materials always have a certain degree of roughness, the effective contacting area will increase at high pressure because the elastomer and hydrogel are very soft and elastic. The microscale elastic deformation leads to the more intimate contact and more generated electrostatic charges at the interfaces. According to Eqs. 2 and 3, the increase in the electrostatic charge density s will then raise the output current and voltage. A 20-megohm resistor was connected to a PDMS-STENG $(3\\times4~\\mathrm{cm})$ , and the voltage drop across the resistor was recorded when pressing a Nylon film onto the PDMS-STENG at different pressures (Fig. 6A). Two reverse voltage peaks were observed, corresponding to the event of touch or separation, respectively (fig. S16). Different from typical pressure sensor, no voltage signal was observed during the time intervals of the touching and separation, although the pressure was still applied on the STENG. However, by increasing the resistance $R$ of the resistor, the measured voltage signals will change to sidestep shape and, finally, to a rectangular shape under open-circuit condition (45). The amplitude of the bimodal voltage increases linearly with the pressure when the touch pressure is low and saturates after the pressure is higher than ${\\sim}70\\mathrm{kPa}$ . The sensitivity (S) is typically defined as $S=(d\\Delta V/V_{\\mathrm{S}})/d P_{\\ddagger}$ where $\\Delta V$ is the relative change of the output voltage, $V_{\\mathrm{{S}}}$ is the saturated voltage, and $P$ is the touch pressure. The calculated sensitivity is $0.013\\mathrm{kPa}^{-1}$ , comparable with that of previously reported TENG-based pressure sensors (45) but smaller than many other sensors (47). The lowest pressure detection limit is about $1.3\\mathrm{kPa}$ , and the recorded voltages at five different touch pressures are shown in Fig. 6B. The ambient temperature variation has little effect on the sensing properties in the temperature range where the STENG is applicable. As shown in fig. S17, no obvious variation of the voltage was observed in the temperature range of $\\mathrm{{0^{\\circ}}}$ to $80^{\\circ}\\mathrm{C}.$ . Because the STENG is mainly an electrostatic charge–based capacitive sensor, the temperature-introduced resistance change of the hydrogel will not vary the voltage signal (48). \n\nConsidering the demonstrated sensing capability of touch and touch pressure, the soft and transparent STENG can be applied as artificial electronic skin. A STENG-based artificial skin with 3 pixel $\\times3$ pixel (each is ${1}\\mathrm{cm}\\times{1}\\mathrm{cm},$ ) was fabricated and can be conformally attached onto a curvy hand (Fig. 6C). This artificial skin can perceive the touch by alien objects and the touch pressure. When pressing 1 pixel with a fingertip, the output voltage varies accordingly with the pressure (Fig. 6D). When pressing the sensor arrays with a $\\mathbf{z}$ -shaped acrylic plate (Fig. 6E), the output voltages can literally represent the touching area of the STENG (Fig. 6F and fig. S18). \n\n# DISCUSSION \n\nWe reported here a soft STENG composed of a sandwich structure of ionic hydrogels and elastomer films for energy conversion and tactile sensing. These material combinations and structural designs allow the following advantages: \n\n(1) High stretchablity (up to $\\lambda=12.6$ or strain $\\mathtt{\\mathtt{E}}=1160\\%$ ) and transparency (up to $96.2\\%$ average transmittance to full spectrum of visible light) are achieved, which are both much higher than those of previously reported stretchable and/or energy conversion devices using percolated conductive networks or ITO as the electrode materials (24, 29, 33, 34, 36). No performance degradation is observed at stretched states as well. \n\n![](images/fc26617bbe921005d99e0176f771828fae4989bed3ed60f477c96eebbdecb555.jpg) \nFig. 6. Tactile sensing by the STENG. (A) Summarized variation of peak amplitudes of the voltage across the resistor (20 megohm) with the contact pressure. Inset: Scheme of the STENG-based tactile sensor. (B) Representative voltage profiles of the STENG as tactile sensor at five different pressures. (C) An image of a STENG-based tactile sensor with 3 pixel $\\times3$ pixel attached on a curvy hand. (D) Voltage signals of the tactile sensor by pressing 1 pixel with a finger at increasing pressures. (E) An image of the tactile sensor pressed with a $z$ -shaped acrylic plate and (F) corresponding voltage signals of the 9 pixels. \n\n(2) The mechanism of STENG is slightly different from that of previously reported TENGs using electrical conductors as the electrode. Ionic conductors (that is, ionic hydrogels) are used, which is demonstrated to be stable and will not be electrolyzed at the interface. \n\n(3) The unique capability of energy harvesting and tactile perception of the STENG may lead to the soft/stretchable self-powered sensors or self-charging power systems in the future (49, 50). For example, selfpowered soft robot or electronic skin might be possible in the future by the combination of soft energy-harvesting and energy storage devices and soft sensors and actuators. \n\n(4) Both elastomers and hydrogels are low cost, lightweight, and biocompatible. It is also possible to design the STENG into arbitrary, complicated shapes as long as a thin elastomer film wraps or seals the hydrogels. Meanwhile, the fabrication is facile for scale-up synthesis. Considering the biocompatibility, the STENG has potential for power devices attached on the skin or implanted inside the human body (51). Furthermore, both the elastomer and hydrogel have large categories of different materials with various unique properties. The combination of the hydrogel and elastomer has recently led to many multifunctional devices, as mentioned in the Introduction. The STENG with the hydrogel/elastomer combination reported here opens up opportunities for energy generation devices with new functional properties (stretchability, transparency, biocompatibility, etc.) and many potential applications ranging from soft robots, foldable touch screens, and artificial skins, to wearable electronics. \n\nIn summary, our approach of soft/stretchable energy harvesting allows the energy conversion from human motions to electricity. The capability of scavenging biomechanical energies of the STENG was demonstrated when applying it as an artificial skin. Capacitors or batteries can be charged by the artificial skin to power wearable electronics. Finally, the sensitivity of the STENG to the input pressure was investigated, which enabled it as an electronic skin for pressure or tactile perception. The applicable temperature of the STENG is optimal at $0^{\\circ}$ to $60^{\\circ}\\mathrm{C};$ otherwise, the freezing or boiling of the ionic solution in the hydrogel may cause the malfunction of the device. For future research, more multifunctional devices can be explored by developing STENGs with other functional hydrogels/elastomers; the interface bonding between the hydrogel and elastomer should be enhanced to further improve the mechanical performances of the STENG; output performances should be improved by maximizing the surface electrostatic charge density through surface treatments/modifications or materials optimization. \n\n# MATERIALS AND METHODS \n\n# Materials \n\nAcrylamide, $N,N,N^{\\prime},N^{\\prime}$ -tetramethylethylenediamine, $N,N^{\\prime}$ - methylenebisacrylamide, ammonium persulfate, and LiCl were from Sigma-Aldrich. Sylgard 184 and VHB film (3M VHB 9469) were used as the elastomer. Lithium foil and $\\mathrm{LiCoO}_{2}$ powder were from MTI Corporation. \n\n# Fabrication of the PAAm-LiCl hydrogel \n\nThe PAAm-LiCl hydrogel was prepared according to the method reported previously. Briefly, acrylamide powder (14 weight $\\%$ relative to deionized water) was added into 8 M LiCl aqueous solution. Subsequently, $N,N^{\\prime}$ -methylenebisacrylamide, ammonium persulfate, and $N\\mathrm{,}N\\mathrm{,}N^{\\prime}\\mathrm{,}N^{\\prime}$ - tetramethylethylenediamine were dissolved in the solution consecutively. \n\nThe solution was then transferred into a glass mold and treated in an oven at $50^{\\circ}\\mathrm{C}$ for 2 hours to form the PAAm-LiCl hydrogel. The thickness of the final hydrogel was controlled by the volume of the solution. Other than mentioned, all the samples used 8 M LiCl. \n\n# Fabrication of the soft TENG \n\nThe elastomer VHB film ( $130\\upmu\\mathrm{m}$ thick; 3M VHB 9469) was used as received. The PDMS film was prepared by spin-coating the mixture of Sylgard 184 base and curing agents (10:1 by weight) followed with a $90^{\\circ}\\mathrm{C}$ treatment for 1 hour. The PAAm-LiCl hydrogel, VHB, and PDMS were cut into the desired shape with a laser cutter. The final device was fabricated by wrapping and sealing the PAAm-LiCl hydrogel with the elastomer films. An Al belt or a $\\mathtt{C u}$ wire was attached to the hydrogel for electrical connection. \n\n# Characterization and measurements \n\nA step motor (LinMot E1100) was used to provide the input of mechanical motions. For all the tests of energy generation of the STENG, the pressure $(100\\mathrm{kPa})$ , speed $(0.2\\mathrm{m}/\\mathrm{s})$ ), and frequency $(\\sim1.5\\mathrm{{Hz})}$ of the step motor were fixed. The voltage and charge quantity were recorded by a Keithley electrometer 6514, and the current was recorded with a Stanford low-noise preamplifier SR570. The force applied by the motor was detected by a Mark-10 force gauge. The mechanical tensile test and stretch cycling test of the STENGs were conducted by an ESM301/Mark-10 system. For the tensile test, the strain rate was fixed at $40~\\mathrm{mm/min}$ . For the antidehydration test, the dry environment was created by storing dehydrated desiccants in an oven at $30^{\\circ}\\mathrm{C}$ . The RH was monitored with a hygrometer, and the weights of the samples were recorded everyday. For the measurement of the output performances of the STENG at different temperatures, the STENG was kept inside a thermostat oven (GDW-50L, Wuxi Zhongtian Company), and the contact-separation motion was controlled by the linear motor outside through a feedthrough hole. For the measurement of the STENG at different RH, dry air gas carrying water vapor though a water bubbler was introduced into the oven at different flowing rates or a commercial humidifier was used to provide a humid environment. The optical transmittance was measured by a Shimadzu UV-3600 spectrophotometer. A Li-ion battery was assembled with commercial $\\mathrm{LiCoO}_{2}$ (MTI Corporation) as the cathode and Li metal as the anode. Before the battery charging by the STENG, the $\\mathrm{LiCoO}_{2}$ -Li battery was discharged to $3.5\\mathrm{V}$ at a current of $1\\upmu\\mathrm{A}$ repeatedly for three times to deplete the residual capacity. The discharge of the battery was conducted by a battery cycler (LAND CT2001A). \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/3/5/e1700015/DC1 \n\nfig. S1. The images of the stretchable PDMS-STENG and hydrogel. \nfig. S2. The explanation of the working mechanism of the STENG. \nfig. S3. The scanning electron microscopy image of the surface of PDMS and VHB. \nfig. S4. The images of the PDMS-STENG and VHB-STENG folded completely. \nfig. S5. The output characteristics of a VHB-STENG at single-electrode mode. \nfig. S6. The working mechanism and output characteristics of the STENG at two-electrode mode. \nfig. S7. Material choices of the PDMS-STENG. \nfig. S8. Rectified current output of the STENG by hand tapping. \nfig. S9. Temperature effect on the performances of the STENG. \nfig. S10. Thermal durability of the STENG. \nfig. S11. Humidity effect on the performances of the STENG. \nfig. S12. The durability of the STENG. \nfig. S13. The $\\boldsymbol{Q}_{\\mathsf{S C}}$ of a VHB-STENG at initial state and different stretched states. \nfig. S14. Stretching cycling test of the STENG. \nfig. S15. Battery charging by the STENG. fig. S16. The difference between the $V_{\\mathrm{OC}}$ and the voltage across the resistor. \nfig. S17. Temperature effect on the sensing properties of the STENG. \nfig. S18. Voltages of the 9 pixels when pressing the sensor matrix with a z-shaped acrylic plate. \nmovie S1. Hand-tapping energy harvesting of a VHB-STENG at initial state. \nmovie S2. Hand-tapping energy harvesting of a VHB-STENG at stretched state. \nmovie S3. Powering an LCD screen by a transparent VHB-STENG. \nmovie S4. Powering an electronic watch with the energy converted from hand tapping by a PDMS-STENG. \n\n# REFERENCES AND NOTES \n\n1. B. Tian, T. Cohen-Karni, Q. Qing, X. Duan, P. Xie, C. M. Lieber, Three-dimensional, flexible nanoscale field-effect transistors as localized bioprobes. Science 329, 830–834 (2010). \n2. T. Sekitani, U. Zschieschang, H. Klauk, T. Someya, Flexible organic transistors and circuits with extreme bending stability. Nat. Mater. 9, 1015–1022 (2010). \n3. D.-H. Kim, J.-H. Ahn, W. M. Choi, H.-S. Kim, T.-H. Kim, J. Song, Y. Y. Huang, Z. Liu, C. Lu, J. A. Rogers, Stretchable and foldable silicon integrated circuits. Science 320, 507–511 (2008). \n4. D.-m. Sun, M. Y. Timmermans, Y. Tian, A. G. Nasibulin, E. I. Kauppinen, S. Kishimoto, T. Mizutani, Y. Ohno, Flexible high-performance carbon nanotube integrated circuits. Nat. Nanotechnol. 6, 156–161 (2011). \n5. M. S. White, M. Kaltenbrunner, E. D. Glowacki, K. Gutnichenko, G. Kettlgruber, I. Graz, S. Aazou, C. Ulbricht, D. A. M. Egbe, M. C. Miron, Z. Major, M. C. Scharber, T. Sekitani, T. Someya, S. Bauer, N. S. Sariciftci, Ultrathin, highly flexible and stretchable PLEDs. Nat. Photonics 7, 811–816 (2013). \n6. J. Liang, L. Li, X. Niu, Z. Yu, Q. Pei, Elastomeric polymer light-emitting devices and displays. Nat. Photonics 7, 817–824 (2013). \n7. L. Zhou, A. Wanga, S.-C. Wu, J. Sun, S. Park, T. N. Jackson, All-organic active matrix flexible display. Appl. Phys. Lett. 88, 083502 (2006). \n8. S. C. B. Mannsfeld, B. C.-K. Tee, R. M. Stoltenberg, C. V. H.-H. Chen, S. Barman, B. V. O. Muir, A. N. Sokolov, C. Reese, Z. Bao, Highly sensitive flexible pressure sensors with microstructured rubber dielectric layers. Nat. Mater. 9, 859–864 (2010). \n9. A. Chortos, J. Liu, Z. Bao, Pursuing prosthetic electronic skin. Nat. Mater. 15, 937–950 (2016). \n10. D.-H. Kim, N. Lu, R. Ma, Y.-S. Kim, R.-H. Kim, S. Wang, J. Wu, S. M. Won, H. Tao, A. Islam, K. J. Yu, T.-i. Kim, R. Chowdhury, M. Ying, L. Xu, M. Li, H.-J. Chung, H. Keum, M. McCormick, P. Liu, Y.-W. Zhang, F. G. Omenetto, Y. Huang, T. Coleman, J. A. Rogers, Epidermal electronics. Science 333, 838–843 (2011). \n11. C. Keplinger, J.-Y. Sun, C. C. Foo, P. Rothemund, G. M. Whitesides, Z. Suo, Stretchable, transparent, ionic conductors. Science 341, 984–987 (2013). \n12. C.-C. Kim, H.-H. Lee, K. H. Oh, J.-Y. Sun, Highly stretchable, transparent ionic touch panel. Science 353, 682–687 (2016). \n13. F.-R. Fan, Z.-Q. Tian, Z. L. Wang, Flexible triboelectric generator. Nano Energy 1, 328–334 (2012). \n14. F. R. Fan, W. Tang, Z. L. Wang, Flexible nanogenerators for energy harvesting and selfpowered electronics. Adv. Mater. 28, 4283–4305 (2016). \n15. H. Wu, Y. Huang, F. Xu, Y. Duan, Z. Yin, Energy harvesters for wearable and stretchable electronics: From flexibility to stretchability. Adv. Mater. 28, 9881–9919 (2016). \n16. R. Hinchet, W. Seung, S.-W. Kim, Recent progress on flexible triboelectric nanogenerators for selfpowered electronics. ChemSusChem 8, 2327–2344 (2015). \n17. Z. Zhao, X. Pu, C. Du, L. Li, C. Jiang, W. Hu, Z. L. Wang, Freestanding flag-type triboelectric nanogenerator for harvesting high-altitude wind energy from arbitrary directions. ACS Nano 10, 1780–1787 (2016). \n18. Z. L. Wang, Triboelectric nanogenerators as new energy technology for self-powered systems and as active mechanical and chemical sensors. ACS Nano 7, 9533–9557 (2013). \n19. U. Khan, S.-W. Kim, Triboelectric nanogenerators for blue energy harvesting. ACS Nano 10, 6429–6432 (2016). \n20. X. Pu, W. Song, M. Liu, C. Sun, C. Du, C. Jiang, X. Huang, D. Zou, W. Hu, Z. L. Wang, Wearable power‐textiles by integrating fabric triboelectric nanogenerators and fiber‐shaped dye‐sensitized solar cells. Adv. Energy Mater. 6, 1601048 (2016). \n21. Y. Yu, H. Sun, H. Orbay, F. Chen, C. G. England, W. Cai, X. Wang, Biocompatibility and in vivo operation of implantable mesoporous PVDF-based nanogenerators. Nano Energy 27, 275–281 (2016). \n22. X. Pu, L. Li, M. Liu, C. Jiang, C. Du, Z. Zhao, W. Hu, Z. L. Wang, Wearable self-charging power textile based on flexible yarn supercapacitors and fabric nanogenerators. Adv. Mater. 28, 98–105 (2016). \n23. Y.-C. Lai, J. Deng, S. Niu, W. Peng, C. Wu, R. Liu, Z. Wen, Z. L. Wang, Electric eel-skin-inspired mechanically durable and super-stretchable nanogenerator for deformable power source and fully autonomous conformable electronic-skin applications. Adv. Mater. 28, 10024–10032 (2016). and waterproof of self-charging power system for harvesting energy from diverse deformation and powering wearable electronics. ACS Nano 10, 6519–6525 (2016). \n25. F. Yi, L. Lin, S. Niu, P. K. Yang, Z. Wang, J. Chen, Y. Zhou, Y. Zi, J. Wang, Q. Liao, Y. Zhang, Z. L. Wang, Stretchable‐rubber‐based triboelectric nanogenerator and its application as self‐powered body motion sensors. Adv. Funct. Mater. 25, 3688–3696 (2015). \n26. B.-U. Hwang, J.-H. Lee, T. Q. Trung, E. Roh, D.-I. Kim, S.-W. Kim, N.-E. Lee, Transparent stretchable self-powered patchable sensor platform with ultrasensitive recognition of human activities. ACS Nano 9, 8801–8810 (2015). \n27. K. N. Kim, J. Chun, J. W. Kim, K. Y. Lee, J.-U. Park, S.-W. Kim, Z. L. Wang, J. M. Baik, Highly stretchable 2D fabrics for wearable triboelectric nanogenerator under harsh environments. ACS Nano 9, 6394–6400 (2015). \n28. X. Chen, X. Pu, T. Jiang, A. Yu, L. Xu, Z. L. Wang, Tunable optical modulator by coupling a triboelectric nanogenerator and a dielectric elastomer. Adv. Funct. Mater. 27, 1603788 (2016). \n29. F. Yi, X. Wang, S. Niu, S. Li, Y. Yin, K. Dai, G. Zhang, L. Lin, Z. Wen, H. Guo, J. Wang, M.-H. Yeh, Y. Zi, Q. Liao, Z. You, Y. Zhang, Z. L. Wang, A highly shape-adaptive, stretchable design based on conductive liquid for energy harvesting and self-powered biomechanical monitoring. Sci. Adv. 2, e1501624 (2016). \n30. J.-Y. Sun, X. Zhao, W. R. K. Illeperuma, O. Chaudhuri, K. H. Oh, D. J. Mooney, J. J. Vlassak, Z. Suo, Highly stretchable and tough hydrogels. Nature 489, 133–136 (2012). \n31. J.-Y. Sun, C. Keplinger, G. M. Whitesides, Z. Suo, Ionic skin. Adv. Mater. 26, 7608–7614 (2014). \n32. C. H. Yang, B. Chen, J. Zhou, Y. M. Chen, Z. Suo, Electroluminescence of giant stretchability. Adv. Mater. 28, 4480–4484 (2016). \n33. F.-R. Fan, L. Lin, G. Zhu, W. Wu, R. Zhang, Z. L. Wang, Transparent triboelectric nanogenerators and self-powered pressure sensors based on micropatterned plastic films. Nano Lett. 12, 3109–3114 (2012). \n34. S. Kim, M. K. Gupta, K. Y. Lee, A. Sohn, T. Y. Kim, K.-S. Shin, D. Kim, S. K. Kim, K. H. Lee, H.-J. Shin, D.-W. Kim, S.-W. Kim, Transparent flexible graphene triboelectric nanogenerators. Adv. Mater. 26, 3918–3925 (2014). \n35. Q. Liang, X. Yan, Y. Gu, K. Zhang, M. Liang, S. Lu, X. Zheng, Y. Zhang, Highly transparent triboelectric nanogenerator for harvesting water-related energy reinforced by antireflection coating. Sci. Rep. 5, 9080 (2015). \n36. K. Y. Lee, M. K. Gupta, S.-W. Kim, Transparent flexible stretchable piezoelectric and triboelectric nanogenerators for powering portable electronics. Nano Energy 14, 139–160 (2015). \n37. S. Niu, Z. L. Wang, Theoretical systems of triboelectric nanogenerators. Nano Energy 14, 161–192 (2015). \n38. K. H. Lee, M. S. Kang, S. Zhang, Y. Gu, T. P. Lodge, C. D. Frisbie, “Cut and stick” rubbery ion gels as high capacitance gate dielectrics. Adv. Mater. 24, 4457–4462 (2012). \n39. S. Niu, Y. Liu, S. Wang, L. Lin, Y. S. Zhou, Y. Hu, Z. L. Wang, Theoretical investigation and structural optimization of single‐electrode triboelectric nanogenerators. Adv. Funct. Mater. 24, 3332–3340 (2014). \n40. D. K. Davies, Charge generation on dielectric surfaces. J. Phys. D Appl. Phys. 2, 1533 (1969). \n41. X. Wen, Y. Su, Y. Yang, H. Zhang, Z. L. Wang, Applicability of triboelectric generator over a wide range of temperature. Nano Energy 4, 150–156 (2014). \n42. J. Park, S. Choi, A. H. Janardhan, S.-Y. Lee, S. Raut, J. Soares, K. Shin, S. Yang, C. Lee, K.-W. Kang, H. R. Cho, S. J. Kim, P. Seo, W. Hyun, S. Jung, H.-J. Lee, N. Lee, S. H. Choi, M. Sacks, N. Lu, M. E. Josephson, T. Hyeon, D.-H. Kim, H. J. Hwang, Electromechanical cardioplasty using a wrapped elasto-conductive epicardial mesh. Sci. Transl. Med. 8, 344ra86 (2016). \n43. H. Yuk, T. Zhang, G. A. Parada, X. Liu, X. Zhao, Skin-inspired hydrogel–elastomer hybrids with robust interfaces and functional microstructures. Nat. Commun. 7, 12028 (2016). \n44. H. Yuk, T. Zhang, S. Lin, G. A. Parada, X. Zhao, Tough bonding of hydrogels to diverse non-porous surfaces. Nat. Mater. 15, 190–196 (2016). \n45. X. Wang, H. Zhang, L. Dong, X. Han, W. Du, J. Zhai, C. Pan, Z. L. Wang, Self‐powered high‐ resolution and pressure‐sensitive triboelectric sensor matrix for real‐time tactile mapping. Adv. Mater. 28, 2896–2903 (2016). \n46. S. W. Chen, X. Cao, N. Wang, L. Ma, H. R. Zhu, M. Willander, Y. Jie, Z. L. Wang, An ultrathin flexible single‐electrode triboelectric‐nanogenerator for mechanical energy harvesting and instantaneous force sensing. Adv. Energy Mater. 7, 1601255 (2017). \n47. L. Pan, A. Chortos, G. Yu, Y. Wang, S. Isaacson, R. Allen, Y. Shi, R. Dauskardt, Z. Bao, An ultra-sensitive resistive pressure sensor based on hollow-sphere microstructure induced elasticity in conducting polymer film. Nat. Commun. 5, 3002 (2014). \n48. J. Kim, M. Lee, H. J. Shim, R. Ghaffari, H. R. Cho, D. Son, Y. H. Jung, M. Soh, C. Choi, S. Jung, K. Chu, D. Jeon, S.-T. Lee, J. H. Kim, S. H. Choi, T. Hyeon, D.-H. Kim, Stretchable silicon nanoribbon electronics for skin prosthesis. Nat. Commun. 5, 5747 (2014). \n49. Z. L. Wang, Towards self‐powered nanosystems: From nanogenerators to nanopiezotronics. Adv. Funct. Mater. 18, 3553–3567 (2008). \n50. X. Pu, L. Li, H. Song, C. Du, Z. Zhao, C. Jiang, G. Cao, W. Hu, Z. L. Wang, A self-charging power unit by integration of a textile triboelectric nanogenerator and a flexible lithiumion battery for wearable electronics. Adv. Mater. 27, 2472–2478 (2015). \n51. Q. Zheng, B. Shi, F. Fan, X. Wang, L. Yan, W. Yuan, S. Wang, H. Liu, Z. Li, Z. L. Wang, In vivo powering of pacemaker by breathing-driven implanted triboelectric nanogenerator. Adv. Mater. 26, 5851–5856 (2014). \n\nperformed measurements. X.P., M.L., W.H., and Z.L.W. analyzed the experimental data, drew the figures, and prepared the manuscript. All authors discussed the results and wrote and commented on the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\n# Acknowledgments \n\nFunding: This study was supported by the “Thousands Talents” program for pioneer researcher and his innovation team, China, National Natural Science Foundation of China (grant nos. 51432005, 61574018, and 51603013), the Youth Innovation Promotion Association of Chinese Academy of Science, the “Hundred Talents Program” of the Chinese Academy of Science, and the National Key Research and Development Program of China (2016YFA0202703). Author contributions: X.P. conceived the idea and designed the experiment. W.H. and Z.L.W. guided the project. X.P. and M.L. fabricated the devices and \n\nSubmitted 20 January 2017 \nAccepted 31 March 2017 \nPublished 31 May 2017 \n10.1126/sciadv.1700015 \n\nCitation: X. Pu, M. Liu, X. Chen, J. Sun, C. Du, Y. Zhang, J. Zhai, W. Hu, Z. L. Wang, Ultrastretchable, transparent triboelectric nanogenerator as electronic skin for biomechanical energy harvesting and tactile sensing. Sci. Adv. 3, e1700015 (2017). \n\n# Ultrastretchable, transparent triboelectric nanogenerator as electronic skin for biomechanical energy harvesting and tactile sensing \n\nXiong Pu, Mengmeng Liu, Xiangyu Chen, Jiangman Sun, \nChunhua Du, Yang Zhang, Junyi Zhai, Weiguo Hu and Zhong Lin Wang (May 31, 2017) \nSci Adv 2017, 3:. \ndoi: 10.1126/sciadv.1700015 \n\nThis article is publisher under a Creative Commons license. The specific license under which this article is published is noted on the first page. \n\nFor articles published under CC BY licenses, you may freely distribute, adapt, or reuse the article, including for commercial purposes, provided you give proper attribution. \n\nFor articles published under CC BY-NC licenses, you may distribute, adapt, or reuse the article for non-commerical purposes. Commercial use requires prior permission from the American Association for the Advancement of Science (AAAS). You may request permission by clicking here. \n\nThe following resources related to this article are available online at http://advances.sciencemag.org. (This information is current as of May 31, 2017): \n\nUpdated information and services, including high-resolution figures, can be found in the \nonline version of this article at: \nhttp://advances.sciencemag.org/content/3/5/e1700015.full \n\nSupporting Online Material can be found at: http://advances.sciencemag.org/content/suppl/2017/05/26/3.5.e1700015.DC1 \n\nThis article cites 51 articles, 7 of which you can access for free at: http://advances.sciencemag.org/content/3/5/e1700015#BIBL " + }, + { + "id": "10.1038_ncomms14956", + "DOI": "10.1038/ncomms14956", + "DOI Link": "http://dx.doi.org/10.1038/ncomms14956", + "Relative Dir Path": "mds/10.1038_ncomms14956", + "Article Title": "Prediction of intrinsic two-dimensional ferroelectrics in In2Se3 and other III2-VI3 van der Waals materials", + "Authors": "Ding, WJ; Zhu, JB; Wang, Z; Gao, YF; Xiao, D; Gu, Y; Zhang, ZY; Zhu, WG", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Interest in two-dimensional (2D) van der Waals materials has grown rapidly across multiple scientific and engineering disciplines in recent years. However, ferroelectricity, the presence of a spontaneous electric polarization, which is important in many practical applications, has rarely been reported in such materials so far. Here we employ first-principles calculations to discover a branch of the 2D materials family, based on In2Se3 and other III2-VI3 van der Waals materials, that exhibits room-temperature ferroelectricity with reversible spontaneous electric polarization in both out-of-plane and in-plane orientations. The device potential of these 2D ferroelectric materials is further demonstrated using the examples of van der Waals heterostructures of In2Se3/graphene, exhibiting a tunable Schottky barrier, and In2Se3/WSe2, showing a significant band gap reduction in the combined system. These findings promise to substantially broaden the tunability of van der Waals heterostructures for a wide range of applications.", + "Times Cited, WoS Core": 1055, + "Times Cited, All Databases": 1128, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000398455400001", + "Markdown": "# Prediction of intrinsic two-dimensional ferroelectrics in In2Se3 and other III2-VI3 van der Waals materials \n\nWenjun Ding1,2,3,\\*, Jianbao $Z\\mathsf{h u}^{1,2,3,4,\\star}$ Zhe Wang $\\cdot^{1,2,3,\\star}$ , Yanfei $\\mathsf{G a o}^{5,6}$ , Di Xiao7, Yi ${\\mathsf{G u}}^{8}$ Zhenyu Zhang2 \n& Wenguang Zhu1,2,3 \n\nInterest in two-dimensional (2D) van der Waals materials has grown rapidly across multiple scientific and engineering disciplines in recent years. However, ferroelectricity, the presence of a spontaneous electric polarization, which is important in many practical applications, has rarely been reported in such materials so far. Here we employ first-principles calculations to discover a branch of the 2D materials family, based on $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ and other $\\ensuremath{\\vert\\vert\\vert}_{2}\\mathrm{-}\\ensuremath{\\mathsf{V}\\vert}_{3}$ van der Waals materials, that exhibits room-temperature ferroelectricity with reversible spontaneous electric polarization in both out-of-plane and in-plane orientations. The device potential of these 2D ferroelectric materials is further demonstrated using the examples of van der Waals heterostructures of $\\mathsf{I n}_{2}\\mathsf{S e}_{3}/\\mathrm{2}$ graphene, exhibiting a tunable Schottky barrier, and $\\mathsf{I n}_{2}\\mathsf{S e}_{3}/\\mathsf{W}\\mathsf{S e}_{2},$ showing a significant band gap reduction in the combined system. These findings promise to substantially broaden the tunability of van der Waals heterostructures for a wide range of applications. \n\nFrearmrnoegrel contfr tcieotcfyh,napolponrgtoiacpnaelr uayspopefll cmatraiitocenrsip,a sauraicszhsa icaoisa endhoanswviatohlwatiihdle memories, field effect transistors and sensors1,2. Previous studies of ferroelectric materials have mainly focused on complex oxides, such as $\\mathrm{ABO}_{3}$ perovskite compounds3. Driven by technological demand for device miniaturization, exploration of the ferroelectric properties of perovskite thin films has been made more intensively1,4,5. Separately, a rapidly increasing number of two-dimensional (2D) van der Waals materials have been discovered, exhibiting a rich variety of emergent physical properties6–10. These developments in principle may offer new and alternative opportunities for realizing ferroelectricity in the ultimate single-layer regime11,12, especially with regard to the most technologically relevant polarizability perpendicular to the film direction. \n\nThe existence of 2D ferroelectricity was predicted long time ago based on an idealized Ising model13, but realistic materials normally suffer from the fundamental constraint that ferroelectricity would disappear when the film thickness is below a critical value, due to the effects of surface energy, depolarizing electrostatic field and electron screening4,5,14–16. In general, the emergence of electric polarization demands breaking of the structural centrosymmetry in the polarization direction. Yet in the pristine structures of all known 2D materials including the well-known graphene and transition-metal dichalcogenides, the projections of their atomic positions on the out-of-plane axis are exclusively centrosymmetric, seemingly excluding any possible out-of-plane polarization. \n\nHere we present the discovery of a class of stable single-layer 2D ferroelectric materials based on III–VI compounds in the form of $\\ensuremath{\\mathrm{III}_{2}}\\mathrm{-}\\ensuremath{\\mathrm{VI}_{3}}$ . Using first-principles density-function theory (DFT) calculations, we reveal that the ground state structures of an intrinsic prototypical $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ quintuple layer (QL) possess both spontaneous out-of-plane and in-plane electric polarization, which can be reversed via laterally shifting the central Se layer through readily accessible kinetic pathways with the assistance of a modest out-of-plane or in-plane electric field. Furthermore, we demonstrate tunability in the Schottky barrier height within an $\\mathrm{In}_{2}\\mathrm{Se}_{3}/$ graphene junction and a significant band gap reduction in the van der Waals heterostructure of $\\mathrm{In}_{2}\\mathrm{Se}_{3}/\\mathrm{W}\\bar{\\mathrm{Se}_{2}}$ , in each case achieved by reversing the out-of-plane polarity of the $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ layer. These findings effectively classify the well-known $\\ensuremath{\\mathrm{III}}_{2}\\ensuremath{-}\\ensuremath{\\mathrm{VI}_{3}}$ compounds actually as the long-sought 2D ferroelectric materials. \n\n# Results \n\nStructures of $\\mathbf{In}_{2}\\mathbf{Se}_{3}$ layered phases. Before exploring the ferroelectric properties, we first systematically examine the detailed structures of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ . Bulk $\\mathrm{In}_{2}\\mathrm{\\dot{S}e}_{3}$ has been shown to exist in two layered crystalline phases named $\\alpha$ and $\\beta$ (refs 17,18), formed by vertical stacking of two different types of covalently bonded 2D $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ QLs via weak van der Waals interactions (Fig. 1a,b). The van der Waals nature of the inter-QL force is supported by earlier experimental observations that few-layer $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ samples can be obtained by exfoliation19,20 or chemical vapour deposition21. Each atomic layer in a QL contains only one elemental species, with the atoms in a given layer arranged in a triangular lattice. The five atomic layers in a QL then stack in the sequence of Se-In-Se-In-Se atomic layers. Despite extensive experimental studies of the bulk structures, the precise alignments of the atomic layers within the a and b phases are still controversial17–19,21–23. \n\nIn this study, as prerequisites we employed DFT calculations to explore all possible atomic configurations (Fig. 1c–h and Supplementary Fig. 1) within a $\\mathrm{QL,}$ including the ones derived from the most-common crystal structures, such as zincblende, wurtzite and face-centred cubic (fcc). From the calculated total energy versus lattice constant for each structure (Supplementary Fig. 2), we find that none of the zincblende, wurtzite or fcc structures is stable. In either the zincblende (ABBCC) or wurtzite (ABBAA) structure shown in Fig. 1c,d, the top of the QL terminates with a Se layer sitting on top of a second In layer, with each Se atop atom forming a single Se–In covalent bond. These high-energy structures can be substantially stabilized when the Se atoms in the top layer execute a lateral structural collective shift, leading to two energetically degenerate ground state structures, \n\n![](images/3a4896c10896908f02e7e9b327410daf3eb323af2a3501d723dc207db6e5c675.jpg) \nFigure 1 | Layered structures of $\\ln_{2}S_{e_{3}}$ . (a) Three-dimensional crystal structure of layered $\\mathsf{I n}_{2}\\mathsf{S e}_{3},$ , with the In atoms in blue and Se atoms in red, and a quintuple layer (QL) is indicated by the black dashed square. (b) Top view of the system along the vertical direction. Each atomic layer in a QL contains only one elemental species, with the atoms arranged in one of the triangular lattices A, B or C as illustrated. (c–h) Side views of several representative structures of one QL $\\mathsf{I n}_{2}\\mathsf{S e}_{3},$ , among which the $c-e$ structures are derived from the zincblende, wurtzite and fcc crystals, respectively. In f, the interlayer spacings between the central Se layer and the two neighbouring In layers are displayed. The black arrows in $\\mathbf{f},\\mathbf{g}$ indicate the directions of the spontaneous electric polarization (P) in the $F E-Z B^{\\prime}$ and FE-WZ0 structures, respectively. \n\n![](images/8d9e33543ef0510ba9074fe8a7ce9389074a2a0df4b429231872d26bd03b61cd.jpg) \nFigure 2 | Kinetics pathways of polarization reversal processes. (a) Evolution of the total energy (y axis) of 1 quintuple layer (QL) $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ in the $F E-Z B^{\\prime}$ phase transforming from the state with the electric polarization pointing downward (left) to the state with the electric polarization pointing upward (right) via a direct shifting process: the Se atoms in the central layer laterally shift from the B to C sites. The green arrows attached to atoms indicate the directions of atomic motion during the polarization reversal processes, which are in the plane perpendicular to the $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ layer and passing through the green dashed line as shown in the top view. $(\\pmb{6})$ Energy profile of the most effective kinetic pathway to reverse the orientation of the electric polarization of one QL $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ in the FE- $\\cdot\\angle B^{\\prime}$ phase involving a three-step concerted mechanism, as detailed in the main text. The activation barrier of the concerted motion is lower than the direct shifting process by an order of magnitude (note that the height of the barrier shown in a is scaled down by a factor of 10). \n\nFE- $\\mathrm{\\cdot}Z\\mathrm{B^{\\prime}}$ (ABBCA) and FE-WZ0 (ABBAC) (Fig. 1f,g), with the total heights of one QL around $6.8\\mathring\\mathrm{A}$ . The dynamical and thermal stability of each of the two structures is further examined by calculating the phonon band structures (Supplementary Fig. 4a,b), confirming the absence of imaginary phonon modes, and ab initio molecular dynamic simulations (Supplementary Fig. 5). In addition, we find that the highly symmetric fcc (ABCAB) structure (Fig. 1e) is unstable, and a metastable structure, fcc0, can be derived by shifting the central Se layer slightly away from the ideal fcc positions (Fig. 1h). The total energy of this metastable fcc0 structure is $0.057\\mathrm{eV}$ per unit cell higher than the two degenerate ground state structures. The most stable FE- $\\mathrm{\\cdot}Z\\mathrm{B^{\\prime}}$ and FE-WZ0 and the metastable fcc0 structures are all semiconductors. Their calculated band structures are provided in Supplementary Fig. 6. \n\nBased on the structural results presented above, we also obtain that the two degenerate ground states of $\\mathrm{FE-ZB^{\\prime}}$ and FE-WZ0 have an in-plane lattice constant of 4.106 and $4.108\\mathring{\\mathrm{A}}$ , respectively, while the metastable state of $\\operatorname{fcc}^{\\prime}$ has an in-plane lattice constant of $4.048\\mathring\\mathrm{A}$ . When compared with the experimentally measured lattice constants, we identify the ground states to be the $\\alpha$ phase, while the $\\operatorname{fcc}^{\\prime}$ state to be the $\\dot{\\boldsymbol{{\\beta}}}$ phase19,22. Furthermore, our detailed calculations confirm that the experimentally observed Raman active A1 mode undergoes a blue shift when the $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ structure transforms from the $\\alpha$ phase to the $\\beta$ phase (Supplementary Fig. 4)19,24. Additionally, we note that the metastable nature of the $\\beta$ phase is consistent with the experimental observation that it is reached at higher temperature from the $\\boldsymbol{\\mathfrak{a}}$ phase through a structural phase transition17,25. In contrast, in a related recent DFT study, only one ground state was considered for the $\\alpha$ phase, while the energetically higher fcc phase was identified to be the $\\beta$ phase26. \n\n![](images/f00e37147752e35aed44b1e4cf6af41a53e0e0c8668e63d73b7ccc63056d0330.jpg) \nFigure 3 | Effects of external electric fields. The calculated activation barrier (black circles) and energy difference (grey squares) between the initial and final states (the insets) in the electric polarization reversal process of 1 quintuple layer $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ via the concerted motion as illustrated in Fig. 2b, plotted as a function of the external electric field applied in the out-of-plane direction (a) and in-plane [110] direction $(\\pmb{6})$ , respectively. The directions of the applied external electric fields are indicated by the blue arrows in the insets. \n\nFerroelectric nature of $\\mathbf{In}_{2}\\mathbf{Se}_{3}$ . Next, we turn to the key prediction that each of the degenerate ground-state structures of the $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ QL is an intrinsic 2D ferroelectric material with both out-of-plane and in-plane electric polarization. As shown in Fig. $\\mathrm{1f,g,}$ the Se atoms in both the top and the bottom surface layers reside on the hollow sites of the respective second-layer In atoms, while each atom in the central Se layer is tetrahedrally coordinated by the two neighbouring In layers, with one Se–In bond connecting to one side vertically and three Se–In bonds to the other side. As a result, the interlayer spacing between the central Se layer and the two In layers is dramatically different, effectively breaking the centrosymmetry and providing the very underlying basis for the emergence of the spontaneous out-of-plane electric polarization. The calculated magnitudes of the electric dipoles for one QL $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ in the degenerate ground states are both around 0.11 eÅ per unit cell (calculated by HSE06, 0.094 eÅ per unit cell by generalized gradient approximationPerdew-Burke-Ernzerhof (GGA-PBE)). In addition, each groundstate structure hosts two equivalent states with opposite electric polarizations, which only differ by the energetically degenerate positions of the central Se-layer atoms. Specifically, in the $\\mathrm{FE-ZB^{\\prime}}$ structure illustrated in Fig. 2a, the atoms in the central Se layer are at the B sites vertically aligned with the lower In layer (left in Fig. 2a), and the resultant electric dipole points downwards; by moving the central Se layer to the neighbouring C sites aligned with the upper In layer (right in Fig. 2a), the resultant electric dipole points upwards. In addition, the $\\boldsymbol{\\mathfrak{a}}$ -phase $\\mathrm{FE-ZB^{\\prime}}$ and FE-WZ0 structures also have in-plane electric polarization due to the in-plane centrosymmetry breaking. The in-plane electric polarization is along the [110] direction defined by the lattice vectors as illustrated in the insets of Fig. 3b. The magnitude of the in-plane electric polarization is calculated to be 2.36 and $7.13\\mathrm{e}\\mathring{\\mathrm{A}}$ per unit cell for the $\\mathrm{FE-ZB^{\\prime}}$ and FE-WZ0 phases, respectively, using the Berry phase approach. This difference can be attributed to the ions that make the two structures deviate from the non-polar reference structure possessing different numbers of charge, as illustrated in Supplementary Fig. 10a. \n\nA critical issue for ultrathin ferroelectric materials is the depolarization effect. It is known that the ferroelectricity of conventional ferroelectric thin films is usually suppressed, as the films are thinner than a critical thickness due to the effects of a depolarizing field induced by uncompensated charges in the presence of metal electrodes4,5,14,15. To examine the influence of the depolarizing field on the stability of the ferroelectric phase of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ , we performed calculations with supercells containing one QL of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ sandwiched between two graphite electrodes in short-circuit, as illustrated in Supplementary Fig. 7a,b for the $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ layer in the ferroelectric FE- $\\bar{\\cdot}\\mathrm{ZB^{\\prime}}$ phase and non-polar $\\operatorname{fcc}^{\\prime}$ phase, respectively. A detailed description of the calculations is provided in Supplementary Note 1. The calculated results confirm that the depolarization effects only slightly reduce the energy difference between the two phases of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ , and the $\\mathrm{FE-Z{\\bar{B}}^{\\prime}}$ phase is still more stable than the non-polar fcc0 phase. The electrostatic potential plot, shown in Supplementary Fig. 7c, also indicates that the built-in electric field within the ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ layer still exists in the presence of the graphite electrodes. All these results predict a realistic material system that is energetically stable and possesses 2D ferroelectricity with out-of-plane electric polarization at the single-layer limit. \n\nFor multilayer $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ films, their net polarization increases as a function of the film thickness and saturates as the thickness is above two QLs, in the cases that the polarization of all the ferroelectric QLs is aligned along the same orientation at each thickness. Detailed calculation results and discussions are provided in Supplementary Fig. 8 and Supplementary Note 2. \n\nIt is known that all ferroelectric materials are also piezoelectric and pyroelectric. We have investigated the piezoelectric property of a single QL of ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ by calculating the variation of the electric dipole as a function of the in-plane lattice deformation (Supplementary Fig. 9a) and the height variation as a function of an external electric displacement field applied in the vertical direction (Supplementary Fig. 9b). The results indicate that the compressive strain has a more significant effect on the electric polarization than the tensile strain. In particular, a tensile strain can slightly enhance the dipole moment of the ferroelectric layer. Furthermore, the electric-field-induced height variation in one QL ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ is very small, on the order of $10^{-3}\\mathring{\\mathrm{A}}$ at the electric displacement field as large as $0.2\\mathrm{V}\\mathring{\\mathrm{A}}^{-1}$ , which would be challenging to be resolved by piezoresponse force microscopy. \n\n![](images/bbd5968c2eb38fb1cc2556c4cd5058226898e1c45978f023809b87592b600d67.jpg) \nFigure 4 | Kinetic pathways of domain wall motion. Initial states containing four possible domain wall structures between two ferroelectric domains of one quintuple layer $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ in the FE- $Z B^{\\prime}$ phase with opposite electric polarizations are shown in a,b (at the bottom centre), along with the energy profiles, final states (at the bottom left and right), and transition states (at the top) of the kinetic pathways involved in the motion of the domain walls. The black dashed squares indicate the positions of the domain walls. \n\nKinetics of polarization reversal. To further demonstrate the ferroelectric nature of the systems, we must show that the direction of the electric polarization can be readily reversed by the application of a physically realistic electric field. We address this issue in two stages: first, we identify the most effective kinetic pathway connecting the two degenerates states with different polarities in the absence of an electric field; secondly, we investigate the effect of an external electric field on further reduction of the activation barrier along the pathway. \n\nAs a brute force check in the first stage, we find that the activation barrier against direct shifting of the central Se layer is $0.85\\mathrm{eV}$ per unit cell, as shown in Fig. 2a. More importantly, an alternative process with a significantly lower activation barrier to reverse the electric polarization is revealed via a three-step concerted motion of the upper three Se-In-Se layers, as illustrated in Fig. 2b. In the first step, the $\\boldsymbol{\\mathfrak{a}}$ -phase $\\mathrm{FE-ZB^{\\prime}}$ structure transforms into the metastable $\\beta$ -phase fcc0 structure by laterally shifting the top three atomic layers together along the same direction to neighbouring sites. In the second step, the central Se atoms rotates around the $\\mathsf{C}$ sites by $60^{\\circ}$ to a degenerate fcc0 structure. In the third step, only the top two layers laterally shift along a direction that is rotated away from the original shifting direction by $60^{\\circ}$ , finally reaching an equivalent FE- $\\bar{Z}\\mathrm{B}^{\\prime}$ structure, but now with the electric polarization reversed. The overall activation barrier of this concerted process is much lower, with the highest barrier to be only $0.066\\mathrm{eV}$ per unit cell along the first step, comparable to that of the popular ferroelectric material ${\\mathrm{Pb}}{\\mathrm{{TiO}}}_{3}$ (ref. 27). \n\nIn the second stage, we examine how the application of a perpendicular electric field reduces the kinetic barrier by lifting the degeneracy of the two polarized states. Our detailed calculations show that the activation barrier associated with the three-step concerted mechanism decreases linearly with the electric displacement field in the range of the field strength less than $0.3\\mathrm{V}\\dot{\\mathrm{A}}^{-1}$ (Fig. 3a). It is worthwhile to note that the electric field induces much more dramatic variation in the energy difference between the two oppositely polarized states than in the activation barrier. As shown in Fig. 3a, an electric displacement field of $0.3\\mathrm{V}\\mathring{\\mathrm{A}}^{-1}$ gives rise to an energy difference as large as $0.056\\mathrm{eV}$ per unit cell, which is expected to result in a nearly ten times population difference of the two oppositely polarized states at room temperature. Moreover, for a ferroelectric domain of a practical device, the energy difference between the two polarized states is proportional to the domain size. Therefore, the population difference increases exponentially with the domain size. Although the activation barrier is also proportional to the domain size, given the relatively small activation barrier of $0.066\\mathrm{eV}$ per unit cell, it is still possible to have an optimal domain size that gives rise to not only a sufficiently large energy difference to drive the reversal of the electric polarization but also a moderate activation barrier to make the kinetic process accessible at room temperature. Experimentally, an electric displacement field as large as $0.3\\mathrm{V}\\mathring{\\mathrm{A}}^{-1}$ had been demonstrated previously, for example, to open a sizable band gap in bilayer graphene28, which is expected to have a lower electric breakdown voltage than the present systems. In addition, it is important to point out that the reversal of the out-of-plane electric polarization accompanies with the reversal of the in-plane electric polarization for the FE- $\\mathrm{\\cdot}Z\\mathrm{B^{\\prime}}$ phase, as illustrated in Fig. 3b. We also examine the effects of the application of an in-plane electric field on the kinetics of the electric polarization reversal process. The calculated results, as summarized in Fig. 3b, indicate that an in-plane electric field of $0.03\\mathrm{V}\\mathring{\\mathrm{A}}^{-1}$ applied in the [110] direction gives rise to an energy difference as large as $0.142\\mathrm{eV}$ per unit cell between the two oppositely polarized states, which is expected to result in a more than 200 times population difference of the two oppositely polarized states at room temperature. These features may offer an alternative approach to switch the orientation of the out-of-plane polarization by the application of an in-plane electric field. \n\n![](images/e14ca0b4f841e6168c8d484860d0fc8924270adb113ba9ffd730c9e9c9b5d61a.jpg) \nFigure 5 | Electronic structures of $\\ln_{2}S_{e_{3}}$ -based heterostructures. (a) Electronic band structure of one quintuple layer (QL) ferroelectric $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ in the $F E-Z B^{\\prime}$ phase (calculated by HSE06); here the inset shows the first Brillouin zone with the high symmetric points of $\\Gamma,$ M and K indicated. (b–e) Demonstration of a tunable Schottky barrier at the interface of a one QL FE- $\\cdot\\angle B^{\\prime}$ $\\ensuremath{\\vert{\\mathsf{n}}_{2}{\\mathsf{S e}}_{3}}/$ graphene heterostructure. (b,d) The side views of the heterostructure. The corresponding electronic band structures are shown in c,e (calculated by GGA-PBE). The bands derived from the $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ layer and the graphene layer are highlighted in red and yellow, respectively. The green circles indicate the Dirac points of the graphene layer. (f–i) Demonstration of a significant band gap reduction in a one QL FE- $Z B^{\\prime}$ $\\mathsf{I n}_{2}\\mathsf{S e}_{3}/\\mathsf{W}\\mathsf{S e}_{2}$ heterostructure. (f,h) The side views of the heterostructure with the electric dipole of the $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ layer pointing downwards and upwards, respectively. The corresponding electronic band structures are shown in g,i (calculated by GGA-PBE). The bands derived from the $\\mathsf{I n}_{2}\\mathsf{S e}_{3}$ layer and the ${\\mathsf{W S e}}_{2}$ layer are highlighted in red and blue, respectively. The Fermi level of each system is shifted to energy zero in all the band structure plots. \n\nSo far we have limited ourselves to ideal 2D systems of infinite size. In physically realistic growth conditions, the systems are more likely to contain different types of defects, especially domain walls3,5. Here we show that the electric polarization reversal process can be further facilitated by the presence of a domain wall between two oppositely polarized domains. In doing so, we construct four possible domain wall structures, as shown in the initial states of Fig. 4a,b, by moving half of the Se atoms in the central layer initially aligned to one In layer to the neighbouring sites aligned to the other In layer. The total formation energy of the two domain walls in the configuration as shown in Fig. 4a $\\mathrm{\\Delta}0.22\\mathrm{eV}$ per unit cell) is much lower than that in Fig. 4b $1.45\\mathrm{eV}$ per unit cell). The calculated activation barriers in the low-energy configuration are 0.40 and $0.28\\mathrm{eV}$ per unit cell along the domain wall, respectively, much lower than the barrier of $0.85\\mathrm{eV}$ per unit cell against the direct shifting mechanism of the central Se layer discussed earlier. \n\n$\\mathbf{In}_{2}\\mathbf{Se}_{3}$ -based van der Waals heterostructures. Next, we demonstrate the device potential of the discovered 2D ferroelectric materials in van der Waals heterostructures, focusing on the electrical transport properties. As a reference, a single ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ QL is a semiconductor with an indirect band gap of $1.46\\mathrm{eV}$ (calculated by HSE06, $0.78\\mathrm{eV}$ by GGA-PBE) (Fig. 5a). Owing to the presence of the out-of-plane electric polarization of the ferroelectric layer, there is a built-in electric field within the material, leading to different alignments of the energy bands with respect to the vacuum level on different sides of a given ferroelectric QL. For a ferroelectric $\\begin{array}{r}{\\operatorname{In}_{2}\\mathrm{Se}_{3}\\mathrm{QL},}\\end{array}$ , such a difference is as large as $1.37\\mathrm{eV}$ (calculated by HSE06). As a van der Waals 2D material is stacked with a ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ layer, the energy bands of the two components are approximately aligned with respect to the vacuum level, due to their weak van der Waals interaction. Therefore, as different sides of the ferroelectric layer are in contact with the other 2D material, different band alignments result in different global electronic structures. As the first specific system, we consider a bilayer heterostructure by stacking a QL of ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ onto a single-layer graphene, which is a non-ferroelectric semimetal. As shown in Fig. 5b–e, the Schottky barrier across the interface can be altered by switching the electric dipole orientation of the $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ layer. The magnitude of the electric dipoles of the system is 0.11 and $0.03\\mathrm{e}\\mathring{\\mathrm{A}}$ per $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ unit cell for the two oppositely polarized configurations as shown in Fig. ${5}\\mathrm{b,d,}$ respectively. The next bilayer heterostructure system considered is formed by stacking a QL of ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ on a monolayer of ${\\mathrm{WSe}}_{2}$ , which is a non-ferroelectric semiconductor. As shown in Fig. 5f–i, the band shift leads to a significant band gap reduction when switching the electric dipole orientation of the $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ layer. The magnitude of the electric dipoles of the system is 0.10 and $0.06\\mathrm{\\check{e}}\\mathrm{\\check{A}}$ per $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ unit cell for the two oppositely polarized configurations as shown in Fig. $^{5\\mathrm{f},\\mathrm{h}}$ respectively. For both heterostructures, the reduction of the electric dipoles in one of the polarized configurations can be attributed to the screening effects due to the charge transfer between the two layers as indicated in Fig. 5e,i. The influence of the graphene and ${\\mathrm{WSe}}_{2}$ layers on the energetics and kinetics of the polarization reversal processes of the ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ layer is discussed in Supplementary Note 3. The observed tunable band alignments with the ferroelectric layer can be exploited for different technological applications, such as for non-volatile memory devices or in graphene-based electronics. It is particularly worthwhile to note that the tunability in the properties can be achieved by the application of an external field, but the desired functionalities can be preserved even after the external field is removed. To provide a generic guideline for the design of desirable heterostructures, a schematic diagram of the band alignments of a single ferroelectric $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ QL is provided in Supplementary Fig. 13. \n\nFamily of 2D ferroelectric $\\mathbf{III}_{2}\\mathbf{-VI}_{3}$ compounds. So far we have limited our discussions on the intrinsic ferroelectric properties of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ . Next, we show that ferroelectric 2D van der Waals materials can be harboured in a wider family of the $\\ensuremath{\\mathrm{III}_{2}}\\mathrm{-}\\ensuremath{\\mathrm{VI}_{3}}$ materials. Our DFT calculations suggest that the ferroelectric phases, FE- $\\mathrm{\\cdot}\\mathrm{ZB^{\\prime}}$ and ${\\mathrm{FE-WZ^{\\prime}}}$ , are also the ground states of ${\\mathrm{Al}}_{2}{\\mathrm{S}}_{3}$ $\\mathrm{\\bar{Al}}_{2}\\mathrm{Se}_{3}$ , ${\\mathrm{Al}}_{2}{\\mathrm{T}}{\\mathbf{e}}_{3}{\\mathrm{:}}$ $\\mathrm{Ga}_{2}\\mathrm{S}_{3}$ , ${\\mathrm{Ga}}_{2}{\\mathrm{Se}}_{3}$ , $\\mathrm{Ga}_{2}\\mathrm{Te}_{3}$ , $\\mathrm{In}_{2}\\mathrm{S}_{3}$ and $\\mathrm{In}_{2}\\mathrm{Te}_{3}$ when such materials are prepared in the QL form. Their semiconducting electronic band structures and optimal lattice constants are shown in Supplementary Fig. 14, and their dynamic stability is confirmed by the lack of imaginary phonon modes in the calculated phonon band structures (Supplementary Fig. 15). We further note that all the In-containing compounds have both the stable ferroelectric (FE-ZB0 and FE-WZ0) and metastable fcc0 structures, while all the Ga-containing compounds only possess the stable ferroelectric structures, with the fcc-derived structure being unstable. \n\n# Conclusions \n\nIn this work, we have discovered a class of stable single-layer van der Waals 2D ferroelectric materials rooted in $\\begin{array}{r l}{\\lefteqn{\\operatorname{III}_{2}-\\operatorname{VI}_{3}}}\\end{array}$ compounds that possess both intrinsic out-of-plane and in-plane electric polarization, which can be reversed through readily accessible kinetic pathways with the assistance of a modest out-of-plane or in-plane electric field. In a broader prospective, these discoveries add an important branch to the family tree of 2D materials. Proper integration of these materials with other classes of 2D systems is expected to substantially broaden the tunability and device potential of van der Waals heterostructures. \n\n# Methods \n\nComputational methods. The first-principles DFT calculations were performed using the Vienna $\\vert A b$ Initio Simulation Package29. Valence electrons were described using the projector-augmented wave30,31 method. The plane wave expansions were determined by the default energy cutoffs given by the Vienna $\\mathbf{\\nabla}_{A b}$ Initio Simulation Package projector-augmented wave potentials. The exchange and correlation functional was treated using the $\\mathrm{PBE}^{32}$ parametrization of GGA for structural relaxations and total energy calculations. For the band structure calculations of pristine $\\ensuremath{\\mathrm{III}_{2}}\\mathrm{-}\\ensuremath{\\mathrm{VI}_{3}}$ compounds, we also used the hybrid functional of Hyed-ScuseriaErnzerhof (HSE06) (ref. 33). To model the 2D films, the supercells contain a unit cell of single QL structures with a vacuum region of more than $15\\mathrm{\\AA}$ . A saw-like self-consistent dipole layer was placed in the middle of the vacuum region to adjust the misalignment between the vacuum levels on the different sides of the film due to the intrinsic electric polarization. A $\\Gamma$ -centred $12\\times12\\times1$ Monkhorst- $\\mathrm{\\cdotPack}^{34}$ $k$ -mesh was used for $k$ -point sampling. Optimized atomic structures were achieved when forces on all the atoms were $\\check{<}0.0\\dot{0}5\\mathrm{eV}\\mathrm{A}^{-1}$ . The in-plane electric polarization was evaluated by using the Berry phase method35. The climbing image nudged elastic band method36 is used to determine the energy barriers of the various kinetic processes. In the heterostructure calculations, we included the van der Waals corrections as parameterized in the semiempirical DFT-D3 method37. More details are provided in Supplementary Note 1. \n\nData availability. All relevant data are available from the authors. \n\n# References \n\n1. Setter, N. et al. Ferroelectric thin films: review of materials, properties, and applications. J. Appl. Phys. 100, 051606 (2006). \n2. Scott, J. F. Applications of modern ferroelectrics. Science 315, 954–959 (2007). \n3. Rabe, K. M., Ahn, C. H. & Triscone, J.-M. (eds). Physics of Ferroelectrics: A Modern Perspective (Springer, 2007). \n4. Ahn, C. H., Rabe, K. M. & Triscone, J.-M. Ferroelectricity at the nanoscale: local polarization in oxide thin films and heterostructures. Science 303, 488–491 (2004). \n5. Dawber, M., Rabe, K. M. & Scott, J. F. Physics of thin-film ferroelectric oxides. Rev. Mod. Phys. 77, 1083–1130 (2005). \n6. Rao, C. N. R. & Maitra, U. Inorganic graphene analogs. Annu. Rev. Mater. Res. 45, 29–62 (2015). \n7. Xu, M., Liang, T., Shi, M. & Chen, H. Graphene-like two-dimensional materials. Chem. Rev. 113, 3766–3798 (2013). \n8. Geim, A. K. & Grigorieva, I. V. Van der Waals heterostructures. Nature 499, 419–425 (2013). \n9. Xu, X., Yao, W., Xiao, D. & Heinz, T. F. Spin and pseudospins in layered transition metal dichalcogenides. Nat. Phys. 10, 343–350 (2014). \n10. Qian, X., Liu, J., Fu, L. & Li, J. Quantum spin Hall effect in two-dimensional transition metal dichalcogenides. Science 346, 1344–1347 (2014). \n11. Chang, K. et al. Discovery of robust in-plane ferroelectricity in atomic-thick SnTe. Science 353, 274–278 (2016). \n12. Shirodkar, S. N. & Waghmare, U. V. Emergence of ferroelectricity at a metal-semiconductor transition in a 1T monolayer of $\\mathbf{MoS}_{2}$ . Phys. Rev. Lett. 112, 157601 (2014). \n13. Onsager, L. Crystal statistics. I. A two-dimensional model with an order-disorder transition. Phys. Rev. 65, 117–149 (1944). \n14. Junquera, J. & Ghosez, P. Critical thickness for ferroelectricity in perovskite ultrathin films. Nature 422, 506–509 (2003). \n15. Fong, D. D. et al. Ferroelectricity in ultrathin perovskite films. Science 304, 1650–1653 (2004). \n16. Lee, D. et al. Emergence of room-temperature ferroelectricity at reduced dimensions. Science 349, 1314–1317 (2015). \n17. Osamura, K., Murakami, Y. & Tomiie, Y. Crystal structures of $\\alpha$ - and $\\beta$ -indium selenide, $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ . J. Phys. Soc. Jpn 21, 1848 (1966). \n18. Ye, J., Soeda, S., Nakamura, Y. & Nittono, O. Crystal structures and phase transformation in $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ compound semiconductor. Jpn J. Appl. Phys. 37, 4264–4271 (1998). \n19. Tao, X. & Gu, Y. Crystalline crystalline phase transformation in two-dimensional $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ thin layers. Nano Lett. 13, 3501–3505 (2013). \n20. Jacobs-Gedrim, R. B. et al. Extraordinary photoresponse in two-dimensional $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ nanosheets. ACS Nano 8, 514–521 (2014). \n21. Lin, M. et al. Controlled growth of atomically thin $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ flakes by van der Waals epitaxy. J. Am. Chem. Soc. 135, 13274–13277 (2013). \n22. Popovic´, S., Cˇ elustka, B. & Bidjin, D. X-ray diffraction measurement of lattice parameters of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ . Phys. Status Solidi A 6, 301–304 (1971). \n23. Popovic´, S., Tonejc, A., Grzˇeta-Plenkovic´, B., Cˇ elustka, B. & Trojko, R. Revised and new crystal data for Indium Selenides. J. Appl. Crystallogr. 12, 416–420 (1979). \n24. Rasmussen, A. M., Teklemichael, S. T., Mafi, E., Gu, Y. & McCluskey, M. D. Pressure-induced phase transformation of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ . Appl. Phys. Lett. 102, 062105 (2013). \n25. Miyazawa, H. & Sugaike, S. Phase transition of $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ . J. Phys. Soc. Jpn 12, 312 (1957). \n26. Debbichi, L., Eriksson, O. & Lebe\\`gue, S. Two-dimensional Indium Selenides compounds: an ab initio study. J. Phys. Chem. Lett. 6, 3098–3103 (2015). \n27. Cohen, R. E. Origin of ferroelectricity in perovskite oxides. Nature 358, 136–138 (1992). \n28. Zhang, Y. et al. Direct observation of a widely tunable bandgap in bilayer graphene. Nature 459, 820–823 (2009). \n29. Kresse, G. & Furthmu¨ller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n30. Blo¨chl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n31. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n32. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n33. Krukau, A. V., Vydrov, O. A., Izmaylov, A. F. & Scuseria, G. E. Influence of the exchange screening parameter on the performance of screened hybrid functionals. J. Chem. Phys. 125, 224106 (2006). \n34. Methfessel, M. & Paxton, A. T. High-precision sampling for Brillouin-zone integration in metals. Phys. Rev. B 40, 3616–3621 (1989). \n35. King-Smith, R. D. & Vanderbilt, D. Theory of polarization of crystalline solids. Phys. Rev. B 47, 1651–1654 (1993). \n36. Henkelman, G., Uberuaga, B. P. & J´onsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000). \n\n37. Grimme, S., Antony, J., Ehrlich, S. & Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 132, 154104 (2010). \n\n# Acknowledgements \n\nW.D., J.Z., Z.W. and W.Z. acknowledge support from the National Natural Science Foundation of China (Grant Nos 11374273 and 11674299) and the Fundamental Research Funds for the Central Universities (Grant Nos WK2090050027, WK2060190027, WK2340000063). Z.Z. acknowledges support from the National Natural Science Foundation of China (Grant Nos 61434002 and 11634011) and the National Key Basic Research Program of China (Grant No. 2014CB921103). We also acknowledge support from the US National Science Foundation, DMR-1206960 (Yi.G.), CMMI 1300223 (Ya.G.) and EFRI-1433496 (D.X.). Computational support was provided by National Supercomputing Center in Tianjin and NERSC of US Department of Energy. \n\n# Author contributions \n\nW.Z. conceived the idea and supervised the project. W.D., J.Z. and Z.W. performed calculations and data analysis. W.D., Z.Z. and W.Z. co-wrote the paper. All authors discussed the results and commented on the manuscript at all stages. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Ding, W. et al. Prediction of intrinsic two-dimensional ferroelectrics in $\\mathrm{In}_{2}\\mathrm{Se}_{3}$ and other $\\begin{array}{r}{{\\mathrm{III}}_{2^{-}}{\\mathrm{VI}}_{3}}\\end{array}$ van der Waals materials. Nat. Commun. 8, 14956 doi: 10.1038/ncomms14956 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1103_PhysRevB.96.245115", + "DOI": "10.1103/PhysRevB.96.245115", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevB.96.245115", + "Relative Dir Path": "mds/10.1103_PhysRevB.96.245115", + "Article Title": "Electric multipole moments, topological multipole moment pumping, and chiral hinge states in crystalline insulators", + "Authors": "Benalcazar, WA; Bernevig, BA; Hughes, TL", + "Source Title": "PHYSICAL REVIEW B", + "Abstract": "We extend the theory of dipole moments in crystalline insulators to higher multipole moments. As first formulated in Benalcazar et al. [Science 357, 61 (2017)], we show that bulk quadrupole and octupole moments can be realized in crystalline insulators. In this paper, we expand in great detail the theory presented previously [Benalcazar et al., Science 357, 61 (2017)] and extend it to cover associated topological pumping phenomena, and a class of three-dimensional (3D) insulator with chiral hinge states. We start by deriving the boundary properties of continuous classical dielectrics hosting only bulk dipole, quadrupole, or octupole moments. In quantum mechanical crystalline insulators, these higher multipole bulk moments manifest themselves by the presence of boundary-localized moments of lower dimension, in exact correspondence with the electromagnetic theory of classical continuous dielectrics. In the presence of certain symmetries, these moments are quantized, and their boundary signatures are fractionalized. These multipole moments then correspond to new symmetry-protected topological phases. The topological structure of these phases is described by nested Wilson loops, which we define. These Wilson loops reflect the bulk-boundary correspondence in a way that makes evident a hierarchical classification of the multipole moments. Just as a varying dipole generates charge pumping, a varying quadrupole generates dipole pumping, and a varying octupole generates quadrupole pumping. For nontrivial adiabatic cycles, the transport of these moments is quantized. An analysis of these interconnected phenomena leads to the conclusion that a new kind of Chern-type insulator exists, which has chiral, hinge-localized modes in 3D. We provide the minimal models for the quantized multipole moments, the nontrivial pumping processes, and the hinge Chern insulator, and describe the topological invariants that protect them.", + "Times Cited, WoS Core": 1068, + "Times Cited, All Databases": 1124, + "Publication Year": 2017, + "Research Areas": "Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000417639900004", + "Markdown": "# PHYSICAL REVIEW B 96, 245115 (2017) S Electric multipole moments, topological multipole moment pumping, and chiral hinge states in crystalline insulators \n\nWladimir A. Benalcazar,1 B. Andrei Bernevig,2,\\* and Taylor L. Hughes1,† 1Department of Physics and Institute for Condensed Matter Theory, University of Illinois at Urbana-Champaign, Illinois 61801, USA 2Department of Physics, Princeton University, Princeton, New Jersey 08544, USA (Received 28 August 2017; published 11 December 2017) \n\nWe extend the theory of dipole moments in crystalline insulators to higher multipole moments. As first formulated in Benalcazar et al. [Science 357, 61 (2017)], we show that bulk quadrupole and octupole moments can be realized in crystalline insulators. In this paper, we expand in great detail the theory presented previously [Benalcazar et al., Science 357, 61 (2017)] and extend it to cover associated topological pumping phenomena, and a class of three-dimensional (3D) insulator with chiral hinge states. We start by deriving the boundary properties of continuous classical dielectrics hosting only bulk dipole, quadrupole, or octupole moments. In quantum mechanical crystalline insulators, these higher multipole bulk moments manifest themselves by the presence of boundary-localized moments of lower dimension, in exact correspondence with the electromagnetic theory of classical continuous dielectrics. In the presence of certain symmetries, these moments are quantized, and their boundary signatures are fractionalized. These multipole moments then correspond to new symmetry-protected topological phases. The topological structure of these phases is described by “nested” Wilson loops, which we define. These Wilson loops reflect the bulk-boundary correspondence in a way that makes evident a hierarchical classification of the multipole moments. Just as a varying dipole generates charge pumping, a varying quadrupole generates dipole pumping, and a varying octupole generates quadrupole pumping. For nontrivial adiabatic cycles, the transport of these moments is quantized. An analysis of these interconnected phenomena leads to the conclusion that a new kind of Chern-type insulator exists, which has chiral, hinge-localized modes in 3D. We provide the minimal models for the quantized multipole moments, the nontrivial pumping processes, and the hinge Chern insulator, and describe the topological invariants that protect them. \n\nDOI: 10.1103/PhysRevB.96.245115 \n\n# I. INTRODUCTION \n\nA successful theory describing the phenomenon of bulk electric polarization in crystalline insulators remained elusive for decades after the development of the band theory of crystals. The difficulty stemmed from the fact that the macroscopic electric polarization of a periodic crystal cannot be unambiguously defined as the dipole of a unit cell [1] and, therefore, the absolute macroscopic polarization of a crystal is ill defined. The recognition that only derivatives of the polarization are well-defined observables and correspond to experimental measurements [1] led to a resolution of this problem and to the formulation of what is now known as the modern theory of polarization [2–6] in crystalline insulators. This theory is formulated in terms of Berry phases [7,8], which account for the dipole moment densities in the bulk of a material, and it has its minimal realization in one dimension [9,10] (1D). A bulk dipole moment manifests itself through the existence of boundary charges [3] [Fig. 1(a)]. When the dipole moment densities vary over time, e.g., by an adiabatic evolution of an insulating Hamiltonian over time, electronic currents appear across the bulk of the material where the polarization is changing [Fig. 1(b)] [2,3]. In particular, if adiabatic evolutions of the Hamiltonian are carried over closed cycles (i.e., those in which the initial and final Hamiltonians are the same), the electronic transport is quantized [11]. This quantization is given by a Chern number and, mathematically, in systems with charge conservation, is closely related to the Hall conductance of a Chern insulator [12] [Fig. 1(c)]. \n\nA remarkable pattern develops in the topological objects describing these systems that follow a hierarchical mathematical structure as the dimensionality of space increases. For example, the expressions for the polarization $P_{1}$ [2,8], the Hall conductance $\\sigma_{x y}$ of a Chern insulator [12–14], and the magnetoelectric polarizability $P_{3}$ of a three-dimensional (3D) time-reversal invariant or inversion-symmetric topological insulator [15–18], are given by \n\n$$\n\\begin{array}{c}{{P_{1}=-\\displaystyle\\frac{e}{2\\pi}\\int_{\\mathrm{BZ}}\\mathrm{Tr}[A],}}\\\\ {{\\sigma_{x y}=-\\displaystyle\\frac{e^{2}}{2\\pi h}\\int_{\\mathrm{BZ}}\\mathrm{Tr}[d A+i A\\wedge A],}}\\\\ {{P_{3}=-\\displaystyle\\frac{e^{2}}{4\\pi h}\\int_{\\mathrm{BZ}}\\mathrm{Tr}\\biggl[A\\wedge d A+\\displaystyle\\frac{2i}{3}A\\wedge A\\wedge A\\biggr],}}\\end{array}\n$$ \n\nwhere BZ is the Brillouin zone in one, two, and three spatial dimensions, respectively, and $\\mathcal{A}$ is the Berry connection, with components $[\\mathcal{A}_{i}(\\mathbf{k})]^{m n}=-i\\langle u_{\\mathbf{k}}^{m}|\\partial_{k_{i}}|u_{\\mathbf{k}}^{n}\\rangle$ , where $\\left|u_{\\mathbf{k}}^{n}\\right\\rangle$ is the Bloch function of band $n$ , and $^{m,n}$ run only over occupied energy bands. \n\n![](images/24d5dd46ba810ca754163522672ee1aaea22f7a14bc11e5c51a6b06027b705f5.jpg) \nFIG. 1. Multipole moments, associated multipole pumping processes, and derived topological insulators. (a), (d), (e) Dipole, quadrupole, and octupole insulators, respectively. Dots of different colors represent corner-localized charges of opposite charge. When protected by symmetries, charges are quantized to either 0 or $\\pm e/2$ . (b), (e), (h) Charge, dipole, and quadrupole pumping, respectively. Pumping over nontrivial closed cycles pumps quanta of charge, dipole, and quadrupole. (c), (f) Insulators with same topology as pumping processes: Chern insulator with chiral edge-localized modes (c), and Chern insulator with hinge-localized modes (f). \n\nThis hierarchical mathematical structure positions the concept of charge polarization at the basis of the field of topological insulators and related phenomena. Fermionic SPTs with time-reversal, charge-conjugation, and/or chiral symmetries [19] in all spatial dimensions were categorized in a periodic classification table of topological insulators and superconductors [15,20,21]. Following this classification, many different groups have begun classifying SPTs protected by reflection [22–26], inversion [17,18,27,28], rotation [29–33], nonsymmorphic symmetries [34–36], and more [37–46]. \n\nThe mathematical topological invariants that characterize these phases are tied to quantized physical observables. For example, in one-dimensional (1D) insulators in the presence of inversion symmetry, the polarization in Eq. (1.1) is quantized to either 0 or $e/2$ and is in exact correspondence with the Berry phase topological invariant [8,15,17,18]. Recently, we showed the existence of quantized quadrupole and octupole moments, as well as quantized dipole currents, in crystalline insulators [47]. The primary goal of this paper is to thoroughly develop the theory of quantized electromagnetic observables in topological crystalline insulators. In addition to the work presented in Ref. [47], in this paper we discuss in more detail the observables of multipole moments and their relations, both in the classical continuum theory and in the quantum mechanical crystalline theory and also discuss the extension of the theory of polarization to account for nonquantized higher multipole moments. To carry this out, we systematically extend the theory of charge polarization in crystalline insulators by taking a different route than the extension suggested by the hierarchical mathematical structure evident in Eqs. (1.1)–(1.3), which deals primarily with polarizations. Our topological structure is also of hierarchical nature, but subtly involves the calculation of Berry phases of reduced sectors within the subspace of occupied energy bands. To find the relevant subspace, we resolve the energy bands into spatially separated “Wannier bands” through a Wilson-loop calculation or, equivalently, a diagonalization of a ground-state projected position operator. We call this structure “nested Wilson loops.” It goes one step beyond the previous developments in the understanding of topological insulator systems in terms of Berry phases [48–52]. At its core, this nested Wilson loop structure reflects the fact that even gapped edges of topological phases can signal a nontrivial bulk-boundary correspondence when the gapped edge Hamiltonian is topological itself and inherits such nontrivial topology from the bulk. \n\nThis topological structure reveals that, in addition to bulk dipole moments, crystalline insulators can realize bulk quadrupole and octupole moments, as initially shown in Ref. [47] [Figs. 1(d) and 1(g)]. In addition, this structure reveals other phenomena, detailed in this paper. When we allow for the adiabatic deformation and evolution of Hamiltonians having nonzero quadrupole and octupole moments, we find new types of quantized electronic transport and currents, extending what is already known in the case of the adiabatic charge pumping [Fig. 1(b)] [11]. In particular, the new types of adiabatic electronic currents are localized not in the bulk, but on edges or hinges of the material. They essentially amount to pumping a dipole or quadrupole across the bulk of the material, respectively [Figs. 1(e) and 1(h)]. If the adiabatic process forms a closed cycle, the transport is quantized, i.e., the amount of dipole or quadrupole being pumped is quantized. The first Chern number characterizes the 1D adiabatic pumping process; this process can be connected to a Chern insulator phase in one spatial dimension higher. The dipole pumping process in the two-dimensional (2D) quadrupole system correspondingly predicts the existence of an associated three-dimensional (3D) “hinge Chern insulator” having the same topological structure as a family of 2D quadrupole Hamiltonians forming an adiabatic evolution through a “nontrivial” cycle (i.e., a cycle that connects a quantized topological quadrupole insulator with a trivial insulator, while maintaining the energy gap open). This insulator has four hinge-localized modes which are chiral and disperse in opposite directions at adjacent hinges, as shown schematically in Fig. 1(f). In principle, the quadrupole pumping of the 3D octupole system would predict a four-dimensional (4D) topological phase, though we will not discuss it any further here. \n\nOur focus throughout this paper is on tight-binding lattice models. A summary of the organization of this paper is detailed in the next subsection. The paper is self-contained, starting with a pedagogical description of the modern theory of polarization. Readers already familiar with the modern theory of electronic polarization, and the connection between Berry phase, Wannier functions, and Wilson loops, can easily skip Sec. III after reading Sec. II. \n\n# Outline \n\nIn Sec. II, we first define electric multipole moments within the classical electromagnetic theory, characterize their boundary signatures, and establish the criteria under which these moments are well defined. \n\nWe then start the discussion of the dipole moment in crystalline insulators in one dimension (1D) in Sec. III, and in two dimensions (2D) in Secs. IV and in V. Our formulation differs from the original one [3] in that, instead of referring to the relationship between electric current and change in electric polarization, we directly calculate the position of electrons in the crystal by means of diagonalizing the position operator projected into the subspace of occupied bands. This approach naturally connects the individual electronic positions with the polarization (i.e., dipole moment), as well as this polarization with the Berry phase accumulated by the subspace of occupied bands across the Brillouin zone of the crystal. Additionally, this approach provides us with eigenstates of well-defined electronic position, which we then use to extend the formulation to higher multipole moments. \n\nIn addition to this formulation, we discuss the symmetry constraints that quantize the dipole moments and present the case of the Su-Schrieffer-Hegger (SSH) model as a primitive model for the realization of the dipole symmetry-protected topological (SPT) phase. We further use extensions of this model that break the symmetries that protect the SPT phase and thus allow an adiabatic change in polarization and the appearance of currents. We will discuss the topological invariant that characterizes the quantization of charge transport in closed adiabatic cycles. \n\nIn Sec. IV, we extend the 1D treatment of the problem to 2D and introduce the concept of Wannier bands, which plays a crucial role in the description of higher multipole moments. We also characterize, in terms of Wannier bands, the topology of a Chern insulator and the quantum spin Hall insulator as examples, and make connections between the topology of a Chern insulator and the quantization of particle transport of Sec. III. \n\nIn Sec. V, we describe the recently found phenomenon of edge polarization [53] and its relation to corner charge. In particular, we use this as an example that allows discriminating corner charge arising from converging edge-localized dipole moments from the corner charge arising from higher multipole moments. \n\nWe then describe the existence of the first higher multipole moment, the quadrupole moment, in Sec. VI. We first present the theory in terms of the diagonalization of position operators. Just as in the case of the dipole, the quadrupole moment is indicated by a topological quantity, which relates to the polarization of a Wannier band-resolved subspace within the subspace of occupied energy bands. From this formulation, we derive the conditions (i.e., the symmetries) under which the quadrupole moment quantizes to $\\pm e/2$ , realizing a quadrupole SPT. We then present a concrete minimal model with quadrupole moment. We describe the observables associated with it: the existence of edge polarization and corner charge, as well as the different symmetry-protected phases associated with this model and the nature of its phase transitions. We then break the symmetries that protect the SPT to cause adiabatic transport of charge, but in a pattern that amounts to a net pumping of dipole moment. This dipole moment transport can also be quantized in an analogous manner to the charge transport in a varying dipole. We describe the invariant associated with this quantization and the extension of this principle to the creation of unusual insulators, not described so far to the best of our knowledge, which present chiral hinge-localized dispersive modes due to its nontrivial topology. \n\nIn Sec. VII, we describe the existence of octupole moments. We describe the hierarchical topological structure that gives rise to higher multipole moments, as well as the minimal model that realizes a quantized octupole SPT. We also describe, by means of a concrete example, how the quantization of quadrupole transport can be realized. \n\nIn Sec. VIII, we present a discussion that highlights and summarizes the main findings in this paper, and its implications in terms of future extensions of this work to other fermionic or bosonic systems, as well as a discussion on the anomalous nature of the boundaries of these multipole moment insulators. \n\n# II. MULTIPOLE EXPANSION IN THE CONTINUUM ELECTROMAGNETIC THEORY \n\nSince the classical theory of multipole moments, even in the absence of a lattice, has various subtleties, we will spend time reviewing it in this section. Our goal is to provide precise definitions for, and to extract the macroscopically observable signatures of, the dipole, quadrupole, and octupole moments in insulators. \n\n# A. Definitions \n\nIn this section we define multipole electric moments in macroscopic materials based on classical charge configurations in the absence of a lattice. We define a macroscopic material as one which can be divided into small volume elements (voxels), as shown in Fig. 2, over which multipole moment densities can be defined, and in such a way that these densities can be treated as continuous functions of the position at larger length scales. For a material divided into such voxels, the expression for the electric potential at position $\\vec{r}$ due to a charge distribution over space is \n\n![](images/967c487bf3fa4e687d033b1ddd6bdb7568608c1ef1f0d2680a900a454904084c.jpg) \nFIG. 2. Macroscopic material divided in small voxels over which the multipole moment densities are calculated. Each voxel is labeled by its center point ${\\vec{R}}.{\\vec{r}}$ is the position (far) outside the material at which the potential is calculated. \n\n$$\n\\phi(\\vec{r})={\\frac{1}{4\\pi\\epsilon}}\\sum_{\\vec{R}}\\int_{v(\\vec{R})}d^{3}\\vec{r^{\\prime}}{\\frac{\\rho(\\vec{r^{\\prime}}+\\vec{R})}{|\\vec{r}-\\vec{R}-\\vec{r^{\\prime}}|}},\n$$ \n\nwhere $\\rho(\\vec{r})$ is the volume charge density, $\\epsilon$ is the dielectric constant, $\\vec{R}$ labels the voxel, and in the integral ${\\vec{r}}^{\\prime}$ runs through the volume $v(\\vec{R})$ of voxel $\\vec{R}$ . Since the voxels are much smaller than the overall size of the material, we have that $|\\vec{r^{\\prime}}|\\ll$ $|\\vec{r}-\\vec{R}|$ as long as $\\vec{r}$ is outside of the material and sufficiently away from $i t$ . Then, one can expand the potential (2.1) in powers of $1/|\\vec{r}-\\vec{R}|$ (see details in Appendix A) to define the multipole moment densities \n\n$$\n\\begin{array}{c}{{\\rho(\\vec{R})=\\displaystyle\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}r^{\\prime}\\rho({\\vec{r}^{\\prime}}+\\vec{R}),}}\\\\ {{{}}}\\\\ {{p_{i}(\\vec{R})=\\displaystyle\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}{\\vec{r}^{\\prime}}\\rho({\\vec{r}^{\\prime}}+\\vec{R})r_{i}^{\\prime},}}\\\\ {{{}}}\\\\ {{q_{i j}(\\vec{R})=\\displaystyle\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}{\\vec{r}^{\\prime}}\\rho({\\vec{r}^{\\prime}}+\\vec{R})r_{i}^{\\prime}r_{j}^{\\prime},}}\\\\ {{{}}}\\\\ {{{\\sigma_{i j k}(\\vec{R})=\\displaystyle\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}{\\vec{r}^{\\prime}}\\rho({\\vec{r}^{\\prime}}+\\vec{R})r_{i}^{\\prime}r_{j}^{\\prime}r_{k}^{\\prime},}}}\\end{array}\n$$ \n\nwhich allow to write the terms in the expansion of the potential \n\n$$\n\\phi(\\vec{r})=\\sum_{l=0}^{\\infty}\\phi^{l}(\\vec{r})\n$$ \n\nas \n\n$$\n\\begin{array}{l}{{\\displaystyle\\phi^{0}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(\\rho(\\vec{R})\\frac{1}{|\\vec{d}|}\\biggr),}}\\\\ {{\\displaystyle\\phi^{1}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(p_{i}(\\vec{R})\\frac{d_{i}}{|\\vec{d}|^{3}}\\biggr),}}\\\\ {{\\displaystyle\\phi^{2}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(q_{i j}(\\vec{R})\\frac{3d_{i}d_{j}-|\\vec{d}|^{2}\\delta_{i j}}{2|\\vec{d}|^{5}}\\biggr),}}\\\\ {{\\displaystyle\\phi^{3}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(o_{i j k}(\\vec{R})\\frac{5d_{i}d_{j}d_{k}-3|\\vec{d}|^{2}d_{k}\\delta_{i j}}{2|\\vec{d}|^{7}}\\biggr),}}\\end{array}\n$$ \n\nwhere $V$ is the total volume of the macroscopic material and $\\vec{d}=\\vec{r}-\\vec{R}$ . The potential $\\phi^{0}({\\vec{r}})$ is due to the free “coarsegrained” charge density in Eq. (2.2). In the limit of $v(\\vec{R})\\to0$ , this coarse-grained charge density is the original continuous charge density, and we recover the original expression (2.1). In this case, all other multipole contributions identically vanish. \n\n# B. Dependence of the multipole moments on the choice of reference frame \n\nThe multipole moments are in general defined with respect to a particular reference frame. For example, given a charge density per unit volume $\\rho(\\vec{r})$ , consider the definition of the dipole moment \n\n$$\nP_{i}=\\int_{v}d^{3}\\vec{r}\\rho(\\vec{r})r_{i}.\n$$ \n\nIf we shift the coordinate axes used in that definition by $\\vec{D}$ such that our new positions are given by $r_{i}^{\\prime}=r_{i}+D_{i}$ , and the charge density in this new reference frame is $\\rho^{\\prime}(\\vec{r^{\\prime}})=\\rho(\\vec{r})$ , the dipole moment is now given by \n\n$$\n\\begin{array}{l}{{P_{i}^{\\prime}=\\displaystyle\\int_{v}d^{3}\\vec{r}^{\\prime}\\rho^{\\prime}(\\vec{r^{\\prime}})r_{i}^{\\prime}}}\\\\ {{\\ }}\\\\ {{\\displaystyle~=\\int_{v}d^{3}\\vec{r}\\rho(\\vec{r})(r_{i}+D_{i})}}\\\\ {{\\ }}\\\\ {{\\displaystyle~=\\int_{v}d^{3}\\vec{r}\\rho(\\vec{r})r_{i}+D_{i}\\int_{v}d^{3}\\vec{r}\\rho(\\vec{r})}}\\\\ {{\\ }}\\\\ {{\\displaystyle~=P_{i}+D_{i}Q,}}\\end{array}\n$$ \n\nwhere $\\boldsymbol{Q}$ is the total charge. Notice, however, that the dipole moment is well defined for any reference frame if the total charge $\\boldsymbol{Q}$ vanishes. Similarly, a quadrupole moment transforms as \n\n$$\n\\begin{array}{l}{{\\displaystyle Q_{i j}^{\\prime}=\\int_{v}d^{3}\\vec{r^{\\prime}}\\rho^{\\prime}(\\vec{r^{\\prime}})r_{i}^{\\prime}r_{j}^{\\prime}}}\\\\ {{\\displaystyle\\quad=\\int_{v}d^{3}\\vec{r}\\rho(\\vec{r})(r_{i}+D_{i})(r_{j}+D_{j})}}\\\\ {{\\displaystyle\\quad=Q_{i j}+P_{i}D_{j}+D_{i}P_{j}+D_{i}D_{j}Q,}}\\end{array}\n$$ \n\nwhich is not uniquely defined independent of the reference frame unless both the total charge and the dipole moments vanish. In general, for a multipole moment to be independent of the choice of reference frame, all of the lower moments must vanish. \n\n# C. Boundary properties of multipole moments \n\nNow, let us consider the macroscopic physical manifestations of the multipole moments. In all cases, we will consider the properties that appear at the boundaries of materials having nonvanishing multipole moments in their bulk. We consider each multipole density separately, assuming as indicated above, that all lower moments vanish. \n\n# 1. Dipole moment \n\nThe potential due to a dipole moment density $p_{i}({\\vec{R}})$ is given by the second equation in Eq. (2.4). As shown in Appendix B, this potential can be recast in the form \n\n$$\n\\begin{array}{l}{{\\displaystyle\\phi^{1}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\oint_{\\partial V}d^{2}\\vec{R}\\biggl(n_{i}p_{i}\\frac{1}{|\\vec{r}-\\vec{R}|}\\biggr)}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(-\\partial_{i}p_{i}\\frac{1}{|\\vec{r}-\\vec{R}|}\\biggr).}}\\end{array}\n$$ \n\nSince both terms scale as $1/|\\vec{r}-\\vec{R}|$ , where $|\\vec{r}-\\vec{R}|$ is the distance from a point in the material to the observation point, we can define the charge densities \n\n$$\n\\begin{array}{r l r}&{}&{\\sigma^{\\mathrm{face\\}a}(\\vec{R})=n_{i}^{(a)}p_{i}(\\vec{R}),}\\\\ &{}&{\\rho(\\vec{R})=-\\partial_{i}p_{i}(\\vec{R}).}\\end{array}\n$$ \n\nFrom now on, we will drop the label of the dependence of the variables on $\\vec{R}$ for convenience. The first term is the areal charge density on the boundary of a polarized material, and the \n\n![](images/061dbbdf2bd5c33b0d3e1b4f70ab26b5e8553ba1ca276fca0f4fec31957caed2.jpg) \nFIG. 3. Boundary charge in a material with uniform dipole moment per unit volume $p_{x}\\neq0$ , $p_{y}=p_{z}=0$ . Red (blue) color represents positive (negative) charge per unit area of magnitude $p_{x}$ . The three arrows pointing out of the flat surfaces represent the unit vectors $\\hat{n}^{(x)}$ , $\\hat{n}^{(-y)}$ , and $\\hat{n}^{(z)}$ . The other three unit vectors are not shown for clarity of presentation. \n\nsecond term is the volume charge density due to a divergence in the polarization. Hence, one manifestation of the dipole is a boundary charge as shown in Fig. 3. \n\n# 2. Quadrupole moment \n\nAs shown in Appendix B, the potential due to a quadrupole moment per unit volume $q_{i j}$ as listed in Eq. (2.4) is equivalent to \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\phi^{2}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{a,b}\\int_{L_{a b}}d\\vec{R}\\biggl(\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}q_{i j}\\biggr)\\frac{1}{d}}}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\sum_{a}\\int_{S_{a}}d^{2}\\vec{R}\\bigl(-\\partial_{j}n_{i}^{(a)}q_{i j}\\bigr)\\frac{1}{d}}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(\\frac{1}{2}\\partial_{j}\\partial_{i}q_{i j}\\biggr)\\frac{1}{d}.}}}\\end{array}\n$$ \n\nThis calculation was carried out for a system with a cubic geometry. $S_{a}$ represents the plane of surface normal to vector $\\bar{\\hat{n}}^{(a)}$ and $L_{a b}$ represents the hinge at the intersection of surfaces with normal vectors ${\\hat{n}}^{(a)}$ and $\\hat{n}^{(b)}$ . Since all the potentials scale as $1/d$ , where $\\vec{d}=\\vec{r}-\\vec{R}$ is the distance from the point in the material to the observation point, each expression in parentheses can be interpreted as a charge density in its own right. Thus, we define the charge densities \n\n$$\n\\begin{array}{r l}&{\\lambda^{\\mathrm{hinge}\\:a,b}=\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}q_{i j},}\\\\ &{\\quad\\sigma^{\\mathrm{face}\\:a}=-\\partial_{j}\\big(n_{i}^{(a)}q_{i j}\\big),}\\\\ &{\\quad\\quad\\quad\\rho=\\frac{1}{2}\\partial_{j}\\partial_{i}q_{i j}.}\\end{array}\n$$ \n\nThe first term is the charge density per length at the hinge $L_{a b}$ of the material. The second term is the area charge density at the boundary surface $S_{a}$ of the material due to a divergence in the quantity $n_{i}^{(a)}q_{i j}$ . Finally, the third term is the direct contribution of the quadrupole moment density to the volume charge density in the bulk of the material. For a cube with constant quadrupole moment $q_{x y}$ and open boundaries, we illustrate the charge density in Fig. 4(a), as indicated by the expression for $\\lambda^{\\mathrm{hinge}}$ . Notice that the expression for the surface charge density $\\sigma^{\\mathrm{face}}$ could be written as \n\n$$\n\\sigma^{\\mathrm{face}~a}=-\\partial_{j}p_{j}^{\\mathrm{face}~a},\n$$ \n\n![](images/4e1a6ed1ac813337648223f86718c1d8c1e2fac15159ac54644800eeb8f83e18.jpg) \nFIG. 4. Boundary properties of a cube with uniform quadrupole moment per unit volume $q_{x y}\\neq0,\\ q_{y z}=q_{z x}=0$ . (a) Boundary charge. Red (blue) color represents positive (negative) charge densities per unit length of magnitude $q_{x y}$ . (b) Boundary polarization. Arrows represent boundary dipole moment per unit area of magnitude $q_{x y}$ . The unit vectors $\\hat{n}^{(x)}$ , $\\hat{n}^{(-y)}$ , and $\\hat{n}^{(z)}$ are shown in (a) for reference. \n\nwhere \n\n$$\np_{j}^{\\mathrm{face}~a}=n_{i}^{(a)}q_{i j}\n$$ \n\nresembles the polarization for the volume charge density $\\rho$ in Eq. (2.9). Thus, we interpret $p_{j}^{\\mathrm{face}~a}$ as a bound dipole density (per unit area). This polarization exists on the surface perpendicular to ${\\hat{n}}^{(a)}$ and runs parallel to that surface. An illustration of this polarization for a cube with constant quadrupole moment $q_{x y}$ is shown in Fig. 4(b). \n\nNotice from (2.11) and (2.13) that the magnitudes of the hinge charge densities and the face dipole densities have the same magnitude as the quadrupole moment \n\n$$\n|\\lambda^{\\mathrm{hinge}}|=\\left|p_{j}^{\\mathrm{face}}\\right|=|q_{x y}|\n$$ \n\nsince the implied sums over $i$ and $j$ in the first equation of (2.11) cancel the factor $\\frac{1}{2}$ because $q_{x y}=q_{y x}$ . \n\n# 3. Octupole moment \n\nFollowing a similar procedure as that employed for the dipole and quadrupole moments, the potential due to an octupole moment per unit volume $o_{i j k}$ [Eq. (2.4)] can be rewritten as \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\phi^{3}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{a,b,c}\\frac{1}{c}n_{i}^{(a)}n_{j}^{(b)}n_{k}^{(c)}o_{i j k}\\frac{1}{r}}}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\sum_{a,b}\\int_{L_{a b}}d\\vec{R}\\biggl(-\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}\\partial_{k}o_{i j k}\\biggr)\\frac{1}{d}}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\sum_{i}\\int_{S_{a}}d^{2}\\vec{R}\\biggl(\\frac{1}{2}n_{i}^{(a)}\\partial_{j}\\partial_{k}o_{i j k}\\biggr)\\frac{1}{d}}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(-\\frac{1}{6}\\partial_{i}\\partial_{j}\\partial_{k}o_{i j k}\\biggr)\\frac{1}{d},~}}\\end{array}\n$$ \n\nfrom which we read off the various charge densities \n\n$$\n\\begin{array}{r l}&{\\delta^{\\mathrm{corner}\\ a,b,c}=\\frac{1}{6}n_{i}^{(a)}n_{j}^{(b)}n_{k}^{(c)}o_{i j k},}\\\\ &{~\\lambda^{\\mathrm{binge}\\ a,b}=-\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}\\partial_{k}o_{i j k},}\\\\ &{~\\sigma^{\\mathrm{face}\\ a}=\\frac{1}{2}n_{i}^{(a)}\\partial_{j}\\partial_{k}o_{i j k},}\\\\ &{~\\rho=-\\frac{1}{6}\\partial_{i}\\partial_{j}\\partial_{k}o_{i j k}.}\\end{array}\n$$ \n\n![](images/1aa3c99dc55b99fec800d8b1d3c32fb9daf5c0227fec06f696ffe24c6250da62.jpg) \nFIG. 5. Boundary properties of a cube with uniform octupole moment per unit volume $o_{x y z}$ . (a) Corner-localized charges. Red (blue) color represents positive (negative) charges with magnitude $o_{x y z}$ . (b) Hinge-localized dipole moments per unit length of magnitude $\\phantom{\\frac{1}{2}}O_{x y z}$ . (c) Surface-localized quadrupole moment densities. Purple squares represent quadrupole moments per unit area of magnitude $o_{x y z}$ . The unit vectors $\\hat{n}^{(x)}$ , $\\hat{n}^{(-y)}$ , and $\\hat{n}^{(z)}$ are shown in (c) for reference. \n\nThe new quantity $\\delta^{\\mathrm{corner}a,b,c}$ represents localized charge bound at a corner where the three surfaces normal to $\\hat{n}^{(a)},\\bar{n}^{(b)}$ , and $n^{(c)}$ intersect. Comparing (2.16) with the expressions for dipole and quadrupole moments, we see that we can rewrite the hinge charge density per unit length and the surface charge density per unit area as \n\n$$\n\\begin{array}{r}{\\lambda^{\\mathrm{hinge}a,b}=-\\partial_{k}p_{k}^{\\mathrm{hinge}a,b},}\\\\ {\\sigma^{\\mathrm{face}a}=\\frac{1}{2}\\partial_{j}\\partial_{k}q_{j k}^{\\mathrm{face}a},\\ }\\end{array}\n$$ \n\nwhere \n\n$$\n\\begin{array}{r l r}&{}&{p_{k}^{\\mathrm{hinge}~a,b}=\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}o_{i j k}}\\\\ &{}&{q_{j k}^{\\mathrm{face}~a}=n_{i}^{(a)}o_{i j k},~}\\end{array}\n$$ \n\nare the polarization per unit length on hinges where surfaces normal to ${\\hat{n}}^{(a)}$ and $\\hat{n}^{(b)}$ intersect and the quadrupole moment density per unit area on faces perpendicular to ${\\hat{n}}^{(a)}$ , respectively. These manifestations at the boundary are illustrated in Fig. 5 for a cube with uniform octupole moment. \n\nNotice from (2.16) and (2.18) that the magnitudes of the corner charge densities, the hinge dipole densities, and the face quadrupole densities have the same magnitude as the octupole moment, \n\n$$\n|\\delta^{\\mathrm{corner}}|=\\left|p_{k}^{\\mathrm{hinge}}\\right|=\\left|q_{j k}^{\\mathrm{face}}\\right|=|o_{x y z}|\n$$ \n\nsince the implied sums over $i$ and $j$ in the first equation of (2.16) and second equation of (2.18) cancel the prefactors of $\\frac{1}{6}$ and $\\frac{1}{2}$ , respectively, because $o_{x y z}=o_{y z x}=o_{z x y}=o_{x z y}=$ $o_{z y x}=o_{y x z}$ . \n\n# D. Bulk moments vs boundary moments \n\nIn this section, we draw an important distinction between boundary observables arising from the presence of a bulk moments vs boundary observables arising from “free” moments of lower dimensionality attached to a boundary. The potential confusion is illustrated in Fig. 6 where we consider a neutral, insulating material with no free charge in the bulk or boundary, so that all charge accumulation is induced by either dipole or quadrupole moments. In Fig. 6(a), there is charge accumulation where two boundary polarizations converge at a corner (in 2D) or a hinge (in 3D). These surface dipoles are meant to be a pure surface effect and not due to a bulk moment. In Fig. 6(b), \n\n$$\n\\begin{array}{r l r}&{Q^{c}=p_{1}+p_{2}\\quad}&{Q^{c}=q_{x y}}\\\\ &{\\xrightarrow[p=0]{\\vec{p_{1}}\\vec{r_{1}}}\\quad}&{|\\vec{p}|=\\underbrace{q_{x y}\\vec{r_{1}}}_{\\begin{array}{c}{p=0}\\\\ {q_{x y}=0}\\\\ {q_{x y}\\neq0}\\end{array}}\\Bigg\\}_{|\\vec{p_{2}}}}&\\\\ &{\\quad\\mathrm{(a)}}&\\end{array}\n$$ \n\nFIG. 6. Corner charges due to (a) a pair of convergent dipoles and (b) a constant quadrupole. The most general case up to quadrupole expansion will have a superposition of both contributions. \n\nthere are both surface polarizations and corner/hinge charge accumulation, but this time exclusively due to a quadrupole moment. The phenomenology in both cases is similar, so the natural question is how to distinguish the surface effect in Fig. 6(a) from the bulk effect in Fig. 6(b). \n\nTo be explicit, let us consider the 2D case. We first consider the existence of only boundary-localized dipole moments. The contribution to charge density due to a dipole moment density ${\\vec{p}}={\\vec{p}}({\\vec{r}})$ is \n\n$$\n\\begin{array}{l}{\\rho=-\\vec{\\nabla}\\cdot\\vec{p},}\\\\ {\\sigma=\\vec{p}\\cdot\\vec{n}}\\end{array}\n$$ \n\nwhich is a restatement of (2.9). The first term is the polarization-induced charge density per unit volume of the material, and ${\\vec{p}}\\cdot{\\vec{n}}$ is the charge density per unit area on a boundary surface with unit normal vector $\\vec{n}$ induced by the bulk polarization $\\vec{p}$ . For the purpose of calculating the accumulated charge, let us consider an area $\\boldsymbol{v}$ which encloses the corner on which charge is accumulated, as shown by the red circle in Fig. 6(a). To relate the induced charge in this volume to the polarization at its boundary, we use the first equation in Eq. (2.20) \n\n$$\n\\begin{array}{l}{{\\displaystyle Q^{\\mathrm{corner}}=\\int_{v}\\rho d v=\\int_{v}(-\\vec{\\nabla}\\cdot\\vec{p})d v}\\ ~}\\\\ {{\\displaystyle~=-\\oint_{\\partial v}\\vec{p}\\cdot d\\vec{s},}}\\end{array}\n$$ \n\nwhere in the second line we have applied Stokes’ theorem, and where $\\partial\\boldsymbol{v}$ is the boundary of area $\\boldsymbol{v}$ . We see from Fig. 6(a) that the boundary dipoles $\\vec{p}_{1}$ and $\\vec{p}_{2}$ puncture the boundary of $\\boldsymbol{v}$ . If we treat the polarizations as fully localized on the edge, we can write \n\n$$\n\\begin{array}{r}{\\vec{p}_{1}(\\vec{r})=\\hat{x}p_{1}\\delta(\\vec{r}-\\vec{r}_{1}),}\\\\ {\\vec{p}_{2}(\\vec{r})=\\hat{y}p_{2}\\delta(\\vec{r}-\\vec{r}_{2}),}\\end{array}\n$$ \n\nwhere $\\vec{r}_{1}$ and $\\vec{r}_{2}$ are shown in Fig. 6. Taking into account that the boundary $\\partial v$ has normal vector $-\\hat{x}$ at $\\vec{r}_{1}$ and $-\\hat{y}$ at $\\vec{r}_{2}$ , we have \n\n$$\n\\begin{array}{r}{Q^{\\mathrm{corner}}=p_{1}+p_{2}.}\\end{array}\n$$ \n\nIn contrast, let us now consider the charge accumulation inside area $v$ due to a quadrupole moment $q_{x y}$ , as shown in Fig. 6(b). It follows from (2.11) that, in this case, the induced charge is \n\n$$\n\\begin{array}{r}{\\rho=\\frac12\\partial_{j}\\partial_{i}q_{i j},}\\end{array}\n$$ \n\nwhere summation is implied for repeated indices. The blue region has quadrupole density $q_{x y}=q_{y x}\\neq0$ , and outside this region is vacuum. The total charge enclosed in the area $\\boldsymbol{v}$ (shown in red) is \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\mathcal{Q}}^{\\mathrm{corner}}=\\int_{v}\\rho d v=\\int_{v}\\bigg(\\frac12\\partial_{j}\\partial_{i}q_{i j}\\bigg)d v}}\\\\ {{\\displaystyle~=\\frac12\\oint_{\\partial v}(\\partial_{i}q_{i j})n_{j}d s},}\\end{array}\n$$ \n\nwhere in the second line we have applied Stokes’ theorem. Here, $n_{j}$ is the $j$ th component of the unit vector $\\hat{n}$ normal to the boundary $\\delta\\boldsymbol{v}$ . Since the quadrupole moment density is constant, there are only two places in $\\partial v$ where the derivative $\\partial_{i}q_{i j}$ does not vanish [see Fig. 6(b)]: (i) at $\\vec{r}_{1}$ the unit vector normal to the boundary $\\partial v$ , and pointing away from the area $\\boldsymbol{v}$ , is $\\hat{n}=-\\hat{x}$ and $\\begin{array}{r}{\\int_{-\\epsilon}^{\\epsilon}\\partial_{y}q_{y x}d y=-q_{y x}}\\end{array}$ , and (ii) at $\\vec{r}_{2}$ the unit vector normal to $\\partial v$ pointing away from $\\boldsymbol{v}$ is $\\hat{n}=-\\hat{y}$ , which leads to $\\begin{array}{r}{\\int_{-\\epsilon}^{\\epsilon}\\partial_{x}q_{x y}d x=-q_{x y},}\\end{array}$ . Thus, the corner charge is \n\n$$\n\\begin{array}{r}{Q^{\\mathrm{corner}}=\\frac{1}{2}(q_{x y}+q_{y x})=q_{x y}.}\\end{array}\n$$ \n\nBy comparing Eq. (2.21) with (2.22), we conclude that, in the case of only boundary-localized “free” dipole moments, the corner-localized charge is given by the sum of the converging boundary polarizations, whereas in the case of a bulk quadrupole moment, the magnitude of the corner charge matches the magnitude of the quadrupole moment. Since the boundary polarizations induced from a bulk quadrupole have the same magnitude as the quadrupole itself [see Eq. (2.13)], adding up the two boundary polarizations in a similar way over-counts the corner charge. Heuristically, the two boundary polarizations share the corner charge if arising from a bulk quadrupole moment, whereas they both contribute independently if arising from “free” surface polarization. In summary, even though both cases in Fig. 6 have edge-localized polarizations converging at a corner of the material, the resulting corner charge is not determined the same way from the boundary polarizations. For example, if we set $p_{1}=p_{2}=q_{x y}$ so that the magnitudes of the edge polarizations match in both cases, the case of converging edge polarizations (2.21) gives a corner charge $Q^{\\mathrm{corner}}=2q_{x y}$ , while the case of a uniform quadrupole moment gives a corner charge $Q^{\\mathrm{corner}}=q_{x y}$ . \n\nWe now generalize the relations between bulk and boundary moments and their associated boundary charges. In 1D, the difference between the total charge on the end of the system and the free charge (i.e., monopole moment) attached to the end is captured by the dipole moment \n\n$$\n\\boldsymbol{Q}^{\\mathrm{end}}-\\boldsymbol{Q}^{\\mathrm{free}}=\\boldsymbol{p}_{x}.\n$$ \n\nIn 2D, the difference between the total corner charge and that coming from the total surface polarization contributions is determined by the bulk quadrupole moment \n\n$$\n\\begin{array}{r}{Q^{\\mathrm{corner}}-p_{x}^{\\mathrm{edge}}-p_{y}^{\\mathrm{edge}}=-q_{x y}.}\\end{array}\n$$ \n\nFinally, in 3D, we can relate the octupole moment to the difference in the corner charge and the total surface quadrupole \n\nand total hinge polarization via \n\n$$\nQ^{\\mathrm{corner}}-\\left(\\sum_{i=x,y,z}p_{i}^{\\mathrm{hinge}}+q_{x y}^{\\mathrm{face}}+q_{y z}^{\\mathrm{face}}+q_{x z}^{\\mathrm{face}}\\right)=o_{x y z}.\n$$ \n\nWe have implicitly assumed in these three equations that the surfaces, hinges, and corners are all associated with positively oriented normal vectors. For simplicity, we have also dropped $\\boldsymbol{Q}^{\\mathrm{free}}$ in the latter two equations: a free corner monopole has to be subtracted from the corner charge. \n\n# E. Symmetries of the multipole moments \n\nSince we are primarily interested in cases where the multipole moments are quantized by symmetry, we need to consider their symmetry transformations. A full discussion of all the transformation properties of all of the components of every multipole moment can be done but would take us too far afield, so we only briefly comment on the simplest properties that provide useful physical intuition. \n\nWe focus on systems with $d$ -dimensional cubiclike symmetries, e.g., the crystal families of orthorhombic, tetragonal, and cubic materials. For a cubic point group, a nonzero, off-diagonal, $2^{d}$ -pole configuration (e.g., $2^{0}:1$ for charge, $2^{1}$ for dipole $p_{x},2^{2}$ for quadrupole $q_{x y}$ , and $2^{3}$ for octupole $o_{x y z}$ ) is only invariant under the $d$ -dimensional “tetrahedral” subgroup $[T(d)]$ of the $d$ -dimensional cubic symmetry group $[O(d)]$ . In 1D, $T(1)$ is just the identity operation. In 2D, $T(2)$ is the normal subgroup of the dihedral group $D_{4}$ (symmetries of the square) which contains the symmetries $\\{1,C_{4}M_{x},C_{4}M_{y},C_{4}^{2}\\}$ , where $M_{x},M_{y}$ are reflections of only the $x$ and $y$ coordinate, respectively, and $C_{4}$ is the rotation by $\\pi/2$ . The quadrupole moment $q_{x y}$ is invariant under $T(2)$ . In 3D, $o_{x y z}$ is invariant under the tetrahedral subgroup $[T(3)=T_{d}]$ of the cubic group $[O(3)=O]$ . \n\nSince the subgroup which leaves the $2^{d}$ -pole invariant is a normal subgroup, we can consider the coset group, for example, $O/T_{d}\\equiv\\mathbb{Z}_{2}$ . The trivial element of this coset represents all of the elements of $T(d)$ , i.e., the ones that leave the multipole moment invariant. The nontrivial element represents the other transformations in $o$ , all of which will cause the off-diagonal $2^{d}$ poles to switch sign. In 1D, this is simple, as the full symmetry group is just $G=\\{1,M_{x}\\}$ , and the polarization is invariant only under 1, so $G/1=$ $G\\equiv\\mathbb{Z}_{2}$ . In conclusion, under a symmetry in $G$ that projects onto the nonidentity element of the $\\mathbb{Z}_{2}$ factor group, the $2^{d}$ pole of a crystal insulator should be quantized. In addition, charge conjugation $C$ quantizes the $2^{d}$ -pole moment (note that each moment depends linearly on the charge). Under these symmetries, the moment is odd, and is hence required to either vanish or be quantized to a nontrivial value allowed by the presence of the lattice. \n\nHaving defined the multipole moment densities in continuum electromagnetic theory, and having characterized their important observable properties, we now move to describe how they arise in crystalline insulators. We start with a review of dipole moments in 1D crystals, and sequentially advance our description towards bulk and edge dipole moments in \n\n2D crystals, quadrupole moments in 2D crystals, and finally octupole moments in 3D crystals. Due to the dependence of the multipole moments on the origin of coordinates when lower multipole moments do not vanish, we assume in what follows that, for any multipole moment in question, all lower multipole moments vanish. \n\n# III. BULK DIPOLE MOMENT IN 1D CRYSTALS \n\nNeutral one-dimensional crystals only allow for a dipole moment. In insulators, the electronic contribution to the polarization1 arises from the displacement of the electrons with respect to the ionic positive charges. In this section, to calculate the polarization, we diagonalize the electronic projected position operator [10,48,50,54], and construct the Wannier centers and Wannier functions [55,56]. The polarization can then be easily extracted. In doing so, we will recover the result that the electronic polarization is given by the Berry phase accumulated by the parallel transport of the subspace of occupied bands across the Brillouin zone (BZ). The electronic polarization can have a topological nature in the presence of certain symmetries [2,8]. \n\n# A. Preliminary considerations \n\nLet us first consider insulators with discrete translation symmetry, but simply composed of point charges. As seen in Sec. II B, the polarization is well defined only if it has zero net charge. Discrete translation symmetry implies that it is sufficient to characterize the polarization by considering a single unit cell. Thus, given a definition of a unit cell, and a coordinate frame fixed within it, the dipole moment density per unit length is given by \n\n$$\np=\\frac{1}{a}\\left(\\sum_{\\alpha=1}^{N_{\\mathrm{nuclei}}}q_{\\alpha}R_{\\alpha}+\\sum_{\\alpha=1}^{N_{\\mathrm{elec}}}-e r_{\\alpha}\\right),\n$$ \n\nwhere $R_{\\alpha}$ are the positions of the positive charges (i.e. the atomic nuclei), $r_{\\alpha}$ are the electronic positions, and $a$ is the lattice constant (from now on, we will set $a=1$ for simplicity, unless otherwise specified). We are free to reposition the coordinate frame so that its origin is at the center of charge of the atomic nuclei, i.e., at \n\n$$\nR_{c}=\\frac{1}{Q_{\\mathrm{nuclei}}}\\sum_{\\alpha=1}^{N_{\\mathrm{nuclei}}}q_{\\alpha}R_{\\alpha},\n$$ \n\nwhere $\\begin{array}{r}{Q_{\\mathrm{nuclei}}=\\sum_{\\alpha=1}^{N_{\\mathrm{nuclei}}}q_{\\alpha}}\\end{array}$ is the total positive charge within contribution to the polarization density due to positive charges. Although the coordinate frame is now fixed, there is still an ambiguity in the definition of the unit cell, as illustrated in Fig. 7, where the same lattice charge configuration is shown with two definitions of the unit cell. In both cases, the locations of both ionic centers (blue dots) and electrons (red circles) are the same, but the electronic positions relative to the ionic charges in the same cell (black arrows), $r$ and $\\boldsymbol{r}^{\\prime}$ , differ by a lattice constant, i.e., $r^{\\prime}=r-a$ . This difference has no physical meaning, and thus the ambiguity is removed by making the identification \n\n![](images/0ec9dea6acfbb27ee59d03eee8e2487aa7084e8816d9398f4da8215965ec52a6.jpg) \nFIG. 7. Ambiguity in the definition of the electronic positions. Two 1D lattices with one atomic site (blue dots) and one electron (red circles) per unit cell. Although the two physical configurations for the two 1D lattices are the same, the electronic positions $r$ and $r^{\\prime}=r-a$ differ by a lattice constant due to the difference in the definitions of their unit cells. \n\n$$\nr_{\\alpha}\\equiv r_{\\alpha\\mod a,}\n$$ \n\nwhere $a$ is the lattice constant. \n\nWith this important subtlety in mind, we now describe the quantum mechanical theory of electronic polarization in crystals developed by King-Smith, Vanderbilt, and Resta [2,3,6]. This theory characterizes the bulk dipole moment, and is commonly known as the modern theory of polarization. At the core, the approach is as follows: since the electronic wave functions are distributed over the material, we calculate their positions by solving for the eigenvalues of the periodic position operator $\\hat{x}$ projected into the subspace of occupied bands [48,50]. These eigenvalues, or Wannier centers [55], will then map the quantum mechanical problem into the classical problem of point charges [3]. Notably, we find that the eigenfunctions associated to these centers are useful in the formulation of higher multipole moments, as we will see for the case of quadrupole (Sec. VI) and octupole (Sec. VII) moments. \n\n# B. Large Wilson loop, Wannier centers, and Wannier functions \n\nThe position operator for the electrons in a crystal with $N$ unit cells and $N_{\\mathrm{orb}}$ orbitals per unit cell is [54] \n\n$$\n\\hat{x}=\\sum_{R,\\alpha}c_{R,\\alpha}^{\\dagger}|0\\rangle e^{-i\\Delta_{k}(R+r_{\\alpha})}\\langle0|c_{R,\\alpha},\n$$ \n\nwhere $\\alpha\\in1\\ldots N_{\\mathrm{orb}}$ labels the orbital, $R\\in{1\\dots N}$ labels the unit cell, $r_{\\alpha}$ is the position of orbital $\\alpha$ relative to the center of positive charge within the unit cell or, more generally, relative to the (fixed) origin of system of coordinates (see Sec. III A), and $\\Delta_{k}=2\\pi/N$ (remember we have set $a=1$ ). Consider the discrete Fourier transform \n\n$$\n\\begin{array}{l}{{\\displaystyle c_{R,\\alpha}=\\frac{1}{\\sqrt{N}}\\sum_{k}e^{-i k(R+r_{\\alpha})}c_{k,\\alpha}},}\\\\ {{\\displaystyle c_{k,\\alpha}=\\frac{1}{\\sqrt{N}}\\sum_{R}e^{i k(R+r_{\\alpha})}c_{R,\\alpha},}}\\end{array}\n$$ \n\nwhere $k\\in\\Delta_{k}\\cdot(0,1,\\dots N-1)$ . We impose the boundary conditions \n\n$$\nc_{R+N,\\alpha}=c_{R,\\alpha}\\rightarrow c_{k+G,\\alpha}=e^{i G r_{\\alpha}}c_{k,\\alpha},\n$$ \n\nwhere $G$ is a reciprocal lattice vector (the phase $e^{i G r_{\\alpha}}$ is generally $e^{i\\mathbf{G}\\cdot\\mathbf{r}_{\\alpha}}$ , and can be positive or negative depending on the choice of origin). In this new basis, we can alternatively write the position operator as \n\n$$\n\\hat{x}=\\sum_{k,\\alpha}c_{k+\\Delta_{k},\\alpha}^{\\dagger}|0\\rangle\\langle0|c_{k,\\alpha},\n$$ \n\nas well as the second quantized Hamiltonian \n\n$$\nH=\\sum_{k}c_{k,\\alpha}^{\\dagger}[h_{k}]^{\\alpha,\\beta}c_{k,\\beta},\n$$ \n\nwhere summation is implied over repeated orbital indices. Due to the periodicity (3.6), the Hamiltonian $h_{k}$ obeys \n\n$$\nh_{k+G}=V^{-1}(G)h_{k}V(G),\n$$ \n\nwhere \n\n$$\n[V(G)]^{\\alpha,\\beta}=e^{-i G r_{\\alpha}}\\delta_{\\alpha,\\beta}.\n$$ \n\nWe diagonalize this Hamiltonian as \n\n$$\n[h_{k}]^{\\alpha,\\beta}=\\sum_{n}\\big[u_{k}^{n}\\big]^{\\alpha}\\epsilon_{n,k}\\big[u_{k}^{*n}\\big]^{\\beta},\n$$ \n\nwhere $[u_{k}^{n}]^{\\alpha}$ is the $\\alpha$ th component of the eigenstate $\\textstyle|u_{k}^{n}\\rangle$ . To enforce the periodicity (3.9), we impose the periodic gauge \n\n$$\n\\big[u_{\\boldsymbol{k}+\\boldsymbol{G}}^{n}\\big]^{\\alpha}=[V^{-1}(\\boldsymbol{G})]^{\\alpha,\\beta}\\big[u_{\\boldsymbol{k}}^{n}\\big]^{\\beta}.\n$$ \n\nThis diagonalization allows us to write Eq. (3.8) as \n\n$$\nH=\\sum_{n,k}\\gamma_{n,k}^{\\dagger}\\epsilon_{n,k}\\gamma_{n,k},\n$$ \n\nwhere \n\n$$\n\\gamma_{n,k}=\\sum_{\\alpha}\\big[u_{k}^{*n}\\big]^{\\alpha}c_{k,\\alpha}\n$$ \n\nis periodic in the BZ, as it obeys \n\n$$\n\\gamma_{n,k}=\\gamma_{n,k+G}.\n$$ \n\nAs we are interested in insulators at zero temperature, we will focus on the occupied electron bands. We hence build the projection operator into occupied energy bands \n\n$$\nP^{\\mathrm{occ}}=\\sum_{n=1}^{N_{\\mathrm{occ}}}\\sum_{k}\\gamma_{n,k}^{\\dagger}|0\\rangle\\langle0|\\gamma_{n,k},\n$$ \n\nwhere $N_{\\mathrm{occ}}$ is the number of occupied energy bands. From now on, we assume that summations over bands include only occupied energy bands. We now proceed to diagonalize the position operator projected into the subspace of occupied bands [54] \n\n$$\n\\begin{array}{r l r}{\\lefteqn{P^{\\mathrm{occ}}\\hat{x}P^{\\mathrm{occ}}=\\sum_{n,k}\\sum_{n^{\\prime},k^{\\prime}}\\gamma_{n,k}^{\\dagger}|0\\rangle\\langle0|\\gamma_{n^{\\prime},k^{\\prime}}}}\\\\ &{}&\\\\ &{}&{\\qquad\\times\\left(\\sum_{q,\\alpha}\\langle0|\\gamma_{n,k}c_{q+\\Delta_{k},\\alpha}^{\\dagger}|0\\rangle\\langle0|c_{q,\\alpha}\\gamma_{n^{\\prime},k^{\\prime}}^{\\dagger}|0\\rangle\\right).}\\end{array}\n$$ \n\nFrom (3.14) we have $\\langle0|\\gamma_{n,k}c_{q,\\alpha}^{\\dagger}|0\\rangle=[u_{k}^{*n}]^{\\alpha}\\delta_{k,q}$ , so the projected position operator reduces to \n\n$$\nP^{\\mathrm{occ}}\\hat{x}P^{\\mathrm{occ}}=\\sum_{m,n=1}^{N_{\\mathrm{occ}}}\\sum_{k}\\gamma_{m,k+\\Delta_{k}}^{\\dagger}|0\\rangle\\left\\langle u_{k+\\Delta_{k}}^{m}\\right|u_{k}^{n}\\right\\rangle\\langle0|\\gamma_{n,k},\n$$ \n\nwhere we have adopted the notation $\\langle u_{q}^{m}|u_{k}^{n}\\rangle=$ $\\begin{array}{r}{\\sum_{\\alpha}[u_{q}^{*m}]^{\\alpha}[u_{k}^{n}]^{\\alpha}}\\end{array}$ $(\\langle u_{k}^{m}|u_{q}^{n}\\rangle\\ne\\delta_{m,n}\\delta_{k,q}$ in general; they only obey $\\langle u_{k}^{m}|u_{k}^{n}\\rangle=\\delta_{m,n}\\nonumber$ ). \n\nThe matrix Gk with components [Gk]mn = ⟨ukm \u000b |ukn⟩ is not unitary due to the discretization of $k$ . However, it is unitary in the thermodynamic limit, as seen in Appendix C. To render it unitary for finite $N$ , consider the singular value decomposition [57] \n\n$$\nG=U D V^{\\dagger},\n$$ \n\nwhere $D$ is a diagonal matrix. The failure of $G$ to be unitary is manifest in the fact that the (real-valued) singular values along the diagonal of $D$ are less than 1. Therefore, we define, at each $k$ , \n\n$$\nF=U V^{\\dagger}\n$$ \n\nwhich is unitary. We refer to $F_{k}$ as the Wilson line element at $k$ . In the thermodynamic limit $N\\to\\infty$ , we have that $[F_{k}]^{m n}=$ $[G_{k}]^{m n}$ . To diagonalize the projected position operator, let us write the eigenvalue problem: \n\n$$\n(P^{\\mathrm{occ}}\\hat{x}P^{\\mathrm{occ}})|\\Psi^{j}\\rangle=E^{j}|\\Psi^{j}\\rangle,\n$$ \n\nwhich, in the basis $\\gamma_{n,k}|0\\rangle$ , adopts the following form: \n\n$$\n\\left(\\begin{array}{c c c c c}{{0}}&{{0}}&{{0}}&{{...}}&{{F_{k_{N}}}}\\\\ {{F_{k_{1}}}}&{{0}}&{{0}}&{{...}}&{{0}}\\\\ {{0}}&{{F_{k_{2}}}}&{{0}}&{{...}}&{{0}}\\\\ {{\\vdots}}&{{\\vdots}}&{{\\vdots}}&{{\\ddots}}&{{\\vdots}}\\\\ {{0}}&{{0}}&{{0}}&{{...}}&{{0}}\\end{array}\\right)\\left(\\begin{array}{c}{{\\nu_{k_{1}}}}\\\\ {{\\nu_{k_{2}}}}\\\\ {{\\nu_{k_{3}}}}\\\\ {{\\vdots}}\\\\ {{\\nu_{k_{N}}}}\\end{array}\\right)^{j}=E^{j}\\left(\\begin{array}{c}{{\\nu_{k_{1}}}}\\\\ {{\\nu_{k_{2}}}}\\\\ {{\\nu_{k_{3}}}}\\\\ {{\\vdots}}\\\\ {{\\nu_{k_{N}}}}\\end{array}\\right)^{j},\n$$ \n\nwhere $k_{1}=0$ , $k_{2}=\\Delta_{k},\\ldots$ , $k_{N}=\\Delta_{k}(N-1)$ , and $j\\in$ $1\\ldots N_{\\mathrm{occ}}$ . Here, we have replaced $G_{k}$ in Eq. (3.21) by $F_{k}$ to restore the unitary character of the Wilson line elements. By repeated application of the equations above, one can obtain the relation \n\n$$\n\\mathcal{W}_{k_{f}\\leftarrow k_{i}}\\left\\vert\\nu_{k_{i}}^{j}\\right\\rangle=(E^{j})^{(k_{f}-k_{i})/\\Delta_{k}}\\left\\vert\\nu_{k_{f}}^{j}\\right\\rangle,\n$$ \n\nwhere we are adopting the bra-ket notation $|\\nu_{k_{l}}^{j}\\rangle$ for the vector formed by the collection of values $[\\nu_{k_{l}}^{j}]^{n}$ , for $n\\in{1\\dots N_{\\mathrm{occ}}}$ . We define the discrete Wilson line as \n\n$$\n\\mathcal{W}_{k_{f}\\leftarrow k_{i}}=F_{k_{f}-\\Delta_{k}}F_{k_{f}-2\\Delta_{k}}\\dotsc F_{k_{i}+\\Delta_{k}}F_{k_{i}}.\n$$ \n\nFor a large Wilson loop, i.e., a Wilson line that goes across the entire Brillouin zone (from now on, by Wilson loop we refer exclusively to large Wilson loops), Eq. (3.23) results in the eigenvalue problem \n\n$$\n\\mathcal{W}_{k+2\\pi\\leftarrow k}\\left|\\nu_{k}^{j}\\right\\rangle=(E^{j})^{N}\\left|\\nu_{k}^{j}\\right\\rangle,\n$$ \n\nwhere the subscript $k$ labels the starting point, or base point, of the Wilson loop. While the Wilson-loop eigenstates depend \n\non the base point, its eigenvalues do not. Furthermore, since the Wilson loop is unitary, its eigenvalues are simply phases \n\n$$\n(E^{j})^{N}=e^{i2\\pi\\nu^{j}}\n$$ \n\nwhich has $N$ solutions \n\n$$\nE^{j,R}=e^{i2\\pi\\nu^{j}/N+i2\\pi R/N}=e^{i\\Delta_{k}(\\nu^{j}+R)}\n$$ \n\nfor $R\\in{0...N-1}$ . The phases $\\ensuremath{\\boldsymbol\\nu}^{j}$ are the Wannier centers. They correspond to the positions of the electrons relative to the center of the unit cells. The eigenfunctions of the Wilson loop at different base points are related to each other [up to a U(1) gauge, which we now fix to be the identity] by the parallel transport equation \n\n$$\n\\left|\\nu_{k_{f}}^{j}\\right>=e^{-i(k_{f}-k_{i})\\nu^{j}}\\mathcal{W}_{k_{f}\\leftarrow k_{i}}\\left|\\nu_{k_{i}}^{j}\\right>,\n$$ \n\nwhich is a restatement of Eq. (3.23). Since $j\\in1\\ldots N_{\\mathrm{occ}}$ and $R\\in{0...N-1}$ , there are as many projected position operator eigenstates and eigenvalues as there are states in the occupied bands. Given the normalized Wilson-loop eigenstates, the eigenstates of the projected position operator, which now reads as \n\n$$\n(P^{\\mathrm{occ}}\\hat{x}P^{\\mathrm{occ}})\\big|\\Psi_{R}^{j}\\big>=e^{i\\Delta_{k}(\\nu^{j}+R)}\\big|\\Psi_{R}^{j}\\big>,\n$$ \n\nare \n\n$$\n\\left|\\Psi_{R}^{j}\\right\\rangle=\\frac1{\\sqrt{N}}\\sum_{n=1}^{N_{\\mathrm{occ}}}\\sum_{k}\\left[\\nu_{k}^{j}\\right]^{n}e^{-i k R}\\gamma_{n k}^{\\dagger}|0\\rangle,\n$$ \n\nwhere ${[\\nu_{k}^{j}]}^{n}$ is the $n$ th component of the $j$ th Wilson-loop eigenstate $|\\nu_{k}^{j}\\rangle$ . This form of the solution follows directly from (3.22). We call these functions the Wannier functions. Here, $j\\in1\\ldots N_{\\mathrm{occ}}$ labels the Wannier function and $R\\in{0...N-1}$ identifies the unit cell to which they are associated. These states obey \n\n$$\n\\begin{array}{r}{\\left\\langle\\Psi_{R_{1}}^{i}\\middle|\\Psi_{R_{2}}^{j}\\right\\rangle=\\delta_{i,j}\\delta_{R_{1},R_{2}},}\\end{array}\n$$ \n\ni.e., they form an orthonormal basis of the subspace of occupied bands of the Hamiltonian. Before using these results to calculate the polarization, let us comment on the gauge freedom of the Wannier functions. If $|\\nu_{k_{0}}^{j}\\rangle$ is the eigenstate of $\\mathscr{W}_{k_{0}+2\\pi\\leftarrow k_{0}}$ , then so is $e^{i\\phi_{0}}|\\nu_{k_{0}}^{j}\\rangle$ . Naively, one could assign different phases $e^{i\\phi_{k}}$ to each of the $|\\nu_{k}^{j}\\rangle$ in the expansion of (3.30). However, this is not allowed because the phases of the Wilson-loop eigenstates at subsequent crystal momenta $k$ are fixed to $e^{i\\phi_{0}^{-}}$ by the parallel transport relation (3.28), which is our gauge-fixing condition. Thus, the Wannier functions (3.30) inherit only an overall phase factor $e^{i\\phi_{0}}$ , as expected. \n\n# C. Polarization \n\nThe prescription detailed above for the diagonalization of $P^{\\mathrm{occ}}\\hat{x}P^{\\mathrm{occ}}$ reveals that the expected value of the electronic positions relative to the center of positive charge within the unit cell is given by the Wannier centers, which are encoded in the phases of the Wilson-loop eigenvalues, i.e., in \n\n$$\n\\mathcal{W}_{k+2\\pi\\leftarrow k}|\\nu_{k}^{j}\\rangle=e^{i2\\pi\\nu^{j}}|\\nu_{k}^{j}\\rangle.\n$$ \n\nFor $j=1\\ldots N_{\\mathrm{occ}}$ , the Wannier centers are the collection of values $\\{\\nu^{j}\\}$ . There are $N_{\\mathrm{occ}}$ Wannier centers associated to each unit cell, and there are $N_{\\mathrm{occ}}$ electrons per cell in the ground state. The electronic contribution to the dipole moment, measured as the electron charge times the displacement of the electrons from the center of the unit cell, is proportional to \n\n$$\np=\\sum_{j}\\nu^{j}.\n$$ \n\nIn the expression above, we have set the electron charge $e=1$ . For convenience we will continue to set $e=1$ in the remainder of the paper, unless otherwise noted. The expression (3.33) is true for any unit cell due to translation invariance, and thus it is a bulk property of the crystal. Since the Wannier centers are the phases of the eigenvalues of the Wilson loop, we can alternatively write the polarization as \n\n$$\np=-\\frac{i}{2\\pi}\\mathrm{log}\\mathrm{det}[\\mathcal{W}_{k+2\\pi\\leftarrow k}].\n$$ \n\nFurthermore, in the thermodynamic limit (see Appendix C), if we write the Wilson loop in terms of the Berry connection \n\n$$\n[\\mathcal{A}_{k}]^{m n}=-i\\big\\langle u_{k}^{m}\\big|\\partial_{k}\\big|u_{k}^{n}\\big\\rangle,\n$$ \n\nwe have \n\n$$\n\\begin{array}{l}{{\\displaystyle p=-\\frac{i}{2\\pi}\\mathrm{log}\\mathrm{det}\\bigl[e^{-i\\int_{k}^{k+2\\pi}\\mathcal{A}_{k}d k}\\bigr]}}\\\\ {{\\displaystyle\\quad=-\\frac{1}{2\\pi}\\int_{k}^{k+2\\pi}\\mathrm{Tr}[\\mathcal{A}_{k}]d k\\mathrm{mod}1,}}\\end{array}\n$$ \n\nwhich is the well-known expression for the polarization in the modern theory of polarization [2,3,6]. The electronic polarization is proportional to the Berry phase that the subspace of occupied bands $P_{\\bf k}^{\\mathrm{occ}}=|u_{\\bf k}^{n}\\rangle\\langle u_{\\bf k}^{n}|$ accumulates as it is parallel transported around the BZ. \n\n# Polarization and gauge freedom \n\nIf the electrons are “reassigned” to new unit cells, the polarization changes by an integer (see Fig. 7). Mathematically, this is evident in Eq. (3.34) from the fact that the Wannier centers $\\ensuremath{\\boldsymbol\\nu}^{j}$ , defined as the log of a U(1) phase, are also defined mod 1. In the expression (3.36) this ambiguity appears because this expression for the polarization is not gauge invariant. One is free to choose a different “gauge” for the functions $\\textstyle|u_{k}^{n}\\rangle$ : \n\n$$\n\\left|u_{k}^{\\prime m}\\right\\rangle=\\sum_{n}[U_{k}]^{m n}\\left|u_{k}^{n}\\right\\rangle.\n$$ \n\nThe Slater determinant that forms the many-body insulating wave function is left invariant by this transformation. The gauge transformation leads to a changed connection \n\n$$\n\\mathcal{A}_{k}^{\\prime}=U_{k}^{\\dagger}\\mathcal{A}_{k}U_{k}-i U_{k}^{\\dagger}\\partial_{k}U_{k}.\n$$ \n\nThis new adiabatic connection gives a polarization \n\n$$\n\\begin{array}{l}{{\\displaystyle p^{\\prime}=p+\\frac{i}{2\\pi}\\int_{k}^{k+2\\pi}d k\\mathrm{Tr}[U_{k}^{\\dagger}\\partial_{k}U_{k}]}}\\\\ {{\\displaystyle\\quad=p+\\frac{i}{2\\pi}\\int_{k}^{k+2\\pi}d k\\mathrm{Tr}[\\partial_{k}\\ln U_{k}]}}\\\\ {{\\displaystyle\\quad=p+\\frac{i}{2\\pi}\\mathrm{Tr}[\\ln U_{k}]\\Bigg|_{k}^{k+2\\pi}}}\\end{array}\n$$ \n\n$$\n\\begin{array}{l}{{\\displaystyle=p+\\frac{i}{2\\pi}\\ln\\left[\\operatorname*{det}U_{k}\\right]\\Bigg\\vert_{k}^{k+2\\pi}}}\\\\ {{\\displaystyle=p+\\frac{i}{2\\pi}\\sum_{i}\\left[i\\phi_{i}(k+2\\pi)-i\\phi_{i}(k)\\right]}}\\\\ {{\\displaystyle=p+n,}}\\end{array}\n$$ \n\nwhere $n$ is an integer. In the second to last line, $\\{\\phi_{i}(k)\\}$ are the phases of the eigenvalues of $U_{k}$ . The fact that $U_{k}$ is periodic in $k$ implies that the phases of its eigenvalues can differ at most by a multiple of $2\\pi$ between $k$ and $k+2\\pi$ . Thus, we see that different gauge choices may vary the polarization, but only by integers. \n\nIn what follows, we will use the Wilson-loop formulation of the polarization instead of the expression (3.36) written in terms of the gauge-dependent Berry connection. We will later see that the formulation in terms of Wilson loops has a key additional advantage: the Wilson-loop eigenfunctions give us access to the Wannier functions (3.30), which in turn allow us to generalize the concept of a quantized dipole moment, as discussed in the next subsection, to quantized higher multipole moments. \n\n# D. Symmetry protection and quantization \n\nThe polarization can be restricted to specific values in the presence of symmetries. For example, a two-band inversionsymmetric insulator at half-filling has only one electron per unit cell. Thus, the electron center of charge has to be located at either the atomic center or halfway between centers, as any other position of the electron violates inversion symmetry. We say that in this case the polarization is “quantized” to be either 0, for electrons at atomic sites, or $\\frac{1}{2}$ , for electrons in-between atomic sites. In what follows, we show how symmetries impose constraints on the allowed values of the Wannier centers and consequently on the polarization. For that purpose, we refer to the relations for Wilson loops [50] that are detailed in Appendix D. We first define the notation for Wilson loops. We denote a Wilson loop with base point $k$ , and with parallel transport towards increasing values of momentum until reaching $k+2\\pi$ as \n\n# 1. Inversion symmetry \n\nA crystal with inversion symmetry obeys \n\n$$\n\\begin{array}{r}{\\hat{\\mathcal{T}}h_{k}\\hat{\\mathcal{T}}^{-1}=h_{-k},}\\end{array}\n$$ \n\nwhere $\\hat{\\mathcal{I}}$ is the unitary $(\\hat{\\mathcal{I}}^{-1}=\\hat{\\mathcal{I}}^{\\dagger}$ ) inversion operator. As shown in Appendix D, in the presence of inversion the Wilson loops obey \n\n$$\nB_{\\mathcal{T},k}\\mathcal{W}_{x,k}B_{\\mathcal{T},k}^{\\dagger}\\overset{\\mathcal{T}}{=}\\mathcal{W}_{x,-k}^{\\dagger},\n$$ \n\nwhere $B_{\\mathcal{T},k}^{m n}=\\langle u_{k}^{m}|\\hat{\\mathcal{T}}|u_{-k}^{n}\\rangle$ is the unitary sewing matrix that connects the states at $|u_{k}^{m}\\rangle$ and $|u_{-k}^{m}\\rangle$ having equal energies (see Appendix $\\mathrm{~D~}$ for details). Since the Wilson-loop eigenvalues are independent of the base point, Eq. (3.44) implies that the set of Wilson-loop eigenvalues has to be equal to its complex conjugate, which implies, for the set of Wannier centers, \n\n$$\n\\{\\nu_{j}\\}\\stackrel{\\mathcal{Z}}{=}\\{-\\nu_{j}\\}\\mod1.\n$$ \n\nThis forces the Wannier centers to be either 0, $\\frac{1}{2}$ , or to come in pairs $\\{\\nu,-\\nu\\}$ . Physically, inversion symmetry implies that the electrons have to either be (i) centered at an atomic site $(\\nu=0$ ), (ii) in-between sites $\\begin{array}{r}{(\\nu=\\frac{1}{2}.}\\end{array}$ ), or (iii) to come in pairs arranged on opposite sides of each atomic center and equally distant from it $(\\{\\nu,-\\nu\\})$ . In the first and third cases, the polarization is 0, while in the second case it is $\\frac{1}{2}$ . Hence, in general, we have that \n\n$$\np\\stackrel{\\mathcal{Z}}{=}-p\\mod1.\n$$ \n\nThat is, under inversion, \n\n$$\np\\stackrel{\\mathcal{Z}}{=}0\\mathrm{or}1/2.\n$$ \n\nThis quantization under inversion symmetry allows for an alternative way of calculating the Wannier centers. From (3.43) it follows that at the inversion-symmetric momenta $k_{*}=0,\\pi$ we have \n\n$$\n[\\hat{\\mathcal{I}},h_{k_{*}}]=0.\n$$ \n\nThus, the eigenstates of the Hamiltonian at $k_{*}$ can be chosen to be simultaneous eigenstates of the inversion operator \n\n$$\n\\mathcal{W}_{x,k}\\equiv F_{k+N\\Delta_{k}}F_{k+(N-1)\\Delta_{k}}\\:.\\:.\\:F_{k+\\Delta_{k}}F_{k},\n$$ \n\nwhere $F_{k}$ is the unitary matrix resulting from the singular value decomposition of $G_{k}$ , which has components $[G_{k}]^{m n}=$ $\\langle u_{k+\\Delta_{k}}^{m}|u_{k}^{n}\\rangle$ (see Sec. III B). Similarly, denote the Wilson loop with base point $k$ that advances the parallel transport towards decreasing values of momentum until reaching $k-2\\pi$ as \n\n$$\n\\mathcal{W}_{-x,k}\\equiv F_{k-N\\Delta_{k}}F_{k-(N-1)\\Delta_{k}}\\:...F_{k-\\Delta_{k}}F_{k}.\n$$ \n\n$$\n\\hat{\\mathcal{T}}|u_{k_{*}}\\rangle=\\mathcal{T}(k_{*})|u_{k_{*}}\\rangle,\n$$ \n\nwhere $\\mathcal{T}(k_{*})$ are the inversion eigenvalues at momenta $k_{*}=$ $_{0,\\pi}$ . The inversion eigenvalues can then be used as labels for the inversion representation at $k^{*}$ that the occupied bands take. If the representation is the same at $k=0$ and $\\pi$ , the topology is trivial, and the polarization is zero. However, if the representations at these two points of the BZ differ, we have a nontrivial topology associated with a nonzero polarization [17,18,28]. We can encode these relations in the expression \n\nThese Wilson loops obey \n\n$$\n\\mathcal{W}_{-x,k}=\\mathcal{W}_{x,k}^{\\dagger}\n$$ \n\nas shown in Appendix D. We now show the quantization of the polarization in 1D crystals due to inversion and chiral symmetries. \n\n$$\ne^{i2\\pi p}={\\cal T}(0){\\cal T}(\\pi).\n$$ \n\nA formal and complete derivation of the relation between Wilson-loop eigenvalues and inversion eigenvalues was first shown in Ref. [50]. The relations between inversion and Wilson-loop eigenvalues that we will use are shown in Tables I and II. \n\nTABLE I. Relation between inversion and Wilson-loop eigenvalues for an insulator with one occupied band. $\\hat{\\mathcal{I}}$ is the inversion operator. $\\mathcal{W}$ is the Wilson loop. The signs $\\pm$ represent $\\pm1$ . \n\n\n
I eigenvalue at k=0I eigenvalue atk=πW
+1
++
+-1
\n\n# 2. Chiral symmetry \n\nAlthough less evident, chiral (sublattice) symmetry also quantizes the polarization. Chiral symmetry implies that the Bloch Hamiltonian obeys \n\n$$\n\\hat{\\Pi}h_{k}\\hat{\\Pi}^{-1}=-h_{k},\n$$ \n\nwhere $\\hat{\\Pi}$ is the unitary $\\hat{\\Pi}^{-1}=\\hat{\\Pi}^{\\dagger}$ ) chiral operator. Under this symmetry, the Wilson loop obeys \n\n$$\nB_{\\Pi,k}\\mathcal{W}_{k}^{\\mathrm{occ}}B_{\\Pi,k}^{\\dagger}\\overset{\\mathrm{chiral}}{=}\\mathcal{W}_{k}^{\\mathrm{unocc}}.\n$$ \n\nHere, $\\mathcal{W}_{k}^{\\mathrm{occ}}~(\\mathcal{W}_{k}^{\\mathrm{unocc}})$ is the Wilson loop at base point $k$ over occupied (unoccupied) bands, and $B_{\\Pi,k}^{m n}=\\langle u_{k}^{m}|\\hat{\\Pi}|u_{k}^{n}\\rangle$ is a sewing matrix that connects states $\\big|u_{k}^{m}\\big\\rangle$ and $\\ensuremath{\\vert u_{k}^{n}\\rangle}$ having opposite energies, that is, such that $\\epsilon_{m,k}=-\\epsilon_{n,k}$ . Equation (3.52) implies that the Wannier centers from the occupied bands $\\ensuremath{\\boldsymbol\\nu}^{j}$ equal those calculated from the unoccupied bands $\\eta^{j}$ , \n\n![](images/a38ef1f14bf3f666d59cc49804653b8136978db87c7c296e7acf6c97cf8d841d.jpg) \nFIG. 8. Su-Schrieffer-Hegger model with Hamiltonian (3.58). (a) Trivial phase $(\\vert\\gamma\\vert>\\vert\\lambda\\vert)$ . (b) Topological dipole phase $(|\\gamma|<|\\lambda|)$ . (c) Energy spectrum for a chain with open boundaries as a function of $\\gamma$ when $\\lambda=1$ . Red energies correspond to two degenerate edge-localized states. (d) Electron density in the topological dipole phase $\\lambda=1$ , $\\gamma=0.5$ ). The total electronic charge at the edges is $\\pm e/2$ relative to background. \n\nwhich leads to \n\n$$\np^{\\mathrm{occ}}\\ {\\stackrel{\\mathrm{chiral}}{=}}\\ -p^{\\mathrm{unocc}}\\ {\\mathrm{~\\mod~}}1.\n$$ \n\nFrom (3.54) and (3.56) we conclude that \n\n$$\n\\{\\nu_{j}\\}\\stackrel{\\mathrm{chiral}}{=}\\{\\eta_{j}\\}\\mod1\n$$ \n\nand, thus, \n\n$$\np^{\\mathrm{occ}}\\stackrel{\\mathrm{chiral}}{=}p^{\\mathrm{unocc}}.\n$$ \n\nIt is important to recall that to have strict chiral symmetry as we assume here, the number of occupied bands in a gapped system will be equal to the number of unoccupied bands. To conclude our argument, an additional consideration is necessary: the Hilbert space over all bands (occupied and unoccupied) is topologically trivial. Thus, the polarization that results from both the occupied and unoccupied bands is necessarily also trivial, i.e., \n\n$$\np^{\\mathrm{{occ}}}+p^{\\mathrm{{unocc}}}=0\\mod1,\n$$ \n\nTABLE II. Relation between inversion and Wilson-loop eigenvalues for an insulator with two occupied bands. $\\hat{\\mathcal{I}}$ is the inversion operator. $\\mathcal{W}$ is the Wilson loop. The signs $\\pm$ represent $\\pm1$ . c.c. stands for complex-conjugate pair of values of magnitude 1. \n\n\n
I eigenvalue at k=0I eigenvalue at k=πW envalue
(++)(++){+1,+1}
(++)(+-){+1,-1}
(++)(--){-1,-1}
(+-)(+-){c.c.}
\n\n$$\np\\stackrel{\\mathrm{chiral}}{=}0\\mathrm{or}1/2,\n$$ \n\ni.e., the polarization is quantized in the presence of chiral (sublattice) symmetry. \n\nIn what follows, we discuss the features of a system with nonzero polarization by studying the minimal model that realizes the dipole phase. In general, a bulk polarization per unit length of $p$ manifests itself at the boundary in the existence of bound surface charges of magnitude $p$ , in exact correspondence to the classical electromagnetic theory [cf. Eq. (2.9)]. Consequently, the topological dipole phase exhibits quantized, fractional boundary charge of $\\pm e/2$ , which can be protected, e.g., by inversion or chiral symmetries. Additionally, we give a concrete example of adiabatic current being pumped in this model [58–61]. \n\n# E. Minimal model with quantized polarization in 1D \n\nA minimal model for an insulator with bulk polarization in one dimension is the Su-Schrieffer-Hegger (SSH) model [9], which describes a chain with alternating strong and weak bonds between atoms, as in polyacetylene [9]. A tight-binding schematic of this structure is shown in Figs. 8(a) and 8(b). Its Hamiltonian is \n\n$$\nH^{\\mathrm{SSH}}=\\sum_{R}(\\gamma c_{R,1}^{\\dag}c_{R,2}+\\lambda c_{R,2}^{\\dag}c_{R+1,1}+\\mathrm{H.c.}),\n$$ \n\nwhere $\\gamma$ and $\\lambda$ are hopping terms within and between unit cells, respectively. Its corresponding Bloch Hamiltonian in \n\nmomentum space is \n\n$$\nh^{\\mathrm{{SSH}}}(k)={\\binom{0}{\\gamma+\\lambda e^{i k}}},\\quad{\\gamma+\\lambda e^{-i k}}\\atop{0},\n$$ \n\nwhere the basis of the matrix follows the numbering in Fig. 8(a). More compactly, we will write this, and the Hamiltonians to come, in terms of the Pauli matrices $\\sigma_{i}$ , for $i=1,2,3$ : \n\n$$\n\\begin{array}{r}{h^{\\mathrm{SSH}}(k)=[\\gamma+\\lambda\\cos(k)]\\sigma_{1}+\\lambda\\sin(k)\\sigma_{2}.}\\end{array}\n$$ \n\nThe SSH model has energies \n\n$$\n\\epsilon(k)=\\pm\\sqrt{\\lambda^{2}+2\\lambda\\gamma\\cos(k)+\\gamma^{2}}.\n$$ \n\nThe model is gapped unless $|\\gamma|=|\\lambda|$ . Thus, at half-filling, the SSH model is an insulator, unless $\\gamma=\\lambda$ $(\\gamma=-\\lambda)$ where the bands touch at the $k=\\pi$ $k=0$ ) points of the BZ and the system is metallic. \n\n# 1. Symmetries \n\nThe Hamiltonian (3.59) has inversion symmetry $\\hat{\\mathcal{T}}h(k)\\hat{\\mathcal{T}}^{-1}=h(-k)$ , with $\\hat{\\mathcal{T}}=\\sigma_{1}$ , and chiral symmetry $\\hat{\\Pi}h(k)\\hat{\\Pi}^{-1}=-h(k)$ with $\\hat{\\Pi}=\\sigma_{3}$ . Thus, this model has quantized polarization: $p=0$ for $\\vert\\gamma\\vert>\\vert\\lambda\\vert$ and $\\begin{array}{r}{p=\\frac{1}{2}}\\end{array}$ for $\\vert\\gamma\\vert<\\vert\\lambda\\vert$ . At $|\\gamma|=|\\lambda|$ , the energy gap closes. This crossing is necessary to change the insulating phase from one with $p=0$ to $\\frac{1}{2}$ , or vice versa. Thus, the polarization is an index that labels two distinct phases: the “trivial” $p=0$ phase and the “nontrivial” or “dipole” phase $\\begin{array}{r}{p=\\frac{1}{2}}\\end{array}$ . This is the simplest example of a symmetry-protected topological (SPT) phase because the two phases are clearly distinguished only in the presence of the symmetries that quantize the dipole moment. However, both the trivial and the “nontrivial” state are described in terms of localized Wannier states; therefore, a more appropriate term for the “nontrivial” state is an obstructed atomic limit [45]. An illustration of these two phases and the transition point is shown in Fig. 8(c), where the spectrum of the open-boundary Hamiltonian is parametrically plotted as a function of $\\gamma$ , for a fixed value of $\\lambda=1$ . \n\n# 2. Quantization of the boundary charge \n\nIn an SSH crystal with open boundaries, one consequence of the quantization of the bulk polarization to $e/2$ in the nontrivial dipole phase is the appearance of $\\pm e/2$ charge at its edges. This accumulation is due to the existence two degenerate and edge-localized modes. In the presence of chiral symmetry, the energies of the edge-localized states are pinned to zero, and are eigenstates of the chiral operator. In the absence of chiral symmetry, the zero-energy protection of the edge modes is lost; chiral-breaking terms lift the energies of the edge modes away from 0, but they will remain degenerate (resulting in a twofold-degenerate ground state at half-filling) as long as inversion symmetry is preserved in the system. \n\nTo determine a fixed sign for the polarization, one must weakly break the degeneracy of the edge modes. For $N$ unit cells, half-filling implies that there are $N$ electrons, $N-1$ of which fill bulk states. The extra electron thus will fill one of the edge states, but if they are degenerate, the electron cannot pick which state to fill. Splitting the degeneracy infinitesimally is enough to decide which end state is filled, thus choosing the “sign” of the dipole. In the SSH model, the symmetry breaking can be achieved by adding the term $\\delta\\sigma_{3}$ to (3.60) for an infinitesimal value of delta δ. Notice that $\\sigma_{3}$ breaks both chiral and inversion symmetries, as required. \n\n# F. Charge pumping \n\nIn this section, we describe the pumping of electronic charge in insulators by means of adiabatic deformations of the Hamiltonian. Originally conceived by Thouless [11] as a method to extract current out of an insulator, this mechanism also has a well-established connection with the quantum anomalous Hall effect [15]. In what follows, we describe two concrete examples of charge pumping. We start with a pedagogical example that allows us to closely follow the motion of the Wannier centers during the adiabatic evolution. However, this model requires a piecewise continuous parametrization. Therefore, we also describe a pumping with a fully continuous parametrization, although it is less obvious pictorially. \n\nThe pedagogical example uses the SSH model as follows. Consider the SSH Hamiltonian (3.60) with additional onsite energies $\\delta\\sigma_{3}$ , which breaks the chiral and inversion symmetries, \n\n$$\n\\begin{array}{r}{h_{\\delta}^{\\mathrm{SSH}}(k)=[\\gamma+\\lambda\\cos(k)]\\sigma_{1}+\\lambda\\sin(k)\\sigma_{2}+\\delta\\sigma_{3}.}\\end{array}\n$$ \n\nWe modify the parameters $\\lambda,\\gamma$ , and $\\delta$ adiabatically: \n\n$$\n(\\delta,\\lambda,\\gamma)=\\left\\{{(\\cos(t),\\sin(t),0),0
Q eigenvalue at k*Q eigenvalue at k* + G/2Eigenvalue of Wk*+G←k*
(++)(++){1,1}
(++)(+-){1,-1}
(++)(--){-1,-1}
(+-)(+-){c.c.}
\n\n# 2. Wannier bands and the edge Hamiltonian \n\nBeing unitary, we can express the Wilson loop as the exponential of a Hermitian matrix \n\n$$\n\\begin{array}{r}{\\mathcal{W}_{\\mathcal{C},{\\bf k}}\\equiv e^{i H_{\\mathcal{W}_{\\mathcal{C}}}({\\bf k})}.}\\end{array}\n$$ \n\nWe refer to $H_{\\mathcal{W}_{\\mathcal{C}}}(\\mathbf{k})$ as the Wannier Hamiltonian. Notice that in the definition above, the argument $\\mathbf{k}$ of the Wannier Hamiltonian is the base point of the Wilson loop. The eigenvalues of $H_{\\mathcal{W}_{\\mathcal{C}}}(\\mathbf{k})$ are precisely the Wannier bands $\\{2\\pi\\nu_{x}(k_{y})\\}$ or $\\{2\\pi\\nu_{y}(k_{x})\\}$ , which only depend on the coordinate of $\\mathbf{k}$ normal to $\\mathcal{C}$ , e.g., in two dimensions, the eigenvalues depend on $k_{y}$ for $\\mathcal{C}$ along $k_{x}$ and vice versa. \n\nThe Wannier Hamiltonian $H_{\\mathcal{W}_{\\mathcal{C}}}(\\mathbf{k})$ has been shown to be adiabatically connected with the Hamiltonian at the edge perpendicular to $\\mathcal{C}$ [49]. The map, however, is not an exact identification, but rather, one that preserves the topological properties of the Hamiltonian at the edge. The Wannier bands, being the spectrum of $H_{\\mathcal{W}}(\\mathbf{k})$ , are adiabatically connected with the energy spectrum of the edge. Indeed, we see from Fig. 15 that this interpretation correctly describes the edge properties of the systems in Eq. (4.28). For example, we recognize the standard edge-state patterns for the Chern insulator and the QSH insulator, while the weak topological insulator has a flat band of edge states as expected for an ideal system with vanishing correlation length. \n\nLet us now mention some useful relations obeyed by the Wannier Hamiltonian. If we denote with $-\\mathcal{C}$ the contour $\\mathcal{C}$ but in reverse order, it follows that \n\n$$\n\\mathcal{W}_{-\\mathcal{C},\\mathbf{k}}=\\mathcal{W}_{\\mathcal{C},\\mathbf{k}}^{\\dagger}=e^{-i H_{\\mathcal{W}_{\\mathcal{C}}}(\\mathbf{k})},\n$$ \n\nthus, we make the identification \n\n$$\nH_{\\mathcal{W}_{-}c}(\\mathbf{k})=-H_{\\mathcal{W}_{c}}(\\mathbf{k}).\n$$ \n\nThe transformations of Wilson loops under the symmetries studied here are derived in detail in Appendix D. Insulators with a lattice symmetry obey \n\n$$\ng_{\\bf k}h_{\\bf k}g_{\\bf k}^{-1}=h_{D_{g}\\bf k},\n$$ \n\nwhere $g_{\\mathbf{k}}$ is the unitary operator \n\n$$\ng_{\\bf k}=e^{-i(D_{g}{\\bf k})\\cdot\\delta}U_{g}.\n$$ \n\n$U_{g}$ is an $N_{\\mathrm{orb}}\\times N_{\\mathrm{orb}}$ matrix that acts on the internal degrees of freedom of the unit cell, and $D_{g}$ is an operator in momentum space sending $\\mathbf{k}\\to D_{g}\\mathbf{k}$ . In real space, on the other hand, we have $\\mathbf{r}\\rightarrow D_{g}\\mathbf{r}+\\delta$ , where $\\delta=0$ in the case of symmorphic symmetries, or takes a fractional value (in unit-cell units) in the case of nonsymmorphic symmetries. \n\nUsing the definition of the Wannier Hamiltonian (4.33), we can rewrite the expression for the transformation of Wilson loops in Appendix $\\mathrm{~D~}$ into the form \n\n$$\nB_{g,{\\bf k}}H_{\\mathcal{W}_{\\it C}}({\\bf k})B_{g,{\\bf k}}^{\\dagger}=H_{\\mathcal{W}_{D_{g}\\mathcal{C}}}(D_{g}{\\bf k}),\n$$ \n\nwhere \n\n$$\nB_{g,\\mathbf{k}}^{m n}=\\big\\langle u_{D_{g}\\mathbf{k}}^{m}\\big|g_{\\mathbf{k}}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle\n$$ \n\nis the unitary sewing matrix that connects states at $\\mathbf{k}$ with those at $D_{g}\\mathbf{k}$ having the same energy. \n\nHence, we can interpret the usual sewing matrix $B_{g,\\mathbf{k}}$ for the bulk Hamiltonian as a symmetry operator of the Wannier Hamiltonian. In particular, we have \n\n$$\n\\begin{array}{r l}&{B_{M_{x},\\mathbf{k}}H_{\\mathcal{W}_{x}}(\\mathbf{k})B_{M_{x},\\mathbf{k}}^{\\dagger}=-H_{\\mathcal{W}_{x}}(M_{x}\\mathbf{k}),}\\\\ &{B_{M_{y},\\mathbf{k}}H_{\\mathcal{W}_{x}}(\\mathbf{k})B_{M_{y},\\mathbf{k}}^{\\dagger}=H_{\\mathcal{W}_{x}}(M_{y}\\mathbf{k}),}\\\\ &{\\quad B_{\\mathcal{T},\\mathbf{k}}H_{\\mathcal{W}_{x}}(\\mathbf{k})B_{\\mathcal{T},\\mathbf{k}}^{\\dagger}=-H_{\\mathcal{W}_{x}}(-\\mathbf{k}).}\\end{array}\n$$ \n\n# V. EDGE DIPOLE MOMENTS IN 2D CRYSTALS \n\nBefore discussing the bulk quadrupole moment in 2D insulators, we take the intermediate step of studying 2D crystalline insulators which may give rise to edge-localized polarizations [53]. In particular, we describe the procedure to calculate the position-dependent polarization in an insulator, and then we show in an example how the edge polarization arises. We start by considering a 2D crystal with $N_{x}\\times N_{y}$ sites. For calculating the polarization along $x$ as a function of position along $y$ , we choose the insulator to have periodic boundary conditions along $x$ and open boundary conditions along $y$ . In this configuration there is no crystal momenta $k_{y}$ , and we can treat this crystal as a wide, pseudo-1D lattice by absorbing the labels $R_{y}\\in1\\ldots N_{y}$ into the internal degrees of freedom of an enlarged unit cell that extends along the entire length of the crystal in the $y$ direction. This is shown schematically in Fig. 16(b). Thus, the formulation in Sec. III B follows through in this case, with the redefinition \n\n$$\nc_{k,\\alpha}\\rightarrow c_{k_{x},R_{y},\\alpha}\n$$ \n\nwhich allows us to write the second-quantized Hamiltonian as \n\n$$\nH=\\sum_{k_{x}}c_{k_{x},R_{y},\\alpha}^{\\dagger}\\big[h_{k_{x}}\\big]^{R_{y},\\alpha,R_{y}^{\\prime},\\beta}c_{k_{x},R_{y}^{\\prime},\\beta}\n$$ \n\nfor ${\\alpha,\\beta\\in1\\dots N_{\\mathrm{orb}}}$ and $R_{y},R_{y}^{\\prime}\\in{1\\ldots N}_{y}$ . In the above redefinitions, notice that, since the boundaries remain closed along $x,k_{x}$ is still a good quantum number. We diagonalize this Bloch Hamiltonian as \n\n$$\n{\\left[h_{k_{x}}\\right]}^{R_{y},\\alpha,R_{y}^{\\prime},\\beta}=\\sum_{n}{\\left[u_{k_{x}}^{n}\\right]}^{R_{y},\\alpha}\\epsilon_{n,k_{x}}{\\left[u_{k_{x}}^{*n}\\right]}^{R_{y}^{\\prime}\\beta},\n$$ \n\nwhere $n\\in1\\ldots N_{\\mathrm{orb}}\\times N_{y}$ . So, if the 2D Bloch Hamiltonian with periodic boundary conditions along $x$ and $y$ , $h_{(k_{x},k_{y})}$ , \n\n![](images/89a677a48f15d27daf6df99380566ef6a95a1d961e110dd77049fb0329494b3b.jpg) \nFIG. 16. Edge polarization in insulator with Hamiltonian (5.10) (inversion symmetric). (a) Lattice with periodic boundaries. (b) Lattice with periodic boundaries along $x$ and open along $y$ . Long vertical rectangles are redefined unit cells in the pseudo-1D lattice construction. (c) Onsite potential on the lattice. Red (blue) sites represent the onsite energies of $+\\delta\\left(-\\delta\\right)$ that break $M_{x}$ and $M_{y}$ symmetry but preserve inversion. (d), (g) Wannier bands $\\nu_{x}(k_{y})$ and $\\nu_{y}(k_{x})$ for the configuration in (a) which has full periodic boundaries. (e) Wannier values $\\nu_{x}$ and (f) polarization $p_{x}(R_{y})$ for the configuration in (b) which has an open boundary. (h) Wannier values $\\nu_{y}$ and (i) polarization $p_{y}(R_{x})$ for a configuration as in (b) but with boundaries open along $x$ and closed along $y$ . In all plots we set $\\lambda_{x}=1,\\lambda_{y}=0.5$ , $\\gamma=0.1$ , $\\delta=0.2$ , and the strength of the small perturbation to break chiral and time-reversal symmetries (see text) to 0.15. We verify that this perturbation does not close the energy gap. \n\nhas $N_{\\mathrm{occ}}$ occupied bands, its associated pseudo-1D Bloch Hamiltonian $h_{k_{x}}$ in Eq. (5.3) has $N_{\\mathrm{occ}}\\times R_{\\mathrm{y}}$ occupied bands. We can diagonalize the Hamiltonian (5.2) as \n\n$$\nH=\\sum_{n,k_{x}}\\gamma_{n,k_{x}}^{\\dagger}\\epsilon_{n,k_{x}}\\gamma_{n,k_{x}},\n$$ \n\nwhere \n\n$$\n\\gamma_{n,k_{x}}=\\sum_{R_{y},\\alpha}\\big[u_{k_{x}}^{*n}\\big]^{R_{y},\\alpha}c_{k_{x},R_{y},\\alpha}.\n$$ \n\nFollowing Sec. III B, the matrices \n\n$$\n\\left[G_{k_{x}}\\right]^{m n}\\equiv\\sum_{R_{y},\\alpha}{\\left[u_{k_{x}+\\Delta k_{x}}^{*m}\\right]^{R_{y},\\alpha}}\\left[u_{k_{x}}^{n}\\right]^{R_{y},\\alpha}\n$$ \n\nare used in the construction of the Wilson line elements $[F_{k_{x}}]^{m n}$ (via singular value decomposition) and subsequently the Wilson loops $[\\mathcal{W}_{k_{x}+2\\pi\\leftarrow k_{x}}]^{m n}$ , where $m,n\\in{1}\\ldots N_{\\mathrm{occ}}\\times N_{y}$ . \n\nNotice that the size of these Wilson-loop matrices is $N_{y}$ times larger than the size of Wilson-loop matrices when both boundaries are closed in the crystal. \n\nThe hybrid Wannier functions have the same form as in Eq. (3.30): \n\n$$\n\\left|\\Psi_{R_{x}}^{j}\\right\\rangle=\\frac{1}{\\sqrt{N_{x}}}\\sum_{n=1}^{N_{\\mathrm{occ}}\\times N_{y}}\\sum_{k_{x}}\\left[\\nu_{k_{x}}^{j}\\right]^{n}e^{-i k_{x}R_{x}}\\gamma_{n,k_{x}}^{\\dagger}\\left|0\\right\\rangle\n$$ \n\nfor $j\\in{1}\\dots N_{\\mathrm{occ}}\\times N_{y}$ , $R_{x}\\in{1\\ldots N_{x}}$ , and where ${[\\nu_{k_{x}}^{j}]}^{n}$ is the nth component of the $j$ th Wilson-loop eigenstate $|\\nu_{k_{x}}^{j}\\rangle$ , and $\\gamma_{n,k_{x}}^{\\dagger}$ is given in Eq. (5.5). In order to spatially resolve the $x$ component of the polarization along the $y$ direction, we calculate the probability density of the hybrid Wannier functions (5.7): \n\n$$\n\\begin{array}{r l r}&{}&{\\rho^{j,R_{x}}(R_{y})=\\displaystyle\\sum_{R_{x}^{j},\\alpha}\\langle\\Psi_{R_{x}}^{j}|\\phi_{R_{x}^{j}}^{R_{y},\\alpha}\\rangle\\langle\\phi_{R_{x}^{j}}^{R_{y},\\alpha}|\\Psi_{R_{x}}^{j}\\rangle}\\\\ &{}&{=\\displaystyle\\frac{1}{N_{x}}\\sum_{k_{x},\\alpha}\\big\\lvert\\big[u_{k_{x}}^{n}\\big]^{R_{y},\\alpha}\\big[\\nu_{k_{x}}^{j}\\big]^{n}\\big\\rvert^{2}}\\end{array}\n$$ \n\n(in the first equation above, no sums are implied over repeated indices). Notice that there is no dependence on the unit cell $R_{x}$ , as expected since the density is translationally invariant in the $x$ direction. Thus, we can write $\\rho^{j,R_{x}}$ simply as $\\rho^{j}$ . This probability density then allows us to resolve the hybrid Wannier functions (5.7) along the $y$ direction. In particular, it will let us determine whether any of these functions are localized at the (open) edges at $R_{y}=0,N_{y}$ . This probability density also allows us to calculate the $x$ component of the polarization via \n\n$$\np_{x}(R_{y})=\\sum_{j}\\rho^{j}(R_{y})\\nu_{x}^{j}\n$$ \n\nwhich is resolved at each site $R_{y}$ . \n\nWe now illustrate the existence of edge polarization with an example. Consider the insulator with Bloch Hamiltonian \n\n$$\n\\begin{array}{r l}&{h(\\mathbf{k})=\\binom{\\delta\\tau_{0}}{q^{\\dagger}(\\mathbf{k})}\\quad q(\\mathbf{k})\\bigg),}\\\\ &{q(\\mathbf{k})=\\binom{\\gamma+\\lambda_{x}e^{i k_{x}}}{\\gamma+\\lambda_{y}e^{-i k_{y}}}\\quad\\gamma+\\lambda_{y}e^{i k_{y}}\\bigg),}\\end{array}\n$$ \n\nwhere $\\tau_{0}$ is the $2\\times2$ identity matrix and $\\tau_{a}$ , $a=1,2,3$ , are Pauli matrices. A tight-binding representation of this model is shown in Fig. 16(a). $\\gamma$ is the strength of the coupling within unit cells, represented by red lines in Fig. 16(a), and $\\lambda_{x}$ and $\\lambda_{y}$ are the strengths of horizontal and vertical hoppings between nearest-neighbor cells. $\\delta$ is the amplitude of an onsite potential [Fig. 16(c)] that breaks reflection symmetry along $x$ and $y$ , but maintains inversion symmetry. When $\\delta=0$ , this model has reflection and inversion symmetries, with operators $\\hat{M}_{x}=$ $\\tau_{x}\\otimes\\tau_{0}$ , $\\hat{M}_{y}=\\tau_{x}\\otimes\\tau_{x}$ , and $\\dot{\\hat{\\mathcal{T}}}=\\tau_{0}\\otimes\\tau_{x}$ . \n\nThis insulator also has fine-tuned chiral and time-reversal symmetries. However, since we are only interested in protection due to spatial symmetries, we add a small perturbation to (5.10) in our numerics of the form \n\n$$\n\\begin{array}{r l}&{h_{\\mathrm{pert}}(\\mathbf{k})=E E\\cos(k_{x})+O E\\sin(k_{x})}\\\\ &{~+E E\\cos(k_{y})+E O\\sin(k_{y}),}\\end{array}\n$$ \n\n![](images/5ca82eb2cded64fcc028a816c3ab7fabf0a37296b8e3d6c84c383f600437adb5.jpg) \nFIG. 17. Electronic charge density in an insulator with Hamiltonian (5.10) with full open boundaries. There are boundary charges at the four corners. \n\nwhere $E E,O E$ , and $E O$ are $4\\times4$ random matrices that obey \n\n$$\n\\begin{array}{r}{[E E,\\hat{M}_{x}]=0,\\quad[E E,\\hat{M}_{y}]=0,}\\\\ {\\{O E,\\hat{M}_{x}\\}=0,\\quad[O E,\\hat{M}_{y}]=0,}\\\\ {\\ [E O,\\hat{M}_{x}]=0,\\quad\\{E O,\\hat{M}_{y}\\}=0,}\\end{array}\n$$ \n\nand with entries in the range [0,1]. These nearest-neighbor perturbations break the chiral and time-reversal symmetries, while preserving the reflection symmetries along both $x$ and $y$ , as well as inversion symmetry. These perturbations are added to ensure that the interesting features do not rely on these fine-tuned symmetries. \n\nWe first consider the general case of generating nonquantized edge polarizations by breaking reflection symmetries (Figs. 16 and 17), and later on discuss the special case in which these edge polarizations are quantized by restoring reflection symmetries (Fig. 18). In both cases, however, preserving inversion symmetry is necessary in order to have an overall vanishing bulk polarization. In particular, well-defined edge polarizations require that the edges do not accumulate charge and are neutral, hence, the bulk of the insulator should not be polarized. \n\nFor the general case of nonquantized edge polarizations, we consider $\\lambda_{x}>\\lambda_{y}$ and $\\gamma\\ll|\\lambda_{x}-\\lambda_{y}|$ . Under these conditions, the crystal is an insulator at half-filling. The inversion eigenvalues of the occupied bands come in $\\pm1$ pairs at all symmetry points. Therefore, there is no protection of degeneracies in the Wannier bands, as we can see from the plots of $\\nu_{x}(k_{y})$ and $\\nu_{y}(k_{x})$ shown in Figs. 16(d) and $16(\\mathrm{g)}$ . If all the boundaries of the system are closed, the crystal has uniform, vanishing bulk polarization protected by inversion symmetry. If instead we open the boundaries along $y$ , as in Fig. 16(b), we can use the formulation from earlier in this section to treat this crystal as a pseudo-1D insulator, with redefined unit cells as shown by the long vertical rectangles in Fig. 16(b). The Wannier values $\\nu_{x}^{j}$ , for $j\\in1\\dots40$ $\\cdot N_{\\mathrm{occ}}=2$ , $N_{y}=20$ ), obtained from this calculation are shown in Fig. 16(e). Using these values and their associated hybrid-Wannier functions, we calculate the polarization $p_{x}(R_{y})$ using (5.9). This is shown in Fig. 16(f). Remarkably, although the polarization vanishes in the bulk, there is edge-localized polarization parallel to the edge. If, instead of opening the boundaries along $y$ , we choose to open them in $x$ , we observe the Wannier values $\\nu_{y}^{j}$ , for $j\\in1\\dots40$ , and polarization $p_{y}(R_{x})$ shown in Figs. 16(h) and 16(i), respectively. We find a vanishing polarization in the bulk, but nonzero edge-localized polarizations tangent to the edge. For our choice of $\\lambda_{x}>\\lambda_{y}$ the values of $|p_{y}|$ localized at the $R_{x}=0,N_{x}$ edges are larger than the values $|p_{x}|$ localized at $R_{y}=0{,}N_{y}$ . \n\n![](images/91ca099203b8f8c16a2355ee00d7745668e439d2d84881ffa1836a851a32345e.jpg) \nFIG. 18. Insulator with Bloch Hamiltonian (5.10) and $\\delta=0$ . Here, we set $\\lambda_{x}>\\lambda_{y}$ . (a) $M_{x}$ eigenvalues along the $(0,k_{y})$ and $(\\pi,k_{y})$ . (b) $M_{y}$ eigenvalues along the $(k_{x},0)$ and $(k_{x},\\pi)$ . (c) Wannier bands $\\nu_{x}(k_{y})$ . (d) Wannier values $\\nu_{x}$ when boundaries are open along $y$ . (e) $p_{x}(R_{y})$ for configuration as in (d). (f) Wannier bands $\\nu_{y}(k_{x})$ . (g) Wannier values $\\vert\\nu_{y}$ when boundaries are open along $x$ . Values at $\\nu_{x}=0.5$ have edge-localized eigenstates. (h) $p_{y}(R_{x})$ for configuration as in (g). The parameters used here are as in Fig. 16 but with $\\delta=0$ , except for (e) and (h), for which $\\delta=10^{-4}$ . \n\nTo complete the picture, we ask what happens if the edge polarization is terminated at a corner. Figure 17 shows the charge density in this insulator [Eq. (5.10)] when both boundaries are open. We see that, relative to the background charge density of $2e$ per unit cell, there are corner-localized charges ${\\cal Q}^{\\mathrm{corner}}$ . These charges and the edge polarizations obey $Q^{\\mathrm{corner}}=p^{\\mathrm{edge\\}x}+p^{\\mathrm{edge\\y}}$ , as expected for insulators with vanishing bulk dipole and quadrupole moments (Sec. II D). As such, this polarization is purely a surface effect [51] and not generated by a bulk quadrupole moment. \n\nNow, let us consider the case with reflection symmetry. As is typical for these types of calculations we still must break the reflection symmetries infinitesimally by setting $0<\\delta\\ll\\gamma,\\lambda_{x},\\lambda_{y}$ . This infinitesimal, nonzero $\\delta$ perturbation breaks reflection symmetries softly and is necessary to choose an unambiguous sign for the quantized edge polarizations. In a lattice with full open boundary conditions, this perturbation serves to split the degeneracy of the four corner-localized mid-gap modes to determine how they are filled at half-filling. This then chooses the signs of the corner charges in a way consistent with the choice of edge polarizations. \n\nWe find that for $\\lambda_{x}>\\lambda_{y}$ we have $\\begin{array}{r}{Q^{\\mathrm{corner}}=p^{\\mathrm{edge\\}y}=\\frac{1}{2}}\\end{array}$ and $p^{{\\mathrm{edge}}\\ x}=0$ , while for $\\lambda_{y}>\\lambda_{x}$ we find $\\begin{array}{r}{Q^{\\mathrm{corner}}=p^{\\mathrm{edge\\}x}=\\frac{1}{2}}\\end{array}$ and $p^{{\\mathrm{edge}}\\ y}=0$ . Let us focus on the case $\\lambda_{x}>\\lambda_{y}$ . By setting $\\delta=0$ , the reflection eigenvalues for this insulator are indicated in Figs. 18(a) and 18(b). Based on the analysis of reflection eigenvalues summarized in Table III, we conclude that $M_{x}$ fixes the Wannier bands to $\\begin{array}{r}{\\nu_{x}^{1,2}(k_{y})=\\frac{1}{2}}\\end{array}$ , as in Fig. 18(c), while $M_{y}$ does not restrict the values of $\\nu_{y}^{1,2}(k_{x})$ to either 0 or $\\frac{1}{2}$ . Instead, they only have to obey $\\nu_{y}^{1}(k_{x})=-\\nu_{y}^{2}(k_{x})$ , as in Fig. 18(f). If we now open the boundaries along $y$ and calculate $\\nu_{x}^{j}$ , we obtain degenerate values $\\begin{array}{r}{\\nu_{x}^{j}=\\frac{1}{2}}\\end{array}$ [Fig. 18(d)], which result in $p_{x}(R_{y})=0$ [Fig. 18(e)]. If we instead open the boundaries along $x$ and calculate $\\nu_{y}^{j}$ we obtain the gapped bands which have corresponding Wannier eigenstates that have weight primarily in the bulk of the sample. Interestingly, in addition to the gapped bulk Wannier states, we find a pair of Wannier values pinned at $\\frac{1}{2}$ that have eigenstates localized at the edges $R_{x}=0$ and $N_{x}$ [Fig. 18(g)]. It is this pair of states that results in the edge polarization of $\\pm{\\frac{1}{2}}$ , as shown in Fig. 18(h) [a small value of $\\delta=10^{-4}$ was chosen for Figs. 18(e) and 18(h) to break Wannier degeneracies]. \n\nIn contrast to this phenomenology, we will see in Sec. VI that insulators with quadrupole moments also have edgelocalized polarizations and corner-localized charges, but, unlike in the present case, these boundary properties obey $|Q^{\\mathrm{corner}}|=|p^{\\mathrm{edge}\\ x}|=|p^{\\mathrm{edge}\\ y}|$ , as required for a quadrupole (see Sec. II D). \n\n# VI. BULK QUADRUPOLE MOMENT IN 2D CRYSTALS \n\nAny quadrupole insulator should have three basic properties: (i) its bulk dipole moment must vanish, otherwise the quadrupole moment is ill defined (see Sec. II B); (ii) the insulator must have at least two occupied bands since a crystal with one occupied band can only generate dipole moments (a quadrupole is made from two separated dipoles); and (iii) it should have edges that are insulators themselves, as only insulating edges can host edge-localized polarization (hence, edges should not host gapless states and thus the bulk must have Chern number $n=0$ ). \n\nFrom the classical analysis of Sec. II C 2 we concluded that the boundary signatures of an ideal 3D insulator with only bulk quadrupole moment density are the existence of charge density per unit length at hinges $\\begin{array}{r}{\\overline{{\\lambda}}^{\\mathrm{hinge}a,b}=\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}q_{i j}}\\end{array}$ and polarization density per unit area at faces $p^{{\\mathrm{face}}a}=$ $n_{i}^{(a)}q_{i j}$ , where in these two expressions summation is implied over repeated indices. In 2D, these expressions reduce to corner charges and edge polarization density per unit length, respectively: \n\n$$\n\\begin{array}{c}{{Q^{\\mathrm{corner}a,b}=\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}q_{i j},}}\\\\ {{p_{j}^{\\mathrm{edge}a}=n_{i}^{(a)}q_{i j}.}}\\end{array}\n$$ \n\nIn the expressions above, $q_{i j}$ is the quadrupole moment per unit area, with $q_{x y}=q_{y x}\\neq0$ , $q_{x x}=q_{y y}=0$ . \n\nThe insulator with Hamiltonian (5.10) meets all the three basic requirements: it is an insulator with two electrons per unit cell, zero bulk polarization, and no Chern number. Furthermore, it does have corner charges when both boundaries are open. However, it fails to meet the relations (6.1); its edge polarizations are not of the same magnitude as its corner charge. Instead, they obey $Q^{\\mathrm{corner}}=p^{\\mathrm{edge\\}x}+p^{\\mathrm{edge\\}y}$ (see Sec. V) and can be accounted for by the theory of polarization up to dipole moments (see Sec. II D). \n\nIn this section, we describe a model realization of a symmetry-protected quadrupole insulator, an insulator with vanishing dipole moment and fractional, quantized quadrupole moment, that manifests through the predicted boundary signatures of Eq. (6.1). This model has two occupied bands, and a vanishing Chern number. Crucially, its pair of Wannier bands are gapped, and each Wannier band can have an associated Berry phase. Physically, this corresponds to a bulk configuration in which two parallel dipoles aligned along one direction are separated along its perpendicular direction. We first describe the formalism of Wannier band topology for 2D insulators, and then describe the observables of a quadrupole insulator. We will then explore the quantization of dipole pumping resulting from nontrivial adiabatic cycles that connect the quadrupole and trivial phases, and end with a description of an insulator with hinge-localized chiral modes in 3D which exhibits the same topology as the dipole pumping process. \n\n# A. Wannier-sector polarization \n\nIn this section, we study the topology of Wannier bands $\\nu_{x}^{j}(k_{y})$ that are gapped across the entire 1 $\\mathbf{\\nabla})\\mathbf{B}Z k_{y}\\in(-\\pi,\\pi]$ a minimal example of which is shown in Fig. 19. Due to the gap in the Wannier spectrum around $\\begin{array}{r}{\\nu_{x}=\\frac{1}{2}}\\end{array}$ we can broadly \n\n![](images/f7dca43718ebc3df67b704788268f3fd48753bc1ae4e9400228e349b607f6bee.jpg) \nFIG. 19. Gapped Wannier bands $\\nu_{x}^{\\pm}(k_{y})$ (red lines to the right of the BZ) and $\\nu_{y}^{\\pm}(k_{x})$ (blue lines above of the BZ) of the quadrupole insulator with Hamiltonian (6.29). \n\ndefine two Wannier sectors \n\n$$\n\\begin{array}{r l}&{\\nu_{x}^{-}=\\big\\{\\nu_{x}^{j}(k_{y}),\\mathrm{~s.t.~}\\nu_{x}^{j}(k_{y})\\mathrm{~is~below~the~Wannier~gap}\\big\\},}\\\\ &{\\nu_{x}^{+}=\\big\\{\\nu_{x}^{j}(k_{y}),\\mathrm{~s.t.~}\\nu_{x}^{j}(k_{y})\\mathrm{~is~above~the~Wannier~gap}\\big\\}.}\\end{array}\n$$ \n\nSince the Wannier bands are defined mod 1, we adopt the convention of defining the Wannier sectors $\\nu_{x}^{-}\\in[0,\\frac{1}{2})$ and $\\nu_{x}^{+}\\in[\\frac{1}{2},1)$ . \n\nWe then choose those above or below the gap and form the projector \n\n$$\n\\begin{array}{c}{{\\displaystyle P_{\\nu_{x}}=\\sum_{j=1}^{N_{W}}\\sum_{R_{x},k_{y}}\\left\\vert\\Psi_{R_{x},k_{y}}^{j}\\middle>\\middle<\\Psi_{R_{x},k_{y}}^{j}\\right\\vert}}\\\\ {{\\displaystyle\\ }}\\\\ {{\\displaystyle=\\sum_{j=1}^{N_{W}}\\sum_{n,m=1}^{N_{\\mathrm{oc}}}\\sum_{\\bf k}\\gamma_{n,{\\bf k}}^{\\dag}\\left\\vert0\\middle>\\left[\\nu_{x,{\\bf k}}^{j}\\right]^{n}\\left[\\nu_{x,{\\bf k}}^{\\ast j}\\right]^{m}\\left<0\\right\\vert\\gamma_{m,{\\bf k}},}}\\end{array}\n$$ \n\nwhere $\\sum_{j}^{N_{W}}$ is a summation over all Wannier bands in the sector $\\nu_{x}$ , for $\\nu_{x}=\\nu_{x}^{+}$ or $\\nu_{x}^{-}.\\ N_{W}$ is the number of Wannier bands in sector $\\nu_{x}$ . $R_{x}\\in{0}...N_{x}-1$ labels the unit cells, $k_{y}=\\Delta_{k_{y}}n_{y}$ , for $\\Delta_{k_{y}}=2\\pi/N_{y}$ , and $n_{y}\\in{0,1,...,N_{y}-1}$ is the crystal momentum along $y$ . \n\nWe are interested in studying the topological properties of the subspace spanned by $P_{\\nu_{x}}$ . As we will see in Sec. IV B 2, the topology of the Wannier sectors is related to the topology of the physical edge Hamiltonian. As such, it will provide a bulk measure of the edge topology. In particular, we want to diagonalize the position operator \n\n$$\n\\begin{array}{r l r}{\\lefteqn{\\hat{y}=\\sum_{\\mathbf{R},\\alpha}c_{\\mathbf{R},\\alpha}^{\\dagger}|0\\rangle e^{-i\\Delta_{k_{y}}(R_{y}+r_{\\alpha,y})}\\langle0|c_{\\mathbf{R},\\alpha}}}\\\\ &{}&{=\\sum_{k_{x},k_{y},\\alpha}c_{k_{x},k_{y}+\\Delta_{k_{y}},\\alpha}^{\\dagger}|0\\rangle\\langle0|c_{k_{x},k_{y},\\alpha},\\quad}\\end{array}\n$$ \n\nprojected into the Wannier sector $\\nu_{x}$ \n\n$$\n\\begin{array}{l}{{\\displaystyle P_{\\nu_{x}}\\hat{y}P_{\\nu_{x}}=\\sum_{j,j^{\\prime}=1}^{N_{W}}\\sum_{\\textbf{k}}\\sum_{n,m,n^{\\prime},m^{\\prime}=1}^{N_{\\mathrm{occ}}}\\gamma_{n,\\mathbf{k}+\\Delta_{\\mathbf{k}_{y}}}^{\\dagger}\\vert0\\rangle\\langle0\\vert\\gamma_{n^{\\prime},\\mathbf{k}}}}\\\\ {{\\displaystyle~\\times\\left(\\left[\\nu_{x,\\mathbf{k}+\\Delta_{\\mathbf{k}_{y}}}^{j}\\right]^{n}\\left[\\nu_{x,\\mathbf{k}+\\Delta_{\\mathbf{k}_{y}}}^{*j}\\right]^{m}\\right.}}\\\\ {{\\displaystyle\\left.\\times\\left\\middle[\\nu_{x,(k_{x},k_{y})}^{j^{\\prime}*}\\right]^{n^{\\prime}}.}\\end{array}\n$$ \n\nTo diagonalize $P_{\\nu_{x}}\\hat{y}P_{\\nu_{x}}$ , we calculate the Wilson loop along $y$ : \n\n$$\n\\begin{array}{r l}&{\\bigl[\\mathcal{W}_{y,\\mathbf{k}}^{\\nu_{x}}\\bigr]^{n,n^{\\prime}}=F_{y,\\mathbf{k}+N_{y}\\Delta_{\\mathbf{k}_{y}}}^{\\nu_{x}}\\cdot\\cdot\\cdot\\cdot F_{y,\\mathbf{k}+\\Delta_{\\mathbf{k}_{y}}}^{\\nu_{x}}F_{y,\\mathbf{k}}^{\\nu_{x}}}\\\\ &{\\qquad=\\bigl[\\nu_{x,\\mathbf{k}+N_{y}\\Delta_{\\mathbf{k}_{y}}}^{j}\\bigr]^{n}[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}\\bigr]^{j,j^{\\prime}}\\bigl[\\nu_{x,\\mathbf{k}}^{j^{\\prime}*}\\bigr]^{n^{\\prime}}}\\\\ &{\\qquad=\\bigl[\\nu_{x,\\mathbf{k}}^{j}\\bigr]^{n}\\bigl[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}\\bigr]^{j,j^{\\prime}}\\bigl[\\nu_{x,\\mathbf{k}}^{j^{\\prime}*}\\bigr]^{n^{\\prime}}}\\end{array}\n$$ \n\nfor $n,n^{\\prime}\\in1\\ldots N_{\\mathrm{occ}}$ and $j,j^{\\prime}\\in1...N_{W}.\\tilde{\\mathcal{W}}$ $\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ is the Wilson loop along $y$ over the Wannier sector $\\nu_{x}$ performed over the Wannier band basis \n\n$$\n\\begin{array}{r l r}{\\left[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}\\right]^{j,j^{\\prime}}=\\big\\langle w_{x,\\mathbf{k}+N_{y}\\Delta_{\\mathbf{k}_{y}}}^{j}\\big|w_{x,\\mathbf{k}+(N_{y}-1)\\Delta_{\\mathbf{k}_{y}}}^{r}\\big\\rangle\\big\\langle w_{x,\\mathbf{k}+(N_{y}-1)\\Delta_{\\mathbf{k}_{y}}}^{r}\\big|\\downarrow...}&\\\\ {\\big|w_{x,\\mathbf{k}+\\Delta_{\\mathbf{k}_{y}}}^{s}\\big\\rangle\\big\\langle w_{x,\\mathbf{k}+\\Delta_{\\mathbf{k}_{y}}}^{s}\\big|w_{x,\\mathbf{k}}^{j^{\\prime}}\\big\\rangle.}&{(6.11)}&\\end{array}\n$$ \n\nIn the expression above, summation is implied over repeated indices $r,\\hdots,s\\in1\\hdots N_{W}$ over all Wannier bands in the Wannier sector $\\nu_{x}$ . \n\nSince $N_{W}
StatesMx eigenvalueMy eigenvalueI eigenvalue
(I++>,|- ->)(+-)(+-)(-1)(+1,+1)
(I+->,|-+>)(+-)(-+)(-1)(-1,-1)
\n\nare \n\n$$\n\\hat{\\mathcal{T}}|m_{x},m_{y}\\rangle=m_{x}m_{y}|m_{x},m_{y}\\rangle.\n$$ \n\nThe two combinations of states that have $\\hat{M}_{x}$ and $\\hat{M}_{y}$ eigenvalues of $(+-)$ are listed in Table IV. However, those two options do not meet the third condition of having $\\hat{\\boldsymbol{\\mathcal{I}}}$ eigenvalues $\\left(+-\\right)$ at the high-symmetry points. Instead, the $\\hat{\\boldsymbol{\\mathcal{I}}}$ eigenvalues at the high-symmetry points are always either $(++)$ or $(--)$ . These inversion eigenvalues imply that the Wilson-loop eigenvalues come in complex-conjugate pairs $\\{\\xi,\\xi^{*}\\}$ , with $\\xi=\\xi^{*}=+1$ or $^{-1}$ . Thus, along the highsymmetry lines (blue and red lines of Fig. 11) the Wilson loops have eigenvalues \n\n$$\n\\{\\xi,\\xi^{*}\\}\\rightarrow\\{1,1\\}\\mathrm{or}\\{-1,-1\\},\n$$ \n\ni.e., at those lines the Wannier bands close the gap. Conversely, if instead of imposing the conditions of having $\\left(+-\\right)$ for both $\\hat{M}_{x}$ and $\\hat{M}_{y}$ eigenvalues, we started by first fixing $\\left(+-\\right)$ for $\\hat{\\boldsymbol{\\mathcal{I}}}$ eigenvalues, at most only one of the reflection eigenvalues will be $\\left(+-\\right)$ . The other one will necessarily have either $(++)$ or $(--)$ . An example of this case is insulator (5.10) with $\\delta=0$ , with reflection eigenvalues shown in Figs. 18(a) and 18(b). \n\n# D. Simple model with topological quadrupole moment \n\nWe now focus on the detailed description of a model for an insulator with a quadrupole moment. The minimal model is a 2D crystal with two occupied bands. For simplicity, we choose a microscopic representation consisting of four spinless fermion orbitals with Hamiltonian \n\n$$\n\\begin{array}{l}{{\\displaystyle H^{q}=\\sum_{\\mathbf{R}}[\\gamma_{x}(c_{\\mathbf{R},1}^{\\dagger}c_{\\mathbf{R},3}+c_{\\mathbf{R},2}^{\\dagger}c_{\\mathbf{R},4}+\\mathrm{H.c.})}}\\\\ {~+\\gamma_{y}(c_{\\mathbf{R},1}^{\\dagger}c_{\\mathbf{R},4}-c_{\\mathbf{R},2}^{\\dagger}c_{\\mathbf{R},3}+\\mathrm{H.c.})}\\\\ {~+\\lambda_{x}(c_{\\mathbf{R},1}^{\\dagger}c_{\\mathbf{R}+\\hat{\\mathbf{x}},3}+c_{\\mathbf{R},4}^{\\dagger}c_{\\mathbf{R}+\\hat{\\mathbf{x}},2}+\\mathrm{H.c.})}\\\\ {~+\\lambda_{y}(c_{\\mathbf{R},1}^{\\dagger}c_{\\mathbf{R}+\\hat{\\mathbf{y}},4}-c_{\\mathbf{R},3}^{\\dagger}c_{\\mathbf{R}+\\hat{\\mathbf{y}},2}+\\mathrm{H.c.})],}\\end{array}\n$$ \n\nwhere $c_{\\mathbf{R},i}^{\\dagger}$ is the creation operator for degree of freedom $i$ in unit cell , for as shown in Fig. 21(a). $\\gamma_{x}$ and $\\gamma_{y}$ represent amplitudes of hopping within a unit cell. $\\lambda_{x}$ and $\\lambda_{y}$ represent the amplitudes of hopping to nearestneighbor unit cells along $x$ and $y$ , respectively. The negative signs, represented by the dashed lines in Fig. 21(a), are a gauge choice for the $\\pi$ flux threaded through each plaquette (including within the unit cell itself). The corresponding Bloch Hamiltonian is \n\n$$\n\\begin{array}{r}{h^{q}(\\mathbf{k})=[\\gamma_{x}+\\lambda_{x}\\cos(k_{x})]\\Gamma_{4}+\\lambda_{x}\\sin(k_{x})\\Gamma_{3}\\quad}\\\\ {+[\\gamma_{y}+\\lambda_{y}\\cos(k_{y})]\\Gamma_{2}+\\lambda_{y}\\sin(k_{y})\\Gamma_{1},}\\end{array}\n$$ \n\n![](images/d68df34f9af5fac56e2149af7b3ce83ea685379b7b6191631421b10f106e1d2d.jpg) \nFIG. 21. Lattice (a) and energy spectrum (b) of the minimal model with quadrupole moment density having the Bloch Hamiltonian (6.29). In (a), dashed lines have a negative sign to account for a flux of $\\pi$ threading each plaquette. In (b) each energy band is twofold degenerate. \n\nwhere $\\Gamma_{0}=\\tau_{3}\\otimes\\tau_{0}$ , $\\Gamma_{k}=-\\tau_{2}\\otimes\\tau_{k}$ , $\\Gamma_{4}=\\tau_{1}\\otimes\\tau_{0}$ for $k=$ 1,2,3, where $\\tau_{1,2,3}$ are Pauli matrices, and $\\tau_{0}$ is the $2\\times2$ identity matrix. The energy bands are \n\n$$\n\\epsilon(\\mathbf{k})=\\pm\\sqrt{\\epsilon_{x}^{2}(k_{x})+\\epsilon_{y}^{2}(k_{y})},\n$$ \n\nwhere $\\epsilon_{i}(k_{i})=\\sqrt{\\gamma_{i}^{2}+2\\gamma_{i}\\lambda_{i}\\cos(k_{i})+\\lambda_{i}^{2}}$ for $i=x,y$ . Each of the upper and lower energy bands is twofold degenerate. This Hamiltonian is gapped across the entire bulk Brillouin zone (BZ) unless $|\\gamma_{x}/\\lambda_{x}|=1$ and $|\\gamma_{y}/\\lambda_{y}|=\\pm1$ . A plot of the energy spectrum in the 2D BZ is shown in Fig. 21(b) for $\\gamma_{x}/\\lambda_{x}=\\gamma_{y}/\\lambda_{y}=0.5$ . We consider this system at halffilling, so that only the lowest two bands are occupied. This Hamiltonian has vanishing polarization and zero Chern number for the entire range of parameters for which it is gapped. Thus, it meets the preliminary requirements of an insulator with quadrupole moment density outlined at the beginning of Sec. VI. The projected position operators along $x$ and $y$ do not commute at half-filling, and the Hamiltonian has a pair of gapped Wannier bands, as shown in Fig. 19. \n\nIn the present form, this Hamiltonian has symmetries that quantize the Wannier-sector polarizations $p_{y}^{\\nu_{x}^{\\pm}},p_{x}^{\\nu_{y}^{\\pm}}=0$ or $\\frac{1}{2}$ which we describe in the following subsection. Associated to this quantization is the existence of sharply quantized corner charges and edge polarizations, in agreement with (6.1). Upon breaking the symmetries that quantize the quadrupole moment, a generalized version of this model can generate values of quadrupole moment satisfying $q_{x y}\\in(0,1]$ . As an extension, we will see that when coupling this system to an adiabatically varying parameter, a quantum of dipole can be pumped in a way analogous to the quantum of charge pumped in the case of a cyclically varying bulk dipole moment (Sec. III F). \n\n# 1. Symmetries \n\nThe quadrupole moment $q_{x y}$ in 2D is even under the group $T(2)$ , which contains the operations $\\{1,C_{4}M_{x},C_{4}M_{y},C_{4}^{2}\\}$ (see Sec. II E), where $M_{x}$ and $M_{y}$ are reflections, and $C_{4}$ is the rotation by $\\pi/2$ around the $z$ axis. This implies that none of the symmetries $\\{C_{4}M_{x},C_{4}M_{y},C_{4}^{2}\\}$ quantize the quadrupole moment $q_{x y}$ in crystalline insulators. On the other hand, the reflection operations $M_{x},M_{y}$ , and $C_{4}$ transform $q_{x y}$ to $-q_{x y}$ . Hence, crystalline insulators with vanishing bulk dipole moment having any of $\\{M_{x},M_{y},C_{4}\\}$ will have a well-defined, quantized quadrupole moment, though most insulators may simply just have a vanishing moment. \n\nThe quadrupole model with Bloch Hamiltonian (6.29) has the reflection symmetries of (4.11) with operators \n\n$$\n\\hat{M}_{x}=i\\tau_{1}\\otimes\\tau_{3},~\\hat{M}_{y}=i\\tau_{1}\\otimes\\tau_{1},\n$$ \n\nas well as $C_{2}$ symmetry \n\n$$\n\\hat{r}_{2}h^{q}({\\bf k})\\hat{r}_{2}^{-1}=h^{q}(-{\\bf k})\n$$ \n\nwith the $C_{2}$ rotation operator \n\n$$\n\\hat{r}_{2}=\\hat{M}_{x}\\hat{M}_{y}=-i\\tau_{0}\\otimes\\tau_{2}.\n$$ \n\nNotice that $C_{2}$ symmetry for this model resembles the inversion symmetry (4.17). The reflection and $C_{2}$ operators obey $\\hat{M}_{x,y}^{2}\\doteq-1$ and $\\hat{r}_{2}^{2}=-1$ . The point group of $h^{q}(\\mathbf{k})$ in Eq. (6.29) is thus the quaternion group \n\n$$\n\\boldsymbol{Q}=\\left\\langle\\bar{e},\\hat{M}_{x},\\hat{M}_{y},\\hat{r}_{2}\\right|\\ \\hat{M}_{x}^{2}=\\hat{M}_{y}^{2}=\\hat{r}_{2}^{2}=\\hat{M}_{x}\\hat{M}_{y}\\hat{r}_{2}=\\bar{e}\\ \\right\\rangle\n$$ \n\nwith $\\bar{e}=-1$ . The quaternion group is of order 8, with elements $\\{\\pm1,\\pm\\hat{M}_{x,y},\\pm\\hat{r}_{2}\\}$ . The three operators in (6.31) and (6.33) each have eigenvalues $\\{-i,-i,+i,+i\\}$ . Due to the $\\pi$ flux threading each plaquette, the reflection operators do not commute, instead, they obey \n\n$$\n[\\hat{M}_{x},\\hat{M}_{y}]=-2i\\tau_{0}\\otimes\\tau_{2},\\quad\\{\\hat{M}_{x},\\hat{M}_{y}\\}=0.\n$$ \n\nThe energy band degeneracy is protected at the high-symmetry points of the BZ by the noncommutation of the reflection operators $\\hat{M}_{x},\\hat{M}_{y}$ (see Appendix G). Thus, it is not possible to lift the twofold degeneracy of the energy bands at those points while preserving both reflection symmetries. Indeed, at each of the high-symmetry points of the BZ, the subspace of occupied bands lies in the two-dimensional representation of the quaternion group. \n\nSince $C_{2}$ transforms the Bloch Hamiltonian $h^{q}(\\mathbf{k})$ the same way as $\\boldsymbol{\\mathcal{T}}$ does, $C_{2}$ symmetry quantizes the bulk dipole moment in $h^{q}(\\mathbf{k})$ to $\\mathbf{p}=\\mathbf{0}$ , as required for an insulator with well-defined quadrupole moment. $M_{x}$ or $M_{y}$ then quantize the quadrupole moment of $h^{q}(\\mathbf{k})$ to either $q_{x y}=0$ or $\\frac{1}{2}$ . The three symmetries in $h^{q}(\\mathbf{k})$ $(M_{x},M_{y}$ , and $C_{2}$ ) are simultaneously present due to the fact that the existence of two of them implies the existence of the third one. \n\nAlternatively, $C_{4}$ also quantizes $q_{x y}$ . If we set $\\gamma_{x}=\\gamma_{y}$ and $\\lambda_{x}=\\lambda_{y}$ , $h^{q}(\\mathbf{k})$ has also $C_{4}$ symmetry, \n\n$$\n\\hat{r}_{4}h^{q}({\\bf k})\\hat{r}_{4}^{-1}=h^{q}(R_{4}{\\bf k}),\\hat{r}_{4}=\\left(\\begin{array}{c c}{0}&{\\tau_{0}}\\\\ {-i\\tau_{2}}&{0}\\end{array}\\right),\n$$ \n\nwhere $R_{4}$ is the rotation by $\\pi/2$ of the crystal momentum, i.e., $R_{4}(k_{x},k_{y})=(k_{y},-k_{x})$ . The $C_{4}$ rotation operator obeys $\\hat{r}_{4}^{2}=\\hat{r}_{2}$ and $\\hat{r}_{4}^{4}=-1$ (the minus sign is due to the flux per unit cell) and has eigenvalues {e±iπ/4,e±i3π/4}. \n\nFinally, $h^{q}(\\mathbf{k})$ , as written in Eq. (6.29), lies in class BDI, i.e., it has time-reversal, chiral, and charge-conjugation symmetries \n\n$$\n\\begin{array}{l}{{\\hat{T}h^{q}({\\bf k})\\hat{T}^{-1}=h^{q}(-{\\bf k}),\\quad\\hat{T}=K}}\\\\ {{\\Pi h^{q}({\\bf k})\\Pi^{-1}=-h^{q}({\\bf k}),\\quad\\Pi=\\Gamma^{0}}}\\end{array}\n$$ \n\n![](images/1db100451060709eb5ac140195b1fae4f312045b6ebb678c30bcd380001e2aeb.jpg) \n\nFIG. 22. (a) Schematic of quadrupole model in the limit $\\gamma_{x}=$ $\\gamma_{y}=0$ . (b) Onsite perturbation that breaks reflection symmetries in $x$ and $y$ while preserving $C_{2}$ symmetry. \n\n$$\nC h^{q}({\\bf k})C^{-1}=-h^{q}({-\\bf k}),~C=\\Gamma^{0}{K}.\n$$ \n\nHowever, these symmetries are not necessary for quantization of the quadrupole moment. In fact, we show in Appendix H that we can break all of these symmetries and still preserve the quantization of the quadrupole observables as long as the reflection symmetries are preserved. \n\n# 2. Boundary signatures of the quadrupole phase \n\nEquation (6.1) gives the physical signatures of the quadrupole phase. With open boundaries, edge-localized polarizations exist, which can generate observable charge or currents as indicated by \n\n$$\n\\begin{array}{c}{{Q^{\\mathrm{edge\\}a}=-\\partial_{j}p_{j}^{\\mathrm{edge\\}a},}}\\\\ {{J_{j}^{\\mathrm{edge\\}a}=\\partial_{t}p_{j}^{\\mathrm{edge\\}a}.}}\\end{array}\n$$ \n\nWhen two perpendicular boundaries are open, the edge polarizations along the boundaries generate a quadrupole pattern (see Fig. 4), and the corner hosts charges having the same magnitude as the edge polarizations. To illustrate these symmetry-protected signatures it will be convenient to use the Hamiltonian (6.29) in the limit $\\gamma_{x}=\\gamma_{y}=0$ , as shown in Fig. 22(a). In this limit it is straightforward to identify the localized 1D boundary TIs associated with the edge polarization by eye, as well as the degenerate, mid-gap modes responsible for the corner charges. \n\nBefore we proceed, we point out a common subtlety in the calculation of electric moments. In the symmetry-protected topological phases with quantized quadrupole moment, the observables are not unambiguously defined, e.g., a value of $\\begin{array}{r}{q_{x y}=\\frac{1}{2}}\\end{array}$ is equivalent to a value of $-{\\frac{1}{2}}$ , and similarly for $p^{\\mathrm{edge}}$ and ${Q}^{\\mathrm{corner}}$ . This occurs when $h^{q}(\\mathbf{k})$ has the quantizing symmetries that transform $q_{x y}$ to $-q_{x y}$ . In order to unambiguously calculate the observables of the quadrupole insulator in a many-body ground state, we infinitesimally break all the symmetries that quantize the quadrupole so it will evaluate to a number close to, but not equal to, either $\\frac{1}{2}$ or $-{\\frac{1}{2}}$ , as was done to fix the sign of the signatures in the SSH model (Sec. III) and insulator $h^{1}({\\bf k})$ (Sec. V). For that purpose, we consider the Hamiltonian \n\n$$\nh_{\\delta}^{q}({\\bf k})=h^{q}({\\bf k})+\\delta\\Gamma_{0},\n$$ \n\n![](images/be51b18cad92cdd9f1ccfb23e54a5acaeea2598cb03954e61fba4444ff0c0689.jpg) \nFIG. 23. Edge polarization in the quadrupole insulator. (a) Schematic of quadrupole model in the limit $\\gamma_{x}=\\gamma_{y}=0$ with open boundaries along $x$ and closed along $y$ . Gray squares are bulk plaquettes over which the polarization is zero. Red and blue lines represent edge-localized 1D quantized dipole moments. (b) Polarization along $y$ as a function of $x$ for $\\gamma/\\lambda=0,0.5,1.1$ when an infinitesimal onsite perturbation as in Fig. 22(b) is added. \n\nwhere $h^{q}(\\mathbf{k})$ is the pristine, reflection-symmetric Hamiltonian in Eq. (6.29) with quantized boundary signatures, and $\\Gamma_{0}=$ $\\tau_{3}\\otimes\\tau_{0}$ represents an onsite potential with the pattern shown in Fig. 22(b). This potential obeys $[\\Gamma^{0},\\hat{M}_{x}]\\neq{\\dot{0}}$ , $[\\Gamma^{0},\\hat{M}_{y}]\\neq0$ , and $[\\Gamma^{0},\\hat{r}_{2}]=0$ . It breaks the quantizing reflection symmetries of the quadrupole moment, but, crucially, retains $C_{2}$ symmetry, which maintains a vanishing, quantized value of the bulk dipole moment. In this section, we will keep $\\delta\\ll\\gamma_{x},\\gamma_{y},\\lambda_{x},\\lambda_{y}$ . \n\nEdge polarization. A direct consequence of the nontrivial bulk topology of the quadrupole phase is the existence of edge polarization parallel to the edge. Consider first the quadrupole insulator in the limit $\\gamma_{x}=\\gamma_{y}=0$ of Eq. (6.39), with $\\delta\\ll$ $\\lambda_{x}=\\lambda_{y}\\equiv\\lambda$ , and having open boundaries along $x$ but closed along $y$ , as shown in Fig. 23(a). In the bulk, the electrons are connected via hopping on the square plaquettes, and form hybridized orbitals localized on the squares [shaded squares in Fig. 23(a)]. The overall electronic displacement in these plaquettes is zero (see Appendix I). At the edges, however, electrons are only connected vertically as in the 1D symmetryprotected dipole phase of the SSH model [compare red and blue edges of Fig. 23(a) with Fig. 8(b)]. The small value of $\\delta$ breaks the reflection symmetries and infinitesimally displaces the electrons away from $\\frac{1}{2}$ to “choose a sign” for the edge polarizations, as shown in the first plot of Fig. 23(b), where we plot the polarization along $y$ resolved in space along $x$ , $p_{y}(R_{x})$ ; this is calculated using the prescription in Sec. V that results in Eq. (5.9). If we turn on $\\gamma_{x}$ and $\\gamma_{y}$ , the edge polarization remains quantized to $\\frac{1}{2}$ (although it exponentially penetrates into the bulk), as long as $|\\gamma_{x}/\\lambda_{x}|<1$ and $|\\gamma_{y}/\\lambda_{y}|<1$ , as shown in the second plot of Fig. 23(b). If, on the other hand, $|\\gamma_{x}/\\lambda_{x}|>1$ or $|\\gamma_{y}/\\lambda_{y}|>1$ , the edge polarization drops to zero, as seen in the third plot of Fig. 23(b). \n\nCorner charge. In the quadrupole insulator with full open boundaries, the edge-localized dipole moments will accumulate corner charge. If edge dipole moments per unit length of $q$ exist, we would expect a corner charge $\\pm2q$ . However, the corner charge in the quadrupole insulator $h^{q}(\\mathbf{k})$ has equal magnitude to the edge polarization, i.e., $q$ , following (6.1). Hence, since the contributions from edge dipole moments alone overcount the corner charge, there has to be an additional direct contribution from the bulk to the corner charge. \n\n![](images/b332ffbe25edb207ff5d770ee20b95edf758a542a45cb2af9c233cd019dcf018.jpg) \nFIG. 24. Corner charge in the quadrupole insulator. (a) Schematic of charge in the limit $\\gamma_{x}=\\gamma_{y}=0$ when an infinitesimal perturbation as in Fig. 22(b) is included. The lines connecting sites represent localized hybrid electron orbitals in the many-body ground state at half-filling. This is an exact representation of the ground state in the zero-correlation length limit. Each blue, green, and red circle represents charges of $+2e$ (ionic), $-e/2$ , and $-e$ , respectively. White circles do not have charge. (b) Simulation of the charge density for $\\lambda_{x}=\\lambda_{y}=1,\\gamma_{x}=\\gamma_{y}=10^{-3}$ , and $\\delta=10^{-3}$ . Sites in the square plaquette orbitals marked with $^{\\mathrm{~a~}*}$ closest to them represent half-charge contributions to the corner charge from the bulk orbitals. \n\nThe different contributions to the corner charge can be clearly illustrated in the limit $\\gamma_{x}=\\gamma_{y}=0$ , shown in Fig. 24(a). The large blue circles represent an ionic charge of $+2e$ which is constant across unit cells. Each unit cell has four electronic degrees of freedom and, thus, at half-filling, each unit cell contributes two electrons. The sites connected by lines represent localized hybrid orbitals of the occupied electrons in the many-body ground state. In the bulk there are two localized square orbitals on each intercell plaquette, and the electrons in these orbitals have equal weight on each site of the plaquette. On the edges there are localized intercell dimer orbitals, one per dimer, where the electrons have equal weight on each site of the dimer. In this limit where $\\gamma_{x}=\\gamma_{y}=0$ each of the green sites in the bulk has an electronic charge of $-e/2$ coming from the two square-localized orbitals, each contributing $\\frac{1}{4}$ of an electron. Similarly, each of the green sites on the edge SSH chains has an electronic charge of $-e/2$ . Finally, there are two red and two white circles at the corners. Each of these degrees of freedom are decoupled from the rest in this limit, and therefore have exactly zero energy. These are the corner modes associated with the fractional corner charge in the topological quadrupole phase. Out of the four mid-gap corner modes, two should be filled at half-filling. A small value of $\\delta\\ll\\lambda_{x},\\lambda_{y}$ in Eq. (6.39) breaks this degeneracy in a manner where $C_{2}$ symmetry is preserved, and specifies which modes are to be filled. When $\\delta>0$ , each of the red circles is occupied since they are at lower energy than the white circles. Thus, each red circle contributes $-e$ to the charge at its corner unit cell. The white circles, on the other hand, remain unoccupied and do not contribute to the electronic corner charge. Notice that in the bulk and the edges, the positive atomic charge cancels the electronic charge. In the corner unit cells, however, there is a total charge of $\\pm e/2$ . Just as in the case of the edge polarization, the corner charge persists as long as $|\\gamma_{x}/\\lambda_{x}|<1$ and $|\\gamma_{y}/\\lambda_{y}|<1$ , and drops to zero otherwise. An example of the distribution of electronic charge density for $\\gamma_{x}\\neq0$ and $\\gamma_{y}\\neq0$ is shown in Fig. 24(b). \n\nThe Hamiltonian (6.29) in the limit $\\gamma_{x,y}=0$ , shown in Fig. 24(a), illustrates two important characteristics of the quadrupole: (i) the fractionalization of the corner charge does not come from the edge polarizations alone, i.e., the contributions due to the nontrivial polarizations give an overall integer contribution to the corner charge. The fractionalization of the corner charge comes from the bulk charge density, and in this simple limit it comes from the corners of the plaquette orbitals that are closest to the corners [circles marked with a $^*$ in Fig. 24(a)]. (ii) Despite the existence of two topological edge dipoles meeting at each corner in the nontrivial phase, there is only one zero-energy state per corner. This is contrary to the conventional notion that a domain between two SSH chains, both of which are in the topological phase, should not trap a stable mid-gap mode. The apparent paradox is resolved because the protected topological corner state is a simultaneous eigenstate of both edge Hamiltonians along the $x$ and $y$ edges. This is evident in the pictorial representation of Fig. 24(a), but can be confirmed in a more general setting by an explicit calculation of the corner-localized eigenstate, as shown in Appendix J. Indeed, the corner states are not traditional $\\boldsymbol{l D}$ domain-wall states, and represent a new mechanism to generate such modes on the boundary of a $2D$ system. \n\nIn order to understand how the boundary polarization arises in the topological quadrupole phase, it is useful to study the topology of the Wannier bands, and how this topological structure manifests at boundaries. We focus on this in the following three sections. \n\n# 3. Topological classes of the Wannier bands \n\nUnder $M_{x}$ , $M_{y}$ , and $C_{2}$ , the Wannier-sector polarizations obey the relations in Eq. (6.19). In the quadrupole insulator $h^{q}(\\mathbf{k})$ , these relations imply that (i) all the Wannier-sector polarizations $p_{x}^{\\nu_{y}^{\\pm}}$ and $p_{y}^{\\nu_{x}^{\\pm}}$ are quantized [see Eq. (6.20)], and (ii) out of these four polarizations two are redundant due to $C_{2}$ symmetry. Specifically, we can rewrite the third expression in Eq. (6.19) as \n\n$$\n\\begin{array}{r}{p_{x}^{\\nu_{y}^{+}}+p_{x}^{\\nu_{y}^{-}}\\overset{C_{2}}{=}0\\mod1,}\\\\ {p_{y}^{\\nu_{x}^{+}}+p_{y}^{\\nu_{x}^{-}}\\overset{C_{2}}{=}0\\mod1,}\\end{array}\n$$ \n\nwhich is the statement that the total dipole moment vanishes, as is needed for a well-defined quadrupole moment (see Sec. II B) \n\n$$\n\\begin{array}{r}{{\\bf p}=(p_{x},p_{y})={\\bf0},}\\end{array}\n$$ \n\nwhere $p_{x}=p_{x}^{\\nu_{y}^{+}}+p_{x}^{\\nu_{y}^{-}}$ and $p_{y}=p_{y}^{\\nu_{x}^{+}}+p_{y}^{\\nu_{x}^{-}}$ \n\nDue to the relations (6.40), only two independent Wanniersector polarizations are necessary to specify the topological class of the Wannier bands, and we can define the index \n\n$$\n\\mathbf{p}^{\\nu}\\equiv\\bigl(p_{x}^{\\nu_{y}^{-}},p_{y}^{\\nu_{x}^{-}}\\bigr).\n$$ \n\nUnder $M_{x},~M_{y}$ , and $C_{2}$ , the classification of the Wannier band topology in $h^{q}(\\mathbf{k})$ is $\\mathbb{Z}_{2}\\times\\mathbb{Z}_{2}$ . A diagram of these classes is shown in Fig. 25 as a function of the ratios $\\gamma_{x}/|\\lambda_{x}|$ and $\\gamma_{y}/|\\lambda_{y}|$ . The central square of the diagram in the ranges $\\gamma_{x}/|\\lambda_{x}|\\in[-1,1]$ and $\\gamma_{y}/|\\lambda_{y}|\\in[-1,1]$ is the region in parameter space having $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},\\frac{1}{2})}\\end{array}$ . Additionally, there are two regions in parameter space with ${\\bf p}^{\\nu}=(0,{\\scriptstyle\\frac{1}{2}})$ , and two more with $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},0)}\\end{array}$ , as well as four regions in the trivial topological class $\\bar{\\mathbf{p}^{\\nu}}=(0,0)$ . \n\n![](images/202648f32cc917d8627e5736aa86c9dedda2bc092f49b6541a05ce133303ebfe.jpg) \nFIG. 25. Diagram of topological classes for the Wannier bands of the insulator $h^{q}(\\mathbf{k})$ with Bloch Hamiltonian (6.29). The indices $\\ensuremath{\\mathbf{p}}^{\\nu}$ are defined in Eq. (6.42). The trivial class has ${\\bf p}^{\\nu}=(0,0)$ . \n\nIn the presence of reflection symmetries, $\\ensuremath{\\mathbf{p}}^{\\nu}$ can be determined by the reflection representation of the Wannier bands at the high-symmetry lines \n\n$$\n\\begin{array}{r}{\\hat{M}_{y}\\big|w_{x,(k_{x},k_{*y})}^{\\pm}\\big\\rangle=\\alpha_{M_{y}}^{\\pm}(k_{x},k_{*y})\\big|w_{x,(k_{x},k_{*y})}^{\\pm}\\big\\rangle,}\\\\ {\\hat{M}_{x}\\big|w_{y,(k_{*x},k_{y})}^{\\pm}\\big\\rangle=\\alpha_{M_{x}}^{\\pm}(k_{*x},k_{y})\\big|w_{y,(k_{*x},k_{y})}^{\\pm}\\big\\rangle}\\end{array}\n$$ \n\nfor $k_{*x,y}=0,\\pi$ (see Sec. VI B). In the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},\\frac{1}{2})}\\end{array}$ class, the values of $\\alpha_{M_{x}}^{\\pm}(k_{*x},k_{y})$ and $\\alpha_{M_{y}}^{\\pm}(k_{x},k_{*y})$ are shown in Fig. 26. For each of the topological classes of the Wannier bands shown in Fig. 25, the corresponding $\\alpha$ values are shown in Table V. Using these values we can evaluate the Wanniersector polarizations according to Eq. (6.22). In $h^{q}(\\mathbf{k})$ , these lead to the Wannier-sector polarization (for the lower Wannier bands) shown in the phase diagram in Fig. 25. \n\n![](images/6148078b3a276306261c9dfaa876c4722495dee000f3f36fc13ade7d107a7824.jpg) \nFIG. 26. Reflection eigenvalues $\\alpha_{M_{y}}^{\\pm}(k_{x},k_{*y})$ (red signs) and $\\alpha_{M_{x}}^{\\pm}(k_{*x},k_{y})$ (blue signs) of the Wannier bands of the occupied energy bands in the topological quadrupole phase. Here, $k_{*x,y}=0,\\pi$ . For the unoccupied bands, all signs are inverted. \n\nTABLE V. Reflection eigenvalues of lower Wannier bands in the different topological classes of the Wannier bands of the Hamiltonian in Eq. (6.29). The upper (lower) values in the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},0)}\\end{array}$ phase correspond to the upper (lower) blocks in the phase diagram in Fig. 25, while the upper (lower) values in the $\\mathbf{p}^{\\nu}=(0,\\textstyle\\frac{1}{2})$ phase correspond to the blocks to the left (right) in the phase diagram in Fig. 25. \n\n\n
pp=(,0)p=(0,)
αmx(0,ky)
αMx(π,k)++±
αm(kx,0)+±
αM(kx,π)
\n\nSince calculating the $\\alpha$ values requires finding the Wannier basis $\\vert w_{x,\\mathbf{k}}^{\\pm}\\rangle$ or $|w_{y,\\mathbf{k}}^{\\pm}\\rangle$ , and finding these bases requires calculating non-Abelian Wilson loops, it would be more convenient to have an easier alternative for determining the $\\alpha$ values. Equation (D35) in Appendix D implies that the Wilson loop $\\mathcal{W}_{x,{\\mathbf{k}}}$ , under $M_{y}$ , obeys \n\n$$\n\\left[B_{M_{y},(k_{x},k_{*y})},\\mathcal{W}_{x,(k_{x},k_{*y})}\\right]=0\n$$ \n\nat $k_{*y}=0,\\pi$ . Thus, both the Wilson loop and the sewing matrix $B_{M_{y},(k_{x},k_{*y})}$ , which encodes the reflection representation at the reflection-invariant lines $(k_{x},k_{*y})$ for $k_{x}\\in[-\\pi,\\pi)$ , can be simultaneously diagonalized and hence they have common eigenstates. Thus, at the reflection-invariant lines in momentum space shown in Fig. 11, it is possible to label the subspace of occupied bands by their respective reflection eigenvalues. The subspaces along each of these lines can be divided into two sectors: one labeled by reflection eigenvalue $+i$ , and another one labeled by a reflection eigenvalue $-i$ . We can then calculate Abelian Wilson loops in each of these sectors separately. This will directly tell us the Wannier values associated with each reflection representation. A detailed calculation of this is shown in Appendix I in the limit $\\gamma_{x}=$ $\\gamma_{y}=0$ . Upon obtaining the values of $\\alpha$ and their corresponding reflection eigenvalues, the Wannier-sector polarization can be calculated using Eq. (6.22). In some cases this method, which relies on resolving states according to their symmetry eigenvalues, will be easier to apply than the full non-Abelian formulation. \n\n# 4. Transitions between the topological classes of Wannier bands \n\nAt the transitions between topological classes indicated in Fig. 25, the Wannier gap closes. This is analogous to the closing of the energy gap in phase transitions between distinct symmetry-protected topological phases. Figure 27 shows the momentum and Wannier value locations at which the Wannier gap closes at all the topological class transitions in Fig. 25. With reflection symmetries $M_{x}$ and $M_{y}$ , the Wannier gap can close at two Wannier values, $\\nu=0$ or $\\frac{1}{2}$ . Consider, for example, the path in parameter space shown by the red line in Fig. 27 that starts in the $\\mathbf{p}^{\\nu}=\\dot{(}\\frac{1}{2},\\frac{1}{2})$ class and ends in the trivial class ${\\bf p}^{\\nu}=(0,0)$ via the intermediate class $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},0)}\\end{array}$ . In Fig. 28 we plot the two Wannier bands for each of the five Hamiltonians corresponding to the red dots in Fig. 27. \n\n![](images/0f6c76df8f05eaa84ff2594dfd59ec286dcc3acef1455af9c1988982f2e83c26.jpg) \nFIG. 27. Diagram of Wannier band transitions in model (6.29). At transitions there is Wannier gap closing at either $\\nu_{x}(k_{y}=0,\\pi)=0$ or $\\nu_{y}(k_{x}=0,\\pi)=0$ (dashed lines) or at either $\\textstyle\\nu_{x}(k_{y}=0,\\pi)={\\frac{1}{2}}$ or $\\textstyle\\nu_{y}(k_{x}=0,\\pi)={\\frac{1}{2}}$ (solid thick lines). \n\nIn the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},\\frac{1}{2})}\\end{array}$ class, both Wannier bands are gapped and nontrivial. At the first transition point, the Wannier bands $\\nu_{x}(k_{y})$ become gapless at $k_{y}=\\pi$ as they become twofold degenerate at $\\begin{array}{r}{\\nu_{x}(k_{y}=\\pi)=\\frac{\\mathrm{i}}{2}}\\end{array}$ . The bands $\\nu_{y}(k_{x})$ , on the other hand, remain gapped at all $\\tilde{k}_{x}\\in(-\\pi,\\pi]$ . On the other side of this transition, in the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},0)}\\end{array}$ class, the Wannier bands $\\nu_{x}(k_{y})$ become gapped again, but this time they have trivial topology (i.e., $p_{y}^{\\nu_{x}^{-}}=0.$ ). \n\nAs the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},0)}\\end{array}$ class approaches the transition into the trivial class ${\\bf p}^{\\nu}=(0,0)$ , another Wannier gap closing event occurs. This time, however, it is the $\\nu_{y}(k_{x})$ bands that close the gap at the $k_{x}=\\pi$ point. They acquire the twofold-degenerate value of $\\nu_{y}(k_{x}=\\pi)=0$ . On the other side of the transition, in the trivial class, both Wannier bands are gapped and have trivial topology. At transitions from the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},\\frac{1}{2})}\\end{array}$ class to the trivial class ${\\bf p}^{\\nu}=(0,0)$ other than the one indicated by the red line in Fig. 28, transitions can occur by closing the Wannier gaps of $\\nu_{y}$ $(\\nu_{x})$ at $k_{x}=0$ or $\\pi$ $k_{y}=0$ or $\\pi$ ), as indicated in Fig. 27. In all cases, however, the Wannier gap always closes at the value $\\textstyle\\nu={\\frac{1}{2}}$ as it leaves the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},\\frac{1}{2})}\\end{array}$ class to either the $\\mathbf{p}^{\\nu}=(0,\\textstyle\\frac{1}{2})$ or $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},0)}\\end{array}$ classes, and then at the value $\\upnu=0$ from these classes to the trivial ${\\bf p}^{\\nu}=(0,0)$ class. This is not accidental. \n\n![](images/416182f9cfff05f2128d7229e7fa221d1ef06b690be0713387e27f085d0bc175.jpg) \nFIG. 28. Wannier bands $\\nu_{x}(k_{y})$ (first line) and $\\nu_{y}(k_{x})$ (second line). The parameters used are, from left to right, $(\\gamma_{x}/\\lambda_{x},\\gamma_{y}/\\lambda_{y})=(0.75,0.75)\\rightarrow(0.75,1)\\rightarrow(0.75,1.25)\\rightarrow$ $(1,1.25)\\rightarrow(1.25,1.25)$ , as in the red lines of Fig. 27. \n\n![](images/1ee2c54c3d76f96a2f0a3f246eaa17655b469d274aa1fb7e1e7d7f98f6fa88b7.jpg) \nFIG. 29. Representative tight-binding Hamiltonians, Wannier values $\\{\\nu_{x}^{j}\\}$ , for $j\\in1\\ldots2N_{y}$ , and polarization $p_{x}(R_{y})$ for all topological classes $\\ensuremath{\\mathbf{p}}^{\\nu}$ of $h^{q}(\\mathbf{k})$ . The tight-binding Hamiltonians have closed boundaries along $x$ and open along $y$ , and are drawn with $\\gamma_{x},\\gamma_{y},\\lambda_{x},\\lambda_{y}=0$ whenever possible to ease the visualization of the edge states and edge polarizations. The Wannier values $\\{\\nu_{x}^{j}\\}$ and polarizations $p_{x}(R_{y})$ are calculated in the same topological class as the Hamiltonians on their left, but with parameters $\\lambda_{x}=\\lambda_{y}=1$ in all four cases and $(\\gamma_{x},\\gamma_{y})=$ (1.25,0.25) in (a), $(\\gamma_{x},\\gamma_{y})=(0.25,0.25)$ in (b), $(\\gamma_{x},\\gamma_{y})=(1.25,1.25)$ in (c), and $(\\gamma_{x},\\gamma_{y})=(0.25,1.25)$ in (d). (a), (b) Have pairs of Wannier edge states (red thick circles) with degenerate values $\\nu_{x}=0$ and $\\frac{1}{2}$ , respectively. (c), (d) Do not have Wannier edge states. Only (b) has a nontrivial edge polarization and quantized quadrupole moment. A value of $\\delta=10^{-3}$ was set in the calculation of $p_{x}(R_{y})$ for all cases to choose the sign of the quadrupole. \n\n# 5. Bulk-boundary correspondence for Wannier bands and edge polarization \n\nWe saw that transitions between different topological classes of Wannier bands close the Wannier gap. Therefore, at a physical boundary between insulators having different Wannier classes, the Wannier gap is also expected to close. We denote this property as a bulk-boundary correspondence for Wannier bands. Consider, for example, the quadrupole insulator (6.30) with closed boundaries along $x$ and open along $y$ . By redefining the unit cell of this 2D crystal to get an effective 1D crystal with a unit cell of $N_{\\mathrm{orb}}\\times N_{\\mathrm{y}}$ sites, we can obtain a Bloch Hamiltonian $h^{q}(k_{x})$ , with only one crystal momentum $k_{x}$ . We write $h^{q}(k_{x})$ to differentiate it from the Bloch Hamiltonian $h^{q}({\\bf k})=h^{q}(k_{x},k_{y})$ , which has full periodic boundaries. While $h^{q}(\\mathbf{k})$ has Wilson loops $\\mathcal{W}_{x,{\\bf k}}$ with Wannier bands $\\nu_{x}^{\\pm}(k_{y})$ , $h^{q}(k_{x})$ has Wilson loops $\\mathcal{W}_{x,k_{x}}$ with Wannier values $\\nu_{x}^{j}$ , for $j\\in1\\ldots2N_{y}$ (at half-filling), as defined in Sec. V. \n\nThe bulk-boundary correspondence for Wannier bands then implies that, if the Wannier bands $\\nu_{x}^{\\pm}(k_{y})$ of $h^{q}(\\mathbf{k})$ have lnocnatlriizveidal tiogepnolstoagtye, io.fe t,hief $\\begin{array}{r}{p_{y}^{\\nu_{x}^{\\pm}}=\\frac{1}{2}}\\end{array}$ ,opt iollf $y$ edwgiteh$\\mathcal{W}_{x,k_{x}}$ $h^{q}(k_{x})$ eigenvalue $\\nu_{x}=0$ or $\\frac{1}{2}$ (as protected by $M_{x}$ ). We denote these as Wannier edge states. Hence, the Wannier values of the insulator with open boundaries along $y$ are gapless, and the gapless states are localized at the edges. If, on the other hand, $p_{y}^{\\nu_{x}^{\\pm}}=0$ , then there are no edge-localized eigenstates of $\\mathcal{W}_{x,k_{x}}$ , $\\begin{array}{r}{p_{y}^{\\nu_{x}^{\\pm}}=\\frac{1}{2}}\\end{array}$ ,xtehnedeWdanlnoinegr .dTgehesirtatWeas,nnlioecralviazleude awt $R_{y}=0$ tahnedr $N_{y}$ $x$ $\\nu_{x}=0$ or $\\frac{1}{2}$ , indicates their dipole moment along $x$ . These modes are thus responsible for the edge-localized polarization parallel to the edge. Whether the topological Wannier edge modes have $\\nu_{x}=0$ or $\\frac{1}{2}$ (the only two allowed values under $M_{x}$ ) is determined by the value of $p_{x}^{\\nu_{y}^{\\pm}}$ . \n\nThe connection between the bulk property $\\begin{array}{r}{p_{y}^{\\nu_{x}^{\\pm}}=\\frac{1}{2}}\\end{array}$ and the existence of Wannier edge states can be seen as follows. The bulk Wannier bands $\\nu_{x}^{\\pm}(k_{y})$ , being gapped, allow us two define two maximally localized Wannier centers along $x$ : one arising from the $\\nu_{x}^{+}$ Wannier sector, which is localized to the right (horizontally) of the center of the unit cell, and another arising from the $\\nu_{x}^{-}$ Wannier sector, which is localized to the left (horizontally) of the center of the unit cell. $\\begin{array}{r}{p_{y}^{\\nu_{x}^{\\pm}}=\\frac{1}{2}}\\end{array}$ tells us that each of these Wannier centers is displaced by half of a unit cell along $y$ , hence giving rise to Wannier edge states when the system’s boundaries are opened. When $p_{y}^{\\nu_{x}^{\\pm}}$ is exactly quantized, which Wannier center of the $\\nu_{x}^{\\pm}$ Wannier bands is displaced up or down is ambiguous in the bulk of the insulator. However, when the boundaries are open, $C_{2}$ symmetry guarantees that there will be one Wannier edge state on each of the lower and upper surfaces (as opposed to, say, two edge states on the upper surface and none on the lower). \n\nThe properties described above can be visualized in Fig. 29, which shows the simplest tight-binding Hamiltonians (by setting $\\gamma_{x},\\gamma_{y},\\lambda_{x},\\lambda_{y}=0$ whenever possible) in all of the four Wannier classes of $h^{q}(\\mathbf{k})$ . Next to each of the tight-binding lattices we show the Wannier values $\\{\\nu_{x}^{j}\\}$ , for $j\\in1\\ldots2N_{y}$ (i.e., the eigenvalues of $\\mathcal{W}_{x,k_{x}})$ , for $h^{q}(k_{x})$ in the same Wannierband topological class, as well as their resulting polarizations $p_{x}(R_{y})$ . \n\nIn the cases in which $\\begin{array}{r}{p_{y}^{\\nu_{x}^{\\pm}}=\\frac{1}{2}}\\end{array}$ [Figs. 29(a) and 29(b)], $2N_{y}-2$ states are spread over the bulk, while two (the topological Wannier edge states) are localized on the edges: one at $R_{y}=0$ and the other one at $R_{y}=N_{y}$ . These two Wannier edge states have dipole moments along $x$ equal to the value of $p_{x}^{\\nu_{y}^{\\pm}}$ . For $p_{x}^{\\nu_{y}^{\\pm}}=0$ [Fig. 29(a)] the edge states have zero dipole moment; note by inspection of the tight-binding lattice that the edge states are each an SSH chain in the trivial phase. For $\\begin{array}{r}{p_{x}^{\\nu_{y}^{\\pm}}=\\frac{1}{2}}\\end{array}$ [Fig. 29(b)], the edge states have nontrivial, half-integer dipole moment; note by inspection of the tight-binding lattice that these edge states are each an SSH chain in the nontrivial phase. \n\nWhen $p_{y}^{\\nu_{x}^{\\pm}}=0$ , on the other hand, there are no Wannier edge states in the $\\mathcal{W}_{x,k_{x}}$ spectrum of $h^{q}(k_{x})$ . This is independent of the value of $p_{x}^{\\nu_{y}^{\\pm}}$ [Figs. 29(c) and 29(d)]. Thus, whether the Wannier bands $\\nu_{y}^{\\pm}(k_{x})$ are trivial or topological [Figs. 29(c) and 29(d), respectively], the absence of Wannier edge states automatically leads to a vanishing dipole moment along $x$ at both $y$ edges. \n\nFrom the analysis above it follows that, of all the four classes in $h^{q}(\\mathbf{k})$ , only the class $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},\\frac{1}{2})}\\end{array}$ exhibits nontrivial edge polarization. Correspondingly, only this class has cornerlocalized charges of $\\frac{1}{2}$ when the boundaries along both $x$ and $y$ are open. Hence, only the $\\begin{array}{r}{\\mathbf{p}^{\\nu}=(\\frac{1}{2},\\frac{1}{2})}\\end{array}$ class has nontrivial quantized quadrupole moment $\\begin{array}{r}{q_{x y}=\\frac{1}{2}}\\end{array}$ , while all the other three classes have trivial quantized quadrupole moment qxy 0. \n\n# 6. Topological phases in the quadrupole insulator \n\nNow that we have identified which Wannier topological classes (in the presence of $M_{x}$ and $M_{y}$ ) have nontrivial quadrupole moments, we look into the symmetry-protected topological quadrupole phases. The quadrupole insulator has a quantized phase protected not only by $M_{x}$ and $M_{y}$ , but also by $C_{4}$ symmetry. That is, we could choose either the combination of $M_{x}$ and $M_{y}$ or $C_{4}$ to protect the quadrupole moment. We analyze these two types of protection separately. \n\na. Reflection symmetric phases. A diagram of the topological quadrupole phases of the insulator $h^{q}(\\mathbf{k})$ is shown in Fig. 30 as a function of the ratios $\\gamma_{x}/|\\lambda_{x}|$ and $\\gamma_{y}/|\\lambda_{y}|$ . The central square of the diagram in the ranges $\\gamma_{x}/|\\lambda_{x}|\\in(-1,1)$ \n\n![](images/a6281e80a6c7274b1427cc773d4982df2475cca6fff138054fd5c7260b94b326.jpg) \nFIG. 30. Phase diagram of the quadrupole insulator $h^{q}(\\mathbf{k})$ with Hamiltonian (6.29). Transitions close the bulk-energy gap when $C_{4}$ symmetry is preserved at the indicated points of the BZ. Transitions close the edge-energy gap when $M_{x}$ and $M_{y}$ reflections are preserved at the indicated edges. \n\nand $\\gamma_{y}/|\\lambda_{y}|\\in(-1,1)$ has a quantized quadrupole moment $\\begin{array}{r}{q_{x y}=\\frac{1}{2}}\\end{array}$ , as it has the boundary signatures of Eq. (6.1). Outside of this region, there is a trivial quantized quadrupole $q_{x y}=0$ . \n\nFollowing the paradigm for the topological characterization of crystalline symmetry-protected topological phases [17,18,27,29,30,32,33,45], we look at the symmetry group representations that the subspace of occupied bands take at the high-symmetry points of the BZ. The point group of the quadrupole insulator $h^{q}(\\mathbf{k})$ is the quaternion group (6.34), which has the character table shown in Appendix K. This group has four one-dimensional representations and one two-dimensional representation. The points of the BZ invariant under this group are $\\mathbf{k}_{*}=\\Gamma,\\mathbf{X},\\mathbf{Y},\\mathbf{M}$ . At all of these points, there is a twofold degeneracy in the spectrum protected by the noncommutation of the $\\hat{M}_{x}$ and $\\hat{M}_{y}$ operators (see Appendix G) and the subspaces of occupied bands at these points lie in the only two-dimensional representation of the quaternion group. Symmetry-allowed perturbations can be added to lift most of the twofold degeneracy of the bulk energy bands of $h^{q}(\\mathbf{k})$ [given in Eq. (6.30)], however, the degeneracy will persist at all $\\mathbf{k}_{*}$ points of the BZ [Fig. 31(a)]. \n\n![](images/884f0f3dcb7ca2908bcfcb81c13bc18cd161dcddf50425be9f3b1d2c042df7b9.jpg) \nFIG. 31. Energy spectrum for quadrupole models that preserve (a) only $M_{x}$ and $M_{y}$ symmetries (Hamiltonian described in Appendix H), and (b) only $C_{4}$ symmetry (Hamiltonian described in Appendix L). Notice that in both cases, $C_{2}$ is also preserved. \n\nSince the quaternion group admits only one twodimensional representation, one cannot construct the typical bulk crystalline topological invariants (the representations are the same at each $\\mathbf{k}_{*}$ ), and hence the topological structure is “hidden” from the point of view of the group representations of the energy bands. Instead, the topology in the presence of $M_{x}$ and $M_{y}$ is captured by the topological classes of the Wannier bands. From the character table in Appendix K it follows that the reflection and $C_{2}$ eigenvalues of the occupied energy bands at each $\\mathbf{k}_{*}$ all come in $(+i,-i)$ pairs. Indeed, these values are necessary to have gapped Wannier bands, $\\nu_{x}^{\\pm}(k_{y})$ and $\\nu_{y}^{\\pm}(k_{x})$ , as shown in Fig. 19 [pairs of reflection or $C_{2}$ eigenvalues other than $(+i,-i)$ , inevitably lead to at least one pair of Wannier bands being gapless, see Sec. VI C]. The Wannier bands can belong to different topological classes, as discussed in Sec. VI D 3, and are identified by a pair of Wannier-sector polarizations as in Eq. (6.42). Since the $q_{x y}=$ $\\frac{1}{2}$ phase coincides with the Wannier band topology having $\\bar{\\mathbf{p}}^{\\nu}=(\\textstyle\\frac{1}{2},\\textstyle\\frac{1}{2})$ , we can construct the index for the reflection symmetry-protected quadrupole phase as \n\n$$\nq_{x y}\\overset{M_{x},M_{y}}{=}p_{y}^{\\nu_{x}^{-}}p_{x}^{\\nu_{y}^{-}}+p_{y}^{\\nu_{x}^{+}}p_{x}^{\\nu_{y}^{+}}\n$$ \n\nwhich takes values \n\n$$\nq_{x y}\\stackrel{M_{x},M_{y}}{=}\\left\\{\\begin{array}{l l}{0,}&{\\mathrm{if~trivial}}\\\\ {1/2,}&{\\mathrm{if~nontrivial.}}\\end{array}\\right.\n$$ \n\nThe expression (6.45) resembles the classical expression for a quadrupole; it is the multiplication of two “coordinates” (one measures the displacement along $x$ and the other one along $y$ ) added over the charges (two electrons in this case). Due to the constraint (6.40), the index simplifies to \n\n$$\nq_{x y}\\overset{M_{x},M_{y}}{=}2p_{y}^{\\nu_{x}^{-}}p_{x}^{\\nu_{y}^{-}}.\n$$ \n\nAccordingly, both the edge polarizations and the corner charges of the insulator in this nontrivial SPT phase are quantized. Appendix $\\mathrm{~H~}$ shows simulations that break all symmetries except the quantizing reflection symmetries $M_{x}$ and $M_{y}$ to verify the quantization of the corner charge and edge polarization, as long as the symmetry-breaking perturbations do not close the Wannier gaps. The protection due to Wannier band topology, instead of bulk-energy band topology, is a new mechanism of topological protection. This protection implies that, at symmetry-preserving boundaries between a topological phase and the vacuum, edges are not required to be gapless, i.e., it allows for the possibility of gapped edges. These edges, however, are topological themselves. The Wannier band protection mechanism leads to the existence of gapped, symmetry-preserving edges which are topological. This idea can be extended far beyond this example so that we can generate bulk topological phases with many types of gapped, surface SPTs. In some sense, these phases represent a simpler version of the gapped, symmetry-preserving surfaces of 3D strong topological phases which must instead be topologically ordered [70–74]. \n\n$b$ . $C_{4}$ -symmetric phases. In the presence of $C_{4}$ symmetry, the quadrupole minimal model $h^{q}(\\mathbf{k})$ , with Hamiltonian (6.29), is in either the trivial phase $q_{x y}=0$ , or the topological phase $\\begin{array}{r}{q_{x y}=\\frac{1}{2}}\\end{array}$ . Unlike the case in which symmetries $M_{x}$ and $M_{y}$ protect the quadrupole moment, under $C_{4}$ symmetry the quadrupole moment is protected by the topology of the bulk-energy bands. Accordingly, a topological index can be built by comparing the rotation representations of the subspace of occupied energy bands at the $C_{4}$ -symmetric points of the BZ, $\\mathbf{k}_{\\star}=\\Gamma$ and M [32,33], shown in Fig. 32(a). Since $C_{4}$ symmetry only has one-dimensional representations, it does not protect degeneracies in the energy bands of $h^{q}(\\mathbf{k})$ . An example of this lack of protection is shown in Fig. 31(b), where we show the energy bands for a Hamiltonian based on $h^{q}(\\mathbf{k})$ that has flux other than $\\pi$ at each plaquette. This modification in the Hamiltonian breaks $M_{x}$ and $M_{y}$ but preserves $C_{4}$ , as detailed in Appendix $\\mathrm{~L~}$ . \n\n![](images/0630e6e8117824b640e1a4afcdd88f0f730587d717f1c7b62e233564fbd1c2d4.jpg) \nFIG. 32. Rotation representations for the occupied bands of the quadrupole model (6.29) in the presence of $C_{4}$ symmetry (6.36). (a) BZ and its $C_{4}$ -invariant momenta $\\mathbf{k}_{\\star}=\\mathbf{\\Gamma}\\mathbf{\\Gamma},\\mathbf{M}$ (b)–(d). Let $\\lambda_{x}=$ $\\lambda_{y}=1,\\gamma_{x}=\\gamma_{y}=\\gamma.C_{4}$ rotation eigenvalues at $\\mathbf{k}_{\\star}$ for (b) quadrupole phase $|\\gamma|<1$ , (c) trivial phase with $\\gamma>1$ , and (d) trivial phase with γ < 1. \n\nIn order to define the topological index, consider $h^{q}(\\mathbf{k}_{\\star})$ , with $\\gamma_{x}=\\gamma_{y}=\\gamma$ and $\\lambda_{x}=\\lambda_{y}=\\lambda$ , which obeys \n\n$$\n[{\\hat{r}}_{4},h^{q}({\\bf k}_{\\star})]=0.\n$$ \n\nFrom this it follows that the eigenstates of $h^{q}(\\mathbf{k}_{\\star})$ are also eigenstates of the rotation operator. Thus, the occupied states at $\\mathbf{k}_{*}$ obey \n\n$$\n\\hat{r}_{4}\\big|u_{\\mathbf{k}_{\\star}}^{n}\\big\\rangle=r_{4}^{n}(\\mathbf{k}_{\\star})\\big|u_{\\mathbf{k}_{\\star}}^{n}\\big\\rangle,\n$$ \n\nwhere $n=1,2$ labels the occupied states, and $r_{4}^{n}(\\mathbf{k}_{\\star})$ is the rotation eigenvalue of the nth occupied state at the $C_{4}$ -invariant momentum $\\mathbf{k}_{\\star}$ . \n\nTo build the index, we first recall that the eigenvalues of the $C_{2}$ operator, $\\hat{r}_{2}=\\hat{r}_{4}^{2}$ , for the occupied bands at the $\\mathbf{k}_{\\star}$ are $\\pm i$ . Thus, the $C_{4}$ eigenvalues in the occupied energy bands come in pairs $r_{4}^{+}(\\mathbf{k}_{\\star})$ , $r_{4}^{-}(\\mathbf{k}_{\\star})$ , such that \n\n$$\n\\begin{array}{r}{(r_{4}^{+}({\\bf k}_{\\star}))^{2}=+i,}\\\\ {(r_{4}^{-}({\\bf k}_{\\star}))^{2}=-i.}\\end{array}\n$$ \n\n![](images/32d732f9d1fd31e7ae41aa72de3e1afb4431260d3a6e7098a879b079744ee277.jpg) \nFIG. 33. Schematic of a $C_{4}$ -symmetric insulator that breaks $M_{x}$ and $M_{y}$ in the topological phase. It has quantized corner charges $\\pm e/2$ but not quantized edge polarizations $e/2+\\Delta$ , in a $C_{4}$ -symmetric pattern. \n\nWith this restriction, there are only two topologically distinct configurations of eigenvalues as shown in Fig. 32. We can then take either the $r_{4}^{+}(\\mathbf{k}_{\\star})$ values or the $r_{4}^{-}(\\mathbf{k}_{\\star})$ values to construct the index \n\n$$\ne^{i2\\pi q_{x y}}\\overset{C_{4}}{=}r_{4}^{+}(\\mathbf{M})r_{4}^{+*}(\\mathbf{\\Gamma}\\mathbf{r})=r_{4}^{-}(\\mathbf{M})r_{4}^{-*}(\\mathbf{\\Gamma}\\mathbf{r}),\n$$ \n\nwhich takes the values of $e^{i2\\pi q_{x y}}=\\pm1$ in the trivial or topological quadrupole phases, respectively. This corresponds to quantized values of the quadrupole of \n\n$$\nq_{x y}\\ {\\stackrel{C_{4}}{=}}\\ \\left\\{{0,\\atop{1/2}}\\right.\\ \\mathrm{{if}\\ t r i v i a l}\\nonumber\n$$ \n\nThis index is independent of the choice of $C_{4}$ rotation operator, provided that the same operator is used at both $\\Gamma$ and M. For example, for the choice of ${\\hat{r}}_{4}$ of (6.36), which obeys $\\hat{r}_{4}^{4}=$ $-\\tau_{0}\\otimes\\tau_{0}$ , its eigenvalues are $e^{\\pm i\\pi/4}$ , $e^{\\pm i3\\pi/4}$ , and the rotat on eigenvalues in the trivial and topological quadrupole phases of (6.29) under $C_{4}$ symmetry are schematically shown in Fig. 32. \n\nIn $C_{4}$ symmetry-preserving transitions, $h^{q}(\\mathbf{k})$ closes the bulk-energy gap at $\\mathbf{I},\\mathbf{X},\\mathbf{Y}$ , or $\\mathbf{M}$ , as indicated by the dots in Fig. 30. At these transitions, the rotation eigenvalues of the occupied energy bands change from the configuration in Fig. 32(b) to those in either 32(c) or 32(d). \n\nWe finally point out that, since $C_{4}$ symmetry does not protect the Wannier-sector polarizations, the quantization of the edge polarizations is not guaranteed in the presence of $C_{4}$ symmetry. For example, if $C_{4}$ -symmetric perturbations having hopping terms between nearest-neighbor unit cells are added, the observables of the Hamiltonian could be modified as schematically shown in Fig. 33 we note that if only fluxes other than $\\pi$ are put on each plaquette to break the reflection symmetries of $h^{q}(\\mathbf{k})$ then the edge polarizations remain quantized. Even though the edge polarizations are not quantized, (i) the corner charge remains quantized, and (ii) the relation between edge polarizations and corner charge still implies the existence of a quantized quadrupole moment, on top of which edge dipoles of magnitude $\\Delta$ are overlapped in a $C_{4}$ -symmetric pattern (see Sec. II D). \n\n# 7. Phase transitions in the quadrupole insulator \n\nThe closing of either the energy gap or the Wannier gap is a property dictated by the bulk band parameters. In this section, we describe how the phase transitions in $h^{q}(\\mathbf{k})$ manifest at the boundaries. In the following description, we set $\\lambda_{x}=\\lambda_{y}=1$ for simplicity. \n\n![](images/5ab547254d3b51b479a09b812fe9db0f8d513031320bbb5621dad51788c6f38f.jpg) \nFIG. 34. Two types of quadrupole phase transitions for Hamiltonian (6.29) with full open boundaries. For (a), (b) we have a $C_{4^{-}}$ , $M_{x}.$ -, and $M_{y}$ -symmetric Hamiltonian. (a) Energy bands as a function of $\\gamma=\\gamma_{x}=\\gamma_{y}$ . (b) Probability density function of the zero-energy modes as the system approaches the transition with $C_{4}.$ , $M_{x}$ -, $M_{y}$ -symmetric Hamiltonian, having $(\\gamma_{x},\\gamma_{y})=(0.75,0.75)$ . (c), (d) Have $M_{x}$ and $M_{y}$ but not $C_{4}$ (c) energy bands as a function of $\\gamma_{y}$ while fixing $\\gamma_{x}=0.5$ . (d) Probability density function of the zero-energy modes as the system approaches the transition for a Hamiltonian having $(\\gamma_{x},\\gamma_{y})=(0.5,0.75)$ . In the simulations, there are $40\\times40$ unit cells. For the purpose of illustration, unit cells in the range $N_{x,y}\\in[5,34]$ are in the topological quadrupole phase with $(\\gamma_{x},\\gamma_{y})$ as indicated. Unit cells outside of $N_{x,y}\\in[5,34]$ are in the trivial phase with $(\\gamma_{x},\\gamma_{y})=(2,2)$ . All unit cells have $\\lambda_{x}=\\lambda_{y}=1$ . \n\nWe start with the $C_{4}$ -, $M_{x}$ -, and $M_{y}$ -symmetric transitions with full open boundaries. The energy bands for this system as a function of the parameter $\\gamma=\\gamma_{x}=\\gamma_{y}$ are shown in Fig. 34(a). In the topological phase, the red lines denote the corner-localized, fourfold-degenerate modes, which are characteristic of the topological quadrupole phase, as seen in Fig. 34(b). During the transition, the bulk-energy gap closes and the corner-localized states hybridize and fuse into the bulk and are no longer present in the trivial phase. \n\nIf we now drive the transition by varying $\\gamma_{y}$ while keeping $|\\gamma_{x}|<1$ , as in Fig 34(c), only the energy gap of the edge parallel to $y$ closes. Consequently, as the transition is approached, the four corner modes hybridize in pairs along the edge parallel to $y$ , as seen in Fig. 34(d). Recall that this phase transition is associated with a closing of the Wannier gap at $\\begin{array}{r}{\\nu_{x}(k_{y}=\\pi)=\\frac{1}{2}}\\end{array}$ when the system has periodic boundary conditions (second column, first row, of Fig. 28). Hence, we conclude that a gap closing of the Wannier bands results in an energy-gap closing in the 1D $x$ -edge Hamiltonian.2 This relation between the bulk property of Wannier-gap closing and the energy-gap closing of the edge can be inferred from the adiabatic mapping connecting the Wannier bands to the Hamiltonian of the edge as detailed in Sec. IV B 2. \n\n![](images/0508d30d50949611edaa565d9ae23599dd3d2468ec37de369232d0a2242954db.jpg) \nFIG. 35. (a) Energy bands and (b) Wannier bands $\\nu_{x}^{j}$ , for $j\\in$ $1\\ldots2N_{y}$ , with closed boundaries along $x$ and open along $y$ as a function of $\\gamma_{y}$ while fixing $\\gamma_{x}=0.5$ . In all plots, $\\lambda_{x}=\\lambda_{y}=1$ . Red lines indicate the twofold-degenerate states with polarization $\\frac{1}{2}$ localized at the open edges. \n\nIndeed, one can verify that the energy-gap closing occurs along the $x$ edge by repeating the calculation in Fig. 34(c), but for a quadrupole insulator with periodic boundaries along $x$ . This is shown in Fig. 35(a). In contrast to what happens in Fig. 34(c), the energy bands in Fig. 35(a) do not close the gap. In this setup, in which boundaries along $x\\ (y)$ are closed (open), this transition can be visualized by plotting the Wannier bands $\\nu_{x}^{j}$ , for $j\\in1\\ldots2N_{y}$ , as a function of the parameter $\\gamma_{y}$ . This is shown in Fig. 35(b). The red line in this figure indicates the twofold Wannier-degenerate states that are localized at the two opposite y edges, having Wannier value of $\\frac{1}{2}$ . These states are characteristic of the quadrupole phase, and are responsible for the quantized edge polarizations (see Sec. VI D 5). Analogous to the corner-localized modes in the energy plots, the edge-localized modes in the Wannier plots hybridize as the Wannier gap closes, and fuse into the bulk outside of the quadrupole phase. Physically, this plot illustrates that (even in the absence of corners) the edge polarizations are clear signatures that persist only as long as the bulk is in the quadrupole topological phase. The mapping described in Sec. IV B 2 that adiabatically maps the Wannier bands of Fig. 35(b) to the edge energies in Fig. 34(c) is consistent with this phenomenology. \n\nIn the phase diagram in Fig. 30 for the quadrupole topological phases of $h^{q}(\\mathbf{k})$ , the blue and red lines indicate the edges at which the energy bands close for $M_{x}$ - and $M_{y}$ -preserving phase transitions, and the black dots indicate the points of the BZ at which the bulk-energy bands close for $C_{4}$ -preserving phase transitions. \n\nLet us make some final notes about the multicritical nature of the bulk phase transition. We see that we only find a bulk phase transition in our phase diagram when $C_{4}$ symmetry is preserved. However, our phase diagram is implicitly assuming that both reflection symmetries are preserved since every point in the phase diagram has reflection symmetry by design. Hence, if we have both reflection symmetries and $C_{4}$ symmetry, we naturally have a bulk critical point where a transition occurs via a double Dirac point in momentum space. If we remove $C_{4}$ symmetry but preserve reflection symmetry, then we have already seen in detail that we will not generically have a bulk critical point separating the quadrupole phase from the trivial phase. Additionally, there is one more option we have not discussed, which is to preserve $C_{4}$ symmetry, but break both reflection symmetries. We need to break both reflections because their product is proportional to the $C_{2}$ rotation operator, and hence must be preserved. This implies that both reflections are either preserved or both broken. In this scenario, there will still generically be a bulk-gap closing when transitioning out of the quadrupole phase. However, the direct transition to a trivial insulator will be replaced by a two-step process with an intermediate phase separating the quadrupole insulator from the trivial insulator. As one tunes a single parameter, the quadrupole phase will first transition to a Chern insulator with a bulk-gap closing at a single Dirac point. Then, as the parameter is further tuned, the Chern insulator will transition to the trivial phase through a second single Dirac point. Thus, breaking reflection symmetries will split the direct quadrupole-to-trivial transition into two single Dirac cone transitions with an intermediate Chern insulator phase. The Chern insulator phase is not compatible with reflection symmetry, and hence does not appear in the phase diagram if reflection symmetry is preserved. \n\n# E. Dipole pumping \n\nWe now break the symmetries that protect the topological quadrupole phase by adding perturbations to the Hamiltonian (6.29). As a result, the quadrupole observables lose their quantization. We will see in particular that a new type of electronic pumping occurs, that of a dipole current. \n\nBreaking the symmetries that quantize the quadrupole can occur in the following scenarios: (i) Perturbation breaks $M_{i}$ and $C_{2}$ symmetries but keeps $M_{j}$ . This quantizes pj±νi and the bulk dipole moment pj but does not quantize $p_{i}^{\\pm\\nu_{j}}$ nor the bulk dipole moment $p_{i}$ . Here, $i,j=x,y$ and $i\\neq j$ . (ii) Perturbation breaks $M_{x}$ and $M_{y}$ symmetries but keeps $C_{2}$ symmetries. This does not quantize $p_{x}^{\\pm\\nu_{y}}$ nor $p_{y}^{\\pm\\nu_{x}}$ , but keeps the total bulk dipole moment quantized, e.g., $\\mathbf{p}=\\mathbf{0}$ . \n\nWe concentrate on the second scenario because we are interested in pumping arising exclusively from the bulk quadrupole moment and not from dipole moment contributions. A perturbation that breaks both reflection symmetries while preserving $C_{2}$ is the one we have used in Eq. (6.39) to choose the “sign” of the quadrupole. The simplest and most illustrative pumping process consists of the adiabatic evolution of the insulator in Eq. (6.39) parametrized by $t$ according to \n\n![](images/3788a171b199809a75ac8e0e95e2c845bbc19791f5d35d6a30a505d117a40101.jpg) \nFIG. 36. Adiabatic pumping (6.53) for the first part of the cycle $0$ 2 there is no dipole pumping, as the insulator is in the trivial phase at both $t=0,\\pi$ . Figure 39 shows the adiabatic evolution of this Hamiltonian with $m=1$ and open boundaries along both directions. In Fig. 39(a), the bulk energies (marked in dark blue) are gapped. The energies that cross the bulk-energy gap (marked in red and green) are each twofold degenerate (i.e., there are a total of four gap-crossing states), and correspond to the corner-localized states. Each pair of twofold-degenerate states localize at opposite corners. At half-filling, the result of pumping is to change the values of the charges at the corners by $e$ , as seen in Fig. 39(b), so that the final quadrupole is equivalent to the original one upon a rotation by $90^{\\circ}$ . In Fig. 39(b), we start at a time $\\epsilon$ and finish at $2\\pi-\\epsilon$ , for $\\epsilon\\ll1$ , so that we clearly define the initial sign of the quadrupole by slightly deviating away from the perfectly symmetric SPT quadrupole phase. \n\n![](images/3de6d92aadee4345bffdaccc49336d2fd49777544f1fe7cbb74a08fbb0a0a1bd.jpg) \nFIG. 39. Adiabatic pumping (6.57) with open boundaries in both directions. $t$ is the pumping adiabatic parameter. (a) Energy spectrum. Green (red) lines are twofold degenerate and have corresponding modes that localize at opposite corners. (b) Corner charge during pumping. Open blue (solid red) circles represent a corner charge of $+e/2\\left(-e/2\\right)$ at the beginning and end points of the pumping process. Charge inversion amounts to pumping a quantum of dipole moment. \n\nAlthough the pumping (6.53) also reflects the characteristics we just described, the convenience of the parametrization (6.57) will become evident when we make a connection between dipole pumping processes and a new type of topological insulator in one higher spatial dimension in the Sec. VI F. \n\n# F. Topological insulator with hinge-localized chiral modes \n\nIn Sec. III F, we saw that adiabatic charge pumping in 1D insulators by means of a changing dipole moment is characterized by the winding of the Wannier eigenvalues as a function of the adiabatic parameter. This winding is equivalent to a Chern number in the mixed momentum-adiabatic parameter space. If we rename the adiabatic parameter $t$ in the model with a torus parametrization to a new momentum variable, e.g., $t\\rightarrow k_{y}$ , the resulting 2D model is a Chern insulator characterized by the usual 2D Chern number over the BZ. An analogous connection exists in the case of the quantization of adiabatic dipole pumping by means of a changing quadrupole moment. \n\nIf we substitute $t\\rightarrow k_{z}$ in Eq. (6.57), the resulting model is the Hamiltonian of a 3D insulator with a winding quadrupole invariant along $k_{z}$ . Figure 40(a) shows the dispersion of this insulator when boundaries are open along both $x$ and $y$ , but closed along z. Notice that this is in essence the same plot as that in Fig. 39(a). The interpretation, however, is different. The corner-localized modes during the adiabatic pumping now map to edge-localized modes that are chiral and carry current in a quadrupolar fashion when an electric field along z is applied. A schematic of this insulator is shown in Fig. 40(b). These hinge-localized modes are protected by the Wannierband Chern number \n\n$$\nn_{y z}^{\\nu_{x}}=\\frac{1}{(2\\pi)^{2}}\\int_{\\mathrm{BZ}}\\mathrm{Tr}\\big[\\tilde{\\mathcal{F}}_{y z,\\mathbf{k}}^{\\nu_{x}}\\big]d^{3}\\mathbf{k},\n$$ \n\nwhere \n\n$$\n\\tilde{\\mathcal{F}}_{j k,{\\bf k}}^{\\nu_{i}}=\\partial_{j}\\tilde{A}_{k,{\\bf k}}^{\\nu_{i}}-\\partial_{k}\\tilde{A}_{j,{\\bf k}}^{\\nu_{i}}+i\\big[\\tilde{A}_{j,{\\bf k}}^{\\nu_{i}},\\tilde{A}_{k,{\\bf k}}^{\\nu_{i}}\\big]\n$$ \n\n![](images/71e3451d8c7e294e50e46210297c258d602ea435ae067faec2df2cfee4a8fde2.jpg) \nFIG. 40. A crystalline insulator with chiral, hinge-localized modes that disperse in equal directions at opposed corners and opposite directions in adjacent ones. This insulator is in the same topological class as the pumping (6.57). Both can be identified via the map $t\\rightarrow k_{z}$ . (a) Energy dispersion for a system with open boundaries along $x$ and $y$ but closed boundaries along z. (b) Hinge-localized modes. Arrows indicate direction of dispersion in the presence of an electric field along z. (c) Wannier bands, each having a nonzero Chern number defined in Eq. (6.58). (d) Illustration of the compatibility relationship between Chern invariants (6.61). Circles indicate direction of chiral currents compatible with the hinge currents of (b). \n\nfor $i,j,k=x,y,z$ and $i\\neq j\\neq k$ , is the Berry curvature over the Wannier bands $\\nu_{i}$ , and $\\tilde{\\mathcal{A}}_{j,\\mathbf{k}}^{\\nu_{i}}$ is the Berry connection of the $\\nu_{i}$ Wannier sector, defined in Eq. (6.17). A plot of these Wannier bands is shown in Fig. 40(c). They are gapped and each of them carry a Chern number (instead of just a Berry phase like the 2D quadrupole model). Notice that we always have \n\n$$\nn_{j k}^{\\nu_{i}^{-}}=-n_{j k}^{\\nu_{i}^{+}}.\n$$ \n\nFrom this analysis, we conclude that 3D insulators have additional anisotropic topological indices that signal the presence of chiral, hinge-localized states parallel to $x,y$ , or $z$ . For example, in the insulator of Fig. 40, we have \n\n$$\n\\begin{array}{l}{{n_{y z}^{\\nu_{x}^{+}}=-n_{z x}^{\\nu_{y}^{+}}=1,}}\\\\ {{\\ n_{x y}^{\\nu_{z}^{+}}=0.}}\\end{array}\n$$ \n\nIn general, this type of cyclic relationship is kept. Thus, unlike the weak indices for polarization (4.26), which are each independent of each other, the Chern numbers $n_{j k}^{\\nu_{i}}$ defined in Eq. (6.58) are related by similar constraints to (6.61), as otherwise the hinge-localized modes would give incompatible hinge current flows. See Fig. 40(d) for an illustration of the compatibility conditions. While the lateral surfaces have chiral currents described by the first equation in Eq. (6.61), the upper and lower surfaces have currents in a quadrupole pattern. \n\n![](images/ef03e9349b3a2855902bc772d15a4aaffcf26f8439fcaeac138c7fb6412c01fa.jpg) \nFIG. 41. Lattice model of an octupole insulator with Bloch Hamiltonian (7.1). (a) Degrees of freedom and couplings within the unit cell. (b) Hopping terms in a lattice with eight unit cells. In both (a) and (b) the dashed lines represent a coupling with negative phase factor. As a result of these phase factors, a flux of $\\pi$ threads each facet. \n\n# VII. BULK OCTUPOLE MOMENT IN 3D CRYSTALS \n\nThe natural extension of the quadrupole moment in 2D is the octupole moment in 3D. In this section, we discuss in detail the calculation of the quantized octupole moment and describe a simple model that realizes it. We discuss both the SPT phase with quantized boundary signatures, and an adiabatic pumping process. In particular, for the latter we will see that an adiabatic cycle can pump a quantum of quadrupole moment. \n\n# A. Simple model with quantized octupole moment in 3D \n\nIn order to have a well-defined octupole moment in the bulk of a 3D insulator, the bulk quadrupole and bulk dipole moments must vanish. Additionally, we require that no Wannier flow exists for Wannier centers along any direction, so as to avoid strong $\\mathbb{Z}_{2}$ insulators and weak topological insulators with layered Chern or $\\mathbb{Z}_{2}$ QSH invariants that would result in metallic boundaries. Using these constraints, we can find a simple model for an octupole insulator as shown in Fig. 41. It has Bloch Hamiltonian \n\n$$\n\\begin{array}{r l}&{h_{\\delta}^{o}(\\mathbf{k})=\\lambda_{y}\\sin(k_{y})\\Gamma^{\\prime1}+[\\gamma_{y}+\\lambda_{y}\\cos(k_{y})]\\Gamma^{\\prime2}}\\\\ &{~+\\lambda_{x}\\sin(k_{x})\\Gamma^{\\prime3}+[\\gamma_{x}+\\lambda_{x}\\cos(k_{x})]\\Gamma^{\\prime4}}\\\\ &{~+\\lambda_{z}\\sin(k_{z})\\Gamma^{\\prime5}+[\\gamma_{z}+\\lambda_{z}\\cos(k_{z})]\\Gamma^{\\prime6}+\\delta\\Gamma^{\\prime0},}\\end{array}\n$$ \n\nwhere $\\Gamma^{\\prime i}=\\sigma_{3}\\otimes\\Gamma^{i}$ for $i=0,1,2,3$ , $\\Gamma^{\\prime4}=\\sigma_{1}\\otimes I_{4\\times4}$ , $\\Gamma^{\\prime5}=$ $\\sigma_{2}\\otimes I_{4\\times4}$ , and $\\Gamma^{\\prime6}=i\\Gamma^{\\prime0}\\Gamma^{\\prime1}\\Gamma^{\\prime2}\\Gamma^{\\prime3}\\Gamma^{\\prime4}\\Gamma^{\\prime5}$ . Here, the internal degrees of freedom follow the numbering in Fig. 41. When $|\\lambda_{i}|>|\\gamma_{i}|$ for all $i=x,y,z$ this system is an insulator at half-filling with four occupied bands and a quantized octupole moment $\\begin{array}{r}{o_{x y z}=\\frac{1}{2}}\\end{array}$ . For $\\delta=0$ , this Hamiltonian has reflection symmetries $M_{x,y,z}$ (up to a gauge transformation, see Appendix E), with operators \n\n$$\n\\begin{array}{r l r}&{}&{\\hat{M}_{x}=\\tau_{0}\\otimes\\tau_{1}\\otimes\\tau_{3},}\\\\ &{}&{\\hat{M}_{x}=\\tau_{0}\\otimes\\tau_{1}\\otimes\\tau_{1},}\\\\ &{}&{\\hat{M}_{x}=\\tau_{1}\\otimes\\tau_{3}\\otimes\\tau_{0},}\\end{array}\n$$ \n\n![](images/f5a94f75304c1a28df166800e17af4b475961a9a719b749a448b3a643b8b96e8.jpg) \nFIG. 42. Electronic charge density of the octupole insulator with open boundaries. Corners have a charge of $\\pm e/2$ relative to the background charge. \n\nwhich obey $\\{\\hat{M}_{i},\\hat{M}_{j}\\}=0$ for $i,j=x,y,z$ and $i\\neq j$ . The octupole moment $\\phantom{\\frac{1}{2}}O_{x y z}$ is odd under each of these symmetries. In the continuum theory, this admits only the solution $o_{x y z}=0$ , but the ambiguity in the position of the electrons due to the introduction of the lattice (see Sec. III A) also allows the solution $\\begin{array}{r}{o_{x y z}=\\frac{1}{2}}\\end{array}$ mod 1. In addition, these symmetries quantize $p_{x},p_{y},p_{z},q_{x y},q_{x z}$ , and $q_{y z}$ , all of which must vanish for $\\phantom{\\frac{1}{2}}O_{x y z}$ to be well defined. \n\nOne signature of the topological octupole moment is the existence of fractional half-charges localized on the corners of a cubic sample. Indeed, the nontrivial quantized octupole phase of this model has corner-localized mid-gap modes. We add an infinitesimal $\\delta$ in the Hamiltonian that breaks the cubic symmetry of the crystal down to tetrahedral symmetry. This splits the degeneracy of the zero modes, hence fixing the sign of the octupole moment. A plot of the charge density for this crystal is shown in Fig. 42. \n\nThe four-dimensional subspace of occupied energy bands in the Hamiltonian (7.1) has reflection eigenvalues $\\{-1,-1,+1,+1\\}$ at all high-symmetry points. Consequently, the Wannier centers of the Wilson loop ${\\cal W}_{z,{\\bf k}}$ come in pairs $\\{\\pm\\nu_{z}^{1}(\\mathbf{k}_{\\perp}),\\pm\\nu_{z}^{2}(\\mathbf{k}_{\\perp})\\}$ , where ${\\bf k}_{\\perp}=(k_{x},k_{y})$ (see Table III). In the 3D BZ of Hamiltonian (7.1), the spectrum of the Wilson loop ${\\mathcal W}_{z,{\\bf k}}$ yields two, twofold-degenerate Wannier bands separated by a Wannier gap, i.e., $\\bar{\\nu_{z}^{1}}(\\mathbf{k}_{\\perp})=\\nu_{z}^{2}(\\mathbf{k}_{\\perp})$ , as seen in Fig. 43. Since an octupole is made from two quadrupoles, we want to show that each of these two-band Wannier sectors has a topological quadrupole moment. We now show how to determine this quadrupole moment. \n\n# B. Hierarchical topological structure of the Wannier bands \n\nMicroscopically, a bulk octupole can be thought of as arising from two spatially separated quadrupoles with opposite sign. Thus, since a quadrupole insulator requires two occupied bands, an octupole insulator requires a minimum of four occupied bands. Our model (7.1) is then a minimum model with octupole moment. To reveal its topological structure, we begin the analysis by performing a Wilson loop along the $z$ direction, \n\n![](images/919154a49349999cd5ee84ba0a905568c27770a338c17f4383ce40ce3cae0edb.jpg) \nFIG. 43. Schematic of the procedure to determine the topology of an octupole moment. A Wilson loop along z over the 3D BZ (purple cube) divides it in two sectors, according to its Wannier value $\\nu_{z}^{\\pm}$ (red and light blue plots over the cube). Each sector has two bands (represented by the red and blue squares) and has quadrupole topology. This can be verified by calculating Wilson loops along $y$ over each sector, which renders two Wannier sectors $\\eta_{y}^{\\pm}$ (red or blue pair of symmetric lines), each of them having a Berry phase of 0 or $\\pi$ in its Wilson loop along $x$ in the $|\\lambda_{i}|<|\\gamma_{i}|$ (for all $i$ ) or $|\\lambda_{i}|>|\\gamma_{i}|$ (for all $i$ ) regime, respectively. \n\n$$\n\\begin{array}{r}{\\mathcal{W}_{z,{\\mathbf{k}}}\\big|\\nu_{z,{\\mathbf{k}}}^{j}\\big\\rangle=e^{i2\\pi\\nu_{z}^{j}({\\mathbf{k}}_{\\perp})}\\big|\\nu_{z,{\\mathbf{k}}}^{j}\\big\\rangle,}\\end{array}\n$$ \n\nwhere ${\\bf k}_{\\perp}=(k_{x},k_{y})$ . The Wilson loop along $z$ is represented by a $4\\times4$ matrix, which has eigenstates $|\\nu_{z,\\mathbf{k}}^{j}\\rangle$ for $j=1,2,3,4$ . In an octupole phase, the Wilson loop splits the four occupied energy bands into two Wannier sectors $\\nu_{z}^{\\pm}({\\bf k}_{\\perp})$ , separated by a Wannier gap. The existence of the Wannier gap is protected by the noncommutation of reflections operators (7.2). Each of the two sectors, $\\nu_{z}^{\\pm}$ , has opposite topological quadrupole moment. The Wannier bands $\\nu_{z}^{\\pm}$ for the minimal octupole insulator with Hamiltonian in Eq. (7.1) are shown in red and light blue in Fig. 43. \n\nIn order to determine the quadrupole moment of each of the sectors $\\nu_{z}^{\\pm}$ , we proceed similarly to Sec. VI for either $\\nu_{z}^{+}$ or $\\nu_{z}^{-}$ . Concretely, let us first rewrite Eq. (7.3) as \n\n$$\n{\\mathcal W}_{z,{\\bf k}}\\big|\\nu_{z,{\\bf k}}^{\\pm,j}\\big\\rangle=e^{i2\\pi\\nu_{z}^{\\pm}({\\bf k}_{\\perp})}\\big|\\nu_{z,{\\bf k}}^{\\pm,j}\\big\\rangle\n$$ \n\nfor $j=1,2$ . Without loss of generality, we choose the sector $\\nu_{z}^{+}$ and construct the Wannier states \n\n$$\n\\big|w_{z,{\\bf k}}^{+_{z},j}\\big>=\\sum_{n=1}^{N_{\\mathrm{occ}}}\\big|u_{{\\bf k}}^{n}\\big>\\big[\\nu_{z,{\\bf k}}^{+,j}\\big]^{n}\n$$ \n\nfor $j=1,2$ . Here, the superscript $+_{z}$ is short for the Wannier sector $\\nu_{z}^{+}$ . We use this basis to calculate the nested Wilson loop along y, \n\n$$\n\\begin{array}{r l}&{\\big[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{+_{z}}\\big]^{j,j^{\\prime}}=\\big\\langle w_{z,\\mathbf{k}+N_{y}\\mathbf{A}_{k_{y}}}^{+_{z},j}\\big\\vert w_{z,\\mathbf{k}+(N_{y}-1)\\mathbf{A}_{k_{y}}}^{+_{z},r}\\big\\rangle\\cdot\\cdot\\cdot}\\\\ &{\\qquad\\big\\langle w_{z,\\mathbf{k}+(N_{y}-1)\\mathbf{A}_{k_{y}}}^{+_{z},r}\\big\\vert\\cdot\\cdot\\cdot}\\\\ &{\\qquad\\big\\vert w_{z,\\mathbf{k}+\\mathbf{A}_{k_{y}}}^{+_{z},s}\\big\\rangle\\big\\langle w_{z,\\mathbf{k}+\\mathbf{A}_{k_{y}}}^{+_{z},s}\\big\\vert w_{z,\\mathbf{k}}^{+_{z},j^{\\prime}}\\big\\rangle,}\\end{array}\n$$ \n\nwhere $\\Delta_{k_{y}}=(0,2\\pi/N_{y},0)$ . Notice that, since $j,r,\\ldots,s,j^{\\prime}=$ 1,2, this nested Wilson loop is non-Abelian. [This Wilson loop was defined in Eq. (6.11) for 2D crystals, but we reproduce it here in its obvious extension to 3D]. We then diagonalize the nested Wilson loop (7.6), \n\n$$\n\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{+_{z}}\\big|\\eta_{y,\\mathbf{k}}^{+_{z},\\pm}\\big\\rangle=e^{i2\\pi\\eta_{y}^{\\pm}(k_{x})}\\big|\\eta_{y,\\mathbf{k}}^{+_{z},\\pm}\\big\\rangle,\n$$ \n\nwhich resolves the Wannier sector $\\nu_{z}^{+}$ into single Wannier bands $\\eta_{y}^{\\pm}(k_{x})$ separated by a Wannier gap (red lines on axes $\\eta_{y}$ in Fig. 43). This Wannier gap is also protected by the non-commutation of (7.2). The quadrupole topology of the Wannier sector $\\nu_{z}^{+}$ manifests in that each of the sectors $\\eta_{y}^{\\pm}$ has a quantized dipole moment, indicated by a Berry phase of 0 or $\\pi$ . For example, let us choose the sector $\\eta_{y}^{+}$ to define the Wannier basis \n\n$$\n|w_{y,\\mathbf{k}}^{+_{z},+_{y}}\\rangle=\\sum_{n=1}^{N_{\\mathrm{occ}}}|u_{\\mathbf{k}}^{n}\\rangle\\big[\\eta_{y,\\mathbf{k}}^{+_{z},+}\\big]^{n}\n$$ \n\nto then calculate a third Wilson loop \n\n$$\n\\begin{array}{r l}&{\\tilde{\\mathcal{W}}_{x,\\mathbf{k}}^{+_{z},+_{y}}=\\big\\langle w_{y,\\mathbf{k}+N_{x}\\mathbf{A}_{k_{x}}}^{+_{z},+_{y}}\\big|w_{y,\\mathbf{k}+(N_{x}-1)\\mathbf{A}_{k_{x}}}^{+_{z},+_{y}}\\big\\rangle}\\\\ &{\\qquad\\times\\big\\langle w_{y,\\mathbf{k}+(N_{x}-1)\\mathbf{A}_{k_{x}}}^{+_{z},+_{y}}\\big|\\cdot\\cdot\\cdot\\big|w_{y,\\mathbf{k}+\\mathbf{A}_{k_{x}}}^{+_{z},+_{y}}\\big\\rangle}\\\\ &{\\qquad\\times\\big\\langle w_{y,\\mathbf{k}+\\mathbf{A}_{k_{x}}}^{+_{z},+_{y}}\\big|w_{y,\\mathbf{k}}^{+}\\big\\rangle.}\\end{array}\n$$ \n\nThis Wilson loop is associated with the Wannier-sector polarization \n\n$$\np_{x}^{+_{z}+_{y}}=-\\frac{i}{2\\pi}\\frac{1}{N_{y}N_{z}}\\sum_{k_{y},k_{z}}\\log\\bigl[\\tilde{\\mathcal{W}}_{x,\\mathbf{k}}^{+_{z},+_{y}}\\bigr]\n$$ \n\nand which for our model takes the values \n\n$$\np_{x}^{+_{z},+_{y}}=\\left\\{\\begin{array}{l l}{1/2,}&{~|\\gamma_{i}|>|\\lambda_{i}|}\\\\ {0,}&{~|\\gamma_{i}|<|\\lambda_{i}|}\\end{array}\\right.\n$$ \n\nfor all $i$ . From this, it follows that the topology of each original Wannier sector $\\nu_{z}^{\\pm}$ is that of a quadrupole, and the topology of the entire Hamiltonian is that of an octupole. \n\nIn this calculation, the order of the nested Wilson loops $\\mathcal{W}_{z}\\rightarrow\\mathcal{W}_{y}\\rightarrow\\mathcal{W}_{x}$ was arbitrary. The same results as in Eq. (7.11) are obtained for any order of Wilson-loop nesting in a quantized octupole insulator, provided that the noncommuting quantizing symmetries are present. \n\n# C. Boundary signatures \n\nClassically, the octupole moment manifests at the faces of a 3D material by the existence of surface-bound quadrupole moments (see Sec. II). In this formulation, the connection between the bulk topology and the boundary topology is given by the adiabatic map between the Wilson loops’ spectrum and the spectrum of the physical boundary Hamiltonians (see Sec. IV B 2). Thus, in the formulation derived in Sec. VII B to characterize the bulk topology of an octupole insulator, we can make the identification \n\n$$\n\\mathcal{W}_{z,{\\bf k}}=e^{-i H_{\\mathrm{surface}}({\\bf k})},\n$$ \n\nwhere ${\\mathcal W}_{z,{\\bf k}}$ is the Wilson loop along $z$ of Eq. (7.3), and $H_{\\mathrm{surface}}(\\mathbf{k})$ has the same topology of the Hamiltonian at the surface of the insulator in the $x y$ plane [we can similarly assign \n\nWilson loops along $x\\ (y)$ to Hamiltonians on the surface yz $(z x)]$ . Similarly, we can make the identification \n\n$$\n\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{+_{z}}=e^{-i H_{\\mathrm{hinge}}(\\mathbf{k})},\n$$ \n\nwhere $\\mathcal{\\tilde{W}}_{y,\\mathbf{k}}^{+_{z}}$ is the nested Wilson loop defined in Eq. (7.6), and $H_{\\mathrm{hinge}}(\\mathbf{k})$ has the same topological properties as the Hamiltonian at the one-dimensional boundaries of the 2D surface $x y$ of the material (i.e., we are now looking into the boundary of the boundary). Notice that in all levels of nesting of the Wilson loops, their Wannier bands remain gapped, which was a condition imposed to avoid boundary metallic modes. Since the Wannier Hamiltonians and edge Hamiltonians are adiabatically connected, this implies that when the Wannier Hamiltonians are gapped, the corresponding boundary Hamiltonians are energy gapped. \n\n# D. Quadrupole pumping \n\nJust as a varying dipole generates charge pumping, and a varying quadrupole generates dipole pumping (pumping of charge on the boundary), an adiabatic evolution of the octupole insulator which interpolates between the topological octupole phase and the trivial octupole phase pumps a quantum of quadrupole. This can be achieved by the Hamiltonian \n\n$$\n\\begin{array}{l}{{\\displaystyle h_{\\mathrm{pump}}^{o}({\\bf k},t)=[-m\\cos(t)+1](\\Gamma^{\\prime2}+\\Gamma^{\\prime4}+\\Gamma^{\\prime6})-m\\sin(t)\\Gamma^{\\prime0}}}\\\\ {~+[\\sin(k_{y})\\Gamma^{\\prime1}+\\cos(k_{y})\\Gamma^{\\prime2}]}\\\\ {~+[\\sin(k_{x})\\Gamma^{\\prime3}+\\cos(k_{x})\\Gamma^{\\prime4}]}\\\\ {~+[\\sin(k_{z})\\Gamma^{\\prime5}+\\cos(k_{z})]\\Gamma^{\\prime6}]}\\end{array}\n$$ \n\nfor $t\\in[0,2\\pi)$ , where $t$ is the adiabatic parameter. The adiabatic cycle can be characterized by a topological invariant that captures the change in octupole moment: \n\n$$\n\\Delta o_{x y z}=\\int_{0}^{2\\pi}d\\tau\\partial_{\\tau}p_{k}^{\\pm_{i}\\pm_{j}}(\\tau)=1\n$$ \n\nfor $i,j,k=x,y,z$ and $i\\neq j\\neq k$ , and where ±i±j (τ ) is defined as in Eq. (7.10) for the instantaneous Hamiltonian (7.14). This particular pumping process preserves the inplane $C_{2}$ symmetries $(x,y,z)\\to(x,-y,-z)$ , $(-x,y,-z)\\to$ $(x,y,-z)$ , and $(x,y,z)\\to(-x,-y,z)$ at all times $t\\in[0,2\\pi)$ , but breaks the reflection symmetries and the overall inversion symmetry $(x,y,z)\\to(-x,-y,-z)$ , except at the SPT phase points at $t=0,\\pi$ . Breaking the reflection symmetries while preserving the in-plane symmetries allows transport only through the hinges, via surface dipole pumping processes. This occurs at all hinges, so that the octupole configuration is inverted as illustrated in Fig. 44. The overall effect amounts to a pumping of a quantum of quadrupole through the 3D bulk. \n\n# VIII. DISCUSSION AND CONCLUSION \n\nIn this paper we have systematically addressed the question of whether insulators can give rise to quantized higher electric multipole moments. Starting from the derivation of observables in a classical, continuum electromagnetic setting, we established the physical signatures of these moments and discussed how the definitions could be generalized for an extended quantum mechanical system in a lattice. \n\n![](images/7f352bf3a524a9d0f64b8f6c20124baf6c54dc99bb5ff407d1b9f4fb2ec484b7.jpg) \nFIG. 44. Initial (left) and final (right) octupole insulators as the result of adiabatic pumping by the Hamiltonian (7.14). Blue (red) dots represent corner-localized charges of $\\pm e/2$ , respectively. A quantum of quadrupole moment is pumped in the process. \n\nThe identification of the higher multipole moments, even in the classical continuum theory, is a subtle matter, especially when a lattice is involved. For example, one signature of a 2D bulk quadrupole moment is a corner charge. However, such a corner charge can arise purely as a surface effect where either free charge is attached to the corner or two edge/surface dipoles converge at a corner. The bulk quadrupole moment exactly captures the failure of the surface dipoles and free charge to account for the corner charge where surfaces intersect (see Fig. 45). The octupole moment has similar subtleties connected to the possibility of surface quadrupole moments and hinge polarizations. If free surface quadrupoles and hinge dipoles were attached to the boundaries in an effort to reproduce the same spatial configuration generated by a bulk octupole moment, they would not produce the correct value of corner charge associated with a bulk octupole moment [see Figs. 45(c) and 45(d)]. Thus, while the quadrupole and octupole moments are bulk properties, their extraction from the associated observable properties, which naturally arise at surfaces and defects, requires care. \n\n![](images/7c8bd5de531b8c6574fab14f8be493fcd986db0934477fc5338144668f1965c3.jpg) \nFIG. 45. Bound states/charges in the quadrupole and octupole SPT phases. (a) Two 1D dipole SPT phases meeting at a corner do not have a corner bound state. (b) A quadrupole SPT phase has edge dipole SPT phases meeting at corners and corner bound state. (c) Three quadrupole and three dipole SPT phases that meet at a corner do not generate a bound state. (d) An octupole SPT phase, which has three surface quadrupoles and three hinge dipoles as in (c), does harbor a corner bound state. \n\nIn the crystalline, quantum mechanical theory, we found that the same macroscopic relations as in the classical continuum theory are maintained. The subtlety that enters at this stage is an inherent ambiguity in the value of the electric moments, where the moments are only well defined up to a “quantum.” In 1D, 2D, and 3D, respectively, the dipole, quadrupole, and octupole densities all have units of charge, and each moment is only well defined up to integer multiples of the electron charge. This ambiguity is countered by the realization that all of the unambiguous observable properties of these moments depend on their changes in time and/or space, and always result in measurements of charges and currents. \n\nOne of the most exciting results of our work is that in the presence of symmetries, multipole moments can take quantized values. The conventional paradigm to quantize such properties is to enforce a symmetry under which a multipole moment transforms nontrivially. In certain scenarios, the aforementioned ambiguity in the definition of these moments in a lattice system allows for the moment to take a nonzero, quantized value. Insulating phases realizing the quantized value are recognized to have a topological character protected by the enforced symmetries. However, the properties of the quadrupole and octupole topological phases are remarkable in the sense that, instead of exhibiting gapless states on the boundary, these phases have gapped boundaries, which are themselves nontrivial SPT phases of lower spatial dimension. This defies the conventional idea of topological phases of matter as phases with a gapped, featureless bulk that, because of their topological nature, require the existence of gapless states on the boundary. Instead, the picture here is similar to the concept in 3D topological phases that a gapped, symmetry-preserving surface cannot be trivial and must have topological order [70–74]. A similar structure follows in the case of the octupole moment; a bulk octupole SPT insulator in 3D generates corner-localized mid-gap bound states, as well as 6 quadrupole SPT phases on its 2D surfaces, and 12 dipole SPT phases on its 1D hinges, all of which converge at the 3D corners. Hence, the quadrupole and octupole phases represent a new mechanism for the realization of SPT phases, i.e., surface SPTs. Following this line of reasoning, our work can naturally be extended to the characterization of other 2D or 3D systems exhibiting edges/surfaces that are gapped fermionic/bosonic SPTs or $\\mathbb{Z}_{n}$ parafermion chains with, e.g., corners that harbor the corresponding topological bound states such as Majorana fermions. \n\nIn this paper, we have also shown that the topological structure of these SPT phases is hierarchical in a way that reflects the relationship between a bulk multipole moment and the lower moments realized on the boundary. For example, the subspace of occupied bands in a quadrupole has two sectors, each having nontrivial dipole topology, while the subspace of occupied bands of an octupole moment has two sectors, each having nontrivial quadrupole topology. Through this hierarchical topological classification, we were able to construct topological invariants that characterize the bulk SPT phases. One can also break the protecting symmetries to generate nonquantized multipole moments, and in such a scenario one can develop protocols by which the system is driven in adiabatic cycles so that the multipole moment changes by a quantized amount and topological pumping occurs. \n\nSuch topological pumping processes can also be used to construct topological insulators in one dimension higher where the adiabatic pumping parameter is interpreted as an additional momentum parameter. We provided an example of this in an adiabatic pumping process where the quadrupole moment changes by an integer and gives rise to an associated 3D insulator with chiral states on the hinges of the material. We believe these developments will lead to the discovery of previously unknown topological crystalline phases of matter. \n\nNote added. We have recently become aware of concomitant work on related topics in Refs. [75–77]. \n\n# ACKNOWLEDGMENTS \n\nWe thank R. Resta, C. Fang, J. Teo, and A. Soluyanov for useful discussions. W.A.B. and T.L.H. thank the US National Science Foundation under Grant No. DMR 1351895-CAR and the Sloan Foundation for support. B.A.B. acknowledges support from US Department of Energy Grant No. DE-SC0016239, NSF Early-concept Grants for Exploratory Research Award No. DMR-1643312, Simons Investigator Award No. ONR-N00014-14-1-0330, Army Research Office Multidisciplinary University Research Initiative Grant No. W911NF-12-1-0461, NSF-Material Research Science and Engineering Center Grant No. DMR-1420541, and the Packard Foundation and Schmidt Fund for Innovative Research. B.A.B. also wishes to thank Ecole Normale Superieure, UPMC Paris, and Donostia International Physics Center for their generous sabbatical hosting during some of the stages of this work. \n\n# APPENDIX A: DETAILS ON THE DEFINITIONS OF THE MULTIPOLE MOMENTS \n\nIn this Appendix, we provide some intermediate steps used in Sec. II A to define the multipole moment densities. Consider the potential (2.1). To simplify the notation, let us define the vector \n\n$$\n{\\vec{d}}={\\vec{r}}-{\\vec{R}}\n$$ \n\nwhich spans from a point in the material $\\vec{R}$ to the observation point $\\vec{r}$ . The potential is \n\n$$\n\\phi(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{\\vec{R}}\\int_{v(\\vec{R})}d^{3}\\vec{r^{\\prime}}\\frac{\\rho(\\vec{r^{\\prime}}+\\vec{R})}{\\vert\\vec{d}-\\vec{r^{\\prime}}\\vert}.\n$$ \n\nNow, let us expand the potential (A2) in powers of $1/|\\vec{d}|$ , \n\n$$\n\\phi(\\vec{r})=\\sum_{l=0}^{\\infty}\\phi^{l}(\\vec{r}),\n$$ \n\nwhere \n\n$$\n\\phi^{l}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{\\vec{R}}\\int_{v(\\vec{R})}d^{3}\\vec{r^{\\prime}}\\rho(\\vec{r^{\\prime}}+\\vec{R})\\frac{|\\vec{r^{\\prime}}|^{l}}{|\\vec{d}|^{l+1}}P_{l}\\left(\\frac{\\vec{d}}{|\\vec{d}|}\\cdot\\vec{\\frac{r^{\\prime}}{|\\vec{r^{\\prime}}|}}\\right),\n$$ \n\nand $P_{l}(x)$ are the Legendre polynomials. Here, the contributions to the total potential are, up to octupole moment, \n\n$$\n\\begin{array}{l}{\\displaystyle\\phi^{0}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{\\vec{R}}Q(\\vec{R})\\frac{1}{|\\vec{d}|},}\\\\ {\\displaystyle\\phi^{1}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{\\vec{R}}P_{i}(\\vec{R})\\frac{d_{i}}{|\\vec{d}|^{3}},}\\\\ {\\displaystyle\\phi^{2}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{\\vec{R}}Q_{i j}(\\vec{R})\\frac{3d_{i}d_{j}-|\\vec{d}|^{2}\\delta_{i j}}{2|\\vec{d}|^{5}},}\\\\ {\\displaystyle\\phi^{3}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{\\vec{R}}O_{i j k}(\\vec{R})\\frac{5d_{i}d_{j}d_{k}-3|\\vec{d}|^{2}\\delta_{i j}d_{k}}{2|\\vec{d}|^{7}},}\\end{array}\n$$ \n\nwhere \n\n$$\n\\begin{array}{l}{{\\displaystyle Q(\\vec{R})=\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R}),}}\\\\ {{\\displaystyle P_{i}(\\vec{R})=\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R})r_{i}^{\\prime},}}\\\\ {{\\displaystyle Q_{i j}(\\vec{R})=\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R})r_{i}^{\\prime}r_{j}^{\\prime},}}\\\\ {{\\displaystyle Q_{i j k}(\\vec{R})=\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R})r_{i}^{\\prime}r_{j}^{\\prime}r_{k}^{\\prime}}}\\end{array}\n$$ \n\nare the charge, dipole, quadrupole, and octupole moments at the voxel centered at $\\vec{R}$ . \n\nIf the voxels are very small compared to the material as a whole, we treat $\\vec{R}$ as a continuum variable. Now, we can define the multipole moment densities \n\n$$\n\\begin{array}{l}{{\\displaystyle\\rho(\\vec{R})=\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R}),}}\\\\ {{\\displaystyle p_{i}(\\vec{R})=\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R})r_{i}^{\\prime}},\\ ~}\\\\ {{\\displaystyle q_{i j}(\\vec{R})=\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R})r_{i}^{\\prime}r_{j}^{\\prime}},\\ ~}\\\\ {{\\displaystyle o_{i j k}(\\vec{R})=\\frac{1}{v(\\vec{R})}\\int_{v(\\vec{R})}d^{3}\\vec{r}^{\\prime}\\rho(\\vec{r}^{\\prime}+\\vec{R})r_{i}^{\\prime}r_{j}^{\\prime}r_{k}^{\\prime}}}\\end{array}\n$$ \n\nto write the potentials as \n\n$$\n\\begin{array}{l}{\\displaystyle\\phi^{0}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(\\rho(\\vec{R})\\frac{1}{|\\vec{d}|}\\biggr),}\\\\ {\\displaystyle\\phi^{1}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(p_{i}(\\vec{R})\\frac{d_{i}}{|\\vec{d}|^{3}}\\biggr),}\\\\ {\\displaystyle\\phi^{2}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(q_{i j}(\\vec{R})\\frac{3d_{i}d_{j}-|\\vec{d}|^{2}\\delta_{i j}}{2|\\vec{d}|^{5}}\\biggr),}\\\\ {\\displaystyle\\phi^{3}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(o_{i j k}(\\vec{R})\\frac{5d_{i}d_{j}d_{k}-3|\\vec{d}|^{2}d_{k}\\delta_{i j}}{2|\\vec{d}|^{7}}\\biggr),}\\end{array}\n$$ \n\nwhere $V$ is the total volume of the macroscopic material. \n\n# APPENDIX B: BOUNDARY PROPERTIES OFINSULATORS WITH MULTIPOLE MOMENT DENSITIES \n\nIn this Appendix, we derive the boundary properties due to the existence of uniform electric multipole moments. We do this for each multipole moment separately, always assuming that all lower moments vanish. \n\n# 1. Dipole moment \n\nThe potential due to a dipole moment density $p_{i}({\\vec{R}})$ is \n\n$$\n\\phi^{1}({\\vec{r}})={\\frac{1}{4\\pi\\epsilon}}\\int_{V}d^{3}{\\vec{R}}\\left(p_{i}({\\vec{R}}){\\frac{d_{i}}{d^{3}}}\\right)\n$$ \n\n[see Eq. (2.4) or (A8)]. Here, ${\\vec{d}}={\\vec{r}}-{\\vec{R}}$ , as defined in the previous Appendix. For convenience, in what follows we refer to the multipole moment densities without their arguments, i.e., we will simply write $p_{i}$ for $p_{i}({\\vec{R}})$ , etc. Now, we use \n\n$$\n\\frac{\\partial}{\\partial R_{i}}\\frac{1}{d}\\equiv\\partial_{i}\\frac{1}{d}=\\frac{d_{i}}{d^{3}}\n$$ \n\nto write the potential due to a dipole moment per unit volume $p_{i}$ as \n\n$$\n\\phi^{1}({\\vec{r}})={\\frac{1}{4\\pi\\epsilon}}\\int_{V}d^{3}{\\vec{R}}\\biggl(p_{i}\\partial_{i}{\\frac{1}{d}}\\biggr).\n$$ \n\nThe expression in parentheses can be decomposed as \n\n$$\np_{i}\\left(\\partial_{i}\\frac{1}{d}\\right)=\\partial_{i}\\left(p_{i}\\frac{1}{d}\\right)-(\\partial_{i}p_{i})\\frac{1}{d},\n$$ \n\nwhere $\\partial_{i}$ in $\\partial_{i}p_{i}$ acts on the arguments of $p_{i}({\\vec{R}})$ ; furthermore, since summation is implied, $\\partial_{i}p_{i}$ is just the divergence of $\\vec{p}(\\vec{R})$ : $\\vec{\\nabla}\\cdot\\vec{p}(\\vec{R})$ . We use this expression to write the potential as \n\n$$\n\\phi^{1}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl[\\partial_{i}\\biggl(p_{i}\\frac{1}{d}\\biggr)-(\\partial_{i}p_{i})\\frac{1}{d}\\biggr].\n$$ \n\nUsing the divergence theorem on the first term we have \n\n$$\n\\phi^{1}({\\vec{r}})={\\frac{1}{4\\pi\\epsilon}}\\oint_{\\partial V}d^{2}{\\vec{R}}\\biggl(n_{i}p_{i}{\\frac{1}{d}}\\biggr)+{\\frac{1}{4\\pi\\epsilon}}\\int_{V}d^{3}{\\vec{R}}\\biggl(-\\partial_{i}p_{i}{\\frac{1}{d}}\\biggr),\n$$ \n\nwhere $\\partial V$ is the boundary of the material. To aid our understanding, we rewrite this expression in terms of the original variables \n\n$$\n\\begin{array}{l}{{\\displaystyle\\phi^{1}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\oint_{\\partial V}d^{2}\\vec{R}\\biggl(n_{i}p_{i}\\frac{1}{|\\vec{r}-\\vec{R}|}\\biggr)}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(-\\partial_{i}p_{i}\\frac{1}{|\\vec{r}-\\vec{R}|}\\biggr).}}\\end{array}\n$$ \n\nSince both terms scale as $1/|\\vec{r}-\\vec{R}|$ , where $|\\vec{r}-\\vec{R}|$ is the distance from a point in the material $\\vec{R}$ to the observation point $\\vec{r}$ , we can define the charge densities of Eq. (2.9). \n\n# 2. Quadrupole moment \n\nThe potential due to a quadrupole moment per unit volume $q_{i j}$ [see Eqs. (2.4) or (A8)] is \n\n$$\n\\phi^{2}({\\vec{r}})={\\frac{1}{4\\pi\\epsilon}}\\int_{V}d^{3}{\\vec{R}}\\biggl(q_{i j}{\\frac{3d_{i}d_{j}-d^{2}\\delta_{i j}}{2d^{5}}}\\biggr),\n$$ \n\n![](images/e989662c10ebb0c16ef27106e1bb0c570debbb51d58f57a314bca5a8d2d2320b.jpg) \nFIG. 46. Boundary segmentation for the calculation of quadrupole signatures. (a) Separation of two-dimensional boundary into its flat faces. (b) Separation of a 1D boundary into its straight lines. \n\nwhere ${\\vec{d}}={\\vec{r}}-{\\vec{R}}$ , as defined in the previous appendix. We make use of \n\n$$\n\\partial_{j}\\partial_{i}\\frac{1}{d}=\\frac{3d_{i}d_{j}-d^{2}\\delta_{i j}}{d^{5}}\n$$ \n\nto write the potential as \n\n$$\n\\phi^{2}({\\vec{r}})={\\frac{1}{4\\pi\\epsilon}}\\int_{V}d^{3}{\\vec{R}}\\bigg({\\frac{1}{2}}q_{i j}\\partial_{i}\\partial_{j}{\\frac{1}{d}}\\bigg).\n$$ \n\nLet us rearrange this expression. We use \n\n$$\n\\begin{array}{c}{{q_{i j}\\partial_{i}\\partial_{j}\\displaystyle\\frac1d=\\partial_{i}\\bigg(q_{i j}\\partial_{j}\\displaystyle\\frac1d\\bigg)-(\\partial_{i}q_{i j})\\partial_{i}\\displaystyle\\frac1d}}\\\\ {{=\\partial_{i}\\partial_{j}\\bigg(q_{i j}\\displaystyle\\frac1d\\bigg)-2\\partial_{i}\\bigg[(\\partial_{j}q_{i j})\\displaystyle\\frac1d\\bigg]+(\\partial_{i}\\partial_{j}q_{i j})\\displaystyle\\frac1d}}\\end{array}\n$$ \n\nin the previous expression to find \n\n$$\n\\begin{array}{c}{{\\phi^{2}(\\vec{r})=\\displaystyle\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\Bigg\\{\\frac{1}{2}\\partial_{i}\\partial_{j}\\left(q_{i j}\\frac{1}{d}\\right)}}\\\\ {{-\\partial_{i}\\left[\\left(\\partial_{j}q_{i j}\\right)\\displaystyle\\frac{1}{d}\\right]+\\left(\\frac{1}{2}\\partial_{i}\\partial_{j}q_{i j}\\right)\\displaystyle\\frac{1}{d}\\Bigg\\}.}}\\end{array}\n$$ \n\nApplying the divergence theorem on the first two terms we have \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\phi^{2}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\oint_{\\partial V}d^{2}\\vec{R}\\biggl[\\frac{1}{2}n_{i}\\partial_{j}\\biggl(q_{i j}\\frac{1}{d}\\biggr)\\biggr]}}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\oint_{\\partial V}d^{2}\\vec{R}(-n_{i}\\partial_{j}q_{i j})\\frac{1}{d}}}\\\\ {{\\displaystyle~+\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(\\frac{1}{2}\\partial_{j}\\partial_{i}q_{i j}\\biggr)\\frac{1}{d}.}}\\end{array}\n$$ \n\nNow, let us specialize to a simple geometry. Consider a cube-shaped material where the boundary consists of flat faces. At the (sharp) intersection of different faces, the normal vector is discontinuous. To avoid this complication, we can break the integral over the entire boundary up into a sum over the faces that compose it, as seen in Fig. 46(a): \n\n$$\n\\oint_{\\partial V}d^{2}\\vec{R}\\biggl[\\frac{1}{2}n_{i}\\partial_{j}\\left(q_{j i}\\frac{1}{d}\\right)\\biggr]=\\sum_{a}\\int_{S_{a}}d^{2}\\vec{R}\\biggl[\\frac{1}{2}n_{i}^{(a)}\\partial_{j}\\left(q_{j i}\\frac{1}{d}\\right)\\biggr].\n$$ \n\nFor the sake of clarity, we have explicitly written the sum over the flat faces $S_{a}$ with normal vector $\\hat{n}^{(a)}$ . Notice that, in this construction, $\\hat{n}^{(a)}$ has components $n_{i}^{(a)}=s_{a}\\delta_{i}^{|a|}$ , where $s_{a=\\pm}=$ \n\n$\\pm1$ encodes the direction. Now, we apply the divergence theorem over the open surfaces $S_{a}$ . We thus have \n\n$$\n\\oint_{\\partial V}d^{2}\\vec{R}\\biggl[\\frac{1}{2}n_{i}\\partial_{j}\\biggl(q_{j i}\\frac{1}{d}\\biggr)\\biggr]=\\sum_{a,b}\\int_{L_{a b}}d\\vec{R}\\biggl(\\frac{1}{2}n_{j}^{(a)}n_{i}^{(b)}q_{j i}\\biggr)\\frac{1}{d},\n$$ \n\nwhere $L_{a b}$ is the one-dimensional boundary of $S_{a}$ when it meets $S_{b}$ [see Fig. 46(b)]. Joining the pieces together, the contributions to the potential from a quadrupole moment are \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\phi^{2}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\sum_{a,b}\\int_{L_{a b}}d\\vec{R}\\biggl(\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}q_{i j}\\biggr)\\frac{1}{d}}}}\\\\ {{\\displaystyle{+\\frac{1}{4\\pi\\epsilon}\\sum_{a}\\int_{S_{a}}d^{2}\\vec{R}\\bigl(-\\partial_{j}n_{i}^{(a)}q_{i j}\\bigr)\\frac{1}{d}}}}\\\\ {{\\displaystyle{+\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(\\frac{1}{2}\\partial_{j}\\partial_{i}q_{i j}\\biggr)\\frac{1}{d}}.}}\\end{array}\n$$ \n\nSince all the potentials scale as $1/d$ , where ${\\vec{d}}={\\vec{r}}-{\\vec{R}}$ is the distance from the point in the material to the observation point, all the expressions in parentheses can each be interpreted as charge densities, thus, we define the charge densities of Eq. (2.11). \n\n# 3. Octupole moment \n\nMaking the change of variables ${\\vec{d}}={\\vec{r}}-{\\vec{R}}$ , as in the previous sections, the potential due to an octupole moment per unit volume $o_{i j k}$ from Eqs. (2.4) or (A8) is \n\n$$\n\\phi^{3}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(o_{i j k}\\frac{5d_{i}d_{j}d_{k}-3d^{2}\\delta_{i j}d_{k}}{2d^{7}}\\biggr).\n$$ \n\nUsing the expression \n\n$$\n\\partial_{k}\\partial_{j}\\partial_{i}\\frac{1}{d}=3\\frac{5d_{i}d_{j}d_{k}-3d^{2}\\delta_{i j}d_{k}}{d^{7}},\n$$ \n\nwe write the potential as \n\n$$\n\\phi^{3}({\\vec{r}})={\\frac{1}{4\\pi\\epsilon}}\\int_{V}d^{3}{\\vec{R}}\\biggl({\\frac{1}{6}}o_{i j k}\\partial_{i}\\partial_{j}\\partial_{k}{\\frac{1}{d}}\\biggr).\n$$ \n\nTo find the potential exclusively as arising from charge distributions, we can proceed as before by partial integration. The result is \n\n$$\n\\begin{array}{l}{\\displaystyle{\\phi^{3}(\\vec{r})=\\frac{1}{4\\pi\\epsilon}\\int_{V}d^{3}\\vec{R}\\biggl(-\\frac{1}{6}\\partial_{i}\\partial_{j}\\partial_{k}\\omega_{i j k}\\biggr)\\frac{1}{d}}}\\\\ {\\displaystyle{+\\frac{1}{4\\pi\\epsilon}\\sum_{a}\\int_{S_{\\epsilon}}d^{2}\\vec{R}\\biggl(\\frac{1}{2}n_{i}^{(a)}\\partial_{j}\\partial_{k}\\omega_{i j k}\\biggr)\\frac{1}{d}}}\\\\ {\\displaystyle{+\\frac{1}{4\\pi\\epsilon}\\sum_{a,b}\\int_{L_{a b}}d\\vec{R}\\biggl(-\\frac{1}{2}n_{i}^{(a)}n_{j}^{(b)}\\partial_{k}\\omega_{i j k}\\biggr)\\frac{1}{d}}}\\\\ {\\displaystyle{+\\frac{1}{4\\pi\\epsilon}\\sum_{a,b,c}\\frac{1}{6}n_{i}^{(a)}n_{j}^{(b)}n_{k}^{(c)}\\omega_{i j k}\\frac{1}{r},}}\\end{array}\n$$ \n\nfrom which we read off the charge densities of Eq. (2.16). \n\n# APPENDIX C: WILSON LINE IN THETHERMODYNAMIC LIMIT \n\nConsider the Wilson-line element $[G_{k}]^{m n}=\\langle u_{k+\\Delta_{k}}^{m}|u_{k}^{n}\\rangle$ , where $\\Delta_{k}=(k_{f}-k_{i})/N$ . For large values of $N$ , we expand $\\langle u_{{k+}\\Delta_{k}}^{m}|=\\langle u_{k}^{m}|+\\Delta_{k}\\partial_{k}\\langle u_{k}^{m}|+\\cdot\\cdot\\cdot$ , and write the Wilson-line element as \n\n$$\n[G_{k}]^{m n}=\\left\\langle u_{k}^{m}\\right|u_{k}^{n}\\right\\rangle+\\Delta_{k}\\bigl\\langle\\partial_{k}u_{k}^{m}\\bigr|u_{k}^{n}\\bigr\\rangle+\\cdot\\cdot\\cdot.\n$$ \n\nNow, since $\\langle u_{k}^{m}|u_{k}^{n}\\rangle=\\delta^{m n}$ , we have that $\\begin{array}{r}{\\langle\\partial_{k}u_{k}^{m}|u_{k}^{n}\\rangle=}\\end{array}$ $-\\langle u_{k}^{m}|\\partial_{k}u_{k}^{n}\\rangle$ . Using this in our expansion while keeping only terms linear in $\\Delta_{k}$ , we have \n\n$$\n[G_{k}]^{m n}=\\delta^{m n}-\\Delta_{k}\\big\\langle u_{k}^{m}\\big|\\partial_{k}u_{k}^{n}\\big\\rangle=\\delta^{m n}-i\\Delta_{k}[\\mathcal{A}_{k}]^{m n},\n$$ \n\nwhere we have defined the Berry connection \n\n$$\n[\\mathcal{A}_{k}]^{m n}=-i\\big\\langle u_{k}^{m}\\big|\\partial_{k}\\big|u_{k}^{n}\\big\\rangle\n$$ \n\nwhich is a purely real quantity. Now, suppose that we evolve the Wilson loop from $k_{i}$ to $k_{f}$ in the thermodynamic limit $N\\rightarrow\\infty$ . This is achieved by the (path-ordered) matrix multiplication \n\n$$\n\\mathcal{W}_{k_{f}\\leftarrow k_{i}}=\\operatorname*{lim}_{N\\rightarrow\\infty}\\prod_{n=1}^{N}[I-i\\Delta_{k}\\mathcal{A}_{k+n\\Delta_{k}}]=\\exp\\biggl[-i\\int_{k_{i}}^{k_{f}}\\mathcal{A}_{k}d k\\biggr].\n$$ \n\n# APPENDIX D: SYMMETRY CONSTRAINTS ON WILSON LOOPS \n\nIn this Appendix, we derive the relations between Wilson loops in the presence of reflection, inversion, and $C_{4}$ symmetries. An initial study that determined relations between Wilson loops can be found in Ref. [50]. In this Appendix, we expand on that analysis. We will see that some of these relations lead to a quantization of the Wannier centers, the bulk polarization, or the Wannier-sector polarizations. Additionally, we also provide relations that impose constraints on these observables in the presence of time-reversal, chargeconjugation, and chiral symmetries. Insulators with a lattice symmetry obey \n\n$$\ng_{\\bf k}h_{\\bf k}g_{\\bf k}^{-1}=h_{D_{g}\\bf k},\n$$ \n\nwhere $g_{\\mathbf{k}}$ is the unitary operator \n\n$$\ng_{\\bf k}=e^{-i(D_{g}{\\bf k})\\cdot\\delta}U_{g}.\n$$ \n\n$U_{g}$ is an $N_{\\mathrm{orb}}\\times N_{\\mathrm{orb}}$ matrix that acts on the internal degrees of freedom of the unit cell, and $D_{g}$ is an operator in momentum space sending $\\mathbf{k}\\to D_{g}\\mathbf{k}$ . In real space, on the other hand, we have $\\mathbf{r}\\rightarrow D_{g}\\mathbf{r}+\\delta$ , where $\\delta=\\mathbf{0}$ in the case of symmorphic symmetries, or takes a fractional value (in unit-cell units) in the case of nonsymmorphic symmetries. The state $g_{\\bf k}|u_{\\bf k}^{n}\\rangle$ is an eigenstate of $h_{D_{g}\\mathbf{k}}$ with energy $\\epsilon_{n,\\mathbf{k}}$ , as can be seen as follows: \n\n$$\nh_{D_{g}\\mathbf{k}}g_{\\mathbf{k}}\\lvert u_{\\mathbf{k}}^{n}\\rvert=g_{\\mathbf{k}}h_{\\mathbf{k}}\\lvert u_{\\mathbf{k}}^{n}\\rvert=\\epsilon_{n,\\mathbf{k}}g_{\\mathbf{k}}\\lvert u_{\\mathbf{k}}^{n}\\rvert.\n$$ \n\nTherefore, one can expand $g_{\\bf k}|u_{\\bf k}^{n}\\rangle$ in terms of the basis of $h_{D_{g}\\mathbf{k}}$ : \n\n$$\ng_{\\mathbf{k}}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle=\\big|u_{D_{g}\\mathbf{k}}^{m}\\big\\rangle\\big\\langle u_{D_{g}\\mathbf{k}}^{m}\\big|g_{\\mathbf{k}}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle=\\big|u_{D_{g}\\mathbf{k}}^{m}\\big\\rangle B_{g,\\mathbf{k}}^{m n},\n$$ \n\nwhere, from now on, summation is implied for repeated band indices only over occupied bands; \n\n$$\nB_{g,\\mathbf{k}}^{m n}=\\big\\langle u_{D_{g}\\mathbf{k}}^{m}\\big|g_{\\mathbf{k}}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle\n$$ \n\nis the unitary sewing matrix that connects states at $\\mathbf{k}$ with those at $D_{g}\\mathbf{k}$ which have the same energy. This matrix obeys \n\n$$\nB_{g,\\mathbf{k}+\\mathbf{G}}^{m n}=B_{g,\\mathbf{k}}^{m n}\n$$ \n\nas can be shown as follows: \n\n$$\n\\begin{array}{r l}&{B_{g,{\\mathbf k}+{\\mathbf G}}^{m n}=\\left\\langle u_{D_{g}{\\mathbf k}}^{m}\\right\\vert V(D_{g}{\\mathbf G})g_{{\\mathbf k}+{\\mathbf G}}V(-{\\mathbf G})\\big\\vert u_{{\\mathbf k}}^{n}\\right\\rangle}\\\\ &{\\qquad=\\left\\langle u_{D_{g}{\\mathbf k}}^{m}\\right\\vert V(D_{g}{\\mathbf G})V(-D_{g}{\\mathbf G})e^{i(D_{g}{\\mathbf G}).\\delta}g_{{\\mathbf k}+{\\mathbf G}}\\big\\vert u_{{\\mathbf k}}^{n}\\right\\rangle}\\\\ &{\\qquad=\\left\\langle u_{D_{g}{\\mathbf k}}^{m}\\right\\vert e^{i(D_{g}{\\mathbf G}).\\delta}g_{{\\mathbf k}+{\\mathbf G}}\\big\\vert u_{{\\mathbf k}}^{n}\\right\\rangle}\\\\ &{\\qquad=\\left\\langle u_{D_{g}{\\mathbf k}}^{m}\\right\\vert g_{{\\mathbf k}}\\big\\vert u_{{\\mathbf k}}^{n}\\right\\rangle}\\\\ &{\\qquad=B_{g,{\\mathbf k}}^{m n},}\\end{array}\n$$ \n\nwhere $V(\\mathbf{k})$ is defined in Eq. (3.10), and we have used Eq. (3.12) as well as the relation \n\n$$\ng_{\\bf k}V({\\bf G})=e^{-i(D_{g}{\\bf k}).\\delta}V(D_{g}{\\bf G})g_{\\bf k}.\n$$ \n\nUsing the expansion in Eq. (D4), we can write \n\n$$\n\\big|u_{\\mathbf{k}}^{n}\\big\\rangle=g_{\\mathbf{k}}^{\\dagger}\\big|u_{D_{g}\\mathbf{k}}^{m}\\big\\rangle B_{g,\\mathbf{k}}^{m n}.\n$$ \n\nSo, an element of a Wilson line from $\\mathbf{k_{1}}$ to $\\mathbf{k}_{2}$ is equal to \n\n$$\n\\begin{array}{r l}&{\\mathcal{W}_{{\\mathbf{k}_{2}}\\leftarrow{\\mathbf{k}_{1}}}^{m n}=\\left\\langle u_{{\\mathbf{k}_{2}}}^{m}\\middle\\vert u_{{\\mathbf{k}_{1}}}^{n}\\right\\rangle}\\\\ &{\\qquad=B_{g,{\\mathbf{k}_{2}}}^{\\dagger m r}\\middle\\langle u_{D_{g}{\\mathbf{k}_{2}}}^{r}\\middle\\vert g_{{\\mathbf{k}}}g_{{\\mathbf{k}}}^{\\dagger}\\middle\\vert u_{D_{g}{\\mathbf{k}_{1}}}^{s}\\right\\rangle B_{g,{\\mathbf{k}_{1}}}^{s n}}\\\\ &{\\qquad=B_{g,{\\mathbf{k}_{2}}}^{\\dagger m r}\\mathcal{W}_{D_{g}{\\mathbf{k}_{2}}\\leftarrow D_{g}{\\mathbf{k}_{1}}}^{r s}B_{g,{\\mathbf{k}_{1}}}^{s n}.}\\end{array}\n$$ \n\nReordering this, we have \n\n$$\nB_{g,\\mathbf{k}_{2}}\\mathcal{W}_{\\mathbf{k}_{2}\\leftarrow\\mathbf{k}_{1}}B_{g,\\mathbf{k_{1}}}^{\\dagger}=\\mathcal{W}_{D_{g}\\mathbf{k}_{2}\\leftarrow D_{g}\\mathbf{k_{1}}}.\n$$ \n\nIn particular, for a Wilson loop at base point $\\mathbf{k}$ we have \n\n$$\n\\boxed{B_{g,\\mathbf{k}}\\mathcal{W}_{\\mathcal{C},\\mathbf{k}}B_{g,\\mathbf{k}}^{\\dagger}=\\mathcal{W}_{D_{g}\\mathcal{C},D_{g}\\mathbf{k}}},\n$$ \n\nwhere, in the Wilson loop $\\mathcal{W}_{\\mathbf{\\mathcal{C}},\\mathbf{k}}$ , the first subindex $\\mathcal{C}$ is the contour along which the Wilson loop is performed, and the second subindex $\\mathbf{k}$ is the starting point, or “base point,” of the Wilson loop. To simplify notation, from now on we will refer to Wilson loops along the contour $\\mathcal{C}=(k_{x},k_{y})\\rightarrow$ $(k_{x}+2\\pi,k_{y})$ along increasing (decreasing) values of $k_{x}$ as $\\mathcal{W}_{x,\\mathbf{k}}\\left(\\mathcal{W}_{-x,\\mathbf{k}}\\right)$ , where ${\\bf k}=(k_{x},k_{y})$ is the base point of the loop. Similarly, for the path $\\mathcal{C}=(\\dot{k}_{x},k_{y})\\rightarrow(k_{x},k_{y}+2\\pi)$ along increasing (decreasing) values of $k_{y}$ , we will denote the Wilson loops as $\\mathcal{W}_{y,\\mathbf{k}}\\ (\\mathcal{W}_{-y,\\mathbf{k}})$ . Figure 47 shows how these Wilson loops transform under the four spatial symmetries we will consider here: reflection in $x$ , reflection in $y$ , inversion, and $C_{4}$ . In what follows, we study the constraints placed by these symmetries on the Wilson loops over the occupied energy bands, as well as on the Wilson loops over the Wannier sectors. \n\n# 1. Constraints due to reflection symmetry along $\\boldsymbol{x}$ \n\nWe consider the constraints that reflection symmetry $M_{x}$ : $x\\to-x$ imposes on the Wilson loops $\\mathcal{W}_{x,{\\bf k}}$ , as well as on the nested Wilson loops W˜ νxk 1 \n\n# a. On the Wilson loop of the occupied energy bands \n\nUnder reflection symmetry along $x$ , the eigenvalues of Wilson loops along $x$ are constrained to be $+1,-1$ , or to \n\n![](images/afb20b8e319e3c22c940c34d2ec28344bbcf27e0f86fb890c21838a5fb70f177.jpg) \nFIG. 47. Relation between Wilson loops along $x$ at base point $\\mathbf{k}$ after (a) reflection along $x$ , (b) reflection along $y$ , (c) inversion, or (d) $\\pi/2$ rotation. \n\ncome in complex-conjugate pairs $e^{\\pm i2\\pi\\nu}$ , as we will see in this section. Consider a system with reflection symmetry along $x$ : \n\n$$\n\\hat{M}_{x}h_{\\mathbf{k}}\\hat{M}_{x}^{-1}=h_{M_{x}\\mathbf{k}},\n$$ \n\nwhere $M_{x}\\mathbf{k}=M_{x}(k_{x},k_{y})=(-k_{x},k_{y})$ . This symmetry allows us to write the expansion \n\n$$\n\\hat{M}_{x}\\left|u_{\\mathbf{k}}^{n}\\right\\rangle=\\left|u_{M_{x}\\mathbf{k}}^{m}\\right\\rangle B_{M_{x},\\mathbf{k}}^{m n},\n$$ \n\nwhere \n\n$$\nB_{M_{x},\\mathbf k}^{m n}=\\big\\langle u_{M_{x}\\mathbf k}^{m}\\big|\\hat{M}_{x}\\big|u_{\\mathbf k}^{n}\\big\\rangle\n$$ \n\nis the unitary sewing matrix $\\langle B^{\\dagger}B=B B^{\\dagger}=1\\rangle$ ), which connects states at $\\mathbf{k}$ with states at $M_{x}\\mathbf{k}$ having the same energy. In particular, $B_{M_{x},{\\bf k}}^{m n}\\neq0$ only if $\\epsilon_{m,M_{x}\\mathbf{k}}=\\epsilon_{n,\\mathbf{k}}$ . \n\nThe relation between Wilson loops in Eq. (D10) for this symmetry is \n\n$$\nB_{M_{x},\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}B_{M_{x},\\mathbf{k}}^{\\dagger}=\\mathcal{W}_{-x,M_{x}\\mathbf{k}}=\\mathcal{W}_{x,M_{x}\\mathbf{k}}^{\\dagger}.\n$$ \n\nAn illustration of this relation is shown in Fig. 47(a). Thus, the Wilson loop at $\\mathbf{k}$ is equivalent (up to a unitary transformation) to the Hermitian conjugate of the Wilson loop at $M_{x}\\mathbf{k}$ . Since the eigenvalues of the Wilson loop along $x$ are $k_{x}$ independent, this directly imposes a restriction on the allowed Wannier centers at each $k_{y}$ , namely, the set of Wilson-loop eigenvalues must obey \n\n$$\n\\left\\{e^{i2\\pi\\nu_{x}^{i}(k_{y})}\\right\\}\\overset{M_{x}}{=}\\left\\{e^{-i2\\pi\\nu_{x}^{i}(k_{y})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{x}^{i}(k_{y})\\right\\}\\overset{M_{x}}{=}\\left\\{-\\nu_{x}^{i}(k_{y})\\right\\}\\mathrm{~mod~}1.\n$$ \n\nThus, at each value of $k_{y}$ the Wannier centers $\\nu_{x}(k_{y})$ are forced to be 0 (centered at unit cell), $\\frac{1}{2}$ (centered in-between unit cells), or to come in pairs $(-\\nu,\\nu)$ (pairs which are equally displaced from the unit cell but at opposite sides of it). From this it follows that, in order to have a gapped Wannier spectrum, we must have an even number $N_{\\mathrm{occ}}$ of occupied bands, for if we have an odd $N_{\\mathrm{occ}}$ , at least one of the Wannier centers must have the value $\\nu=0$ or $\\frac{1}{2}$ , equivalent to having at least one mid-gap state in the Wannier spectrum. Equation (D16) also implies that, under reflection symmetry $M_{x}$ along $x$ , the polarization \n\n$$\np_{x}(k_{y})=\\sum_{j=1}^{N_{\\mathrm{occ}}}\\nu^{j}(k_{y})\\bmod1\n$$ \n\nobeys \n\n$$\np_{x}(k_{y})\\overset{M_{x}}{=}-p_{x}(k_{y})\\bmod1,\n$$ \n\ni.e., \n\n$$\np_{x}(k_{y})\\overset{M_{x}}{=}0\\mathrm{or}1/2\n$$ \n\nfor $k_{y}\\in[-\\pi,\\pi)$ . For gapped systems, the Wannier spectrum is not discontinuous. In this case, the above restriction on $p_{x}(k_{y})$ implies that the total polarization along $x$ , \n\n$$\np_{x}=\\frac{1}{N_{y}}\\sum_{k_{y}}p_{x}(k_{y}),\n$$ \n\nobeys \n\n$$\np_{x}\\overset{M_{x}}{=}-p_{x}\\bmod1,\n$$ \n\ni.e., the total polarization is also quantized, \n\n$$\np_{x}\\ {\\stackrel{M_{x}}{=}}\\ 0\\ {\\mathrm{or}}\\ 1/2.\n$$ \n\n# b. On the nested Wilson loop over Wannier sectors \n\nIn Sec. VI we saw that the topological quadrupole is represented by the topology of the Wannier-sector polarizations (6.16). These are subspaces within the subspace of occupied bands that belong to the same subset of Wannier bands. In this section we impose reflection symmetry on the Hamiltonian to see how the Wannier-sector polarizations are affected. For that purpose, we first focus on the Wilson-loop eigenfunctions \n\n$$\n\\mathcal{W}_{x,\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle=e^{i2\\pi\\nu_{x}^{i}(k_{y})}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle.\n$$ \n\nUsing Eq. (D14), we have that \n\n$$\n\\mathcal{W}_{x,M_{x}\\mathbf{k}}^{\\dagger}B_{M_{x},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big|=B_{M_{x},\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big|=e^{i2\\pi\\nu_{x}^{i}(k_{y})}B_{M_{x},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big|.\n$$ \n\n$B_{M_{x},\\mathbf{k}}|\\nu_{x,\\mathbf{k}}^{i}\\rangle$ is hence an eigenfunction of $\\mathcal{W}_{x,M_{x}\\mathbf{k}}$ with eigenvalue $e^{-i2\\pi\\nu_{x}^{i}(k_{y})}$ . We now expand this function as \n\n$$\nB_{M_{x},\\mathbf{k}}|\\nu_{x,\\mathbf{k}}^{i}\\rangle=\\big|\\nu_{x,M_{x}\\mathbf{k}}^{j}\\big\\rangle\\alpha_{M_{x},\\mathbf{k}}^{j i},\n$$ \n\nwhere \n\n$$\n\\alpha_{M_{x},\\mathbf{k}}^{j i}=\\big\\langle\\nu_{x,M_{x}\\mathbf{k}}^{j}\\big|B_{M_{x},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle\n$$ \n\nis a unitary sewing matrix that connects Wilson-loop eigenstates at base points $\\mathbf{k}$ and $M_{x}\\mathbf{k}$ having opposite Wilson-loop eigenvalues. If $\\alpha_{M_{x},{\\bf k}}^{j i}\\neq0$ , we require that $-\\nu_{x}^{j}(k_{y})=\\nu_{x}^{i}(k_{y})$ . \n\nThis implies that $\\alpha_{M_{x},{\\bf k}}$ is restricted to be block diagonal in the $\\upnu=0$ and $\\frac{1}{2}$ sectors and off diagonal between the sectors $\\nu,-\\nu$ . \n\nNow, let us act with the reflection operator on $|w_{x,\\mathbf{k}}^{j}\\rangle$ , i.e., the states representing the Wannier basis as defined in Eq. (6.5), \n\n$$\n\\begin{array}{r l}&{\\hat{M}_{x}\\big|w_{x,\\mathbf{k}}^{j}\\big\\rangle=\\hat{M}_{x}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle\\big[\\nu_{x,\\mathbf{k}}^{j}\\big]^{n}}\\\\ &{\\qquad=\\big|u_{\\mathcal{M}_{\\mathrm{A}}\\mathbf{k}}^{m}\\big\\rangle\\big\\langle u_{\\mathcal{M}_{\\mathbf{x}}\\mathbf{k}}^{m}\\big|\\hat{M}_{x}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle\\big[\\nu_{x,\\mathbf{k}}^{j}\\big]^{n}}\\\\ &{\\qquad=\\big|u_{\\mathcal{M}_{\\mathbf{x}}\\mathbf{k}}^{m}\\big\\rangle B_{M_{x,\\mathbf{k}}}^{m n}\\big[\\nu_{x,\\mathbf{k}}^{j}\\big]^{n}}\\\\ &{\\qquad=\\big|u_{\\mathcal{M}_{\\mathbf{x}}\\mathbf{k}}^{m}\\big\\rangle\\big[\\nu_{x,\\mathcal{M}_{\\mathbf{x}}\\mathbf{k}}^{i}\\big]^{m}\\alpha_{M_{x,\\mathbf{k}}}^{i j}}\\\\ &{\\qquad=\\big|w_{x,\\mathcal{M}_{\\mathbf{x}}\\mathbf{k}}^{i}\\big\\rangle\\alpha_{M_{x,\\mathbf{k}}}^{i j}.}\\end{array}\n$$ \n\nFrom this relation we can write \n\n$$\n\\begin{array}{r l}&{\\big|w_{x,\\mathbf{k}}^{j}\\big|=\\hat{M}_{x}^{\\dagger}\\big|w_{x,{M_{x}\\mathbf{k}}}^{i}\\big|\\alpha_{M_{x},\\mathbf{k}}^{i j},}\\\\ &{\\big\\langle w_{x,\\mathbf{k}}^{j}\\big|=\\big[\\alpha_{M_{x},\\mathbf{k}}^{\\dagger}\\big]^{j i}\\big\\langle w_{x,{M_{x}\\mathbf{k}}}^{i}\\big|\\hat{M}_{x},}\\end{array}\n$$ \n\nwhere $\\nu_{x}^{i}(k_{y})=-\\nu_{x}^{j}(k_{y})$ for nonzero $\\alpha_{M_{x},\\mathbf{k}}^{j i}$ . The Wilson-line elements for the $|w_{x,\\mathbf{k}}^{j}\\rangle$ holonomy are related by \n\n$$\n\\begin{array}{r l}&{\\bigl[\\mathcal{\\tilde{W}}_{\\mathbf{k}_{2}\\leftarrow\\mathbf{k}_{1}}^{\\nu_{x}}\\bigr]^{i j}=\\bigl\\langle w_{x,\\mathbf{k}_{2}}^{i}\\big\\vert w_{x,\\mathbf{k}_{1}}^{j}\\bigr\\rangle}\\\\ &{\\qquad=\\bigl[\\alpha_{M_{x},\\mathbf{k}_{2}}^{\\dagger}\\bigr]^{i i^{\\prime}}\\bigl\\langle w_{x,M_{x}\\mathbf{k}_{2}}^{i^{\\prime}}\\big\\vert w_{x,M_{x}\\mathbf{k}_{1}}^{j^{\\prime}}\\bigr\\rangle\\alpha_{M_{x},\\mathbf{k}_{1}}^{j^{\\prime}j}}\\\\ &{\\qquad=\\bigl[\\alpha_{M_{x},\\mathbf{k}_{2}}^{\\dagger}\\bigr]^{i i^{\\prime}}\\bigl[\\mathcal{\\tilde{W}}_{M_{x}\\mathbf{k}_{2}\\leftarrow M_{x}\\mathbf{k}_{1}}^{\\nu_{x}^{\\prime}}\\bigr]^{i^{\\prime}j^{\\prime}}\\alpha_{M_{x},\\mathbf{k}_{1}}^{j^{\\prime}j}.}\\end{array}\n$$ \n\nIn particular, for the nested Wilson loops along $y$ in the basis $|w_{x}^{j}\\rangle$ , we have \n\n$$\n\\begin{array}{r}{\\big[\\tilde{\\mathcal{W}}_{y,{\\bf k}}^{\\nu_{x}}\\big]^{i j}=\\big[\\alpha_{M_{x},{\\bf k}}^{\\dagger}\\big]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{y,M_{x}{\\bf k}}^{\\nu_{x}^{\\prime}}\\big]^{i^{\\prime}j^{\\prime}}\\big[\\alpha_{M_{x},{\\bf k}}\\big]^{j^{\\prime}j}.}\\end{array}\n$$ \n\nEquation (D28) implies two things: first, since $\\nu_{x}^{j}(k_{y})=$ $-\\nu_{x}^{i}(k_{y})$ for nonzero $\\alpha_{M_{x},\\mathbf{k}}^{j i}$ , this expression tells us that Wilson loops along $y$ at base point $\\mathbf{k}$ , over Wannier sectors $\\nu_{x}=0$ or $\\frac{\\mathrm{i}}{2}$ , are equivalent (up to unitary transformations) to Wilson loops along $y$ over the same Wannier sector at base point $M_{x}\\mathbf{k}$ . Second, suppose that we have gapped Wannier bands $\\{\\nu_{x}(k_{y}),-\\nu_{x}(k_{y})\\}$ across the entire range $k_{y}\\in(-\\pi,\\pi]$ . Then, Eq. (D28) tells us that if we calculate the Wilson loop along $y$ over the Wannier sector $\\nu_{x}(k_{y})$ at base point $\\mathbf{k}$ , this Wilson loop is equivalent (up to a unitary transformation) to the Wilson loop along $y$ at base point $M_{x}\\mathbf{k}$ over the sector $-\\nu_{x}(k_{y})$ . Thus, for the eigenvalues $\\exp[i2\\pi\\nu_{y}^{\\nu_{x},j}(k_{x})]$ of the Wilson loop $\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ over the Wannier sector $\\nu_{x}$ , $M_{x}$ implies that \n\n$$\n\\left\\{e^{i2\\pi\\nu_{y}^{\\nu_{x},j}(k_{x})}\\right\\}\\overset{M_{x}}{=}\\left\\{e^{i2\\pi\\nu_{y}^{-\\nu_{x},j}(-k_{x})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{y}^{\\nu_{x},j}(k_{x})\\right\\}\\overset{M_{x}}{=}\\left\\{\\nu_{y}^{-\\nu_{x},j}(-k_{x})\\right\\}\\mathrm{~mod~}1,\n$$ \n\nwhere $j\\in1\\ldots N_{\\nu_{x}}$ labels the eigenvalue, and $N_{\\nu_{x}}$ is the number of Wannier bands in the sector $\\nu_{x}$ . The Wannier-sector polarization can be written as \n\n$$\np_{y}^{\\nu_{x}}=\\frac{1}{N_{x}}\\sum_{k_{x}}\\sum_{j=1}^{N_{\\nu_{x}}}\\nu_{y}^{\\nu_{x},j}(k_{x})\\ \\mathrm{mod}\\ 1.\n$$ \n\nHence, since $k_{x}$ is a dummy variable, $M_{x}$ symmetry implies that \n\n$$\np_{y}^{\\nu_{x}}\\overset{M_{x}}{=}p_{y}^{-\\nu_{x}}\\mathrm{mod}1,\n$$ \n\nwhich is the first expression in Eq. (6.19). \n\n# 2. Constraints due to reflection symmetry along y \n\nWe now derive the constraints that reflection symmetry $M_{y}:y\\rightarrow-y$ imposes on the Wilson loops along $x$ , $\\mathcal{W}_{x,{\\bf k}}$ , and on the nested Wilson loops along $y$ over Wannier sector $\\nu_{x},\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ · \n\n# a. On the Wilson loop over energy bands \n\nConsider a system with reflection symmetry along $y$ \n\n$$\n\\hat{M}_{y}h_{\\mathbf{k}}\\hat{M}_{y}^{\\dagger-1}=h_{M_{y}\\mathbf{k}},\n$$ \n\nwhere $M_{y}\\mathbf{k}=M_{y}(k_{x},k_{y})=(k_{x},-k_{y})$ . This symmetry allows us to write the expansion \n\n$$\n\\hat{M}_{y}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle=\\big|u_{M_{y}\\mathbf{k}}^{m}\\big\\rangle B_{M_{y},\\mathbf{k}}^{m n},\n$$ \n\nwhere \n\n$$\nB_{M_{y},{\\bf k}}^{m n}=\\langle u_{M_{y}\\mathbf{k}}^{m}|\\hat{M}_{y}|u_{\\mathbf{k}}^{n}\\rangle\n$$ \n\nis the unitary sewing matrix, which connects states at $\\mathbf{k}$ with states at $M_{y}\\mathbf{k}$ . In particular, $B_{M_{y},{\\bf k}}^{m n}\\neq0$ only if $\\epsilon_{m,M_{y}\\mathbf{k}}=\\epsilon_{n,\\mathbf{k}}$ . \n\nUnder this symmetry, the Wilson loop along $x$ starting at base point $\\mathbf{k}$ obeys \n\n$$\nB_{M_{y},\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}B_{M_{y},\\mathbf{k}}^{\\dagger}=\\mathcal{W}_{x,M_{y}\\mathbf{k}}.\n$$ \n\nA schematic of this relation is shown in Fig. 47(b). The Wilson loops based at $\\mathbf{k}$ and $M_{y}\\mathbf{k}$ are equivalent up to a unitary transformation. Hence, the sets of their eigenvalues are the same, namely, \n\n$$\n\\left\\{e^{i2\\pi\\nu_{x}^{i}(k_{y})}\\right\\}\\overset{M_{y}}{=}\\left\\{e^{i2\\pi\\nu_{x}^{i}(-k_{y})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{x}^{i}(k_{y})\\right\\}\\stackrel{M_{y}}{=}\\left\\{\\nu_{x}^{i}(-k_{y})\\right\\}\\mathrm{~mod~}1\n$$ \n\nwhich leads to \n\n$$\np_{x}(k_{y})\\overset{M_{y}}{=}p_{x}(-k_{y})\\bmod1.\n$$ \n\nNotice that the overall polarization along $x$ [Eq. (4.9)] is not constrained by reflection symmetry along $y$ . \n\n# b. On the nested Wilson loop over Wannier sectors \n\nNow, we focus on the Wilson-loop eigenfunctions \n\n$$\n\\begin{array}{r}{\\mathcal{W}_{x,\\mathbf{k}}{\\left|\\nu_{x,\\mathbf{k}}^{i}\\right\\rangle}=e^{i2\\pi\\nu_{x}^{i}(k_{y})}{\\left|\\nu_{x,\\mathbf{k}}^{i}\\right\\rangle}.}\\end{array}\n$$ \n\nRewriting Eq. (D35) as $B_{M_{y},\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}=\\mathcal{W}_{x,M_{y}\\mathbf{k}}B_{M_{y},\\mathbf{k}}$ , we have that \n\n$$\n\\begin{array}{r l}&{\\mathcal{W}_{x,M_{y}\\mathbf{k}}B_{M_{y},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle=B_{M_{y},\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle}\\\\ &{\\qquad=e^{i2\\pi\\nu_{x}^{i}(k_{y})}B_{M_{y},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle.}\\end{array}\n$$ \n\n$B_{M_{y},\\mathbf{k}}|\\nu_{x,\\mathbf{k}}^{i}\\rangle$ is an eigenfunction of $\\mathcal{W}_{x,M_{y}\\mathbf{k}}$ with eigenvalue ei2πνix(ky). We now expand this function as \n\n$$\nB_{M_{y},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle=\\big|\\nu_{x,M_{y}\\mathbf{k}}^{j}\\big\\rangle\\alpha_{M_{y},\\mathbf{k}}^{j i},\n$$ \n\nwhere \n\n$$\n\\alpha_{M_{y},\\mathbf{k}}^{j i}=\\big\\langle\\nu_{x,M_{y}\\mathbf{k}}^{j}\\big|B_{M_{y},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle\n$$ \n\nis a sewing matrix that connects Wilson-loop eigenstates at base point ${\\bf k}=(k_{x},k_{y})$ and base point $M_{y}\\mathbf{k}=(k_{x},-k_{y})$ having the same Wilson-loop eigenvalues; if $\\alpha_{M_{y},{\\bf k}}^{j i}\\neq0$ , we require that $\\nu_{x}^{j}(-k_{y})=\\nu_{x}^{i}(k_{y})$ . Following the same procedure as in Eq. (D25) for the Wannier sectors $|w_{x,\\mathbf{k}}^{j}\\rangle$ , we have \n\n$$\n\\hat{M}_{y}|w_{x,\\mathbf{k}}^{j}\\rangle=\\left|w_{x,M_{y}\\mathbf{k}}^{i}\\right\\rangle\\alpha_{M_{y},\\mathbf{k}}^{i j},\n$$ \n\nfrom which it follows that \n\n$$\n\\left|w_{x,\\mathbf{k}}^{j}\\right>=\\hat{M}_{y}^{\\dagger}\\big|w_{x,M_{y}\\mathbf{k}}^{i}\\big>\\alpha_{M_{y},\\mathbf{k}}^{i j}.\n$$ \n\nUsing these expressions, there is the following relation for a Wilson-line element: \n\n$$\n\\begin{array}{r}{\\big[\\tilde{\\mathcal{W}}_{{\\bf k}_{2}\\leftarrow{\\bf k}_{1}}^{\\nu_{x}}\\big]^{i j}=\\big[\\alpha_{M_{y},{\\bf k}_{2}}^{\\dagger}\\big]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{M_{y}{\\bf k}_{2}\\leftarrow M_{y}{\\bf k}_{1}}^{\\nu_{x}^{\\prime}}\\big]^{i^{\\prime}j^{\\prime}}\\big[\\alpha_{M_{y},{\\bf k}_{1}}\\big]^{j^{\\prime}j}.}\\end{array}\n$$ \n\nIn particular, the nested Wilson loop along $y$ in the basis $|w_{x}^{j}\\rangle$ obeys \n\n$$\n\\begin{array}{r}{\\big[\\tilde{\\mathcal{W}}_{y,{\\bf k}}^{\\nu_{x}}\\big]^{i j}=\\big[\\alpha_{M_{y},{\\bf k}}^{\\dagger}\\big]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{-y,M_{y}{\\bf k}}^{\\nu_{x}^{\\prime}}\\big]^{i^{\\prime}j^{\\prime}}\\big[\\alpha_{M_{y},{\\bf k}}\\big]^{j^{\\prime}j},}\\end{array}\n$$ \n\nwhich looks similar to the one in Appendix $\\mathrm{~D~1~}$ , but with the important difference in the structure of $\\alpha_{M_{y},{\\bf k}}^{j i}$ , which connects Wilson-loop eigenstates such that $\\nu_{x}^{j}(k_{y})=\\nu_{x}^{i}(-k_{y})$ . Another important difference is the fact that $\\hat{M}_{y}$ reverses the loop contour along $y$ and preserves it along $x$ . This expression tells us that the Wilson-loop eigenvalues are related by \n\n$$\n\\left\\{e^{i2\\pi\\nu_{y}^{\\nu_{x},j}(k_{x})}\\right\\}\\overset{M_{y}}{=}\\left\\{e^{-i2\\pi\\nu_{y}^{\\nu_{x},j}(k_{x})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{y}^{\\nu_{x},j}(k_{x})\\right\\}\\overset{M_{y}}{=}\\left\\{-\\nu_{y}^{\\nu_{x},j}(k_{x})\\right\\}\\mathrm{mod}1,\n$$ \n\nfrom which it follows that $\\nu_{y}^{\\nu_{x}}(k_{x})$ is either $0,\\{\\scriptstyle{\\frac{1}{2}}$ , or comes in pairs $\\nu,-\\nu.\\ M_{y}$ thus implies that the polarization (D31) over the Wannier sector $\\nu_{x}$ obeys \n\n$$\np_{y}^{\\nu_{x}}\\stackrel{M_{y}}{=}-p_{y}^{\\nu_{x}}\\mathrm{mod}1,\n$$ \n\nfrom which it follows that \n\n$$\np_{y}^{\\nu_{x}}\\overset{M_{y}}{=}0\\mathrm{or}1/2,\n$$ \n\nwhich is the second expression in Eq. (6.19). In particular, values of $\\nu_{y}^{\\nu_{x}}(k_{x})$ that come in pairs $\\nu,-\\nu$ do not contribute to $p_{y}^{\\nu_{x}}$ . \n\nThe results in this subsection, and in the previous one, provide the constraints due to both reflection symmetries on the Wilson loops $\\mathcal{W}_{y,{\\bf k}}$ and $\\tilde{\\mathcal{W}}_{x,\\mathbf{k}}^{\\nu_{y}}$ . The constraints due to these reflection symmetries on $\\mathcal{W}_{x,{\\mathbf{k}}}$ and $\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ can be obtained simply by replacing the labels $x\\leftrightarrow y$ in the results of these two subsections. \n\n# 3. Constraints due to inversion symmetry \n\nWe now derive the constraints that inversion symmetry imposes on the Wilson loops $\\mathcal{W}_{x,{\\bf k}}$ and on $\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ . \n\n# a. On the Wilson loop over energy bands \n\nConsider the constrains imposed by inversion symmetry \n\n$$\n\\hat{\\mathcal{T}}h_{\\mathbf{k}}\\hat{\\mathcal{T}}^{-1}=h_{-\\mathbf{k}},\n$$ \n\nunder which the Wilson loop obeys [see Eq. (D10)] \n\n$$\nB_{\\mathcal{T},\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}B_{\\mathcal{T},\\mathbf{k}}^{\\dagger}=\\mathcal{W}_{-x,-\\mathbf{k}}=\\mathcal{W}_{x,-\\mathbf{k}}^{\\dagger},\n$$ \n\nwhere \n\n$$\nB_{\\mathcal{T},\\mathbf{k}}^{m n}=\\big\\langle u_{-\\mathbf{k}}^{m}\\big\\vert\\hat{\\mathcal{T}}\\big\\vert u_{\\mathbf{k}}^{n}\\big\\rangle\n$$ \n\nconnects energy eigenstates at $\\mathbf{k}$ and $-\\mathbf{k}$ having the same energy. A schematic of this relation is shown in Fig. 47(c). Equation (D14) implies that the set of eigenvalues obey \n\n$$\n\\left\\{e^{i2\\pi\\nu_{x}^{i}(k_{y})}\\right\\}\\stackrel{\\mathcal{Z}}{=}\\left\\{e^{-i2\\pi\\nu_{x}^{i}(-k_{y})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{x}^{i}(k_{y})\\right\\}\\stackrel{\\mathcal{Z}}{=}\\left\\{-\\nu_{x}^{i}(-k_{y})\\right\\}\\mod1.\n$$ \n\nIn particular, for values $k_{y}^{*}=0,\\pi$ of the $y$ coordinate of the Wilson-loop base point, we recover the identical condition as for reflection symmetry along $x$ . Thus, at these points the Wilson-loop eigenvalues are either $0,\\ {\\frac{1}{2}}$ , or come in pairs $\\nu,-\\nu$ . We also have \n\n$$\np_{x}(k_{y})\\overset{\\mathcal{Z}}{=}-p_{x}(-k_{y})\\bmod1,\n$$ \n\nso that the polarization obeys \n\n$$\np_{x}\\overset{\\mathcal{Z}}{=}-p_{x}\\bmod1,\n$$ \n\ni.e., it is quantized \n\n$$\np_{x}\\overset{\\mathcal{Z}}{=}0\\mathrm{or}1/2,\n$$ \n\nwhich is the relation given in Eq. (4.20). \n\n# b. On the nested Wilson loop over Wannier sectors \n\nFor the Wilson-loop eigenstates \n\n$$\n\\begin{array}{r}{\\mathcal{W}_{x,\\mathbf{k}}{\\left|\\nu_{x,\\mathbf{k}}^{i}\\right|}=e^{i2\\pi\\nu_{x}^{i}(k_{y})}{\\left|\\nu_{x,\\mathbf{k}}^{i}\\right|},}\\end{array}\n$$ \n\none can use Eq. (D52) to show that $B_{T,\\mathbf{k}}|\\nu_{x,\\mathbf{k}}^{i}\\rangle$ is an eigenstate of $\\mathcal{W}_{x,-\\mathbf{k}}$ with eigenvalue $e^{-i2\\pi\\nu_{x}^{i}(k_{y})}$ . Thus, in the expansion \n\n$$\nB_{\\mathcal{T},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle=\\big|\\nu_{x,-\\mathbf{k}}^{j}\\big\\rangle\\alpha_{\\mathcal{T},\\mathbf{k}}^{j i},\n$$ \n\nthe sewing matrix \n\n$$\n\\alpha_{\\mathcal{T},\\mathbf{k}}^{j i}=\\left\\langle\\nu_{x,-\\mathbf{k}}^{j}\\middle|B_{\\mathcal{T},\\mathbf{k}}\\middle|\\nu_{x,\\mathbf{k}}^{i}\\right\\rangle\n$$ \n\nconnects Wilson-loop eigenstates at base points $\\mathbf{k}$ and $-\\mathbf{k}$ having opposite Wannier centers, i.e., $\\alpha_{\\mathbf{k}}^{j i}\\neq0$ only if $\\nu_{x}^{i}(k_{y})=$ $-\\nu_{x}^{j}(-k_{y})$ . For the Wannier sectors $|w_{x,\\mathbf{k}}^{j}\\rangle$ , we have \n\n$$\n\\hat{\\mathcal{T}}\\big|w_{x,\\mathbf{k}}^{j}\\big\\rangle=\\big|w_{x,-\\mathbf{k}}^{i}\\big\\rangle\\alpha_{\\mathcal{T},\\mathbf{k}}^{i j},\n$$ \n\nfrom which it follows that \n\n$$\n\\begin{array}{r}{|w_{x,\\mathbf{k}}^{j}\\rangle=\\hat{\\mathcal{T}}^{\\dagger}|w_{x,-\\mathbf{k}}^{i}\\rangle\\alpha_{\\mathcal{T},\\mathbf{k}}^{i j}.}\\end{array}\n$$ \n\nUsing these expressions, there is the following relation for a Wilson-line element: \n\n$$\n\\left[\\tilde{\\mathcal{W}}_{{\\bf k}_{2}\\leftarrow{\\bf k}_{1}}^{\\nu_{x}}\\right]^{i j}=\\left[\\alpha_{\\mathcal{T},{\\bf k}_{2}}^{\\dagger}\\right]^{i i^{\\prime}}\\left[\\tilde{\\mathcal{W}}_{-{\\bf k}_{2}\\leftarrow-{\\bf k}_{1}}^{\\nu_{x}^{\\prime}}\\right]^{i^{\\prime}j^{\\prime}}\\left[\\alpha_{\\mathcal{T},{\\bf k}_{1}}\\right]^{j^{\\prime}j}.\n$$ \n\nIn particular, the Wilson loop along $y$ obeys \n\n$$\n\\begin{array}{r}{\\big[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}\\big]^{i j}=[\\alpha_{\\mathcal{T},\\mathbf{k}}^{\\dagger}]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{-y,-\\mathbf{k}}^{\\nu_{x}^{\\prime}}\\big]^{i^{\\prime}j^{\\prime}}[\\alpha_{\\mathcal{T},\\mathbf{k}}]^{j^{\\prime}j}.}\\end{array}\n$$ \n\nThus, the Wilson-loop eigenvalues are related by \n\n$$\n\\left\\{e^{i2\\pi\\nu_{y}^{\\nu_{x},j}(k_{x})}\\right\\}\\overset{\\mathcal{Z}}{=}\\left\\{e^{-i2\\pi\\nu_{y}^{-\\nu_{x},j}(-k_{x})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{y}^{\\nu_{x},j}(k_{x})\\right\\}\\overset{\\mathcal{Z}}{=}\\left\\{-\\nu_{y}^{-\\nu_{x},j}(-k_{x})\\right\\}\\mathrm{~mod~}1.\n$$ \n\nThus, we have that \n\n$$\np_{y}^{\\nu_{x}}(k_{x})\\overset{\\mathcal{Z}}{=}-p_{y}^{-\\nu_{x}}(-k_{x})\\mathrm{mod}1,\n$$ \n\nand the Wannier-sector polarization (D31) under inversion symmetry obeys \n\n$$\np_{y}^{\\nu_{x}}\\overset{\\mathcal{Z}}{=}-p_{y}^{-\\nu_{x}}\\mathrm{mod}1,\n$$ \n\nwhich is the third expression in Eq. (6.19). \n\n# 4. Constraints due to $C_{4}$ symmetry \n\nWe now derive the constraints that $C_{4}$ symmetry imposes on the Wilson loops $\\mathcal{W}_{x,{\\mathbf{k}}}$ and on $\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ . \n\n# a. On the Wilson loop over energy bands \n\nNow, we consider $C_{4}$ symmetry \n\n$$\n\\hat{r}_{4}h_{\\mathbf{k}}\\hat{r}_{4}^{-1}=h_{R_{4}\\mathbf{k}}\n$$ \n\nunder which the Wilson loop obeys \n\n$$\n\\begin{array}{r l}&{B_{C_{4},\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}B_{C_{4},\\mathbf{k}}^{\\dagger}=\\mathcal{W}_{y,R_{4}\\mathbf{k}},}\\\\ &{B_{C_{4},\\mathbf{k}}\\mathcal{W}_{y,\\mathbf{k}}B_{C_{4},\\mathbf{k}}^{\\dagger}=\\mathcal{W}_{-x,R_{4}\\mathbf{k}},}\\end{array}\n$$ \n\nwhere \n\n$$\nB_{C_{4},\\mathbf{k}}^{m n}=\\left\\langle u_{R_{4}\\mathbf{k}}^{m}\\middle|\\hat{r}_{4}\\middle|u_{\\mathbf{k}}^{n}\\right\\rangle\n$$ \n\nis the sewing matrix with elements $B_{C_{4},\\mathbf{k}}^{m n}\\neq0$ only if $\\epsilon_{m,R_{4}{\\bf k}}=$ $\\epsilon_{n,\\mathbf{k}}$ . The Wannier values are then related by \n\n$$\n\\begin{array}{r}{\\left\\{\\nu_{x}^{i}(k_{y})\\right\\}\\stackrel{C_{4}}{=}\\left\\{\\nu_{y}^{i}(k_{x}=-k_{y})\\right\\}\\bmod1,}\\\\ {\\left\\{\\nu_{y}^{i}(k_{x})\\right\\}\\stackrel{C_{4}}{=}\\left\\{-\\nu_{x}^{i}(k_{y}=k_{x})\\right\\}\\bmod1.}\\end{array}\n$$ \n\nThese in turn lead to \n\n$$\n\\begin{array}{r}{p_{x}(k_{y})\\overset{C_{4}}{=}p_{y}(k_{x}=-k_{y})\\mathrm{mod}1,}\\\\ {p_{y}(k_{x})\\overset{C_{4}}{=}-p_{x}(k_{y}=k_{x})\\mathrm{mod}1.}\\end{array}\n$$ \n\nNotice that the successive application of one of these relations after the other one leads to (D56), which is nothing but the constraint due to $C_{2}$ symmetry (in the absence of spin). The constraint over the polarization is then \n\n$$\np_{x}\\overset{C_{4}}{=}p_{y}\\overset{C_{4}}{=}0\\mathrm{or}1/2.\n$$ \n\n# b. On the nested Wilson loop over Wannier sectors \n\nThe two relations in Eq. (D71) allow us to write the expansions \n\n$$\n\\begin{array}{r}{B_{C_{4},\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i}\\big\\rangle=\\big|\\nu_{y,R_{4}\\mathbf{k}}^{j}\\big\\rangle\\alpha_{C_{4},\\mathbf{k}}^{j i},}\\\\ {B_{C_{4},\\mathbf{k}}\\big|\\nu_{y,\\mathbf{k}}^{i}\\big\\rangle=\\big|\\nu_{x,R_{4}\\mathbf{k}}^{j}\\big\\rangle\\beta_{C_{4},\\mathbf{k}}^{j i},}\\end{array}\n$$ \n\nwhere $\\alpha_{C_{4},\\mathbf{k}}$ and $\\beta_{C_{4},\\mathbf{k}}$ are the sewing matrices \n\n$$\n\\alpha_{C_{4},{\\bf k}}^{j i}=\\big\\langle\\nu_{y,R_{4}{\\bf k}}^{j}\\big|B_{C_{4},{\\bf k}}\\big|\\nu_{x,{\\bf k}}^{i}\\big\\rangle\n$$ \n\nwith $\\alpha_{C_{4},{\\bf k}}^{j i}\\neq0$ only if $\\nu_{x}^{i}(k_{y})=\\nu_{y}^{j}(k_{x}=-k_{y})$ , and \n\n$$\n\\beta_{C_{4},{\\bf k}}^{j i}=\\left<\\nu_{x,R_{4}{\\bf k}}^{j}\\right|B_{C_{4},{\\bf k}}\\right|\\nu_{y,{\\bf k}}^{i}\\rangle\n$$ \n\nwith $\\beta_{C_{4},\\mathbf{k}}^{j i}\\neq0$ only if $\\nu_{y}^{i}(k_{x})=-\\nu_{x}^{j}(k_{y}=k_{x})$ . \n\nThe Wannier sectors $|w_{x,\\mathbf{k}}^{j}\\rangle$ and $|w_{y,\\mathbf{k}}^{j}\\rangle$ transform as \n\n$$\n\\begin{array}{r}{\\hat{r}_{4}\\big|w_{x,\\mathbf{k}}^{j}\\big\\rangle=\\big|w_{y,R_{4}\\mathbf{k}}^{i}\\big\\rangle\\alpha_{C_{4},\\mathbf{k}}^{i j},}\\\\ {\\hat{r}_{4}\\big|w_{y,\\mathbf{k}}^{j}\\big\\rangle=\\big|w_{x,R_{4}\\mathbf{k}}^{i}\\big\\rangle\\beta_{C_{4},\\mathbf{k}}^{i j}.}\\end{array}\n$$ \n\nUsing these expressions and their Hermitian conjugates, we find the following relations for the Wilson-line elements: \n\n$$\n\\begin{array}{r}{\\left[\\tilde{\\mathcal{W}}_{{\\bf k}_{2}\\leftarrow{\\bf k}_{1}}^{\\nu_{x}}\\right]^{i j}=\\left[\\alpha_{C_{4},{\\bf k}_{2}}^{\\dagger}\\right]^{i i^{\\prime}}\\left[\\tilde{\\mathcal{W}}_{R_{4}{\\bf k}_{2}\\leftarrow R_{4}{\\bf k}_{1}}^{\\nu_{y}}\\right]^{i^{\\prime}j^{\\prime}}\\left[\\alpha_{C_{4},{\\bf k}_{1}}\\right]^{j^{\\prime}j},}\\\\ {\\left[\\tilde{\\mathcal{W}}_{{\\bf k}_{2}\\leftarrow{\\bf k}_{1}}^{\\nu_{y}}\\right]^{i j}=\\left[\\beta_{C_{4},{\\bf k}_{2}}^{\\dagger}\\right]^{i i^{\\prime}}\\left[\\tilde{\\mathcal{W}}_{R_{4}{\\bf k}_{2}\\leftarrow R_{4}{\\bf k}_{1}}^{\\nu_{x}}\\right]^{i^{\\prime}j^{\\prime}}\\left[\\beta_{C_{4},{\\bf k}_{1}}\\right]^{j^{\\prime}j}.}\\end{array}\n$$ \n\nIn particular, the nested Wilson loops along $x$ and $y$ obey \n\n$$\n\\begin{array}{r l}&{\\big[\\tilde{\\mathcal{W}}_{y,{\\bf k}}^{\\nu_{x}}\\big]^{i j}=\\big[\\alpha_{C_{4},{\\bf k}}^{\\dagger}\\big]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{-x,R_{4}{\\bf k}}^{\\nu_{y}}\\big]^{i^{\\prime}j^{\\prime}}\\big[\\alpha_{C_{4},{\\bf k}}\\big]^{j^{\\prime}j},}\\\\ &{\\big[\\tilde{\\mathcal{W}}_{x,{\\bf k}}^{\\nu_{y}}\\big]^{i j}=\\big[\\beta_{C_{4},{\\bf k}}^{\\dagger}\\big]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{y,R_{4}{\\bf k}}^{\\nu_{x}}\\big]^{i^{\\prime}j^{\\prime}}\\big[\\beta_{C_{4},{\\bf k}}\\big]^{j^{\\prime}j}.}\\end{array}\n$$ \n\nThese expressions tell us that the Wilson-loop eigenvalues are related by \n\n$$\n\\begin{array}{r l r}&{}&{\\left\\{e^{i2\\pi\\nu_{y}^{\\nu_{x}}(k_{x})}\\right\\}\\stackrel{C_{4}}{=}\\left\\{e^{-i2\\pi\\nu_{x}^{\\nu_{y}}(k_{x})}\\right\\},}\\\\ &{}&{\\left\\{e^{i2\\pi\\nu_{x}^{\\nu_{y}}(k_{y})}\\right\\}\\stackrel{C_{4}}{=}\\left\\{e^{i2\\pi\\nu_{y}^{-\\nu_{x}}(-k_{y})}\\right\\}}\\end{array}\n$$ \n\nor \n\n$$\n\\begin{array}{r l}&{\\left\\{\\nu_{y}^{\\nu_{x}}(k_{x})\\right\\}\\overset{C_{4}}{=}\\left\\{-\\nu_{x}^{\\nu_{y}}(k_{x})\\right\\}\\bmod1,}\\\\ &{\\left\\{\\nu_{x}^{\\nu_{y}}(k_{y})\\right\\}\\overset{C_{4}}{=}\\left\\{\\nu_{y}^{-\\nu_{x}}(-k_{y})\\right\\}\\bmod1}\\end{array}\n$$ \n\nor, for the Wannier-sector polarizations \n\n$$\n\\begin{array}{r l}&{p_{y}^{\\nu_{x}^{\\pm}}\\stackrel{C_{4}}{=}-p_{x}^{\\nu_{y}^{\\pm}}\\bmod1,}\\\\ &{p_{x}^{\\nu_{y}^{\\pm}}\\stackrel{C_{4}}{=}p_{y}^{\\nu_{x}^{\\mp}}\\bmod1.}\\end{array}\n$$ \n\nNotice that the sequential application of these two equations, which amounts to a $C_{2}$ rotation (or inversion), results in Eq. (D69). \n\n# 5. Constraints due to time-reversal symmetry \n\nIn this section we derive the constraints that time-reversal symmetry $\\mathrm{TR}:t\\rightarrow-t$ imposes on the Wilson loops $\\mathcal{W}_{x,{\\bf k}}$ and on the nested Wilson loops $\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ . \n\n# a. On the Wilson loop over energy bands \n\nThe time-reversal operator is $\\hat{T}=Q K$ , where $K$ is complex conjugation and $\\boldsymbol{Q}$ is a unitary operator, so that $Q^{-1}=Q^{\\dagger}$ . For spinless systems, ${\\hat{T}}^{2}=1$ . For spinful systems, ${\\hat{T}}^{2}=-1$ . Time-reversal symmetry (TRS) is stated as \n\n$$\n{\\hat{T}}h_{\\mathbf{k}}{\\hat{T}}^{-1}=h_{-\\mathbf{k}}.\n$$ \n\nAs before, it is possible to expand \n\n$$\n\\hat{T}\\left|u_{\\mathbf{k}}^{n}\\right\\rangle=\\left|u_{-\\mathbf{k}}^{m}\\right\\rangle\\left\\langle u_{-\\mathbf{k}}^{m}\\right|\\hat{T}\\left|u_{\\mathbf{k}}^{n}\\right\\rangle=\\left|u_{-\\mathbf{k}}^{m}\\right\\rangle V_{\\mathbf{k}}^{m n},\n$$ \n\nwhere \n\nor \n\nis the sewing matrix, which is unitary. Here, the asterisk represents complex conjugation. The sewing matrix has nonzero elements $V_{\\mathbf{k}}^{m n}\\neq0$ only if $\\epsilon_{n}({\\bf k})=\\epsilon_{m}(-{\\bf k})$ . \n\n$$\nV_{\\bf k}^{m n}=\\left\\langle u_{-\\bf k}^{m}\\right|\\hat{T}\\left|u_{\\bf k}^{n}\\right\\rangle=\\left\\langle u_{-\\bf k}^{m}\\right|Q\\left|u_{\\bf k}^{n*}\\right\\rangle\n$$ \n\nFor spinful systems, ${\\hat{T}}^{2}=-1$ leads to $Q^{T}=-Q$ , which can be seen from joining the two expressions \n\n$$\n\\begin{array}{l}{{\\hat{T}^{2}=Q K Q K=Q Q^{*}=-1,}}\\\\ {{Q Q^{\\dagger}=1\\rightarrow Q^{*}Q^{T}=1,}}\\end{array}\n$$ \n\n$$\n\\left\\{\\nu_{x}^{i}(-k_{y})\\right\\}\\stackrel{\\mathrm{TR}}{=}\\left\\{\\nu_{x}^{i}(k_{y})\\right\\}\\bmod1,\n$$ \n\nso that $Q^{*}Q^{T}=-Q^{*}Q$ or $Q^{*}(Q^{T}+Q)=0$ , from which $Q^{T}=-Q$ . This implies that $V_{\\mathbf{k}}^{T}=-V_{-\\mathbf{k}}$ , as can be seen as follows: \n\n$$\n\\begin{array}{c}{{V_{\\bf k}^{m n}=\\left\\langle u_{-\\bf k}^{m}\\right\\vert Q\\left\\vert u_{\\bf k}^{n*}\\right\\rangle,}}\\\\ {{V_{\\bf k}^{\\dagger m n}=\\left[V_{\\bf k}^{T*}\\right]^{m n}=\\left\\langle u_{\\bf k}^{m*}\\right\\vert Q^{T*}\\left\\vert u_{-\\bf k}^{n}\\right\\rangle,}}\\\\ {{\\left[V_{\\bf k}^{T}\\right]^{m n}=\\left\\langle u_{\\bf k}^{m}\\right\\vert Q^{T}\\left\\vert u_{-\\bf k}^{n*}\\right\\rangle,}}\\\\ {{\\left[V_{\\bf k}^{T}\\right]^{m n}=-\\left\\langle u_{\\bf k}^{m}\\right\\vert Q\\left\\vert u_{-\\bf k}^{n*}\\right\\rangle,}}\\\\ {{V_{\\bf k}^{T}=-V_{-\\bf k}.}}\\end{array}\n$$ \n\nAt time-reversal-invariant momenta ${\\bf k}_{*}=-{\\bf k}_{*}$ , this relation reduces to $V_{\\mathbf{k}_{*}}^{T}=-V_{\\mathbf{k}_{*}}$ , which is not possible if $V_{\\mathbf{k}^{*}}$ is one dimensional. ∗Since $V_{\\mathbf{k}}^{m n}\\neq0$ only if $\\epsilon_{m}(-\\mathbf{k})=\\epsilon_{n}(\\mathbf{k})$ , this means that at the time-reversal-invariant momenta the energy spectrum is at least twofold degenerate. Reordering terms in the expansion of ${\\hat{T}}|u_{\\mathbf{k}}^{n}\\rangle=Q|u_{\\mathbf{k}}^{n*}\\rangle$ above, we have \n\n$$\n\\begin{array}{r}{\\left|u_{-\\mathbf{k}}^{n}\\right\\rangle=Q\\left|u_{\\mathbf{k}}^{m*}\\right\\rangle V_{\\mathbf{k}}^{\\dagger m n},}\\\\ {\\left\\langle u_{-\\mathbf{k}}^{n}\\right|=V_{\\mathbf{k}}^{n m}\\big\\langle u_{\\mathbf{k}}^{m*}\\big|Q^{\\dagger}.}\\end{array}\n$$ \n\nNow, consider two momenta $\\mathbf{k}_{1},\\mathbf{k}_{2}$ , which are very close to each other. There is the following relation between Wilson lines: \n\n$$\n\\begin{array}{r l r}&{}&{\\mathcal{W}_{-{\\bf k}_{2}\\leftarrow-{\\bf k}_{1}}^{m n}=\\left\\langle u_{-{\\bf k}_{2}}^{m}\\right\\vert u_{-{\\bf k}_{1}}^{n}\\right\\rangle=V_{{\\bf k}_{2}}^{m r}\\langle u_{{\\bf k}_{2}}^{r*}\\vert Q^{\\dagger}Q\\left\\vert u_{{\\bf k}_{1}}^{s*}\\right\\rangle V_{{\\bf k}_{1}}^{\\dagger s n}}\\\\ &{}&{=V_{{\\bf k}_{2}}^{m r}\\mathcal{W}_{{\\bf k}_{2}\\leftarrow{\\bf k}_{1}}^{r s*}V_{{\\bf k}_{1}}^{\\dagger s n}\\qquad(\\mathrm{I}}\\end{array}\n$$ \n\nor, more compactly, \n\n$$\n\\mathscr{W}_{-\\mathbf{k}_{2}\\leftarrow-\\mathbf{k}_{1}}=V_{\\mathbf{k}_{2}}\\mathscr{W}_{\\mathbf{k}_{2}\\leftarrow\\mathbf{k}_{1}}^{*}V_{\\mathbf{k}_{1}}^{\\dagger}.\n$$ \n\nFor Wilson loops starting at a base point $\\mathbf{k}$ we have \n\n$$\n\\mathcal{W}_{-x,-\\mathbf{k}}=\\mathcal{W}_{x,-\\mathbf{k}}^{\\dagger}=V_{\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}^{*}V_{\\mathbf{k}}^{\\dagger}.\n$$ \n\nThus, as before, there is an equivalence up to a unitary transformation. Thus, the set of eigenvalues must obey \n\n$$\n\\left\\{e^{-i2\\pi\\nu_{x}^{i}(-k_{y})}\\right\\}\\stackrel{\\mathrm{TR}}{=}\\left\\{e^{-i2\\pi\\nu_{x}^{i}(k_{y})}\\right\\}\n$$ \n\nwhich implies that \n\n$$\np_{x}(k_{y})\\overset{\\mathrm{TR}}{=}p_{x}(-k_{y})\\bmod1.\n$$ \n\nThis does not impose a constraint on the values of polarization. \n\n# b. On the nested Wilson loop over Wannier sectors \n\nLet us calculate how the Wilson-loop eigenstates transform under TR. Acting with the Wilson loop $\\mathcal{W}_{x,-\\mathbf{k}}^{\\dagger}\\mathrm{on}V_{\\mathbf{k}}|\\nu_{x,\\mathbf{k}}^{i*}\\rangle$ , and making use of (D92), we have \n\n$$\n\\mathcal{W}_{x,-\\mathbf{k}}^{\\dagger}V_{\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i*}\\big\\rangle=V_{\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}^{*}\\big|\\nu_{x,\\mathbf{k}}^{i*}\\big\\rangle=e^{-i2\\pi\\nu_{x}^{i}(k_{y})}V_{\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i*}\\big\\rangle.\n$$ \n\nSo, $V_{\\mathbf{k}}|\\nu_{x,\\mathbf{k}}^{i*}\\rangle$ is an eigenstate of $\\mathcal{W}_{x,-\\mathbf{k}}^{\\dagger}$ with eigenvalue e−i2πνix(ky). Thus, we can write the expansion \n\n$$\nV_{\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i*}\\big\\rangle=\\big|\\nu_{x,-\\mathbf{k}}^{j}\\big\\rangle\\alpha_{T,\\mathbf{k}}^{j i},\n$$ \n\nwhere \n\n$$\n\\alpha_{T,{\\bf k}}^{j i}=\\left<\\nu_{x,-{\\bf k}}^{j}\\right|V_{\\bf k}\\left|\\nu_{x,{\\bf k}}^{i*}\\right>\n$$ \n\nis the sewing matrix connecting $|\\nu_{x,{\\bf k}}^{i*}\\rangle$ with $|\\nu_{x,-\\mathbf{k}}^{j}\\rangle$ . In particular, $\\alpha_{T,{\\bf k}}^{j i}\\neq0$ only if $\\nu_{x}^{i}(k_{y})=\\nu_{x}^{j}(-k_{y})$ . \n\nNow, we act with the TR operator on the Wannier basis: \n\n$$\n\\begin{array}{r}{\\hat{T}\\big|w_{x,\\mathbf{k}}^{j}\\big\\rangle=\\hat{T}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle\\big[\\nu_{x,\\mathbf{k}}^{j*}\\big]^{n}=\\big|u_{-\\mathbf{k}}^{m}\\big\\rangle V_{\\mathbf{k}}^{m n}\\big[\\nu_{x,\\mathbf{k}}^{j}\\big]^{n}}\\\\ {=\\big|u_{-\\mathbf{k}}^{m}\\big\\rangle\\big[\\nu_{x,-\\mathbf{k}}^{i}\\big]^{m}\\alpha_{T,\\mathbf{k}}^{i j}=\\big|w_{x,-\\mathbf{k}}^{i}\\big\\rangle\\alpha_{T,\\mathbf{k}}^{i j}.}\\end{array}\n$$ \n\nAt the time-reversal-invariant momenta (TRIM) we have \n\n$$\n\\begin{array}{r}{\\hat{T}|w_{x,\\mathbf{k}_{*}}^{j}\\rangle=|w_{x,\\mathbf{k}_{*}}^{i}\\rangle\\alpha_{T,\\mathbf{k}_{*}}^{i j},}\\end{array}\n$$ \n\nwhich implies that, when ${\\hat{T}}^{2}=-1$ , there has to be Kramers degeneracy in the Wannier centers at these invariant momenta. To see this, one can act with the TR operator twice: \n\n$$\n\\begin{array}{r}{\\hat{T}\\big(\\hat{T}\\big|w_{x,\\mathbf{k}_{*}}^{i}\\big)\\big)=\\hat{T}\\big(\\big|w_{x,\\mathbf{k}_{*}}^{j}\\big)\\alpha_{T,\\mathbf{k}_{*}}^{j i}\\big)=\\big(\\hat{T}\\big|w_{x,\\mathbf{k}_{*}}^{j}\\big)\\big)\\alpha_{T,\\mathbf{k}_{*}}^{*j i}}\\\\ {=\\big|w_{x,\\mathbf{k}_{*}}^{k}\\big|\\alpha_{T,\\mathbf{k}_{*}}^{k j}\\alpha_{T,\\mathbf{k}_{*}}^{*j i},\\qquad\\mathrm{(I}}\\end{array}\n$$ \n\nwhile, on the other hand, \n\n$$\n\\hat{T}\\big(\\hat{T}\\big|w_{x,\\mathbf{k}_{*}}^{i}\\big\\rangle\\big)=\\hat{T}^{2}\\big|w_{x,\\mathbf{k}_{*}}^{i}\\big\\rangle=-\\big|w_{x,\\mathbf{k}_{*}}^{i}\\big\\rangle.\n$$ \n\nThus, the sewing matrix needs to obey \n\n$$\n-\\delta^{k i}=\\alpha_{T,{\\bf k}_{\\ast}}^{k j}\\alpha_{T,{\\bf k}_{\\ast}}^{\\ast j i},\n$$ \n\na restriction that is impossible to meet if $\\alpha_{T,\\mathbf{k}_{*}}$ is a single number, i.e., if there are no degeneracies. Since $\\alpha_{T,{\\bf k}_{\\ast}}^{j i}\\neq0$ only if $\\nu_{x}^{i}(k_{*y})=\\nu_{x}^{j}(k_{*y})$ , this means that at the TRIM points of the BZ, the Wannier centers are at least twofold degenerate. When $\\hat{T}^{2}=1$ , on the other hand, the Wannier centers are not required to be degenerate. \n\nFrom (D99) we have the transformation \n\n$$\n\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}*}\\overset{\\mathrm{TR}}{=}\\alpha_{T,\\mathbf{k}}^{\\dagger}\\tilde{\\mathcal{W}}_{-y,-\\mathbf{k}}^{\\nu_{x}}\\alpha_{T,\\mathbf{k}}\\overset{\\mathrm{TR}}{=}\\alpha_{T,\\mathbf{k}}^{\\dagger}\\tilde{\\mathcal{W}}_{y,-\\mathbf{k}}^{\\nu_{x}\\dagger}\\alpha_{T,\\mathbf{k}}\n$$ \n\nfrom which it follows that \n\n$$\n\\left\\{\\nu_{y}^{\\nu_{x},j}(k_{x})\\right\\}\\stackrel{\\mathrm{TR}}{=}\\left\\{\\nu_{y}^{\\nu_{x},j}(-k_{x})\\right\\}\\mod1,\n$$ \n\nwhere $j\\in1\\ldots N_{\\nu_{x}}$ labels the eigenvalue, and $N_{\\nu_{x}}$ is the number of Wannier bands in the sector $\\nu_{x}$ . This implies that \n\n$$\np_{y}^{\\nu_{x}}(k_{x})\\overset{\\mathrm{TR}}{=}p_{y}^{\\nu_{x}}(-k_{x})\\bmod1,\n$$ \n\nwhich does not impose further constraints on the Wanniersector polarization. \n\n# 6. Constraints due to chiral symmetry \n\nIn this section we derive the constraints that chiral symmetry imposes on the Wilson loops $\\mathcal{W}_{x,{\\bf k}}$ and on the nested Wilson loops $\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}$ . \n\n# a. On the Wilson loop over energy bands \n\nUnder chiral symmetry, the Bloch Hamiltonian obeys \n\n$$\n\\hat{\\Pi}h_{\\mathbf{k}}\\hat{\\Pi}^{-1}=-h_{\\mathbf{k}}.\n$$ \n\nwhere $\\hat{\\Pi}$ is the chiral operator, which is unitary. Chiral symmetry relates the Wilson loops on opposite sides of the energy gap \n\n$$\nB_{\\Pi,{\\bf k}}\\mathcal{W}_{x,{\\bf k}}^{\\mathrm{occ}}B_{\\Pi,{\\bf k}}^{\\dagger}=\\mathcal{W}_{x,{\\bf k}}^{\\mathrm{unocc}},\n$$ \n\nwhere occ (unocc) stands for Wilson loops over occupied (unoccupied) bands. The sewing matrix $\\mathbf{\\hat{\\Pi}}^{m n}=\\langle u_{\\mathbf{k}}^{m}|\\hat{\\Pi}|u_{\\mathbf{k}}^{n}\\rangle$ connects states at $\\mathbf{k}$ on opposite sides of the energy gap, i.e., such that $\\epsilon_{n}(\\mathbf{k})=-\\epsilon_{m}(\\mathbf{k})$ when the Fermi level is at $\\epsilon=0$ . Thus, for a nonzero $B_{\\mathbf{k}}^{m n}$ , if $m$ labels a state in the occupied band, $n$ labels a state in the unoccupied band, or vice versa. Let us denote $|\\nu\\rangle$ as the eigenstates for $\\mathscr{W}^{\\mathrm{occ}}$ and $|\\eta\\rangle$ as the eigenstates for $\\mathcal{W}^{\\mathrm{unocc}}$ . Likewise, we denote the eigenvalues of $\\mathcal{W}^{\\mathrm{occ}}\\left(\\mathcal{W}^{\\mathrm{unocc}}\\right)$ as $e^{i2\\pi\\nu}(e^{i2\\pi\\eta})$ . From (D108), it follows that chiral symmetry relates the Wannier values of occupied and unoccupied bands according to \n\n$$\n\\left\\{\\nu_{x}^{i}(k_{y})\\right\\}\\stackrel{\\mathrm{chiral}}{=}\\left\\{\\eta_{x}^{i}(k_{y})\\right\\}\\mathrm{mod}1.\n$$ \n\nThis in turn leads to \n\n$$\np_{x}^{\\mathrm{occ}}(k_{y})\\overset{\\mathrm{chiral}}{=}p_{x}^{\\mathrm{unocc}}(k_{y})\\bmod1.\n$$ \n\nSince the Hilbert space of the Hamiltonian (occupied and unoccupied energy bands included) at each $k_{y}$ is complete, and thus always has trivial topology, we have that \n\n$$\np_{x}^{\\mathrm{occ}}(k_{y})+p_{x}^{\\mathrm{unocc}}(k_{y})=0\\ \\mathrm{mod}\\ 1\n$$ \n\nor \n\n$$\np_{x}^{\\mathrm{occ}}(k_{y})=-p_{x}^{\\mathrm{unocc}}(k_{y})\\mathrm{mod}1.\n$$ \n\nUsing (D110) and (D112), we conclude that \n\n$$\np_{x}^{\\mathrm{occ}}(k_{y})\\overset{\\mathrm{chiral}}{=}p_{x}^{\\mathrm{unocc}}(k_{y})\\overset{\\mathrm{chiral}}{=}0\\mathrm{or}1/2,\n$$ \n\ni.e., under chiral symmetry the polarization at each $k_{y}$ is quantized. This implies that the overall polarization is also \n\nquantized: \n\n$$\np_{x}^{\\mathrm{occ}}\\stackrel{\\mathrm{chiral}}{=}p_{x}^{\\mathrm{unocc}}\\stackrel{\\mathrm{chiral}}{=}0\\mathrm{or}1/2.\n$$ \n\n# b. On the Wilson loop over Wannier sectors \n\nFrom (D108) it follows that $B_{\\Pi,{\\bf k}}|\\nu_{x,{\\bf k}}^{i}\\rangle$ is an eigenstate of $\\mathcal{W}_{x,{\\bf k}}^{\\mathrm{unocc}}$ with eigenvalue $e^{i2\\pi\\nu_{x}^{i}(k_{y})}$ . Thus, in the expansion \n\n$$\nB_{\\Pi,{\\bf k}}|\\nu_{x,{\\bf k}}^{i}\\rangle=|\\eta_{x,{\\bf k}}^{j}\\rangle\\alpha_{\\Pi,{\\bf k}}^{j i}\n$$ \n\nthe sewing matrix \n\n$$\n\\alpha_{\\Pi,{\\bf k}}^{j i}=\\left\\langle\\eta_{x,{\\bf k}}^{j}\\right|B_{\\Pi,{\\bf k}}\\right|\\nu_{x,{\\bf k}}^{i}\\right\\rangle\n$$ \n\nconnects eigenstates of Wilson loop over occupied and unoccupied energy bands at base points $\\mathbf{k}$ and having the same Wannier centers $[\\alpha_{\\mathbf{k}}^{j i}\\neq0$ only if $\\nu_{x}^{i}(k_{y})=\\eta_{x}^{j}(k_{y})]$ . Let us consider the Wannier sectors \n\n$$\n\\big|w_{x,\\mathbf{k}}^{\\mathrm{occ},j}\\big\\rangle=\\sum_{n=1}^{N_{\\mathrm{occ}}}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle\\big[\\nu_{x,\\mathbf{k}}^{j}\\big]^{n},\n$$ \n\n$$\n|w_{x,\\mathbf{k}}^{\\mathrm{unocc},j}\\rangle=\\sum_{n=N_{\\mathrm{occ}}+1}^{N}|u_{\\mathbf{k}}^{n}\\rangle\\big[\\eta_{x,\\mathbf{k}}^{j}\\big]^{n},\n$$ \n\nwhere in the first (second) equation $n$ runs over occupied (unoccupied) bands. Under chiral symmetry, the Wannier sectors obey \n\n$$\n\\begin{array}{r}{\\hat{\\Pi}\\big|w_{x,\\mathbf{k}}^{\\mathrm{occ},j}\\big\\rangle=\\big|w_{x,\\mathbf{k}}^{\\mathrm{unocc},i}\\big\\rangle\\alpha_{\\Pi,\\mathbf{k}}^{i j}.}\\end{array}\n$$ \n\nUsing this expression, one arrives to the following relation for a Wilson-line element: \n\n$$\n\\big[\\tilde{\\mathcal{W}}_{{\\bf k}_{2}\\leftarrow{\\bf k}_{1}}^{\\nu_{x}}\\big]^{i j}=\\big[\\alpha_{\\Pi,{\\bf k}_{2}}^{\\dagger}\\big]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{{\\bf k}_{2}\\leftarrow{\\bf k}_{1}}^{\\eta_{x}}\\big]^{i^{\\prime}j^{\\prime}}\\big[\\alpha_{\\mathcal{T},{\\bf k}_{1}}\\big]^{j^{\\prime}j},\n$$ \n\nwhere the sewing matrices $\\alpha_{\\Pi,{\\bf k}}$ only Wilson connect lines eigenstates such that $\\nu_{x}=\\eta_{x}$ . In particular, the nested Wilson loop along $y$ obeys \n\n$$\n\\big[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}}\\big]^{i j}=[\\alpha_{\\Pi,\\mathbf{k}}^{\\dagger}]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\eta_{x}}\\big]^{i^{\\prime}j^{\\prime}}[\\alpha_{\\Pi,\\mathbf{k}}]^{j^{\\prime}j}.\n$$ \n\nThus, the Wilson-loop eigenvalues are related by \n\n$$\n\\left\\{e^{i2\\pi\\nu_{y}^{\\nu_{x},j}(k_{x})}\\right\\}=\\left\\{e^{i2\\pi\\nu_{y}^{\\eta_{x},j}(k_{x})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{y}^{\\nu_{x},j}(k_{x})\\right\\}=\\left\\{\\nu_{y}^{\\eta_{x},j}(k_{x})\\right\\}\\ \\mathrm{mod}\\ 1,\n$$ \n\nwhich implies that \n\n$$\np_{y}^{\\nu_{x}}(k_{x})\\overset{\\mathrm{chiral}}{=}p_{y}^{\\eta_{x}}(k_{x})\\mathrm{mod}1.\n$$ \n\nHence, the Wannier-sector polarization (D31) under chiral symmetry obeys \n\n$$\np_{y}^{\\nu_{x}}\\overset{\\mathrm{chiral}}{=}p_{y}^{\\eta_{x}}\\mathrm{mod}1.\n$$ \n\nSince the Hilbert space of the Hamiltonian at each $k_{x}$ is complete, and thus it has trivial topology, we also have \n\n$$\np_{y}^{\\nu_{x}}(k_{x})+p_{y}^{-\\nu_{x}}(k_{x})+p_{y}^{\\eta_{x}}(k_{x})+p_{y}^{-\\eta_{x}}(k_{x})=0\\mathrm{~mod}1,\n$$ \n\nwhich results in the relation for the Wannier-sector polarizations \n\n$$\np_{y}^{\\nu_{x}}+p_{y}^{-\\nu_{x}}+p_{y}^{\\eta_{x}}+p_{y}^{-\\eta_{x}}=0\\mathrm{~mod~}1.\n$$ \n\nNotice that (D125), along with (D123), is insufficient to quantize the Wannier-sector polarization. At most, we have \n\n$$\np_{y}^{\\nu_{x}}(k_{x})+p_{y}^{-\\nu_{x}}(k_{x})\\stackrel{\\mathrm{chiral}}{=}p_{y}^{\\eta_{x}}(k_{x})+p_{y}^{-\\eta_{x}}(k_{x})\\stackrel{\\mathrm{chiral}}{=}0\\mathrm{or}1/2,\n$$ \n\nwhich is compatible with (D113), since $p_{y}^{\\mathrm{occ}}(k_{x})=p_{y}^{\\nu_{x}}(k_{x})+$ $p_{y}^{-\\nu_{x}}(k_{x})$ and $p_{y}^{\\mathrm{unocc}}(k_{x})=p_{y}^{\\eta_{x}}(k_{x})+p_{y}^{-\\eta_{x}}(k_{x})$ . \n\n# 7. Constraints due to charge-conjugation symmetry \n\nFinally, we derive the constraints that charge-conjugation symmetry imposes on the Wilson loops $\\mathcal{W}_{x,{\\bf k}}$ and on the nested Wilson loops $\\dot{\\mathcal W}_{y,{\\bf k}}^{\\nu_{x}}$ . \n\n# a. On the Wilson loop over energy bands \n\nUnder charge-conjugation symmetry, the Bloch Hamiltonian obeys \n\n$$\n{\\hat{C}}h_{\\mathbf{k}}{\\hat{C}}^{-1}=-h_{-\\mathbf{k}}.\n$$ \n\nHere, we will treat $\\hat{C}$ as being antiunitary such that $\\hat{C}=\\hat{Q}K$ is the charge-conjugation operator, composed of a unitary matrix $\\hat{Q}$ and complex conjugation $K$ . The Wilson loop transforms as \n\n$$\nB_{C,\\mathbf{k}}\\mathcal{W}_{x,\\mathbf{k}}^{\\mathrm{occ*}}B_{C,\\mathbf{k}}^{\\dagger}=\\mathcal{W}_{-x,-\\mathbf{k}}^{\\mathrm{unocc}}=\\mathcal{W}_{x,-\\mathbf{k}}^{\\mathrm{unocc}\\dagger}.\n$$ \n\nThe sewing matrix $B_{\\mathbf{k}}^{m n}=\\langle u_{-\\mathbf{k}}^{m}|\\hat{C}|u_{\\mathbf{k}}^{n}\\rangle=\\langle u_{-\\mathbf{k}}^{m}|\\hat{Q}|u_{\\mathbf{k}}^{n*}\\rangle$ connects states at $\\mathbf{k}$ with states at $-\\mathbf{k}$ such that $\\epsilon_{n}(\\mathbf{k})=-\\epsilon_{m}(-\\mathbf{k})$ . Thus, for a nonzero $B_{\\mathbf{k}}^{m n}$ , if $m$ labels a state in the occupied band, $n$ labels a state in the unoccupied band, or vice versa. Let us denote $|\\nu\\rangle$ as the eigenstates for $\\mathscr{W}^{\\mathrm{occ}}$ and $|\\eta\\rangle$ as the eigenstates for $\\mathcal{W}^{\\mathrm{unocc}}$ . Likewise, let us denote the eigenvalues of $\\mathcal{W}^{\\mathrm{occ}}~(\\mathcal{W}^{\\mathrm{unocc}})$ as $e^{i2\\pi\\nu}~(e^{i2\\pi\\eta})$ . Equation (D129) implies that the Wannier centers obey \n\n$$\n\\left\\{\\nu_{x}^{i}(k_{y})\\right\\}\\stackrel{\\mathrm{CC}}{=}\\left\\{\\eta_{x}^{i}(-k_{y})\\right\\}\\mod1,\n$$ \n\nwhich implies that \n\n$$\np_{x}^{\\mathrm{occ}}(k_{y})\\stackrel{\\mathrm{CC}}{=}p_{x}^{\\mathrm{unocc}}(-k_{y})\\mod1\n$$ \n\nand \n\n$$\np_{x}^{\\mathrm{occ}}\\stackrel{\\mathrm{CC}}{=}p_{x}^{\\mathrm{unocc}}\\mod1.\n$$ \n\nHence, charge-conjugation symmetry relates the polarization of occupied bands with the polarization of unoccupied bands. Using (D132) and (D112), we conclude that \n\n$$\np_{x}^{\\mathrm{occ}}\\stackrel{\\mathrm{CC}}{=}p_{x}^{\\mathrm{unocc}}\\stackrel{\\mathrm{CC}}{=}0\\mathrm{or}1/2,\n$$ \n\ni.e., under charge-conjugation symmetry the polarization is quantized. \n\n# b. On the Wilson loop over Wannier sectors \n\nFrom Eq. (D129) it follows that $B_{C,\\mathbf{k}}|\\nu_{x,\\mathbf{k}}^{i*}\\rangle$ is an eigenstate of $\\mathscr{W}_{x,-\\mathbf{k}}^{\\mathrm{unocc}\\dagger}$ with eigenvalue $e^{-i2\\pi\\nu_{x}^{i}(k_{y})}$ . Thus, in the expansion \n\n$$\nB_{C,\\mathbf{k}}\\big|\\nu_{x,\\mathbf{k}}^{i*}\\big\\rangle=\\big|\\eta_{x,-\\mathbf{k}}^{j}\\big\\rangle\\alpha_{C,\\mathbf{k}}^{j i},\n$$ \n\nthe sewing matrix \n\n$$\n\\alpha_{C,{\\bf k}}^{j i}=\\left<\\eta_{x,-{\\bf k}}^{j}\\right|B_{C,{\\bf k}}\\right|\\nu_{x,{\\bf k}}^{i*})\n$$ \n\nhas $\\alpha_{C,{\\bf k}}^{j i}\\neq0$ only if $\\nu_{x}^{i}(k_{y})=\\eta_{x}^{j}(-k_{y})$ . Let us consider the Wannier sectors \n\n$$\n\\big|w_{x,\\mathbf{k}}^{\\mathrm{occ},j}\\big\\rangle=\\sum_{n=1}^{N_{\\mathrm{occ}}}\\big|u_{\\mathbf{k}}^{n}\\big\\rangle\\big[\\nu_{x,\\mathbf{k}}^{j}\\big]^{n},\n$$ \n\n$$\n|w_{x,\\mathbf{k}}^{\\mathrm{unocc},j}\\rangle=\\sum_{n=N_{\\mathrm{occ}}+1}^{N}|u_{\\mathbf{k}}^{n}\\rangle\\big[\\eta_{x,\\mathbf{k}}^{j}\\big]^{n},\n$$ \n\nwhere in the first (second) equation $n$ runs over occupied (unoccupied) bands. Under charge-conjugation symmetry, the Wannier sectors obey \n\n$$\n\\hat{C}\\left|w_{x,\\mathbf{k}}^{\\mathrm{occ},i}\\right>=\\left|w_{x,-\\mathbf{k}}^{\\mathrm{unocc},j}\\right>\\alpha_{C,\\mathbf{k}}^{j i}.\n$$ \n\nUsing this expression, one arrives to the following relation for the nested Wilson loop along $y$ : \n\n$$\n\\begin{array}{r}{\\left[\\tilde{\\mathcal{W}}_{y,\\mathbf{k}}^{\\nu_{x}*}\\right]^{i j}=[\\alpha_{C,\\mathbf{k}}^{\\dagger}]^{i i^{\\prime}}\\big[\\tilde{\\mathcal{W}}_{-y,-\\mathbf{k}}^{\\eta_{x}}\\big]^{i^{\\prime}j^{\\prime}}[\\alpha_{C,\\mathbf{k}}]^{j^{\\prime}j}.}\\end{array}\n$$ \n\nThus, the Wilson-loop eigenvalues are related by \n\n$$\n\\left\\{e^{i2\\pi\\nu_{y}^{\\nu_{x},j}(k_{x})}\\right\\}\\stackrel{\\mathrm{CC}}{=}\\left\\{e^{i2\\pi\\nu_{y}^{\\eta_{x},j}(-k_{x})}\\right\\}\n$$ \n\nor \n\n$$\n\\left\\{\\nu_{y}^{\\nu_{x},j}(k_{x})\\right\\}=\\left\\{\\nu_{y}^{\\eta_{x},j}(-k_{x})\\right\\}\\ \\mathrm{mod}\\ 1.\n$$ \n\nThis implies that \n\n$$\np_{y}^{\\nu_{x}}(k_{x})\\stackrel{\\mathrm{CC}}{=}p_{y}^{\\eta_{x}}(-k_{x})\\mathrm{mod}1.\n$$ \n\nHence, the Wannier-sector polarization (D31), under chargeconjugation symmetry, obeys \n\n$$\np_{y}^{\\nu_{x}}\\overset{\\mathrm{CC}}{=}p_{y}^{\\eta_{x}}\\mathrm{~mod~}1.\n$$ \n\nUsing this expression along with (D126), we also have the relations \n\n$$\np_{y}^{\\nu_{x}}+p_{y}^{-\\nu_{x}}\\stackrel{\\mathrm{CC}}{=}p_{y}^{\\eta_{x}}+p_{y}^{-\\eta_{x}}\\stackrel{\\mathrm{CC}}{=}0\\mathrm{or}1/2.\n$$ \n\n# APPENDIX E: PLAQUETTE FLUX AND ITS RELATION TO THE COMMUTATION OF REFLECTION OPERATORS \n\nIn this Appendix, we study the conditions under which reflection symmetry is compatible with nonzero flux on a plaquette. The existence of reflection symmetry (up to a gauge transformation) and the commutation relations of the $x$ and $y$ reflections depend on the value of the flux. This is important in the model for a quadrupole insulator (6.29) due to the requirement that reflection operators must not commute in order to have gapped Wannier bands (see Sec. VI C). Furthermore, the cases in which plaquettes have 0 or $2\\pi$ fluxes are gapless at half-filling, and therefore are not useful in the construction of a 2D quadrupole Hamiltonian. On the other hand, plaquettes with $\\pi$ flux are gapped at half-filling and obey $[\\dot{M}_{x},\\dot{M}_{y}]\\neq0$ . Thus, they can be used in the construction of a nontrivial quadrupole model built from arrays of such plaquettes. Indeed, the quadrupole insulator (6.29) is built exactly this way using plaquettes with $\\pi$ flux. \n\n![](images/9c5c8b878eba6dad34dc9993b207cde41fba4db544e7ed041194f51426ec55d6.jpg) \nFIG. 48. Hopping configurations on a plaquette with four sites. Dotted lines indicate a flipped sign compared to solid lines. (a)–(d) Have either 0 or $2\\pi$ flux, while (e) and (f) are different configurations with $\\pi$ flux; (g) is a generic configuration with flux $\\Phi$ . \n\nLet us start with the simple square configuration in Fig. 48(a), which has no flux. Its Hamiltonian is \n\n$$\nH_{0}=\\left(\\begin{array}{l l l l}{0}&{1}&{1}&{0}\\\\ {1}&{0}&{0}&{1}\\\\ {1}&{0}&{0}&{1}\\\\ {0}&{1}&{1}&{0}\\end{array}\\right)\n$$ \n\nor, more compactly, $H_{0}=\\mathbb{I}\\otimes\\sigma^{x}+\\tau^{x}\\otimes\\mathbb{I}$ . This plaquette has reflection symmetries that exchange left and right $\\dot{M}_{x}^{0}=$ $\\mathbb{I}\\otimes\\sigma^{x}$ and up and down $\\hat{M}_{y}^{0}=\\tau^{x}\\otimes\\mathbb{I}$ . These operators multiply to give the inversion operator $\\hat{\\mathcal{T}}=\\hat{M}_{x}^{0}\\hat{M}_{y}^{0}=\\tau^{x}\\otimes\\sigma^{x}$ . In this case, we have $[\\hat{M}_{x}^{0},\\hat{M}_{y}^{0}]=0$ . Hence, $\\hat{\\mathcal{I}}^{2}=$ Mˆ 0Mˆ 0Mˆ 0Mˆ 0 (Mˆ 0)2(Mˆ 0)2 1. This system has energies $\\{-2,\\stackrel{\\sim}{0},0,+2\\}$ and therefore is gapless at half-filling. \n\nNow, let us consider configurations with $\\pi$ flux. When the flipped bond is between sites 1 and 2 [see Fig. 48(b)] we have \n\n$$\nH_{12}=-\\tau^{z}\\otimes\\sigma^{x}+\\tau^{x}\\otimes\\mathbb{I}.\n$$ \n\nThe energies of $H_{12}$ are $\\{-1,-1,+1,+1\\}$ , and hence this system is gapped at half-filling. This system has a reflection symmetry in the $x$ direction, but does not have an exact reflection symmetry in the $y$ direction; it only has a reflection symmetry times (up to) a gauge transformation. This is because, although the magnetic field is invariant under reflection, the vector potential is not, and we must multiply a pair of the second-quantized operators by a $^{-1}$ in order to recover the symmetry. This $^{-1}$ is the gauge transformation. As such, the reflection operator that sends $x\\to-x$ does not change, i.e., $\\hat{M}_{x}^{12}=\\mathbb{I}\\otimes\\overset{\\cdot}{\\sigma^{x}}$ . However, the reflection operator in the y direction now has additional signs and we have $\\hat{M}_{y}^{12}=$ $\\tau^{x}\\otimes\\sigma^{z}=\\hat{M}_{y}^{0}(\\mathbb{I}\\otimes\\sigma^{z})$ where ${\\mathcal G}=(\\mathbb I\\otimes\\sigma^{z})$ is one choice for the gauge transformation [another would be ${\\mathcal G}=-(\\mathbb I\\otimes\\sigma^{z})]$ . This gauge transformation multiplies either $c_{1}^{\\dagger}$ and $c_{3}^{\\dagger}$ or $c_{2}^{\\dagger}$ and $c_{4}^{\\dagger}$ by a minus sign depending on our choice of $\\mathcal{G}$ , and leaves the other operators unchanged. In this case, the commutation relations have now changed to $\\{\\hat{M}_{x}^{12},\\hat{M}_{y}^{12}\\}=0$ . \n\nLet us consider another $\\pi$ -flux configuration such that the flipped bond is between sites 1 and 3, as in Fig. 48(c). The Hamiltonian is \n\n$$\nH_{13}=\\mathbb{I}\\otimes\\sigma^{x}-\\tau^{x}\\otimes\\sigma^{z}.\n$$ \n\nThis has reflection in $y$ , but reflection only up to gauge transformation in the $x$ direction. The gauge transformation in this case is $\\mathcal{G}=\\tau^{z}\\otimes\\mathbb{I}$ . The reflection operators are $\\hat{M}_{x}^{13}=$ $\\tau^{z}\\otimes\\sigma^{x}$ and $\\hat{M}_{y}^{13}=\\tau^{x}\\otimes\\mathbb{I}$ . These also have a nonvanishing commutator. \n\nLet us see what happens if we have $2\\pi$ flux through the plaquette. If the bonds are arranged as Figs. 48(d) and 48(e), the system has reflection symmetries in both the $x$ and $y$ directions with reflection operators $\\hat{M}_{x}^{0}$ and $\\hat{M}_{y}^{0}$ as above, which commute. However, there is another option where the bonds are as in Fig. 48(f). In this case, both reflection symmetries are only good up to a gauge transformation and the operators are $\\hat{M}_{x}^{2\\pi}=\\hat{M}_{x}^{1\\bar{3}}$ and $\\check{M}_{y}^{2\\pi}=\\hat{M}_{y}^{12}$ . However, the two operators commute. Hence, only gauge transformations associated with odd numbers of $\\pi$ flux lead to noncommuting operators in the spinless case. \n\nGeneral formulation. Let us now consider the general case shown in Fig. $48(\\mathrm{g)}$ . Let us take the general Hamiltonian for a square with flux $\\Phi$ : \n\n$$\nH_{\\Phi}=\\left({\\begin{array}{c c c c}{0}&{e^{i\\varphi_{12}}}&{e^{-i\\varphi_{13}}}&{0}\\\\ {e^{-i\\varphi_{12}}}&{0}&{0}&{e^{i\\varphi_{24}}}\\\\ {e^{i\\varphi_{13}}}&{0}&{0}&{e^{-i\\varphi_{34}}}\\\\ {0}&{e^{-i\\varphi_{24}}}&{e^{i\\varphi_{34}}}&{0}\\end{array}}\\right),\n$$ \n\nwhere the total flux through a plaquette is $\\Phi=\\varphi_{12}+\\varphi_{24}+$ $\\varphi_{34}+\\varphi_{13}$ . Now, let us consider the reflection operators $\\hat{M}_{x}=$ $\\hat{M}_{x}^{0}\\mathcal G_{x}$ and $\\hat{M}_{y}=\\hat{M}_{y}^{0}\\mathcal{G}_{y}$ where $\\hat{M}_{x,y}^{0}$ are as above, i.e., the reflection operators with vanishing flux and \n\n$$\n\\mathcal{G}_{x,y}=\\mathrm{diag}[e^{i\\varphi_{1x,y}},e^{i\\varphi_{2x,y}},e^{i\\varphi_{3x,y}},e^{i\\varphi_{4x,y}}]\n$$ \n\nare the gauge choices to account for the flux $\\Phi$ . By brute force evaluation we can check the conditions under which $[H_{\\phi},\\hat{M}_{x,y}]=0$ . The condition, in both cases, reduces to the constraint $1-e^{2i\\Phi}=0$ , which is solved by $\\Phi=n\\pi$ for some integer $n$ . This makes physical sense since reflection $M_{x}$ or $M_{y}$ flips a magnetic field in the $z$ direction (i.e., the flux threading the plaquette), however, flipping a magnetic flux of $0,\\pi$ is equivalent to 0, $-\\pi$ through a gauge transformation. \n\nFinally, we consider the commutator between the reflection operators. By brute force evaluation of the commutator, one can show that if $1-e^{i\\Phi}=0$ the commutator vanishes. Otherwise, if $\\Phi$ is an odd multiple of $\\pi$ we find $[\\hat{M}_{x},\\hat{M}_{y}]=2\\hat{\\mathcal{T}}$ where $\\hat{\\mathcal{I}}$ is the inversion operator. Furthermore, one can show that $\\hat{\\mathcal{T}}^{2}=e^{i\\alpha}e^{i\\Phi}\\mathbb{I}$ where $\\alpha$ is a global phase that depends on the gauge choice, and $e^{i\\Phi}$ is $\\pm1$ for $\\Phi$ an even/odd multiple of $\\pi$ . We find $\\alpha=3\\varphi_{12}-\\varphi_{13}+\\varphi_{24}-\\varphi_{34}$ . \n\n# APPENDIX F: CONDITIONS FOR GAPPED WANNIER BANDS AND SUBSEQUENT QUANTIZED WANNIER-SECTOR POLARIZATION BEYOND THE $N_{\\mathrm{occ}}=2$ CASE \n\nIn Sec. VI C we established that a crystal with $N_{\\mathrm{occ}}=2$ occupied bands having reflection and inversion symmetries has gapless Wannier bands if the reflection operators commute. Here, we generalize this study to the cases in which $N_{\\mathrm{occ}}=4$ , $N_{\\mathrm{occ}}=4n$ , and $N_{\\mathrm{occ}}=4n+2$ . The cases with odd $N_{\\mathrm{occ}}$ do not need to be considered because they automatically generate gapless Wannier spectra. \n\n# 1. $N_{\\mathrm{occ}}=4\\colon$ Gapped Wannier bands with trivial Wannier polarizations \n\nUnlike the $N_{\\mathrm{occ}}=2$ case, if four energy bands are occupied, it is possible to meet the conditions of having $\\hat{M}_{x}$ and $\\hat{M}_{y}$ obeying $[\\hat{M}_{x},\\hat{M}_{y}]=0$ , as well as $\\hat{\\mathcal{T}}=\\hat{M}_{x}\\hat{M}_{y}$ , such that their eigenvalues over the occupied bands come in pairs $\\left(+-\\right)$ at any high-symmetry point. This occurs only for the choice of states $(|++\\rangle,|+-\\rangle,|-+\\rangle,|--\\rangle)$ , where $m_{x}$ and $m_{y}$ in $|m_{x},m_{y}\\rangle$ are the eigenvalues of the reflection operators $\\hat{M}_{x}$ and $\\hat{M}_{y}$ , respectively. In that case, the Wannier bands at the high-symmetry points are gapped. Using this basis, the sewing matrices for $\\check{M}_{x},\\hat{M}_{y}$ , and $\\breve{\\hat{\\boldsymbol{\\tau}}}$ at the high-symmetry points $\\mathbf{k}^{*}=$ $\\mathbf{\\Gamma}_{\\Gamma,\\mathbf{X},\\mathbf{Y},\\mathbf{M}}$ take the forms \n\n$$\n\\begin{array}{r l}&{B_{M_{x},\\mathbf{k}^{*}}=\\tau^{z}\\otimes\\mathbb{I},}\\\\ &{B_{M_{y},\\mathbf{k}^{*}}=\\mathbb{I}\\otimes\\sigma^{z},}\\\\ &{B_{\\mathcal{T},\\mathbf{k}^{*}}=B_{M_{x},\\mathbf{k}^{*}}B_{M_{y},\\mathbf{k}^{*}}=\\tau^{z}\\otimes\\sigma^{z}.}\\end{array}\n$$ \n\nThese matrices are useful because they represent the symmetries that the Wannier Hamiltonian must have at the highsymmetry points [see Eq. (4.40)]. For example, $H_{\\mathcal{W}_{x}}(\\mathbf{k})$ must satisfy \n\n$$\n\\begin{array}{r l r}&{}&{\\left[H_{\\mathcal{W}_{x}}({\\bf k}^{*}),B_{M_{y},{\\bf k}^{*}}\\right]=\\left\\{H_{\\mathcal{W}_{x}}({\\bf k}^{*}),B_{M_{x},{\\bf k}^{*}}\\right\\}\\quad}\\\\ &{}&{=\\left\\{H_{\\mathcal{W}_{x}}({\\bf k}^{*}),B_{\\mathcal{T},{\\bf k}^{*}}\\right\\}=0.}\\end{array}\n$$ \n\nSimilarly, $H_{\\mathcal{W}_{y}}(\\mathbf{k})$ must satisfy \n\n$$\n\\begin{array}{r l r}&{}&{\\left[H_{\\mathcal{W}_{y}}({\\bf k}^{*}),B_{M_{x},{\\bf k}^{*}}\\right]=\\left\\{H_{\\mathcal{W}_{y}}({\\bf k}^{*}),B_{M_{y},{\\bf k}^{*}}\\right\\}\\quad}\\\\ &{}&{=\\left\\{H_{\\mathcal{W}_{y}}({\\bf k}^{*}),B_{\\mathcal{T},{\\bf k}^{*}}\\right\\}=0.}\\end{array}\n$$ \n\nImposing these symmetries on all 16 Hermitian matrices $\\tau^{i}\\otimes$ $\\sigma^{j}$ , for $i,j=0,x,y,z$ (where $\\tau,\\sigma$ are Pauli matrices and $\\tau^{0}=$ $\\sigma^{0}=\\mathbb{I}$ ), the most general form for the Wannier Hamiltonians is \n\n$$\n\\begin{array}{r l}&{H_{\\mathcal{W}_{x}}(\\mathbf{k}^{*})=\\delta_{1}\\tau^{x}\\otimes\\sigma^{z}+\\delta_{2}\\tau^{x}\\otimes\\mathbb{I}+\\delta_{3}\\tau^{y}\\otimes\\sigma^{z}+\\delta_{4}\\tau^{y}\\otimes\\mathbb{I},}\\\\ &{H_{\\mathcal{W}_{y}}(\\mathbf{k}^{*})=\\beta_{1}\\tau^{z}\\otimes\\sigma^{x}+\\beta_{2}\\mathbb{I}\\otimes\\sigma^{x}+\\beta_{3}\\tau^{z}\\otimes\\sigma^{y}+\\beta_{4}\\mathbb{I}\\otimes\\sigma^{y},}\\end{array}\n$$ \n\nwhere $\\delta_{i}$ and $\\beta_{i}$ , for $i={1,2,3,4}$ , are coefficients which can vary between the different high-symmetry points. The Wannier energies of $H_{\\mathcal{W}_{x}}$ and $H_{\\mathcal{W}_{y}}$ are, respectively, \n\n$$\n\\begin{array}{r l r}&{}&{\\theta_{x}=2\\pi\\nu_{x}=\\left\\{\\pm\\sqrt{(\\delta_{1}-\\delta_{2})^{2}+(\\delta_{3}-\\delta_{4})^{2}},\\right.}\\\\ &{}&{\\left.\\pm\\sqrt{(\\delta_{1}+\\delta_{2})^{2}+(\\delta_{3}+\\delta_{4})^{2}},\\right.}\\\\ &{}&{\\theta_{y}=2\\pi\\nu_{y}=\\left\\{\\pm\\sqrt{(\\beta_{1}-\\beta_{2})^{2}+(\\beta_{3}-\\beta_{4})^{2}},\\right.}\\\\ &{}&{\\left.\\pm\\sqrt{(\\beta_{1}+\\beta_{2})^{2}+(\\beta_{3}+\\beta_{4})^{2}}\\right.}\\end{array}\n$$ \n\nmod $2\\pi$ . By direct computation, we find that the eigenstates of the upper (or lower) bands $\\nu_{x}$ of $H_{\\mathcal{W}_{x}}$ have $(+-)$ eigenvalues under $B_{M_{y},\\mathbf{k}^{*}}$ , for any values of the $\\delta$ coefficients. Hence, the $\\alpha_{M_{y},{\\bf k}^{*}}$ sewing matrix at each high-symmetry point has $\\left(+-\\right)$ eigenvalues and, thus, the eigenvalues of the Wilson loop over Wannier band $\\nu_{x}$ come in pairs $(\\nu_{y}^{\\nu_{x}}(k_{x}),-\\nu_{y}^{\\nu_{x}}(k_{x}))$ at $k_{x}=0,\\pi$ . Now, since it is not possible to continuously deform the bands $(\\nu_{y}^{\\nu_{x}}(k_{x}),-\\nu_{y}^{\\nu_{x}}(k_{x}))$ at $k_{x}=0,\\pi$ to $[0,\\frac{1}{2}]$ or $[\\textstyle{\\frac{1}{2}},0]$ at any other point in $k_{x}$ without breaking reflection symmetry along $y$ , it follows that the eigenvalues of the Wilson loop over Wannier band $\\nu_{x}$ come in pairs $(\\nu_{y}^{\\nu_{x}}(k_{x}),-\\nu_{y}^{\\nu_{x}}(k_{x}))$ at all $k_{x}\\in(-\\pi,\\pi]$ , which results in a vanishing Wannier-sector polarization of Eq. (6.16). For $H_{\\mathcal{W}_{y}}$ , a similar statement is true. Hence, the quadrupole moment vanishes when the reflection operators commute. \n\n# 2. $N_{\\mathrm{occ}}=4n$ : Generalizing the $N_{\\mathrm{occ}}=4$ case \n\nNow, let us generalize the previous argument. Suppose we have $4n$ occupied bands and the $M_{x},M_{y}$ , and $\\boldsymbol{\\mathcal{T}}$ eigenvalues all come in $(+-)$ pairs at each high-symmetry point. We can arrange the basis of occupied energy bands such that \n\n$$\n\\begin{array}{r c l}{{}}&{{}}&{{B_{M_{x},\\mathbf{k}^{*}}=\\tau^{z}\\otimes\\mathbb{I}_{2n},}}\\\\ {{}}&{{}}&{{B_{M_{y},\\mathbf{k}^{*}}=\\mathbb{I}_{2n}\\otimes\\sigma^{z},}}\\\\ {{}}&{{}}&{{B_{\\mathcal{T},\\mathbf{k}^{*}}=\\mu^{z}\\otimes\\mathbb{I}_{n}\\otimes\\sigma^{z}.}}\\end{array}\n$$ \n\nCrucially, each Wannier Hamiltonian at a high-symmetry point has to commute with one reflection sewing matrix, and anticommute with the other since one reflection preserves the contour and the other flips it. Consider $H_{\\mathcal{W}_{x}}(\\mathbf{k}^{*})$ . It must satisfy $[H_{\\mathcal{W}_{x}}(\\mathbf{k}^{*}),B_{M_{y},\\mathbf{k}^{*}}]=\\{H_{\\mathcal{W}_{x}}(\\mathbf{k}^{*}),B_{M_{x},\\mathbf{k}^{*}}\\}$ . We can label an eigenstate of $H_{\\mathcal{W}_{x}}(\\mathbf{k}^{*})$ as $|\\nu_{x}^{j},b_{m_{y}}\\rangle$ , where $\\nu_{x}^{j}$ is its Wannier eigenvalue, and $b_{m_{y}}$ is the eigenvalue under $B_{M_{y},\\mathbf k^{*}}$ . For each $|\\nu_{x}^{j},b_{m_{y}}\\rangle$ we have another state $B_{M_{x},\\mathbf{k}^{*}}|\\nu_{x}^{j},b_{m_{y}}\\rangle$ which has opposite Wannier eigenvalue, but the same $b_{m_{y}}$ . This is because $M_{x}$ complex conjugates the Wannier eigenvalue, but since the Wannier Hamiltonian commutes (by assumption) with $M_{y}$ , it leaves $b_{m_{y}}$ invariant. \n\nNow, we can see from the form of our sewing matrices in Eq. (F6) that there are an equal, and even, number of $\\pm$ eigenvalues ( $4n$ bands means $2n$ each of $\\pm$ , which is a necessary and direct result of our need for gapped Wannier bands. This means that each of the gapped Wannier sectors has an equal number of $\\pm$ reflection sewing eigenvalues. \n\nHence, since the reflection-sewing eigenvalues of a Wannier sector determine its polarization as indicated in Table III, we find that the Wannier centers of the projected Wannier sector must come in complex-conjugate pairs, and hence its polarization is trivial. This result can be applied mutatis mutandis for the other Wilson-loop Hamiltonian ${\\cal H}_{W_{y}}$ . Since the nested Wilson loops must be trivial in both directions, the quadrupole is trivial. \n\n# 3. $N_{\\mathrm{occ}}=4n+2$ : Gapless Wannier bands \n\nThis case mirrors the $N_{\\mathrm{occ}}=2$ case. In order to have gapped Wannier bands for any set of $4n+2$ occupied energy bands, we must choose an array of occupied states such that there are $2n+1$ eigenvalues $+1$ and $2n+1$ eigenvalues $^{-1}$ of both $M_{x}$ and $M_{y}$ . After making this choice, we can try to arrange them such that the products of the eigenvalues, i.e., the inversion eigenvalues, also come in $\\pm$ pairs, so that the Wannier bands are gapped. To achieve that, we also need $2n+1$ inversion eigenvalues $+1$ and $2n+1$ inversion eigenvalues $^{-1}$ . No matter what arrangement we choose, the number of inversion eigenvalues $+1$ and the number of inversion eigenvalues $^{-1}$ is always an even number and cannot be $2n+1$ . Hence, we cannot ever find exactly matched pairs of $\\pm$ inversion eigenvalues. An alternative way of stating this is that we can find exactly matched pairs for $4n$ bands, but the remaining eigenvalues reduce to the two-band problem that we have already shown is gapless. \n\n![](images/232caf1ae6c08d6dfa01e175b8c1f99eac69c2c84d5ee8e4e88f4135bc19306f.jpg) \nFIG. 49. Energy bands of Hamiltonian (H1), which breaks all symmetries in Eq. (6.29) except the reflection symmetries $M_{x},M_{y}$ , which have anticommuting reflection operators. The energies are degenerate at the high-symmetry points $\\mathbf{k}_{*}=\\Gamma,\\mathbf{X},\\mathbf{Y},\\mathbf{M}$ . In this simulation, $\\lambda_{x}=\\lambda_{y}=1$ , $\\gamma_{x}=\\gamma_{y}=0.5$ , $W=0.75$ . \n\nIn conclusion, we have shown that with commuting reflection operators, the Wannier spectrum is either gapless or has trivial topology. \n\n# APPENDIX G: PROOF THAT NONCOMMUTINGREFLECTION OPERATORS PROTECT THE ENERGYDEGENERACY AT THE HIGH-SYMMETRY POINTSOF THE BZ \n\nThe Hamiltonian for the quadrupole insulator (6.29) is symmetric under reflections in $x$ and $y$ , where the reflection operators obey $[\\hat{M}_{x},\\hat{M}_{y}]\\neq0$ . At the high-symmetry points of the BZ, $\\mathbf{k}_{*}=\\Gamma,\\mathbf{X},\\mathbf{Y}$ , and M, the Hamiltonian commutes with both reflection operators \n\n$$\n[\\hat{M}_{j},h^{q}({\\bf k}_{*})]=0\n$$ \n\nfor $j=x,y$ . Thus, at these points of the BZ there are two natural bases that satisfy \n\n$$\n\\hat{M}_{x}|u_{\\mathbf{k}_{*}}^{i}\\rangle=m_{x}^{i}|u_{\\mathbf{k}_{*}}^{i}\\rangle,\\quad\\hat{M}_{y}|v_{\\mathbf{k}_{*}}^{i}\\rangle=m_{y}^{i}|v_{\\mathbf{k}_{*}}^{i}\\rangle,\n$$ \n\nwhere $i=1,2$ labels the energy states. \n\nIn the particular case of the reflection operators (6.31) of the quadrupole Hamiltonian (6.29), which obey \n\n$$\n\\{\\hat{M}_{x},\\hat{M}_{y}\\}=0,\n$$ \n\nwe can consider labeling the energy bands at the $\\mathbf{k}_{*}$ points according to their $\\hat{M}_{x}$ reflection eigenvalues, so that \n\n$$\n\\begin{array}{r}{h^{q}({\\bf k}_{*})\\big|u_{{\\bf k}_{*}}^{n}\\big\\rangle=\\epsilon^{n}({\\bf k}_{*})\\big|u_{{\\bf k}_{*}}^{n}\\big\\rangle,~}\\\\ {\\hat{M}_{x}\\big|u_{{\\bf k}_{*}}^{n}\\big\\rangle=m_{x}^{n}({\\bf k}_{*})\\big|u_{{\\bf k}_{*}}^{n}\\big\\rangle.~}\\end{array}\n$$ \n\nPicking $\\vert u_{\\mathbf{k}_{\\ast}}^{n}\\rangle$ to be a simultaneous eigenstate of $h^{q}(\\mathbf{k}_{*})$ and $\\hat{M}_{x}$ is possible since $[{\\hat{M}}_{x},h^{q}({\\bf k}_{*})]=0$ . Then, we have \n\n$$\n\\hat{M}_{x}\\hat{M}_{y}\\big|u_{\\mathbf{k}_{*}}^{n}\\big\\rangle=-\\hat{M}_{y}\\hat{M}_{x}\\big|u_{\\mathbf{k}_{*}}^{n}\\big\\rangle=-m_{x}^{n}(\\mathbf{k}_{*})\\hat{M}_{y}\\big|u_{\\mathbf{k}_{*}}^{n}\\big\\rangle,\n$$ \n\nso, for every eigenstate $\\vert u_{\\mathbf{k}_{*}}^{n}\\rangle$ with reflection eigenvalue $m_{x}^{n}(\\mathbf{k}_{*})$ there is another eigenstate $\\hat{M}_{y}|u_{\\mathbf{k}_{*}}^{n}\\rangle$ with eigenvalue $-m_{x}^{n}(\\mathbf{k}_{*})$ . The energy of this eigenstate is \n\n$$\nh^{q}(\\mathbf{k}_{*})\\hat{M}_{y}\\big|u_{\\mathbf{k}_{*}}^{n}\\big\\rangle=\\hat{M}_{y}h^{q}(\\mathbf{k}_{*})\\big|u_{\\mathbf{k}_{*}}^{n}\\big\\rangle=\\epsilon^{n}(\\mathbf{k}_{*})\\hat{M}_{y}\\big|u_{\\mathbf{k}_{*}}^{n}\\big\\rangle,\n$$ \n\ni.e., it is degenerate in energy to $\\vert u_{\\mathbf{k}_{*}}^{n}\\rangle$ . \n\n![](images/589bb8b57b2738830ba0607cb65d704b1f3611334dd5a1c89c6d32872905ccd8.jpg) \nFIG. 50. Quadrupole with Hamiltonian (H1), which breaks charge-conjugation symmetry due to the term proportional to $W$ . (a) Lowest 100 energies for system with open boundaries as a function of perturbation strength $W$ . The lattice has 20 sites per side. (b) Edge polarization as a function of perturbation strength $W$ . (c) Electron density of a system with $24\\times24$ unit cells, at $W=1.0$ . The corner charge is $\\pm0.498$ . (d) The same simulation as in (c) but with no symmetry-breaking perturbation $W=0.0$ . The corner charge is $\\pm0.499$ . In (b)–(d) a value of $\\delta=10^{-3}$ was added to choose the sign of the quadrupole. In these simulations, $\\lambda=1$ , $\\gamma=0.1$ . \n\n# APPENDIX H: PERTURBATIONS ON THE QUADRUPOLE HAMILTONIAN \n\nIn Sec. VI B, we mention that the Wannier-sector polarizations (6.16), and consequently the quadrupole invariant (6.47), are quantized in the presence of reflection symmetries. The analytic proofs of these assertions are in Appendix D. In this section we show results of simulations in which all symmetries, other than the noted reflection symmetries, are broken. In particular, we show that breaking charge-conjugation symmetry still leaves the corner charges and edge polarizations quantized. The Hamiltonian we are considering is \n\n$$\n\\begin{array}{r l r}{\\lefteqn{h=h^{q}({\\bf k})+W[\\cos(k_{x})R_{e,e}+\\sin(k_{x})R_{o,e}}}\\\\ &{}&{+\\cos(k_{y})R_{e,e}+\\sin(k_{y})R_{e,o}],}\\end{array}\n$$ \n\nwhere $h^{q}(\\mathbf{k})$ is the quadrupole Hamiltonian defined in Eq. (6.29), which is in the topological phase for $\\delta=0$ , and $R_{e,e},R_{e,o}$ , and $R_{o,e}$ are random $4\\times4$ matrices that obey \n\n$$\n\\begin{array}{r}{[R_{e,i},\\hat{M}_{x}]=0,\\quad\\{R_{o,e},\\hat{M}_{x}\\}=0,}\\\\ {{[}R_{i,e},\\hat{M}_{y}]=0,\\quad\\{R_{e,o},\\hat{M}_{y}\\}=0}\\end{array}\n$$ \n\nfor ${i=e,o}$ . Here, $\\hat{M}_{x}$ and $\\hat{M}_{y}$ are the reflection operators (6.31). These conditions ensure that reflection symmetries along $x$ and $y$ are preserved while breaking all other symmetries. In Fig. 50(a), we show the energies as a function of the perturbation strength $W$ for a system with open boundaries. The lack of charge-conjugation symmetry is evident in the asymmetry in the spectrum around zero energy. The in-gap modes, however, remain at an energy close to zero because they are highly localized at the corners, and the perturbation does not include onsite energies, rather, it includes nearest-neighbor hopping terms. We also see in Fig. 50(a) that the energy gap is maintained at least for values $00$ and $m_{y}>0$ intersect is in the quadrupole phase (purple region). The zero-energy corner state is localized on the corner shown by the black dot. (b) Probability density function of the zero-energy state localized at the corner for the configuration of domains shown in (a) for an insulator with $20\\times20$ sites. The simulation uses Hamiltonian (J1) with parameters $\\gamma_{x}=-0.01$ for $x\\in[0,9]$ , $\\gamma_{x}=-1.5$ for $x\\in$ [10,20] and $\\gamma_{y}=-0.01$ for $y\\in[0,9]$ , $\\gamma_{y}=-1.5$ for $y\\in[10,20]$ . \n\nBy these sets of calculations of Abelian Wilson loops (i.e., Berry phases), we have thus determined that both Wanniersector polarizations are nontrivial, and thus there is a nontrivial quadrupole moment of $\\frac{1}{2}$ in this phase, as per Eq. (6.47). \n\n# APPENDIX J: DERIVATION OF THE CORNER-LOCALIZED ZERO-ENERGY STATE FROM THE LOW-ENERGY EDGE HAMILTONIAN \n\nWe claimed that the protected topological corner state in the quadrupole model is a simultaneous eigenstate of both edge Hamiltonians along the $x$ and $y$ edges. To demonstrate this, let us begin with our lattice Hamiltonian (6.29) with $\\lambda=1$ : \n\n$$\n\\begin{array}{r}{h^{q}({\\bf k})=\\sin k_{x}\\Gamma_{3}+(\\gamma_{x}+\\cos k_{x})\\Gamma_{4}}\\\\ {+\\sin k_{y}\\Gamma_{1}+(\\gamma_{y}+\\cos k_{y})\\Gamma_{2}.}\\end{array}\n$$ \n\nTo simplify the present discussion, we will solve a continuum version of the Hamiltonian by assuming that $\\gamma_{x}=-1+m_{x}$ and $\\gamma_{y}=-1+m_{y}$ for $m_{x,y}$ small and positive (negative) for the topological (trivial) phase. We can take a continuum limit, or equivalently a $k\\cdot p$ expansion about $(k_{x},k_{y})=0$ , to find the Hamiltonian \n\n$$\n\\begin{array}{r}{H=k_{x}\\Gamma_{3}+m_{x}\\Gamma_{4}+k_{y}\\Gamma_{1}+m_{y}\\Gamma_{2}.}\\end{array}\n$$ \n\nWe now use this Hamiltonian to solve for the states localized on the $x$ edge, and then project the Hamiltonian into these states to form the $x$ -edge Hamiltonian, from which we can then calculate the corner states. We will treat the $x$ edge as a domain wall where $m_{x}$ steps from positive (inside the topological phase) to negative (outside the topological phase), and the $y$ edge as a domain wall where $m_{y}$ steps from positive to negative, as shown in Fig. 51. We use the ansatz $\\Psi(x,k_{y})=f(x)\\Phi_{x}(k_{y})$ for the wave function localized at the $x$ edge in the absence of $y$ edges. In this ansatz, $f(x)$ is a scalar function of $x$ and $\\Phi_{x}(k_{y})$ is a spinor which depends on $k_{y}$ . By inserting this ansatz into the Schrödinger equation with \n\nHamiltonian (J2) and dividing by $f(x)$ we have \n\n$$\n\\begin{array}{l}{\\displaystyle\\left(-i\\frac{\\partial_{x}f(x)}{f(x)}\\Gamma_{3}+m_{x}(x)\\Gamma_{4}\\right)\\Phi_{x}(k_{y})}\\\\ {\\displaystyle\\qquad+(k_{y}\\Gamma_{1}+m_{y}\\Gamma_{2})\\Phi_{x}(k_{y})=\\epsilon\\Phi_{x}(k_{y}),}\\end{array}\n$$ \n\nwhere we have replaced $k_{x}\\rightarrow-i\\partial_{x}$ , and $\\epsilon$ is the energy. Since the first term in parentheses has all the dependence on $x$ , Eq. (J3) only has a solution if the first term is a constant. In particular, we choose that constant to be zero (a different value only redefines the zero-point energy of the Hamiltonian), \n\n$$\n(-i\\partial_{x}\\Gamma_{3}+m_{x}(x)\\Gamma_{4})f(x)\\Phi_{x}(k_{y})=0.\n$$ \n\nThis has the solution $\\begin{array}{r}{f(x)=C\\exp[\\int_{0}^{x}m_{x}(x^{\\prime})d x^{\\prime}]}\\end{array}$ , with normalization constant $C$ . The matrix equation that results from solving (J4) can be simplified to $(\\mathbb{I}-\\tau^{z}\\otimes\\sigma^{z})\\Phi_{x}=0$ , from which follows that $\\Phi_{x}$ is a positive eigenstate of $\\tau^{z}\\otimes\\sigma^{z}$ , i.e., $\\Phi_{x1}=\\left(1,0,0,0\\right)$ or $\\Phi_{x2}=(0,0,0,1)$ . We now project the remaining part of the Hamiltonian into the subspace spanned by these two states to find the low-energy Hamiltonian of the $x$ edge \n\n$$\nH_{\\mathrm{edge,}\\hat{x}}=-k_{y}\\mu^{y}+m_{y}\\mu^{x},\n$$ \n\nwhere $\\mu^{a}$ are Pauli matrices in the basis $(\\Phi_{x1},\\Phi_{x2})$ . \n\nPerforming an analogous calculation for the y edge, we find the matrix equation $(\\mathbb{I}-\\mathbb{I}\\otimes\\sigma^{z})\\boldsymbol{\\Phi}_{y}=0$ , which has solutions that are positive eigenstates of $\\mathbb{I}\\otimes\\sigma^{z}$ , i.e., $\\Phi_{y1}=\\left(1,0,0,0\\right)$ or $\\Phi_{y2}=(0,0,1,0)$ . We then project the remaining bulk terms into this basis to find the $y$ -edge Hamiltonian \n\n$$\nH_{\\mathrm{edge,}\\hat{y}}=-k_{x}\\gamma^{y}+m_{x}\\gamma^{x},\n$$ \n\nwhere $\\gamma^{a}$ are Pauli matrices in the basis $(\\Phi_{y1},\\Phi_{y2})$ . \n\nBoth of these edge Hamiltonians take the form of massive $(1+1)\\mathrm{{D}}$ Dirac models, i.e., the natural minimal continuum model for a $(1+1)\\mathrm{{D}}$ topological insulator (an alternative analysis arriving to this conclusion is found in Ref. [78]). Now, the key feature we mentioned earlier, i.e., the simultaneous zero-energy state can be found by considering a corner, i.e., either the $x$ edge with a $y$ -domain wall or the $y$ edge with an $x$ -domain wall. \n\nLet us first look for the zero-energy states localized at a $y$ -domain wall on the upper portion of a vertical 1D chain with Hamiltonian (J5). The ansatz in this case is of the form $\\begin{array}{r}{\\Phi_{x}(y)=\\exp[\\int_{0}^{y}m_{y}(y^{\\prime})d y^{\\prime}]\\phi_{x,y}}\\end{array}$ , which, from the Schrödinger equation for Hamiltonian (J5), and choosing zero energy, leads to a matrix equation that simplifies to \n\n$$\n(\\mathbb{I}-\\mu^{z})\\phi_{x,y}=0.\n$$ \n\nUsing similar calculations to those above, we find the following matrix equation for the $x$ -domain wall on the right side of a horizontal 1D insulator with Hamiltonian (J6): \n\n$$\n(\\mathbb{I}-\\gamma^{z})\\phi_{y,x}=0.\n$$ \n\nHence, the corner state we find for an $x$ edge with a $y$ -domain wall is the positive eigenstate of $\\mu^{z}$ while that for the $y$ edge with an $x$ -domain wall is the positive eigenstate of $\\gamma^{z}$ . In both cases, the solutions are identical, i.e., they are the first basis elements $\\Phi_{x1}=\\Phi_{y1}=(1,0,0,0)$ . Therefore, the corner zero-energy state is a simultaneous state of both domain-wall \n\nTABLE VI. Character table of the quaternion group. \n\n\n
Rep./class{1}{-1}{±Mx}{±M}{±}}
Xtriv11111
XM111-1-1
XM11-11-1
'x11-1-11
2-2000
\n\nHamiltonians, given by \n\n$$\n\\Psi^{\\mathrm{corner}}(x,y)=e^{\\int_{0}^{x}m_{x}(x^{\\prime})d x^{\\prime}}e^{\\int_{0}^{y}m_{y}(y^{\\prime})d y^{\\prime}}(1,0,0,0).\n$$ \n\nThus, although both edges are 1D topological insulators, they only produce a single zero mode. \n\n# APPENDIX K: CHARACTER TABLEOF THE QUATERNION GROUP \n\nThe quadrupole insulator with Bloch Hamiltonian (6.29) has the symmetry of the quaternion group (6.34). The character table for this group is shown in Table VI. There are four one-dimensional representations of this group and one twodimensional representation. The quadrupole insulator (6.29) takes the two-dimensional representation at all $\\mathbf{k}_{*}$ points of the BZ. \n\n# APPENDIX L: $C_{4}$ -SYMMETRIC QUADRUPOLE INSULATOR \n\nA schematic representation of a quadrupole with $C_{4}$ symmetry is shown in Fig. 52(a). It is a variation of the insulator shown in Fig. 21, but here we set $\\gamma_{x}=\\gamma_{y}=\\gamma$ and $\\lambda_{x}=\\lambda_{y}=\\lambda$ , and allow the fluxes threading each plaquette to be different than $\\pi$ . The “red” plaquettes, delimited by the intracell $\\gamma$ couplings, have flux $\\varphi_{0}$ , while the “blue” plaquettes, delimited by the intercell $\\lambda$ hoppings, have flux $\\varphi$ . To simplify the formulation, we take the fluxes into account by replacing \n\n![](images/afde47327e5c53ec879652ab337dff8eae658e9e44d80ac2bddff31cfd9b6ce8.jpg) \nFIG. 52. Quadrupole model that preserves $C_{4}$ symmetry. (a) $C_{4}$ - symmetric lattice. Red (blue) plaquettes have flux $\\varphi_{0}$ $(\\varphi)$ . Plaquettes sharing red and blue couplings have a flux of $-(\\varphi_{0}+\\varphi)/2$ . (b) Energy spectrum when $\\varphi_{0}=0$ , $\\varphi=\\pi$ . Despite the fact that the degeneracy of the occupied bands is lifted, the quadrupole remains quantized and stable. \n\n$$\n\\gamma\\to\\gamma e^{i\\varphi_{0}/4},\\quad\\lambda\\to\\lambda e^{i\\varphi/4}\n$$ \n\nin the directions of the arrows in Fig. 52(a), or their complex conjugate in the opposite direction. This implies that plaquettes sharing red couplings and blue hoppings have a flux of $-(\\varphi+$ $\\varphi_{0})/2$ . When $\\varphi=\\varphi_{0}=0,\\pi$ the insulators have reflection symmetries $M_{x}$ , $M_{y}$ . If $\\varphi=\\varphi_{0}=0$ , we have $[\\hat{M}_{x},\\hat{M}_{y}]=0$ , and the spectrum is gapless. If $\\varphi=\\varphi_{0}=\\pi$ , on the other hand, we recover the insulator (6.29), which has $\\{\\hat{M}_{x},\\hat{M}_{y}\\}=0$ , and realizes a quadrupole SPT phase. In Fig. 52(b), we show the energy spectrum for the values $\\varphi_{0}=0,\\ \\varphi=\\pi$ . Since the anticommuting reflection symmetries are lost, so is the protection of the degeneracies at the high-symmetry points of the BZ (cf. Fig. 49). The energy and Wannier bands remain gapped during the deformation $\\varphi_{0}=\\pi\\rightarrow\\varphi_{0}=0$ that connects the quadrupole (6.29) with the Hamiltonian with the energy spectrum in Fig. 52(b). Thus, the nontrivial topology persists, with the topological signatures shown in Fig. 32 and a nontrivial index (6.51). Indeed, edge polarization and charge density simulations on this model present the signatures of a quantized quadrupole of Figs. 23(b) and 24(b). \n\n[24] Y. Ueno, A. Yamakage, Y. Tanaka, and M. Sato, Phys. Rev. Lett. 111, 087002 (2013). \n[25] F. Zhang, C. L. Kane, and E. J. Mele, Phys. Rev. Lett. 111, 056403 (2013). \n[26] A. Lau, J. van den Brink, and C. Ortix, Phys. Rev. B 94, 165164 (2016). \n[27] L. Fu and C. L. Kane, Phys. Rev. B 76, 045302 (2007). \n[28] A. M. Turner, Y. Zhang, and A. Vishwanath, Phys. Rev. B 82, 241102 (2010). \n[29] L. Fu, Phys. Rev. Lett. 106, 106802 (2011). \n[30] C. Fang, M. J. Gilbert, and B. A. Bernevig, Phys. Rev. B 86, 115112 (2012). \n[31] C. Fang, M. J. Gilbert, and B. A. Bernevig, Phys. Rev. B 87, 035119 (2013). \n[32] J. C. Y. Teo and T. L. Hughes, Phys. Rev. Lett. 111, 047006 (2013). \n[33] W. A. Benalcazar, J. C. Y. Teo, and T. L. Hughes, Phys. Rev. B 89, 224503 (2014). \n[34] C.-X. Liu, R.-X. Zhang, and B. K. VanLeeuwen, Phys. Rev. B 90, 085304 (2014). \n[35] S. Kobayashi, Y. Yanase, and M. Sato, Phys. Rev. B 94, 134512 (2016). \n[36] A. Alexandradinata, Z. Wang, and B. A. Bernevig, Phys. Rev. X 6, 021008 (2016). \n[37] R. S. K. Mong, A. M. Essin, and J. E. Moore, Phys. Rev. B 81, 245209 (2010). \n[38] P. Jadaun, D. Xiao, Q. Niu, and S. K. Banerjee, Phys. Rev. B 88, 085110 (2013). \n[39] R.-J. Slager, A. Mesaros, V. Juricic, and J. Zaanen, Nat. Phys. 9, 98 (2013). \n[40] T. Morimoto and A. Furusaki, Phys. Rev. B 88, 125129 (2013). \n[41] K. Shiozaki and M. Sato, Phys. Rev. B 90, 165114 (2014). \n[42] C.-K. Chiu, J. C. Y. Teo, A. P. Schnyder, and S. Ryu, Rev. Mod. Phys. 88, 035005 (2016). \n[43] X.-Y. Dong and C.-X. Liu, Phys. Rev. B 93, 045429 (2016). \n[44] H. Watanabe and L. Fu, Phys. Rev. B 95, 081107 (2017). \n[45] B. Bradlyn, L. Elcoro, J. Cano, M. G. Vergniory, Z. Wang, C. Felser, M. I. Aroyo, and B. A. Bernevig, Nature (London) 547, 298 (2017). \n[46] K. Shiozaki, M. Sato, and K. Gomi, Phys. Rev. B 95, 235425 (2017). \n[47] W. A. Benalcazar, B. A. Bernevig, and T. L. Hughes, Science 357, 61 (2017). \n[48] R. Yu, X. L. Qi, A. Bernevig, Z. Fang, and X. Dai, Phys. Rev. B 84, 075119 (2011). \n[49] L. Fidkowski, T. S. Jackson, and I. Klich, Phys. Rev. Lett. 107, 036601 (2011). \n[50] A. Alexandradinata, X. Dai, and B. A. Bernevig, Phys. Rev. B 89, 155114 (2014). \n[51] M. Taherinejad and D. Vanderbilt, Phys. Rev. Lett. 114, 096401 (2015). \n[52] T. Olsen, M. Taherinejad, D. Vanderbilt, and I. Souza, Phys. Rev. B 95, 075137 (2017). \n[53] Y. Zhou, K. M. Rabe, and D. Vanderbilt, Phys. Rev. B 92, 041102 (2015). \n[54] R. Resta, Phys. Rev. Lett. 80, 1800 (1998). \n[55] G. H. Wannier, Rev. Mod. Phys. 34, 645 (1962). \n[56] N. Marzari and D. Vanderbilt, Phys. Rev. B 56, 12847 (1997). \n[57] I. Souza, N. Marzari, and D. Vanderbilt, Phys. Rev. B 65, 035109 (2001). \n[58] M. J. Rice and E. J. Mele, Phys. Rev. Lett. 49, 1455 (1982). \n[59] M. Atala, M. Aidelsburger, J. T. Barreiro, D. Abanin, T. Kitagawa, E. Demler, and I. Bloch, Nat. Phys. 9, 795 (2013). \n[60] L. Wang, M. Troyer, and X. Dai, Phys. Rev. Lett. 111, 026802 (2013). \n[61] H.-I. Lu, M. Schemmer, L. M. Aycock, D. Genkina, S. Sugawa, and I. B. Spielman, Phys. Rev. Lett. 116, 200402 (2016). \n[62] S. Coh and D. Vanderbilt, Phys. Rev. Lett. 102, 107603 (2009). \n[63] D. Asahi and N. Nagaosa, Phys. Rev. B 86, 100504 (2012). \n[64] T. L. Hughes, H. Yao, and X.-L. Qi, Phys. Rev. B 90, 235123 (2014). \n[65] C. Sgiarovello, M. Peressi, and R. Resta, Phys. Rev. B 64, 115202 (2001). \n[66] M. Taherinejad, K. F. Garrity, and D. Vanderbilt, Phys. Rev. B 89, 115102 (2014). \n[67] G. W. Winkler, A. A. Soluyanov, and M. Troyer, Phys. Rev. B 93, 035453 (2016). \n[68] E. Prodan, Phys. Rev. B 83, 235115 (2011). \n[69] A. A. Soluyanov and D. Vanderbilt, Phys. Rev. B 85, 115415 (2012). \n[70] A. Vishwanath and T. Senthil, Phys. Rev. X 3, 011016 (2013). \n[71] P. Bonderson, C. Nayak, and X.-L. Qi, J. Stat. Mech.: Theory Exp. (2013) P09016. \n[72] C. Wang, A. C. Potter, and T. Senthil, Phys. Rev. B 88, 115137 (2013). \n[73] X. Chen, L. Fidkowski, and A. Vishwanath, Phys. Rev. B 89, 165132 (2014). \n[74] M. A. Metlitski, C. L. Kane, and M. P. A. Fisher, Phys. Rev. B 92, 125111 (2015). \n[75] Z. Song, Z. Fang, and C. Fang, Phys. Rev. Lett. 119, 246402 (2017). \n[76] F. Schindler, A. M. Cook, M. G. Vergniory, Z. Wang, S. S. P. Parkin, B. A. Bernevig, and T. Neupert, arXiv:1708.03636. \n[77] J. Langbehn, Y. Peng, L. Trifunovic, F. von Oppen, and P. W. Brouwer, Phys. Rev. Lett. 119, 246401 (2017). \n[78] Y. Peng, Y. Bao, and F. von Oppen, Phys. Rev. B 95, 235143 (2017). " + }, + { + "id": "10.1038_ncomms15341", + "DOI": "10.1038/ncomms15341", + "DOI Link": "http://dx.doi.org/10.1038/ncomms15341", + "Relative Dir Path": "mds/10.1038_ncomms15341", + "Article Title": "Ultrathin metal-organic framework array for efficient electrocatalytic water splitting", + "Authors": "Duan, JJ; Chen, S; Zhao, C", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Two-dimensional metal-organic frameworks represent a family of materials with attractive chemical and structural properties, which are usually prepared in the form of bulk powders. Here we show a generic approach to fabricate ultrathin nullosheet array of metal-organic frameworks on different substrates through a dissolution-crystallization mechanism. These materials exhibit intriguing properties for electrocatalysis including highly exposed active molecular metal sites owning to ultra-small thickness of nullosheets, improved electrical conductivity and a combination of hierarchical porosity. We fabricate a nickel-iron-based metal-organic framework array, which demonstrates superior electrocatalytic performance towards oxygen evolution reaction with a small overpotential of 240 mV at 10 mA cm(-2), and robust operation for 20,000 s with no detectable activity decay. Remarkably, the turnover frequency of the electrode is 3.8 s(-1) at an overpotential of 400 mV. We further demonstrate the promise of these electrodes for other important catalytic reactions including hydrogen evolution reaction and overall water splitting.", + "Times Cited, WoS Core": 1090, + "Times Cited, All Databases": 1117, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000402742100001", + "Markdown": "# Ultrathin metal-organic framework array for efficient electrocatalytic water splitting \n\nJingjing Duan1, Sheng Chen1 & Chuan Zhao1 \n\nTwo-dimensional metal-organic frameworks represent a family of materials with attractive chemical and structural properties, which are usually prepared in the form of bulk powders. Here we show a generic approach to fabricate ultrathin nanosheet array of metal-organic frameworks on different substrates through a dissolution–crystallization mechanism. These materials exhibit intriguing properties for electrocatalysis including highly exposed active molecular metal sites owning to ultra-small thickness of nanosheets, improved electrical conductivity and a combination of hierarchical porosity. We fabricate a nickel-iron-based metal-organic framework array, which demonstrates superior electrocatalytic performance towards oxygen evolution reaction with a small overpotential of $240\\mathsf{m V}$ at $10\\mathsf{m A}\\mathsf{c m}^{-2},$ , and robust operation for 20,000 s with no detectable activity decay. Remarkably, the turnover frequency of the electrode is $3.8\\mathsf{s}^{-1}$ at an overpotential of $400\\mathsf{m V}.$ We further demonstrate the promise of these electrodes for other important catalytic reactions including hydrogen evolution reaction and overall water splitting. \n\nMjeotialn-ionrg amneictal firoanms ewitohrkosrga(nMicOlFigs)a,ndsc,onhsatvreucetemdergebdy of applications1,2. However, MOFs are generally considered to be poor electrocatalysts for electrochemical reactions such as the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), the two core processes for electrochemical water splitting3–5. Taking OER as an example, the state-of-the-art MOFs operate at a energy cost significantly above thermodynamic requirements, showing a high overpotential and small turnover frequency (TOF) during oxygen evolution3. \n\nThe activity of an electrocatalyst is usually dependent on, among many other factors, accessible active centres, electrical conductivity and electrode geometry. Improvement in catalytic efficiency requires each of these parameters to be optimized, but increasing one of them without compromising the others is difficult. For example, MOFs have abundant intrinsic molecular metal sites, but few of them are utilized for electrocatalysis because of their poor electrical conductivity (usually $\\sim10^{-10}\\mathrm{S}\\mathrm{m}^{-1})^{6,7}$ and small pore size (usually within several nanometres)1. The recently reported strategies like calcinations at high temperature may sacrifice MOFs’ intrinsic molecular metal active sites8, while hybridization with secondary conductive supports (polyaniline9, graphene10 and so on) may block their intrinsic micropores, and the bulk conductive MOF has limited meso- and macro-porosity (tens of nanometres to several micrometres) for effective mass transport during electrocatalysis7. Very recently, a few two-dimensional (2D) MOFs have been synthesized11–15, but the majority of 2D MOFs reported to date have been prepared in powder form, and little effort has been devoted to increasing the macro-/meso-porosity, conductivity or number of catalytic centres. \n\nIn this work, we develop a strategy for the in situ growth of ultrathin nanosheet arrays of 2D MOFs on various supports. Unexpectedly, the integrated MOF electrodes demonstrate superior performances towards OER, HER and overall water splitting. The material is prepared via a facile one-step chemical bath deposition method (Fig. 1) by adding the organic ligand (2,6-naphthalenedicarboxylic acid dipotassium) into an aqueous solution of metal salt (nickel acetate and iron nitrate) in the presence of the substrate. As shown in the right corner of Fig. 1, the crystal structure of the MOF consists of alternating organic hydrocarbon (2,6-naphthalenedicarboxylic group) and inorganic metal-oxygen-layers $\\mathrm{\\DeltaMO}_{6}$ units; $\\mathbf{M}=\\mathbf{Ni}$ , Fe or $\\mathrm{Cu}$ ). The metal ions (Ni, Fe or $\\mathrm{Cu}^{\\mathrm{\\prime}}$ ) are octahedrally coordinated, and each metal ion is coordinated to two trans monodentate carboxylates and four equatorial water molecules, while each naphthalene dicarboxylate bridges two metal atoms16,17. Moreover, the controlled experiments show that the 2D sheet-array morphology of the MOF cannot be obtained without using metal salts (Supplementary Fig. 1), substrates (Supplementary Fig. 2) or in different addition order of precursors (Supplementary Fig. 3). We further investigate the growth mechanisms by examining samples obtained at different reaction durations. NiFe-MOF evolves from micro-rods at $^{3\\mathrm{h}}$ (Supplementary Fig. 4a,b) into small-size nanosheets at $\\mathrm{10h}$ (Supplementary Fig. 4c,d), and then large-size nanosheets at $20\\mathrm{h}$ (Fig. 2), which is very similar to the previous reports of a dissolution-crystallization mechanism for nanocrystal growth18. \n\n# Results \n\nCharacterizations of the NiFe-MOF electrode. The structure and morphology of NiFe-MOF was characterized with a number of techniques. The photograph in Fig. 2a shows that the NiFeMOF grown on nickel foam (NiFe-MOF/NF) material is a 3D macroscopic film with high flexibility, which can be easily made into different sizes. The material is rich in macroporosity, with the pore size between 200 and $400\\upmu\\mathrm{m}$ (Fig. 2b). The surface of the film is composed of an array of vertically grown nanosheets with the distance between adjacent layers around tens of nanometres (Fig. 2c). The nanosheets have a lateral size of several hundred nanometres (Fig. 2d) with smooth well-defined morphology. The pores inside the NiFe-MOF range from 2.5 to $18\\mathrm{nm}$ as determined by nitrogen adsorption (Supplementary Fig. 5)19. Despite their rich porosity, these MOF nanosheets have a welldefined crystalline structure as revealed by the clear lattice fringes $(\\sim1.4\\mathrm{nm}$ lattice spacing due to the slit-like pores formed between adjacent metal-organic carbon layers, Fig. 2e), concentric circular rings of SAED pattern (inset of Fig. 2e), as well as X-ray diffraction (Supplementary Fig. 6). The thickness of nanolayers is determined to be $\\sim3.5\\mathrm{nm}$ by atomic force microscopy (AFM) (Fig. 2f). \n\nMoreover, X-ray photoemission spectroscopy (XPS) analysis reveals that the material contains Ni, Fe, O and C as the main components (Supplementary Fig. 7), where the $\\mathrm{Fe/Ni}$ atomic ratio is $23\\%$ ; therefore we determine the chemical formula of NiFe \n\n![](images/354ba58083181b1ee293e7a8c4df071dd430d4b118bff37529f1a8a0288beed3.jpg) \nFigure 1 | Synthetic process of metal-organic framework nanosheet array. Metal salts and substrate are firstly mixed together in an aqueous solution, and then introduces the organic ligand. Next, the MOF nanosheet array grows on the surface of substrate via a dissolution-crystallization mechanism. \n\n![](images/938ed5fc8ea84e3702e8317582593d28f5cebf7b4c4de4f01f8f02fb3638f10e.jpg) \nFigure 2 | Morphological characterization of NiFe-MOF electrodes. (a) An optical image (size: $1\\mathsf{c m}\\times3\\mathsf{c m}\\times1\\mathsf{m m})$ . (b,c) SEM images (scale bars are $300\\upmu\\mathrm{m}$ for b and $1\\upmu\\mathrm{m}$ for $\\overrightarrow{\\mathbf{c}},$ ). (d) Transmission electron microscopy image (Scale bar, $100\\mathsf{n m},$ ). (e) High-resolution transmission electron microscopy image (Scale bar, $5\\mathsf{n m}\\cdot$ ) and selected area electron diffraction (SAED) pattern (scale bar, $10/1{\\mathsf{n m}})$ . (f) AFM image and corresponding height profile along the marked green line. \n\nMOF as $\\mathrm{Ni_{0.8}F e_{0.2}(C_{12}H_{6}O_{4})(H_{2}O)_{4}}$ . This result is comparable to the elemental analysis conducted using both energy-dispersive X-ray spectroscopy and inductively coupled plasma with optical emission spectrometer (ICP-OES, please see Supplementary Fig. 8). Moreover, the C1s XPS spectrum shows the presence of both $\\alpha,\\beta$ -carbon and $\\pi-\\pi^{*}$ carbon that originated from the naphthalene ring of the organic ligand. The XPS $\\mathrm{Ni}_{2\\mathrm{p}3/2}$ peak located at $856\\mathrm{eV}$ indicates that Ni has an oxidation state of $+2$ in the MOF structure. Further, XPS $\\mathrm{Fe}_{2\\mathrm{p}1/2}$ at $723\\mathrm{eV}$ indicates that Fe has an oxidation state of $+3$ inside the material. \n\nElectrocatalytic oxygen and hydrogen evolution. The electrocatalytic performance of NiFe-MOF for OER (the anodic reaction of water splitting) was tested in 0.1 M KOH electrolyte in a typical three-electrode system. All the data were acquired without iR-correction. According to the linear sweep voltammograms (LSV) of Fig. 3a and Supplementary Figs 9 and 10 (The reverse scan of LSVs) the NiFe-MOF demonstrated an overpotential of $240\\mathrm{mV}$ at a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , which is much smaller than other controlled samples including the Ni-MOF (without Fe, $296\\mathrm{mV},$ ), Fe-MOF/NF (without Ni, $354\\mathrm{mV}.$ ), nickel foam (without MOF, $370\\mathrm{mV}.$ ), NiFe-MOF powder loaded on NF (denoted as bulk NiFe-MOF, without mesopores, $318\\mathrm{mV},$ ), calcined NiFe-MOF (at $650^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ in ${\\mathrm{N}}_{2}.$ , without molecular NiFe sites, $336\\mathrm{mV},$ ) and NiFe-MOF grown on a glassy carbon macrodisc electrode (NiFe-MOF/GC, without macro- and meso-porosity, $406\\mathrm{mV}.$ ). Even compared with the commercial benchmark OER catalyst $\\mathrm{IrO}_{2}$ , NiFe-MOF shows a significantly smaller overpotential $(\\varrho10\\mathrm{mA}\\mathrm{cm}^{-2}$ (240 versus $320\\mathrm{mV}.$ ) and 2.7 times higher current density at $1.7\\mathrm{V}$ versus RHE (300 versus $80\\mathrm{mAcm}^{-2}$ ). Moreover, assuming all the Ni and Fe sites inside NiFe-MOF are involved in OER, the TOF of $3.8\\mathsf{s}^{-1}$ is obtained for NiFe-MOF at an overpotential of $400\\mathrm{mV}$ . In contrast, the TOF of benchmark $\\mathrm{IrO}_{2}$ is only $0.14\\mathsf{s}^{-1}$ . Supplementary Table 1 also summarizes a comparison of NiFe-MOF with recently reported OER electrocatalysts. It suggests that NiFe-MOF/NF is already one of the most efficient electrocatalysts for OER reported in the literature, to the best of our knowledge. \n\nThe superior OER performance of NiFe-MOF electrode was also confirmed by its smaller Tafel plots derived from LSVs $(34\\mathrm{mV}\\mathrm{dec}^{-1}$ , Fig. 3b and Supplementary Fig. 11) than other controlled samples such as Ni-MOF $(4\\dot{5}\\mathrm{mV}\\mathrm{dec}^{-1}),$ , bulk NiFe-MOF $(56\\mathrm{mV}\\mathrm{dec}^{-1})$ and $\\mathrm{IrO}_{2}$ $(43\\mathrm{mV}\\mathrm{dec}^{-1}$ ). This result is consistent with that obtained from the steady state test $(38\\mathrm{mV}\\mathrm{dec}^{-1}$ for NiFe-MOF and $46\\mathrm{mV}\\mathrm{dec}^{-1}$ for $\\mathrm{IrO}_{2}$ ; Supplementary Fig. 12). The average electron transfer number (N) of NiFe-MOF obtained by using a rotating ring-disk electrode is 3.95 (Fig. 3c and Supplementary Figs 13,14); the reaction Faradic efficiency was $95\\pm2.5\\%$ , both indicating OER follows a four-electron pathway (that is, $4\\mathrm{OH}^{-}\\rightarrow2\\mathrm{H}_{2}\\mathrm{\\bar{O}}+\\mathrm{O}_{2}+4\\mathrm{e}^{-})$ to generate oxygen molecules. Remarkably, the NiFe-MOF electrode showed excellent stability as confirmed by prolonged chronoamperometric experiment (fixed at $1.42\\mathrm{V}$ versus RHE for $20{,}000\\mathbf{s}.$ , Fig. 3d), cyclic voltammetry (1,000 cycles, Supplementary Fig. 15a) and electrochemical impedance spectroscopy (EIS, Supplementary Fig. 15b). \n\nFurthermore, the NiFe-MOF is also highly active towards HER, the cathodic reaction of water splitting. The electrocatalytic performance of NiFe-MOF for HER was tested in 0.1 M KOH by polarizing the electrode to negative potentials (Fig. 4a). At the current density of $10\\mathrm{mAcm}^{-2}$ , NiFe-MOF exhibits the smallest overpotential of $134\\mathrm{mV}$ , compared to other samples including Ni-MOF $(177\\mathrm{mV})$ , bulk NiFe-MOF $(196\\mathrm{mV})$ and calcined NiFeMOF $(255\\mathrm{mV})$ . The TOF of NiFe-MOF for HER at the overpotential of $400\\mathrm{mV}$ is $2.8\\mathsf{s}^{-1}$ , which outperforms that of Ni-MOF $(0.91s^{-1})$ , bulk NiFe-MOF $(0.53\\mathrm{s}^{-1})$ and calcined NiFe-MOF $(0.19s^{-1})$ . This performance is comparable to stateof-the-art non-precious metal based HER catalysts (Supplementary Table 2). Further, prolonged chronoamperometric experiment at $-0.2\\mathrm{V}$ (versus RHE, Fig. 4b) for $2,000s$ showed a stable current response, and the LSVs obtained before and after chronoamperometric test are also identical, all indicating excellent durability of the NiFe-MOF for HER. \n\nElectrocatalytic overall water splitting. To test the overall water splitting, a two-electrode cell was constructed by using NiFeMOF as both the anode and the cathode. The photograph (inset of Fig. 4c) and corresponding movie (Supplementary Movie 1) reveal that at the applied cell voltage of $1.6\\mathrm{V}$ , a large amount of $\\mathrm{H}_{2}$ gas bubbles evolve at the cathode and $\\mathrm{O}_{2}$ gas bubbles evolve at the anode, also confirmed by gas chromatography (Supplementary Fig. 16). The electrolytic cell demonstrated excellent catalytic activity and can deliver a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ at a voltage only of $1.55\\mathrm{V}$ (Fig. 4c), which is $70\\mathrm{mV}$ smaller than using the benchmark precious metal-based $\\mathrm{Pt/C}$ cathodes and $\\mathrm{IrO}_{2}$ anodes. The Tafel slope obtained for NiFeMOF $(256\\mathrm{mV}\\mathrm{dec}^{-1}$ ) is also lower than the $\\mathrm{Pt/C}$ cathode and $\\mathrm{IrO}_{2}$ anode system $(267\\mathrm{mV}\\mathrm{dec}^{-1}$ , Supplementary Fig. 17). To the best of our knowledge, the NiFe-MOF outperforms most, if not all, bifunctional electrocatalysts reported for full water splitting20–22. Furthermore, the electrolytic cell demonstrates excellent stability in a prolonged chronoamperometric test at $1.5\\mathrm{V}$ for $20\\mathrm{h}$ (inset of Fig. 4d). The durability of water electrolysis is further supported by the almost identical LSVs (Fig. 4d), X-ray diffraction profiles (Supplementary Fig. 18), and scanning electron microscopy (SEM) images (Supplementary Fig. 19) obtained before and after the chronoamperometric test. \n\n![](images/9ac3835b866238ee19a16b2d90f7832f160c409ae0c0efa12e1e6facbfa0aeb4.jpg) \nFigure 3 | Electrocatalytic properties of NiFe-MOF and other samples for OER. (a) LSV plots obtained with NiFe-MOF, nickel-based metal-organic framework (Ni-MOF), bulk NiFe-MOF and $\\mathsf{I r O}_{2}$ for OER at $10\\mathrm{mVs}^{-1}$ in 0.1 M KOH. (b) Tafel plots obtained with NiFe-MOF, Ni MOF and bulk NiFe-MOF. (c) Rotate ring disk electrode voltammogram obtained for NiFe-MOF in 0.1 M KOH. The ring potential is set at $\\ensuremath{1.4\\vee}$ versus reversible hydrogen electrode (RHE) to monitor the production of hydrogen peroxide; the inset of (c) shows the corresponding electron transfer number $(N)$ as a function of applied potentials. (d) Chronoamperometric testing of NiFe-MOF for 20,000 s at $\\phantom{-}1.42\\vee$ (versus RHE) in 0.1 M KOH. \n\n# Discussion \n\nThe materials’ mechanisms for different reactions have been discussed. First, it is generally accepted that Ni-based catalysts have three intermediate steps in the $\\mathrm{OER}^{22,23}$ $\\mathrm{\\mathrm{~E}}^{0}$ versus RHE, reversible hydrogen electrode), that is: \n\n$$\n\\mathrm{NiOOH+OH^{-}\\leftrightarrow N i O(O H)}+\\mathrm{e},\\mathrm{E}^{0}=1.43\\mathrm{V}\n$$ \n\n$$\n\\mathrm{NiO(OH)}_{2}+2\\mathrm{OH}^{-}\\leftrightarrow\\mathrm{NiOO}_{2}+2\\mathrm{H}_{2}\\mathrm{O}+2\\mathbf{e},\\mathrm{E}^{0}=1.55\\mathrm{V}\n$$ \n\n$$\n\\mathrm{NiOO}_{2}+\\mathrm{OH}^{-}\\rightarrow\\mathrm{NiOOH}+\\mathrm{O}_{2}+\\mathrm{e}\n$$ \n\n$$\n\\mathrm{Overall:4OH^{-}\\leftrightarrow{O}_{2}+2H_{2}O+4e}\n$$ \n\nStep (1) and (2) are highly reversible, while step (3) is fast and irreversible and determines the overall rate of the process; catalysts are mostly used to facilitate the kinetics of step (3). In the anodic OER process, $\\mathrm{NiO}_{6}$ inside MOF was oxidized into $\\mathrm{NiO_{6}/N i O O H}$ species as active centres, which then promote the oxidation of $\\mathrm{OH^{-}}$ into molecular oxygen. In addition, $23\\mathrm{wt\\%}$ of Fe impurity enhances the activity of Ni-based catalysts through introducing additional structural vacancies (Supplementary Fig. 20)23,24. \n\nSecond, the HER pathway in alkaline media could be the Volmer–Heyrovsky process or Volmer–Tafel pathways: \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{e}\\longrightarrow\\mathrm{H}_{\\mathrm{ads}}+\\mathrm{OH}^{-}\\left(\\mathrm{Volmer}\\right)\n$$ \n\nand \n\n$$\n\\ H_{\\mathrm{ads}}+\\mathrm{H}_{\\mathrm{ads}}\\longrightarrow\\mathrm{H}_{2}(\\mathrm{Tafel})\n$$ \n\nor \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{H}_{\\mathrm{ads}}+\\mathrm{e}\\rightarrow\\mathrm{H}_{2}+\\mathrm{OH}^{-}\\left(\\mathrm{Heyrovsky}\\right)\n$$ \n\nBoth pathways involve the adsorption of $\\begin{array}{r l}{\\mathrm{H}_{2}\\mathrm{O}_{:}}\\end{array}$ , electrochemical reduction into adsorbed $\\mathrm{~H~}$ atom and $\\mathrm{OH^{-}}$ , and desorption of $\\mathrm{H}_{2}$ . In this work, $\\mathrm{NiO}_{6}$ inside MOF was partially reduced to form $\\mathrm{Ni}/\\mathrm{NiO}_{6}$ interface at the cathode. On such interface, the $\\mathrm{OH^{-}}$ generated by $_\\mathrm{H}_{2}\\mathrm{O}$ splitting could preferentially attach to a $\\mathrm{NiO}_{6}$ site at the interface due to strong electrostatic affinity to the locally positively charged $\\mathrm{Ni}^{2+}$ species, while a nearby Ni site would facilitate $\\mathrm{~H~}$ adsorption and thus the Volmer process, imparting synergistic HER catalytic activity25. \n\nThe significantly enhanced performance of NiFe-MOF catalyst for water splitting has been further discussed, which is attributable to its optimal structural characteristics for electrocatalysis including highly exposed molecular metal active sites owing to ultrathin MOF sheets, improved electrical conductivity through 2D nanostructuration, and a combination of hierarchical porosity. First, NiFe metal oxides/hydroxides are active catalytic centres for OER, HER and overall water splitting; however, they usually show compromised catalytic performance owing to limited exposed metal active sites22. In contrast, MOF material has inherent molecular metal centres, as potential active sites for electrocatalysis. The direct use of MOF as electrocatalyst can provide enormous molecular metal sites as catalytic centres; while the ultrathin (thickness, $\\sim3.5\\mathrm{nm}$ ) yet large (lateral size $>100\\mathrm{nm}$ ) 2D MOF nanosheets structure allows for these metal sites to be highly exposed to electrolyte ions for use in catalytic reactions. This is confirmed by a two-fold increase of electrochemical active surface measured by using double-layer capacitance of the 2D NiFe-MOF nanosheets, compared with the bulk NiFe-MOF (0.036 versus $0.016\\mathrm{F}\\mathrm{cm}^{-2}$ , Supplementary Fig. 21). Interestingly, the highly exposed metal NiFe centres also render MOF nanosheets very hydrophilic, as suggested by zeta potential $\\mathrm{(-29.2mV}$ , Supplementary Fig. 22), contact angle 1 $38^{\\mathrm{o}}$ , Supplementary Fig. 23) and Fourier transform infrared (FT-IR) spectra analyses (Supplementary Fig. 24), which can facilitate the adsorption of water onto electrode surface, and promote the kinetics of water dissociation26. \n\n![](images/d8501d797f9bcc9ff8abff5dc149e970cce25e504758843d516d471a5a52c282.jpg) \nFigure 4 | Electrocatalytic properties of NiFe-MOF and other samples for HER and overall water splitting. (a) LSV plots obtained with NiFe-MOF, bulk NiFe-MOF, Ni-MOF and calcined NiFe-MOF for HER at $10\\mathsf{m}\\mathsf{V}^{-1}$ in 0.1 M KOH. (b) LSV of NiFe-MOF for HER before and after chronoamperometric testing for 2000 s at $-0.2\\vee$ (versus RHE) in $0.1M\\mathsf{K O H};$ the inset of $(\\pmb{6})$ shows corresponding chronoamperometric profile. (c) LSV plots of a full electrolytic cell using two NiFe-MOF electrodes obtained at $10\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in $0.1M\\mathsf{K O H},$ ; the inset photograph shows the evolution of hydrogen and oxygen gas bubbles at the NiFe-MOF electrodes at an applied cell voltage of $1.6\\vee;$ the LSV obtained using a $\\mathsf{P t/C}$ cathode and a $\\mathsf{I r O}_{2}$ anode was included for comparison. (d) LSV plots of the two-electrode electrolytic cell obtained before and after $20\\mathsf{h}$ chronoamperometric tests at a cell voltage of $1.5\\mathsf{V};$ the inset shows corresponding chronoamperometric plot. \n\nMoreover, we scratched 2D MOF nanosheets from nickel foam substrates, and then pressed it at $10\\mathrm{MPa}$ for 3 min to form a uniform thin film of thickness $\\sim240\\mathrm{nm}$ (Supplementary Fig. 25). We found that the 2D MOF nanosheets have intrinsic high electrical conductivity $(1\\pm0.2\\times10^{-3}\\mathrm{S}\\mathrm{m}^{-1})$ measured by a four-point probe, which is almost three orders of magnitude higher than its bulk counterpart $(1\\pm0.5\\times10^{-6}\\mathrm{Sm^{-1}})$ . Such enhancement is generally due to 2D nanostructuration that can lead to vacancy engineering inside the material. These vacancies can act as shallow donors to increase the carrier concentration of metal octahedral units (that is, $\\mathrm{NiFeO}_{6};$ of the MOF, thereby enhancing the conductivity of materials27–29. The high conductivity can facilitate the charge transport during electrocatalysis, thus contributing to the observed high activity of the 2D NiFe-MOF. Moreover, the direct growth of NiFe-MOF on nickel foam can eliminate the need for insulating chemical binders. Generally, to construct powders of MOFs into usable electrodes, insulating polymeric binders, for example Nafion, are required to glue these materials to a substrate electrode, which can reduce the contact area between electrolytes and catalytic active sites and deteriorate the overall conductivity of electrode. This is confirmed by the large internal resistance of bulk NiFe-MOF/NF (prepared by the Nafion-assisted drop-casting method, $8.2\\Omega$ ) than NiFe-MOF $(2.8\\Omega$ , prepared by the direct growth method, Supplementary Fig. 26). The enhanced catalystsubstrate contact on binder-free electrode contribute to efficient electron transport and consequently high catalytic activity. \n\nFurther, the unique hierarchical porous architecture of NiFe-MOF sheet array on nickel foam also contributes to the enhanced activity by ensuring effective mass transport within the electrodes $({\\dot{\\mathrm{Fig.}}}^{\\cdot}3\\mathsf{a}-\\mathsf{c})^{3\\mathrm{C}}$ . One of the major challenges of using MOFs for electrocatalysis is the very small pore size (usually within several nanometres) of bulk MOF materials, which inhibits the effective mass transport of electrolyte to the active centres and diffusion of products, leading to impeded electrode performance. This is particularly a problem in water splitting as the electrode products are $\\mathrm{O}_{2}$ and $\\mathrm{H}_{2}$ gases, which can potentially block the active sites of MOFs and prohibit ionic transportation, and is one of the major sources of overpotential. Here, the as-prepared NiFe-MOF electrode demonstrates a combination of hierarchical-scale porosity (several-hundred-micrometre macropores, tens-of-nanometre open pores, several-nanometre mesopores and intrinsic microporosity). The extra-large macropores of nickel foam can facilitate the mass transport of electrolytes and gaseous products (Fig. 2a,b), while the open pores between vertically aligned nanosheets (Fig. 2c), small mesopores and micropores of MOF (Fig. 2e and Supplementary Fig. 5) provide enormous, highly accessible active sites and short ion diffusion pathways. \n\nFinally, we show the synthetic approach is generic and can be adapted for a range of MOF materials and substrate materials. Supplementary Fig. 27 shows ultrathin NiFe-MOF nanosheet can be grown on stainless steel mesh via a similar procedure. SEM images in Supplementary Fig. 27 show the stainless steel mesh is coated by numerous ultrathin nanosheets of NiFe-MOF with the lateral size of several micrometres and thickness of a few nanometres. Supplementary Fig. 28 shows the synthetic procedure is also adaptable to other transition metals-based MOF materials, such as copper-based MOF (denoted as Cu-MOF) on nickel foam. AFM reveals the nanosheets have typical thickness of $6.8\\mathrm{nm}$ and lateral size of tens of nanometres (Supplementary Fig. $27c,\\mathrm{d},$ . All the above data suggest the 2D MOF nanosheet array is a promising class of materials for electrochemical applications. \n\nIn summary, this work demonstrates a universal strategy to fabricate ultrathin nanosheet arrays of 2D MOFs, which can be easily adaptable to prepare many other metal-based 2D MOFs such as cobalt, manganese, titanium and molybdenum. The as-resultant material combines a number of remarkable features, and exhibited significantly enhanced catalytic performances with high catalytic activity, favourable kinetics and strong durability towards electrocatalysis such as OER, HER and overall water splitting. The performance of our electrode for water splitting challenges a common conception that MOFs themselves are an inert catalyst for electrochemical reactions. \n\n# Methods \n\nSynthesis of NiFe-MOF electrode. A piece of nickel foam (NF) $(2\\mathrm{cm}\\times1\\mathrm{cm}\\times1.6\\mathrm{mm})$ ) or stainless steel mesh, was immersed into a vial containing $1\\mathrm{ml}$ of DI-water and $8\\mathrm{mg}$ of $\\mathrm{Ni}(\\mathrm{Ac})_{2}\\cdot4\\mathrm{H}_{2}\\mathrm{O}$ and $2\\mathrm{mg}$ of $\\mathrm{Fe(NO_{3})_{3}\\cdot9H_{2}O}$ . Next, $10\\mathrm{mg}$ of organic ligand 2,6-naphthalenedicarboxylate tetrahydrate was added into the above solution, and the vial was sealed for reaction at $60^{\\circ}\\mathrm{C}$ for $20\\mathrm{h}$ . After cooling down to room temperature, the nickel foam was taken out, bath ultrasonicated for $1\\mathrm{min}$ and then rinsed with copious DI-water. \n\nPhysical characterizations. X-ray diffractionwas performed on a Philips 1130 X-ray diffractometer (40 kV, 25 mA, Cu $\\operatorname{K}\\upalpha$ radiation, $\\lambda{=}1.5418\\mathrm{\\AA}$ ); the contact angle was measured on a Theta/Attension Optical Tensiometer; the electrical conductivity was measured on a Signatone Four Point Probing System with the MOF nanosheets scratched out and pressed into a circular pellet (1 cm in diameter and $43\\upmu\\mathrm{m}$ thick); XPS was performed on an Axis Ultra (KratosAnalytical, UK) XPS spectrometer equipped with an Al Ka source $(1486.6\\mathrm{eV})$ ; inductively coupled plasma optical emission spectrometer (ICP-OES) methodology was used for elemental analysis conducted on a Thermo Scientific iCAP 6500 duo optical emission spectrometer fitted with a simultaneous charge induction detector; FT-IR spectra were recorded on a Nicolet 6700 spectrometer; zeta potential was monitored on a Malvern Zetasizer Nano series analyser; GC was conducted on the Shimadzu GC-2010; AFM was conducted on Bruker Dimension ICON SPM using peak force mode; morphologies of the samples were observed on transmission electron microscopy (TecnaiG2Spirit and JEOL JEM-ARM200F) and SEM (QUANTA 450); energy-dispersive X-ray spectroscopy and element mapping were acquired on the SEM (QUANTA 450). Further, the porosity was evaluated by using nitrogen adsorption–desorption isotherms measured at $77\\mathrm{K}$ on a TriStar II 3020 Micrometrics apparatus. \n\nElectrochemical characterizations. OER and HER were studied in a standard three-electrode glass cell connected to a 760 workstation (Pine Research Instruments, US) using the NiFe-MOF as the working electrode, carbon rod as a counter electrode and $\\mathrm{{\\hat{A}g/A g C l/K C l}}$ (3 M) as a reference electrode. All the measured potentials were converted to reversible hydrogen electrodes (RHE) according to Potentia $\\mathrm{|=E_{Ag/AgCl}+0.059p H+0.197V}$ . The two-electrode system was built by employing two NiFe-MOF electrodes. The electrolyte was prepared using DI-water $\\bar{(18\\mathrm{M}\\bar{\\Omega}\\mathrm{cm}^{-1})}$ and KOH. LSV and CV were recorded with the scan rates of $10\\mathrm{mVs}^{-1}$ ; Tafel plots are recorded with the linear portions at low overpotential fitted to the Tafel equation $(\\eta=b\\log j+a$ , where $\\eta$ is overpotential, $j$ is the current density, and $b$ is the Tafel slope; EIS was recorded under the following conditions: AC voltage amplitude 0 or $1.5\\mathrm{V}$ , frequency ranges $10^{6}$ to \n\n${1\\mathrm{Hz}}, $ and open circuit; the current density was normalized to the geometrical area; \nAll the electrochemical data were presented without iR correction. \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding author on request. \n\n# References \n\n1. Wang, C., Liu, X., Keser Demir, N., Chen, J. P. & Li, K. Applications of water stable metal-organic frameworks. Chem. Soc. Rev. 45, 5107–5134 (2016). \n2. Zhang, H. Ultrathin Two-dimensional nanomaterials. ACS Nano 9, 9451–9469 (2015). \n3. Flugel, E. A., Lau, V. W., Schlomberg, H., Glaum, R. & Lotsch, B. V. Homonuclear mixed-valent cobalt imidazolate framework for oxygen-evolution electrocatalysis. Chem. Eur. J. 22, 3676–3680 (2016). \n4. Gong, Y., Shi, H. F., Jiang, P. G., Hua, W. & Lin, J. H. Metal(II)-induced coordination polymer based on 4-(5-(Pyridin-4-yl)-4H-1,2,4-triazol-3-yl)benzoate as an electrocatalyst for water splitting. Cryst. Growth Des. 14, 649–657 2014 : \n5. Miner, E. M. et al. Electrochemical oxygen reduction catalysed by $\\mathrm{Ni}_{3}$ (hexaiminotriphenylene)2. Nat. Commun. 7, 10942 (2016). \n6. Sun, L., Campbell, M. G. & Dinca, M. Electrically conductive porous metalorganic frameworks. Angew. Chem. Int. Ed. 55, 3566–3579 (2016). \n7. Sheberla, D. et al. Conductive MOF electrodes for stable supercapacitors with high areal capacitance. Nat. Mater. 16, 220–224 (2016). \n8. Zhong, H. X. et al. ZIF-8 derived graphene-based nitrogen-doped porous carbon sheets as highly efficient and durable oxygen reduction electrocatalysts. Angew. Chem. Int. Ed. 53, 14235–14239 (2014). \n9. Wang, L. et al. Flexible solid-state supercapacitor based on a metal-organic framework interwoven by electrochemically-deposited PANI. J. Am. Chem. Soc. 137, 4920–4923 (2015). \n10. Jahan, M., Liu, Z. & Loh, K. P. A graphene oxide and copper-centered metal organic framework composite as a tri-functional catalyst for HER, OER, and ORR. Adv. Funct. Mater. 23, 5363–5372 (2013). \n11. Peng, Y. et al. Membranes. Metal-organic framework nanosheets as building blocks for molecular sieving membranes. Science 346, 1356–1359 (2014). \n12. Choi, M. et al. Stable single-unit-cell nanosheets of zeolite MFI as active and long-lived catalysts. Nature 461, 246–249 (2009). \n13. Ren, L. et al. Self-Pillared, Single-unit-cell Sn-MFI zeolite nanosheets and their use for glucose and lactose isomerization. Angew. Chem. Int. Ed. 54, 10848–10851 (2015). \n14. Zhao, M. et al. Ultrathin 2D metal-organic framework nanosheets. Adv. Mater. 27, 7372–7378 (2015). \n15. Wu, G., Huang, J., Zang, Y., He, J. & Xu, G. Porous field-effect transistors based on a semiconductive metal-organic framework. J. Am. Chem. Soc. 139, 1360–1363 (2016). \n16. Kaduk, J. A. & Hanko, J. A. Salts of aromatic carboxylates: the crystal structures of nickel(II) and cobalt(II) 2,6-naphthalenedicarboxylate tetrahydrate. J. Appl. Crystallogr. 34, 710–714 (2001). \n17. Ma, T. Y., Dai, S., Jaroniec, M. & Qiao, S. Z. Metal-organic framework derived hybrid $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ -carbon porous nanowire arrays as reversible oxygen evolution electrodes. J. Am. Chem. Soc. 136, 13925–13931 (2014). \n18. Portehault, D., Cassaignon, S., Baudrin, E. & Jolivet, J.-P. Morphology control of cryptomelane type $\\mathrm{{MnO}}_{2}$ nanowires by soft chemistry. Growth mechanisms in aqueous medium. Chem. Mater. 19, 5410–5417 (2007). \n19. Kruk, M., Jaroniec, M. & Sayari, A. Application of large pore MCM-41 molecular sieves to improve pore size analysis using nitrogen adsorption measurements. Langmuir 13, 6267–6273 (1997). \n20. Jiang, N., You, B., Sheng, M. & Sun, Y. Electrodeposited cobalt-phosphorousderived films as competent bifunctional catalysts for overall water splitting. Angew. Chem. Int. Ed. 54, 6251–6254 (2015). \n21. Jin, H. et al. In situ cobalt-cobalt oxide/N-doped carbon hybrids as superior bifunctional electrocatalysts for hydrogen and oxygen evolution. J. Am. Chem. Soc. 137, 2688–2694 (2015). \n22. Luo, J. et al. Water photolysis at $12.3\\%$ efficiency via perovskite photovoltaics and Earth-abundant catalysts. Science 345, 1593–1596 (2014). \n23. Lu, X. & Zhao, C. Electrodeposition of hierarchically structured threedimensional nickel-iron electrodes for efficient oxygen evolution at high current densities. Nat. Commun. 6, 6616 (2015). \n24. Trotochaud, L., Young, S. L., Ranney, J. K. & Boettcher, S. W. Nickel–iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation. J. Am. Chem. Soc. 136, 6744–6753 (2014). \n25. Gong, M. et al. Nanoscale nickel oxide/nickel heterostructures for active hydrogen evolution electrocatalysis. Nat. Commun. 5, 4695 (2014). \n26. Chen, S., Duan, J., Jaroniec, M. & Qiao, S. Z. Three-dimensional N-doped graphene hydrogel/NiCo double hydroxide electrocatalysts for highly efficient oxygen evolution. Angew. Chem. Int. Ed. 52, 13567–13570 (2013). \n27. Kim, H. S. et al. Oxygen vacancies enhance pseudocapacitive charge storage properties of $\\mathrm{MoO}_{3-x}.$ Nat. Mater. 16, 454–460 (2016). \n28. Lee, S. et al. Enhanced intrinsic catalytic activity of lambda- $\\cdot\\mathrm{MnO}_{2}$ by electrochemical tuning and oxygen vacancy generation. Angew. Chem. Int. Ed. \n55, 8599–8604 (2016). \n29. Voiry, D. et al. Enhanced catalytic activity in strained chemically exfoliated $\\mathrm{WS}_{2}$ nanosheets for hydrogen evolution. Nat. Mater. 12, 850–855 (2013). \n30. Li, Y., Hasin, P. & Wu, Y. $\\mathrm{Ni}_{x}\\mathrm{Co}_{3-x}\\mathrm{O}_{4}$ nanowire arrays for electrocatalytic oxygen evolution. Adv. Mater. 22, 1926–1929 (2010). \n\n# Acknowledgements \n\nWe acknowledge the financial support from the Australian Research Council (DP160103107) and a UNSW Vice-Chancellor’s Research Fellowship (S.C.). This research used equipment funded by the Australian Research Council (ARC) located at the UNSW MWAC analytic centre and UOW Electron Microscopy Centre. \n\n# Author contributions \n\nC.Z. and S.C. designed the research; J.J.D. and S.C. synthesized the samples and performed the characterizations; all authors co-wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Duan, J. et al. Ultrathin metal-organic framework array for efficient electrocatalytic water splitting. Nat. Commun. 8, 15341 doi: 10.1038/ncomms15341 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2017 " + }, + { + "id": "10.1038_ncomms15218", + "DOI": "10.1038/ncomms15218", + "DOI Link": "http://dx.doi.org/10.1038/ncomms15218", + "Relative Dir Path": "mds/10.1038_ncomms15218", + "Article Title": "Fast oxygen diffusion and iodide defects mediate oxygen-induced degradation of perovskite solar cells", + "Authors": "Aristidou, N; Eames, C; Sanchez-Molina, I; Bu, XN; Kosco, J; Islam, MS; Haque, SA", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Methylammonium lead halide perovskites are attracting intense interest as promising materials for next-generation solar cells, but serious issues related to long-term stability need to be addressed. Perovskite films based on CH3NH3PbI3 undergo rapid degradation when exposed to oxygen and light. Here, we report mechanistic insights into this oxygen-induced photodegradation from a range of experimental and computational techniques. We find fast oxygen diffusion into CH3NH3PbI3 films is accompanied by photo-induced formation of highly reactive superoxide species. Perovskite films composed of small crystallites show higher yields of superoxide and lower stability. Ab initio simulations indicate that iodide vacancies are the preferred sites in mediating the photo-induced formation of superoxide species from oxygen. Thin-film passivation with iodide salts is shown to enhance film and device stability. The understanding of degradation phenomena gained from this study is important for the future design and optimization of stable perovskite solar cells.", + "Times Cited, WoS Core": 1027, + "Times Cited, All Databases": 1090, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000400962100001", + "Markdown": "# Fast oxygen diffusion and iodide defects mediate oxygen-induced degradation of perovskite solar cells \n\nNicholas Aristidou1, Christopher Eames2, Irene Sanchez-Molina1, Xiangnan ${\\mathsf{B}}{\\mathsf{u}}^{1}$ , Jan Kosco1, M. Saiful Islam2 \n& Saif A. Haque1 \n\nMethylammonium lead halide perovskites are attracting intense interest as promising materials for next-generation solar cells, but serious issues related to long-term stability need to be addressed. Perovskite films based on ${\\mathsf{C H}}_{3}{\\mathsf{N H}}_{3}{\\mathsf{P b l}}_{3}$ undergo rapid degradation when exposed to oxygen and light. Here, we report mechanistic insights into this oxygen-induced photodegradation from a range of experimental and computational techniques. We find fast oxygen diffusion into $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ films is accompanied by photo-induced formation of highly reactive superoxide species. Perovskite films composed of small crystallites show higher yields of superoxide and lower stability. Ab initio simulations indicate that iodide vacancies are the preferred sites in mediating the photo-induced formation of superoxide species from oxygen. Thin-film passivation with iodide salts is shown to enhance film and device stability. The understanding of degradation phenomena gained from this study is important for the future design and optimization of stable perovskite solar cells. \n\nMeotnhe aofm tmhoe iumo aprdohmailsiidneg celraossvessk oef hmavte ibaelcs fmoer lectronics such as solar cells, light-emitting diodes and lasers1–5. Solar cell applications in particular have attracted intense interest in recent years with a rapid rise in power conversion efficiencies of up to $22\\%$ for perovskite photovoltaics6–17. \n\nHowever, despite such remarkable progress, serious issues related to the long-term stability of perovskite halides need to be addressed before they can be used successfully in commercial solar cell applications. It has been generally observed that moisture, elevated temperature, oxygen and UV radiation all cause degradation of hybrid perovskite materials and device instability at higher rates than those typically observed in polymer and dye-sensitized photovoltaics18–37. We recently demonstrated38,39 that exposure of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ photoactive layers to light and oxygen leads to the formation of superoxide $(\\dot{\\mathrm{O}}_{2}^{-}$ ) species. This reactive $\\mathrm{O}_{2}^{-}$ species can deprotonate the methylammonium cation $\\mathrm{(CH_{3}\\tilde{N}H_{3}^{+}}$ ) of photo-excited $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}{^{\\ast}}$ , leading to the formation of $\\mathrm{\\bar{PbI}}_{2}$ , water, methylamine and iodine,38,39 as shown schematically in Fig. 1. \n\nThis oxygen-induced degradation pathway has been shown to affect the stability of both $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{\\bar{P}b I}_{3}$ photoactive layers and solar cell devices40. Transient absorption spectroscopy studies of interfacial charge transfer in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ -based films revealed that such oxygen-induced degradation results in a large decrease in the yield of photo-induced charge carriers39. While recent work has demonstrated the importance of electron extraction in reducing the severity of this degradation pathway20,38–40, it is highly unlikely that charge extraction alone will completely solve this problem. Hybrid lead halide layers deposited from solution typically produce polycrystalline films with varied microstructure and particle morphologies. The impact of film microstructure on charge carrier transport, photoluminescence, device performance parameters (for example, $J_{s c},$ $V_{\\mathrm{oc}},$ fill factor) and tolerance to moisture has been reported recently41–51. It is reasonable to suppose that the particle size and defect chemistry of the films may also influence oxygen diffusion into the perovskite layer and its susceptibility to oxidative reactions. \n\nStudies on $\\mathrm{\\CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ suggest a significant equilibrium defect concentration of $\\mathrm{I}^{-}$ , $\\mathrm{Pb}^{\\tilde{2}\\mp}$ and $\\mathrm{C}\\check{\\mathrm{H}}_{3}\\mathrm{N}\\mathrm{H}_{3}^{+}$ vacancies at room temperature, which could provide vacancy-mediated pathways for ion transport52. Our previous work53 and other studies54–58 indicate that these hybrid perovskites are mixed ionic-electronic conductors, and also implicate vacancy-mediated iodide ion diffusion as being responsible for the observed hysteresis effects. Recent studies have also investigated the role of ion migration in perovskite degradation21. Ionic defect and transport phenomena in hybrid perovskites thus have important implications in terms of the long-term stability and performance of perovskite solar cell devices. However, the exact mechanism of oxygen diffusion and the defect species associated with oxygen and light-induced degradation are poorly understood. Additionally, these stability issues raise important questions that have not been fully addressed. Specifically, these questions relate to: (i) the origin of the observed fast rate of oxygen-induced degradation of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films and (ii) the relationship between the film particle size, oxygen transport, intrinsic vacancies and the mechanism of oxygen-induced degradation. \n\nHere we combine experimental and computational methods to address these important questions at the microscopic level, extending our previous work on hybrid perovskites38–40,53. Specifically, we have probed the dynamics of oxygen diffusion in perovskite films and investigated how the film morphology influences reactivity to molecular oxygen. Oxygen diffusion into perovskite films is observed to occur remarkably fast with, for example, a typical film ( $500\\mathrm{nm}$ thick) reaching complete saturation within $10\\mathrm{min}$ . Density functional theory (DFT) calculations also reveal the importance of iodide vacancies as reaction mediators to form superoxide species. The results provide valuable insights for the design of perovskite devices exhibiting improved environmental stability. \n\n![](images/845ee065ece2066c2907b74c3c71bc33a51d025582acb258ae024beb880bc215.jpg) \nFigure 1 | Oxygen-induced photo-degradation. Schematic representation of the reaction steps of $\\mathsf{O}_{2}$ with ${\\mathsf{C H}}_{3}{\\mathsf{N H}}_{3}{\\mathsf{P b l}}_{3}$ . (a) Oxygen diffusion and incorporation into the lattice, $(\\pmb{6})$ photoexcitation of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ to create electrons and holes (c) superoxide formation from $\\mathsf{O}_{2},$ and (d) reaction and degradation to layered $\\mathsf{P b l}_{2},$ ${\\sf H}_{2}{\\sf O},$ $\\mathsf{I}_{2}$ and $C H_{3}N H_{2}$ . \n\n# Results \n\nOxygen diffusion. We first consider the dynamics of oxygen diffusion in hybrid perovskite films. $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ were chosen for a comparative study, since both have been widely tested in photovoltaic devices. (Note that the formula $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ refers to a perovskite material fabricated from a combination of iodide and chloride precursors.) Of the two systems, $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ films are reported to be more stable59,60 but the origin(s) of this superior stability remains unclear. In our study, films were fabricated as described in the Methods section onto clean glass substrates. X-ray diffraction (XRD) (see Supplementary Fig. 1) was used to characterize both materials, and confirmed that in both cases $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ is the compound formed. We recognize that the concentration of chlorine within the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ film may be too low to determine through XRD. The presence of any chlorine may give rise to differences in charge carrier recombination, which could influence stability, but the low Cl levels mean this is unlikely to be the dominant effect. Chlorine substitution is thus unlikely to be responsible for the improved stability of the material. \n\nIsothermal gravimetric analysis (IGA) was used to probe the dynamics of oxygen diffusion as illustrated in Fig. 2a. In a typical experiment, the sample chamber with the perovskite film was first flushed with He gas for $30\\mathrm{min}$ . Next, the weight of the perovskite sample was recorded as a function of exposure to dry air $(\\mathrm{N}_{2}=80\\%$ $\\mathrm{O}_{2}=20\\%$ over the course of $20\\mathrm{min}$ at room temperature $(25^{\\circ}\\mathrm{C})$ . As can be seen from the IGA traces in Fig. 2a, oxygen diffusion into both $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{C\\bar{H}_{3}N H_{3}P b I_{3}(\\bar{C}l)}$ films was rapid, with saturation being achieved within $5{\\mathrm{-}}10\\operatorname*{min}$ . Further evidence for the fast rate of oxygen diffusion in these two materials was obtained from time-of-flight secondary ion mass spectrometry (ToF-SIMS) measurements, in which the depth profile of oxygen throughout the films was determined. In these experiments, films of both $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ were soaked in dry air in the absence of light and ToF-SIMS data collected. The ToF-SIMS images shown in Fig. $^{2\\mathrm{b},\\mathrm{c}}$ represent slices through $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}\\mathrm{(Cl)}$ layers at a depth of approximately $200\\mathrm{nm}$ in the films, after soaking for $30\\mathrm{min}$ . 3D profiles (raw data) showing oxygen concentration as a function of film depth are also provided in Supplementary Fig. 2. Taken together, these findings demonstrate that oxygen enters the perovskite samples and is uniformly distributed throughout the films. As the time period for oxygen uptake to reach saturation is in agreement with the fast degradation rate previously observed in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ photoactive layers and devices $^{38-40}$ , we conclude that the high sensitivity of $\\mathrm{\\dot{C}H_{3}N H_{3}P b I_{3}}$ devices to oxygen is owed, in part, to the rapid rate at which oxygen can diffuse into the films. \n\n![](images/503c6a50fb587b6569b1bd8176f66b56e1a175daede704327f3a20978f29f1dd.jpg) \nFigure 2 | Oxygen diffusion. (a) Isothermal gravimetric analysis plot (IGA) of ${\\mathsf{C H}}_{3}{\\mathsf{N H}}_{3}{\\mathsf{P b l}}_{3}$ (MAPI) and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}(\\mathsf{C l})$ (MAPIC) thin films coated on non-conductive cleaned glass with 30 min of Helium soaking before oxygen exposure, where $t=0$ corresponds to the time at which oxygen was introduced into the system. (b,c) ToF-SIMS surface images $(100\\times100\\upmu\\mathrm{m})$ of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}(\\mathsf{C l})$ respectively after exposure to dry air flow with no illumination, where the maximum counts (MC) and the total number of secondary oxygen ion counts (TC) are shown with the colour scales corresponding to the interval [0, MC]. \n\nFrom the IGA data we can estimate the air $(80\\%\\mathrm{N}_{2}$ and $20\\%\\mathrm{O}_{2})$ ) diffusion coefficient, $D_{\\mathrm{a}},$ to be in the range $10^{-7}{-}10^{-9}\\mathrm{cm}^{2}\\mathrm{s}^{-1}$ for the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite material (calculations provided in SI). This value is comparable to the fast diffusion of gases into polymer thin films where, for example, the diffusion coefficient61 in poly-(3-hexylthiophene-2,5-diyl) (P3HT) thin films is of the order of $\\mathrm{1\\dot{0}^{-8}c m^{2}}\\mathsf{s}^{-1}$ . It is widely accepted that these fast diffusion kinetics are responsible for the relatively low stability of semiconducting polymer films to molecular oxygen $^{62-64}$ . As such, we propose that the fast oxygen diffusion kinetics are critical to the observed oxygen- and light-induced degradation rates seen in perovskite-based optoelectronic devices. \n\nParticle size dependence. Next we considered the effect of visible light and oxygen on the relative stability of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{C}\\mathrm{\\bar{H}}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}\\mathrm{(Cl)}$ films and devices. Figure 3a,b shows the absorption spectra of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{\\bar{CH}_{3}N H_{3}P b I_{3}(C l)}$ films on glass substrates measured as a function of ageing under illumination in dry air. Figure 3a,b reveals that both perovskite materials rapidly degrade under these conditions. However, it is apparent that $\\mathrm{CH}_{3}\\mathrm{\\bar{NH}}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ films degrade at a significantly slower rate than $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films. Figure 3c shows the power conversion efficiency (PCE) versus time profile for $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\dot{\\mathrm{Cl}})$ -based solar cells, with the devices being continuously aged in dry air under light. The corresponding current–voltage curves are provided as Supplementary Fig. 3 in Supplementary information. For these studies, a solar cell architecture of the type [FTO/compact- $\\mathrm{\\cdotTiO}_{2},$ /mesoporous$\\mathrm{TiO}_{2}/$ perovskite/spiro-OMeTAD/Au] was employed and all PCE measurements were performed on un-encapsulated devices as in previous work44. The PCEs of the solar cells were determined from current–voltage characteristics ascertained at regular time intervals over the course of $\\boldsymbol{4}\\mathrm{h}$ . In Fig. 3c, $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ devices show a relatively small $10\\%$ drop in PCE over the 4-h ageing period whereas the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\bar{\\mathrm{PbI}}_{3}$ devices display a more substantial $(\\approx80\\%)$ drop in PCE under the same ageing conditions. The better stability of the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ solar cells (compared to $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3})$ is consistent with the absorption data in Fig. 3a,b, as well as other recent reports59. The difference in stability between $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ observed here may be related to the smaller size of the particles. \n\nThe next question that arises relates to the origin of the difference in stability observed between $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ . To identify the cause(s) for this difference we first determined the yield of photo-induced superoxide $(\\mathrm O_{2}^{-})$ formation for the two perovskites. We have previously established that $\\mathrm{O}_{2}^{-}$ is the key reactive species responsible for the hybrid perovskite and device degradation38,40. Here the yield of $\\dot{\\mathrm{O}_{2}^{-}}$ was determined for both $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{\\dot{Pb}I}_{3}(\\mathrm{Cl})$ films using a hydroethidine (HE) fluorescent probe (as described in the Methods section). As detailed elsewhere38, the degradation effect we observe cannot be ascribed to degradation of the hole transporting material spiro-OMeTAD since we have not used spiro-OMeTAD in these experiments. \n\nFigure 3d shows the rate of increase in HE emission and, accordingly, the $\\mathrm{O}_{2}^{-}$ generation yield. The data in Fig. 3d show that $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ produces a significantly higher yield of superoxide than $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ , consistent with the film and device stability data in Fig. $_{3\\mathrm{a-c}}$ It is reasonable to propose that this difference in reactivity stems from differences in the particle sizes within the films. For example, the presence of chloride ions in the precursor mixture is known to slow down the rate of crystal formation, leading to larger crystals28,29. This was confirmed by taking scanning electron microscopy (SEM) images of the $\\mathrm{CH}_{3}\\mathrm{\\bar{N}H}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ films. Figure 3e,f shows that the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ film consists of crystal domains that are several hundreds of nanometres in diameter, considerably larger than those observed in the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ sample. This strongly suggests that crystal size plays a crucial role in determining the stability. \n\nIn order to test this hypothesis, we next investigated, in a systematic manner, the stability of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films composed of different crystal sizes. The controlled growth of $\\mathrm{CH}_{3}\\mathrm{\\bar{N}H}_{3}\\mathrm{PbI}_{3}$ crystals was achieved following the method previously reported by Gra¨tzel and co-workers50. In this way, we prepared samples with small ( $\\left(100\\mathrm{nm}\\right)$ , medium ( $\\left(160\\mathrm{nm}\\right)$ and large $(250\\mathrm{nm})$ perovskite crystals as confirmed by SEM. Representative SEM images are shown in Fig. 4a–c. In Fig. 4d the magnitude of the absorbance at $750\\mathrm{nm}$ is plotted against ageing time, with black, red and blue curves corresponding to films composed of small (sample 1), medium (sample 2) and large (sample 3) $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ crystallites, respectively. The corresponding absorption spectra are provided in Supplementary Fig. 4. We stress that these measurements were recorded until the $\\mathrm{C}\\dot{\\mathrm{H}}_{3}\\mathrm{N}\\mathrm{H}_{3}\\mathrm{Pb}\\mathrm{I}_{3}$ film had turned completely yellow, indicating full conversion of the perovskite to the degradation product, $\\mathrm{\\bar{PbI}}_{2}$ . It is apparent from the data in Fig. 4d that the films with large $\\mathrm{CH}_{3}\\mathrm{N}\\mathrm{\\bar{H}}_{3}\\mathrm{PbI}_{3}$ crystals are considerably more stable than the films composed of small $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ crystals. We note that all three samples showed similar rates of oxygen uptake, with the films reaching saturation within $10\\mathrm{min}$ , as determined by IGA experiments (Supplementary Fig. 5). \n\n![](images/9f6ea0f970e5537b0dc0eb5d571f7f0fe4545d01611aea6d11b8a96e4f8fe074.jpg) \nFigure 3 | Stability comparison of $\\mathbf{CH_{3}N H_{3}P b l_{3}}$ and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}(\\mathsf{C l})$ . (a,b) Light absorption spectrum for ageing $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}(\\mathsf{C l})$ under dry air and illumination $(25\\mathsf{m w c m}^{-2};$ respectively. (c) Normalized power conversion efficiency loss for photovoltaic devices employing $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ (referred to as MAPI) and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}(\\mathsf{C l})$ (referred to as MAPIC) as the light harvesting materials in an [FTO/planar- $\\cdot\\mathsf{T i O}_{2},$ /mesoporous$T_{1}0_{2},$ /perovskite/spiro-OMeTAD/Au] architecture. J-V curves obtained for these studies are shown in Supplementary Fig. 4. (d) Normalized fluorescence intensity increase of the HE probe at $610\\mathsf{n m}$ (excitation at $520{\\mathsf{n m}}$ ). $I_{\\mathsf{F}}(t)$ is the fluorescence maximum at time t, while $I_{\\mathsf{F}}(t_{0})$ is the background fluorescence intensity. $I_{\\mathsf{F}}(t)/I_{\\mathsf{F}}(t_{0})$ ratio corresponds to the yield of superoxide generation for the perovskite films. (e,f) Surface SEM images of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}(\\mathsf{C l})$ films deposited on cleaned glass substrates. \n\nNext, we consider the possible correlation between $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ crystal size, materials stability and superoxide $\\bigl(\\mathrm{O}_{2}^{-}$ ) generation yield. Figure 4e shows the measured rate of increase of $\\mathrm{O}_{2}^{-}$ species in these three samples; a correlation is observed between the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ crystallite size, stability (that is, tolerance to visible light and oxygen stress) and $\\mathrm{O}_{2}^{-}$ yield. It is evident that the $\\mathrm{CH}_{3}\\mathrm{\\tilde{NH}}_{3}\\mathrm{PbI}_{3}$ films with large crystallites show a relatively low yield of superoxide formation and display better stability. Conversely, the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films composed of smaller crystallites show a higher yield of superoxide generation and rapidly degrade within 2 days. There thus appears to be a direct correlation between yield of superoxide generation (and subsequently degradation rate) and perovskite crystallite size. \n\n![](images/f0d73ac2159cc9e8b53b6a1d4847c8c1a4253d4ad362c186b6a15b3b59bd4652.jpg) \nFigure 4 | Particle size effects. (a–c) Surface SEM images of small (sample 1), medium (sample 2) and large (sample 3) crystal sizes of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ (d) Normalized absorbance decay at $750\\mathsf{n m}$ for methylammonium lead iodide of sample 1 (small crystals, $100\\mathsf{n m}.$ , sample 2 (medium crystals, $150\\mathsf{n m}$ ) and sample 3 (large crystals, $250\\mathsf{n m};$ with degradation conditions of illumination $(25\\mathsf{m w c m}^{-2})$ and dry air. (e) Superoxide yield plot for $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ (with small (black), medium (red), large (blue) crystal sizes and a toluene dripped prepared sample (green) and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}(\\mathsf{C l})$ (brown). \n\nSuperoxide formation sites. To obtain atomic-scale insights into the energetics and defect mechanisms of the degradation process we have used ab initio simulations based on DFT. We first probed the reaction with oxygen (with no photo-generated electrons in the perovskite lattice), described by the following equation: \n\n$$\n\\mathrm{4CH_{3}N H_{3}P b I_{3}+O_{2}\\longrightarrow4P b I_{2}+2I_{2}+2H_{2}O+4C H_{3}N H_{2}}\n$$ \n\nThe enthalpy was calculated to be $+1.60\\mathrm{eV}$ per $\\mathrm{O}_{2}$ molecule, indicating that the reaction in the absence of light is unfavourable, which is consistent with observation. We have already shown that in order for the overall degradation reaction to occur, the film must be exposed to both $\\bar{\\mathrm{~O~}}_{2}$ and light in order for superoxide species to $\\mathrm{form}^{38,39}$ . The implication is that $\\mathrm{O}_{2}$ acts as an electron scavenger and absorbs electrons generated by light or an external electrical bias. \n\nThe next step in the reaction sequence is for superoxide $\\mathrm{O}_{2}^{-}$ to react with photo-oxidized $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}{^{\\ast}}$ to produce $\\mathrm{PbI}_{2}$ , $\\mathrm{I}_{2}$ , $_\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{2}$ according to the following reaction (illustrated in Fig. 1): \n\n$$\n\\mathrm{4CH_{3}N H_{3}P b I_{3}^{\\star}+O_{2}^{-}\\rightarrow4P b I_{2}+2I_{2}+2H_{2}O+4C H_{3}N H_{2}}\n$$ \n\nIn contrast to reaction (1), the calculated enthalpy for reaction (2) is negative $(-1.40\\mathrm{eV}$ per $\\mathrm{O}_{2}$ molecule), indicating that the degradation reaction is now highly favourable, again in agreement with observation. This indicates that both the photo-oxidized $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and the $\\mathrm{O}_{2}^{-}$ species are unstable with respect to the reaction products. \n\nA key step in the degradation reaction is the formation of the superoxide species according to $\\mathrm O_{2}+e^{-}=\\mathrm O_{2}^{-}$ . This raises the important question of where the superoxide forms in the crystal lattice. It is plausible that ionic defects such as iodide vacancies play a key role in mediating superoxide formation from $\\mathrm{O}_{2}$ and hence the degradation reaction. As noted, recent work52 indicates a significant population of intrinsic Schottky-type defects (a stoichiometric combination of anion and cation vacancies), whose formation can be expressed using Kro¨ger–Vink notation as: \n\n$$\nn i l\\rightarrow V_{\\mathrm{MA}}^{'}+V_{\\mathrm{Pb}}^{'\\prime}+3V_{\\mathrm{I}}^{\\bullet}+\\mathrm{MAPbI}_{3}\n$$ \n\nwhere nil represents the perfect (defect-free) $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ lattice, $V$ indicates a vacancy, subscripts indicate the type of lattice site and superscripts the effective charge of the defect (a dot for each positive charge and prime for each negative charge). Such vacancy defects may act as molecular or charge traps which in turn could mediate the electron transfer reaction with oxygen. It is known that the anion vacancy in binary lead halides can trap a photoelectron to form an $\\mathrm{~F~}$ centre24. \n\nTo investigate this process, we calculated the energetics for superoxide formation from $\\mathrm{O}_{2}$ molecules on various lattice and vacancy sites in the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite structure; the most favourable configurations and the corresponding superoxide formation energies are summarized in Fig. 5. Two main findings emerge. First, superoxide formation by direct electron transfer from the perovskite to oxygen is energetically favourable. Analysis of the electron density and bond lengths shows that the photo-generated electron resides on the $\\mathrm{O}_{2}$ molecule; upon adsorption the $\\mathrm{O}_{2}$ bond length increases from 1.22 to $1.33\\mathring{\\mathrm{A}}$ and the species becomes spin polarized. Second, superoxide formation energies indicate that vacant iodine sites are the preferred location for the reduction process in the crystal bulk. Interestingly, an iodide ion is of similar size to the superoxide species (as illustrated in Fig. 6), and in occupying an iodide vacancy, the superoxide ion restores the full octahedral coordination of $\\dot{\\mathrm{Pb}}^{2+}$ . \n\nFurther evidence for the favourable energetics of $\\mathrm{O}_{2}$ reduction is given by the calculated band structures for $\\mathrm{O}_{2}$ incorporation into $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ reported in Fig. 7. In Fig. 7a it can be seen that the unoccupied oxygen $\\pi^{*}$ anti-bonding orbital is located in the middle of the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ band gap where it can readily act as an acceptor state for photo-excited electrons in the conduction band. Moreover, when the $\\mathrm{O}_{2}^{-}$ superoxide species occupies an iodide vacancy (Fig. 7b), the oxygen states are shifted down into the valence band as a result of changes in bonding interactions, clearly indicating that it is even more energetically favourable for $\\mathrm{O}_{2}$ to be reduced by photo-excited electrons in the conduction band. \n\n![](images/56d0f049c65c71190161ebd42c24e8f3c1bc638af52eb9f458c70b0d86cb5260.jpg) \nFigure 5 | Lattice sites for superoxide formation. Schematic representation of possible $\\mathsf{O}_{2}$ binding and reduction sites in $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ ([001] plane) and corresponding superoxide formation energy: (a) face site neighbouring four iodide ions, (b) neutral iodide vacancy (with a photoelectron on the defect site) and negatively charged lead (c) and methylammonium (d) vacancies (with no photoelectron on them since this was found to be unphysical). \n\n![](images/9bfdc4966279bfca104a1bab2a175e928dcc586d1330295b745bee7d58578ace.jpg) \nFigure 6 | Size comparison of superoxide and iodide anions. Atomic structure of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ showing (a) superoxide ion, $\\mathsf{O}_{2}^{-}$ , occupying an iodide vacancy, $V_{\\mathrm{1}}^{\\times}$ (for clarity, a pseudo-cubic sub-region of the structure is shown and not the full tetragonal supercell used in the calculations). (b) Comparison of relative size of iodide and superoxide anions (using ionic radius of $\\mid^{-}$ and, for the superoxide ion, interpolation between covalent radius in $\\mathsf{O}_{2}$ and ionic radius of $\\mathsf{O}_{2}^{-}$ ). \n\nProposed degradation mechanism. To summarize our four key observations: (i) photo-induced oxygen degradation of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ shows a strong particle size dependence, (ii) structural degradation from the black perovskite phase to the yellow lead $\\mathrm{PbI}_{2}$ phase occurs on a timescale of days (see absorbance data, Fig. 3a), whereas the device performance degrades in a matter of hours (see efficiency data, Fig. 3c), (iii) rapid oxygen uptake occurs on a timescale of less than $^\\mathrm{1h}$ and results in superoxide generation, and (iv) superoxide formation is always associated with degradation and is facilitated by iodide vacancies. \n\nTo rationalize these findings, we propose a mechanism that is summarized schematically in Fig. 8. The $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ sample is under illumination throughout this process to provide a constant source of photo-excited electrons in the bulk and surface regions. Oxygen is admitted to the sample and diffuses between the particles and within an hour permeates the inter-particle regions (Fig. 8a). Superoxide species immediately begin to form at the particle surfaces as $\\mathrm{O}_{2}$ is reduced while occupying surface iodide vacancies. Over the first few hours there is an initial reaction between these superoxide species and the particle surfaces, leading to their passivation. The degradation of the particle surfaces prevents the extraction of the photocurrent65, causing the device properties such as efficiency (PCE) to decline rapidly. On a timescale of days (Fig. 8b) oxygen diffuses into the interior of the particles where it occupies bulk iodide vacancies while being reduced, leading to full structural degradation of the material. \n\n![](images/41943b14a6a5a1dd39be2bf93dc5d65663c8ee6d29d12d303542adadabc878de.jpg) \nFigure 7 | Band structure and density of states for oxygen incorporation into $\\mathbf{CH_{3}N H_{3}P b l_{3}},$ (a) $\\mathsf{O}_{2}$ in defect-free $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ and (b) $\\mathsf{O}_{2}$ at iodide vacancy in $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ . Key: blue— $\\begin{array}{r}{-C\\mathsf{H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3},}\\end{array}$ red— ${{\\bf{\\cdot}}}{\\bf{O}}_{2}$ . Note the band structure is folded due to the use of a large supercell. \n\n![](images/5295aa9355d9eecac21879bb931a062bad22e365436b5870f86f575221e3fc21.jpg) \nFigure 8 | Oxygen diffusion pathways and associated degradation regions. (a) $\\mathsf{O}_{2}$ diffusion in inter-particle regions and initial reaction with particle surfaces over a timescale of hours leading to reduction in device efficiency, open circuit voltage and photocurrent and (b) $\\mathsf{O}_{2}$ diffusion into particle bulk regions over a time scale of days leading to a phase change from the photo-absorbing perovskite phase into the non-absorbing lead iodide phase (yellow). \n\nFor both the surface and bulk reactions we would expect the particle size and iodide vacancy levels to influence the rate of reaction. It is well known that particle surfaces are normally much more reactive than the bulk; in the halide perovskites it has been shown that different particle facets can display markedly different photovoltaic behaviour66. Furthermore, Haruyama et $a l.^{67}$ have shown that in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ the most prominent surfaces are vacancy rich with defect concentrations of 1012 cm \u0002 2, and our data show that oxygen reduction occurs most readily at the iodide vacancies. Thus, the increased initial degradation rate for smaller crystallites may be directly related to the surface vacancy concentration. Figure 3 shows SEM micrographs of large crystallites with typical sizes of ca. $250\\mathrm{nm}$ and small crystallites of ca. $100\\mathrm{nm}$ . Based on these average values, we would expect the number density of surface vacancies to be around $2.4\\times\\dot{10}^{17}\\mathrm{cm}^{-3}$ in the large crystallites and around $6.0\\times10^{17}\\mathrm{cm}^{-3}$ in the small crystallites. The small crystallites thus provide more than twice as many surface adsorption/ reaction sites per unit volume as the large crystallites. \n\nIn addition, bulk adsorption/reaction sites will contribute significantly to the rate of degradation over long time-scales. Iodide vacancy concentrations in the bulk have been estimated52 at $10^{22}\\mathrm{cm}^{-3}$ , which suggests that in a typical particle, bulk vacancies will be five orders of magnitude more numerous than surface vacancies. Since our ToF-SIMS data show that $\\mathrm{O}_{2}$ can diffuse into the bulk, the increased degradation rate for smaller crystallites may be due to the shorter $\\mathrm{O}_{2}$ diffusion path lengths to the particle interiors. In general, the characteristic time constant, $t,$ for ion diffusion is given by $t=L^{2}/D,$ where $L$ is the diffusion path length and $D$ is the diffusion coefficient. The rate of oxygen permeation into the bulk of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ can be expected to drop by a factor of four for every doubling of the particle size. This model can thus account for our observations. We recognize that other factors such as the rate of reaction between the superoxide species and methylammonium cation may also limit the overall rate of degradation, but such topics are left for future investigations. \n\nFilm passivation using salt additives. Finally, a key question that arises relates to whether the stability of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films can be improved by inhibiting superoxide formation at iodide vacancies, for example, by defect passivation. To investigate this, a solution of either chloride or iodide salts of cations phenylethylammoniun or methylammonium and trimethlsulfonium iodide was spin-coated onto the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite films. Ionic passivating agents carrying bulky cations were chosen to ensure that substitution with methylammonium cations in the perovskite was unfavourable. The successful preparation of the films was confirmed by XRD analysis (see Supplementary Fig. 6). The stabilities of the coated films were examined after exposure to light and oxygen. As can be seen in Fig. 9a (raw absorbance data are presented in Supplementary Fig. 7), all the iodide saltcoated samples display an enhanced tolerance to light and oxygen (relative to the uncoated control sample), showing little or no degradation over the ageing time period. In contrast, the chloride salt derivatives showed no stability enhancement, exhibiting a comparable rate of degradation as that of an uncoated perovskite sample. We note that the iodide treated films showed no sign of any degradation over 3 weeks of ageing under light and oxygen. Furthermore, the enhanced stability of the coated samples is consistent with the superoxide generation data shown in Fig. 9b. In particular, it can be seen again that all the iodide salt coated samples show a significantly lower yield of superoxide species than the uncoated sample and the chloride salt-treated samples. \n\n![](images/ce4cb87a6c0643b3d4561a285b4096a02a14d1dd8b70a77ac0ac0316e366d07c.jpg) \nFigure 9 | Film passivation using salt additives. (a) Normalized absorbance decay at $750\\mathsf{n m}$ under illumination $(25\\mathsf{m w c m}^{-2})$ and dry air flow for a pristine $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ and $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ coated with phenylethylammonium iodide $(P h E t N H_{3}l)$ , methylammonium iodide $(M e N H_{3}l)$ , trimethylsulfonium iodide $(M e_{3}\\mathsf{S}|)$ , phenylethylammonium chloride $(P h E t N H_{3}C l),$ and methylammonium chloride $(M e N H_{3}C l)$ as described in the experimental section. (b) Superoxide yield plot comparing the generation of superoxide for $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ treated with the coatings and without. (c) Normalized power conversion efficiency loss for photovoltaic devices employing ${\\mathsf{C H}}_{3}{\\mathsf{N H}}_{3}{\\mathsf{P b l}}_{3}$ with and without a $10\\mathsf{m}{\\mathsf{M}}$ treatment of ${\\mathsf{M e N H}}_{3}{\\mathsf{I}}$ as the light harvesting material in an [FTO/planar- $\\cdot\\mathsf{T i O}_{2}/$ mesoporous- $\\cdot\\mathsf{T i O}_{2},$ /perovskite/spiro-OMeTAD/Au] architecture. J-V curves obtained for these studies are shown in the Supplementary Fig. 13. \n\nTo confirm that the iodide salt treatments are indeed passivating iodide defects rather than some other effect, we performed time-resolved photoluminescence, IGA, SEM and superoxide yield measurements. IGA data presented in Supplementary Fig. 8 indicate similar fast oxygen diffusion kinetics in both $\\mathrm{\\bar{CH}}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ treated and untreated films. In contrast, a control sample comprising a $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ film encapsulated in glass showed little or no weight increase upon exposure to oxygen; in this instance the glass layer functions as an oxygen blocking layer. In addition, time-resolved photoluminescence measurements were performed on perovskite films treated with different concentrations (0.001 M, 0.005 M and $0.01\\mathrm{M})$ of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ . As can be seen from the data provided in Supplementary Fig. 9, increasing the iodide salt concentration leads to an increased photoluminescence lifetime. Moreover, this observation is consistent with the iodide salt treatment reducing the number of defects and therefore the number of trap states for non-radiative recombination, resulting in longer emission lifetimes. Recent studies68,69 have found that alkali metal halide salts introduced at the perovskite interface can decrease halide vacancy levels, resulting in improved device performance. \n\nNext, the relative stability and superoxide yield of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films treated with different concentrations of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ were investigated. The relationship between $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ concentration, stability and superoxide yield is shown in Supplementary Fig. 10, which shows that increasing the concentration of $\\mathrm{C}\\mathrm{\\bar{H}}_{3}\\mathrm{N}\\mathrm{H}_{3}\\mathrm{I}$ salt leads to lower yields of superoxide generation and consequently better stability. Finally, surface SEM images were taken of a treated and an untreated $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ film to show that the treatment does not induce any significant morphological changes to the film’s surface (provided in Supplementary Fig. 11). Taken together, the results in Supplementary Figs 8–11 strongly suggest that salt treatments passivate the crystal defects rather than providing a physical barrier layer to oxygen diffusion. \n\nPassivation of crystal defects using iodide salts reduces superoxide yields and enhances film stabilities, but it is not known whether they improve device stability. To address this question, cells were fabricated and characterized under different conditions (as described in the experimental section). The results, shown in Fig. 9c and Supplementary Figs 12,13 and Supplementary Table 1, indicate that solar cells that use $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ -coated $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films exhibit better stability than those that use uncoated perovskite layers. More specifically, exposure of devices using uncoated perovskite layers to light and dry air for just $2.5\\mathrm{h}$ leads to a $50\\%$ drop in the PCE. In contrast, devices containing $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ coated layers exhibit a significantly smaller drop in efficiency $(10\\%)$ over the same ageing period. The relationships between concentration of the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ coating in solution and the device stability are shown in Supplementary Figs 12,13 and Supplementary Table 1. It is clear from these results that increasing the concentration of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ salt leads to progressively higher stability. \n\nThese results further confirm that the iodide anion from the salt passivates the iodide vacancies in the crystal, and by occupying the otherwise vacant iodide sites leads to increased stability by suppressing superoxide formation. We note that degradation of the coated devices is not halted completely, which suggests that other factors also influence overall device stability. For example, it is possible that iodide vacancies in the bulk are not filled by iodide ions from the coating and these can still act as sites for superoxide generation. Nevertheless, it is clear from the present findings that the iodide salt coatings lead to significant improvements in device stability. \n\n# Discussion \n\nThe present study suggests that iodide defects in the $\\mathrm{CH}_{3}\\mathrm{N}\\mathrm{\\bar{H}}_{3}\\mathrm{PbI}_{3}$ structure are key sites for superoxide formation. In addition, the results demonstrate that iodide salt treatment can be employed to reduce the number of problematic iodide vacancies, thereby hindering the electron transfer reaction that generates superoxide species. Although this study is not exhaustive it does highlight a critical issue for further work, and could include probing the combined effect of oxygen and water on $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Pb}\\mathrm{I}_{3}$ as well as large-scale atomistic simulations of oxygen diffusion and iodine interstitials. \n\nIn conclusion, a combination of IGA, photoluminescence, SIMS and ab initio simulation techniques has provided mechanistic insights into oxygen- and light-induced degradation of perovskite solar cells. We found that fast oxygen diffusion into $\\mathrm{\\bar{CH}}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ films is accompanied by formation of superoxide species, which are critical to oxygen-induced degradation. The yield of superoxide $(\\mathrm O_{2}^{-})$ species and thus the degradation rate are dependent on crystallite size when exposed to light and oxygen: perovskite films composed of small crystallites show high yields of photo-induced superoxide formation and therefore low stability. $\\vert A b$ initio simulations indicate that iodide vacancies are the preferred sites in mediating the photo-induced formation of superoxide species from $\\mathrm{O}_{2}$ . We also demonstrated that thin-film passivation with iodide salts leads to reduced superoxide formation, and consequently enhanced film and device stabilities. These combined results improve our fundamental understanding of degradation phenomena in perovskite solar cells, and provide a strategy for greatly improving their long-term stability. \n\n# Methods \n\nMaterials and synthesis. All chemicals were purchased from Sigma-Aldrich and used as received, except $\\mathrm{TiO}_{2}$ nanoparticles from Dyesol and methylammonium iodide (MAI), which were synthesized in the lab. Methylamine $33\\%$ wt solution in ethanol (6.2 ml, 0.046 mol) was cooled down in an ice bath. Hydroiodic acid $55\\%$ wt solution in water $(10\\mathrm{ml},0.073\\mathrm{mol})$ ) was then added dropwise under vigorous stirring. The reaction was stirred for $^{\\textrm{1h}}$ at $0^{\\circ}\\mathrm{C}$ . The product precipitated from the solution as a white-yellowish solid. Ethanol $(5\\mathrm{ml})$ was added to ensure full precipitation of the solid, which was filtered and washed with cold ethanol. Recrystallization of the product in ethanol/diethyl ether afforded the pure compound as white crystalline solid $(6.4\\mathrm{g},87\\%)$ . Synthesis of phenyl-ethylammonium iodide (PEAI): Phenylethylamine $33\\%$ wt solution in ethanol (6.2 ml, $0.046\\mathrm{mol}$ ) was cooled down in an ice bath. Hydroiodic acid $55\\%$ wt solution in water $\\mathrm{10ml,0.073mol}$ was then added dropwise under vigorous stirring. The reaction was stirred for $^{\\textrm{1h}}$ at $0{}^{\\circ}\\mathrm{C}$ . The product precipitated from the solution as a white-yellowish solid. Ethanol $(5\\mathrm{ml})$ was added to ensure full precipitation of the solid, which was filtered and washed with cold ethanol. Recrystallization of the product in ethanol/diethyl ether afforded the pure compound as white crystalline solid. \n\nFilm fabrication. All films were deposited onto clean glass substrates of ca. 1 cm by $1\\mathrm{cm}$ in size. The glass substrates were washed sequentially in acetone, water and isopropylalcohol (IPA) under sonication for $10\\mathrm{min}$ during each washing cycle. A Laurell Technologies WS-650MZ-23NPP Spin Coater was used to fabricate the films. (a) $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ : A $1\\mathbf{M}$ solution of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ was formed by adding $\\mathrm{PbI}_{2}$ in a 1:1 molar ratio with MAI in a solvent mixture of $7{:}3\\ \\gamma$ -butyrolactone to DMSO. This solution was then spin-coated onto the substrates using a consecutive two-step spin program under a nitrogen atmosphere in a glove box. The first spinning cycle was performed at $1{,}000\\mathrm{r.p.m}$ . for $10s$ followed by ${5,000}\\mathrm{r.p.m}$ . for $20s$ , as reported by Jeon et $a l.^{70}$ . During the second phase, the substrate was treated with toluene (ca. $350\\mathrm{ml}$ ) drop-casting. The films were then annealed at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ (b) Crystal size variation: Films were prepared with controlled crystal size in accordance with the two-step deposition method described by Gra¨tzel et $a l.^{50}$ . Twenty microlitres of a 1 M solution of $\\mathrm{PbI}_{2}$ in DMF was spin-coated onto glass substrates at ${3,000}\\mathrm{r.p.m}$ . for 5 s and then at $6{,}000\\mathrm{r.p.m}$ . for another 5 s. The films were then annealed at $40^{\\circ}\\mathrm{C}$ for $3\\mathrm{min}$ followed by heating at $100^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ . Once the films had cooled to room temperature, $200\\upmu\\mathrm{l}$ of $0.038\\mathbf{M}$ (sample 3), $0.050\\mathrm{M}$ (sample 2) and $0.063\\mathrm{M}$ (sample 1) MAI in IPA solution were loaded on top of them for $20\\mathrm{s}$ , before spinning at $4{,}000\\mathrm{r}{.}\\mathrm{p}{.}\\mathrm{m}$ . for $20s$ Films were then annealed at $100^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ (c) Chlorine treated $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ : A $1\\mathrm{M}$ solution was created by dissolving $\\mathrm{PbCl}_{2}$ and MAI in a 1:3 ratio in DMF. The solution was then spin-coated onto substrates at $1{,}000\\mathrm{r.p.m}$ . for $10s$ followed by ${5,000}\\mathrm{r.p.m}$ . for $20s$ . Annealing was carried out by leaving the films at room temperature for $30\\mathrm{min}$ followed by heating at $100^{\\circ}\\mathrm{C}$ for an hour. \n\nDevice fabrication. FTO-coated glass substrates $\\mathrm{100}\\times25\\mathrm{mm},$ 2.3 mm thick TEC15, Pilkington) were first etched with $Z\\mathrm{n}$ power and aqueous hydrochloric acid $(37\\%)$ , and then cut into $25\\times25\\mathrm{{mm}}$ pieces followed by cleaning sequentially in acetone, distilled water and IPA under sonication for $10\\mathrm{min}$ during each washing cycle. A compact $\\mathrm{TiO}_{2}$ layer was prepared by spin coating a solution comprised of \n\n$350\\upmu\\mathrm{l}$ titanium isopropoxide (Aldrich), $35\\upmu\\mathrm{l}$ hydrochloric acid $(37\\%)$ and $5\\mathrm{ml}$ anhydrous ethanol at $5{,}000\\mathrm{r.p.m}$ . for $30s$ . The $\\mathrm{TiO}_{2}$ films were sintered at $160^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ and then at $500^{\\circ}\\mathrm{C}$ for $45\\mathrm{{min}}$ . Next, a mesoporous- $\\mathrm{TiO}_{2}$ film was deposited onto this using a solution of $20\\mathrm{nm}$ particle transparent titania paste (18NR-T, Dyesol). The solution was spin-coated onto the substrates at ${5,000}\\mathrm{r.p.m}$ . for $30s$ . Once spun, the films were dried on a hotplate at $80^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ , and then sintered at $500^{\\circ}\\mathrm{C}$ for $45\\mathrm{min}$ . The desired perovskite layer was prepared using a consecutive five-step spin program inside glovebox as previously described40. In instances where iodine salt layer were used, 1, 2, 6 and $10\\mathrm{mM}$ solution of MAI with IPA were prepared respectively. The solution was then spin-coated onto the perovskite layer. The Spiro-OMeTAD hole conductor layer was spin-coated onto the perovskite films from a solution of $72.3\\:\\mathrm{mg}\\mathrm{ml}^{\\dot{-}1}\\:2,2^{\\prime},7,\\dot{7}^{\\prime}.$ -tetrakis(N,N-di-p-methoxyphenylamine ${\\bf\\nabla})9,9^{\\prime}$ -spirobifluorene (spiro-OMeTAD) powder in $1\\mathrm{ml}$ anhydrous chlorobenzene. The spiro-OMeTAD solution contained additives including $17.5\\upmu\\mathrm{l}$ lithium bis(trifluoromethane) sulfonimide lithium salt (Li-TFSl) and $28.8\\upmu\\mathrm{l}$ 4-tert-butylpyridine (tBP). Finally, a $100\\mathrm{nm}$ -thick gold contact was evaporated under vacuum (approximately $10^{-6}\\mathrm{T}$ at a rate of $0.2\\:\\mathrm{nm}\\:s^{-1},$ ) with an active pixel area of $0.12\\mathrm{cm}^{2}$ . \n\nCurrent–voltage (JV) measurements. The JV characteristics were carried out using an AM1.5 simulated solar illumination (Oriel Instruments) and a Keithley 2400 source meter. Calibration was performed with a silicon photodiode before measurement. The scans were performed at a rate of $0.125\\mathrm{V}_{\\mathrm{~}}^{\\bullet}-1$ for both forward scan (from short circuit open circuit) and backward scan (in the opposite direction). Cells were placed unmasked under continuous 1 sun illumination during aging and were masked during each scan to ensure the active area $(0.12\\mathrm{{cm}}^{2})$ ) is same for all measured devices. \n\nSuperoxide measurements. A stock $31.7\\upmu\\mathrm{M}$ solution of the HE probe was prepared by dissolving $10\\mathrm{mg}$ in $10\\mathrm{ml}$ of dry toluene; sonication was used to facilitate miscibility. Films were then added to $10\\mathrm{ml}$ of $0.317\\upmu\\mathrm{M}$ solution created from the stock solution. Photoluminescence spectra were recorded using an excitation wavelength of $520\\mathrm{nm}$ and slit widths of $10\\mathrm{mm}$ on a Horiba Yobin-Ybon Fluorolog-3 spectrofluorometer. \n\nFilm coatings. A $0.01\\mathrm{M}$ solution was prepared by dissolving the iodide salt (phenylethylammonium iodide, MAI or trimethylsulfonium iodide) in a 1:4 solvent mixture of IPA to chlorobenzene. One hundered microlitres of this solution was then dripped onto pre-deposited perovskite films with a 20 s loading time before spinning at $4{,}000\\mathrm{r.p.m}$ . and annealing at $100^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ . The chloride salt derivatives of the cations phenylethylammonium and methylammonium were prepared using the same protocol. \n\nAgeing conditions. Films were sealed in a controlled environment, where dry air was gassed through for the duration of the degradation and illumination was provided by a tungsten lamp equipped with a UV-blocking filter as previously reported38,40. \n\nSpectroscopy and microscopy. $^1\\mathrm{H}$ NMR was recorded on a $400\\mathrm{MHz}$ Bruker spectrometer running and analysed using TopSpin software. Deuterated acetone was employed as the reference. UV–Vis was performed on a PerkinElmer UV/VIS Spectrometer Lambda 25. XRD patterns were measured on a PANalytical X’Pert Pro MRD diffractometer using Ni filtered Cu $K_{\\alpha}$ radiation at $40\\mathrm{kV}$ and $40\\mathrm{mA}$ . SEM-EDX measurements were carried out on a JEOL 6400 scanning electron microscope operated at $20\\mathrm{kV}$ . IGA measurements were conducted on a Mettler Toledo TGA spectrometer. For ToF-SIMS samples were fabricated onto clean glass substrates. The samples were then soaked under dry flux in the dark for an hour before the ToF-SIMS measurements were recorded. Data were obtained using an IONTOF ToF.SIMS-Qtac LEIS spectrometer employing an Argon sputter gun for oxygen ion detection. \n\nAb initio calculations. DFT calculations were performed using the numeric atomcentred basis set all-electron code FHI-AIMS71,72. Tight basis sets were used with tier 2 basis functions for all species. Electronic exchange and correlation were modelled with the semi-local PBE exchange-correlation functional73. For the treatment of spin orbit coupling we used an atomic zeroth-order regular approximation $(\\mathrm{ZORA})^{71}$ . Van der Waals forces were accounted for by applying a Tkatchenko–Sheffler electrodynamic screening scheme74. $\\mathrm{O}_{2}$ absorption in the bulk was calculated using a $2\\times2\\times1$ supercell (giving a tetragonal cell of 192 atoms). A gamma point offset grid at a density of $0.\\overset{\\smile}{04}\\mathring{\\mathrm{A}}^{-1}$ was used for $k$ -point sampling. Structures were relaxed with convergence criteria of $10^{^{\\bullet}-4}\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ for forces, $10^{-5}$ electrons for the electron density and $10^{-7}\\mathrm{eV}$ for the total energy. These settings ensured highly converged energies and equilibrium distances. \n\nData availability. The data that support the findings of this study are available from the authors on reasonable request. \n\n# References \n\n1. Tan, Z.-K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n2. Lin, Q., Armin, A., Nagiri, R. C. R., Burn, P. L. & Meredith, P. Electro-optics of perovskite solar cells. Nat. Photonics 9, 106–112 (2015). \n3. Hoye, R. L. Z. et al. Enhanced performance in fluorene-free organometal halide perovskite light-emitting diodes using tunable, low electron affinity oxide electron injectors. Adv. Mater. 27, 1414–1419 (2015). \n4. Xing, G. et al. Low-temperature solution-processed wavelength-tunable perovskites for lasing. Nat. Mater. 13, 476–480 (2014). Chin, X. Y., Cortecchia, D., Yin, J., Bruno, A. & Soci, C. Lead iodide perovskite light-emitting field-effect transistor. Nat. Commun. 6, 7383 (2015). \n6. Gr¨atzel, M. The light and shade of perovskite solar cells. Nat. Mater. 13, 838–842 (2014). \n7. Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n8. Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n9. Chen, W. et al. Efficient and stable large-area perovskite solar cells with inorganic charge extraction layers. Science 350, 944–948 (2015). \n10. Yang, W. S. et al. High-performance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237 (2015). \n11. Berry, J. et al. Hybrid organic–inorganic perovskites (HOIPs): opportunities and challenges. Adv. Mater. 27, 5102–5112 (2015). \n12. Kaltenbrunner, M. et al. Flexible high power-per-weight perovskite solar cells with chromium oxide-metal contacts for improved stability in air. Nat. Mater. 14, 1032–1039 (2015). \n13. Xiao, Z. et al. Giant switchable photovoltaic effect in organometal trihalide perovskite devices. Nat. Mater. 14, 193–198 (2015). \n14. McMeekin, D. P. et al. A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells. Science 351, 151–155 (2016). \n15. Babayigit, A., Ethirajan, A., Muller, M. & Conings, B. Toxicity of organometal halide perovskite solar cells. Nat. Mater. 15, 247–251 (2016). \n16. Eperon, G. E. et al. Perovskite-perovskite tandem photovoltaics with optimized band gaps. Science 354, 861–865 (2016). \n17. Saliba, M. et al. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). \n18. Soon, Y. W. et al. Correlating triplet yield, singlet oxygen generation and photochemical stability in polymer/fullerene blend films. Chem. Commun. 49, 1291–1293 (2013). \n19. Berhe, T. A. et al. Organometal halide perovskite solar cells: degradation and stability. Energy Env. Sci. 9, 323–356 (2016). \n20. Pearson, A. J. et al. Oxygen degradation in mesoporous $\\mathrm{Al_{2}O_{3}/C H_{3}N H_{3}P b I_{3-x}C l_{x}}$ perovskite solar cells: kinetics and mechanisms. Adv. Energy Mater. 6, 1600014 (2016). \n21. Yuan, H. et al. Degradation of methylammonium lead iodide perovskite structures through light and electron beam driven ion migration. J. Phys. Chem. Lett. 7, 561–566 (2016). \n22. Christians, J. A., Miranda Herrera, P. A. & Kamat, P. V. Transformation of the excited state and photovoltaic efficiency of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite upon controlled exposure to humidified air. J. Am. Chem. Soc. 137, 1530–1538 (2015). \n23. Yang, J., Siempelkamp, B. D., Liu, D. & Kelly, T. L. Investigation of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ degradation rates and mechanisms in controlled humidity environments using in situ techniques. ACS Nano 9, 1955–1963 (2015). \n24. Schoonman, J. Organic–inorganic lead halide perovskite solar cell materials: a possible stability problem. Chem. Phys. Lett. 619, 193–195 (2015). \n25. Tiep, N. H., Ku, Z. & Fan, H. J. Recent advances in improving the stability of perovskite solar cells. Adv. Energy Mater. 6, 1501420 (2016). \n26. Tian, Y. et al. Mechanistic insights into perovskite photoluminescence enhancement: light curing with oxygen can boost yield thousandfold. Phys. Chem. Chem. Phys. 17, 24978–24987 (2015). \n27. Leguy, A. M. A. et al. Reversible hydration of $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ in films, single crystals, and solar cells. Chem. Mater. 27, 3397–3407 (2015). \n28. Zhang, L. & Sit, P. H.-L. Ab initio study of interaction of water, hydroxyl radicals, and hydroxide ions with $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ surfaces. J. Phys. Chem. C 119, 22370–22378 (2015). \n29. Misra, R. K. et al. Temperature- and component-dependent degradation of perovskite photovoltaic materials under concentrated sunlight. J. Phys. Chem. Lett. 6, 326–330 (2015). \n30. Deretzis, I. et al. Atomistic origins of $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ degradation to $\\mathrm{PbI}_{2}$ in vacuum. Appl. Phys. Lett. 106, 131904 (2015). \n31. Han, Y. et al. Degradation observations of encapsulated planar $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite solar cells at high temperatures and humidity. J. Mater. Chem. A 3, 8139–8147 (2015). \n32. Guerrero, A. et al. Interfacial degradation of planar lead halide perovskite solar cells. ACS Nano 10, 218–224 (2016). \n33. Song, D. et al. Degradation of organometallic perovskite solar cells induced by trap states. Appl. Phys. Lett. 108, 093901 (2016). \n34. Nie, W. et al. Light-activated photocurrent degradation and self-healing in perovskite solar cells. Nat. Commun. 7, 11574 (2016). \n35. Ahn, N. et al. Trapped charge-driven degradation of perovskite solar cells. Nat. Commun. 7, 13422 (2016). \n36. Li, B., Li, Y., Zheng, C., Gao, D. & Huang, W. Advancements in the stability of perovskite solar cells: degradation mechanisms and improvement approaches. RSC Adv. 6, 38079–38091 (2016). \n37. You, J. et al. Improved air stability of perovskite solar cells via solutionprocessed metal oxide transport layers. Nat. Nanotechnol. 11, 75–81 (2016). \n38. Aristidou, N. et al. The role of oxygen in the degradation of methylammonium lead trihalide perovskite photoactive layers. Angew. Chem. Int. Ed. 54, 8208–8212 (2015). \n39. O’Mahony, F. T. F. et al. Improved environmental stability of organic lead trihalide perovskite-based photoactive-layers in the presence of mesoporous TiO2. J. Mater. Chem. A 3, 7219–7223 (2015). \n40. Bryant, D. et al. Light and oxygen induced degradation limits the operational stability of methylammonium lead triiodide perovskite solar cells. Energy Environ. Sci. 9, 1655–1660 (2016). \n41. Ball, J. M., Lee, M. M., Hey, A. & Snaith, H. J. Low-temperature processed meso-superstructured to thin-film perovskite solar cells. Energy Environ. Sci. 6, 1739–1743 (2013). \n42. Bastiani, M. D., D’Innocenzo, V., Stranks, S. D., Snaith, H. J. & Petrozza, A. Role of the crystallization substrate on the photoluminescence properties of organo-lead mixed halides perovskites. APL Mater. 2, 081509 (2014). \n43. Grancini, G. et al. The impact of the crystallization processes on the structural and optical properties of hybrid perovskite films for photovoltaics. J. Phys. Chem. Lett. 5, 3836–3842 (2014). \n44. Nie, W. et al. High-efficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 347, 522–525 (2015). \n45. de Quilettes, D. W. et al. Impact of microstructure on local carrier lifetime in perovskite solar cells. Science 348, 683–686 (2015). \n46. Srimath Kandada, A. R. & Petrozza, A. Photophysics of hybrid lead halide perovskites: the role of microstructure. Acc. Chem. Res. 49, 536–544 (2016). \n47. Sharenko, A. & Toney, M. F. Relationships between lead halide perovskite thin-film fabrication, morphology, and performance in solar cells. J. Am. Chem. Soc. 138, 463–470 (2016). \n48. Zhang, W. et al. Enhanced optoelectronic quality of perovskite thin films with hypophosphorous acid for planar heterojunction solar cells. Nat. Commun. 6, 10030 (2015). \n49. Salim, T. et al. Perovskite-based solar cells: impact of morphology and device architecture on device performance. J. Mater. Chem. A 3, 8943–8969 (2015). \n50. Im, J.-H., Jang, I.-H., Pellet, N., Gra¨tzel, M. & Park, N.-G. Growth of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ cuboids with controlled size for high-efficiency perovskite solar cells. Nat. Nanotechnol. 9, 927–932 (2014). \n51. Li, X. et al. Improved performance and stability of perovskite solar cells by crystal crosslinking with alkylphosphonic acid o-ammonium chlorides. Nat. Chem. 7, 703–711 (2015). \n52. Walsh, A., Scanlon, D. O., Chen, S., Gong, X. G. & Wei, S.-H. Self-regulation mechanism for charged point defects in hybrid halide perovskites. Angew. Chem. Int. Ed. 54, 1791–1794 (2015). \n53. Eames, C. et al. Ionic transport in hybrid lead iodide perovskite solar cells. Nat. Commun. 6, 7497 (2015). \n54. Azpiroz, J. M., Mosconi, E., Bisquert, J. & De Angelis, F. Defect migration in methylammonium lead iodide and its role in perovskite solar cell operation. Energy Environ. Sci. 8, 2118–2127 (2015). \n55. Yang, T.-Y., Gregori, G., Pellet, N., Gra¨tzel, M. & Maier, J. The significance of ion conduction in a hybrid organic–inorganic lead-iodide-based perovskite photosensitizer. Angew. Chem. Int. Ed. 54, 7905–7910 (2015). \n56. Richardson, G. et al. Can slow-moving ions explain hysteresis in the current–voltage curves of perovskite solar cells? Energy Environ. Sci. 9, 1476–1485 (2016). \n57. Egger, D. A., Rappe, A. M. & Kronik, L. Hybrid organic–inorganic perovskites on the move. Acc. Chem. Res. 49, 573–581 (2016). \n58. de Quilettes, D. W. et al. Photo-induced halide redistribution in organicinorganic perovskite films. Nat. Commun. 7, 11683 (2016). \n59. Colella, S. et al. $\\mathrm{MAPbI_{3-x}C l_{x}}$ mixed halide perovskite for hybrid solar cells: the role of chloride as dopant on the transport and structural properties. Chem. Mater. 25, 4613–4618 (2013). \n60. Aldibaja, F. K. et al. Effect of different lead precursors on perovskite solar cell performance and stability. J. Mater. Chem. A 3, 9194–9200 (2015). \n61. Hintz, H. et al. Photodegradation of P3HT—a systematic study of environmental factors. Chem. Mater. 23, 145–154 (2011). \n62. L¨uer, L. et al. Oxygen-induced quenching of photoexcited states in polythiophene films. Org. Electron. 5, 83–89 (2004). \n63. Jørgensen, M. et al. Stability of polymer solar cells. Adv. Mater. 24, 580–612 (2012). \n64. Beaupre´, S. & Leclerc, M. PCDTBT: en route for low cost plastic solar cells. J. Mater. Chem. A 1, 11097 (2013). \n65. Calloni, A. et al. Stability of organic cations in solution-processed $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskites: formation of modified surface layers. J. Phys. Chem. C 119, 21329–21335 (2015). \n66. Leblebici, S. Y. et al. Facet-dependent photovoltaic efficiency variations in single grains of hybrid halide perovskite. Nat. Energy 1, 16093 (2016). \n67. Haruyama, J., Sodeyama, K., Han, L. & Tateyama, Y. Termination dependence of tetragonal $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ surfaces for perovskite solar cells. J. Phys. Chem. Lett. 5, 2903–2909 (2014). \n68. Yen, H.-J. et al. Large grained perovskite solar cells derived from single-crystal perovskite powders with enhanced ambient stability. ACS Appl. Mater. Interfaces 8, 14513–14520 (2016). \n69. Boopathi, K. M. et al. Synergistic improvements in stability and performance of lead iodide perovskite solar cells incorporating salt additives. J. Mater. Chem. A 4, 1591–1597 (2016). \n70. Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n71. Blum, V. et al. Ab initio molecular simulations with numeric atom-centered orbitals. Comput. Phys. Commun. 180, 2175–2196 (2009). \n72. Ren, X. et al. Resolution-of-identity approach to Hartree–Fock, hybrid density functionals, RPA, MP2 and GW with numeric atom-centered orbital basis functions. New J. Phys. 14, 053020 (2012). \n73. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n74. Tkatchenko, A., Ambrosetti, A. & DiStasi, R. A. Jr. Interatomic methods for the dispersion energy derived from the adiabatic connection fluctuation-dissipation theorem. J. Chem. Phys. 138, 074106 (2013). \n\n# Acknowledgements \n\nM.S.I. acknowledges support from the EPSRC for the Energy Materials Programme grant (EP/K016288) and Archer HPC facilities through the Materials Chemistry Consortium (EP/L000202). S.A.H. acknowledges financial support from EPRSC via EP/M023532/1, EP/K010298/1 and EP/K030671/1 grants. We thank L.M. Peter (Bath) and C.A.J. Fisher (JFCC, Nagoya) for useful discussions. \n\n# Author contributions \n\nS.A.H. conceived and supervised the experimental project. M.S.I. and C.E. conceived and performed the computational work. N.A. performed optical spectroscopy, superoxide yield, salt coating experiments and microscopy studies, I.S.-M. conducted optical spectroscopy experiments, J.K. conducted the salt coating experiments and X.B. fabricated and characterized the solar cell devices. S.A.H., N.A., M.S.I. and C.E. drafted the initial versions of the paper. All authors contributed to the analysis, discussion and writing of the final version of the paper. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Aristidou, N. et al. Fast oxygen diffusion and iodide defects mediate oxygen-induced degradation of perovskite solar cells. Nat. Commun. 8, 15218 doi: 10.1038/ncomms15218 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1038_ncomms15437", + "DOI": "10.1038/ncomms15437", + "DOI Link": "http://dx.doi.org/10.1038/ncomms15437", + "Relative Dir Path": "mds/10.1038_ncomms15437", + "Article Title": "Efficient hydrogen production on MoNi4 electrocatalysts with fast water dissociation kinetics", + "Authors": "Zhang, J; Wang, T; Liu, P; Liao, ZQ; Liu, SH; Zhuang, XD; Chen, MW; Zschech, E; Feng, XL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Various platinum-free electrocatalysts have been explored for hydrogen evolution reaction in acidic solutions. However, in economical water-alkali electrolysers, sluggish water dissociation kinetics (Volmer step) on platinum-free electrocatalysts results in poor hydrogen-production activities. Here we report a MoNi4 electrocatalyst supported by MoO2 cuboids on nickel foam (MoNi4/MoO2@Ni), which is constructed by controlling the outward diffusion of nickel atoms on annealing precursor NiMoO4 cuboids on nickel foam. Experimental and theoretical results confirm that a rapid Tafel-step-decided hydrogen evolution proceeds on MoNi4 electrocatalyst. As a result, the MoNi4 electrocatalyst exhibits zero onset overpotential, an overpotential of 15 mV at 10 mA cm(-2) and a low Tafel slope of 30 mV per decade in 1M potassium hydroxide electrolyte, which are comparable to the results for platinum and superior to those for state-of-the-art platinum-free electrocatalysts. Benefiting from its scalable preparation and stability, the MoNi4 electrocatalyst is promising for practical water-alkali electrolysers.", + "Times Cited, WoS Core": 995, + "Times Cited, All Databases": 1031, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000401513800001", + "Markdown": "# Efficient hydrogen production on MoNi4 electrocatalysts with fast water dissociation kinetics \n\nJian Zhang1, Tao Wang2, Pan Liu3,4, Zhongquan Liao5, Shaohua Liu1, Xiaodong Zhuang1, Mingwei Chen3,4, Ehrenfried Zschech5 & Xinliang Feng1 \n\nVarious platinum-free electrocatalysts have been explored for hydrogen evolution reaction in acidic solutions. However, in economical water-alkali electrolysers, sluggish water dissociation kinetics (Volmer step) on platinum-free electrocatalysts results in poor hydrogen-production activities. Here we report a ${M o N i_{4}}$ electrocatalyst supported by ${\\mathsf{M o O}}_{2}$ cuboids on nickel foam $(M_{0}{\\mathsf{N i}}_{4}/{M_{0}\\mathsf{O}}_{2}@{\\mathsf{N i}}),$ , which is constructed by controlling the outward diffusion of nickel atoms on annealing precursor $N i M o O_{4}$ cuboids on nickel foam. Experimental and theoretical results confirm that a rapid Tafel-step-decided hydrogen evolution proceeds on $M o N i_{4}$ electrocatalyst. As a result, the $M o N i_{4}$ electrocatalyst exhibits zero onset overpotential, an overpotential of $15\\mathsf{m V}$ at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ and a low Tafel slope of $30\\mathsf{m V}$ per decade in 1 M potassium hydroxide electrolyte, which are comparable to the results for platinum and superior to those for state-of-the-art platinum-free electrocatalysts. Benefiting from its scalable preparation and stability, the $M o N i_{4}$ electrocatalyst is promising for practical water-alkali electrolysers. \n\nrowing concern about the energy crisis and the seriousness of environmental contamination urgently demand the development of renewable energy sources as feasible alternatives to diminishing fossil fuels. Owing to its high energy density and environmentally friendly characteristics, molecular hydrogen is an attractive and promising energy carrier to meet future global energy demands1,2. In many of the approaches to hydrogen production, the electrocatalytic hydrogen evolution reaction (HER) from water splitting is the most economical and effective route for the future hydrogen economy3–6. To accelerate the sluggish HER kinetics, particularly in alkaline electrolytes, highly active and durable electrocatalysts are essential to lower the kinetic HER overpotential7,8. As a benchmark HER electrocatalyst with a zero HER overpotential, the precious metal platinum (Pt) plays a dominant role in present $\\mathrm{H}_{2}$ -production technologies, such as water-alkali electrolysers9–11. Unfortunately, the scarcity and high cost of Pt seriously impede its large-scale applications in electrocatalytic HERs. \n\nTo develop efficient and earth-abundant alternatives to Pt as HER electrocatalysts, great efforts have been made to understand the fundamental HER mechanisms on the surfaces of electrocatalysts in alkaline environments12,13. The HER kinetics in alkaline solutions involves two steps: electron-coupled water dissociation (the Volmer step for the formation of adsorbed hydrogen); and the concomitant combination of adsorbed hydrogen into molecular hydrogen (the Heyrovsky or Tafel step; Supplementary Note 1)12,14. Accordingly, the HER activity of an electrocatalyst in alkaline electrolytes is synergistically dominated by the prior Volmer step and subsequent Tafel step13. The low energy barrier $(\\Delta G(\\mathrm{H}_{2}\\mathrm{O}){=}0.44\\mathrm{eV})$ of the Volmer step provides the Pt catalyst with a fast Tafel step-determined HER process (Tafel $\\mathrm{slop}=30\\mathrm{mV}$ per decade) in alkaline electrolytes, which is responsible for its excellent HER activity12,15. Inspired by the fundamental HER mechanism that occurs on Pt, the development of novel $\\mathrm{\\Pt}$ -free electrocatalysts with a significantly accelerated Volmer step is an appealing approach. Recently, several electrocatalysts with a decreased HER overpotential, such as CoP/S (with an overpotential at $10\\operatorname{mA}{\\mathrm{cm}^{-2}}$ $\\mathrm{\\sim48\\mathrm{mV}}$ ) and $\\mathbf{Mo}_{2}\\mathbf{C}/$ graphene (with an overpotential at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ : $\\sim34\\mathrm{mV})$ have been reported in acidic solutions16,17. Nevertheless, under alkaline conditions, the sluggish Volmer step on these $\\mathrm{Pt}$ -free electrocatalysts results in far lower HER activity than the Pt catalyst18–21. \n\nIn past decades, various Ni- or Mo-based oxides, hydroxides, layered double hydroxides, phosphides and sulfides have been reported as electrocatalysts for water splitting. Ni atoms are broadly recognized as excellent water dissociation centres, while Mo atoms have superior adsorption properties towards hydrogen13,22–24. Therefore, Mo–Ni-based alloy electrocatalysts $(\\mathrm{Mo}_{x}\\mathrm{Ni}_{y})$ can be promising candidates to effectively reduce the energy barrier of the Volmer step and speed up the sluggish HER kinetics under alkaline conditions. In this study, we demonstrate a $\\mathrm{MoNi_{4}}$ electrocatalyst anchored on $\\mathrm{MoO}_{2}$ cuboids, which are vertically aligned on nickel foam $\\mathrm{(MoNi_{4}/M o O_{2}@N i)}$ . $\\mathrm{MoNi_{4}}$ nanoparticles with a size of $20{-}100\\mathrm{nm}$ are constructed in situ on the $\\mathrm{MoO}_{2}$ cuboids by controlling the outward diffusion of $\\mathrm{\\DeltaNi}$ atoms when previously synthesized $\\mathrm{NiMoO_{4}}$ cuboids are heated in a $\\mathrm{H}_{2}/\\mathrm{Ar}$ $\\left(\\mathrm{v}/\\mathrm{v},\\ 5/95\\right)$ atmosphere at $500^{\\circ}\\mathrm{C}$ . The resultant $\\mathrm{MoNi_{4}/M o O_{2}\\textcircled{\\div}N i}$ exhibits a high HER activity with a zero onset overpotential and a low Tafel slope of $\\sim30\\mathrm{mV}$ per decade in a 1 M KOH aqueous solution, which are highly comparable to those for the Pt catalyst (onset overpotential: $\\ensuremath{\\boldsymbol{0}}\\ensuremath{\\mathrm{mV}}$ ; Tafel slope: $32\\mathrm{mV}$ per decade). In addition, the achieved $\\mathrm{MoNi_{4}}$ electrocatalyst requires low overpotentials of only $\\sim15$ and $\\sim44\\mathrm{mV}$ to stably deliver cathodic current densities of 10 and $200\\mathrm{mAcm}^{-2}$ , respectively, presenting state-of-the-art HER activity amongst all reported $\\mathrm{\\Pt}$ -free electrocatalysts7,10,18. Experimental investigations reveal that the $\\mathrm{{MoNi}_{4}}$ electrocatalyst behaves as the highly active centre and manifests fast Tafel step-determined HER kinetics. Furthermore, density functional theory (DFT) calculations determine that the kinetic energy barrier of the Volmer step for the $\\mathrm{MoNi_{4}}$ electrocatalyst is as low as $0.39\\mathrm{eV}$ . These results confirm that the sluggish Volmer step is drastically accelerated for the $\\mathrm{MoNi_{4}}$ electrocatalyst. \n\n![](images/d8623f3ecbb253a4237d0c1c79760ce00868e1feb75cfab70491bbba42f0dd40.jpg) \nFigure 1 | Synthetic scheme of MoNi4 electrocatalyst supported by the MoO2 cuboids on nickel foam. Synthetic scheme of ${M o N i_{4}}$ electrocatalyst supported by the ${\\mathsf{M o O}}_{2}$ cuboids on nickel foam. Scale bars, Ni foam, $20\\upmu\\mathrm{m}$ (top) and $1\\upmu\\mathrm{m}$ (bottom); NiMoO4/Ni foam, $10\\upmu\\mathrm{m}$ (top) and $2\\upmu\\mathrm{m}$ (bottom); $\\mathsf{M o N i_{4}/M o O_{2}/N i}$ foam, $20\\upmu\\mathrm{m}$ (top) and $1\\upmu\\mathrm{m}$ (bottom). \n\n# Results \n\nSynthesis of the $\\mathbf{MoNi_{4}}$ electrocatalyst. The synthesis of the $\\mathrm{MoNi_{4}}$ electrocatalyst involves two steps, as illustrated in Fig. 1. First, the $\\mathrm{NiMoO_{4}}$ cuboids were grown beforehand on a piece of nickel foam $(1\\times3\\mathrm{cm}^{2})$ via a hydrothermal reaction at $150^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ in $15\\mathrm{ml}$ of deionized water containing $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\bullet}6\\mathrm{H}_{2}\\mathrm{O}$ $(0.04\\mathrm{M})$ and $(\\mathrm{NH_{4}})_{6}\\mathrm{Mo_{7}O_{24}}{\\bullet}4\\mathrm{H}_{2}\\mathrm{O}$ (0.01 M). Second, when the as-synthesized $\\mathrm{NiMoO_{4}}$ cuboids were calcined in a $\\mathrm{H}_{2}/\\mathrm{Ar}$ $(\\mathrm{v}/\\mathrm{v},\\ 5/95)$ atmosphere at $500^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ , the inner $\\mathrm{Ni}$ atoms diffused outward due to the formation of $\\mathrm{MoO}_{2}$ . As a result, $\\mathrm{MoNi_{4}}$ nanoparticles were directly constructed on the surfaces of the $\\mathrm{MoO}_{2}$ cuboids. To probe the formation mechanism of the $\\mathrm{MoNi_{4}}$ nanoparticles, different calcination temperatures and times were investigated (Supplementary Figs 1–5). In comparison with the smooth surfaces of precursor $\\mathrm{NiMoO_{4}}$ at $400^{\\circ}\\mathrm{C},$ the appearance of numerous surface nanoparticles at $500^{\\circ}\\mathrm{C}$ indicated the formation of $\\mathrm{{MoNi}_{4}}$ on the resulting $\\mathrm{MoO}_{2}$ cuboids (Supplementary Fig. 1a,b). When the calcination temperature reached $600^{\\circ}\\mathrm{C},$ $\\mathrm{MoNi}_{3}$ nanoparticles on the $\\mathrm{MoO}_{2}$ cuboids $\\mathrm{(MoNi_{3}/M o O_{2}@N i)}$ were produced due to the continuous reduction of $\\mathrm{MoO}_{2}$ (Supplementary Fig. 1c,d). In addition, with increased calcination time at $500^{\\circ}\\mathrm{C},$ the $\\mathrm{MoNi_{4}}$ nanoparticles gradually emerged and grew into bulk particles on the $\\mathrm{MoO}_{2}$ cuboids (Supplementary Figs 2–5). \n\nStructural characterizations of the $\\mathbf{MoNi_{4}}$ electrocatalyst. X-ray diffraction characterization reveals that the crystalline structure of the as-obtained precursor on the Ni foam can be indexed to $\\mathrm{NiMoO_{4}}$ (Supplementary Fig. 6). The morphology of $\\mathrm{NiMoO_{4}}$ was scrutinized by scanning electron microscopy (SEM). As shown in Supplementary Figs 7 and 8, dense $\\mathrm{NiMoO_{4}}$ cuboids with sizes in the range of $0.5\\mathrm{-}1.0\\upmu\\mathrm{m}$ and lengths of tens of microns are vertically aligned on the nickel foam. Elemental mapping, energy dispersive spectroscopy and X-ray photoelectron spectroscopy (XPS) confirm that the $\\mathrm{NiMoO_{4}}$ cuboids consist of Ni, Mo and O elements, and the molar ratio of $\\mathrm{Ni}$ to Mo is $\\sim1{:}1.01$ (Supplementary Figs 9 and 10). \n\nThe product of the $\\mathrm{NiMoO_{4}}$ cuboids on the Ni foam calcined at $500^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ was surveyed with X-ray diffraction using $\\mathrm{Cu-K}\\mathfrak{a}$ radiation, SEM and high-resolution transmission electron microscopy (HRTEM). In Supplementary Fig. 11, the sharp X-ray diffraction diffraction peaks at $\\sim44.6^{\\circ}$ , $52.0^{\\circ}$ and $76.5^{\\circ}$ originate from the Ni foam (JCPDS, No. 65–2865). The peaks located at \n\n![](images/863448edcb82b3503561a5bf520a6542c6d85806aabb70f91573041bf5d94187.jpg) \nFigure 2 | Morphology and chemical composition analyses of $\\mathsf{M o N i}_{4}/\\mathsf{M o O}_{2}@\\mathsf{N i}$ . (a–c) Typical SEM and (d–f) HRTEM images of ${\\mathsf{M o N i_{4}}}/{\\mathsf{M o O}}_{2}@{\\mathsf{N i}};$ $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ corresponding elemental mapping images of the ${M o N i_{4}}$ electrocatalyst and the ${\\mathsf{M o O}}_{2}$ cuboids. The inset image in d is the related selected-area electron diffraction pattern of the ${M o N i_{4}}$ electrocatalyst and the ${\\mathsf{M o O}}_{2}$ cuboids. Scale bars, (a) $20\\upmu\\mathrm{m},$ (b) $1\\upmu\\mathrm{m};$ (c) $100\\mathsf{n m}$ ; (d–f) $2{\\mathsf{n m}}$ ; inset in d, $11/\\mathsf{n m},$ (g) 20 nm. \n\n$26.3^{\\circ}$ , $37.0^{\\circ}$ , $41.5^{\\circ}$ , $49.5^{\\circ}$ , $53.7^{\\circ}$ , $60.5^{\\circ}$ and $66.9^{\\circ}$ are indexed to metallic $\\mathrm{MoO}_{2}$ (JCPDS, No. 32-0671). The appearance of peaks at $31.0^{\\circ}$ and $43.5^{\\circ}$ are assigned to the (200) and (121) facets of $\\mathrm{MoNi_{4}}$ (JCPDS, No. 65–5480), respectively. Thus, these result suggest that the obtained product on the nickel foam consists of $\\mathrm{MoNi_{4}}$ and $\\mathrm{MoO}_{2}$ . As shown in Fig. $2\\mathsf{a}\\mathsf{-c},$ numerous nanoparticles with sizes in the range of $20\\mathrm{-}100\\mathrm{nm}$ are uniformly anchored on the cuboids, which are vertically aligned on the nickel foam. The corresponding energy-dispersive X-ray spectroscopy (EDX) analysis further confirms that the products are composed of Mo, Ni and O, and the molar ratio of Mo to $\\mathrm{\\DeltaNi}$ is $\\sim1{:}1.3$ (Supplementary Fig. 12). Clearly, the HRTEM images of the samples show lattice fringes with lattice distances of 0.35 and $0.28\\mathrm{nm}$ , which correspond to the (110) facet of $\\mathrm{MoO}_{2}$ and the (200) facet of $\\mathrm{MoNi_{4}}$ , respectively (Fig. 2d–f). The selected-area electron diffraction pattern shows diffraction patterns of the (200) facet of $\\mathrm{MoNi_{4}}$ and the (110) facet of $\\mathrm{MoO}_{2}$ (the inset in Fig. 2d). Noticeably, the scanning TEM–EDX characterizations indicate that the surface nanoparticles are constituted by only Mo and Ni with an atomic ratio of 1:3.84, which well approaches to 1:4 (Fig. $2\\mathrm{g}$ and Supplementary Fig. 13). The XPS analysis was carried out to probe the chemical compositions and surface valence states of the $\\mathrm{MoNi_{4}}$ nanoparticles and the supporting $\\mathrm{MoO}_{2}$ cuboids. As illustrated in Supplementary Fig. 14, the XPS spectrum confirms the presence of Mo, Ni and O, and the molar ratio of Mo to Ni is $\\sim1{:}1.1$ . As shown in Supplementary Figs 15–17, XPS peaks of metallic $\\mathrm{Mo}^{0}$ and $\\mathrm{\\DeltaNi^{0}}$ are observed at 229.3 and $852.5\\mathrm{eV}$ , respectively, further confirming the existence of $\\mathrm{Mo}^{0}$ and $\\mathrm{\\DeltaNi^{0}}$ in the surfaces of $\\mathrm{MoNi_{4}/M o O_{2}\\textcircled{\\div}N i}$ . \n\nElectrocatalytic HER performance. To evaluate the electrocatalytic HER activities of the electrocatalysts, a three-electrode system in an Ar-saturated $1\\mathrm{M}\\mathrm{KOH}$ aqueous solution was used using a $\\mathrm{Hg/HgO}$ electrode and a graphite rod as the reference and counter electrodes, respectively (Supplementary Fig. 18). All potentials are referenced to the reversible hydrogen electrode (RHE), and the ohmic potential drop loss from the electrolyte resistance has been subtracted (Supplementary Figs 19 and 20). For comparison, pure Ni nanosheets and $\\mathrm{MoO}_{2}$ cuboids were also prepared on the nickel foam using the hydrothermal reactions (Supplementary Figs 21–25). As displayed in Fig. 3a and Supplementary Fig. 26, a commercial $\\mathrm{Pt/C}$ electrocatalyst deposited on the nickel foam (weight density: $1\\mathrm{mgcm}^{-2}.$ ) using Nafion as a binder exhibited a zero HER onset overpotential and delivered a current density of $10\\mathrm{mV}\\mathrm{cm}^{-2}$ at an overpotential of $\\sim10\\mathrm{mV}$ . However, the maximum current density only reached $80\\mathrm{mA}\\mathrm{cm}^{-2}$ due to the $\\mathrm{Pt}$ catalyst significantly peeling off from the support, caused by the generated $\\mathrm{H}_{2}$ bubbles. Although the Ni nanosheets on the nickel foam could act as an HER electrocatalyst, the HER occurred at a very high overpotential of $\\sim253\\mathrm{mV}$ . For the $\\mathrm{MoO}_{2}$ cuboids on the nickel foam, the cathodic current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ was delivered at an overpotential as large as $\\sim48\\mathrm{mV}$ . In comparison to the Ni nanosheets and the $\\mathrm{MoO}_{2}$ cuboids, the $\\mathrm{NiMoO_{4}}$ cuboids and $\\mathrm{MoNi_{3}/M o O_{2}}$ cuboids on the nickel foam exhibited a similar onset overpotential of $\\mathrm{\\sim}10\\mathrm{mV}$ and an overpotential of $\\sim30$ and $37\\mathrm{mV}$ at $\\mathrm{i}0\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively (Supplementary Figs 27–29). Remarkably, $\\mathrm{MoNi_{4}/M o O_{2}@N i}$ exhibited an onset overpotential of $0\\mathrm{mV}$ , which was highly comparable to that of the $\\mathrm{Pt}$ catalyst. In addition, for the supported $\\mathrm{MoNi_{4}}$ electrocatalyst, the overpotential at current densities of 10 and $200\\mathrm{mAcm}^{\\cdot-2}$ was as low as $\\sim15$ and $44\\mathrm{mV}$ , respectively, which were significantly lower than the values for the $\\mathrm{Ni}$ nanosheets, $\\mathrm{MoO}_{2}$ cuboids, $\\mathrm{\\DeltaNiMoO_{4}}$ cuboids, $\\mathrm{MoNi_{3}/M o O_{2}}$ cuboids and state-of-the-art $\\mathrm{\\Pt}$ -free HER electrocatalysts such as NiO/Ni heterostructures ( $\\sim85\\mathrm{mV}$ at $10\\operatorname{mA}{\\mathrm{cm}^{-2}})^{25}$ , pyrite-type CoPS nanowires ( $\\mathrm{\\Phi_{\\cdot}}\\sim48\\mathrm{mV}$ at 10 mA cm \u0002 2)16, nickel doped carbon ( $\\cdot\\sim34\\mathrm{mV}$ at 10 mA cm \u0002 2)26, a $\\mathrm{Mo}_{2}\\mathrm{C}/{\\i}$ carbon/graphene hybrid ( $\\cdot\\sim34\\mathrm{mV}$ at 10 mA cm \u0002 2)17, $\\mathrm{MoSSe/NiSe}_{2}$ foam ( $\\mathrm{\\Omega}\\cdot\\mathrm{\\sim69mV}$ at $10\\mathrm{mAcm}^{-2})^{27}\\mathrm{,}$ , $\\mathrm{Fe}_{0.9}\\mathrm{Co}_{0.1}\\mathrm{S}_{2}/$ carbon nanotubes $\\mathrm{\\Phi}^{\\prime}\\mathrm{\\sim}100\\mathrm{mV}$ at $10\\mathrm{mAcm}^{-2})^{28}$ , ${\\mathrm{Ni}}_{2}{\\mathrm{P}}$ nanoparticles ( $\\sim120\\mathrm{mV}$ at $10\\mathrm{mAcm}^{-2})^{29}$ and strained MoS2 nanosheets (B170 mV at 10 mA cm\u0002 2)30 (Supplementary Table 1)31–39. \n\nFigure 3b displays the Tafel plots of the corresponding polarization curves, which provide profound insights into the fundamental HER kinetic mechanism occurring on the surfaces of the electrocatalysts. As a result of the low energy barrier $\\mathrm{(0.44eV}$ on $\\mathrm{Pt}\\overrightharpoon{}$ ) of the Volmer step, the kinetic rate-limiting step for the $\\mathrm{\\Pt}$ catalyst is the Tafel process, and the theoretical Tafel slope is $30\\mathrm{mV}$ per decade (here the Tafel slope of the commercial Pt catalyst was measured to be $32\\mathrm{mV}$ per decade)12. Remarkably, the Tafel slope of the $\\mathrm{MoNi_{4}}$ electrocatalyst was as low as $30\\mathrm{mV}$ per decade, which is far lower than the values of $129\\mathrm{mV}$ per decade for the Ni nanosheets and $75\\mathrm{mV}$ per decade for the $\\mathrm{MoO}_{2}$ cuboids and highly comparable to that of the $\\mathrm{\\Pt}$ -based catalyst (Fig. 3c and Supplementary Table 1). This result indicated that the electrocatalytic HER kinetics on the $\\mathrm{MoNi_{4}}$ electrocatalyst were determined by the Tafel step rather than a coupled Volmer– Tafel or Volmer–Heyrovsky process. In other words, the prior Volmer step has been significantly accelerated. The exchange current density of the $\\mathrm{MoNi_{4}}$ electrocatalyst was estimated to be $\\sim1.24\\mathrm{mAcm}^{-2}$ (Supplementary Fig. 30). To clarify the influence of the active surface area on the electrocatalytic HER activity, the corresponding electrochemical double-layer capacitances (Cps) of the electrocatalysts were analysed by applying cyclic voltammetry cycles at different scan rates40. The Cps of the Ni nanosheets and $\\mathrm{MoO}_{2}$ cuboids were $\\sim0.001$ and $0.640\\mathrm{F}$ , respectively, while the $\\mathrm{MoNi_{4}}$ electrocatalyst had a high $\\mathrm{Cp}$ of $2.220\\mathrm{F}$ (Supplementary Fig. 31). On the basis of its $\\mathrm{Cp}$ , the $\\mathrm{MoNi_{4}}$ electrocatalyst was calculated to have a turnover frequency of $0.4\\ s^{-1}$ at a low overpotential of $50\\mathrm{mV}$ , which was higher than the turnover frequency values of the previously reported $\\mathrm{Pt}$ -free electrocatalysts (Supplementary Fig. 32 and Supplementary Table 1)41–44. \n\nLong-term electrocatalytic stability is another important criterion for HER electrocatalysts. To investigate the durability of the $\\mathrm{MoNi_{4}}$ electrocatalyst, continuous cyclic voltammetry scans were performed between 0.2 and $-0.2\\mathrm{V}$ at a scan rate of $50\\mathrm{mVs}^{-1}$ in a 1 M KOH solution. As depicted in Fig. 3d, the HER overpotential of the $\\mathrm{MoNi_{4}}$ electrocatalyst at $200\\mathrm{\\mAcm}^{-2}$ increased by only $6\\mathrm{mV}$ after 2,000 cyclic voltammetry cycles. In addition, a long-term electrocatalytic HER process was successively carried out at current densities of 10, 100 and $200\\mathrm{mAcm}^{-2}$ (Supplementary Movie 1). The inset in Fig. 3d demonstrates that the $\\mathrm{MoNi_{4}}$ electrocatalyst retained a steady HER activity, and only an increase of $\\sim3\\mathrm{mV}$ in potential was observed at a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ after a period of $10\\mathrm{{h}}$ of hydrogen production. The overpotential required for large current densities of 100 and $200\\mathrm{mA}\\mathrm{\\dot{c}}\\mathrm{m}^{-2}$ was augmented by only 2 and $5\\mathrm{mV}$ , respectively. After a series of HER durability assessments, the structure of the $\\mathrm{MoNi_{4}}$ electrocatalyst was examined using SEM and HRTEM. $\\mathrm{MoNi_{4}/M o O_{2}\\textcircled{\\div}N i}$ showed no structural variations, highlighting the superior structural robustness of the $\\mathrm{MoNi_{4}}$ electrocatalyst during the electrocatalytic HER process (Supplementary Figs 33–36). \n\nThe approach to the synthesis of $\\mathrm{MoNi_{4}/M o O_{2}}@\\mathrm{Ni}$ is scalable on the nickel foam. The $\\mathrm{MoNi_{4}}$ electrocatalyst was thus prepared on commercially available nickel foam with dimensions of $6\\times20\\mathrm{cm}^{2}$ . As shown in Supplementary Fig. 37, the $\\mathrm{MoNi_{4}}$ electrocatalyst supported by the $\\mathrm{MoO}_{2}$ cuboids on the nickel foam was free-standing and highly flexible. It is notable that the $\\mathrm{MoNi_{4}}$ electrocatalyst unveiled a steady HER activity even though the supporting Ni foam was deformed to various degrees (Supplementary Fig. 38). For reported Raney nickel and nickel– molybdenum alloy electrodes, concentrated alkaline solutions $(30\\mathrm{wt\\%})$ and high electrolyte temperatures $(70^{\\circ}\\mathrm{C})$ are generally demanded to achieve high cathodic current densities of $200{-}500\\operatorname*{mA}\\operatorname{cm}^{-2}$ (ref. 45). Here high cathodic current densities of up to 200 and $500\\mathrm{mAcm}^{-2}$ were delivered by the $\\mathrm{{MoNi}_{4}}$ electrocatalyst at extremely low overpotentials of $\\sim44$ and $\\sim65\\mathrm{mV}$ in a $5.3\\mathrm{wt\\%}$ KOH solution at room temperature. \n\n![](images/2134eccf626e9643957b31f7ce658c98aa33abb990ceeca6f311c11c766be26c.jpg) \nFigure 3 | Electrocatalytic activities of different catalysts. (a) Polarization curves and (b) Tafel plots of the ${M o N i_{4}}$ electrocatalyst supported by the ${\\mathsf{M o O}}_{2}$ cuboids, pure Ni nanosheets and ${\\mathsf{M o O}}_{2}$ cuboids on the nickel foam. (c) Comparison with selected state-of-the-art HER electrocatalysts. (d) Polarization curves of the $M o N i_{4}$ electrocatalyst before and after 2,000 cyclic voltammetry cycles; inset: long-term stability tests of the $M o N i_{4}$ electrocatalyst at different current densities: 10; 100; and $200\\mathsf{m A c m}^{-2}$ . Electrolyte: 1 M KOH aqueous solution; scan rate: $1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . \n\nAfterward, a water-alkali electrolyser was built up in a $1\\mathrm{M}$ KOH solution using $\\mathrm{MoNi_{4}/M o O_{2}}@\\mathrm{Ni}$ as the cathode and a previously reported $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm S_{2}$ hybrid as the anode (Supplementary Fig. $39)^{38}$ . As exhibited in Supplementary Fig. 40a, for a noble metal-based $\\mathrm{Pt-Ir/C}$ couple, a cell voltage of $\\mathrm{\\sim}1.7\\mathrm{V}$ was applied for a current density of $10\\mathrm{mAcm}^{-2}$ . In contrast, the $\\mathrm{MoNi_{4}{-}M o S_{2}/N i_{3}S_{2}}$ couple required a low cell voltage of only ${\\sim}1.47\\mathrm{V}$ to deliver a current density of $10\\mathrm{m}\\mathrm{\\check{A}}\\mathrm{cm}^{-2}$ , which is much lower than that for the noble metal-based $\\mathrm{Pt-Ir/C}$ couple. Over $\\mathrm{10h}$ of galvanostatic electrolysis at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , the applied voltage of the $\\mathrm{{MoNi_{4}-}}$ $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ couple had an augmentation of $\\sim0.02\\mathrm{V}$ , which is much lower than the value of $0.07\\mathrm{V}$ for the $\\mathrm{Pt-Ir/C}$ couple (Supplementary Fig. 40b). Moreover, the electrolyser with a high current density of $200\\mathrm{\\mAcm}^{-2}$ was durably driven by the $\\mathrm{MoNi_{4}{-}M o S_{2}/\\tilde{N}i_{3}S_{2}}$ couple at a low voltage of $\\mathrm{\\sim}\\mathrm{1.70V}$ (Supplementary Movie 2). \n\nHER active centres. To understand the intrinsic contributions of the surface $\\mathrm{MoNi_{4}}$ nanoparticles and the underlying $\\mathrm{MoO}_{2}$ cuboids to the HER activity, pure $\\mathrm{MoO}_{2}$ nanosheets and $\\mathrm{MoNi_{4}}$ nanoparticles supported by $\\mathrm{MoO}_{2}$ cuboids were also synthesized on carbon cloth. Thus, the contribution of the underlying Ni foam could be excluded (Supplementary Fig. 41). Clearly, the pristine $\\mathrm{MoO}_{2}$ nanosheets on carbon cloth showed a very high \n\nHER onset potential of $\\sim240\\mathrm{mV}$ in $1\\mathrm{M}\\mathrm{KOH}$ and $\\sim200\\mathrm{mV}$ in 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}.$ suggesting that the $\\mathrm{MoO}_{2}$ electrocatalyst inherently presented a very sluggish Volmer step and a poor Tafel process (Supplementary Fig. 42). In contrast, the $\\mathrm{MoNi_{4}}$ electrocatalyst supported by the $\\mathrm{MoO}_{2}$ cuboids on the carbon cloth $(\\mathrm{MoNi_{4}/}$ $\\mathrm{MoO}_{2}@\\mathrm{C})$ exhibited a zero onset potential, which was similar to that for $\\mathrm{MoNi_{4}/M o O_{2}}@\\mathrm{Ni}$ . When the surface $\\mathrm{MoNi_{4}}$ nanoparticles of $\\mathrm{MoNi_{4}/M o O_{2}@C}$ were etched away using $^{2\\mathrm{M}}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ aqueous solution. Obviously, the produced ${\\mathrm{MoO}}_{2}@{\\mathrm{C}}$ showed a largely increased onset potential of $\\sim133\\mathrm{mV}$ (Supplementary Figs 43–46). These results demonstrate that the excellent HER activity of the $\\mathrm{MoNi_{4}/M o O_{2}@N i}$ unambiguously originates from the surface $\\mathrm{MoNi_{4}}$ nanoparticles rather than from the supporting $\\mathrm{MoO}_{2}$ cuboids. \n\nTo gain profound insight into the electrocatalytic HER active sites, we also analysed the surface electrochemical behaviour of the $\\mathrm{MoNi_{4}}$ electrocatalyst on the $\\mathrm{MoO}_{2}$ cuboids. For a freshly prepared $\\mathrm{MoNi_{4}}$ electrocatalyst, an electrochemical cyclic voltammetry cycle between $-0.025$ and $0.275\\mathrm{V}$ (versus RHE) was initially performed with a scan rate of $1\\mathrm{mV}s^{-1}$ . Obviously, the positions of the electrochemically reversible peaks shifted from $\\bar{0}.175\\mathrm{V}/0.113\\mathrm{V}$ to $0.215\\mathrm{V}/0.064\\dot{\\mathrm{V}}$ when the KOH concentration was changed from 1 to $0.1\\mathrm{M}$ (Supplementary Fig. 47a). The strong dependence on the concentration of KOH as the electrolyte revealed that the electrochemically reversible peaks originated from an ad-/desorption process of water molecules or hydrogen (between 0.05 and $0.35\\mathrm{V}$ , as reported) rather than from the surface redox reactions of the $\\mathrm{MoNi_{4}}$ electrocatalyst and supporting $\\mathrm{MoO}_{2}$ cuboids12. In addition, in contrast to the results on pure Ni nanosheets $(0.150\\mathrm{V})$ and $\\mathrm{MoO}_{2}$ (0.164 V) cuboids, the water or hydrogen adsorption peak of the $\\mathrm{MoNi_{4}}$ electrocatalyst showed an anodic shift to $0.175\\mathrm{V}$ , reflecting a superior water or hydrogen adsorption property (Supplementary Fig. 47b). \n\nTo evaluate the intrinsic electrocatalytic HER activity of the $\\mathrm{MoNi_{4}}$ electrocatalyst, the recorded cathodic current density was normalized versus the related Brunauer Emmett Teller specific surface area of the $\\mathrm{MoNi_{4}}$ electrocatalyst $(32\\mathrm{m}^{\\frac{1}{2}}\\mathrm{g}^{-1})$ (Supplementary Fig. 48). As described in Supplementary Fig. 49, when the current density was below $0.38{\\dot{\\mathrm{A}}}\\mathrm{m}^{-2}$ , the polarization curve of the $\\mathrm{{MoNi}_{4}}$ electrocatalyst nearly overlapped with that of the $\\mathrm{Pt}$ catalyst. However, the HER overpotential of the $\\mathrm{{MoNi}_{4}}$ electrocatalyst was much lower than that of the $\\mathrm{Pt}$ catalyst at large current densities $\\mathrm{\\Omega}(>0.38\\mathrm{Am}^{-2}.$ ). These results illustrate that the intrinsic HER activity associated with the specific surface area of the $\\mathrm{MoNi_{4}}$ electrocatalyst is even higher than that of the Pt catalyst under alkaline conditions. \n\nTheoretical calculations. To understand the fundamental mechanism of the outstanding HER activity on $\\mathrm{MoNi_{4}/}$ $\\begin{array}{r}{\\mathrm{MoO}_{2}@\\mathrm{Ni}.}\\end{array}$ the kinetic energy barrier of the prior Volmer step $(\\Delta G(\\mathrm{H}_{2}\\mathrm{O}))$ and the concomitant combination of adsorbed H into molecular hydrogen $(\\Delta G(\\mathrm{H})$ , Tafel step) were studied using the DFT calculations according to the as-built electrocatalyst models including the (111) facet of Ni metal, the (110) facet of Mo metal, the (110) facet of $\\mathrm{MoO}_{2}$ and the (200) facet of $\\mathrm{MoNi_{4}}$ (Supplementary Fig. 50). As shown in Fig. 4, $\\mathrm{MoO}_{2}$ has a large energy barrier for the Volmer step $(\\Delta G(\\mathrm{H}_{2}\\mathrm{O})=1.01\\:\\mathrm{eV})$ and a strong hydrogen adsorption free energy $(|\\Delta G(\\mathrm{H})|=1.21\\mathrm{eV};$ , indicating a very sluggish Volmer–Tafel mechanism. Thus, $\\mathrm{MoO}_{2}$ is not the highly active centre for the HER, which agrees well with the experimental results. The $\\Delta G(\\mathrm{H}_{2}\\mathrm{O})$ values on pure $\\mathrm{\\DeltaNi}$ metal and Mo metal are as high as 0.91 and $0.65\\mathrm{eV}$ , respectively (Fig. 4b and Supplementary Fig. 51). In contrast, the $\\Delta G(\\bar{\\mathrm{H}}_{2}\\mathrm{O})$ on $\\mathrm{MoNi_{4}}$ is significantly decreased to $0.39\\mathrm{eV}$ , which is even lower than the value of $0.44\\mathrm{eV}$ on $\\mathrm{\\Pt}$ (ref. 15). In addition, $\\mathrm{MoNi_{4}}$ has a lower $|\\Delta G(\\mathrm{H})|$ of $0.74\\mathrm{eV}$ than the value of $1.21\\mathrm{eV}$ for $\\mathrm{MoO}_{2}$ , which corresponds to a superior hydrogen adsorption capability (Fig. 4c). Thereby, the HER reaction on $\\mathrm{MoNi_{4}}$ is associated with a process defined by a fast Tafel step rather than a sluggish Volmer–Tafel step (Supplementary Fig. 52). \n\n# Discussion \n\nIn summary, we have demonstrated a $\\mathrm{MoNi_{4}}$ electrocatalyst supported by $\\mathrm{MoO}_{2}$ cuboids on nickel foam or carbon cloth. As favoured by a largely reduced energy barrier of the Volmer step, the achieved $\\mathrm{MoNi_{4}}$ electrocatalyst exhibits a high HER activity under alkaline conditions, which is highly comparable to that for $\\mathrm{Pt}$ and outperforms any reported results for $\\mathrm{\\Pt}$ -free electrocatalysts, to the best of our knowledge. Moreover, the large-scale preparation and excellent catalytic stability provide $\\mathrm{\\bar{MoNi}_{4}/}$ $\\mathrm{MoO}_{2}@\\mathrm{Ni}$ with a promising utilization in water-alkali electrolysers for hydrogen production. Therefore, the exploration and understanding of the $\\mathrm{{MoNi_{4}}}$ electrocatalyst provide a promising alternative to $\\mathrm{Pt}$ catalysts for emerging applications in energy generation. \n\n![](images/55fc2e71214ccdf68a17341fd00842c6aed4edb9477ce7d216e65a078a163a12.jpg) \nFigure 4 | DFT calculations. (a) Calculated free energies of $H_{2}O$ adsorption, activated $H_{2}O$ adsorption, OH adsorption and H adsorption. (b) Calculated adsorption free energy diagram for the Volmer step. (c) Calculated adsorption free energy diagram for the Tafel step. Blue balls: Ni; aqua balls: Mo; red balls: O. \n\n# Methods \n\nMaterial synthesis. To synthesize the $\\mathrm{MoNi_{4}}$ electrocatalyst, $\\mathrm{NiMoO_{4}}$ cuboids were first constructed on nickel foam through a hydrothermal reaction46. First, the commercial nickel foam was successively washed with ethanol, a 1 M HCl aqueous solution and deionized water. Second, one piece of nickel foam $(1\\times3\\mathrm{cm}^{2})$ was immersed into $15\\mathrm{ml}$ of $_\\mathrm{H}_{2}\\mathrm{O}$ containing $\\mathrm{Ni(NO_{3})_{2}{\\bullet6}H_{2}O}$ $(0.04\\mathrm{M})$ and $(\\mathrm{NH_{4}})_{6}\\mathrm{Mo_{7}O_{24}{\\bullet4}H_{2}O}$ $(0.01\\mathrm{M})$ in a Teflon autoclave. Third, the autoclave was heated at $150^{\\circ}\\mathrm{C}$ for $^{6\\mathrm{h}}$ in a drying oven. After washing with deionized water, the $\\mathrm{NiMoO_{4}}$ cuboids were achieved on the nickel foam. Finally, the as-constructed $\\mathrm{NiMoO_{4}}$ cuboids were heated at $500^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ in a $\\mathrm{H}_{2}/\\mathrm{Ar}$ (4:96) atmosphere, and then, the $\\mathbf{MoNi}_{4}$ electrocatalyst anchored on the $\\mathbf{MoO}_{2}$ cuboids was obtained. The loading weight of the formed $\\mathrm{{MoNi}_{4}}$ nanoparticles and $\\mathrm{MoO}_{2}$ cuboids on the nickel foam was $\\sim43.4\\mathrm{mgcm}^{2}$ . The pure Ni nanosheets and $\\mathbf{MoO}_{2}$ cuboids on the nickel foam, as well as the pure $\\mathrm{MoO}_{2}$ nanosheets and $\\mathrm{MoN_{4}}$ nanoparticles supported by $\\mathrm{MoO}_{2}$ cuboids on carbon cloth, were also prepared following the same procedure for $\\mathrm{MoNi_{4}}$ by changing the precursors and substrates. \n\nStructure characterizations. SEM, as well as corresponding elemental mapping, and EDX analysis were carried out with a Gemini 500 (Carl Zeiss) system. HRTEM was performed using a LIBRA 200 MC Cs scanning TEM (Carl Zeiss) operating at an accelerating voltage of $200\\mathrm{kV}$ . XPS experiments were carried out on an AXIS Ultra DLD (Kratos) system using Al $\\operatorname{K}\\upalpha$ radiation. XRD patterns were recorded on a PW1820 powder diffractometer (Phillips) using $\\mathrm{Cu-K}\\mathfrak{a}$ radiation. The electrochemical tests were carried out on WaveDriver 20 (Pine Research Instrumentation) and CHI 660E Potentiostat (CH Instruments) systems. \n\nElectrochemical measurements. All electrochemical tests were performed at room temperature. The electrochemical HER was carried out in a three-electrode system. A standard $\\mathrm{Hg/HgO}$ electrode and a graphite rod were used as the reference and counter electrodes, respectively. The $\\mathrm{Hg/HgO}$ electrode was calibrated using bubbling $\\mathrm{H}_{2}$ gas on a Pt coil electrode. Potentials were referenced to an RHE by adding $0.923\\mathrm{V}$ $(0.099+0.059\\times\\mathrm{pH})$ in a $1\\mathrm{M}\\mathrm{KOH}$ aqueous solution. For comparison, $\\mathrm{Pt/C}$ $20\\mathrm{wt\\%}$ , FuelCellStore; loaded on the nickel foam at $1\\mathrm{mg}\\mathrm{cm}^{-2}$ ) was used as an HER electrocatalyst. The impedance spectra of the electrocatalysts in a three-electrode set-up were recorded at different HER overpotentials in a $1\\mathrm{M}$ KOH electrolyte. All voltages and potentials were corrected to eliminate electrolyte resistances unless noted. Electrolyte resistance: $0.94\\Omega;$ scan rate: $1\\mathrm{mVs}^{-1}$ . \n\nTheoretical calculations. All computations were performed by applying the plane-wave-based DFT method with the Vienna Ab Initio Simulation Package and periodic slab models. The electron ion interaction was described with the projector augmented wave method. The electron exchange and correlation energy were treated within the generalized gradient approximation in the Perdew–Burke– Ernzerhof formalism. The cut-off energy of $400\\mathrm{eV}$ and Gaussian electron smearing method with $\\sigma{=}0.05\\mathrm{eV}$ were used. The geometry optimization was performed when the convergence criterion on forces became smaller than $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ and the energy difference was $<10^{-4}\\mathrm{eV}$ . The adsorption energy $(E_{\\mathrm{ad}s})$ of species X is calculated by $E_{\\mathrm{ads}}=E(\\mathrm{X}/\\mathrm{slab})-E(\\mathrm{X})-E(\\mathrm{slab})$ , and a more negative $E_{\\mathrm{ads}}$ indicates a more stable adsorption. For the DFT calculations, the reactant $\\mathrm{(H}_{2}\\mathrm{O)}$ and intermediates (OH and H) are first adsorbed on all possible active sites of the catalyst. Afterwards, the VASP software is utilized to optimize the adsorption. For evaluating the energy barrier $(E_{\\mathrm{a}}=E_{\\mathrm{TS}}-E_{\\mathrm{IS}})$ , the transitional state (TS) was located using the Nudged Elastic Band method. All transition states were verified by vibration analyses with only one imaginary frequency. The $\\mathtt{p}(3\\times3)$ -Ni(111), $\\mathtt{p}(3\\times3)$ -Mo(110), $\\mathsf{p}(3\\times3)–\\mathsf{M o O}_{2}(110)$ and $\\mathrm{\\p}(1\\times1){-}\\mathrm{MoNi}_{4}(200)$ surfaces were utilized to simulate the properties of these electrocatalysts. \n\nData availability. The data that support the findings of this study are available from the corresponding author on reasonable request. \n\n# References \n\n1. Turner, J. et al. Renewable hydrogen production. Int. J. Energy Res. 32, 379–407 (2008). \n2. Dunn, S. Hydrogen futures: toward a sustainable energy system. Int. J. Hydrog. Energy 27, 235–264 (2002). \n3. Holladay, J. D., Hu, J., King, D. L. & Wang, Y. An overview of hydrogen production technologies. Catal. Today 139, 244–260 (2009). \n4. Kudo, A. & Miseki, Y. Heterogeneous photocatalyst materials for water splitting. Chem. Soc. Rev. 38, 253–278 (2009). \n5. Lewis, N. S. & Nocera, D. G. Powering the planet: chemical challenges in solar energy utilization. Proc. Natl Acad. Sci. USA 103, 15729–15735 (2006). \n6. Greeley, J., Jaramillo, T. F., Bonde, J., Chorkendorff, I. & Norskov, J. K. Computational high-throughput screening of electrocatalytic materials for hydrogen evolution. Nat. Mater. 5, 909–913 (2006). \n7. McKone, J. R., Marinescu, S. C., Brunschwig, B. S., Winkler, J. R. & Gray, H. B. Earth-abundant hydrogen evolution electrocatalysts. Chem. Sci. 5, 865–878 (2014). hydrogen evolution reaction in alkaline solutions—a review. Int. J. Hydrog. Energy 40, 256–274 (2015). \n9. Carmo, M., Fritz, D. L., Mergel, J. & Stolten, D. A comprehensive review on PEM water electrolysis. Int. J. Hydrog. Energy 38, 4901–4934 (2013). \n10. Zou, X. & Zhang, Y. Noble metal-free hydrogen evolution catalysts for water splitting. Chem. Soc. Rev. 44, 5148–5180 (2015). \n11. Zheng, Y., Jiao, Y., Jaroniec, M. & Qiao, S. Z. Advancing the electrochemistry of the hydrogen-evolution reaction through combining experiment and theory. Angew. Chem. Int. Ed. 54, 52–65 (2015). \n12. Subbaraman, R. et al. Enhancing hydrogen evolution activity in water splitting by tailoring $\\operatorname{Li}+$ -Ni $\\left(\\mathrm{OH}\\right)_{2}$ -Pt interfaces. Science 334, 1256–1260 (2011). \n13. Subbaraman, R. et al. Trends in activity for the water electrolyser reactions on 3d M (Ni, Co, Fe, Mn) hydr (oxy) oxide catalysts. Nat. Mater. 11, 550–557 (2012). \n14. Danilovic, N. et al. Enhancing the alkaline hydrogen evolution reaction activity through the bifunctionality of $\\mathrm{Ni(OH)}_{2}/$ metal catalysts. Angew. Chem. Int. Ed. 124, 12663–12666 (2012). \n15. Fajı´n, J. L. C., Cordeiro, M. N. D. S. & Gomes, J. R. B. Density functional theory study of the water dissociation on platinum surfaces: general trends. J. Phys. Chem. A 118, 5832–5840 (2014). \n16. Caban-Acevedo, M. et al. Efficient hydrogen evolution catalysis using ternary pyrite-type cobalt phosphosulphide. Nat. Mater. 14, 1245–1251 (2015). \n17. Li, J.-S. et al. Coupled molybdenum carbide and reduced graphene oxide electrocatalysts for efficient hydrogen evolution. Nat. Commun. 7, 11204–11211 (2016). \n18. McCrory, C. C. L. et al. Benchmarking hydrogen evolving reaction and oxygen evolving reaction electrocatalysts for solar water splitting devices. J. Am. Chem. Soc. 137, 4347–4357 (2015). \n19. Morales-Guio, C. G., Stern, L.-A. & Hu, X. Nanostructured hydrotreating catalysts for electrochemical hydrogen evolution. Chem. Soc. Rev. 43, 6555–6569 (2014). \n20. Shi, Y. & Zhang, B. Recent advances in transition metal phosphide nanomaterials: synthesis and applications in hydrogen evolution reaction. Chem. Soc. Rev. 45, 1529–1541 (2016). \n21. Yan, Y., Xia, B., Xu, Z. & Wang, X. Recent development of molybdenum sulfides as advanced electrocatalysts for hydrogen evolution reaction. ACS Catal. 4, 1693–1705 (2014). \n22. Hinnemann, B. et al. Biomimetic hydrogen evolution: $\\mathbf{MoS}_{2}$ nanoparticles as catalyst for hydrogen evolution. J. Am. Chem. Soc. 127, 5308–5309 (2005). \n23. Tran, P. D. et al. Coordination polymer structure and revisited hydrogen evolution catalytic mechanism for amorphous molybdenum sulfide. Nat. Mater. 15, 640–646 (2016). \n24. Ng, J. W. D. et al. Gold-supported cerium-doped $\\mathrm{NiO_{x}}$ catalysts for water oxidation. Nat. Energy 1, 16053–16060 (2016). \n25. Gong, M. et al. Nanoscale nickel oxide/nickel heterostructures for active hydrogen evolution electrocatalysis. Nat. Commun. 5, 4695–4700 (2014). \n26. Fan, L. et al. Atomically isolated nickel species anchored on graphitized carbon for efficient hydrogen evolution electrocatalysis. Nat. Commun. 7, 10667–10673 (2016). \n27. Zhou, H. et al. Efficient hydrogen evolution by ternary molybdenum sulfoselenide particles on self-standing porous nickel diselenide foam. Nat. Commun. 7, 12765–12771 (2016). \n28. Wang, D.-Y. et al. Highly active and stable hybrid catalyst of cobalt-doped $\\mathrm{FeS}_{2}$ nanosheets–carbon nanotubes for hydrogen evolution reaction. J. Am. Chem. Soc. 137, 1587–1592 (2015). \n29. Popczun, E. J. et al. Nanostructured nickel phosphide as an electrocatalyst for the hydrogen evolution reaction. J. Am. Chem. Soc. 135, 9267–9270 (2013). \n30. Li, H. et al. Activating and optimizing $\\ensuremath{\\mathrm{MoS}}_{2}$ basal planes for hydrogen evolution through the formation of strained sulphur vacancies. Nat. Mater. 15, 48–53 (2015). \n31. Staszak-Jirkovsky, J. et al. Design of active and stable Co-Mo- $\\cdot S_{\\mathrm{x}}$ chalcogels as pH-universal catalysts for the hydrogen evolution reaction. Nat. Mater. 15, 197–203 (2015). \n32. Jiao, Y., Zheng, Y., Davey, K. & Qiao, S.-Z. Activity origin and catalyst design principles for electrocatalytic hydrogen evolution on heteroatom-doped graphene. Nat. Energy 1, 16130–16138 (2016). \n33. Gong, Q. et al. Ultrasmall and phase-pure $\\mathrm{W}_{2}\\mathrm{C}$ nanoparticles for efficient electrocatalytic and photoelectrochemical hydrogen evolution. Nat. Commun. 7, 13216–13223 (2016). \n34. Wu, H. B., Xia, B. Y., Yu, L., Yu, X.-Y. & Lou, X. W. Porous molybdenum carbide nano-octahedrons synthesized via confined carburization in metalorganic frameworks for efficient hydrogen production. Nat. Commun. 6, 6512–6519 (2015). \n35. Li, Y. H. et al. Local atomic structure modulations activate metal oxide as electrocatalyst for hydrogen evolution in acidic water. Nat. Commun. 6, 8064–8070 (2015). \n36. Konkena, B. et al. Pentlandite rocks as sustainable and stable efficient electrocatalysts for hydrogen generation. Nat. Commun. 7, 12269–12276 (2016). \n37. Liang, H.-W. et al. Molecular metal- $\\mathbf{\\cdotN_{x}}$ centres in porous carbon for electrocatalytic hydrogen evolution. Nat. Commun. 6, 7992–7999 (2015). \n38. Zhang, J. et al. Interface engineering of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures for highly enhanced electrochemical overall-water-splitting activity. Angew. Chem. Int. Ed. 128, 6814–6819 (2016). \n39. McKone, J. R., Sadtler, B. F., Werlang, C. A., Lewis, N. S. & Gray, H. B. Ni–Mo nanopowders for efficient electrochemical hydrogen evolution. ACS Catal. 3, 166–169 (2013). \n40. Merki, D., Vrubel, H., Rovelli, L., Fierro, S. & Hu, X. Fe, Co, and Ni ions promote the catalytic activity of amorphous molybdenum sulfide films for hydrogen evolution. Chem. Sci. 3, 2515–2525 (2012). \n41. Xie, J. et al. Defect-rich $\\mathbf{MoS}_{2}$ ultrathin nanosheets with additional active edge sites for enhanced electrocatalytic hydrogen evolution. Adv. Mater. 25, 5807–5813 (2013). \n42. Popczun, E. J., Read, C. G., Roske, C. W., Lewis, N. S. & Schaak, R. E. Highly active electrocatalysis of the hydrogen evolution reaction by cobalt phosphide nanoparticles. Angew. Chem. Int. Ed. 126, 5531–5534 (2014). \n43. Kibsgaard, J. & Jaramillo, T. F. Molybdenum phosphosulfide: an active, acidstable, earth-abundant catalyst for the hydrogen evolution reaction. Angew. Chem. Int. Ed. 53, 14433–14437 (2014). \n44. Cao, B., Veith, G. M., Neuefeind, J. C., Adzic, R. R. & Khalifah, P. G. Mixed close-packed cobalt molybdenum nitrides as non-noble metal electrocatalysts for the hydrogen evolution reaction. J. Am. Chem. Soc. 135, 19186–19192 (2013). \n45. Birry, L. & Lasia, A. Studies of the hydrogen evolution reaction on raney nickel–molybdenum electrodes. J. Appl. Electrochem. 34, 735–749 (2004). \n46. Peng, S., Li, L., Wu, H., Madhavi, S. & Lou, X. Controlled growth of $\\mathrm{NiMoO}_{4}$ nanosheet and nanorod arrays on various conductive substrates as advanced electrodes for asymmetric supercapacitors. Adv. Energy Mater. 5, 1401172–1401178 (2015). \n\n# Acknowledgements \n\nThis work was financially supported by the ERC Grant on 2DMATER and EC under Graphene Flagship (No. CNECT-ICT-604391). We also acknowledge the Cfaed \n\n(Center for Advancing Electronics Dresden), the Dresden Center for Nanoanalysis (DCN) at TU Dresden and Dr Horst Borrmann for the X-ray diffraction characterizations in Max Planck Institute for Chemical Physics of Solids. \n\n# Author contributions \n\nJ.Z. and X.F. conceived and designed the experiments and wrote the paper; J.Z. carried out the synthesis and characterization of electrocatalysts; T.W. performed the DFT calculations; P.L., S.L., Z.L., X.Z., M.C. and E.Z. assisted with the HRTEM and XPS characterizations. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Zhang, J. et al. Efficient hydrogen production on $\\mathrm{MoNi_{4}}$ electrocatalysts with fast water dissociation kinetics. Nat. Commun. 8, 15437 doi: 10.1038/ncomms15437 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2017 " + }, + { + "id": "10.1016_j.actamat.2017.02.036", + "DOI": "10.1016/j.actamat.2017.02.036", + "DOI Link": "http://dx.doi.org/10.1016/j.actamat.2017.02.036", + "Relative Dir Path": "mds/10.1016_j.actamat.2017.02.036", + "Article Title": "Reasons for the superior mechanical properties of medium-entropy CrCoNi compared to high-entropy CrMnFeCoNi", + "Authors": "Laplanche, G; Kostka, A; Reinhart, C; Hunfeld, J; Eggeler, G; George, EP", + "Source Title": "ACTA MATERIALIA", + "Abstract": "The tensile properties of CrCoNi, a medium-entropy alloy, have been shown to be significantly better than those of CrMnFeCoNi, a high-entropy alloy. To understand the deformation mechanisms responsible for its superiority, tensile tests were performed on CrCoNi at liquid nitrogen temperature (77 K) and room temperature (293 K) and interrupted at different strains. Microstructural analyses by transmission electron microscopy showed that, during the early stage of plasticity, deformation occurs by the glide of 1/2 < 110 > dislocations dissociated into 1/6 < 112 > Shockley partials on 011) planes, similar to the behavior of CrMnFeCoNi. Measurements of the partial separations yielded a stacking fault energy of 22 +/- 4 mJ m(-2), which is similar to 25% lower than that of CrMnFeCoNi. With increasing strain, nullotwinning appears as an additional deformation mechanism in CrCoNi. The critical resolved shear stress for twinning in CrCoNi with 16 mu m grain size is 260 +/- 30 MPa, roughly independent of temperature, and comparable to that of CrMnFeCoNi having similar grain size. However, the yield strength and work hardening rate of CrCoNi are higher than those of CrMnFeCoNi. Consequently, the twinning stress is reached earlier (at lower strains) in CrCoNi. This in turn results in an extended strain range where nullotwinning can provide high, steady work hardening, leading to the superior mechanical properties (ultimate strength, ductility, and toughness) of medium-entropy CrCoNi compared to high-entropy CrMnFeCoNi. (C) 2017 Acta Materialia Inc. Published by Elsevier Ltd.", + "Times Cited, WoS Core": 984, + "Times Cited, All Databases": 1028, + "Publication Year": 2017, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000397692600030", + "Markdown": "Full length article \n\n# Reasons for the superior mechanical properties of medium-entropy CrCoNi compared to high-entropy CrMnFeCoNi \n\nG. Laplanche a, \\*, A. Kostka a, b, C. Reinhart a, J. Hunfeld a, G. Eggeler a, E.P. George a, b \n\na Institut für Werkstoffe, Ruhr-Universit€at Bochum, D-44801, Bochum, Germany b Materials Research Department and Center for Interface Dominated Materials (ZGH), Ruhr-University Bochum, Germany \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: \nReceived 15 September 2016 \nReceived in revised form \n7 February 2017 \nAccepted 12 February 2017 \nAvailable online 13 February 2017 \nKeywords: \nMedium-entropy and high-entropy alloys \nStrain hardening \nShockley partial dislocations \nStacking fault energy \nDeformation twinning \n\nThe tensile properties of CrCoNi, a medium-entropy alloy, have been shown to be significantly better than those of CrMnFeCoNi, a high-entropy alloy. To understand the deformation mechanisms responsible for its superiority, tensile tests were performed on CrCoNi at liquid nitrogen temperature (77 K) and room temperature (293 K) and interrupted at different strains. Microstructural analyses by transmission electron microscopy showed that, during the early stage of plasticity, deformation occurs by the glide of $1/2{<}110{>}$ dislocations dissociated into $1/6{<}112{>}$ Shockley partials on {111} planes, similar to the behavior of CrMnFeCoNi. Measurements of the partial separations yielded a stacking fault energy of $22\\pm4~\\mathrm{mJ~m}^{-2}$ , which is ${\\sim}25\\%$ lower than that of CrMnFeCoNi. With increasing strain, nanotwinning appears as an additional deformation mechanism in CrCoNi. The critical resolved shear stress for twinning in CrCoNi with $16~{\\upmu\\mathrm{m}}$ grain size is $260\\pm30~\\mathrm{MPa}$ , roughly independent of temperature, and comparable to that of CrMnFeCoNi having similar grain size. However, the yield strength and work hardening rate of CrCoNi are higher than those of CrMnFeCoNi. Consequently, the twinning stress is reached earlier (at lower strains) in CrCoNi. This in turn results in an extended strain range where nanotwinning can provide high, steady work hardening, leading to the superior mechanical properties (ultimate strength, ductility, and toughness) of medium-entropy CrCoNi compared to high-entropy CrMnFeCoNi. \n\n$\\circledcirc$ 2017 Acta Materialia Inc. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). \n\n# 1. Introduction \n\nDespite what is often assumed in the high-entropy alloy (HEA) literature, and sometimes explicitly stated [e.g. Ref. [1], that configurational entropy (compositional complexity) correlates directly with the degree of solid solution strengthening, there is actually scant evidence to support this notion. In most papers where superior mechanical properties are attributed to solid solution strengthening from multiple principal elements, the results are clouded by the presence of second phases. This complicates mechanistic interpretation because of the introduction of “composite” effects. In the case of complex solid solutions with facecentered cubic (FCC) structures, Gali and George [2] first showed that increasing the number of constituent elements from four in the CrFeCoNi medium-entropy alloy (MEA), to five in the CrMnFeCoNi HEA, had negligible effect on the degree of solid solution strengthening as evidenced by their similar yield and ultimate tensile strengths. Subsequent studies [3,4] on a family of singlephase FCC alloys, including several MEAs comprising the elements present in the CrMnFeCoNi HEA, found no systematic correlation between mechanical properties and number of alloying elements (i.e., configurational entropy). For example, it was found that the ternary CrCoNi had the highest yield strength and hardness, higher than those of the quaternary and quinary alloys containing more elements. Additionally, alloys with the same configurational entropy had different strengths (e.g., FeNi was significantly stronger than FeCo, and CrCoNi was significantly stronger than MnFeNi). Interestingly, similar alloying trends were noted also for ductility, with the stronger alloys generally being the more ductile [4]. Consistent with the fact that the CrCoNi MEA [4] has higher strength and ductility than the CrMnFeCoNi HEA [2,5], it has also been demonstrated that the fracture toughness of the MEA [6] is higher than that of the HEA [7]. \n\nThe microstructural aspects of plasticity in the CrMnFeCoNi HEA and its non-equiatomic counterparts have been extensively investigated during the past three years [5,8e23]. Detailed analysis of microstructure evolution with strain, coupled with determination of the critical stress for twinning, has greatly improved our understanding of work hardening mechanisms and reasons for the increase in strength and ductility of this HEA with decreasing temperature [16]. In contrast, despite having superior mechanical properties, the CrCoNi MEA has received little attention so far. Consequently, the microstructural origins of its high strength and ductility remain unclear. Even basic features of its plastic deformation behavior including slip planes, Burgers vectors, and dislocation dissociations, have not been reported. In addition, its stacking fault energy has not been determined. Finally, basic questions about its twinning behavior remain unanswered, including: (1) when does twinning start at $293\\mathrm{~K~}$ and 77 K? (2) Is there a critical stress for twinning? (3) Does the twinning stress depend on temperature? (4) How does its magnitude compare to that of the CrMnFeCoNi HEA? To answer these questions and shed light on the micromechanisms of deformation and fracture in the CrCoNi MEA, we interrupted mechanical tests after several different strains and analyzed the microstructures by transmission electron microscopy (TEM). Its deformation mechanisms were then compared to those of CrMnFeCoNi to develop a better understanding of the superior mechanical properties of CrCoNi. \n\n# 2. Experimental methods \n\n# 2.1. Processing \n\nAn equiatomic CrCoNi alloy weighing $2.1~\\mathrm{kg}$ was produced by vacuum induction melting using pure elements (purity $\\geq99.9\\mathrm{wt\\%}$ as starting materials. Melting was performed in a Leybold Heraeus IS 1/III vacuum induction furnace operating at $5{-}20~\\mathrm{kW}.$ Prior to melting, the furnace chamber was evacuated to 3 mbar and then backfilled with Ar (purity, $99.998~\\mathrm{vol\\%}$ ) to a pressure of 500 mbar. The raw materials were melted in a $\\mathtt{M g O}$ crucible and poured into a zirconia-slurry coated cylindrical steel mold having a diameter of $45\\mathrm{mm}$ and height of $160~\\mathrm{{mm}}$ . These processes are similar to those used for the melting and casting of the CrMnFeCoNi HEA [16,24,25]. The cast ingot was turned on a lathe to reduce its diameter from $45\\ \\mathrm{mm}$ to $40\\ \\mathrm{mm}$ , sealed in an evacuated quartz tube, and homogenized at 1473 K for $^{48\\mathrm{~h~}}$ . After homogenization, the quartz tube was taken out of the furnace and allowed to cool in air to room temperature, following which the alloy was removed from the quartz tube. The homogenized ingot was swaged using a four-die rotary swaging machine of type HMP R6-4-120-21S (HMP Umformtechnik GmbH, Pforzheim, Germany). In seven steps, its diameter was reduced from 40 to $16.5\\mathrm{mm}$ (total true strain of \\~1.8). After the final reduction, the swaged material was recrystallized for $^\\mathrm{~1~h~}$ at 1173 K followed by air-cooling. Swaging was used for deformation processing of the present CrCoNi alloy since that was how we produced the CrMnFeCoNi alloy in our previous study [16]. This facilitated direct comparison of their mechanical properties. \n\n# 2.2. Mechanical testing \n\nFrom the recrystallized rod, rectangular dog-bone shaped tensile specimens (gauge length, $20\\mathrm{mm}$ ) were fabricated by electrical discharge machining such that their loading axes were parallel to the rod axis. Before the tensile tests, all faces of the specimens were ground to 1000 grit finish using SiC paper resulting in a final thickness of ${\\sim}1.2\\ \\mathrm{mm}$ and a gauge section of $\\mathord{\\sim}4.8\\ \\mathrm{mm}^{2}$ . Tensile tests were performed at an engineering strain rate of $10^{-3}s^{-1}$ in a Zwick/ Roell test rig of type Z100 at 77 K and 293 K. The room-temperature (293-K) tests were conducted in ordinary ambient air while the 77- K tests utilized a custom-built chamber filled with liquid nitrogen into which the specimens and grips were fully immersed. At 293 K, strains were measured with an extensometer attached to the gauge section and engineering stress-strain curves were obtained from these strains and the output from the load cell. At $77~\\mathrm{K},$ our extensometer could not be used, so strains were determined indirectly from crosshead displacements that were corrected using the following procedure. First, 20 Vickers microindents spaced $1\\ \\mathrm{mm}$ apart were made along the gauge lengths of several tensile specimens using a force of $3.9~\\mathsf{N}.$ . The specimens were tensile tested to different stress levels, unloaded, and the plastic strains in their gauge sections determined by averaging the change in spacing of the indents. In this way, a full engineering stress-strain curve was constructed from the different interrupted tests. This calibration curve was used to correct the crosshead displacements and obtain engineering stress-strain curves for the specimens tested at $77\\mathrm{K}.$ For both test temperatures, true stress-strain curves were obtained from the engineering stress-strain curves assuming constancy of volume during plastic deformation. \n\n# 2.3. Microstructural characterization \n\nLongitudinal sections were cut from the recrystallized alloy, ground and polished with SiC abrasive papers down to a grit size of $8~{\\upmu\\mathrm{m}}$ and then with diamond suspensions down to $1~{\\upmu\\mathrm{m}}$ Final polishing was performed with a vibratory polisher (Buehler Vibromet 2) and colloidal silica having a particle size of $0.06~{\\upmu\\mathrm{m}}$ ; long polishing times up to $^{48\\mathrm{~h~}}$ were employed to minimize residual deformation near the surface. \n\nPhase characterization was carried out by X-ray diffraction using a PANalytical X’Pert Pro MRD diffractometer equipped with a 4- bounce germanium (220) monochromator (Cu Ka radiation $\\lambda=0.154~\\mathrm{{nm}}$ ; $2\\theta$ range from $40^{\\circ}$ to $120^{\\circ}$ ; step size $\\varDelta2\\theta=0.006^{\\circ}$ ; integration time 280 s). \n\nChemical composition of the swaged alloy was determined at a commercial laboratory (Revierlabor GmbH, Essen, Germany), which is the same one that we had used previously [36]. Metallic elements were analyzed by $\\mathsf{x}$ -ray fluorescence analysis (XRFA), oxygen by carrier gas hot extraction, and carbon and sulfur by the combustion IR absorption method. Additional chemical analyses were performed by us using energy dispersive X-ray spectroscopy (EDX) at an accelerating voltage of $25\\mathrm{kV}$ and a working distance of $8.5\\ \\mathrm{mm}$ in a scanning electron microscope (SEM) of type Leo 1530 VP. Five locations, each covering an area of $400~{\\upmu\\mathrm{m}}\\times300~{\\upmu\\mathrm{m}}$ and spaced $2~\\mathrm{mm}$ apart between the center and the outer edge of the recrystallized rod were analyzed by EDX to check whether the recrystallized alloys are chemically homogeneous. \n\nTexture was determined by electron backscatter diffraction (EBSD) in a SEM of type Quanta FEI 650 ESEM equipped with a Hikari XP camera (EDAX, AMETEK) at an accelerating voltage of $30\\mathrm{kV},$ , a working distance of $11-15\\mathrm{mm}$ and step sizes between 0.3 and $1~{\\upmu\\mathrm{m}}$ . Pattern analysis was performed using the TSL OIM Analysis software (version 6.2.0). As rotary swaging is axisymmetric, the texture of the recrystallized rod is represented by an inverse pole figure (IPF) along a direction parallel to the rod axis. The IPF was calculated using the harmonic expansion method up to a series expansion degree of 22 and a Gaussian half width of $5^{\\circ}$ without imposing any sample symmetry. Texture intensities are given as multiples of a random orientation distribution (m.r.d.). \n\nMean grain size was determined with the Heyn linear intercept method (ASTM E112-10) using four equidistant and parallel lines of identical length per micrograph. Annealing twin boundaries were not counted as grain boundaries. Five backscatter electron micrographs, taken at locations spaced $2~\\mathrm{mm}$ apart between the center and the outer surface of the recrystallized rod were used for the determination of the mean grain size. Using this method, the determination of the mean grain size involved about 1000 \n\nintercepts. \n\nTo investigate microstructure evolution during tensile straining, slices for TEM were cut from the gauge sections of deformed tensile specimens. These slices were ground to a thickness of $90\\upmu\\mathrm{m}$ using 600-grit SiC paper. TEM foils were then prepared by double-jet electrochemical thinning at $20~\\mathsf{V}$ using an electrolyte consisting of $70\\mathrm{vol}\\%$ of methanol, $20\\mathrm{vol}\\%$ of glycerine, and $10\\mathrm{vol}\\%$ perchloric acid at $253\\mathrm{K}.$ . TEM analyses were performed on a Tecnai Supertwin F20 G2 instrument operating at $200~\\mathrm{kV}$ . \n\n# 2.4. Dislocation analysis and measurement of the stacking fault energy (SFE) \n\nTo determine the operative slip systems and the SFE of the CrCoNi alloy, $3\\mathrm{mm}$ diameter TEM disks need to be extracted from strained specimens at $45^{\\circ}$ to the loading axis. For geometrical reasons, such disks could not be obtained from the gauge sections $(1.2\\times4\\times20\\mathrm{mm}^{3}.$ ) of our tensile specimens. Therefore, additional cylindrical specimens with a length of $10~\\mathrm{mm}$ and a diameter of $4~\\mathrm{mm}$ were deformed in compression at $293\\mathrm{~K~}$ to ${\\sim}4\\%$ strain at an engineering strain rate of $1\\bar{0}^{-3}\\ s^{-1}$ . The stress-strain curves in compression and tension are identical during the early stage of plasticity, i.e. they exhibit the same yield stress and work hardening rate up to $4\\%$ strain. Slices were cut from the compression specimen at $45^{\\circ}$ to the loading axis and TEM specimens were prepared as described in section 2.3. To determine the Burgers vectors of the dislocations introduced during compression, ${\\pmb{g}}\\cdot{\\pmb{b}}$ analysis was carried out. In the following, $\\pmb{b}$ is the Burgers vector of a full dislocation and $\\pmb{b_{\\mathrm{p}1}}$ and $\\pmb{b_{\\mathrm{p}2}}$ are the Burgers vectors of the corresponding Shockley partials. \n\nMeasurements of dissociation widths were performed on partial dislocations lying on {111} planes nearly parallel to the TEM foil using the ${<}111{>}$ zone-axis nearly perpendicular to the TEM foil. Under these conditions, three $\\pmb{g}$ vectors of type ${<}110>$ are available, e.g. 2 0 2 , 2 2 0 and $[0\\ 2\\ \\overline{{2}}]$ for the [111] zone axis. Weak beam was employed using the ${\\pmb g}(3{\\bf g})$ configuration leading to $\\pmb{g}\\cdot\\pmb{b}\\leq2$ , an excitation distance $\\xi_{\\mathrm{g}}\\sim100~\\mathrm{nm}$ determined using the large angle convergent beam technique [26e28] and an excitation error $s_{\\mathrm{g}}\\sim0.1\\bar{5}\\ \\mathrm{nm}^{-1}$ calculated using \n\n$$\ns_{g}=\\frac{1}{2}\\left(n-1\\right)~\\left|\\mathbf{g}\\right|^{2}~\\lambda\n$$ \n\nwhere $\\lambda$ is the electron wavelength and $n=3$ for ${\\pmb g}(3{\\bf g})$ [28]. To ensure that the image peak position of the partials is insensitive to foil thickness and dislocation depth, Cockayne [29] has shown that the parameter $w=s_{\\mathrm{g}}\\xi_{\\mathrm{g}}$ should fulfill the requirement that $w\\ge5$ , which is the case in the present study since $w=15$ . Regarding the resolution (image width) of the partials, Cockayne [30] suggested using an excitation error $s_{\\mathrm{g}}\\geq0.2~\\mathrm{nm}^{-1}$ to obtain an image halfwidth (or full-width at half-height) of an edge partial of $2.5\\ \\mathrm{nm}$ (the image of an edge dislocation is 1.75 times broader than that of a screw [31]). Note that edge and screw here refer to the character of the full dislocation. Historically, Cockayne’s experiments were performed using an acceleration voltage of $100~\\mathrm{kV}$ in the TEM, which yields a value of $s_{\\mathrm{g}}=0.2\\ \\mathrm{nm}^{-1}$ for copper. In the present study the acceleration voltage was $200~\\mathrm{kV},$ , making $s_{\\mathrm{g}}$ closer to $0.15\\ \\mathrm{\\nm}^{-1}$ , which results in a resolution of $3.3\\ \\mathrm{nm}$ for an edge partial, i.e., partials spaced less than $3.3\\ \\mathrm{{\\nm}}$ apart cannot be resolved. While this slight decrease in resolution may be problematic in FCC materials with a high SFE like copper or nickel $(\\mathrm{SFE}>40~\\mathrm{mJ}~\\mathrm{m}^{-2},$ ), it does not impose a significant burden in materials with a low SFE like the CrCoNi alloy studied here. Dissociation widths were measured at locations spaced $30\\mathrm{nm}$ apart along extended, straight sections of isolated dislocations in relatively thick areas (foil thickness: $260~\\mathrm{{nm}}$ ) to minimize effects of image forces. \n\nBecause the strain field in regions between the Shockley partials is different from that outside the dissociated pair, one of the two partials appears brighter than the other when using weak beam diffraction imaging. Moreover, the image peaks of the partials are not equidistant from their respective cores, i.e., the observed dissociation width $d_{\\mathrm{obs}}$ differs from the actual spacing between partials, $d_{\\mathrm{{act}}},$ and the following correction has to be applied to determine the actual dissociation width [30]: \n\n$$\nd_{\\mathrm{act}}=\\sqrt{d_{\\mathrm{obs}}^{2}-\\frac{4}{a\\ b}}+\\frac{b-a}{a\\ b}\n$$ \n\n$$\na=\\frac{-S_{g}}{\\frac{\\mathbf{g}}{2\\pi}\\cdot\\left(\\pmb{b}_{\\mathbf{p}1}+\\frac{\\pmb{b}_{\\mathbf{p}1,e}}{2(1-\\nu)}\\right)}\n$$ \n\n$$\nb=\\frac{-s_{g}}{\\frac{\\mathbf{g}}{2\\pi}\\cdot\\left(\\pmb{b}_{\\mathbf{p}2}+\\frac{\\pmb{b}_{\\mathbf{p}2,e}}{2(1-\\nu)}\\right)}\n$$ \n\nwhere $\\nu$ is Poisson’s ratio (0.3 for the CrCoNi alloy [4]), and $\\pmb{b_{\\mathrm{p}1}},\\pmb{b_{\\mathrm{p}2}}$ and ${\\pmb{b}}_{{\\bf p}1,{\\bf e}},{\\pmb{b}}_{{\\bf p}2,{\\bf e}}$ are the Burgers vectors of the partial dislocations and their edge components, respectively, which can be calculated from the lattice parameter determined in section 3.1. \n\nThe equilibrium spacing between Shockley partials is the result of two opposing forces. On the one hand, the partials want to be as close as possible to minimize the width and thus energy of the stacking fault, while on the other they want to be as far apart as possible to minimize the repulsive elastic interaction between the dislocations. Assuming isotropic elasticity, the SFE can be calculated from the dissociation width using \n\n$$\nS F E=\\frac{G~b_{\\mathrm{p}}^{2}}{8~\\pi~d_{\\mathrm{act}}}\\left(\\frac{2-\\nu}{1-\\nu}\\right)\\left(1-\\frac{2~\\nu~\\cos(2~\\beta)}{2-\\nu}\\right)\n$$ \n\nwhere $G$ is the shear modulus (87 GPa for the CrCoNi alloy [4]), $\\beta$ is the angle between the dislocation line and the Burgers vector of the full dislocation, and $b_{\\mathfrak{p}}$ is the magnitude of the Burgers vector of the partials $\\mathrm{(0.146\\nm}$ , derived from the measured lattice parameter in section 3.1). \n\n# 3. Results and discussion \n\n# 3.1. Crystallography, chemical composition, microstructure and texture \n\nAn X-ray diffraction pattern taken on a longitudinal section of the swaged and recrystallized rod is shown in Fig. 1. All diffraction peaks can be indexed assuming a single FCC phase with a lattice parameter $a=0.3567~\\mathrm{nm}$ . \n\nAs shown in Table 1, the chemical composition of the CrCoNi alloy determined by XRFA, 32.53Cr-33.30Co-32.85Ni (at.%), is close to the targeted equiatomic composition. Additionally, EDX measurements performed at different locations (as described in section 2.3) revealed a uniform, nearly equiatomic chemical composition. The concentrations of the impurity elements, C, O, and S, are all relatively low. Similar results were previously reported for the CrMnFeCoNi alloy [36] and are presented in Table 1 for comparison. Based on these results, it is unlikely that the superior mechanical properties of the CrCoNi MEA are due to deviations from the equiatomic composition or major differences in the impurity concentrations. \n\nThe microstructure and the texture of the fully recrystallized \n\n![](images/8c34af0d9102264161c4de3f21c4b4a164db538a6f2cfcce495c5545d31dfd21.jpg) \nFig. 1. X-ray diffraction pattern of the recrystallized CrCoNi alloy indexed as singlephase FCC with lattice parameter $a=0.3567~\\mathrm{nm}$ . \n\nTable 1 Chemical composition (in at.%) of the CrCoNi medium-entropy alloy. For comparison, the chemical composition (in at.%) of the CrMnFeCoNi high-entropy alloy taken from Ref. [36] is also given. The precision of the values is $0.02\\%$ and $0.005\\%$ for metallic and non-metallic elements, respectively. \n\n\n
AlloyCrMnFeCoNiC0S
CrCoNi32.530.090.9533.3032.850.0190.2260.004
CrMnFeCoNi19.4120.1020.5620.2619.580.0510.0330.009
\n\nCrCoNi were characterized by EBSD. Fig. 2a shows a high magnification backscatter micrograph in which the longitudinal axis of the swaged rods is indicated by the white arrow in the upper right corner. An equiaxed grain structure can be seen along with a few dark regions that are elongated along the rod axis (see upper left corner in Fig. 2a). EDX analysis revealed that these dark regions are oxide particles. Additional analyses (not shown here) revealed that these oxides formed during melting and casting and their volume fraction did not change after thermomechanical processing. However, they fracture during swaging causing them to appear as stringers aligned parallel to the deformation direction. Using image analysis software their surface area fraction, which does not vary along the radius, was determined to be $0.004\\pm0.001$ Fig. 2b is a grain orientation map with an overlaid image quality map where the individual crystallites are colored according to their crystallographic orientation relative to the rod axis (as shown in the upper right corner of Fig. 2a). In Fig. 2b, equiaxed grains containing several S3 annealing twins can be observed. Their density was determined to be $2.5\\pm0.1$ twins per grain using the procedure described in Ref. [32]. The grain size is uniform along the radius of the recrystallized rod and has a mean value of $16\\pm5~{\\upmu\\mathrm{m}}$ . The IPF in Fig. 2c shows that the texture along the rod axis is almost random, with a slight ${<}111{>}$ and a weak ${<}100{>}$ fiber texture, as indicated by a maximum pole intensity that is ${\\sim}2.3$ times random. This slight texture obtained after swaging and recrystallization is typical of FCC metals and alloys [24,33e36]. Finally, as XRD and EBSD are relatively coarse-scale observations that could miss small secondphase particles, extensive TEM analysis was carried out to look for precipitates. Fig. 3a is a bright field (BF) image taken at low magnification showing the absence of any second phase particles at the grain boundaries or within the grains. The white dashed circle in Fig. 3a indicates the selected area contributing to the selected area diffraction (SAD) pattern shown in Fig. 3b. No additional diffraction spots other than those of the FCC lattice can be seen, consistent with the absence of secondary phases. Additionally, the as-recrystallized alloy exhibits a very low dislocation density as shown in Fig. 3a. Similar results were obtained at all other locations examined. In summary, the CrCoNi MEA investigated here is singlephase FCC, with an equiaxed nearly random grain structure, a grain size of approximately 16 $\\upmu\\mathrm{m}$ , and low starting dislocation density. \n\n# 3.2. Tensile properties \n\nThe true stress e true strain response of the polycrystalline CrCoNi alloy tensile tested to fracture at 77 K and $293\\mathrm{K}$ is shown in Fig. 4a (arrowed curves). Also shown are stress-strain curves from several additional tests that were interrupted before failure and unloaded after reaching different stress levels (the corresponding engineering stress-strain curves are not shown in the interest of saving space). As the test temperature is decreased from $293\\mathrm{~K~}$ to $77~\\mathrm{\\K},$ the yield strength $\\sigma_{\\mathrm{y}}$ increases from $360~\\pm~10$ MPa to $560\\pm20\\mathrm{MPa}$ and the ultimate tensile strength $\\sigma_{\\mathrm{uts}}$ increases from ${\\sim}870\\ensuremath{\\mathrm{MPa}}$ to ${\\sim}1230\\ensuremath{\\mathrm{MPa}}$ . Additionally, the tensile ductility (strain to failure) increases from ${\\sim}38\\%$ at $293\\mathrm{~K~}$ to ${\\sim}45\\%$ at $77\\mathrm{K}.$ . \n\nThe derivative of true stress with respect to true strain, $\\mathrm{d}\\sigma/\\mathrm{d}\\varepsilon$ which is the work hardening rate (WHR), is shown in Fig. 4b as a function of true stress. The grey area indicates the region in which necking is predicted to occur according to Consid\u0002ere’s criterion: ${\\bf d}\\sigma/$ $\\mathbf{d}\\varepsilon<\\sigma$ . At 77 K, the WHR is consistently higher than at 293 K and its intersection with the necking line $(\\mathsf{d}\\sigma/\\mathsf{d}\\varepsilon=\\sigma)$ occurs at higher strain. As a consequence of the postponement of necking, the ductility at $77\\mathrm{K}$ is higher than at $293\\ \\mathrm{K}.$ Two stages can be distinguished in both WHR curves (Fig. 4b) with an initial rapid decrease followed by a slower second stage. The extended region of work hardening at $77\\mathrm{K}$ compared to $293\\mathrm{~K~}$ is due to the earlier onset of nanotwinning, as discussed later. For comparison, the previously reported [16] true stress e true strain curves of the CrMnFeCoNi alloy, and its work hardening rate as a function of true stress, are shown in Figs. 4c and d, respectively. \n\n![](images/e2d78269da5c23761e9bd27da87fa9ffa6ba8b79c9da1ac0f61d078d68ccd984.jpg) \nFig. 2. Representative microstructure of the recrystallized CrCoNi alloy. (a) SEM backscatter micrograph with white arrow in the upper right corner indicating the axis of the swaged rod, (b) color-coded grain orientation map on a plane parallel to the deformation direction where the colors indicate the crystal orientations (see stereographic triangle in the upper right corner), (c) inverse pole figure showing weak texture parallel to the rod axis (texture is shown as multiples of random orientation, with the red arrow indicating a maximum of 2.3 times random orientation). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/1626f239dca1f94caec9facd48390031d690c9e4399a78d946b93212c4ae0abb.jpg) \nFig. 3. Representative TEM micrograph of the CrCoNi alloy in the as-recrystallized state. (a) High magnification BF image. (b) Diffraction pattern from the selected area highlighted by the dashed circle in (a). \n\n![](images/90531bf1d03cc649ce144cec54fd41dd6f9b2dcaea341760a6c8ff56873b3448.jpg) \nFig. 4. True stress-strain curves of tensile tests at $77\\mathrm{K}$ and $293\\mathrm{~K~}$ of (a) CrCoNi medium-entropy alloy and (c) CrMnFeCoNi high-entropy alloy. Curves with arrows at the end are from specimens tested to fracture while the other curves in (a) are from interrupted tests. Work hardening rate $(\\mathrm{d}\\upsigma/\\mathrm{d}\\upvarepsilon)$ versus true stress of (b) CrCoNi and (d) CrMnFeCoNi. \n\n# 3.3. Dislocation analysis \n\nBurgers vector analysis based on the $\\pmb{g}\\cdot\\pmb{b}=0$ technique in a specimen deformed in compression to $4\\%$ true strain is shown in Fig. 5. As expected for FCC materials [37], long dislocations lying in a (111) plane almost parallel to the TEM foil can be observed in the scanning TEM image (Fig. 5a) obtained in multi-beam condition, see diffraction pattern in Fig. 5b. The white dashed rectangle in Fig. 5a is shown magnified in the $\\pmb{g}(3\\mathbf{g})$ weak beam micrographs in Figs. 5cee where three independent $<220>$ -type $\\pmb{g}$ vectors were used for the Burgers vector analysis. Figs. 5cee reveal the dissociation of a full $1/2[1\\ {\\overline{{1}}}\\ 0]$ dislocation into two Shockley partials according to the following dislocation reaction \n\n$$\n1/2{\\Big[}1\\ {\\overline{{1}}}\\ 0{\\Big]}=1/6{\\Big[}2\\ {\\overline{{1}}}\\ {\\overline{{1}}}{\\Big]}+1/6{\\Big[}1\\ {\\overline{{2}}}\\ 1{\\Big]}\n$$ \n\nConsistent with the above dissociation scheme, for $\\pmb{g}$ ½2 2 0\u0006 (Fig. 5e), which is parallel to the Burgers vector of the full dislocation, both partials are visible; for $\\textbf{g}[0\\overline{{2}}\\ 2]$ (Fig. 5c), the 1=6 2 1 1 partial is invisible $({\\pmb g}{\\cdot}{\\pmb b}=0)$ while the other $1/6[1\\ {\\overline{{2}}}\\ 1]$ is visible; and for $\\textbf{g}[\\overline{{2}}\\textbf{0}2]$ (Fig. 5d) the $1/6[2\\ {\\overline{{1}}}\\ {\\overline{{1}}}]$ partial is visible while the other $1/6[1\\ {\\overline{{2}}}\\ 1]$ is invisible. \n\n![](images/995f4061c42180cdaba1c889e07189d5592e236e60b3d32bc8b821b43c30986f.jpg) \nFig. 5. Dislocation analysis after compression at $293\\mathrm{K}$ to $4\\%$ true strain. (a) STEM image obtained using the diffraction condition shown in (b) revealing long dislocations lying in the (111) plane almost parallel to the TEM foil. (b) Diffraction pattern showing that the [111] zone-axis is almost parallel to the incident beam. (cee) ${\\pmb g}(3{\\bf g})$ Weak beam micrographs obtained from the area marked with a white dashed rectangle in (a). The $\\pmb{g}$ vectors used to set up the ${\\pmb g}(3{\\pmb g})$ diffraction condition are indicated with white arrows at the top of each image. \n\n# 3.4. Stacking fault energy \n\nThe separation distance between Shockley partials was measured using images like that shown in Fig. 5e. From these measurements, the actual separation distance $d_{\\mathrm{{act}}}$ was calculated using Eqs. (2)e(4), and the results are plotted in Fig. 6 as a function of the angle $\\beta$ between the dislocation line and the Burgers vector of the full dislocation. The error bars in Fig. 6 represent $\\pm1$ standard deviation corresponding to at least four distinct measurements at different points along straight segments of isolated dislocations. Eq. (5) was fitted to the experimental data points using the method of weighted least squares, yielding a SFE of $22\\pm4\\mathrm{mJ}\\mathrm{m}^{-2}$ , see red and black dashed lines in Fig. 6. This value is comparable to those obtained using the weak beam technique in binary ${\\mathsf{C o}}_{94}{\\mathsf{F e}}_{6}$ , $\\mathrm{Co}_{68}\\mathrm{Ni}_{32}$ [38], and the TWIP (twinning induced plasticity) steels ${\\mathrm{Fe}}_{66}{\\mathrm{M}}-$ $\\mathrm{n}_{24}\\mathrm{Al}_{5}\\mathrm{Si}_{5}$ [39] and $\\mathrm{Fe_{69}C r_{20}N i_{11}}$ [40] (compositions in at.%), but lower than the value of $30\\pm5\\mathrm{mJ}\\mathrm{m}^{-2}$ obtained in the CrMnFeCoNi HEA [20]. \n\n# 3.5. Microstructural evolution with strain at 293 K and $77K$ \n\nTo obtain a better understanding of the governing deformation mechanisms, we analyzed the microstructures of specimens strained to different levels. Representative images showing the microstructural evolution at $293\\mathrm{K}$ and $77\\mathrm{K}$ are provided in Figs. 7 and 8, respectively, where the pictures in the left column are lowmagnification BF micrographs, those in the middle column are higher magnification BF (Fig. 7a and Figs. 8aeb) or dark field (DF) (Figs. $7b-c$ and Figs. 8ced) micrographs, and those in the right column are selected area diffraction (SAD) patterns (Figs. $_{7a-c}$ and Figs. 8ced). When deformation twins were detected, they were imaged edge-on under DF conditions and the diffraction spots used for imaging are circled in red in the corresponding SAD patterns (Figs. 7bec and Figs. 8ced). \n\nAfter $9.7\\%$ true strain at 293 K (Fig. 7a), there is a strong increase in dislocation density relative to the unstrained state (Fig. 3) as well as extended SFs, which will be discussed in section 3.7. Plasticity occurs by dislocation glide on several different {111} planes. This observation is in good agreement with previous studies on concentrated FCC solid solutions [37]. Dislocations are found to pile-up against grain boundaries, which hinder dislocation transmission. Since the $1/2{<}110{>}$ dislocations are dissociated into relatively widely separated $1/6{<}112{>}$ Shockley partials with stacking faults in between, cross slip is hampered and dislocation glide occurs on well-defined {111} planes. An increase in plastic strain from 9.7 to $12.9\\%$ at $293\\mathrm{~K~}$ results in the activation of a second deformation mechanism, deformation twinning, as shown in Fig. 7b. At a much higher strain of $38.3\\%$ (in the fractured specimen), the volume fraction of twins is significantly greater and several intersecting twins are present within the grains as shown in the lowmagnification BF micrograph in Fig. 7c. Larger strains also result in higher dislocation densities and their organization into cell structures as shown in the inset of Fig. 7c. \n\n![](images/756260f4ebfd47dfee46f54faa458ccc521b6ebb6098753eaaaca068368de580.jpg) \nFig. 6. Spacing between Shockley partial dislocations as a function of the angle between the dislocation line and the Burgers vector of the full dislocation. The dashed lines represent partial dislocation spacings calculated using Eq. (5) for different stacking fault energies indicated on the right side of the figure. \n\nFig. 8 summarizes the microstructural evolution during deformation at 77 K. As at room temperature, the initial stage of plastic deformation is characterized by dislocation glide on ${<}110{>}\\{111\\}$ slip systems (Figs. 8aeb) with the formation of dislocation pile-ups at the grain boundaries, see lower left corner of Fig. 8b, and by the formation of extended SFs. However, deformation twinning starts at lower plastic strain at $77\\mathrm{K}$ than 293 K. Thus, while deformation twinning was first detected after $12.9\\%$ true strain at $293\\ \\mathrm{K},$ it is present in specimens strained to $6.7\\%$ at $77\\mathrm{K},$ Fig. 8c. Finally, as in the case of the ruptured 293-K specimen (Fig. 7c), at $77\\mathrm{K}$ also the ruptured specimen $(44.2\\%$ true strain) contains several intersecting twins, Fig. 6d. \n\nThe nature of the stacking faults (intrinsic versus extrinsic) was assessed as follows. Fig. 9 shows wide stacking faults exhibiting fringe contrast in a specimen subjected to $6.7\\%$ true strain at $77\\mathrm{K}.$ · The stacking faults are intersected by nanotwins indicated with red arrows in Fig. 9a. The character of the stacking fault was determined using a procedure developed for FCC materials [28]. When the origin of a $\\pmb{g}$ vector of type ${<}111{>}$ , $<220>$ or ${<}400{>}$ is placed at the center of the stacking fault in the DF micrograph (g[111] in Fig. 9b), it points away from the bright outer fringe if the fault is intrinsic and toward it if it is extrinsic. The reverse correlation occurs if the reflections are ${<}200{>}$ , $\\phantom{0}{<}222>$ or ${<}440>$ . As the ${\\pmb g}[111]$ vector is pointing away from the bright outer fringe, it is concluded that the stacking faults in Fig. 9b are intrinsic rather than extrinsic. \n\n# 3.6. Critical twinning stress \n\nBased on the above microstructural observations we conclude that twinning starts at true strains between $4.0\\%$ and $6.7\\%$ at $77\\mathrm{~K~}$ and between $9.7\\%$ and $12.9\\%$ at 293 K. The corresponding true stress values, hereafter referred to as the twinning stress values, are $835\\pm55$ MPa at $77\\mathrm{K}$ and $740\\pm45$ MPa at 293 K. Given the overlap in these values and the experimental scatter, we consider the roughly temperature-independent twinning stress to be ${\\sim}790\\ \\pm\\ 100$ MPa. Assuming a Taylor factor of 3.06, the critical resolved shear stress for twinning can then be estimated as $260\\pm30$ MPa. This value is comparable to that determined in the CrMnFeCoNi HEA with the same grain size: $235\\pm10$ MPa [16]. Different models [41e50] have been proposed for the prediction of the critical twinning stress in FCC materials, which depends on factors such as SFE, grain size, and shear modulus (among others). Here we kept the grain size constant so it need not be considered as a contributing factor. However, further studies are needed to understand how the other factors interact to produce roughly similar twinning stresses in CrCoNi and CrMnFeCoNi. Regardless, what can be concluded is that the twinning stress is more easily reached in CrCoNi (present study) than in CrMnFeCoNi [16]. This is because of two reasons. First, the yield stress of CrCoNi is significantly higher than that of CrMnFeCoNi: 360 MPa versus 265 MPa at $293\\mathrm{~K~}$ and $560\\ensuremath{\\mathrm{MPa}}$ versus 460 MPa at 77 K, see Fig. 4. This has been explained using a new theory of solid solution strengthening that takes into account atomic volume misfits in concentrated solid solutions [17]. The compositional dependence of yield stress has also been correlated with the mean square atomic displacements of the constituent atoms from their ideal FCC lattice positions and shown to be higher in CrCoNi than in CrMnFeCoNi [51]. Second, the work hardening rate is higher in CrCoNi than in CrMnFeCoNi, which is mainly due to the fact that the shear modulus of the former (87 GPa [4]) is larger than that of the latter (81 GPa [36]). The earlier activation of twinning means that there is a larger strain range where nanotwinning can occur in CrCoNi which then results in superior mechanical properties. Another noteworthy result is that, in both alloys, the yield stress increases with decreasing temperature but the twinning stress is relatively insensitive to temperature. Consequently, the twinning stress is reached more easily (i.e., at lower strains) at $77\\mathrm{K}$ than at $293\\mathrm{K}$ and the mechanical properties of both alloys improve at cryogenic temperatures. \n\n![](images/bd2ca711f7e37c4327943e1860b7fd1523e6024de4b199811bf4413b5742d484.jpg) \nFig. 7. TEM micrographs showing microstructural evolution with true tensile strain at $293\\mathrm{K}.$ Figures in the left column are low magnification BF images, those in the middle are either (a) BF or (bec) DF images, and those in the right column are SAD patterns. Diffraction spots circled in red in the SAD patterns (bec) were used to obtain the corresponding DF images where nanotwins are observed edge-on. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n# 3.7. Further features of microstructure prior to the onset of twinning \n\nFig. 10 shows some interesting microstructural features in a specimen deformed in tension at $293\\mathrm{~K~}$ to a true strain of $9.7\\%$ . Fig. 10a shows a network of extended and contracted nodes, which further confirms the low SFE measured in the present study since networks of extended and contracted nodes are frequently observed in relatively low SFE materials [52] as a result of intersections of dissociated dislocations [53]. Fig. 10b also reveals the presence of extended SFs on different {111} planes that intersect each other. One set of SFs is edge-on (white arrowheads in Fig. 10b), which produce the streaks observed in the diffraction pattern on the right side of Fig. 10b; they intersect another set of SFs that are more in plane (indicated by the red arrowheads). Stacking faults that are sheared during deformation typically leave behind interfacial partial dislocations [54]. These interfacial dislocations may be mobile and their glide may result in thickening or thinning of the SF. Further interactions may lead to two intrinsic SFs forming on successive {111} planes producing first an extrinsic SF [55] and ultimately a nanotwin when three or more intrinsic SFs form on successive {111} planes. An example of extended SFs (bright and dark fringes) which intersect edge-on nanotwins is shown in Fig. 9. Based on these observations, it is therefore likely that the formation of extended SFs plays a key role in the formation of twins as suggested by many authors in the literature, e.g., in Cu-based alloys [56], and TWIP and Hadfield steels [50,57,58]. \n\n![](images/33a4bae90606c7fab5608bb5142404562a6be2b75fafefdf50c298bf8e44b67b.jpg) \nFig. 8. TEM micrographs showing microstructural evolution with true tensile strain at $77\\mathrm{K}.$ In (a) and (b) both rows are BF images. In (c) and (d) figures in the left column are BF images, those in the middle are DF images, and those in the right column are SAD patterns showing diffraction spots from the twin and matrix. Diffraction spots circled in red in the SAD patterns were used to obtain the dark field images. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n# 4. Summary and conclusions \n\nAn equiatomic CrCoNi medium-entropy alloy was produced by vacuum induction melting and casting followed by swaging at room temperature and recrystallization at $1173\\mathrm{~K~}$ for $^\\mathrm{~1~h~}$ . This thermomechanical process yielded a FCC single-phase material with a uniform grain size of ${\\sim}16\\upmu\\mathrm{m}$ and close to random texture. Its mechanical properties were investigated at $77\\mathrm{K}$ and $293\\mathrm{K}$ and the governing deformation mechanisms characterized by TEM. Based on a comparison of the present results with those from earlier studies on the CrMnFeCoNi HEA, the following conclusions can be \n\n![](images/57fc35b9dea0558602cdffcf20da0a5d691036a62192375802743196e2ab020d.jpg) \nFig. 9. (a) BF micrograph showing edge-on twins intersected by extended stacking faults (black and white fringes). (b) DF micrograph. (c) Diffraction pattern showing the presence of extra diffraction spots (circled in red) due to the presence of edge-on deformation twins. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/6dc8531a9d2a6744aa3d726911a92a9b112ac12dac2662ce652573a8244f2cdc.jpg) \nFig. 10. Interesting microstructural features observed prior to mechanical twinning. (a) Network of in-plane dislocations showing extended nodes (left image) and corresponding diffraction pattern (right image). (b) Intersections of two families of SFs (left image): SFs of the 1st family are edge-on and are indicated by white arrowheads at the bottom of Fig. 10b whereas SFs of the 2nd family are close to in-plane and are indicated by red arrowheads. The corresponding diffraction pattern shows streaks (white arrowhead) perpendicular to edge-on SFs. Negative images of the diffraction patterns are shown to highlight (a) absence or (b) presence of streaks due to edge-on stacking faults. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\ndrawn. \n\n(1) The yield strength, work hardening rate, ultimate tensile strength, and elongation to fracture of the CrCoNi MEA all increase strongly with decreasing temperature, similar to what has been observed before in the CrMnFeCoNi HEA [16]. However, the mechanical properties of the CrCoNi MEA are superior to those of the CrMnFeCoNi HEA. Both alloys were processed similarly to have close to random texture and practically identical grain sizes, so the difference in mechanical behavior must be due to other reasons. \n\n(2) The initial stage of plasticity in CrCoNi is characterized by the glide of $1/2{<}110{>}$ dislocations dissociated into two $1/6{<}112{>}$ Shockley partials on {111} planes with a stacking fault in between, similar to the behavior of CrMnFeCoNi. \n\n(3) The separation between the Shockley partials in CrCoNi ranges from ${\\sim}5\\mathrm{nm}$ near the screw orientation to ${\\sim}11\\ \\mathrm{nm}$ near the edge, which is larger than the corresponding partial separations in CrMnFeCoNi, ${\\sim}4$ and ${\\sim}6.5\\ \\mathrm{nm}$ , respectively [20]. These relatively wide dissociations are expected to hamper cross-slip and promote planar slip in the early stages of plastic deformation in both alloys. \n\n(4) From the measured partial separations, the stacking fault energy of CrCoNi can be estimated to be $22\\pm4~\\mathrm{mJ}~\\mathrm{m}^{-2}$ , which is approximately $25\\%$ lower than that determined previously for CrMnFeCoNi $(30\\pm5~\\mathrm{mJ}~\\mathrm{m}^{-2}.$ [20]. \n(5) As deformation progresses, nanotwinning is activated as an additional deformation mechanism in CrCoNi at true strains between $4.0\\%$ and $6.7\\%$ at 77 K and between $9.7\\%$ and $12.9\\%$ at $293\\ \\mathrm{K}.$ This is earlier than in CrMnFeCoNi [16]. Twinning promotes a high work hardening rate by introducing extra boundaries that act as barriers to dislocation motion (“dynamic Hall-Petch effect”), which postpones the onset of necking and increases ductility. \n(6) The true tensile stress and resolved shear stress for the onset of twinning in CrCoNi are determined to be $790\\pm100\\mathrm{MPa}$ and $260~\\pm~30$ MPa, respectively, roughly independent of temperature. For the same grain size, the corresponding twinning stresses in CrMnCoFeNi were previously found to be comparable: $720\\pm30$ MPa and $235\\pm10\\mathrm{MPa}$ , respectively [16]. \n(7) There are at least two reasons why the ultimate strength and ductility of the CrCoNi MEA are higher than those of the CrMnFeCoNi HEA: its yield strength and work hardening rate are higher, which allow the twinning stress to be reached earlier (after smaller plastic strains) and nanotwinning to occur over a more extended strain range. This in turn allows the necking instability to be postponed more effectively in CrCoNi than in CrMnFeCoNi and the strength-ductility combination to be better. \n(8) The critical stress for twinning in both alloys is roughly independent of temperature, but their yield strengths increase with decreasing temperature. This makes it easier to reach the twinning stress as the temperature is lowered. Therefore, nanotwinning occurs over a more extended strain range, allowing the necking instability to be postponed and the strength-ductility combination to improve as the temperature is decreased in both alloys. \n\n# Acknowledgments \n\nG.L., E.P.G., and G.E. acknowledge funding from the German Research Foundation (DFG) through projects LA 3607/1-1, GE 2736/ 1-1, and project B7 of the SFB/TR 103, respectively. \n\n# References \n\n[1] J.-W. Yeh, Physical metallurgy of high-entropy alloys, JOM 67 (2015) 2254. \n[2] A. Gali, E.P. George, Tensile properties of high- and medium-entropy alloys, Intermetallics 39 (2013) 74. \n[3] Z. Wu, H. Bei, F. Otto, G.M. Pharr, E.P. George, Recovery, recrystallization, grain growth and phase stability of a family of FCC-structured multi-component equiatomic solid solution alloys, Intermetallics 46 (2014) 131. \n[4] Z. Wu, H. Bei, G.M. Pharr, E.P. George, Temperature dependence of the mechanical properties of equiatomic solid solution alloys with face-centered cubic crystal structures, Acta Mater. 81 (2014) 428. \n[5] F. Otto, A. Dlouhý, C. Somsen, H. Bei, G. Eggeler, E.P. George, The influences of temperature and microstructure on the tensile properties of a CoCrFeMnNi high-entropy alloy, Acta Mater. 61 (2013) 5743. \n[6] B. Gludovatz, A. Hohenwarter, K.V.S. Thurston, H. Bei, Z. Wu, E.P. George, R.O. Ritchie, Exceptional damage-tolerance of a medium-entropy alloy CrCoNi at cryogenic temperatures, Nat. Commun. 7 (2016). \n[7] B. Gludovatz, A. Hohenwarter, D. Catoor, E.H. Chang, E.P. George, R.O. Ritchie, A fracture-resistant high-entropy alloy for cryogenic applications, Science 345 (2014) 1153. \n[8] C. Zhu, Z.P. Lu, T.G. Nieh, Incipient plasticity and dislocation nucleation of FeCoCrNiMn high-entropy alloy, Acta Mater. 61 (2013) 2993. \n[9] G.A. Salishchev, M.A. Tikhonovsky, D.G. Shaysultanov, N.D. Stepanov, A.V. Kuznetsov, I.V. Kolodiy, A.S. Tortika, O.N. Senkov, Effect of Mn and V on structure and mechanical properties of high-entropy alloys based on CoCrFeNi system, J. Alloys Compd. 591 (2014) 11. \n[10] J.Y. He, C. Zhu, D.Q. Zhou, W.H. Liu, T.G. Nieh, Z.P. Lu, Steady state flow of the FeCoNiCrMn high entropy alloy at elevated temperatures, Intermetallics 55 (2014) 9. \n[11] C.C. Tasan, Y. Deng, K.G. Pradeep, M.J. Yao, H. Springer, D. Raabe, Composition dependence of phase stability, deformation mechanisms, and mechanical properties of the CoCrFeMnNi high-entropy alloy system, JOM 66 (2014) 1993. \n[12] N. Stepanov, M. Tikhonovsky, N. Yurchenko, D. Zyabkin, M. Klimova, S. Zherebtsov, A. Efimov, G. Salishchev, Effect of cryo-deformation on structure and properties of CoCrFeNiMn high-entropy alloy, Intermetallics 59 (2015) 8. \n[13] Z. Zhang, M.M. Mao, J. Wang, B. Gludovatz, Z. Zhang, S.X. Mao, E.P. George, Q. Yu, R.O. Ritchie, Nanoscale origins of the damage tolerance of the highentropy alloy CrMnFeCoNi, Nat. Commun. 6 (2015). \n[14] W. Woo, E.W. Huang, J.-W. Yeh, H. Choo, C. Lee, S.-Y. Tu, In-situ neutron diffraction studies on high-temperature deformation behavior in a CoCrFeMnNi high entropy alloy, Intermetallics 62 (2015) 1. \n[15] T.M. Smith, M.S. Hooshmand, B.D. Esser, F. Otto, D.W. McComb, E.P. George, M. Ghazisaeidi, M.J. Mills, Atomic-scale characterization and modeling of $60^{\\circ}$ dislocations in a high-entropy alloy, Acta Mater. 110 (2016) 352. \n[16] G. Laplanche, A. Kostka, O.M. Horst, G. Eggeler, E.P. George, Microstructure evolution and critical stress for twinning in the CrMnFeCoNi high-entropy alloy, Acta Mater. 118 (2016) 152. \n[17] C. Varvenne, A. Luque, W.A. Curtin, Theory of strengthening in fcc high entropy alloys, Acta Mater. 118 (2016) 164. \n[18] Z. Li, K.G. Pradeep, Y. Deng, D. Raabe, C.C. Tasan, Metastable high-entropy dual-phase alloys overcome the strengtheductility trade-off, Nature 534 (2016) 227. \n[19] H.S. Oh, D. Ma, G.P. Leyson, B. Grabowski, E.S. Park, F. Ko€rmann, D. Raabe, Lattice distortions in the FeCoNiCrMn high entropy alloy studied by theory and experiment, Entropy 18 (2016) 321. \n[20] N.L. Okamoto, S. Fujimoto, Y. Kambara, M. Kawamura, Z.M. Chen, H. Matsunoshita, K. Tanaka, H. Inui, E.P. George, Size effect, critical resolved shear stress, stacking fault energy, and solid solution strengthening in the CrMnFeCoNi high-entropy alloy, Sci. Rep. 6 (2016). \n[21] Y. Liu, J. Wang, Q. Fang, B. Liu, Y. Wu, S. Chen, Preparation of superfine-grained high entropy alloy by spark plasma sintering gas atomized powder, Intermetallics 68 (2016) 16. \n[22] D.-H. Lee, M.-Y. Seok, Y. Zhao, I.-C. Choi, J. He, Z. Lu, J.-Y. Suh, U. Ramamurty, M. Kawasaki, T.G. Langdon, J.-i. Jang, Spherical nanoindentation creep behavior of nanocrystalline and coarse-grained CoCrFeMnNi high-entropy alloys, Acta Mater. 109 (2016) 314. \n[23] B. Wang, A. Fu, X. Huang, B. Liu, Y. Liu, Z. Li, X. Zan, Mechanical properties and microstructure of the CoCrFeMnNi high entropy alloy under high strain rate compression, J. Mater. Eng. Perform 25 (2016) 2985. \n[24] G. Laplanche, O. Horst, F. Otto, G. Eggeler, E.P. George, Microstructural evolution of a CoCrFeMnNi high-entropy alloy after swaging and annealing, J. Alloys Compd. 647 (2015) 548. \n[25] G. Laplanche, U.F. Volkert, G. Eggeler, E.P. George, Oxidation behavior of the CrMnFeCoNi high-entropy alloy, Oxid. Metals 85 (2016) 629. \n[26] P.M. Kelly, A. Jostsons, R.G. Blake, J.G. Napier, The determination of foil thickness by scanning transmission electron microscopy, Phys. Status Solidi (a) 31 (1975) 771. \n[27] S.M. Allen, Foil thickness measurements from convergent-beam diffraction patterns, Philos. Mag. A 43 (1981) 325. \n[28] D.B. Williams, C.B. Carter, Transmission Electron Microscopy: a Textbook for Materials Science, Springer, US, Boston, MA, 1996. \n[29] D.J.H. Cockayne, The weak-beam technique as applied to dissociation measurements, J. de Physique Colloques C7 35 (1974) 141. \n[30] D.J.H. Cockayne, A theorrtical analysis of the weak-beam method of electron microscopy, Z. für Naturforsch. 27a (1972) 452. \n[31] R. Dr Ridder, S. Amelinckx, Approximate theoritical treatmen of weak-beam dislocation images, Phys. Status Solidi (b) 48 (1971) 541. \n[32] F. Otto, N.L. Hanold, E.P. George, Microstructural evolution after thermomechanical processing in an equiatomic, single-phase CoCrFeMnNi highentropy alloy with special focus on twin boundaries, Intermetallics 54 (2014) 39. \n[33] A.T. English, G.Y. Chin, On the variation of wire texture with stacking fault energy in f.c.c. metals and alloys, Acta Metall. 13 (1965) 1013. \n[34] D.N. Lee, Y.H. Chung, M.C. Shin, Preferred orientation in extruded aluminium alloy rod, Scr. Metall. 17 (1983) 339. \n[35] H.J. Shin, H.T. Jeong, D.N. Lee, Deformation and annealing textures of silver wire, Mater Sci. Eng. A 279 (2000) 244. \n[36] G. Laplanche, P. Gadaud, O. Horst, F. Otto, G. Eggeler, E.P. George, Temperature dependencies of the elastic moduli and thermal expansion coefficient of an equiatomic, single-phase CoCrFeMnNi high-entropy alloy, J. Alloys Compd. 623 (2015) 348. \n[37] R.W.K. Honeycombe, The Plastic Deformation of Metals, second ed., Edward Arnold Ltd, London, 1984. \n[38] T.C. Tisone, The concentration and temperature dependence of the stacking fault energy in face-centered cubic Co-Fe alloys, Acta Metall. 21 (1973) 229. \n[39] D.T. Pierce, J.A. Jim\u0003enez, J. Bentley, D. Raabe, J.E. Wittig, The influence of stacking fault energy on the microstructural and strain-hardening evolution of FeeMneAleSi steels during tensile deformation, Acta Mater. 100 (2015) 178. \n[40] J. Lu, L. Hultman, E. Holmstro€m, K.H. Antonsson, M. Grehk, W. Li, L. Vitos, A. Golpayegani, Stacking fault energies in austenitic stainless steels, Acta Mater. 111 (2016) 39. \n[41] J.A. Venables, Deformation twinning in face-centred cubic metals, Philos. Mag. 6 (63) (1961) 379. \n[42] J.B. Cohen, J. Weertman, A dislocation model for twinning in f.c.c. metals, Acta Metall. 11 (1963) 996. \n[43] J.A. Venables, The electron microscopy of deformation twinning, J. Phys. Chem. Solids 25 (1964) 685. \n[44] G. Fontaine, Propagation des macles dans les m\u0003etaux fortement \u0003ecrouis, Phys. Status Solidi (b) 15 (1966) 603. \n[45] S. Mahajan, G.Y. Chin, Formation of deformation twins in f.c.c. crystals, Acta Metall. 21 (1973) 1353. \n[46] N. Narita, J. Takamura, Deformation twinning in silver-and copper-alloy crystals, Philos. Mag. 29 (1974) 1001. \n[47] H. Fujita, T. Mori, A formation mechanism of mechanical twins in F.C.C. Metals, Scr. Metall. 9 (1975) 631. \n[48] J.F.M. Vergnol, J. Grilh\u0003e, Relationship between extrinsic stacking faults and mechanical twinning in F.C.C. solid solutions with low stacking fault energy, J. Phys. 45 (1984) 1479. \n[49] I. Karaman, H. Sehitoglu, K. Gall, Y.I. Chumlyakov, H.J. Maier, Deformation of single crystal Hadfield steel by twinning and slip, Acta Mater. 48 (2000) 1345. \n[50] I. Karaman, H. Sehitoglu, Y.I. Chumlyakov, H.J. Maier, I.V. Kireeva, Extrinsic stacking faults and twinning in hadfield manganese steel single crystals, Scr. Mater. 44 (2001) 337. \n[51] N.L. Okamoto, K. Yuge, K. Tanaka, H. Inui, E.P. George, Atomic displacement in the CrMnFeCoNi high-entropy alloyeA scaling factor to predict solid solution strengthening, AIP Adv. 6 (2016) 125008. \n[52] P.C.J. Gallagher, J. Washburn, The formation of extrinsic-intrinsic faulting, Philos. Mag. 15 (1967) 969. \n[53] M.J. Whelan, Dislocation interactions in face-centred cubic metals, with particular reference to stainless steel, Proc. R. Soc. Lond. A Math. Phys. Eng. Sci. 249 (1959) 114. \n[54] L. Re\u0003my, The interaction between slip and twinning systems and the influence of twinning on the mechanical behavior of fcc metals and alloys, Metall. Trans. A 12 (1981) 387. \n[55] J.P. Hirth, J. Lothe, Theory of Dislocations, John Wiley & Sons, New York, 1982. \n[56] F. Tranchant, J. Vergnol, M.F. Denanot, J. Grilhe\u0003, Mechanical twinning mechanisms in Cu-Al crystals with very low stacking fault energy, Scr. Metall. 21 (1987) 269. \n[57] H. Idrissi, L. Ryelandt, M. Veron, D. Schryvers, P.J. Jacques, Is there a relationship between the stacking fault character and the activated mode of plasticity of FeeMn-based austenitic steels? Scr. Mater. 60 (2009) 941. \n[58] H. Idrissi, K. Renard, L. Ryelandt, D. Schryvers, P.J. Jacques, On the mechanism of twin formation in FeeMneC TWIP steels, Acta Mater. 58 (2010) 2464. " + }, + { + "id": "10.1080_21663831.2017.1343208", + "DOI": "10.1080/21663831.2017.1343208", + "DOI Link": "http://dx.doi.org/10.1080/21663831.2017.1343208", + "Relative Dir Path": "mds/10.1080_21663831.2017.1343208", + "Article Title": "Heterogeneous materials: a new class of materials with unprecedented mechanical properties", + "Authors": "Wu, XL; Zhu, YT", + "Source Title": "MATERIALS RESEARCH LETTERS", + "Abstract": "Here we present a perspective on heterogeneous materials, a new class of materials possessing superior combinations of strength and ductility that are not accessible to their homogeneous counterparts. Heterogeneous materials consist of domains with dramatic strength differences. The domain sizes may vary in the range of micrometers to millimeters. Large strain gradients near domain interfaces are produced during deformation, which produces a significant back-stress to strengthen the material and to produce high back-stress work hardening for good ductility. High interface density is required to maximize the back-stress, which is a new strengthening mechanism for improving mechanical properties. [GRAPHICS] .", + "Times Cited, WoS Core": 1048, + "Times Cited, All Databases": 1104, + "Publication Year": 2017, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000428140600001", + "Markdown": "# Heterogeneous materials: a new class of materials with unprecedented mechanical properties \n\nXiaolei Wu & Yuntian Zhu \n\nTo cite this article: Xiaolei Wu & Yuntian Zhu (2017): Heterogeneous materials: a new class of materials with unprecedented mechanical properties, Materials Research Letters, DOI: 10.1080/21663831.2017.1343208 \n\nTo link to this article: http://dx.doi.org/10.1080/21663831.2017.1343208 \n\n# Heterogeneous materials: a new class of materials with unprecedented mechanical properties \n\nXiaolei $\\mathsf{W u^{a,b}}$ and Yuntian Zhuc,d \n\naState Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing, People’s Republic of China; bSchool of Engineering Science, University of Chinese Academy of Sciences, Beijing, People’s Republic of China; cDepartment of Materials Science and Engineering, North Carolina State University, Raleigh, NC, USA; dNano Structural Materials Center, School of Materials Science and Engineering, Nanjing University of Science and Technology, Nanjing, People’s Republic of China \n\n# ABSTRACT \n\nHere we present a perspective on heterogeneous materials, a new class of materials possessing superior combinations of strength and ductility that are not accessible to their homogeneous counterparts. Heterogeneous materials consist of domains with dramatic strength differences. The domain sizes may vary in the range of micrometers to millimeters. Large strain gradients near domain interfaces are produced during deformation, which produces a significant back-stress to strengthen the material and to produce high back-stress work hardening for good ductility. High interface density is required to maximize the back-stress, which is a new strengthening mechanism for improving mechanical properties. \n\nARTICLE HISTORY Received 27 May 2017 \n\n# KEYWORDS \n\nHeterogeneous materials; strain gradient; back-stress; mechanical incompatibility; mechanical properties \n\n![](images/518db9a5ec962ad371c78d01ba3c3e1ba213eb7f7557e97cc0d95e08c5404edc.jpg) \n\n# IMPACT STATEMENT \n\nHeterogeneous materials are becoming the next hot research field after the nanomaterials era. \n\n# Background \n\nMaterials are either strong or ductile, but rarely both at the same time [1,2]. Stronger and tougher materials are desired for many structural applications such as transportation vehicles for higher energy efficiency and better performance. For the last three decades, nanostructured (ultrafine-grained) metals have been extensively studied because of their high strength. However, overcoming their low ductility has been a challenge [2–25], which is one of the major reasons why they have not been widely commercialized for industrial applications. Another major obstacle to practical structural applications of nanostructured metals is the challenge in scaling up for industrial production at low cost [26]. \n\nAfter over a century’s research, we have almost reached the limit on how much further we can improve the mechanical properties of metals and alloys. Our conventional wisdom from the textbook and literature is to reinforce a weak matrix by a stronger reinforcement such as second-phase particles or fibers. A question arises on if there exist yet-to-be-explored new strategies to make the next generation of metals and alloys with a ‘quantum jump’ in strength and ductility instead of the incremental improvements that we have seen for the last several decades. \n\nRecently, there have been several reports on superior combinations of strength and ductility in various metals and alloys that are processed to have widely different microstructures, including the gradient structure [27–32], heterogeneous lamella structure [33], bimodal structure [10,25,34,35], harmonic structure [36–38], laminate structure [39,40], dual-phase steel [41–43], nanodomained structure [44], nanotwinned grains [45,46], etc. [47]. These materials have one common feature: there is a dramatic difference in strength between different domains, while the sizes and geometry of the domains may vary widely. In other words, there are huge microstructural heterogeneities in these materials. Therefore, these materials can be considered as heterogeneous materials. \n\nIn this perspective, we will present the fundamental physics that renders these heterogeneous materials superior mechanical properties as well as the microstructures that are required for producing the best mechanical properties. \n\n# Definition of heterogeneous materials \n\nHeterogeneous materials can be defined as materials with dramatic heterogeneity in strength from one domain area to another. This strength heterogeneity can be caused by microstructural heterogeneity, crystal structure heterogeneity or compositional heterogeneity. The domain sizes could be in the range of micrometers to millimeters, and the domain geometry can vary to form very diverse material systems. \n\n# Deformation behavior of heterogeneous materials \n\nDuring deformation, for example, tensile testing, of the heterogeneous materials, with increasing applied strain, the deformation process can be classified into three stages (see Figure 1). In stage $I,$ both soft and hard domains deform elastically, which is similar to a conventional homogeneous material. \n\n![](images/0f194b0f506d40a06e4fb2238fc0b96f9558284fb34169862585f5ee0db16e09.jpg) \nFigure 1. The three deformation stages of heterogeneous materials (the red stress–strain curve). \n\nIn stage $H,$ the soft domains will start dislocation slip first to produce plastic strain, while the hard domains will remain elastic, which creates a mechanical incompatibility. The soft domains need to deform together with the neighboring hard domains and, therefore, cannot plastically deform freely. The strain at the domain interface needs to be continuous, although the softer domains will typically accommodate more strains since they are plastically deforming. Therefore, there will be a plastic strain gradient in the soft domain near the domain interface. This strain gradient needs to be accommodated by geometrically necessary dislocations, which will make the softer phase appear stronger [33,48], leading to synergetic strengthening to increase the global measured yield strength of the material [29]. \n\nIn an extreme/ideal case, the soft domains are completely surrounded by the hard domain matrix so that the soft domain cannot change its shape as required by plastic deformation until the hard domain matrix starts to deform plastically. Geometrically necessary dislocations will pile-up at the domain boundaries in the soft domain, but cannot transmit across the domain boundary, building up high back-stress (see Figure 2). This can make the soft domain almost as strong as the hard domain matrix, making the global yield strength much higher than what is predicted by the rule of mixture [33]. \n\nIn stage III, both the soft and hard domains deform plastically, but the soft domains sustain much higher strain than the hard domains, producing the socalled strain partitioning [43,49–53]. When neighboring domains sustain different plastic strains, strain gradients are expected to exist near the domain boundaries in both the soft and hard domains. These strain gradients will become larger with increasing strain partitioning, and consequently produce back-stress work hardening. The back-stress work hardening will help with preventing necking during tensile testing, thus improving ductility. This is the primary reason why dual-phase steel has extraordinary work hardening, and consequently high ductility [43,49,51,53]. \n\n![](images/07e1f7120bd8d5776f2340ee6712dd8d8419ed79d270b7f323bee2d354ab97d3.jpg) \nFigure 2. A 4-μm soft grain surrounded by a hard ultrafinegrained matrix in heterogeneous lamella Ti. Dislocation pile-ups are marked by green lines. \n\n# Back-stress strengthening and back-stress work hardening \n\nAs discussed above, back-stress plays a significant role in the reported extraordinary strength and ductility of heterogeneous metals. Two types of dislocations are usually involved in the plastic deformation of metals and alloys: statistically stored dislocations and geometrically necessary dislocations. The flow stress as a function of dislocation density is conventionally calculated as [54–56] \n\n$$\n\\tau=\\alpha G b\\sqrt{\\rho_{\\mathrm{S}}+\\rho_{\\mathrm{G}}},\n$$ \n\nwhere $\\tau$ is the shear flow stress, $\\alpha$ is a constant, $G$ is the shear modulus, $b$ is the magnitude of Burgers vector, and $\\rho_{\\mathsf{S}}$ and $\\rho_{\\mathrm{G}}$ are the densities of statistically stored dislocations and geometrically necessary dislocations, respectively. In this equation, the statistically stored dislocations and geometrically necessary dislocations are treated to have the same contribution to the flow stress. Obviously, the back-stress caused by geometrically necessary dislocations area is ignored. \n\nFor conventional homogeneous metals, Equation (1) has been used to reasonably explain their mechanical behaviors, because the back-stress caused by the geometrically necessary dislocations is relatively small. However, for heterogeneous materials, the back-stress can be much higher than the strengthening associated with the statistically stored dislocations [33,48], and therefore has to be considered. As discussed later, the back-stress can be utilized to design heterogeneous materials with unprecedented mechanical properties. \n\nWhat is the physical origin of back-stress? To answer this question, let us have a look at the piling-up of geometric dislocations as schematically shown in Figure 3(A). Assume that there is a dislocation source at point $X_{i}$ , which emits geometrically necessary dislocations with the same Burgers vector toward the domain boundary on a slip plane. Under an applied shear stress $\\tau_{a}$ , there are seven dislocations piled up and the system reached equilibrium. These dislocations collectively produce a long-range stress, $\\tau_{b}$ , toward the dislocation source as indicated by the arrow, which counterbalances the applied stress. The effective stress at the dislocation source can be expressed as $\\tau_{e}=\\tau_{a}-\\tau_{b}$ . If the critical stress to operate the dislocation source is $\\boldsymbol{\\tau}_{c}$ , then $\\tau_{e}$ has to be higher than $\\boldsymbol{\\tau}_{c}$ for the dislocation source to emit more dislocations. In other words, higher applied stress is needed for more dislocations to be piled up. Therefore, back-stress is a long-range stress created by geometrically necessary dislocations. The above discussion describes how back-stress can be produced from an individual dislocation pile. The experimentally measured back-stress is the global collective back-stress in the whole sample, just like the measured yield stress is a global stress contributed by individual yielding events in the whole sample. \n\n![](images/d113c216a0ae952f04d57b286e9d7d3888d479c79b2e7f18413311c7208672a5.jpg) \nFigure 3. (A) Schematics of the piling-up of geometrically necessary dislocations. (B) Plastic strain and strain gradient as a function of distance from the domain interface. (C) The effective stress $\\mathbf{\\sigma}=\\mathbf{\\sigma}$ applied stress back-stress) as a function of distance from the domain interface. \n\nBack-stress is connected with plastic strain gradient. The plastic strain is produced by the slip of dislocations, with each dislocation leaving a displacement of one Burgers vector in its wake. Therefore, in Figure 3(A) the strain is zero at the domain interface (pile-up head), and the strain is increased to seven Burges vector at the dislocation source. The black curve in Figure 3(B) shows a smoothed strain curve as a function of distance from the interface, the other curve in Figure 3(B) is the corresponding strain gradient curve. Therefore, the pile-up of geometrically necessary dislocations produces strain gradient as well as stress gradient (Figure 3(C)). In other words, if strain gradient is observed, there will exist the pile-up of geometrically necessary dislocations and corresponding back-stress. \n\nNote that another scenario to produce an array of geometrically necessary dislocations and the associated back-stress is when dislocations are emitted from a ledge on the domain boundary and/or grain boundary, but they form an array on a slip plane near the boundary [57]. This will produce the same back-stress to counterbalance the stress at the dislocation source, although the strain gradient will be different from what is described in Figure 3(B). \n\nThe highest plastic strain always occurs at the dislocation source. \n\nBack-stress has the same physical origin as the Bauschinger effect [58]. The larger Bauschinger effect corresponds to the higher back-stress. However, backstress can be used to improve the strength and ductility of metals if appropriate heterogeneous structures can be designed, instead of just a phenomenon of mechanical behavior as the Bauschinger effect is often regarded. The back-stress and its evolution during a tensile test can be measured experimentally [33,48]. \n\n# Microstructural requirement for the optimum mechanical properties \n\nAfter discussing the role of back-stress in the mechanical behavior and the physical origin of back-stress, it naturally follows that we can design heterogeneous structures to maximize back-stress for the best mechanical properties. Since back-stress is produced by dislocation pile-up at domain boundaries, we should design the heterogeneous structure with high density of domain interfaces. However, the spacing between the domain interfaces should be large enough to allow an effective dislocation pile-up in at least the soft domains and ideally in both soft and hard domains. Another design factor is to maximize strain partitioning among heterogeneous domains, which will consequently increase the strain gradient, which will consequently increase back-stress work hardening. This means that the strength between the domains should be large, and the domain geometries should be such that large strain partitioning can be easily realized. \n\nWith the above two criteria for high back-stress, we can make comments on the effectiveness of various heterogeneous structures. For the gradient structure [27–32], there will be two dynamically migrating interfaces during the tensile tests [28,29], which allows dislocation density accumulation over the whole sample volume. However, the low interface density also limits its capability of back-stress work hardening. For a bimodal structure [10,25,34,35], the interface density is usually not maximized, which did not make the full use of the back-stress hardening potential. For a laminate structure [39,40], the soft and hard laminates are subjected to the same applied strain, which limits their strain portioning capability and consequently back-stress development. For dual-phase steel [41–43], the hard martensitic domains typically account for $5\\text{\\textperthousand}$ by volume and are embedded in the soft matrix. Although this allows significant strain portioning to increase the back-stress work hardening and consequently high ductility, the continuous soft matrix also allows the material to yield at low stress, which is why dual-phase materials typically have very high ductility, but limited enhancement in strength. For a harmonic structure [36–38], the soft domains are totally surrounded by hard domain layers similar to a cellular structure. It has been observed to enhance the ductility, but the strength improvement is so far limited, which could be improved by reducing the domain interface spacing and hard domain volume fraction to further constrain the soft domains. For the heterogeneous lamella structure [33], the soft lamella domains with a volume fraction of $<30\\%$ are embedded in a hard matrix (Figure 4), which renders it high strength because the rigid constraint by the hard matrix makes the soft domains almost as strong as the hard matrix during the deformation stage II (see Figure 1). The strong strain partitioning during deformation stage III also renders unprecedented high strain hardening, which increases its ductility. Therefore, the heterogeneous lamella structure [33] presents a near-ideal heterogeneous structure. This explains why the heterogeneous lamella structure has shown the most dramatic improvement in strength and ductility among all reported types of heterogeneous materials. \n\n![](images/0a452dad1e52be54e14c407ca30e009df47cd66b166836097d8fec8a71899a79.jpg) \nFigure 4. Schematics of lamella structure with elongated soft coarse-grained domains embedded in an ultrafine-grained matrix. \n\n# Future perspective \n\nHeterogeneous materials is a fast emerging field that is to become a hot research field in the post-nanostructured materials era. There is a huge research community in the area of nanostructured materials, which has been extensively studied for over three decades. The maturing of this field and the challenge to the practical applications of nanostructured materials have made it hard to secure research funding in many countries in the world. Heterogeneous materials have many similarities to nanostructured materials because the hard domains could be nanostructured/ultrafine grained, which makes it easy for researchers in the nanostructured materials community to transit to the heterogeneous materials field. In addition, several types of heterogeneous materials can be produced by the current industrial processing technology so that their practical applications have a very low barrier. \n\nThere are many scientific and engineering issues that need to be addressed by both experimentalists and modelers from the communities of both materials science and mechanics. The heterogeneous materials community is quickly growing, with more international conferences and workshops being organized, for example, the biannual the minerals, metals & materials society symposium on heterogeneous and gradient materials. Sessions on heterogeneous materials are also inserted into conventional successful symposia such as the TMS biannual meeting on ultrafine-grained materials. These activities help with the fast development in the area of heterogeneous materials. \n\n# Disclosure statement \n\nNo potential conflict of interest was reported by the authors. \n\n# Funding \n\nX.W. was supported by the National Natural Science Foundation of China (NSFC) [grant number 11572328] and the Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDB22040503]. Y.Z. was supported by the US Army Research Office [grant number W911 NF-12- 1-0009], and the Jiangsu Key Laboratory of Advanced Micro & Nano Materials and Technology. \n\n# References \n\n[1] Valiev RZ, Alexandrov IV, Zhu YT, et al. Paradox of strength and ductility in metals processed by severe plastic deformation. J Mater Res. 2002;17:5–8. \n[2] Zhu YT, Liao XZ. Nanostructured metals – retaining ductility. Nature Mater. 2004;3:351–352. \n[3] Jia D, Wang YM, Ramesh KT, et al. Deformation behavior and plastic instabilities of ultrafine-grained titanium. Appl Phys Lett. 2001;79:611–613. \n[4] Zhao YH, Liao XZ, Horita Z, et al. Determining the optimal stacking fault energy for achieving high ductility in ultrafine-grained Cu-Zn alloys. Mater Sci Eng A. 2008;493:123–129. \n[5] Zhao YH, Bingert JF, Zhu YT, et al. Tougher ultrafine grain Cu via high-angle grain boundaries and low dislocation density. Appl Phys Lett. 2008;92:081903. \n[6] Zhao YH, Zhu YT, Liao XZ, et al. Tailoring stacking fault energy for high ductility and high strength in ultrafine grained Cu and its alloy. Appl Phys Lett. 2006;89:121906. \n[7] Wang YM, Ma E, Valiev RZ, et al. Tough nanostructured metals at cryogenic temperatures. Adv Mater. 2004;16:328–331. [8] Zhao YH, Bingert JE, Liao XZ, et al. Simultaneously increasing the ductility and strength of ultra-fine-grained pure copper. Adv Mater. 2006;18:2949–2952. \n[9] Zhao YH, Liao XZ, Cheng S, et al. Simultaneously increasing the ductility and strength of nanostructured alloys. Adv Mater. 2006;18:2280–2283. \n[10] Zhao YH, Topping T, Bingert JF, et al. High tensile ductility and strength in bulk nanostructured nickel. Adv Mater. 2008;20:3028–3033. \n[11] Cheng S, Zhao YH, Zhu YT, et al. Optimizing the strength and ductility of fine structured 2024 Al alloy by nanoprecipitation. Acta Mater. 2007;55:5822–5832. \n[12] Estrin Y, Vinogradov A. Extreme grain refinement by severe plastic deformation: A wealth of challenging science. Acta Mater. 2013;61:782–817. \n[13] Meyers MA, Mishra A, Benson DJ. Mechanical properties of nanocrystalline materials. Prog Mater Sci. 2006;51:427–556. \n[14] Lu L, Zhu T, Shen YF, et al. Stress relaxation and the structure size-dependence of plastic deformation in nanotwinned copper. Acta Mater. 2009;57:5165–5173. \n[15] Wang YM, Ma E. Three strategies to achieve uniform tensile deformation in a nanostructured metal. Acta Mater. 2004;52:1699–1709. \n[16] Yan FK, Liu GZ, Tao NR, et al. Strength and ductility of 316L austenitic stainless steel strengthened by nano-scale twin bundles. Acta Mater. 2012;60:1059–1071. \n[17] Youssef K, Sakaliyska M, Bahmanpour H, et al. Effect of stacking fault energy on mechanical behavior of bulk nanocrystalline Cu and Cu alloys. Acta Mater. 2011;59:5758–5764. \n[18] An XH, Han WZ, Huang CX, et al. High strength and utilizable ductility of bulk ultrafine-grained Cu-Al alloys. Appl Phys Lett. 2008;92:201915. \n[19] Zhang X, Wang H, Scattergood RO, et al. Tensile elongation $(110\\%)$ observed in ultrafine-grained Zn at room temperature. Appl Phys Lett. 2002;81:823–825. \n[20] Huang XX, Kamikawa N, Hansen N. Increasing the ductility of nanostructured Al and Fe by deformation. Mater Sci Eng A. 2008;493:184–189. \n[21] Wang GY, Li GY, Zhao L, et al. The origin of the ultrahigh strength and good ductility in nanotwinned copper. Mater Sci Eng A. 2010;527:4270–4274. \n[22] Lu L, Shen YF, Chen XH, et al. Ultrahigh strength and high electrical conductivity in copper. Science. 2004;304:422–426. \n[23] An XH, Wu SD, Zhang ZF, et al. Enhanced strengthductility synergy in nanostructured Cu and Cu-Al alloys processed by high-pressure torsion and subsequent annealing. Scr Mater. 2012;66:227–230. \n[24] Xiao GH, Tao NR, Lu K. Strength-ductility combination of nanostructured Cu-Zn alloy with nanotwin bundles. Scr Mater. 2011;65:119–122. \n[25] Wang YM, Chen MW, Zhou FH, et al. High tensile ductility in a nanostructured metal. Nature. 2002;419: 912–915. \n[26] Zhu YT, Lowe TC, Langdon TG. Performance and applications of nanostructured materials produced by severe plastic deformation. Scripta Mater. 2004;51: 825–830. \n[27] Lu K. Making strong nanomaterials ductile with gradients. Science. 2014;345:1455–1456. \n[28] Wu XL, Jiang P, Chen L, et al. Extraordinary strain hardening by gradient structure. Proc Natl Acad Sci USA. 2014;111:7197–7201. \n[29] Wu XL, Jiang P, Chen L, et al. Synergetic strengthening by gradient structure. Mater Res Lett. 2014;2:185–191. \n[30] Fang TH, Li WL, Tao NR, et al. Revealing extraordinary intrinsic tensile plasticity in gradient nano-grained copper. Science. 2011;331:1587–1590. \n[31] Chen AY, Liu JB, Wang HT, et al. Gradient twinned 304 stainless steels for high strength and high ductility. Mater Sci Eng A. 2016;667:179–188. \n[32] Wei YJ, Li YQ, Zhu LC, et al. Evading the strength- ductility trade-off dilemma in steel through gradient hierarchical nanotwins. Nat Commun. 2014;5:3580. \n[33] Wu XL, Yang MX, Yuan FP, et al. Heterogeneous lamella structure unites ultrafine-grain strength with coarsegrain ductility. Proc Natl Acad Sci USA. 2015;112:14501– 14505. \n[34] Han BQ, Huang JY, Zhu YT, et al. Strain rate dependence of properties of cryomilled bimodal 5083 Al alloys. Acta Mater. 2006;54:3015–3024. \n[35] Han BQ, Lee Z, Witkin D, et al. Deformation behavior of bimodal nanostructured 5083 Al alloys. Metall Mater Trans A. 2005;36:957–965. \n[36] Sawangrat C, Kato S, Orlov D, et al. Harmonic-structured copper: performance and proof of fabrication concept based on severe plastic deformation of powders. J Mater Sci. 2014;49:6579–6585. \n[37] Zhang Z, Vajpai SK, Orlov D, et al. Improvement of mechanical properties in SUS304L steel through the control of bimodal microstructure characteristics. Mater Sci Eng. 2014;598:106–113. \n[38] Vajpai SK, Ota M, Watanabe T, et al. The development of high performance Ti-6Al-4V alloy via a unique microstructural design with bimodal grain size distribution. Metall Mater Trans A. 2015;46:903–914. \n[39] Ma XL, Huang CX, Moering J, et al. Mechanical properties in copper/bronze laminates: role of interfaces. Acta Mater. 2016;116:43–52. \n[40] Beyerlein IJ, Mayeur JR, Zheng SJ, et al. Emergence of stable interfaces under extreme plastic deformation. Proc Natl Acad Sci USA. 2014;111:4386–4390. \n[41] Calcagnotto M, Adachi Y, Ponge D, et al. Deformation and fracture mechanisms in fine- and ultrafine-grained ferrite/martensite dual-phase steels and the effect of aging. Acta Mater. 2011;59:658–670. \n[42] Li ZM, Pradeep KG, Deng Y, et al. Metastable highentropy dual-phase alloys overcome the strength-ductility trade-off. Nature. 2016;534:227–231. \n[43] Park K, Nishiyama M, Nakada N, et al. Effect of the martensite distribution on the strain hardening and ductile fracture behaviors in dual-phase steel. Mater Sci Eng. 2014;604:135–141. \n[44] Wu XL, Yuan FP, Yang MX, et al. Nanodomained nickel unite nanocrystal strength with coarse-grain ductility. Sci Rep. 2015;5:11728. \n[45] Lu K, Yan FK, Wang HT, et al. Strengthening austenitic steels by using nanotwinned austenitic grains. Scr Mater. 2012;66:878–883. \n[46] Li YS, Tao NR, Lu K. Microstructural evolution and nanostructure formation in copper during dynamic plastic deformation at cryogenic temperatures. Acta Mater. 2008;56:230–241. \n[47] Ma E, Zhu T. Towards strength–ductility synergy through the design of heterogeneous nanostructures in metals. Mater Today. 2017; doi:10.1016/ j.mattod.2017.02.003 \n[48] Yang MX, Pan Y, Yuan FP, et al. Back stress strengthening and strain hardening in gradient structure. Mater Res Lett. 2016;4:145–151. \n[49] Cong ZH, Jia N, Sun X, et al. Stress and strain partitioning of ferrite and martensite during deformation. Metall Mater Trans A. 2009;40:1383–1387. \n[50] Tasan CC, Diehl M, Yan D, et al. Integrated experimentalsimulation analysis of stress and strain partitioning in multiphase alloys. Acta Mater. 2014;81:386–400. \n[51] Han QH, Asgari A, Hodgson PD, et al. Strain partitioning in dual-phase steels containing tempered martensite. Mater Sci Eng. 2014;611:90–99. \n[52] Wang MM, Tasan CC, Ponge D, et al. Nanolaminate transformation- induced plasticity-twinning-induced plasticity steel with dynamic strain partitioning and enhanced damage resistance. Acta Mater. 2015;85:216–228. \n[53] Yang MX, Yuan FP, Xie QG, et al. Strain hardening in Fe16Mn-10Al-0.86C-5Ni high specific strength steel. Acta Mater. 2016;109:213–222. \n[54] Gao H, Huang Y, Nix WD, et al. Mechanism-based strain gradient plasticity – I. Theory. J Mech Phys Solids. 1999;47:1239–1263. \n[55] Gao HJ, Huang YG. Geometrically necessary dislocation and size-dependent plasticity. Scr Mater. 2003;48:113–118. \n[56] Ashby MF. Deformation of plastically non-homogeneous materials. Philos Mag. 1970;21:399–424. \n[57] Murr LE. Dislocation ledge sources: dispelling the myth of frank-read source importance. Metall Mater Trans A. 2016;47:5811–5826. \n[58] Kato H, Moat R, Mori T, et al. Back stress work hardening confirmed by Bauschinger effect in a TRIP steel using bending tests. ISIJ Int. 2014;54:1715–1718. " + }, + { + "id": "10.1002_adma.201702678", + "DOI": "10.1002/adma.201702678", + "DOI Link": "http://dx.doi.org/10.1002/adma.201702678", + "Relative Dir Path": "mds/10.1002_adma.201702678", + "Article Title": "Transparent, Flexible, and Conductive 2D Titanium Carbide (MXene) Films with High Volumetric Capacitance", + "Authors": "Zhang, CF; Anasori, B; Seral-Ascaso, A; Park, SH; McEvoy, N; Shmeliov, A; Duesberg, GS; Coleman, JN; Gogotsi, Y; Nicolosi, V", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "2D transition-metal carbides and nitrides, known as MXenes, have displayed promising properties in numerous applications, such as energy storage, electromagnetic interference shielding, and catalysis. Titanium carbide MXene (Ti3C2Tx), in particular, has shown significant energy-storage capability. However, previously, only micrometer-thick, nontransparent films were studied. Here, highly transparent and conductive Ti3C2Tx films and their application as transparent, solid-state supercapacitors are reported. Transparent films are fabricated via spin-casting of Ti3C2Tx nullosheet colloidal solutions, followed by vacuum annealing at 200 degrees C. Films with transmittance of 93% (approximate to 4 nm) and 29% (approximate to 88 nm) demonstrate DC conductivity of approximate to 5736 and approximate to 9880 S cm(-1), respectively. Such highly transparent, conductive Ti3C2Tx films display impressive volumetric capacitance (676 F cm(-3)) combined with fast response. Transparent solid-state, asymmetric supercapacitors (72% transmittance) based on Ti3C2Tx and single-walled carbon nullotube (SWCNT) films are also fabricated. These electrodes exhibit high capacitance (1.6 mF cm(-2)) and energy density (0.05 mu W h cm(-2)), and long lifetime (no capacitance decay over 20 000 cycles), exceeding that of graphene or SWCNT-based transparent supercapacitor devices. Collectively, the Ti3C2Tx films are among the state-of-the-art for future transparent, conductive, capacitive electrodes, and translate into technologically viable devices for next-generation wearable, portable electronics.", + "Times Cited, WoS Core": 943, + "Times Cited, All Databases": 984, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000411379000027", + "Markdown": "# Transparent, Flexible, and Conductive 2D Titanium Carbide (MXene) Films with High Volumetric Capacitance \n\nChuanfang (John) Zhang, Babak Anasori, Andrés Seral-Ascaso, Sang-Hoon Park, Niall McEvoy, Aleksey Shmeliov, Georg S. Duesberg, Jonathan N. Coleman,\\* Yury Gogotsi,\\* and Valeria Nicolosi\\* \n\n2D transition-metal carbides and nitrides, known as MXenes, have displayed promising properties in numerous applications, such as energy storage, electromagnetic interference shielding, and catalysis. Titanium carbide MXene $(\\bar{\\Gamma}\\mathrm{i}_{3}\\bar{\\mathsf C}_{2}\\bar{\\Gamma}_{x})$ , in particular, has shown significant energy-storage capability. However, previously, only micrometer-thick, nontransparent films were studied. Here, highly transparent and conductive $\\bar{\\Pi}_{1_{3}}\\mathsf C_{2}\\bar{\\Pi}_{x}$ films and their application as transparent, solid-state supercapacitors are reported. Transparent films are fabricated via spin-casting of $\\bar{\\Gamma}\\dot{\\mathbf{i}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{x}$ nanosheet colloidal solutions, followed by vacuum annealing at $200^{\\circ}C$ . Films with transmittance of $93\\%1{\\approx}4~\\mathsf{n m})$ and $29\\%$ $(\\approx88~\\mathsf{n m})$ ) demonstrate DC conductivity of $\\approx5736$ and ${\\approx}9880~\\mathsf{S}~{\\mathsf{c m}}^{-1}$ , respectively. Such highly transparent, conductive $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\bar{\\mathsf{T}}_{x}$ films display impressive volumetric capacitance $(676\\mathsf{F}\\mathsf{c m}^{-3})$ combined with fast response. Transparent solid-state, asymmetric supercapacitors ( $72\\%$ transmittance) based on $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\bar{\\mathsf{T}}_{x}$ and single-walled carbon nanotube (SWCNT) films are also fabricated. These electrodes exhibit high capacitance $(7.6~m\\mathsf{F}~\\mathsf{c m}^{-2})$ and energy density $(0.05\\upmu\\mathrm{w}\\mathsf{h}\\mathsf{c m}^{-2})$ , and long lifetime (no capacitance decay over 20 000 cycles), exceeding that of graphene or SWCNT-based transparent supercapacitor devices. Collectively, the $\\bar{\\Gamma}\\dot{\\mathsf{I}}_{3}\\mathsf{C}_{2}\\bar{\\Gamma}_{x}$ films are among the state-of-the-art for future transparent, conductive, capacitive electrodes, and translate into technologically viable devices for next-generation wearable, portable electronics. \n\nA future trend in consumer electronics will be the shift toward optically transparent devices. $[1-5]$ To achieve this, potential primary power sources need to be transparent and resilient, with high capacity as well as long lifetime.[6] Supercapacitors are capable of providing high capacitance, long lifetime, and a fast charge–discharge rate, and thus are ideal for future portable electronics.[7,8] The charge storage mechanisms of supercapacitors rely either on electrosorption of ions at the electrode/electrolyte interface (termed as electrical double layer capacitance) or fast redox reactions occurring on (or near) electrode surfaces (termed as pseudocapacitance).[9–14] The key to transparent, flexible supercapacitors lies in the design of the electrodes. According to the guiding principles that we proposed recently on transparent capacitive electrodes (TCE),[6,15,16] their optoelectronic properties and electrochemical performances could be quantitatively evaluated through two simple figures of merit $(\\mathrm{FoM_{e}}$ and $\\mathrm{FoM_{c})}$ . The former, $\\mathrm{FoM_{e}}$ described as the ratio of DC conductivity to optical conductivity $(\\sigma_{\\mathrm{DC}}/\\sigma_{\\mathrm{op}})$ , specifies the optoelectronic properties, while the latter, $\\mathrm{FoM}_{\\mathrm{c}},$ determined by the ratio of volumetric capacitance to optical conductivity $(C_{\\mathrm{V}}/\\upsigma_{\\mathrm{op}})$ , quantifies the charge storage performance. In order to engineer a transparent supercapacitor with excellent power density and volumetric capacitance, both of the FoMs need to be maximized for a given material. \n\nTo this end, substantial research efforts have been focused on developing TCEs with high transmittance $(T)$ at a low sheet resistance $\\left(\\ensuremath{R_{\\mathrm{s}}}\\right).^{[17-20]}$ As such, the $\\sigma_{\\mathrm{DC}}/\\sigma_{\\mathrm{op}}$ $\\mathrm{(FoM_{e})}$ , given by Equation (1), is maximized: \n\n$$\nT=\\left(1+\\frac{188.5}{R_{\\mathrm{s}}}\\frac{\\sigma_{\\mathrm{op}}}{\\sigma_{\\mathrm{DC}}}\\right)^{2}\n$$ \n\nIn many industrial applications, a potential TCE with $T>90\\%$ and $R_{\\mathrm{s}}~<~100~\\Omega~\\mathrm{sq}^{-1}$ is required, leading to a mini­mum $\\mathrm{FoM_{e}}$ of 35. Despite indium tin oxide (ITO) possessing a $\\mathrm{FoM_{e}}$ as high as 220 $\\left(R_{\\mathrm{s}}<10\\Omega\\ \\mathrm{sq}^{-1}\\right.$ , while $T>85\\%)$ ),[15] its intrinsic brittleness coupled with costs and high-temperature processing render ITO unlikely to be the material of choice for future transparent energy-storage devices. Said otherwise, in the frame of scalable application of transparent, flexible supercapacitors, TCE should be simultaneously capable of storing charge and transporting current efficiently, even in a distorted configuration. Although flexible thin films made of metal or metal nanowires (i.e., silver) demonstrated a $\\mathrm{FoM_{e}}$ of up to 500,[15] their poor capacitive performances resulted in low $C_{\\mathrm{v}}$ (low $\\mathrm{FoM_{c}}$ ). On the other hand, while thin films made of single-walled carbon nanotubes (SWCNTs), chemically modified graphene, conducting polymers or their composites, etc., have shown either good $\\mathrm{FoM_{e}}$ or relatively high $C_{\\mathrm{v}}^{\\ [19,21-23]}$ few have shown high values of both FoMs, not to mention outstanding electrochemical performance in practical devices. \n\nRecently, a large class of 2D metal carbides and nitrides called MXenes have emerged. MXenes have the formula of $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x},$ , where $n=1$ , 2, or 3, M is an early transition metal, X is C and/ or N, and $\\mathrm{\\DeltaT}$ is a terminating group.[24–26] By selectively etching the A element (typically aluminum, Al, or gallium, Ga) from their ternary carbide precursors in a hydrofluoric acid (HF)- containing aqueous medium, multilayered (m-) MXenes terminated with oxygen $_{(-\\mathrm{O})}$ , hydroxyl $(\\mathrm{-OH})$ , and/or fluoride $(-\\mathrm{F})$ groups are obtained.[27,28] Upon solvent intercalation and shaking or sonication, the m-MXene can be delaminated (d-) into predominantly single nanosheets, forming a colloidal d-MXene solution.[29–31] Among $>20$ MXenes that have already been discovered, titanium carbide $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x})$ is the most widely studied, with numerous applications such as supercapacitors,[26] Li-ion batteries,[32] electromagnetic-interference shielding,[33] and water desalination,[34,35] already reported. Sonicated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes have also been employed for fabrication of TCEs,[36–38] showing a low $\\mathrm{FoM_{e}}$ . \n\nconductivity behavior and free from notorious percolation problems. Consequently, the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films function efficiently as both a transparent conductor and an active material for capacitive energy storage, showcasing excellent optoelectronic properties and impressive volumetric capacitance, respectively. The devices, symmetric or asymmetric, were assembled through a facile sandwiching process (Scheme 1), and demonstrated long lifetime, high transparency, high energy, power density, etc., which are superior to all other reported transparent supercapacitor devices. \n\n$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene has shown remarkable electronic conductivity and electrochemical performances,[36,39] and thus is ideal for fabricating powerful transparent supercapacitors. We synthesized $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ by selective etching of its precursor as described in the supporting information (Figure S1, Supporting Information) and delaminated the etched powder to form a colloidal solution of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes via the mild exfoliation route[26,40] (manual shaking) of the filtrated cake in deionized water (Video S1 in the Supporting Information). The resulting colloidal solution contained $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ single sheets with a lateral size of a few micrometers (Figure 1a). The lattice symmetry of the flake in the selected area electron diffraction (SAED, Figure S2a, Supporting Information) is in good agreement with previous reports on MXene structure.[40] No Al was detected in the energy-dispersive (EDX) spectrum (Figure S2b, Supporting Information). Scanning electron microscopy (SEM) images along with the associated size histogram (Figure 1b; and Figure S2c,d, Supporting Information) indicate a mean lateral length $()$ of $3.2~{\\upmu\\mathrm{m}}$ and lateral width $()$ of $2.1\\ \\upmu\\mathrm{m}$ for the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes. The thickness of the flakes is around $1.5\\mathrm{nm}$ , according to the atomic force microscopy (AFM) measurement in Figure S3 (Supporting Information), in good agreement with the previous report.[40] \n\nUpon spin-casting the colloidal solution, followed by annealing at $200~^{\\circ}\\mathrm{C}$ under vacuum, transparent, conductive \n\nHere, we report on advanced $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ TCEs and the corresponding state-of-the-art solid-state supercapacitor devices. Through spin-casting of colloidal solutions of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets, followed by vacuum annealing at $200^{\\circ}\\mathrm{C},$ highly ordered, continuous films were obtained which are made of large $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes aligned parallel to the substrate. Such an architecture ensures the formation of a conductive network, demonstrating bulk-like $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films were produced, as shown in Figure S4a (Supporting Information). We controlled the thickness and therefore the transmittance of the films by adjusting the volume cast onto glass or poly(ethylene terephthalate) (PET) substrates and/or the spinning speeds (Figure S4b–f, Supporting Information). We selected a $T=91\\%$ film as typical sample and reported their morphological and structural characterizations. The top-view and cross-sectional SEM images in Figure 1c,d collectively demonstrate a continuous coverage of the substrate without protruding corners of flakes, indicating the orientation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes parallel to the substrate. This was confirmed by AFM and X-ray diffraction (XRD). As shown in Figure 1e, the flakes are compactly packed, and the height variations are within nanometers (Figure 1f). The XRD pattern of the $T=91\\%$ film in Figure S5 (Supporting Information) shows a high intensity for the (002) peak, suggesting the flakes align parallel to the substrate under the effect of the shear force.[36] A Raman spectrum of a typical sample is shown in Figure S6 (Supporting Information), revealing characteristic peaks typical of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ .[41] \n\n![](images/df9d9658de07879c3a15d98aa6dc4ce5feaca6f4dee39f1f39310a0586482d3b.jpg) \nScheme 1.  Schematic demonstration of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ MXene-based transparent, flexible solid-state supercapacitor fabrication. $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ MXene film was made by spin-casting of MXene colloidal solution on a PET substrate (top left scheme). Silver paint was coated onto one of the edges of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ film, followed by the coating of nail polish and gel electrolyte (top middle scheme). The nail polish was used to prevent the contamination of silver connection from the gel. The films were then sandwiched into supercapacitors (top right scheme) and naturally dried before tests. Symmetric supercapacitors were constructed by sandwiching two gel electrolyte-covered $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films, as shown in the bottom right scheme. For the asymmetric supercapacitors, a film of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ was sandwiched with a SWCNT film. \n\n![](images/7d3f47b053af655c7e5fc9cf9bab0281cc90cbd064cbb15d9995104da8628d87.jpg) \nFigure 1.  Characterization of the delaminated $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ flakes and $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films $(T=97\\%)$ . a,b) Annular dark field scanning transmission electron micro scopy (ADF STEM) image (a) and flake size histogram (b) of $\\mathrm{Ti}_{3}C_{2}\\mathsf{T}_{x}$ MXene nanosheets. The mean lateral length, $$ , was obtained by averaging the lateral dimensions of $N$ nanosheets. c,d) Top-view (c) and cross-sectional (d) SEM images of spun-cast $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ film. e) AFM image of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ film. f) Height profiles of the different lines marked on (e). \n\nWe then studied the optoelectronic properties of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films. The transmittance spectra of various films are relatively featureless (Figure 2a), showing a broad peak in the visible region as the films become thicker. The film thickness was estimated as described below and is shown in Figure $\\mathrm{{S7a}}$ (Supporting Information). We plotted the transmittance $(T)$ at $550~\\mathrm{nm}$ as a function of $R_{\\mathrm{s}}$ and compared our $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ to other transparent thin films, as shown in Figure 2b. At $T=95\\%$ , the $R_{\\mathrm{s}}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ reaches $1032~\\Omega~\\mathrm{sq}^{-1}$ . While this value is higher than that of the previously reported poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) films $(256~\\Omega~\\mathrm{~sq}^{-1})$ ,[16] it is substantially lower than some other TCEs in a similar transmittance region, as seen in Figure 2b. The high $T$ coupled with low $R_{\\mathrm{s}}$ gives $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ excellent optoelectronic properties compared to most other transparent, conductive thin films. For example, at $T=87\\%$ , the sheet resistance of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ $(201\\Omega\\mathrm{sq}^{-1})$ is much lower than that of PEDOT/SWCNT $(861~\\Omega~\\mathrm{sq}^{-1})^{[21]}$ or P3-SWCNT $(3814~\\Omega~\\mathrm{{sq}^{-1})}$ .[18] Graphene, in comparison with MXene, in either its chemically modified or pristine state, exhibits substantially inferior optoelectronic properties to that of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ in this work. For instance, the $R_{\\mathrm{s}}$ reached $10492{\\Omega}\\mathrm{sq}^{-1}$ in chemically modified graphene oxide films at $T=80\\%$ ,[42] and as high as $2.7\\times10^{5}~\\Omega~\\mathrm{sq}^{-1}$ in liquid-exfoliated graphene flakes at $T=92\\%$ .[43] To obtain the $\\mathrm{FoM_{e}}$ for all the studied thin films, we fitted the data in Figure 2b using Equation (1). For other films, such as nanotubes,[18] nanowires,[15] and graphene nanosheets,[43] the measured values deviate apparently from the fitted curve in the high-transparency region, indicative of percolation effects. For potential incorporation into transparent electronics, percolation behavior is undesirable and should be avoided.[18] Interestingly, the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films follow bulk-like behavior (the fitted line) quite well, relatively independent of the film thickness. By plotting the $T^{-0.5}-1$ as a function of $R_{\\mathrm{s}}$ we are able to verify that the bulk-like conductivity behavior applies to the material in the whole range of transmittance. As shown in Figure 2c, all measured data points are roughly on the fitted bulk-type DC conductivity curve.[16] We note such a bulk-like behavior is of significance and clearly distinguishes our results from the above-mentioned thin films, as well as previously reported $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films, which demonstrated apparent percolation in the films with $T>90\\%$ [36,38] In other words, the technologically viable devices based on our $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ thin films would operate in the bulk-like regime, in which the DC conductivity is roughly independent of $T$ \n\n![](images/56f63abfe11a330a7de614344ea63edb03dba09210c12b2476edd914728df1d1.jpg) \nFigure 2.  Optoelectronic properties of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films. a) Transmittance spectra of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films with various transmittance values. b) $\\tau$ plotted as a function of $R_{\\mathrm{s}}$ for the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films and comparison to the literature. The dashed lines are obtained by fitting the points using Equation (1). Detailed information is presented in Table S1 (Supporting Information). c) $T^{-0.5}-1$ plotted as a function of $R_{\\mathrm{s}}$ for $\\mathsf{H}-\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films to verify the fitting model. d) $T^{-0.5}-1$ plotted as a function of thickness for the films thicker than $20\\ \\mathsf{n m}$ to obtain the optical conductivity $(\\sigma_{\\circ\\mathsf{p}})$ of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ . The dashed line is obtained by fitting the points using Equation (2). e) $R_{\\mathfrak{s}}$ plotted as a function of thickness for $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films with various $\\tau$ . The dashed line is a description of $R_{\\mathrm{s}}=1/\\sigma_{\\mathrm{DC}}t.$ f) Comparison of $\\sigma_{\\mathrm{DC}}/\\sigma_{\\circ\\mathsf{p}}$ in $\\mathrm{Ti}_{3}C_{2}\\mathsf{T}_{x}$ films to various other TCEs, the bars are color coded based on the values presented in Table S2 (Supporting Information). \n\nSince the thickness, $t_{\\mathrm{{i}}}$ of the highly transparent $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films $(T>90\\%)$ could not be accurately measured from contact profilometry, we used Equation (2) to predict the thickness of all the above-mentioned films, if the optical conductivity, $\\sigma_{\\mathrm{op}},$ is known:[16] \n\n$$\nT=\\left[1+188.5\\sigma_{\\mathrm{op}}t\\right]^{-2}\n$$ \n\nThe above equation can also be written as: \n\n$$\n(T^{-0.5}-1)=188.5\\sigma_{\\mathrm{op}}(t)\n$$ \n\nEquation (3) indicates that, when $\\mathbf{\\chi}_{t}$ is described as $T^{-0.5}–1$ , the data should vary linearly. Fitting the data should give the slope, which equals to $188.5\\sigma_{\\mathrm{op}}$ . Therefore, we additionally prepared a number of relatively opaque films on glass substrates and measured their $T$ and $\\mathbf{\\Phi}_{t,\\mathbf{\\Phi}}$ the latter was obtained by contact profilometry. As seen in Figure 2d, the thickness of these films ranges from 32 nm $(T=56\\%)$ to $155\\mathrm{nm}$ $(T=16\\%)$ . From the slope of the fitted line, we obtained the film’s $\\sigma_{\\mathrm{op}}$ to be $520\\pm40\\mathrm{S\\cm^{-1}}$ . Notably, this value is substantially higher than that of PEDOT:PSS $(24\\ \\mathrm{S\\cm^{-1}})^{[16]}$ and similar to the $\\sigma_{\\mathrm{op}}$ of graphene films $(420^{[43]}$ and $500~\\mathrm{{S}~c m^{-1[44]}}$ ). Using $\\sigma_{\\mathrm{op}}=520\\textup{S c m}^{-1}$ and Equation (2), the thickness of any $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ -based thin films could be calculated. Figure $\\mathtt{S7a}$ (Supporting Information) summarizes all the calculated thicknesses of the above-mentioned $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films, which were used for the rest of the study, unless specifically noted. \n\nShown in Figure 2e is the sheet resistance data plotted as a function of film thickness. In general, $R_{\\mathrm{s}}$ scales inversely with $t_{:}$ , a behavior which is usually seen in bulk material (illustrated by the dashed line).[15] Impressively, our $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films display a DC conductivity ranging from 3450 to $9880\\ \\mathrm{S\\cm^{-1}}$ (Figure S7b,c, Supporting Information) with almost no percolation problems. According to Dillon et al.,[36] the sheet conductance of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films decreased by three times upon transferring the films from a dry $\\mathrm{N}_{2}$ environment to humid air, due to water adsorption and intercalation between MXene sheets. Based on this, it is reasonable to anticipate that the intrinsic DC conductivity of our $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ thin films is higher than the measured and reported value, since we conducted all the tests in ambient conditions. The $\\mathrm{FoM_{e}}$ obtained through fitting the $T$ versus $R_{\\mathrm{s}}$ data in Figure 2b is 15. Apart from PEDOT:PSS[16] and silver nanowires,[15] which possess conductivity ratios of 39 and 500, respectively, the current $\\mathrm{FoM_{e}}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film (Table S2, Supporting Information) has surpassed all other graphene, SWCNT, or SWCNT/conductive polymer thin films,[18,19,42,45,46] as shown in Figure 2f. Sonicating the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ colloidal solution gives flakes with similar thickness single sheets (Figure S9, Supporting Information) but with much smaller lateral size $(<300\\ \\mathrm{nm}$ , Figure S8, Supporting Information), consequently, the $\\mathrm{FoM_{e}}$ is much lower (1.7) and of the same order of magnitude as previously reported $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films,[36] as seen in Figure S10 (Supporting Information). We also produced $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ colloidal solution (Figure S11, Supporting Information) and evaluated the $T-R_{\\mathrm{s}}$ properties of the corresponding transparent films (Figure \n\nS12, Supporting Information). The $\\mathrm{FoM_{e}}$ in these small-flakes $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ $\\mathrm{(S-Ti_{2}C T_{\\it x})}$ reaches 0.5 (Figure S10a, Supporting Information), a value comparable to the best transparent graphene films.[47] Direct comparison of these samples suggests that the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films produced through the manual shaking (no sonication) approach result in the best optoelectronic properties. Through optimizing the synthesis conditions and controlling the type/amount of surface functionalities, further improvement of DC conductivity is expected. Considering the route to film fabrication is facile, cost-effective, and scalable, it is reasonable to assume that the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films may indeed meet the requirement for future transparent conductors. \n\nNext we studied the electrochemical properties of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films with various transmittance (Figure S13, Supporting Information), which were fabricated on glass substrates, in a three-electrode setup. The cyclic voltammograms (CVs) of a $T=91\\%$ film at 20 and $200\\ \\mathrm{mV\\s^{-1}}$ in Figure S14a (Supporting Information) show a quasirectangular shape with a Coulombic efficiency of $100\\%$ , indicating that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films behave well as a supercapacitor material, similar to thick MXene “clay” electrodes.[48–50] The broad CV peak in the range $-0.15–0.2\\mathrm{~V~}$ (vs $\\mathrm{\\Ag/AgCl)}$ could be attributed to the valence change of $\\mathrm{Ti^{+}}$ induced by the reversibly bonding/debonding of hydronium to the O-groups terminated on the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ as previously monitored by in situ Raman spectroscopy[51] and X-ray adsorption spectroscopy.[52] Normalized CVs of different films are shown in Figure 3a; and Figure S14b–d, Supporting Information. For the $T=91\\%$ sample, the quasirectangular CV shape is maintained up to $500\\ \\mathrm{mV\\s^{-1}}$ (i.e., a charge–discharge time of 1.3 s), indicating high-rate electrochemical responses have been achieved in the transparent $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films. Figure 3b compares the normalized CV curves of various films at $\\bar{1}00\\mathrm{mVs^{-1}}$ . As the film becomes thicker, the enclosed area broadens, coupled with a more rapid response upon voltage reversal, best seen in the gradual shifting of the peak position to a more negative potential. The measured areal capacitances (referred to as $C/A_{,}^{\\prime}$ ) of various films at different scan rates are presented in Figure 3c. Also included are fittings of $C/A$ based on Equation (4):[6] \n\n$$\nC/A=C_{\\mathrm{A}}\\left[1-\\frac{\\upsilon\\tau}{\\Delta V}\\left(1-e^{-\\frac{\\Delta V}{\\upsilon\\tau}}\\right)\\right]\n$$ \n\nwhere $\\tau=R_{\\mathrm{ESR}}~C$ is the time constant, $\\Delta V$ is the voltage window (0.65 V), $\\nu$ is the sweep rate, and $C_{\\mathrm{A}}$ is the intrinsic areal capacitance, which is ideally achieved in the absence of electron transport or ion diffusion limitations across the transparent films.[16] The above model substantially simplifies the complex electrochemical behavior of the electrode and provides valuable insights into the overall behavior of the thin films.[6] The $T=98\\%$ exhibits $0.13~\\mathrm{mF~cm^{-2}}$ at $10\\ \\mathrm{mV\\s^{-1}}$ , a value close to PEDOT:PSS transparent films with a similar $T,$ however, it is substantially higher than that of transparent films made of graphene quantum-dots ( $T=93\\%$ , $9.1~\\upmu\\mathrm{F}~\\mathrm{cm}^{-2},$ ).[45] Increasing the film thickness to $60~\\mathrm{nm}$ $T=40\\%)$ results in much higher capacitances. For example, comparing to the $T=98\\%$ , the $C/A$ boosts by 26 and 150 times, reaching 3.4 and $3.0~\\mathrm{mF~cm^{-2}}$ in the $T=40\\%$ sample at 10 and $200\\ \\mathrm{\\mV\\s^{-1}}$ , respectively. The differences in the rate handling of these two films could be well attributed to the substantially higher sheet resistance $(1238~\\Omega~\\mathrm{sq}^{-1})$ in the former, in contrast to $22~\\Omega~\\mathrm{sq}^{-1}$ in the latter. The electrochemical impedance spectroscopy (EIS) spectra in Figure S15 (Supporting Information) also support that the $T=98\\%$ sample exhibited a much higher equivalent series resistance (ESR) than the rest of the films, leading to a lower $C_{\\mathrm{A}}$ (Figure 3c) and larger time constant (8 s) than other $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films $_{(\\approx0.6\\mathrm{~s})}$ , as shown in Figure 3d; and Figure S16 (Supporting Information). By correlating $R_{\\mathrm{s}}$ with the time constant for each film, it quickly becomes evident that the electronic transport across the transparent films largely controls the time constant of the films (inset of Figure 3d). Said otherwise, to ensure fast electrochemical responses in the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films without electrical percolation problems, $T=91\\%$ seems to be optimum, as it exhibits high areal capacitance of $0.48~\\mathrm{mF~cm}^{-2}$ and provides efficient pathways for electron transport, as demonstrated in Video S2 (Supporting Information). \n\n![](images/64270d7ac323300c39c12f0ac3cec1e9f9e74095d6563ed714daa5b4e3224761.jpg) \nFigure 3.  Electrochemical characterization of $\\mathrm{Ti}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films. a) Normalized CV curves of $T=97\\%$ film at various scan rates. b,c) CV curves at $\\mathsf{l o o m V s^{-1}}$ (b) and measured areal capacitance (c) of various $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films. The dashed lines are obtained by fitting the capacitance using Equation (4). d) Time constants, which were fitted from (c), of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ with various $\\tau$ values. Inset shows the time constants plotted as a function of $R_{\\mathrm{s}},$ demonstrating a linear relationship. e) $\\tau$ of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films plotted as a function of intrinsic capacitances $(C_{\\mathsf{A}})$ which are obtained in (c), and compared to other transparent film systems. The dashed lines are obtained by fitting the capacitance using Equation (5). Detailed values are presented in Table S3 (Supporting Information). f) Comparison of volumetric capacitance of $\\Gamma_{{\\sf I}_{3}}\\mathsf C_{2}\\mathsf T_{x},$ which is obtained from (d), to other transparent film systems, whose values can be found in Table S4 (Supporting Information). \n\nThe transmittances of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films were plotted as a function of $C_{\\mathrm{A}}$ and compared to other TCEs, as shown in Figure 3e; and Figure S17 (Supporting Information). At $T>90\\%$ , the region of interest for transparent devices, the $C_{\\mathrm{A}}$ displayed by our $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films are slightly lower than the values obtained for $\\mathrm{RuO}_{2}/\\mathrm{PEDOT}$ films,[6] but similar to PEDOT:PSS films,[16] and greatly exceed that of P3-SWCNT.[18] To quantify the capacitive charge storage ability of transparent films, we fitted the data in Figure 3e according to Equation (5): \n\n$$\nT=\\left(1+\\frac{188.5\\sigma_{\\mathrm{op}}}{C_{\\mathrm{v}}}C_{\\mathrm{A}}\\right)^{-2}\n$$ \n\nwhere, $C_{\\mathrm{V}}/\\sigma_{\\mathrm{op}}$ is $\\mathrm{FoM_{c}}$ , $C_{\\mathrm{V}}$ is volumetric capacitance $({\\mathrm{F}}{\\mathrm{cm}}^{-3})$ . A good fit of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films is revealed with a $\\mathrm{FoM_{c}}$ of $1.3\\mathrm{F}\\mathrm{S}\\mathrm{cm}^{-2}$ , a value between $0.3\\mathrm{~F~S~cm}^{-2}$ for P3-SWCNT and $1.9\\mathrm{~F~S~cm}^{-2}$ for PEDOT:PSS.[16,18] Assuming that the optical conductivity is constant for all the films studied, we thus obtained a volumetric capacitance of $676~\\mathrm{F~cm}^{-3}$ in the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ , which is substantially higher than other transparent thin films, as shown in Figure 3f. For instance, in a similar thickness region, values of only $30\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ for wrinkled graphene, $^{20]}\\approx50\\mathrm{~F~cm}^{-3}$ for PEDOT:PSS[16] or SWCNT,[18,53] $130~\\mathrm{~F~}\\mathrm{cm}^{-3}$ for $\\mathrm{MWCNT}^{\\{54\\}}$ and $160\\ \\mathrm{F\\cm^{-3}}$ for MWCNT/graphene composite films were achieved.[55] The excellent volumetric capacitance further verifies the high efficiency of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films in playing both the role of superior transparent conductor and high-performance supercapacitor electrode. \n\nTo explore the practical applications of the TCEs in portable, flexible energy-storage devices, we integrated the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films into transparent, flexible solid-state supercapacitors (Scheme 1). \n\nPhotographs of the film, as well as a transparent device in flat and bent states are shown in Figure 4a and Scheme 1, respectively. Figure S18 (Supporting Information) displays the transmittance spectra of a single electrode and the symmetric device, revealing a $T$ of about $80\\%$ in the latter, which is significantly higher than the transmittance of other reported supercapacitor devices based on cellulose nanofiber/rGO ( $(T=56\\%)$ ,[5] wrinkled graphene $(T=60\\%)$ ,[20] or graphene film $(T=69\\%)$ ,[56] etc. The normalized CV curves under different scan rates are presented in Figure 4b. The rapid current response upon voltage reversal, coupled with rectangular CV shapes up to $200\\mathrm{mVs^{-1}}$ indicate highly capacitive behavior and excellent power handling properties in the device. The symmetric sloping galvanostatic charge-discharge (GCD) curves in Figure 4c also support this point. The $C/A$ of the transparent solid-state supercapacitor were calculated from CVs and GCD profiles, and are presented in Figure 4d. The resultant $C/A$ values from the two approaches are comparable, exhibiting $0.86\\mathrm{~mF~cm^{-2}}$ at $2\\ \\upmu\\mathrm{A}\\ \\mathrm{cm}^{-2}$ and maintaining $94\\%$ of initial capacitance as the current density increased by 16 times, indicative of high-rate response. \n\nFigure 4e compares the $C/A$ of various transparent films. Unlike graphene-based transparent devices, whose $C/A$ (or $\\boldsymbol{\\Pi}$ were achieved at the cost of $T$ (or $C/A\\}$ ,[5,20,45,56,57] a good combination of both high $T$ and $C/A$ has been achieved in our $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ -based device. Although similar capacitance values were reached in the $\\mathrm{RuO}_{2}/$ PEDOT films,[6] the cost and toxicity of $\\mathrm{RuO}_{2}$ greatly limit its potential for practical use in TCEs.[13] The lifetime of the symmetric device was evaluated through GCD measurements (Figure 4f). $95\\%$ of initial capacitance was retained after 24 000 cycles. Typical GCD curves during cycling are shown in the inset of Figure 4f; and Figure S19 (Supporting Information), based on which the Coulombic efficiency was determined to be $\\approx100\\%$ , implying the excellent performances are not due to other parasitic reactions.[26] \n\nBy pairing two electrodes with different potential windows, the voltage window of the asymmetric device can be widened,[6,58–60] thus enhancing the energy density of the device. Here we fabricated a SWCNT film via an aerosol-jet spraying technique and paired it up with $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film $(T=91\\%)$ to form a solid-state asymmetric device. The transmittance spectra of the typical SWCNT electrode, as well as the asymmetric device, are shown in Figure S20 (Supporting Information), revealing a $T$ of $82\\%$ and $72\\%$ , respectively. Figure 5a shows the CVs of the asymmetric device under different voltage windows. The quasirectangular CV shape has been well maintained in the range of $0{\\mathrm{-}}1\\mathrm{~V},$ above which a sharp CV tail starts to evolve with relatively low Coulombic efficiency $95\\%$ , Figure S21, Supporting Information). Therefore, the asymmetric device was cycled within $0{-}1\\mathrm{~V},$ as demonstrated in Figure 5b. The box CV shape is clearly visible at scan rates up to $500\\mathrm{mVs^{-1}}$ , suggesting both capacitive behavior, good rate capability and reversible redox/ double-layer capacitance in the asymmetric device. This is also confirmed by the small CV peaks and sublinear GCD curves (Figure 5b,c). Consequently, the areal capacitance is enhanced to $1.4~\\mathrm{mF~cm^{-2}}$ at $4\\upmu\\mathrm{A}\\mathrm{cm}^{-2}$ , and maintained at $0.5~\\mathrm{mF~cm}^{-2}$ as the current density was elevated by 12 times, showcasing somewhat inferior rate handling to the symmetric device (Figure 4f,g). However, by further optimization, such as introducing redox pairs with higher capacitance,[61] or controlling the thickness of the films to better balance the charge across the two electrodes,[7,58,60,62] higher capacitance coupled with improved rate performance may be envisaged. \n\n![](images/aa3748b25682ef2753039dadb6e1e3a5e2fe48428265db96e4f118829542f35c.jpg) \nFigure 4.  Electrochemical performances of transparent, flexible, symmetric solid-state supercapacitors based on $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films. a) Photographs of flexible, transparent $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ film on PET substrate and symmetric solid-state supercapacitor, showing a high transmittance. b,c) CV curves at various scan rates (b) and GCD curves at different current densities (c) for the symmetric device. d) Measured areal capacitance obtained from GCD and CV curves. e) Measured areal capacitance comparison among various transparent supercapacitors. Detailed values are presented in Table S5 (Supporting Information). f) Cycling stability of a symmetric device. Inset shows the typical GCD curves upon cycling. \n\nEnergy and power densities of the MXene-based transparent devices were further calculated, and compared to that of the reported transparent supercapacitors. As shown in Figure 5e, both the power density and energy density in the asymmetric configuration have been substantially improved compared to the symmetric device. For example, the highest energy density has been improved by ${\\approx}5$ -fold, reaching $0.05\\upmu\\mathrm{Wh}\\mathrm{cm}^{-2}$ at a power density of $2.4~\\upmu\\mathrm{W}~\\mathrm{cm}^{-2}$ in the asymmetric device, which is enough to power burst communication or other related products.[18] \n\nActually, the energy density of the asymmetric device has outperformed other transparent supercapacitors based on PEDOT:PSS,[6,16] graphene quantum-dot,[45] or reduced multilayer graphene oxide thin films,[63] etc.[23] Moreover, the asymmetric device demonstrates excellent long-term cycling stability. As demonstrated in Figure 5f, the capacitance gradually increases over the course of $20~000$ cycles with excellent Coulombic efficiency $(100\\%)$ . The increased capacitance probably stems from the improved access to deep sites between MXene sheets so that more active sites become available for capacitive charge storage during cycling.[6] The electrochemical performance of the transparent solid-state supercapacitors clearly indicates the potential of highly transparent, conductive $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ . \n\nIn summary, we have produced highly ordered $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ transparent films. These films, made of compact, large flakes aligned parallel to the substrate, have demonstrated outstanding optoelectronic properties, such as high transmittance, high DC conductivity with bulk-like behavior, good figure of merit, etc. and are free from percolation issues. These properties render the films efficient as both a transparent conductor and as the active material for high-performance capacitive charge storage, including high areal and volumetric capacitances ( $\\cdot0.48\\mathrm{~mF~cm}^{-2}$ and $676\\ensuremath{\\mathrm{~F~}}\\ensuremath{\\mathrm{cm}}^{-3}$ , respectively) in the supercapacitor electrode, with long lifetime, high energy density and good power handling in prototype all-solid-state devices. Undoubtedly, through further optimization of the MXene synthesis, selection of MXene composition, and/or tuning the properties of the flakes, the optoelectronic and electrochemical properties of the MXene-based films and devices could be further improved. \n\nOn the fundamental side, these findings show that transparent films can be engineered based on metallic, 2D materials with excellent optoelectronic and flexible properties, in sharp contrast to most other transparent electrodes, in which either flexibility or conductivity issues were encountered. On the practical side, the strategy we adopted here is facile, cost-effective, and sustainable. The achieved volumetric capacitance and prototype performance show that the flexible $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films hold great promise in many areas, such as touch screens, displays, organic solar cells, transparent energy-storage devices, wearable electronics, etc. \n\n![](images/60a6ca061371b4ec10258feb8589938eeb02fda168913494c3c7896611abdc4d.jpg) \nFigure 5.  Electrochemical performances of transparent, asymmetric solid-state supercapacitors based on $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ and SWCNT films. a) CV curves at $50\\ m\\vee\\mathsf{s}^{-1}$ of asymmetric solid-state supercapacitor based on $\\bar{\\Gamma}\\mathrm{i}_{3}\\mathsf C_{2}\\mathsf T_{x}/$ /SWCNT films. b,c) Normalized CV curves at various scan rates (b) and GCD at different current densities (c) of the asymmetric device. d) Measured areal capacitance at various current densities. Insets are photographs of SWCNT film and the asymmetric device. e) Ragone plots of symmetric and asymmetric supercapacitor devices, and comparison to other transparent devices. Detailed values are presented in Table S6 (Supporting Information). f) Cycling stability of the asymmetric device at $32\\upmu\\mathsf{A}\\mathsf{c m}^{-2}$ (the inset shows the typical GCD curves upon cycling). \n\nThis work was funded by the European Research Council (ERC) under the number of 2D NANOCAP and 2D3D. G.S.D. acknowledges the support of SFI under Contract Nos. 12/RC/2278 and PI_15/IA/3131. N.M. acknowledges support from SFI through No. 15/SIRG/3329. \n\n# Experimental Section \n\nExperimental details including MXene synthesis, films fabrication, detailed optoelectronic properties of handshaken and sonicated $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ films, and their transmittance spectra are listed in the Supporting Information. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Supporting information \n\nSupporting information is available from the Wiley Online Library or from the author. \n\n# Keywords \n\nMXene, percolation, solid-state supercapacitors, transparent conductive electrodes, volumetric capacitance \n\nReceived: May 13, 2017 Revised: June 11, 2017 Published online: \n\n# Acknowledgements \n\nThe authors specifically acknowledge Mohamed Alhabeb (Drexel University), who provided the recipe for etching the MAX with high yield and thank Dahnan Spurling for help with the films’ conductivity measurements and Daire Tyndall for making some films in the early stage of this study. Both Mohamed Alhabeb and Kathleen Maleski (Drexel University) are also acknowledged for the helpful data discussion. The authors also acknowledge Advanced Microscopic Laboratory (AML) of Trinity College Dublin for providing access to SEM, TEM, and STEM. \n\n[5]\t K. Gao, Z. Shao, X. Wu, X. Wang, Y. Zhang, Nanoscale 2013, 5, 5307. \n[6]\t C.  Zhang, T. M.  Higgins, S.-H.  Park, S. E.  O’Brien, D.  Long, J. N. Coleman, V. Nicolosi, Nano Energy 2016, 28, 495. [7]\t X.  Xiao, T.  Li, Z.  Peng, H.  Jin, Q.  Zhong, Q.  Hu, B.  Yao, Q.  Luo, C. Zhang, L. Gong, J. Chen, Y. Gogotsi, J. Zhou, Nano Energy 2014, 6, 1. \n[8]\t P. Simon, Y. Gogotsi, Acc. Chem. Res. 2013, 46, 1094. \n[9]\t C. Zhang, M. Beidaghi, M. Naguib, M. R. Lukatskaya, M.-Q. Zhao, B. Dyatkin, K. M. Cook, S. J. Kim, B. Eng, X. Xiao, D. Long, W. Qiao, B. Dunn, Y. Gogotsi, Chem. Mater. 2016, 28, 3937. \n[10]\t C.  Zhang, R.  Maloney, M. R.  Lukatskaya, M.  Beidaghi, B.  Dyatkin, E.  Perre, D.  Long, W.  Qiao, B.  Dunn, Y.  Gogotsi, J. Power Sources 2015, 274, 121. \n[11]\t L. Fan, L. Yang, X. Ni, J. Han, R. Guo, C. Zhang, Carbon 2016, 107, 629. \n[12]\t C. Zhang, K. B. Hatzell, M. Boota, B. Dyatkin, M. Beidaghi, D. Long, W. Qiao, E. C. Kumbur, Y. Gogotsi, Carbon 2014, 77, 155. \n[13]\t C.  Zhang, Y.  Xie, M.  Zhao, A. E.  Pentecost, Z.  Ling, J.  Wang, D. Long, L. Ling, W. Qiao, ACS Appl. Mater. Interfaces 2014, 6, 9751. \n[14]\t F.  Xiong, S.  Tan, Q.  Wei, G.  Zhang, J.  Sheng, Q.  An, L.  Mai, Nano Energy 2017, 32, 347. \n[15]\t S.  De, T. M.  Higgins, P. E.  Lyons, E. M.  Doherty, P. N.  Nirmalraj, W. J. Blau, J. J. Boland, J. N. Coleman, ACS Nano 2009, 3, 1767. \n[16]\t T. M.  Higgins, J. N.  Coleman, ACS Appl. Mater. Interfaces 2015, 7, 16495. \n[17]\t F. S.  Gittleson, D.  Hwang, W.-H.  Ryu, S. M.  Hashmi, J.  Hwang, T. Goh, A. D. Taylor, ACS Nano 2015, 9, 10005. \n[18]\t P. J.  King, T. M.  Higgins, S.  De, N.  Nicoloso, J. N.  Coleman, ACS Nano 2012, 6, 1732. \n[19]\t I. Nam, S. Park, G.-P. Kim, J. Park, J. Yi, Chem. Sci. 2013, 4, 1663. \n[20]\t T. Chen, Y. Xue, A. K. Roy, L. Dai, ACS Nano 2014, 8, 1039. \n[21]\t S.  De, P. E.  Lyons, S.  Sorel, E. M.  Doherty, P. J.  King, W. J.  Blau, P. N.  Nirmalraj, J. J.  Boland, V.  Scardaci, J.  Joimel, J. N.  Coleman, ACS Nano 2009, 3, 714. \n[22]\t P. Chen, G. Shen, Appl. Phys. Lett. 2009, 94, 043113 1. \n[23]\t H. Y.  Jung, M. B.  Karimi, M. G.  Hahm, P. M.  Ajayan, Y. J.  Jung, Sci. Rep. 2012, 2, 773. \n[24]\t M.  Naguib, M.  Kurtoglu, V.  Presser, J.  Lu, J.  Niu, M.  Heon, L. Hultman, Y. Gogotsi, M. W. Barsoum, Adv. Mater. 2011, 23, 4248. \n[25]\t M.  Naguib, O.  Mashtalir, J.  Carle, V.  Presser, J.  Lu, L.  Hultman, Y. Gogotsi, M. W. Barsoum, ACS Nano 2012, 6, 1322. \n[26]\t M.  Ghidiu, M. R.  Lukatskaya, M.-Q.  Zhao, Y.  Gogotsi, M. W. Barsoum, Nature 2014, 516, 78. \n[27]\t J.  Halim, S.  Kota, M. R.  Lukatskaya, M.  Naguib, M. Q.  Zhao, E. J. Moon, J. Pitock, J. Nanda, S. J. May, Y. Gogotsi, M. W. Barsoum, Adv. Funct. Mater. 2016, 26, 3118. \n[28]\t B. Anasori, M. R. Lukatskaya, Y. Gogotsi, Nat. Rev. Mater. 2017, 2, 16098. \n[29]\t O. Mashtalir, M. Naguib, V. N. Mochalin, Y. Dall’Agnese, M. Heon, M. W. Barsoum, Y. Gogotsi, Nat. Commun. 2013, 4, 1716. \n[30]\t F. Du, H. Tang, L. Pan, T. Zhang, H. Lu, J. Xiong, J. Yang, C. Zhang, Electrochim. Acta 2017, 235, 690. \n[31]\t C.  Zhang, S.  Pinilla, N.  McEvoy, C. P.  Cullen, B.  Anasori, E.  Long, S.-H.  Park, A.  Seral-Ascaso, A.  Shmeliov, D.  Krishnan, C.  Morant, X. Liu, G. S. Duesberg, Y. Gogotsi, V. Nicolosi, Chem. Mater. 2017, 29, 4848. \n[32]\t X.  Xie, M.-Q.  Zhao, B.  Anasori, K.  Maleski, C. E.  Ren, J.  Li, B. W.  Byles, E.  Pomerantseva, G.  Wang, Y.  Gogotsi, Nano Energy 2016, 26, 513. \n[33]\t F.  Shahzad, M.  Alhabeb, C. B.  Hatter, B.  Anasori, S.  Man Hong, C. M. Koo, Y. Gogotsi, Science 2016, 353, 1137. \n[34]\t C. E.  Ren, K. B.  Hatzell, M.  Alhabeb, Z.  Ling, K. A.  Mahmoud, Y. Gogotsi, J. Phys. Chem. Lett. 2015, 6, 4026. \n[35]\t K.  Rasool, M.  Helal, A.  Ali, C. E.  Ren, Y.  Gogotsi, K. A.  Mahmoud, ACS Nano 2016, 10, 3674. \n[36]\t A. D. Dillon, M. J. Ghidiu, A. L. Krick, J. Griggs, S. J. May, Y. Gogotsi, M. W. Barsoum, A. T. Fafarman, Adv. Funct. Mater. 2016, 26, 4162. \n[37]\t K.  Hantanasirisakul, M.-Q.  Zhao, P.  Urbankowski, J.  Halim, B. Anasori, S. Kota, C. E. Ren, M. W. Barsoum, Y. Gogotsi, Adv. Electron. Mater. 2016, 2, 1600050. \n[38]\t M.  Mariano, O.  Mashtalir, F.  Antonio, W.-H.  Ryu, B.  Deng, F.  Xia, Y. Gogotsi, A. Taylor, Nanoscale 2016, 8, 16371. \n[39]\t M.-Q.  Zhao, C. E.  Ren, Z.  Ling, M. R.  Lukatskaya, C.  Zhang, K. L. Van Aken, M. W. Barsoum, Y. Gogotsi, Adv. Mater. 2015, 27, 339. \n[40]\t A.  Lipatov, M.  Alhabeb, M. R.  Lukatskaya, A.  Boson, Y.  Gogotsi, A. Sinitskii, Adv. Electron. Mater. 2016, 2, 1600255. \n[41]\t M.  Naguib, O.  Mashtalir, M. R.  Lukatskaya, B.  Dyatkin, C.  Zhang, V.  Presser, Y.  Gogotsi, M. W.  Barsoum, Chem. Commun. 2014, 50, 7420. \n[42]\t X.  Li, G.  Zhang, X.  Bai, X.  Sun, X.  Wang, E.  Wang, H.  Dai, Nat. Nanotechnol. 2008, 3, 538. \n[43]\t S. De, P. J. King, M. Lotya, A. O’Neill, E. M. Doherty, Y. Hernandez, G. S. Duesberg, J. N. Coleman, Small 2010, 6, 458. \n[44]\t H. A.  Becerril, J.  Mao, Z.  Liu, R. M.  Stoltenberg, Z.  Bao, Y.  Chen, ACS Nano 2008, 2, 463. \n[45]\t K. Lee, H. Lee, Y. Shin, Y. Yoon, D. Kim, H. Lee, Nano Energy 2016, 26, 746. \n[46]\t S. De, J. N. Coleman, ACS Nano 2010, 4, 2713. \n[47]\t J.  Wu, H. A.  Becerril, Z.  Bao, Z.  Liu, Y.  Chen, P.  Peumans, Appl. Phys. Lett. 2008, 92, 263302. \n[48]\t Y.-Y.  Peng, B.  Akuzum, N.  Kurra, M.-Q.  Zhao, M.  Alhabeb, B.  Anasori, E. C.  Kumbur, H. N.  Alshareef, M.-D.  Ger, Y.  Gogotsi, Energy Environ. Sci. 2016, 9, 2847. \n[49]\t N.  Jäckel, B.  Krüner, K. L.  Van Aken, M.  Alhabeb, B.  Anasori, F. Kaasik, Y. Gogotsi, V. Presser, ACS Appl. Mater. Interfaces 2016, 8, 32089. \n[50]\t N. Kurra, B. Ahmed, Y. Gogotsi, H. N. Alshareef, Adv. Energy Mater. 2016, 6, 1601372. \n[51]\t M. Hu, Z. Li, T. Hu, S. Zhu, C. Zhang, X. Wang, ACS Nano 2016, 10, 11344. \n[52]\t M. R.  Lukatskaya, S.-M.  Bak, X.  Yu, X.-Q.  Yang, M. W.  Barsoum, Y. Gogotsi, Adv. Energy Mater. 2015, 5, 1500589. \n[53]\t Z.  Niu, W.  Zhou, J.  Chen, G.  Feng, H.  Li, Y.  Hu, W.  Ma, H.  Dong, J. Li, S. Xie, Small 2013, 9, 518. \n[54]\t S. W. Lee, B.-S. Kim, S. Chen, Y. Shao-Horn, P. T. Hammond, J. Am. Chem. Soc. 2009, 131, 671. \n[55]\t H. R.  Byon, S. W.  Lee, S.  Chen, P. T.  Hammond, Y.  Shao-Horn, Carbon 2011, 49, 457. \n[56]\t Y.  Gao, Y. S.  Zhou, W.  Xiong, L. J.  Jiang, M.  Mahjouri-samani, P.  Thirugnanam, X.  Huang, M. M.  Wang, L.  Jiang, Y. F.  Lu, APL Mater. 2013, 1, 12101. \n[57]\t X. Fan, T. Chen, L. Dai, RSC Adv. 2014, 4, 36996. \n[58]\t L. Kong, C. Zhang, J. Wang, D. Long, W. Qiao, L. Ling, Mater. Chem. Phys. 2015, 149–150, 495. \n[59]\t L. Kong, C. Zhang, S. Zhang, J. Wang, R. Cai, C. Lv, W. Qiao, L. Ling, D. Long, J. Mater. Chem. A 2014, 2, 17962. \n[60]\t L.  Kong, C.  Zhang, J.  Wang, W.  Qiao, L.  Ling, D.  Long, Sci. Rep. 2016, 6, 21177. \n[61]\t M. Boota, C. Chen, M. Bécuwe, L. Miao, Y. Gogotsi, Energy Environ. Sci. 2016, 9, 2586. \n[62]\t X. Xiao, C. Zhang, S. Lin, L. Huang, Z. Hu, Y. Cheng, T. Li, W. Qiao, D.  Long, Y.  Huang, L.  Mai, Y.  Gogotsi, J.  Zhou, Energy Storage Mater. 2015, 1, 1. \n[63]\t J. J.  Yoo, K.  Balakrishnan, J.  Huang, V.  Meunier, B. G.  Sumpter, A.  Srivastava, M.  Conway, A. L.  Mohana Reddy, J.  Yu, R.  Vajtai, P. M. Ajayan, Nano Lett. 2011, 11, 1423. " + }, + { + "id": "10.1126_science.aal4211", + "DOI": "10.1126/science.aal4211", + "DOI Link": "http://dx.doi.org/10.1126/science.aal4211", + "Relative Dir Path": "mds/10.1126_science.aal4211", + "Article Title": "PEROVSKITE PHYSICS Extremely efficient internal exciton dissociation through edge states in layered 2D perovskites", + "Authors": "Blancon, JC; Tsai, H; Nie, W; Stoumpos, CC; Pedesseau, L; Katan, C; Kepenekian, M; Soe, CMM; Appavoo, K; Sfeir, MY; Tretiak, S; Ajayan, PM; Kanatzidis, MG; Even, J; Crochet, JJ; Mohite, AD", + "Source Title": "SCIENCE", + "Abstract": "Understanding and controlling charge and energy flow in state-of-the-art semiconductor quantum wells has enabled high-efficiency optoelectronic devices. Two-dimensional (2D) Ruddlesden-Popper perovskites are solution-processed quantum wells wherein the band gap can be tuned by varying the perovskite-layer thickness, which modulates the effective electron-hole confinement. We report that, counterintuitive to classical quantum-confined systems where photogenerated electrons and holes are strongly bound by Coulomb interactions or excitons, the photophysics of thin films made of Ruddlesden-Popper perovskites with a thickness exceeding two perovskite-crystal units (>1.3 nullometers) is dominated by lower-energy states associated with the local intrinsic electronic structure of the edges of the perovskite layers. These states provide a direct pathway for dissociating excitons into longer-lived free carriers that substantially improve the performance of optoelectronic devices.", + "Times Cited, WoS Core": 922, + "Times Cited, All Databases": 997, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000397082900033", + "Markdown": "# Extremely efficient internal exciton dissociation through edge states in layered 2D perovskites \n\nJ.-C. Blancon,1 H. Tsai,1,2 W. Nie,1 C. C. Stoumpos,3 L. Pedesseau,4 C. Katan,5 M. Kepenekian,5 C. M. M. Soe,3 K. Appavoo,6 M. Y. Sfeir,6 S. Tretiak,1 P. M. Ajayan,2 M. G. Kanatzidis,3,7 J. Even,4 J. J. Crochet,1\\* A. D. Mohite1\\* \n\n1Los Alamos National Laboratory, Los Alamos, NM 87545, USA. 2Department of Materials Science and Nanoengineering, Rice University, Houston, TX 77005, USA. 3Department of Chemistry, Northwestern University, Evanston, IL 60208, USA. 4Fonctions Optiques pour les Technologies de l’Information (FOTON), INSA de Rennes, CNRS, UMR 6082, 35708 Rennes, France. 5Institut des Sciences Chimiques de Rennes (ISCR), Université de Rennes 1, CNRS, UMR 6226, 35042 Rennes, France. 6Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, NY 11973, USA. 7Department of Materials Science and Engineering, Northwestern University, Evanston, IL 60208, USA. \n\nCorresponding author. Email: jcrochet@lanl.gov (J.C.C.); amohite@lanl.gov (A.D.M.) \n\nUnderstanding and controlling charge and energy flow in state-of-the-art semiconductor quantum-wells has enabled high-efficiency optoelectronic devices. Two-dimensional Ruddlesden-Popper perovskites are solution-processed quantum-wells wherein the band gap can be tuned by varying the perovskite layer thickness, which modulates the effective electron-hole confinement. We report that, counterintuitive to classical quantum-confined systems where photo-generated electrons and holes are strongly bound by Coulomb interactions or excitons, the photo-physics of thin films made of Ruddlesden-Popper perovskites with a thickness exceeding two perovskite crystal-units $(>1.3$ nanometers) is dominated by lower energy states associated with the local intrinsic electronic structure of the edges of the perovskite layers. These states provide a direct pathway for dissociating excitons into longer-lived free-carriers that significantly improve the performance of optoelectronic devices. \n\nTwo-dimensional (2D) Ruddlesden-Popper perovskites (RPPs) are a class of quantum-well (QW) like materials described by the formula $\\mathrm{\\mathbf{A}_{n}\\mathbf{A}_{n-1}^{3}\\mathbf{M}_{n}\\mathbf{X}_{3n+1}}$ where A, A’ are cations, M is metal and X is halide; the value of n determines the QW thickness and, as a result, the degree of quantum and dielectric confinement as well as the optical band gap (or color) (1–9). They have emerged as an alternative to bulk (3D) organic-inorganic (hybrid) perovskites because of their technologically relevant photo- and chemical-stability coupled with high-performance optoelectronic devices (10–12). Compared with 3D perovskites and classical semiconductorbased QWs, RPPs offer tremendous advantages because of the tunability of their optoelectronic properties through both chemical and quantum-mechanical degrees of freedom. For two decades, most RPP crystals with $\\scriptstyle\\mathbf{n=1}$ (6, 13–15) have been studied with few prototypes of optoelectronic devices (3, 16). Recently, the synthesis of phase-pure (purified to one n-value) 2D perovskites with high n-values $\\scriptstyle\\mathbf{n=2}$ to 5) was achieved (4), which led to the demonstration of highefficiency thin film solar cells based on RPPs $\\scriptstyle\\mathrm{n=3,4}$ with technology-relevant stability (12). However, there is limited understanding of the fundamental physical properties of phase-pure 2D perovskites of high n-value in thin films typically used for optoelectronic applications. Furthermore, the fate of photogenerated electron-hole pairs and the underlying photophysical processes such as charge separation and recombination are unknown. \n\nWe investigated photophysical and optoelectronic properties of phase-pure homogenous 2D perovskites, and show that in thin films (fig. S1) for $\\scriptstyle\\mathbf{n>2}$ , there exists an intrinsic mechanism for dissociation of the strongly bound electronhole pairs (excitons) to long-lived free-carriers provided by lower energy states at the edges of the layered perovskites. Moreover, once carriers are trapped in these edge states, they remain protected and do not lose their energy via nonradiative processes and can contribute to photocurrent in a photovoltaic (PV) device or radiatively recombine efficiently as desired for light-emission applications. We validate these findings through PV devices with record efficiencies and two-orders higher photoluminescence quantum yields (PLQY) using $\\scriptstyle\\mathrm{n>2}$ layered perovskites. \n\nThe crystal structure and evidence for phase-purity of the investigated layered 2D perovskite family of $\\mathrm{(BA)_{2}(M A)_{n}}$ - $\\mathrm{\\Delta_{1}P b_{n}I_{3n+1}}$ with n from 1 to 5 are shown in Fig. 1, A and B. In order to understand the origin of the thin film optical properties, we compared them to those of their exfoliated crystal counterparts prepared by mechanically exfoliating fewlayers of pristine RPPs crystals. The optical absorption and photoluminescence (PL) properties of the thin films and exfoliated crystals are illustrated Fig. 1, C to $\\mathrm{~F~}{}$ (fig. S1) $(I7)$ , along with bulk $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ perovskites for comparison. \n\nThere was a dramatic difference in the optical properties of the thin films and exfoliated crystals (Fig. 1, C to H, and table S1 and fig. S2) (17). In the exfoliated crystals, band gap absorption and emission increased monotonously from 1.85 eV to $2.42\\ \\mathrm{eV}$ with decreasing n from 5 to 1 (QW thickness varying from $3.139~\\mathrm{nm}$ to $0.641\\mathrm{nm}$ ), which is expected from quantum and dielectric confinement resulting in many-body interactions and large exciton binding energies at room temperature $(5-9,\\ 13,\\ 18)$ . This behavior was confirmed by estimating the exciton binding energies as a function of n (figs. S3 and S4) $(I7)$ , which amounts to $380~\\mathrm{meV}$ , $270{\\mathrm{~meV}}$ , and an average value of $220~\\mathrm{meV}$ for $\\scriptstyle\\mathrm{n=1}$ , $\\scriptstyle\\mathbf{n=2}$ and $\\scriptstyle\\mathrm{n>2}$ , respectively. These values of exciton binding energy ${\\it\\Omega}>200{\\it\\Omega}$ meV) attest to the robustness of the excitonic states at room temperature in phase pure RPPs up to $\\scriptstyle\\mathbf{n}=5$ . They are about one order of magnitude larger than the values found in 3D lead halide perovskites (19) due to quantum confinement effects. Moreover, as compared to lead-salt (LS) materials in which dielectric confinement effects become dominant, they are similar to LS quantum dots (20), LS nanorods (21) and LS nanosheets (22) for similar confinement lengths (see more detailed discussion in section ST1 in the SM and table S2) $(I7)$ . For $n=3-5$ , the exciton binding energy reached a value of ${\\sim}200~\\mathrm{meV}$ , consistent with a system exhibiting 2D quantum confinement, given negligible enhancement of the Coulomb interactions caused by dielectric confinement (9). However, in thin films the optical band gap is in a good agreement with that observed for exfoliated crystals for $\\scriptstyle\\mathbf{n=}1$ and 2 but red-shifted by 200 to $300\\mathrm{meV}$ for $n=3-5$ (Fig. 1G). \n\nWe note that the band gap stayed almost constant in thin films with $\\scriptstyle\\mathbf{n>2}$ . Any modification to the pristine 2D perovskites phase during thin film fabrication has already been excluded (11, 12). Effects such as changes in dielectric environment and differences in crystallinity (23, 24) cannot account for the redshifts observed in RPP thin films for $\\scriptstyle\\mathbf{n>2}$ . The redshifts are also not consistent with electronic impurities at surfaces/interfaces/boundaries in perovskites where carriers are trapped a few tens of millielectron volts within the band gap (25–28). Furthermore, optical absorption anisotropy measurements (fig. S5) rule out effects from different orientations of the perovskite layers with respect to light polarization in both thin films and exfoliated crystals $(I7)$ . \n\nWe further studied the microscopic origin of the lowenergy band gap in thin films for $\\scriptstyle\\mathrm{n>2}$ by confocal spatial mapping $(\\sim1~\\upmu\\mathrm{m}$ resolution) of the PL on a representative $\\scriptstyle\\mathbf{n=3}$ exfoliated crystal (Fig. 2A). Although majority of the basal plane of exfoliated crystal yields spatially homogeneous PL at its band gap energy $(2.010\\ \\mathrm{eV})$ , appreciable PL emission was observed from the edges of the exfoliated crystal at $1.680\\ \\mathrm{eV}$ . Figure 2B illustrates the PL spectra of the exfoliated crystal, edges of the exfoliated crystal, and corresponding thin film. The spectra collected at the crystaledges contain PL peaks observed in both the thin film and exfoliated crystal, which indicates a common origin of the PL from states associated with the edges of the exfoliated crystal (labeled as layer-edge-states, LES) and the PL at low energy in thin films for $\\scriptstyle\\mathbf{n>2}$ . Similar results were obtained in the case of $\\scriptstyle\\mathbf{n}=4$ and 5 RPP exfoliated crystals (fig. S6) $(I7)$ , whereas the LES emission was absent when $\\mathbf{n}=\\mathbf{1}$ or 2. \n\nWe probed the spectral origin of the emitting states observed above using PL excitation (PLE) spectroscopy and time-resolved PL (TRPL). The PLE measurements were performed near the edges of the exfoliated crystal in Fig. 2A and revealed both the main exciton emission (labeled Xstate) at $2.010\\ \\mathrm{eV}$ and the LES at $1.680\\ \\mathrm{eV}.$ . We monitored the PL intensity at the LES energy while sweeping the lightexcitation energy between 1.800 and $2.900~\\mathrm{eV}$ (Fig. 2C). The PLE showed a clear peak at the position of the exciton $\\left(2.010\\pm0.007~\\mathrm{eV}\\right)$ , but no direct absorption into the LES was observed in the exfoliated crystal (PLE was negligible below $1.900~\\mathrm{eV})$ . The spectrum exhibited two high-energy features at ${\\sim}2.110\\ \\mathrm{eV}$ and $2.200~\\mathrm{eV},$ , associated with excited excitonic states and band-to-band absorption, which yielded an exciton binding energy of $200\\ \\mathrm{meV}$ , in agreement with our absorption measurements (Fig. 1E). \n\nThese results and the comparable PL intensity of both the X and LES features suggested that part of the photoexcited exciton population decayed to the LES. This mechanism was further validated by probing the TRPL response of both states (Fig. 2D). At short times after the arrival of the light-excitation pulse, the exciton-state became populated over a period of ${\\sim}100$ fs (25, 29) (not resolved here). However, the LES emission reached its maximum PL intensity $\\sim200$ ps after the $\\mathbf{X}$ -state, which is indicative of slow carrier filling from the higher energy exciton to the low-energy edge states. We also observed a nearly four-fold increase in the carrier lifetime of the LES as compared to the exciton, suggesting suppressed nonradiative recombination of the localized carriers. Figure 2E schematically summarizes the photoemission mechanisms in 2D perovskites. The photoexcited exciton diffuses in the perovskite layer emitting a photon at the exciton energy (geminate radiative recombination, see below) or can be quenched via nonradiative recombination. However, these measurements elucidate that, in 2D perovskites with $\\scriptstyle\\mathrm{n>2}$ , a part of the photogenerated exciton population travel to the edges of the crystal within its diffusion time, and then undergoes an internal conversion to a LES and efficiently emits photons at a lower energy than the main exciton. \n\nWe gained further insight into the physical origin of the optical transitions (Fig. 1, C and D) by analyzing the absorption and photoemission properties of thin films. Figure 3A describes the transitions in thin films with $\\scriptstyle\\mathbf{n=3}$ (fig. S7 for the other n-values) $(I7)$ . The absorption spectrum exhibits resonances at $1.947~\\pm~0.005$ , $2.067~\\pm~0.006$ , and $2.173~\\pm$ $0.006\\ \\mathrm{eV};$ , which are very close in energy to the main exciton-state in exfoliated crystals (2.039 eV). These features were also observed in the PL spectra at relatively high lightexcitation intensity (Fig. 3A, inset), i.e., after saturating the lower-energy LES population. The excitonic nature of these optical resonances was confirmed through (i) linear dependence of the integrated PL signal with respect to the light-excitation intensity ${\\mathrm{I}}_{0}$ (Fig. 3B, black) and (ii) the negative temperature dependence of their peak energy (figs. S8 and S9) $(5,6,77)$ . On the other hand, the main PL peak at $1.695\\pm0.015\\mathrm{eV}$ (Fig. 3A, inset) corresponds to the LES peak observed in exfoliated crystals (Fig. 2B). In sharp contrast to exfoliated crystals (Fig. 2), the PL was dominated by the LES peak, and a broad absorption feature around 1.73 eV (Fig. 3A) accounts for direct absorption into this LES and related mini-bands. These features are a direct consequence of both the light sampling across numerous LES in thin films (Fig. 3D) because of: preferential orientation of perovskite layers normal to the substrate (fig. S10) (12, 17), small grain sizes typically of the order of $200{-}400\\ \\mathrm{nm}$ (fig. S11) (12, 17), and the relaxation of optical transition selection rules in imperfect crystals. \n\nWe also observed that the PL signal associated with the LES varied nonlinearly with the photoexcitation intensity ${\\mathrm{I}}_{0}$ between 1.30 and 1.45 (Fig. 3B and fig. S7) $(I7)$ . This signal corresponds to a mixed bimolecular and monomolecular recombination of photoexcited carriers (27), thus implying a partial dissociation of excitons to free-carrier-like entities as the excitonic states convert (or dissociate) to LES. This conclusion is also consistent with the smooth rise of the absorption at the optical band gap in comparison to the sharp excitonic features observed in exfoliated crystals (Fig. 1, C and E). Moreover, the energy of the LES varied with temperature as $0.21~\\mathrm{meV/K}$ (fig. S12) $(I7)$ , which has been attributed in 3D perovskites to the thermal expansion of the lattice where free carriers dominate (30). On the contrary, the RPPs with $\\scriptstyle\\mathrm{n\\leq2}$ that do not exhibit the LES showed negligible or negative temperature dependence of their optical resonances (fig. S8) $(I7)$ , consistent with classical excitonic theory $(5,6)$ . \n\nAll of these measurements establish that a different physical origin and behavior of the excitonic and LES features and validated that the main band-gap optical transition in RPP thin films with $\\scriptstyle\\mathrm{n>2}$ originates from the intrinsic electronic structure associated with the edges of the 2D perovskite layers (see discussion in section ST2 in the SM on the possible causes of LES formation) $(I7)$ . Based on our observations, the primary mechanism that emerges in thin films is trapping of the free carriers after exciton dissociation to a deep electronic state located at layer-edges. This model is compatible with both the higher PL efficiency and the longer lifetime of the LES as compared to the higher energy X-states (Fig. 3, B and C). These results imply that, once the carriers are localized at LES, they are protected from non-radiative decay mechanisms such as electronphonon coupling (31, 32) or electronic impurities (25). These key mechanisms of the photoemission in RPPs are captured in Fig. 3E (fig. S13), where, after photogeneration of excitons (left), they can either decay via classical processes (dominant for $\\scriptstyle\\mathrm{n\\leq2}$ , middle) or dissociate to free-carriers potentially trapped at LES (dominant for $\\scriptstyle\\mathbf{n>2}$ , right). The process involving intrinsic dissociation of the primary photogenerated excitons to free carrier like states that exist lower in energy in a single-component material is non-intuitive, and not observed in any classical quantum-confined material system. \n\nMotivated by the observed internal exciton dissociation from a part of the higher energy excitonic states to LES that protect the carriers over an appreciably longer timescale, we fabricated high-efficiency PV cells with RPPs and measured their current-voltage (J-V) characteristics and power conversion efficiency (PCE) (Fig. 4, A and B). We observed a sharp break in the current density and PCE from $<2\\%$ for $\\scriptstyle\\mathbf{n=1}$ and 2 to ${>}12\\%$ for $\\scriptstyle\\mathrm{n>2}$ . Assuming comparable charge transport properties for all RPPs, the performance of PV cells for $\\scriptstyle\\mathbf{n>2}$ are impacted by the presence of the LES as: (i) it extends the absorption from the visible to the near infrared, and (ii) it contributes to internal exciton dissociation to free-carrier-like entities that can be more readily collected by the built-in field in a PV device. This was confirmed by measuring the external quantum efficiency (EQE) spectra (Fig. 4C), which showed about five-fold enhancement in collection efficiency in PV cells using RPPs with $\\scriptstyle\\mathbf{n>2}$ as compared to $\\scriptstyle\\mathbf{n=1}$ and 2. Furthermore, the free carriers that converge to the LES remain protected, thus exhibiting long recombination carrier lifetimes resulting in a much higher probability for efficient PL (Fig. 4D and fig. S14) $(I7)$ , which has tremendous implications for high-efficiency lightemitting devices using RPPs with $\\mathrm{n}{>}2$ . The variations of the PL efficiency in thin films and of the solar cell efficiency (33) between RPPs with $\\scriptstyle\\mathrm{n=3,4,5}$ were possibly due to small variations of the crystal crystallinity and ordering (12), and/or light out-coupling and photon recycling effects (34). These results pave the path forward for the rational design of high-efficiency optoelectronic devices with solutionprocessed layered 2D perovskite-based materials. \n\n# REFERENCES AND NOTES \n\n1. S. N. Ruddlesden, P. Popper, New compounds of the K2NiF4 type. Acta Crystallogr. 10, 538–539 (1957). doi:10.1107/S0365110X57001929 \n2. S. N. Ruddlesden, P. Popper, The compound Sr3Ti2O7 and its structure. Acta Crystallogr. 11, 54–55 (1958). doi:10.1107/S0365110X58000128 \n3. C. R. Kagan, D. B. Mitzi, C. D. Dimitrakopoulos, Organic-inorganic hybrid materials as semiconducting channels in thin-film field-effect transistors. Science 286, 945–947 (1999). doi:10.1126/science.286.5441.945 Medline \n4. C. C. Stoumpos, D. H. Cao, D. J. Clark, J. Young, J. M. Rondinelli, J. I. Jang, J. T. Hupp, M. G. Kanatzidis, Ruddlesden–Popper hybrid lead iodide perovskite 2D homologous semiconductors. Chem. Mater. 28, 2852–2867 (2016). doi:10.1021/acs.chemmater.6b00847 \n5. T. Ishihara, J. Takahashi, T. Goto, Optical properties due to electronic transitions in two-dimensional semiconductors (CnH2n+1NH3)2PbI4. Phys. Rev. B 42, 11099– 11107 (1990). doi:10.1103/PhysRevB.42.11099 Medline \n6. N. Kitazawa, M. Aono, Y. Watanabe, Synthesis and luminescence properties of lead-halide based organic-inorganic layered perovskite compounds (CnH2n+1NH3)2PbI4 ( $\\scriptstyle\\mathtt{n=4}$ , 5, 7, 8 and 9). J. Phys. Chem. Solids 72, 1467–1471 (2011). doi:10.1016/j.jpcs.2011.08.029 \n7. J. Even, L. Pedesseau, C. Katan, Understanding quantum confinement of charge carriers in layered 2D hybrid perovskites. ChemPhysChem 15, 3733–3741 (2014). doi:10.1002/cphc.201402428 Medline \n8. D. Sapori, M. Kepenekian, L. Pedesseau, C. Katan, J. Even, Quantum confinement and dielectric profiles of colloidal nanoplatelets of halide inorganic and hybrid organic-inorganic perovskites. Nanoscale 8, 6369–6378 (2016). doi:10.1039/C5NR07175E Medline \n9. L. Pedesseau, D. Sapori, B. Traore, R. Robles, H.-H. Fang, M. A. Loi, H. Tsai, W. Nie, J.-C. Blancon, A. Neukirch, S. Tretiak, A. D. Mohite, C. Katan, J. Even, M. Kepenekian, Advances and promises of layered halide hybrid perovskite semiconductors. ACS Nano 10, 9776–9786 (2016). doi:10.1021/acsnano.6b05944 Medline \n10. I. C. Smith, E. T. Hoke, D. Solis-Ibarra, M. D. McGehee, H. I. Karunadasa, A layered hybrid perovskite solar-cell absorber with enhanced moisture stability. Angew. Chem. Int. Ed. 53, 11232–11235 (2014). doi:10.1002/anie.201406466 Medline \n11. D. H. Cao, C. C. Stoumpos, O. K. Farha, J. T. Hupp, M. G. Kanatzidis, 2D homologous perovskites as light-absorbing materials for solar cell applications. J. Am. Chem. Soc. 137, 7843–7850 (2015). doi:10.1021/jacs.5b03796 Medline \n12. H. Tsai, W. Nie, J.-C. Blancon, C. C. Stoumpos, R. Asadpour, B. Harutyunyan, A. J. Neukirch, R. Verduzco, J. J. Crochet, S. Tretiak, L. Pedesseau, J. Even, M. A. Alam, G. Gupta, J. Lou, P. M. Ajayan, M. J. Bedzyk, M. G. Kanatzidis, A. D. Mohite, High-efficiency two-dimensional Ruddlesden-Popper perovskite solar cells. Nature 536, 312–316 (2016). doi:10.1038/nature18306 Medline \n13. K. Tanaka, T. Kondo, Bandgap and exciton binding energies in lead-iodide-based natural quantum-well crystals. Sci. Technol. Adv. Mater. 4, 599–604 (2003). doi:10.1016/j.stam.2003.09.019 \n14. K. Tanaka, T. Takahashi, T. Kondo, K. Umeda, K. Ema, T. Umebayashi, K. Asai, K. Uchida, N. Miura, Electronic and excitonic structures of inorganic–organic perovskite-type quantum-well crystal (C4H9NH3)2PbBr4. Jpn. J. Appl. Phys. 44, 5923–5932 (2005). doi:10.1143/JJAP.44.5923 \n15. K. Gauthron, J.-S. Lauret, L. Doyennette, G. Lanty, A. Al Choueiry, S. J. Zhang, A. Brehier, L. Largeau, O. Mauguin, J. Bloch, E. Deleporte, Optical spectroscopy of two-dimensional layered (C(6)H(5)C(2)H(4)-NH(3))(2)-PbI(4) perovskite. Opt. Express 18, 5912–5919 (2010). doi:10.1364/OE.18.005912 Medline \n16. D. B. Mitzi, K. Chondroudis, C. R. Kagan, Organic-inorganic electronics. IBM J. Res. Develop. 45, 29–45 (2001). doi:10.1147/rd.451.0029 \n17. Materials and methods are available as supplementary materials. \n18. O. Yaffe, A. Chernikov, Z. M. Norman, Y. Zhong, A. Velauthapillai, A. van der Zande, J. S. Owen, T. F. Heinz, Excitons in ultrathin organic-inorganic perovskite crystals. Phys. Rev. B 92, 045414 (2015). doi:10.1103/PhysRevB.92.045414 \n19. L. M. Herz, Charge-carrier dynamics in organic-inorganic metal halide perovskites. Annu. Rev. Phys. Chem. 67, 65–89 (2016). doi:10.1146/annurevphyschem-040215-112222 Medline \n20. J. Jasieniak, M. Califano, S. E. Watkins, Size-dependent valence and conduction band-edge energies of semiconductor nanocrystals. ACS Nano 5, 5888–5902 (2011). doi:10.1021/nn201681s Medline \n21. A. C. Bartnik, A. L. Efros, W.-K. Koh, C. B. Murray, F. W. Wise, Electronic states and optical properties of PbSe nanorods and nanowires. Phys. Rev. B 82, 195313 (2010). doi:10.1103/PhysRevB.82.195313 \n22. J. Yang, F. W. Wise, Electronic states of lead-salt nanosheets. J. Phys. Chem. C 119, 26809–26816 (2015). doi:10.1021/acs.jpcc.5b08207 \n23. J.-C. Blancon, M. Paillet, H. N. Tran, X. T. Than, S. A. Guebrou, A. Ayari, A. San Miguel, N.-M. Phan, A.-A. Zahab, J.-L. Sauvajol, N. Del Fatti, F. Vallée, Direct measurement of the absolute absorption spectrum of individual semiconducting single-wall carbon nanotubes. Nat. Commun. 4, 2542 (2013). doi:10.1038/ncomms3542 Medline \n24. Y. Lin, X. Ling, L. Yu, S. Huang, A. L. Hsu, Y.-H. Lee, J. Kong, M. S. Dresselhaus, T. Palacios, Dielectric screening of excitons and trions in single-layer MoS2. Nano Lett. 14, 5569–5576 (2014). doi:10.1021/nl501988y Medline \n25. X. Wu, M. T. Trinh, D. Niesner, H. Zhu, Z. Norman, J. S. Owen, O. Yaffe, B. J. Kudisch, X.-Y. Zhu, Trap states in lead iodide perovskites. J. Am. Chem. Soc. 137, 2089–2096 (2015). doi:10.1021/ja512833n Medline \n26. W. Nie, H. Tsai, R. Asadpour, J.-C. Blancon, A. J. Neukirch, G. Gupta, J. J. Crochet, M. Chhowalla, S. Tretiak, M. A. Alam, H.-L. Wang, A. D. Mohite, Solar cells. Highefficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 347, 522–525 (2015). doi:10.1126/science.aaa0472 Medline \n27. J.-C. Blancon, W. Nie, A. J. Neukirch, G. Gupta, S. Tretiak, L. Cognet, A. D. Mohite, J. J. Crochet, The effects of electronic impurities and electron–hole recombination dynamics on large-grain organic–inorganic perovskite photovoltaic efficiencies. Adv. Funct. Mater. 26, 4283–4292 (2016). doi:10.1002/adfm.201505324 \n28. D. W. de Quilettes, S. M. Vorpahl, S. D. Stranks, H. Nagaoka, G. E. Eperon, M. E. Ziffer, H. J. Snaith, D. S. Ginger, Solar cells. Impact of microstructure on local carrier lifetime in perovskite solar cells. Science 348, 683–686 (2015). doi:10.1126/science.aaa5333 Medline \n29. K. Abdel-Baki, F. Boitier, H. Diab, G. Lanty, K. Jemli, F. Lédée, D. Garrot, E. Deleporte, J. S. Lauret, Exciton dynamics and non-linearities in two-dimensional hybrid organic perovskites. J. Appl. Phys. 119, 064301 (2016). doi:10.1063/1.4941345 \n30. H. Wang, L. Whittaker-Brooks, G. R. Fleming, Exciton and free charge dynamics of methylammonium lead iodide perovskites are different in the tetragonal and orthorhombic phases. J. Phys. Chem. C 119, 19590–19595 (2015). doi:10.1021/acs.jpcc.5b04403 \n31. Z. Guo, X. Wu, T. Zhu, X. Zhu, L. Huang, Electron–phonon scattering in atomically thin 2D perovskites. ACS Nano 10, 9992–9998 (2016). doi:10.1021/acsnano.6b04265 Medline \n32. D. B. Straus, S. Hurtado Parra, N. Iotov, J. Gebhardt, A. M. Rappe, J. E. Subotnik, J. M. Kikkawa, C. R. Kagan, Direct observation of electron–phonon coupling and slow vibrational relaxation in organic–inorganic hybrid perovskites. J. Am. Chem. Soc. 138, 13798–13801 (2016). doi:10.1021/jacs.6b08175 Medline \n33. O. D. Miller, E. Yablonovitch, S. R. Kurtz, Strong internal and external luminescence as solar cells approach the Shockley-Queisser limit. IEEE J. Photovolt. 2, 303–311 (2012). doi:10.1109/JPHOTOV.2012.2198434 \n34. J. M. Richter, M. Abdi-Jalebi, A. Sadhanala, M. Tabachnyk, J. P. H. Rivett, L. M. Pazos-Outón, K. C. Gödel, M. Price, F. Deschler, R. H. Friend, Enhancing photoluminescence yields in lead halide perovskites by photon recycling and light out-coupling. Nat. Commun. 7, 13941 (2016). doi:10.1038/ncomms13941 Medline \n35. J. C. de Mello, H. F. Wittmann, R. H. Friend, An improved experimental determination of external photoluminescence quantum efficiency. Adv. Mater. 9, 230–232 (1997). doi:10.1002/adma.19970090308 \n36. N. Sestu, M. Cadelano, V. Sarritzu, F. Chen, D. Marongiu, R. Piras, M. Mainas, F. Quochi, M. Saba, A. Mura, G. Bongiovanni, Absorption F-sum rule for the exciton binding energy in methylammonium lead halide perovskites. J. Phys. Chem. Lett. 6, 4566–4572 (2015). doi:10.1021/acs.jpclett.5b02099 Medline \n37. A. Miyata, A. Mitioglu, P. Plochocka, O. Portugall, J. T.-W. Wang, S. D. Stranks, H. J. Snaith, R. J. Nicholas, Direct measurement of the exciton binding energy and effective masses for charge carriers in organic-inorganic tri-halide perovskites. Nat. Phys. 11, 582–587 (2015). doi:10.1038/nphys3357 \n38. J. Even, L. Pedesseau, C. Katan, Analysis of multivalley and multibandgap absorption and enhancement of free carriers related to exciton screening in hybrid perovskites. J. Phys. Chem. C 118, 11566–11572 (2014). doi:10.1021/jp503337a \n39. R. L. Milot, R. J. Sutton, G. E. Eperon, A. A. Haghighirad, J. Martinez Hardigree, L. Miranda, H. J. Snaith, M. B. Johnston, L. M. Herz, Charge-carrier dynamics in 2D hybrid metal–halide perovskites. Nano Lett. 16, 7001–7007 (2016). doi:10.1021/acs.nanolett.6b03114 Medline \n40. H.-H. Fang, F. Wang, S. Adjokatse, N. Zhao, M. A. Loi, Photoluminescence enhancement in formamidinium lead iodide thin films. Adv. Funct. Mater. 26, 4653–4659 (2016). doi:10.1002/adfm.201600715 \n\n# ACKNOWLEDGMENTS \n\nThe work at Los Alamos National Laboratory (LANL) was supported by LANL LDRD program (J-C.B., W.N., S.T., A.D.M.) and was partially performed at the Center for Nonlinear Studies. The work was conducted, in part, at the Center for Integrated Nanotechnologies (CINT), a U.S. Department of Energy, Office of Science user facility. Work at Northwestern University was supported by grant SC0012541 from the U.S. Department of Energy, Office of Science. The work in France was supported by Cellule Energie du CNRS (SOLHYBTRANS Project) and University of Rennes 1 (Action Incitative, Défis Scientifique Emergents 2015). This research used resources of the Center for Functional Nanomaterials, which is a U.S. DOE Office of Science Facility, at Brookhaven National Laboratory under Contract No. DE-SC0012704. Author contributions: J.C.B, A.D.M and J.J.C. conceived the idea, designed the experiments, and wrote the manuscript. H.T. and W.N. fabricated thin-films and performed all device measurements and analysis. J.E, C.K. and S.T. analyzed the data and performed HSE calculations with support from M.K. and L.P. and provided insight into the mechanisms. M.G.K., C.S.S. and C.M.M.S. developed the chemistry for the synthesis of phasepure crystals and provided insight into the chemical origin of the edge states. M.S. and K.A. performed several complementary measurements to provide insight into the mechanisms and to validate the observed findings. P.M.A. provided insights into the origin of edge states. All authors contributed to this work, read the manuscript and agree to its contents, and all data are reported in the main text and supplemental materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/cgi/content/full/science.aal4211/DC1 \nMaterials and Methods \nSupplementary Text \nFigures S1 to S14 \nTables S1 and S2 \nReferences (35–40) \n\n17 November 2016; accepted 22 February 2017 \nPublished online 9 March 2017 \n10.1126/science.aal4211 \n\n![](images/20d611f3a848d5b3ff6387ead96e6e1a5f91e2726f00601c55c2aa061e3d1d76.jpg) \nFig. 1. Evidence of phase-purity of the RPPs $\\scriptstyle\\mathbf{n=1}$ to 5) and comparison of optical properties of thin films and exfoliated crystals. (A) Schematics of the QW like crystal structure showing perovskite layers in the plane $(\\hat{a},\\hat{b})$ sandwiched between organic spacing layers. (B) Phase purity established by monitoring the position and number of the low angle peaks in x-ray diffraction patterns for each n-value. Absorption and photoluminescence (PL) of the thin films (C) and (D) and exfoliated crystals (E) and (F). (G) Optical band gap derived from absorption (open symbols) and PL (full symbols) as a function of n. (inset) Shift of the optical band gap in thin films with respect to exfoliated crystals (from absorption). (H) PL linewidth versus n showing inhomogeneous broadening in thin films as compared to exfoliated crystals. \n\n![](images/c4cec9079a7dddd01d3af4f0cf8ee69ca76f664802482f9ebe2c3dc8fa0f3dc0.jpg) \nFig. 2. Microscopic origin of the low-energy band gap in 2D perovskite thin films for $\\scriptstyle{\\mathsf{n}}=3$ . (A) PL intensity map of a single exfoliated crystal, probed at 2.010 eV and 1.680 eV. (Right) Microscopy image showing the layer edges of the exfoliated crystal. Scale bar is $10\\upmu\\mathrm{m}$ . (B) Comparison of the PL in the exfoliated crystal, at the exfoliated crystal edges, and in the corresponding thin film. (C) PLE integrated signal of the LES, measured by locally exciting the exfoliated crystal edges. The measured PL profile of the LES is also plotted. (D) TRPL of the PL features X and LES observed in (B) and (C). (E) Schematics of the photo-absorption and PL processes in 2D perovskite exfoliated crystals with $n{>}2$ . \n\n![](images/5078a4731dc616e0fa5d866a19ec51aa38bfe6f354727c3ff3f1517d3746fa5f.jpg) \nFig. 3. Optical absorption and emission mechanisms in thin films of 2D perovskites. (A) Thin film $\\scriptstyle{\\mathsf{n}}=3$ absorption (green), PL at photoexcitation 100 mW/cm2 (black) and $10^{6}\\mathrm{\\mW/cm^{2}}$ (red). (B) Lightexcitation intensity (I0) dependence of the integrated PL. Dashed lines are fits to the data. (C) TRPL in the thin films $\\scriptstyle\\mathsf{n}=3$ . (Inset) Corresponding lifetimes of the X-states and LES as a function of the n-value. Excitation at ${\\sim}100\\ \\mathrm{\\mW/cm^{2}}$ . (D) Schematics of the photo-absorption and PL processes in a 2D perovskite thin film with $n{>}2$ . In contrast to exfoliated crystals, thin film perovskite layers are preferentially oriented normal to the substrate (fig. S10) (12, 17), therefore excitation light probes numerous amount of LES. (E) Summary of the main photoemission mechanisms in thin films. The diffusion length was estimated from fig. S13 (17). \n\n![](images/134f4eec7e8e7a16a0e9ddaaad6f670d1b82384343b019b80defc553b73c8306.jpg) \nFig. 4. Figures of merit of thin film devices for light-harvesting and solid-state emission. (A) J-V characteristics measured under AM1.5 illumination. (B) Power conversion efficiency as a function of 2D perovskite n-value (QW thickness). (C) External quantum efficiency for the PV devices in A. (D) PL quantum yield (PLQY) in thin films as a function of n-value for several light excitation intensity. \n\nExtremely efficient internal exciton dissociation through edge states in layered 2D perovskites \nJ.-C. Blancon, H. Tsai, W. Nie, C. C. Stoumpos, L. Pedesseau, C. Katan, M. Kepenekian, C. M. M. Soe, K. Appavoo, M. Y. Sfeir, S. Tretiak, P. M. Ajayan, M. G. Kanatzidis, J. Even, J. J. Crochet and A. D. Mohite (March 9, 2017) \npublished online March 9, 2017 \n\nThis copy is for your personal, non-commercial use only. \n\n# Article Tools \n\nVisit the online version of this article to access the personalization and article tools: http://science.sciencemag.org/content/early/2017/03/08/science.aal4211 \n\n# Permissions \n\nObtain information about reproducing this article: http://www.sciencemag.org/about/permissions.dtl " + }, + { + "id": "10.1021_acsenergylett.7b00236", + "DOI": "10.1021/acsenergylett.7b00236", + "DOI Link": "http://dx.doi.org/10.1021/acsenergylett.7b00236", + "Relative Dir Path": "mds/10.1021_acsenergylett.7b00236", + "Article Title": "Recombination in Perovskite Solar Cells: Significance of Grain Boundaries, Interface Traps, and Defect Ions", + "Authors": "Sherkar, TS; Momblona, C; Gil-Escrig, L; Avila, J; Sessolo, M; Bolink, HJ; Koster, LJA", + "Source Title": "ACS ENERGY LETTERS", + "Abstract": "Trap-assisted recombination, despite being lower as compared with traditional inorganic solar cells, is still the dominullt recombination mechanism in perovskite solar cells (PSCs) and limits their efficiency. We investigate the attributes of the primary trap assisted recombination channels (grain boundaries and interfaces) and their correlation to defect ions in PSCs. We achieve this by using a validated device model to fit the simulations to the experimental data of efficient vacuum-deposited p-i-n and n-i-p CH3NH3PbI3 solar cells, including the light intensity dependence of the open circuit voltage and fill factor. We find that, despite the presence of traps at interfaces and grain boundaries (GBs), their neutral (when filled with photogenerated charges) disposition along with the long-lived nature of holes leads to the high performance of PSCs. The sign of the traps (when filled) is of little importance in efficient solar cells with compact morphologies (fused GBs, low trap density). On the other hand, solar cells with noncompact morphologies (open GBs, high trap density) are sensitive to the sign of the traps and hence to the cell preparation methods. Even in the presence of traps at GBs, trap-assisted recombination at interfaces (between the transport layers and the perovskite) is the dominullt loss mechanism. We find a direct correlation between the density of traps, the density of mobile ionic defects, and the degree of hysteresis observed in the current voltage (J-V) characteristics. The presence of defect states or mobile ions not only limits the device performance but also plays a role in the J-V hysteresis.", + "Times Cited, WoS Core": 917, + "Times Cited, All Databases": 955, + "Publication Year": 2017, + "Research Areas": "Chemistry; Electrochemistry; Energy & Fuels; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000401500200040", + "Markdown": "# Recombination in Perovskite Solar Cells: Significance of Grain Boundaries, Interface Traps, and Defect Ions \n\nTejas S. Sherkar,† Cristina Momblona,‡ Lidón Gil-Escrig,‡ Jorge Ávila,‡ Michele Sessolo,‡ Henk J. Bolink, $\\sharp\\oplus$ and L. Jan Anton Koster\\*,† \n\n†Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 4, 9747AG Groningen, The Netherlands ‡Instituto de Ciencia Molecular, Universidad de Valencia, C/Catedrático J. Beltrán 2, 46980 Paterna Valencia, Spain \n\nSupporting Information \n\nABSTRACT: Trap-assisted recombination, despite being lower as compared with traditional inorganic solar cells, is still the dominant recombination mechanism in perovskite solar cells (PSCs) and limits their efficiency. We investigate the attributes of the primary trapassisted recombination channels (grain boundaries and interfaces) and their correlation to defect ions in PSCs. We achieve this by using a validated device model to fit the simulations to the experimental data of efficient vacuum-deposited $\\mathbf{p}{-}\\mathbf{i}{-}\\mathbf{n}$ and $\\mathbf{n}{-}\\mathbf{i}{-}\\mathbf{p}$ $\\mathbf{CH}_{3}\\mathbf{NH}_{3}\\mathbf{PbI}_{3}$ solar cells, including the light intensity dependence of the opencircuit voltage and fill factor. We find that, despite the presence of traps at interfaces and grain boundaries $\\mathbf{\\Gamma}(\\mathbf{GB}\\mathbf{s})$ , their neutral (when filled with photogenerated charges) disposition along with the longlived nature of holes leads to the high performance of PSCs. The sign of the traps (when filled) is of little importance in efficient solar cells with compact morphologies (fused GBs, low trap density). On the other hand, solar cells with noncompact morphologies (open GBs, high trap density) are sensitive to the sign of the traps and hence to the cell preparation methods. Even in the presence of traps at GBs, trap-assisted recombination at interfaces (between the transport layers and the perovskite) is the dominant loss mechanism. We find a direct correlation between the density of traps, the density of mobile ionic defects, and the degree of hysteresis observed in the current−voltage $\\left(J-V\\right)$ characteristics. The presence of defect states or mobile ions not only limits the device performance but also plays a role in the $J{-}V$ hysteresis. \n\n![](images/c66bdbd11127c8097b7391291d55cdef7a9030e6f5e3518b5909e3270c494911.jpg) \n\nperovskites, $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Pb}\\mathrm{X}_{3}$ $\\mathrm{(X~=~Cl,}$ Br, I), as a photoactive material show device power conversion efficiencies upward of $22\\%$ .1 High device efficiency arises from the many desirable properties of perovskites, including a high absorption coefficient, high carrier mobilities, and long charge carrier diffusion lengths.2−4 Efficient perovskite solar cells (PSCs) can be prepared by vacuum deposition5,6 and solution processing7,8 and in $\\mathrm{{\\ttp}-i-n}$ as well as $\\mathtt{n-i-p}$ configurations.9 While the efficiency of PSCs is high, it is still far from the theoretical maximum $(31\\%)$ .10 One of the reasons (others being optical losses, nonideal transport layers, and contact energy offsets) is the recombination of charge carriers in the device, which reduces the fill factor (FF) and the open-circuit voltage $(V_{\\mathrm{OC}})$ of the solar cell. At solar fluences, radiative recombination (between free electrons and free holes) is weak in PSCs.11 On the other hand, nonradiative recombination has been shown to be the dominant recombination mechanism in $\\mathrm{PSCs},^{12,13}$ which limits the efficiency of existing PSCs.14,15 \n\nNonradiative recombination takes place when a electron (or hole) trapped in a defect/impurity (energy level in the band gap of the perovskite) recombines with a hole (or electron) in the valence (or conduction) band of the perovskite. In polycrystalline perovskite thin films, defects or impurities are likely to be concentrated at grain boundaries (GBs) and at film surfaces.16−18 The surface of the photoactive perovskite in PSCs is covered with ETL and $\\mathrm{\\bfHTL},$ which forms an interface. While nonradiative recombination at interfaces has been shown to severely influence the PSC performance,15 the role of the GBs on the overall device performance is still under debate.19−22 A few studies suggest that traps at GBs lead to increased trap-assisted recombination,23,24 insulating products (e.g., $\\mathrm{PbI}_{2}^{\\cdot}$ ) formed at GBs passivate the traps and hence minimize trap-assisted recombinatio n,19,20 and GBs act as hole transport highways, which leads to improved hole collection.21 With the nature of GBs possibly changing with processing conditions and stoichiometry ,22,25 it is important to investigate their role on the charge carrier dynamics in PSCs and quantify their influence (detrimental or otherwise) on the device performance. This would help to identify appropriate approaches for further increasing the efficiency of PSCs. \n\nGBs are ubiquitous in polycrystalline films and are formed due to a break in the crystal structure of the material. The different orientations of neighboring crystal grains give rise to dislocations, misplaced atoms (interstitials), vacancies, distorted bond angles, and bond distances at the GBs.26 These GBs are known to play a critical role in the charge carrier dynamics and photophysics of CdTe, poly-Si, and copper indium gallium selenide (CIGS) thin films used in solar cells.27−30 Several GB models exist in the literature to explain their influence on the charge carrier dynamics in inorganic polycrystalline solar cells.31−33 However, hybrid perovskites are different from the above-mentioned inorganic photovoltaic materials in terms of doping levels and the nature of GB defect traps. Perovskites are lightly doped materials, and due to the presence of charged ionic defects, it is likely that the traps are electrically charged when empty34−36 and neutral when filled with photogenerated charges. A different perspective to GB physics is thus essential in the case of PSCs. It could help answer the question, is there a need to move toward single-crystalline materials or are polycrystalline films prepared using existing methods sufficient to achieve high-performing PSCs? \n\nIn this Letter, we investigate the attributes of the primary trap-assisted recombination channels, namely, GBs and interfaces, and their correlation to ionic defects in existing PSCs. We accomplish this by using our device model15 to fit the simulation to the experimental data of vacuum-deposited $\\mathtt{p-i-n}$ and $\\mathrm{n-i-p\\CH_{3}N H_{3}P b I_{3}}$ solar cells.9 The model takes as input the full experimental data sets, and the only free parameters (to fit) are the carrier mobility in the perovskite and the trap density plus the charge capture coefficients. The model achieves excellent agreement with the experimental measurements (for both $\\mathtt{p-i-n}$ and $\\mathtt{n-i-p}$ cells), including the light intensity dependence of the $V_{\\mathrm{OC}}$ and FF. We find that we can quantitatively describe all of the experimental data set only when we consider trap-assisted recombination at GBs and predominantly at interfaces (HTL/perovskite and perovskite/ ETL) and weak bimolecular recombination in the perovskite absorber, ruling out the scenario of strong bulk trap-assisted recombination in the perovskite. Despite the presence of traps, their neutral (when filled) disposition along with the long-lived nature of holes leads to the high performance of PSCs. The sign (if charged or neutral when filled) of traps is of little importance in efficient solar cells with compact morphologies (fused GBs, low trap density). On the other hand, solar cells that have noncompact morphologies (open GBs, high trap density) are sensitive to the sign of the traps and hence to the preparation methods (e.g., under/overstoichiometric routes, environmental conditions). Even in the presence of traps at GBs, trap-assisted recombination at interfaces is the dominant recombination channel. Finally, we simulate fast forward/ reverse current−voltage $\\left(J-V\\right)$ scans, which reveal little $J{-}V$ hysteresis, consistent with that observed experimentally for the $\\mathtt{p-i-n}$ cell.9 We observe direct correlation between the density of traps, the density of mobile ionic defects, and the degree of hysteresis in PSCs. Defect states (or mobile ions) not only retard the device performance but also play a role in the $J{-}V$ hysteresis. Finally, we give an estimate of the mobile ion density in this specific set of solar cells studied here. \n\nThe experimental data considered in this Letter were obtained from full vacuum-deposited $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ devices prepared by some of the authors and published recently.9 Both $\\mathrm{{\\ttp}-i-n}$ and $\\mathtt{n-i-p}$ device configurations are studied (Figure 1), where i is the perovskite absorber layer, $\\boldsymbol{\\mathrm{\\tt~p\\}}$ is the hole transport layer (HTL), and n is the electron transport layer (ETL). For the $\\mathrm{{\\ttp}-i-n}$ cell, indium tin oxide (ITO) and silver $(\\mathrm{Ag})$ are used as the anode and cathode, respectively, and for the $\\mathtt{n-i-p}$ cell, the anode is gold $\\left(\\mathrm{Au}\\right)$ and the cathode is ITO. The HTL is composed of a $10~\\mathrm{\\nm}$ thick film of $N4,N4,N4^{\\prime\\prime},N4^{\\prime\\prime}$ - tetra( $[1,1^{\\prime}$ -biphenyl]-4-yl)- $[1,1^{\\prime}{:}4^{\\prime},1^{\\prime\\prime}$ -terphenyl]- $^{4,4^{\\prime\\prime}}$ -diamine (TaTm) in contact with the perovskite, followed by a $40\\ \\mathrm{nm}$ thick TaTm film doped with $^{2,2^{\\prime}}$ -(perfluoronaphthalene-2,6- diylidene) dimalononitrile $\\left(\\mathrm{F}_{6}{\\mathrm{-}}\\mathrm{TCNNQ}\\right)$ in contact with the anode. Analogously, the ETL comprises an undoped $\\mathrm{C}_{60}$ fullerene film ( $\\mathbf{\\hat{\\Pi}}_{10\\ \\mathrm{nm}})$ and a $\\mathrm{C}_{60}$ layer $\\left(40\\ \\mathrm{nm}\\right)$ doped with N1,N4-bis(tri- $p$ -tolylphosphoranylidene)-benzene-1,4-diamine $\\left(\\mathrm{PhIm}\\right)$ in contact with the cathode. The perovskite $\\left(\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}\\right)$ thin films are prepared by co-evaporation of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ and $\\mathrm{PbI}_{2}$ in a vacuum chamber, to a final thickness of $500\\mathrm{nm}$ . The perovskite shows a band-to-band transition at 780 nm, which translates into a band gap $(E_{\\mathrm{gap}})$ of $1.59\\mathrm{eV.}$ 9 The $\\mathrm{{\\ttp-}}$ $\\mathrm{i}{-}\\mathrm{n}$ and $\\mathtt{n-i-p}$ solar cells show efficiencies of around 16 and $18\\%$ , respectively, with a record efficiency of $20.3\\%$ using the $\\mathtt{n-i-p}$ configuration.9 Doping of HTL and ETL increases their conductivity and also increases the electric field strength in the perovskite layer, resulting in efficient charge extraction from the perovskite to the external contacts.9,15 This is reflected in a high FF and $V_{\\mathrm{OC}}$ for both $\\mathtt{p-i-n}$ and $\\mathtt{n-i-p}$ cells.9 \n\n![](images/ef9a31107f6955e6533c4a2a4463b9734dd846917d0a02847b8c87c5422029da.jpg) \nFigure 1. (a) Schematics of the vacuum-deposited perovskite cells used and (b) scanning electron microscope (SEM) image of the $\\mathbf{CH}_{3}\\mathbf{NH}_{3}\\mathbf{PbI}_{3}$ surface. \n\nWe recently developed a device model15 that describes the operation of PSCs and quantitatively explains the role of contacts, the ETL and HTL, charge generation, transport of charge carriers, and recombination. Our 1D device model is based on the drift−diffusion equations for electrons and holes throughout the device and on solving the Poisson equation in one dimension. In the perovskite layer, the absorption of light generates free electrons and holes. The transport of these free charges is governed by drift−diffusion and electrically induced drift; for electrons37 \n\n![](images/87aed7703928634d1902c5cf264742c8acbae6667d279e2494bc32436a2425c4.jpg) \nFigure 2. (a) In typical inorganic solar cells (poly-Si, CdTe), the empty neutral traps at GBs and interfaces when filled with electrons result in a weakened transport due to the potential barrier $(q\\phi_{\\mathrm{B}})$ and the nonradiative recombination between holes and trapped electrons is strong. (b) In PSCs, it is likely that the empty traps are positively charged due to accumulated iodide vacancies $\\left(V_{\\mathrm{I}}^{+}\\right)$ at GBs and interfaces. Therefore, when filled with electrons, the traps are neutral, electron transport is relatively unaffected, and nonradiative recombination is weak. \n\n$$\nJ_{n}=-q n\\mu_{n}{\\frac{\\partial V}{\\partial x}}+q D_{n}{\\frac{\\partial n}{\\partial x}}\n$$ \n\nand for holes \n\n$$\nJ_{p}=-q p\\mu_{p}{\\frac{\\partial V}{\\partial x}}-q D_{p}{\\frac{\\partial p}{\\partial x}}\n$$ \n\nwhere $J_{n}$ and $J_{p}$ are electron and hole current densities, respectively, $q$ is the electronic charge $\\left(1.602\\times10^{-19}\\mathrm{~C}\\right)$ , $V$ is the electrostatic potential, $n$ and $p$ are electron and hole concentrations, $\\textstyle\\mu_{n}$ and $\\mu_{p}$ are electron and hole mobilities, and $D_{n}$ and $D_{p}$ are electron and hole diffusion constants, respectively. The diffusion constants are assumed to obey the Einstein relation.37 \n\nThe defect ion current density $\\left(J_{\\mathrm{a}},\\right.$ anion; $J_{\\mathrm{c}},$ cation) is also given by the equations above. However, because the electrodes are ion-blocking, $J_{\\mathrm{{a}}}=J_{\\mathrm{{c}}}=0$ . \n\nThe electric potential throughout the device is solved from the Poisson equation \n\n$$\n\\frac{\\partial}{\\partial x}\\bigg(\\in\\frac{\\partial V}{\\partial x}\\bigg)=-q\\big(p-n+N_{D}^{+}-N_{A}^{-}+X_{c}-X_{\\mathrm{a}}+Q_{\\mathrm{T}}\\Sigma_{\\mathrm{T}}f_{\\mathrm{T}}\\big)\n$$ \n\nwhere $\\epsilon$ is the permittivity, $N_{A}^{-}$ and $N_{D}^{+}$ are the ionized p-type and $\\mathfrak{n}$ -type doping, respectively, and $X_{\\mathrm{c}}$ and $X_{\\mathrm{a}}$ are the cationic and anionic defect densities, $^{36,38-4\\bar{0}}$ respectively, in the perovskite absorber. The trap density is $\\Sigma_{\\mathrm{T}},$ the sign of the trap when filled is $Q_{\\mathrm{T}}\\in\\{-1,\\ 0,\\ 1\\},$ and the occupation probability of the trap is $f_{\\mathrm{T},\\nu=n,p},$ which is given by \n\n$$\nf_{\\mathrm{T},\\nu=n,p}=\\left[1+\\left(\\frac{g_{_{0,\\nu}}^{\\phantom{}}}{g_{_{1,\\nu}}^{\\phantom{}}}\\right)\\left(\\frac{\\nu}{N_{\\mathrm{cv}}^{\\phantom{}}}\\exp(E_{\\mathrm{trap}}/V_{\\mathrm{t}}^{\\phantom{}})\\right)^{\\alpha}\\right]^{-1}\n$$ \n\nwhere $g_{0,1}$ are the degeneracy factors of empty and filled trap levels, respectively, $N_{\\mathrm{cv}}$ is the effective density of states of both the conduction and valence band, $E_{\\mathrm{trap}}\\left(=E_{\\mathrm{gap}}/2\\right)$ is the midgap trap energy level, $\\alpha$ is the sign of the trapped charge carrier (1 for holes, $^{-1}$ for electrons), and $V_{\\mathrm{t}}=k T/q$ is the thermal voltage, with $k$ being the Boltzmann constant and $T$ the temperature. We neglect the degeneracy of traps and set $g_{0}/g_{1}=$ 1. \n\nThe boundary condition on the electrostatic potential is \n\n$$\nq(V(L)-V(0)+V_{\\mathrm{app}})=W_{\\mathrm{c}}-W_{\\mathrm{a}}\n$$ \n\nwith $V_{\\mathrm{app}}$ being the externally applied voltage and $W_{\\mathrm{a}}$ and $W_{\\mathrm{c}}$ the anode and cathode work functions, respectively. The builtin potential is then given by $V_{\\mathrm{bi}}=\\big(W_{\\mathrm{c}}-\\mathbf{\\bar{W}}_{\\mathrm{a}}\\big)/q$ . \n\nThe boundary conditions for charge carrier densities at electrode contacts are given by15 \n\n$$\nn,p=N_{\\mathrm{cv}}\\exp(-\\phi_{n,p}/V_{t})\n$$ \n\nwhere $\\phi_{n,p}$ is the offset $(\\mathrm{in\\eV})$ between the cathode (anode) work function and the conduction (valence) band of the perovskite. \n\nThe generated charge carriers in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ can recombine via both bimolecular and trap-assisted mechanisms. The bimolecular recombination rate $(R_{\\mathrm{BR}}^{-})$ is given by \n\n$$\nR_{\\mathrm{BR}}=k_{\\mathrm{BR}}(n p-{n_{\\mathrm{i}}}^{2})\n$$ \n\nwhere $k_{\\mathrm{BR}}$ is the bimolecular recombination constant and $n_{\\mathrm{i}}$ is the intrinsic carrier concentration. The trap-assisted recombination rate $(R_{\\mathrm{SRH}})$ is given by the Shockley−Read−Hall (SRH) equation37 \n\n$$\nR_{\\mathrm{SRH}}={\\frac{C_{n}C_{p}\\Sigma_{\\mathrm{T}}}{C_{n}(n+n_{1})+C_{p}(p+p_{1})}}{\\left(n p-n_{\\mathrm{i}}^{2}\\right)}\n$$ \n\nwhere $C_{n}$ and $C_{p}$ are the capture coefficients for electrons and holes, respectively. $C_{n}$ denotes the probability per unit time that the electron in the conduction band will be captured for the case that the trap is filled with a hole and able to capture the electron. Correspondingly, $C_{p}$ denotes the probability per unit time that the hole in the valence band will be captured when the trap is filled with a electron and able to capture the hole. The constants $n_{1}$ and $p_{1}$ are defined as \n\n$$\nn_{1}=n(f_{\\mathrm{T},n}^{-1}-1)\\qquad\\quad p_{1}=p(f_{\\mathrm{T},p}^{-1}-1)^{-1}\n$$ \n\nThe interface traps are located in a $2\\mathrm{nm}$ thick region at $\\mathrm{HTL}/$ perovskite $\\left(\\Sigma_{\\mathrm{T},p}\\right)$ and perovskite/ETL $\\left(\\Sigma_{\\mathrm{T},n}\\right)$ material interfaces and operate as recombination centers.15 Recombination is most effective when traps are located midgap, and it is shown that recombination dynamics for an arbitrary distribution of traps near the middle of the band gap is identical.41 \n\nThe details of the slow (“stabilized”) $J{-}V$ scans used to fit to the experimental data, fast forward/reverse $J{-}V$ scans, and hysteresis simulations, which include preconditioning, are presented in the Supporting Information (SI). \n\nThe numerical approaches and procedures to solve the above-mentioned equations can be found in refs 15 and 42. \n\nDefects and impurities located at GBs and surfaces can act as traps for photogenerated charge carriers. In hybrid PSCs, electrons are the trapped carriers.12,43,44 A negative GB is formed when electrons fill the empty uncharged GB traps, and a neutral GB is formed when electrons fill the empty charged traps. Figure 2 shows the case of a filled negative and a filled neutral GB. It is clear that GBs can act as (1) potential barriers $\\left(E_{\\mathrm{B}}=q\\phi_{\\mathrm{B}}\\right)$ for electrons, which impedes their transport from one crystallite to another and thus affects their long-range mobility, and (2) recombination centers where the trapped electrons recombine nonradiatively with free holes in the valence band. Because hybrid perovskites are ionic conductors, the associated traps are expected to be electrically charged.34−36 \n\n![](images/f673578c33bd8d68649925d753f647f3b84949a00644530e620428b84426a886.jpg) \nFigure 3. The $\\mathbf{p}{-}\\mathbf{i}{-}\\mathbf{n}$ device skeleton showing the energy levels, interface traps (red), and GBs (dashed lines). Upon illumination, free electrons and holes are transported through the respective materials and are extracted at the electrodes. \n\nPositively charged iodide vacancies $\\left(V_{\\mathrm{I}}^{+}\\right)$ are the dominant defect ions, as indicated by recent theoretical studies.35,38 Migration of these defect ions has been shown to occur via the GBs rather than the crystal bulk.16 GBs typically show weak emission in photoluminescence (PL) measurements,23,45 suggesting trapping and nonradiative recombination of carriers. It is therefore likely that accumulation of $\\boldsymbol{V}_{\\mathrm{I}}^{+}$ at GBs and surfaces (or interfaces) induces trap states that act as recombination centers for photogenerated carriers. Few theoretical studies predict the iodide vacancies to have energy states outside of the band gap;46 however, these calculations are performed considering iodide vacancies as bulk point defects. The more relevant and performance-limiting features are the GBs and interfaces (or surfaces) where iodide vacancies and ions are most likely to reside at in thin films.16,20 Many recent experimental results point to the trapping nature of the accumulated iodide vacancies at GBs and interfaces.43,45,47 A recently published theoretical study looked at carrier trapping at surface defects and reported that iodide vacancies do exhibit energy states inside of the band gap.48 Therefore, we assume that the GB traps (accumulated $\\dot{V}_{\\mathrm{I}}^{+}$ ) when filled with charge carriers (electrons) are likely to be electrically neutral. Filled neutral traps are less likely to lead to rapid recombination as compared to filled charged traps, confirming the light-soaking experiments in PSCs where trap filling by photogenerated charges reduces the trap-assisted recombination in the device.47 \n\nA refinement of our full 3D drift−diffusion simulation49 is currently a work in progress to take into account the accumulation of ionic defects at 3D GBs to explain the recently reported anomalous photovoltaic effect.50 \n\nIn our devices, the experimentally observed crystal size is ${\\sim}100~\\mathrm{nm}$ on average.9 Therefore, we incorporate GBs in our device model and place them $L_{\\mathrm{GB}}=100\\ \\mathrm{nm}$ apart along the thickness of the perovskite absorber. The traps at GBs $(\\Sigma_{\\mathrm{T},\\mathrm{GB}})$ and at interfaces $\\left(\\Sigma_{\\mathrm{T},p},\\ \\Sigma_{\\mathrm{T},n}\\right)$ are charged when empty and neutral when filled. Because the device is electrically neutral in the dark, we assume in the model that the charged empty traps (accumulated $V_{\\mathrm{I}}^{+}$ ) are compensated by an equal density (volume) of mobile iodide ions given by \n\n$$\nX_{\\mathrm{a}}=(n_{\\mathrm{GB}}\\times\\Sigma_{\\mathrm{T,GB}}+\\Sigma_{\\mathrm{T},n}+\\Sigma_{\\mathrm{T},p})/L_{\\mathrm{abs}}\n$$ \n\nwhere $n_{\\mathrm{GB}}$ is the number of GBs along the absorber thickness $(L_{\\mathrm{abs}})$ . This makes the perovskite slightly p-type, in agreement with the literature.43,44,51 The distribution of these mobile iodide ions in the perovskite layer is solved from the coupled continuity and Poisson equation discussed before and according to the device operating conditions (i.e., external bias, illumination, preconditioning), as detailed in SI. \n\nNow, we fit the simulations to the experimental data of both $\\mathtt{p-i-n}$ and $\\mathtt{n-i-p}$ solar cells prepared by vacuum deposition.9 The $\\mathrm{{\\ttp}-i-n}$ device skeleton is shown in Figure 3. In the $\\mathtt{n-i-p}$ device, the p and n layers are interchanged by reversing the order of vacuum deposition of the same materials.9 The only difference is the top metal contact, silver $(\\mathrm{Ag})$ for the $\\mathrm{{\\ttp}-i-n}$ cell and gold (Au) for the $\\mathtt{n{-i{-p}}}$ cell. The model takes as input an extensive experimental data set (Table 1), and the only free parameters (to fit) are the carrier mobility in the perovskite and the trap density plus the charge capture coefficients. \n\nWe find that the model achieves quantitative agreement with the experimental data sets (both $\\mathtt{p-i-n}$ and $\\mathtt{n-i-p}$ cell) only when we consider (i) trap-assisted recombination at interfaces (HTL/perovskite and perovskite/ETL), (ii) trap-assisted recombination at GBs, and (ii) weak bimolecular recombination in the perovskite layer. When we considered other scenarios, mainly of bulk trap-assisted recombination in the perovskite, the simulations did not fit the experimental data of the light intensity dependence of the $V_{\\mathrm{OC}}$ and FF. The FF is more sensitive to the location and strength of different recombination channels in the device. For example, if we consider bulk trap-assisted recombination in simulations, the FF shows a positive dependence on light intensity. However, in our devices, we see the FF initially increasing and then decreasing with lowering of light intensity. Therefore, we rule out bulk trap-assisted recombination in perovskite as a primary recombination channel and a (device) performance-limiting attribute. \n\nThe experimental data under “stabilized” conditions (slow scan) for both $\\mathtt{p-i-n}$ and $\\mathtt{n-i-p}$ cells are shown in Figure 4a. The devices are illuminated by a standard AM 1.5G light source. Figure 4a also shows the fit to the experimental $J{-}V$ characteristics of both cells. The simulated fit is also performed under “stabilized” conditions, that is, an infinitely slow $J{-}V$ scan, where all mobile ions (calculated from eq 10) are redistributed in the perovskite layer according to the steadystate operating condition (applied bias, illumination) during the scan. In order to fit the simulation to the experimental data, we find that we need weak bimolecular recombination in the perovskite bulk and trap-assisted recombination at interfaces (HTL/perovskite and perovskite/ETL) and at GBs. The simulation of $\\mathtt{p-i-n}$ and $\\mathtt{n-i-p}$ cells is performed using the same set of device parameters, including all of the fitting parameters. The only change is the removal of the hole energetic offset $(0.1~\\mathrm{eV})$ in $\\mathsf{n{-i{-}\\mathsf{p}}}$ cells where gold is used as the anode as compared to ITO as the anode in the $\\mathtt{p-i-n}$ cell, which has a lower work function than gold $\\left(\\mathrm{Au}\\right)$ .9 The calculated charge generation profile in both cells is shown in Figure 4b. The material optical constants $(\\eta,\\kappa)$ as input to the transfer matrix model52 in order to calculate the generation profile in $\\mathtt{p\\mathrm{-i\\mathrm{-}n}}$ and $\\mathtt{n-i-p}$ cells are obtained from the literature and are provided in the SI. Table 1 lists all of the device parameters used in the simulation to fit to the experimental data. The only free parameters (to fit) are the carrier mobility in the perovskite and the trap density plus the charge capture coefficients. The maximum generation rate $\\left({G_{\\mathrm{max}}}\\right)$ is calculated by the transfer matrix model52 and corresponds to a maximum short-circuit current density of $19.9\\ \\mathrm{\\hat{mA}}/\\mathrm{cm}^{2}$ . The charge carrier mobilities extracted from the fit are in agreement with reported values for $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ solar cells.11,23 Bimolecular recombination takes place in the perovskite bulk with the recombination coefficient $1\\times10^{-9}$ $\\mathrm{{\\dot{c}m}}^{3}\\ s^{-1}$ .11 Trap-assisted recombination takes place at material interfaces (HTL/perovskite and perovskite/ETL) and at GBs. Here, $C_{p}
parameter symbolvalue
perovskite band gapEgap1.59 eVref 9
density of states (DOS)Nv3.1 × 10l8 cm-3
perovskite conduction band minimumE。-5.43eVref 9
perovskite valence band maximumE,-3.84eVref 9
TaTm HOMO levelEHOMO-5.4 eVref 9
C60 LUMO levelELUMO-4.0 eVref 53
built-in voltageVbi1.4Vref 9
hole mobility in TaTm (HTL)μp4 × 10-3 cm²/(V s)
electron mobility in C60 (ETL)μn3 × 10-² cm²/(V s)ref 53
perovskite relative permittivity24.1ref 54
TaTm relative permittivity3
C60 relative permittivity∈n3.9ref 55
ionized doping in C60/PhImND5 × 10l8 cm-3ref 9
ionized doping in TaTm/FTCNNQNA1 × 10l6 cm-3ref 9
bimolecular recombination constantkBR1 × 10-9 cm s-1ref 11
electron and hole mobility in perovskiteμnp5 cm²/(V s)fit
HTL/perovskite interface trap density1 × 10l° cm-2fit
perovskite/ETL interface trap densityT2 × 10° cm-2fit
GB trap densityT,GB1.8 X 10° cm-2fit
electron and hole capture coefficientsCm Cp1 × 10-,1× 10-8 cm3 s-1fit
number of grid points1000
grid spacing△x0.6 nm 5.4 × 10²1 cm-3 s-1
maximum charge generation rateGmax
\n\nEven in the presence of traps at GBs in the perovskite layer, trap-assisted recombination at interfaces is the dominant loss mechanism, in agreement with our previous report.15 At solar fluences, traps at GBs are filled with photogenerated charges and become neutral and hence do not act as space charge. In addition, due to the low trap density at GBs and the existence of an alternate pathway (bimolecular) for charge carriers to recombine, GBs are benign at solar fluences. \n\nAs seen in Figure 4a, the $\\mathtt{n-i-p}$ cell shows improved performance with the $V_{\\mathrm{OC}}$ and FF reaching $1.12\\mathrm{~V~}$ and $81\\%$ , respectively. From the fit parameters in Table 1, the trap density at the HTL/perovskite interface (which is the front interface for the $\\mathtt{p-i-n}$ cell) is higher than that at the perovskite/ETL interface (which is the front interface for the $\\mathtt{n-i-p}$ cell). Because the quality of the front interface has a greater impact on the device performance,15 the $\\mathtt{n-i-p}$ cell performs better. The enhanced performance of the $\\mathtt{n-i-p}$ cell also derives from the higher conductivity of the doped ETL as compared to doped $\\mathrm{{HTL},}$ which boosts charge extraction at the front interface, and in part due to the use of gold $\\left(\\mathrm{Au}\\right)$ as the anode, which eliminates the hole energetic offset that is otherwise present in the $\\mathtt{p-i-n}$ cell where ITO is used as the anode.9 \n\nThe light intensity dependence of the $V_{\\mathrm{OC}}$ and FF for both $\\mathrm{{\\ttp}-i-n}$ and $\\mathtt{n-i-p}$ cells is shown in Figure 5a,b. The light intensity dependence of $V_{\\mathrm{OC}}$ reveals the dominant mechanism in solar cells, with slopes of $k T/q$ and $2k T/q$ indicating dominant bimolecular and trap-assisted recombination, respectively.56,57 Due to the superior quality of the front interface in the $\\mathtt{n-i-p}$ cell, trap-assisted recombination is suppressed $(\\mathrm{slope}=1.55k T/q)$ as compared to the $\\mathtt{p\\mathrm{-i\\mathrm{-}n}}$ cell (slope $\\mathbf{\\Sigma}=\\mathbf{\\Sigma}$ $2.1k T/q,$ ). Under open-circuit conditions, no current (hence no power) is extracted from the solar cell. As a solar cell is operated close to maximum power, the FF is the more relevant characteristic. The light intensity dependence of the FF trend reveals that there is some competition between bimolecular and trap-assisted recombination in these cells. In a pure bimolecular recombination scenario, FF increases with decreasing light intensity as the recombination rate is proportional to the product of charge carrier densities (which decreases with decreasing light intensity). For a pure trap-assisted recombination scenario, FF decreases with decreasing light intensity as the proportion of free charges recombining with trapped charges (the number of traps remains the same) increases with decreasing light intensity. Now, as can be seen in Figure 5b, bimolecular recombination dominates for light intensities above $0.1\\ \\mathrm{Sun}_{;}$ , while trap-assisted recombination does so below 0.1 Sun. The FF is more sensitive (as compared to $V_{\\mathrm{OC},}$ ) to leakage at lower light intensities58 and hence the anomalous FF value of the $\\mathtt{p-i-n}$ cell at 0.001 Sun. \n\n![](images/2c983d82cd9d775d39299fdb8204328a52231e324ede5c0c32da5d1bdcfe5176.jpg) \nFigure 4. (a) $J{-}V$ characteristics of $\\mathbf{p}{-}\\mathbf{i}{-}\\mathbf{n}$ and $\\mathbf{n-i-p}$ PSCs. The open symbols are experimental data for vacuum-deposited $\\mathbf{CH}_{3}\\mathbf{NH}_{3}\\mathbf{PbI}_{3}$ solar cells.9 The solid lines represent the simulations. (b) Normalized generation profile for the $\\mathbf{p}{-}\\mathbf{i}{-}\\mathbf{n}$ and $\\mathbf{n}{-}\\mathbf{i}{-}\\mathbf{p}$ (inset) solar cell as calculated using the transfer matrix model.52 \n\n![](images/e89a98bed2662b43a1eae9029787a5c7fc0a23c1fde5a069c016d8a48a5e499d.jpg) \nFigure 5. Light intensity dependence of (a) $V_{\\mathrm{oc}}$ and (b) FF for both $\\mathbf{p-i-n}$ and $\\mathbf{n}{-}\\mathbf{i}{-}\\mathbf{p}$ cells. The filled symbols and lines in (a) represent experimental data and simulation, respectively. The open and filled symbols in (b) represent experimental data and simulation, respectively. \n\nAlthough traps at GBs and interfaces are likely to be charged (due to accumulated ionic defects) when empty and hence neutral when filled, the sign of the filled trap has little to do with the overall device performance when the solar cell in question is efficient, with fused GBs (low trap densities). The PSCs used here show compact morphology and have high efficiencies reaching $20\\%$ with little or no hysteresis,9 and hence, the sign of the filled traps shows only a marginal change in device performance (Figure S2 in the SI). On the other hand, solar cells with open GBs (high trap densities) show high sensitivity to the sign of filled traps at GBs, as shown in Figure S2. Charged filled traps lead to faster SRH recombination due to the Coulombic attraction between opposite charged species (a negative filled trap and a hole). However, even then, some PSCs with open GBs (high trap densities) show decent efficiencies $(\\sim\\bar{1}2\\%)$ .47 This can be attributed to the likely case of the existence of charged empty traps (accumulated $V_{\\mathrm{I}}^{+}$ at GBs and interfaces) and thus neutral filled traps, which lowers the SRH recombination rate in PSCs. Solar cell preparation methods are likely to influence the properties of traps, which is why there seems to be no agreement in the literature about the impact of GBs on the device performance.19−21,23,24 \n\nUntil this point, we simulated the current−voltage $\\left(J-V\\right)$ scans under “stabilized” conditions (an infinitely slow $J{-}V$ scan), such that all mobile iodide ions $\\left(X_{\\mathrm{a}}\\right)$ given by eq 10 (compensating the presence of accumulated iodide vacancies $\\boldsymbol{V}_{\\mathrm{I}}^{+}$ at GBs/interfaces acting as traps and recombination centers for photogenerated charge carriers) were allowed to redistribute at every step of the scan. This naturally resulted in hysteresis-free device characteristics as the forward and reverse scans yielded the same $J{-}V$ curve. While the role of preconditioning and scan rate is more or less clear in the context of $J{-}V$ hysteresis in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ solar cells,59−63 we would like to answer the following question: Is there a relation between the density of trap states, the density of defect mobile ions, and the degree of hysteresis seen in PSCs? \n\nThe trap density in the $\\mathrm{{\\ttp}-i-n}$ and $\\mathtt{n-i-p}$ cells studied here is known from Table 1. In the model, the mobile iodide ion $\\left(X_{\\mathrm{a}}\\right)$ density is assumed to be related to the trap density (accumulated $\\boldsymbol{V}_{\\mathrm{I}}^{+}$ ) by eq 10 because their origin is the same (dislocation of iodide ions). We now simulate the extreme case (where cells would show maximum hysteresis) of a fast voltage scan rate $\\'{V}_{\\mathrm{scan}}=\\infty)$ after preconditioning (infinitely long) at $-0.2\\:\\mathrm{V}$ (for forward scan) and $1.2\\mathrm{V}$ (for reverse scan) bias. The fast forward scan simulation is performed after preconditioning the device at $-0.2\\mathrm{~V~}$ under illumination such that negative iodide ions are pushed toward the ETL and stay put throughout the scan. For the fast reverse scan, the device is preconditioned at $1.2\\mathrm{V}$ under illumination such that the iodide ions are pushed away from the ETL and their distribution remains fixed during the scan. This gives us an envelope (two $J{-}V$ curves enclosing a small area) that relates to the degree of hysteresis. The simulated hysteresis is shown in Figure 6 and is consistent with the experimentally observed little hysteresis in $\\mathrm{{\\ttp}-i-n}$ cells and no hysteresis in $\\mathsf{n{-i{-}\\mathsf{p}}}$ cells that we study here.9 In these cells made by some of us, the degree of measured $J{-}V$ hysteresis is relatively unchanged when the scans are performed with or without preconditioning, irrespective of the scan rate.9 The simulation details of the fast scans and “stabilized” scans are included in the SI. It is clear that highperforming PSCs are likely to show little or no hysteresis because they contain a low density of traps and hence mobile defect ions. This is in agreement with Calado et al.,64 who provide evidence that devices with minimal hysteresis still have moving ions but low trap densities that results in decreased recombination strength in the device and therefore little hysteresis. As shown in Figure S3, poor solar cells with high trap density (and thus defect ions) show more hysteresis in the $J{-}V$ characteristics. Therefore, defect states or mobile ions not only limit the device performance but also play a role in the hysteresis observed in their $J{-}V$ characteristics of PSCs. \n\n![](images/5809ad51be716ff116c4f0370cd1749fdcae15a367f31796921057debf2c668b.jpg) \nFigure 6. Simulated forward/reverse scan of $\\mathbf{p-i-n}$ and $\\mathbf{n}{-}\\mathbf{i}{-}\\mathbf{p}$ cells showing hysteresis in the $J{-}V$ curves when negative iodide ions $(X_{\\mathrm{a}}$ $\\mathbf{\\Sigma}=4\\times\\mathbf{i0^{14}\\ c m^{-3}},$ ) are mobile. The forward scan is performed after preconditioning at $\\mathbf{-0.2V}_{\\mathrm{i}}$ , and the reverse scan is carried out after preconditioning at $\\mathbf{1.2\\deltaV}$ . \n\nAn estimate of the density of the mobile ions in the specific set of PSCs studied in this paper would be $X_{\\mathrm{a}}\\approx10^{15}~\\mathrm{cm}^{-3}$ at the most. \n\nIt is possible that ionic defects other than the iodide complexes act as trap-assisted recombination centers and contribute to $J{-}V$ hysteresis. However, the activation energies for migration of I complexes are much lower as compared to those of other ionic $\\mathrm{(CH_{3}N H_{3})}$ , Pb, etc.) complexe s,38,63 and hence, I complexes are more likely to influence the device optoelectronic performance.45 \n\nIn conclusion, we investigated the attributes of the primary trap-assisted recombination channels (GBs and interfaces) and their correlation to defect ions in PSCs. We achieved this by using a device model15 to fit the simulations to the experimental data of efficient $\\mathrm{{\\ttp}-i-n}$ and $\\mathrm{n-i-p\\CH_{3}N H_{3}P b I_{3}}$ solar cells. The model utilized an extensive experimental data set (Table 1) as input, and the only free parameters (to fit) were the carrier mobility in the perovskite and the trap density plus the charge capture coefficients. Excellent agreement was found between the simulated data and experimental data, including the light intensity dependence of $V_{\\mathrm{OC}}$ and FF. We found that despite the presence of traps at GBs, their neutral (when filled with photogenerated charges) disposition along with the long-lived nature of holes leads to the high performance of PSCs. The sign (if charged or neutral when filled) of traps is of little importance in efficient solar cells with compact morphologies (fused GBs, low trap density). On the other hand, solar cells with noncompact morphologies (open GBs, high trap density) are sensitive to the sign of the traps and hence cell preparation methods (e.g., under/overstoichiometric routes, environmental conditions). Even in the presence of traps at GBs in the perovskite layer, trap-assisted recombination at interfaces is the dominant loss mechanism, in agreement with our previous report.15 We found a direct correlation between the density of trap states, the density of mobile ions, and the degree of hysteresis observed in the current−voltage $\\left(J-V\\right)$ characteristics. High-performing PSCs are likely to show little or no hysteresis because they contain low density of traps and hence ions, while poor solar cells with high trap density (and thus ions) show more hysteresis. Therefore, defects states or mobile ions not only limit the device performance but also play a role in the hysteresis observed in the $J{-}V$ characteristics of PSCs. We found that the specific set of devices studied in this Letter contain a defect mobile ion density on the order $10^{15}$ $\\mathsf{c m}^{-3}$ at the most. \n\nFocus should be directed toward passivation of traps at interfaces (HTL/perovskite and perovskite/ETL) where trapassisted recombination dominates, while the use of polycrystalline perovskite films with fused GBs as absorber is good enough to achieve high-performance solar cells. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsenergylett.7b00236. \n\nSimulation details, optical data, and additional results (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author \n$^{*}\\mathrm{E}$ -mail: l.j.a.koster@rug.nl. \nORCID \nHenk J. Bolink: 0000-0001-9784-6253 \nL. Jan Anton Koster: 0000-0002-6558-5295 \nNotes \nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThe Valencian team acknowledges financial support from the Spanish Ministry of Economy and Competitiveness (MINECO) via the Unidad de Excelencia Mari ́a de Maeztu MDM2015-0538 and MAT2014-55200, PCIN-2015-255, and the Generalitat Valenciana (Prometeo/2016/135). C.M. and M.S. thank the MINECO for their pre- and postdoctoral (JdC) contracts. This work is part of the Industrial Partnership Programme (IPP) “Computational sciences for energy research” of the Foundation for Fundamental Research on Matter (FOM), which is part of The Netherlands Organisation for Scientific Research (NWO). This research programme is cofinanced by Shell Global Solutions International B.V. This is a publication by the FOM Focus Group “Next Generation Organic Photovoltaics”, participating in the Dutch Institute for Fundamental Energy Research (DIFFER). \n\n# REFERENCES \n\n(1) Green, M. A.; Emery, K.; Hishikawa, Y.; Warta, W.; Dunlop, E. D.; Levi, D. H.; Ho-Baillie, A. W. Solar cell efficiency tables (version 49). Prog. Photovoltaics 2017, 25, 3. (2) Kojima, A.; Teshima, K.; Shirai, Y.; Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 2009, 131, 6050−6051. (3) Stranks, S. D.; Eperon, G. E.; Grancini, G.; Menelaou, C.; Alcocer, M. J.; Leijtens, T.; Herz, L. M.; Petrozza, A.; Snaith, H. J. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 2013, 342, 341− 344. (4) Edri, E.; Kirmayer, S.; Mukhopadhyay, S.; Gartsman, K.; Hodes, G.; Cahen, D. Elucidating the charge carrier separation and working mechanism of CH3NH3PbI3-xClx perovskite solar cells. Nat. Commun. 2014, 5, 3461. \n\n(5) Liu, M.; Johnston, M. B.; Snaith, H. J. Efficient planar heterojunction perovskite solar cells by vapour deposition. Nature 2013, 501, 395−398. \n(6) Malinkiewicz, O.; Yella, A.; Lee, Y. H.; Espallargas, G. M.; Graetzel, M.; Nazeeruddin, M. K.; Bolink, H. J. Perovskite solar cells employing organic charge-transport layers. Nat. Photonics 2013, 8, 128−132. \n(7) You, J.; et al. Low-temperature solution-processed perovskite solar cells with high efficiency and flexibility. ACS Nano 2014, 8, 1674−1680. \n(8) Nie, W.; et al. High-efficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 2015, 347, 522−525. (9) Momblona, C.; Gil-Escrig, L.; Bandiello, E.; Hutter, E. M.; Sessolo, M.; Lederer, K.; Blochwitz-Nimoth, J.; Bolink, H. J. Efficient vacuum deposited pin and nip perovskite solar cells employing doped charge transport layers. Energy Environ. Sci. 2016, 9, 3456−3463. (10) Sha, W. E. I.; Ren, X.; Chen, L.; Choy, W. C. The efficiency limit of CH3NH3PbI3 perovskite solar cells. Appl. Phys. Lett. 2015, 106, 221104. \n(11) Wehrenfennig, C.; Eperon, G. E.; Johnston, M. B.; Snaith, H. J.; Herz, L. M. High charge carrier mobilities and lifetimes in organolead trihalide perovskites. Adv. Mater. 2014, 26, 1584−1589. \n(12) Wetzelaer, G. A. H.; Scheepers, M.; Sempere, A. M.; Momblona, C.; Ávila, J.; Bolink, H. J. Trap-Assisted Non-Radiative Recombination in Organic-Inorganic Perovskite Solar Cells. Adv. Mater. 2015, 27, 1837−1841. \n(13) Johnston, M. B.; Herz, L. M. Hybrid perovskites for photovoltaics: Charge-carrier recombination, diffusion, and radiative efficiencies. Acc. Chem. Res. 2016, 49, 146−154. \n(14) Tress, W.; Marinova, N.; Inganäs, O.; Nazeeruddin, M.; Zakeeruddin, S. M.; Graetzel, M. Predicting the Open-Circuit Voltage of CH3NH3PbI3 Perovskite Solar Cells Using Electroluminescence and Photovoltaic Quantum Efficiency Spectra: the Role of Radiative and Non-Radiative Recombination. Adv. Energy Mater. 2015, 5, 1400812. \n(15) Sherkar, T. S.; Momblona, C.; Gil-Escrig, L.; Bolink, H. J.; Koster, L. J. A. Improving the Performance of Perovskite Solar Cells: Insights From a Validated Device Model. Adv. Energy Mater. 2017, 1602432. \n(16) Shao, Y.; et al. Grain boundary dominated ion migration in polycrystalline organic-inorganic halide perovskite films. Energy Environ. Sci. 2016, 9, 1752−1759. \n(17) Cui, P.; Fu, P.; Wei, D.; Li, M.; Song, D.; Yue, X.; Li, Y.; Zhang, Z.; Li, Y.; Mbengue, J. M. Reduced surface defects of organometallic perovskite by thermal annealing for highly efficient perovskite solar cells. RSC Adv. 2015, 5, 75622−75629. \n(18) Wu, X.; Trinh, M. T.; Niesner, D.; Zhu, H.; Norman, Z.; Owen, J. S.; Yaffe, O.; Kudisch, B. J.; Zhu, X.-Y. Trap states in lead iodide perovskites. J. Am. Chem. Soc. 2015, 137, 2089−2096. \n(19) Chen, Q.; Zhou, H.; Song, T.-B.; Luo, S.; Hong, Z.; Duan, H.-S.; Dou, L.; Liu, Y.; Yang, Y. Controllable self-induced passivation of hybrid lead iodide perovskites toward high performance solar cells. Nano Lett. 2014, 14, 4158−4163. \n(20) MacDonald, G. A.; Yang, M.; Berweger, S.; Killgore, J. P.; Kabos, P.; Berry, J. J.; Zhu, K.; DelRio, F. W. Methylammonium lead iodide grain boundaries exhibit depth-dependent electrical properties. Energy Environ. Sci. 2016, 9, 3642−3649. \n(21) Yun, J. S.; Ho-Baillie, A.; Huang, S.; Woo, S. H.; Heo, Y.; Seidel, J.; Huang, F.; Cheng, Y.-B.; Green, M. A. Benefit of grain boundaries in organic-inorganic halide planar perovskite solar cells. J. Phys. Chem. Lett. 2015, 6, 875−880. \n(22) Jacobsson, T. J.; et al. Unreacted PbI2 as a Double-Edged Sword for Enhancing the Performance of Perovskite Solar Cells. J. Am. Chem. Soc. 2016, 138, 10331−10343. \n(23) de Quilettes, D. W.; Vorpahl, S. M.; Stranks, S. D.; Nagaoka, H.; Eperon, G. E.; Ziffer, M. E.; Snaith, H. J.; Ginger, D. S. Impact of microstructure on local carrier lifetime in perovskite solar cells. Science 2015, 348, 683−686. (24) Bischak, C. G.; Sanehira, E. M.; Precht, J. T.; Luther, J. M.; Ginsberg, N. S. Heterogeneous Charge Carrier Dynamics in OrganicInorganic Hybrid Materials: Nanoscale Lateral and Depth-Dependent Variation of Recombination Rates in Methylammonium Lead Halide Perovskite Thin Films. Nano Lett. 2015, 15, 4799−4807. \n(25) Ono, L. K.; Qi, Y. Surface and Interface Aspects of Organometal Halide Perovskite Materials and Solar Cells. J. Phys. Chem. Lett. 2016, 7, 4764−4794. \n(26) Nelson, J. The Physics of Solar Cells; Imperial College Press: London, 2003. \n(27) Visoly-Fisher, I.; Cohen, S. R.; Gartsman, K.; Ruzin, A.; Cahen, D. Understanding the Beneficial Role of Grain Boundaries in Polycrystalline Solar Cells from Single-Grain-Boundary Scanning Probe Microscopy. Adv. Funct. Mater. 2006, 16, 649−660. \n(28) Li, C.; et al. Grain-boundary-enhanced carrier collection in CdTe solar cells. Phys. Rev. Lett. 2014, 112, 156103. \n(29) Distefano, T.; Cuomo, J. Reduction of grain boundary recombination in polycrystalline silicon solar cells. Appl. Phys. Lett. 1977, 30, 351−353. \n(30) Gloeckler, M.; Sites, J. R.; Metzger, W. K. Grain-boundary recombination in Cu (In, Ga) Se2 solar cells. J. Appl. Phys. 2005, 98, 113704. \n(31) Seto, J. Y. The electrical properties of polycrystalline silicon films. J. Appl. Phys. 1975, 46, 5247−5254. \n(32) Landsberg, P.; Abrahams, M. Effects of surface states and of excitation on barrier heights in a simple model of a grain boundary or a surface. J. Appl. Phys. 1984, 55, 4284−4293. \n(33) Card, H. C.; Yang, E. S. Electronic processes at grain boundaries in polycrystalline semiconductors under optical illumination. IEEE Trans. Electron Devices 1977, 24, 397−402. \n(34) Yin, W.-J.; Yang, J.-H.; Kang, J.; Yan, Y.; Wei, S.-H. Halide perovskite materials for solar cells: a theoretical review. J. Mater. Chem. A 2015, 3, 8926−8942. \n(35) Walsh, A.; Scanlon, D. O.; Chen, S.; Gong, X.; Wei, S.-H. SelfRegulation Mechanism for Charged Point Defects in Hybrid Halide Perovskites. Angew. Chem. 2015, 127, 1811−1814. \n(36) Yin, W.-J.; Shi, T.; Yan, Y. Unusual defect physics in CH3NH3PbI3 perovskite solar cell absorber. Appl. Phys. Lett. 2014, 104, 063903. \n(37) Selberherr, S. Analysis and Simulation of Semiconductor Devices; Springer-Verlag: Vienna, 1984. \n(38) Eames, C.; Frost, J. M.; Barnes, P. R.; O’regan, B. C.; Walsh, A.; Islam, M. S. Ionic transport in hybrid lead iodide perovskite solar cells. Nat. Commun. 2015, 6, 7497. \n(39) Azpiroz, J. M.; Mosconi, E.; Bisquert, J.; de Angelis, F. Defect migration in methylammonium lead iodide and its role in perovskite solar cell operation. Energy Environ. Sci. 2015, 8, 2118−2127. \n(40) Yuan, Y.; Huang, J. Ion Migration in Organometal Trihalide Perovskite and Its Impact on Photovoltaic Efficiency and Stability. Acc. Chem. Res. 2016, 49, 286−293. \n(41) Simmons, J.; Taylor, G. Nonequilibrium steady-state statistics and associated effects for insulators and semiconductors containing an arbitrary distribution of traps. Phys. Rev. B 1971, 4, 502. \n(42) Koster, L. J. A.; Smits, E. C. P.; Mihailetchi, V. D.; Blom, P. W. M. Device model for the operation of polymer/fullerene bulk heterojunction solar cells. Phys. Rev. B: Condens. Matter Mater. Phys. 2005, 72, 085205. \n(43) Leijtens, T.; Stranks, S. D.; Eperon, G. E.; Lindblad, R.; Johansson, E. M.; McPherson, I. J.; Rensmo, H.; Ball, J. M.; Lee, M. M.; Snaith, H. J. Electronic properties of meso-superstructured and planar organometal halide perovskite films: charge trapping, photodoping, and carrier mobility. ACS Nano 2014, 8, 7147−7155. \n(44) Leijtens, T.; Eperon, G. E.; Barker, A. J.; Grancini, G.; Zhang, W.; Ball, J. M.; Kandada, A. R. S.; Snaith, H. J.; Petrozza, A. Carrier trapping and recombination: the role of defect physics in enhancing the open circuit voltage of metal halide perovskite solar cells. Energy Environ. Sci. 2016, 9, 3472−3481. \n(45) deQuilettes, D. W.; Zhang, W.; Burlakov, V. M.; Graham, D. J.; Leijtens, T.; Osherov, A.; Bulović, V.; Snaith, H. J.; Ginger, D. S.; Stranks, S. D. Photo-induced halide redistribution in organic-inorganic perovskite films. Nat. Commun. 2016, 7, 11683. \n(46) Du, M.-H. Density functional calculations of native defects in CH3NH3PbI3: effects of spin-orbit coupling and self-interaction error. J. Phys. Chem. Lett. 2015, 6, 1461−1466. \n(47) Shao, S.; Abdu-Aguye, M.; Sherkar, T. S.; Fang, H.-H.; Adjokatse, S.; Brink, G. t.; Kooi, B. J.; Koster, L.; Loi, M. A. The Effect of the Microstructure on Trap-Assisted Recombination and Light Soaking Phenomenon in Hybrid Perovskite Solar Cells. Adv. Funct. Mater. 2016, 26, 8094−8102. \n(48) Uratani, H.; Yamashita, K. Charge Carrier Trapping at Surface Defects of Perovskite Solar Cell Absorbers: A First-Principles Study. J. Phys. Chem. Lett. 2017, 8, 742−746. \n(49) Sherkar, T. S.; Koster, L. J. A. Can ferroelectric polarization explain the high performance of hybrid halide perovskite solar cells? Phys. Chem. Chem. Phys. 2016, 18, 331−338. \n(50) Yuan, Y.; Li, T.; Wang, $\\mathrm{Q.;}$ Xing, J.; Gruverman, A.; Huang, J. Anomalous photovoltaic effect in organic-inorganic hybrid perovskite solar cells. Science Adv. 2017, 3, e1602164. \n(51) Xing, G.; Mathews, N.; Sun, S.; Lim, S. S.; Lam, Y. M.; Grätzel, M.; Mhaisalkar, S.; Sum, T. C. Long-range balanced electron-and holetransport lengths in organic-inorganic CH3NH3PbI3. Science 2013, 342, 344−347. \n(52) Burkhard, G. F.; Hoke, E. T.; McGehee, M. D. Accounting for interference, scattering, and electrode absorption to make accurate internal quantum efficiency measurements in organic and other thin solar cells. Adv. Mater. 2010, 22, 3293−3297. \n(53) Tress, W. Device Physics of Organic Solar Cells. Ph.D. thesis, TU Dresden, Dresden, Germany, 2011. \n(54) Brivio, F.; Butler, K. T.; Walsh, A.; van Schilfgaarde, M. Relativistic quasiparticle self-consistent electronic structure of hybrid halide perovskite photovoltaic absorbers. Phys. Rev. B: Condens. Matter Mater. Phys. 2014, 89, 155204. \n(55) Mönch, T.; Sherkar, T. S.; Koster, L. J. A.; Friederich, P.; Riede, M.; Formanek, P.; Koerner, C.; Vandewal, K.; Wenzel, W.; Leo, K. Experimental and theoretical study of phase separation in ZnPc: C 60 blends. Org. Electron. 2015, 27, 183−191. \n(56) Koster, L. J. A.; Mihailetchi, V. D.; Ramaker, R.; Blom, P. W. Light intensity dependence of open-circuit voltage of polymer: fullerene solar cells. Appl. Phys. Lett. 2005, 86, 123509−123509. (57) Mandoc, M.; Kooistra, F.; Hummelen, J.; De Boer, B.; Blom, P. Effect of traps on the performance of bulk heterojunction organic solar cells. Appl. Phys. Lett. 2007, 91, 263505. \n(58) Tvingstedt, K.; Gil-Escrig, L.; Momblona, C.; Rieder, P.; Kiermasch, D.; Sessolo, M.; Baumann, A.; Bolink, H. J.; Dyakonov, V. Removing Leakage and Surface Recombination in Planar Perovskite Solar Cells. ACS Energy Letters 2017, 2, 424−430. \n(59) Snaith, H. J.; Abate, A.; Ball, J. M.; Eperon, G. E.; Leijtens, T.; Noel, N. K.; Stranks, S. D.; Wang, J. T.-W.; Wojciechowski, K.; Zhang, W. Anomalous hysteresis in perovskite solar cells. J. Phys. Chem. Lett. 2014, 5, 1511−1515. \n(60) Tress, W.; Marinova, N.; Moehl, T.; Zakeeruddin, S. M.; Nazeeruddin, M. K.; Grätzel, M. Understanding the rate-dependent J− V hysteresis, slow time component, and aging in CH 3 NH 3 PbI 3 perovskite solar cells: the role of a compensated electric field. Energy Environ. Sci. 2015, 8, 995−1004. \n(61) Unger, E. L.; Hoke, E. T.; Bailie, C. D.; Nguyen, W. H.; Bowring, A. R.; Heumüller, T.; Christoforo, M. G.; McGehee, M. D. Hysteresis and transient behavior in current-voltage measurements of hybrid-perovskite absorber solar cells. Energy Environ. Sci. 2014, 7, 3690−3698. \n(62) Richardson, G.; O’Kane, S. E.; Niemann, R. G.; Peltola, T. A.; Foster, J. M.; Cameron, P. J.; Walker, A. B. Can slow-moving ions explain hysteresis in the current−voltage curves of perovskite solar cells? Energy Environ. Sci. 2016, 9, 1476−1485. \n(63) Meloni, S.; et al. Ionic polarization-induced current-voltage hysteresis in CH3NH3PbX3 perovskite solar cells. Nat. Commun. 2016, 7, 10334. \n\n(64) Calado, P.; Telford, A. M.; Bryant, D.; Li, X.; Nelson, J.; O’regan, B. C.; Barnes, P. R. Evidence for ion migration in hybrid perovskite solar cells with minimal hysteresis. Nat. Commun. 2016, 7, 13831. " + }, + { + "id": "10.1126_sciadv.1603015", + "DOI": "10.1126/sciadv.1603015", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.1603015", + "Relative Dir Path": "mds/10.1126_sciadv.1603015", + "Article Title": "Machine learning of accurate energy-conserving molecular force fields", + "Authors": "Chmiela, S; Tkatchenko, A; Sauceda, HE; Poltavsky, I; Schütt, KT; Müller, KR", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Using conservation of energy-a fundamental property of closed classical and quantum mechanical systems-we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of 0.3 kcal mol(-1) for energies and 1 kcal mol(-1) angstrom(-1) for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods.", + "Times Cited, WoS Core": 852, + "Times Cited, All Databases": 949, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000401955300043", + "Markdown": "# A P P L I E D M A T H E M A T I C S \n\n# Machine learning of accurate energy-conserving molecular force fields \n\n2017 $\\circledcirc$ The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\nStefan Chmiela,1 Alexandre Tkatchenko, $^{2,3_{*}}$ Huziel E. Sauceda,3 Igor Poltavsky,2 Kristof T. Schütt,1 Klaus-Robert Müller1,4,5\\* \n\nUsing conservation of energy—a fundamental property of closed classical and quantum mechanical systems— we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of $0.3\\ \\mathsf{k c a l\\ m o l}^{-1}$ for energies and $1\\ k\\mathbf{c}\\mathbf{a}|\\ \\mathbf{mol}^{-1}\\ \\mathring{\\mathsf{A}}^{-1}$ for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods. \n\n# INTRODUCTION \n\nWithin the Born-Oppenheimer (BO) approximation, predictive simulations of properties and functions of molecular systems require an accurate description of the global potential energy hypersurface $V_{\\mathrm{BO}}(\\overrightarrow{r_{1}},\\overrightarrow{r_{2}},...,\\overrightarrow{r_{N}})$ , where $\\overrightarrow{r_{i}}$ indicates the nuclear Cartesian coordinates. Although $V_{\\mathrm{BO}}$ could, in principle, be obtained on the fly using explicit ab initio calculations, more efficient approaches that can access the long time scales are required to understand relevant phenomena in large molecular systems. A plethora of classical mechanistic approximations to $V_{\\mathrm{BO}}$ have been constructed, in which the parameters are typically fitted to a small set of ab initio calculations or experimental data. Unfortunately, these classical approximations may suffer from the lack of transferability and can yield accurate results only close to the conditions (geometries) they have been fitted to. Alternatively, sophisticated machine learning (ML) approaches that can accurately reproduce the global potential energy surface (PES) for elemental materials (1–9) and small molecules (10–16) have been recently developed (see Fig. 1, A and B) (17). Although potentially very promising, one particular challenge for direct ML fitting of molecular PES is the large amountofdatanecessarytoobtainanaccuratemodel.Often,manythousands or even millions of atomic configurations are used as training data for ML models. This results in nontransparent models, which are difficult to analyze and may break consistency (18) between energies and forces. \n\nA fundamental property that any force field $\\mathbf{F}_{i}(\\overrightarrow{r_{1}},\\overrightarrow{r_{2}},...,\\overrightarrow{r_{N}})$ must satisfy is the conservation of total energy, which implies that $\\mathbf{F}_{i}(\\overrightarrow{r_{1}},\\overrightarrow{r_{2}},...,\\overrightarrow{r_{N}})=-\\nabla_{\\overrightarrow{r_{i}}}V(\\overrightarrow{r_{1}},\\overrightarrow{r_{2}},...,\\overrightarrow{r_{N}})$ . Any classical mechanistic expressions for the potential energy (also denoted as classical force field) or analytically derivable ML approaches trained on energies satisfy energy conservation by construction. However, even if conservation of energy is satisfied implicitly within an approximation, this does not imply that the model will be able to accurately follow the trajectory of the true ab initio potential, which was used to fit the force field. In particular, small energy/force inconsistencies between the force field model and ab initio calculations can lead to unforeseen artifacts in the PES topology, such as spurious critical points that can give rise to incorrect molecular dynamics (MD) trajectories. Another fundamental problem is that classical and ML force fields focusing on energy as the main observable have to assume atomic energy additivity—an approximation that is hard to justify from quantum mechanics. \n\nHere, we present a robust solution to these challenges by constructing an explicitly conservative ML force field, which uses exclusively atomic gradient information in lieu of atomic (or total) energies. In this manner, with any number of data samples, the proposed model fulfills energy conservation by construction. Obviously, the developed ML force field can be coupled to a heat bath, making the full system (molecule and bath) non–energy-conserving. \n\nWe remark that atomic forces are true quantum-mechanical observables within the BO approximation by virtue of the Hellmann-Feynman theorem. The energy of a molecular system is recovered by analytic integration of the force-field kernel (see Fig. 1C). We demonstrate that our gradient-domain machine learning (GDML) approach is able to accurately reproduce global PESs of intermediate-sized molecules within $0.{\\dot{3}}\\mathrm{kcalmol}^{-1}$ for energies and $1\\mathrm{\\kcal\\mol^{-1}\\mathring{A}^{-1}}$ for atomic forces relative to the reference data. This accuracy is achieved when using less than 1000 training geometries to construct the GDML model and using energy conservation to avoid overfitting and artifacts. Hence, the GDML approach paves the way for efficient and precise MD simulations with PESs that are obtained with arbitrary high-level quantumchemical approaches. We demonstrate the accuracy of GDML by computing AIMD-quality thermodynamic observables using pathintegral MD (PIMD) for eight organic molecules with up to 21 atoms and four chemical elements. Although we use density functional theory (DFT) calculations as reference in this development work, it is possible to use any higher-level quantum-chemical reference data. With state-of-the-art quantum chemistry codes running on current highperformance computers, it is possible to generate accurate reference data for molecules with a few dozen atoms. Here, we focus on intramolecular \n\n# Descriptor encodes molecular structure. \n\n$$\nD_{i j}={\\left\\{\\begin{array}{l l}{\\|{\\vec{r_{i}}}-{\\vec{r_{j}}}\\|^{-1}}&{{\\mathrm{for~}}i>j}\\\\ {0}&{{\\mathrm{for~}}i\\leq j}\\end{array}\\right.}\n$$ \n\nKernel function measures the similarity between pairs of inputs. \n\n$$\n\\kappa:\\langle\\phi(\\mathbf{D}),\\phi(\\mathbf{D}^{\\prime})\\rangle_{\\mathcal{H}}\n$$ \n\n# Problem: \n\nEnergy-based model lacks detail in undersampled regions. \n\n![](images/67158f81682638f196dd1dbd0eb83acd035a0f66ea5fdae8e5e9a7877b3cf466.jpg) \n\n![](images/b066b2797980961c27e462458e9885ab238aaa22625137d5f53ace1d29410b1d.jpg) \nFig. 1. The construction of ML models: First, reference data from an MD trajectory are sampled. (A) The geometry of each molecule is encoded in a descriptor. This representation introduces elementary transformational invariances of energy and constitutes the first part of the prior. A kernel function then relates all descriptors to form the kernel matrix—the second part of the prior. The kernel function encodes similarity between data points. Our particular choice makes only weak assumptions: It limits the frequency spectrum of the resulting model and adds the energy conservation constraint. Hess, Hessian. (C) These general priors are sufficient to reproduce good estimates from a restricted number of force samples. (B) A comparable energy model is not able to reproduce the PES to the same level of detail. \n\n# Solution: \n\nTraining in the force domain accurately reproduces PES topology. \n\n$$\n\\hat{f}_{F}(\\vec{x})=\\sum_{i=1}^{M}\\sum_{j=1}^{3N}(\\vec{\\alpha}_{i})_{j}\\frac{\\partial}{\\partial x_{j}}\\nabla\\kappa(\\vec{x},\\vec{x}_{i})\n$$ \n\n$$\n\\hat{f}_{E}(\\vec{x})=\\sum_{i=1}^{M}\\sum_{j=1}^{3N}(\\vec{\\alpha}_{i})_{j}\\frac{\\partial}{\\partial x_{j}}\\kappa(\\vec{x},\\vec{x}_{i})\n$$ \n\n![](images/fa483a98b1fb60ca462674242e90ce79d60fe2d0ae907c3c8bbbb022a3c3a524.jpg) \nFig. 2. Modeling the true vector field (leftmost subfigure) based on a small number of vector samples With GDML, a conservative vector field estimate $\\hat{\\pmb f}_{\\sf F}$ is obtained directly. A naïve estimator $\\hat{\\pmb f}_{\\sf F}^{-}$ with independent predictions for each element of the output vector is not capable of imposing energy conservation constraints. We perform a Helmholtz decomposition of this nonconservative vector field to show the error component that violates the law of energy conservation. This is the portion of the overall prediction error that was avoided with GDML because of the addition of the energy conservation constraint. \n\nforces in small- and medium-sized molecules. However, in the future, the GDML model should be combined with an accurate model for intermolecular forces to enable predictive simulations of condensed molecular systems. Widely used classical mechanistic force fields are based on simple harmonic terms for intramolecular degrees of freedom. Our GDML model correctly treats anharmonicities by using no assumptions whatsoever on the analytic form on the interatomic potential energy functions within molecules. \n\n![](images/6b88459475cbbd19499a5dbd47b257890ccdd80a9c28f0c8ba37a1f0ea797f8b.jpg) \nFig. 3. Efficiency of GDML predictor versus a model that has been trained on energies. (A) Required number of samples for a force prediction performance of MAE $(1\\ \\mathsf{k c a l\\ m o l}^{-1}\\ \\mathring{\\mathsf{A}}^{-1};$ with the energy-based model (gray) and GDML (blue). The energy-based model was not able to achieve the targeted performance with the maximum number of 63,000 samples for aspirin. (B) Force prediction errors for the converged models (same number of partial derivative samples and energy samples). (C) Energy prediction errors for the converged models. All reported prediction errors have been estimated via cross-validation. \n\n# METHODS \n\nThe GDML approach explicitly constructs an energy-conserving force field, avoiding the application of the noise-amplifying derivative operator to a parameterized potential energy model (see the Supplementary Materials for details). This can be achieved by directly learning the functional relationship \n\n$$\n\\hat{f}_{\\mathrm{F}}:(\\overrightarrow{r_{1}},\\overrightarrow{r_{2}},...,\\overrightarrow{r_{N}})_{i}\\stackrel{\\mathrm{ML}}{\\rightarrow}\\mathbf{F}_{i}\n$$ \n\nbetween atomic coordinates and interatomic forces, instead of computing the gradient of the PES (see Fig. 1, C and B). This requires constraining the solution space of all arbitrary vector fields to the subset of energy-conserving gradient fields. The PES can be obtained through direct integration of $\\dot{\\boldsymbol{f}}_{\\mathrm{F}}$ up to an additive constant. \n\nTo construct $\\hat{\\boldsymbol f}_{\\mathrm{F}}^{\\phantom{\\dagger}}$ we used a generalization of the commonly used kernel ridge regression technique for structured vector fields (see the Supplementary Materials for details) (19–21). GDML solves the normal equation of the ridge estimator in the gradient domain using the Hessian matrix of a kernel as the covariance structure. It maps to all partial forces of a molecule simultaneously (see Fig. 1A) \n\n$$\n\\bigl(\\mathbf{K}_{\\mathrm{Hess}(\\kappa)}+\\lambda\\mathbb{I}\\bigr)\\overrightarrow{\\mathrm{d}}=\\nabla V_{B O}=-\\mathbf{F}\n$$ \n\nWe resorted to the extensive body of research on suitable kernels and descriptors for the energy prediction task (10, 13, 17). \n\nFor our application, we considered a subclass from the parametric Matérn family (22–24) of (isotropic) kernel functions \n\n$$\n\\upkappa:C_{\\nu=n+\\frac{1}{2}}(d)=\\exp\\left(-\\frac{\\sqrt{2\\nu}d}{\\upsigma}\\right)P_{n}(d),\n$$ \n\n$$\nP_{n}(d)=\\sum_{k=0}^{n}{\\frac{(n+k)!}{(2n)!}}{\\binom{n}{k}}\\left({\\frac{2{\\sqrt{2\\nu}}d}{\\sigma}}\\right)^{n-k}\n$$ \n\nwhere $d=\\|{\\vec{x}}-{\\vec{x}}^{\\prime}\\|$ is the Euclidean distance between two molecule descriptors. It can be regarded as a generalization of the universal Gaussian kernel with an additional smoothness parameter $n$ . Our parameterization $n=2$ resembles the Laplacian kernel, as suggested by Hansen et al. (13), while being sufficiently differentiable. \n\nTo disambiguate Cartesian geometries that are physically equivalent, we use an input descriptor derived from the Coulomb matrix (see the Supplementary Materials for details) (10). \n\nThe trained force field estimator collects the contributions of the partial derivatives 3N of all training points $M$ to compile the prediction. It takes the form \n\n$$\n\\hat{f}_{\\mathrm{F}}\\big(\\overrightarrow{\\mathbfit{x}}\\big)=\\sum_{i=1}^{M}\\sum_{j=1}^{3N}\\big(\\overrightarrow{\\mathbfit{a}}_{i}\\big)_{j}\\frac{\\partial}{\\partial x_{j}}\\nabla\\kappa\\big(\\overrightarrow{\\mathbfit{x}},\\overrightarrow{\\mathbfit{x}}_{i}\\big)\n$$ \n\nand a corresponding energy predictor is obtained by integrating $\\hat{f}_{\\mathrm{F}}(\\vec{x})$ with respect to the Cartesian geometry. Because the trained model is a (fixed) linear combination of kernel functions, integration only affects the kernel function itself. The expression \n\n$$\n\\hat{f}_{\\mathrm{E}}\\big(\\overrightarrow{\\textbf{\\textit{x}}}\\big)=\\sum_{i=1}^{M}\\sum_{j=1}^{3N}\\big(\\overrightarrow{\\textbf{\\textit{a}}}_{i}\\big)_{j}\\frac{\\partial}{\\partial x_{j}}\\upkappa\\big(\\overrightarrow{\\textbf{\\textit{x}}},\\overrightarrow{\\textbf{\\textit{x}}}_{i}\\big)\n$$ \n\nfor the energy predictor is therefore neither problem-specific nor does it require retraining. \n\nWe remark that our PES model is global in the sense that each molecular descriptor is considered as a whole entity, bypassing the need for arbitrary partitioning of energy into atomic contributions. This allows the GDML framework to capture chemical and longrange interactions. Obviously, long-range electrostatic and van der Waals interactions that fall within the error of the GDML model will have to be incorporated with explicit physical models. Other approaches that use ML to fit PESs such as Gaussian approximation potentials (3, 8) have been proposed. However, these approaches consider an explicit localization of the contribution of individual atoms to the total energy. The total energy is expressed as a linear combination of local environments characterized by a descriptor that acts as a nonunique partitioning function to the total energy. Training on force samples similarly requires the evaluation of kernel derivatives, but w. r.t. those local environments. Although any partitioning of the total energy is arbitrary, our molecular total energy is physically meaningful in that it is related to the atomic force, thus being a measure for the deflection of every atom from its ground state. \n\n![](images/0ff20e3569ddceef875592c5f684e30a4d1e5a98e958e203dd1bf5ed05ca4aa4.jpg) \nFig. 4. Results of classical and PIMD simulations. The recently developed estimators based on perturbation theory were used to evaluate structural and electronic observables (30). (A) Comparison of the interatomic distance distributions, $\\begin{array}{r}{h(r)=\\langle\\frac{2}{N(N-1)}{\\sum}_{i H3 phase transition. Contrary to the common understanding that the electrochemical oxidation of carbonate electrolytes causes the CO2 and CO evolution at potentials above 4.7 V vs. Li/Li+, we believe that the observed CO2 and CO are mainly due to the chemical reaction of reactive lattice oxygen with the electrolyte. This hypothesis is based on gas analysis using On-line Electrochemical Mass Spectrometry (OEMS), by which we prove that all three materials release oxygen from the particle surface and that the oxygen evolution coincides with the onset of CO2 and CO evolution. Interestingly, the onsets of oxygen evolution for the different NMCs correlate well with the high-voltage redox feature at similar to 4.7 V vs. Li/Li+ for NMC111 and NMC622 as well as at similar to 4.3 V vs. Li/Li+ for NMC811. To support this hypothesis, we show that no CO2 or CO is evolved for the LiNi0.43Mn1.57O4 (LNMO) spinel up to 5 V vs. Li/Li+, consistent with the absence of oxygen release. Lastly, we demonstrate by the use of C-13 labeled conductive carbon that it is the electrolyte rather than the conductive carbon which is oxidized by the released lattice oxygen. Taking these findings into consideration, a mechanism is proposed for the reaction of released lattice oxygen with ethylene carbonate yielding CO2, CO, and H2O. (C) The Author(s) 2017. Published by ECS. All rights reserved.", + "Times Cited, WoS Core": 978, + "Times Cited, All Databases": 1050, + "Publication Year": 2017, + "Research Areas": "Electrochemistry; Materials Science", + "UT (Unique WOS ID)": "WOS:000404397300004", + "Markdown": "# Oxygen Release and Its Effect on the Cycling Stability of $\\mathbf{LiNi_{x}M n_{y}C o_{z}O_{2}}$ (NMC) Cathode Materials for Li-Ion Batteries \n\nRoland Jung,a,b,∗,z Michael Metzger,a,∗ Filippo Maglia,b Christoph Stinner,b and Hubert A. Gasteigera,∗∗ \n\naChair of Technical Electrochemistry, Department of Chemistry and Catalysis Research Center, \nTechnische Universita¨t Mu¨nchen, Garching, Germany \nbBMW AG, Munich, Germany \n\nLayered $\\mathrm{LiNi_{x}M n_{y}C o_{z}O_{2}}$ (NMC) is a widely used class of cathode materials with $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ (NMC111) being the most common representative. However, Ni-rich NMCs are more and more in the focus of current research due to their higher specific capacity and energy. In this work we will compare $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ (NMC111), $\\mathrm{LiNi_{0.6}M n_{0.2}C o_{0.2}O_{2}}$ (NMC622), and $\\mathrm{LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}}$ (NMC811) with respect to their cycling stability in NMC-graphite full-cells at different end-of-charge potentials. It will be shown that stable cycling is possible up to $4.4\\mathrm{V}$ for NMC111 and NMC622 and only up to $4.0\\mathrm{V}$ for NMC811. At higher potentials, significant capacity fading was observed, which was traced back to an increase in the polarization of the NMC electrode, contrary to the nearly constant polarization of the graphite electrode. Furthermore, we show that the increase in the polarization occurs when the NMC materials are cycled up to a high-voltage feature in the $\\mathrm{dq/dV}$ plot, which occurs at ${\\sim}4.7\\mathrm{v}$ vs. $\\mathrm{Li/Li^{+}}$ for NMC111 and NMC622 and at ${\\sim}4.3\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ for NMC811. For the latter material, this feature corresponds to the H2 $\\rightarrow\\mathrm{H}3$ phase transition. Contrary to the common understanding that the electrochemical oxidation of carbonate electrolytes causes the $\\mathbf{CO}_{2}$ and CO evolution at potentials above $4.7\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ , we believe that the observed $\\mathrm{CO}_{2}$ and CO are mainly due to the chemical reaction of reactive lattice oxygen with the electrolyte. This hypothesis is based on gas analysis using On-line Electrochemical Mass Spectrometry (OEMS), by which we prove that all three materials release oxygen from the particle surface and that the oxygen evolution coincides with the onset of $\\mathrm{CO}_{2}$ and CO evolution. Interestingly, the onsets of oxygen evolution for the different NMCs correlate well with the high-voltage redox feature at ${\\sim}4.7\\mathrm{v}$ vs. $\\mathrm{Li/Li^{+}}$ for NMC111 and NMC622 as well as at ${\\sim}4.3\\mathrm{~V~}$ vs. ${\\mathrm{Li/Li^{+}}}$ for NMC811. To support this hypothesis, we show that no $\\mathrm{CO}_{2}$ or CO is evolved for the $\\mathrm{LiNi_{0.43}M n_{1.57}O_{4}}$ (LNMO) spinel up to $5\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ , consistent with the absence of oxygen release. Lastly, we demonstrate by the use of $^{13}\\mathrm{C}$ labeled conductive carbon that it is the electrolyte rather than the conductive carbon which is oxidized by the released lattice oxygen. Taking these findings into consideration, a mechanism is proposed for the reaction of released lattice oxygen with ethylene carbonate yielding $\\mathrm{CO}_{2}$ , CO, and $\\mathrm{H}_{2}\\mathrm{O}$ . \n\n$\\circledcirc$ The Author(s) 2017. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives 4.0 License (CC BY-NC-ND, http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is not changed in any way and is properly cited. For permission for commercial reuse, please email: oa $@$ electrochem.org. [DOI: 10.1149/2.0021707jes] All rights reserved. \n\nManuscript submitted January 16, 2017; revised manuscript received April 13, 2017. Published May 2, 2017. This article is a version of Paper 39 from the New Orleans, Louisiana, Meeting of the Society, May 28-June 1, 2017. \n\nLi-Ion batteries have recently been used as power supply for electric vehicles (EVs). In order to penetrate the mass market, a significant reduction in costs and further performance improvements have to be achieved to realize a longer driving range of EVs.1 The latter highly depends on the choice of the cathode active material, for which several potential materials exist,2 of which layered lithium nickel manganese cobalt oxide $\\mathrm{(LiNi_{x}M n_{y}C o_{z}O_{2}}$ , NMC) is one of the most promising class of cathode materials.3 This is due to the high specific capacity and good stability of the layered structure which changes its volume by less than $2\\%$ during Li insertion/extraction.4–6 Due to the sloped voltage profile of NMC, a higher capacity and energy density can be achieved when the upper cutoff voltage is increased.7–9 Even though the theoretical capacity of NMC is as high as ${\\sim}275\\ \\mathrm{mAh/g_{NMC}}$ , not all of the lithium can be extracted due to structural instabilities occurring when an exceedingly large fraction of lithium is removed.9,10 Additionally, the sloped voltage profile requires very high voltages to achieve complete removal of lithium, which in turn can lead to electrolyte oxidation, surface film formation, and transition metal dissolution, ultimately diminishing the cycling stability.11–17 For these reasons, the operating potential of NMC based cathode materials is nowadays limited to ${\\sim}4.3\\mathrm{V}.$ , restricting their capacities to much below their theoretical values.5 In order to improve the accessible capacity at reasonable upper cutoff voltages, Ni-rich NMCs (Ni-content ${\\mathrm{>}}\\mathrm{>}\\mathrm{Mn}\\mathrm{-}$ and Co-content) recently became the focus of interest, as more lithium can be extracted from their structure within the same voltage window. Therefore, they provide larger specific capacities and energy densities, which are crucial for a longer driving range of electric vehicles.2,18,19 \n\nSo far, however, Ni-rich NMCs suffer from a shorter lifetime due to a faster capacity fading compared to $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ (NMC111), the most common NMC material with a nickel:manganese:cobalt ratio of 1:1:1.18–20 For example, Noh et al. reported initial capacities at a $0.1~\\mathrm{C}$ -rate and an end-of-charge potential of $4.3\\mathrm{~V~}$ vs. $\\mathrm{Li/Li^{+}}$ of $203\\mathrm{\\mAh/g}$ and $163\\mathrm{\\mAh/g}$ for $\\mathrm{LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}}$ (NMC811) and NMC111, respectively.18 Unfortunately, the capacity retention for NMC811 in NMC-Li cells after 100 cycles at a $0.5\\mathrm{C}$ -rate was only $70\\%$ compared to $92\\%$ for NMC111.18 Furthermore, it was shown that layered oxides with rising Ni-contents are thermally less stable.18,21 At temperatures $\\ge170^{\\circ}\\mathrm{C}$ , the bulk materials undergo a two-phase transition from their layered structure to a spinel structure and eventually to a rock-salt structure, both of which are accompanied by release of lattice oxygen.18,21–27 For materials aged under battery operating conditions $(<60^{\\circ}\\mathrm{C})$ , the formation of disordered spinel and rock-salt type phases was reported to happen on the particle surface with the bulk structure remaining intact, i.e., remaining in the rhombohedral structure as reported for NMC,9 $\\mathrm{LiNi}_{0.8}\\mathrm{Co}_{0.2}\\mathrm{\\bar{O}}_{2}$ ,28,29, $\\mathrm{LiNiO}_{2}$ ,30, and NCA $\\mathrm{(LiNi_{0.80}C o_{0.15}A l_{0.05}O_{2})}$ .31 Even though it was not explicitly shown in these latter reports, the observed phase transitions suggest a release of oxygen from the particle surface, which was also pointed out in the reports by Abraham et al., Muto et al., and Hwang et al.28–31 So far, a release of oxygen from the oxide lattice under battery operating conditions was shown only for overlithiated NMC materials $(\\mathrm{Li}_{1+\\mathrm{x}}(\\mathrm{Ni},\\mathrm{Mn},\\mathrm{Co})_{1-\\mathrm{x}}\\mathrm{O}_{2})$ , in which lithium additionally occupies the transition metal layers.32–36 The exception is a recent publication by Gu´eguen et al., who showed oxygen evolution during battery cycling for NMC111.37 \n\nIn this study, we will compare two Ni-rich NMCs, namely $\\mathrm{LiNi_{0.6}M n_{0.2}C o_{0.2}O_{2}}$ (NMC622) and $\\mathrm{LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}}$ (NMC811) to $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ (NMC111) with respect to their cycling stability in full-cells with graphite anodes. Through an evaluation of the anode and cathode polarization in a three-electrode set-up, we conclude that the capacity fading at high voltages is due to the NMC electrode rather than the graphite electrode. By means of On-line Electrochemical Mass Spectrometry (OEMS) we prove that at high degrees of delithiation all three NMC materials release oxygen already at room temperature. The onset of the oxygen evolution corresponds well with the onset of the formation of $\\mathrm{CO}_{2}$ and CO, which is typically assigned to electrochemical electrolyte oxidation, raising the question whether the evolution of ${\\bf\\ddot{O}}_{2}$ actually causes the observed $\\mathrm{CO}_{2}$ and CO evolution. This question as well as the consequences of the oxygen release on the polarization and the cycling stability will be discussed with the experimental findings presented in this work. \n\n# Experimental \n\nElectrode Preparation.—Layered NMC and spinel LNMO electrodes were prepared by dispersing the active material particles $\\mathrm{(LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ (NMC111), $\\mathrm{LiNi_{0.6}M n_{0.2}C o_{0.2}O_{2}}$ (NMC622), $\\mathrm{LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}}$ (NMC811) or $\\mathrm{LiNi_{0.43}M n_{1.57}O_{4}}$ (LNMO), all from Umicore, Belgium) $(91.5~\\mathrm{\\\\%}_{\\mathrm{wt}})$ , conductive carbon (Super C65, Timcal, Switzerland) $(4.4~\\%_{\\mathrm{wt}})$ and polyvinylidene fluoride binder (PVDF, Kynar HSV 900, Arkema, France) $(4.1~\\%_{\\mathrm{wt}})$ in Nmethylpyrrolidone (NMP, anhydrous, $99.5\\%$ , Sigma-Aldrich). The slurry was mixed in a planetary mixer (Thinky, USA) at $2000\\mathrm{rpm}$ for $2\\times5$ minutes. In between the two runs the slurry was ultrasonicated for 10 minutes in an ultrasonic bath. The resulting ink was spread onto aluminum foil (thickness $18~{\\upmu\\mathrm{m}}$ , MTI Corporation, USA) using a gap bar coater (RK PrintCoat Instruments, UK). For OEMS measurements, the ink was coated onto a H2013 polyolefin separator (Celgard, USA) or a stainless steel mesh (316 grade, $26~{\\upmu\\mathrm{m}}$ aperture, $25~{\\upmu\\mathrm{m}}$ wire diameter, The Mesh Company, UK) to allow for a short diffusion time of the evolved gases to the head-space of the OEMS cell and to the capillary leading to the mass spectrometer.38,39 NMC622 electrodes containing $^{13}\\mathrm{C}$ -labeled carbon $(99\\ \\%)\\ {\\%}_{\\mathrm{{atom}}}\\ ^{13}{\\mathrm C}$ , Sigma-Aldrich, Germany) were prepared with the same composition as the ones containing Super C65, however, due to strong agglomeration of the carbon, the ink was prepared in a ball mill (Pulverisette 7, Fritsch, Germany) using zirconia balls with a diameter of $10~\\mathrm{mm}$ at $180\\mathrm{rpm}$ for 60 minutes. After drying at $50^{\\circ}\\mathrm{C}$ , electrodes were punched and dried overnight at $120^{\\circ}\\mathrm{C}$ (if coated on aluminum or stainless steel mesh) and at $95^{\\circ}\\mathrm{C}$ (if coated on H2013 separator) under dynamic vacuum in a glass oven (drying oven 585, B¨uchi, Switzerland) and transferred to a glove box $\\mathrm{\\mathrm{\\Omega}}_{\\mathrm{{}}}\\mathrm{\\mathrm{O}}_{2}$ and $\\mathrm{H}_{2}\\mathrm{O}<0.1$ ppm, MBraun, Germany) without exposure to ambient air. \n\nThe graphite electrodes were composed of graphite (MAG-D20, Hitachi), Super C65 (Timcal, Switzerland), sodium carboxymethylcellulose (Na-CMC, Dow Wolff Cellulosics) and styrene-butadiene rubber (SBR, JSR Micro) at a weight ratio of 95.8:1:1:2.2. The slurry was prepared by dispersing graphite, Super C65 and Na-CMC in highly pure water (18 M\u0002 cm, Merck Millipore, Germany) using a planetary mixer (Thinky, USA; at $2000~\\mathrm{rpm}$ for 30 minutes). The slurry was ultrasonicated for 10 minutes in an ultrasonic bath. SBR was added to the slurry and mixed at $500~\\mathrm{rpm}$ for 2 minutes. The ink was coated onto copper foil (thickness $12\\upmu\\mathrm{m}$ , MTI Corporation, USA) using a gap bar coater (RK PrintCoat Instruments, UK). The coating was dried at $50^{\\circ}\\mathrm{C}$ in air, punched out, dried overnight at $120^{\\circ}\\mathrm{C}$ under vacuum in a glass oven (B¨uchi oven, s. above) and transferred to a glove box without exposure to ambient air. \n\nThe specific surface areas of the NMC and LNMO were determined by BET, using an Autosorb iQ nitrogen gas sorption analyzer (Quantachrome Instruments, USA). The determined BET areas of these materials are $0.26~\\mathrm{m}^{2}/\\mathrm{g}$ , $0.35~\\mathrm{m}^{2}/\\mathrm{g}$ , $0.18~\\mathrm{m}^{2}/\\mathrm{g}$ , and $0.23~\\mathrm{m}^{2}/\\mathrm{g}$ for NMC111, NMC622, NMC811, and LNMO, respectively. \n\nElectrochemical characterization.—The electrochemical characterization of NMC was performed in Swagelok T-cells which were assembled in an argon filled glove box $(\\mathbf{O}_{2}$ and $\\mathrm{H}_{2}\\mathrm{O}<0.1$ ppm, MBraun, Germany), with NMC as working electrode $\\mathrm{10~mm}$ diameter) \n\nand graphite as counter electrode $\\mathrm{11~mm}$ diameter). The areal mass loading of the NMC electrodes was $15.5\\pm1\\mathrm{mg}/\\mathrm{cm}^{2}$ and the one of the graphite electrodes was adapted according to the mass loading of the NMC electrodes and their specific capacities at the various cutoff voltages, aiming to achieve a constant balancing factor. The areal capacity of the anode (in $\\mathrm{mAh}/\\mathrm{cm}^{2}$ ) was 1.2-fold oversized compared to the cathode (referenced to the reversible capacities of NMC and graphite at a 1 C-rate; if referenced to $\\mathrm{0.1~C}$ , the anode is roughly 1.1-fold oversized). To monitor the potential of both the NMC cathode and the graphite anode, a lithium reference electrode (thickness $0.45\\mathrm{mm}$ , battery grade foil, $99.9\\%$ , Rockwood Lithium, USA) was used. Two glass fiber separators (glass microfiber filter, 691, VWR, Germany) punched to a diameter of $11\\ \\mathrm{mm}$ were used between working and counter electrode, and one at the reference electrode (diameter of $10~\\mathrm{mm}^{\\cdot}$ ). $80~\\upmu\\mathrm{L}$ of LP57 electrolyte $(1\\mathrm{~M~LiPF}_{6}$ in EC:EMC 3:7 wt/wt, $<20\\mathrm{\\ppm\\H_{2}O}$ , BASF, Germany) were used between working and counter electrode and $40~\\upmu\\mathrm{L}$ were added to the reference electrode side. The cells were cycled in a climate chamber (Binder, Germany) at $25^{\\circ}\\mathrm{C}$ with a battery cycler (Series 4000, Maccor, USA). All cells were cycled 300 times at 1 C with a lower cutoff of $3\\mathrm{V}$ and an upper cutoff of 4.2, 4.4, or $4.6\\mathrm{V}$ for NMC111 and NMC622, and 4.0, 4.1, $4.2\\mathrm{V}$ for NMC811. Prior to cycling, the formation of the cells was done with 2 cycles at $0.1\\mathrm{{C}}$ in the voltage range between $3\\mathrm{~V~}$ and $4.2~\\mathrm{V}.$ If the upper cutoff was ${>}4.2~\\mathrm{V}.$ , the first cycle after formation, i.e., the third cycle of the cell was also done at $0.1~\\mathrm{C}$ to the specified upper cutoff. For upper cutoff voltages $<4.2~\\mathrm{V},$ i.e., for the NMC811 cells also the upper cutoff during formation was adapted to this voltage. The C-rate was referenced to the approximate reversible capacity of the NMC at 1 C: i) 140, 160, and $180\\ \\mathrm{mAh/g}$ for NMC111 at upper cutoff voltages of 4.2, 4.4, and $4.6\\mathrm{~V~}$ respectively; ii) 160, 180, and $200\\ \\mathrm{\\mAh/g}$ for NMC622 at upper cutoff voltages of 4.2, 4.4, and $4.6\\mathrm{V},$ , respectively; and, iii) 130, 150, and $170{\\mathrm{mAh/g}}$ for NMC811 at cutoff voltages of 4.0, 4.1, and $4.2\\mathrm{V},$ respectively. The charge was done in constant current-constant voltage (CCCV) mode with a current limitation corresponding to C/20, while the discharge was done in constant current (CC) mode. Two cells were built for each combination of NMC material and cutoff voltage and the error bars in the figures represent the standard deviation from two cells for each combination. \n\nFor recording $\\mathrm{dq/dV}$ plots, NMC-graphite full-cells were assembled as described above and were cycled in a climate chamber (Binder, Germany) at $25^{\\circ}\\mathrm{C}$ with a battery cycler (Series 4000, Maccor, USA). The formation of the cells was done at $0.1\\mathrm{C}$ (two cycles) in the voltage range between $3\\mathrm{V}$ and $4.2\\mathrm{V}.$ In the third cycle, the cutoff voltage was increased to $4.8\\mathrm{V}.$ . The lower cutoff was kept constant at $3\\mathrm{V}.$ . The dq/dV plot of the third cycle will be shown in the Results section. \n\nOn-line electrochemical mass spectrometry (OEMS).—Two different types of OEMS experiments were designed and performed with either NMC or spinel LNMO (diameter $15\\mathrm{mm}$ ) as working electrode, and either metallic lithium or graphite as counter electrode. With metallic lithium as counter electrode (lithium metal foil, diameter $16~\\mathrm{mm}$ , thickness $0.45~\\mathrm{mm}$ , battery grade foil, $99.9\\ \\%$ , Rockwood Lithium, USA), two H2013 polyolefin separators (diameter $28~\\mathrm{mm}$ , Celgard, USA) and $120~\\upmu\\mathrm{L}$ of LP57 electrolyte $(1\\mathrm{~M~LiPF}_{6}$ in EC:EMC 3:7 wt/wt, $<20\\mathrm{ppmH}_{2}\\mathrm{O}$ , BASF, Germany) were employed. The cells were charged up to $5\\mathrm{\\DeltaV}$ at a $0.05\\mathrm{C}$ -rate (referenced to the theoretical capacities of NMC111, NMC622, NMC811, and LNMO of $277.8\\ \\mathrm{mAh/g},276.5\\ \\mathrm{mAh/g},275.5\\ \\mathrm{mAh/g}$ , and $147\\mathrm{mAh/g}$ , respectively). The loadings of the cathodes were $\\mathrm{15.8~mg/cm^{2}}$ (NMC111), $15.5\\mathrm{mg}/\\mathrm{cm}^{2}$ (NMC622), $15.0\\mathrm{mg/cm^{2}}$ (NMC811), and $17.5\\mathrm{mg}/\\mathrm{cm}^{2}$ (LNMO). All electrodes were coated on H2013 separator (Celgard, USA). \n\nWith graphite as the counter electrode (diameter $16\\mathrm{mm}$ , see upper section for details on the type of graphite), two glass fiber separators (diameter $28~\\mathrm{mm}$ , glass microfiber filter, 691, VWR, Germany) and $400\\upmu\\mathrm{L}$ of $1.5\\mathrm{MLiPF}_{6}$ in ethylene carbonate (EC, BASF, Germany) were employed. The mixture of EC with $\\mathrm{LiPF}_{6}$ is a liquid at room temperature due to the melting point depression caused by the addition of $\\mathrm{LiPF}_{6}$ . The cells were cycled 4 times at a $0.2\\mathrm{C}$ -rate (referenced to the above given theoretical capacities of the NMC materials) in the voltage range $2.6{-}4.8\\mathrm{~V~}$ for NMC111 and NMC622 and from $2.6{-}4.4\\mathrm{~\\overset{.}{V}}$ for NMC811. The loadings of the cathode active material were $9.4~\\mathrm{mg/cm^{2}}$ (NMC111), $\\mathrm{11.4~mg/cm^{2}}$ (NMC622), and $9.3~\\mathrm{mg/cm}^{2}$ (NMC811) and the electrodes were coated on stainless steel mesh (see above for details). The graphite counter electrode was capacitively 1.4-fold oversized (referenced to the theoretical capacities of NMC and graphite). \n\nAll cells were assembled in a glove box with argon atmosphere $(\\mathbf{O}_{2}$ and $\\mathrm{H}_{2}\\mathrm{O}<0.1$ ppm, MBraun, Germany). The cells were placed in a climate chamber at $25^{\\circ}\\mathrm{C}$ (Binder, Germany) and connected to the potentiostat (Series G300 potentiostat, Gamry, USA) and the mass spectrometer system, which has been described in detail elsewhere.39 The cells were held at OCV for $\\boldsymbol{4\\mathrm{h}}$ before starting the above described protocols. The gas evolution during the OCV and the charging/cycling period was recorded by OEMS. All mass signals were normalized to the ion current of the $^{36}\\mathrm{Ar}$ isotope to correct for fluctuations of pressure and temperature. Conversion of the ion currents to concentrations was done for $\\mathbf{O}_{2}$ , $\\mathrm{CO}_{2}$ , $\\mathrm{H}_{2}$ , $\\mathrm{C}_{2}\\mathrm{H}_{4}$ , and CO using calibration gases (Ar with $2000\\ \\mathrm{ppm}$ each of $\\mathrm{H}_{2}$ , $\\mathbf{O}_{2}$ , ${\\mathrm{C}}_{2}{\\mathrm{H}}_{4}$ , and $\\mathrm{CO}_{2}$ as well as Ar with 2000 ppm each of $\\mathrm{H}_{2}$ , $\\mathbf{O}_{2}$ , CO, and $\\mathrm{CO}_{2}$ ; Westfalen, Germany) and based on a cell volume of $9.5\\mathrm{cm}^{3}$ . Unlike all other gases quantified in this work, CO does not have a unique $\\mathrm{m/z}$ channel. Therefore the amount of CO was determined on channel $\\mathrm{m/z}=28$ , which was corrected for the fractions of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and $\\mathbf{CO}_{2}$ both of which give additional intensity to channel $\\mathrm{m/z}=28$ . The fraction of the signal on channel $\\mathrm{m/z}=28\\$ stemming exclusively from CO was therefore calculated as the total signal on channel $\\mathrm{m}/\\mathrm{z}=28$ subtracted by 1.51 times the signal on channel $\\mathrm{m/z}=26$ and 0.14 times the signal on channel $\\mathrm{m}/\\mathrm{z}=44$ , with the factors 1.51 and 0.14 being the fractions of $\\mathrm{{C}_{2}\\mathrm{{H}_{4}}}$ and $\\mathrm{CO}_{2}$ on channel $\\mathrm{m}/\\mathrm{z}=28$ compared to their unique signals on $\\mathrm{m/z}=26\\left(\\mathrm{C}_{2}\\mathrm{H}_{4}\\right)$ and $\\mathrm{m}/\\mathrm{z}=44\\left(\\mathrm{CO}_{2}\\right)$ , respectively. These factors were determined by flowing pure $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and $\\mathrm{CO}_{2}$ through the OEMS cell and recording the resulting signals originating from the pure gases.40 \n\n# Results \n\nElectrochemical cycling of NMC-graphite cells.—Figure 1a shows the cycling stability of NMC111-graphite full-cells with different upper cutoff voltages of 4.2, 4.4, and $4.6\\mathrm{V}$ . The cells have a very stable cycling performance for upper cutoff voltages of $4.2\\mathrm{V}$ and $4.4\\dot{\\mathrm{V}}$ (black and gray lines), however, cycling to $4.6\\mathrm{~V~}$ leads to a fast capacity fading (light gray line), which is in agreement with previous reports in the literature.9,11,13 While the error bars are hardly visibly for cutoff voltages $\\leq4.4\\mathrm{~V~}$ and at low cycle numbers at a cutoff of $4.6~\\mathrm{V},$ , the error bars at higher cycle numbers significantly increase, which is due to the delayed onset of the so-called rollover-failure for the two cells. This failure mechanism was described previously by Dubarry et al. and Burns et al. and was shown to be due to growing kinetic resistances or more generally an impedance buildup.41,42 In our data the increasing polarization stems almost exclusively from the NMC cathodes, which will be discussed below. The coulombic efficiencies (right axis in Figure 1a) for cells cycled to $4.2~\\mathrm{V}$ and $4.4\\mathrm{~V~}$ are in average ${>}99.9\\%$ , indicating the absence of major side reactions. When the end-of-charge voltage is increased to $4.6~\\mathrm{V},$ , the coulombic efficiency decreases to ${\\sim}99.6\\%$ (before the onset of the rollover-failure), reflecting an increasing loss of cyclable lithium. A further decrease of the coulombic efficiency is observed at the onset of the rollover-failure. On the other hand, any increase in the polarization during cell discharge can be monitored by plotting the charge-averaged mean discharge voltage, defined as: \n\n$$\n\\begin{array}{r}{\\bar{\\bf V}_{\\mathrm{discharge}}=\\int{\\bf V}_{\\mathrm{discharge}}\\mathrm{~\\boldmath~\\cdot~}\\mathrm{d}{\\bf q}_{\\mathrm{discharge}}\\mathrm{~\\boldmath~/~}\\int\\mathrm{d}{\\bf q}_{\\mathrm{discharge}}}\\end{array}\n$$ \n\nAs the cells were cycled with a lithium reference electrode, $\\bar{\\nabla}_{\\mathrm{discharge}}$ can be determined independently for the NMC111 cathode $(\\equiv\\bar{\\mathrm{\\boldmath~V~}}$ cdiastchhoadrege) and the graphite anode $(\\equiv\\bar{\\mathrm{V}}_{\\mathrm{discharge}}^{\\mathrm{anode}})$ for each end-ofcharge voltage as a function of the cycle number, which is depicted in Figure 1b by the solid and dashed lines, respectively. While the energy \n\n![](images/937fe8c5ef6133c32739a4d946bbd47a3327f4eb829ad495ab26ca24817a7488.jpg) \nFigure 1. (a) Specific discharge capacity and coulombic efficiency of NMC111-graphite cells and (b) charge-averaged mean discharge voltage (s. Eq. 1) of the NMC111 cathode (≡ ¯Vcdiastchhoadrege; solid lines) and the graphite anode $(\\equiv\\bar{\\nabla}_{\\mathrm{discharge}}^{\\mathrm{anode}}$ ; dashed lines) vs. cycle number in LP57 electrolyte $\\mathrm{1\\MLiPF_{6}}$ in EC:EMC 3:7) operated with different upper cutoff voltages $(4.2\\mathrm{~V},4.4\\mathrm{~V},$ , $4.6\\mathrm{~V~}_{\\cdot}$ ) and a constant lower cutoff voltage of $3.0{\\mathrm{~V}}.$ Formation was done at a rate of $0.1\\mathrm{{C}}$ . Cycling was performed at $1\\mathrm{C}$ and $25^{\\circ}\\mathrm{C}$ . For each condition, two independent cells were run and the data in the figure always represent the average of two cells (the error bars in (a) represent the standard deviation between the two cells). \n\nfading of the cells is further detailed in the Discussion section, it may tdmoertchcheoanpirdsiotmdio,unic.tse.o,wfhnceatrhpeeatcahibteyseaonsncsde $\\bar{\\mathrm{\\DeltaV}}_{\\mathrm{discharge}}=\\bar{\\mathrm{V}}_{\\mathrm{discharge}}^{\\mathrm{cathode}}-\\bar{\\mathrm{V}}_{\\mathrm{discharge}}^{\\mathrm{anode}}$ Vdischarge e.agegUifnog-r like NMC would be expected to gradually increase with the number of cycles. This can indeed be seen when cycling with an upper cutoff potential of $4.2\\mathrm{V}$ (solid black line in Figure 1b). On the other hand, when impedance buildup becomes dominant, V¯ cdiastchhoadrege decreases with the number of cycles, as can be seen when the upper cutoff potential reaches $4.6\\mathrm{~V~}$ (solid light gray line in Figure 1b). Interestingly, the charge-averaged mean discharge voltages of the graphite anodes ( ¯Vanode discharge) remain fairly constant over the complete number of cycles, even at high end-of-charge voltages. This suggests that a crucial contributing factor for the fast capacity fading of the NMC111-graphite cells at an upper cutoff of $4.{\\bar{6}}\\ \\mathrm{V}$ is a strong impedance buildup on the NMC111 cathode rather than on the graphite anode. In fact, previous reports in the literature showed a drastic rise of the low frequency semicircle in the impedance spectra of NMC111-graphite11 and NMC442-graphite cells,43,44 which was attributed to the positive electrode. Later, Petibon et al. showed that the increase of impedance in NMC442-graphite cells operated at high cutoff potentials, indeed stems from the positive electrode, proven by using symmetric cells.45 Even though these results are consistent with our observations on the charge-averaged mean discharge voltage (Figure 1b) one has to be careful since an additive-containing electrolyte was used in \n\n![](images/212a9cad8c4cf757f902d5fc20779ee31438272ccf8c4a4eef672a38ceb4cfb9.jpg) \nFigure 2. (a) Specific discharge capacity and coulombic efficiency of NMC622-graphite cells and (b) charge-averaged mean discharge voltage (s. Eq. 1) of the NMC622 cathode (≡ ¯Vcdiastchhoadrege; solid lines) and the graphite anode $(\\equiv\\bar{\\nabla}_{\\mathrm{discharge}}^{\\mathrm{anode}}$ ; dashed lines) vs. cycle number in LP57 electrolyte $(1~\\mathrm{M}~\\mathrm{LiPF_{6}}$ in EC:EMC 3:7) operated with different upper cutoff voltages $(4.2\\mathrm{~V},4.4\\mathrm{~V};$ , $4.6\\mathrm{\\V}$ ) and a constant lower cutoff voltage of $3.0\\mathrm{V}.$ . Formation was done at a rate of $0.1\\mathrm{{C}}$ . Cycling was performed at $1\\mathrm{C}$ and $25^{\\circ}\\mathrm{C}$ . For each condition, two independent cells were run and the data in the figure always represent the average of two cells (the error bars in (a) represent the standard deviation between the two cells). \n\nReferences 43–45, which likely causes a different surface film formation and impedance. A detailed discussion about the reason for the rise in the polarization of NMC111 with upper cutoff potential is given in the Discussion section. \n\nFigure 2a shows the cycling stability of NMC622-graphite cells. Similar to the case of the NMC111-graphite cells also NMC622- graphite cells can be cycled stably to upper cutoff voltages of $4.2\\:\\mathrm{V}$ and $4.4\\mathrm{V}$ with excellent coulombic efficiencies of ${>}99.\\dot{9}\\%$ , whereas at an upper cutoff potential of $4.6~\\mathrm{V},$ , the capacity fades rapidly and the coulombic efficiency decreases to ${\\sim}99.6\\%$ (before the rolloverfailure), as was observed for NMC111. In analogy to the cells with NMC111, the occurrence of a rollover-failure41,42 at $4.6\\mathrm{V}$ cutoff indicates growing polarization and causes the large error bars at high cycle numbers as described above. Also with respect to the mean discharge voltages, NMC622 (s. Figure 2b) is very similar to NMC111: V¯ cdiastchhoadrege slightly increases with cycle number for $4.2\\mathrm{V}$ cutoff voltage, remains essentially constant for $4.4\\:\\mathrm{V}$ cutoff voltage, and decreases rapidly at $4.6\\mathrm{V}$ cutoff voltage, proving a continuous impedance growth of the hvaolntda,ge¯V.adinsocdhearge remains essentially constant, independent of the cutoff \n\nFigure 3a displays the cycling performance of $\\mathrm{\\cdotLiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}}$ (NMC811)-graphite cells. Due to the less stable cycling behavior of NMC811, the upper cutoff voltages were limited to $4.0\\mathrm{V},4.1\\mathrm{V};$ and $4.2\\mathrm{V}$ . It can be observed that the NMC811 only performs fairly stable with a coulombic efficiency ${>}99.9\\%$ , when the upper cutoff voltage is set to $4.0\\mathrm{V}.$ For cutoff potentials of $4.1\\mathrm{V}$ and $4.2\\mathrm{V}.$ , poor cycling stability is observed. In order to aid the comparison between the different NMCs, the capacity retentions measured between the $5^{\\mathrm{th}}$ and the $300^{\\mathrm{th}}$ cycles at a 1C-rate for all cells presented in Figures 1–3 are summarized in Table I. Stable cycling with capacity retentions $290\\%$ is possible for NMC111 and NMC622 up to $4.4\\mathrm{V}$ and for NMC811 only up to $4.0\\mathrm{V},$ , whereby its capacity retention is still clearly lower than that for the cells with NMC111 and NMC622 cycled to $4.4\\mathrm{V}.$ It is interesting to note that the measured specific capacity of NMC811 at a $4.2\\mathrm{V}$ cutoff is similar to the one of NMC622 at $4.4\\mathrm{V}$ (see values in parentheses in Table I), however, with the latter one still having a stable cycling performance. The impact of the different cutoff voltages on the specific energy of the cells will be picked-up again in the Discussion section. The coulombic efficiencies for the NMC811- graphite cells are ${>}99.9\\%$ at $4.0\\mathrm{V}$ cutoff potential, and even at $4.1\\mathrm{V}$ and $4.2\\mathrm{~V~}$ where pronounced capacity fading is observed, their coulombic efficiency remains at ${\\sim}99.9\\%$ , i.e., similar to that of the NMC111 and NMC622 cells at $4.4\\mathrm{V}.$ The fact that the latter display substantially lower capacity fading suggests that its origin must be an enhanced cathode and/or anode impedance growth. \n\n![](images/a1e4b3cf4ac6101cce4d39c4d13c7333b549c2c86da1825a0788372345a0ba8a.jpg) \nFigure 3. (a) Specific discharge capacity and coulombic efficiency of ENqM. 1C)8o1f1t-hgeraNpMhitCe8c1e1llcsatahnod e( $(\\equiv\\bar{\\mathsf{V}}_{\\mathrm{discharge}}^{\\mathrm{cathode}}$ ;e rsaoglied imnesa)nandidstcheargreapvhoitlteaagneo(dse. $(\\equiv\\bar{\\nabla}_{\\mathrm{discharge}}^{\\mathrm{anode}}$ ; dashed lines) vs. cycle number in LP57 electrolyte $(1~\\mathrm{M}~\\mathrm{LiPF}_{6}$ in EC:EMC 3:7) operated with different upper cutoff voltages $(4.0\\mathrm{~V},4.1\\mathrm{~V},$ $4.2\\:\\mathrm{V}_{\\cdot}$ ) and a constant lower cutoff voltage of $3.0~\\mathrm{V}.$ Formation was done at a rate of $0.1\\mathrm{C}$ . Cycling was performed at $1\\mathrm{C}$ and $25^{\\circ}\\mathrm{C}$ . For each condition, two independent cells were run and the data in the figure always represent the average of two cells (the error bars in (a) represent the standard deviation between the two cells). \n\nThe mean discharge voltages versus cycle number of the NMC811 \ncathodes and the graphite anodes are shown in Figure 3b. Different \nfnruombtehreocbosnesrtvaendt foor revNenMsCli1g1h1tlaynidn cNreMasCin6g2 $\\bar{\\mathsf{V}}_{\\mathrm{discharge}}^{\\mathrm{cathode^{-}}}$ vcalutoefsfwpiotthecnyticalle, $4.2\\mathrm{\\check{V}}$ \nthe NMC811 cells display a continuously decreasing V¯ cdiastchhoadrege value, \neven at the lowest cutoff potential of $4.0\\mathrm{V}.$ . At $4.2\\mathrm{V}$ cutoff, V¯ cdiastchhoadrege \ndrops as rapidly with cycle number for NMC811 as in the case of \n\n
TableIeasueapacityrtetetwentheadcleoftheNgrapitecellsiFguresTheluesiacket are the specific capacities in units of mAh/gNMc of the 5t and the 30oth cycles.
4.0 V4.1V4.2V4.4V4.6V
NMC11193% (140.2 → 130.0) 95% (155.4 → 147.3)94% (162.8 → 153.2) 94% (177.8 → 166.8)42% (183.4 > 77.1)
NMC622 NMC81190% (131.9 → 118.1)77% (149.3 → 114.4)66% (172.5 → 114.7)39% (203.1→ 79.9)
\n\n$4.6\\mathrm{V}$ for NMC111 and NMC622, indicating that the observed strong cathode impedance growth sets in at ${\\sim}0.4\\ \\mathrm{\\bar{V}}$ lower cutoff potentials for NMC811. On the other hand, the mean discharge potentials for tsihemiglraarlpyhiatsefoarntohde NinMtChe11N1ManCd8t1h1e-gNraMpChi6t2e2cceellsls $(\\bar{\\bar{\\mathrm{V}}}_{\\mathrm{discharge}}^{\\mathrm{an\\hat{o}d e}})$ nbeghliagvieble increase with cycle number for all cutoff potentials. In summary, the observed capacity decay at $\\mathrm{\\hbar>4.0\\V}$ cutoff potential for NMC811 full-cells and at ${\\bar{>}}4.4{\\mathrm{~V~}}$ for NMC111 and NMC622 full-cells seems to be largely related to the onset of a strong cathode impedance growth (i.e., a strong fading of $\\bar{\\mathsf{V}}_{\\mathrm{discharge}}^{\\mathrm{cathode}})$ ) above these cutoff potentials. \n\nThe above results clearly demonstrate a similarity between NMC111 and NMC622, but a big difference to NMC811 with respect to the onset of the cathode impedance growth. To investigate the origin of this difference and to find the reason for the instability occurring for NMC111 and NMC622 at $4.6\\mathrm{~V~}$ and for NMC811 at $4.1{-}4.2\\mathrm{V}.$ a $\\mathrm{dq/dV}$ plot of the delithiation and lithiation of the three NMC materials in NMC-graphite cells of the $3^{\\mathrm{rd}}$ cycle is depicted in Figure 4. The voltage region up to $3.8\\mathrm{~V~}$ is very similar for all three NMC compositions, with two anodic peaks between $3.4\\mathrm{V}$ and $3.8\\mathrm{V}$ . While the first one originates from the lithium intercalation into the graphite anode, the second one stems from the phase transition from a hexagonal to a monoclinic $(\\mathrm{H}1\\rightarrow\\mathrm{M}$ ) lattice of the NMC.18,46–49 In the region ${>}3.8~\\mathrm{V},$ it becomes very obvious that the $\\mathrm{dq/dV}$ curve for the NMC811 cell deviates substantially from that of the NMC111 and NMC622 cells. In particular, NMC811 has a small anodic feature at ${\\sim}3.95\\mathrm{~V~}$ and a large anodic peak at ${\\sim}4.15~\\mathrm{V},$ , both of which are absent for the other NMCs. The first one belongs to the $\\mathbf{M}\\rightarrow$ H2 phase transition and the latter one corresponds to the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition as was reported before for $\\bar{\\mathrm{LiNiO}_{2}}^{46-48}$ and Ni-rich $\\mathrm{\\hat{NMC}^{18,49}}$ materials. In contrast, for NMCs with Ni-contents ${<}80\\%$ the $\\mathbf{M}\\rightarrow\\mathbf{H}2$ and $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transitions have not been reported. Accordingly, for NMC111 and NMC622 such distinct features are not observed. However, for NMC622 a broad peak around $4.1\\mathrm{V}$ is visible, which might indicate an $\\mathbf{M}\\to\\mathbf{H}2$ phase transition. For both NMC111 as well as NMC622, a clear redox peak is observed at $4.6\\mathrm{V},$ , which could correspond, in analogy to NMC811, to a $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition or could also indicate an oxygen redox feature, a process which has been suggested for $\\mathrm{Li_{2}R u_{\\mathrm{1-y}}S n_{y}O_{3}}^{50}$ and $\\mathrm{Li}_{2}\\mathrm{IrO}_{3}{}^{51}$ by Tarascon’s group and was investigated theoretically using DFT.52,53 The vertical dotted lines mark the upper cutoff voltages which were chosen for the cells presented in the Figures 1–3. Note that up to the onset of the H2 $\\rightarrow\\mathrm{H}3$ phase transition of NMC811 at $\\mathrm{>}4.0\\mathrm{~V~}$ and up to the onset of the redox feature at ${>}4.4\\mathrm{~V~}$ of NMC111 and NMC622, the capacity retention of the materials is very stable. In other words, stable cycling was only possible if the cutoff voltage was below the onset of the last peak in the dq/dV plot. The early onset of the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ transition at $\\bar{>}4.0\\mathrm{V}$ (NMC811) explains why NMC811 cannot be cycled stably at $\\mathrm{>}4.0\\mathrm{~V~}$ cutoff voltages, whereas NMC111 and NMC622 cells show an excellent performance at potentials as high as $4.4\\mathrm{~V~}$ . The detrimental effect of the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition was already described before for $\\mathrm{LiNiO}_{2}$ and NMC811 and was explained by a significant reduction of the unit-cell volume upon this phase transition, which we will critically review in the Discussion section.18,47 \n\n![](images/81e9fcf6a7094f6c81b5b92298e704c9cd13c856638912ef37e1ddf7605f0468.jpg) \nFigure 4. Differential capacity vs. cell voltage of NMC-graphite cells recorded at a 0.1 C-rate ${\\dot{3}}^{\\mathrm{{rd}}}$ cycle). The vertical dotted lines mark the upper cutoff voltages, which were chosen for the cells in Figures 1–3. The peaks are assigned to their corresponding phase transitions with H1, H2 and H3 representing the three hexagonal phases and M the monoclinic one. $\\mathrm{C}_{6}\\to\\mathrm{LiC}_{\\mathrm{x}}$ indicates the lithiation of graphite. \n\nGas analysis of NMC-Li and LNMO-Li half-cells by OEMS.— Figure 5 shows the results of On-line Electrochemical Mass Spectrometry (OEMS) measurements with NMC-Li and LNMO-Li half-cells. For these experiments, metallic lithium was chosen as a counterelectrode in order to achieve a stable reference potential. Figure 5a displays the voltage profiles of NMC111 (black), NMC622 (red), NMC811 (green) as well as LNMO (blue) upon the first charging from OCV to $5\\mathrm{V}$ at a $0.05\\mathrm{C}$ -rate and $25^{\\circ}\\mathrm{C}$ as a function of the stateof-charge (SOC) (note that $100\\%$ SOC is defined as the removal of all lithium from the cathode materials; s. Experimental section). The three lower panels show the total moles of evolved gas, normalized to the BET surface area of the cathode active material (CAM) in units of $\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{CAM}}^{2}$ for $\\mathbf{O}_{2}$ (Figure 5b), $\\mathrm{CO}_{2}$ (Figure 5c), and CO (Figure 5d). Note that normalization of the gassing data to the BET surface area is meant to account for the differences in the available surface area for electrochemical oxidation reactions. Figure 5b demonstrates that for all three NMC compositions a release of oxygen can be detected near a state-of-charge of ${\\sim}80{\\sim}90\\%$ , corresponding to onset potentials for $\\mathbf{O}_{2}$ evolution of ${\\sim}4.3\\mathrm{~V~}$ vs. $\\mathrm{Li/Li^{+}}$ (or ${\\sim}4.2\\mathrm{~V~}$ cell voltage in a full-cell vs. graphite) for NMC811 and of ${\\sim}4.7\\ \\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ (or ${\\sim}4.6\\mathrm{~V~}$ cell voltage in a full-cell vs. graphite) for NMC111 and NMC622 (this will be seen more clearly later, when discussing Figure 6). The observed onset for $\\mathbf{O}_{2}$ evolution on NMC111 at ${\\sim}80\\%$ SOC during electrochemical delithiation (s. Figure 5) is in surprisingly good agreement with the observed onset for oxygen loss upon the chemical delithiation of NMC111 (with ${\\mathrm{NO}}_{2}{\\mathrm{BF}}_{4}$ ), which was found to initiate at a lithium content corresponding to ${\\sim}75\\%$ SOC.6 The scatter in the reported $\\mathbf{O}_{2}$ concentration of ca. $\\pm0.5~\\upmu\\mathrm{mol}_{\\mathrm{O}_{2}}/\\mathrm{m}^{2}\\mathrm{cam}$ for NMC111 and NMC622 and of ca. $\\pm1\\upmu\\mathrm{mol}_{\\mathrm{O}_{2}}/\\mathrm{m}^{2}\\mathrm{cam}$ for NMC811 corresponds to our experimental error in quantifying the $\\mathrm{O}_{2}$ concentration of ca. $\\pm10\\ \\mathrm{ppm}$ . As was already reported previously,54 no $\\mathbf{O}_{2}$ evolution is observed for the LNMO half-cell up to $5.0\\mathrm{V}$ . \n\nAt roughly the same potentials at which the evolution of $\\mathbf{O}_{2}$ initiates, a strong increase of the $\\mathrm{CO}_{2}$ (Figure 5c) and the CO (Figure 5d) evolution rates (i.e., an increase in the slope of the lines) is observed for all NMC materials. Here it should be noted that the more gradual increase of the $\\mathrm{CO}_{2}$ concentration (Figure 5c) starting at low SOC values is believed to be due to the electrooxidation of $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ impurities (reported to occur in the potential range above ${\\sim}3.7\\ \\mathrm{V}^{55}$ to $\\mathrm{\\sim}4.0\\ \\mathrm{V}^{12}$ ) and possibly of transition metal carbonates in the first charge depicted in Figure 5. In this case, one would expect that the $\\mathrm{CO}_{2}$ evolution at low voltages (i.e., below ${\\sim}4.2\\mathrm{V}$ ) would be absent in the second charge, which indeed is the case (see discussion of Figures 7–9). In addition, the fact that the evolution of CO does not occur until the onset of $\\mathbf{O}_{2}$ evolution (s. Figure 5d) is consistent with the assumption that the $\\mathbf{CO}_{2}$ evolution at lower potentials is due to the oxidation of carbonate impurities. The very similar onsets of $\\mathbf{O}_{2}$ , $\\mathrm{CO}_{2}$ and CO evolution raise the question whether the formation of $\\mathrm{CO}_{2}$ and CO at higher potentials is only due to the electrooxidation of the electrolyte and/or the conductive carbon on the cathode surface, or if it is linked to the release of highly reactive oxygen (e.g., atomic oxygen or singlet oxygen) from the NMC lattice and its subsequent chemical reaction with electrolyte and/or conductive carbon to CO and $\\mathrm{CO}_{2}$ . We will present a detailed answer to this fundamental question in the Discussion section, and first present the other experimental results. \n\n![](images/fb94117a316d5cd453b6c26eb3407f62c23dfbe9dfbfcb5c79269682a0692982.jpg) \nFigure 6. (a) Specific differential capacity vs. cell voltage of the NMC-Li cells shown in Figure 5. (b) Evolution of $\\mathrm{O}_{2}$ as a function of the cell voltage. The OEMS data are smoothed, baseline corrected, and converted into units of $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}]$ . \n\n![](images/60ad12b2eb6151d60d0ccfa1a3ac156151b45f00d07818e6b3bf9aa980d20d11.jpg) \nFigure 5. (a) Cell voltage vs. specific capacity of NMC-Li cells using NMC111 (black), NMC622 (red), NMC811 (green), and LNMO (blue). The cells contain $120\\upmu\\mathrm{LLP}57$ electrolyte $\\mathrm{1MLiPF_{6}}$ in EC:EMC 3:7) and Celgard H2013 separators. The total moles of evolved gases in the OEMS cell, normalized by the cathode active material (CAM) BET area versus the theoretical state-of-charge (SOC) is shown for (b) $\\mathrm{O}_{2}$ , (c) $\\mathrm{CO}_{2}$ , and (d) CO. \n\nAgain, in contrast to the data shown for the NMC materials, no CO evolution is observed for the LNMO half-cell up to $5.0~\\mathrm{V},$ and only minor amounts of $\\mathrm{CO}_{2}$ $({\\sim}10\\upmu\\mathrm{mol/m}_{\\mathrm{CAM}}^{2})$ ) are formed at ${\\sim}15\\%$ SOC (corresponding to ${\\sim}4.5\\mathrm{\\V}$ ), which are likely due to the oxidation of low amounts of carbonate impurities on the surface of LNMO. This is at variance with Luo et al.,35 who observed the formation of $\\mathrm{CO}_{2}$ on LNMO surfaces above $4.75\\mathrm{~V~}$ (at room temperature), which they suggested to be due to the electrooxidation of electrolyte. While we cannot explain this discrepancy, we do not observe any significant $\\mathrm{CO/CO}_{2}$ formation on LNMO at ${>}4.7\\mathrm{~V~}$ and up to $5.0\\mathrm{V}$ (i.e., after the initial formation from presumably surface impurities), so that we believe that the electrochemical oxidation of the electrolyte and/or the carbon support is negligible on LNMO surfaces up to $5.0\\mathrm{V}$ at $25^{\\circ}\\mathrm{C}$ (this is consistent with our previous OEMS study54). The fact that hardly any gas evolution is observed at operating voltages as high as $5\\mathrm{V}$ for LNMO but that significant $\\mathrm{CO/CO}_{2}$ formation is observed for the NMC materials at ${>}4.2\\ \\mathrm{V}.$ , supports the hypothesis that the CO and $\\mathbf{CO}_{2}$ evolution is at least partially a consequence of the release of reactive oxygen from the NMC lattice. A catalytic effect of Ni or Co on the electrolyte oxidation also appears unlikely, as the gas evolution for NMC111 and NMC622 shows great similarity, although the materials differ in both the Ni and the $\\scriptstyle{\\mathrm{Co}}$ content. More clearly, a catalytic effect of Ni species can be ruled out due to their presence in LNMO, which evidently shows insignificant gas evolution up to $5.0\\mathrm{V}.$ . \n\n![](images/ab6231400050aaec1544360b8f2f74aaeac97cf635e1fd961bbba1a6e71142d1.jpg) \nFigure 7. (a) Cell voltage vs. time of a NMC111-graphite cell over four charge/discharge cycles at $0.2~\\mathrm{C}$ and $25^{\\circ}\\mathrm{C}$ between 2.6 and $4.8~\\mathrm{V}_{:}$ , in a cell containing $400~\\upmu\\mathrm{L}$ of $1.5\\mathrm{~M~LiPF}_{6}$ in ethylene carbonate (EC), glassfiber separators and $16.69~\\mathrm{mg}$ NMC111. (b) Evolution of $\\mathrm{CO}_{2}$ (dark blue), $\\mathrm{H}_{2}$ (green), $\\mathrm{C}_{2}\\mathrm{H}_{4}$ (orange), CO (blue), and $\\mathrm{O}_{2}$ (black, 10-fold magnified) as a function of time. Solid lines indicate the gases stemming from the NMC electrode and dashed lines from the graphite electrode; gas concentrations are referenced to the NMC BET area (left y-axis) and to the sum of graphite and conductive carbon BET area (right $\\mathbf{x}$ -axis). The OEMS data are smoothed, baseline corrected, and converted into units of $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}]$ and $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}]$ . \n\nIn order to better visualize the gas evolution at the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition for NMC811 and at the redox feature at ${\\sim}4.6\\mathrm{\\V}$ for NMC111 and NMC622, which were shown to be detrimental for the cycling stability, the charging curves of the NMC materials in Figure 5 are now plotted in their $\\mathrm{dq/dV}$ representation and the corresponding $\\mathbf{O}_{2}$ evolution data are shown as a function of the potential (see Figure 6). The observed peaks in the specific differential capacity vs. voltage plot (Figure 6a) are in good agreement with the features observed in Figure 4 (note that the positive shift of ${\\sim}0.1\\mathrm{v}$ in the peak positions in Figure 6a is due to the fact that in Figure 4 the full-cell potential is plotted, whereas in Figure 6a the potential is plotted vs. Li). Figure 6b depicts the $\\mathrm{O}_{2}$ evolution and demonstrates clearly that the onset potential of $\\mathbf{O}_{2}$ evolution fits very well to the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition (NMC811) and to the redox feature at ${\\sim}4.6\\mathrm{V}$ (NMC111 and NMC622), indicating that the release of oxygen is not related to a specific potential, but is rather depending on the occurrence of this very last peak in the dq/dV plot. \n\nGas analysis of NMC-graphite full-cells by OEMS.—In order to investigate if oxygen release occurs only in the first cycle or also in the subsequent ones, the gas evolution was measured for all three NMC materials cycled four times in a full-cell setup at $0.2~\\mathrm{C}$ vs. a graphite anode. In order to avoid signal fluctuations (i.e., on the oxygen channel $\\mathrm{m}/\\mathrm{z}=32\\$ ) coming from the transesterification of the linear carbonate EMC,40,56–58 the LP57 electrolyte is replaced by $1.5\\mathrm{~M~LiPF}_{6}$ in EC for these full-cell experiments. Additionally, due to the low vapor pressure of EC, the background signals from the electrolyte decrease by two orders of magnitude, leading to an improved signal to noise ratio in the mass spectrometer.59 Since we are particularly interested in the oxygen release occurring at the last peak in the $\\mathrm{dq/dV}$ plot (see Figure 4 and Figure 6), the upper cutoff potentials were $4.8\\mathrm{~V~}$ for NMC111 and NMC622, and $4.4\\mathrm{~V~}$ for NMC811 (compare to features in Figure 4 and Figure 6a). The first four cycles of the NMC111-graphite cell are depicted in Figure 7a together with the corresponding evolution/consumption of $\\mathrm{CO}_{2}$ , $\\mathrm{H}_{2}$ , $\\mathrm{O}_{2}$ , CO, and ${\\mathrm{C}}_{2}{\\mathrm{H}}_{4}$ in Figure 7b. From the beginning of the first charge, a steep increase of the ethylene signal (dashed orange line) is observed, which is caused by the reduction of EC in the course of the SEI formation on the graphite electrode.12,60–62 Once the SEI is formed, the reduction of EC stops, so that the ethylene concentration stays constant at around $8\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}$ (s. right-hand y-axis), an amount equal to ${\\sim}1.2$ monolayers of the main EC reduction product lithium ethylene dicarbonate (LEDC) on the graphite anode.12 Simultaneously with the ethylene evolution, roughly $1.{\\overset{\\cdot}{2}}\\ \\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}$ carbon monoxide (dashed light-blue line) are evolved (after ca. 2.5 hours), which are typically ascribed to a minor EC reduction pathway with the ring opening at the carbonyl carbon atom.12,63 Subsequently, the CO signal shows a stepwise increase, which will be discussed in the next paragraph. Furthermore, hydrogen (dashed green line) starts to evolve from the beginning of the measurement, due to the reduction of trace water in the electrolyte.12,64 The $\\mathrm{H}_{2}$ signal initially evolves at a fast rate and then gradually approaches a concentration of ${\\sim}12~\\mathrm{\\upmumol/m}_{\\mathrm{{C}}}^{2}$ by the end of the measurement. The reason why the $\\mathrm{H}_{2}$ evolution does not stop after the first charge like the ${\\mathrm{C}}_{2}{\\mathrm{H}}_{4}$ evolution is, we believe, caused by the formation of protic species from electrolyte decomposition and their subsequent reduction at the graphite anode yielding continuous hydrogen evolution.12 \n\n![](images/bb7119e7c1dc0f8f0007a8e95434f18d9afec280d29c79fe0b5f766ae5b5db63.jpg) \nFigure 8. (a) Cell voltage vs. time of a NMC622-graphite cell over four charge/discharge cycles at $0.2\\mathrm{~C~}$ and $25^{\\circ}\\mathrm{C}$ between 2.6 and $4.8~\\mathrm{V}$ , in a cell containing $400~\\upmu\\mathrm{L}$ of $1.5\\mathrm{~M~LiPF}_{6}$ in ethylene carbonate (EC), glassfiber separators and $20.23\\mathrm{\\mg\\NMC}622.$ (b) Evolution of $\\mathrm{CO}_{2}$ (dark blue), $\\mathrm{H}_{2}$ (green), $\\mathrm{C}_{2}\\mathrm{H}_{4}$ (orange), CO (blue), and $\\ensuremath{\\mathbf{O}}_{2}$ (black, 10-fold magnified) as a function of time. Solid lines indicate the gases stemming from the NMC electrode and dashed lines from the graphite electrode; gas concentrations are referenced to the NMC BET area (left y-axis) and to the sum of graphite and conductive carbon BET area (right $\\textbf{\\em X}$ -axis). The OEMS data are smoothed, baseline corrected, and converted into units of $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}]$ and $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}]$ . \n\nBesides $\\mathrm{C}_{2}\\mathrm{H}_{4}$ , CO, and $\\mathrm{H}_{2}$ one can also observe a linear increase of the $\\mathrm{CO}_{2}$ concentration in the first four hours of the measurement (up to ${\\sim}4.6\\mathrm{~V~}$ cell potential) to $50~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}$ . This increase can be assigned to the oxidation of carbonate impurities on the NMC particles, which are typically around $0.1\\%\\mathrm{_wt}$ .12,18 The total $\\mathrm{CO}_{2}$ signal of $50~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}$ corresponds to ${\\sim}50~\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}~\\cdot~0.26~\\mathrm{m}^{2}/\\mathrm{g}$ · $16.69\\ \\mathrm{mg_{NMC}}=217$ nmol $\\mathrm{CO}_{2}$ or to 217 nmol of carbonate (in the case of $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ , it was shown, that one mole of $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ releases one mole of $\\mathrm{CO}_{2}$ upon electrochemical oxidation65). If referenced to $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ $\\left(73.89\\mathrm{g/mol}\\right)$ ), which is customarily done, this would amount to $16\\upmu\\mathrm{g}\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ equal to $0.10\\mathrm{~\\}\\%_{\\mathrm{wt}}$ . \n\n![](images/e5e9b2a4ea8e8a4c95168249989c03bd45e9fa9b4b25bddaaec5c0ea56de3851.jpg) \nFigure 9. (a) Cell voltage vs. time of a NMC811-Graphite cell over four charge/discharge cycles at $0.2\\mathrm{C}$ and $25^{\\circ}\\mathrm{C}$ between 2.6 and $4.4~\\mathrm{V}_{:}$ in a cell containing $400~\\upmu\\mathrm{L}$ of $1.5\\mathrm{~M~LiPF}_{6}$ in ethylene carbonate (EC), glassfiber separators and $16.40~\\mathrm{mg}$ NMC811. (b) Evolution of $\\mathrm{CO}_{2}$ (dark blue), $\\mathrm{H}_{2}$ (green), ${\\mathrm{C}}_{2}{\\mathrm{H}}_{4}$ (orange), CO (blue), and $\\ensuremath{\\mathbf{O}}_{2}$ (black, 10-fold magnified) as a function of time. Solid lines indicate the gases stemming from the NMC electrode and dashed lines from the graphite electrode; gas concentrations are referenced to the NMC BET area (left y-axis) and to the sum of graphite and conductive carbon BET area (right $\\mathbf{x}$ -axis). The OEMS data are smoothed, baseline corrected, and converted into units of $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}]$ and $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}]$ . \n\nAfter four hours, the cell voltage reaches ${\\sim}4.6\\mathrm{V}$ and oxygen starts to evolve. The onset potential fits very well to the one found in Figure 6 (note that in the Figures 7–9 the NMC–graphite full-cell potential is reported, whereas in Figure 6 the potential is measured vs. a metallic lithium counter electrode, the potential of which is ${\\sim}0.1\\mathrm{v}$ below the potential of lithiated graphite). Simultaneously to $\\mathbf{O}_{2}$ , the CO and $\\mathbf{CO}_{2}$ signals increase until the cell switches from the CV-phase at $4.8\\mathrm{V}$ to the discharge, from which point on the CO and $\\mathrm{CO}_{2}$ concentrations stay constant until the cell voltage again increases above ${\\sim}4.6\\mathrm{~V~}$ in the following cycles, where $\\mathbf{O}_{2}$ , $\\scriptstyle{\\mathrm{CO}}$ , and $\\mathrm{CO}_{2}$ evolve again, leading to a stepwise increase of these signals. The fact that after the first cycle no $\\mathbf{CO}_{2}$ is evolved below ${\\sim}4.6\\ \\mathrm{V}$ in any of the subsequent cycles confirms our prior hypothesis that the $\\mathbf{CO}_{2}$ evolution below $4.6\\mathrm{~V~}$ is due to the oxidation of carbonate impurities in the first cycle (s. discussion of Figure 5). By subtracting the amount of CO evolved during the SEI formation $(\\sim1.2\\ \\upmu\\mathrm{mol/m}_{\\mathrm{C}}^{2}$ or ${\\sim}25\\ \\upmu\\mathrm{mol/m}_{\\mathrm{\\scriptsize{NMC}}}^{2})$ and the amount of $\\mathrm{CO}_{2}$ related to carbonate impurity oxidation in the first cycle $(\\sim50~\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2})$ ), the total amount of CO and $\\mathrm{CO}_{2}$ evolved exclusively due to processes at high voltage after the four cycles are ${\\sim}80\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}$ and ${\\sim}180\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}$ , respectively. \n\nWhile the step-like profile of the oxygen signal is similar to that of the CO and $\\mathrm{CO}_{2}$ signal, showing a rapid rise every time the potential goes above ${\\sim}4.6\\mathrm{\\V}$ , it does exhibit a superimposed potentialindependent continuous decrease. This consumption of oxygen in the cell is most likely caused by a slow but steady reduction of the evolved oxygen at the graphite anode, which would be consistent with the observed decreasing consumption rate over time, as a more protective SEI is being formed (note that an analogous consumption of $\\mathrm{CO}_{2}$ is observed in the second and, to a much lesser degree in the third cycle, which appears smaller in magnitude than the $\\mathbf{O}_{2}$ consumption only due to the fact that the oxygen signal is magnified by a factor of ten). Thus, in order to estimate the total amount of evolved oxygen over the four cycles, one can sum up the steep increases of the oxygen signal in each cycle, which gives a total oxygen evolution of ${\\sim}9~\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}$ \n\nNote that all values which are summed up over the four cycles are corrected for the decreasing concentrations due to gas consumption (for $\\mathbf{CO}_{2}$ and $\\mathrm{O}_{2}$ ) on the graphite anode by summing up the increases rather than considering the total concentrations measured at the end of the experiment. Additionally, it is quite apparent that the amount of evolved oxygen decreases from cycle to cycle, which would be consistent with our assumption that the oxygen is released mainly from the near-surface regions of the NMC particles and that its release becomes slower as the oxygen depleted surface layer increases in thickness.36 This hypothesis is also supported by the total amount of released oxygen, which will be discussed in further detail in the Discussion section. \n\nThe results of the analogous experiment with an NMC622-graphite cell cycling at $0.2\\mathrm{~C~}$ between $2.6\\mathrm{~V~}$ and $4.8\\mathrm{~V~}$ are shown in Figure 8. For all gases, a very similar trend as for the NMC111-graphite cell is observed. The total amounts of evolved gases during SEIformation are ${\\sim}8~\\mathrm{\\upmumol/m}_{\\mathrm{C}}^{2}$ of ethylene and ${\\sim}1.2~\\upmu\\mathrm{mol/m}_{\\mathrm{C}}^{2}$ of CO. Additionally, ${\\sim}10~\\mathrm{\\upmumol/m_{C}^{2}}$ of hydrogen is evolved over the course of the experiment. Prior to the onset of oxygen evolution at ${\\sim}4.54\\$ $\\mathrm{\\DeltaV}$ (vertical dotted line), the oxidation of carbonate impurities results in ${\\sim}19\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}\\mathrm{CO}_{2}$ . This corresponds to ${\\sim}19\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}$ · $0.35~\\mathrm{m^{2}/g}\\cdot20.23~\\mathrm{mg_{NMC}}=135~\\mathrm{nmo}$ l $\\mathrm{CO}_{2}$ or to $135\\ \\mathrm{nmol}$ of carbonate. Again, if referenced to $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ , this would amount to $10~\\upmu\\up g$ $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ equal to $0.05~\\%_{\\mathrm{wt}}$ . As was observed for NMC111, no $\\mathrm{CO}_{2}$ is evolved below ${\\sim}4.5\\mathrm{v}$ in any of the subsequent cycles, confirming our prior hypothesis that the $\\mathrm{CO}_{2}$ evolution below $4.5\\mathrm{V}$ is due to the oxidation of carbonate impurities in the first cycle (s. discussion of Figure 5). \n\nBy subtracting the amount of CO evolved during the SEI formation $(\\sim1.2\\upmu\\mathrm{mol/m}_{\\mathrm{C}}^{2}$ or ${\\sim}20\\upmu\\mathrm{mol/m}^{2}\\mathrm{{NMC}})$ and the amount of $\\mathrm{CO}_{2}$ related to carbonate impurity oxidation in the first cycle $(\\sim19~\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2})$ , the total amount of CO and $\\mathrm{CO}_{2}$ evolved exclusively due to processes at high voltage after the four cycles are ${\\sim}79~\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}$ and ${\\sim}171~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}$ , respectively. The estimated amount of evolved oxygen over the four charge/discharge cycles using the above described approach is ${\\sim}6~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}$ . The total amounts of gaseous species are very similar for both the NMC111-graphite and NMC622- graphite cells, illustrating once again a similarity also in the gassing behavior of NMC111 and NMC622 as it was shown in Figure 5 and Figure 6. \n\nLastly, a similar experiment was performed with an NMC811- graphite cell (see Figure 9), except that the upper cutoff voltage was reduced to $4.4~\\mathrm{V},$ , as this voltage is sufficient to include the complete peak stemming from the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ transition (see Figure 4). During the SEI formation a total of ${\\sim}8~\\mathrm{\\upmumol/m}_{\\mathrm{C}}^{2}$ of ethylene and ${\\sim}1.5$ $\\mathrm{|\\upmumol/m}_{\\mathrm{C}}^{2}$ of CO are evolved. These amounts fit very well to the gas amounts detected in the experiments with NMC111 and NMC622 (see Figure 7 and Figure 8), which is expected since the gases at this initial stage of the first cycle were shown to originate solely from the graphite electrode,12 i.e., they are independent of the cathode material. Over the four cycles of the measurement, ${\\sim}13\\upmu\\mathrm{mol/m}_{\\mathrm{C}}^{2}$ of hydrogen are formed, which also fits to the amounts measured in the NMC111 and NMC622 cells. The upper cutoff potential can have an influence mainly on the hydrogen evolution as a result of the cross-talk between cathode and anode.12,42,66 The underlying assumption of the following analysis is that the cross-talk effect be either similar for all the measurements or has only a minor effect on the overall gas evolution. Prior to the onset of oxygen evolution at already ${\\sim}4.2\\mathrm{~V~}$ (vertical dotted line), the oxidation of carbonate impurities results in ${\\sim}80$ $\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}\\mathrm{CO}_{2}$ . This corresponds to ${\\sim}80~\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}{\\cdot}0.18~\\mathrm{m}^{2}/\\mathrm{g}$ · $16.40\\ \\mathrm{mg_{NMC}}=236$ nmol $\\mathrm{CO}_{2}$ (or carbonate). Again, if referenced to $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ , this would amount to $17\\ \\upmu\\mathrm{g}\\ \\mathrm{Li}_{2}\\mathrm{CO}_{3}$ equal to $0.11~\\%_{\\mathrm{wt}}$ . By subtracting the amount of CO evolved during the SEI formation $({\\stackrel{.}{\\sim}}50\\upmu\\mathrm{mol/m}^{2}\\mathrm{NMC})$ ) and the amount of $\\mathrm{CO}_{2}$ related to carbonate impurity oxidation in the first cycle $({\\sim}80\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2})$ , the total amount of CO and $\\mathrm{CO}_{2}$ evolved exclusively at ${>}4.2\\mathrm{~V~}$ (i.e., after the onset of oxygen release) after the four cycles are ${\\sim}70~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}$ and ${\\sim}170~\\mathrm{\\upmumol/m}_{\\mathrm{NMC}}^{2}$ , respectively. The estimated oxygen release over the four cycles is ${\\sim}8\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}$ . Thus, even though the upper cutoff \n\n![](images/b1979bdf72bd3e49fee5519bd14d0cc86994dfed0d3e2578de32a3997bbe41e7.jpg) \nFigure 10. (a) Cell voltage vs. time of a NMC622-graphite cell over the first charge/discharge cycles at $0.2\\mathrm{C}$ and $25^{\\circ}\\mathrm{C}$ between 2.6 and $4.8~\\mathrm{V},$ in a cell containing $400~\\upmu\\mathrm{L}$ of $1.5\\mathrm{~M~LiPF}_{6}$ in ethylene carbonate (EC), glassfiber separators and $18.40\\mathrm{mg}\\mathrm{NMC}622$ . The NMC622 electrode was prepared with $^{13}\\mathrm{\\dot{C}}$ -labeled carbon instead of Super C65. (b) Evolution of $\\mathrm{CO}_{2}$ (dark blue), $\\mathrm{H}_{2}$ (green), $\\mathrm{C}_{2}\\mathrm{H}_{4}$ (orange), CO (blue), and $\\mathbf{O}_{2}$ (black, 10-fold magnified), $^{13}{\\bf C}{\\bar{\\bf O}}_{2}$ (gray, 10-fold magnified) and $^{13}\\mathrm{CO}$ (bright blue, 10-fold magnified) as a function of time. Solid lines indicate the gases stemming from the NMC electrode and dashed lines from the graphite electrode; gas concentrations are referenced to the NMC BET area (left y-axis) and to the sum of graphite and conductive carbon BET area (right $\\mathbf{\\sigma}_{\\mathbf{X}}$ -axis). The OEMS data are smoothed, baseline corrected, and converted into units of $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}]$ and $[\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}]$ \n\npotential in the NMC811-graphite cell is reduced by $0.4\\mathrm{V}$ compared to the NMC111 and NMC622 cells, the amounts of evolved CO, $\\mathrm{CO}_{2}$ , and $\\mathbf{O}_{2}$ are very similar. This finding is remarkable, because if the CO and $\\mathrm{CO}_{2}$ were a result of electrochemical electrolyte oxidation a difference between the amounts measured at $4.4\\mathrm{V}$ and $4.8\\mathrm{~V~}$ would be expected, especially since the electrolyte is commonly believed to be stable against oxidation to CO and $\\mathrm{CO}_{2}$ at potentials as low as $4.4\\mathrm{V}.^{59,67,68}$ One could explain the similar amounts of gas with $4.4\\mathrm{V}$ (NMC811) and $4.8\\mathrm{~V~}$ (NMC111 and NMC 622) cutoff potentials, if one were to assume that $\\mathbf{CO}_{2}$ and CO are actually the result of the oxygen release from the NMC lattice. In consequence, this could mean that the electrochemical oxidation of carbonate electrolytes would actually be negligible or at least very low on NMC surfaces at both 4.4 V and even $4.8\\mathrm{V},$ , if there were no release of lattice oxygen, which in turn would explain the complete absence of $\\mathrm{CO}/\\mathrm{CO}_{2}$ up to $4.8\\mathrm{~V~}$ in EC-only electrolyte on a carbon black electrode at $25^{\\circ}\\mathrm{C}$ .59 This is also supported by the fact that LNMO can be operated at a potential of $4.8\\mathrm{~V~}$ with insignificant $\\mathrm{CO/CO}_{2}$ evolution due to the absence of oxygen release (see Figure 5). \n\nHaving presented substantial evidence that the $\\mathrm{CO/CO}_{2}$ evolution at high potentials is mostly caused by a chemical reaction of the released lattice oxygen, the question remains whether the evolved $\\mathrm{CO/CO_{2}}$ derive from its reaction with the electrolyte or with the conductive carbon in the NMC electrode. Therefore, an NMC622 electrode with $4.4\\:\\%_{\\mathrm{wt}}\\:^{13}\\mathrm{C}$ -labeled carbon as conductive additive was prepared, replacing the Super C65 conductive carbon, such that a reaction of released lattice oxygen with carbon would result in ${}^{13}\\mathrm{CO}/{}^{13}\\mathrm{CO}_{2}$ , while its reaction with electrolyte would result in ${}^{12}\\mathrm{CO}/{}^{12}\\mathrm{CO}_{2}$ . The NMC622-graphite cell with $^{13}\\dot{\\mathbf{C}}$ conductive carbon was charged to $4.8~\\mathrm{V}$ and subsequently discharged to $2.6\\mathrm{~V~}$ (see Figure 10a). The capacity reached during the CC-phase was only $198~\\mathrm{mAh/g_{NMC}}$ , i.e., ${\\sim}17\\%$ lower than for the NMC622 electrode with Super C65 (see \n\nFigure 8); this inferior electrode performance is likely caused by the strongly agglomerated structure of the $^{13}\\mathrm{C}$ -carbon, resulting in a poor electronic accessibility of the active material particles in the cathode. Nevertheless, also for this electrode, the release of oxygen can be clearly seen. It is shifted to a higher potential of $4.75~\\mathrm{V},$ , compared to the $4.54\\mathrm{V}$ for NMC622 with Super C65 (s. Figure 8), which can be rationalized by the fact that the material contains more lithium at ${\\sim}4.6\\mathrm{V}$ due to the worse cathode performance, which in turn renders it more stable at this voltage. Additionally, the cutoff potential is only $50~\\mathrm{mV}$ above the $\\mathbf{O}_{2}$ onset, which is the reason for the overall lower oxygen evolution. \n\nIn total, by the end of the first cycle, ${\\sim}1.5~{\\upmu}\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}$ , ${\\sim}23~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}$ and ${\\sim}9.3~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}$ of $\\mathbf{O}_{2}$ , $\\mathbf{CO}_{2}$ , and CO were formed, respectively, whereby these values were again corrected by the ${\\sim}13~{\\upmu\\mathrm{mol/m}}_{\\mathrm{NMC}}^{2}~\\mathrm{CO}_{2}$ stemming from carbonate oxidation prior to the onset of oxygen evolution and by the $\\mathrm{\\sim}1.1\\upmu\\mathrm{mol/m}_{\\mathrm{C}}^{2}$ CO originating from EC reduction on the graphite anode. In comparison, in the first cycle of the NMC622-graphite cell with Super C65 (Figure 8) ${\\sim}2.9\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{2}$ , ${\\sim}40\\upmu\\mathrm{mol/\\bar{m}_{N M C}^{2}}$ and ${\\sim}19\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}$ of $\\mathbf{O}_{2}$ , $\\mathrm{CO}_{2}$ and CO were evolved, respectively (again, corrected for contributions from carbonate oxidation and EC reduction). It is interesting to note, that not only the amount of oxygen is cut in half, but also the amounts of $\\mathrm{CO}_{2}$ and CO are cut in half, which shows once more that these gases are linked to the oxygen evolution. Finally, Figure 10 clearly shows that neither the evolution of $^{13}{\\bf C O}$ nor $^{13}{\\bf C O}_{2}$ was observed, proving that the carbon additive in the cathode is stable at potentials of $4.8\\mathrm{V}$ and also stable against the released oxygen from the NMC lattice. Therefore, the observed $\\mathrm{CO/CO}_{2}$ formation at high potentials can be ascribed to the oxidation of EC (possibly also the binder) rather than of the conductive carbon by released lattice oxygen. \n\n# Discussion \n\nCorrelation between oxygen release and surface structure of NMC.—We first want to focus on the correlation between the H2 $\\rightarrow\\mathrm{H}3$ phase transition at ${\\sim}4.2\\mathrm{v}$ for NMC811 and the high-voltage feature at ${\\sim}4.6\\mathrm{\\V}$ of NMC111 and NMC622 observed in the $\\mathrm{dq/dV}$ analysis (Figure 4) and the oxygen release detected for the different NMCs by OEMS (Figures 7–9). For NMC111 it is known that upon lithium extraction the c-parameter increases until roughly 2/3 of the lithium is removed and it is ascribed to repulsive interactions of the negatively charged oxygen layers upon the removal of the positive lithium ions.7,11 Upon further removal of lithium, i.e., at higher states of charge, a decreasing c-parameter is reported, which has been linked to increasing covalency between the metal and the oxygen.7,69 Increasing covalency in principle corresponds to a decrease of the oxygen anion charge density, i.e., an oxidation of the lattice oxygen anions (from 2- in the idealized ionic structure to a lower charge density of the oxygen atom). This hypothesized oxidation of the oxygen anions (recently shown by Tarascon’s group for the model compounds $\\mathrm{Li_{2}R u_{\\mathrm{1-y}}S n_{y}O_{3}}$ and $\\mathrm{Li}_{2}\\mathrm{Ir}{\\bf O}_{3})^{50,51}$ would also be consistent with the release of oxygen from the NMC material. The $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition was described in the literature for $\\mathrm{LiNiO}_{2}$ (LNO), where it occurs at ${\\sim}4.2\\mathrm{v}$ vs. $\\mathrm{Li/Li^{+}}$ 46–48 and Li et al. showed by in-situ XRD that the c-parameter of the LNO unit cell at low states of charges gradually increases and drastically shrinks at the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition.47 At roughly the same voltage, this phase transition also occurs for NMC811, as described by Noh et al. and Woo et al.,18,49 and the associated volume contraction was hypothesized to lead to capacity fading.18,49 We believe that in analogy to the interpretation in the case of NMC111 the shrinkage of the c-parameter for NMC811 at the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition can be also a result of a decreasing repulsion between the oxygen layers, caused by the oxidation of the oxygen anions, which finally may result in $\\mathbf{O}_{2}$ release. As was reported by Strehle et al. on Li-rich NMC $(\\mathbf{Li}_{1+\\mathrm{x}}(\\mathbf{Ni},\\mathbf{Mn},\\mathbf{Co})_{1-\\mathrm{x}}\\mathbf{O}_{2})$ , we believe that due to the limited diffusion length of oxygen anions in the bulk NMC particles at $25^{\\circ}\\mathrm{C}$ , the oxygen release is limited to the surface-near region yielding a disordered spinel or rock-salt type layer while the bulk structure stays intact.36 \n\nBy a detailed investigation of the $\\mathrm{d}{\\mathrm{q}}/\\mathrm{d}{\\mathrm{V}}$ plot shown in Figure 4, one can observe that the peak assigned to the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition (NMC811) as well as the high-voltage feature (NMC111 and NMC622) are reversible. If these features are at least partially related to oxygen redox, the reversibility of the peak also indicates a reversibility of the oxygen redox upon relithiation. This reversibility is not contradicting the experimentally observed irreversible oxygen loss, since the dq/dV analysis reflects mostly processes in the bulk, where no oxygen loss can occur due to the limited bulk diffusivity of oxygen anions in the layered oxide particle. We believe that the oxygen release would likely occur throughout the entire particle, if the oxygen anion diffusion were fast enough and/or if the NMC particles were small enough. In other words, the NMC structure is thermodynamically unstable at high degrees of delithiation, and only retains its oxygen and its layered bulk structure due to the kinetically hindered oxygen diffusion. This hypothesis is supported by the literature, where it is reported that layered NMC21,25,27,70,71 and NCA22,25,26,70 structures in the charged state (low lithium content) are not stable at high temperatures $(>170^{\\circ}\\mathrm{C})$ and decompose under release of oxygen, forming a disordered spinel or rock-salt structure, which are thermodynamically more stable than the layered structure at low lithium contents. In these reports, the oxygen release is a bulk phenomenon due to the significantly faster oxygen anion diffusion at elevated temperatures. Consequently, a complete transformation of the layered structure into the spinel or rock-salt structure is observed. \n\nThe limitation of spinel or rock-salt structures to the surface-near regions was already reported before for various layered oxides.9,28–31 In particular, Muto et al. found for NCA that the rock-salt formation on the surface can be up to $100~\\mathrm{{nm}}$ thick after 500 cycles at $80^{\\circ}\\mathrm{C}$ .30 Jung et al. investigated NMC532 in the voltage range between $3{\\mathrm{-}}4.8\\mathrm{V}$ and found a spinel layer thickness of $12\\mathrm{-}15\\mathrm{nm}$ and a thickness of the rock-salt phase of $2{-}3\\mathrm{nm}$ after 50 cycles at room temperature.9 Abraham et al. observed a $35{-}45\\ \\mathrm{nm}$ thick rock-salt structure on $\\mathrm{LiNi_{0.8}C o_{0.2}O_{2}}$ after calendaric aging of a charged electrode at $60^{\\circ}\\mathrm{C}$ for 8 weeks.28 They also stated that the oxygen release was expected to occur from the surface-near region of the material, as their XAS and EELS data showed both that the Ni:O and Co:O ratios were twice as high on the surface compared to the bulk and that the Ni oxidation states on the surface matched NiO whereas in the bulk it matched that of Ni in a layered structure.28,29 Even though a release of oxygen could not be shown in these reports, it is implicitly required because of the lower oxygen to metal ratios in the spinel and rock-salt phases compared to the layered structure: $\\mathbf{MO}_{2}$ (layered) $\\rightarrow\\mathbf{M}_{3}\\mathbf{O}_{4}$ (spinel) $\\mathbf{\\Gamma}\\to\\mathbf{MO}$ (rock-salt) (i.e., metal/oxygen $.=1{:}2\\rightarrow3{:}4\\rightarrow1{:}1$ ). \n\nIn Figures 7–9, the amount of released oxygen is largest in the first cycle and decreases in the subsequent cycles. This fits to the hypothesis that the oxygen is released only from surface-near regions and is therefore fastest in the first cycle, and lower in subsequent cycles, since then it has to diffuse through the already formed disordered spinel or rock-salt layer. In summary, a clear correlation can be made between the structural rearrangement of the NMC particle surface and the release of oxygen. Additionally, the spinel or rock-salt surface layer is very likely the cause of the increase in the polarization (represented by a decrease in the charge-averaged mean discharge voltage of the cathode, ¯Vcdiastchhoadrege) observed during cycling in the Figures 1–3. \n\nConnection between released $\\mathbf{\\delta}_{O_{2}}$ and evolution of CO and $c o_{2}$ .— The total amount of oxygen released during the four cycles (Figures 7–9) is similar for all three NMCs, ranging from 6–9 μmol/m2NMC (see Table II) and for the chosen upper cutoff potentials there is no apparent correlation with the Ni or $\\mathrm{Co}$ contents in the NMCs. Furthermore, Table II summarizes the measured amounts of $\\mathrm{CO}_{2}$ and CO within the four cycles shown in Figures 7–9. They are corrected for the $\\mathrm{CO}_{2}$ derived from carbonate oxidation and for the CO originating from EC reduction, such that only gassing processes at high-voltage are regarded. As was already discussed, a closer examination of the $2^{\\mathrm{nd}}$ , $3^{\\mathrm{rd}}$ , and $4^{\\mathrm{th}}$ cycle in Figures 7–9 reveals that $\\mathrm{CO}/\\mathrm{CO}_{2}$ only evolve once the evolution of $\\mathbf{O}_{2}$ is observed, confirming that $\\mathrm{CO}/\\mathrm{CO}_{2}$ produced at low potentials in the $1^{\\mathrm{st}}$ cycle is indeed due to SEI formation (CO) and carbonate impurity oxidation $\\left(\\mathbf{CO}_{2}\\right)$ . This raises the question, whether CO and $\\mathbf{CO}_{2}$ derive from the chemical reaction of the released lattice oxygen with the electrolyte. A significant reaction of the evolved oxygen with conductive carbon can be excluded, since it was shown in Figure 10 that no $^{13}{\\bf C O}$ and $^{13}{\\bf C O}_{2}$ was evolved when $^{13}\\mathrm{C}$ labeled carbon was used as conductive additive in the NMC electrode instead of conventional carbon (Super C65). Another interesting observation is that in the case of NMC811-graphite cells, $\\mathrm{O}_{2}$ , CO, and $\\mathbf{CO}_{2}$ evolve already at ${\\sim}4.2\\mathrm{V}.$ . At this potential, no gas evolution is observed for the analogous cells with NMC111 (onset of $\\mathbf{O}_{2}$ evolution at ${\\sim}4.57\\mathrm{V}$ ) or NMC622 (onset of $\\mathrm{O}_{2}$ evolution at ${\\sim}4.54\\mathrm{V}$ ), so that it is too low to ascribe the evolved gases to the electrochemical oxidation of the electrolyte, which strongly supports our hypothesis that the evolution of $\\mathrm{O}_{2}$ , CO, and $\\mathrm{CO}_{2}$ are of the same origin. \n\nTable II. Total amounts of oxygen, carbon monoxide, and carbon dioxide evolved at high potentials over the first four cycles in the cells shown in the Figures 7–9 (the amounts of $\\mathbf{CO}_{2}$ stemming from oxidation of carbonate impurities as well as the CO originating from EC reduction, both in the first cycle, were subtracted). \n\n\n
NMC111NMC622NMC811
02 CO[μmol/m2mc]968
[μmol/m2Mc]807970
CO2[μmol/m2Mc]180171170
\n\nThe purely electrochemical oxidation of EC-only electrolyte on a carbon electrode, i.e., in the absence of any possible catalytic effect by transition metal surfaces, was studied in a recent report by Metzger et al. by applying a linear sweep voltammetry procedure from OCV up to $5.5\\mathrm{~V~}$ with a scan rate of $\\mathrm{{\\bar{0.2}m V/s}}$ .59 There, the onset of $\\mathrm{CO}_{2}$ and CO evolution was at ${\\sim}4.8\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ , where the sum of the CO and $\\mathrm{CO}_{2}$ -evolution rate was determined to be $0.3\\upmu\\mathrm{mol/(m}_{\\mathrm{C}}^{2}{\\cdot}\\mathrm{h})$ .59 For comparison, in the NMC111-graphite cell (Figure 7), the total amount of CO and $\\mathrm{CO}_{2}$ produced between $4.6\\mathrm{~V~}$ and the end of the first cycle is $59~{\\upmu\\mathrm{mol/\\bar{m}}}_{\\mathrm{NMC}}^{2}$ and was detected within $1.5\\mathrm{h}$ , corresponding to an average evolution rate of ${\\sim}39~{\\upmu\\mathrm{mol/(m}_{\\mathrm{NMC}}^{2}\\cdot h)}$ ; if referenced to the total surface area of conductive carbon and NMC in the cell $(0.052\\mathrm{m}^{2}\\mathrm{c}$ and $0.0043\\mathrm{m}_{\\mathrm{NMC}}^{2};$ ), this equates to ${\\sim}3.0\\upmu\\mathrm{mol/(m}_{\\mathrm{NMC+C}}^{2}.\\mathrm{h})$ Comparing both values and excluding any catalytic effect of the active material for the above-described reasons, it becomes clear that the purely electrochemical oxidation of EC can only account for at best ${\\sim}10\\%$ of the evolved CO and $\\mathrm{CO}_{2}$ . \n\nThis estimate shows that the electrochemical electrolyte oxidation occurs to a certain extent at high potentials, consistent with previous reports in the literature, which show that the voltage of the NMC slowly drops during storage via a self-discharge caused by electrochemical electrolyte oxidation.72–75 However, once the potential is above the threshold voltage for the release of lattice oxygen, the majority of CO and $\\mathrm{CO}_{2}$ generated in cells containing NMC stems from chemical electrolyte oxidation. A detailed discussion of the chemical and electrochemical pathways and their ratios on the total electrolyte oxidation will be presented below. \n\nWhile the absence of oxygen evolution for the high voltage spinel makes sense, considering that the spinel phase is the stable phase which forms upon oxygen release of the layered material, it is interesting that no CO and $\\mathrm{CO}_{2}$ are evolved with LNMO up to a potential of $5\\mathrm{\\:V}$ (see Figure 5), on a surface for which one would not expect a substantially different catalytic effect (if there is any) for the electrochemical oxidation of electrolyte than for NMC surfaces. This implies that the electrolyte should be very stable (i.e. negligible or very minor electrochemical electrolyte oxidation) at the potentials used for the NMC-graphite cells, further supporting our hypothesis that most of the $\\mathrm{CO}_{2}$ and CO are produced by the chemical reaction of released lattice oxygen with the electrolyte. Here it should be noted that a chemical reaction of oxygen with EC is expected to be only possible at room temperature, if the oxygen is in a reactive form, e.g., as atomic oxygen or singlet oxygen, because EC does not decompose in dry air at the operating temperatures of a lithium ion battery (i.e. it does not react with triplet oxygen). Furthermore, a catalytic effect of Ni or Co appears unlikely as NMC111 and NMC622 have almost identical gassing behavior despite their different Ni and Co composition, and as $\\mathrm{Ni}$ is also present in the LNMO, which evidently does not exhibit significant electrolyte oxidation at room temperature up to $5.0\\mathrm{V}.$ . \n\nIn Figures 7–9, the oxygen evolution stops after some cycles, whereas the formation of CO and $\\mathrm{CO}_{2}$ from cycle to cycle decreases at a much slower rate. We believe that the more quickly decreasing oxygen signal over cycling is due to the very fast chemical reaction of released reactive oxygen with EC, so that oxygen can only be detected as $\\mathbf{O}_{2}$ gas if a larger amount is formed within a short period of time, preventing that all of the released oxygen reacts with the electrolyte to $\\mathrm{CO}_{2}$ and CO (i.e., allowing for the escape of some fraction of the oxygen into the head-space of the OEMS cell). This can be rationalized by considering that once reactive oxygen is released (in the following we assume that the reactive species is ${}^{1}{\\bf O}_{2}$ ) two different follow-up reactions are possible i) the chemical reaction with EC, and/or ii) the physical quenching of two singlet oxygen molecules forming triplet oxygen $(\\bar{2}^{1}0_{2}\\rightarrow\\mathsf{\\bar{2}}^{3}0_{2}+\\mathrm{hv})$ . The rate of the first reaction can be written as \n\n$$\n\\mathbf{r}_{1}=\\mathbf{k}_{1}\\cdot\\left[^{1}\\mathbf{O}_{2}\\right]\\cdot\\left[\\mathbf{EC}\\right]\n$$ \n\nand depends on the product of the concentrations of singlet oxygen $[{}^{1}\\mathrm{O}_{2}]$ and EC [EC] (first order reaction with respect to singlet oxygen) and determines how much $\\mathrm{CO}_{2}$ and CO are observed. In contrast, the rate of singlet oxygen quenching can be written as: \n\n$$\n\\mathbf{r}_{2}=\\mathbf{k}_{2}\\cdot\\left[^{1}\\mathbf{O}_{2}\\right]^{2}\n$$ \n\nIt depends on the squared concentration of singlet oxygen (second order reaction with respect to singlet oxygen) and determines how much triplet oxygen is detected in the mass spectrometer. The decay constant for $\\mathrm{^{i}}\\breve{\\mathbf{O}}_{2}$ in propylene carbonate was shown to be $3.3\\cdot10^{4}\\mathrm{s}^{-1}$ ,76 which we assume to be reasonably similar for ethylene carbonate. Additionally, Kazakov et al.77 proved that both chemical as well as physical quenching occur in acetone, for which decay constants ranging from $\\bar{2}\\cdot10^{4}-\\bar{4}\\cdot10^{4}\\mathrm{s}^{-176}$ were reported. The similarity of the decay constants led us to expect that also in our system both reactions can occur with the rate constants $\\mathbf{k}_{1}$ and $\\mathbf{k}_{2}$ having similar orders of magnitude, so that the extents of $\\mathbf{r}_{1}$ and ${\\bf r}_{2}$ should be mostly dependent on the reactant concentrations $[{}^{1}\\mathrm{O}_{2}]$ and [EC]. Due to the linear and squared dependency of $\\mathbf{r}_{1}$ and ${\\bf r}_{2}$ , respectively, on the singlet oxygen concentration, which is fairly low compared to the concentration of EC, it is expected that $\\mathbf{r}_{1}>>\\mathbf{r}_{2}$ explaining the much larger quantities of $\\mathrm{CO}_{2}$ and CO, which are roughly 20 times higher than the amount of $\\mathbf{O}_{2}$ (s. Table II). Furthermore, the ratio of $\\mathbf{r}_{2}/\\mathbf{r}_{1}$ derived from Reactions 2 and 3 is proportional to the detected ratio of $\\mathbf{O}_{2}$ to $\\mathrm{CO}_{2}$ (assuming that $\\mathrm{CO}_{2}$ is produced by Reaction 2, as discussed later) and can be written as \n\n$$\n\\frac{{\\bf r}_{2}}{{\\bf r}_{1}}=\\frac{{\\bf k}_{2}}{{\\bf k}_{1}\\cdot[{\\bf E C}]}\\cdot\\left[\\sp1{\\bf O}_{2}\\right]\\propto\\ \\frac{{\\bf n}({\\bf O}_{2})}{{\\bf n}({\\bf C O}_{2})}\n$$ \n\nWith Eq. 4 it becomes clear that once the release of oxygen becomes slower (due to the growing thickness of the oxygen depleted surface layer), the local concentration of ${}^{1}{\\bf O}_{2}$ decreases, so that the ratio of $\\mathrm{O}_{2}/\\mathrm{CO}_{2}$ released to the gas phase (and detected by the mass spectrometer) is predicted to decrease over cycling, as indeed is observed. The gradually decreasing release of lattice oxygen over cycling, which we ascribe to a growing thickness of an oxygen depleted surface layer is also consistent with the observed decrease of the mean discharge potential of the cathode shown in the Figures 1–3. For Li-rich NMC materials $(\\mathrm{Li}_{1+\\mathrm{x}}(\\mathrm{Ni},\\mathrm{Mn},\\mathrm{Co})_{1-\\mathrm{x}}{\\bf O}_{2})$ the total amount of released lattice oxygen is comparably large in the first cycle.32–36 For this material class Strehle et al.36 found a ratio of $\\mathrm{\\mathrm{O}}_{2}/\\mathrm{CO}_{2}$ close to $1/1$ in contrast to ${\\sim}1/20$ for the NMC materials (s. Table II), which based on Eq. 4 would suggest a ${\\sim}20$ -fold higher ${}^{1}{\\bf O}_{2}$ concentration near the active material surface, surprisingly consistent with the ${\\sim}20$ -fold higher BET surface area of the $(\\mathrm{Li}_{1+\\mathrm{x}}(\\mathrm{Ni},\\mathrm{Mn},{\\mathrm{Co}})_{1-\\mathrm{x}}{\\mathrm{O}}_{2})$ material examined by Strehle et al.36 \n\nIn a recent publication by Li et al. on NMC811 it was suggested that the c-axis contraction of the unit cell at potentials of ${\\sim}4.2\\mathrm{~V~}$ may not be the reason for the poor cycling stability.78 Instead, a rapid increase of the parasitic heat flow above $4.2\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ was detected and it was hypothesized that the highly delithiated cathode surface be very reactive toward the electrolyte causing an increased cathode impedance.78 Our observation of a growing polarization is consistent with the study by Li et al., however, we believe that it might be the chemical reaction of the released oxygen with the electrolyte that drives the parasitic heat flow, rather than the direct electrochemical oxidation of the electrolyte on the surface. Additionally, Imhof et al. reported $\\mathrm{CO}_{2}$ evolution for LNO already at $4.2\\mathrm{~V~}$ and ascribed it to the reactivity of the surface toward electrolyte.79 However, since this onset potential coincides with the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition,47 we believe that it is more likely related to a release of oxygen from the layered LNO structure, followed by its chemical reaction with the electrolyte to $\\mathrm{CO}_{2}$ rather than to an electrochemical oxidation of the electrolyte at potentials as low as $4.2\\mathrm{V}.$ \n\nIn summary, the above discussion strongly supports our hypothesis that the majority of the $\\mathrm{CO/CO}_{2}$ evolution $(>90\\%)$ during cycling is due to the chemical reaction of released lattice oxygen with the electrolyte, with the exception of the $\\mathrm{CO/CO}_{2}$ evolved at low potentials in the first cycle, which we believe derive from SEI formation (EC reduction on graphite) and carbonate impurity oxidation. \n\nAnode related $C_{2}H_{4}$ and $\\pmb{H}_{2}$ signals.—The amounts of ethylene evolved in Figures 7–9 are between $7{-}9\\ \\mathrm{\\upmumol/m}_{\\mathrm{C}}^{2}$ , very similar to what was observed in a previous report by Metzger et al.12 In the same report, the hydrogen evolution which was detected from the beginning of the measurement and was ascribed to the reduction of trace water in the electrolyte.12 The amount of hydrogen accumulated over the four cycles shown in Figures 7–9 ranges from $10–13~{\\upmu\\mathrm{mol}}/{\\mathrm{m}}_{\\mathrm{c}}^{2}$ . If we only consider the amount of hydrogen formed in the first cycle before the onset of $\\mathbf{O}_{2}$ evolution (which will lead to further formation of $\\mathrm{H}_{2}\\mathrm{O}$ , as will be discussed later), we find ${\\sim}6.6~\\upmu\\mathrm{mol/m}_{\\mathrm{C}}^{2}~\\mathrm{H}_{2}$ for the NMC111 (Figure 7) and for the NMC622 (Figure 8) cell as well as ${\\sim}8.0~\\mathrm{\\upmu\\mathrm{mol/m}_{C}^{2}}\\$ $\\mathrm{H}_{2}$ for the NMC811 cell (Figure 9). The fact that all three values are reasonably similar supports the assumption that the evolution of $\\mathrm{H}_{2}$ up to this point is not related to the cathode active material. With the total surface area of the graphite-electrodes, this corresponds to an absolute amount of ${\\sim}0.6{-}0.7~\\upmu\\mathrm{mol}$ $\\mathrm{H}_{2}$ being evolved. This amount would require $1.2{-}1.4~{\\upmu\\mathrm{mol}}$ $\\mathrm{H}_{2}\\mathrm{O}$ in the electrolyte, if all $\\mathrm{H}_{2}$ were formed via $\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{e}^{-}\\rightarrow0.5\\mathrm{H}_{2}+\\mathrm{OH}^{-}$ . Using the density of the electrolyte $(1.5~\\mathrm{g/mL})^{80}$ and the electrolyte volume $(400~\\upmu\\mathrm{L})$ ), the above amount would correspond to a water content of 36–42 ppm for all three cells, which fits very well with the report by Metzger et al., who observed a hydrogen evolution corresponding to $33~\\mathrm{ppm}$ of trace water using an LP57 electrolyte.12 In summary, the gases from the anode side are consistent with our previous findings. \n\nProposed mechanism of EC oxidation by reactive oxygen.—As discussed above, our data indicate that the majority of the evolved CO and $\\mathrm{CO}_{2}$ are actually a consequence of the reaction of the released oxygen from the NMC, which is likely very reactive in the moment it is released from the material (see Figures 7–9). In Figure 10, we demonstrated that the carbon source for the CO and $\\mathrm{CO}_{2}$ formation is not the conductive carbon in the electrode. The only remaining carbon source in the cell is therefore ethylene carbonate (EC) and possibly the binder. In Scheme 1, we propose a mechanism for how oxygen might react with EC, whereby it is clear that oxygen in its triplet ground state does not react with EC. As the reaction requires the oxygen to be reduced, there are only the two carbon atoms bound to the hydrogen which can be potentially oxidized (the carbonylcarbon is already in its maximum oxidation state). Our proposed mechanism starts with an electrophilic attack on the carbon by the $\\mathbf{O}_{2}$ molecule, yielding a peroxo group carrying the proton which was initially bound to the carbon. The rather unstable peroxo group would immediately decompose, forming a carbonyl group and releasing a water molecule. This molecule could potentially decompose forming \n\n![](images/832c093c6b5af05cc78088bab3aa0c3da41d39c2ca19a2eb80415cad9a08ba4b.jpg) \nScheme 1. Proposed mechanism for the oxidation of ethylene carbonate (EC) with reactive oxygen (e.g., singlet oxygen) released from the NMC structure and yielding $\\mathrm{CO}_{2}$ , CO, and $\\mathrm{H}_{2}\\mathrm{O}$ . The overall reaction equation is $\\mathrm{EC}+2\\ensuremath{\\mathrm{O}_{2}}$ $\\rightarrow2\\mathrm{CO}_{2}+\\mathrm{CO}+2\\mathrm{H}_{2}\\mathrm{O}$ . \n\nCO, $\\mathrm{CO}_{2}$ and formaldehyde, in which case, however, the predicted $\\mathrm{CO}_{2}/\\mathrm{CO}$ ratio would be $1/1$ , which does not match the observed ratios in Figures 7—9 nor did we observe any formaldehyde in the mass spectrometer. Instead, a second ${}^{1}{\\bf O}_{2}$ molecule could attack the other carbon atom if the EC molecule attacked in the first step is assumed to be adsorbed at the NMC surface forming another carbonyl group and releasing another molecule of water. The formed molecule would readily decompose, yielding two molecules of $\\mathrm{CO}_{2}$ , one molecule CO, aside with the previously formed two $\\mathrm{H}_{2}\\mathrm{O}$ molecules. The formation of water upon the reaction of electrolyte with oxygen was already hypothesized before.81,82 \n\nThe overall proposed reaction would thus be $\\mathrm{EC}+2\\ \\mathrm{O}_{2}\\ \\rightarrow$ $2\\mathrm{CO}_{2}+\\mathrm{CO}+2\\mathrm{H}_{2}\\mathrm{O}$ , predicting a $\\mathrm{CO}_{2}$ to CO ratio of 2:1. Examining the evolved amounts summarized in Table II, a somewhat higher $\\mathrm{CO}_{2}$ :CO ratio ranging from 2.2:1 to 2.4:1 was measured. Considering that water is a reaction product, several follow-up reactions are likely to occur: i) $\\mathrm{H}_{2}\\mathrm{O}$ can be reduced at the graphite anode, yielding $\\mathrm{H}_{2}$ and $\\mathrm{OH^{-}}$ , as was reported previously by our group64 and which would be consistent with the observed continuous evolution of $\\mathrm{H}_{2}$ in Figures 7–9; ii) OH- produced by the reduction of $\\mathrm{H}_{2}\\mathrm{O}$ at the anode was shown to lead to rather high rates of EC hydrolysis, producing $\\mathrm{CO}_{2}$ gas;80 iii) chemical reaction of $\\mathrm{LiPF}_{6}$ with $\\mathrm{H}_{2}\\mathrm{O}$ can yield $\\mathrm{Li_{x}P O_{y}F_{z}}$ species, which are frequently reported as surface species at the interface between electrolyte and the NMC cathode.15,16 A combination of i) and ii) would lead to additional $\\mathrm{CO}_{2}$ evolution (as well as to the observed ongoing $\\mathrm{H}_{2}$ evolution) and therefore to a higher $\\mathrm{CO}_{2}$ :CO ratio than the ratio of 2:1 predicted by Scheme 1, consistent with our observations (s. Table II). In order to check if the reduction of water forming $\\mathrm{H}_{2}$ and $\\mathrm{OH^{-}}$ can be a reasonable, we will calculate the total amount of water which can be formed according to Scheme 1 and compare it to the $\\mathrm{H}_{2}$ formed at potentials $\\geq4.6\\mathrm{~V~}$ in Figures 7–9. For the following calculation, we will use the values obtained for the NMC111-graphite cell as an example. As stated in Table II, ${\\sim}80$ $\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}\\mathrm{CO}$ are formed. Assuming the stoichiometry in Scheme 1, this would imply that ${\\sim}160\\upmu\\mathrm{mol/m}_{\\mathrm{NMC}}^{\\bar{2}}\\mathrm{H}_{2}\\mathrm{O}$ be formed at the same time. Multiplying this value with the active material mass of the NMC electrode $(16.69\\mathrm{mg})$ and the BET-surface area of the NMC111 (0.26 $\\mathrm{m}^{2}/\\mathrm{g})$ ), one obtains a total of $0.7~\\upmu\\mathrm{mol}$ $\\mathrm{H}_{2}\\mathrm{O}$ $(\\equiv12.5~\\upmu\\mathrm{g}_{\\mathrm{H}_{2}\\mathrm{O}})$ . Analogous to the calculation in the previous section, this would correspond to an increase of the $\\mathrm{H}_{2}\\mathrm{O}$ content in the electrolyte by $21\\mathrm{ppm}$ . The reduction of this in-situ formed water at the negative graphite electrode via $\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{e}^{-}\\rightarrow0.5\\mathrm{H}_{2}+\\mathrm{OH}^{-}$ could yield $0.35~\\upmu\\mathrm{mol}_{\\mathrm{H}_{2}}$ which, when normalized to the NMC or carbon surface area would amount to $80\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{NMC}}^{2}$ and $3.8\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}$ , respectively. Since water can be formed as soon as oxygen is released for the first time, we examine the hydrogen signal in Figure 7 from this point until the end of the measurement: the amount of $\\mathrm{H}_{2}$ increases from $6.6\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}$ to 11.7 $\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}$ , i.e., by $5.1\\upmu\\mathrm{mol}/\\mathrm{m}_{\\mathrm{C}}^{2}$ , which may be compared to the above predicted value of $3.8~\\mathrm{\\upmumol/m}_{\\mathrm{C}}^{2}$ . Analogous estimates can be made for the NMC622 and the NMC811 cells, for which the agreement is also within a factor of ${\\sim}2$ . Considering that besides the reduction of the formed water several additional reactions occur simultaneously like hydrogen formation from initially present trace water reduction (see Results section), hydrolysis of EC, as well as decomposition of $\\mathrm{LiPF}_{6}$ , the calculated maximum of hydrogen from the reduction of in-situ generated water actually fits astonishingly well to the experimentally observed amount. \n\nTable III. Electrode loading, moles of NMC, theoretically possible amounts of released oxygen and detected amounts of $\\mathbf{O}_{2}$ , CO, and $\\mathbf{CO}_{2}$ of the cells shown in Figure 7–9 (the amounts of CO and $\\mathbf{CO}_{2}$ are corrected for the amounts originating from EC reduction and carbonate impurity oxidation). Based on these values, the equations in the text and assuming a layered to spinel or layered to rock-salt transformation the volume fractions (fspinel, frock-salt) from which oxygen is released as well as the oxygen depleted surface layer thicknesses (tspinel, trock-salt) are calculated considering either the sum of $\\mathbf{O}_{2}$ and twice the amount of CO (model I) or the sum of $\\mathbf{O}_{2}$ and $\\mathbf{CO}_{2}$ (model II) according to Scheme 1. \nNMC111 NMC622 NMC811 \n\n\n
electrode loading amount of NMC detected CO[mgNMC/cm²]9.4411.459.28
max. O2,spinel max. O2,rock-salt detected O2[μmol] [μmol]173209169
515942
[μmol]819674
[nmol] [nmol]39 34742 55924
detected CO2[nmol]7811211207 502
fspinel,O,co (model I)[%]1.42.01.0
fspinel,O,co (model II)[%] 1.62.11.3
frock-salt,O,Co (model I)[%]0.91.20.6
frock-salt.O.co (model II)[%]1.01.30.7
tspinel,O,co (model I)[nm] 11.611.812.1
tspinel.O,cO (model II)[nm]13.012.714.6
trock-salt.O,co (model I)[nm]7.37.26.9
trock-salt,O,cO (model II)[nm]8.17.88.2
\n\nEstimation of oxygen depleted surface layer thickness.—Based on the OEMS data presented in Figures 7–9 and summarized in Table III, the oxygen depleted surface layer thickness was estimated as a compact, homogeneous layer around the NMC particles in a similar way as reported by Strehle et al.36 We considered both scenarios, a layered to disordered spinel (Eq. 5) and a layered to rock-salt (Eq. 6) transformation using, in analogy to the literature,21,22,36,83 the following general equations with $\\mathbf{M}=(\\mathrm{Ni},\\mathrm{Mn},\\mathrm{Co})$ : \n\n$$\nL i_{x}M O_{2}\\rightarrow\\frac{x+1}{3}L i_{3-\\frac{3}{x+1}}M_{\\frac{3}{x+1}}O_{4}+\\frac{1-2x}{3}O_{2}\n$$ \n\nspinel transformation \n\n$$\nL i_{x}M O_{2}\\rightarrow(x+1)L i_{1-\\frac{1}{x+1}}M_{\\frac{1}{x+1}}O+\\frac{1-x}{2}O_{2}\n$$ \n\nrock-salt transformation \n\nFor the $\\mathbf{x}$ -values in Eqs. 5 and 6 we determined the lithium content in the material at the end of the first charge from Figures 7–9 resulting in $\\mathbf{x}=0.06$ , 0.08 and 0.13 for NMC111, NMC622, and NMC811, respectively. Using these $\\mathbf{x}$ -values the theoretical oxygen loss per mol of NMC can be calculated for the different NMCs: \n\n# NMC111: \n\n$$\nL i_{0.06}M O_{2}\\rightarrow\\frac{53}{150}L i_{9_{/53}}M_{150_{/53}}O_{4}+\\frac{22}{75}O_{2}\n$$ \n\nspinel transformation \n\n$$\n{\\cal L}i_{0.06}M{\\cal O}_{2}\\rightarrow\\frac{53}{50}{\\cal L}i_{3_{/53}}{\\cal M}_{50_{/53}}{\\cal O}+\\frac{47}{100}{\\cal O}_{2}\n$$ \n\n[8] \n\nrock-salt transformation \n\nNMC622: \n\n$$\n{\\cal L}i_{0.08}{\\cal M}{\\cal O}_{2}\\rightarrow\\frac{9}{25}{\\cal L}i_{2}{}_{k9}{\\cal M}_{25_{/9}}{\\cal O}_{4}+\\frac{7}{25}{\\cal O}_{2}\n$$ \n\nspinel transformation \n\n$$\n{\\cal L}i_{0.08}M{\\cal O}_{2}\\rightarrow\\frac{27}{25}{\\cal L}i_{2}{}_{/27}M_{25}{}_{/27}{}^{}{\\cal O}+\\frac{23}{50}{\\cal O}_{2}\n$$ \n\nrock-salt transformation \n\nNMC811: \n\n$$\nL i_{0.13}M O_{2}\\rightarrow\\frac{113}{300}L i_{39}\\diamond_{/113}M_{300}\\diamond_{/113}O_{4}+\\frac{37}{150}O_{2}\n$$ \n\nspinel transformation \n\n$$\nL i_{0.13}M O_{2}\\rightarrow\\frac{113}{100}L i_{13}{}_{/113}M_{100}{}_{/113}O+\\frac{87}{200}O_{2}\n$$ \n\nrock-salt transformation \n\nThe active material loadings of the electrodes used in the OEMS measurements in Figures 7–9 are listed in Table III. Multiplying by the area $(1.767~\\mathrm{cm}^{2})$ ) and dividing by the molar mass of the NMC materials yields the amount of NMC in mol (see second row in Table III). Using the stoichiometric relation between the layered oxide on the left-hand-side and the evolved oxygen on the right-hand-side in Eqs. 7–12, the maximum amounts of oxygen which can be evolved if a spinel or rock-salt phase is formed (max. $\\mathbf{O}_{2}$ , spinel and max. $\\mathbf{O}_{2,\\mathrm{rock-salt}})$ can be calculated (see $3^{\\mathrm{rd}}$ and $4^{\\mathrm{th}}$ row in Table III). For the calculation of the layer thickness from our experimental data we use two different models based on the mechanism presented in Scheme 1. In model I we calculate the layer thickness for the spinel and rock-salt phase taking into account the sum of the detected oxygen plus twice the amount of CO (remember that one mol of CO is formed per two moles of released oxygen in Scheme 1). In contrast, model II is based on the measured amounts of $\\mathbf{O}_{2}$ and $\\mathrm{CO}_{2}$ (one mol of $\\mathbf{CO}_{2}$ is formed per mol of released oxygen). In an ideal case, i.e., if the ratio of $\\mathrm{CO}_{2}/\\mathrm{CO}$ were exactly 2:1, both models would yield exactly the same results. As the measured $\\mathrm{CO}_{2}/\\mathrm{CO}$ ratio is between 2.2:1 and 2.4:1 due to possible side reactions of the in-situ formed $\\mathrm{H}_{2}\\mathrm{O}$ with EC yielding $\\mathrm{CO}_{2}$ , the calculation with model II will slightly overestimate the layer thickness and can therefore be considered as an upper limit, whereas we believe that model I should yield the more precise values. The detected amounts of $\\mathbf{O}_{2}$ , CO, and $\\mathrm{CO}_{2}$ are given in the $5^{\\mathrm{th}}-7^{\\mathrm{th}}$ row of Table III. \n\nThe molar fraction of cathode active material converted to a spinel $(\\mathrm{f_{spinel}})$ or rock-salt structure $\\mathrm{(f_{rock-salt})}$ was calculated by dividing either the detected $\\mathbf{O}_{2}$ plus twice the amount of detected CO (model I) or the measured amounts of $\\mathrm{O}_{2}$ and $\\mathrm{CO}_{2}$ (model II) by max. $\\mathbf{O}_{2,\\mathrm{spinel}}$ or max. $\\mathbf{O}_{2,\\mathrm{rock-salt}}$ (Table III, ${8^{\\mathrm{th}}}$ to $11^{\\mathrm{th}}$ row). \n\nThe thus estimated molar fractions should be equal to the ratio of the particle shell volume from which oxygen is released $\\mathrm{(V_{\\mathrm{shell}})}$ to the total particle volume $(\\mathrm{V_{particle}})$ . Using Eq. 13 and the radius $\\mathbf{r}_{1}$ of the complete particle, one can calculate the radius ${\\bf r}_{2}$ of the intact fraction of the particle. The difference of $\\mathrm{\\dot{\\tau}_{r_{1}}}$ and $\\mathbf{r}_{2}$ is the averaged surface-near layer thickness (tspinel, trock-salt) of the oxygen depleted surface layer. \n\n$$\n{\\frac{V_{s h e l l}}{V_{p a r t i c l e}}}={\\frac{{}^{4}/{}_{3}\\uppi\\left(r_{1}^{3}-r_{2}^{3}\\right)}{{}^{4}/{}_{3}\\uppi r_{1}^{3}}}=1-{\\frac{r_{2}^{3}}{r_{1}^{3}}}\n$$ \n\nThe particle radius $\\mathbf{r}_{1}$ was obtained from the respective BET-surface area assuming spherical particles (Eq. 14) and a crystallographic density of NMC of $\\bar{\\uprho}_{\\mathrm{NMC}}=\\bar{4}.8~\\mathrm{g}/\\mathrm{cm}^{3}$ . \n\n$$\nr_{1}=\\frac{3}{A_{B E T}*\\uprho_{N M C}}\n$$ \n\nThe resulting layer thicknesses for the spinel and rock-salt transformations $(\\mathbf{t}_{\\mathrm{spinel,O}_{2},\\mathrm{CC}}$ , $\\mathbf{t}_{\\mathrm{spinel},\\mathrm{O}_{2},\\mathrm{CO}_{2}}$ , trock-salt,O2,CO, trock-salt,O2,CO2 ) are shown in the $12^{\\mathrm{th}}{-}15^{\\mathrm{th}}$ row of Table III. \n\nThe calculated oxygen depleted volume fractions considering a spinel or rock-salt transformation are in the range $1.0\\%-2.1\\%$ and $0.6\\%-1.3\\%$ , respectively. It is interesting to note that the oxygen depleted volume fractions calculated for NMC622 are roughly doubled compared to the ones for NMC811, while the values for NMC111 are in between the two values. Interestingly, this parallels their BET surface area, with the one of NMC111 $(\\bar{0.2}\\dot{6}\\mathrm{m}^{2}/\\dot{\\mathrm{g}})$ being in between the ones of NMC622 $(0.35~\\mathrm{m}^{2}/\\mathrm{g})$ and NMC811 $(0.18~\\mathrm{m}^{2}/\\mathrm{g})$ ), the latter two being different by a factor of 2. This already suggests that the conversion of the layered to the spinel/rock-salt structure may be limited by the formed oxygen-depleted surface-near film. \n\nDue to the differences in the BET surface area of the three NMCs, the obtained layer thicknesses turn out to be very similar. For model I, the calculated layer thicknesses for the spinel and rock-salt transformations are $11.6~\\mathrm{nm}{-}12.1~\\mathrm{nm}$ and $6.9\\ \\mathrm{nm-7.3\\nm}$ , respectively. Also for the calculation based on model II, the obtained values are very close to the ones obtained using model I ( $12.7~\\mathrm{nm}{-}14.6~\\mathrm{nm}$ and $7.8~\\mathrm{nm}{-8.2}~\\mathrm{nm}$ , respectively). These calculated layer thicknesses are in good agreement with previous reports in the literature on NMC,9 $\\mathrm{Li\\bar{Ni}_{0.8}C o_{0.2}\\mathrm{O}_{2}{}^{28}}$ , $\\mathrm{NCA}^{30}$ and Li-rich NMC.36 As expected, a transformation to the spinel phase leads to a thicker surface layer than the transformation to the rock-salt phase, since the former contains more oxygen in its structure than the latter. Moreover, it is very likely that for the different NMC materials different ratios of spinel and rocksalt phases occur with higher rock-salt ratios for Ni-richer NMC as they tend to form rock-salt rather than spinel phases.9,70 However, this would not significantly affect the estimated surface layer thickness, as shown in Table III. Additionally, as it was shown in Figures 7–9, an increase in the oxygen signal cannot be observed anymore after a few cycles; however, we believe that the oxygen release is ongoing also in subsequent cycles, but is only detected as CO and $\\mathrm{CO}_{2}$ . This would also explain the steady decrease of the charge-averaged mean cathode discharge potential shown in Figures 1–3 (solid lines in panels b). All in all, we demonstrated in this section that the film thicknesses deduced from the gas evolution data from OEMS yield values which are consistent with microscopy data from the literature. \n\nPotential dependence of electrochemical and chemical electrolyte oxidation.—In the sections above we showed that the release of reactive oxygen from the surface of the NMC is accompanied by the majority of the observed $\\mathrm{CO}_{2}$ and CO evolution (see Figures 7–9). In this section we want to schematically illustrate the relation between electrochemical and chemical electrolyte oxidation, taking into account the results of this work and previous reports in the literature. Scheme 2a depicts the here proposed electrochemical and chemical pathways, exemplified for the oxidation of the commonly used electrolyte constituent EC (analogous mechanisms can be envisioned for other solvents). \n\nThe purely electrochemical pathway (see upper left panel in Scheme 2a) sets in when the voltage of the cathode is raised above the stability limit of the electrolyte Vsolvent oxidation which can occur on the surface in contact with the electrolyte (e.g., on conductive carbon additive59), at a rate which increases with increasing cathode potential (Scheme 2b). In this process, EC is electro-oxidized to CO or $\\mathrm{CO}_{2}$ and protic species $(\\mathrm{R}{-}\\mathrm{H}^{+})^{12}$ which increase the acidity of the electrolyte84 whereby the in parallel occurring reduction of the protic species on the graphite anode leads to the observed strongly enhanced hydrogen evolution (see Figures 7–9). To compensate the negative charge transferred to the NMC electrode upon electrochemical solvent oxidation, $\\mathrm{Li^{+}}$ -ions from the electrolyte have to be intercalated into the NMC active material. As a consequence, when storing a battery cell charged to a high cutoff voltage, the electrochemical solvent oxidation and the concomitant $\\mathrm{Li^{+}}$ intercalation induce an apparent self-discharge, which can be observed by a voltage drop due to the sloped voltage profile of NMC (s. upper right panel of Scheme 2a).72–75 Note that during cycling instead of the intercalation of $\\mathrm{Li^{+}}$ into the NMC the \n\n# (a) Two mechanistic electrolyte oxidation pathways \n\n![](images/3c44653c19e379a024244a5e6f7d8a5ae20d7dfc54f2988311d4c7289008d6c7.jpg) \nScheme 2. (a) Schematic description of the proposed electrochemical and chemical electrolyte oxidation pathways (exemplarily shown for EC) which occur at high potentials, and their effect upon battery storage at high potentials. The shown electrochemical EC oxidation yields $\\mathrm{CO}/\\mathrm{CO}_{2}$ and protic $\\mathrm{R}{\\mathrm{-}}\\mathrm{H}^{+}$ species, and its rate increases with the cathode potential (upper left panel). The intercalation of ${\\mathrm{Li}^{+}}$ upon electrochemical EC oxidation causes a voltage drop during storage (upper right panel). The chemical EC oxidation initiates upon reactive oxygen release (e.g., singlet oxygen, $^1{\\bf O}_{2}$ ) from the NMC surface, which reacts with EC to $\\mathrm{CO}_{2}$ , CO, and $\\mathrm{H}_{2}\\mathrm{O}$ (lower left panel). During storage at OCV the surface reconstruction continues as long as the cathode potential is high enough to allow for oxygen release, which is expected to alter the Galvani potential (lower right panel). (b) Schematic potential dependence of both processes: for $\\mathrm{\\DeltaV_{cathode}V_{O_{2}}}$ release (Region II), electrolyte oxidation proceeds simultaneously via both the chemical pathway at the rate $\\mathrm{{r}_{c h e m}^{O2}}$ . (purple line) and the electrochemical pathways. The sum of both reactions, , is represented by the black line. \n\nelectrons can be transferred via the external circuit to the negative electrode and $\\mathrm{Li^{+}}$ would be intercalated into the graphite anode. \n\nIn contrast, the here proposed chemical electrolyte oxidation (lower left panel of Scheme 2a) initiates once the cathode potential exceeds the threshold voltage $\\mathrm{V}_{\\mathrm{O}_{2}\\mathrm{release}}$ for the release of reactive oxygen from the layered NMC structure (here depicted exemplarily as singlet oxygen, $^1{\\bf O}_{2}\\dot{.}$ ). We showed that this surface transformation into a spinel or rock-salt phase occurs at very low lithium contents $\\mathbf{\\bar{x}}<0.2$ in $\\mathrm{Li}_{\\mathrm{x}}\\mathrm{MO}_{2}$ ) and that the threshold potential $\\mathrm{V}_{\\mathrm{O}_{2}}$ release varies for different NMC compositions, being ${\\sim}4.{\\bar{7}}\\mathrm{v}$ vs. $\\mathrm{Li/Li^{+}}$ for NMC111 and NMC622, and ${\\sim}4.3\\mathrm{~V~}$ vs. $\\mathrm{Li/Li^{+}}$ for NMC811. The rate of the chemical electrolyte oxidation associated with the release of reactive oxygen (accompanied by the evolution of $\\mathrm{CO}_{2}$ and CO, see Figures 7–9) is hardly potential dependent, i.e., it jumps from quasi zero to a rather high and fairly constant value (see Scheme 2b). Upon OCV storage, the surface reconstruction is ongoing as long as the cathode potential is high enough to allow for it, which is likely to affect the Galvani potential (and thus the OCV) due to the formation of the thermodynamically more stable spinel/rock-salt structure at the near surface layer (lower right panel of Scheme 2a). However, due to the above-described voltage drop during the simultaneously occurring electrochemical electrolyte oxidation (i.e., a gradual re-lithiation of the NMC), the oxygen release will stop as soon as $\\mathrm{\\DeltaV_{cathode}}$ falls below $\\mathrm{v}_{\\mathrm{o}_{2}}$ release. Therefore, one would expect that the open circuit potential decay during extended OCV storage is mostly controlled by the rate of the electrochemical pathway. \n\nScheme 2b schematically summarizes the potential dependence of the electrochemical (dark blue line) and chemical electrolyte oxidation (purple line), with the sum of both processes represented by the black line. As described before, the electrochemical pathway is a function of the cathode voltage, which is shown to proceed at a rate increasing exponentially with potential (dark blue line). In contrast, the chemical pathway is likely to have a very weak potential dependence as long as the released lattice oxygen is provided, which would predict a sudden onset once the potential exceeds $\\mathrm{v}_{\\mathrm{o}_{2}}$ release with a weak potential dependence after that point (purple line). At $\\mathrm{\\DeltaV_{cathode}\\sim V_{O_{2}r e l e a s}}$ e (Region I), no chemical electrolyte oxidation is expected, so that the total electrolyte oxidation rate (black line) is identical to the electrochemical oxidation (dark blue line). On the other hand, at $\\mathrm{\\DeltaV_{cathode}>V_{O_{2}}}$ release (Region II), the total electrolyte oxidation rate is the sum of the rates of the electrochemical and chemical pathways, with the latter being the dominant pathway. This implies that the intrinsic electrochemical stability of electrolyte solvents can only be measured with “inert” electrodes which do not release lattice oxygen, e.g., carbon black.59 Note that the rate of the electrochemical pathway investigated in the report by Metzger et al.59 at $5.0\\mathrm{~V~}$ vs. $\\bar{\\mathrm{Li}}/\\mathrm{Li^{+}}$ would only be roughly $10\\%$ of the total electrolyte oxidation observed in this work on NMC111 (Figure 7) at $4.9\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ (see second paragraph of the Discussion section for a detailed calculation), which led us to the conclusion that the chemical pathway would be the dominant one at this potential. \n\nIn a recent report by Xia et al.,72 a voltage drop from $4.7~\\mathrm{V}$ to roughly $4.5~\\mathrm{V}$ was observed for NMC442-graphite cells during storage at OCV for $500\\mathrm{~h~}$ at $40^{\\circ}\\mathrm{C}$ with LP57 electrolyte. A voltage drop by $200~\\mathrm{mV}$ in a NMC material corresponds to roughly $20\\ \\mathrm{mAh/g_{NMC}}$ , corresponding to an exchanged amount of electrons of $746~{\\upmu\\mathrm{mol_{e}/g_{N M C}}}$ . As the BET-surface area of the used NMC442 material as well as the electrode composition were not stated, we will assume for the following calculation that its BET surface area was similar to that of our NMC111 $(0.26~\\mathrm{m}^{2}/\\mathrm{g})$ and that the electrode composition was also similar to that in our study ( $91.5\\%$ NMC and $4.4\\%$ C65). Dividing the specific amount of electrons by the estimated surface areas and accounting for the electrode composition, a total of $220~{\\upmu\\mathrm{mol_{e}/m_{N M C+C}^{2}}}$ is obtained. Assuming that the electrochemical oxidation of one solvent molecule leads to the intercalation of one ${\\mathrm{Li}^{+}}$ - ion into NMC, also $220\\upmu\\mathrm{mol}_{\\mathrm{solvent}}/\\mathrm{m}_{\\mathrm{NMC+C}}^{2}$ would be decomposed by this process. When dividing this value by the storage time of $500\\mathrm{h}$ , an average decomposition rate of $0.44\\upmu\\mathrm{mol}_{\\mathrm{solvent}}/(\\mathrm{m}_{\\mathrm{NMC+C}}^{\\searrow}\\cdot\\mathrm{h})$ would be obtained at a potential ranging between 4.8 and $4.6\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ . This may be compared with the electrochemical oxidation rate of EC on a carbon surface at $5\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ and $40^{\\circ}\\mathrm{C}$ , which was reported to be ${\\sim}1.1\\upmu\\mathrm{mol}_{\\mathrm{solvent}}/(\\mathrm{m}_{\\mathrm{C}}^{2}{\\cdot}\\mathrm{h})$ .59 Thus, the average electrolyte oxidation rate between 4.8 and $4.6\\mathrm{~V~}$ (vs. $\\mathrm{Li/Li^{+}}$ ) of $0.44~{\\upmu\\mathrm{mol}}_{\\mathrm{solvent}}/(\\mathrm{m}_{\\mathrm{NMC+C}}^{2}{\\cdot}\\mathrm{h})$ which would be required to rationalize the observed potential decay during the OCV hold by Xia et al.72 is reasonably consistent with the electrochemical EC oxidation rate of ${\\sim}1.1\\ \\mathrm{\\upmumol_{\\mathrm{solvent}}/(\\mathrm{m}}_{\\mathrm{C}}^{2}{\\cdot}\\mathrm{h})$ at the higher potential of $5.0\\mathrm{V},$ , particularly considering that the EMC oxidation rate in the LP57 electrolyte was found to be even higher (unpublished results). Consequently, we believe that during OCV storage the electrochemical oxidation is the dominating process that leads to the observed voltage drop, as was already stated in the reports by the Dahn group.72–75 The apparent rate determined in this work, which includes the effect of the chemical electrolyte oxidation due to oxygen release at $25^{\\circ}\\mathrm{C}$ and ${\\sim}4.9\\mathrm{v}$ vs. $\\mathrm{Li/Li^{+}}$ is ${\\sim}3.0\\upmu\\mathrm{mol}_{\\mathrm{solvent}}/(\\mathrm{m}_{\\mathrm{NMC+C}}^{2}{\\cdot}\\mathrm{h})$ (see the detailed calculation in the second paragraph of the Discussion section), and is therefore ${\\sim}3$ -fold higher than the rate of pure electrochemical solvent oxidation at higher temperature $(40^{\\circ}\\mathrm{C})$ and higher potential (5 V vs. $\\mathrm{Li/Li^{+}}$ ). Compared to the rate of pure electrochemical oxidation at $25^{\\circ}\\mathrm{C}$ and $5\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ of $\\sim0.3\\ \\mathrm{\\bar{\\upmu}m o l/(\\mathrm{m}_{\\mathrm{C}}^{2}\\cdot\\mathrm{h})}$ it is even ${\\sim}10$ -fold higher.59 This unambiguously demonstrates the dominating effect of the chemical electrolyte oxidation at potentials at which oxygen is released from the NMC lattice (Scheme 2b). \n\n![](images/39a9f4432afce160db571fab4072e7592236aa96f185bd57a7684cad24bd15b6.jpg) \nFigure 11. Specific energy of NMC111-graphite, NMC622-graphite and NMC811-graphite cells in LP57 electrolyte (1 M $\\mathrm{LiPF}_{6}$ in EC:EMC 3:7). The full columns represent the specific energy of the $5^{\\mathrm{th}}$ cycle (1 C-rate), the dashed part of the columns of the $\\mathrm{\\dot{3}00^{t h}}$ cycle (1 C-rate). The data are extracted from the cells shown in the Figures 1–3. \n\nSpecific energy densities of NMC111, NMC622 and NMC811.— In the previous sections it was demonstrated that the release of oxygen from the NMC surface has a very detrimental impact on the material stability, as it causes significant gas evolution (Figures 7–9) as well as a significant increase of the polarization of the cathode material most probably due to the oxygen depleted surface layer (Figures 1–3). For NMC811, the oxygen release occurs already at potentials as low as $4.3\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ , whereas for NMC111 and NMC622 it occurs roughly at $4.7\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ . These values limit the end-of-charge voltage that can be applied to achieve a stable cycling and they have therefore a severe impact on the achievable specific energy of these materials. We want to highlight that additional aging mechanisms will be occurring in parallel, like lithium loss due to SEI growth on the anode, electrochemical electrolyte oxidation at high potentials on the cathode, metal dissolution from the cathode, etc.; however, when cycling up to potentials where oxygen release occurs, the formation of a resistive surface layer is the most severe aging mechanism under these conditions, causing significant capacity and discharge voltage fading during extended charge/discharge cycling (Figures 1–3). The specific energies of the cells shown in the Figures 1–3 are depicted in Figure 11 with the full bars representing the specific energy of the $5^{\\mathrm{th}}$ cycle at a 1C-rate. The dashed bars indicate the remaining specific energy after 300 cycles. As discussed before, stable cycling was possible for NMC111 and NMC622 up to $4.4\\mathrm{V}$ and up to $4.0\\mathrm{V}$ for NMC811. This is also clearly visible in Figure 11, as the differences between the specific energies in the $5^{\\mathrm{th}}$ and $300^{\\mathrm{th}}$ cycle are fairly low for these voltage limits, but increase significantly for the others. The highest specific energy with stable cycling was achieved with NMC622 cycled up to $4.4\\mathrm{\\V}$ . Comparing only the cells with stable cycling performance, it becomes clear that NMC811 reaches the lowest specific energy, which is due to the very low applicable end-of-charge voltage of only $4.0\\mathrm{V}.$ \n\nThis rather sobering outlook for NMC811 emphasizes the need to prohibit the oxygen release from the surface. Our results suggest that one way of making use of the high capacities of NMC811 and achieving stable cycling at the same time might be possible by either a core-shell structure in which the core consists of NMC811 with i) a shell that has a Ni-content of up to $60\\%$ (surface like NMC622) and does not release oxygen until ${>}4.4\\:\\mathrm{V}$ or ii) a shell consisting of an ordered spinel like high-voltage spinel (LNMO) that does hardly evolve any gases (Figure 5) due to the absence of oxygen release. In both cases the shell would need to be thick enough to prevent oxygen loss from the core structure via the limited diffusion of the oxygen anions. Indeed, these approaches have been used by several research groups and we believe that the prevention of oxygen release explains the successful use of core-shell85–88 materials possessing Nicontents in the core and shell of $80\\%$ and $\\leq55\\%$ , respectively, and full concentration gradient89–91 materials with Ni-contents of $\\geq75\\%$ and $\\leq56\\%$ in the particle center and the surface, respectively. Additionally, also a superior performance of $\\mathrm{LiMn}_{2}{\\mathrm{O}}_{4}$ coated NMC over uncoated samples was reported by Cho et al.92 \n\n# Conclusions \n\nThis work focused on a fundamental understanding of the aging phenomena at high voltage of $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ (NMC111), $\\mathrm{LiNi_{0.6}M n_{0.2}C o_{0.2}O_{2}}$ (NMC622), and $\\mathrm{LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}}$ (NMC811). NMC-graphite cells were cycled to different endof-charge potentials and it was demonstrated that stable cycling is possible up to $4.4\\mathrm{~V~}$ for NMC111 and NMC622 and only up to $4.0\\mathrm{V}$ for NMC811. The capacity fading rates observed at $4.6\\mathrm{V}$ for NMC111 and NMC622 and $4.1~\\mathrm{V}$ and $4.2\\mathrm{~V~}$ for NMC811 are due to a significant increase in the polarization of the NMC electrode as evidenced by charge/discharge cycling in a 3-electrode setup with a lithium reference electrode. In contrast, the polarization of the graphite electrode remained rather constant. By a $\\mathrm{\\dq/dV}$ analysis we demonstrated that the significant rise in the impedance occurs when the NMC materials are cycled up to a high-voltage feature at ${\\sim}4.7\\mathrm{v}$ vs. $\\mathrm{Li/Li^{+}}$ for NMC111 and NMC622 and up to the $\\mathrm{H}2\\rightarrow\\mathrm{H}3$ phase transition at ${\\sim}4.3\\mathrm{V}$ vs. $\\mathrm{Li/Li^{+}}$ for NMC811; we hypothesize that this is caused by oxygen release from the NMC lattice. \n\nOxygen release is evidenced by On-line Electrochemical Mass Spectrometry (OEMS). Simultaneously with the oxygen evolution, also $\\mathrm{CO}_{2}$ and CO are evolved, which we suggest to be mostly due to a chemical reaction of electrolyte with released lattice oxygen rather than the electrochemical oxidation of electrolyte on the cathode surface. We proposed a mechanism for the reaction of released oxygen with ethylene carbonate yielding $\\mathrm{CO}_{2}$ , CO and $\\mathrm{H}_{2}\\mathrm{O}$ . By quantifying the evolved gases, we estimated the thickness of the oxygen depleted surface layer to be up to ${\\sim}15~\\mathrm{nm}$ , which is in agreement with previous microscopy studies in the literature. Furthermore we showed that no oxygen is released from high voltage spinel (LNMO) and in consequence also no $\\mathrm{CO}_{2}$ or CO evolution was observed. These results support the hypothesis that the $\\mathrm{CO}_{2}$ and CO evolution at potentials up to $4.8\\mathrm{V}$ is to a large extent linked to the release of oxygen, rather than to the electrochemical oxidation of the carbonate electrolyte. \n\nThe highest specific energy of ${\\sim}650\\ \\mathrm{mWh/g_{NMC}}$ with a stable cycling performance at a 1 C-rate was obtained in NMC622-graphite cells cycled up to $4.4~\\mathrm{V}.$ . Due to the low end-of-charge voltage limit of $4.0\\mathrm{V}$ for a stable cycling of NMC811-graphite cells, the achieved specific energy is significantly lower than for the NMC622 cells. Therefore a stabilization of the NMC surface is necessary to prevent the release of oxygen from the particle surface. \n\n# Acknowledgment \n\nThe authors thank BMW AG for their financial support. Umicore is greatly acknowledged for supplying the cathode materials. We thank Benjamin Strehle and Sophie Solchenbach for very fruitful discussions and great contributions to this work. R. J. also thanks TUM-IAS for their support in the frame of the Rudolf-Diesel Fellowship of Dr. Peter Lamp. M. M. gratefully acknowledges funding by BASF SE through its electrochemistry and battery research network. \n\n# References \n\n1. O. Groeger, H. A. Gasteiger, and J. -P. Suchsland, Journal of The Electrochemical Society, 162, A2605 (2015). \n2. D. Andre, S. -J. Kim, P. Lamp, S. F. Lux, F. Maglia, O. Paschos, and B. Stiaszny, J. Mater. Chem. A, 3, 6709 (2015). \n3. K. G. Gallagher, S. Goebel, T. Greszler, M. Mathias, W. Oelerich, D. Eroglu, and V. Srinivasan, Energy Environ. Sci., 7, 1555 (2014). 4. I. Belharouak, Y. K. Sun, J. Liu, and K. Amine, J. Power Sources, 2003, 123, 247. \n5. M. S. Whittingham, Chem. Rev. (Washington, DC, U. S.), 104, 4271 (2004). 6. J. Choi and A. Manthiram, J. Electrochem. Soc., 152, A1714 (2005). 7. N. Yabuuchi, Y. Makimura, and T. Ohzuku, Journal of The Electrochemical Society, 154, A314 (2007). \n8. M. G. Kim, H. J. Shin, J. -H. Kim, S. -H. Park, and Y. -K. Sun, Journal of The Electrochemical Society, 152, A1320 (2005). \n9. S. -K. Jung, H. Gwon, J. Hong, K. -Y. Park, D. -H. Seo, H. Kim, J. Hyun, W. Yang, and K. Kang, Adv. Energy Mater., 4, 1300787 (2014). \n10. H. Gabrisch, T. Yi, and R. Yazami, Electrochem. Solid-State Lett., 11, A119 (2008). \n11. I. Buchberger, S. Seidlmayer, A. Pokharel, M. Piana, J. Hattendorff, P. Kudejova, R. Gilles, and H. A. Gasteiger, Journal of The Electrochemical Society, 162, A2737 (2015). \n12. M. Metzger, B. Strehle, S. Solchenbach, and H. A. Gasteiger, Journal of The Electrochemical Society, 163, A798 (2016). \n13. D. R. Gallus, R. Schmitz, R. Wagner, B. Hoffmann, S. Nowak, I. Cekic-Laskovic, R. W. Schmitz, and M. Winter, Electrochim. Acta, 134, 393 (2014). \n14. H. Zheng, Q. Sun, G. Liu, X. Song, and V. S. Battaglia, J. Power Sources, 207, 134 (2012). \n15. Y. -C. Lu, A. N. Mansour, N. Yabuuchi, and Y. Shao-Horn, Chemistry of Materials, 21, 4408 (2009). \n16. A. M. Andersson, D. P. Abraham, R. Haasch, S. MacLaren, J. Liu, and K. Amine, Journal of The Electrochemical Society, 149, A1358 (2002). \n17. J. Wandt, A. Freiberg, R. Thomas, Y. Gorlin, A. Siebel, R. Jung, H. A. Gasteiger, and M. Tromp, Journal of Materials Chemistry A, 4, 18300 (2016). \n18. H. -J. Noh, S. Youn, C. S. Yoon, and Y. -K. Sun, J. Power Sources, 233, 121 (2013). \n19. W. Liu, P. Oh, X. Liu, M. -J. Lee, W. Cho, S. Chae, Y. Kim, and J. Cho, Angew. Chem., Int. Ed., 54, 4440 (2015). \n20. J. Zheng, W. H. Kan, and A. Manthiram, ACS Appl. Mater. Interfaces, 7, 6926 (2015). \n21. S. -M. Bak, E. Hu, Y. Zhou, X. Yu, S. D. Senanayake, S. -J. Cho, K. -B. Kim, K. Y. Chung, X. -Q. Yang, and K. -W. Nam, ACS Appl. Mater. Interfaces, 6, 22594 (2014). \n22. S. -M. Bak, K. -W. Nam, W. Chang, X. Yu, E. Hu, S. Hwang, E. A. Stach, K. -B. Kim, K. Y. Chung, and X. -Q. Yang, Chem. Mater., 25, 337 (2013). \n23. H. Konishi, T. Yuasa, and M. Yoshikawa, J. Power Sources, 196, 6884 (2011). \n24. H. Arai, S. Okada, Y. Sakurai, and J. -i. Yamaki, Solid State Ionics, 109, 295 (1998). \n25. I. Belharouak, W. Lu, D. Vissers, and K. Amine, Electrochemistry Communications, 8, 329 (2006). \n26. I. Belharouak, D. Vissers, and K. Amine, Journal of The Electrochemical Society, 153, A2030 (2006). \n27. S. -T. Myung, K. -S. Lee, C. S. Yoon, Y. -K. Sun, K. Amine, and H. Yashiro, J. Phys. Chem. C, 114, 4710 (2010). \n28. D. P. Abraham, R. D. Twesten, M. Balasubramanian, I. Petrov, J. McBreen, and K. Amine, Electrochem. Commun., 4, 620 (2002). \n29. D. P. Abraham, R. D. Twesten, M. Balasubramanian, J. Kropf, D. Fischer, J. McBreen, I. Petrov, and K. Amine, Journal of The Electrochemical Society, 150, A1450 (2003). \n30. S. Muto, Y. Sasano, K. Tatsumi, T. Sasaki, K. Horibuchi, Y. Takeuchi, and Y. Ukyo, Journal of The Electrochemical Society, 156, A371 (2009). \n31. S. Hwang, W. Chang, S. M. Kim, D. Su, D. H. Kim, J. Y. Lee, K. Y. Chung, and E. A. Stach, Chem. Mater., 26, 1084 (2014). \n32. F. La Mantia, F. Rosciano, N. Tran, and P. Novak, J. Appl. Electrochem., 38, 893 (2008). \n33. P. Lanz, H. Sommer, M. Schulz-Dobrick, and P. Novak, Electrochim. Acta, 93, 114 (2013). \n34. A. R. Armstrong, M. Holzapfel, P. Novak, C. S. Johnson, S. -H. Kang, M. M. Thackeray, and P. G. Bruce, J. Am. Chem. Soc., 128, 8694 (2006). \n35. K. Luo, M. R. Roberts, R. Hao, N. Guerrini, D. M. Pickup, Y. -S. Liu, K. Edstro¨ m, J. Guo, A. V. Chadwick, L. C. Duda, and P. G. Bruce, Nat Chem, 8, 684 (2016). \n36. B. Strehle, K. Kleiner, R. Jung, F. Chesneau, M. Mendez, H. A. Gasteiger, and M. Piana, Journal of The Electrochemical Society, 164, A400 (2017). \n37. A. Gu´eguen, D. Streich, M. He, M. Mendez, F. F. Chesneau, P. Nov´ak, and E. J. Berg, Journal of The Electrochemical Society, 163, A1095 (2016). \n38. M. Metzger, J. Sicklinger, D. Haering, C. Kavakli, C. Stinner, C. Marino, and H. A. Gasteiger, Journal of The Electrochemical Society, 162, A1227 (2015). chemical Society, 160, A471 (2013). \n40. B. Strehle, S. Solchenbach, M. Metzger, K. U. Schwenke, and H. A. Gasteiger, to be submitted. \n41. M. Dubarry, C. Truchot, B. Y. Liaw, K. Gering, S. Sazhin, D. Jamison, and C. Michelbacher, J. Power Sources, 196, 10336 (2011). \n42. J. C. Burns, A. Kassam, N. N. Sinha, L. E. Downie, L. Solnickova, B. M. Way, and J. R. Dahn, Journal of The Electrochemical Society, 160, A1451 (2013). \n43. L. Ma, J. Xia, and J. R. Dahn, Journal of The Electrochemical Society, 161, A2250 (2014). \n44. K. J. Nelson, G. L. d’Eon, A. T. B. Wright, L. Ma, J. Xia, and J. R. Dahn, Journal of The Electrochemical Society, 162, A1046 (2015). \n45. R. Petibon, L. Madec, D. W. Abarbanel, and J. R. Dahn, Journal of Power Sources, 300, 419 (2015). \n46. H. Arai, S. Okada, H. Ohtsuka, M. Ichimura, and J. Yamaki, Solid State Ionics, 80, 261 (1995). \n47. W. Li, J. N. Reimers, and J. R. Dahn, Solid State Ionics, 1993, 67, 123. \n48. J. P. Peres, F. Weill, and C. Delmas, Solid State Ionics, 116, 19 (1999). \n49. S. U. Woo, C. S. Yoon, K. Amine, I. Belharouak, and Y. K. Sun, J. Electrochem. Soc., 154, A1005 (2007). \n50. M. Sathiya, G. Rousse, K. Ramesha, C. P. Laisa, H. Vezin, M. T. Sougrati, M. L. Doublet, D. Foix, D. Gonbeau, W. Walker, A. S. Prakash, M. Ben Hassine, L. DuPont, and J. M. Tarascon, Nat Mater, 12, 827 (2013). \n51. E. McCalla, A. M. Abakumov, M. Saubanere, D. Foix, E. J. Berg, G. Rousse, M. -L. Doublet, D. Gonbeau, P. Novak, G. Van Tendeloo, R. Dominko, and J. -M. Tarascon, Science (Washington, DC, U. S.), 350, 1516 (2015). \n52. D. -H. Seo, J. Lee, A. Urban, R. Malik, S. Kang, and G. Ceder, Nat Chem, 8, 692 (2016). \n53. M. Saubanere, E. McCalla, J. M. Tarascon, and M. L. Doublet, Energy & Environental Science, 9, 984 (2016). \n54. M. Xu, N. Tsiouvaras, A. Garsuch, H. A. Gasteiger, and B. L. Lucht, J. Phys. Chem. C, 118, 7363 (2014). \n55. S. A. Freunberger, Y. Chen, Z. Peng, J. M. Griffin, L. J. Hardwick, F. Bard´e, P. Nov´ak, and P. G. Bruce, Journal of the American Chemical Society, 133, 8040 (2011). \n56. E. S. Takeuchi, H. Gan, M. Palazzo, R. A. Leising, and S. M. Davis, Journal of The Electrochemical Society, 144, 1944 (1997). \n57. H. Yoshida, T. Fukunaga, T. Hazama, M. Terasaki, M. Mizutani, and M. Yamachi, J. Power Sources, 68, 311 (1997). \n58. R. Petibon, L. Rotermund, K. J. Nelson, A. S. Gozdz, J. Xia, and J. R. Dahn, Journal of The Electrochemical Society, 161, A1167 (2014). \n59. M. Metzger, C. Marino, J. Sicklinger, D. Haering, and H. A. Gasteiger, Journal of The Electrochemical Society, 162, A1123 (2015). \n60. B. Zhang, M. Metzger, S. Solchenbach, M. Payne, S. Meini, H. A. Gasteiger, A. Garsuch, and B. L. Lucht, The Journal of Physical Chemistry C, 119, 11337 (2015). \n61. M. Nie, D. Chalasani, D. P. Abraham, Y. Chen, A. Bose, and B. L. Lucht, J. Phys. Chem. C, 117, 1257 (2013). \n62. D. Aurbach, Y. Gofer, M. Ben-Zion, and P. Aped, J. Electroanal. Chem., 339, 451 (1992). \n63. M. Onuki, S. Kinoshita, Y. Sakata, M. Yanagidate, Y. Otake, M. Ue, and M. Deguchi, Journal of The Electrochemical Society, 155, A794 (2008). \n64. R. Bernhard, M. Metzger, and H. A. Gasteiger, Journal of The Electrochemical Society, 162, A1984 (2015). \n65. S. Meini, N. Tsiouvaras, K. U. Schwenke, M. Piana, H. Beyer, L. Lange, and H. A. Gasteiger, Phys. Chem. Chem. Phys., 15, 11478 (2013). \n66. R. Dedryvere, D. Foix, S. Franger, S. Patoux, L. Daniel, and D. Gonbeau, J. Phys. Chem. C, 114, 10999 (2010). \n67. L. Xing and O. Borodin, Phys. Chem. Chem. Phys., 14, 12838 (2012). \n68. K. Abe, T. Hattori, K. Kawabe, Y. Ushigoe, and H. Yoshitake, Journal of The Elecrochemical Society, 154, A810 (2007). \n69. Y. Koyama, N. Yabuuchi, I. Tanaka, H. Adachi, and T. Ohzuku, Journal of The Electrochemical Society, 151, A1545 (2004). \n70. L. Wu, K. -W. Nam, X. Wang, Y. Zhou, J. -C. Zheng, X. -Q. Yang, and Y. Zhu, Chem. Mater., 23, 3953 (2011). \n71. K. -W. Nam, W. -S. Yoon, and X. -Q. Yang, J. Power Sources, 189, 515 (2009). \n72. J. Xia, K. J. Nelson, Z. Lu, and J. R. Dahn, Journal of Power Sources, 329, 387 (2016). \n73. J. Xia and J. R. Dahn, Journal of Power Sources, 324, 704 (2016). \n74. M. Nie, J. Xia, and J. R. Dahn, Journal of The Electrochemical Society, 162, A1186 (2015). \n75. J. Xia, M. Nie, J. C. Burns, A. Xiao, W. M. Lamanna, and J. R. Dahn, Journal of Power Sources, 307, 340 (2016). \n76. F. Wilkinson, W. P. Helman, and A. B. Ross, Journal of Physical and Chemical Reference Data, 24, 663 (1995). \n77. D. V. Kazakov, V. P. Kazakov, G. Y. Maistrenko, D. V. Mal’zev, and R. Schmidt, The Journal of Physical Chemistry A, 111, 4267 (2007). \n78. J. Li, L. E. Downie, L. Ma, W. Qiu, and J. R. Dahn, Journal of The Electrochemical Society, 162, A1401 (2015). \n79. R. Imhof and P. Novak, J. Electrochem. Soc., 146, 1702 (1999). \n80. M. Metzger, B. Strehle, S. Solchenbach, and H. A. Gasteiger, Journal of The Electrochemical Society, 163, A1219 (2016). \n81. M. Jiang, B. Key, Y. S. Meng, and C. P. Grey, Chem. Mater., 21, 2733 (2009). \n82. S. Meini, S. Solchenbach, M. Piana, and H. A. Gasteiger, Journal of The Electrochemical Society, 161, A1306 (2014). \n83. N. Yabuuchi, Y. -T. Kim, H. H. Li, and Y. Shao-Horn, Chemistry of Materials, 20, 4936 (2008). \n84. T. Ma, G. -L. Xu, Y. Li, L. Wang, X. He, J. Zheng, J. Liu, M. H. Engelhard, P. Zapol, L. A. Curtiss, J. Jorne, K. Amine, and Z. Chen, The Journal of Physical Chemistry Letters, 1072 (2017). \n85. J. -Y. Liao and A. Manthiram, J. Power Sources, 282, 429 (2015). \n86. Y. -K. Sun, S. -T. Myung, B. -C. Park, J. Prakash, I. Belharouak, and K. Amine, Nat. Mater., 8, 320 (2009). \n87. Y. -K. Sun, S. -T. Myung, M. -H. Kim, J. Prakash, and K. Amine, J. Am. Chem. Soc., \n127, 13411 (2005). \n88. Y. -K. Sun, D. -H. Kim, C. S. Yoon, S. -T. Myung, J. Prakash, and K. Amine, Adv. Funct. Mater., 20, 485 (2010). \n89. Y. -K. Sun, Z. Chen, H. -J. Noh, D. -J. Lee, H. -G. Jung, Y. Ren, S. Wang, C. S. Yoon, S. -T. Myung, and K. Amine, Nat. Mater., 11, 942 (2012). \n90. E. -J. Lee, H. -J. Noh, C. S. Yoon, and Y. -K. Sun, J. Power Sources, 273, 663 (2015). \n91. C. Hua, K. Du, C. Tan, Z. Peng, Y. Cao, and G. Hu, J. Alloys Compd., 614, 264 (2014). \n92. Y. Cho, S. Lee, Y. Lee, T. Hong, and J. Cho, Adv. Energy Mater., 1, 821 (2011). " + }, + { + "id": "10.1016_j.actamat.2016.11.016", + "DOI": "10.1016/j.actamat.2016.11.016", + "DOI Link": "http://dx.doi.org/10.1016/j.actamat.2016.11.016", + "Relative Dir Path": "mds/10.1016_j.actamat.2016.11.016", + "Article Title": "Directly cast bulk eutectic and near-eutectic high entropy alloys with balanced strength and ductility in a wide temperature range", + "Authors": "Lu, YP; Gao, XZ; Jiang, L; Chen, ZN; Wang, TM; Jie, JC; Kang, HJ; Zhang, YB; Guo, S; Ruan, HH; Zhao, YH; Cao, ZQ; Li, TJ", + "Source Title": "ACTA MATERIALIA", + "Abstract": "High entropy alloys (HEAs) usually possess weak liquidity and castability, and considerable compositional inhomogeneity, mainly because they contain multiple elements with high concentrations. As a result, large-scale production of HEAs by casting is limited. To address the issue, the concept of eutectic high entropy alloys (EHEAs) was proposed, which has led to some promise in achieving good quality industrial scale HEAs ingots, and more importantly also good mechanical properties. In the practical large-scale casting, the actual composition of designed EHEAs could potentially deviate from the eutectic composition. The influence of such deviation on mechanical properties of EHEAs is important for industrial production, which constitutes the topic of the current work. Here we prepared industrial-scale HEAs ingots near the eutectic composition: hypoeutectic alloy, eutectic alloy and hypereutectic alloy. Our results showed that the deviation from eutectic composition does not significantly affect the mechanical properties, castability and the good mechanical properties of EHEAs can be achieved in a wide compositional range, and at both room and cryogenic temperatures. Our results suggested that EHEAs with simultaneous high strength and high ductility, and good liquidity and castability can be readily adapted to large-scale industrial production. The deformation behavior and microstructure evolution of the eutectic and near-eutectic HEAs were thoroughly studied using a combination of techniques, including strain measurement by digital image correlation, in-situ synchrotron X-ray diffraction, and transmission electron microscopy. The wavy strain distribution and the therefore resulted delay of necking in EHEAs were reported for the first time. (C) 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.", + "Times Cited, WoS Core": 877, + "Times Cited, All Databases": 920, + "Publication Year": 2017, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000393000800016", + "Markdown": "Full length article \n\n# Directly cast bulk eutectic and near-eutectic high entropy alloys with balanced strength and ductility in a wide temperature range \n\nYiping Lu a, 1, Xuzhou Gao b, 1, Li Jiang a, 1, Zongning Chen a, Tongmin Wang a, \\*, Jinchuan Jie a, Huijun Kang a, Yubo Zhang a, Sheng Guo c, \\*\\*, Haihui Ruan d, Yonghao Zhao b, Zhiqiang Cao a, Tingju Li a, \\*\\*\\* \n\na Key Laboratory of Solidification Control and Digital Preparation Technology (Liaoning Province), School of Materials Science and Engineering, Dalian \nUniversity of Technology, Dalian 116024, PR China \nb School of Materials Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, PR China \nc Surface and Microstructure Engineering Group, Materials and Manufacturing Technology, Chalmers University of Technology, SE-41296 Gothenburg, \nSweden \nd Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: \nReceived 27 September 2016 \nReceived in revised form \n27 October 2016 \nAccepted 5 November 2016 Keywords: \nHigh entropy alloys \nIndustrial scale casting Mechanical properties Eutectic \nIn-situ X-ray diffraction \n\nHigh entropy alloys (HEAs) usually possess weak liquidity and castability, and considerable compositional inhomogeneity, mainly because they contain multiple elements with high concentrations. As a result, large-scale production of HEAs by casting is limited. To address the issue, the concept of eutectic high entropy alloys (EHEAs) was proposed, which has led to some promise in achieving good quality industrial scale HEAs ingots, and more importantly also good mechanical properties. In the practical large-scale casting, the actual composition of designed EHEAs could potentially deviate from the eutectic composition. The influence of such deviation on mechanical properties of EHEAs is important for industrial production, which constitutes the topic of the current work. Here we prepared industrial-scale HEAs ingots near the eutectic composition: hypoeutectic alloy, eutectic alloy and hypereutectic alloy. Our results showed that the deviation from eutectic composition does not significantly affect the mechanical properties, castability and the good mechanical properties of EHEAs can be achieved in a wide compositional range, and at both room and cryogenic temperatures. Our results suggested that EHEAs with simultaneous high strength and high ductility, and good liquidity and castability can be readily adapted to large-scale industrial production. The deformation behavior and microstructure evolution of the eutectic and near-eutectic HEAs were thoroughly studied using a combination of techniques, including strain measurement by digital image correlation, in-situ synchrotron X-ray diffraction, and transmission electron microscopy. The wavy strain distribution and the therefore resulted delay of necking in EHEAs were reported for the first time. \n\n$\\circledcirc$ 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. \n\n# 1. Introduction \n\nRecently, a new type of alloys, high entropy alloys (HEAs) or multi-principal-element alloys, is becoming new research frontier in the metallic materials community [1e14]. Compared to conventional metallic alloys based on one or two principal elements, HEAs generally contain at least four principal elements. The concept of HEAs is a breakthrough to the alloy design in traditional physical metallurgy, and opens a new field for explorations of new materials and new properties [13,15]. Although the high configuration entropy in HEAs helps to stabilize solid solutions (against compound phases), previous studies have showed that most HEAs contain multiple phases rather than a single-phase solid solution [2,16e18]. From the alloy preparation perspective, most HEAs are made by casting, although the powder metallurgy route is also gaining more attention [19,20]. Casting of HEAs, particularly at a large scale (kilogram scale) is quite often a challenge, as most HEAs possess weak liquidity and castability (see Fig. S1 in the Supplementary Information for a demonstration) and considerable chemical inhomogeneity [21], which retards their industrial application. From the mechanical properties perspective, it is already known that in general single-phased body-centered cubic (bcc)-structured HEAs have limited ductility [22], while singlephased face-centered cubic (fcc)-structured HEAs could have high ductility but their strength is low [23]. How to reach the both high strength and high ductility is another challenge for the engineering application of HEAs. \n\nTo address the above mentioned problems facing the real application of HEAs, the current authors proposed to use the eutectic alloy concept to design HEAs, aiming at good castability of eutectic alloys and composite structure to resolve the strengthductility trade-off [21,24]. Our initial efforts in making eutectic HEAs (EHEAs) have led to kilogram-scale $\\mathsf{A l C o C r F e N i}_{2.1}$ HEA with good liquidity and castability, which also exhibits good mechanical properties at both room temperature and elevated temperatures up to $700^{\\circ}\\mathsf C$ [21]. \n\nPractically, the actual composition of EHEAs could deviate from the designed eutectic composition, especially for the large-scale casting. How would the deviation from the eutectic composition affect mechanical properties of EHEAs? The acceptable compositional range for desired mechanical properties is certainly important for the industrial production of EHEAs, but remains unexplored. This motivates the current work. Here we prepared industrial-scale ingots near the previously studied eutectic composition, AlCoCrFeNi2.1, and tested how the mechanical properties of EHEAs vary in a compositional range near the eutectic composition. We chose to use directly cast materials for the study, since we are expecting to avoid subsequent thermomechanical treatments by developing sufficiently good as-cast materials. Certainly, the performance of as-cast materials that are reported here can be further improved by thermomechanical treatments [21,24]. \n\n# 2. Experimental \n\nThe master alloy of hypoeutectic AlCoCrFeNi2.0 (Ni2.0), eutectic AlCoCrFeNi2.1 (Ni2.1), and hypereutectic AlCoCrFeNi2.2 (Ni2.2) were prepared from commercially pure elements (Al, Co, Ni: $99.9~\\mathrm{wt\\%}$ ; Cr, Fe: $99.5\\mathrm{-}99.6~\\mathrm{wt\\%}$ . The raw elements were alloyed in a BN crucible in the vacuum induction melting furnace. The BN crucible was heated to $600^{\\circ}\\mathsf C$ and held for $^{1\\mathrm{~h~}}$ to remove the water vapor, before putting into the furnace. The pouring temperature was set to be $1500~^{\\circ}\\mathsf C.$ An IRTM-2CK infrared pyrometer was employed to monitor the temperature with an absolute accuracy of $\\pm2^{\\circ}{\\mathsf{C}}.$ Approximately $2.5~\\mathrm{kg}$ of master alloys were melted, superheated and poured into a MgO crucible with the length of $220~\\mathrm{{mm}}$ , upper inner diameter of $62~\\mathrm{{mm}}$ and bottom inner diameter of $50~\\mathrm{mm}$ . In all cases, the furnace chamber was first evacuated to $6\\times10^{-2}$ Pa and then backfilled with high-purity argon gas to reach $0.06\\ensuremath{\\mathrm{MPa}}$ . The microstructure and composition of the alloy were investigated by scanning electron microscope (SEM, Zeiss Supra 55) equipped with an attached $\\mathsf{X}$ -ray energy dispersive spectrometer (EDS). The phase constitution of the alloy was characterized by the X-ray diffractometer (XRD, Shimadzu XRD-6000) using a Cu target, with the scanning rate of $4^{\\circ}/\\mathrm{min}$ and the 2q scanning range of $20^{\\circ}-100^{\\circ}$ . Room-temperature (RT) tensile tests were performed using the Instron 5569 testing machine at a constant strain rate of $1\\times10^{-3}$ $s^{-1}$ , and the bar-shaped tensile test samples had a gauge length of $20~\\mathrm{mm}$ , width of $3\\ \\mathrm{mm}$ and thickness of $3~\\mathrm{mm}$ . Cryogenic tensile tests at $-70^{\\circ}C$ and $-196^{\\circ}C$ were performed on rod-shaped samples with a gauge length of $28~\\mathrm{mm}$ and diameter of $5\\mathrm{mm}$ , using a MTS 810 testing machine at an strain rate of $1\\times10^{-3}\\:s^{-1}.$ Before tensile tests, the specimens and grips were immersed in a liquid nitrogen bath for about $5{-}10~\\mathrm{min}$ ; during tensile tests, the specimens stayed completely submerged in the liquid nitrogen and the temperature was measured by the thermocouple. After stretching to tensile rupture, thin sheets with a thickness of $300\\upmu\\mathrm{{m}}$ were cut from the cross section of the gauge areas for microstructure observation using transmission electron microscopy (TEM, JEM2100F). TEM samples were first mechanically ground to $45~{\\upmu\\mathrm{m}}$ in thickness, then punched into foils with a diameter of $3\\ \\mathrm{mm}$ , and finally thinned by a twin-jet electropolisher using the electrolyte made of $90\\mathrm{{vol}\\%}$ alcohol and $10\\mathrm{vol}\\%$ perchloric acid at a voltage of $20\\mathrm{~kV}.$ To further understand the deformation behavior, the strain field of the AlCoCrFeNi2.1 EHEA sheet within the gauge length was further mapped by the Nakazima test (strain measurement by digital image correlation, SMDIC, see Fig. S2). Tensile tests were carried out on a Series LFM- $20\\ \\mathrm{kN}$ electromechanical universal testing machine with a strain rate of $1\\times10^{-3}\\ s^{-1}$ at room temperature. Bar-shaped tensile samples with a gauge length of $20\\mathrm{mm}$ width of $3\\ \\mathrm{mm}$ and thickness of ${\\sim}2~\\mathrm{mm}$ were grounded and polished before tension. The measurement to evaluate the strain needs an initial high-contrast stochastic pattern of spots on the outer surface of the test sample, which was achieved by first spraying a background of adhesive and flexible matte white paint on the tensile samples, and then spraying a fine layer of spots of black paint onto the background. From the beginning of loading to the final failure, the evolution of the black spots was recorded using two CCD cameras positioned in a non-symmetrical configuration: first one directly in front of the specimen and the second one at about $32^{\\circ}$ to the normal direction of the specimen. This setting allows performing 3D DIC analysis. The CCD camera recorded 2 images per second during the tension test, which were processed using the ARAMIS software to determine the full-field displacements. For understanding the phase transformation during the tensile testing, in-situ synchrotron XRD analysis was carried out on the 4W1A beamline at Beijing Synchrotron Radiation Facility (BSRF), China. The synchrotron X-ray with the wavelength of $1.54\\mathring{\\mathsf{A}}$ was irradiated on the tensile test sheets from the beginning of loading to final fracture. Dogbone-shaped specimens with a gauge length of $13\\mathrm{mm}$ and cross-section of $3\\mathrm{mm}\\times1$ mm were uniaxially tensile tested using a specially designed testing device (see Fig. S3) at a stretching speed of $10\\ \\upmu\\mathrm{m}\\ s^{-1}$ . Before testing, the specimens were grinded, polished and cleaned with alcohol. The tensile specimen was positioned at $45^{\\circ}$ from the incident beam, while a fan-shaped detector with the apex angle of $120^{\\circ}$ was set at the direction of the emergent beam (Figs. S4 and S5). The incident beam and the detector were kept within the same plane. The scanning range was set from $20^{\\circ}$ to $160^{\\circ}$ , as main peaks are concentrated in this range. The diffraction patterns were collected every per $30s.$ Then diffraction angle 2q corresponding to the (hkl) crystal plane was converted to the lattice spacing, d, using the Bragg's law. The lattice strain perpendicular to the (hkl) crystal plane was determined from the shifts of the lattice spacing. Specifically, the lattice strains $\\varepsilon_{\\mathrm{hkl}}$ during an applied load can be calculated from the equation $\\varepsilon_{\\mathrm{hkl}}=(\\mathbf{d}_{\\mathrm{hkl}}\\mathbf{-d}_{\\mathrm{hkl},0})/\\mathbf{d}_{\\mathrm{hkl},0}$ in which $\\mathbf{d}_{\\mathrm{hkl}}$ is determined from the hkl εreflection during tension, and $\\mathbf{d}_{\\mathrm{hkl},0}$ refers to the value for zero load. Finally, lattice strain as a function of loading time for five families of (hkl) crystal planes were obtained during the tensile loading at RT. \n\n# 3. Results and discussion \n\n# 3.1. Microstructure and phase identification \n\nIndustrial scale $\\mathsf{A l C o C r F e N i_{x}}$ $\\mathbf{\\tilde{x}}=2.0$ , 2.1 and 2.2) ingots of ${\\sim}2.5~\\mathrm{kg}$ each in weight were prepared. All the ingots exhibited an excellent castability during the casting process, similar to most conventional eutectic alloys. SEM images of the cast microstructure of Ni2.0, Ni2.1 and Ni2.2 ingots are shown in Fig. $_{1(\\mathsf{a}-\\mathsf{c})}$ . Even at such a large ingot, the dominating microstructure in hypoeutectic (Ni2.0) and hypereutectic (Ni2.2) HEAs are fairly uniform and fine lamella, very similar to those in the EHEA (Ni2.1), except for the existence of some small amounts of primary phases. Inter-lamellar spacing in all three HEAs ingots are about $1{-}3\\upmu\\mathrm{m}$ . According to the microstructure and EDS analysis, the hypoeutectic $\\mathsf{N i2.0}$ alloy comprises a small amount of primary NiAl-rich phase plus eutectic FeCr-rich phase/NiAl-rich phase, while the hypereutectic Ni2.2 alloy comprise a small amount of primary FeCr-rich phase plus eutectic FeCr-rich phase/NiAl-rich phase. The FeCr-rich phase and \n\n![](images/4e1e09b5e63e65e67012d4c9bbcc7bae2a1ee8243f9bd33f9ea4e474d3ea79b2.jpg) \nFig. 1. SEM image showing the microstructure of the bulk AlCoCrFeNix $\\mathbf{\\check{X}}=2.0,$ , 2.1, and 2.2) alloys: (a) hypoeutectic $_{\\mathrm{AlCoCrFeNi_{2.0}}}$ alloy; (b) eutectic AlCoCrFeNi2.1 alloy, and (c) hypereutectic AlCoCrFeN $\\mathbf{i}_{2.2}$ alloy. \n\nNiAl-rich phase have been previously identified to be fcc and B2 phase, respectively [21]. The XRD patterns shown in Fig. 2 further confirm that only a mixture of fcc and B2 phases are observed in Ni2.0, Ni2.1 and Ni2.2 HEAs, and the amount of fcc phase increases when the alloy compositions shifts from hypoeutectic to hypereutectic composition, in agreement with the microstructural observation. TEM observations (see section 3.5 and Ref. [24]) further show that the fcc phase is actually ordered, with the $\\mathbf{L}1_{2}$ structure. \n\n# 3.2. Tensile properties \n\nThe hypoeutectic Ni2.0 and hypereutectic Ni2.2 alloys exhibit a combination of both high strength and high ductility, close to that of the Ni2.1 EHEA. Specifically, from the RT engineering stressstrain curves given in Fig. 3(a), the yield and fracture stresses of Ni2.0, Ni2.1 and Ni2.2 alloys are almost the same, which are \\~ 545 MPa and ${\\sim}1100\\ \\mathrm{MPa}$ , respectively. Ni2.0 and Ni2.1 alloys fracture at $16\\mathrm{-}17\\%$ elongation, while that of the hypereutectic Ni2.2 alloy reaches ${\\sim}20\\%$ , owing to the highest content of the soft fcc phase among three alloys. \n\nThe engineering stress-stain curves for Ni2.0, Ni2.1 and Ni2.2 alloys at cryogenic temperatures are shown in Fig. 3(b and c). At $-70^{\\circ}\\mathsf C,$ , the yield stress, fracture stress and elongation of Ni2.0, Ni2.1 and Ni2.2 alloys are $580~\\mathrm{MPa}/1034~\\mathrm{MPa}/10.5\\%,$ , 595 MPa/1168 $\\mathrm{MPa}/15.8\\%$ , $570~\\mathrm{MPa}/1143~\\mathrm{MPa}/18.0\\%$ respectively. Compared to the RT properties, both the yield strength and fracture strength increase slightly, which is in trade-off of elongation. Still, a quite good combination of strength and ductility is maintained at $-70^{\\circ}\\mathsf C,$ from hypoeutectic to eutectic to hypereutectic alloys. At even lower temperature of $-196^{\\circ}C,$ , the yield strength continues to increase, to ${\\sim}700\\ensuremath{\\mathrm{MPa}}$ for all three alloys, while the ductility decreases sharply, to $4\\%$ for hypoeutectic Ni2.0 alloy which contains more hard/brittle B2 phase, and to $7\\%$ and $9\\%$ for eutectic and hypereutectic alloys. The early fracture also limits the fracture strength of three alloys to 1000e1100 MPa. With decreasing temperature, dislocation motions become more difficult due to the reduced thermal energy for crossing Peierls-Nabarro barriers, and more dislocations accumulate inside the crystal before moving out to accommodate the plastic strain, thus leading to less ductility. This scenario is more severe in the bcc phase than in the fcc phase due to the much higher temperature sensitivity of the Peierls-Nabarro force in the former [23,25], which explains why the hypoeutectic Ni2.0 alloy containing more of bcc phase shows the lowest ductility at $-196^{\\circ}C,$ while the hypereutectic Ni2.2 alloy containing more fcc phase can keep a decent ductility (of ${\\sim}9\\%$ elongation) at the same temperature. The detailed mechanical properties of casting bulk AlCoCrFeNix $\\mathbf{\\check{X}}=2.0$ , 2.1, and 2.2 ) alloys are summarized in Table 1. \n\n![](images/6295f20da95a73820fafc0f6f533c585a846cbc6c4fffc56940b2d4f005873c5.jpg) \nFig. 2. XRD pattern of AlCoCrF $\\mathrm{\\partial_{\\z}N i_{x}}$ $\\mathbf{\\check{x}}=2.0,2.1$ and 2.2) alloys. \n\n![](images/d414d5446ea4639e5fc78320d2f716b54acd93b18ee5552d4c75fcd32a41ffb9.jpg) \nFig. 3. Engineering tensile stress-strain curves of AlCoCrFeNix $\\mathbf{\\tilde{x}}=2.0$ , 2.1 and 2.2) alloys. at RT (a), at $-70^{\\circ}C$ (b), and at $-196^{\\circ}C$ (c). \n\nFig. 4 shows the fracture surface morphology of the as-cast Ni2.1 EHEA at cryogenic temperatures and at room temperature. Ni2.0 and Ni2.2 alloys present similar fracture morphology, so only the Ni2.1 alloy is chosen for analysis here. For the same reason, only results from the Ni2.1 alloy are given in the following discussions to represent all three alloys unless otherwise stated. As shown in \n\nFig. 4, the fracture surface features mainly trench-like microstructures. By connecting the fcc/B2 composite structure in the Ni2.1 EHEA, it is reasonable to infer the formation mechanism of these trench-like microstructures: during the tensile deformation, the hard B2 phase is barely deformed while the soft fcc phase is stretched; the fcc phase then gradually becomes thinner and edges up, leaving the barely deformed bcc phase at the bottom of the trench. This assumption is supported by the EDS analysis made at the fractured surface. The fact that there exist more trench-like microstructures in the $-196^{\\circ}C$ fractured alloy also lends support to the above given argument on the temperature-sensitive flow stress of the bcc phase. \n\n# 3.3. The Nakazima test \n\nIt is of interest to note that although presenting a large ductility, necking is not obvious in tensile tests at both RT and cryogenic temperatures (see Fig. 5(a)). The mechanism for this peculiar deformation deserves further studies. The Nakazima tests (SMDIC) were therefore conducted to map the full-field strain distribution. Besides the eutectic and near-eutectic HEAs, the as-cast fcc-structured pure Ni and bcc-structured pure Fe specimens were also tested for comparison. Fig. 5(b) shows the strain field of the EHEA specimen within the gauge length at different stages during tension. In the early stages of deformation, the strain is distributed almost uniformly throughout the entire loading area. After a few seconds, strain localization occurs within a narrow band at some location. Subsequently, the other strain localization appears at a new location. During the course of deformation, it is found that the high-strain and the low-strain regions alternatively appear, exhibiting a wavy strain distribution. This feature is in line with the negligible necking observed in three types of HEAs, which however is markedly different from the conventional understanding of deformation behavior of strain-hardening materials. If the strain hardening rate is uniform, strain localization should occur in one narrow zone, which leads to necking and fracture. This is the case for pure Ni and Fe as shown in Fig. 5(c and d). For both pure Ni and pure Fe, the strain is first distributed almost uniformly within the gauge length at the early stages of loading. With further deformation, the strain starts to localize in just one narrow band (much faster in bcc-Fe compared to fcc-Ni), finally leading to the necking and fracture of the tensile sample. The distinct deformation behavior of EHEAs in comparison with pure metals may be understood from a soft region/hard region composite structure assumption. During tensile deformation, the softer region will deform first, while the hard regions will stay less deformed. With further deformation, the soft region becomes sufficiently hardened such that the initially hard region start to undergo more deformation (strain). As the deformation goes on, the alternation of soft and hard regions leads to the wavy strain distribution, as is shown in Fig. 5(b). It should be stressed that the “wave length” of the wavy strain field observed in Fig. 5(b) is much larger than the width of fcc and B2 lamella. Therefore, the soft and hard regions are not simply corresponding to the soft fcc and hard B2 lamella in the microstructure. Our understanding of deformation behavior of EHEA at this stage is merely qualitative. The main point is that the actual hardening behavior in EHEA is not uniform, which leads to the nonuniform strain field during the whole course of plastic deformation till fracture. From the perspective of the phase constitution in the eutectic alloy, the hard B2 phase renders the alloy with high strength, while the soft fcc phase enables the alloy to have some decent ductility. Such a combination brings about the good balance of high strength and high ductility in the EHEA. However, the very limited deformability of the hard B2 phase also restricts the further deformation of the alloy (Fig. 4). To the best of our knowledge, this is the first time that such a wavy distribution of strain is reported in HEAs and even in metallic materials. The therefore resulted effective delay of necking (and failure) is of significant importance for engineering materials in service. \n\n![](images/7f8219429cf149b7aa8e8dd6725bd2517f1e10a5d5fdf024b98932dc6285bb0f.jpg) \nFig. 4. Fracture surface morphology of the AlCoCrFeNi2.1 EHEAs: (a) at $-196^{\\circ}C;$ (b) at $-70{}^{\\circ}\\mathsf C;$ (c) at RT. \n\n![](images/6b7c96ad071a603a8ca7215d9daa7bb635806b433403974c0d063be94f30f077.jpg) \nFig. 5. Appearance of the tensile specimen at the end of the Nakazima test (a); Nakazima test results measured at different time steps (stages) during tension: (b) the strain field of the AlCoCrFeN $\\mathrm{i}_{2.1}$ EHEA, presenting wave-like distribution; (c) and (d) the strain field of the pure Ni and pure Fe metal, showing the evolution of strain localization and necking development. \n\n# 3.4. In-situ synchrotron X-ray diffraction test \n\nThe simultaneous achievement of high strength and high ductility in large-scale directly cast hypoeutectic, eutectic and hypereutectic HEAs is quite appealing, which is also seldom seen in both conventional alloys and other HEAs reported previously, at the as-cast state. It is intriguing to understand whether any phase transformation occurs during the deformation process. For this purpose, in-situ synchrotron XRD under uniaxial tensile loading at RT was conducted for the Ni2.1 EHEA. Fig. 6(a) shows the diffraction patterns taken from the tensile test specimen, from the beginning of loading to the final fracture. No phase transformation can be detected, suggesting the combination of high strength and high ductility does not originate from phase transformations. Fig. 6(b) shows the variation of lattice strain with loading time for five different crystallographic planes, indicating a strong elastic anisotropy. It can be seen that {200} and {311} planes have the lowest elastic modulus, while {220} and {222} planes have the highest. For the Ni2.1 EHEA with the fcc/B2 composite structure, its deformation behavior is quite similar to that of traditional fcc alloys and other fcc-structured HEAs [26]. This scenario also echoes our previous argument for the decent but still limited ductility in the EHEA due to the role B2 phase plays. It is worth noting that {200} and {311} planes of the AlCoCrFeNi2.1 EHEA can sustain larger lattice strain compared to the fcc-structured HEA reported previously [26], of above \\~ 0.004 and ${\\sim}0.003$ till tensile fracture. The apparent reason for the larger lattice strain in {200} and {311} planes is due to the lower elastic moduli in these planes, which can be immediately seen by comparing Fig. 6(b) with a similar plot measured for fcc-structured CoCrFeMnNi HEA in Ref. [26]. The elastic modulus on {311} planes is quite close to that on {200} planes, and it is noted that this also differs to the case for CoCrFeMnNi, where the elastic modulus on {311} planes is noticeably higher than that on {200} planes. It is of great interest to look further into the seemingly peculiar elastic behavior of the EHEA, and specifically why the elastic moduli on {200} and {311} planes are close and much lower than those on other planes, which however is not the focus of the current work and will be addressed separately. \n\n![](images/864168c335fac66767b45f76183fc1a5fc10500798b16fed01e859297fd0d6a4.jpg) \nFig. 6. (a) Selected X-ray diffraction patterns collected at different time steps during tensile loading at RT. (b) Loading time versus lattice strain curves for five crystal planes obtained during tensile loading at RT. The stresses at the 5th, 10th, 15th, 20th and 25th minute of the tensile testing process tracted from the recorded stress as a function of loading time, and indicated on the plot. \n\n# 3.5. TEM analysis \n\nTEM analysis was performed to further identify the structure of these eutectic and near-eutectic HEAs after tensile testing. The dark lamellar structure in Fig. 7(a) is confirmed to correspond to the B2 phase, while the light lamellar structure corresponds to the ordered fcc (L12) phase, with their diffraction patters given in Fig. 7(b and c). TEM results confirm that the Ni2.1 EHEA after tensile testing still comprise a mixture of (ordered) fcc and B2 phase, and there is no new phase formed during the tensile testing process, in agreement with the in-situ synchrotron XRD result. Fig. 8 displays the microstructure of the Ni2.1 EHEA after tensile fracture. It is clear that a large number of dislocations occur in the soft fcc phase, while no obvious dislocation are observed in the hard/brittle B2 phase. Dislocation slip was blocked in the fcc/B2 phase boundary. A higher dislocation density is seen in the fcc phase near the fcc/B2 phase boundary, compared to the dislocation density further inside the fcc phase. Except for dislocations, no detectable twinning was observed under TEM. It is therefore experimentally confirmed that the easy motion of dislocations in the soft fcc phase provides the N2.1 EHEA with high ductility, and the block-up of dislocations at the fcc/B2 phase boundaries provides the EHEA with high strength. Moreover, the long and straight dislocations and high density of dislocation debris demonstrate the strong interaction of multiple slip systems at room temperature. \n\n# 4. Application potential of EHEAs in cryogenic environments \n\nThe simultaneous achievement of good castability and chemical homogeneity, and both high strength and high ductility at both room temperature and cryogenic temperatures, in directly cast industrial-scale EHEAs, provides these materials with great application potential in environments requiring directly cast materials (no subsequent thermomechanical treatment) with superior properties. Cryogenic environments, for example, can be the ideal occasion where EHEAs can find their applications. We use the propeller blades of the icebreaker as a specific example here to explain how directly-cast EHEAs can be the material of the choice in such an environment. An icebreaker is a special-purpose designed ship to move and navigate through ice-covered waters (in particular the Arctic, is opening up new waterways and international trade route), and provide safe waterways for other ships. The external components of the icebreaker's propulsion system, including propellers and propeller shafts, determines its ability to propel itself onto the ice, break it, and clear the debris from its path successfully, are therefore essential for its safety. Mainly due to their irregular shape and large volume, propeller blades are prepared by direct casting and are not subject to subsequent thermomechanical treatments to further improve the mechanical performance. Thus, the directly cast materials need to satisfy the demanding application environments. The materials used for propeller blades of icebreakers must have high strength and high impact toughness (therefore high ductility) at low temperatures. Stainless steel and bronze are commonly used materials for propeller blades [27], but there remains a large room for these two materials to improve. Bronze have good castability and high ductility but its low strength is a concern, while stainless steels have poorer castability and their strength is also not high enough. The newly developed EHEAs, with excellent castability and chemical homogeneity and relatively low density $({\\sim}7.38~\\mathrm{g/cm^{3}}$ [21]) can therefore be the (much) better alternative materials for propeller blades. Our results also show that EHEAs containing high amount of Cr and Al, possess quite good corrosion resistance in the sea water (the potentiodynamic polarization curves of AlCoCrFeNi2.1 EHEA in $3.5\\%\\mathsf{N a C l}$ solution, the simulated seawater environment, is given in Fig. S6), which is also a necessary material property as propeller blade materials (see Table 1). \n\n![](images/adf59dc3728784a23da4856026dc6f0ec0a60f8ec46410e48944707a3a049d07.jpg) \nFig. 7. TEM images from the tensile Ni2.1 EHEA specimen stretched to fracture at RT: (a) Bright-field image showing the lamellar structure; (b) and (c) are the SADP (selected-area diffraction pattern) corresponding to the $\\mathbf{L}1_{2}$ and B2 phase, respectively. Superlattice diffraction spots are indicated by circles. \n\n![](images/ca0ab1433dfebe9c691443464fa1cea4cfe84c7eb6b4df931863bc7e27d2af0f.jpg) \nFig. 8. TEM images from the tensile Ni2.1 EHEA specimen stretched to fracture at RT: (a) a large number of dislocations are observed in the $\\mathtt{L}1_{2}$ phase, but not in the B2 phase; (b) dislocations within the $\\mathbf{L}1_{2}$ phase. \n\n# 5. Summary \n\nTo conclude, large-scale $(-2.5~\\mathrm{Kg})$ eutectic and near-eutectic AlCoCrFeNix $\\mathbf{\\tilde{X}}=2.0$ , 2.1 and 2.2) HEAs with alternating fine $\\mathsf{L}1_{2}/$ B2 lamellar structure were prepared, and their mechanical properties were evaluated at both room temperature and cryogenic temperatures. Tensile tests show that directly cast eutectic HEAs can exhibit both high strength and ductility in a comfortable compositional range, and also in a wide temperature range, which outperform most of conventional cast alloys and also HEAs reported previously. The deformation behavior and microstructure evolution of the eutectic and near-eutectic HEAs were carefully investigated by strain measurement using digital image correlation, in-situ synchrotron X-ray diffraction, and TEM. It is found for the first time that the strain field of the EHEA shows a wavy distribution and almost no necking occurs before fracture. The deformation behavior of EHEAs differs significantly from those of conventional fcc- and bcc-structured metals. The fine lamellar microstructure comprising fcc and B2 phase, and the related existence of soft and hard regions in EHEAs, effectively delays the onset of necking. The good ductility of the EHEA is mainly provided by the dislocation motion in the soft fcc phase, while the pile-up of dislocations at the fcc/B2 phase boundaries provides the alloy with high strength, which however also limits the further deformation of the alloy. No detectable phase transitions occurred during deformation and no deformation twins were observed after the tensile testing. Our results further convince that EHEAs have great potential in industrial applications, for example in ship propulsion systems. \n\nTable 1 Yield strength, fracture strength and elongation $(\\mathbb{E}\\mathbb{L}\\%)$ to fracture of Ni2.0, Ni2.1 and Ni2.2 alloys at room temperature (RT), and $-70$ and $-196^{\\circ}C$ . \n\n\n
Test temperatureAlloysOy (MPa)OUTs (MPa)EL%
RTNi2.0545.6107616.6
-70°CNi2.1546.4104617.7
Ni2.2544.5112020.5
Ni2.0580103410.5
Ni2.1595116815.8
-196 °CNi2.2570114318.0
Ni2.07159523.7
Ni2.169010516.7
Ni2.270511519.3
\n\n# Acknowledgments \n\nThis research was supported by the National Science Foundation of China (Nos. 51525401, 51471044 and 51671044), the National Key Research and Development Program of China (No. 2016YB0701203), the Fundamental Research Funds for Central Universities, Key Laboratory of Basic Research Projects, Department of Education of Liaoning Province (LZ2014007), and the Natural Science Foundation of Liaoning Province (2014028013). SG acknowledges the startup grant from Areas of Advance Materials Science at Chalmers University of Technology and the Junior \n\nResearcher Grant from the Swedish Research Council under grant 2015-04087. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007- 2013) under REA grant agreement no 608743(SG). \n\n# Appendix A. Supplementary data \n\nSupplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.actamat.2016.11.016. \n\n# References \n\n[1] B. Gludovatz, A. Hohenwarter, D. Catoor, E.H. Chang, E.P. George, R.O. Ritchie, A fracture-resistant high-entropy alloy for cryogenic applications, Science 345 (2014) 1153e1158. \n[2] O.N. Senkov, J.D. Miller, D.B. Miracle, C. Woodward, Accelerated exploration of multi-principal element alloys with solid solution phases, Nat. Commun. 6 (2015) 6529. \n[3] C. Zhu, Z.P. Lu, T.G. Nieh, Incipient plasticity and dislocation nucleation of FeCoCrNiMn high-entropy alloy, Acta Mater. 61 (2013) 2993e3001. \n[4] Z. Wu, Y. Gao, H. Bei, Thermal activation mechanisms and Labusch-type strengthening analysis for a family of high-entropy and equiatomic solidsolution alloys, Acta Mater. 120 (2016) 108e119. \n[5] J.Y. He, H. Wang, H.L. Huang, X.D. Xu, M.W. Chen, Y. Wu, et al., A precipitationhardened high-entropy alloy with outstanding tensile properties, Acta Mater. 102 (2016) 187e196. \n[6] Z. Li, K.G. Pradeep, Y. Deng, D. Raabe, C.C. Tasan, Metastable high-entropy dual-phase alloys overcome the strength-ductility trade-off, Nature 534 (2016) 227e230. \n[7] Z. Zhang, M.M. Mao, J. Wang, B. Gludovatz, Z. Zhang, S.X. Mao, et al., Nanoscale origins of the damage tolerance of the high-entropy alloy CrMnFeCoNi, Nat. Commun. 6 (2015) 10143. \n[8] J.Y. He, W.H. Liu, H. Wang, Y. Wu, X.J. Liu, T.G. Nieh, et al., Effects of Al addition on structural evolution and tensile properties of the FeCoNiCrMn highentropy alloy system, Acta Mater. 62 (2014) 105e113. \n[9] Z. Wang, I. Baker, Z. Cai, S. Chen, J.D. Poplawsky, W. Guo, The effect of interstitial carbon on the mechanical properties and dislocation substructure evolution in Fe40.4Ni11.3Mn34.8Al7.5Cr6 high entropy alloys, Acta Mater. 120 (2016) 228e239. \n[10] W.H. Liu, Z.P. Lu, J.Y. He, J.H. Luan, Z.J. Wang, B. Liu, et al., Ductile CoCrFeNiMox high entropy alloys strengthened by hard intermetallic phases, Acta Mater. 116 (2016) 332e342. \n[11] J.W. Yeh, S.K. Chen, S.J. Lin, J.Y. Gan, T.S. Chin, T.T. Shun, et al., Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes, Adv. Eng. Mater. 6 (2004) 299e303. \n[12] B. Cantor, I.T.H. Chang, P. Knight, A.J.B. Vincent, Microstructural development in equiatomic multicomponent alloys, Mater. Sci. Eng. A 375e377 (2004) 213e218. \n[13] Y. Zhang, T.T. Zuo, Z. Tang, M.C. Gao, K.A. Dahmen, P.K. Liaw, Z.P. Lu, Microstructures and properties of high-entropy alloys, Prog. Mater. Sci. 61 (2014) 1e93. \n[14] Z.P. Lu, H. Wang, M.W. Chen, I. Baker, J.W. Yeh, C.T. Liu, et al., An assessment on the future development of high-entropy alloys: summary from a recent workshop, Intermetallics 66 (2015) 67e76. \n[15] M.C. Gao, J.-W. Yeh, P.K. Liaw, Y. Zhang, High-entropy Alloys: Fundamentals and Applications, Springer, Cham, Switzerland, 2016. \n[16] F. Otto, Y. Yang, H. Bei, E.P. George, Relative effects of enthalpy and entropy on the phase stability of equiatomic high-entropy alloys, Acta Mater. 61 (2013) 2628e2638. \n[17] D.J.M. King, S.C. Middleburgh, A.G. McGregor, M.B. Cortie, Predicting the formation and stability of single phase high-entropy alloys, Acta Mater. 104 (2016) 172e179. \n[18] X.D. Xu, P. Liu, S. Guo, A. Hirata, T. Fujita, T.G. Nieh, et al., Nanoscale phase separation in a fcc-based CoCrCuFeNiAl0.5 high-entropy alloy, Acta Mater. 84 (2015) 145e152. \n[19] Z. Fu, W. Chen, H. Wen, D. Zhang, Z. Chen, B. Zheng, et al., Microstructure and strengthening mechanisms in an FCC structured single-phase nanocrystalline $\\mathrm{Co}_{25}\\mathrm{Ni}_{25}\\mathrm{Fe}_{25}\\mathrm{Al}_{7.5}\\mathrm{Cu}_{17.5}$ high-entropy alloy, Acta Mater. 107 (2016) 59e71. \n[20] S. Varalakshmi, M. Kamaraj, B.S. Murty, Synthesis and characterization of nanocrystalline AlFeTiCrZnCu high entropy solid solution by mechanical alloying, J. Alloy. Compd. 460 (2008) 253e257. \n[21] Y. Lu, Y. Dong, S. Guo, L. Jiang, H. Kang, T. Wang, et al., A promising new class of high-temperature alloys: eutectic high-entropy alloys, Sci. Rep. 4 (2014) 6200. \n[22] O.N. Senkov, G.B. Wilks, J.M. Scott, D.B. Miracle, Mechanical properties of $\\mathsf{N b}_{25}\\mathsf{M o}_{25}\\mathsf{T a}_{25}\\mathsf{W}_{25}$ and $\\mathrm{V}_{20}\\mathrm{Nb}_{20}\\mathrm{Mo}_{20}\\mathrm{Ta}_{20}\\mathrm{W}_{20}$ refractory high entropy alloys, Intermetallics 19 (2011) 698e706. \n[23] C. Varvenne, A. Luque, W.A. Curtin, Theory of strengthening in fcc high entropy alloys, Acta Mater. 118 (2016) 164e176. \n[24] I. Wani, T. Bhattacharjee, S. Sheikh, Y. Lu, S. Chatterjee, P. Bhattacharjee, Mater. Res. Lett. (2016) 1, http://dx.doi.org/10.1080/21663831.2016.1160451. \n[25] F. Otto, A. Dlouhý, C. Somsen, H. Bei, G. Eggeler, E.P. George, The influences of temperature and microstructure on the tensile properties of a CoCrFeMnNi high-entropy alloy, Acta Mater. 61 (2013) 5743. \n[26] Y. Wu, W.H. Liu, X.L. Wang, D. Ma, A.D. Stoica, T.G. Nieh, et al., In-situ neutron diffraction study of deformation behavior of a multi-component high-entropy alloy, Appl. Phys. Lett. 104 (2014) 051910. \n[27] J. Carlton, Marine Propellers and Propulsion, third ed., Butterworth-Heinemann, Oxford, UK, 2012. " + }, + { + "id": "10.1126_sciadv.1601314", + "DOI": "10.1126/sciadv.1601314", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.1601314", + "Relative Dir Path": "mds/10.1126_sciadv.1601314", + "Article Title": "Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module", + "Authors": "Lee, H; Song, C; Hong, YS; Kim, MS; Cho, HR; Kang, T; Shin, K; Choi, SH; Hyeon, T; Kim, DH", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Electrochemical analysis of sweat using soft bioelectronics on human skin provides a new route for noninvasive glucose monitoring without painful blood collection. However, sweat-based glucose sensing still faces many challenges, such as difficulty in sweat collection, activity variation of glucose oxidase due to lactic acid secretion and ambient temperature changes, and delamination of the enzyme when exposed to mechanical friction and skin deformation. Precise point-of-care therapy in response to the measured glucose levels is still very challenging. We present a wearable/disposable sweat-based glucose monitoring device integrated with a feedback transdermal drug delivery module. Careful multilayer patch design and miniaturization of sensors increase the efficiency of the sweat collection and sensing process. Multimodal glucose sensing, as well as its real-time correction based on pH, temperature, and humidity measurements, maximizes the accuracy of the sensing. The minimal layout design of the same sensors also enables a strip-type disposable device. Drugs for the feedback transdermal therapy are loaded on two different temperature-responsive phase change nulloparticles. These nulloparticles are embedded in hyaluronic acid hydrogel microneedles, which are additionally coated with phase change materials. This enables multistage, spatially patterned, and precisely controlled drug release in response to the patient's glucose level. The system provides a novel closed-loop solution for the noninvasive sweat-based management of diabetes mellitus.", + "Times Cited, WoS Core": 895, + "Times Cited, All Databases": 971, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000397044000018", + "Markdown": "# B I O E N G I N E E R I N G \n\n# Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module \n\nHyunjae Lee,1,2\\* Changyeong Song,1,2\\* Yong Seok Hong,1,2 Min Sung Kim,1,2 Hye Rim Cho,1,3 Taegyu Kang,1,2 Kwangsoo Shin,1,2 Seung Hong Choi,1,3 Taeghwan Hyeon,1,2† Dae-Hyeong $\\K\\sin^{1,2+}$ \n\n2017 $\\circledcirc$ The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\nElectrochemical analysis of sweat using soft bioelectronics on human skin provides a new route for noninvasive glucose monitoring without painful blood collection. However, sweat-based glucose sensing still faces many challenges, such as difficulty in sweat collection, activity variation of glucose oxidase due to lactic acid secretion and ambient temperature changes, and delamination of the enzyme when exposed to mechanical friction and skin deformation. Precise point-of-care therapy in response to the measured glucose levels is still very challenging. We present a wearable/disposable sweat-based glucose monitoring device integrated with a feedback transdermal drug delivery module. Careful multilayer patch design and miniaturization of sensors increase the efficiency of the sweat collection and sensing process. Multimodal glucose sensing, as well as its real-time correction based on pH, temperature, and humidity measurements, maximizes the accuracy of the sensing. The minimal layout design of the same sensors also enables a strip-type disposable device. Drugs for the feedback transdermal therapy are loaded on two different temperature-responsive phase change nanoparticles. These nanoparticles are embedded in hyaluronic acid hydrogel microneedles, which are additionally coated with phase change materials. This enables multistage, spatially patterned, and precisely controlled drug release in response to the patient’s glucose level. The system provides a novel closed-loop solution for the noninvasive sweat-based management of diabetes mellitus. \n\n# INTRODUCTION \n\nDiabetes is one of the most prevalent chronic diseases, causing uncontrollable blood glucose levels (1). Patients with diabetes are advised to check their blood glucose level daily and to take periodic insulin shots for continuous management of their blood glucose level (2). However, patients often do not follow this recommendation because of the pain and accompanying intense stress of repetitive blood collection and insulin shots. This often leads to various severe diabetic complications, such as cardiovascular and kidney diseases, stroke, blindness, and nerve degeneration. In addition, insulin overtreatment causes an abrupt drop in the blood glucose concentration, which may cause seizures, unconsciousness, and even death. Therefore, a novel method for painless and stress-free glucose monitoring (3–5) and precise maintenance of homeostasis through controlled drug delivery (6, 7) is highly desirable. \n\nExtensive efforts have been made to develop noninvasive sweatbased biomarker monitoring methods. Wearable biosensors enable continuous monitoring of metabolites [including glucose (3–5), lactate (8), and alcohol (9)] and electrolytes [including potassium (3), calcium (10), and heavy metal ions $(l I)]$ in sweat. The estimation of the blood glucose concentration based on the sweat-based glucose measurement is a potential solution (12, 13). However, many challenges still exist for the accurate sweat-based glucose measurement (14, 15). For example, the sweat collection procedure is tedious, and the sweat collection times vary depending on environmental conditions. In addition to the difficulty of measuring glucose levels in sweat because of its much smaller concentration than that in blood, lactic acid in sweat, ambient temperature changes, and various medications can induce errors in enzyme-based glucose sensing. Mechanical friction and deformation of devices on soft human skin can delaminate the enzyme from the glucose sensor and cause mechanical fractures in devices. A closed-loop system with the feedback delivery of a precisely controlled amount of drugs in response to the glucose monitoring result is another important unaccomplished goal for maintaining homeostasis (6, 7). \n\nVarious kinds of flexible and stretchable devices based on an ultrathin (16–18) and stretchable design (19, 20) have been developed for monitoring individual health status and delivering the corresponding feedback therapy (21, 22). Here, we develop a patch-based wearable/strip-type disposable system for noninvasive sweat glucose monitoring and microneedle-based point-of-care therapy (23). Key novel advantages of this system include (i) mass production–compatible porous metal-based electrodes and fabrication processes, (ii) miniaturized sensor design that allows for reliable sweat analysis even with an infinitesimal amount of sweat, (iii) patch- and disposable-type design for enhancing practical applicability, (iv) multiple sweat control and uptake layers for efficient sweat collection, (v) a porous gold nanostructure for maximizing the electrochemically active surface area for detection of a small amount of glucose in sweat with high sensitivity, (vi) multiple glucose sensing devices for enhanced accuracy, and (vii) multistage and precisely controlled transdermal drug [metformin or chlorpropamide (type 2 diabetes drugs)] delivery through biocompatible hyaluronic acid hydrogel microneedles containing drug-loaded phase change nanoparticles (PCNs). Metformin is one of the first-line drugs for treating type 2 diabetes (24). Because drug delivery through the skin can bypass the digestive system, transdermal delivery of metformin requires a lower dosage of drugs than oral delivery and prevents gastrointestinal side effects (23). This novel system for high-fidelity sweat glucose measurement and feedback-controlled drug delivery enables efficient management of blood glucose concentration without pain and stress. \n\n# RESULTS \n\n# System design of the wearable diabetes patch and disposable strip \n\nThe patch-based wearable devices in Fig. 1A have an ultrathin and stretchable design (fig. S1A), which enables conformal contact with the skin for efficient sweat collection and high performance under physical deformation. The same sensors can be further miniaturized and fabricated as a disposable strip (Fig. 1B). Depending on the sweat glucose concentration, an appropriate amount of metformin (or chlorpropamide) is transdermally delivered through microneedles. The drug delivery can be thermally controlled in a multistage manner. The microneedles assembled on the multichannel thermal actuator can be periodically replaced with new ones (Fig. 1C and fig. S1, B and C). These patch-type devices are fabricated on a handle substrate and then transfer-printed onto a thin silicone patch (fig. S2). The strip-type sensor is fabricated on a thin polyimide (PI) substrate. Patterned electrochemical functionalization completes the fabrication. \n\nThe system operation sequence is schematically described in fig. S3. After wearing the patch, sweat accumulates in the porous sweat-uptake layer. A waterproof band behind the silicone patch aids in sweat collection and prevents delamination of the patch from the skin. A porous and negatively charged Nafion layer between the sensors and the sweat-uptake layer helps in the immobilization of the enzyme (25) and screens out negatively charged molecules that may affect the glucose sensing (for example, drug molecules contained in sweat, such as acetaminophen or acetylsalicylic acid) (25, 26). A humidity sensor monitors the critical amount of sweat for reliable glucose sensing by measuring impedance change by sweat generation. Above the critical humidity, the glucose, $\\mathrm{\\boldmath~\\pH,}$ and temperature sensors begin taking measurements to determine correlated blood glucose level. The $\\mathrm{\\pH}$ and temperature sensors correct potential errors of the enzyme-based glucose level measurement in real time. Upon hyperglycemia, thermal actuation controls the feedback transdermal delivery of metformin loaded in PCNs. \n\n![](images/312b75b6b960eadc053ad8ed4c539218c3ae804344726925d92478ef652a93dc.jpg) \nFig. 1. Wearable/disposable sweat monitoring device and microneedle-based transdermal drug delivery module. (A) Optical camera image (top; dotted line, edges of the patch) and schematic (bottom) of the wearable sweat monitoring patch. A porous sweat-uptake layer is placed on a Nafion layer and sensors. (B) Optical camera image (top) and schematic (bottom) of the disposable sweat monitoring strip. (C) Optical camera image (top; dotted line, edges of the patch) and schematic (bottom) of the transdermal drug delivery device. Replacement-type microneedles are assembled on a three-channel thermal actuator. (D) Schematic drawing of the glucose sensor in an exploded view. PB, prussian blue. (E) Minimum volume of the artificial sweat required for sensing with different sizes of the glucose sensor. (F) Scanning electron microscope (SEM) images before (left) and after (right) immobilization of the enzyme (enz.) on the porous gold electrode. (G) Comparison of the ${\\sf H}_{2}{\\sf O}_{2}$ sensitivity in the planar and porous gold electrode deposited with Prussian blue at different $H_{2}O_{2}$ concentrations. (H) Schematic of the drug-loaded microneedles. The right inset describes details of different PCNs. (I) SEM image of the microneedles. (J) Confocal microscope images of the released dye from microneedles (MN) (top view) into the $4\\%$ agarose gel (green, agar; red, dye). (K) Infrared (IR) camera image of the three-channel (ch) thermal actuator. \n\n# Materials and key device design \n\nA series of stretchable sensors (humidity, glucose, $\\mathrm{\\pH}.$ , and temperature) are monolithically integrated (Fig. 1A) for efficient sweat-based glucose sensing. Multipoint sensing for glucose (triple) and $\\mathrm{\\pH}$ (quadruple) improves the detection accuracy (fig. S1A). In the glucose and pH sensors, the reference and counter electrodes are designed to be packed as closely as possible to minimize the required amount of sweat (Fig. 1D). As the working electrode diameter $(D_{\\mathrm{work}})$ decreases, the required sweat amount can be reduced to as small as $1\\upmu\\mathrm{l}$ (Fig. 1E), which is a 20-fold decrease from that previously reported by Lee et al. (5). The working electrode consists of porous gold formed by electrodeposition and enzymes [glucose oxidase $\\left(\\mathrm{GOx}\\right)]$ ] drop-casted on it and then covered by Nafion and sequentially cross-linked by glutaraldehyde (Fig. 1F). The porous structure allows for a larger electrochemically active surface area (27, 28) and stronger enzyme immobilization (29, 30). Cyclic voltammograms (fig. S4A) and ac impedance measurements (fig. S4, B and C) using the $\\mathrm{Fe(CN)_{6}}^{3-/4-}$ redox couple show a high charge storage capacity and low interfacial impedance in the porous structure. The high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ reducing catalytic activity of the porous structure (Fig. 1G and fig. S4D) confirms the enhanced sensitivity. Robustly cross-linked enzymes on the porous metal structure also enhance the reliability of the sensor under mechanical friction and deformation. \n\nFilm-type microneedles (fig. S1B) are integrated on top of the stretchable heater (fig. S1C), and these needles can be periodically replaced (Fig. 1C). For the multistep and precisely controlled drug delivery, two types of metformin-loaded PCNs [PCN1, melting transition temperature $(T_{\\mathrm{m,l}})=38^{\\circ}\\mathrm{C};$ PCN2, $T_{\\mathrm{m},2}=43^{\\circ}\\mathrm{C}]$ are embedded in the hyaluronic acid hydrogel microneedles (Fig. 1H). The hyaluronic acid hydrogel is a widely used biocompatible material (31). An additional coating with phase change materials (PCMs) prevents unwanted dissolution of the hyaluronic acid matrix in contact with interstitial fluids (Fig. 1H). Controlled thermal actuation by the integrated heater activates either PCN1 alone or both PCNs (fig. S5). An SEM image of the fabricated microneedles is shown in Fig. 1I. Confocal microscope images show the dye release from microneedles into $4\\%$ agarose gel (tissue-like gel) (Fig. 1J) (32). The heater is designed with three channels (Fig. 1K) and triggers the multistage drug delivery that can be tuned with thermal patterns. \n\n# Sweat control optimization \n\nEfficient use of the generated sweat is an important issue in the sweatbased monitoring system, which is enabled by the sweat-uptake and waterproof layers. A porous and hydrophilic sweat-uptake layer (Fig. 2A, inset) (33, 34), which is placed on the Nafion layer and sensors, absorbs sweat and delivers it to the sensors through the Nafion layer (fig. S6A). \n\nThe waterproof band added on the elastomeric silicone patch covers the outside to separate the sweat from external humidity (Fig. 2A), suppresses sweat evaporation (fig. S6B), and prevents delamination of the patch during skin deformation (Fig. 2B). The strip-type sensor absorbs sweat by the capillary force formed by the gap (fluidic channel) between the sweat-drawing layer and substrate (Figs. 1B, bottom inset, and 2C). The miniaturized sensor design (Fig. 1, D and E) and the fast collection of sweat enable rapid sensing. The miniaturized glucose sensor can be stably operated with only $1\\upmu\\mathrm{l}$ of sweat (Fig. 2D and fig. S6, C and D). \n\n# Electrochemical and electrical characterization of individual sensors \n\nThe humidity sensor monitors the sweat collection procedure through impedance changes of poly(3,4-ethylenedioxythiophene) (PEDOT) interdigitated electrodes to estimate an appropriate starting point of sweat analysis (Fig. 2E). The glucose sensor based on a Prussian blue– deposited porous gold electrode is calibrated to the glucose concentration range between $10\\upmu\\mathrm{M}$ and $1\\mathrm{mM}$ (typical glucose concentrations in human sweat) by the galvanostatic method (Fig. 2F and fig. S7, A and B). These glucose concentrations correspond to typical sweat glucose concentrations of both hypoglycemic and hyperglycemic patients as well as healthy people (12, 13). The glucose sensor is stable under mechanical deformation (fig. S7C) and selectively detects glucose in the presence of other biomolecules [including ascorbic acid, uric acid, and lactic acid (3, 35)] and drugs [including acetaminophen, acetylsalicylic acid, and metformin (fig. S7D) (36–38)], whose concentrations are in values commonly found in the human sweat. The glucose sensor works for one full day without additional calibration under ambient conditions and for several days depending on storage conditions (fig. S7E). \n\nThe enzyme-based glucose sensor shows deviations at different pH levels (fig. S7F), and thus simultaneous monitoring of pH levels is important. The $\\mathrm{\\pH}$ sensor measures changes in the open circuit potential (OCP) between a polyaniline (PANi)–deposited working electrode and an $\\mathrm{\\Ag/AgCl}$ electrode. The pH sensor is calibrated using standard pH buffer solutions (Fig. 2G and fig. S8A) and maintains stable operation under deformation (fig. S8B). Because the dependence of measured OCP and the pH was not linear, the calibration curves were obtained for every pH difference of 0.5. The pH sensor is reliable over repeated use at different pH levels (fig. S8C) and different temperatures (fig. S8D). The resistor-based temperature sensor is also calibrated for skin temperature monitoring (Fig. 2H). The simultaneous use of these co-integrated sensors can enhance the accuracy of glucose sensing. For example, metabolic secretion of lactic acid in sweat lowers the pH level to 4 to 5. The simultaneous $\\mathrm{\\pH}$ sensing can correct this $\\mathrm{\\pH}$ -dependent deviation (Fig. 2I and fig. S7F) of the enzyme-based glucose sensor. Simulated hyperglycemia— $\\mathrm{.0.3\\:mM}$ sweat glucose—is monitored in vitro under two different $\\mathrm{\\pH}$ variation settings $5\\mathrm{\\rightarrow}4\\mathrm{\\rightarrow}5$ and $5{\\rightarrow}6{\\rightarrow}5$ ; Fig. 2J, left and right). In both cases, real-time correction increases glucose measurement accuracy. The glucose sensor with the current device setting does not show significant deviations at different temperatures (Fig. 2K). \n\n# Thermoresponsive PCNs \n\nPCMs have melting temperatures that are low but above human body temperature, and thus they are widely used in the thermoresponsive drug delivery (39). PCNs are made of PCMs, drugs, and biocompatible ligands (Fig. 3A). Different PCNs enable temperature-dependent stepwise drug delivery. We use palm oil (PCN1, $T_{\\mathrm{m}}=38^{\\circ}\\mathrm{C},$ ) and tridecanoic acid (PCN2, $T_{\\mathrm{m}}=43^{\\circ}\\mathrm{C}$ ), which melt above the skin temperature \n\n1 $30^{\\circ}\\mathrm{C};$ fig. S9A). The drugs (metformin or chlorpropamide) are embedded in the PCM matrix (Fig. 3A and fig. S9, B to D). Pluronic F127 and 3,4-dihydroxyl-L-phenylalanine (DOPA)–conjugated hyaluronic acid (fig. S10, A and B) are used as ligands, which make an oil-in-water emulsion (fig. S11A). Cryogenic transmission electron microscopy (cryoTEM) images show that PCNs below the melting temperature are solid (Fig. 3, B and C, left). Above the melting temperature, PCNs change to liquid and aggregate (Fig. 3, B and C, right). Cytotoxicity tests show that both PCNs are nontoxic and suitable for biomedical applications (fig. S11B). The hydrodynamic diameters and negative zeta potentials of the PCNs slightly increase and decrease, respectively, as the temperature increases from the skin temperature ( $30^{\\circ}\\mathrm{C};$ fig. S9A) to above melting temperatures ( $40^{\\circ}$ and $45^{\\circ}\\mathrm{C};$ Fig. 3D and fig. S11C). The PCM matrices can block the drug release before thermal actuation. Their stepwise temperature-dependent melting controls the amount of the drug release. When the temperature reaches $40^{\\circ}\\mathrm{C},$ only the drugs contained in PCN1 are released, whereas at $45^{\\circ}\\mathrm{C}_{:}$ , the drugs in both PCN1 and PCN2 are released (fig. S11D). \n\n# Microneedle fabrication and multistage drug delivery \n\nThe microneedles are fabricated by molding the hyaluronic acid hydrogel matrix containing drug-loaded PCNs, followed by an additional PCM spray coating (Fig. 3E, left, and fig. S12). A confocal laser fluorescence microscope image shows that the dye-loaded PCNs are well embedded in the microneedles (Fig. 3E, right). Hydrogel-based microneedles dissolve when they come in contact with body fluids (Fig. 3F, left), whereas the PCM coating prevents the dissolution before the controlled melting of the PCM (Fig. 3F, right). The microneedles should be stiff enough to penetrate into the skin (40); compression tests confirm their mechanical strength (Fig. 3G). The microneedles successfully penetrate into $4\\%$ agarose gel (tissue-like gel) and generate pores (Fig. 3H, left). After poration by microneedles, vertical heat transfer dissolves the outside PCM coating and embedded PCNs. Although accidental peel-offs create small defects in the PCM coating, the drug contained in the PCNs is not released. The vertical temperature distribution of the agarose gel imaged by an IR camera confirms the successful heat transfer (Fig. 3H, right). To investigate the stepwise drug release, we heated the microneedles containing dyes from $25^{\\circ}$ to $45^{\\circ}\\mathrm{C}$ (Fig. 3I). There is a negligible release under and around the skin temperature $(30^{\\circ}\\mathrm{C})$ due to the PCM coating and PCNs. At the elevated temperature $(40^{\\circ}\\mathrm{C})$ , the PCM coating on microneedles and PCN1 are dissolved, and metformin in PCN1 is released. At the higher temperature $(45^{\\circ}\\mathrm{C})$ , metformin in both PCN1 and PCN2 is released. Spatial patterning of the embedded heater subdivides the release steps further, which is precisely controlled (fig. S13A) by co-integrated temperature sensors (fig. S13, B and C). Heaters consisting of the three channels together with the two types of PCNs result in eight different spatiothermal patterns (Fig. 3J) and six-stage programmed dye-release profiles (Fig. 3K). \n\n![](images/bca77dfe4971cac35d2e609796b79fffd7691792dd548b2ff1170bb8d17bbddf.jpg) \nFig. 2. Optimization of the sweat control and characterization of individual sensors. (A) Optical image of the wearable sweat analysis patch with a sweat-uptake layer and a waterproof band. The inset shows the magnified view of the porous sweat-uptake layer. (B) Optical image of the sweat analysis patch under deformation. (C) Optical image of the disposable sweat analysis strip on human skin with perspiration. (D) Glucose (glu.) concentration measurement at different sweat volumes $(0.3~\\mathsf{m M}$ glucose in artificial sweat). (E) Optical image (top) and calibration curve (bottom) of the humidity sensor. Inset shows the image before and after wetting of the sensor. (F) Optical image (top) and calibration curve (bottom) of the glucose sensor. (G) Optical image (top) and calibration curve (bottom) of the pH sensor. (H) Optical image (top) and calibration curve (bottom) of the temperature sensor. (I) Changes of the relative sensitivity of the uncorrected glucose sensor at different pH levels. The relative sensitivity $(S/S_{\\mathrm{o}})$ is defined as measured sensitivity divided by sensitivity at pH 5. (J) In vitro monitoring of glucose changes with (green) and without (red) correction using simultaneous pH measurements (blue). (K) Calibration curves of the glucose sensor at different temperatures. \n\n# Sweat-based glucose monitoring on human subjects \n\nWearable/disposable sweat-based glucose sensors are used for human sweat analysis. The wearable patch is connected to a portable electrochemical analyzer (Fig. 4A and fig. S14). The monitoring starts with humidity sensing to determine the optimum point to start sweat analysis (Fig. 4B). When the sweat-uptake layer absorbs a sufficient amount of sweat, the glucose and $\\mathrm{\\pH}$ sensors detect the sweat glucose and $\\mathrm{\\pH}$ levels, respectively. The triple glucose and quadruple pH sensing (fig. S1A) improve the detection accuracy (Fig. 4C). The correction using the measured $\\mathrm{\\pH}$ enables more accurate glucose sensing (Fig. 4D). The patch works reliably under different skin temperatures (temperature range, $30^{\\circ}$ to $37^{\\circ}\\mathrm{C}$ ) before, during, and after physical movements (fig. S15, A and B). The changes of skin temperature with the current experimental setting are small because of homeostatic functions of the nervous system (41). The patch is reusable and/or reattachable multiple times (fig. S15, C and D). \n\nThe disposable strip-type sensor is more convenient for the sweat analysis. The strip-type sensor first absorbs sweat (Fig. 2C) because of the capillary effect, and it is then connected to the hardware for sweat analysis through a ZIF connector (Fig. 4E). The absorbed sweat should cover the surface of both pH and glucose sensors (Fig. 4F). The amount of absorbed sweat can be monitored by measuring the impedance between the electrodes of the glucose sensor (Pt counter electrode and $\\mathrm{\\Ag/AgCl}$ reference electrode) and those of the $\\mathrm{\\pH}$ sensor (two PANideposited working electrodes) (Fig. 4G). The strip-type sensor can be stably operated with $4{\\upmu\\upmu\\upmu\\upmu$ of sweat (fig. S16A). When the sweat covers both glucose and pH sensors, the measurements begin (Fig. 4H). The calibration curves for a strip-type device are shown in fig. S16 (B and C). \n\nThe sweat $\\mathrm{pH}$ levels vary among subjects and depending on the physiological conditions of each subject (fig. S17A). The sweat glucose levels corrected by pH measurements before and after a meal agree well with the sweat glucose levels measured among subjects using a commercial glucose assay kit (Fig. 4I). Statistical analysis confirms the reliable correlation of sweat glucose levels measured by the wearable and disposable sweat glucose sensors with the blood glucose levels measured by a commercial glucose meter (fig. S17B). For the accurate estimation of the blood glucose level based on the sweat glucose level, the correlation factor between the glucose concentration of blood and sweat should be found for each individual subject with enough data (fig. S17C). With this data, it is clear that blood glucose concentration tends to vary before and after a meal, similarly to the measured sweat glucose concentration (Fig. 4J). \n\n# Controlled transdermal drug delivery using microneedles \n\nTransdermal drug delivery experiments based on the fabricated microneedles and integrated heaters in vivo are conducted on 8-to-12-week-old diabetic (db/db) mice (type 2 diabetes mellitus model). The in vivo treatment starts with lamination of a therapeutic patch on the shaved abdomen of the db/db mouse (Fig. 4K). Trypan blue staining on the mouse skin confirms that the microneedles can successfully penetrate the skin for the drug (metformin) delivery (fig. S18A). The integrated heaters modulate the amount of the drug delivery by the controlled thermal actuation (fig. S18B). Control groups that have no patch (black), microneedles without diabetes drugs (red), and microneedles with diabetes drugs (blue, dose 1; green, dose 2) are used (Fig. 4L). The experimental groups (blue and green) show significant decrease in blood glucose level compared to the control groups (black and red). As more metformin is delivered to the db/db mice, the blood glucose level is suppressed more. The blood glucose concentration of the measurement group (dose 2, green) decreased to $7.6\\mathrm{mM}$ , which is a normoglycemic state $(<11\\mathrm{mM})$ . \n\n![](images/c7e31eea6b7aaf91cf8d127d07f669370b60cf32e54bfb775df76beef184dedb.jpg) \nFig. 3. Characterization of PCNs and PCN-loaded microneedles. (A) Schematic illustration of the PCN. HA, hyaluronic acid. (B) Cryo-TEM image of PCN1 (palm oil) below the melting temperature (left) and TEM image of PCN1 above the melting temperature (right). (C) Cryo-TEM image of PCN2 (tridecanoic acid) below the melting temperature (left) and TEM image of PCN2 above the melting temperature (right). (D) Dynamic light scattering size measurement of PCNs at $30^{\\circ}$ (skin temperature), $40^{\\circ},$ and $45^{\\circ}\\mathsf{C}.$ (E) Optical image (left) and confocal fluorescence (FL) microscope image (right) of PCM-coated microneedles. Microneedles contain dye-loaded PCNs for imaging. (F) Microneedle dissolution test in PBS before (left) and after (right) the PCM coating. (G) Mechanical strength test of microneedles in their dry and wet states. (H) Confocal microscope image of microneedles penetrating into $4\\%$ agarose gel (left) and IR camera image of the thermal actuation on the gel (right). (I) Drug-release profile from microneedles. (J) IR camera images of eight different spatiothermal profiles using the three-channel thermal actuator for multistage drug delivery. (K) Multistage drug-release profile. a.u., arbitrary units. \n\n![](images/06c7be92d20ae22083254577581c61f74cbe6527d6d839aec55148a22145168c.jpg) \nFig. 4. Sweat-based glucose monitoring and feedback therapy in vivo. (A) Optical camera image of the subject using a cycle ergometer for sweat generation with the wearable patch on the subject’s arm. (B) Real-time humidity monitoring to check the accumulation of sweat. (C) Multimodal glucose and pH sensing to improve detection accuracy. (D) Measured sweat glucose concentrations $\\left(n=3\\right)$ ), pH levels $(n=4)$ , and corrected sweat glucose level $(n=3)$ based on the averaged $\\mathsf{p H}$ (dotted line, glucose concentration measured by a commercial glucose assay). (E) Optical camera image of the disposable strip-type sensors connected to a zero insertion force (ZIF) connector. (F) Optical camera images of the sweat uptake via the fluidic channel of the strip. (G) Humidity monitoring of the disposable strip using impedance measurements. (H) Sweat glucose and pH monitoring using the disposable strip. (I) Ratio of sweat glucose concentrations $(n=3)$ ) measured by the patch and a commercial glucose assay with and without the pH-based correction before and after a meal. (J) Comparison of the sweat and blood glucose concentrations before and after a meal. (K) Optical camera image of the transdermal drug delivery device on the db/db mouse. (L) Blood glucose levels of the db/db mice for the treated groups (microneedles with the drugs) and control groups (without the patch, microneedle without the drugs) $(^{*}P<0.05$ , ${\\sf X}\\ast{\\sf P}<0.01$ versus control, Student’s t test). \n\n# DISCUSSION \n\nWe report a novel material structure, device design, and system integration strategy for a sweat glucose monitoring device integrated with feedback transdermal drug delivery microneedles. Depending on the design, the device can be either wearable-patch type or disposable-strip type. For efficient sweat control and sensing, the sweat monitoring patch is assembled with multiple sweat-uptake and waterproof layers, and sensor sizes are miniaturized to the point that ${\\sim}1\\upmu\\mathrm{l}$ of sweat is sufficient for reliable measurement. The measurements of sweat glucose levels with real-time correction based on $\\mathrm{\\pH}$ , temperature, and humidity sensing are accurate under various environment changes. The sweat glucose data are well correlated with the blood glucose levels. For precise and timely drug delivery, two types of metformin-loaded PCNs are embedded in the PCM-coated microneedles. The thermoresponsive microneedles controlled by multichannel heaters enable the multistage and spatially patterned transdermal drug release in response to the measured sweat glucose level. \n\nFor practical application of the current system, there are several things to improve. The long-term stability and uniformity of sensors are particularly important to make the system practically applicable to human subjects with minimum recalibrations. Further studies about the correlation between glucose levels of blood and sweat are needed before application to diabetic patients. Although metformin used in the system shows slow suppression of the blood glucose levels due to its working mechanism (42), another kind of drug (for example, chlorpropamide) can be loaded for synergistic treatment or fast regulation of blood glucose level. With further improvements in these points, clinical translation can be pursued for sweat-based sensing and feedback therapy. The current system provides important new advances toward the painless and stress-free point-of-care treatment of diabetes mellitus. \n\n# MATERIALS AND METHODS Fabrication process of the device array \n\nThe wearable device fabrication began with spin-coating of the PI precursor $\\mathrm{\\langle\\sim1.5~\\upmum;}$ product $\\#575798$ , Sigma-Aldrich) on a $\\mathrm{SiO}_{2}$ wafer, followed by thermal curing of the PI. A $\\mathrm{Cr}/$ Au thin film $({\\sim}30\\mathrm{nm}/{\\sim}70\\mathrm{nm})$ ) was deposited on electrodes by thermal evaporation. The $\\mathrm{{Cr/Au}}$ thin film was patterned by photolithography and wet etching. A $\\mathrm{Cr/Pt}$ thin film $(\\sim10\\mathrm{nm}/{\\sim}100\\mathrm{nm})$ ) was deposited by sputtering and patterned by photolithography for the temperature sensor and the counter electrode of the glucose sensor. The top epoxy layer $(\\sim1.5\\upmu\\mathrm{m}$ ; SU8-2, MicroChem) was coated and patterned by photolithography. The bottom PI layer was selectively isolated by photolithography and reactive-ion etching. The device was transfer-printed onto a polydimethylsiloxane (PDMS) substrate (Sylgard 184, Dow Chemical) using a water-soluble tape (product #5414, 3M). The strip-type device was fabricated on the PI film ( $125\\upmu\\mathrm{m}$ ; Isoflex) using the same procedures. \n\n# Functionalization of sensors and electrodes with electrochemically active materials \n\n(i) PEDOT electrodeposition. A solution of $0.01\\mathrm{~M~}3.4$ -ethylenedioxythiophene (product #483028, Sigma-Aldrich) and $\\mathrm{0.1MLiClO_{4}}$ (product $\\#271004$ , Sigma-Aldrich) in acetonitrile (product $\\#271004$ , SigmaAldrich) was prepared. The gold electrode was dipped in the solution, and galvanostatic electrodeposition was performed for $40\\ s$ at $1.2\\mathrm{V}$ (potential versus commercial $\\mathrm{\\Ag/AgCl}$ electrode). \n\n(ii) $\\mathrm{\\Ag/AgCl}$ electrodeposition. An aqueous solution of $5~\\mathrm{mM}$ $\\mathrm{AgNO}_{3}$ (product $\\#209139$ , Sigma-Aldrich) and 1 M ${\\mathrm{KNO}}_{3}$ (product $\\#\\mathrm{P}8394$ , Sigma-Aldrich) was prepared. The gold electrode was dipped in the prepared solution. The potential was swept from $-0.9$ to $0.9{\\mathrm{~V~}}$ versus a Ag electrode for 14 segments at a scan rate of $0.1\\mathrm{~V~}\\boldsymbol{\\mathrm{s}}^{-1}$ . For chlorination, the electrode was dipped in an aqueous solution of $0.1\\mathrm{~M~}$ KCl (product #P5405, Sigma-Aldrich) and 0.01 M HCl (product #H1758, Sigma-Aldrich). The potential was swept from $-0.15$ to $1.05\\mathrm{V}$ versus a commercial Ag/AgCl electrode for four segments at a scan rate of $0.05\\mathrm{V~s}^{-1}$ . \n\n(iii) Porous gold electrodeposition. An aqueous solution of $2~\\mathrm{mM}$ $\\mathrm{\\HAuCl_{4}}$ (product #70-0500, Strem Chemicals) in 2 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ (product $\\#320501$ , Sigma-Aldrich) was prepared. The gold electrode was dipped in the prepared solution. The porous gold was electrodeposited by the galvanostatic method for $5\\mathrm{min}$ at $-1\\mathrm{V}$ with a Pt counter electrode and a commercial $\\mathrm{\\Ag/AgCl}$ electrode (total charge, ${\\sim}0.5\\mathrm{C},$ ). \n\n(iv) Prussian blue electrodeposition. An aqueous solution of $10\\mathrm{mM}$ KCl, $2.5~\\mathrm{mM}$ ${\\mathrm{K}}_{3}[\\mathrm{Fe}(\\mathrm{CN})_{6}]$ (product $\\#\\mathrm{P}702587$ , Sigma-Aldrich), and $2.5\\mathrm{mM}\\mathrm{FeCl_{3}}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ (product $\\#236489$ , Sigma-Aldrich) in $0.1\\mathrm{~M~}$ HCl was prepared. The gold electrode was dipped in the solution, and the potential was swept from 0 to $0.5\\mathrm{~V~}$ versus a commercial Ag/AgCl for two segments at a scan rate of $0.02\\mathrm{V~s}^{-1}$ . \n\n(v) GOx immobilization. 1 weight $\\%$ (wt $\\%$ ) chitosan (product #C3646, Sigma-Aldrich) solution was prepared by dissolving the chitosan in 2 wt $\\%$ acetic acid (product $\\#695092$ , Sigma-Aldrich). The chitosan solution was mixed with an exfoliated graphite (product $\\#282863$ , Sigma-Aldrich) solution $(2{\\mathrm{~mg~ml}}^{-1}),$ ) in $1\\times$ phosphate-buffered saline (Dulbecco’s PBS, WELGENE Inc.). The exfoliation process was conducted using an ultrasonic machine (Sonics VCX-750, Vibra-Cell) for $30\\mathrm{min}$ . The chitosan/graphene solution was mixed with GO $\\mathrm{:}(0.05\\mathrm{g}\\mathrm{ml}^{-1}$ ; product #G7141, Sigma-Aldrich) and bovine serum albumin (BSA) $\\mathsf{\\bar{(0.01\\ g\\ m l^{-1}}}$ ; product #A2153, Sigma-Aldrich). A solution of $\\operatorname{GOx}$ $(0.05\\mathrm{~\\bar{g}\\ m l^{-1})}$ and BSA $(0.01\\ \\mathrm{g\\ml^{-1}},$ ) was also prepared in $1\\times$ PBS. GOx and BSA $(0.8\\upmu\\mathrm{l})$ in a PBS solution was drop-casted on the porous gold–deposited electrode. After drying the electrodes under ambient conditions, $0.8~\\upmu\\mathrm{l}$ of GOx in the chitosan/graphene solution was drop-casted on the electrode. After drying the electrodes under ambient conditions, $2\\upmu\\mathrm{l}$ of 0.5 wt $\\%$ Nafion (product $\\#309389$ , Sigma-Aldrich) \n\nwas drop-casted on the glucose sensor. After drying of Nafion under ambient conditions, $0.8~\\upmu\\mathrm{l}$ of 2 wt $\\%$ glutaraldehyde (product $\\#\\mathrm{G}5882$ , Sigma-Aldrich) was drop-casted on the glucose sensor for robust crosslinking of the enzyme layer. \n\n(vi) PANi electrodeposition. An aqueous solution of $0.1\\mathrm{~M~}$ aniline (product $\\#242284$ , Sigma-Aldrich) in 1 M HCl was prepared. The gold electrode was dipped into the solution, and the potential was swept from $-0.2$ to 1 V versus a commercial $\\mathrm{\\Ag/AgCl}$ electrode for 60 segments at a scan rate of $0.1\\mathrm{~V~s~}^{-1}$ . \n\n# Fabrication of microneedles \n\nA female PDMS (Sylgard 184, Dow Chemical) mold was prepared on the basis of commercial microneedles (PAMAS, Prestige). The microneedles have a height of $1\\mathrm{mm}$ and a round base diameter of $250~{\\upmu\\mathrm{m}}$ . The drug-loaded PCNs [metformin (product #D150959, Sigma-Aldrich) or chlorpropamide (product #C129531, Aladdin)] and a $2\\%$ hyaluronic acid solution were drop-casted on the PDMS mold. The sample was placed under vacuum until no bubble was generated. After degassing, the sample was dried at room temperature. The microneedles were carefully peeled from the mold. The PCM (tetradecanol; product $\\#185388$ , Sigma-Aldrich) was sprayed on the microneedles. The morphology of the microneedles was examined with a field-emission SEM. (For further details, see the Supplementary Materials.) \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/3/3/e1601314/DC1 Supplementary Text fig. S1. Optical camera images of the wearable diabetes patch. \nfig. S2. Device fabrication process. \nfig. S3. Schematic illustration of the operation sequence of the diabetes treatment system. \nfig. S4. Electrochemical analysis of the planar and porous gold electrode. \nfig. S5. Drug delivery from microneedles with integrated heaters. \nfig. S6. Effect of the sweat control layers and miniaturization of the glucose sensor. \nfig. S7. Characterization of the glucose sensor. \nfig. S8. Characterization of the pH sensor. \nfig. S9. Skin temperature and characterization of chlorpropamide-loaded PCNs. \nfig. S10. Characterization of hyaluronic acid, DOPA-conjugated hyaluronic acid. \nfig. S11. Characterization of the PCNs. \nfig. S12. Fabrication process of the microneedles. \nfig. S13. Characterization of the heater and temperature sensor and their cooperation. \nfig. S14. Portable electrochemical analyzer for the wearable diabetes patch. \nfig. S15. Reliability of the wearable diabetes patch under variable skin temperature and multiple reuses. \nfig. S16. Sweat uptake and calibration of the disposable strip-type sensors. \nfig. S17. Human sweat analysis. \nfig. S18. Feedback microneedle therapy. \n\n# REFERENCES AND NOTES \n\n1. D. R. Whiting, L. Guariguata, C. Weil, J. Shaw, IDF diabetes atlas: Global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res. Clin. Pract. 94, 311–321 (2011). \n2. The Diabetes Control and Complications Trial Research Group, The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N. Engl. J. Med. 329, 977–986 (1993). \n3. A. J. Bandodkar, W. Jia, C. Yardimci, X. Wang, J. Ramirez, J. Wang, Tattoo-based noninvasive glucose monitoring: A proof-of-concept study. Anal. Chem. 87, 394–398 (2015). \n4. W. Gao, S. Emaminejad, H. Y. Nyein, S. Challa, K. Chen, A. Peck, H. M. Fahad, H. Ota, H. Shiraki, D. Kiriya, D.-H. Lien, G. A. Brooks, R. W. Davis, A. Javey, Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529, 509–514 (2016). \n5. H. Lee, T. K. Choi, Y. B. Lee, H. R. Cho, R. Ghaffari, L. Wang, H. J. Choi, T. D. Chung, N. Lu, T. Hyeon, S. H. Choi, D.-H. Kim, A graphene-based electrochemical device with 11, 566–572 (2016). \n6. O. Veiseh, R. Langer, Diabetes: A smart insulin patch. Nature 524, 39–40 (2015). \n7. J. Yu, Y. Zhang, Y. Ye, R. DiSanto, W. Sun, D. Ranson, F. S. Ligler, J. B. Buse, Z. Gu, Microneedle-array patches loaded with hypoxia-sensitive vesicles provide fast glucoseresponsive insulin delivery. Proc. Natl. Acad. Sci. U.S.A. 112, 8260–8265 (2015). \n8. S. Imani, A. J. Bandodkar, A. M. V. Mohan, R. Kumar, S. Yu, J. Wang, P. P. Mercier, A wearable chemical–electrophysiological hybrid biosensing system for real-time health and fitness monitoring. Nat. Commun. 7, 11650 (2016). \n9. J. Kim, I. Jeerapan, S. Imani, T. N. Cho, A. Bandodkar, S. Cinti, P. P. Mercier, J. Wang, Noninvasive alcohol monitoring using a wearable tattoo-based iontophoretic-biosensing system. ACS Sens. 1, 1011–1019 (2016). \n10. H. Y. Y. Nyein, W. Gao, Z. Shahpar, S. Emaminejad, S. Challa, K. Chen, H. M. Fahad, L.-C. Tai, H. Ota, R. W. Davis, A. Javey, A wearable electrochemical platform for noninvasive simultaneous monitoring of ${\\mathsf{C a}}^{2+}$ and pH. ACS Nano 10, 7216–7224 (2016). \n11. W. Gao, H. Y. Y. Nyein, Z. Shahpar, H. M. Fahad, K. Chen, S. Emaminejad, Y. Gao, L.-C. Tai, H. Ota, E. Wu, J. Bullock, Y. Zeng, D.-H. Lien, A. Javey, Wearable microsensor array for multiplexed heavy metal monitoring of body fluids. ACS Sens. 1, 866–874 (2016). \n12. J. Moyer, D. Wilson, I. Finkelshtein, B. Wong, R. Potts, Correlation between sweat glucose and blood glucose in subjects with diabetes. Diabetes Technol. Ther. 14, 398–402 (2012). \n13. K. Sakaguchi, Y. Hirota, N. Hashimoto, W. Ogawa, T. Hamaguchi, T. Matsuo, J.-I. Miyagawa, M. Namba, T. Sato, S. Okada, Evaluation of a minimally invasive system for measuring glucose area under the curve during oral glucose tolerance tests: Usefulness of sweat monitoring for precise measurement. J. Diabetes Sci. Technol. 7, 678–688 (2013). \n14. S. K. Vashist, Non-invasive glucose monitoring technology in diabetes management: A review. Anal. Chim. Acta 750, 16–27 (2012). \n15. M. J. Tierney, H. L. Kim, M. D. Burns, J. A. Tamada, R. O. Potts, Electroanalysis of glucose in transcutaneously extracted samples. Electroanalysis 12, 666–671 (2000). \n16. M. Kaltenbrunner, T. Sekitani, J. Reeder, T. Yokota, K. Kuribara, T. Tokuhara, M. Drack, R. Schwödiauer, I. Graz, S. Bauer-Gogonea, S. Bauer, T. Someya, An ultra-lightweight design for imperceptible plastic electronics. Nature 499, 458–463 (2013). \n17. T. Sekitani, U. Zschieschang, H. Klauk, T. Someya, Flexible organic transistors and circuits with extreme bending stability. Nat. Mater. 9, 1015–1022 (2010). \n18. J. Kim, D. Son, M. Lee, C. Song, J.-K. Song, J. H. Koo, D. J. Lee, H. J. Shim, J. H. Kim, M. Lee, T. Hyeon, D.-H. Kim, A wearable multiplexed silicon nonvolatile memory array using nanocrystal charge confinement. Sci. Adv. 2, e1501101 (2016). \n19. D.-H. Kim, N. Lu, R. Ma, Y.-S. Kim, R.-H. Kim, S. Wang, J. Wu, S. M. Won, H. Tao, A. Islam, K. J. Yu, T.-i. Kim, R. Chowdhury, M. Ying, L. Xu, M. Li, H.-J. Chung, H. Keum, M. McCormick, P. Liu, Y.-W. Zhang, F. G. Omenetto, Y. Huang, T. Coleman, J. A. Rogers, Epidermal electronics. Science 333, 838–843 (2011). \n20. K.-I. Jang, H. U. Chung, S. Xu, C. H. Lee, H. Luan, J. Jeong, H. Cheng, G.-T. Kim, S. Y. Han, J. W. Lee, J. Kim, M. Cho, F. Miao, Y. Yang, H. N. Jung, M. Flavin, H. Liu, G. W. Kong, K. J. Yu, S. I. Rhee, J. Chung, B. Kim, J. W. Kwak, M. H. Yun, J. Y. Kim, Y. M. Song, U. Paik, Y. Zhang, Y. Huang, J. A. Rogers, Soft network composite materials with deterministic and bio-inspired designs. Nat. Commun. 6, 6566 (2015). \n21. D. Son, J. Lee, S. Qiao, R. Ghaffari, J. Kim, J. E. Lee, C. Song, S. J. Kim, D. J. Lee, S. W. Jun, S. Yang, M. Park, J. Shin, K. Do, M. Lee, K. Kang, C. S. Hwang, N. Lu, T. Hyeon, D.-H. Kim, Multifunctional wearable devices for diagnosis and therapy of movement disorders. Nat. Nanotechnol. 9, 397–404 (2014). \n22. J. Kim, M. Lee, H. J. Shim, R. Ghaffari, H. R. Cho, D. Son, Y. H. Jung, M. Soh, C. Choi, S. Jung, K. Chu, D. Jeon, S.-T. Lee, J. H. Kim, S. H. Choi, T. Hyeon, D.-H. Kim, Stretchable silicon nanoribbon electronics for skin prosthesis. Nat. Commun. 5, 5747 (2014). \n23. M. R. Prausnitz, R. Langer, Transdermal drug delivery. Nat. Biotechnol. 26, 1261–1268 (2008). \n24. UK Prospective Diabetes Study (UKPDS) Group, Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). Lancet 352, 854–865 (1998). \n25. M. Zhang, C. Liao, C. H. Mak, P. You, C. L. Mak, F. Yan, Highly sensitive glucose sensors based on enzyme-modified whole-graphene solution-gated transistors. Sci. Rep. 5, 8311 (2015). \n26. Y. Zhang, Y. Hu, G. S. Wilson, D. Moatti-Sirat, V. Poitout, G. Reach, Elimination of the acetaminophen interference in an implantable glucose sensor. Anal. Chem. 66, 1183–1188 (1994). \n27. Z. Niu, L. Liu, L. Zhang, Q. Shao, W. Zhou, X. Chen, S. Xie, A universal strategy to prepare functional porous graphene hybrid architectures. Adv. Mater. 26, 3681–3687 (2014). \n28. W. Wang, S. You, X. Gong, D. Qi, B. K. Chandran, L. Bi, F. Cui, X. Chen, Bioinspired nanosucker array for enhancing bioelectricity generation in microbial fuel cells. Adv. Mater. 28, 270–275 (2016). \n29. L. Pan, G. Yu, D. Zhai, H. R. Lee, W. Zhao, N. Liu, H. Wang, B. C.-K. Tee, Y. Shi, Y. Cui, Z. Bao, Hierarchical nanostructured conducting polymer hydrogel with high electrochemical activity. Proc. Natl. Acad. Sci. U.S.A. 109, 9287–9292 (2012). \n30. J. C. Claussen, A. Kumar, D. B. Jaroch, M. H. Khawaja, A. B. Hibbard, D. M. Porterfield, T. S. Fisher, Nanostructuring platinum nanoparticles on multilayered graphene petal nanosheets for electrochemical biosensing. Adv. Funct. Mater. 22, 3399–3405 (2012). \n31. A. Singh, M. Corvelli, S. A. Unterman, K. A. Wepasnick, P. McDonnell, J. H. Elisseeff, Enhanced lubrication on tissue and biomaterial surfaces through peptide-mediated binding of hyaluronic acid. Nat. Mater. 13, 988–995 (2014). \n32. S. Y. Yang, E. D. O’Cearbhaill, G. C. Sisk, K. M. Park, W. K. Cho, M. Villiger, B. E. Bouma, B. Pomahac, J. M. Karp, A bio-inspired swellable microneedle adhesive for mechanical interlocking with tissue. Nat. Commun. 4, 1702 (2013). \n33. X. Huang, Y. Liu, K. Chen, W.-J. Shin, C.-J. Lu, G.-W. Kong, D. Patnaik, S.-H. Lee, J. F. Cortes, J. A. Rogers, Stretchable, wireless sensors and functional substrates for epidermal characterization of sweat. Small 10, 3083–3090 (2014). \n34. D. P. Rose, M. E. Ratterman, D. K. Griffin, L. Hou, N. Kelley-Loughnane, R. R. Naik, J. A. Hagen, I. Papautsky, J. C. Heikenfeld, Adhesive RFID sensor patch for monitoring of sweat electrolytes. IEEE Trans. Biomed. Eng. 62, 1457–1465 (2015). \n35. C. J. Harvey, R. F. LeBouf, A. B. Stefaniak, Formulation and stability of a novel artificial human sweat under conditions of storage and use. Toxicol. In Vitro 24, 1790–1796 (2010). \n36. D. S. Young, D. W. Thomas, R. B. Friedman, L. C. Pestaner, Effects of drugs on clinical laboratory tests (AACC Press, ed.4, 1995). pp. 374–391. \n37. Z. Tang, X. Du, F. R. Louie, J. G. Kost, Effects of drugs on glucose measurements with handheld glucose meters and a portable glucose analyzer. Am. J. Clin. Pathol. 113, 75–86 (2000). \n38. J. A. Hirst, A. J. Farmer, R. Ali, N. W. Roberts, R. J. Stevens, Quantifying the effect of metformin treatment and dose on glycemic control. Diabetes Care 35, 446–454 (2012). \n39. G. D. Moon, S.-W. Choi, X. Cai, W. Li, E. C. Cho, U. Jeong, L. V. Wang, Y. Xia, A new theranostic system based on gold nanocages and phase-change materials with unique features for photoacoustic imaging and controlled release. J. Am. Chem. Soc. 133, 4762–4765 (2011). \n40. M. R. Prausnitz, Microneedles for transdermal drug delivery. Adv. Drug Deliv. Rev. 56, 581–587 (2004). \n41. K. Nakamura, S. F. Morrison, A thermosensory pathway that controls body temperature. Nat. Neurosci. 11, 62–71 (2008). \n42. N. C. Sambol, J. Chiang, M. O’Conner, C. Y. Liu, E. T. Lin, A. M. Goodman, L. Z. Benet, J. H. Karam, Pharmacokinetics and pharmacodynamics of metformin in healthy subjects and patients with noninsulin-dependent diabetes mellitus. J. Clin. Pharmacol. 36, 1012–1021 (1996). \n\nAcknowledgments: All animal procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of the Biomedical Research Institute of Seoul National University Hospital. All experiments were performed according to IACUC guidelines. The human sweat study was performed in compliance with the protocol approved by the institutional review board at the Seoul National University (IRB No. 1605/003-002). Funding: This work was supported by IBS-R006-D1. Author contributions: H.L., C.S., T.H., and D.-H.K. designed the experiments. H.L., C.S., Y.S.H., M.S.K., H.R.C., T.K., K.S., S.H.C., T.H., and D.-H.K. performed the experiments and analysis. H.L., C.S., T.H., and D.-H.K. wrote the paper. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 10 June 2016 \nAccepted 2 February 2017 \nPublished 8 March 2017 \n10.1126/sciadv.1601314 \n\nCitation: H. Lee, C. Song, Y. S. Hong, M. S. Kim, H. R. Cho, T. Kang, K. Shin, S. H. Choi, T. Hyeon, D.-H. Kim, Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module. Sci. Adv. 3, e1601314 (2017). \n\n# ScienceAdvances \n\n# Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module \n\nHyunjae Lee, Changyeong Song, Yong Seok Hong, Min Sung Kim, Hye Rim Cho, Taegyu Kang, Kwangsoo Shin, Seung Hong Choi, Taeghwan Hyeon and Dae-Hyeong Kim \n\nSci Adv 3 (3), e1601314. DOI: 10.1126/sciadv.1601314 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nhttp://advances.sciencemag.org/content/suppl/2017/03/06/3.3.e1601314.DC1 \n\nREFERENCES \n\nThis article cites 41 articles, 5 of which you can access for free http://advances.sciencemag.org/content/3/3/e1601314#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_nature23011", + "DOI": "10.1038/nature23011", + "DOI Link": "http://dx.doi.org/10.1038/nature23011", + "Relative Dir Path": "mds/10.1038_nature23011", + "Article Title": "Neuromorphic computing with nulloscale spintronic oscillators", + "Authors": "Torrejon, J; Riou, M; Araujo, FA; Tsunegi, S; Khalsa, G; Querlioz, D; Bortolotti, P; Cros, V; Yakushiji, K; Fukushima, A; Kubota, H; Uasa, SY; Stiles, MD; Grollier, J", + "Source Title": "NATURE", + "Abstract": "Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information(1). Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nulloscale nonlinear oscillators. A simple estimation indicates that to fit 10(8) oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nulloscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals(2-5) and several candidates, including memristive(6) and superconducting(7) oscillators, a proof of concept of neuromorphic computing using nulloscale oscillators has yet to be demonstrated. Here we show experimentally that a nulloscale spintronic oscillator (a magnetic tunnel junction)(8,9) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.", + "Times Cited, WoS Core": 983, + "Times Cited, All Databases": 1044, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000406358300030", + "Markdown": "# Neuromorphic computing with nanoscale spintronic oscillators \n\nJacob Torrejon1, Mathieu Riou1, Flavio Abreu Araujo1, Sumito Tsunegi2, Guru Khalsa3†, Damien Querlioz4, Paolo Bortolotti1, Vincent Cros1, Kay Yakushiji2, Akio Fukushima2, Hitoshi Kubota2, Shinji Yuasa2, Mark D. Stiles3 & Julie Grollier1 \n\nNeurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information1. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit $\\mathbf{10^{8}}$ oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals2–5 and several candidates, including memristive6 and superconducting7 oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction)8,9 can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators. \n\nNanoscale spintronic oscillators (or spin-torque nano-oscillators) are nanoscale pillars composed of two ferromagnetic layers separated by a non-magnetic spacer (Fig. 1a). Charge currents become spinpolarized when they flow through these junctions and generate torques on the magnetizations10,11 that lead to sustained magnetization precession at frequencies of hundreds of megahertz to several tens of gigahertz. Magnetization oscillations are converted into voltage oscillations through magneto-resistance. The resulting radio-frequency oscillations, of up to tens of millivolts (ref. 12), can be detected by measuring voltage amplitude that results when an input signal of $V_{\\mathrm{in}}{=}\\pm250\\mathrm{mV}$ is injected (here for $I_{\\mathrm{DC}}{=}6.5\\mathrm{mA}$ (vertical dotted line) and $\\mu_{0}H=430\\mathrm{mT}$ ). d, Schematic of the experimental set-up. A d.c. current $I_{\\mathrm{DC}}$ and a rapidly varying waveform that encodes the input $V_{\\mathrm{in}}$ are injected into the spintorque nano-oscillator. The microwave voltage $V_{\\mathrm{osc}}$ emitted by the oscillator in response to the excitation is measured with an oscilloscope. For computing, the amplitude $\\widetilde{V}$ of the oscillator is used, and measured directly with a microwave diode. e, Input $V_{\\mathrm{in}}$ (top; magenta) and measured microwave voltage $V_{\\mathrm{osc}}$ (bottom; grey) emitted by the oscillator as a function of time. Here $I_{\\mathrm{DC}}{=}6\\mathrm{mA}$ and $\\mu_{0}H{=}430\\mathrm{mT}$ . The envelope $\\widetilde{V}$ of the oscillator signal is highlighted in blue. For computing it is sampled periodically, as shown by the blue circles labelled $V_{1-7}$ . \n\n![](images/6a2a9cad7e91fb417e3a74864f92dd1327139b4f2156c4831a900b34307311cc.jpg) \nTime, t (μs) \nFigure 1 | Spin-torque nano-oscillator for neuromorphic computing. a, Schematic of a spin-torque nano-oscillator, consisting of a non-magnetic spacer (gold) between two ferromagnetic layers, with magnetization $m$ for the free layer (blue) and $M$ for the fixed layer (silver). A current injected into the oscillator induces magnetization precessions of $m$ For our experiments we used a nano-oscillator with a diameter of $375\\mathrm{nm}$ ; however, diameters of $10{-}500\\mathrm{nm}$ are possible. b, Measured a.c. voltage emitted by the oscillator as a function of time, $V_{\\mathrm{{osc}}}=\\widetilde{V}(t)\\mathrm{{cos}}(\\omega t+\\varphi)$ , for a steady current injection of $7\\mathrm{mA}$ at an external magnetic field $\\mu_{0}H=430\\mathrm{mT}$ . The dotted blue lines highlight the amplitude $\\widetilde{V}$ . c, Voltage amplitude $\\widetilde{V}$ as a function of d.c. current $I_{\\mathrm{DC}}$ at $\\mu_{0}H=430\\mathrm{mT}$ (blue squares). The purple shaded area highlights the typical excursion in the \n\n![](images/3fa8d9edfe4f2e5098f27927c1db483dc8d40da5efb441dae14199121ba6fe41.jpg) \nFigure 2 | Spoken-digit recognition. a–d, Principle of the experiment. a, Audio waveform corresponding to the digit 1 pronounced by speaker 1. b, Filtering to frequency channels for acoustic feature extraction. The audio waveform is divided in intervals of duration $\\tau$ The cochlear model filters each interval into 78 frequency channels (65 for the spectrogram model), which are then concatenated as 78 (65) values for each interval, to form the filtered input. c, Pre-processed input (transformed from the purple shaded region in $\\mathbf{b}$ ). The filtered input is multiplied by a randomly filled binary matrix (masking process), resulting in 400 points separated by a time step $\\theta$ of 100 ns in each interval of duration $\\tau\\left(\\tau=400\\theta\\right)$ ). d, Oscillator output. The envelope $\\widetilde V(t)$ of the emitted voltage amplitude of the experimental oscillator is shown $\\begin{array}{r}{{\\bf\\nabla}_{\\mu_{0}H=430\\mathrm{mT}},}\\end{array}$ $I_{\\mathrm{DC}}{=}6\\mathrm{mA}$ ). The 400 values of $\\widetilde V(t)$ per interval $\\tau$ ( ${\\widetilde{V}}_{i},$ , sampled with a time step $\\theta$ ) emulate 400 neurons. The reconstructed output $^{\\mathfrak{s}}1^{:}$ , corresponding to this digit, is \n\nthe voltage across the junction (Fig. 1b). Spin-torque nano-oscillators are therefore simple and ultra-compact: their lateral size can be scaled down to $10\\mathrm{nm}$ and their power consumption reduced to $1\\upmu\\mathrm{W}$ (ref. 13). Because they have the same structure as present-day magnetic memory cells, they are compatible with complementary metal–oxide– semiconductor (CMOS) technology, have high endurance, operate at room temperature and can be fabricated in large numbers (currently up to hundreds of millions) on a single chip14. Just as the frequency of a neuron is modified by the spikes received from other neurons, the frequencies of spin-torque nano-oscillators are highly sensitive to the magnetization dynamics of neighbouring oscillators to which they are coupled15,16. Together, these features of spin-torque nano-oscillators make them promising candidates for use in neuromorphic computing with large arrays of coupled oscillators17–21. However, they have yet to be used to perform an actual computing task. \n\nOur idea is to exploit the amplitude dynamics of spin-torque nano-oscillators for neuromorphic computing. Their oscillation amplitude $\\tilde{V}$ (dotted blue line in Fig. 1b) is robust to noise, owing to the confinement that is provided by the counteracting torques exerted by the injected current and magnetic damping22. In addition, $\\tilde{V}$ is highly nonlinear as a function of the injected current and depends intrinsically on past inputs15. Exploiting the amplitude dynamics of spin-torque nano-oscillators thus combines in one single nanodevice the two most crucial properties of neurons—nonlinearity and memory—the obtained by linearly combining the 400 values of $\\widetilde{V_{i}}$ , sampled from each interval $\\tau$ . e, f, Spoken-digit recognition rates in the testing set as a function of the number of utterances $N$ used for training for the spectrogram filtering (e; $\\mu_{0}H=430\\mathrm{mT}$ , $I_{\\mathrm{DC}}{=}6\\mathrm{mA}$ ) and for the cochlear filtering (f; $\\mu_{0}H=448\\mathrm{mT}$ $I_{\\mathrm{DC}}{=}7\\mathrm{mA}$ ). Because there are many ways to pick the $N$ utterances, the recognition rate is an average over all $10!/[(10-N)!N!]$ combinations of $N$ utterances out of the 10 in the dataset. The red curves are the experimental results using the magnetic oscillator. The black curves are control trials, in which the pre-processed inputs are used for reconstructing the output on a computer directly, as described in Methods, without going through the experimental set-up. The error bars correspond to the standard deviation of the recognition rate, based on training with all possible combinations. \n\nrealization of which would otherwise require several electronics components and a much larger on-chip area using conventional $\\mathrm{CMOS}^{23}$ . To compute, we encode neural inputs in the time-dependent current $I(t)$ that is injected into the oscillator and use the amplitude response $\\widetilde V(t)$ as the neural output. \n\nOur nano-oscillators consist of circular magnetic tunnel junctions, with a 6-nm-thick free layer of FeB of $375\\mathrm{-nm}$ diameter, which have magnetic vortex ground states (see Methods). We measure the dynamics of the signal amplitude $\\widetilde V(t)$ directly using a microwave diode. In Fig. 1c we show the nonlinear response of the amplitude $\\widetilde{V}$ to a d.c. current $I_{\\mathrm{DC}}colon\\tilde{V}\\propto\\sqrt{(I_{\\mathrm{DC}}-I_{\\mathrm{th}})}$ , where $I_{\\mathrm{th}}$ is the current threshold for steady oscillations to occur15. Using an arbitrary waveform generator, we inject a varying current though the junctions in addition to the d.c. current, using the set-up schematized in Fig. 1d. The resulting voltage oscillations, recorded with an oscilloscope, are shown in Fig. 1e. The amplitude of the oscillator varies in response to the injected d.c. current, with a relaxation time that induces a few hundred nanoseconds memory of past inputs22. \n\nRecent studies have revealed that time-multiplexing can enable a single oscillator to emulate a full neural network24–26. Here we use this approach—a form of “reservoir computing”4,5 (see Methods)— to demonstrate the ability of spin-torque nano-oscillators to realize neuromorphic tasks. We perform a benchmark task of spoken-digit recognition. The input data, taken from the TI-46 database27, are audio waveforms of isolated spoken digits (0 to 9) pronounced by five different female speakers (Fig. 2a). The goal is to recognize the digits, independent of the speaker. \n\n![](images/e099345ecbf33d78e90651320ffdaf4f7077c0b15acd146859dae1eb1c7172b6.jpg) \nFigure 3 | Conditions for optimal waveform classification and identification of important oscillator properties. The task consists of recognizing sine waveforms from square ones with the same period. The target for the output that is reconstructed from the oscillator’s response is one for square, zero for sine. We emulate 24 neurons ${\\widetilde{V}}_{i},$ , $\\tau=24\\theta$ . a, Rootmean-square (r.m.s.) deviation of output-to-target deviations: map as a function of d.c. current $I_{\\mathrm{DC}}$ and magnetic field $\\mu_{0}H$ . b, Extraction of parameters from the time traces of the oscillator’s response. Top, maximum positive $(V_{\\mathrm{up}})$ and negative $\\ensuremath{(V_{\\mathrm{dw}})}$ variations in the oscillator’s amplitude in response to the varying pre-processed input. Bottom, noise \n$\\Delta V$ of the voltage amplitude $\\widetilde{V}$ at steady state under $I_{\\mathrm{DC}}$ . c, Maximal response $(\\ensuremath{V_{\\mathrm{up}}}\\ensuremath{V_{\\mathrm{dw}}})$ of the oscillator to the input: map in the $I_{\\mathrm{DC}^{-}}\\mu_{0}H$ plane. d, Inverse of the noise amplitude $1/\\Delta V;$ map in the $I_{\\mathrm{DC}^{-}}\\mu_{0}H$ plane. The threshold current $I_{\\mathrm{th}}$ is indicated by a white solid line. In c and d, the optimal range of bias conditions for waveform classification is marked by a white dashed rectangle (currents of $6{-}7\\mathrm{mA}$ and magnetic fields of $350{\\mathrm{-}}450\\mathrm{mT}$ ). e, Map of the ratio of maximal amplitudes to noise $V_{\\mathrm{up}}V_{\\mathrm{dw}}/\\Delta V;$ showing that these parameters largely determine the performance of the oscillator (compare with a). \n\nNeural networks classify information through chain reactions: neuron after neuron, each input undergoes a series of nonlinear transformations28. In a trained network, the same digit always triggers a similar chain reaction even if it is pronounced by different speakers, whereas different digits generate different chain reactions, thus allowing pattern recognition. An input can trigger a chain reaction in space by using ensembles of neurons, wherein the state of downstream neurons depends on the state of upstream neurons. But an input can also trigger a chain reaction in time by constantly exciting a single nonlinear oscillator with memory: in this case, the state of the oscillator in the future depends on the state of the oscillator in the past. We use the latter approach, which simplifies the hardware because only one oscillator is needed, but requires preprocessing of the input: each point of the audio waveform is converted into a fast-paced binary sequence that is designed to generate a chain reaction of amplitude variations in the oscillator24. \n\nThe procedure is illustrated in Fig. 2a–d and detailed in Methods. Because acoustic features are mainly encoded in frequencies29, we filter each audio file into $N_{f}$ different frequency channels (a standard procedure in speech recognition), which are then concatenated in intervals of duration $\\tau$ (Fig. 2b). For preprocessing, each of these segments is multiplied by a randomly filled binary matrix (of dimension $N_{f}\\times N_{\\theta})$ . In this way, each point of the input audio waveform is converted into a binary sequence of duration $\\tau$ that is composed of $N_{\\theta}$ points separated by a time step $\\theta$ $\\left(\\tau=N_{\\theta}\\theta\\right),$ . When this preprocessed input (Fig. 2c) is applied as a current to our spin-torque nano-oscillator, the resulting amplitude variations $\\widetilde V(t)$ (Fig. 2d) function as a set of $N_{\\theta}$ neurons coupled in time (we take $N_{\\theta}$ samples $\\widetilde{V}_{i}$ per interval $\\tau$ ). For spoken-digit recognition, we emulate $N_{\\theta}=400$ neurons and use $\\scriptstyle\\theta=100$ ns (about one-fifth of the relaxation time of the oscillators) to set the oscillator in a transient state. \n\nThe responses of the voltage amplitude $\\widetilde V(t)$ of the oscillator are recorded for each utterance of each spoken digit. The goal of the subsequent training process, performed on a computer, is to choose a linear combination of these responses (sets of $\\tilde{\\bar{V_{i}}}$ in each $\\tau$ ) for each digit such that the sum is one for that digit and zero for the rest (see Methods). Because each digit has been pronounced ten times by each of the five speakers, we can use some of the data to determine the coefficients (training), and the rest to evaluate the recognition performance (testing); see Methods. To assess the effect of our oscillator on the quality of recognition, we always perform a control trial without the oscillator. In that case, the preprocessed input traces are used to reconstruct the outputs on the computer directly, without going through the experimental set-up. \n\nThe improvement shown in the experimental results over the control results (see Fig. 2e, f) indicates that the spin-torque nano-oscillator greatly improves the quality of spoken-digit recognition, despite the added noise that is concomitant to its nanometre-scale size. In Fig. 2e (linear spectrogram filtering), we present an example in which the extraction of acoustic features, achieved by Fourier transforming the audio waveform over finite time windows, plays a minimal part in classification. Without the oscillator (black line), the recognition rates are consistent with random choices; with the oscillator (red line), the recognition rate is improved by $70\\%$ , reaching values of up to $80\\%$ . This example highlights the crucial role of the oscillator in the recognition process. Using nonlinear cochlear filtering30 (Fig. 2f), which is the standard in reservoir computing24–26 and has been optimized on the basis of the behaviour of biological ears, we achieve recognition rates of up to $99.6\\%$ , as high as the state-of-the-art. Compared to the control trial, the oscillator reduces the error rate by a factor of up to 15. Our results with a spin-torque nano-oscillator are therefore comparable to the recognition rates obtained with more complicated electronic or optical systems (between $95.7\\%$ and $99.8\\%$ for the same task with cochlear filtering)23–26,29. \n\nThe optimal operating conditions for pattern recognition with our spin-torque nano-oscillator are determined by the oscillation amplitude and noise. We use a simpler task, classification of sine and square waveforms with the same period25, to investigate the ability of the oscillator to classify waveforms in a wide range of injected d.c. currents $I_{\\mathrm{DC}}$ and applied magnetic fields $\\mu_{0}H$ (see Methods). As can be seen in Fig. 3a, the quality of pattern recognition, characterized by the root-meansquare of deviations between the reconstructed output and the target, varies from $10\\%$ to more than $30\\%$ depending on the bias conditions. The oscillator performs well when it responds strongly to the timevarying preprocessed input, with large amplitude variations in both the positive and negative directions, $V_{\\mathrm{up}}$ and $V_{\\mathrm{dw}}$ respectively (Fig. 3b, top). On the other hand, it performs poorly when the noise in the oscillator $\\Delta V$ (the standard deviation of the noise in the voltage amplitude) is high (Fig. 3b, bottom). As shown in Fig. 3b, we extract these parameters from the time traces of the voltage emitted from the oscillator at each bias point, and plot $V_{\\mathrm{up}}V_{\\mathrm{dw}}$ (Fig. 3c) and $1/\\Delta V$ (Fig. 3d) as a function of the d.c. current $I_{\\mathrm{DC}}$ and field $\\mu_{0}H$ . The red regions of large oscillation amplitudes in Fig. 3c correspond to low magnetic fields, in which the magnetization is weakly confined, and to high currents, for which the spin torque on magnetization is maximal. The blue regions of high noise in Fig. 3d correspond to areas just above the threshold current $I_{\\mathrm{th}}$ for oscillation, in which the oscillation amplitude $\\tilde{V}$ is growing rapidly as a function of current and is becoming sensitive to external fluctuations15. As can be seen by comparing Fig. 3c and d, the range of bias conditions highlighted by the dotted white boxes (currents of $6{-}7\\mathrm{mA}$ and magnetic fields of $350{-}450\\mathrm{mT}$ ) features wide variations in oscillation amplitudes and low noise. In this region, root-mean-square deviations below $15\\%$ are achieved, and there are no classification errors between sine and square waveforms. The similarity between the map of $V_{\\mathrm{up}}V_{\\mathrm{dw}}/\\Delta V$ (Fig. 3e) and that of the classification performance (Fig. 3a) confirms that the best conditions for classification correspond to regions of optimal compromise between low noise and large amplitude variations. The necessity of a high signal-to-noise ratio for efficient neuromorphic computing, highlighted here for magnetic oscillators, is a general guideline that applies to any type of nanoscale oscillator. \n\nAs a conclusion, our pattern-recognition results show that simple, ultra-compact spintronic oscillators have all of the properties that are needed to emulate collections of neurons: nonlinearity, memory and stability. The ability of groups of these oscillators to mimic neural connections by influencing the behaviour of one another through current and magnetic-field coupling opens up a route to realizing large-scale neural networks in hardware, which exploit magnetization dynamics for computing15–21. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# received 25 January; accepted 2 June 2017. \n\n1. Buzsaki, G. Rhythms of the Brain (Oxford Univ. Press, 2011). \n2. Hoppensteadt, F. C. & Izhikevich, E. M. Oscillatory neurocomputers with dynamic connectivity. Phys. Rev. Lett. 82, 2983–2986 (1999). \n3. Aonishi, T., Kurata, K. & Okada, M. Statistical mechanics of an oscillator associative memory with scattered natural frequencies. Phys. Rev. Lett. 82, 2800–2803 (1998). \n4. Jaeger, H. & Haas, H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science 304, 78–80 (2004). \n5. Maass, W., Natschläger, T. & Markram, H. Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput. 14, 2531–2560 (2002). \n6. Pickett, M. D., Medeiros-Ribeiro, G. & Williams, R. S. A scalable neuristor built with Mott memristors. Nat. Mater. 12, 114–117 (2013). \n7. Segall, K. et al. Synchronization dynamics on the picosecond time scale in coupled Josephson junction neurons. Phys. Rev. E 95, 032220 (2017). \n8. Kiselev, S. I. et al. Microwave oscillations of a nanomagnet driven by a spin-polarized current. Nature 425, 380–383 (2003). \n9. Rippard, W. H., Pufall, M. R., Kaka, S., Russek, S. E. & Silva, T. J. Direct-current induced dynamics in $\\mathsf{C o}_{90}\\mathsf{F e}_{10}/\\mathsf{N i}_{80}\\mathsf{F e}_{20}$ point contacts. Phys. Rev. Lett. 92, 027201 (2004). \n10.\t Slonczewski, J. C. Current-driven excitation of magnetic multilayers. J. Magn. Magn. Mater. 159, L1–L7 (1996). \n11.\t Berger, L. Emission of spin waves by a magnetic multilayer traversed by a current. Phys. Rev. B 54, 9353–9358 (1996). \n12.\t Tsunegi, S., Yakushiji, K., Fukushima, A., Yuasa, S. & Kubota, H. Microwave emission power exceeding $10\\upmu\\mathsf{W}$ in spin torque vortex oscillator. Appl. Phys. Lett. 109, 252402 (2016). \n13.\t Sato, H. et al. Properties of magnetic tunnel junctions with a MgO/CoFeB/Ta/ CoFeB/MgO recording structure down to junction diameter of 11 nm. Appl. Phys. Lett. 105, 062403 (2014). \n14.\t Apalkov, D., Dieny, B. & Slaughter, J. M. Magnetoresistive random access memory. Proc. IEEE 104, 1796–1830 (2016). \n15.\t Slavin, A. & Tiberkevich, V. Nonlinear auto-oscillator theory of microwave generation by spin-polarized current. IEEE Trans. Magn. 45, 1875–1918 (2009). \n16.\t Houshang, A. et al. Spin-wave-beam driven synchronization of nanocontact spin-torque oscillators. Nat. Nanotechnol. 11, 280–286 (2016). \n17.\t Macià, F., Kent, A. D. & Hoppensteadt, F. C. Spin-wave interference patterns created by spin-torque nano-oscillators for memory and computation. Nanotechnology 22, 095301 (2011). \n18.\t Pufall, M. R. et al. Physical implementation of coherently coupled oscillator networks. IEEE J. Explor. Solid-State Comput. Devices Circuits 1, 76–84 (2015). \n19.\t Nikonov, D. E. et al. Coupled-oscillator associative memory array operation for pattern recognition. IEEE J. Explor. Solid-State Comput. Devices Circuits 1, 85–93 (2015). \n20.\t Yogendra, K., Fan, D. & Roy, K. Coupled spin torque nano oscillators for low power neural computation. IEEE Trans. Magn. 51, 4003909 (2015). \n21.\t Grollier, J., Querlioz, D. & Stiles, M. D. Spintronic nanodevices for bioinspired computing. Proc. IEEE 104, 2024–2039 (2016). \n22.\t Grimaldi, E. et al. Response to noise of a vortex based spin transfer nanooscillator. Phys. Rev. B 89, 104404 (2014). \n23.\t Soriano, M. C. et al. Delay-based reservoir computing: noise effects in a combined analog and digital implementation. IEEE Trans. Neural Netw. Learn. Syst. 26, 388–393 (2015). \n24.\t Appeltant, L. et al. Information processing using a single dynamical node as complex system. Nat. Commun. 2, 468 (2011). \n25.\t Paquot, Y. et al. Optoelectronic reservoir computing. Sci. Rep. 2, 287 (2012). \n26.\t Martinenghi, R., Rybalko, S., Jacquot, M., Chembo, Y. K. & Larger, L. Photonic nonlinear transient computing with multiple-delay wavelength dynamics. Phys. Rev. Lett. 108, 244101 (2012). \n27.\t Texas Instruments. 46-Word Speaker-Dependent Isolated Word Corpus (TI-46), NIST Speech Disc 7-1.1, https://catalog.ldc.upenn.edu/LDC93S9 (NIST, 1991). \n28.\t LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015). \n29.\t Yildiz, I. B., von Kriegstein, K. & Kiebel, S. J. From birdsong to human speech recognition: Bayesian inference on a hierarchy of nonlinear dynamical systems. PLOS Comput. Biol. 9, e1003219 (2013). \n30.\t Lyon, R. A computational model of filtering, detection, and compression in the cochlea. in IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP 82) Vol. 7, 1282–1285 (IEEE, 1982). \n\nAcknowledgements This work was supported by the European Research Council (ERC) under grant bioSPINspired 682955. We thank L. Larger, B. Penkovsky and F. Duport for discussions. \n\nAuthor Contributions The study was designed by J.G. and M.D.S., samples were optimized and fabricated by S.T. and K.Y., experiments were performed by J.T. and M.R., numerical studies were realized by F.A.A., M.R. and G.K., and all authors contributed to analysing the results and writing the paper. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Correspondence and requests for materials should be addressed to J.G. (julie.grollier@cnrs-thales.fr). \n\nReviewer Information Nature thanks F. Hoppensteadt and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\n# Methods \n\nSamples. Magnetic tunnel junction (MTJ) films with a stacking structure of buffer/PtMn(15) $/\\mathrm{Co_{71}F e_{29}(2.5)/R u(0.9)/C o_{60}F e_{20}B_{20}(1.6)/C o_{70}F e_{30}(0.8)/M g O(1)}_{A}$ / $\\mathrm{Fe_{80}B_{20}(6)/M g O(1)/T a(8)/R u(7)}$ (with thicknesses given in parentheses in nanometres) were prepared by ultrahigh vacuum (UHV) magnetron sputtering. After annealing at $360^{\\circ}\\mathrm{C}$ for $1\\mathrm{h}$ , the resistance–area products (RA) were approximately $3.6\\Omega\\mathrm{\\upmum}^{\\mathrm{\\tilde{2}}}$ . Circular-shape MTJs with a diameter of approximately $375\\mathrm{nm}$ were patterned using Ar ion etching and e-beam lithography. The resistance of the samples is close to $40\\Omega$ and the magneto-resistance ratio is about $135\\%$ at room temperature. The FeB layer presents a vortex structure as the ground state for the dimensions used here. In a small region called the core of the vortex, the magnetization spirals out of plane. Under d.c. current injection, the core of the vortex steadily gyrates around the centre of the dot with a frequency in the range $250{\\mathrm{-}}400{\\mathrm{MHz}}$ for the oscillators we consider here. Vortex dynamics driven by spin torque are well understood, well controlled and have been shown to be particularly stable22. \n\nMeasurement set-up. The experimental implementation for spoken-digit recognition and sine/square classification tasks is illustrated in Fig. 1d. The pre-processed input signal $V_{\\mathrm{in}}$ is generated by a high-frequency arbitrary-waveform generator and injected as a current through the magnetic nano-oscillator. The sampling rate of the source is set to ${200}\\mathrm{MHz}$ (20 points per interval of time θ) for the spoken-digit recognition task and ${500}\\mathrm{MHz}$ (50 points per interval of time θ) for the classification of sines and squares. The peak-to-peak variation in the input signal is $500\\mathrm{mV},$ which corresponds to peak-to-peak current variations of $6\\mathrm{mA}$ , as illustrated in Fig. 1c (part of the incoming signal is reflected owing to impedance mismatch). The bias conditions of the oscillator are set by a d.c. current source and an electromagnet that applies a field perpendicular to the plane of the magnetic layers. The oscillating voltage emitted by the nano-oscillator is rectified by a planar tunnel microwave diode, with a bandwidth of $0.1{-}12.4\\mathrm{GHz}$ and a response time of 5 ns. The input dynamic range of the diode is between $1\\upmu\\mathrm{W}$ and $3.15\\mathrm{mW}$ , corresponding to a d.c. output level of $0{\\mathrm{-}}400{\\mathrm{mV}}.$ We use an amplifier to adjust the emitted power of the nano-oscillator to the working range of the diode. The output signal is then recorded by a real-time oscilloscope. In Figs 1b, c, e, 2d and $3\\mathrm{b-e}$ , the amplitude of the signal emitted by the oscillator is shown without amplification (the signal measured after the diode has been divided by the total amplification of the circuit, about $+21$ dB). If, owing to sampling errors, the measured envelope of the oscillators is shifted with respect to the input, classification accuracy can be degraded. We use alignment marks to align our measurements with the input when we reconstruct the output. The alignment precision is $\\pm1$ ns. \n\nGeneral concepts of reservoir computing. In machine learning, a reservoir is a network of recurrently and randomly connected nonlinear nodes4,5. When an input signal is injected in the reservoir, it is mapped to a higher-dimensional space in which it can become linearly separable. The key insight behind reservoir computing is that the network does not need any tuning: all connections inside the reservoir are kept fixed. Only external connections (between the reservoir and an output layer) are trained to achieve the desired task. \n\nIn other words, reservoir computing requires the generation of complex nonlinear dynamics but, as a trade-off, learning is greatly simplified. For efficient reservoir computing, several requirements related to the dynamical properties of the network should be satisfied. First, different inputs should trigger different dynamics (separation property) and similar inputs should generate similar dynamics (approximation property), enabling efficient classification. Second, the reservoir state should not depend only on present inputs but also on recent past inputs. This short-term memory, called fading memory, is essential for processing temporal sequences for which the history of the signal is important. \n\nA single nonlinear oscillator can emulate a reservoir when it is set in transient dynamics by a rapidly varying input24. The loss of parallelism is compensated by an additional pre-processing input step: the input is multiplied by a rapidly varying mask, which enables virtual nodes to be defined, interconnected in time through the resultant oscillator dynamics. This approach provides a marked simplification of the reservoir scheme for hardware implementations, and has been realized in hardware with optical or electronic oscillators assembled from several components23–26. \n\nSpoken-digit recognition. For this task, the inputs are taken from the NIST TI-46 data corpus27. The input consists of isolated spoken digits said by five different female speakers. Each speaker pronounces each digit ten times. The 500 audio waveforms are sampled at a rate of $12.5\\mathrm{kHz}$ and have variable time lengths. \n\nWe used two different filtering methods: spectrogram and cochlear models. Both filters break the word into several time intervals $N_{\\tau}$ of duration $\\tau$ and analyse the frequency content in each interval $\\tau$ through either a Fourier transform (spectrogram model; 65 channels, $N_{\\tau}\\in\\{24,...,67\\}$ ; Fig. 2b) or a more complicated nonlinear approach (cochlear model; 78 channels, $N_{\\tau}{\\in}\\{14,...,41\\} $ ). The input for each word is composed of an amplitude for each of the $N_{f}{=}65$ or $N_{f}{=}78$ frequency channels times $N_{\\tau}$ time intervals. This input is pre-processed by multiplying the frequency content for each time interval by a mask matrix containing $N_{f}\\times N_{\\theta}$ random binary values, giving a total of $N_{\\tau}\\times N_{\\theta}$ values as input to the oscillator (Fig. 2c). Here, we are modelling $N_{\\theta}=400$ input neurons, each of which is connected to all of the frequency channels for each time interval. \n\nEach preprocessed input value is consecutively applied to the oscillator as a constant current for a time interval of $\\theta\\approx100\\mathrm{ns}$ , which is about five times shorter than the relaxation time of the oscillator, as recommended in ref. 24. This time is short enough to guarantee that the oscillator is maintained in its transient regime so the emulated neurons are connected to each other, but is long enough to let the oscillator respond to the input excitation. The amplitude of the a.c. voltage across the oscillator is recorded for offline post-processing (Fig. 2d). \n\nThe post-processing of the output consists of two distinct steps. The first is called the training (or learning) process and the second is called the classification (or recognition) process. The goal of training is to determine a set of weights $w_{i,\\theta},$ where i indexes the desired digit. These weights are used to multiply the output voltages to give $10N_{\\tau}$ output values, which are then averaged over the $N_{\\tau}$ time intervals to give 10 output values $y_{i},$ which should ideally be equal to the target values $\\widetilde{y}_{i}=1.0$ for the appropriate digit and 0.0 for the rest. In the training process, a fraction of the utterances are used to train these weights; the rest of the utterances are used in the classification process to test the results. \n\nThe optimum weights are found by minimizing the difference between $\\widetilde{y}_{i}$ and $y_{i}$ for all of the words used in the training. In practice, optimal values are determined by using techniques for extracting meaningful eigenvalues from singular matrices such as the linear Moore–Penrose pseudo-inverse operator (denoted by a dagger symbol †). If we consider the target matrix $\\widetilde{Y}$ , which contains the targets $\\widetilde{y}_{i}$ for all of the time steps $\\tau$ used for the training, and the response matrix S, which contains all neuron responses for all of the time steps $\\tau$ used for the training, then the matrix W, which contains the optimal weights, is given by $W=\\widetilde{Y}S^{\\dagger}$ . This step is performed on a computer and takes several seconds. In the future, real-time processing on a nanosecond timescale could be realized using fully parallel networks of interacting nano-oscillators. \n\nDuring the classification phase, the ten reconstructed outputs corresponding to one digit are averaged over all of the time steps $\\tau$ of the signal, and the digit is identified by taking the maximum value of the ten averaged reconstructed outputs. The averaged reconstructed output that corresponds to the digit in question should be close to 1 and the others should be close to 0. The efficiency of the recognition is evaluated by the word success rate, which is the rate of digits that are correctly identified. The training can be done using more or fewer data (here ‘utterances’). We always trained the system using the ten digits spoken by the five speakers. The only parameter that we changed is the number of utterances used for the training. If we use $N$ utterances for training, then we use the remaining $10-N$ utterances for testing. However, some utterances are very well pronounced whereas others are hardly distinguishable. As a consequence, the resulting recognition rate depends on which $N$ utterances are picked for training in the set of ten (for example, if $N=2$ , then the utterances picked for training could be the first and second, but also the second and third, or the sixth and tenth, or any other of the 10!/(8!2!) combinations of 2 picked out of 10). To avoid this bias, the recognition rates that we present here are the average of the results over all possible combinations. The error bars corresponds to the standard deviation of the word recognition rate. The raw spectrogram is not complex enough to allow a correct reconstruction of the target during the training. Adding the oscillator brings complexity and suppresses this phenomenon. \n\nSine- and square-wave classification. For this classification task, the input is a random sequence of 160 sines and squares with the same period—the first half of the sequence for training and the second half for classification. Each period is discretized into eight points separated by a time step $\\tau$ . The pre-processing consists of multiplying the value of each point by the same binary sequence that is generated by a random distribution of $+1$ and $^{-1}$ values. In contrast to spokendigit recognition, the mask is a binary vector (instead of a binary matrix). The fast binary sequence contains 24 values, so 24 neurons $\\widetilde{V}_{i}$ are emulated during each time step $\\tau$ \n\nThe target $\\widetilde{y}$ for the network output y is 0 for all of the trajectories in response to a sine and 1 for all of the trajectories in response to a square. The best weights are found by linear regression, as explained above for the spoken-digit recognition task. For sine/square recognition, we record five points instead of one for each neuron when we measure the output of the oscillator. During post-processing, we use these additional states between $\\widetilde{V}_{i}$ and $\\widetilde{V}_{i+1}$ to increase the number of coefficients available for solving the problem, and thus increase classification accuracy. In addition, the best performance does not necessarily correspond to a target in exact phase with the oscillator’s output. The standard deviation of the root-meansquare value of $V_{\\mathrm{output}}-V_{\\mathrm{target}},$ obtained with ten repetitions, is around $1\\%$ . \n\nData availability. The datasets generated and analysed during this study are available from the corresponding author on reasonable request. " + }, + { + "id": "10.1126_science.aah4496", + "DOI": "10.1126/science.aah4496", + "DOI Link": "http://dx.doi.org/10.1126/science.aah4496", + "Relative Dir Path": "mds/10.1126_science.aah4496", + "Article Title": "Highly stretchable polymer semiconductor films through the nulloconfinement effect", + "Authors": "Xu, J; Wang, SH; Wang, GJN; Zhu, CX; Luo, SC; Jin, LH; Gu, XD; Chen, SC; Feig, VR; To, JWF; Rondeau-Gagne, S; Park, J; Schroeder, BC; Lu, C; Oh, JY; Wang, YM; Kim, YH; Yan, H; Sinclair, R; Zhou, DS; Xue, G; Murmann, B; Linder, C; Cai, W; Tok, JBH; Chung, JW; Bao, ZN", + "Source Title": "SCIENCE", + "Abstract": "Soft and conformable wearable electronics require stretchable semiconductors, but existing ones typically sacrifice charge transport mobility to achieve stretchability. We explore a concept based on the nulloconfinement of polymers to substantially improve the stretchability of polymer semiconductors, without affecting charge transport mobility. The increased polymer chain dynamics under nulloconfinement significantly reduces the modulus of the conjugated polymer and largely delays the onset of crack formation under strain. As a result, our fabricated semiconducting film can be stretched up to 100% strain without affecting mobility, retaining values comparable to that of amorphous silicon. The fully stretchable transistors exhibit high biaxial stretchability with minimal change in on current even when poked with a sharp object. We demonstrate a skinlike finger-wearable driver for a light-emitting diode.", + "Times Cited, WoS Core": 992, + "Times Cited, All Databases": 1070, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000391739900042", + "Markdown": "# FLEXIBLE ELECTRONICS \n\n# Highly stretchable polymer semiconductor films through the nanoconfinement effect \n\nJie $\\mathbf{X}\\mathbf{u},^{\\mathbf{1}*}$ Sihong Wang,1\\* Ging-Ji Nathan Wang,1 Chenxin Zhu,2 Shaochuan Luo,3 \nLihua Jin,4,5 Xiaodan $\\mathbf{G}\\mathbf{u},^{1,6}\\dag$ Shucheng Chen,1 Vivian R. Feig,7 John W. F. To,1 \nSimon Rondeau-Gagné, $^{1\\ddag}$ Joonsuk Park,7 Bob C. Schroeder, $^{1\\S}$ Chien Lu,1 Jin Young Oh,1 \nYanming Wang,7 Yun-Hi Kim,8 He Yan,9 Robert Sinclair,7 Dongshan Zhou,3 Gi Xue,3 \nBoris Murmann,2 Christian Linder,5 Wei Cai,4 Jeffery B.-H. Tok,1 \nJong Won Chung, $\\mathbf{\\mu}^{1,10}||$ Zhenan $\\mathbf{Bao^{1}}||$ \n\nSoft and conformable wearable electronics require stretchable semiconductors, but existing ones typically sacrifice charge transport mobility to achieve stretchability. We explore a concept based on the nanoconfinement of polymers to substantially improve the stretchability of polymer semiconductors, without affecting charge transport mobility. The increased polymer chain dynamics under nanoconfinement significantly reduces the modulus of the conjugated polymer and largely delays the onset of crack formation under strain. As a result, our fabricated semiconducting film can be stretched up to $100\\%$ strain without affecting mobility, retaining values comparable to that of amorphous silicon. The fully stretchable transistors exhibit high biaxial stretchability with minimal change in on current even when poked with a sharp object. We demonstrate a skinlike finger-wearable driver for a light-emitting diode. \n\nE tamrseapcthmiynesineo as physiological monitoring ,iecerlafelactmreo(n4iic)t,sokrminusgs $(I)_{:}$ ,aenmdmpehlcuahmnatanenid$(2),$ electronic skins (3), and humanmachine interface (4), must be mechanically compatible with biological tissues, with characteristics of low modulus, flexibility, and stretchability. Several approaches based on geometric designs, such as buckles (5), wavy patterns (1, 2), and kirigami $\\textcircled{6}$ , impart stretchability to electronics and have the potential for a variety of wearable applications. Stretchable electronics based on intrinsically stretchable materials may enable scalable fabrication, higher device density, and better strain tolerance but remain scarce owing to the lack of high-performance stretchable semiconductors that possess both high mechanical ductility and high carrier mobility at large strains. Although some nanomaterial systems [such as two-dimensional (2D) materials] possess moderate stretchability (below $20\\%$ strain) with good electrical performance $(7)$ , their rigid nature has limited device density, mechanical robustness, and wide applicability. \n\nConjugated polymers have been developed as a softer semiconductor with high charge carrier mobilities rivaling that of poly-Si (8–10), but their stretchability remains poor. Molecular design rules (11–14) that are effective in improving stretchability often result in a decrease in mobility. Nanowire and nanofibril networks (15, 16) and microcracked films (17) improved strain tolerance, but the materials used were already known to be ductile (18) and had low mobilities. More recently, high-performance but brittle conjugated polymers have been afforded improved stretchability through blending with a ductile lowerperformance conjugated polymer (19). However, the films still have limited ductility due to the unchanged polymer chain packing and dynamics. \n\nNanoconfinement of polymers into nanometerscale dimensions is known to result in peculiar thermodynamic and kinetic properties due to the finite-size effect and the interface effect. Nanoconfinement can alter many polymer physical properties, including lowering the mechanical modulus (20) and glass transition temperature (21) and increasing the mechanical ductility (22). These changes have been attributed to the enhanced polymer chain dynamics in the amorphous regions (23, 24) and the restricted growth of large crystallites (25), and these are all desirable for stretchable materials. Therefore, we hypothesized that the increased polymer chain dynamics and suppressed crystallization from nanoconfinement may increase the mechanical stretchability of high-mobility, less ductile polymer semiconductors. \n\nNanoconfinement of polymer semiconductor is achieved by forming nanofibrils inside a soft, deformable elastomer (Fig. 1A). Good charge transport is maintained owing to the connectivity between the nanofibril aggregates, while their interfacing with the deformable elastomer prevents crack propagation. Possible fabrication techniques include photolithographic patterning (26), nanostructure templating (27), and phase separation (28), but only the latter method can simultaneously introduce all desirable features in one step, is more scalable, and can be achieved at low cost. We describe a conjugated-polymer/ elastomer phase separation–induced elasticity (termed CONPHINE) methodology to achieve the desired morphology. \n\nWe first investigate poly(2,5-bis(2-octyldodecyl)- 3,6-di(thiophen-2-yl)diketopyrrolo[3,4-c]pyrrole1,4-dione-alt-thieno[3,2-b]thiophen) (DPPT-TT; 1) (table S1) (29) as the high-mobility semiconducting polymer and polystyrene-block-poly(ethylene-ranbutylene)-block-polystyrene (SEBS) as the soft elastomer (Fig. 1B). Their comparable surface energies should ensure a nanoscale mixed morphology (fig. S1 and table S2). The improvement in mechanical ductility is investigated on three model films of 1: (i) thick neat film $(\\sim135\\mathrm{nm})$ ), (ii) thin neat film $(\\sim35\\ \\mathrm{nm})$ ) with the nanoconfinement effect, and (iii) thin film/SEBS bilayer film with both the nanoconfinement effect and a deformable interface (Fig. 1C). As an important parameter representing the polymer chain dynamics, the glass transition temperatures $(T_{\\mathrm{g}})$ of DPPT-TT obtained by the differential AC chip calorimetric method show a decreasing trend from the thick, to the thin, and finally to the nanofiber (obtained by removing SEBS from the CONPHINE film) films (Fig. 1D and fig. S2). This trend confirms increased chain dynamics due to nanoconfinement (21, 23, 24). Suppressed crystallization in thinner films (25) was also observed (Fig. 1E and fig. S3). These two effects together result in a decrease in the measured elastic modulus and a significant increase in the onset strains of plasticity and cracks from thick to thin film (Fig. 1F and figs. S4 to S6) (20, 22, 30). Under 2D nanoconfinement, the simulated modulus of the DPPT-TT nanofiber is one-half that of the bilayer film and almost one-sixth that of the thick film (Fig. 1F and fig. S7). The introduction of the SEBS deformable interface further decreases the crystallinity (Fig. 1E) and reduces crack propagation, which makes the bilayer film further softened and more ductile (Fig. 1F and figs. S4 to S6). The improvement in stretchability from these effects is shown by both the dichroic ratios (from ultraviolet/ visible spectroscopy) (fig. S8) and substantially different crack size of these films under strain (fig. S9). \n\nAs observed by the atomic force microscopy (AFM) phase images, the CONPHINE-1 film showed the desired fiber network with smaller nanofiber diameters at higher SEBS concentrations (fig. S10). At 70 weight $\\%$ (wt $\\%$ ) of SEBS, the nanofiber diameter became small enough $\\cdot{<}50~\\mathrm{nm})$ ) to give a strong nanoconfinement effect at both the top and bottom surfaces (Fig. 1G). As revealed by x-ray photoelectron spectroscopy (XPS) (fig. S11), the layer between the top and bottom surfaces is primarily occupied by SEBS, containing a small amount of DPPT-TT. This morphology is depicted in Fig. 1H. Unlike the pregrown nanowires and nanofibers $(I5,I6)_{;}$ , the model films and the CONPHINE-1 with $70\\%$ SEBS film along the $q_{x y}$ axes, normalized by the exposure time and volume of DPPT-TT layer and offset for clarity. (F) Elastic moduli, onset strains of plasticity, and onset strains of crack of the model films, with the simulated modulus of the nanofiber film. The error bars of elastic moduli and onset strains represent the standard deviation and the range of measurement error, respectively. (G) AFM phase images of the top and bottom interfaces of the CONPHINE-1 film with 70 wt $\\%$ SEBS. (H) A 3D illustration of the morphology of the CONPHINE-1 film. (I) Photographs of a CONPHINE1 film (blue area) at $0\\%$ strain and stretched to $100\\%$ strain on a rubber substrate. \n\n![](images/10b8b340639162ce7f6ec55a1275f4a396f5b9eaa13497383264887a98c8bba0.jpg) \nFig. 1. Nanoconfinement effect for enhancing the stretchability of polymer semiconducting film through the CONPHINE method. (A) A 3D schematic of the desired morphology composed of embedded nanoscale networks of polymer semiconductor to achieve high stretchability, which can be used to construct a highly stretchable and wearable TFT. (B) Chemical structures of semiconducting polymer DPPT-TT (labeled as 1) and SEBS elastomer. (C) Three model films of DPPT-TT for investigation of the nanoconfinement effect (i.e., increased chain dynamics and suppressed crystallization). (D) Glass transition temperatures of the thick, thin, and nanofiber films. (E) XRD line cuts for three \n\nnanofibers formed from phase separation have reduced crystallinity but still high aggregation (fig. S12), which ensures both enhanced stretchability and good charge transport. The CONPHINE-1 film can be stretched up to $100\\%$ strain when supported on a rubbery substrate without any visible cracks (Fig. 1I). An additional benefit of the CONPHINE method is the reduced consumption of conjugated polymers and transparent film. \n\nThe stretchability of the CONPHINE-1 film is studied by applying $100\\%$ strain on a polydimethylsiloxane (PDMS)–supported film (Fig. 2A), then transferring the CONPHINE-1 film to a Si substrate for morphology characterization. The CONPHINE-1 film with $70\\%$ SEBS can be effectively stretched to $100\\%$ strain without resulting in any cracks even at the nanoscale, as characterized by AFM (Fig. 2B and fig. S13A), despite inhomogeneity in film thickness after deformation (fig. S13B). In comparison, the neat-1 film at $100\\%$ strain developed cracks with widths around $20~{\\upmu\\mathrm{m}}$ (Fig. 2B). \n\nThe electrical performance of the CONPHINE1 film functioning as a stretchable semiconductor was measured in a thin-film transistor (TFT) by soft contact lamination (13) on a bottom-gate– bottom-contact stack: octadecyltrimethoxysilane (OTS)–assembled $\\mathrm{SiO_{2}}$ (gate dielectric)–coated highly doped Si (gate), with Au contacts on the top (Fig. 2C and fig. S14). Because the DPPT-TT nanofibers on the bottom surface of the CONPHINE film are exposed, good ohmic contacts can be formed with the Au electrodes (fig. S15). The CONPHINE film can be prepared on a wafer scale with good uniformity in electrical performance (fig. S16). By comparing the mobility from the CONPHINE-1 film with different SEBS contents, it was determined that 70 wt $\\%$ SEBS provides the optimum condition for enabling the highest mobility at $100\\%$ strain (fig. S17). As shown in Fig. 2D(i), the CONPHINE-1 film (i.e., 70 wt $\\%$ SEBS) displays a transfer property similar to that of the neat-1 film (i.e., $0\\%$ SEBS), which demonstrates that this approach does not sacrifice the semiconductor’s electrical performance. When both films were stretched to $100\\%$ strain parallel to charge transport, the transfer curve of the CONPHINE film remained unaffected, with its on current ${\\sim}3$ orders of magnitude higher than that of the severely degraded neat-1 film [Fig. 2D(ii) and fig. S18, A and B]. In addition, the CONPHINE1 film showed no decrease in mobility during the entire stretching process (Fig. 2E), in which its mobility at $100\\%$ strain reached a maximum value of $\\mathrm{1.32~cm^{2}/V{\\cdot}s,}$ and $1.08~\\mathrm{cm^{2}/V{\\cdot}s}$ on average, which is a $\\sim3$ -order-of-magnitude improvement compared to the neat-1 film. When the stretching was perpendicular to the charge transport direction, we observed only a very small decrease in both the on current and the mobility from the CONPHINE-1 film at $100\\%$ strain (Fig. 2, D(iii) and F). This, too, is a marked improvement compared to the ${\\sim}2\\cdot$ -orders-of-magnitude decrease in the neat film. To further probe the film’s stretchability, we observed that the CONPHINE-1 film can even be stretched to $200\\%$ strain, with its mobility maintained at $0.33\\mathrm{cm^{2}/V{\\cdot}s}$ (Fig. 2G and fig. S19). \n\n![](images/7a8df822af3782e3d8f56d61fc75415298805ca2463ad3d0ec4e2dc9ac746000.jpg) \nFig. 2. Characterization of the semiconducting film stretchability and and the neat-1 film in its original condition (i), under $100\\%$ strain parallel to electrical performance under different strains. (A) Schematic illustration the charge transport direction (ii), and under $100\\%$ strain perpendicular to of the stretching of the semiconducting film supported on PDMS substrate. the charge transport direction (iii). (E and F) Mobilities from the CONPHINE-1 (B) Optical microscope images of a neat-1 film (left) and a CONPHINE-1 film film (blue) and the neat-1 film (black) at different strains (E) parallel and (F) (middle) under $100\\%$ strain, with an AFM phase image (right) showing that perpendicular to the charge transport direction. (G) Comparison of the obthe color variation in CONPHINE-1 film is not due to cracks. (C) Schematic of tained mobilities at stretched strains in this study to previously reported rethe soft contact lamination method for characterizing the electrical per- sults in the literature. (H) Mobilities of the CONPHINE-1 film (green) and the formance of a semiconducting layer upon stretching. (D) Transfer curves $\\mathrm{\\DeltaV_{D}=}$ neat-1 film (black) as a function of $100\\%$ strain stretching cycles parallel to −80 V, with $V_{\\mathsf{D}}$ representing drain voltage) obtained from the CONPHINE-1 film the charge transport direction. \n\nFor the CONPHINE-1 film, the on current only changes moderately after 100 cycles with $100\\%$ strain at 1 s per cycle. (fig. S17, E to $\\mathrm{H}$ , and the mobility is still high at $0.2~\\mathrm{cm^{2}/V{\\cdot}s}$ (Fig. 2H and fig. S20). There are no visible cracks in the film after 100 cycles (fig. S21); however, we do observe a slight increase in film roughness (fig. S22), which is known to contribute to decreased mobility (16). In comparison, for the neat-1 film, both the on current and mobility decreased by $^{>3}$ orders of magnitude after 100 cycles (Fig. 2H and figs. S17, I to K, and S20). Compared to the literaturereported cyclability for semiconductor films (13, 16, 17), the mobility of our CONPHINE film after cycled stretching is more than 10 times as high, even with twice the strain. Moreover, the CONPHINE film is suitable for long-term usage in practical applications. Although the chain conformation under nanoconfinement has a metastable nature (31), the relatively long chain relaxation time allows the film to maintain a similar nanoscale morphology, electrical performance, and stretchability, as was confirmed with a CONPHINE-1 film after being stored for 1 year (fig. S23). \n\nWe fabricated fully stretchable transistors in a bottom-gate–bottom-contact structure, with carbon nanotube (CNT) networks as the electrodes geometry and dielectric capacitance under strain (table S3); also for the values in (F)] with strains up to $100\\%$ , both parallel to (filled circles) and perpendicular to (open circles) the charge transport direction. (F) Changes in the on current, off current, and mobility after multiple stretching-releasing cycles (up to 1000 cycles) at $25\\%$ strain along the charge transport direction. (G) Drain current $(I_{\\mathsf{D}})$ and gate current $(I_{\\mathsf{G}})$ of a fully stretchable TFT under sequential stretching, twisting, and poking with a sharp object. (H) Demonstration of the fully stretchable transistor as a finger-wearable driver for an LED. \n\n![](images/ec14bee02a7b21f3af31ec3f062a27e04288627d801291348110a42792f06c43.jpg) \nFig. 3. Fully stretchable transistor fabricated from the CONPHINE-1 film. (A) Device structure (channel length: $200\\upmu\\mathrm{m}$ channel width: $4\\mathsf{m m}$ ; dielectric capacitance: $15\\upmu\\mathsf{F}/\\mathsf{m}^{2})$ . (B) Images showing the transistor’s transparency (left) and skinlike nature when attached on the back of a hand (middle), with the conformability shown in the SEM image (right). (C) A typical transfer curve $\\cdot V_{\\mathsf{D}}=$ $-30\\vee)$ at $0\\%$ strain. (D) Distribution of the mobility from 20 devices in the arrays of fully stretchable transistors (shown with increased contrast in the inset). (E) Changes in the on current and mobility [calculated with measured device \n\n![](images/1b65264e82e5cd7fd5cea39e988965d2138b483bb5b03100fa509be5329edc18.jpg) \nFig. 4. Applying the CONPHINE method on four distinct conjugated films at $100\\%$ strain exhibited uneven thicknesses (fig. S29), but no cracks semiconducting polymers to improve their stretchability. (A to D) Optical due to plastic deformation. (E) Transfer curves $\\mathrm{\\DeltaV_{D}=-80\\Omega V)}$ of these neat micrographs of neat conjugated polymer films (middle) and corresponding polymer films (left) and the corresponding CONPHINE films (right) at $100\\%$ CONPHINE films (right) at $100\\%$ strain, for polymers of (A) P-29-DPPDTSE strain, with the same vertical axis in the two diagrams. (F) Normalized (2), (B) PffBT4T-2DT (3), (C) P(DPP2TTVT) (4), and (D) PTDPPTFT4 (5), with mobilities of neat films (gray) and the corresponding CONPHINE films (green) the chemical structures shown on the left. Scale bar, $20\\upmu\\mathrm{m}$ . The CONPHINE of these conjugated polymers, under $100\\%$ strain. \n\nand SEBS as the dielectric layer, stretchable substrate, and encapsulation layer (Fig. 3A and fig. S24). The obtained TFT device has good transparency and excellent conformability for constructing e-skins on human epidermis (Fig. 3B). As shown via a representative transfer curve (Fig. 3C) and output characteristics (fig. S25A), the fully stretchable TFT gives ideal transistor performance and an average mobility of $0.59\\mathrm{cm^{2}/V{\\cdot}s}$ obtained from 20 devices with minimal variations (Fig. 3D). The lower mobility relative to that from the earlier soft contact lamination method is attributed to a higher contact resistance from CNT electrodes compared to Au (fig. S26). When the device is stretched to $100\\%$ strain along the charge transport direction, there is only a slight drop in the on current, owing to the increase in channel length from stretching, with the mobility stably maintaining a value of $0.55~\\mathrm{cm^{2}/V{\\cdot}s}$ even after being stretched to $100\\%$ strain (Fig. 3E, fig. S25B, and table S4). Along the perpendicular direction, the combined effect of the slight decrease in mobility and the device geometric change makes the transfer curve highly stable under strain up to $100\\%$ (Fig. 3E and fig. S25C). Moreover, this fully stretchable TFT is highly robust over 1000 repeated stretching cycles to $25\\%$ strain at four cycles per second (the general range for applied strains in most wearable electronic applications) (Fig. 3F and fig. S25, D and E). The high stretchability and robustness of the TFT are also revealed by its stable drain current under sequential stretching, twisting, and even poking by a sharp object (Fig. 3G and movie S1). We also attached our transistor, serving as a light-emitting diode (LED) driver, conformably to a human finger to demonstrate its potential use for wearable electronics (Fig. 3H and movie S2). \n\nWe applied our CONPHINE method to four other high-performance semiconducting polymers (2 to 5), with their chemical structures shown in Fig. 4, A to D (10, 13, 32) (table S1 and fig. S27). All neat films of these polymers severely crack when subjected to $100\\%$ strain (middle column in Fig. 4, A to D), leading to degraded mobilities as shown. Upon using our CONPHINE method, we again obtained nanoconfined morphologies with deformable interfaces (fig. S28). The stretchability of all these films (CONPHINE2 to CONPHINE-5) is significantly improved, displaying only inhomogeneous deformations at $100\\%$ strain (right-column images in Fig. 4, A to D, and fig. S29). As a result, both the on currents and mobilities (values are indicated in their respective images) from these films at $100\\%$ strain exceed their neat counterparts by one to four orders of magnitude (Fig. 4, E and F). Notably, four different conjugated polymers (including 1) are imparted with mobilities ${>}1.0\\ \\mathrm{cm^{2}/V{\\cdot}s}$ at $100\\%$ strain. \n\nPolymer nanoconfinement enables high stretchablity in semiconducting materials. In this study, we introduced the CONPHINE method to create conjugated-polymer nanostructures with increased chain dynamics and decreased crystallinity embedded in an elastomer matrix to maintain the mobility during stretching. We anticipate that this general approach will advance the development of stretchable semiconductors for stretchable electronic-skin applications. \n\n# REFERENCES AND NOTES \n\n1. D.-H. Kim et al., Science 333, 838–843 (2011). \n2. D.-H. Kim et al., Nat. Mater. 10, 316–323 (2011). \n3. B. C. K. Tee et al., Science 350, 313–316 (2015). \n4. M. Kaltenbrunner et al., Nature 499, 458–463 (2013). \n5. Y. Sun, W. M. Choi, H. Jiang, Y. Y. Huang, J. A. Rogers, \nNat. Nanotechnol. 1, 201–207 (2006). \n6. T. C. Shyu et al., Nat. Mater. 14, 785–789 (2015). \n7. H. Lee et al., Nat. Nanotechnol. 11, 566–572 (2016). \n8. C. B. Nielsen, M. Turbiez, I. McCulloch, Adv. Mater. 25, \n1859–1880 (2013). \n9. H. N. Tsao et al., J. Am. Chem. Soc. 133, 2605–2612 (2011). \n10. I. Kang, H.-J. Yun, D. S. Chung, S.-K. Kwon, Y.-H. Kim, \nJ. Am. Chem. Soc. 135, 14896–14899 (2013). \n11. A. D. Printz, D. J. Lipomi, Appl. Phys. Rev. 3, 021302 (2016). \n12. B. Roth et al., Chem. Mater. 28, 2363–2373 (2016). \n13. H.-C. Wu et al., Chem. Mater. 26, 4544–4551 (2014). \n14. R. Peng et al., J. Mater. Chem. C Mater. Opt. Electron. Devices \n3, 3599–3606 (2015). \n15. E. Song et al., Adv. Electron. Mater. 2, 1500250 (2016). \n16. M. Shin et al., Adv. Mater. 27, 1255–1261 (2015). \n17. A. Chortos et al., Adv. Mater. 26, 4253–4259 (2014). \n\n18. B. O’Connor et al., Adv. Funct. Mater. 21, 3697–3705 (2011). \n19. J. I. Scott et al., ACS Appl. Mater. Interfaces 8, 14037–14045 (2016). \n20. C. M. Stafford, B. D. Vogt, C. Harrison, D. Julthongpiput, R. Huang, Macromolecules 39, 5095–5099 (2006). \n21. J. L. Keddie, R. A. L. Jones, R. A. Cory, Europhys. Lett. 27, 59–64 (1994). \n22. L. Si, M. V. Massa, K. Dalnoki-Veress, H. R. Brown, R. A. L. Jones, Phys. Rev. Lett. 94, 127801 (2005). \n23. J. A. Forrest, K. Dalnoki-Veress, J. R. Dutcher, Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 56, 5705–5716 (1997). \n24. C. J. Ellison, J. M. Torkelson, Nat. Mater. 2, 695–700 (2003). \n25. K. Shin et al., Macromolecules 40, 6617–6623 (2007). \n26. J. F. Chang, M. C. Gwinner, M. Caironi, T. Sakanoue, H. Sirringhaus, Adv. Funct. Mater. 20, 2825–2832 (2010). \n27. J. Kim et al., Mater. Lett. 130, 227–231 (2014). \n28. S. Wang et al., Proc. Natl. Acad. Sci. U.S.A. 112, 10599–10604 (2015). \n29. Y. Li, S. P. Singh, P. Sonar, Adv. Mater. 22, 4862–4866 (2010). \n30. B. O’Connor et al., ACS Nano 4, 7538–7544 (2010). \n\n31. S. Napolitano, Ed., Non-Equilibrium Phenomena in Confined Soft Matter (Springer, 2015). 32. Y. Liu et al., Nat. Commun. 5, 5293 (2014). \n\n# ACKNOWLEDGMENTS \n\nJ.X., S.W., and Z.B. conceived and designed the experiments; J.X. fabricated the CONPHINE films; J.X., S.W., C.Z., and C.L. fabricated the transistor devices and did the measurements; G.-J.N.W, S.R.-G., B.C.S., Y.-H.K., and H.Y. provided the conjugated polymers; S.L., D.Z., and G.X. performed the glass transition measurement; L.J., Y.W., C.L., and W.C. carried out the mechanical simulations; X.G. did the grazing incidence x-ray diffraction (XRD) characterizations; S.C., V.R.F., and J.W.F.T. did the XPS and scanning electron microscopy (SEM) characterizations; J.P. and R.S. did the scanning transmission electron microscopy characterization; J.Y.O. helped with the film transfer process; S.W., J.X., Z.B., J.W.C., and J.B.-H.T. organized the data and wrote the manuscript; and all authors reviewed and commented on the manuscript. This work is supported by Samsung Electronics (material fabrication and devices) and the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under award DE-SC0016523 (material characterization). S.R.-G. thanks the Fonds de Recherche du Québec: Nature et Technologies for a postdoctoral fellowship. B.C.S. acknowledges the National Research Fund of Luxembourg for financial support (project 6932623). H.Y. thanks the Hong Kong Innovation and Technology Commission for support through ITC-CNERC14SC01. C.L. acknowledges support from the National Science Foundation through CMMI-1553638. Y.-H.K. thanks the NRF Korea (2015R1A2A1A10055620). J.X., Z.B., J.W.C., and Sangyoon Lee are inventors on patent application no. 62/335,250 submitted by Samsung Electronics Co., Ltd., and the board of Trustees of the Leland Stanford Junior University. The GIXD measurements were performed in Advanced Light Source beamline 7.3.3 and SSRL 11-3, which are supported by the director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under contract nos. DE-AC02-05CH11231 and DE-AC02-76SF00515, respectively. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/355/6320/59/suppl/DC1 \nMaterials and Methods \nTables S1 to S4 \nFigs. S1 to S29 \nReferences (33–47) \nMovies S1 and S2 \n29 June 2016; accepted 2 December 2016 \n10.1126/science.aah4496 \n\n# Science \n\n# Highly stretchable polymer semiconductor films through the nanoconfinement effect \n\nJie Xu, Sihong Wang, Ging-Ji Nathan Wang, Chenxin Zhu, Shaochuan Luo, Lihua Jin, Xiaodan Gu, Shucheng Chen, Vivian R Feig, John W. F. To, Simon Rondeau-Gagné, Joonsuk Park, Bob C. Schroeder, Chien Lu, Jin Young Oh, Yanming Wang, Yun-Hi Kim, He Yan, Robert Sinclair, Dongshan Zhou, Gi Xue, Boris Murmann, Christian Linder, Wei Cai, Jeffery B.-H. Tok, Jong Won Chung and Zhenan Bao \n\nScience 355 (6320), 59-64. DOI: 10.1126/science.aah4496 \n\n# Trapping polymers to improve flexibility \n\nPolymer molecules at a free surface or trapped in thin layers or tubes will show different properties from those of the bulk. Confinement can prevent crystallization and oddly can sometimes give the chains more scope for motion. Xu et al. found that a conducting polymer confined inside an elastomer−−a highly stretchable, rubber-like polymer−−retained its conductive properties even when subjected to large deformations (see the Perspective by Napolitano). \n\nScience, this issue p. 59; see also p. 24 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/355/6320/59 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2017/01/04/355.6320.59.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/355/6320/24.full \n\nREFERENCES \n\nThis article cites 44 articles, 3 of which you can access for free http://science.sciencemag.org/content/355/6320/59#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.aan0202", + "DOI": "10.1126/science.aan0202", + "DOI Link": "http://dx.doi.org/10.1126/science.aan0202", + "Relative Dir Path": "mds/10.1126_science.aan0202", + "Article Title": "Two-dimensional sp2 carbon-conjugated covalent organic frameworks", + "Authors": "Jin, EQ; Asada, M; Xu, Q; Dalapati, S; Addicoat, MA; Brady, MA; Xu, H; Nakamura, T; Heine, T; Chen, QH; Jiang, DL", + "Source Title": "SCIENCE", + "Abstract": "We synthesized a two-dimensional (2D) crystalline covalent organic framework (sp(2)c-COF) that was designed to be fully pi-conjugated and constructed from all sp(2) carbons by C=C condensation reactions of tetrakis(4-formylphenyl)pyrene and 1,4-phenylenediacetonitrile. The C=C linkages topologically connect pyrene knots at regular intervals into a 2D lattice with pi conjugations extended along both x and y directions and develop an eclipsed layer framework rather than the more conventionally obtained disordered structures. The sp(2)c-COF is a semiconductor with a discrete band gap of 1.9 electron volts and can be chemically oxidized to enhance conductivity by 12 orders of magnitude. The generated radicals are confined on the pyrene knots, enabling the formation of a paramagnetic carbon structure with high spin density. The sp(2) carbon framework induces ferromagnetic phase transition to develop spin-spin coherence and align spins unidirectionally across the material.", + "Times Cited, WoS Core": 924, + "Times Cited, All Databases": 977, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000407793600031", + "Markdown": "# MOLECULAR FRAMEWORKS \n\n# Two-dimensional $\\mathbf{sp}^{2}$ carbon–conjugated covalent organic frameworks \n\nEnquan Jin,1 Mizue Asada,2 Qing Xu,1 Sasanka Dalapati,1 Matthew A. Addicoat,3 Michael A. Brady,4 Hong $\\mathbf{X}\\mathbf{u},^{1,2}$ Toshikazu Nakamura,2 Thomas Heine,5 Qiuhong Chen,1 Donglin Jiang1\\* \n\nWe synthesized a two-dimensional (2D) crystalline covalent organic framework $\\mathsf{\\mathsf{s p}}^{2}\\mathsf{c}$ -COF) that was designed to be fully $\\pi$ -conjugated and constructed from all $\\mathsf{s p}^{2}$ carbons by $c=c$ condensation reactions of tetrakis(4-formylphenyl)pyrene and 1,4-phenylenediacetonitrile. The $c=c$ linkages topologically connect pyrene knots at regular intervals into a 2D lattice with $\\pi$ conjugations extended along both $x$ and $y$ directions and develop an eclipsed layer framework rather than the more conventionally obtained disordered structures.The $\\mathsf{s p}^{2}\\mathsf{c}$ -COF is a semiconductor with a discrete band gap of 1.9 electron volts and can be chemically oxidized to enhance conductivity by 12 orders of magnitude. The generated radicals are confined on the pyrene knots, enabling the formation of a paramagnetic carbon structure with high spin density. The $\\mathsf{s p}^{2}$ carbon framework induces ferromagnetic phase transition to develop spin-spin coherence and align spins unidirectionally across the material. \n\nn coovanljeungtateordgbaonidc fnrgabmaseewdornk $\\mathrm{sp}^{2}.$ h-haytberixdpilzoeidt carbons could create materials with excepU tional electronic and magnetic properties $(I)$ . To design such an extended structure, the $\\mathrm{sp}^{2}$ carbon chains must be able to diverge at regular intervals. Such branches should have appropriate geometry for extended $\\pi$ conjugation at the point of knot so that the chains strictly propagate along the $x$ and $y$ directions without blocking the extension of $\\pi$ conjugation. However, amorphous materials will form if the $\\mathrm{sp}^{2}$ carbon bond formation reactions are irreversible if an in situ structural self-healing process is lacking (2, 3). Thus, designing well-defined two-dimensional (2D) materials and fabricating extended $\\mathrm{sp}^{2}$ carbon networks with chain propagation along both $x$ and $y$ directions are challenging goals. \n\nWe report a topology-directed reticular construction of crystalline $\\mathrm{sp}^{2}$ carbon–conjugated covalent organic framework $(\\mathrm{sp^{2}c\\mathrm{-}C O F)}$ by designing a $\\mathrm{C=C}$ bond formation reaction (Fig. 1A). This reaction (4–7) enables structural self-healing under thermodynamic control during polycondensation. Topology-directed polycondensation (8–13) of $C_{2}.$ symmetric 1,3,6,8-tetrakis(4-formylphenyl)pyrene (TFPPy) as knots and $C_{2}$ -symmetric linear 1,4- phenylenediacetonitrile (PDAN) as linkers under solvothermal conditions (mesitylene/dioxane $\\mathbf{\\Sigma}=\\mathbf{\\Sigma}$ $1/5\\mathrm{v/v,4MNaOH,\\it\\Omega^{\\ddagger}}$ 3 days, $90^{\\circ}\\mathrm{C})$ yielded a $\\scriptstyle\\operatorname{sp}^{2}\\csc\\mathrm{OF}$ . The 2D $\\mathrm{sp}^{2}$ carbon sheet consists of $\\mathrm{sp}^{2}$ carbon chains extended along the $x$ and $y$ directions in which pyrene units serve as interweaving registry points that are periodically pitched at 2-nm intervals (Fig. 1, B and D). The 2D sheets crystallize and form stacked layers at 3.58-Å separation, creating ordered pyrene columnar arrays and 1D nanochannels (Fig. 1, C and E). We use the term $\\pi$ conjugation rather than 2D for $\\displaystyle\\operatorname{sp}^{2}\\mathbf{c}$ -COF because it offers $\\pi$ conjugation along both the $\\boldsymbol{x}$ and $y$ directions. Note that a 2D sheet can form, with restricted $\\pi$ conjugation blocked at the point of vertices, as occurs in a 2D polyphenylenevinylene framework knotted by all meta-substituted 1,3,5-phenyl focal units $(I4)$ . We unexpectedly found that the fully conjugated 2D layers offer the structural base of an $\\displaystyle\\mathbf{sp}^{2}$ carbon lattice that can accommodate exceptionally dense spins and unidirectional spin alignment via ferromagnetic phase transition. \n\nThe chemical structure of $\\displaystyle\\operatorname{sp}^{2}\\mathbf{c}$ -COF was characterized by various analytical methods [see supplementary materials, figs. S1 to S7, and tables S1 and S2 (15)]. Fourier-transform infrared spectroscopy revealed that the peak at $2220\\mathrm{{cm}^{-1}}$ had newly appeared for the cyano side group (16) and the peak at $2720\\mathrm{{cm}^{-1}}$ assigned to the C–H bond of the aldehyde group was greatly attenuated, indicating the polycondensation between TFPPy and PDAN (fig. S1). Solid-state $^{13}\\mathrm{C}$ nuclear magnetic resonance spectroscopy of $\\scriptstyle\\operatorname{sp}^{2}\\csc\\mathrm{OF}$ revealed that the peak at 24.20 parts per million (ppm) for the methylene carbon of PDAN disappeared upon polycondensation, and the peak at 120.44 ppm assigned to PDAN units was shifted to 107.74 ppm (cyano side group), indicating the formation of $\\scriptstyle\\mathbf{C}=\\mathbf{C}$ linkages in $\\displaystyle\\operatorname{sp}^{2}\\mathtt{c}$ -COF (fig. S2). Similar spectral changes were also observed for a model compound (a TFPPy core bound to four PDAN groups) (figs. S1 and S2 and scheme S1A). Field-emission scanning electron microscopy revealed that $\\mathrm{sp}^{2}\\mathrm{c}$ -COF and a model compound adopted a belt morphology (fig. S3). Thermogravimetric analysis suggested that $\\operatorname{sp}^{2}\\operatorname{c-COF}$ was stable up to $350^{\\circ}\\mathrm{C}$ under nitrogen (fig. S4). \n\nThe $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-COF}$ exhibited powder x-ray diffraction (PXRD) peaks at $3.6^{\\circ},$ $5.2\\%$ $5.9^{\\circ},$ $7.3^{\\circ},$ 11.2°, $11.8^{\\circ},14.2^{\\circ},$ and $24.7^{\\circ},$ which were assigned to the (110), (200), (210), (220), (240), (420), (520), and (001) facets, respectively (fig. S5, red curve and inset). We used density functional–based tight binding (DFTB) calculations to optimize the conformation of the 2D single layer and the configuration of different stacking models (17, 18). The energetically most favorable AA-stacking model yielded a PXRD pattern (fig. S5, pink curve) in good agreement with the experimentally observed profile. The Pawley-refined PXRD pattern (fig. S5, black curve) with the $c2/m$ space group with unitcell parameters of $a=34.4632\\mathrm{{\\AA}}$ , $b=35.4951\\mathrm{\\AA},c=$ 3.7199 ${\\mathrm{\\AA}},$ $\\alpha=\\gamma=90{^\\circ},$ and $\\upbeta=104.0277^{\\circ}$ reproduced the experimentally observed curve with negligible differences (fig. S5, green curve). Tables S1 and S2 summarize the atomistic coordinates generated by DFTB calculation and Pawley refinements, respectively. Thus, the reconstruction of $\\mathrm{sp^{2}c}$ -COF structure shows an extended 2D tetragon lattice with $\\mathrm{sp}^{2}$ carbon backbones along the $x$ and $y$ directions (Fig. 2A). The presence of the (001) facet at $24.7^{\\circ}$ suggests the structural ordering with 3.58-Å separation in the $z$ direction perpendicular to the 2D sheets (Fig. 2B). \n\nThe $\\displaystyle\\operatorname{sp}^{2}\\mathbf{c}$ -COF exhibited reversible nitrogen sorption isotherm curves with a Brunauer-EmmettTeller surface area of $692\\mathrm{m}^{2}\\mathrm{g}^{-1}$ (fig. S6A). The pore-size distribution profile revealed that $\\displaystyle\\operatorname{sp}^{2}\\mathtt{c}.$ COF is microporous with a pore size of $1.88~\\mathrm{nm}$ (fig. S6B). This result is consistent with the lattice as revealed by the structural analysis. \n\nSolid-state electronic absorption spectroscopy of $\\mathrm{sp^{2}c}$ -COF (fig. S7A, red curve) showed an absorption band at $498\\mathrm{nm}$ , whose red shift of $53\\mathrm{nm}$ from that of the model compound (fig. S7A, black curve, and scheme S1A) is indicative of extended $\\pi$ conjugation. In contrast, the imine-linked 2D COF (fig. S7A, blue curve; figs. S8 and S9; and scheme S1B), an analog to $\\operatorname{sp}^{2}\\mathrm{c}{\\mathrm{-}}\\mathrm{COF},$ , exhibited an absorption band blue-shifted $21\\mathrm{nm}$ relative to $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-COF}$ , indicating that the $\\scriptstyle\\mathbf{C}=\\mathbf{C}$ linkage is more effective in transmission of $\\pi$ conjugation over the 2D lattice than that of the $\\mathrm{C}{=}\\mathrm{N}$ bond. Moreover, the contrast in the optical colors (fig. S7B) between $\\operatorname{sp}^{2}\\mathrm{c}{\\mathrm{-}}\\mathrm{COF}$ (red), imine-linked 2D COF (yellow), and model compound (yellow-orange) also reflects the extended $\\pi$ conjugation in $\\mathrm{sp}^{2}\\mathrm{c}$ -COF. Cyclic voltammetry (CV) of $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-}\\mathrm{COF}$ (fig. S10) revealed an oxidation potential at $0.94\\mathrm{V}$ and a reduction potential at $-0.96\\mathrm{V}$ , indicating a narrow band gap of $1.90\\mathrm{eV}$ . The highest occupied molecular orbital (HOMO) level was evaluated (19) as $-5.74~\\mathrm{eV}_{:}$ , and the lowest unoccupied molecular orbital (LUMO) level was $-3.84\\mathrm{~eV},$ , constituting a semiconductor band structure. \n\n![](images/41e7e8e4f30716d3c9dea7c0ce2fdc55efc6183c842ef525300368ebc5f84ac7.jpg) \nFig. 1. Chemical and lattice structures of a crystalline porous $\\mathsf{s p}^{2}$ carbon framework. (A) Schematic representation of the synthesis of the crystalline porous $\\mathsf{s p}^{2}$ -hybridized carbon covalent organic framework $(\\mathsf{s p}^{2}\\mathsf{c}$ -COF) with pyrene knots and phenylenevinylene linkers connected by $C=C$ bonds (one pore is shown). ${\\mathsf{T F P P y}}$ , tetrakis(4-formylphenyl)pyrene; PDAN, 1,4-phenylenediacetonitrile. (B and C) Reconstructed crystal structures of (B) one layer and (C) many layers of the 2D $\\mathsf{s p}^{2}\\mathsf{c}$ -COF (three \nby-three unit cell). The pyrene knots are regularly interweaved in a $2-\\mathsf{n m}$ pitch along the $x$ and y directions and are stacked at an interval of $3.58\\AA$ along the z direction via $\\pi^{-}\\pi$ interactions to form ordered pyrene knot $\\pi$ arrays and 1D channels. (D and E) Ball (pyrene knot) and stick (phenylenevinylene chain) representations of (D) a 2D sheet with extended $\\pi$ conjugations along the $x$ and y directions and (E) the stacked $\\mathsf{s p}^{2}\\mathsf{c}$ -COF. \n\nThe $\\displaystyle\\mathbf{sp}^{2}\\mathbf{c}$ -COF solid samples were chemically oxidized by iodine and pressed to make thin discs with a thickness of $0.08\\mathrm{cm}$ . The electrical conductivity was measured across a 0.2-cm-width Pt gap electrode under air at $25^{\\circ}\\mathrm{C}.$ . The iodine-doped $\\mathrm{sp}^{2}\\mathrm{c}$ -COF exhibited a linear current-voltage $(I{-}V)$ profile indicative of ohmic conduction (fig. S11, red curve). The slope yielded a conductivity of $7.1\\times$ $10^{-2}\\mathrm{S}\\mathrm{m}^{-1}$ . The pristine COF sample was an insulator with a conductivity of only $6.1\\times10^{-14}\\mathrm{{Sm}^{-1}}$ (fig. S11, black curve). \n\n![](images/4a49488ab2360379e166b8c1f537aeea531932743924871ad3a44c0e3f27d0c4.jpg) \nFig. 2. Crystal structure. (A and B) Reconstructed crystal structure at top (A) and side (B) views. The 2D layers are stacked at a 3.58-Å interval along the $z$ direction. \n\nTo investigate the feature of radical species in the $\\mathrm{2D\\thinspacesp^{2}}$ carbon framework, we monitored the doping process of the COF samples in the presence of iodine vapor under iodine-saturated pressure in a sealed quartz tube with electron spin resonance (ESR) spectroscopy (Fig. 3). An ESR signal appeared at $g$ -factor $=2.003$ , just after $3\\mathrm{min}$ of iodine doping (Fig. 3A). The peak-to-peak height increased and leveled off after 1 day of doping (Fig. 3B). The increase in ESR intensity with iodine doping indicates that the charge carriers generated also possess a spin degree of freedom. The ESR linewidth and resonance field $(g\\mathbf{\\cdot}$ -factor) were almost constant regardless of the doping level; the shift of the g-factor from that of the free electron $\\left(g=2.0023\\right)$ was very small. The ESR linewidth of $0.13\\mathrm{mT}$ indicates that the $\\mathrm{sp}^{2}$ carbon lattice is free of anisotropic $g$ -tensor and hyperfine interactions. \n\n![](images/ee4cd56fc3ceeeeec3cd199d0c76cc4fc6d997ed3252291fc6c543b3068b2095.jpg) \nFig. 3. ESR studies. (A) Time evolution of the electron spin resonance (ESR) spectra upon iodine doping. (B) Plot of the peak-to-peak height of the ESR signals versus doping time. The peak intensity was saturated after 26 hours and did not decrease after doping. (C) Temperature dependency of the spin susceptibility $(\\chi_{\\mathrm{spin}})$ for the iodine-doped $\\mathsf{s p}^{2}\\mathsf{c}$ -COF. a. u., arbitrary units. (D) Temperature dependency of the ESR linewidth $(\\Delta H_{\\mathsf{p p}})$ . \n\nThese results suggest that the frontier electrons maintain to locate at the pyrene knots and do not form nonradical bipolarons. \n\nThe temperature dependence of the spin susceptibility $\\chi_{\\mathrm{spin}}$ determined by integrating the ESR signal intensity (Fig. 3C) shows that the $g$ -factor was temperature independent. The Curie-like enhancement of the $\\chi_{\\mathrm{spin}}$ value indicates that the existing spin freedom persists to the low temperature (Fig. 3C). Figure 3D shows the temperature dependency of the ESR linewidth, $\\Delta H_{\\mathrm{pp}}$ . The ESR linewidth is almost constant above $100~\\mathrm{K}.$ . The temperature-independent ESR linewidth is dominated by the spin-spin exchange interaction through space between spins in neighboring layers and indicates the localized nature of the spins at the pyrene knots. Considerable exchange interaction between spins is an evidence for the high density of spins generated in the iodine-doped $\\displaystyle\\mathrm{sp}^{2}\\mathrm{c}$ -COF. The ESR linewidth gradually increased below $100\\mathrm{K},$ suggesting that long-range magnetic order developed in the framework. Such a 2D spin structure is inaccessible by either 1D conjugated polymers (20, 21) or conventional 2D COFs (1). \n\nThe absence of bipolarons observed for $\\mathrm{sp}^{2}\\mathrm{c}-$ COF is totally different from 1D conjugated polymers, which eventually form bipolarons without spins and greatly diminish the spins in the doped materials (22–25). We compared the ESR spectra with those of 1D $\\displaystyle\\mathrm{sp}^{2}\\mathrm{c}$ -polymer (scheme S2) and $\\mathrm{C=N}$ -linked 2D COFs upon iodine doping, which gave rise to only very weak ESR signals (fig. S12). The ESR intensities of $\\mathrm{sp}^{2}\\mathrm{c}$ -COF were 120 and 25 times higher than those of 1D $\\displaystyle\\operatorname{sp}^{2}\\mathrm{c}$ -polymer and $\\mathrm{C=N}$ -linked 2D COFs at room temperature, respectively. The fully $\\pi$ -conjugated $\\mathrm{sp}^{2}$ carbon 2D lattice is essential for generating high-density radicals in the materials. Moreover, we used wideangle x-ray scattering (WAXS) to investigate the structure of crystalline $\\scriptstyle\\operatorname{sp}^{2}\\csc\\mathrm{OF}$ upon iodine doping (26, 27). The WAXS peaks were unchanged before and after prolonged iodine doping with respect to the (110), (200), (210), (220), (240), (420), and (001) facets (fig. S13), indicating that the pyrene arrays are retained upon chemical oxidation. \n\nunit and $8.1\\mathrm{K},$ respectively. Therefore, iodinedoped $\\mathrm{sp^{2}c}$ -COF with exceptionally dense spins is a bulk magnet. \n\nMagnetization $(M)$ –applied field $(H)$ relations revealed that $\\mathrm{sp}^{2}\\mathrm{c}$ -COF yielded linear curves at the temperatures above $20\\mathrm{K}$ ; below 10 K, the M-H plots became nonlinear (Fig. 4B, blue and red curves). The nonlinearity denotes a ferromagnetic phase transition, whereas the spin-spin coherence is developed with unidirectionally aligned spins across the material (Fig. 4C). \n\nTo verify that the observed long-range order was intrinsic, we used superconducting quantum interference device (SQUID) magnetometry to perform magnetic susceptibility measurements. Figure 4A shows the temperature dependence of the magnetic susceptibility $(\\chi)$ . The spin susceptibilities determined by both ESR and SQUID measurements were in agreement in the entire temperature range. Above $100\\mathrm{K}$ , the spins were paramagnetic and randomly oriented in the material. The magnetic susceptibility was greatly enhanced below $100~\\mathrm{K}.$ By using the magnetic susceptibility below $30~\\mathrm{K}$ and assuming $S=1/2$ spin, the spin concentration and the Weiss temperature (Q) were estimated to be 0.7 per pyrene \n\nAs controls, we investigated the electronic and magnetic behaviors of the model compound, a 1,6-linear polymer (scheme S3), and an amorphous version of $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-}\\mathrm{COF}$ referred to as $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-}\\mathrm{CMP}$ (CMP, conjugated microporous polymer) (scheme S4). $\\mathrm{sp}^{2}\\mathrm{c-CMP}$ has the same components as $\\operatorname{sp}^{2}\\mathbf{c}\\mathbf{-}\\mathbf{COF}$ but does not possess ordered layer structure (fig. S14, A to C). The 1,6-linear polymer exhibited an absorption band at $446\\mathrm{nm}$ (fig. S15) and an electronic bandgap of $2.34\\ \\mathrm{eV}$ (fig. S16B and table S3). The $\\mathrm{sp}^{2}\\mathrm{c}$ -CMP sample exhibited an adsorption band at $436~\\mathrm{nm}$ (fig. S15), which is blueshifted by $62\\mathrm{nm}$ from that of $\\mathrm{sp^{2}c\\mathrm{-}C O F(498\\mathrm{nm)}}$ . From the adsorption spectrum, the optical band gap of $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-}\\mathrm{CMP}$ was evaluated to be $2.01\\ \\mathrm{eV}$ , whereas its electronic band gap was $1.96\\mathrm{eV}$ (fig. S16C and table S3), according to the CV measurements. Upon doping with iodine, the model compound exhibited a conductivity of only $4.1\\times$ $10^{-8}\\mathrm{{Sm^{-1}}}$ (fig. S17A) and an ESR intensity equal to $1/100$ that of $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-COF}$ (fig. S18, A and B). The spin density is negligible (fig. S19, A and B). Upon doping, the model compound did not exhibit magnetic state transition and magnetic field response from the $M\\mathrm{-}H$ curve (fig. S20A). The 1,6- linear polymer, upon doping with iodine, exhibited a conductivity of $2.9\\times10^{-7}\\mathrm{{Sm}^{-1}}$ (fig. S17B). From the time-dependent ESR measurements (fig. S18C), the saturated ESR intensity is $1/406$ that of $\\displaystyle\\operatorname{sp}^{2}\\mathbf{c}$ -COF (fig. S18A). The 1,6-linear polymer had a spin density of only 0.004 per pyrene unit (fig. S19, A and C) and did not exhibit magnetic state transition and magnetic field response (fig. S20B). The $\\mathrm{sp}^{2}\\mathrm{c}\\mathrm{-}\\mathrm{CMP}$ samples, upon doping with iodine, exhibited a conductivity of $8.1\\times10^{-3}\\mathrm{~S~m~}^{-1}$ (fig. S17C), which is one order of magnitude lower than that of $\\operatorname{sp}^{2}\\mathrm{c}{\\mathrm{-}}\\mathrm{COF}$ . The time-dependent ESR measurements revealed signals at $g=2.003$ (fig. S18D). However, the saturated ESR intensity is only 1/5 that of $\\operatorname{sp}^{2}\\mathrm{c}{\\mathrm{-}}\\mathrm{COF}$ (fig. S18A). The spin density is $0.057$ per pyrene unit (fig. S19, A and D). These results indicate that the amorphous $\\mathrm{sp}^{2}\\mathrm{c-CMP}$ cannot form a dense spin system. The SQUID measurements revealed that a small amount of part of $\\mathrm{sp^{2}c\\mathrm{-}C M P}$ is paramagnetic at room temperature and shows a trace of superparamagnetism at low temperature (fig. S20C, $\\Theta=1.5\\:\\mathrm{K}$ ), as indicated by the decreased magnetism after the field of 40,000 Oe (red curve). In contrast, the ferromagnetism with increasing magnetism is an overwhelming majority in $\\mathrm{sp^{2}c}$ -COF with saturated magnetism after the field of 40,000 Oe (Fig. 4B, red curve). These results confirmed that the observed electronic and spin functions are inherent to $\\operatorname{sp}^{2}\\mathrm{c}\\mathrm{-COF}$ and originate from its extended crystalline structure. \n\n10. L. Ascherl et al., Nat. Chem. 8, 310–316 (2016). \n11. S. Kandambeth et al., J. Am. Chem. Soc. 134, 19524–19527 (2012). \n12. M. R. Rao, Y. Fang, S. De Feyter, D. F. Perepichka, J. Am. Chem. Soc. 139, 2421–2427 (2017). \n13. X.-H. Liu et al., J. Am. Chem. Soc. 135, 10470–10474 (2013). \n14. X. Zhuang et al., Polym. Chem. 7, 4176–4181 (2016). \n15. Materials and methods, figs. S1 to S7, and tables S1 and S2 are available as supplementary materials. \n16. B. C. Thompson, Y.-G. Kim, T. D. McCarley, J. R. Reynolds, J. Am. Chem. Soc. 128, 12714–12725 (2006). \n17. B. Aradi, B. Hourahine, T. Frauenheim, J. Phys. Chem. A 111, 5678–5684 (2007). \n18. www.dftb.org \n19. $E_{\\mathsf{H O M O}}=-e(E_{\\mathsf{o x i d a t i o n,~o n s e t}}+4.8-E_{\\mathsf{F c/F c+}})$ ; $E_{\\mathsf{L U M O}}=$ $-e(E_{\\mathrm{reduction,\\onset}}+4.8-E_{\\mathsf{F c/F c+}})$ , where $E_{\\mathsf{H O M O}}$ is the HOMO energy level, $E_{\\mathsf{L U M O}}$ is the LUMO energy level, e is an electron particle, Eoxidation, onset and Ereduction, onset are the onset oxidation and reduction potentials, respectively, and $E_{\\mathsf{F C/F C+}}$ is the potential of a ferrocene/ferricenium ion couple as external standard, measured under the same conditions. \n20. J. L. Bredas, G. B. Street, Acc. Chem. Res. 18, 309–315 (1985). \n21. S. Kuroda, K. Marumoto, Y. Shimoi, S. Abe, Thin Solid Films 393, 304–309 (2001). \n22. A. Sakamoto, Y. Furukawa, M. Tasumi, J. Phys. Chem. 98, 4635–4640 (1994). \n23. I. Orion, J. P. Buisson, S. Lefrant, Phys. Rev. B 57, 7050–7065 (1998). \n24. W. R. Salaneck, R. H. Friend, J. L. Brédas, Phys. Rep. 319, 231–251 (1999). \n25. R. R. Chance, J. Bredas, R. Silbey, Phys. Rev. B 29, 4491–4495 (1984). \n26. A. Hexemer et al., J. Phys. Conf. Ser. 247, 012007 (2010). \n27. J. Ilavsky, J. Appl. Cryst. 45, 324–328 (2012). \n\n# ACKNOWLEDGMENTS \n\n![](images/e94157c08ac6e1e8516abb29c6a32d4b0e86295cf46a4c3f33a9b29e514c7e4d.jpg) \nFig. 4. Magnetization and spin alignment. (A) Temperature dependence of the spin susceptibility, $\\chi$ , determined by the superconducting quantum interference device (SQUID) magnetometer for the iodinedoped $\\mathsf{s p}^{2}\\mathsf{c}\\mathsf{-C O F}$ . emu, electromagnetic units. (B) Magnetic (M)-applied field $(H)$ profiles at different temperatures (red, $2\\mathsf{K};$ blue, $5\\mathsf{K};$ purple, $10\\mathsf{K};$ brown, $20\\mathsf{K};$ green, $100\\mathsf{K}$ black, 300 K).The nonlinearity of the curves denotes the ferromagnetic phase transition. (C) Schematic of spin alignment in $\\mathsf{s p}^{2}\\mathsf{c}$ -COF (threeby-three lattice). Red arrows represent spins. The spins are isolated at the knots and are unidirectionally aligned across the framework via ferromagnetic phase transition to develop spin-spin coherence. \n\nE.J. acknowledges Chinese Scholarship Concert for financial support for his study in Japan. S.D. is now an international research fellow of the Japan Society for the Promotion of Science. M.A.B. acknowledges the Advanced Light Source, which is supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under contract DE-AC02-05CH11231. T.H. and M.A. acknowledge supercomputer time at ZIH Dresden and financial support by the European Research Council (grant ERC-StG 256962 C3ENV) and the VolkswagenStiftung. D.J. acknowledges a Grantin-Aid for Scientific Research (A) (17H01218) from the Ministry of Education, Culture, Sports, Science and Technology, Japan, and support from the ENEOS Hydrogen Trust Fund and the Ogasawara Foundation for the Promotion of Science and Engineering. D.J. conceived and designed the project. E.J., Q.X., S.D., H.X., and Q.C. conducted the experiments. M.A.A. and T.H. conducted DFTB calculations and structure simulations. M.A. and T.N. conducted ESR and SQUID measurements. M.A.B. conducted WAXS measurements. D.J., E.J., Q.C., and S.D. wrote the manuscript and discussed the results with all authors. All data are reported in the main text and supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\n# REFERENCES AND NOTES \n\n1. N. Huang, P. Wang, D. Jiang, Nat. Rev. Mater 1, 16068 (2016). \n2. Y. Xu, S. Jin, H. Xu, A. Nagai, D. Jiang, Chem. Soc. Rev. 42, 8012–8031 (2013). \n3. J.-X. Jiang et al., Angew. Chem. Int. Ed. 46, 8574–8578 (2007). \n4. D. T. Mowry, J. Am. Chem. Soc. 67, 1050–1051 (1945). \n5. H. E. Zimmerman, L. Ahramjian, J. Am. Chem. Soc. 81, 2086–2091 (1959). \n6. S. Patai, Y. Israeli, J. Chem. Soc. 0, 2025–2030 (1960). \n7. D. A. M. Egbe et al., Macromolecules 37, 8863–8873 (2004). \n8. P. J. Waller, F. Gándara, O. M. Yaghi, Acc. Chem. Res. 48, 3053–3063 (2015). \n9. J. W. Colson et al., Science 332, 228–231 (2011). \n\nwww.sciencemag.org/content/357/6352/673/suppl/DC1 \nMaterials and Methods \nSchemes S1 to S4 \nFigs. S1 to S20 \nTables S1 to S3 \nReferences (28–31) \nCoordinates File S1 \n20 February 2017; resubmitted 21 June 2017 \nAccepted 11 July 2017 \n10.1126/science.aan0202 \n\n# Science \n\n# Two-dimensional $\\mathsf{s p}^{2}$ carbon−conjugated covalent organic frameworks \n\nEnquan Jin, Mizue Asada, Qing Xu, Sasanka Dalapati, Matthew A. Addicoat, Michael A. Brady, Hong Xu, Toshikazu Nakamura, Thomas Heine, Qiuhong Chen and Donglin Jiang \n\nScience 357 (6352), 673-676. DOI: 10.1126/science.aan0202 \n\n# Conjugated covalent networks \n\nAlthough graphene and related materials are two-dimensional (2D) fully conjugated networks, similar covalent organic frameworks (COFs) could offer tailored electronic and magnetic properties. Jin et al. synthesized a fully $\\pi$ -conjugated COF through condensation reactions of tetrakis(4-formylphenyl)pyrene and 1,4-phenylenediacetonitrile. The reactions were reversible, which provides the self-healing needed to form a crystalline material of stacked, $\\pi$ -bonded 2D sheets. Chemical oxidation of this semiconductor with iodine greatly enhanced its conductivity, and the radicals formed on the pyrene centers imparted a high spin density and paramagnetism. \n\nScience, this issue p. 673 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1002_adma.201605531", + "DOI": "10.1002/adma.201605531", + "DOI Link": "http://dx.doi.org/10.1002/adma.201605531", + "Relative Dir Path": "mds/10.1002_adma.201605531", + "Article Title": "An Artificial Solid Electrolyte Interphase with High Li-Ion Conductivity, Mechanical Strength, and Flexibility for Stable Lithium Metal Anodes", + "Authors": "Liu, YY; Lin, DC; Yuen, PY; Liu, K; Xie, J; Dauskardt, RH; Cui, Y", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "An artificial solid electrolyte interphase (SEI) is demonstrated for the efficient and safe operation of a lithium metal anode. Composed of lithium-ion-conducting inorganic nulloparticles within a flexible polymer binder matrix, the rationally designed artificial SEI not only mechanically suppresses lithium dendrite formation but also promotes homogeneous lithium-ion flux, significantly enhancing the efficiency and cycle life of the lithium metal anode.", + "Times Cited, WoS Core": 838, + "Times Cited, All Databases": 912, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000396166800023", + "Markdown": "# An Artificial Solid Electrolyte Interphase with High Li-Ion Conductivity, Mechanical Strength, and Flexibility for Stable Lithium Metal Anodes \n\nYayuan Liu, Dingchang Lin, Pak Yan Yuen, Kai Liu, Jin Xie, Reinhold H. Dauskardt, and Yi Cui\\* \n\nEfficient and stable operation of a lithium (Li) metal anode has become the enabling factor for next-generation high capacity energy storage systems.[1–3] Due to its highest theoretical specific energy $(3860\\mathrm{\\mAh\\g^{-1})}$ , low density $(0.534\\textrm{g c m}^{-3})$ , and the lowest electrochemical potential $(-3.040\\mathrm{~V~}$ vs standard hydrogen electrode), a Li metal anode has long been considered the “Holy Grail” of battery chemistry.[4,5] Nevertheless, fundamental challenges remain for a Li metal anode despite almost five decades of research, which prevents it from practical applications in rechargeable batteries. \n\nA natural solid electrolyte interphase (SEI) is known to form on Li metal surfaces when in contact with organic electrolytes and functions as a passivation layer.[6,7] However, as a “hostless” electrode, the virtually infinite volumetric change during Li stripping/plating induces significant mechanical instability in the relatively fragile SEI layer, leading to the formation of cracks. The cracks locally enhance the Li-ion flux, which result in nonuniform Li deposition with dendritic morphology that can trigger an internal short circuit and compromise the safety of battery operation. Moreover, the high-surface-area ramified Li and the recurring breakdown/repair of SEI bring about continuous side reactions, severely reducing the cycle life.[8–10] In recognition of the problems associated with the “hostless” nature of Li metal, stable hosts such as layered reduced graphene oxide and nanofibers with “lithiophilic” coatings have been successfully introduced for metallic Li.[11–13] For the first time, the approach minimized the volumetric change at the whole electrode level during Li plating/stripping. Moreover, porous Li with highly increased surface area can be obtained, which reduces the effective current density and the degree of interface fluctuation during cycling, leading to more uniform Li deposition with greatly improved cycling stability. Other approaches exploring 3D conductive current collectors demonstrated similar effects in confining Li dendrites and improving cycling efficiency.[14–16] Thus, further engineering of the SEI layer on porous Li nanocomposite electrodes shall be the next leap needed to push the cycling efficiency closer to real battery operation requirements. \n\nIt is apparent from the above discussion that the quality of the SEI layer is critical for the efficient and stable operation of Li metal anodes and several requirements need to be satisfied for an ideal SEI layer.[17] First, it has to be homogeneous in all aspects (composition, morphology, etc.) to prevent only limited locations of Li metal nucleation and growth. Second, it shall possess high elastic modulus and compact structure, for theoretical predictions have shown that a solid film with modulus on the order of 1 GPa should be sufficient in suppressing dendrite.[18,19] Third, the SEI layer has to be flexible enough to accommodate the ineligible interface fluctuation during battery cycling without repeated breakdown/repair. And more importantly, high ionic conductivity of the SEI layer is essential to facilitate the easy and uniform transport of Li-ions throughout the whole electrode surface. However, native SEI can hardly meet all the requirements, which necessitates the rational design of artificial SEI. \n\nThe concept of artificial SEI has been actively explored in previous studies, and various artificial coatings have been applied on Li foil surfaces, such as polyacetylene,[20] tetraethoxysilane,[21] lithium phosphorus oxynitride,[22] ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ particles,[23,24] and ultrathin ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ film via atomic layer deposition.[25] Admittedly, these coatings are effective to some extent in suppressing side reactions and Li dendrite formation, especially under static conditions or at the initial stage of cycling. Nevertheless, the protective effects often wear off after prolonged battery operations. This can be attributed to the fact that most of these studies focused only on a single aspect of the SEI requirement, such as providing strong physical barriers or certain Li-ion conductivity, while failed to take the whole picture into consideration. Inadequate thickness or compositional control of the coatings may lead to compromised SEI homogeneity and more importantly, given the limited Li-ion conductivity or poor flexibility of the coating materials, the cracking of the artificial SEI layers during cycling will induce even greater inhomogeneity on Li metal surface, exacerbating dendrite growth and side reactions.[4,26] \n\nHerein, we propose the rational design of an artificial SEI layer, composed of $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles joined together by styrene butadiene rubber $(\\mathrm{Cu_{3}N\\mathrm{~\\ensuremath~{~+~}~}\\mathrm{SBR}})$ , which can simultaneously possess high mechanical strength, good flexibility, and high Li-ion conductivity being all indispensable for an ideal SEI. Notably, the $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles will be passivated spontaneously when in contact with metallic Li to form $\\mathrm{Li}_{3}\\mathrm{N}$ , which is among one of the fastest Li-ion conductors with ionic conductivity on the order of ${\\approx}10^{-3}–10^{-4}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1}$ at room temperature.[27–29] This can effectively facilitate the transport of Li-ions across the electrode surface, resulting in more uniform Li-ion flux. Moreover, compared to pure inorganic phase coatings, composite artificial SEI with both inorganic nanoparticles and a polymeric binder can better maintain structural integrity during Li plating/stripping thanks to the good flexibility of the SBR, which is also desirable for SEI homogeneity. Furthermore, the proposed artificial SEI can be applied via a facile solution coating process with good thickness and compositional control and also applicable to porous Li electrodes. The introduction of such a artificial SEI layer with superior Li-ion conductivity, mechanical strength, and flexibility significantly enhanced the stability of the Li metal anode both under static condition and during prolonged cycling. The Coulombic efficiency can be improved to above $97.4\\%$ with a current density up to $1\\mathrm{\\mA\\cm^{-2}}$ in corrosive carbonate electrolyte on copper (Cu) current collector and if applied on porous Li-coated polyimide– zinc oxide electrode (Li-coated $\\mathrm{PI-ZnO})$ , the coating rendered a $40\\%$ increase in cycle life when paired with Li titanate (LTO). \n\nFigure 1a schematically illustrates the fabrication process of the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ artificial SEI layer and its microstructure. $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles with a size of sub- $\\cdot100\\ \\mathrm{nm}$ were synthesized via a facile one-step reaction between $\\mathtt{C u(I I)}$ methoxide $(\\mathrm{Cu}(\\mathrm{OMe})_{2})$ and benzylamine (Figure S1, Supporting Information).[30] The resulting nanoparticles can be readily dispersed in tetrahydrofuran (THF) with SBR to form a stable colloidal solution, which can then be applied on the Li surface via doctor blade casting or drop casting to afford a conformal protection layer. When in contact with Li, $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles can be converted to $\\mathrm{Li}_{3}\\mathrm{N}$ , rendering a protective Li metal surface coating with a mechanically strong Li-ion conducting inorganic phase connected tightly within a flexible polymeric matrix. Compare to unprotected Li, the highly Li-ion conducting artificial SEI not only mechanically suppresses Li dendrite but also contributes to the even distribution of Li-ion flux across the electrode surface, resulting in more uniform Li plating/stripping behavior (Figure 1b). \n\nFigure 2a shows the scanning electron microscopy (SEM) image of the as-synthesized $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles, which clearly reveals nonagglomerated nanoparticles with size below $100\\mathrm{nm}$ A powder X-ray diffraction (XRD) pattern confirms the crystallinity of the nanoparticles, which matches well with the $\\mathrm{Cu}_{3}\\mathrm{N}$ standard (JCPDS No. 55-0308, Joint Committee on Powder Diffraction Standards, Figure 2b). Noticeably, the $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles can afford a stable dispersion in THF for days without precipitation nor chemical degradation, as little changes in the XRD pattern can be detected for samples dispersed overnight in THF (Figure 2b). Such small particle size, good dispersity and chemical stability make the $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles desirable to yield a uniform and conformal coating on the Li metal surface. \n\n![](images/1968fb3d3b909a9d2fee76cc597d72cd4a560ae77b91be0f20b8f5d235043b97.jpg) \nFigure 1.  a) Schematic illustration of the fabrication of the $\\mathsf{C u}_{3}\\mathsf{N}+\\mathsf{S B R}$ composite artificial SEI. b) Schematic illustration of the Li plating/stripping behavior of bare Li (upper figure), where the cracking of SEI results in the formation of Li-ion flux “hot spots” and Li dendrites; and the artificial SEI protected Li (lower figure), where the good mechanical properties can suppress Li dendrite formation and the high Li-ion conductivity can afford more uniform distribution of Li-ion flux. \n\n![](images/dec455fb2532cd088fceb9d63eb675bd2bbd494c338e9ab8fed8a817c8843cce.jpg) \nFigure 2.  a) SEM image of the as-synthesized $C u_{3}N$ nanoparticles. b) XRD patterns of the as-synthesized $C u_{3}N$ nanoparticles and $C u_{3}N$ nanoparticle dispersed in THF overnight. The inset picture demonstrates the good dispersity of the $C u_{3}N$ nanoparticles in THF. c) Top-view SEM image of the docto bladed $C u_{3}N+S B R$ coating on $\\mathsf{C u}$ foil. d) CV scans of the $C u_{3}N+S B R$ coating on Cu foil at a scan rate of $0.1\\ m\\vee s^{-1}$ . \n\nIn order to evaluate the electrochemical properties of the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ artificial SEI layer, it was first applied on a Cu foil current collector via doctor blading. Figure 2c shows the topview SEM image of the artificial SEI layer, where a dense and uniform composite coating can clearly be observed. The thickness ( $400~\\mathrm{nm}$ and above) of the coating layer can be changed easily by adjusting the gap size of the blade, demonstrating the facileness and great tunability of our proposed method for Li metal surface stabilization (Figure S2, Supporting Information). Cyclic voltammetry (CV) were carried out to confirm the conversion of $\\mathrm{Cu}_{3}\\mathrm{N}$ to $\\mathrm{Li}_{3}\\mathrm{N}$ in the presence of metallic Li (Figure 2d). During the first CV cycle, a main cathodic peak at ${\\approx}0.48\\mathrm{~V~}$ (vs $\\mathrm{Li^{+}/L i}$ ) can be observed, confirming the lithiation of $\\mathrm{Cu}_{3}\\mathrm{N}$ to $\\mathrm{Li}_{3}\\mathrm{N}$ and Cu. It shall be noted that the conversion reaction of $\\mathrm{Cu}_{3}\\mathrm{N}$ is only partially reversible. During the first delithiation, the anodic peak centered at ${\\approx}1.3~\\mathrm{V}$ corresponds well with the oxidation of ${\\mathrm{Cu}}^{0}$ to $\\mathrm{Cu^{+}}$ in $\\mathrm{Cu}_{3}\\mathrm{N}$ , while the anodic peak at ${\\approx}2.1\\ \\mathrm{V}$ shall be associated with the oxidation of ${\\mathrm{Cu}}^{0}$ to $\\mathrm{Cu^{+}}$ in $\\mathrm{Cu}_{2}\\mathrm{O}$ . And redox peaks belonging to both nitride and oxide can be seen in subsequent CV cycles.[30,31] Fortunately, the electrochemical potential of the Li metal anode will usually not exceed the decomposition voltage $(\\approx0.5{\\mathrm{~V~}}$ theoretically) of $\\mathrm{Li}_{3}\\mathrm{N}$ under normal operation conditions,[32] which guarantees the validity of our proposed coating as a Li-ion conducting artificial SEI on Li metal electrode. Raman spectra of the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ artificial SEI after lithiation exhibited distinctive peaks in accordance with those of standard $\\mathrm{Li}_{3}\\mathrm{N}$ powder, corroborating the CV measurements (Figure S3, Supporting Information).[33] \n\nThe morphology of Li deposition on a $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ protected Cu current collector was then studied to evaluate the dendrite suppression capability of the artificial SEI. Specially fabricated crimped separators with a Li-ion conducting area of $0.5~\\mathrm{cm}^{-2}$ were used for all the electrochemical measurements, which can provide a more accurately defined effective area, and thus current density, compare to normal separators (Figure S4, Supporting Information). The protected Cu current collectors were subjected to ten activation cycles between 0 and $0.4\\mathrm{~V~}$ at a low current density of $0.01\\mathrm{mA}\\mathrm{cm}^{-2}$ to ensure the complete conversion of $\\mathrm{Cu}_{3}\\mathrm{N}$ before being cycled galvanostatically at different current densities, and an upper cut-off voltage of $0.4\\mathrm{~V~}$ was set for the cycling to prevent the decomposition of $\\mathrm{Li}_{3}\\mathrm{N}$ . After five galvanostatic plating/stripping cycles at a current density of $0.5\\mathrm{\\mA\\cm^{-2}}$ and a capacity of $0.5\\mathrm{\\mAh\\cm^{-2}}$ , there were no observable dendrites on Cu foil protected by the mechanically robust and highly Li-ion conducting $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ artificial SEI (Figure 3a), while excessive wire-shaped Li with diameter around $1{-}2~{\\upmu\\mathrm{m}}$ has already formed on the bare $\\mathtt{C u}$ counterpart (Figure 3b). The color of the Li deposit on the protected $\\mathrm{{Cu}}$ foil remained silver and shiny, similar to that of pristine Li metal (Figure 3c). In contrast, dark gray Li was observed for deposition directly on bare Cu, stemming from a less compact Li deposition morphology (Figure 3d).[34] The effective dendrite suppression can be attributed to the Li-ion conducting artificial SEI that fostered a uniform Li-ion flux to prevent local “hot spots” as well as the high elastic modulus of the inorganic nanoparticles that mechanically impeded the dendrite formation. \n\n![](images/383ca2e10a0ff78bf061c8e32620ec7f6b32ffbf491194931c8471a6c0431423.jpg) \nFigure 3.  Top-view SEM images and the corresponding digital photographs of Li deposition after five galvanostatic plating/stripping cycles on a,c) $C\\mathsf{u}_{3}\\mathsf{N}+S\\mathsf{B}\\mathsf{R}$ artificial SEI protected $\\mathsf{C u}$ foil and b,d) bare $\\mathsf{C u}$ foil. e) Schematic showing the relationship between the misalignment angle, θ, indentation depth, $h$ , and $r$ during the initial contact of the nanoindentation measurements. f) Elastic modulus versus depth curves of a representative indentation test in which the red curve shows the modulus with correction for the misalignment between the indenter and the artificial SEI surface, and the blue curve shows the modulus without correction. \n\nThe mechanical properties of the artificial SEI were evaluated using nanoindentation. The elastic modulus versus depth curves are shown in Figure S5 (Supporting Information), in which the modulus of the artificial SEI increased from 0.71 to $0.81\\mathrm{\\GPa}$ . The slight increase in modulus was due to densification of the artificial SEI resulting from the $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticle packing under compression.[35,36] The low modulus from depth 0 to ${\\approx}1.5~\\upmu\\mathrm{m}$ was likely due to a combination of imperfect alignment between the flat punch indenter and the artificial SEI surface, and the effect of surface roughness. A simple analysis was performed to verify the effect of misalignment as shown in Figure 3e: the indenter was found to be at $\\theta=2.3^{\\circ}$ relative to the artificial SEI surface and began contact starting from one side of the circular punch as indicated by $r$ . Since $r\\approx h/\\theta$ , the contact area was a function of the indentation depth and a corrected modulus was calculated. A representative elastic modulus versus depth curve was corrected based on this analysis and is shown by the red curve in Figure 3f. The “dip” in modulus at $h<0.7~{\\upmu\\mathrm{m}}$ was related to the surface roughness of the artificial SEI (arithmetic mean roughness, $R_{\\mathrm{a}}=0.44~{\\upmu\\mathrm{m}}$ , and root mean squared roughness, $R_{\\mathrm{q}}=0.58~\\upmu\\mathrm{m})$ as shown in Figure S6 (Supporting Information). An elastic modulus on the order of 1 GPa is known to help suppress Li dendrites. \n\nCoulombic efficiency, which is defined as the ratio between the extractable and the deposited capacity, is another crucial parameter to examine for a practical Li metal anode. Although it remains a great challenge to determine the exact Coulombic efficiency of anodes with prestored Li,[11,12] measuring the value on $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ protected Cu current collectors could serve as direct evidence of the stabilizing effect our proposed artificial SEI layer when applied on Li metal surface. As can be seen from Figure 4a, at a current density of $1\\mathrm{\\mA\\cm^{-2}}$ in carbonate electrolyte (1 M lithium hexafluorophosphate in 1:1 ethylene carbonate/diethyl carbonate (EC/DEC) with $10\\ \\mathrm{wt\\%}$ fluoroethylene carbonate additive), the Coulombic efficiency of bare Cu started at around $95\\%$ and quickly decayed to merely $70\\%$ within 50 stripping/plating cycles due to the growth of Li dendrites and the continuous breakdown/repair of SEI that consumed both Li and the electrolyte. Surprisingly, the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ protected Cu demonstrated a much improved Coulombic efficiency of ${\\approx}97.4\\%$ averaged between the 20th and 70th cycles and such high efficiency performance was able to be sustain for more than 100 cycles. In addition, the overpotential increase due to the existence of the artificial SEI was minimal (Figure 4a inset), thanks to its relatively high ionic conductivity. Since the effective current density can be significantly reduced on porous Li metal anodes, Coulombic efficiency at a lower current density of $0.25\\mathrm{\\mA\\cm^{-2}}$ was also studied to better resemble the real working condition of the artificial SEI protected porous Li. With reduced current density, the Coulombic efficiency increased to as high as ${\\approx}98\\%$ , which was stable for at least 150 cycles (Figure 4b). It is known that higher cycling efficiency can be expected in ether electrolyte due to the formation of a relatively flexible oligomer SEI that could better withstand the volumetric change during battery cycling.[37] Accordingly, with the protection of the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ artificial SEI, the Coulombic efficiency at $0.25\\mathrm{\\mA\\cm^{-2}}$ was on average $98.5\\%$ for more than 300 cycles in ether electrolyte (Figure S7, Supporting Information, 1 M lithium bis(trifluoromethanesulfonyl)imide in 1:1 w/w 1,3-dioxolane/1,2-dimethoxyethane with $1\\mathrm{wt\\%}$ lithium nitrate additive). Such significant improvement in cycling efficiency, especially in the corrosive carbonate electrolyte, strongly indicates that the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ artificial SEI layer can indeed suppress Li dendrite propagation and retard the continuous breakdown/repair of the SEI on a Li metal surface. Moreover, the drastic morphological differences in the SEI layer after prolonged battery cycling strongly support the Coulombic efficiency measurements (Figures S8 and S9, Supporting Information). SEI as thick as tens of micrometers was accumulated on the bare Cu electrode while the SEI layer on the protected electrode was thin and uniform. Finally, it shall be noted that the composite coating outperformed coatings with $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles or SBR alone (Figure S10, Supporting Information). The Coulombic efficiency of the pure inorganic coating started high with a much faster decay for it is more prone to cracking without the flexible polymeric binder, demonstrating the synergistic effect between the inorganic and the polymeric phase. And there existed an optimal coating thickness ${\\mathrm{\\Omega}}^{}\\approx1{\\mathrm{~}}\\upmu\\mathrm{m}$ , 1 mil doctor blade) for the artificial SEI layer; coatings that are too thin do not provide sufficient mechanical property to suppress Li dendrite propagation while coatings that are too thick compromise the impedance of the cell (Figure S11, Supporting Information). \n\n![](images/bd71bbbb038a68f0795fe94b1eba8944e6f8df4a132ba42528601846a33a5fcd.jpg) \nFigure 4.  Coulombic efficiency of $C\\mathsf{u}_{3}\\mathsf{N}+S\\mathsf{B}\\mathsf{R}$ artificial SEI protected Cu foil and bare Cu foil at a current density of a) $\\mathsf{1\\ m A\\ c m^{-2}}$ (cycling capacity $\\mathsf{l}\\mathsf{m A h c m}^{-2}$ ; inset, the corresponding voltage profiles at the 20th cycle) and b) $0.25~\\mathsf{m A c m}^{-2}$ (cycling capacity $0.5\\mathsf{m A h c m^{-2}},$ ). c) SEM image and digital photography of the $\\mathsf{C u}_{3}\\mathsf{N}+\\mathsf{S B R}$ (1 mil) protected Li metal foil. d) The equivalent circuit for the interpretation of the impedance spectra. e) Summary of the $R_{\\mathsf{S E I}}$ value as a function of cycle number. \n\nTo further investigate the stabilizing effect of the artificial SEI layer, $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ was doctor bladed onto a Li foil surface (Figure $\\scriptstyle4C$ ), and electrochemical impedance spectroscopy measurements in a symmetric cell configuration were performed under both static and continuous cycling conditions in a EC/DEC electrolyte. The equivalent circuit for the interpretation of the impedance spectra is shown schematically in Figure 4d. The Ohmic part of the cell $(R_{\\mathrm{s}})$ reflects a combined resistance of the electrolyte, separator, and electrodes. $R_{\\mathrm{SEI}}$ and CPE1 are the resistance and capacitance of the SEI layer on the surface of two electrodes, which corresponds to the semicircle at high frequencies. $R_{\\mathrm{{ct}}}$ and $C_{\\mathrm{dl}}$ are the charge transfer resistance and its relative double-layer capacitance, which appear as a semicircle at medium frequencies. $Z_{\\mathrm{w}}$ represents the Warburg impedance related to a combined effect of Li-ions diffusing across the electrode–electrolyte interfaces, corresponding to the sloped line at low frequency end.[38] Under an open circuit potential condition (Figure S12, Supporting Information), the impedance of bare Li foil increased with increasing storage time, indicating that the native SEI on Li metal cannot fully passivate the surface. On the contrary, only a small increase in impedance was observed for the protected Li foil thanks to the compact $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ layer that hindered the reaction between the Li metal and the electrolyte. When the symmetric cells were cycled galvanostatically at a current density of $0.5\\mathrm{\\mA\\cm^{-2}}$ and a capacity of $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ (Figure S13, Supporting Information), the size of the semicircle at medium frequency decreased significantly with the cycle number for a bare Li foil due to the increase in Li surface area (dendrite formation) while the variation in $R_{\\mathrm{{ct}}}$ was much smaller for the protected Li foil. This further confirmed the dendrite suppression capability of the artificial SEI. More importantly, a continuous increase in the $R_{\\mathrm{SEI}}$ value was observed for the bare Li foil, which indicates the repeated breakdown/repair of the native SEI during cycling (Figure 4e). Nevertheless, Li protected by the artificial SEI layer showed nearly constant $R_{\\mathrm{SEI}}$ throughout 200 cycles. Thus, it is evident that the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ coating is beneficial in forming a stable and less resistive SEI layer on Li metal surface during prolonged battery cycling. \n\nFinally the protective effects of the $\\mathrm{Cu}_{3}\\mathrm{N}+\\mathrm{SBR}$ artificial SEI was tested on a novel 3D porous Li metal anode, which was fabricated via thermal infusion of molten Li into zinc oxide coated polyimide nanofibers (Li-coated $\\mathrm{PI-ZnO}$ , Figure S15, Supporting Information).[12] Thanks to the high porosity and rapid liquid intake of the Li-coated $\\mathrm{PI-ZnO}$ , the coating solution can be drop casted and evenly spread across the electrode to afford conformal coating. Due to the reason that it remains challenging to determine the exact Coulombic efficiency value of electrodes with prestored Li,[11,12] a semiquantitative method was adopted instead. Namely, the high areal capacity LTO electrode $(\\approx3\\mathrm{\\mAh\\cm^{-2}},$ ) was paired with an oversized Li metal anode $(\\approx10\\mathrm{mAh}\\mathrm{cm}^{-2}$ , Figure 5a) such that the cycle life of the cells can reflect the Coulombic efficiency of the anode well. If the Li metal electrode has a Coulombic efficiency of $\\approx90\\%$ , $0.3\\mathrm{\\mAh\\cm^{-2}}$ of Li will be lost at each cycle and the cell will start to decay at ${\\approx}23$ cycles $(0.3\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}\\times23=$ oversized $7\\mathrm{mAh}\\mathrm{cm}^{-2}$ of Li). If the efficiency is lower, the cycle life will be even shorter ( $80\\%$ : 12 cycles; $70\\%$ : 8 cycles). Notably, LTO is a good choice as the counter electrode for it has no prestored Li and the cycling efficiency can be nearly $100\\%$ despite the initial cycle $(\\approx90\\%$ , Figure 5b black line shows the stable cycling of LTO with highly oversized Li, $750~\\upmu\\mathrm{m})$ so that Li lost can be mainly attributed to the anode side. As can be seen in Figure 5b, at a cycling current density of $\\approx1.5\\mathrm{\\mA\\cm^{-2}}$ , a Li foil with $50~{\\upmu\\mathrm{m}}$ in thickness (theoretical capacity $10\\ \\mathrm{mAh\\cm^{-2}}$ , orange line) started to decay at 20 cycles, indicating that the Coulombic efficiency is ${\\approx}88.3\\%$ . The performance was even worse for an electrodeposited Li (green line), which started to decay only at eight cycles (Coulombic efficiency $\\approx70\\%$ . However, with the introduction of a stable host for Li, no obvious decay can be observed for a Li-coated $\\mathrm{PI-ZnO}$ electrode for the first 65 cycles, corresponding to a Coulombic efficiency of ${\\approx}96.4\\%$ (blue line). \n\n![](images/03426ef21133c1d8da48ee77dbebc5081cd342446082d5254ccdf7b01f77f6b7.jpg) \nFigure 5.  a) Stripping capacity of Li-coated $\\mathsf{P l-Z n O}$ anode after the application of the $C u_{3}N+S B R$ artificial SEI with an areal capacity of $\\mathsf{l o m A h c m^{-2}}$ . b) Discharge capacity of various Li metal anode-LTO cathode cells for the first 100 galvanostatic cycles in EC/DEC with $1\\:\\mathrm{vol\\%}$ vinylene carbonate. Rate was set at $0.2\\mathsf{C}$ for the first two cycles and $0.5\\mathrm{~C~}$ for later cycles (1 $\\mathsf{C}=170\\mathsf{m A}\\mathsf{g}^{-1};$ . The areal capacity of the cathodes was ${\\approx}3\\ m A h\\ c m^{-2}$ . \n\nFurther improvement in cycle life can be clearly observed after the artificial SEI protection (red line), where stable cycling was sustained for at least 90 cycles (Coulombic efficiency ${\\approx}97.4\\%$ , the actual value shall be even higher considering the low first cycle Coulombic efficiency of LTO). The indirect method demonstrates the effectiveness of the artificial SEI coating on further improving the performance of porous Li metal anode toward practical battery applications.[39] \n\nIn conclusion, the quality of the SEI layer is a critical determinant for the efficient and stable operation of Li metal anodes, which needs to be mechanically strong yet flexible enough to accommodate volume change during cycling and be extremely homogeneous in all aspects including not only composition, morphology but also ionic conductivity. To realize such a goal, we proposed the rational design of a composite artificial SEI layer, consisted of sub- $100~\\mathrm{nm}$ $\\mathrm{Cu}_{3}\\mathrm{N}$ nanoparticles connected tightly within a polymeric binder matrix, which can be converted into a highly Li-ion conducting $\\mathrm{Li}_{3}\\mathrm{N}$ phase on a Li metal surface. Compared with single-component artificial SEI layers, pronounced synergistic effects can be observed between the inorganic nanoparticles and the polymeric binders; namely, the closely packed inorganic phase provided mechanical stiffness to suppress Li dendrite propagation while the polymeric phase maintained the integrity of the film without cracking in the presence of the significant interface fluctuation during battery cycling. More importantly, the high Li-ion conductivity of the artificial SEI guaranteed uniform Li-ion flux across the whole electrode surface and prevented the formation of local “hot spots.” And the facile solution processing of the artificial SEI not only offered great tunability of the film but also made it applicable to porous Li anodes with stable host. Thanks to its outstanding Li-ion conductivity, mechanical properties, and chemical stability, the artificial SEI layer can effectively suppress Li dendrite formation and protect the Li metal surface from repeated SEI breakdown/repair under both static and long-term cycling conditions. Moreover, the cycling efficiency of the protected porous Li metal anode can be clearly improved when paired with LTO, demonstrating our proposed approach as a promising way to tackle the problem of Li metal, and push porous Li one step closer toward practical applications for next-generation rechargeable batteries. \n\n# Experimental Section \n\nThe experimental methods can be found in the Supporting Information. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThe work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the US \n\nDepartment of Energy under the Battery Materials Research (BMR) program and the Battery 500 Consortium program. \n\nReceived: October 13, 2016 Revised: November 7, 2016 Published online: \n\n[1]\t P. G.  Bruce, S. A.  Freunberger, L. J.  Hardwick, J.-M.  Tarascon, Nat. Mater. 2012, 11, 19. \n[2]\t X.  Wang, L.  Fan, D.  Gong, J.  Zhu, Q.  Zhang, B.  Lu, Adv. Funct. Mater. 2016, 26, 1104. \n[3]\t Y.  Yang, B.  Wang, J.  Zhu, J.  Zhou, Z.  Xu, L.  Fan, J.  Zhu, R.  Podila, A. M. Rao, B. Lu, ACS Nano 2016, 10, 5516. \n[4]\t W.  Xu, J.  Wang, F.  Ding, X.  Chen, E.  Nasybulin, Y.  Zhang, J.-G. Zhang, Energy Environ. Sci. 2014, 7, 513. \n[5]\t H.  Kim, G.  Jeong, Y.-U.  Kim, J.-H.  Kim, C.-M.  Park, H.-J.  Sohn, Chem. Soc. Rev. 2013, 42, 9011. [6]\t E. Peled, J. Electrochem. Soc. 1979, 126, 2047. \n[7]\t R.  Cao, J.  Chen, K. S.  Han, W.  Xu, D.  Mei, P.  Bhattacharya, M. H. Engelhard, K. T. Mueller, J. Liu, J. G. Zhang, Adv. Funct. Mater. 2016, 26, 3059. \n[8]\t D. Aurbach, E. Zinigrad, Y. Cohen, H. Teller, Solid State Ionics 2002, 148, 405. \n[9]\t G.  Zheng, S. W.  Lee, Z.  Liang, H.-W.  Lee, K.  Yan, H.  Yao, H.  Wang, W. Li, S. Chu, Y. Cui, Nat. Nanotechnol. 2014, 9, 618. \n[10]\t K.  Yan, H.-W.  Lee, T.  Gao, G.  Zheng, H.  Yao, H.  Wang, Z.  Lu, Y. Zhou, Z. Liang, Z. Liu, S. Chu, Y. Cui, Nano Lett. 2014, 14, 6016. \n[11]\t D.  Lin, Y.  Liu, Z.  Liang, H.-W.  Lee, J.  Sun, H.  Wang, K.  Yan, J.  Xie, Y. Cui, Nat. Nanotechnol. 2016, 11, 626. \n[12]\t Y. Liu, D. Lin, Z. Liang, J. Zhao, K. Yan, Y. Cui, Nat. Commun. 2016, 7, 10992. \n[13]\t Z. Liang, D. Lin, J. Zhao, Z. Lu, Y. Liu, C. Liu, Y. Lu, H. Wang, K. Yan, X. Tao, Y. Cui, Proc. Natl. Acad. Sci. USA 2016, 113, 2862. \n[14]\t X.-B. Cheng, H.-J. Peng, J.-Q. Huang, F. Wei, Q. Zhang, Small 2014, 10, 4257. \n[15]\t R. Zhang, X.-B. Cheng, C.-Z. Zhao, H.-J. Peng, J.-L. Shi, J.-Q. Huang, J. Wang, F. Wei, Q. Zhang, Adv. Mater. 2016, 28, 2090. \n[16]\t S.  Jin, S.  Xin, L.  Wang, Z.  Du, L.  Cao, J.  Chen, X.  Kong, M.  Gong, J. Lu, Y. Zhu, H. Ji, R. S. Ruoff, Adv. Mater. 2016, 28, 9094. \n[17]\t X.-B.  Cheng, R.  Zhang, C.-Z.  Zhao, F.  Wei, J.-G.  Zhang, Q.  Zhang, Adv. Sci. 2016, 3, 1500213. \n[18]\t C. Monroe, J. Newman, J. Electrochem. Soc. 2005, 152, A396. \n[19]\t G.  Stone, S.  Mullin, A.  Teran, D.  Hallinan, A.  Minor, A.  Hexemer, N. Balsara, J. Electrochem. Soc. 2012, 159, A222. \n[20]\t D. Belov, O. Yarmolenko, A. Peng, O. Efimov, Synth. Met. 2006, 156, 745. \n[21]\t G. A.  Umeda, E.  Menke, M.  Richard, K. L.  Stamm, F.  Wudl, B. Dunn, J. Mater. Chem. 2011, 21, 1593. \n[22]\t N. J. Dudney, J. Power Sources 2000, 89, 176. \n[23]\t H.  Lee, D. J.  Lee, Y.-J.  Kim, J.-K.  Park, H.-T.  Kim, J. Power Sources 2015, 284, 103. \n[24]\t D. J.  Lee, H.  Lee, Y. J.  Kim, J. K.  Park, H. T.  Kim, Adv. Mater. 2016, 28, 857. \n[25]\t A. C. Kozen, C.-F. Lin, A. J. Pearse, M. A. Schroeder, X. Han, L. Hu, S.-B. Lee, G. W. Rubloff, M. Noked, ACS Nano 2015, 9, 5884. \n[26]\t N. W. Li, Y. X. Yin, C. P. Yang, Y. G. Guo, Adv. Mater. 2016, 28, 1853. \n[27]\t U. V. Alpen, A. Rabenau, G. Talat, Appl. Phys. Lett. 1977, 30, 621. \n[28]\t G.  Ma, Z.  Wen, M.  Wu, C.  Shen, Q.  Wang, J.  Jin, X.  Wu, Chem. Commun. 2014, 50, 14209. \n[29]\t M.  Wu, Z.  Wen, Y.  Liu, X.  Wang, L.  Huang, J. Power Sources 2011, 196, 8091. \n[30]\t R.  Deshmukh, G.  Zeng, E.  Tervoort, M.  Staniuk, D.  Wood, M. Niederberger, Chem. Mater. 2015, 27, 8282. \n[31]\t N.  Pereira, L.  Dupont, J.  Tarascon, L.  Klein, G.  Amatucci, J. Electrochem. Soc. 2003, 150, A1273. \n[32]\t W. D.  Richards, L. J.  Miara, Y.  Wang, J. C.  Kim, G.  Ceder, Chem. Mater. 2015, 28, 266. \n[33]\t Y. Nakamori, S. Orimo, Mater. Sci. Eng. B 2004, 108, 48. \n[34]\t J.  Dahn, presented at Scalable Energy Storage: Beyond Lithium Ion, San Jose, CA, USA, August 2009. \n[35]\t C. J. Buchko, M. J. Slattery, K. M. Kozloff, D. C. Martin, J. Mater. Res. 2000, 15, 231. \n[36]\t J.  Ballarre, E.  Jimenez-Pique, M.  Anglada, S. A.  Pellice, A. L. Cavalieri, Surf. Coat. Technol. 2009, 203, 3325. \n[37]\t D.  Aurbach, O.  Youngman, Y.  Gofer, A.  Meitav, Electrochim. Acta 1990, 35, 625. \n[38]\t Q.-C. Zhuang, S.-G. Sun, S.-D. Xu, X.-Y. Qiu, Y.-H. Qiang, Diagnosis of Electrochemical Impedance Spectroscopy in Lithium-Ion Batteries, INTECH Open Access Publisher, Rijeka, Croatia 2012. \n[39]\t J.  Qian, B. D.  Adams, J.  Zheng, W.  Xu, W. A.  Henderson, J.  Wang, M. E. Bowden, S. Xu, J. Hu, J. G. Zhang, Adv. Funct. Mater. 26, 7094. " + }, + { + "id": "10.1002_advs.201600190", + "DOI": "10.1002/advs.201600190", + "DOI Link": "http://dx.doi.org/10.1002/advs.201600190", + "Relative Dir Path": "mds/10.1002_advs.201600190", + "Article Title": "Extremely Stretchable Strain Sensors Based on Conductive Self-Healing Dynamic Cross-Links Hydrogels for Human-Motion Detection", + "Authors": "Cai, GF; Wang, JX; Qian, K; Chen, JW; Li, SH; Lee, PS", + "Source Title": "ADVANCED SCIENCE", + "Abstract": null, + "Times Cited, WoS Core": 827, + "Times Cited, All Databases": 870, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000397020800006", + "Markdown": "# Extremely Stretchable Strain Sensors Based on Conductive Self-Healing Dynamic Cross-Links Hydrogels for Human-Motion Detection \n\nGuofa Cai, Jiangxin Wang, Kai Qian, Jingwei Chen, Shaohui Li, and Pooi See Lee\\* \n\nStretchable, wearable, flexible, and human friendly soft electronic devices are of significance to meet the escalating requirements of increasing complexity and multifunctionality of modern electronics.[1–6] Strain sensors can generate repeatable electrical changes upon mechanical deformations. They have found particular interest and broad applications in robotics, sports, health monitor, and therapeutics, etc. To date, several representative strain sensors using carbon nanotubes,[7–9] metal/ semiconductor,[10–12] graphene,[13–15] conductive polymer,[16,17] and microfluidic[18,19] as conductive materials combining with elastomeric substrates have been successfully fabricated. However, most of these devices can only be stretched to a very limited extent (usually less than $200\\%$ . Lewis and co-workers[20] have developed a capacitive soft strain sensor using an ionically conductive fluid and silicone elastomer as the conductor and dielectric/encapsulant respectively, which can be stretched up to $700\\%$ , but the gauge factor is small $(0.348\\pm0.11)$ ). We can define the gauge factor as $(\\Delta R/R_{0})/\\varepsilon.$ , where $\\Delta R/R_{0}$ is relative resistance change, $R_{0}$ is the resistance at $0\\%$ strain, $R$ is the resistance under stretch, and $\\varepsilon$ is the applied strain.[21] In addition, introducing self-healing properties to these soft electronic devices that can repeatably recover mechanical and electrical performance under room temperature, even at the same damaged location or under extremely stretchable situation, is of high importance to avoid the degradation of the device performance during the deformation. \n\nNowadays, self-healing materials have attracted increasing attention, especially in soft electronics field. Haick and coworkers[22] have reported a self-healing flexible sensing platform by dispersing metal particles in polyurethane diol as selfhealing electrode. Bao and co-workers[23] have demonstrated a self-healing electronic sensor skin based on nanostructured μNi particles-supramolecular organic composite. Park and coworkers[24] have developed self-healing conductive hydrogel by polymerizing pyrrole in agarose solution. However, none of these self-healing electronic devices can be stretched over \n\n$100\\%$ . Recently, there are intense research on highly stretchable hydrogels, which are mainly focusing on ionic conductors due to their excellent transparency and small resistance variation under high stretching states.[25–29] In particular, conductive hydrogels are promising materials for the fabrication of ionic skin, bioelectrodes, and biosensors because many hydrogels with high water concentration have biocompatibility properties.[24,30–32] Therefore, it is of great interest to fabricate highly stretchable self-healing strain sensor by combining the advantages of both biocompatible hydrogels and electronic conductors for applications in robotics, human motion detection, entertainment, medical monitoring, and treatment etc. \n\nHerein, we introduce a new type of extremely stretchable self-healing piezoresistive strain sensor using different electronic conductors comprised of single wall carbon nanotube (SWCNT), graphene, and silver nanowire in self-healing hydrogel (SWCNT, graphene, and silver nanowire/hydrogel) as the conductive sensing channel built on a commercial transparent elastic substrate. The conductive hydrogel exhibits a fast self-healing capability which can restore $98\\pm0.8\\%$ of its initial conductivity within $3.2\\mathrm{~s~}$ healing time. Moreover, no external stimuli (such as heat, pH, light, or catalyst) are required. The fast self-healing process of the SWCNT/hydrogel ensures rapid recovery of the electrical property of the sensor after being released to the relaxed state and avoids the degradation of the device performance during the large deformation. The selfhealing strain sensor is capable of monitoring strain, flexion, and twist forces. Moreover, it can measure and withstand strain up to $100\\%$ , with high gauge factor and excellent cycling stability. Based on these key features, the self-healing strain sensor can be used to accurately detect large-scale human motion by embedding it in gloves, garments, or directly attaching it on skin. The present methodology developed paves the way for practical applications of highly stretchable self-healing strain electronic devices. \n\nThe fabrication process of conductive hydrogel is illustrated in Figure 1a (see the Experimental Section in the Supporting Information for details). Figure 1b illustrates the key reaction in forming crosslinked hydrogel. Borax, the salt of a strong base and a weak acid, is hydrolyzed in aqueous solution, yielding a boric acid/tetrafunctional borate ion. In the gelation experiments, trigonal planar $\\mathrm{B}(\\mathrm{OH})_{3}$ and tetrahedral $\\mathrm{B}(\\mathrm{OH})_{4}^{-}$ exist as monomeric species due to the low concentration of borax employed (0.02 m). $\\mathrm{\\DeltaB(OH)_{3}}$ is capable of complexing polyvinyl alcohol (PVA), however, it cannot produce polyol gels. The main reason is that the complexation reaction occurs through the attachment of boron to adjacent alcohol groups of the same polymeric chain and this prevents cross-linking from taking place. Therefore, the crosslinked hydrogel is formed via tetrafunctional borate ion interaction with –OH group of PVA. The process is particularly effective in forming 3D gel networks. The hydrogen-bonding between tetrafunctional borate ion and –OH group provides the self-healing function because the cross-link is so weak that it is neither resemblance of covalent bond character nor esterification involved.[33–35] The hydrogen-bonding can be easily broken and reformed, allowing the hydrogel to self-heal and reform. The cross-links are dynamically associated and dissociated readily under room temperature. The network cross-linked by weak hydrogen-bonding is easily disrupted by a mechanical deformation, however, it is relatively facile for the bonds to reform due to proximity of plenty –OH groups and borate ions, hence allowing self-healing at room temperature. In addition, the PVA-borax hydrogel exhibits non-Newtonian behavior, resulting in flow under low stress and limited dimensional stability.[35,36] Therefore, the sufficient mobility of polymer chain and free tetrafunctional borate ions enables the hydrogen bond across broken interfaces to trigger the self-healing process rapidly and without the need of external stimuli. Although the PVA itself can form hydrogel and autonomously self-healing property according to the previous reports, the concentration of the PVA used is very high and the stretchability is limited.[37–39] Before forming the hydrogel, SWCNT and $4\\mathrm{\\mt\\%}$ PVA solution were homogeneously mixed under the surfactant assistance of BYK 348 which is a polyether modified siloxane (purchased from BYKChemie GmbH). The SWCNT and water are wrapped in the 3D networks during the hydrogel crosslinking process, thereby the conductive self-healing hydrogel was formed as shown in Figure 1c. It is worth noting that most of the free volume (or pores) within the hydrogel is taken up by water. The hydrogel is composed of water with weight percentage more than $95\\ \\mathrm{wt\\%}$ . The scanning electron microscope (SEM) micrographs taken from freeze-dried SWCNT/hydrogel are shown in Figure 1d,e. The microstructure of the freeze-dried SWCNT/hydrogel is 3D porous networks cross-linked by the SWCNT and some immobilized polymer. The porous structure of the SWCNT and polymeric network inside the SWCNT/hydrogel is highly beneficial to the stretchability and facilitating rapid response of hydrogels. In order to reveal the interactions between the PVA and tetrafunctional borate ion, Fourier transform infrared spectroscopy (FTIR) experiment was conducted on Spectrum GX FTIR Spectrometer. As shown in Figure S1 (Supporting Information), the broad and strong peak around $3400~\\mathrm{cm}^{-1}$ is attributed to the symmetrical stretching vibration of –OH groups. The –OH stretching peak is sensitive to hydrogen bonding. Compared with pure PVA, the –OH stretching peak shifts to a higher wavenumber and the peak is enhanced after formation of the hydrogel, indicating the presence of hydrogen bonding interactions between the hydroxyl groups on the PVA molecular chains and tetrafunctional borate ion.[40,41] In addition, dynamic mechanical measurements of the pure hydrogel and SWCNT/ hydrogel were carried out to investigate their rheological properties. Figure S2 (Supporting Information) shows the changes in the storage $\\mathbf{\\vec{G}}^{\\prime}$ , solid symbols) and loss modulus ( $\\mathbf{{{G}}^{\\prime\\prime}}$ , hollow symbols) as a function of angular frequency for hydrogel and SWCNT/hydrogel. It can be seen that the presence of SWCNT raises the moduli and enhances the elastic response of the hydrogel. In addition, both hydrogels have a solid behavior with the storage modulus exceeding the loss modulus over the entire frequency range. \n\n![](images/0794dec3844f4b4dbd95611562e51a077d271d258a52b72b554f6ccb785f151e.jpg) \nFigure 1.  a) The fabrication process of conductive hydrogel. b) Crosslinking reaction between PVA and tetrafunctional borate ion. c) Photo image of SWCNT/hydrogel. d,e) SEM images of the freeze-dried SWCNT/hydrogel. \n\nFigure $2\\mathsf{a}_{1}\\mathsf{-}\\mathsf{a}_{3}$ shows the representative optical microscope images of how the SWCNT/hydrogel was healed after being completely separated by a scapel. The two fractured surfaces rapidly contact each other after the scapel was removed. The cutting groove was partially healed after $30~\\mathrm{s}$ and totally restored to normal after $60~\\mathrm{s}$ at room temperature without any external assistance (such as heat, light, and force). To further investigate the healing property of the SWCNT/hydrogel and recovery of the conductivity, the SWCNT/hydrogel was completely bifurcated and then the two furcated parts were rapidly brought together. Figure 2b presents the resistance changes over time of the SWCNT/hydrogel during the cutting and healing process. Once the conductive hydrogel was completely cut off, an open circuit was formed and the resistance changed to infinity. As the two furcated parts were brought together, the resistance dropped quickly and the resistance reached a constant value within $3.2~\\mathrm{s}$ . In addition, the self-healing efficiency of the SWCNT/hydrogel was calculated by $\\mathrm{Rr/Ri}$ (Rr is the recovered conductivity and Ri is the initial conductivity). $\\mathrm{Rr/Ri}$ is $98.6\\%$ after healing for 3.2 s. It is worth noting that the resistance is lower than that of original value at the moment the two furcated parts get in contact, which is due to the transfer of free ions in the hydrogel, similar phenomenon was observed in the reduced graphene oxide based hydrogel.[42] Figure 2c shows the repetitive cutting-healing processes with five cycles at the same location. The resistance of the sample is relatively stable during the cycling. The high self-healing efficiency was observed in each cutting-healing process (Figure S3, Supporting Information). The average efficiencies are $98\\pm0.8\\%$ for the five selfhealing cycles within about $3.2\\mathrm{~s~}$ , indicating the SWCNT/ hydrogel possesses significant and repeatable electrical restoration performance. \n\n![](images/1ec6a1cf532840af878d8c80008f3d00e50a5cce36b9545c1be820824d2b6aee.jpg) \nFigure 2.  a) In situ self-healing optical images of the SWCNT/hydrogel at ro noomf tehempelercatruicrea,l the healing time of $(\\mathsf{a}_{1}\\mathrm{-}\\mathsf{a}_{3})$ are 0, 30, 60 s, respectively. b) Time evolutio healing process by resistance measurements under ambient conditions. c) cycling of the cutting-healing processes at the same location. d) Circuit comprises self-healing SWCNT/hydrogel in series with an LED indicator, d1) undamaged, ${\\sf d}_{2}^{\\prime}$ ) completely bifurcated, and ${\\sf d}_{3}$ ) electrical healing. \n\nThe self-healing property of SWCNT/hydrogel was also demonstrated on a complete circuit composed of a LED indicator with SWCNT/hydrogel as the conductor, as shown in Figure $2\\mathrm{d}_{1}{-}\\mathrm{d}_{3}$ . The LED indicator was successfully lighted when a driving voltage of $5\\mathrm{~V~}$ was applied. The LED indicator was extinguished when the SWCNT/hydrogel was completely bifurcated and the circuit became open-circuit state. Once the two furcated parts were partially brought together, the circuit was restored and the LED indicator could be lighted up again. The demonstration here illustrates that the SWCNT/hydrogel has great potential in applications of self-healing electronic device such as biosensors, electronic skin, wearable electronics, and so on. \n\nTo evaluate the performance of the strain sensor, we realized the self-healing piezoresistive strain sensor using the SWCNT/ hydrogel as conductor, and Scotch permanent clear mounting tape (VHB 4010, 3 m) as elastomeric substrates and encapsulant, as shown in Figure 3a. The high stretchability of both SWCNT/hydrogel and VHB tape allowed the self-healing strain \n\nsensor to remain intact up to $100\\%$ strain, the highest value for electronic strain sensor so far, to the best of our knowledge.[43–45] The excellent performances of the device are derived from all parts of the device or their coordination with each other. Although the SWCNT/hydrogel itself could not be recovered to the initial state under extreme strain conditions, it can work well when attached to the VHB tape. A strain sensor using the hydrogel without the electronic conducting component (SWCNT) was also prepared on the elastic substrate with the same parameters for comparison. Relative resistance changes versus strains are shown in Figure 3b. The relative resistance change increases with increasing tensile strain. A relative resistance change $[(R\\ -R_{0})/R_{0}\\ =$ $\\Delta R/R_{0}$ , $R_{0}$ is the resistance at $0\\%$ strain, $R$ is the resistance under stretch] of $1514\\%$ was observed at $100\\%$ strain for $\\operatorname{SWCNT}/$ hydrogel, the sensitivity is nearly three times higher than that of the hydrogel without electronic conductor $(533\\%)$ . The large resistance change is highly desired for strain sensing applications, which is prerequisite for high sensitivity. Moreover, the SWCNT/hydrogel based strain sensor also showed reproducible and reliable responses to the small strain from $2\\%$ to $100\\%$ (Figure S4, Supporting Information). These results indicate that the SWCNT/hydrogel based strain sensor can work well from small strain to extreme strain. There are two aspects leading to the piezoresistive effects of SWCNT/ hydrogel: one is the intrinsic piezoresistivity of the hydrogel, the other is the change of the contact conditions of SWCNT for electron conduction, such as contact area, loss of contacts and spacing variations upon stretching, and so on. The electrical conductivity of hydrogel without electronic conductor comes from ions conductivity (such as $\\mathrm{\\DeltaNa^{+}}$ , $\\mathrm{H^{+}}$ in the hydrogel).[26,32] In addition, the relative resistance changes versus strains of the strain sensor can fit into a parabolic equation $\\begin{array}{r}{\\mathrm{y}=\\mathrm{A}\\varepsilon^{2}+\\mathrm{B}\\varepsilon+\\mathrm{C}}\\end{array}$ , where y is the relative resistance changes and $\\varepsilon$ is the tensile strain.[23,46] There is no relative resistance change when there is no strain applied to the sensor, so C is zero in the equation. Moreover, the value A can be defined as the sensitivity factor. Larger A value leads elativ changes, corresponding to higher sensitivity in the sen Hence, the sensitivity of the quation in Figure 3b. It c based strain sensor without electronic co the SWCNT/ hydrogel bas he hydrogel without ith the experiment shows the photographs based self-healing strain sensor stretched to different s \n\nGauge factor represents the sensitivity of the sensors. Usually, brittle or poorly stretchable conductive materials have higher gauge factor. However, these materials do not possess or only sustain small stretchability. A relatively small strain could result in an irreversible fracture and lead to an infinite gauge factor. In the cases that high stretchability is required, the gauge factor of SWCNT/hydrogel was 0.24 at $100\\%$ strain and increased to 1.51 at $100\\%$ strain (Figure S6, Supporting Information). The gauge factor is higher than that of the hydrogel without electronic conductor $\\mathrm{(from~0.09~}$ at $100\\%$ strain to 0.53 at $100\\%$ strain), and other piezoresistive electronic strain sensor (0.06 at $20\\%$ strain)[8] and capacitive soft strain sensors based on ionic conductor $(0.348\\pm0.11$ at $70\\%$ strain).[20] Although some strain sensors exhibit much higher gauge factors, the poor stretchability and lack of self-healing capability restrict their applications under rigorous mechanical deformations.[47–49] \n\n![](images/2e61caf862878f8c3c2519c8fe569e61940e75b7a72bd5c359fde572d9a5d0df.jpg) \nFigure 3.  a) A piezoresistive strain sensor was fabricated by sandwiching a layer of conductive hydrogel between two layers of commercial tape (VHB 4010, 3 m)), which were then connected to two metallic electrodes, the piezoresistive strain sensor exhibited high extensibility up to $100\\%$ . b) Plot of relative resistance change versus strain for SWCNT/hydrogel and hydrogel without electronic-conductor-based strain sensors. The equation represents a parabolic equation $y=\\mathsf{A}\\varepsilon^{2}+\\mathsf{B}\\varepsilon+\\mathsf{C}$ where y is the relative resistance changes and $\\varepsilon$ is the tensile strain. c) Variation of normalized resistances as a function of flexion angle from $0^{\\circ}$ to $\\overline{{150^{\\circ}}}$ , inset presents the definition of flexion angle with bending radius of $2c m$ . d) Variation of normalized resistances as a function of twist angle up to two revolutions. Equations in (c) and (d) represent a parabolic equation $y=\\mathsf{A}\\theta^{2}+\\mathsf{B}\\theta+\\mathsf{C}$ , where y is the resistance changes and $\\theta$ is the flexion or twist angle. Error bars indicate standard deviation based on measurements of three devices. \n\nThe responses of the SWCNT/hydrogel based strain sensor for other types of deformation such as flexion and twist which are related to human body movements were also tested. Figure 3c displays the resistance change as a function of flexion angle for the SWCNT/hydrogel based strain sensor. When the sensor was flexed, tensile stress built up at the outer curvature and compressive force built at the inner curvature. The conductive SWCNTs are separated from one another at the outer curvature and approached closer to one another at the inner curvature. However, the separated SWCNT played a dominant role for the device, thereby the resistance increased with increasing flexion angle. It can be seen that the resistance increased to $118\\%$ from its original value with bending angle increasing from $0^{\\circ}$ to $150^{\\circ}$ . \n\nWhen the strain sensor was twisted, the resistance changes versus twist angle still obeys the flexion parabolic equation within the twist angle of less than $540^{\\circ}$ as shown in the Figure 3d. However, the conductive SWCNT will be separated from one another around the twist point under larger twist angle (more than $540^{\\circ})$ ), hence, the resistance of the device rapidly increases with increasing twist angle that detaches the SWCNT contacts or entanglements. The sensor responds to the twist angle with a good sensitivity, the resistance increases to $457\\%$ from the value of the untwisted state after two revolutions $(720^{\\circ})$ as shown in Figure 3d. The stability of the sensor was also investigated by repeatedly applying $70\\%$ stretching strain to the sensor and the resistance was measured at the released state (Figure S7, Supporting Information). The resistance of the sensor remains almost constant with minor fluctuations within $10\\%$ within the first 700 cycles strain test (between $0\\%$ to $700\\%$ strain). However, the largest resistance fluctuations were observed after 700 cycles due to partial water evaporation of the hydrogel during the long-term cycles. The loss of water from hydrogels might become significant in long-term cycles, which can be reduced by an appropriate encapsulation. Finding ideal packaging materials and technology for long lifetimes is a large undertaking beyond the scope of this paper. We suggest that SWCNT/hydrogel with $100\\%$ stretchability is a superior candidate for strain sensing applications, considering the fast self-healing property and significantly improved piezoresistive responses compared to the hydrogel without electronic conductor counterparts. \n\n![](images/bb7278d95b04ba5e6df94e7c3c2748e6da109b7b07ec6aec69981a67cac45d58.jpg) \nFigure 4.  Monitoring various human motion in real time a) Relative resistance changes versus time for the bending and release of the index finger, the inset shows the sensor was fixed on a white cotton glove. b) Relative resistance changes versus time when bending the knee at different angles, the insets show the the sensor mounted on the knee at different bending angles at $79.8^{\\circ}$ , $92.5^{\\circ}$ , $122.7^{\\circ}$ , respectively. c) Relative resistance changes versus time for the neck bending and release, the inset presents the the sensor directly attached on the neck. d) Relative resistance changes versus time for the elbow bending and release, the inset presents the sensor directly attached on the elbow joint. \n\nThe excellent sensing performances were not only observed in SWCNT/hydrogel based strain sensor, but could also be achieved on graphene/hydrogel based strain sensor and silver nanowire/hydrogel based strain sensor (Figure S8 and Figure S9, Supporting Information). A relative resistance change of $916\\%$ and gauge factor of 0.92 were observed at $100\\%$ strain for graphene/hydrogel. The silver nanowire/ hydrogel based strain sensor exhibits high relative resistance change of $2249\\%$ and gauge factor of 2.25 at $100\\%$ strain. However, the silver nanowire/hydrogel based strain sensor is not stable due to the easy oxidation of silver nanowires in water and air. The results indicate that the outstanding sensor performance can be obtained on various electronic conductor/ hydrogel based strain sensors. \n\nThe self-healing SWCNT/hydrogel is promising material platform for wearable strain sensor. For demonstration, the SWCNT/hydrogel based sensor was mounted on the white cotton glove, garment, or directly attached on the skin to detect the bending and stretching of the human body, such as finger knuckle, knee joint, neck and elbow joint. Figure 4a shows the motion detection for the index finger. We checked the response behaviors of the SWCNT/hydrogel based strain sensor when the fingers were repeatedly bent at a frequency of $1\\ \\mathrm{Hz}$ . It can be seen that the sensor responded to the motion of the finger rapidly and repeatedly. The background noise is corresponding to the slight trembling of the finger that can be detected by the SWCNT/hydrogel strain sensor, indicating the high sensitivity of the sensor. Figure 4b illustrates the detection of knee joint bending, the sensor is stretched when the bending angles are at $79.8^{\\circ}$ , $92.5^{\\circ}$ , $122.7^{\\circ}$ , respectively, and released when straightening the knee, the resistance increases during the bending and recover during the releasing process. It can be seen that the resistance of the sensor increased as the bending angle increased. Moreover, the sensor is capable of distinguishing the different bending angles of the knee. When the knee was held at a certain angle, the resistance of SWCNT/hydrogel based strain sensor remained at a constant value and returned to the original value after straightening the knee. Furthermore, when the SWCNT/hydrogel based strain sensor was used to further monitor other human-motion such as neck bending and elbow bending, sharp and rapid responses were also observed as shown in Figure 4c,d, respectively. Although a slight drift is noticed in these responses, the sensor exhibited good stability and repeatability in the signal. The hysteresis of the sensor in the response could lead to the signal drift. Figure S10 (Supporting Information) depicts the relative resistance changes of $100\\%$ and $100\\%$ strain under stretching–releasing cycles, significant hysteresis is observed during the $100\\%$ stretching– releasing cycling. The hysteresis is caused by rearrangement of the CNT in the hydrogel matrix and the considerable hysteresis of VHB tape. However, even in this case, the original resistance of the sensor is almost fully recovered after releasing it from strain and the hysteresis is negligible within $100\\%$ strain. Moreover, the sensor also has important advantages of low creep and fast response. As seen in Figure S11 (Supporting Information), a step strain of $100\\%$ was imposed within 1 s, revealing a percent overshoot and creep recovery time of $7.4\\%$ and $0.7~\\mathrm{s}$ , respectively, which can be attributed to the excellent self-healing property of the conductive SWCNT/hydrogel. The differences in the degree of muscle movements could lead to a slight drift. In order to prove this, the response behavior of the sensor was also investigated by repeatedly applying $100\\%$ stretching strain to the sensor as shown in Figure S12 (Supporting Information). It can be seen that the sensor exhibits a negligible drift under the constant strain. These results demonstrate that our strain sensors can be used as human motion sensor and have the potential application in a wide range of stretchable devices. \n\nIn summary, the present work first demonstrated the extremely stretchable self-healing strain sensors based on various repeatable self-healing conductive hydrogels such as SWCNT, graphene, and silver nanowire/hydrogel under ambient conditions. The conductive SWCNT/hydrogel exhibits fast electrical healing speed (within 3.2 s) and high self-healing efficiency $(98\\pm0.8\\%)$ . The strain sensor is capable of sustaining severe elastic deformation (up to $100\\%$ ) with high gauge factor of 1.51. After being stretched to $700\\%$ strain for 1000 cycles, no significant change was observed in the intrinsic properties of the strain sensor. The electrical resistance can effectively recover by self-healing of the conductive SWCNT/hydrogel. Furthermore, the strain sensor could effectively monitor and distinguish multifarious human motion when used as wearable strain sensor. We found that the SWCNT/hydrogel based strain sensors have good response, stability, and repeatability of the signal during the human motion detection measurements. We believe that our extremely stretchable self-healing strain sensor could find a wide range of applications in robotics, sports, health monitoring, and medical treatments. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThis research is supported by the National Research Foundation Competitive Research Programme NRF-CRP13-2014-02, and National Research Foundation Investigatorship Award NRF-NRFI2016-05 that is supported by the National Research Foundation, Prime Minister’s Office, Singapore. \n\nReceived: May 19, 2016 Revised: June 24, 2016 Published online: \n\n[8]\t T.  Yamada, Y.  Hayamizu, Y.  Yamamoto, Y.  Yomogida, A. Izadi-Najafabadi, D. N. Futaba, K. Hata, Nat. Nano 2011, 6, 296. \n[9]\t Z. Y.  Liu, D. P.  Qi, P. Z.  Guo, Y.  Liu, B. W.  Zhu, H.  Yang, Y. Q.  Liu, B.  Li, C. G.  Zhang, J. C.  Yu, B.  Liedberg, X. D.  Chen, Adv. Mater. 2015, 27, 6230. \n[10]\t M.  Amjadi, A.  Pichitpajongkit, S.  Lee, S.  Ryu, I.  Park, ACS Nano 2014, 8, 5154. \n[11]\t X.  Xiao, L. Y.  Yuan, J. W.  Zhong, T. P.  Ding, Y.  Liu, Z. X.  Cai, Y. G.  Rong, H. W.  Han, J.  Zhou, Z. L.  Wang, Adv. Mater. 2011, 23, 5440. \n[12]\t S.  Gong, D. T. H.  Lai, B.  Su, K. J.  Si, Z.  Ma, L. W.  Yap, P. Z.  Guo, W. L. Cheng, Adv. Electron. Mater. 2015, 1, 1400063. \n[13]\t C. Y.  Yan, J. X.  Wang, W. B.  Kang, M. Q.  Cui, X.  Wang, C. Y.  Foo, K. J. Chee, P. S. Lee, Adv. Mater. 2014, 26, 2022. \n[14]\t Y. R.  Jeong, H.  Park, S. W.  Jin, S. Y.  Hong, S.-S.  Lee, J. S.  Ha, Adv. Funct. Mater. 2015, 25, 4228. \n[15]\t M. T.  Chen, L.  Zhang, S. S.  Duan, S. L.  Jing, H.  Jiang, C. Z.  Li, Adv. Funct. Mater. 2014, 24, 7548. \n[16]\t B.  Sun, Y.-Z.  Long, S.-L.  Liu, Y.-Y.  Huang, J.  Ma, H.-D.  Zhang, G. Shen, S. Xu, Nanoscale 2013, 5, 7041. \n[17]\t M. F.  Li, H. Y.  Li, W. B.  Zhong, Q. H.  Zhao, D.  Wang, ACS Appl. Mater. Interfaces 2014, 6, 1313. \n[18]\t S.  Xu, Y. H.  Zhang, L.  Jia, K. E.  Mathewson, K.-I.  Jang, J.  Kim, H. R.  Fu, X.  Huang, P.  Chava, R.  Wang, S.  Bhole, L. Z.  Wang, Y. J.  Na, Y.  Guan, M.  Flavin, Z. S.  Han, Y. G.  Huang, J. A.  Rogers, Science 2014, 344, 70. \n[19]\t S. Cheng, Z. G. Wu, Adv. Funct. Mater. 2011, 21, 2282. \n[20]\t A.  Frutiger, J. T.  Muth, D. M.  Vogt, Y.  Mengüç, A.  Campo, A. D. Valentine, C. J. Walsh, J. A. Lewis, Adv. Mater. 2015, 27, 2440. \n[21]\t N. Lu, C. Lu, S. Yang, J. Rogers, Adv. Funct. Mater. 2012, 22, 4044. \n[22]\t T.-P. Huynh, H. Haick, Adv. Mater. 2016, 28, 138. \n[23]\t B. C. K. Tee, C. Wang, R. Allen, Z. N. Bao, Nat. Nano 2012, 7, 825. \n[24]\t J.  Hur, K.  Im, S. W.  Kim, J.  Kim, D.-Y.  Chung, T.-H.  Kim, K. H.  Jo, J. H. Hahn, Z. Bao, S. Hwang, N. Park, ACS Nano 2014, 8, 10066. \n[25]\t J.-Y. Sun, X. H. Zhao, W. R. K. Illeperuma, O. Chaudhuri, K. H. Oh, D. J. Mooney, J. J. Vlassak, Z. G. Suo, Nature 2012, 489, 133. \n[26]\t C. Keplinger, J.-Y. Sun, C. C. Foo, P. Rothemund, G. M. Whitesides, Z. G. Suo, Science 2013, 341, 984. \n[27]\t J. X. Wang, C. Y. Yan, G. F. Cai, M. Q. Cui, A. L. S. Eh, P. S. Lee, Adv. Mater. 2016, 28, 4490. \n[28]\t L.-W.  Xia, R.  Xie, X.-J.  Ju, W.  Wang, Q. M.  Chen, L.-Y.  Chu, Nat. Commun. 2013, 4, 2226. \n[29]\t L. B. Hu, W. Yuan, P. Brochu, G. Gruner, Q. B. Pei, Appl. Phys. Lett. 2009, 94, 161108. \n[30]\t M. R. Abidian, D. C. Martin, Adv. Funct. Mater. 2009, 19, 573. \n[31]\t S.  Brahim, D.  Narinesingh, A.  Guiseppi-Elie, Biosens. Bioelectron. 2002, 17, 53. \n[32]\t J.-Y.  Sun, C.  Keplinger, G. M.  Whitesides, Z. G.  Suo, Adv. Mater. 2014, 26, 7608. \n[33]\t R. F. Nickerson, J. Appl. Polym. Sci. 1971, 15, 111. \n[34]\t E. Z. Casassa, A. M. Sarquis, C. H. Van Dyke, J. Chem. Educ. 1986, 63, 57. \n[35]\t V.  de Zea Bermudez, P. P.  de Almeida, J. F.  Seita, J. Chem. Educ. 1998, 75, 1410. \n[36]\t S.  Spoljaric, A.  Salminen, N. D.  Luong, J.  Seppälä, Eur. Polym. J. 2014, 56, 105. \n[37]\t H. J. Zhang, H. S. Xia, Y. Zhao, ACS Macro Lett. 2012, 1, 1233. \n[38]\t G. Li, H. J. Zhang, D. Fortin, H. S. Xia, Y. Zhao, Langmuir 2015, 31, 11709. \n[39]\t G.  Li, Q.  Yan, H. S.  Xia, Y.  Zhao, ACS Appl. Mater. Interfaces 2015, 7, 12067. \n[40]\t S. N.  Kale, J.  Mona, S.  Dhobale, T.  Thite, S. L.  Laware, J. Appl. Polym. Sci. 2011, 121, 2450. \n[41]\t X.  Qi, X.  Yao, S.  Deng, T.  Zhou, Q.  Fu, J. Mater. Chem. A 2014, 2, 2240. \n[42]\t R. G. Peng, Y. Yu, S. Chen, Y. K. Yang, Y. H. Tang, RSC Adv. 2014, 4, 35149. \n[43]\t S. Ryu, P. Lee, J. B. Chou, R. Xu, R. Zhao, A. J. Hart, S.-G. Kim, ACS Nano 2015, 9, 5929. \n[44]\t Y.  Wang, R.  Yang, Z. W.  Shi, L. C.  Zhang, D. X.  Shi, E. G.  Wang, G. Y. Zhang, ACS Nano 2011, 5, 3645. \n[45]\t J. E. Mates, I. S. Bayer, J. M. Palumbo, P. J. Carroll, C. M. Megaridis, Nat. Commun. 2015, 6, 8874. \n[46]\t Y.  Wang, S.  Gong, S. J.  Wang, G. P.  Simon, W. L.  Cheng, Mater. Horiz. 2016, 3, 208. \n[47]\t E. Roh, B.-U. Hwang, D. Kim, B.-Y. Kim, N.-E. Lee, ACS Nano 2015, 9, 6252. \n[48]\t X.  Li, R. J.  Zhang, W. J.  Yu, K. L.  Wang, J. Q.  Wei, D. H.  Wu, A. Y.  Cao, Z. H.  Li, Y.  Cheng, Q. S.  Zheng, R. S.  Ruoff, H. W.  Zhu, Sci. Rep. 2012, 2, 870. \n[49]\t J. Kim, M. Lee, H. J. Shim, R. Ghaffari, H. R. Cho, D. Son, Y. H. Jung, M.  Soh, C.  Choi, S.  Jung, K.  Chu, D.  Jeon, S.-T.  Lee, J. H.  Kim, S. H.  Choi, T.  Hyeon, D.-H.  Kim, Nat. Commun. 2014, 5, 5747. " + }, + { + "id": "10.1002_cphc.201700126", + "DOI": "10.1002/cphc.201700126", + "DOI Link": "http://dx.doi.org/10.1002/cphc.201700126", + "Relative Dir Path": "mds/10.1002_cphc.201700126", + "Article Title": "C1s Peak of Adventitious Carbon Aligns to the Vacuum Level: Dire Consequences for Material's Bonding Assignment by Photoelectron Spectroscopy", + "Authors": "Greczynski, G; Hultman, L", + "Source Title": "CHEMPHYSCHEM", + "Abstract": "The C1s signal from ubiquitous carbon contamination on samples forming during air exposure, so called adventitious carbon (AdC) layers, is the most common binding energy (BE) reference in X-ray photoelectron spectroscopy studies. We demonstrate here, by using a series of transition-metal nitride films with different AdC coverage, that the BE of the C1s peak E-B(F) varies by as much as 1.44 eV. This is a factor of 10 more than the typical resolvable difference between two chemical states of the same element, which makes BE referencing against the C1s peak highly unreliable. Surprisingly, we find that C1s shifts correlate to changes in sample work function phi(SA), such that the sum E-B(F) + phi(SA) is constant at 289.50 +/- 0.15 eV, irrespective of materials system and air exposure time, indicating vacuum level alignment. This discovery allows for significantly better accuracy of chemical state determination than offered by the conventional methods. Our findings are not specific to nitrides and likely apply to all systems in which charge transfer at the AdC/substrate interface is negligible.", + "Times Cited, WoS Core": 860, + "Times Cited, All Databases": 884, + "Publication Year": 2017, + "Research Areas": "Chemistry; Physics", + "UT (Unique WOS ID)": "WOS:000403885800004", + "Markdown": "# C1s Peak of Adventitious Carbon Aligns to the Vacuum Level: Dire Consequences for Material’s Bonding Assignment by Photoelectron Spectroscopy \n\nGrzegorz Greczynski\\* and Lars Hultman[a] \n\nThe C 1s signal from ubiquitous carbon contamination on samples forming during air exposure, so called adventitious carbon (AdC) layers, is the most common binding energy (BE) reference in X-ray photoelectron spectroscopy studies. We demonstrate here, by using a series of transition-metal nitride films with different AdC coverage, that the BE of the C 1s peak $E_{\\tt B}^{\\tt F}$ varies by as much as $1.44\\:\\mathrm{eV.}$ This is a factor of 10 more than the typical resolvable difference between two chemical states of the same element, which makes BE referencing against the C 1s peak highly unreliable. Surprisingly, we find that C 1s shifts correlate to changes in sample work function $\\phi_{\\mathsf{S A}},$ such that the sum $E_{\\tt B}^{\\tt F}+\\phi_{\\tt S A}$ is constant at $289.50\\pm0.15\\mathrm{eV},$ irrespective of materials system and air exposure time, indicating vacuum level alignment. This discovery allows for significantly better accuracy of chemical state determination than offered by the conventional methods. Our findings are not specific to nitrides and likely apply to all systems in which charge transfer at the AdC/substrate interface is negligible. \n\nX-ray photoelectron spectroscopy (XPS) is an essential analytical tool in surface science and materials research, providing information about surface chemistry and composition. The first observation of chemical shifts between Cu atoms in metallic and oxidized state,[1] followed by a report on a S 1s peak split in the photoelectron spectrum of sulfur atoms in thiosulfate,[2] shortly after, carbon atoms in 1,2,4,5-benzenetetracarboxylic acid,[3] and the whole range of N-containing organic molecules,[4] laid grounds for chemical analysis by electron spectroscopy (ESCA).[5,6] The unambiguous bonding assignment relies, however, on the correct measurement of binding energy (BE) values. This is often a nontrivial task because of the lack of an internal BE reference.[7] During the XPS experiments the negative charge continuously removed from the surface region as a result of a photoelectric effect has to be replenished with a sufficiently high rate to preserve charge neutrality. If this condition is not fulfilled, the surface acquires positive potential, which decreases the kinetic energy of escaping photoelectrons, and in consequence leads to the apparent shift of all core level peaks towards higher BE; the phenomenon commonly referred to as charging. Since the specimen’s charging state is not known a priori, the problem with correct BE referencing arises for the vast majority of samples. The natural zero of the BE scale exists only for specimens, in which the density of states (DOS) exhibits a well-defined cut-off at the Fermi energy $\\boldsymbol{E}_{\\intercal}$ the so-called Fermi edge, as is the case for metals in which high conductivity ensures Fermi level alignment between the sample and the spectrometer. All other samples that lack an internal BE reference present a serious challenge, which is reflected by a large spread of reported BE values for the same chemical state.[8] Some examples include $\\mathsf{T i O}_{2}$ with the reported $\\$123$ and O1s peak positions varying from 458.0 to $459.6\\mathrm{eV},$ and from 529.4 to $531.2\\:\\mathrm{eV},$ respectively. In a similar way, for $\\mathsf{S i}_{3}\\mathsf{N}_{4},$ Si 2p and N 1s peaks have been reported at BE varying from 100.6 to $102.1\\ \\mathrm{eV},$ and 397.4 to $398.6\\mathrm{eV},$ respectively.[8] It is highly disturbing that after more than 50 years of development, the BE of constituting elements in many technologically relevant materials is accessed with an accuracy that is not better than the magnitude of typical large chemical shifts of the order of $1\\ \\mathrm{eV,}$ much larger than the instrument resolution at $0.1\\ \\mathrm{eV}$ (or less), which makes the bonding assignment ambiguous, often leading to an arbitrary spectra interpretation and contradicting results. \n\nThe situation is worsened by the fact that the use of a natural BE reference such as the Fermi edge in the case of conducting samples, is not at all common. This is again reflected by the spread of reported BE values, not as large as for insulators, yet significant enough to often prevent correct bonding assignment. For example, in the case of transition-metal (TM) nitrides, which exhibit pronounced DOS at the Fermi level and, hence, metallic-like conductivity, reported BE values for core level signals often differ by more than $1\\ \\mathrm{eV}.$ ; the $\\$123$ core level of TiN varies from 454.77 to $455.8\\:\\mathrm{eV},$ whereas the position of the N 1s peak changes by $0.9\\mathsf{e V}$ for TiN, and $1.2\\:\\mathrm{eV}$ for ZrN, MoN, and NbN. \n\nIt has become a common procedure to use the C 1s signal from the adventitious carbon (AdC) layer present on the vast majority of surfaces following air exposure, as a BE reference. To calibrate the BE scale the C C/C H peak of AdC is deliberately set at $284.0\\substack{-285.2\\mathrm{eV}}$ and all core-level spectra are aligned accordingly.[9] The method was first proposed by Siegbahn et al.[6] in the early days of XPS applications and was originally based on the observation that the AdC layer is present on all air-exposed surfaces with the C 1s line as it appeared constant at $285.0\\mathrm{eV},$ which made it an ideal candidate for BE referencing.[10] Soon after, however, the claim was dropped, as it became clear that the C1s BE in practice varies with the thickness of the hydrocarbon layer by as much as $0.6\\:\\mathrm{eV}$ for Pd and Au substrates.[11,12] In the review of existing literature published in 1982, Swift concluded that “although the use of C 1s electrons from adventitious carbon layers is often a convenient method of energy referencing, interpretation of binding energy data obtained should be treated with caution”.[9] In the following years, problems with using the C 1s peak for BE referencing accumulated. For example, Werrett et al. reported inconsistent results when referencing to C 1s of AdC during studies of oxidized Al-Si alloys, which was due to the oxidation of AdC,[13] whereas Gross et al. showed that the Au 4f signal from gold particles deliberately deposited on amorphous $\\mathsf{S i O}_{2}$ provides more reliable BE reference than C 1s.[14] More recent examples indicate that the issue of correct referencing of XPS spectra remains unresolved,[15,16] which contrasts with the fact that the method based on adventitious carbon is widely adopted. \n\nOur literature review shows that in 58 of the first 100 topcited papers dealing with XPS studies of magnetron sputtered films published between 2010 and 2016 in peer-reviewed journals, C 1s of AdC was used as a BE reference,[17] whereas, alarmingly, the remaining papers lack information about any referencing method used. Within the first group, the C 1s peak was set quite arbitrary at the BE, varying from 284.0 to $285.2\\:\\mathrm{eV}$ (here we disregard two extreme cases of 283.0 and $298.8\\mathsf{e V}$ . This serious inconsistency easily accounts for the large spread of reported BE values for the same chemical species (see examples above), and contradicts the notion of the BE reference, which per definition should be associated with one single energy value (as was originally intended in ref. [6]). \n\nHere, we examine the reliability of using AdC for XPS BE referencing by measuring the position of the C1s peak for a series of TM nitride thin-film layers that exhibit a well-defined Fermi edge cut-off serving as an internal BE reference. Measurements are performed as a function of the AdC layer thickness, which scales with the air exposure time. We show that the BE of the C 1s peak of AdC measured with respect to the Fermi edge $E_{_B}^{\\mathsf{F}}$ varies by as much as $1.44\\:\\mathrm{eV},$ from $284.08\\mathsf{e V}$ in the case of MoN to $285.52\\mathrm{eV}$ for a HfN sample. This is a factor of 10 more than the typical resolvable difference between two chemical states of the same element, which makes the energy referencing against the C1s peak of AdC highly unreliable. Moreover, we demonstrate that the position of the C 1s peak of AdC closely follows changes in sample work function $\\phi_{\\mathsf{S A}},$ assessed here by ultraviolet photoelectron spectroscopy (UPS), in such a way that the sum $E_{\\tt B}^{\\tt F}+\\phi_{\\tt S A}$ is essentially constant at $289.50\\pm0.15\\mathrm{eV},$ which corresponds well to the gas-phase BE value of longer alkanes lowered by the intermolecular relaxation energy. This indicates that C 1s aligns to the vacuum level $E_{\\lor\\mathsf{A C}},$ and implies that its BE is steered by the sample work function. Clearly, the C 1s of AdC cannot be used for reliable BE referencing of XPS spectra in a conventional way, unless a complementary measurement of $\\phi_{\\mathsf{S A}}$ is performed and C 1s is set at \n\n$289.50-\\phi_{\\mathsf{S A}}$ . We show that this approach results in a considerably better accuracy of chemical state determination as compared with the status quo. \n\nThe ubiquitous nature of AdC has been analyzed in detail by Barr et al.,[18] who concluded that it predominantly consists of polymeric hydrocarbon species (C C/C H), together with a minor component ( $10\\mathrm{-}30\\%$ of the total signal intensity) due to carbooxides containing C O C and $0{\\mathrm{-}}{\\mathsf{C}}{\\mathrm{=}}{\\mathsf{O}}$ bonds. Indeed, a set of C 1s core level spectra acquired from (TM)N surfaces in the as-received state (see Figure 1) reveals that carbon is present in several chemical states almost on every surface analyzed. In all cases, however, the spectra are dominated by the aliphatic carbon C C/C H peak, whereas C O C and $0-C=0$ contributions present at higher BE appear in much lower concentrations. Clearly, there is a substantial change in the C 1s spectra appearance depending on the (TM)N studied. Not only do the number of component peaks change (e.g., no $0-C=0$ peak is observed in the present case of WN and MoN), but, more importantly, the BE of the dominant C C/C H peak, measured with respect to the Fermi level of the spectrometer $\\boldsymbol{E}_{\\mathrm{B}}^{\\intercal},$ exhibits large variation: from $284.08\\mathrm{eV}$ in the case of MoN surface to $285.52\\mathrm{eV}$ for HfN, as summarized in Table 1. The $1.44\\mathrm{eV}$ change in the position of the C 1s peak is certainly disturbing, as one would clearly expect the BE of carbon species present in the same chemical state to be independent of the underlying substrate, especially if used for referencing XPS spectra. \n\n![](images/9c410314ab3f09592bd08ed34ea4671e34631214a05a63a96a3a4d20767e8dd3.jpg) \nFigure 1. C 1s XPS spectra of adventitious carbon obtained from as-received air-exposed (ca. $10\\mathrm{min.}$ ) polycrystalline (TM)N thin films, where ${\\mathsf{T}}M=M\\circ,\\ V,$ W, Ti, Cr, Nb, Ta, Zr, and Hf, grown by magnetron sputtering on $\\mathsf{S i}(001)$ substrates. \n\n
Table1. Binding energies relative to Fermi level E for all component peaks in C1s spectra together with work function values sa obtained from polycrystalline (TM)N thin films in the as-received state, where TM=Mo, V, W, Ti, Cr, Nb, Ta, Zr, and Hf.
(TM)N C-C/C-HC1s BE relative to Fermi level, E [eV] C-o 01C=o△BE Cc-o-Cc-c△BE Co-c=o-Cc-c[eV]Work function
TiN284.52286.24289.061.724.54 4.90
VN284.15285.96288.511.814.36 5.16
CrN284.60286.14288.561.543.96 4.83
ZrN285.49287.21289.541.724.05 4.09
NbN284.76286.52289.181.764.42 4.65
MoN284.08285.761.685.35
HfN285.52287.17289.751.654.23 4.00
TaN285.08286.75289.391.674.31 4.41
WN284.22285.731.715.23
\n\nThe C 1s contribution due to C O also shifts from sample to sample, from $285.76\\:\\mathrm{eV}$ for as-received MoN to 287.21 for $z_{\\mathsf{r N}}$ $1.45\\mathrm{eV}$ difference), essentially following the $C-C/C-H$ peak, so that the relative BE difference $\\Delta(\\mathsf{C}_{\\mathsf{C}-0}-\\mathsf{C}_{\\mathsf{C}-\\mathsf{C}})$ is nearly constant at $1.70\\pm0.13\\mathrm{eV}$ (cf. Table 1). The BE of the $0-C=0$ peak does not follow the shifts observed for all other C 1s contributions, which is best seen by comparing the C 1s spectra recorded from TiN and CrN surfaces, see Figure 1, and varies from 288.51 eV for VN to $289.75\\mathrm{eV}$ for HfN ( $1.24\\:\\mathrm{eV}$ difference). Some C 1s spectra (TiN, ZrN) possess also an extra contribution at significantly lower BE $(282.0-282.5\\:\\mathrm{eV})$ , which is assigned to carbide formation during film growth,[19] and as such is of minor importance for this work. \n\nThe amount of AdC that accumulates on the surface of (TM)N films exhibits a steady increase with the air exposure time, as illustrated in Figure 2, in which surface C concentrations are plotted for all nitride samples in the time span from 10 minutes to 7 months. Even though the percentage amount of AdC varies somewhat between different samples, the accumulation rate is essentially the same and amounts to ca. $5a t\\%$ per decade. The corresponding evolution of $E_{_{8}}^{\\tt F}$ of the dominant C C/C H C1s peak of AdC with air exposure time is shown in Figure 3 (a). Interestingly, even though there is a certain variation in C 1s $E_{_{8}}^{\\tt F}$ for each materials system (rather random and not exceeding $0.5\\mathrm{eV}.$ ), a large spread in BE of the C 1s peak observed for samples in the as-received state persists for layers that were sputter-cleaned and subsequently exposed to ambient atmosphere for time periods varying from 10 minutes to 7 months. Thus, we can conclude that the template dependence of C 1s BE takes place irrespective of the amount of accumulated adventitious carbon. We note also that changes in the BE’s of the intrinsic core level signals (metal and nitrogen peaks) during prolonged air exposure are lower than 0.1 eV. \n\n![](images/4489f7a22dba8bc8e912c7ce6a696d7857170a336ee633a238282bc3655c4a68.jpg) \nFigure 2. Surface carbon concentrations plotted as a function of air exposure time for polycrystalline (TM)N thin films, where ${\\mathsf{T}}M=M\\circ,$ $\\mathsf{V},$ W, Ti, Cr, Nb, Ta, $Z\\boldsymbol{\\mathrm{r}},$ and Hf, grown by magnetron sputtering on Si(001) substrates. \n\nTo address the issue of C 1s shifts, we first obtain a reliable evaluation of the charging state of the \nactual (TM)N film. To do this, we record DOS in the vicinity of \nthe Fermi edge (Fermi level cut-off). Electrons close to $\\boldsymbol{E}_{\\intercal}$ pos \nsess the highest kinetic energy of all excited photoelectrons \n(essentially equal to $h\\nu-\\phi_{\\mathsf{S A}}),$ which results in relatively long \nmean free path $\\lambda,$ from to 18 to $24\\mathbb{A}.^{[20]}$ In consequence, the \n\n![](images/adf834458abc9c2914509b1542c29c058a2e7cdc958d7bb8115b6280dcd2a5dc.jpg) \nFigure 3. a) Binding energy of the $C{\\mathrm{-}}C/C{\\mathrm{-}}{\\mathsf{H}}$ peak in the C 1s spectra of adventitious C referenced to Fermi level $E_{\\scriptscriptstyle{8}\\prime}^{\\scriptscriptstyle{\\mathsf{F}}}$ b) work function obtained by UPS from the secondary electron cut-off $\\phi_{\\mathsf{S A}},$ and c) C 1s BE referenced to Vacuum level $E_{\\mathsf{v A C}}^{}$ for a set of polycrystalline $(\\mathsf{T M})\\mathsf{N}$ thin films, where ${\\mathsf{T M}}={\\mathsf{M o}}$ , V, W, Ti, Cr, Nb, Ta, Zr, and ${\\mathsf{H f}},$ grown by magnetron sputtering on Si(001) substrates. The dashed curves in (a) and (b) are only for eye guiding to emphasize the symmetry between the plots. \n\n![](images/15b9c4353e428125481437f8b27da8718a892c3cc81d8c16c880e05447d6c330.jpg) \nFigure 4. The portion of the valence band spectra in the close vicinity of the Fermi level $\\mathsf{E}_{\\mathsf{F}}$ indicating the Fermi level cut-off for as-received polycrystalline (TM)N thin films, where ${\\mathsf{T}}M=M\\circ,$ , V, W, Ti, Cr, Nb, Ta, $Z\\boldsymbol{\\mathsf{r}},$ and ${\\mathsf{H f}},$ grown on Si(001) substrates: a) as measured (referencing to $\\boldsymbol{E}_{\\mathsf{F}})$ , and b) aligned by using the common procedure of referencing to C 1s peak of adventitious carbon set at $284.5\\mathrm{eV.}$ . \n\nXPS probing depth, given by $3\\times\\lambda,$ well exceeds the thickness of the AdC layer, which is in the range $4.5{\\-}{-}9\\AA.$ This, together with the fact that adventitious carbon being a wide band gap material does not possess DOS near ${E}_{\\mathfrak{F}}^{[18]}$ implies that the spectral intensity in this region is solely determined by the TM(N). Figure 4 (a) shows the Fermi level cut-off for all TM(N) samples in the as-received state, as measured. In all cases, the rapid drop in DOS coincides with $\"0^{\\prime\\prime}$ of the BE scale, which is indicative of a Fermi level alignment between sample and the spectrometer. This proves that a good electrical contact is established to the instrument and excludes any possibility of charging in the (TM)N layer. \n\nThe fact that C 1s shifts (cf. Figure 1) while the Fermi edge from the underlying (TM)N film appears at $\"0\"$ eV (Figure 4 (a)) clearly indicates decoupling of the measured energy levels of adventitious carbon from the Fermi level of the underlying substrate and, hence, spectrometer. The implications for BE referencing that employs the C 1s peak are severe. If, as commonly practiced, one would align all recorded spectra by setting the C C/C H peak of AdC at $284.5\\mathrm{eV},$ the highest portion of the valence band spectra recorded from (TM)N appears as shown in Figure 4 (b). Contrafactory, some specimens (TiN, VN) would exhibit no DOS at $\\boldsymbol{E}_{\\intercal}$ despite their metallic character, whereas for other films (HfN, ZrN, and TaN) such calibration of the BE scale results in a non-zero DOS above the Fermi level. These examples demonstrate that the common procedure of referencing to the C1s level set at the arbitrary chosen BE value within the range, $284.0\\substack{-285.2\\mathrm{eV},}$ is not justified because it leads to unphysical results. The latter is not realized if dealing with core level spectra, in which case shifts in peak positions by $\\pm1$ eV do not lead to such clear contradictions. \n\nTo gain more insight into the energy level alignment at the AdC/(TM)N interface, we perform measurements of sample work function $\\phi_{\\mathsf{S A}}$ in the same instrument; that is, without breaking the vacuum. As summarized in Figure 3 (b), in which sample work function is plotted for all TM(N) layers in the order of an increasing TM mass, and for various amounts of air exposure time, $\\phi_{\\mathsf{S A}}$ exhibits large apparent variations, that in the case of as-received samples range from $4.00\\:\\mathrm{eV}$ for HfN to $5.35\\mathrm{eV}$ for MoN. More importantly, a direct comparison to the $E_{_B}^{\\mathsf{F}}$ values shown in Figure 3 (a) reveals that the trend in work function closely correlates to that observed for the C 1s peak of AdC, such that the sum $E_{\\tt B}^{\\tt F}+\\phi_{\\tt S A}$ remains constant for all samples, irrespective of air exposure time at $289.50\\pm0.15\\mathrm{eV}$ (see Figure 3 (c)). This implies that C 1s aligns to the vacuum level $\\boldsymbol{E_{\\mathrm{vac}}},^{[21,22]}$ rather than to the Fermi level, as is implicitly assumed when using this peak for BE referencing. Hence, the position of the C 1s peak measured with respect to $\\boldsymbol{E}_{\\intercal}$ is steered by the substrate work function, which disqualifies this signal as a reliable reference, unless a complementary measurement of $\\phi_{\\mathsf{S A}}$ is performed and spectra are aligned to C 1s set at $289.50-\\phi_{\\mathsf{S A}}$ eV. The position of the C 1s C C/C H peak referenced to $E_{\\lor\\mathsf{A C}},$ $,289.50\\mathrm{eV},$ corresponds very well with the gasphase value of $290.15\\mathrm{eV}$ measured for longer alkanes by Pireaux et al.,[23] compensated for the intermolecular relaxation energy due to electronic and atomic polarization of the neighboring molecules surrounding the core hole, which is typically of the order of $1-3\\ \\mathrm{eV}.^{[24]}$ \n\nThe vacuum level alignment is characteristic of a weak interaction at the interface to the substrate and is regularly observed for organic films deposited on metals by using ex-situ techniques (e.g. spin coating) in the absence of both charge transfer across the interface and interface dipole formation.[25] \n\n![](images/69433085b79572126956cf96e58acf6395a8fd2a2beed32f7455f667a9fdfd97.jpg) \nFigure 5. Schematic illustration of the energy level alignment at the interface between adventitious carbon layer and a) the low work function substrate, and b) the high work function substrate. For all tested samples the sum of $E_{\\scriptscriptstyle\\mathrm{B}}^{\\scriptscriptstyle\\mathsf{F}}$ and $\\phi_{\\mathsf{S A}}$ is constant, which is indicative of vacuum level alignment. \n\nSuch contacts remain within the Schottky–Mott limit, in which the electronic levels of the adsorbate are determined by the work function of the substrate.[26] As a matter of fact, the process of AdC adsorption is also classified as physical,[18] because the principal species (hydrocarbons) are not chemically reactive and can be readily desorbed by a gentle anneal in vacuum.[27] In the present case, the potential interaction between AdC species and (TM)N film is further suppressed by the presence of a native oxide layer. \n\nOur findings are schematically summarized in Figure 5, in which the relevant energy levels and critical parameters are indicated for (a) a low work function sample, and (b) a high work function sample. Independent of $\\phi_{\\mathsf{S A}}$ we find that the Fermi level cut-off of (TM)N aligns with that of the spectrometer (which is established during the calibration procedure), whereas the BE of C 1s from adventitious carbon $E_{\\scriptscriptstyle\\tt B}^{\\tt F}$ closely follows the changes in $\\phi_{\\mathsf{S A}}$ . Since $\\Delta E_{\\tt B}^{\\tt F}\\cong\\Delta\\phi_{\\mathsf{S A}},$ the position of the C 1s peak with respect to the vacuum level, $E_{\\tt B}^{\\tt F}+\\phi_{\\mathsf{S A}},$ remains constant at $289.50\\pm0.15\\mathrm{eV}.$ . This agrees with a common-sense notion of constant energy levels associated with C atoms present in the same chemical environment and provides grounds for more reliable referencing of the XPS spectra. \n\nIn conclusion, we established by using a series of TM nitride thin-film layers covered with a few monolayers of adventitious carbon (AdC), that the BE of the C 1s peak of AdC measured with respect to the Fermi edge $E_{_B}^{\\mathsf{F}}$ depends on the substrate, and varies from $284.08\\mathrm{eV}$ for MoN to $285.52\\mathrm{eV}$ for the HfN sample in the as-received state. This wide spread in C 1s peak position is independent of the time samples are exposed to ambient atmosphere, hence of the AdC layer thickness. This disturbing result shows that the commonly used referencing of XPS spectra against the C 1s peak of AdC is unreliable. Moreover, we demonstrate that the C 1s signal closely follows the variation of sample work function $\\phi_{\\mathsf{S A}},$ such that the sum \n\n$E_{\\tt B}^{\\tt F}+\\phi_{\\tt S A}$ is constant at $289.50\\pm0.15\\mathrm{eV},$ indicating alignment to the vacuum level. Thus, the position of the C 1s peak from AdC layer is decoupled from the instrument Fermi level and is steered by the sample work function, and as such cannot be used for reliable BE referencing of XPS spectra. A possible remedy here is a complementary measurement of $\\phi_{\\mathsf{S A}}$ and referencing to C 1s set at $289.50-\\phi_{5\\tt A},$ which, as we demonstrate, yields consistent results for the whole series of TM nitrides, irrespective of air exposure time. Conclusions from this work are not limited to nitrides and likely apply to all substrates that exhibit weak interaction towards AdC. \n\n# Acknowledgements \n\nThe authors most gratefully acknowledge the financial support of the VINN Excellence Center Functional Nanoscale Materials (FunMat) Grant 2005-02666, the Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkçping University (Faculty Grant SFO-Mat-LiU 2009-00971), the Knut and Alice Wallenberg Foundation Grant 2011.0143, and the aforsk Foundation Grant 16-359. \n\n# Conflict of interest \n\nThe authors declare no conflict of interest. \n\nKeywords: analytical methods · binding energy · surface analysis $\\cdot$ surface chemistry $\\cdot\\cdot$ X-ray photoelectron spectroscopy [1] E. Sokolowski, C. Nordling, K. Siegbahn, Phys. Rev. 1958, 110, 776. [2] S. Hagstrçm, C. Nordling, K. Siegbahn, Z. Phys. 1964, 178, 439. [3] G. Axelson, U. Ericson, A. Fahlman, K. Hamrin, J. Hedman, R. Nordberg, C. Nordling, K. Siegbahn, Nature 1967, 213, 70. \n\n[4] R. Nordberg, R. G. Albridge, T. Bergmark, U. Ericson, A. Fahlman, K. Hamrin, J. Hedman, G. Johansson, C. Nordling, K. Siegbahn, B. Lindberg, Nature 1967, 214, 481. \n[5] A. Fahlman, K. Hamrin, J. Hedman, R. Nordberg, C. Nordling, K. Siegbahn, Nature 1966, 210, 4. \n[6] K. Siegbahn, C. Nordling, A. Fahlman, R. Nordberg, K. Hamrin, J. Hedman, G. Johansson, T. Bergmark, S.-E. Karlsson, I. Lindgren, B. Lindberg, ESCA—Atomic, Molecule and Solid State Structure Studied by Means of Electron Spectroscopy, Almqvist & Wiksells Boktryckeri, Uppsala, Sweden, 1967. \n[7] J. B. Metson, Surf. Interface Anal. 1999, 27, 1069. \n[8] NIST X-ray Photoelectron Spectroscopy Database, Version 4.1 (National Institute of Standards and Technology, Gaithersburg, 2012), http://srdatA.nist.gov/xps/. Accessed: 2016-11-22. \n[9] P. Swift, Surf. Interface Anal. 1982, 4, 47. \n[10] G. Johansson, J. Hedman, A. Berndtsson, M. Klasson, R. Nilsson, J. Electron Spectrosc. Relat. Phenom. 1973, 2, 295. \n[11] S. Kohiki, K. Oki, J. Electron Spectrosc. Relat. Phenom. 1984, 33, 375. \n[12] S. Kinoshita, T. Ohta, H. Kuroda, Bull. Chem. Soc. Jpn. 1976, 49, 1149. \n[13] C. R. Werrett, A. K. Bhattacharya, D. R. Pyke, Appl. Surf. Sci. 1996, 103, 403. \n[14] Th. Gross, M. Ramm, H. Sonntag, W. Unger, H. M. Weijers, E. H. Adem, Surf. Interface Anal. 1992, 18, 59. \n[15] A. P8lisson-Schecker, H. J. Hug, J. Patscheider, Surf. Interface Anal. 2012, 44, 29. \n[16] M. Jacquemin, M. J. Genet, E. M. Gaigneaux, D. P. Debecker, ChemPhysChem 2013, 14, 3618. \n[17] According to the Scopus Database search for “XPS” and “magnetron sputtering” articles published during 2010 –2016, as of 2016-11-24. \n[18] T. L. Barr, S. Seal, J. Vac. Sci. Technol. A 1995, 13, 1239. \n[19] G. Greczynski, S. Mr#z, L. Hultman, J. M. Schneider, Appl. Surf. Sci. 2016, 385, 356. \n[20] S. Tanuma, C. J. Powell, D. R. Penn, Surf. Interface Anal. 2011, 43, 689. \n[21] H. Ishii, E. Sugiyama, E. Ito, K. Seki, Adv. Mater. 1999, 11, 605. \n[22] H. D. Hagstrum, Surf. Sci. 1976, 54, 197. \n[23] J. J. Pireaux, S. Svensson, E. Basilier, P.-g. Malmqvist, U. Gelius, R. Caudano, K. Siegbahn, Phys. Rev. A 1976, 14, 2133. \n[24] M. Lçgdlund, G. Greczynski, A. Crispin, T. Kugler, M. Fahlman, W. R. Salaneck, Photoelectron Spectroscopy of Interfaces for Polymer-Based Electronic Devices, in Conjugated Polymer and Molecular Interfaces: Science and Technology for Photonic and Optoelectronic Application (Eds.: W. R. Salaneck, K. Seki, A. Kahn, J. J. Pireaux), Marcel Dekker, New York, 2001. \n[25] S. Braun, W. R. Salaneck, M. Fahlman, Adv. Mater. 2009, 21, 1450. \n[26] E. H. Rhoderick, R. H. Williams, Metal-Semiconductor Contacts, Clarendon Press, Oxford, 1988. \n[27] G. Greczynski, L. Hultman, Appl. Phys. Lett. 2016, 109, 211602. " + }, + { + "id": "10.1038_nature22987", + "DOI": "10.1038/nature22987", + "DOI Link": "http://dx.doi.org/10.1038/nature22987", + "Relative Dir Path": "mds/10.1038_nature22987", + "Article Title": "Making waves in a photoactive polymer film", + "Authors": "Gelebart, AH; Mulder, DJ; Varga, M; Konya, A; Vantomme, G; Meijer, EW; Selinger, RLB; Broer, DJ", + "Source Title": "NATURE", + "Abstract": "Oscillating materials(1-4) that adapt their shapes in response to external stimuli are of interest for emerging applications in medicine and robotics. For example, liquid-crystal networks can be programmed to undergo stimulus-induced deformations in various geometries, including in response to light(5,6). Azobenzene molecules are often incorporated into liquid-crystal polymer films to make them photoresponsive(7-11); however, in most cases only the bending responses of these films have been studied, and relaxation after photo-isomerization is rather slow. Modifying the core or adding substituents to the azobenzene moiety can lead to marked changes in photophysical and photochemical properties(12-15), providing an opportunity to circumvent the use of a complex set-up that involves multiple light sources, lenses or mirrors. Here, by incorporating azobenzene derivatives with fast cis-to-trans thermal relaxation into liquid-crystal networks, we generate photoactive polymer films that exhibit continuous, directional, macroscopic mechanical waves under constant light illumination, with a feedback loop that is driven by self-shadowing. We explain the mechanism of wave generation using a theoretical model and numerical simulations, which show good qualitative agreement with our experiments. We also demonstrate the potential application of our photoactive films in light-driven locomotion and self-cleaning surfaces, and anticipate further applications in fields such as photomechanical energy harvesting and miniaturized transport.", + "Times Cited, WoS Core": 817, + "Times Cited, All Databases": 862, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000404332000043", + "Markdown": "# Making waves in a photoactive polymer film \n\nAnne Helene Gelebart1,2, Dirk Jan Mulder1, Michael Varga3, Andrew Konya3, Ghislaine Vantomme2, E. W. Meijer2, Robin L. B. Selinger3 & Dirk J. Broer1,2 \n\nOscillating materials1–4 that adapt their shapes in response to external stimuli are of interest for emerging applications in medicine and robotics. For example, liquid-crystal networks can be programmed to undergo stimulus-induced deformations in various geometries, including in response to light5,6. Azobenzene molecules are often incorporated into liquid-crystal polymer films to make them photoresponsive7–11; however, in most cases only the bending responses of these films have been studied, and relaxation after photo-isomerization is rather slow. Modifying the core or adding substituents to the azobenzene moiety can lead to marked changes in photophysical and photochemical properties12–15, providing an opportunity to circumvent the use of a complex set-up that involves multiple light sources, lenses or mirrors. Here, by incorporating azobenzene derivatives with fast cis-to-trans thermal relaxation into liquid-crystal networks, we generate photoactive polymer films that exhibit continuous, directional, macroscopic mechanical waves under constant light illumination, with a feedback loop that is driven by self-shadowing. We explain the mechanism of wave generation using a theoretical model and numerical simulations, which show good qualitative agreement with our experiments. We also demonstrate the potential application of our photoactive films in light-driven locomotion and self-cleaning surfaces, and anticipate further applications in fields such as photomechanical energy harvesting and miniaturized transport. \n\nWe followed two well-known strategies for reducing the thermal relaxation time of an azobenzene: (i) adding a push–pull group and (ii) forming a tautomerizable azohydrazone16. Correspondingly, we designed two polymerizable azo-derivatives (Fig. 1, Extended Data Fig. 1). The first molecule corresponds to a hydrogen-bonded azopyridine (I) and the second one has a hydroxyl group at the ortho position (II). Each azo-derivative $(7\\mathrm{mol\\%})$ ) was copolymerized with a mixture of a liquid-crystal monoacrylate (RM23, $42\\mathrm{mol}\\%$ ) and a liquid-­crystal diacrylate (RM82, $50\\mathrm{mol\\%}$ ), initiated by $1\\mathrm{mol\\%}$ of photoinitiator. The mixtures containing I and II are henceforth denoted as mixtures I and II, respectively, and the azo-derivatives themselves are referred to ­simply as I or II. The monomer mixture was aligned before polymerization in a splayed configuration over the cross-section of a thin film, with homeotropic alignment at one surface and planar alignment at the other. This splay-aligned configuration was chosen because it gives rise to the largest deformation in free-standing films, as compared to uniaxial alignment, owing to the expansion and shrinkage behaviour that occurs on opposite sides of the liquid-crystal network (LCN) film, as explored in ref. 17 and shown in Supplementary Video 1. \n\nWe studied the thermal relaxation of LCN films made of mixtures I and II using ultraviolet spectroscopy, and compared them to LCNs containing: (i) A6MA, a commonly used azobenzene for photoresponsive materials; (ii) Disperse Red 1 acrylate (DR1A), a known commercial ultrafast azo-derivative; and (iii) AzoPy, which corresponds to I without the hydrogen bond. See Extended Data Fig. 2 and Extended Data Table 1 for the compositions of the mixtures and their thermal characterization. \n\nAs shown in Fig. 1, at room temperature, the half-life of A6MA is long, typically more than $^\\mathrm{1h}$ , whereas azo-derivatives I and II exhibit much faster relaxation. However, temperature plays an important part in the relaxation process (Fig. 1 and Extended Data Fig. 3), and the half-life drops below 1 s at $70^{\\circ}\\mathrm{C}$ and $90^{\\circ}\\mathrm{C}$ for II and I, respectively. \n\n![](images/93a324722ff1508fd0ce080338c8dc9be13ae8983d3772def02bd0568ae3e141.jpg) \nFigure 1 | Azo dyes and their cis-to-trans relaxation. a, Chemical structures of azo-derivatives and liquid crystal mesogens. b, The half-lives of the cis-to-trans relaxation of the azo-derivatives decrease exponentially as a function of temperature. \n\n![](images/9d6c1a5034b515065e9cb23b8dd638e08c46d934406a5bbf6b8b9caa022596c7.jpg) \nFigure 2 | Mechanism of wave propagation and parameters that s.d. ${\\mathrm{'}n=3}$ ). c, Influence of light intensity on wave frequency. Planar side influence the propagation speed. a, Schematic of the experimental set-up, up, $L=22\\mathrm{mm}$ . Error bars, s.d. $\\displaystyle(n=3)$ ). d, e, Comparison of simulation showing a polymeric film that is constrained at both extremities under an (left) and experimental (right) data for planar-up (d) and homeotropic-up oblique-incidence light source (left). The blue arrows show the way the (e) configurations (Supplementary Videos 4 and 5). The arrows indicate film deforms while the red ones indicate the propagation direction of the the propagation direction of the wave. The scale bar represents the wave. b, Frequency of the wave versus the angle of the incident light. Black, magnitude of the scalar order parameter, S (colour scale: blue, low; red, planar side up with an end-to-end distance of $L=22\\mathrm{mm}$ ; red, planar side high). Incident light, $10^{\\circ}$ from the left; $L=22\\mathrm{mm}$ ; scale bars, $5\\mathrm{mm}$ ; films up with $L=17\\mathrm{mm}$ ; blue, homeotropic side up with $L=22\\mathrm{mm}$ . Error bars, made of mixture I; film size, $23\\mathrm{mm}\\times4\\mathrm{mm}\\times20\\upmu\\mathrm{m}$ . \n\nComparing AzoPy with I shows that the hydrogen bond enhances the push–pull effect, which results in a further decrease in the half-life. As predicted, the thermal relaxation of DR1A is very fast, less than 1 s at $30^{\\circ}\\mathrm{C}.$ . Furthermore, the cis-to-trans thermal relaxation of the azo-­derivatives follows a stretched exponential function, as previously described for such glassy materials18–20. \n\nWith the aim of translating this fast molecular relaxation to the ­macroscopic deformation of the LCNs, small thin strips of the ­polymer were clamped at one end and exposed to ultraviolet light. As ­previously reported, when A6MA is used, the film bends and remains in this ­position when the light is switched off. When I or II is used, the ­bending and relaxation are both instantaneous as illumination is applied and removed. However, on the basis of the molecular ­relaxation at room temperature, the time to full recovery is expected to be more then $10\\mathrm{{min}}$ and about $1\\mathrm{min}$ for I and II, respectively, which is much slower than the observed macroscopic deformation. This faster ­recovery can be explained by a large increase in the temperature of the film of several tens of degrees during ultraviolet exposure. In the exposed films, we recorded temperatures of up to $85^{\\circ}\\mathrm{C}.$ —higher than the glass transition temperature $(T_{\\mathrm{g}})$ of the LCN, which is measured to be around $50^{\\circ}\\mathrm{C}$ . At this temperature, the half-life decreases to $2s$ and less than 1 s for I and $\\mathbf{II}$ , respectively. It has recently been shown21 that in the direct vicinity of the azobenzene molecules the temperature can reach $228^{\\circ}\\mathrm{C},$ and even higher temperatures have been calculated22. On the basis of these findings, we postulate that the molecular relaxation of the azobenzene moieties is faster because of the higher temperatures; hence, we expect even faster macroscopic relaxation. \n\nTo benefit from this fast relaxation, we studied different sample ­configurations. When a strip of a thin LCN film made of mixture I is placed on a glass surface, enabling free movement without further ­constraints, the polymeric film deforms in a caterpillar-like fashion. When the film is clamped at one end only, we observe oscillations ­similar to those reported in ref. 6. Finally, when two edges of the film are glued together, a tube forms. On illumination, the tube buckles and continuously deforms, as shown (in real time) in Supplementary Video 2. \n\nMore interestingly, when the same film (that is, made from mixture I) is attached at both ends to a substrate and exposed to light $(405\\mathrm{nm})$ , a continuous travelling wave is initiated. Because the distance between the two ends is shorter than the length of the strip, a buckled initial shape is created (Fig. 2a). Turning on a fixed light source initiates a wave that continuously regenerates and propagates in a repeating, snake-like motion until the light is turned off. Similar results were obtained when using a film made of mixture II or DR1A, which has an extremely short half-life of $1.9s$ at $25^{\\circ}\\mathrm{C}$ . However, when using an LCN containing A6MA, no continuous wave could be obtained owing to the thermal relaxation being too slow (see Supplementary Video 3). This result suggests that the wave propagation is not restricted to the custom-made azo-derivatives; we anticipate that any molecule with a short half-life could give rise to such types of deformation. In the rest of this study, LCN films made with mixture I were used. \n\nThe use of a splay-aligned LCN gives an extra degree of control to the system: the direction of the wave is controlled by the orientation of the film with regard to the planar and homeotropic sides. As demonstrated in Fig. 2a, when the planar side is placed upwards, the induced wave propagates away from the light source; when the homeotropic side is up, the wave propagates towards the light source. Supplementary Videos 4 and 5 show (in real time) this light-induced periodic wave motion for planar-up and homeotropic-up configurations, respectively. These two distinct wave trajectories are driven by the different photoactuation responses of the two sides of the film. On illumination, the planar side shrinks strongly along the long axis of the film and expands weakly along the other two axes, causing the light-exposed area to curve downwards. In contrast, the homeotropic side shrinks strongly along the thickness axis of the film and expands weakly along the other two axes, causing the light-exposed area to curve upwards. Both types of deformation also induce slight curvature across the short axis of the film, as in a ‘slap band’ bracelet. This slight deformation can produce mechanical instabilities such as snap-through transitions. As discussed further below, effects from self-shadowing produce a feedback loop that enables wave propagation and regeneration, because continuous displacement of the wave changes the position of the exposed and unexposed areas. \n\nThe speed of the displacement is greatly influenced by whether the planar or the homeotropic side is facing the light source. With the ­planar side towards the oblique incoming light, the wave travels in the direction away from the lamp with a frequency of $2.5{\\mathrm{s}}^{-1}$ . When the film is flipped to put the homeotropic side upwards, the wave has a slower frequency of $\\stackrel{\\cdot}{0.8}s^{-1}$ under the same exposure conditions, and the wave travels towards the light. \n\nThe incident angle between the light and the film is also found to influence the propagation speed of the generated waves. The wave propagates for angles of $0^{\\circ}-45^{\\circ}$ with the planar side up and of $0^{\\circ}-15^{\\circ}$ with the homeotropic side up (Fig. 2b and Extended Data Fig. 4). Above these critical values, the film becomes fully exposed, cancelling the self-shadowing effect. This working range of angles is valid for ­distances between the two attached points of $2.2\\mathrm{-}1.6\\mathrm{cm}$ for a film with an initial length of $2.3\\mathrm{cm}$ , for example, buckled with the end-to-end distance reduced by up to $30\\%$ . In the planar-up configuration, a ­maximum speed is found for angles of $10^{\\circ}-25^{\\circ}$ . The intensity of the light also greatly influences the speed at which the waves travel. As shown in Fig. 2c, for a sample illuminated at an intensity of $510\\mathrm{mW}\\mathrm{cm}^{-2}$ , a frequency of $3s^{-1}$ is reached. When the intensity is reduced to $230\\mathrm{mW}\\mathrm{cm}^{-2}$ , the frequency decreases to $0.5s^{-1}$ . The motion stops entirely for light intensities of less than $175\\mathrm{mW}\\mathrm{cm}^{-2}$ , owing to the photo-thermal effect. For intensities below $150\\mathrm{mW}\\mathrm{cm}^{-2}$ , the temperature remains below the glass transition temperature $T_{\\mathrm{g}}$ (Extended Data Fig. 5a). A reference measurement with a uniaxially aligned film did not result in wave deformation, despite crossing $T_{\\mathrm{g}}$ on illumination (Extended Data Fig. 5b). \n\nAs mentioned above, temperature plays an important part, as shown in Fig. 3. On exposure, the overall temperature of the film rises to roughly $50^{\\circ}\\mathrm{C}$ . When the wave reaches the clamped end of the film, it arrests for a short period before a new wave forms and starts to ­propagate. During this very short period, the temperature reaches values close to $100^{\\circ}\\mathrm{C}$ (Fig. 3 and Extended Data Fig. 6; Supplementary Videos 4 and 5). The substantial heat generated also contributes to the deformation through thermal expansion, and is considered in the mechanism of creation and propagation of the wave. \n\n![](images/0578d657693a3498c620a6f334f3cf42e2f9ae4adb38a3ed548a26ba953b9ba5.jpg) \nFigure 3 | Temperature traces recorded by an infrared thermal camera during wave propagation. LCN films $\\cdot L=22\\mathrm{mm}$ ) made of mixture I were exposed to ultraviolet light $(500\\mathrm{mW}\\mathrm{cm}^{-2}$ ). a–d, Temperature profiles during exposure at the homeotropic $(\\mathbf{a},\\mathbf{b})$ and planar $(\\mathbf{c},\\mathbf{d})$ sides of the film. a, c, Snapshots of the temperature distribution (colour scale: yellow, high; blue, low) across the film at different times $t$ (as indicated); local hot spots are evident. The schematics at the top of a and c represent the clamped film and wave direction. b, d, Oscillating temperatures at positions 1 (black), 2 (red) and 3 (blue) as indicated in a and c. \n\nTo gain insight into the mechanism of this wave generation and its directionality, we carried out finite-element elastodynamics ­analysis. We consider an LCN film with a ‘blueprinted’ director field23, with the director homeotropic on one side and planar on the other with a linear gradient in between producing splay alignment (Fig. 2a). In ­simulations, the film is initially buckled into a curved shape, clamped at both ends on a solid substrate, then relaxed to mechanical ­equilibrium. We model incoming light as a plane wave from the left side of the ­sample at an angle of $10^{\\circ}$ above the horizontal. To determine which ­elements on the film surface are illuminated, incident light is ­represented as a grid of parallel rays and their first intersection with the surface is calculated. We model the light-induced motion of the film using a Hamiltonian-based elastodynamics algorithm with explicit time ­stepping. Our Hamiltonian-based model includes the kinetic energy of the film, its elastic strain energy and the coupling between nematic order and mechanical strain23–25. Details of the simulation model are provided in Methods. \n\nTo model photoactuation, we make a rough approximation that the scalar order parameter S in each element along the surface decreases linearly in time when illuminated and increases linearly in time when shadowed, bounded by upper and lower limits. As S decreases within a volume element, coupling between nematic order and strain causes the material to shrink along the local director and expand in the two orthogonal directions. The decrease in S can be caused by either the isomerization of the azo units or the thermal expansion that is induced by the light exposure. In Fig. 2d, e, the colour indicates the magnitude of the scalar order parameter S, with blue and red regions showing the lowest and highest values, respectively. \n\nThe results of our simulations demonstrate the feedback ­mechanism that continuously generates waves. Consider first the planar-up configuration (Fig. 2d). As light shines from the left and strikes the film, the local order parameter decreases in the area shown in blue. There, the top surface of the film contracts along its long axis and the film curves downwards creating a bump just after the illuminated part. The resulting stress pushes the crest of the bump from the middle of the film towards the right, away from the incident light. When the crest approaches the clamped end, it arrests, and the upward curvature that is induced in the blue region drives the formation of a new wave crest to the left. Once the new crest grows to a critical size, it shadows the old crest, which then disappears via a pop-through transition. This process repeats continuously, as shown in Supplementary Video 4. \n\n![](images/f009de350fe952bac6ae29e46e5f4522a136e99717b65031eb13636089c15e67.jpg) \nFigure 4 | Two example applications, demonstrating rejection of contaminants and oscillatory transport of a framed film. \na, Photoactuated wave motion ejects sand from the surface of the film via a snap-through release of energy, demonstrating the mechanism for a self-cleaning surface; see Supplementary Video 6. b, Schematic representation of photoactuated locomotion along a flat substrate. c, d, The short ends of the active film, planar side up (c) or homeotropic side up (d), are fixed to a passive frame. The direction of motion is dependent on the side that is exposed; see also Supplementary Videos 7 and 8. The dashed line in c represents the top surface of the glass plate. The composition and dimensions of the active film are as in Fig. 2; plastic frame, $15\\mathrm{mm(length)}\\times5\\mathrm{mm}$ (width); scale bars, $5\\mathrm{mm}$ . \n\nNext consider the homeotropic-up configuration (Fig. 2e). In the illuminated region, the homeotropic material at the top of the film expands along both directions orthogonal to the surface normal, inducing upwards curvature. The resulting stress pulls the crest of the bump towards the left, towards the light source, where it arrests when it approaches the clamped end. The shadowed region relaxes back towards equilibrium, causing the crest to shrink until light passes over it and nucleates the growth of a new crest to the right. There is a brief time delay while the new crest forms, followed by a popthrough transition whereby the old crest disappears and the new crest grows. This process repeats continuously, as shown in Supplementary Video 5. \n\nThere is qualitative agreement between the simulated trajectories and experimental observations (see Supplementary Videos 4 and 5). The simulations demonstrate that light-induced actuation, self-­shadowing and mechanical constraints are sufficient to create a feedback loop, producing wave generation that is driven by a constant light source. Additional simulations show that both pre-buckling the film and clamping it on a solid substrate are necessary to enable the pop-through transition at the end of each cycle. \n\nTo demonstrate the versatility of our experimental system, we developed a few examples where wave propagation is used to achieve lightdriven devices. First, we place sand on the film, either before or during illumination, at the side of the origin of the wave (Fig. 4a). While the wave develops, the sand is continuously transported towards the opposite side of the film. When energy is stored in the film, for instance when the weight of the sand inhibits wave propagation, the film ­suddenly releases the energy, ejecting the sand far from the film. The film can be used many times without showing any damage or fatigue with respect to the sand or the light. Second, we used the LCN film to carry uphill an object that is much heavier and larger in size than itself. The repeated propagation of the wave makes such a ­challenging operation possible by simultaneously pushing the object upwards and preventing it from sliding (Supplementary Video 6). Finally, and most remarkably, we realized a light-fuelled self-propelled device using photoactuated mechanical wave generation. When the LCN is attached to a plastic frame (Fig. 4b), the device moves while the wave is ­travelling through the sample. The travelling direction is controlled by the ­orientation of the film, as described previously, demonstrating directional light-induced locomotion. Small objects (with masses of a few milligrams) can be attached to the frame and transported over large distances (centimetres). Videos (in real time) of the light-fuelled device are provided in Supplementary Videos 7 and 8. We anticipate that the generation of waves as demonstrated here has potential applications in fields such as photomechanical energy harvesting, self-cleaning by contaminant rejection, and miniaturized transport of species in poorly accessible places. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# received 19 January; accepted 16 May 2017. \n\n1.\t Tabata, O., Hirasawa, H., Aoki, S., Yoshida, R. & Kokufuta, E. Ciliary motion actuator using self-oscillating gel. Sensor. Actuat. A 95, 234–238 (2002). \n2. Murase, Y., Maeda, S., Hashimoto, S. & Yoshida, R. Design of a mass transport surface utilizing peristaltic motion of a self-oscillating gel. Langmuir 25, 483–489 (2009). \n3. Maeda, S., Hara, Y., Yoshida, R. & Hashimoto, S. Peristaltic motion of polymer gels. Angew. Chem. Int. Ed. 47, 6690–6693 (2008). \n4. Maeda, S., Hara, Y., Sakai, T., Yoshida, R. & Hashimoto, S. Self-walking gel. Adv. Mater. 19, 3480–3484 (2007). \n5. Martinez, A. & Smalyukh, I. I. Light-driven dynamic Archimedes spirals and periodic oscillatory patterns of topological solitons in anisotropic soft matter. Opt. Express 23, 4591–4604 (2015). \n6. White, T. J. et al. A high frequency photodriven polymer oscillator. Soft Matter 4, 1796–1798 (2008). \n7. Yu, Y., Nakano, M. & Ikeda, T. Photomechanics: directed bending of a polymer film by light. Nature 425, 145 (2003). \n8. van Oosten, C. L., Harris, K. D., Bastiaansen, C. W. M. & Broer, D. J. Glassy photomechanical liquid-crystal network actuators for microscale devices. Eur. Phys. J. E 23, 329–336 (2007). \n9. Li, M.-H., Keller, P., Li, B., Wang, X. & Brunet, M. Light-driven side-on nematic elastomer actuators. Adv. Mater. 15, 569–572 (2003). \n10.\t Iamsaard, S. et al. Conversion of light into macroscopic helical motion. Nat. Chem. 6, 229–235 (2014). \n11.\t Yamada, M. et al. Photomobile polymer materials: towards light-driven plastic motors. Angew. Chem. Int. Ed. 47, 4986–4988 (2008). \n12.\t Bandara, H. M. D. & Burdette, S. C. Photoisomerization in different classes of azobenzene. Chem. Soc. Rev. 41, 1809–1825 (2012). \n13.\t García-Amorós, J. & Velasco, D. Recent advances towards azobenzene-based light-driven real-time information-transmitting materials. Beilstein J. Org. Chem. 8, 1003–1017 (2012). \n14.\t van Oosten, C. L., Bastiaansen, C. W. M. & Broer, D. J. Printed artificial cilia from liquid-crystal network actuators modularly driven by light. Nat. Mater. 8, 677–682 (2009). \n15.\t Camacho-Lopez, M., Finkelmann, H., Palffy-Muhoray, P. & Shelley, M. Fast liquid-crystal elastomer swims into the dark. Nat. Mater. 3, 307–310 (2004). \n16.\t Brode, W. R., Gould, J. H. & Wyman, G. M. The relation between the absorption spectra and the chemical constitution of dyes. XXV. Phototropism and cis-trans isomerism in aromatic azo compounds. J. Am. Chem. Soc. 74, 4641–4646 (1952). \n17.\t Mol, G. N., Harris, K. D., Bastiaansen, C. W. M. & Broer, D. J. Thermo-mechanical responses of liquid-crystal networks with a splayed molecular organization. Adv. Funct. Mater. 15, 1155–1159 (2005). \n18.\t Mita, I., Horie, K. & Hirao, K. Photochemistry in polymer solids. 9. Photoisomerization of azobenzene in a polycarbonate film. Macromolecules 22, 558–563 (1989). \n19.\t Poutanen, M., Ikkala, O. & Priimagi, A. Structurally controlled dynamics in azobenzene-based supramolecular self-assemblies in solid state. Macromolecules 49, 4095–4101 (2016). \n20.\t Serra, F. & Terentjev, E. M. Effects of solvent viscosity and polarity on the isomerization of azobenzene. Macromolecules 41, 981–986 (2008). \n21.\t Vapaavuori, J., Laventure, A., Bazuin, C. G., Lebel, O. & Pellerin, C. Submolecular plasticization induced by photons in azobenzene materials. J. Am. Chem. Soc. 137, 13510–13517 (2015). \n22.\t Fang, G. J. et al. Athermal photofluidization of glasses. Nat. Commun. 4, 1521 (2013). \n23.\t Sawa, Y. et al. Shape and chirality transitions in off-axis twist nematic elastomer ribbons. Phys. Rev. E 88, 022502 (2013). \n24.\t Konya, A., Gimenez-Pinto, V. & Selinger, R. L. B. Modeling defects, shape evolution, and programmed auto-origami in liquid crystal elastomers. Front. Mater. 3, 24 (2016). \n25.\t de Haan, L. T. et al. Accordion-like actuators of multiple 3D patterned liquid crystal polymer films. Adv. Funct. Mater. 24, 1251–1258 (2014). \n\nSupplementary Information is available in the online version of the paper. \n\nAcknowledgements This work was supported financially by the Netherlands Organization for Scientific Research (NWO; TOP PUNT grant 10018944), the European Research Council (Vibrate ERC, grant 669991), and US National Science Foundation grants DMR 1409658 and CMMI 1436565. A.H.G. acknowledges funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7-2013, grant number 607602. Computing resources provided by the Ohio Supercomputer Center (M.V., A.K., R.L.B.S.) R.L.B.S. acknowledges F. Nazarov for discussions and B. L. Mbanga for his role in developing the Finite Element Method algorithm. The work of D.J.M. forms part of the research programme of the Dutch Polymer Institute (DPI), project 776n. \n\nAuthor Contributions A.H.G. and D.J.M. designed the experiments. A.H.G. studied the macroscopic deformations and analysed the results. D.J.M. synthesized I. G.V. synthesized II. M.V. and A.K. developed the theoretical model. D.J.B. supervised the overall research. E.W.M. participated in the interpretation of the results. R.L.B.S. supervised the theoretical modelling. All authors contributed to the writing of the manuscript. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests. Readers are welcome to comment on the online version of the paper. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Correspondence and requests for materials should be addressed to D.J.B. (D.Broer@tue.nl; experiments) or R.L.B.S. (rselinge@kent.edu; theory). \n\nReviewer Information Nature thanks T. Ikeda, R. Verduzco and Y. Yu for their contribution to the peer review of this work. \n\nMethods \nSynthesis of azopyridine $\\mathbf{(AzoPy)}$ ), precursor of I. See Extended Data Fig. 1 for the chemical structures. \n4-(4-hydroxyphenylazo)pyridine (ii). 4-(4-hydroxyphenylazo)pyridine (ii) was prepared according the procedure described in ref. 26. \n$^\\mathrm{i}\\mathrm{H}$ NMR ${\\bf{400M H z}}$ , $\\mathrm{[D_{6}]D M S O)}$ : $\\delta\\left(\\mathrm{p.p.m.}\\right)=10.64$ (s, OH, 1H), 8.75 $(\\mathrm{d},J{=}6\\mathrm{Hz},$ , 2H), 7.86 $(\\mathrm{d},J{=}9\\mathrm{Hz},2\\mathrm{H},$ , 7.66 $(\\mathrm{d},J{=}6\\mathrm{Hz},2\\mathrm{H},$ , 6.98 $(\\mathrm{d},J{=}9\\mathrm{Hz},$ 2H). $^{13}\\mathrm{CNMR}$ ( $\\mathrm{100MHz}$ , $\\mathrm{[D_{6}]D M S O_{4}^{'}}$ ): $\\delta(\\mathrm{p.p.m.})=162.76$ , 157.28, 151.72, 145.71, 126.25, 116.65, 116.26. \n$^{6}$ -bromohexyl methacrylate (iii). 6-bromohexyl methacrylate (iii) was prepared according the procedure described in ref. 27, except that here acryloyl chloride was replaced by methacryloyl chloride. \n$^1\\mathrm{H}$ NMR ${'}_{400}\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}.$ ): $\\delta(\\mathtt{p.p.m.})=6.10$ (s, 1H), 5.55 (s, 1H), 4.15 $(\\mathrm{t},J=7\\mathrm{Hz},$ , 2H), 3.41 $\\mathrm{\\Phi_{(t,}}J{=}7\\mathrm{Hz}$ , 2H), 1.94 (s, 3H), 1.88 (p, $,J{=}7\\mathrm{Hz}$ , 2H), 1.70 $(\\mathrm{p},J{=}7\\mathrm{Hz},2\\mathrm{H}$ ), 1.45 (m, 4H). \n$^{13}\\mathrm{C}$ NMR $\\boldsymbol{\\cdot}100\\mathrm{MHz}$ , CDCl3): $\\delta(\\mathrm{p.p.m.})=167.47$ , 136.46, 125.24, 64.52, 33.68, 32.62, 28.46, 27.80, 25.23, 18.33. \nIR (ATR): $\\bar{\\nu}_{\\mathrm{max}}(c m^{-1})=838$ , 937, 989, 1,011, 1,139, 1,159, 1,248, 1,294, 1,317, 1,404, 1,418, 1,454, 1,498, 1,582, 1,597, 1,636, 1,716, 2,007, 2,863, 2,940. \n4-(4-(6-methacryloxy)hexyloxyphenylazo)pyridine (AzoPy). Compound ii $(0.50\\mathrm{g},$ $2.5\\mathrm{mmol}$ ), compound iii $(0.88g,2.75\\mathrm{mmol})$ ), $\\mathrm{K}_{2}\\mathrm{CO}_{3}\\left(1.40\\mathrm{g},10\\mathrm{mmol}\\right)$ and a grain of KI were suspended in $25\\mathrm{ml}$ butanone under an argon atmosphere before the mixture was heated to reflux. After $15\\mathrm{h}$ the mixture was cooled and filtered. $25\\mathrm{ml}$ butanone was added to the filtrate. The filtrate was washed three times with $0.1\\mathrm{M}$ KOH and once with brine. The organic layer was dried with $\\mathrm{MgSO_{4},}$ filtered and concentrated before it was subjected to column chromatography $30\\%$ EtOAc in heptane). Yield, $0.539\\mathrm{g}$ (1.47 mmol, $59\\%$ ) orange solid. \n$\\mathrm{{^{1}H}}$ NMR ${\\bf\\Phi}_{\\mathrm{400MHz}}$ , $\\mathrm{CDCl}_{3}$ ): $\\delta\\left(\\mathrm{p.p.m.}\\right)=8.77$ $\\mathrm{\\Phi}_{\\cdot}\\mathrm{d},J{=}6\\mathrm{Hz}$ , 2H), 7.95 $(\\mathrm{d},J{=}6\\mathrm{Hz},$ 2H), 7.01 (d $\\lvert,J=11\\mathrm{Hz}$ , 2H), 6.10 (s, 1H), 5.54 (s, 1H), 4.17 $\\mathrm{\\Phi_{(t,}}J=7\\mathrm{Hz}$ 2H), 4.06 $(\\mathrm{t},J{=}6\\mathrm{Hz},$ 2H), 1.94 (s, 3H), 1. $35\\:(\\mathrm{p},J=5\\mathrm{Hz},2\\mathrm{H},$ , 1.71 $(\\mathrm{d},J{=}7\\mathrm{Hz},$ 2H), 1.51 $\\mathrm{(m,4H)}$ ; see Extended Data Fig. 7. \n$^{13}\\mathrm{C}$ NMR (100 MHz, $\\mathrm{CDCl}_{3}$ ): $\\delta\\left(\\mathrm{p.p.m.}\\right)=167.52$ , 162.81, 157.44, 151.22, 146.74, 136.50, 125.61, 125.26, 116.16, 114.86, 68.27 64.59, 29.03, 28.56, 25.71, 18.35. IR (ATR): $\\bar{\\nu}_{\\mathrm{max}}(c m^{-1})=737$ , 838, 937, 989, 1,011, 1,139, 1,159, 1,248, 1,294, 1,317, 1,404, 1,418, 1,454, 1,498, 1,597, 1,636, 1,715, 2,007, 2,862, 2.940. \nMS (MALDI-ToF): $m/z$ calc. $\\mathrm{C}_{21}\\mathrm{H}_{25}\\mathrm{N}_{3}\\mathrm{O}_{3}+\\mathrm{H}^{+}$ , 368.20 $[\\mathrm{M}+\\mathrm{H}]^{+}$ ; found, 368.21. \nSynthesis of II. $(E)$ -4-((4-hydroxyphenyl)diazenyl)benzene-1,3-diol. 4-aminophenol (15 mmol, 1.6 g, 1 equiv.) was suspended in water $\\left(4.1\\mathrm{ml}\\right)$ . The reaction mixture was stirred and cooled to $0^{\\circ}\\mathrm{C}$ with an ice bath. Concentrated HCl $\\mathrm{\\langle4.1ml\\rangle}$ was added dropwise. After $10\\mathrm{min}$ of stirring, a solution of sodium nitrite $\\mathrm{(17mmol)}$ $1.14{\\mathrm{g}}{\\mathrm{.}}$ , 1.1 equiv.) in water $(3.5\\mathrm{ml})$ was added dropwise into the mixture. The ­solution was stirred for $2\\mathrm{h}$ at $0^{\\circ}\\mathrm{C}$ . Then, this solution was added dropwise over $2\\mathrm{h}$ to a solution of resorcinol (15 mmol, $1.6\\mathrm{g}$ , 1 equiv.) dissolved in water $(3.5\\mathrm{ml})$ and NaOH (37.5 mmol, 1.5 g, 2.5 equiv.) at $0^{\\circ}\\mathrm{C}$ . Stirring was continued for 3 h while the mixture was warmed to room temperature. The solution was acidified with 1 M HCl and a red solid precipitated as the pure product with a yield of $85\\%$ . $^1\\mathrm{H}$ NMR $(400\\mathrm{MHz}$ , $\\mathrm{CD}_{3}\\mathrm{OD}$ ): $\\delta\\left(\\mathrm{p.p.m.}\\right)=7.68$ (d, $J{=}8.6\\mathrm{Hz}$ , 2H), 7.63 $(\\mathrm{d},J{=}9.0\\mathrm{Hz},$ , 1H), 6.89 $\\mathrm{\\Delta}Q,J{=}8.6\\mathrm{Hz},2\\mathrm{H}$ ), 6.48 $\\mathrm{\\Phi_{dd,}}J=9.0\\mathrm{Hz},J=2.3\\mathrm{Hz},$ 1H), 6.31 $(\\mathrm{d},J=2.3\\mathrm{Hz}$ , 1H). \n$^{13}\\mathrm{C}$ NMR ${\\bf\\Phi}_{\\mathrm{101MHz}}$ , $\\mathrm{CD}_{3}\\mathrm{OD}$ ): $\\delta$ $\\delta\\left(\\mathrm{p.p.m.}\\right)=163.05$ , 161.18, 156.64, 145.30, 134.66, 133.44, 124.38, 116.94, 109.46, 104.01. \nMS (MALDI-ToF): $m/z$ calc. $\\mathrm{C}_{12}\\mathrm{H}_{10}\\mathrm{N}_{2}\\mathrm{O}_{3}+\\mathrm{H}^{+}$ , 231.08 $[\\mathrm{M}+\\mathrm{H}]^{+}$ ; found, 231.03. \n(E)-6-(4-((4-((6-(acryloyloxy)hexyl)oxy)-2-hydroxyphenyl)diazenyl)phenoxy)hexyl acrylate—II. Trihydroxyazobenzene $(0.43\\mathrm{mmol}$ , $100~\\mathrm{{mg}}$ , 1 e quiv.), 6-­bromohexylacrylate27 $\\mathrm{0.86mmol}$ , $204\\mathrm{mg}$ , 2 equiv.), potassium carbonate $(0.86\\mathrm{mmol}$ , $120\\mathrm{mg}$ , 2 equiv.) and sodium iodide (catalytic amount) were ­suspended in DMF $\\left(5\\mathrm{ml}\\right)$ under an argon atmosphere and heated at $70^{\\circ}\\mathrm{C}$ overnight. The mixture was cooled, filtered and concentrated under vacuum. Chloroform was added to the mixture and the organic layer was washed with saturated $\\mathrm{NaHCO}_{3}$ solution. The organic layer was dried over magnesium sulfate and concentrated. The crude mixture was subjected to chromatography column ( $5\\%$ methanol in chloroform). The desired compound was obtained as an orange powder with a yield of $80\\%$ . \n$^1\\mathrm{H}$ NMR ${}^{\\cdot}400\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3,}$ ): $\\delta\\left(\\mathrm{p.p.m.}\\right)=13.68$ (s, 1H), 7.77 $(\\mathrm{d},J=8.8\\mathrm{Hz},$ , 2H), 7.73 (d, $J{=}8.8\\mathrm{Hz}$ , 1H), 6.97 $(\\mathrm{d},J{=}8.8\\mathrm{Hz}$ , 2H), 6.58 (dd, $J{=}8.8\\mathrm{Hz}$ , $J{=}2.6\\mathrm{Hz}$ , 1H), 6.40 (m, 3H), 6.12 (dd, $J{=}17.3\\mathrm{Hz},J{=}10.4\\mathrm{Hz},$ 2H), 5.82 (dd, $J{=}10.4\\mathrm{Hz}$ , \n\n$J{=}1.5\\mathrm{Hz}$ , 2H), 4.18 (m, 4H), 4.02 (m, 4H), 1.83 (m, 4H), 1.72 (m, 4H), 1.50 $(\\mathrm{m},8\\mathrm{H})$ ; see Extended Data Fig. 7. \n\n$^{13}\\mathrm{C}$ NMR (101 MHz, $\\mathrm{CDCl}_{3}$ ): $\\delta\\left(\\mathrm{p.p.m.}\\right)=166.46$ , 162.82, 161.08, 155.76, 144.46, 134.16, 132.79, 130.69, 128.72, 123.45, 115.11, 108.28, 101.99, 68.33, 68.29, 64.64, 29.22, 29.11, 28.70, 25.88, 25.86. \n\nMS (MALDI-ToF): $m/z$ calc. $\\mathrm{C}_{30}\\mathrm{H}_{38}\\mathrm{N}_{2}\\mathrm{O}_{7}+\\mathrm{H}^{+}$ , 539.28 $[\\mathrm{M}+\\mathrm{H}]^{+}$ ; found, 539.32. Mixture and film preparation. AzoPy was mixed with 6OBA (4-((6-(acryloyloxy) hexyl)oxy)benzoic acid; custom-made by Synthon Chemicals) in an equimolar ratio to form a supramolecular diacrylate. The molecules were dissolved in hot ethanol; upon cooling, compound I precipitates. \n\nTo form the LCN based on I, $9\\mathrm{mg}\\left(7\\mathrm{mol}\\%\\right)$ of I, $61\\mathrm{mg}\\left(50\\mathrm{mol\\%}\\right)$ of RM82 and $30\\mathrm{mg}\\left(42\\mathrm{mol}\\%\\right)$ of RM23 were dissolved in dichloromethane and subsequently the solvent was evaporated. To prepare the LCN based on II, $63\\mathrm{mg}\\left(50\\mathrm{mol\\%}\\right)$ of RM82, 30 mg $42\\mathrm{mol}\\%)$ of RM23 and 7 mg $(7\\mathrm{mol\\%})$ of azo-derivative II, were used to achieve a similar cross-link density and molar amount of azo compound. The equivalent of $1\\mathrm{wt\\%}$ of photoinitiator, Irgacure 819, was also added to perform photopolymerization. \n\nCustom-made cells were prepared by gluing together a glass plate coated with polyimide and a clean, uncoated glass plate that was treated with ozone. The spacing was chosen to be $20\\upmu\\mathrm{m}$ and fixed using glass beads of the respective diameter. Consequently, all of the LCNs used for macroscopic deformation have a thickness of $20\\upmu\\mathrm{m}$ . \n\nThe cells were filled by capillary action at $95^{\\circ}\\mathrm{C}$ , at which temperature the ­mixtures are isotropic. Once the cells were totally filled, the temperature was decreased to reach the nematic phase, at $80^{\\circ}\\mathrm{C}$ . The polymerization was ­performed at this temperature for about $45\\mathrm{{min}}$ , with an Exfo Omnicure S2000 equipped with a $320{-}500{\\cdot}\\mathrm{nm}$ filter. The light intensity during the polymerization is about $50\\pm15\\mathrm{mW}\\mathrm{cm}^{-2}$ . A $405\\mathrm{-nm}$ or $455\\mathrm{-nm}$ cut-off filter was used with I and II, respectively, to prevent premature isomerization of the azobenzene. After ­photopolymerization, the film was post-cured at $130^{\\circ}\\mathrm{C}$ for $10\\mathrm{{min}}$ and slowly cooled to room temperature. \n\nWe performed differential scanning calorimetry on both the mixture and the polymerized films (TA instrument Q1000) (Extended Data Fig. 2). The maximum absorption was determined using a spectrophotometer Shimadzu UV-31020. \n\nThe films were peeled off and cut into the desired shapes using a razor blade. They were typically cut as long strips $(2.3\\mathrm{cm}\\times4\\mathrm{mm})$ , with the alignment director of the molecule parallel to the long edge. Actuation. The azo-derivative-containing films were actuated using 405-nm LED light (ThorsLab) mounted with a collimator. The ultraviolet intensity at the focus point was $510\\mathrm{mW}\\mathrm{cm}^{-2}$ . The films were unclamped, clamped at one side, or taped at both ends. The deformations were recorded with a camera and the recordings were further treated with image analysis software. \n\nThe sample used to measure the frequencies shown in Fig. 2 are $23\\mathrm{mm}$ long, $4\\mathrm{mm}$ wide and $20\\upmu\\mathrm{m}$ thick. The ends are fixed at $2.2\\mathrm{cm}$ or $1.7\\mathrm{cm}$ apart using tape, which produces a pre-set curvature. The illumination is fixed and comes from the left side. \n\nTo create the device presented in Fig. 4c, d, the film is stuck to a passive frame. The passive frame applies a mechanical constraint, allowing the wave to propagate. Locomotion is driven by self-shadowing effects that produce a feedback loop. Characterization techniques. The mesophases of the mixtures and the alignment of the LCNs were verified using polarized optical microscopy (Leica D300). \n\nThe thermal properties $\\cdot_{\\mathrm{{Z}_{g})}}$ of the LCNs were determined using differential scanning calorimetry (TAinstrument Q1000). Three cycles from $-70^{\\circ}\\mathrm{C}$ to $150^{\\circ}\\mathrm{C}$ at a rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ were performed. \n\nThe transmission spectrum were recorded with an ultraviolet spectrophotometer (Shimadzu UV-3102). Transmission is measured to ensure that light is going throughout the overall thickness of the films; see Extended Data Fig. 8. \n\nThe isomerization kinetic of the two azo-derivatives were characterized using an ultraviolet spectrophotometer (Shimadzu UV-3102) in kinetic mode. Measurements were recorded after 1 min exposure to light of a wavelength that corresponds to the absorbance maximum $-365\\mathrm{nm}$ $365\\mathrm{nm}$ , $405\\mathrm{nm}$ and $470\\mathrm{nm}$ for the films containing A6MA, I, II and DR1A, respectively. The relaxation was monitored by following the absorbance at the respective wavelength with a ­measurement done every 1 s (limit of the instrument). The absorbance could not be measured during the exposure to 365-nm LED light because the detector was over-saturated with the illuminating light. The first measurement was done within the first second after switching off the ultraviolet light, which gives a certain error on the precision of measurement especially when characterizing fast relaxation. Films with thicknesses of $5\\upmu\\mathrm{m}$ were used to analyse the photochemical properties. Thicker samples resulted in an absorbance that was too high. \n\nThe relaxation kinetics were fitted with a stretched exponential ­function: $A(t)=A_{\\infty}-(A_{\\infty}-A_{0})\\mathrm{e}^{-(k t)^{\\beta}}.$ . The stretch exponent parameter $\\beta=0.60\\pm0.05$ , $0.34\\pm0.02,0.72\\pm0.03$ , $0.49\\pm0.12$ and $0.44\\pm0.11$ for A6MA, DR1A, AzoPy, I and II, respectively. Because $A_{\\infty}=0$ and $A_{0}=-1$ for the normalized data, the half-life is $\\scriptstyle{\\tau={\\sqrt[[object Object]]{k}}}$ . \n\nFinite-element elastodynamics simulation. We model a nematic ­elastomer thin film discretized in a three-dimensional tetrahedral mesh with 5,717 nodes and 19,478 tetrahedral volume elements, with physical dimensions \n\n$1.5\\mathrm{cm}\\times0.1\\mathrm{cm}\\times250\\upmu\\mathrm{m}$ . The nematic director $\\pmb{n}$ within each element ­represents the splayed, ‘blueprinted’ structure that is present in the material, with a ­gradient from planar on one surface to homeotropic on the other. The scalar order ­parameter $s$ in each element varies with time as described below. Light-driven mechanical response is modelled via the Hamiltonian: \n\n$$\nH=\\frac{1}{2}{\\sum_{t}{V^{t}C_{i j k l}\\varepsilon_{i j}^{t}\\varepsilon_{k l}^{t}}}-\\alpha{\\sum_{t}{V^{t}\\varepsilon_{i j}^{t}(S^{t}-S^{0})\\frac{1}{2}\\Big(3n_{i}^{t}n_{j}^{t}-\\delta_{i j}\\Big)}}+\\frac{1}{2}{\\sum_{p}{m_{P}\\nu_{p}^{2}}}\n$$ \n\nHere, the first term is the elastic strain energy summed over elements $t,$ where $\\varepsilon_{i j}$ is the Green–Lagrange strain, $C_{i j k l}$ is a tensor of elastic constants and $V^{t}$ is the volume of element t in its reference state. The second term is the potential energy due to coupling of strain and nematic order, with coupling coefficient $\\alpha$ ; $S^{t}$ is the instantaneous nematic scalar order parameter in element $t$ and $S^{0}$ is the value in the fully relaxed nematic state. The last term represents kinetic energy using the lumped-mass approximation, with mass $m_{P}$ and instantaneous velocity $\\nu_{P}$ of each node $\\boldsymbol{p}$ . The coupling coefficient $\\alpha$ is set such that a uniaxially aligned sample shrinks in length by $44\\%$ when fully switched from nematic to isotropic. \n\nThe material density was set at $1.2\\mathrm{g}\\mathrm{cm}^{-3}$ in accord with experimental ­measurements. The elastic constants used in the simulation are a Poisson ratio of 0.49 and Young’s modulus of $3.4\\mathrm{MPa}$ . Although we might expect the material to have a Poisson ratio closer to the incompressible limit of 0.5, we used a reduced value to improve the numerical stability of the simulation. The computational mesh we used for our finite-element simulations has a length-to-thickness aspect ratio of 60, which is not as extreme as the film in the experimental system, which has a length-to-thickness ratio of 1,000. Because the bending energy scales as film thickness cubed, we used a softer Young’s modulus in the simulation so that the bending energy is still of the right order of magnitude. \n\nTo model photoactuation in the sample with splay geometry, the local scalar order parameter S in each element evolves as a function of time according to its exposure to light. We make the simplifying assumption that S decreases linearly in time for illuminated surface elements, and increases linearly in time for those in shadow. In both cases, S is bounded by upper and lower limits that refer ­respectively to the fully relaxed nematic state and the maximally disordered illuminated state. \n\nThe rate of change that we selected for S enables full transition in less than 1 s in each direction. \n\nThe effective force on each node is calculated as the derivative of the total potential energy with respect to node displacement. Every node experiences an effective force contribution from each tetrahedral element it touches, and these are summed vectorwise at each time step. Node equations of motion are integrated using the velocity Verlet algorithm, with new forces calculated at each time step, while clamped nodes at the ends of the film are held fixed. The optics calculation to determine which parts of the top surface of the film are illuminated is also repeated at each time step. \n\nThe substrate below the film is modelled as an infinitely hard and smooth ­surface, and collisions between the film and the substrate are treated as inelastic. \n\nDissipative forces proportional to node momentum are added to approximate the effects of air resistance. The finite-element simulation suggests that kinetic energy plays a key part in the shape response. If we increase the amount of ­dissipation (drag) in the finite-element simulation above a threshold value, then wave motion fails to initiate. \n\nThe simulation code is implemented for GPU acceleration. Using a time step of $2\\times10^{-5}\\mathrm{s},2\\times10^{6}$ time steps requires about $25\\mathrm{min}$ to execute on a single GPUequipped processor, modelling a total of 40 s of motion. \n\nThe finite-element model does not take into consideration the ­temperature dependence of the elastic moduli of the material or the effects of thermal ­expansion. These effects may be explored in more detailed modelling efforts in the future, but the present simulation demonstrates that they are not essential for generating perpetual wave motion. \n\nData availability. The datasets generated and analysed during this study are ­available from the corresponding authors on reasonable request. \n\n26.\t Naidek, K. P. et al. Ruthenium acetate cluster amphiphiles and their Langmuir-Blodgett films for electrochromic switching devices. Eur. J. Inorg. Chem. 2014, 1150–1157 (2014). \n27.\t Stumpel, J. E., Liu, D., Broer, D. J. & Schenning, A. P. H. J. Photoswitchable hydrogel surface topographies by polymerisation-induced diffusion. Chem. Eur. J. 19, 10922–10927 (2013). \n\n![](images/a48e4d3948712a3436b86165e7c19adeec1f62ea1be22b246f47088d693609ef.jpg) \nExtended Data Figure 1 | Synthetic routes for constituent compounds. Components of the LCN films include AzoPy, I and II. \n\n![](images/9b6a7b3b9c5d09391be6524895574cd382232e25010c0ce15dd3fef29d67c11d.jpg) \nExtended Data Figure 2 | Thermal characterization of the mixtures used in the study. a, Differential scanning calorimetry scans (second runs, exotherm downwards) showing the phase behaviour of all mixtures investigated. The nematic-to-isotropic transition occurs at $90^{\\circ}\\mathrm{C}$ . \n\nb, Differential scanning calorimetry scan of a polymerized sample showing the change in specific heat at the glass transition temperature $(T_{\\mathrm{g}})$ . The table summarizes the $T_{\\mathrm{g}}$ data of the various polymerized compositions. c, Normalized absorption spectra of the various mixtures investigated. \n\n![](images/b1ce4b0bc634061d73323cc660923d77dc41b5d871dd0b5e98db492ba910aacf.jpg) \nExtended Data Figure 3 | Relaxation kinetics of the azo-derivatives embedded in the LCN. a–d, Thermal relaxation from the photostationary cis stat to the trans state of A6MA (a), I (b), II (c) and DR1A (d) at various temperatures. Here $\\begin{array}{r}{\\Delta A=\\frac{A(t)-A_{\\infty}}{A_{\\infty}-A_{0}}}\\end{array}$ and $A(t)=-\\left(A_{\\infty}-A_{0}\\right)\\bar{e^{-(k t)^{\\beta}}}+A_{\\infty}$ . \n\n![](images/d0d9177932abc350a25668615057574c75195682a65f0cb9ac233fd1c1d3ff90.jpg) \nExtended Data Figure 4 | Pictures taken at different angles showing the curvatures that were created, inducing the self-shadowing effect. Scale bar, $5\\mathrm{mm}$ . At $90^{\\circ}$ , the bump is formed (indicated by the arrow), but because no shadow is created the wave cannot propagate and the film remains in that position. \n\n![](images/784ac253ab376c3c71140c709634dacfce967b16feeb32211e78c63a308d2254.jpg) \nExtended Data Figure 5 | Temperature measured at the front of the wave. a, Influence of the intensity on the temperature increase at the front of the wave. The red shaded region is a guide to help to visualize the glass transition region. b, Measured temperature for the uniaxially oriented sample. Despite the rubbery character of the films, no motion was observed. \n\nExtended Data Figure 6 | Temperature measurements during wave propagation. a, c, Thermal pictures of the wave taken at different times t. b, Temperature profile over the length of the film (along the black line in a) for the homeotropic-up sample during wave propagation at $t=0$ s \n\n![](images/fea0051ca33ce87b57079d0a9e0381821a733eabe1b0929eddd09de974b6feab.jpg) \n(black line), $t=0.67s$ (dark grey line) and $t=1.40s$ (light grey line). d, Temperature profiles over the length of the film (along the black line in c) for the planar-up sample at $t=0$ s (black line), $t=0.11\\:s$ (dark grey line) and $t=0.22s$ (light grey line). \n\n![](images/5f0a7d7a4124ccd228a5edf4cc921dc59bc74c9ce0288866ef60ee7036fef98c.jpg) \nExtended Data Figure 7 ${\\bf{\\tau}}^{\\mathbf{{1}}}{\\bf{H}}{\\bf{N M R}}$ spectra of the constituent compounds. a, $\\mathrm{{}^{1}H N M R}$ of the compound AzoPy, which was used to form compound b, $^1\\mathrm{H}$ NMR of compound II. \n\n![](images/30e0339acae83a9eb90196daa1c7d8783bc4efcc0dba71e6e9dbb5180977333a.jpg) \nExtended Data Figure 8 | Transmission spectra of the LCN films. Transmissions (T, expressed as percentages) for compound I (green), compound II (black), A6MA (red), AzoPy (pink) and DR1A (blue) are shown. Thickness, $20\\upmu\\mathrm{m}$ . The films containing A6MA, compound I and AzoPy are actuated with $405\\mathrm{-nm}$ light. At this wavelength, the transmissions are $6.3\\%$ , $4.1\\%$ and $8.9\\%$ , respectively. The samples containing DR1A and compound II are illuminated with 455-nm light. At this wavelength, the initial transmissions are $26\\%$ and $13\\%$ , respectively. \n\nExtended Data Table 1 | Chemical compositions of the mixtures \n\n\n
AzoPyMixture with Mixture with Mixture with Mixture with Mixture withA6MADR1A
AzoPy7 m!/
Compound17 ml%/
CompoundIl7 mol % /
A6MA///7 m0l % /
DR1A//1 ml %
RM8257 mmlg%50 mmg%50 mmlg%51 mmg%57 mmlg%
RM2335 mmg%42 mmlg%41 mmlg%41 mmlg%41 mml %
Irgacure8191 mmg%1 mmlg%1 mmg%1 mml%1 mmlg%
\n\nThe mixture containing DR1A has a slightly different composition (lower molar percentage of dye) because the extinction coefficient of DR1A is higher than the other molecules. Consequently, the amounts of RM23 and RM82 are also adjusted to maintain a similar quantity of cross-linker. Both the molar ratio $(\\mathfrak{m o l}\\%)$ and the corresponding amount $(\\mathsf{m g})$ are reported. " + }, + { + "id": "10.1038_ncomms14101", + "DOI": "10.1038/ncomms14101", + "DOI Link": "http://dx.doi.org/10.1038/ncomms14101", + "Relative Dir Path": "mds/10.1038_ncomms14101", + "Article Title": "Intragranular cracking as a critical barrier for high-voltage usage of layer-structured cathode for lithium-ion batteries", + "Authors": "Yan, PF; Zheng, JM; Gu, M; Xiao, J; Zhang, JG; Wang, CM", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "LiNi1/3Mn1/3Co1/3O2-layered cathode is often fabricated in the form of secondary particles, consisting of densely packed primary particles. This offers advantages for high energy density and alleviation of cathode side reactions/corrosions, but introduces drawbacks such as intergranular cracking. Here, we report unexpected observations on the nucleation and growth of intragranular cracks in a commercial LiNi1/3Mn1/3Co1/3O2 cathode by using advanced scanning transmission electron microscopy. We find the formation of the intragranular cracks is directly associated with high-voltage cycling, an electrochemically driven and diffusion-controlled process. The intragranular cracks are noticed to be characteristically initiated from the grain interior, a consequence of a dislocation-based crack incubation mechanism. This observation is in sharp contrast with general theoretical models, predicting the initiation of intragranular cracks from grain boundaries or particle surfaces. Our study emphasizes that maintaining structural stability is the key step towards high-voltage operation of layered-cathode materials.", + "Times Cited, WoS Core": 804, + "Times Cited, All Databases": 864, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000392095500001", + "Markdown": "# Intragranular cracking as a critical barrier for high-voltage usage of layer-structured cathode for lithium-ion batteries \n\nPengfei $\\mathsf{Y a n}^{1,\\star}$ , Jianming Zheng2,\\*, Meng $\\mathsf{G u}^{1}$ , Jie Xiao2, Ji-Guang Zhang2 & Chong-Min Wang1 $\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ -layered cathode is often fabricated in the form of secondary particles, consisting of densely packed primary particles. This offers advantages for high energy density and alleviation of cathode side reactions/corrosions, but introduces drawbacks such as intergranular cracking. Here, we report unexpected observations on the nucleation and growth of intragranular cracks in a commercial $\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ cathode by using advanced scanning transmission electron microscopy. We find the formation of the intragranular cracks is directly associated with high-voltage cycling, an electrochemically driven and diffusion-controlled process. The intragranular cracks are noticed to be characteristically initiated from the grain interior, a consequence of a dislocation-based crack incubation mechanism. This observation is in sharp contrast with general theoretical models, predicting the initiation of intragranular cracks from grain boundaries or particle surfaces. Our study emphasizes that maintaining structural stability is the key step towards high-voltage operation of layered-cathode materials. \n\nExmpelcohriangi lmitshihuams -lion1 1b6eatetneray aLcItBiv) erlescetarrocdhe odepigcrafdoar itohne degradation allows us to design better electrode materials. In the case of layered transition metal (TM) oxide cathode degradation, three mechanisms have been identified2–5,12,17,18: (1) Layer to spinel/rock salt phase transformation, which is characteristically initiated from the individual particle surface and gradually propagated inwards with battery cycling. (2) Side reactions between the cathode and electrolyte, leading to electrolyte decomposition and passivation of the solid electrode. (3) Corrosion and dissolution of the cathode materials in the electrolyte. These findings lead to the application of coating techniques and other surface treatments to stabilize vulnerable surfaces on the cathode materials. Such coating and surface treatments have been frequently verified as effective methods for improving cathode cycling stability19–28. Besides chemical instability, another degradation mechanism is associated with the volume change of the material upon lithium (Li) ion extraction and reinsertion. Non-uniform accommodation of such a volume change will generate stress, which can lead to mechanical failure29. In fact, intergranular crack formation is one of the most well-known material degradation mechanisms29–35. \n\nDuring the charge process of layered TM oxides, Li ions are extracted from the lattice, which usually causes lattice expansion along the $\\mathbf{\\Psi}_{c}$ direction and shrinkage along the $^a$ and $b$ directions29,36–38, which is reversed upon discharging. This type of lattice expansion and shrinkage is generally termed as lattice breathing, which has been theoretically and experimentally verified. For example, when $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ (NMC333) is delithiated to $\\mathrm{Li}_{0.5}\\mathrm{Ni}_{1/3}\\mathrm{Mn}_{1/3}\\mathrm{Co}_{1/3}\\mathrm{O}_{2}.$ , Yoon et al.37 found that the lattice could expand $2.0\\%$ along the $\\mathbf{\\Psi}_{c}$ direction and shrink $1.4\\%$ along the $^a$ direction, inducing significant strain for oxides with ionic bonds. \n\n![](images/2774bf4e5192074bbe16dd5dee1cda648e0706d8a46770d19c401e16379b6077.jpg) \nFigure 1 | Electrochemical performance and observations of fracture. (a) Specific capacity as a function of cycle number, revealing the $\\mathsf{L i}/\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/}$ ${\\phantom{}_{3}}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ half cell’s capacity fading has strong dependence on the high cutoff voltages, (b–d) charge/discharge profiles of $\\mathsf{L i}/\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ half cells at different high cutoff voltages, and (e–g) low magnification HAADF images of $\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ after 100 cycles at different high cutoff voltages. The red arrows indicate voids and the yellow arrows in $\\pmb{\\mathscr{g}}$ indicate intragranular cracks. Scale bars, $500\\mathsf{n m}$ $(\\pmb{\\theta}\\mathbf{-}\\pmb{\\theta})$ . \n\nTo increase the volumetric energy density of the electrode, the packing density of the active electrode component should be increased. One way to accomplish this in commercial LIB cathodes is to use primary particles to form densely packed secondary particles. However, such secondary particles always generate intergranular cracks during battery charge/discharge cycling, due to the anisotropic expansion and shrinkage of each primary particle31,32,39. Such strain-induced cracking has been considered to be one of the major degradation mechanisms for the cathode for the following reasons: (1) Cracks can result in poor grain-to-grain connections, leading to poor electrical conductivity and even loss of active materials due to fragmentation; (2) Cracks create fresh surfaces that will be exposed to electrolytes and generate new sites for surface phase transformation, corrosion and side reactions, consequently accelerating cell degradation. \n\nBesides intergranular cracks, intragranular cracks were also observed in several cathode materials after prolonged cycling39–41. For example, Chen et $a l.^{40}$ found cracks in the bc planes of $\\mathrm{LiFePO_{4}}.$ , Wang et al.41 noted cracks in $\\mathrm{LiCoO}_{2}$ particles, and Kim et al.39 observed cracks in $\\mathrm{LiNi_{0.6}M n_{0.2}C o_{0.2}O_{2}}$ after 150 cycles at $60^{\\circ}\\mathrm{C}.$ . Compared with intergranular cracks, intragranular cracks are smaller in size but much higher in density, and thus, they can generate many more fresh surfaces that will be exposed to electrolytes. Moreover, intragranular cracking is not only a mechanical failure but also more likely to be a structural degradation under severe electrochemical conditions. Therefore, the previously proposed effective design concepts (such as surface coating) for preventing intergranular cracking31,39,42,43 may not solve the intragranular cracking problem. Mitigation of intragranular cracking requires a stable structural framework of the cathode material and careful controls of cycle conditions. A systematic investigation on intragranular cracking in cathode materials is still lacking. \n\nIn this work, we report detailed observations on the cracking phenomenon in NMC333 layered-cathode materials by using advanced scanning transmission electron microscopy (STEM). In particular, the intragranular cracking process is comprehensively investigated. We find that the density of intragranular cracks in NMC333 cathodes abruptly increases when cycled at a high cutoff voltage of $4.7\\mathrm{V}$ . In contrast expectations, we also observe the intragranular cracks to actually initiate from the grain interior, which is in sharp contrast with general theoretical models predicting the surface or grain boundary to be the preferred sites for intragranular crack initiation $^{42,44-46}$ . We also verify that the edge dislocation core can assist the incubation of intragranular cracks, and that intragranular cracking is an electrochemically driven and diffusion-controlled process, mimicking the classic model of slow crack growth during fatigue process of materials. \n\n# Results \n\nHigh cutoff voltage cycling induced intragranular cracking. The performance of NMC333 cathode electrodes in Li/NMC333 half-cells cycled at different voltage ranges, that is, $2.7\\sim4.2\\:\\mathrm{V}$ , $2.7\\sim4.5\\:\\mathrm{V}$ , and $2.7\\sim4.7\\mathrm{V}$ , are shown in Fig. 1a, and the corresponding charge/discharge voltage profile evolutions are shown in Fig. 1b–d, respectively. Electrochemical data indicate that the cycling stability of the NMC333 cathode shows strong dependence on the charge cutoff voltages that are applied for battery cycling. Generally, the higher the charge cutoff voltage, the faster degradation of the battery performance. When the battery was cycled at a low charge cutoff voltage of $4.2\\mathrm{V}$ , the NMC333 shows excellent cycling stability along with very limited voltage decay. However, with the increase of charge cutoff voltage, the NMC333 shows obvious voltage fading and capacity decay. Particularly, serious voltage decay and capacity fading occur when cycling at $4.7\\mathrm{V}$ . \n\nBecause excessive Li metal was used as anode for these three cells, it is believed that their performance difference should be mainly associated with instability of the cathode and electrolyte. It is known that a higher charge voltage can result in aggravated degradation of the cathode and electrolyte due to the side reactions between the cathode and electrolyte, formation of a thicker phase transformation layer on the surface of the cathode, and severe surface corrosion of the cathode18,47. For the densely packed secondary particles, the formation of intergranular cracks also contributes to the degradation of the cell. The general features of these intergranular cracks are representatively identified in the cross-sectional scanning electron microscopy (SEM) images in Fig. $\\operatorname{le-g},$ Fig. 2a,b and Supplementary Fig. 1. Comparing the pristine and cycled samples, it is obvious that after 100 cycles, the samples cycled at different high cutoff voltages of 4.2, 4.5, and $4.7\\mathrm{V}$ exhibit no significant differences in terms of the intergranular cracking features. \n\nIntragranular cracks are one of the significant differences for the samples cycled at different charge cutoff voltages. In the sample cycled at $4.7\\mathrm{V}$ , the number of intragranular cracks were significantly higher than the samples cycled at 4.2 and $4.5\\mathrm{V}$ , as shown representatively in Fig. 1e–g. Intragranular cracks are hardly seen in the samples cycled at 4.2 and $4.5\\mathrm{V}$ , but are universally observed in the sample cycled at $4.7\\mathrm{V}$ . In the sample cycled at $4.7\\mathrm{V}$ , it would be expected that the intragranular cracking characteristics would substantially contribute to the faster capacity degradation as compared with those cycled at 4.2 and $4.5\\mathrm{V}$ . The abrupt increase of the density of intragranular cracks also indicates the high cutoff cycle voltage is the direct driving force for intragranular crack generation, suggesting a critical cycle voltage between 4.5 and $\\mathrm{\\bar{4.7V}}$ for initializing the intragranular cracks in NMC333. \n\n![](images/aea9d7a0de532cc42adc8d4203904cc73e2a5a85efc12de8c779de99f5872c77.jpg) \nFigure 2 | Intergranular and intragranular cracks. Cross-sectional SEM images of secondary particles from (a) the pristine material and $(\\pmb{6})$ the cycled one (100 cycles at the high cutoff voltage of $4.7\\vee$ . (c) and (d) are HAADF images from cycled $\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ cathode particles, showing intragranular cracks along (001) plane. The yellow arrows indicate real cracks and the pink arrows indicate incubation cracks. Scale bars, $5\\upmu\\mathrm{m}$ $(\\mathbf{a},\\mathbf{b})$ ; $50\\mathsf{n m}$ (c); and $10\\mathsf{n m}$ (d). \n\n![](images/c261fe572360fd58c46529b4724f5c38e9a0aba4c75c398631ba46dfc04abcfb.jpg) \nFigure 3 | Lattice images of premature cracks. Each pair of HAADF and ABF images are taken simultaneously. (a,b) [010] axis. (c) The corresponding lattice model. (d,e) A crack tip; (f) The corresponding model. (g,h) [1–10] axis. (i) Strain map at Mode I crack tip, which matches the strain contrast in h. Scale bars, $2{\\mathsf{n m}}$ . \n\nStructural features of the intragranular cracks. SEM and STEM observations reveal the details of these intergranular cracks as marked by the yellow arrows in Figs 1g and 2c, d. As the intragranular cracks are mostly observed in the sample cycled at $4.7\\mathrm{V}$ , we focused our effort on the NMC333 sample that was subjected to 100 cycles at $4.7\\mathrm{V}$ in order to reveal the detailed structure of the intragranular cracks and understand their formation mechanism. \n\nTwo types of intragranular cracks can be uniquely identified. One type possesses the classical term of crack, which is featured by two free surfaces as indicated by the yellow arrows in the STEM high-angle annular dark-field (HAADF) images of Fig. 2c, d. The two free surfaces appear to be parallel along the whole crack except at the very tip, which is markedly different from a wedge-shaped crack formed by fast extension of crack under stress. Furthermore, cracks are predominantly parallel to (003) planes in the layer structure. These morphological features of the cracks are associated with their formation process, which will be discussed in detail in the subsequent sections. \n\nThe other type of crack appears as narrow, dark strips when observed under STEM-HAADF imaging as indicated by the pink arrows in Fig. 2c, d. The dark strips are all parallel to the (003) planes (the layers) and distribute randomly with various spacing among the strips. The closest distance between two strips is a single layer of TM. As shown in the inset of Fig. 2c, the (003) plane spacing is $0.48\\mathrm{nm}$ , while the dark contrasted strip corresponds to a widened TM plane spacing, ranging from 0.6 to $0.8\\mathrm{nm}$ . Therefore, these dark contrasted strips appear to be formed by a parallel splitting of two adjacent TM layers, leading to a wider $\\boldsymbol{c}$ plane spacing. \n\nIt should be noted that, not always, but for some cases, the dark contrasted strip is spatially connected to the real crack as representatively shown in Fig. 2d. This observation likely indicates that the dark contrasted strip is a premature crack. The reason we term the dark contrasted strip as a premature crack is because it does not have two free surfaces. With the continued cycling of the battery, the premature crack will further develop into a real crack. \n\nIt is interesting to note that the dark strip contrasted region still possesses internal structural features. As shown in Fig. 3a,b and Supplementary Fig. 2, high-resolution STEM-HAADF and annular bright-field (ABF) images were simultaneously collected from one premature crack. As verified by the ABF image, the dark contrasted strip that appeared in the STEM-HAADF image is actually not empty. As denoted by the pink arrow in Fig. 3b, there are some black dots that appeared with a rock-salt-like structure. Simulated HAADF/ABF images are shown in Supplementary Fig. 3 to support our interpretation. Thus, the dark contrasted strip, in fact, still contains an internal structure with material of low density. Its crystal model is illustrated in Fig. 3c. The very tip of the dark contrasted strip shows bending of the TM atomic row, forming a ‘V’ shape that looks just as the configuration of a crack tip. Fig. 3d, e are imaged from [010] axis and Fig. 3g, h are from [1–10] axis. The crystal model of the dark contrasted strip is illustrated in Fig. 3f. The ABF image shown in Fig. 3h even shows a strain contour at the tip, which is very similar to the strain contour of a real crack generated by tensile stress (Mode I crack, Fig. 3i). These structural features clearly demonstrate that the dark contrasted strips are premature cracks, which were formed by splitting the two neighbouring TM slabs and propagated along (003) planes. \n\nAnother significant feature of the intragranular cracking is that a large fraction of the intragranular cracks terminate within the grain interior, as representatively shown in Fig. 4, for which the red arrows highlight the intragranular end-to-end cracks that were fully terminated within the grain interior. These observations indicate that the intragranular cracks are initiated from the grain interior, which is in contrast with cracking models that predict the surface or grain boundary should be the preferred crack initiation site $^{42,44-46}$ . However, based on thermal analogy analysis, Kalnaus et al.48 predicted cracking may initiate from the centre of the particle. Operando X-ray diffraction measurement has indicated the inhomogeneous lithiation/delithiation within a single cathode crystal49. Therefore, the variation of the $\\mathbf{\\Psi}_{c}$ plane spacing at different delithiation states within a single grain can lead to a complex strain pattern within the grain interior. Figure 4e gives a general illustration on the intragranular crack formation process under tensile stress. Inhomogenous Li distribution is believed to be the direct cause of such tensile stress. This internal cracking model also matches our proposed Mode I crack mechanism based on the observations on the crack tips in Fig. 3. \n\nGeneration of dislocations in the primary particles. Within the densely packed secondary particles, dislocation activity in the primary particle is another unique feature. High density of dislocations in both pristine and cycled samples were observed based on STEM-BF imaging, as representatively shown in Fig. $^{5\\mathrm{a},\\mathrm{b},}$ for which the blue arrows highlight the dislocations. The dislocation density is in the range of $\\mathrm{\\check{10}}^{11}\\mathrm{\\check{c}m}^{-2}$ . The observation of high-density dislocation in the primary particles is in marked contrast to the case of using nano-sized particles to assemble the battery electrode, where dislocation activity is hardly visible within the layer-structured particles. The high-density dislocations in the primary particle, as indicated in Fig. $^{5\\mathrm{a},\\mathrm{b}}$ , is the consequence of the formation of secondary particles by packing the smaller primary particles. Within the densely packed secondary particles, the primary particles are randomly oriented and in direct contact with their adjacent primary particles. Therefore, thermally (material synthesis process) and electrochemically (battery cycling) induced strain between neighbouring primary particles cannot be concordantly accommodated, which can inherently initiate dislocation in the primary particles. Figure 5c is a high-resolution STEM-HAADF image showing an end-on edge dislocation with Burger’s vector $\\stackrel{\\rightharpoonup}{b}=1\\big/3[1\\bar{1}01]\\approx0.5\\mathrm{nm}$ , which is a whole dislocation as shown in Fig. 5e. At the dislocation core area, due to the lattice mismatch and distortion, strain can build up accordingly. Our geometric phase analysis $\\left(\\mathrm{GPA}\\right)^{50}$ on Fig. 5c is shown in Fig. 5d. It can be seen in this out-of-plane strain map $(\\varepsilon_{y y})$ that the left side with the extra plane is under compressive lattice strain, while the right side is under tensile strain. \n\n![](images/d1d4b08f02eb9fe41263db6fc1d810593e471fcd42245c4a759bca44c9fc72a0.jpg) \nFigure 4 | Intragranular cracks in $\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ (NMC333). The NMC333 particles are cycled 100 times with the high cutoff voltage of $4.7\\mathrm{V}.$ In a–d, the arrows highlight the crack tips that are terminated in grain interior, and (e) a schematic diagram showing crack formation in the grain interior due to tensile stress. Scale bars, $100\\mathsf{n m}$ (a,b); $200\\mathsf{n m}(\\pmb{\\mathsf{c}});$ and $50\\mathsf{n m}$ (d). \n\nThe effects of dislocation on the battery properties can be evaluated from the following two aspects: firstly, the role of the dislocation itself on the ionic transport characteristics; and secondly, the evolution of dislocations and their effect on the structural stability of the material. In terms of dislocation itself, it is known that the dislocation core can act as a fast channel for ionic transport49. At the same time, the strain field associated with the dislocation can affect the active ion distribution and transport characteristics in the lattice. As shown in the GPA $\\varepsilon_{y y}$ strain map in Fig. 5d, the lattice strain field introduced by the edge dislocation goes well beyond the dislocation core (indicated by the yellow arrow in Fig. 5c); in fact, previous Bragg coherent diffraction imaging49 shows the strain field of an edge dislocation can reach more than $100\\mathrm{nm}$ . Therefore, the high-density dislocations in the primary particles will definitely affect, either detrimentally or beneficially, the properties of cathode materials41,49,51. To our best knowledge, this is the first report on discovering the high-density dislocations in layered cathodes when the primary particles are packed as dense secondary particles. \n\n# Discussion \n\nThere have been many studies on the cracking mechanisms of cathode materials for LIBs32,33,44–46,51,52. However, these research efforts are mostly based on theoretical modelling of the stress-strain evolution. Fundamental understanding on the crack incubation is still far from clear. On the basis of what we have observed, the dark contrast strip (the premature crack) is the predecessor of the intragranular crack. The transition from the dark contrasted strip to the crack is a diffusion-controlled process, which is in essence an electrochemical driving process. Now, the key question is the origin of the dark contrasted strip or the premature cracks. On the basis of intensive observation using high-resolution STEM-HAADF imaging, we found that there exists a close correlation between edge dislocations and premature crack, as typically shown in Fig. 6. Fig. 6a and b show the nucleation of a premature crack at the dislocation core as indicated by the red arrows. Fig. 6d–f shows the association of an edge dislocation with premature cracks. These observations indicate that edge dislocation core can act as the nucleation site for crack incubation. From an energy point of view, Li and O ions will be preferentially removed from the tensile part of the dislocation core region to release strain. Kinetically, the dislocation core is a fast diffusion pathway. Therefore, the nucleation of the premature crack from the dislocation core is an electrochemically driven, but diffusion limited, process as schematically shown in Fig. 6c, which is similar to the fatigueinduced cracks in the slip band53. Our proposed mechanism is also supported by previous theoretical calculation work done by Huang et al.51 who proposed dislocation-based cracking models. \n\n![](images/e447e48dede564bb0489c3b9b45657be8e29ffa40c21f52e5654e3fcbe4c8002.jpg) \nFigure 5 | Dislocations in both pristine and cycled $\\mathsf{L i N i}_{1/3}\\mathsf{M n}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{O}_{2}$ (NMC333). High density of dislocations are shown in the bright-field images of (a) pristine and (b) cycled NMC333 (after 100 cycles at the high cutoff voltage of 4.7 V). (c) A HAADF image showing an end-on edge dislocation in pristine NMC333, (d) is the corresponding strain map by GPA and (e) shows the dislocation model of (c). Scale bars, $200\\mathsf{n m}$ (a,b); 5 nm (c,d). \n\nWe have drawn the conclusion that high-voltage cycling is the direct driving force for intragranular crack generation as evidenced by the drastic increase of intragranular crack density in the $4.7\\mathrm{V}$ sample (Fig. 1g). Higher cycle voltage will result in deeper Li-ion extraction, which, on one hand, can aggravate structure instability, and on the other hand, can amplify the internal strain within a grain. Therefore, when the cycle voltage exceeds a critical value, in this case, some point between 4.5 and \n\n$4.7\\mathrm{V}_{:}$ intragranular cracks can be massively initiated as shown in Fig. 7a. As dislocation can act as a nucleation site for incubation of intragranular crack, we schematically illustrate in Fig. 7b the overall formation process of intragranular cracking based on a dislocation-nucleation mechanism. One of the fundamental questions is how the battery cycling rate contributes to the generation of intragranular cracks. To test the rate effect, the battery was cycled at 1C (as compared with 0.1C) at a cutoff voltage of 4.2 and $4.5\\mathrm{V}$ . No premature cracks were identified at these samples. The results clearly point out the effect of cycle voltage on the intragranular crack formation. \n\nThe present observation has relevant implications for electrode design and battery operation. Although many surface coating methods have been used to minimize the surface-initiated structure degradation and cation dissolution in layer-structured cathode materials, these methods cannot be used to prevent the intrinsic, intragranular cracks that were initiated inside the primary particles and aggravated by the high-voltage charge process. During the Li-ion extraction and insertion processes, the lattice of crystal will be subject to change (either expansion or contraction). Although these changes are reversible within the certain limit, too large a lattice change, such as those induced by a high-voltage charge process, will lead to the irreversible formation of the dislocations and cracks, which will in turn be detrimental for the performance of the battery, as what has been observed in the present case. Therefore, on one hand, for the currently available NMC materials, the charge voltage has to be well controlled to minimize the electrochemically induced intragranular cracks. On the other hand, in order to push the NMC-layerbased materials for high-voltage applications, efforts have to be made to adjust the chemistry and structure of the material such that it can alleviate the internal grain strain, cause minimal Li distribution inhomogeneity, and retain a stable lattice during charge and discharge cycling. \n\n![](images/8f32e32a9e46ec6c306a95fab02a5dbc9891a9daeed7da25c102065d398c87ab.jpg) \nFigure 6 | Dislocation associated with cracks in cycled $\\mathbf{LiNi_{1/3}M n_{1/3}C o_{1/}}$ $30_{2}.$ (a,b) are the early incubation stages, showing vacancy condensation at dislocation core and (c) is the corresponding model. (d–f) show dislocations associated with cracks. Red arrows indicate crack tips. Scale bars, $2{\\mathsf{n m}}$ ; except f $(5\\mathsf{n m})$ . \n\n# Methods \n\nCathode material and cell test. NMC333 pristine electrode laminates were provided by the Cell Analysis, Modelling, and Prototyping Facility at Argonne National Laboratory (pristine powders are commercially available and are manufactured by TODA KOGYO Company, Japan). The electrode laminates were punched into electrode disks that were $\\%$ inches in diameter and dried at $75^{\\circ}\\mathrm{C}$ overnight under a vacuum. Coin cells were assembled with the dried cathode electrode, metallic lithium foil as an anode electrode, Celgard2500 polyethylene (PE) membrane as separator, and 1 M lithium hexafluorophosphate $\\left(\\mathrm{LiPF}_{6}\\right)$ 1 dissolved in ethylene carbonate and dimethyl carbonate (1:2 in volume) as an electrolyte in an argon-filled MBraun glovebox. All the cathode electrodes were cycled at $\\mathrm{C}/10$ rate $\\mathsf{\\check{(}1C=180\\ m A\\ g^{-1}},$ ) in the voltage range of 2.7–4.2 V, 2.7–4.5 V, $2.7{-}4.7\\:\\mathrm{V}$ and $2.7–4.8\\mathrm{V}$ . \n\nMicrostructure characterization and simulation. FIB/SEM imaging and TEM specimen preparation by FIB lift out were conducted on a FEI Helios DualBeam Focused Ion Beam operating at $2{-}30\\mathrm{kV}$ . Firstly, $1.2\\upmu\\mathrm{m}$ thick Pt layer $(200\\mathrm{nm}$ e-beam deposition followed by $1\\upmu\\mathrm{m}$ ion beam deposition) was deposited on the particles to be lifted out to avoid Ga ion beam damage. After lift out, the specimen was thinned to $200\\mathrm{nm}$ using $30\\mathrm{kV}$ Ga ion beam. A final polishing was performed using $2\\mathrm{kV}$ Ga ion to remove the surface damage layer and further thinning to electron transparency. After a $2\\mathrm{kV}$ Ga ion polish, the surface damage layer was believed to be $<1\\mathrm{nm}$ (ref. 54). The FIB-prepared NMC333 samples were investigated by using a JEOL JEM-ARM200CF microscope at $200\\mathrm{kV}$ . This microscope is equipped with a probe spherical aberration corrector, enabling sub-angstrom imaging using STEM-HAADF/ABF detectors. For STEM-HAADF imaging, the inner and outer collection angles of an annular dark-field detector were set at 68 and 280 mrad, respectively. For STEM-ABF imaging, the inner and outer collection angles are 10 and 23 mrad, respectively. [010] and [1–10] zone axis STEM-HAADF/ABF images are simulated by using the $\\mathrm{\\dot{Q}S T E M}^{55}$ , which is a suite of software for quantitative image simulation of electron microscopy images, including model building and TEM/STEM/CBED image simulation. The collection angles for HAADF and ABF are 68–280 mrads and 10–20 mrads, respectively. A probe size of $0.8\\mathring\\mathrm{A}$ is used with 27.5 mrad as convergence angle at $200\\mathrm{kV}$ . \n\n![](images/88cb67fbdf439eb476c0916163c7a5a7f90622cfe5b4443bf3c9ad5f5d846240.jpg) \nFigure 7 | Cycle voltage governed intragranular cracking and underlying dislocation-based mechanism. (a) HAADF images overlaid diagram shows the apparent dependence of intragranular cracking on the cycle voltage; when cycled below $4.5\\mathsf{V},$ intragranular crack can be hardly generated, while above $4.7\\mathsf V,$ intragranular density shows a drastic increase; and (b) schematic diagrams to illustrate the dislocation-assisted crack incubation, propagation and multiplication process. \n\nDifferent sample thicknesses (5, 10, 20, 30, 40 and $50\\mathrm{nm}$ ) with different focus values $(-5,~-4,~-3,~-2,~-1,0,1,2,3,4,5\\mathrm{nm})$ are simulated. \n\nData availability. All relevant data are kept in storage at the Environmental Molecular Sciences Laboratory at Pacific Northwest National Laboratory and are available from the corresponding authors on request. \n\n# References \n\n1. Sathiya, M. et al. Origin of voltage decay in high-capacity layered oxide electrodes. Nat. Mater. 14, 230–238 (2015). \n2. Lin, F. et al. Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries. Nat. Commun. 5, 3529 (2014). \n3. Xu, B., Fell, C. R., Chi, M. F. & Meng, Y. S. Identifying surface structural changes in layered Li-excess nickel manganese oxides in high voltage lithium ion batteries: a joint experimental and theoretical study. Energy Environ. Sci. 4, 2223–2233 (2011). \n4. Yan, P. et al. Evolution of lattice structure and chemical composition of the surface reconstruction layer in $\\mathrm{Li}_{1.2}\\mathrm{Ni}_{0.2}\\mathrm{Mn}_{0.6}\\mathrm{O}_{2}$ cathode material for lithium ion batteries. Nano Lett. 15, 514–522 (2015). \n5. Zheng, J. et al. Corrosion/fragmentation of layered composite cathode and related capacity/voltage fading during cycling process. Nano Lett. 13, 3824–3830 (2013). \n6. Gu, M. et al. Formation of the spinel phase in the layered composite cathode used in li-ion batteries. ACS nano 7, 760–767 (2013). \n7. Rana, J. et al. Structural changes in $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ cathode material for li-ion batteries. Adv. Energy Mater. 4, 1300998 (2014). \n8. Gu, L., Xiao, D., Hu, Y. S., Li, H. & Ikuhara, Y. Atomic-scale structure evolution in a quasi-equilibrated electrochemical process of electrode materials for rechargeable batteries. Adv. Mater. 27, 2134–2149 (2015). \n9. Yan, P. et al. Probing the degradation mechanism of $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ cathode for li-ion batteries. Chem. Mater. 27, 975–982 (2015). \n10. Kobayashi, H. et al. Changes in the structure and physical properties of the solid solution $\\mathrm{LiNi}_{1-x}\\mathrm{Mn}_{x}\\mathrm{O}_{2}$ with variation in its composition. J. Mater. Chem. 13, 590–595 (2003). \n11. Muto, S. et al. Capacity-fading mechanisms of $\\mathrm{LiNiO}_{2}$ -based lithium-ion batteries II. Diagnostic analysis by electron microscopy and spectroscopy. J. Electrochem. Soc. 156, A371–A377 (2009). \n12. Hong, J. et al. Structural evolution of layered $\\mathrm{Li}_{1.2}\\mathrm{Ni}_{0.2}\\mathrm{Mn}_{0.6}\\mathrm{O}_{2}$ upon electrochemical cycling in a Li rechargeable battery. J. Mater. Chem. 20, 10179–10186 (2010). \n13. McCalla, E. et al. Visualization of O-O peroxo-like dimers in high-capacity layered oxides for Li-ion batteries. Science 350, 1516–1521 (2015). \n14. Shukla, A. K. et al. Unravelling structural ambiguities in lithium- and manganese-rich transition metal oxides. Nat. Commun. 6, 8711 (2015). \n15. Wu, Y. et al. Probing the initiation of voltage decay in Li-rich layered cathode materials at the atomic scale. J. Mater. Chem. A 3, 5385–5391 (2015). \n16. He, K. et al. Visualizing non-equilibrium lithiation of spinel oxide via in situ transmission electron microscopy. Nat. Commun. 7, 11441 (2016). \n17. Boulineau, A., Simonin, L., Colin, J. F., Bourbon, C. & Patoux, S. First evidence of manganese-nickel segregation and densification upon cycling in Li-rich layered oxides for lithium batteries. Nano Lett. 13, 3857–3863 (2013). \n18. Yang, P. et al. Phosphorus enrichment as a new composition in the solid electrolyte interphase of high-voltage cathodes and its effects on battery cycling. Chem. Mater. 27, 7447–7451 (2015). \n19. Zheng, J. M. et al. The effects of ${\\mathrm{AlF}}_{3}$ coating on the performance of $\\mathrm{Li}[\\mathrm{Li}_{0.2}\\mathrm{Mn}_{0.54}\\mathrm{Ni}_{0.13}\\mathrm{Co}_{0.13}]\\mathrm{O}_{2}$ positive electrode material for lithium-ion battery. J. Electrochem. Soc. 155, A775–A782 (2008). \n20. Zheng, J. et al. Functioning mechanism of AlF3 coating on the Li- and Mn-rich cathode materials. Chem. Mater. 26, 6320–6327 (2014). \n21. Seok Jung, Y., Cavanagh, A. S., Yan, Y., George, S. M. & Manthiram, A. Effects of atomic layer deposition of ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ on the $\\mathrm{Li}[\\mathrm{Li}_{0.20}\\mathrm{Mn}_{0.54}\\mathrm{Ni}_{0.13}\\mathrm{Co}_{0.13}]\\mathrm{O}_{2}$ cathode for lithium-ion batteries. J. Electrochem. Soc. 158, A1298–A1302 (2011). \n22. Knoops, H. C. M., Donders, M. E., van de Sanden, M. C. M., Notten, P. H. L. & Kessels, W. M. M. Atomic layer deposition for nanostructured Li-ion batteries. J. Vac. Sci. Technol. A 30, 010801 (2012). \n23. Sun, Y.-K. et al. The role of ${\\mathrm{AlF}}_{3}$ coatings in improving electrochemical cycling of Li-enriched nickel-manganese oxide electrodes for Li-ion batteries. Adv. Mater. 24, 1192–1196 (2012). \n24. Liao, H. G. et al. Facet development during platinum nanocube growth. Science 345, 916–919 (2014). \n25. Wise, A. M. et al. Effect of $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ coating on stabilizing $\\mathrm{LiNi_{0.4}M n_{0.4}C o_{0.2}O_{2}}$ cathodes. Chem. Mater. 27, 6146–6154 (2015). \n26. Min, S. H., Jo, M. R., Choi, S.-Y., Kim, Y.-I. & Kang, Y.-M. A layer-structured electrode material reformed by a $\\mathrm{PO}_{4}–\\mathrm{O}_{2}$ hybrid framework toward enhanced lithium storage and stability. Adv. Energy Mater 6, 1501717 (2016). hod materials with superior high-voltage cycling behavior for lithium ion battery application. Energ Environ. Sci. 7, 768–778 (2014). \n28. Lin, F. et al. Metal segregation in hierarchically structured cathode materials for high-energy lithium batteries. Nat. Energy 1, 15004 (2016). \n29. Mukhopadhyay, A. & Sheldon, B. W. Deformation and stress in electrode materials for Li-ion batteries. Prog. Mater. Sci. 63, 58–116 (2014). 30. Kiziltas¸-Yavuz, N. et al. Synthesis, structural, magnetic and electrochemical properties of $\\mathrm{LiNi_{1/3}M n_{1/3}C o_{1/3}O_{2}}$ prepared by a sol-gel method using table sugar as chelating agent. Electrochim. Acta 113, 313–321 (2013). \n31. Lee, E. J. et al. Development of microstrain in aged lithium transition metal oxides. Nano Lett. 14, 4873–4880 (2014). \n32. Miller, D. J., Proff, C., Wen, J. G., Abraham, D. P. & Bareno, J. Observation of microstructural evolution in Li battery cathode oxide particles by in situ electron microscopy. Adv. Energy Mater. 3, 1098–1103 (2013). 33. Robertz, R. & Novak, P. Structural changes and microstrain generated on $\\mathrm{LiNi}_{0.80}\\mathrm{Co}_{0.15}\\mathrm{Al}_{0.05}\\mathrm{O}_{2}$ during cycling: effects on the electrochemical performance. J. Electrochem. Soc. 162, A1823–A1828 (2015). \n34. Nadimpalli, S. P. V., Sethuraman, V. A., Abraham, D. P., Bower, A. F. & Guduru, P. R. Stress Evolution in lithium-ion composite electrodes during electrochemical cycling and resulting internal pressures on the cell casing. J. Electrochem. Soc. 162, A2656–A2663 (2015). \n35. Choi, J. & Manthiram, A. Comparison of the electrochemical behaviors of stoichiometric $\\mathrm{LiNi_{1/3}C o_{1/3}M n_{1/3}O_{2}}$ and lithium excess $\\operatorname{Li}_{1.03}$ $\\mathrm{(Ni_{1/3}C o_{1/3}M n_{1/3})_{0.97}O_{2}}$ . Electrochem. Solid-State Lett. 7, A365–A368 (2004). \n36. Zhou, Y. N. et al. Tuning charge-discharge induced unit cell breathing in layerstructured cathode materials for lithium-ion batteries. Nat. Commun. 5, 5381 (2014). \n37. Yoon, W. S., Chung, K. Y., McBreen, J. & Yang, X. Q. A comparative study on structural changes of $\\mathrm{LiCo_{1/3}N i_{1/3}M n_{1/3}O_{2}}$ and $\\mathrm{LiNi_{0.8}C o_{0.15}A l_{0.05}O_{2}}$ during first charge using in situ XRD. Electrochem. Commun. 8, 1257–1262 (2006). \n38. Dolotko, O., Senyshyn, A., Mu¨hlbauer, M. J., Nikolowski, K. & Ehrenberg, H. Understanding structural changes in NMC Li-ion cells by in situ neutron diffraction. J. Power Sources 255, 197–203 (2014). 39. Kim, H., Kim, M. G., Jeong, H. Y., Nam, H. & Cho, J. A new coating method for alleviating surface degradation of $\\mathrm{LiNi_{0.6}C o_{0.2}M n_{0.2}O_{2}}$ cathode material: nanoscale surface treatment of primary particles. Nano Lett. 15, 2111–2119 (2015). \n40. Chen, G., Song, X. & Richardson, T. J. Electron microscopy study of the $\\mathrm{LiFePO_{4}}$ to $\\mathrm{FePO_{4}}$ phase transition. Electrochem. Solid-State Lett. 9, A295–A298 (2006). \n41. Wang, H., Jang, Y. I., Huang, B., Sadoway, D. R. & Chiang, Y. M. TEM study of electrochemical cycling-induced damage and disorder in $\\mathrm{LiCoO}_{2}$ cathodes for rechargeable lithium batteries. J. Electrochem. Soc. 146, 473–480 (1999). 42. Hu, Y., Zhao, X. & Suo, Z. Averting cracks caused by insertion reaction in lithium–ion batteries. J. Mater. Res. 25, 1007–1010 (2010). \n43. Tan, G., Wu, F., Li, L., Chen, R. & Chen, S. Coralline glassy lithium phosphatecoated $\\mathrm{LiFePO_{4}}$ cathodes with improved power capability for lithium ion batteries. J. Phys. Chem. C 117, 6013–6021 (2013). \n44. Woodford, W. H., Chiang, Y.-M. & Carter, W. C. ‘Electrochemical shock’ of intercalation electrodes: a fracture mechanics analysis. J. Electrochem. Soc. 157, A1052–A1059 (2010). \n45. Klinsmann, M., Rosato, D., Kamlah, M. & McMeeking, R. M. Modeling crack growth during Li extraction in storage particles using a fracture phase field approach. J. Electrochem. Soc. 163, A102–A118 (2016). 46. Park, J., Lu, W. & Sastry, A. M. Numerical simulation of stress evolution in lithium manganese dioxide particles due to coupled phase transition and intercalation. J. Electrochem. Soc. 158, A201–A206 (2011). \n47. Manthiram, A., Knight, J. C., Myung, S. T., Oh, S. M. & Sun, Y. K. Nickel-rich and lithium-rich layered oxide cathodes: progress and perspectives. Adv. Energy Mater. 6, 1501010 (2016). \n48. Kalnaus, S., Rhodes, K. & Daniel, C. A study of lithium ion intercalation induced fracture of silicon particles used as anode material in Li-ion battery. J. Power Sources 196, 8116–8124 (2011). \n49. Ulvestad, A. et al. Topological defect dynamics in operando battery nanoparticles. Science 348, 1344–1347 (2015). \n50. Zhu, Y., Ophus, C., Ciston, J. & Wang, H. Interface lattice displacement measurement to 1 pm by geometric phase analysis on aberration-corrected HAADF STEM images. Acta Mater. 61, 5646–5663 (2013). \n51. Shadow Huang, H.-Y. & Wang, Y.-X. Dislocation based stress developments in lithium-ion batteries. J. Electrochem. Soc. 159, A815–A821 (2012). \n52. Gabrisch, H., Wilcox, J. & Doeff, M. M. TEM study of fracturing in spherical and plate-like LiFePO $\\cup_{4}$ particles. Electrochem. Solid-State Lett. 11, A25–A29 (2008). \n53. Li, L. L., Zhang, Z. J., Zhang, P., Wang, Z. G. & Zhang, Z. F. Controllable fatigue cracking mechanisms of copper bicrystals with a coherent twin boundary. Nat. 3536 (2014). \n\n54. Mayer, J., Giannuzzi, L. A., Kamino, T. & Michael, J. TEM sample preparation and FIB-induced damage. MRS Bull. 32, 400–407 (2011). 55. Woo, J., Borisevich, A., Koch, C. & Guliants, V. V. Quantitative analysis of HAADF–STEM images of MoVTeTaO M1 phase catalyst for propane ammoxidation to acrylonitrile. ChemCatChem 7, 3731–3737 (2015). \n\n# Acknowledgements \n\nWe thank Dr Yuanyuan Zhu for help on the GPA analysis. This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, Subcontract No. 6951379 under the Advanced Battery Materials Research (BMR) program. The microscopic analysis in this work was conducted in the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL), a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at PNNL. PNNL is operated by Battelle for the Department of Energy under Contract DE-AC05-76RLO1830. \n\n# Author contributions \n\nC.-M.W., J.X., J.Z. and J.-G.Z. initiated this research project. P.Y., J.Z., J.-G.Z. and C.-M.W. designed the experiment. J.Z. carried out material preparation and battery test. P.Y. conducted TEM experimental work and drafted the manuscript. All authors were involved in revising the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting financial interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Yan, P. et al. Intragranular cracking as a critical barrier for high-voltage usage of layer-structured cathode for lithium-ion batteries. Nat. Commun. 8, 14101 doi: 10.1038/ncomms14101 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1021_jacs.7b06765", + "DOI": "10.1021/jacs.7b06765", + "DOI Link": "http://dx.doi.org/10.1021/jacs.7b06765", + "Relative Dir Path": "mds/10.1021_jacs.7b06765", + "Article Title": "Promoter Effects of Alkali Metal Cations on the Electrochemical Reduction of Carbon Dioxide", + "Authors": "Resasco, J; Chen, LD; Clark, E; Tsai, C; Hahn, C; Jaramillo, TF; Chan, K; Bell, AT", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "The electrochemical reduction of CO2 is known to be influenced by the identity of the alkali metal cation in the electrolyte; however, a satisfactory explanation for this phenomenon has not been developed. Here we present the results of experimental and theoretical studies aimed at elucidating the effects of electrolyte cation size on the intrinsic activity and selectivity of metal catalysts for the reduction of CO2. Experiments were conducted under conditions where the influence of electrolyte polarization is minimal in order to show that cation size affects the intrinsic rates of formation of certain reaction products, most notably for HCOO-, C2H4, and C2H5OH over Cu(100)- and Cu(111)-oriented thin films, and for CO and HCOO- over polycrystalline Ag and Sn. Interpretation of the findings for CO2 reduction was informed by studies of the reduction of glyoxal and CO, key intermediates along the reaction pathway to final products. Density functional theory calculations show that the alkali metal cations influence the distribution of products formed as a consequence of electrostatic interactions between solvated cations present at the outer Helmholtz plane and adsorbed species having large dipole moments. The observed trends in activity with cation size are attributed to an increase in the concentration of cations at the outer Helmholtz plane with increasing cation size.", + "Times Cited, WoS Core": 774, + "Times Cited, All Databases": 849, + "Publication Year": 2017, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000408074800054", + "Markdown": "# Promoter Effects of Alkali Metal Cations on the Electrochemical Reduction of Carbon Dioxide \n\nJoaquin Resasco,†,‡ Leanne D. Chen,§,∥,⊥ Ezra Clark,†,‡ Charlie Tsai,§,∥ Christopher Hahn,§,∥ Thomas F. Jaramillo, $\\S,\\lVert\\rVert_{\\mathbb{P}}$ Karen Chan, ${\\S},\\|\\oplus$ and Alexis T. Bell\\*,†,‡ \n\n†Department of Chemical Engineering, University of California, Berkeley, California 94720, United States \n‡Joint Center for Artificial Photosynthesis, Material Science Division, Lawrence Berkeley National Laboratory, Berkeley, California \n94720, United States \n§SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California \n94305, United States \n∥SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United \nStates \n\n\\*S Supporting Information \n\n![](images/e3f476f0fbc211b907437194c0f9a7c6cc389e665e04903783df999c266dfa81.jpg) \n\nABSTRACT: The electrochemical reduction of $\\mathrm{CO}_{2}$ is known to be influenced by the identity of the alkali metal cation in the electrolyte; however, a satisfactory explanation for this phenomenon has not been developed. Here we present the results of experimental and theoretical studies aimed at elucidating the effects of electrolyte cation size on the intrinsic activity and selectivity of metal catalysts for the reduction of $\\mathrm{CO}_{2}$ . Experiments were conducted under conditions where the influence of electrolyte polarization is minimal in order to show that cation size affects the intrinsic rates of formation of certain reaction products, most notably for $\\mathrm{HCOO^{-}},$ , $\\mathrm{C}_{2}\\mathrm{H}_{4},$ and $\\mathrm{C_{2}H_{5}O H}$ over $\\operatorname{Cu}(100)$ - and $\\mathrm{{Cu}}(111)$ -oriented thin films, and for CO and ${\\mathrm{HCOO^{-}}}$ over polycrystalline $\\mathbf{A}\\mathbf{g}$ and $\\scriptstyle{\\mathrm{Sn}}$ . Interpretation of the findings for $\\mathrm{CO}_{2}$ reduction was informed by studies of the reduction of glyoxal and CO, key intermediates along the reaction pathway to final products. Density functional theory calculations show that the alkali metal cations influence the distribution of products formed as a consequence of electrostatic interactions between solvated cations present at the outer Helmholtz plane and adsorbed species having large dipole moments. The observed trends in activity with cation size are attributed to an increase in the concentration of cations at the outer Helmholtz plane with increasing cation size. \n\n# INTRODUCTION \n\nThe electrochemical reduction of $\\mathrm{CO}_{2}$ offers a means for storing electrical energy produced by renewable but intermittent resources, such as wind and solar radiation.1,2 Hydrocarbons and alcohols, rather than carbon monoxide and formic acid, are the preferred products of $\\mathrm{CO}_{2}$ reduction because of their high energy density. Despite extensive efforts aimed at identifying electrocatalysts that can produce these products, copper $\\mathrm{(Cu)}$ remains the only material capable of doing so with significant yields.3−5 Nevertheless, Cu requires a high overpotential $(\\sim-1\\mathrm{v}$ versus RHE) and produces a broad spectrum of products.6,7 Clearly, the discovery of novel means for reducing $\\mathrm{CO}_{2}$ to desirable products with higher efficiency and selectivity is needed. To do so requires understanding the fundamental processes occurring at the electrode surface. In addition to metal−adsorbate interactions, a full description of electrochemical reactions must include the effects of solvation and interfacial electric fields. A number of studies have shown that one way of influencing the product distribution is through changes in the electrolyte cation.8−13 \n\nThe role of cations is particularly interesting because a number of studies have shown that both the activity and selectivity of Ag, $\\mathrm{Hg,}$ and $\\mathtt{C u}$ for the $\\mathrm{CO}_{2}$ reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ are influenced significantly by the size of the alkali metal cation in the electrolyte.8−13 Similar effects have also been observed for the electrochemical reduction of oxygen, the oxidation of hydrogen, and the oxidation of low molecular weight alcohols.14−18 For $\\mathrm{Ag}$ and $\\mathrm{Hg,}$ which are selective for $\\mathrm{CO}_{2}$ reduction to carbon monoxide (CO) and formate anions $\\left(\\mathrm{{HCOO^{-}}}\\right)$ , respectively, increasing the alkali metal cation size increases the rates of formation of these products.8,10,11 For $\\begin{array}{r}{\\mathrm{Cu},}\\end{array}$ increasing alkali metal size leads to higher selectivities to $\\mathbf{C}_{2}$ products, e.g., ethylene and ethanol.9,12,13 Explanations for these phenomena have been attributed to differences in local $\\mathrm{\\boldmath~\\pH,}$ or differences in kinetic overpotentials due to the electrochemical potential in the outer Helmholtz plane being affected by cation size.8,10,11,13 \n\nOne of the challenges to finding a consistent interpretation for the effects of cation size on the intrinsic kinetics of $\\mathrm{CO}_{2}$ reduction is that many studies are carried out under conditions where mass transport also contributes to the observed activity and product distribution. In a recent study, we reported the effects of cation size on the rate of the ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ under strong mass-transport limitations.13 We showed that the increase in $\\mathrm{\\tt{pH}}$ and the decrease in $\\mathrm{CO}_{2}$ concentration near the cathode, caused by inadequate mass transfer through the hydrodynamic boundary layer in front of the cathode, could be offset by the hydrolysis of solvated cations. We showed that the increased buffering effect of solvated cations with cation size could be captured theoretically and suggested that this effect is responsible for the observed changes in the overall current density and the distribution of product current densities with cation size. \n\nIn this work, we present a combined experimental and theoretical study of the effects of electrolyte cation size on the intrinsic activity and selectivity of metal catalysts for the reduction of $\\mathrm{CO}_{2}$ . In contrast to earlier studies, experiments were conducted at sufficiently low applied voltages to avoid the effects of concentration polarization of the electrolyte, so that the influence of cation size on the intrinsic activity and selectivity of each catalyst could be observed. Most of our work was conducted using epitaxially grown $\\mathtt{C u}(100)$ or $\\mathrm{{Cu}}(111)$ thin films; a more limited study was carried out using polycrystalline $\\mathbf{Ag}$ and Sn films. Density functional theory (DFT) calculations were used to investigate how cations and cation size affect the stabilization of reaction intermediates involved in the reduction of $\\mathrm{CO}_{2}$ . These calculations demonstrate that adsorbed species with large dipole moments oriented away from the solvent are stabilized by electrostatic interactions with solvated cations, while trends in activity with cation size arise from differences in ion concentration at the Helmholtz plane. \n\n# METHODS \n\nElectrode Preparation. Single-side polished $\\operatorname{Si}(100)$ or (110) wafers (Virginia semiconductor, $\\mathrm{i}-10\\Omega\\mathrm{cm},$ ) were diced into ${\\sim}4\\mathrm{cm}^{2}$ sized pieces that were then used as electrode substrates. Prior to Cu deposition, the native oxide was removed from the Si substrates by submerging them in a $10\\%$ HF solution for $\\{\\dot{s}\\ \\mathrm{min}\\$ . Immediately after HF etching, the Si pieces were transferred to a vacuum chamber for sputter deposition of $\\mathtt{C u}$ in an AJA ATC Orion-5 sputtering system. The base pressure of the sputtering system prior to deposition was ${\\sim}2$ $\\times10^{-7}$ Torr. The flow rate of the sputtering gas (Ar) was 25 sccm and the sputtering pressure was adjusted to $2\\times10^{-3}$ Torr by controlling the speed at which the chamber was pumped, using a variable butterfly valve. Cu $(99.999\\%$ Kurt Lesker) was deposited at a rate of $1\\ \\mathrm{\\AA}/s,$ , as determined by a calibrated quartz crystal monitor, at ambient temperature. The total film thickness deposited was $100~\\mathrm{{nm}}$ . Polished, polycrystalline foils of $\\mathbf{A}\\mathbf{g}$ and $S_{\\mathrm{n}}$ $99.99\\%$ Alfa Aesar) were also used as electrodes without further preparation. \n\nElectrode Characterization. The structure of the Cu thin films was characterized by X-ray diffraction. The orientation and epitaxial quality of the films were determined using symmetric $\\theta\\cdot2\\theta$ scans, in plane $\\phi$ scans, $\\omega$ scans, or rocking curves, and pole figures. XRD patterns were taken with a PANanalytical X’Pert diffractometer, which uses a Cu $\\mathrm{K}\\alpha$ $\\mathit{\\Omega}\\left(\\lambda=1.54056\\mathrm{\\AA}\\right.$ ) X-ray source. Symmetric $\\theta-2\\theta$ scans were collected on samples fixed onto a flat glass slide in lockedcoupled mode with a goniometer resolution of $0.001^{\\circ}$ . Measured diffraction patterns were compared to known standards taken from the International Center for Diffraction Data (ICDD) PDF4 database (card #71-4610 for $\\mathtt{C u}$ ). \n\nElectrochemical Measurements. All electrochemical experiments were conducted in a gastight electrochemical cell machined from polyether ether ketone (PEEK).19 The cell was cleaned with 20 wt $\\%$ nitric acid and oxidized in UV-generated ozone for $15~\\mathrm{min}$ prior to the initiation of an experiment. The working and counter electrodes were parallel and separated by an anion-conducting membrane (Selemion AMV AGC Inc.). A gas dispersion frit was incorporated into the cathode chamber to provide vigorous electrolyte mixing. The exposed geometric surface area of each electrode was $\\scriptstyle{1\\ \\mathrm{cm}^{2}}$ and the electrolyte volume of each electrode chamber was $1.8~\\mathrm{mL}$ . The counter electrode was a Pt foil $(99.9\\%$ Sigma-Aldrich) that was flame annealed prior to each experiment. The working electrode potential was referenced against an $\\mathrm{\\Ag/AgCl}$ electrode (Innovative Instruments, Inc.) that was calibrated against a homemade standard hydrogen electrode (SHE). 0.05 M $\\mathbf{M}_{2}\\mathbf{CO}_{3}$ (M referring to an alkali metal cation) solutions were prepared by mixing ultrapure salts (SigmaAldrich $99.995\\%$ ) and $18.2~\\mathrm{M}\\Omega$ DI, and were used as the electrolyte without further purification. The cathode chamber was sparged with $\\mathrm{CO}_{2}$ $(99.999\\%$ Praxair) at a rate of 5 sccm for $20~\\mathrm{min}$ prior to and throughout the duration of all electrocatalytic measurements. Upon saturation with $\\mathrm{CO}_{2}$ the $\\mathsf{p H}$ of the electrolyte was 6.8, which was maintained throughout the duration of electrolysis. \n\nElectrochemical measurements were performed using a Biologic VSP-300 potentiostat. All electrochemical data were recorded versus the reference electrode and converted to the RHE scale. Potentiostatic electrochemical impedance spectroscopy (PEIS) was used to determine the uncompensated resistance $\\left(R_{\\mathrm{u}}\\right)$ of the electrochemical cell by applying voltage waveforms about the open circuit potential with an amplitude of $\\bar{2}0~\\mathrm{mV}$ and frequencies ranging from ${50}\\ \\mathrm{Hz}$ to $500~\\mathrm{kHz}$ . The potentiostat compensated for $85\\%$ of $R_{\\mathrm{u}}$ in situ and the last $15\\%$ was postcorrected to arrive at accurate potentials. The electrocatalytic activity was assessed by conducting chronoamperometry at each fixed applied potential for $70~\\mathrm{min}$ . \n\nProduct Analysis. The effluent from the electrochemical cell was passed through the sampling loop $(250~\\mu\\mathrm{L})$ of an Agilent 7890B gas chromatograph equipped with a pulsed-discharge helium ionization detector (PDHID). He $99.9999\\%$ Praxair) was used as the carrier gas. The effluent of the electrochemical cell was sampled every $14~\\mathrm{min}$ . The gaseous products were separated using a Hayesep- $\\scriptstyle\\cdot\\mathrm{e}$ capillary column (Agilent) connected in series with a packed ShinCarbon ST column (Restek Co.). The column oven was maintained at $50~^{\\circ}\\mathrm{C}$ for 1 min followed by a temperature ramp at $30~{^\\circ}\\mathrm{C}/\\mathrm{min}$ to $250\\ ^{\\circ}\\mathrm{C},$ which was maintained for the duration of the analysis. The signal response of the PDHID to each gaseous product was calibrated by analyzing a series of NIST-traceable standard gas mixtures (Air Gas). \n\nThe electrolyte from both electrode chambers was collected after electrolysis and analyzed using a Thermo Scientific UltiMate 3000 liquid chromatograph equipped with a refractive index detector (RID). The electrolyte aliquots were stored in a refrigerated autosampler until analyzed in order to minimize the evaporation of volatile products. The liquid-phase products contained in a $10\\mu\\mathrm{L}$ sample were separated using a series of two Aminex HPX 87-H columns (Bio-Rad) and a 1 mM sulfuric acid eluent $99.999\\%$ Sigma-Aldrich). The column oven was maintained at $60~^{\\circ}\\mathrm{C}$ for the duration of the analysis. The signal response of the RID to each liquid-phase product was calibrated by analyzing standard solutions of each product at a concentration of 1, 10, and $50~\\mathrm{mM}$ . \n\n![](images/8e9064bbde83765035a957c659f6a7065450caefe38b8400dbbffb352ffc8f54.jpg) \nFigure 1. Structural characterization of oriented Cu thin films. (a) Symmetric $\\theta-2\\theta,$ in plane $\\phi,$ and $\\omega$ rocking curve scans for Cu deposited on Si(100). (b) Symmetric $\\theta-2\\theta,$ in plane $\\phi,$ and $\\omega$ rocking curve scans for $\\mathtt{C u}$ deposited on Si(110). (c) $\\mathrm{Cu}(11\\mathrm{\\bar{1}})$ pole figure for $\\mathtt{C u}$ deposited on Si(100). (d) $\\mathrm{Cu}(200)$ pole figure for Cu deposited on Si(110). \n\nTheoretical Calculations. Plane-wave density functional theory (DFT) calculations employing periodic boundary conditions was used for all calculations in this study. The Quantum ESPRESSO20 code and the Atomic Simulation Environment $\\bar{(\\mathrm{ASE})}^{21}$ were used, along with ultrasoft pseudopotentials and the Bayesian error estimation exchangecorrelation functional with van der Waals interactions (BEEF-vdW).22 This functional has been optimized for both chemisorption energies and long-range van der Waals interactions. For all calculations, a planewave cutoff of $500~\\mathrm{eV}$ and a density cutoff of ${5000}\\mathrm{eV}$ were used, based on convergence tests from previous studies.23 A Monkhorst−Pack24 kpoint grid of $(4\\times4\\times1)$ was used for $(3\\times3)$ cells while a $(2\\times2\\times1)$ grid was used for $(6\\times6)$ cells. All systems were modeled using a periodic $\\operatorname{Cu}(111)$ slab, two ice-like water bilayers, the solvated ion and at least $12\\mathrm{~\\AA~}$ of vacuum perpendicular to the surface. The field effect on various $\\mathrm{CO}_{2}$ adsorbates without ions or solvating waters was also investigated by applying a sawtooth potential in each simulation cell, for moderate field strengths where the vacuum energy remains above the Fermi level.25 As an example, Figure S3 in the Supporting Information (SI) shows the average potential energy along the $z-$ direction for $\\mathrm{CH}_{3}$ on $\\mathtt{C u}$ (111), with an applied sawtooth potential. \n\nConstrained minima hopping26 (CMH) was used for the global optimization of water structures surrounding each solvated ion. CMH enforces molecular identity by constraining the atomic distances within each molecular entity through Hookean constraints. The atoms were thermalized in a Maxwell−Boltzmann distribution at an initial temperature of $1000~\\mathrm{K},$ then evolved through molecular dynamics and relaxed to locate new local minima. To save computational cost, CMH was performed on two layers of Cu. The Cu atoms were fixed, while all others were allowed to relax. The convergence criterion for the CMH was satisfied when three successive lowest energy minima were found within $0.05~\\mathrm{eV}$ of each other. Thereafter, the system was relaxed until the forces on all atoms were less than $0.05\\ \\mathrm{eV}/{\\mathring{\\mathrm{A}}}.$ Finally, the third layer of Cu was added back into the system to perform a single point calculation and obtain a more accurate value for the energy. \n\n# RESULTS \n\nCation Effects on $\\mathsf{C u}(100)$ and $\\mathsf{c u}(111)$ Oriented Films. Epitaxially grown Cu thin films were used as electrocatalysts in order to have well-defined catalytic surfaces.27 These films were prepared by radio frequency sputtering of Cu onto silicon (Si) single crystal substrates, taking advantage of the epitaxial relationship between Cu and Si substrates of different orientations.27,28 Most of our studies were conducted on the $\\operatorname{Cu}(100)$ surface because it has been shown that polycrystalline Cu consists mostly of (100) oriented crystallites, and the $\\operatorname{Cu}(100)$ surface has a higher selectivity to more desirable products such as $\\mathrm{C}_{2+}$ hydrocarbons and oxygenates (e.g., ethylene and ethanol).29−32 Symmetric $\\theta-2\\theta$ XRD patterns of $100\\ \\mathrm{nm}$ thick Cu films deposited on Si(100) and Si(110) substrates are shown in Figure 1. The observation of a single $\\operatorname{Cu}(200)$ diffraction peak for Cu deposited on Si(100) indicates that the film is oriented with the (100) crystallographic direction normal to the film plane. Similarly, for Cu deposited on Si(110) only the diffraction peak associated with $\\operatorname{Cu}(111)$ is observed.27,28 While symmetric XRD scans establish the out-ofplane texture relationships, both out-of-plane and in-plane texture analyses are necessary to determine whether the Cu thin films grow epitaxially on Si, as a film with strong fiber texture would show a similar diffraction pattern. To this end, in planetexture analysis was conducted using X-ray pole figures. Pole figures represent the texture of a material and show the distribution of particular crystallographic directions in a stereographic projection. The $\\mathrm{Cu}(111)$ X-ray pole figure for $\\operatorname{Cu}(100)$ on $\\operatorname{Si}(100)$ exhibits discrete Bragg reflections, indicating cube-on-cube epitaxial growth of Cu on the \n\n![](images/103541a73ca2f469c81d53c500759010655a4ebb003fce41e3b70a2174b40c07.jpg) \nFigure 2. Effect of alkali metal cations on the total activity over $\\operatorname{Cu}(100)$ . (a) Linear sweep voltammograms for $\\mathrm{CO}_{2}$ reduction on $\\operatorname{Cu}(100)$ in $\\mathrm{CO}_{2}$ saturated $0.1\\mathrm{~M~}$ bicarbonate electrolytes containing different metal cations. (b) Average current densities obtained during bulk electrolysis as a function of metal cation at different potentials. \n\n![](images/d8f74da50489dbfa1fdac6f739c9145451a244d98eb0869efd4817f32255e63e.jpg) \nFigure 3. Cation effect on the rates of formation of major products of $\\mathrm{CO}_{2}$ reduction over $\\mathrm{Cu}(100)$ . Partial current densities for each of the major products as a function of the electrolyte metal cation on $\\mathtt{C u}(100)$ . Data are presented at potential between $-0.7$ to $-1.1\\mathrm{~V~}$ vs RHE. \n\nSi(100) substrate. 4-fold symmetry is observed for the $\\mathrm{{Cu}}(111)$ Bragg reflections with an azimuthal angle of $90^{\\circ}$ apart, which is expected for a Cu (100) single-crystal. For $\\mathtt{C u}$ (111) on Si (110), 6-fold symmetry is observed for the $\\mathtt{C u}$ (200) Bragg reflections, indicating both strong out-of-plane and in-plane texture and thus epitaxial growth on the Si(110) substrate (Figure 1a). Six diffraction spots in the pole figure are seen instead of three because there are two discrete sets of crystallites from twinning with an azimuthal angle of ${60}^{\\circ}$ apart. These results demonstrate that $\\mathtt{C u}$ thin films can be grown epitaxially with both (100) and (111) orientations. \n\nThe steady state activity and selectivity of the $\\operatorname{Cu}(100)$ surface was investigated in $\\mathrm{CO}_{2}$ -saturated bicarbonate electrolytes containing different alkali metal cations, by using potentiometric electrolysis at potentials from $-0.7$ to $-1.1{\\mathrm{~V~}}$ vs the reversible hydrogen electrode (RHE). Figure 2 shows the total current density as a function of electrolyte cation at various potentials. From both steady state potentiostatic and potential sweep measurements, it is clear that the total current density increases with cation size, and this trend is observed at all applied potentials. To identify the contributions to the increase in the total current density, we examined the effects of cation size on the product distribution. As large differences in total current density exist for electrolytes containing different cations, partial currents provide a better representation of trends in product formation rates than faradaic efficiencies. Complete information regarding faradaic efficiencies can be found in the SI (Figure S1, Table S1). \n\nFigure 3 shows the partial current density for each of the major products as a function of electrolyte cation. Formation rates of minor liquid products can be found in the Supporting Information (Table S1). A key finding is that the production rates of hydrogen and carbon monoxide are relatively unaffected by increasing cation size, whereas the rates of formate, ethylene, and ethanol formation increase monotonically with increasing cation size. The rate of methane production reaches a maximum for ${\\mathbf{N}}{\\mathbf{a}}^{+}.$ - and $\\mathrm{K^{+}}.$ - based electrolytes and is lower in all other electrolytes. The trends seen in Figure 3 are consistent with previous amperometric measurements.9 It is notable that these trends are independent of the applied overpotential. \n\nTo probe the effects of mass transport limitations, the $\\mathrm{CO}_{2}$ flow rate into the electrochemical cell was varied. As the $\\mathrm{CO}_{2}$ flow rate is increased, the hydrodynamic boundary layer thickness will decrease, resulting in a larger maximum diffusive flux of $\\mathrm{CO}_{2}$ to the electrode surface. At low reaction rates (i.e., low current densities), for which diffusion of $\\mathrm{CO}_{2}$ is sufficiently rapid to prevent depletion at the cathode surface, increasing the flow rate of $\\mathrm{CO}_{2}$ should have no effect on catalyst activity. Whereas under mass transport limited conditions, increased reactant availability will affect the product distribution measured.13,32 Figure 4 shows that doubling the $\\mathrm{CO}_{2}$ flow rate from 5 to 10 sccm has no impact on the measured selectivity or activity of $\\mathtt{C u}$ (100) at $-0.9\\mathrm{V}$ vs RHE and $-1.0\\mathrm{V}$ vs RHE. However, at $-1.1\\mathrm{~V~}$ vs RHE, doubling the $\\mathrm{CO}_{2}$ flow rate decreases the faradic efficiency to $\\mathrm{H}_{2}$ and $\\mathrm{CH}_{4}$ and increases the faradaic efficiency for $\\mathrm{C}_{2+}$ products. As shown previously, these trends are due to the increased rate of mass transfer at higher gas flow rates, which improves the supply of $\\mathrm{CO}_{2}$ to the cathode.32 Therefore, the effects of cation size on the partial current densities observed in Figure 3 at potentials more positive than ${\\sim}-1.0\\mathrm{~V~}$ vs RHE are ascribable to the influence of cation size on the intrinsic kinetics of $\\operatorname{Cu}(100).$ , particularly for the formation of formate, ethylene, and ethanol, and to a lesser degree, methane. \n\n![](images/4c1ba36410c5365b7f5970c17255bfa0a2e9c24788f5b2b372b92e3c2f6fa6c9.jpg) \nFigure 4. $\\mathrm{CO}_{2}$ flow rate studies for probing external mass transport limitations: Current efficiency (bars) and total current density (dots) for $\\mathrm{CO}_{2}$ reduction over $\\operatorname{Cu}(100)$ at different flow rates of $\\mathrm{CO}_{2}$ . \n\nThe effects of cation size were also investigated for $\\mathrm{CO}_{2}$ reduction over a $\\operatorname{Cu}(111)$ surface, and the results are presented in Figure 5. The trends with increasing cation size for the closepacked $\\mathrm{{Cu}}(111)$ surface are consistent with those observed for the $\\operatorname{Cu}(100)$ surface. Partial currents to $\\mathrm{{HCOO^{-}}}$ , $\\mathrm{C}_{2}\\mathrm{H}_{4},$ and $\\mathrm{C_{2}H_{5}O H}$ increase with increasing cation size while rates of formation of $\\operatorname{H}_{2},$ CO, and $\\mathrm{CH}_{4}$ are less affected by cation size. However, the effect of cation size is more pronounced on the close-packed surface, resulting in high selectivity $(\\sim40\\%$ FE) to $\\mathrm{C}_{2}\\mathrm{H}_{4}$ in $\\mathrm{CsHCO}_{3}$ even on a $\\mathrm{{Cu}}(111)$ surface, which is known to be more selective for producing $\\mathrm{CH}_{4}$ than $\\mathrm{C}_{2}\\mathrm{H}_{4}$ in $\\mathrm{K^{+}}$ - containing electrolytes.29,31,33−36 \n\nRelative Effects of Alkali Metal Cations. To further investigate the effects of the alkali metal cations, electrolysis was performed with mixtures of small $\\left(\\mathrm{Li}^{+}\\right)$ and larger $(\\mathrm{\\tilde{Na}^{+},~K^{+}},$ $\\bar{\\mathrm{~C~}}s^{+}\\mathrm{~,~}$ ) cations in the electrolyte, maintaining the total salinity at $0.1~\\mathrm{{M}}.$ . The results are shown in Figure 6. It is evident that the composition of the electrolyte has a noticeable effect on the partial currents for $\\mathrm{HCOO^{-}}$ , $\\mathrm{C}_{2}\\mathrm{H}_{4},$ and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ . No significant effect on the partial currents of $\\mathrm{H}_{2},$ CO, and $\\mathrm{CH}_{4},$ was observed. For the latter three products, the effect of the larger cation dominates that of the $\\mathrm{Li^{+}}$ cation, and even at relatively low percentages of the larger cation. Conversely, an electrolyte mixture that is dilute in the smaller cation results in identical selectivity to a solution that does not contain the small cation. These results suggest that the concentration of larger cations near the cathode surface is larger and/or that the larger cations have a much more significant promotional effect on the production of $\\mathrm{C}_{2}\\mathrm{H}_{4},$ $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH},$ , and ${\\mathrm{HCOO^{-}}}$ . \n\nCation Effect on Polycrystalline Ag and Sn. As carbon monoxide is a reaction intermediate which undergoes further reduction on Cu, the production rate of CO itself is less straightforward to interpret than that of the other major products.37 Therefore, to investigate the effect of cation size on CO production, and to provide further insights into the trends observed for $\\operatorname{Cu}(100)$ and $\\mathtt{C u}(111)$ , experiments were conducted on polycrystalline Ag and Sn foilsmetals that selectively produce CO and ${\\mathrm{HCOO^{-}}},$ , respectively.3,38 As seen in Figure 7, the current densities for CO and $\\mathrm{HCOO^{-}}$ production on both metals increases with cation size. This suggests that increasing cation size facilitates activation of $\\mathrm{CO}_{2}$ . Here again, we see that as with $\\operatorname{Cu}(100)$ and $\\mathrm{{Cu}}(111)$ , the rate of $\\mathrm{H}_{2}$ evolution is unaffected by cation size. These trends are also consistent with previous literature reports.8−11,13,39 \n\nCation Effects on Elementary Reaction Steps: Reduction of Intermediates. As shown above, the size of the electrolyte cation influences the formation of $\\mathbf{C}_{2}$ products. Recent theoretical studies suggest that $\\scriptstyle{\\mathrm{C-C}}$ bonds are formed via the reaction of two molecules of adsorbed CO or by the reaction of adsorbed CO with a formyl group, HCO.40 A recent study has shown that the latter process dominates at applied potentials near $-1\\mathrm{~V~}$ and leads to the formation of adsorbed $\\bar{\\mathrm{HC}}(\\mathrm{O}){\\mathrm{-C}}(\\mathrm{O})$ species, which then undergoes hydrogenation to form $\\mathrm{C}_{2}\\mathrm{H}_{4}$ or ${\\mathrm{CH}}_{3}{\\mathrm{CHO}}$ and $\\mathrm{C_{2}H_{5}O H}$ 40 Experimental studies suggest that the precursor to ${\\mathrm{CH}}_{3}{\\mathrm{CHO}}$ and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ is glyoxal (OHC−CHO).41 Therefore, to investigate which steps in the formation of $\\mathbf{C}_{2}$ products are affected by the electrolyte cation size, we carried out experiments in electrolyte containing glyoxal. As shown in Figure 8, the cation size has no effect on the partial currents of ${\\mathrm{CH}}_{3}{\\mathrm{CHO}}$ and $\\mathrm{C_{2}H_{5}O H}$ formation, which in this case requires no $\\scriptstyle{\\mathrm{C-C}}$ bond formation as glyoxal is the starting reagent. Consistent with previous observations, no $\\mathrm{C}_{2}\\mathrm{H}_{4}$ was observed during the hydrogenation of glyoxal.41 These findings strongly suggest that the size of the electrolyte cation affects the rate of $\\scriptstyle{\\mathrm{C-C}}$ bond formation, the rate increasing with increasing cation size, but has a negligible effect on the hydrogenation of glyoxal to ${\\mathrm{CH}}_{3}{\\mathrm{CHO}}$ and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ . \n\nAs larger cations facilitate $\\mathrm{CO}_{2}$ activation, evidenced by the increase in rates to CO and $\\scriptstyle{\\mathrm{HCOO^{-}}}$ (see Figure 3), experiments were carried out in electrolyte solutions saturated with CO but free of dissolved $\\mathrm{CO}_{2},$ in order to assess whether an increase in the surface coverage of adsorbed CO relative to adsorbed H favors $\\scriptstyle{\\mathrm{C-C}}$ coupling. Consistent with the results for $\\mathrm{CO}_{2}$ reduction over $\\operatorname{Cu}(1{\\bar{0}}0)$ , no change in methane activity with cation size was observed from CO reduction at $-1\\mathrm{~V~}$ vs \n\n![](images/388f87939fc5e82e3e84d0b75a124109b65b15fbd3ff7d65f0cf68aa0b377f75.jpg) \nFigure 5. Cation effect on the rates of formation of major products of $\\mathrm{CO}_{2}$ reduction over $\\mathrm{Cu}(111)$ . Partial current densities for each of the major products as a function of the electrolyte metal cation on ${\\mathrm{Cu}}(111)$ . Data are presented for the potential of $-1.0\\mathrm{~V~}$ vs RHE. \n\n![](images/45eeb850410c30c42b4fb59eff765d62451c6163adf95935009835a3afd4d43a.jpg) \nFigure 6. Relative effects of alkali metal cations. Partial currents for ethylene, ethanol, and formate formation as a function of the electrolyte composition on $\\mathrm{{Cu}}(100)$ . Data are presented for a potential of $-1.0\\mathrm{V}$ vs RHE. A mixture of ${\\mathrm{LiHCO}}_{3}$ and $\\mathrm{XHCO}_{3}$ electrolyte is used with X being Na, K, Cs (second cation). A fixed total salinity of $0.1\\mathrm{~M~}$ was used in all experiments. \n\nRHE. Figure 8b clearly shows that the rates of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ formation increase with increasing cation size. We note that the magnitude of this effect is comparable to that observed during the reduction of $\\mathrm{CO}_{2},$ which shows that the effect of cation size on the formation of multicarbon products cannot be ascribed solely to more facile $\\mathrm{CO}_{2}$ activation. \n\n# DISCUSSION \n\nCation Promoter Effects. The data presented in this study demonstrate that the size of the alkali metal cations in the electrolyte affects the intrinsic rates of formation of certain reaction products. On $\\mathtt{C u}$ (100) and $\\mathtt{C u}$ (111), these effects are most notable for $\\mathrm{HCOO^{-}}$ , $\\mathrm{C}_{2}\\mathrm{H}_{4},$ and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH};$ over polycrystalline $\\mathrm{Ag}$ and $S\\mathrm{n}_{\\mathrm{\\ell}}$ , the effects of cation size are observed for the formation of CO and $\\mathrm{HCOO^{-}}$ . It is also shown that larger cations have a stronger effect than smaller cations, and that only a small fraction of the larger cation is needed in the electrolyte to observe its influence. Trends in the partial current densities derived from the studies of the reduction of key reaction intermediates (OHCCHO and CO) suggest that the elementary steps promoted by the presence of metal cations are the activation of $\\mathrm{CO}_{2}$ and the initial $\\scriptstyle{\\mathrm{C-C}}$ coupling, whether through CO dimerization or CO−CHO coupling, and not the hydrogenation of $\\mathbf{C}_{2}$ intermediates leading to ethylene and ethanol. \n\nWe propose that the energetics for the formation of $\\mathrm{HCOO^{-}}$ and $\\mathbf{C}_{2}$ products are influenced by the presence of hydrated alkali ions located at the edge of the Helmholtz plane, and that the observed effects of cation size are attributable to differences in the cation concentration in the outer Helmholtz plane. This explanation is supported by DFT calculations performed using minimum energy structures of solvated cations at the interface. Since both $\\operatorname{Cu}(100)$ and $\\mathrm{{Cu}}(111)$ surfaces show consistent trends in activity with respect to alkali cation size, the closepacked $\\mathrm{{Cu}}(111)$ surface was chosen for the DFT simulations, which has also been frequently used in previous theoretical $\\mathrm{CO}_{2}\\mathrm{R}$ studies42−45 and where the water structure is more welldefined.46 \n\n![](images/dc4dcbcc85a97c50e35246b2d5d0a052b74ed9c46393b184b5a292b92f047ef7.jpg) \nFigure 7. Cation effect on two electron products. Partial currents for each of the major products as a function of the electrolyte metal cation on polycrystalline $\\mathbf{A}\\mathbf{g}$ and $S_{\\mathrm{n}}$ . Data are presented for a potential of $-1.0\\mathrm{~V~}$ vs RHE. \n\n![](images/453ef40de7a61a8dd1c7bb8acd715380e1548ad64a4f6242dcbec026cedd334a.jpg) \nFigure 8. Cation effects of the reduction of reaction intermediates. $\\left(\\mathsf{a}-\\mathsf{c}\\right)$ Partial currents for hydrogen, ethanol, and acetaldehyde formation from the reduction of glyoxal on $\\operatorname{Cu}(100)$ . Data are presented at a potential of $-0.6\\:\\mathrm{V}$ vs RHE. $\\left(\\mathrm{d-f}\\right)$ Partial currents for hydrogen, ethylene, and ethanol formation from the reduction of CO on $\\mathtt{C u}(100)$ . Data are presented at a potential of $-0.8\\mathrm{~V~}$ vs RHE. \n\nBecause the potentials applied during $\\mathrm{CO}_{2}$ reduction are much more negative than the potential of zero charge (PZC) of the low-index facets of Cu ≈ −0.7 VSHE,47 solvated cations should accumulate near the surface of the electrode during reaction.40,48 Given the very negative reduction potentials of alkali ions, they do not chemisorb under $\\mathrm{CO}_{2}$ reduction conditions. There is also evidence from studies of oxygen reduction that the cations remain partially solvated at the interface.49 The presence of the cation at the metal surface gives rise to high electric fields of $\\mathrm{{\\sim}}\\mathrm{{1\\V/\\mathring{A}}}$ in the vicinity of the ion.25,50 In contrast to classical continuum models of the electrochemical interface, the fields are highly localized when the structure of the cation and solvating waters is modeled explicitly. References 25 and 50 show that such fields extend roughly $\\lvert5\\mathring{\\mathrm{A}}$ from the center of the solvated cations and outside of this region decay to zero. \n\nThe strength of the adsorbate-field interaction can be probed qualitatively by the application of a uniform field in vacuum. This approach circumvents the challenge of finding a global minimum in the water and solvated cation structure in the presence of various adsorbates on the surface, which introduces many more degrees of freedom than standard atomistic computations in heterogeneous catalysis. It has also been shown previously that the effect of alkali promoters in heterogeneous catalysis can be modeled approximately by the effect of a uniform field.51 The interaction energy between an adsorbate and a uniform electric field at the interface is given by the following:5 2 \n\n$$\n\\Delta E=\\mu\\mathrm{{\\epsilon}}-\\frac{1}{2}\\alpha\\epsilon^{2}+\\ldots\n$$ \n\nwhere $\\mu$ and $\\alpha$ are the dipole moment and the polarizability (respectively) of the adsorbate, and $\\varepsilon$ represents the electric field. Adsorbate dipoles oriented in the opposite direction of the field will be stabilized, and vice versa. \n\nFigure 9 shows the field stabilization for various adsorbates that have been proposed to be involved in the electrochemical reduction of $\\mathrm{CO}_{2}$ on $\\mathrm{Cu}(111)$ .43,49,52 The change in adsorption free energy for each species was determined by applying a uniform field oriented perpendicular to the surface in vacuum.43 The corresponding values of $\\mu$ and $\\alpha_{\\iota}$ determined by fitting eq 1 with the calculated data, are given in Table 1. We note that $\\mathrm{H^{*}}$ does not have a significant value of $\\mu$ and is not affected by the electric field, which is consistent with previous experimental sbtyudtihes tdheanttihtayveo sthoewcnatihoant ihnydsrolugteinona.1d4s−o1r6ptSi ioncies tuhneaenecetregdy for hydrogen adsorption is a descriptor for the hydrogen evolution activity on metals, the rate for hydrogen production should also be relatively insensitive to the identity of the cation, consistent with the experimental data presented here.53 Recent calculations of the electrochemical barriers for $\\mathrm{CO}_{2}$ reduction using an explicit solvent model have shown that reduction of $^{*}\\mathrm{CO}$ to form $^{*}{\\mathrm{CHO}}$ is the limiting step for $\\mathrm{CH}_{4}$ formation.43 Since the value of $\\mu$ for $^{*}\\mathrm{CHO}$ is zero, the cation-induced field would stabilize $^{*}\\mathrm{CO}$ and therefore increase the energy barrier for hydrogenation to $^{*}\\mathrm{HCO},$ the rate-limiting step on the path to $\\mathrm{CH}_{4}$ formation. Therefore, $\\mathrm{CH}_{4}$ formation should occur in regions of the catalyst that are not strongly influenced by the cations located at the outer Helmholtz plane, and correspondingly the partial current density for $\\mathrm{CH}_{4}$ should not be strongly affected by cation identity, which is consistent with the trend in the experimental data shown above. \n\n![](images/bef8af1f4c45af337f879c8d1eaf9e6a47688c4aacb4526b9cb82f66916b0992.jpg) \nFigure 9. Field effects on various $\\mathrm{CO}_{2}\\mathrm{R}$ intermediates on $\\mathrm{Cu}(111)$ . The energy of each adsorbate is plotted as a function of field strength, which is obtained by applying a uniform electric field oriented perpendicular to the slab. The curves are fit to Equation 1 and the corresponding dipole moment $\\mu$ and polarizability $\\alpha$ of the adsorbates are given in Table 1. Solid curves highlight the adsorbates that are most strongly affected by an electric field. Adsorbates with positive dipole moments $\\mu$ (oriented in the direction opposite to the electric field) are stabilized, while adsorbates with negative $\\mu$ (aligned with the electric field) are destabilized. \n\nTable 1. Dipole Moments and Polarizabilities of Adsorbates on $\\mathbf{Cu(111)}$ , Determined with eq 1 \n\n\n
adsorbateμ (eA)α (eA²/V)
*CO0.760.40
*COOH-0.190.60
*OCHO0.040.42
*CO0.230.22
*CHO0.000.36
*OCCO0.660.54
*OCCHO0.750.74
*CHOH-0.050.52
*CH-0.020.18
*CH-0.080.26
*CH-0.030.44
*OH-0.260.14
*H0.000.00
\n\nFor adsorbates containing $\\scriptstyle{\\mathrm{C}}={\\mathrm{O}}$ bonds oriented perpendicular to the surfacein particular, $^*\\mathrm{CO}_{2},$ $\\scriptstyle{\\mathrm{\"occo}}$ , and \\*OCCHOthe field stabilization should be large, $\\mathrm{\\Omega}\\sim1\\ \\mathrm{eV}$ for fields of ${\\sim}-1~\\mathrm{V/\\mathringA}$ in the vicinity of the cations. As shown in Table 1, these species have the largest dipole moments. Previous theoretical calculations have shown that on weakly binding metals such as Ag, the field-induced stabilization of $^*\\mathrm{CO}_{2}$ is crucial for the activation of $\\mathrm{CO}_{2}$ to form CO.25 The barrier for the hydrogenation of ${\\mathrm{\\mathrm{*}}}_{\\mathrm{CO}_{2}}$ to $^{*}{\\mathrm{COOH}}$ is generally very small,54 so stabilization of $^{*}\\mathrm{CO}_{2}$ should increase the coverage of $*_{\\mathrm{COOH}}$ . The $^{*}{\\mathrm{COOH}}$ species can undergo further hydrogenation to form HCOOH or $^{*}\\mathrm{CO}$ . The chemical hydrogenation barriers for $^{*}{\\mathrm{COOH}}$ to form HCOOH are surmountable at 0.69 and $0.75\\ \\mathrm{eV}$ on $\\operatorname{Cu}(111)$ and ${\\mathrm{Cu}}(211)$ respectively, and $0.46~\\mathrm{{\\eV}}$ on $\\mathrm{Ag}(211),^{23}$ consistent with increased HCOOH production observed on all of the surfaces investigated. For weakly binding metals such as $\\mathbf{A}\\mathbf{g}$ and $S\\mathrm{n}_{\\mathrm{\\ell}}$ , the field effect would promote $\\mathrm{CO}_{(\\mathrm{g)}}$ production, whereas for moderate to strongly binding metals such as $\\mathtt{C u}$ and Pt, $^{*}\\mathrm{CO}$ produced in the vicinity of a cation would also be field stabilized, thereby decreasing its desorption rate and increasing its $^{*}\\mathrm{CO}$ coverage there. \n\nOn Cu surfaces, formation of the initial intermediates to $\\mathbf{C}_{2}$ products are also field-assisted. The greater stabilization of the $^{*}\\mathrm{{OCCO}}$ relative to $2^{*}\\mathrm{CO}$ in the presence of a cation is due to the differences in the dipole moments of the product and reactant species,36 which has the effect of lowering the barrier to $\\scriptstyle{\\mathrm{C-C}}$ bond formation. In the absence of the cation-created electrostatic field and effects of solvation by water, the barrier for this process is not surmountable at room temperature.55 At higher overpotentials, where $^{*}{\\mathrm{CHO}}$ can be produced, $^{*}\\bar{\\mathrm{CO}}\\mathrm{-^{*}C H\\bar{O}}$ coupling would also be a feasible route toward $\\mathbf{C}_{2}$ products, and the corresponding barrier should be similarly field-stabilized due to the large dipole on $^{*}\\mathrm{OCCHO}_{;}$ , as shown in Figure 9.40 Since the formation of glyoxal via addition of a hydrogen atom to $^{*}\\mathrm{OCCHO}$ is the first step along the path to forming ethylene and ethanol, the observation (see Figure 8) that the selectivity of products derived from glyoxal is independent of cation size suggests that the rate-determining step in formation of $\\mathbf{C}_{2}$ products occurs at the point of $\\scriptstyle{\\mathrm{C-C}}$ bond formation and prior to formation of glyoxal.54 The net effect of increased CO production, CO coverage, and $\\scriptstyle{\\mathrm{C-C}}$ coupling on Cu on field-stabilized sites results in a net nonmonotonic trend in the partial current density for CO with cation size. \n\nWhile the influence of the cation-induced field at the catalyst surface can explain the role of cations in promoting elementary steps in the reduction of $\\mathrm{CO}_{2}$ that involve strong dipole moments, it does not explain the observed trend with cation size. We therefore explored the possibilities that this effect is due to disparities in the magnitude of the electrostatic field induced by cations of different size and/or an increase in the concentration of solvated cations at the outer Helmholtz plane as a function of size. \n\nConstrained minima hopping26 (CMH) was used to obtain the optimized structure of water surrounding each solvated ion on $\\bar{\\mathrm{Cu}(111)}$ . The structures of the solvated ions are shown in Figure S5 and the distances of the solvated cation from the $\\mathrm{{Cu}}(111)$ surface are given in Table S3. Figure 10 shows that the calculated fields in the vicinity of adsorbed CO $({}^{*}\\mathrm{CO})$ do not show a systematic variation with cation size. Moreover, any differences in the binding energy of intermediates induced by cations would give rise to exponential differences in current density, which we do not observe. \n\nWe hypothesize, therefore, that the ion specificity arises from an increase in the concentration of cations at the outer Helmholtz plane with increasing cation size. To determine the driving force for each cation toward the Helmholtz plane from bulk solution, we used these globally optimized solvation structures for each cation (Table S3) and calculated the energy required to move a solvated cation from the bulk of the electrolyte to a fixed distance of $6.25\\mathrm{~\\AA~}$ above the $\\mathrm{{Cu}}(111)$ surface the (see the SI for details). Figure 11 shows this energy change with the cathode potential relative to that for $\\mathrm{Li}^{+}$ , $\\Delta\\Delta E$ The potential $U$ vs SHE is determined through the following: \n\n![](images/b8e99f47ef9f37d7e5c2ff28df7f5e17c822a1cfab251a12f3658aee2ff3171c.jpg) \nFigure 10. Electric field distribution near the center of the adsorbate plotted as a function of the $z$ -coordinate of the simulation cell for the 2 $^{*}\\mathrm{CO}$ initial state. The geometry of an example structure is overlaid to clearly illustrate the position of the adsorbate. The cell is viewed from the side and rotated $90^{\\circ}$ . The minimum $z$ value is taken at the $\\mathtt{C u}$ surface, and the $z$ -position of the solvated cations is roughly at $20\\textup{\\AA}$ and not included in the overlay. \n\n![](images/8c0aac67df797d86f4f398003c63c751f239bee358143035e5eade74e2c02dd4.jpg) \nFigure 11. The change in energy for bringing a solvated cation from bulk electrolyte to the outer Helmholtz plane at the $\\mathtt{C u}$ (111) facet for different cations shown as a function of the standard hydrogen electrode (SHE) potential. All energies are referenced to that for the $\\mathrm{Li^{+}}$ cation. The dependence of these energies on cathode potential results from the partial electron transfer to the ion upon migration from the bulk to the Helmholtz plane, and is reflected in eq 5. This energy becomes more negative with increasing ion size, suggesting a greater concentration of larger cations in the outer Helmholtz plane and giving rise to increased product current densities. The vertical dotted line indicates the potential for the standard hydrogen electrode. \n\n$$\nU=\\frac{\\Phi-\\Phi_{\\mathrm{SHE}}}{e}\n$$ \n\nwhere $\\Phi$ is the work function of the interface and $\\Phi_{\\mathrm{SHE}}$ is that corresponding to the standard hydrogen electrode, determined experimentally to be ${\\sim}4.4~\\mathrm{eV}.^{56}$ The value of $\\Delta\\Delta E$ becomes more negative with increasing cation size, its magnitude increasing in the order $\\mathrm{Li^{+}}120\\ m A h/g}$ over 100 cycles). As shown in Fig. 6C, the coulombic efficiency was ${\\sim}100\\%$ , and the cell exhibited good rate capability when higher current densities (0.2 and $0.3\\mathrm{mA}/\\mathrm{cm}^{\\sharp}.$ ) were applied. \n\nLi-S and Li- ${\\bf\\cal O}_{2}$ chemistries were also demonstrated as hybrid solidliquid electrolyte systems. Conventional Li-S batteries using liquid electrolyte suffer from the polysulfide shuttling effect and side reactions with Li metal that cause significant capacity decay and low coulombic efficiency. The hybrid SSE system can avoid these issues. The dense garnet SSE can physically block the dissolved polysulfides from reacting with the Li metal and locally confine the sulfur/polysulfide active materials to the cathode side. To demonstrate the garnet SSE blocking effect in the Li-S system, we used an elemental sulfur cathode to construct the hybrid solid-liquid Li-S battery full cell. A conventional liquid electrolyte, $^\\textrm{\\scriptsize1M}$ LiTFSI in DME/DOL [1:1 $\\left(\\mathrm{v/v}\\right)]$ , was applied to the sulfur cathode. The sulfur loading was ${\\sim}1.0~\\mathrm{mg/cm}^{2}$ . The galvanostatic discharge and charge curves are shown in Fig. 6D. The initial discharge and charge capacities were 1532 and $1388\\mathrm{mAh/g},$ respectively, which correspond to $90.6\\%$ coulombic efficiency. The cycling performance exhibited both high capacity and $599\\%$ coulombic efficiency, which indicates that the garnet SSE can effectively block the polysulfide migration/shuttling effect for Li-S batteries (fig. S11). Note that the shuttling effect in liquid electrolyte–based Li-S batteries exhibits a higher charge capacity than the discharge capacity. In this system, the coulombic efficiency is typically defined as the ratio of discharge capacity over charge capacity. The cell performance degradation is possible due to the deposition of the dissolved sulfur and polysulfide materials into the isolated pores on garnet SSE surface (fig. S12). These deposited active materials lack sufficient electron transfer pathway and became “dead active materials” that cannot be used anymore, which leads to fast capacity decay. Garnet SSE remained stable, and no phase change after cycling in batteries was observed (fig. S13). \n\nSimilar to the shuttling effect in Li-S batteries, conventional Li- $O_{2}$ batteries suffer from the diffusion of oxygen through the electrolyte layer to Li metal, which forms an insulating oxide layer on the anode surface and increases interfacial resistance. In addition, to lower the charge overpotential, redox mediators are often used in the liquid electrolyte, which can directly react with the Li metal anode and induce unfavorable side reactions. By introducing this hybrid solid-liquid electrolyte, these challenges can be avoided because Li metal will not be oxidized by gaseous oxygen or corroded by redox mediators. Here, we demonstrate a hybrid solid-liquid $\\mathrm{Li}{\\-}\\mathrm{O}_{2}$ cell using a carbon cathode. Figure 6E displays the cell’s electrochemical performance at a current density of $15\\mathrm{\\bar{\\upmu}A\\mathrm{\\bar{/cm}}}^{2}$ with a charge/discharge time limit of 10 hours. The cell can be cycled over 10 cycles and showed a stable flat discharge plateau at ${\\sim}2.5\\mathrm{V}$ . \n\nRecently, an interface-engineered all–solid-state battery was developed to adopt a porous garnet electrolyte structure to enhance Li-ion \n\n![](images/b5fd67fa6dab6bfd516835450be7507bd791585d3ba4104499aff946b14bad76.jpg) \nFig. 5. Schematic and first-principles computation of the Li-Al alloy interface between the Li metal and the garnet SSE. (A) The reaction between Al and Li promotes enhanced molten Li infusion onto the garnet’s rough surface, whereas the formation of a Li-Al alloy fills the gap between the garnet solid electrolyte and the Li metal to improve interfacial contact and enhance ${\\mathsf{L}}{\\mathsf{i}}^{+}$ transport. (B) Calculated mutual reaction energy $\\Delta E_{\\mathrm{D,mutual}}$ of the garnet and Li-Al alloy interfaces. \n\nFu et al., Sci. Adv. 2017; 3 : e1601659 7 April 2017 transfer at the electrode-electrolyte interface with improved capacities and cycling performance (51). We envision that garnet structure with interface engineering can be designed into interconnected ion and electron networks for Li-S and $\\mathrm{Li}{\\cdot}\\mathrm{O}_{2}$ batteries to host dissolved sulfur/ polysulfides or active catalysts with high surface areas. In addition, the porous garnet structure can be an ideal three-dimensional ionconducting scaffold to confine Li in the cell during repeated cycling. \n\n![](images/4779434a10fe6a00d75cd958a1616b2968ac670aa1e60060d7d93253f71737c7.jpg) \nFig. 6. Hybrid solid-state battery demonstrations. (A) EIS of the hybrid solid-liquid LIBs. $\\mathsf{L i F e P O}_{4}$ cathode is used with a conventional electrolyte on the cathode side: $1\\mathsf{M L i P F}_{6}$ in ethylene carbonate (EC)/diethyl carbonate (DEC) [1:1 (v/v)]. (B) Galvanostatic charge/discharge profiles of the hybrid solid-liquid Li-ion cell. (C) Cycling performance of the cell over 100 cycles at different current densities. (D) Electrochemical performance of the hybrid solid-liquid Li-S cell. Elemental sulfur was used as the cathode, and 1 M LiTFSI in dimethoxyethane (DME)/1,3-dioxolane (DOL) [1:1 $(\\mathsf{v}/\\mathsf{v})]$ was used as the electrolyte on the cathode side. (E) Electrochemical performance of the hybrid solid-liquid Li- ${\\boldsymbol{\\cdot}}{\\boldsymbol{0}}_{2}$ battery. Highly conductive carbon was used as the cathode, and 1 M LiTFSI in tetraethylene glycol dimethyl ether (TEGDME) was used on the cathode side. \n\n# DISCUSSION \n\nWe demonstrate an effective strategy to modify the garnet solid electrolyte (LLCZN) and Li metal by introduction of an ultrathin conformal metal coating. We discovered that the metal layer would be immediately replaced by molten Li metal and then migrated toward the bulk Li metal. The alloying process significantly improves the wettability between the molten Li metal and the garnet SSE. By forming this Li-rich solid solution, the garnet surface becomes lithiophilic, which allows the bulk Li electrode to conformally adhere to the garnet surface after solidification of molten Li metal. Because the Li/metal weight ratio is near $100\\%$ , their solid solution can be considered as a pure Li phase. As a result, intimate contact between garnet and Li metal is achieved, which decreases the interfacial resistance, minimizes polarization, and stabilizes the voltage plateau during Li stripping/plating. The interfacial resistance at $20^{\\circ}\\mathrm{C}$ was drastically reduced from 950 to $75\\ \\mathrm{ohm}{\\cdot}\\mathrm{cm}^{2}$ using the Al-coated garnet SSE. The Li stripping and plating behavior of the symmetric cells exhibited a flat voltage plateau, demonstrating a stable charge transfer at the $\\mathrm{Li}/$ garnet SSE interface. It is anticipated that a series of metals, which could be alloyed with molten Li, can be used to modify the interface wettability with Li metal. In current stage, this work has addressed the main challenge of surface wettability between a garnet SSE and an Li metal. In the future, we will focus on creating an artificial solid electrolyte interface layer to further stabilize the garnet SSE interface in between a garnet SSE and a metallic Li anode. The advantages of the solid-state garnet SSE/Li metal configuration enable the development of a hybrid electrolyte system using the improved solidstate garnet SSE Li metal anode and a thin liquid electrolyte cathode interfacial layer. The hybrid electrolyte system exhibits good cell performances for different battery chemistries including Li-ion, Li-sulfur, and Li-oxygen batteries. This hybrid electrolyte design potentially avoids some fundamental challenges linked with conventional liquid-based electrolytes, such as Li dendrite growth, which paves the way for next-generation Li metal batteries. \n\n# MATERIALS AND METHODS Garnet SSE preparation \n\nThe LLCZN powder was synthesized via a modified sol-gel method. The starting materials were $\\mathrm{LiNO}_{3}$ $99\\%$ , Alfa Aesar), $\\mathrm{La}(\\mathrm{NO}_{3})_{3}$ $(99.9\\%$ , Alfa Aesar), $\\mathrm{Ca}(\\mathrm{NO}_{3})_{2}$ $(99.9\\%$ , Sigma-Aldrich), $\\mathrm{ZrO}(\\mathrm{NO}_{3})_{2}$ $(99.9\\%$ , Alfa Asear), and $\\mathrm{Nb}{\\mathrm{Cl}}_{5}$ $99.99\\%$ , Alfa Aesar). Stoichiometric amounts of these chemicals were dissolved in deionized water, and $10\\%$ excess $\\mathrm{LiNO}_{3}$ was added to compensate for Li volatilization during the high-temperature pellet preparation. Citric acid and ethylene glycol (1:1 mole ratio) were added to the solution. The solution was evaporated at $120^{\\circ}\\mathrm{C}$ for 12 hours to produce the precursor gel and then calcined to $400^{\\circ}$ and $800^{\\circ}\\mathrm{C}$ for 5 hours to synthesize the garnet powder. The garnet powders were then uniaxially pressed into pellets and sintered at $1050^{\\circ}\\mathrm{C}$ for 12 hours covered by the same type of powder. The sintered LLCZN pellets were polished to a thickness of ${\\sim}300~\\upmu\\mathrm{m}$ with a smooth surface. For the Al coating, $20~\\mathrm{nm}$ of Al was deposited using an Angstrom NexDep Ebeam evaporator at a rate of $0.2\\ \\mathrm{nm}/s$ . The pressure was kept below $5\\times10^{-6}$ torr during the deposition process. \n\n# Material characterization \n\nThe phase analysis was performed with powder XRD on a D8 Advance with LynxEye and SolX (Bruker AXS) using a $\\mathrm{Cu}\\ K\\upalpha$ radiation source operated at $40\\ensuremath{\\mathrm{kV}}$ and $40~\\mathrm{mA}$ . The morphology of the samples was examined by a field emission SEM (JEOL 2100F). \n\n# Electrochemical characterization \n\nThe symmetric Li | SSE | Li cell was prepared and assembled in an argon-filled glove box. The garnet electrolyte ceramic disc was wetpolished using sandpaper (400 and 800 grit) and rinsed with isopropanol alcohol several times. The thickness $(300\\upmu\\mathrm{m})$ of the garnet ceramic was controlled. To measure the ionic conductivity of the garnet SSE, we coated a Au paste on both sides of the ceramic disc, and it acted as a blocking electrode. The gold electrodes were sintered at $700^{\\circ}\\mathrm{C}$ to form good contact with the ceramic pellet. To prepare the nonblocking cell with Li metal, we pressed Li granular $(99\\%$ , Sigma) into fresh Li foil, and then we polished the surface to remove the oxidized layer. Fresh Li electrodes were then attached to the ceramic disc’s surfaces and gently pressed by hand. The symmetric cell was placed in between the stainless steel plates and heated at $170^{\\circ}\\mathrm{C}$ to soften the Li metal before being gently pressed by hand to improve contact with the stainless steel. The symmetric cell was heated to $200^{\\circ}\\mathrm{C}$ to melt the Li and naturally cooled down to room temperature. The symmetric cell was then assembled into a 2032 coin cell with a highly conductive carbon sponge. The carbon sponge acted as the force absorber and prevented the garnet ceramic disc from being damaged. Battery test clips were used to hold and provide good contact with the coin cell. The edge of the cell was sealed with an epoxy resin. The EIS was performed in a frequency range of 1 MHz to $100\\mathrm{mHz}$ with a $50\\mathrm{-mV}$ perturbation amplitude. Conductivities were calculated using $\\upsigma{=}L/(Z\\times A)$ , where $Z$ is the impedance for the real axis in the Nyquist plot, $L$ is the garnet ceramic disc length, and $A$ is the surface area. The activation energies were obtained from the conductivities as a function of temperature using the Arrhenius equation. The symmetric cell was tested on a homemade hotplate. The galvanostatic Li stripping and plating test was performed with a Bio-Logic MPG-2 battery cycler. All the cells were tested in an argon-filled glove box. \n\n# First-principles computation \n\nWe considered the interface as a pseudobinary of Li-Al alloy and garnet SSE using the same approach as defined in previous work (28, 52). The phase diagrams were constructed to identify possible thermodynamically favorable reactions. The energies for the materials used in our study were obtained from the Materials Project database (53), and the compositional phase diagrams were constructed using the pymatgen package (54). The mutual reaction energy of the pseudobinary is calculated using the same approach as defined in our previous work (28). \n\n# Hybrid solid-state battery preparation and evaluation \n\nAll the cells were assembled in an argon-filled glove box. The hybrid solid-state cells were assembled in 2032 coin cells following the similar schematic shown in fig. S8. The electrode slurry coating method was carried out in ambient environment. The $\\mathrm{LiFePO_{4}}$ electrode consisted of $70\\%$ commercial $\\mathrm{LiFePO_{4}}$ powder (MTI Corporation), $20\\%$ carbon black, and $10\\%$ polyvinylidene fluoride (PVDF) binder in $N.$ -methyl-2- pyrrolidone (NMP) solvent. The electrode was dried in vacuum at $100^{\\circ}\\mathrm{C}$ for 24 hours. $\\mathrm{LiPF}_{6}$ (1 M) in a mixture of EC and DEC [1:1 (v/v)] was used as the electrolyte for the hybrid solid-state LIBs. The galvanostatic charge and discharge test was measured using a cutoff voltage window of 2 to $4.5\\mathrm{V}$ . The sulfur electrode consists of $70\\%$ elemental sulfur powder (Sigma), $20\\%$ carbon black, and $10\\%$ polyvinylpyrrolidone (Sigma, $M_{\\mathrm{w}}=360{,}000)$ binder in water. The electrode was dried in vacuum at $60^{\\circ}\\mathrm{C}$ for 24 hours. Bis(trifluoromethane)sulfonimide Li salt (1 M) (LiTFSI, Sigma) in a mixture of DME and DOL [1:1 $\\mathbf{\\tau}(\\mathbf{v}/\\mathbf{v})]$ was used as the electrolyte for the hybrid solid-state Li-S batteries. The galvanostatic discharge and charge test was measured using a cutoff voltage window of 1 to $3.5\\mathrm{V}$ . The carbon cathode for the Li- ${\\bf\\cal O}_{2}$ battery consists of $90\\%$ high-conductivity carbon (Ketjen Black EC600JD) and $10\\%$ PVDF binder in an NMP solvent. The slurry was casted onto a gas diffusion layer (Toray carbon paper) and dried under vacuum at $100^{\\circ}\\mathrm{C}$ for 24 hours. LiTFSI $(1\\mathbf{M})$ in TEGDME acted as the electrolyte for the hybrid solid-state $\\mathrm{Li}{\\cdot}\\mathrm{O}_{2}$ batteries. The battery was tested under a current density of $15\\upmu\\mathrm{A}/\\mathrm{cm}^{2}$ with a charge/discharge time limit of 10 hours. \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/3/4/e1601659/DC1 \n\nfig. S1. Cross sectional SEM image of garnet SSE. \nfig. S2. Cross section of Al-coated garnet SSE pellet. \nfig. S3. Magnified SEM image of Al-coated garnet SSE. \nfig. S4. Cross section of garnet-Li metal. \nfig. S5. Cross section of the interface between Li metal and Al-coated garnet SSE. \nfig. S6. Digital image and XRD of the lithiated Al-coated garnet SSE. \nfig. S7. Preparation of Li | Al–garnet SSE–Al | Li. \nfig. S8. Symmetric cell setup for charge and discharge tests. \nfig. S9. Digital image of the symmetric cells assembled into 2032 coin cells. \nfig. S10. Cross-sectional SEM images of the cycled Li | Al-coated garnet SSE interface. \nfig. S11. Electrochemical performance of the hybrid solid-state Li-S battery: Cycling stability of the cell and coulombic efficiency of the cell. fig. S12. SEM image of the garnet SSE in cycled Li-S cell. \nfig. S13. XRD profile of the garnet after cycling in Li-S cell. \ntable S1. The phase equilibria and decomposition energies of the garnet SSE and Li-Al alloy interfaces. \n\n# REFERENCES AND NOTES \n\n1. M. Armand, J.-M. Tarascon, Building better batteries. Nature 451, 652–657 (2008). \n2. B. Scrosati, J. Garche, Lithium batteries: Status, prospects and future. J. Power Sources 195, 2419–2430 (2010). \n3. W. Xu, J. Wang, F. Ding, X. Chen, E. Nasybulin, Y. Zhang, J.-G. Zhang, Lithium metal anodes for rechargeable batteries. Energy Environ. Sci. 7, 513–537 (2014). 4. H. Kim, G. Jeong, Y.-U. Kim, J.-H. Kim, C.-M. Park, H.-J. Sohn, Metallic anodes for next generation secondary batteries. Chem. Soc. Rev. 42, 9011–9034 (2013). \n5. C. Brissot, M. Rosso, J.-N. Chazalviel, S. Lascaud, Dendritic growth mechanisms in lithium/ polymer cells. J. Power Sources 81–82, 925–929 (1999). \n6. D. Aurbach, E. Zinigrad, Y. Cohen, H. Teller, A short review of failure mechanisms of lithium metal and lithiated graphite anodes in liquid electrolyte solutions. Solid State Ion. 148, 405–416 (2002). \n7. S.-O. Tung, S. Ho, M. Yang, R. Zhang, N. A. Kotov, A dendrite-suppressing composite ion conductor from aramid nanofibres. Nat. Commun. 6, 6152 (2015). 8. M.-H. Ryou, D. Jin Lee, J.-N. Lee, Y. Min Lee, J.-K. Park, J. Wook Choi, Excellent cycle life of lithium-metal anodes in lithium-ion batteries with mussel-inspired polydopamine-coated separators. Adv. Energy Mater. 2, 645–650 (2012). \n9. H. Wu, D. Zhuo, D. Kong, Y. Cui, Improving battery safety by early detection of internal shorting with a bifunctional separator. Nat. Commun. 5, 5193 (2014). \n10. W. Luo, L. Zhou, K. Fu, Z. Yang, J. Wan, M. Manno, Y. Yao, H. Zhu, B. Yang, L. Hu, A thermally conductive separator for stable Li metal anodes. Nano Lett. 15, 6149–6154 (2015). \n11. J. Qian, W. A. Henderson, W. Xu, P. Bhattacharya, M. Engelhard, O. Borodin, J.-G. Zhang, High rate and stable cycling of lithium metal anode. Nat. Commun. 6, 6362 (2015). \n12. Y. Lu, Z. Tu, L. A. Archer, Stable lithium electrodeposition in liquid and nanoporous solid electrlytes. Nat. Mater. 13, 961–969 (2014). \n13. N.-W. Li, Y.-X. Yin, C.-P. Yang, Y.-G. Guo, An artificial solid electrolyte interphase layer for stable lithium metal anodes. Adv. Mater. 28, 1853–1858 (2016). \n14. Z. Liang, D. Lin, J. Zhao, Z. Lu, Y. Liu, C. Liu, Y. Lu, H. Wang, K. Yan, X. Tao, Y. Cui, Composite lithium metal anode by melt infusion of lithium into a 3D conducting scaffold with lithiophilic coating. Proc. Natl. Acad. Sci. U.S.A. 113, 2862–2867 (2016). \n15. D. Lin, Y. Liu, Z. Liang, H.-W. Lee, J. Sun, H. Wang, K. Yan, J. Xie, Y. Cui, Layered reduced graphene oxide with nanoscale interlayer gaps as a stable host for lithium metal anodes. Nat. Nanotechnol. 11, 626–632 (2016). \n16. Y. Liu, D. Lin, Z. Liang, J. Zhao, K. Yan, Y. Cui, Lithium-coated polymeric matrix as a minimum volume-change and dendrite-free lithium metal anode. Nat. Commun. 7, 10992 (2016). \n17. C.-P. Yang, Y.-X. Yin, S.-F. Zhang, N.-W. Li, Y.-G. Guo, Accommodating lithium into 3D current collectors with a submicron skeleton towards long-life lithium metal anodes. Nat. Commun. 6, 8058 (2015). \n18. A. C. Luntz, J. Voss, K. Reuter, Interfacial challenges in solid-state Li ion batteries. J. Phys. Chem. Lett. 6, 4599–4604 (2015). \n19. J. Li, C. Ma, M. Chi, C. Liang, N. J. Dudney, Solid electrolyte: The key for high-voltage lithium batteries. Adv. Energy Mater. 5, 1401408 (2015). \n20. Y. Wang, W. Davidson Richards, S. P. Ong, L. J. Miara, J. Chul Kim, Y. Mo, G. Ceder, Design principles for solid-state lithium superionic conductors. Nat. Mater. 14, 1026–1031 (2015). \n21. K. K. Fu, Y. Gong, J. Dai, A. Gong, X. Han, Y. Yao, C. Wang, Y. Wang, Y. Chen, C. Yan, Y. Li, E. D. Wachsman, L. Hu, Flexible, solid-state, ion-conducting membrane with 3D garnet nanofiber networks for lithium batteries. Proc. Natl. Acad. Sci. U.S.A. 13, 7094–7099 (2016). \n22. Y. Kato, S. Hori, T. Saito, K. Suzuki, M. Hirayama, A. Mitsui, M. Yonemura, H. Iba, R. Kanno, High-power all-solid-state batteries using sulfide superionic conductors. Nat. Energy 1, 16030 (2016). \n23. W. D. Richards, L. J. Miara, Y. Wang, J. C. Kim, G. Ceder, Interface stability in solid-state batteries. Chem. Mater. 28, 266–273 (2016). \n24. J. F. M. Oudenhoven, L. Baggetto, P. H. L. Notten, All-solid-state lithium-ion microbatteries: A review of various three-dimensional concepts. Adv. Energy Mater. 1, 10–33 (2011). \n25. J. G. Kim, B. Son, S. Mukherjee, N. Schuppert, A. Bates, O. Kwon, M. J. Choi, H. Y. Chung, S. Park, A review of lithium and non-lithium based solid state batteries. J. Power Sources 282, 299–322 (2015). \n26. V. Thangadurai, S. Narayanan, D. Pinzaru, Garnet-type solid-state fast Li ion conductors for Li batteries: Critical review. Chem. Soc. Rev. 43, 4714–4727 (2014). \n27. Y. Zhu, X. He, Y. Mo, Origin of outstanding stability in the lithium solid electrolyte materials: Insights from thermodynamic analyses based on first-principles calculations. ACS Appl. Mater. Interfaces 7, 23685–23693 (2015). \n28. Y. Zhu, X. He, Y. Mo, First principles study on electrochemical and chemical stability of the solid electrolyte-electrode interfaces in all-solid-state Li-ion batteries. J. Mater. Chem. A 4, 3253–3266 (2015). \n29. F. Han, Y. Zhu, X. He, Y. Mo, C. Wang, Electrochemical stability of $\\mathsf{L i}_{10}\\mathsf{G e P}_{2}\\mathsf{S}_{12}$ and $\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}$ solid electrolytes. Adv. Energy Mater. 6, 1501590 (2016). \n30. J. B. Bates, N. J. Dudney, G. R. Gruzalski, R. A. Zuhr, A. Choudhury, C. F. Luck, Electrical properties of amorphous lithium electrolyte thin films. Solid State Ion. 53–56, 647–654 (1992). \n31. T. Thompson, A. Sharafi, M. D. Johannes, A. Huq, J. L. Allen, J. Wolfenstine, J. Sakamoto, A tale of two sites: On defining the carrier concentration in garnet-based ionic conductors for advanced Li batteries. Adv. Energy Mater. 5, 1500096 (2015). \n32. L. Cheng, E. J. Crumlin, W. Chen, R. Qiao, H. Hou, S. Franz Lux, V. Zorba, R. Russo, R. Kostecki, Z. Liu, K. Persson, W. Yang, J. Cabana, T. Richardson, G. Chen, M. Doeff, The origin of high electrolyte-electrode interfacial resistances in lithium cells containing garnet type solid electrolytes. Phys. Chem. Chem. Phys. 16, 18294–18300 (2014). \n33. M. Kotobuki, H. Munakata, K. Kanamura, Y. Sato, T. Yoshida, Compatibility of $\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}$ solid electrolyte to all-solid-state battery using Li metal anode. J. Electrochem. Soc. 157, A1076–A1079 (2010). \n34. H. Buschmann, J. Dölle, S. Berendts, A. Kuhn, P. Bottke, M. Wilkening, P. Heitjans, A. Senyshyn, H. Ehrenberg, A. Lotnyk, V. Duppel, L. Kienle, J. Janek, Structure and dynamics of the fast lithium ion conductor $\"\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}{}^{\\prime\\prime}$ . Phys. Chem. Chem. Phys. 13, 19378–19392 (2011). \n35. L. Cheng, W. Chen, M. Kunz, K. Persson, N. Tamura, G. Chen, M. Doeff, Effect of surface microstructure on electrochemical performance of garnet solid electrolytes. ACS Appl. Mater. Interfaces 7, 2073–2081 (2015). \n36. M. R. Busche, T. Drossel, T. Leichtweiss, D. A. Weber, M. Falk, M. Schneider, M.-L. Reich, H. Sommer, P. Adelhelm, J. Janek, Dynamic formation of a solid-liquid electrolyte interphase and its consequences for hybrid-battery concepts. Nat. Chem. 8, 426–434 (2016). \n37. X. Yu, Z. Bi, F. Zhao, A. Manthiram, Hybrid lithium–sulfur batteries with a solid electrolyte membrane and lithium polysulfide catholyte. ACS Appl. Mater. Interfaces 7, 16625–16631 (2015). \n38. F. Sagane, T. Abe, Y. Iriyama, Z. Ogumi, ${\\mathsf{L i}}^{+}$ and ${\\mathsf{N a}}^{+}$ transfer through interfaces between inorganic solid electrolytes and polymer or liquid electrolytes. J. Power Sources 146, 749–752 (2005). \n39. Y. Ishihara, K. Miyazaki, T. Fukutsuka, T. Abe, Kinetics of lithium-ion transfer at the interface between $\\mathsf{L i}_{4}\\mathsf{T i}_{5}\\mathsf{O}_{12}$ thin films and organic electrolytes. J. Phys. Chem. C 3, 83–86 (2014). \n40. H. Kitaura, H. Zhou, All-solid-state lithium-oxygen battery with high safety in wide ambient temperature range. Sci. Rep. 5, 13271 (2015). \n41. L. Wang, Y. Wang, Y. Xia, A high performance lithium-ion sulfur battery based on a $\\mathsf{L i}_{2}\\mathsf{S}$ cathode using a dual-phase electrolyte. Energy Environ. Sci. 8, 1551–1558 (2015). \n42. F. Sagane, T. Abe, Z. Ogumi, ${\\mathfrak{L}}^{+}$ -ion transfer through the interface between ${\\mathsf{L i}}^{+}$ -ion conductive ceramic electrolyte and ${\\mathsf{L i}}^{+}$ -ion-concentrated propylene carbonate solution. J. Phys. Chem. C 113, 20135–20138 (2009). \n43. Q. Wang, J. Jin, X. Wu, G. Ma, J. Yang, Z. Wen, A shuttle effect free lithium sulfur battery based on a hybrid electrolyte. Phys. Chem. Chem. Phys. 16, 21225–21229 (2014). \n44. X. Yu, Z. Bi, F. Zhao, A. Manthiram, Polysulfide-shuttle control in lithium-sulfur batteries with a chemically/electrochemically compatible NaSICON-type solid electrolyte. Adv. Energy Mater. 6, 1601392 (2016). \n45. Y. Kihira, S. Ohta, H. Imagawa, T. Asaoka, Effect of simultaneous substitution of alkali earth metals and Nb in $\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}$ on lithium-ion conductivity. ECS Electrochem. Lett. 2, A56–A59 (2013). \n46. R. Murugan, V. Thangadurai, W. Weppner, Fast lithium ion conduction in garnet-type $\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}$ . Angew. Chem. Int. Ed. 46, 7778–7781 (2007). \n47. Y. Li, Z. Wang, C. Li, Y. Cao, X. Guo, Densification and ionic-conduction improvement of lithium garnet solid electrolytes by flowing oxygen sintering. J. Power Sources 248, 642–646 (2014). \n48. M. M. Ahmad, M. M. Al-Quaimi, Origin of the enhanced ${\\mathsf{L}}{\\mathsf{i}}^{+}$ ionic conductivity in $\\mathsf{G d}^{+3}$ substituted $\\mathsf{L i}_{5+2x}\\mathsf{L a}_{3}\\mathsf{N b}_{2-x}\\mathsf{G d}_{x}\\mathsf{O}_{12}$ lithium conducting garnets. Phys. Chem. Chem. Phys. 17, 16007–16014 (2015). \n49. A. Sharafi, H. M. Meyer, J. Nanda, J. Wolfenstine, J. Sakamoto, Characterizing the Li– $\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}$ interface stability and kinetics as a function of temperature and current density. J. Power Sources 302, 135–139 (2016). \n50. R. Kanno, M. Murayama, T. Inada, T. Kobayashi, K. Sakamoto, N. Sonoyama, A. Yamada, S. Kondo, A self-assembled breathing interface for all-solid-state ceramic lithium batteries. Electrochem. Solid State Lett. 7, A455–A458 (2004). \n51. J. van den Broek, S. Afyon, J. L. M. Rupp, Interface-engineered all-solid-state li-ion batteries based on garnet-type fast ${\\mathsf{L i}}^{+}$ conductors. Adv. Energy Mater. 6, 1600736 (2016). \n52. L. J. Miara, W. D. Richards, Y. E. Wang, G. Ceder, First-principles studies on cation dopants and electrolyte|cathode interphases for lithium garnets. Chem. Mater. 27, 4040–4047 (2015). \n53. A. Jain, S. Ping Ong, G. Hautier, W. Chen, W. Davidson Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, K. A. Persson, Commentary: The materials project: A materials genome approach to accelerating materials innovation. APL Mater. 1, 11002 (2013). \n54. S. P. Ong, L. Wang, B. Kang, G. Ceder, Li−Fe− $\\cdot\\mathsf{P}{-}\\mathsf{O}_{2}$ phase diagram from first principles calculations. Chem. Mater. 20, 1798–1807 (2008). \n\nAcknowledgments: We acknowledge the support of the Maryland NanoCenter and its FabLab and NISPLab. Funding: This work was supported by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (contract #DEEE0006860). Author contributions: K.F. and Y.G. designed the experiment and wrote the paper. Y.Z. conducted the computational work. B.L., S.X., Y.Y., W.L., C.W., S.D.L., J.D., and Y.C. helped to conduct the experimental work and analyze the results. Y.M., E.W., and L.H. directed this work and revised the manuscript. \n\nCompeting interests: L.H., E.W., Y.G., K.F., and C.W. applied for a patent application (62/329846) titled “Engineered interface of solid state electrolyte anode with Li-metal alloys towards solidstate batteries” to the United States Patents and Trademark Office. All authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 19 July 2016 \nAccepted 14 February 2017 \nPublished 7 April 2017 \n10.1126/sciadv.1601659 \n\nCitation: K. Fu, Y. Gong, B. Liu, Y. Zhu, S. Xu, Y. Yao, W. Luo, C. Wang, S. D. Lacey, J. Dai, Y. Chen, Y. Mo, E. Wachsman, L. Hu, Toward garnet electrolyte–based Li metal batteries: An ultrathin, highly effective, artificial solid-state electrolyte/metallic Li interface. Sci. Adv. 3, e1601659 (2017). \n\n# ScienceAdvances \n\n# Toward garnet electrolyte−based Li metal batteries: An ultrathin, highly effective, artificial solid-state electrolyte/metallic Li interface \n\nKun (Kelvin) Fu, Yunhui Gong, Boyang Liu, Yizhou Zhu, Shaomao Xu, Yonggang Yao, Wei Luo, Chengwei Wang, Steven D Lacey, Jiaqi Dai, Yanan Chen, Yifei Mo, Eric Wachsman and Liangbing Hu \n\nSci Adv 3 (4), e1601659. DOI: 10.1126/sciadv.1601659 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nhttp://advances.sciencemag.org/content/suppl/2017/04/03/3.4.e1601659.DC1 \n\nREFERENCES \n\nThis article cites 54 articles, 3 of which you can access for free http://advances.sciencemag.org/content/3/4/e1601659#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1021_acs.jpclett.6b02682", + "DOI": "10.1021/acs.jpclett.6b02682", + "DOI Link": "http://dx.doi.org/10.1021/acs.jpclett.6b02682", + "Relative Dir Path": "mds/10.1021_acs.jpclett.6b02682", + "Article Title": "Cs2InAgCl6: A New Lead-Free Halide Double Perovskite with Direct Band Gap", + "Authors": "Volonakis, G; Haghighirad, AA; Milot, RL; Sio, WH; Filip, MR; Wenger, B; Johnston, MB; Herz, LM; Snaith, HJ; Giustino, F", + "Source Title": "JOURNAL OF PHYSICAL CHEMISTRY LETTERS", + "Abstract": "A(2)BB'X-6 halide double perovskites based on bismuth and silver have recently been proposed as potential environmentally friendly alternatives to lead-based hybrid halide perovskites. In particular, Cs2BiAgX6 (X = Cl, Br) have been synthesized and found to exhibit band gaps in the visible range. However, the band gaps of these compounds are indirect, which is not ideal for applications in thin film photovoltaics. Here, we propose a new class of halide double perovskites, where the B3+ and B+ cations are In3+ and Ag+, respectively. Our first-principles calculations indicate that the hypothetical compounds Cs2InAgX6 (X = Cl, Br, I) should exhibit direct band gaps between the visible (I) and the ultraviolet (Cl). Based on these predictions, we attempt to synthesize Cs2InAgCl6 and Cs2InAgBr6, and we succeed to form the hitherto unknown double perovskite Cs2InAgCl6. X-ray diffraction yields a double perovskite structure with space group Fm3m. The measured band gap is 3.3 eV, and the compound is found to be photosensitive and turns reversibly from white to orange under ultraviolet illumination. We also perform an empirical analysis of the stability of Cs2InAgX6 and their mixed halides based on Goldschmidts rules, and we find that it should also be possible to form Cs2InAg(Cl1xBrx)(6) for x < 1. The synthesis of mixed halides will open the way to the development of lead-free double perovskites with direct and tunable band gaps.", + "Times Cited, WoS Core": 839, + "Times Cited, All Databases": 887, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000394484100011", + "Markdown": "# $\\mathbf{Cs}_{2}\\mathbf{ln}\\mathbf{AgCl}_{6}$ : A New Lead-Free Halide Double Perovskite with Direct Band Gap \n\nGeorge Volonakis,† Amir Abbas Haghighirad,‡ Rebecca L. Milot,‡ Weng H. Sio,† Marina R. Filip,† Bernard Wenger,‡ Michael B. Johnston,‡ Laura M. Herz,‡ Henry J. Snaith,‡ and Feliciano Giustino\\*,† †Department of Materials, University of Oxford, Parks Road OX1 3PH, Oxford, United Kingdom ‡Department of Physics, Clarendon Laboratory, University of Oxford, Parks Road, Oxford OX1 3PU, United Kingdom \n\nSupporting Information \n\nABSTRACT: $\\mathrm{A}_{2}\\mathrm{BB^{\\prime}X}_{6}$ halide double perovskites based on bismuth and silver have recently been proposed as potential environmentally friendly alternatives to lead-based hybrid halide perovskites. In particular, $\\mathrm{Cs}_{2}\\mathrm{BiAgX}_{6}$ ( $\\mathrm{{\\overset{\\triangledown}{X}=C l}},$ , Br) have been synthesized and found to exhibit band gaps in the visible range. However, the band gaps of these compounds are indirect, which is not ideal for applications in thin film photovoltaics. Here, we propose a new class of halide double perovskites, where the $\\mathbf{B}^{3+}$ and $\\mathbf{B}^{+}$ cations are $\\mathrm{In}^{3+}$ and ${\\bf A}{\\bf g}^{+}.$ , respectively. Our first-principles calculations indicate that the hypothetical compounds $\\mathrm{Cs}_{2}\\mathrm{InAg}\\mathrm{X}_{6}$ 1 $\\mathrm{{\\ddot{X}=C l}},$ , Br, I) should exhibit direct band gaps between the visible (I) and the ultraviolet (Cl). Based on these predictions, we attempt to synthesize $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{InAgBr}_{6},$ and we succeed to form the hitherto unknown double perovskite $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ . X-ray diffraction yields a double perovskite structure with space group $F m\\overline{{3}}\\dot{m}$ . The measured band gap is $3.3~\\mathrm{eV}_{\\cdot}$ , and the compound is found to be photosensitive and turns reversibly from white to orange under ultraviolet illumination. We also perform an empirical analysis of the stability of $\\mathrm{Cs}_{2}\\mathrm{InAg}\\mathrm{X}_{6}$ and their mixed halides based on Goldschmidt’s rules, and we find that it should also be possible to form $\\mathrm{Cs}_{2}\\mathrm{InAg}(\\mathrm{Cl}_{1-x}\\mathrm{Br}_{x})_{6}$ for $x<1$ . The synthesis of mixed halides will open the way to the development of lead-free double perovskites with direct and tunable band gaps. \n\n![](images/cacf491c0465c60dd1904959a6173ea9a4e5465102db24ff303647df3d37c9c2.jpg) \n\nD uring the last four yfiears, Pb-based halide perovskites have achieving record power conversion efficiencies above $22\\%$ , and surpassing polycrystalline and thin-film silicon photovoltaics (PV).1−4 While the efficiency of these materials improves steadily, there are two remaining challenges that need to be addressed in order to use perovskite solar cells for electricity production, namely the compound stability and the presence of lead.5 On the front of $\\mathrm{Pb}$ replacement, several lead-free perovskites and perovskite-derivatives have been proposed during the past two years as potential substitutes for $\\mathbf{MAPbI}_{3}$ $(\\mathrm{MA}{\\mathrm{\\overline{{{\\Omega}}}}}={\\mathrm{CH}}_{3}{\\mathrm{NH}}_{3}),$ 6 including vacancy-ordered double perovskites, cation-ordered double perovskites (also known as elpasolites), and two-dimensional perovskites.7−17 Among these compounds, Pb-free halide double perovskites based on Bi and $\\mathbf{Ag}$ were recently proposed as stable and environmentally friendly alternatives to $\\mathbf{\\dot{MAPbI}}_{3}$ .12−15 While these Bi/ $\\mathbf{A}_{\\mathbf{g}}$ double perovskites exhibit band gaps in the visible $\\operatorname{\\from}1.9$ to $2.2\\ \\mathrm{eV}^{1\\bar{5}}$ ), the gaps are indirect, which is not ideal for thin film PV applications. In fact, indirect band gaps imply weak oscillator strengths for optical absorption and for radiative recombination, therefore indirect semiconductors such as silicon need a much thicker absorber layer, which can be problematic if charge carriers mobilities are low. In order to circumvent this limitation, in this work we develop a new class of $\\mathrm{Pb}$ -free halide double perovskites, which exhibit direct band gaps. We first use available databases and first-principles calculations to identify double perovskites with direct band gaps, and then we synthesize and characterize the new In-based compound $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}.$ X-ray diffraction (XRD) indicates a double perovskite structure with space group $F m\\overline{{3}}m$ at room temperature, with a direct band gap of $3.3~\\mathrm{eV}$ \n\nThe starting point of our investigation is the recent work on $\\mathrm{Cs}_{2}\\mathrm{BiAgCl}_{6}$ by some of us.12 In that work we succeeded in synthesizing the new double perovskite $\\mathrm{Cs}_{2}\\mathrm{BiAgCl}_{6}$ by following the well-known reaction route for making $\\mathrm{Cs}_{2}\\mathrm{BiNaCl}_{6}\\mathrm{}_{}^{18}$ and by replacing the $\\mathrm{\\DeltaNaCl}$ precursor by $\\mathrm{\\sf~AgCl.}$ The successful replacement of Na by $\\mathbf{Ag}$ can be attributed to the close match between the ionic radii of ${{\\ N}_{\\mathrm{{a}}}}^{+}$ (1.02 Å) and of ${\\bf A}{\\bf g}^{+}$ (1.15 Å). Motivated by this observation, here we set to discover new halide double perovskites containing Ag. To this aim we search for known halide elpasolites containing ${\\mathbf{N}}{\\mathbf{a}}^{+}$ as the ${\\bf{B}}^{+}$ cation. We consider data from the Materials Project (www.materialsproject.org), the International Crystal Structure Database (ICSD), and literature reviews.18−21 We find 42 elpasolites with composition $\\mathrm{Cs_{2}B^{3+}N a X}_{6},\\mathrm{X=Cl}_{\\mathrm{\\ell}}$ , Br, I. In 30 of these compounds the $\\mathbf{B}^{3+}$ cation is a lanthanide or actinide; in 7 compounds we find transition metals with small ionic radii $\\left(<0.9\\mathring\\mathrm{A}\\right)$ , namely, Sc, Ti, Y, and Fe; and 5 compounds contain Bi, Sb, Tl, or In. Lanthanides, actinides and transition metals pose a challenge to computational predictions based on density functional theory (DFT), therefore we leave them aside for future work. Bi and Sb double perovskites were extensively discussed recently.12 The incorporation of Tl in halide double perovskites was also proposed;22 however, this element is highly toxic and hence unsuitable for optoelectronic applications. Indium, on the other hand, is a common element in the optoelectronic industry, for example it is used to make transparent conductors in the form of tin doped indium oxide (ITO). Two In/Na-based halide double perovskites have been reported so far, $\\mathrm{Cs}_{2}\\mathrm{InNaCl}_{6}^{19,20}$ and $\\mathrm{Cs}_{2}\\mathrm{InNaBr}_{6}$ .20 Following this observation, we proceed to assess the structural, electronic, and optical properties of the hypothetical compounds $\\mathrm{Cs_{2}I n A g X}_{6}$ with $\\mathrm{X}=\\mathrm{Cl},$ Br, I using DFT calculations. \n\nAs a structural template for our calculations we use the facecentered cubic $F m\\overline{{3}}\\overline{{m}}$ elpasolite unit cell, which contains one $\\mathrm{B}^{\\mathrm{+}}\\mathrm{X}_{6}$ and one $\\mathbf{B}^{3+}\\mathbf{X}_{6}$ octahedra.12,14 The resulting atomistic model consists of $\\mathrm{InX}_{6}$ and $\\mathrm{AgX}_{6}$ octahedra which alternate along the [100], [010], and [001] directions, as shown in Figure 1a. This rock-salt ordering of the B-site cations is also found in many oxide double perovskites. After optimizing the structure within the local density approximation (LDA) to DFT (see Computational Methods), we obtain the lattice constants a $\\dot{{\\bf\\Phi}}=10.20\\dot{{\\bf\\Phi}}\\dot{{\\bf A}},$ $10.74\\mathrm{~\\AA},$ and $11.52\\mathrm{~\\AA~}$ for $\\mathrm{\\boldmath~X~}=\\mathrm{\\boldmath~Cl~},$ Br, and I, respectively. The calculated lattice constants are slightly smaller than what we found for the corresponding Bi-based double perovskites $\\mathrm{10.50{-}11.76~\\AA},$ .12 This can be attributed to the smaller size of $\\mathrm{In}^{3+}$ as compared to $\\mathrm{Bi}^{3+}$ . Despite the presence of two different B-site cations, within DFT/LDA the $\\mathrm{BX}_{6}$ octahedra are of similar size; for example in the case of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ the $\\mathrm{In-Cl}$ and $\\scriptstyle\\mathbf{Ag-Cl}$ bond lengths are 2.50 and $2.59\\mathrm{~\\AA~},$ respectively. Employing higher level nonlocal functionals for the structural optimization yields a slightly larger lattice constant, $10.62\\mathrm{~\\AA~}$ for $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6},$ and bond lengths of 2.54 and $2.77\\mathrm{~\\AA~}$ for $_\\mathrm{In-Cl}$ and $\\mathrm{Ag-Cl},$ respectively. All parameters related to structural optimization with different functionals are included in Table S1 of the Supporting Information. \n\n![](images/502772b3daa62d956df67790565c2790059f7e9b461453d1e3d1db7fc221c7bf.jpg) \nFigure 1. Atomistic model and octahedral factors of the In-based halide double perovskites $\\mathrm{Cs}_{2}\\mathrm{InAg}X_{6}$ $\\mathrm{{\\cdot}}\\mathrm{{X}}=\\mathrm{{Cl}},$ , Br, I): (a) Ball-and-stick model of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6},$ with In atoms in red and $\\mathbf{A}\\mathbf{g}$ atoms in gray. The green spheres indicate $\\mathrm{cl},$ and the purple spheres in the center of each cavity are $C s$ atoms. The primitive unit cell contains one $\\mathrm{InCl}_{6}$ and one ${\\mathrm{AgCl}}_{6}$ octahedra in a face-centered cubic structure, with space group $F m\\overline{{3}}m$ ; here we show the conventional cubic cell. (b) Octahedral factor $\\mu=R_{\\mathrm{B}}/R_{\\mathrm{X}}$ corresponding to $\\mathrm{AgX}_{6}$ octahedra (orange dots), and to $\\mathrm{InX}_{6}$ octahedra (blue dots), for solid solutions of Cl, Br, and I. The perovskite structure is expected to be unstable for values of the octahedral factor below $\\mu=\\sqrt{2}\\:-\\:1=0.41_{.}$ , as indicated by the red horizontal line.23 \n\nA complete study of the stability of these hypothetical compounds would require the calculation of the phonon dispersion relations (dynamical stability) and of the quaternary convex hulls (thermodynamic stability).24 Since these calculations are demanding, we perform a preliminary assessment of compound stability using Goldschmidt’s empirical criteria. According to these criteria, one can assign a perovskite with formula $\\mathrm{\\bfABX}_{3}$ two parameters called the tolerance factor and the octahedral factor. The tolerance factor is defined as $t={\\left(R_{\\mathrm{A}}+R_{\\mathrm{X}}\\right)}/{\\sqrt{2}}{\\left(R_{\\mathrm{B}}+R_{\\mathrm{X}}\\right)},$ with $R_{\\mathrm{{A}}},R_{\\mathrm{{B}}},$ and $R_{\\mathrm{X}}$ being the ionic radii of the elements in a $\\mathrm{ABX}_{3}$ perovskite; stable structures usually correspond to $0.750.41$ . In order to evaluate these parameters, we employ the Shannon ionic radii. Since we have double perovskites, and therefore different radii for the ${\\bf{B}}^{+}$ and $\\mathbf{B}^{3+}$ sites, as a first attempt we consider for $R_{\\mathrm{B}}$ the average between the radii of $\\mathrm{In}^{3+}$ and ${\\mathbf{A}}{\\mathbf{g}}^{+}$ . For $\\mathrm{Cs}_{2}\\mathrm{InAg}\\mathrm{X}_{6}$ with $\\mathrm{\\DeltaX=Cl^{-}}$ , $\\mathrm{Br}^{-}$ , $\\mathrm{I}^{-}$ we obtain $(\\mu,\\ t)\\ =\\ (0.54,\\ 0.94),$ (0.50,0.93), and (0.44,0.91), respectively. All these parameters fall within the range of stability of standard halide perovskites,23 therefore they are not very informative. A more stringent test can be obtained by considering the limiting cases where the structures were composed entirely of $\\mathrm{InX}_{6}$ octahedra or of $\\mathrm{AgX}_{6}$ octahedra. In this scenario, we find that the tolerance factor is within the stability region for all compounds $\\left(0.86
CsInAgCl6CsBiAgCl6Cs2BiAgBr6
HSE2.1-2.62.11.7
PBEO2.9-3.32.72.3
exp.3.32.2-2.81.9-2.2
\n\nare shown in Figure S2 of the Supporting Information. The valence band top of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ has no occupied In-s orbitals. \n\nThis is closely linked with the direct character of the band gap of this compound. In fact, in the related $\\mathrm{\\Bi/Ag}$ elpasolite $\\mathrm{Cs}_{2}\\mathrm{BiAgCl}_{6}\\mathrm{,}^{1\\dot{2},15}$ the Bi s states at the top of the valence band interact with the directional $\\log\\ d$ states along the [100] direction; this interaction pushes the valence band top to the $X$ point and leads to an indirect band gap in $\\mathrm{Cs}_{2}\\mathrm{BiAgCl}_{6}$ . To confirm this point, we artificially removed the Bi s states from the top of the valence band of $\\mathrm{Cs}_{2}\\mathrm{BiAgCl}_{6},$ using a fictitious Hubbard $U$ correction of $10~\\mathrm{eV}$ . The resulting band structure, shown in Supporting Figure S3, exhibits a direct gap at $\\Gamma,$ as in the case of the present compound $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ . \n\nThe electron effective mass calculated for $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ is $m_{\\mathrm{e}}^{*}$ $=0.29~m_{\\mathrm{e}}$ $\\cdot m_{\\mathrm{e}}$ is the free electron mass); the hole effective mass is $m_{\\mathrm{h}}^{*}=0.28~m_{\\mathrm{e}}$ . In the calculation of the hole effective mass, we have not considered the nondispersive band, which can be seen in Figure 2a between $\\Gamma$ and X. This flat band originates from the hybridization of $\\mathrm{Cl}{-}3p_{x,y}$ states and $4d_{x^{2}-y^{2}}$ states of In and $\\mathbf{Ag},$ which leads to a two-dimensional wave function confined within the equatorial (001) plane (wave function labeled as “iii” in Figure 2b). This flat band will likely prevent carrier transport along the six equivalent $X$ wavevectors, and possibly favor the formation of deep defects. \n\n![](images/66e472d22336488c2f0430cc9e0bd487e8f66841af442b4ba6e0939686eae118.jpg) \nFigure 3. Structural and optical characterization of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ : (a) Measured powder XRD pattern for the as-synthesized $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ (top), and the XRD pattern calculated from the atomistic model optimized using DFT/LDA (bottom). (b) Measured UV−vis absorbance showing the band gap of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ at $380~\\mathrm{nm}$ and the defect-related features at $585~\\mathrm{nm}$ as discussed in the text. The straight lines are a guide to the eye. The insets shows $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ under ambient light and under UV illumination. (c) Normalized PL spectrum recorded as a function of time following excitation at 405 nm. The vertical line indicates the center wavelength of the PL at zero time, defined by the arrival time of the excitation pulse on the sample. (d) Time-resolved PL intensity recorded for a powder sample of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ . The fast and slow components of the PL decay are indicated on the plot. The fast (slow) component was fit with a stretched exponential (monoexponential) function, and $\\tau$ represents the average lifetime. \n\nSince we expect $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ to be stable, and to exhibit a direct band gap as well as small and balanced effective masses, we proceed to attempt the synthesis of this compound. We prepare samples of $\\mathrm{Cs}_{2}\\mathrm{BiAgCl}_{6}$ by precipitation from an acidic solution of hydrochloric acid. A mixture of a 1 mmol ${\\mathrm{InCl}}_{3}$ (Sigma-Aldrich, $99.99\\%$ ) and $\\mathsf{A g C l}$ (Sigma-Aldrich, $99\\%$ ) is first dissolved in 5 mL 10 M HCl. Then $2\\mathrm{\\mmol}$ of CsCl (Sigma-Aldrich, $99.9\\%$ ) are added and the solution is heated to $11\\bar{5}^{\\circ}{\\mathrm{C}}.$ A white precipitate forms immediately after adding CsCl. We leave the hot solution for $30~\\mathrm{min}$ under gentle stirring, to ensure a complete reaction before filtering. We wash the resulting solid with ethanol and dry in a furnace overnight at $100^{\\circ}\\mathrm{C}$ . The as-formed powder appears stable under ambient conditions. In Figure 3a we show the measured X-ray diffraction (XRD) pattern of this powder. The refined lattice parameter is $10.47\\mathrm{~\\bar{A},}$ only $2.6\\%$ larger than in our DFT/LDA calculation. This is in line with the typical underestimation of lattice parameters by DFT/LDA in the range of $1-2\\%$ . The refined structural parameters are provided in Table S2 of the Supporting Information. In Figure 3a we include the powder diffraction pattern calculated from our optimized DFT/LDA structure. We can see that all the peaks in the calculation and in the XRD measurement match very closely; there is a small offset between the two patterns, which is related to the difference in the lattice parameters. To confirm this point, we reoptimize the theoretical model using the experimental lattice constant; in this case we find no discernible difference between the two patterns, as shown in Figure S4a of the Supporting Information. This comparison indicates that the synthesized compound is a double perovskite or elpasolite, within a $F m\\overline{{3}}m$ space group. We also measured the XRD pattern after exposing the samples to ambient conditions for more than three months, as shown in Figure S5 of the Supporting Information. The compound appears to be very stable with no structural decomposition observed. While we can successfully synthesize $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6},$ our preliminary attempts at making the related bromide compound, $\\mathrm{Cs}_{2}\\mathrm{InAgBr}_{6},$ have been unsuccessful thus far. In fact, by following a similar route as above, with CsBr instead of $\\mathrm{CsCl}_{\\mathrm{\\ell}}$ , we obtain a pale yellow powder that does not match the elpasolite $F m\\overline{{3}}m$ crystal structure. \n\nIn order to investigate whether the In and $\\mathbf{Ag}$ cations are fully ordered, we have calculated the XRD pattern in three different scenarios: (1) using an ordered structure optimized within DFT/LDA, (2) using an ordered structure optimized with DFT/HSE, and (3) using the measured lattice parameter and a perovskite structure with $0.5\\ \\mathrm{In}$ and $0.5~\\mathrm{Ag}$ occupations on the Wyckoff sites. Scenarios (1) and (2) are meant to describe a fully ordered $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ crystal using DFT functionals that yield rather different $\\mathrm{In-Cl}$ and $\\mathrm{\\Ag-Cl}$ bond lengths (as shown in Table S1). These calculated XRD patterns are compared to experiment in Figure S6 of the Supporting Information. The main peaks associated with ordering effects are indicated by the green arrows in this figure. We find that the main peaks associated with ordering effects (indicated by the green arrows) are extremely weak even in the theoretical fully ordered structures. Furthermore, we see that in the HSE structure these peaks are slightly more visible than in the LDA structure. This effect is due to the more pronounced difference in bond lengths between $\\mathrm{In-Cl}$ and $\\mathrm{\\Ag-Cl}$ in the HSE structure (as seen in Table S1). In the fully disordered model the intensity of the ordering peaks is vanishing. The difference between the XRD patterns calculated for the ordered structures (Figure S6b and S6c) and the disordered structure (Figure S6d) are much smaller than our experimental resolution (Figure S6a). Therefore, in the case of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6},$ XRD is not sufficient to probe the nature of cation order/disorder. Given this uncertainty on the structure, we explored the effects of disorder on the electronic structure. To this aim we considered a virtual crystal approximation with the In and $\\mathbf{Ag}$ sites replaced by the pseudoatom $0.5\\ \\mathrm{In}+0.5$ Ag. As shown in Figure S7, the DFT/ HSE band structure of this disordered model is very close to that of the ordered model, with the same direct band gap at $\\Gamma$ . This demonstrates that our electronic structure analysis should be mostly insensitive to cation ordering. \n\nIn order to characterize the optical properties of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6},$ we measured the diffuse reflectance and applied the Kubelka− Munk theory (see Methods) to estimate the absorbance, and the time-resolved photoluminescence (PL) spectra. The Kubelka−Munk function $F(R)$ is shown in Figure 3b. We can clearly recognize the onset of absorption near $380\\ \\mathrm{nm}\\ (3.3\\ \\mathrm{eV})$ and further identify a second absorption feature at $585\\mathrm{nm}$ (2.1 eV). The full reflectance spectra is shown in Figure S8 of the Supporting Information. In Figure 3c we see a well-defined PL peak centered around $608~\\mathrm{{nm}}\\left(2.04~\\mathrm{{eV}}\\right)$ , with a FWHM of 120 nm $\\left(0.37~\\mathrm{eV}\\right)$ . This peak appears to redshift on a time scale of $100~\\mathrm{{ns}},$ , suggesting that subgap states are being filled on this time scale. \n\nA compound with the absorption onset and PL peak close to $2.1~\\mathrm{\\eV}$ should be colored orange and not white as the $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ powder. However, we have observed that under photoexcitation, the compound turns orange as shown in the insets of Figure 3b. This coloration might relate to local photoinduced electronic or structural changes. For example, the precursor compound $\\mathtt{A g C l}$ is a known photosensitive material, where the oxidation state of $\\mathbf{Ag}$ changes upon illumination. This photochromic behavior may be connected with the strong sensitivity of the electronic structure of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ to small changes in the $\\mathrm{\\Ag-Cl}$ and $\\mathrm{In-Cl}$ bond lengths, as shown in Table S1 of the Supporting Information. The process observed here is fully reversible and upon return to ambient light the sample becomes immediately white. The orange coloration is consistent with the optical absorption around $2.1~\\mathrm{eV}$ and the emission spectra shown in Figure $^{3\\mathrm{b},\\mathrm{c}}$ . Based on these observations, we propose that the measured absorption and emission around $2.1~\\mathrm{\\eV}$ might relate to (possibly photoinduced) defect states, and the actual band gap of the compound is at $3.3~\\mathrm{eV}$ \n\nIn Figure 3d we see that the time-resolved PL intensity of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ exhibits two time scales: a fast relaxation with a lifetime of 1 ns, followed by a very slow decay with a long lifetime of $6~\\mu s$ . This observation is consistent with timeresolved PL measurements on the related $\\mathrm{Cs}_{2}\\mathrm{BiAgX}_{6}$ $\\mathrm{\\nabla{X}=C l,}$ Br) double perovskites, which also exhibit two decay components with very different lifetimes.13 For completeness in Figure S4b of the Supporting Information, we show that the PL lifetime is insensitive to the intensity of the pump laser. Taken together, the PL redshift with time, and the fast initial PL decay component suggest that a tail of subgap defect states or energetic disorder is present. \n\n![](images/4d0324c6a580f13d0113fb73e562610ac1ef371c2059d63f42b8df370429cfea.jpg) \nFigure 4. Theoretical optical absorption coefficient and band gap of mixed halides: (a) Calculated absorption coefficient of the compound synthesized in this work, $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ (left, blue lines), and of the hypothetical compound $\\mathrm{Cs}_{2}\\mathrm{InAgBr}_{6}$ (right, blue lines). For comparison we show the theoretical absorption coefficients of silicon (purple), gallium arsenide (black), as calculated in ref 26, and $\\mathbf{MAPbI}_{3}$ (green) (unpublished results). (b) Calculated band gaps of hypothetical mixed-halide double perovskites $\\mathrm{Cs}_{2}\\mathrm{InAg}(\\mathrm{Cl}_{1-x-y}\\mathrm{Br}_{x}\\mathrm{I}_{y})_{6}$ within the HSE (left) and PBE0 (right) hybrid functional. The corners of the triangle correspond to $\\mathrm{Cs}_{2}\\mathrm{InAg}X_{6}$ with $\\mathrm{X}=\\mathrm{Cl},$ Br, I. \n\nWe now employ DFT to compare the ideal optical absorption spectrum of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{InAgBr}_{6}$ with the spectra calculated for the standard semiconductors Si and $\\dot{\\mathrm{GaAs}},^{26}$ and for $\\mathbf{MAPbI}_{3}$ (unpublished results). In Figure 4a we see that, while $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ is a direct-gap semiconductor, the absorption coefficient of the perfect crystal is considerably smaller than those of Si, GaAs, and $\\mathbf{MAPbI}_{3}$ throughout the visible spectrum. On the other hand, if we could synthesize an ideal crystal of the bromine compound, $\\mathrm{Cs}_{2}\\mathrm{InAgBr}_{6},$ we should obtain an absorption coefficient that is comparable to or even higher than that in silicon. \n\nIn view of developing more efficient absorbers based on the $\\mathrm{In/Ag}$ combination, we theoretically investigate the optical properties of mixed halide compounds. To this aim we consider the hypothetical solid solutions $\\mathrm{Cs}_{2}\\mathrm{InAg}(\\mathrm{Cl}_{1-x}\\mathrm{Br}_{x})_{6},$ $\\mathrm{Cs}_{2}\\mathrm{InAg}_{\\overline{{\\cdot}}}$ ${{\\left({\\operatorname{Br}_{1-x}}{\\bar{\\operatorname{I}}}_{x}\\right)}_{6}}$ and $\\mathrm{Cs}_{2}\\mathrm{InAg}(\\mathrm{Cl}_{1-x}\\mathrm{I}_{x})_{6}$ with $x=0.25$ , 0.50, and 0.75. To model mixed-halide double perovskites without inducing artificial ordering effects, we employ the virtual-crystal approximation (see Computational Methods). Figure 4b shows a ternary map of the band gap calculated for these mixes, as obtained by interpolating linearly from the above combinations. We report band gaps calculated using DFT/HSE and DFT/PBE0 for $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ . The band gaps of the mixed halide double perovskites are tunable within the visible spectrum. These results indicate that the $\\mathrm{In/Ag}$ halide double perovskites may be promising for applications in tandem solar cell architectures. \n\nIn summary, by combining first-principles calculations and experiments we discovered a novel direct band gap halide double perovskite, $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ . This new compound crystallizes in a double perovskite structure with space group $F m\\overline{{3}}m,$ , has a direct band gap at $\\Gamma$ of $3.3~\\mathrm{eV}$ . In addition, this new compound exhibits PL at around $2.1~\\mathrm{\\eV}$ and shows an interesting photochromic behavior whereby the color changes reversibly to orange under UV illumination. Our analysis indicates that by developing mixed halides $\\mathrm{Cs}_{2}\\mathrm{InAg}\\mathrm{X}_{6}$ with $\\mathbf{\\boldsymbol{X}}=\\mathbf{\\boldsymbol{C}}\\mathbf{\\boldsymbol{l}},$ , Br, and I, it should be possible to obtain good optical absorbers with tunable and direct band gaps. The existence of the related compound $\\mathrm{Cs}_{2}\\mathrm{InNaBr}_{6}$ (with Na in place of $\\mathrm{Ag}{\\dot{}}$ ) strongly suggests that it should be viable to synthesize also $\\mathrm{Cs}_{2}\\mathrm{InAgBr}_{6}$ . Overall, we expect that the exploration of mixed-halide double perovskites starting from $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ will offer new opportunities for developing environmentally friendly perovskite photovoltaics and optoelectronics. \n\n# COMPUTATIONAL METHODS \n\nStructural optimization was carried out within DFT using the Quantum ESPRESSO suite.27 Ultrasoft pseudopotentials28,29 were used to describe the electron−ion interaction, and exchange-correlation effects were taken into account within the LDA.30,31 The planewaves kinetic energy cutoffs were set to 35 and $280~\\mathrm{Ry}$ for the electronic wave functions and the charge density, respectively. The Brillouin zone was sampled using a $15~\\times~15~\\times~15$ unshifted grid. The thresholds for the convergence of forces and total energy were set to $10^{-3}~\\mathrm{Ry}$ and $10^{=4}$ Ry, respectively. In order to overcome the DFT band gap problem we employed hybrid functional calculations as implemented in the VASP code.32 We used the PBE0 functional33 and the HSE06 functional.34 In the latter case we set the screening parameter to $0.2\\mathring\\mathrm{A}^{-1}$ and we used a mixing of $25\\%$ of Fock exchange with $75\\%$ of PBE exchange. In the hybrid calculations we used the projector augmented wave method,35 with a $400~\\mathrm{eV}$ kinetic energy cutoff. In the hybrid calculations the Brillouin zone was sampled using a $6\\times6\\times6$ unshifted grid for Cl or Br. For the I-based compound, $\\mathrm{Cs}_{2}\\mathrm{InAgI}_{6},$ DFT/LDA yields a spurious band crossing and the resulting band structure is metallic. In this case, in order to perform hybrid calculations we sampled the Brillouin zone using a $2\\times2\\times2$ shifted grid. We verified the correctness of the results by repeating the same procedure for $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ . For the calculations of the optical absorption coefficients we used the YAMBO code36 within the random-phase approximation. In this case we used norm-conserving pseudopotentials37 (with kinetic energy cutoff of $120~\\mathrm{Ry}$ ), the $\\mathbf{\\mathrm{PBE}}^{38}$ generalized gradient approximation, and a dense Brillouin zone grid with $40\\times40\\times$ 40 points. In order to correct for the band gap underestimation in DFT/PBE, we used scissor corrections as obtained from our HSE/PBE0 calculations. The optical $f$ sum rule was maintained by scaling the oscillator strengths.39 The calculations based on the virtual-crystal approximation were performed by using the procedure of Bellaiche and Vanderbilt.40 \n\n# EXPERIMENTAL METHODS \n\nPowder XRD was performed using a Panalytical X’pert diffractometer $\\mathrm{(Cu\\mathrm{-}K}\\alpha_{\\mathrm{1}}$ radiation; $\\lambda\\ =\\ 154.05\\ \\mathrm{pm})$ at room temperature. Structural parameters were obtained by Rietveld refinement using the General Structural Analysis Software.41,42 A Varian Cary 300 UV−vis spectrophotometer with an integrating sphere was used to acquire diffuse reflectance. To estimate the visible light absorption spectrum, we apply the Kubelka−Munk theory to convert the diffuse reflectance in the $F(R)$ function, $F(R)\\stackrel{\\cdot}{=}(1-R)^{2}/2\\mathrm{R}=K/S,$ where $R$ is the absolute reflectance of the sample, $K$ is the molar absorption coefficient, and S is the scattering coefficient.Time-resolved PL spectra were recorded following laser excitation at $405\\ \\mathrm{nm},$ , at a repetition rate of $10~\\mathrm{MHz}$ (Picoquant, LDH-D-C-405M). The PL signal was collected and directed toward a grating monochromator (Princeton Instruments, SP-2558), and detected with a photon-counting detector (PDM series from MPD). \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpclett.6b02682. \n\nFigures of the molecular orbital diagram and projected density of states for $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6},$ XRD data of a sample exposed to ambient conditions for three months, measured reflectance and Kubelka−Munk function and additional figures relevant to the in-text discussions about spin−orbit coupling, and the octahedra ordering effects as well as tables showing the DFT structural parameters and calculated band gaps and Rietveld refinement of $\\mathrm{Cs}_{2}\\mathrm{InAgCl}_{6}$ (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Author \n\n$^{*}\\mathrm{E}$ -mail: feliciano.giustino@materials.ox.ac.uk; Phone: $(+44)$ 01865 272380. \n\n# ORCID \n\nGeorge Volonakis: 0000-0003-3047-2298 Michael B. Johnston: 0000-0002-0301-8033 Laura M. Herz: 0000-0001-9621-334X Feliciano Giustino: 0000-0001-9293-1176 \n\nNotes The authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThe authors are grateful to Marios Zacharias for sharing the calculated absorption coefficients of Si, GaAs, and $\\mathbf{MAPbI}_{3}$ . The research leading to these results has received funding from the Graphene Flagship (Horizon 2020 Grant No. 696656 - GrapheneCore1), the Leverhulme Trust (Grant RL-2012- 001), and the UK Engineering and Physical Sciences Research Council (Grant No. EP/J009857/1, EP/M020517/1 and EP/ L024667/1). The authors acknowledge the use of the University of Oxford Advanced Research Computing (ARC) facility (http://dx.doi.org/10.5281/zenodo.22558) and the ARCHER UK National Supercomputing Service under the “AMSEC” Leadership project and PRACE for awarding us access to the Dutch national supercomputer ‘Cartesius’. \n\n# REFERENCES \n\n(1) Xing, G.; Mathews, N.; Sun, S.; Lim, S. S.; Lam, Y. M.; Grätzel, M.; Mhaisalkar, S.; Sum, T. C. Long Range Balanced Electron-and Hole-Transport Lengths in Organic-Inorganic $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ . Science 2013, 342, 344. \n(2) Stranks, S. D.; Eperon, G. E.; Grancini, G.; Menelaou, C.; Alcocer, M. J. P.; Leijtens, T.; Herz, L. M.; Petrozza, A.; Snaith, H. J. Electron-Hole Diffusion Lengths Exceeding 1 Micrometer in an Organometal Trihalide Perovskite Absorber. Science 2013, 342, 341− 344. \n(3) Seo, J.; Noh, J. H.; Seok, S. I. Rational Strategies for Efficient Perovskite Solar Cells. Acc. Chem. Res. 2016, 49, 562−572. \n(4) Eperon, G. E.; et al. Perovskite-perovskite tandem photovoltaics with optimized bandgaps. Science 2016, 354, 861. \n(5) Green, M.; Ho-Baillie, A.; Snaith, H. J. The Emergence of Perovskite Solar Cells. Nat. Photonics 2014, 8, 506. \n(6) Giustino, F.; Snaith, H. J. Toward Lead-Free Perovskite Solar Cells. ACS Energy Letters 2016, 1, 1233−1240. \n(7) Stoumpos, C. C.; Malliakas, C. D.; Kanatzidis, M. G. Semiconducting Tin and Lead Iodide Perovskites with Organic Cations: Phase Transitions, High Mobilities, and Near-Infrared Photoluminescent Properties. Inorg. Chem. 2013, 52, 9019. \n(8) Noel, N.; Stranks, S. D.; Abate, A.; Wehrenfennig, C.; Guarnera, S.; Haghighirad, A.-A.; Sadhanala, A.; Eperon, G. E.; Pathak, S. K.; Johnston, M. B.; Petrozza, A.; Herz, L. M.; Snaith, H. J. Lead-Free Organic-Inorganic Tin Halide Perovskite for Photovoltaic Applications. Energy Environ. Sci. 2014, 7, 3061. \n(9) Saparov, B.; Hong, F.; Sun, J.-P.; Duan, H.-S.; Meng, W.; Cameron, S.; Hill, I. G.; Yan, Y.; Mitzi, D. B. Thin-Film Preparation and Characterization of $\\mathrm{Cs}_{3}\\mathrm{Sb}_{2}\\mathrm{I}_{9}$ : A Lead-Free Layered Perovskite Semiconductor. Chem. Mater. 2015, 27, 5622−5632. \n(10) Kim, Y.; Yang, Z.; Jain, A.; Voznyy, O.; Kim, G.-H.; Liu, M.; Quan, L. N.; GarcíadeArquer, F. P.; Comin, R.; Fan, J. Z.; Sargent, E. H. Pure Cubic-Phase Hybrid Iodobismuthates $\\mathrm{AgBi_{2}I_{7}}$ for Thin-Film Photovoltaics. Angew. Chem. 2016, 128, 9738−9742. \n(11) Xiao, Z.; Meng, W.; Mitzi, D. B.; Yan, Y. Crystal Structure of $\\mathrm{AgBi}_{2}\\mathrm{I}_{7}$ Thin Films. J. Phys. Chem. Lett. 2016, 7, 3903−3907. \n(12) Volonakis, G.; Filip, M. R.; Haghighirad, A. A.; Sakai, N.; Wenger, B.; Snaith, H. J.; Giustino, F. Lead-Free Halide Double Perovskites via Heterovalent Substitution of Noble Metals. J. Phys. Chem. Lett. 2016, 7, 1254−1259. \n(13) Slavney, A. H.; Hu, T.; Lindenberg, A. M.; Karunadasa, H. I. A Bismuth-Halide Double Perovskite with Long Carrier Recombination Lifetime for Photovoltaic Applications. J. Am. Chem. Soc. 2016, 138, 2138−2141. \n(14) McClure, E. T.; Ball, M. R.; Windl, W.; Woodward, P. M. $\\mathrm{Cs}_{2}\\mathrm{AgBiX}_{6}$ ( $\\mathrm{\\nabla{X}}=\\mathrm{Br},$ Cl) - New Visible Light Absorbing, Lead-Free Halide Perovskite Semiconductors. Chem. Mater. 2016, 28, 1348− 1354. \n(15) Filip, M. R.; Hillman, S.; Haghighirad, A. A.; Snaith, H. J.; Giustino, F. Band Gaps of the Lead-Free Halide Double Perovskites $\\mathrm{Cs}_{2}\\mathrm{BiAgCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{BiAgBr}_{6}$ from Theory and Experiment. J. Phys. Chem. Lett. 2016, 7, 2579−2585. \n(16) Milot, R. L.; Eperon, G. E.; Green, T.; Snaith, H. J.; Johnston, M. B.; Herz, L. M. Radiative Monomolecular Recombination Boosts Amplified Spontaneous Emission in $\\mathrm{HC}(\\mathrm{NH}2)2\\mathrm{SnI}3$ Perovskite Films. J. Phys. Chem. Lett. 2016, 7, 4178−4184. \n(17) Kaltzoglou, A.; Antoniadou, M.; Kontos, A. G.; Stoumpos, C. C.; Perganti, D.; Siranidi, E.; Raptis, V.; Trohidou, K.; Psycharis, V.; Kanatzidis, M. G.; Falaras, P. Optical-Vibrational Properties of the $\\mathrm{Cs2SnX}6$ $\\mathrm{\\DeltaX=Cl}$ , Br, I) Defect Perovskites and Hole-Transport Efficiency in Dye-Sensitized Solar Cells. J. Phys. Chem. C 2016, 120, 11777−11785. \n(18) Morrs, L. R.; Robinson, W. R. Crystal Structure of $\\mathrm{Cs}_{2}\\mathrm{BiNaCl}_{6}$ . Acta Crystallogr., Sect. B: Struct. Crystallogr. Cryst. Chem. 1972, 28, 653−654. \n(19) Morss, L. R.; Siegal, M.; Stenger, L.; Edelstein, N. Preparation of Cubic Chloro Complex Compounds of Trivalent Metals: $\\mathrm{Cs}_{2}\\mathrm{NAMCl}_{6}$ Inorg. Chem. 1970, 9, 1771−1775. \n(20) Meyer, G.; Gaebell, H. Halo-Elpasolites. IV. On BromoElpasolites $\\mathrm{Cs}_{2}\\mathrm{B}^{\\mathrm{I}}\\mathrm{M}^{\\mathrm{III}}\\mathrm{Br}_{6},$ $\\mathbf{B}^{\\mathrm{I}}=\\mathrm{Li}$ , ${\\bf N a};$ $\\mathbf{M}^{\\mathrm{III}^{-}}=S c$ , Y, La−Lu, In, V, Cr). Z. Naturforsch. B 1978, 33, 1476−1478. \n(21) Meyer, G. Halo-Elpasolites. VI. The First-Iodo-Elpasolites, $\\mathrm{CsB}^{I}\\mathbf{M}^{I I I}\\mathbf{I}_{6}$ $ ^{\\prime}\\mathrm{B}^{I}{=}\\mathrm{Li},\\ \\mathrm{Na},$ ). Z. Naturforsch. B 1980, 35, 268−276. \n(22) Giorgi, G.; Yamashita, K. Alternative, Lead-Free, Hybrid Organic-Inorganic Perovskites for Solar Applications: A DFT Analysis. Chem. Lett. 2015, 44, 826. \n(23) Li, C.; Lu, $\\mathrm{X.;}$ Ding, W.; Feng, L.; Gao, Y.; Guo, Z. Formability of $\\mathrm{ABX}_{3}$ $\\mathrm{\\boldmath~X=F,}$ , Cl, Br, I) Halide Perovskites. Acta Crystallogr., Sect. B: Struct. Sci. 2008, 64, 702−707. \n(24) Hautier, G.; Ong, S. P.; Jain, A.; Moore, C. J.; Ceder, G. Accuracy of Density Functional Theory in Predicting Formation Energies of Ternary Oxides from Binary Oxides and its Implication on Phase Stability. Phys. Rev. B: Condens. Matter Mater. Phys. 2012, 85, 155208. \n(25) Even, J.; Pedesseau, L.; Jancu, J.-M.; Katan, C. Importance of Spin-Orbit Coupling in Hybrid Organic/Inorganic Perovskites for Photovoltaic Applications. J. Phys. Chem. Lett. 2013, 4, 2999. \n(26) Zacharias, M.; Giustino, F. One-shot Calculation of Temperature-Dependent Optical Spectra and Phonon-Induced Band-Gap Renormalization. Phys. Rev. B: Condens. Matter Mater. Phys. 2016, 94, 075125. \n(27) Giannozzi, P.; et al. QUANTUM ESPRESSO: A Modular and Open-Source Software Project for Quantum Simulations of Materials. J. Phys.: Condens. Matter 2009, 21, 395502. \n(28) Rappe, A. M.; Rabe, K. M.; Kaxiras, E.; Joannopoulos, J. D. Optimized Pseudopotentials. Phys. Rev. B: Condens. Matter Mater. Phys. 1990, 41, 1227. \n(29) Vanderbilt, D. Soft Self-Consistent Pseudopotentials in a Generalized Eigenvalue Formalism. Phys. Rev. B: Condens. Matter Mater. Phys. 1990, 41, 7892. \n(30) Ceperley, D. M.; Alder, B. J. Ground State of the Electron Gas by a Stochastic Method. Phys. Rev. Lett. 1980, 45, 566. \n(31) Perdew, J. P.; Zunger, A. Self-Interaction Correction to DensityFunctional Approximations for Many-Electrons Systems. Phys. Rev. B: Condens. Matter Mater. Phys. 1981, 23, 5048. \n(32) Kresse, G.; Furthmuller, J. Efficient Iterative Schemes For ab initio Total-Energy Calculations Using a Plane-Wave Basis Set. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 11169−11186. \n(33) Paier, J.; Hirschl, R.; Marsman, M.; Kresse, G. The PerdewBurke-Ernzerhof Exchange-Correlation Functional Applied to the G2−1 Test Set Using a Plane-Wave Basis Set. J. Chem. Phys. 2005, 122, 234102. \n(34) Krukau, A. V.; Vydrov, O. A.; Izmaylov, A. F.; Scuseria, G. E. Influence of the Exchange Screening Parameter on the Performance of Screened Hybrid Functionals. J. Chem. Phys. 2006, 125, 224106. (35) Blöchl, P. E. Projector Augmented-Wave Method. Phys. Rev. B: Condens. Matter Mater. Phys. 1994, 50, 17953−17979. (36) Marini, A.; Hogan, C.; Grüning, M.; Varsano, D. Yambo: An Ab Initio Tool for Excited State Calculations. Comput. Phys. Commun. 2009, 180, 1392. \n(37) Troullier, N.; Martins, J. L. Efficient Pseudopotentials for PlaneWave Calculations. Phys. Rev. B: Condens. Matter Mater. Phys. 1991, 43, 1993. \n(38) Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865. \n(39) Zacharias, M.; Patrick, C. E.; Giustino, F. Stochastic Approach to Phonon-Assisted Optical Absorption. Phys. Rev. Lett. 2015, 115, 177401. \n(40) Bellaiche, L.; Vanderbilt, D. Virtual Crystal Approximation Revisited: Application to Dielectric and Piezoelectric Properties of Perovskites. Phys. Rev. B: Condens. Matter Mater. Phys. 2000, 61, 7877. (41) Larson, A. C.; Von Drele, R. B. General Structure Analysis System (GSAS). Los Alamos National Laboratory Report LAUR 2000, 86−748. \n(42) Toby, B. H. EXPGUI, A Graphical User Interface for GSAS. J. Appl. Crystallogr. 2001, 34, 210−234. " + }, + { + "id": "10.1039_c7ee00488e", + "DOI": "10.1039/c7ee00488e", + "DOI Link": "http://dx.doi.org/10.1039/c7ee00488e", + "Relative Dir Path": "mds/10.1039_c7ee00488e", + "Article Title": "Designed formation of hollow particle-based nitrogen-doped carbon nullofibers for high-performance supercapacitors", + "Authors": "Chen, LF; Lu, Y; Yu, L; Lou, XW", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "Carbon-based materials, as one of the most important electrode materials for supercapacitors, have attracted tremendous attention. At present, it is highly desirable but remains challenging to prepare one-dimensional carbon complex hollow nullomaterials for further improving the performance of supercapacitors. Herein, we report an effective strategy for the synthesis of hollow particle-based nitrogen-doped carbon nullofibers (HPCNFs-N). By embedding ultrafine zeolitic imidazolate framework (ZIF-8) nulloparticles into electrospun polyacrylonitrile (PAN), the as-prepared composite nullofibers are carbonized into hierarchical porous nullofibers composed of interconnected nitrogen-doped carbon hollow nulloparticles. Owing to its unique structural feature and the desirable chemical composition, the derived HPCNFs-N material exhibits much enhanced electrochemical properties as an electrode material for supercapacitors with remarkable specific capacitance at various current densities, high energy/power density and long cycling stability over 10 000 cycles.", + "Times Cited, WoS Core": 784, + "Times Cited, All Databases": 811, + "Publication Year": 2017, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000407211200008", + "Markdown": "
Volume 10|Number 8|August 2017|Pages 1707-1864
\n\n# Energy & Environmental Science \n\nrsc.li/ees \n\n![](images/bfbf9db36e0696c7687b3495d827564ae4462a88f4e2e787f31b74a85fd77d75.jpg) \n\n# Designed formation of hollow particle-based nitrogen-doped carbon nanofibers for high-performance supercapacitors† \n\nLi-Feng Chen, $\\textcircled{1}$ Yan Lu, Le Yu $\\textcircled{1}$ \\* and Xiong Wen (David) Lou $\\textcircled{1}$ \n\nReceived 20th February 2017, Accepted 7th April 2017 \n\nDOI: 10.1039/c7ee00488e \n\nrsc.li/ees \n\nCarbon-based materials, as one of the most important electrode materials for supercapacitors, have attracted tremendous attention. At present, it is highly desirable but remains challenging to prepare onedimensional carbon complex hollow nanomaterials for further improving the performance of supercapacitors. Herein, we report an effective strategy for the synthesis of hollow particle-based nitrogen-doped carbon nanofibers (HPCNFs-N). By embedding ultrafine zeolitic imidazolate framework (ZIF-8) nanoparticles into electrospun polyacrylonitrile (PAN), the as-prepared composite nanofibers are carbonized into hierarchical porous nanofibers composed of interconnected nitrogen-doped carbon hollow nanoparticles. Owing to its unique structural feature and the desirable chemical composition, the derived HPCNFs-N material exhibits much enhanced electrochemical properties as an electrode material for supercapacitors with remarkable specific capacitance at various current densities, high energy/power density and long cycling stability over 10 000 cycles. \n\n# Broader context \n\nSupercapacitors have been considered as one of the most promising electrochemical energy storage devices because of their high power density and long life span. Owing to their attractive physical and chemical properties including light weight, large surface area, good electrical conductivity and good chemical stability, carbon materials have been regarded as the most important candidates as electrodes for supercapacitors. In the past few decades, much effort has been devoted to optimizing the electrochemical performance of carbon materials. Particularly, the design and synthesis of one-dimensional carbon hollow nanostructures are highly desirable due to their unique structural features. Moreover, introducing heteroatom dopants is also beneficial for enhancing the electrochemical activity. However, there are still some challenges in the preparation of high-performance electrodes using complex hollow nanostructured carbon materials with controllable compositions. In this work, a facile electrospinning and carbonization method is designed to prepare hollow particle-based N-doped carbon nanofibers (HPCNFs-N). Benefiting from its hierarchical porous structure and high N-doping level, the obtained HPCNFs-N sample exhibits excellent electrochemical performance with remarkable specific capacitances at various current densities, high energy/power density and long-term cycling stability. \n\n# Introduction \n\nSupercapacitors have been regarded as one of the most promising energy storage devices for next-generation electronics and electric vehicles owing to their high power density, fast charge/discharge rate and long cycle life.1–4 The electrochemical properties of supercapacitors mainly depend on electrode materials.5,6 Therefore, the development of advanced electrode materials has become a hot topic for research in renewable energy-related fields. Among available candidates, carbonaceous materials are recognized as the most promising electrodes for supercapacitors because of their notable features including relatively light weight, high conductivity, high chemical stability, controllable porosity and plenty of active sites.7–11 \n\nIn the past few decades, much effort has been devoted to optimizing the performance of carbon materials for supercapacitors. Particularly, the design and synthesis of onedimensional (1D) carbon hollow nanostructures (i.e., carbon nanotubes) are highly desirable due to their apparent structural advantages as follows: (I) hollow structures guarantee sufficient contact area between the active sites and the electrolyte; (II) nano-sized subunits provide a reduced ion/electron diffusion path;5 and (III) the overall 1D features are believed to be beneficial for electron transport.12,13 Furthermore, introducing heteroatom dopants (N, P, B, S, etc.) is supposed to enhance the electrochemical activity by modifying the band gap and/or changing the surface characteristics.14,15 Nevertheless, the energy/ power density of hollow structures with simple configurations (i.e., single-shelled nanotubes) often suffers from low tapping density of the active materials.16 Besides, the synthetic strategies for hollow structures usually require some expensive hard templates, which have to be removed by additional treatments.17 Also, the doping processes need some hazardous chemical reactions.18,19 These complex synthetic procedures largely hinder the practical applications of carbon-based materials for supercapacitors. \n\nTo address these issues, we develop a facile electrospinning and carbonization method to prepare hollow particle-based N-doped carbon nanofibers (denoted as HPCNFs-N). ZIF-8 nanoparticles are first embedded into electrospun polyacrylonitrile (PAN) to form PAN/ZIF-8 composite nanofibers. After a subsequent carbonization reaction, primary ZIF-8 nanoparticle subunits within the PAN matrix are transformed into interconnected N-doped carbon hollow nanoparticles for forming the hierarchical porous nanofibers. During the synthesis, the electrospinning method enables the formation of a 1D composite precursor. Therefore, no redundant template-removal treatments are involved. Moreover, a large amount of N species within the organic ligands in ZIF-8 and PAN molecules is well-retained in the final product. Benefiting from the hierarchical porous structure and high N-doping level, these HPCNFs-N exhibit excellent electrochemical performance with high specific capacitance, remarkable energy/power density and long-term cycling stability. \n\n# Results and discussion \n\nThe synthetic strategy for HPCNFs-N is schematically depicted in Fig. 1. In a typical procedure, ZIF-8 nanoparticles are first embedded into PAN nanofibers by an electrospinning method. After a heat treatment at $900~^{\\circ}\\mathrm{C}$ in an inert atmosphere, the organic ligands in ZIF-8 and PAN molecules are decomposed and converted into N-doped carbon materials. Meanwhile, the $\\scriptstyle{\\mathrm{Zn}}^{2+}$ species in ZIF-8 particles are reduced to metallic Zn, which further vaporizes at high temperatures. The large mass loss within the interconnected ZIF-8 particles results in the formation of the hierarchical porous nanofibers. \n\n![](images/9678c12541ce62af4d9ad38f44795bdbf65b65a8bac30ebc1cab2ec2dc1a39d8.jpg) \nFig. 1 Schematic illustration of the synthesis of hollow particle-based N-doped carbon nanofibers (HPCNFs-N). \n\nAs revealed by the field-emission scanning electron microscopy (FESEM) observations (Fig. 2a and c), the as-prepared PAN/ZIF-8 composite nanofibers are very long and uniform in diameter $\\mathrm{{(\\sim1.4~\\upmum)}}$ . Compared with the electrospun PAN nanofibers without adding ZIF-8 particles (Fig. S1, see the $\\mathrm{ESI\\dag}\\right)_{\\mathrm{\\Delta}}$ ), the rough surface of the PAN/ZIF-8 sample indicates that the ZIF-8 nanoparticles are well dispersed within the whole nanofiber. The corresponding transmission electron microscopy (TEM) image (Fig. 2d) confirms the solid nature of the as-prepared PAN/ZIF-8 nanofibers. The XRD results also confirm the successful loading of ZIF-8 particles within the amorphous PAN nanofibers for the PAN/ZIF-8 sample (Fig. S2, see the $\\mathrm{ESI\\dag}$ ). \n\nAfter the thermal treatment in ${\\bf N}_{2}$ gas, the resultant HPCNFs-N sample retains the fiber-like morphology without apparent changes in appearance (Fig. 3a and b). Benefitting from the entangled network formed by the electrospun PAN/ZIF-8 nanofibers, the obtained HPCNFs-N sample exhibits good flexibility (inset of Fig. 3a and Fig. S3, see the $\\mathrm{ESI\\dag}$ ). Magnified FESEM images (Fig. 3c and d) and TEM images (Fig. 3e and f) reveal that these nanofibers are composed of numerous hollow nanoparticles interconnected with each other. In addition, the confined carbonization process within the PAN matrix can prevent the carbonized ZIF-8 nanoparticles from agglomerating (Fig. S4, see the ESI†). As shown by the high-resolution transmission electron microscope (HRTEM) examination (Fig. 3g), a distinct set of visible lattice fringes with an inter-planar spacing of $\\sim0.35\\ \\mathrm{nm}$ can be clearly identified, corresponding to the $d$ -spacing of the (002) plane of graphitic carbon.20,21 The existence of graphitic carbon might be beneficial to the electrical conductivity of HPCNFs-N. Furthermore, energy-filtered transmission electron microscope (EFTEM) mapping images based on an individual nanofiber demonstrate the uniform distribution of C and N elements within the entire porous structure (Fig. 3h–k). The effect of carbonization temperature on the structure of HPCNFs-N is also investigated. When PAN/ZIF-8 is heated at a temperature of $800~^{\\circ}\\mathrm{C},$ , the volume shrinkage for the achieved sample (denoted as HPCNFs-N-800) is reduced (Fig. S5a, see the $\\mathbf{\\mathbf{E}S I\\dagger}$ ). As a result, the diameter of the HPCNFsN-800 nanofibers is much larger than that of the HPCNFs-N product annealed at $900^{\\circ}\\mathrm{C}$ (Fig. S6, see the $\\mathrm{ESI\\dag}$ ). In comparison, the sample annealed at $1000~^{\\circ}\\mathrm{C}$ (denoted as HPCNFs-N-1000) is rather compact (Fig. S5c, see $\\mathrm{ESI\\dagger}$ ) with a reduced diameter of the obtained nanofibers (Fig. S7, see the ESI†). Besides, more broken hollow nanoparticles can be observed along the whole fiber. \n\n![](images/6ff993bfb20a6e7dc6fa5cd51c97c076fbf14894d389abf1fa57f3c8c73b4479.jpg) \nFig. 2 FESEM and TEM images of the PAN/ZIF-8 composite nanofibers. \n\n![](images/3baf01e1a36f11e5eacdacd84fd25ce47a0b24277deb0c7c7a983974bd8eb5b3.jpg) \nFig. 3 FESEM and TEM images of the HPCNFs-N sample. (a–c) Top view of FESEM images; (d) magnified FESEM image of the selected region in (c); (e and f) TEM and (g) HRTEM images. Elemental mapping images of (h) C, (i) N, (j) O and (k) overlap. Inset in (a): Photograph of a piece of the folded HPCNFs-N sample. Inset in (g): A high resolution TEM image of the HPCNFs-N shell. \n\nTwo broad peaks can be identified from the X-ray powder diffraction (XRD) patterns (Fig. 4a) of HPCNFs-N and the control samples, confirming the crystalline nature of carbon with a very small particle size.22 Raman spectra further provide some information about the characteristic G and D bands of the carbon species in the as-prepared nanofibers. As shown in Fig. 4b, the intensive peaks emerged at around 1338 and $1585~\\mathrm{cm}^{-1}$ are associated with the in-plane $\\mathbf{A_{1g}}$ zone-edge mode (D band) and the doubly degenerate zone center $\\mathbf{E}_{2\\mathrm{g}}$ mode (G band), respectively.15,23,24 Meanwhile, the broad peak appearing in the $2500{-}3500~\\mathrm{cm}^{-1}$ region can be assigned to the second-order of D band (2D band).25 According to the increased intensity ratio of the $\\mathbf{G}$ to D bands $\\left(I_{\\mathrm{G}}/I_{\\mathrm{D}}\\right)$ , the graphenic order of carbon in the nanofibers is largely enhanced with the increase in carbonization temperature. \n\nThe chemical compositions of the HPCNFs-N sample are further investigated by electron energy-loss spectroscopy (EELS) measurements. Two visible edges in the EELS spectrum (Fig. 4c) starting at 279 and $395\\ \\mathrm{eV}$ are assigned to the characteristic K-shell ionization edges of C and N, respectively, indicating the co-existence of C and N in the sample.26 The two bands clearly show a pre-peak corresponding to the ${\\boldsymbol{1}}{\\boldsymbol{s}}{-}{\\boldsymbol{\\pi}}^{*}$ antibonding orbit, followed by a wider band related to the ${\\bf15-}\\upsigma^{\\ast}$ antibonding orbit. The well-defined $\\pi^{*}$ and $\\upsigma^{\\ast}$ features of C and N K-edge confirm that both C and N elements are $\\mathsf{s p}^{2}$ hybridized.20,26,27 According to the EELS spectrum, the $\\mathbf{N}/\\mathbf{C}$ ratio within HPCNFs-N is approximately 0.091 ( $91.66\\pm12.5~\\mathrm{at\\%}\\mathrm{~C~}$ and $8.34\\:\\pm\\:1.1$ at% N), consistent with the result from elemental analysis $(78.43\\mathrm{wt\\%}$ C, $9.39\\mathrm{wt\\%}]$ N and $1.15\\mathrm{wt\\%H}$ ; the atomic ratio of $\\mathbf{N}/\\mathbf{C}$ is 0.103). X-ray photoelectron spectroscopy (XPS) measurements are also conducted to further clarify the contents and types of N species in the samples. From XPS survey spectra (Fig. S8a, $\\mathrm{ESI\\dag}\\$ ), the atomic percentage of N in HPCNFs-N, HPCNFs-N-800 and HPCNFs-N-1000 is estimated to be around $7.85\\%$ , $12.05\\%$ and $3.63\\%$ , respectively. Besides, the atomic percentage of oxygen in HPCNFs-N-800, HPCNFs-N and HPCNFs-N-1000 is $6.06\\%$ , $5.35\\%$ and $4.94\\%$ , respectively. Moreover, there are no Zn species remaining for all the samples after the high temperature annealing and the subsequent acid treatment. Their N1s region spectra (Fig. 4d and Fig. S8b and c, see the $\\mathrm{ESI\\dag}\\$ ) can be deconvoluted into four peaks, pyridinic N (N-6), pyrrolic/pyridonic N (N-5), quaternary N and oxidic N.28,29 Among these types, the N-5 and N-6 species are the dominant N-containing functional groups in HPCNFs-N, which serve as electrochemically active sites in various electrochemical applications.30,31 The N-5 species are gradually converted to the N-6 and inactive quaternary N species upon the increase of the carbonization temperature. \n\nPore characteristics of the samples are characterized through ${\\bf N}_{2}$ adsorption–desorption measurements. The remarkable hysteresis loop of type IV indicates that the HPCNFs-N sample exhibits a mesoporous structure (Fig. S9, see the ESI†).32 The corresponding pore-size-distribution (PSD) curve shows that the size of the majority of the pores falls in the range of 3 to $4~\\mathrm{nm}$ . Detailed parameters about the Brunauer–Emmett–Teller (BET) specific surface area $\\left(S_{\\mathrm{BET}}\\right)$ and pore volume are summarized in Table S1 $\\left(\\mathrm{ESI\\dag}\\right)$ . It can be found that $S_{\\mathbf{BET}}$ of HPCNFs-N $(417.9\\mathrm{~m}^{2}\\mathrm{~g}^{-1})$ is much larger than that of the N-doped carbon (denoted as $\\mathbf{C}\\mathbf{-}\\mathbf{N}\\dot{}$ ) obtained by carbonizing ZIF-8 particles $\\left(223.1~\\mathrm{m}^{2}~\\mathrm{g}^{-1}\\right.$ , Fig. S10, see the $\\mathrm{ESI\\dag}$ ). Besides, $S_{\\mathrm{BET}}$ of the N-doped carbon nanofibers (denoted as N-CNFs) obtained by carbonizing the electrospun PAN nanofibers is very small. The above results demonstrate the importance of the introduction of ZIF-8 nanoparticles into the precursor to improve the specific surface area of HPCNFs-N. \n\n![](images/4ce38bbf3a8e5c94ae952ce8cb3f16b80f075260c0fd46b31e37427e3668cf41.jpg) \nFig. 4 (a) XRD patterns and (b) Raman spectra of HPCNFs-N and the control samples. (c) Electron energy loss spectroscopy and (d) high-resolution XPS spectra of the deconvoluted N1s peak of the HPCNFs-N sample. \n\nNext, the electrochemical performance of HPCNFs-N is assessed as electrodes for supercapacitors in a two-electrode cell configuration using an aqueous $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution $\\left(2.0{\\bf\\delta M}\\right)$ as the electrolyte (Fig. S11, see the $\\mathrm{ESI\\dag}$ ). The typical cyclic voltammetry (CV) curves of HPCNFs-N at sweep rates ranging from 2.0 to $100.0\\ \\mathrm{mV}\\ \\mathrm{s}^{-1}$ are presented in Fig. 5a. The nearly rectangular shape suggests its classical capacitive behavior as the electrodes of electrical double layer supercapacitors,33 where the small humps originate from Faradaic reactions of active functional groups on the HPCNFs-N surface. Moreover, the CV profiles over variable scan rates (up to $1500\\mathrm{\\mV\\s^{-1}}$ ; Fig. S12a, see the ESI†) display quasi-rectangular shapes, suggesting its high-rate capability. In comparison, the control samples of C–N (Fig. S13a, see the ESI†) and N-CNFs (Fig. S14, see the ESI†) show similar rectangular CV curves with much reduced capacitance. This clearly verifies the importance of large surface area and desirable chemical composition for electrochemical performance. \n\nFurthermore, the galvanostatic charge/discharge curves of HPCNFs-N (Fig. 5b and Fig. S12b, see the $\\mathrm{ESI\\dag}$ collected at various current densities from 1.0 to $200.0\\mathrm{~A~g~}^{-1}$ are nearly linear and symmetrical, which further confirms its capacitorlike feature and good electrochemical reversibility. The specific capacitance $\\left(C_{s}\\right)$ as a function of the current density is calculated based on the discharge curves. As seen in Fig. 5c, $C_{\\mathrm{s}}$ of HPCNFs-N is as high as 307.2, 283.2, 264, 252.2 and $235.2\\ \\mathrm{F}\\ \\mathrm{g}^{-1}$ at discharge current densities of 1.0, 2.0, 5.0, 10.0 and $20.0\\mathrm{A}\\mathrm{g}^{-1}$ , respectively. This suggests that about $76.6\\%$ of the capacitance is retained when the charge–discharge rate is increased from 1.0 to $20.0\\mathrm{~A~g}^{-1}$ . Moreover, even at a much higher current density of $50.0\\mathrm{A}\\mathrm{g}^{-1}$ , $C_{\\mathrm{s}}$ for HPCNFs-N still reaches a high value of $193.4\\mathrm{~F~g}^{-1}$ . The variation of IR drop at different discharge current densities (Fig. S12c, see the $\\mathrm{ESI\\dag}$ ) reveals that the supercapacitor device based on the HPCNFs-N electrodes has a small internal resistance, which is beneficial for high power discharge in practical applications. The remarkable performance of HPCNFs-N compares favorably to the behavior of many reported representative carbon materials (Table S2, see the ESI†).15,19,34–43 Although the control samples of HPCNFs-N-800, HPCNFs-N-1000 (Fig. S12d–f, see the $\\mathrm{ESI\\dag}$ ) and C–N (Fig. S13b, see the $\\mathrm{ESI\\dag}$ ) display similar electrochemical characteristics to capacitor-like electrodes, their electrochemical properties in terms of $C_{s}$ values and/or rate performance are much inferior. Overall, these inspiring results might be attributed to the unique structural and compositional features of HPCNFs-N, such as high specific area, desirable pore size distribution and sufficient electrochemically active sites. \n\n![](images/f98770281d63edd4c908d45305741b9401742cd59be6299929503d4546dc4a55.jpg) \nFig. 5 (a) CV curves of the HPCNFs-N sample at different scan rates. (b) Galvanostatic charge–discharge curves at different current densities and (c) variation of specific capacitance against the current density of HPCNFs-N and the control samples. (d) Cycling performance of the HPCNFs-N device at a current density of $5.0\\mathsf{A g}^{-1}$ . \n\nThe power/energy density is a key parameter for evaluating the electrochemical performance of the electrode materials in supercapacitors.37,38,44,45 The Ragone plots (Fig. S15, see the $\\mathrm{ESI\\dag}$ ) clearly illustrate that the supercapacitor device using the HPCNFs-N electrodes exhibits much enhanced energy/power density compared with the supercapacitors based on the control samples. Besides, the power/energy density of the device in our work is comparable to that of some other similar carbon-based supercapacitors.15,38,40,42 Specifically, an energy density of as high as 10.96 W h $\\mathrm{kg}^{-1}$ can be achieved at a power density of 250 W $\\mathrm{kg}^{-1}$ . Moreover, it still maintains 6.72 W h $\\log^{-1}$ even at a high power density of $25000~\\mathrm{W~kg}^{-1}$ . Overall, the performance is competitive with that of some N-doped carbon-based supercapacitors.15,37,38 \n\nLastly, the electrochemical stability of the supercapacitor is tested by continuous galvanostatic charge–discharge cycling at a current density of $5.0\\mathrm{~A~g^{-1}}$ . As shown in Fig. 5d, the specific capacitance maintains $98.2\\%$ of the initial value after 10 000 cycles, indicating the excellent electrochemical stability of the supercapacitor device. The Coulombic efficiency maintains almost $100\\%$ after the first few cycles (Fig. S16, see the $\\mathrm{ESI\\dag}$ ). Furthermore, we study the morphology of electrodes after repeated charge–discharge processes. As indicated by morphological observations, the integrity of the HPCNFs-N electrode is well preserved, confirming its superior structural stability (Fig. S17, see the ESI†). \n\nThe above excellent electrochemical properties of HPCNFs-N might be ascribed to their unique structural and compositional features. First, the hierarchical porous structure composed of numerous interconnected carbon hollow nanoparticles guarantees sufficient electrochemically active sites, improved electrochemical kinetics and enhanced structural stability. Second, the unique 1D fiber-like architecture ensures good ion/electron transport. Third, the high N-doping level might be beneficial for the electrochemical reactions by introducing functional groups and/or modifying the band gap. \n\n# Conclusions \n\nIn summary, we present an effective method for producing hollow particle-based N-doped carbon nanofibers via a simple carbonization treatment of an electrospun ZIF-8/PAN composite precursor. With these hierarchical porous nanofibers as the electrodes, the as-assembled supercapacitor device exhibits remarkable supercapacitive performance with high specific capacitances at various current densities $\\left(307.2\\mathrm{~F~g}^{-1}\\right.$ at $1.0\\mathrm{~A~g^{-1}}$ and $193.4\\mathrm{~F~g}^{-1}$ at $50.0\\mathrm{~A~g~}^{-1},$ , enhanced energy/power density (a maximum energy density of $10.96\\mathrm{W}\\mathrm{h}\\mathrm{kg}^{-1}$ and a power density of $25000\\mathrm{W}\\mathrm{kg}^{-1})$ 1 and outstanding cycling stability with only $1.8\\%$ capacitance loss over 10 000 cycles. \n\n# Experimental \n\n# Preparation of ZIF-8 particles \n\nTypically, $\\mathbf{1.487}\\:\\mathrm{g}$ of $\\mathrm{Zn}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ was dissolved in $100~\\mathrm{{mL}}$ of methanol. $3.284~\\mathrm{g}$ of 2-methylimidazole (MeIM) was dissolved into $50~\\mathrm{mL}$ of methanol. Then, the two solutions were rapidly mixed together under magnetic stirring at room temperature for $^{2\\mathrm{~h~}}$ . Next, the white powder was collected by centrifugation $\\left(10000\\mathrm{rpm},3\\mathrm{min}\\right)$ , washed several times with methanol, and dried at $80~^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{~h~}}$ . \n\n# Preparation of hollow particle-based N-doped carbon nanofibers (HPCNFs-N) \n\n$\\boldsymbol{0.263\\mathrm{~g~}}$ of the as-synthesized ZIF-8 powder was dispersed in $2.063~\\mathrm{g}$ of dimethylformamide (DMF) solvent via sonication for $30~\\mathrm{min}$ , followed by the addition of $\\mathbf{0.175~g}$ of polyacrylonitrile (PAN, average MW 150 000). The mixture was stirred for $24\\mathrm{~h~}$ to form a homogeneously dispersed solution. Then, the mixture solution was loaded into a syringe $\\mathrm{5~mL}$ ) using a stainless-steel nozzle, which was connected to a high-voltage power supply. The high voltage, feeding rate, temperature and distance between the anode and cathode are fixed at $20~\\mathrm{kV}$ , $1.0\\ \\mathrm{mL}\\mathrm{h}^{-1}$ , $35~^{\\circ}\\mathrm{C}$ and $18~\\mathrm{cm}$ , respectively. Then, the electrospun PAN/ZIF-8 was dried at $70\\ ^{\\circ}\\mathrm{C}$ overnight in a vacuum. Afterwards, the composite nanofibers were carbonized under the protection of $\\mathbf{N}_{2}$ gas through a two-stage heating process. Specifically, they were first heated at $550~^{\\circ}\\mathrm{C}$ for $^\\textrm{\\scriptsize1h}$ with a ramping rate of $2{\\bf\\nabla}^{\\circ}{\\bf C}$ $\\operatorname*{min}^{-1}$ , followed by a further thermal annealing process at $900^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{~h~}}$ with a ramping rate of $5\\mathrm{\\mathrm{~}^{\\circ}C\\mathrm{~min}^{-1}}$ . Subsequently, the resultant materials were washed thoroughly in a $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution $\\left(3.0\\ \\mathbf{M}\\right)$ to remove residual $Z\\mathrm{n}$ species. Finally, the as-obtained HPCNFs-N sample was rinsed with ethanol and deionized water and dried in a vacuum at $80~^{\\circ}\\mathrm{C}.$ . \n\nThe control sample of N-doped carbon nanofibers (N-CNFs) was synthesized by a similar procedure without adding ZIF-8 particles. For the other two samples of hollow particle-based N-doped carbon nanofibers annealed at $800~^{\\circ}\\mathrm{C}$ (denoted as HPCNFs-N-800) or $1000~^{\\circ}\\mathrm{C}$ (HPCNFs-N-1000), the PAN/ZIF-8 fiber was carbonized under the protection of ${\\bf N}_{2}$ gas through a two-stage heating process. They were first heated at $550~^{\\circ}\\mathrm{C}$ for $^\\textrm{\\scriptsize1h}$ with a ramping rate of $2{\\mathrm{~}}^{\\circ}{\\bf C}{\\mathrm{~min}}^{-1}$ , followed by a further thermal annealing process at $800~^{\\circ}\\mathrm{C}$ (or $1000~^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{~h~}}$ with a ramping rate of $5\\ ^{\\circ}\\mathbf{C}\\ \\operatorname*{min}^{-1}$ . \n\n# Material characterization \n\nThe morphology of the samples was examined using a fieldemission scanning electron microscope (FESEM; JEOL-6700F) and a transmission electron microscope (TEM; JEOL, JEM2010). High-resolution transmission electron microscopy (HRTEM) images, energy filtered transmission electron microscopy (EFTEM) mapping images and electron energy loss spectroscopy (EELS) spectra were collected on a JEM-ARM 200F atomic resolution analytical microscope. The crystal phase of the products was examined by X-ray diffraction (XRD; Bruker, D8-Advance X-ray Diffractometer, Cu Ka radiation, $\\lambda=1.5406\\overset{\\circ}{\\mathrm{A}}$ ). Raman scattering spectra were collected on a confocal micro-Raman system (WITec alpha 300) under ambient conditions, using a diode laser (excitation wavelength is $532~\\mathrm{nm}$ ). X-ray photoelectron spectroscopy (XPS) spectra were obtained on an ESCALab MKII X-ray photoelectron spectrometer with a $\\mathbf{Mg}\\ \\mathrm{K}\\mathfrak{a}$ $(1253.6\\ \\mathrm{eV})$ excitation source. Elemental analysis was carried out using a CNH analyzer (Elementarvario EL cube). $\\ensuremath{\\mathbf{N}}_{2}$ adsorption/desorption isotherms were obtained on Quantachrome Instruments v4.01, and the Barrett–Emmett– Teller (BET) theory was used for surface area calculations. Poresize-distribution (PSD) plots were obtained from the adsorption branch of the isotherm using the Barrett–Joyner–Halenda (BJH) model. \n\n# Electrochemical measurements \n\nAll electrochemical measurements were carried out using a twoelectrode system with a $\\mathbf{CHI660D}$ electrochemical workstation at room temperature. Before the assembly of the supercapacitors, the electrodes were soaked in an aqueous $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte $\\left(2.0{\\bf\\delta M}\\right)$ for $^{6\\mathrm{~h~}}$ . The employed two-electrode configuration consisted of two slices of electrode materials with the same size (1 $.0\\ \\mathrm{cm}\\ \\times\\ 1.0\\ \\mathrm{cm})$ , filter paper (pore size: $225~\\mathrm{nm}$ as the separator, and a pair of Ti foil as the current collectors. Moreover, the whole supercapacitor device was wrapped with parafilm for fixation. The tap density of the supercapacitor electrode was estimated by direct mass and physical dimension measurements, which is about $0.27\\mathrm{gcm}^{-3}$ . CV curves and galvanostatic charge/discharge measurements were recorded at the working voltage of 0.0 to $1.0\\mathrm{V}$ . For the electrochemical performance of N-CNFs and C–N, the electrode slurry was prepared by mixing the active material $(80~\\mathrm{wt\\%})$ , acetylene black (Super-P, $10\\mathrm{\\wt{\\%}}$ ) and polyvinylidene fluoride (PVDF, $10~\\mathrm{wt\\%})$ in $N_{\\mathbf{\\lambda}}$ -methyl-2- pyrrolidone. After spreading the above slurry on Ti foil (active material loading: $\\sim1.0\\ \\mathrm{mg\\cm}^{-2},$ , the electrodes were dried at $80~^{\\circ}\\mathbf{C}$ for $24\\mathrm{~h~}$ under vacuum. \n\nThe mass based specific capacitance $\\left(C_{s}\\right)$ was calculated from the galvanostatic discharge process using eqn (1): \n\n$$\nC_{\\mathrm{s}}={\\frac{4I_{\\mathrm{cons}}}{m\\mathrm{d}V/\\mathrm{d}t}}\n$$ \n\nwhere $I_{\\mathrm{cons}}$ (A) corresponds to the constant discharge current, dV/dt $(\\mathrm{V~}\\mathrm{S}^{-1})$ represents the slope of the discharge curve, and $m$ (g) refers to the total mass of the active material on the two electrodes. \n\nThe energy density $(E)$ and power density $(P)$ of the supercapacitor device were calculated using eqn (2) and (3) \n\n$$\nE=\\frac{\\displaystyle\\frac{1}{8}\\times C_{\\mathrm{s}}\\times(\\Delta V)^{2}\\times1000}{3600}\n$$ \n\n$$\nP=\\frac{E\\times3600}{\\Delta t}\n$$ \n\nwhere $E$ $\\varepsilon~(\\mathrm{W}\\mathrm{~h~}\\mathrm{kg}^{-1})$ is the mass based energy density, $\\Delta V$ (V) corresponds to the voltage window, $P$ $^{\\circ}(\\mathrm{W}\\ \\mathrm{kg}^{-1})$ is the average power density and $\\Delta t$ (s) refers to the discharge time. \n\n# Acknowledgements \n\nX. W. L. acknowledges the funding support from the National Research Foundation (NRF) of Singapore via the NRF investigatorship (NRF-NRFI2016-04) and the Ministry of Education of \n\nSingapore through the AcRF Tier-2 funding (MOE2014-T2-1-058; \nARC41/14). \n\n# Notes and references \n\n1 P. Huang, C. Lethien, S. Pinaud, K. Brousse, R. Laloo, V. Turq, M. Respaud, A. Demortiere, B. Daffos, P. L. Taberna, B. Chaudret, Y. Gogotsi and P. Simon, Science, 2016, 351, 691. \n2 G. G. Eshetu, M. Armand, B. Scrosati and S. Passerini, Angew. Chem., Int. Ed., 2014, 53, 13342. \n3 G. Q. Zhang and X. W. Lou, Adv. Mater., 2013, 25, 976. \n4 S. J. Peng, L. L. Li, H. B. Wu, S. Madhavi and X. W. Lou, Adv. Energy Mater., 2015, 5, 1401172. \n5 A. S. Arico, P. Bruce, B. Scrosati, J. M. Tarascon and W. Van Schalkwijk, Nat. Mater., 2005, 4, 366. \n6 P. Simon and Y. Gogotsi, Nat. Mater., 2008, 7, 845. \n7 L. L. Zhang and X. S. Zhao, Chem. Soc. Rev., 2009, 38, 2520. \n8 J. L. Liu, L. L. Zhang, H. B. Wu, J. Y. Lin, Z. X. Shen and X. W. Lou, Energy Environ. Sci., 2014, 7, 3709. \n9 D. Pech, M. Brunet, H. Durou, P. H. Huang, V. Mochalin, Y. Gogotsi, P. L. Taberna and P. Simon, Nat. Nanotechnol., \n2010, 5, 651. \n10 Y. Wang, Z. Q. Shi, Y. Huang, Y. F. Ma, C. Y. Wang, M. M. Chen and Y. S. Chen, J. Phys. Chem. C, 2009, 113, 13103. \n11 J. F. Chen, Y. L. Han, X. H. Kong, X. Z. Deng, H. J. Park, Y. L. Guo, S. Jin, Z. K. Qi, Z. Lee, Z. H. Qiao, R. S. Ruoff and H. X. Ji, Angew. Chem., Int. Ed., 2016, 55, 13822. \n12 R. H. Baughman, A. A. Zakhidov and W. A. de Heer, Science, \n2002, 297, 787. \n13 W. Li, F. Zhang, Y. Q. Dou, Z. X. Wu, H. J. Liu, X. F. Qian, D. Gu, Y. Y. Xia, B. Tu and D. Y. Zhao, Adv. Energy Mater., \n2011, 1, 382. \n14 F. B. Su, C. K. Poh, J. S. Chen, G. W. Xu, D. Wang, Q. Li, J. Y. Lin and X. W. Lou, Energy Environ. Sci., 2011, 4, 717. \n15 L. F. Chen, Z. H. Huang, H. W. Liang, H. L. Gao and S. H. Yu, Adv. Funct. Mater., 2014, 24, 5104. \n16 G. Q. Zhang, B. Y. Xia, C. Xiao, L. Yu, X. Wang, Y. Xie and X. W. Lou, Angew. Chem., Int. Ed., 2013, 52, 8643. \n17 W. Zhang, Z. Y. Wu, H. L. Jiang and S. H. Yu, J. Am. Chem. Soc., 2014, 136, 14385. \n18 L. Qie, W. M. Chen, H. H. Xu, X. Q. Xiong, Y. Jiang, F. Zou, X. L. Hu, Y. Xin, Z. L. Zhang and Y. H. Huang, Energy Environ. Sci., 2013, 6, 2497. \n19 H. Zhu, J. Yin, X. L. Wang, H. Y. Wang and X. R. Yang, Adv. Funct. Mater., 2013, 23, 1305. \n20 Y. C. Zhao, Z. Liu, W. G. Chu, L. Song, Z. X. Zhang, D. L. Yu, Y. J. Tian, S. S. Xie and L. F. Sun, Adv. Mater., 2008, 20, 1777. \n21 D. Y. Chung, K. J. Lee, S. H. Yu, M. Kim, S. Y. Lee, O. H. Kim, H. J. Park and Y. E. Sung, Adv. Energy Mater., 2015, 5, 1401309. \n22 F. C. Zheng, Y. Yang and Q. W. Chen, Nat. Commun., 2014, \n5, 5261. \n23 B. Y. Xia, Y. Yan, N. Li, H. B. Wu, X. W. Lou and X. Wang, Nat. Energy, 2016, 1, 15006. \n24 A. C. Ferrari, Solid State Commun., 2007, 143, 47. \n25 H. J. Huang, S. B. Yang, R. Vajtai, X. Wang and P. M. Ajayan, Adv. Mater., 2014, 26, 5160. \n26 L. Ci, L. Song, C. H. Jin, D. Jariwala, D. X. Wu, Y. J. Li, A. Srivastava, Z. F. Wang, K. Storr, L. Balicas, F. Liu and P. M. Ajayan, Nat. Mater., 2010, 9, 430. \n27 R. R. Schlittler, J. W. Seo, J. K. Gimzewski, C. Durkan, M. S. M. Saifullah and M. E. Welland, Science, 2001, 292, 1136. \n28 D. H. Guo, R. Shibuya, C. Akiba, S. Saji, T. Kondo and J. Nakamura, Science, 2016, 351, 361. \n29 C. Young, R. R. Salunkhe, J. Tang, C. C. Hu, M. Shahabuddin, E. Yanmaz, M. S. A. Hossain, J. H. Kim and Y. Yamauchi, Phys. Chem. Chem. Phys., 2016, 18, 29308. \n30 L. F. Chen, X. D. Zhang, H. W. Liang, M. G. Kong, Q. F. Guan, P. Chen, Z. Y. Wu and S. H. Yu, ACS Nano, 2012, 6, 7092. \n31 H. M. Jeong, J. W. Lee, W. H. Shin, Y. J. Choi, H. J. Shin, J. K. Kang and J. W. Choi, Nano Lett., 2011, 11, 2472. \n32 J. Wei, D. D. Zhou, Z. K. Sun, Y. H. Deng, Y. Y. Xia and D. Y. Zhao, Adv. Funct. Mater., 2013, 23, 2322. \n33 P. Simon, Y. Gogotsi and B. Dunn, Science, 2014, 343, 1210. \n34 J. Tang, R. R. Salunkhe, J. Liu, N. L. Torad, M. Imura, S. Furukawa and Y. Yamauchi, J. Am. Chem. Soc., 2015, 137, 1572. \n35 H. L. Jiang, B. Liu, Y. Q. Lan, K. Kuratani, T. Akita, H. Shioyama, F. Q. Zong and Q. Xu, J. Am. Chem. Soc., 2011, 133, 11854. \n36 F. F. Cao, M. T. Zhao, Y. F. Yu, B. Chen, Y. Huang, J. Yang, X. H. Cao, Q. P. Lu, X. Zhang, Z. C. Zhang, C. L. Tan and H. Zhang, J. Am. Chem. Soc., 2016, 138, 6924. \n37 B. Li, F. Dai, Q. F. Xiao, L. Yang, J. M. Shen, C. M. Zhang and M. Cai, Energy Environ. Sci., 2016, 9, 102. \n38 J. Zhao, H. W. Lai, Z. Y. Lyu, Y. F. Jiang, K. Xie, X. Z. Wang, Q. Wu, L. J. Yang, Z. Jin, Y. W. Ma, J. Liu and Z. Hu, Adv. Mater., 2015, 27, 3541. \n39 N. P. Wickramaratne, J. T. Xu, M. Wang, L. Zhu, L. M. Dai and M. Jaroniec, Chem. Mater., 2014, 26, 2820. \n40 Y. L. Cheng, L. Huang, X. Xiao, B. Yao, L. Y. Yuan, T. Q. Li, Z. M. Hu, B. Wang, J. Wan and J. Zhou, Nano Energy, 2015, 15, 66. \n41 C. H. Wang, C. Liu, J. S. Li, X. Y. Sun, J. Y. Shen, W. Q. Han and L. J. Wang, Chem. Commun., 2017, 53, 1751. \n42 G. Y. Zhu, L. B. Ma, H. L. Lv, Y. Hu, T. Chen, R. P. Chen, J. Liang, X. Wang, Y. R. Wang, C. Z. Yan, Z. X. Tie, Z. Jin and J. Liu, Nanoscale, 2017, 9, 1237. \n43 K. Xiao, L. X. Ding, G. X. Liu, H. B. Chen, S. Q. Wang and H. H. Wang, Adv. Mater., 2016, 28, 5997. \n44 L. F. Shen, L. Yu, H. B. Wu, X. Y. Yu, X. G. Zhang and X. W. Lou, Nat. Commun., 2015, 6, 6694. \n45 L. L. Li, S. J. Peng, H. B. Wu, L. Yu, S. Madhavi and X. W. Lou, Adv. Energy Mater., 2015, 5, 1500753. " + }, + { + "id": "10.1021_jacs.6b12755", + "DOI": "10.1021/jacs.6b12755", + "DOI Link": "http://dx.doi.org/10.1021/jacs.6b12755", + "Relative Dir Path": "mds/10.1021_jacs.6b12755", + "Article Title": "Fused Nonacyclic Electron Acceptors for Efficient Polymer Solar Cells", + "Authors": "Dai, SX; Zhao, FW; Zhang, QQ; Lau, TK; Li, TF; Liu, K; Ling, QD; Wang, CR; Lu, XH; You, W; Zhan, XW", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "We design and synthesize four fused-ring electron acceptors based on-6,6,12,12-tetrakis(4-hexylphenyl)-indacenobis(dithieno[3,2-b-2',3'-d]thiophene) as the electron-rich unit and 1,1-dicyanomethylene-3-indanones with 0-2 fluorine substituents as the electron-deficient units. These four molecules exhibit broad (550-850 nm) and strong absorption with high extinction coefficients of (2.1-2.5) x 10(5) M-1 cm(-1). Fluorine substitution downshifts the LUMO energy level, red-shifts the absorption spectrum, and enhances electron mobility. The polymer solar cells based on the fluorinated electron acceptors exhibit power conversion efficiencies as high as 11.5%, much higher than that of their nonfluorinated counterpart (7.7%). We investigate the effects of the fluorine atom number and position on electronic properties, charge transport, film morphology, and photovoltaic properties.", + "Times Cited, WoS Core": 823, + "Times Cited, All Databases": 844, + "Publication Year": 2017, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000393541000041", + "Markdown": "# Fused Nonacyclic Electron Acceptors for Efficient Polymer Solar Cells \n\nShuixing Dai, Fuwen Zhao, Qianqian Zhang, Tsz-Ki Lau, Tengfei Li, Kuan Liu, Qidan Ling, Chunru Wang, Xinhui Lu, Wei You, and Xiaowei Zhan J. Am. Chem. Soc., Just Accepted Manuscript $\\cdot$ DOI: 10.1021/jacs.6b12755 • Publication Date (Web): 06 Jan 2017 Downloaded from http://pubs.acs.org on January 6, 2017 \n\n# Just Accepted \n\n“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier $(\\mathsf{D O}|\\oplus)$ . “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts. \n\n# Fused Nonacyclic Electron Acceptors for Efficient Polymer Solar Cells \n\nShuixing Dai,†,‡ Fuwen Zhao,§ Qianqian Zhang,⊥ Tsz-Ki Lau,# Tengfei Li,† Kuan Liu,† Qidan Ling,‡ Chunru Wang,§ Xinhui Lu,# Wei You,⊥ and Xiaowei Zhan†,\\* \n\n† Department of Materials Science and Engineering, College of Engineering, Key Laboratory of Polymer Chemistry and Physics of Ministry of Education, Peking University, Beijing 100871, China ‡ Fujian Key Laboratory of Polymer Materials, College of Materials Science and Engineering, Fujian Normal University, Fuzhou 350007, China \n§ Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China \n⊥ Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-3290, United States \n\n# Department of Physics, Chinese University of Hong Kong, New Territories, Hong Kong, China \n\nABSTRACT: We design and synthesize four fused-ring electron acceptors based on 6,6,12,12-tetrakis(4-hexylphenyl)-indacenobis(dithieno[3,2-b;2',3'-d]thiophene) as the electron-rich unit and 1,1-dicyanomethylene-3-indanones with 0 to 2 fluorine substituents as the electron-deficient units. These four molecules exhibit broad $550{-}850~\\mathrm{nm}$ ) and strong absorption with high extinction coefficients of $(2.1-2.5)\\times10^{5}~\\mathrm{M}^{-1}~\\mathrm{cm}^{-1}$ . Fluorine substitution down shifts LUMO energy level, red shift absorption spectrum, and enhance electron mobility. The polymer solar cells based on the fluorinated electron acceptors exhibit power conversion efficiencies as high as $11.5\\%$ , much higher than that of their nonfluorinated counterpart $(7.7\\%)$ . We investigate the effects of the fluorine atom number and position on electronic properties, charge transport, film morphology, and photovoltaic properties. \n\nKeywords: indacenobis(dithienothiophene); fused-ring electron acceptor; nonfullerene acceptor; fluorinated acceptor; polymer solar cell \n\n# ■ INTRODUCTION \n\nOrganic solar cells (OSCs) are considered to be one of promising alternatives to silicon-based solar cells since they present unique features, such as low processing cost, semi-transparency, flexibility, and light weight.1-3 For a long period of time, OSCs mainly employed fullerene derivatives (e.g., $\\mathrm{PC}_{61}\\mathrm{BM}$ and $\\mathrm{PC}_{71}\\mathrm{BM},$ ) as electron acceptors which, paired with electron donating polymers or small molecules, have successfully achieved power conversion efficiencies (PCEs) over $11\\%$ .4-7 However, fullerene derivatives suffer from several shortcomings, such as poor absorption in the visible region, limited tunability of energy levels, and morphology instability, which hinder the further development of OSCs. On the other hand, nonfullerene electron acceptors possess advantages over their fullerene counterpart, such as enhanced absorption in the visible and even near infrared (NIR) region, tunable energy levels, good device stability, and easy synthesis and purification. For all these reasons, rapid progress has been made with these nonfullerene electron acceptors, which have led to impressive PCEs.8-35 \n\nRecently, indacenodithiophene (IDT) and indacenodithieno[3,2-b]thiophene (IDTT)-based fused-ring electron acceptors (FREAs) have attracted considerable attention.36-51 These FREAs exhibit broad and strong absorption, suitable lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) energy levels, and high electron mobility. OSCs based on these FREAs have exhibited high PCEs with small energy loss51 and good device stability.37 Most of these FREAs, such as ITIC,36 ITIC- $\\mathrm{\\cdot}\\mathrm{Th}^{37}$ and IDIC,38,48 are based on IDT or IDTT donor unit and 1,1-dicyanomethylene-3-indanone (IC) acceptor unit. \n\nIn this work, we design and synthesize an electron-rich unit 6,6,12,12-tetrakis(4-hexylphenyl)- indacenobis(dithieno[3,2-b;2',3'-d]thiophene) (IBDT) and three electron-deficient units fluorinated IC, to construct a small library of four FREAs (INIC series) based on IBDT end-capped with IC or fluorinated IC (Chart 1, Scheme 1). Our molecular design rationale is as follows. First, IBDT has larger rigid and coplanar structure and stronger electron-donating ability than IDT and IDTT, both of which are beneficial to enhancing the absorption and charge transport. Second, fluorinated IC has stronger electron-withdrawing ability than IC due to strong electronegativity of fluorine atom, and promotes intermolecular interactions through forming non-covalent F-S and F-H bonds, which is favorable for charge transport.52-54 Third, “acceptor−donor−acceptor” structure in INIC series can induce intramolecular charge transfer and lead to broad and strong absorption throughout the visible and even NIR region $500{-}850~\\mathrm{nm}$ ). Indeed, our results show that fluorinated INIC exhibit lower energy levels, red-shifted absorption, and higher electron mobility than nonfluorinated INIC. Furthermore, nonfullerene OSCs based on fluorinated INIC electron acceptor and a wide-bandgap polymer donor $\\mathrm{FTAZ^{55}}$ (Chart 1) exhibit PCEs as high as $11.5\\%$ , significantly higher than that of nonfluorinated INIC $(7.7\\%)$ . More importantly, with this series, we are able to investigate the effects of the number of fluorine atoms and their positions on electronic properties, charge transport, film morphology, and photovoltaic properties. \n\n![](images/9123916a55a521e332cb6a4fa93fe721bc4fbebc30375e22fdc7530b63427b04.jpg) \nChart 1. Chemical structures of INIC series and FTAZ. \n\n# ■ RESULTS AND DISCUSSION \n\nSynthesis and Characterization. The fluorinated IC moieties (2, 4 and 7) were synthesized from corresponding monofluorinated or difluorinated indanedione (1, 3, 6) and malononitrile (Scheme 1). Compound 4 is a mixture of two isomer, which was difficult to separate. Thus we used them together for the final condensation reaction without separation. Stille coupling reaction between compounds 8 and 9 with $\\mathrm{Pd}(\\mathrm{PPh}_{3})_{4}$ catalyst yielded compound 10. A double nucleophilic addition of (4-hexylphenyl)magnesium bromide to the ester groups in 10, followed by intramolecular cyclization via acid-mediated Friedel−Crafts reaction afforded IBDT (11). Compound 11 was lithiated by $n$ -butyllithium in THF solution at $-78{}^{\\circ}\\mathrm{C}$ , then quenched by dry DMF to afford aldehyde 12. INIC, \n\nINIC1, INIC2 and INIC3 were synthesized using Knoevenagel condensation reactions between IC, 2, 4, 7 and aldehyde 12, respectively. The new compounds were fully characterized by spectroscopic methods and elemental analysis (see Supporting Information). \n\nThe four INIC series compounds exhibit good solubility in organic solvents, such as chloroform (CF) and $o$ -dichlorobenzene (DCB). The thermal stability of these four molecules was investigated using thermogravimetric analysis (TGA) (Figure S1, Supporting Information). The TGA curves of four compounds show decomposition temperatures ( $T_{\\mathrm{d}},5\\%$ weight loss) varying from $302^{\\circ}\\mathrm{C}$ to 342 $^{\\circ}\\mathrm{C}$ , which indicate good thermal stability. \n\nThe UV-vis absorption spectra of INIC, INIC1, INIC2 and INIC3 were measured in chloroform solution and thin film. In solution, four molecules show similar absorption spectra shapes with peaks from $692~\\mathrm{nm}$ to $710~\\mathrm{nm}$ (Figure 1a), and similar molar extinction coefficients from $2.1\\times10^{5}\\mathrm{M}^{-1}$ $\\mathrm{cm}^{-1}$ to $2.5\\times10^{5}\\mathrm{M}^{-1}\\mathrm{cm}^{-1}$ at maximum absorption peaks (Table 1). In thin films, all four molecules show red-shifted and broader absorption spectra than their solutions. The absorption peaks of these four compounds red shift gradually from $706~\\mathrm{nm}$ to $744~\\mathrm{nm}$ (Figure 1b). Fluorination red-shifts the absorption of INIC: INIC2 with $\\mathrm{~F~}$ at meta-position exhibits red-shifted absorption relative to INIC1 with F at ortho-position, and INIC3 with two $\\mathrm{~F~}$ atoms exhibits red-shifted absorption relative to INIC1 and INIC2 with one F atom. The optical bandgaps of INIC, INIC1, INIC2 and INIC3 are calculated to be 1.57, 1.56, 1.52 and $1.48\\mathrm{eV}$ from the absorption edge, respectively (Table 1). \n\nCyclic voltammetry (CV) was employed to investigate the electrochemical properties of INIC, INIC1, INIC2 and INIC3 (Figure 1c). Four compounds exhibit irreversible reduction waves and quasi-reversible oxidation waves. The HOMO and LUMO energy levels are calculated from the onset oxidation and reduction potentials, assuming the absolute energy level of $\\mathrm{FeCp}_{2}^{+/0}$ to be $4.8\\:\\mathrm{eV}$ below vacuum. The HOMO levels of INIC, INIC1, INIC2 and INIC3 are estimated to be $-5.45\\mathrm{eV}$ to –5.54 eV and LUMO levels are $-3.88\\ \\mathrm{\\eV}$ to –4.02 eV (Figure 1d, Table 1). The fluorination down-shifts the molecular HOMO and LUMO levels. Specifically, INIC3 with two fluorines has lower LUMO level than INIC1 and INIC2 with one fluorine, whereas three fluorine-modified molecules show similar HOMO levels. The bandgap of INIC, INIC1, INIC2 and INIC3 estimated from the CV data is 1.57, 1.57, 1.54, and $1.50\\mathrm{eV},$ respectively, similar to the optical bandgaps. \n\n![](images/8c66d3c89a07a5c2baca5fdb3b0cf1f3767293354654b7de84fd61726b821803.jpg) \nScheme 1. Synthetic Routes for INIC, INIC1, INIC2 and INIC3. \n\n![](images/416403e3e617baf377451a49b9d843ee66624c10e6c86c3be03278142979e906.jpg) \n\n![](images/12cc3b00aefb042ebd17d485dac49318fb588244942142b54ca93d1fac51d710.jpg) \nFigure 1. (a) UV-vis absorption spectra of INIC, INIC1, INIC2 and INIC3 in chloroform and (b) as a \n\nthin film; (c) cyclic voltammograms for INIC, INIC1, INIC2 and INIC3 and (d) energy levels for FTAZ, INIC, INIC1, INIC2 and INIC3. \n\nTable 1. Absorption and Energy Levels of INIC, INIC1, INIC2 and INIC3 \n\n\n
compoundTdaAs, maxbAf maxEmaxdEgopt eHOMOfLUMOgEgv h
(nm) (nm)
INIC(C) 311692706(Ml cm-) 2.1 ×105(eV) 1.57(eV)(eV)(eV)
INIC13027107202.2 ×1051.56-5.45 -5.54-3.88 -3.971.57 1.57
INIC23427047282.1 ×1051.52-5.52-3.98
1.54
INIC33277107442.5 ×1051.48-5.52-4.021.50
\n\naThe decomposition temperature measured from TGA. bAbsorption maximum in solution. cAbsorption maximum in film. dMolar extinction coefficient at $\\lambda_{\\operatorname*{max}}$ in solution. eOptical bandgap calculated from the absorption edge of thin film. ${}^{f}\\mathrm{HOMO}$ energy level estimated from the onset oxidation potential. gLUMO energy level estimated from the onset reduction potential. hHOMO–LUMO gap estimated from CV. \n\nThe electron mobilities of four compounds were measured using the space charge-limited current (SCLC) method (Figure S2). The electron mobilities of INIC, INIC1, INIC2 and INIC3 are $6.1\\times10^{-5}$ , $1.0\\times10^{-4}$ , $1.2\\times{{10}^{-4}}$ and $1.7\\times10^{-4}\\ \\mathrm{cm}^{2}\\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ , respectively (Table S1). Fluorinated compounds, particularly difluorinated INIC3, exhibit higher mobility. \n\nPhotovoltaic Properties. Our previously reported wide-bandgap $(2.00\\mathrm{eV})$ polymer donor FTAZ exhibits strong absorption at $400{-}620~\\mathrm{{nm}}$ with a molar extinction coefficient of $9.8\\times10^{4}\\mathrm{M}^{-1}\\mathrm{cm}^{-1}$ , which is complementary with absorption of INIC series (Figure S3).55 The energy levels of FTAZ $(\\mathrm{HOMO}=-5.38~\\mathrm{eV}$ ; $\\mathrm{LUMO}=-3.17~\\mathrm{eV})$ match with those of INIC series (Figure 1d). FTAZ exhibits a high hole mobility of $1.2\\times10^{-3}\\ \\mathrm{cm}^{2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ ,56 matching with those of INIC series (Table S1). Thus, we used FTAZ as a donor and INIC series as acceptors to fabricate bulk heterojunction (BHJ) OSCs with a structure of indium tin oxide (ITO)/ZnO/FTAZ:acceptor $/\\mathrm{MoO}_{x}/\\mathrm{Ag}$ . The optimized FTAZ/acceptor weight ratio is 1:1.5 (Table S2). The optimized 1,8-diiodooctane (DIO) content is $0.25\\%$ DIO $\\left(\\mathbf{v}/\\mathbf{v}\\right)$ (Table S3). Table 2 summarizes the open circuit voltage $(V_{\\mathrm{OC}})$ , short circuit current density $(J_{\\mathrm{SC}})$ , fill factor (FF), and PCE of the optimized devices. The current density–voltage $(J{-}V)$ curves of the best PSCs are shown in Figure 2a. \n\nFluorination of INIC decreases average $V_{\\mathrm{OC}}$ of OSCs from 0.957 V to $0.857\\mathrm{~V~}$ , which is consistent with the trend of lowering LUMO by fluorination in INIC series. The OSCs based on nonfluorinated INIC show average $J_{\\mathrm{SC}}$ value of $13.51\\mathrm{\\mA}\\mathrm{cm}^{-2}$ , while fluorination of INIC enhances average $J_{\\mathrm{SC}}$ to $16.63{-}19.44~\\mathrm{mA}\\mathrm{cm}^{-2}$ . In particular, the OSCs based on difluorinated INIC3 show the highest $J_{\\mathrm{SC}}$ of $19.68\\mathrm{\\mA}\\mathrm{cm}^{-2}$ . The trend in fill factor (FF) is similar to that in $J_{\\mathrm{SC}}$ . The OSCs based on nonfluorinated INIC show average FF value of $57.9\\%$ , while fluorination of INIC enhances average FF to $64.3\\%67.4\\%$ . In particular, the OSCs based on difluorinated INIC3 show the highest FF of $68.5\\%$ . The best PCE of the OSCs based on nonfluorinated INIC is $7.7\\%$ , while the best PCE of the OSCs based on monofluorinated INIC1 and INIC2 is $10.1\\%$ and $10.8\\%$ , respectively. The OSCs based on difluorinated INIC3 show the best performance: $V_{\\mathrm{OC}}$ of 0.852 V, $J_{\\mathrm{SC}}$ of $19.68~\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ , FF of $68.5\\%$ , and PCE of $11.5\\%$ . Clearly, fluorination of INIC significantly enhances the performance of nonfullerene OSCs. The photon energy loss $(E_{\\mathrm{loss}})$ is calculated using the formula $E_{\\mathrm{loss}}=E_{\\mathrm{g}}-{\\mathrm e}V_{\\mathrm{OC}}$ .57,58 The $\\ensuremath{E_{\\mathrm{loss}}}$ values of the OSCs are $0.61{\\-}0.63\\ \\mathrm{eV}$ , which are relatively small. \n\nTable 2. Performance of the optimized OSCs based on FTAZ: acceptor. \n\n\n
deviceaVoc (V)Jsc (m)FF (%)PCE (%)calculated (m cm )Eloss (eV)
bestaverage b
FTAZ: INIC0.957±0.00613.51±0.1857.9±1.37.77.513.000.61
FTAZ: INIC10.929±0.00316.63±0.0664.3±0.410.19.915.930.63
FTAZ: INIC20.903±0.00417.56±0.2066.8±0.910.810.617.170.62
FTAZ: INIC30.857±0.00319.44±0.2467.4±1.011.511.219.130.62
\n\na FTAZ/acceptor $=1{:}1.5$ (w/w), $0.25\\%$ DIO (v/v). bAverage PCEs are obtained from 10 devices. \n\n![](images/bc6ddb857d8b42235b93fc3359dd2cc76e0f7ccef49feb1b8ee2e5a08d97a3ee.jpg) \n\n![](images/befb8d7eb3d3d2f53b6547e250d553d8b08a5c51c4a5f4df61eb7f71f518b6ec.jpg) \nFigure 2. (a) $J{-}V$ characteristics and (b) EQE spectra of the best OSCs under illumination of an AM \n\n$1.5\\mathrm{G}$ at $100\\mathrm{mW}\\mathrm{cm}^{-2}$ , (c) $J_{\\mathrm{ph}}$ versus $V_{\\mathrm{eff}}$ characteristics and (d) $J_{\\mathrm{SC}}$ versus light intensity of the optimized devices. \n\nThe external quantum efficiency (EQE) spectra of the optimized devices are shown in Figure 2b. The OSCs based on these four INIC acceptors show broad photoresponse extending from 300 to 850 nm. The maximum EQE values of INIC, INIC1, INIC2 and INIC3-based devices are $62.6\\%$ , $71.5\\%$ , 75.8 and $77.0\\%$ , respectively, indicating efficient charge generation and collection. In the NIR region, the IPCE spectra are broadened and enhanced gradually from INIC to INIC1, INIC2 and INIC3, resembling the absorption profile of the four INIC acceptors in the NIR region (Figure 1b). The $J_{\\mathrm{SC}}$ values of INIC, INIC1, INIC2 and INIC3-based devices calculated from integration of the EQE spectra with the AM 1.5G reference spectrum are 13.00, 15.93, 17.17 and $19.13~\\mathrm{\\mA~}\\mathrm{cm}^{-2}.$ , respectively, which are in good agreement with $J_{\\mathrm{SC}}$ values measured from $J{-}V$ (the error is $<5\\%$ , Table 2). \n\nTo probe the exciton/charge dynamics, we measured the photocurrent density $(J_{\\mathrm{ph}})$ versus the effective voltage $\\left(V_{\\mathrm{eff}}\\right)$ to study the charge generation, dissociation and extraction properties. $J_{\\mathrm{ph}}$ is defined as $J_{\\mathrm{L}}-J_{\\mathrm{D}},$ , where $J_{\\mathrm{L}}$ and $J_{\\mathrm{D}}$ are the photocurrent densities under illumination and in the dark, respectively. $V_{\\mathrm{eff}}$ is defined as $V_{0}-V_{\\mathrm{bias}},$ , where $V_{0}$ is the voltage at which photocurrent is zero and $V_{\\mathrm{bias}}$ is the applied voltage bias. In Figure 2c, $J_{\\mathrm{ph}}$ reaches saturation $\\left(J_{\\mathrm{sat}}\\right)$ at $2\\mathrm{~V~}$ , suggesting the charge recombination reach the minimal level and all the charge are collected by the electrodes. The charge dissociation probability $(P(E,T))$ can be calculated from $J_{\\mathrm{ph}}/J_{\\mathrm{sat}}$ . Under short-circuit condition, the $P(E,T)$ of INIC, INIC1, INIC2 and INIC3-based OSCs are $94.5\\%$ , $94.1\\%$ , $94.2\\%$ and $95.5\\%$ , respectively, indicating efficient charge dissociation and collection for all four INIC based OSCs. \n\nWe also measured the $J_{\\mathrm{SC}}$ versus light density $(P)$ curves to study charge recombination behavior (Figure 2d). The relationship between $J_{\\mathrm{SC}}$ and $P$ can be described as $J_{\\mathrm{sc}}\\propto P^{\\alpha}$ .59 If all the charges are swept out and collected by the electrode before recombination, $\\ensuremath{\\alpha}$ should be equal to 1, while $\\alpha<1$ means the existence of charge recombination. The $\\ensuremath{\\boldsymbol{a}}$ values of INIC, INIC1, INIC2 and INIC3-based OSCs are 0.983, 0.976, 0.981 and 0.98, respectively, suggesting negligible bimolecular charge recombination at the short circuit condition. \n\nThe hole mobility and electron mobility of the four blended films were measured using the SCLC method (Figure S4). The FTAZ: fluorinated INIC blends exhibit higher electron mobility than the FTAZ: INIC blend (Table S4), resembling the trend in pure INIC series (Table S1). Since hole mobilities of all the blended films are similar $\\left(1.8\\times{{10}^{-4}}\\right.$ to $3.0\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1})$ , the FTAZ: INIC blend shows unbalanced charge transport $(\\mu_{\\mathrm{h}}/\\mu_{\\mathrm{e}}=13)$ ), while the FTAZ: fluorinated INIC blends show more balanced charge transport $\\bar{\\mu_{\\mathrm{h}}}/\\mu_{\\mathrm{e}}=1.4$ to 2.4). Thus, the higher electron mobility and more balanced charge transport in the FTAZ: fluorinated INIC blends are one of the reasons for the higher $J_{\\mathrm{SC}}$ and higher FF in these fluorinated INIC-based devices (Table 2). \n\n# Film Morphology and Microstructure \n\nTo understand the active layer morphology, we first used atomic force microscope (AFM) to obtain the height and phase images of these four active layers (Figure S5). All four active layers (thin films) exhibit smooth surface morphology with a root-mean-square (RMS) roughness of $0.54\\mathrm{-}0.9\\ \\mathrm{nm}$ . We next employed grazing-incidence wide-angle and small-angle X-ray scattering (GIWAXS and GISAXS) measurements to probe the bulk morphology of these thin films.60,61 Figure 3a shows 2D GIWAXS patterns of FTAZ:INIC, FTAZ:INIC1, FTAZ:INIC2, FTAZ:INIC3 thin films. The films of FTAZ:INIC, FTAZ:INIC1, FTAZ:INIC2 exhibit preferential “face-on” oriented molecular packing with the lamellar peak located at $q_{\\mathrm{r}}\\approx0.32{\\mathrm{~}}\\mathring{\\mathrm{A}}^{-1}$ and the $\\pi{-}\\pi$ peak located at $q_{\\mathrm{z}}\\approx1.7\\textup{\\AA}^{-1}$ (Figure 3b), which agree with the corresponding peak positions of pure FTAZ (Figure S6), indicating that the mixing of FTAZ and INIC/INIC1/INIC2 preserves the favorable “face-on” oriented FTAZ semi-crystalline domains. Interestingly, the GIWAXS pattern of FTAZ:INIC3 is dramatically different: the face-on oriented domains present a sharp lamella peak at $q_{\\mathrm{r}}\\approx0.29{\\textrm{\\AA}}^{-1}$ and a $\\pi{-}\\pi$ peak at $q_{\\mathrm{z}}\\approx1.84\\mathrm{~\\AA}^{-1}$ , agreeing with the corresponding lattice constants of pure INIC3 (Figure S6). Therefore, the lamella peak appearing at $q_{\\mathrm{z}}=0.42\\ \\mathrm{\\AA^{-1}}$ , clearly visible in the out-of-plane direction (Figure 3b, right), should be assigned to “edge-on” oriented FTAZ domains. Notice that the lattice constant of FTAZ shrinks a lot $(d=2\\pi/\\mathrm{q}=15.0\\mathrm{~\\AA})$ compared with that of other films $(d=19.6\\mathrm{~\\AA~}$ ), indicating that the co-crystallization of FTAZ and INIC3 leads to a tighter packing of FTAZ. Thus, FTAZ/INIC3 blend films not only exhibit highest crystallinity compared with other three counterparts, but also maintain both FTAZ and INIC3 semi-crystalline packings. Although FTAZ domains reorient into relatively unfavorable “edge-on” orientation, INIC3 domains remain in the favorable “face-on” orientation. This is consistent with the highest electron mobility and more balanced electron and hole mobility observed in the FTAZ/INIC3 blend film. \n\nFigure 3c and Figure S7 present 2D GISAXS patterns, GISAXS intensity profiles and best fittings along the in-plane direction of pure FTAZ, pure acceptors and the FTAZ:acceptor blends. We adopt the Debye-Anderson-Brumberger (DAB) model, a polydispersed hard sphere model and a fractal-like network model61 to account for the scattering contribution from intermixing amorphous phases, FTAZ domains and acceptor domains, respectively. The FTAZ domains remain the same for the four blends $(\\sim4.5\\ \\mathrm{nm})$ and the acceptor domains are $15.6~\\mathrm{nm}$ , $14.5~\\mathrm{nm}$ , $23.1\\ \\mathrm{nm}$ , $17.6\\ \\mathrm{nm}$ for INIC, INIC1, INIC2, INIC3, respectively. The correlation lengths of the intermixing phase are 32.6 nm, $27.0\\ \\mathrm{nm}$ , $39.0\\ \\mathrm{{\\nm}}$ , $42.0\\ \\mathrm{nm}$ for FTAZ:INIC, FTAZ:INIC1, FTAZ:INIC2, FTAZ:INIC3, respectively. These results suggest that the nanoscale phase separation of all four films is in a reasonable range for efficient exciton dissociation. The stronger crystallinity of INIC3 doesn’t lead to undesirable micron size aggregation as observed in some small molecule acceptors with strong crystallinity.62 \n\n![](images/543080e2a46b865df8fb3b06188b2f43bde4c9058085b82eac52120308443794.jpg) \nFigure 3. a) 2D GIWAXS patterns. b) The corresponding GIWAXS intensity profiles along the \n\nin-plane (left) and out-of-plane (right) directions. c) The GISAXS intensity profiles and best fittings along the in-plane direction. \n\n# ■ CONCLUSIONS \n\nIn summary, four new fused-ring electron acceptors (FREAs), INIC, INIC1, INIC2 and INIC3, based on a fused-nonacyclic IBDT core end-capped with nonfluorinated or fluorinated IC were designed and synthesized for application in nonfullerene OSCs. These four molecules have strong absorption in the visible and even near-infrared region with high extinction coefficients of $2.1{-}2.5\\times$ $10^{5}~\\mathrm{M}^{-1}~\\mathrm{cm}^{-1}$ . Three fluorinated molecules INIC1, INIC2, and INIC3 show red-shifted absorption and lower HOMO/LUMO energy levels relative to the nonfluorinated INIC due to electron-withdrawing property of fluorine. The fluorinated molecules, particularly the difluorinated INIC3, have higher electron mobilities than INIC without fluorine substitution. FTAZ/INIC3 blend films not only exhibit highest crystallinity compared with other three counterparts, but also maintain both FTAZ and INIC3 semi-crystalline packings, possibly due to fluorine-induced intermolecular interactions. This is the main reason for the highest electron mobility and more balanced electron and hole mobility observed in the FTAZ/INIC3 blend film. The nanoscale phase separation of all the films is in a reasonable range for efficient exciton dissociation, and the stronger crystallinity of INIC3 doesn’t lead to undesirable micron size aggregation. Since the wide-bandgap polymer donor FTAZ and the narrow-bandgap INIC series acceptors exhibit complementary absorption, matched energy levels and matched mobility, the nonfullerene OSCs based on FTAZ:INIC series blends exhibit small energy loss of $0.61{\\-}0.63\\ \\mathrm{eV}$ , yet efficient charge dissociation and collection, negligible bimolecular charge recombination, and finally high PCEs of $7.7\\mathrm{-}11.5\\%$ . Fluorination of INIC significantly enhances the PCE from $7.7\\%$ to $51\\%$ , in particular, the OSCs based on difluorinated \n\nINIC3 show the best PCE of $11.5\\%$ . These results demonstrate the great potential of the new IBDT and fluorinated IC building blocks for constructing high-performance nonfullerene acceptors. \n\n# ■ ASSOCIATED CONTENT \n\n# Supporting Information \n\nDetailed experimental procedures including synthesis, characterization and device fabrication, and additional characterization data, such as TGA, SCLC, AFM, GIWAXS and GISAXS. These materials are available free of charge via the Internet at http://pubs.acs.org. \n\n# ■ AUTHOR INFORMATION \n\n# Corresponding Author \n\n\\* E-mail: xwzhan@pku.edu.cn \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ■ ACKNOWLEDGMENT \n\nX.Z. wish to thank the 973 Program (No. 2013CB834702) and the NSFC (No. 91433114). T.L. and X.L. acknowledge the financial support from RGC of Hong Kong GRF (No. 14303314) and CUHK Direct Grant (no. 4053128). Q.Z., and W.Y. were supported by the Office of Naval Research (No. N000141410221) and NSF (No. DMR-1507249). \n\n# ■ REFERENCES \n\n(1) Cheng, Y. J.; Yang, S. H.; Hsu, C. S. Chem. Rev. 2009, 109, 5868. \n(2) Lu, L.; Zheng, T.; Wu, Q.; Schneider, A. M.; Zhao, D.; Yu, L. Chem. Rev. 2015, 115, 12666. \n\n# Journal of the American Chemical Society \n\n(3) Lin, Y.; Zhan, X. Acc. Chem. Res. 2016, 49, 175. (4) Chen, C.-C.; Chang, W.-H.; Yoshimura, K.; Ohya, K.; You, J.; Gao, J.; Hong, Z.; Yang, Y. \nAdv. Mater. 2014, 26, 5670. (5) Zhou, H.; Zhang, Y.; Mai, C. K.; Collins, S. D.; Bazan, G. C.; Nguyen, T. Q.; Heeger, A. J. \nAdv. Mater. 2015, 27, 1767. (6) Zhao, J.; Li, Y.; Yang, G.; Jiang, K.; Lin, H.; Ade, H.; Ma, W.; Yan, H. Nat. Energy 2016, 1, \n15027. (7) Li, M.; Gao, K.; Wan, X.; Zhang, Q.; Kan, B.; Xia, R.; Liu, F.; Yang, X.; Feng, H.; Ni, W.; \nWang, Y.; Peng, J.; Zhang, H.; Liang, Z.; Yip, H.-L.; Peng, X.; Cao, Y.; Chen, Y. Nat. Photon. 2016, \nDOI: 10.1038/nphoton.2016.240. (8) Zhan, X.; Facchetti, A.; Barlow, S.; Marks, T. J.; Ratner, M. A.; Wasielewski, M. R.; Marder, \nS. R. Adv. Mater. 2011, 23, 268. (9) Lin, Y.; Zhan, X. Mater. Horiz. 2014, 1, 470. (10)Zhong, Y.; Trinh, M. T.; Chen, R.; Purdum, G. E.; Khlyabich, P. P.; Sezen, M.; Oh, S.; Zhu, \nH.; Fowler, B.; Zhang, B.; Wang, W.; Nam, C. Y.; Sfeir, M. Y.; Black, C. T.; Steigerwald, M. L.; Loo, \nY. L.; Ng, F.; Zhu, X. Y.; Nuckolls, C. Nat. Commun. 2015, 6, 8242. (11) Zhong, Y.; Trinh, M. T.; Chen, R.; Wang, W.; Khlyabich, P. P.; Kumar, B.; Xu, Q.; Nam, \nC.-Y.; Sfeir, M. Y.; Black, C.; Steigerwald, M. L.; Loo, Y.-L.; Xiao, S.; Ng, F.; Zhu, X. Y.; Nuckolls, \nC. J. Am. Chem. Soc. 2014, 136, 15215. (12)Wu, Q.; Zhao, D.; Schneider, A. M.; Chen, W.; Yu, L. J. Am. Chem. Soc. 2016, 138, 7248. (13) Meng, D.; Sun, D.; Zhong, C.; Liu, T.; Fan, B.; Huo, L.; Li, Y.; Jiang, W.; Choi, H.; Kim, T.; \nKim, J. Y.; Sun, Y.; Wang, Z.; Heeger, A. J. J. Am. Chem. Soc. 2016, 138, 375. (14) Meng, D.; Fu, H.; Xiao, C.; Meng, X.; Winands, T.; Ma, W.; Wei, W.; Fan, B.; Huo, L.; \nDoltsinis, N. L.; Li, Y.; Sun, Y.; Wang, Z. J. Am. Chem. Soc. 2016, 138, 10184. (15) Sun, D.; Meng, D.; Cai, Y.; Fan, B.; Li, Y.; Jiang, W.; Huo, L.; Sun, Y.; Wang, Z. J. Am. \nChem. Soc. 2015, 137, 11156. (16) Lee, J.; Singh, R.; Sin, D. H.; Kim, H. G.; Song, K. C.; Cho, K. Adv. Mater. 2016, 28, 69. (17)Zhong, H.; Wu, C.-H.; Li, C.-Z.; Carpenter, J.; Chueh, C.-C.; Chen, J.-Y.; Ade, H.; Jen, A. K. \nY. Adv. Mater. 2016, 28, 951. (18) Lin, H.; Chen, S.; Hu, H.; Zhang, L.; Ma, T.; Lai, J. Y.; Li, Z.; Qin, A.; Huang, X.; Tang, B.; \nYan, H. Adv. Mater. 2016, 28, 8546. (19) Liu, Y.; Mu, C.; Jiang, K.; Zhao, J.; Li, Y.; Zhang, L.; Li, Z.; Lai, J. Y.; Hu, H.; Ma, T.; Hu, \nR.; Yu, D.; Huang, X.; Tang, B. Z.; Yan, H. Adv. Mater. 2015, 27, 1015. (20) Liu, J.; Chen, S.; Qian, D.; Gautam, B.; Yang, G.; Zhao, J.; Bergqvist, J.; Zhang, F.; Ma, W.; \nAde, H.; Inganäs, O.; Gundogdu, K.; Gao, F.; Yan, H. Nat. Energy 2016, 1, 16089. (21)Zhang, X.; Lu, Z.; Ye, L.; Zhan, C.; Hou, J.; Zhang, S.; Jiang, B.; Zhao, Y.; Huang, J.; Zhang, \nS.; Liu, Y.; Shi, Q.; Liu, Y.; Yao, J. Adv. Mater. 2013, 25, 5791. (22)Zhan, X.; Tan, Z. a.; Domercq, B.; An, Z.; Zhang, X.; Barlow, S.; Li, Y.; Zhu, D.; Kippelen, \nB.; Marder, S. R. J. Am. Chem. Soc. 2007, 129, 7246. (23)Lin, Y.; Wang, Y.; Wang, J.; Hou, J.; Li, Y.; Zhu, D.; Zhan, X. Adv. Mater. 2014, 26, 5137. (24)Sharenko, A.; Proctor, C. M.; van der Poll, T. S.; Henson, Z. B.; Nguyen, T.-Q.; Bazan, G. C. (25)Shivanna, R.; Shoaee, S.; Dimitrov, S.; Kandappa, S. K.; Rajaram, S.; Durrant, J. R.; \nNarayan, K. S. Energy Environ. Sci. 2014, 7, 435. (26)Guo, Y.; Li, Y.; Awartani, O.; Zhao, J.; Han, H.; Ade, H.; Zhao, D.; Yan, H. Adv. Mater. 2016, \n28, 8483. (27) Hartnett, P. E.; Timalsina, A.; Matte, H. S.; Zhou, N.; Guo, X.; Zhao, W.; Facchetti, A.; \nChang, R. P.; Hersam, M. C.; Wasielewski, M. R.; Marks, T. J. J. Am. Chem. Soc. 2014, 136, 16345. (28) Gao, L.; Zhang, Z. G.; Xue, L.; Min, J.; Zhang, J.; Wei, Z.; Li, Y. Adv. Mater. 2016, 28, \n1884. (29)Earmme, T.; Hwang, Y.-J.; Murari, N. M.; Subramaniyan, S.; Jenekhe, S. A. J. Am. Chem. \nSoc. 2013, 135, 14960. (30)Li, H.; Hwang, Y.-J.; Courtright, B. A. E.; Eberle, F. N.; Subramaniyan, S.; Jenekhe, S. A. \nAdv. Mater. 2015, 27, 3266. (31)Li, H.; Kim, F. S.; Ren, G.; Hollenbeck, E. C.; Subramaniyan, S.; Jenekhe, S. A. Angew. \nChem. Int. Ed. 2013, 52, 5513. (32)Zhou, E.; Cong, J.; Hashimoto, K.; Tajima, K. Adv. Mater. 2013, 25, 6991. (33)Zhou, Y.; Kurosawa, T.; Ma, W.; Guo, Y.; Fang, L.; Vandewal, K.; Diao, Y.; Wang, C.; Yan, \nQ.; Reinspach, J.; Mei, J.; Appleton, A. L.; Koleilat, G. I.; Gao, Y.; Mannsfeld, S. C. B.; Salleo, A.; \nAde, H.; Zhao, D.; Bao, Z. Adv. Mater. 2014, 26, 3767. (34) Zhou, Y.; Ding, L.; Shi, K.; Dai, Y. Z.; Ai, N.; Wang, J.; Pei, J. Adv. Mater. 2012, 24, 957. (35)Dou, C.; Long, X.; Ding, Z.; Xie, Z.; Liu, J.; Wang, L. Angew. Chem. Int. Ed. 2016, 55, \n\n1436. \n\n(36) Lin, Y.; Wang, J.; Zhang, Z.-G.; Bai, H.; Li, Y.; Zhu, D.; Zhan, X. Adv. Mater. 2015, 27, \n1170. (37) Lin, Y.; Zhao, F.; He, Q.; Huo, L.; Wu, Y.; Parker, T. C.; Ma, W.; Sun, Y.; Wang, C.; Zhu, D.; \nHeeger, A. J.; Marder, S. R.; Zhan, X. J. Am. Chem. Soc. 2016, 138, 4955. (38)Lin, Y.; He, Q.; Zhao, F.; Huo, L.; Mai, J.; Lu, X.; Su, C. J.; Li, T.; Wang, J.; Zhu, J.; Sun, Y.; \nWang, C.; Zhan, X. J. Am. Chem. Soc. 2016, 138, 2973. (39)Holliday, S.; Ashraf, R. S.; Wadsworth, A.; Baran, D.; Yousaf, S. A.; Nielsen, C. B.; Tan, C. \nH.; Dimitrov, S. D.; Shang, Z.; Gasparini, N.; Alamoudi, M.; Laquai, F.; Brabec, C. J.; Salleo, A.; \nDurrant, J. R.; McCulloch, I. Nat. Commun. 2016, 7, 11585. (40) Liu, W.; Li, S.; Huang, J.; Yang, S.; Chen, J.; Zuo, L.; Shi, M.; Zhan, X.; Li, C.-Z.; Chen, H. \nAdv. Mater. 2016, 28, 9729. (41) Bin, H.; Zhang, Z. G.; Gao, L.; Chen, S.; Zhong, L.; Xue, L.; Yang, C.; Li, Y. J. Am. Chem. \nSoc. 2016, 138, 4657. (42)Bin, H.; Gao, L.; Zhang, Z.-G.; Yang, Y.; Zhang, Y.; Zhang, C.; Chen, S.; Xue, L.; Yang, C.; \nXiao, M.; Li, Y. Nat. Commun. 2016, 7, 13651. (43) Yang, Y.; Zhang, Z. G.; Bin, H.; Chen, S.; Gao, L.; Xue, L.; Yang, C.; Li, Y. J. Am. Chem. \nSoc. 2016, 138, 15011. (44)Baran, D.; Ashraf, R. S.; Hanifi, D. A.; Abdelsamie, M.; Gasparini, N.; Rohr, J. A.; Holliday, \nS.; Wadsworth, A.; Lockett, S.; Neophytou, M.; Emmott, C. J. M.; Nelson, J.; Brabec, C. J.; \nAmassian, A.; Salleo, A.; Kirchartz, T.; Durrant, J. R.; McCulloch, I. Nat. Mater. 2016, DOI: \n\n# Journal of the American Chemical Society \n\n(45)Li, S.; Ye, L.; Zhao, W.; Zhang, S.; Mukherjee, S.; Ade, H.; Hou, J. Adv. Mater. 2016, 28, 9423. (46) Yao, H.; Chen, Y.; Qin, Y.; Yu, R.; Cui, Y.; Yang, B.; Li, S.; Zhang, K.; Hou, J. Adv. Mater. 2016, 28, 8283. (47) Li, Z.; Jiang, K.; Yang, G.; Lai, J. Y.; Ma, T.; Zhao, J.; Ma, W.; Yan, H. Nat. Commun. 2016, 7, 13094. (48) Lin, Y.; Zhao, F.; Wu, Y.; Chen, K.; Xia, Y.; Li, G.; Prasad, S. K.; Zhu, J.; Huo, L.; Bin, H.; Zhang, Z. G.; Guo, X.; Zhang, M.; Sun, Y.; Gao, F.; Wei, Z.; Ma, W.; Wang, C.; Hodgkiss, J.; Bo, Z.; Inganas, O.; Li, Y.; Zhan, X. Adv. Mater. 2016, DOI: 10.1002/adma.201604155. (49)Lin, Y.; Zhang, Z.-G.; Bai, H.; Wang, J.; Yao, Y.; Li, Y.; Zhu, D.; Zhan, X. Energy Environ. Sci. 2015, 8, 610. (50)Wu, Y.; Bai, H.; Wang, Z.; Cheng, P.; Zhu, S.; Wang, Y.; Ma, W.; Zhan, X. Energy Environ. Sci. 2015, 8, 3215. (51) Cheng, P.; Zhang, M.; Lau, T.; Wu, Y.; Jia, B.; Wang, J.; Yan, C.; Qin, M.; Lu, X.; Zhan, X. Adv. Mater. 2016, DOI: 10.1002/adma.201605216. (52)Lei, T.; Xia, X.; Wang, J.-Y.; Liu, C.-J.; Pei, J. J. Am. Chem. Soc. 2014, 136, 2135. (53)Sakamoto, Y.; Komatsu, S.; Suzuki, T. J. Am. Chem. Soc. 2001, 123, 4643. (54)Kim, H. G.; Kang, B.; Ko, H.; Lee, J.; Shin, J.; Cho, K. Chem. Mater. 2015, 27, 829. (55)Price, S. C.; Stuart, A. C.; Yang, L.; Zhou, H.; You, W. J. Am. Chem. Soc. 2011, 133, 4625. (56) Li, W.; Albrecht, S.; Yang, L.; Roland, S.; Tumbleston, J. R.; McAfee, T.; Yan, L.; Kelly, M. A.; Ade, H.; Neher, D.; You, W. J. Am. Chem. Soc. 2014, 136, 15566. \n\n(57)Veldman, D.; Meskers, S. C. J.; Janssen, R. A. J. Adv. Funct. Mater. 2009, 19, 1939. (58)Kawashima, K.; Fukuhara, T.; Suda, Y.; Suzuki, Y.; Koganezawa, T.; Yoshida, H.; Ohkita, H.; Osaka, I.; Takimiya, K. J. Am. Chem. Soc. 2016, 138, 10265. (59)Schilinsky, P.; Waldauf, C.; Brabec, C. J. Appl. Phys. Lett. 2002, 81, 3885. (60)Lu, X.; Hlaing, H.; Germack, D. S.; Peet, J.; Jo, W. H.; Andrienko, D.; Kremer, K.; Ocko, B. M. Nat. Commun. 2012, 3, 795. (61) Mai, J.; Lau, T.-K.; Li, J.; Peng, S.-H.; Hsu, C.-S.; Jeng, U. S.; Zeng, J.; Zhao, N.; Xiao, X.; Lu, X. Chem. Mater. 2016, 28, 6186. (62) Shin, W. S.; Jeong, H.-H.; Kim, M.-K.; Jin, S.-H.; Kim, M.-R.; Lee, J.-K.; Lee, J. W.; Gal, Y.-S. J. Mater. Chem. 2006, 16, 384. \n\nFor Table of Contents use only \n\n![](images/b54a2792f9d9d478e3702d59213a40b969dbb812faacfcb18ff37b8c677f64d1.jpg) " + }, + { + "id": "10.1038_ncomms15640", + "DOI": "10.1038/ncomms15640", + "DOI Link": "http://dx.doi.org/10.1038/ncomms15640", + "Relative Dir Path": "mds/10.1038_ncomms15640", + "Article Title": "Ultra-bright and highly efficient inorganic based perovskite light-emitting diodes", + "Authors": "Zhang, LQ; Yang, XL; Jiang, Q; Wang, PY; Yin, ZG; Zhang, XW; Tan, HR; Yang, Y; Wei, MY; Sutherland, BR; Sargent, EH; You, JB", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Inorganic perovskites such as CsPbX3 (X = Cl, Br, I) have attracted attention due to their excellent thermal stability and high photoluminescence quantum efficiency. However, the electroluminescence quantum efficiency of their light-emitting diodes was <1%. We posited that this low efficiency was a result of high leakage current caused by poor perovskite morphology, high non-radiative recombination at interfaces and perovskite grain boundaries, and also charge injection imbalance. Here, we incorporated a small amount of methylammonium organic cation into the CsPbBr3 lattice and by depositing a hydrophilic and insulating polyvinyl pyrrolidine polymer atop the ZnO electron-injection layer to overcome these issues. As a result, we obtained light-emitting diodes exhibiting a high brightness of 91,000 cd m(-2) and a high external quantum efficiency of 10.4% using a mixed-cation perovskite Cs(0.87)MA(0.13)PbBr(3) as the emitting layer. To the best of our knowledge, this is the brightest and most-efficient green perovskite light-emitting diodes reported to date.", + "Times Cited, WoS Core": 791, + "Times Cited, All Databases": 850, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000402804700001", + "Markdown": "# Ultra-bright and highly efficient inorganic based perovskite light-emitting diodes \n\nLiuqi Zhang1, Xiaolei Yang1, Qi Jiang1, Pengyang Wang1, Zhigang Yin1,2, Xingwang Zhang1,2, Hairen Tan3, Yang (Michael) Yang4, Mingyang Wei3, Brandon R. Sutherland3, Edward H. Sargent3 & Jingbi You1,2 \n\nInorganic perovskites such as $\\mathsf{C s P b}\\mathsf{X}_{3}$ $\\mathsf{X}=\\mathsf{C l}$ , Br, I) have attracted attention due to their excellent thermal stability and high photoluminescence quantum efficiency. However, the electroluminescence quantum efficiency of their light-emitting diodes was $<1\\%$ . We posited that this low efficiency was a result of high leakage current caused by poor perovskite morphology, high non-radiative recombination at interfaces and perovskite grain boundaries, and also charge injection imbalance. Here, we incorporated a small amount of methylammonium organic cation into the ${\\mathsf{C s P b}}{\\mathsf{B}}{\\mathsf{r}}_{3}$ lattice and by depositing a hydrophilic and insulating polyvinyl pyrrolidine polymer atop the ZnO electron-injection layer to overcome these issues. As a result, we obtained light-emitting diodes exhibiting a high brightness of $91,000{\\mathsf{c d}}{\\mathsf{m}}^{-2}$ and a high external quantum efficiency of $10.4\\%$ using a mixed-cation perovskite $\\mathsf{C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3}$ as the emitting layer. To the best of our knowledge, this is the brightest and most-efficient green perovskite light-emitting diodes reported to date. \n\nrganic–inorganic perovskites have received extensive attention in recent years in view of their attractive electrical and optical properties. Solution-processed perovskite solar cells have demonstrated a high certified power conversion efficiency of $22.1\\%$ , which is comparable to photovoltaics made from traditional inorganic semiconductor materials such as Si, CIGS and CdTe (refs 1–8). In addition, they have been utilized as efficient low-threshold gain media in optically pumped lasers9,10. Perovskite materials exhibit high photoluminescence quantum yield (PLQY, $>90\\%$ in solution for nanocrystals) and high colour purity with narrow emission linewidths $<20\\mathrm{nm}$ (refs 11–15). These features make them promising candidates as new materials for light-emitting diodes (LEDs). \n\nElectroluminescence (EL) from trihalide organic–inorganic perovskite-based LEDs (PeLEDs) was first reported in 2014 (ref. 16). The peak brightness of these LEDs was of order $300\\mathrm{cd}\\mathrm{m}^{-2}$ at green wavelengths, and the external quantum efficiency (EQE) from $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{\\bar{P}b I}_{3-x}\\mathrm{Cl}_{x}$ ( $754\\mathrm{nm}$ emission, red) and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ - $517\\mathrm{nm}$ emission, green) based LEDs were 0.76 and $0.1\\%$ , respectively16. By interface engineering and perovskite layer optimization, the EQE was increased to over $3\\%$ (refs 17–27). A breakthrough in organic–inorganic PeLEDs was achieved by controlling the crystallization process of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ by adopting a nanocrystal pinning method. As a result, a dense film with small crystal domains $\\left(<100\\mathrm{nm}\\right)$ was obtained, effectively confining charge carriers. These devices demonstrated an impressive EQE of $8.53\\%$ (ref. 28). More recently, by confining electrons and holes to two-dimensional (2D) perovskites29, Yuan et al. and Wang et al. obtained near-infrared EQEs of 8.8 and $11.7\\%$ , respectively30,31. Combined with nanocrystal pinning and 2D perovskites, Rand et al. also achieved close to $10\\%$ EQE of organic–inorganic LEDs32. \n\nCompared with monovalent organic cation-based lead-halide perovskites, all inorganic perovskites exhibit improved thermal stability and more efficient PL, making them attractive in a number of optoelectronic device applications14,15,33,34. Inorganic perovskites such as $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ $\\mathrm{{\\langleX=Cl_{\\it{i}}}}$ Br, I) have attracted great attention due to their improved thermal stability and higher PLQY in comparison with organic-cation perovskites. Recently, $\\mathrm{CsPb}{\\mathrm{X}}_{3}$ nanocrystals have been successfully synthesized and used as emitting materials for $\\mathrm{LEDs}^{14,15}$ . $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ thin film-based LEDs have also been demonstrated34. However, the EQE of the LEDs based on these materials remain $<1\\%$ (refs 15,34). During revising of this manuscript, Li et al. and Ling et al. both reported inorganic $\\mathrm{CsPbBr}_{3}$ LEDs with about $6\\%$ EQE by surface passivation of perovskite nanocrystals and controlling perovskite thin film morphology, respectively35,36. There is still much more room for improvement in brightness and efficiency. The low efficiency may arise from high leakage current due to poor morphology (high density of pinholes), significant nonradiative recombination at the interface of perovskite/injection layers and within the perovskite layer itself and charge injection imbalance15,34. \n\nIn this report, we achieved high-quality dense $\\mathrm{CsPbBr}_{3}$ perovskite thin films by incorporating a small amount of organic methylammonium cation into the lattice and by using a hydrophilic insulating polymer interface layer on top of the $\\mathrm{znO}$ electron-injecting electrode. We fabricated high performance mixed-cation perovskite LEDs with an active layer composition of $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ . These LEDs exhibited a peak brightness of $91,000{\\ c d}\\mathrm{m}^{-2}$ and a peak EQE of $10.43\\%$ . This represents the brightest and most-efficient green perovskite LEDs reported to date28,30,31. \n\n# Results \n\nMorphology of $\\mathbf{CsPbBr}_{3}$ films. $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ perovskite thin films were fabricated by spin-coating a $\\mathrm{CsBr:PbBr}_{2}$ precursor from dimethyl sulfoxide (DMSO) onto substrates, followed by annealing at $100^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ to remove residual solvent and to induce perovskite crystallization. A high ratio of $\\mathrm{CsBr:PbBr}_{2}$ (2.2:1) precursor solution was used to guarantee the formation of pure phase $\\mathrm{CsPbBr}_{3}$ , while the excess CsBr would be readily precipitated during solution stirring33. As shown in Fig. 1a, the perovskite film directly deposited onto the electron-injection layer of $\\mathrm{{}}Z\\mathrm{{nO}}$ exhibited a high density of pinholes. To improve the surface morphology, we first introduced a thin hydrophilic insulating polymer, polyvinyl pyrrolidine (PVP), between the $\\mathrm{{}}Z\\mathrm{{nO}}$ and perovskite layers. The density of pinholes was largely reduced by inserting the PVP intermediate layer, as shown in Fig. 1b. Real-time contact angle results showed that PVP-modified $\\mathrm{znO}$ films have increased hydrophilicity (Supplementary Fig. 1). As a result, the PVP-modified substrate has better wetting of the hydrophilic perovskite precursor solution, leading to uniform growth of perovskite films with reduced pinholes. Although the perovskite film surface coverage was significantly improved by introducing the PVP intermediate layer, there was still an appreciable density of pinholes. To improve further the morphology of the perovskite film, we added a small amount of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Br}$ (MABr) into the precursor solution. We hypothesized that molecular pinning would help reduce pinholes by better controlling the crystallization kinetics of the $\\mathrm{Cs}\\bar{\\mathrm{Pb}}\\mathrm{Br}_{3}$ films37,38. Figure 1c shows that the morphology of the perovskite film was improved considerably once we did add MABr, leading to now a negligible density of pinholes, which could be good for reducing current leakage in LEDs. \n\nCrystal and band structure of $\\mathbf{CsPbBr}_{3}$ films. We characterized the crystal structure of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ films deposited on bare $\\mathrm{znO}$ and $\\mathrm{ZnO/\\dot{P}V P}$ substrates, and on $\\mathrm{ZnO/PVP}$ with the MABr additive. X-ray diffraction pattern of these three films were almost identical, with all crystallographic signatures matching that of the pure $\\mathrm{CsPbBr}_{3}$ phase (Supplementary Fig. 2). The band structure of $\\mathrm{CsPbBr}_{3}$ films with and without the MABr additive were determined using ultraviolet photoelectron spectroscopy (UPS; Supplementary Fig. 3, Supplementary Table 1) in combination with linear absorption measurements (Supplementary Fig. 4). The conduction and valence band relative to vacuum of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ with MABr are located at $-3.37$ and $-5.71\\mathrm{eV}$ , respectively. This could form a good alignment with electron-injecting layer such as $\\mathrm{{}}Z\\mathrm{{nO}}$ $(-3.8\\bar{4}\\mathrm{eV}$ ; Supplementary Fig. 5) and hole-injecting such as CBP $\\left(-6.0\\mathrm{eV}\\right)^{39}$ (Fig. 3b). \n\nChemical states of $\\mathbf{CsPbBr}_{3}$ films. We also carried out X-ray photoelectron spectroscopy (XPS) measurements on $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ films with and without the MABr additive (Supplementary Figs 6 and 7). The $\\mathrm{Pb}$ 4f core level from pure $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ can be fit to four peaks (Supplementary Fig. 7). Two main peaks are located at $138.9\\mathrm{eV}$ $\\mathrm{(Pb~4f_{7/2})}$ and $142.8\\mathrm{eV}$ (Pb $4f_{5/2,}$ ), which correspond to $\\operatorname{Pb-Br}$ bonding28,40. Two additional weaker peaks at 137.1 and $141.9\\mathrm{eV}$ can be attributed to $\\mathrm{\\Pb}$ metallic states28,40. After incorporating MABr into the $\\mathrm{CsPbBr}_{3}$ lattice, only $\\mathrm{\\Pb{-}B r}$ peaks were found, indicating that $\\mathrm{Pb}$ metallic states, which are known to function as non-radiative recombination centres28,40, have been suppressed. \n\nPhotoluminescence of $\\mathbf{CsPbBr}_{3}$ films. We carried out steady-state PL on $\\mathrm{CsPbBr}_{3}$ thin films deposited from different conditions (Fig. 2a). The $\\mathrm{CsPbBr}_{3}$ films directly deposited on $\\mathrm{{}}Z\\mathrm{{nO}}$ showed weak green emission at $524\\mathrm{nm}$ with a full width at half maximum (FWHM) of $24\\mathrm{nm}$ . Perovskites deposited onto the PVP-modified $\\mathrm{znO}$ showed a dramatic increase in PL intensity, indicating that non-radiative recombination in the perovskite layer or at the interfaces has been significantly suppressed. The enhancement of PL is posited to arise from several phenomena. First, the improved morphology may reduce non-radiative recombination at grain boundaries (Fig. 1a,b), leading to enhanced PL. Second, PVP could passivate $\\mathrm{znO}$ surface defects41, which could act as non-radiative recombination traps at the interface of $\\mathrm{ZnO}/$ perovskite. After PVP modification, the PL emission intensity and carrier lifetime of $\\mathrm{znO}$ increased considerably (Supplementary Fig. 8), indicating a reduced surface defects of $\\mathrm{znO}$ with PVP layer. Similar enhancement were also observed while coating PVP on perovskite surface, further confirming our argument (Supplementary Fig. 8). \n\n![](images/9d4692cf535e78dfae68d27ecdeae01dfbfc6daa9658065dbe752aba46c1cc2c.jpg) \nFigure 1 | Morphology of $\\mathsf{c s P b}\\mathsf{B r}_{3}$ films deposited under different conditions. (a–c) Planar SEM images of $\\mathsf{C s P b B r}_{3}$ deposited on ZnO, ZnO/PVP an $\\mathsf{C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3}$ on $Z_{\\mathsf{I}{\\mathsf{I}}}{\\mathsf{O}}/{\\mathsf{P}}{\\mathsf{V}}{\\mathsf{P}},$ respectively, here PVP is polyvinyl pyrrolidine. The scale bar is $2\\upmu\\mathrm{m}$ in all images. \n\n![](images/6e9502c675e9d03e68d794d519f02a51adcb76cdf69ca56cd8957abca90b5357.jpg) \nFigure 2 | PL behaviour of $\\cos P b B r_{3}$ films deposited under different conditions. (a) Steady-state PL of $\\mathsf{C s P b B r}_{3}$ films on $Z n O$ , $Z_{\\mathsf{I}\\mathsf{{n O}}/\\mathsf{P}\\mathsf{V}\\mathsf{P}}$ and $\\mathsf{C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3}$ film on $Z_{\\mathsf{n O}}/{\\mathsf{P V P}},$ respectively, here PVP is polyvinyl pyrrolidine, MA is $C H_{3}N H_{3}$ . (b) Time-resolved $P L$ of $\\mathsf{C s P b B r}_{3}$ films on $Z n O$ and $Z_{\\mathsf{I}\\mathsf{I}}{\\mathsf{O}}/{\\mathsf{P}}{\\mathsf{V}}{\\mathsf{P}}$ and $\\mathsf{C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3}$ on ZnO/PVP. (c) PL image of $\\mathsf{C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3}$ films on $Z_{\\mathsf{I}\\mathsf{{n O}}/\\mathsf{P}\\mathsf{V}\\mathsf{P}}$ under ultraviolet lamp excitation. (d) PLQY of $\\mathsf{C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3}$ as a function of excitation power density. \n\nThe PL was further improved by introducing MABr into the $\\mathrm{CsPbBr}_{3}$ lattice. This increase in PL intensity is consistent with the reduction of perovskite grain boundaries, as well as the suppression of Pb metallic recombination centres, which were confirmed by scanning electron microscopy (SEM) and XPS results, respectively (Fig. 1c and Supplementary Fig. 7). The emission peak from $\\mathrm{CsPbBr}_{3}$ has been slightly shifted from 524 to $526\\mathrm{nm}$ after adding MABr, indicating that a small fraction of MA cations have been introduced into the $\\mathrm{CsPbBr}_{3}$ crystal lattice. A single Gaussian emission peak at $526\\mathrm{nm}$ shows that the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ layer with MABr additive is a pure perovskite phase, which could be ascribed to the formation of an alloy phase of $\\mathrm{Cs}_{1-x}\\mathrm{MA}_{x}\\mathrm{Pb}\\mathrm{Br}_{3}$ . We estimate that the MA content in this alloyed perovskite is 0.13, that is, $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ -based on the band-edge emission as shown in Fig. 2a, and the band-edge emission form pure $\\mathbf{MAPb}\\mathbf{B}\\mathbf{r}_{3}$ $(540\\mathrm{nm})^{28}$ according to the linear relationship $\\mathrm{E_{g,Cs1-\\boldsymbol{x}M A\\boldsymbol{x}P b B r3}=(1-\\boldsymbol{x})E_{g,C s P b B r_{3}}+\\boldsymbol{x}E_{g,M A P b B r3}}$ (ref. 42). The final MABr content in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ as estimated from the change in bandgap is approximately consistent with the initial precursor composition where $\\mathrm{CsBr{:}P b B r_{2}{:}M A B r=2.2{:}1{:}0.1}$ and only 1 mol CsBr contributes to the formation of $\\mathrm{CsPbBr}_{3}$ and the initial MABr ratio is $0.1\\mathrm{mol}$ The linear absorption of $\\mathrm{CsPbBr}_{3}$ with and without MABr was consistent with the PL results (Supplementary Fig. 4). We further observed that the PL FWHM narrowed from $24\\mathrm{nm}$ to $18\\mathrm{nm}$ after introducing MABr. This indicates that the MABr additive has improved the sharpness of the perovskite band edge. \n\n![](images/a886ecbbf917638dc133d43dae54e7ebbfa3765313afba3a4ea16989c03fadb8.jpg) \nFigure 3 | Device structure of $\\cos P b B r_{3}$ inorganic-based perovskite LEDs. (a) Device structure, $\\mathrm{g|ass/|TO/ZnO/PVP/CsPbBr_{3}/C B P/M o O_{3}/A l}_{\\cdot}$ here PVP is polyvinyl pyrrolidine, CBP is $4,4^{\\prime}$ -Bis(N-carbazolyl)- ${\\boldsymbol{\\cdot}}{\\boldsymbol{1}},{\\boldsymbol{\\cdot}}{\\boldsymbol{\\cdot}}$ -biphenyl. $Z n O$ are $C B P/M O O_{3}$ are used as the electron and hole injection layers, respectively. PVP was used to improve peorvskite morphology and also passivate the interface defects and improve charge injection balance. (b) Band alignment of each functional layer. (c) Cross-sectional SEM image of the LEDs, scale bar is $500\\mathsf{n m}$ . \n\nWe next acquired time-resolved PL decay spectra of the different perovskite layers (Fig. 2b). The time-resolved PL curves were fit to bi-exponential decays, where the fast decay component is associated with trap-assisted recombination at grain boundaries or surfaces, and the slow decay is ascribed to radiative recombination inside the bulk perovskite phase28,43. For the ${\\mathrm{ZnO/CsPbBr}}_{3}$ , $\\mathrm{PVP/CsPbBr}_{3}$ and $\\mathrm{PVP}/\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ films, the decay times are $\\stackrel{\\prime}{\\tau}_{1}=1.2\\mathrm{ns}$ , $\\tau_{2}=4.6\\mathrm{ns}\\$ ), $\\cdot\\tau_{1}=2.1$ ns, $\\tau_{2}=6.4\\mathrm{ns}$ ) and ( $\\tau_{1}=1.8\\mathrm{ns}$ , $\\tau_{2}=7.5\\mathrm{ns}$ , respectively. Generally, it was found that the PL lifetime of the perovskite film is increased after PVP modification, and further increased after the addition of MABr. We observed that the Cs–MA mixed perovskite has a marginally faster decay component in comparison with pure Cs perovskite. We hypothesize that this may be a result of increased surface defects in the Cs–MA mixed perovskite. However, the slow decay component of ${\\mathrm{Cs}}{\\mathrm{-}}{\\mathrm{MA}}$ exhibited a longer lifetime, indicative of less bulk defects, consistent with the observed reduction of $\\mathrm{\\sfPb}$ metallic states (Supplementary Fig. 7). Although Cs–MA sample showed shorter lifetime in fast decay component compared with pure Cs, stronger PL from Cs–MA samples (Fig. 3a) indicated that the overall defects including surface and bulk defects in $_{\\mathrm{Cs-MA}}$ are less than that of in pure Cs. The $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ films show bright and uniform green PL under ultraviolet lamp excitation (Fig. 2c). Both PVP interface engineering and MABr lattice incorporation enhanced the PL emission of the perovskite film, which is beneficial to realize high performance LEDs. \n\nThe PLQY of $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{Pb}\\mathrm{\\bar{B}r}_{3}$ was measured as a function of excitation power density (Fig. 2d). As seen in other perovskites, the PLQY increases with excitation power30,31. This is attributed to state-filling of recombination centres in the perovskite layer30,31. Our inorganic-based perovskite materials, $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ , exhibited high quantum yield $(35.8\\%)$ even at low light intensity $(0.07\\mathrm{m}\\mathrm{\\bar{W}}\\mathrm{cin}^{-2})$ . This is significantly higher than previous reports at a similar order of power excitation, indicative of reduced non-radiative recombination centres in the perovskite layer30,31. Upon increasing the excitation intensity to $4.{\\dot{7}}0\\operatorname{mW}\\operatorname{cm}^{-2}$ , the quantum efficiency increased to as high as $55\\%$ . The high PL quantum yield suggests promise for high EQE LEDs. \n\nLight-emitting diodes based on $\\mathbf{CsPbBr}_{3}$ films. We fabricated LEDs consisting of glass/indium tin oxide $(\\mathrm{ITO})/\\mathrm{ZnO}/\\mathrm{PVP}/$ $\\mathrm{CsPbBr_{3}/C B P/M o O_{3}/\\bar{A}l}$ (Fig. 3a), where $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ is the emitting layer, Apart from ITO and $\\mathrm{MoO}_{3}/\\mathrm{Al}.$ which were deposited in vacuum, all layers were solution processed via spin coating. The band alignment of the $\\mathrm{CsPbBr}_{3}$ LEDs could be drawn as shown in Fig. 3b based on the band structure of $\\mathrm{CsPbBr}_{3}$ and $\\mathrm{{}}Z\\mathrm{{nO}}$ (Supplementary Figs 3 and 5), and also the valence band of CBP $\\dot{(-6.0\\mathrm{eV})^{39}}$ . ZnO and $\\mathrm{CBP/MoO}_{3}$ are used as the electron and hole injection layers, respectively. In addition to improve perovskite morphology and also passivate the interface defects, which has been illustrate above (Figs 1 and 2). PVP layer could also induce an electron-injection barrier (Fig. 3b), which could improve charge injection balance, this will be discussed later. The electrons and holes injected from each side recombine radiatively in the perovskite layer, resulting in photon emission. A crosssectional SEM image of a typical device showed a clear sandwich structure (Fig. 3c). The thicknesses of the $\\mathrm{ZnO/PVP}$ , $\\mathrm{CsPbBr}_{3}$ and $^{4,4^{\\prime}}$ -Bis(N-carbazolyl)- $^{1,1^{\\prime}}$ -biphenyl (CBP) $\\ensuremath{\\mathrm{/MoO}}_{3}$ layers are $\\sim45\\mathrm{nm}$ , $100\\mathrm{nm}$ and $80\\mathrm{nm}$ , respectively. \n\n![](images/aa9df19fa54b5abe0d6d6ee3247963e49a4d96242cc87fe4ca913f180b8dd8fb.jpg) \nFigure 4 | EL performance of the devices. (a) EL spectra of $\\mathsf{C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3}$ -based devices under varying voltage bias (the emission image is shown in inset). (b) The corresponding CIE coordinate. (c) $1-V$ and voltage–light intensity $(L-V)$ curves for the devices with and without PVP buffer layer or with and without $C H_{3}N H_{3}B r$ (MABr) additive, that is, $Z_{\\mathsf{n O/C s P b B r_{3}}},$ $Z n{\\mathsf{O}}/{\\mathsf{P V P}}/{\\mathsf{C s P b B r}}_{3}$ and $\\mathsf{Z n O/P V P/C s}_{0.87}\\mathsf{M A}_{0.13}\\mathsf{P b B r}_{3},$ respectively, here PVP is polyvinyl pyrrolidine. (d) Current efficiency and EQE of devices with and without PVP buffer layer, with and without ${\\mathsf{C H}}_{3}{\\mathsf{N H}}_{3}{\\mathsf{B r}}$ (MABr) additive, that is, $Z_{\\mathsf{n}}{\\mathsf{O}}/{\\mathsf{C}}{\\mathsf{s P b}}{\\mathsf{B r}}_{3},$ $Z_{\\mathsf{n O/P V P/C s P b B r_{3}}}$ and $\\mathsf{Z n O/P V P/C s_{0.87}M A_{0.13}P b B r_{3}},$ respectively. \n\nElectroluminescence of light-emitting diodes. The EL spectra of $\\mathrm{CsPbBr}_{3}$ and $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ -based devices are centred at 516 and $520\\mathrm{nm}$ , respectively (Supplementary Fig. 9). Compared to the PL emission at $526\\mathrm{nm}$ for $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ , the EL emission showed a slight blue shift to $520\\mathrm{nm}$ , which has also been observed in other perovskite-based $\\mathrm{LEDs^{16,44}}$ . The blue shift in the EL spectrum could be ascribed to free carrier emission, as already demonstrated in several perovskite systems16,44,45. For the devices using $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ as an emitting layer, the EL spectrum as a function of voltage bias was measured (Fig. 4a), and an EL image of the device under operation was taken (inset of Fig. 4a). The EL showed very narrow emission $({\\mathrm{FWHM}}=18\\mathrm{nm})$ ) and high colour purity. This spectral line width is narrower than that of previously reported perovskite nanocrystal-based $\\mathrm{LEDs}^{14,15}$ . The devices exhibited saturated and pure colour $(90.2\\%)$ at green wavelengths, with Commission Internationale de l’Eclairage (CIE) chromaticity coordinates at (0.11, 0.78) (Fig. 4b). \n\nWe measured the voltage–current $\\left(I-V\\right)$ curve of the devices (Fig. 4c) and found that the control devices (without both PVP and MABr) showed higher injection current. This could be two reasons: one is high density of pinholes in the perovskite layer which results in a significant electron and hole injection leakage; and another could be the imbalanced charge injection. After introducing the PVP buffer layer and the MABr additive, the injection current of $\\mathrm{CsPbBr}_{3}$ device was significantly reduced, indicating that the current leakage and charge injection imbalance has been suppressed. The turn-on voltage was slightly increased after inserting an immediate layer of PVP, which could be mainly due to the injection barrier caused by the insulating nature of PVP layer46. The further minor increase of turn-on voltage after MABr incorporation might be ascribed to deeper valence band of $\\mathrm{Cs}_{0.87}\\mathrm{M}\\mathrm{\\bar{A}}_{0.13}\\mathrm{Pb}\\mathrm{Br}_{3}$ $\\bar{(5.71\\mathrm{eV})}$ compared to $\\mathrm{CsPbBr}_{3}$ $(5.50\\mathrm{eV})$ (Supplementary Fig. 3, Supplementary Table $1)^{47}$ . Similar phenomenon has also been found by Sun et al. in FA–Cs mixture nanocrystal-based $\\mathrm{LEDs^{48}}$ . Although the turn-on voltage increased after incorporating PVP buffer layer and adding MABr salt, it can be calculated that the current efficiency are significantly increased from $0.02\\mathrm{cd}\\mathrm{A}^{-1}$ $(\\mathrm{CsPbBr}_{3}),$ to $1{\\mathrm{cdA}}^{-1}$ 1 $(\\mathrm{PVP}/\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3})$ at small brightness $(1\\operatorname{cd}\\mathrm{m}^{-2})$ . The increase of current efficiency indicated the non-radiative recombination has been suppressed, which will be discussed later. The control devices showed a maximum brightness of $300\\mathrm{cd}\\mathrm{m}^{-2}$ (Fig. 4c). The maximum brightness was dramatically increased to $\\mathrm{i}1600\\mathrm{cd}\\mathrm{m}^{-2}$ by introducing the PVP intermediate layer. Consistent with this was an observed increase in the current efficiency from $0.26{\\mathrm{cd}}{\\mathrm{A}}^{-1}$ to $7.19\\mathrm{cd}\\mathrm{A}^{-1}$ (Fig. 4d). The EQE of the LEDs from control devices of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ on $\\mathrm{znO}$ is $<0.1\\%$ . The addition of the PVP buffer layer improved the quantum efficiency to $2.4\\%$ (Fig. 4d). \n\n
Table 1 | Device performance with and without PVP intermediate layers or CHNHBr (MABr) additive.
DevicesVth(V) Lmax(cd m-2)Current efficiency (Cd A-1)EQE (%)
ZnO/CsPbBr32.3 2.63500.26 0.09
ZnO/PVP/CsPbBr311,600 91,0007.19 33.92.41
ZnO/PVP/Cso.87MAo.13PbBr32.910.43
\n\nThe MABr salt additive further improves both the maximum brightness and EQE. The maximum brightness of $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ -based LEDs increased to as high as $91,000{\\mathrm{cd~m}}^{-2}$ . The current efficiency and quantum efficiency were increased to $33.9\\mathrm{cdA}^{-1}$ and $10.{\\dot{4}}3\\%$ , respectively (Fig. 4d). The best devices exhibited an internal quantum efficiency (IQE) of $47\\%$ calculated by ${\\mathrm{IQE}}=2n^{2}{\\mathrm{EQE}}$ , where n is the refractive of glass $(1.5)^{31}$ . The device performance parameters are summarized in Table 1. To the best of our best knowledge, these devices are the brightest and most-efficient perovskite-based LEDs emitting at green wavelengths reported to date. \n\nThese devices also demonstrated high reproducibility (Supplementary Fig. 10). The high performance in the $\\mathrm{ZnO/PVP}/\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ LED is a result of careful optimization of the interfaces and perovskite layers (Supplementary Figs 11–13, Supplementary Tables 2 and 3). It was found that a high amount of MABr compositionally mixed with $\\mathrm{CsPbBr}_{3}$ led to a significant decrease in LED performance. We attribute this to poor morphology (Supplementary Fig. 14). \n\nWe tested the stability of $\\mathrm{CsPbBr}_{3}$ LEDs (Supplementary Fig. 15). Consistent with what was observed in previous perovskite LED reports33,49, the devices decayed after several minutes. The decay mechanism is hypothesized to be a result of ion migration under steady-state voltage bias. To improve device stability, we attempted to incorporate ion-migration-inhibiting polymers50, such as PVP, into the perovskite layer. The results indeed showed that the stability had been significantly improved—the output was stable for several hours. While encouraging, the efficiency of this polymer-blended device is reduced in comparison with the $\\mathrm{ZnO/PVP}/\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ devices (Supplementary Fig. 16). We will study in more depth the underlying phenomena leading to this stability/efficiency compromise in our future work. We have also tested the transient light emission response of our perovskite LEDs (Supplementary Fig. 17). Nearly instantaneous turn-on was achieved with a response time about $18\\mathrm{ms}$ to reach their maximum output light intensities. Such a fast turn-on is comparable to that of conventional LEDs51. \n\n# Discussion \n\nWe found that the improvement via PVP could be due to three reasons. First, the improvement of the perovskite film morphology, as shown in Fig. $^{\\mathrm{1a,b}}$ , leads to reduced pinholes which minimize current leakage (Fig. 4a). Second, the suppression of non-radiative recombination at the $\\mathrm{ZnO}/$ perovskite interface, which has been confirmed by PL results (Fig. 2a, Supplementary Fig. 8), improves the radiative efficiency. \n\nIn addition to improvement of perovskite film morphology and passivation of defects at interface, PVP could improve the charge injection balance in our perovskite LEDs, and thus enhancing devices EL efficiency. Similar mechanism has been proposed in previous reports, while using PMMA insulting layer in quantum dot LEDs46. It was found that the injection current from electron only devices is much higher than that of the current from hole only devices, while using ZnO and CBP as the main injection layers, respectively (Supplementary Fig. 18). These results indicated that the electron injected by $\\mathrm{znO}$ is faster than holes injected by CBP, which could be due to the different carrier mobility of $\\mathrm{{}}Z\\mathrm{{nO}}$ and CBP (ref. 46). This will lead to charge injection imbalance and also the excess electron current while using these layer as electron- and hole-injection layers in LEDs, and thus degrading EL efficiency46. Insulting PVP layer can slow down electron-injection via an energy barrier (Fig. 3b, Supplementary Fig. 18), an improvement of charge balance could be anticipated by inserting a PVP layer on $\\overline{{Z\\mathrm{nO}}}$ surface as the electron-injection layer. In fact, the reduction of device injection current via PVP insertion confirmed the improvement of charge injection balance (Fig. 4c)46, and thus improving EL emission efficiency. \n\nThere could be two key improvements of leading to superior performance for MA–Cs mixed perovskite devices. The first one is ascribed to the suppression of non-radiative recombination centres by eliminating the $\\mathrm{Pb}$ metallic phase by compositionally blending $\\mathrm{CsPbBr}_{3}$ with MABr to form the compound $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ . PL (Fig. 2a) and time-resolved PL (Fig. 2b) both indicated that the less defects in Cs–MA films. Second, the key advance that led to the dramatic improvement in EL brightness and efficiency is the reduction of leakage current via improved morphology as a result of both PVP-modified $\\mathrm{znO}$ and the MABr additive (Fig. 1c). \n\nIn summary, we have obtained high-quality $\\mathrm{Cs_{0.87}M A_{0.13}P b B r_{3}}$ perovskite light-emitting thin films with minimized pinholes through electron-injecting interface passivation and perovskite composition modulation. These strategies jointly reduced the device leakage current. Furthermore, the non-radiative recombination centres at the interfaces and in the perovskite film were suppressed and also the charge injection balance were improved. As a result of these advances, we obtained ultra-bright and highly efficient inorganic perovskite-based LEDs. With additional optimizations to the perovskite and interfacial layers, the inorganic perovskite-based LEDs have promise to reach $20\\%$ EQE, making them competitive with materials such as semiconducting organics and colloidal quantum dots. \n\n# Methods \n\nPreparation of perovskite solution and $z_{n0}$ nanoparticles. CsBr (Sigma Aldrich, $99.9\\%$ ) and $\\mathrm{Pb}\\mathrm{Br}_{2}$ (Aldrich, $99.99\\%\\rvert\\$ $\\scriptstyle(\\mathrm{CsBr:PbBr}_{2}$ molar ratio of 2.2:1) solutions were prepared using DMSO as a solvent. The solution concentration is $0.5\\mathrm{M}$ (CsBr 1.1 M, $\\mathrm{PbBr}_{2}0.5\\mathrm{M}$ ). A high ratio of $\\mathrm{CsBr:PbBr}_{2}$ was used to suppress the formation of non- $\\mathrm{.csPbBr}_{3}$ phases. For films which incorporated the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Br}$ additive, $0.05~\\mathrm{M}$ $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Br}$ was added to the solution $(\\mathrm{CsBr{:}P b B r_{2}{:}M A B r=2.2{:}1{:}0.1)}$ . Comparative studies used additional ratios of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ solutions, such as $\\mathrm{CsBr{:}P b B r_{2}{:}M A B r=2{:}1{:}0.1}$ , 2.1:1:0.1, 2.2:1:0.1, 2.4:1:0.1 and 2.2:1:0.2. The precursor solutions were stirred at $45^{\\circ}\\mathrm{C}$ overnight. And then the solution was stand for $^{4\\mathrm{h}}$ at room temperature, precipitates were formed in the CsBr-rich solution, top transparent solution was decanted and filtered for using. The details of precursor preparation procedures were shown in Supplementary Fig. 19. The ZnO nanoparticles were synthesized using a previously developed method8. The synthesized $\\mathrm{znO}$ nanoparticles were dispersed in methanol and n-butanol to form a $2\\%$ ZnO nanoparticle solution. \n\nLight-emitting diode fabrication. The glass/ITO substrate was sequentially washed with isopropanol, acetone, distilled water and isopropanol. The sheet resistance of ITO is $15\\Omega$ per square. $\\mathrm{znO}$ nanoparticles of concentration $2\\%$ by weight were spin-coated onto ITO substrates at $2{,}000\\mathrm{r}{.}\\mathrm{p}{.}\\mathrm{m}$ for $30\\mathrm{s}$ and then annealed at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ . For control devices, perovskite precursor $(\\mathrm{CsBr};\\mathrm{PbBr}_{2}=2.2{:}1)$ was spin-coated onto $\\mathrm{znO}$ at $2{,}000\\mathrm{r.p.m}$ . for $2\\mathrm{min}$ , and then annealed at 100 for $20\\mathrm{min}$ . After, a $2\\mathrm{wt\\%}$ CBP solution was spin-coated onto the perovskite. The devices were transferred into a vacuum chamber for $\\mathrm{MoO}_{3}/\\mathrm{Al}$ deposition. For PVP interface-modified devices, $0.5\\mathrm{wt\\%}$ PVP solution in DMSO was spin-coated onto $\\mathrm{znO}$ at $2{,}000\\mathrm{r.p.m}$ . for 1 min, and then annealed at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ to induce crosslinking. However, we found that the PVP is slightly washed away during spin-coating of the DMSO solution. The PVP thickness before and after DMSO solution washing are 8.4 and $5.0\\mathrm{nm}$ , respectively, which were measured by ellipsometer (Supplementary Fig. 20). For MABr additive devices, the ratio of CsBr:PbBr2:MABr is 2.2:1:0.1, the final composition is $\\mathrm{Cs}_{0.87}\\mathrm{MA}_{0.13}\\mathrm{PbBr}_{3}$ as determined by band-edge emission measurements. The solution concentration was $0.5\\mathrm{M}$ . The device active area was $0.108\\mathrm{cm}^{2}$ . \n\nMaterials and device characterization. A field emission SEM (FEI NanoSEM650) was used to acquire SEM images. The instrument uses an electron beam accelerated at $500\\mathrm{V}$ to $30\\mathrm{kV}$ enabling operation at a variety of currents. Absorption measurement were carried out by Hitachi ultraviolet–visible U-4100 spectrophotometer. Absorbance was determined from a transmittance measurement using integrated sphere. PL measurements were carried out by FLS980 Spectrometer. The X-ray diffraction patterns $\\cdot\\theta-2\\theta$ scans) were taken on a Rigaku D/MAX-2500 system using Cu ka ( $\\lambda{=}1.5405\\mathrm{\\AA}$ ) as the X-ray source. Scans were taken with $0.5\\mathrm{mm}$ wide source and detector slits, and X-ray generator settings at $40\\mathrm{kV}$ and $30\\mathrm{mA}$ . XPS was performed on the Thermo Scientific ESCALab 250Xi using $200\\mathrm{W}$ monochromated Al $\\operatorname{K}\\upalpha$ $\\mathtt{\\rVert\\Psi(1,486.6e V)}$ radiation. The $500\\upmu\\mathrm{m}$ X-ray spot was used for XPS analysis. The base pressure in the analysis chamber was $\\sim3\\times10^{-10}$ mbar. Typically the hydrocarbon C1s line at $284.8\\mathrm{eV}$ from adventitious carbon is used for energy referencing. UPS samples were analyzed on a Thermo Scientific ESCALab 250Xi. The gas discharge lamp was used for UPS, with helium gas admitted and the HeI $(21.22\\mathrm{eV})$ emission line employed. The helium pressure in the chamber during analysis was $\\sim2\\mathrm{E}-8$ mbar. The data was acquired with a $-10\\mathrm{V}$ bias. The work function of the measured sample can be calculated from following equation: $h\\nu-\\phi{=}E_{\\mathrm{Fermi}}{-}E_{\\mathrm{cutoff}},$ here, $h\\nu=21.22\\mathrm{eV}$ , $E_{\\mathrm{Fermi}}{=}21.08\\mathrm{eV}$ (using Ni as the standard sample for calibration), $E_{\\mathrm{cut-off}}$ is the cut-off shown in the corresponding Figures. The PLQY was measured using a Horiba Fluorolog system equipped with a single grating and a Quanta-Phil integration sphere coupled to the Fluorolog system with optic fibre bundles30. The following settings were applied for PLQY measurements: an excitation wavelength of $\\scriptstyle400{\\mathrm{nm}};$ bandpass values of 10 and $5\\mathrm{nm}$ for the excitation and emission slits, respectively; step increments of $1\\mathrm{nm}$ and integration time of $0.5\\:s$ per data point. The excitation power density in the power-dependent PLQY characterization was tuned by varying the slit width on the Fluorolog monochromator. $J{-}V$ characteristics of LEDs were taken using a Keithley 2,400 source metre. Two Keithley 2,400 source metre units linked to a calibrated silicon photodiode were used to measure the current–voltage–brightness characteristics. The measurement system has been carefully calibrated by efficient InGaN/GaN LEDs with a similar photon response by PR-650 SpectraScan. A Lambertian profile was assumed in the calculation of EQE28,30,31. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# References \n\n1. Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n2. Kim, H. S. et al. Lead iodide perovskite sensitized all-solid-state submicron thin film mesoscopic solar cell with efficiency exceeding $9\\%$ . Sci. Rep. 2, 591 (2012). \n3. Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n4. Burschka, J. et al. Sequential deposition as a route to high-performance perovskite-sensitized solar cells. Nature 499, 316–319 (2013). \n5. Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n6. Yang, W. S. et al. High-performance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237 (2015). \n7. Bi, D. et al. Efficient luminescent solar cells based on tailored mixed-cation perovskites. Sci. Adv. 2, e1501170 (2016). \n8. You, J. et al. Improved air stability of perovskite solar cells via solutionprocessed metal oxide transport layers. Nat. Nanotechnol. 11, 75–81 (2016). \n9. Xing, G. et al. Low-temperature solution-processed wavelength-tunable perovskites for lasing. Nat. Mater. 13, 476–480 (2014). \n10. Zhu, H. et al. Lead halide perovskite nanowire lasers with low lasing thresholds and high quality factors. Nat. Mater. 14, 636–643 (2015). \n11. Stranks, S. D. & Snaith, H. J. Metal-halide perovskites for photovoltaic and light-emitting devices. Nat. Nanotechnol. 10, 391–402 (2015). \n12. Deschler, F. et al. High photoluminescence efficiency and optically pumped lasing in solution-processed mixed halide perovskite semiconductors. J. Phys. Chem. Lett. 5, 1421–1426 (2014). \n13. Zhang, F. et al. Brightly luminescent and color-tunable colloidal $\\mathrm{CH_{3}N H_{3}P b X_{3}}$ $\\mathrm{{\\cdot}}\\mathrm{{X}}=\\mathrm{{Br}},$ , I, Cl) quantum dots: potential alternatives for display technology. ACS Nano 9, 4533–4542 (2015). \n14. Protesescu, L. et al. Nanocrystals of cesium lead halide perovskites $\\mathrm{'CsPbX_{3}}$ , $\\mathrm{X=Cl}$ , Br, and I): novel optoelectronic materials showing bright emission with wide color gamut. Nano Lett. 15, 3692–3696 (2015). \n15. Song, J. et al. Quantum dot light-emitting diodes based on inorganic perovskite cesium lead halides $\\mathrm{(CsPbX_{3})}$ . Adv. Mater. 27, 7162–7167 (2015). \n16. Tan, Z. K. et al. Bright light- emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n17. Li, G. et al. Efficient light-emitting diodes based on nanocrystalline perovskite in a dielectric polymer matrix. Nano Lett. 15, 2640–2644 (2015). \n18. Jaramillo-Quintero, O. A., Sanchez, R. S., Rincon, M. & Mora-Sero, I. Bright visible-infrared light emitting diodes based on hybrid halide perovskite with Spiro-OMeTAD as a hole-injecting layer. J. Phys. Chem. Lett. 6, 1883–1890 (2015). \n19. Sadhanala, A. et al. Blue-green color tunable solution processable organolead chloride \u0002 bromide mixed halide perovskites for optoelectronic applications. Nano Lett. 15, 6095–6101 (2015). \n20. Gil-Escrig, L. et al. Efficient photovoltaic and electroluminescent perovskite devices. Chem. Commun. 51, 569–571 (2015). \n21. Li, J., Bade, S. G. R., Shan, X. & Yu, Z. Single-layer light-emitting diodes using organometal halide perovskite/poly(ethylene oxide) composite thin films. Adv. Mater. 27, 5196–5202 (2015). \n22. Kim, Y. H. et al. Multicolored organic/inorganic hybrid perovskite light-emitting diodes. Adv. Mater. 27, 1248–1254 (2015). \n23. Hoye, R. L. Z. et al. Enhanced performance in fluorene-free organometal halide perovskite light-emitting diodes using tunable, low electron affinity oxide electron injectors. Adv. Mater. 27, 1414–1419 (2015). \n24. Aygu¨ler, M. F. et al. Light-emitting electrochemical cells based on hybrid lead halide perovskite nanoparticles. J. Phys. Chem. C 119, 12047–12054 (2015). \n25. Yu, J. C. et al. High-performance planar perovskite optoelectronic devices: a morphological and interfacial control by polar solvent treatment. Adv. Mater. 27, 3492–3500 (2015). \n26. Xing, J. et al. High-efficiency light-emitting diodes of organometal halide perovskite amorphous nanoparticles. ACS Nano 10, 6623–6630 (2016). \n27. Wang, J. et al. Interfacial control toward efficient and low-voltage perovskite light-emitting diodes. Adv. Mater. 27, 2311–2316 (2015). \n28. Cho, H. et al. Overcoming the electroluminescence efficiency limitations of perovskite light-emitting diodes. Science 350, 1222–1225 (2015). \n29. Dou, L. et al. Atomically thin two-dimensional organic-inorganic hybrid perovskites. Science 349, 1518–1521 (2015). \n30. Yuan, M. et al. Perovskite energy funnels for efficient light-emitting diodes. Nat. Nanotechnol. 11, 872–877 (2016). \n31. Wang, N. et al. Perovskite light-emitting diodes based on solution-processed self-organized multiple quantum wells. Nat. Photon. 10, 699–704 (2016). \n32. Xiao, Z. Efficient perovskite light-emitting diodes featuring nanometre-sized crystallites. Nat. Photonics. 11, 108–115 (2017). \n33. Kulbak, M., Cahen, D. & Hodes, G. How important is the organic part of lead halide perovskite photovoltaic cells? Efficient $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ cells. J. Phys. Chem. Lett. 6, 2452–2456 (2015). \n34. Yantara, N. et al. Inorganic halide perovskites for efficient light-emitting diodes. J. Phys. Chem. Lett. 6, 4360–4364 (2015). \n35. Li, J. et al. 50-fold EQE improvement up to $6.27\\%$ of solution-processed all-inorganic perovskite $\\mathrm{Cs}\\mathrm{Pb}\\mathrm{Br}_{3}$ QLEDs via surface ligand density control. Adv. Mater. 29, 1603885 (2016). \n36. Ling, Y. et al. Enhanced optical and electrical properties of polymer-assisted all-inorganic perovskites for light-emitting diodes. Adv. Mater. 28, 8983–8989 (2016). \n37. Meng, L., You, J., Guo, T. & Yang, Y. Recent advances in the inverted planar structure of perovskite solar cells. Acc. Chem. Res. 49, 155–165 (2016). \n38. Jeon, N. J. et al. Compositional engineering of perovskite materials for high-performance solar cells. Nature 517, 476–480 (2015). \n39. Veldhuis, S. A. et al. Perovskite materials for light-emitting diodes and lasers. Adv. Mater. 28, 6804–6834 (2016). \n40. Zhang, W. et al. Enhanced optoelectronic quality of perovskite thin films with hypophosphorous acid for planar heterojunction solar cells. Nat. Commun. 6, 10030 (2015). \n41. Small, C. E. et al. High-efficiency inverted dithienogermole– thienopyrrolodione-based polymer solar cells. Nat. Photon. 6, 115–120 (2012). \n42. Noh, J. H., Im, S. H., Heo, J. H., Mandal, T. N. & Seok, S. I. Chemical management for colorful, efficient, and stable inorganic–organic hybrid nanostructured solar cells. Nano Lett. 13, 1764 (2013). \n43. Shi, D. et al. Low trap-state density and long carrier diffusion in organolead trihalide perovskite single crystals. Science 347, 519–522 (2015). \n44. Palma, A. L. et al. Mesoscopic perovskite light-emitting diodes. ACS Appl. Mater. Interfaces 8, 26989–26997 (2016). \n45. D’Innocenzo, V. et al. Excitons versus free charges in organo-lead tri-halide perovskites. Nat. Commun. 5, 3586 (2014). \n46. Dai, X. et al. Solution-processed, high-performance light-emitting diodes based on quantum dots. Nature 515, 96–99 (2014). \n47. Endres, J. et al. Valence and conduction band densities of states of metal halide perovskites: a combined experimental \u0002 theoretical study. J. Phys. Chem. Lett. 7, 2722–2729 (2016). \n48. Zhang, X. et al. Hybrid perovskite light-emitting diodes based on perovskite nanocrystals with organic–inorganic mixed cations. Adv. Mater 29, 1606405 (2017). \n49. Zhang, X. et al. Enhancing the brightness of cesium lead halide perovskite nanocrystal based green light-emitting devices through the interface engineering with perfluorinated monomers. Nano Lett. 16, 1415–1420 (2016). \n50. Zhou, Q. et al. In situ fabrication of halide perovskite nanocrystal embedded polymer composite films with enhancednphotoluminescence for display backlights. Adv. Mater. 28, 9163–9168 (2016). \n51. Li, J. et al. Single-layer halide perovskite light-emitting diodes with sub-band gap turn-on voltage and high brightness. J. Phys. Chem. Lett. 7, 4059–4066 (2016). \n\n# Acknowledgements \n\nWe thank Prof Junxi Wang and Prof Hua Yang from Institute of Semiconductors, Chinese Academy of Sciences for kindly providing GaN/InGaN LEDs to us for calibration of our measurement system, and for helping us with the CIE measurement. We also thank Prof Lu Li and Prof Xing Yang from Chongqing University of Arts and Science for brightness calibration measurement. We thank Prof Bo Wang from Beijing University of Technology for helping with contact angle measurements. We also would like to Prof Haibo Zeng from Nanjing University of Science and Technology for fruitful discussions. This work is supported by National 1,000 Young Talents awards, National Key Research and Development Program of China (Grant No. 2016YFB0700700), National Natural Science Foundation of China (Grant Numbers: 61634001, 61574133), Beijing Municipal Science & Technology Commission (Grant No. Z151100003515004) and Young top-notch talent project of Beijing. H.T. acknowledges the Netherlands Organisation for Scientific Research (NWO) for a Rubicon grant (680-50-1511) to support his postdoctoral research at University of Toronto. \n\n# Author contributions \n\nJ.Y. conceived the idea, designed the experiment and analyzed the data. L.Z. fabricated devices and collected all data. X.Y., Q.J., P.W., Z.Y. were involved in data analysis. H.T. and M.W. carried out PLQY measurements, Y.Y. is responsible for LED response \n\nmeasurements. J.Y., L.Z. and X.Z. co-wrote the manuscript. H.T., B.R.S. and E.H.S. improved the manuscript. J.Y. and X.Z. directed and supervised the project. All authors contributed to discussions and finalizing the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Zhang, L. et al. Ultra-bright and highly efficient inorganic based perovskite light-emitting diodes. Nat. Commun. 8, 15640 doi: 10.1038/ncomms15640 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2017 " + }, + { + "id": "10.1126_science.aai8142", + "DOI": "10.1126/science.aai8142", + "DOI Link": "http://dx.doi.org/10.1126/science.aai8142", + "Relative Dir Path": "mds/10.1126_science.aai8142", + "Article Title": "Bismuthene on a SiC substrate: A candidate for a high-temperature quantum spin Hall material", + "Authors": "Reis, F; Li, G; Dudy, L; Bauernfeind, M; Glass, S; Hanke, W; Thomale, R; Schafer, J; Claessen, R", + "Source Title": "SCIENCE", + "Abstract": "Quantum spin Hall materials hold the promise of revolutionary devices with dissipationless spin currents but have required cryogenic temperatures owing to small energy gaps. Here we show theoretically that a room-temperature regime with a large energy gap may be achievable within a paradigm that exploits the atomic spin-orbit coupling. The concept is based on a substrate-supported monolayer of a high-atomic number element and is experimentally realized as a bismuth honeycomb lattice on top of the insulating silicon carbide substrate SiC(0001). Using scanning tunneling spectroscopy, we detect a gap of similar to 0.8 electron volt and conductive edge states consistent with theory. Our combined theoretical and experimental results demonstrate a concept for a quantum spin Hall wide-gap scenario, where the chemical potential resides in the global system gap, ensuring robust edge conductance.", + "Times Cited, WoS Core": 801, + "Times Cited, All Databases": 842, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000405901600037", + "Markdown": "# Bismuthene on a SiC substrate: A candidate for a hightemperature quantum spin Hall material \n\nF. Reis,1\\* G. Li,2,3\\* L. Dudy,1 M. Bauernfeind,1 S. Glass,1 W. Hanke,3 R. Thomale,3 J. Schäfer,1† R. Claessen \n\n1Physikalisches Institut and Röntgen Research Center for Complex Material Systems, Universität Würzburg, D-97074 Würzburg, Germany. 2School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, China. 3Institut für Theoretische Physik und Astrophysik, Universität Würzburg, D-97074 Würzburg, Germany. \\*These authors contributed equally to this work. \n\n†Corresponding author. Email: joerg.schaefer@physik.uni-wuerzburg.de \n\nQuantum spin Hall materials hold the promise of revolutionary devices with dissipationless spin currents, but have required cryogenic temperatures owing to small energy gaps. Here we show theoretically that a room-temperature regime with a large energy gap may be achievable within a paradigm that exploits the atomic spin-orbit coupling. The concept is based on a substrate-supported monolayer of a high-Z element, and is experimentally realized as a bismuth honeycomb lattice on top of the insulator SiC(0001). Using scanning tunneling spectroscopy, we detect a gap of ${\\sim}0.8\\mathsf{e V}$ and conductive edge states consistent with theory. Our combined theoretical and experimental results demonstrate a concept for a quantum spin Hall wide-gap scenario, where the chemical potential resides in the global system gap, ensuring robust edge conductance. \n\nQuantum spin Hall (QSH) systems are two-dimensional representatives of the family of topological insulators, which exhibit conduction channels at their edges inherently protected against certain types of scattering. Initially predicted for graphene $(\\boldsymbol{I},\\boldsymbol{2})$ , and eventually realized in HgTe quantum wells (3, 4), in the QSH systems realized so far $(5,\\ 6)$ , the decisive bottleneck preventing applications is the small bulk energy gap of less than $30\\mathrm{meV}$ . The chemical potential must reside safely within this gap to avoid detrimental contributions to the edge current from the bulk material, and very low temperatures (below that of liquid helium) are needed to suppress thermal excitation of charge carriers into those bulk electron bands (7, 8). Strategies to shift the thermal operation limit above room temperature must, therefore, tailor the energy gap of the system toward significantly larger values. \n\nAlthough the $\\mathsf{Q S H}$ phase is characterized by universal topological properties (2), other aspects such as the bulk energy gap are material-specific, and depend on the combination of spin-orbit coupling (SOC) (scaling as $Z^{4}$ in elements of atomic number $Z$ ), orbital hybridization, and the symmetries of the layer-substrate system. The minute SOC in graphene precludes a noticeable gap; one strategy to generate enhanced gaps in related QSH honeycomb layer materials (1) is to use elements heavier than C. For systems with the group-IV elements Si, Ge, and Sn, predicted gaps are 2 meV (9), 24 meV (9), and 100 meV (10), respectively. According to the Kane-Mele model $(I)$ , these gaps are still relatively small, because SOC enters the gap determination only in higher-order perturbation theory. This applies to hypothetical freestanding materials with poor chemical stability. Real-world variants require a supporting substrate for epitaxial synthesis, which brings concurrent bonding interactions into play. Attempts were made to grow, e.g., silicene on a metallic Ag substrate $(I I,\\ I2)$ , which however shortcircuits any edge states of interest. An insulating $\\mathbf{MoS}_{2}$ substrate can stabilize germanene (13), yet the compressive strain renders the material a metal. Stanene flakes on $\\mathrm{Bi_{2}T e_{3}}$ are plagued by the same problem (14). \n\nTurning to group $\\mathrm{\\DeltaV}$ of the periodic table, bismuth ( $Z=83$ ) must be expected to yield an even larger gap. Its thin free-standing layers have been predicted to be topologically non-trivial (15–17). The existence of a monolayer bismuthene QSH phase on a silicon substrate has been proposed (18), and extended to a SiC substrate (19). However, experimental growth of a hexagonal single-layer Bi phase on Si(111) has failed (20, 21). \n\nHere we show, combining theory and experiment, that for bismuthene grown on a SiC(0001) substrate, the substrate is not only stabilizing the quasi-2D topological insulator but also plays a pivotal role for achieving the large gap, with the strong on-site SOC coming directly into play. \n\nOur experimental realization of supported bismuthene employs a SiC(0001) substrate, on which we generate a $(\\sqrt{3}\\times\\sqrt{3})\\mathbf{R}30^{\\circ}$ superstructure of Bi atoms in honeycomb geometry (Fig. 1A and fig. S1). The resulting lattice constant of $5.35\\mathrm{~\\AA~}$ is significantly larger than that of buckled Bi(111) bilayers. This causes a fully planar configuration of the honeycomb layer, which is energetically favorable (19). The synthesis described in (22) starts from a hydrogen-etched SiC wafer on which a monolayer of Bi is epitaxially deposited, giving rise to sharp electron diffraction peaks (fig. S2). A scanning tunneling microscopy (STM) overview (Fig. 1B) shows that the whole surface is smoothly covered with flakes of typical diameter ${\\sim}25~\\mathrm{nm}$ , separated by phase-slip domain boundaries (related to the Bi-induced surface reconstruction), and including occasional defects. Alternatively, the flakes are also terminated by SiC substrate steps (Fig. 1C). Inspection of the layer on a smaller scale reveals the characteristic honeycomb pattern of bismuthene (Fig. 1D). Detailed view of the honeycomb structure is provided by the close-up STM in Fig. 1E. For both occupied and empty states, respectively, the images show a honeycomb pattern throughout. \n\nTo establish that the electronic structure of the synthesized material corresponds to bismuthene, we performed angle-resolved photoelectron spectroscopy (ARPES) and compared it with density-functional theory (DFT) (Fig. 2 and fig. S4). The electron bands in Fig. 2A are obtained using a hybrid exchange-correlation functional, including SOC (22). At the K-point, the direct energy gap amounts to $1.06\\ \\mathrm{eV}$ [six orders of magnitude larger than in graphene with ${\\boldsymbol{\\sim}}1$ μeV (23)]. The conduction band minimum at $\\Gamma$ leads to an indirect gap of $0.67\\ \\mathrm{eV}$ in DFT. The $\\mathbf{k}$ -resolved dispersion from ARPES in Fig. 2B exhibits the characteristic maximum at the K-point and a band splitting there, in close agreement with the DFT overlay. From the ARPES close-up in Fig. 2C of the valence band maximum at $\\mathbb{K},$ we derive a large band splitting of ${\\sim}0.43\\ \\mathrm{eV}$ , subsequently identified as the unique “Rashba fingerprint” of the system. The constant energy maps in Fig. 2D reflect the energy degeneracy of the $\\mathrm{K}\\mathrm{-}$ and K’-points and give further proof of the high degree of long-range order in the Bi honeycomb lattice. The excellent agreement of ARPES and DFT results suggests the realization of a single bismuthene layer on SiC (while clearly excluding a double-layer, see fig. S5). \n\nNext, we disentangle the key mechanisms that determine the energetics near the Fermi level $E_{\\mathrm{{F}}}$ by reducing (downfolding) the full DFT band structure to the relevant lowenergy model [see (22) for details]. Inclusion of substrate bonding proves indispensable in this procedure. We decompose the band structure into $\\sigma$ -bond contributions formed by Bi 6s -, $p_{x}$ - and $p_{y}$ -orbitals, and $\\pi$ -bond contributions formed by $p_{z}$ -orbitals. As a consequence of hybridization with the substrate via $\\pi$ -bonds, the orbital content at low energies is predominantly of $\\sigma$ -type (Fig. 3A) and $p_{x}$ - and $p_{y}$ - orbitals play the main role close to $E_{\\mathrm{{F}}}$ , whereas the $p_{z}$ - orbital is pushed out of this energy region. \n\nFocusing on the low-energy bands around the Fermi level, we find that without relativistic effects the mere orbital hybridization in the $\\sigma$ -bonding sector (with eight bands coming from two-fold orbital, spin, and sublattice degrees of freedom) yields a Dirac-like band crossing at the K point (Fig. 3B). SOC affects the bandstructure via two leading contributions: First, the local (on-site) SOC term $\\lambda_{\\mathrm{soc}}L_{z}\\sigma_{z}$ generates large matrix elements between $p_{x}$ - and $p_{y}$ -orbitals [see, e.g., (24)], and directly determines the magnitude of the energy gap at the $\\mathrm{\\bfK}$ -point (Fig. 3C), which is of order $\\sim2\\lambda_{\\mathrm{soc}}$ . Second, the $\\pi$ -bonding sector hybridizes with the substrate, which breaks inversion symmetry. It features a Rashba term which, in leading order of perturbation theory, couples into the $\\sigma$ -bonding sector, yielding a composite effective Hamiltonian \n\n$$\nH_{\\mathrm{eff}}^{\\sigma\\sigma}=H_{\\mathrm{0}}^{\\sigma\\sigma}+\\lambda_{\\mathrm{SOC}}H_{\\mathrm{SOC}}^{\\sigma\\sigma}+\\lambda_{\\mathrm{R}}H_{\\mathrm{R}}^{\\sigma\\sigma}\n$$ \n\nwhere $H_{0}^{\\sigma\\sigma},H_{\\mathrm{{soc}}}^{\\sigma\\sigma}$ , and $H_{\\mathrm{R}}^{\\sigma\\sigma}$ are specified in (22). \n\nWe derive the prefactors for Bi/SiC as $\\lambda_{\\mathrm{soc}}\\sim0.435\\mathrm{eV}$ and $\\lambda_{\\mathrm{{R}}}\\sim0.032\\:\\mathrm{{eV}}$ (22). Although the Rashba term $\\lambda_{\\mathrm{R}}$ is much smaller than $\\lambda_{\\mathrm{soc}}$ , it induces the large valence band splitting (as seen clearly in ARPES) into states of opposite spin character, while leaving the conduction band spindegenerate at K (Fig. 3D). The six valence band maxima are energy-degenerate, heir large momentum separation and the huge Rashba splitting prevents spin scattering in the bulk (25), as discussed for 2D semiconductors. \n\nThe mechanism at work here produces a QSH phase with the non-trivial topological invariant $Z_{2}=1$ [see (22) and fig. S6 for derivation], and is very different from the Kane-Mele mechanism (1) for graphene. Graphene’s gap emerges owing to SOC between next-nearest neighbors and at the level of second-order perturbation theory,and is therefore minute. In other group-IV monolayers, such as silicene, the SOC remains of the next-nearest neighbor type (26), and the relevant orbital is still $p_{z}$ . In contrast, in bismuthene the low-energy physics is driven by the huge onsite SOC of $p_{x}$ - and $p_{y}$ -orbitals. This is also distinct from HgTe/CdTe quantum wells, where the small band gap is governed by a complex band situation and opens only upon strain (3, 4). \n\nAnother fundamental ingredient that stabilizes the widegap QSH phase in bismuthene is the comparatively large lattice constant defined by the SiC substrate registry. It corresponds to a planar configuration close to its energy minimum (19), i.e., is effectively strain-free and not subject to buckling. As argued for functionalized stanene $(I O)$ , the topological gap is lost when external strain shifts another band through the gap. This phase transition to a trivial system is promoted by compressive strain, whereas tensile strain stabilizes the QSH phase. Not surprisingly, compressed germanene $(I3)$ and stanene $(I4)$ have been reported to be metals, which highlights the importance of the substrate. \n\nA landmark feature of QSH systems are the helical edge channels, connecting valence and conduction states by two bands of opposite spin (fig. S8), irrespective of the edge architecture (zigzag or armchair). Within the bulk gap, they exhibit an approximately constant density of states (DOS). In a ribbon simulation, the states rapidly decay toward the bulk within one unit cell, i.e., ${\\sim}5\\mathrm{\\AA}$ (fig. S8). \n\nUsing a tunneling tip, the local DOS (LDOS) is inspected at the atomic scale. Bismuthene edges exist at SiC substrate steps. Differential tunneling conductivity $(\\mathrm{d}I/\\mathrm{d}V)$ curves, reflecting the LDOS, have been recorded along a path toward an uphill step in Fig. 4A. Far from the edge, the spectrum evidences a large bulk gap of ${\\sim}0.8\\ \\mathrm{eV}.$ Notably, the tunneling spectrum reproduces both the Rashba fingerprint in the occupied states, and the structure in the empty states (fig. S7). Closer to the boundary, a state emerges filling the entire gap – as in the DFT ribbon model for both armchair and zigzag edges (fig. S8). Its signal increases continuously toward the edge, while retaining its shape and exhibiting a zero-bias anomaly, where $\\mathrm{d}I/\\mathrm{d}V$ is suppressed. The anomaly may reflect tip-related electron scattering (27), or hint at Luttinger liquid behavior of the edge channel (28), which requires further study. Importantly, this spectral dip is not an inherent property of the bandstructure-derived metallic DOS in the gap, but is rather a many-body feature imprinted on top of it; this is evidenced by the dip remaining fixed to the chemical potential, irrespective of occasional small shifts of the bulk band edges (see, e.g., Fig. 4B and fig. S9). The edge DOS in Fig. 4B (and see also figs. S9 and S10) shows equivalent behavior for upper and lower terrace, showing the robustness against the particular geometric situation. The $\\mathrm{~d~}I/\\mathrm{d}V$ signal (integrated over the gap) in Fig. 4C shows a decay length of $(4\\pm1)\\textup{\\AA},$ matching well with DFT for simple ribbon edges (fig. S8). \n\nIn this material system, it is the covalent bonding between the orbitals of the Bi monolayer with the substrate that generates the large topological gap, as well as gives rise to the stabilization of the compound system. This is in contrast to earlier theory work on hypothetical free-standing material (15, 17, 29) which cannot be used for applications. In experiments with bulk (metallic) Bi crystals, pealed-off layers reportedly show QSH conductance quantization (30), and in spectroscopy topological states have been claimed at terrace steps (31). Edge states for a single Bi layer on $\\mathrm{Bi_{2}T e_{3}}$ of ${\\sim}2~\\mathrm{nm}$ extent have been detected (32) within a small gap of $\\mathrm{\\sim}70\\ \\mathrm{meV}$ , but with $E_{\\mathrm{{F}}}$ in the substrate valence band. In contrast, in our case $E_{\\mathrm{{F}}}$ resides within both the bismuthene gap $(\\sim0.8\\ \\mathrm{eV})$ as well as the SiC gap $(3.2~\\mathrm{eV})$ , so that conduction should solely be governed by the edge states. \n\nAlthough the topological character of the edge states has experimentally yet to be established, e.g., by a direct transport measurement of the QSH effect with its universal quantized conductance, the agreement between experimental evidence and theoretical prediction already strongly suggests that the QSH scenario in Bi/SiC is valid. For HgTe $(4,5)$ the gap is ${\\sim}30~\\mathrm{meV};$ , and in InAs/GaSb/AlSb quantum wells $\\left(6\\right)$ it is $\\mathrm{\\sim}4~\\mathrm{meV_{:}}$ , which necessitates experiments below $300~\\mathrm{{mK}}.$ . The key problem in these systems are the “charge puddles”, where defects push $E_{\\mathrm{{F}}}$ into the bulk bands, overriding the 1D channel $(7,8)$ . In contrast, the large-gap in bismuthene suggests it may be operational at room temperature. The domain size of $\\sim25\\ \\mathrm{nm}$ is expected to be increased by optimized epitaxial growth, facilitating transport measurements on patterned samples. \n\nOur work demonstrates the decisive role of the substrate for controlling the relevant orbitals in 2D QSH insulators. Here this approach is utilized to exploit the atomic (on-site) spin-orbit coupling to directly determine the topological energy gap. This kind of material engineering generates a paradigm in that it opens a systematic route to create largegap QSH systems in monolayer-substrate composites, e.g., by using other group-V elements. \n\n# REFERENCES AND NOTES \n\n1. C. L. Kane, E. J. Mele, Quantum spin Hall effect in graphene. Phys. Rev. Lett. 95, 226801 (2005). doi:10.1103/PhysRevLett.95.226801 Medline \n2. C. L. Kane, E. J. Mele, $\\mathcal{Z}_{2}$ topological order and the quantum spin Hall effect. Phys. Rev. Lett. 95, 146802 (2005). doi:10.1103/PhysRevLett.95.146802 Medline \n3. B. A. Bernevig, T. L. Hughes, S.-C. Zhang, Quantum spin Hall effect and topological phase transition in HgTe quantum wells. Science 314, 1757–1761 (2006). doi:10.1126/science.1133734 Medline \n4. M. König, S. Wiedmann, C. Brüne, A. Roth, H. Buhmann, L. W. Molenkamp, X.-L. Qi, S.-C. Zhang, Quantum spin hall insulator state in HgTe quantum wells. Science 318, 766–770 (2007). doi:10.1126/science.1148047 Medline \n5. A. Roth, C. Brüne, H. Buhmann, L. W. Molenkamp, J. Maciejko, X.-L. Qi, S.-C. Zhang, Nonlocal transport in the quantum spin Hall state. Science 325, 294–297 (2009). doi:10.1126/science.1174736 Medline \n6. I. Knez, R.-R. Du, G. Sullivan, Evidence for helical edge modes in inverted InAs/GaSb quantum wells. Phys. Rev. Lett. 107, 136603 (2011). doi:10.1103/PhysRevLett.107.136603 Medline \n7. M. König, M. Baenninger, A. G. F. Garcia, N. Harjee, B. L. Pruitt, C. Ames, P. Leubner, C. Brüne, H. Buhmann, L. W. Molenkamp, D. Goldhaber-Gordon, Spatially resolved study of backscattering in the quantum spin Hall state. Phys. Rev. X 3, 021003 (2013). doi:10.1103/PhysRevX.3.021003 \n8. J. I. Väyrynen, M. Goldstein, L. I. Glazman, Helical edge resistance introduced by charge puddles. Phys. Rev. Lett. 110, 216402 (2013). doi:10.1103/PhysRevLett.110.216402 Medline \n9. C.-C. Liu, W. Feng, Y. Yao, Quantum spin Hall effect in silicene and twodimensional germanium. Phys. Rev. Lett. 107, 076802 (2011). doi:10.1103/PhysRevLett.107.076802 Medline \n10. Y. Xu, B. Yan, H.-J. Zhang, J. Wang, G. Xu, P. Tang, W. Duan, S.-C. Zhang, Largegap quantum spin Hall insulators in tin films. Phys. Rev. Lett. 111, 136804 (2013). doi:10.1103/PhysRevLett.111.136804 Medline \n11. B. Lalmi, H. Oughaddou, H. Enriquez, A. Kara, S. Vizzini, B. Ealet, B. Aufray, Epitaxial growth of a silicene sheet. Appl. Phys. Lett. 97, 223109 (2010). doi:10.1063/1.3524215 \n12. P. Vogt, P. De Padova, C. Quaresima, J. Avila, E. Frantzeskakis, M. C. Asensio, A. Resta, B. Ealet, G. Le Lay, Silicene: Compelling experimental evidence for graphenelike two-dimensional silicon. Phys. Rev. Lett. 108, 155501 (2012). doi:10.1103/PhysRevLett.108.155501 Medline \n13. L. Zhang, P. Bampoulis, A. N. Rudenko, Q. Yao, A. van Houselt, B. Poelsema, M. I. Katsnelson, H. J. W. Zandvliet, Structural and electronic properties of germanene on MoS2. Phys. Rev. Lett. 116, 256804 (2016). doi:10.1103/PhysRevLett.116.256804 Medline \n14. F.-F. Zhu, W. J. Chen, Y. Xu, C. L. Gao, D. D. Guan, C. H. Liu, D. Qian, S.-C. Zhang, J. F. Jia, Epitaxial growth of two-dimensional stanene. Nat. Mater. 14, 1020–1025 (2015). doi:10.1038/nmat4384 Medline \n15. Z. Liu, C.-X. Liu, Y.-S. Wu, W.-H. Duan, F. Liu, J. Wu, Stable nontrivial $\\mathcal{Z}_{2}$ topology in ultrathin Bi (111) films: A first-principles study. Phys. Rev. Lett. 107, 136805 (2011). doi:10.1103/PhysRevLett.107.136805 Medline \n16. M. Wada, S. Murakami, F. Freimuth, G. Bihlmayer, Localized edge states in twodimensional topological insulators: Ultrathin Bi films. Phys. Rev. B 83, 121310 (2011). doi:10.1103/PhysRevB.83.121310 \n17. S. Murakami, Quantum spin Hall effect and enhanced magnetic response by spinorbit coupling. Phys. Rev. Lett. 97, 236805 (2006). doi:10.1103/PhysRevLett.97.236805 Medline \n18. M. Zhou, W. Ming, Z. Liu, Z. Wang, P. Li, F. Liu, Epitaxial growth of large-gap quantum spin Hall insulator on semiconductor surface. Proc. Natl. Acad. Sci. U.S.A. 111, 14378–14381 (2014). doi:10.1073/pnas.1409701111 Medline \n19. C.-H. Hsu, Z.-Q. Huang, F.-C. Chuang, C.-C. Kuo, Y.-T. Liu, H. Lin, A. Bansil, The nontrivial electronic structure of Bi/Sb honeycombs on SiC(0001). New J. Phys. 17, 025005 (2015). doi:10.1088/1367-2630/17/2/025005 \n20. T. Kuzumaki, T. Shirasawa, S. Mizuno, N. Ueno, H. Tochihara, K. Sakamoto, Reinvestigation of the Bi-induced Si (111)- $({\\sqrt{3}}\\times{\\sqrt{3}})$ surfaces by low-energy electron diffraction. Surf. Sci. 604, 1044–1048 (2010). doi:10.1016/j.susc.2010.03.022 \n21. R. H. Miwa, T. M. Schmidt, G. P. Srivastava, Bi covered Si(111) surface revisited. J. Phys. Condens. Matter 15, 2441–2447 (2003). doi:10.1088/0953- 8984/15/17/302 \n22. See supplementary materials. \n23. Y. Yao, F. Ye, X.-L. Qi, S.-C. Zhang, Z. Fang, Spin-orbit gap of graphene: Firstprinciples calculations. Phys. Rev. B 75, 041401 (2007). doi:10.1103/PhysRevB.75.041401 \n24. G.-F. Zhang, Y. Li, C. Wu, Honeycomb lattice with multiorbital structure: Topological and quantum anomalous Hall insulators with large gaps. Phys. Rev. B 90, 075114 (2014). doi:10.1103/PhysRevB.90.075114 \n25. D. Xiao, G.-B. Liu, W. Feng, X. Xu, W. Yao, Coupled spin and valley physics in monolayers of MoS2 and other group-VI dichalcogenides. Phys. Rev. Lett. 108, 196802 (2012). doi:10.1103/PhysRevLett.108.196802 Medline \n26. C.-C. Liu, S. Guan, Z. Song, S. A. Yang, J. Yang, Y. Yao, Low-energy effective Hamiltonian for giant-gap quantum spin Hall insulators in honeycomb Xhydride/halide $(X=N-B i)$ monolayers. Phys. Rev. B 90, 085431 (2014). doi:10.1103/PhysRevB.90.085431 \n27. E. Mariani, L. I. Glazman, A. Kamenev, F. von Oppen, Zero-bias anomaly in the tunneling density of states of grapheme. Phys. Rev. B 76, 165402 (2007). doi:10.1103/PhysRevB.76.165402 \n28. J. Voit, One-dimensional Fermi liquids. Rep. Prog. Phys. 58, 977–1116 (1995). doi:10.1088/0034-4885/58/9/002 \n29. A. Takayama, T. Sato, S. Souma, T. Oguchi, T. Takahashi, One-dimensional edge states with giant spin splitting in a bismuth thin film. Phys. Rev. Lett. 114, 066402 (2015). doi:10.1103/PhysRevLett.114.066402 Medline \n30. C. Sabater, D. Gosálbez-Martínez, J. Fernández-Rossier, J. G. Rodrigo, C. Untiedt, J. J. Palacios, Topologically protected quantum transport in locally exfoliated bismuth at room temperature. Phys. Rev. Lett. 110, 176802 (2013). doi:10.1103/PhysRevLett.110.176802 Medline \n31. I. K. Drozdov, A. Alexandradinata, S. Jeon, S. Nadj-Perge, H. Ji, R. J. Cava, B. Andrei Bernevig, A. Yazdani, One-dimensional topological edge states of bismuth bilayers. Nat. Phys. 10, 664–669 (2014). doi:10.1038/nphys3048 \n32. F. Yang, L. Miao, Z. F. Wang, M.-Y. Yao, F. Zhu, Y. R. Song, M.-X. Wang, J.-P. Xu, A. V. Fedorov, Z. Sun, G. B. Zhang, C. Liu, F. Liu, D. Qian, C. L. Gao, J.-F. Jia, Spatial and energy distribution of topological edge states in single Bi(111) bilayer. Phys. Rev. Lett. 109, 016801 (2012). doi:10.1103/PhysRevLett.109.016801 Medline \n33. S. Glass, F. Reis, M. Bauernfeind, J. Aulbach, M. R. Scholz, F. Adler, L. Dudy, G. Li, R. Claessen, J. Schäfer, Atomic-scale mapping of layer-by-layer hydrogen etching and passivation of SiC(0001) substrates. J. Phys. Chem. C 120, 10361– 10367 (2016). doi:10.1021/acs.jpcc.6b01493 \n34. T. Seyller, Passivation of hexagonal SiC surfaces by hydrogen termination. J. Phys. Condens. Matter 16, S1755 (2004). doi:10.1088/0953-8984/16/17/016 \n35. K. V. Emtsev, T. Seyller, L. Ley, L. Broekman, A. Tadich, J. D. Riley, R. G. C. Leckey, M. Preuss, Correlation effects at ideal SiC{0001}– $\\left\\langle1\\times1\\right\\rangle$ surfaces. Phys. Rev. B 73, 075412 (2006). doi:10.1103/PhysRevB.73.075412 \n36. G. Kresse, D. Joubert, From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). doi:10.1103/PhysRevB.59.1758 \n37. J. P. Perdew, K. Burke, M. Ernzerhof, Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). doi:10.1103/PhysRevLett.77.3865 Medline \n38. A. V. Krukau, O. A. Vydrov, A. F. Izmaylov, G. E. Scuseria, Influence of the exchange screening parameter on the performance of screened hybrid functionals. J. Chem. Phys. 125, 224106 (2006). doi:10.1063/1.2404663 Medline \n39. G. Kresse, J. Furthmüller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). doi:10.1103/PhysRevB.54.11169 Medline \n40. A. A. Mostofi, J. R. Yates, G. Pizzi, Y.-S. Lee, I. Souza, D. Vanderbilt, N. Marzari, An updated version of wannier90: A tool for obtaining maximally-localised Wannier functions. Comput. Phys. Commun. 185, 2309–2310 (2014). doi:10.1016/j.cpc.2014.05.003 \n41. J. C. Slater, G. F. Koster, Simplified LCAO method for the periodic potential problem. Phys. Rev. 94, 1498–1524 (1954). doi:10.1103/PhysRev.94.1498 \n42. H. Min, J. E. Hill, N. A. Sinitsyn, B. R. Sahu, L. Kleinman, A. H. MacDonald, Intrinsic and Rashba spin-orbit interactions in graphene sheets. Phys. Rev. B 74, 165310 (2006). doi:10.1103/PhysRevB.74.165310 \n43. L. Fu, C. Kane, Time reversal polarization and a $\\mathcal{Z}_{2}$ adiabatic spin pump. Phys. Rev. B 74, 195312 (2006). doi:10.1103/PhysRevB.74.195312 \n44. T. Fukui, Y. Hatsugai, Quantum spin Hall effect in three dimensional materials: Lattice computation of $Z_{2}$ topological invariants and its application to Bi and Sb. J. Phys. Soc. Jpn. 76, 053702 (2007). doi:10.1143/JPSJ.76.053702 \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Deutsche Forschungsgemeinschaft (DFG) under Grant SCHA1510/5, the SPP 1666 Priority Program “Topological Insulators”, the DFG Collaborative Research Center SFB 1170 “ToCoTronics” in Würzburg, as well as by the European Research Council (ERC) through ERC-StG-Thomale336012 “Topolectrics”. G. L. acknowledges the computing time granted at the Leibniz Supercomputing Centre (LRZ) in Munich. F. R. acknowledges many helpful discussions with M. R. Scholz and J. Aulbach. Competing Interests: The authors declare no competing financial interests. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/cgi/content/full/science.aai8142/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S10 \nReferences (33–44) \n\n15 August 2016; resubmitted 16 December 2016 \nAccepted 9 June 2017 \nPublished online 29 June 2017 \n10.1126/science.aai8142 \n\n![](images/b3d155c1fc8ac9e13da762b2cb71f072f0e6cfc1ec0ceda0ffe24d5f671f594f.jpg) \nFig. 1. Bismuthene on SiC(0001) structural model. (A) Sketch of a bismuthene layer placed on the threefold-symmetric SiC(0001) substrate in $(\\sqrt{3}\\times\\sqrt{3})\\ \\mathsf{R30}^{\\circ}$ commensurate registry. (B) Topographic STM overview map showing that bismuthene fully covers the substrate. The flakes are of $-25$ nm extent, limited by domain boundaries. (C) Substrate step height profile, taken along the red line in (B). The step heights correspond to SiC steps. (D) The honeycomb pattern is seen on smaller scanframes. (E) Close-up STM images for occupied and empty states (left and right panel, respectively). They confirm the formation of Bi honeycombs. \n\n![](images/eb5672a24b7a696c07c8492839caeb9e0ed5fb336ad5ed4b807a3be63e4d7eea.jpg) \nFig. 2. Theoretical band structure and ARPES measurements. (A) DFT band structure calculation (using a HSE exchange functional) including SOC, showing the wide band gap and a significant band splitting in the valence band (dashed line). (B) ARPES band dispersion through the Brillouin zone. The band maximum at K and the valence band splitting are in close agreement with the theoretical prediction (overlay). The zero of energy $(E_{F})$ is aligned to the Fermi level of the spectrometer. (C) Close-up of ARPES showing a valence band maximum at the $\\mathsf{K}$ -point with large SOC-induced splitting in a wide momentum range. (D) Constant energy surfaces from ARPES at various binding energies. The cut at low binding energies is taken at the topmost intensity corresponding to the valence band maximum. The maps are consistent with the six-fold degeneracy of the $k-$ and $\\mathsf{K}'$ -points of the hexagonal lattice. \n\n![](images/835b6284ea59035558a18401cfc3c542e1804b853ff0552ea3952fffe45b4269.jpg) \nFig. 3. Calculated electronic structure of the low-energy effective model of Bi $\\pmb{\\sigma}$ -bands. (A) The contribution of Bi $s$ and $p$ -orbitals to the electronic structure of bismuthene (without SOC). In each panel, the symbol size is proportional to the relative weight of the orbital. In Bi/SiC, $p_{x}$ - and $p_{y}$ -orbitals prevail around $E_{F}$ , demonstrating orbital decomposition. (B) Electronic structure of the low energy effective model without SOC. (C) Inclusion of the strong atomic SOC opens a huge gap at the K-point. (D) Further including the Rashba term lifts the degeneracy of the topmost valence band, and induces a large splitting with opposite spin character there. \n\n![](images/0bbed23e03254eee5eaccb600180b5c9c294b44f91652f9a84fd5aca6cfe7733.jpg) \nFig. 4. Tunneling spectroscopy of edge states at substrate steps. (A) Differential conductivity d I /dV (reflecting the LDOS) at different distances to the edge. A large gap of ${\\sim}0.8\\mathsf{e V}$ is observed in bulk bismuthene (black curve). Upon approaching the edge, additional signal of increasing strength emerges that fills the entire gap. Inset: STM measurement locations (color-coded dots relate to spectrum color) at uphill substrate step causing the boundary. (B) Spatially resolved d I /dV data across the same step. The d $I/{\\mathsf{d}}V$ signal of the ingap states peaks at both film edges (grey dashed lines mark d I /dV maxima). (C) Topographic $z(x)$ line profile of the step, and ${\\mathsf{d}}I/{\\mathsf{d}}V$ signal of bismuthene (integrated over the gap from $+0.15$ to $+0.55\\ \\mathrm{eV},$ , showing an exponential decrease away from the step edge, on either side. \n\n# Science \n\n# Bismuthene on a SiC substrate: A candidate for a high-temperature quantum spin Hall materia \n\nF. Reis, G. Li, L. Dudy, M. Bauernfeind, S. Glass, W. Hanke, R. Thomale, J. Schäfer and R. Claessen \n\npublished online June 29, 2017 \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1002_adma.201603276", + "DOI": "10.1002/adma.201603276", + "DOI Link": "http://dx.doi.org/10.1002/adma.201603276", + "Relative Dir Path": "mds/10.1002_adma.201603276", + "Article Title": "Black Phosphorus nullosheets as a Robust Delivery Platform for Cancer Theranostics", + "Authors": "Tao, W; Zhu, XB; Yu, XH; Zeng, XW; Xiao, QL; Zhang, XD; Ji, XY; Wang, XS; Shi, JJ; Zhang, H; Mei, L", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "2D black phosphorus (BP) nullo-materials are presented as a delivery platform. The endocytosis pathways and biological activities of PEGylated BP nullosheets in cancer cells are revealed for the first time. Finally, a triple-response combined therapy strategy is achieved by PEGylated BP nullosheets, showing a promising and enhanced antitumor effect.", + "Times Cited, WoS Core": 759, + "Times Cited, All Databases": 797, + "Publication Year": 2017, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000392729000008", + "Markdown": "# Black Phosphorus Nanosheets as a Robust Delivery Platform for Cancer Theranostics \n\nWei Tao, Xianbing Zhu, Xinghua Yu, Xiaowei Zeng, Quanlan Xiao, Xudong Zhang, Xiaoyuan Ji, Xusheng Wang, Jinjun Shi,\\* Han Zhang,\\* and Lin Mei\\* \n\nThe wave of research on 2D nanomaterials began in 2004, when the first graphene was exfoliated from graphite by a mechanical cleavage technique.[1,2] Over the past decade, an increasing number of monolayer/multilayer 2D nanomaterials with various unique physical and chemical properties have been widely studied and have shown promising applications in optoelectronics, electronics, energy storage and conversion, and biomedicine (e.g., therapeutic delivery, imaging/diagnosis, and biosensors).[3,4] Examples include transition-metal dichal­ cogenides (TMDs),[5] covalent–organic frameworks (COFs),[6] hexagonal boron nitride (h-BN),[7] metal–organic frameworks (MOFs),[8] layered double hydroxides (LDHs),[9] and black phos­ phorus (BP).[10] Among the large family of 2D nanomaterials, BP has recently attracted enormous attention due to its distinct structure with corrugated planes of $\\mathrm{\\DeltaP}$ atoms, which are con­ nected by strong intralayer $\\mathrm{{P-P}}$ bonding and weak interlayer van der Waals forces.[11] By breaking down the weak inter­ layer interactions, the bulk BP can be exfoliated into thin BP sheets with a few layers or even a monolayer. A layer-dependent bandgap of $0.3\\ \\mathrm{eV}$ to ${\\approx}2\\ \\mathrm{eV},$ as well as highly accurate opticalresponse properties and an anisotropic charge transport, can be achieved by controlling the structure, leading to fascinating electronic and photoelectronic applications of BP.[12] \n\nMore recently, a few studies have also shown the potential of BP nanomaterials in biomedical applications. For instance, ultrathin BP nanosheets (NSs) could generate efficient single oxygen and serve as effective photodynamic therapy (PDT) agents.[13] Because of the high extinction coefficient and photo­ thermal conversion efficiency, the latest reports have shown that there is promising potential for BP quantum dots (QDs) and BP nanoparticles (NPs) as a photothermal therapy (PTT) of cancer.[14,15] The cytotoxicity of BP nanomaterials was also preliminarily studied in these reports, showing no observable toxicity in various cells.[13–16] However, despite the few pio­ neering studies, the potential of using BP-based nanomaterials as a theranostic delivery platform has not been demonstrated. We expect that the BP NSs may have great possibility to enable efficient loading of theranostic agents, similar to graphene, $\\mathsf{M o S}_{2}$ , or other theranostic tools, because of the atomically thin 2D structure and relatively large surface area.[4,17] In addition, the biological activities of BP-based nanomaterials are closely related with the fate (e.g., pathway, location, biocompatibility, and biodegradability) of these nano-systems in cancer cells, playing a crucial role in an essential understanding of BP and other emerging 2D nanomaterials in cancer cells. Nevertheless, research on the biological activities of BP-based nanomaterials has also not been reported until now. \n\nHerein, we designed a theranostic delivery platform based on 2D BP NSs (Figure 1a), studied their biological activities by screening the endocytosis pathways in tumor cells, and finally applied this BP delivery platform in cancer theranostics. BP NSs were synthesized by a modified mechanical exfoliation method from bulk BP and were then functionalized with positively charged polyethylene glycol–amine $(\\mathrm{PEG-NH}_{2})$ via electrostatic adsorption to improve their biocompatibility and physiological stability. The developed PEGylated BP NSs could load thera­ nostic agents with high efficiency, such as doxorubicin (DOX) for chemotherapy and cyanine7 (Cy7) for in vivo near-infrared (NIR) imaging. The endocytosis pathways of PEGylated BP NSs were revealed with a final concentration in lysosomes (Figure 1b). With excellent biocompatibility, DOX-loaded PEGylated BP NSs exhib­ ited enhanced antitumor effects (i.e., photothermal-, chemo-, and biological response-induced therapy) both in vitro and in vivo. Therefore, our study demonstrated the promising use of BP as an innovative 2D platform for theranostic delivery and revealed the biological activities of PEGylated BP NSs in cancer cells for the first time, which we expect will provide insights for deep understanding of the emerging 2D nanomaterials. \n\nIn the first set of experiments, a modified mechanical exfoliation method[13] was adopted to prepare the 2D BP NSs (Figure S1, Supporting Information). Although organic solvents such as N-methyl-2-pyrrolidone (NMP) could also lead to good exfoliation efficiency,[11,18] we chose oxygen molecule-free water as the solvent for the mechanical exfoliation of bulk BP into NSs via probe sonication. This solvent will avoid the potential toxicity associated with organic solvents and ensure a clean surface of the obtained NSs for medical use. Due to the electron screening effect, BP NSs would aggregate and precipitate, especially in the presence of salts such as phosphate-buffered saline (PBS) and cell culture medium (Figure S2a,b,e, Supporting Informa­ tion). Therefore, after centrifugation to remove un-exfoliated BP, pure BP NSs were modified by ${\\mathrm{PEG}}-{\\mathrm{NH}}_{2}$ to enhance their stability in physiological medium. As presented in this study, the PEGylated BP NSs were observed with negligible agglom­ eration after one week of incubation, showing remarkable sta­ bility in PBS and cell culture medium (Figure S2a,c,d,f,g, Sup porting Information). The chemical composition and crystal structure of BP-PEG NSs were further confirmed by X-ray dif­ fractometry (XRD) and X-ray photoelectron spectroscopy (XPS). As shown in Figure S3 (Supporting Information), the BP-PEG NSs could be indexed into orthorhombic BP consistent with JCPDS No. 73-1358.[13,15] No other elements were detected except P, C, and O, indicating the high purity of the final product (Figure S4a, Supporting Information). The two strong peaks at ${\\approx}129.9\\$ and $\\approx130.7\\ \\mathrm{eV}$ are the $2{\\mathrm{p}}3/2$ and $2\\mathrm{p}1/2$ orbitals of zero-valent P in the $\\mathrm{~P~}2\\mathrm{p}$ spectrum, respectively (Figure S4b, Supporting Information). The weak peak at ${\\approx}134.0\\ \\mathrm{eV}$ is the signal of oxidized phosphorus due to the minor degradation on the surface of NSs as previously reported.[13] The hydrodynamic size of BP-PEG NSs in PBS and fetal bovine serum (FBS) was further monitored over a span of one week (Figure S5, Sup­ porting Information). This study further confirmed the stability of BP-PEG NSs, as their sizes had no significant change. The zeta potential of BP-based NSs was determined (Figure S6, Sup­ porting Information), and a relatively reduced surface charge of BP-PEG NSs was observed compared with that in a previous study $(-10.3\\mathrm{mV}$ in our study vs $-35.4\\mathrm{mV}_{.}$ ),[15] possibly attribut­ able to the inhibition of the partial oxidation of BP (formation of phosphate groups) via this modified method. \n\n![](images/def462d9a98ea659274a8708f58a46c10d0d5188d5643d322a0a82d3e4938753.jpg) \nFigure 1.  a) Schematic representation of the PEGylated BP theranostic delivery platform. $1\\colon P E G{\\mathrm{-}}N H_{2}$ (surface modification), 2: DOX (therapeutic agents), 3: $C y7-N H_{2}$ (NIR imaging agents), 4: FA-PEG $N\\mathsf{H}_{2}$ (targeting agents), 5: FITC-PEG $\\mathsf{N H}_{2}$ (fluorescent imaging agents). b) Screening and summary of the endocytosis pathways and biological activities of PEGylated BP NSs in cancer cells. \n\nTransmission electron microscopy (TEM) and atomic force microscopy (AFM) were used to characterize the surface mor­ phology of BP NSs pre- and post-PEGylation (Figure 2a–f). The average size of BP NSs was ${\\approx}120~\\mathrm{nm}$ (TEM and AFM), and the average height of BP NSs was ${\\approx}1{-}2~\\mathrm{nm}$ (AFM). For BP-PEG \n\n![](images/82a8bc57e7671471e1185016fe6d3ab2f0eba3e5da0b56fd33894495398215f8.jpg) \nFigure 2.  Characterization of PEGylated BP NSs. TEM images of a) BP NSs and b) BP-PEG NSs (scale bar $=200\\ \\mathsf{n m}$ ). AFM images of c) BP NSs and d) BP-PEG NSs (scale bar $=200\\ \\mathsf{n m}$ ). AFM measured thickness of e) BP NSs and f) BP-PEG NSs. g) STEM (scale bar $=60\\ \\mathsf{n m}$ ) and EDS mapping (scale bar $=40\\ \\mathsf{n m}$ ) of BP-PEG-FA NSs. h) UV–vis–NIR spectra of BP-PEG/DOX NSs at different DOX/NS feeding ratios after the removal of excess free DOX. i) DOX loading capacities on BP-PEG NSs $(w/w\\%)$ with increasing DOX/NS feeding ratios. \n\nNSs, the average size was ${\\approx}100~\\mathrm{nm}$ (TEM and AFM) and the average height was ${\\approx}2{-}3$ nm. The minimal decrease in the size of BP-PEG NSs was caused by additional sonication during the coating of ${\\mathrm{PEG}}-{\\mathrm{NH}}_{2}$ , and the slight increase in thickness could be attributed to a few amount of PEG that was coated on the NS surface.[19,20] To further demonstrate that ${\\mathrm{PEG}}{\\mathrm{-NH}}_{2}$ or other functionalized ${\\mathrm{PEG}}{\\mathrm{-NH}}_{2}$ such as folic acid (FA)- ${\\mathrm{PEG}}{\\mathrm{-NH}}_{2}$ could be successfully coated on the surface of BP NSs, we tested the Fourier transform infrared spectra (FT-IR) and scanning transmission electron microscopy (STEM) with energy dispersive X-ray spectroscopy (EDS) mapping of ele­ ments. With an absorption band at ${\\approx}2900~\\mathrm{cm^{-1}}$ that was attrib­ utable to the CH vibration in the PEG segment and character­ istic stretching vibration at ${\\approx}1637{-}1653~\\mathrm{cm^{-1}}$ from the amide bonding within FA structure, the coating of ${\\mathrm{PEG}}{\\mathrm{-NH}}_{2}$ or FA-PEG $\\cdot\\mathrm{NH}_{2}$ was confirmed (Figure S7, Supporting Informa­ tion). The feasibility of this coating method was also validated by STEM-EDS showing the excellent co-localization of four dif­ ferent elements (C, O, and N elements from the surface coating FA-PEG $\\boldsymbol{\\cdot}\\mathrm{NH}_{2}$ , and $\\mathrm{\\DeltaP}$ element from BP) in Figure $2\\mathrm{g}$ . Raman spectral analysis, which is an effective method for sample iden­ tification through detailed rotational and vibrational modes, was performed to verify the structure of PEGylated BP NSs (Figure  S8, Supporting Information). The Raman spectra of exfoliated BP NSs showed nearly the same peaks located at ${\\approx}363.6\\$ , 439.3, and $467.4~\\mathrm{cm}^{-1}$ with those of bulk BP reported previously,[13] which correspond to $\\mathrm{~A_{g}^{1},~B_{2g},}$ and $\\mathrm{A_{g}^{2}}$ modes of BP, respectively, suggesting that all prepared NSs did not have structural transformations compared with the corresponding bulk counterpart. A slight shift toward a low wavenumber could be found in PEGylated BP NSs, which could be caused by the slight change in the ultrathin height after PEG (or func­ tionalized PEG) coating.[21] Similar to the targeting modified ${\\mathrm{PEG}}{\\mathrm{-NH}}_{2}$ (i.e., $\\mathrm{FA\\mathrm{-}P E G\\mathrm{-}N H_{2}} $ ), the fluorescence-modified ${\\mathrm{PEG}}{\\mathrm{-NH}}_{2}$ (i.e., F $\\mathsf{\\vec{I}T C.P E G-N H_{2}})$ could also be coated on the surface of BP NSs with the same principle. The amount of PEG that was coated on the BP surface was ${\\approx}25.8\\%$ $(\\mathrm{w}/\\mathrm{w}\\ \\%)$ of the PEGylated BP NSs that was determined by the absorbance of FITC-labeled PEG. At the end of this part, the excellent photo­ thermal properties of BP-PEG NSs were tested and well dem­ onstrated (see the Supporting Information). \n\nIn the next set of experiments, we tested the use of BP-PEG NSs as a novel theranostic delivery platform. Since 2D nano­ materials such as TMDs, graphene, and their derivatives, which possess a relatively high surface area, have been widely reported as drug carriers to interact with various types of drug molecules,[2,20] the potential loading abilities of BP-based mate­ rials were well worth the expectation. A solution of BP-PEG NSs was mixed with DOX at different feeding ratios (DOX/NSs feeding ratios: 0.6, 1.2, 1.8, 2.4, 3, 3.6, and 4.2) and then stirred overnight. The UV–vis–NIR spectra were measured to calculate the drug-loading ratios of these BP-PEG NSs after removing excess free DOX molecules (Figure 2h). As the DOX/NSs feeding ratio increased, the loading capacity of DOX increased almost linearly and reached a saturation level at a DOX/NSs feeding ratio of 3 (Figure 2i). Our tested conditions showed that the saturation of DOX loading was tested to be $\\approx108\\%$ and that this was noticeably higher than many conventional NP-based nano-delivery systems with a usual range of $\\approx10\\%-30\\%$ for drug loading.[22] Moreover, the drug-release behavior of this novel delivery platform was further investigated in our studies. The DOX-loaded NSs (BP-PEG/DOX NSs) were dialyzed in PBS solution at different $\\mathrm{\\pH}$ values (7.4 and 5.0). The drugrelease kinetics was determined by collecting the released DOX molecules at different time intervals (Figures S12 and S13, Sup­ porting Information). ${\\approx}33.4\\%$ of DOX was released from the DOX-loaded NSs at $\\mathrm{pH}~5.0$ over a span of $24\\mathrm{~h~}$ while ${\\approx}15.2\\%$ of DOX was released at $\\mathrm{pH}~7.4$ in our studies. The cause of this release may be the protonation of the amino group pre­ sent on the sugar moiety of DOX. An NIR laser-induced local hyperthermia stimulus for the on/off control of the DOX release from BP-PEG/DOX NSs could also be observed, leading to a higher drug release of $54.4\\%$ . $\\mathrm{Cy}7{\\mathrm{-NH}}_{2}$ could be loaded on the surface of BP-PEG NSs using the similar method, and the Cy7-loaded NSs used in this study were ${\\approx}30.4\\%$ $(\\mathrm{w}/\\mathrm{w}\\ \\%)$ of $\\mathrm{Cy}7{\\mathrm{-NH}}_{2}$ on the NS surface (Figure S14, Supporting Information). Moreover, the fluorescence of loaded molecules could be quenched partially by PEGylated BP NSs, indicating strong interactions between drug molecules and BP-PEG NSs (Figure S15, Supporting Information).[20] \n\nAfter confirming the in vitro safety of these PEGylated BP NSs (see the Supporting Information), we next continued to evaluate the in vitro therapeutic effects of PEGylated BP NSs as single photothermal agents and as drug carriers based on their satisfactory performance. HeLa cells were selected as model cancer cells in our following studies. Through MTT assays, we could observe the excellent photothermal therapy (PTT) efficiency of BP NSs and BP-PEG NSs in promoting the death of cancer cells, since ${\\approx}90\\%$ of the cells were killed by only using $50~{\\upmu\\mathrm{g}}~\\mathrm{mL}^{-1}$ BP NSs or BP-PEG NSs (while ${\\approx}40\\%$ for $25~\\upmu\\mathrm{g}\\mathrm{\\mL^{-1}}$ irradiated with an $808~\\mathrm{nm}$ laser at $1.0\\mathrm{~W~cm}^{-2}$ for $10\\mathrm{min}$ compared with the cells without treatment (Figure S18a, Supporting Information). The results also demonstrated that PEGylation did not influence the great PTT effect of BP NSs. We subsequently tested the potential of these NSs as a drugdelivery platform for cancer chemotherapy with DOX as a model drug. BP-PEG/DOX NSs exhibited slightly reduced cytotoxicity compared with free DOX (Figure S18b, Supporting Information), similar to many nano-delivery platforms. These results may be attributed to the relatively slower endocytosis of the nano-delivery platform and additional process of intracel­ lular DOX release compared with free DOX molecules. In order to promote the therapeutic efficiency and construct specific tar­ geting delivery systems, we also introduced targeting modified BP-PEG-FA NSs to act as model nano-carriers for DOX due to the specific binding ability between FA and folate receptor overexpressed on many cancer cells, a finding that was also demon­ strated by many groups as well as by our previous studies.[23] Based on the former studies, quantitative flow cytometry (FCM) was used to further demonstrate the strong FA-mediated cancer targeting effect of BP-PEG-FA NSs. As shown in Figure S19 (Supporting Information), the cellular DOX fluorescence inten­ sity in HeLa cells after $^{1\\mathrm{h}}$ of incubation with BP-PEG-FA/DOX NSs was significantly higher than BP-PEG/DOX NSs, proving a higher cellular uptake efficiency of BP-PEG-FA/DOX NSs. Furthermore, the in vitro cellular toxicity of BP-PEG-FA NSs as photothermal agents and BP-PEG-FA/DOX NSs as chemo­ therapy agents was both effectively enhanced compared with that of BP-PEG NSs and BP-PEG/DOX NSs, also indicating the good in vitro targeting effect of BP-PEG-FA NSs. Taken together, the results indicated that PEGylated BP NSs could be utilized to develop a versatile and functionalized delivery plat­ form and that they are very promising for application in cancer theranostics due to the excellent PTT effect, high-loading effi­ ciency, and especially low toxicity. \n\nIn the third set of experiments, we performed a biolog­ ical study of this delivery platform in cancer cells. When the PEGylated BP NSs reached the external milieu of cancer cells through long-term circulation, they could interact with the surface of the cell plasma membrane. The interaction results in the internalization of PEGylated BP NSs through a process termed endocytosis, either clathrin-dependent or clathrin-inde­ pendent.[24] The clathrin-independent pathways are divided into (1) macropinocytosis, (2) caveolae-independent endocytosis, and (3) caveolae-dependent endocytosis. Macropinocytosis is controlled by Rab34, which is considered a biomarker of this process. The caveolae-independent endocytosis mainly includes flotillin-, Arf6-, Cdc42-, and RhoA-dependent endocytosis.[25] Fluorescent imaging agents FITC-labeled BP-PEG (BP-PEGFITC) NSs were employed in the screening of all the possible endocytosis pathways of these NSs. The BP-PEG-FITC NSs could be internalized by HeLa cells efficiently after $^{4\\mathrm{h}}$ of incu­ bation (Figure S20, Supporting Information). Moreover, macro­ pinocytosis and caveolae-dependent endocytosis are involved in the entry of the BP-PEG-FITC NSs into the cells. We observed both co-localization of FITC-positive vesicles with caveolaepositive vesicles (Figure 3a) and FITC-positive vesicles with Rab34-positive vesicles (Figure 3b). However, no merging of FITC-positive vesicles with clathrin-, flotillin-, Arf6-, Cdc42-, or RhoA-positive vesicles was found (Figures S21–S25, Supporting Information). These results suggested that the pathways for PEGylated BP NSs occur mainly through caveolae-dependent endocytosis and macropinocytosis but not via the clathrindependent pathway. \n\nIn the classic endocytosis pathways, nano-systems would be transported to early endosomes, late endosomes soon afterward, and finally lysosomes after being internalized into the cells. Rab5 and EEA1 are widely used markers in early endosomes, whereas Rab7 is used as a marker of late endosomes.[26] We then verified whether our PEGylated BP NSs would be transported via this pathway by detecting the co-localization between caveolae and DsRed-Rab5 (Figure S26a, Supporting Information) since cav­ eolae-positive vesicles may deliver BP-PEG-FITC NSs to early endosomes and then transport them to late endosomes. As pre­ sented in our studies, BP-PEG-FITC NSs co-localized perfectly with both DsRed-Rab5-labeled early endosomes and DsRedRab7-marked late endosomes (Figure 3c,d). Furthermore, BPPEG-FITC NSs merged well with the lysosomes while the LysoTracker was used to mark lysosomes (Figure 3e). These results indicated that BP-PEG-FITC NSs were taken up by cells through caveolae-dependent endocytosis and were then transported to early endosomes and late endosomes, and finally degraded in lysosomes through the classic endocytosis pathway. However, in the macropinocytosis pathway, we did not find that DsRed-Rab34 co-localized with EEA1-labeled early endosomes (Figure  S26b, Supporting Information). In contrast, DsRed-Rab34 co-localized well with DsRed-Rab7-labeled late endosomes (Figure S26c, \n\nSupporting Information). These data implied that “macropino­ cytosis (Rab34-labeled) $\\rightarrow$ late endosomes (Rab7-labeled) $\\rightarrow$ lys­ osomes” could be a novel endocytosis pathway in the turnover of BP-PEG-FITC NSs (Figure 1b). \n\nAfter revealing the endocytosis pathways, we then studied the biological activities of PEGylated BP NSs and focused on autophagy studies since it could sequester most nanomaterials and transport them to lysosomes for degradation.[27] To test the relationship between PEGylated BP NSs and autophagy, LC3-II protein and P62 protein were used as autophagy marker pro­ teins.[28] After incubation with BP-PEG-FITC NSs for $24\\mathrm{~h~}$ , the LC3-II protein levels were increased and P62 protein levels were reduced in the cells (Figure 3f). Furthermore, autophago­ somes were significantly increased as shown in Figure 3g, indicating that PEGylated BP NSs could induce autophagy in cancer cells. We further found that P62, which is a marker of sequestosome1 (SQSTM1) and an adapter molecule that selectively recognized and bound the substrates of autophagy, co-localized with BP-PEG-FITC NSs (Figure S27a, Supporting Information). LC3, which is a marker of autophagosomes, could interact directly with P62/SQSTM1 and capture P62 on the isolation membrane. We observed co-localization between P62-positive sequestosome1 and LC3-positive autophagosomes (Figure S27b, Supporting Information). As expected, we also perceived that BP-PEG-FITC NSs containing vesicles merged perfectly with LC3-positive autophagosomes (Figure S28a, Sup­ porting Information). P62-positive sequestosome1 selects the target, and LC3-positive autophagosomes select P62. Finally, autophagosomes containing BP-PEG-FITC NSs translocated to fuse with lysosomes for degradation (Figure S28b, Supporting Information). These results advocated P62-positive seques­ tosome1 targeted BP-PEG-FITC NSs and transported them to LC3-positive autophagosomes. The autophagosomes then delivered them to lysosomes. Therefore, in addition to classic endocytosis pathways, autophagy was demonstrated to be involved in the degradation of PEGylated BP NSs. \n\nSince the PEGylated BP NSs were finally concentrated in the lysosomes for degradation, we may further enhance the thera­ peutic effect and reduce the dose of PEGylated BP NSs by inhib­ iting the activities of lysosomes and autophagy. To verify this, Chloroquine (CQ), which is a lysosome tropic agent that pre­ vents endosomal acidification, blocks the fusion of autophago­ somes with lysosomes and disrupts lysosomes,[29] was utilized in this part of our studies. We incubated pre-treated HeLa cells ( $30\\times10^{-6}$ m free CQ, $24\\mathrm{~h~}$ incubation) with BP-PEG NSs and BP-PEG-FA NSs at low concentrations (5, 10, and $25~\\upmu\\mathrm{g}\\ \\mathrm{mL}^{-1},$ ), as well as HeLa cells without pre-treated (i.e., free from CQ). After $^{4\\mathrm{h}}$ of incubation with these NSs, HeLa cells were washed with PBS three times, placed into medium, and then irradi­ ated with an $808~\\mathrm{nm}$ NIR laser at $1.0\\ \\mathrm{W\\cm}^{-2}$ for $10~\\mathrm{min}$ . As expected, the cell viability decreased in the presence of CQ molecules in both BP-PEG NSs and BP-PEG-FA NSs groups compared with the CQ-free BP-PEG NSs and BP-PEG-FA NSs groups (Figure 3h). Moreover, free CQ did not show observable toxicity to HeLa cells at our tested concentration. Thus, the ther­ apeutic effects could be caused by the inhibition of lysosomes and blockade of the fusion between autophagosomes and lys­ osomes under the effect of CQ, which may reduce the degra­ dation of PEGylated BP NSs. We further introduced DOX-load \n\n![](images/f582276f9be302fcc7d8b82ecc410500c9caa3511a19727d987fb1e833b44674.jpg) \nFigure 3.  Endocytosis pathways and biological activities of PEGylated BP NSs. a) CLSM images of HeLa cells incubated with BP-PEG-FITC NSs for $4\\ h$ , while caveolae were detected with primary antibodies against caveolae. CLSM images of HeLa cells transfected with b) DsRed-Rab34, c) DsRed-Rab5, and d) DsRed-Rab7 after $4h$ of incubation with BP-PEG-FITC NSs. e) For lysosome detection, the HeLa cells were treated with BPPEG-FITC NSs for $4h$ and then were treated with Lyso-Tracker probes for 30 min. f) HeLa cells were treated with BP-PEG NSs for $24\\ h$ , and then the LC3I/II and P62 protein levels were analyzed by western blotting. Histograms represent the quantitative analysis of LC3 and P62 protein expression performed by Image J, respectively (\\* $P<0.05$ , $\\because P<0.01$ ). g) EGFP-LC3-transfected HeLa cells were treated with BP-PEG NSs for $24\\ h$ , and then quantification of cells with EGFP-LC3 vesicles was performed $(^{1}\\ast\\ast P<0.07)^{\\prime},$ ). h) Relative viabilities of HeLa cells after different types of treatment at different BP concentrations (5, 10, and $25\\upmu\\mathrm{g}\\mathsf{m}\\mathsf{L}^{-1}$ ). HeLa cells treated with only BP-PEG NSs or CQ $(30\\times70^{-6}~\\mathrm{m})$ was used as control (\\* $P<0.05$ , $\\because P<0.01$ , $\\because0.001$ ). \n\nNSs for the enhanced therapy of cancer in vitro. Even at a low DOX concentration $(5\\ \\upmu\\mathrm{g}\\ \\mathrm{mL}^{-1}.$ ), the cell viability in groups treated with three factors (NIR, CQ, and DOX) was significantly decreased because of the synergistic effect compared with that in previous groups. Until now, we confirmed the excellent in vitro therapeutic effect of these PEGylated BP NSs, which were attributed to the PTT effect triggered by the NIR irradiation of BP-based NSs, DOX-induced chemotherapy, and CQ-mediated inhibition of lysosomes and autophagy. \n\nIn the final set of the experiments, we carried out animal assays to test the possibilities of the PEGylated BP theranostic delivery platform for in vivo application as inspired by so many exciting in vitro results. We first studied the in vivo distribution and tumor accumulation of our BP delivery platform via Cy7- loaded PEGylated BP NSs. After intravenous (i.v.) injection of BP-PEG/Cy7 NSs and BP-PEG-FA/Cy7 NSs at different time frames (1, 12, and $24\\mathrm{h}$ ), a whole-animal NIR imaging approach was utilized to monitor the dynamic change of fluorescent PEGylated BP NSs and their tumor accumulation (Figure 4a and Figure S29, Supporting Information). As presented in the results, Cy7-loaded PEGylated BP NSs were distributed throughout the whole body with strong fluorescence signals at 1 h post-injection. At $^{12\\mathrm{~h~}}$ post-injection, the fluorescence sig­ nals in both groups decreased due to the clearance of the dye by the body. Meanwhile, more signals were detected in the tumor tissues of the BP-PEG-FA NSs group than in those of the BP-PEG NSs group. At $24\\mathrm{h}$ post-injection, the fluorescence sig­ nals continued to wane in both groups. However, strong fluo­ rescence signals could be observed in the tumor tissues of both groups, demonstrating good tumor accumulation of PEGylated BP NSs through the blood circulation and an enhanced perme­ ability retention (EPR) effect. Moreover, stronger signals of the BP-PEG-FA/Cy7 NSs group than those of the BP-PEG/Cy7 NSs group could further demonstrate the in vivo targeting effect of BP-PEG-FA NSs, indicating versatile modification such as the targeting effect being very feasible with our PEGylated BP NSs. We further confirmed the good in vivo tumor accumula­ tion of our PEGylated BP NSs and their versatile ability to be in vivo targeting via the ex vivo study of excised organs at $24\\mathrm{h}$ post-injection (Figure 4b,c). The fluorescence signals remained majorly in the liver and kidney because Cy7 is metabolized throughout the liver (liver Kupffer cells play an important role in the uptake and degradation in extra-phagocytosis) and excreted through the kidney. The signals in the lung could be caused by the mechanical retention of larger-sized NSs in lung capillaries. These biodistribution results were in good agree ment with the excellent long circulation confirmed by pharma­ cokinetic studies (Figure S30, Supporting Information). \n\n![](images/60e83f78d03d77a1fad96c6540144a8ca16b59a8d88212fb0783949a759ad6fe.jpg) \nFigure 4.  In vivo NIR imaging and antitumor effect of PEGylated BP NSs. a) Time-lapse NIR bio-imaging of nude mice. The tumors were circled with a red-dotted line. G1: BP-PEG/Cy7 NSs group; G2: BP-PEG-FA/Cy7 NSs group. b) NIR bio-imaging of major organs and tumors after i.v. injection at $24\\ h$ . H: Heart; LI: Liver; S: Spleen; LU; Lung; K: Kidney; T: Tumor. c) Semi-quantitative biodistribution of BP-PEG/Cy7 NSs and BP-PEG-FA/Cy7 NSs in nude mice measured by the averaged fluorescence intensity of organs and tumors. d) Inhibition of HeLa tumor growth after different treatments (\\* $P<0.05$ , \\*\\* $P<0.01$ ). Group 1: Saline; Group 2: CQ; Group 3: DOX; Group 4: BP-PEG-FA/DOX; Group 5: BP-PEG-FA $^+$ NIR; Group 6: BP-PEG$\\mathsf{F A}+\\mathsf{N l R}+\\mathsf{C Q}$ ; Group 7: BP-PEG-FA/DOX + NIR + CQ. e) Morphology of tumors removed from the sacrificed mice in all groups at the end point of study. f) H&E stained histological images of tissue sections from major organs after $\\rceil4\\mathrm{~d~}$ of treatment with BP-PEG-FA NSs, BP-PEG-FA ${\\mathsf{N S s}}+{\\mathsf{C Q}}$ , and BP-PEG-FA/DOX ${\\mathsf{N S s}}+{\\mathsf{C Q}}$ . Saline was used as a control. \n\nBased on the in vivo biological response (see the Supporting Information) and enhanced in vitro therapeutic effects, we car­ ried out an in vivo antitumor study to validate the enhanced therapy of cancer using our PEGylated BP theranostic delivery platform. BP-PEG-FA NSs were chosen as the model NSs considering their in vivo targeting effect. The tumor-bearing nude mice were treated with Group 1: saline (control), Group 2: CQ (biological response-induced therapy control), Group 3: DOX (chemotherapy control), Group 4: BP-PEG-FA/DOX NSs (chemotherapy with delivery platform group), Group 5: BPPEG-FA $\\mathrm{NSs\\+\\NIR}$ (PTT group), Group 6: BP-PEG-FA NSs with i.t.-injected $\\mathrm{CQ}+\\mathrm{NIR}$ (PTT $^+$ biological response-induced therapy group), and Group 7: BP-PEG-FA/DOX $\\mathrm{NSs\\+\\NIR}$ with i.t.-injected CQ (combined triple-response therapy group: chemotherapy $+\\mathrm{\\PTT{\\Sigma}^{+}}$ biological response induced therapy) at the same dose. Groups 5–7 were treated with an $808\\ \\mathrm{nm}$ laser at $1\\mathrm{~W~cm}^{-2}$ for $10\\ \\mathrm{min}$ at tumor sites after $24\\mathrm{~h~}$ injec­ tion. The tumor volumes were calculated based on the width and length of the tumors that were measured every 2 d during the 2 week-treatment (Figure 4d). As displayed in our studies, compared with saline, Groups 3–7 all showed decreasing tumor growth in mice. A better therapeutic effect could be observed in Groups 4 and 5 compared with Group 3 (clinical chemotherapy drug), indicating the promising application of PEGylated BP NSs as drug carriers and PTT agents. Moreover, a significant therapeutic effect could be found in both Groups 6 and 7, dem­ onstrating that the enhanced antitumor effect of PEGylated BP NSs could be achieved by this combined therapy strategy. Group 7 showed the best therapeutic effect, which was in good agreement with the in vitro toxicity results. CQ seemed to minimally inhibit tumors compared with saline, indicating that the enhanced therapy effect could be caused by inhibiting the degradation of the BP-based NSs. Meanwhile, we found that the body weights of nude mice were not significantly affected, demonstrating that there were no acute side effects in our com­ bined therapy (Figure S32, Supporting Information). At the end of the 2 week-treatment, all nude mice were euthanized and the tumors were collected, clearly showing the excellent thera­ peutic effect of our PEGylated BP NSs in the enhanced therapy of cancer (Figure 4e). No tissue damage could be found in the major organs in any experimental group as assessed by H&E staining (Figure 4f). Moreover, no observable side effect or tox­ icity of our PEGylated BP NSs was found even at a higher dose of $10\\mathrm{mg}\\mathrm{kg}^{-1}$ in the in vivo toxicity studies (see the Supporting Information), indicating the promising in vivo application of this BP theranostic delivery platform. However, many more sys­ tematic studies still need to be performed before future clinical studies of these PEGylated BP NSs, as well as some bio- and immune-compatibility studies.[30] \n\nIn summary, we have demonstrated the promising appli­ cation of BP NSs as a robust delivery platform for the first time, thus opening an exciting and new research point of 2D BP nanomaterials as a delivery vehicle. Furthermore, we have revealed the biological activities and screened the endocytosis pathways of PEGylated BP NSs in cancer cells for the first time, providing guidance for the essential understanding of BP and other emerging 2D nanomaterials for cancer theranostics. A triple-response combined therapy strategy was proposed with these PEGylated BP NSs for cancer treatment. Both in vitro and in vivo experiments verified the safety and enhanced antitumor effect of this platform. Finally, with the flexible modification with functionalized ${\\mathrm{PEG}}{\\mathrm{-NH}}_{2}$ and great biosafety, these BP NSs could provide a robust platform for cancer theranostics. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThe Administrative Committee on Animal Research in Tsinghua University approved the protocols for all animal assays in this paper. W.T., X.Z. and X.Y. contributed equally to this work. The authors acknowledge the financial support from the National Institutes of Health (NIH) Grants (R00CA160350 and CA200900), Tsinghua Scholarship for Overseas Graduate Studies (2013159), National Natural Science Foundation of China (61435010 and 31270019), Guangdong Natural Science Funds for Distinguished Young Scholar (2014A030306036), Natural Science Foundation of Guangdong Province (2016A030310023 and 2015A030313848), Science and Technology Planning Project of Guangdong Province (2016A020217001), Science and Technology Innovation Commission of Shenzhen (KQTD2015032416270385, JCYJ20150625103619275, JCYJ20150430163009479, JCYJ201603080922 49215 and JCYJ20160301152300347), and Natural Science Foundation of SZU (827/000010). The authors are also grateful for Dr. Ling Ji’s assistance with the blood routine test (BRT) at Peking University Shenzhen Hospital. \n\nReceived: June 22, 2016 \nRevised: August 18, 2016 \nPublished online: October 31, 2016 \n\n[1]\t a) K. S.  Novoselov, A. K.  Geim, S. V.  Morozov, D.  Jiang, Y.  Zhang, S. V.  Dubonos, I. V.  Grigorieva, A. A.  Firsov, Science 2004, 306, 666; b) H. Zhang, ACS Nano 2015, 9, 9451; c) Y. Zhang, T.-T. Tang, C.  Girit, Z.  Hao, M. C.  Martin, A.  Zettl, M. F.  Crommie, Y. R.  Shen, F. Wang, Nature 2009, 459, 820; d) X. Peng, L. Peng, C. Wu, Y. Xie, Chem. Soc. Rev. 2014, 43, 3303; e) X. Li, J. Zhu, B. Wei, Chem. Soc. Rev. 2016, 45, 3145; f) X. Cao, C. Tan, X. Zhang, W. Zhao, H. Zhang, Adv. Mater. 2016, 28, 6167. \n[2]\t Y. Chen, C. Tan, H. Zhang, L. Wang, Chem. Soc. Rev. 2015, 44, 2681. \n[3]\t a) X. Huang, C. Tan, Z. Yin, H. Zhang, Adv. Mater. 2014, 26, 2185; b) R. Kurapati, K. Kostarelos, M. Prato, A. Bianco, Adv. Mater. 2016, 28, 6052; c) G. Yang, C. Zhu, D. Du, J. Zhu, Y. Lin, Nanoscale 2015, 7, 14217. \n[4]\t D. Chimene, D. L. Alge, A. K. Gaharwar, Adv. Mater. 2015, 27, 7261. \n[5]\t X. Qian, J. Liu, L. Fu, J. Li, Science 2014, 346, 1344. \n[6]\t S.  Lin, C. S.  Diercks, Y. B.  Zhang, N.  Kornienko, E. M.  Nichols, Y.  Zhao, A. R.  Paris, D.  Kim, P.  Yang, O. M.  Yaghi, C. J.  Chang, Science 2015, 349, 1208. \n[7]\t a) T. T. Tran, K. Bray, M. J. Ford, M. Toth, I. Aharonovich, Nat. Nanotechnol. 2016, 11, 37; b) Z.  Liu, L.  Ma, G.  Shi, W.  Zhou, Y.  Gong, S.  Lei, X.  Yang, J.  Zhang, J.  Yu, K. P.  Hackenberg, A.  Babakhani, J. C. Idrobo, R. Vajtai, J. Lou, P. M. Ajayan, Nat. Nanotechnol. 2013, 8, 119. \n[8]\t S. S.  Han, J. L.  Mendoza-Cortes, W. A.  Goddard, Chem. Soc. Rev. 2009, 38, 1460. \n[9]\t P. J. Sideris, U. G. Nielsen, Z. Gan, C. P. Grey, Science 2008, 321, 113. \n[10]\t a) F. Xia, H. Wang, Y. Jia, Nat. Commun. 2014, 5, 4458; b) C. R. Ryder, J. D. Wood, S. A. Wells, Y. Yang, D. Jariwala, T. J. Marks, G. C. Schatz, M. C. Hersam, Nat. Chem. 2016, 8, 597. \n[11]\t P.  Yasaei, B.  Kumar, T.  Foroozan, C.  Wang, M.  Asadi, D.  Tuschel, J. E. Indacochea, R. F. Klie, A. Salehi-Khojin, Adv. Mater. 2015, 27, 1887. \n[12]\t a) X.  Ling, H.  Wang, S.  Huang, F.  Xia, M. S.  Dresselhaus, Proc. Natl. Acad. Sci. USA 2015, 112, 4523; b) L. Li, Y. Yu, G. J. Ye, Q. Ge, X.  Ou, H.  Wu, D.  Feng, X. H.  Chen, Y.  Zhang, Nat. Nanotechnol. 2014, 9, 372; c) S.  Das, W.  Zhang, M.  Demarteau, A.  Hoffmann, M. Dubey, A. Roelofs, Nano Lett. 2014, 14, 5733. \n[13]\t H.  Wang, X.  Yang, W.  Shao, S.  Chen, J.  Xie, X.  Zhang, J.  Wang, Y. Xie, J. Am. Chem. Soc. 2015, 137, 11376. \n[14]\t Z.  Sun, H.  Xie, S.  Tang, X.-F.  Yu, Z.  Guo, J.  Shao, H.  Zhang, H. Huang, H. Wang, P. K. Chu, Angew. Chem. 2015, 127, 11688. \n[15]\t C.  Sun, L.  Wen, J.  Zeng, Y.  Wang, Q.  Sun, L.  Deng, C.  Zhao, Z.  Li, Biomaterials 2016, 91, 81. \n[16]\t N. M.  Latiff, W. Z.  Teo, Z.  Sofer, A. C.  Fisher, M.  Pumera, Chem. - Eur. J. 2015, 21, 13991. \n[17]\t a) M. Orecchioni, R. Cabizza, A. Bianco, L. G. Delogu, Theranostics 2015, 5, 710; b) K.  Yang, L.  Feng, X.  Shi, Z.  Liu, Chem. Soc. Rev. 2013, 42, 530. \n[18]\t J.  Kang, J. D.  Wood, S. A.  Wells, J. H.  Lee, X.  Liu, K. S.  Chen, M. C. Hersam, ACS Nano 2015, 9, 3596. \n[19]\t L.  Cheng, J.  Liu, X.  Gu, H.  Gong, X.  Shi, T.  Liu, C.  Wang, X.  Wang, G.  Liu, H.  Xing, W.  Bu, B.  Sun, Z.  Liu, Adv. Mater. 2014, 26, 1886. \n[20]\t T.  Liu, C.  Wang, X.  Gu, H.  Gong, L.  Cheng, X.  Shi, L.  Feng, B.  Sun, Z. Liu, Adv. Mater. 2014, 26, 3433. \n[21]\t a) A.  Favron, E.  Gaufres, F.  Fossard, A. L.  Phaneuf-L’Heureux, N. Y.  Tang, P. L.  Levesque, A.  Loiseau, R.  Leonelli, S.  Francoeur, R.  Martel, Nat. Mater. 2015, 14, 826; b) X.  Zhang, H.  Xie, Z.  Liu, C.  Tan, Z.  Luo, H.  Li, J.  Lin, L.  Sun, W.  Chen, Z.  Xu, L.  Xie, W.  Huang, H.  Zhang, Angew. Chem. Int. Ed. 2015, 54, 3653. \n[22]\t a) W. Tao, X. Zeng, J. Wu, X. Zhu, X. Yu, X. Zhang, J. Zhang, G. Liu, L.  Mei, Theranostics 2016, 6, 470; b) X.  Zeng, W.  Tao, L.  Mei, L. Huang, C. Tan, S. S. Feng, Biomaterials 2013, 34, 6058. \n[23]\t W.  Tao, J.  Zhang, X.  Zeng, D.  Liu, G.  Liu, X.  Zhu, Y.  Liu, Q.  Yu, L. Huang, L. Mei, Adv. Healthcare Mater. 2015, 4, 1203. \n[24]\t S. D. Conner, S. L. Schmid, Nature 2003, 422, 37. \n[25]\t S. Mayor, R. E. Pagano, Nat. Rev. Mol. Cell Biol. 2007, 8, 603. \n[26]\t G. Sahay, D. Y. Alakhova, A. V. Kabanov, J. Controlled Release 2010, 145, 182. \n[27]\t J. J.  Li, D.  Hartono, C. N.  Ong, B. H.  Bay, L. Y.  Yung, Biomaterials 2010, 31, 5996. \n[28]\t a) S.  Pankiv, T. H.  Clausen, T.  Lamark, A.  Brech, J. A.  Bruun, H. Outzen, A. Overvatn, G. Bjorkoy, T. Johansen, J. Biol. Chem. 2007, 282, 24131; b) Y.  Kabeya, N.  Mizushima, T.  Ueno, A.  Yamamoto, T. Kirisako, T. Noda, E. Kominami, Y. Ohsumi, T. Yoshimori, EMBO J. 2000, 19, 5720. \n[29]\t a) X.  Zhang, Y.  Dong, X.  Zeng, X.  Liang, X.  Li, W.  Tao, H.  Chen, Y. Jiang, L. Mei, S.-S. Feng, Biomaterials 2014, 35, 1932; b) X. Zhang, Y.  Yang, X.  Liang, X.  Zeng, Z.  Liu, W.  Tao, X.  Xiao, H.  Chen, L. Huang, L. Mei, Theranostics 2014, 4, 1085. \n[30]\t a) M.  Orecchioni, D. A.  Jasim, M.  Pescatori, R.  Manetti, C.  Fozza, F. Sgarrella, D. Bedognetti, A. Bianco, K. Kostarelos, L. G. Delogu, Adv. Healthcare Mater. 2016, 5, 276; b) M. Pescatori, D. Bedognetti, E. Venturelli, C. Ménard-Moyon, C. Bernardini, E. Muresu, A. Piana, G.  Maida, R.  Manetti, F.  Sgarrella, A.  Bianco, L. G.  Delogu, Biomaterials 2013, 34, 4395; c) M. J.  Sailor, J.-H.  Park, Adv. Mater. 2012, 24, 3779. " + }, + { + "id": "10.1073_pnas.1708489114", + "DOI": "10.1073/pnas.1708489114", + "DOI Link": "http://dx.doi.org/10.1073/pnas.1708489114", + "Relative Dir Path": "mds/10.1073_pnas.1708489114", + "Article Title": "An anion-immobilized composite electrolyte for dendrite-free lithium metal anodes", + "Authors": "Zhao, CZ; Zhang, XQ; Cheng, XB; Zhang, R; Xu, R; Chen, PY; Peng, HJ; Huang, JQ; Zhang, Q", + "Source Title": "PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA", + "Abstract": "Lithium metal is strongly regarded as a promising electrode material in next-generation rechargeable batteries due to its extremely high theoretical specific capacity and lowest reduction potential. However, the safety issue and short lifespan induced by uncontrolled dendrite growth have hindered the practical applications of lithium metal anodes. Hence, we propose a flexible anion-immobilized ceramic-polymer composite electrolyte to inhibit lithium dendrites and construct safe batteries. Anions in the composite electrolyte are tethered by a polymer matrix and ceramic fillers, inducing a uniform distribution of space charges and lithium ions that contributes to a dendrite-free lithium deposition. The dissociation of anions and lithium ions also helps to reduce the polymer crystallinity, rendering stable and fast transportation of lithium ions. Ceramic fillers in the electrolyte extend the electrochemically stable window to as wide as 5.5 V and provide a barrier to short circuiting for realizing safe batteries at elevated temperature. The anion-immobilized electrolyte can be applied in all-solid-state batteries and exhibits a small polarization of 15 mV. Cooperated with LiFePO4 and LiNi0.5Co0.2Mn0.3O2 cathodes, the all-solid-state lithium metal batteries render excellent specific capacities of above 150 mAh.g(-1) and well withstand mechanical bending. These results reveal a promising opportunity for safe and flexible next-generation lithium metal batteries.", + "Times Cited, WoS Core": 744, + "Times Cited, All Databases": 796, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000413237900037", + "Markdown": "# An anion-immobilized composite electrolyte for dendrite-free lithium metal anodes \n\nChen-Zi Zhaoa,1, Xue-Qiang Zhanga,1, Xin-Bing Chenga,1, Rui Zhanga, Rui $\\mathsf{\\mathbf{x}}\\mathsf{\\mathbf{u}}^{\\mathsf{\\mathbf{b}}}$ , Peng-Yu Chena, Hong-Jie Penga, Jia-Qi Huangb, and Qiang Zhanga,2 \n\naBeijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; and bAdvanced Research Institute for Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China \n\nEdited by Thomas E. Mallouk, The Pennsylvania State University, University Park, PA, and approved September 8, 2017 (received for review May 22, 201 \n\nLithium metal is strongly regarded as a promising electrode material in next-generation rechargeable batteries due to its extremely high theoretical specific capacity and lowest reduction potential. However, the safety issue and short lifespan induced by uncontrolled dendrite growth have hindered the practical applications of lithium metal anodes. Hence, we propose a flexible anion-immobilized ceramic–polymer composite electrolyte to inhibit lithium dendrites and construct safe batteries. Anions in the composite electrolyte are tethered by a polymer matrix and ceramic fillers, inducing a uniform distribution of space charges and lithium ions that contributes to a dendrite-free lithium deposition. The dissociation of anions and lithium ions also helps to reduce the polymer crystallinity, rendering stable and fast transportation of lithium ions. Ceramic fillers in the electrolyte extend the electrochemically stable window to as wide as ${\\pmb5.5\\pmb v}$ and provide a barrier to short circuiting for realizing safe batteries at elevated temperature. The anion-immobilized electrolyte can be applied in all–solid-state batteries and exhibits a small polarization of $15~\\mathsf{m v}$ . Cooperated with ${\\mathsf{L i F e P O}}_{4}$ and $\\mathbf{LiNi_{0.5}C o_{0.2}M n_{0.3}O_{2}}$ cathodes, the all–solid-state lithium metal batteries render excellent specific capacities of above $\\mathsf{150\\ m A h{\\cdot}g^{-1}}$ and well withstand mechanical bending. These results reveal a promising opportunity for safe and flexible next-generation lithium metal batteries. \n\nlithium metal anode | composite electrolyte | all–solid-state lithium batteries | immobilized anion | lithium dendrite \n\nThe expanding demand for energy storage calls for safe, highenergy density, and low-cost batteries. Lithium (Li) metal with a very high theoretical specific capacity of $3{,}860\\ \\mathrm{\\mAh{\\cdot}g^{-1}}$ and the lowest reduction potential $-3.04\\mathrm{~V~}$ vs. standard hydrogen electrode) has been strongly regarded as a promising anode material in next-generation rechargeable batteries (1–3). However, the uncontrolled dendrite growth during Li plating and stripping results in potential issues such as short circuiting and short lifespan (4), hindering the practical applications of Li metal batteries (LMBs) over decades (5). \n\nGenerally, Li metal anodes are operated in organic liquid electrolytes, which compromise on the viscosity and dielectric constant. Those organic electrolytes react with the Li metal, forming a solidelectrolyte interphase (SEI) (6–8). However, the as-formed SEI is heterogeneous, which induces the inhomogeneous Li deposition (9, 10). Consequently, Li dendrites are generated inevitably on a working anode in liquid electrolytes. Moreover, the natural SEI is too fragile to tolerate the volumetric and morphological change of Li metal anode (11). With the increasing cycle number, the repeated crack and formation of the SEI accelerate the continual consumption of both Li metal and electrolyte, increasing the interfacial resistance between the Li anode and electrolyte (12). It also causes a serious safety hazard when Li dendrites penetrate through a separator and contact with a cathode directly (13). \n\nExtensive efforts have been devoted to solving the above problems, including electrolyte additives (7, 14), stable nanostructured Li metal hosts (15), and the separator modification (16, 17). Despite these efforts varying from each other, most of them aim to adjust the ion distribution during cycling. In terms of the ion distribution, space-charge theory is widely accepted in cases of nonaqueous electrolytes. In this theory, the electrolyte is divided into a quasineutral region and a space-charge region. The quasi-neutral region approaches the cathode side, at which the ion transfer is governed by diffusion. In contrast, when ions travel close to the anode side, the ion transport is mainly driven by the electric field, leaving a space-charge region that accounts for ramified Li metal growth. Consequently, it is rewarding to design the electrolyte, which can regulate the ion distribution (including both Li cations and the counter anions) to inhibit Li dendrite growths (18, 19). Recently, several lithiophilic matrices were proposed to regulate the diffusion behavior of Li ions, realizing uniform distribution of Li ions near the anode side (6, 20, 21). Archer and coworkers (22, 23) pioneered the concept of anion regulation and found that a portion of immobilized anions (even as small as $10\\%$ ) in liquid electrolytes contribute to stable electrodeposition and 10-fold increased cell lifetime (24). \n\nImmobilizing anions in liquid electrolytes improves the cycling performance of Li metal anodes significantly. However, such an approach is unreliable, owing to the intrinsic reactivity of Li metal and the fragile SEI formed in liquid electrolytes (25). Moreover, the liquid electrolyte also suffers from leakage, fire, and explosion, hindering the development of next-generation LMBs seriously. To address the aforementioned issues and build a safe battery, the solid electrolyte is regarded as one of the ultimate choices to operate Li metal anodes safely even at elevated temperature, which can avoid leaking, combusting, and corroding Li metal inherently (26–29). The excellent electrochemical stability of solid \n\n# Significance \n\nThe Li metal electrode is regarded as a “Holy Grail” anode for next-generation batteries due to its extremely high theoretical capacity and lowest reduction potential. Unfortunately, uncontrolled dendrite growth leads to serious safety issues. This work realizes a dendrite-free Li metal anode by introducing an anion-immobilized composite solid electrolyte, where anions are tethered to polymer chains and ceramic particles. Immobilized anions contribute to uniform distribution of Li ions and dendrite-free Li deposition. The flexible electrolyte can be applied in all–solid-state Li metal batteries with excellent specific capacities. This work demonstrates a concept to adjust ion distribution based on solid-state electrolytes for safe dendritefree Li anodes, paving the way to practical Li metal batteries. \n\nAuthor contributions: C.-Z.Z., X.-Q.Z., and Q.Z. designed research; C.-Z.Z., X.-Q.Z., X.-B.C., R.Z., R.X., P.-Y.C., H.-J.P., and J.-Q.H. performed research; R.Z., R.X., P.-Y.C., H.-J.P., and J.-Q.H. contributed new reagents/analytic tools; C.-Z.Z., X.-Q.Z., X.-B.C., R.Z., R.X., P.-Y.C., H.-J.P., J.-Q.H., and Q.Z. analyzed data; and C.-Z.Z., X.-Q.Z., X.-B.C., R.Z., J.-Q.H., and Q.Z. wrote the paper. \n\nelectrolytes enables high-voltage cathode materials to pair with a Li metal anode, widening the working voltage window and therefore increasing the gravimetric energy density (30, 31). Besides, solidstate batteries can be packed more densely in a flexible configuration, increasing the volumetric energy density as well (32, 33). \n\nIn this contribution, we develop an anion-immobilized solid-state composite electrolyte to protect Li metal anodes (Fig. 1). Garnettype Al-doped $\\mathrm{Li}_{6.75}\\mathrm{La}_{3}\\mathrm{Zr}_{1.75}\\mathrm{Ta}_{0.25}\\mathrm{O}_{12}$ (LLZTO) ceramic particles are well dispersed in a polymer–Li salt matrix to synthesize a polyethylene oxide (PEO)–lithium bis(trifluoromethylsulphonyl)imide (LiTFSI)-LLZTO (PLL) solid electrolyte membrane. In contrast to routine liquid electrolytes with mobile anions, the PLL solid electrolyte contributes to effective immobilization of anions for realizing uniform ion distribution and dendrite-free Li deposition. On the one hand, the active ceramic filler serves as a rigid part to block dendrites and offers an ultimate protection at extreme temperature (34). On the other hand, the polymer–Li salt substrate acts as a soft part to adapt the changes in the electrode for maintaining a closely contacted interface and sufficient cross-boundary ion transportation. Chemical and mechanical interactions between ceramic particles and the polymer matrix result in reduced PEO crystallinity and pinned $\\mathrm{TFSI^{-}}$ anions, enabling relatively fast $\\mathrm{Li^{+}}$ conduction and a wide electrochemical stability window. We further successfully demonstrate the application of this flexible membrane in all–solid-state $\\mathrm{LiFePO_{4}}$ (LFP)-Li and $\\mathrm{LiNi_{0.5}C o_{0.2}M n_{0.3}O_{2}}$ (NCM)-Li batteries and manage to obtain dendrite-free LMBs. \n\n# Results and Discussion \n\nTo link polymer chains onto $\\mathrm{TFSI^{-}}$ anions and LLZTO particles intensively, a PEO substrate was mixed with Li salts at first, and then LLZTO particles were added with continual rapid stirring at $65^{\\circ}\\mathrm{C}$ , which was slightly above the melting point of PEO. During the fast mixing at elevated temperature, PEO chains can be fibrillated mechanically and partially entangled with $\\mathrm{TFSI^{-}}$ anions and LLZTO particles. When cooled down to room temperature, the polymer chains were pinned locally, leading to the increase of noncrystallized PEO with immobilized anions. \n\nThe as-obtained PLL composite electrolyte is freestanding, is mechanically flexible, and can be fully bended (Fig. $2A$ and $B$ ), making it feasible for fabricating flexible solid-state batteries. Detailed morphology was characterized by scanning electron microscopy (SEM). The PLL membrane exhibits a clear and smooth surface with few protuberances (Fig. 2C). The cross-section image indicates a thickness of around $30\\upmu\\mathrm{m}$ , from which it can be clearly observed that the PEO-Li salt polymer and ceramic particles are fully intermingled (Fig. $2D$ ). \n\n![](images/f5e22e60201fe0b3fa14f5d87470ed9266f7708735beb345c264e2e6dc83e02f.jpg) \nFig. 1. Schematic of the electrochemical deposition behavior of the Li metal anode with (A) the PLL solid electrolyte with immobilized anions and (B) the routine liquid electrolyte with mobile anions. \n\nX-ray diffraction (XRD) patterns were conducted to investigate the crystallinity (Fig. $2E$ ). LLZTO acts as the most rigid part in the composite membrane. Nearly all diffraction peaks of LLZTO powders match well with the standard pattern of the known garnet phase $\\mathrm{Li_{5}L a_{3}N b_{2}O_{12}}$ (Powder Diffraction File 80-0457), while signals of other impurities are below the detection limit. $\\mathrm{Li}_{5}\\mathrm{La}_{3}\\mathrm{M}_{2}\\mathrm{O}_{5}$ $\\bar{\\mathbf{M}}=\\mathbf{Nb}$ , Ta) is widely accepted as a model with a typical garnet-type cubic structure to identify the crystalline composition of LLZTO (35). This well-matched curve indicates the garnet-type crystalline nature of LLZTO, which is regarded as a promising oxide electrolyte for solidstate LMBs due to its high ionic conductivity, excellent electrochemical stability, and outstanding mechanical properties such as a shear modulus of 55 GPa (36, 37). Another critical part in the electrolyte is the soft PEO matrix. There are strong and sharp characteristic peaks in the XRD pattern of pure PEO membrane, indicating its crystallizing tendency at room temperature. However, the intensities of its characteristic peaks drop markedly upon the addition of Li salts, indicating the reduction of PEO crystallinity. In the PLL composite electrolyte, all components are integrated without losing their own identities. The weakened peaks of PEO also suggest the increase of PEO phase with low crystallinity. The polymer chains in amorphous PEO phase can wrap and immobilize anions, which is crucial for high ionic conductivity of a composite electrolyte. \n\nThermogravimetric analysis (TGA) was employed to evaluate the thermal stability of various electrolytes (SI Appendix, Fig. S1). All three electrolytes, i.e., PEO, LiTFSI-PEO, and PLL, are relatively stable until $300^{\\circ}\\mathrm{C},$ in sharp contrast to thermally unstable and volatile organic liquid electrolytes (21). As the temperature rises, PEO decomposes at $350{\\-}400\\ ^{\\circ}\\mathrm{C}$ ; while in the TGA curve of LiTFSI-PEO, the slope above $400~^{\\circ}\\mathrm{C}$ is ascribed to the decomposition of LiTFSI. The vanishing of polymer significantly threatens the survival of electrolyte membranes. Little weight was retained above $500^{\\circ}\\mathrm{C}$ in both PEO and PEO-LiTFSI electrolytes. The cathode and anode will meet directly, raising serious safety issues at this condition. Nevertheless, as for the PLL composite electrolyte, there is $42.6\\%$ of initial weight left at a temperature of $800~^{\\circ}\\mathrm{C}$ , which is 10 times higher than that of ceramic-filler–free electrolytes. This indicates the extraordinary thermal stability of remaining LLZTO fillers, which thereby act as a barrier between electrodes at extreme conditions and ensure safety. \n\nThe electrochemical stability window is a determinant factor for electrolytes applied in high-voltage Li batteries toward high-energy densities. It can be obtained from the linear sweep voltammetry of the tested electrolyte sandwiched between a Li counter electrode and a stainless steel working electrode. The PLL composite electrolyte (with $40\\%$ LLZTO ceramic particles) exhibits a voltage window as large as $5.5\\mathrm{~V~}$ without distinct reaction (SI Appendix, Figs. S2 and S3), indicating its good tolerance to polarization and great potential for high-voltage Li batteries. The key lies in the addition of LLZTO particles, which widens the voltage window from less than $5.0{-}5.\\bar{5}\\mathrm{V}$ . LLZTO and its surface passivation layer render excellent electrochemical stability against the Li metal, and finely dispersed ceramic fillers help to remove impurities from the interfaces. All of these account for the enhanced stability of PLL composite solid electrolyte in a working battery. \n\nThe conductivity of a composite electrolyte, which is mainly featured by either cation or vacancy conduction, is a key factor for practical applications. The PLL composite electrolyte renders low electrical conductivity according to potentiostatic coulometry measurements under various bending states (SI Appendix, Fig. S4). The ionic conductivities of PLL composite electrolyte with different LLZTO contents were evaluated by electrochemical impedance spectroscopy (EIS). Symmetric cells were utilized for the measurements, consisting of two identical stainless steel foils as blocking electrodes and a PLL electrolyte membrane sandwiched in between (SI Appendix, Figs. S5 and S6). The evaluation was conducted at $20{-}80~^{\\circ}\\mathrm{C}$ . An Arrhenius plot of ionic conductivity was obtained correspondingly, along with a well-fitted EIS spectrum at $25^{\\circ}\\mathrm{C}$ (Fig. $3A$ ). An intercept of a real axis and an inclined tail appear in each EIS spectrum. The intercept at high frequency was used for calculating the ionic conductivity based on the membrane thickness and the electrode surface area (38). The straight line at low frequency represents the migration of Li ions and reveals the interfacial inhomogeneity. The PLL composite electrolyte with $40\\%$ LLZTO content has a preferable ionic conductivity of $1.12\\times10^{-5}{\\mathrm{S}}{\\cdot}{\\mathrm{cm}}^{-1}$ at $25^{\\circ}\\mathrm{C}$ , probably because the multiple ion conducting channels consisting of polymer segments, LLZTO crystals, and heterogeneous interfaces performed and cooperated the best with the moderate ratios. The conductivity increased with the rise of testing temperature. It approaches $1\\mathsf{\\check{0}}^{-3}\\mathsf{S}{\\cdot}\\mathsf{c m}^{-1}$ at $70~^{\\circ}\\mathrm{C}$ , which is comparable to those of liquid electrolytes. Compared with other composite electrolytes with nonactive fillers such as $\\mathrm{SiO}_{2}$ $({\\sim}2\\times10^{-6}\\ \\mathrm{S{\\cdot}c m^{-1}}$ at room temperature) (39) and ${\\bf A l}_{2}{\\bf O}_{3}$ $(1.0\\dot{\\times}10^{-6}\\ \\mathrm{S{\\cdot}c m^{-1}}$ at room temperature) (40), the PLL electrolyte exhibits notable improvements in ionic conductivity at both room and elevated temperatures. \n\n![](images/75eabcddb079616d91309c946c5bc6d97068e7e705f407d3f1822667846a70db.jpg) \nFig. 2. Morphological and structural characterization for the PLL composite solid electrolyte. (A and B) Digital images of the PLL electrolyte at (A) flat and (B) bended states. (C and D) SEM images of (C) the surface and $(D)$ a cross-section of the PLL electrolyte. (E) XRD patterns of the PLL electrolyte (red), the PEO-LiTFSI electrolyte (green), pure PEO membrane (orange), LLZTO powders (blue), and the powder diffraction file (PDF) of $\\mathsf{L i}_{5}\\mathsf{L a}_{2}\\mathsf{N b}_{2}\\mathsf{O}_{12}$ . (Scale bars in $c$ and $D_{\\iota}$ $10\\ {\\upmu\\mathrm{m}}.$ ) \n\nIn addition to the relatively high Li ionic conductivity, PLL composite electrolyte with $40\\%$ LLZTO also possesses a Li ion transference number $(t_{+})$ as high as 0.58 (Fig. $3B$ and $S I$ Appendix, Fig. S7 and Table S1). While for the solid composite electrolytes without ceramic fillers (LiTFSI-PEO) and with inadequate ceramic fillers $20\\%$ LLZTO) $t_{+}$ is 0.37 and 0.38, respectively, indicating that anions are not fixed effectively. The $t_{+}$ of routine liquid electrolytes is as limited as 0.22 in $1.0\\mathrm{M}\\mathrm{LiPF}_{6}$ –ethylene carbonate/diethyl carbonate $\\mathrm{(EC/DEC=1:1}$ , in volume) and 0.21 in $1.0\\mathrm{M}$ LiTFSI–1,3-dioxolane/dimethoxyethane $(\\mathrm{DOL}/\\mathrm{DME}=1{:}1\\$ , in volume). The low $t_{+}$ of routine liquid electrolytes reflects ineffective transportation of Li ions, which leads to a strong space charge near the anode and hence dendritic Li deposition. In contrast, the PLL composite electrolyte with a high $t_{+}$ is expected to effectively protect the Li metal anode in a working battery. \n\nThe advantage of the high- $\\cdot t_{+}$ PLL composite electrolyte is illustrated by modeling the distribution of Li ions on the anode surface (Fig. $3C$ and $D$ ). Uniformly distributed Li ions can guide dendrite-free Li deposition. In the electrolyte with mobile anions (featured by small $t_{+,}$ ), free anions tend to move in the opposite direction to cations, becoming a barrier for cation transportation under an applied electric field. Therefore, a large concentration gradient of Li ions forms from the bulk electrolyte to the anode surface. More seriously, such a gradient becomes more predominant with the time of Li deposition extending. When anions are immobilized, it is much easier for Li ions to diffuse from the bulk electrolyte to the anode surface. Hence, a much more harmonious environment is built for uniform Li deposition. Anion immobilization is beneficial for the inhibition of space charge formation, which could induce a homogeneous $\\mathrm{Li^{+}}$ distribution and further lead to a uniform Li deposition. Besides, this surface environment with a uniform distribution of Li ions is established rapidly, exhibiting the potential to reclaim Li ions from disturbance. Therefore, the PLL composite electrolyte with a high $t_{+;}$ , namely a high fraction of immobilized anions, renders uniform distribution of Li ions and hopefully dendrite-free Li deposition. \n\n![](images/dd17b8349b5e17e3b981719b1d325ba2112828fefd56fd485db4f8ce7c63999a.jpg) \nFig. 3. Diffusion behaviors of Li ions in the PLL electrolyte. (A) The Arrhenius plot of the PLL electrolyte at temperatures from $20^{\\circ}\\mathsf{C}$ to $80^{\\circ}\\mathsf C.$ . Inset shows the EIS spectrum of the electrolyte at room temperature $(25~^{\\circ}\\mathsf{C})$ . (B) $t_{+}$ of $(i)$ PLL composite electrolyte, (ii) PEO-LiTFSI solid electrolyte, (iii) 1 M LiPF6-EC/DEC, and (iv) 1 M LiTFSI-DOL/DME liquid electrolytes. $\\boldsymbol{\\varsigma}$ and $D$ ) $t_{+}$ from the anode surface to the bulk electrolyte (C) after $1.0\\ s$ and $(D)$ at the steady state with $0\\%$ , $25\\%$ , $50\\%$ , $75\\%$ , and $100\\%$ of immobilized anions. These results were obtained from the finite-element method (FEM). (E and $F_{\\cdot}$ ) SEM images of Li metal plating on Cu foils with the presence of (E) PLL and $(F)$ routine liquid electrolytes (1 M LiPF6-EC/DEC). (Scale bars in $\\boldsymbol{\\varepsilon}$ and F, $10~\\upmu\\mathrm{m}$ .) \n\n![](images/8ef167523d09d043164805188244573e9155f829027cb19b0735a84f3e1b5802.jpg) \nFig. 4. Electrochemical cycling performance of the PLL electrolyte. (A and B) Cycling performance (A) and corresponding galvanostatic discharge/charge profile (B) of the all–solid-state LFP j Li metal battery at a rate of 0.1 C and at $60~^{\\circ}\\mathsf{C}$ $1.0~{\\mathsf{C}}=180~{\\mathsf{m A}}{\\cdot}{\\mathsf{g}}^{-1};$ . (C) Voltage profiles of the lithium plating/ stripping in a Li–Li symmetrical cell with PLL $(60~^{\\circ}\\mathsf{C})$ and routine liquid electrolytes $(25~^{\\circ}\\mathsf{C})$ at a current density of $0.10\\ m\\mathsf{A}{\\cdot}\\mathsf{c m}^{-2}$ . (D) An all–solidstate NCM PLL electrolyte Li metal pouch cell was assembled to light the LED at both flat and bended states. \n\nThe influence of the PLL electrolyte (with $40\\%$ LLZTO) on the Li deposition was visibly probed by SEM. A total of $0.10\\mathrm{mAh}{\\cdot}\\mathrm{cm}^{-2}$ of Li metal was deposited on $\\mathrm{Cu}$ foils at a current density of $0.10\\mathrm{\\mA}{\\cdot}\\mathrm{cm}^{-2}$ , with the presence of a PLL solid electrolyte membrane and a 1.0-M $\\mathrm{LiPF}_{6}$ -EC/DEC liquid electrolyte, respectively (Fig. 3 $E$ and $F$ ). Obviously, Li dendrites grow and accumulate in the liquid electrolyte, forming an extremely uneven surface. Once the dendrites keep growing and reach cathodes, the short circuiting will occur, and this situation is even worse since it is difficult for compliant liquid electrolytes to block dendrites. On the contrary, the PLL composite solid electrolyte contributes to smooth Li deposits and it is also rigid enough for dendrite inhibition (41–44). Compared with Li dendrites deposited in liquid electrolytes, Li metal is plated uniformly and free of dendrites on the $\\mathrm{Cu}$ foil surface by using the PLL electrolyte. \n\nWith excellent mechanical and electrochemical properties proved, the PLL composite electrolyte was applied in all–solidstate lithium batteries. Cells of LFP Li metal were adopted to demonstrate the cycling performance, which were assembled without liquid electrolyte addition. The all–solid-state batteries exhibited stable cycling capability. A specific capacity of around $155\\ \\mathrm{mAh{\\cdotg}^{-1}}$ and a Coulombic efficiency of $99\\%$ were retained $\\left(0.1\\mathrm{~C~}\\right)$ at $60~^{\\circ}\\mathrm{C}$ (Fig. 4A). The cells maintain excellent cycling performance with $13\\%$ capacity fade in 100 cycles, indicating the potential of PLL composite electrolytes in practical applications. Flat plateaus appeared in both charge and discharge profiles, and polarization during cycling was as limited as $0.0\\bar{5}\\ \\bar{\\mathrm{~V~}}$ (Fig. 4B). Although batteries with PLL electrolytes are promising for future applications, it is noteworthy that there are limitations resulting from elevated temperature operation, including a more sophisticated battery management system (BMS), limited applications in some consumer electronics, and longer startup time, etc. Much more effort is needed to conquer these issues. \n\nThe long-term electrochemical stability of PLL composite solid electrolytes against the Li metal was evaluated by using symmetrical Li Li cells. The electrolyte membrane was sandwiched between two Li metal foils. The Li metal was plated and stripped time after time to mimic a practical cycling process. Fig. $4C$ and $S I$ Appendix, Figs. S8 and S9A display voltage profiles of cells cycled at a current density of $0.10\\dot{\\mathrm{~mA}}{\\cdot}\\mathrm{cm}^{-2}$ . The cell with the PLL electrolyte exhibited excellent stability with a nearly constant voltage polarization of $15\\mathrm{mV}$ during the $400\\mathrm{-h}$ cycling. Li Li cells at a current density of $0.20~\\mathrm{mA{\\cdot}c m}^{=_{2}}$ also render a stable cycling with a polarization as limited as $60\\mathrm{mV}$ for $800\\mathrm{h}$ (SI Appendix, Fig. S10). The interfacial resistances between PLL electrolyte and Li metal before and after cycling are all below $15\\Omega$ ( $\\cdot\\boldsymbol{S}\\boldsymbol{I}$ Appendix, Fig. S11 and Table S2), which are much lower than that of a routine liquid electrolyte $(\\sim70~\\Omega$ ; $S I$ Appendix, Table S1). Besides, the resistance was even slightly reduced after 100 cycles, owing to the enhancement of interface optimization after cycles. The interface between PLL electrolyte and Li anode remained stable during cycling, from which a safe battery will benefit a lot. However, the interface was unstable in a routine liquid electrolyte at both room and elevated temperatures (Fig. $4C$ and $S I$ Appendix, Figs. S8, S9, and S12). The voltage polarization was severer than that of the cell with the PLL electrolyte, indicating large fluctuations upon cycling. This can be ascribed to the uneven Li plating/stripping and heterogeneous Li metal/electrolyte interface. The remarkable performance of the PLL composite electrolyte against liquid electrolytes results from the fixed anions, homogeneous ion distribution, and fast transport of Li ions. \n\nTo demonstrate the versatility of the PLL composite electrolyte, an all–solid-state NCM PLL electrolyte Li metal pouch cell was assembled to light a light-emitting diode (LED) (Fig. $\\left|4D\\right>$ ). The LED can be lighted whenever the pouch cell is flat or bended, indicating the ability of the PLL composite electrolyte to be applied in flexible devices. Therefore, the PLL composite electrolyte can not only stabilize the Li metal anode, suppress Li dendrite growth, and enhance the safety of LMBs, but also hold promise for flexible and wearable electronics. \n\nThe improved electrochemical performance of Li metal anodes cycled with the PLL solid electrolyte can be attributed to two factors. First, anions as large as $\\mathrm{TFSI}^{-}$ can be firmly trapped by PEO chains and LLZTO particles. Fixed anions contribute to an improved conductivity (24) and dendrite-free Li deposition (45). Second, the relatively slow dynamic response, especially the slow anion movement, helps the PLL solid electrolyte tolerate turbulence during cycling. An efficient Li metal anode demands homogeneous plating/stripping. However, defects and turbulence are difficult to avoid in a working battery. In liquid electrolytes, ions and electrons travel freely in the interspace. Once a tiny Li dendrite forms, the local electrical field will change rapidly, making it easier for subsequent Li deposition on the existing tip. The deposited Li continuously acts as a preferential deposition spot, resulting in endless Li growth. Finally, a hazardous dendrite appears. This domino effect leads to easy loss in efficiency. On the contrary, in the solid electrolyte with immobilized anions, the turbulence in ion distribution can be tolerated due to the slow transport of anions. Ions move uniformly, driven by the electric field, resulting in continuously homogeneous deposition of Li metal (46, 47). \n\n![](images/d9954e9da482cfc1eed711a8c6b95ae20719c13e1f43ed9bc282e845b274b4ac.jpg) \nFig. 5. Schematic of the immobilized anions tethered to polymer chains and LLZTO ceramic particles. \n\nTo better understand the origin and role of immobilized anions in the PLL composite electrolyte, diffusion behaviors of Li ions in the electrolyte are thoroughly investigated. Li ions in the composite electrolyte can move through three conducting channels: (i) LLZTO particles whose content is above the percolation threshold (48), $(\\ddot{u})$ the PEO-Li salt substrate with reduced polymer crystallinity and enhanced Li salt dissociation, and (iii) interfaces between ceramic fillers and the polymer matrix with immobilized anions (Fig. 5). \n\nLi ion channels within the LLZTO crystals are constructed from $\\left(\\mathrm{La}_{3}\\mathrm{Ta}_{2}\\mathrm{O}_{12}\\right)_{\\mathrm{n}}^{-}$ chains interconnected through Li and La ions. In this work, the LLZTO ceramic used in the PLL electrolyte was sintered with an excess amount of Li precursors. As a result, the number of Li ions (or atoms) is beyond the number of tetrahedral sites, resulting in the occupation of octahedral sites by excess Li and shortening of the Li–Li distance. The electrostatic repulsion between the fairly close Li ions, together with the dynamic process, pushes Li ions to move along the transport channels in the LLZTO crystal (49). Previous ab initio calculations revealed that Li ions migrated in a priority sequence of octahedral site, tetrahedral site, and vacant octahedral site (27). In addition, $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ is widely believed to form on the surface of LLZTO exposed in air, which may also help Li ions migrate, following an interstitial– substitutional exchange (knockoff) mechanism (48, 50). \n\nChains in the polymer substrate are known to transport Li ions through segmental motions, which will be promoted in amorphous regions (51, 52). Differential scanning calorimetry (DSC) was introduced to evaluate the ability of polymer chains in the matrix to move segmentally. SI Appendix, Fig. S13 exhibits the DSC curve and $S I$ Appendix, Fig. S13, Inset shows the enlarged curve at around $-40^{\\circ}\\mathrm{C}$ , representing the glass transition temperature $(T_{\\mathrm{g}})$ . The PLL composite electrolyte exhibits the lowest $\\mathrm{{\\bar{\\itT}_{g}}}$ of $-57~^{\\circ}\\mathrm{C}$ and the melting point $(T_{\\mathrm{m}})$ , suggesting that it is easiest for PEO segments in the PLL electrolytes to move at ambient temperature. Therefore, the PLL electrolyte is featured with the fastest ion transport. The pure PEO membrane does not show a glass transition. At around $50^{\\circ}\\mathrm{C},$ a sharp peak appears, corresponding to a quick and regular melting process at the melting point. That is a common characteristic of a large crystallized polymer. By adding Li salts and LLZTO fillers successively, the peak corresponding to \n\n1. Cheng XB, Zhang R, Zhao CZ, Zhang Q (2017) Toward safe lithium metal anode in rechargeable batteries: A review. Chem Rev 117:10403–10473. \n2. Zhang R, et al. (2017) Advanced micro/nanostructures for lithium metal anodes. Adv Sci (Weinh) 4:1600445. \n3. Lin D, Liu Y, Cui Y (2017) Reviving the lithium metal anode for high-energy batteries. Nat Nanotechnol 12:194–206. \n4. Lu D, et al. (2017) Formation of reversible solid electrolyte interface on graphite surface from concentrated electrolytes. Nano Lett 17:1602–1609. \n5. Fang R, et al. (2017) More reliable lithium-sulfur batteries: Status, solutions and prospects. Adv Mater 29:1606823. \n6. Lin D, et al. (2017) Three-dimensional stable lithium metal anode with nanoscale lithium islands embedded in ionically conductive solid matrix. Proc Natl Acad Sci USA \n114:4613–4618. \n\npolymer melting shifts to a lower temperature, suggesting the increase of amorphous phase. This can also be proved in the cooling part of DSC curves, as well as in XRD results. \n\nInterfaces between heterostructured materials have been witnessed to transport ions, although the mechanisms are still debated (53, 54). In the light of Lewis acid/base theory, it can be proposed that acidic groups on garnet particles and anions in Li salts will link with each other. $\\mathrm{TFSI}^{-}$ , as a Lewis base, furnishes the electron pair shared by the acidic group and $\\mathrm{TFSI^{-}}$ anion (55). The affinity between oxide fillers and Li–salt anions facilitates the dissociation of LiTFSI, after which anions get immobilized while free Li cations emerge and move rapidly along the extended interface. \n\nIt was suggested that the polymer with more amorphous phases contributes to the increase of Li ionic conductivity. In recent years, finite-element simulations revealed that ion transportation occurs near the ceramic–polymer interface (56, 57). In addition, Li NMR was also utilized and indicated that Li ions prefer to migrate through the ceramic phase in the $\\mathrm{Li_{7}L a_{3}Z r_{2}O_{12}\\mathrm{-}P E}($ O composite electrolyte system (58). Although the ion migration path in the composite electrolyte is still controversial, all three ion channels contribute to the fast ion conduction in composite electrolytes. It is also possible that in different conditions (such as different temperatures or charge/discharge stages), the three channels perform synergistic roles. \n\n# Conclusions \n\nWe proposed a flexible anion-immobilized PLL composite electrolyte membrane to inhibit dendrites in a Li metal anode. Through the addition of LLZTO particles, the crystallization of PEO is sharply reduced and anions are effectively immobilized due to their interactions with ceramic particles and polymer matrix, resulting in well-distributed Li ions and dendrite-free deposition. The PLL composite electrolyte possesses a high Li ionic conductivity of $1.12\\dot{\\times}10^{-5}\\mathrm{{S}{\\cdot}\\mathrm{{cm}^{-1}}}$ at $25^{\\circ}\\mathrm{C}$ and a wide electrochemical window of $5.5\\mathrm{~V~}$ . The existence of LLZTO fillers affords a barrier to avoid short circuiting. With such excellent mechanical and electrochemical properties, the PLL composite electrolyte was applied in all–solid-state LMBs and achieved stable cycling performance with high specific capacities and dendrite-free Li deposition. The development of an anion-immobilized composite electrolyte reveals a promising opportunity for next-generation safe and flexible LMBs. \n\n# Materials and Methods \n\nThe PLL composite electrolyte was prepared by first dissolving PEO and LiTFSI. The Al-doped LLZTO powders were added into the solution. The as-obtained slurry was sealed and stirred rapidly at $65^{\\circ}\\mathsf{C}$ until good dispersion. The electrolyte membrane was obtained by doctor blading the slurry on a polytetrafluoroethylene plate. More details on the materials and methods can be found in SI Appendix. \n\nACKNOWLEDGMENTS. The authors thank Kai Liu, Chong Yan, Ying-Zhi Sun, Jin Xie, and Xiao-Ru Chen at Tsinghua University for helpful discussion. This work was supported by the National Key Research and Development Program (Grants 2016YFA0202500, 2016YFA0200102, and 2015CB932500) and the National Natural Science Foundation of China (Grants 21422604 and 21676160). \n\n7. Zhao C-Z, et al. (2016) $\\mathsf{L i}_{2}\\mathsf{S}_{5}$ -based ternary-salt electrolyte for robust lithium metal anode. Energy Storage Mater 3:77–84. \n8. Cheng XB, et al. (2015) A review of solid electrolyte interphases on lithium metal anode. Adv Sci 3:1500213. \n9. Yan C, et al. (2016) Lithium metal protection through in-situ formed solid electrolyte interphase in lithium-sulfur batteries: The role of polysulfides on lithium anode. J Power Sources 327:212–220. \n10. Cheng X-B, et al. (2017) Implantable solid electrolyte interphase in lithium-metal batteries. Chem 2:258–270. \n11. Cheng X-B, et al. (2017) Sulfurized solid electrolyte interphases with a rapid $\\mathsf{L i}+$ diffusion on dendrite-free Li metal anodes. Energy Storage Mater, 10.1016/j.ensm.2017.03.008. \n12. Liu B, et al. (2017) Stabilization of Li metal anode in DMSO-based electrolytes via optimization of salt-solvent coordination for $L i{\\mathrm{-}}O_{2}$ batteries. Adv Energy Mater 7:1602605. \n13. Manthiram A, Chung S-H, Zu C (2015) Lithium-sulfur batteries: Progress and prospects. Adv Mater 27:1980–2006. \n14. Zhang X-Q, Cheng X-B, Chen X, Yan C, Zhang Q (2017) Fluoroethylene carbonate additives to render uniform Li deposits in lithium metal batteries. Adv Funct Mater 27: 1605989. \n15. Li Q, Zhu S, Lu Y (2017) 3D porous Cu current collector/Li-metal composite anode for stable lithium-metal batteries. Adv Funct Mater 27:1606422. \n16. Lin D, Zhuo D, Liu Y, Cui Y (2016) All-integrated bifunctional separator for Li dendrite detection via novel solution synthesis of a thermostable polyimide separator. J Am Chem Soc 138:11044–11050. \n17. Liu K, Bai P, Bazant MZ, Wang C-A, Li J (2017) A soft non-porous separator and its effectiveness in stabilizing Li metal anodes cycling at $10\\mathsf{m A c m}^{-2}$ observed in situ in a capillary cell. J Mater Chem A 5:4300–4307. \n18. Tikekar MD, Choudhury S, Tu Z, Archer LA (2016) Design principles for electrolytes and interfaces for stable lithium-metal batteries. Nat Energy 1:16114. \n19. Tu Z, et al. (2017) Nanoporous hybrid electrolytes for high-energy batteries based on reactive metal anodes. Adv Energy Mater 7:1602367. \n20. Zhang R, et al. (2017) Lithiophilic sites in doped graphene guide uniform lithium nucleation for dendrite-free lithium metal anodes. Angew Chem Int Ed Engl 56: 7764–7768. \n21. Fu KK, et al. (2016) Flexible, solid-state, ion-conducting membrane with 3D garnet nanofiber networks for lithium batteries. Proc Natl Acad Sci USA 113:7094–7099. \n22. Jayaprakash N, Jones WD, Moganty SS, Archer LA (2012) Composite lithium battery anodes based on carbon $\\scriptstyle{1@\\mathsf{C o}_{3}\\mathsf{O}_{4}}$ nanostructures: Synthesis and characterization. J Power Sources 200:53–58. \n23. Lu Y, Korf K, Kambe Y, Tu Z, Archer LA (2014) Ionic-liquid-nanoparticle hybrid electrolytes: Applications in lithium metal batteries. Angew Chem Int Ed Engl 53:488–492. \n24. Tikekar MD, Archer LA, Koch DL (2014) Stability analysis of electrodeposition across a structured electrolyte with immobilized anions. J Electrochem Soc 161:A847–A855. \n25. Long P, Xu Q, Peng G, Yao X, Xu X (2016) NiS nanorods as cathode materials for allsolid-state lithium batteries with excellent rate capability and cycling stability. ChemElectroChem 3:764–769. \n26. Chen R, Qu W, Guo X, Li L, Wu F (2016) The pursuit of solid-state electrolytes for lithium batteries: From comprehensive insight to emerging horizons. Mater Horiz 3: 487–516. \n27. Thangadurai V, Narayanan S, Pinzaru D (2014) Garnet-type solid-state fast Li ion conductors for Li batteries: Critical review. Chem Soc Rev 43:4714–4727. \n28. Luo W, et al. (2017) Reducing interfacial resistance between garnet-structured solidstate electrolyte and Li-metal anode by a germanium layer. Adv Mater 29:1606042. \n29. Erickson EM, et al. (2015) Review-development of advanced rechargeable batteries: A continuous challenge in the choice of suitable electrolyte solutions. J Electrochem Soc 162:A2424–A2438. \n30. Liu W, et al. (2017) Enhancing ionic conductivity in composite polymer electrolytes with well-aligned ceramic nanowires. Nat Energy 2:17035. \n31. Yue L, et al. (2016) All solid-state polymer electrolytes for high-performance lithium ion batteries. Energy Storage Mater 5:139–164. \n32. Ren Y, et al. (2015) Oxide electrolytes for lithium batteries. J Am Ceram Soc 98: 3603–3623. \n33. Li JC, Ma C, Chi MF, Liang CD, Dudney NJ (2015) Solid electrolyte: The key for highvoltage lithium batteries. Adv Energy Mater 5:1401408. \n34. Liu K, Wang C-A (2014) Garnet-type $\\mathsf{L i}_{6.4}\\mathsf{L a}_{3}\\mathsf{Z r}_{1.4}\\mathsf{T a}_{0.6}\\mathsf{O}_{12}$ thin sheet: Fabrication and application in lithium–hydrogen peroxide semi-fuel cell. Electrochem Commun 48: 147–150. \n35. Luo W, et al. (2016) Transition from superlithiophobicity to superlithiophilicity of garnet solid-state electrolyte. J Am Chem Soc 138:12258–12262. \n36. Ni JE, Case ED, Sakamoto JS, Rangasamy E, Wolfenstine JB (2012) Room temperature elastic moduli and Vickers hardness of hot-pressed LLZO cubic garnet. J Mater Sci 47: 7978–7985. \n37. Yu S, et al. (2016) Elastic properties of the solid electrolyte $\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}$ (LLZO). Chem Mater 28:197–206. \n38. Li Y, et al. (2016) Mastering the interface for advanced all-solid-state lithium rechargeable batteries. Proc Natl Acad Sci USA 113:13313–13317. \n39. Fan L, Nan C-W, Zhao S (2003) Effect of modified $\\mathsf{S i O}_{2}$ on the properties of PEO-based polymer electrolytes. Solid State Ion 164:81–86. \n40. Croce F, et al. (2001) Role of the ceramic fillers in enhancing the transport properties of composite polymer electrolytes. Electrochim Acta 46:2457–2461. \n41. Liu Y, et al. (2017) An artificial solid electrolyte interphase with high Li-ion conductivity, mechanical strength, and flexibility for stable lithium metal anodes. Adv Mater 29:1605531. \n42. Liu K, et al. (2017) Lithium metal anodes with an adaptive “solid-liquid” interfacial protective la . J Am Chem Soc 139:4815–4820. \n43. Yao X, et al. (2016) High-energy all-solid-state lithium batteries with ultralong cycle life. Nano 16:7148–7154 \n44. Zhang (2017) High-capacity, low-tortuosity, and channel-guided lithium Natl Acad Sci USA 114:3584–3589. \n45. L able cycling of lithium metal batteries using high transference Energ Mater 5:1402073. \n46. T MD Archer LA (2015) Nanostructured electrolytes for ab ndary batteries. Acc Chem Res 48:2947–2956. \n47. T 16) Stabilizing electrodeposition in elastic solid ions. Sci Adv 2:e1600320. \n48. Shi S, of Li-ion transport in the solid electrolyte inerpha 15487 \n49. Yan $\\mathsf{x,}$ ) Li/Li $\\scriptstyle\\gamma\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}/\\mathsf{I}$ LiFePO4 all-solid-state battery with ultrathin na solid electrolyte. J Phys Chem C 121:1431–1435. \n50. Shi S, Qi Y, Li H, Hector LG (2013) Defect thermodynamics and diffusion mechanisms in $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ and implications for the solid electrolyte interphase in Li-ion batteries. J Phys Chem C 117:8579–8593. \n51. Zeng XX, et al. (2016) Reshaping lithium plating/stripping behavior via bifunctional polymer electrolyte for room-temperature solid Li metal batteries. J Am Chem Soc 138:15825–15828. \n52. Zhang JJ, et al. (2015) Safety-reinforced poly(propylene carbonate)-based all-solidstate polymer electrolyte for ambient-temperature solid polymer lithium batteries. Adv Energy Mater 5:1501082. \n53. Zhou W, et al. (2016) Plating a dendrite-free lithium anode with a polymer/ceramic/ polymer sandwich electrolyte. J Am Chem Soc 138:9385–9388. \n54. Fu KK, et al. (2017) Toward garnet electrolyte-based Li metal batteries: An ultrathin, highly effective, artificial solid-state electrolyte/metallic Li interface. Sci Adv 3: e1601659. \n55. Lin D, et al. (2016) High ionic conductivity of composite solid polymer electrolyte via in situ synthesis of monodispersed $\\mathsf{S i O}_{2}$ nanospheres in poly(ethylene oxide). Nano Lett 16:459–465. \n56. Kalnaus S, Sabau AS, Tenhaeff WE, Dudney NJ, Daniel C (2012) Design of composite polymer electrolytes for Li ion batteries based on mechanical stability criteria. J Power Sources 201:280–287. \n57. Kalnaus S, et al. (2013) Analysis of composite electrolytes with sintered reinforcement structure for energy storage applications. J Power Sources 241:178–185. \n58. Zheng J, Tang M, Hu YY (2016) Lithium ion pathway within $\\mathsf{L i}_{7}\\mathsf{L a}_{3}\\mathsf{Z r}_{2}\\mathsf{O}_{12}$ -polyethylene oxide composite electrolytes. Angew Chem Int Ed Engl 55:12538–12542. " + }, + { + "id": "10.1021_jacs.6b09645", + "DOI": "10.1021/jacs.6b09645", + "DOI Link": "http://dx.doi.org/10.1021/jacs.6b09645", + "Relative Dir Path": "mds/10.1021_jacs.6b09645", + "Article Title": "Design of Lead-Free Inorganic Halide Perovskites for Solar Cells via Cation-Transmutation", + "Authors": "Zhao, XG; Yang, JH; Fu, YH; Yang, DW; Xu, QL; Yu, LP; Wei, SH; Zhang, LJ", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Hybrid organic inorganic halide perovskites with the prototype material of CH3NH3PbI3 have recently attracted intense interest as low-cost and high-performance photovoltaic absorbers. Despite the high power conversion efficiency exceeding 20% achieved by their solar cells, two key issues-the poor device stabilities associated with their intrinsic material instability and the toxicity due to water-soluble Pb2+-need to be resolved before large-scale commercialization. Here, we address these issues by exploiting the 6 strategy of cation-transmutation to design stable inorganic Pb-free halide perovskites for solar cells. The idea is to convert two divalent Pb2+ ions into one monovalent M+ and one trivalent M3+ ions, forming a rich class of quaternary halides in double-perovskite structure. We find through first-principles calculations this class of materials have good phase stability against decomposition and wide range tunable optoelectronic properties. With photovoltaic-functionality-directed materials screening, we identify 11 optimal materials with intrinsic thermodynamic stability, suitable band gaps, small carrier effective masses, and low excitons binding energies as promising candidates to replace Pb-based photovoltaic absorbers in perovskite solar cells. The chemical trends of phase stabilities and electronic properties are also established for this class of materials, offering useful guidance for the development of perovskite solar cells fabricated with them.", + "Times Cited, WoS Core": 770, + "Times Cited, All Databases": 803, + "Publication Year": 2017, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000394829200019", + "Markdown": "# Design of Lead-free Inorganic Halide Perovskites for Solar Cells via Cation-transmutation \n\nXingang Zhao, Jihui Yang, Yuhao Fu, Dongwen Yang, Qiaoling Xu, Liping Yu, Su-Huai Wei, and Lijun Zhang J. Am. Chem. Soc., Just Accepted Manuscript $\\cdot$ Publication Date (Web): 23 Jan 2017 Downloaded from http://pubs.acs.org on January 23, 2017 \n\n# Just Accepted \n\n“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier $(\\mathsf{D O}|\\oplus)$ . “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts. \n\n# Design of Lead-free Inorganic Halide Perovskites for Solar Cells via Cation-transmutation \n\nXin-Gang Zhao†,‡, Jihui Yang⊥,‡, Yuhao $\\mathrm{Fu}^{\\dagger}$ , Dongwen Yang†, Qiaoling $\\mathrm{Xu}^{\\dag}$ , Liping $\\mathrm{Yu}^{\\#}$ , Su-Huai Wei§,\\* and Lijun Zhang†,\\$,\\* \n\n†Department of Materials Science and Engineering and Key Laboratory of Automobile Materials of MOE, Jilin University \nChangchun 130012, China \n⊥Department of Materials Science and Nanoengineering, Rice University, Houston, Texas 77005, USA \n§Beijing Computational Science Research Center, Beijing 100094, China \n#Department of Physics, Temple University, Philadelphia, PA 19122, USA \n\\$State Key Laboratory of Superhard Materials, Jilin University, Changchun 130012, China \n\nKEYWORDS: photovoltaic, solar cell absorbers, halide perovskites, material design, first-principles calculation \n\nABSTRACT: Hybrid organic-inorganic halide perovskites with the prototype material of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ have recently attracted intense interest as low-cost and high-performance photovoltaic absorbers. Despite the high power conversion efficiency exceeding $20\\%$ achieved by their solar cells, two key issues — the poor device stabilities associated with their intrinsic material instability and the toxicity due to water soluble ${\\mathrm{Pb}}^{2+}$ — need to be resolved before large-scale commercialization. Here, we address these issues by exploiting the strategy of cation-transmutation to design stable inorganic $\\mathrm{Pb}$ -free halide perovskites for solar cells. The idea is to convert two divalent $\\mathrm{Pb}^{2+}$ ions into one monovalent $\\mathbf{M}^{+}$ and one trivalent $\\mathbf{M}^{3+}$ ions, forming a rich class of quaternary halides in double-perovskite structure. We find through first-principles calculations this class of materials have good phase stability against decomposition and wide-range tunable optoelectronic properties. With photovoltaic-functionality-directed materials screening, we identify eleven optimal materials with robust intrinsic thermodynamic stability, suitable band gaps, small carrier effective masses, and low excitons binding energies as promising candidates to replace $\\mathrm{Pb}$ -based photovoltaic absorbers in perovskite solar cells. The chemical trends of phase stabilities and electronic properties are also established for this class of materials, offering useful guidance for the development of perovskite solar cells fabricated with them. \n\n# 1. Introduction \n\nical fHorymbruilda orfg $\\mathrm{AM}^{\\mathrm{IV}}\\mathrm{X}^{\\mathrm{VII}}{}_{3}$ a,nwichehraelidAe rpeeproevsseknittsesa ws imthalla cmhoenmovalent organic molecule, ${\\bf{M}}^{\\mathrm{{IV}}}$ is a divalent group-IVA cation and $\\boldsymbol{\\mathrm{X}}^{\\mathrm{{VII}}}$ is a halogen anion, have recently attracted a tremendous amount of attention in the photovoltaic community.1–15 Current record power conversion efficiency (PCE) of solar cells based on them has been boosted from initial value of $3.8\\%$ ,8 step by ste p,16,17,5,18–21 to current 22.1%.22 During this process the breakthrough step is the first solid-state perovskite solar cell designed by Kim et al. yielding the PCE exceeding $9\\%$ ,16 which triggered significant perovskite solar cell research activities and made PCEs dramatically enhanced within only shortly seven years. Such a rapid progress far surpasses the cases of many conventional thin film solar cells (i.e., fabricated with crystalline Si, CdTe, $\\mathrm{Cu(In,Ga)Se}_{2}$ , etc.) that achieved similar PCEs after decades of efforts. The high PCE of halide perovskites originates from their intrinsic material properties, including suitable band gaps and high threshold light absorption,23,24 defect-tolerant feature,25–29 ultra-long carrier diffusion length,9 low exciton binding energy,30, 31 balanced electron and hole mobilit y,32,33 etc. These unique properties, accompanying with the low-cost solution-based fabrication routes, make them ideal candidates as new-generation photovoltaic absorbers. \n\nDespite enormous success of $\\mathrm{AM}^{\\mathrm{IV}}\\mathrm{X}^{\\mathrm{VII}}{}_{3}$ perovskites in solar cell applications, challenges are still standing in their way to large-scale commercial applications. The first serious issue is their poor long-term device stability, especially under heat tahned hiuntmriindsiitcy ctohnedrimtiodnys,nawmhich icnosutaldbilbietyparotfia $\\dot{\\mathrm{AM}}^{\\mathrm{IV}}\\mathrm{X}^{\\mathrm{VII}}{}_{3}$ e.3d4–t3o6 While the underlying mechanism remain unclear, it is likely because of the organic cations involved that correspond to rather loose chemical bonding, and their inherent instability.3,37,38 Experimentally, it has been demonstrated that mixing a small amount of inorganic cations such as ${\\mathrm{Cs}}^{+}$ with methylammonium $\\mathrm{(CH}_{3}\\mathrm{NH}_{3}^{+}\\mathrm{)}$ /formamidinium $(\\mathrm{CH}_{3}(\\mathrm{NH}_{2})_{2}^{+})$ at the A site significantly increases the stabilities of perovskite films.2,39–41 Contrast to the organic-inorganic hybrid perovskites, purely inorganic $\\mathrm{Cs}\\mathrm{Pb}\\bar{\\mathrm{X}}^{\\mathrm{VII}}{}_{3}$ perovskites exhibit excellent thermal stability.3,38 Secondly, because the upper groupIVA elements such as Sn and Ge at the ${\\bf{M}}^{\\mathrm{{IV}}}$ site tend to be oxidized from divalent Sn2+/Ge2+ to tetravalent Sn4+/Ge4+,32,42–44 and thus cause the instability issue, current halide perovskite based solar cells with high PCEs exclusively contain the toxic element — Pb. This will inevitably cause potential environmental concerns for large-scale solar cell devices.45–47 Consequently, it is of great interest to find alternative halide perovskites consisting of completely inorganic components having good stability and meanwhile made of less toxic elements. \n\nTo eliminate the toxic $\\mathrm{Pb}$ , while the straightforward idea is considering other divalent cations beyond group-IVA elements, it turns out that the choice is limited and the resulting compounds have poor optoelectronic properties for solar cells (e.g., too large band gaps and heavy carrier effective masses).48–52 Alternatively, one can consider to transmute two divalent $\\mathrm{Pb}^{2+}$ ions into one monovalent ion $\\mathbf{M}^{+}$ and one trivalent ion $\\mathbf{M}^{3+}$ , i.e., $2\\mathbf{Pb}^{2+}\\rightarrow\\mathbf{M}^{+}+\\mathbf{M}^{3+}$ , by keeping the total number of valance electrons unchanged at $\\dot{\\mathrm{~M~}}^{\\mathrm{{IV}}}$ sites. Known as atomic transmutation, this design strategy has led to great success in finding new materials with improved functionalities such as solar absorbers. Typical example is the evolution of binary $\\mathrm{ZnSe}$ to ternary $\\mathrm{CuGaSe}_{2}$ and then to quaternary $\\mathrm{Cu_{2}Z n S n S e_{4}}$ : $\\mathrm{ZnSe}$ has a wide band gap of $2.8~\\mathrm{eV};$ , which is too large for solar cell application. By transmuting two $Z\\mathrm{n}^{2+}$ ions into one $\\mathrm{Cu}^{+}$ and one $\\mathrm{{\\dot{G}a}}^{3+}$ , i.e., $2\\dot{\\mathrm{Z}}\\mathrm{n}^{2+}{\\rightarrow}\\mathrm{Cu}^{+}{+}\\dot{\\mathrm{Ga}}^{3+}$ , $\\mathrm{CuGaSe}_{2}$ is obtained with a band gap of $1.7\\ \\mathrm{eV}.$ Further atomic transmutation, i.e., $2\\mathrm{Ga}^{3+}{\\rightarrow}Z\\mathrm{n}^{2+}{+}\\mathrm{S}\\mathrm{n}^{4+}$ , leads to $\\mathrm{Cu}_{2}\\mathrm{ZnSnSe}_{4}$ with a band gap of $1.0~\\mathrm{eV}.^{53,54}$ Both $\\mathrm{CuGaSe}_{2}$ and $\\mathrm{Cu}_{2}Z\\mathrm{nSnSe}_{4}$ based compounds have been used in solar cells showing high PCEs of above $20\\%$ and $10\\%$ , respectively. With this transmutation strategy applied, a novel class of $\\mathrm{Pb}$ -free quaternary materials in the formula of ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\mathrm{VII}}{}_{6}$ with double-perovskite structures may form. Considering that the $6s^{2}p^{0}$ configuration of $\\mathrm{Pb}^{2+}$ is believed to be responsible for the unique optoelectronic properties of AMIVXVII3 perovskites,24,55 the available choice of $\\mathbf{M}^{3+}$ can be $\\mathrm{Bi}^{3+}$ and $\\mathrm{\\dot{S}b}^{3+}$ and $\\mathbf{M}^{+}$ can be any size-matching monovalent cations. Compatible with the smaller sizes of $\\mathrm{Bi}^{3+}/\\mathrm{Sb}^{3+}$ than $\\mathrm{Pb}^{2+}$ , the small inorganic cations (rather than the large organic cations commonly used in $\\mathrm{AM}^{\\mathrm{{IV}}}\\mathrm{X}^{\\mathrm{{VII}}}{}_{3,}$ ) can be adopted at the A site to stabilize the perovskite lattice, opening the avenue for achieving the inorganic halide perovskites with good stabilities. In fact, several such double-perovskite compounds ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\mathrm{VII}}{}_{6}$ have been synthesized since $1970\\mathrm{s}^{56-60}$ but never considered for photovoltaic applications. Only until quite recently proposals of using $\\mathrm{Cs}_{2}\\mathrm{AgBiCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{AgBiBr}_{6}$ as potential solar absorbers were put forward.61–63 Though exhibiting good stability when exposed to air, neither of them show superior photovoltaic performance due to their indirect Given the fact that the group of quaternary band-gap feature and large gap values (above 2 eV).61,63,64 ${\\bf{A}}_{2}{\\bf{M}}^{+}{\\bf{M}}^{3+}{\\bf{X}}^{\\mathrm{{VII}}}{}_{6}$ perovskites is much broader owing to its multinary nature, one tweoxtn,daersyisfteomthaetircmeexpmlboerrastiomnayof ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\mathrm{VII}}6$ sp.eIrnovssukcihtecsobnyconsidering as many as possible ( $\\mathrm{A},\\mathrm{M}^{+},\\mathrm{M}^{3+},\\hat{\\mathrm{X}}^{\\mathrm{VII}})$ combinations are strongly desired to seek for the best candidates for photovoltaic applications. \n\n![](images/05d00e8a46b8aa4f99c9432c816df8cfd2c23a0e1abf7b490773f859b7dc0d9e.jpg) \nFigure 1. (a) Space of candidate $\\mathrm{A_{2}M^{+}M^{3+}X^{V I I}}_{6}$ perovskites for materials screening: left panel shows adopted double-perovskite structure, and right panel shows schematic idea of atomic transmutation. (b) Materials screening process by considering the properties relevant to photovoltaic performance, i.e., decomposition enthalpy $(\\Delta H)$ , band gap, carriers effective masses ${(m_{e}}^{*}{,}{m_{h}}^{*})$ , and exciton binding energy $(\\Delta E_{\\mathrm{b}})$ .The red squares mean the materials passing the screening (Selected) and the green ones mean not passing (Abandoned). The optimal non-toxic $\\mathrm{A_{2}M^{+}M^{3+}X^{V I I}}_{6}$ perovskites satisfying all the criterions are marked with red checks. \n\nHere we present via systematic first-principles calculations a study of phase stability and photovoltaic related properties for this class of inorganic $\\mathrm{Pb}$ -free ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\mathrm{VII}}{}_{6}$ halide perovskites. Our goal is to identify new stable ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\mathrm{VII}}{}_{6}$ perovskites with potentially superior photovoltaic performance. Different from the previous theoretical work that focused on the ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}_{6}^{\\mathrm{VII}^{\\star}}$ with $\\mathbf{M}^{+}$ limited to be group IB elements,61,63,64 we consider a much broader range of monovalent elements at the $\\mathbf{M}^{+}$ site to accommodate different combinations of elements for the other sites. Specifically, we have considered combinations of (A, $\\mathbf{M}^{+}$ , $\\mathbf{M}^{3+}$ , $\\mathrm{\\dot{X}^{V I I})}$ with $\\mathbf{A}=\\mathbf{C}\\mathbf{s}^{+}$ $\\mathbf{M}^{+}=\\mathbf{\\Phi}$ group IA $(\\mathrm{Na}^{+},\\mathrm{K}^{+},\\mathrm{Rb}^{+})/$ group IB $\\mathrm{(Cu^{+}}$ , ${\\bf A}{\\bf g}^{+}$ , ${\\mathrm{Au}}^{+}$ )/group IIIA $(\\bar{\\mathrm{In}}^{+},\\bar{\\mathrm{Tl}}^{+})$ , $\\dot{\\mathbf{M}}^{3+}=\\mathbf{B}\\dot{\\mathbf{i}}^{3+}/\\mathbf{S}\\mathbf{b}^{3+}$ , and $\\mathbf{X}=\\mathbf{F}/\\mathbf{Cl}^{\\top}\\mathbf{Br}/\\mathbf{I}^{-}$ . As summarized in Figure 1a, in total there are 64 candidate compounds considered, of which only $\\mathrm{Cs}_{2}\\mathrm{AgBiCl}_{6}$ , $\\mathrm{Cs}_{2}\\mathrm{AgBiBr}_{6}$ , $\\mathrm{Cs}_{2}\\mathrm{NaBiCl}_{6}$ , and $\\mathrm{Cs}_{2}\\mathrm{KBiCl}_{6}$ were experimentally synthesized.56–64 Our results indicate that most of the materials in this family have robust stability against decomposition and show flexible tunability of optoelectronic properties with band gaps in the range from infrared to ultraviolet. Through photovoltaic-functionality-directed materials screening, we have identified 11 optimal compounds as promising $\\mathrm{Pb}$ -free photovoltaic absorbers, as depicted in Figure 1b. Especially, we find two $\\mathrm{In}^{+}$ based compounds, $\\mathrm{Cs}_{2}\\mathrm{InSbCl}_{6}$ and ${\\mathrm{Cs}}_{2}{\\mathrm{InBiCl}}_{6}$ , have direct optical band gaps of 1.02 and $0.91\\mathrm{eV}_{:}$ , respectively and they show high theoretical solar cell efficiencies comparable to that of $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ . Equally importantly, we have established the ties for this novel class of chemical trends of phase stability and optoelectronic proper- $\\mathrm{A}_{2}\\mathrm{\\dot{M}^{+}M^{3+}X^{\\hat{\\mathrm{VII}}}}_{6}$ perovskites. Our work offers useful guidance for selectively utilizing these stable and $\\mathrm{Pb}$ -free halide perovskites as promising solar absorbers. \n\n# 2. Computational Methods \n\nOur first-principles calculations were performed within the framework of density-functional theory (DFT) using the plane-wave pseudopotential approach as implemented in the VASP code.65,66 The electron-core interactions are described with the frozen-core projected augmented wave pseudopotentials.67 We use the generalized gradient approximation formulated by Perdew, Burke, and Ernzerhof (PBE)68 as the exchange-correlation functional. The equilibrium structural parameters (including both lattice parameters and internal coordinates) of each candidate material are obtained by total energy minimization via the conjugate-gradient algorithm. The kinetic energy cutoffs for the plane-wave basis set are optimized to ensure the residual forces on atoms converged to below $0.0002~\\mathrm{eV}/\\mathrm{\\AA}$ . The $k$ -point meshes with grid spacing of $2\\pi{\\times}0.025\\mathrm{~\\AA^{-1}}$ or less is used for electronic Brillouin zone integration. The electronic structures and optical absorption spectra are calculated by taking into account of the spin-orbit coupling (SOC) effect, with the Heyd-Scuseria-Ernzerhof (HSE) hybrid functional69 remedying the underestimation of band gaps in common DFT-PBE calculations. The validity of our methodology in the ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}_{6}^{\\mathrm{VII}}$ perovskite system is supported by good agreements on lattice parameters and band gaps between theory and available experiments (Table S1 in the Supporting Information). The comparison of optical absorption spectra between theory and experiment for two existing candidate ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\mathrm{VII}}{}_{6}$ perovskites, $\\mathrm{Cs}_{2}\\mathrm{AgBiCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{AgBiBr}_{6}$ (Figure S3 in the Supporting Information) also indicates reasonably well agreement on absorption edges and relative intensities. Harmonic phonon spectrum is calculated with a finite-difference supercell approach,70 and roomtemperature phonon spectrum is obtained by taking into account anharmonic phonon-phonon interaction with a selfconsistent ab initio lattice dynamical method.71 To give an evaluation of photovoltaic performance of the optimal materials, the maximum solar cell efficiency, i.e., “spectroscopic limited maximum efficiency $\\mathrm{(SLME)}^{,7\\dot{2},\\dot{7}3}$ is calculated. Creation of calculation workflows, management of large amounts of calculations, extraction of calculated results, and postprocessing analysis are performed by using an open-source Python framework designed for large-scale high-throughput energetic and property calculations, the Jilin University Materials-design Python Package $(\\mathrm{Jump}^{2}$ , to be released soon). More details on calculations of photovoltaic-relevant properties are depicted in Supporting Information. \n\n# 3. Results and Discussion \n\n# 3.1 Phase stability of the class of ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\bf{\\cal H}}{\\bf\\Sigma}_{6}$ perovskites \n\nWe begin by probing the most energetically favored spatial distribution of $\\mathbf{\\check{M}}^{+}\\mathbf{X}^{\\mathrm{{VII}}}{}_{6}$ and $\\mathbf{\\Delta}\\mathbf{\\breve{M}}^{3+}\\mathbf{X}^{\\mathrm{vII}}{}_{6}^{}$ motifs in ${\\bf A}_{2}{\\bf M}^{+}{\\bf M}^{3+}{\\bf X}^{\\mathrm{VII}}{}_{6}$ perovskites. We construct a $2{\\times}2{\\times}2$ supercell of standard cubic perovskites, in which various types of arrangements of $\\mathbf{M}^{\\mathrm{+}}\\mathbf{X}_{\\mathrm{~6~}}^{\\mathrm{VII}}$ and $\\mathbf{M}^{3+}\\mathbf{X}_{6}^{\\mathrm{{VII}}}$ motifs are considered. In total, there are six different configurations. Figure 2a shows the calculated total energies for the case of $\\mathrm{Cs}_{2}\\mathrm{AgBiCl}_{6}$ . Clearly the most stable configuration $\\mathbf{F}$ is the standard doubleperovskite structure (in space group of $F m{-}3m)$ with $\\mathrm{{M}^{+}{X}^{\\mathrm{{VII}}}}_{6}$ and M3+XVII6 alternating along the three crystallographic axes and forming the rock-salt type ordering. This arrangement agrees with the structure type determined by the X-ray diffraction experiments.61,74 The decrease of total energies from the configuration A to the $\\mathbf{F}$ can be understood from the variation of electrostatic energies among $\\mathbf{M}^{+}$ and $\\mathbf{M}^{3+}$ cations, which show generally the same trend (as in Table S2 of Supporting Information). It is worth mentioning that other metastable configurations, especially $\\mathbf{D}$ and $\\mathbf{E}$ , may exist at finite temperatures, since their energies are only slightly higher (by less than $30\\mathrm{\\meV/atom})$ . We find that different arrangements of $\\ensuremath{\\mathbf{M}}^{\\ensuremath{+}}\\ensuremath{\\mathbf{X}}^{\\ensuremath{\\mathrm{VII}}}6$ and $\\ensuremath{\\mathbf{M}}^{3+}\\ensuremath{\\mathbf{X}}^{\\mathrm{VII}}6$ motifs can lead to a qualitative change of band gap features, i.e., from a zero gap in A, direct gaps in $\\mathbf{B}{\\cdot}\\mathbf{E}$ , to an indirect gap in F. Besides, the gap values can also be widely modified quantitatively, i.e., from 0 in $\\mathbf{A}$ to $2.62\\ \\mathrm{eV}$ in F. These results imply that the possible disorder effect caused by varied arrangements of $\\mathbf{M}^{\\mathrm{+}}\\dot{\\mathbf{X}}^{\\mathrm{VII}}6$ and $\\mathbf{M}^{3+}\\mathbf{X}_{6}^{\\mathrm{{VII}}}$ motifs at finite temperatures may offer an opportunity to further tune the optoelectronic properties of $\\mathrm{A}_{2}\\mathrm{\\dot{M}^{+}M^{3+}X^{\\mathrm{\\dot{V}I I}}}_{6}$ perovskites. This phenomenon is worth further study. In the remaining, we focus on the most stable configuration — the ordered doubleperovskite structure. \n\n![](images/ca8170515f3a6eebef6b393b95062d7fbed38657ad4a0e5ed8d809be8de82a19.jpg) \nFigure 2. (a) Energies of the $\\mathrm{Cs}_{2}\\mathrm{AgBiCl}_{6}$ perovskites with different types of $\\mathrm{AgCl}_{6}$ (in grey) $+\\mathrm{BiCl}_{6}$ (in blue) motifs arrangements. The energy of the lowest configuration $\\mathbf{F}$ is set to zero. b) Distribution mapping of all the $\\mathrm{A_{2}\\mathrm{M^{+}M^{3+}X^{\\mathrm{VII}}}}_{6}$ perovskites with effective tolerance factor $(t_{e f f})$ and octahedral factor $(\\mu_{e f f})$ as variables (red/green/blue/matron colors represent fluorides/chlorides/bromides/iodides; open/filled symbols correspond to Sb/Bi compounds). (c) Decomposition enthalpy $(\\Delta H)$ of $\\mathrm{A_{2}M^{+}M^{3+}X^{V I I}}_{6}$ double perovskites. (d) The $\\Delta H$ corresponding to different decomposition pathways for selected $\\mathrm{A_{2}M^{+}M^{3+}X^{V I I}}_{6}$ . \n\nTo evaluate the structural stability of materials in the perovskite structure, two empirical quantities in the framework of the idealized solid-sphere model, the Goldschmidt tolerance factor $t$ and the octahedral factor $\\mu$ , are usually considered. Previous statistic analysis of all the existing halide perovskites indicate that formability of perovskites requires $0.44<\\mu<$ 0.90 and $0.81500$ $\\mathrm{mV},$ ) are required in order to reach moderate $\\mathrm{CO}_{2}$ reduction selectivity and activity.12,15 Of these products, formate $\\left(\\mathrm{HCOO^{-}}\\right)$ is a valuable two-electron product used in a variety of industries and whose production has increased greatly in the past 10 years.11 Sn electrodes have emerged as attractive candidates for $\\mathrm{CO}_{2}$ reduction on a large scale,16−18 g iven the relative abundance of Sn in the Earth’s crust19 and high selectivity for CO2 reduction to formate (HCOO−).16,17,20−23 The selectivity for ${\\mathrm{HCOO^{-}}}$ on Sn and other formate-producing catalysts has yet to be fully determined. \n\nSeveral possibilities have been represented in the literature for how Sn reduces $\\mathrm{CO}_{2}$ to $\\mathrm{HCOO^{-}}$ . Early $\\mathrm{CO}_{2}$ studies proposed that ${\\mathrm{HCOO^{-}}}$ could be made via a one-electron transfer to $\\mathrm{CO}_{2},$ forming a $\\mathrm{CO}_{2}^{\\bullet-}$ radical anion24−26 that would exist freely in solution; a subsequent proton transfer from water would form $\\mathrm{HCOO^{\\bullet}};$ , and a second electron transfer results in the $\\mathrm{HCOO^{-}}$ product. Experimental works on Sn electrodes have used Tafel slopes to support this mechanism,16,18 suggesting that the initial one-electron transfer to $\\mathrm{CO}_{2}^{\\bullet-}$ is the rate-limiting step in the reaction. Recent theoretical calculations have proposed that $\\mathrm{\\textHCOO^{-}}$ production occurs through proton-coupled electron transfer (PCET) on the electrode surface27,28 and that $\\mathrm{HCOO^{-}}$ production on a variety of metal surfaces can occur through both the $*_{\\mathrm{COOH}}$ and $^{*}\\mathrm{OCHO}$ intermediates. To date, many questions remain as to why Sn exhibits a high selectivity for formic acid production in comparison to other $\\mathrm{CO}_{2}$ reduction catalysts. \n\nIn this study, the catalytic activity of Sn electrodes is investigated for the $\\mathrm{CO}_{2}\\mathrm{RR}$ in aqueous electrolyte as a function of potential. By comparing the production of $\\mathrm{\\check{H}C O O\\check{\\Sigma}}$ on $S_{\\mathrm{n}}$ electrodes with that of other metal catalysts active for the ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ and by performing density functional theory (DFT) calculations to estimate the binding energies of various intermediates on these metal surfaces, we propose a means to understand how Sn is selective for the ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ to $\\mathrm{HCOO^{-}}$ . \n\n# EXPERIMENTAL METHODS \n\nAll electrochemical experiments were performed using a continuous flow electrolysis reactor previously reported.29 The compartments were filled with $0.1\\mathrm{~M~KHCO}_{3}$ electrolyte (Sigma-Aldrich, $99.99\\%$ metals basis) and constantly purged with $\\mathrm{CO}_{2}$ (5.0, Praxair) at $20\\ \\mathrm{sccm}$ . The $\\mathrm{\\ttpH}$ of the electrolyte was consistently measured to be 6.8 before and after each ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ experiment, and a $\\mathrm{Ag/AgCl}$ reference electrode (Acumen) was used for all experiments. Finally, the compartments were separated by an anion exchange membrane (Selemion membrane, AMV). \n\nElectrolysis of $\\mathrm{CO}_{2}$ on Sn electrodes were performed using a Biologic VMP3 potentiostat with an electrochemical impedance spectroscopy (EIS) capable channel. The resistance across the cell was measured; for all experiments, $85\\%$ of the ohmic loss was compensated by the potentiostat, and the remaining $15\\%$ was manually compensated after each experiment. All potentials shown in this work are versus the reversible hydrogen electrode (RHE). Furthermore, experiments using Ar instead of $\\mathrm{CO}_{2}$ to show that $\\mathrm{CO}_{2}$ was the primary reacting species were conducted in a manner similar to that for the $\\mathrm{CO}_{2}$ electrolysis experiments (Figure S1 in the Supporting Information). The quantification of gas and liquid products were performed in a fashion similar to that described in our previous work.30 \n\nPrevious reports show that the activity of $S_{\\mathrm{n}}$ for $\\mathrm{CO}_{2}\\mathrm{RR}$ depends greatly on the treatment performed on the surface before electrolysis.15,16 For this study, a high-purity Sn foil $(99.99\\%)$ was purchased from Alfa Aesar and mechanically polished. The $S_{\\mathrm{n}}$ foils were then electropolished in 0.1 M HCl at a potential of $-3.0\\mathrm{~V~}$ vs a graphite counter electrode placed at a distance of $2\\ \\mathrm{cm}$ from the foil. The foils were then rinsed and inserted into the electrochemical cell. This pretreatment removed all excess oxide from the surface, leaving only a native oxide on the Sn electrodes (Figure S2 in the Supporting Information). This oxide layer was removed in the electrochemical cell via cyclic voltammetry (Figure S3 in the Supporting Information), where a reductive feature at $-0.3{\\mathrm{~V~}}$ vs RHE was observed. This feature is representative of the reduction of $S\\mathfrak{n}^{2+}$ to metallic $\\scriptstyle{\\mathrm{Sn}}$ .31 \n\nBinding energies of adsorbates on the (211) facet of FCC transition metals were obtained from density functional theory (DFT) calculations by Peterson et al.32 Binding energies of adsorbates on the Sn were calculated using a methodology almost identical with that used for the (211) facet for transition metalsplane-wave periodic DFT calculations performed using the DACAPO code with Vanderbilt ultrasoft pseudopotentials.33,34 A plane-wave energy cutoff of $340~\\mathrm{eV}$ and a density cutoff of $640\\ \\mathrm{eV}$ were used. The RPBE exchange-correlation functional was chosen for compatibility with the (211) facet energies as well as its minimal errors for chemisorption energies.35 The Brillouin zone was sampled with a $4\\times4\\times1$ Monkhorst−Pack $k$ -point set.36 Each slab used a $3\\times3$ unit cell with four layers−two layers frozen at the bulk lattice constant and two layers allowed to relax freely. \n\n# RESULTS AND DISCUSSION \n\nThe selectivity of Sn electrodes toward $\\mathrm{HCOO^{-}}$ as a function of potential is depicted in Figure 1. Only hydrogen $\\left(\\operatorname{H}_{2}\\right)$ , $\\mathrm{HCOO^{-}}.$ , and carbon monoxide (CO) were detected; no further reduced products were observed from the polycrystalline Sn electrodes. The partial current densities of $\\mathrm{HCOO^{-}}$ and $\\mathrm{H}_{2}$ (Figure 1A), normalized to the geometric surface area, show an overall increase in current density as the potential becomes more cathodic. The total Faradaic efficiency for all potentials measured ranged from $90\\%$ to $110\\%$ . Both $\\mathrm{H}_{2}$ and $\\mathrm{HCOO^{-}}$ are first detected at $-0.44\\mathrm{V}$ vs RHE with $\\mathrm{H}_{2}$ as the major product, while the first potential where CO is detected is at $-0.59\\mathrm{V}$ vs RHE. No products are detected before $-0.44\\mathrm{V},$ , and the only Faradaic current measured before this potential is the reduction of the native oxide layer of $\\mathrm{Sn.^{37}\\ H C O O^{-}}$ becomes the major product at $-0.8\\mathrm{~V~}$ and reaches a maximum Faradaic efficiency of $70\\%$ between $-0.9$ and $-1.0\\mathrm{~V},$ whereas CO reaches a maximum Faradaic efficiency of $17\\%$ at $-0.76\\mathrm{~V~}$ . As the overpotential increases with potentials more negative than $-1.0$ $\\mathrm{\\DeltaV}$ vs RHE, the partial current density for $\\mathrm{\\:HCOO^{-}}$ plateaus because, at higher $\\mathbf{CO}_{2}\\mathrm{RR}$ current densities, mass transport becomes limiting. In our electrochemical cell, this mass transport limit is $\\sim8-10\\mathrm{\\mA}/\\mathrm{cm}^{214}$ for $2\\mathrm{e}^{-}\\mathrm{CO}_{2}\\mathrm{RR}$ products. Methane, methanol, and other further reduced products were not detected. The electrochemical results are consistent with previous studies on Sn electrodes, $^{12,15,16,38-40}$ demonstrating a high selectivity for $\\mathrm{HCOO^{-}}$ production. \n\n![](images/66ff57eba709bc8e3b3a9f4ed4600eb3aaf3fa9f8270c9d0846a8fa696794494.jpg) \nFigure 1. Partial current densities (A) and Faradaic efficiencies (B) for formate, CO, and hydrogen produced on polycrystalline Sn. The Sn electrode is selective toward hydrogen at the earlier overpotentials but becomes selective to formate around $-0.8\\mathrm{~V~}$ vs RHE. A maximum Faradaic efficiency to formate is observed around $-0.9\\mathrm{~V~}$ vs RHE before mass transport of $\\mathrm{CO}_{2}$ becomes the rate-limiting step for $\\mathbf{CO}_{2}\\mathbf{RR}$ \n\nIn light of these results, it is important to consider possible mechanisms and pathways. Tafel slope analysis can be helpful in understanding aspects regarding the hydrogen evolution reaction (HER). Several reports have extrapolated this type of analysis to derive mechanistic information from Sn electrodes,16,18 particularly on whether the first step is a protoncoupled electron transfer (PCET) or a transfer of one electron to the $\\mathrm{CO}_{2}$ molecule. However, in this work, we focus on gaining insights by directly comparing the CO and ${\\mathrm{HCOO^{-}}}$ production of Sn electrodes to other polycrystalline metal foil catalysts. The CO and $\\mathrm{HCOO^{-}}$ partial current densities of the metals selected for this comparisonAg, Au, Cu, Zn, Pt, and Niare taken from our previous studies utilizing the same type of electrochemical cell.14,29,30 A consistent potential of $-0.9\\mathrm{~V~}$ vs RHE was selected for all metals included in this study; at this potential, only two-electron products (i.e., $\\mathrm{H}_{2},$ CO, $\\mathrm{HCOO^{-}})$ are measured on all metals except Cu. Furthermore, this potential is in the kinetic-limited region for each catalyst, allowing for us to analyze the intrinsic activity of each metal without any effect of $\\mathrm{CO}_{2}$ mass transport limitations. \n\nFirst, we examine the case of CO production. Figure 2 plots the calculated binding energies of $^{*}{\\mathrm{COOH}}$ on each metal surface along with each metal’s experimentally measured partial current densities toward CO. A trend in activity is observed in the form of a volcano plot for $\\mathrm{CO}_{2}\\mathrm{RR}$ to CO. The Sabatier principle, which states that binding to key intermediates that is neither too strong nor too weak leads to maximum activity, is evident in Figure 2. This volcano plot is very similar to those in previous reports14 using ${\\mathrm{CO}}^{*}$ binding energies as a descriptor and further supports the hypothesis that $\\mathrm{CO}_{2}$ reduction to CO proceeds through a carbon-bound $^{*}{\\mathrm{COOH}}$ intermediate, supporting the notion of $*_{\\mathrm{COOH}}$ as a descriptor for CO production. Sn appears on the weak-binding leg of the volcano due to its weak interaction with ${\\mathrm{COOH^{*}}}$ , suggesting that $\\mathrm{CO}_{2}\\mathrm{RR}$ to CO on Sn occurs through a pathway similar to that hypothesized on transition metals.27,41 \n\n![](images/a63d58d3c041c9f2f8ea3242090b991173123fc2d0f7bc4210a3fb3241f639ce.jpg) \nFigure 2. Volcano plot using $^{*}{\\mathrm{COOH}}$ binding energy as a descriptor for CO partial current density at $-0.9{\\mathrm{~V~}}$ vs RHE. Sn appears on the weak-binding leg of the volcano, suggesting that $^{*}{\\mathrm{COOH}}$ binding energy is a key intermediate for $\\mathrm{CO}_{2}$ reduction to CO on Sn. \n\nA similar approach was utilized to understand the key intermediate for $\\mathrm{HCOO^{-}}$ production. Using $\\mathrel{\\mathrm{\\cdots}}\\mathrm{COOH}$ binding energies as a descriptor, the partial current densities of $\\mathrm{HCOO^{-}}$ have been plotted (Figure S4 in the Supporting Information). No clear volcano trend is observed, indicating that $*_{\\mathrm{COOH}}$ may not be the key intermediate for $\\mathrm{\\:HCOO^{-}}$ production. Moreover, metals with similar $\\mathrel{\\mathrm{\\cdots}}\\mathrm{COOH}$ binding energies (e.g., Sn and $\\mathrm{Ag}$ ) exhibit vastly different partial current densities for $\\mathrm{HCOO^{-}}.$ , which is unexpected if $^{*}{\\mathrm{COOH}}$ is the main intermediate for ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ to $\\mathrm{HCOO^{-}}$ . As no correlation is observed between $^{*}{\\mathrm{COOH}}$ binding energies and $\\mathrm{HCOO^{-}}$ activity, $^{*}{\\mathrm{COOH}}$ binding energy is not likely the key descriptor for the reduction of $\\mathrm{CO}_{2}$ to $\\mathrm{HCOO^{-}}$ , unlike the case for CO production. \n\nFigure 3 plots ${\\mathrm{HCOO^{-}}}$ partial current densities at $-0.9\\mathrm{V}$ vs RHE versus $^{*}\\mathrm{OCHO}$ binding energies instead, to establish whether $\\mathrm{\\Pi{HCOO}^{-}}$ production proceeds through an oxygenbound intermediate. Indeed, a clear volcano trend is observed among all (Figure 3). Au, Ag, Pt, and $\\mathtt{C u}$ are on the weakbinding side of the volcano, indicating that $^{*}\\mathrm{OCHO}$ may not interact strongly enough with the surface to lead to high selectivity to $\\mathrm{HCOO^{-}}$ . Ni and $Z\\mathrm{n}$ are on the strong-binding side of the volcano, indicating that $^{*}\\mathrm{OCHO}$ binds too strongly to the surface for further reduction to formate. Sn appears near the top of this volcano, implying that Sn has a near-optimal binding energy of the key intermediate $^{*}\\mathrm{OCHO}$ to produce $\\mathrm{HCOO^{-}}$ . This volcano suggests that \\*OCHO is a key intermediate for $\\mathrm{HCOO^{-}}$ production on transition metals as well as Sn and provides an explanation for Sn’s high selectivity toward $\\mathrm{HCOO^{-}}$ . While $^{*}\\mathrm{OCHO}$ has been suggested as a possible intermediate for $\\mathrm{HCOO^{-}}$ production on $\\mathrm{Cu}^{42}$ and other metals,28 no other experimental work to date has established $^{*}\\mathrm{OCHO}$ as the primary intermediate for $\\mathrm{\\:HCOO^{-}}$ production on a wide range of metals or proposed a possible explanation for Sn’s selectivity to $\\mathrm{HCOO^{-}}$ . \n\n![](images/c04b846810f63f0d1122754a2a686e1e230566a54e2cfd5770326c521a1283fb.jpg) \nFigure 3. Volcano plot using $^{*}\\mathrm{OCHO}$ binding energy as a descriptor for ${\\mathrm{HCOO^{-}}}$ partial current density at $-0.9\\mathrm{V}$ vs RHE. Sn appears near the top of the volcano, suggesting that $^{*}\\mathrm{OCHO}$ is a key intermediate for $\\mathrm{CO}_{2}$ reduction to $\\mathrm{HCOO^{-}}$ on Sn. \n\n![](images/9643e27793eef642367b01668af5cee137586dbf16db3c68901de97d8c6cacb8.jpg) \nFigure 4. Mechanism that includes pathways for CO and $\\mathrm{HCOO^{-}}$ production from $\\mathrm{CO}_{2}$ . $\\mathrm{CO}_{2}$ may bind to the electrode surface in an initial electrochemical step via the carbon or the oxygens (resulting in a single adsorption intermediate, $*_{\\mathrm{COOH}}$ , or a bidentate $^{*}\\mathrm{OCHO}$ intermediate, respectively). The second electrochemical step results in the production of CO or $\\mathrm{HCOO^{-}}$ . For metals that are far from the optimal $^{*}\\mathrm{OCHO}$ binding energy but near the optimal $*_{\\mathrm{COOH}}$ binding energy, it is possible that $*_{\\mathrm{COOH}}$ may be the intermediate for ${\\mathrm{HCOO^{-}}}$ production. \n\nSeveral additional insights can be obtained from Figures 2 and 3 about metal selectivity toward $2\\mathrm{e}^{-}$ products (i.e., $\\mathrm{H}_{2},\\mathrm{CO},$ and $\\mathrm{HCOO^{-}}\\mathrm{,}$ ). For the metals that are not near the peaks of the $^{*}{\\mathrm{COOH}}$ and ${}^{*}\\mathrm{OCHO}$ volcanos (e.g., Pt, Ni), the major product being produced at $-0.9\\mathrm{~V~}$ vs RHE is $\\mathrm{H}_{2};$ ; this is unsurprising, as neither of these catalysts have optimal binding energies for either $\\mathrm{HCOO^{-}}$ or CO production. With regard to the ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ both $\\mathrm{Pt}$ and Ni produce more $\\mathrm{HCOO^{-}}$ than CO. As both Pt and Ni have a very strong binding affinity for carbon-bound intermediates such as $*_{\\mathrm{COOH}}$ and $^{*}\\mathrm{CO}_{;}$ , it is likely that CO poisons the metal surface and limits the amount of CO produced on these electrodes. For the metals that are not near the peak of the \\*OCHO volcano but near the peak of the $*_{\\mathrm{COOH}}$ volcano (e.g., Au, $\\mathrm{Ag}{\\dot{}}$ , the major product being produced at $-0.9\\mathrm{V}$ vs RHE is CO, with only a small amount of $\\mathrm{\\textHCOO^{-}}$ being detected. This suggests that, although the $*_{\\mathrm{COOH}}$ binding energies for most of the metals in this study are weaker in comparison to $^{*}\\mathrm{OCHO}$ , kinetic limitations that are not captured in the electronic energy calculations might play a nontrivial role in determining selectivity for these metals. For instance, metal cation interactions on Au and Ag could alter the electrode surface in a way that would lead to lower barriers for $*_{\\mathrm{COOH}}$ adsorption,43 limiting the production of $\\mathrm{\\:HCOO^{-}}$ and leading to the high selectivity of CO. For these metals with low binding affinity to oxygen but near-optimal carbon binding affinity, it appears that the $*_{\\mathrm{COOH}}$ pathway to CO is preferable to the \\*OCHO pathway to $\\mathrm{HCOO^{-}}$ . From these observations, it seems that, regardless of $^{*}{\\mathrm{COOH}}$ binding energy, if a metal is not near the peak of the $^{*}\\mathrm{OCHO}$ volcano, ${\\mathrm{HCOO^{-}}}$ production is greatly reduced in comparison to other $2e^{-}$ products. \n\nHowever, for the metals that are near the peak of the \\*OCHO volcano but not near the peak of the $*_{\\mathrm{COOH}}$ volcano $(\\mathrm{e.g.,\\Cu,\\Zn})_{\\mathrm{.}}$ , the major product formed on these surfaces is $\\mathrm{H}_{2}$ . Furthermore, on $Z\\mathrm{n}$ the major ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ product is CO, whereas the major ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ product on $\\mathtt{C u}$ is $\\mathrm{HCOO^{-}}$ . Zn could be limited in its production of $\\mathrm{HCOO^{-}}$ due to its very strong $^{*}\\mathrm{OCHO}$ binding energy, which could lead to a higher Faradaic efficiency for hydrogen evolution. While it has been shown that $Z\\mathrm{n}$ binds CO very weakly, $^{14}\\mathrm{Zn}$ has an intermediate $*_{\\mathrm{COOH}}$ binding energy due to a bidentate interaction with the surface. Both carbon and oxygen binding energies play a role in determining $*_{\\mathrm{COOH}}$ binding energy on $Z\\mathrm{n}$ , which explains why it does not sit on the weak-binding side of the $\\scriptstyle{\\mathrm{\"cooH}}$ volcano. $\\mathrm{Cu},$ having an intermediate $^{*}{\\mathrm{COOH}}$ binding energy and sitting on the weak-binding side of the $^{*}\\mathrm{OCHO}$ volcano, also produces methane and ethylene at this potential. On the basis of these results, $\\mathtt{C u}$ binds $^{*}\\mathrm{OCHO}$ weakly enough for $\\mathrm{HCOO^{-}}$ production to not dominate the $\\mathrm{CO}_{2}\\mathrm{RR}$ (although it is the major $\\mathrm{CO}_{2}\\mathrm{RR}$ product at this potential) but has an intermediate $^{*}{\\mathrm{COOH}}$ binding energy to the surface for further reduced products to be observed. Along with a high overpotential for the hydrogen evolution reaction,27,28 Cu seems to have a combination of binding energies that enables it to produce ${>}2\\tt{e}^{-}$ products. For the metals that are near the peak of both the $*_{\\mathrm{COOH}}$ and \\*OCHO volcanoes (e.g., Sn, In), the major product formed on the electrode surface is $\\mathrm{HCOO^{-}}$ (Figures S5 and S6 in the Supporting Information). For Sn, the $^{*}\\mathrm{OCHO}$ pathway for $\\mathrm{HCOO^{-}}$ production dominates over the $*_{\\mathrm{COOH}}$ pathway for CO production. The $^{*}\\mathrm{OCHO}$ volcano suggests that oxygen-bound intermediates interact more strongly with the Sn surface than carbon-bound intermediates and steer Sn’s selectivity to ${\\mathrm{HCOO^{-}}}$ over CO. \n\nThese results suggest that, for the metals shown in Figures 2 and 3, CO production occurs primarily through a key carbonbound intermediate, $^{*}{\\mathrm{COOH}}$ , and ${\\mathrm{HCOO^{-}}}$ production proceeds primarily through a key oxygen-bound intermediate, $^{*}\\mathrm{OCHO}$ . It is important to consider both $\\scriptstyle{\\mathrm{\"cooH}}$ and $^{*}\\mathrm{OCHO}$ binding energies for these pathways, as the two energies do not scale (Figure S7 in the Supporting Information). Figures 2 and 3 underscore the importance of both carbon and oxygen affinities for understanding the $\\mathbf{CO}_{2}\\mathrm{RR}.$ Additionally, these results are consistent with recent operando spectroscopic techniques that have reported observing $^{*}\\mathrm{OCHO}$ on Sn electrodes.40,44 While it has been suggested that $\\mathrm{HCOO^{-}}$ could be generated through the $*_{\\mathrm{COOH}}$ intermediate,28 particularly on transition-metal surfaces with very low binding affinity to $^{*}\\mathrm{OCHO}$ (e.g., Au, Ag), our results do not indicate any relationship between $^{*}{\\mathrm{COOH}}$ binding energy and $\\mathrm{HCOO^{-}}$ production (Figure S4 in the Supporting Information). \n\nFrom a combination of the insights gained from the $^{*}{\\mathrm{COOH}}$ and $^{*}\\mathrm{OCHO}$ volcanoes, a mechanism for ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ to $2\\mathrm{e}^{-}$ products is presented in Figure 4. The first PCET can take place either on one of the oxygens, resulting in a carbon-bound $\\scriptstyle{\\mathrm{COOH^{*}}}$ (top path), or on the carbon atom, resulting in an oxygen-bound ${\\mathrm{OCHO^{*}}}$ (bottom path). The second electrochemical step for the top and bottom paths leads directly to $^{*}\\mathrm{CO}$ and $*_{\\mathrm{HCOOH}}$ , respectively. The final step of desorption results in either CO or ${\\mathrm{HCOO^{-}}}$ being released from the surface of the electrode. These results provide new insights into the $\\mathrm{CO}_{2}\\mathrm{RR}$ on metal catalysts to $2\\mathrm{e}^{-}$ products. \n\n# CONCLUSIONS \n\nWe have reported the catalytic activity of Sn electrodes for $\\mathrm{CO}_{2}$ reduction as a function of potential. Using an electrochemical cell designed for high sensitivity to identify and quantify the products of the ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ we note that the only products observed are $\\mathrm{H}_{2},$ CO, and $\\mathrm{HCOO^{-}}$ . $\\mathrm{HCOO^{-}}$ was confirmed as the major ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ product formed on $S_{\\mathrm{n}}$ and was the dominant product over $\\mathrm{H}_{2}$ at potentials more negative than $-0.8\\mathrm{~V~}$ vs RHE. We have compared the production of CO and $\\mathrm{\\textHCOO^{-}}$ on Sn to that of other metals to examine trends in behavior. DFT calculated \\*COOH binding energy emerges as a descriptor for the $\\mathrm{CO}_{2}\\mathrm{RR}$ to CO, resulting in a clear volcano trend and suggesting that $^{*}{\\mathrm{COOH}}$ is a key intermediate for CO production. However, $^{*}{\\mathrm{COOH}}$ binding energies do not describe $\\mathrm{\\textHCOO^{-}}$ production across the metals in this study, suggesting that ${\\mathrm{HCOO^{-}}}$ does not primarily proceed through this carbon-bound intermediate. Instead, we find that $^{*}\\mathrm{OCHO}$ binding energies accurately describe the behavior of the $\\mathrm{CO}_{2}\\mathrm{RR}$ to $\\mathrm{\\bfH{COO}^{-}}$ across the range of metals, resulting in a clear volcano trend. Furthermore, Sn is located near the top of the volcano, indicating that it has a near-optimal $^{*}\\mathrm{OCHO}$ binding energy for the production of $\\mathrm{HCOO^{-}}$ . These results underscore the importance of surface oxophilicity in describing the activity and selectivity of metal catalysts for $\\mathrm{CO}_{2}$ reduction. Establishing trends in CO and ${\\mathrm{HCOO^{-}}}$ production that incorporate the appropriate descriptors is helpful for designing catalysts that can achieve high selectivity to $\\mathrm{HCOO^{-}}$ , CO, and other products of interest. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acscatal.7b00687. \n\n${\\mathrm{HCO}}_{3}^{-}$ reduction experiments, SEM of poly-Sn and XPS before/after pretreatment, CV and CAs of $\\mathrm{CO}_{2}\\mathrm{RR}$ on Sn, ${\\mathrm{HCOO^{-}}}$ production vs $*_{\\mathrm{COOH}}$ binding energy, $\\scriptstyle*_{\\mathrm{COOH}}$ volcano including In, $^{*}\\mathrm{OCHO}$ volcano including In, and \\*OCHO binding energy vs $\\mathrel{\\mathrm{\\cdots}}\\mathrm{COOH}$ binding energy (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author \n$^{*}\\mathrm{E}$ -mail for T.F.J.: jaramillo@stanford.edu. ORCID \nChristopher Hahn: 0000-0002-2772-6341 Thomas F. Jaramillo: 0000-0001-9900-0622 \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis material is based upon work supported by the National Science Foundation CAREER Award No. 1066515 and by the Global Climate & Energy Project (GCEP) at Stanford University. The DFT calculations performed were funded by the Air Force Office of Scientific Research (AFOSR) through the Multidisciplinary University Research Initiative (MURI) under AFOSR Award No. FA9550-10-1-0572. J.T.F. acknowledges support by a National Science Foundation Graduate Research Fellowship. The authors also thank Joshua Willis for his help with Figure 4. Thanks are due to Dr. Stephen R. Lynch of the Stanford Department of Chemistry NMR facility for his help with the 600 and 500 MHz experiments. \n\n# REFERENCES \n\n(1) Karl, T. R.; Trenberth, K. E. Science 2003, 302, 1719−1723. (2) Hoffert, M. I.; Caldeira, K.; Benford, G.; Criswell, D. R.; Green, \nC.; Herzog, H.; Jain, A. K.; Kheshgi, H. S.; Lackner, K. S.; Lewis, J. S.; \nLightfoot, H. D.; Manheimer, W.; Mankins, J. C.; Mauel, M. E.; \nPerkins, L. J.; Schlesinger, M. E.; Volk, T.; Wigley, T. M. Science 2002, \n298, 981−987. \n(3) D’Alessandro, D. M.; Smit, B.; Long, J. R. Angew. Chem., Int. Ed. \n2010, 49, 6058−6082. (4) Pires, J. C. M.; Martins, F. G.; Alvim-Ferraz, M. C. M.; Simões, \nM. Chem. Eng. Res. Des. 2011, 89, 1446−1460. \n(5) Whipple, D. T.; Kenis, P. J. A. J. Phys. Chem. Lett. 2010, 1, 3451− \n3458. \n(6) Costentin, C.; Robert, M.; Saveant, J. M. Chem. Soc. Rev. 2013, \n42, 2423−2436. (7) Lu, Q.; Rosen, J.; Zhou, Y.; Hutchings, G. S.; Kimmel, Y. C.; \nChen, J. G.; Jiao, F. Nat. Commun. 2014, 5, 3242. (8) Agarwal, A. S.; Zhai, Y.; Hill, D.; Sridhar, N. ChemSusChem 2011, \n4, 1301−1310. (9) True, W. R. Oil and Gas Journal 2012, 110, 78−84. (10) Le Berre, C.; Serp, P.; Kalck, P.; Torrence, G. P. Ullmann’s \nEncyclopedia of Industrial Chemistry 2013, 1−34. (11) Reutemann, W.; Kieczka, H. Ullmann’s Encyclopedia of Industrial \nChemistry 2011, 1. (12) Hori, Y.; et al. Electrochim. Acta 1994, 39, 1833−1839. (13) Gattrell, M.; Gupta, N.; Co, A. J. Electroanal. Chem. 2006, 594, \n1−19. \n(14) Kuhl, K. P.; Hatsukade, T.; Cave, E. R.; Abram, D. N.; \nKibsgaard, J.; Jaramillo, T. F. J. Am. Chem. Soc. 2014, 136, 14107− \n14113. (15) Jitaru, M.; Lowy, D. A.; Toma, M.; Toma, B. C.; Oniciu, L. J. \nAppl. Electrochem. 1997, 27, 875−889. \n(16) Chen, Y.; Kanan, M. W. J. Am. Chem. Soc. 2012, 134, 1986− \n1989. \n(17) Machunda, R. L.; Ju, H.; Lee, J. Curr. Appl. Phys. 2011, 11, 986− \n988. (18) Prakash, G. K. S.; Viva, F. A.; Olah, G. A. J. Power Sources 2013, \n223, 68−73. \n(19) Vesborg, P. C. K.; Jaramillo, T. F. RSC Adv. 2012, 2, 7933− \n7947. (20) Anawati; Frankel, G. S.; Agarwal, A.; Sridhar, N. Electrochim. \nActa 2014, 133, 188−196. (21) Bumroongsakulsawat, P.; Kelsall, G. H. Electrochim. Acta 2014, \n141, 216−225. (22) Wu, J.; Harris, B.; Sharma, P. P.; Zhou, X. D. ECS Trans. 2013, \n58, 71−80. \n(23) Li, Y.; Qiao, J.; Zhang, X.; Lei, T.; Girma, A.; Liu, Y.; Zhang, J. \nChemElectroChem 2016, 3, 1618−1628. (24) Hori, Y.; Suzuki, S. Bull. Chem. Soc. Jpn. 1982, 55, 660−665. (25) Jordan, J.; Smith, P. T. Proc. Chem. Soc. 1960, 246−247. (26) Paik, W.; Andersen, T. N.; Eyring, H. Electrochim. Acta 1969, 14, 1217−1232. \n(27) Peterson, A. A.; Abild-Pedersen, F.; Studt, F.; Rossmeisl, J.; Nørskov, J. K. Energy Environ. Sci. 2010, 3, 1311−1315. \n(28) Yoo, J. S.; Christensen, R.; Vegge, T.; Norskov, J. K.; Studt, F. ChemSusChem 2016, 9, 358−363. \n(29) Kuhl, K. P.; Cave, E. R.; Abram, D. N.; Jaramillo, T. F. Energy Environ. Sci. 2012, 5, 7050−7059. \n(30) Hatsukade, T.; Kuhl, K. P.; Cave, E. R.; Abram, D. N.; Jaramillo, T. F. Phys. Chem. Chem. Phys. 2014, 16, 13814−13819. \n(31) BARONETTI, G.; de Miguel, S. R.; et al. Appl. Catal. 1986, 24, 109−116. \n(32) Peterson, A. A.; Nørskov, J. K. J. Phys. Chem. Lett. 2012, 3, 251− 258. \n(33) Vanderbilt, D. Phys. Rev. B: Condens. Matter Mater. Phys. 1990, 41, 7892−7895. \n(34) Center for Atomicscale Materials Design (CAMD), Technical University of Denmark, Lyngby, Denmark. \n(35) Hammer, B.; Hansen, L.; Nørskov, J. Phys. Rev. B: Condens. Matter Mater. Phys. 1999, 59, 7413−7421. \n(36) Monkhorst, H. J.; Pack, J. D. Phys. Rev. B 1976, 13, 5188−5192. (37) Takeno, N. AIST Today (Jpn. Ed.) 2005, 241−243. \n(38) Zhang, S.; Kang, P.; Meyer, T. J. J. Am. Chem. Soc. 2014, 136, 1734−1737. \n(39) Wu, J.; Risalvato, F. G.; Ke, F. S.; Pellechia, P. J.; Zhou, X. D. J. Electrochem. Soc. 2012, 159, F353−F359. \n(40) Baruch, M. F.; Pander, J. E.; White, J. L.; Bocarsly, A. B. ACS Catal. 2015, 5, 3148−3156. \n(41) Shi, C.; Hansen, H. A.; Lausche, A. C.; Norskov, J. K. Phys. Chem. Chem. Phys. 2014, 16, 4720−4727. \n(42) Durand, W. J.; Peterson, A. A.; Studt, F.; Abild-Pedersen, F.; Nørskov, J. K. Surf. Sci. 2011, 605, 1354−1359. \n(43) Chen, L. D.; Urushihara, M.; Chan, K.; Nørskov, J. K. ACS Catal. 2016, 6, 7133−7139. \n(44) Dutta, A.; Kuzume, A.; Rahaman, M.; Vesztergom, S.; Broekmann, P. ACS Catal. 2015, 5, 7498−7502. " + }, + { + "id": "10.1039_c7ee01047h", + "DOI": "10.1039/c7ee01047h", + "DOI Link": "http://dx.doi.org/10.1039/c7ee01047h", + "Relative Dir Path": "mds/10.1039_c7ee01047h", + "Article Title": "Electrocatalysis of polysulfide conversion by sulfur-deficient MoS2 nulloflakes for lithium-sulfur batteries", + "Authors": "Lin, HB; Yang, LQ; Jiang, X; Li, GC; Zhang, TR; Yao, QF; Zheng, GW; Lee, JY", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "Lithium-sulfur batteries are promising next-generation energy storage devices due to their high energy density and low material cost. Efficient conversion of lithium polysulfides to lithium sulfide (during discharge) and to sulfur (during recharge) is a performance-determining factor for lithium-sulfur batteries. Here we show that MoS2-x/reduced graphene oxide (MoS2-x/rGO) can be used to catalyze the polysulfide reactions to improve the battery performance. It was confirmed, through microstructural characterization of the materials, that sulfur deficiencies on the surface participated in the polysulfide reactions and significantly enhanced the polysulfide conversion kinetics. The fast conversion of soluble polysulfides decreased their accumulation in the sulfur cathode and their loss from the cathode by diffusion. Hence in the presence of a small amount of MoS2-x/rGO (4 wt% of the cathode mass), high rate (8C) performance of the sulfur cathode was improved from a capacity of 161.1 mA h g(-1) to 826.5 mA h g(-1). In addition, MoS2-x/rGO also enhanced the cycle stability of the sulfur cathode from a capacity fade rate of 0.373% per cycle (over 150 cycles) to 0.083% per cycle (over 600 cycles) at a typical 0.5C rate. These results provide direct experimental evidence for the catalytic role of MoS2-x/rGO in promoting the polysulfide conversion kinetics in the sulfur cathode.", + "Times Cited, WoS Core": 836, + "Times Cited, All Databases": 867, + "Publication Year": 2017, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000403320300017", + "Markdown": "# Electrocatalysis of polysulfide conversion by sulfur-deficient $M o S_{2}$ nanoflakes for lithium–sulfur batteries† \n\nReceived 18th April 2017, Accepted 15th May 2017 \n\nHaibin Lin,a Liuqing Yang,a Xi Jiang,a Guochun Li,a Tianran Zhang,a Qiaofeng Yao,a Guangyuan Wesley Zheng\\*ab and Jim Yang Lee \\*a \n\nDOI: 10.1039/c7ee01047h \n\nrsc.li/ees \n\nLithium–sulfur batteries are promising next-generation energy storage devices due to their high energy density and low material cost. Efficient conversion of lithium polysulfides to lithium sulfide (during discharge) and to sulfur (during recharge) is a performance-determining factor for lithium–sulfur batteries. Here we show that ${M O S}_{2-x}/$ reduced graphene oxide $(M\\mathrm{oS}_{2-x}/\\mathsf{r}\\mathsf{G}\\mathsf{O})$ can be used to catalyze the polysulfide reactions to improve the battery performance. It was confirmed, through microstructural characterization of the materials, that sulfur deficiencies on the surface participated in the polysulfide reactions and significantly enhanced the polysulfide conversion kinetics. The fast conversion of soluble polysulfides decreased their accumulation in the sulfur cathode and their loss from the cathode by diffusion. Hence in the presence of a small amount of $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}$ (4 wt% of the cathode mass), high rate (8C) performance of the sulfur cathode was improved from a capacity of 161.1 mA h ${\\mathfrak{g}}^{-1}$ to $826.5~\\mathsf{m A}$ h ${\\mathfrak{g}}^{-1}$ In addition, $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}$ also enhanced the cycle stability of the sulfur cathode from a capacity fade rate of $0.373\\%$ per cycle (over 150 cycles) to $0.083\\%$ per cycle (over 600 cycles) at a typical 0.5C rate. These results provide direct experimental evidence for the catalytic role of $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}$ in promoting the polysulfide conversion kinetics in the sulfur cathode. \n\n# Broader context \n\nAmong the alternatives proposed to succeed lithium-ion batteries, lithium–sulfur batteries have drawn the most interest because of the very high theoretical capacity of the sulfur cathode (about $1672\\mathrm{\\mA}\\mathrm{~h~g^{-1}~}$ . In addition, sulfur also has the benefits of being low cost, naturally abundant and environmentally benign. The development of lithium–sulfur batteries is however met with several technical challenges. The insulating properties of sulfur and its discharge products $\\mathrm{Li}_{2}\\mathrm{S}_{2}$ and $\\mathrm{Li}_{2}\\mathrm{S}$ ) resulted in a slow discharge/charge process and a low practical capacity. The intermediate products formed during battery discharge and charge, i.e. lithium polysulfides $\\left(\\operatorname{Li}_{2}\\mathbf{S}_{n}\\right.$ , where $3\\leq n\\leq8$ ), are electrolyte soluble. The loss of sulfur electrochemically as dissolved lithium polysulfides is the cause of rapid capacity fading during cycling. This article reports the development of an electrocatalyst, $\\ensuremath{\\mathbf{MoS}}_{2-x}/$ reduced graphene oxide $\\left(\\mathbf{MoS}_{2-x}/\\mathbf{rGO}\\right)$ , which can accelerate the kinetics of polysulfide conversion reactions to insoluble products. Sulfur deficiencies in the $\\mathbf{MoS}_{2}$ nanoflakes were found to be the catalytic centers. The fast conversion of soluble polysulfides can lower their accumulation in the cathode, and hence their effusion from the electrode. Consequently lithium–sulfur batteries using this catalyst in the sulfur cathode could increase the battery rate performance and cycle stability. \n\n# Introduction \n\nAmong the next-generation rechargeable batteries proposed to succeed lithium-ion batteries, lithium–sulfur batteries have drawn the most interest because of the high theoretical capacity of the sulfur cathode $\\left(1672\\mathrm{\\mA}\\mathrm{h}\\mathrm{g}^{-1}\\right.$ , about 10 times of that of a typical lithium-ion battery cathode).1–4 Sulfur also has the advantages of low cost, natural abundance and environmental benignity. The development of lithium–sulfur batteries is however met with several technical challenges. The insulating properties of sulfur and its discharge products $(\\mathrm{Li}_{2}\\mathrm{S}_{2}$ and $\\mathrm{Li}_{2}\\mathrm{S}$ result in a slow discharge/charge process and a low practical capacity. The intermediate products formed during battery discharge and charge, i.e. lithium polysulfides $(\\mathrm{Li}_{2}\\mathrm{S}_{n},$ where $3~\\le~n~\\le~8\\rangle$ , are electrolyte soluble and as such can migrate to the lithium metal anode and deposit there.5,6 The loss of electrochemically active lithium polysulfides leads to a rapid capacity fading during cycling. \n\nThe strategies developed to date to address these challenges consist mostly of the following: (i) new cathode designs to increase the electrode conductivity and polysulfide retention,7–10 (ii) new electrolyte formulations,11,12 separator structure13–15 and binder chemistry16,17 to minimize polysulfide migration, and (iii) surface engineering of the lithium metal anode to protect against passivation by the lithium polysulfides migrating from the cathode.18–20 Although substantial progress has been made, these strategies are still far from realizing the full potential of the lithium–sulfur batteries. \n\nSome recent research has considered the alternative of improving the kinetics of polysulfide conversion in the sulfur cathode.21–23 During battery discharge and charge, the conversion between sulfur and its end products $(\\mathrm{Li}_{2}\\mathrm{S}_{2}$ and $\\mathrm{Li}_{2}\\mathrm{S}$ ) has to occur via lithium polysulfides as the intermediate products which are soluble in most lithium–sulfur battery electrolytes used today.24 Since sulfur, $\\mathrm{Li}_{2}\\mathrm{S}_{2}$ and $\\mathrm{Li}_{2}\\mathrm{S}$ are insoluble, accelerating the rates of conversion of soluble lithium polysulfides (to S, $\\mathrm{Li}_{2}\\mathrm{S}_{2}$ or $\\mathrm{Li}_{2}\\mathrm{S}$ ) can reduce the presence of polysulfides in the electrolyte, and hence their impact on the battery performance. This could improve both the sulfur utilization and the battery cycle stability. Although the use of polar compounds such as Magne´li phase $\\mathrm{Ti}_{4}\\mathrm{O}_{7}$ $\\left(2\\times10^{3}\\mathrm{~S~cm}^{-1}\\right)$ ,23 metal-like TiC $(10^{4}\\ \\mathrm{S\\cm^{-1}})^{25}$ and $\\mathbf{CoS}_{2}$ $(6.7\\ \\times\\ 10^{3}\\ \\mathrm{~S~cm}^{-1})^{22}$ as conductive sulfur hosts with good polarity for polysulfide adsorption has been known for some time, the use of platinum, nickel21 and cobalt26 as the ‘‘catalysts’’ for polysulfide conversion is a relatively recent development. As such the catalysis of polysulfide conversion is still in an early phase of research. \n\nIn the search for catalysts which can provide good performance at low cost, we discovered $\\mathbf{MoS}_{2}$ to be a strong candidate. $\\mathbf{MoS}_{2}$ has been shown to be highly effective for the catalysis of several industrially important reactions such as the hydrogen evolution reaction (HER), the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER). $^{27-30}\\mathrm{~MoS}_{2}$ with sulfur deficiencies, in particular, has drawn the most research interest because of the high electrochemical activity associated with the presence of sulfur deficiencies.31,32 Indeed, our previous work on using $\\mathbf{MoS}_{2}$ as the lithium-ion battery anode has revealed some behavior of the lithium–sulfur batteries, but without the issues of low sulfur conductivity and polysulfide shuttle in discharge and charge.33 Deficiencies such as $\\mathbf{MoS}_{2}$ edge sites and terrace surfaces have shown good electrochemical activity for $\\mathrm{Li}_{2}\\mathrm{S}$ deposition.34 Herein, rGO decorated with few-layer $\\mathbf{MoS}_{2}$ nanoflakes with a controlled amount of sulfur deficiency $\\left(\\mathbf{MoS}_{2-x}/\\mathbf{rGO}\\right)$ was used to catalyze the polysulfide conversion in a sulfur cathode. The $\\mathbf{MoS}_{2}$ nanoflakes were prepared by the sonication assisted liquid phase exfoliation of commercial $\\mathbf{MoS}_{2}$ powder in $N_{\\mathbf{\\lambda}}$ -methyl-2-pyrrolidone (NMP). The amount of sulfur deficiencies could be varied by changing the time and temperature in a heat treatment in hydrogen. The experimental results confirmed the involvement of surface sulfur deficiencies in the polysulfide conversion reactions and their catalytic effect on the kinetics of polysulfide conversion. In the presence of a small amount $(4~\\mathrm{wt\\%})$ of the cathode mass) of $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{r}}\\ensuremath{\\mathbf{GO}}$ in the sulfur cathode, the sulfur cathode exhibited both high-rate capability (capacity of $826.5\\ \\mathrm{mA}\\ \\mathrm{h}\\ \\mathrm{g}^{-1}$ at an 8C rate) and good cycle stability (capacity fade rate of $0.083\\%$ per cycle for 600 cycles at a 0.5C rate). These performances place $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ as one of the best (if not the best) polysulfide conversion catalysts reported to date. \n\n# Experimental section \n\n# Chemicals \n\nN-Methyl-2-pyrrolidone (NMP, $99.5\\mathrm{wt\\%}\\$ , polyvinylidene fluoride (PVDF, $99.5~\\mathrm{wt\\%})$ , sulfur $\\left(99.5~\\mathrm{{\\wt\\%}}\\right)$ , lithium sulfide $(\\mathrm{Li}_{2}S$ $99.98~\\mathrm{wt\\%}$ , 1,3-dioxolane $\\mathrm{(DOL,99.8~wt\\%}$ , 1,2-dimethoxyethane (DME, $99.5~\\mathrm{wt\\%}^{\\cdot}$ , molybdenum(VI) oxide $\\left(\\mathbf{MoO}_{3},99.5\\%\\right)$ , lithium bis(trifluoromethanesulfonyl) imide (LiTFSI, $99.95~\\mathrm{wt\\%}$ and lithium nitrate $\\left(\\mathrm{LiNO}_{3}\\right.$ , $99.99\\mathrm{wt\\%}$ from Sigma Aldrich; molybdenum(IV) sulfide $(\\mathbf{MoS}_{2}$ , $99\\mathrm{wt\\%}$ from Alfa Aesar; and Super-P carbon $\\mathrm{(99.5~wt\\%~}$ ) from Timcal were used as received. \n\n# Preparation of $\\mathbf{MoS}_{2}$ nanoflakes and $\\mathbf{MoS}_{2}/\\mathbf{GO}$ composite \n\nFew-layer $\\mathbf{MoS}_{2}$ nanoflakes were prepared by the sonicationassisted exfoliation of commercial $\\mathbf{MoS}_{2}$ powder in NMP.35 In brief, $100{\\mathrm{~mg~MoS}}_{2}$ powder was dispersed in $20~\\mathrm{mL}$ NMP, and sonicated for 5 hours under ambient conditions. After centrifugation at $10000~\\mathrm{rpm}$ for 5 minutes, the supernatant containing the $\\mathbf{MoS}_{2}$ nanoflakes was diluted with $30~\\mathrm{mL}$ water to form the $\\mathbf{MoS}_{2}$ stock solution. A graphene oxide (GO) sample prepared using a modified Hummer’s method36 was added to this solution and sonically homogenized for 10 minutes. The composite formed as such $\\left({\\bf M o S}_{2}/{\\bf G O}\\right)$ was recovered by vacuum filtration. \n\n# Preparation of $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ and $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ composites \n\n$\\mathbf{MoS}_{2}$ nanoflakes with sulfur deficiencies (sulfur-deficient $\\mathbf{MoS}_{2}$ nanoflakes) were formed by heating the $\\mathbf{MoS}_{2}/\\mathbf{GO}$ composite prepared above in a $10\\%\\mathrm{H}_{2}/\\mathrm{Ar}$ mixture. Different combinations of reaction temperature and time were used for the preparation. A $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ composite without the sulfur deficiencies was also prepared for performance comparison. Here the rGO was separately prepared by heating a GO sample in a $10\\%$ $\\mathbf{H}_{2}/\\mathbf{Ar}$ atmosphere at $600^{\\circ}\\mathrm{C}$ for 6 hours. The rGO was dispersed into the $\\mathbf{MoS}_{2}$ stock solution to a $\\mathbf{rGO/MoS}_{2}$ mass ratio of 8 : 2 (the same ratio as that of rGO to $\\mathbf{MoS}_{2-x}$ in $\\mathbf{MoS}_{2-x}/\\mathbf{r}\\mathbf{GO})$ , and sonically homogenized for 5 hours. The $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ composite was then recovered by vacuum filtration. \n\n# Preparation of rGO/S, $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ and $\\mathbf{MoS}_{2-x}/\\mathbf{rGO}/\\mathbf{S}$ composites \n\n$\\mathbf{r}\\mathbf{GO}/\\mathbf{S}$ , $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ and $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ composites (the actual cathode materials for the lithium–sulfur test batteries) were prepared by the conventional melt-diffusion method. In brief sulfur powder and rGO (or $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{r}}\\ensuremath{\\mathbf{GO}}$ or $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}]$ in a 75 : 25 mass ratio were homogenized by grinding; and then sealed in a vial with Ar. The mixture was then heated at $155~^{\\circ}\\mathrm{C}$ for 5 hours to distribute the sulfur uniformly in rGO (or in $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ or $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}})$ . \n\n# Materials characterization \n\nThe morphology of the composites in this study was examined by field emission scanning electron microscopy (FESEM) on a JEOL JSM-6700F SEM, by transmission electron microscopy (TEM) on a JEOL 2100F microscope, and by high-resolution TEM (HRTEM) on a JEOL 2100F system. The composite crystal structures were determined by X-ray diffraction (XRD) on a BRUKER D8 ADVANCE (Germany) instrument using Cu $\\mathbf{K}_{\\alpha}$ radiation. X-ray photoelectron spectroscopy (XPS) analysis of the samples was performed on a Kratos AXIS Ultra DLD surface analyzer using a monochromatic Al $\\mathbf{K}_{\\alpha}$ radiation source at $15\\mathrm{kV}$ (1486.71 eV). The XPS peak locations were corrected by referencing the C 1s peak of adventitious carbon to $284.5\\ \\mathrm{eV}$ . Spectral deconvolution was carried out using the XPS Peak 4.1 software. The rGO and sulfur contents of the composites were analyzed by thermogravimetry (TGA) on a Shimadzu DTG-60H analyzer in air (for the measurement of the rGO content) or in $\\ensuremath{\\mathbf{N}}_{2}$ (for the measurement of the sulfur content) at a temperature ramp rate of $10\\ ^{\\circ}{\\bf C}\\ \\operatorname*{min}^{-1}$ . \n\n# Adsorption properties of lithium polysulfides \n\n$\\mathrm{Li}_{2}\\mathrm{S}$ and sulfur in amounts corresponding to the nominal stoichiometry of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ were added to a 1 : 1 (v/v) DOL/DME mixture and stirred overnight at $60~^{\\circ}\\mathbf{C}.$ The concentration of the $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ solution prepared as such was $3\\mathrm{\\mmol\\L}^{-1}$ , and was used as the stock solution for adsorption measurements. $10\\mathrm{mg}\\mathrm{rGO}_{\\mathrm{i}}$ $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ or $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ was added to $2~\\mathrm{mL}$ each of the lithium polysulfide stock solution. The mixtures were vigorously stirred to facilitate adsorption. \n\n# Cell assembly and electrochemical measurements \n\nSymmetric electrochemical cells were assembled by the following procedure: $80~\\mathrm{wt\\%}$ active material $\\mathrm{(MoS}_{2-x}/\\mathrm{rGO}$ , $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ , or rGO) and $20\\mathrm{wt\\%}$ PVDF binder were homogenized in NMP to form a consistent slurry, which was then uniformly applied to an Al foil. The foil was cut into $1\\mathrm{cm}\\times1$ cm sheets. The active material loadings on the sheets were about $2{-}4~\\mathrm{mg}$ . CR2025 coin cells were assembled in an Ar-filled M Braun glove box by using two coated Al sheets as the cathode and anode, a Celgard 2400 separator, and ${\\ 50\\ \\upmu\\mathrm{L}}$ electrolyte of $^{1\\mathrm{~M~}}$ LiTFSI and $0.2\\textbf{M}$ $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ in a 1 : 1 (v/v) DOL/DME mixture. The counter electrode after the test was disassembled from the cell, rinsed with DOL thrice to remove the lithium salt on the surface; and then evacuated overnight at room temperature for ex situ analysis on the next day. Lithium–sulfur test batteries were assembled by a slightly different procedure: an NMP slurry of $80\\ \\mathrm{wt\\%}$ active material $\\mathrm{(MoS}_{2-x}/\\mathrm{r}\\mathrm{GO}/\\mathrm{S}$ , $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ or rGO/S), $10\\mathrm{wt\\%}$ Super P and $10~\\mathrm{wt\\%}$ PVDF was applied onto an Al foil to a loading of $\\sim1.5\\mathrm{mg}\\mathrm{cm}^{-2}$ . CR2025 coin cells were assembled using the coated Al foil as the cathode, a lithium metal foil anode, a Celgard 2400 separator, and $50~{\\upmu\\mathrm{L}}\\ 1~\\mathrm{M}$ LiTFSI and $2\\mathrm{wt}\\%\\mathrm{LiNO}_{3}$ solution in DOL/DME $\\left(1:1\\ \\mathbf{v}/\\mathbf{v}\\right)$ as the electrolyte. A Neware battery tester was used to regulate the cell discharge and charge. The cathode specific capacities were normalized only by the mass of sulfur, as per the common practice. Cyclic voltammetry (CV) \n\nand electrochemical impedance measurements were carried out on an Autolab type III electrochemical workstation. \n\n# Results and discussion \n\nFig. 1A shows the major steps in the preparation of $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ The $\\mathbf{MoS}_{2}$ nanoflakes and GO (Fig. 1B) were co-dispersed in water; and then the mixed solid phase recovered by filtration was heated in a reducing hydrogen atmosphere at high temperature. The nanocomposite formed as such consisted of $\\mathbf{MoS}_{2-x}$ nanoflakes on a thin film of rGO. rGO, a common substrate for electrochemical devices,37–39 was used here as a flexible and conductive catalyst support. Fig. 1C is the TEM image of the $\\mathbf{MoS}_{2}$ nanoflakes formed by the liquid phase exfoliation of bulk commercial $\\mathbf{MoS}_{2}$ particles shown in Fig. S1 $\\bigl(\\mathrm{ESI\\dag}\\bigr)$ . $\\mathbf{MoS}_{2}$ could be exfoliated into nanoflakes very easily by this procedure and formed a uniform dispersion in the solvent (Fig. S2, $\\mathrm{ESI\\dag}$ ). The HRTEM image in Fig. 1D shows the layer-like structure of the $\\mathbf{MoS}_{2}$ nanoflakes, which were about $3{\\mathrm{-}}5{\\mathrm{nm}}$ in thickness and consisted of 6–8 layers. The lattice spacing of $0.62\\ \\mathrm{nm}$ matches well with the (002) diffraction of hexagonal $\\mathbf{MoS}_{2}$ .40 The small $\\mathbf{MoS}_{2}$ nanoflakes were well dispersed on the rGO sheets. The high temperature treatment in hydrogen removed some sulfur atoms in the $\\mathbf{MoS}_{2}$ nanosheets to result in the formation of sulfur deficiencies. The geometric compatibility between the two 2D nanomaterials (rGO and $\\mathbf{MoS}_{2}$ nanosheets) should improve the quality of the interfacial contact, and the 2D-on-2D construction also allowed a good exposure of the sulfur deficiencies on the catalyst surface for the conversion of adsorbed polysulfides. \n\nThe effects of heat treatment temperature and time on the structure of the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ composite were analyzed by XRD and XPS. The XRD patterns of samples prepared under different conditions are quite similar (Fig. 2A). The broad diffraction at around $2\\theta=20{-}30^{\\circ}$ can be attributed to the disorderly stacked rGO sheets. The diffraction peaks of the $\\mathbf{MoS}_{2}$ nanoflakes are in good agreement with the 2H phase of $\\mathbf{MoS}_{2}$ (PDF#37-1492),41 and hence the phase purity of $\\mathbf{MoS}_{2}$ was good. The most intense $\\mathbf{MoS}_{2}$ peak was the (002) peak at $2\\theta\\sim15^{\\circ}$ , suggesting [001] as the crystal growth direction. Fig. 2B shows the expanded view of the $\\mathbf{MoS}_{2}$ (002) peak. There was a slight shift of this peak to lower $2\\theta$ values with the increase in treatment severity (higher temperature or longer heat treatment time). The shift indicates an increase in the lattice parameter42 caused most likely by the removal of sulfur by hydrogen. The resultant reduction of Mo to a lower oxidation state with a larger atomic radius led to the increase in the lattice parameter. \n\nThe surface compositions of $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ composites prepared under different heat treatment conditions were characterized by XPS. The total molybdenum (Mo) and sulfur (S) contents of the samples as analyzed by XPS are summarized in Table S1 $\\left(\\mathrm{ESI\\dag}\\right)$ . The $\\mathbf{Mo}{:}S$ ratio of the as-synthesized $\\mathbf{MoS}_{2}$ nanoflakes was $33.2:65.4$ , close to the $_{1:2}$ ratio in stoichiometric $\\mathbf{MoS}_{2}$ . The $\\mathbf{Mo}{:}S$ ratio increased with the increase in reaction temperature and reaction time; indicating the progressive removal of the sulfur element. The Mo 3d spectra were deconvoluted to determine the stoichiometric $\\mathbf{MoS}_{2}$ (red), the sulfur-deficient $\\mathbf{MoS}_{2}$ (blue) and the $\\mathbf{MoO}_{3}$ (green) contents of various samples (Fig. 2C).43,44 Specifically the Mo $3\\mathrm{d}_{5/2}$ and $3\\mathrm{d}_{3/2}$ doublets at ${\\sim}229.5\\ \\mathrm{eV}$ and $232.5\\ \\mathrm{eV}$ were deconvoluted into two sets of peaks. The first set of peaks with binding energies of $232.6{\\mathrm{~eV}}$ and $229.5\\ \\mathrm{eV}$ could be attributed to stoichiometric $\\mathbf{MoS}_{2}$ , while the second set at lower binding energies ( $232.2\\:\\mathrm{eV}$ and 229.1 eV) could be assigned to sulfur-deficient $\\mathbf{MoS}_{2}$ . The peak distinctively upstream of the $\\mathbf{MoS}_{2}$ peaks may be attributed to $\\mathbf{MoO}_{3}$ (green).44 The appearance of $\\mathbf{MoO}_{3}$ could be attributed to the oxidation of some low oxidation state Mo atoms in $\\mathbf{MoS}_{2}$ , as per the previous report.35 The results showed that the increase in temperature and reaction time increased the amount of sulfur deficiency. The presence of $\\mathbf{MoO}_{3}$ in the $700~^{\\circ}\\mathrm{C}$ sample could be due to the oxidation of Mo metal clusters (which is highly susceptible to atmospheric oxidation). Thermal annealing of $\\mathbf{MoS}_{2}$ in a hydrogen environment could lead to the removal of sulfur atoms as $\\mathrm{H}_{2}\\mathrm{S}$ gas and hence the formation of sulfur deficiencies. The excess Mo could also form Mo metal clusters.59 The Mo metal clusters were oxidized to $\\mathbf{MoO}_{3}$ after the sample was removed from the heating chamber. $\\mathbf{MoO}_{3}$ could also be formed directly by the substitution of sulfur in $\\mathbf{MoS}_{2}$ with oxygen from GO during the heat treatment. Although the $700^{\\circ}\\mathrm{C}$ sample contained a high sulfur deficiency content, the deep reduction of $\\mathbf{MoS}_{2}$ led to an unstable nanoflake structure (Fig. S3, ESI†) caused by the excessive expansion of the lattice parameter. The $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{r}}\\ensuremath{\\mathbf{GO}}$ composite with the highest sulfur deficiency content which could still preserve the nanoflake structure was prepared at $600~^{\\circ}\\mathrm{C}$ for 6 hours $\\left(x=0.42\\right)$ . \n\n![](images/4248976533c03d3522488bd46602dd1a8dffd3b587098dfdaca66f175ed04b26.jpg) \nFig. 1 (A) Schematic of the synthesis of the $M\\mathrm{oS}_{2-x}/\\mathrm{rGO}$ composite and the conversion of ${\\mathsf{L i}}_{2}{\\mathsf{S}}_{x}$ on the $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}$ surface. TEM images of (B) a thin GO film and (C) $M\\circ\\mathsf{S}_{2}$ nanoflakes. (D) HRTEM image of $M\\circ\\mathsf{S}_{2}$ nanoflakes. \n\nThe morphology of the stable high sulfur-deficiency $\\mathrm{MoS}_{2-x}/\\$ rGO composite (prepared at $600~^{\\circ}\\mathrm{C}$ for 6 hours) was examined by both FESEM and TEM. The FESEM image in Fig. 3A shows that the composite mirrored the laminate structure of rGO synthesized under the same conditions (Fig. S4A, ESI†). TEM images (Fig. 3B and C) confirm the presence of $\\mathbf{MoS}_{2-x}$ nanoflakes on the rGO sheets. The $0.62\\mathrm{nm}$ lattice spacing in the HRTEM image of a $\\mathbf{MoS}_{2-x}$ nanoflake sample (Fig. 3D) is the same as that of the (002) planes of hexagonal $\\mathbf{MoS}_{2}$ in Fig. 1D, indicating that the sulfur deficiencies did not alter the native $\\mathbf{MoS}_{2}$ structure. The rGO content in the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ composite as calculated by TGA (Fig. S5, ESI†) was about $78~\\mathrm{wt\\%}$ . For comparison, a composite containing $\\mathbf{MoS}_{2}$ and rGO (reduced from GO by heating in hydrogen at $600~^{\\circ}\\mathrm{C}$ for 6 hours), $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ was also analyzed. The rGO content in the latter was similar, $77\\ \\mathrm{wt\\%}$ . TGA nonetheless detected higher thermal stability for rGO in $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ to suggest the stronger interaction between rGO and $\\mathbf{MoS}_{2}$ when the latter was sulfur deficient. Since sulfur deficiencies can render the $\\mathbf{MoS}_{2-x}$ surface more electron rich,45 and rGO formed below $600~^{\\circ}\\mathrm{C}$ has general p-type characteristics,46 electron transfer from rGO to $\\mathbf{MoS}_{2-x}$ may occur to develop a stronger bond between the two at their interface.47 Such electron coupling is expected to contribute positively to the charge transfer at the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ interface. \n\n![](images/49ca8c87609a4b1b19ac78907c56cfc646fb7875131a60c450b6b638df972026.jpg) \nFig. 2 (A and B) XRD patterns and (C) Mo 3d XPS spectra of $M O S_{2}$ nanoflakes and $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}$ composites formed by different combinations of reactio temperature and time in a hydrogen atmosphere. \n\n![](images/65b62e0063678b447f6ffaf775f3ee184bc248c1352f0793c91c012c7fa5d076.jpg) \nFig. 3 (A) FESEM image, (B and C) TEM images and (D) HRTEM image of the $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}$ composite prepared by heating $M O S_{2}/G O$ in a hydrogen atmosphere at $600^{\\circ}\\mathsf C$ for 6 hours. \n\nThe catalytic effect of $\\ensuremath{\\mathbf{MoS}}_{2-x}$ on the polysulfide redox reactions was first revealed by CV in symmetric cells with identical working and counter electrodes in a $0.2\\ensuremath{\\mathrm{~M~}}\\ensuremath{\\mathrm{Li}_{2}}\\ensuremath{\\mathrm{S}}_{6}$ electrolyte (Fig. 4A). $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ and rGO prepared under the same conditions were used as the experimental controls (Fig. 4B and C). The CV of a $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ -free electrolyte was also measured to correct for capacitive contributions. The voltammogram of the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ electrode in the $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ electrolyte exhibited high reversibility with four distinct peaks at $-0.047\\mathrm{~V~}_{;}$ $-0.39\\mathrm{~V~}$ , 0.047 V and $0.39{\\mathrm{~V~}}$ respectively (Fig. 4A). The $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ electrode exhibited remnants of these peaks as broad redox features at $-0.31\\mathrm{V},-0.61\\mathrm{V},0.31\\mathrm{V}$ and $_{0.61\\mathrm{\\:V}}$ (Fig. 4B). For the rGO electrode, only a very drawn-out reduction peak at $-1.22\\mathrm{V}$ and a very drawn-out oxidation peak at $1.22{\\mathrm{~V~}}$ were detected (Fig. 4C). \n\n![](images/2de345e5d7da2cf292c4741e1d741b674c9b979bed3a3241f6ddfa2fe3ba63fb.jpg) \nFig. 4 Cyclic voltammograms of symmetric cells with identical electrodes of (A) $\\mathsf{M o S}_{2-x}/\\mathsf{r G O},$ (B) $M\\circ\\mathsf{S}_{2}/\\mathsf{r G O}$ and $(\\mathsf{C})$ rGO in electrolytes with and without $0.2\\ M\\ L i_{2}\\mathsf{S}_{6}$ at $3\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . (D) Multi-cycle voltammograms of the $M\\cup\\mathsf{S}_{2-x}/\\mathsf{r G O}$ symmetric cell at $\\mathsf{3}\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . (E) Electrochemical impedance spectra of the symmetric cells. (F) Voltammograms of the $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}$ symmetric cell at different scan rates. \n\nFig. 4D shows the first five cycles of the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ electrode in CV. The nearly perfect superimposition of the peaks suggests good stability of the sulfur-deficient $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ electrode. In the first cathodic scan from zero potential between the electrodes, only the peak at $-0.39{\\mathrm{V}}$ (peak a) appeared. The cathodic peak at $-0.047\\mathrm{~V~}$ (peak d) emerged only from the second scan onwards. Since $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ was the only electrochemically active species in the electrolyte, it is reasonable to assume that $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ was reduced to $\\mathrm{Li}_{2}\\mathrm{S}$ (or $\\mathrm{Li}_{2}\\mathrm{S}_{2}$ ) on the working electrode, and oxidized to sulfur on the counter electrode in the cathodic scan. Hence the reduction of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ on the working electrode which manifested in peak a was complemented by the oxidation of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ on the counter electrode. Peak b in the following anodic scan was due to the reconstitution of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ by the oxidation of $\\mathrm{Li}_{2}\\mathrm{S}$ (or $\\mathrm{Li}_{2}\\mathrm{S}_{2}$ ) on the working electrode. Similarly, peaks c and d identical in shape to peaks a and b were due to the oxidation of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ to sulfur, and the reduction of sulfur to $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ on the working electrode respectively. Therefore, the peaks at $-0.39\\mathrm{~V}/0.047\\mathrm{~V~}$ and $-0.047\\mathrm{~V}/0.39\\mathrm{~V}\\ddagger$ were paired redox features of the symmetric cell. The reactions are summarized in Fig. S6 $\\bigl(\\mathrm{ESI\\dag}\\bigr)$ . The sharpness of the peaks and the narrow peak separation in each redox pair indicate good electrochemical reversibility and facile polysulfide conversion. It should be mentioned that the two paired redox peaks related to the $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ conversion reaction were absent in a previous study on $\\mathbf{CoS}_{2}$ using the symmetric cell.22 The high scan rate $\\mathbf{\\left(50\\mVs^{-1}\\right)}$ and the narrow voltage range (from $-0.7\\:\\mathrm{V}$ to $0.7\\mathrm{V}$ ) used in that study could have suppressed the detectability of these redox features. When the electrodes were $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ without the surface sulfur deficiencies, the broadened peaks and the increased peak separation are indications of reduced electrochemical reversibility and slower reactions (Fig. 4B). $\\S$ Electrochemical reversibility and conversion kinetics were the lowest with the rGO electrodes, resulting in the merging of peaks (Fig. 4C). \n\n![](images/7dd55159aaec12057bf6446bf812eec99da3044f3441c6d5a0aa8fdf9224452f.jpg) \nFig. 5 FESEM images of (A) the pristine rGO electrode and (B and C) the rGO counter electrode removed from the symmetric cell after scanning to $-1.4\\mathsf{V};$ (D) the pristine $M\\cup\\mathsf{S}_{2-x}/{\\mathsf{r G O}}$ electrode and (E and F) the $M\\cup S_{2-x}/\\Upsilon\\mathsf{G O}$ counter electrode after scanning to $-1.4\\mathsf{V}.$ XPS spectra of $(G)$ the rGO and (H and I) $M\\cup\\mathsf{S}_{2-x}/\\mathsf{r G O}$ counter electrodes of symmetric cells after scanning to $-1.4\\ V,$ or after scanning to $-1.4\\ V$ and returning to $0\\vee$ \n\nThe polarity-induced adsorption between the polysulfides and a polar sulfide surface may have contributed to the more facile kinetics of polysulfide conversion on $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ and $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ (the apolar rGO surface is antagonistic to polysulfide adsorption).48 This was demonstrated by a simple visual adsorption test (Fig. S8, $\\mathrm{ESI\\dag}$ ) where the adsorption of $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ on $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ and $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ completely decolorized the polysulfide solution. Electrochemical impedance spectroscopy (Fig. 4E) also registered the smallest charge transfer resistance (the size of the high frequency semicircle in the Nyquist plot) for the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ symmetric cell. In the CVs measured at different scan rates (Fig. 4F), there were some slight shifts of the redox peaks with the increase in the scan rate. However, the peak separation in the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ cell at a high scan rate of $9\\mathrm{mV}\\mathrm{s}^{-1}$ was still significantly narrower than the peak separations in the $\\mathbf{MoS}_{2}/\\mathbf{rGO}$ or rGO cells at $3\\mathrm{mVs}^{-1}$ . All the above are evidence for the greatly enhanced kinetics of polysulfide conversion on the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ surface. \n\nFor additional insights into the reactions of polysulfides on the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ surface, the counter electrodes of symmetric cells with $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ or rGO electrodes after scanning from $_{0\\mathrm{~V~}}$ to $-1.4\\mathrm{~V~}$ were examined by FESEM. $\\P$ Fig. 5 shows the FESEM images of the rGO (A–C) and the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ (D–F) counter electrodes before and after scanning to $-1.4\\mathrm{V}.$ . The larger number of sulfur particles and their more uniform distribution on the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ surface could only come from the presence of more electrochemically active sites for polysulfide conversion. XPS was also used to analyze the surfaces of the counter electrodes of symmetric cells after scanning from 0 to $-0.14\\mathrm{~V~}$ , and from $-0.14\\mathrm{\\DeltaV}$ to $_{0\\mathrm{~V~}}$ . Fig. 5G and H show, respectively, the S 2p XPS spectra of the rGO and $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ counter electrodes. The $163.5\\ \\mathrm{eV}$ and 164.7 eV peaks could be attributed to the sulfur deposited on the counter electrodes, while the very prominent peak at ${\\sim}169\\ \\mathrm{eV}$ to the S–O bond in oxidized sulfur species such as $-S\\mathbf{O}_{x}$ .21 Since sulfur deposition on the counter electrode was mostly completed when the symmetric cells were scanned to $-0.39\\mathrm{~V~}$ (Fig. 4D), the sulfur deposit would be extensively oxidized when the cells were scanned to $-1.4{\\mathrm{~V}}.$ . The stronger S–O peak from the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{r}}\\ensuremath{\\mathbf{GO}}$ cell can then be used as an indirect evidence for more sulfur formation in this cell (Fig. 5G and H). When this symmetric cell was returned to $_{0\\mathrm{~V~}}$ from $-1.4\\mathrm{~V~}$ , the decrease in the S–O peak intensity was caused by the electrochemical reduction of the oxidized sulfur species on the counter electrode. In contrast, the S–O peak from the rGO symmetric cell underwent very minor intensity changes from $-1.4\\:\\mathrm{V}$ to $_{0\\mathrm{{V}}}$ , an indication of the limited sulfur presence on the rGO surface. The more extensive sulfur formation and reduction reactions in the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ cell could only be caused by the existence of catalytically more active sites on the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{r}}\\ensuremath{\\mathbf{GO}}$ surface. There was also evidence in the Mo 3d XPS spectra for the interaction between $\\ensuremath{\\mathbf{MoS}}_{2-x}$ and polysulfides during the polysulfide conversion reactions (Fig. 5I). When the symmetric cells were scanned to $-1.4\\mathrm{V}$ the sulfur-deficient $\\mathbf{MoS}_{2}$ component (blue curve) in $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ was significantly diminished in intensity. It is believed that the deficiencies in $\\mathbf{MoS}_{2-x}$ rendered the surface of $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ electron-rich. The XPS results of Fig. 5I indicate a weaker XPS signal from the sulfur deficiencies after sulfur deposition, suggesting the electron transfer from the former to the latter.43,49,50 It has been reported in the oxygen reduction reaction (ORR) research that oxygen adsorption on an oxygendeficient surface would elongate the $_{0-0}$ bond for an easier reduction.56 The sulfur deficiencies on the $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ surface may likewise facilitate the reduction of sulfur to polysulfides, probably through the involvement of some metastable $\\mathbf{S}_{x}\\mathbf{\\bullet}^{-}$ species.57,58 When the symmetric cell was scanned back to $0\\mathrm{v}$ XPS showed that the sulfur deficiencies were restored, and hence the reversibility of the overall process. These changes establish the correspondence between sulfur deficiency and the extent and reversibility of polysulfide conversion, and provide indirect proof for sulfur deficiencies as the origin of enhanced catalytic activity in polysulfide electrochemical reactions. \n\nThe actual performance of $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{rGO}}$ as a catalyst in lithium– sulfur batteries was evaluated in coin cells using a $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ composite cathode and a lithium metal anode. Coin cells with a $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ or $\\mathbf{r}\\mathbf{GO}/\\mathbf{S}$ cathode were also assembled for comparison. The sulfur contents in the composites as assayed by TGA were about $75\\ \\mathrm{wt\\%}$ (Fig. S9, ESI†). Fig. 6A shows the typical voltammograms and the galvanostatic discharge–charge voltage profile of the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ cathodes between 1.8 and $2.6{\\mathrm{~V}}.$ Since lithiation of $\\mathbf{MoS}_{2}$ occurs below 1.5 V vs. $\\mathrm{Li/Li^{+}}$ , the $\\mathbf{MoS}_{2}$ nanoflakes would not have contributed to any capacity in the $1.8\\substack{-2.6\\mathrm{~V~}}$ voltage range.51 The two cathodic peaks at about $2.3\\mathrm{V}$ and $2.0\\mathrm{V}$ could be associated with the reduction of sulfur to soluble long-chain lithium polysulfides $\\left(\\mathrm{Li}_{2}\\mathrm{S}_{x},4\\le x\\le8\\right)$ , and the subsequent conversion of the latter to insoluble short-chain polysulfides $\\left(\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S\\right)$ respectively. The two peaks in the reverse anodic scan at about $2.3\\mathrm{\\:V}$ and $2.4\\:\\mathrm{V}$ represent the reverse reactions of the conversion of short-chain polysulfides to sulfur.52,53 The two distinct discharge voltage plateaus (at ${\\sim}2.34\\mathrm{V}$ and 2.12 V) at the 0.5C rate could be attributed to the conversion of sulfur to long-chain lithium polysulfides, and the formation of $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ from the latter. The reverse of these reactions occurred during charge to form two corresponding voltage plateaus at ${\\sim}2.23\\ \\mathrm{V}$ and $2.35{\\mathrm{~V~}}$ respectively. The galvanostatic discharge and charge curves are therefore in agreement with the voltammograms.54,55 The generally intense peaks on $\\mathrm{MoS}_{2-x}/\\$ $\\mathbf{r}\\mathbf{GO}/\\mathbf{S}$ indicate the great extent of the polysulfide conversion due to the fast electrode kinetics. \n\nFig. 6B compares the electrochemical performance of the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ , $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ and rGO/S cathodes at different C-rates $\\mathrm{from}\\ 0.2\\mathrm{C}$ to 8C; $1\\mathrm{C}=1600\\ \\mathrm{mA}\\ \\mathrm{g}^{-1})$ . The first cycle discharge capacities of $\\mathbf{r}\\mathbf{GO}/\\mathbf{S}$ , $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ and $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ at the 0.2C rate were $1210.5\\mathrm{\\mA\\h\\g}^{-1}$ , $1243.2\\mathrm{\\mA}\\mathrm{\\h\\g}^{-1}$ and $1310.5\\mathrm{\\mA}$ h ${\\mathrm{g}}^{-1}$ respectively. The capacity difference deviated more at higher rates, and was $826.5\\mathrm{\\mAh\\g^{-1}}$ for $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ $(63.1\\%$ of its 0.2C capacity), $473.3\\mathrm{\\mA}$ h ${\\mathrm{g}}^{-1}$ for $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ $(38.1\\%$ of its 0.2C capacity) and $161.1\\mathrm{\\mA}$ h ${\\mathrm{g}}^{-1}$ for $\\mathbf{r}\\mathbf{GO}/\\mathbf{S}$ $(13.3\\%$ of its 0.2C capacity) at the 8C rate, which was the test limit of this study. The higher affinity of $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ for polysulfide adsorption and the catalytic effect of sulfur deficiencies in $\\mathbf{MoS}_{2}$ for polysulfide conversion are expected to be the contributive factors although their respective contributions are difficult to resolve at this time. Fig. 6C shows the galvanostatic discharge and charge curves of the cells at different C-rates. An increase in the C-rate caused the charge voltage plateaus to shift positively and the discharge voltage plateaus to shift negatively. The voltage plateaus at the 8C rate were clearly visible in the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ cell, due to the more facile electrode kinetics on $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathbf{rGO}}$ . \n\n![](images/670203f406bec129a1b112cacc6e6a2d541cb0d2755df1e5a61ec9a3fb66c04e.jpg) \nFig. 6 (A) Cyclic voltammograms at $0.1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ and the representative galvanostatic discharge–charge voltage profile at 0.5C, (B) comparison of rate performance at different C-rates, $(\\mathsf{C})$ galvanostatic discharge–charge curves and (D and E) cycle stability of rGO/S, $M\\mathrm{o}{\\sf S}_{2}/\\mathrm{r}\\mathsf{G}\\mathsf{O}/\\mathsf{S}$ and $\\mathsf{M o S}_{2-x}/\\mathsf{r G O}/\\mathsf{S}$ cells in the $1.8\\substack{-2.6\\mathrm{~V~}}$ voltage range at 0.5C $\\mathtt{(1C=1600\\ m A\\ g^{-1}}$ based on the mass of sulfur). \n\nThe cyclabilities of the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ , $\\mathbf{MoS}_{2}/\\mathbf{rGO}/\\mathbf{S}$ and $\\mathbf{r}\\mathbf{GO}/\\mathbf{S}$ cathodes at the typical 0.5C rate are compared in Fig. 6D. Not only were the $\\mathbf{r}\\mathbf{GO}/\\mathbf{S}$ and $\\mathrm{MoS}_{2}/\\mathrm{rGO}/\\mathrm{S}$ cathodes lower in initial capacity (1013.3 mA h $\\mathrm{g}^{-1}$ and $1033\\mathrm{\\mA}\\mathrm{~h~}\\mathrm{~g^{-1}~}$ ), they also exhibited more severe capacity fading endings with $445.3\\mathrm{\\mA}$ h $\\mathrm{g}^{-1}$ and $576.4\\mathrm{\\mA}$ h ${\\mathrm{g}}^{-1}$ after 150 cycles. In contrast, the $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ cathode exhibited both higher discharge capacity and greater cycle stability (initial discharge capacity of $1159.9\\mathrm{mAhg}^{-1}$ and capacity of $819.9\\mathrm{\\mA}$ h ${\\mathrm{g}}^{-1}$ after 150 cycles). The long-term cycling performance of $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}/\\mathrm{S}$ at the 0.5C rate was also evaluated (Fig. 6E). After 600 cycles of continuous cycling, a discharge capacity of $628.2\\:\\mathrm{mA}\\mathrm{hg}^{-1}$ remained (a capacity fade rate of $0.083\\%$ per cycle). The Coulombic efficiency was as high as $99.6\\%$ . Cycle stability was thereof another benefit of the catalysis of polysulfide conversion in the sulfur electrode. A higher conversion rate of soluble polysulfides to insoluble sulfur products could decrease their accumulation in the cathode and consequently, their loss from the cathode by diffusion. Greater cycle stability was therefore realized by suppressing a major capacity loss mechanism. Compared to other catalysts in use today for the lithium–sulfur batteries (Table S2, ESI†), $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}$ is clearly a well-rounded choice with a strong performance in almost all functional categories. \n\n# Conclusions \n\nIn this study, we demonstrated the effectiveness of $\\ensuremath{\\mathbf{MoS}}_{2-x}/\\ensuremath{\\mathrm{r}}\\ensuremath{\\mathbf{GO}}$ as a catalyst for polysulfide conversion in a sulfur cathode. It was confirmed that the surface sulfur deficiencies participated in the polysulfide conversion and catalyzed the kinetics of polysulfide redox reactions. When a small amount of $\\mathrm{MoS}_{2-x}/\\mathrm{rGO}\\left(4\\mathrm{wt}\\%\\right)$ was added to the sulfur cathode, high-rate performance and good cycle stability of the batteries were obtained. The high rate performance could be attributed to the acceleration of the polysulfide conversion kinetics on the surface sulfur deficiencies. The fast conversion of soluble polysulfides decreased their accumulation in the sulfur cathode and inhibited their subsequent loss from the cathode by diffusion. The suppression of this loss mechanism led to a more sustained cyclability. The study here not only presented a catalyst candidate which is among the best reported to date, but it also provided experimental evidence for and some new insights into the origin of the catalytic effects. \n\n# Acknowledgements \n\nH. L. acknowledges the National University of Singapore for his research scholarship. \n\n# References \n\n1 W. Zhou, B. Guo, H. Gao and J. B. Goodenough, Adv. Energy Mater., 2016, 6, 1502059. \n2 J. Li, L. Yang, S. Yang and J. Y. Lee, Adv. Energy Mater., 2015, 5, 1501808. 3 J. Zhang, H. Hu, Z. Li and X. W. Lou, Angew. Chem., Int. Ed., 2016, 55, 3982–3986. 4 M. Wild, L. O’Neill, T. Zhang, R. Purkayastha, G. Minton, M. Marinescu and G. J. Offer, Energy Environ. Sci., 2015, 8, 3477–3494. \n5 Y. X. Yin, S. Xin, Y. G. Guo and L. J. Wan, Angew. Chem., Int. Ed., 2013, 52, 13186–13200. \n6 Q. Pang, X. Liang, C. Y. Kwok and L. F. Nazar, Nat. Energy, 2016, 1, 16132. 7 X. Ji, K. T. Lee and L. F. Nazar, Nat. Mater., 2009, 8, 500–506. 8 H.-J. Peng, J.-Q. Huang, M.-Q. Zhao, Q. Zhang, X.-B. Cheng, X.-Y. Liu, W.-Z. Qian and F. Wei, Adv. Funct. Mater., 2014, 24, 2772–2781. \n9 G. Zheng, Q. Zhang, J. J. Cha, Y. Yang, W. Li, Z. W. Seh and Y. Cui, Nano Lett., 2013, 13, 1265–1270. \n10 X. Wang, T. Gao, X. Fan, F. Han, Y. Wu, Z. Zhang, J. Li and C. Wang, Adv. Funct. Mater., 2016, 26, 7164–7169. \n11 S. Zhang, K. Ueno, K. Dokko and M. Watanabe, Adv. Energy Mater., 2015, 5, 1500117. \n12 J. Chen, K. S. Han, W. A. Henderson, K. C. Lau, M. Vijayakumar, T. Dzwiniel, H. Pan, L. A. Curtiss, J. Xiao, K. T. Mueller, Y. Shao and J. Liu, Adv. Energy Mater., 2016, 6, 1600160. \n13 J. Balach, T. Jaumann, M. Klose, S. Oswald, J. Eckert and L. Giebeler, Adv. Funct. Mater., 2015, 25, 5285–5291. \n14 S. H. Chung and A. Manthiram, Adv. Mater., 2014, 26, 1360–1365. \n15 J.-Q. Huang, Q. Zhang, H.-J. Peng, X.-Y. Liu, W.-Z. Qian and F. Wei, Energy Environ. Sci., 2014, 7, 347–353. \n16 P. Bhattacharya, M. I. Nandasiri, D. Lv, A. M. Schwarz, J. T. Darsell, W. A. Henderson, D. A. Tomalia, J. Liu, J.-G. Zhang and J. Xiao, Nano Energy, 2016, 19, 176–186. \n17 T. Nakazawa, A. Ikoma, R. Kido, K. Ueno, K. Dokko and M. Watanabe, J. Power Sources, 2016, 307, 746–752. \n18 G. Zheng, S. W. Lee, Z. Liang, H. W. Lee, K. Yan, H. Yao, H. Wang, W. Li, S. Chu and Y. Cui, Nat. Nanotechnol., 2014, 9, 618–623. \n19 W. Xu, J. Wang, F. Ding, X. Chen, E. Nasybulin, Y. Zhang and J.-G. Zhang, Energy Environ. Sci., 2014, 7, 513–537. \n20 Y. Yang, G. Zheng and Y. Cui, Energy Environ. Sci., 2013, 6, 1552. \n21 H. Al Salem, G. Babu, C. V. Rao and L. M. Arava, J. Am. Chem. Soc., 2015, 137, 11542–11545. \n22 Z. Yuan, H. J. Peng, T. Z. Hou, J. Q. Huang, C. M. Chen, D. W. Wang, X. B. Cheng, F. Wei and Q. Zhang, Nano Lett., 2016, 16, 519–527. \n23 Q. Pang, D. Kundu, M. Cuisinier and L. F. Nazar, Nat. Commun., 2014, 5, 4759. \n24 Y. Gorlin, M. U. M. Patel, A. Freiberg, Q. He, M. Piana, M. Tromp and H. A. Gasteiger, J. Electrochem. Soc., 2016, 163, A930–A939. \n25 H. J. Peng, G. Zhang, X. Chen, Z. W. Zhang, W. T. Xu, J. Q. Huang and Q. Zhang, Angew. Chem., Int. Ed., 2016, 55, 12990–12995. \n26 Y.-J. Li, J.-M. Fan, M.-S. Zheng and Q.-F. Dong, Energy Environ. Sci., 2016, 9, 1998–2004. \n27 K. Chang, Z. Mei, T. Wang, Q. Kang, S. Ouyang and J. Ye, ACS Nano, 2014, 8, 7078–7087. \n28 J. Kibsgaard, Z. Chen, B. N. Reinecke and T. F. Jaramillo, Nat. Mater., 2012, 11, 963–969. \n29 D. Kiriya, P. Lobaccaro, H. Y. Nyein, P. Taheri, M. Hettick, H. Shiraki, C. M. Sutter-Fella, P. Zhao, W. Gao, R. Maboudian, J. W. Ager and A. Javey, Nano Lett., 2016, 16, 4047–4053. \n30 M. Asadi, B. Kumar, C. Liu, P. Phillips, P. Yasaei, A. Behranginia, P. Zapol, R. F. Klie, L. A. Curtiss and A. Salehi-Khojin, ACS Nano, 2016, 10, 2167–2175. \n31 Y. Yin, J. Han, Y. Zhang, X. Zhang, P. Xu, Q. Yuan, L. Samad, X. Wang, Y. Wang, Z. Zhang, P. Zhang, X. Cao, B. Song and S. Jin, J. Am. Chem. Soc., 2016, 138, 7965–7972. \n32 H. Li, C. Tsai, A. L. Koh, L. Cai, A. W. Contryman, A. H. Fragapane, J. Zhao, H. S. Han, H. C. Manoharan, F. Abild-Pedersen, J. K. Norskov and X. Zheng, Nat. Mater., 2016, 15, 48–53. \n33 G. Ji, Y. Yu, Q. Yao, B. Qu, D. Chen, W. Chen, J. Xie and J. Y. Lee, NPG Asia Mater., 2016, 8, e247. \n34 H. Wang, Q. Zhang, H. Yao, Z. Liang, H.-W. Lee, P.-C. Hsu, G. Zheng and Y. Cui, Nano Lett., 2014, 14, 7138–7144. \n35 A. Jawaid, D. Nepal, K. Park, M. Jespersen, A. Qualley, P. Mirau, L. F. Drummy and R. A. Vaia, Chem. Mater., 2016, 28, 337–348. \n36 W. Tang, B.-M. Goh, M. Y. Hu, C. Wan, B. Tian, X. Deng, C. Peng, M. Lin, J. Z. Hu and K. P. Loh, J. Phys. Chem. C, 2016, 120, 2600–2608. \n37 B. Qu, C. Ma, G. Ji, C. Xu, J. Xu, Y. S. Meng, T. Wang and J. Y. Lee, Adv. Mater., 2014, 26, 3854–3859. \n38 J. Wu, M. Liu, P. P. Sharma, R. M. Yadav, L. Ma, Y. Yang, X. Zou, X. D. Zhou, R. Vajtai, B. I. Yakobson, J. Lou and P. M. Ajayan, Nano Lett., 2016, 16, 466–470. \n39 F. Wu, J. Li, Y. Su, J. Wang, W. Yang, N. Li, L. Chen, S. Chen, R. Chen and L. Bao, Nano Lett., 2016, 16, 5488–5494. \n40 M. Thripuranthaka, R. V. Kashid, C. Sekhar Rout and D. J. Late, Appl. Phys. Lett., 2014, 104, 081911. \n41 X. Fan, P. Xu, Y. C. Li, D. Zhou, Y. Sun, M. A. Nguyen, M. Terrones and T. E. Mallouk, J. Am. Chem. Soc., 2016, 138, 5143–5149. \n42 J. Xiao, X. Chen, P. V. Sushko, M. L. Sushko, L. Kovarik, J. Feng, Z. Deng, J. Zheng, G. L. Graff, Z. Nie, D. Choi, J. Liu, J.-G. Zhang and M. S. Whittingham, Adv. Mater., 2012, 24, 2109–2116. \n43 D. M. Sim, M. Kim, S. Yim, M.-J. Choi, J. Choi, S. Yoo and Y. S. Jung, ACS Nano, 2015, 9, 12115–12123. \n44 I. S. Kim, V. K. Sangwan, D. Jariwala, J. D. Wood, S. Park, K.-S. Chen, F. Shi, F. Ruiz-Zepeda, A. Ponce, M. Jose-Yacaman, V. P. Dravid, T. J. Marks, M. C. Hersam and L. J. Lauhon, ACS Nano, 2014, 8, 10551–10558. \n45 L.-p. Feng, J. Su and Z.-t. Liu, RSC Adv., 2015, 5, 20538–20544. \n46 N. D. K. Tu, J. Choi, C. R. Park and H. Kim, Chem. Mater., 2015, 27, 7362–7369. \n47 X. Wang, G. Li, M. H. Seo, F. M. Hassan, M. A. Hoque and Z. Chen, Adv. Energy Mater., 2015, 5, 1501106. \n48 Q. Pang and L. F. Nazar, ACS Nano, 2016, 10, 4111–4118. \n49 H.-J. Peng, Z.-W. Zhang, J.-Q. Huang, G. Zhang, J. Xie, W.-T. Xu, J.-L. Shi, X. Chen, X.-B. Cheng and Q. Zhang, Adv. Mater., 2016, 28, 9551–9558. \n50 E. Gracia-Espino, G. Hu, A. Shchukarev and T. Wågberg, J. Am. Chem. Soc., 2014, 136, 6626–6633. \n51 J. Ye, W. Chen, Q. Chen, Z. Yu and J. Y. Lee, Electrochim. Acta, 2016, 190, 538–547. \n52 L. Wang, Y. Wang and Y. Xia, Energy Environ. Sci., 2015, 8, 1551–1558. \n53 C. Wang, X. Wang, Y. Yang, A. Kushima, J. Chen, Y. Huang and J. Li, Nano Lett., 2015, 15, 1796–1802. \n54 K. Park, J. H. Cho, J.-H. Jang, B.-C. Yu, A. T. De La Hoz, K. M. Miller, C. J. Ellison and J. B. Goodenough, Energy Environ. Sci., 2015, 8, 2389–2395. \n55 J. Liu, W. Li, L. Duan, X. Li, L. Ji, Z. Geng, K. Huang, L. Lu, L. Zhou, Z. Liu, W. Chen, L. Liu, S. Feng and Y. Zhang, Nano Lett., 2015, 15, 5137–5142. \n56 F. Cheng, T. Zhang, Y. Zhang, J. Du, X. Han and J. Chen, Angew. Chem., Int. Ed., 2013, 52, 2474–2477. \n57 H. L. Wu, L. A. Huff and A. A. Gewirth, ACS Appl. Mater. Interfaces, 2015, 7, 1709–1719. \n58 D.-H. Han, B.-S. Kim, S.-J. Choi, Y. Jung, J. Kwak and S.-M. Park, J. Electrochem. Soc., 2004, 151, E283. \n59 D. Kiriya, P. Lobaccaro, H. Y. Y. Nyein, P. Taheri, M. Hettick, H. Shiraki, C. M. Sutter-Fella, P. Zhao, W. Gao, R. Maboudian, J. W. Ager and A. Javey, Nano Lett., 2016, 16, 4047–4053. " + }, + { + "id": "10.1038_ncomms15893", + "DOI": "10.1038/ncomms15893", + "DOI Link": "http://dx.doi.org/10.1038/ncomms15893", + "Relative Dir Path": "mds/10.1038_ncomms15893", + "Article Title": "Origin of fast ion diffusion in super-ionic conductors", + "Authors": "He, XF; Zhu, YZ; Mo, YF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Super-ionic conductor materials have great potential to enable novel technologies in energy storage and conversion. However, it is not yet understood why only a few materials can deliver exceptionally higher ionic conductivity than typical solids or how one can design fast ion conductors following simple principles. Using ab initio modelling, here we show that fast diffusion in super-ionic conductors does not occur through isolated ion hopping as is typical in solids, but instead proceeds through concerted migrations of multiple ions with low energy barriers. Furthermore, we elucidate that the low energy barriers of the concerted ionic diffusion are a result of unique mobile ion configurations and strong mobile ion interactions in super-ionic conductors. Our results provide a general framework and universal strategy to design solid materials with fast ionic diffusion.", + "Times Cited, WoS Core": 727, + "Times Cited, All Databases": 794, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000403770700001", + "Markdown": "# Origin of fast ion diffusion in super-ionic conductors \n\nXingfeng ${\\mathsf{H}}{\\mathsf{e}}^{1},$ Yizhou Zhu1 & Yifei Mo1,2 \n\nSuper-ionic conductor materials have great potential to enable novel technologies in energy storage and conversion. However, it is not yet understood why only a few materials can deliver exceptionally higher ionic conductivity than typical solids or how one can design fast ion conductors following simple principles. Using ab initio modelling, here we show that fast diffusion in super-ionic conductors does not occur through isolated ion hopping as is typical in solids, but instead proceeds through concerted migrations of multiple ions with low energy barriers. Furthermore, we elucidate that the low energy barriers of the concerted ionic diffusion are a result of unique mobile ion configurations and strong mobile ion interactions in super-ionic conductors. Our results provide a general framework and universal strategy to design solid materials with fast ionic diffusion. \n\nScoloidmpmonatenrtisals nwith feacstt oicohneicmitcralnspeonret ayre isntodrisapgensabnlde electrochemical membranes1–6, which are critical in the societal shift to renewable energy. These electrochemical devices can further improve through the use of super-ionic conductor (SIC) materials, which have several orders of magnitude higher ionic conductivity than typical solids. For example, lithium SICs, including $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ (LGPS)7, $\\mathrm{Li}_{7}\\mathrm{P}_{3}\\mathrm{S}_{11}$ (ref. 8), lithium garnet (for example, $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ (refs 9,10)), and $\\mathrm{Li^{+}}$ -conducting NASICON (for example, $\\mathrm{Li_{1.3}A l_{0.3}T i_{1.7}(P O_{4})_{3}}$ (ref. 11)), achieve high Li ionic conductivity, $\\sim1-10\\mathrm{mS}\\mathrm{cm}^{-1}$ at room temperature (RT), and low activation energy, ${\\sim}0.2\\mathrm{-}0.3\\mathrm{eV}$ . These SIC materials are promising solid electrolytes for the development of next-generation all-solid-state Li-ion batteries, which provide improved safety, higher energy density, and better thermal stability than current organic electrolyte-based Li-ion batteries6,7,12,13. Despite significant research efforts, only a few materials out of tens of thousands of known inorganic materials have been identified as SICs. It is of great scientific interests to understand why these SICs can achieve several orders of magnitude faster ionic diffusion than other solid materials, and to enable a rationally guided materials design strategy for fast ion conductors. \n\nCurrent understanding of ionic diffusion in solids is based on the classical diffusion model, which describes ionic transport as the hopping of individual ions from one lattice site to another through inter-connected diffusion channels in the crystal structural framework14 (Fig. 1). The crystal structural framework determines the energy landscape of the ion migration. During ion diffusion, a mobile ion migrates through the energy landscape, and the highest energy of the energy landscape along the diffusion path determines the energy barrier $E_{\\mathrm{a}}$ of ionic diffusion. A low activation energy $E_{\\mathrm{a}}$ and a high concentration $n_{c}$ of mobile ion carriers (such as vacancies or interstitials) are required to achieve high ionic conductivity $\\sigma$ which is proportional to $n_{c}\\cdot\\exp(-E_{\\mathrm{a}}/k_{\\mathrm{B}}\\mathrm{\\bar{}}T)$ at temperature $T$ On the basis of this classical diffusion model, current research efforts in the design and discovery of fast ion conductors target materials with crystal structural frameworks that yield an energy landscape of low barriers. For example, the structural framework with body-centred cubic (bcc) anion packing yields the flattest energy landscape with the lowest $\\mathrm{Li^{+}}$ migration barrier, for example, $\\mathrm{\\sim}0.2\\mathrm{e}\\bar{\\mathrm{V}}$ in lithium-containing sulfides, whereas non-bcc structural frameworks such as in face-centred cubic or hexagonal close-packed exhibit significantly higher energy barriers13. Unfortunately, bcc anion packing is a rare structural feature in Li-containing oxides and sulfides, and among known Li SICs is only found in LGPS and $\\mathrm{Li}_{7}\\mathrm{P}_{3}\\mathrm{S}_{11}$ . Other well-known SICs, such as lithium garnet and NASICON, do not exhibit bcc anion packing, but still achieve high $\\mathrm{Li^{+}}$ ionic conductivity of $\\stackrel{\\bullet}{\\sim}1\\mathrm{m}\\check{\\mathrm{S}}\\mathrm{cm}^{-1}$ at RT. \n\nSuper-ionic conduction is known to be activated at high mobile-ion concentration $n_{\\mathrm{c}}$ and in specific mobile ion sublattice configuration achieved through materials doping. For example, Li garnet achieves the highest RT Li conductivity, $\\sigma_{\\mathrm{RT}}=\\sim0.1$ to $\\mathrm{\\check{1}m S c m^{-1}}$ $(E_{\\mathrm{a}}=\\sim0.3\\mathrm{eV})$ ), at $6.4\\substack{-7.0\\mathrm{Li}}$ per formula unit in the doped, cubic-phase $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ compositions10,15,16, whereas $\\mathrm{Li}_{5}\\mathrm{La}_{3}\\mathrm{Ta}_{2}\\mathrm{O}_{12}$ composition of the same crystal structural framework only exhibits $\\sigma_{\\mathrm{RT}}=\\sim10^{-3}\\mathrm{mScm}^{-1}$ $(E_{\\mathrm{a}}=\\sim0.5\\mathrm{eV})^{17}$ . $\\mathrm{Li^{+}}$ -conducting NASICON $\\mathrm{Li}_{1+x}\\mathrm{Al}_{x}\\mathrm{Ti}_{2-x}(\\mathrm{PO}_{4})_{3}$ achieves high ionic conductivity $\\sigma_{\\mathrm{RT}}=\\sim1\\mathrm{mScm}^{-1}$ $(E_{\\mathrm{a}}=\\sim0.3\\mathrm{eV})$ at $\\scriptstyle x=0.2-0.3$ (ref. 11), whereas $\\operatorname{LiTi}_{2}(\\operatorname{PO}_{4})_{3}$ composition has only $\\sigma_{\\mathrm{RT}}=\\sim10^{-3}\\mathrm{mScm}^{-1}$ $\\left(E_{\\mathrm{a}}=\\sim0.45\\mathrm{eV}\\right)^{11,}$ 18. Therefore, the super-ionic conduction in these materials is only activated at certain doped compositions with particular $\\dot{\\mathrm{Li}}^{+}$ sublattice ordering. However, the classical diffusion model, which predicts similar migration barriers for the same crystal framework, fails to capture such super-ionic conduction in these materials. For example, the classical model cannot explain why $\\mathrm{Li^{+}}$ migrations suddenly exhibit significantly lower activation energy barriers in the same crystal structural framework with similar energy landscape as seen in doped Li garnet and NASICON. The answer to this question may help guide the design of SIC materials, especially those with distinctive crystal structural frameworks that deviate from the optimal bcc anion packing. \n\n![](images/1bf781272e19c0855f2298481ddc286b9f3c90a3044f349553912c2b853c13b3.jpg) \nFigure 1 | Schematic illustration of single-ion migration versus multi-ion concerted migration. For single-ion migration (upper insets), the migration energy barrier is the same as the barrier of the energy landscape. In contrast, the concerted migration of multiple ions (lower insets) has a lower energy barrier as a result of strong ion-ion interactions and unique mobile ion configuration in super-ionic conductors. \n\nIn this study, we reveal the origin of fast ionic diffusion in SIC materials with distinctive structural frameworks. We demonstrate a general understanding of fast ionic diffusion across a range of materials using a diffusion model with explicit consideration of the unique mobile-ion sublattice at super-ionic states. Furthermore, we establish a simple conceptual framework for activating fast ion conduction with low migration barriers through materials design, which is generally applicable to any ion-conducting materials. \n\n# Results \n\nConcerted ion migration in super-ionic conductors. We performed ab initio molecular dynamics (AIMD) simulations to study diffusion mechanism in the model SIC materials, \n\n![](images/036e866b5a20af404b999b407b21dc8b8e7914b2097cd081d4d0e9862dec45e7.jpg) \nFigure 2 | Li ion diffusion in super-ionic conductors. (a–c) Crystal structures of (a) LGPS, (b) LLZO and (c) LATP marked with Li sites (partially filled green spheres), ${\\mathsf{L i}}^{+}$ diffusion channels (green bars), and polyanion groups (purple and blue polyhedra). (d–f) The probability density of ${\\mathsf{L i}}^{+}$ spatial occupancy during AIMD simulations. The zoom-in subsets show the elongation feature of probability density along the migration channel (Li: green; ${\\mathsf{O}}/{\\mathsf{S}}$ : yellow). The isosurfaces are $6\\rho_{0},$ $,6\\rho_{0},2\\rho_{0}$ for LGPS, LLZO, LATP, respectively, where $\\rho_{0}$ is the mean probability density in each structure and the inner isosurfaces have twice the density of the outer isosurfaces. $({\\pmb g}-{\\bf\\dot{i}})$ Van Hove correlation functions of ${\\mathsf{L i}}^{+}$ dynamics on distinctive Li ions during AIMD simulations. \n\nLGPS, cubic-phase $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ (LLZO) and $\\mathrm{Li_{1.3}A l_{0.3}T i_{1.7}(P O_{4})_{3}}$ (LATP) (Fig. 2 and Supplementary Fig. 1), which have different anion packing (that is, bcc in LGPS versus non-bcc in LLZO and LATP). The high Li ionic conductivities and low activation energies calculated from AIMD simulations are in good agreement with experimental values7,9,11 (Supplementary Table 1 and Supplementary Fig. 1). By analysing $\\bar{\\mathrm{Li^{+}}}$ dynamics from AIMD simulations, we found that most Li ions migrate in a highly concerted fashion, that is, multiple ions hop simultaneously into their nearest sites within a few picoseconds (Supplementary Note 1 and Supplementary Fig. 2). The strong time correlation in $\\mathrm{Li^{+}}$ hopping during the concerted migration is confirmed by the van Hove correlation function (Fig. 2g–i) of $\\mathrm{Li^{+}}$ dynamics. In addition, to characterize the extent of concerted migrations, we calculated the correlation factor related to the Haven ratio. Whereas a correlation factor of 1.0 corresponds to isolated single-ion diffusion, the correlation factor is calculated as 3.0, 3.0 and 2.1 for LGPS, LLZO and LATP, respectively, in the AIMD simulations at $900~\\mathrm{K},$ corresponding to correlated hopping of approximately two to three ions on average in these SICs. Therefore, the concerted migration is the dominant mechanism for fast diffusion in SICs, as it is in liquids19,20. \n\nThe concerted migration extracted from AIMD simulations (illustrated as insets Fig. 3a–c) is simultaneous hopping of multiple adjacent ions into their nearest sites. In LGPS, a typical concerted migration involves four Li ions occupying Li1 and Li3 sites hopping simultaneously along the c channel into their nearest-neighbour Li3 and Li1 sites, respectively (Fig. 3a), as observed in a previous study21. In LLZO, Li ions partially co-occupy tetrahedral (T) sites and octahedral (O) sites. During concerted migration in LLZO, T-site Li ions hop to the nearest-neighbour O sites and the Li ions occupying these O sites hop into their nearest neighbour T sites, resulting in concerted hopping of multiple Li ions along the garnet diffusion channel (Fig. 3b) similar to previous modelling studies22,23. In LATP, the typical concerted migration mode is that two Li ions at adjacent M1 and M2 sites migrate in pair. The $\\mathrm{Li^{+}}$ on the M1 site hops into the unoccupied M2 site, and at the same time the $\\mathrm{Li^{+}}$ on the M2 site hops into the next M1 site (Fig. 3c). The migration barriers of these concerted migrations were calculated using nudged-elastic-band (NEB) methods based on ab initio computation (Fig. 3a–c), and were found to be 0.20, 0.26 and $0.27\\mathrm{eV}$ in LGPS, LLZO and LATP, respectively. Given the highly disordered nature of the Li sublattice, various modes of concerted migration mechanisms involving different number of Li and different Li configurations were observed during AIMD simulations and are illustrated in Supplementary Note 2 and Supplementary Fig. 3. The other modes of concerted migration also show migration barriers similar to the typical modes in Fig. 3. The calculated energy barriers of concerted migration are in good agreement with the activation energies obtained from the AIMD simulations and from experiments7,9,11 (Supplementary Table 1). Therefore, these typical concerted migrations observed in AIMD simulations represent the key diffusion mechanisms in SICs. \n\n![](images/6941cee2430d4d7b80551fa14734c97a536e9890564f0bf5996cd9f98327ba1a.jpg) \nFigure 3 | Concerted migration and energy landscape in super-ionic conductors. (a–c) Migration energy barrier in $\\mathbf{\\eta}(\\mathbf{a})$ LGPS, $(\\pmb{6})$ LLZO, (c) LATP for concerted migration of multiple Li ions hopping into the next sites along the diffusion channel. Insets show the ${\\mathsf{L i}}^{+}$ path (green spheres) and $0/5$ ions (yellow spheres). (d–f) The energy landscape of single ${\\mathsf{L i}}^{+}$ along the migration channel (shown in insets) across multiple Li sites (partially filled green sphere) and ${\\mathsf{L i}}^{+}$ pathway (red spheres). \n\nOrigin of concerted migration with low barriers. Given such low energy barriers for multi-ion concerted migration, a relatively flat energy landscape along $\\mathrm{Li^{+}}$ diffusion channels is expected. Surprisingly, the energy landscapes have barriers of 0.47, 0.58 and $0.4\\bar{9}\\mathrm{eV}$ for LGPS, LLZO and LATP, respectively (Fig. 3d–f), which are significantly higher than the energy barrier of concerted migration. On the basis of the classical diffusion model, these high barriers of the energy landscape would lead to even higher activation energy $E_{\\mathrm{a}},$ as each migrating ion feels the high barriers of the energy landscape along the diffusion channel. Thus, the low-barrier concerted migration of multiple ions cannot be explained by the classical diffusion model. As super-ionic conduction is only activated at specific composition with high Li concentration, the mobile-ion configuration and the interactions among these ions, which are neglected in the classical diffusion model, must be considered in order to properly describe the concerted migration in SICs. \n\nTo reveal the mechanism of multi-ion concerted migration, here we performed a simple diffusion model on the basis of the classical diffusion model by taking into account the configuration of mobile ions and Coulomb interactions among them. In this model, we chose an energy landscape (Fig. 4a) with a $0.6\\mathrm{eV}$ barrier, similar to that in LLZO (Fig. 3e), and included Coulomb interaction among mobile ions with a strength $K$ of ${\\sim}2{\\mathrm{-}}4\\mathrm{eV}\\mathring\\mathrm{A}$ fitted to ab initio calculations (Supplementary Note 3). In addition, the unique $\\mathrm{Li^{+}}$ configuration in SIC materials (Fig. 3d–f) was also considered in this model. In SICs, the mobile ions occupy the high-energy sites (Fig. 4a,b), such as the octahedral O sites in LLZO (Fig. 3e) and the M2 sites in LATP (Fig. 3f), which are near the highest energy point along the diffusion path. At high Li concentration of these SIC materials, the high-energy sites in SICs are occupied because the low-energy sites (for example, tetrahedral $\\mathrm{\\DeltaT}$ sites in LLZO and M1 sites in LATP) are preferably occupied and cannot accommodate all Li ions inserted. The extra Li ions occupying high-energy sites are stabilized by Coulomb interactions from nearby mobile ions (within $\\sim2\\dot{-}3\\mathring\\mathrm{A};$ ) during the minimization of the overall lattice energy. \n\nOur model shows that such a unique mobile-ion configuration under strong mobile ion-ion interactions is the key for achieving low-barrier concerted migration in these SICs. At typical $K$ values of $2{\\-}4\\mathrm{eV}\\mathring\\mathrm{A}$ in these SICs, the concerted migration of multiple ions shows a significantly lower migration barrier of ${\\sim}0.2{\\mathrm{-}}0.4\\ \\mathrm{\\bar{e}V}$ (Fig. 4d and Supplementary Fig. 4), which is in good agreement with those from NEB calculations (Fig. 3a–c) and AIMD simulations (Supplementary Table 1). Therefore, this simple diffusion model captures the key physics of concerted migration in the SICs. This model demonstrates that low energy barrier of multi-ion concerted migration is a result of the unique mobileion configuration with high-energy site occupancy. During the concerted migration of multiple ions, the ions located at the highenergy sites migrate downhill, which cancels out a part of the energy barrier felt by other uphill-climbing ions. As a result, concerted migration of multiple ions has a significantly lower energy barrier than the energy landscape of the crystal structural framework. \n\nIn addition, high-energy sites should have locally low barriers and flat energy landscapes, in order to activate low-barrier concerted migration. As observed in the AIMD simulations (Fig. 2d,e), the high-energy sites are associated with elongated spatial occupancy density of mobile Li ions. For example, the Li probability density is elongated at the octahedral (O) sites in LLZO (Fig. 2e). That elongated density indicates a locally flat energy landscape for $\\mathrm{Li^{+}}$ to hop out. The easy migration of ions occupying high-energy sites may facilitate the onset of multi-ion concerted migration24. Otherwise, for the energy landscape in \n\n![](images/87ad001e12842b7c9d11654844c1aa781cb445d51a788339836aed5c09c94c7f.jpg) \nFigure 4 | Diffusion model for concerted migration. (a,b) The potential energy of the structural framework with low $\\mathbf{\\eta}(\\mathbf{a})$ or high $(\\pmb{\\ b})$ barriers at the high-energy sites. The mobile ion (grey sphere) configurations and the migration paths (arrows) are illustrated. (c) The energy profile for the concerted migration in the energy landscape (a) and $\\mathbf{(6)}$ at ${\\cal K}=3\\mathsf{e V}\\mathsf{A}$ (d) The energy barrier of concerted migration at different Coulomb interaction strength $K$ . \n\nFig. 4b as in non-SIC materials (Supplementary Note 4 and Supplementary Fig. 5), multiple ions would simultaneously climb uphill, leading to higher energy barrier for concerted migration (Fig. 4c). \n\n# Discussion \n\nIn summary, our theory demonstrates a simple conceptual framework for understanding fast ion diffusion in SICs. Specifically, mobile ions occupying high-energy sites can activate concerted migration with a reduced migration energy barrier. In addition to lithium garnet and NASICON SICs, this mechanism is observed in other SIC materials, such as $\\mathrm{Li}_{7}\\mathrm{P}_{3}\\mathrm{S}_{11},$ $\\mathrm{\\sf{\\beta-Li}}_{3}\\mathrm{\\sf{PS}}_{4}$ , LISICON, $\\mathrm{Li}_{x}\\mathrm{La}_{2/3-x/3}\\mathrm{TiO}_{3}$ (LLTO) perovskite25, and Na þ - conducting NASICON, where high-energy sites are occupied along the diffusion path and the concerted migration with low energy barrier is confirmed in ab initio modelling (Supplementary Note 5 and Supplementary Figs 6–11). The concerted migration of multiple ions is also reported for low-barrier diffusion in other Li ionic conductors, for example, $\\mathrm{Li}_{3}\\mathrm{OX}$ $(\\mathrm{X}=\\mathrm{Cl},\\ \\mathrm{Br})^{26}$ and doped $\\mathrm{Li}_{3}\\mathrm{PO}_{4}$ (refs 27,28). In addition to $\\mathrm{Li^{+}}$ and $\\mathrm{Na^{+}}$ conductors, our proposed model is generally applicable to conductors of other ions. For example, $\\mathbf{Ag}$ super-ionic conductor $\\mathrm{AgI}^{29}$ is known for highly concerted migration, and oxygen ionic conductors of fluorite structure (for example, $\\mathrm{Bi}_{2}\\mathrm{O}_{3}.$ ) (Supplementary Fig. 12) and $\\mathrm{La}_{1-x}\\mathrm{Ba}_{1+x}\\mathrm{GaO}_{4-x/2}$ (ref. 30) also show concerted migration behaviour. Therefore, our proposed theory and identified mechanism are universally applicable to fast diffusion in a broad range of ion-conducting materials. \n\nMoreover, our theory provides a simple strategy for designing super-ionic conductor materials, that is, inserting mobile ions into high-energy sites to activate concerted ion migration with lower barriers. This explains how super-ionic conduction in lithium garnet and NASICON SICs is activated at certain compositions with increased Li concentration. Here, we demonstrate this strategy by designing a number of novel fast ion conducting materials to activate concerted migration with reduced diffusion barrier. We select ${\\mathrm{LiTaSiO}}_{5}$ and $\\mathrm{LiAlSiO_{4}}$ (details of structures in Supplementary Note 6 and Supplementary Figs 13 and 14), which have structures with a decent bottleneck size of diffusion channels and well-connected $\\mathrm{Li^{+}}$ percolation network, but have not been studied for $\\mathrm{Li^{+}}$ transport. The original structures show low $\\mathrm{Li^{+}}$ conductivities and high activation energies similar to their high-barrier energy landscapes (Supplementary Figs 13 and 14). Extra Li ions are inserted into the high-energy sites of ${\\mathrm{LiTaSiO}}_{5}$ and $\\mathrm{LiAlSiO_{4}}$ by aliovalent substitution of non-Li cations with lower valences. For the doped materials, AIMD simulations show $\\mathrm{Li^{+}}$ concerted migrations with significantly reduced migration barriers of $0.2\\bar{3}{-0.28}\\mathsf{e V}$ and $\\bar{\\mathrm{Li}^{+}}$ conductivities of $1{-}4\\mathrm{mS}\\mathrm{cm}^{-1}$ at RT (Supplementary Figs 13 and 14), which are comparable to many known Li SICs. These results demonstrate that the design strategy based on our simple conceptual framework can be successfully utilized to design novel fast ion conducting materials. In addition, this strategy for facilitating diffusion is generally applicable to any ion-conducting materials. \n\n# Methods \n\nDensity functional theory computation. All density functional theory (DFT) calculations in this study were performed using Vienna $\\mathbf{\\nabla}_{A b}$ initio Simulation package $(\\mathrm{VASP})^{31}$ within the projector augmented-wave approach. Perdew–Burke–Ernzerhof $(\\mathrm{PBE})^{3\\bar{2}}$ generalized-gradient approximation (GGA) functionals were adopted in all calculations. The parameters in static DFT calculations were consistent with the Materials Project33–35. The nudged elastic band (NEB) calculations were performed in supercell models using a $T$ -centred $2\\times2\\times2$ k-point grid. \n\nAb initio molecular dynamics simulation. $\\vert A b$ initio molecular dynamics (AIMD) simulations were performed in supercell models using non-spin-polarized DFT calculations with a $\\Gamma$ -centred $k$ -point. The time step was set to $2\\mathrm{fs}$ . The initial structures were statically relaxed and were set to an initial temperature of $100\\mathrm{K}$ . The structures were then heated to targeted temperatures (300–1500 K) at a constant rate by velocity scaling over a time period of $2\\mathrm{ps}$ . The NVT ensemble using a Nose´–Hoover thermostat36 was adopted. The total time of AIMD simulations were in the range of 100 to $600\\mathrm{ps}$ until the total mean square displacement of Li ions was ${\\phantom{-}}>250\\mathrm{\\AA}^{2}$ in each AIMD simulation and until the diffusivity was converged. \n\nAs in previous studies37–39, the diffusivity $D$ was calculated as the mean square displacement over time interval $\\Delta t$ : \n\n$$\nD{=}\\frac{1}{2N d\\Delta t}{\\sum_{i=1}^{N}{\\left\\langle|{{\\bf{r}}_{i}}(t+\\Delta t)-{{\\bf{r}}_{i}}(t)|^{2}}\\right\\rangle_{t}},\n$$ \n\nwhere $d=3$ is the dimension of the diffusion system, $N$ is the total number of diffusion ions, ${\\bf r}_{i}(t)$ is the displacement of the $i$ -th ion at time $t,$ and the bracket represents averaging over $t.$ The ionic conductivity was calculated based on the Nernst-Einstein relationship using \n\n$$\n\\sigma{=}\\frac{n q^{2}}{k_{\\mathrm{B}}T}D,\n$$ \n\nwhere $n$ is the number of mobile ions per unit volume and $q$ is the ionic charge. The probability density of mobile ions was calculated as the fraction of time that each spatial location was occupied. \n\nTime correlation of ${\\pmb{\\lfloor\\dot{\\imath}\\dagger}}$ dynamics. The van Hove correlation function $^{40}$ was calculated from the AIMD simulations. The distinctive part $G_{\\mathrm{d}}$ describes the radial distribution of different ions after time interval $\\Delta t$ with respect to the initial ion, \n\n$$\nG_{\\mathrm{d}}(r,\\Delta t)=\\frac{1}{4\\pi r^{2}N n}\\Bigg\\langle\\sum_{i=1}^{N}\\sum_{j=1,j\\neq i}^{N}\\delta\\big(r-\\big|\\mathbf{r}_{i}(t+\\Delta t)-\\mathbf{r}_{j}(t)\\big|\\big)\\Bigg\\rangle_{t},\n$$ \n\nwhere $\\delta$ is the Dirac delta function. The correlation function is averaged over the time t. \n\nThe Haven ratio is often used to measure the correlation effect in ionic diffusion41. In this study, we defined a similar correlation factor $f$ to quantify the correlation of ion migration: \n\n$$\nf=\\frac{N D_{\\sigma}}{D}.\n$$ \n\nWhile $D$ is the self-diffusion diffusivity of individual ions, $D_{\\sigma}$ is the diffusivity of the centre of all diffusion ions and is calculated as: \n\n$$\nD_{\\sigma}=\\frac{1}{2d\\Delta t}\\left\\langle\\left|\\frac{1}{N}\\sum_{i=1}^{N}\\mathbf{r}_{i}(t+\\Delta t)-\\frac{1}{N}\\sum_{i=1}^{N}\\mathbf{r}_{i}(t)\\right|^{2}\\right\\rangle_{t}.\n$$ \n\nEnergy landscape of single-ion migration. The energy landscape of a single $\\mathrm{Li^{+}}$ along the migration channel (Fig. 3d–f) was calculated using the NEB methods. In LGPS, three $\\mathrm{Li^{+}}$ ions in the $\\scriptstyle{c}$ channel were removed and the energy landscape was obtained by migrating a $\\mathrm{Li^{+}}$ across the $\\mathbf{\\Psi}_{c}$ channel. The energy landscape of cubic-phase LLZO corresponds to single $\\mathrm{Li^{+}}$ migration between two neighbouring tetrahedral sites after removing a Li ion. The energy landscape of LATP corresponds to single $\\mathrm{Li^{+}}$ migration between two neighbouring M1 sites after removing a Li ion. In the NEB calculations, the charge states of all ions were maintained by inserting extra electrons into the system as in the previous study13. To avoid excessive relaxation of the $\\mathrm{Li^{+}}$ sublattice, only non-Li cations and anions were relaxed during the NEB calculations. \n\nDiffusion model for concerted migration. In the diffusion model illustrated in Fig. 4, four mobile ions were arranged in a 1D lattice consisting of two unit cells. The 1D unit cell has a period of $L=6\\mathring\\mathrm{A}$ , which is similar between two nearest-neighbour M1 sites in LATP (Figs 2f and 3f). The total energy $E$ of the entire mobile lattice is given by the sum of the potential energy $\\phi$ from the crystal framework (that is, the energy landscape) and the Coulomb interaction among mobile ions: \n\n$$\nE=\\sum_{i}\\phi(x_{i})+\\sum_{i,j,i\\neq j}{\\frac{K}{\\left|x_{i}-x_{j}\\right|}},\n$$ \n\nwhere $x_{i}$ is the position of the ion $i$ and $K$ is the Coulomb interaction strength between two mobile ions. The lattice energy landscape $\\phi$ considered in the main text (Fig. 4a,b) is defined as follows. The energy landscape in Fig. 4a is given by \n\n$$\n\\phi_{\\mathrm{a}}(x)=E_{\\mathrm{a}}\\cdot\\frac{\\cos\\theta-0.25\\cos2\\theta-C_{1}}{C_{2}},\n$$ \n\nwhere $\\theta=2\\pi x/L-\\pi$ and the normalization factors $C_{1}$ and $C_{2}$ are $-1.25$ and 2.00, respectively. The highest point of the energy landscape is $E_{\\mathrm{a}}=0.6\\mathrm{eV}$ , which is set similar to the single Li-ion energy landscape of LLZO (Fig. 3e). The energy landscape in Fig. 4b is given by \n\n$$\n\\phi_{b}(x)=E_{\\mathrm{a}}\\cdot\\frac{\\cos\\theta-1.5\\cos2\\theta-C_{1}}{C_{2}},\n$$ \n\nwhere $C_{1}=-2.50$ and $C_{2}=4.08$ . This energy landscape has the same highest energy point of $0.6\\mathrm{eV}$ , but has a higher local barrier of $0.3\\mathrm{eV}$ at the high-energy sites (Fig. 4b). \n\nMaterials. The crystal structures investigated were obtained from the Inorganic Crystal Structure Database42 and Materials Project35. The structures with disordered site occupancies were ordered using the same method used in previous studies38,39. The structure of LATP was derived from the $\\operatorname{LiTi}_{2}(\\operatorname{PO}_{4})_{3}$ structure by partially substituting Ti with Al and by inserting extra Li atoms into M2 sites (Fig. 2f). The occupancy of Al/Ti and Li were ordered to obtain the structure. \n\nData availability. The computation data to support the findings of this study is available from the corresponding author on reasonable request. \n\n# References \n\n1. Tarascon, J.-M. & Armand, M. Issues and challenges facing rechargeable lithium batteries. Nature 414, 359–367 (2001). \n2. Dunn, B., Kamath, H. & Tarascon, J.-M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n3. Wachsman, E. D. & Lee, K. T. Lowering the temperature of solid oxide fuel cells. Science 334, 935–939 (2011). \n4. Sunarso, J. et al. Mixed ionic–electronic conducting (MIEC) ceramic-based membranes for oxygen separation. J. Membr. Sci. 320, 13–41 (2008). \n5. Xu, T. Ion exchange membranes: state of their development and perspective. J. Membr. Sci. 263, 1–29 (2005). \n6. Janek, J. & Zeier, W. G. A solid future for battery development. Nat. Energy 1, \n16141 (2016). \n7. Kamaya, N. et al. A lithium superionic conductor. Nat. Mater. 10, 682–686 (2011). \n8. Seino, Y., Ota, T., Takada, K., Hayashi, A. & Tatsumisago, M. A sulphide lithium super ion conductor is superior to liquid ion conductors for use in rechargeable batteries. Energy Environ. Sci. 7, 627–631 (2014). \n9. Murugan, R., Thangadurai, V. & Weppner, W. Fast lithium ion conduction in garnet-type $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ . Angew. Chem. Int. Ed. 46, 7778–7781 (2007). conductors for Li batteries: critical review. Chem. Soc. Rev. 43, 4714–4727 (2014). \n11. Aono, H., Sugimoto, E., Sadaoka, Y., Imanaka, N. & Adachi, G.-Y. Ionic conductivity and sinterability of lithium titanium phosphate system. Solid State Ionics 40/41, 38–42 (1990). \n12. Kato, Y. et al. High-power all-solid-state batteries using sulfide superionic conductors. Nat. Energy 1, 16030 (2016). \n13. Wang, Y. et al. Design principles for solid-state lithium superionic conductors. Nat. Mater. 14, 1026–1031 (2015). \n14. Hull, S. Superionics: crystal structures and conduction processes. Rep. Prog. Phys. 67, 1233–1314 (2004). \n15. Allen, J. L., Wolfenstine, J., Rangasamy, E. & Sakamoto, J. Effect of substitution (Ta, Al, Ga) on the conductivity of $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}.\\jmath$ . Power Sources 206, 315–319 (2012). \n16. Li, Y., Han, J.-T., Wang, C.-A., Xie, H. & Goodenough, J. B. Optimizing $\\mathrm{Li^{+}}$ conductivity in a garnet framework. J. Mater. Chem. 22, 15357–15361 (2012). \n17. Thangadurai, V., Kaack, H. & Weppner, W. J. F. Novel fast lithium ion conduction in garnet-type $\\mathrm{Li}_{5}\\mathrm{La}_{3}\\mathrm{M}_{2}\\mathrm{O}_{12}$ $\\mathbf{M}=\\mathbf{N}\\mathbf{b}$ , Ta). J. Am. Ceram. Soc. 86, 437–440 (2003). \n18. Arbi, K., Rojo, J. M. & Sanz, J. Lithium mobility in titanium based Nasicon $\\mathrm{Li}_{1+x}\\mathrm{Ti}_{2-x}\\mathrm{Al}_{x}(\\mathrm{PO}_{4})_{3}$ and $\\mathrm{LiTi}_{2}\\mathrm{-}x\\mathrm{Zr}_{x}(\\mathrm{PO}_{4})_{3}$ materials followed by NMR and impedance spectroscopy. J. Eur. Ceram. Soc. 27, 4215–4218 (2007). \n19. Donati, C. et al. Stringlike cooperative motion in a supercooled liquid. Phys. Rev. Lett. 80, 2338–2341 (1998). \n20. Keys, A. S., Hedges, L. O., Garrahan, J. P., Glotzer, S. C. & Chandler, D. Excitations are localized and relaxation is hierarchical in glass-forming liquids. Phys. Rev. X 1, 021013 (2011). \n21. Xu, M., Ding, J. & Ma, E. One-dimensional stringlike cooperative migration of lithium ions in an ultrafast ionic conductor. Appl. Phys. Lett. 101, 031901 (2012). \n22. Jalem, R. et al. Concerted migration mechanism in the Li ion dynamics of garnet-type $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ . Chem. Mater. 25, 425–430 (2013). \n23. Meier, K., Laino, T. & Curioni, A. Solid-state electrolytes: revealing the mechanisms of Li-ion conduction in tetragonal and cubic LLZO by first-principles calculations. J. Phys. Chem. C 118, 6668–6679 (2014). \n24. Burbano, M., Carlier, D., Boucher, F., Morgan, B. J. & Salanne, M. Sparse cyclic excitations explain the low ionic conductivity of stoichiometric $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ . Phys. Rev. Lett. 116, 135901 (2016). \n25. Catti, M. Short-range order and $\\mathrm{Li^{+}}$ ion diffusion mechanisms in $\\mathrm{Li}_{5}\\mathrm{La}_{9}\\bigsqcup_{2}(\\mathrm{TiO}_{3})_{16}$ (LLTO). Solid State Ionics 183, 1–6 (2011). \n26. Emly, A., Kioupakis, E. & Van der Ven, A. Phase stability and transport mechanisms in antiperovskite $\\mathrm{Li}_{3}\\mathrm{OCl}$ and $\\mathrm{Li}_{3}\\mathrm{OBr}$ superionic conductors. Chem. Mater. 25, 4663–4670 (2013). \n27. Deng, Y. et al. Structural and mechanistic insights into fast lithium-ion conduction in $\\mathrm{Li}_{4}\\mathrm{SiO}_{4}–\\mathrm{Li}_{3}\\mathrm{PO}_{4}$ solid electrolytes. J. Am. Chem. Soc. 137, 9136–9145 (2015). \n28. Du, Y. A. & Holzwarth, N. Li ion diffusion mechanisms in the crystalline electrolyte $\\gamma{\\mathrm{-}}\\mathrm{Li}_{3}\\mathrm{PO}_{4}$ . J. Electrochem. Soc. 154, A999–A1004 (2007). \n29. Morgan, B. J. & Madden, P. A. Relationships between atomic diffusion mechanisms and ensemble transport coefficients in crystalline polymorphs. Phys. Rev. Lett. 112, 145901 (2014). \n30. Kendrick, E., Kendrick, J., Knight, K. S., Islam, M. S. & Slater, P. R. Cooperative mechanisms of fast-ion conduction in gallium-based oxides with tetrahedral moieties. Nat. Mater. 6, 871–875 (2007). \n31. Kresse, G. & Furthmuller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169 (1996). \n32. Perdew, J. P., Ernzerhof, M. & Burke, K. Rationale for mixing exact exchange with density functional approximations. J. Chem. Phys. 105, 9982–9985 (1996). \n33. Jain, A. et al. A high-throughput infrastructure for density functional theory calculations. Comput. Mater. Sci. 50, 2295–2310 (2011). \n34. Jain, A. et al. Formation enthalpies by mixing GGA and GGA $+\\mathrm{U}$ calculations. Phys. Rev. B 84, 045115 (2011). \n35. Jain, A. et al. Commentary: the materials project: a materials genome approach to accelerating materials innovation. APL Mater. 1, 011002 (2013). \n36. Nose, S. Constant temperature molecular dynamics methods. Prog. Theor. Phys. Suppl. 103, 1–46 (1991). \n37. Mo, Y., Ong, S. P. & Ceder, G. Insights into diffusion mechanisms in P2 layered oxide materials by first-principles calculations. Chem. Mater. 26, 5208–5214 (2014). \n38. Mo, Y., Ong, S. P. & Ceder, G. First principles study of the $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ lithium super ionic conductor material. Chem. Mater. 24, 15–17 (2012). \n39. He, X. & Mo, Y. Accelerated materials design of $\\mathrm{Na}_{0.5}\\mathrm{Bi}_{0.5}\\mathrm{TiO}_{3}$ oxygen ionic conductors based on first principles calculations. Phys. Chem. Chem. Phys. 17, 18035–18044 (2015). \n40. Van Hove, L. Correlations in space and time and born approximation scattering in systems of interacting particles. Phys. Rev. 95, 249 (1954). \n41. Compaan, K. & Haven, Y. Correlation factors for diffusion in solids. Trans. Faraday Soc. 52, 786–801 (1956). \n42. Belsky, A., Hellenbrandt, M., Karen, V. L. & Luksch, P. New developments in the Inorganic Crystal Structure Database (ICSD): accessibility in support of materials research and design. Acta Crystallogr. Sect. B: Struct. Sci. 58, 364–369 (2002). \n\n# Acknowledgements \n\nWe acknowledge the support by A. James Clark School of Engineering, University of Maryland. This research used computational facilities from the University of Maryland supercomputing resources, the Maryland Advanced Research Computing Center (MARCC), and the Extreme Science and Engineering Discovery Environment (XSEDE) supported by National Science Foundation Award No. DMR150038. We thank Alexander Epstein for reviewing the manuscript. \n\n# Author contributions \n\nY.M. conceived and oversaw the project. Y.M. and X.H. designed the computation and analyses, and X.H. performed them. Y.M. and X.H. wrote the manuscript. All authors contributed to discussions and revisions of the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: He, X. et al. Origin of fast ion diffusion in super-ionic conductors. Nat. Commun. 8, 15893 doi: 10.1038/ncomms15893 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/ \n\n$\\copyright$ The Author(s) 2017 " + }, + { + "id": "10.1038_s41929-017-0008-y", + "DOI": "10.1038/s41929-017-0008-y", + "DOI Link": "http://dx.doi.org/10.1038/s41929-017-0008-y", + "Relative Dir Path": "mds/10.1038_s41929-017-0008-y", + "Article Title": "General synthesis and definitive structural identification of MN4C4 single-atom catalysts with tunable electrocatalytic activities", + "Authors": "Fei, HL; Dong, JC; Feng, YX; Allen, CS; Wan, CZ; Volosskiy, B; Li, MF; Zhao, ZP; Wang, YL; Sun, HT; An, PF; Chen, WX; Guo, ZY; Lee, C; Chen, DL; Shakir, I; Liu, MJ; Hu, TD; Li, YD; Kirkland, AI; Duan, XF; Huang, Y", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Single-atom catalysts (SACs) have recently attracted broad research interest as they combine the merits of both homogeneous and heterogeneous catalysts. Rational design and synthesis of SACs are of immense significance but have so far been plagued by the lack of a definitive correlation between structure and catalytic properties. Here, we report a general approach to a series of monodispersed atomic transition metals (for example, Fe, Co, Ni) embedded in nitrogen-doped graphene with a common MN4C4 moiety, identified by systematic X-ray absorption fine structure analyses and direct transmission electron microscopy imaging. The unambiguous structure determination allows density functional theoretical prediction of MN4C4 moieties as efficient oxygen evolution catalysts with activities following the trend Ni > Co > Fe, which is confirmed by electrochemical measurements. Determination of atomistic structure and its correlation with catalytic properties represents a critical step towards the rational design and synthesis of precious or nonprecious SACs with exceptional atom utilization efficiency and catalytic activities.", + "Times Cited, WoS Core": 1622, + "Times Cited, All Databases": 1672, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000428619500012", + "Markdown": "# General synthesis and definitive structural identification of MN $\\phantom{+}4\\overline{1}$ single-atom catalysts with tunable electrocatalytic activities \n\nHuilong Fei1, Juncai Dong $\\oplus2$ , Yexin Feng3, Christopher S. Allen   4,5, Chengzhang Wan1, Boris Volosskiy1, Mufan Li1, Zipeng Zhao6, Yiliu Wang1, Hongtao Sun $\\oplus1$ , Pengfei $\\mathsf{A n}^{2}$ , Wenxing Chen $\\textcircled{1}$ 7, Zhiying Guo2, Chain Lee1, Dongliang Chen2, Imran Shakir8\\*, Mingjie Liu9, Tiandou ${\\mathsf{H}}{\\mathsf{u}}^{2}$ , Yadong Li7, Angus I. Kirkland4,5, Xiangfeng Duan1,10\\* and Yu Huang6,10\\* \n\nSingle-atom catalysts (SACs) have recently attracted broad research interest as they combine the merits of both homogeneous and heterogeneous catalysts. Rational design and synthesis of SACs are of immense significance but have so far been plagued by the lack of a definitive correlation between structure and catalytic properties. Here, we report a general approach to a series of monodispersed atomic transition metals (for example, Fe, Co, Ni) embedded in nitrogen-doped graphene with a common $M N_{4}C_{4}$ moiety, identified by systematic X-ray absorption fine structure analyses and direct transmission electron microscopy imaging. The unambiguous structure determination allows density functional theoretical prediction of $M N_{4}C_{4}$ moieties as efficient oxygen evolution catalysts with activities following the trend $N i>C o>F e,$ which is confirmed by electrochemical measurements. Determination of atomistic structure and its correlation with catalytic properties represents a critical step towards the rational design and synthesis of precious or nonprecious SACs with exceptional atom utilization efficiency and catalytic activities. \n\nfficient and cost-effective electrocatalysts play critical roles in energy conversion and storage1–3. Homogeneous and heterogeneous catalysts represent two parallel frontiers of electrocatalysts, each with their own merits and drawbacks4,5. Homogeneous catalysts are attractive for their highly uniform active sites, tunable coordination environment and maximized atom utilization efficiency, but are limited by their relatively poor stability and recyclability. Heterogeneous catalysts are appealing for their high durability, excellent recyclability, and easy immobilization and integration with electrodes, but usually have rather low atom utilization efficiency due to the limited surface sites accessible to reactants. To this end, considerable efforts have been devoted to developing nanoscale heterogeneous catalysts that can increase the exposed surface atoms3. However, the inhomogeneity in the distribution of particle sizes and facets poses a serious challenge for controlling active sites and fundamental mechanistic studies6,7. In contrast, homogeneous catalysts typically exhibit the well-defined atomic structure with tunable coordination environment that is essential for deciphering the catalytic reaction pathway and rational design of targeted catalysts with tailored catalytic properties8. \n\nSingle-atom catalysts (SACs) with monodispersed single atoms supported on solid substrates are recently emerging as an exciting class of catalysts that combine the merits of both homogeneous and heterogeneous catalysts9–14. However, most SACs studied to date employ metal oxides (for example, $\\mathrm{TiO}_{2},$ , $\\mathrm{CeO}_{2}$ and $\\mathrm{FeO}_{x}^{\\cdot}$ ) as supporting substrates to prevent atom aggregation15–18, which cannot be readily applied in electrocatalytic applications due to their low electrical conductivity and/or poor stability in harsh liquid-phase electrolytes (for example, strong acid or base). Atomic transitionmetal–nitrogen moieties supported in carbon (M–N–Cs) represent a unique class of SACs with high electrical conductivity and superior (electro)chemical stability for electrocatalytic applications19. In particular, Fe-based M–N–Cs have been extensively studied as electrocatalysts towards the oxygen reduction reaction (ORR) with demonstrated activity and stability approaching those of commercial $\\mathrm{Pt/C}$ catalysts20,21. In addition, as suggested by numerous theoretical studies, M–N–Cs are promising candidates for catalysing a wide range of electrochemical processes, such as hydrogen reduction/oxidation22, $\\mathrm{CO}_{2}/\\mathrm{CO}$ reduction23 and $\\Nu_{2}$ reduction24. \n\nA significant advantage of SACs is that the well-defined single atomic site could allow precise understanding of the catalytic reaction pathway, and rational design of targeted catalysts with tailored activity (in a manner similar to homogeneous catalyst design). However, this perceived advantage has been investigated theoretically23,24, but has not yet been demonstrated experimentally in M–N–Cs, largely because existing M–N–Cs were generally obtained through pyrolysis of metal-, nitrogen- and carbon-containing molecular or polymeric precursors and the as-synthesized materials are typically highly heterogeneous, concurrently containing single atomic metals along with crystalline particles, and crystalline and amorphous carbon25–28. Such structural and compositional heterogeneity poses a key obstacle to unambiguously identifying the exact atomistic structure of the active sites and to further establishing a definitive correlation with the catalytic properties that can guide the subsequent design of future generations of SACs. This issue is readily manifested by tracking the research status of Fe–N–C ORR catalysts. Despite extensive efforts, the nature of the active sites and the atomistic structure of the $\\mathrm{FeN}_{x}C_{x}$ moieties remain elusive, largely due to the difficulty in synthesizing $\\mathrm{Fe-N-C}$ catalysts free of Fe particles and the lack of an accurate method to determine the coordination configuration of the metal sites27,29. Only very recently was the porphyrin-based $\\mathrm{FeN}_{4}\\mathrm{C}_{12}$ moiety identified by $\\mathrm{\\DeltaX}$ -ray absorption fine structure (XAFS) analysis26. Additionally, it is very challenging to produce a series of closely related single atomic sites with systematically tunable compositions, which are essential for mechanistic studies. Although attempts have been made to elucidate the roles of different metals in affecting the catalytic activity of M–N–Cs, they were severely complicated by the fact that the physicochemical characteristics (for example, degree of graphitization, carbon structure, nitrogen-doping type and surface area) of the synthesized M–N–Cs are highly dependent on the metal identity and any observed differences in catalytic activity are highly convoluted with various structural characteristics30,31. These limitations represent the key challenges in establishing the exact structure-to-property correlation in SACs, which is essential for the rational design and synthesis of new SACs with tailored activities for wide ranges of electrocatalytic processes32–34. \n\nHere, we report a general approach to a series of atomic $3d$ metals embedded in nitrogen-doped holey graphene frameworks (M–NHGFs, ${\\mathrm{M}}={\\mathrm{Fe}}$ , Co or Ni), unambiguously determining their atomistic structures and correlation with electrocatalytic activity towards the oxygen evolution reaction (OER); a reaction that is essential for diverse clean energy technologies including water splitting, $\\mathrm{CO}_{2}$ reduction and rechargeable metal–air batteries2,35–37. Our studies show that different M–NHGFs adopt an identical $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety with the same local atomic coordination configuration embedded in graphene lattices, as revealed by thorough analyses of extended X-ray absorption fine structure (EXAFS) and X-ray absorption near-edge structure (XANES), and directly imaged by annular dark-field scanning transmission electron microscope (ADF-STEM). The unambiguous identification of the $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ structural configuration has allowed us to use density functional theory (DFT) to explore the catalytic properties of M–NHGFs towards OER, which predicts that the catalytic activity and mechanistic pathways are strongly dependent on the $d$ -orbital configurations of the metals with the activity trend $\\mathrm{Ni-NHGF}>\\mathrm{Co-NHGF}>\\mathrm{Fe-NHGF}.$ This is further corroborated by electrochemical measurements, which show Ni–NHGF exhibits outstanding catalytic activity and stability, demonstrating the first example of an OER catalyst based on single Ni atoms. \n\n# Results \n\nSynthesis and structural characterization of M–NHGFs. The preparation of M–NHGFs involves a two-step process (Fig. 1). In brief, an aqueous suspension of graphene oxide (GO), metal precursor and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was prepared at the desired ratio and hydrothermally treated to self-assemble into a 3D graphene hydrogel. After being freeze dried, the gel was then thermally annealed in an $\\mathrm{NH}_{3}$ atmosphere to obtain M–NHGFs. This annealing treatment further reduces graphene and incorporates nitrogen dopants into the graphene lattice as the effective binding sites for individual metal atoms. In our synthetic strategy, the use of GO as carbon substrate precursor is advantageous in that it could be mass-produced and that its reduced form exhibits rich defective sites inherited from GO, which provide tremendous numbers of vacancies for incorporating nitrogen atoms and anchoring metal atoms38. In addition, it can prevent the formation of amorphous carbon, which has proven to be a serious interfering species preventing clear atomistic imaging of the exact coordination configuration of the metal centres. The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ added in the hydrothermal treatment was employed to create inplane holes in the graphene sheet via an oxidative-etching process, which is beneficial for mass transport during catalytic processes as demonstrated in our previous studies39,40. The increased porosity in M–NHGFs compared with their non-holey counterparts, M–NGFs, was characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Brunauer–Emmett– Teller (BET) surface area analysis (Supplementary Figs.  1–3). Compositional analysis by X-ray photoelectron spectroscopy (XPS) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) reveals that the different M–NHGFs have similar nitrogen $(\\sim5\\mathrm{at\\%})$ and metal contents $(\\sim0.05\\mathrm{at\\%})$ (Supplementary Fig. 4 and Supplementary Table 1). \n\nAtomic structure analysis of M–NHGFs by XAFS and ADF-STEM. Element-selective XAFS spectroscopy, including EXAFS and XANES, is powerful for determining the coordination environment and chemical state of the absorbing centre with high sensitivity. The forms of the metal in M–NHGFs ( ${\\bf\\dot{M}}={\\bf F}{\\bf e}$ , Co and Ni) are first identified by EXAFS analysis. Figure 2a shows the EXAFS Fourier transform (FT) of all three M–NHGFs. Ni–NHGF exhibits a major peak at $1.44\\mathring\\mathrm{A}$ , which is much shorter than the $\\mathrm{Ni-O}$ peak at $1.6\\dot{5}\\mathring{\\mathrm{A}}$ for the $\\mathrm{NiO}_{6}$ octahedra in NiO reference and thus can be attributed to the backscattering between Ni and light atoms. In addition, the FT of Ni–NHGF also reveals a minor signal at $2.01\\mathring{\\mathrm{A}}$ , which overlaps partially with the Ni–Ni peak at $2.{\\overset{\\smile}{1}}8{\\overset{\\circ}{\\mathrm{A}}}$ for bulk Ni. The same observations can be made in Fe–NHGF and Co–NHGF with the minor peaks located at 2.03 and $1.92\\mathring{\\mathrm{A}}$ , respectively, which are shifted to the lower $R$ direction compared with the corresponding Fe–Fe $(2.20\\mathring\\mathrm{A})$ and $\\mathrm{Co-Co}\\ (2.17\\mathrm{\\AA})$ peaks of bulk Fe and Co. We note that such an EXAFS-FT profile, featuring the co-presence of the Gaussian-like main peak and the minor satellite peak, has never been observed in previously reported $\\mathrm{M-N-C}$ materials26,41, which turns out to be a key characteristic of the $\\mathrm{MN}_{x}\\mathrm{C}_{y}$ atomic structure adopted by M–NHGFs and will be discussed later. EXAFS wavelet transform (WT) analysis is powerful for discriminating the backscattering atoms even when they overlap substantially in $R$ -space, by providing not only radial distance resolution but also $k$ -space resolution42. In contrast to the FT analysis, WT analysis of all M–NHGFs detects only one intensity maximum at approximately $4.0\\mathring\\mathrm{A}^{-1}$ (Fig. 2b), which can be assigned to the M–N/O/C contributions (Supplementary Figs. 7–9), suggesting that the metals in M–NHGFs exist as mononuclear M centres without the presence of metal-derived crystalline structures. Increasing the metal loading could lead to the formation of metallic crystallite that could prevent an unambiguous identification of atomic-site structure (Supplementary Figs. 5–11 and Supplementary Note 1). \n\nThe coordination configurations for the $\\mathrm{MN}_{x}\\mathrm{C}_{y}$ moieties in M–NHGFs were then investigated by quantitative least-squares EXAFS curve-fitting analysis. The EXAFS spectrum of Ni–NHGF was first analysed by using three backscattering paths: Ni–N, Ni–O and $\\mathrm{Ni-C}$ , based on the EXAFS-WT results. The best-fitting analyses show clearly that the main peak at $1.44\\mathring\\mathrm{A}$ originates from $\\mathrm{Ni-N}$ and $\\mathrm{Ni-O}$ first shell coordination (Fig. $^{2\\mathrm{c},\\mathrm{d}},$ , whereas the minor satellite peak at $2.01\\mathring{\\mathrm{A}}$ is satisfactorily interpreted as Ni–C contribution. The coordination numbers of the $\\mathrm{\\DeltaN}$ and O atoms in the first coordination sphere of Ni are estimated to be 3.9 and 1.1 at distances of 1.89 and $2.{\\overset{\\cdot}{1}}0{\\overset{\\circ}{\\mathrm{A}}}$ , respectively (Supplementary Table  2), indicating a square-pyramidal configuration for the Ni–N/O bonding. A second coordination sphere by C atoms is clearly demonstrated at $2.65\\mathring{\\mathrm{A}}$ with coordination number of 4.3 (Supplementary Table 2). \n\n![](images/13fd8df2fa84c04f3a451b6d8ec8d7be2e9d841d76ee5bc9e1b78db34b18f11e.jpg) \nFig. 1 | The preparation route to M–NHGFs. The graphene oxide solution in the presence of ${\\sf H}_{2}{\\sf O}_{2}$ and metal precursors was hydrothermally treated to form a 3D graphene hydrogel. After freeze drying the hydrogel, a thermal annealing process in an $N H_{3}$ atmosphere was used to further reduce the graphene and incorporate N-dopants into the 2D graphene lattice. \n\nTogether, these analyses reveal a $\\mathrm{NiN_{4}C_{4}}$ moiety with one oxygen atom in the axial direction, as schematically shown in the inset of Fig.  2d. The same analyses on Fe–NHGF and Co–NHGF reveal that they adopt identical coordination configurations to Ni–NHGF (Supplementary Figs.  12–16, Supplementary Tables  3  and  4, and Supplementary Note 2). \n\nXANES spectroscopy has higher sensitivity to the 3D arrangement of atoms around the photo-absorber and was applied to better identify the atomic-site structures. Figure 3a–c shows the XANES profiles for Ni–NHGF, Fe–NHGF and Co–NHGF along with their corresponding reference samples. The results show that for each metal the XANES profile is significantly different from those of the corresponding references. Irrespective of the metals, the XANES profiles of all M–NHGFs are nearly identical, strongly suggesting that the same coordination environment is adopted by $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moieties in different M–NHGFs. Comparison of the first derivative XANES for Ni–NHGF, Fe–NHGF and Co–NHGF with references indicates that the stable valence states for the metals are approximately $+2,+3$ and $+2$ , respectively. Moreover, the pre-edge peak, which is due to a $1s\\mathrm{-}4p_{z}$ shakedown transition characteristic for a square-planar configuration with high $D_{4h}$ symmetry, demonstrates rather weak intensity in all M–NHGFs, indicating a broken $D_{4h}$ symmetry and calling for axial ligands. \n\nWe continued our path towards resolving the atomic-site structure in M–NHGFs by comparing simulated XANES spectra with the experimental spectra of various $\\mathrm{MN}_{x}C_{y}$ moieties. We first evaluated a previously identified porphyrin-based $\\mathrm{FeN}_{4}\\mathrm{C}_{12}$ moiety26 and a pyridinic-N-based $\\mathrm{CoN_{4}C_{8}}$ moiety41. XANES calculations performed on the porphyrin-based $\\mathrm{MN}_{4}\\mathrm{C}_{12}$ moieties, with various axial oxygen or nitrogen ligands considered (Supplementary Figs. 17–19), show that all simulated spectra are drastically different from the experimental spectra above $50\\mathrm{eV}$ above the absorption edge. Despite some improvement, the structures based on the pyridinic-N-based $\\mathrm{MN}_{4}\\mathrm{C}_{8}$ architecture also show unsatisfactory agreement (Supplementary Figs.  20–22). We then carried out another series of XANES simulation by embedding the $\\mathrm{NiN_{4}C_{4},}$ $\\mathrm{FeN_{4}C_{4}}$ and $\\mathrm{CoN_{4}C_{4}}$ moieties in the 2D graphene lattice (Supplementary Figs. 23a, 24a and 25a). In contrast to the porphyrin-based moiety and the pyridinic-N-based moiety, the graphene-enclosed $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ structural motif can be regarded as a single metal atom occupying the divacancy in the graphene lattice with coordination to four pyridinic Ns included in six-member rings. With such a divacancybased motif, the agreement is substantially improved over the entire energy range. In particular, the white line and post-edge features in Ni–NHGF, Fe–NHGF and Co–NHGF are well reproduced, but a discrepancy is still present at the pre-edge features a and $b$ . With the addition of one end-on dioxygen molecule in the axial position of the metal centre, excellent agreement is obtained; all the features for the experimental spectra are correctly reproduced, especially for the weak pre-edge peaks $^{a,b}$ and the relative intensities between the peaks $c-f$ (Fig. 3d–f). Further, it appears that the spectra are slightly influenced by the orientation of the absorbed dioxygen (six-member-ring direction versus the five-member-ring direction) (Supplementary Figs. 23b, 24b and 25b). However, when an additional N atom or end-on dioxygen were included, large discrepancies on the relative intensities between the pre-edge features and white line start to emerge (Supplementary Figs. 23c–f, $24\\mathsf{c}\\mathrm{-}\\mathsf{f},$ 25c–f). Together, these XANES simulations clearly demonstrate single metal centres with four N atoms and one adsorbed O atom in the first coordination sphere and four C atoms in the second coordination sphere (see the structure model in the inset of Fig. 3d–f), which is fully consistent with the EXAFS results. \n\nStructural refinement based on the as-determined $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety via XANES fitting reveals that the calculated spectra match excellently with the experimental spectra (Fig.  3g–i), and the bond metrics are in good agreement with those determined by EXAFS analysis and DFT prediction (Supplementary Table  5). Further, EXAFS simulations based on such divacancy-based $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety show the simulated EXAFS spectra are nearly identical to the experimental spectra (Fig. 2a), and each coordination sphere’s spectral contribution to the overall spectra can be well interpreted by the analysis of shell-by-shell EXAFS simulation (Supplementary Fig. 26). \n\nThe combination of EXAFS-WT, EXAFS-FT and XANES analyses on M–NHGFs has unambiguously revealed the implantation of the $\\mathrm{NiN_{4}C_{4},}$ $\\mathrm{FeN}_{4}\\mathrm{C}_{4}$ and $\\mathrm{CoN_{4}C_{4}}$ moieties in the 2D graphene lattices. While this divacancy-based moiety has been explored theoretically for its intriguing electronic, magnetic and catalytic properties43,44, it’s never been fully identified experimentally, which seriously hampers its fundamental and applied investigations. We note that although several previous experimental studies suggested the divacancy-based $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety11,12,45,46, there was insufficient spectroscopic evidence to verify its existence, as such structural assignments were mainly based on EXAFS spectra and none of the previously reported EXAFS spectra could well match with the simulated standard spectra of the divacancy-based $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety (Supplementary Fig. 27). Significantly, our comprehensive structural analyses provide the solid spectroscopic fingerprints of this divacancy-based $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety. The formation of this moiety could be related to the use of crystalline graphene as the carbon precursor and the fact that it causes the least geometrical distortion to the hosting graphene lattices by having the metal atom occupying the divacancy of graphene lattice. In contrast, the porphyrin-based $\\mathrm{FeN}_{4}\\mathrm{C}_{12}$ moiety (and pyridinic-N-based $\\mathrm{MN}_{4}\\mathrm{C}_{8.}$ ) cannot be easily integrated in graphene lattices26. \n\n![](images/f2e6a1bee82edc918322fb6508a7f67bf60857b9a31013e2883d63b09e7c04e5.jpg) \nFig. 2 | Structural characterizations of M–NHGFs by EXAFS spectroscopy. a, Fourier transformed magnitudes of the experimental K-edge EXAFS signals of M–NHGFs along with reference samples (solid lines). The dashed lines represent calculated spectra based on a divacancy-based $M N_{4}C_{4}$ moiety enclosed in the graphene lattice. The Fourier transforms are not corrected for phase shift. b, Wavelet transforms for the $k^{3}$ -weighted EXAFS signals of M–NHGFs with optimum resolutions at $2.0\\mathring{\\mathsf{A}}.$ The maxima at approximately $4.0\\mathring{\\mathsf{A}}^{-1}$ are associated with the $M-N/\\mathsf{O}/\\mathsf{C}$ contributions. c,d, Ni K-edge EXAFS analysis of Ni–NHGF in $k\\left(\\mathbf{c}\\right)$ and R (d) spaces. Curves from top to bottom are the Ni–N, Ni–O and Ni–C two-body backscattering signals $\\mathbb{\\chi}_{2}$ included in the fit and the total signal (red line) superimposed on the experimental signal (black line). The measured and calculated spectra show excellent agreement. The inset in d shows the structure of a $\\mathsf{N i N}_{4}\\mathsf C_{4}$ moiety derived from the EXAFS result, where the teal, red, blue and grey spheres represent Ni, O, N and C, respectively. \n\nThe atomic structures of M–NHGFs were further directly imaged by ADF-STEM. The STEM images show a uniform dispersion of the heavy metal atoms, almost exclusively in the single-atom format, as represented by bright dots, throughout the graphene matrix (Fig.  4a,b). Though most of the metal atoms are identified in the region with multi-layer stacked graphene that prevents unambiguous resolution of the atomic structure, there are cases in single-layer regions. The atomic thickness of single-layer graphene provides an ideal imaging platform for visualizing structural details at the atomic scale. As demonstrated in the high-resolution STEM images (Fig.  4c–e), atomic structures within single-layer graphene can be clearly resolved and the observed coordination configurations of the atomic metals apparently match well with the $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moieties derived from XAFS studies. In addition, the arrangement of the light elements near the metal site and the overall graphene honeycomb lattice structure remain largely undistorted, which further excludes the existence of the porphyrinic structure or pyridinicN-based structure in M–NHGFs, since they can only form in strongly disordered graphene lattice or between graphene zigzag edges26,41. \n\nTheoretical and experimental evaluation on OER activity. Although Fe-, Co- and Ni-based oxides and derivatives are intensively studied as OER catalysts, the size dependence of electronic structure and catalytic reactivity suggests that the atomic metals within M–NHGFs could have different catalytic behaviour47. In addition, the catalytic properties of SACs can be tuned by a ligand–field effect, which differs depending on the identity of the metal centres and their interaction with the coordination configuration. The well-defined atomistic structure and the adoption of the identical $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety by different metals provide us an ideal model system to probe the effects of the metal centres in determining the catalytic activity (both theoretically and experimentally). To this end, DFT calculations were conducted to explore M–NHGFs as potential OER catalysts and elucidate the roles of metals in influencing the electronic nature of the atomic sites and consequently the OER energetics. Consistent with prior studies48, we assumed a four-step OER mechanism that proceeds through $\\mathrm{OH^{*}}$ , ${}^{\\mathrm{O^{*}}}$ , ${\\mathrm{OOH^{*}}}$ and ${\\mathrm{~O}}_{2}^{*}$ (the asterisk denotes the adsorption site). As suggested by previous DFT calculations by us and others49–51, the C atoms close to $\\mathrm{\\DeltaN}$ in nitrogen-doped carbon catalysts are the preferential binding sites for the oxygen intermediates rather than the $\\mathrm{\\DeltaN}$ itself due to dopinginduced charge redistribution. Therefore, we considered both the M and C in $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moieties as possible absorption sites for the intermediates. For each intermediate, the preferred absorption location (M or C) can be determined by the difference in absorption energy between these two sites (see Supplementary Table 6). It can be concluded that whether the C atoms participate in the OER process depends strongly on the number of $d$ electrons $(N_{d})$ of the metal in $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moieties. Specifically, for Fe $(N_{d}=6)$ and Co $(N_{d}=7)$ , all intermediates bind more strongly at the M site than the C site and therefore the reaction proceeds through the single-site mechanism (Fig. 5a). On the other hand, for Ni $(N_{d}=8)$ ), ${{\\cal O}^{*}}$ and $\\mathrm{OH^{*}}$ prefer to reside at the C site, while the $\\mathrm{\\Gamma_{OOH^{*}}}$ is favourably adsorbed on the M atom. This reaction pathway is referred to as the dual-site mechanism (Fig. 5b). The calculated energy diagrams of the OER at $1.23\\mathrm{V}$ for the different M–NHGFs following the suggested reaction pathways are presented in Fig. 5c. One important parameter that can be used to evaluate the catalytic activity is the limiting reaction barrier, which is determined from the free energy of the rate-determining step (RDS). For Fe–NHGF, the RDS is the oxidation of ${{\\mathrm{O^{*}}}}$ to $\\mathrm{\\Gamma_{OOH^{*}}}$ with limiting barrier as large as $0.97\\mathrm{eV.}$ In addition, the free energy of the intermediates for Fe–NHGF are most negative among all studied catalysts, suggesting that the chemical adsorption of the intermediates is very strong, leading to a high activation barrier for the reaction to proceed. For Co–NHGF, the RDS is the oxidation of ${\\mathrm{OH^{*}}}$ to ${{\\cal O}^{*}}$ with much lower limiting barrier of $0.52\\mathrm{eV.}$ The Ni–NHGF with dual-site mechanism shows the smallest limiting barrier of $0.42\\mathrm{eV},$ with the formation of ${\\mathrm{OOH}}^{*}$ as the RDS. The desorption of ${\\mathrm{O}}_{2}^{*}$ from the absorption site is the last step and its energy barrier is largest for Fe–NHGF, followed by Co–NHGF and Ni–NHGF. For comparison, we also included the energy diagram of Ni–NHGF with the single-site mechanism, which gives a significantly larger limiting barrier of $1.24\\mathrm{eV},$ , highlighting the critical role of the C atoms in facilitating the OER kinetics of Ni–NHGF. The energy diagrams for these three different catalysts at their respective minimum potential, where all steps become downhill, are shown in Supplementary Fig. 28. Further, by correlating the overpotential and descriptor (the difference between free energy of ${{\\cal O}^{*}}$ and $\\mathrm{OH^{*}}$ ), a typical volcano plot was constructed, where the $\\mathrm{NiN_{4}C_{4}}$ (dual-site mechanism) was located at the peak position and thus identified as the most active OER catalyst (Supplementary Fig. 29). Additional calculations performed on the $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moieties in the presence of the axial dioxygen molecule show the activity trend remains ${\\mathrm{Ni}}{>}{\\mathrm{Co}}>{\\mathrm{Fe}}$ (Supplementary Fig.  30). Our simulation results indicate that the catalytic activity and reaction pathways are strongly dependent on the metal identity in M–NHGFs. \n\n![](images/d7609771d58627f2fdd895230e2c2713a79c5ecda8a7e48a0e3c1b56d50cd6b7.jpg) \nFig. 3 | Structural characterization by XANES spectroscopy on M–NHGFs. a–c, The experimental K-edge XANES spectra and first derivative curves (insets) of M–NHGFs and reference samples (bulk metal and metal oxide). d–f, Comparison between the experimental K-edge XANES spectra of M–NHGFs and the theoretical spectra calculated based on $M N_{4}C_{4}$ moieties embedded in the 2D graphene lattice. Some of the main features reproduced are highlighted at points a–f. The teal, golden and plum spheres represent Ni, Fe and Co, respectively, and the blue, red and grey spheres represent N, O and C, respectively. g–i, Comparison between the experimental XANES spectra (black dotted lines) for M–NHGFs and the best-fit theoretical spectra (solid red lines). The insets show the geometrically refined $M N_{4}C_{4}$ structure. \n\n![](images/6b29242db8b40e18c18cfcaf07b8635e66acd189cd02279ab59a1ab0f032ceae.jpg) \nFig. 4 | Atomic structure characterizations of M–NHGFs by ADF-STEM. a,b, Uniform distribution of single metal atoms dispersed in the graphene matrix revealed by low (a) and high (b) magnification TEM images. The circle and arrow indicate some typical individual metal atoms in multi-layer and single-layer regions of the graphene support, respectively. Scale bars, 5 nm (a); 2 nm (b). c–e, High-resolution TEM images enable the direct visualization of the atomic metals of Ni (c), Fe (d) and Co (e) embedded in the 2D graphene lattice. The overlaid schematics represent the structural models determined from XAFS analysis. Scale bars, $0.5\\mathsf{n m}$ . The bright region at the top part of d is attributed to out-of-focus thick graphene layers or non-planar flakes. \n\nWe then proceeded to evaluate the OER catalytic activities of M–NHGFs by electrochemical measurements. Figure  5d shows the linear sweep voltammetry (LSV) for different M–NHGFs along with a metal-free NHGF. A precious-metal-based OER catalyst, ${\\mathrm{RuO}}_{2}/{\\mathrm{C}},$ was also included for reference purpose. The NHGF exhibits inferior OER activity and the overpotential at a current density of $10\\mathrm{mAcm}^{-2}$ $(\\eta_{10})$ is as large as $494\\mathrm{mV}.$ The addition of metals results in differing degrees of activity increase: $_{\\mathrm{Ni>Co>Fe}}$ . Specifically, the Ni–NHGF catalyst shows an onset potential of $1.43\\mathrm{V}$ (defined as the potential at $0.5\\operatorname{mA}\\mathrm{cm}^{-2}.$ ) and its $\\eta_{10}$ is $331\\mathrm{mV},$ much smaller than those of Co–NHGF $(402\\mathrm{mV})$ and Fe–NHGF $(488\\mathrm{mV})$ . This experimentally observed trend is consistent with the DFT-predicted trend. Optimizations of synthetic conditions reveal that the catalytic activity of Ni–NHGF is sensitive to annealing temperature and Ni concentration (Supplementary Figs. 31 and 32). In addition, acid-leaching treatment did not lead to a decrease in OER activity, confirming the absence of Ni nanocrystallines (Supplementary Fig.  33). Control experiments on the non-holey Ni–NGF suggest that the porous structure introduced by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ etching leads to improved OER activity in Ni–NHGF, which can be attributed to the enhanced mass-transport properties (Supplementary Fig. 34). To put it into context, the $\\eta_{10}$ value of Ni–NHGF is superior or comparable to most of the documented nanoparticulate Ni catalysts, such as Ni/NiO(OH) particles embedded in nitrogen functionalized carbon $(390\\mathrm{mV})^{52}$ , nickel vanadium layered double hydroxide (NiV-LDH) $(318\\mathrm{mV})^{53}$ , exfoliated NiCoLDH $(334\\mathrm{mV})^{54}$ , $\\mathrm{NiCoO}_{x}$ thin film $(380\\mathrm{mV})^{55}$ , and nickel carbide on conductive carbon $\\mathrm{(Ni_{3}C/C)}$ $(316\\mathrm{mV})^{56}$ . \n\nThe OER kinetics were then analysed by Tafel plots (Fig.  5e). The Tafel slope for Ni–NHGF $\\mathrm{\\Delta}63\\mathrm{mV}$ per decade) is much smaller than Co–NHGF ( $\\mathrm{80mV}$ per decade) and Fe–NHGF ( $\\mathrm{164mV}$ per decade). The metal-free NHGF has an even larger Tafel slope of $175\\mathrm{mV}$ per decade, suggesting important roles for metals in promoting the reaction kinetics. The Faradaic efficiency of Ni–NHGF was determined to be ${\\sim}99.2\\%$ by rotating ring-disk electrode (RRDE) technique (Supplementary Figs.  35 and 36), indicating exclusive generation of $\\mathrm{O}_{2}$ during the OER process through a four-electron process, that is, $4\\mathrm{OH^{-}}\\to\\mathrm{O}_{2}+2\\mathrm{H}_{2}\\mathrm{O}+4\\mathrm{e}^{-}$ . To evaluate the intrinsic activity of Ni–NHGF, we estimated the turnover frequency (TOF), which indicates the activity of a catalyst on the per-active-site basis. For the estimation, it is assumed all the Ni atoms participate in catalysis and one Ni atom contributes to one active site. The TOF of the Ni–NHGF catalyst at different overpotentials is presented along with the TOF values of some recently reported non-precious-metal catalysts (Fig. 5f)6,53,54,57–60. The comparison results clearly show that Ni–NHGF is among the most active OER catalysts with the highest atom utilization efficiency. For example, at $0.3\\mathrm{V}$ overpotential, the TOF of Ni–NHGF $(0.72s^{-1})$ is two orders of magnitude higher than that of $\\boldsymbol{\\upalpha}{\\cdot}\\mathrm{Ni}(\\mathrm{OH})_{2}$ $(0.0024s^{-1})^{59}$ . Furthermore, this value is even higher than  that of G–CoFeW $(0.46\\mathsf{s}^{-1})^{58}$ and comparable to that of NiCo-UMOFNs $(0.86\\mathsf{s}^{-1})^{6}$ , which represent the most active OER catalysts reported to date. \n\nStability tests by both electrochemical measurements and structural characterization of XAFS suggest that the Ni atom and its coordinating matrix are robust enough to withstand the OER operation condition (Supplementary Figs.  37–39 and Supplementary Note  3). Lastly, Ni–NHGF is also highly active towards ORR in alkaline media and therefore can serve as a superior bifunctional electrocatalyst (Supplementary Figs.  40 and 41, and Supplementary Table  7). To demonstrate its potential for practical applications, a two-electrode rechargeable $Z\\mathrm{n}$ –air battery was fabricated from Ni–NHGF and it shows a superior peak power density $(158\\mathrm{mW}\\mathrm{cm}^{-2})$ ) compared with that from precious $\\mathrm{Pt/C\\mathrm{-}R u O_{2}/C}$ catalysts $(98\\mathrm{mW}\\mathrm{cm}^{-2},$ ) (Supplementary Fig.  42), which can be ascribed to its high catalytic activity as well as hierarchical porosity for improved mass transport. \n\n![](images/a7b19d68abd6c9576c44386261b88a7920cc242ebb90234e002a7422ea4bb06b.jpg) \nFig. 5 | Evaluation of catalytic activity by DFT simulations and electrochemical measurements. a,b, Proposed reaction scheme with the intermediates having optimized geometry of the single-site (a) and dual-site mechanisms (b) towards OER. c, Free energy diagram at $1.23\\vee$ for OER over Fe–NHGF, Co–NHGF and Ni–NHGF with a single-site mechanism, and Ni–NHGF with a dual-site mechanism. The highlights indicate the rate-determining step with the values of the limiting energy barrier labelled. d, OER activity evaluated by LSV in 1 M KOH at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ for NHGF, Fe–NHGF, Co–NHGF and Ni–NHGF along with a $\\mathsf{R u O}_{2}/\\mathsf C$ catalyst as a reference point. The data are presented with current–resistance (iR) correction. e, The Tafel plots of the corresponding catalysts shown in d. f, TOF values of the Ni–NHGF catalyst and other recently reported OER catalysts based on earth-abundant metals, including NiCo–UMOFNs (ref. 6), G–CoFeW (ref. 58), MnCo–LDH (ref. 60), ${\\mathsf{N i C e O}}_{x}.$ –Au (ref. 57), exfoliated NiFe–LDH (ref. 54), NiV–LDH (ref. 53) and $(\\mathsf{x}-\\mathsf{N i}(\\mathsf{O H})_{2}$ (ref. 59). The TOF values are based on the total amounts of metal for all catalysts. \n\n# Conclusions \n\nIn summary, we have developed a rational and general strategy to a series of monodispersed atomic metals embedded in nitrogendoped graphene lattices. By combining EXAFS and XANES analyses with direct STEM imaging, we unambiguously identified that the resulting M–N–Cs ${\\mathrm{~\\boldmath~\\mathcal~{~M~}~}}={\\mathrm{Fe}}$ , Co, Ni) adopt an identical $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ configuration with single metal atoms occupying the divacancies in the graphene lattice, such that the least distortion to the 2D graphene lattice  is exerted. Significantly, the presence of the well-defined $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moieties in different M–NHGFs provides an ideal model system to probe and quantitatively establish the correlation between the atomistic structure of the metal centres and the catalytic properties, which, for example, successfully identified Ni–NHGF to be a highly active and stable OER catalyst, as demonstrated by both theoretical calculations and experimental studies. With the high intrinsic activity, the overall OER catalytic performance of Ni–NHGF may be further improved by increasing the metal loading and thus the density of active sites. Our study defines a general and efficient synthetic strategy to a broad class of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ - based $\\mathrm{\\Delta\\M-N-C}$ catalysts for diverse electrocatalytic applications, including OER and ORR, hydrogen oxidation and evolution, $\\mathrm{CO}_{2}$ reduction and $\\Nu_{2}$ reduction. \n\n# Methods \n\nSynthesis of M–NHGFs. All chemicals were purchased from Sigma-Aldrich unless otherwise specified. Graphene oxide (GO) was synthesized by oxidation of natural graphite flakes (100 mesh) following a modified Hummers’ method61. The M–NHGFs ${\\bf\\dot{M}}={\\bf F}{\\bf e}$ , Co, Ni) were synthesized using a two-step process. In a typical procedure for synthesizing Ni–NHGF, $50\\upmu\\mathrm{l}$ of $3\\mathrm{mg}\\mathrm{ml^{-1}N i C l_{2}{\\cdot}6H_{2}O}$ and $15\\upmu\\mathrm{l}$ of $30\\%$ $\\mathrm{H}_{2}\\mathrm{O}_{2}$ were added into $10\\mathrm{ml}$ of $2\\mathrm{mg}\\mathrm{ml}^{-1}$ GO suspension and sonicated for $^\\mathrm{1h}$ . The mixed suspension was hydrothermally treated at $180^{\\circ}\\mathrm{C}$ for $^{6\\mathrm{h}}$ , forming a porous hydrogel. After freeze drying, the gel was placed in the center of 1-inch quartz tube furnace and annealed at $900^{\\circ}\\mathrm{C}$ for $^\\mathrm{1h}$ with flows of Ar $(100\\ s c c\\mathrm{{cm})}$ and $\\mathrm{NH}_{3}$ ( $50\\mathrm{sccm})$ to obtain Ni–NHGF. As control samples, non-holey Ni–NGF was prepared without the addition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ during the hydrothermal process and metal-free NHGF was prepared without the addition of Ni precursor. Fe–NHGF and Co–NHGF were prepared by the same procedure but changing the metal precursor to $2\\mathrm{mg}\\mathrm{ml^{-1}F e C l_{3}}$ and $3\\mathrm{mg}\\mathrm{ml^{-1}C o C l_{2}{\\cdot}6H_{2}O},$ , respectively. \n\nMaterial characterizations. The morphology and structure of the resulting materials were characterized by SEM (Zeiss Supra 40VP), TEM (Titan S/TEM3 FEI), X-ray diffraction (XRD, Panalytical X’Pert Pro X-ray Powder Diffractometer) and XPS (Kratos AXIS Ultra DLD spectrometer). Quantitative analysis of metal loading was carried out using inductively coupled plasma atomic emission spectroscopy (TJA RADIAL IRIS 1000 ICP-AES). The BET surface area and DFT pore size distribution were measured by Micromeritics ASAP 2020. ADF STEM imaging was performed on an aberration-corrected JEOL ARM300CF STEM equipped with a JEOL ETA corrector operated at an accelerating voltage of $80\\mathrm{kV}$ located in the electron Physical Sciences Imaging Centre (ePSIC) at Diamond Light Source. ADF imaging was performed at $80\\mathrm{keV}$ with a CL aperture of $30\\upmu\\mathrm{m}$ , convergence semiangle of $24.8\\mathrm{mrad}$ , beam current of $12\\mathrm{pA}$ , and acquisition angle of 27–110 mrad. \n\n$\\mathbf{X}$ -ray absorption data collection, analysis and modelling. Fe, Co and Ni K-edge X-ray absorption spectra were acquired under ambient conditions in fluorescence mode at beamlines 1W1B and 1W2B of the Beijing Synchrotron Radiation Facility (BSRF), using a Si (111) double-crystal monochromator. The storage ring of BSRF was operated at $2.5\\mathrm{GeV}$ with a maximum current of $250\\mathrm{mA}$ in decay mode. While the energy was calibrated using $\\mathrm{Fe/Co/Ni}$ foil, the incident and fluorescence X-ray intensities were monitored by using standard $\\Nu_{2}$ -filled ion chambers and Ar-filled Lytle-type detector, respectively. A detuning of about $25\\%$ by misaligning the silicon crystals was performed to suppress the high harmonic content. The in situ XAFS experiments in the operando state were performed using a bespoke plastic electrochemical cell under the fluorescence model. The cell had flat walls $(\\sim4.5\\mathrm{cm}$ wide) with a single circular hole of $0.8\\mathrm{cm}$ diameter. Thin carbon paper ${\\mathrm{70}}\\upmu\\mathrm{m}$ thick) was loaded with Ni–NHGF catalysts and used as the working electrode, which was kept in contact with a slip of copper tape and fixed with epoxy glue to the exterior of the wall of the cell, over the $0.8\\mathrm{cm}$ hole, with the Ni–NHGF layer facing inward. A platinum spiral wire and a $\\mathrm{Hg/Hg_{2}C l_{2}};$ , KCl (saturated) electrode were used as counter electrode and reference electrode, respectively. During the measurement, a series of potentials controlled by an electrochemical workstation were applied to the working electrode in $1\\mathrm{M}\\mathrm{KOH}$ solution. The XAFS raw data were background subtracted, normalized, and Fourier transformed by standard procedures within the ATHENA program62,63. Least-squares curve fitting analysis of the EXAFS $\\chi(\\boldsymbol{k})$ data was carried out using the ARTEMIS program62, based on the EXAFS equation, which expressed in terms of single- and multiple-scattering expansion is: \n\n$$\n\\begin{array}{l}{{\\displaystyle\\chi(k)~=~S_{0}^{2}\\sum_{T}\\frac{N_{T}\\mid F_{\\mathrm{eff}}^{T}(\\pi,k,R_{T})\\mid}{k R_{T}^{2}}e x p\\Bigl(-2R_{T}/\\lambda(k)-2k^{2}\\sigma_{_T}^{2}\\Bigr)}}\\\\ {{\\displaystyle s i n\\bigl(2k R_{T}+\\phi_{_T}(k)+2\\delta_{c}(k)\\bigr)}}\\end{array}\n$$ \n\nwhere $k={\\sqrt{2m_{e}(E{-}E_{0})}}$ represents a scale conversion from the photo energy $(E,{\\mathrm{eV}})$ to the wave number $(k,\\mathring\\mathrm{A}^{-1})$ of the excited photoelectron, as measured from absorption threshold $E_{0}$ . The sums are over a series of equivalent scattering paths, $T$ , which originate at the central absorption atoms, travelling to one or more of the neighbouring atoms, and then back to the original central atoms. The equivalent scattering paths, with a degeneracy of $N_{{\\scriptscriptstyle{P}}}$ are grouped according to the atomic number of the passed atoms and the total path length $R_{\\varGamma}$ of the photoelectron. The dependence of the EXAFS oscillatory structure on path length and energy is reflected by the $s i n\\big(2k R_{T}+\\phi_{r}(k)_{\\scriptscriptstyle{r}}+2\\delta_{c}(k)\\big)$ term, where $\\phi_{\\/Gamma}(\\boldsymbol{k})$ is the effective scattering phase shift for path $\\boldsymbol{{\\cal T}}$ ​. $F_{\\mathrm{eff}}^{I^{-}}(\\pi,k,R_{I^{-}}^{'})$ denotes the effective scattering amplitude for path $T$ . The amplitude decay due to inelastic scattering is captured by the exponential term $e x p(-2R_{\\varGamma}/\\lambda(k))$ , where $\\lambda(k)$ is the photoelectron mean free path. The additional broadening effect due to thermal and structural disorder in absorber–scatterer(s) path lengths is accounted for by the Debye–Waller term $e x p\\Bigl(-2k^{2}\\sigma_{_{T}}^{2}\\Bigr)$ . $S_{0}{}^{2}$ is a many-body amplitude-reduction factor due to excitation in response to the creation of the core hole. In this work, although the scattering amplitudes and phase shifts for all paths, as well as the photoelectron mean free path, were theoretically calculated by ab-initio code FEFF9.0 (ref. 64), the variable parameters that are determined by using the EXAFS equation to fit the experimental data are $N_{{\\scriptscriptstyle{F}}},R_{{\\scriptscriptstyle{F}}},$ and ${\\sigma_{\\itGamma}}^{2}$ . The $S_{0}^{\\ 2}$ parameter was determined in the fit of $\\mathrm{Fe/Co/Ni}$ standards, and used as fixed value in the rest of the EXAFS models. All fits were performed in the $R$ space with $k$ -weight of 2. The EXAFS R-factor $(R_{\\mathrm{f}})$ which measures the percentage misfit of the theory to the data, was used to evaluate the goodness of the fit. The best-fit results are shown in Supplementary Figs. 12–16, with the fitting parameter values listed in Supplementary Tables 2–4. \n\nThe Fe, Co and Ni K-edge theoretical XANES calculations were carried out with the FDMNES code in the framework of real-space full multiple-scattering (FMS) scheme using Muffin-tin approximation for the potential64–66. The energydependent exchange-correlation potential was calculated in the real Hedin–Lundqvist scheme, and then the spectra convoluted using a Lorentzian function with an energy-dependent width to account for the broadening due both to the core–hole width and to the final state width. The $\\mathrm{MN}_{x}\\mathrm{C}_{y}$ $(\\mathrm{M}=\\mathrm{Fe}$ , Co or Ni) moieties were built based on three typical architectures, namely porphyrin-based, pyridinic-N-based ones, and those enclosed in a graphene sheet. To avoid artificial biases, all models were first optimized by DFT calculation. The probability of various axial oxygen or nitrogen ligands was also considered in the calculation. Satisfactory convergence for the cluster sizes had been achieved. Additional EXAFS simulations based on the porphyrin-based moiety and divacancy-based $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ moiety were performed with FEFF9.0, and the thermal disorder was taken into account by using the correlated Debye model with Debye temperature of $475\\mathrm{K}$ . \n\nQuantitative XANES fitting was carried out with the MXAN code in the framework of the full MS scheme67,68. The potential calculation was consistent with FDMNES. Inelastic processes were taken into account by a convolution with a broadening Lorentzian function having an energy-dependent width of the form ${\\Gamma(E)=\\hat{\\Gamma_{\\mathrm{c}}}+\\hat{\\Gamma_{\\mathrm{mfp}}}(E)}$ in which the constant part, $\\boldsymbol{{\\cal T}}_{\\mathrm{e}},$ takes care of both the core–hole lifetime and the experimental resolution, while the energy-dependent term represents intrinsic and extrinsic inelastic processes. Minimization of the M–NHGF XANES spectra has been carried out starting from the structures provided by DFT calculation. The fitting quality was evaluated using the square residue function $(R_{\\mathrm{sq}})$ , where a statistical weight of 1 and a constant experimental error of $1.2\\%$ were used. \n\nDFT modelling. The spin-polarized DFT calculations were performed by using the Vienna ab initio Simulation Package $\\mathrm{(VASP)^{69,70}}$ . The Kohn–Sham wave functions were expanded in a plane wave basis set with a cutoff energy of $550\\mathrm{eV}.$ The projector-augmented wave (PAW) method and PBE potential for the exchangecorrelation functional were used. The Brillouin zone was sampled by the $3\\times3\\times1$ Monkhorst–Pack $k$ -point mesh. All atoms were allowed to relax until the forces fell below $0.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . We employed a graphene supercell with surface periodicity of $6\\times6$ including 72 atoms as a basis to construct the M–NHGFs moieties. A vacuum region of $15\\mathrm{\\AA}$ was created to ensure negligible interaction between mirror images. The ZPE and entropy corrections were included by calculating the phonons by the using the Phonopy71. \n\nThe overpotentials were evaluated using a previously described approach72. The OER occur via the following steps: \n\n$$\n4\\mathrm{OH}^{-}+\\mathrm{\\Omega}^{*}\\rightarrow\\mathrm{{}^{*}O H}+3\\mathrm{OH}^{-}+\\mathrm{{}~e^{-}}\n$$ \n\n$$\n\\mathrm{\\mathrm{^{*}O H}}+3\\mathrm{OH}^{-}+\\mathrm{e}^{-}\\rightarrow\\mathrm{^{*}O}+\\mathrm{H}_{2}\\mathrm{O}+2\\mathrm{OH}^{-}+2\\mathrm{e}^{-}\n$$ \n\n$$\n\\mathrm{\\mathrm{~\\boldmath~\\Psi~}}^{*}\\mathrm{\\boldmath~\\cal~H~}_{2}\\mathrm{\\boldmath~O~}+\\mathrm{\\boldmath~20H~}^{-}\\mathrm{\\boldmath~\\Psi~}+\\mathrm{\\boldmath~2e}^{-}\\rightarrow\\mathrm{\\mathrm{~\\boldmath~\\Psi~}}^{*}\\mathrm{OOH~}+\\mathrm{\\boldmath~H_{2}O~}+\\mathrm{\\boldmath~OH~}^{-}+\\mathrm{\\boldmath~3e}^{-}\n$$ \n\n$$\n\\begin{array}{r l}&{\\mathrm{*}_{O O H\\mathrm{~+~}H_{2}O\\mathrm{~+~}O H^{-}\\mathrm{~+~}3e^{-}\\rightarrow\\mathrm{~}^{*}O_{2}\\mathrm{~+~}2H_{2}O\\mathrm{~+~}4e^{-}\\mathrm{~}}}\\\\ &{\\mathrm{*}_{O_{2}\\mathrm{~+~}2H_{2}O\\mathrm{~+~}4e^{-}\\rightarrow\\mathrm{~O_{2}\\mathrm{~+~}2H_{2}O\\mathrm{~+~}4e^{-}\\mathrm{~+~}^{*}}}}\\end{array}\n$$ \n\nwhere $^*$ represents the preferable adsorption site for intermediates. For each step, the reaction free energy is calculated by \n\n$$\n\\Delta G=\\Delta E+\\Delta Z\\mathrm{PE}-T\\Delta S+\\Delta G_{U}+\\Delta G_{\\mathrm{pH}}\n$$ \n\nwhere $\\Delta E$ is the total energy difference between reactants and products of reactions, Δ​ZPE is the zero-point energy correction, Δ​S is the vibrational entropy change at finite temperature $T$ , $\\Delta G_{U}=-\\mathrm{e}U$ , where e is the elementary charge, $U$ is the electrode potential, $\\Delta G_{\\mathrm{pH}}$ is the correction of the $\\mathrm{H^{+}}$ free energy. \n\nThe overpotential $\\eta$ can be evaluated from the Gibbs free energy differences of each step as \n\n$$\n\\eta\\ =\\ \\operatorname{max}[\\Delta G_{1},\\Delta G_{2},\\Delta G_{3},\\Delta G_{4},\\Delta G_{5}]/e-1.23]\n$$ \n\nwhere $\\Delta G_{1},\\Delta G_{2},\\Delta G_{3},\\Delta G_{4}$ and $\\Delta G_{5}$ are the free energy of reactions (2) to (6). \n\nBesides ZPE corrections and entropy corrections, we also take the influence of water environment into account by using a bilayer water model. The interaction between water and adsorbed intermediates will stabilize $\\mathrm{OH^{*}}$ and ${\\mathrm{OOH}}^{*}$ groups on the surfaces relative to adsorbed O, due to hydrogen bonding72. \n\nIn the main text, we have discussed two kinds of possible reaction pathways, depending on adsorption site preference for ${}_{\\mathrm{O^{*}}}$ , $\\mathrm{OH^{*}}$ and ${\\mathrm{OOH}}^{*}$ intermediate (centre M atom or C atom adjacent to the M- $\\mathrm{\\cdotN_{4}}$ complex). The binding energies of ${\\mathrm{O^{*}}}$ , $\\mathrm{OH^{*}}$ and $\\mathrm{OOH^{*}}$ intermediates on the two competing adsorption sites, for Fe–NHGF, Co–NHGF and Ni–NHGF systems are summarized in Supplementary Table 6. The binding energies of adsorbed intermediate I $(I=\\mathrm{O^{*}}$ , $\\mathrm{OH^{*}}$ or OOH\\*) are calculated by equation (9): \n\n$$\nE_{\\mathrm{I}}^{b}=E_{I}{-}E{*}{-}n\\times\\mu_{\\mathrm{H}}{-}m\\times\\mu_{\\mathrm{O}}\n$$ \n\nwhere $E_{\\scriptscriptstyle I}$ is the total energies of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ -embedded graphene sheet with adsorbed intermediate $I,E_{\\l}$ \\* is the total energy of free $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ -embedded graphene sheet, $n$ and $m$ are the numbers of $\\mathrm{~H~}$ and O atoms, $\\mu_{\\mathrm{H}}$ and $\\mu_{\\mathrm{o}}$ are chemical potentials of H and O, corresponding to gas phase molecules. \n\nElectrochemical measurements. A CHI 760E electrochemical workstation (CH Instruments) was used to measure the electrocatalytic properties of the samples. The catalyst dispersion was prepared by mixing $4\\mathrm{mg}$ catalyst, $\\mathrm{1ml}$ ethanol and $40\\upmu15\\mathrm{wt\\%}$ Nafion solution and sonicating the mixture for 1 h. $14\\upmu\\mathrm{l}$ of the catalyst suspension was drop-cast onto a freshly polished glassy carbon electrode (5 mm in diameter), leading to a loading density of $0.275\\mathrm{mgcm^{-2}}$ . For reference purposes, electrode of $\\mathrm{RuO}_{2}/\\mathrm{C}$ catalyst, synthesized by oxidizing $20\\mathrm{wt\\%Ru/C}$ (Premetek) in air at $300^{\\circ}\\mathrm{C}$ for $^{\\mathrm{1h,}}$ was prepared with mass loading of $0.138\\mathrm{mgcm^{-2}}$ . The electrochemical test was performed in a three-electrode cell using Pt wire as counter electrode, Hg/HgO, 1 M NaOH as reference electrode. The measured potential against reference electrode was converted to reversible hydrogen electrode (RHE) according to $E_{\\mathrm{RHE}}{=}E_{\\mathrm{Hg/Hgo}}{+}0.915$ in 1 M KOH. For OER test, a 1 M KOH aqueous solution saturated with oxygen was used as the electrolyte. The LSV polarization curves were recorded at $5\\mathrm{mVs^{-1}}$ after 5 sweeps to reach a stable state. The Faradaic efficiency for OER was determined by rotating ring-disk electrode (RRDE) consisting of a glassy carbon disk electrode and a Pt ring electrode. Specifically, to determine the OER reaction pathway by detecting $\\mathrm{HO}_{2}^{-}$ formation, the ring electrode is kept at a constant potential of $1.5\\mathrm{V}$ versus RHE for oxidizing any $\\mathrm{HO}_{2}^{-}$ produced at the disk electrode, which was swept at $10\\mathrm{mVs^{-1}}$ in the OER potential region at a rotating speed of $1{,}500\\mathrm{r.p.m}$ . To determine the Faradaic efficiency, a constant current of $200\\upmu\\mathrm{A}$ was applied to the disk electrode, and the ring electrode was held constant at $0.4\\mathrm{V}$ vs RHE to reduce the $\\mathrm{O}_{2}$ generated at the disk. The Faradaic efficiency $(f)$ is calculated by equation (10): \n\n$$\nf{=}\\frac{I_{\\mathrm{r}}}{I_{\\mathrm{d}}N}\n$$ \n\nwhere $I_{\\mathrm{d}}$ and $I_{\\mathrm{r}}$ are the disk and ring current, respectively, and $N$ is the ring collection efficiency $(N\\sim0.2$ , calibrated with a potassium ferricyanide redox couple). \n\nThe TOF value is calculated by equation (11): \n\n$$\n\\mathrm{TOF}=\\frac{j\\times A}{4\\times F\\times m}\n$$ \n\nwhere $j$ is the current density at a given overpotential, $A$ is the geometric surface area of the electrode, $F$ is the Faraday constant, and $m$ is the number of moles of metal on the electrode. \n\nData availability. The data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\nReceived: 27 June 2017; Accepted: 8 November 2017; Published online: 8 January 2018 \n\n# References \n\n1.\t Faber, M. S. & Jin, S. Earth-abundant inorganic electrocatalysts and their nanostructures for energy conversion applications. Energy Environ. Sci. 7, \n3519–3542 (2014). \n2.\t Jiao, Y., Zheng, Y., Jaroniec, M. & Qiao, S. Z. Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions. Chem. Soc. Rev. \n44, 2060–2086 (2015). \n3.\t Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science 355, eaad4998 (2017). \n4.\t Astruc, D., Lu, F. & Aranzaes, J. R. Nanoparticles as recyclable catalysts: the frontier between homogeneous and heterogeneous catalysis. Angew. Chem. Int. Ed. 44, 7852–7872 (2005). \n5.\t Copéret, C., Chabanas, M., Petroff Saint-Arroman, R. & Basset, J.-M. Homogeneous and heterogeneous catalysis: bridging the gap through surface organometallic chemistry. Angew. Chem. Int. Ed. 42, 156–181 (2003). \n6.\t Zhao, S. et al. Ultrathin metal–organic framework nanosheets for electrocatalytic oxygen evolution. Nat. Energy 1, 16184 (2016). \n7.\t Ping, Y., Nielsen, R. J. & Goddard, W. A. The reaction mechanism with free energy barriers at constant potentials for the oxygen evolution reaction at the $\\mathrm{IrO}_{2}$ (110) surface. J. Am. Chem. Soc. 139, 149–155 (2017). \n8.\t Gorin, D. J., Sherry, B. D. & Toste, F. D. Ligand effects in homogeneous Au catalysis. Chem. Rev. 108, 3351–3378 (2008). \n9.\t Yang, X.-F. et al. Single-atom catalysts: a new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748 (2013). \n10.\tFlytzani-Stephanopoulos, M. & Gates, B. C. Atomically dispersed supported metal catalysts. Annu. Rev. Chem. Biomol. Eng. 3, 545–574 (2012). \n11.\tDeng, D. et al. A single iron site confined in a graphene matrix for the catalytic oxidation of benzene at room temperature. Sci. Adv. 1, e1500462 (2015). \n12.\tYin, P. et al. Single cobalt atoms with precise N-coordination as superior oxygen reduction reaction catalysts. Angew. Chem. Int. Ed. 55, \n10800–10805 (2016). \n13.\tLiu, J. Catalysis by supported single metal atoms. ACS Catal. 7, 34–59 (2017). \n14.\tZhang, W. & Zheng, W. Single atom excels as the smallest functional material. Adv. Funct. Mater. 26, 2988–2993 (2016). \n15.\tLin, J. et al. Remarkable performance of $\\mathrm{Ir}_{1}/\\mathrm{FeO}_{x}$ single-atom catalyst in water gas shift reaction. J. Am. Chem. Soc. 135, 15314–15317 (2013). \n16.\tYang, M., Allard, L. F. & Flytzani-Stephanopoulos, M. Atomically dispersed Au– $\\left(\\mathrm{OH}\\right)_{x}$ species bound on titania catalyze the low-temperature water-gas shift reaction. J. Am. Chem. Soc. 135, 3768–3771 (2013). \n17.\tJones, J. et al. Thermally stable single-atom platinum-on-ceria catalysts via atom trapping. Science 353, 150–154 (2016). \n18.\tLiu, P. et al. Photochemical route for synthesizing atomically dispersed palladium catalysts. Science 352, 797–800 (2016). \n19.\tBezerra, C. W. B. et al. A review of Fe–N/C and Co–N/C catalysts for the oxygen reduction reaction. Electrochim. Acta 53, 4937–4951 (2008). \n20.\tLefèvre, M., Proietti, E., Jaouen, F. & Dodelet, J.-P. Iron-based catalysts with improved oygen reduction activity in polymer electrolyte fuel cells. Science \n324, 71 (2009). electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt. Science 332, 443 (2011). \n22.\tChoi, W. I., Wood, B. C., Schwegler, E. & Ogitsu, T. Combinatorial search for high-activity hydrogen catalysts based on transition-metal-embedded graphitic carbons. Adv. Energy Mater. 5, 1501423 (2015). \n23.\tTripkovic, V. et al. Electrochemical $\\mathrm{CO}_{2}$ and CO reduction on metal-functionalized porphyrin-like graphene. J. Phys. Chem. C 117, 9187–9195 (2013). \n24.\tLi, X.-F. et al. Conversion of dinitrogen to ammonia by $\\mathrm{FeN}_{3}$ -embedded graphene. J. Am. Chem. Soc. 138, 8706–8709 (2016). \n25.\tKramm, U. I. et al. On an easy way to prepare metal–nitrogen doped carbon with exclusive presence of $\\mathrm{MeN}_{4}$ -type sites active for the ORR. J. Am. Chem. Soc. 138, 635–640 (2016). \n26.\tZitolo, A. et al. Identification of catalytic sites for oxygen reduction in iron- and nitrogen-doped graphene materials. Nat. Mater. 14, 937–942 (2015). \n27.\tSahraie, N. R. et al. Quantifying the density and utilization of active sites in non-precious metal oxygen electroreduction catalysts. Nat. Commun. 6, 8618 (2015). \n28.\tHolby, E. F. & Zelenay, P. Linking structure to function: the search for active sites in non-platinum group metal oxygen reduction reaction catalysts. Nano Energy 29, 54–64 (2016). \n29.\tSa, Y. J. et al. A general approach to preferential formation of active Fe– $\\cdot\\mathrm{N}_{x}$ sites in Fe–N/C electrocatalysts for efficient oxygen reduction reaction. J. Am. Chem. Soc. 138, 15046–15056 (2016). \n30.\tPeng, H. et al. Effect of transition metals on the structure and performance of the doped carbon catalysts derived from polyaniline and melamine for ORR application. ACS Catal. 4, 3797–3805 (2014). \n31.\tOh, H.-S. & Kim, H. The role of transition metals in non-precious nitrogen-modified carbon-based electrocatalysts for oxygen reduction reaction. J. Power Sources 212, 220–225 (2012). \n32.\tJiang, W.-J. et al. Understanding the high activity of Fe–N–C electrocatalysts in oxygen reduction: $\\mathrm{Fe}/\\mathrm{Fe}_{3}C$ nanoparticles boost the activity of $\\mathrm{Fe-N}_{x}.$ J. Am. Chem. Soc. 138, 3570–3578 (2016). \n33.\tJia, Q. et al. Spectroscopic insights into the nature of active sites in iron–nitrogen–carbon electrocatalysts for oxygen reduction in acid. Nano Energy 29, 65–82 (2016). \n34.\tFei, H. et al. Atomic cobalt on nitrogen-doped graphene for hydrogen generation. Nat. Commun. 6, 8668 (2015). \n35.\tCheng, F. & Chen, J. Metal–air batteries: from oxygen reduction electrochemistry to cathode catalysts. Chem. Soc. Rev. 41, 2172–2192 (2012). \n36.\tKim, W., McClure, B. A., Edri, E. & Frei, H. Coupling carbon dioxide reduction with water oxidation in nanoscale photocatalytic assemblies. Chem. Soc. Rev. 45, 3221–3243 (2016). \n37.\tGong, M. et al. An advanced Ni–Fe layered double hydroxide electrocatalyst for water oxidation. J. Am. Chem. Soc. 135, 8452–8455 (2013). \n38.\tLin, L.-C. & Grossman, J. C. Atomistic understandings of reduced graphene oxide as an ultrathin-film nanoporous membrane for separations. Nat. Commun. 6, 8335 (2015). \n39.\tXu, Y. et al. Holey graphene frameworks for highly efficient capacitive energy storage. Nat. Commun. 5, 4554 (2014). \n40.\tXu, Y. et al. Solution processable holey graphene oxide and its derived macrostructures for high-performance supercapacitors. Nano Lett. 15, 4605–4610 (2015). \n41.\tLiu, W. et al. Single-atom dispersed Co-N-C catalyst: structure identification and performance for hydrogenative coupling of nitroarenes. Chem. Sci. 7, 5758–5764 (2016). \n42.\tFunke, H., Scheinost, A. C. & Chukalina, M. Wavelet analysis of extended X-ray absorption fine structure data. Phys. Rev. B 71, 094110 (2005). \n43.\tKattel, S., Atanassov, P. & Kiefer, B. Stability, electronic and magnetic properties of in-plane defects in graphene: a first-principles study. J. Phys. Chem. C 116, 8161–8166 (2012). \n44.\tCheng, M.-J., Kwon, Y., Head-Gordon, M. & Bell, A. T. Tailoring metalporphyrin-like active sites on graphene to improve the efficiency and selectivity of electrochemical $\\mathrm{CO}_{2}$ reduction. J. Phys. Chem. C 119, 21345–21352 (2015). \n45.\tCui, X. et al. A graphene composite material with single cobalt active sites: a highly efficient counter electrode for dye-sensitized solar cells. Angew. Chem. Int. Ed. 55, 6708–6712 (2016). \n46.\tChen, Y. et al. Isolated single iron atoms anchored on N-doped porous carbon as an efficient electrocatalyst for the oxygen reduction reaction. Angew. Chem. Int. Ed. 56, 6937–6941 (2017). \n47.\tTyo, E. C. & Vajda, S. Catalysis by clusters with precise numbers of atoms. Nat. Nanotech. 10, 577–588 (2015). \n48.\tLiao, P., Keith, J. A. & Carter, E. A. Water oxidation on pure and doped hematite (0001) surfaces: prediction of Co and Ni as effective dopants for electrocatalysis. J. Am. Chem. Soc. 134, 13296–13309 (2012). \n49.\tFeng, Y. et al. Tuning the catalytic property of nitrogen-doped graphene for cathode oxygen reduction reaction. Phys. Rev. B 85, 155454 (2012). \n50.\tZhang, J., Zhao, Z., Xia, Z. & Dai, L. A metal-free bifunctional electrocatalyst for oxygen reduction and oxygen evolution reactions. Nat. Nanotech. 10, 444–452 (2015). \n51.\tGuo, D. et al. Active sites of nitrogen-doped carbon materials for oxygen reduction reaction clarified using model catalysts. Science 351, 361–365 (2016). \n52.\tRen, J., Antonietti, M. & Fellinger, T.-P. Electrocatalysts: efficient water splitting using a simple Ni/N/C paper electrocatalyst. Adv. Energy Mater. 5, 1401660 (2015). \n53.\tFan, K. et al. Nickel–vanadium monolayer double hydroxide for efficient electrochemical water oxidation. Nat. Commun. 7, 11981 (2016). \n54.\tSong, F. & Hu, X. Exfoliation of layered double hydroxides for enhanced oxygen evolution catalysis. Nat. Commun. 5, 4477 (2014). \n55.\tMcCrory, C. C. L., Jung, S., Peters, J. C. & Jaramillo, T. F. Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 135, 16977–16987 (2013). \n56.\tXu, K. et al. Dual electrical-behavior regulation on electrocatalysts realizing enhanced electrochemical water oxidation. Adv. Mater. 28, 3326–3332 (2016). \n57.\tNg, J. W. D. et al. Gold-supported cerium-doped $\\mathrm{NiO}_{x}$ catalysts for water oxidation. Nat. Energy 1, 16053 (2016). \n58.\tZhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n59.\tGao, M. et al. Efficient water oxidation using nanostructured $\\upalpha$ ​-nickelhydroxide as an electrocatalyst. J. Am. Chem. Soc. 136, 7077–7084 (2014). \n60.\tSong, F. & Hu, X. Ultrathin cobalt–manganese layered double hydroxide is an efficient oxygen evolution catalyst. J. Am. Chem. Soc. 136, 16481–16484 (2014). \n61.\tHummers, W. S. & Offeman, R. E. Preparation of graphitic oxide. J. Am. Chem. Soc. 80, 1339–1339 (1958). \n62.\tRavel, B. & Newville, M. ATHENA, ARTEMIS, HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 12, 537–541 (2005). \n63.\tKoningsberger, D. C., Prins, R. (eds) X-Ray Absorption: Principles, Applications, Techniques of EXAFS, SEXAFS, and XANES (Wiley, New York, 1988). \n64.\tRehr, J. J. & Albers, R. C. Theoretical approaches to X-ray absorption fine structure. Rev. Mod. Phys. 72, 621–654 (2000). \n65.\tJoly, Y. X-ray absorption near-edge structure calculations beyond the muffin-tin approximation. Phys. Rev. B 63, 125120 (2001). \n66.\tBunău, O. & Joly, Y. Self-consistent aspects of X-ray absorption calculations. J. Phys. Condens. Matter. 21, 345501 (2009). \n67.\tBenfatto, M., Congiu-Castellano, A., Daniele, A. & Della Longa, S. MXAN: a new software procedure to perform geometrical fitting of experimental XANES spectra. J. Synchrotron Radiat. 8, 267–269 (2001). \n68.\tHayakawa, K., Hatada, K., Longa, S. D., D’Angelo, P. & Benfatto, M. Progresses in the MXAN fitting procedure. AIP Conf. Proc. 882, 111–113 (2007). \n69.\tKresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993). \n70.\tKresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251–14269 (1994). \n71.\tTogo, A., Oba, F. & Tanaka, I. First-principles calculations of the ferroelastic transition between rutile-type and $\\mathrm{CaCl}_{2}$ -type $\\mathrm{SiO}_{2}$ at high pressures. Phys. Rev. B 78, 134106 (2008). \n72.\tNørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n\n# Acknowledgements \n\nY.H. acknowledges support from the Office of Naval Research under award number N000141712608. X.D. acknowledges financial support from the National Science Foundation EFRI-1433541. I.S. acknowledges the financial support from the Deanship of Scientific Research at the King Saud University for funding this research through the International Research Group Project No: IRG14-19. J.D. acknowledges support from the National Natural Science Foundation of China (grant 11605225), Youth Innovation Promotion Association, Chinese Academy of Sciences  (CAS) and Jialin Xie Foundation of the Institute of High Energy Physics, CAS. We thank Z. Zhuang for the help with in situ XAFS characterization. We thank Diamond Light Source for access and support in use of the electron Physical Science Imaging Centre (EM16967) that contributed to the results presented here. A.I.K. acknowledges financial support from EPSRC (platform grants EP/F048009/1 and EP/K032518/1) and from the EU (ESTEEM2; Enabling Science and Technology through European Electron Microscopy), 7th Framework Programme of the European Commission. Y.F. acknowledges support from the National Science Foundation of China (grants 11604092 and 11634001). M.L. acknowledges the support from the US Department of Energy, Office of Basic Energy Sciences, under contract DE-SC0012704. \n\n# Author contributions \n\nX.D. and Y.H. designed the research. H.F. performed the synthesis, most of the structural characterizations, and electrochemical tests. J.D., P.A., W.C., Z.G., D.C. and T.H. performed the XAFS measurement and analysed the EXAFS and XANES data. Y.F. and M.L. performed DFT simulations. C.W., B.V., M.L., Z.Z. and H.S. assisted in the electrochemical tests. Y.W. and C.L. assisted in the XRD and BET surface area analysis. C.S.A. conducted the aberration-corrected STEM characterization under the supervision of A.I.K. I.S. contributed to the discussion and analysis of the electrochemical testing results. The paper was co-written by X.D., H.F., J.D., Y.F., I.S. and Y.H. The research was supervised by X.D. and Y.H. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing financial interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-017-0008-y. \nReprints and permissions information is available at www.nature.com/reprints. Correspondence and requests for materials should be addressed to I.S. or X.D. or Y.H. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1038_nature26160", + "DOI": "10.1038/nature26160", + "DOI Link": "http://dx.doi.org/10.1038/nature26160", + "Relative Dir Path": "mds/10.1038_nature26160", + "Article Title": "Unconventional superconductivity in magic-angle graphene superlattices", + "Authors": "Cao, Y; Fatemi, V; Fang, S; Watanabe, K; Taniguchi, T; Kaxiras, E; Jarillo-Herrero, P", + "Source Title": "NATURE", + "Abstract": "The behaviour of strongly correlated materials, and in particular unconventional superconductors, has been studied extensively for decades, but is still not well understood. This lack of theoretical understanding has motivated the development of experimental techniques for studying such behaviour, such as using ultracold atom lattices to simulate quantum materials. Here we report the realization of intrinsic unconventional superconductivity-which cannot be explained by weak electron-phonon interactions-in a two-dimensional superlattice created by stacking two sheets of graphene that are twisted relative to each other by a small angle. For twist angles of about 1.1 degrees-the first 'magic' angle-the electronic band structure of this 'twisted bilayer graphene' exhibits flat bands near zero Fermi energy, resulting in correlated insulating states at half-filling. Upon electrostatic doping of the material away from these correlated insulating states, we observe tunable zero-resistance states with a critical temperature of up to 1.7 kelvin. The temperature-carrier-density phase diagram of twisted bilayer graphene is similar to that of copper oxides (or cuprates), and includes dome-shaped regions that correspond to superconductivity. Moreover, quantum oscillations in the longitudinal resistance of the material indicate the presence of small Fermi surfaces near the correlated insulating states, in analogy with underdoped cuprates. The relatively high superconducting critical temperature of twisted bilayer graphene, given such a small Fermi surface (which corresponds to a carrier density of about 1011 per square centimetre), puts it among the superconductors with the strongest pairing strength between electrons. Twisted bilayer graphene is a precisely tunable, purely carbon-based, two-dimensional superconductor. It is therefore an ideal material for investigations of strongly correlated phenomena, which could lead to insights into the physics of high-critical-temperature superconductors and quantum spin liquids.", + "Times Cited, WoS Core": 5816, + "Times Cited, All Databases": 6389, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000429103300032", + "Markdown": "# Unconventional superconductivity in magic-angle graphene superlattices \n\nYuan $\\mathrm{Cao^{1}}$ , Valla Fatemi1, Shiang Fang2, Kenji Watanabe3, Takashi Taniguchi3, Efthimios Kaxiras2,4 & Pablo Jarillo-Herrero1 \n\nThe behaviour of strongly correlated materials, and in particular unconventional superconductors, has been studied extensively for decades, but is still not well understood. This lack of theoretical understanding has motivated the development of experimental techniques for studying such behaviour, such as using ultracold atom lattices to simulate quantum materials. Here we report the realization of intrinsic unconventional superconductivity—which cannot be explained by weak electron–phonon interactions—in a two-dimensional superlattice created by stacking two sheets of graphene that are twisted relative to each other by a small angle. For twist angles of about $1.1^{\\circ}$ —the first ‘magic’ angle— the electronic band structure of this ‘twisted bilayer graphene’ exhibits flat bands near zero Fermi energy, resulting in correlated insulating states at half-filling. Upon electrostatic doping of the material away from these correlated insulating states, we observe tunable zero-resistance states with a critical temperature of up to 1.7 kelvin. The temperature–carrierdensity phase diagram of twisted bilayer graphene is similar to that of copper oxides (or cuprates), and includes domeshaped regions that correspond to superconductivity. Moreover, quantum oscillations in the longitudinal resistance of the material indicate the presence of small Fermi surfaces near the correlated insulating states, in analogy with underdoped cuprates. The relatively high superconducting critical temperature of twisted bilayer graphene, given such a small Fermi surface (which corresponds to a carrier density of about $10^{11}$ per square centimetre), puts it among the superconductors with the strongest pairing strength between electrons. Twisted bilayer graphene is a precisely tunable, purely carbon-based, two-dimensional superconductor. It is therefore an ideal material for investigations of strongly correlated phenomena, which could lead to insights into the physics of high-critical-temperature superconductors and quantum spin liquids. \n\nStrong interactions among particles lead to fascinating states of matter, such as quark–gluon plasmas, various forms of nuclear matter within neutron stars, strange metals and fractional quantum Hall states1–3. An intriguing class of strongly correlated materials is the unconventional superconductors, which includes materials with a range of superconducting critical temperatures $T_{\\mathrm{c}}$ , from heavy-fermion and organic superconductors with relatively low $T_{c}$ (a few to a few tens of kelvin) to iron pnictides and cuprates that can have $T_{\\mathrm{c}}>100\\mathrm{K}$ (refs 4–8). Despite extensive experimental efforts to characterize these materials, unconventional superconductors are challenging to study theoretically because the models that are typically used to describe them cannot be solved exactly, motivating the development of alternative approaches for investigating and modelling strongly correlated systems. One approach is to simulate quantum materials with ultracold atoms trapped in optical lattices, although technical advances are necessary to realize $d$ -wave superfluidity with ultracold atoms at lower temperatures than are currently possible9,10. \n\nHere we report the observation of unconventional superconductivity in a two-dimensional superlattice made from graphene—specifically, ‘magic angle’ twisted bilayer graphene (TBG). Created by the moiré pattern between the two graphene sheets, the magic-angle TBG superlattice has a periodicity of about $13\\mathrm{nm}$ , between that of crystalline superconductors (a few ångström) and optical lattices (about a micrometre). One of the key advantages of this system is the in situ electrical tunability of the charge carrier density in a flat band with a bandwidth of the order of $10\\mathrm{meV.}$ This tunability enables us to study the phase diagram of unconventional superconductivity in unprecedented resolution, without relying on multiple devices that are possibly hampered by different disorder realizations. The superconductivity that we observe has several features similar to that of cuprates, including dome structures in the phase diagram and quantum oscillations that point to small Fermi surfaces near a correlated insulator state. Furthermore, it occurs for record-low carrier densities of the order of $10^{11}\\mathrm{cm}^{-2}$ , orders of magnitude lower than the carrier densities of typical two-dimensional superconductors. The relatively high $T_{\\mathrm{c}}{=}1.7\\mathrm{K}$ for such small densities puts magic-angle TBG among the superconductors with the strongest coupling, in the same league as cuprates and the recently identified FeSe thin layers11. Our results establish magic-angle TBG as a purely carbon-based two-dimensional superconductor and, more importantly, as a relatively simple and highly tunable material that enables thorough investigation of strongly correlated physics. \n\nMonolayer graphene has a linear energy dispersion at its charge neutrality point. When two aligned graphene sheets are stacked, the hybridization of their bands due to interlayer hopping results in fundamental modifications to the low-energy band structure depending on the stacking order (AA or AB). If an additional twist angle is present between layers, a hexagonal moiré pattern consisting of alternating AA- and AB-stacked regions emerges and acts as a superlattice modulation12–16. The superlattice potential folds the band structure into the mini Brillouin zone. Hybridization between adjacent Dirac cones in the mini Brillouin zone has an effect on the Fermi velocity at the charge neutrality point, reducing it from the typical value12–18 of $10^{6}\\mathrm{m}\\mathrm{s}^{-1}$ . At low twist angles, each electronic band in the mini Brillouin zone has a four-fold degeneracy of spins and valleys, the latter inherited from the original electronic structure of graphene12,17,19. For convenience, we define the superlattice density $n_{s}=4/A$ to be the density that corresponds to full-filling of each set of degenerate superlattice bands, where $\\stackrel{\\cdot}{A}\\approx\\sqrt{3}a^{2}/(2\\theta^{2})$ is the area of the moiré unit cell, $a=0.246\\mathrm{nm}$ is the lattice constant of the underlying graphene lattice and $\\theta$ is the twist angle. In Supplementary Video, we present an animation of the way in which the band structure in the mini Brillouin zone of TBG evolves as the twist angle varies from $\\theta=3^{\\circ}$ to $\\theta=0.8^{\\circ}$ , calculated using a continuum model for one valley12. \n\nSpecial angles, namely the ‘magic angles’, exist, at which the Fermi velocity drops to zero; the first magic angle is predicted12 to be $\\theta_{\\mathrm{magic}}^{(1)}{\\approx}1.1^{\\circ}$ . Near this twist angle, the energy bands near charge neutrality, which are separated from other bands by single-particle gaps, become remarkably flat. The typical energy scale for the entire bandwidth is about $5{\\mathrm{-}}10\\mathrm{meV}$ (Fig. 1c)12,18. Experimentally confirmed consequences of the flatness of these bands are high effective mass in the flat bands (as observed in quantum oscillations) and correlated insulating states at half-filling of these bands, corresponding to $n=\\pm n_{\\mathrm{s}}/2$ , where $n{=}C V_{\\mathrm{g}}/e$ is the carrier density defined by the gate voltage $V_{\\mathrm{g}}$ (C is the gate capacitance per unit area and $e$ is the electron charge)18. These insulating states are a result of the competition between Coulomb energy and quantum kinetic energy, which gives rise to a correlated insulator at half-filling that has characteristics consistent with Mott-like insulator behaviour18. The doping density that is required to reach the Mott-like insulating states is $\\bar{n}_{s}/\\bar{2}\\approx(1.2\\dot{-}1.6)\\times10^{1\\bar{2}}{\\mathrm{cm}}^{-2}$ , depending on the exact twist angle. Here we report transport data that clearly demonstrate that superconductivity is achieved as the material is doped slightly away from the Mott-like insulating state in magic-angle TBG. We observed superconductivity across multiple devices with slightly different twist angles, with the highest critical temperature that we achieved being $1.7\\mathrm{K}.$ . \n\n# Superconductivity in magic-angle TBG \n\nIn Fig. 1a we show the typical device structure of fully encapsulated TBG devices. The two sheets of graphene originate from the same exfoliated flake, which permits a relative twist angle that is controlled precisely to within about $0.1^{\\circ}-0.2^{\\circ}$ (refs 17, 20, 21). The encapsulated TBG stack is etched into a ‘Hall’ bar and contacted from the edges22. Electrical contacts are made from non-superconducting materials (thermally evaporated Au on a Cr sticking layer) to avoid any potential proximity effects. The carrier density $n$ is tuned by applying a voltage to a Pd/Au bottom gate electrode. In Fig. 1b we show the longitudinal resistance $R_{x x}$ as a function of temperature for two magic-angle devices, M1 and M2, with twist angles of $1.16^{\\circ}$ and $1.05^{\\circ}$ , respectively. At the lowest temperature studied of $70\\mathrm{mK}$ , both devices show zero resistance, and therefore a superconducting state. The critical temperature $T_{\\mathrm{c}}$ as calculated using a resistance of $50\\%$ of the ‘normal’-state (non-superconducting) value is approximately $1.7\\mathrm{K}$ and $0.5\\mathrm{K}$ for the two devices that we studied in detail. In Fig. 1c, d we show a singleparticle band structure and density of states (DOS) near the charge neutrality point calculated for $\\theta=1.05^{\\circ}$ . The superconductivity in both devices occurs when the Fermi energy $E_{\\mathrm{{F}}}$ is tuned away from charge neutrality $\\langle E_{\\mathrm{F}}{=}0\\rangle$ ) to be near half-filling of the lower flat band $(E_{\\mathrm{{F}}}<0_{\\mathrm{{:}}}$ as indicated in Fig. 1d). The DOS within the energy scale of the flat bands is more than three orders of magnitudes higher than that of two uncoupled graphene sheets, owing to the reduction of the Fermi velocity and the increase in localization that occurs near the magic angle. However, the energy at which the DOS peaks does not generally coincide with the density that is required to half-fill the bands. In addition, we did not observe any appreciable superconductivity when the Fermi energy was tuned into the flat conduction bands $(E_{\\mathrm{{F}}}>0)$ . In Fig. 1e we show the current–voltage $\\stackrel{\\cdot}{I}-V_{x x},$ where $V_{x x}$ is the four-probe voltage, as defined in Fig. 1a) curves of device M2 at different temperatures. We observe typical behaviour for a twodimensional superconductor. The inset shows a tentative fit of the same data to a $\\dot{V}_{x x}\\propto I^{3}$ power law, as is predicted in a Berezinskii– Kosterlitz–Thouless transition in two-dimensional superconductors23. This analysis yields a Berezinskii–Kosterlitz–Thouless transition temperature of $T_{\\mathrm{BKT}}{\\approx}1.0\\mathrm{K}$ at $n{=}-1.44\\times10^{12}\\mathrm{cm}^{-2}$ , where, as before, $n$ is the carrier density induced by the gate and measured from the charge neutrality point (which is different from the actual carrier density involved in transport, as we show below). \n\n![](images/148ace75394e46eb18823a2931916cda43ed5487d920be3dd392556cf2f7eeaf.jpg) \nFigure 1 | Two-dimensional superconductivity in a graphene superlattice. a, Schematic of a typical twisted bilayer graphene (TBG) device and the four-probe $\\dot{V}_{x x},V_{\\mathrm{g}},$ I and the bias voltage $V_{\\mathrm{bias,}}^{}$ ) measurement scheme. The stack consists of hexagonal boron nitride on the top and bottom, with two graphene bilayers (G1, G2) twisted relative to each other in between. The electron density is tuned by a metal gate beneath the bottom hexagonal boron nitride layer. b, Fourprobe resistance $R_{x x}=V_{x x}/I$ ( $\\left.V_{x x}\\right.$ and $I$ are defined in a) measured in two devices M1 and M2, which have twist angles of $\\theta=1.16^{\\circ}$ and $\\theta=1.05^{\\circ}$ , respectively. The inset shows an optical image of device M1, including the main ‘Hall’ bar (dark brown), electrical contact (gold), back gate (light green) and $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate (dark grey). c, The band energy $E$ of TBG at $\\theta=1.05^{\\circ}$ in the first mini Brillouin zone of the superlattice. The bands near charge neutrality $\\left(E=0\\right)$ ) have energies of less than $15\\mathrm{meV}.$ \nd, The DOS corresponding to the bands shown in c, for energies of $-10$ to $+10\\mathrm{meV}$ (blue; $\\theta=1.05^{\\circ},$ . For comparison, the purple lines show the total DOS of two sheets of freestanding graphene without interlayer interaction (multiplied by $10^{3\\cdot}$ ). The red dashed line shows the Fermi energy $E_{\\mathrm{F}}$ at half-filling of the lower branch $(E<0)$ of the flat bands, which corresponds to a density of $n=-n_{\\mathrm{s}}/2$ , where $n_{\\mathrm{s}}$ is the superlattice density (defined in the main text). The superconductivity is observed near this half-filled state. e, Current–voltage $(V_{x x}–I)$ curves for device M2 measured at $n=-1.44\\times10^{12}{\\mathrm{cm}}^{-2}$ and various temperatures. At the lowest temperature of $70\\mathrm{mK}$ the curves indicate a critical current of approximately $50\\mathrm{nA}$ . The inset shows the same data on a logarithmic scale, which is typically used to extract the Berezinskii–Kosterlitz– Thouless transition temperature ( $T_{\\mathrm{BKT}}{=}1.0\\mathrm{K}$ in this case), by fitting to a $V_{x x}\\propto I^{3}$ power law (blue dashed line). \n\nIn contrast to other known two-dimensional and layered superconductors, the superconductivity in magic-angle TBG requires the application of only a small gate voltage, corresponding to a minimal density of only $1.2\\dot{\\times}10^{12}\\mathrm{cm}\\dot{^{-2}}$ from charge neutrality, an order of magnitude lower than the value of $1.5\\times10^{13}\\mathrm{cm}^{-2}$ in $\\mathrm{LaAlO_{3}/S r T i O_{3}}$ interfaces and of $7\\times10^{13}\\mathrm{cm}^{-2}$ in electrochemically doped $\\ensuremath{\\mathrm{MoS}}_{2}$ , among others24. Therefore, gate-tunable superconductivity can be realized in a high-mobility system without the need for ionic-liquid gating or chemical doping. In Fig. 2a we show the two-probe conductance of device M1 versus $n$ at zero magnetic field and at a 0.4-T perpendicular magnetic field. Near the charge neutrality point $(n=0)$ , a typical V-shaped conductance is observed, which originates from the renormalized Dirac cones of the TBG band structure. The insulating states centred at approximately $\\pm3.2\\times10^{12}\\mathrm{cm}^{-2}$ (which corresponds to $n_{\\mathrm{s}}$ for $\\theta=1.16^{\\circ}$ ) are due to single-particle bandgaps in the band structure that correspond to filling $\\pm4$ electrons in each superlattice unit cell. In between, there are conductance minima at $\\pm2$ and $\\pm3$ electrons per unit cell. These minima are associated with many-body gaps induced by the competition between the Coulomb energy and the reduced kinetic energy due to confinement of the electronic state in the superlattice near the magic angle; these gaps give rise to insulating behaviour near the integer fillings18. One possible mechanism for the gaps is similar to the gap mechanism in Mott insulators, but with an extra two-fold degeneracy (for the case of $\\pm2$ electrons) from the valleys in the origi­ nal graphene Brillouin zone17,18,25,26. In the vicinity of $^{-2}$ electrons per unit cell $(n\\approx-1.3\\times10^{12}{\\mathrm{cm}}^{-2}$ to $n{\\approx}-1.9\\times10^{12}\\mathrm{cm}^{-2})$ and at a superconductivity. Measurements were conducted at $70\\mathrm{mK}$ ; $V_{\\mathrm{bias}}{=}10\\upmu\\mathrm{V}.$ b, Four-probe resistance $R_{x x},$ measured at densities corresponding to the region bounded by pink dashed lines in a, versus temperature. Two superconducting domes are observed next to the half-filling state, which is labelled ‘Mott’ and centred around $-n_{s}/2=-1.58\\times10^{12}\\mathrm{{cm}^{-2}}$ . The remaining regions in the diagram are labelled as ‘metal’ owing to the metallic temperature dependence. The highest critical temperature observed in device M1 is $T_{\\mathrm{c}}=0.5\\:\\mathrm{K}$ (at $50\\%$ of the normal-state resistance). c, As in b, but for device M2, showing two asymmetric and overlapping domes. The highest critical temperature in this device is $T_{\\mathrm{c}}{=}1.7\\mathrm{K}$ . \n\n![](images/d8f60dd5d98eb87c7acd59f830aace16d5fb19240027489d6314add453b1f606.jpg) \nFigure 2 | Gate-tunable superconductivity in magic-angle TBG. a, Two-probe conductance $G_{2}=I/V_{\\mathrm{bias}}$ of device M1 $\\cdot\\theta=1.16^{\\circ},$ measured in zero magnetic field (red) and at a perpendicular field of $B_{\\perp}=0.4$ T (blue). The curves exhibit the typical V-shaped conductance near charge neutrality $\\scriptstyle\\mathbf{\\bar{\\alpha}}_{n=0}$ , vertical purple dotted line) and insulating states at the superlattice bandgaps $n=\\pm n_{\\mathrm{s}}$ , which correspond to filling $\\pm4$ electrons in each moiré unit cell (blue and red bars). They also exhibit reduced conductance at intermediate integer fillings of the superlattice owing to Coulomb interactions (other coloured bars). Near a filling of $^{-2}$ electrons per unit cell, there is considerable conductance enhancement at zero field that is suppressed in $B_{\\perp}=0.4$ T. This enhancement signals the onset of \n\n![](images/195b891457c2db3fe727eee02164a26bf0fd64f1202bc63b22084ceabffa315e.jpg) \nFigure 3 | Magnetic-field response of the superconducting states in magic-angle TBG. a, b, Four-probe resistance as a function of density $n$ and perpendicular magnetic field $B_{\\perp}$ in devices M1 (a) and M2 (b). As well as the dome structures around half-filling (similar to those in Fig. 2b, c), there are oscillatory features near the boundary between the superconducting phase and the correlated insulator phase. These oscillations are indicative of phase-coherent transport through inhomogeneous regions in the device (Methods, Extended Data Fig. 1). \nc, Differential resistance $\\mathrm{d}V_{x x}/\\mathrm{d}I$ versus d.c. bias current $I$ for different $B_{\\perp},$ measured for device M2. d, $R_{x x^{-}}T$ curves for different $B_{\\perp}$ , measured for device M1. e, Perpendicular $(B_{\\mathrm{c}\\perp})$ and parallel $(\\boldsymbol{B}_{\\mathrm{c}\\parallel})$ critical magnetic field versus temperature for device M1 (triangles; at $50\\%$ of the normal-state resistance). The fitting curves for $\\boldsymbol{B}_{\\mathrm{c}\\perp}$ correspond to Ginzburg–Landau theory for a two-dimensional superconductor. $B_{\\mathrm{c}\\parallel}$ is fitted to $B_{\\mathrm{c}\\parallel}(0)\\dot{(1-T/T_{\\mathrm{c}})}^{1/2}$ , where $B_{c\\parallel}(0)$ is the parallel critical field at zero temperature. Measurements in a–c were conducted at $70\\mathrm{mK}$ . \n\ntemperature of $70\\mathrm{mK}$ , the conductance is substantially higher at zero magnetic field than it is in a perpendicular magnetic field of $B_{\\perp}{=}0.4\\mathrm{T},$ consistent with mean-field suppression of a superconducting state by the magnetic field. Here, the maximum conductance is limited only by the contact resistance (Fig. 2a), which is absent in the four-probe measurements shown in the other figures. \n\nIn Fig. 2b, c we show the four-probe resistance of devices M1 and M2, respectively, as a function of density $n$ and temperature T. Both devices show two pronounced superconducting domes on each side of the half-filling correlated insulating state. These features are similar to those associated with high-temperature superconductivity in cuprate materials. At the base temperature, the resistance inside the domes is lower than our measurement noise floor, which is more than two and three orders of magnitude lower than the normal-state resistance for devices M1 and M2, respectively. The $I{-}V$ curves inside the domes display critical current behaviour (Fig. 1e), while being ohmic in the metallic phases outside the domes. Upon cooling while $n$ is fixed at the middle of the half-filling state, the correlated insulating phase is exhibited at intermediate temperatures (from 1 K to 4 K); at lower temperatures, both devices exhibit signs of superconductivity at the lowest temperatures. Device M1 becomes weakly superconducting, whereas device M2 becomes fully superconducting. This behaviour may be explained by a coexistence of superconducting and insulating phases due to sample inhomogeneity. \n\n# Magnetic-field response \n\nThe application of a perpendicular magnetic field $B_{\\perp}$ to a twodimensional superconductor creates vortices that introduce dissipation and gradually suppress superconductivity . In Fig. 3a, b we show the resistance of devices M1 and M2 as a function of density and $B_{\\perp}$ . Both devices exhibit a maximum critical field of approximately $70\\mathrm{mT}.$ The critical field varies strongly with doping density, showing two similar domes on each side of the half-filling state. Near the Mott-like insulating state $(n\\approx-1.47\\times10^{12}{\\mathrm{cm}}^{-2}$ to $n{\\approx}-1.67\\times10^{12}\\mathrm{cm}^{-2}$ for M1; $n{\\approx}-1.25\\times10^{12}{\\mathrm{cm}}^{-2}$ to $n{\\approx}-1.35\\times10^{12}{\\mathrm{cm}}^{-2}$ for M2), periodic oscillations of the resistance and critical current as a function of $B_{\\perp}$ appear (see Methods and Extended Data Fig. 1 for detailed analysis). The oscillations seem to originate from phase-coherent transport through arrays of Josephson junctions, similarly to superconducting quantum interference device (SQUID)-like superconductor rings around one or more insulating islands. These junction regions could be due to slight density inhomogeneities in the devices, which would cause a few islands to be doped into the insulating phase while other parts of the device remain superconducting. Apart from these oscillatory behaviours near the boundary of the half-filling insulating state, the critical current and zero resistivity inside the domes are gradually suppressed by $B_{\\perp}$ (Fig. 3c, d). \n\nIn Fig. 3e we show the critical magnetic field versus temperature for device M1, under perpendicular and parallel field configurations. The temperature dependence of the perpendicular critical field $\\boldsymbol{B}_{\\mathrm{c\\perp}}$ is well described by Ginzburg–Landau theory: $\\begin{array}{r}{B_{\\mathrm{c\\perp}}=[\\varPhi_{0}/(2\\pi\\xi_{\\mathrm{GL}}^{2})](1-T/T_{\\mathrm{c}})}\\end{array}$ , where $\\varPhi_{0}=h/(2e)$ is the superconducting flux quantum, $h$ is the Planck constant, and $\\xi_{\\mathrm{GL}}$ is the Ginzburg–Landau superconducting coherence length, determined from the fit to be $\\xi_{\\mathrm{GL}}\\approx52\\mathrm{nm}$ at $T=0$ . On the other hand, the in-plane critical field dependence is not well explained by the Ginzburg–Landau theory for thin-film superconductors, owing to the atomic thickness of TBG $\\left(0.6\\mathrm{nm}\\right)$ ; at this thickness, the theory predicts an in-plane critical field of $B_{c\\parallel}\\geq36$ T as the temperature approaches zero23. Instead, we interpret the dependence of $T_{c}$ on the in-plane magnetic field $B_{\\parallel}$ as a result of paramagnetic pair-breaking owing to the Zeeman energy. The zero-temperature in-plane critical field is extrapolated to be around $1.1\\mathrm{T}_{:}$ , which is higher than but close to the value in the Pauli limit of $\\cdot B_{\\mathrm{p}}{\\approx}1.85\\operatorname{TK}^{-1}\\times T_{\\mathrm{c}}{\\approx}0.93\\$ T, estimated on the basis of the Bardeen–Cooper–Schrieffer (BCS) gap formula $\\varDelta\\approx1.76k_{\\mathrm{B}}T_{\\mathrm{c}}$ , where $k_{\\mathrm{B}}$ is the Boltzmann constant. \n\n![](images/da44cd32c390ad6781fd39cec81238326a001e5acbb67e0903b968971afd40f6.jpg) \nFigure 4 | Temperature–density phase diagrams of magic-angle TBG metal transition at the lowest temperatures. d–f, Schematic phase diagrams at different magnetic fields. a–c, $R_{x x}–T$ curves for device M1 at different for the magnetic fields in a–c. The horizontal axis shows the relative filling densities (see legend), measured in $\\boldsymbol{B}_{\\perp}=0$ T (a), $B_{\\perp}{=}0.4\\mathrm{T}$ (b) and $n/n_{s}$ . Short coloured lines at the top and bottom of the plots denote the $B_{\\perp}=8$ T (c). The magnetic field induces a superconductor–insulator– densities plotted in a–c. \n\nWe note that the superconductor–metal transition in magic-angle TBG is not sharp, so extracting both $B_{c}$ and $T_{c}$ has some uncertainty. Qualitatively, the dependence of the in-plane critical field on temperature is $B_{\\mathrm{c}\\parallel}\\propto\\overset{\\cdot}{(1-T/T_{c})}^{1/2}$ near $T_{c}$ (ref. 27). The results described above are consistent with the existence of two-dimensional superconductivity confined in an atomically thin space. As we show in the following, the coherence length $\\xi$ is comparable to the inter-particle spacing and might suggest that the system is driven close to a crossover between a BCS-like state and a Bose–Einstein condensate (the BCS–BEC crossover). \n\n# Phase diagram of magic-angle TBG \n\nThe phase diagram of magic-angle TBG consists of correlated insulator phases and superconducting phases, which can be realized via continuous tuning of temperature, magnetic field and carrier density. Similarly to the superconducting domes discussed above, the correlated Mott-like insulator phase at half-filling also assumes a dome shape, with a transition to a metallic phase at about $4{-}6\\operatorname{K}$ and centred around half-filling density. It has been shown18 that the Mott-like insulator phase crosses over to a metallic phase upon application of a strong magnetic field of around $6\\mathrm{T}$ either perpendicular or parallel to the devices. A plausible explanation for this crossover is that the many-body charge gap is closed by the Zeeman energy. \n\nIn Fig. 4a–c we show the resistance versus temperature data measured in device M1 at zero magnetic field, $B_{\\perp}{=}0.4\\mathrm{T}$ and $B_{\\perp}=8~\\mathrm{T}$ respectively. At zero field, we observe the transition from a metal at high temperatures (above 5 K) to a superconductor. Close to half-filling there is an intermediate region in which insulating temperature dependence is observed from about $1\\mathrm{K}$ to $4\\mathrm{K}$ (above $T_{\\mathrm{c}}\\mathrm{\\cdot}$ ); we identify this region as corresponding to the Mott-like insulating phase at half-filling. In a small magnetic field $B_{\\perp}{=}0.4\\mathrm{T},$ which is above the critical magnetic field, the system remains an insulator down to zero temperature near half-filling and a metal away from half-filling. Finally, in a strong magnetic field $B_{\\perp}=8\\mathrm{T}$ , the correlated insulator phase is fully suppressed by the Zeeman effect and the system is metallic everywhere between $n{=}{-}n_{\\mathrm{s}}$ and the charge neutrality point. Our data highlight the rich phase space of metal–insulator–superconducting physics in magicangle $\\mathrm{T}\\mathrm{\\dot{B}}\\mathrm{G}^{28}$ . A schematic of the evolution of the phase diagram as the magnetic field increases is shown in Fig. 4d–f. \n\n# Quantum oscillations in the normal state \n\nWe studied quantum oscillations in the entire accessible density range, including in the vicinity of the correlated insulating state at which superconductivity occurs. In Fig. 5a, b we show the Shubnikov–de Haas oscillations in longitudinal resistance $R_{x x}$ as a function of carrier density for the hole-doped region $(E_{\\mathrm{{F}}}<0)$ for device M2. The Landau levels in a TBG superlattice typically follow $\\begin{array}{r}{n/n_{s}=N\\phi/\\phi_{0}+s,}\\end{array}$ where $\\scriptstyle\\phi=B_{\\perp}A$ is the magnetic flux that penetrates each unit cell, $\\phi_{0}=h/e$ is the (non-superconducting) flux quantum, $N=\\pm1,\\pm2,\\pm3,\\ldots$ is the Landau-level index, $s{=}0$ denotes the Landau fan that emanates from the Dirac point, and $s{=}{\\pm}1$ denote the Landau fans that result from electron-like or hole-like quasiparticles near the band edges of the single-particle superlattice bands in the mini Brillouin zone, which emanate from $\\pm n_{\\mathrm{s}}$ . The Landau levels also exhibit a four-fold degeneracy due to spins and valleys, and so the filling-factor sequence is $\\pm4,\\pm8,\\pm12,.$ … \n\nUnexpectedly, in addition to these expected Landau fans, we also observe a Landau fan that emanates from the correlated insulating state at $-n_{\\mathrm{s}}/2$ . This Landau fan has $N=-1/2,-1,-3/2,-2,\\ldots$ (that is, filling factors of $-2,-4,-6,-8,\\ldots)$ and $s{=}{-}1/2$ . The superconducting dome is distinguishable in Fig. 5a directly beneath this Landau fan, being very close to zero field and next to the correlated insulating region. Unlike commonly observed broken-symmetry states that split from a single degenerate Landau level into multiple levels, the halved filling factors appear to be intrinsic to the fan, holding down to the lowest magnetic field at which oscillations are still visible. Fractional values for $s$ have been reported in graphene superlattices as a result of Hofstadter’s butterfly, which typically occurs in much stronger magnetic fields (greater than $10\\mathrm{T}$ ) but becomes obvious only at the intersection of Landau levels with different integer $s$ (refs 29–31). Therefore, the physics of Hofstadter’s butterfly cannot explain the additional stand-alone fan observed here, which appears at fields as low as 1 T. Furthermore, the halving of the filling factors and $s$ is unlikely to be explained in a non-interacting picture of unit-cell doubling due to strain or to the formation of a charge density wave, in which case either spin or valley degeneracy must be broken. We observed the same Landau level sequence in two other magic-angle TBG devices, so it is robust against small variations in twist angle and consistent across samples (Methods, Extended Data Fig. 2). \n\n![](images/fed09f1d17d21a48509b7aca7a4d1eb7b3618e8fad5036122d0716abe49364d7.jpg) \nFigure 5 | Quantum oscillations in magic-angle TBG at high fields. a, Resistance $R_{x x}$ versus density $n$ (hole-doped side with respect to charge neutrality) and $B_{\\perp}$ in device M2. The lower half of the diagram shows the Landau-level structure deduced from the oscillations. The blue Landau fan, which originates from the charge neutrality point (CNP), and the purple Landau fan, which originates from the superlattice density $\\mathbf{\\tilde{\\rho}}_{n}=-n_{\\mathrm{s}},$ yellow shaded region), illustrate the filling-factor sequences $^{-4}$ $,-8,-12,..$ expected from the single-particle band structure with four-fold spin and valley degeneracies. The additional red fan, which originates from $-n_{s}/2$ (red shaded region), instead has a filling-factor sequence of $-2,-4,-6,\\ldots$ \nthat is not expected from the single-particle band structure. b, Temperaturedependent quantum oscillation traces $\\Delta R_{x x}/R_{x x}(B=1\\mathrm{T})$ at the carrier densities labelled A, B and C in a. From black to orange, the temperatures are 0.7 K, 1.2 K, $2.0\\mathrm{K},$ $3.0\\mathrm{K},$ , $4.2\\mathrm{K}$ , $6\\mathrm{K},$ $10\\mathrm{K},$ $15\\mathrm{K},$ $20\\mathrm{K}$ and $30\\mathrm{K}$ . c, Lifshitz– Kosevich fit (solid lines) of the normalized amplitudes of the oscillations shown in b (data points). d, e, Shubnikov–de Haas oscillation frequencies $f_{\\mathrm{SdH}}$ and effective masses $m^{*}/m_{\\mathrm{e}}$ as a function of carrier density $n$ . The error bars correspond to the $90\\%$ confidence level in fitting to the Lifshitz– Kosevich formula (see Methods for definition). $M={\\phi_{0}}\\Delta n/\\Delta f_{\\mathrm{SdH}}$ is the Fermi surface degeneracy. \n\nTo study the non-trivial origin of the Landau fan near half-filling further, we measured the effective mass from the temperature-dependent quantum oscillation amplitude according to the Lifshitz–Kosevich formula (Methods). In Fig. 5b, c we show the oscillations and oscillation amplitudes at three different densities (indicated by arrows in Fig. 5a). In Fig. 5d, e we show the oscillation frequency $f_{\\mathrm{SdH}}$ and the effective mass extracted by fitting the oscillation amplitudes to the Lifshitz–Kosevich formula. The dependence of $f_{\\mathrm{SdH}}$ on carrier density $n$ provides another perspective on the oscillations because the value of $M=\\phi_{0}\\Delta n/\\Delta f_{\\mathrm{SdH}}$ extracted from the slope $\\Delta n/\\Delta f_{\\mathrm{SdH}}$ provides the number of degenerate Fermi pockets $M$ directly. The experimental data clearly fit to $M=4$ near the charge neutrality point and for densities beyond the superlattice gap, whereas $M=2$ for the quantum oscillations that start near the correlated insulator state and right above the superconducting dome. The effective mass of the anomalous oscillations is about $(0.2\\mathrm{-}0.4)m_{\\mathrm{e}},$ where $m_{\\mathrm{e}}$ is the bare electron mass. This mass is much larger than the mass near charge neutrality (about $0.1m_{\\mathrm{e}}\\mathrm{,}$ and beyond the superlattice gap (about $0.05m_{\\mathrm{e}}^{\\cdot}$ at the same $\\Delta n$ , where $\\Delta n$ is density relative to the value of $n$ at which $f_{\\mathrm{SdH}}=0$ in Fig. 5d. \n\nThe quantum oscillations above the superconducting dome clearly indicate the existence of small Fermi surfaces that originate from the correlated insulating state, which have areas proportional to $n^{\\prime}{=}|n|-n_{\\mathrm{s}}/2$ rather than of a large Fermi surface with an area that corresponds to the density $|n|$ itself. The Hall measurements shown in Extended Data Fig. 3 also support this conclusion. Notably, similar small Fermi pockets that do not correspond to any pockets in the single-particle Fermi surface have been observed in underdoped cuprates, although their origin is debated $\\cdot^{32-34}$ . Among the possibilities, the small Fermi surface that we observe could be the Fermi surface of quasiparticles that are created by doping a Mott insulator6,35. On the other hand, the halved degeneracy might be related to spin– charge separation, as predicted in a doped Mott insulator35. More experimental and theoretical work is needed to clarify the origin of the quantum oscillations. \n\n# Discussion \n\nThe appearance of both superconductor and correlated insulator phases in the flat bands of magic-angle TBG at such a small carrier density cannot be explained by weak-coupling BCS theory. The carrier density that is responsible for $T_{\\mathrm{c}}=1.7\\:\\mathrm{K}$ is extremely small according to the quantum oscillation measurements, merely $n^{\\prime}{=}1.5\\times10^{11}\\mathrm{cm}^{-2}$ at optimal doping. To place this in the context of other superconductors, in Fig. 6 we plot $T_{\\mathrm{c}}$ against $T_{\\mathrm{F}}$ on a logari­ thmic scale for various materials, where $T_{\\mathrm{{F}}}$ is the Fermi temperature. $T_{\\mathrm{{F}}}$ is proportional to the two-dimensional carrier density $n_{\\mathrm{2D}},$ which the quantum oscillations data show to be equivalent to $n^{\\prime}$ for the superconducting dome region of magic-angle $\\mathrm{TBG}^{36}$ . Most unconventional superconductors have $T_{\\mathrm{c}}/T_{\\mathrm{F}}$ values of about $0.01\\mathrm{-}0.05$ , whereas all of the conventional BCS superconductors lie on the far right in the plot, with much smaller ratios. Magic-angle TBG is located above the trend line on which most cuprates, heavy-fermion and organic superconductors lie, with a $T_{\\mathrm{c}}/T_{\\mathrm{F}}$ value approaching that of the recently observed exotic FeSe monolayer on $\\mathrm{SrTiO}_{3}$ (Fig. 6 inset). This finding strongly suggests that the superconductivity in magic-angle TBG originates from electron correlations instead of weak electron–phonon coupling. One other frequently compared temperature is the Bose–Einstein condensation temperature for a three-dimensional boson gas $T_{\\mathrm{BEC}},$ assuming that all particles in the occupied Fermi sea pair up and condense. Cuprates and other unconventional superconductors typically have $T_{\\mathrm{c}}/T_{\\mathrm{BEC}}$ ratios of roughly 0.1–0.2. The $T_{\\mathrm{c}}/T_{\\mathrm{BEC}}$ ratio for magic-angle TBG is estimated to be up to 0.37, indicating very strong electron–electron interactions and possibly close proximity to the BCS–BEC crossover. This behaviour is in agreement with the fact that the coherence length in magic-angle TBG ( $\\xi\\approx50\\mathrm{nm}$ at optimal doping) is of the same order of magnitude as the average inter-particle distance, $(n^{\\prime})^{-1/2}{\\approx}26\\mathrm{nm}$ . \n\n![](images/c5fed603fc0f437825a2a40d1c98711a9a438eb2bbf12554734612430ba0b556.jpg) \nFigure 6 | Superconductivity in the strong-coupling limit. Logarithmic plot of critical temperature $T_{\\mathrm{c}}$ versus Fermi temperature $T_{\\mathrm{F}}$ for various superconductors36. The top axis is the corresponding two-dimensional carrier density $n_{2\\mathrm{D}}$ for two-dimensional materials or $\\ensuremath{n_{\\mathrm{3D}}}^{2/3}$ for threedimensional materials, normalized by the effective mass $m^{*}/m_{\\mathrm{e}}$ and the Fermi surface degeneracy $g$ (and a constant factor of $1/1.52$ for the threedimensional density). Two-dimensional superconductors are represented by filled circles; other symbols represent three-dimensional (but potentially two-dimensional-like) superconductors. For comparison, we also plot $T_{\\mathrm{BEC}}{=}1.04\\hbar n_{3\\mathrm{D}}/m^{*}$ for a three-dimensional bosonic gas (dashed line). Bose–Einstein condensation temperatures in $^{4}\\mathrm{He}$ , paired fermionic $^{40}\\mathrm{K}$ and paired fermionic $^{6}\\mathrm{Li}$ are shown as open pink squares36,44 ( $T_{c}$ and $T_{\\mathrm{F}}$ have both been multiplied by $10^{8}$ for $^{40}\\mathrm{K}$ and $^{6}\\mathrm{Li}$ ). The point for magic \n\nThe realization of unconventional superconductivity in a graphene superlattice establishes magic-angle TBG as a relatively simple, clean, accessible and, most importantly, highly tunable material, which could be used to study correlated electron physics. The interactions in magicangle TBG could possibly be further fine-tuned by the twist angle and by the application of perpendicular electric fields by means of differential gating18,37. Moreover, $T_{c}$ could possibly be enhanced further by applying pressure to the graphene superlattice to increase the interlayer hybridization or by coupling different magic-angle TBG structures to induce Josephson coupling in the vertical direction38. Similar magicangle superlattices and flat-band electronic structures could also be realized with other two-dimensional materials or lattices to investigate strongly correlated systems with different properties. \n\nangle TBG (large red filled circle) is calculated from the two-dimensional density and the effective mass obtained from quantum oscillations (Fig. 5d, e) at the optimal doping $(n_{2\\mathrm{D}}=1.5\\times\\mathsf{\\bar{l}}0^{11}\\mathrm{cm}^{-2}$ and $m^{*}{=}0.2m_{\\mathrm{e}})$ , using $g=1$ to account for the halved degeneracy. Data for other materials are from refs 36,45–54. The blue shaded region is the approximate region in which almost all known unconventional superconductors lie. The inset shows the variation in $T_{\\mathrm{c}}/T_{\\mathrm{F}}$ as a function of doping $n^{\\prime}$ for magic-angle TBG (red filled circles). The horizontal dashed lines are the approximate $T_{\\mathrm{c}}/T_{\\mathrm{F}}$ values of the corresponding material. YBCO, $\\mathrm{YBa}_{2}\\mathrm{Cu}_{3}\\mathrm{O}_{7-\\delta};$ LSCO, $\\mathrm{La}_{2-x}\\mathrm{Sr}_{x}\\mathrm{CuO}_{4}$ ; BSCCO, $\\mathrm{Bi}_{2}\\mathrm{Sr}_{2}\\mathrm{Ca}_{2}\\mathrm{Cu}_{3}\\mathrm{O}_{y};$ LAO, ${\\mathrm{LaAlO}}_{3}$ ; STO, $\\mathrm{SrTiO}_{3}$ ; 1L, single layer; EDLT, electric double-layer transistor; BEDT, bisethylenedithiol; TMTSF, tetramethyltetraselenafulvalene. \n\nFinally, despite several apparent similarities between magic-angle TBG and cuprates, there are key differences between the realizations of them. First, the valley degree of freedom in the underlying graphene lattices leads to an extra degeneracy, resulting in two carriers per superlattice unit cell at half-filling in the parent correlated insulator state. Higher quality devices and fine tuning may lead to superconductivity near the regions corresponding to one and three carriers per unit cell. Second, in magic-angle TBG the underlying superlattice is triangular, which should have a fundamental influence on the type of spin-singlet ground state it can host, owing to magnetic frustration. The lattice symmetry should also impose limitations on the possible superconducting pairing symmetry in magic-angle TBG; further experiments, for example, involving tunnelling and Josephson heterojunctions, are required to confirm this39. Various pairing symmetries, including $(d+i d^{\\prime})$ -wave, $(p_{x}+i p_{y})$ -wave and spin-triplet $s$ -wave symmetries, have been predicted theoretically in the hypothetical superconductivity of monolayer or few-layer graphene40–42. If the mechanism for superconductivity in magic-angle TBG is indeed related to the correlated half-filling insulating state, as is the case in $d_{x^{2}-y^{2}}$ -wave cuprates, then the pairing symmetry might be chiral $(d+i d^{\\prime})$ -wave, to satisfy the underlying triangular symmetry of the superlattice. We anticipate that further experimental and theoretical work on magic-angle TBG and related magic-angle superlattices will provide insights into the key factors that govern unconventional superconductivity, and bring us closer to realizing tunable quantum spin liquids43. \n\nOnline Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# received 5 February; accepted 26 February 2018. Published online 5 March 2018. \n\n1. Rajagopal, K. & Wilczek, F. in At the Frontier of Particle Physics (ed. Shifman, M.) Vol. 3, 2061–2151 (World Scientific, 2001). \n2. v. Löhneysen, H., Rosch, A., Vojta, M. & Wölfle, P. Fermi-liquid instabilities at magnetic quantum phase transitions. Rev. Mod. Phys. 79, 1015–1075 (2007). \n3. Stormer, H. L. Nobel Lecture: The fractional quantum Hall effect. Rev. Mod. Phys. 71, 875–889 (1999). \n4. Pfleiderer, C. Superconducting phases of f-electron compounds. Rev. Mod. Phys. 81, 1551–1624 (2009). \n5. Ishiguro, T., Yamaji, K. & Saito, G. Organic superconductors 2nd edn (Springer, 1998). \n6. Lee, P. A., Nagaosa, N. & Wen, X.-G. Doping a Mott insulator: physics of high-temperature superconductivity. Rev. Mod. Phys. 78, 17–85 (2006). \n7. Keimer, B., Kivelson, S. A., Norman, M. R., Uchida, S. & Zaanen, J. From quantum matter to high-temperature superconductivity in copper oxides. Nature 518, 179–186 (2015). \n8. Stewart, G. R. Superconductivity in iron compounds. Rev. Mod. Phys. 83, 1589–1652 (2011). \n9. Bloch, I., Dalibard, J. & Zwerger, W. Many-body physics with ultracold gases. Rev. Mod. Phys. 80, 885–964 (2008). \n10.\t Mazurenko, A. et al. A cold-atom Fermi–Hubbard antiferromagnet. Nature 545, 462–466 (2017). \n11.\t Wang, Z., Liu, C., Liu, Y. & Wang, J. High-temperature superconductivity in one-unit-cell FeSe films. J. Phys. Condens. Matter 29, 153001 (2017). \n12.\t Bistritzer, R. & MacDonald, A. H. Moiré bands in twisted double-layer graphene. Proc. Natl Acad. Sci. USA 108, 12233–12237 (2011). \n13.\t Suárez Morell, E., Correa, J. D., Vargas, P., Pacheco, M. & Barticevic, Z. Flat bands in slightly twisted bilayer graphene: tight-binding calculations. Phys. Rev. B 82, 121407 (2010). \n14.\t Moon, P. & Koshino, M. Energy spectrum and quantum Hall effect in twisted bilayer graphene. Phys. Rev. B 85, 195458 (2012). \n15.\t Fang, S. & Kaxiras, E. Electronic structure theory of weakly interacting bilayers. Phys. Rev. B 93, 235153 (2016). \n16.\t Trambly de Laissardiére, G., Mayou, D. & Magaud, L. Numerical studies of confined states in rotated bilayers of graphene. Phys. Rev. B 86, 125413 (2012). \n17.\t Cao, Y. et al. Superlattice-induced insulating states and valley-protected orbits in twisted bilayer graphene. Phys. Rev. Lett. 117, 116804 (2016). \n18.\t Cao, Y. et al. Correlated insulator behaviour at half-filling in magic-angle graphene superlattices. Nature 556, https://doi.org/10.1038/nature26154 (2018). \n19.\t Lopes dos Santos, J. M. B., Peres, N. M. R. & Castro Neto, A. H. Continuum model of the twisted graphene bilayer. Phys. Rev. B 86, 155449 (2012). \n20.\t Kim, K. et al. van der Waals heterostructures with high accuracy rotational alignment. Nano Lett. 16, 1989–1995 (2016). \n21.\t Kim, K. et al. Tunable moiré bands and strong correlations in small-twist-angle bilayer graphene. Proc. Natl Acad. Sci. USA 114, 3364–3369 (2017). \n22.\t Wang, L. et al. One-dimensional electrical contact to a two-dimensional material. Science 342, 614–617 (2013). \n23.\t Tinkham, M. Introduction to Superconductivity (Courier Corporation, 1996). \n24.\t Saito, Y., Nojima, T. & Iwasa, Y. Highly crystalline 2D superconductors. Nat. Rev. Mater. 2, 16094 (2016). \n25.\t Mott, N. F. Metal-Insulator Transitions (Taylor and Francis, 1990). \n26.\t Imada, M., Fujimori, A. & Tokura, Y. Metal-insulator transitions. Rev. Mod. Phys. 70, 1039–1263 (1998). \n27.\t Klemm, R. A. & Luther, A. Theory of the upper critical field in layered superconductors. Phys. Rev. B 12, 877–891 (1975). \n28.\t Goldman, A. M. in BCS: 50 Years (eds Cooper, L. N. & Feldman, D.) 255–275 (World Scientific, 2011). \n29.\t Hunt, B. et al. Massive Dirac fermions and Hofstadter butterfly in a van der Waals heterostructure. Science 340, 1427–1430 (2013). \n30.\t Ponomarenko, L. A. et al. Cloning of Dirac fermions in graphene superlattices. Nature 497, 594–597 (2013). \n31.\t Dean, C. R. et al. Hofstadter’s butterfly and the fractal quantum Hall effect in moiré superlattices. Nature 497, 598–602 (2013). \n32.\t Yelland, E. A. et al. Quantum oscillations in the underdoped cuprate $\\mathsf{Y B a}_{2}\\mathsf{C u}_{4}\\mathsf{O}_{8}$ . Phys. Rev. Lett. 100, 047003 (2008). \n33.\t Bangura, A. F. et al. Small Fermi surface pockets in underdoped high temperature superconductors: observation of Shubnikov–de Haas oscillations in $\\mathsf{Y B a}_{2}\\mathsf{C u}_{4}\\mathsf{O}_{8}$ . Phys. Rev. Lett. 100, 047004 (2008). \n34.\t Jaudet, C. et al. de Haas–van Alphen oscillations in the underdoped hightemperature superconductor YBa2Cu3O6.5. Phys. Rev. Lett. 100, 187005 (2008). \n35.\t Kaul, R. K., Kim, Y. B., Sachdev, S. & Senthil, T. Algebraic charge liquids. Nat. Phys. 4, 28–31 (2008). \n36.\t Uemura, Y. J. Condensation, excitation, pairing, and superfluid density in high- $\\cdot\\bar{T}_{\\mathrm{c}}$ superconductors: the magnetic resonance mode as a roton analogue and a possible spin-mediated pairing. J. Phys. Condens. Matter 16, S4515–S4540 (2004). \n37.\t Gonzalez-Arraga, L. A., Lado, J. L., Guinea, F. & San-Jose, P. Electrically controllable magnetism in twisted bilayer graphene. Phys. Rev. Lett. 119, 107201 (2017). \n38.\t Yankowitz, M. et al. Dynamic band-structure tuning of graphene moiré superlattices with pressure. Nature (in the press); preprint at https://arxiv.org/ abs/1707.09054 (2017). \n39.\t Tsuei, C. C. & Kirtley, J. R. Pairing symmetry in cuprate superconductors. Rev. Mod. Phys. 72, 969 (2000). \n40.\t Nandkishore, R., Levitov, L. S. & Chubukov, A. V. Chiral superconductivity from repulsive interactions in doped graphene. Nat. Phys. 8, 158–163 (2012). \n41.\t Uchoa, B. & Castro Neto, A. H. Superconducting states of pure and doped graphene. Phys. Rev. Lett. 98, 146801 (2007). \n42.\t Hosseini, M. V. & Zareyan, M. Unconventional superconducting states of interlayer pairing in bilayer and trilayer graphene. Phys. Rev. B 86, 214503 (2012). \n43.\t Balents, L. Spin liquids in frustrated magnets. Nature 464, 199–208 (2010). \n44.\t Ku, M. J. H., Sommer, A. T., Cheuk, L. W. & Zwierlein, M. W. Revealing the superfluid lambda transition in the universal thermodynamics of a unitary fermi gas. Science 335, 563–567 (2012). \n45.\t Qian, T. et al. Absence of a Holelike Fermi surface for the iron-based $\\mathsf{K}_{0.8}\\mathsf{F e}_{1.7}\\mathsf{S e}_{2}$ superconductor revealed by angle-resolved photoemission spectroscopy. Phys. Rev. Lett. 106, 187001 (2011). \n46.\t Hashimoto, T. et al. Sharp peak of the zero-temperature penetration depth at optimal composition in $\\mathsf{B a F e}_{2}(\\mathsf{A s}_{1-x}\\mathsf{P}_{x})_{2}$ . Science 336, 1554–1557 (2012). \n47.\t Saito, Y., Kasahara, Y., Ye, J., Iwasa, Y. & Nojima, T. Metallic ground state in an ion-gated two-dimensional superconductor. Science 350, 409–413 (2015). \n48.\t Ye, J. T. et al. Superconducting dome in a gate-tuned band insulator. Science 338, 1193–1196 (2012). \n49.\t Peelaers, H. & Van de Walle, C. G. Effects of strain on band structure and effective masses in ${\\mathsf{M o S}}_{2}$ . Phys. Rev. B 86, 241401(R) (2012). \n50.\t Caviglia, A. D. et al. Electric field control of the La $\\mathsf{M O}_{3}/\\mathsf{S r T i O}_{3}$ interface ground state. Nature 456, 624–627 (2008). \n51.\t McCollam, A. et al. Quantum oscillations and subband properties of the two-dimensional electron gas at the $\\mathsf{L a A l O}_{3}/\\mathsf{S r T i O}_{3}$ interface. APL Mater. 2, 022102 (2014). \n52.\t Ueno, K. et al. Electric-field-induced superconductivity in an insulator. Nat. Mater. 7, 855–858 (2008). \n53.\t Weller, T. E., Ellerby, M., Saxena, S. S., Smith, R. P. & Skipper, N. T. Superconductivity in the intercalated graphite compounds $\\mathsf{C}_{6}\\mathsf{Y}\\mathsf{b}$ and $\\mathsf{C}_{6}\\mathsf{C}\\mathsf{a}$ Nat. Phys. 1, 39–41 (2005). \n54.\t Valla, T. et al. Anisotropic electron-phonon coupling and dynamical nesting on the graphene sheets in superconducting ${\\mathsf{C a C}}_{6}$ using angle-resolved photoemission spectroscopy. Phys. Rev. Lett. 102, 107007 (2009). \n\n# Supplementary Information is available in the online version of the paper. \n\nAcknowledgements We acknowledge discussions with R. Ashoori, S. Carr, R. Comin, L. Fu, P. A. Lee, L. Levitov, K. Rajagopal, S. Todadri, A. Vishwanath and M. Zwierlein. This work was primarily supported by the Gordon and Betty Moore Foundation’s EPiQS Initiative through grant GBMF4541 and the STC Center for Integrated Quantum Materials (NSF grant number DMR-1231319) for device fabrication, transport measurements and data analysis (Y.C., P.J.-H.), and theoretical calculations (S.F.). Data analysis by V.F. was supported by AFOSR grant number FA9550-16-1-0382. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by MEXT, Japan and JSPS KAKENHI grant numbers JP15K21722 and JP25106006. This work made use of the Materials Research Science and Engineering Center Shared Experimental Facilities, supported by the NSF (DMR-0819762), and of Harvard’s Center for Nanoscale Systems, supported by the NSF (ECS-0335765). E.K. acknowledges additional support by ARO MURI award W911NF-14-0247. \n\nAuthor Contributions Y.C. fabricated samples and performed transport measurements. Y.C., V.F. and P.J.-H. performed data analysis and discussed the results. P.J.-H. supervised the project. S.F. and E.K. provided numerical calculations. K.W. and T.T. provided hexagonal boron nitride samples. Y.C., V.F. and P.J.-H. co-wrote the manuscript with input from all co-authors. \n\nAuthor Information Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing interests. Readers are welcome to comment on the online version of the paper. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Correspondence and requests for materials should be addressed to P.J.-H. (pjarillo@mit.edu) or Y.C. (caoyuan@mit.edu). \n\nReviewer Information Nature thanks E. Mele, J. Robinson and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\n# Methods \n\nSample preparation. The devices were fabricated using a modified dry-transfer technique17,18,20. Monolayer graphene and hexagonal boron nitride (about $10{-}30\\mathrm{nm}$ thick) were exfoliated on $\\mathrm{SiO}_{2}/\\mathrm{Si}$ chips and high-quality flakes were picked using optical microscopy and atomic force microscopy. We used a poly(bisphenol A carbonate) (PC)/polydimethylsiloxane (PDMS) stack on a glass slide mounted on a custom-made micro-positioning stage to pick up a hexagonal boron nitride flake at $90^{\\circ}\\mathrm{C},$ and then used the van der Waals force between hexa­ gonal boron nitride and graphene to tear a graphene flake at room temperature. The separated graphene pieces were rotated manually by a twist angle of about $1.2^{\\circ}{-}1.3^{\\circ}$ and stacked together again, which resulted in a controlled TBG structure. The stack was encapsulated with another hexagonal boron nitride flake on the bottom and released onto a metal gate at $160^{\\circ}\\mathrm{C}$ . We did not perform any heat annealing after this step because we found that TBG tended to relax to Bernalstacked bilayer graphene at high temperatures. The final device geometry was defined by using electron-beam lithography and reactive ion etching. Electrical connections were made to the TBG by Cr/Au edge-contacted leads22. \n\nMeasurements. Transport measurements were performed in a dilution refrigerator with a base temperature of $70\\mathrm{mK}$ , except for the temperature-dependent quantum oscillations, which were measured in a $^3\\mathrm{He}$ fridge. \n\nWe used standard low-frequency lock-in techniques with an excitation frequency of about $5{\\mathrm{-}}10\\mathrm{Hz}$ and an excitation current of about $0.4{-}5\\mathrm{nA}$ . The current flowing through the sample was amplified by a current pre-amplifier and measured by the lock-in amplifier. The four-probe voltage was amplified by a voltage preamplifier at $\\times1,000$ gain and measured by another lock-in amplifier. \n\nThe twist angle of the devices was determined from the transport measurements at low temperatures18. In brief, a rough estimate of the twist angle is provided by the carrier density of the superlattice gaps at $\\pm n_{s},$ which present as strongly insulating states. To refine this estimate, the Landau levels that appear at high magnetic fields were fitted to the Wannier diagram, which gives the twist angle with an uncertainty of about $0.01^{\\circ}-0.02^{\\circ}$ . \n\nExtracting the quantum oscillation frequency and effective mass. The effective mass in device M2 was extracted using the standard Lifshitz–Kosevich formula, which relates the temperature-dependence of resistance change $\\Delta R_{x x}(T)$ to the cyclotron mass $m^{*}$ (at a given magnetic field $B_{\\perp}$ ): \n\n$$\n\\Delta R_{x x}(T)\\propto\\frac{\\chi}{\\sinh(\\chi)},\\quad\\chi=\\frac{2\\pi^{2}k_{\\mathrm{B}}T m^{*}}{\\hbar e B_{\\perp}}\n$$ \n\nFor each gate voltage (carrier density), we measured the $R_{x x}–B_{\\perp}$ curves at different temperatures, normalized them by their low-field values and subtracted a common polynomial background in $B_{\\perp}$ . Examples of the curves are shown in Fig. 5b. The oscillation frequencies shown in Fig. 5d were extracted from these curves plotted versus $1/B_{\\perp}$ . From the temperature-dependent amplitude of the most prominent peak, we extracted $m^{*}$ using the above equation (Fig. 5e). The error bars in Fig. 5d, e represent $90\\%$ confidence intervals of the fit. \n\nCommensuration and twist angle. Mathematically, in a twisted moiré system, the lattice is strictly periodic only when the twist angle satisfies a specific relation such that lattice registration order is perfectly recovered in a finite distance. These special cases are termed ‘commensurate’ structures. One important parameter in commensurate TBG structures is $\\boldsymbol{r},$ which can be intuitively understood as the number of ‘apparent’ moiré pattern wavelengths that it takes to recover the lattice periodicity fully19,55. The simplest commensurate structures with $r=1$ are called ‘minimal’ structures. These structures have exactly one moiré spot per unit cell. In TBG, as well as the minimal structures, which occur only at discrete angles, there are other commensurate structures that are arbitrarily close to any given angle $\\theta$ with large $r.$ However, at small twist angles, the evolution of the band structure of TBG can be viewed as semi-continuous; that is, an infinitesimal change in twist angle does not have a substantial effect on the band structure even though the lattice could be in a different family of commensurate structures (different $r)^{19}$ . In other words, the TBG system can be well approximated by a continuum model, as originally proposed in ref. 12, and the physics in minimal structures is representative of all nearby commensurate structures12. In our experiments, we do not expect the lattice to be in perfect commensuration, owing to disorder and intrinsic randomness due to the fabrication process. However, we think that the continuum model can faithfully represent the realistic TBG system in which any commensuration effect has been smoothed out. \n\nWe deduced the size of the moiré unit cell and the twist angle on the basis of the density of the superlattice gaps $\\pm n_{\\mathrm{s}}$ ( $\\pm4$ electrons per moiré unit cell), and then cross-checked the twist angle with the Landau levels observed at high magnetic fields. $\\pm n_{\\mathrm{s}}$ are the only multiples of $n_{\\mathrm{s}}$ that correspond to Fermi energies located within single-particle band gaps and therefore exhibit strong insulating behaviour. \n\nFor twist angles above about $0.9^{\\circ}-1^{\\circ}$ , the band structure at energies higher than these gaps is strongly overlapping and no single particle gaps at $\\pm2n_{s},\\pm3n_{s},$ … appear12–14,19,56. The experimentally measured values for the single-particle insulating gaps that we observe are in the approximately 30–60-meV range17,18. However, below about $0.9^{\\circ}-1^{\\circ}$ , the superlattice gaps at $\\pm n_{s}$ close and there is no single-particle gap at any energy in the system21,56. In this regime, there are Diraclike bands that cross at $\\pm2n_{\\mathrm{s}}$ which might be responsible for the resistance peaks observed in devices with very small twist angles, although possible interaction effects may enhance these peaks21. The states observed in very-low-twist devices are clearly different from the strong insulating gaps observed here and previously18. There is a marked change in the band structure at about $0.9^{\\circ}-1^{\\circ}$ (depending on the parameters of the model being used), which leads to a transition from singleparticle gaps at $\\pm n_{\\mathrm{s}}$ to resistive states at $\\pm2n_{s}$ . This crossover can be observed clearly in Supplementary Video, in which we show an evolution of the band structure of TBG from $\\theta=3^{\\circ}$ to $\\theta=0.8^{\\circ}$ . The data in the video were calculated using the continuum model12 \n\nPossible effects due to finite electrical fields. It has been shown that by applying a perpendicular electrical field to Bernal-stacked bilayer graphene, topological states can emerge on the AB/BA stacking boundaries while the bulk of the AB and BA regions remains gapped57–59. In small-angle TBG, a similar effect can alter the band structure because the AA-stacked regions in the moiré pattern are interconnected by the AB/BA stacking boundaries. This effect has been observed recently in scanning tunnelling experiments on ultrasmall-twist-angle samples60. \n\nThe question then arises of how the flat bands in magic-angle TBG are affected by the network of topological boundaries when a residual electrical field is present. Theoretical work on $\\theta=1.5^{\\circ}$ TBG has shown that when an inter-layer potential difference of $\\Delta V=300\\mathrm{mV}$ is applied the low-energy superlattice bands become even flatter and the electronic states become more localized37. Therefore, there is good reason to believe that the flat-band physics presented here holds even when a perpendicular electric field is present, because the electric field will probably render the band structure even more localized and correlated as the twist angle approaches the magic angle. In our experiments, we estimate that the potential difference between the two layers induced by our gate voltage is at most about $50\\mathrm{mV},$ and probably much less, owing to screening. Any possible effects of the residual electric field should be minimal. \n\nPhase-coherent transport behaviour in superconducting magic-angle TBG. In Fig. 3a, b we observe oscillatory behaviour in the measured longitudinal resistance $R_{x x}$ as a function of perpendicular magnetic field $B_{\\perp}$ when the charge density is close to the boundary between the half-filling insulating state and the superconducting states. The oscillations are most clearly seen for $n{\\approx}-1.70\\times10^{12}\\mathrm{cm}^{-2}$ to $n{\\approx}-1.60\\times10^{12}{\\mathrm{cm}}^{-2}$ and $n{\\approx}-1.50\\times10^{12}\\mathrm{cm}^{-2}$ to $n{\\approx}-1.47\\times10^{12}{\\mathrm{cm}}^{-2}$ in device M1. \n\nIn Extended Data Fig. 1a, b we show the differential resistance $\\mathrm{d}V_{x x}/\\mathrm{d}I$ versus bias current $I$ and perpendicular magnetic field $B_{\\perp}$ . At zero bias current, the oscillations of the differential resistance with $B_{\\perp}$ shown correspond to line cuts in Fig. 3a at densities of $n{\\approx}-1.48\\times10^{12}{\\mathrm{cm}}^{-2}$ (Extended Data Fig. 1a) and $n{\\approx}-1.6{\\overset{\\cdot}{8}}\\times10^{12}\\mathrm{cm}^{-2}$ (Extended Data Fig. 1b). The critical current, above which the superconductor becomes normal, oscillates with $B_{\\perp}$ at the same frequency, as can be visualized by the bright peaks in Extended Data Fig. 1a, b. The oscillation period is $\\Delta B=22.5\\mathrm{mT}$ in Extended Data Fig. 1a and about $\\Delta B{=}4\\mathrm{mT}$ in Extended Data Fig. 1b. \n\nThe fact that the critical current is maximum at zero $B_{\\perp}$ and oscillates at periodic intervals of the magnetic field suggests the existence of Josephson junction arrays—in the simplest case, a superconducting quantum interference device (SQUID)-like superconducting loop, around a normal or insulating island23. It is unclear whether this inhomogeneous behaviour is a result of sample disorder or a coexistence of two different phases (such as the superconducting phase and the correlated insulator phase). Owing to the two-dimensional nature of our devices, the detailed current distribution in the device cannot be uniquely determined at this moment by transport measurements; however, from the oscillation period we deduce the effective loop area of the SQUID approximately using $S{=}\\varPhi_{0}/\\varDelta B$ , where $\\varPhi_{0}=h/(2e)$ is the superconducting quantum flux. (Note the difference between $\\phi_{0}=h/e$ for the quantum Hall effect and $\\varPhi_{0}=h/(2e)$ for superconductivity.) For the experimental data in Extended Data Fig. 1a, b, we obtain areas of $S=0.{\\dot{0}}9\\upmu\\mathrm{m}^{2}$ and $S=0.5\\upmu\\mathrm{m}^{2}$ , respectively. By comparison, the total device area between the voltage probes is approximately $\\dot{1}\\upmu\\mathrm{m}^{2}$ . \n\nUsing a simple model of a SQUID with a phenomenological decay of the oscillation amplitude at higher magnetic fields, we attempt to reproduce the observed oscillations qualitatively using numerical simulations. In Extended Data Fig. 1c we show the simulated I– $.B_{\\perp}$ map of the differential resistance for a SQUID with area $S=0.09\\upmu\\mathrm{m}^{2}$ , with the same critical current $I_{\\mathrm{c1}}{=}I_{\\mathrm{c2}}{=}7\\mathrm{nA}$ in the two branches, corresponding to the experimental data in Extended Data Fig. 1a. In Extended Data \n\nFig. 1d we show the simulation for an asymmetric SQUID with area $S=0.5\\upmu\\mathrm{m}^{2}$ and critical currents of $I_{\\mathrm{c1}}{=}6\\mathrm{nA}$ and $I_{c2}=10\\mathrm{nA}$ for the two branches, which account for the partial cancellation of the critical current at low fields (that is, the total critical current does not reach zero in an oscillation) seen in Extended Data Fig. 1b. These simulations provide a qualitative perspective on the oscillatory phenomenon; the actual supercurrent distribution is probably much more complex and will need to be established via magnetic imaging techniques. However, our data indicate that the superconducting behaviour that we observe is indeed a phase-coherent phenomenon. Although we did not fabricate SQUID devices deliberately using magic-angle TBG, these periodic oscillations of the critical current in $B_{\\perp}$ are probably a result of the Josephson effect through a superconductor with insulating puddles, further confirming the existence of superconductivity in magic-angle TBG. \n\nInduced superconductivity in graphene and graphene-based systems through proximity to another superconductor has been demonstrated, and graphene-based Josephson junctions continue to be explored61–63. Superconductivity in graphene induced by proximity to a high- ${\\varGamma_{\\mathrm{c}}}$ superconductor has been reported recently, and indications of induced unconventional pairing have been observed64,65. \n\nSupplementary quantum oscillation data and low-field Hall effect. In Extended Data Fig. 2 we show magneto-transport data for device M1 and another magicangle device D1. Both devices show evidence for the existence of an extra Landau fan with a degeneracy of $M=2$ that emerges from the half-filling insulating states. All of the magic-angle devices that we have measured so far display quantum oscillations that correspond to emergent quasiparticles on one side of the half-filling states—the one that is away from the charge neutrality point (that is, $n<-n_{\\mathrm{s}}/2$ for $E_{\\mathrm{{F}}}<0$ and $n>n_{\\mathrm{s}}/2$ for $E_{\\mathrm{{F}}}{>}0$ ; see ref. 18 for the $E_{\\mathrm{{F}}}>0$ data)—but not the other ${'}n>-n_{\\mathrm{s}}/2$ or $nn_{s}/2$ . This behaviour is in agreement with the measurements of the quantum oscillation frequency shown in Fig. 5d. \n\nThis resetting effect is quickly suppressed by raising the temperature to about $10\\mathrm{K}$ . Beyond this temperature the Hall density increases monotonically towards the band edge. At these higher temperatures, the Hall density in the flat bands no longer follows $n_{\\mathrm{H}}=n$ . This could possibly be explained by the thermal energy $k T$ being close to the bandwidth of the flat bands, in which case the Hall coefficient must take into consideration the contributions from carriers that are thermally excited into the higher-energy, highly dispersive bands, which have opposite polarity. By contrast, up to $30\\mathrm{K}$ the Hall density measured at very high densities ( $|n|>n_{\\mathrm{s}})$ exhibits very linear behaviour according to $|n_{\\mathrm{H}}|=|n|-n_{\\mathrm{s}}$ regardless of the temperature, which is consistent with the highly-dispersive, low-mass bands above and below the flat bands, as seen in Fig. 1c. \n\nData availability. The data that support the findings of this study are available from the corresponding authors on reasonable request. \n\n![](images/5d2cda55987ed667b0add977045f4d79490368f7d01ec4ff274819f89bbffee8.jpg) \nxtended Data Figure 1 | Evidence of phase-coherent transport in observed in the critical current (identified approximately as the position uperconducting magic-angle TBG. a, b, Differential resistance $\\mathrm{d}V/\\mathrm{d}I$ of the bright peaks in dV/dI). c, d, Simulations intended to reproduce versus bias current $I$ and perpendicular field $B_{\\perp}$ , at two different charge qualitatively the behaviour observed in a and b. densities $n$ , corresponding to those in Fig. 3a. Periodic oscillations are \n\n![](images/0443da801735bedd58635f64c32ceea5a224b39858b315bac13c4c8d958034fc.jpg) \nExtended Data Figure 2 | Supplementary quantum oscillation data. a, b, Quantum oscillations in device M1 (a; $\\theta=1.16^{\\circ}$ , data shown for $R_{x x})$ and device D1 (b; $\\theta=1.08^{\\circ}$ , data shown for the two-probe conductance $G_{2,}^{\\mathrm{~\\tiny~,~}}$ ). The first derivative with respect to the gate-defined charge density $n$ has been taken in both cases to enhance the colour contrast. Both devices \n\nexhibit a Landau fan that emerges from the half-filling state $-n_{s}/2$ and have a Landau level sequence of $-2,-4,-6,-8,...,$ consistent with the results shown in Fig. 5. By comparison, the Landau fans that start from charge neutrality have a sequence of $-4,-8,-12,..$ \n\n![](images/d3a4b74b9d09cd45e30a17dcea5eecb709f903abd134eb44ef43367265aefd17.jpg) \nxtended Data Figure 3 | Low-field Hall effect in magic-angle TBG. $31.8\\mathrm{K}$ . Coloured vertical bars correspond to densities of $\\dot{\\mathbf{\\theta}}-n_{s},-n_{s}/2,n_{s}/2$ a, b, Low-field Hall effect for devices M1 (a) and M2 (b). The Hall density and $n_{s}$ for the two samples. Dashed lines are the expected Hall density if $n_{\\mathrm{H}}=-\\left(1/e\\right)(\\mathrm{d}R_{x y}/\\mathrm{d}B_{\\perp})_{B^{\\perp}=0}^{-1}$ is plotted as a function of the total charge the offset given in the corresponding formula is considered. ensity induced by the gBa⊥te ${\\L}^{\\L}(n)$ , measured at temperatures from $0.4\\mathrm{K}$ to " + }, + { + "id": "10.1016_j.cpc.2017.09.033", + "DOI": "10.1016/j.cpc.2017.09.033", + "DOI Link": "http://dx.doi.org/10.1016/j.cpc.2017.09.033", + "Relative Dir Path": "mds/10.1016_j.cpc.2017.09.033", + "Article Title": "WannierTools: An open-source software package for novel topological materials", + "Authors": "Wu, QS; Zhang, SN; Song, HF; Troyer, M; Soluyanov, AA", + "Source Title": "COMPUTER PHYSICS COMMUNICATIONS", + "Abstract": "We present an open-source software package Wannier Tools, a tool for investigation of novel topological materials. This code works in the tight-binding framework, which can be generated by another software package Wannier90 (Mostofi et al., 2008). It can help to classify the topological phase of a given material by calculating the Wilson loop, and can get the surface state spectrum, which is detected by angle resolved photoemission (ARPES) and in scanning tunneling microscopy (STM) experiments. It also identifies positions of Weyl/Dirac points and nodal line structures, calculates the Berry phase around a closed momentum loop and Berry curvature in a part of the Brillouin zone (BZ). Program summary Program title: WannierTools Program Files doi: http://dx.doi.org/10.17632/ygsmh4hyh6.1 Licensing provisions: GNU General Public Licence 3.0 Programming language: Fortran 90 External routines/libraries used: BIAS (http://www/netlib.org/blas) LAPACK (http://www.netlib.org/lapack) Nature of problem: Identifying topological classificatiOns of crystalline systems including insulators, semimetals, metals, and studying the electronic properties of the related slab and ribbon systems. Solution method: Tight-binding method is a good approximation for solid systems. Based on that, Wilson loop is used for topological phase classification. The iterative Green's function is used for obtaining the surface state spectrum. (C) 2017 Elsevier BV. All rights reserved.", + "Times Cited, WoS Core": 1950, + "Times Cited, All Databases": 2057, + "Publication Year": 2018, + "Research Areas": "Computer Science; Physics", + "UT (Unique WOS ID)": "WOS:000424726700035", + "Markdown": "# WannierTools: An open-source software package for novel topological materials \n\nQuanSheng Wu a,\\*, ShengNan Zhang b, Hai-Feng Song c, Matthias Troyer a, Alexey A. Soluyanov a,d \n\na Theoretische Physik and Station Q Zurich, ETH Zurich, 8093 Zurich, Switzerland b Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China c Institute of Applied Physics and Computational Mathematics, Beijing 100094, China d Department of Physics, St. Petersburg State University, St. Petersburg, 199034, Russia \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: Received 1 March 2017 Accepted 29 September 2017 Available online 18 October 2017 \n\nKeywords: \nNovel topological materials \nTopological number \nSurface state \nTight-binding model \n\nWe present an open-source software package WannierTools, a tool for investigation of novel topological materials. This code works in the tight-binding framework, which can be generated by another software package Wannier90 (Mostofi et al., 2008). It can help to classify the topological phase of a given material by calculating the Wilson loop, and can get the surface state spectrum, which is detected by angle resolved photoemission (ARPES) and in scanning tunneling microscopy (STM) experiments. It also identifies positions of Weyl/Dirac points and nodal line structures, calculates the Berry phase around a closed momentum loop and Berry curvature in a part of the Brillouin zone (BZ). \n\n# Program summary \n\nProgram title: WannierTools \nProgram Files doi: http://dx.doi.org/10.17632/ygsmh4hyh6.1 \nLicensing provisions: GNU General Public Licence 3.0 \nProgramming language: Fortran 90 \nExternal routines/libraries used: BLAS (http://www/netlib.org/blas) • LAPACK (http://www.netlib.org/lapack) \n\nNature of problem: Identifying topological classifications of crystalline systems including insulators, semimetals, metals, and studying the electronic properties of the related slab and ribbon systems. Solution method: Tight-binding method is a good approximation for solid systems. Based on that, Wilson loop is used for topological phase classification. The iterative Green’s function is used for obtaining the surface state spectrum. \n\n$\\mathfrak{C}$ 2017 Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nNovel topological states have attracted much attention during the past decades. They give a lot of opportunities to explore new physics and to realize new quantum devices [1,2]. Since quantum spin hall effect (QSHE) was predicted in 2005 [3], and realized in HgTe/CdTe quantum wells in 2007 [4,5], more and more topological novel states were discovered, such as 3D topological insulators [6–8], Dirac [9,10], Weyl [11–13] semimetals, Hourglass fermions [14], Nodal line semimetals [15–17] and nodal chain metals [18] et al. Nowadays, a lot of new topological phases are emerging, and more and more materials are identified to be topologically non-trivial. \n\nOne important feature of topological materials is topologically protected surface [19] states, which are robust against the white noise disorder and have novel transport properties [5] due to spin-momentum locked features. In experiments, the surface states and transport properties are detectable, therefore, taken as an evidence for non-trivial topology in bulk band structures [5,6,20]. The logic here is that the bulk-edge correspondence principle, which tells that there are topologically protected $d-1$ -dimension edge states if the topological property is non-trivial in $d$ -dimension bulk. In the theoretical part, besides calculation of surface-state spectrum and transport properties, we could also calculate topological numbers such as the $\\mathbb{Z}_{2}$ number [21], Chern number [22] and Wilson loops [23] (identical to Wannier charge centers [24]) to study the topology of energy band structures of a material directly. \n\nAt present, there are more and more groups joining the investigation of novel topological materials. However, there are only a few software packages that can be used so far. Z2pack [25] is a package that uses the Wannier charge centers (WCCs) to classify the topological properties of real compounds. By using Z2pack, the WCCs can be obtained either from tight-binding (TB) model or from first-principle packages, such as VASP, ABINIT and Quantum-espresso. PythTB [26] is another software package with a Python implementation of TB models. There are many functions to build and solve TB models of the electronic structure of systems for arbitrary dimensional systems (crystals, slabs, ribbons, clusters, etc.) in PythTB, and it can compute Berry phases and related properties. \n\nHere we introduce a TB dependent open-source software package called WannierTools, which can be used for novel topological materials investigation. Unlike Z2pack, it can be used to calculate the surface states of materials, and, being parallelized with MPI, it is faster than PythTB. It is a user friendly and efficient single program implemented in Fortran90. The only thing needed to run it is an input file, which contains some parameters describing your systems, and a TB model written in Wannier90_hr.dat format [27]. With WannierTools, topological numbers like the $\\mathbb{Z}_{2}$ numbers or Wilson loops for the bulk system can be calculated in order to explore the topological properties of a material. It can also help to search for Weyl/Dirac points or nodal loop structures in the BZ of metallic systems. There are plenty of other functions, e.g. studying the electron structure properties for slab and ribbon systems, studying the Berry curvature for bulk systems, studying the Berry phase around one momentum loop in the BZ for nodal-line systems and so on. \n\nThis paper is organized as follows. In Section 2, we review briefly some basic theories related to this package. In Section 3, we introduce the capabilities of this package. In Section 4, we introduce the installation and basic usages. In Section 5, we introduce a new topological material HfPtGe in order to show you how to use WannierTools to explore a new topological phase. \n\n# 2. Methods \n\n# 2.1. TB method \n\nTB method is a semi-empirical approach to study electronic structures of solid-state systems by projecting the Hamiltonian of the system onto a series of local orbitals. There are several ways to construct TB models, such as Slater–Koster method [28], maximum localized Wannier functions (MLWF) [29], and discretization of $k$ ·p model [30] onto a lattice. Among these methods, the MLWF method [29] is widely used by the people who are interested in real materials simulations. MLWF is implemented in Wannier90, which has many interfaces with different first-principle software packages like VASP, WIEN2k, et al. Therefore MLWF TB models can be automatically obtained from first-principle calculations together with Wannier90 [27]. \n\nIn different TB methods, the basis functions could be mutually orthogonal or non-orthogonal. However, WannierTools is only capable of dealing with the TB models with orthogonal basis functions. Fortunately, the Wannier functions (WFs) for MLWF TB method fulfill this limitation. In this section, we give some brief introductions to the general orthogonal TB methods. The details of how to construct MLWF TB models can be found in Refs. [31,29]. \n\nLet i label the atoms, $\\mu$ label the orbitals, $m$ label the combination of $\\{i\\mu\\}$ , R label the lattice vectors in 3D crystal, and ${\\pmb{\\tau}}_{i}$ label the position of atoms in a home unit cell. The local orbital for the i’th atom centered at ${\\pmb R}+\\pmb{\\tau}_{i}$ can be written as \n\n$$\n\\phi_{R m}(\\pmb{r})\\equiv\\phi_{m}(\\pmb{r}-\\pmb{R})\\equiv\\varphi_{i\\mu}(\\pmb{r}-\\pmb{R}-\\pmb{\\tau}_{i}).\n$$ \n\nThe orthogonality of orbitals requires $\\langle\\phi_{R m}\\vert\\phi_{R^{\\prime}n}\\rangle=\\delta_{R R^{\\prime}}\\delta_{m n}.$ . TB parameters of the Hamiltonian that have the translational symmetry due to Bloch theorem can be calculated via \n\n$$\nH_{m n}({\\pmb R})=\\langle\\phi_{{\\pmb0}m}|\\hat{H}|\\phi_{{\\pmb R}n}\\rangle\n$$ \n\nOnce we have the TB Hamiltonian $H_{m n}(\\pmb{R})$ , the Hamiltonian in k space can be obtained by a Fourier transformation (FT) [29]. There are two conventions [26] for FTs. One is \n\n$$\nH_{m n}({\\pmb k})=\\sum_{\\pmb{R}}e^{i{\\pmb k}\\cdot{\\pmb R}}H_{m n}({\\pmb R})\n$$ \n\nThe other one is \n\n$$\nH_{m n}({\\pmb k})=\\sum_{{\\pmb R}}e^{i{\\pmb k}\\cdot({\\pmb R}+{\\pmb\\tau}_{m}-{\\pmb\\tau}_{n})}H_{m n}({\\pmb R})\n$$ \n\nIt can be demonstrated that eigenvalues for these two conventions are the same, but the eigenvectors are different. The eigenvectors of the first convention Eq. (3) are analogous to the Bloch wave functions $\\psi_{n\\pmb{k}}(\\pmb{r})$ . The eigenvectors of the second convention Eq. (4) are analogous to the periodic part of the Bloch wave functions $u_{n k}(\\pmb{r})=\\psi_{n k}(\\pmb{r})e^{-i\\pmb{k}\\pmb{r}}$ , which is of great importance in Berry phase and Berry curvature or the Wannier centers calculations. Therefore, the second convention is used in WannierTools. \n\nAccording to the bulk-edge correspondence, there are topologically protected surface states if the topology of bulk energy bands is non-trivial. In order to study such surface states, we have to construct a slab system which is periodic along two directions at the surface. In practice, a new unit cell is defined with lattice vectors R′1,2,3, \n\n$$\n\\begin{array}{r}{\\mathbf{R}_{1}^{\\prime}=U_{11}\\mathbf{R}_{1}+U_{12}\\mathbf{R}_{2}+U_{13}\\mathbf{R}_{3}}\\\\ {\\mathbf{R}_{2}^{\\prime}=U_{21}\\mathbf{R}_{1}+U_{22}\\mathbf{R}_{2}+U_{23}\\mathbf{R}_{3}}\\\\ {\\mathbf{R}_{3}^{\\prime}=U_{31}\\mathbf{R}_{1}+U_{32}\\mathbf{R}_{2}+U_{33}\\mathbf{R}_{3}}\\end{array}\n$$ \n\nwhere $\\mathbf{R}_{1,2,3}$ are lattice vectors of the original unit cell of the bulk system, ${\\pmb R}_{1}^{\\prime}$ and ${\\bf R}_{2}^{\\prime}$ are two lattice vectors in the target slab surface, ${\\bf R}_{3}^{\\prime}$ is the other lattice vector which is out of the surface and fulfills the volume fixed condition, \n\n$$\n\\mathbf{R}_{1}^{\\prime}\\cdot(\\mathbf{R}_{2}^{\\prime}\\times\\mathbf{R}_{3}^{\\prime})=\\mathbf{R}_{1}\\cdot(\\mathbf{R}_{2}\\times\\mathbf{R}_{3})\n$$ \n\nSince the slab system is non-periodic along the ${\\pmb R}_{3}^{\\prime}$ direction, the Hamiltonian of a slab system with a 2D momentum $k_{\\parallel}$ can be calculated by the following FT \n\n$$\nH_{m n}^{s l a b}({\\bf k}_{\\parallel})=\\sum_{\\parallel{\\bf R}\\parallel}e^{i{\\bf k}_{\\parallel}\\cdot{\\bf R}}H_{m n}^{s l a b}({\\bf R})\n$$ \n\nwhere $\\begin{array}{r}{\\mathbf{R}=a^{\\prime}\\mathbf{R}_{3}^{\\prime}+b^{\\prime}\\mathbf{R}_{2}^{\\prime}+c^{\\prime}\\mathbf{R}_{3}^{\\prime}}\\end{array}$ and $\\|\\mathbf R\\|$ is a restriction that the summation is only carried on $a^{\\prime}$ and $b^{\\prime}$ with different $c^{\\prime}$ . We label the layer index along ${\\pmb R}_{3}^{\\prime}$ as i, j. As a consequence, the Hamiltonian of a slab system with $n_{s}$ layers can be written in the layer index matrix form, \n\n$$\nH_{m n}^{s l a b}({\\bf k}_{\\parallel})=\\left(\\begin{array}{c c c c}{H_{m n,11}({\\bf k}_{\\parallel})}&{H_{m n,12}({\\bf k}_{\\parallel})}&{\\cdot\\cdot}&{H_{m n,1n_{s}}({\\bf k}_{\\parallel})}\\\\ {H_{m n,21}({\\bf k}_{\\parallel})}&{H_{m n,22}({\\bf k}_{\\parallel})}&{\\cdot\\cdot}&{H_{m n,2n_{s}}({\\bf k}_{\\parallel})}\\\\ {\\vdots}&{\\vdots}&{\\cdot}&{\\vdots}\\\\ {H_{m n,n_{s}1}({\\bf k}_{\\parallel})}&{H_{m n,n_{s}2}({\\bf k}_{\\parallel})}&{\\cdot\\cdot}&{H_{m n,n_{s}n_{s}}({\\bf k}_{\\parallel})}\\end{array}\\right)\n$$ \n\nwhere the diagonal elements of the Hamiltonian are the intra-plane ones, and the off diagonal elements are the inter-plane ones. The element in Eq. (10) can be read explicitly as, \n\n$$\nH_{m n,i j}(\\mathbf{k}_{\\parallel})=\\sum_{\\mathbf{R}=\\{\\mathbf{R}_{1}^{\\prime},\\mathbf{R}_{2}^{\\prime},(i-j)\\mathbf{R}_{3}^{\\prime}\\}}e^{i\\mathbf{k}_{\\parallel}\\cdot\\mathbf{R}}H_{m n}(\\mathbf{R})\n$$ \n\nFinally the energy band of the slab system can be obtained straightforwardly to diagonalize Eq. (10). \n\nBy the way, the Hamiltonian for the ribbon system can be obtained in the same way as the slab system does. The difference is that there are two confined directions $\\mathbf{R}_{1}^{\\prime},\\mathbf{R}_{2}^{\\prime}$ in ribbon systems, which enlarges the size of Hamiltonian. \n\n# 2.2. Wannier charge center calculation \n\n$\\mathbb{Z}_{2}$ topological number [21] and Chern number [22] are applied to classify topological properties for time-reversal invariant and time-reversal symmetry breaking systems respectively. In inversion symmetric invariant system, the $\\mathbb{Z}_{2}$ topological number can be calculated by multiplying the parities of the occupied bands at time reversal invariant momenta (TRIMs) in the Brillouin zone [32]. There are several methods [33,23,24] to calculate the $\\mathbb{Z}_{2}$ number in inversion symmetry breaking systems. Among them it was demonstrated that the Wilson loop [23] and Wannier charge centers (WCCs) [24] method are equivalent to each other, and are also valid for time-reversal symmetry breaking systems. In WannierTools, we take the algorithm presented in Refs. [24,25]. The hybrid WFs [34] are defined as \n\n$$\n|n k_{x}l_{y}\\rangle=\\frac{1}{2\\pi}\\int_{0}^{2\\pi}d k_{y}e^{-i k_{y}l_{y}}|\\psi_{n\\mathbf{k}}\\rangle\n$$ \n\nwhere $|\\psi_{n\\mathbf{k}}\\rangle$ is the Bloch wave function. The hybrid Wannier centers are defined as \n\n$$\n\\begin{array}{l}{\\displaystyle\\bar{y}_{n}(k_{x})=\\langle n k_{x}0|y|n k_{x}0\\rangle}\\\\ {\\displaystyle=\\frac{i}{2\\pi}\\int_{-\\pi}^{\\pi}d k_{y}\\langle u_{n,k_{x},k_{y}}|\\partial_{k_{y}}|u_{n,k_{x},k_{y}}\\rangle}\\end{array}\n$$ \n\nwhere $\\vert u_{n,k_{x},k_{y}}\\rangle$ is the periodic part of Bloch function $|\\psi_{n\\mathbf{k}}\\rangle$ . In practice , the integration over $k_{y}$ is transformed by a summation over the discretized $k_{y}^{-}$ . Eq. (14) can be reformulated using the discretized Berry phase formula [35], \n\n$$\n\\bar{y}_{n}(k_{x})=-\\frac{1}{2\\pi}\\mathrm{Im}\\ln\\prod_{j}M_{n n}^{(j)}\n$$ \n\nwhere the gauge-dependent overlap matrix $M_{m n}^{(j)}=\\langle u_{m,k_{x},k_{y_{j}}}|u_{n,k_{x},k_{y_{j+1}}}\\rangle$ is introduced. However, the summation of the hybrid Wannier centers $\\bar{y}_{n}(k_{x})$ over $k_{x}$ is gauge invariant [36], which is the total electronic polarization. As shown in Ref. [35,37], there is another way to obtain $\\bar{y}_{n}(k_{x})$ . Firstly, we get the ‘‘unitary part’’ $\\tilde{M}^{(j)}$ of each overlap matrix $M_{m n}^{\\{j\\}}$ by carrying out the single value decomposition $M=V\\Sigma W^{\\dagger}$ , where $\\mathsf{V}$ and W are unitary and $\\Sigma$ is real-positive and diagonal. Then we set $\\tilde{M}^{(j)}=\\bar{V}W^{\\bar{\\dagger}}$ . The eigenvalues $\\lambda_{n}$ of matrix $\\begin{array}{r}{\\varLambda=\\prod_{j}\\tilde{M}^{(j)}}\\end{array}$ are all of unit modulus. The hybrid Wannier centers are defined with the phases of $\\lambda_{n}$ eventually, \n\n$$\n\\bar{y}_{n}(k_{x})=-\\frac{1}{2\\pi}\\mathrm{Im}\\ln{\\lambda_{n}}\n$$ \n\nWe can get the topological properties of $k_{x}-k_{y}$ plane from the evolution of $\\bar{y}_{n}(k_{x})$ along a $k_{x}$ string. The details of such classification of WCCs or Wilson loop are discussed in Refs. [23,37,24]. More information can be found in Ref. [25]. \n\n# 2.3. Berry phase and Berry curvature \n\nIn this section, we give the basic formalism for computing Berry phase [38,39] and Berry curvature [40,41] of Bloch states. Firstly, we introduce the single band case, where the energy bands are isolated to each other. A Berry phase $\\phi_{n}$ is a geometric phase associated with the phase evolution of the $n$ ’th state over a closed curve $c$ in external parameter space $k$ , defined as \n\n$$\n\\phi_{n}=\\oint_{\\mathcal{C}}\\pmb{A}_{n}\\cdot d\\pmb{k}\n$$ \n\nwhere the Berry connection is $A_{n,\\alpha}=i\\langle u_{n,\\pm}|\\partial_{\\alpha}u_{n,\\pm}\\rangle$ , $\\alpha=k_{x},k_{y},k_{z}$ , and Berry curvature is introduced \n\n$$\n\\begin{array}{r l}&{\\Omega_{n,\\alpha\\beta}=\\partial_{\\alpha}A_{n,\\beta}-\\partial_{\\beta}A_{n,\\alpha}}\\\\ &{\\qquad=i\\langle\\partial_{\\alpha}u_{n,\\boldsymbol{k}}|\\partial_{\\beta}u_{n,\\boldsymbol{k}}\\rangle-i\\langle\\partial_{\\beta}u_{n,\\boldsymbol{k}}|\\partial_{\\alpha}u_{n,\\boldsymbol{k}}\\rangle}\\\\ &{\\qquad=-2\\operatorname{Im}\\langle\\partial_{\\alpha}u_{n,\\boldsymbol{k}}|\\partial_{\\beta}u_{n,\\boldsymbol{k}}\\rangle}\\end{array}\n$$ \n\nSecondly, for multi-band case, it is often to treat the occupied $N_{o c c}$ bands as a joint band manifold, which is referred to as the ‘‘non-Abelian’’ case. Generalizations for the formalism of Berry phase and Berry curvature from single band to multi-band case are as follows, \n\n$$\n\\phi=\\oint_{\\cal C}\\mathrm{Tr}[A]\\cdot d{\\bf k}\n$$ \n\nwhere the Berry connection [39] is $\\mathcal{A}_{m n,\\alpha}=i\\langle u_{m,k}|\\partial_{\\alpha}u_{n,k}\\rangle,\\alpha=k_{x},k_{y},k_{z}$ , and Berry curvature is \n\n$$\n\\begin{array}{r l}&{\\Omega_{m n,\\alpha\\beta}=\\partial_{\\alpha}A_{m n,\\beta}-\\partial_{\\beta}A_{m n,\\alpha}-i[\\mathcal{A}_{\\alpha},\\mathcal{A}_{\\beta}]_{m n}}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\\\ &{\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad\\quad}\\quad}\\end{array}\n$$ \n\nand define \n\n$$\n\\mathcal{\\Omega}_{\\alpha\\beta}=\\mathrm{Tr}\\mathcal{\\Omega}_{m n,\\alpha\\beta}\n$$ \n\nwhere Tr denotes a trace over the occupied bands. \n\nIn practice, the integration of Eq. (21) is implemented on a discrete $k$ mesh. The loop $c$ is discretized into a series of closely space points $k_{j}$ . Accordingly, the Berry phase becomes \n\n$$\n\\phi=-\\sum_{j}\\mathrm{Im}\\ln\\mathrm{det}M^{(j)}=-\\mathrm{Im}\\ln\\prod_{j}\\mathrm{det}M^{(j)}\n$$ \n\nwhere the overlap matrix $M_{m n}^{(j)}$ is the same as in Eq. (15), i.e., $M_{m n}^{(j)}=\\langle u_{m,\\pmb{k}_{j}}|u_{n,\\pmb{k}_{j+1}}\\rangle$ . \n\n# 2.4. Calculation of surface states \n\nTheoretically, we have two methods to get surface spectrum corresponding to the bulk topology. One is that we calculate the band structure of a slab system, which was introduced in Section 2.1. The other one is to calculate the surface Green’s function (SGF) for a semiinfinite system that will be introduced in this section. In the 1970s, one of the most popular GF approaches was based on the ‘‘effective field’’ and transfer matrix [42–44], which are relatively of slow convergence especially near singularities. Now, the extensively used schemes to obtain the SGFs is the iterative Green’s function method developed in the 1980s [45,46]. With an effective concept of principle layers (The layer that is large enough to guarantee that hoppings between the next nearest layers are negligible.), the iterative procedure can save quite an amount of computational time. The method [45,46] involves replacing the principle layer by an effective two principle layers, and these effective layers interact through energy-dependent residual interactions which are weaker than those of the original ones. This replacement can be repeated iteratively until the residual interactions between the effective layers become as small as desired. Each new iteration doubles the number of the original layers included in the new effective layer. That is, after $n$ iterations, one has a chain of lattice constant $2^{n}$ times the original one, and each effective layer replacing $2^{n}$ original layers. The details of the algorithm are presented in Ref. [47]. For the integrity of the paper, we list the main iterations that we reused in WannierTools. The most important parameters for iteration i are the following \n\n$$\n\\begin{array}{r l}&{\\alpha_{i}=\\alpha_{i-1}(\\omega-\\varepsilon_{i-1})^{-1}\\alpha_{i-1}}\\\\ &{\\beta_{i}=\\beta_{i-1}(\\omega-\\varepsilon_{i-1})^{-1}\\beta_{i-1}}\\\\ &{\\varepsilon_{i}=\\varepsilon_{i-1}+\\alpha_{i-1}(\\omega-\\varepsilon_{i-1})^{-1}\\beta_{i-1}+\\beta_{i-1}(\\omega-\\varepsilon_{i-1})^{-1}\\alpha_{i-1}}\\\\ &{\\varepsilon_{i}^{s}=\\varepsilon_{i-1}^{s}+\\alpha_{i-1}(\\omega-\\varepsilon_{i-1})^{-1}\\beta_{i-1}}\\\\ &{\\tilde{\\varepsilon}_{i}^{s}=\\tilde{\\varepsilon}_{i-1}^{s}+\\beta_{i-1}(\\omega-\\varepsilon_{i-1})^{-1}\\alpha_{i-1}}\\end{array}\n$$ \n\nwith the initialization $\\varepsilon_{0}=\\tilde{\\varepsilon}_{0}=\\tilde{\\varepsilon}_{0}^{s}=H_{00}(\\mathbf{k}_{\\parallel}),\\alpha_{0}=H_{01}(\\mathbf{k}_{\\parallel}),\\beta_{0}=H_{01}^{\\dagger}(\\mathbf{k}_{\\parallel})$ , where $H_{00}(\\mathbf{k}_{\\parallel})$ is the intra-hopping parameters in the principle layers, $H_{01}(\\mathbf{k}_{\\parallel})$ is the inter-hopping parameters between the nearest neighbor of principle layers. \n\nIteration of Eq. (27) should be converged until $\\varepsilon_{n}\\simeq\\varepsilon_{n-1}$ and $\\tilde{\\varepsilon}_{n}^{s}\\simeq\\tilde{\\varepsilon}_{n-1}^{s}$ . The SGFs $G_{s}(\\mathbf{k}_{\\parallel},\\omega)$ and the bulk GF $G_{b}(\\mathbf{k}_{\\|},\\omega)$ can be obtained as \n\n$$\n\\begin{array}{r}{G_{s}(\\mathbf{k}_{\\parallel},\\omega)\\simeq(\\omega-\\varepsilon_{n}^{s})^{-1}}\\\\ {\\tilde{G}_{s}(\\mathbf{k}_{\\parallel},\\omega)\\simeq(\\omega-\\tilde{\\varepsilon}_{n}^{s})^{-1}}\\\\ {G_{b}(\\mathbf{k}_{\\parallel},\\omega)\\simeq(\\omega-\\varepsilon_{n})^{-1}}\\end{array}\n$$ \n\nwhere $\\tilde{G}_{s}$ is the SGF of the dual surface. The surface spectrum function $A(\\mathbf{k}_{\\parallel},\\omega)$ can be obtained from the imaginary part of SGF \n\n$$\nA(\\mathbf{k}_{\\parallel},\\omega)=-\\frac{1}{\\pi}\\operatorname*{lim}_{\\eta\\rightarrow0^{+}}\\mathrm{Im}\\mathrm{Tr}G_{s}(\\mathbf{k}_{\\parallel},\\omega+i\\eta)\n$$ \n\nTable 1 Main capabilities of WannierTools: Bulk topology studies. \n\n\n
Control flag in wt .inDescription
BulkBand_calcEnergy bands for a 3D bulk system.
BulkFS_calc3D Fermi surface in 1st BZ.
FindNodes_calcLocate Weyl, Dirac point positions and nodal line structures in 1st BZ.
BulkGap_plane_calcGap function in a 3D k plane.
Wanniercenter_calcWCCs [24] for a 3D k plane.
BerryPhase_calcBerry phase for a closed path in 3D k space.
BerryCurvature_calcBerry curvature in a 3D k plane.
\n\nTable 2 Main capabilities of WannierTools: related responses from the bulk topology. \n\n\n
Control flag in wt .inDescription
Dos_calcDensity of state of a 3D bulk system
JDos_calcJoint density of state [54] of a 3D bulk system
SlabBand_calcEnergy bands of a 2D slab system.
WireBand_calcEnergy bands of a 1D ribbon system.
SlabSS_calcSurface state spectrum along some k lines at different energies.
SlabArc_calcSurface state spectrum in the 2D BZ at a fixed energy.
SlabQPI_calcQuasi-particle interference (QPl) [55] pattern of surface state.
SlabSpintexture_calcSpin texture [56] of surface state.
\n\nThe spin texture of surface states can also be obtained with [48] \n\n$$\n\\mathbf{S}(\\mathbf{k}_{\\parallel},\\omega)=-\\frac{1}{\\pi}\\operatorname*{lim}_{\\eta\\rightarrow0^{+}}\\mathrm{Im}\\mathrm{Tr}\\left[\\sigma G_{s}(\\mathbf{k}_{\\parallel},\\omega+i\\eta)\\right]/A(\\mathbf{k}_{\\parallel},\\omega)\n$$ \n\nwhere $\\pmb{\\sigma}$ are the Pauli matrices. \n\n# 2.5. Algorithm for searching nodal points/lines \n\nNodal point is a gapless point between the highest valence band and the lowest conduction band. In terms of degeneracy character, nodal point could be classified into Weyl, Triple, Dirac, hyper-Dirac point with 2-fold degeneracy, 3-fold degeneracy, 4-fold degeneracy or higher degeneracy respectively. They also can be sorted into nodal point and nodal line by the connectivity between them. Searching the Weyl/Dirac points and the nodal-line structures is very important for such nodal systems. Some symmetry protected nodal points or nodal lines which are located in high symmetry lines or mirror planes are easy to find. While the other nodes which are located anywhere in the BZ need more efforts to be found. Here we introduce an algorithm trying to find all the nodal points. \n\nBasically, node points are local minima of the energy gap function in 3D BZ. Local minima can be obtained by using some well known multidimensional minimization methods, e.g., Nelder and Mead’s Downhill Simplex Method [49], Conjugate Gradient Methods [50], QuasiNewton Methods [51] et al. However, the local minimum obtained from those methods depends on a initial point. One initial point gives only one local minimum. So, in order to find all the nodes, we have to choose different initial points in the whole 3D BZ. WannierTools takes a uniform mesh of the 1st BZ as a set of initial points for the Nelder and Mead’s Downhill Simplex Method [49]. Eventually, the nodes will be selected out from a set of local minima. It is easy to check the convergence of the number of nodes by increasing the initial point mesh. This algorithm is very suitable for high throughput search of new Weyl, Dirac semimetals and nodal-line metals. It has been checked to be very efficient to find Weyl points in $\\mathsf{W T e}_{2}$ [13,52], MoTe2 [53]. \n\n# 3. Capabilities of WannierTools \n\nThere are two kinds of tasks that WannierTools can do to study novel topological materials. a. One is to get the topology of materials’ band structure. b. The other one is to explore the properties of surface states corresponding to the bulk topology. For part a, we need to study the bulk band structure, 3D Fermi surface, density of state (DOS) to check whether the bulk material is a band insulator or a metal. Further, WCCs calculations are applied to get the $\\mathbb{Z}_{2}$ topological index or Chern number for band insulators, the nodes searching algorithm and the energy gap function calculation are applied to search for Weyl/Dirac point positions or nodal-line structures; The Berry phase and Berry curvature calculations are also aided to the classification of topology. After the topological classification is done, one can turn to part b, which means to study the bulk topology related properties, such as joint density of state (JDOS), which is related to the optical conductivity [54], electronic structure of the slab and wire systems, spin-texture of the surface states, Quasi-particle interference (QPI) pattern of surface states et al. These two main capabilities of WannierTools are listed in Tables 1 and 2. The meaning of control flags in Tables 1 and 2 is illustrated in the documentation, which is distributed with WannierTools. \n\n# 4. Installation and usage \n\nIn this section, we will show how to install and use the WannierTools software package. \n\n# 4.1. Get WannierTools \n\nWannierTools is an open source free software package. It is released on Github under the GNU General Public Licence 3.0 (GPL), and it can be downloaded directly from the public code repository: https://github.com/quanshengwu/wannier_tools. \n\n# 4.2. Build WannierTools \n\nTo build and install WannierTools, a Fortran 90 compiler, BLAS, and LAPACK linear algebra libraries are needed. An MPI-enabled Fortran 90 compiler is needed if you want to compile a parallel version. WannierTools can be successfully compiled using the state-of-art Intel Fortran compiler. Most of the MPI implementations, such as MPICH, MVAPICH and Intel MPI are compatible with WannierTools. The downloaded WannierTools software package is likely a compressed file with a zip or tar.gz suffix. One should uncompress it firstly, then move into the wannier_tools/soc folder and edit the Makefile file to configure the compiling environment. It is noteworthy that one should set up the Fortran compiler, BLAS and LAPACK libraries manually by modifying the following lines in Makefile file according to the user’s particular system. \n\n$$\n\\begin{array}{l}{\\mathbf{f}90}\\\\ {\\mathbf{libs}}\\end{array}=\n$$ \n\nOnce the compiling environment is configured, the executable binary wt.x will be compiled by typing the following command in the current directory (wannier_tools/soc) \n\n$\\$8$ make \n\n# 4.3. Running WannierTools \n\nBefore running WannierTools, the user must provide two files wannier90_hr.dat1 and wt.in. The file called wannier90_hr.dat containing the TB parameters has fixed format which is defined in software Wannier90 [27]. It can be generated by the software Wannier90 [27], or generated by users with a toy TB model, or generated from a discretization of $k\\cdot p$ model onto a cubic lattice. The other file wt.in is the master input file for WannierTools. It is designed to be simple and user friendly. The details of wt.in are described comprehensively in the documentation that contained within the WannierTools distribution. An example file is provided in Appendix. \n\nAfter putting wt.in and wannier90_hr.dat in the same folder, one can run it in single processor in the same folder like this \n\n\\$ wt.x & or in multiprocessor $\\$1$ mpirun -np 4 wt.x & \n\nSome important information during the running process are written in WT.out, from which, you can check the running status. After the whole program is done, you would obtain two kinds of files other than WT.out. One is the data file suffixed with dat. and the other one is a plotting script for software gnuplot suffixed with gnu. You can get nice plots with gnuplot [57]. Taking a bulk band structure calculation from the examples, two files bulkek.dat and bulkek.gnu are accomplished after a successful running of WannierTools. A band structure plot bulkek.png will be generated with the following command \n\ngnuplot bulkek.gnu \n\n# 5. Examples \n\nIn the past few years, WannierTools has been successfully applied in many projects, such as finding type-II Weyl semimetals $\\mathsf{W I e}_{2}$ [13,52], MoTe2 [53], triple point metals [58] ZrTe, TaN, nodal chain metals IrF4 [18], topological phase in $\\mathrm{InAs}_{1-x}{\\sf S}{\\sf b}_{x}$ [59] et al. Besides, more and more groups notice this package, and becoming users. There are several examples in the wannier_tools/examples directory like ${\\tt B i}_{2}\\mathsf{S e}_{3}$ , $\\mathsf{W T e}_{2}$ , $\\mathrm{IrF}_{4}$ . MLWF TB Hamiltonians for those materials and the necessary input files for generating those Hamiltonians can be downloaded from the Github repository [60]. The detailed hands-on tutorials for those examples are listed in the wiki of Github [61]. In this paper, a new series of topological materials called ternary silicides and ternary germanides TiPtSi, ZrPtSi, ZrPtGe, HfPtSi and HfPtGe [62,63] are exhibited as an example to show how to study topological properties of new materials with WannierTools. \n\n# 5.1. Crystal structure and band structure \n\nTernary silicides and ternary germanides are crystallized with the orthorhombic TiNiSi type structure in a nonsymmorphic orthorhombic space group No.62 (Pnma) [64,62], containing three glide reflections $G_{x}=\\{m_{x}|{\\textstyle\\frac{1}{2}},{\\textstyle\\frac{1}{2}},{\\textstyle\\frac{1}{2}}\\},G_{z}=\\{m_{z}|{\\textstyle\\frac{1}{2}},0,{\\textstyle\\frac{1}{2}}\\},\\tilde{G}_{y}=\\{m_{y}|0,{\\textstyle\\frac{1}{2}},0\\}$ [65], three screw rotations $S_{x}=\\{R_{2x}|\\textstyle{\\frac{1}{2}},\\ {\\frac{1}{2}},\\ {\\frac{1}{2}}\\},S_{z}=\\{R_{2z}|\\textstyle{\\frac{1}{2}},0,\\textstyle{\\frac{1}{2}}\\},S_{y}=\\{R_{2y}|0,\\textstyle{\\frac{1}{2}},0\\}$ and an inversion symmetry I. These materials seem to be interesting systems in the search for new superconducting intermetallic compounds [63]. Due to the same crystal structure and similar chemical properties, these materials show very similar band structures. In this paper, we are only focusing on HfPtGe compound. \n\nAs mentioned in Section 4.3, we need a TB model of HfPtGe for WannierTools. Firstly, a first-principle calculation within Vienna Ab initio Simulation Package (VASP) [66,67] using Gamma centered $K$ -points mesh $8\\times13\\times7$ and energy cut $360\\mathrm{eV}$ for plane wave expansions was performed. Then the band structure and the partial density of states (PDOS) shown in Fig. 1c and d were analyzed, where the PDOS indicate that the relevant orbitals close to the Fermi level are dominated by Hf 5d orbitals and Pt 5d orbitals, besides, they are also hybridized with Ge 4p and Pt s orbitals. In the end, a 112-band MLWF TB Hamiltonian with Hf 5d, Pt 6s 5d and Ge 4p as projectors are constructed with Wannier90. Fig . 1c shows that the band structures calculated from the MLWF TB model are quite fitted to the first-principle calculated band structures. After the successful construction of MLWF TB model, the master input file wt.in is needed, which is attached in the Appendix. \n\n![](images/45ddf1becc6bcf64850d1a023f75cac6769ce8219198e3c30b4687ee9060eac1.jpg) \nFig. 1. a. Crystal structure of HfPtGe. The gray plane is (010) plane. b. 3D Brillouin Zone (BZ) and 2D BZ for (010) surface c. Band structure of HfPtGe with SOC, the red lines are from Wannier TB model, the black lines are from first-principle calculation. d. Partial density of states (PDOS). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/836966da5b161fbebcd1abab722a4661d46112b5916f90f26a959c8e1625a61f.jpg) \nFig. 2. Energy gap $\\varDelta E(k_{x},k_{z})$ between the lowest conduction band and the topest valence band at $k_{y}=0$ plane. a. Without SOC, it is a nodal loop. b. With SOC, The nodal loop will be gapped out. c. The nodal loop distribution in the momental space $k_{x}–k_{z}$ and energy space E. The blue plane is a energy fixed plane $E=E_{F}$ . d. Fermi surface plot, purple and cyan pockets represent hole and electron pockets respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n# 5.2. Energy gap shape \n\nThere are two ‘‘Dirac like’’ cones along Y –Γ –Z direction which are shown in the band structure plot Fig. 1c. From the literature, we know that such cones could be originated from a nodal line structure without SOC [16]. Calculations of the energy gap at $k_{y}=0$ plane both for without SOC and with SOC cases were performed to study the details of positions of these ’’Dirac like’’ cones. The results are shown in Fig. 2a and b, where there is a gapless nodal line protected by the $\\tilde{G}_{y}$ mirror symmetry [16] in the ${\\sf k}_{\\mathrm{y}}=0$ plane without SOC , while, the gapless line will be gapped when SOC turns on. One thing should mentioned is that the SOC strength of this material is very weak, and the opened gap is not very big. The smallest gap is about $0.1\\mathrm{meV}$ where the $k$ points are located at $(\\pm0.4,0.0,\\pm0.229)$ . \n\nWe can further study the nodal line distribution in momentum and energy space, which shown in Fig. 2c. It is clearly shown that the nodal line is not in the same energy plane. There are six nodes crossing the Fermi level. In such case, there are electron pockets and hole pockets which link together on the Fermi surface at the same time, which are shown in Fig. 2d. Those compensated hole and electron pockets will cause extremely large positive magnetoresistance [68]. \n\nThe related settings in the master input file wt.in for this section are as follows \n\n&CONTROL \nBulkGap_plane_calc = T \nBulkFS_calc = T \n/ \n&PARAMETERS \n$\\tt N K1=\\ 101$ \nNK2= 101 \nNK3= 101 \n/ \nKPLANE_BULK \n-0.50 0.00 -0.50 ! Original point for 3D k plane 1.00 0.00 0.00 ! The first vector to define 3d k space plane 0.00 0.00 1.00 ! The second vector to define 3d k space plane \n\n# 5.3. Wannier charge center \n\nFrom the gap shape calculation for the whole BZ in the SOC case, we can conclude that HfPtGe is a semimetal with a continuous finite energy gap between electron-like and hole-like bands. Similar to classification of band insulators [69], $\\mathbb{Z}_{2}$ topological indices $\\left(\\nu_{0},\\nu_{1}\\nu_{2}\\nu_{3}\\right)$ are still appropriate for such a semimetal. $\\mathbb{Z}_{2}$ number of a bulk material can be obtained through calculations of WCCs in six time reversal invariant planes $\\mathtt{k_{x}}=0$ , $\\pi$ , ${\\bf k}_{\\mathrm{y}}=0$ , $\\pi$ and $\\boldsymbol{\\mathrm{k}}_{\\mathrm{z}}=\\boldsymbol{0}$ , $\\pi$ plane. The results calculated by WannierTools are shown in Fig. 3. It shows that the $Z_{2}$ invariant numbers are 1 for $k_{x}=0,k_{y}=0,k_{z}=0$ plane, while zeros for other planes. Eventually, the topological index is (1, 000), which indicates that HfPtGe is a ‘‘strong’’ topological material in all three reciprocal lattice directions. The related settings for this section in wt.in are as follows. \n\n![](images/77b9b1f5a70ac67983b4160412f6d4c14bf44bf8b063b1decfa944e0f83f0692.jpg) \nFig. 3. a. Wannier charge center evolution for the time-reversal invariant planes of HfPtGe. (a) $\\mathbb{Z}_{2}=1$ for $k_{x}=0\\left(\\mathbf{b}\\right)\\mathbb{Z}_{2}=1$ for $k_{y}=0\\left({\\mathrm{c}}\\right)\\mathbb{Z}_{2}=1$ for $k_{z}=0\\left({\\bf d}\\right)\\mathbb{Z}_{2}=0$ for $k_{x}$ $\\scriptstyle={\\frac{\\pi}{a}}$ (e) $\\mathbb{Z}_{2}=0$ for $\\begin{array}{r}{k_{y}=\\frac{\\pi}{b}}\\end{array}$ (f) $\\mathbb{Z}_{2}=0$ for $\\begin{array}{r}{k_{z}=\\frac{\\pi}{c}}\\end{array}$ . \n\n&CONTROL \nZ2_3D_calc = T \n/ \n\n# 5.4. Surface state spectrums \n\nDue to the bulk-edge correspondence, there should be topologically protected surface states of any cuts of surface for a strong topological material [69]. Here we study the (010) surface which is shown as a gray plane in Fig. 1a. The surface state spectrums calculated by WannierTools are shown in Fig. 4a, b. For a 3D strong topological insulator, there is surface Dirac cone at the $\\boldsymbol{{\\Gamma}}$ point [7]. Indeed, there is a Dirac like cone of HfPtGe at the $\\boldsymbol{{\\Gamma}}$ point. However, the dispersion of this cone is highly anisotropic and even tiled in the momentum space. Such tiled cone is result from that the nodal line is located at different energies. Fig. 4b shows a $E=E_{F}$ iso-energy plot of the surface state spectrum. From this plot, we can learn that the surface states originate from the $k$ points that have the smallest gap. The related settings for this section in wt.in are as follows. \n\n&CONTROL \nSlabSS_calc = T \nSlabArc_calc $\\mathbf{\\Psi}=\\mathbf{\\Psi}_{\\mathrm{T}}$ \n/ \n&PARAMETERS \nE_arc = 0.0 ! Fixed energy Fermi arc calculation \n/ \nKPATH_SLAB \n4 ! numker of k lines for a slab system \nX -0.50 0.00 G 0.00 0.00 ! k path for a slab system \nG 0.00 0.00 Z 0.00 0.50 \nZ 0.00 0.50 R -0.50 0.50 \nR -0.50 0.50 X -0.50 0.00 \nKPLANE_SLAB \n-0.5 -0.5 1.0 0.0 0.0 1.0 \n\n# 5.5. Surface state spin texture \n\nThe key ingredient to generate topological non-trivial properties is the SOC interaction, which have a similar behavior as a Lorentz force in quantum Hall states. The SOC interaction will make a spin and a momentum locked to each other, forming a spin texture in momentum space. For different topological phase, the spin texture will be different [70]. In topological insulator ${\\tt B i}_{2}{\\tt S e}_{3}$ , the spin texture is Dirac type. The spin texture calculated by WannierTools for HfPtGe is shown in Fig. 4c. The related settings for spin texture calculations in wt.in are as follows. \n\n![](images/4aaea6a175086f00ee259e476252eb4df353fee6c666cabd9d59234cbd24b4b5.jpg) \nFig. 4. Surface state spectrum (SSS) of HfPtGe in the presence of SOC. a. SSS along high symmetry $k$ -line at different energies. b. SSS in 2D BZ at a fixed energy $E-E_{F}=0.{\\mathrm{c}}$ Spin texture for the ${\\mathsf{S S S i n b}}$ . \n\n&CONTROL \nSlabSpintexture_calc $\\mathbf{\\sigma}=\\mathbf{\\sigma}$ T \n/ \n\nKPLANE_SLAB -0.50 -0.50 1.00 0.00 0.00 1.00 \n\n# 6. Conclusions \n\nIn conclusion, we presented an open-source software package called WannierTools. It is very user-friendly and is written in Fortran90, using MPI techniques to get excellent performance in computer cluster. We showed how to use this software package to identify the topological properties for a new material and to get the surface state spectrum which can be compared with experimental data. As an example, we explored a new topological material HfPtGe, which was identified as a Dirac nodal line semimetal. \n\n# Acknowledgments \n\nQSW would like to thank Xi Dai, Zhong Fang, Lei Wang, Li Huang, Dominik Gresch, Zhida Song for helpful discussions. Especially, QSW appreciates Rui Yu and Haijun Zhang for their kindly helps at the beginning of this project. QSW, AAS, MT were supported by Microsoft Research, and the Swiss National Science Foundation through the National Competence Centers in Research MARVEL and QSIT, ERC Advanced Grant SIMCOFE. QSW was also supported by the National Natural Science Foundation of China (11404024). SNZ was supported by NSF-China under Grants No. 11074174. HFS was supported by National High Technology Research and Development Program of China under Grant 2015AA01A304, and Science Challenge Project No. JCKY2016212A502. This job was started in IOP CAS, finished in ETH Zurich. \n\n# Appendix. wt.in for HfPtGe \n\n&TB_FILE \nHrfile $\\mathbf{\\sigma}=\\mathbf{\\sigma}$ \"wannier90_hr.dat\" \n/ \n&CONTROL \nBulkBand_calc ${\\begin{array}{l}{=\\mathrm{~T~}}\\\\ {=\\mathrm{~T~}}\\\\ {=\\mathrm{~T~}}\\\\ {=\\mathrm{~T~}}\\\\ {=\\mathrm{~T~}}\\\\ {=\\mathrm{~T~}}\\\\ {=\\mathrm{~T~}}\\end{array}}$ \nBulkFS_calc \nBulkGap_plane_calc \nZ2_3D_calc \nSlabSS_calc \nSlabArc_calc \nSlabSpintexture_calc \n/ \n&SYSTEM \nNumOccupied $\\mathbf{\\sigma}=\\mathbf{\\sigma}$ 64 \n$\\mathsf{S}0\\mathsf{C}=\\mathsf{\\Omega}1$ \nE_FERMI $\\mathbf{\\tau}=\\mathbf{\\tau}$ 8.4551 \n/ \n\n&PARAMETERS E_arc $\\mathit{\\Theta}=\\ 0.0$ \n\nOmegaNum $\\mathit{\\Theta}=\\ 100\\$ \nOmegaMin $\\mathbf{\\epsilon}=\\mathbf{\\epsilon}-\\mathbf{0}.6$ \nOmegaMax $\\mathbf{\\tau}=\\mathbf{\\tau}$ 0.6 \n$\\mathtt{N k1}\\ =\\ 101$ \n$\\mathtt{N k}2\\ =\\ 201$ \n$\\mathtt{N k3}\\ =\\ 101$ \n${\\tt N P}=2$ \nGap_threshold = 0.05 \n/ LATTICE \nAngstrom \n6.6030000 0.0000000 0.0000000 0.0000000 3.9500000 0.0000000 0.0000000 0.0000000 7.6170000 \n\nATOM_POSITIONS \n12 \nDirect \nHf 0.029900 0.250000 0.186300 \nHf 0.470100 -0.250000 0.686300 \nHf -0.029900 0.750000 -0.186300 \nHf 0.529900 0.250000 0.313700 \nGe 0.750600 0.250000 0.621500 \nGe -0.250600 -0.250000 1.121500 \nGe -0.750600 0.750000 -0.621500 \nGe 1.250600 0.250000 -0.121500 \nPt 0.142500 0.250000 0.561700 \nPt 0.357500 -0.250000 1.061700 \nPt -0.142500 0.750000 -0.561700 \nPt 0.642500 0.250000 -0.061700 \n\n# PROJECTORS \n\n5 5 5 5 3 3 3 3 6 6 6 6 \nHf dxy dyz dxz dx2-y2 dz2 Hf dxy dyz dxz dx2-y2 dz2 Hf dxy dyz dxz dx2-y2 dz2 Hf dxy dyz dxz dx2-y2 dz2 Ge px py pz \nGe px py pz \nGe px py pz \nGe px py pz \nPt s dxy dyz dxz dx2-y2 dz2 Pt s dxy dyz dxz dx2-y2 dz2 Pt s dxy dyz dxz dx2-y2 dz2 Pt s dxy dyz dxz dx2-y2 dz2 \n\nSURFACE $\\begin{array}{c c c}{{1}}&{{0}}&{{0}}\\\\ {{0}}&{{0}}&{{1}}\\\\ {{0}}&{{-1}}&{{0}}\\end{array}$ \n\n
KPATH_BULK
9Y -0.500000.000000.00000G0.000000.000000.00000
G0.000000.000000.00000Z0.000000.000000.50000
Z0.000000.000000.50000T -0.500000.000000.50000
T-0.500000.000000.50000Y-0.500000.000000.00000
Y-0.500000.000000.00000S-0.500000.500000.00000
S-0.500000.500000.00000X0.000000.500000.00000
X0.000000.500000.00000U0.000000.500000.50000
U0.000000.500000.50000R -0.500000.500000.50000
R -0.500000.500000.50000S -0.500000.500000.00000
\n\nX -0.50 0.00 G 0.00 0.00 \nG 0.00 0.00 Z 0.00 0.50 \nZ 0.00 0.50 R -0.50 0.50 \nR -0.50 0.50 X -0.50 0.00 \n\nKPLANE_SLAB -0.5 -0.5 1.0 0.0 0.0 1.0 \n\nKPLANE_BULK -0.50 0.00 -0.50 1.00 0.00 0.00 0.00 0.00 1.00 \n\nKCUBE_BULK \n-0.50 -0.50 -0.50 \n1.00 0.00 0.00 \n0.00 1.00 0.00 \n0.00 0.00 1.00 \n\n# References \n\n[1] X.-L. Qi, S.-C. Zhang, Rev. Modern Phys. 83 (2011) 1057–1110. http://dx.doi.org/10.1103/RevModPhys.83.1057. [2] M.Z. Hasan, C.L. Kane, Rev. Modern Phys. 82 (2010) 3045–3067. http://dx.doi.org/10.1103/RevModPhys.82.3045. [3] C.L. Kane, E.J. Mele, Phys. Rev. Lett. 95 (2005) 226801. http://dx.doi.org/10.1103/PhysRevLett.95.226801. [4] B.A. Bernevig, T.L. Hughes, S.-C. Zhang, Science 314 (5806) (2006) 1757–1761. http://dx.doi.org/10.1126/science.1133734. [5] M. König, S. Wiedmann, C. Brüne, A. Roth, H. Buhmann, L.W. Molenkamp, X.-L. Qi, S.-C. Zhang, Science 318 (5851) (2007) 766–770. http://dx.doi.org/10.1126/science. 1148047. [6] D. Hsieh, D. Qian, L. Wray, Y. Xia, Y.S. Hor, R.J. Cava, M.Z. Hasan, Nature 452 (7190) (2008) 970–974. http://dx.doi.org/10.1038/nature06843. [7] H. Zhang, C.-X. Liu, X.-L. Qi, X. Dai, Z. Fang, S.-C. Zhang, Nat. Phys. 5 (6) (2009) 438–442. http://dx.doi.org/10.1038/nphys1270. [8] Y. Xia, D. Qian, D. Hsieh, L. Wray, A. Pal, H. Lin, A. Bansil, D. Grauer, Y.S. Hor, R.J. Cava, M.Z. Hasan, Nat. Phys. 5 (6) (2009) 18. http://dx.doi.org/10.1038/nphys1274. [9] Z. Wang, Y. Sun, X.-Q. Chen, C. Franchini, G. Xu, H. Weng, X. Dai, Z. Fang, Phys. Rev. B 85 (2012) 195320. http://dx.doi.org/10.1103/PhysRevB.85.195320. [10] Z. Wang, H. Weng, Q. Wu, X. Dai, Z. Fang, Phys. Rev. B 88 (12) (2013) 125427. http://dx.doi.org/10.1103/PhysRevB.88.125427. [11] X. Wan, A.M. Turner, A. Vishwanath, S.Y. Savrasov, Phys. Rev. B 83 (2011) 205101. http://dx.doi.org/10.1103/PhysRevB.83.205101. [12] H. Weng, C. Fang, Z. Fang, B.A. Bernevig, X. Dai, Phys. Rev. X 5 (2015) 011029. http://dx.doi.org/10.1103/PhysRevX.5.011029. [13] A.A. Soluyanov, D. Gresch, Z. Wang, Q. Wu, M. Troyer, X. Dai, B.A. Bernevig, Nature 527 (7579) (2015) 495–498. http://dx.doi.org/10.1038/nature15768. [14] Z. Wang, A. Alexandradinata, R.J. Cava, B.A. Bernevig, Nature 532 (2016) 189–194. http://dx.doi.org/10.1038/nature17410. [15] A.A. Burkov, M.D. Hook, L. Balents, Phys. Rev. B 84 (2011) 235126. http://dx.doi.org/10.1103/PhysRevB.84.235126. [16] R. Yu, H. Weng, Z. Fang, X. Dai, X. Hu, Phys. Rev. Lett. 115 (2015) 036807. http://dx.doi.org/10.1103/PhysRevLett.115.036807. [17] G. Bian, T.-R. Chang, H. Zheng, S. Velury, S.-Y. Xu, T. Neupert, C.-K. Chiu, S.-M. Huang, D.S. Sanchez, I. Belopolski, N. Alidoust, P.-J. Chen, G. Chang, A. Bansil, H.-T. Jeng, H. Lin, M.Z. Hasan, Phys. Rev. B 93 (2016) 121113. http://dx.doi.org/10.1103/PhysRevB.93.121113. [18] T. Bzdušek, Q. Wu, A. Rüegg, M. Sigrist, A.A. Soluyanov, Nature 538 (2016) 75–78. http://dx.doi.org/10.1038/nature19099. [19] Note: For 3D system, it is surface. For 2D system, surface represents the edge. For the simplicity, we use surface in the whole article. [20] M.Z. Hasan, C.L. Kane, Rev. Modern Phys. 82 (4) (2010) 3045–3067. http://dx.doi.org/10.1103/RevModPhys.82.3045. [21] C.L. Kane, E.J. Mele, Phys. Rev. Lett. 95 (2005) 146802. http://dx.doi.org/10.1103/PhysRevLett.95.146802. [22] D.J. Thouless, M. Kohmoto, M.P. Nightingale, M. den Nijs, Phys. Rev. Lett. 49 (1982) 405–408. http://dx.doi.org/10.1103/PhysRevLett.49.405. [23] R. Yu, X.L. Qi, A. Bernevig, Z. Fang, X. Dai, Phys. Rev. B 84 (2011) 075119. http://dx.doi.org/10.1103/PhysRevB.84.075119. [24] A.A. Soluyanov, D. Vanderbilt, Phys. Rev. B 83 (2011) 235401. http://dx.doi.org/10.1103/PhysRevB.83.235401. [25] D. Gresch, G. Autès, O.V. Yazyev, M. Troyer, D. Vanderbilt, B.A. Bernevig, A.A. Soluyanov, Phys. Rev. B 95 (2017) 075146. http://dx.doi.org/10.1103/PhysRevB.95.075146. [26] S. Coh, D. Vanderbilt, Python tight binding (PythTB), 2013. http://www.physics.rutgers.edu/pythtb. [27] A.A. Mostofi, J.R. Yates, Y.S. Lee, I. Souza, D. Vanderbilt, N. Marzari, Comput. Phys. Comm. 178 (9) (2008) 685–699. http://dx.doi.org/10.1016/j.cpc.2007.11.016. [28] J.C. Slater, G.F. Koster, Phys. Rev. 94 (1954) 1498–1524. http://dx.doi.org/10.1103/PhysRev.94.1498. [29] N. Marzari, A.A. Mostofi, J.R. Yates, I. Souza, D. Vanderbilt, Rev. Modern Phys. 84 (2012) 1419–1475. http://dx.doi.org/10.1103/RevModPhys.84.1419. [30] M. Willatzen, L.C. Lew Yan Voon, The k·p Method-Electronic Properties of Semiconductors, Vol. 53, Springer Berlin Heidelberg, Berlin, Heidelberg, 2009, pp. 1689–1699. http://dx.doi.org/10.1007/978-3-540-92872-0. [31] A.A. Mostofi, J.R. Yates, G. Pizzi, Y.-S. Lee, I. Souza, D. Vanderbilt, N. Marzari, Comput. Phys. Comm. 185 (8) (2014) 2309–2310. http://dx.doi.org/10.1016/j.cpc.2014.05.003. [32] L. Fu, C.L. Kane, Phys. Rev. B 76 (4) (2007) 045302. http://dx.doi.org/10.1103/PhysRevB.76.045302. [33] T. Fukui, Y. Hatsugai, J. Phys. Soc. Japan 76 (5) (2007) 053702. http://dx.doi.org/10.1143/JPSJ.76.053702. [34] S. Coh, D. Vanderbilt, Phys. Rev. Lett. 102 (2009) 107603. http://dx.doi.org/10.1103/PhysRevLett.102.107603. [35] N. Marzari, D. Vanderbilt, Phys. Rev. B 56 (1997) 12847–12865. http://dx.doi.org/10.1103/PhysRevB.56.12847. [36] R.D. King-Smith, D. Vanderbilt, Phys. Rev. B 47 (1993) 1651–1654. http://dx.doi.org/10.1103/PhysRevB.47.1651. [37] A.A. Soluyanov, D. Vanderbilt, Phys. Rev. B 83 (3) (2010) 035108. http://dx.doi.org/10.1103/PhysRevB.83.035108. [38] J. Zak, Phys. Rev. Lett. 62 (1989) 2747–2750. http://dx.doi.org/10.1103/PhysRevLett.62.2747. [39] D. Xiao, M.-C. Chang, Q. Niu, Rev. Modern Phys. 82 (2010) 1959–2007. http://dx.doi.org/10.1103/RevModPhys.82.1959. [40] D.J. Thouless, M. Kohmoto, M.P. Nightingale, M. den Nijs, Phys. Rev. Lett. 49 (1982) 405–408. http://dx.doi.org/10.1103/PhysRevLett.49.405. [41] M.-C. Chang, Q. Niu, J. Phys.: Condens. Matter 20 (19) (2008) 193202. http://stacks.iop.org/0953-8984/20/i=19/a=193202. [42] L.M. Falicov, F. Yndurain, J. Phys. C: Solid State Phys. 8 (2) (1975) 147–157. http://dx.doi.org/10.1088/0022-3719/8/2/009. http://stacks.iop.org/0022-3719/8/i=2/a=009? key=crossref.ac4c021c6e5663539c9803c4730140dd. [43] D.H. Lee, J.D. Joannopoulos, Phys. Rev. B 23 (1981) 4988–4996. http://dx.doi.org/10.1103/PhysRevB.23.4988. http://link.aps.org/doi/10.1103/PhysRevB.23.4988. [44] D.H. Lee, J.D. Joannopoulos, Phys. Rev. B 23 (1981) 4997–5004. http://dx.doi.org/10.1103/PhysRevB.23.4997. http://link.aps.org/doi/10.1103/PhysRevB.23.4997. [45] F. Guinea, C. Tejedor, F. Flores, E. Louis, Phys. Rev. B 28 (1983) 4397–4402. http://dx.doi.org/10.1103/PhysRevB.28.4397. [46] M.P.L. Sancho, J.M.L. Sancho, J. Rubio, J. Phys. F: Met. Phys. 14 (5) (1984) 1205–1215. http://dx.doi.org/10.1088/0305-4608/14/5/016. [47] M.P.L. Sancho, J.M.L. Sancho, J. M.L. Sancho, J. Rubio, J. Phys. F: Met. Phys. 15 (4) (1985) 851–858. http://dx.doi.org/10.1088/0305-4608/15/4/009. \n\n[48] X. Dai, T.L. Hughes, X.-L. Qi, Z. Fang, S.-C. Zhang, Phys. Rev. B 77 (2008) 125319. http://dx.doi.org/10.1103/PhysRevB.77.125319. \n[49] J.A. Nelder, R. Mead, Comput. J. 7 (4) (1965) 308–313. http://dx.doi.org/10.1093/comjnl/7.4.308. \n[50] M. Hazewinkel, Encyclopaedia of Mathematics (set), in: Encyclopaedia of Mathematics, Springer, Netherlands, 1994. \n[51] W. Press, Numerical Recipes 3rd Edition: The Art of Scientific Computing, Cambridge University Press, 2007. \n[52] F.Y. Bruno, A. Tamai, Q.S. Wu, I. Cucchi, C. Barreteau, A. de la Torre, S.M. Walker, S. Riccò, Z. Wang, T.K. Kim, M. Hoesch, M. Shi, N.C. Plumb, E. Giannini, A.A. Soluyanov, F. Baumberger, Phys. Rev. B 94 (2016) 121112(R). http://dx.doi.org/10.1103/PhysRevB.94.121112. \n[53] A. Tamai, Q.S. Wu, I. Cucchi, F.Y. Bruno, S. Ricco, T.K. Kim, M. Hoesch, C. Barreteau, E. Giannini, C. Bernard, A.A. Soluyanov, F. Baumberger, Phys. Rev. X 6 (2016) 031021. \nhttp://dx.doi.org/10.1103/PhysRevX.6.031021. \n[54] G.P.P. Giuseppe Grosso, Solid State Physics, Second Edition, second ed., Academic Press, 2013, pp. 535–536. \n[55] H. Inoue, A. Gyenis, Z. Wang, J. Li, S.W. Oh, S. Jiang, N. Ni, B.A. Bernevig, A. Yazdani, Science 351 (6278) (2016) 1184–1187. http://dx.doi.org/10.1126/science.aad8766. \nhttp://arxiv.org/abs/http://science.sciencemag.org/content/351/6278/1184.full.pdf. \n[56] H. Zhang, C.-X. Liu, S.-C. Zhang, Phys. Rev. Lett. 111 (2013) 066801. http://dx.doi.org/10.1103/PhysRevLett.111.066801. \n[57] T. Williams, C. Kelley, et al., Gnuplot 5.0: A portable, multi-platform, command-line driven graphing utility, 2015. http://gnuplot.sourceforge.net/. \n[58] Z. Zhu, G.W. Winkler, Q. Wu, J. Li, A.A. Soluyanov, Phys. Rev. X 6 (2016) 031003. http://dx.doi.org/10.1103/PhysRevX.6.031003. \n[59] G.W. Winkler, A.A. Soluyanov, Q. Wu, M. Troyer, P. Krogstrup, Phys. Rev. Lett. 117 (2016) 076403. http://dx.doi.org/10.1103/PhysRevLett.117.076403. \n[60] WannierTools Github repository, 2016. https://github.com/quanshengwu/wannier_tools/. \n[61] WannierTools wiki, 2016. https://github.com/quanshengwu/wannier_tools/wiki/. \n[62] C. Benndorf, H. Eckert, R. Pottgen, Dalton Trans. 45 (2016) 8215–8223. http://dx.doi.org/10.1039/C6DT00861E. \n[63] S. Yashiro, Y. Nagata, H. Samata, S. Abe, J. Alloys Compd. 298 (12) (2000) 51–58. http://dx.doi.org/10.1016/S0925-8388(99)00649-0. \n[64] Y. Nagata, K. Sodeyama, S. Yashiro, H. Sasaki, H. Samata, T. Uchida, M. Lan, J. Alloys Compd. 281 (2) (1998) 112–116. http://dx.doi.org/10.1016/S0925-8388(98)00780-4. \n[65] The reason that I put a $\\sim$ onto $\\tilde{G}_{y}$ is that the shifting vector in $\\tilde{G}_{y}$ is perpendicular to the mirror plane. The square of $\\tilde{G}_{y}$ is the same as the square of $m_{y}$ . In this regard, we can call $\\tilde{G}_{y}$ a mirror plane. \n[66] G. Kresse, J. Furthmüller, Phys. Rev. B 54 (1996) 11169–11186. http://dx.doi.org/10.1103/PhysRevB.54.11169. \n[67] G. Kresse, D. Joubert, Phys. Rev. B 59 (1999) 1758–1775. http://dx.doi.org/10.1103/PhysRevB.59.1758. \n[68] M.N. Ali, J. Xiong, S. Flynn, J. Tao, Q.D. Gibson, L.M. Schoop, T. Liang, N. Haldolaarachchige, M. Hirschberger, N.P. Ong, R.J. Cava, Nature 514 (7521) (2014) 205–208. \n[69] L. Fu, C.L. Kane, Phys. Rev. B 76 (2007) 045302. http://dx.doi.org/10.1103/PhysRevB.76.045302. \n[70] H. Zhang, C.-X. Liu, S.-C. Zhang, Phys. Rev. Lett. 111 (2013) 066801. http://dx.doi.org/10.1103/PhysRevLett.111.066801. " + }, + { + "id": "10.1038_ncomms15199", + "DOI": "10.1038/ncomms15199", + "DOI Link": "http://dx.doi.org/10.1038/ncomms15199", + "Relative Dir Path": "mds/10.1038_ncomms15199", + "Article Title": "Face classification using electronic synapses", + "Authors": "Yao, P; Wu, HQ; Gao, B; Eryilmaz, SB; Huang, XY; Zhang, WQ; Zhang, QT; Deng, N; Shi, LP; Wong, HSP; Qian, H", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000x (20x) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.", + "Times Cited, WoS Core": 759, + "Times Cited, All Databases": 805, + "Publication Year": 2017, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000401222500002", + "Markdown": "# Face classification using electronic synapses \n\nPeng $\\Upsilon a o^{1}$ , Huaqiang Wu1,2, Bin Gao1,2, Sukru Burc Eryilmaz3, Xueyao Huang1, Wenqiang Zhang1, Qingtian Zhang1, Ning Deng1,2, Luping $\\mathsf{S h i}^{2}$ , H.-S. Philip Wong3 & He Qian1,2 \n\nConventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is $1,000\\times(20\\times)$ lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system. \n\nRrecacoengngnititniagvde crnocmespuirtninalgm- fcmohrie e evgarineditanytg opfr imanltiysetlei gtsoe1,nta htiaisesuvkaesl recognition2,3, to navigating the city streets for a self-driving car4. Currently, these demonstrations2–5 use conventional central processing units and graphics processing units with off-chip memories to implement large-scale neural networks that are trained offline and require kilowatts of power consumption. Custom-designed neuromorphic hardware6 with complementary metal oxide semiconductor (CMOS) technologies greatly reduces the energy consumption required. Yet, current approaches6–10 are not scalable to the large number of synaptic weights required for solving increasingly complex problems in the coming decade11. The main reason that current approaches are inadequate arise from the fact that on-chip weight storage using static random access memory is area inefficient and is thus limited in memory capacity11, and off-chip weight storage using dynamic random access memory incurs $>100$ times larger power consumption than on-chip memory12. Integrating non-volatile, analogue weight storage on-chip, in close proximity to the neuron circuits is essential for future, large-scale energy-efficient neural networks that are trained online to respond to changing input data instantly like the human brain. Meanwhile, pattern recognition tasks based on analogue resistive random access memory (RRAM) have been demonstrated either through simulations or on a small crossbar array13,14. However, the analogue RRAM cells still face the major challenges such as CMOS compatibility and cross-talk issues, which blocks the realization of large scale array integration. On the other hand, resistive memory arrays with relative mature technology have the problem on realizing bidirectional analogue resistance modulation15, in which the cell conductance changes continuously in response to the SET (high conductance state to low conductance state transition) and the RESET (low conductance state to high conductance state transition) operation. This issue harms the online training function. Innovations are urgently required to find a suitable structure to combine the advantages. \n\nIn this paper, an optimized memory cell structure, which is compatible with CMOS process and has bidirectional analogue behaviour is implemented. This RRAM device16,17 is integrated in a 1024-cell array and 960 cells are employed in a neuromorphic network18. The network is trained online to recognize and classify grey-scale face images from the Yale Face Database19. In the demonstration, we propose two programming schemes suitable for analogue resistive memory arrays: one using a write-verify method for classification performance and one without writeverify for simplifying the control system. These two programming methods are used for parallel and online weight update and both converge successfully. This network is tested with unseen face images from the database and some constructed face images with up to $31.25\\%$ noise. The accuracy is approximately equivalent to the standard computing system. Apart from the high recognition accuracy achieved, this on-chip, analogue weight storage using RRAM consumes 1,000 times less energy than an implementation of the same network using an Intel Xeon Phi processor with off-chip weight storage. The outstanding performance of this neuromorphic network mainly results from such a cell structure for reliable analogue weight storage. This bidirectional analogue RRAM array is capable of integrating with CMOS circuits to a large scale and suitable for running more complex deep neural networks20–22. \n\n# Results \n\nRRAM-based neuromorphic network. A one-layer perceptron neural network is adopted for this hardware system demonstration, as shown in Supplementary Fig. 1. The architecture of one transistor and one resistive memory (1T1R) array, illustrated in Fig. 1a, is used to realize this neural network. The cells in a row are organized by connecting the transistor source to the source line (SL) and connecting transistor gate to the same word line (WL), while the cells in a column are organized by connecting the top electrode of the resistive memory to the bit line (BL). Figure 1a describes how the network is mapped to the 1T1R structure, that is, the input of preneuron layer, adaptable synaptic weight and weighted sum output of postneuron layer are in accordance with the pulse input from BL, cell conductance and current output through SL, respectively. Remarkable bidirectional analogue switching behaviour of our device allows us to use single 1T1R cell as a synapse to save area and energy, instead of combining two 1T1R cells as a single synapse (or weight) with differential encoding as was done in previous works13,15. The 1T1R array consists of 1024 cells with 128 rows and 8 columns and is optimized for bidirectional analogue switching. The arrays are constructed using fully CMOS-compatible fabrication process (see Methods section), as shown in Fig. 1b. \n\nThis network is trained to distinguish one person’s face from others. The operation procedure consists of two phases: training and testing. The flow diagram of the algorithm is given in Fig. 2a. The training phase includes two subprocedures: inference and weight update. During the inference process, the nine training images (belonging to three persons) are input to the network on BL side. The activation function of the output neurons is realized by measuring the total currents on SL side (three lines) to obtain the weighted sum and applying the sum to a nonlinear activation function (tanh function) to get three output values. Each pattern is classified according to the neuron that has the largest output values. These nine images are chosen from the Yale Face Database and cropped and down-sampled to 320 pixels in $20\\times16$ size, as Fig. 2c shows. The image is in grey scale where each pixel value ranges from 0 to 255 with smaller value corresponding to darker square. A parallel read operation (Fig. 2b) is employed for inference. The input voltage pulses are applied row by row on the fabricated array through BLs, and the total current through the SL is sensed and accumulated by a conductance linear weighting process, as the equation shows: \n\n![](images/f44a22d31e774a0ab38ec3d8f48b1b5c5f31f14caf00348f9407c91c49e6cd56.jpg) \nFigure 1 | The 1T1R architecture and the 1024-cell-1T1R array. (a) Mapping of a one-layer neural network on the 1T1R array, that is, the input of preneuron layer, adaptable synaptic weight and weighted sum output of postneuron layer maps to the pulse input from BL, cell conductance and current output through SL, respectively. In 1T1R, $'\\top^{\\prime}$ represents transistor, $'\\mathsf{R}^{\\prime}$ represents RRAM. (b) The micrograph of a fabricated 1024-cell-1T1R array using fully CMOS compatible fabrication process. \n\n![](images/25676da0500ef54fed04109725e86022d889e959c4bb3d0cb898aeb6b961a483.jpg) \nFigure 2 | Flowchart of the perceptron model. (a) The training process flow chart. In this demonstration, a batch learning model is used to accelerate the converging speed. Here $'n^{\\prime}$ represents the number of pattern, ranging from 1 to 9, $'\\dot{I}^{\\prime}$ implies the index of a pixel of an input pattern and can be defined from 1 to 320, $'j^{\\prime}$ is the number of output neuron that is 1–3. A correct classification during the inference phase means the active function value of a matching class of the input pattern is greater than other two classes. This network converges when all training patterns are correctly recognized. (b) The schematic of parallel read operation and how a pattern is mapped to the input. (c) The nine training images, which is a cropped and subsampled subset of the Yale Face Database19. \n\n$$\nI_{j}(n)=\\sum_{i=1}^{320}W_{i j}V_{i}(n).\n$$ \n\nbetween the reference output when loading the nth pattern and the corresponding target value determined by the pattern’s label, as shown in Fig. 2a. $\\bar{\\Delta}W_{i j}$ is the desired change for the weight connecting the neuron $i$ in input layer and the neuron $j$ in output layer. Equation (2) follows the delta rule24 and implements both sign- and amplitude-based weight update, while equation (3) only points out the switching direction (sign-based only), following the Manhattan rule25. The hyper-parameters ( $\\upbeta$ controls the nonlinearity of activation function, $\\eta$ is the learning rate and $f^{\\mathrm{t}}$ is the target value) in Fig. 2a can be found in the Methods section (test platform and the hyper-parameter values), along with the information of the platform of this demonstration. \n\nThe testing process is also a parallel read operation that reads all rows at the same time to identify the class of an input test image that is different from all the training images. \n\nHere $V_{i}\\left(n\\right)$ is the input signal and represents the related pixel $i$ in the pattern $n$ . The pixel value leads to a matching input pulse number during the total 255 time slices to sense the weighted sum of currents, as illustrated in Fig. 2b. The total current is measured externally using the source measurement unit of a semiconductor parameter analyser, while the nonlinear activation function to the current is implemented in the software. During the weight update process, the programming of the RRAM is conducted after loading the entire nine training patterns at each iteration23. The programming process follows either one of the two learning rules (2) or (3) below: an update scheme using write-verify and an update scheme without write-verify. \n\n$$\n\\Delta W_{i j}=\\eta\\sum_{n=1}^{9}\\Delta_{i j}(n),\n$$ \n\n$$\n\\Delta W_{i j}=\\eta\\cdot s\\mathrm{gn}\\sum_{n=1}^{9}\\Delta_{i j}(n).\n$$ \n\nHere the learning rate $\\eta$ is a constant. $\\Delta_{i j}(n)$ is the calculated error \n\nRealization of bidirectional analogue RRAM array. RRAM devices based on resistive switching phenomenon exhibit promising potential as the electronic synapse26–29. These devices have higher operation speed than the biological counterpart and they also have low energy consumption29. Besides, they are compatible with CMOS fabrication process30–32 and can be scaled down33 remarkably to reach density as high as $10^{11}$ synapses per $\\mathrm{cm}^{2}$ . Although continuous conductance modulation behaviour on a single resistive switching device and simple neuromorphic computing on a small resistive array were reported recently14,30, to our knowledge, large neuromorphic network utilizing the bidirectional analogue behaviour of resistive switching synapse for face classification task is not realized yet. This is due to the nature of imperfection of the device11,13,15, such as abrupt switching during SET, the variation between each cell and the fluctuation during repeated cycles. These shortcomings have prevented the implementation of bidirectional analogue weight update and reliable update operations for a large array. Generally, the physical mechanism of the resistive switching process is attributed to the reversible modulation of the local concentration of the oxygen vacancies in a nanoscale region17 of the oxide. The generation or migration of a small number of oxygen vacancies in this region may induce a notable change of the conductance and thus makes the device stochastically exhibiting abrupt conductance transition step by step. This abrupt transition is more readily observed during the SET process, since the generation of each oxygen vacancy during SET process can increase the local electric field/temperature and accelerate the generation of other vacancies, and finally resulting in a large amount of oxygen vacancies formed in a short time, analogous to avalanche breakdown. This positive feedback of oxygen vacancy generation and electrical field/temperature should be effectively suppressed to avoid abrupt switching. Furthermore, the random distribution of oxygen vacancies contributes to the large variations of conductance, operation voltage and switching speed from cell to cell, which makes the system difficult to converge during the training process. \n\nThe $\\mathrm{TiN/TaO}_{x}/\\mathrm{HfAl}_{y}\\mathrm{O}_{x}/\\mathrm{TiN}$ stacks are used as the analogue RRAM cell. All these materials are fab-friendly to enable realizing future high-density and large-scale array integration with CMOS technology. To fight against the electric field-induced avalanche breakdown during SET process, a conductive metal oxide layer is used to enhance the inner temperature of the filament region, and thus avoiding large local electric field34. The conductive metal oxide layer also helps to reserve plenty of oxygen ions, which improves the analogue behaviour during RESET process. The robust analogue switching behaviour with good cell-to-cell uniformity (Supplementary Note 1) benefits a lot from the utilizing of $\\mathrm{HfAl}_{y}\\mathrm{O}_{x}$ switching layer, since $\\mathrm{HfO}_{2}$ is well-known as phase-stable. And the $\\mathrm{HfO}_{x}/\\mathrm{AlO}_{y}$ laminate structure is leveraged to control the generation of oxygen vacancies in such a RRAM cell design. The ratio between $\\mathrm{HfO}_{2}$ and ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ is well adjusted during fabrication process and optimized as 3:1. This structure design shows a better analogue performance compared with $\\mathrm{TiN/TaO}_{x}/\\mathrm{HfO}_{2}/\\mathrm{TiN}$ (Supplementary Note 2). \n\nThe 1T1R structure is used to further improve the bidirectional analogue switching performance and uniformity. Compared to the two-terminal RRAM cell, the three-terminal 1T1R cell improves the controllability of continuous weights tuning at array level since the compliance current controlled by the transistor’s gate voltage can significantly suppress the overshoot and feedback effects during SET process. In addition, exploiting transistors could guarantee persistent scaling-up of array scale by eliminating the sneak path and avoid several bottlenecks of analogue RRAM array. \n\nFigure 3a shows the smooth and symmetrical $I{-}V$ curves of the optimized 1T1R cell. A 40 times window is exhibited using a quasi-DC sweep. The elimination of the abrupt conductance transition at both SET and RESET processes enables bidirectional continuous conductance change for weight update. Typical analogue behaviour under identical pulse train during SET and RESET processes is shown in Fig. ${3\\mathrm{b}},\\boldsymbol{\\mathbf{c}}.$ , respectively, showing that the conductance can be modulated by applying identical voltage pulses (conductance changes under continuous SET and RESET pulse cycles is shown in Supplementary Fig. 8). This remarkably simplifies the update strategy and control circuits. Similar analogue behaviours can be observed under different pulse conditions for a wide range of pulse amplitude and duration (see Supplementary Note 1). \n\nTo further suppress the influence of the slight resistance variation across cells in the array, a write-verify programming scheme that is in accordance with equation (2) is proposed and experimentally compared with the scheme without write-verify that implements equation (3). The write-verify flow is shown in Supplementary Fig. 9. During the weight update phase of each learning iteration, identical voltage pulses are applied to the 1T1R cell to increase (or decrease) the cell conductance, until the conductance is larger (or smaller) or equal to the target value35, based on equation(2). Hence the final synapse weight only slightly deviates from the target in most of cases. In contrast, without write-verify, only one SET (or RESET) pulse is applied on the selected 1T1R cell to increase (or decrease) the conductance without checking whether it reaches the target value or not. Avoiding the write-verify step simplifies the control circuit since it is not necessary to calculate the specific analogue value of the error between the target weight and the current weight, but it may slow down the convergence due to cycle-to-cycle and device-todevice variations. Figure 3d,e specify the waveforms during the SET process for the scheme with and without write-verify. Similar RESET waveforms are illustrated in Supplementary Fig. 10 and are applied in parallel row by row as well. \n\nThe switching window and conductance modulation steps depend on the pulse width and the pulse amplitude, which leads to a trade-off between the learning accuracy and the convergence speed. The effects of the pulse condition on the training process are shown in Fig. 3f,g. We can see the opposite trend that a higher pulse amplitude requires less number of pulses but results in a larger deviation from the target, creating a trade-off between accuracy and speed. When the pulse amplitude is $<1.5\\mathrm{V}$ , the device conductance is not able to reach the higher conductance range (for example, $>10\\upmu\\mathrm{S},$ . This implies another trade-off between the conductance modulation range and the accuracy, which is detailed in Methods section ‘Device performance during write-verify RESET process’. The operation conditions should be carefully optimized according to application at hand as well as speed, energy and accuracy requirements: for example, lower amplitude and shorter duration could be employed to increase modulation accuracy for both training rules at the expense of speed. Similar measurement is conducted during write-verify SET process and the result is shown in Methods section ‘Device performance during write-verify SET process’. The SET and RESET operation conditions with $V_{\\mathrm{wl}}=\\bar{2}.3\\:\\mathrm{V}$ , $V_{\\mathrm{bl}}{=}2.1\\:\\mathrm{V}$ (50 ns) and $V_{\\mathrm{wl}}{\\stackrel{-}{=}}8.0\\mathrm{V}$ , $V_{\\mathrm{bl}}{=}2.0\\:\\mathrm{V}$ $(50\\mathrm{ns})$ provides a reasonable balance between accuracy and speed and hence are used in the following experiments. \n\nGrey-scale face image classification. The optimized 1024-cell1T1R array is used to demonstrate face classification by the neuromorphic network. All the 1T1R cells are programmed to an initially state around $40\\upmu\\mathrm{S}$ . Even with slight device variations, the system works smoothly under both operation schemes. The network converges after 10 iterations for the write-verify operation scheme, while for the scheme without write-verify, the network converges after 58 iterations. Figure $^{4\\mathrm{a},\\mathrm{b}}$ reveal the progress of the training process when identifying the face of the first person. The trace of conductance evolution in single RRAM cell is shown in Supplementary Note 3. The final conductance distribution and visual map diagram are presented in Fig. $^{4c,\\mathrm{d}}$ . Conductances are normalized as integers from 0 to 255 in the map. The detailed process for the faces of other two people are provided in Supplementary Figs 15 and 16. Furthermore, another two demonstrations are conducted, one starting from a tight low conductance distribution around $4\\upmu\\mathrm{S}$ and another proceeding from a wide conductance distribution state. Both succeed to converge (see Supplementary Note 4). The initial distribution state hardly affects the convergence of the training. \n\nTwo sets of patterns are used in the test process. One set contains 24 images (Supplementary Fig. 19) in the Yale Face Database for these three persons (not shown during training). The other set consists of 9,000 patterns constructed by introducing noise to the training images. Noise patterns are generated by randomly choosing some pixels and assigning them a random value. One thousand different patterns are generated from each training image, in which different numbers of noise pixels (1–100) are introduced. Three noise patterns are presented in Fig. 5a. For the test patterns without noise, 2 out of the 24 patterns are misclassified using the write-verify scheme; whereas 3 patterns are misclassified using the scheme without write-verify, as Fig. 5c shows. This is close to the 22/24 accuracy with the standard computing system. The real-time changes of the misclassification rate under the two schemes during training are given as well (Supplementary Note 5). Figure 5b shows the recognition rate on the 9,000 augmented noisy test patterns. It is shown that scheme with write-verify presents a much lower misclassification rate for the entire set of testing patterns. This trend indicates that more noise pixels lead to a lower recognition rate. The average recognition rate on the total 9,000 augmented noisy test patterns is $88.08\\%$ and $85.04\\%$ for the write-verify and without write-verify methods, respectively, slightly decreasing compared with the $91.48\\%$ recognition rate by standard method. Total latency and energy consumption comparisons during the training process are presented in Fig. 5c. These data are acquired from experimental measurements. As the input is encoded by the pulse number, which has the maximum value of 255, the contribution to latency and energy consumption of inference phase is quite large. During weight update phase, the total latency and energy is actually $422.4\\upmu s$ and $61.16\\mathrm{nJ}$ for the write-verify scheme from the beginning to the end, whereas the corresponding speed and energy using the scheme without write-verify is $34.8\\upmu\\mathrm{s}$ and $197.98\\mathrm{n}]$ , respectively. Considering that the scheme with write-verify needs more programming pulses at each epoch, the write-verify scheme requires relatively longer latency during weight update phase. However, it performs better when taking energy consumption into consideration, and this is mainly due to the lower number of iterations required. Besides, the total latency and energy during the entire training process can benefit a lot from the decrease of the number of iterations because the major latency and energy consumed by inference task could be suppressed. Therefore, although the scheme without write-verify simplifies the update operation, the scheme with write-verify has superior performance of recognition accuracy, total latency and energy consumption using the same pulse amplitude and width. \n\n![](images/dfa5ebb6ccb9e97701aac68718d3dba493755947335d54176b51c50378cdd5fb.jpg) \nFigure 3 | The performance of the optimized device and two examples for programming. (a) Typical $1-V$ curve of a single 1T1R cell for a quasi-DC sweep, the gate voltage is 1.8 and $8\\vee$ during SET and RESET process, respectively. Inset is a transmission electron microscope (TEM) image of the RRAM device. (b) An example of the typical continuous conductance tuning performance under an identical pulse train condition during SETprocess, along with the fitting curve. $V_{\\mathrm{w}1}=2.4\\:\\forall,$ $V_{\\mathrm{bl}}=2.0$ V (50 ns), $V_{\\mathsf{s l}}=0\\mathsf{V}.$ . (c) Tuning performance during RESEToperation, along with the fitting curve. $V_{\\mathrm{wl}}=8\\mathsf{V},$ $V_{\\sf b I}=0\\vee,$ $V_{\\mathsf{s l}}=2.3\\mathsf{V}$ (50 ns). (d) An example of the SET programming waveform applied on the first row to adjust the weight, following write-verify scheme. (e) Waveforms for programming without write-verify. $(\\pmb{\\uparrow})$ The precision measurement result during RESET process using verified pulse train with different amplitudes. y Axis represents the final conductance accuracy (the difference between the target conductance and the measured conductance over the target conductance) after programming from a same initial state $40\\upmu\\mathsf{S}$ . $\\mathbf{\\sigma}(\\mathbf{g})$ y Axis represents the number of pulses needed to reach the target conductance from the same initial state $40{\\upmu\\mathrm{S}}$ . These curves show the relationship of tuning speed with respect to different programming pulse amplitudes. \n\n![](images/fa9b0826966ae07a9c29346bccbc5cb7628b1a0e232de870ae072ecba1de17f9.jpg) \nFigure 4 | The training process of the experimental demonstration. (a) The activation function output value of the first class versus the iteration number using the write-verify scheme. The inset figure zooms in the several last steps. (b) The training process for programming without write-verify. (c) The initial and final conductance distribution comparison of the first row when updating with write-verify. Inset shows the final conductance map. (d) The conductance distribution of the first row and the conductance map for the case without write-verify. \n\n![](images/d469a26f336f79626df28d1e39e286d9b057b79d00ba02f689fe8dfd5ea1efad.jpg) \nFigure 5 | The test result with latency and energy comparison. (a) A standard example of the constructed test patterns with 100 noise pixels with respect to each training image in Fig. 2c. (b) The recognition rate curve of two programming strategies during the test. The $x$ axis represents the amount of noise. (c) The comparison between with (W/) and without (W/O) schemes in terms of latency and energy consumption during training process and testing recognition rate in the normalized format. \n\nAnalogue RRAM array enables lower energy consumption. The energy consumption of the same network executed on conventional computing platforms are estimated and compared with the hardware used in this experiment. The average energy consumption leveraging Intel Xeon Phi processor36 with a hypothetical off-chip storage is $1,000\\times$ larger than this work, given that the average energy consumption is around $30{\\mathrm{nJ}}$ (33 and $25{\\mathrm{nJ}}$ for scheme with write-verify and without writeverify, respectively) at every epoch for the same classification task. Energy consumed due to off-chip non-volatile storage access dominates in the case of off-chip non-volatile memory, as the write energy of a 2 KB page size is $38.04\\upmu\\mathrm{J}$ per page using NAND flash37. For this network, the weight matrix is roughly $2\\mathrm{KB}$ for 16-bit weights. If a hypothetical hardware with Intel Xeon Phi processor where digital RRAM is integrated on-chip is assumed, the energy consumption is roughly $703{\\mathrm n}]$ per epoch, which is $20\\times$ larger than reported in this paper using on-chip RRAM analogue weight storage. The bidirectional analogue RRAM array realizes remarkable energy consumption saving and reaches a comparative accuracy during this experimental demonstration. It is important to note that these energy values only include the energy consumption for synaptic operations (reading synapses and updating synapses) and not the computation within the neurons (see Supplementary Note 6 for details). \n\n# Discussion \n\nIn summary, a neuromorphic network is developed using a bidirectional analogue 1024-cell-1T1R RRAM array. The optimized RRAM metal oxide stack $(\\mathrm{TiN/TaO}_{x}/\\mathrm{HfAl}_{y}\\mathrm{O}_{x}/\\mathrm{TiN})$ exhibits gradual and continuous weight change. Based on this device technology, an integrated neuromorphic network hardware system is built and trained online for grey-scale face classification. Both with and without write-verify operation schemes are studied for the neuromorphic network and they achieve a relatively high recognition rate after converging, that is, 22/24 and 21/24, respectively. There is trade-off between these two schemes. The scheme with write-verify shows a much better approach providing $4.61\\times$ faster converging speed, $1.05\\times$ higher recognition accuracy and $4.41\\times$ lower energy consumption, whereas the scheme without write-verify simplifies the operation to a great degree. This integrated neuromorphic network hardware system has remarkable energy consumption benefit compared to other hardware platforms. The resistive switching memory cell can be scaled down to $10\\mathrm{nm}$ (ref. 33), which provides around $10^{11}$ synapses per $\\mathrm{cm}^{2}$ . With further monolithic integration with neuron circuits, more complex deep neural networks and human-brain-like cognitive computing could be realized on a small chip. Meanwhile, it has to be noticed that the related accuracy, speed and power are all important for the actual application . To achieve a comparable classification accuracy on larger network as the state of art and realize the superiority on power and speed simultaneously, there are many technical issues to be solved. Both experimental and simulation efforts should be paid on the device optimization, algorithm modification, operation strategy improvement and system architecture design39. \n\n# Methods \n\nRRAM stack and fabrication process. The metal-oxide-semiconductor fieldeffect-transistor circuits are fabricated in a standard CMOS foundry. The technology node is $1.2\\upmu\\mathrm{m}$ . The CMOS circuitry works as the WL decoder and cell selector. The RRAM devices are formed on the drain of the transistors by using the following processes (Supplementary Fig. 2). The $\\mathrm{HfO}_{2}/\\mathrm{Al}_{2}\\mathrm{O}_{3}$ multilayer structure is deposited on the TiN bottom electrode with atomic layer deposition method by repeating $\\mathrm{HfO}_{2}$ and $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ cycles at $200^{\\circ}\\mathrm{C}$ periodically. For each period, three cycles of $\\mathrm{HfO}_{2}$ and one cycles of $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ are deposited. The thickness of one atomic layer deposition cycle of both $\\mathrm{HfO}_{2}$ and $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ is around $1\\textup{\\AA}$ The final thickness of the $\\mathrm{HfAl}_{y}\\mathrm{O}_{x}$ layer is about $8\\mathrm{nm}$ . Then a 60 nm $\\mathrm{TaO}_{x}$ capping layer that acts as an in-built current compliance layer and oxygen reservoir is deposited by physical vapour deposition method. The top electrode TiN/Al are deposited by reactive sputtering and electron beam evaporation, respectively. Finally, the top Al pad is patterned by dry etching with $\\mathrm{Cl}_{2}/\\mathrm{BCl}_{3}$ plasma. \n\nWrite-verify programming method. Two programming schemes, one with writeverify while the other without, are proved at array level. The scheme with writeverify is described in Supplementary Fig. 9. Target conductance values are send to the Tester (Supplementary Fig. 3) in each learning iteration and multiple electrical pulses are applied to the 1T1R cell to increase (decrease) the conductance, until the conductance is larger (smaller) or equal to the target values. Finally, the cell conductance slightly deviates from the target in most of the cases. \n\nDevice performance during write-verify RESET process. Pulse amplitude and pulse width highly effect the cell performance according to Supplementary Figs 4 and 6. Meanwhile, we can conclude from Fig. $3\\mathrm{f},\\mathrm{g}$ of the main text that there is a tradeoff between tuning speed and tuning accuracy. Further, Supplementary Fig. 11 implies that the conductance modulation range must be considered when determining the pulse condition. \n\nDuring the experiment of Fig. $^{3\\mathrm{f},\\mathrm{g}}$ and Supplementary Fig. 11, a sequence of identical RESET pulses with write-verify are applied to examine how varied pulse amplitudes affect weight adjustment. The raw data are statistically averaged over 32 random chosen cells under 3 repeated procedures to get rid of device variances. The procedure starts with precisely initializing cell conductance at $40\\upmu\\mathrm{S}$ $(25\\mathrm{k}\\Omega)$ . Then a specified pulse train is applied to tune cell conductance to a certain target value. The refined conductance value and total pulse number when write-verify passes are recorded. The programming pulse width is $50\\mathrm{ns}$ , and the gate voltage $V_{\\mathrm{wl}}$ is $_{8\\mathrm{V}}$ . The BL is grounded and the pulse number limitation is set to 500. Several trials are conducted during each test, tuning the 32 cells’ conductance to $33.3\\upmu\\mathrm{S}$ $(30\\mathrm{k}\\Omega)$ , $28.6\\upmu\\mathrm{S}$ $(35\\mathrm{k}\\Omega)$ , $25\\upmu\\mathrm{S}$ $(40\\mathrm{k}\\Omega)$ , $22.2\\upmu\\mathrm{S}$ $(45\\mathrm{k}\\Omega)$ , $20\\upmu\\mathrm{S}$ $(50\\mathrm{k}\\Omega)$ , $18.2\\upmu\\mathrm{S}$ $(55\\mathrm{k}\\Omega)$ , $13.3\\upmu\\mathrm{S}$ $(75\\mathrm{k}\\Omega)$ and $10\\upmu\\mathrm{S}$ $\\mathbf{\\bar{100k}}\\pmb{\\Omega})$ . \n\nDevice performance during write-verify SET process. Similar measurement is conducted during write-verify SET process to see how pulse amplitude affect conductance modulation precision, modulation pass rate and modulation speed. \n\nDuring the test, a sequence of identical SET pulses with write-verify are applied to examine how pulse amplitudes affect weight adjustment. The raw data are statistically averaged over 32 random chosen cells under 3 repeated procedures to get rid of device variances. The procedure starts with precisely initializing cell conductance at $4\\upmu\\mathrm{S}$ $(250\\mathrm{k}\\Omega)$ . Then a specified pulse train is applied on BL to tune cell conductance to a certain target value. The refined conductance value and total pulse number when write-verify pass are recorded. The programming pulse width is $50\\mathrm{ns}$ , and the gate voltage $V_{\\mathrm{wl}}$ is $2.8\\mathrm{V}$ . The SL is grounded and the pulse number limitation is set to 300. Several trials are conducted during each test, tuning the 32 cells’ conductance to a same target conductance target set as in the RESET test, that is, $33.3\\upmu\\mathrm{S}$ $(30\\mathrm{k}\\Omega)$ , $28.6\\upmu\\mathrm{S}$ $(35\\mathrm{k}\\Omega)$ , $25\\upmu\\mathrm{S}$ $(40\\mathrm{k}\\Omega)$ , $22.2\\upmu\\mathrm{S}$ $(45\\mathrm{k}\\Omega)$ , $20\\upmu\\mathrm{S}$ $(50\\mathrm{k}\\Omega)$ , $18.2\\upmu\\mathrm{S}$ $(55\\mathrm{k}\\Omega)$ , $13.3\\upmu\\mathrm{S}$ $(75\\mathrm{k}\\Omega)$ and $10\\upmu\\mathrm{S}$ $\\langle100\\mathrm{k}\\Omega\\rangle$ . The results are shown in Supplementary Fig. 12. We can conclude that there is a tradeoff between tuning speed, conductance modulation range and tuning accuracy when determining the SET pulse conditions. \n\nThe perceptron network. A one-layer perceptron is adopted for this hardware system demonstration, and the schematic diagram is shown in Supplementary Fig. 1. The perceptron model is used to classify each pattern to three categories. This schematic illustrates how to map the network to the proposed 1T1R structure, that is, the input of preneuron layer, adaptable synaptic weight and the weighted sum output of postneuron layer are in accordance with the pulse input from BL, 1T1R cell conductance and current output through SL separately. The nonlinear function ‘tanh’ is regarded as the activation function here. \n\nUnseen test images from the Yale Face Database. We have obtained full permissions to use the images from Yale Face Database and are compliant with Yale’s policy of reuse/use of these images (http://vision.ucsd.edu/content/yale-face \n\ndatabase). The total 9 training images are presented in Fig. 2c, the other 24 cropped and down-sampled face images from the Yale Face Database are used to evaluate the perceptron’s generation ability, as shown in Supplementary Fig. 19. \n\nTest platform and the hyper-parameter values. As is mentioned in the main text, the weights are implemented using the 1,024-cell-1T1R array, and the nonlinear activation function tanh with respected to the SL current is implemented by the software. The control instructions are sent to the external equipment to generate practical programming pulses side by side. All these in union work automatically. The diagram of this platform is shown in Supplementary Fig. 3. \n\nA fitted behaviour RRAM model is extracted from experiment data and used for the simulation to decide the hyper-parameters in Fig. 2a. Eventually $\\beta$ is defined as $1.5\\mathrm{A}^{-1}$ , and $\\eta$ equals to 1. Apart from these, the target value of the activation function $f^{\\mathrm{t}}$ is 0.3 for the right class and 0 for other wrong classes during training process. \n\nData availability. The data that support the findings of this study are available from the authors upon reasonable request; see Author contributions section for specific data sets. \n\n# References \n\n1. Najafabadi, M. M. et al. Deep learning applications and challenges in big data analytics. J. Big Data 2, 1–21 (2015). \n2. Le, Q. V. in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference 8595–8598 (IEEE, 2013). \n3. Russakovsky, O. et al. Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115, 211–252 (2015). \n4. Hadsell, R. et al. Learning long-range vision for autonomous off-road driving. J. Field Robot. 26, 120–144 (2009). \n5. Krizhevsky, A., Sutskever, I. & Hinton, G. E. in Advances in Neural Information Processing Systems 1097–1105 (Curran Associates, Inc., 2012). \n6. Merolla, P. A. et al. A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 345, 668–673 (2014). \n7. Benjamin, B. V. et al. Neurogrid: a mixed-analog-digital multichip system for large-scale neural simulations. Proc. IEEE 102, 699–716 (2014). \n8. Vogelstein, R. J., Mallik, U., Vogelstein, J. T. & Cauwenberghs, G. Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses. IEEE Trans. Neural Netw. 18, 253–265 (2007). \n9. Khan, M. M. et al. in Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on, 2849–2856 (IEEE, 2008). \n10. Schemmel, J., Fieres, J. & Meier, K. in Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on, 431–438 (IEEE, 2008). \n11. Eryilmaz, S. B., Kuzum, D., Yu, S. & Wong, H. S. P. in 2015 IEEE International Electron Devices Meeting (IEDM), 4.1.1–4.1.4 (IEEE, 2015). \n12. Han, S. et al. in Proceedings of the 43rd International Symposium on Computer Architecture. 243–254 (IEEE Press, 2016). \n13. Prezioso, M. et al. Training and operation of an integrated neuromorphic network based on metal-oxide memristors. Nature 521, 61–64 (2015). \n14. Park, S. et al. Electronic system with memristive synapses for pattern recognition. Sci. Rep. 5, 10123 (2015). \n15. Burr, G. W. et al. Experimental demonstration and tolerancing of a large-scale neural network (165,000 Synapses) using phase-change memory as the synaptic weight element. IEEE Trans. Electron. Devices 62, 3498–3507 (2015). \n16. Wong, H.-S. P. & Salahuddin, S. Memory leads the way to better computing. Nat. Nanotechnol. 10, 191–194 (2015). \n17. Wong, H.-S. P. et al. Metal–oxide RRAM. Proc. IEEE 100, 1951–1970 (2012). \n18. Rosenblatt, F. The perceptron: a probabilistic model for information storage and organization in the brain. Psychol. Rev. 65, 386 (1958). \n19. Belhumeur, P. N., Hespanha, J. P. & Kriegman, D. J. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19, 711–720 (1997). \n20. LeCun, Y., Bottou, L., Bengio, Y. & Haffner, P. Gradient-based learning applied to document recognition. Proc. IEEE 86, 2278–2324 (1998). \n21. Hinton, G. E. & Salakhutdinov, R. R. Reducing the dimensionality of data with neural networks. Science 313, 504–507 (2006). \n22. Mnih, V. et al. Human-level control through deep reinforcement learning. Nature 518, 529–533 (2015). \n23. LeCun, Y. A., Bottou, L., Orr, G. B. & Mu¨ller, K.-R. in Neural Networks: Tricks of the Trade 9–48 (Springer, 2012). \n24. Hertz, J., Krogh, A. & Palmer, R. G. in Introduction to the Theory of Neural Computation Vol. 1 (Basic Books, 1991). \n25. Schiffmann, W., Joost, M. & Werner, R. Optimization of the backpropagation algorithm for training multilayer perceptrons. Univ. Koblenz. Inst. Phys. Rheinau 3–4 (1994). \n26. Kuzum, D., Yu, S. & Wong, H. P. Synaptic electronics: materials, devices and applications. Nanotechnology 24, 382001 (2013). \n27. Ohno, T. et al. Short-term plasticity and long-term potentiation mimicked in single inorganic synapses. Nat. Mater. 10, 591–595 (2011). \n28. Alibart, F., Zamanidoost, E. & Strukov, D. B. Pattern classification by memristive crossbar circuits using ex situ and in situ training. Nat. Commun. 4, 2072 (2013). \n29. Yu, S. et al. A low energy oxide-based electronic synaptic device for neuromorphic visual systems with tolerance to device variation. Adv. Mater. 25, 1774–1779 (2013). \n30. Kim, K.-H. et al. A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications. Nano Lett. 12, 389–395 (2011). \n31. Indiveri, G., Linares-Barranco, B., Legenstein, R., Deligeorgis, G. & Prodromakis, T. Integration of nanoscale memristor synapses in neuromorphic computing architectures. Nanotechnology 24, 384010 (2013). \n32. Fackenthal, R. et al. in Solid-State Circuits Conference Digest of Technical Papers (ISSCC), 2014 IEEE International, 338–339 (IEEE, 2014). \n33. Govoreanu, B. et al. in Electron Devices Meeting (IEDM), 2011 IEEE International, 31.36. 31–31.36. 34 (IEEE, 2011). \n34. Sekar, D. et al. in 2014 IEEE International Electron Devices Meeting, 28.23. 21–28.23. 24 (IEEE, 2014). \n35. Gao, L., Chen, P.-Y. & Yu, S. Programming protocol optimization for analog weight tuning in resistive memories. IEEE Electron. Device Lett. 36, 1157–1159 (2015). \n36. Shao, Y. S. & Brooks, D. in Proceedings of the 2013 International Symposium on Low Power Electronics and Design, 389–394 (IEEE Press, 2013). \n37. Park, S., Kim, Y., Urgaonkar, B., Lee, J. & Seo, E. A comprehensive study of energy efficiency and performance of flash-based SSD. J. Syst. Architect. 57, 354–365 (2011). \n38. Burr, G. et al. in 2015 IEEE International Electron Devices Meeting (IEDM), 4.4. 1–4.4. 4 (IEEE, 2015). \n39. Gokmen, T. & Vlasov, Y. Acceleration of deep neural network training with resistive cross-point devices: design considerations. Front. Neurosci 10, 333 (2016). \n\n# Acknowledgements \n\nWe thank Professor Shimeng Yu of Arizona State University for the valuable discussions. We acknowledge the use of the Yale Face Database. This work is supported in part by the Beijing Advanced Innovation Center for Future Chip (ICFC), National Key Research and Development Program of China (2016YFA0201803), National Hi-tech (R&D) Project of China (2014AA032901), and NSFC (61674089). S.B.E. and H.-S.P.W. are supported in part by the National Science Foundation Expeditions in Computing (Award no. 1317470) and member companies of the Stanford SystemX Alliance. \n\n# Author contributions \n\nP.Y., H.W., B.G. and S.B.E. designed the research and conceptualized the technical framework. P.Y., X.H. and W.Z. performed the experiments. P.Y., Q.Z. and S.B.E. contributed to the simulation. P.Y., B.G. and H.-S.P.W. contributed to the paper writing. All authors discussed and reviewed the manuscript. H.W. and H.Q. were in charge and advised on all parts of the project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at http://www.nature.com/ naturecommunications \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nHow to cite this article: Yao, P. et al. Face classification using electronic synapses. \nNat. Commun. 8, 15199 doi: 10.1038/ncomms15199 (2017). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis work is licensed under a Creative Commons Attribution 4.0 International License. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ " + }, + { + "id": "10.1103_PhysRevLett.120.145301", + "DOI": "10.1103/PhysRevLett.120.145301", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevLett.120.145301", + "Relative Dir Path": "mds/10.1103_PhysRevLett.120.145301", + "Article Title": "Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties", + "Authors": "Xie, T; Grossman, JC", + "Source Title": "PHYSICAL REVIEW LETTERS", + "Abstract": "The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 104 data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.", + "Times Cited, WoS Core": 1518, + "Times Cited, All Databases": 1718, + "Publication Year": 2018, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000429451000012", + "Markdown": "# Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties \n\nTian Xie and Jeffrey C. Grossman Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA \n\n![](images/223cc87ba20d1fa320f9de6875fa13da8d8be5a0dd0cb9df369c331c81bef3df.jpg) \n\n(Received 18 October 2017; revised manuscript received 15 December 2017; published 6 April 2018) \n\nThe use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with $10^{4}$ data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design. \n\nDOI: 10.1103/PhysRevLett.120.145301 \n\nMachine learning (ML) methods are becoming increasingly popular in accelerating the design of new materials by predicting material properties with accuracy close to ab initio calculations, but with computational speeds orders of magnitude faster [1–3]. The arbitrary size of crystal systems poses a challenge as they need to be represented as a fixed length vector in order to be compatible with most ML algorithms. This problem is usually resolved by manually constructing fixed length feature vectors using simple material properties [1,3–6] or designing symmetry-invariant transformations of atom coordinates [7–9]. However, the former requires a case-by-case design for predicting different properties, and the latter makes it hard to interpret the models as a result of the complex transformations. \n\nIn this Letter, we present a generalized crystal graph convolutional neural networks (CGCNN) framework for representing periodic crystal systems that provides both material property prediction with density functional theory (DFT) accuracy and atomic level chemical insights. Recent advances in “deep learning” have enabled learning from a very raw representation of data, e.g., pixels of an image, making it possible to build general models that outperform traditionally expert designed representations [10]. By looking into the simplest form of crystal representation, i.e., the connection of atoms in the crystal, we directly build convolutional neural networks on top of crystal graphs generated from crystal structures. The CGCNN achieves similar accuracy with respect to DFT calculations as DFT compared with experimental data for eight different properties after being trained with data from the Materials Project [11], indicating the generality of this method. We also demonstrate the interpretability of the CGCNN by extracting the energy of each site in the perovskite structure from the total energy, an example of learning the contribution of local chemical environments to the global property. The empirical rules generalized from the results are consistent with the common knowledge for discovering more stable perovskites and can significantly reduce the search space for high throughput screening. \n\nThe main idea in our approach is to represent the crystal structure by a crystal graph that encodes both atomic information and bonding interactions between atoms, and then build a convolutional neural network on top of the graph to automatically extract representations that are optimum for predicting target properties by training with DFT calculated data. As illustrated in Fig. 1(a), a crystal graph $\\mathcal{G}$ is an undirected multigraph which is defined by nodes representing atoms and edges representing connections between atoms in a crystal (the method for determining atom connectivity is explained in the Supplemental Material [12]). The crystal graph is unlike normal graphs since it allows multiple edges between the same pair of end nodes, a characteristic for crystal graphs due to their periodicity, in contrast to molecular graphs. Each node $i$ is represented by a feature vector $\\boldsymbol{\\nu}_{i:}$ , encoding the property of the atom corresponding to node $i$ . Similarly, each edge $(i,j)_{k}$ is represented by a feature vector $\\pmb{u}_{(i,j)_{k}}$ corresponding to the kth bond connecting atom $i$ and atom $j$ . \n\nThe convolutional neural networks built on top of the crystal graph consist of two major components: convolutional layers and pooling layers. Similar architectures have been used for computer vision [22], natural language processing [23], molecular fingerprinting [24] and general graph-structured data [25,26], but not for crystal property prediction to the best of our knowledge. The convolutional layers iteratively update the atom feature vector $\\mathbf{\\nabla}\\nu_{i}$ by “convolution” with surrounding atoms and bonds with a nonlinear graph convolution function, \n\n![](images/6766dc8c1eef962e14d0687e24a428cc2ee1b79f27eaef388d4fd042d80e1580.jpg) \nFIG. 1. Illustration of the crystal graph convolutional neural networks. (a) Construction of the crystal graph. Crystals are converted to graphs with nodes representing atoms in the unit cell and edges representing atom connections. Nodes and edges are characterized by vectors corresponding to the atoms and bonds in the crystal, respectively. (b) Structure of the convolutional neural network on top of the crystal graph. $R$ convolutional layers and $L_{1}$ hidden layers are built on top of each node, resulting in a new graph with each node representing the local environment of each atom. After pooling, a vector representing the entire crystal is connected to $L_{2}$ hidden layers, followed by the output layer to provide the prediction. \n\n$$\n\\pmb{\\nu}_{i}^{(t+1)}=\\mathbf{C}\\mathrm{onv}\\left(\\pmb{\\nu}_{i}^{(t)},\\pmb{\\nu}_{j}^{(t)},\\pmb{u}_{(i,j)_{k}}\\right),\\quad(i,j)_{k}\\in\\mathcal{G}.\n$$ \n\nAfter $R$ convolutions, the network automatically learns the feature vector viðRÞ for each atom by iteratively including its surrounding environment. The pooling layer is then used for producing an overall feature vector $\\pmb{\\nu}_{c}$ for the crystal, which can be represented by a pooling function, \n\n$$\n\\pmb{\\nu}_{c}=\\mathrm{Pool}(\\pmb{\\nu}_{0}^{(0)},\\pmb{\\nu}_{1}^{(0)},...,\\pmb{\\nu}_{N}^{(0)},...,\\pmb{\\nu}_{N}^{(R)})\n$$ \n\nthat satisfies permutational invariance with respect to atom indexing and size invariance with respect to unit cell choice. In this work, a normalized summation is used as the pooling function for simplicity, but other functions can also be used. In addition to the convolutional and pooling layers, two fully connected hidden layers with the depths of $L_{1}$ and $L_{2}$ are added to capture the complex mapping between crystal structure and property. Finally, an output layer is used to connect the $L_{2}$ hidden layer to predict the target property $\\hat{y}.$ . \n\nThe training is performed by minimizing the difference between the predicted property $\\hat{y}$ and the DFT calculated property $y_{:}$ defined by a cost function $J(y,\\hat{y})$ . The whole CGCNN can be considered as a function $f$ parametrized by weights W that maps a crystal $\\mathcal{C}$ to the target property $\\hat{y}$ . Using backpropagation and stochastic gradient descent (SGD), we can solve the following optimization problem by iteratively updating the weights with DFT calculated data: \n\n$$\n\\operatorname*{min}_{W}J(y,f({\\mathcal{C}};W))\n$$ \n\nthe learned weights can then be used to predict material properties and provide chemical insights for future materials design. \n\nIn the Supplemental Material (SM) [12], we use a simple example to illustrate how a CGCNN composed of one linear convolution layer and one pooling layer can differentiate two crystal structures. With multiple convolution layers, pooling layers, and hidden layers, the CGCNN can extract any structure differences based on the atom connections and discover the underlaying relations between structure and property. \n\nTo demonstrate the generality of the CGCNN, we train the model using calculated properties from the Materials Project [11]. We focus on two types of generality in this work: (1) the structure types and chemical compositions for which our model can be applied and (2) the number of properties that our model can accurately predict. \n\nThe database we used includes a diverse set of inorganic crystals ranging from simple metals to complex minerals. After removing ill-converged crystals, the full database has 46 744 materials covering 87 elements, 7 lattice systems, and 216 space groups. As shown in Fig. 2(a), the materials consist of as many as seven different elements, with $90\\%$ of them binary, ternary, and quaternary compounds. The number of atoms in the primitive cell ranges from 1 to 200, and $90\\%$ of crystals have less than 60 atoms (Fig. S2). Considering most of the crystals originate from the Inorganic Crystal Structure Database [27], this database is a good representation of known stoichiometric inorganic crystals. \n\nThe CGCNN is a flexible framework that allows variance in the crystal graph representation, neural network architecture, and training process, resulting in different $f$ in Eq. (3) and prediction performance. To choose the best model, we apply a train-validation scheme to optimize the prediction of formation energies of crystals. Each model is trained with $60\\%$ of the data and then validated with $20\\%$ of the data, and the best-performing model in the validation set is selected. In our study, we find that the neural network architecture, especially the form of convolution function in Eq. (1), has the largest impact on prediction performance. We start with a simple convolution function, \n\n$$\n\\boldsymbol{\\nu}_{i}^{(t+1)}=g\\Biggl[\\biggl(\\sum_{j,k}\\boldsymbol{\\nu}_{j}^{(t)}\\oplus\\boldsymbol{u}_{(i,j)_{k}}\\biggr)\\boldsymbol{W}_{c}^{(t)}+\\boldsymbol{\\nu}_{i}^{(t)}\\boldsymbol{W}_{s}^{(t)}+\\boldsymbol{b}^{(t)}\\Biggr],\n$$ \n\n![](images/df8964f1403efe102e368038833d91a07e93e3193a380b9c273975032572f590.jpg) \nFIG. 2. Performance of CGCNN on the Materials Project database [11]. (a) Histogram representing the distribution of the number of elements in each crystal. (b) Mean absolute error as a function of training crystals for predicting formation energy per atom using different convolution functions. The shaded area denotes the MAEs of DFT calculations compared with experiments [28]. (c) 2D histogram representing the predicted formation per atom against DFT calculated value. (d) Receiver operating characteristic curve visualizing the result of metalsemiconductor classification. It plots the proportion of correctly identified metals (true positive rate) against the proportion of wrongly identified semiconductors (false positive rate) under different thresholds. \n\nwhere $\\oplus$ denotes concatenation of atom and bond feature vectors, $\\boldsymbol{W}_{c}^{(t)}$ , $\\boldsymbol{W}_{s}^{(t)}$ , and $\\mathbf{\\boldsymbol{b}}^{(t)}$ are the convolution weight matrix, self-weight matrix, and bias of the tth layer, respectively, and $g$ is the activation function for introducing nonlinear coupling between layers. By optimizing hyperparameters in Table S1, the lowest mean absolute error (MAE) for the validation set is $0.108\\ \\mathrm{eV},$ =atom. One limitation of Eq. (4) is that it uses a shared convolution weight matrix $\\mathbf{\\Delta}W_{c}^{(t)}$ for all neighbors of $i$ , which neglects the differences of interaction strength between neighbors. To overcome this problem, we design a new convolution function that first concatenates neighbor vectors $\\boldsymbol{z}_{(i,j)_{k}}^{(t)}=\\boldsymbol{\\nu}_{i}^{(t)}\\oplus\\boldsymbol{\\nu}_{j}^{(t)}\\oplus\\boldsymbol{u}_{(i,j)_{k}}$ , then perform convolution by \n\n$$\n\\begin{array}{c}{{\\pmb{\\nu}_{i}^{(t+1)}=\\pmb{\\nu}_{i}^{(t)}+\\displaystyle\\sum_{j,k}\\sigma\\Bigl(z_{(i,j)_{k}}^{(t)}{\\pmb{W}}_{f}^{(t)}+{\\pmb{b}}_{f}^{(t)}\\Bigr)}}\\\\ {{\\odot g\\Bigl(z_{(i,j)_{k}}^{(t)}{\\pmb{W}}_{s}^{(t)}+{\\pmb{b}}_{s}^{(t)}\\Bigr),}}\\end{array}\n$$ \n\nwhere $\\odot$ denotes element-wise multiplication and $\\sigma$ denotes a sigmoid function. In Eq. (5), the $\\sigma(\\cdot)$ functions as a learned weight matrix to differentiate interactions between neighbors and adding $\\mathbf{\\boldsymbol{\\nu}}_{i}^{(t)}$ makes learning deeper networks easier [29]. We achieve MAE on the validation set of $0.039\\ \\mathrm{eV}.$ =atom using the modified convolution function, a significant improvement compared to Eq. (4). In Fig. S3, we compare the effects of several other hyperparameters on the MAE which are much smaller than the effect of the convolution function. \n\nFigures 2(b) and 2(c) show the performance of the two models on 9350 test crystals for predicting the formation energy per atom. We find a systematic decrease of the MAE of the predicted values compared with DFT calculated values for both convolution functions as the number of training data is increased. The best MAEs we achieved with Eqs. (4) and (5) are 0.136 and $0.039\\ \\mathrm{eV},$ =atom, respectively, and $90\\%$ of the crystals are predicted within 0.3 and $0.08\\ \\mathrm{eV}.$ =atom errors. In comparison, Kirklin et al. reports that the MAE of the DFT calculation with respect to experimental measurements in the Open Quantum Materials Database is $0.081{-}0.136~\\mathrm{eV/atom}$ depending on whether the energies of the elemental reference states are fitted, although they also find a large MAE of $0.082\\ \\mathrm{eV}_{I}$ atom between different sources of experimental data. Given the comparison, our CGCNN approach provides a reliable estimation of DFT calculations and can potentially be applied to predict properties calculated by more accurate methods like GW [30] and quantum Monte Carlo calculations [31]. \n\nAfter establishing the generality of the CGCNN with respect to the diversity of crystals, we next explore its prediction performance for different material properties. We apply the same framework to predict the absolute energy, band gap, Fermi energy, bulk moduli, shear moduli, and Poisson ratio of crystals using DFT calculated data from the Materials Project [11]. The prediction performance of Eq. (5) is improved compared to Eq. (4) for all six properties (Table S4). We summarize the performance in Table I and the corresponding 2D histograms in Fig. S4. As we can see, the MAEs of our model are close to or higher than DFT accuracy relative to experiments for most properties when ${\\sim}10^{4}$ training data are used. For elastic properties, the errors are higher since less data are available, and the accuracy of DFT relative to experiments can be expected if ${\\sim}10^{4}$ training data are available (Fig. S5). \n\nTABLE I. Summary of the prediction performance of seven different properties on test sets. \n\n\n
Property# of train dataUnit MAEmodelMAEDFT
Formation28046eV/atom 0.0390.081-0.136 [28]
energy Absolute28046eV/atom0.072
energy Band gap16458eV0.388 0.6 [32]
Fermi energy28046eV0.363
Bulk moduli2041log(GPa)0.054 0.050 [13]
Shear moduli2041log(GPa)0.087 0.069 [13]
Poisson ratio20410.030
\n\nRecently, Jong et al. [33] developed a statistical learning (SL) framework using multivariate local regression on crystal descriptors to predict elastic properties using the same data from the Materials Project. By using the same number of training data, our model achieves root mean squared error (RMSE) on test sets of $0.105\\log(\\mathrm{GPa})$ and $0.127\\ \\log(\\mathrm{GPa})$ for the bulk and shear moduli, which is similar to the RMSE of SL on the entire data set of 0.0750 $\\mathrm{log(GPa)}$ and $0.1378~\\mathrm{log(GPa)}$ . Comparing the two methods, the CGCNN predicts properties by extracting features only from the crystal structure, while SL depends on crystal descriptors like cohesive energy and volume per atom. Recently, 1585 new crystals with elastic properties have been uploaded to the Materials Project database. Our model in Table I achieves MAE of $0.077\\ \\log(\\mathrm{GPa})$ for bulk moduli and $0.114\\ \\log(\\mathrm{GPa})$ for shear moduli on these crystals, showing good generalization to materials from potentially different crystal groups. \n\nIn addition to predicting continuous properties, the CGCNN can also predict discrete properties by changing the output layer. By using a softmax activation function for the output layer and a cross entropy cost function, we can predict the classifications of metal and semiconductor with the same framework. In Fig. 2(d), we show the receiver operating characteristic curve of the prediction on 9350 test crystals. Excellent prediction performance is achieved with the area under the curve at 0.95. By choosing a threshold of 0.5, we get metal prediction accuracy at 0.80, semiconductor prediction accuracy at 0.95, and overall prediction accuracy at 0.90. \n\nModel interpretability is a desired property for any ML algorithm applied in materials science, because it can provide additional information for material design which may be more valuable than simply screening a large number of materials. However, nonlinear functions are needed to learn the complex structure-property relations, resulting in ML models that are difficult to interpret. The CGCNN resolves this dilemma by separating the convolution and pooling layers. After the $R$ convolutional and $L_{1}$ hidden layers, we map the last atom feature vector viðRÞ to a scalar ˜vi and perform a linear pooling to predict the target property directly without the $L_{2}$ hidden layers (details discussed in SM [12]). Therefore, we can learn the contribution of different local chemical environments, represented by $\\tilde{v}_{i}$ for each atom, to the target property while maintaining a model with high capacity to ensure the prediction performance. \n\nWe demonstrate how this local chemical environment related information can be used to provide chemical insights and guide the material design by a specific example: learning the energy of each site in perovskites from the total energy above hull data. Perovskite is a crystal structure type with the form of $A B X_{3}$ , where the site $A$ atom sits at a corner position, the site $B$ atom sits at a body centered position, and site $X$ atoms sit at face centered positions [Fig. 3(a)]. The database [34] we use includes the energy above hull of 18 928 perovskite crystals, in which $A$ and $B$ sites can be any nonradioactive metals and $X$ sites can be one or several elements from O, N, S, and F. We use the CGCNN with a linear pooling to predict the total energy above hull of perovskites in the database, using Eq. (4) as the convolution function. The resulting MAE on 3787 test perovskites is $0.130\\ \\mathrm{eV},$ =atom as shown in Fig. 3(b), which is slightly higher than using a complete pooling layer and $L_{2}$ hidden layers $\\operatorname{\\langle0.099\\eV/}$ atom as shown in Fig. S6) due to the additional constraints introduced by the simplified pooling layer. However, this CGCNN allows us to learn the energy of each site in the crystal while training with the total energy above hull, providing additional insights for material design. Figures 3(c) and 3(d) visualize the mean of the predicted site energies when each element occupies the $A$ and $B$ site, respectively. The most stable elements that occupy the $A$ site are those with large radii due to the space needed for 12 coordinations. In contrast, elements with small radii like Be, B, and Si are the most unstable for occupying the $A$ site. For the $B$ site, elements in groups 4, 5, and 6 are the most stable throughout the periodic table. This can be explained by crystal field theory, since the configuration of $d$ electrons of these elements favors the octahedral coordination in the $B$ site. Interestingly, the visualization shows that large atoms from groups 13–15 are stable in the $A$ site, in addition to the well-known region of groups 1–3 elements. Inspired by this result, we applied a combinatorial search for stable perovskites using elements from groups 13–15 as the $A$ site and groups 4–6 as the $B$ site. Because of the theoretical inaccuracies of DFT calculations and the possibility of metastable phases that can be stabilized by temperature, defects, and substrates, many synthesizable inorganic crystals have positive calculated energies above hull at $0\\mathrm{~K~}$ . Some metastable nitrides can even have energies up to $0.2{\\mathrm{~eV}},$ =atom above hull as a result of the strong bonding interactions [35]. In this work, since some of the perovskites are also nitrides, we choose to set the cutoff energy for potential synthesizability at $0.2\\ \\mathrm{eV}$ =atom. We discovered 33 perovskites that fall within this threshold out of 378 in the entire data set, among which 8 are within the cutoff out of 58 in the test set (Table S5). Many of these compounds like ${\\mathrm{PbTiO}}_{3}$ [36], $\\mathrm{Pb}{\\mathrm{Zr}}\\mathrm{O}_{3}$ [36], $\\mathrm{SnTaO}_{3}$ [37], and $\\mathrm{PbMoO}_{3}$ [38] have been experimentally synthesized. Note that $\\mathrm{PbMoO}_{3}$ has calculated energy of $0.18\\ \\mathrm{eV}_{/}$ =atom above hull, indicating that our choice of cutoff energy is reasonable. In general, chemical insights gained from the CGCNN can significantly reduce the search space for high throughput screening. In comparison, there are only 228 potentially synthesizable perovskites out of 18 928 in our database: the chemical insight increased the search efficiency by a factor of 7. \n\n![](images/6a2af6ea80c6176da76eb63a78fd7ada69d9e4c2b96e63feaaf9dfcbadaeda12.jpg) \nFIG. 3. Extraction of site energy of perovskites from total formation energy. (a) Structure of perovskites. (b) 2D histogram representing the predicted total energy above hull against DFT calculated value. (c),(d) Periodic table with the color of each element representing the mean of the site energy when the element occupies $A$ site (c) or $B$ site (d). \n\nIn summary, the crystal graph convolutional neural networks present a flexible machine learning framework for material property prediction and design knowledge extraction. The framework provides a reliable estimation of DFT calculations using around $10^{4}$ training data for eight properties of inorganic crystals with diverse structure types and compositions. As an example of knowledge extraction, we apply this approach to the design of new perovskite materials and show that information extracted from the model is consistent with common chemical insights and significantly reduces the search space for high throughput screening. \n\nThe code for the CGCNN is available from Ref. [39]. \n\nThis work was supported by Toyota Research Institute. Computational support was provided through the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, and the Extreme Science and Engineering Discovery Environment, supported by National Science Foundation Grant No. ACI-1053575. \n\n[1] A. Seko, A. Togo, H. Hayashi, K. Tsuda, L. Chaput, and I. Tanaka, Phys. Rev. Lett. 115, 205901 (2015). \n[2] F. A. Faber, A. Lindmaa, O. A. von Lilienfeld, and R. Armiento, Phys. Rev. Lett. 117, 135502 (2016). \n[3] D. Xue, P. V. Balachandran, J. Hogden, J. Theiler, D. Xue, and T. Lookman, Nat. Commun. 7, 11241 (2016). \n[4] O. Isayev, C. Oses, C. Toher, E. Gossett, S. Curtarolo, and A. Tropsha, Nat. Commun. 8, 15679 (2017). [5] L. M. Ghiringhelli, J. Vybiral, S. V. Levchenko, C. Draxl, and M. Scheffler, Phys. Rev. Lett. 114, 105503 (2015). [6] O. Isayev, D. Fourches, E. N. Muratov, C. Oses, K. Rasch, A. Tropsha, and S. Curtarolo, Chem. Mater. 27, 735 (2015). [7] K. T. Schütt, H. Glawe, F. Brockherde, A. Sanna, K. R. Müller, and E. K. U. Gross, Phys. Rev. B 89, 205118 (2014). [8] F. Faber, A. Lindmaa, O. A. von Lilienfeld, and R. Armiento, Int. J. Quantum Chem. 115, 1094 (2015). [9] A. Seko, H. Hayashi, K. Nakayama, A. Takahashi, and I. Tanaka, Phys. Rev. B 95, 144110 (2017). \n[10] Y. LeCun, Y. Bengio, and G. Hinton, Nature (London) 521, 436 (2015). \n[11] A. Jain, S. P. Ong, G. Hautier, W. Chen, W. D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder et al., APL Mater. 1, 011002 (2013). \n[12] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevLett.120.145301 for further details, which includes Refs. [4,13–21]. \n[13] M. De Jong, W. Chen, T. Angsten, A. Jain, R. Notestine, A. Gamst, M. Sluiter, C. K. Ande, S. Van Der Zwaag, J. J. Plata et al., Sci. Data 2, 150009 (2015). \n[14] R. Sanderson, Science 114, 670 (1951). \n[15] R. Sanderson, J. Am. Chem. Soc. 74, 4792 (1952). \n[16] B. Cordero, V. Gómez, A. E. Platero-Prats, M. Rev´es, J. Echeverría, E. Cremades, F. Barragán, and S. Alvarez, Dalton Trans. 21, 2832 (2008). \n[17] A. Kramida, Y. Ralchenko, J. Reader et al., Atomic Spectra Database (National Institute of Standards and Technology, Gaithersburg, MD, 2013). \n[18] W. M. Haynes, CRC Handbook of Chemistry and Physics (CRC Press, Boca Raton, FL, 2014). \n[19] D. Kingma and J. Ba, arXiv:1412.6980. \n[20] N. Srivastava, G. E. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, J. Mach. Learn. Res. 15, 1929 (2014). \n[21] V. A. Blatov, Crystallography Reviews 10, 249 (2004). \n[22] A. Krizhevsky, I. Sutskever, and G. E. Hinton, in Advances in Neural Information Processing Systems (MIT Press, Cambridge, MA, 2012), pp. 1097–1105. \n[23] R. Collobert and J. Weston, in Proceedings of the 25th International Conference on Machine Learning (ACM, New York, 2008), pp. 160–167. \n[24] D. K. Duvenaud, D. Maclaurin, J. Iparraguirre, R. Bombarell, T. Hirzel, A. Aspuru-Guzik, and R. P. Adams, in Advances in Neural Information Processing Systems (MIT Press, Cambridge, MA, 2015), pp. 2224–2232. \n[25] M. Henaff, J. Bruna, and Y. LeCun, arXiv:1506.05163. \n[26] J. Gilmer, S. S. Schoenholz, P. F. Riley, O. Vinyals, and G. E. Dahl, Proceedings of the 34th International Conference on Machine Learning, 2017, http://proceedings.mlr.press/ v70/gilmer17a.html. \n[27] M. Hellenbrandt, Crystallography Reviews 10, 17 (2004). \n[28] S. Kirklin, J. E. Saal, B. Meredig, A. Thompson, J. W. Doak, M. Aykol, S. Rühl, and C. Wolverton, npj Comput. Mater. 1, 15010 (2015). \n[29] K. He, X. Zhang, S. Ren, and J. Sun, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE, New York, 2016), pp. 770–778. \n[30] M. S. Hybertsen and S. G. Louie, Phys. Rev. B 34, 5390 (1986). \n[31] W. Foulkes, L. Mitas, R. Needs, and G. Rajagopal, Rev. Mod. Phys. 73, 33 (2001). \n[32] A. Jain, G. Hautier, C. J. Moore, S. P. Ong, C. C. Fischer, T. Mueller, K. A. Persson, and G. Ceder, Comput. Mater. Sci. 50, 2295 (2011). \n[33] M. De Jong, W. Chen, R. Notestine, K. Persson, G. Ceder, A. Jain, M. Asta, and A. Gamst, Sci. Rep. 6, 34256 (2016). \n[34] I. E. Castelli, T. Olsen, S. Datta, D. D. Landis, S. Dahl, K. S. Thygesen, and K. W. Jacobsen, Energy Environ. Sci. 5, 5814 (2012). \n[35] W. Sun, S. T. Dacek, S. P. Ong, G. Hautier, A. Jain, W. D. Richards, A. C. Gamst, K. A. Persson, and G. Ceder, Sci. Adv. 2, e1600225 (2016). \n[36] G. Shirane, K. Suzuki, and A. Takeda, J. Phys. Soc. Jpn. 7, 12 (1952). \n[37] J. Lang, C. Li, X. Wang et al., Mater. Today: Proc. 3, 424 (2016). \n[38] H. Takatsu, O. Hernandez, W. Yoshimune, C. Prestipino, T. Yamamoto, C. Tassel, Y. Kobayashi, D. Batuk, Y. Shibata, A. M. Abakumov et al., Phys. Rev. B 95, 155105 (2017). \n[39] CGCNN website, https://github.com/txie-93/cgcnn. " + }, + { + "id": "10.1063_1.5019779", + "DOI": "10.1063/1.5019779", + "DOI Link": "http://dx.doi.org/10.1063/1.5019779", + "Relative Dir Path": "mds/10.1063_1.5019779", + "Article Title": "SchNet - A deep learning architecture for molecules and materials", + "Authors": "Schütt, KT; Sauceda, HE; Kindermans, PJ; Tkatchenko, A; Müller, KR", + "Source Title": "JOURNAL OF CHEMICAL PHYSICS", + "Abstract": "Deep learning has led to a paradigm shift in artificial intelligence, including web, text, and image search, speech recognition, as well as bioinformatics, with growing impact in chemical physics. Machine learning, in general, and deep learning, in particular, are ideally suitable for representing quantum-mechanical interactions, enabling us to model nonlinear potential-energy surfaces or enhancing the exploration of chemical compound space. Here we present the deep learning architecture SchNet that is specifically designed to model atomistic systems by making use of continuous-filter convolutional layers. We demonstrate the capabilities of SchNet by accurately predicting a range of properties across chemical space for molecules and materials, where our model learns chemically plausible embeddings of atom types across the periodic table. Finally, we employ SchNet to predict potential-energy surfaces and energy-conserving force fields for molecular dynamics simulations of small molecules and perform an exemplary study on the quantum-mechanical properties of C-20-fullerene that would have been infeasible with regular ab initio molecular dynamics. Published by AIP Publishing.", + "Times Cited, WoS Core": 1389, + "Times Cited, All Databases": 1517, + "Publication Year": 2018, + "Research Areas": "Chemistry; Physics", + "UT (Unique WOS ID)": "WOS:000437190300025", + "Markdown": "# SchNet – A deep learning architecture for molecules and materials \n\nK. T. Schütt, H. E. Sauceda, P.-J. Kindermans, A. Tkatchenko, and K.-R. Müller \n\nCitation: The Journal of Chemical Physics 148, 241722 (2018); doi: 10.1063/1.5019779 \nView online: https://doi.org/10.1063/1.5019779 \nView Table of Contents: http://aip.scitation.org/toc/jcp/148/24 \nPublished by the American Institute of Physics \nArticles you may be interested in \nNon-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials \nparametrized from machine learning \nThe Journal of Chemical Physics 148, 241706 (2018); 10.1063/1.5009502 \n\nImproving the accuracy of Møller-Plesset perturbation theory with neural networks The Journal of Chemical Physics 147, 161725 (2017); 10.1063/1.4986081 \n\nMethods to locate saddle points in complex landscapes The Journal of Chemical Physics 147, 204104 (2017); 10.1063/1.5012271 \n\nNeural networks vs Gaussian process regression for representing potential energy surfaces: A comparative \nstudy of fit quality and vibrational spectrum accuracy \nThe Journal of Chemical Physics 148, 241702 (2018); 10.1063/1.5003074 \n\nwACSF—Weighted atom-centered symmetry functions as descriptors in machine learning potentials The Journal of Chemical Physics 148, 241709 (2018); 10.1063/1.5019667 \n\nThe nature of three-body interactions in DFT: Exchange and polarization effects The Journal of Chemical Physics 147, 084106 (2017); 10.1063/1.4986291 \n\n# SchNet – A deep learning architecture for molecules and materials \n\nK. T. Schu¨ tt,1,a) H. E. Sauceda,2 P.-J. Kindermans,1 A. Tkatchenko,3,b) and K.-R. Mu¨ ller1,4,5,c) \n1Machine Learning Group, Technische Universita¨t Berlin, 10587 Berlin, Germany \n2Fritz-Haber-Institut der Max-Planck-Gesellschaft, 14195 Berlin, Germany \n3Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg \n4Max-Planck-Institut fu¨r Informatik, Saarbru¨cken, Germany \n5Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, \nSeoul 136-713, South Korea \n\n(Received 16 December 2017; accepted 8 March 2018; published online 29 March 2018) \n\nDeep learning has led to a paradigm shift in artificial intelligence, including web, text, and image search, speech recognition, as well as bioinformatics, with growing impact in chemical physics. Machine learning, in general, and deep learning, in particular, are ideally suitable for representing quantum-mechanical interactions, enabling us to model nonlinear potential-energy surfaces or enhancing the exploration of chemical compound space. Here we present the deep learning architecture SchNet that is specifically designed to model atomistic systems by making use of continuous-filter convolutional layers. We demonstrate the capabilities of SchNet by accurately predicting a range of properties across chemical space for molecules and materials, where our model learns chemically plausible embeddings of atom types across the periodic table. Finally, we employ SchNet to predict potential-energy surfaces and energy-conserving force fields for molecular dynamics simulations of small molecules and perform an exemplary study on the quantum-mechanical properties of $\\mathbf{C}_{20}$ - fullerene that would have been infeasible with regular ab initio molecular dynamics. Published by AIP Publishing. https://doi.org/10.1063/1.5019779 \n\n# I. INTRODUCTION \n\nAccelerating the discovery of molecules and materials with desired properties is a long-standing challenge in computational chemistry and the materials sciences. However, the computational cost of accurate quantum-chemical calculations proves prohibitive in the exploration of the vast chemical space. In recent years, there have been increased efforts to overcome this bottleneck using machine learning, where only a reduced set of reference calculations is required to accurately predict chemical properties1–15 or potential-energy surfaces.16–25 While these approaches make use of painstakingly handcrafted descriptors, deep learning has been applied to predict properties from molecular structures using graph neural networks.26,27 However, these are restricted to predictions for equilibrium structures due to the lack of atomic positions in the input. Only recently, approaches that learn a representation directly from atom types and positions have been developed.28–30 While neural networks are often considered as a “black box,” there has recently been an increased effort to explain their predictions in order to understand how they operate or even extract scientific insight. This can be done either by analyzing a trained model31–37 or by directly designing interpretable models.38 For quantum chemistry, some of us have proposed such an interpretable architecture with Deep Tensor \n\nNeural Networks (DTNNs) that not only learns the representation of atomic environments but also allows for spatially and chemically resolved insights into quantum-mechanical observables.28 \n\nHere we build upon this work and present the deep learning architecture SchNet that allows us to model complex atomic interactions in order to predict potential-energy surfaces or speeding up the exploration of chemical space. SchNet, being a variant of DTNNs, is able to learn representations for molecules and materials that follow fundamental symmetries of atomistic systems by construction, e.g., rotational and translational invariance as well as invariance to atom indexing. This enables accurate predictions throughout compositional and configurational chemical space, where symmetries of the potential energy surface are captured by design. Interactions between atoms are modeled using continuousfilter convolutional (cfconv) layers30 being able to incorporate further chemical knowledge and constraints using specifically designed filter-generating neural networks. We demonstrate that these allow us to efficiently incorporate periodic boundary conditions (PBCs) enabling accurate predictions of formation energies for a diverse set of bulk crystals. Beyond that, both SchNet and DTNNs provide local chemical potentials to analyze the obtained representation and allow for chemical insights.28 An analysis of the obtained representation shows that SchNet learns chemically plausible embeddings of atom types that capture the structure of the periodic table. Finally, we present a path-integral molecular dynamics (PIMD) simulation using an energy-conserving force field learned by SchNet trained on reference data from a classical MD at the $\\mathrm{PBE+vdW}^{\\mathrm{TS39,40}}$ level of theory effectively accelerating the simulation by three orders of magnitude. Specifically, we employ the recently developed perturbed path-integral approach41 for carrying out imaginary time PIMD, which allows quick convergence of quantum-mechanical properties with respect to the number of classical replicas (beads). This exemplary study shows the advantages of developing computationally efficient force fields with ab initio accuracy, allowing nanoseconds of PIMD simulations at low temperatures—an inconceivable task for regular ab initio molecular dynamics (AIMD) that could be completed with SchNet within hours instead of years. \n\n# II. METHOD \n\nSchNet is a variant of the earlier proposed Deep Tensor Neural Networks (DTNNs)28 and therefore shares a number of their essential building blocks. Among these are atom embeddings, interaction refinements and atom-wise energy contributions. At each layer, the atomistic system is represented atom-wise being refined using pairwise interactions with the surrounding atoms. In the DTNN framework, interactions are modeled by tensor layers, i.e., atom representations and interatomic distances are combined using a parameter tensor. This can be approximated using a low-rank factorization for computational efficiency.42–44 SchNet instead makes use of continuous-filter convolutions with filter-generating networks30,45 to model the interaction term. These can be interpreted as a special case of such factorized tensor layers. In the following, we introduce these components and describe how they are assembled to form the SchNet architecture. For an overview of the SchNet architecture, see Fig. 1. \n\n# A. Atom embeddings \n\nAn atomistic system can be described uniquely by a set of $n$ atom sites with nuclear charges $Z=(Z_{1},...,Z_{n})$ and positions $R=(\\mathbf{r}_{1},...,\\mathbf{r}_{n})$ . Through the layers of SchNet, the atoms are described by a tuple of features $X^{l}=(\\mathbf{x}_{1}^{l},\\ldots...,\\mathbf{x}_{n}^{l})$ , with $\\mathbf{x}_{i}^{l}\\in\\mathbb{R}^{F}$ with the number of feature maps $F$ , the number of atoms $n$ , and the current layer $l$ . The representation of site $i$ is initialized using an embedding dependent on the atom type $Z_{i}$ \n\n![](images/a8c8493aee177eb8cfb92cb41eb7fd25ce5b7539fe2190131ae572661c945b73.jpg) \nFIG. 1. Illustrations of the SchNet architecture (left) and interaction blocks (right) with atom embedding in green, interaction blocks in yellow, and property prediction network in blue. For each parameterized layer, the number of neurons is given. The filter-generating network (orange) is shown in detail in Fig. 2. \n\n$$\n\\begin{array}{r}{{\\bf x}_{i}^{0}={\\bf a}_{Z_{i}}.}\\end{array}\n$$ \n\nThese embeddings ${\\bf a}_{Z}$ are initialized randomly and optimized during training. They represent atoms of a system disregarding any information about their environment for now. \n\n# B. Atom-wise layers \n\nAtom-wise layers are dense layers that are applied separately to the representations $\\mathbf{x}_{i}^{l}$ of each atom $i$ \n\n$$\n\\mathbf{x}_{i}^{l+1}=W^{l}\\mathbf{x}_{i}^{l}+\\mathbf{b}^{l}.\n$$ \n\nSince weights $W^{l}$ and biases ${\\mathbf b}^{l}$ are shared across atoms, our architecture remains scalable with respect to the number of atoms. While the atom representations are passed through the network, these layers transform them and process information about the atomic environments incorporated through interaction layers. \n\n# C. Interaction blocks \n\nThe interaction blocks of SchNet add refinements to the atom representation based on pairwise interactions with the surrounding atoms. In contrast to DTNNs, here we model these with continuous-filter convolutional (cfconv) layers that are a generalization of the discrete convolutional layers commonly used, e.g., for images46,47 or audio data.48 This generalization is necessary since atoms are not located on regular grid-like image pixels, but can be located at arbitrary positions. Therefore, a filter-tensor, as used in conventional convolutional layers, is not applicable. Instead we need to model the filters continuously with a filter-generating neural network. Given atom-wise representations $X^{l}$ at positions $R$ , we obtain the interactions of atom $i$ as the convolution with all surrounding atoms \n\n$$\n\\mathbf{x}_{i}^{l+1}=(X^{l}*W^{l})_{i}=\\sum_{j=0}^{n_{\\mathrm{atoms}}}\\mathbf{x}_{j}^{l}\\circ W^{l}(\\mathbf{r}_{j}-\\mathbf{r}_{i}),\n$$ \n\nwhere “ ” represents the element-wise multiplication. Note that we perform feature-wise convolutions for computational efficiency.49 Cross-feature processing is subsequently performed by atom-wise layers. Instead of a filter tensor, we define a filter-generating network $W^{l}:\\mathbb{R}^{3}\\xrightarrow[]{}\\mathbb{R}^{F}$ that maps the atom positions to the corresponding values of the filter bank (see Sec. II D). \n\nA cfconv layer together with three atom-wise layers constitutes the residual mapping50 of an interaction block (see Fig. 1, right). We use a shifted softplus $\\operatorname{ssp}(x)=\\ln$ $(0.5e^{x}$ $+\\ 0.5)$ as activation functions throughout the network. The shifting ensures that $\\operatorname{ssp}(0)=0$ and improves the convergence of the network while having infinite order of continuity. This allows us to obtain smooth potential energy surfaces, force fields, and second derivatives that are required for training with forces as well as the calculation of vibrational modes. \n\n# D. Filter-generating networks \n\nThe filter-generating network determines how interactions between atoms are modeled and can be used to constrain the model and include chemical knowledge. We choose a fully connected neural network that takes the vector pointing from atom $i$ to its neighbor $j$ as an input to obtain the filter values $W(\\mathbf{r}_{j}-\\mathbf{r}_{i})$ (see Fig. 2, left). This allows us to include known invariances of molecules and materials into the model. \n\n![](images/d5543272bbeabbdf0fb72c36796201ac73280c7d6bc2290dd9831b5c656237ca.jpg) \nFIG. 2. Architecture of the filter-generating network used in SchNet (left) and $5\\mathring{\\mathrm{A}}\\times5\\mathring{\\mathrm{A}}$ cuts through generated filters (right) from the same filter-generating networks (columns) under different periodic bounding conditions (rows). Each filter is learned from data and represents the effect of an interaction on a given feature of an atom representation located in the center of the filter. For each parameterized layer, the number of neurons is given. \n\n# 1. Rotational invariance \n\nIt is straightforward to include rotational invariance by computing pairwise distances instead of using relative positions. We further expand the distances in a basis of Gaussians \n\n$$\ne_{k}(\\mathbf{r}_{j}-\\mathbf{r}_{i})=\\exp(-\\gamma(\\|\\mathbf{r}_{j}-\\mathbf{r}_{i}\\|-\\mu_{k})^{2}),\n$$ \n\nwith centers $\\mu_{k}$ chosen on a uniform grid between zero and the distance cutoff. This has the effect of decorrelating the filter values, which improves the conditioning of the optimization problem. The number of Gaussians and the hyper parameter $\\gamma$ determine the resolution of the filter. We have set the grid spacing and scaling parameter $\\gamma$ to be $0.11/\\mathring{\\mathrm{A}}^{2}$ for all models in this work. \n\n# 2. Periodic boundary conditions \n\nFor atomistic systems with periodic boundary conditions (PBCs), each atom-wise feature vector $\\mathbf{x}_{i}$ has to be equivalent across all periodic repetitions, i.e., $\\mathbf{x}_{i}=\\mathbf{x}_{i a}=\\mathbf{x}_{i b}$ for repeated unit cells $a$ and $b$ . Due to the linearity of the convolution, we are, therefore, able to apply the PBCs directly to the filter to accurately describe the atom interactions while keeping invariance to the choice of the unit cell. Given a filter $\\tilde{W}^{l}(\\mathbf{r}_{j b}-\\mathbf{r}_{i a})$ over all atoms with $\\|{\\bf r}_{j b}-{\\bf r}_{i a}\\|
PropertyUnitSchNet (T = 6)enn-s2s29
EHOMOeV0.041 ± 0.0010.043
ELUMOeV0.034 ± 0.0000.037
△EeV0.063 ± 0.0000.069
ZPVEmeV1.7 ± 0.0331.5
μD0.033 ± 0.0010.030
αbohr30.235 ± 0.0610.092
(R²>bohr20.073 ± 0.0020.180
UoeV0.014 ± 0.0010.019
UeV0.019 ± 0.0060.019
HeV0.014 ± 0.0010.017
GeV0.014 ± 0.0000.019
Cvcal/mol K0.033 ± 0.0000.040
\n\n![](images/99a37b6a109c61508725866c9ea7bf847a18bf7361f3f7c5144969ca2f86879a.jpg) \nFIG. 3. Mean absolute error (in eV) of energy predictions $(U_{0})$ on the QM9 dataset53–55 depending on the number of interaction blocks and reference calculations used for training. For reference, we give the best performing DTNN models $(\\mathrm{T}=3)$ .28 \n\nFigure 3 shows learning curves of SchNet for the total energy $U_{0}$ with $T\\in\\{1,2,3,6\\}$ interaction blocks compared to the best performing DTNN models.28 The best performing DTNN with $T=3$ interaction blocks can only outperform the SchNet model with $T=1$ . We observe that beyond two interaction blocks the error improves only slightly from $0.015\\mathrm{eV}$ with $T=2$ interaction blocks to $0.014{\\mathrm{~eV}}$ for $T\\in\\{3,6\\}$ using 110k training examples. When training on fewer examples, the differences become more significant and $T=6$ , while having the most parameters, exhibits the lowest errors. Additionally, the model requires much less epochs to converge, e.g., using $110\\mathrm{k}$ training examples reduces the required number of epochs from 2400 with $T=2$ to less than 750 epochs with $T=6$ . \n\n# B. Learning formation energies of materials \n\nWe employ SchNet to predict formation energies for bulk crystals using 69 640 structures and reference calculations from the Materials Project (MP) repository.58,59 It consists of a large variety of bulk crystals with atom type ranging across the whole periodic table up to $Z=94$ . Mean absolute errors (MAEs) are listed in Table II. Again, we use $T=6$ interaction blocks and atomic representations with $F=64$ feature dimension. We set the distance cutoff $r_{\\mathrm{cut}}=5\\mathrm{~\\AA~}$ and discard two examples from the dataset that would include isolated atoms with this setting. Then, the data are randomly split into $60~000$ training examples, a validation set of 4500 examples and the remaining data as test set. Even though the MP repository is much more diverse than the QM9 molecule benchmark, SchNet is able to predict formation energies up to a mean absolute error of 0.035 eV/atom. The distribution of the errors is shown in Appendix A. On a smaller subset 3000 training examples, SchNet still achieves an MAE of 0.127 ev/atom improving significantly upon the descriptors proposed by Faber et al.5 \n\nTABLE II. Mean absolute errors for formation energy predictions in eV/atom on the Materials Project dataset. For SchNet, we give the average over three repetitions as well as standard errors of the mean of the repetitions. Best models in bold. \n\n\n
ModelN= 3000N= 60000
Ext. Coulomb matrix 50.64
Ewald sum matrix50.49
Sine matrix50.37
SchNet (T = 6)0.127 ± 0.0010.035 ± 0.000
\n\nSince the MP dataset contains 89 atom types ranging across the periodic table, we examine the learned atom type embeddings $\\ensuremath{\\mathbf{x}}^{0}$ . Due to their high dimensionality, we visualize two leading principal components of all sp-atom type embeddings as well as their corresponding group (see Fig. 4). The neural network aims to use the embedding space efficiently such that this 2d projection explains only about $20\\%$ of the variance of the embeddings, i.e., since important directions are missing, embeddings might cover each other in the projection while actually being further apart. Still, we already recognize a grouping of elements following the groups of the periodic table. This implies that SchNet has learned that atom types of the same group exhibit similar chemical properties. Within some of the groups, we can even observe an ordering from lighter to heavier elements, e.g., in groups IA and IIA from light elements on the left to heavier ones on the right or, less clear in group VA with a partial ordering N– As, $\\mathrm{\\mathbf{P}}\\}{-}\\{\\mathrm{Sb},\\mathrm{\\Bi}\\}$ . Note that this knowledge was not imposed on the machine learning model, but inferred by SchNet from the geometries and formation energy targets of the MP data. \n\n![](images/5b9161bc87b0ff1953b7ac5a8267f262938e2be72f6429e6eaec3eb1b6318164.jpg) \nFIG. 4. The two leading principal components of the learned embeddings $\\ensuremath{\\mathbf{x}}^{0}$ of sp atoms learned by SchNet from the Materials Project dataset. We recognize a structure in the embedding space according to the groups of the periodic table (color-coded) as well as an ordering from lighter to heavier elements within the groups, e.g., in groups IA and IIA from light atoms (left) to heavier atoms (right). \n\n# C. Local chemical potentials \n\nSince the SchNet is a variant of DTNNs, we can visualize the learned representation with a “local chemical potential” $\\Omega_{Z_{\\mathrm{probe}}}({\\bf r})$ as proposed by Schu¨tt et al.:28 We compute the energy of a virtual atom that acts as a test charge. This can be achieved by adding the probe atom $(Z_{\\mathrm{probe}},{\\bf r}_{\\mathrm{probe}})$ as an input of SchNet. The continuous filter-convolution of the probe atom with the atoms of the system \n\n$$\n\\mathbf{x}_{\\mathrm{probe}}^{l+1}=(X^{l}*W^{l})_{i}=\\sum_{i=0}^{n_{\\mathrm{atoms}}}\\mathbf{x}_{i}^{l}\\circ W^{l}(\\mathbf{r}_{\\mathrm{probe}}-\\mathbf{r}_{i})\n$$ \n\nensures that the test charge only senses but does not influence the feature representation. We use Mayavi60 to visualize the potentials. \n\nFigure 5 shows a comparison of the local potentials of various molecules from QM9 generated by DTNN and SchNet. Both DTNN and SchNet can clearly grasp fundamental chemical concepts such as bond saturation and different degrees of aromaticity. While the general structure of the potential on the surfaces is similar, the SchNet potentials exhibit sharper features and have a more pronounced separation of high-energy and low-energy areas. The overall appearance of the distinguishing molecular features in the “local chemical potentials” is remarkably robust to the underlying neural network architecture, representing the common quantum-mechanical atomic embedding in its molecular environment. It remains to be seen how the “local chemical potentials” inferred by the networks can be correlated with traditional quantum-mechanical observables such as electron density, electrostatic potentials, or electronic orbitals. In addition, such local potentials could aid in the understanding and prediction of chemical reactivity trends. \n\nIn the same manner, we show cuts through $\\Omega_{C}({\\bf r})$ for graphite and diamond in Fig. 6. As expected, they resemble the periodic structure of the solid, much like the corresponding filters in Fig. 2. In solids, such local chemical potentials could be used to understand the formation and distribution of defects, such as vacancies and interstitials. \n\n# D. Combined learning of energies and atomic forces \n\nWe apply SchNet to the prediction of potential energy surfaces and force fields of the MD17 benchmark set of molecular dynamics trajectories introduced by Chmiela et al.21 MD17 is a collection of eight molecular dynamics simulations for small organic molecules. Tables III and IV list mean absolute errors for energy and force predictions. We trained SchNet on randomly sampled training sets with $N=1000$ and $N=50000$ reference calculations for up to $2\\times10^{6}$ mini-batch gradient steps and additionally used a validation set of 1000 examples for early stopping. The remaining data were used for testing. We also list the performances of gradient domain machine learning $(\\mathrm{GDML})^{21}$ and $\\mathrm{DTNN}^{28}$ for reference. SchNet was trained with $T=3$ interaction blocks and $F=64$ feature maps using only energies as well as using the combined loss for energies and forces from Eq. (5) with $\\rho=0.01$ . This trade-off constitutes a compromise to obtain a single model that performs well on energies and forces for a fair comparison with GDML. Again, we do not use a distance cutoff due to the small molecules and a range up to $20\\textup{\\AA}$ for the Gaussian expansion to cover all distances. In Sec. III E, we will see that even lower errors can be achieved when using two separate SchNet models for energies and forces. \n\n![](images/99075358bd1370500c8b9c97e0d79c035058d3d1969f94a296ee0939eb36aec1.jpg) \nFIG. 5. Local chemical potentials $\\Omega_{C}({\\bf r})$ of DTNN (top) and SchNet (bottom) using a carbon test charge on a $\\begin{array}{r}{\\sum_{i}\\lVert\\mathbf{r}-\\mathbf{r}_{i}\\rVert=3.7\\mathrm{~\\AA~}}\\end{array}$ isosurface are shown fo benzene, toluene, methane, pyrazine, and propane. \n\nSchNet can take significant advantage of the additional force information, reducing energy, and force errors by 1-2 orders of magnitude compared to energy only training on the small training set. With 50 000 training examples, the improvements are less apparent as the potential energy surface is already well-sampled at this point. On the small training set, SchNet outperforms GDML on the more flexible molecules malondialdehyde and ethanol, while GDML reaches much lower force errors on the remaining MD trajectories that all include aromatic rings. A possible reason is that GDML defines an order of atoms in the molecule, while the SchNet architecture is inherently invariant to indexing which constitutes a greater advantage in the more flexible molecules. \n\nWhile GDML is more data-efficient than a neural network, SchNet is scalable to larger datasets. We obtain MAEs of energy and force predictions below 0.12 kcal/mol and $0.33\\mathrm{kcal/(mol/\\mathring{A})}$ , respectively. Remarkably, SchNet performs better while using the combined loss with energies and forces on 1000 reference calculations than training on energies of 50 000 examples. \n\n![](images/38dfe90e0781de7eb39d58fe5206f3c387f311831b7e974c6490def8c5675010.jpg) \nFIG. 6. Cuts through local chemical potentials $\\Omega_{C}({\\bf r})$ of SchNet using a carbon test charge are shown for graphite (left) and diamond (right). \n\nTABLE III. Mean absolute errors for total energies (in kcal/mol). GDML,21 DTNN,28 and SchNet30 test errors for $\\Nu=1000$ and $\\mathrm{N}{=}50000$ reference calculations of molecular dynamics simulations of small organic molecules are shown. Best results are given in bold. \n\n\n
N= 1000N= 50000
GDMLSchNetDTNNSchNet
Trained onForcesEnergyEnergy + forcesEnergyEnergyEnergy + forces
Benzene0.071.190.080.040.080.07
Toluene0.122.950.120.180.160.09
Malondialdehyde0.162.030.130.190.130.08
Salicylic acid0.123.270.200.410.250.10
Aspirin0.274.200.370.250.12
Ethanol0.150.930.080.070.05
Uracil0.112.260.140.130.10
Naphthalene0.123.580.160.200.11
\n\nTABLE IV. Mean absolute errors for atomic forces [in $\\mathrm{kcal/(mol/\\hat{A})}]$ ]. GDML21 and $\\mathrm{SchNet}^{30}$ test errors for N $=1000$ and $\\mathrm{N}=50000$ reference calculations of molecular dynamics simulations of small organic molecules are shown. Best results are given in bold. \n\n\n
N= 1000N= 50000
GDMLSchNetSchNet
Trained onForcesEnergyEnergy + forcesEnergyEnergy + forces
Benzene0.2314.120.311.230.17
Toluene0.2422.310.571.790.09
Malondialdehyde0.8020.410.661.510.08
Salicylic acid0.2823.210.853.720.19
Aspirin0.9923.541.357.360.33
Ethanol0.796.560.390.760.05
Uracil0.2420.080.563.280.11
Naphthalene0.2325.360.582.580.11
\n\n# E. Application to molecular dynamics of $\\pmb{C}_{20}$ -fullerene \n\nAfter demonstrating the accuracy of SchNet on the MD17 benchmark set, we perform a study of a ML-driven MD simulation of $\\mathbf{C}_{20}$ -fullerene. This middle-sized molecule has a complex PES that requires to be described with accuracy to reproduce vibrational normal modes and their degeneracies. Here, we use SchNet to perform an analysis of some basic properties of the PES of $\\mathbf{C}_{20}$ when introducing nuclear quantum effects (NQE). The reference data were generated by running classical MD at $500\\mathrm{~K~}$ using DFT at the generalized gradient approximation (GGA) level of theory with the Perdew-Burke-Ernzerhof (PBE)39 exchange-correlation functional and the Tkatchenko-Scheffler (TS) method40 to account for van der Waals interactions. Further details about the simulations can be found in Appendix B. \n\nBy training SchNet on DFT data at the $\\mathrm{PBE+vdW^{TS}}$ level, we reduce the computation time per single point by three orders of magnitude from 11 s using 32 CPU cores to $10\\mathrm{ms}$ using one NVIDIA GTX1080. This allows us to perform long MD simulations with DFT accuracy at low computational cost, making this kind of study feasible. \n\nIn order to obtain accurate energy and force predictions, we first perform an extensive model selection on the given reference data. We use 20k $\\mathbf{C}_{20}$ reference calculations as the training set, $4.5\\mathrm{k}$ examples for early stopping, and report the test error on the remaining data. Table $\\mathrm{\\DeltaV}$ lists the results for various settings of number of interaction blocks $T.$ , number of feature dimensions $F$ of the atomic representations, and the energy-force trade-off $\\rho$ of the combined loss function. First, we select the best hyper-parameters $T,F$ of the model given the trade-off $\\rho=0.01$ that we established to be a good compromise on MD17 (see the upper part of Table V). We find that the configuration of $T=6$ and $F=128$ works best for energies as well as forces. Given the selected model, we next validate the best choice for the trade-off $\\rho$ . Here we find that the best choices for energy and forces vastly diverge: While we established before that energy predictions benefit from force information (see Table III), we achieve the best force predictions for $\\mathbf{C}_{20}$ -fullerene when neglecting the energies. We still benefit from using the derivative of an energy model as force model since this still guarantees an energy-conserving force field.21 \n\nTABLE V. Mean absolute errors for energy and force predictions of $\\mathbf{C}_{20}$ - fullerene in kcal/mol and $\\mathrm{kcal/(mol/\\AA)}$ , respectively. We compare SchNet models with varying numbers of interaction blocks $T_{\\mathrm{{}}}$ , feature dimensions $F$ , and energy-force tradeoff $\\rho$ . For force-only training $(\\rho=0)$ , the integration constant is fitted separately. Best models in bold. \n\n\n
TFpEnergyForces
3640.0100.2280.401
6640.0100.2020.217
31280.0100.1880.197
61280.0100.10020.120
61280.1000.0270.171
61280.0100.1000.120
61280.0010.2380.061
61280.0000.2600.058
\n\n![](images/f6ceef9328478001c8ead722408d92f05d96e617838855c1698f9713692dcb1e.jpg) \nFIG. 7. Normal mode analysis of the fullerene $\\mathbf{C}_{20}$ dynamics comparing SchNet and DFT results. \n\nFor energy predictions, we obtain the best results when using a larger $\\rho{=}0.1$ as this puts more emphasis on the energy loss. Here, we select the force-only model as force field to drive our MD simulation since we are interested in the mechanical properties of the $C_{20}$ fullerene. Figure 7 shows a comparison of the normal modes obtained from DFT and our model. In the bottom panel, we show the accuracy of SchNet with the largest error being ${\\sim}1\\%$ of the DFT reference frequencies. Given these results and the accuracy reported in Table V, we obtained a model that successfully reconstructs the PES and its symmetries.61 \n\nIn addition, in Fig. 8, we present an analysis of the nearest neighbor (1nn), diameter and radial distribution functions at $300\\mathrm{K}$ for classical MD (blue) and PIMD (green) simulations that include nuclear quantum effects. See Appendix B for further details on the simulation. From Fig. 8 (and Fig. 11), it looks like nuclear delocalization does not play a significant role in the peaks of the pair distribution function $h(r)$ for $\\mathbf{C}_{20}$ at room temperature. The nuclear quantum effects increase the 1nn distances by less than $0.5\\%$ but the delocalization of the bond lengths is considerable. This result agrees with previously reported PIMD simulations of graphene.62 However, here we have non-symmetric distributions due to the finite size of C20. \n\nOverall, with SchNet we could carry out 1.25 ns of PIMD, reducing the runtime compared to DFT by 3-4 orders of magnitude: from about 7 years to less than $^{7\\mathrm{~h~}}$ with much less computational resources. Such long time MD simulations are required for detailed studies on mechanical and thermodynamical properties as a function of the temperature, especially in the low temperature regime, where the nuclear quantum effects become extremely important. Clearly, this application evinces the need for fast and accurate machine learning model such as SchNet to explore the different nature of chemical interactions and quantum behavior to better understand molecules and materials. \n\n![](images/44701d9fddb1de1d1be644e6af9bd30bbf2172e2c790acf27eea488b20014bc7.jpg) \nFIG. 8. Analysis of the fullerene $\\mathbf{C}_{20}$ dynamics at $300\\mathrm{K}$ using SchNet@DFT. Distribution functions for nearest neighbours, diameter of the fullerene, and the atomicpair distribution function using classical MD (blue) and PIMD (green) with 8 beads. \n\n# IV. CONCLUSIONS \n\nInstead of having to painstakingly design mechanistic force fields or machine learning descriptors, deep learning allows us to learn a representation from first principles that adapts to the task and scale at hand, from property prediction across chemical compound space to force fields in the configurational space of single molecules. The design challenge here has been shifted to modeling quantum interactions by choosing a suitable neural network architecture. This gives rise to the possibility to encode known quantumchemical constraints and symmetries within the model without losing the flexibility of a neural network. This is crucial in order to be able to accurately represent, e.g., the full potential-energy surface and, in particular, its anharmonic behavior. \n\nWe have presented the deep learning architecture SchNet which can be applied to a variety of applications ranging from the prediction of chemical properties for diverse datasets of molecules and materials to highly accurate predictions of potential energy surfaces and energy-conserving force fields. As a variant of DTNNs, SchNet follows rotational, translational, and permutational invariances by design and, beyond that, is able to directly model periodic boundary conditions. Not only does SchNet yield fast and accurate predictions, but it also allows us to examine the learned representation using local chemical potentials.28 Beyond that, we have analyzed the atomic embeddings learned by SchNet and found that fundamental chemical knowledge had been recovered purely from a dataset of bulk crystals and formation energies. Most importantly, we have performed an exemplary pathintegral molecular dynamics study on the fullerene $\\mathbf{C}_{20}$ at the PBE+vdWTS level of theory that would not have been computationally feasible with common DFT approaches. These encouraging results will guide future work such as studies of larger molecules and periodic systems as well as further developments toward interpretable deep learning architectures to assist chemistry research. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Federal Ministry of Education and Research (BMBF) for the Berlin Big Data Center BBDC (No. 01IS14013A). Additional support was provided by the DFG (No. MU 987/20-1), from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 657679, the BK21 program funded by the Korean National Research Foundation Grant (No. 2012-005741) and the Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (No. 2017-0-00451). A.T. acknowledges support from the European Research Council (ERC-CoG grant BeStMo). \n\n# APPENDIX A: ERROR DISTRIBUTIONS \n\nIn Figs. 9 and 10, we show histograms of the predicted properties of the QM9 and Materials Project dataset, respectively. The histograms include all test errors made across all three repetitions. \n\n![](images/8224b21354d88d70761cf9c12c90ea8b97148f32390cb2c44c61bf8a07199d57.jpg) \nFIG. 9. Histograms of absolute errors for all predicted properties of QM9. The histograms are plotted on a logarithmic scale to visualize the tails of the distribution. \n\n![](images/c760d80e0dc383022a49836afdfa80af4283195f582707bbe3b8b46ef6d29a9e.jpg) \nFIG. 10. Histogram of absolute errors for the predictions of formation energies/atom for the Materials Project dataset. The histogram is plotted on a logarithmic scale to visualize the tails of the distribution. \nFIG. 11. Histograms of absolute errors for all predicted properties of QM9. The histograms are plotted on a logarithmic scale to visualize the tails of the distribution. \n\n# APPENDIX B: MD SIMULATION DETAILS \n\nThe reference data for $C_{20}$ were generated using classical molecular dynamics in the NVT ensemble at $500\\mathrm{K}$ using the Nose-Hoover thermostat with a time step of 1 fs. The forces and energies were computed using DFT with the generalized gradient approximation (GGA) level of theory with the non-empirical exchange-correlation functional of PerdewBurke-Ernzerhof (PBE)39 and the Tkatchenko-Scheffler (TS) method40 to account for ubiquitous van der Waals interactions. The calculations were done using all-electrons with a light basis set implemented in the FHI-aims code.63 \n\nThe quantum nuclear effects are introduced using pathintegral molecular dynamics (PIMD) via Feynman’s path integral formalism. The PIMD simulations were done using the SchNet model implementation in the i-PI code.64 The integration time step was set to 0.5 fs to ensure energy conservation along the MD using the NVT ensemble with a stochastic path integral Langevin equation (PILE) thermostat.65 In PIMD, the treatment of NQE is controlled by the number of beads, P. In our example for $C_{20}$ fullerene, we can see that at room temperature using 8 beads gives an already converged radial distribution function $h(r)$ as shown in Fig. 11. \n\n$^1{\\bf M}$ . Rupp, A. Tkatchenko, K.-R. M¨uller, and O. A. von Lilienfeld, Phys. Rev. Lett. 108, 058301 (2012). \n$^2\\mathrm{G}$ . Montavon, M. Rupp, V. Gobre, A. Vazquez-Mayagoitia, K. Hansen, A. Tkatchenko, K.-R. Mu¨ller, and O. A. von Lilienfeld, New J. Phys. 15, 095003 (2013). \n$^3\\mathrm{K}$ . Hansen, G. Montavon, F. Biegler, S. Fazli, M. Rupp, M. Scheffler, O. A. von Lilienfeld, A. Tkatchenko, and K.-R. M¨uller, J. Chem. Theory Comput. 9, 3404 (2013). \n$^4{\\mathrm{K}}$ . T. Schu¨ tt, H. Glawe, F. Brockherde, A. Sanna, K.-R. M ¨uller, and E. Gross, Phys. Rev. B 89, 205118 (2014). \n${}^{5}\\mathrm{F}.$ Faber, A. Lindmaa, O. A. von Lilienfeld, and R. Armiento, Int. J. Quantum Chem. 115, 1094 (2015). \n$^6{\\bf R}$ . Ramakrishnan, P. O. Dral, M. Rupp, and O. A. von Lilienfeld, J. Chem. Theory Comput. 11, 2087 (2015). \n$^7\\mathrm{K}$ . Hansen, F. Biegler, R. Ramakrishnan, W. Pronobis, O. A. von Lilienfeld, K.-R. M¨uller, and A. Tkatchenko, J. Phys. Chem. Lett. 6, 2326 (2015). \n$^{8}\\mathrm{F}.$ A. Faber, A. Lindmaa, O. A. von Lilienfeld, and R. Armiento, Phys. Rev. Lett. 117, 135502 (2016). \n$^9\\mathbf{M}$ . Hirn, S. Mallat, and N. Poilvert, Multiscale Model. Simul. 15, 827 (2017). \n$^{10}\\mathrm{F}.$ A. Faber, L. Hutchison, B. Huang, J. Gilmer, S. S. Schoenholz, G. E. Dahl, O. Vinyals, S. Kearnes, P. F. Riley, and O. A. von Lilienfeld, J. Chem. Theory Comput. 13(11), 5255–5264 (2017). \n${}^{11}\\mathrm{H}.$ . Huo and M. Rupp, preprint arXiv:1704.06439 (2017). \n$^{12}\\mathbf{M}.$ Eickenberg, G. Exarchakis, M. Hirn, and S. Mallat, Advances in Neural Information Processing Systems 30 (Curran Associates, Inc., 2017), pp. 6522–6531. \n$^{13}\\mathrm{{O}}$ . Isayev, C. Oses, C. Toher, E. Gossett, S. Curtarolo, and A. Tropsha, Nat. Commun. 8, 15679 (2017). \n$^{14}\\mathrm{K}$ . Ryczko, K. Mills, I. Luchak, C. Homenick, and I. Tamblyn, preprint arXiv:1706.09496 (2017). \n$^{15}\\mathrm{I}.$ Luchak, K. Mills, K. Ryczko, A. Domurad, and I. Tamblyn, preprint arXiv:1708.06686 (2017). \n${}^{16}\\mathbf{J}.$ Behler and M. Parrinello, Phys. Rev. Lett. 98, 146401 (2007). \n${}^{17}\\mathbf{J}.$ Behler, J. Chem. Phys. 134, 074106 (2011). \n18A. P. Barto´k, M. C. Payne, R. Kondor, and G. Cs´anyi, Phys. Rev. Lett. 104, 136403 (2010). \n19A. P. Bart´ok, R. Kondor, and G. Cs´anyi, Phys. Rev. B 87, 184115 (2013). \n${}^{20}\\mathrm{A}$ . V. Shapeev, Multiscale Model. Simul. 14, 1153 (2016). \n21S. Chmiela, A. Tkatchenko, H. E. Sauceda, I. Poltavsky, K. T. Schu¨tt, and K.-R. Mu¨ller, Sci. Adv. 3, e1603015 (2017). \n22F. Brockherde, L. Voigt, L. Li, M. E. Tuckerman, K. Burke, and K.-R. M¨uller, Nat. Commun. 8, 872 (2017). \n23J. S. Smith, O. Isayev, and A. E. Roitberg, Chem. Sci. 8, 3192 (2017). \n$^{24}\\mathrm{E}$ . V. Podryabinkin and A. V. Shapeev, Comput. Mater. Sci. 140, 171 (2017). \n$^{25}\\mathrm{P}.$ Rowe, G. Cs´anyi, D. Alf\\`e, and A. Michaelides, Phys. Rev. B 97(5), 054303 (2018). \n$\\ensuremath{^26}\\ensuremath{\\mathrm{D}}$ . K. Duvenaud, D. Maclaurin, J. Iparraguirre, R. Bombarell, T. Hirzel, A. Aspuru-Guzik, and R. P. Adams, in Conference on Neural Information Processing Systems, edited by C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, and R. Garnett (Curran Associates, Inc., 2015), pp. 2224–2232. \n27S. Kearnes, K. McCloskey, M. Berndl, V. Pande, and P. F. Riley, J. Comput.- Aided Mol. Des. 30, 595 (2016). \n$^{28}\\mathrm{K}$ . T. Schu¨tt, F. Arbabzadah, S. Chmiela, K.-R. Mu¨ller, and A. Tkatchenko, Nat. Commun. 8, 13890 (2017). \n${}^{29}\\mathrm{J}$ . Gilmer, S. S. Schoenholz, P. F. Riley, O. Vinyals, and G. E. Dahl, in Proceedings of the 34th International Conference on Machine Learning (PMLR, 2017), pp. 1263–1272. \n$^{30}{\\dot{\\mathrm{K}}}$ . T. Schu¨tt, P.-J. Kindermans, H. E. Sauceda, S. Chmiela, A. Tkatchenko, and K.-R. M¨uller, in Advances in Neural Information Processing Systems 30 (Curran Associates, Inc., 2017), pp. 992–1002. \n$\\ensuremath{{^31\\mathrm{D}}}$ . Baehrens, T. Schroeter, S. Harmeling, M. Kawanabe, K. Hansen, and K.-R. Mu¨ller, J. Mach. Learn. Res. 11, 1803–1831 (2010). \n$^{32}\\mathrm{K}$ . Simonyan, A. Vedaldi, and A. Zisserman, eprint arXiv:1312.6034 (2013). \n33S. Bach, A. Binder, G. Montavon, F. Klauschen, K.-R. M¨uller, and W. Samek, PLoS One 10, e0130140 (2015). \n$^{34}\\mathrm{L}$ . M. Zintgraf, T. S. Cohen, T. Adel, and M. Welling, in International Conference on Learning Representations, 2017. \n$^{35}\\mathrm{G}$ . Montavon, S. Lapuschkin, A. Binder, W. Samek, and K.-R. M¨uller, Pattern Recognit. 65, 211 (2017). \n$^{36}\\mathrm{P.-J}$ . Kindermans, K. T. Sch ¨utt, M. Alber, K.-R. M ¨uller, D. Erhan, B. Kim, and S. D¨ahne, eprint arXiv:1705.05598 (2017). \n$^{37}\\mathrm{G}$ . Montavon, W. Samek, and K.-R. Mu¨ller, Digital Signal Process. 73, 1 (2018). \n$^{38}{\\dot{\\mathrm{K}}}$ . Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhudinov, \nR. Zemel, and Y. Bengio, in International Conference on Machine Learning (PMLR, 2015), pp. 2048–2057. \n${}^{39}\\mathrm{\\dot{J}}$ P. Perdew, K. Burke, and M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996). \n$^{40}\\mathrm{{\\dot{A}}}$ . Tkatchenko and M. Scheffler, Phys. Rev. Lett. 102, 073005 (2009). \n$^{41}\\mathrm{I}.$ Poltavsky and A. Tkatchenko, Chem. Sci. 7, 1368 (2016). \n$^{42}\\mathrm{G}$ . W. Taylor and G. E. Hinton, in Proceedings of the 26th Annual \nInternational Conference on Machine Learning ICML 09 (ACM, 2009), Vol. 49, p. 1. \n43D. Yu, L. Deng, and F. Seide, IEEE Trans. Audio, Speech, Lang. Process. \n21, 388 (2013). \n$^{44}\\mathrm{R}$ . Socher, A. Perelygin, J. Y. Wu, J. Chuang, C. D. Manning, A. Y. Ng, and C. Potts, in Conference on Empirical Methods in Natural Language Processing (ACL, 2013), Vol. 1631, p. 1642. \n$^{45}\\mathrm{X}.$ . Jia, B. De Brabandere, T. Tuytelaars, and L. V. Gool, in Advances in Neural Information Processing Systems 29, edited by D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett (Curran Associates, Inc., 2016), \npp. 667–675. \n46Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel, Neural Comput. 1, 541 (1989). \n47A. Krizhevsky, I. Sutskever, and G. E. Hinton, Advances in Neural Information Processing Systems (Curran Associates, Inc., 2012), pp. 1097–1105. \n48A. van den Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. Senior, K. Kavukcuoglu. “WaveNet: A Generative Model for Raw Audio,” arXiv:1609.03499 (2016). \n49F. Chollet, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE, 2017), pp. 1251–1258. \n${}^{50}\\mathrm{\\ddot{K}}$ . He, X. Zhang, S. Ren, and J. Sun, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2016), pp. 770–778. \n51A. Pukrittayakamee, M. Malshe, M. Hagan, L. Raff, R. Narulkar, S. Bukkapatnum, and R. Komanduri, J. Chem. Phys. 130, 134101 (2009). \n52D. P. Kingma and J. Ba, in International Conference on Learning Representations, 2015. \n$^{53}\\mathrm{R}$ . Ramakrishnan, P. O. Dral, M. Rupp, and O. A. von Lilienfeld, Sci. Data 1, 140022 (2014). \n$^{54}\\mathrm{L}$ . C. Blum and J.-L. Reymond, J. Am. Chem. Soc. 131, 8732 (2009). \n${}^{55}\\mathrm{J}.$ -L. Reymond, Acc. Chem. Res. 48, 722 (2015). \n$^{56}\\mathrm{O}$ . Vinyals, S. Bengio, and M. Kudlur, eprint arXiv:1511.06391 (2015). \n$^{57}\\mathrm{\\bfM}$ . Gastegger, J. Behler, and P. Marquetand, Chem. Sci. 8(10), 6924–6935 (2017). \n58A. Jain, S. P. Ong, G. Hautier, W. Chen, W. D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, and K. A. Persson, APL Mater. 1, 011002 (2013). \n$^{59}\\mathrm{\\dot{S}}$ . P. Ong, W. D. Richards, A. Jain, G. Hautier, M. Kocher, S. Cholia, D. Gunter, V. L. Chevrier, K. A. Persson, and G. Ceder, Comput. Mater. Sci. 68, 314 (2013). \n$^{60}\\mathrm{P}.$ Ramachandran and G. Varoquaux, Comput. Sci. Eng. 13, 40 (2011). \n61Code and trained models are available at: https://github.com/atomisticmachine-learning/SchNet. \n${}^{62}\\mathrm{I}.$ Poltavsky, R. A. DiStasio, Jr., and A. Tkatchenko, J. Chem. Phys. 148, 102325 (2018). \n$^{63}\\mathrm{V}.$ Blum, R. Gehrke, F. Hanke, P. Havu, V. Havu, X. Ren, K. Reuter, and M. Scheffler, Comput. Phys. Commun. 180, 2175 (2009). \n$^{64}\\mathrm{M}$ . Ceriotti, J. More, and D. E. Manolopoulos, Comput. Phys. Commun. 185, 1019 (2014). \n$^{65}\\mathrm{M}$ . Ceriotti, M. Parrinello, T. E. Markland, and D. E. Manolopoulos, J. Chem. Phys. 133, 124104 (2010). " + }, + { + "id": "10.1038_s41586-018-0691-0", + "DOI": "10.1038/s41586-018-0691-0", + "DOI Link": "http://dx.doi.org/10.1038/s41586-018-0691-0", + "Relative Dir Path": "mds/10.1038_s41586-018-0691-0", + "Article Title": "Efficient and stable emission of warm-white light from lead-free halide double perovskites", + "Authors": "Luo, JJ; Wang, XM; Li, SR; Liu, J; Guo, YM; Niu, GD; Yao, L; Fu, YH; Gao, L; Dong, QS; Zhao, CY; Leng, MY; Ma, FS; Liang, WX; Wang, LD; Jin, SY; Han, JB; Zhang, LJ; Etheridge, J; Wang, JB; Yan, YF; Sargent, EH; Tang, J", + "Source Title": "NATURE", + "Abstract": "Lighting accounts for one-fifth of global electricity consumption(1). Single materials with efficient and stable white-light emission are ideal for lighting applications, but photon emission covering the entire visible spectrum is difficult to achieve using a single material. Metal halide perovskites have outstanding emission properties(2,3); however, the best-performing materials of this type contain lead and have unsatisfactory stability. Here we report a lead-free double perovskite that exhibits efficient and stable white-light emission via self-trapped excitons that originate from the Jahn-Teller distortion of the AgCl6 octahedron in the excited state. By alloying sodium cations into Cs2AgInCl6, we break the dark transition (the inversion-symmetry-induced parity-forbidden transition) by manipulating the parity of the wavefunction of the self-trapped exciton and reduce the electronic dimensionality of the semiconductor(4). This leads to an increase in photoluminescence efficiency by three orders of magnitude compared to pure Cs2AgInCl6. The optimally alloyed Cs-2(Ag0.60Na0.40) InCl6 with 0.04 per cent bismuth doping emits warm-white light with 86 +/- 5 per cent quantum efficiency and works for over 1,000 hours. We anticipate that these results will stimulate research on singleemitter-based white-light-emitting phosphors and diodes for next-generation lighting and display technologies.", + "Times Cited, WoS Core": 1705, + "Times Cited, All Databases": 1781, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000450960000050", + "Markdown": "# Efficient and stable emission of warm-white light from lead-free halide double perovskites \n\nJiajun Luo1,11, Xiaoming Wang2,11, Shunran Li1,11, Jing Liu1,11, Yueming $\\mathrm{Guo}^{3}$ , Guangda $\\mathrm{{Niu^{1}}}$ , Li $\\mathrm{Yao^{1}}$ , Yuhao $\\mathrm{Fu^{4}}$ , Liang $\\mathrm{Gao}^{1,5}$ , Qingshun Dong6, Chunyi Zhao7, Meiying Leng1, Fusheng $\\mathrm{Ma}^{6}$ , Wenxi Liang1, Liduo $\\mathrm{Wang^{6}}$ , Shengye $\\mathrm{Jin^{7}}$ , Junbo $\\mathrm{Ha}\\mathrm{\\bar{n}}^{8}$ , Lijun Zhang4, Joanne Etheridge3,9, Jianbo Wang10, Yanfa $\\mathrm{Yan^{2*}}$ , Edward H. Sargent5 & Jiang Tang1\\* \n\nLighting accounts for one-fifth of global electricity consumption1. Single materials with efficient and stable white-light emission are ideal for lighting applications, but photon emission covering the entire visible spectrum is difficult to achieve using a single material. Metal halide perovskites have outstanding emission properties2,3; however, the best-performing materials of this type contain lead and have unsatisfactory stability. Here we report a lead-free double perovskite that exhibits efficient and stable white-light emission via self-trapped excitons that originate from the Jahn–Teller distortion of the $\\mathbf{AgCl}_{6}$ octahedron in the excited state. By alloying sodium cations into $\\mathbf{Cs_{2}A g I n C l_{6}},$ we break the dark transition (the inversion-symmetry-induced parity-forbidden transition) by manipulating the parity of the wavefunction of the self-trapped exciton and reduce the electronic dimensionality of the semiconductor4. This leads to an increase in photoluminescence efficiency by three orders of magnitude compared to pure $\\mathbf{Cs}_{2}\\mathbf{AgInCl_{6}}$ . The optimally alloyed $\\mathbf{Cs}_{2}(\\mathbf{Ag}_{0.60}\\mathbf{Na}_{0.40})\\mathbf{InCl}_{6}$ with 0.04 per cent bismuth doping emits warm-white light with ${\\bf86\\pm5}$ per cent quantum efficiency and works for over 1,000 hours. We anticipate that these results will stimulate research on singleemitter-based white-light-emitting phosphors and diodes for nextgeneration lighting and display technologies. \n\nMetal halide perovskites have rapidly advanced the field of opto­ electronic devices because of their exceptional defect tolerance, low-cost solution processing and tunable emission across the visible spectrum5–8. For example, the photoluminescence quantum yield (PLQY) of perovskite nanocrystals is now close to unity9,10, and green and red electroluminescent devices have been reported to have external quantum efficiencies that reach $20.1\\%^{11-14}$ . For lighting applications, white emission from a single emitter layer is of particular interest, because it simplifies device structure and avoids the self-absorption and colour instability seen in mixed and multiple emitters15. \n\nBroadband and white emission typically originate from self-trapped excitons (STEs) that exist in semiconductors with localized carriers and a soft lattice16–18. Although hybrid metal halide perovskites, par­ ticularly those with low-dimensional crystal structures15,19–21, have received considerable attention as broadband-emission materials, they rarely achieve high PLQY21. Further challenges in their use as emitters include their reliance on water-soluble lead-based materials, unsatis­ factory stability and a lack of systematic understanding of the origins of white emission. \n\nHere we focused on the double perovskite $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ , which is a promising material emitting warm-white light, in view of its broad spectrum (400–800 nm) and its all-inorganic and lead-free nature22–24. \n\nWe first performed first-principles density-functional-theory and many-body perturbation-theory calculations using the GW approxima­ tion and the Bethe–Salpeter equation (BSE) to understand the origins of the broadband emission in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . The GW-BSE calculations indicated that the lowest exciton, which has a binding energy $\\boldsymbol{E_{\\mathrm{b}}}$ of $0.25\\mathrm{eV},$ is dark (emits no photons) because the associated transition is parity-forbidden24 (Fig. 1a). This exciton was calculated with the crystal structure fixed in its ground-state equilibrium, which represents the situation of the free exciton. We then investigated exciton–phonon coupling by relaxing the lattice, which represents the situation of the STEs (Fig. 1b). We found that the STEs in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ arise from a strong Jahn–Teller distortion of the $\\mathrm{AgCl}_{6}$ octahedron (see inset of Fig. 1b); that is, the $\\mathrm{Ag-Cl}$ bonds are elongated by $0.08\\mathring\\mathrm{A}$ in the axial direction but compressed by $0.2\\mathring\\mathrm{A}$ in the equatorial plane. Hole trap­ ping at $\\mathrm{Ag}$ atoms that changes the electronic configuration of $\\mathrm{\\Ag}$ to $\\bar{4d^{9}}$ favours a Jahn–Teller distortion. The STE has the same orbital char­ acter as the free exciton, indicating a parity-forbidden transition. The self-trapping energy $E_{\\mathrm{st}}$ and lattice-deformation energy $E_{\\mathrm{d}}$ —which are the excited-state and ground-state energy differences between the STE and free-exciton configurations, as shown in the configuration coor­ dinate diagram of Fig. 1c—were calculated to be $0.53\\mathrm{eV}$ and $0.67\\mathrm{eV},$ respectively. The emission energy was thus calculated to be $E_{\\mathrm{PL}}=E_{\\mathrm{g}}$ $-E_{\\mathrm{st}}-E_{\\mathrm{d}}-E_{\\mathrm{b}}=1.82\\:\\mathrm{eV},$ where $E_{\\mathrm{g}}{=}3.27\\mathrm{eV}$ is the fundamental band­ gap energy, based on GW calculations and experimental results. This value agrees with the experimental photoluminescence peak value22 of $2\\mathrm{eV.}$ The phonon frequency, $\\hbar\\Omega_{\\mathrm{g}}$ ( $\\mathbf{\\mathit{\\hat{h}}},$ reduced Planck constant), of the ground state, obtained by fitting the configuration coordinate diagram, is $18.3\\mathrm{meV},$ which agrees well with the phonon eigenmode of $17\\mathrm{meV.}$ The corresponding eigenvector shows displacement in agreement with the Jahn–Teller distortion (Extended Data Fig. 1), consistent with the view that the Jahn–Teller distortion is responsible for STE formation in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . Strong electron–phonon coupling, which is necessary for STE formation, is confirmed by the large Huang–Rhys25 factor $S{=}E_{\\mathrm{d}}/\\mathrm{{\\hbar}}\\Omega_{\\mathrm{g}}{=}37$ , consistent with experimental results (Extended Data Fig. 2). With the phonon frequency $\\hbar\\Omega_{\\mathrm{e}}=17.4\\mathrm{meV}$ of the excited state, we can estimate the exciton self-trapping time as $\\tau=2\\pi/\\Omega_{\\mathrm{e}}=238$ fs, which indicates an ultrafast transition from a free exciton to an STE fol­ lowing photoexcitation. The calculated photoluminescence spectrum and a comparison with the experimental data are shown in Fig. 1d. Overall the agreement is good, except for the small deviations at $400-$ $450\\mathrm{nm}$ , which could be attributed to the free-exciton emission not accounted for in our calculations. \n\nThe above theoretical analysis indicates an extremely low PLQY for pure $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . The PLQY is defined as the ratio of the radiative recombination rate $(k_{\\mathrm{rad}})$ to the sum of the radiative and non-radiative $(k_{\\mathrm{non}})$ recombination rates. From Fermi’s golden rule, $k_{\\mathrm{rad}}$ is propor­ tional to the transition dipole moment, $\\mu=\\langle\\varphi_{\\mathrm{h}}^{}|\\hat{\\mu}|\\varphi_{\\mathrm{e}}^{}\\rangle$ , where $\\varphi_{\\mathrm{e}}$ and $\\varphi_{\\mathrm{h}}$ are the electron and hole wavefunctions, respectively, and $\\hat{\\mu}$ is the electric dipole operator. The dark transition of the free excitons and STEs in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ results in extremely low radiative recombination rates, leading to low PLQY $(<0.1\\%$ ; Extended Data Fig. 2d). Increasing $k_{\\mathrm{rad}}$ and reducing $k_{\\mathrm{non}}$ are two strategies to enhance the PLQY. The first and most critical step towards improving the PLQY is to break the parity-forbidden transition by manipulating the symmetry of the STE wavefunction. A practical approach to this end is to partially substitute Ag with an element that can sustain the double-perovskite structure, but has a distinctively different electronic configuration to $\\operatorname{Ag}.$ , such as a group-IA element (alkali metal). We therefore explored alloying Na into $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . Broadband emission was also observed in pure $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ (Extended Data Fig. 3), but with very low efficiency due to strong phonon emission, as indicated by a simulated high Huang–Rhys factor of 80 at the excited state. We note that the Huang–Rhys factor can potentially serve as the figure of merit for the design of efficient white-light-emitting materials from STEs (Extended Data Table 1). Because the lattice mismatch between $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ is as low as $0.30\\%$ (Supplementary Table 1), we anticipated that $\\mathrm{Na^{+}}$ could be incorporated uniformly into $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}.$ without causing detrimen­ tal defects or phase separation. For the synthesis, CsCl, NaCl, AgCl and ${\\mathrm{InCl}}_{3}$ precursors were mixed into an HCl solution in a hydrothermal autoclave, which was heated for a given time and then slowly cooled down, resulting in white precipitates as final products. This straight­ forward synthesis gave a product yield of nearly $90\\%$ . \n\n![](images/1e29a7ab36274c77b3e46994fa8e8b1308b83f2ab2f09951b7f39539abd96e7e.jpg) \nFig. 1 | Computational studies of the STEs in $\\mathbf{Cs}_{2}\\mathbf{AgInCl_{6}}$ . a, GW band structure of $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . The orbital characters and free-exciton wavefunction are plotted as a fat-band structure. The green, blue, cyan and red colours denote the Cl $3p$ , $\\mathrm{Ag4}d$ , In 5s and $\\mathrm{Ag}5s$ orbitals, respectively. The magenta circles indicate the lowest free-exciton amplitude $\\vert A_{\\nu c k}\\vert,$ where $\\begin{array}{r}{|\\bar{S\\rangle}=\\sum_{\\nu c\\pmb{k}}A_{\\nu c\\pmb{k}}|\\nu c\\rangle}\\end{array}$ is the exciton wavefunction, $\\nu$ and $c$ denote the valence and conduction states, and $\\pmb{k}$ is the wavevector. $\\vert S\\rangle$ is derived from the electron and hole states with the same parity (labels at the zone centre G and X) along GX, implying a dark transition. b, STE in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . Cs atoms are omitted for clarity. The cyan and magenta isosurfaces represent the electron and hole orbital densities $\\langle\\rho=\\langle\\psi\\bar{|\\psi\\rangle}$ ) , respectively. The \nelectron state (red dashed circle) is rather extended and the hole state (black dashed circle) is compact, consistent with the small (large) effective mass of the conduction (valence) band shown in a. The inset shows the Jahn–Teller distortion of the $\\mathrm{\\AgCl}_{6}$ octahedron. Here the hole isosurface is obvious, whereas the electron isosurface is invisible owing to its small density. c, Configuration coordinate diagram for the STE formation. $E_{\\mathrm{st}},E_{\\mathrm{d}}$ and $E_{\\mathrm{PL}}$ are the self-trapping, lattice-deformation and emission energies, respectively. d, Calculated photoluminescence spectrum compared with the experimental result. The calculated curve has been shifted to align its maximum with that of the experimentally measured curve for better comparison. \n\nX-ray diffraction (XRD) patterns of a series of compositions (Fig. 2a) confirmed the pure double-perovskite phase. The intensity of the (111) diffraction peak (marked with an asterisk in Fig. 2a) is related to the $\\mathrm{Na/Ag}$ composition through the dispersion factor of the Na, Ag and In atoms26. These agree well with the compositions determined using inductively coupled plasma optical emission spec­ trometry (ICP-OES; Supplementary Table 3). This observation also suggests a high degree of B(I) and $\\mathbf{B}^{\\prime}(\\mathrm{III})$ site ordering and negligible antisite defects (Supplementary Fig. 2). The refined lattice param­ eters follow a linear increase upon Na substitution, indicating sol­ id-solution behaviour with $\\mathrm{Na^{+}/A g^{+}}$ randomly distributed27 at B(I) sites in $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ (Extended Data Fig. 4). Upon Na alloying, an evident excitonic absorption peak emerged near $365\\mathrm{nm}$ , and the intensity of white emission was enhanced by three orders of mag­ nitude compared to the pure $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ (Fig. 2b). A similar phenomenon was also found in Li-doped $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and Na-doped $\\mathrm{Cs}_{2}\\mathrm{AgSbCl}_{6}$ (Extended Data Fig. 5), suggesting a general trend of alkali-metal-induced photoluminescence enhancement in double perovskites. We then recorded the photoluminescence spec­ tra of a series of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ powders by varying the measure­ ment temperatures, and found that the extracted activation energy (Supplementary Figs. 6, 7) increases monotonically with increasing Na content, suggesting suppression of the non-radiative process and ther­ mal quenching upon Na alloying. With optimized Na content, Bi dop­ ing and slow cooling, we obtained the highest PLQY of $(86\\pm5)\\%$ at a Na content of about $40\\%$ (Fig. 2c, Supplementary Fig. 8). To the best of our knowledge, this PLQY represents the highest efficiency reported for white-emitting materials (Supplementary Table 4). The bestperforming white-light-emitting lead halide perovskites C4N2H14PbBr428 and $\\mathrm{CuGaS_{2}/Z n S}$ quantum dots29 exhibit PLQYs of $20\\%$ and $73\\%$ , respectively. The $\\mathrm{Bi}^{3+}$ incorporation is believed to improve crystal perfection and promote exciton localization30, further enhancing the PLQY (Extended Data Fig. 6). \n\n![](images/04ab5409a59619b800ad3a4d7566e92239029e571237a46a4da4ecf5344d0185.jpg) \nFig. 2 | Characterization of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ with different Na content. All samples were doped using a small amount ( $0.04\\%$ , atomic ratio to In) of Bi, and the compositions were determined from ICP-OES results (Supplementary Table 3). a, XRD patterns of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ powders with different Na content. The asterisk marks the (111) diffraction peak. $\\theta$ , diffraction angle; a.u., arbitrary units. b, Optical absorption (solid lines) and photoluminescence (dashed lines) spectra of pure $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ . c, Activation energy and PLQY of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ powder versus Na content. The reproducibility of the PLQY results is shown in Supplementary Fig. 8d (best, about $86.2\\%$ ; \naverage, about $71.0\\%$ ; lowest, about $56.0\\%$ ). The dashed lines are guides for the eye. d, Excitation spectra of photoluminescence, measured at different wavelengths. e, Emission intensity versus excitation power for $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ . The linear fit result has a high $R^{2}$ value of 0.998. f, Transient absorption spectra for $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ (laser pulse of $325\\mathrm{nm}$ and $4\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ ). $\\Delta A/A$ is the optical density. The irregular peaks located at about $650\\mathrm{nm}$ are from frequency doubling of the pumping light. All data shown in the figure were obtained from measurements on $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ powder and crystals. \n\nThe STE origin of the white emission was further experimentally con­ firmed via photoluminescence excitation (PLE) spectra (Fig. 2d). For emission from 460 to $700\\mathrm{nm}$ , the PLE spectra exhibit identical shapes and features, indicating that the white emission originates from the relaxa­ tion of the same excited state. The experimental observations that the PLE spectra decrease to nearly zero at wavelengths above $400\\mathrm{nm}$ , that the emis­ sion intensity from $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ exhibits a linear dependence on the excitation power (Fig. 2e) and that the PLQY results are independent from the photoexcitation power (Supplementary Fig. 9) all suggest that the emission does not arise from permanent defects. Surface-defect emis­ sion is also ruled out by the comparable photoluminescence intensity of single crystals and ball-milled powders (Supplementary Fig. 10). The transient absorption data further provide direct evidence of $\\mathrm{STEs^{17}}$ . With 325-nm-wavelength laser photoexcitation, $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ exhibited a broad photoinduced absorption at energies across the visible spectrum (Fig. 2f, Supplementary Fig. 11), with an onset time of about 500 fs, con­ sistent with our calculated exciton self-trapping time. \n\nWe performed further theoretical analysis to understand the trend of the PLQY as a function of Na content. In Fig. 3a, we show the calcu­ lated transition dipole moment of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{1-x}\\mathrm{Na}_{x}\\mathrm{InCl}_{6}$ as a function of Na concentration. It is clear that with the increase of Na content, the transition dipole moment first increases and then decreases, reflecting the observed composition-dependent PLQY. Figure 3b compares the electron wavefunction of the STEs before and after the Na alloying. Na incorporation breaks the inversion symmetry of the $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ lattice and changes the electron wavefunction at the Ag site from symmetric to asymmetric; this results in a parity change in the STE wavefunction and consequently allows radiative recombination. Because $\\mathrm{Na^{+}}$ contributes to neither the conduction-band minimum nor the valence-band maxi­ mum of the alloy, the second effect of Na incorporation is to reduce the electronic dimensionality4 of the $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ lattice by partially isolat­ ing the $\\mathrm{AgCl}_{6}$ octahedra (Supplementary Fig. 12). The newly formed $\\mathrm{NaCl}_{6}$ octahedra serve as barriers that confine the spatial distribution of the STEs (Fig. 3c), thus enhancing the electron and hole orbital overlap and increasing the transition dipole moment. For example, the radius of the STE is reduced from more than $20\\textup{\\AA}$ for the pure $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ to only $9\\mathring{\\mathrm{A}}$ with $50\\%$ Na incorporation, which increases the transition dipole moment from zero to 0.07 (in arbitrary units, a.u.). \n\nTwo factors account for the decreased PLQY upon further increasing the Na content. For Na-rich compounds, the electron remains strongly confined within a single In octahedron $\\mathrm{In}~5s$ and Cl $3p$ ), and the hole is always located on the $\\mathrm{Ag4}d$ orbital and the neighbouring Cl $3p$ orbitals (Fig. 3d). Therefore, the orbital spatial overlap between electrons and holes for the STEs, and hence the transition dipole moment, is markedly reduced. The second factor is the increased non-radiative loss in the Na-rich alloy. We found that the excited- and ground-state curves cross in the configuration coordinate diagram of pure $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ (Fig. 3e), which means that some photoexcited electrons can recombine with holes non-radiatively through phonon emission. The resulting diminished transition dipole moment and enhanced non-radiative recombination rates explain the decreased PLQY for Na-rich alloys. \n\nThe photoluminescence spectrum of the best-performing $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ powder exhibits extended overlap with the sen­ sitivity of the human eye to optical wavelengths (that is, the lumi­ nosity function) (Fig. 3a), which enables a theoretical luminous efficacy reaching about $373\\mathrm{lm}\\mathrm{W}^{-1}$ . Emission stability is another key, yet very challenging, parameter for lighting applications. The $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ materials demonstrated little emission degrada­ tion when tested from $233\\mathrm{K}$ to $343\\mathrm{K}$ . A version of the material slightly richer in N $\\mathrm{\\dot{\\a}\\left(N a/(A g+N a)=0.46\\right)}$ showed stable emission up to $393\\mathrm{K}$ (Supplementary Fig. 13). We further annealed our $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ powders on a hotplate at $150^{\\circ}\\mathrm{C}$ for $^{1,000\\mathrm{h}}$ and observed little pho­ toluminescence decay of the white emission (Fig. 4b). We propose that the strongly bound excitons and nearly defect-free lattice of $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ prevent photoluminescence quenching and that the all-inorganic composition also helps resist thermal stress (decom position temperature of up to about $863\\mathrm{K}$ ; Supplementary Fig. 14). \n\n![](images/3eef8bb6d7dc5bf40aca2ec66083d3ca0a8b682e1268a233e6efebdea2434fae.jpg) \nFig. 3 | Mechanistic investigations of PLQY in $\\mathbf{C_{{S_{2}}}}\\mathbf{A}\\mathbf{g}_{1-x}\\mathbf{Na}_{x}\\mathbf{In}\\mathbf{C}\\mathbf{l_{6}}$ . a, Transition dipole moment, $\\mu$ , as a function of Na content in $\\mathrm{Cs}_{2}\\mathrm{Ag}_{1-x}\\mathrm{Na}_{x}\\mathrm{InCl}_{6}$ . Assuming constant nonradiative recombination, the PLQY is proportional to $\\mu$ . b, Parity change of the electron wavefunction (isosurface at Ag site; see the key in the inset of $\\mathbf{d}$ ) of the STE before and after Na incorporation. c, Configuration showing the strengthened STE confinement by the surrounding $\\mathrm{NaCl}_{6}$ octahedra. The STEs are confined within two lattice parameters surrounded by the $\\mathrm{NaCl}_{6}$ octahedra. d, STE in Na-rich $\\mathrm{Cs}_{2}\\mathrm{Ag}_{1-x}\\mathrm{Na}_{x}\\mathrm{InCl}_{6}$ . The STE is located in two neighbouring octahedra $\\mathrm{\\langleAgCl_{6}}$ and $\\mathrm{InCl}_{6}$ ) with the hole derived from the $\\mathrm{Ag4}d/\\mathrm{Cl}$ $3p$ orbitals and the electron from In $5s/\\mathrm{Cl}3p$ orbitals. e, Configuration coordinate diagram of the STE formation in $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ (inset). The STE is located within a single distorted $\\mathrm{InCl}_{6}$ octahedron. The hole is located at the well known $V_{\\mathrm{k}}$ centre, that is, a $\\mathrm{Cl}_{2}^{-}$ dimer ion, whereas the electron is derived from In $5s/\\mathrm{Cl}$ $3p$ orbitals. The separation of the electron and hole makes the optical transition very weak. In $\\mathbf{b-e}$ , the cyan and magenta isosurfaces denote electrons and holes, respectively. \n\nWe fabricated a white-emission light-emitting diode (LED) by directly pressing the $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ powders onto a commercial ultraviolet LED chip, without using epoxy or silica encapsulation for protection. With the contribution from the blue light of the ultraviolet LED chip $(380-410\\mathrm{nm})$ , the device has CIE coordinates (0.396, 0.448), located at a warm-white point with a correlated colour temperature of $4{,}054\\mathrm{K}$ , which fulfils the requirements for indoor lighting. The \n\n![](images/e6710dee28ac637218953b5c12b57e4948b49c899f02d3f2ab1a956b7be67d56.jpg) \n\nFig. 4 | White emission from \n$\\mathbf{C}s_{2}\\mathbf{A}\\mathbf{g}_{1-x}\\mathbf{Na}_{x}\\mathbf{InCl}_{6}$ . a, Luminosity function (dashed line) and photoluminescence spectra (solid lines) of $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ measured at different temperatures from $233\\mathrm{K}$ to \n$343\\mathrm{K}$ b, Photoluminescence stability of \n$\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ against continuous heating at $150^{\\circ}\\mathrm{C}$ on a hotplate, measured after cooling to room temperature. c, Operational stability of $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ down-conversion devices, measured in air without any encapsulation. \nThe box plot shows the results for five different samples measured separately, with the box \nedges representing quartiles, the band inside the box showing the median and the end of the whiskers representing the minimum and maximum of the data. d, XRD patterns of a \n$\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ film (black line) and \npowder (red line). The inset shows a ${300}\\mathrm{-nm}$ - thick quartz substrate and $500\\mathrm{-nm}$ -thick \n$\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ films under $254\\mathrm{-nm}$ \nultraviolet illumination. \n\nwhite LED showed negligible degradation when operated at about $5,000\\mathrm{cd}\\mathrm{m}^{-2}$ for over $^{1,000\\mathrm{h}}$ in air (Fig. 4c). This outstanding photo­ metric performance, combined with its easy manufacture, indicate promise for white-phosphor applications. \n\nThe broadband emission associated with the STEs provides a new strategy to produce single-material-based, white-light electrolumi­ nescence. We thus fabricated prototype double-perovskite-based electroluminescence devices. XRD measurements confirmed the pure phase of the thermally evaporated $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ film, which showed bright and uniform warm-white photoluminescence under ultraviolet-lamp excitation (Fig. 4d). Our electroluminescence device demonstrated bias-insensitive broadband emission and a peak current efficiency of 0.11 cd $\\mathrm{A}^{-1}$ , which was mainly limited by the low quality of the $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ films (Supplementary Figs. 15–17). Further research should focus on optimizing emitting-layer quality and device configuration to increase electroluminescence performance. \n\nIn summary, Na alloying into $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ breaks the parityforbidden transition and reduces its electronic dimensionality, leading to efficient white emission via radiative recombination of STEs. This white-light-emitting material also demonstrates outstanding stability and low-cost manufacture, indicating promise for solid-state lighting. We believe that halide double perovskites hold great potential for dis­ play and lighting applications and merit further study to realize their full potential. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, statements of data availability and associated accession codes are available at http://sci-hub.tw/10.1038/s41586-018-0691-0. \n\nReceived: 27 February 2018; Accepted: 31 August 2018; \nPublished online 7 November 2018. \n1. Sun, Y. et al. Management of singlet and triplet excitons for efficient white organic light-emitting devices. Nature 440, 908–912 (2006). \n2.\t Tan, Z. K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n3. Cho, H. et al. Overcoming the electroluminescence efficiency limitations of perovskite light-emitting diodes. Science 350, 1222–1225 (2015). \n4.\t Xiao, Z. et al. Searching for promising new perovskite-based photovoltaic absorbers: the importance of electronic dimensionality. Mater. Horiz. 4, 206–216 (2017). \n5. Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskite as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n6. Burschka, J. et al. Sequential deposition as a route to high-performance perovskite-sensitized solar cells. Nature 499, 316–319 (2013). \n7. Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n8. Yin, W. J., Shi, T. & Yan, Y. Unique properties of halide perovskites as possible origins of the superior solar cell performance. Adv. Mater. 26, 4653–4658 (2014). \n9. Protesescu, L. et al. Nanocrystals of cesium lead halide perovskites $\\mathsf{\\ C s P b}\\mathsf{X}_{3}$ , $\\mathsf{X}{=}\\mathsf{C l}$ , Br, and I): novel optoelectronic materials showing bright emission with wide color gamut. Nano Lett. 15, 3692–3696 (2015). \n10.\t Zhou, Q. et al. In situ fabrication of halide perovskite nanocrystal embedded polymer composite films with enhanced photoluminescence for display backlights. Adv. Mater. 28, 9163–9168 (2016). \n11.\t Wang, N. et al. Perovskite light-emitting diodes based on solutionprocessed self-organized multiple quantum wells. Nat. Photon. 10, 699–704 (2016). \n12.\t Yuan, M. et al. Perovskite energy funnels for efficient light-emitting diodes. Nat. Nanotechnol. 11, 872–877 (2016). \n13.\t Yang, X. et al. Efficient green light-emitting diodes based on quasi-twodimensional composition and phase engineered perovskite with surface passivation. Nat. Commun. 9, 570 (2018); correction 9, 1169 (2018). \n14.\t Zhao, B. et al. High-efficiency perovskite-polymer bulk heterostructure light-emitting diodes. Preprint at https://arxiv.org/abs/1804.09785 (2018). \n15.\t Dohner, R. E., Hoke, T. K. & Karunadasa, I. H. Self-assembly of broadband white-light emitters. J. Am. Chem. Soc. 136, 1718–1721 (2014). \n16.\t Song, K. S. & Williams, R. T. Self-Trapped Excitons (Springer, New York, 2008). \n17.\t Smith, M. D. & Karunadasa, H. I. White-light emission from layered halide perovskites. Acc. Chem. Res. 51, 619–627 (2018). \n18.\t Ueta, M., Kanzaki H., Kobayashi K., Toyozawa Y. & Hanamura E. in Excitonic Processes in Solids 309–369 (Springer, Berlin, Heidelberg, 1986). \n19.\t Dohner, R. E., Jaffe, A., Bradshaw, R. L. & Karunadasa, I. H. Intrinsic white-light emission from layered hybrid perovskites. J. Am. Chem. Soc. 136, 13154– 13157 (2014). \n20.\t Mao, L., Wu, Y., Stoumpos, C. C., Wasielewski, M. R. & Kanatzidis, M. G. White-light emission and structural distortion in new corrugated two-dimensional lead bromide perovskites. J. Am. Chem. Soc. 139, 5210–5215 (2017). \n21.\t Zhou, C. et al. Luminescent zero-dimensional organic metal halide hybrids with near-unity quantum efficiency. Chem. Sci. 9, 586–593 (2018). \n22.\t Volonakis, G. et al. Cs2InAgCl6: a new lead-free halide double perovskite with direct band gap. J. Phys. Chem. Lett. 8, 772–778 (2017). \n23.\t Zhao, X. G. et al. Cu–In halide perovskite solar absorbers. J. Am. Chem. Soc. 139, 6718–6725 (2017). \n24.\t Meng, W. et al. Parity-forbidden transitions and their impact on the optical absorption properties of lead-free metal halide perovskites and double perovskites. J. Phys. Chem. Lett. 8, 2999–3007 (2017). \n25.\t Huang, K. & Rhys, A. Theory of light absorption and non-radiative transitions in F-centres. Proc. R. Soc. Lond. A 204, 406–423 (1950). \n26.\t Lim, T.-W. et al. Insights into cationic ordering in Re-based double perovskite oxides. Sci. Rep. 6, 19746 (2016). \n27.\t Maughan, A. E. et al. Defect tolerance to intolerance in the vacancy-ordered double perovskite semiconductors $\\mathsf{C s}_{2}\\mathsf{S n l}_{6}$ and Cs2TeI6. J. Am. Chem. Soc. 138, 8453–8464 (2016). \n28.\t Yuan, Z. et al. One-dimensional organic lead halide perovskites with efficient bluish white-light emission. Nat. Commun. 8, 14051 (2017). \n29.\t Kim, J.-H. et al. White electroluminescent lighting device based on a single quantum dot emitter. Adv. Mater. 28, 5093–5098 (2016). \n30.\t Moser, F. & Lyu, S. Luminescence in pure and I-doped AgBr crystals. J. Lumin. 3, 447–458 (1971). \n\nAcknowledgements This work was financially supported by the National Natural Science Foundation of China (51761145048 and 61725401), the National Key R&D Program of China (2016YFB0700702, 2016YFA0204000 and 2016YFB0201204), the HUST Key Innovation Team for Interdisciplinary Promotion (2016JCTD111) and the Program for JLU Science and Technology Innovative Research Team. The calculation of broadband emission at the University of Toledo was supported by the Center for Hybrid Organic Inorganic Semiconductors for Energy (CHOISE), an Energy Frontier Research Center funded by the Office of Basic Energy Sciences, Office of Science within the US Department of Energy. The analysis of the electronic properties of halide double perovskites was funded by the Office of Energy Efficiency and Renewable Energy (EERE), US Department of Energy, under award number DE-EE0006712. Part of the code development was supported by the National Science Foundation under contract number DMR-1807818. Y.Y. acknowledges support from the Ohio Research Scholar Program. For the theoretical calculations we used the resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under contract number DE-AC02-05CH11231. Y.G. and J.E. acknowledge financial support by the Australian Research Council (DP150104483) and the use of instrumentation at the Monash Centre for Electron Microscopy. The authors from HUST thank the Analytical and Testing Center of HUST and the facility support of the Center for Nanoscale Characterization and Devices, WNLO. We also thank Z. Xiao for useful discussion about emission mechanisms and some XRD measurements, as well as T. Zhai, H. Song, Y. Zhou, H. Han, X. Lu and L. Xu for providing access to some facilities. \n\nReviewer information Nature thanks C. C. Stoumpos and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\nAuthor contributions J.T. conceived the idea and guided the whole project. J. Luo, S.L. and J. Liu designed and performed most of the experiments and analysed the data; X.W. performed most of the theoretical calculations and analysis (GW-BSE, STE, photoluminescence) under the guidance of Y.Y.; S.L. discovered the phosphor; L.Y. contributed in electroluminescence device optimization; L.G. carried out transient-absorption experiments; M.L. assisted in data analysis and photoluminescence measurements; Y.G. and J.E. carried out the electron microscopy measurements and analysed the results; Y.F. and L.Z. simulated the band alignment and the contour plots of the valence-band maximum and conduction-band maximum charge densities; C.Z. and S.J. provided some optical measurements; Q.D., F.M., L.W., W.L. and J.H. helped in the PLQY measurement and electroluminescence device fabrication; G.N. was involved in data analysis and experimental design; J.W. contributed to DFT calculations, Y.Y. helped in manuscript writing; J. Luo, X.W., E.H.S. and J.T. wrote the paper; all authors commented on the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\nAdditional information \nExtended data is available for this paper at https://doi.org/10.1038/s41586- 018-0691-0. \nSupplementary information is available for this paper at https://doi.org/ 10.1038/s41586-018-0691-0. \nReprints and permissions information is available at http://www.nature.com/ reprints. \nCorrespondence and requests for materials should be addressed to Y.Y. or J.T. \nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional \n\nclaims in published maps and institutional affiliations. \n\n# Methods \n\nMaterials. Caesium chloride (CsCl, $99.99\\%$ ), silver chloride (AgCl, $99.99\\%$ ), sodium chloride (NaCl, $99.99\\%$ ), lithium chloride (LiCl, $99.9\\%$ ), anhy­ drous indium chloride $\\mathrm{(InCl_{3}}$ , $99.999\\%$ ), anhydrous bismuth chloride $\\mathrm{(BiCl}_{3}$ $99.999\\%$ ), anhydrous antimony chloride ${\\mathrm{SbCl}}_{3}$ , $99.99\\%$ ), zinc acetate dehydrate $\\mathrm{(Zn(CH_{3}C O O)_{2}.2H_{2}O>98\\%)}$ , tetramethylammonium hydroxide (TMAH, $98\\%$ ) and polyethylenimine (PEIE) were purchased from Sigma Aldrich. Molybdenum oxide $(\\mathrm{MoO}_{3},99\\%)$ and $^{4,4^{\\prime}}$ -cyclohexylidenebis $\\mathrm{.}N,N_{\\cdot}$ -bis(4-methylphenyl)benze­ namine] (TAPC, $99\\%$ ) were purchased from Guangdong Aglaia Optoelectronic Materials Company. Hydrochloric acid, ethanol, acetone, isopropanol, ethyl acetate, 1-butanol and dimethyl sulfoxide (DMSO, $99\\%$ ) were purchased from Sinopharm Chemical Reagent Company. Patterned indium tin oxide (ITO) glass substrates (sheet resistance, $15\\Omega\\mathrm{sq}^{-1},$ ) were purchased from Guangdong Xiangcheng Technology Company. All materials were used as received. \n\nSynthesis of alloyed double-perovskite materials. Because double perovskites are generally impurity-sensitive, a Teflon autoclave was soaked overnight with aqua regia and high-purity raw materials were used. Then, 1 mmol anhydrous $\\mathrm{InCl}_{3}$ , $0.005\\mathrm{mmol}$ anhydrous ${\\mathrm{BiCl}}_{3}$ and 2 mmol CsCl were first dissolved in $10\\mathrm{ml}$ of a $10\\mathrm{{M}}$ HCl solution in a $25\\mathrm{-ml}$ Teflon autoclave. Then $x\\mathrm{mmol}$ of $\\mathrm{\\AgCl}$ and $_{1-x}$ mmol of NaCl were added and the solution was heated at $180^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ in a stainless-steel Parr autoclave. The solution was then steadily cooled to $50^{\\circ}\\mathrm{C}$ at a speed of $3^{\\circ}\\mathrm{Ch}^{-1}$ (the cooling process was key in determining the PLQY of the products). The as-prepared crystals were then filtered out, washed with isopro­ panol and dried in a furnace at $60^{\\circ}\\mathrm{C}$ . $\\mathrm{{Na}}$ -doped $\\mathrm{Cs}_{2}\\mathrm{Ag}\\mathrm{Sb}{\\mathrm{Cl}_{6}}$ was synthesized by substituting the ${\\mathrm{InCl}}_{3}$ with ${\\mathrm{SbCl}}_{3}$ , and Li-doped $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ was obtained by mix­ ing 20 mmol LiCl with 1 mmol $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ in a $25\\mathrm{-ml}$ Teflon autoclave containing $4\\mathrm{ml}$ of a $10\\mathrm{MHCl}$ solution, and then following exactly the same procedure as for the $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ synthesis. \n\nCharacterization and calibration of the PLQY of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ . The PLQY was measured using an absolute photoluminescence measurement system (Hamamatsu Quantaurus-QY) at Tsinghua University. The excitation wavelength was $365\\mathrm{nm}$ , and the step increments and integration time were $1\\mathrm{nm}$ and 0.5 s per data point, respectively. Commercial $\\mathrm{YAG:C\\bar{e}^{3+}}$ powder purchased from Hunan LED Company with a standard PLQY $80\\%-85\\%$ , $460\\mathrm{nm}$ excitation) was used to calibrate the system. \n\nElectroluminescence device fabrication. Colloidal $\\mathrm{znO}$ nanocrystals were synthe­ sized following a published procedure31. Patterned indium-doped ITO substrates were cleaned by sequential sonication in acetone, ethanol and deionized water, for $30\\mathrm{min}$ in each bath. After drying, solutions of PEIE in isopropanol $(0.1\\mathrm{wt\\%})$ were spin-coated onto the ITO substrates at $5,000{\\mathrm{r.p.m}}$ . for $60~\\mathsf{s}.$ , followed by a layer of $\\mathrm{{}}Z\\mathrm{{nO}}$ nanocrystals spun at ${3,000}\\mathrm{r.p.m},$ . for 60 s, and a further PEIE layer $(0.1\\mathrm{wt\\%}$ in 2-methoxyethanol), spin-coated at ${5,000}\\mathrm{r.p.m.}$ for $60~\\mathsf{s}.$ . The $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ film was deposited by thermal evaporation of CsCl, AgCl, NaCl, ${\\mathrm{InCl}}_{3}$ and ${\\mathrm{BiCl}}_{3}$ in separate crucibles at a stoichiometric molar ratio of 2:0.6:0.4:1:\\~0.005. The evap­ oration rate was monitored by a quartz microbalance. After the pressure of the evaporator chamber (Fangsheng Technology, OMV-FS300) was pumped down to $6\\times10^{-6}$ mTorr, one precursor was heated slowly to achieve a desirable deposition rate (CsCl, $0.10{-}0.2\\bar{0}\\bar{\\mathrm{\\AA}}s^{-1}$ ; NaCl $,0.01{-}0.03\\mathring{\\mathrm{A}}\\dot{\\mathbf{s}}^{-1}$ ; AgCl $,0.05\\mathrm{-}0.10\\mathring\\mathrm{A}s^{-1}$ ; ${\\mathrm{InCl}}_{3}$ , $0.10{-}0.20\\mathring{\\mathrm{A}}s^{-1}$ ; ${\\mathrm{BiCl}}_{3}$ , $0.01\\mathrm{~\\AA~}\\ s^{-1}.$ ). The shutter was then manually opened until a certain thickness was deposited. The evaporation sequence was CsCl, $\\mathrm{InCl}_{3}$ , ${\\mathrm{BiCl}}_{3}$ , $\\mathrm{\\DeltaNaCl}$ and $\\mathrm{\\AgCl}$ . Then, the $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ film was exposed to air for $5\\mathrm{min}$ and further annealed at $150^{\\circ}\\mathrm{C}$ in $\\Nu_{2}$ for $5\\mathrm{{min}}$ to promote crystallization. Afterwards, $40\\mathrm{-nm}$ -thick TAPC layers were deposited at a speed of $0.1\\dot{0}-0.20\\mathring{\\mathrm{A}}s^{-1}$ , followed by the deposition of the $\\mathrm{MoO}_{3}/$ Al electrode to complete the device (device area, $4\\mathrm{mm}^{2}$ ). \n\nMaterial characterization. Powder XRD measurements were performed by grind­ ing $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ crystals into fine powders in a mortar, using a Philips X’pert pro MRD diffractometer with $\\operatorname{CuK}\\alpha$ radiation. High-resolution XRD measure­ ments were conducted on a powder diffractometer (D8 ADVANCE, Bruker) using a $\\operatorname{CuK}\\alpha$ rotating anode. The absorption and reflectance spectra were measured on an ultraviolet–visible spectrophotometer (PerkinElmer Instruments, Lambda 950) with an integrating sphere, which was calibrated by measuring a reference material $\\mathrm{\\Delta[MgO]}$ powder) at the same time. The photoluminescence and PLE measurements were carried out using an Edinburgh Instruments Ltd UC920 spectrometer. The temperature-dependent photoluminescence spectra were measured using a Horiba Jobin Yvon LabRAM HR800 Raman spectrometer excited by a $325\\mathrm{-nm}$ -wavelength He–Cd laser and at a temperature ranging from 80 to $500~\\mathrm{K}$ , achieved using a liquid-nitrogen cooler. The intensity-dependent photoluminescence measure­ ment was also carried out using a picosecond-pulse diode laser (Light Conversion, Pharos) with 365-nm output wavelength and 50-ps pulse width, and the pulse intensity was monitored by a power meter (Ophir PE10BF-C). The power density was controlled by neutral-density filters (Light Conversion, Pharos). The photo­ luminescence lifetime measurement was performed using time-correlated sin­ gle-photon counter technology. The excitation beam was a picosecond-pulse diode laser (Light Conversion, Pharos) with $365\\mathrm{-nm}$ output wavelength and 50-ps pulse width. For the transient-absorption measurement, an amplified Yb:KGW laser (Light Conversion, Pharos) with 5-kHz repetition rate was used to generate fem­ tosecond-laser pulses (pump wavelength, $325\\mathrm{nm}$ ; intensity, $4\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ ). A crystal with a size of about $0.2\\times1.0\\times1.0\\:\\mathrm{min}^{3}$ was placed on the glass substrate during the measurement. ICP-OES measurements were carried out using a Perkin Elmer Optima 7300DV spectrometer with the $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ powders dissolved in HCl. Thermal gravimetric analysis were performed with a PerkinElmer Diamond TG/DTA6300 system at a heating rate of $10^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ from room temperature to $800^{\\circ}\\mathrm{C}$ in $\\Nu_{2}$ flow using an alumina crucible. A $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ thin film fab­ ricated by thermal evaporation was characterized by scanning electron microscopy (FEI Nova NanoSEM450, without Pt coating), ultraviolet photoemission spectros­ copy (Specs UVLS, He i excitation, $21.2\\mathrm{eV}$ ; referenced to the Fermi edge of argonetched gold). Stability against heat was measured by simply putting the powders on a $150^{\\circ}\\mathrm{C}$ hotplate in ${\\bf N}_{2}$ , and the photoluminescence intensity was measured after a certain time interval. We note that all measurements were performed on powder and crystals, except for the electroluminescence measurements, which were made on films. \n\nTransmission electron microscopy analysis. Transmission electron microscopy (TEM) specimens were prepared by crushing the as-grown single crystals and then drop-casting them onto a TEM copper grid covered by an ultrathin carbon film. TEM characterization was carried out on a JEOL 2100F TEM with a field-emis­ sion gun operating at $200\\mathrm{kV}$ at the Monash Centre for Electron Microscopy (MCEM). Low-dose selected-area electron diffraction and scanning electron nanobeam diffraction were performed to avoid beam damage. Using a nominal current density of $2\\mathsf{p A}\\mathsf{c m}^{-\\bar{2}}$ , no change in lattice parameters was observed after several minutes’ exposure. For the scanning electron nanobeam diffraction meas­ urement, a step size of $5\\mathrm{nm}$ was used and a dataset of $10\\times10$ diffraction patterns of (2,048 pixels) $\\times(2{,}048$ pixels) was collected from a square region of $50\\times50\\mathrm{nm}^{2}$ We deployed a digital micrograph script for automatic control of the scanning coils and pattern acquisition, developed by J. M. Zuo’s group at the University of Illinois at Urbana-Champaign. \n\nFirst-principles density functional theory, many-body perturbation theory and BSE calculations. Density functional theory, GW and BSE calculations were performed using the VASP code32,33 with projector augmented-wave (PAW)34 potentials. A kinetic energy cutoff of $520~\\mathrm{eV}$ and $\\Gamma$ -centred $4\\times4\\times4k$ -mesh were employed. Because the band gaps of both $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ were found to be sensitive to the bond length, we used the more accurate $\\mathrm{PBE0}^{35}$ functional to relax the atomic coordinates with a force tolerance of $0.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ while keeping the lattice parameters fixed at their experimental values. With the relaxed coordinates, GW calculations were performed using the $\\mathrm{PBE}^{36}$ wavefunc­ tion. Partial self-consistency on Green’s function only—the $\\mathrm{GW}_{0}$ scheme—was adopted. For the GW calculations, an energy cutoff of $200\\mathrm{eV}$ for the response function, 200 real frequency grids for the dielectric function and 1,000 bands were used. The results were further extrapolated to infinite-basis sets and a number of bands37. GW band structures were obtained using Wannier interpolation with the wannier90 code38. BSE calculations were performed using the GW quasipar­ ticle energies. The number of occupied/virtual states used for $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ were $2/2$ and $24/4$ , respectively, to achieve convergence of the sev­ eral low-lying exciton states. The exciton binding energies were extrapolated to infinitely dense $k$ -meshes. For a finer $k$ -mesh, GW calculations are computation­ ally prohibitive. We used Wannier interpolation to interpolate the GW quasipar­ ticle energies and model the dielectric function3 $^9\\varepsilon_{\\mathfrak{q}},$ which was fitted from the value obtained with a coarser grid to interpolate the dielectric function $\\begin{array}{r}{{\\bf\\nabla}_{\\mathcal{E}_{\\bf q}}=1}\\end{array}$ $+[(\\varepsilon_{\\infty}-1)^{-1}+a q^{2}+b q^{4}]^{-1}$ , where $\\varepsilon_{\\infty}$ is the static dielectric constant, $q$ is the wave vector, and $a$ and $b$ are fitting parameters). \n\nSTE calculation. To study the STE properties, we used the restricted open-shell Kohn–Sham (ROKS) theory $^{40-42}$ , as implemented in the cp2k code43. A supercell with a single $\\Gamma$ point was used in the calculation. The double-zeta valence polar­ ization molecularly optimized basis sets44, PBE exchange-correlation functional and Goedecker–Teter–Hutter pseudopotentials45 were used. Energy cutoffs of 300 Ry and 1,200 Ry (1 rydberg, $1\\ {\\mathrm{Ry}}=13.605\\ {\\mathrm{eV}},$ ) were used for $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6},$ respectively. The delocalization error of the PBE functional was removed using the scaled Perdew–Zunger self-interaction correction $^{46,47}$ only on the unpaired electrons48. The scaling parameter $\\alpha$ of the Hartree energy was fitted to reproduce the exciton binding energies calculated by the GW-BSE approach. The exciton binding energy within the ROKS framework is calculated as $E_{\\mathrm{b}}{=}E_{\\mathrm{g}}-\\left(S_{1}-E_{0}\\right)$ , where $S_{1}$ and $E_{0}$ are the first excited singlet-state and groundstate energies, respectively. We obtained $\\alpha{=}0.30$ and $\\alpha{=}0.34$ for $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6},$ respectively. Because the present self-interaction correction scheme is not meant to correct the bandgap, the excited-state curves in the configuration coordinate diagrams were shifted by aligning the free-exciton energy with that from the GW-BSE calculations. A supercell with a size of $21.0\\times21.0\\times21.0\\mathring{\\mathrm{A}}^{3}$ was found enough to obtain convergence of both the free exciton and the STE of $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ . However, for $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6},$ owing to the small effective mass of the electron, a supercell with a size as large as $4\\bar{1}.9\\times41.9\\times41.9\\mathring{\\mathrm{A}}^{3}$ is needed. For a completely delocalized state, the self-interaction correction is zero; hence, we neglected the self-interaction correction on the electron wavefunction of the STE in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . This can safely reduce the supercell size to only $20.9\\times20.9\\times20.9\\mathring{\\mathrm{A}}^{3}$ . For the alloyed double perovskites, we used a supercell of $21.0\\times21.0\\times21.0\\mathring{\\mathrm{A}}^{3}$ and $\\alpha=0.34$ . \n\nConfiguration coordinate diagram and photoluminescence spectra calculation. The configuration coordinate (Q) diagram was constructed by linearly interpolat­ ing the coordinates between the free-exciton and STE configurations and then calculating both the ground-state and excited-state energies at each coordinate. The coordinate difference between the free-exciton and STE configurations is $\\begin{array}{r}{\\Delta Q=\\sqrt{\\sum_{\\boldsymbol{\\kappa},i}M_{\\boldsymbol{\\kappa}}(R_{\\boldsymbol{\\kappa},i}^{\\mathrm{e}}-R_{\\boldsymbol{\\kappa},i}^{\\mathrm{g}})^{2}}}\\end{array}$ , where $\\kappa$ denotes the atom, $i=(x,y,z)$ , $M$ is the atomic mass and $R$ are the atomic coordinates with e and $\\mathbf{g}$ for the excited and ground state, respectively. The calculated $\\Delta Q$ is $4.35\\mathring{\\mathrm{A}}\\mathrm{AMU}^{\\bar{1/2}}$ and $9.16\\mathring{\\mathrm{A}}\\mathbf{AMU}^{1/2}$ , respectively, for $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ . The coordinate Q was linearly inter­ polated between 0 and $\\Delta Q$ . The phonon frequency $\\varOmega$ was obtained by a third-or­ der polynomial fit $((1/2)\\Omega^{2}Q^{2}+\\lambda Q^{3}$ ; $\\lambda$ is a fitting parameter) of the excited- or ground-state curve. The normalized photoluminescence intensity in the leading order can be written ${\\mathfrak{s}}^{49}I(h\\nu)=C\\nu^{x}A(h\\nu)$ ( $\\overset{\\cdot}{x}=3$ for dipole-allowed transition, $x=5$ for dipole-forbidden transition), where $h\\nu$ is the photon energy and $C$ is the normalization factor, which includes the transition dipole moments for dipoleallowed transitions, or the magnetic dipole moments and electric quadruple moments for dipole-forbidden transitions. $A$ is the normalized spectral function, under the Franck–Condon approximation: \n\n$$\nA(h\\nu)=\\sum_{m,n}w_{m}(T)\\ |\\langle\\chi_{_{\\mathbf{g}n}}\\ |\\chi_{_{\\mathbf{e}m}}\\rangle|^{2}\\delta(E_{\\mathrm{ZPL}}+\\hbar\\omega_{m}-\\hbar\\omega_{n}-h\\nu)\n$$ \n\n$w_{m}(T)$ is the thermal occupation factor of the excited-state phonons with energy $\\hbar\\omega_{m}=(m)\\hbar\\Omega_{m},$ where $\\varOmega_{m}$ is the phonon frequency, $m$ is the corresponding quan­ tum number, $n$ denotes the related ground-state quantity, $T$ is the temperature and $k_{\\mathrm{B}}$ is the Boltzmann constant. $E_{\\mathrm{ZPL}}$ is the zero-phonon line energy, which is the energy difference between the minima of the excited- and ground-state curves plus the zero-point energy difference, $(1/2)\\hbar(\\Omega_{\\mathrm{e}}-\\Omega_{\\mathrm{g}})$ . $\\chi_{e m}$ and $\\chi_{\\mathrm{g}n}$ are the harmonic phonon wavefunctions of the excited and ground states, respectively. The Franck– Condon factors $|\\langle\\chi_{\\mathrm{g}n_{\\cdot}}|\\chi_{\\mathrm e m}\\rangle|^{2}$ were calculated by the recurrence method50. The $\\delta$ function in equation (1) was replaced by the Lorentzian with a broadening para­ meter of $0.03\\mathrm{eV},$ which is around the phonon cutoff frequency of $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ (Extended Data Fig. 2). \n\nLED devices on ultraviolet chips. GaN-based ultraviolet chips (14 W output, $365-370\\mathrm{nm}$ peak emission) were purchased from Taiwan Epileds Company. The $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ crystals were ball-milled into fine powder, and the powder was painted onto the commercial chips without encapsulation. The LEDs were driven by a Keithley 2400 source meter, and the emission spectra and intensity were recorded by a Photo Research SpectraScan PR655 photometer. For the device stability test, the LED was continuously powered by a Keithley 2400 source meter at a fixed current, and the initial brightness was set at about $5,000\\mathrm{cd}\\mathrm{m}^{-2}$ . The device performance was monitored after a certain time interval. \n\nElectroluminescence device performance measurement. The density–voltage and luminance–voltage characteristics and the electroluminescence spectra of the devices were collected by a Photo Research SpectraScan PR655 photometer and a Keithley 2400 source meter constant-current source. All the experiments were carried out at room temperature under ambient conditions in the dark. \n\nCalculation and comparison of Huang–Rhys factors. In principle, the Huang Rhys factor (S) reflects how strongly electrons couple to phonons and can be obtained by fitting the temperature-dependent full-width at half-maxima (FWHM) of photoluminescence peaks using the following equation51 \n\n$$\n\\mathrm{FWHM}=2.36\\sqrt{S}\\hbar\\omega_{\\mathrm{phonon}}\\sqrt{\\cot\\left(\\frac{\\hbar\\omega_{\\mathrm{phonon}}}{2k_{\\mathrm{B}}T}\\right)}\n$$ \n\nwhere $\\hbar\\omega_{\\mathrm{phonon}}$ is the phonon frequency. For $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ , S and $\\hbar\\omega_{\\mathrm{phonon}}$ are cal­ culated as 38.7 and $20.1\\mathrm{meV},$ respectively, in good agreement with our simulation results (37 and $17.4\\mathrm{meV}$ ). Extended Data Table 1 lists the S values of a few repre­ sentative compounds—we note that the Huang–Rhys factor of nanomaterials is generally higher than that of their bulk counterparts because of quantum confine­ ment52. The Huang–Rhys factor of $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ is 38.7, which is larger than that of many common emitters, such as ${\\mathrm{CdSe}}^{{\\bar{53}}}$ , $Z\\mathrm{nSe}^{54}$ and $\\mathrm{CsPbBr}_{3}{}^{55}$ , indicating the easy formation of STEs in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . For comparison, formation of STEs is also found in materials with high Huang–Rhys factors56, such as $\\mathrm{Cs}_{3}\\mathrm{Sb}_{2}\\mathrm{I}_{9}$ , $\\mathrm{Cs}_{3}\\mathrm{Bi}_{2}\\mathrm{I}_{9}$ and $\\mathrm{Rb}_{3}\\mathrm{Sb}_{2}\\mathrm{I}_{9}$ . However, for efficient STE emission, S should not be overly large, because otherwise the excited-state energy would be dissipated by phonons, as is the case in $\\mathrm{Cs}_{2}\\mathrm{NaInCl}_{6}$ . This is because S also influences photoluminescence emission through the Franck–Condon factor, as described by equation (1). If we assume that the ground and excited states have similar phonon frequencies, the Franck–Condon factor ( $F,$ at zero temperature) can be simplified as \n\n$$\nF=|\\langle\\chi_{_n}\\mid\\chi_{_m}\\rangle|^{2}=\\frac{\\mathrm{e}^{-S}S^{n}}{n!}\n$$ \n\nThe photoluminescence peak appears at $n{\\approx}S$ , so \n\n$$\nF_{\\mathrm{max}}=\\frac{\\mathrm{e}^{-S}S^{S}}{S!}\n$$ \n\nwhich is a monotonically decreasing function of S. Because the photoluminescence intensity is positively correlated with S, the larger the $S_{;}$ , the smaller the radiative rate and the lower the emission efficiency. Thereby, the S value could potentially serve as the figure of merit for the design of efficient emission from STEs. The ideal value of the Huang–Rhys parameter should be intermediate for efficient STE emitters. \n\nMechanistic study of $\\mathbf{B_{i}^{3+}}$ doping. Extended Data Fig. 6 provides information about the effect of $\\mathrm{Bi}^{3+}$ incorporation on the PLQY improvement. For a Bi-doped $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ sample, the XRD measurement revealed smaller FWHM (from $0.058^{\\circ}$ to $0.034^{\\circ})$ of the diffraction patterns, and the optical measurement demonstrated diminished sub-bandgap absorption after $400\\mathrm{nm}$ and increased photolumines­ cence lifetime—from 2,971 ns $(70\\%)$ to 5,989 ns $(97\\%)$ . Because an $\\bar{\\mathrm{In}}^{3+}$ vacancy is a deep defect in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6},$ and isovalent doping helps to reduce vacancy defects in perovskite, we believe that Bi doping passivates defects and suppresses non-ra­ diative recombination loss. Additionally, the theoretical simulation indicated that Bi doping introduces a shallow state right above the valence-band maximum and forms nanoelectronic domains in the matrix that concentrate holes. The holes finally relax to Ag sites through $\\mathrm{Bi}6s/\\mathrm{Ag}4d$ orbital hybridization and lattice inter­ action, promoting exciton localization, just like I-doped AgBr for STE emission. Therefore, Bi doping improves crystal quality and promotes radiative recombina­ tion, enhancing the PLQY. \n\nCode availability. The customized codes required for STE calculation with cp2k and the Python script used to calculate the Franck–Condon factors and lumines­ cence spectrum are freely available at https://github.com/wxiaom86. \n\n# Data availability \n\nThe datasets analysed during the study are available from the corresponding authors upon request. \n\n31.\t Dai, X. et al. Solution-processed, high-performance light-emitting diodes based on quantum dots. Nature 515, 96–99 (2014). \n32.\t Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n33.\t Kresse, G. & Furthmüller, J. Efficiency of ab initio total energy calculations for metals and semiconductors using a plane wave basis set. Comput. Mater. Sci. 6, 15 (1996). \n34.\t Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n35.\t Perdew, J. P., Ernzerhof, M. & Burke, K. Rationale for mixing exact exchange with density functional approximations. J. Chem. Phys. 105, 9982–9985 (1996). \n36.\t Perdew, J., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n37.\t Klimeš, J., Kaltak, M. & Kresse, G. Predictive GW calculations using plane waves and pseudopotentials. Phys. Rev. B 90, 075125 (2014). \n38.\t Mostofi, A. A. et al. wannier90: a tool for obtaining maximally-localised Wannier functions. Comput. Phys. Commun. 178, 685–699 (2008). \n39.\t Cappellini, G. et al. Model dielectric function for semiconductors. Phys. Rev. B 47, 9892 (1993). \n40.\t Kowalczyk, T., Tsuchimochi, T., Chen, P. T., Top, L. & Van Voorhis, T. Excitation energies and Stokes shifts from a restricted open-shell Kohn–Sham approach. J. Chem. Phys. 138, 164101 (2013). \n41.\t Filatov, M. & Shaik, S. A spin-restricted ensemble-referenced Kohn–Sham method and its application to diradicaloid situations. Chem. Phys. Lett. 304, 429–437 (1999). \n42.\t Frank, I., Hutter, J., Marx, D. & Parrinello, M. Molecular dynamics in low-spin excited states. J. Chem. Phys. 108, 4060–4069 (1998). \n43.\t Hutter, J., Iannuzzi, M., Schiffmann, F. & Vandevondele, J. Cp2k: atomistic simulations of condensed matter systems. Wiley Interdiscip. Rev. Comput. Mol. Sci. 4, 15–25 (2014). \n44.\t VandeVondele, J. & Hutter, J. Gaussian basis sets for accurate calculations on molecular systems in gas and condensed phases. J. Chem. Phys. 127, 114105 (2007). \n45.\t Goedecker, S., Teter, M. & Hutter, J. Separable dual-space Gaussian pseudopotentials. Phys. Rev. B 54, 1703–1710 (1996). \n46.\t Perdew, J. P. & Zunger, A. Self-interaction correction to density-functional approximations for many-electron systems. Phys. Rev. B 23, 5048–5079 (1981). \n47.\t VandeVondele, J. & Sprik, M. A molecular dynamics study of the hydroxyl radical in solution applying self-interaction-corrected density functional methods. Phys. Chem. Chem. Phys. 7, 1363 (2005). \n48.\t d’Avezac, M., Calandra, M. & Mauri, F. Density functional theory description of hole-trapping in $\\mathsf{S i O}_{2}$ : a self-interaction-corrected approach. Phys. Rev. B 71, 205210 (2005). \n49.\t Alkauskas, A., Lyons, J. L., Steiauf, D. & Van De Walle, C. G. First-principles calculations of luminescence spectrum line shapes for defects in semiconductors: the example of GaN and $Z n0.$ . Phys. Rev. Lett. 109, 267401 (2012). \n50.\t Ruhoff, P. T. Recursion relations for multi-dimensional Franck–Condon overlap integrals. Chem. Phys. 186, 355–374 (1994). \n51.\t Stadler, W. et al. Optical investigations of defects in $\\mathtt{C d}_{1-x}Z\\mathsf{n}_{x}\\mathsf{T e}$ . Phys. Rev. B 51, 10619 (1995). \n52.\t Nandakumar, P. et al. Optical absorption and photoluminescence studies on CdS quantum dots in Nafion. J. Appl. Phys. 91, 1509–1514 (2002). \n53.\t Türck, V. et al. Effect of random field fluctuations on excitonic transitions of individual CdSe quantum dots. Phys. Rev. B 61, 9944 (2000). \n54.\t Zhao, H. et al. Energy-dependent Huang–Rhys factor of free excitons. Phys. Rev. B 68, 125309 (2003). \n55.\t Lao, X. et al. Luminescence and thermal behaviors of free and trapped excitons in cesium lead halide perovskite nanosheets. Nanoscale 10, 9949–9956 (2018). \n56.\t McCall, K. M. et al. Strong electron−phonon coupling and self-trapped excitons in the defect halide perovskites $\\mathsf{A}_{3}\\mathsf{M}_{2}\\mathsf{l}_{9}$ ( $\\mathtt{A=C s}$ , Rb; $\\mathsf{M}=\\mathsf{B i}$ , Sb). Chem. Mater. 29, 4129–4145 (2017). \n57.\t Leung, C. H. & Song, K. S. On the luminescence quenching of F centers in alkali halides. Solid State Commun. 33, 907 (1980). \n58.\t Mulazzi, E. & Terzi, N. Evaluation of the Huang–Rhys factor and the half-width of F-band in KCl and NaCl crystals. J. Phys. Colloq. 28, 49–54 (1967). \n59.\t Schulz, M. et al. Intensity dependent effects in silver chloride: bromine-bound exciton and biexciton states. Phys. Status Solidi B 177, 201–212 (1993). \n60.\t Andrews, L. J. et al. Thermal quenching of chromium photoluminescence in ordered perovskites. I. Temperature dependence of spectra and lifetimes. Phys. Rev. B 34, 2735 (1986). \n\n![](images/ecd8c0621f6f14326a32255d770f627a79e767863590c0554151aff334b66a37.jpg) \nExtended Data Fig. 1 | Phonon band structure of $\\mathbf{Cs_{2}A g I n C l_{6}}$ and the zone-centre Jahn–Teller phonon mode (inset). The phonon band structure was calculated by the finite-difference method with the supercell approach. The consistency of the displacement pattern of the phonon eigenvector with that of the lattice distortion during STE formation, as \nwell as the consistency of the phonon eigenfrequency with the phonon frequency fitted from the configuration coordinate diagram, confirm that the Jahn–Teller phonon mode coupled with the photoexcited excitons is responsible for the STE formation in $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . \n\n![](images/14365b49ec9454dee48c42f7b6ac29816c30e6e7f2565714d5c6385be6a7f10a.jpg) \nxtended Data Fig. 2 | Emission characterization of pure $\\mathbf{Cs}_{2}\\mathbf{AgInCl_{6}}$ . of temperature. We note that we used a relatively low-temperature , The broad photoluminescence (PL) spectrum of $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ measured region to avoid the influence of defect-assisted emission. d, The PLQY of at room temperature. b, Temperature-dependent photoluminescence $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . The reference was measured in an integrating sphere with a pectra of pure $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . c, Fitting results of the FWHM as a function blank quartz plate. \n\n![](images/34ee2fa47e012c640f150a272819abd10c03a7339bc9461ec74b4eb48069d30e.jpg) \nExtended Data Fig. 3 | Electronic and optical properties of $\\mathbf{Cs}_{2}\\mathbf{NaInCl}_{6}$ . a, GW-calculated band structure. The GW bandgap is $6.42\\mathrm{eV.}$ The lowest exciton, with a binding energy of $0.8\\mathrm{eV},$ is dark. The first bright exciton \nhas a binding energy of $0.44\\mathrm{eV.}$ b. Calculated optical absorption (‘Abstheory’) and photoluminescence (‘PL-theory’) spectra are compared with experimental results (‘Abs-exp.’ and ‘PL-exp.’). \n\n![](images/b7dd9c0d2d49d6d0446112971f7d9469d5889cbb60467c58b63540f4f0c0619b.jpg) \nExtended Data Fig. 4 | Alloy behaviour of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ . a, XRD patterns of $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ shifted to lower degrees with increasing sodium substitution (theta, diffraction angle). b, Refined lattice parameter, plotted as a function of the nominal $x$ in $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6},$ showing a linear increase with increased sodium substitution (see Supplementary \n\n![](images/e1c8a248fc0f067f6a77598bad3bdbac68e9ce9c061f3fcec975835a3730a230.jpg) \nFig. 3 for details of the characterization). We note that selected-area electron diffraction and scanning electron nanobeam diffraction analysis results (Supplementary Figs. 4, 5) suggest the existence of a microscopic super-lattice $\\mathrm{(Na/Ag}$ ordering). \n\n![](images/26fe8ab3f15dbd58d200c69fd717b690406234fa608e1a13107ae19086d39c5e.jpg) \nExtended Data Fig. 5 | Photoluminescence enhancement of doped double-perovskite powders. a, Photoluminescence spectra of pure $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ and Li-doped $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . b, Photoluminescence spectra of pure $\\mathrm{Cs}_{2}\\mathrm{Ag}\\mathrm{Sb}{\\mathrm{Cl}_{6}}$ and $\\mathrm{{Na}}$ -doped $\\mathrm{Cs}_{2}\\mathrm{Ag}\\mathrm{Sb}{\\mathrm{Cl}_{6}}$ . \n\n![](images/ccc9757cb17926daab28291960618fc89a409af6681f817c79cff87f413fd5ea.jpg) \nExtended Data Fig. 6 | Characterization of the effect of Bi doping on Bi-doped $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . The inset shows the band alignment of pure and $\\mathrm{Cs}_{2}\\mathrm{Ag}_{x}\\mathrm{Na}_{1-x}\\mathrm{InCl}_{6}$ . a, High-resolution single-crystal XRD of the (111) Bi-doped $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . CBM, conduction band minimum; VBM, valence peaks of $\\mathrm{Cs_{2}A g_{0.60}N a_{0.40}I n C l_{6}}$ with and without Bi doping. b, Absorption band maximum. The small shallow peak marked by an arrow is derived spectra of various materials with and without Bi doping for wavelengths from the Bi 6s states, which hybridize with the $\\mathrm{Ag4}d$ states. f, Partial of $500{-}950~\\mathrm{nm}$ . c, PLQY results. d, Photoluminescence lifetime. density of states (PDOS) of Bi-doped $\\mathrm{Cs}_{2}\\mathrm{AgInCl}_{6}$ . e, Comparison of the total density of states (DOS) between pure and \n\nExtended Data Table 1 | Huang–Rhys factors \n\n\n
CompoundsHuang-Rhys factor
CdSe531
ZnSe540.3
CsPbBr3553.2
Cs3Bi2lg5679.5
Cs3Sb2lg5642.7
Rb3Sb2lg5650.4
NaC[57,5842
AgCI:Br5922
Cs2NaYCl6607.0
Cs2NalnCl680(ES)/188(GS)*
Cs2AglnCl638.7
Cs2Ag0.60Nao.4olnCl640.9
CS2Ago.16Na0.84lnCl651.0
" + }, + { + "id": "10.1126_science.aav0652", + "DOI": "10.1126/science.aav0652", + "DOI Link": "http://dx.doi.org/10.1126/science.aav0652", + "Relative Dir Path": "mds/10.1126_science.aav0652", + "Article Title": "Magnetic hysteresis up to 80 kelvin in a dysprosium metallocene single-molecule magnet", + "Authors": "Guo, FS; Day, BM; Chen, YC; Tong, ML; Mansikkamäki, A; Layfield, RA", + "Source Title": "SCIENCE", + "Abstract": "Single-molecule magnets (SMMs) containing only one metal center may represent the lower size limit for molecule-based magnetic information storage materials. Their current drawback is that all SMMs require liquid-helium cooling to show magnetic memory effects. We now report a chemical strategy to access the dysprosium metallocene cation [(Cp-iPr5)Dy(Cp*)](+) (Cp-iPr5, penta-iso-propylcyclopentadienyl; Cp*, pentamethylcyclopentadienyl), which displays magnetic hysteresis above liquid-nitrogen temperatures. An effective energy barrier to reversal of the magnetization of U-eff = 1541 wave number is also measured. The magnetic blocking temperature of T-B = 80 kelvin for this cation overcomes an essential barrier toward the development of nullomagnet devices that function at practical temperatures.", + "Times Cited, WoS Core": 1491, + "Times Cited, All Databases": 1549, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000453845000058", + "Markdown": "# MOLECULAR MAGNETS \n\n# Magnetic hysteresis up to 80 kelvin in a dysprosium metallocene single-molecule magnet \n\nFu-Sheng Guo1, Benjamin M. Day1,2, Yan-Cong Chen3, Ming-Liang Tong3\\*, Akseli Mansikkamäki4\\*, Richard A. Layfield1\\* \n\nSingle-molecule magnets (SMMs) containing only one metal center may represent the lower size limit for molecule-based magnetic information storage materials. Their current drawback is that all SMMs require liquid-helium cooling to show magnetic memory effects. We now report a chemical strategy to access the dysprosium metallocene cation $[(\\mathsf{C p}^{i\\mathsf{P r5}})\\mathsf{D}\\mathsf{y}(\\mathsf{C p}^{\\ast})]^{+}$ $(\\mathsf{C p}^{i\\mathsf{P r}5}$ , penta-iso-propylcyclopentadienyl; $\\mathtt{C p}^{*}$ , pentamethylcyclopentadienyl), which displays magnetic hysteresis above liquid-nitrogen temperatures. An effective energy barrier to reversal of the magnetization of $U_{\\mathrm{eff}}=1541$ wave number is also measured. The magnetic blocking temperature of $T_{\\mathsf{B}}=80$ kelvin for this cation overcomes an essential barrier toward the development of nanomagnet devices that function at practical temperatures. \n\nT thieonoibnsecrovoartidoinatoifons coowmpmoaugndestitchraet caoxna- tain a single lanthanide ion stimulated considerable interest in monometallic singlemolecule magnets (SMMs) $(I)$ . This family of materials shows magnetic hysteresis properties that arise from the electronic structure at the molecular level rather than interactions across comparatively large magnetic domains (2–4). In addition to the considerable fundamental interest in SMMs and related magnetic molecules, their magnetic memory properties have inspired proposals for applications as spin qubits (5) and in nanoscale spintronic devices $\\textcircled{6}$ . A key performance parameter of an SMM is the magnetic blocking temperature, $T_{\\mathrm{B}},$ one description of which refers to the maximum temperature at which it is possible to observe hysteresis in the field dependence of the magnetization, subject to the field sweep rate. The blocking temperature provides a means of comparing different SMMs and, to date, the vast majority that show any hysteresis at all require liquid-helium cooling to do so (7, 8). A few notable examples have emerged from the extreme cold to set record blocking temperatures above the liquid-helium regime (9–12), including the dysprosium metallocene $[(\\mathrm{Cp}^{\\mathrm{ttt}})_{2}\\mathrm{Dy}][\\mathrm{B}(\\mathrm{C}_{6}\\mathrm{F}_{5})_{4}]$ $\\mathrm{(Cp^{ttt}}$ , 1,2,4-tri-tertbutylcyclopentadienyl), which showed magnetic hysteresis with coercivity up to $60\\mathrm{~K~}$ (13–15); however, this threshold still falls markedly short of the more practically accessible $77~\\mathrm{K}$ temperature at which nitrogen liquefies. We now show that by designing the ligand framework so that two key structural parameters— that is, the Dy- $\\mathbf{\\cdot}\\mathbf{Cp}_{\\mathrm{cent}}$ distances (cent refers to the centroid of the Cp ligand) and the Cp-Dy-Cp bending angle—are rendered short and wide, respectively, we achieve an axial crystal field of sufficient strength to furnish an SMM that shows hysteresis above $77\\mathrm{K}$ \n\nA dysprosium metallocene cation was targeted with cyclopentadienyl substituents of sufficient bulk to produce a wide Cp-Dy-Cp angle, but not too bulky to preclude close approach of the ligands. Thus, the borohydride precursor complex $[(\\boldsymbol{\\mathfrak{n}}^{5}{\\mathrm{-}}\\mathbf{C}\\boldsymbol{\\mathfrak{p}}^{i\\mathrm{Pr}5})\\mathbf{D}\\mathbf{y}(\\boldsymbol{\\mathfrak{n}}^{5}{\\mathrm{-}}\\mathbf{C}\\mathbf{p}^{*})(\\mathbf{B}\\mathbf{H}_{4})]$ (2) $(\\mathrm{Cp}^{i\\mathrm{Pr}5}$ , pentaiso-propylcyclopentadienyl; $\\mathrm{Cp^{*}}$ , pentamethylcyclopentadienyl) was synthesized by treating $\\mathrm{{[Dy(n^{5}-}}$ $\\mathrm{Cp}^{i\\mathrm{Pr}5})(\\mathrm{BH}_{4})_{2}(\\mathrm{THF})]$ (1) with $\\mathrm{KCp^{*}}$ (Fig. 1). The molecular structures of 1 and 2 were determined by x-ray crystallography (figs. S4 and S5 and tables S1 to S3). The target compound $[(\\mathsf{\\eta}^{5}-$ $\\mathrm{Cp^{*})D y(\\eta^{5}\\mathrm{-}C p^{i P r5})][B(C_{6}F_{5})_{4}]}$ (3), hereafter abbreviated $[\\mathrm{Dy}{-}5^{{\\ast}}][\\mathrm{B}(\\mathrm{C}_{6}\\mathrm{F}_{5})_{4}]$ , was then isolated in $60\\%$ yield by treating 2 with the superelectrophile $[(\\mathrm{Et_{3}S i})_{2}(\\upmu\\mathrm{-H}][\\mathrm{B}(\\mathrm{C}_{6}\\mathrm{F}_{5})_{4}]$ (Et, ethyl) (16). An x-ray crystallographic analysis of the molecular structure of 3 at 150 K (Fig. 1, figs. S6 and S7, and tables S1 and S4) revealed that the $\\mathrm{Dy}{-}5^{*}$ cation features Dy- $\\mathrm{{Cp^{*}}}$ and $\\mathrm{Dy-Cp}^{i\\mathrm{Pr}5}$ distances of 2.296(1) and $2.284(1)\\mathrm{\\AA},$ respectively, which are, on average, 0.026 Å shorter than the analogous distances of 2.32380(8) and 2.30923(8) Å determined for $\\mathrm{[(Cp^{tt})_{2}D y]^{+}}$ (13). Furthermore, the $\\mathrm{Cp\\mathrm{-}}$ 一 Dy-Cp angle in ${\\mathrm{Dy}}{-}5^{*}$ is $162.507(1)^{\\circ}$ and hence almost $9.7^{\\circ}$ wider than the angle of $152.845(2)^{\\circ}$ found in $\\mathrm{{[(Cp^{tt})_{2}D y]}^{+}}$ . On the basis of these structural parameters, the crystal field in Dy- ${\\cdot}5^{*}$ should be stronger and more axial than in $\\mathrm{[(Cp^{tt})_{2}D y]^{+}}$ , and hence, an improvement in the SMM properties can be expected. \n\nThe dc molar magnetic susceptibility $(\\chi_{\\mathrm{M}})$ was measured for compounds 1 to 3 in the temperature range of 2 to $300\\mathrm{K}$ using an applied field of 1000 Oe, and the field dependence of the magnetization for 1 and 2 was measured at $T=$ 2 and $5\\mathrm{K}$ using fields up to $70\\mathrm{kOe}$ (figs. S8 to S12). A description of the properties of 1 and 2 is provided in the supplementary materials. For 3, the $\\chi_{\\mathrm{M}}T$ value was measured to be $13.75\\mathrm{cm}^{3}\\mathrm{K}$ $\\mathrm{mol}^{-1}$ at $300\\mathrm{~K~}$ and then manifested a steady decrease down to $75\\mathrm{K}.$ At lower temperatures, a sharp drop in $\\chi_{\\mathrm{M}}T$ was observed, indicating the onset of magnetic blocking, with a value of $0.94\\mathrm{cm}^{3}\\mathrm{Kmol}^{-1}$ reached at $2\\mathrm{K}$ . Overall, the dc magnetic properties of compounds 1 to 3 are typical for a monometallic complex of $\\mathrm{Dy}^{3+}$ with a $^6\\mathrm{H}_{15/2}$ ground multiplet $(I7)$ . The SMM properties of compounds 1 to 3 were then established through measurements of the in-phase (the real component, $\\chi^{\\prime}$ ) and the out-of-phase (the imaginary component, $\\chi^{\\prime\\prime})$ ac susceptibilities as functions of the ac frequency $(\\upnu)$ and temperature, using an oscillating field of 5 Oe and zero applied dc field (figs. S13 to S28 and tables S5 to S7). Focusing again on 3, the $\\chi^{\\prime\\prime}(\\mathbf{v})$ isotherms show well-defined maxima up to $130\\mathrm{K}$ (Fig. 2). The $\\chi^{\\prime}(\\upnu)$ and $\\chi^{\\prime\\prime}(\\upnu)$ data were then used to derive Cole-Cole plots of $\\chi^{\\prime\\prime}(\\chi^{\\prime})$ for relaxation in the temperature range of 82 to 138 K in intervals of $2\\mathrm{K},$ with each plot adopting a parabolic shape (figs. S26 to S28). Accurate fits of the ac susceptibility plots were obtained using equations describing $\\chi^{\\prime}$ and $\\chi^{\\prime\\prime}$ in terms of frequency, the isothermal susceptibility $(\\chi_{T})$ , adiabatic susceptibility $(\\chi_{S})$ , the relaxation time $\\mathbf{\\eta}(\\uptau).$ , and the fitting parameter $\\mathbf{\\alpha}_{\\mathrm{~\\mathfrak~{~a~}~}}$ to represent the distribution of relaxation times (eqs. S1 and S2) (18). \n\nThe resulting values of $\\mathbf{\\boldsymbol{a}}=\\mathbf{\\boldsymbol{0}}$ to 0.027 indicate a very narrow range of relaxation times in the high-temperature regime. The relaxation times at temperatures in the range of 2 to $83\\mathrm{~K~}$ were determined in intervals of about $5\\mathrm{K}$ from plots of the magnetization decay versus time (figs. S29 to S48 and table S8). These data show, for example, that the magnetization in 3 decays almost to zero over a 50-s time period at $77~\\mathrm{K},$ increasing to about 500 min at $15\\ \\mathrm{K}$ The temperature at which $\\tau=100$ s is $65\\mathrm{K}$ The relaxation times determined from the ac and dc measurements were then combined to obtain further insight into the magnetic relaxation by plotting $\\boldsymbol{\\tau}$ as a function of $T^{1}$ (Fig. 2), which revealed a strong, linear dependence of the relaxation time on temperature in the range of 55 to $138\\mathrm{K}$ The $\\tau(T^{1})$ plot in the range of 10 to $55\\mathrm{K}$ is curved in nature and represents an intermediate regime before purely temperature-independent relaxation is observed below $10~\\mathrm{K}.$ The relaxation time can be expressed as $\\tau^{-1}=~\\tau_{0}^{-1}\\mathrm{e}^{-U_{\\mathrm{eff}}/k_{\\mathrm{B}}T}+$ ${C T}^{n}+\\uptau_{\\mathrm{QTM}}^{-1},$ , in which the first term represents Orbach relaxation with $U_{\\mathrm{eff}}$ as the effective energy barrier to relaxation of the magnetization $\\mathbf{\\mathit{k}_{B}}$ , Boltzmann constant), the second term represents the contribution from Raman processes ( $\\cdot c,$ the Raman coefficient; $n$ , the Raman exponent), and the third term represents the rate of quantum tunneling of the magnetization (QTM). Using this equation, an excellent fit [adjusted coefficient of determination $(R^{2})=0.99958]$ of the data was obtained with $\\tau_{0}=4.2(6)\\times10^{-12}\\ s$ s; $U_{\\mathrm{eff}}=1541\\mathrm{(11)cm^{-1}}$ ; $C=3.1$ $\\mathrm{(1)}\\times\\mathrm{10^{-8}}\\mathrm{s^{-1}}\\mathrm{K^{-n}}$ and $n=3.0(1)$ ; and $\\tau_{\\mathrm{QTM}}=2.5$ $\\left(2\\right)\\times\\left10^{4}$ s. The $U_{\\mathrm{eff}}$ value determined for 3 exceeds the value of 1277 $\\mathrm{cm}^{-1}$ determined for $[(\\mathrm{Cp}^{\\mathrm{ttt}})_{2}\\mathrm{Dy}][\\mathrm{B}(\\mathrm{C}_{6}\\mathrm{F}_{5})_{4}]$ by about $20\\%$ $(\\boldsymbol{I3})$ . \n\n![](images/7b94f0ee98eddb5128cda179fe6ed032085d6c696123404320ceb71142b8bcb0.jpg) \nFig. 1. Synthesis and molecular structures. (A) Reaction scheme for the synthesis of 3. (B) Thermal ellipsoid representation $50\\%$ probability) of the molecular structure of the Dy- $5^{*}$ cation in 3, as determined by x-ray crystallography {for clarity, the hydrogen atoms and $[\\mathsf{B}(\\mathsf{C}_{6}\\mathsf{F}_{5})_{4}]^{-}$ counter anion are omitted}. \n\nPotential applications of SMMs in information storage devices rely on the occurrence of magnetic remanence and coercivity; therefore, the hysteresis is a critical consideration (19). For 3, using a relatively fast field sweep rate of $200\\mathrm{Oe}\\ s^{-1}$ revealed $M(H)$ hysteresis from 2 up to $85\\mathrm{~K~}$ , with the loops gradually closing as the temperature increased (Fig. 3, A and B). At these temperature limits, coercive fields $(H_{\\mathrm{c}})$ of $50\\mathrm{kOe}$ and 210 Oe $_{5.0\\mathrm{T}}$ and $21\\mathrm{mT},$ ), respectively, were measured (Fig. 3C, fig. S49, and table S9). Fixing the temperature at $77\\mathrm{K},$ a reduction in the sweep rate resulted in the coercive field approximately halving with the rate, that is, $H_{\\mathrm{c}}=5802$ Oe at $700\\ \\mathrm{Oe}\\ \\mathrm{s}^{-1}$ , 2946 Oe at $350\\mathrm{Oe}\\mathrm{s}^{-1}$ , 1688 Oe at $200\\mathrm{Oe}\\ s^{-1}$ , 825 Oe at $100\\mathrm{Oe}\\ s^{-1}$ , 398 Oe at $50\\mathrm{Oe}\\ s^{-1}$ , and 191 Oe at 25 Oe $\\mathbf{s}^{-1}$ (fig. S50 and table S10). The observation of coercivity in 3 at 25 Oe $\\mathbf{s}^{-1}$ is notable because this sweep rate is slower than the $39\\mathrm{Oe}\\mathrm{s}^{-1}$ used to determine the blocking temperature of $60\\mathrm{K}$ for $[(\\mathrm{Cp}^{\\mathrm{ttt}})_{2}\\mathrm{Dy}][\\mathrm{B}(\\mathrm{C}_{6}\\mathrm{F}_{5})_{4}]$ (13). At $80~\\mathrm{K}$ and $25\\mathrm{Oe\\s^{-1}}$ , a coercive field of $63\\mathrm{Oe}$ was measured (Fig. 3D), and the loops were completely closed at higher temperatures. Consistent with this finding, the field-cooled and zero-fieldcooled magnetic susceptibilities for 3 diverged at $^{78\\mathrm{~K~}}$ (fig. S51). By analogy with the development of high-temperature (high- $\\cdot T_{\\mathrm{C}})$ superconductors, we propose to designate the Dy- $.5^{\\ast}$ cation in 3 as a high-temperature, or high- $\\cdot T_{\\mathrm{B}},$ SMM. \n\nThe importance of the strong axial crystal field in the Dy- $.5^{*}$ cation combined with the absence of an equatorial field is illustrated further by comparing the $U_{\\mathrm{eff}}$ and $T_{\\mathrm{B}}$ values for 3 with those of the precursors 1 and 2. In the case of 1, the $\\mathrm{Cp}^{i\\mathrm{Pr}5}$ ligand provides a strong axial field, but the pseudo-octahedral coordination geometry introduces a non-negligible equatorial field and, although slow magnetic relaxation in zero field is observed with this system, the positions of the maxima in $\\chi^{\\prime\\prime}(\\upnu)$ are temperature-independent up to $10\\mathrm{K}$ and only observed up to $30\\mathrm{K}$ (figs. S13 to S16). The resulting energy barrier of $241(7)\\mathrm{cm}^{-1}$ is comparatively small, and the rate of QTM is, at $5.0(1)\\times10^{-3}$ s (fig. S17), some seven orders of magnitude faster than found with 3. The competing equatorial field in 2 is more prominent, because the maxima in $\\chi^{\\prime\\prime}(\\upnu)$ are very weakly temperature-dependent from 3 to $20~\\mathrm{K},$ with the resulting energy barrier a negligible $7(1)\\mathrm{cm}^{-1}$ (figs. S19 to S22). In both 1 and 2, the $M(H)$ hysteresis loops collected at $2\\mathrm{~K~}$ and $200\\mathrm{Oe}\\ s^{-1}$ are waist-restricted, with no coercivity and only small openings as the field magnitude increases (figs. S18 and S23). \n\n![](images/13733d54af6e3d888278260ff570965b55193e858f1e219a30d820a04239f774.jpg) \nFig. 2. Dynamic magnetic properties. (A) Frequency dependence of the out-of-phase $\\chi^{\\prime\\prime}{}_{\\sf M}$ molar magnetic susceptibility for 3, collected in zero dc field at ac frequencies of $\\upnu=0.1$ to 1488 $H z$ from $82\\mathsf{K}$ (green trace) to $138\\mathsf{K}$ (purple trace) in $2\\mathsf{K}$ intervals. Solid lines represent fits to the data using eqs. S1 and S2, with adjusted $R^{2}=0.99823$ to 0.99988. (B) Temperature dependence of the relaxation time for 3. The red points are from the ac susceptibility data, and the blue points are from measurements of the dc magnetic relaxation time. The solid green line is the best fit to $\\tau^{-1}=\\ \\tau_{0}^{-1}\\mathrm{e}^{-U_{\\mathrm{eff}}/k_{\\mathrm{B}}T}+C T^{n}+\\tau_{\\mathrm{Q7M}}^{-1}$ , using the parameters stated in the text. \n\nAb initio calculations have enabled quantitative analysis of the properties of SMMs on a microscopic scale (20), particularly systems with $\\boldsymbol{\\mathfrak{\\upeta}}^{n}$ -bonded organometallic ligands (21–30). Calculations on the $\\mathrm{Dy}{-}5^{\\ast}$ cation were performed at the XMS-CASPT2//SA-CASSCF/RASSI level (31, 32): The resulting energies, principal components of the $\\pmb{g}$ -tensors, and the principal magnetic axes of the eight lowest Kramers’ doublets in Dy- ${\\boldsymbol{\\cdot}}{\\boldsymbol{5}}^{*}$ corresponding to the crystal-field (CF) states of the $^6\\mathrm{H}_{15/2}$ ground multiplet are listed in table S11. The principal magnetic axis in the ground doublet of Dy- $.5^{*}$ (Fig. 4) is projected toward the centroids of the two cyclopentadienyl ligands, with the principal axes of the next six doublets almost collinear and the largest deviation angle $5.3^{\\circ}$ with the fifth doublet. The highest doublet is perpendicular to the ground doublet. \n\nThe $\\pmb{g}$ -tensor of the ground doublet is calculated to be perfectly axial, that is, $g_{x}=g_{y}=0.000$ and $g_{z}=20.000$ (table S11), which is consistent with the experimental hysteresis measurements in which QTM is completely blocked at zero field. In the six lowest doublets, the CF is highly axial, and each state can be assigned to a definite projection (greater than $96\\%$ character) of the total angular momentum, $M_{J}$ (table S12). The transverse components of the $\\pmb{g}$ -tensors increase roughly by an order of magnitude in each doublet upon moving to higher energy. In the fifth doublet, the transverse components are non-negligible, and in the sixth doublet, the transverse components are large enough to allow considerable tunneling. In the two highest states, the axiality is weaker and considerable mixing occurs under the CF, which most likely results from the asymmetry of the coordination environment. \n\nThe ab initio CF parameters were calculated for the Dy- ${\\boldsymbol{\\cdot}}{\\boldsymbol{5}}^{*}$ cation following a previously established methodology (33, 34) and are listed in table S13. The off-diagonal elements of the CF operator clearly have non-negligible elements owing to the low $C_{1}$ point symmetry of Dy- ${\\boldsymbol{\\cdot}}{\\boldsymbol{5}}^{*}$ ; however, the axial second-rank parameter $B_{2}^{0}$ is at least two orders of magnitude larger than any other parameter. This creates a highly axial CF environment despite the absence of point symmetry (or pseudosymmetry) that would be needed for a strictly axial CF. The off-diagonal elements of the CF play some role, and, in the higher-lying doublets of the ground multiplet, the axial nature of the CF is lost (vide infra). This demonstrates that strict point symmetry is not required to achieve a highly axial CF, provided that the axial parameters are sufficiently strong in comparison to the other CF parameters arising from the low-symmetry components of the CF. \n\n![](images/598e3327b5e3837c0c90fab6cf2a72959f0a256e12553a21808c7d0fc5ad72ae.jpg) \nFig. 3. Magnetic hysteresis properties of 3. (A and B) Magnetization versus field hysteresis loops in the temperature ranges of 2 to $75\\mathsf{K}$ (A) and 75 to $85\\mathsf{K}$ (B) using a field sweep rate of $200\\mathsf{O e}\\mathsf{s}^{-1}$ . (C) Expansion of the hysteresis loops at $77\\upkappa$ showing the coercive fields. (D) Hysteresis loops at $80~\\mathsf{K}$ using a field sweep rate of 25 Oe $\\mathsf{s}^{-1}$ . \n\n![](images/7c8b0b5616ceba641bffc40d987b2c18af27097300102428b5b356f16bac37f0.jpg) \nFig. 4. Magnetic relaxation in the Dy- $5^{\\ast}$ cation. (A) The principal magnetic axis of the ground Kramers’ doublet. (B) Relaxation mechanism for Dy- $.5^{*}$ . Blue arrows show the most probable relaxation route, and red arrows show transitions between states with less probable, but nonnegligible, matrix elements; darker shading indicates a higher probability. \n\nThe magnetic relaxation in the Dy- ${\\boldsymbol{\\cdot}}{\\boldsymbol{5}}^{*}$ cation was studied further by constructing a qualitative relaxation barrier from the ab initio results, which follows a methodology in which the transition magnetic moment between the different states was calculated and the relaxation pathway follows the largest matrix elements (Fig. 4B and table S14) (35). The results predict that the barrier is crossed at the fourth excited doublet, corresponding to a $U_{\\mathrm{eff}}$ value of $1524~\\mathrm{{cm}^{-1}}$ for the Orbach process, which is consistent with the calculated $\\pmb{g}\\mathrm{.}$ -tensors for this doublet and is in excellent agreement with the experimentally determined barrier height of $\\mathrm{1541(11)cm^{-1}}$ . To gain deeper insight into the nature of the spin-phonon relaxation, the first-order spin-phonon couplings with the optical phonons (approximated as the molecular vibrations) were evaluated from firstprinciples calculations (tables S15 to S18). In earlier work on $[(\\mathrm{Cp}^{\\mathrm{tt}})_{2}\\mathrm{Dy}]^{+}(I4)_{;}$ , vibrations of the C–H oscillators in the $\\mathrm{Cp}$ rings were recognized as the most important contribution to the Orbach relaxation, because they initiated the transition from the ground doublet to the first excited doublet. In the case of Dy- ${\\boldsymbol{\\cdot}}{\\boldsymbol{5}}^{*}$ , these oscillators are absent, and the analogous transition from the ground to the first excited doublet is most likely initiated by out-of-plane vibrations of the $\\mathrm{Cp^{*}}$ ligand when comparing the frequency of these modes (632.9 and $640.5\\mathrm{cm}^{-1}.$ ) to the calculated gap between the ground and first excited doublets $(672~\\mathrm{{cm}^{-1}},$ ) (see movies S1 to S7). Because the out-of-plane vibrations couple strongly to vibrations of the $\\mathrm{Cp^{*}}$ methyl groups, it is conceivable that their energies can be tuned by choosing ligand substituents that would bring the vibrational modes out of resonance with the excitation gap. Such an approach should lead to further improvements in SMM performance beyond those of the Dy- ${\\boldsymbol{\\cdot}}{\\boldsymbol{5}}^{*}$ cation and therefore enhance their potential for applications in magnetic information storage materials. \n\nNote added in proof: A study describing the properties of related cationic dysprosium metallocenes was recently published by Long, Harvey, and others (36). \n\nREFERENCES AND NOTES \n1. N. Ishikawa, M. Sugita, T. Ishikawa, S. Y. Koshihara, Y. Kaizu, J. Am. Chem. Soc. 125, 8694–8695 (2003). \n2. B. M. Day, F.-S. Guo, R. A. Layfield, Acc. Chem. Res. 51, 1880–1889 (2018). \n3. J.-L. Liu, Y.-C. Chen, M.-L. Tong, Chem. Soc. Rev. 47, 2431–2453 (2018). \n4. J. M. Frost, K. L. M. Harriman, M. Murugesu, Chem. Sci. 7, 2470–2491 (2016). \n5. M. Shiddiq et al., Nature 531, 348–351 (2016). \n6. S. Thiele et al., Science 344, 1135–1138 (2014). \n7. D. N. Woodruff, R. E. P. Winpenny, R. A. Layfield, Chem. Rev. 113, 5110–5148 (2013). \n8. P. Zhang, L. Zhang, J. Tang, Dalton Trans. 44, 3923–3929 (2015). \n9. J. D. Rinehart, M. Fang, W. J. Evans, J. R. Long, J. Am. Chem. Soc. 133, 14236–14239 (2011). \n10. Y.-C. Chen et al., J. Am. Chem. Soc. 138, 2829–2837 (2016). \n11. S. K. Gupta, T. Rajeshkumar, G. Rajaraman, R. Murugavel, Chem. Sci. 7, 5181–5191 (2016). \n12. F. Liu et al., Nat. Commun. 8, 16098 (2017). \n13. F.-S. Guo et al., Angew. Chem. Int. Ed. 56, 11445–11449 (2017). \n14. C. A. P. Goodwin, F. Ortu, D. Reta, N. F. Chilton, D. P. Mills, Nature 548, 439–442 (2017). \n15. C. A. P. Goodwin, D. Reta, F. Ortu, N. F. Chilton, D. P. Mills, J. Am. Chem. Soc. 139, 18714–18724 (2017). \n16. S. J. Connelly, W. Kaminsky, D. M. Heinekey, Organometallics 32, 7478–7481 (2013). \n17. C. Benelli, D. Gatteschi, Introduction to Molecular Magnetism: From Transition Metals to Lanthanides (Wiley-VCH, 2015). \n18. Y.-N. Guo, G.-F. Xu, Y. Guo, J. Tang, Dalton Trans. 40, 9953–9963 (2011). \n19. S. Demir, M. I. Gonzalez, L. E. Darago, W. J. Evans, J. R. Long, Nat. Commun. 8, 2144 (2017). \n20. L. Ungur, L. F. Chibotaru, Inorg. Chem. 55, 10043–10056 (2016). \n21. L. Ungur, J. J. Le Roy, I. Korobkov, M. Murugesu, L. F. Chibotaru, Angew. Chem. Int. Ed. 53, 4413–4417 (2014). \n22. J. J. Le Roy, L. Ungur, I. Korobkov, L. F. Chibotaru, M. Murugesu, J. Am. Chem. Soc. 136, 8003–8010 (2014). \n23. J. J. Le Roy et al., J. Am. Chem. Soc. 135, 3502–3510 (2013). \n24. K. L. M. Harriman et al., Chem. Sci. 8, 231–240 (2017). \n25. T. P. Latendresse, N. S. Bhuvanesh, M. Nippe, J. Am. Chem. Soc. 139, 14877–14880 (2017). \n26. T. Pugh, N. F. Chilton, R. A. Layfield, Angew. Chem. Int. Ed. 55, 11082–11085 (2016). \n27. T. Pugh et al., Nat. Commun. 6, 7492 (2015). \n28. T. Pugh, V. Vieru, L. F. Chibotaru, R. A. Layfield, Chem. Sci. 7, 2128–2137 (2016). \n29. T. Pugh, N. F. Chilton, R. A. Layfield, Chem. Sci. 8, 2073–2080 (2017). \n30. A. F. R. Kilpatrick et al., Chem. Commun. (Camb.) 54, 7085–7088 (2018). \n31. L. Ungur, L. F. Chibotaru, Computational Modelling of Magnetic Properties of Lanthanide Compounds in Lanthanide and Actinides in Molecular Magnetism, R. A. Layfield, M. Murugesu, Eds. (Wiley-VCH, 2015). \n32. T. Shiozaki, W. Gyõrffy, P. Celani, H.-J. Werner, J. Chem. Phys 135, 081106 (2011). \n33. L. Ungur, L. F. Chibotaru, Chemistry 23, 3708–3718 (2017). \n34. L. F. Chibotaru, in Ab Initio Methodology for Pseudospin Hamiltonians of Anisotropic Magnetic Complexes, S. A. Rice, A. R. Dinner, Eds. (Advances in Chemical Physics Series, Wiley, 2013), vol. 153, pp. 397–519. \n35. L. Ungur, M. Thewissen, J.-P. Costes, W. Wernsdorfer, L. F. Chibotaru, Inorg. Chem. 52, 6328–6337 (2013). \n36. K. R. McClain et al., Chem. Sci. (Camb.) 9, 8492–8503 (2018). \n\n# ACKNOWLEDGMENTS \n\nThe authors thank the CSC-IT Center for Science in Finland, the Finnish Grid and Cloud Infrastructure (persistent identifier \n\nurn:nbn:fi:research-infras-2016072533), and H. M. Tuononen (University of Jyväskylä) for providing computational resources. Funding: The authors thank the European Research Council (CoG grant 646740), the EPSRC (EP/M022064/1), the NSF China (projects 21620102002 and 91422302), the National Key Research and Development Program of China (2018YFA0306001), and the Academy of Finland (projects 282499 and 289172). Author contributions: R.A.L. conceived the original idea and formulated the research aims. Synthetic and crystallographic work was carried out by F.-S.G. and B.M.D. Magnetic measurements were conducted by Y.-C.C. and M.-L.T. The theoretical analysis was carried out by A.M. All authors analyzed the data. R.A.L. wrote the manuscript, with contributions from all authors. Competing interests: The authors declare no competing interests. Data and materials availability: Metrical data for the solid-state structures of 1 to 3 are available free of charge from the Cambridge Crystallographic \n\nData Centre under reference numbers CCDC 1854466 to 1854468. All other data are in the main text or supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/362/6421/1400/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S51 \nTables S1 to S18 \nReferences (37–77) \nMovies S1 to S7 \nData S1 to S3 \n\n13 August 2018; accepted 9 October 2018 \nPublished online 18 October 2018 \n10.1126/science.aav0652 \n\n# Science \n\n# Magnetic hysteresis up to 80 kelvin in a dysprosium metallocene single-molecule magnet \n\nFu-Sheng Guo, Benjamin M. Day, Yan-Cong Chen, Ming-Liang Tong, Akseli Mansikkamäki and Richard A. Layfield \n\nScience 362 (6421), 1400-1403. DOI: 10.1126/science.aav0652originally published online October 18, 2018 \n\n# Breaking through the nitrogen ceiling \n\nSingle-molecule magnets could prove useful in miniaturizing a wide variety of devices. However, their application has been severely hindered by the need to cool them to extremely low temperature using liquid helium. Guo et al. now report a dysprosium compound that manifests magnetic hysteresis at temperatures up to 80 kelvin. The principles applied to tuning the ligands in this complex could point the way toward future architectures with even higher temperature performance. \n\nScience, this issue p. 1400 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41467-017-02685-9", + "DOI": "10.1038/s41467-017-02685-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-017-02685-9", + "Relative Dir Path": "mds/10.1038_s41467-017-02685-9", + "Article Title": "Skin-inspired highly stretchable and conformable matrix networks for multifunctional sensing", + "Authors": "Hua, QL; Sun, JL; Liu, HT; Bao, RR; Yu, RM; Zhai, JY; Pan, CF; Wang, ZL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Mechanosensation electronics (or Electronic skin, e-skin) consists of mechanically flexible and stretchable sensor networks that can detect and quantify various stimuli to mimic the human somatosensory system, with the sensations of touch, heat/cold, and pain in skin through various sensory receptors and neural pathways. Here we present a skin-inspired highly stretchable and conformable matrix network (SCMN) that successfully expands the e-skin sensing functionality including but not limited to temperature, in-plane strain, humidity, light, magnetic field, pressure, and proximity. The actualized specific expandable sensor units integrated on a structured polyimide network, potentially in three-dimensional (3D) integration scheme, can also fulfill simultaneous multi-stimulus sensing and achieve an adjustable sensing range and large-area expandability. We further construct a personalized intelligent prosthesis and demonstrate its use in real-time spatial pressure mapping and temperature estimation. Looking forward, this SCMN has broader applications in humanoid robotics, new prosthetics, human-machine interfaces, and health-monitoring technologies.", + "Times Cited, WoS Core": 1204, + "Times Cited, All Databases": 1273, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000422649500006", + "Markdown": "# Skin-inspired highly stretchable and conformable matrix networks for multifunctional sensing \n\nQilin Hua1,2,3, Junlu Sun1, Haitao Liu1, Rongrong Bao1,2, Ruomeng $\\mathsf{Y u}^{4}$ Junyi Zhai 1,2, Caofeng Pan 1,2 & Zhong Lin Wang1,2,4 \n\nMechanosensation electronics (or Electronic skin, e-skin) consists of mechanically flexible and stretchable sensor networks that can detect and quantify various stimuli to mimic the human somatosensory system, with the sensations of touch, heat/cold, and pain in skin through various sensory receptors and neural pathways. Here we present a skin-inspired highly stretchable and conformable matrix network (SCMN) that successfully expands the e-skin sensing functionality including but not limited to temperature, in-plane strain, humidity, light, magnetic field, pressure, and proximity. The actualized specific expandable sensor units integrated on a structured polyimide network, potentially in three-dimensional (3D) integration scheme, can also fulfill simultaneous multi-stimulus sensing and achieve an adjustable sensing range and large-area expandability. We further construct a personalized intelligent prosthesis and demonstrate its use in real-time spatial pressure mapping and temperature estimation. Looking forward, this SCMN has broader applications in humanoid robotics, new prosthetics, human–machine interfaces, and health-monitoring technologies. \n\nTthe hcuomnavne soemnavtiorsoenmsoerny slystiemuli na ocoelmecptlreixc lnietmwpourlkthermoreceptors, nociceptors, etc.) and transmits these signals via neural pathways, enabling the sensations of touch, heat/cold, and punching invasion. Consisting of mechanically flexible and stretchable sensor networks, mechanosensation electronics (electronic skin, $\\mathrm{e}{\\mathrm{-}}s\\mathrm{kin})^{1-6}$ has been developed to mimic the human somatosensory system by detecting and quantifying various stimuli in the ambient environment and have attracted tremendous attention for their revolutionary applications in robotics7,8, prosthetics4,9,10, and health-monitoring technologies3,11,12. E-skin, which is capable of sensing different stimuli, is likely to boost emergence of the Internet of ‘actions’ (IoA), as we suppose, which would be a new era of health care, medical science, and robotics. The IoA would ascribe a world where billions of objects tightly integrated with sensors, processors, and actuators to sense stimuli and do actions interactively and adaptively; could naturally allow people to interact and communicate with the surroundings, including physical objects and external stimuli; and do some actions in response after computations13. \n\nMechanosensation electronics is supposed to be the core part of IoA2,11,14–16, and multi-functionalities are of essential importance in developing smart and interactive flexible/stretchable electronics2,15–17. Indeed, the ability to sense multiple stimuli is an ultimate goal for e-skin systems3–5. However, previous reports have mainly focused on single or dual sensory capabilities. Many emerging sensors, including pressure18–21, strain22–28, and temperature29,30, are underway to achieve excellent performance. Strain and temperature sensing were demonstrated by whisker arrays22 and thin film sensors31. Pressure sensing coupled with temperature (e.g., nanocomposites32, organic transistors33, thermoelectric34, or ferroelectric35 materials), strain (e.g., carbon nanotubes36, gold thin films26, or liquid conductors37 in silicone rubber, interlocked micro/nanostructures25,38,39, elastomer-based integrated tactile sensors10, energy-harvesting $\\mathtt{e-s k i n}^{40}$ ), or proximity41,42 were also illustrated. Epidermal electronics11,43, piezoelectric sensors44 , and micro-hairy sensors12 showed cutaneous and physiological monitoring. Si-nanoribbon strain, pressure, and temperature sensor arrays associated with humidity sensors and heaters were reported in a prosthetic $s\\mathrm{kin}^{9}$ , but it did not show evidence of the sensory inputs recorded simultaneously. Surely, highly sensitive detections for different stimuli are not easy to implement due to decoupling interference of multiple signal34. Thus a simultaneous detection and high selectivity of multi-complex stimuli from the ambient environment remains a challenge, which puts high demands on a high-density sensor array4. Additionally, mechanoreceptor density varies widely for different areas of skin for a human, such as between fingertips $(241\\mathrm{cm}^{-2})$ and palms $(58\\thinspace{\\mathrm{cm}}^{-2})^{45}$ . However, few reported e-skins achieved adjustable sensing range and area expansion46–48 in analogy of mechanoreceptors of the human skin. \n\nHere we present a skin-inspired highly stretchable and conformable matrix network (SCMN) as a multi-sensory e-skin that is capable of detecting temperature, in-plane strain, relative humidity (RH), ultraviolet (UV) light, magnetic field, pressure, and proximity provides to realize simultaneous multi-stimulus sensing and exhibits an adjustable sensing range and large-area expandability, as well as potentially suitable for high-density three-dimensional (3D) integration scheme. More impressively, we likewise construct a personalized intelligent prosthetic hand for touch/temperature sensing that not only contour pressure distribution on fingers but also estimate temperatures of grasping objects simultaneously. This is a milestone using mechanosensation electronics toward IoA. \n\n# Results \n\nSkin-inspired SCMN for multifunctional sensing. Figure 1a schematically illustrates the human somatosensory system in the skin, which consists of neural networks that receive and transmit touch, heat/cold, and pain signals from the external environment. Moreover, various mechanoreceptors and thermoreceptors distributed in the epidermal and dermal layers enable the spatiotemporal recognition of the magnitude and location of touch and temperature stimuli49. As inspired by the human skin with this complex somatosensory system, we designed and fabricated a SCMN composed of 100 sensory nodes connected by meandering wires to achieve multifunctional sensing performance using stretchable and expandable structures (Fig. 1b), with corresponding tilted SEM images shown in Fig. 1c and its inset, respectively. The multilayered design layout and the corresponding fabrication process presented in Fig. 1d and Supplementary Fig. 1, respectively, show that six different types of sensor units are responsible for the different categories of sensing performance. Such design makes the device capable of detecting temperature, RH, UV light, magnetic field, in-plane strain, and pressure/proximity stimuli from the environment simultaneously. Furthermore, the SCMN shows a very good flexibility and stretchability due to the application of meandering interconnects, which are demonstrated in Fig. 1e. \n\nSCMN stretchability and expandability. The meandering interconnects are critical for allowing the stable and uniform expansion of the network to several orders of magnitude larger than the original area and for the positioning of the nodes in predefined locations. \n\nThe stretching test is performed on a one-dimensional meandering interconnect, utilizing a customized stretch-testing platform (inset of Fig. 2a), and a detailed stretching procedure of a meandering wire can also be seen in Supplementary Movie 1. When the meandering wires are stretched from their original length $\\left(L/L_{0}=1\\right)$ to $800\\%$ expansion $\\left(L/L_{0}=8\\right)$ , the extension of the wires presents a linear increase (shown in Fig. 2b), and the tensile force and resistance of the meandering wires show no obvious changes, which exhibits a superior stretchable and expandable capability. Upon mechanical deformation for over the designed ratio $\\left(L/L_{0}=8\\right)$ , both the force and the resistance change exponentially with the strain, as shown in Fig. 2a. The meandering wires show a very good stability after 54,000 cycles at $30\\%$ expansion in durability tests (Fig. 2c). In addition, the relative resistance shows only a little increase $(\\leq2.6\\%)$ with the reduction of bend radii; in particular, the meandering wires can be curved at a bend radius of $150~{\\upmu\\mathrm{m}}$ with good durability over 450 cycles (Fig. 2d). \n\nBy designing a matrix array of nodes connected to meandering wires, a network containing 100 nodes is successfully fabricated and placed on the customized stretch-testing platform (Supplementary Fig. 2a) to evaluate its stretchable and expandable performances. The polyimide (PI) network can be easily stretched and expanded along the desired directions (Fig. 2e and Supplementary Fig. 2b–i; Supplementary Movie 2), which achieves sensing area increase (Supplementary Fig. 2; Supplementary Movie 3), predefined sensory node location (Fig. 2f, Supplementary Figs. 2b and 3), and complex-shape object conform (Supplementary Fig. 3). These characteristics demonstrate the feasibility of SCMNs with adjustable sensing range and large-area expandability. \n\nTemperature sensing. Resistive metals, platinum $\\left(\\mathrm{Pt}\\right)$ and constantan alloy ( $45\\%$ Ni, $55\\%$ Cu), are most commonly used as resistance temperature detectors (RTDs) and strain gauges. Pt has can be differentiated clearly, as shown in Fig. 3b. Additionally, resistance responses of the temperature sensor under different stimuli (e.g., pressure, UV light, magnetic field, and RH) are presented in Supplementary Fig. 5, which surely shows a favorable selectivity in temperature for the SCMN. \n\n![](images/badf5c6bc3ae8427a76f310dcdb7d13e649ec90df1bd9e0aadb1f1ccb7c0c0fb.jpg) \nFig. 1 Skin-inspired highly stretchable and conformable matrix networks. a Schematic illustration of SCMNs conforming to the surface of a human arm and an expanded network (expansion: $200\\%$ ) conforming to the surface of a human abdomen (right); the tree branch-like connections of neurons (left bottom); the sensory receptors of the glabrous skin (left top). b Optical image of the fabricated polyimide network $(10\\times10$ array, scale bar: $5\\mathsf{m m}\\cdot$ ). c Tilted SEM image of the polyimide network (scale bar: $500\\upmu\\mathrm{m}\\right)$ ; the inset is a higher resolution SEM image of a meandering interconnect (scale bar: $50\\upmu\\mathrm{m})$ . d Schematic layout of an SCMN—an integrated sensor array with eight functions. (temp.: temperature). e Image of an SCMN attached to a sheet of paper, demonstrating ultrahigh flexibility and stretchability. The inset (upper) shows an SCMN conforming to a human finger, (middle) an SCMN attached to human skin with compression, and (bottom) an SCMN stretched by a human hand (scale bar: 1 cm) \n\na higher temperature but lower strain sensitivity when compared with constantan alloy, as shown in Supplementary Figs. 4a, b. A Pt thin film is deposited on the patterned nodes of the SCMN to act as a RTD, as shown in the inset of Fig. 3a. The temperature coefficient of resistance (TCR) is a key metric for evaluating the TCR ¼ 10 \u0002 ΔTR, where R0 is the original resistance value of the Pt thermal response of temperature sensors and is defined as thin film at $\\bar{0}^{\\circ}\\mathrm{C}$ and $\\Delta R$ is the resistance change corresponding to the temperature change $\\Delta T.$ . Fig. 3a strikingly demonstrates that the relative resistance of the temperature sensor changes linearly as the temperature increases from 0 to $70^{\\circ}\\mathrm{C},$ and the obtained TCR of $\\mathrm{Pt}$ is $2410\\mathrm{ppm}/^{\\circ}\\mathrm{C}$ , which is comparable with the TCR value of commercial products $3850\\mathrm{ppm}/{}^{\\circ}\\mathrm{C})$ . Moreover, the spatial temperature distribution can be easily recognized with temperature sensors diagonally on the SCMN (Supplementary Fig. 4c), and imaging temperatures close to $36.8^{\\circ}\\mathrm{C}$ and $45.8^{\\circ}\\mathrm{C}$ \n\nIn-plane strain sensing. Constantan alloy is used in our experiment as an in-plane strain gauge due to its high strain sensitivity and low TCR (Supplementary Figs. 4a, b). The gauge factor (GF) is defined as $\\begin{array}{r}{\\dot{\\mathrm{GF}}\\overset{\\leftarrow}{=}\\frac{\\Delta R/R_{0}}{\\varepsilon}}\\end{array}$ , where $\\Delta R$ is the change in resistance caused by strain $\\varepsilon$ , and $R_{0}$ is the resistance of the undeformed gauge. As shown in Fig. 3c, the relative change of resistance is linearly correlated with the applied strain, leading to a high GF of 18. The high GF may be mechanically induced using prebent samples with various radii of curvature50; the detailed strain calculation method is shown in Supplementary Fig. 6a and Supplementary Note 1. In addition, the temporal resistance changes for different curvatures of the strain sensor under cyclical bending (Strain: 0.7, 1.3, and $1.5\\%$ ) reveal its favorable durability for sensing different strains (presented in Fig. 3d). Our device exhibits good in-plane strain discrimination to the other external stimuli, such as RH (Supplementary Fig. 6b), magnetic field (Supplementary Fig. 6c), pressure (Supplementary Fig. 6d), and UV light (Supplementary Fig. 6e), which have very small impacts on in-plane strain sensing, as shown in Supplementary Fig. 6. Upon attachment of the strain sensor to a human finger, the bending finger manners can be recorded by the SCMN, as shown in Supplementary Fig. 6f, indicating the potential for applications in health-monitoring systems, medical diagnostic instruments, and encrypted information transmissions. \n\n![](images/28d4b74f517fa9ed31867a90e92e268a3a824dae945cddca88d49ae5697b4c8c.jpg) \nFig. 2 Mechanical and electrical testing of the meandering interconnects. a Relative resistance and tensile force change with the extension of the meandering interconnects (50-μm-wide, $50\\mathrm{-}\\upmu\\mathrm{m}$ -thick polyimide wire coated with $\\mathsf{A g}$ thin films); the green section shows a perfectly stable performance region, and the inset depicts a schematic of the customized stretch-testing platform. b Optical images of a meandering wire stretched from an $L/L_{0}$ of 1 to 8 (scale bar: $3\\mathsf{m m}$ ). c Durability testing at $300\\%$ expansion, with an inset showing the stretching at $L/L_{0}=1$ and $L/L_{0}=3$ . d Relative resistance change vs. bend radius, with an inset showing bend durability at a bend radius of $150\\upmu\\mathrm{m}$ e Optical image of an expanding SCMN (scale bar: $2({\\mathsf{c m}}),{\\mathsf{\\Gamma}}$ , with an inset depicting an enlarged view of the red rectangle (scale bar: $5\\mathsf{m m}^{\\cdot}$ ). The network is made of 100 nodes ( $1.6\\mathsf{m m}$ in diameter) connected by $50\\mathrm{-}\\upmu\\mathrm{m}$ -wide, 25- $\\upmu\\mathrm{m}$ -thick polyimide wires coated with Au thin films. f Optical image of a twisted SCMN (scale bar: $2c m$ ) \n\nHumidity sensing. Human skin contains no specific receptors for humidity sensing and is instead able to sense changes in humidity via mechanoreceptors and thermoreceptors51. In our device, a fabricated capacitor-based sensor, as shown in the inset of Fig. 3e, is used to sense ambient RH. The absorption of water molecules changes the permittivity of the PI and thus the capacitance of the humidity sensor, yielding a linear correlation between relative changes in capacitance and RH, which results in a slope of 0.07 (Fig. 3e). The fast response times of the humidity sensor for absorption $(1.5s)$ and desorption $(50.6\\mathrm{s})$ are presented in Supplementary Fig. 7a. A good RH selectivity in multi-stimulus sensing of SCMN is presented as well, external stimuli, such as pressure loads (Supplementary Fig. 7b), temperature changes (Supplementary Fig. 7c), magnetic fields (Supplementary Fig. 7d), and in-plane strain (Supplementary Fig. 7e), have negligible effects on humidity sensing. Additionally, the capacitances of RH sensing do not show any noticeable changes although capacitance signals exhibit larger disturbances when UV light $(3\\mathrm{mW}\\mathrm{cm}^{-2}.$ ) turns on (Supplementary Figs. 7f). Spatial humidity mapping clearly discriminates areas of the humidity sensor arrays that are only partially covered by water droplets (Fig. 3f), demonstrating the potential for use in detecting spatial differences in RH. \n\nLight sensing. Sensing ambient light, including UV, visible and infrared (IR) light, is another important function of the artificial human somatosensory system. Humans can neither see nor differentiate the illumination intensity of UV or IR light, neither with eyes nor skins. Overexposure to UV or IR light can be harmful to the human body, hence it is necessary to achieve UV or IR light e-skin detecting. Additionally, the inclusion of optical sensors in e-skin would broaden the vision sensing range for humans. Here we take UV sensor based on $\\mathrm{{}}Z\\mathrm{{nO}}$ as an example, while IR sensor, which can be achieved by depositing the corresponding sensitive material on the interdigital electrodes, is not demonstrated in this work yet. $\\mathrm{znO}$ -based metal–semiconductor–metal sensors were integrated into the network, because $\\mathrm{znO}$ is regarded as one of the most promising candidates for UV photodetection52. As shown in Supplementary Fig. 8a, a remarkable increase is observed in the current induced by $355\\mathrm{nm}\\mathrm{UV}$ illumination $(286.5\\mathrm{mW}\\mathrm{cm}^{-2}),$ at a $5\\mathrm{V}$ bias, with a rapid response time at the rising edge of 41 ms (Supplementary Fig. 8b). Moreover, photocurrent induced by UV light is linear with respect to illumination intensity, resulting in a fast photoresponsivity $R$ of $0.738\\mathrm{A}/\\mathrm{W}_{\\colon}$ , as shown in Fig. 3g. The good repeatability of UV sensors is investigated under various UV illumination intensities, as presented in Fig. 3h. External disturbances such as magnetic fields (Supplementary Fig. 8c), RH (Supplementary Fig. 8d), strain (Supplementary Fig. 8f), and pressure (Supplementary Fig. 8g) have negligible effects on UV light sensing. Normalized photocurrents exhibit a small growth due to the excited electron concentration of the conduction band in $\\mathrm{{}}Z\\mathrm{{nO}}$ increasing as temperature (Supplementary Fig. 8e) but which would have a small impact on UV discrimination from other stimuli. Moreover, it is feasible to replace $\\mathrm{znO}$ thin film with other materials, such as CdS for visible light and $\\mathrm{Ge/Si}$ for IR light, implying the potential to expand light sensing by SCMNs to a wider spectral range. \n\n![](images/7ca0b67049ef2012d9f842a2a27a9bed95bace7caeba6b78fd94a2f29a2f88ea.jpg) \n\nMagnetic field sensing. Highly sensitive, giant magnetoresistive (GMR)-sensing elements composed of $\\mathrm{Co/Cu}$ multilayers are deposited on the sensory nodes (inset of Fig. 3i), adding a “sixth sense”53 to the SCMN for the presence of static or dynamic magnetic field detection (magnetoreception). The GMR ratio $\\mathrm{GMR}(H_{\\mathrm{ext}})=[R(H_{\\mathrm{ext}})-R_{\\mathrm{sat}}]/R_{\\mathrm{sat}},$ is defined as the magnetic field dependence of changes in sensor resistance $R\\big(H_{\\mathrm{ext}}\\big)$ and normalized to the resistance value when the sample is magnetically saturated $R_{\\mathrm{sat}}^{53}$ . We conduct a GMR characteristic measurement of as-fabricated $[\\mathrm{Co/Cu}]_{50}$ multilayers at room temperature. A high GMR ratio of $50\\%$ is obtained (presented in Fig. 3i), which is a typical value for $\\mathrm{{Co/Cu}}$ multilayers53,54. Then a permanent magnet is used to approach or withdraw from the sensor equipped with $[\\mathrm{Co/Cu}]_{10}$ multilayers alternatively. The resistance changes with respect to the intensity of the magnetic field are derived by varying the distance between the sensor and the magnetic field, as shown in Fig. 3j and Supplementary Fig. 9a. Owing to the GMR effect, the resistance is observed to drop as the magnet is moving forward, while resistance recovers to the original value as the magnet is moving backward. Furthermore, when varying each other external stimulus (e.g., temperature, RH, UV light, pressure or in-plane strain, as shown in Supplementary Figs. 9b-f), changes in resistance all present little shifts by altering the same distance between the magnet and the sensor. And the resistance variations were recorded during the application of three different strains (0.85, 1.2, and $1.47\\%$ ) independently and in conjunction with an approaching magnet (pink), as shown in Supplementary Fig. 9g, indicating that magnetic field sensing can be differentiated easily when applied strains. In short, this magnetoreceptive e-skin enables magnetic field proximity detection, navigation, and touchless control and essentially intensifies the sensing range of the e-skin. \n\nPressure and proximity sensing. Dual-mode capacitor-based sensors can provide both pressure and proximity sensing capabilities for e-skin, extending the tactile sensing functionality in contact and non-contact modes24,41,42. The pressure and proximity sensor array is fabricated on the other side of the PI substrate, which is composed of an Ecoflex dielectric layer sandwiched between Ag thin film electrode layers and exhibits comparable performance in both pressure detection and object proximity sensing. \n\nPressures arouse an increase in capacitance of the sensor as a result of the reduced distance between the two $\\mathrm{Ag}$ electrodes, regardless of RH, UV light, magnetic field, temperature, or in-plane strain (Supplementary Figs. 10a-e). Pressure sensing performance is evaluated based on pressure sensitivity, which is defined as $\\begin{array}{r}{S=\\frac{\\Delta C/C_{0}}{\\Delta P},}\\end{array}$ where $\\Delta C$ is the capacitance change, $C_{0}$ is the original capacitance of the device, and $\\Delta P$ is the change in the applied pressure. The capacitance responses to various pressures for two consecutive loading tests is shown in Fig. 4a. Under pressures ${<}16$ $\\mathrm{\\kPa_{:}}$ , the sensitivity of the fabricated pressure sensor is $22.4\\mathrm{MPa}^{-1}$ , which is larger than previously reported values24,36,55. Under pressures ranging from 16 to $360\\ \\mathrm{kPa}$ , the sensitivity of the pressure sensor is $1.25\\mathrm{MPa}^{-1}$ , which is comparable to the record values achieved by our previously reported pressure sensor (1.45 $\\mathrm{MPa^{-1}}$ for pressures up to $100\\mathrm{kPa})^{24}$ and by Ag nanowire pressure sensors $\\cdot1.{\\dot{6}}2\\mathrm{MPa}^{-1}$ for pressures up to $500\\mathrm{\\kPa})^{5.}$ 5. In addition, pressure as low as $7.3\\pm1.2\\mathrm{Pa}$ is detected and recorded in real time by the sequential application of six water droplets to the sensor, as shown in Fig. 4b. The capacitance also returns to its original value after removal of the droplets, clearly indicating the ability to detect small pressures with superior stability. Furthermore, pressure distribution mapping of the 2D surface is also demonstrated by applying a stamp in shape of a $\"6\"$ to the sensor array, as shown in Fig. 4c. \n\nFigure 4d shows capacitance changes corresponding to a human finger approaching the device (green), gently pressing it (pink), and moving away (white). These results indicate that the pressure (contact) and proximity (non-contact) sensing modes coexist, and the detailed capacitance responses of the two modes are presented in Supplementary Fig. 10f. Capacitance changes are determined with a finger repeatedly approaching the device (green, from a distance of approximately $1{\\mathrm{cm}}^{\\cdot}$ ), pressing it (pink), and then moving away (white). Finger proximity leads to a decrease in capacitance, whereas physical contact induces an increase in capacitance by reducing the distance between the two electrodes. The capacitance changes with disturbances in the fringe electric field in either contact or non-contact mode, and Supplementary Fig. $10\\mathrm{g}$ illustrates the capacitive working mechanism. \n\nProximity signals from the SCMN change with respect to the distance of an approaching finger, and the capacitance drops sharply when the distance falls below $2\\mathrm{cm}$ , as shown in Fig. 4e. Furthermore, tests comparing the capacitance-reduction signals of various materials, including copper, aluminum, PVC, glass, wood, ceramic, and a human hand41, indicate that the surface charge of the approaching material affects the electric field generated by the proximity sensors. In particular, an approaching hand elicits the largest change in capacitance41. The capacitance alternately decreases when a finger periodically approaches within $4\\mathrm{cm}$ of the sensor and decreases further when the distance is reduced to $3c m$ , as depicted in the inset of Fig. 4e. More importantly, the position of the approaching finger can be clearly identified, as illustrated by the position contour map in Fig. 4f. Therefore, this soft, capacitor-based sensor array enables the precise location/magnitude identification of pressures loads and approaching objects with high sensitivity, a rapid response, and high reversibility. \n\nSCMN adjustable sensing range and area expansion. The spatial resolution of human tactile sensing varies across the body. For instance, the spatial resolution at fingertips is about seven times larger than that of $\\mathrm{\\palm}^{56}$ . As inspired by the variable spatial resolution of mechanoreceptors distributed in different parts of human skin, the SCMN, sensors with multiple sensory functions all integrated in a structured PI network as distributed layout (Supplementary Fig. 11a), does allow the density of the sensory nodes to be adjusted with the meandering structure stretching to represent areas of the skin with highly differing mechanoreceptor density. Besides, different functional sensors could be fabricated on the same sensory node in stack with insulation of PI dielectric thin films, regarded as stacked layout or 3D integration57,58 (schematically shown in Supplementary Fig. 11b), which will contribute to high density of mechanosensation electronics. Our fabricated SCMN, actually, is integrated by a combination of the distributed and stacked layouts (Supplementary Fig. 11c). Additionally, design rules of 3D stacked layouts for the multifunctional sensors are presented in Supplementary Table 1. \n\n![](images/f248cd9e87b0abd32671c4067162e1607c8cc35d9714f9370eecedd9de664942.jpg) \nFig. 4 Pressure and proximity sensing performances and area expansion. a Capacitance response to various pressures for two consecutive load tests. b Real-time small-pressure recording during the sequential application of six water droplets to the sensor; the corresponding pressure is $7.3\\pm1.2\\mathsf{P a}$ . c Pressure mapping of a number $\"6\"$ stamped on the pressure sensor array with a pressure of $8\\mathsf{k P a}$ . d Capacitance changes from a finger cyclically approaching the device (green, from a distance of approximately 1 cm), pressing it (pink) and moving away (white). e The relative capacitance change reduces with the decreasing distance of an approaching finger. The inset shows the capacitance difference as a finger repeatedly approaches the device. f Proximity detection of a hand and identification of its position. g Schematic illustration of an SCMN as an artificial electronic skin on a hand, showing sensing adjustability and expandability (scale bar: 1 cm). h Pressure mapping before and after the $300\\%$ expansion of an SCMN; the position of the pressure load is also identified after expansion \n\nFigure $4\\mathrm{g}$ schematically illustrates the attachment of SCMN to an artificial hand as e-skin both with and without sensing area expansion, exhibiting superior area adjustability and expandability for multi-stimulus sensing (also depicted in Supplementary Fig. 3). As shown in Fig. 4h, spatial pressure mapping can be achieved before and after $30\\%$ expansion of the SCMN, indicating that SCMNs can be used to both identify the position of the pressure load and estimate the size of the loading object even with network stretching/expansion. Indeed, the SCMN could realize a 25-fold (or more) expansion of the sensing area, ranging from the original coverage $\\dot{(}16\\mathrm{cm}^{-2}),$ to the expandable size $(400\\mathrm{cm}^{-2},$ ), shown in Supplementary Fig. 2. Furthermore, this property can be used to define the detection area not only for pressure but also for other external stimuli (e.g., temperature, inplane strain, proximity, humidity, optical, magnetic field, etc.). These sensory nodes of the SCMN are adjustable and expandable to predefined locations for multifunctional sensing and, through network sensing area expansion, can be used to emulate the different densities of mechanoreceptors in the human skin. \n\nSimultaneous multiple stimuli sensing. The fabricated SCMN, integration of temperature, in-plane strain, humidity, UV light, magnetic, pressure, and proximity sensors, can in real time record various signals induced from the external environment simultaneously, as well as differentiate each stimulus because of each flexible sensor having good selectivity and discrimination for external stimuli. The sensing ability and orthogonality between sensors in the SCMN are presented in the form of thumbnails in Supplementary Table 2, and the corresponding index is also shown in Supplementary Table 3. \n\nFigure 5a shows real-time recording signals in temperature, pressure, and proximity simultaneously. The procedure involves artificial/human hand proximity, three consecutive pressure loads, human hand contact, and three-time breathing toward the SCMN. When an artificial wood hand or a human hand is brought to approach the SCMN with a distance of about $1\\mathrm{cm}$ , the capacitances of the capacitor-based soft sensor are both triggered to decrease as the interferences of fringe electric field in noncontact mode. It is very noticeable that human hand approaching would lead to a much larger reduction in capacitance. However, the resistance of the temperature sensor does not show any obvious change during proximity sensing. Then placing three bottles (empty, filled with water, filled with hot water) on the SCMN in sequence. On the one hand, the capacitances of the pressure and proximity sensor exhibit corresponding increase rates with applying pressures (2.4, 4, and $3.2\\mathrm{kPa}$ ). On the other hand, the resistance of the temperature sensor begins to cause a sharp increase (up to a temperature of $33.2^{\\circ}\\mathrm{C}$ correspondingly) when loading the third bottle that is filled with hot water and then recovers to the range of room temperature after removal of the bottle. With human hand contacts on the SCMN, both signals from proximity and temperature sensing change simultaneously. The capacitance falls to the lowest level, and the resistance arises to a corresponding skin temperature at $32.7^{\\circ}\\mathrm{C}$ Similarly, human breaths (exhale, containing moisture and heat) toward the SCMN for three times could bring the same change trends in capacitance and resistance as human hand contacts. Additionally, the detailed procedure is also shown in Supplementary Movie 4. Fig. 5b illustrates real-time multiple stimuli sensing as a permanent magnet put near or loaded on the SCMN. The magnetic field from the magnet causes a drop in resistance of the magnetic sensor when the magnet is moving close to the SCMN. Meanwhile, the fringe electric field of the soft sensor disturbed by the magnet also leads to a decrease in capacitance. With the proximity distances change between $1\\mathrm{cm}$ and $2\\mathrm{cm}$ alternatively, the resistance and the capacitance both show periodical fluctuations. Furthermore, a pressure of $5\\mathrm{kPa}$ loaded on the SCMN by introducing the magnet induces an increase in capacitance for pressure sensing and makes it reach the minimum of resistance for magnetic sensing at the same time. The presence of magnet proximity/loading can be seen in Supplementary Movie 5. We can see the SCMN simultaneously monitoring three or more stimuli in Supplementary Fig. 12 as well. Notably, the specific sensor has a good selective detection for its sensitive stimuli, only with a little disturbances induced by other stimuli. More specifically, the coupled process of human finger contact/ touch (Fig. 5a, and Supplementary Fig. 12a) and human exhale toward the SCMN (Fig. 5a, Supplementary Figs. 12b, c) can be recorded in real time and differentiated simultaneously. \n\nPersonalized intelligent prosthetic hand with pressure and temperature sensing. These capabilities of sensing pressure and temperature are essential features of the human $s\\mathrm{kin}^{3,4}$ . As schematically shown in Fig. 6a, human hand can naturally differentiate temperatures when touching. Hence, we construct an intelligent prosthetic hand in personalized SCMN configuration, consisting of pressure and temperature sensor pixels on fingers, to facilitate simultaneous and sensitive pressure and temperature sensing. Pressure sensors integrated into the prosthetics could help disabled patients to regain the functionality of force sensing for grasp control and object manipulation. Furthermore, sensing temperature can provide information about the surroundings and avoid damaging temperatures. When the prosthetic hand is going to grasp a cup filled with water, temperature sensor would achieve cold/hot sensation for water and contribute to prevent injury from high temperatures. Notably, the prosthetic hand, adding the intelligent factor by means of multiple sensors integration, can not only contour pressure distribution on fingers but also estimate temperatures of grasping objects simultaneously. \n\n![](images/4a168ae616818574239b6f33fc1d05747740a4fddf0cb6fade832e3460a68bcc.jpg) \nFig. 5 Simultaneous multiple-stimuli sensing performances. a Real-time simultaneous sensing of temperature, pressure, and proximity stimuli. Signals in recording: Proximity—artificial/human hand approaches the SCMN with a distance of about 1 cm; Pressure—loading bottles on the SCMN with pressures of $2.4\\mathsf{k P a}$ (empty), $4\\mathsf{k P a}$ (filled with water), and $3.2\\mathsf{k P a}$ (filled with hot water) consecutively; Contact—human hand on the SCMN; and Exhale—human breaths toward the SCMN for three times (Details are described in Supplementary Movie 4). b Real-time simultaneous sensing of magnetic field, pressure, and proximity stimuli. The detailed procedures of a permanent magnet put near or loaded on the SCMN: the magnet approaches the SCMN with a distance of about $1.5\\mathsf{c m}_{}$ the proximity distances change between 1 cm and $2c m$ alternatively; the magnet loaded on the SCMN corresponding to a pressure of $5\\mathsf{k P a}$ (see Supplementary Movie 5) \n\n![](images/a45f4d67abb7a7a9415b41170149e71c08d75a3604ae2be51bb435458554c4c5.jpg) \nFig. 6 The intelligent prosthetic hand with personalized SCMN configuration. a Schematic illustration of human hand picking up a cup with temperature detection at the same time. b Images show operations of the intelligent prosthetic hand to grasp (upper) and release (bottom). The procedures of grasping/releasing are also shown in Supplementary Movie 6. The intelligent prosthetic hand equipped with five pressure sensors (P1, P2, P3, P4, and P5) and one temperature sensor (T0) on fingers. c Pressure distribution contour on the fingers when the intelligent prosthetic hand is grasping a water cup and sensing temperature of $59.1^{\\circ}\\mathsf C$ . d–g The intelligent prosthetic hand grasps/releases cups filled with water with four different temperatures: $27^{\\circ}\\mathsf{C}$ (d), $487^{\\circ}\\mathsf C$ (e), $59.1^{\\circ}\\mathsf C$ (f), and $71.2^{\\circ}\\mathsf{C}\\ (\\pmb{\\mathsf{g}})$ . h Temperature estimation by the fitting equation when the intelligent prosthetic hand is grasping \n\nThe grasping and releasing operations of the intelligent prosthetic hand are visually described in Fig. 6b and Supplementary Movie 6. The intelligent prosthetic hand equipped with five pressure sensors (P1, P2, P3, P4, and P5) and one temperature sensor (T0) on fingers. Herein P1 is on the middle finger, P2, P3, and P4 are on the forefinger, and P5 and T0 are on the thumb, respectively. Their positions are also presented in Fig. 6c. By optimizing testing circuitry and shield setting, the interference from proximity signals is minimized, leading to a better sensing performance in contact mode. The intelligent prosthetic hand grasps/releases cups filled water with four different temperatures (water temperatures are measured with an infrared thermometer, respectively) are illustrated in Fig. 6d–g. When the intelligent prosthetic hand touches the cup, five pressure sensors (P1, P2, P3, P4, and P5) on fingers begin to increase the capacitance in pace with the increase of grip strength quickly, then the capacitance keeps small variations over a period of time at the peaks of grip strength. Meanwhile, temperature sensor (T0) also exhibits increment trend of resistance change at various degrees according to different water temperatures. The higher temperature causes a larger resistance change, which is just the same as mentioned above. Furthermore, capacitances of all five pressure sensors fast recover to the original values, and resistances of temperature sensor show recovery behavior as well, when the intelligent prosthetic hand coming to release. Impressively, pressure distribution on the fingers is illustrated in Fig. 6c, while the intelligent prosthetic hand grasping a cup with water temperature of $59.1^{\\circ}\\mathrm{C}$ is illustrated in Fig. 6f. Compared with other pressure sensors on the fingers, the pressure sensor (P2) exhibits the largest capacitance change, which means that P2 bears the maximum grip pressure (about $200\\mathrm{kPa})$ in the grasp operation. Moreover, we are able to derive the linear relation between temperature and resistance according to the resistance values from 27, 48.7, and $71.2^{\\circ}\\mathrm{C}$ . As shown in Fig. 6h, the resistance value from $59.1^{\\circ}\\mathrm{C}$ is very close to the fitting one, representing a small variation of $2.6\\%$ . In effect, we can do temperature estimation through the experimental data and the fitting equation when the intelligent prosthetic hand is performing grasp/release operations. Briefly, the personalized intelligent prosthetic devices could allow amputees or individuals with nerve damage to regain considerable functionalities, such as touch and temperature sensing, to improve the rehabilitation and transform the lives and abilities of the disabled patients. \n\n# Discussion \n\nSkin-inspired highly stretchable and conformable matrix networks have been fabricated that integrate temperature, strain, humidity, light, magnetic, pressure, and proximity sensors as multifunctional detection matrix. The SCMN presented in this work successfully expands the sensing functionality of e-skin into seven categories, and it can simultaneously detect and differentiate three or more stimuli. Take the magnetic sensing and the pressure sensing as examples (Fig. 6b, Supplementary Movie 5, Supplementary Figs. 9 and 10), the SCMN works very well in different environment, like changing temperature, RH, UV intensity, or in-plane strain. Moreover, the sensing area of the SCMN can be adjusted and predefined by stretching and expanding the meandering interconnects, which acted as neural pathways. This skin-inspired SCMN, which features simultaneous multi-stimulus sensing, adjustable sensing range/large-area expandability, and potential high-density 3D integration, can sense the magnitude and location of multi-stimulus sensing in real time, impressively construct a personalized intelligent prosthesis for pressure/temperature sensing, and will likely attract considerable attention for its application to humanoid robotics, new prosthetics, human–machine interfaces, and healthmonitoring technologies. \n\n# Methods \n\nFabrication of the highly stretchable and conformable PI networks. First, the Kapton HN film (DuPont) was cleaned by ultra-sonication with acetone, alcohol, and deionized water for $10\\mathrm{min}$ ; dried by $\\Nu_{2}$ flow; and cured in an oven at $80^{\\circ}\\mathrm{C}$ for $^{4\\mathrm{h}}$ . Second, a 3-inch silicon wafer was spin-coated with a $4{\\cdot}||\\mathbf{m}$ -thick photoresist layer, and then the Kapton film was bonded to the wafer using the hot-press method. Third, after being spin-coated with a 2- $-\\upmu\\mathrm{m}$ -thick negative photoresist layer (NR9-1500PY), the Kapton film was patterned by UV lithography (Suss MicroTech, MA 6). Fourth, Au (or $\\mathrm{{Cr/Cu/Al/Ni})}$ thin film (DC 100 W, 3 mTorr, $10\\mathrm{min}$ ) was deposited by sputter coating (Denton Vacuum, Discovery 635) and then lifted off to form a patterned Au mask. Fifth, the patterned Kapton film was etched $(\\mathrm{O}_{2}$ plasma, 150 mTorr, 100 W) using a reactive ion etcher (South Bay Tech., RIE 2000). Finally, the etched Kapton film was released, and the metal mask was removed by wet or dry etching to obtain the highly stretchable and conformable PI networks. \n\nFabrication of expandable sensors and soft sensor array integrated on the SCMN. The fabrication process is illustrated in Supplementary Fig. 1. Step 1: A layer of poly (methyl methacrylate) (PMMA; $4{,}000\\ \\mathrm{r.p.m}$ . for $60~\\mathsf{s}.$ , baked at $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ ) and a layer of PI (polyamide acid solution; $2{,}000\\ \\mathrm{r.p.m}$ . for $60\\mathrm{{s}}$ and $^{4\\mathrm{h}}$ at $250^{\\circ}\\mathrm{C},$ four times to form a ${30}\\mathrm{-}\\upmu\\mathrm{m}$ film) were sequentially spin-coated onto a Si wafer. Step 2: Metal electrodes and dielectric layer preparation. Photolithography (NR9-1500PY, $2\\upmu\\mathrm{m})$ , sputtered aluminum thin films, and lift-off photoresist were used to pattern the row and column meandering structures, and a PI dielectric layer $\\left\\langle500\\mathrm{nm}\\right\\rangle$ was prepared between the electrodes. Step 3: Expandable sensor preparation consisted of photolithography (NR9-1500PY, $2\\upmu\\mathrm{m}\\dot{}$ ) to generate the sensor patterns, sputtering of the specific sensitive elements (Pt for temperature, Constantan for in-plane strain, $\\mathrm{{Co/Cu}}$ multilayer for magnetic field, Al/PI for humidity, $\\mathrm{{Al/ZnO}}$ for UV light, etc.), lift-off of the photoresists, and encapsulation of the patterned PI layer $(3\\upmu\\mathrm{m})$ . Additionally, the specific sensor patterns and elements for each stimulus are available in the literature $^{30,31,52,53,^{\\bullet}59-61}$ . Step 4: Network preparation consisted of photolithography (NR9-1500PY, $2\\upmu\\mathrm{m},$ followed by sputtering of a $\\mathrm{SiO}_{2}$ etching mask, lift-off of the photoresist, and reactive ion etching (RIE, $\\mathrm{O}_{2}$ plasma, 150 mTorr, 200 W). Step 5: Network pickup and soft sensor array preparation. Immersion in hot acetone partially removed the PMMA layer, and the network was retrieved from the silicon wafer and attached to a piece of poly(vinyl alcohol) (PVA) or poly(dimethylsiloxane) (PDMS). Sputtered Ag thin films formed the bottom and top electrodes via a mask on the opposite side of the etched network structure, and Ecoflex silicone elastomers (Smooth- $\\mathrm{{.On\\0010}}$ , mixing part A and part B with the ratio of 1:1 in weight, $300\\mathrm{r.p.m}$ . for $50\\mathrm{s}$ cured at room temperature over one night, and cut into pad size) were placed on the sensory nodes between the two electrodes. Finally, some certain amounts of PDMS or PVA solutions were poured uniformly on the fabricated network and then baked at $60^{\\circ}\\mathrm{C}$ for several hours. The SCMN with a layer of PDMS or PVA can be obtained. \n\nCharacterization of the integrated sensors. SEM images were obtained on a Hitachi SU8020. Applied force was measured using a force gauge (ATI, Nano 17). Sensor resistance and capacitance measurements were recorded on an Agilent (E4980A) Precision LCR meter with custom LabVIEW programs, and sensor currents were measured on a Keithley 4200 SC. \n\nData availability. All data supporting this study and its findings are available within the article and its Supplementary Information or from the corresponding author upon reasonable request. \n\nReceived: 11 January 2016 Accepted: 20 December 2017 \nPublished online: 16 January 2018 \n\n# References \n\n1. Takei, K. et al. Nanowire active-matrix circuitry for low-voltage macroscale artificial skin. Nat. Mater. 9, 821–826 (2010). \n2. Wang, C. et al. User-interactive electronic skin for instantaneous pressure visualization. Nat. Mater. 12, 899–904 (2013). \n3. Chortos, A. & Bao, Z. Skin-inspired electronic devices. Mater. Today 17, 321–331 (2014). \n4. Chortos, A., Liu, J. & Bao, Z. Pursuing prosthetic electronic skin. Nat. Mater. 15, 937–950 (2016). \n5. Bao, Z. Skin-inspired organic electronic materials and devices. MRS Bull. 41, 897–904 (2016). \n6. Kim, S., Laschi, C. & Trimmer, B. Soft robotics: a bioinspired evolution in robotics. Trends Biotechnol. 31, 287–294 (2013). \n7. Dahiya, R. S., Metta, G., Valle, M. & Sandini, G. Tactile sensing: from humans to humanoids. IEEE Trans. Robot. 26, 1–20 (2010). \n8. Rus, D. & Tolley, M. T. Design, fabrication and control of soft robots. Nature 521, 467–475 (2015). \n9. Kim, J. et al. Stretchable silicon nanoribbon electronics for skin prosthesis. Nat. Commun. 5, 5747 (2014). \n10. Gerratt, A. P., Michaud, H. O. & Lacour, S. P. Elastomeric electronic skin for prosthetic tactile sensation. Adv. Funct. Mater. 25, 2287–2295 (2015). \n11. Kim, D. H. et al. Epidermal electronics. Science 333, 838–843 (2011). \n12. Pang, C. et al. Highly skin-conformal microhairy sensor for pulse signal amplification. Adv. Mater. 27, 634–640 (2015). \n13. McEvoy, M. A. & Correll, N. Materials science. Materials that couple sensing, actuation, computation, and communication. Science 347, 1261689 (2015). \n14. Tee, B. C. et al. A skin-inspired organic digital mechanoreceptor. Science 350, 313–316 (2015). \n15. Gao, W. et al. Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529, 509–514 (2016). \n16. Chou, H. H. et al. A chameleon-inspired stretchable electronic skin with interactive colour changing controlled by tactile sensing. Nat. Commun. 6, 8011 (2015). \n17. Son, D. et al. Multifunctional wearable devices for diagnosis and therapy of movement disorders. Nat. Nanotechnol. 9, 397–404 (2014). \n18. Mannsfeld, S. C. et al. Highly sensitive flexible pressure sensors with microstructured rubber dielectric layers. Nat. Mater. 9, 859–864 (2010). \n19. Fan, F. R. et al. Transparent triboelectric nanogenerators and self-powered pressure sensors based on micropatterned plastic films. Nano Lett. 12, 3109–3114 (2012). \n20. Lee, S. et al. A transparent bending-insensitive pressure sensor. Nat. Nanotechnol. 11, 472–478 (2016). \n21. Wu, W., Wen, X. & Wang, Z. L. Taxel-addressable matrix of vertical-nanowire piezotronic transistors for active and adaptive tactile imaging. Science 340, 952–957 (2013). \n22. Harada, S., Honda, W., Arie, T., Akita, S. & Takei, K. Fully printed, highly sensitive multifunctional artificial electronic whisker arrays integrated with strain and temperature sensors. ACS Nano 8, 3921–3927 (2014). \n23. Frutiger, A. et al. Capacitive soft strain sensors via multicore-shell fiber printing. Adv. Mater. 27, 2440–2446 (2015). \n24. Zhao, X., Hua, Q., Yu, R., Zhang, Y. & Pan, C. Flexible, stretchable and wearable multifunctional sensor array as artificial electronic skin for static and dynamic strain mapping. Adv. Electron. Mater. 1, 1500142 (2015). \n25. Pang, C. et al. A flexible and highly sensitive strain-gauge sensor using reversible interlocking of nanofibres. Nat. Mater. 11, 795–801 (2012). \n26. Gong, S. et al. A wearable and highly sensitive pressure sensor with ultrathin gold nanowires. Nat. Commun. 5, 3132 (2014). \n27. Yamada, T. et al. A stretchable carbon nanotube strain sensor for humanmotion detection. Nat. Nanotechnol. 6, 296–301 (2011). \n28. Hua, Q. et al. Bioinspired electronic whisker arrays by pencil-drawn paper for adaptive tactile sensing. Adv. Electron. Mater. 2, 1600093 (2016). \n29. Yokota, T. et al. Ultraflexible, large-area, physiological temperature sensors for multipoint measurements. Proc. Natl. Acad. Sci. USA 112, 14533–14538 (2015). \n30. Webb, R. C. et al. Ultrathin conformal devices for precise and continuous thermal characterization of human skin. Nat. Mater. 12, 938–944 (2013). \n31. Lichtenwalner, D. J., Hydrick, A. E. & Kingon, A. I. Flexible thin film temperature and strain sensor array utilizing a novel sensing concept. Sens. Actuat. A Phys. 135, 593–597 (2007). \n32. Tien, N. T. et al. A flexible bimodal sensor array for simultaneous sensing of pressure and temperature. Adv. Mater. 26, 796–804 (2014). \n33. Someya, T. et al. Conformable, flexible, large-area networks of pressure and thermal sensors with organic transistor active matrixes. Proc. Natl. Acad. Sci. USA 102, 12321–12325 (2005). \n34. Zhang, F., Zang, Y., Huang, D., Di, C. A. & Zhu, D. Flexible and self-powered temperature-pressure dual-parameter sensors using microstructure-framesupported organic thermoelectric materials. Nat. Commun. 6, 8356 (2015). \n35. Park, J., Kim, M., Lee, Y., Lee, H. S. & Ko, H. Fingertip skin-inspired microstructured ferroelectric skins discriminate static/dynamic pressure and temperature stimuli. Sci. Adv. 1, e1500661 (2015). \n36. Lipomi, D. J. et al. Skin-like pressure and strain sensors based on transparent elastic films of carbon nanotubes. Nat. Nanotechnol. 6, 788–792 (2011). \n37. Park, Y. L., Chen, B. R. & Wood, R. J. Design and fabrication of soft artificial skin using embedded microchannels and liquid conductors. IEEE Sens. J. 12, 2711–2718 (2012). \n38. Park, J. et al. Giant tunneling piezoresistance of composite elastomers with interlocked microdome arrays for ultrasensitive and multimodal electronic skins. ACS Nano 8, 4689–4697 (2014). \n39. Park, J. et al. Tactile-direction-sensitive and stretchable electronic skins based on human-skin-inspired interlocked microstructures. ACS Nano 8, 12020–12029 (2014). \n40. Park, S. et al. Stretchable energy-harvesting tactile electronic skin capable of differentiating multiple mechanical stimuli modes. Adv. Mater. 26, 7324–7332 (2014). \n41. Hyung-Kew, L., Sun-Il, C. & Euisik, Y. Dual-mode capacitive proximity sensor for robot application: implementation of tactile and proximity sensing capability on a single polymer platform using shared electrodes. IEEE Sens. J. 9, 1748–1755 (2009). \n42. Zhang, B. et al. Dual functional transparent film for proximity and pressure sensing. Nano Res. 7, 1488–1496 (2014). \n43. Jeong, J. W. et al. Capacitive epidermal electronics for electrically safe, long-term electrophysiological measurements. Adv. Healthc. Mater. 3, 642–648 (2014). \n44. Dagdeviren, C. et al. Conformable amplified lead zirconate titanate sensors with enhanced piezoelectric response for cutaneous pressure monitoring. Nat. Commun. 5, 4496 (2014). \n45. Johansson, R. S. & Vallbo, A. B. Tactile sensibility in the human hand: relative and absolute densities of four types of mechanoreceptive units in glabrous skin. J. Physiol. 286, 283–300 (1979). \n46. Lanzara, G., Salowitz, N., Guo, Z. & Chang, F. K. A spider-web-like highly expandable sensor network for multifunctional materials. Adv. Mater. 22, 4643–4648 (2010). \n47. Lanzara, G., Feng, J. & Chang, F. K. Design of micro-scale highly expandable networks of polymer-based substrates for macro-scale applications. Smart Mater. Struct. 19, 045013 (2010). \n48. Hyung-Kew, L., Sun-Il, C. & Euisik, Y. A flexible polymer tactile sensor: fabrication and modular expandability for large area deployment. J. Micro. 15, 1681–1686 (2006). \n49. Purves, D. et al. (eds). in Neuroscience 2nd edn. (Sinauer Associates, Sunderland, MA, 2001). Available from: http://www.ncbi.nlm.nih.gov/books/ NBK10895/. \n50. Kang, D. et al. Ultrasensitive mechanical crack-based sensor inspired by the spider sensory system. Nature 516, 222–226 (2014). \n51. Ackerley, R., Olausson, H., Wessberg, J. & McGlone, F. Wetness perception across body sites. Neurosci. Lett. 522, 73–77 (2012). \n52. Liu, K., Sakurai, M. & Aono, M. ZnO-based ultraviolet photodetectors. Sensors 10, 8604–8634 (2010). \n53. Melzer, M. et al. Imperceptible magnetoelectronics. Nat. Commun. 6, 6080 (2015). \n54. Melzer, M. et al. Stretchable magnetoelectronics. Nano. Lett. 11, 2522–2526 (2011). \n55. Yao, S. & Zhu, Y. Wearable multifunctional sensors using printed stretchable conductors made of silver nanowires. Nanoscale 6, 2345–2352 (2014). \n56. Craig, J. C. & Lyle, K. B. A comparison of tactile spatial sensitivity on the palm and fingerpad. Percept. Psychophys. 63, 337–347 (2001). \n57. Shulaker, M. M. et al. Three-dimensional integration of nanotechnologies for computing and data storage on a single chip. Nature 547, 74–78 (2017). \n58. Jiyoung, K. et al. A stacked memory device on logic 3D technology for ultrahigh-density data storage. Nanotechnology 22, 254006 (2011). \n59. Oprea, A. et al. Temperature, humidity and gas sensors integrated on plastic foil for low power applications. Sens. Actuat. B Chem. 140, 227–232 (2009). \n60. Lee, H., Lee, S., Jung, S. & Lee, J. Nano-grass polyimide-based humidity sensors. Sens. Actuat. B Chem. 154, 2–8 (2011). \n61. Parkin, S. S., Bhadra, R. & Roche, K. P. Oscillatory magnetic exchange coupling through thin copper layers. Phys. Rev. Lett. 66, 2152–2155 (1991). \n\n# Acknowledgements \n\nThe authors are thankful for support from the support of National Natural Science Foundation of China (No. 61405040, 51432005, 61505010 and 51502018), national key R & D project from Minister of Science and Technology of China (2016YFA0202703), and the “Thousand Talents” program of China for pioneering researchers and innovative teams. \n\n# Author contributions \n\nQ.H. and C.P. conceived the idea, Q.H., C.P. and Z.L.W. discussed the data and prepared the manuscript. Q.H. and C.P. designed the structures of the multifunctional e-skin. Q.H. fabricated the SCMN and performed the data measurements. J.S., H.L., and R.B. provided assistance with the experiments. R.B. designed the prosthetic hand and analyzed the corresponding data. R.Y. and J.Z. helped with manuscript writing. All the authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 017-02685-9. \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1016_j.cpc.2018.01.012", + "DOI": "10.1016/j.cpc.2018.01.012", + "DOI Link": "http://dx.doi.org/10.1016/j.cpc.2018.01.012", + "Relative Dir Path": "mds/10.1016_j.cpc.2018.01.012", + "Article Title": "The PSEUDODOJO: Training and grading a 85 element optimized norm-conserving pseudopotential table", + "Authors": "van Setten, MJ; Giantomassi, M; Bousquet, E; Verstraete, MJ; Hamann, DR; Gonze, X; Rignullese, GM", + "Source Title": "COMPUTER PHYSICS COMMUNICATIONS", + "Abstract": "First-principles calculations in crystalline structures are often performed with a planewave basis set. To make the number of basis functions tractable two approximations are usually introduced: core electrons are frozen and the diverging Coulomb potential near the nucleus is replaced by a smoother expression. The norm-conserving pseudopotential was the first successful method to apply these approximations in a fully ab initio way. Later on, more efficient and more exact approaches were developed based on the ultrasoft and the projector augmented wave formalisms. These formalisms are however more complex and developing new features in these frameworks is usually more difficult than in the norm conserving framework. Most of the existing tables of norm-conserving pseudopotentials, generated long ago, do not include the latest developments, are not systematically tested or are not designed primarily for high precision. In this paper, we present our PSEUDODOJO framework for developing and testing full tables of pseudopotentials, and demonstrate it with a new table generated with the ONCVPSP approach. The PSEUDODOJO is an open source project, building on the ABIPY package, for developing and systematically testing pseudopotentials. At present it contains 7 different batteries of tests executed with ABINIT, which are performed as a function of the energy cutoff. The results of these tests are then used to provide hints for the energy cutoff for actual production calculations. Our final set contains 141 pseudopotentials split into a standard and a stringent accuracy table. In total around 70,000 calculations were performed to test the pseudopotentials. The process of developing the final table led to new insights into the effects of both the core-valence partitioning and the non-linear core corrections on the stability, convergence, and transferability of norm-conserving pseudopotentials. The PSEUDODOJO hence provides a set of pseudopotentials and general purpose tools for further testing and development, focusing on highly accurate calculations and their use in the development of ab initio packages. The pseudopotential files are available on the PSEUDODOJO web-interface pseudo-dojo.org under the name NC (ONCVPSP) v0.4 in the psp8, UPF2, and PSML 1.1 formats. The webinterface also provides the inputs, which are compatible with the 3.3.1 and higher versions of ONCVPSP. All tests have been performed with ABINIT 8.4. (C) 2018 Elsevier B.V. All rights reserved.", + "Times Cited, WoS Core": 1303, + "Times Cited, All Databases": 1349, + "Publication Year": 2018, + "Research Areas": "Computer Science; Physics", + "UT (Unique WOS ID)": "WOS:000428483000005", + "Markdown": "# The PseudoDojo: Training and grading a 85 element optimized norm-conserving pseudopotential table \n\nM.J. van Setten a,b,\\*, M. Giantomassi a,b, E. Bousquet c, M.J. Verstraete c,b, D.R. Hamann d,e, X. Gonze a,b, G.-M. Rignanese a,b \n\na Nanoscopic Physics, Institute of Condensed Matter and Nanosciences, Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium \nb European Theoretical Spectroscopy Facility (ETSF) \nc Q-Mat, Department of Physics, University of Liège, Belgium \nd Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854-8019, USA \ne Mat-Sim Research LLC, P.O. Box 742, Murray Hill, NJ, 07974, USA \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: \nReceived 28 October 2017 \nReceived in revised form 16 January 2018 \nAccepted 25 January 2018 \nAvailable online xxxx \nKeywords: \nFirst-principles calculation \nElectronic structure \nDensity functional theory \nPseudopotential \n\nFirst-principles calculations in crystalline structures are often performed with a planewave basis set. To make the number of basis functions tractable two approximations are usually introduced: core electrons are frozen and the diverging Coulomb potential near the nucleus is replaced by a smoother expression. The norm-conserving pseudopotential was the first successful method to apply these approximations in a fully ab initio way. Later on, more efficient and more exact approaches were developed based on the ultrasoft and the projector augmented wave formalisms. These formalisms are however more complex and developing new features in these frameworks is usually more difficult than in the normconserving framework. Most of the existing tables of norm-conserving pseudopotentials, generated long ago, do not include the latest developments, are not systematically tested or are not designed primarily for high precision. In this paper, we present our PseudoDojo framework for developing and testing full tables of pseudopotentials, and demonstrate it with a new table generated with the ONCVPSP approach. The PseudoDojo is an open source project, building on the AbiPy package, for developing and systematically testing pseudopotentials. At present it contains 7 different batteries of tests executed with ABINIT, which are performed as a function of the energy cutoff. The results of these tests are then used to provide hints for the energy cutoff for actual production calculations. Our final set contains 141 pseudopotentials split into a standard and a stringent accuracy table. In total around 70,000 calculations were performed to test the pseudopotentials. The process of developing the final table led to new insights into the effects of both the core-valence partitioning and the non-linear core corrections on the stability, convergence, and transferability of norm-conserving pseudopotentials. The PseudoDojo hence provides a set of pseudopotentials and general purpose tools for further testing and development, focusing on highly accurate calculations and their use in the development of ab initio packages. The pseudopotential files are available on the PseudoDojo web-interface pseudo-dojo.org under the name NC (ONCVPSP) $\\mathsf{v}0.4$ in the psp8, UPF2, and PSML 1.1 formats. The webinterface also provides the inputs, which are compatible with the 3.3.1 and higher versions of ONCVPSP. All tests have been performed with ABINIT 8.4. \n\n$\\circledcirc$ 2018 Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nMany physical and chemical properties of solids are determined by the structure and dynamics of the valence electrons. This is true not only for the formation of chemical bonds, but also for the magnetic behavior and for low-energy excitations. In contrast, the core electrons only indirectly affect these properties. Based on these observations, Density Functional Theory (DFT) electronic structure calculations often assume that the complicated interaction between valence electrons and the ions (formed by the atom nuclei and the core electrons) can be replaced by an effective potential known as a pseudopotential (PSP). The core states are thus eliminated and the valence electrons are described by smooth pseudowavefunctions. This is particularly useful when a planewave (PW) basis set is used to describe the electronic wavefunctions. Such a basis set has the nice advantage that its completeness can be systematically improved thanks to a single parameter, the maximal kinetic energy of the planewaves in the basis set, also called the energy cut-off $\\left(E_{\\mathrm{c}}\\right)$ . Describing the oscillations of the all-electron (AE) wavefunctions near the atomic core would indeed require a prohibitively large number of planewaves. \n\nOne can safely state that any calculation using pseudopotentials can only be as efficient and accurate as the pseudopotentials that are used. Obviously, the problem of finding good pseudopotentials could be avoided altogether by using a basis set that is capable of describing all electronic states on an equal footing. The allelectron approaches, however, immediately lose the elegance of the single convergence parameter in the planewave approach. In a sense the problem of finding a good pseudopotential is now moved to finding a good basis set. Recently it was shown that indeed the variations between the results obtained with different AE-codes, using standard production settings, can be as large as the differences between the results of AE-codes and PW-codes [1]. \n\nNorm-conserving pseudopotentials (NCPPs) [2,3] are among the first pseudopotentials that were routinely used in realistic calculations and paved the way for the ever expanding application of density functional theory [4,5] to solids. It is because of the elegance of the norm-conserving approach that NCPPs are supported by many ab-initio codes. The relatively simple and robust formalism of the NCPP also means that new developments are usually implemented for NCPPs first, see e.g. the recent availability of the temperature dependence of the electronic structure [6]. \n\nUnfortunately, many NCPP tables still in use nowadays for first-principles calculations were generated long ago, before the advent of optimization techniques such as the one by Rappe, Rabe, Kaxiras, and Joannopoulos (RRKJ) [7]. Even more importantly, no systematic validation of these tables is available. Very few of these pseudopotentials allow one to perform non-collinear calculations with the inclusion of the spin–orbit (SO) term. Last but not least, most of these legacy NCPPs employ only one projector per angular channel, hence it is difficult to find NCPPs including semi-core states or pseudopotentials with good scattering properties at high energies. \n\nPresently many NCPP tables are available: The tables by Hartwigsen, Goedecker, Hutter, and Krack (HGHK) [8,9] provide spin–orbit coupling but they were not primarily designed for PW applications and, indeed, on average rather large cutoffs are needed. The NC tables previously available for use with ABINIT,1 contain semi-core states for selected elements but the input files and the pseudopotential generator are not available anymore. The tables from the OPIUM project [10] have RRKJ optimization but not all the atoms of the periodic table are available and multiple projectors for a given angular channel are not supported. NC potentials from the QUANTUM-ESPRESSO community are available [11] in the UPF format, but do not have more than one projector. The table by Schlipf and Gygi (SG15) [12] was designed for efficiency and does not have non-linear core corrections. \n\nAs compared to the more recently developed ultrasoft pseudopotentials [13] (USPP) and the projector-augmented-wave method [14] (PAW), calculations using NCPPs usually require a larger kinetic energy cutoff making them less efficient. The implementation of both the PAW and USPP formalisms is however much more demanding. Moreover little is known about the reliability of these two approaches when applied beyond standard ground state calculations [15]. In contrast NCPPs have been used for decades in different ab-initio fields. \n\nNCPPs continue to represent a valid choice for ab-initio calculations because of the simplicity and robustness of the formalism. We also believe that many future developments in first principles codes will be first implemented within the NCPP formalism and eventually generalized to the USPP/PAW case (NCPPs can be seen as a particular case of the USPP/PAW formalism under certain assumptions). For all the reasons mentioned above the ab-initio community would greatly benefit from the availability of a periodic table of reliable and accurate NCPPs. \n\nWith this in mind, we have constructed a new NCPP table, using the PBE exchange–correlation functional [16], distributed within the PseudoDojo (PD-PBE), using the new framework of the optimized norm-conserving Vanderbilt pseudopotential (ONCVPSP) [17,18]. The main advantage of ONCVPSP is that it produces NCPPs that are usually softer, i.e. lead to converged results at lower cutoff energies, and more accurate (semi-core states can be included via multiple projectors) than traditional NCPPs. Moreover, ONCVPSP is interfaced with libxc [19] and can therefore generate NCPPs for many XC flavors with or without spin–orbit (SO) terms. Our main goal is to provide a set of well-tested and accurate NCPPs that can be used for (a) applications in which the USPP/PAW formalism is not available or not implemented, (b) high-throughput calculations (HTC) and/or systematic studies involving NCPPs e.g. validation of a new PAW/USPP implementation or comparison of the accuracy of the different formalisms in different domains like $\\mathsf{N C}{+}\\mathsf{G W}$ vs PAW+GW. See for example our recent systematic study on the convergence properties of GW [20]. \n\nThe PseudoDojo is an open source project hosted on GitHub and provides a user web-interface at pseudo-dojo.org. We provide pseudopotential files that can be used immediately, as well as the corresponding inputs so that users can tune or change some parameters (e.g. the XC functional) according to their needs. Moreover, we provide an open source python toolbox, that can be used for the automatized generation and validation of pseudopotentials. The pseudopotential files are available on the PseudoDojo webinterface in the ABINIT psp8 format, in the UPF2 format and in the PSML 1.1 XML [21] format shared by SIESTA and ABINIT. The input files, the results of the generation, and the test results are presented via Jupyter notebooks [22] as static HTML pages. Finally, each pseudopotential is linked to a DojoReport file with a full record of the different tests that were performed to validate the pseudopotential (cutoff convergence, $\\varDelta$ -Gauge, Garrity, Bennett, Rabe, and Vanderbilt (GBRV) tests [23]). One can hence easily compare PSPs for a given element and then select the most appropriate one according to a chosen criterion (e.g. efficiency vs accuracy). \n\nThe remaining of this article is organized as follows: The ONCVPSP formalism and the most important differences with respect to standard NCPPs are discussed in Section 2. Subsequently the PseudoDojo project is presented in Section 3 including the python framework used for the automatic generation and validation of the pseudopotentials (PSPs) as well as the web interface that provides access to the PSPs. Section 4 describes the general strategy employed to generate the PD-PBE. Sections 5 and 6 describe the performance of the PSPs in convergence, $\\varDelta$ -Gauge [24], and GBRV [23] tests. A detailed discussion per group of elements of the choices made and the parameters employed for the pseudization is given in Section 7. \n\n# 2. Formalism \n\nThe accuracy of the ONCVPSP pseudopotentials is based on the use of two projectors and generalized norm conservation to reproduce the binding and scattering properties of the all-electron potentials. The underlying formalism of generalized norm conservation was developed by Vanderbilt and used to generate ultrasoft pseudopotentials (USPPs) [13]. Suppose we construct several radial pseudo-wavefunctions $\\varphi_{i}$ at energies $\\varepsilon_{i}$ and angular momentum $\\ell$ , which agree with all-electron radial wavefunctions $\\psi_{i}$ outside a ‘‘core radius’’ $r_{c}$ , have continuous values and first derivatives at $r_{c}$ , and satisfy \n\n$$\n\\left\\langle\\varphi_{i}\\mid\\varphi_{j}\\right\\rangle_{r_{c}}=\\left\\langle\\psi_{i}\\mid\\psi_{j}\\right\\rangle_{r_{c}}\n$$ \n\nwhere the notation indicates that norms and overlaps are calculated inside $r_{c}$ . These $\\varphi_{i}$ obey generalized norm conservation in the sense that the integrated charge density inside $r_{c}$ of any linear combination of the $\\varphi_{i}$ equals that of the corresponding combination of $\\psi_{i}$ . Let these actually be $r$ times the radial wavefunctions so that the kinetic energy operator simplifies to $T=[-d^{2}/d r^{2}+\\ell(\\ell+1)/r^{2}]/2$ in atomic units. We introduce the projectors \n\n$$\n|\\chi_{i}\\rangle=(\\varepsilon_{i}-T-V_{\\mathrm{loc}})|\\varphi_{i}\\rangle,\n$$ \n\nwhere $V_{\\mathrm{loc}}$ is a local potential agreeing with the all-electron potential outside $r_{c}$ , and form the non-local operator \n\n$$\nV_{\\mathrm{NL}}=\\sum_{i,j}\\left|\\chi_{i}\\right\\rangle(B^{-1})_{i j}\\left\\langle\\chi_{j}\\right|\n$$ \n\nwhere \n\n$$\nB_{i j}=\\left\\langle\\varphi_{i}\\mid\\chi_{j}\\right\\rangle.\n$$ \n\nGeneralized norm conservation is sufficient to prove that $B_{i j}$ is a symmetric matrix, so $V_{\\mathrm{NL}}$ is a Hermitian operator. Furthermore, for solutions of the non-local radial Schrödinger equation \n\n$$\n\\left(T+V_{\\mathrm{loc}}+V_{\\mathrm{NL}}\\right)\\varphi=\\varepsilon\\varphi,\n$$ \n\n$d\\ln\\varphi/d r$ and $d^{2}\\ln\\varphi/d\\varepsilon d r$ will agree with those of all-electron solutions $\\psi$ at each $\\varepsilon_{i}$ for $r\\geq r_{c}$ [13]. In fact Eq. (3) is transformed using the eigenvectors of $B_{i j}$ to form orthonormal projectors $|\\tilde{\\chi}_{i}\\rangle$ for a computationally convenient diagonal $V_{\\mathrm{NL}}$ . \n\nIt is straightforward to show that these principles apply to positive-energy scattering as well as bound-state solutions, paralleling the result for basic norm conservation [25]. The local potential $V_{\\mathrm{loc}}$ is generally chosen to be a smooth polynomial continuation of the all-electron potential $V_{\\mathrm{AE}}$ to the origin, continued from the smallest $r_{c}$ among the included $\\ell$ . This allows considerable flexibility which can sometimes be exploited to further extend the range of log-derivative agreement for one or more ℓ. Note that ultrasoft pseudopotentials are constructed from $\\varphi_{i}$ which do not satisfy Eq. (1), but are compensated by the introduction of an overlap operator on the right side of the radial Schrödinger equation and an augmentation contribution to the charge density [13]. \n\nThe strategy employed in ONCVPSP to obtain the accuracy of two-projector ultrasoft potentials and nearly competitive convergence while retaining the simplicity of norm conservation is to enlist the convergence metric introduced by Rabe and coworkers (RRKJ) [7]. They observed that the error in the kinetic energy made by truncating the radial Fourier expansion of a pseudowavefunction $\\varphi$ at some cutoff wave vector $q_{\\mathrm{c}}$ was an accurate predictor of the convergence error made by similarly truncating the planewave expansion in calculations for solids. An optimization formalism was developed independently for ONCVPSP [17,18]. The pseudo-wavefunction is first constrained to satisfy $M$ continuity constraints, \n\n$$\n\\left.\\frac{d^{n}\\varphi}{d r^{n}}\\right|_{r_{c}}=\\left.\\frac{d^{n}\\psi}{d r^{n}}\\right|_{r_{c}},n=0,M-1.\n$$ \n\n$\\varphi$ is then expanded in a set of $N\\ge M+3$ basis functions $\\{\\xi_{i}\\}$ , initially chosen to be an orthogonalized set of spherical Bessel functions. The actual amount of constraints used in this work is specified in Table 2. Employing singular-value analysis, a linear combination $\\varphi_{0}$ is formed which satisfies Eq. (6), as well as a new set of $N-M$ ‘‘null space’’ basis functions $\\{\\xi_{i}^{\\tilde{\\mathsf{N}}}\\}$ , which are mutually orthonormal, orthogonal to $\\varphi_{0}$ , and give zero contribution to Eq. (6) when added to $\\varphi_{0}$ . A generalized residual kinetic energy operator is defined as: \n\n$$\n\\langle\\xi_{i}|\\hat{E}^{\\mathrm{r}}(q_{\\mathrm{c}})\\left|\\xi_{j}\\right\\rangle\\equiv\\int_{q_{\\mathrm{c}}}^{\\infty}\\xi_{i}(q)\\xi_{j}(q)q^{4}d q\n$$ \n\nusing the radial Fourier transform \n\n$$\n\\xi_{i}(q)=4\\pi\\int_{0}^{\\infty}j_{\\ell}(q r)\\xi_{i}(r)r^{2}d r.\n$$ \n\nThe cutoff energy error to be minimized for optimum convergence $\\langle\\varphi|\\hat{E}^{\\mathrm{r}}|\\varphi\\rangle$ can now be expressed as \n\n$$\n\\begin{array}{l}{{\\displaystyle{{\\cal E}}^{\\mathrm{r}}(q_{c})=\\langle\\varphi_{0}\\vert\\hat{\\cal E}^{\\mathrm{r}}\\vert\\varphi_{0}\\rangle+2\\sum_{i=1}^{N-M}y_{i}\\langle\\varphi_{0}\\vert\\hat{\\cal E}^{\\mathrm{r}}\\left\\vert\\xi_{i}^{\\mathrm{N}}\\right\\rangle}}\\\\ {{\\displaystyle~+\\sum_{i,j=1}^{N-M}y_{i}y_{j}\\left\\langle\\xi_{i}^{\\mathrm{N}}\\right\\vert\\hat{\\cal E}^{\\mathrm{r}}\\left\\vert\\xi_{j}^{\\mathrm{N}}\\right\\rangle}}\\end{array}\n$$ \n\nwhere $y_{i}$ are the coefficients of the $\\xi_{i}^{\\mathrm{N}}$ basis functions to be added to $\\varphi_{0}$ . The $y_{i}$ are subject to the norm constraint \n\n$$\n\\sum_{i=1}^{N-M}y_{i}^{2}=\\langle\\psi\\mid\\psi\\rangle_{r_{c}}-\\langle\\varphi_{0}\\mid\\varphi_{0}\\rangle_{r_{c}}.\n$$ \n\nStandard methods for minimizing Eq. (9) subject to Eq. (10) can be quite unstable. Instead, the positive-definite $E_{i j}^{\\mathrm{r}}$ matrix, the last term in Eq. (9), is diagonalized finding its eigenvalues $e_{i}$ and using its eigenvectors to form the new ‘‘residual’’ basis function set $\\{\\xi_{i}^{\\mathrm{R}}\\}$ as linear combinations of the $\\xi_{i}^{\\mathrm{N}}$ . When these functions are added to $\\varphi_{0}$ with coefficients $x_{i}$ to form $\\varphi$ , the residual energy takes the diagonal quadratic form \n\n$$\nE^{\\mathrm{r}}=E_{00}^{\\mathrm{r}}+\\sum_{i=1}^{N-M}\\left(2f_{i}x_{i}+e_{i}x_{i}^{2}\\right)\n$$ \n\nwhere $f_{i}=\\langle\\varphi_{0}|\\hat{E}^{\\mathrm{r}}\\left|\\xi_{i}^{\\mathrm{R}}\\right\\rangle$ . The $x_{i}$ satisfy the same norm constraint as the $y_{i}$ in Eq. (10)⏐. The $e_{i}$ span a very large dynamic range $\\sim$ $10^{6}–10^{8}$ , which may explain the difficulties in applying standard optimization procedures to Eq. (9). We next solve the constraint equation for $x_{1}$ , the coefficient corresponding to the smallest $e_{i}$ , as a function of x2, . . . , xN M : \n\n$$\nx_{1}=s\\Bigg[\\langle\\psi\\mid\\psi\\rangle_{r_{c}}-\\langle\\varphi_{0}\\mid\\varphi_{0}\\rangle_{r_{c}}-\\sum_{i=2}^{N-M}x_{i}^{2}\\Bigg]^{1/2}.\n$$ \n\nIts sign s is determined by the requirement that $f_{1}x_{1}$ be negative at the minimum. Setting the derivatives of $E^{\\mathrm{r}}$ with respect to $x_{2},\\ldots,x_{N-M}$ to zero using Eq. (12) for $x_{1}$ we find \n\n$$\nx_{i}=-f_{i}/(e_{i}-e_{1}-f_{1}/x_{1})~.\n$$ \n\nThe denominator in Eq. (13) is always positive, so the sum in Eq. (12) is a monotonically increasing function of $\\left|x_{1}\\right|$ starting from zero for $|x_{1}|=0$ , and Eq. (12) can be solved by a straightforward interval-halving search on $\\left|x_{1}\\right|$ [18]. The optimum $x_{i}$ are based on a prescribed $q_{c}$ . However, Eq. (9) can be evaluated for any cutoff $q$ using $y_{i}$ calculated from the $q_{c}$ -optimized $x_{i}$ , thereby providing a kinetic-energy-error per electron convergence profile. \n\nThe above procedure is applied to the first (lowest energy) projector $\\varphi_{1}$ in the two-projector generalized norm-conserving construction. For the second projector, the convergence-optimized $\\varphi_{1}$ is used to add the linear $\\left\\langle\\varphi_{1}\\right\\vert\\varphi_{2}\\right\\rangle_{r_{c}}$ overlap constraint to the continuity constraints of Eq. (6). The procedure continues as above, retaining the original spherical-Bessel-function basis set for convenience, and the coefficients are found determining the convergence-optimized $\\varphi_{2}$ . While there are only $N-M-1$ degrees of freedom for norm conservation and optimization, convergence profiles are usually quite comparable to those for $\\varphi_{1}$ . As the broad range of $\\hat{\\boldsymbol E}^{\\mathrm{r}}$ eigenvalues suggests, convergence improvements decrease rapidly as more degrees of freedom are added, and 3–5 invariably suffice. \n\nWhile it is observed that scattering states can be used as well as bound states to satisfy the generalized norm-conservation requirements and retain its resulting accuracy, they cannot be used in the optimization because the radial Fourier transform of such a $\\varphi$ is essentially a delta function of $q$ . To deal with this, an artificial all-electron bound state is created at each positive $\\varepsilon_{i}$ by adding a smoothly rising barrier to the all-electron potential beginning at $r_{c}$ . A satisfactory form is \n\n$$\nV_{\\mathrm{AEB}}(r)=V_{\\mathrm{AE}}(r)+\\left.v_{\\infty}\\theta(x)x^{3}/(1+x^{3});x=(r-r_{c})/r_{\\mathrm{b}},\\right.\n$$ \n\nwhere the height and shape parameters $v_{\\infty}$ and $r_{\\mathrm{b}}$ are chosen to bind a state with the appropriate number of nodes at $\\varepsilon_{i}$ and produce a decaying tail roughly comparable to those of the highest occupied bound states. The optimized convergence properties of the corresponding bound pseudo-wavefunctions are typically comparable to those of the valence functions [17,18]. \n\nThe symmetry of $B_{i j}$ and other consequences of general norm conservation are strictly true for pseudopotentials based on nonrelativistic all-electron calculations. Nonetheless, we have proceeded to apply them to scalar-relativistic [26] and fully relativistic calculations. \n\nIn these cases, a fractional asymmetry2 of $\\sim10^{-4}$ to $10^{-5}$ was found for both light and heavy atoms, so $B_{i j}$ was simply symmetrized before proceeding. This manifests itself in disagreements of comparable magnitude in comparisons of quantities such as eigenvalues and norms computed with the final pseudopotentials. In the fully relativistic case, the large component of the Dirac wavefunction is renormalized and only it is used to compute the Eq. (1) norms and overlaps and the matching constraints of Eq. (6). This yields errors comparable to the scalar-relativistic case, and an order of magnitude smaller than obtained using both components. \n\nRelativistic non-local pseudopotentials are generated as sums over total angular momenta $j=\\ell\\pm1/2,j>0$ , of terms $V_{j}^{\\mathrm{Rel}}(\\mathbf{r},\\mathbf{r}^{\\prime})$ like Eq. (3). While these may be used directly in some applications, most require potentials in the (schematic) form \n\n$$\nV(\\mathbf{r},\\mathbf{r}^{\\prime})=V_{\\mathrm{loc}}+\\sum_{\\ell}\\left[V_{\\ell}^{\\mathrm{SR}}(\\mathbf{r},\\mathbf{r}^{\\prime})+\\mathbf{L}\\cdot\\mathbf{S}V_{\\ell}^{\\mathrm{S0}}(\\mathbf{r},\\mathbf{r}^{\\prime})\\right],\n$$ \n\nwhere \n\n$$\n{\\cal V}_{\\ell}^{\\mathrm{{SR}}}=\\frac{(\\ell+1)V_{\\ell+1/2}^{\\mathrm{Rel}}+\\ell V_{\\ell-1/2}^{\\mathrm{{Rel}}}}{2\\ell+1},{\\cal V}_{\\ell}^{\\mathrm{S0}}=\\frac{2\\left(V_{\\ell+1/2}^{\\mathrm{Rel}}-V_{\\ell-1/2}^{\\mathrm{Rel}}\\right)}{2\\ell+1}\n$$ \n\nDirect use of these ‘‘scalar-relativistic’’ and ‘‘spin–orbit’’ potentials as sums and differences is both cumbersome and requires subtractions of many nearly equal quantities in applications, with the resulting inaccuracies. For these applications, ONCVPSP forms new projectors $\\big|\\tilde{\\chi}_{\\ell}^{\\mathsf{S R}}\\big\\rangle$ and $\\big|\\tilde{\\chi}_{\\ell}^{\\mathsf{S O}}\\big\\rangle$ from their eigenfunctions to create diagonal non-lo⏐cal opera⏐tors, some of whose eigenvalue coefficients are negligibly small. Either form can be selected. \n\n# 3. The PseudoDojo \n\n# 3.1. The PseudoDojo python framework \n\nThe PseudoDojo is a python framework for the automatic generation and validation of pseudopotentials. It consists of three different parts: (1) a database of reference results produced with AE and PSP codes, (2) a set of tools and graphical interfaces that facilitate the generation and the initial validation of the PSPs and (3) a set of scripts to automate the execution of the different tests in a crystalline environment (automatic generation of input files, job submission on massively parallel architectures, post-processing and analysis of the final results).3 \n\nThe database currently contains the reference all-electron results for the $\\varDelta$ -Gauge and the GBRV benchmarks as well as the structural parameters used in these tests. The PseudoDojo is presently interfaced with ONCVPSP. It provides a GUI to set up the input parameters and visualize the results of the comparison of the PSP to the atomic reference calculation, e.g. their logarithmic derivatives. In particular, series of PSPs can be generated for ranges of input parameters. Finally, after the initial ‘internal’ validation against the atomic reference calculation the implemented ‘external’ tests can be executed via AbiPy and ABINIT [27,28]. The currently implemented external tests include the $\\varDelta$ -Gauge, the GBRV tests, automatic convergence testing the evaluation of the acoustic modes at $\\boldsymbol{{\\Gamma}}$ within DFPT, and ghost state testing of the electronic structure up to high energies ( ${\\widetilde{\\mathbf{\\Gamma}}}{\\sim}200\\mathrm{eV}$ above the Fermi level). All of these can be executed fully automatically on various parallel architectures. New tests based on reference data for any observable that can be calculated with ABINIT can be added in a straightforward way. Interface to other DFT codes, additional tests, and other pseudopotential generators can be easily added as well. The table presented here is compatible with ONCVPSP 3.3.1 and higher and the external tests are all performed with ABINIT 8.4. \n\n# 3.2. The Dojo-report \n\nAn important aspect of the PseudoDojo is keeping track of the results of various validation tests. To this end, the PeudoDojo creates a report for each pseudopotential. This DojoReport is a humanreadable text document in JSON format,4 containing entries for each test. It is automatically produced by the python code at the end of the test. In addition to the raw data it contains the final results as function of $E_{\\mathrm{c}}$ . \n\nThe data in the report is in principle not intended for the ab-initio code.5 The main goal of the DojoReport is to keep a record of the different tests, so that it can be used by high-level languages (e.g. python) to read the data and produce plots or rank pseudopotentials associated to the same element according to some criterion. In addition, the information in the DojoReport can be used to set up high-throughput calculations. Finally, new validation tests can be easily added to the JSON document. \n\n# 3.3. The PseudoDojo web interface \n\nIn addition to the PseudoDojo python framework itself, the PseudoDojo provides a web-interface [29] for the on-line visualization of both the internal and external validations. The webinterface allows for a fast visualization of the test results for a particular pseudopotential, via the HTML version of the DojoReport generate automatically from a Jupyter Notebook [22], without having to install the python package. Both the pseudopotential files and the corresponding input files can be downloaded. The PSP table discussed in this work corresponds to the NC (ONCVPSP) PBE v0.4 table on the web interface. \n\n# 4. The PD-PBE tables \n\n# 4.1. General design principles \n\nDespite several significant improvements proposed in the literature [30,7,25,17,18], elements with localized d- or f-electrons are still difficult to pseudize within the NC formalism. For this reason, unlike other similar projects, e.g. the GBRV table in which all the ultrasoft pseudopotentials require an $E_{\\mathrm{c}}$ less than $20\\mathrm{Ha}$ [23] or the SG15 table [12], which is mainly focusing on efficiency, we do not make any attempt to generate an entire periodic table of NCPPs that converge below the same $E_{\\mathrm{c}}$ . Instead, we mainly focus on accuracy and transferability and attempt to tune the pseudization parameters so that elements with similar electronic configurations require similar $E_{\\mathrm{c}}$ to achieve convergence. \n\nIn this first version of the PseudoDojo we present and discuss the pseudopotentials for the GGA-PBE exchange–correlation (XC) functional [16]. For this functional well-tested sets of reference data are available. Pseudopotentials for the LDA-PW [31] and PBEsol [32] functionals are also available via the PseudoDojo web interface, reference values for these functionals are currently under development. PSPs for other semi-local XC functionals can be generated directly for most elements, especially since as of version 3.0 the ONCVPSP package is interfaced with the libxc library enabling well over $250~\\mathrm{{XC}}$ functionals [33]. For each flavor of exchange– correlation functional we define a standard and a stringent accuracy version. \n\nFor those elements in which the separation between core and valence is not obvious, we provide a version with and without semi-core electrons. As a rule of thumb, NCPPs with semi-core states are more accurate and transferable since the error introduced by the frozen-core approximation is reduced. Moreover, semi-core states may be needed for accurate GW calculations, in particular in those systems in which there is an important overlap between valence and semi-core electrons and therefore a significant contribution to the exchange part of the self-energy [34,35]. We adapt the notation, e.g. Fe-sp, to indicate additional semi-core states included in the valence. \n\nFor elements that show a particularly slow convergence in reciprocal space (e.g. transition metals) we also provide two different versions: normal and high. The default version, normal accuracy, is designed to give a good description of the scattering properties of the atom in different chemical environments with a reasonable $E_{\\mathrm{c}}$ . The high-accuracy version, with small core radii, requires a larger $E_{\\mathrm{c}}$ to converge but is more transferable and can be used for accurate first-principles calculations or for the study of systems under high pressure. The high accuracy version is also recommended for calculations in magnetic systems. \n\nIn special cases, discussed in Section 7, we also provide low accuracy pseudopotentials. We do this when the standard version converges only at cutoff energies higher than $40\\mathrm{Ha}$ . \n\nExcept for some noticeable exceptions listed in Table 1, all the PSPs of our tables contain two projectors per angular channel. This ensures a logarithmic derivative in close agreement with the AE counterpart up to at least $3{\\-}\\mathsf{-}5\\mathsf{\\ }\\mathsf{H a}$ . In many cases, we achieve agreement even up to $10\\:\\mathrm{Ha}$ . Further element specific details will be discussed in Section 7. \n\nIn general, we enforce the continuity of the derivatives of the pseudized potentials at $r_{c}$ up to the fourth order (M in Eq. (6), input parameter ncon $\\mathtt{\\Omega}=4$ ). This is done in order to avoid possible problems in the computation of elastic properties introduced by the RRKJ optimization technique (see also the discussion in Refs. [17,18]). Those pseudopotentials that deviate from this rule are listed in Table 2 and discussed in more detail in Section 7. A drawback of this additional requirement is that it usually leads to pseudopotentials that are slightly harder than the ones obtained by enforcing continuity up to the third order as it is commonly done. In general, we found that one can decrease the required $E_{\\mathrm{c}}$ by ${\\sim}5\\mathrm{{Ha}}$ if ncon $^{\\scriptstyle=3}$ (continuous derivatives up to third order) is used. \n\nTable 1 Number of non-local projectors in the s, p, d, and f channels. All other pseudopotentials are constructed using two projectors per angular channel. The highest nonlocal l projector is p of H–Mg (except for F and O where it is d), d for Al–Xe and Tl– Rn, and f for Cs–Hg except for Ba where it is d. \n\n\n
PseudoSPf
H2100
He2100
O-high2210
0210
F2 2210
Lanthanides2221
Au-sp2221
Hg-sp2221
\n\nTable 2 Order of the derivative of the pseudized potential that is still continuous. Only those pseudopotentials are listed that deviate from having continuity up to exactly the fourth-order derivative at the core radius for each angular channel (see Eq. (6)). \n\n\n
PseudoSd
In-spd54
In-d54
Ga-low33
Fe-sp3
Fe-sp-high3 33
\n\nIt is well known that nonlinear core corrections (NLCC) improve the transferability of pseudopotentials [36]. PSPs that do not include semi-core states usually improve the most. However, even when semi-core states are present, adding NLCCs has benefits. They remove the nonphysical oscillations of the local part close to the origin, oscillations which often appear in the case of gradientcorrected functionals when the total local potential is unscreened. These oscillations not only create problems if the potentials are represented in a non-planewave basis set but also tend to spoil convergence in Fourier and real space. \n\nIn PD-PBE, a NLCC is included in all the PSPs with electrons frozen in the core except for the third row semi-core PSPs (Na-sp–Cl-sp) and Ne. We use a recently implemented NLCC following Teter, which contains two parameters [37]. These model core charges are by construction smooth in both real and reciprocal space, which significantly improves convergence. Teter suggested to use these two parameters to minimize the difference between the chemical hardness of the pseudo and the AE wavefunction [37]. In constructing PD-PBE, however, we did not observe a clear correlation between the PSP quality (in reproducing AE results for crystalline test systems) and the level at which the pseudized wavefunction reproduces the AE chemical hardness. \n\nFrom a purely technical perspective, on the other hand, Teter’s model function allowed us to avoid numerical instabilities and convergence issues especially in the case of elements with localized AE core charges. Standard models, indeed, produce charges that are either too peaked and thus difficult to integrate on a homogeneous mesh in real-space or model charges with strong oscillations in the high-order derivatives required for DFPT calculations. This can spoil the convergence of the physical properties with the cutoff energy and have disastrous effects for density functional perturbation theory calculations, in particular for the fulfillment of the acoustic sum rule. This is the reason why we add a test in the PseudoDojo for the acoustic modes at $\\boldsymbol{\\Gamma}$ . Large deviations from zero (when the ASR is not enforced by the code) usually indicate that the model core charge and its derivatives cannot be correctly described with a sufficiently small cutoff energy and these inaccuracies will likely affect the phonon modes at other $q$ -points as well. \n\n# 5. Convergence and energy cutoff hints \n\nFor most elements, the options described in the previous section lead to several different PSPs. To assist users in selecting pseudopotentials, we define two tables: standard and stringent accuracy, both of which contain only one PSP per element. For about half the elements, the stringent table contains a different, more accurate, PSP than the standard table. In this and the next section, we evaluate the results of the convergence studies and the validation tests for these two tables. \n\nThe design of the PD-PBE allows for different required energy cutoffs $\\left(E_{\\mathrm{c}}\\right)$ for each pseudopotential. Moreover, different physical properties usually show a different convergence behavior with respect to $E_{\\mathrm{c}}$ . Typical examples are phonons and the bulk modulus, which are much more sensitive to the truncation of the PW basisset than, e.g., the total energy. It is however useful to have an initial estimate for the starting $E_{\\mathrm{c}}$ for the convergence study, both for ‘normal’ users and for high-throughput calculations (HTC). We therefore provide calculated high, normal, and low precision hints for $E_{\\mathrm{c}}\\colon E_{\\mathrm{c}}^{\\mathrm{h,n,l}}$ based on different tests.6 \n\nThe ONCVPSP code already provides initial hints for Ec based on the convergence of the electronic eigenvalues in the atomic environments $(\\epsilon)$ . We used these values to define an initial mesh of $E_{\\mathrm{c}}$ values (a dense sub-mesh with a step of $2\\mathrm{Ha}$ around the initial value provided by the PSP generator continued by a coarse mesh with a step of $10\\mathrm{Ha}$ to ensure absolute convergence). On this mesh, we use the PseudoDojo framework to compute the $\\varDelta$ -Gauge, the GBRV parameters, and the phonons at $\\boldsymbol{{\\Gamma}}$ as a function of $E_{\\mathrm{c}}$ . The final results as well as the total energies used for fitting the EOS curve are all saved in the DojoReport. \n\nThe hints are calculated according to the parameters specified in Table 3. Using the hint for one of the accuracies ensures that the absolute value of the indicated quantity is smaller than the indicated bound. $O^{c}$ indicates the converged value of observable O, which is obtained from the largest $E_{\\mathrm{c}}$ grid point. This point is initially $22~\\mathrm{Ha}$ higher than the high precision estimate given by ONCVPSP. All curves are however inspected manually to ensure convergence. In an automatic fashion, additional grid-points are added until a curve is approved with a converged tail.7 The hints are reported in the DojoReport of each PSP file and listed in the supplementary material. Fig. 1 summarizes the hints for the high and standard tables,8 Tables 4 and 5 report the statistics on the two tables. \n\n# 6. Discussion of the validation per table \n\n# 6.1. $\\varDelta$ -Gauge \n\nThe $\\varDelta$ -Gauge is defined as the integral over the difference between the equation of state curve calculated using two different computational approaches within a predefined volume range expressed in meV per atom [24]. The physical quantities that are related to the $\\varDelta$ -Gauge are the parameters of the Birch–Murnaghan equation of state: the equilibrium volume $V_{0}$ , the bulk modulus B, and the first derivative of the bulk modulus $B_{1}$ . It was introduced by Cottenier and coworkers in 2014 and presently already 24 data sets have been calculated. This large number of data sets, involving \n\n![](images/e9a4e5ddf92c4e0f02d4a15252848f0a4ecdd1aae44211594077090fdb284e60.jpg) \nFig. 1. Violin plot of the hints for the standard and stringent tables. \n\nTable 3 Criteria for the low, normal and high hints of PD-PBE. $\\epsilon$ indicates the maximal deviation among electronic energy (not used for the low hint criterion), $\\varDelta_{1}$ the revised $\\varDelta$ -Gauge as introduced in Ref. [38]. TE indicates the total electronic energy per atom obtained at the equilibrium volume defined in the reference equilibrium structure as given the $\\varDelta$ -Gauge benchmark. \n\n\n
ObservableUnitLowNormalHigh
-EAE(mHa/electron)-<1<1
△1-A(meV)<2<1<0.5
TE-TEC(meV/atom)<10<5<2
\n\nTable 4 Statistics on the low, normal and high hints for the standard table. The cutoff energies are in Hartree. \n\n\n
ZvallmaxEE
Count72.0072.0072.0072.0072.00
Mean12.002.0332.7437.2543.36
Std5.240.567.697.778.13
Min1.001.0014.0018.0024.00
25%8.002.0028.7533.0038.75
50%13.002.0033.5038.0044.00
75%16.002.0038.0042.0048.25
Max25.003.0050.0055.0065.00
\n\nTable 5 Statistics on the low, normal and high hints for the stringent table. The cutoff energies are in Hartree. \n\n\n
ZvallmaxEEE
Count72.0072.0072.0072.0072.00
Mean14.002.0337.5742.1748.22
Std6.850.5610.9010.8510.92
Min1.001.0014.0018.0024.00
25%8.752.0031.7536.0042.00
50%14.502.0037.5042.0048.00
75%19.252.0045.2550.0056.00
Max27.003.0062.0066.0072.00
\n\n![](images/2fa127cdb30e52085f51328d37c2016ff632422a77368361041286613f6c5d3d.jpg) \nFig. 2. Violin plot of the distribution of $\\varDelta$ values calculated at the low, normal, and high hints. The outliers, occurring at about 10.4, 7.7, and 5.9 for each $E_{\\mathrm{c}}$ hint in the standard table, are Cr, Mn, and Fe respectively. \n\n13 different codes (including 5 AE codes), makes the $\\varDelta$ -Gauge very useful in the validation of PSPs [1]. To test a PSP, one compares the results calculated using a PSP with those calculated using a reference AE code. The $\\varDelta$ -Gauge averaged over the periodic table between the most reliable AE data sets is around $0.1{-}0.3\\ \\mathrm{meV}.$ . In this work, we use Wien2k results as a reference from the 3.1 version of the Delta calculation package [1]. The average $\\varDelta$ -Gauge, with respect to the Wien2k results, of the NCPP tables included in Ref. [1] is 1.4.9 The drawbacks of the $\\varDelta$ -Gauge are however that the prescribed computational settings for the calculation are rather stringent making it unsuitable for fast pre-testing. Moreover, only single element compounds are included and only ground state properties are tested. \n\nFig. 2 summarizes the results of the $\\varDelta$ -Gauge tests for the standard and stringent tables. A full table of the results per PSP is available in the supplementary information. For the $\\varDelta$ -Gauge test, the most significant difference between the two tables is confined to three elements: Cr, Mn, and Fe. For these elements the structures used in the $\\varDelta$ -Gauge test are magnetic. To resolve the magnetic structure a harder PSP is needed. When we exclude these three elements the mean $\\varDelta$ -Gauge are 0.70 and 0.64 for the standard and high tables. \n\nThe design of the $\\varDelta$ -Gauge is such that elements for which the bulk modulus is very soft are hard to test. The noble gas solids for instance always have a low $\\varDelta$ -Gauge. To remedy this, Jollet et al. have introduced a renormalized version of the $\\varDelta$ -Gauge: the $\\varDelta^{\\prime}$ -Gauge [38]. For the latter, a value less than 2 in general indicates an accurate potential for ground state structural properties. Fig. 3 summarizes the results of the $\\varDelta^{\\prime}$ -Gauge tests for the standard and stringent tables. In addition to what we have learned from the $\\varDelta$ -Gauge, the $\\varDelta^{\\prime}$ -Gauge shows that Hg, Sr, and Ba are problematic elements. Their $\\varDelta^{\\prime}$ -Gauge values, 7.2 (6.4), 6.1 (6.2), and 5.0 (4.8) respectively (stringent in brackets), are relatively high. We did not manage to create high accuracy versions that have a significantly better $\\varDelta^{\\prime}$ -Gauge. \n\nFor both the standard and stringent tables, Figs. 2 and 3 indicate that the low and normal hints already result in a converged $\\varDelta$ -Gauge and $\\varDelta^{\\prime}$ -Gauge. This is made clear in Fig. 4, which shows the errors at low and normal $E_{\\mathrm{c}}$ hint with respect to their converged values at the high hint. A similar convergence is observed for the equilibrium volume $V_{0}$ . The outlier in $V_{0}$ is Ne. Since the bulk modulus of the solid state structure of Ne is however very small, the equation of state curve is very flat (the total energy changes less than 1 meV over the volume changes in the $\\varDelta$ -Gauge calculations). This is a generic feature for all the crystal cases where the energy landscape is flat. This is thus not a problem of PSP but of the system. As a result, an error in $V_{0}$ does not affect the $\\varDelta$ -Gauge significantly. \n\n![](images/031c50b1df92afe165cdf3717b32a35524b8a6bcb77f5e4e3a456d07bc011b47.jpg) \nFig. 3. Violin plot of the distributions $\\varDelta^{\\prime}$ -Gauge values calculated at the low, normal, and high hints. Again Cr, Mn, and Fe are outliers in the standard table. In addition Hg (6.4), Sr (6.1), and Ba (5.0) appear as outliers also in the stringent table. \n\n![](images/8108bfd57a8ff4a9b527f38399b1d1e55a161aaf5aae7cc36dc19890affedcce.jpg) \nFig. 4. Violin plot of the distribution of the error in $V_{0}$ and $a_{0}$ and $\\varDelta$ -Gauge at the low and normal hint as compared to their values at the high hint. The outlier in $V_{0}$ is Ne, the negative outlier in $\\varDelta$ -Gauge is Al, and the positive outlier in $\\varDelta$ -Gauge is Se-spd. \n\nFig. 5 shows that the convergence of $B$ and $B_{1}$ is a factor of 10 to 100 slower than that of $V_{0}$ and the $\\varDelta$ -Gauge itself. \n\n# 6.2. The GBRV dataset \n\nComplementary to the $\\varDelta$ -Gauge test we also perform the GBRV test on the two tables [23]. The GBRV tests consist of two parts. In the first test, the optimal lattice parameter of FCC and BCC single element structures are compared to AE reference values. In the second test, the lattice parameters of rocksalt, half-Heusler and perovskite structures are compared. Reference values for noble gas FCC and BCC structures are however not present. We confirm the observation of Garrity et al. that the FCC and BCC results show a strong correlation, see Section 6.5. We hence only discuss here the FCC results. The noble gases are not present in the GBRV tests since the FCC and BCC structures do not bind in GGA-PBE. \n\n![](images/8f4daf4a12a7e70c3793a1e8a7d1787c0c0b1c63bed2f025ef4ec2d743985435.jpg) \nFig. 5. Violin plot of the error in B and $\\mathbf{B}_{1}$ at the low and normal hint as compared to their values at the high hint. The large negative outlier is $\\mathsf{N e}$ and the positive outlier is Mg. \n\n![](images/64c741956c29ad230645cb21b8aaef1d49b95fcdd08fac28f00fc4a593d7b07e.jpg) \nFig. 6. Violin plot of the relative error on the lattice parameter of the GBRV test set. \n\nIn contrast with the $\\varDelta$ -Gauge test, the GBRV test has only been performed once using an AE-code. We hence do not have a well established error bar on the reference values as we have for the $\\varDelta$ -Gauge test. Optimally, the test will be run with another AE-code at some point in the future. \n\nFig. 6 summarizes the distribution of the relative errors of the lattice parameter of the FCC GBRV test. Also for the GBRV test, we observe that both the low and normal hints already provide rather converged results, see also Fig. 4. In contrast to the $\\varDelta$ -Gauge tests, however, the stringent table does not significantly improve the GBRV test results. This difference mostly relates to the fact that the GBRV tests do not contain any magnetic systems whereas the $\\varDelta$ -Gauge tests do. In the $\\varDelta$ -Gauge tests we observe the strongest difference between the standard and stringent tables for magnetic systems. Finally, we observe that in the GBRV tests the NCPPs tend to underestimate the lattice parameter with respect to the AE reference. The same trend is observed for the PAW data sets that have performed the GBRV tests [23,38]. \n\nTable 6 GBRV average errors (relative error in $\\%$ in the lattice parameter) per compound group as compared to the GBRV-PAW, GBRV-USPP, pslib, and VASP results [23]. \n\n\n
GBRV PAWGBRV USPPpslibVASPThis
AB030.0890.0780.2000.1270.185
hH0.1260.1110.1440.1400.116
Rocksalt0.1290.1210.2160.1500.184
\n\nTable 7 The outliers (relative error larger than $0.25\\%$ ) in the GBRV compound tests. The columns list the lattice parameter of the conventional cell in Angstrom. \n\n\n
FormulaAEGBRV PAWGBRV USPPpslibVASPThis
CdPLi5.9695.9575.9555.9455.9525.946
SrHfO34.1554.1414.1484.1334.1464.140
LiAuS6.0155.9955.9946.0085.9935.993
HfO4.6114.5864.5964.5744.5844.594
LiF4.0764.0764.0744.0814.0674.062
KNiF34.0394.0354.0364.0374.0364.026
VO4.1924.1894.1904.1924.1914.180
NaCl5.7145.7025.7015.6965.7015.698
Lil6.0386.0236.0206.0306.0216.021
SrLiF33.8843.8833.8813.8843.8843.873
KZnF34.1324.1344.1334.1304.1394.121
SrTa034.0664.0704.0674.0504.0674.055
Sr0s033.9823.9793.9833.9863.9923.972
CaO4.8394.8344.8344.8284.8424.826
\n\nBesides the FCC and BCC elemental structures the GBRV reference data also contains 63 rocksalt structures, 54 half-Heusler structures (hH), and 138 perovskites $(\\mathsf{A B O}_{3})$ . The presence of these multiple-element systems allows for a real test of transferability. A full account of the GBRV compound test is given in the supplementary material. The stringent-table results do not differ significantly from the results obtained for the standard table. We therefore discuss here only the latter at normal $E_{\\mathrm{c}}$ hint. Table 6 compares the performance of our standard table to that of various existing PAW data sets and USPP tables. Clearly, all tables are of similar accuracy. Within the distribution, PD-PBE does not perform best but it also does not perform worst in any of the structure types. \n\nTo investigate if the PSP for one specific element is performing badly in the GBRV compound test we summarize the results per element in Fig. 7. We observe that our PSPs tend to slightly underestimate the AE lattice parameters although the distribution of our relative error is quite symmetric and peaked around the mean value. The other tables also tend to underestimate the AE reference but some with broader distribution. The elements that stand out most in the FCC and BCC tests F, S, and K also stand out in the compound test. Cs and Rb on the other hand perform better in the compounds than in the single element tests. \n\nFinally, in Table 7 we list those systems in the GBRV compound tests that have an error of more than $0.25\\%$ with respect to the AE reference. \n\nA general observation over all GBRV tests is that the elements that show larger deviations in our NCPP table like F also stand out in the PAW tables [23,38]. This seems to suggest that the error originates from the freezing of the core rather than from pseudizing the valence electrons. However for the most problematic elements, F, S, Cs, Rb, and K adding additional states to the valence partition turned out to be very difficult. \n\n# 6.3. Ghost state detection \n\nThe separable non-local operator that enters the pseudo Hamiltonian can lead to eigenstates for a given quantum number l which are not ordered in energy by the number of nodes. As a result, eigenstates with nodes can appear with energies below the nodeless eigenstate, or the nodeless state can be followed directly by states with more than one node [39,40]. The second projector in the ONCVPSP scheme is usually very efficient in removing these so-called ghost states in the occupied and low energy unoccupied energy range. The eventual appearance of ghost states at higher energies is, however, unavoidable. Since we aim at generating PSPs that can be used also to calculate properties requiring an accurate description of the unoccupied region, i.e. optical properties or GW calculations, we explicitly test our PSPs for the presence of ghost states. This is done in the elemental solids by scanning the band structure and the density of states for dispersionless states, up to energies around $200\\:\\mathrm{eV}$ above the Fermi level. Ghost states could be removed in many cases by tuning the position of the second projector. Also, the addition of more semi-core states was found to improve the quality of the logarithmic derivative at high energies. Table 8 lists those PSPs that even after careful optimization of the input parameters still contain ghost states in the first $200~\\mathrm{eV}$ of unoccupied space and lists the ‘ghost-free’ alternatives. \n\n![](images/4cad55a3c0e59bbd9cda9558013d75a8d508d10c38b5e557676a3c306219d1f8.jpg) \nFig. 7. GBRV compound tests error per element. \n\nTable 8 Pseudopotentials that have a ghost state present in the first $200\\:\\mathrm{eV}$ of unoccupied space. ϵ gives the energy (eV) at which the ghost appears. Alt PSP provides the high-accuracy alternative that does not show any sign of ghost states. \n\n\n
PSPEAlt PSP
Mg84Mg-sp
Cd74Cd-sp
Sn-d60Sn-spd-high
Sb-d10Sb-spd-high
Te-d77Te-spd-high
Hg66Hg-sp
Tl-d65Tl-spd-high
Pb-d77Pb-spd-high
Bi-d66Bi-spd-high
Po-d59Po-spd-high
\n\nNote that the ghost states listed here are all so high in energy that for ground state calculations they do not cause any problem. Only for applications that require an accurate description of the unoccupied space as well (like GW and optical properties), do the nonphysical resonances introduced by the ghost states lead to incorrect results. \n\n# 6.4. Phonon modes at $\\boldsymbol{\\Gamma}$ \n\nCalculating the phonon modes at $\\boldsymbol{{\\Gamma}}$ allows for the evaluation of two useful quantities even when no reference values are available. First, it allows for an evaluation of the rate of convergence of the optical modes. Second, evaluating how strongly the acoustic sum rule is broken for the acoustic modes provides another test for the PSPs. \n\n![](images/3920f63237e19951e554f8bcf2b353628b1a81c0cfc39bd582f7964addb143ef.jpg) \nFig. 8. Violin plot of the distribution of the relative errors in the highest optical phonon (HOP) and lowest optical phonon (LOP) at $\\boldsymbol{{\\cal T}}$ at the low and normal hint as compared to their values at the high hint, after enforcing the acoustic sum rule. \n\nThe convergence of the optical phonon modes is illustrated in Fig. 8. In contrast with properties like the equilibrium volume and the $\\varDelta$ -Gauge the phonon modes are by far not converged at the low $E_{\\mathrm{c}}$ hint. \n\nThe breaking of the acoustic sum rule (ASR) is shown in Fig. 9, except for a few outliers the error remains within $2~{\\mathsf{c m}}^{-1}$ . We note that, although only slightly, the error is larger in the stringent table than in the standard table. This is caused by the harder pseudopotentials. All of the values obtained are easily corrected by standard techniques for imposing the ASR. \n\n# 6.5. Correlations between the tests \n\nPerforming different tests makes sense provided the results do not correlate strongly. To investigate the correlation between the different tests, the correlation matrix between the GBRV FCC and BCC, $\\varDelta$ -Gauge, $\\varDelta^{\\prime}$ -Gauge, and the absolute error in the acoustic sum rule for the phonon mode is shown in Fig. 10. \n\nAs indicated above, the FCC and BCC GBRV tests show a very strong correlation which means that performing both does not add additional information. $\\varDelta$ -Gauge and $\\varDelta^{\\prime}$ -Gauge also show some correlation, as expected, but considering both still adds information. The GBRV tests and the two $\\varDelta$ -Gauge test on the other hand hardly show any correlation. The error on the acoustic phonon modes finally seems to be completely decoupled from all other tests. \n\n![](images/c116cb6e9f1df169c7d206ed997d6f9d1d78bcfecf05c8323b96a89e6bda53c9.jpg) \nFig. 9. Violin plot of the distribution of the absolute errors in the highest acoustic phonon (HAP) and lowest acoustic phonon (LAP) at $\\boldsymbol{{\\cal T}}$ not enforcing the acoustic sum rule. The outliers are Ne $(\\sim14)$ , Mg $(\\sim11)$ , Na $(\\sim6)$ , Ge $(\\sim4)$ , an $\\operatorname{Cu}\\left(\\sim4\\right)$ all in $\\mathsf{c m}^{-1}$ . \n\n# 7. Discussion of individual pseudopotentials \n\nIn the figures presented in this section the $\\prec$ and $>$ symbols indicate that a specific PSP is part of the standard or stringent table respectively. \n\n# 7.1. H, He \n\nThe 1s wavefunctions in H and He are rather localized. One should therefore exercise special care to find values for the pseudization radii that give a good compromise between accuracy and efficiency. In H the pseudization radius for the 1s is set to 1.0 a.u. and 1.25 a.u. in He. Both PSPs contain two s projectors. \n\nThe p orbitals in H and He are not bound in GGA-PBE hence we use only one projector for the p channel. The main test results for the H and He pseudopotentials are shown in Fig. 11. \n\n# 7.2. Li, Be \n\nIn Li and Be, the 1s states are more localized than in H and He and the p orbitals are bound. We include the 1s electrons in the semicore, which yield PSPs that are more transferable and accurate, at the price of a non-negligible increase in the $E_{\\mathrm{c}}$ , see Fig. 12. For this reason, the PD-PBE provides two versions for elements. The standard version uses a s channel cutoff radius of 1.4 a.u. for Li and 1.35 a.u. for Be with an indicative $E_{\\mathrm{c}}$ of $35~\\mathrm{Ha}$ and $42\\ \\mathrm{Ha}$ , respectively. The local part of the PSPs is obtained by pseudizing the AE potential and two projectors both for s and p. The high accuracy versions mainly differ from the standard ones in the use of smaller $r_{c}$ for the s channel (1.2 a.u.. both for Li and Be) and, consequently, have a slower convergence in reciprocal space. \n\n![](images/d0623a1335200cdc51404b3f3f7a31b45d694c529cf4c935f93b6a3814609daa.jpg) \nFig. 10. Correlation between the results of the tests in the PseudoDojo including all PBE pseudopotentials. FCC and BCC denote the relative errors in the lattice parameters of the GBRV tests, the $\\varDelta$ -Gauge and $\\varDelta^{\\prime}$ -Gauge are the test from the Delta calculation package tests and ASR the absolute error in the first acoustic mode. The diagonal shows the distribution of the test results using the $x$ -axis of that column and an arbitrary $y$ -axis scale. \n\n![](images/72199a8d17f19b688e3a688e9d4f8a02063ff851e2c3601ad84ea0d1876d9a73.jpg) \nFig. 11. The main test results for H and He PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. The noble gases are not present in the GBRV tests since the FCC and BCC structures do not bind in GGAPBE. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/521638bacdf31232c4959ecaf77ff6f706db07b3bc828e4a1590c505e9d54d45.jpg) \nFig. 12. The main test results for Li and Be $\\mathsf{P S P s}$ . The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n# 7.3. B, C, N, O, F, Ne \n\nIn this set of elements, the 1s states are in the core, and the $E_{\\mathrm{c}}$ is governed by the spatial localization of the 2p states. The choice of $r_{c}$ for the p channel has therefore a significant impact on the transferability of the PSPs. We use two projectors per angular channel and a pseudized version of the AE potential as local part. The maximum angular momentum explicitly included in these PSPs is the $\\mathfrak{p}$ channel, $l_{m a x}=1$ . For O and F in addition a single d projector is added to improve transferability. An overview of the evolution of the main test results for these PSPs is shown in Fig. 13. \n\nF is one of the elements for which the GBRV tests show the largest error. This is also observed in the PAW tables that have been tested with the GBRV test. In addition it is observed that the F PSPs perform badly in describing atomization energies or molecular systems [41]. \n\n![](images/e1d9b8c61d4097f738d542fb95074d3c8dd2922f6b5bf06e14af9a0cc173f082.jpg) \nFig. 13. The main test results for B to Ne PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\nNe is one of the few elements with frozen core states for which adding non-linear core corrections does not improve transferability. The AE core is rather localized and therefore difficult to model without spoiling convergence. Especially the equation of state curves obtained in the $\\varDelta$ -Gauge calculations tend to be far from the reference curves. Moreover, solving the electronic selfconsistency problem turned out to be unstable for many of the model core charges tried. \n\n# 7.4. Na, Mg \n\nIn both PSPs with 2s and 2p in the valence no non-linear core corrections are applied. As for Ne, the very strong localization of the 1s core makes creating a transferable model core charge very complicated. Adding the 2s and 2p significantly improves both the $\\varDelta$ -Gauge and GBRV test results. In addition, for $\\mathtt{M g}$ , the ghost state at around $80\\mathrm{eV}$ is removed test results, see Fig. 14. \n\n# 7.5. Al, Si, P, S, Cl, Ar \n\nIn this series the 2s, 2p and 3s states are full and the 3p orbitals are gradually filled. The shell with $\\ n\\ =\\ 2$ is well separated from the $n=3$ electrons and can be safely frozen in the core. Moreover the 3s and 3p electrons are rather delocalized and their pseudization does not pose any problem in the NC formalism. For these elements, it is common practice to include d projectors in order to improve the transferability, see Fig. 15. \n\nFor the purpose of convergence studies and the comparison to AE results we also provide a version with 2s and $2{\\tt p}$ in the valence for this series of elements. The high $E_{\\mathrm{c}}$ required for these PSPs and non-systematic accuracy improvement make them however hardly useful for standard application. They are therefore not part of the stringent table. \n\n# 7.6. K, Ca \n\nThe default versions for these two elements have the 3s and 3p in the valence and contain two d projectors to improve transferability. Given the reasonable $E_{\\mathrm{c}}$ hints and the good test results, see Fig. 16, these are part both of the standard and stringent table. \n\n![](images/19b599bc6a65ab6e0c6af9fd944e76f48f2c87f02e09b83af6920884a8892d76.jpg) \nFig. 14. The main test results for Na and Mg PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/09f47a7f04c613c852e7b98e6a2613976abb9d5b68957a7fca661c897d2664d8.jpg) \nFig. 15. The main test results for the Al to Ar PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/b9a316e29ed15780cbad860177450199f2ffd21a03df64c2c4bb003d680a33c3.jpg) \nFig. 16. The main test results for the K and Ca PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/ef8a4b7ca2f4b54784ebee90467eb23e61ae6a83e80e947b204309bdfcc94a66.jpg) \nFig. 17. The main test results for the 3d transition metal PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n# 7.7. 3d transition metals \n\nFor the 3d transition metals, the 3s and 3p states are part of the valence partition. For both Fe PSPs, the degree of continuity at the pseudization radius was lowered to the third derivative. Generation a PSP for Fe with continuous derivatives up to fourth order at the pseudization radius leads to prohibitively large requirements on the $E_{\\mathrm{c}}$ . \n\nThe most complicated elements in this series are Cr, Mn, and Fe. Especially obtaining a PSP that performs well in the magnetic structures of the $\\varDelta$ -Gauge test is very hard. The standard versions, with a still reasonable $E_{\\mathrm{c}}$ hint, have $\\varDelta$ -Gauge results that are well beyond what is usually considered acceptable (see Fig. 17). The high accuracy version fixes this, however at the cost of a considerable increase in the $E_{\\mathrm{c}}$ needed. Both the standard and the high versions, however perform equally well in the (non-magnetic) GBRV tests. Special care has hence to be taken when selecting a PSP for these elements. It is suggested to double-check the final results obtained with the standard PSP with those coming from the stringent version. \n\n# 7.8. Ga, Ge, As, Se, Br, Kr \n\nIn these elements, the 3d shell is full and we have a progressive filling of the 3p states. The 3d electrons, however, overlap with the 3p states and therefore can play a role in determining the physical properties of a crystalline system. For this reason, our standard table contains pseudopotentials with 3d electrons in valence for Ga, Ge, As, Se, while 3d electrons are frozen in Br and Kr. This is our recommended configuration albeit the presence of the localized 3d states leads to a relatively large $E_{\\mathrm{c}}$ , see Fig. 18. A version of Ga–Ge– As–Se with the 3d electrons frozen in the core is also available for low $E_{\\mathrm{c}}$ applications. \n\n![](images/e29b8804e6585c4ef4502f5f1c097794b3a0ddb571f311ee6257d81babed49e0.jpg) \nFig. 18. The main test results for the Ga to Kr PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\nFor Br (and as well for I) we also provide a version with 3s, 3p, and 3d (4s, 4p, 4d for Iodine) in the valence. These are provided mainly for the use in accurate GW calculations in which the inclusion of entire electronic shells can be important, see e.g. Ref. [42] for the example on I. For ground state calculations the 3d (4d) valence has been found to be sufficiently accurate and is therefore the choice for the stringent table. \n\n# 7.9. Rb, Sr \n\nThe main test results and $E_{\\mathrm{c}}$ hints for the PSPs for Rb and Sr are shown in Fig. 19. For both elements, very reasonable $E_{\\mathrm{c}}$ hints can be achieved. The alkaline elements from Rb downward start to show a decreasing performance in the GBRV test. As for F and S, this is in line with the results obtained for PAW data sets in the GBRV tests. Attempts to make harder, more accurate PSPs did not lead to improved GBRV results. \n\n# 7.10. 4d transition metals \n\nThe PSPs for the 4d transition metals all contain the 4s and 4p states in the valence. This leads to both reasonable $E_{\\mathrm{c}}$ energies and test results, see Fig. 20. Only Ru and Rh have $\\varDelta$ -Gauge results that are only barely acceptable. The $\\varDelta^{\\prime}$ -Gauge results for these two PSPs (1.5 and 2.2) are still well within the acceptable range. The relatively high bulk modulus of these two elemental solids (310 and 250) causes the high $\\varDelta$ -Gauge values. For Cd, finally, we provide three versions. The version with the 4s and 4p states in the core (Cd) gives the best results for the $\\varDelta$ -Gauge but the GBRV is far from ideal. Including the 4s and $\\mathsf{4p}$ states in the valence (Cd-sp) improves the GBRV results at the price of a non-negligible increase of $\\dot{E}_{\\mathrm{c}}$ while the $\\varDelta$ -Gauge worsens. Decreasing the core radius in the high-accuracy version (Cd-sp-high) leads to acceptable GBRV and $\\varDelta$ -Gauge results but at the cost of a larger $E_{\\mathrm{c}}$ . Our standard table includes Cd-sp while the stringent table uses Cd-sp-high. \n\n![](images/e90819207a27d23e9c55659ee8829d75a09c2e2c78b55162ae5f6c5eea565c32.jpg) \nFig. 19. The main test results for the Rb and Sr PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/9abaa7306fb698afed3d1d15c77599e1f0fc278729f031bf83c6dc67d70e9dbe.jpg) \nFig. 20. The main test results for the 4d transition metal PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n# 7.11. In, Sn, Sb, Te, I, Xe \n\nIn the series from In to I, we provide three different versions of core-valence partitioning: no $n=4$ states in the valence (except for In), 4d in the valence, and the full $n=4$ shell in the valence. For all these pseudopotentials $\\varDelta$ -Gauge, $\\varDelta^{\\prime}$ -Gauge and GBRV are well within the acceptable range. The main difference lies in the description of the unoccupied space. The PSPs for which all $n=4$ states are frozen in the core show deviations in the logarithmic derivative starting around $3\\mathrm{\\:Ha}$ above the Fermi level. Including the 4d, which lie 0.7–1.5 Ha below the Fermi level, introduces ghost states in the elemental solid between 20 and $80\\mathrm{eV}$ above the Fermi level. Finally including the full $n=4$ shell we see no sign of ghost states and the logarithmic derivatives agree well up to $7-10~\\mathrm{Ha}$ above the Fermi level. The cost for this accuracy is an increase in $E_{\\mathrm{c}}$ of 20–30 Ha, see Fig. 21. \n\n![](images/e5971016202bcdb37dd63dff11debf960ad05d1250e3546b66fe7370236129b3.jpg) \nFig. 21. The main test results for the In to Xe PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\nFor Xe we freeze the full $n=4$ shell. The tests did not reveal any ghost states but the logarithmic derivative shows a sharp deviation around $4\\:\\mathrm{Ha}$ above the Fermi level. A version with the full $n=$ 4 shell in the valence is also available but not included in our recommended tables. \n\n# 7.12. Cs, Ba \n\nThe pseudopotentials for Cs and Ba both have the 5s and 5p states in the valence. For Cs, the transferability could be improved by adding explicit f projectors. For Ba, also a PSP is provided based on a reference state in which a 6s-electron is excited to the 5d-state. This version improves the $\\varDelta$ -Gauge results but at the same time worsens the GBRV test results to a similar degree, see Fig. 22. \n\n# 7.13. 5d transition metals \n\nFor the 5d transition metals we observed that including only the 5d in the valence led to PSPs that sometimes have good test results for $\\varDelta$ -Gauge and GBRV but tend to have ghost states only a few eV above the Fermi level. For this reason, we always include the 5s and 5p in the valence partition. \n\nAn additional difficulty in the series of the 5d transition metals is that in PBE the 4f states lie in the same energy range as the 5s and 5p states. For Hf and Ta, the 4f even lie above the 5p states. Indeed for Hf the agreement with the AE reference for both the $\\varDelta$ -Gauge and GBRV tests improves significantly if, besides the 5s and 5p also the 4f is taken into the valence partition, see Fig. 23. For Ta, this still improves the $\\varDelta$ -Gauge results significantly but the GBRV results worsen. For W the changes are rather small. \n\nFor all PSPs for the 5d transition metals it turned out to be beneficial to include explicit f-projectors even when the 4f electrons are frozen in the core. \n\nFinally, we note that, although for ${\\mathsf{W}}{\\mathrm{-Hg}}$ the ground state properties can be described well enough with the 4f frozen, for optical properties and GW this may not be the case. This is the case even for elements like Au where the 4f electrons lie about $3\\mathrm{\\:Ha}$ below the Fermi level. \n\n![](images/962e8ac54e01557496a72cd10788da96a3b1dc8e393a9c2d974ea7a66c4e790d.jpg) \nFig. 22. The main test results for the Cs and Ba PSPs. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/0e0d092d9cb01526f2b515a81c5ab20283a63cd8ad63f84efe536f659b7ed7d7.jpg) \nFig. 23. The main test results for the 5d transition metal PSPs. GBRV reference data is not available for Lu and Hg. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\n# 7.14. Lanthanides \n\nIn crystalline systems the lanthanides usually occur in the $^{3+}$ oxidation state with three electrons donated to an anion. Typical examples of lanthanides with $^{3+}$ oxidation state are given by their nitrides. Since in standard KS theory, GGA or LDA, the strongly localized f states are not described correctly, these $^{3+}$ pseudopotentials with 4f electrons frozen in the core offer a convenient solution. They are all generated with the valence configuration: $5s^{2}5\\mathsf{p}^{6}5\\mathsf{d}^{1}6s^{2}$ . It should be stressed, however, that these pseudopotentials are supposed to be used only if the f electrons are not important in the physics of the crystal (e.g. magnetism, bonding, etc.). These PSP will be mostly useful when only the steric effect of the lanthanide is of importance. Due to this limitation the lanthanide PSPs are not part of the predefined tables standard and stringent. PSPs for lanthanides with 4f states in valence are currently being developed but testing these correctly is a topic on its own and will be presented elsewhere. \n\n![](images/4828c7742b8b07456a23b7a0215a5752b9d40cf4b1ea7e67f078572094ba65d0.jpg) \nFig. 24. Lattice parameters of the nitrides of the lanthanide series. Comparison of PD-PBE to VASP results obtained with comparable PAW data sets. For reference also the experimental results are shown. \n\n![](images/77f880fa40e69009380f831744f022dad8ffac924a674a4d59fbb26f451c0729.jpg) \nFig. 25. The main test results for the $\\ensuremath{\\mathrm{~\\boldmath~{~\\cal~T}~l~}}$ to Rn PSPs. GBRV reference data is not available for Po and Rn. The blue, green, and red data are calculated at the high, normal, and low $E_{\\mathrm{c}}$ hints respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\nFor La, GBRV reference results are available, our La-sp PSP underestimates the BCC lattice parameter by $0.1\\%$ , no $\\varDelta$ -Gauge reference is available for La. For Lu the availability of reference results is opposite; we find a $\\varDelta$ -Gauge of 1.0 for our Lu-fsp, Lu is the only exception where the 4f is included in the valence. The hints we derive for these two elements based on the convergence of these tests are 50, 55, and 65 and 46, 50, and $58\\mathrm{~Ha}$ (low, normal, high) for La and Lu respectively. \n\nFor the other lanthanides, no GBRV or $\\varDelta$ -Gauge reference data are available. The PSPs presented here are therefore tested by comparing the relaxed lattice parameters of their nitride rock salt structures with those obtained from PAW calculations. Fig. 24 compares the lattice parameters obtained using our PSPs to those obtained using VASP [43] with comparable $^{3+}$ PAW data sets.10 \n\nIn general we observe a very decent agreement between the PD-PBE and the VASP results. Moreover, comparing to the experimental results we conclude that for the structural properties of rocksalt nitrides, the 4f states of Sm–Lu can indeed be frozen in the core. \n\n# 7.15. Tl, Pb, Po, At, Rn \n\nFor the final set of elements, Tl–Rn, the pseudization of 6p valence electrons is not very demanding. We provide versions with the 5d in the valence in the standard table and versions with 5s and 5p in the valence as well in the stringent table. Both for the $\\varDelta$ -Gauge and GBRV tests the results are good and also converge quickly, see Fig. 25. \n\n# 8. Conclusions \n\nIn this paper we have presented the PseudoDojo project, a framework for developing, testing and storing pseudopotentials, and discussed our PD-PBE: an 84 element table of PBE normconserving pseudopotentials. The PseudoDojo is interfaced with ONCVPSP [17,18] to generate the PSPs and ABINIT [27,28] via the AbiPy package for running the tests. The PSP files are available on the PseudoDojo web-interface at www.pseudo-dojo.org in the psp8, UPF2, and PSML 1.1 formats. \n\nThe PseudoDojo toolkit contains a graphical interface to the ONCVPSP [17,18] code. It enables the generation of (series of) pseudopotentials and the preparation of tests. \n\nThe validation part of the PseudoDojo consists of a series of 7 tests in crystalline environments: $\\varDelta$ -Gauge [24], $\\varDelta^{\\prime}$ -Gauge [38], GBRV-FCC, GBRV-BCC, GBRV-compound [23], ghost state detection, and phonons at $\\boldsymbol{\\Gamma}$ , all executed using ABINIT [27,28]. By studying the correlation between the results for the different tests we show that these form a complementary set. Only the GBRV-FCC and BCC show a strong correlation, such that performing both does not increase the amount of information. \n\nThe present version of the PD-PBE contains a total of 141 PSPs and defines two tables, with standard and stringent accuracy. Both tables contain one PSP per element. For the final set of PSPs a total of around 70,000 calculations have been performed during the testing process. All these calculations have been performed using the PseudoDojo tools building on the high-throughput framework of the AbiPy project. The present DFT calculations are all performed using ABINIT version 8.4. \n\nIn the development of the PD-PBE, valuable insights were obtained concerning the effects of the core-valence partitioning and the non-linear core corrections on the stability, convergence, and transferability of norm-conserving pseudopotentials. \n\nNon-linear core corrections—PSP that have the 1s frozen in the core and the 2s and 2p completely filled (included in the valence partition) do not improve upon adding non-linear core corrections. Often they even become unstable (small changes in the unit cell volume or $E_{\\mathrm{c}}$ lead to drastic changes in the total energy). For the magnetic 3d transition metals adding well-balanced non-linear core corrections dramatically improves the results on magnetic systems. Non-magnetic systems are much less sensitive and also perform well without non-linear core corrections. In some cases the model core charges for non-linear core correction can be quite localized. These hard models reproduce the AE results very well, and can have beneficial effects on ground state properties, but may render the PSP difficult to converge, especially in DFPT calculations. \n\nCore-valence partitioning—In the fifth row main group elements, the description of the unoccupied space improves clearly by increasing the valence partition. Including 4d alone leads to actual ghost states in the range of $20{\\-}80\\ \\mathrm{eV}$ above the Fermi level. Including the full $n=4$ shell removes all signs of ghost states up to several hundreds of eV. The exception is Xe for which putting the $n=4$ shell in the valence partition does not lead to any negative effect. A similar situation arises in the 5d transition metals. Including only the 5d in the valence partition for these elements leads to ghost states just above the Fermi level. Despite the good results obtained for the $\\varDelta$ -Gauge, these pseudopotentials are not transferable and can perform poorly if used in other crystalline environments. \n\nExtra projectors—In both the second row B-F and fifth row transition metals with frozen 4f, the PSPs are improved by the addition of additional projectors, d and f, respectively. \n\nSupplementary material: PD_v0.4_supplementary-data-andtests: HTML version of the Jupyter Notebook performing the statistical analysis presented in this work, PD_v0.4_supplementary-correlations-elements: HTML version of the Jupyter Notebook performing the element wise comparison and correlation studies between the tests, PD_v0.4_supplementary-GBRV-compoundsstandard: HTML version of the Jupyter Notebook performing statistical analysis of the GBRV compound tests and the lanthanide nitride lattice parameter comparison. \n\n# Acknowledgments \n\nFinancial support was provided from F.R.S.-FNRS through the PDR Grants T.1031.14 (HiT4FiT) for MJVS, T.0238.13 (AIXPHO) for MG, and T.1077.15 (Transport in novel vdW heterostructures) for MJV. The work was supported by the Communauté Française de Belgique through the BATTAB project (ARC 14/19-057) and AIMED (ARC 15/19-09). The authors also thank the CÉCI facilities funded by F.R.S.-FNRS (Grant No. 2.5020.1) and Tier-1 supercomputer of the Fédération Wallonie-Bruxelles funded by the Walloon Region (Grant No. 1117545). The authors thank J.M. Beuken and Y. Pouillon for technical support, B. Van Troeye, J.-J. Adjizian, A. Miglio and the other members of the NAPS group at the UCLouvain for feedback on the earlier versions of the pseudopotentials, M. Stankovski, J. Junquera, A. García, S. Cottenier, and K. Lejaeghere for useful discussions, and M. Ueshiba for inspiration. \n\n# Appendix A. Supplementary data \n\nSupplementary material related to this article can be found online at https://doi.org/10.1016/j.cpc.2018.01.012. \n\n# References \n\n[1] K. Lejaeghere, G. Bihlmayer, T. Björkman, P. Blaha, S. Blügel, V. Blum, D. Caliste, I.E. Castelli, S.J. Clark, A. Dal Corso, S. de Gironcoli, T. Deutsch, J. Kay Dewhurst, I. Di Marco, C. Draxl, M. Dułak, O. Eriksson, J.A. Flores-Livas, K.F. Garrity, L. Genovese, P. Giannozzi, M. Giantomassi, S. Goedecker, X. Gonze, O. Grånäs, E.K.U. Gross, A. Gulans, F. Gygi, D.R. Hamann, P.J. Hasnip, N.A.W. Holzwarth, D. Iuan, D.B. Jochym, F. Jollet, D. Jones, G. Kresse, K. Koepernik, E. Küçükbenli, Y.O. Kvashnin, I.L.M. Locht, S. Lubeck, M. Marsman, N. Marzari, U. Nitzsche, L. Nordström, T. Ozaki, L. Paulatto, C.J. Pickard, W. Poelmans, M.I.J. Probert, K. Refson, M. Richter, G.-M. Rignanese, S. Saha, M. Scheffler, M. Schlipf, K. Schwarz, S. Sharma, F. Tavazza, P. Thunström, A. Tkatchenko, M. Torrent, D. Vanderbilt, M.J. van Setten, V. Van Speybroeck, J.M. Wills, J.R. Yates, G.-X. Zhang, S. Cottenier, Science 351 (6280) (2016) 1415. \n\n[2] D. Hamann, M. Schlüter, C. Chiang, Phys. Rev. Lett. 43 (20) (1979) 1494–1497. [3] G. Bachelet, D. Hamann, M. Schlüter, Phys. Rev. B 26 (8) (1982) 4199–4228. [4] P. Hohenberg, W. Kohn, Phys. Rev. 136 (1964) B864–B871. [5] W. Kohn, L.J. Sham, Phys. Rev. 140 (1965) A1133–A1138. [6] S. Poncé, G. Antonius, P. Boulanger, E. Cannuccia, A. Marini, M. Côté, X. Gonze, Comput. Mater. Sci. 83 (2014) 341. [7] A. Rappe, K. Rabe, E. Kaxiras, J. Joannopoulos, Phys. Rev. B 41 (2) (1990) 1227–1230. [8] C. Hartwigsen, S. Goedecker, J. Hutter, Phys. Rev. B 58 (1998) 3641–3662. [9] M. Krack, Theo. Chem. Acc. 114 (1) (2005) 145–152. [10] http://opium.sourceforge.net. (Accessed 14 July 2017). [11] http://www.quantum-espresso.org/pseudopotentials. (Accessed 14 July 2017). [12] M. Schlipf, F. Gygi, Comput. Phys. Comm. 196 (2015) 36–44. [13] D. Vanderbilt, Phys. Rev. B 41 (11) (1990) 7892–7895. [14] P.E. Blöchl, Phys. Rev. B 50 (24) (1994) 17953–17979. [15] J. Klimeš, M. Kaltak, G. Kresse, Phys. Rev. B 90 (2014) 075125. [16] J.P. Perdew, K. Burke, M. Ernzerhof, Phys. Rev. Lett. 77 (18) (1996) 3865–3868. [17] D.R. Hamann, Phys. Rev. B 88 (2013) 085117. [18] D.R. Hamann, Phys. Rev. B 95 (2017) 239906. [19] M.A. Marques, M.J. Oliveira, T. Burnus, Comput. Phys. Comm. 183 (10) (2012) 2272–2281. [20] M.J. van Setten, M. Giantomassi, X. Gonze, G.-M. Rignanese, G. Hautier, Phys. Rev. B 96 (2017) 155207. [21] A. García, M. Verstraete, Y. Pouillon, J. Junquera, arXiv:1707.08938. [22] http://jupyter.org. (Accessed 18 October 2017). [23] K.F. Garrity, J.W. Bennett, K.M. Rabe, D. Vanderbilt, Comput. Mater. Sci. 81 (2014) 446–452. [24] K. Lejaeghere, V.V. Speybroeck, G.V. Oost, S. Cottenier, Crit. Rev. Solid State Mater. Sci. 39 (1) (2013) 1–24. [25] D. Hamann, Phys. Rev. B 40 (5) (1989) 2980–2987. [26] D.D. Koelling, B.N. Harmon, J. Phys. C Solid State Phys. 10 (1977) 3107. [27] X. Gonze, B. Amadon, P.-M. Anglade, J.-M. Beuken, F. Bottin, P. Boulanger, F. Bruneval, D. Caliste, R. Caracas, M. Côé, T. Deutsch, L. Genovese, P. Ghosez, M. Giantomassi, S. Goedecker, D. Hamann, P. Hermet, F. Jollet, G. Jomard, S. Leroux, M. Mancini, S. Mazevet, M. Oliveira, G. Onida, Y. Pouillon, T. Rangel, G.-M. Rignanese, D. Sangalli, R. Shaltaf, M. Torrent, M. Verstraete, G. Zerah, J. Zwanziger, Comput. Phys. Comm. 180 (12) (2009) 2582–2615. [28] X. Gonze, F. Jollet, F. Abreu Araujo, D. Adams, B. Amadon, T. Applencourt, C. Audouze, J.M. Beuken, J. Bieder, A. Bokhanchuk, E. Bousquet, F. Bruneval, D. Caliste, M. Côté, F. Dahm, F. Da Pieve, M. Delaveau, M. Di Gennaro, B. Dorado, C. Espejo, G. Geneste, L. Genovese, A. Gerossier, M. Giantomassi, Y. Gillet, D.R. Hamann, L. He, G. Jomard, J. Laflamme Janssen, S. Le Roux, A. Levitt, A. Lherbier, F. Liu, I. Lukačević, A. Martin, C. Martins, M.J.T. Oliveira, S. Poncé, Y. Pouillon, T. Rangel, G.M. Rignanese, A.H. Romero, B. Rousseau, O. Rubel, A.A. Shukri, M. Stankovski, M. Torrent, M.J. Van Setten, B. Van Troeye, M.J. Verstraete, D. Waroquiers, J. Wiktor, B. Xu, A. Zhou, J.W. Zwanziger, Comput. Phys. Comm. 205 (2016) 106–131. [29] http://www.pseudo-dojo.org, 2017. [30] N. Troullier, J.L. Martins, Phys. Rev. B 43 (3) (1991) 1993–2006. [31] J.P. Perdew, Y. Wang, Phys. Rev. B 45 (1992) 13244–13249. [32] J.P. Perdew, A. Ruzsinszky, G.I. Csonka, O.A. Vydrov, G.E. Scuseria, L.A. Constantin, X. Zhou, K. Burke, Phys. Rev. Lett. 100 (2008) 136406. [33] M.A. Marques, M.J. Oliveira, T. Burnus, Comput. Phys. Comm. 183 (10) (2012) 2272–2281. [34] P. Scherpelz, M. Govoni, I. Hamada, G. Galli, J. Chem. Theory Comput. 12 (8) (2016) 3523–3544. [35] M.L. Tiago, S. Ismail-Beigi, S.G. Louie, Phys. Rev. B 69 (2004) 125212. [36] S.G. Louie, S. Froyen, M.L. Cohen, Phys. Rev. B 26 (1982) 1738–1742. [37] M. Teter, Phys. Rev. B 48 (1993) 5031–5041. [38] F. Jollet, M. Torrent, N. Holzwarth, Comput. Phys. Comm. 185 (4) (2014) 1246–1254. [39] X. Gonze, P. Käckell, M. Scheffler, Phys. Rev. B 41 (1990) 12264–12267. [40] Xavier Gonze, Roland Stumpf, Matthias Scheffler, Phys. Rev. B 44 (1991) 8503–8513. [41] S. Goedecker, Private Communication. [42] P. Scherpelz, M. Govoni, I. Hamada, G. Galli, J. Chem. Theory Comput. 12 (2016) 3523. [43] G. Kresse, J. Furthmüller, Phys. Rev. B 54 (1996) 11169. " + }, + { + "id": "10.1038_s41929-017-0017-x", + "DOI": "10.1038/s41929-017-0017-x", + "DOI Link": "http://dx.doi.org/10.1038/s41929-017-0017-x", + "Relative Dir Path": "mds/10.1038_s41929-017-0017-x", + "Article Title": "High-efficiency oxygen reduction to hydrogen peroxide catalysed by oxidized carbon materials", + "Authors": "Lu, ZY; Chen, GX; Siahrostami, S; Chen, ZH; Liu, K; Xie, J; Liao, L; Wu, T; Lin, DC; Liu, YY; Jaramillo, TF; Norskov, JK; Cui, Y", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Hydrogen peroxide (H2O2) is a valuable chemical with a wide range of applications, but the current industrial synthesis of H2O2 involves an energy-intensive anthraquinone process. The electrochemical synthesis of H2O2 from oxygen reduction offers an alternative route for on-site applications; the efficiency of this process depends greatly on identifying cost-effective catalysts with high activity and selectivity. Here, we demonstrate a facile and general approach to catalyst development via the surface oxidation of abundant carbon materials to significantly enhance both the activity and selectivity (similar to 90%) for H2O2 production by electrochemical oxygen reduction. We find that both the activity and selectivity are positively correlated with the oxygen content of the catalysts. The density functional theory calculations demonstrate that the carbon atoms adjacent to several oxygen functional groups (-COOH and C-O-C) are the active sites for oxygen reduction reaction via the two-electron pathway, which are further supported by a series of control experiments.", + "Times Cited, WoS Core": 1353, + "Times Cited, All Databases": 1437, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000428621500015", + "Markdown": "# High-efficiency oxygen reduction to hydrogen peroxide catalysed by oxidized carbon materials \n\nZhiyi $\\mathbf{L}\\mathbf{u}\\oplus^{1}$ , Guangxu Chen1, Samira Siahrostami2, Zhihua Chen3, Kai Liu1, Jin Xie1, Lei Liao1, Tong $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{1}$ , Dingchang Lin1, Yayuan Liu $\\oplus1$ , Thomas F. Jaramillo3, Jens K. Nørskov2,4 and Yi Cui1,5\\* \n\nHydrogen peroxide $(H_{2}O_{2})$ is a valuable chemical with a wide range of applications, but the current industrial synthesis of ${\\bf H}_{2}\\bar{\\bf O}_{2}$ involves an energy-intensive anthraquinone process. The electrochemical synthesis of ${\\bf H}_{2}\\bar{\\bf O}_{2}$ from oxygen reduction offers an alternative route for on-site applications; the efficiency of this process depends greatly on identifying cost-effective catalysts with high activity and selectivity. Here, we demonstrate a facile and general approach to catalyst development via the surface oxidation of abundant carbon materials to significantly enhance both the activity and selectivity $(-90\\%)$ for ${\\bf H}_{2}\\bar{\\bf O}_{2}$ production by electrochemical oxygen reduction. We find that both the activity and selectivity are positively correlated with the oxygen content of the catalysts. The density functional theory calculations demonstrate that the carbon atoms adjacent to several oxygen functional groups (–COOH and C–O–C) are the active sites for oxygen reduction reaction via the two-electron pathway, which are further supported by a series of control experiments. \n\nhe enormous need for hydrogen peroxide $\\mathrm{(H}_{2}\\mathrm{O}_{2})$ places this chemical as one of the 100 most important chemicals in the world1. $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is a potential energy carrier2 and an environmentally friendly oxidant for various chemical industries and environmental remediation3, thus the need for efficient and inexpensive $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production is essential. The current industrial process for the synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ involves an energy-intensive anthraquinone oxidation/reduction, which requires complex and large-scale infrastructure and generates a substantial volume of waste chemicals3. The direct synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ from hydrogen and oxygen in the presence of catalysts $^{4-6}$ provides a more straightforward route and ideally solves the issues associated with the indirect anthraquinone route. However, as the hydrogen/oxygen mixture is potentially explosive, researchers have aimed to eliminate the danger of explosion and to simultaneously find selective and active catalysts4,7–10. Another attractive and alternative route for the on-site direct production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is through an electrochemical process in a fuel cell setup, where oxygen reduction undergoes a two-electron pathway11–13. Substantial efforts in recent years on this fuel cell concept have aimed at efficiently generating electricity simultaneously with a high-yield production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (refs 14–20). \n\nFor the two-electron route, electrocatalysts with high activity and selectivity are a prerequisite. Noble metals and their alloys (for example, $\\mathrm{Pd}\\mathrm{-Au}^{21}$ , $\\mathrm{Pt-Hg^{14}}$ and $\\mathrm{Pd-Hg^{15}})$ are currently the most efficient catalysts, requiring small overpotentials for oxygen reduction as well as high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity (up to ${\\sim}98\\%$ ). However, the scarcity of noble metals may hinder their large-scale application. Carbon-based materials have shown great promise as alternative catalysts for the electrochemical synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2},$ as they are earth-abundant, highly tunable and electrochemically stable under reaction conditions. Recent studies demonstrate the capability of carbon materials for the electrochemical production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , with their performance strongly correlated to heteroatom doping16,22–24 and material structure18,25–27, as both of these parameters can tailor the electronic structure of carbon atoms. Despite progress in this area, there is room for improvement in developing improved carbon-based materials, and much to learn regarding structure–activity relationships. \n\nHerein, we demonstrate an effective approach to enhancing both the activity and selectivity of carbon materials for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production by means of surface oxidation of the carbon catalyst. For example, after oxidizing commercially available carbon nanotubes (CNTs), we observe a significant decrease in overpotential and an enhanced selectivity up to ${\\sim}90\\%$ in both basic and neutral media. Catalyst characterization reveals the existence of both $C{\\mathrm{-}}\\mathrm{O}$ and $\\scriptstyle{\\mathrm{C=O}}$ functional groups on the surface of the oxidized CNTs (O-CNTs). The oxygen reduction reaction (ORR) activity and selectivity are found to be positively correlated with the oxygen content, indicating the importance of oxygen functional groups. The general efficacy of this approach is demonstrated by observing a similarly enhanced oxygen reduction performance on other forms of oxidized carbon—oxidized super P (O-SP) and oxidized acetylene black (O-AB)—which have a much lower cost than O-CNT. To elucidate the catalytic mechanism, we employ density functional theory (DFT) calculations to investigate the activities of a wide variety of oxygen functional groups and identify several possible sites with enhanced ORR activity. Moreover, guided by the DFT results, a series of experiments are performed to fabricate O-CNTs with prominent selectivity, which further supports the active sites of the oxidized carbon materials for electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis. \n\n# Results \n\nORR activities of CNTs and O-CNTs. The O-CNTs were prepared by the chemical oxidation of CNTs using concentrated nitrate acid (see Methods for more details)28. The ORR performance was evaluated in an aqueous solution $(0.1\\mathrm{M}\\mathrm{KOH}$ or $0.1\\mathrm{M}$ phosphate buffered saline) using a rotating ring-disk electrode. The ORR can follow either of a $4e^{-}$ or $2e^{-}$ pathway. The $2e^{-}$ pathway is preferred in this study as the production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is the objective. Figure 1a shows electrochemical results in a basic electrolyte (0.1 M KOH, $\\mathrm{\\pH}\\sim13)$ , the oxygen reduction currents measured on a disk electrode (solid lines) and the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ oxidation currents measured on a platinium  ring electrode (dashed lines). The amount of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ formed was quantified by the ring electrode, which was potentiostated at $1.2\\mathrm{V}$ (versus the reversible hydrogen electrode, the same below) to avoid ORR currents at the ring, allowing only $\\mathrm{H}_{2}\\mathrm{O}_{2}$ oxidation. According to the polarization curves, the O-CNTs showed a much higher current and a remarkably lower overpotential $\\cdot{\\sim}130\\mathrm{mV}$ lower at $0.2\\mathrm{mA}\\dot{}$ ) with respect to the commercial CNTs. It should be noted that the current increased very quickly to the limiting current for the O-CNTs, indicating fast ORR kinetics, which was also reflected in the lower Tafel slope (Supplementary Fig. 1)29. This fast kinetics may make the O-CNTs a promising candidate in alkaline fuel cells for the synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . In addition to the higher activity, the O-CNTs exhibited a significantly higher $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity (around ${\\sim}90\\%$ in the potential range of $0.4\\mathrm{-}0.65\\mathrm{V})$ than the CNTs $(\\sim60\\%)$ , as shown in Fig. 1c. This performance enhancement was also observed in neutral electrolyte $\\mathrm{(pH\\sim}7)$ , where the onset potential measured at $0.05\\mathrm{mA}$ shifted in a positive direction by $\\mathord{\\sim}150\\mathrm{mV}$ and the selectivity increased from ${\\sim}60\\%$ to ${\\sim}85\\%$ for CNTs exposed to the oxidation treatment (Fig. $^{\\mathrm{1b,d}},$ ). The stability of the O-CNTs was demonstrated by long-term testing $\\left(\\sim10\\mathrm{h}\\right)$ with negligible changes in activity or selectivity as measured on both the ring and disc electrodes (Fig. $^{1\\mathrm{e,f}},$ ). The gradual degradation on the ring current in neutral electrolyte was attributed to anion poisoning rather than current efficiency degradation, as the ring current could be recovered after electrochemical ring cleaning. The ORR activity of the O-CNTs was also evaluated under acidic conditions $(0.1\\mathrm{M}$ $\\mathrm{HClO_{4}},$ , as shown in Supplementary Fig. 2. It is observed that the activity and selectivity are both significantly improved compared with CNTs, but not as good as those performed under base conditions. \n\nThe high activity and selectivity of the O-CNT catalyst make it the most active non-precious electrocatalyst towards electrochemical reduction of oxygen to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ under basic conditions (Supplementary Table $1)^{22,24,30,31}$ . To improve the ORR current for practical applications, we loaded our catalyst onto Teflon-treated carbon fibre paper with a loading of ${\\sim}0.5\\mathrm{mgcm}^{-2}$ and measured their steady-state polarization curves (Supplementary Fig. 3). The Teflon-treated carbon fibre paper is highly hydrophobic, thus providing abundant three-phase contact points for the $\\mathrm{ORR}^{32,33}$ . In 1 M KOH, the electrode achieved current densities of 20 and $40\\mathrm{mAcm}^{-2}$ at 0.72 and $0.68\\mathrm{V},$ respectively, while maintaining a similarly high selectivity of ${>}90\\%$ . In addition, we performed the ORR performance of O-CNT catalysts in a reactor reported previously20 and it was found that the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentration can be easily accumulated to around $1,975\\mathrm{mgl^{-1}}$ within $30\\mathrm{min}$ (the polarization curve and $\\mathrm{V}{-}t$ curve under constant current of the reactor can be seen in Supplementary Fig.  4). Compared with previous reports (Supplementary Table $2)^{16,25,26}$ , the yield and production rate are still among the highest values, demonstrating that electrochemical reduction of oxygen to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is practical in an alkali environment. \n\n![](images/efdaf9219af9d4d302fd390a793c563e24aebb0c885c612db57edf2883cd6a99.jpg) \nFig. 1 | Oxygen reduction performance of CNTs and O-CNTs. a,b, Polarization curves at 1,600 r.p.m. (solid lines) and simultaneous ${\\sf H}_{2}{\\sf O}_{2}$ detection currents at the ring electrode (dashed lines) for both catalysts in 0.1 M KOH (a) or 0.1 M phosphate buffered saline (PBS; b). c,d, Calculated selectivity of these two catalysts at various potentials at 0.1 M KOH (c) and 0.1 M PBS (d). e,f, Stability measurements of O-CNTs at 0.1 M KOH (e) and 0.1 M PBS (f). These results indicate that the O-CNTs possess both higher activity and higher ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ selectivity than CNTs towards oxygen reduction to produce ${\\sf H}_{2}{\\sf O}_{2}$ in alkaline and neutral electrolytes. RHE, reversible hydrogen electrode. \n\nCharacterizations of CNTs and O-CNTs. Physical and chemical characterization of the two samples may shed light on the origin of the performance enhancement. Transmission electron microscopy images (Fig. 2a,b) and $\\mathrm{\\DeltaX}$ -ray diffraction patterns (Fig. 2c) demonstrate that the tube-like structure and crystallinity were not affected by the oxidation process. Raman spectra of both samples (Fig. 2d) reveal that the intensity ratio of the D and G peaks was slightly increased after oxidation, indicating that the oxidation process created some disorder (that is, defect) in the graphitic structure28. Figure 2e depicts the X-ray photoelectron spectroscopy (XPS) survey scans to detect the elements presented on the CNT and O-CNT surfaces. A new peak that can be indexed to oxygen 1s emerged after nitric acid treatment, yielding a carbon-to-oxygen ratio of 92:8, which is substantially different from the commercial CNTs that exhibited negligible oxygen content. The carbon 1s spectrum of the O-CNTs (Fig. 2f) can be deconvoluted into the following bands: carbon in graphite at $284.5\\mathrm{eV},$ defects (attributed to carbon atoms no longer in the regular tubular structure) at $285.4\\mathrm{eV},$ carbon singly bound to oxygen (C–O) at $286.1\\mathrm{eV},$ carbon bound to two oxygens (that is, $-\\mathrm{COOH})$ at $288.7\\mathrm{eV}$ and the characteristic shakeup line of carbon in aromatic compounds at $290.5\\mathrm{eV}$ $\\scriptstyle\\overbrace{\\pi\\mathrm{-}\\pi^{*}}$ transition)34. The deconvolution of the oxygen 1s spectrum (Fig. 2g) shows two peaks: oxygen doubly bound to carbon $\\scriptstyle(\\mathrm{C=O})$ at $531.6\\mathrm{eV}$ and oxygen singly bound to carbon (C–O) at $533.2\\mathrm{eV}^{35}$ . These results indicate that the oxidation treatment induced more oxygen-containing functional groups (for example, C–OH, C–O–C, $\\scriptstyle{\\mathrm{C=O}}$ and $_\\mathrm{C-OOH}$ which is confirmed by the Fourier-transform infrared spectroscopy spectrum in Supplementary Fig.  5), accompanied with a slightly more disordered structure for the O-CNTs. \n\nAdditional control experiments were performed to identify the main reason for enhanced performance. The commercial CNTs usually incorporate iron-based catalysts36,37, which may contribute to the ORR activity and selectivity. Thus, we determined the iron concentrations of the catalysts by inductively coupled plasma mass spectrometry, as listed in Supplementary Table 3. The results demonstrated that the iron in CNTs can be removed by the oxidation treatment. They also showed that the iron concentration in commercial carbon nanoparticles (for example, super P (SP)) is one magnitude less than in CNTs. However, as the ORR activity and selectivity of SP that is free of iron are both similar to those of CNTs (shown next), we believe that the small amount of iron in CNTs may not play a vital role in determining the ORR performance. Moreover, in terms of the trace amount of iron in SP and O-SP and the greatly \n\n![](images/66ea3783be751cfd16ada904a2725bb2e4b87e397203874e0dbdf055163324c2.jpg) \nFig. 2 | Characterizations of CNTs and O-CNTs. a,b, Transmission electron microscopy images of CNTs before (a) and after oxidation (b). Scale bars, $10\\mathsf{n m}$ . c,d, $\\mathsf{X}$ -ray diffraction patterns (c) and Raman spectra (d) of CNTs and O-CNTs. e, XPS survey of both samples. f,g, Deconvoluted carbon 1s $(\\pmb{\\uparrow})$ and oxygen 1s $\\mathbf{\\sigma}(\\mathbf{g})$ spectra of O-CNTs. These results indicate that the oxidation treatment creates abundant oxygen-containing functional groups on the surface of CNTs. \n\n# Nature Catalysis | www.nature.com/natcatal \n\nenhanced ORR performance (especially the onset potential) for O-SP, we can conclude that the presence of iron nanoparticles did not contribute substantially to ORR performance. Moreover, to mitigate the possible contribution from the iron, the commercial CNTs were first treated with concentrated HCl and NaSCN solution before performing ORR measurements. Electrochemical results demonstrated that the CNTs showed slightly enhanced ORR activity and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity before and after HCl and NaSCN treatment (Supplementary Fig. 6), further supporting our conclusion. \n\nIt has been reported that the defects in the carbon materials may act as reactive sites for oxygen adsorption or reduction during the electrocatalytic process25. In the present study, the O-CNTs were further treated in a mixed hydrogen/argon atmosphere to reduce the oxygen-containing functional group (R-O-CNTs). XPS data reveal that this hydrogen reduction process removed most of the oxygen while the R-O-CNT structure still retained defects, as shown by the Raman spectrum (Supplementary Fig. 7). However, in terms of ORR activity and selectivity, R-O-CNTs perform far worse than O-CNTs (Supplementary Fig. 8), indicating that oxygenated defects play an important role in these catalysts; for example, as active sites themselves or by affecting the electronic structure of the material. \n\nORR activities of carbon nanoparticles and oxidized carbon nanoparticles. The oxygen content on the catalysts can be tuned by changing the process time for oxidation. Longer oxidation times gave rise to a gradual increase in the oxygen content up to $9\\%$ within $48\\mathrm{h}$ (Supplementary Fig. 9). In Fig. 3a,b, we have plotted the oxygen content of each sample versus the current and the selectivity at $0.6\\mathrm{V},$ respectively. A nearly linear correlation was observed in both plots, further validating the importance of oxygen functional groups. To demonstrate the general efficacy of this surface oxidation strategy for the ORR to produce $\\mathrm{H}_{2}\\mathrm{O}_{2}$ we examined two other types of low-cost carbon material (SP and acetylene black (AB)) and found that the ORR activity and selectivity of the oxidized carbon materials (O-SP and O-AB; characterization shown in Supplementary Figs. 10–13) both improved significantly or were comparable in both basic and neutral electrolytes (Fig. 3c,d and Supplementary Figs. 14 and 15). Notably, O-SP and O-AB achieved selectivities of ${\\sim}93$ and ${\\sim}72\\%$ , respectively, which are much higher than the values for original SP and AB ( $_{\\sim68}$ and $\\sim30\\%$ , respectively). \n\n![](images/a8db98cdd32966a2881dcdae0a2a40c1295539aa5e128ed8cc2570d663febbab.jpg) \nFig. 3 | ORR activities of O-CNTs with diverse oxygen content and other carbon materials. a,b, Plots of ${\\sf H}_{2}{\\sf O}_{2}$ current (a) and selectivity $(\\pmb{\\ b})$ at $0.6\\mathsf{V}$ as a function of oxygen content for O-CNTs with various oxidation times, demonstrating that both the activity and selectivity correlate linearly with the oxygen content. c, Polarization curves at 1,600 r.p.m. (solid lines) and simultaneous ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ detection currents at the ring electrode (dashed lines) for the carbon materials SP and AB and their oxidized derivatives. d, ${\\sf H}_{2}{\\sf O}_{2}$ current (0.6 V) comparison of SP, O-SP, AB and O-AB, suggesting that the oxidation process is generally applicable for carbon materials. \n\nDFT calculations. The above experimental results demonstrate that the oxidation treatment of nanostructured carbons generates abundant oxygen functional groups, which may tailor the electronic structure of carbon materials and significantly modulate their oxygen reduction activity. The identification of active sites for this catalytic process is important for mechanistic understanding and for the rational design of future catalysts. Herein, we employ DFT calculations to study the activities of a wide range of oxygen functional groups (a total of nine configurations, as shown in Fig.  4a) towards ORR. A two-dimensional graphene sheet is used as the model system, where different types of oxygen functional groups, including carboxyl (–COOM, $\\mathrm{M}{=}\\mathrm{H}$ and Na for this calculation), carbonyl $\\scriptstyle(\\mathrm{C=O})$ , etheric (O–C–O) and hydroxyl $\\left(-\\mathrm{OH}\\right)$ were introduced at different locations of the graphene; for example, the basal plane or edge. The activity of a catalyst for the ORR is determined to a large extent by its binding to all ORR intermediates $(\\mathrm{OOH^{*}}$ , O and $\\mathrm{OH^{*}}$ ). Thus, catalytic activities for the different structures are determined by the binding energies of the reaction intermediates to the active sites (the carbon atoms denoted by blue circles in Fig. 4a) of the catalyst. For the two-electron ORR, the overpotential is either due to hydrogenation of oxygen (equation (1)) or the reduction of ${\\mathrm{OOH}}^{*}$ to form $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (equation (2)). \n\n$$\n\\mathrm{O}_{2}+\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{e}^{-}\\rightarrow\\mathrm{OOH}^{*}+\\mathrm{OH}^{-}\n$$ \n\n$$\n\\mathrm{OOH^{*}+e^{-}\\to H O_{2}^{-}}\n$$ \n\nWe use $\\Delta G_{\\mathrm{OOH}^{*}}$ as a descriptor and plot the activity volcano to underline the activities of different oxygen functional groups14,15. The limiting potential, $U_{\\mathrm{L}},$ which can be considered a metric of activity, is defined as the lowest potential at which all the reaction steps are downhill in free energy. The theoretical overpotential is defined as the maximum difference between the limiting potential and equilibrium potential. Figure $\\ensuremath{4\\mathrm{b}}$ shows the calculated $U_{\\mathrm{L}}$ as a function of $\\Delta G_{\\mathrm{OOH}^{*}}$ for the two-electron ORR to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ on these materials. The structures located on the right side of the volcano bind $\\mathrm{{OOH^{*}}}$ weakly, hence equation (1) is a limiting step. Those located on the left side, however, bind $\\mathrm{{OOH^{*}}}$ strongly, thus equation (2) is limiting. As a result, the binding strength of ${\\mathrm{\\Gamma}}_{\\mathrm{{OOH}^{*}}}$ to the surface ultimately determines the ORR activity. The maximum limiting potential is $0.70\\mathrm{V},$ representing zero overpotential at the top of the volcano. The computed values in Fig. 4 suggest that the $-\\mathrm{OH}$ functional group does not significantly contribute to the ORR. However, the C–O–C groups on the basal plane and at the edge of the graphene (O basal 1 and O edge) are highly active for the two-electron reduction of oxygen to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ with overpotentials of $0.02\\mathrm{V}$ and $0.06\\mathrm{V},$ respectively, comparable with the previously reported noble metal catalysts14. Among different possible configurations for the –COOM functional group, we find that the armchair edge is the most active (COOM edge 2), yielding an overpotential of $0.06\\mathrm{V}.$ \n\n![](images/e5214f4a52a51c578fe887577a00c033aa94de236e2c7d54e02114b46cd5344b.jpg) \nFig. 4 | DFT results of the ORR activities of different oxygen functional groups. a, Different oxygen functional group type configurations examined in this study. The carbon atoms denoted by a blue circle are the active sites under investigation ( ${\\bf\\dot{M}}={\\sf H}$ and $\\mathsf{N a}$ ). b, Calculated two-electron (solid black) ORR-related volcano plot for the electro-reduction of oxygen to ${\\sf H}_{2}{\\sf O}_{2}$ displayed with the limiting potential plotted as a function of $\\Delta G_{\\sf00H},$ \\*. The equilibrium potential for the two-electron ORR is shown as the dashed black line. The green squares display the activities of $P t-H g$ and Pd–Au alloys adapted from ref. 14, and the result for the OH basal configuration is out of the range. \n\n# Discussion \n\nWhile XPS analysis was helpful in elucidating the different species of oxidized carbon in these materials, the ratios were very similar in all the oxidized samples (Supplementary Table 4); thus, it is challenging to experimentally confirm the active functional groups unequivocally. Here, to support that the DFT results that demonstrate the oxygen functional groups (–C–O–C and –COOM) are active and selective for electrochemical oxygen reduction to produce $\\mathrm{H}_{2}\\mathrm{O}_{2}.$ we choose two different methods to fabricate O-CNTs, which are rich in these two functional groups. It should be noted that the nanotube morphologies are mostly preserved after these two oxidation methods (Supplementary Fig. 16), thus the possible contribution from morphology change to the overall ORR activity can be excluded. The first method is oxidizing CNTs by highly concentrated KOH solution at a high temperature (denoted by CNTsKOH). According to the XPS results (Supplementary Fig. 17), the intensity of the $\\scriptstyle{\\mathrm{C=O}}$ bond was much higher than that of the C–O bond, suggesting the formation of a –COOH functional group on the surface38. The broad peak at around $535\\mathrm{eV}$ can be attributed to firmly absorbed $\\mathrm{H}_{2}\\mathrm{O}^{38}$ . Thus, although the as-measured oxygen content is ${\\sim}8.5\\%$ , the oxygen content of the functional group should be much lower. The second method is oxidizing CNTs by mixing with poly(ethylene oxide) (PEO; mass ratio: 1:4) and carbonizing the mixture at $600^{\\circ}\\mathrm{C}$ for $3\\mathrm{h}$ (denoted by CNTs-PEO). The XPS results showed that the $C{\\mathrm{-}}\\mathrm{O}$ bond was dominated in CNTs-PEO, indicating the formation of a $-C{\\mathrm{-}}\\mathrm{O-C}$ functional group as the material was produced at a high temperature. The oxygen content was ${\\sim}4.3\\%$ for this material. \n\nThe electrochemical results reveal that both CNTs-KOH and CNTs-PEO show significantly improved ORR activity and selectivity $(\\sim83\\%$ and ${\\sim}87\\%$ for CNTs-KOH and CNTs-PEO, respectively), demonstrating that both functional groups are active sites for electrochemical reduction of oxygen to produce $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Although the selectivity of both samples is comparable with O-CNTs, lower onset potentials are observed. We hypothesize that the different onset potentials can be attributed to the possibility of the presence of different oxygen functional groups. According to our DFT calculations, the type of functional group determines the activity. There also seems to be a synergy effect between different functional groups. For example, the O-CNT catalyst shows multiple oxygen functional groups, thus it is possible that its activity may be affected by several highly active functional groups. As only one oxygen functional group is dominated in CNTs-KOH and CNTs-PEO, the possible synergistic effect seems to be negligible. Moreover, the CNTs-PEO shows slightly higher activity than CNTs-KOH, indicating that the –C–O–C functional group is more active than the –COOM group. Therefore, combined with our DFT calculation, we believe that the above results can further support the active sites of carbon materials for electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis. Overall, this combination of DFT calculations relating to the controlled synthesis of carbon materials with a variety of oxygen functional groups yields the fundamental understanding needed to provide guidance towards the design of future carbon-based catalysts for the electrochemical production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . \n\nIn summary, a surface oxidation treatment was shown to enhance the activity and selectivity of CNTs towards $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production by means of the ORR. The oxidized O-CNTs drastically lowered the needed overpotential by ${\\sim}130\\mathrm{mV}$ at $0.2\\mathrm{mA}$ compared with standard CNTs while simultaneously increasing the selectivity from ${\\sim}60$ to ${\\sim}90\\%$ . The ORR activity and selectivity were also examined as a function of oxygen content in the O-CNTs and a nearly linear correlation emerged that reflects the importance of oxygen functional groups in driving catalysis. This surface oxidation approach was also effective for enhancing the ORR performance of other types of carbon material, validating the generality of this strategy. Based on DFT calculations, we can assign the origin of the high activity to the –COOH functional group in the armchair edge as well as the $\\scriptstyle{\\mathrm{C-O-C}}$ functional group in the basal plane of the graphene, and these active functional groups are supported by further controlled experiments. We propose that our experimental observations, as well as the theoretical calculations, provide new insights into catalyst development that may be relevant in the production of industrial chemicals by means of clean, renewable electrical energy. \n\n# Methods \n\nSurface oxidation of carbon materials. First, the pre-determined quantities of raw CNTs (multiwalled, 0.2 g) and nitric acid (12 M, $200\\mathrm{ml}$ ) were added to a threenecked, round-bottomed glass flask. Afterwards, the reaction flask equipped with a reflux condenser, magnetic stirrer and thermometer was mounted in a preheated water bath. The temperature was kept at $80^{\\circ}\\mathrm{C}$ and the oxidized products were denoted by O-CNT-6, O-CNT-12, O-CNT-24 and O-CNT with oxidizing times of 6, 12, 24 and $48\\mathrm{h}$ , respectively. After oxidation for a certain time, the slurry was taken out, cooled, centrifuged and washed with water and ethanol several times until the pH was neutral. Finally, the sample was dried at $60^{\\circ}\\mathrm{C}$ in a vacuum oven overnight. For SP and AB, the oxidation process was similar to that for the CNTs (48 h). The reduction of O-CNTs was performed in a tube furnace at a temperature of $800^{\\circ}\\mathrm{C}$ for 2 h under a mixed hydrogen $(20\\%)$ /argon atmosphere. \n\nCNTs oxidized by other methods. We chose two different methods to oxidize the CNTs to preferentially create different surface oxygen functional groups. One method was oxidizing CNTs by highly concentrated KOH solution in an autoclave. Briefly, $\\sim50\\mathrm{mg}$ of CNTs was first dispersed in 6 M KOH solution $\\left(40\\mathrm{ml}\\right)$ . Afterwards, the suspension was transferred to an autoclave, which was sealed and put into an oven maintained at $180^{\\circ}\\mathrm{C}$ for $^{\\mathrm{12h}}$ . After the reaction, the product was taken out, cooled down naturally, centrifuged and washed with water and ethanol several times until the $\\mathrm{\\DeltapH}$ was neutral. Finally, the sample was dried at $60^{\\circ}\\mathrm{C}$ in a vacuum oven overnight. This product was denoted by CNTs-KOH. Another method was to oxidize the CNTs by mixing with PEO (mass ratio: 1:4) and carbonizing the mixture at $600^{\\circ}\\mathrm{C}$ for 3 h under an argon atmosphere. This sample was denoted by CNTs-PEO. \n\nCharacterization. The size and morphology of the samples were measured using transmission electron microscopy (FEI Tecnai). XPS (SSI SProbe XPS spectrometer with Al(Ka) source) was used to determine the heteroatoms and functional groups. The X-ray powder diffraction patterns were recorded on an X-ray diffractometer (Rigaku $\\mathrm{D}/\\mathrm{max}2500_{,}^{\\cdot}$ ) in the range $20{-}60^{\\circ}$ . The Raman and ultraviolet-visible spectroscopy were conducted in HORIBA Scientific LabRAM and Cary 6000i, respectively. \n\nSample preparation and electrochemical characterization. The electrodes were prepared by dispersing the oxidized products in ethanol to achieve a catalyst concentration of ${\\sim}3.3\\mathrm{mg}\\mathrm{ml}^{-1}$ with $5\\mathrm{wt\\%}$ Nafion. After sonication for $60\\mathrm{{min}}$ , $6\\upmu\\upmu$ of the catalyst ink was drop-dried onto a glassy carbon disc (area: $0.196\\mathrm{cm}^{2}.$ . The electrochemical tests were performed in a computer-controlled Bio-Logic VSP Potentiostat with a three-electrode cell at room temperature. The glass carbon electrode loaded with catalyst was used as the working electrode. A graphite rod and a saturated calomel electrode were used as the counter and reference electrode, respectively. Two electrolytes with pH ${\\sim}13$ (0.1 M KOH) and ${\\sim}7\\$ (0.1 M phosphate buffered saline) were chosen. The ORR activity and selectivity were investigated by polarization curves and rotating ring-disk electrode measurements in oxygensaturated electrolyte at a scan rate of $10\\mathrm{mVs^{-1}}$ . Polarization curves in nitrogensaturated electrolytes were also recorded as a reference. Electrocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production on Teflon-treated carbon fibre paper loaded with O-CNTs $(\\sim2\\mathrm{mgcm^{-2}},$ was performed in a two-compartment cell with Nafion 117 membrane as separator. Both the cathode compartment $(25\\mathrm{ml})$ and anode compartment were filled with the same electrolyte (1 M KOH). The polarization curves were both system resistance corrected. \n\n$\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of the O-CNTs on the rotating ring-disk electrode was calculated based on the current of both disc and ring electrodes (equation (3)). A potential of $1.2\\mathrm{V}$ (versus the reversible hydrogen electrode) was applied on the ring of the working electrode at a speed of $1{,}600\\ \\mathrm{r.p.m}$ . during the entire testing process. \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}_{2}\\ \\mathrm{yield}:\\mathrm{H}_{2}\\mathrm{O}_{2}(\\%)=200^{*}\\frac{I_{\\mathrm{R}}/N}{I_{\\mathrm{D}}+I_{\\mathrm{R}}/N}\n$$ \n\nwhere $I_{\\mathrm{R}}$ is the ring current, $I_{\\mathrm{D}}$ is the disk current and $N$ is the collection efficiency (0.256 after calibration). \n\n${\\bf{H}}_{2}{\\bf{O}}_{2}$ concentration measurement. The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentration was measured by a traditional cerium sulfate $\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ titration method based on the mechanism that a yellow solution of ${\\mathrm{Ce^{4+}}}$ would be reduced by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to colourless ${\\mathrm{Ce}}^{3+}$ (equation (4)). Thus, the concentration of ${\\mathrm{Ce^{4+}}}$ before and after the reaction can be measured by ultraviolet-visible spectroscopy. The wavelength used for the measurement was $316\\mathrm{nm}$ . \n\n$$\n2\\mathrm{Ce}^{4+}+\\mathrm{H}_{2}\\mathrm{O}_{2}\\rightarrow2\\mathrm{Ce}^{3+}+2\\mathrm{H}^{+}+\\mathrm{O}_{2}\n$$ \n\nTherefore, the concentration of $\\mathrm{H}_{2}\\mathrm{O}_{2}\\left(M\\right)$ can be determined by equation (5): \n\n$$\nM=2\\times M\\mathrm{Ce}^{4+}\n$$ \n\nwhere $M C e^{4+}$ is the mole of consumed ${\\mathrm{Ce^{4+}}}$ . \n\nThe yellow transparent $\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ solution (1 mM) was prepared by dissolving $33.2\\mathrm{mg}\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ in $100\\mathrm{ml}0.5\\mathrm{M}$ sulfuric acid solution. To obtain the calibration curve, $\\mathrm{H}_{2}\\mathrm{O}_{2}$ with known concentration was added to $\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ solution and measured by ultraviolet-visible spectroscopy. Based on the linear relationship between the signal intensity and ${\\mathrm{Ce^{4+}}}$ concentration $(\\sim0.1{-}0.8\\mathrm{mM})$ , the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentrations of the samples could be obtained. The concentration of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ \n\nwas also determined using commercially available $\\mathrm{H}_{2}\\mathrm{O}_{2}$ testing strip paper. $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of the O-CNTs tested on Teflon-treated carbon fibre paper was determined by this method. The electrode was kept at the potential with an initial ORR current at ${\\sim}20\\mathrm{mAcm}^{-2}$ until a certain amount of charge (10 C) was accumulated. \n\nComputational study. The simulations were handled using the Atomic Simulation Environment39. The electronic structure calculations were performed using the QUANTUM ESPRESSO programme package40. The electronic wavefunctions were expanded in plane waves up to a cutoff energy of $500\\mathrm{eV},$ while the electron density was represented on a grid with an energy cutoff of $5{,}000\\mathrm{eV.}$ Core electrons were approximated with ultrasoft pseudopotentials41. We used the BEEF-vdW exchange-correlation functional42, which has been shown to accurately describe chemisorption and physisorption properties on graphene. Graphene structures were modelled as one layer. A vacuum region of about $20\\textup{\\AA}$ was used to decouple the periodic replicas. To model oxygen functional groups in the basal plane, we used a super cell of lateral size $8\\times8$ , and the Brillouin zone was sampled with $(2\\times2\\times1)$ Monkhorst–Pack k-points. For the oxygen functional groups in the edge, we used the super cell of lateral size $3\\times4$ and the Brillouin zone was sampled with $(1\\times4\\times1)$ Monkhorst–Pack k-points. \n\nDetails of the calculated free energy of adsorptions. We considered three intermediates in the ORR: $\\mathrm{OH^{*}}$ , ${{\\mathrm{O^{*}}}}$ and ${\\mathrm{OOH}}^{*}$ . The catalytic activity of the material was determined by the binding energies of the reaction intermediates to the active sites of the catalyst. \n\nTo estimate the adsorption energies of different intermediates at zero potential and $\\mathrm{\\pH}=0$ , we calculated the reaction energies of each individual intermediate and corrected them for zero-point energy (ZPE) and entropy (TS) using equation (6): \n\n$$\n\\Delta G=\\Delta\\mathrm{E}+\\Delta\\mathrm{ZPE-T}\\Delta\\mathrm{S}\n$$ \n\nAdditionally, we used the computational hydrogen electrode model, which exploits the fact that the chemical potential of a proton–electron pair is equal to gas-phase hydrogen at standard conditions, and the electrode potential was taken into account by shifting the electron energy by $-e U$ where $e$ and $U$ are the elementary charge and the electrode potential, respectively43. As the ground state of the oxygen and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ molecules are poorly described in DFT calculations, we used gas-phase $\\mathrm{H}_{2}\\mathrm{O}$ and hydrogen as reference states as they are readily treated in the DFT calculations. The entropy for $\\mathrm{H}_{2}\\mathrm{O}$ was calculated at 0.035 bar, which is the equilibrium pressure of $\\mathrm{H}_{2}\\mathrm{O}$ at $300\\mathrm{K}$ . The free energy of this state is therefore equal to that of liquid water43. \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 10 June 2017; Accepted: 1 December 2017; Published: xx xx xxxx \n\n# References \n\n1.\t Myers, R. L. The 100 Most Important Chemical Compounds (Greenwood Press, London, 2007). \n2.\t Fukuzumi, S., Yamada, Y. & Karlin, K. D. Hydrogen peroxide as a sustainable energy carrier: electrocatalytic production of hydrogen peroxide and the fuel cell. Electrochim. Acta 82, 493–511 (2012). \n3.\t Campos‐Martin, J. M., Blanco‐Brieva, G. & Fierro, J. L. Hydrogen peroxide synthesis: an outlook beyond the anthraquinone process. Angew. Chem. Int. Ed. 45, 6962–6984 (2006). \n4.\t Edwards, J. K. et al. Switching off hydrogen peroxide hydrogenation in the direct synthesis process. Science 323, 1037–1041 (2009). \n5.\t Solsona, B. E. et al. Direct synthesis of hydrogen peroxide from $\\mathrm{H}_{2}$ and $\\mathrm{~O}_{2}$ using $\\mathrm{Al}_{2}\\mathrm{O}_{3}$ supported Au–Pd catalysts. Chem. Mater. 18, 2689–2695 (2006). \n6.\t Freakley, S. J. et al. Palladium–tin catalysts for the direct synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ with high selectivity. Science 351, 965–968 (2016). \n7.\t Samanta, C. Direct synthesis of hydrogen peroxide from hydrogen and oxygen: an overview of recent developments in the process. Appl. Catal. A Gen. 350, 133–149 (2008). \n8.\t Edwards, J. K., Freakley, S. J., Lewis, R. J., Pritchard, J. C. & Hutchings, G. J. Advances in the direct synthesis of hydrogen peroxide from hydrogen and oxygen. Catal. Today 248, 3–9 (2015). \n9.\t Rankin, R. B. & Greeley, J. Trends in selective hydrogen peroxide production on transition metal surfaces from first principles. ACS Catal. 2, 2664–2672 (2012). \n10.\tSolsona, B. E. et al. Direct synthesis of hydrogen peroxide from $\\mathrm{H}_{2}$ and $\\mathrm{~O}_{2}$ using $\\mathrm{Al}_{2}\\mathrm{O}_{3}$ supported Au−​Pd catalysts. Chem. Mater. 18, 2689–2695 (2006). \n11.\tWood, K. N., O’Hayre, R. & Pylypenko, S. Recent progress on nitrogen/ carbon structures designed for use in energy and sustainability applications. Energy Environ. Sci. 7, 1212–1249 (2014). \n12.\tDrogui, P., Elmaleh, S., Rumeau, M., Bernard, C. & Rambaud, A. Hydrogen peroxide production by water electrolysis: application to disinfection. J. Appl. Electrochem. 31, 877–882 (2001). \n13.\tYamanaka, I. & Murayama, T. Neutral $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis by electrolysis of water and $\\mathrm{~O}_{2}$ . Angew. Chem. Int. Ed. 47, 1900–1902 (2008). \n14.\tSiahrostami, S. et al. Enabling direct $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production through rational electrocatalyst design. Nat. Mater. 12, 1137–1143 (2013). \n15.\tVerdaguer-Casadevall, A. et al. Trends in the electrochemical synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ : enhancing activity and selectivity by electrocatalytic site engineering. Nano Lett. 14, 1603–1608 (2014). \n16.\tFellinger, T.-P., Hasché, F., Strasser, P. & Antonietti, M. Mesoporous nitrogen-doped carbon for the electrocatalytic synthesis of hydrogen peroxide. J. Am. Chem. Soc. 134, 4072–4075 (2012). \n17.\tChoi, C. H. et al. Hydrogen peroxide synthesis via enhanced two-electron oxygen reduction pathway on carbon-coated Pt surface. J. Phys. Chem. C 118, \n30063–30070 (2014). \n18.\tPark, J., Nabae, Y., Hayakawa, T. & Kakimoto, M. Highly selective twoelectron oxygen reduction catalyzed by mesoporous nitrogen-doped carbon. ACS Catal. 4, 3749–3754 (2014). \n19.\tChoi, C. H. et al. Tuning selectivity of electrochemical reactions by atomically dispersed platinum catalyst. Nat. Commun. 7, 10922 (2016). \n20.\tChen, Z. et al. Development of a reactor with carbon catalysts for modularscale, low-cost electrochemical generation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . React. Chem. Eng. 2, \n239–245 (2017). \n21.\tJirkovský, J. S. et al. Single atom hot-spots at Au–Pd nanoalloys for electrocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. J. Am. Chem. Soc. 133, 19432–19441 (2011). \n22.\tPerazzolo, V. et al. Nitrogen and sulfur doped mesoporous carbon as metal-free electrocatalysts for the in situ production of hydrogen peroxide. Carbon 95, 949–963 (2015). \n23.\tSidik, R. A., Anderson, A. B., Subramanian, N. P., Kumaraguru, S. P. & Popov, B. N. $\\mathrm{O}_{2}$ reduction on graphite and nitrogen-doped graphite: experiment and theory. J. Phys. Chem. B 110, 1787–1793 (2006). \n24.\tHasché, F., Oezaslan, M., Strasser, P. & Fellinger, T.-P. Electrocatalytic hydrogen peroxide formation on mesoporous non-metal nitrogen-doped carbon catalyst. J. Energy Chem. 25, 251–257 (2016). \n25.\tLiu, Y., Quan, X., Fan, X., Wang, H. & Chen, S. High‐yield electrosynthesis of hydrogen peroxide from oxygen reduction by hierarchically porous carbon. Angew. Chem. Int. Ed. 54, 6837–6841 (2015). \n26.\tLi, N. et al. A novel carbon black graphite hybrid air-cathode for efficient hydrogen peroxide production in bioelectrochemical systems. J. Power Sources \n306, 495–502 (2016). \n27.\tMoraes, A. et al. Surface and catalytical effects on treated carbon materials for hydrogen peroxide electrogeneration. Electrocatalysis 7, 60–69 (2016). \n28.\tRosca, I. D., Watari, F., Uo, M. & Akasaka, T. Oxidation of multiwalled carbon nanotubes by nitric acid. Carbon 43, 3124–3131 (2005). \n29.\t Liang, Y. et al. $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocrystals on graphene as a synergistic catalyst for oxygen reduction reaction. Nat. Mater. 10, 780–786 (2011). \n30.\tAssumpção, M. et al. A comparative study of the electrogeneration of hydrogen peroxide using Vulcan and Printex carbon supports. Carbon 49, \n2842–2851 (2011). \n31.\tBarros, W. R. Oxygen reduction to hydrogen peroxide on $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ nanoparticles supported on Printex carbon and graphene. Electrochim. Acta 162, \n263–270 (2015). \n32.\tMehta, V. & Cooper, J. S. Review and analysis of PEM fuel cell design and manufacturing. J. Power Sources 114, 32–53 (2003). \n33.\tLu, Z. Superaerophilic carbon‐nanotube‐array electrode for high‐performance oxygen reduction reaction. Adv. Mater. 28, 7155–7161 (2016). \n34.\tDatsyuk, V. et al. Chemical oxidation of multiwalled carbon nanotubes. Carbon 46, 833–840 (2008). \n35.\tKundu, S., Wang, Y., Xia, W. & Muhler, M. Thermal stability and reducibility of oxygen-containing functional groups on multiwalled carbon nanotube surfaces: a quantitative high-resolution XPS and TPD/TPR study. J. Phys. Chem. C 112, 16869–16878 (2008). \n36.\tAndrews, R., Jacques, D., Qian, D. & Rantell, T. Multiwall carbon nanotubes: synthesis and application. Acc. Chem. Res. 35, 1008–1017 (2002). \n37.\t Huang, W., Wang, Y., Luo, G. & Wei, F. $99.9\\%$ purity multi-walled carbon nanotubes by vacuum high-temperature annealing. Carbon 41, 2585–2590 (2003). \n38.\tYue, Z., Jiang, W., Wang, L., Gardner, S. & Pittman, C. U. Surface characterization of electrochemically oxidized carbon fibers. Carbon 37, 1785–1796 (1999). \n39.\tBahn, S. R. & Jacobsen, K. W. An object-oriented scripting interface to a legacy electronic structure code. Comput. Sci. Eng. 4, 56–66 (2002). \n40.\tGiannozzi, P. et al. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials. J. Phys. Condens. Matter 21, 395502 (2009). \n41.\tAdllan, A. A. & Dal Corso, A. Ultrasoft pseudopotentials and projector augmented-wave data sets: application to diatomic molecules. J. Phys. Condens. Matter 23, 425501 (2011). \n42.\tWellendorff, J. et al. Density functionals for surface science: exchangecorrelation model development with Bayesian error estimation. Phys. Rev. B 85, 235149 (2012). \n43.\tNørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n\n# Acknowledgements \n\nThis work was initiated by the support of the Materials Sciences and Engineering Division of the Basic Energy Sciences office at the US Department of Energy, under contract DEAC02-76-SFO0515. We acknowledge support from SUNCAT seed funding in SLAC. We also gratefully acknowledge support from the Chemical Sciences, Geosciences, and Biosciences Division of the Office of Sciences at the US Department of Energy to the SUNCAT Center for Interface Science and Catalysis under award number DE-SC0004993. \n\n# Author contributions \n\nZ.L., G.C., S.S. and Y.C. conceived the research. Z.L., G.C., Z.C., K.L., J.X., L.L., T.W., D.L. and Y.L. performed the experiments. S.S. and J.K.N. performed the theoretical calculation. Z.L., G.C., Z.C., T.F.J. and Y.C. contributed new reagents and analytical tools. Z.L., G.C., S.S., Z.C., T.F.J., J.K.N. and Y.C. analysed the data. Z.L., G.C., S.S., Z.C., T.F.J., J.K.N. and Y.C. wrote the paper. \n\n# Competing interests \n\nThe authors declare no competing financial interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-017-0017-x. \n\nReprints and permissions information is available at www.nature.com/reprints. Correspondence and requests for materials should be addressed to Y.C. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1103_PhysRevLett.120.143001", + "DOI": "10.1103/PhysRevLett.120.143001", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevLett.120.143001", + "Relative Dir Path": "mds/10.1103_PhysRevLett.120.143001", + "Article Title": "Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics", + "Authors": "Zhang, LF; Han, JQ; Wang, H; Car, R; Weinull, E", + "Source Title": "PHYSICAL REVIEW LETTERS", + "Abstract": "We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.", + "Times Cited, WoS Core": 1319, + "Times Cited, All Databases": 1452, + "Publication Year": 2018, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000429119100003", + "Markdown": "# Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics \n\nLinfeng Zhang and Jiequn Han Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA \n\nHan Wang\\* Institute of Applied Physics and Computational Mathematics, Fenghao East Road 2, Beijing 100094, People’s Republic of China and CAEP Software Center for High Performance Numerical Simulation, Huayuan Road 6, Beijing 100088, People’s Republic of China \n\nRoberto Car Department of Chemistry, Department of Physics, Program in Applied and Computational Mathematics, Princeton Institute for the Science and Technology of Materials, Princeton University, Princeton, New Jersey 08544, USA \n\nWeinan E† \nDepartment of Mathematics and Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA \nand Center for Data Science, Beijing International Center for Mathematical Research, Peking University, Beijing Institute of Big Data Research, Beijing 100871, People’s Republic of China \n\n(Received 3 August 2017; published 4 April 2018) \n\nWe introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size. \n\nDOI: 10.1103/PhysRevLett.120.143001 \n\nMolecular dynamics (MD) is used in many disciplines, including physics, chemistry, biology, and materials science, but its accuracy depends on the model for the atomic interactions. $A b$ initio molecular dynamics (AIMD) [1,2] has the accuracy of density functional theory (DFT) [3], but its computational cost limits typical applications to hundreds of atoms and time scales of ${\\sim}100$ ps. Applications requiring larger cells and longer simulations are currently accessible only with empirical force fields (FFs) [4–6], but the accuracy and transferability of these models is often in question. \n\nDeveloping FFs is challenging due to the many-body character of the potential energy. Expansions in two- and three-body interactions may capture the physics [7], but are strictly valid only for weakly interacting systems. A large class of potentials, including the embedded atom method (EAM) [8], the bond order potentials [9], and the reactive FFs [10], share the physically motivated idea that the strength of a bond depends on the local environment, but the functional form of this dependence can only be given with crude approximations. \n\nMachine learning (ML) methodologies are changing this state of affairs [11–20]. When trained on large data sets of atomic configurations and corresponding potential energies and forces, ML models can reproduce the original data accurately. In training these models, the atomic coordinates cannot be used as they appear in MD trajectories because their format does not preserve the translational, rotational, and permutational symmetry of the system. Different ML models address this issue in different ways. Two successful schemes are the Behler-Parrinello neural network (BPNN) [13] and the gradient-domain machine learning (GDML) method [19]. In the BPNN, symmetry is preserved by mapping the coordinates onto a large set of two- and threebody symmetry functions, which are, however, largely ad hoc. Fixing the symmetry functions may become painstaking in systems with many atomic species. In the GDML, the same goal is achieved by mapping the coordinates onto the eigenvalues of the Coulomb matrix, whose elements are the inverse distances between all distinct pairs of atoms. It is not straightforward how to use the Coulomb matrix in extended periodic systems. \n\nSo far, GDML has only been used for relatively small molecules. \n\nIn this Letter, we introduce a neural network (NN) based scheme for MD simulations, called deep potential molecular dynamics (DPMD), which overcomes the limitations associated with auxiliary quantities like the symmetry functions or the Coulomb matrix (All the examples presented in this work are tested using the DeePMD-kit package [21], which is available at [22]). In our scheme, a local reference frame and a local environment is assigned to each atom. Each environment contains a finite number of atoms, whose local coordinates are arranged in a symmetry preserving way following the prescription of the deep potential method [23], an approach that was devised to train a NN with the potential energy only. With typical AIMD data sets, this is insufficient to reproduce the trajectories. DPMD overcomes this limitation. In addition, the learning process in DPMD improves significantly over the deep potential method thanks to the introduction of a flexible family of loss functions. The NN potential constructed in this way reproduces accurately the AIMD trajectories, both classical and quantum (path integral), in extended and finite systems, at a cost that scales linearly with system size and is always several orders of magnitude lower than that of equivalent AIMD simulations. \n\nIn DPMD, the potential energy of each atomic configuration is a sum of “atomic energies” $E=\\textstyle\\sum_{i}E_{i}$ , where $E_{i}$ is determined by the local environment of atom $i$ within a cutoff radius $R_{c}$ and can be seen as a realization of the embedded atom concept. The environmental dependence of $E_{i}$ , which embodies the many-body character of the interactions, is complex and nonlinear. The NN is able to capture the analytical dependence of $E_{i}$ on the coordinates of the atoms in the environment in terms of the composition of the sequence of mappings associated with the individual hidden layers. The additive form of $E$ naturally preserves the extensive character of the potential energy. Because of the analyticity of the atomic energies, DPMD is, in principle, a conservative model. \n\n$E_{i}$ is constructed in two steps. First, a local coordinate frame is set up for every atom and its neighbors inside $R_{c}$ [24]. This allows us to preserve the translational, rotational, and permutational symmetries of the environment, as shown in Fig. 1, which illustrates the format adopted for the local coordinate information $\\{D_{i j}\\}$ . The $1/R_{i j}$ factor present in $D_{i j}$ reduces the weight of the particles that are more distant from atom $i$ . \n\nNext, $\\{D_{i j}\\}$ serves as input of a deep neural network (DNN) [25], which returns $E_{i}$ in output (Fig. 2). The DNN is a feed forward network, in which data flow from the input layer to the output layer $(E_{i})$ , through multiple hidden layers consisting of several nodes that input the data $d_{l}^{\\mathrm{in}}$ from the previous layer and output the data $d_{k}^{\\mathrm{{out}}}$ to the next layer. A linear transformation is applied to the input data, i.e., $\\tilde{\\boldsymbol{d}}_{k}=$ $\\sum_{l}w_{k l}d_{l}^{\\mathrm{in}}+b_{k}$ , followed by action of a nonlinear function $\\varphi$ on $\\tilde{\\boldsymbol{d}}_{k}$ , i.e., $d_{k}^{\\mathrm{out}}=\\varphi(\\tilde{d}_{k})$ . In the final step from the last hidden layer to $E_{i}$ , only the linear transformation is applied. The composition of the linear and nonlinear transformations introduced above provides the analytical representation of $E_{i}$ in terms of the local coordinates. The technical details of this construction are discussed in the Supplemental Material [26]. In our applications, we adopt the hyperbolic tangent for $\\varphi$ and use five hidden layers with decreasing number of nodes per layer, i.e., 240, 120, 60, 30, and 10 nodes, respectively, from the innermost to the outermost layer. It is known empirically that the hidden layers greatly enhance the capability of neural networks to fit complex and highly nonlinear functional dependences [27,28]. In our case, only by including a few hidden layers could DPMD reproduce the trajectories with sufficient accuracy. \n\n![](images/4eec028f19f8266035bc1fb27a0dd2bd39e579ea0be08abc94d7daee995ba4c4.jpg) \nFIG. 1. Schematic plot of the neural network input for the environment of atom $i$ , taking water as an example. Atom $j$ is a generic neighbor of atom $i$ , $(e_{x},e_{y},e_{z})$ is the local frame of atom i, $e_{x}$ is along the $_\\mathrm{O-H}$ bond, $\\boldsymbol{e}_{z}$ is perpendicular to the plane of the water molecule, $\\boldsymbol{e}_{y}$ is the cross product of $\\pmb{e}_{z}$ and $e_{x}$ , and $(x_{i j},y_{i j},z_{i j})$ are the Cartesian components of the vector $\\pmb{R}_{i j}$ in this local frame. $R_{i j}$ is the length of $\\pmb{R}_{i j}$ . The neural network input $D_{i j}$ may either contain the full radial and angular information of atom $j$ , i.e., $D_{i j}=\\{1/R_{i j},x_{i j}/R_{i j}^{2},y_{i j}/R_{i j}^{2},z_{i j}/R_{i j}^{2}\\}$ or only the radial information, i.e., $\\dot{D_{i j}}=\\{1/R_{i j}\\}$ . We first sort the neighbors of atom $i$ according to their chemical species, e.g., oxygens first then hydrogens. Within each species, we sort the atoms according to their inverse distances to atom $i$ , i.e., $1/R_{i j}$ . We use $\\{D_{i j}\\}$ to denote the sorted input data for atom $i$ . \n\n![](images/af817281967fc2948c7458859df215c40568a2296108185e339cb8e726d03848.jpg) \nFIG. 2. Schematic plot of the DPMD model. The frame in the box is an enlargement of a DNN. The relative positions of all neighbors with respect to atom $i$ , i.e., $\\{R_{i j}\\}$ , is first converted to $\\{D_{i j}\\}$ , then passed to the hidden layers to compute $E_{i}$ . \n\nWe use the Adam method [29] to optimize the parameters $w_{k l}$ and $b_{k}$ of each layer with the family of loss functions \n\n$$\nL(p_{\\epsilon},p_{f},p_{\\xi})=p_{\\epsilon}\\Delta\\epsilon^{2}+\\frac{p_{f}}{3N}\\sum_{i}\\lvert\\Delta F_{i}\\rvert^{2}+\\frac{p_{\\xi}}{9}\\lvert\\lvert\\Delta\\xi\\rvert\\rvert^{2}.\n$$ \n\nHere $\\Delta$ denotes the difference between the DPMD prediction and the training data, $N$ is the number of atoms, $\\epsilon$ is the energy per atom, $\\boldsymbol{F}_{i}$ is the force on atom $i$ , and $\\xi$ is the virial tensor $\\begin{array}{r}{\\Xi=-\\frac{1}{2}\\sum_{i}{\\pmb{R}}_{i}\\otimes{\\pmb{F}}_{i}}\\end{array}$ divided by $N.$ In Eq. (1), $p_{\\epsilon},~p_{f}$ , and $p_{\\xi}$ are tunable prefactors. When virial information is missing from the data, we set $p_{\\xi}=0$ . In order to minimize the loss function in Eq. (1) in a well balanced way, we vary the magnitude of the prefactors during training. We progressively increase $p_{\\epsilon}$ and $p_{\\xi}$ and decrease $p_{f}$ , so that the force term dominates at the beginning, while energy and virial terms become important at the end. We find that this strategy is very effective and reduces the total training time to a few core hours in all the test cases. \n\nTo test the method, we have applied DPMD to extended and finite systems. As representative extended systems, we consider (a) liquid water at $P=1$ bar and $T=300~\\mathrm{K}$ , at the path-integral AIMD (PI-AIMD) level, (b) ice Ih at $P=1$ bar and $T=273\\mathrm{~K~}$ , at the PI-AIMD level, (c) ice Ih at $P=1$ bar and $T=330~\\mathrm{K}$ , at the classical AIMD level, and (d) ice Ih at $P=2.13$ kbar and $T=238\\mathrm{~K~}$ , which is the experimental triple point for ice I, II, and III, at the classical AIMD level. The variable periodic simulation cell contains $64~\\mathrm{H}_{2}\\mathrm{O}$ molecules in the case of liquid water and 96 $\\mathrm{H}_{2}\\mathrm{O}$ molecules in the case of ices. We adopt $R_{c}=6.0\\mathrm{~\\AA~}$ and use the full radial and angular information for the 16 oxygens and the 32 hydrogens closest to the atom at the origin, while retaining only radial information for all the other atoms within $R_{c}$ . All the ice simulations include proton disorder. Deuterons replace protons in simulations (c) and (d). The hybrid version of Perdew-Burke-Ernzerhof PBE0 $+$ Tkatchenko-Scheffler TS [30,31] functional is adopted in all cases. As representative finite systems, we consider benzene, uracil, naphthalene, aspirin, salicylic acid, malonaldehyde, ethanol, and toluene, for which classical AIMD trajectories with the Perdew-Burke-Ernzerhof PBE $+$ TS functional [31,32] are available [33]. In these systems, we set $R_{c}$ large enough to include all the atoms and use the full radial and angular information in each local frame. \n\nWe discuss the performance of DPMD according to four criteria: (i) generality of the model; (ii) accuracy of the energy, forces, and virial tensor; (iii) faithfulness of the trajectories; and (iv) scalability and computational cost [34]. \n\nGenerality.—Bulk and molecular systems exhibit different levels of complexity. The liquid water samples include quantum fluctuations. The organic molecules differ in composition and size, and the corresponding data sets include large numbers of conformations. Yet DPMD produces satisfactory results in all cases, using the same methodology, network structure, and optimization scheme. The excellent performance of DPMD in systems so diverse suggests that the method should be applicable to harder systems such as biological molecules, alloys, and liquid mixtures. \n\nTABLE I. The RMSE of the DPMD prediction for water and ices in terms of the energy, the forces, and/or the virial. The RMSEs of the energy and the virial are normalized by the number of molecules in the system. \n\n\n
SystemEnergy (meV)Force (meV/A)Virial (meV)
Liquid water1.040.42.0
Ice Ih (b)0.743.31.5
Ice Ih (c)0.726.8
Ice Ih (d)0.825.4...
\n\nAccuracy.—We quantify the accuracy of energy, forces, and virial predictions in terms of the root-mean-square error (RMSE) in the case of water and ices (Table I) and in terms of the mean absolute error (MAE) in the case of the organic molecules (Table II). No virial information was used for the latter. In the water case, the RMSE of the forces is comparable to the accuracy of the minimization procedure in the original AIMD simulations, in which the allowed error in the forces was less than $10^{-3}$ Hartree/Bohr. In the case of the molecules, the predicted energy and forces are generally slightly better than the GDML benchmark. \n\nMD trajectories.—In the case of water and ices, we perform path-integral or classical DPMD simulations at the thermodynamic conditions of the original models, using the I-PI software [35], but with much longer simulation time (300 ps). The average energy $\\bar{E}_{:}$ density $\\bar{\\rho}.$ , radial distribution functions (RDFs), and a representative angular distribution function (ADF), i.e., a three-body correlation function, are reproduced with high accuracy. The results are summarized in Table III. The RDFs and ADF of the quantum trajectories of water are shown in Fig. 3. The \n\nTABLE II. The MAE of the DPMD prediction for organic molecules in terms of the energy and the forces. The numbers in parentheses are the GDML results [19]. \n\n\n
MoleculeEnergy (meV)Force (meV/A)
Benzene(3.0)7.6 (10.0)
Uracil(4.0)9.8 (10.4)
Naphthalene(5.2)7.1 (10.0)
Aspirin(11.7)19.1 (42.9)
Salicylic acid(5.2)10.9 (12.1)
Malonaldehyde(6.9)12.7 (34.7)
Ethanol(6.5)8.3 (34.3)
Toluene(5.2)8.5 (18.6)
\n\nTABLE III. The equilibrium energy and density, $\\bar{\\boldsymbol{E}}$ and $\\bar{\\rho}$ , of water and ices, with DPMD and AIMD. The numbers in square brackets are the AIMD results. The numbers in parentheses are statistical uncertainties in the last one or two digits. The training AIMD trajectories for the ices are shorter and more correlated than in the water case. \n\n\n
SystemE (eV/HO)
Liquid water-467.678(2) [-467.679(6)]1.013(5)[1.013(20)]
Ice Ih (b)-467.750(1)[-467.747(4)] 0.967(1)[0.966(6)]
Ice Ih (c)-468.0478(3)[-468.0557(16)] 0.950(1) [0.949(2)]
Ice Ih (d)-468.0942(2) [-468.1026(9)] 0.986(1) [0.985(2)]
\n\nRDFs of ice are reported in the Supplemental Material. A higher-order correlation function, the probability distribution function of the $_{0-0}$ bond orientation order parameter $Q_{6}$ [36], is additionally reported in the Supplemental Material and shows excellent agreement between DPMD and AIMD trajectories. In the case of the molecules, we perform DPMD at the same temperature of the original data, using a Langevin thermostat with a damping time $\\tau=0.1$ ps. The corresponding distributions of interatomic distances are very close to the original data (Fig. 4). \n\nScalability and computational cost.—All the physical quantities in DPMD are sums of local contributions. Thus, after training on a relatively small system, DPMD can be directly applied to much larger systems. The computational cost of DPMD scales linearly with the number of atoms. Moreover, DPMD can be easily parallelized due to its local decomposition and the near-neighbor dependence of its atomic energies. In Fig. 5, we compare the cost of DPMD fixed-cell simulations (NVT) of liquid water with that of equivalent simulations with AIMD and the empirical FF TIP3P (transferable intermolecular potential with 3 points) [41] in units of CPU core seconds/step/molecule. \n\nWhile in principle the environmental dependence of $E_{i}$ is analytical, in our implementation, discontinuities are present in the forces, due to adoption of a sharp cutoff radius, limitation of angular information to a fixed number of atoms, and abrupt changes in the atomic lists due to sorting. These discontinuities are similar in magnitude to those present in the AIMD forces due to finite numerical accuracy in the enforcement of the Born-Oppenheimer condition. In both cases, the discontinuities are much smaller than thermal fluctuations and perfect canonical evolution is achieved by coupling the systems to a thermostat. We further note that long-range Coulomb interactions are not treated explicitly in the current implementation, although implicitly present in the training data. Explicit treatment of Coulombic effects may be necessary in some applications and deserves further study. \n\n![](images/c5c6d1590661c9caab6bc0aaf2cf3e3d21939ff9539c93df5c5ef8760a7695ae.jpg) \nFIG. 3. Correlation functions of liquid water from DPMD and PI-AIMD. (Left) RDFs. (Right) The O-O-O ADF within a cutoff radius of $3.7\\mathrm{~\\AA~}$ . \n\n![](images/4d0b597e39d0ab200bff642f5cb54b9cb0d452be9c9de6ed3d83ddffc2a4210a.jpg) \nFIG. 4. Interatomic distance distributions of the organic molecules. The solid lines denote the DPMD results. The dashed lines denote the AIMD results. \n\n![](images/418f1a91ae075ce8a9611a78fae6b93fd59f55b9b64aa0d966b8abc806a7f573.jpg) \nFIG. 5. Computational cost of MD step versus system size, with DPMD, TIP3P, $\\mathrm{PBE+TS}$ , and $\\mathrm{PBE0+TS}$ . All simulations are performed on a Nersc Cori supercomputer with the Intel Xeon CPU E5-2698 v3. The TIP3P simulations use the Gromacs codes (version 4.6.7) [42]. The $\\mathrm{PBE}+\\mathrm{TS}$ and $\\mathrm{PBE0+TS}$ simulations use the Quantum Espresso codes [43]. \n\nIn conclusion, DPMD realizes a paradigm for molecular simulation, wherein accurate quantum mechanical data are faithfully parametrized by machine learning algorithms, which make possible simulations of DFT-based AIMD quality on much larger systems and for much longer time than with direct AIMD. While substantially more predictive than empirical FFs, DFT is not chemically accurate [44]. In principle, DPMD could be trained with chemically accurate data from high-level quantum chemistry [45] and/or quantum Monte Carlo calculations [46], but so far this has been prevented by the large computational cost of these calculations. \n\nDPMD should also be very useful to coarse grain the atomic degrees of freedom, for example, by generating a NN model for a reduced set of degrees of freedom while using the full set of degrees of freedom for training. The above considerations suggest that DPMD should enhance considerably the realm of AIMD applications by successfully addressing the dilemma of accuracy versus efficiency that has confronted the molecular simulation community for a long time. \n\nThe authors acknowledge H.-Y. Ko and B. Santra for sharing the AIMD data on water and ice. The work of J. H. and W. E. is supported in part by Major Program of NNSFC under Grant No. 91130005, ONR Grant No. N00014-13-1- 0338, DOE Awards No. DE-SC0008626 and No. DESC0009248, and NSFC Grant No. U1430237. The work of R. C. is supported in part by DOE-SciDAC Grant No. DESC0008626. The work of H. W. is supported by the National Science Foundation of China under Grants No. 11501039 and No. 91530322, the National Key Research and Development Program of China under Grants No. 2016YFB0201200 and No. 2016YFB0201203, and the Science Challenge Project No. JCKY2016212A502. \n\n[10] A. C. T. van Duin, S. Dasgupta, F. Lorant, and W. A. Goddard, J. Phys. Chem. A 105, 9396 (2001). \n[11] A. P. Thompson, L. P. Swiler, C. R. Trott, S. M. Foiles, and G. J. Tucker, J. Comput. Phys. 285, 316 (2015). \n[12] T. D. Huan, R. Batra, J. Chapman, S. Krishnan, L. Chen, and R. Ramprasad, npj Comput. Mater. 3, 37 (2017). \n[13] J. Behler and M. Parrinello, Phys. Rev. Lett. 98, 146401 (2007). \n[14] J. Behler, J. Chem. Phys. 145, 170901 (2016). \n[15] T. Morawietz, A. Singraber, C. Dellago, and J. Behler, Proc. Natl. Acad. Sci. U.S.A. 113, 8368 (2016). \n[16] A. P. Bartók, M. C. Payne, R. Kondor, and G. Csányi, Phys. Rev. Lett. 104, 136403 (2010). \n[17] M. Rupp, A. Tkatchenko, K.-R. Müller, and O. A. von Lilienfeld, Phys. Rev. Lett. 108, 058301 (2012). \n[18] K. T. Schütt, F. Arbabzadah, S. Chmiela, K. R. Müller, and A. Tkatchenko, Nat. Commun. 8, 13890 (2017). \n[19] S. Chmiela, A. Tkatchenko, H. E. Sauceda, I. Poltavsky, K. T. Schütt, and K.-R. Müller, Sci. Adv. 3, e1603015 (2017). \n[20] J. S. Smith, O. Isayev, and A. E. Roitberg, Chem. Sci. 8, 3192 (2017). \n[21] Han Wang, Linfeng Zhan, Jiequn Han, and Weinan E, Comput. Phys. Commun. DOI: 10.1016/j.cpc.2018.03.016 (2018). \n[22] https://github.com/deepmodeling/deepmd-kit. \n[23] J. Han, L. Zhang, R. Car, and W. E, Commun. Comput. Phys. 23, 629 (2018). \n[24] Some flexibility can be used in the definition of the local frame of atom i. Usually we define it in terms of the two atoms closest to $i$ , independent of their species. Exceptions to this rule are discussed in the Supplemental Material. \n[25] I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning (MIT Press, Cambridge, MA, 2016). \n[26] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevLett.120.143001 for the technical details of the construction of the DNN model. \n[27] Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle, in Advances in Neural Information Processing Systems (MIT Press, Cambridge, 2007), p. 153. \n[28] A. Krizhevsky, I. Sutskever, and G. E. Hinton, Advances in Neural Information Processing Systems (Curran, Red Hook, 2012), p. 1097. \n[29] D. Kingma and J. Ba, arXiv:1412.6980. \n[30] C. Adamo and V. Barone, J. Chem. Phys. 110, 6158 (1999). \n[31] A. Tkatchenko and M. Scheffler, Phys. Rev. Lett. 102, 073005 (2009). \n[32] J. P. Perdew, K. Burke, and M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996). \n[33] http://quantum-machine.org/. \n[34] We refer to the Supplemental Material for full details on the DPMD implementation and the training data sets, which includes [23,29,35–40]. \n[35] M. Ceriotti, J. More, and D. E. Manolopoulos, Comput. Phys. Commun. 185, 1019 (2014). \n[36] W. Lechner and C. Dellago, J. Chem. Phys. 129, 114707 (2008). \n[37] M. Ceriotti, D. E. Manolopoulos, and M. Parrinello, J. Chem. Phys. 134, 084104 (2011). \n[38] G. J. Martyna, M. L. Klein, and M. Tuckerman, J. Chem. Phys. 97, 2635 (1992). \n[39] M. Parrinello and A. Rahman, Phys. Rev. Lett. 45, 1196 (1980). \n[40] S. Ioffe and C. Szegedy, in Proceedings of the 32nd International Conference on Machine Learning (PMLR, 2015), Vol. 37, pp. 448–456. \n[41] W. L. Jorgensen, J. Chandrasekhar, J. D. Madura, R. W. Impey, and M. L. Klein, J. Chem. Phys. 79, 926 (1983). \n[42] S. Pronk, S. Páll, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. Shirts, J. Smith, P. Kasson, D. van der \n\nSpoel, B. Hess, and E. Lindahl, Bioinformatics 29, 845 (2013). [43] P. Giannozzi et al., J. Phys. Condens. Matter 29, 465901 (2017). [44] Conventionally, chemical accuracy corresponds to an error of $1~\\mathrm{kcal/mol}$ in the energy. [45] J. D. Watts, J. Gauss, and R. J. Bartlett, J. Chem. Phys. 98, 8718 (1993). [46] D. Ceperley and B. Alder, Science 231, 555 (1986). " + }, + { + "id": "10.1038_s41467-018-04060-8", + "DOI": "10.1038/s41467-018-04060-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-04060-8", + "Relative Dir Path": "mds/10.1038_s41467-018-04060-8", + "Article Title": "Aqueous rechargeable zinc/sodium vanadate batteries with enhanced performance from simultaneous insertion of dual carriers", + "Authors": "Wan, F; Zhang, LL; Dai, X; Wang, XY; Niu, ZQ; Chen, J", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Rechargeable aqueous zinc-ion batteries are promising energy storage devices due to their high safety and low cost. However, they remain in their infancy because of the limited choice of positive electrodes with high capacity and satisfactory cycling performance. Furthermore, their energy storage mechanisms are not well established yet. Here we report a highly reversible zinc/sodium vanadate system, where sodium vanadate hydrate nullobelts serve as positive electrode and zinc sulfate aqueous solution with sodium sulfate additive is used as electrolyte. Different from conventional energy release/storage in zinc-ion batteries with only zinc-ion insertion/extraction, zinc/sodium vanadate hydrate batteries possess a simultaneous proton, and zinc-ion insertion/extraction process that is mainly responsible for their excellent performance, such as a high reversible capacity of 380 mAh g(-1) and capacity retention of 82% over 1000 cycles. Moreover, the quasi-solid-state zinc/sodium vanadate hydrate battery is also a good candidate for flexible energy storage device.", + "Times Cited, WoS Core": 1393, + "Times Cited, All Databases": 1458, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000430798100012", + "Markdown": "# Aqueous rechargeable zinc/sodium vanadate batteries with enhanced performance from simultaneous insertion of dual carriers \n\nFang Wan1, Linlin Zhang1, Xi Dai1, Xinyu Wang1, Zhiqiang Niu1 & Jun Chen1,2 \n\nRechargeable aqueous zinc-ion batteries are promising energy storage devices due to their high safety and low cost. However, they remain in their infancy because of the limited choice of positive electrodes with high capacity and satisfactory cycling performance. Furthermore, their energy storage mechanisms are not well established yet. Here we report a highly reversible zinc/sodium vanadate system, where sodium vanadate hydrate nanobelts serve as positive electrode and zinc sulfate aqueous solution with sodium sulfate additive is used as electrolyte. Different from conventional energy release/storage in zinc-ion batteries with only zinc-ion insertion/extraction, zinc/sodium vanadate hydrate batteries possess a simultaneous proton, and zinc-ion insertion/extraction process that is mainly responsible for their excellent performance, such as a high reversible capacity of $380m{\\tt A h g}^{-1}$ and capacity retention of $82\\%$ over 1000 cycles. Moreover, the quasi-solid-state zinc/sodium vanadate hydrate battery is also a good candidate for flexible energy storage device. \n\nithium-ion batteries have been widely used in portable electronics and considered for electric vehicles, as well as ■ large-scale energy storage systems due to their high energy density1,2. However, the increasing concerns about cost, safety, the limited lithium resources as well as environmental impact motivate the search of alternative battery systems3–5. In this regard, rechargeable aqueous batteries are the promising alternatives since the utilization of aqueous electrolytes will contribute to better safety, lower cost, easier processing, and higher ionic conductivity compared with the case of organic electrolytes6–8. Among various aqueous batteries, there is a growing interest in aqueous $Z\\mathrm{n}$ -ion batteries (ZIBs) due to the distinctive merits of $Z\\mathrm{n}$ , in terms of high theoretical capacity $(820\\mathrm{mAh\\g^{-1}},$ ), low redox potential $-0.76\\mathrm{V}$ vs. standard hydrogen electrode), excellent stability in water, and nontoxicity9–14. \n\nRecently, significant research efforts have been made in designing the materials and devices of aqueous $\\mathrm{ZIBs}^{15-32}$ . However, aqueous ZIBs are still in their infancy and there are still some challenges, which limit the practical application of aqueous ZIBs. For instance, although some active materials such as $\\mathrm{MnO}_{2}{}^{20-24}$ , $\\mathrm{Mo}_{6}\\mathrm{S}_{8}{}^{29,30}$ , prussian blue analogs25–28, $\\mathrm{Na}_{3}\\mathrm{V}_{2}(\\mathrm{PO}_{4})_{3}{}^{31}$ , and vanadium-based compounds16–18 have been fabricated as the positive electrodes of aqueous ZIBs, most of them often exhibit limited capacity of less than $300\\mathrm{mAhg^{-1}}$ and/ or poor cycling performance. In addition, the conventional energy release/storage mechanism of ZIBs is the insertion/ extraction of $Z\\mathrm{n}^{2+}$ in the host materials16–18,31,33. However, in some cases of $\\mathrm{Zn}/\\mathrm{MnO}_{2}$ system, the chemical conversion reaction between $\\mathrm{MnO}_{2}$ and $\\mathrm{H^{+}}$ can also mainly contribute to the good electrochemical performance of the highly reversible $\\mathrm{Zn/MnO}_{2}$ system24. Both different mechanisms in $\\mathrm{MnO}_{2}$ positive electrodes may be attributed to their variety in crystallographic polymorph and particle size, which are dependent on the ion insertion thermodynamics and kinetics of $\\mathrm{\\bar{H}^{+}}$ and $Z\\mathrm{n}^{2+}$ . As a result, $\\mathrm{H^{+}}$ and $Z n^{2^{*}+}$ cannot simultaneously insert into $\\mathrm{MnO}_{2}$ and their insertion is often a two-step process, where $\\mathrm{H^{+}}$ first inserts into $\\mathrm{MnO}_{2}$ and then $Z\\mathrm{n}^{2+34}$ . Compared with a consequent insertion process, simultaneous insertion of dual carriers would achieve enhanced synergistic effect of their ion insertion thermodynamics and kinetics35,36. Therefore, the feasible host materials that are able to carry out a simultaneous $\\mathrm{H^{+}}$ and $\\mathrm{Zn}^{2+}$ insertion/ extraction process with enhanced performance should be considered and developed. \n\nOwing to the low cost and multivalence of vanadium, vanadates have been utilized as the positive electrodes of lithium/ sodium-ion batteries37–41. As one of promising positive electrodes, $\\mathrm{NaV}_{3}\\mathrm{O}_{8}$ is composed of $\\mathrm{V}_{3}\\mathrm{O}_{8}$ layers and inserted sodium ions39. More importantly, the interlayer distance $(0.708\\mathrm{nm})$ of $\\mathrm{NaV}_{3}\\mathrm{O}_{8}$ would be large enough to enable the insertion/extraction of $Z\\mathrm{n}^{2+}$ $(0.074\\mathrm{nm})$ , and $\\mathrm{H}^{\\mp}$ could steadily exist between the $\\mathrm{V}_{3}\\mathrm{O}_{8}$ layers42,43. Therefore, the nanostructured $\\mathrm{NaV}_{3}\\mathrm{O}_{8}$ would be an ideal positive electrodes of aqueous rechargeable ZIB with a simultaneous $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ insertion/extraction process. \n\nHere we fabricate $\\mathrm{NaV}_{3}\\mathrm{O}_{8}{\\cdot}1.5\\mathrm{H}_{2}\\mathrm{O}$ (NVO) nanobelts by a simple liquid–solid stirring strategy. The interlayer water and sodium ions could act as pillars to stabilize the $\\mathrm{V}_{3}\\mathrm{O}_{8}$ layers during the charge/discharge process. As the positive electrodes for aqueous ZIBs, they exhibit a simultaneous $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ insertion/ extraction process with a high reversible capacity of $380\\mathrm{mAhg^{-1}}$ and enhanced cycling performance by the addition of ${\\mathrm{Na}}_{2}{\\mathrm{SO}}_{4}$ into the $\\mathrm{ZnSO_{4}}$ electrolyte to inhibit the dissolution of NVO and Zn dendrite deposition synchronously. Furthermore, the nanobelt structure of NVO endows their corresponding positive electrodes with the ability of being bent without any cracks to serve as the electrodes of flexile ZIBs. As a proof of concept, flexible softpackaged ZIBs are assembled using quasi-solid-state electrolyte, exhibiting stable electrochemical performances at different bending states. \n\n# Results \n\nPreparation and characterization of NVO nanobelts. NVO nanobelts were prepared through a facile liquid–solid stirring method, just stirring the $\\mathrm{V}_{2}\\mathrm{O}_{5}$ powder in NaCl aqueous solution (Methods section for details). With the increase of stirring time, the color of suspension changed from yellow to black red (Supplementary Fig. 1) due to the insertion of sodium ions into ${\\mathrm{V}}_{x}{\\mathrm{O}}_{y}$ layers and the formation of nanobelt morphology via a dissolution-recrystallization process44,45. The crystalline phase of as-prepared sample was tested by X-ray diffraction (XRD), as shown in Fig. 1a. Its characteristic peaks are in good agreement with NVO with $\\mathrm{P}2_{1}/\\mathrm{m}$ space group (JCPDS: 16–0601). In the $\\mathbf{P}2_{1}/$ m NVO, hydrated sodium ions, acting as pillars, are between the $\\mathrm{V}_{3}\\mathrm{O}_{8}$ layers to stabilize the layered structure, which consists of edge-sharing $\\mathrm{VO}_{5}$ tetragonal pyramids and ${\\mathrm{VO}}_{6}$ octahedrons, as depicted in Fig. 1b. Furthermore, obviously, the XRD pattern suggests the high purity of the as-prepared NVO, which can also be confirmed by combining its $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) with Fourier transform infrared (FTIR) spectra (Supplementary Fig. 2). The XPS spectroscopy of the as-prepared NVO shows six peaks that all belong to Na, V, and O without other impure elements. In its FTIR spectra, absorption bands located at 968 and $999c m^{-1}$ are assigned to stretching vibrations of $\\mathrm{V=O}$ , while those at 545, 732, 1400, and $1633\\mathrm{{cm}^{-1}}$ are ascribed to symmetric and asymmetric stretching vibrations of $_{\\mathrm{v-O-V}}$ bonds, vibrations of $_\\mathrm{Na-O}$ bonds as well as crystal water vibrations, respectively46–48. \n\n![](images/2b263667a03d77f3a494adbf41cea400a8d7b9d4192a3182333b75ca9652f038.jpg) \nFig. 1 Crystal structure and morphology of NVO. a XRD pattern of NVO nanobelts. b Crystal structure of NVO nanobelts, $\\mathsf{N a}^{+}$ exists in the form of hydrated ion. c SEM, d TEM, e high-resolution TEM, and f TEM elemental mapping images of NVO nanobelts. Scale bars of $1\\upmu\\mathrm{m}.$ , 200, 5 and $400\\mathsf{n m}$ , respectively \n\n![](images/ce583da3e109e8c14ebd198db2c7ea1ce42cd5e89114e1dc6d0abbb00fac10da.jpg) \nFig. 2 Electrochemical performance of Zn/NVO batteries in 1 M $Z n S O_{4}$ electrolyte and function of ${\\mathsf N a}_{2}{\\mathsf S}{\\mathsf O}_{4}$ electrolyte additive. a First charge/discharge curve of NVO electrode in $Z n S O_{4}$ electrolyte. b Comparison of reversible capacity and operating voltage between NVO nanobelts and other reported positive electrode materials. c Cycling performance of NVO electrode in $Z n S O_{4}$ electrolyte. The insets are optical images of NVO electrodes in $Z n S O_{4}$ and $Z n S O_{4}/N a_{2}S O_{4}$ electrolytes for different periods. SEM images of the Zn negative electrode surface from Zn/steel mesh batteries after one CV cycle from –0.2 to $0.3\\mathrm{V}$ in d $Z n S O_{4}$ and e $Z n S O_{4}/N a_{2}S O_{4}$ electrolytes. Scale bars, $2\\upmu\\mathrm{m}$ . f Schematic diagram: ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ additive suppresses the dissolution of NVO nanobelts and the formation of $Z n$ dendrites \n\nFigure 1c and Supplementary Fig. 3 are the typical scanning electron microscopy (SEM) images of NVO, showing a homogeneous nanobelt morphology. They are tens of micrometers in length and $50{-}200\\mathrm{nm}$ in width. Transmission electron microscopy (TEM) image also affirms their anisotropic and flat morphology with high aspect ratio, as well as their crystallinity (Fig. 1d, e). The interplanar spacings of 0.23 and $0.15\\mathrm{nm}$ , corresponding to $(-303)$ and (123) planes of NVO nanobelts, respectively, are observed in their high-resolution TEM image (Fig. 1e), which is well matched with the XRD result (Fig. 1a). In addition, the homogeneous distributions of Na, V, and O in NVO nanobelts were further evidenced by TEM elemental mapping images in Fig. 1f. Such favorable morphological features would be beneficial for the fast kinetics of the carrier insertion/extraction. \n\nElectrochemical performance of NVO nanobelts. The electrochemical performances of NVO nanobelts as the positive electrodes of ZIBs were investigated in assembled coin cells. In contrast to traditional alkaline Zn-based batteries with poor coulombic efficiency and fast capacity decay7, mild $1\\mathrm{M}\\ Z\\mathrm{nSO_{4}}$ aqueous solution was initially used as the electrolyte in our case. The NVO nanobelts deliver an average operating voltage of about $0.8\\mathrm{V}$ vs. $Z\\mathrm{n}^{2+}/Z\\mathrm{n}$ , as well as a high reversible capacity of 380 $\\mathrm{mAh~g^{-1}}$ based on the mass of NVO in positive electrode in the first cycle at a current density of $0.05\\dot{\\mathrm{Ag}}^{-1}$ (Fig. 2a), which is higher than those of previously reported positive electrodes (Fig. 2b)7,15–19,24–31. However, unfortunately, a rapid degradation in capacity occurs with an increase in the cycle number, decaying to only $3\\dot{3}\\mathrm{mAh}\\mathrm{g}^{-1}$ after 300 cycles at a current density of $0.5\\mathrm{A}$ $\\mathbf{g}^{-1}$ (Fig. 2c). Such rapid capacity fading would be ascribed to the fast dissolution of NVO in the aqueous $\\mathrm{ZnSO_{4}}$ electrolyte and the formation of vertical and harsh $Z\\mathrm{n}$ dendrites, as suggested by the inset in Fig. 2c, d, respectively. The addition of $\\mathrm{Na}^{\\mathrm{\\mp}}$ into the electrolyte can change the dissolution equilibrium of $\\mathrm{Na^{+}}$ from NVO electrodes and thus impede the continuous NVO dissolution. To confirm this, NVO electrodes were dipped into the $\\mathrm{ZnSO_{4}}$ electrolytes with different concentrations of $\\mathrm{\\DeltaNa_{2}S O_{4}}$ (the inset in Fig. 2c and Supplementary Fig. 4). When the concentration of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ is up to $1\\mathrm{M}$ , the electrolyte would be transparent and colorless even when the NVO positive electrodes were in the electrolyte for $24\\mathrm{h}$ , indicating that the NVO dissolution was suppressed. Therefore, 1 M $\\mathrm{N}\\mathrm{\\bar{a}}_{2}\\mathrm{SO}_{4}$ was added into the $\\mathrm{ZnSO_{4}}$ electrolyte as the electrolyte additive in our $Z_{\\mathrm{{n/NVO}}}$ system. In addition, according to electrostatic shield mechanism, the dendrite deposition during charge process would be avoided by adding other positive ions with lower reduction potential into electrolyte49. Compared with $Z\\mathrm{n}^{2+}$ , $\\mathrm{Na^{+}}$ has a lower reduction potential. As a result, the addition of ${\\ N a}_{2}{\\ S}{\\ O}_{4}$ in $\\mathrm{ZnSO_{4}}$ electrolyte could effectively avoid the growth of $Z\\mathrm{n}$ dendrites (Fig. 2e, Supplementary Figs 6 and 7) in comparison with the case of $\\mathrm{ZnSO_{4}}$ electrolyte without $\\mathrm{Na}_{2}\\mathrm{SO}_{4}.$ where a large number of vertical and harsh Zn dendrites formed on the surface of $Z\\mathrm{n}$ negative electrode (Fig. 2d, Supplementary Figs 5 and 6). Therefore, the $\\mathrm{Na^{+}}$ from ${\\ N a}_{2}{\\ S}{\\ O}_{4}$ not only can prevent the dissolution of NVO, but also suppresses the $Z\\mathrm{n}$ dendrite deposition, as depicted in Fig. 2f. \n\n![](images/a3a0a5e99f24b97ed6684ad3832c758bbd36c8780931d81d988da9fa790e1679.jpg) \nFig. 3 Electrochemical performance of Zn/NVO batteries in 1 M $Z n S O_{4}$ electrolyte with 1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ additive. Comparison of a second CV curves $(0.1\\mathsf{m V}$ $\\mathsf{s}^{-1},$ ) and b cycling performance $(1\\mathsf{A}\\mathsf{g}^{-1})$ of NVO electrodes in $Z n S O_{4}$ and $Z n S O_{4}/N a_{2}S O_{4}$ electrolytes. c Long-term cycle life $(4\\mathsf{A}\\mathsf{g}^{-1})$ and d rate performance of NVO electrodes in $Z n S O_{4}/N a_{2}S O_{4}$ electrolyte. e Comparison of energy and power densities of $Z n/N V O$ battery with ZIBs based on reported positive electrodes \n\nFigure 3a compares the second cyclic voltammetly (CV) profiles of the $Z_{\\mathrm{{n}/\\mathrm{{NVO}}}}$ batteries based on electrolytes with and without $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ additive. They display two pairs of similar redox peaks, indicating that the addition of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ leads to negligible change in the redox reactions of $Z_{\\mathrm{{n/NVO}}}$ batteries. It is also affirmed by their charge/discharge curves (Supplementary Fig. 8). Moreover, the two pairs of redox peaks locating at $0.55/0.77$ and $0.85/1.06\\mathrm{V}$ can be ascribed to the reversible redox reactions from $\\mathrm{NaZn_{0.1}V_{3}O_{8}{\\cdot}1.5H_{2}O}$ to $\\mathrm{H}_{2.14}\\mathrm{NaZn}_{0.2}\\mathrm{V}_{3}\\mathrm{O}_{8}{\\cdot}1.5\\mathrm{H}_{2}\\mathrm{O}$ and then $\\mathrm{H_{3.9}N a Z n_{0.5}V_{3}O_{8}{\\cdot}1.5H_{2}O}$ (corresponding calculation process and analysis see Supplementary Information and following energy storage mechanism section), corresponding to the valence changes of vanadium from $\\mathrm{V}^{5+}$ to $\\mathrm{V}^{\\dot{4}+}$ and $\\mathrm{V}^{4+}$ to $\\mathrm{V}^{3+}$ respectively50–52. More importantly, it is noted that, after first cycle, subsequent four cycles show a nearly overlapping shape in the $Z_{\\mathrm{{n/NVO}}}$ battery with $\\mathrm{ZnSO_{4}/N a_{2}S O_{4}}$ electrolyte (Supplementary Fig. 9). In contrast, the corresponding CV curves in the case of $\\mathrm{ZnSO_{4}}$ electrolyte without $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ significantly decrease with the increase of cycles. These indicate that the addition of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ endows $Z_{\\mathrm{{n/NVO}}}$ battery with better reversibility of carrier insertion/extraction. Therefore, the capacity of $Z_{\\mathrm{{n/NVO}}}$ battery with $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ additive can still stabilize at $221\\mathrm{mAhg^{-1}}$ after 100 cycles with a retention rate of $90\\%$ at a current density of $1\\mathrm{Ag^{-1}}$ , which is superior to that $(84\\mathrm{mAh}\\mathrm{g}^{-1}$ , a retention rate of $34\\%$ ) of the case without $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ additive (Fig. 3b). Such excellent electrochemical performance is ascribed to the restriction of continuous NVO dissolution and $Z\\mathrm{n}$ dendrite formation through the addition of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}.$ as suggested in Fig. 4a, b. There are lots of harsh black depositions that consist of Na, V, Zn, S, and O elements formed on the surface of $Z\\mathrm{n}$ negative electrode from battery after 100 cycles at $\\mathbf{1}\\mathrm{Ag}^{-1}$ without $\\bar{\\bf N}{\\bf a}_{2}\\mathrm{SO}_{4}$ additive (Fig. 4a), suggesting that some side reactions have happened on the Zn negative electrode because of the dissolved NVO in the electrolyte. In contrast, the $Z\\mathrm{n}$ negative electrode from battery with $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ additive is clean and smooth after 100 cycles at 1 A $\\mathbf{g}^{-1}$ (Fig. 4b), revealing that ${\\ N a}_{2}{\\ S}{\\ O}_{4}$ additive indeed avoids the side reactions and the growth of $Z\\mathrm{n}$ dendrites on the Zn negative electrode. The morphology and structure evolution of NVO during the charge/discharge process is also important for the stable electrochemical properties of $Z_{\\mathrm{{n/NVO}}}$ batteries. Compared with the original NVO nanobelts (Fig. 4c), the NVO nanobelts in the positive electrodes still display a similar morphology without obvious change after discharging to $0.3\\mathrm{V}$ (Fig. 4d) and recharging to $1.25\\mathrm{V}$ (Fig. 4e). Even after 100 cycles, the nanobelt morphology of NVO can still be distinguished clearly (Fig. 4f), suggesting high morphology and structure stability of NVO during the charge/discharge process. It is beneficial for the stable cycling performance of $Z_{\\mathrm{{n/NVO}}}$ batteries. Therefore, the $Z\\mathrm{n}/$ NVO batteries with $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ additive display long-term cycle life with a high capacity retention ratio of $82\\%$ even after 1000 cycles at $4\\mathrm{Ag^{-1}}$ (Fig. 3c). \n\n![](images/6eb6ba4fd676e936d8068264ca0cddebac30a3b61cd378ba856681a6e296b959.jpg) \nFig. 4 Morphology change of $Z n$ negative electrode and NVO positive electrode after cycling and kinetics of electrochemical process. SEM images and corresponding EDS analysis of Zn negative electrodes $(1\\mathsf{A}\\mathsf{g}^{-1}$ , 100th cycle) from $Z n/N V O$ batteries based on a $Z n S O_{4}$ and b $Z n S O_{4}/N a_{2}S O_{4}$ electrolytes. Scale bars, $2\\upmu\\mathrm{m}$ . SEM images of NVO electrodes at different states: c origin, d first discharged to $0.3\\mathrm{V}.$ e first charged to $1.25\\mathrm{V}.$ and f after 100 cycles at $0.1\\mathsf{A g}^{-1}$ in $Z n S O_{4}/N a_{2}S O_{4}$ electrolyte. Scale bars, $1\\upmu\\mathrm{m}$ . $\\pmb{\\mathsf{g}}\\mathsf{C V}$ curves of NVO electrode at different scan rates in $Z n S O_{4}/N a_{2}S O_{4}$ electrolyte and $\\boldsymbol{\\mathsf{h}}$ the corresponding plots of log (peak current) vs. log (scan rate) at each peak. i The capacitive contributions at different scan rates in $Z n S O_{4}/N a_{2}S O_{4}$ electrolyte \n\nApart from the high capacity retention ratio, the NVO nanobelts also exhibit excellent rate capability, as displayed in Fig. 3d. They can display a high capacity of $165^{\\prime}\\mathrm{mAh\\g^{-}}^{\\prime}$ at a high current density of $\\mathbf{\\dot{\\boldsymbol{4}}\\boldsymbol{A}}\\mathbf{g}^{-1}$ (the charge/discharge process was completed in $5\\mathrm{{min}}$ ), maintaining $44\\%$ of that at $0.{\\dot{1}}\\operatorname{A}\\operatorname{g}^{-1}$ . This performance is much higher than that $(80\\mathrm{mAh}\\mathrm{g}^{-1}$ at $4\\mathrm{Ag^{-1}}$ maintaining $25\\%$ of that at $0.1\\mathrm{Ag}^{-1}$ ) of NVO nanorods (Supplementary Fig. 10) because the favorable nanobelt morphology is beneficial for the fast kinetics of the carrier insertion/ extraction. Furthermore, the plateaus in charge–discharge curves can still be easily distinguished even at the high current density of $4\\mathrm{Ag^{-1}}$ . In addition, impressively, when the current density abruptly recovers from 4 to $0.1\\mathrm{A}\\dot{\\mathrm{g}}^{-1}$ after 30 cycles, the capacity of NVO nanobelts is able to recover to $310\\mathrm{\\dot{mAh}g^{-1}}$ (Supplementary Fig. 11). As a result, our $Z_{\\mathrm{{n/NVO}}}$ batteries display not only a superior energy density $(300\\mathrm{Wh}\\mathrm{kg}^{-1}),$ but also an impressive power energy density $(3600\\mathrm{W}\\mathrm{kg}^{-1}\\mathrm{\\Omega}^{\\cdot}$ based on the mass of NVO in positive electrode. Compared with previous reported ZIBs based on various active materials, the $\\bar{Z}\\mathrm{n/NVO}$ batteries deliver steady and higher energy densities over a wide range of power densities, as displayed in the Ragone plots (Fig. 3e)9,16,27,31,33. The high rate performance of $Z_{\\mathrm{{n/NVO}}}$ batteries significantly depends on their kinetics origin, which was investigated by CV characterizations in detail. Figure $4\\mathrm{g}$ displays the CV curves of the $Z_{\\mathrm{{n/NVO}}}$ batteries at different scan rates from 0.1 to $0.5\\mathrm{mVs^{-1}}$ with a voltage window from 0.3 to $1.25\\mathrm{V}$ . There are two reduction peaks and two oxidation peaks in each curve. Their peak currents $(i)$ and scan rates (v) have a relationship as below:53,54 \n\n$$\ni=a\\nu^{\\mathrm{b}},\n$$ \n\nwhich can be rewritten as \n\n$$\n\\log(i)=b\\log(\\nu)+\\log(a),\n$$ \n\nwhere $b$ represents the slope of $\\log(i)$ vs. $\\log(\\nu)$ curve, which is often in a range of 0.5–1. When $b$ value is 0.5, the electrochemical process is controlled by ionic diffusion. If $b$ value reaches to 1, the pseudocapacitance will dominate the charge/discharge process. By fitting the plots of $\\log(i)$ vs. $\\log(\\nu)$ (Fig. 4h), the calculated $b$ values of peak 1, 2, 3, and 4 are 0.63, 0.83, 0.68, and 0.65, respectively, indicating that the electrochemical reaction of $Z\\mathrm{n}/$ NVO batteries is controlled by ionic diffusion and pseudocapacitance synchronously. This characteristic is responsible for the high rate performance of the $Z_{\\mathrm{{n/NVO}}}$ batteries. In addition, the capacitive contribution can be calculated through the following \n\n![](images/9f99a6381a510aca74616b20a084d162e268536d5d0845571d51a96da2d04356.jpg) \nFig. 5 Simultaneous $\\mathsf{H}^{+}$ and $Z n^{2+}$ insertion/extraction mechanism. a Second charge/discharge curve of NVO nanobelts at $0.1\\mathsf{A g}^{-1}$ . Ex situ b XRD patterns, c FTIR spectra, d solid state $^1\\mathsf{H}$ NMR, and XPS spectra of e $Z n\\ 2\\mathsf{p}$ and f V $2{\\mathsf{p}}$ at selected states \n\nequation55,56: \n\n$$\ni=k_{1}\\nu+k_{2}\\nu^{1/2},\n$$ \n\nwhich can be reformulated as \n\n$$\ni/\\nu^{1/2}=k_{1}\\nu^{1/2}+k_{2},\n$$ \n\nwhere i, $k_{1}\\nu,$ and $k_{2}\\nu^{1/2}$ represent the current response, capacitive, and ionic diffusion contribution, respectively. Since $k_{1}$ can be obtained by fitting the $i/\\nu^{1/2}$ vs. $\\mathbf{\\Sigma}_{\\nu}^{\\mathbf{\\scriptscriptstylei}/2}$ plots, the capacitive contribution is calculated to be $44.8\\%$ at the scan rate of 0.1 $\\mathrm{m}\\mathrm{V}\\thinspace s^{-1}$ . With the increase of scan rate, the percentage of capacitive contribution raises to $51.6\\%$ , $58.1\\%$ , $61.8\\%$ , and $67.8\\%$ at the scan rates of 0.2, 0.3, 0.4, and $0.5\\mathrm{mVs^{-1}}$ , respectively (Fig. 4i), revealing that the $Z_{\\mathrm{{n/NVO}}}$ batteries have favorable charge transfer kinetics. \n\nThe excellent performance of $Z_{\\mathrm{{n/NVO}}}$ coin-type batteries motivated us to fabricate soft-packed batteries with a high theoretical capacity of $1520\\mathrm{mAh}$ (Supplementary Fig. 12a). They display a charge capacity of $1040\\mathrm{mAh}$ in the first cycle (completed in $0.5\\mathrm{h}\\dot{}$ ), the corresponding energy density is 144 $\\dot{\\mathrm{Wh}}\\dot{\\mathrm{kg}}^{-1}$ based on the total mass of NVO positive electrode and $Z\\mathrm{n}$ negative electrode, which is higher than other aqueous lithium-ion batteries $(50{-}100\\mathrm{Wh}\\mathrm{kg}^{-1})$ and aqueous sodium-ion batteries $(\\sim30\\mathrm{Wh}\\mathrm{kg}^{-1})^{8,57-59}$ . Furthermore, according to the total weight of whole soft-packed battery, they still achieve a high energy density of $70\\mathrm{Wh}\\mathrm{kg^{-1}}$ that is higher than those of commercial $\\mathrm{Pb}$ -acid and Ni-Cd batteries23. In addition, it is noted that a high capacity of $800\\mathrm{mAh}$ can be obtained even after 100 cycles at $0.5\\mathrm{\\dot{A}g^{-1}}$ (Supplementary Fig. 12b), displaying the potential in practical application. \n\nEnergy storage mechanism. At the selected states of second charge/discharge process, as marked in the Fig. 5a, various ex situ tests including XRD, FTIR, solid state $\\mathrm{^1H}$ nuclear magnetic resonance $\\mathrm{^{*}H N M R})$ , and XPS were utilized to analyze the NVO positive electrodes for further understanding the energy storage mechanism of $Z_{\\mathrm{{n/NVO}}}$ systems. It is interesting that $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}}$ (JCPDS: 39–688) is successively formed during the discharge process, as reflected by the ex situ XRD analysis (Fig. 5b and Supplementary Fig. 13). Subsequently, $\\mathrm{Zn_{4}S O_{4}(O H)_{6}\\bullet\\cdot4H_{2}O}$ gradually disappears after charging from 0.3 to $1.25\\mathrm{V}$ . These results indicate the reversible and successive formation/decomposition of $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}}$ on the positive electrode during the charge/discharge process, which was also proved by the FTIR spectra at the selected charge/discharge states (Fig. 5c). In the FTIR spectra, the intensity of peak at $11\\dot{2}0\\mathrm{cm}^{-1}$ belonging to $\\mathrm{Zn_{4}S O_{4}(\\bar{O}H)_{6}{*4}H_{2}O}$ is gradually enhanced in the discharge process60. While in the charge process, it becomes weaker gradually and completely invisible at fully charged state. In the $Z_{\\mathrm{{n/NVO}}}$ systems, the $\\mathrm{OH^{-}}$ in $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}}$ comes from the decomposition of water in the aqueous $\\mathrm{ZnSO_{4}/N a_{2}S O_{4}}$ electrolyte. As a result, a large amount of $\\mathrm{H^{+}}$ yields synchronously. To reach a neutral charge system, these $\\mathrm{H^{+}}$ could not exist in the electrolyte and would move into the positive electrode to balance its rich electron during the discharge procedure. To confirm the continuous insertion/extraction of $\\mathrm{\\bar{H}}^{\\bar{+}}$ in the NVO during the charge/discharge process, the NVO-based positive electrodes were characterized by ex situ solid state $^1\\mathrm{H}$ NMR at the selected states during the second cycling, as displayed in Fig. 5d. Compared with the initial state, there is an extra peak at $2.7\\mathrm{ppm}$ at the selected charge/discharge states. Since this peak is not assigned to the $^1\\mathrm{H}$ from the hydroxyl and crystal water of $\\mathrm{Zn_{4}\\bar{S}O_{4}(O H)_{6}{*4}H_{2}O_{5}}$ which is usually located at $\\mathrm{i}.5\\mathrm{ppm}^{24}$ , this extra peak would be ascribed to the $\\dot{\\mathrm{H}}^{+}$ that inserted in the NVO during the discharge process. This peak is gradually enhanced during discharge process. Reversibly, it is then reduced and finally returns to the initial state during the charge process. It indicates the continuous and reversible insertion/extraction of $\\mathrm{H^{+}}$ in the NVO during the charge/discharge process. \n\nIn addition to the reversible and successive insertion/extraction of $\\mathrm{H^{+}}$ , whether $Z\\mathrm{n}^{2+}$ takes part in the energy storage in $Z_{\\mathrm{{n/NVO}}}$ systems was investigated by the XPS spectra at the selected charge/discharge states (Fig. 5e and Supplementary Fig. 14). In the $\\mathtt{Z n2p}$ spectra of NVO electrodes (Fig. 5e), three pairs of $\\dot{Z}\\mathrm{n}^{2+}$ peaks located at 1023/1046, 1024/1047, and $1025/1048\\mathrm{eV}$ are assigned to the inserted $Z\\mathrm n^{2+}$ in NVO, as well as the $Z\\mathrm n^{2+}$ in $Z\\mathrm{n}$ $(\\mathrm{OH})_{2}$ and $\\mathrm{ZnSO_{4}}$ from $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}},$ respectively. It is noted that a small quantity of the inserted $Z n^{2^{*}+}$ in NVO is detected at the initial state of second cycling (state a in Fig. 5a). It reveals that some of the inserted $Z n^{2^{*}+}$ were not extracted from NVO even after full charging at first cycling, which is further confirmed by the XPS spectra at the selected charge/discharge states of first cycling (Supplementary Fig. 14). However, in the second cycling, there is a gradual increase in the intensity of peaks belonging to the inserted $Z\\mathrm{n}^{2+}$ in NVO during the discharge process (Fig. 5e). Subsequently, this peak is consecutively decreased and finally reaches the initial state during charge process. It suggests the continuous and reversible insertion/ extraction of $Z\\mathrm{n}^{2+}$ in the NVO during cycling. Furthermore, the peaks of the $Z\\mathrm{n}^{2+}$ in $Z\\mathrm{n}(\\mathrm{OH})_{2}$ and $\\mathrm{ZnSO_{4}}$ from $\\mathrm{\\bar{Z}n_{4}S O_{4}(O H)_{6}{\\cdot}4H_{2}O}$ also display a similar trend, suggesting the reversible conversion of $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}}$ during cycling. Therefore, according to above discussion, it is confirmed that H + and $Z\\mathrm{n}^{2+}$ can simultaneously insert into and extract from NVO during cycling, which is quite different from the consequent insertion/extraction mechanism of $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ into/from $\\mathrm{MnO}_{2}^{34}$ . \n\nOwing to the polarity, the insertion of $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ would result in the decrease of ${\\bf d}$ -space in NVO, as reflected by XRD patterns, where the peak at $12.2^{\\circ}$ (the (001) reflection of NVO) gradually shifts to high degree during discharge process. However, impressively, the peak at $12.2^{\\circ}$ finally recovers to the initial state during the charge process (Fig. 5b), indicating the reversible structural evolution of NVO due to the simultaneous insertion/extraction of $\\mathrm{H^{+}}$ and $Z\\mathrm n^{2+}$ . Furthermore, even after 100 cycles the NVO still remain good structural reversibility of NVO during the cycling, as suggested by their XRD patterns (Supplementary Fig. 15). In addition, to understand the repeatability of energy storage mechanism, the NVO electrode was also characterized by the ex situ XRD at the selected states of 10th charge/discharge process (Supplementary Fig. 16). They display similar XRD patterns at the selected states compared with the case of second cycle, suggesting that the mechanism that was suggested by second cycle is implemented for the following cycles. The insertion/extraction of $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ will lead to the valence change of vanadium in NVO. The $\\mathrm{~V~}2\\mathrm{p}$ peak of the XPS spectra at the selected charge/discharge states shifts to low bonding energy (low valence) during the discharge process, corresponding to the reduction of vanadium (Fig. 5f). And then it is backed to the original bonding energy gradually in the charge process since the vanadium is oxidized to initial state. In addition, it is noted that the peak shift of $\\mathrm{~V~}2\\mathrm{p}$ at the discharge process from state a to state d and charge process from state i to state n is small, indicating that $\\mathrm{H^{+}}$ and $\\breve{Z}\\mathrm{n}^{2^{\\bullet}+}$ insertion/extraction is slower at the discharge stage from $1.25{-}0.85\\mathrm{V}$ and charge stage from $1.0\\mathrm{-}1.25\\mathrm{V}$ . \n\nSince the dissolution of discharge products in electrolyte can be ignored (Supplementary Information for details) and no electrolyte or other deposits remained in the electrodes after being washed by deionized water, as suggested by above XRD and FTIR results, the quantify of the inserted $Z\\mathrm{n}^{2+}$ in NVO can be directly reflected by inductively coupled plasma atomic emission spectroscopy (ICP-AES) of the charge/discharge products on the positive electrode (Supplementary Information for details). The mole ratios of Na, Zn, and $\\mathrm{\\DeltaV}$ in the charge/discharge products are 1:3.1:3 (first discharge at $0.3\\mathrm{V},$ ) and 1:0.1:3 (first charge at $1.25\\mathrm{V},$ , respectively. According to the first discharge and charge capacities, the electron transfer numbers are 4.9 and 4.7, respectively. Therefore, the inserted $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ can be quantified via combining the ICP-AES results with the electron transfer numbers to understand the discharge and charge products. The first discharge products are $\\mathrm{H_{3.9}N a Z n_{0.5}V_{3}O_{8}.1.5H_{2}O}$ and $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}},$ and the first charge product is $\\mathrm{NaZn_{0.1}V_{3}O_{8}{\\cdot}1.5H_{2}O}$ Hence, the electrochemical reactions of the aqueous $Z_{\\mathrm{{n/NVO}}}$ batteries can be summarized as below: \n\nFirst discharge: \n\nPositive electrode: \n\n$$\n3.9\\mathrm{H}_{2}\\mathrm{O}\\leftrightarrow3.9\\mathrm{H}^{+}+3.9\\mathrm{OH}^{-}\n$$ \n\n$$\n1.95\\mathrm{Zn}^{2+}+0.65\\mathrm{ZnSO}_{4}+3.9\\mathrm{OH}^{-}+2.6\\mathrm{H}_{2}\\mathrm{O}\\leftrightarrow0.65\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}\\cdot4\\mathrm{H}_{2}\\mathrm{O}\n$$ \n\n$$\n\\begin{array}{r}{\\mathrm{NaV}_{3}\\mathrm{O}_{8}\\cdot1.5\\mathrm{H}_{2}\\mathrm{O}+3.9\\mathrm{H}^{+}+0.5\\mathrm{Zn}^{2+}+4.9\\mathrm{e}^{-}}\\\\ {\\longrightarrow\\mathrm{H}_{3.9}\\mathrm{NaZn}_{0.5}\\mathrm{V}_{3}\\mathrm{O}_{8}\\cdot1.5\\mathrm{H}_{2}\\mathrm{O}}\\end{array}\n$$ \n\nNegative electrode: \n\n$$\n2.45\\mathrm{Zn}\\leftrightarrow2.45\\mathrm{Zn}^{2+}+4.9\\mathrm{e}^{-}\n$$ \n\n# Overall: \n\n$$\n\\begin{array}{r}{\\mathrm{NaV}_{3}\\mathrm{O}_{8}\\cdot1.5\\mathrm{H}_{2}\\mathrm{O}+0.65\\mathrm{ZnSO}_{4}+6.5\\mathrm{H}_{2}\\mathrm{O}+2.45\\mathrm{Zn}\\longrightarrow}\\\\ {0.65\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{H}_{3.9}\\mathrm{NaZn}_{0.5}\\mathrm{V}_{3}\\mathrm{O}_{8}\\cdot1.5\\mathrm{H}_{2}\\mathrm{O}}\\end{array}\n$$ \n\nSubsequent cycles: Positive electrode: \n\n$$\n\\begin{array}{r}{\\mathrm{H_{3.9}N a Z n_{0.5}V_{3}O_{8}\\cdot1.5H_{2}O\\leftrightarrow N a Z n_{0.1}V_{3}O_{8}\\cdot1.5H_{2}O}}\\\\ {+3.9\\mathrm{H^{+}}+0.4\\mathrm{Zn^{2+}}+4.7\\mathrm{e^{-}}}\\end{array}\n$$ \n\n$$\n0.65\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}\\cdot4\\mathrm{H}_{2}\\mathrm{O}\\longleftrightarrow1.95\\mathrm{Zn}^{2+}+0.65\\mathrm{ZnSO}_{4}+3.9\\mathrm{OH}^{-}+2.6\\mathrm{H}_{2}\\mathrm{O}\n$$ \n\n$$\n3.9\\mathrm{H}^{+}+3.9\\mathrm{OH}^{-}\\leftrightarrow3.9\\mathrm{H}_{2}\\mathrm{O}\n$$ \n\nNegative electrode: \n\n$$\n2.35\\mathrm{Zn}^{2+}+4.7\\mathrm{e}^{-}\\leftrightarrow2.35\\mathrm{Zn}\n$$ \n\nOverall: \n\n$$\n\\begin{array}{r l}&{0.65Z\\mathrm{n}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}\\cdot4\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{H}_{3.9}\\mathrm{NaZn}_{0.5}\\mathrm{V}_{3}\\mathrm{O}_{8}\\cdot1.5\\mathrm{H}_{2}\\mathrm{O}\\leftrightarrow}\\\\ &{\\mathrm{NaZn}_{0.1}\\mathrm{V}_{3}\\mathrm{O}_{8}\\cdot1.5\\mathrm{H}_{2}\\mathrm{O}+0.65\\mathrm{ZnSO}_{4}+6.5\\mathrm{H}_{2}\\mathrm{O}+2.35\\mathrm{Zn}}\\end{array}\n$$ \n\nIn the first discharge process, the $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ simultaneously insert into NVO to form $\\mathrm{H_{3.9}N a Z n_{0.5}V_{3}O_{8}{\\cdot}1.5H_{2}O}$ , which is not a completely reversible reaction. After being charged to $1.25\\mathrm{V}$ , the $\\mathrm{H^{+}}$ and partial $Z\\mathrm{n}^{2+}$ are simultaneously extracted to obtain $\\mathrm{NaZn_{0.1}V_{3}O_{8}{\\cdot}1.5H_{2}O}$ . This procedure is reversible and the following cycles implement this mechanism. According to the overall reaction equation, the capacity contributions of $\\mathrm{\\bar{H}^{+}}$ and $Z\\mathrm{n}^{2+}$ were calculated to be $83\\%$ (about $315\\mathrm{mAh}\\mathrm{g}^{-1},$ ) and $17\\%$ (about $65\\mathrm{mAh}\\mathrm{g}^{-1}\\mathrm{\\AA}$ ), respectively. Such behavior is different from the previously reported cases, where only $Z\\mathrm{n}^{2+}$ or $\\mathrm{H^{+}}$ inserts into host materials or $\\mathrm{\\dot{H}^{+}}$ first inserts into host materials and then $Z\\mathrm{n}^{2}$ $^+$ with two steps16,24,34. As discussed above, the $\\mathrm{ZnSO_{4}}$ and $\\mathrm{H}_{2}\\mathrm{O}$ in electrolyte participate in the electrochemical reactions during cycling. When the $\\mathrm{ZnSO_{4}}$ and $\\mathrm{H}_{2}\\mathrm{O}$ are also considered, the corresponding energy density and power density of $Z_{\\mathrm{{n/NVO}}}$ batteries are about $\\mathrm{180~Wh~kg^{-1}}$ and $2160\\mathrm{W}\\mathrm{kg}^{-1}$ , respectively. \n\n![](images/0752b7048e87d25f1adbfc942b14a7c1f36449724d5ea9e2fbc3a0f2056fbe0b.jpg) \nFig. 6 Configuration and performance of flexible quasi-solid-state $Z n/N V O$ batteries. a Schematic diagram of a flexible quasi-solid-state Zn/NVO battery. b LED array containing 52 bulbs powered by two flexible quasi-solid-state $Z n/N V O$ batteries under bending state. c Cycling performance under different bending states $(0.5\\mathsf{A g}^{-1})$ of the flexible quasi-solid-state $Z n/N\\vee{\\bigcirc}$ battery. The insets show the optical images of the quasi-solid-state Zn/NVO battery at corresponding bending states \n\nFlexible quasi-solid-state ${\\bf Z}{\\bf n}/{\\bf N V}{\\bf O}$ batteries. Recent development of flexible electronic devices has raised the urgent requirements for energy storage devices with high flexibility61–65. Since the flexible energy storage devices often suffer from the possible leakage of harmful electrolytes during the bending process, aqueous ZIBs will be safer in comparison with other batteries based on organic electrolytes61,66. Compared with liquid electrolytes, quasi-solid-state electrolytes are more beneficial for preventing the leakage of electrolytes. Moreover, quasi-solid-state electrolytes exhibit high flexibility, and can simultaneously control the dissolution of active materials and the deposition of dendrites67,68. Therefore, quasi-solid-state ZIBs will be good candidates for flexible energy storage devices. Besides, the morphology of nanobelts guarantees our NVO positive electrodes to be flexible without obvious cracks even at bending state (Supplementary Fig. 17). As a proof of concept, flexible $\\mathrm{\\bar{Z}n/N V O}$ batteries were assembled by sandwiching quasi-solid-state gelation $/Z_{\\mathrm{nSO_{4}}}$ electrolyte between the NVO positive electrode and $Z\\mathrm{n}$ foil, and then sealed by Al-plastic films (Fig. 6a and Supplementary Fig. 18). Although the performance of the quasi-solid-state $Z\\mathrm{n}/$ NVO batteries cannot touch that of batteries based on aqueous $\\mathrm{ZnSO_{4}/N a_{2}S O_{4}}$ electrolyte due to the degraded ionic conductivity of quasi-solid-state electrolyte, they still display the excellent capacities of 288, 228, 160, 115, and $\\mathrm{{\\dot{8}0m A h\\mathrm{g^{-1}}}}$ at 0.1, 0.2, 0.5, 1, and $2\\mathrm{Ag^{-1}}$ , respectively based on the mass of NVO in positive electrode (Supplementary Fig. 19a), which are better than most of the reported aqueous ZIBs15,18,20–22,25–27,29,31. Furthermore, when the current density abruptly recovers from 2 to $0.1\\mathrm{Ag}^{-1}$ after 25 cycles, the capacity can recover to $270\\mathrm{mAhg^{=}}^{1}$ , indicating the excellent rate performance of our quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ batteries. In addition, the corresponding charge/discharge curves at different current densities deliver two reduction and two oxidation plateaus, respectively (Supplementary Fig. 19b), which are similar to those in aqueous $\\mathrm{ZnSO_{4}/N a_{2}S O_{4}}$ electrolyte, indicating that the quasi-solid-state electrolyte nearly has no influence on the reaction mechanism of $Z_{\\mathrm{{n/NV}\\bar{O}}}$ systems. \n\nTo further understand the energy storage mechanisms of the quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ battery, the NVO-based electrodes from quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ battery was characterized by ex situ XRD at the selected states of second charge/discharge process (Supplementary Fig. 20). The XRD patterns of the NVObased electrodes from quasi-solid-state $\\bar{Z}_{\\mathrm{n/NVO}}$ battery are similar with the case of NVO-based electrodes from liquid $Z\\mathrm{n}/$ NVO battery, indicating that quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ battery shows a similar energy storage mechanism. In addition, in the quasi-solid-state electrolyte, the content of water is about $71\\%$ , which is enough to offer water for participating in the reactions, like the case of $Z_{\\mathrm{{n/NVO}}}$ battery based on liquid electrolyte. It is noted that the intensity of peaks corresponding to $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}}$ is gradually enhanced during discharge process. Subsequently, it is reduced and finally returns to the initial state. It indicates the reversible formation/decomposition of $\\mathrm{Zn_{4}S O_{4}(O H)_{6}{*4H_{2}O}}$ on NVO during the charge/discharge process in quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ battery. It is similar to the case of $Z_{\\mathrm{{n/NVO}}}$ battery based on liquid electrolyte. \n\nIn order to demonstrate the viability of our quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ batteries as flexible energy storage devices, we tested the cycling performance of a representative battery with a length of 9 cm at different bending states. As shown in Fig. 6c, it delivers a stable capacity of $160\\mathrm{\\check{mAh}g^{-1}}$ at a current density of $0.5\\mathrm{Ag}^{-1}$ after activation in the initial 10 cycles. After 30 cycles, when the battery was bent to form a circular column with a diameter of 3 cm and even $2\\mathrm{cm}$ , it was still able to display a steady capacity of 157 and $145\\mathrm{mAhg^{-1}}$ , respectively. Moreover, after the battery recovered from bending state to flat state after 90 cycles, the capacity could be still up to $133\\mathrm{mAhg^{-1}}$ . During such a bending process, the battery is always able to charge/discharge well with only a slight capacity fading, displaying the high stability of the quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ batteries as flexible energy storage devices. To demonstrate the flexibility of the resultant quasisolid-state $Z_{\\mathrm{{n/NVO}}}$ batteries via a simple visual cue, we integrated two quasi-solid-state $Z_{\\mathrm{{n/NVO}}}$ batteries in series. They can light up fifty-two light-emitting diodes with a shape of $^{\\alpha}Z\\mathrm{I}\\mathrm{B}s^{\\mathrm{3}}$ even under bending state (Fig. 6b), illustrating the practical application potential of our flexible quasi-solid-state $\\bar{Z}_{\\mathrm{{n/NVO}}}$ batteries. \n\n# Discussion \n\nThe performance of rechargeable aqueous ZIBs inevitably depends on the host electrodes and optimal electrolytes to a large extent16,24,69. Owing to the nanobelt morphology and appropriate interlayer spacing, NVO nanobelts were used as the positive electrodes of high performance aqueous ZIBs, in which $\\mathrm{ZnSO_{4}}$ aqueous solution with $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ additive was used as electrolyte. The $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ additive not only limits the continuous dissolution of NVO via changing the dissolution equilibrium of $\\mathrm{Na^{+}}$ from NVO electrodes, but also synchronously restricts the growth of $Z\\mathrm{n}$ dendrites based on an electrostatic shield mechanism49, since Na possesses a lower reduction potential than $Z\\mathrm{n}^{2+}$ . More importantly, a simultaneous $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ insertion/extraction process is achieved in our highly reversible $Z_{\\mathrm{{n/NVO}}}$ system, which is different from conventional ZIBs with only $Z\\mathrm{n}^{2+}$ insertion/extraction and some $\\mathrm{Zn/MnO}_{2}$ systems with $\\mathrm{H^{+}}$ or two-step $\\mathrm{H}^{+}/\\mathrm{Zn}^{2+}$ insertion/extraction process24,33,34. Such novel energy release/storage mechanism remarkably enhances the performance of $Z_{\\mathrm{{n/NV\\bar{O}}}}$ batteries, which deliver a superior reversible capacity of $380\\mathrm{mAhg^{-1}}$ (corresponding energy density: $300\\mathrm{{Wh}\\dot{k g}^{-1},}$ ), a high capacity retention of $82\\%$ after 1000 cycles at $4\\mathrm{A}\\bar{\\mathrm{g}}^{-1}$ . The simultaneous $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ insertion/ extraction mechanism will guide further developing new appropriate host materials for aqueous metal-ion batteries with high performance. Moreover, the nanobelt morphology of NVO makes the corresponding positive electrodes possess the capacity of enduring the high strain without obvious cracks at bending state, guaranteeing that the NVO nanobelts can act as the positive electrodes of flexile ZIBs. As a proof of concept, flexible softpackaged $Z_{\\mathrm{{n/NVO}}}$ batteries were assembled using quasi-solidstate gelation $/Z_{\\mathrm{nSO_{4}}}$ as electrolyte. Flexible $Z_{\\mathrm{{n/NVO}}}$ batteries still show a high capacity of $\\mathrm{\\dot{2}88\\ m A h\\ g^{-1}}$ and superior rate capability even quasi-solid-state electrolyte is used. Impressively, they are able to remain stable electrochemical properties under different bending states. Their high flexibility and excellent electrochemical performance of flexible quasi-solid-state $Z\\mathrm{n}/$ NVO batteries will pave the way for the potential application of ZIBs as portable, flexible, and wearable energy storage devices. \n\n# Methods \n\nMaterials. Super P, polyvinylidene fluoride (PVDF) and filter papers were purchased from Sinopharm Chemical Reagent Co., Ltd. Vanadium pentoxide, sodium chloride, sodium sulfate, zinc sulfate, and 1-methyl-2-pyrrolidone (NMP) were purchased from Alfa Aesar. Zn foils and gelatin were from Sigma-Aldrich and Beijing Solarbio Science & Technology Co., Ltd., respectively. Al-plastic films were from Aladdin. \n\nPreparation of NVO nanobelts. One gram of commercial $\\mathrm{V}_{2}\\mathrm{O}_{5}$ powder was added into $15\\mathrm{mL}$ of $\\mathrm{\\DeltaNaCl}$ aqueous solution (2 M). After stirring for $96\\mathrm{h}$ at $30{}^{\\circ}\\mathrm{C},$ . the suspension was washed with deionized water for several times. Finally, the black red product was obtained by freeze-drying. \n\nFabrication of quasi-solid-state electrolyte. A measure of 1.5 grams of gelatin was added into $6\\mathrm{mL}$ of $\\mathrm{ZnSO_{4}}$ aqueous solution (1 M) under magnetic stirring at $60^{\\circ}\\mathrm{C}$ . After $0.5\\mathrm{h}$ the solution became transparent and was then poured into a watch glass with a diameter of $9.5\\mathrm{cm}$ to gel at room temperature. After that, the gel electrolyte film was peeled from the watch glass and cut into desired size. \n\nAssembly of Zn/NVO batteries. The positive electrode was prepared by mixing NVO nanobelts, super $\\mathrm{\\bfP}$ and PVDF in a weight ratio of 7:2:1 by NMP, then casting the slurry on steel meshes. After drying at $80^{\\circ}\\mathrm{C}$ , the positive electrode with $2\\mathrm{mg}$ $\\mathrm{cm}^{-2}$ NVO nanobelts was achieved. CR2032 coin cells were assembled by a traditional method using filter papers and $Z\\mathrm{n}$ foils as separators and negative electrodes, respectively. The aqueous electrolyte for coin cells was 1 M $\\mathrm{ZnSO_{4}}$ or $1\\mathrm{M}$ $Z_{\\mathrm{{nSO}_{4}/1}}$ M $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ . The aqueous electrolyte for liquid soft-packaged batteries was $\\mathrm{~l~M~ZnSO_{4}/1}$ M $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ . Liquid soft-packaged batteries were assembled by sandwiching separator and electrolyte between the NVO positive electrode and $Z\\mathrm{n}$ foil, and then sealed by Al-plastic films. Quasi-solid-state batteries were fabricated by sandwiching gelatin $/Z\\mathrm{nSO_{4}}$ gel electrolyte between NVO positive electrode and $Z\\mathrm{n}$ foil without additional separators, and then packaged by Al-plastic films. \n\nCharacterization. The morphology of NVO was characterized by SEM (JEOL JSM-7500F) and TEM (JEOL-2100 F, $200\\mathrm{kV}$ ) with energy dispersive spectroscopy (EDS) for elemental analysis. XRD tests were performed on Rigaku Ultima IV with Cu Kα radiation. FTIR and XPS spectra were collected through Bruker Tensor II and PerkinElmer PHI 1600 ESCA, respectively. The solid state $^1\\mathrm{H}$ NMR spectra were taken from a $300\\mathrm{MHz}$ superconducting NMR spectrometer (Varian Infinitplus-300). ICP-AES results were obtained from PerkinElmer Optima 8300. CV curves were measured by an electrochemical workstation (CHI 660E) with a voltage window of $0.3\\mathrm{-}1.25\\mathrm{V}$ at different scan rates from 0.1 to $0.5\\mathrm{mVs^{-1}}$ . Galvanostatic charge/discharge tests were performed on a battery test system (LAND CT2001A) with a voltage range from 0.3 to $1.25\\mathrm{V}$ . \n\nData availability. The authors declare that all the relevant data are available within the paper and its Supplementary Information file or from the corresponding author upon reasonable request. \n\nReceived: 31 October 2017 Accepted: 30 March 2018 \nPublished online: 25 April 2018 \n\n# References \n\n1. Armand, M. & Tarascon, J. M. Building better batteries. Nature 451, 652–657 (2008). \n2. Dunn, B., Kamath, H. & Tarascon, J. M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n3. Yabuuchi, N., Kubota, K., Dahbi, M. & Komaba, S. Research development on sodium-ion batteries. Chem. Rev. 114, 11636–11682 (2014). \n4. Hu, X. et al. Rechargeable room-temperature $_\\mathrm{Na-CO}_{2}$ batteries. Angew. Chem. Int. Ed. 55, 6482–6486 (2016). \n5. Zhao, Q., Yan, Z., Chen, C. & Chen, J. Spinels: controlled preparation, oxygen reduction/evolution reaction application, and beyond. Chem. Rev. 117, 10121–10211 (2017). \n6. Yamada, Y. et al. Hydrate-melt electrolytes for high-energy-density aqueous batteries. Nat. Energy 1, 16129 (2016). \n7. Zhang, N. et al. Cation-deficient spinel $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ cathode in $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte for rechargeable aqueous Zn-ion battery. J. Am. Chem. Soc. 138, 12894–12901 (2016). \n8. Kim, H. et al. Aqueous rechargeable Li and Na ion batteries. Chem. Rev. 114, 11788–11827 (2014). \n9. Lee, J., Ju, J. B., Cho, W. I., Cho, B. W. & Oh, S. H. Todorokite-type $\\mathrm{MnO}_{2}$ as a zinc-ion intercalating material. Electrochim. Acta 112, 138–143 (2013). \n10. Lee, B. et al. Elucidating the intercalation mechanism of zinc ions into α- $\\mathrm{MnO}_{2}$ for rechargeable zinc batteries. Chem. Commun. 51, 9265–9268 (2015). \n11. Haupler, B. et al. Aqueous zinc-organic polymer battery with a high rate performance and long lifetime. NPG Asia Mater. 8, e283 (2016). \n12. Xu, D. et al. Preparation and characterization of $\\mathrm{MnO}_{2}/$ acid-treated CNT nanocomposites for energy storage with zinc ions. Electrochim. Acta 133, 254–261 (2014). \n13. Li, H. et al. Enhancement on cycle performance of $Z\\mathrm{n}$ anodes by activated carbon modification for neutral rechargeable zinc ion batteries. J. Electrochem. Soc. 162, A1439–A1444 (2015). \n14. Lee, B. et al. Critical role of $\\mathrm{\\tt{pH}}$ evolution of electrolyte in the reaction mechanism for rechargeable zinc batteries. ChemSusChem 9, 2948–2956 (2016). \n15. Kaveevivitchai, W. & Manthiram, A. High-capacity zinc-ion storage in an open-tunnel oxide for aqueous and nonaqueous $Z\\mathrm{n}$ -ion batteries. J. Mater. Chem. A 4, 18737–18741 (2016). capacity and long-life aqueous rechargeable zinc battery using a metal oxide intercalation cathode. Nat. Energy 1, 16119 (2016). \n17. Alfaruqi, M. H. et al. Electrochemical zinc intercalation in lithium vanadium oxide: a high-capacity zinc-ion battery cathode. Chem. Mater. 29, 1684–1694 (2017). \n18. He, P. et al. Layered $\\mathrm{VS}_{2}$ nanosheet-based aqueous $Z\\mathrm{n}$ ion battery cathode. Adv. Energy Mater. 7, 1601920 (2017). \n19. Jiang, B. et al. Manganese sesquioxide as cathode material for multivalent zinc ion battery with high capacity and long cycle Life. Electrochim. Acta 229, 422–428 (2017). \n20. Alfaruqi, M. H. et al. Enhanced reversible divalent zinc storage in a structurally stable $\\mathsf{a}{\\mathrm{-}}\\mathsf{M}\\mathsf{n}\\mathsf{O}_{2}$ nanorod electrode. J. Power Sources 288, 320–327 (2015). \n21. Alfaruqi, M. H. et al. A layered $\\delta\\mathrm{-}\\mathrm{MnO}_{2}$ nanoflake cathode with high zincstorage capacities for eco-friendly battery applications. Electrochem. Commun. 60, 121–125 (2015). \n22. Alfaruqi, M. H. et al. Electrochemically induced structural transformation in a $\\gamma{\\mathrm{-}}\\ensuremath{\\mathrm{MnO}_{2}}$ cathode of a high capacity zinc-ion battery system. Chem. Mater. 27, 3609–3620 (2015). \n23. Zhang, N. et al. Rechargeable aqueous zinc-manganese dioxide batteries with high energy and power densities. Nat. Commun. 8, 405 (2017). \n24. Pan, H. et al. Reversible aqueous zinc/manganese oxide energy storage from conversion reactions. Nat. Energy 1, 16039 (2016). \n25. Trócoli, R. & La Mantia, F. An aqueous zinc-ion battery based on copper hexacyanoferrate. ChemSusChem 8, 481–485 (2015). \n26. Zhang, L., Chen, L., Zhou, X. & Liu, Z. Morphology-dependent electrochemical performance of zinc hexacyanoferrate cathode for zinc-ion battery. Sci. Rep. 5, 18263 (2015). \n27. Zhang, L., Chen, L., Zhou, X. & Liu, Z. Towards high-voltage aqueous metalion batteries beyond 1.5 V: The zinc/zinc hexacyanoferrate system. Adv. Energy Mater. 5, 1400930 (2015). \n28. Liu, Z., Pulletikurthi, G. & Endres, F. A prussian blue/zinc secondary battery with a bio-ionic liquid-water mixture as electrolyte. ACS Appl. Mater. Interfaces 8, 12158–12164 (2016). \n29. Chae, M. S., Heo, J. W., Lim, S. C. & Hong, S. T. Electrochemical zinc-ion intercalation properties and crystal structures of $\\mathrm{ZnMo}_{6}\\mathrm{S}_{8}$ and $\\mathrm{Zn_{2}M o_{6}S_{8}}$ chevrel phases in aqueous electrolytes. Inorg. Chem. 55, 3294–3301 (2016). \n30. Cheng, Y. et al. Highly reversible zinc-ion intercalation into chevrel phase $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ nanocubes and applications for advanced zinc-ion batteries. ACS Appl. Mater. Interfaces 8, 13673–13677 (2016). \n31. Li, G. et al. Towards polyvalent ion batteries: a zinc-ion battery based on NASICON structured $\\mathrm{Na}_{3}\\mathrm{V}_{2}(\\mathrm{PO}_{4})_{3}$ . Nano Energy 25, 211–217 (2016). \n32. Liu, W. et al. Investigation of zinc ion storage of transition metal oxides, sulfides, and borides in zinc ion batteries system. Chem. Commun. 53, 6872–6874 (2017). \n33. Xu, C., Li, B., Du, H. & Kang, F. Energetic zinc ion chemistry: the rechargeable zinc ion battery. Angew. Chem. Int. Ed. 51, 933–935 (2012). \n34. Sun, W. et al. $\\mathrm{Zn/MnO}_{2}$ battery chemistry with $\\mathrm{H^{+}}$ and $\\mathrm{Zn}^{2+}$ coinsertion. J. Am. Chem. Soc. 139, 9775–9778 (2017). \n35. Cheng, Y. et al. Rechargeable Mg-Li hybrid batteries: status and challenges. $J.$ Mater. Res. 31, 3125–3141 (2016). \n36. Gao, T. et al. Enhancing the reversibility of $\\mathrm{Mg/S}$ battery chemistry through Li + mediation. J. Am. Chem. Soc. 137, 12388–12393 (2015). \n37. Wang, H., Wang, W., Ren, Y., Huang, K. & Liu, S. A new cathode material $\\mathrm{Na}_{2}\\mathrm{V}_{6}\\mathrm{O}_{16}{\\cdot}\\mathrm{xH}_{2}\\mathrm{O}$ nanowire for lithium ion battery. J. Power Sources 199, 263–269 (2012). \n38. Nguyen, D. et al. Plate-type $\\mathrm{NaV}_{3}\\mathrm{O}_{8}$ cathode by solid state reaction for sodium-ion batteries. ECS Electrochem. Lett. 3, A69–A71 (2014). \n39. Dong, Y. et al. Hierarchical zigzag $\\mathrm{Na}_{1.25}\\mathrm{V}_{3}\\mathrm{O}_{8}$ nanowires with topotactically encoded superior performance for sodium-ion battery cathodes. Energy Environ. Sci. 8, 1267–1275 (2015). \n40. Wang, H., Liu, S., Ren, Y., Wang, W. & Tang, A. Ultrathin $\\mathrm{Na}_{1.08}\\mathrm{V}_{3}\\mathrm{O}_{8}$ nanosheets—a novel cathode material with superior rate capability and cycling stability for Li-ion batteries. Energy Environ. Sci. 5, 6173–6179 (2012). \n41. Ko, Y. W. et al. Electrospun single-phase $\\mathrm{Na}_{1.2}\\mathrm{V}_{3}\\mathrm{O}_{8}$ materials with tunable mrphologies as cathodes for rechargeable lithium-ion batteries. ChemElectroChem 2, 837–846 (2015). \n42. Reddy Channu, V. S., Holze, R., Yeo, I. H., Mho, Si & Kalluru, R. R. Electrochemical properties of polyaniline-modified sodium vanadate nanomaterials. Appl. Phys. A 104, 707–711 (2011). \n43. Ye, P., Wang, X., Wang, M., Fan, Y. & Xiang, X. Recovery of vanadium from stone coal acid leaching solution by coprecipitation, alkaline roasting and water leaching. Hydrometallurgy 117, 108–115 (2012). \n44. Durupthy, O. et al. Influence of $\\mathrm{\\pH}$ and ionic strength on vanadium(V) oxides formation. From $\\mathrm{V}_{2}\\mathrm{O}_{5}{\\cdot}\\mathrm{nH}_{2}\\mathrm{O}$ gels to crystalline $\\mathrm{NaV}_{3}\\mathrm{O}_{8}{\\cdot}1.5\\mathrm{H}_{2}\\mathrm{O}.$ J. Mater. Chem. 15, 1090–1098 (2005). \n45. Rui, X. et al. Ambient dissolution-recrystallization towards large-scale preparation of $\\mathrm{V}_{2}\\mathrm{O}_{5}$ nanobelts for high-energy battery applications. Nano Energy 22, 583–593 (2016). \n46. Chithaiah, P., Chandrappa, G. T. & Livage, J. Formation of crystalline $\\mathrm{Na}_{2}\\mathrm{V}_{6}\\mathrm{O}_{16}.3\\mathrm{H}_{2}\\mathrm{O}$ ribbons into belts and rings. Inorg. Chem. 51, 2241–2246 (2012). \n47. Shirpour, M., Cabana, J. & Doeff, M. New materials based on a layered sodium titanate for dual electrochemical Na and Li intercalation systems. Energy Environ. Sci. 6, 2538–2547 (2013). \n48. Kang, H. et al. $\\mathrm{NaV}_{3}\\mathrm{O}_{8}$ nanosheet@polypyrrole core-shell composites with good electrochemical performance as cathodes for Na-ion batteries. Nanoscale 7, 9261–9267 (2015). \n49. Ding, F. et al. Dendrite-free lithium deposition via self-healing electrostatic shield mechanism. J. Am. Chem. Soc. 135, 4450–4456 (2013). \n50. Zhang, X. H. et al. $\\mathrm{P2-Na_{2/3}N i_{1/3}M n_{5/9}A l_{1/9}O_{2}}$ microparticles as superior cathode material for sodium-ion batteries: enhanced properties and mechanisam via graphene connection. ACS Appl. Mater. Interfaces 8, 20650–20659 (2016). \n51. He, G., Bridges, C. A. & Manthiram, A. Crystal chemistry of electrochemically and chemically lithiated layered $\\mathsf{a}_{\\mathrm{I}^{-}}\\mathrm{LiVOPO}_{4}$ . Chem. Mater. 27, 6699–6707 (2015). \n52. Kim, J.-H. et al. Integrated nano-domains of disordered and ordered spinel phases in $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ for Li-Ion batteries. Chem. Mater. 26, 4377–4386 (2014). \n53. Zhang, K. et al. Urchin-like $\\mathrm{CoSe}_{2}$ as a high-performance anode material for sodium-ion batteries. Adv. Funct. Mater. 26, 6728–6735 (2016). \n54. Chao, D. et al. Array of nanosheets render ultrafast and high-capacity Na-ion storage by tunable pseudocapacitance. Nat. Commun. 7, 12122 (2016). \n55. Chao, D. et al. Pseudocapacitive $\\mathrm{\\DeltaNa}$ -ion storage boosts high rate and areal capacity of self-branched 2D layered metal chalcogenide nanoarrays. ACS Nano 10, 10211–10219 (2016). \n56. Xia, X. et al. Generic synthesis of carbon nanotube branches on metal oxide arrays exhibiting stable high-rate and long-cycle sodium-ion storage. Small 12, 3048–3058 (2016). \n57. Luo, J.-Y., Cui, W.-J., He, P. & Xia, Y.-Y. Raising the cycling stability of aqueous lithium-ion batteries by eliminating oxygen in the electrolyte. Nat. Chem. 2, 760–765 (2010). \n58. Shan, X. et al. Bivalence $\\mathrm{Mn}_{5}\\mathrm{O}_{8}$ with hydroxylated interphase for high-voltage aqueous sodium-ion storage. Nat. Commun. 7, 13370 (2016). \n59. Suo, L. et al. “Water-in-salt” electrolyte enables high-voltage aqueous lithiumion chemistries. Science 350, 938–943 (2015). \n60. Qu, Q., Li, L., Bai, W. & Yan, Cw Initial atmospheric corrosion of zinc in presence of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ and $\\mathrm{(NH_{4})_{2}S O_{4}}$ . Trans. Nonferrous Metals Soc. China 16, 887–891 (2006). \n61. Hiralal, P. et al. Nanomaterial-enhanced all-solid flexible zinc-carbon batteries. ACS Nano 4, 2730–2734 (2010). \n62. Niu, Z. et al. All-solid-state flexible ultrathin micro-supercapacitors based on graphene. Adv. Mater. 25, 4035–4042 (2013). \n63. Cao, J. et al. A flexible nanostructured paper of a reduced graphene oxidesulfur composite for high-performance lithium-sulfur batteries with unconventional configurations. Adv. Mater. 28, 9629–9636 (2016). \n64. Chen, C. et al. Foldable all-solid-state supercapacitors integrated with photodetectors. Adv. Funct. Mater. 27, 1604639 (2016). \n65. Zhao, J. et al. A smart flexible zinc battery with cooling recovery ability. Angew. Chem. Int. Ed. 129, 7979–7983 (2017). \n66. Zeng, Y. et al. Achieving ultrahigh energy density and long durability in a flexible rechargeable quasi-solid-state $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ battery. Adv. Mater. 29, 1700274 (2017). \n67. Huang, W. et al. Quasi-solid-state rechargeable lithium-ion batteries with a Calix[4]quinone cathode and gel polymer electrolyte. Angew. Chem. Int. Ed. 52, 9162–9166 (2013). \n68. Hu, X. et al. Quasi-solid state rechargeable $\\mathrm{Na}{\\mathrm{-}}\\mathrm{CO}_{2}$ batteries with reduced graphene oxide Na anodes. Sci. Adv. 3, e1602396 (2017). \n69. Liu, Z. et al. Dendrite-free nanocrystalline zinc electrodeposition from an ionic liquid containing nickel triflate for rechargeable $Z\\mathrm{n}$ -based batteries. Angew. Chem. Int. Ed. 55, 2889–2893 (2016). \n\n# Acknowledgements \n\nThis work was supported by MOST (2017YFA0206701), National Natural Science Foundation of China (21573116 and 51602218), Ministry of Education of China (B12015), and Tianjin Basic and High-Tech Development (15JCYBJC17300). Z.N. thanks the Young Thousand Talents Program. \n\n# Author contributions \n\nJ.C., Z.N., and F.W. conceived the idea. F.W. performed the experiments. L.Z. and X.D. contributed to electrochemical measurement. X.W. assisted in packaging the flexible \n\nquasi-solid-state batteries. J.C., Z.N., and F.W. wrote the paper. All authors took part in the result discussion and data analysis. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-04060-8. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1038_s41929-018-0164-8", + "DOI": "10.1038/s41929-018-0164-8", + "DOI Link": "http://dx.doi.org/10.1038/s41929-018-0164-8", + "Relative Dir Path": "mds/10.1038_s41929-018-0164-8", + "Article Title": "Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells", + "Authors": "Li, JZ; Chen, MJ; Cullen, DA; Hwang, S; Wang, MY; Li, BY; Liu, KX; Karakalos, S; Lucero, M; Zhang, HG; Lei, C; Xu, H; Sterbinsky, GE; Feng, ZX; Su, D; More, KL; Wang, GF; Wang, ZB; Wu, G", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Platinum group metal (PGM)-free catalysts that are also iron free are highly desirable for the oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells, as they avoid possible Fenton reactions. Here we report an efficient ORR catalyst that consists of atomically dispersed nitrogen-coordinated single Mn sites on partially graphitic carbon (Mn-N-C). Evidence for the embedding of the atomically dispersed MnN4 moieties within the carbon surface-exposed basal planes was established by X-ray absorption spectroscopy and their dispersion was confirmed by aberration-corrected electron microscopy with atomic resolution. The Mn-N-C catalyst exhibited a half-wave potential of 0.80 V versus the reversible hydrogen electrode, approaching that of Fe-N-C catalysts, along with significantly enhanced stability in acidic media. The encouraging performance of the Mn-N-C catalyst as a PGM-free cathode was demonstrated in fuel cell tests. First-principles calculations further support the MnN4 sites as the origin of the ORR activity via a 4e(-) pathway in acidic media.", + "Times Cited, WoS Core": 1208, + "Times Cited, All Databases": 1262, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000452918800010", + "Markdown": "# Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells \n\nJiazhan Li1,2,11, Mengjie Chen2,11, David A. Cullen3, Sooyeon Hwang4, Maoyu Wang5, Boyang Li6, Kexi Liu6, Stavros Karakalos $\\textcircled{1}$ 7, Marcos Lucero5, Hanguang Zhang2, Chao Lei8, Hui $\\mathsf{X}\\mathsf{\\mathbf{u}}^{\\mathsf{8}}$ , George E. Sterbinsky9, Zhenxing Feng $\\textcircled{10}5$ , Dong Su $\\oplus4$ , Karren L. More10, Guofeng Wang6, Zhenbo Wang $\\textcircled{10}1\\star$ and Gang Wu   2\\* \n\nPlatinum group metal (PGM)-free catalysts that are also iron free are highly desirable for the oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells, as they avoid possible Fenton reactions. Here we report an efficient ORR catalyst that consists of atomically dispersed nitrogen-coordinated single Mn sites on partially graphitic carbon (Mn-N-C). Evidence for the embedding of the atomically dispersed $\\pmb{M_{\\Pi}}\\mathbf{N_{4}}$ moieties within the carbon surface-exposed basal planes was established by X-ray absorption spectroscopy and their dispersion was confirmed by aberration-corrected electron microscopy with atomic resolution. The Mn-N-C catalyst exhibited a half-wave potential of 0.80 V versus the reversible hydrogen electrode, approaching that of Fe-N-C catalysts, along with significantly enhanced stability in acidic media. The encouraging performance of the Mn-N-C catalyst as a PGM-free cathode was demonstrated in fuel cell tests. First-principles calculations further support the $\\pmb{M_{\\Pi}}\\mathbf{M_{4}}$ sites as the origin of the ORR activity via a $46^{-}$ pathway in acidic media. \n\nevelopment of cost-effective and high-performance platinum group metal (PGM)-free catalysts for the sluggish oxygen reduction reaction (ORR) is key to realizing the large-scale application of proton-exchange membrane fuel cells (PEMFCs)1–6. A wide variety of carbon defects, including nitrogen doping and surface-exposed carbon basal plane edges and steps, are believed to act as preferred catalytic sites, thus facilitating the ORR by directly providing adsorption sites and/or by modifying the electronic properties of carbon7,8. However, the activity of such metal-free active sites in acidic media is not sufficient because they suffer from large overpotential, mostly catalysing the ORR via a two-electron pathway9. In contrast, the co-doped metal and nitrogen in the form of ${\\mathrm{MN}}_{x}{\\mathrm{C}}_{y}$ can tune the electronic and geometric properties of carbon matrix more significantly. The ${\\mathrm{MN}}_{x}{\\mathrm{C}}_{y}$ moieties themselves are also believed to be acting as the active sites to directly adsorb $\\mathrm{~O}_{2}$ and catalyse the subsequent $_{\\mathrm{O-O}}$ bond breaking in acidic media, therefore significantly improving the ORR catalytic activity6,10,11. The bonding energies of ${\\mathrm{MN}}_{x}{\\mathrm{C}}_{y}$ sites with $\\mathrm{O}_{2}$ and other ORR intermediates are dependent on the nature of the transition metal, which leads to significantly different activities and stabilities. Among the studied transition metals, Fe or Co with N-doped carbon form the M-N-C catalysts, which are recognized to be the most promising PGM-free catalysts12. They exhibit encouraging ORR activities and stabilities even in harsh acidic media13. Despite tremendous efforts to develop Fe-N-C and Co-N-C catalysts, they still suffer from insufficient durability, especially at the desirable high voltages $(>0.6\\mathrm{V})$ , which limits their practical applications in $\\mathrm{PEMFCs^{14-17}}$ . \n\nKinetic losses primarily result from the dissolution of active metal sites15,16. These problems may be caused by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ oxidative attack or by protonation of the doped N neighbouring the active metal sites followed by anion adsorption14. Carbon corrosion of catalysts also promotes dissolution of the metal sites18,19 and induces significant charge- and mass-transport resistances due to the changes in the carbon lattice structures and morphologies20. Thus, a relatively high degree of graphitization is vital for PGM-free catalyst stability to enhance the corrosion resistance of the carbon. The Fe-N-C catalysts are also criticized for their participation in and/or promotion of the Fenton reactions $\\mathrm{(Fe^{2+}+H_{2}O_{2})}$ , where dissolved Fe ions combine with $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , a byproduct of the two-electron ORR21. As a result, a significant amount of active oxygen-containing hydroxyl and hydroperoxyl radicals are generated that can degrade the ionomer within the electrode and the polymer membrane in PEMFCs (Supplementary Note 1). Therefore, high-performance PGM- and Fe-free catalysts are highly desirable for PEMFC technologies. In principle, the Co-N-C catalyst is a logical alternative22, but it suffers from substantial generation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ during the ORR in acidic media, and is thus likely to participate in Fenton reactions23. The $\\mathrm{Co-N}$ coordinated structures are even less stable in acids than Fe-N-C catalysts24. Unlike Fe and $\\scriptstyle\\mathbf{Co},$ Fenton reactions involving Mn ions are insignificant because of weak reactivity between Mn and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (ref. 23). We discovered that Mn doping promotes the stability of nanocarbon (NC) catalysts and catalyses graphitic structures in catalysts25,26. Preliminary density functional theory (DFT) calculations predicted that $\\mathrm{MnN}_{4}$ moieties embedded in carbon have comparable activity and enhanced stability relative to $\\mathrm{FeN_{4}}$ sites. Inspired by this theoretical prediction, we hypothesized that Mn-N-C catalysts are probably more stable than Fe-N-C in harsh acidic media. However, a grand challenge is to increase the density of $\\mathrm{MnN}_{4}$ active sites in catalysts because Mn atoms tend to form unstable and inactive metallic compounds, oxides and carbides during the heat treatment when simply increasing the amount of Mn precursors13,27. \n\nKnowledge gained through our previous studies on Fe and Co catalysts22,27–31 provides guidelines for the synthesis of Mn-N-C catalysts with atomic dispersion of $\\mathrm{MnN}_{4}$ active sites within a porous three-dimensional (3D) carbon framework. A zinc-containing zeolitic imidazolate frameworks (ZIF-8), a type of metal–organic framework with flexible control of the structure and chemistry, enables the formation of atomically dispersed $\\mathrm{MN_{4}}$ active sites for Fe- or Co-N-C catalysts22,32–34. The unique hydrocarbon networks in ZIF precursors can be directly converted into $\\mathrm{N}.$ and M-doped highly disordered carbon, while maintaining their original polyhedral particle shape and porous structure during thermal activation35. Recently, synthesis based on ZIF-8 precursors with chemical doping or ion confinement has resulted in atomically dispersed Fe or Co sites with increased density2,22,27,36. Motivated by these successes, we explore the ZIF approach to prepare atomically dispersed Mn-N-C catalysts. However, unlike Fe and Co ions, Mn ions cannot easily exchange the original $Z\\mathrm{n}$ and form complexes with N in the ZIF-8 precursor. Only a low density of atomic Mn sites are introduced using a conventional one-step chemical doping. Due to a wide variety of Mn valences from 0 to $+7$ , Mn aggregates easily form during the high-temperature carbonization even at a low content. Thus, realizing atomically dispersed $\\mathrm{MnN_{4}}$ sites with increased density is very challenging. \n\nHere, we report a catalyst with atomically dispersed $\\mathrm{MnN}_{4}$ sites obtained through a two-step synthesis strategy involving doping and adsorption processes by leveraging the unique properties of ZIF-8 precursors, which has been shown to effectively increase the active-site density. In the first step of synthesis, Mn ions are combined with $Z\\mathrm{n}$ ions to prepare Mn-doped ZIF-8 precursors. After carbonization and acid leaching, the derived porous carbon is used as a host to adsorb additional Mn and N sources followed by a subsequent thermal activation. This atomically dispersed Mn-N-C catalyst achieves promising activity and excellent stability for the ORR in aqueous acids. \n\n# Results \n\nAtomically dispersed and N-coordinated Mn sites. A continuous two-step doping and adsorption approach as shown in Fig. 1 has proved effective for gradually introducing more $\\mathrm{MnN_{4}}$ active sites in Mn-N-C catalysts. Supplementary Fig. 1 presents the overall morphology of the best-performing 20Mn-NC-second catalyst (where 20 is molar percentage of Mn against the total metals in solutions durng the synthesis of Mn-doped ZIF-8 precursors; second refers to the sample obtained after the second adsorption step) and shows a homogeneous distribution of polyhedral carbon particles with a size of about $50\\mathrm{nm}$ , which directly transforms from the 20Mn-ZIF-8 nanocrystal precursors with slight size reduction. The dominant diffraction peaks corresponding to carbon in the X-ray diffraction (XRD) spectra together with the broad D and G bonds in the Raman spectra (Supplementary Fig. 2) are consistent with a partially graphitized carbon structures (meso-graphitic), which is confirmed by high-resolution scanning transmission electron microscopy (HR-STEM) images (Supplementary Fig. 1h). Both XRD patterns and STEM images verified the absence of any crystalline Mn-containing phases or clusters in the catalyst. The carbon particles exhibit a high degree of microporosity, an essential characteristic for increasing surface areas available for hosting active sites. The morphology (shape and size) and structure (extent of graphitization) of carbon particles can be tuned by varying the Mn content in the first step. As shown in Supplementary Fig. 3, the carbon particle size is slightly increased by adding more Mn content. Large particles with an irregular shape appeared when the Mn content reached $30\\mathrm{at\\%}$ , indicating that excess Mn ions in the solution disturb the controlled growth of the ZIF nanocrystals. Raman results further indicated that the Mn content in the first step can significantly increase the extent of graphitization in the resulting carbon structures (Supplementary Fig. 4 and Supplementary Table 1). All three of the nMn-NC-first ( ${\\mathrm{\\Delta}n=10}$ , 20 and $30\\mathrm{at\\%}$ ) samples exhibited much smaller ratios of D and G peak areas $(\\mathrm{Area_{\\mathrm{D}}/A r e a_{\\mathrm{G}}})$ relative to the Mn-free 0Mn-NC sample. The carbon structures remain nearly the same after the second adsorption step of synthesis. \n\nAccording to inductively coupled plasma-mass spectrometry (ICP-MS), the Mn content in the 20Mn-NC-second catalyst, which exhibited the highest catalyst activity, can be up to $3.03\\mathrm{wt\\%}$ (Supplementary Table 2), which is comparable to other atomically dispersed Fe and Co catalysts (Supplementary Table 3). As no significant Mn clustering was observed by HR-STEM and XRD analyses, homogeneous dispersion of atomic Mn species is likely, which was further examined by X-ray absorption spectroscopy (XAS) measurements. X-ray absorption near edge structure (XANES) spectroscopy and extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) spectroscopy analyses are based on our established experimental and theoretical modelling methods22,27,28,37,38. Several standard Mn compounds (for example, MnO, $\\mathrm{MnO}_{2}$ and Mn phthalocyanine $(\\mathrm{Pc})$ ) were included in the XANES/EXAFS studies to compare with the 20Mn-NC-second catalyst. MnPc has a well-defined $\\mathrm{MnN_{4}}$ chemical structure (Supplementary Fig. 5), which provides a baseline for the bulk catalyst measurements and can be used to identify the possible active sites in the 20Mn-NC-second catalyst. As shown in Fig. 2a, the XANFS edge profile of the 20Mn-NC-second catalyst is close to that of $\\mathrm{{Mn}(\\pi)}$ in MnO but is far from that of ${\\mathrm{Mn}}({\\mathrm{IV}})$ in $\\mathrm{MnO}_{2},$ suggesting that the oxidation state of Mn in the 20Mn-NC-second catalyst is close to $^{2+}$ ​. Figure 2b shows the EXAFS spectrum of the MnPc, which is well fitted with $\\mathrm{MnN}_{4}$ coordination $(\\mathrm{CN}_{\\mathrm{Mn-N}}{=}4\\pm0.4,$ where CN refers to coordination number and $\\mathrm{{Mn-N}}$ is the scattering path). The fit is also plotted in $k$ -space in Supplementary Fig. 5. As shown in Fig. 2c, the EXAFS of the 20Mn-NC-second catalyst is well represented by a combination of the $\\mathrm{{Mn-N}}$ and $\\scriptstyle{\\mathrm{Mn-C}}$ scattering paths (Supplementary Table 4). The first shell coordination number of $\\mathrm{{Mn-N}}$ is given by $\\mathrm{CN}_{\\mathrm{Mn-N}}{=}3.2{\\pm}1.0$ , suggesting the dominant $\\scriptstyle\\mathrm{Mn-N}$ structure in the 20Mn-NC-second catalyst is likely to be $\\mathrm{MnN_{4}}$ . We also compared the Mn K-edge EXAFS spectra of 20Mn-NC-second to manganese nitride $\\mathrm{{(Mn_{4}N)}}$ and metallic manganese (Mn foil) to exclude the formation of nitrides and metallic Mn (Supplementary Fig. 6). Both $\\mathrm{{Mn}_{4}N}$ and Mn foil exhibit peaks at ${\\sim}2.3\\mathring\\mathrm{A}$ assigned to Mn–Mn distance, corresponding to the metallic structure. The absence of a Mn–Mn peak in the 20Mn-NC-second spectra further verifies there is no such Mn clusters in the catalyst. We note that the peak at around $1.9\\mathring\\mathrm{A}$ deviates from the fitted curve for 20Mn-NC-second catalyst, which may be due to a weak Mn–O scattering path caused by a very small amounts of O, since MnPc does not have a $_\\mathrm{Mn-O}$ scattering path. We have attempted to add a $_\\mathrm{Mn-O}$ scattering path directly from the MnO structure, but this did not provide us with representative structure information. Compared with standard MnPc that has a well-defined and uniform $\\mathrm{MnN_{4}}$ molecule structure, the 20Mn-NC-second catalyst exhibits disorganized structures, especially in terms of the disordered nature and defective structures that comprise the edges of carbon planes and grain/domain boundary at the surface of the carbon particles. Due to a low content of Mn and a more disorganized, defective carbonaceous/meso-graphitic structure, the EXAFS data of the actual catalyst 20Mn-NCsecond exhibits more noise, which could also contribute to the peak deviation observed at around $1.9\\mathring\\mathrm{A}$ . We also compared the Mn catalysts at different synthesis stages, which shows the evolution of the Mn local structures and demonstrates the formation of atomically dispersed Mn sites instead of Mn clusters. Although we tried the measurement for 20Mn-NC-first to study the possible structure changes of the active sites after the adsorption step, due to a very low Mn concentration $(0.68\\mathrm{wt\\%}$ by ICP-MS) the recorded spectrum was not sufficient for high-quality data analyses (Supplementary Fig. 7). \n\n![](images/2627c98e1b0e19ff3298d93c5af5e5341c1f0ace8ac7167d979add1846ec7038.jpg) \nFig. 1 | Schematic of atomically dispersed $\\mathsf{M n N}_{4}$ site catalyst synthesis. A two-step doping and adsorption approach can gradually increase the density of the atomically dispersed and nitrogen-coordinated $\\mathsf{M n N}_{4}$ sites into the 3D carbon particles. In the first step, Mn-doped ZIF-8 precursors are carbonized and then leached with an acid solution to prepare a partially graphitized carbon host with optimal nitrogen doping and microporous structures. In the second step, additional Mn and N sources were adsorbed into the 3D carbon host followed by a thermal activation to generate increased density of $M n N_{4}$ active sites. \n\nThe elemental quantifications of different precursors and Mn-N-C catalysts determined from $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) are summarized in Supplementary Table 5. The content of N in the 20Mn-ZIF precursor is $31.2\\mathrm{at\\%}$ and the N 1s spectrum shows a symmetric and sharp peak at $398.6\\mathrm{eV}$ corresponding to $\\mathrm{C}{=}\\mathrm{N}$ of 2-methylimidazole (Fig. 2d)39. After pyrolysis, the hydrocarbon networks of the precursors transformed into partially graphitized carbon with a $\\mathrm{\\DeltaN}$ content of $2.2{\\mathrm{at\\%}}$ . The samples obtained at the different processing steps exhibited nearly identical C 1s spectra (Fig. 2e and Supplementary Table 6) and carbon content, indicating that the second adsorption step does not induce any change to the carbon structure. Although the N content continuously decreased during processing to a level of $1.3\\mathrm{at\\%}$ after the second adsorption step, the amount of N appears to be sufficient to form a significant fraction of $\\mathrm{MnN}_{4}$ coordination relative to the low content of Mn (approximately half that of N). In addition to two dominant peaks that correspond to graphitic- and pyridinic-N, respectively, the N 1s XPS peak at $399.1\\mathrm{eV}$ could be attributed to N atoms bonded to M sites40, likely $\\mathrm{MnN}_{4}$ in the catalyst. The percentage of $\\mathrm{MnN}_{4}$ increased from $5.8\\%$ to $11.2\\%$ after the second adsorption step (Supplementary Table 7); the percentage of pyridinic-N decreased by about $10\\%$ , likely due to further coordination with Mn ions as evidenced by the N 1s peak shift from the original pyridinic-N at $398.4\\mathrm{eV}$ to $399.1\\mathrm{eV}.$ The XPS Mn $2p$ peak of 20Mn-NC-first (Fig. 2f) shows a $0.7\\mathrm{eV}$ shift to a higher bonding energy compared with the sample before acid leaching (20Mn-NC). It was reported that the interaction between metallic clusters and $\\mathrm{MN}_{x}$ could change the charge density of the central metal ions and lead to a shift in the binding energy12. Thus, the positive shift may be due to the removal of Mn clusters during acid leaching. Considering that 20Mn-NC-first and 20Mn-NCsecond exhibit the same Mn $2p$ peak position, no additional Mn clusters are produced during the second adsorption step. \n\nFigure 3a–c present typical bright-field and medium-angle annular dark field (MAADF) STEM images of the carbon particles in the 20Mn-NC-second catalyst that show highly disordered carbon structures with randomly oriented graphitic domains and less dense, pore-like morphologies (dark contrast in Fig. 3c). Similar carbon phases were observed in other ZIF-8-derived catalysts22,27,28, but the Mn-N-C catalyst appears to contain domains with a higher degree of graphitization. Low voltage, aberration-corrected STEM imaging coupled with electron energy loss spectroscopy (EELS) was used to study the atomic dispersion and local environment of Mn at an atomic resolution. The MAADF detector extends the range of the collection semi-angle to 54–200 mrad (versus 86–200 mrad for high-angle annular dark field STEM), which can provide more contrast from lower-scattering, light elements for example, carbon and nitrogen. Distinguishable signals for C, N, O and Mn are observed in the EELS maps across the carbon nanoparticles (Fig. 3e–h), respectively, acquired for the particle shown in Fig. 3d. The bright spots shown in the high-resolution MAADFSTEM images in Fig. 3i,j correspond to single heavy atoms that are uniformly dispersed across/within the carbon structure, indicating a high density of Mn doping. Furthermore, an EEL point spectrum (Fig. 3k) was obtained by placing the $1\\mathring\\mathrm{A}$ electron probe directly on a single atom (for example, as circled in red in Fig. 3j), which is near the edge of a single or double graphene layer (basal planes) that form the graphite domains of the carbon nanoparticles. Based on the ångström resolution of the electron probe and thin sample area, the signal that contributes to the EEL point spectrum (Fig. 3k) originates from the atom and its closest neighbouring atoms. The co-existence of N and a single Mn within this ångström region provides strong evidence for a $\\mathrm{{Mn-N}}$ coordinate structure, suggesting that single Mn ions are anchored by $\\mathrm{~N~}$ within carbon. The immediate vicinity of single Mn sites with N is confirmed by similar EELS analyses acquired from different areas of the catalysts (Supplementary Fig. 8). \n\nAtomically dispersed Mn sites are also observed in MAADFSTEM images acquired of the 20Mn-NC-first catalyst and the EEL point spectra reveal a similar co-existence of Mn and $\\mathrm{~N~}$ (Supplementary Fig. 8). We infer from this result that the state of Mn in the 20Mn-NC-first is similar to that in the 20Mn-NC-second, and is likely that of a $\\mathrm{MnN_{4}}$ coordinated structure. The primary difference between the two catalysts is that the density of $\\mathrm{MnN}_{4}$ active sites is significantly increased after the second adsorption step. The signals of both Mn and N become much stronger after the second adsorption step as evidenced in the comparison of the EELS elemental maps (Supplementary Fig. 9), indicating a higher density of $\\mathrm{MnN_{4}},$ which is also verified by MAADF-STEM imaging, as shown in Supplementary Fig. 8. Although a number of bright spots are uniformly dispersed in the MAADF-STEM images for 20Mn-NC-first, only a few Mn-N coordinated sites were confirmed by EELS. Many of the brighter atoms probed showed N but not Mn by EELS and may be residual $Z\\mathrm{n}$ ( $0.1{\\mathrm{at\\%}}$ , Supplementary Table 5). After the second adsorption step, the co-existence of Mn and N becomes dominant and is easily verified by EEL spectra acquired for many different areas, indicating a significant increase in the density of $\\mathrm{MnN}_{4}$ sites in the 20Mn-NC-second catalyst. ICP-MS results also verify that the Mn content increases from $0.68\\mathrm{wt\\%}$ in the 20Mn-NC-first to $3.03\\mathrm{wt\\%}$ in the $20\\ensuremath{\\mathrm{Mn}}$ -NC-second. The two-step Mn dopingadsorption method effectively increases the density of $\\mathrm{MnN}_{4}$ active sites without the concomitant formation of Mn clusters. \n\n![](images/df72a149f4978f0fe86ebbd070e6e4b385376c5a73a5be0f539e3b02a375f3a0.jpg) \nFig. 2 | Structural characterization by XANES, EXAFS and XPS. a, The experimental K-edge XANES spectra of 20Mn-NC-second catalyst and reference samples (MnO, $\\mathsf{M n O}_{2}$ and standard MnPc). b,c, Fourier transforms of Mn K-edge EXAFS data (open circle) and model-based fits (red line) of standard MnPc (b) and the $20M{\\mathfrak{n}}$ -NC-second catalyst (c). d–f, High-resolution N 1s (d), C 1s (e) and Mn $2p$ (f) XPS data of materials obtained from different processing steps. The 20Mn-NC was prepared through a pyrolysis of the 20Mn-ZIF-8 precursor. The 20MnNC-first is obtained after an acid leaching and a heat treatment of $20M n-N C$ . The 20Mn-NC-second catalyst is the final catalyst after two-step doping and adsorption processes. \n\nORR activity of atomically dispersed Mn-N-C catalysts. The ORR activity and four-electron selectivity $\\mathrm{(H}_{2}\\mathrm{O}_{2}$ yield) of all catalyst samples were evaluated using a rotating ring-disk electrode (RRDE) in a 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte. Unlike ZIF-derived Fe and Co catalysts, one-step chemical doping of Mn into ZIFs is not an effective method to generate high ORR activity. With Mn doping content ranging from 0 to $30\\mathrm{at\\%}$ , poor ORR activity is measured for all Mn-NC-first samples exhibiting half-wave potential $(E_{1/2})$ less than $0.65\\mathrm{V},$ which is likely due to an insufficient density of active sites (Supplementary Fig. 10). Inspired by the concept of host–guest strategy41, we introduced more $\\mathrm{MnN_{4}}$ active sites into the promising Mn-NC-first host through the second adsorption step. The adsorption step leads to significantly enhanced activity for all samples; the 20Mn-NC-second catalyst exhibited the most positive $E_{1/2}$ up to $0.8\\mathrm{V}$ versus the reversible hydrogen electrode (RHE) (Fig. 4a). Note that there is no Fe contamination during this multistep processing procedure, as evidenced by negligible Fe content in the catalysts determined by ICP-MS and XPS analyses (Supplementary Fig. 11) as well as poor activity of the Mn-free control sample after multiple heating treatments. Considering the comparable carbon structure and N dopant (Supplementary Tables 1 and 5) before and after the adsorption step of synthesis, the enhanced performance originated from the increasing $\\mathrm{MnN}_{4}$ concentration. A poisoning experiment was performed by employing KSCN to block the $\\mathrm{M}{-}\\mathrm{N}_{x}$ sites42. The negative shift of $150\\mathrm{mV}$ of $E_{1/2}$ (Supplementary Fig. 12) further verifies that the primary active sites in the 20Mn-NC-second catalyst are metal-based $\\mathrm{MnN_{4}},$ instead of metal-free $\\mathrm{CN}_{x}$ sites. The adsorption step also leads to an obvious enhancement of activity for both ketjenblack (KJ-black) and polyaniline-derived nanocarbon (PANI-NC) (Fig. 4b), indicating that the adsorption step is an effective strategy to introduce $\\mathrm{MnN}_{4}$ active sites, regardless of the carbon host. However, an optimal nitrogen doping level and the pore structure of the carbon host are crucial for maximum activity during the adsorption step. The adsorption using distinct Mn salts without N source still leads to an improvement in the activity (Fig. $\\mathtt{4c}$ and Supplementary Fig. 13). This suggests that Mn ions chemically bonded with the pre-doped N in the carbon host and form $\\mathrm{MnN}_{4}$ active sites through subsequent thermal activation. Co-adsorption of Mn and N sources yields improved activity with an increased N content in the final 20Mn-NC-second catalyst. (Supplementary Table 5). Due to significant reductions of micropores and Brunauer–Emmett–Teller surface areas of the carbon host after adsorption process (Supplementary Fig. 14), we believe that N sources can stabilize Mn ions through possible coordination in the micropores. During the pyrolysis, the N source creates additional $\\mathrm{~N~}$ doping in the carbon host, which can further coordinate with Mn ions and form $\\mathrm{MnN_{4}}$ active sites. Cyanamide exhibited the best performance, compared with other $\\mathrm{~N~}$ sources (for example, dipicolylamine, phenanthroline and melamine), probably due to its size and unique $\\mathrm{C}\\equiv\\mathrm{N}$ structures. The $\\mathrm{C}\\equiv\\mathrm{N}$ structures decompose at the elevated temperature and easily bond to unsaturated carbon atoms to form stable pyridinic- $\\mathbf{\\cdotN^{34}}$ . This is favourable for the formation of $\\mathrm{MnN}_{4}$ active sites. \n\n![](images/f35cdce039c58ce837905ebef9a080261b52d08ddc10c805c95faee2c40c5424.jpg) \nFig. 3 | Morphology and atomic structure of the 20Mn-NC-second catalyst. a–d, Representative HR-TEM (a,b) and STEM (c,d) images of a carbon particle in the catalyst. e–h, EELS elemental maps of C (e), N $(\\pmb{\\uparrow})$ , O $\\mathbf{\\sigma}(\\mathbf{g})$ and ${\\cal M}{\\sf n}\\left({\\bf h}\\right)$ of the area in (d). i,j, Aberration-corrected MAADF-STEM images. k, EEL point spectrum from the atomic sites circled in red in j. Image resolution in i and j is roughly $0.1\\mathsf{n m}$ using an accelerating voltage of $60{\\sf k V}.$ \n\n![](images/4635ae2cc47d3669a06740df05bb9f89a0a4046c24a5084120b57f041fcb82da.jpg) \nFig. 4 | ORR activity studied by using RRDE and fuel cell tests. a–d, Steady-state ORR polarization plots in $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ electrolytes $\\mathsf{P t/C}$ catalyst reference was studied in 0.1 M ${\\mathsf{H C l O}}_{4})$ to study the effect of synthesis steps (that is, first doping and second adsorption) on Mn-N-C catalyst activity (a), effect of various carbon hosts used for the second adsorption step on resultant activity $(\\pmb{6})$ , effect of different nitrogen sources used for the adsorption step on final catalyst activity $(\\bullet)_{i}$ , and comparison of catalytic activity of Fe-, Co- and Mn-N-C catalysts prepared from identical procedures (d). e, Four-electron selectivity (that is, ${\\sf H}_{2}{\\sf O}_{2}$ yields) of the ORR on Fe-, Co- and Mn-N-C catalysts. f, Fuel cell performance of the best-performing 20Mn-NC-second and 20FeNC-second catalysts in both ${\\sf H}_{2}/\\sf{O}_{2}$ and ${\\sf H}_{2},$ /air conditions. Error bars represent the standard deviation from at least three independent measurements. \n\nThe influence of post-treatments on the Mn-NC host before adsorption was investigated. When directly using 20Mn-NC without an acidic treatment as the host for the second adsorption step, the activity showed an obvious decline (Supplementary Fig. 15). Acid leaching effectively removes the MnO clusters from the 20Mn-NC host, which likely creates pore structures and increases micropore sizes (from 1.0 to $1.4\\mathrm{nm}\\dot{}$ ) and surface areas (from 699 to $821\\mathrm{m}^{2}\\mathrm{g}^{-1})$ ) (Supplementary Figs. 16 and 17 and Supplementary Table 8), which is favourable for the subsequent adsorption. As a result, the 20Mn-NCsecond catalyst exhibits the highest electrochemically accessible surface area of $715\\mathrm{m}^{2}\\mathrm{g}^{-1}$ (Supplementary Fig. 18 and Supplementary Table 9), corresponding to the highest ORR activity. The correlation between the porous structure of the carbon host and the ORR activity was established (Supplementary Figs. 19 and 20). \n\nThe ORR activity of the best-performing 20Mn-NC-second catalyst, which is higher than that of a 20Co-NC-second catalyst and approaches that of a 20Fe-NC-second catalyst (Fig. 4d), is $60\\mathrm{mV}$ less than of a $\\mathrm{Pt/C}$ catalyst $(\\sim0.86\\mathrm{V})$ . The atomically dispersed Mn catalyst represents one of the best PGM- and Fe-free catalysts (Supplementary Table $10)^{43}$ . The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield of the 20Mn-NCsecond catalyst is less than $2\\%$ indicating a four-electron reduction pathway, which is comparable to that of the 20Fe-NC-second, and much lower than that of the $20\\mathrm{Co}$ -NC-second catalyst (Fig. 4e). When the catalyst loadings vary within a wide range from 0.2 to $1.2\\mathrm{mg}\\mathrm{cm}^{-2}$ , the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yields (Supplementary Fig. 21) remain at a very low level $(<4\\%)$ . This further indicates a $4\\mathrm{e}-$ ​pathway, rather than the $2e^{-}+2e^{-}$ pathway. A Tafel slope of ${\\sim}80\\mathrm{mV}\\mathrm{dec^{-1}}$ for the 20Mn-NC-second is comparable to that of Co- or Fe-based catalysts (Supplementary Fig. 22 and Supplementary Table 11), indicating a similar rate-determining step involving mixed controls including transfer of the first electron $(118\\mathrm{mV}\\mathrm{dec^{-1}})$ and the diffusion of intermediates at catalyst surfaces $(59\\mathrm{mV}\\mathrm{dec^{-1}})^{44}$ . \n\nThe 20Mn-NC-second catalyst is further studied as a cathode in membrane electrode assemblies (MEAs) for fuel cells. The open circuit voltage is $0.95\\mathrm{V}$ using $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}{:}$ suggesting a high intrinsic ORR activity in fuel cell environments. The 20Mn-NC-second cathode is capable of generating current densities of 0.35 and $2.0\\mathrm{Acm}^{-2}$ at 0.6 and $0.2\\mathrm{V},$ respectively, at a reasonable 1.0 bar partial pressure (Fig. 4f). The corresponding power density is up to $0.46\\mathrm{W}\\mathrm{cm}^{-2}$ . The achieved performance exceeds the Fe-N-C catalyst derived from PANI reported in 2010 (ref. 45); however, the performance is inferior to the 20Fe-NC-second catalyst especially in the kinetic range. \n\nEnhanced catalyst stability in acids. The $20\\ensuremath{\\mathrm{Mn}}$ -NC-second catalyst exhibited excellent stability, as evidenced by a loss of only $17\\mathrm{mV}$ in $E_{1/2}$ after 30,000 potential cycles from 0.6 to $1.0\\mathrm{V}$ in $\\mathrm{~O}_{2}$ -saturated $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution (Fig. 5a). The stability is largely enhanced over traditional Fe-N-C catalysts derived from PANI (loss $80\\mathrm{mV}$ after 5,000 cycles)45, as well as the ZIF-derived 20Fe-NC-second catalyst ( $29\\mathrm{mV}$ loss) (Fig. 5b). The microstructure and morphology of carbon in the 20Mn-NC-second catalyst remain nearly the same (Supplementary Fig. 23) after the potential cycling tests. Long-term durability tests were conducted by holding at a constant potential of $0.7\\mathrm{V}$ for 100 hours during the ORR (Fig. 5c). The 20Mn-NC-second catalyst retains $88\\%$ of its initial current density and exhibits a $29\\mathrm{mV}$ loss of $E_{1/2}$ after 100 hours (Fig. 5d). The identical cyclic voltammetry curves during the stability tests (inset of Fig. 5d) indicate excellent resistance to carbon corrosion. To test the 20Mn-MCsecond catalyst under harsher conditions, we performed the durability test at $0.8\\mathrm{V}$ (Fig. 5e). A larger decline of the current density of $57\\%$ after 100 hours is observed, relative to $0.7\\mathrm{V}.$ The loss of current density during the test can be partially recovered by potential cycling between 0 to $1.0\\mathrm{V}.$ For the first 20 hours, nearly $90\\%$ of the activity can be restored. However, the irreversible loss accumulates and the current density only recovers $70\\%$ after 80 hours, indicating that the activity loss is due to multiple factors. The reversible activity loss may be associated with deactivation of active sites by anion binding or reversible adsorption of oxygen-containing functional groups on local carbon atoms adjacent to $\\mathrm{MnN_{4}}$ sites, which are considered to be part of the active site46. After the 100 hour test at $0.8\\mathrm{V},$ $E_{\\scriptscriptstyle{1/2}}$ showed a loss of $18\\mathrm{mV}$ for the 20Mn-NC-second catalyst (Fig. 5f). In comparison, the 20Fe-NC-second catalyst only retains $39\\%$ of its activity and a loss of $E_{1/2}$ is up to $48\\mathrm{mV}$ (Supplementary Fig. 24). The increase of capacitance for the $20\\ensuremath{\\mathrm{Mn}}$ -NC-second catalyst (inset of Fig. 5f) is around $30\\%$ , much less than that of the \n\n![](images/ceb32bd12fa7b850aacfc754f79b7d466a3418c749f06b0aa26aba69bdd84fc5.jpg) \nFig. 5 | Catalyst stability studied by using potential cycling and constant potentials. a,b, Steady-state ORR polarization plots before and after potential cycling stability tests (0.6–1.0 V, 30,000 cycles) for the 20Mn-NC-second (a) and 20Fe-NC-second $(\\pmb{\\ b})$ catalysts. c,e, i–t curves (where i is current density and t is time) at constant potentials of 0.7 V (c) and $0.8\\mathsf{V}$ (e). d,f, Steady-state ORR polarization plots and cyclic voltammetry curves before and after constant potential tests at $0.7\\mathrm{V}$ (d) and $0.8\\mathsf{V}$ (f) for 100 hours in $\\mathsf{O}_{2}$ -saturated 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ . \n\n20Fe-NC-second catalyst $(60\\%)$ , suggesting an enhanced carbon oxidation resistance. The catalyst degradation may be dependent on total number of electrons passing through catalysts during the ORR. Therefore, we calculated the degradation rates against the total electric charge (Supplementary Table 12). The degradation of $E_{1/2}$ at $0.8\\mathrm{V}$ is $0.237\\mathrm{mVC^{-1}}$ for the 20Mn-NC-second catalyst, much less than that for the 20Fe-NC-second catalyst $(0.71\\dot{6}\\mathrm{mVC^{-1}}^{\\cdot},$ ). Stability tests at a constant current density $(1.42\\mathrm{mA}\\mathrm{cm}^{-2},$ further verified that the 20Mn-NC-second catalyst is more stable than the $20\\mathrm{Fe}$ -NC-second catalyst (Supplementary Fig. 25). Corrosion resistance of carbon in catalysts was further assessed by cycling at a high potential range $(1.0\\mathrm{-}1.5\\mathrm{V})$ in $\\Nu_{2}$ -saturated $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ (Supplementary Fig. 26). After $^{5,000}$ cycles, the capacitance of the 20Mn-NC-second and 30Mn-NC-second increase $52\\%$ and $34\\%$ , respectively, suggesting carbon oxidation in catalysts. However, these values are much lower than those of 0Mn-NC-second $(70\\%)$ and the 20Fe-NC-second catalyst $(94\\%)$ (Supplementary Table 9), indicating significantly enhanced carbon stability due to Mn doping into ZIF-8 precursors. Thus, the enhanced stability of the Mn-N-C catalyst likely results from the improved corrosion resistance of the carbon in the catalysts. \n\n![](images/6eab15cbbb614e9f5e460f88a2abcbcb94d340b2f8e7122fbb94d2e0250088d7.jpg) \nFig. 6 | Fundamental understanding of possible Mn active sites by using DFT calculations. a, Atomistic structure of $M n N_{4}C_{12}$ active site in the 20MnNC-second catalyst. b, Calculated free-energy evolution diagram for ORR through a $4\\mathsf{e}^{-}$ associative pathway on the $M n N_{4}C_{12}$ active site under electrode potential of $U=1.23\\vee$ and $U{=}0.80\\backslash$ V. c, Atomistic structure of initial state (left panel, that is, state $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ in b), transition state (middle panel) and final state (right panel, that is, state $^{\\star}\\mathsf{O}+^{\\star}\\mathsf{O}\\mathsf{H}$ in b) for OOH dissociation reaction on $M n N_{4}C_{12}$ active site. Grey, blue, purple, red and white balls represent C, N, Mn, O and H atoms, respectively. \n\nTo evaluate catalyst stability under real fuel cell operating conditions, we conducted 100 hour life tests at a challenging high voltage of $0.7\\mathrm{V}$ for MEAs made with the 20Mn-NC-second catalyst (Supplementary Fig. 27). Although an initial degradation occurred at $0.7\\mathrm{V},$ enhanced durability of the Mn-N-C cathode was observed, compared with Co- and Fe-based catalysts15,22. The Mn-N-C catalyst prepared from the two-step doping and adsorption approach represents one of the most stable PGM-free catalysts in acidic electrolytes (Supplementary Table 10). In addition to the intrinsic stability of the 20Mn-NC-second catalyst, non-electrochemical factors including degradation of the catalyst/ionomer interfaces and water flooding also influence the performance durability of PGM-free cathodes. \n\nDFT calculations. We identified a variety of possible $\\mathrm{MnN}_{x}\\mathrm{C}_{y}$ active sites and predicted their adsorption energies, free-energy evolution and activation energies for the ORR in acids. As shown in Supplementary Fig. 28, nine possible active sites (denoted as $\\mathrm{MnN}_{2}\\mathrm{C}_{12},$ $\\mathrm{MnN}_{3}\\mathrm{C}_{9}$ , $\\mathrm{MnN}_{3}\\mathrm{C}_{11},$ $\\mathrm{MnN}_{4}\\mathrm{C}_{8},$ , $\\mathrm{MnN}_{4}\\mathrm{C}_{10},$ $\\mathrm{MnN}_{4}\\mathrm{C}_{12},$ $\\mathrm{MnN}_{5}{\\mathrm C}_{10},$ $\\mathrm{Mn}_{2}\\mathrm{N}_{5}\\mathrm{C}_{12}$ and $\\mathrm{Mn}_{2}\\mathrm{N}_{6}\\mathrm{C}_{14})$ are carefully examined in the computational study. The predicted adsorption energy of $\\mathrm{O}_{2},$ OOH, O, OH and $\\mathrm{H}_{2}\\mathrm{O}$ on each of these potential $\\mathrm{MnN}_{x}\\mathrm{C}_{y}$ active sites are presented in Supplementary Table 13. The DFT adsorption energy results indicate that $\\mathrm{MnN}_{2}\\mathrm{C}_{12}$ and $\\mathrm{MnN}_{3}\\mathrm{C}_{9}$ sites, which have fewer chelated $\\mathrm{\\DeltaN}$ atoms around the central metal atom than the other sites, bind the final product $_\\mathrm{H}_{2}\\mathrm{O}$ too strongly to be good active sites. Moreover, $\\begin{array}{r}{\\mathrm{MnN}_{3}\\mathrm{C}_{11},\\mathrm{MnN}_{4}\\mathrm{C}_{8},}\\end{array}$ and $\\mathrm{Mn}_{2}\\mathrm{N}_{5}\\mathrm{C}_{12}$ sites were predicted to bind the intermediate OH too strongly, which are not good active sites as well. Computational screening identified that $\\mathrm{MnN}_{4}\\mathrm{C}_{10},$ $\\mathrm{MnN}_{4}\\mathrm{C}_{12},$ $\\mathrm{MnN}_{5}\\mathrm{C}_{10},$ and $\\mathrm{Mn}_{2}\\mathrm{N}_{6}\\mathrm{C}_{14}$ sites have an appropriate binding strength with the ORR species and can be active sites for the $4\\mathrm{e}^{-}$ pathway. \n\nXAS analyses suggest that $\\mathrm{MnN_{4}}$ structures are likely. Among studied $\\mathrm{MnN}_{4}\\mathrm{C}_{\\mathrm{y}}$ sites, the $\\mathrm{MnN}_{4}\\mathrm{C}_{12}$ site (a $\\mathrm{Mn-N_{4}}$ moiety bridging over two adjacent zigzag graphitic edges, as shown in Fig. 6a) was further predicted as the most optimal active sites (Supplementary Table 13). Its free-energy evolution for the ORR (Fig. 6b) and the transition state for an OOH dissociation on the active site were also calculated (Fig. 6c). We assumed a $4\\mathrm{e}^{-}$ pathway, in which an $\\mathrm{O}_{2}$ molecule will first adsorb on the top of central Mn and then $\\mathrm{O}_{2}$ will be protonated to form OOH. Next, the OOH will dissociate into O and OH, and finally both O and OH will be protonated to form the final product $\\mathrm{H}_{2}\\mathrm{O}$ . We employed the computational hydrogen electrode method developed by Nørskov et al.47 and computed the free energies of all elementary steps as a function of electrode potential $U$ with reference to the RHE. Figure $6\\ensuremath{\\mathrm{b}}$ shows that, under the standard potentials of the ORR, $\\begin{array}{r}{U{=}1.23\\mathrm{V},}\\end{array}$ that is, zero overpotential, some of the elementary reactions along the $4\\mathrm{e}^{-}$ ORR associative pathway are endergonic and thus thermodynamically unfavourable on the $\\mathrm{MnN}_{4}\\mathrm{C}_{12}$ site. However, the free-energy change for these elementary reactions involving charge transfer will become negative (that is, exergonic reaction) when the electrode potential $U$ is lower than a limiting potential of $0.80\\mathrm{V}.$ Moreover, our computational results (Fig. 6b) show that both the free-energy differences between ${\\mathrm{~O}}_{2}^{*}$ and ${\\mathrm{OOH}}^{*}$ as well as between $\\mathrm{OH^{*}}$ and $\\mathrm{H}_{2}\\mathrm{O}^{*}$ $^{'*}$ represents the adsorption of the molecule on the active site) are close to zero under the limiting potential, suggesting that the $\\mathrm{MnN}_{4}\\mathrm{C}_{12}$ site could have an optimal activity for the $\\mathrm{ORR^{48}}$ . We performed the climbing image nudged elastic band (CI-NEB) calculation to locate the transition state and predict the activation energies for the OOH dissociation reaction49, which is the crucial step of breaking the $_{\\mathrm{O-O}}$ bond for the $4\\mathrm{e}^{-}$ ORR associative pathway on the $\\mathrm{MnN}_{4}\\mathrm{C}_{12}$ site. Figure 6c shows the atomic details of this reaction. In the initial state, OOH is adsorbed on the central Mn atom; in the final state, both the dissociated O and OH are co-adsorbed on the central Mn atom. The reaction process from the initial state to the final state requires passing a transition state and overcoming an energy barrier of $0.49\\mathrm{eV},$ which is surmountable. Consequently, the DFT results predict that it is both thermodynamically and kinetically favourable for the $4\\mathrm{e}^{-}$ ORR to occur on the $\\mathrm{MnN}_{4}\\mathrm{C}_{12}$ site. According to the XANES and EXAFS analysis (Fig. 2), the atomic Mn sites in the catalysts have an oxidation state of $^{2+}$ ​ and coordinate with N mainly in the form of $\\mathrm{MnN_{4}}$ . The MAADF-STEM images (Fig. 3) further proved the atomic dispersion and N was detected in the immediate vicinity of the single Mn sites by EEL point spectrum. Hence, the computational model explains well our experimental findings. Although multiple possible sites in nanocarbon are able to coordinate with single metals sites50, their ORR activities and stabilities in acids are not sufficient. In contrast, the $\\mathrm{MnN_{4}}$ structure therefore is the most stable and the most active sites for the ORR in acids, likely due to the lone pair electrons in pyridinic-N, which can form strong coordination bonds with transition metals. \n\nWe also performed DFT calculations to specifically examine the influence of water solvent on the ORR in Mn-N-C catalysts, suggesting that the water solvent effect is not significant enough to alter the reaction mechanism for the ORR on the Mn-N-C catalysts (Supplementary Fig. 29). The $\\mathrm{MnN}_{4}$ sites with surrounding graphitic-N dopants would also be active to promote the $4\\mathrm{e}^{-}$ ORR following the same OOH dissociation pathway (Supplementary Fig. 30). The $\\mathrm{MnN}_{4}$ site with immediately adjacent graphitic-N dopants could have a lower limiting potential and lower activation energy for $_{\\mathrm{O-O}}$ bond breaking than the $\\mathrm{MnN}_{4}$ site without graphitic-N dopants. \n\n# Conclusion \n\nAn atomically dispersed and nitrogen-coordinated Mn-N-C catalyst has been developed through a two-step doping and adsorption approach, which is effective to significantly increase the density of active sites. Atomically dispersed $\\mathrm{MnN}_{4}$ sites were verified using XAS experiments to determine their possible coordination as well as directly observed at the atomic scale using low voltage, aberration-corrected STEM imaging coupled with EELS analysis. The high activity of the Mn-N-C catalyst was evidenced by a commendable $E_{\\scriptscriptstyle{1/2}}$ of $0.80\\mathrm{V}$ versus RHE in acids, which results from intrinsic activity of atomically dispersed $\\mathrm{MnN_{4}}$ sites with increased density within a 3D porous ZIF-derived carbon. The remarkable stability is due to the robust $\\mathrm{MnN_{4}}$ sites and the enhanced corrosion resistance of adjacent carbon derived from Mn doping. DFT calculations also further confirmed that the $\\mathrm{MnN}_{4}\\mathrm{C}_{12}$ site has a favourable binding energy with $\\mathrm{O}_{2}\\mathrm{:}$ , OOH and $\\mathrm{H}_{2}\\mathrm{O}$ during the ORR as well as a surmountable energy barrier to break $_{\\mathrm{O-O}}$ bonds for complete $4\\mathrm{e}^{-}$ reduction. Therefore, the reported atomically dispersed Mn-N-C catalyst demonstrates an alternative concept to develop robust and highly active PGM-free catalysts as replacements for Fe catalysts in future PEMFC technologies. \n\n# Methods \n\nCatalysts synthesis. In the first doping step, Mn-doped ZIF-8 precursors were synthesized in a dimethylformamide (DMF) solution. The precursors are designated as nMn-ZIF, where $n$ is the molar percentage of Mn against total metals (Mn and $Z\\mathrm{n}$ ) in the solutions. In this work, the $n$ value varied from 0 (Mn free) to $30\\mathrm{at\\%}$ and the concentration of 2-methylimidazle and $Z\\mathrm{n}^{2+}$ were controlled at 80 and $40\\mathrm{mmoll^{-1}}$ , respectively. Typically, a controlled amount of zinc(ii) nitrate hexahydrate and manganese(iii) acetate dihydrate were dissolved into DMF to form a uniform solution in a round-bottom flask (A). 2-Methylimidazole was dissolved in a conical-flask with DMF solution (B). After mixing solutions A and B, the reaction temperature was increased to ${120^{\\circ}\\mathrm{C}},$ holding for $24\\mathrm{h}$ to allow Mn-doped ZIF-8 nanocrystals to grow. After cooling down to room temperature, the Mn-ZIF-8 nanocrystals were collected by centrifugation, washed at least three times with ethanol, and then dried at $60^{\\circ}\\mathrm{C}$ in a vacuum oven for 5 h. The Mn-ZIF-8 precursors were subsequently heated at a temperature of $1,100^{\\circ}\\mathrm{C}$ in a tube furnace under $\\Nu_{2}$ flow for $^\\mathrm{1h}$ to obtain the Mn and N co-doped nanocarbon (NC). The samples were labelled as nMn-NC, where $n$ is atomic percent of Mn against total metal (for example, 20Mn-NC). Next, acid leaching treatment in $0.5\\mathbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution at $80^{\\circ}\\mathrm{C}$ for 5 h was carried out to remove Mn clusters and open porous structures of nMn-NC samples. Typically, $\\mathrm{100ml}$ acid solution was used for $100\\mathrm{mg}$ sample. An additional heat treatment at $900^{\\circ}\\mathrm{C}$ under $\\Nu_{2}$ flow for $^{3\\mathrm{h}}$ is necessary to repair the carbon structure. Such-prepared carbon samples labelled as nMn-NC-first are ready for the second adsorption step. \n\nIn the second adsorption step, the nMn-NC-first powder was dispersed into a mixed solution (isopropanol: water $=1{:}1$ ) containing $\\mathrm{{Mn}(\\pi)}$ chloride and nitrogen sources (for example, dipicolylamine, cyanamide, phenanthroline or melamine). After 2 h ultrasonication along with and 5 h magnetic stirring, the mixture was collected by centrifugation $_{(13,552g)}$ and then dried at $60^{\\circ}\\mathrm{C}$ in a vacuum oven for 5 h. A subsequent thermal activation at temperature of $1,100^{\\circ}\\mathrm{C}$ under $\\mathrm{N}_{2}$ atmosphere for 1 h was conducted to synthesize the final catalysts, labelled as nMnNC-second. As control samples, 20Co-NC-second and 20Fe-NC-second samples were prepared through similar procedures. \n\nPhysical characterization. The overall particle size and distribution of the catalysts’ morphologies were analysed using scanning electron microscopy on a Hitachi SU 70 microscope at a working voltage of $5\\mathrm{kV.}$ The crystal phases in catalyst samples were studied by using powder XRD on a Rigaku Ultima IV diffractometer with Cu Kα​X-rays. XPS was carried out using a Kratos AXIS Ultra DLD XPS system equipped with a hemispherical energy analyser and a monochromatic Al Kα​source operated at $15\\mathrm{keV}$ and $150\\mathrm{W}$ . Pass energy was fixed at $40\\mathrm{eV}$ for all of high-resolution scans. The $\\mathrm{N}_{2}$ isothermal adsorption/desorption was recorded at $77\\mathrm{K}$ on a Micromeritics TriStar II. Before measurements, samples were degassed at $150^{\\circ}\\mathrm{C}$ for 5 h under vacuum. Atomic-resolution MAADF images of atomically dispersed Mn sties were captured in a Nion Ultra STEM U100 operated at $60\\mathrm{keV}$ and equipped with a Gatan Enfina electron energy loss spectrometer at Oak Ridge National Laboratory. HR-TEM and high-angle annular dark field STEM were performed on JEOL JEM-2100F and Hitachi HD2700C with a probe-corrector, respectively, at Brookhaven National Laboratory. Mn K-edge EXAFS experiments were carried out at beamline 9BM-C at Advanced Photon Sources at Argonne National Laboratory. The EXAFS data were collected in fluorescence mode due to low Mn concentration by using a Vertox ME4 silicon drift diode detector. Data analysis and EXAFS fitting were performed with the Athena, Artemis, and IFEFFIT software packages. \n\nElectrochemical measurements. An electrochemical workstation (CHI760b) was employed to perform electrochemical measurements in a three-electrode cell, in which an $\\mathrm{Hg/HgSO_{4}}$ ( $\\mathrm{{K_{2}S O_{4}}}$ -saturated) electrode and a graphite rod were used as the reference and counter electrodes, respectively. A RRDE (Pine, AFMSRCE 3005) with a disk diameter of $5.6\\mathrm{mm}$ was used as working electrode. The reference electrode was calibrated to a RHE in the same electrolyte before each measurement. The calibration of reference electrode was performed in a two-electrode system. In the studied electrolyte (that is, $0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4}$ ), a Pt wire coated with Pt black was used for the RHE. The Pt electrode is purged and saturated with high purity $\\mathrm{H}_{2}$ during calibrating. A two-probe multi-meter was employed to measure the potential difference between the reference electrode and the Pt electrode, which is relative to RHE. The catalyst ink for the RRDE tests was prepared by ultrasonically dispersing $5.0\\mathrm{mg}$ catalysts and $30\\upmu\\mathrm{l}$ Nafion $(5\\mathrm{wt\\%})$ into $2.0\\mathrm{ml}$ isopropanol solution. The ink was drop-casted on the disk electrode with a controlled loading of $0.8\\mathrm{mgcm}^{-2}$ and dried at room temperature to yield a thinfilm electrode. The electrocatalytic activity for the ORR was tested by steady-state measurement using staircase potential control with a step of $0.05\\mathrm{V}$ at an interval of 30 s from 1.0 to $0\\mathrm{V}$ versus RHE in $\\mathrm{O}_{2}$ -saturated 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution at $25^{\\circ}\\mathrm{C}$ and a rotation rate of $900\\mathrm{r.p.m}$ . Before recording the steady-state ORR polarization plots, cyclic voltammetry in $\\mathrm{O}_{2}$ -saturated $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at a scan rate of $50\\mathrm{mVs^{-1}}$ was performed to activate the catalysts until repeatable capacitance of catalyst samples is achieved. Four-electron selectivity during the ORR was determined by measuring the ring current for calculating $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield. Catalyst stability was studied by cycling potentials from 0.6 to $1.0\\mathrm{V}$ in $\\mathrm{O}_{2}$ -saturated $0.5\\mathbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at a scanning rate of $50\\mathrm{{mVs^{-1}}}$ . To determine the carbon corrosion of catalysts, potential cycling was conducted at high potentials from 1.0 to $1.5\\mathrm{V}$ in $\\Nu_{2}$ -saturated $0.5\\mathbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at a scanning rate of $500\\mathrm{mVs^{-1}}$ . In addition, holding at constant potential (for example, 0.7 and 0.8 V) or constant current density for $\\boldsymbol{\\mathrm{100h}}$ during the ORR was carried out. Pt/Vulcan XC-72 $20\\mathrm{wt\\%}$ Pt) was used as the $\\mathrm{Pt/C}$ reference, which was tested in $0.1\\mathrm{MHClO_{4}}$ solution with a Pt loading of $60\\upmu\\mathrm{gcm}^{-2}$ . \n\nFuel cell tests. The best-performing Mn-N-C catalyst was used to prepare cathodes for MEA tests in real fuel cell environments. The cathode catalyst inks were dispersed by ball mixing the catalyst in 1-proponal, de-ionized water, and Nafion suspension for 2 d. The inks were brush painted on one side of a Nafion 212 membrane until the cathode catalyst loading reached $\\sim4.0\\mathrm{mgcm}^{-2}$ . An inhouse-made Pt electrode decal $(0.25\\operatorname*{mg}\\mathrm{Ptcm^{-2}},$ was used as the anode, and it was transferred onto the other side of brush painted Nafion 212 membrane at ${\\sim}150^{\\circ}\\mathrm{C}$ for $3\\mathrm{min}$ . The full catalyst-coated membrane, which had an active geometric area of $5.0\\mathrm{cm}^{2}$ , was inserted between two Toray H30 gas diffusion layers and assembled into a single cell with single-serpentine flow channels. The single cell was then evaluated in a fuel cell test station (100 W, Scribner 850e, Scribner Associates). The cells were conditioned at $0.3\\mathrm{V},$ $100\\%$ relative humidity and $80^{\\circ}\\mathrm{C}$ for at least 3 h and until the steady-state current was reached. Air/oxygen flowing at $200\\mathrm{ml}\\mathrm{min}^{-1}$ and $\\mathrm{H}_{2}$ (purity $99.999\\%$ ) flowing at $200\\mathrm{ml}\\mathrm{min}^{-1}$ were used as the cathode and anode reactants, respectively. The back pressures during the fuel cell tests are based on US Department of Energy protocols, that is 1.0 bar reactant gas. Because of $100\\%$ relative humidity, vapour pressure is around 0.5 bar. Thus, the total pressure applied to MEAs is around 1.5 bar $\\mathrm{150KPa)}$ . Fuel cell polarization curves were recorded in a current control mode. All the cathode catalyst layers contain $35\\mathrm{wt\\%}$ of Nafion. \n\nComputational methods. All the first-principles DFT calculations in this work were performed using the Vienna ab initio simulation package. The projector augmented wave pseudopotential was used to describe the core electrons of the elements. The energy cut-off was set as $400\\mathrm{eV}$ to expand wave function. The electronic exchange-correlation was described by generalized gradient approximation with the Perdew, Burke and Ernzernhof functional. The brillouin zone was sampled with Monkhorst-pack $4\\times4\\times1~k$ -point mesh for active sites $\\mathrm{MnN}_{2}\\mathrm{C}_{12},$ $\\bf{M n N}_{3}C_{9},$ $\\mathrm{MnN}_{3}\\mathrm{C}_{11}$ , $\\mathrm{MnN}_{4}\\mathrm{C}_{10},$ $\\mathrm{MnN}_{5}{\\mathrm C}_{10},$ $\\mathrm{Mn}_{2}\\mathrm{N}_{6}\\mathrm{C}_{14}$ and $\\mathrm{Mn}_{2}\\mathrm{N}_{5}\\mathrm{C}_{12},$ $3\\times3\\times1~k$ -point mesh for site $\\mathrm{MnN}_{4}\\mathrm{C}_{12},$ and $4\\times3\\times1$ k-point mesh for site $\\mathrm{MnN}_{4}\\mathrm{C}_{8}$ . A vacuum region of $14\\mathrm{\\AA}$ thick was added in the direction normal to the carbon layer to ensure negligible interaction between the slab and its images. In the DFT structure optimization calculations, the atomic positions were allowed to relax until the force on each ion was below $0.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . The transition states of chemical reaction were located using the CI-NEB method, in which the force along and perpendicular to the reaction path were relaxed to less than $0.05\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . Zeropoint energy correction has been included in all the reported energies. \n\n# Data availability \n\nThe data that support the findings of this study are available from the primary corresponding author (G.Wu) upon reasonable request. \n\nReceived: 16 May 2018; Accepted: 17 September 2018; Published online: 29 October 2018 \n\n# References \n\n1.\t Lefèvre, M., Proietti, E., Jaouen, F. & Dodelet, J.-P. Iron-based catalysts with improved oxygen reduction activity in polymer electrolyte fuel cells. Science 324, 71–74 (2009). \n2.\t Proietti, E. et al. Iron-based cathode catalyst with enhanced power density in polymer electrolyte membrane fuel cells. Nat. Commun. 2, 416 (2011). \n3.\t Wu, G. & Zelenay, P. Nanostructured nonprecious metal catalysts for oxygen reduction reaction. Acc. Chem. Res. 46, 1878–1889 (2013). \n4.\t Gewirth, A. A., Varnell, J. A. & DiAscro, A. M. Nonprecious metal catalysts for oxygen reduction in heterogeneous aqueous systems. Chem. Rev. 118, 2313–2339 (2018). \n5.\t Chung, H. T. et al. Direct atomic-level insight into the active sites of a high-performance PGM-free ORR catalyst. Science 357, 479–484 (2017). \n6.\t Wu, G., More, K. L., Johnston, C. M. & Zelenay, P. High-performance electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt. Science 332, 443–447 (2011). \n7.\t Yan, D. et al. Defect chemistry of nonprecious-metal electrocatalysts for oxygen reactions. Adv. Mater. 29, 1606459 (2017). \n8.\t Gong, K., Du, F., Xia, Z., Durstock, M. & Dai, L. Nitrogen-doped carbon nanotube arrays with high electrocatalytic activity for oxygen reduction. Science 323, 760–764 (2009). \n9.\t Masa, J., Xia, W., Muhler, M. & Schuhmann, W. On the role of metals in nitrogen‐doped carbon electrocatalysts for oxygen reduction. Angew. Chem. Int. Ed. 54, 10102–10120 (2015). \n10.\tLiu, J. et al. High performance platinum single atom electrocatalyst for oxygen reduction reaction. Nat. Commun. 8, 15938 (2017). \n11.\tZitolo, A. et al. Identification of catalytic sites for oxygen reduction in iron- and nitrogen-doped graphene materials. Nat. Mater. 14, 937–942 (2015). \n12.\tJiang, W. J. et al. Understanding the high activity of Fe-N-C electrocatalysts in oxygen reduction: $\\mathrm{Fe}/\\mathrm{Fe}_{3}\\mathrm{C}$ nanoparticles boost the activity of Fe-Nx. J. Am. Chem. Soc. 138, 3570–3578 (2016). \n13.\tWu, G. et al. Carbon nanocomposite catalysts for oxygen reduction and evolution reactions: from nitrogen doping to transition-metal addition. Nano Energy 29, 83–110 (2016). \n14.\tBanham, D. et al. A review of the stability and durability of non-precious metal catalysts for the oxygen reduction reaction in proton exchange membrane fuel cells. J. Power Sources 285, 334–348 (2015). \n15.\tFerrandon, M. et al. Stability of iron species in heat-treated polyaniline–iron– carbon polymer electrolyte fuel cell cathode catalysts. Electrochim. Acta 110, 282–291 (2013). \n16.\tWu, G. Current challenge and pÿerspective of PGM-free cathode catalysts for PEM fuel cells. Front. Energy 11, 286–298 (2017). \n17.\tWu, G. et al. Performance durability of polyaniline-derived non-precious cathode catalysts. ECS Trans. 25, 1299–1311 (2009). \n18.\tChoi, C. H. et al. Stability of Fe-N-C catalysts in acidic medium studied by operando spectroscopy. Angew. Chem. Int. Ed. 54, 12753–12757 (2015). \n19.\tKramm, U. I., Lefevre, M., Bogdanoff, P., Schmeisser, D. & Dodelet, J. P. Analyzing structural changes of Fe-N-C cathode catalysts in pem fuel cell by mossbauer spectroscopy of complete membrane electrode assemblies. J. Phys. Chem. Lett. 5, 3750–3756 (2014). \n20.\tGoellner, V. et al. Degradation of Fe/N/C catalysts upon high polarization in acid medium. Phys. Chem. Chem. Phys. 16, 18454–18462 (2014). \n21.\tWalling, C. Fenton’s reagent revisited. Acc. Chem. Res. 8, 125–131 (1975). \n22.\tWang, X. X. et al. Nitrogen-coordinated single cobalt atom catalysts for oxygen reduction in proton exchange membrane fuel cells. Adv. Mater. 30, 1706758 (2018). Co and Ni) in magnetite on its catalytic activity in heterogeneous fenton and UV/Fenton reaction: from the perspective of hydroxyl radical generation. Appl. Catal. B 150–151, 612–618 (2014). \n24.\tWu, G. et al. Synthesis–structure–performance correlation for polyaniline– Me–C non-precious metal cathode catalysts for oxygen reduction in fuel cells. J. Mater. Chem. 21, 11392–11405 (2011). \n25.\tGupta, S. et al. Quaternary FeCoNiMn-based nanocarbon electrocatalysts for bifunctional oxygen reduction and evolution: promotional role of Mn doping in stabilizing carbon. ACS Catal. 7, 8386–8393 (2017). \n26.\tWang, X. et al. Size-controlled large-diameter and few-walled carbon nanotube catalysts for oxygen reduction. Nanoscale 7, \n20290–20298 (2015). \n27.\tZhang, H., Osgood, H., Xie, X., Shao, Y. & Wu, G. Engineering nanostructures of PGM-free oxygen-reduction catalysts using metal–organic frameworks. Nano Energy 31, 331–350 (2017). \n28.\t Pan, F. et al. Unveiling active sites of $\\mathrm{CO}_{2}$ reduction on nitrogencoordinated and atomically dispersed iron and cobalt catalysts. ACS Catal. 8, \n3116–3122 (2018). \n29.\tWang, X. X. et al. Ordered $\\mathrm{Pt}_{3}\\mathrm{Co}$ intermetallic nanoparticles derived from metal–organic frameworks for oxygen reduction. Nano. Lett. 18, 4163–4171 (2018). \n30.\tQiao, Z. et al. 3D polymer hydrogel for high-performance atomic iron-rich catalysts for oxygen reduction in acidic media. Appl. Catal. B 219, 629–639 (2017). \n31.\tGupta, S. et al. Engineering favorable morphology and structure of Fe-N-C oxygen-reduction catalysts through tuning of nitrogen/carbon precursors. ChemSusChem 10, 774–785 (2017). \n32.\tWang, H., Zhu, Q.-L., Zou, R. & Xu, Q. Metal-organic frameworks for energy applications. Chem 2, 52–80 (2017). \n33.\tChen, Y. et al. Isolated single iron atoms anchored on N-doped porous carbon as an efficient electrocatalyst for the oxygen reduction reaction. Angew. Chem. Int. Ed. 56, 6937–6941 (2017). \n34.\tZhang, H. et al. Single atomic iron catalysts for oxygen reduction in acidic media: particle size control and thermal activation. J. Am. Chem. Soc. 139, \n14143–14149 (2017). \n35.\tXia, B. Y. et al. A metal–organic framework-derived bifunctional oxygen electrocatalyst. Nat. Energy 1, 15006 (2016). \n36.\tYang, L., Zeng, X., Wang, W. & Cao, D. Recent progress in MOF-derived, heteroatom-doped porous carbons as highly efficient electrocatalysts for oxygen reduction reaction in fuel cells. Adv. Func. Mater. 28, \n1704537 (2018). \n37.\tFeng, Z. et al. Atomic-scale cation dynamics in a monolayer $\\mathrm{VO}_{x}/\\upalpha\\mathrm{-Fe}_{2}\\mathrm{O}_{3}$ catalyst. RSC Adv. 5, 103834–103840 (2015). \n38.\tWeng, Z. et al. Active sites of copper-complex catalytic materials for electrochemical carbon dioxide reduction. Nat. Commun. 9, 415 (2018). \n39.\tLiu, Z. et al. Tuning the electronic environment of zinc ions with a ligand for dendrite-free zinc deposition in an ionic liquid. Phys. Chem. Chem. Phys. 19, \n25989–25995 (2017). \n40.\tChen, Y. Z. et al. From bimetallic metal–organic framework to porous carbon: high surface area and multicomponent active dopants for excellent electrocatalysis. Adv. Mater. 27, 5010–5016 (2015). \n41.\tLai, Q. et al. Metal–organic-framework-derived Fe-N/C electrocatalyst with five-coordinated Fe- $\\cdot\\mathrm{N}_{x}$ sites for advanced oxygen reduction in acid media. ACS Catal. 7, 1655–1663 (2017). \n42.\tWang, Q. et al. Phenylenediamine-based $\\mathrm{FeN}_{x}/\\mathrm{C}$ catalyst with high activity for oxygen reduction in acid medium and its active-site probing. J. Am. Chem. Soc. 136, 10882–10885 (2014). \n43.\tSahraie, N. R. et al. Quantifying the density and utilization of active sites in non-precious metal oxygen electroreduction catalysts. Nat. Commun. 6, \n8618 (2015). \n44.\tLi, Y. et al. An oxygen reduction electrocatalyst based on carbon nanotubegraphene complexes. Nat. Nanotech. 7, 394–400 (2012). \n45.\tWu, G. et al. Titanium dioxide-supported non-precious metal oxygen reduction electrocatalyst. Chem. Commun. 46, 7489–7491 (2010). \n46.\tHerranz, J. et al. Unveiling N-protonation and anion-binding effects on Fe/N/C-catalysts for $\\mathrm{O}_{2}$ reduction in pem fuel cells. J Phys. Chem. C 115, \n16087–16097 (2011). \n47.\tNorskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n48.\tKulkarni, A., Siahrostami, S., Patel, A. & Norskov, J. K. Understanding catalytic activity trends in the oxygen reduction reaction. Chem. Rev. 118, \n2302–2312 (2018). \n49.\tHenkelman, G., Uberuaga, B. P. & Jónsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000). \n50.\tZhang, C., Zhang, W. & Zheng, W. Pinpointing single metal atom anchoring sites in carbon for oxygen reduction: Doping sites or defects? Chin. J. Catal. \n39, 4–7 (2018). \n\n# Acknowledgements \n\nG.Wu thanks the Research and Education in eNergy, Environment and Water (RENEW) program at the University at Buffalo, SUNY and National Science Foundation (CBET1604392, 1804326) for partial financial support. G.Wu, G.Wang and H.X. acknowledge support from the US Department of Energy (DOE), Energy Efficiency and Renewable Energy, Fuel Cell Technologies Office (DE-EE0008075). Electron microscopy research was conducted at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences of (D.A.C. and K.L.M) and the Center for Functional Nanomaterials at Brookhaven National Laboratory (S.H. and D.S., under contract No. DE-SC0012704), which both are US DOE Office of Science User Facilities. XAS measurements were performed at beamline 9-BM at the Advanced Photon Source, a User Facility operated for the US DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357 (Z.F. and G.E.S.). Z.W. and J.L. thank the National Natural Science Foundation of China (Grant No. 21273058 and 21673064) for support. \n\n# Author contributions \n\nG.Wu, Z.W. and J. L. designed the experiments, analysed the experimental data, and wrote the manuscript. J.L., M.C. and H.Z. synthesized catalyst samples and carried out electrochemical measurements. D.A.C., K.L.M, S.H. and D.S performed electron microscopy analyses and data interpretation. S.K. conducted XPS analysis. M.W., M.L., G.E.S. and Z.F. recorded and analysed XAS data. C.L. and H.X. carried out fuel cell tests. B.L., K.L. and G.Wang conducted computational studies. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-018-0164-8. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to Z.W. or G.W. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2018 " + }, + { + "id": "10.1038_s41467-018-04949-4", + "DOI": "10.1038/s41467-018-04949-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-04949-4", + "Relative Dir Path": "mds/10.1038_s41467-018-04949-4", + "Article Title": "Polyaniline-intercalated manganese dioxide nullolayers as a high-performance cathode material for an aqueous zinc-ion battery", + "Authors": "Huang, JH; Wang, Z; Hou, MY; Dong, XL; Liu, Y; Wang, YG; Xia, YY", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Rechargeable zinc-manganese dioxide batteries that use mild aqueous electrolytes are attracting extensive attention due to high energy density and environmental friendliness. Unfortunately, manganese dioxide suffers from substantial phase changes (e.g., from initial alpha-, beta-, or gamma-phase to a layered structure and subsequent structural collapse) during cycling, leading to very poor stability at high charge/discharge depth. Herein, cyclability is improved by the design of a polyaniline-intercalated layered manganese dioxide, in which the polymerstrengthened layered structure and nulloscale size of manganese dioxide serves to eliminate phase changes and facilitate charge storage. Accordingly, an unprecedented stability of 200 cycles with at a high capacity of 280 mA h g(-1) (i.e., 90% utilization of the theoretical capacity of manganese dioxide) is achieved, as well as a long-term stability of 5000 cycles at a utilization of 40%. The encouraging performance sheds light on the design of advanced cathodes for aqueous zinc-ion batteries.", + "Times Cited, WoS Core": 1198, + "Times Cited, All Databases": 1253, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000439687600004", + "Markdown": "# Polyaniline-intercalated manganese dioxide nanolayers as a high-performance cathode material for an aqueous zinc-ion battery \n\nJianhang Huang1,2, Zhuo Wang1, Mengyan Hou1, Xiaoli Dong1, Yao Liu1, Yonggang Wang 1 & Yongyao Xia1 \n\nRechargeable zinc–manganese dioxide batteries that use mild aqueous electrolytes are attracting extensive attention due to high energy density and environmental friendliness. Unfortunately, manganese dioxide suffers from substantial phase changes (e.g., from initial α-, $\\upbeta$ -, or $\\gamma$ -phase to a layered structure and subsequent structural collapse) during cycling, leading to very poor stability at high charge/discharge depth. Herein, cyclability is improved by the design of a polyaniline-intercalated layered manganese dioxide, in which the polymerstrengthened layered structure and nanoscale size of manganese dioxide serves to eliminate phase changes and facilitate charge storage. Accordingly, an unprecedented stability of 200 cycles with at a high capacity of $280\\mathsf{m A}\\mathsf{h g}^{-1}$ (i.e., $90\\%$ utilization of the theoretical capacity of manganese dioxide) is achieved, as well as a long-term stability of 5000 cycles at a utilization of $40\\%$ . The encouraging performance sheds light on the design of advanced cathodes for aqueous zinc-ion batteries. \n\nn light of pressing concerns regarding environmental pollution and climatic deterioration associated with the combustion of fossil fuels, building a low-carbon society that is based on renewable energy sources has gained widespread attention. However, the utilization of renewable energy sources such as wind and solar requires a safe, green, economic, and efficient electrochemical energy conversion system that can accommodate/ smoothen the intermittency of renewable power1–4. As a result, aqueous ${\\mathrm{Li}}^{+}$ (or $\\mathrm{Na}^{+}$ ) batteries are attracting extensive attention due to safety and environmentally friendliness that arise from the use of mild aqueous electrolytes containing ${\\mathrm{Li}}^{+}$ (or $\\mathrm{Na}^{+})^{5-16}$ . Unfortunately, electrode materials for ${\\mathrm{Li}}^{+}$ (or $\\mathrm{Na^{+}}$ ) storage in aqueous electrolytes generally suffer from low capacity $(<150$ mA $\\cdot\\ln{\\mathrm{g}^{-1}})^{5-16}$ , which should be remedied with large-scale energy storage. In such situations, the electrode materials for $Z\\mathrm{n}^{2+}$ storage in mild aqueous electrolytes have entered researchers’ spotlight. For example, copper hexacyanoferrate17,18, V2O53,19,20, and $\\breve{\\mathrm{MnO}_{2}}^{21-25}$ have been recently reported for $Z\\mathrm n^{2+}$ storage. Among these materials, $\\mathrm{MnO}_{2}$ attracts much attention because of its high theoretical capacity $(308\\mathrm{\\mAh\\g^{-1}})\\$ ), low cost, and low toxicity23–25. As the most widespread primary battery, $\\mathrm{Zn}{-}\\mathrm{Mn}\\mathrm{O}_{2}$ alkaline battery has been commercialized for a very long time. However, the development of rechargeable $\\mathrm{Zn}{-}\\mathrm{Mn}\\mathrm{O}_{2}^{\\cdot}$ battery was dramatically hindered by the poor reversibility of $\\mathrm{MnO}_{2}$ in alkaline electrolyte26,27. \n\nRecently, the reversible $Z\\mathrm{n}^{2+}$ and/or $\\mathrm{H^{+}}$ insertion into a $\\mathrm{MnO}_{2}$ host in a mild aqueous electrolyte was demonstrated21–25, triggering enthusiasm for the development of a rechargeable $\\mathrm{Zn}{-}\\mathrm{Mn}\\mathrm{O}_{2}$ battery using a mild aqueous electrolyte. Various manganese dioxide phases, including α-MnO222,23,28–31, β-MnO224, $\\gamma{-}\\mathrm{MnO}_{2}{}^{32}$ , ${\\delta\\mathrm{-}}\\mathrm{Mn}{\\mathrm{O}_{2}}^{33}$ , spinel-type MnO234, and other types35–37, have been reported as host materials for $\\mathrm{Zn}^{2+}/\\mathrm{H}^{+}$ insertion in a mild aqueous electrolyte. However, no matter what the original architecture is, the $\\mathrm{MnO}_{2}$ hosts suffer serious structural transformation during cycling processes and transform into layered manganese oxide phases with interlaminar water molecules24,31,32 (Supplementary Fig. 1). The formation of the layered structure should be attributable to manganese dissolution and the insertion of hydrated $Z\\mathrm{n}^{2+}$ (i.e., $[\\mathrm{Zn}(\\mathrm{H}_{2}\\mathrm{O})_{6}]^{2+})$ and $\\mathrm{H^{+}}$ (i.e., $\\mathrm{H}_{3}\\mathrm{O}^{+},$ ) (see Supplementary Fig. 1 and Supplementary Note 1). With coordinated water molecules, the strong electrostatic repulsion between $Z\\mathrm{n}^{2+}$ (or $\\mathrm{H^{+}}$ ) and the host material can be diminished effectively19,31. That is to say, theoretically, that the layered structure with $1\\times\\infty$ tunnels and extended interlayer spacing are advantageous for the storage of guest-hydrated cations. However, during the phasechange process (i.e., from α-, $\\beta\\cdot,\\gamma$ -phase to layered structure with interlaminar water), large volumetric change leads to significant capacity fading24. In addition, with the insertion of a large amount of hydrated cations, the layered structure of manganese oxide will collapse during the charge/discharge process33,35, which aggravates capacity fading. As a result, when cycled with high charge/discharge depth, the $\\mathrm{MnO}_{2}$ electrode generally exhibits very poor stability. $\\mathrm{Up}$ to the present, the stable cycling of a $\\mathrm{MnO}_{2}$ electrode with the utilization of $590\\%$ $({\\sim}277\\ \\mathrm{{mA}h\\breve{g}^{-1}=}$ $308\\mathrm{mA}$ h $\\mathbf{g}^{-1}\\times90\\%)$ has never been reported, to the best of our knowledge. Currently, the best reported cycle life of $\\mathrm{MnO}_{2}$ in a mild aqueous electrolyte with high utilization of $84\\%$ ${\\sim}260\\operatorname{mAh}$ $\\mathbf{g}^{-1}.$ ) is 45 cycles, which was achieved by Liu’s group23. Very recently, Chen et al. demonstrated an improvement to 150 cycles with a lower utilization of $75\\%$ $({\\sim}230\\dot{\\mathrm{mAhg}}^{-1})^{24}$ . Although there are some reports about high stability (more than 5000 cycles) of a $\\mathrm{MnO}_{2}$ cathode in a mild aqueous electrolyte, excellent stability has been achieved with very low utilization of the theoretical capacity for $\\mathrm{MnO}_{2}$ $(<30\\%)^{23,25}$ . Therefore, it is still a great challenge to efficiently utilize the high capacity of a $\\mathrm{MnO}_{2}$ cathode in a mild aqueous electrolyte. \n\nAs mentioned above, the capacity fading of a $\\mathrm{MnO}_{2}$ cathode arises from both the phase transformation and the instability of $_\\mathrm{H}_{2}\\mathrm{O}$ -intercalated layered structure. Directly using the layered $\\mathrm{MnO}_{2}$ as an electrode material, which can avoid phase transformations while intercalating a guest polymer into $\\mathrm{MnO}_{2}$ , to strengthen the extended layered structure is a promising solution. Here we prepare the polyaniline (PANI)-intercalated $\\mathrm{MnO}_{2}$ nanolayers through an interface reaction. The nanoscale size of the layered $\\mathrm{MnO}_{2}^{\\cdot}$ and the guest polymer in the interlayer efficiently facilitates the charge storage and strengthen the extended layered structure, and thus as-prepared PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers exhibit high-rate capability and a long cycling life. Even with a high utilization of $90\\%$ $(\\sim\\mathrm{\\dot{2}80}\\mathrm{mAhg^{-1}}.$ , the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers still display a very stable cycling performance, which is superior to previous reports. Furthermore, a detailed investigation is performed to clarify the co-insertion mechanism of $Z\\mathrm{n}^{\\mathrm{2+}}$ and $\\dot{\\mathrm{H^{+}}}$ . \n\n# Results \n\nStructural characterization. The PANI-intercalated $\\mathrm{MnO}_{2}$ is prepared by a simple one-step inorganic/organic interface reaction (Fig. 1a), which was developed by our group38. At the interface of the organic phase (i.e., $\\mathrm{CCl}_{4}$ -containing aniline monomer) and the inorganic phase (i.e., $\\mathrm{KMnO}_{4}$ aqueous solution), the chemical oxidation polymerization of aniline and the reduction of $\\mathrm{MnO}_{4}^{2-}$ occur simultaneously, facilitating the layerby-layer assembly of the layered manganese dioxide and polyaniline (Fig. 1a). Furthermore, the diffusion of aniline from the organic phase to the inorganic phase and the production of PANI restrict the growth of $\\mathrm{MnO}_{2}$ to two dimensions. Finally, the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers gather together to form a mesoporous structure. Figure 1b presents the scanning electron microscopy (SEM) image of the as-prepared sample, showing a grainy morphology that comprises aggregates of primary particles. Examination of transmission electron microscopy (TEM) data shown in Fig. 1c indicates that the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite exhibits a spongiform structure. The diffraction rings obtained from selected-area electron diffraction (SAED) analysis (inset of Fig. 1c) indicate polycrystalline character of the sample. The high-resolution transmission electron microscopy (HR-TEM) image (Fig. 1d) reveals that the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers possess a typical size around $10\\mathrm{nm}$ and a distinct mesoporous structure, and the $\\mathrm{MnO}_{2}$ nanolayers show an expanded interlayer space $(\\sim1.0\\:\\mathrm{nm})$ . The mesoporous structure is further supported by an obvious hysteresis loop in the nitrogen adsorption–desorption isotherms (Supplementary Fig. 2a), which indicate a large surface area of $277\\dot{\\mathrm{m}^{2}}\\mathrm{g^{-1}}$ and a pore size that is mainly centered at $4\\mathrm{nm}$ (Supplementary Fig. 2b). It should be noted that the layered structure of the $\\mathrm{MnO}_{2}$ is not very apparent in Fig. 1d because of the shielding of PANI. In order to clarify this point, the PANI-intercalated $\\mathrm{MnO}_{2}$ composite was heat treated at $400^{\\circ}\\mathrm{C}$ in air for several minutes to obtain a clear view of the intercalated structure (Fig. 1e). After heat treatment to partially remove the shielding of PANI, the expanded interlayer space can be clearly detected in Fig. 1e. Certainly, the result of Fig. 1e also demonstrates that heat treatment at $400^{\\circ}\\mathrm{C}$ did not destroy the expanded layer structure, indicating a good structure stability of the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers. The PANI in the composite was characterized with Fourier transform infrared (FT-IR) spectroscopy (Supplementary Fig. 3), and the weight percentage of PANI $(5\\mathrm{wt\\%})$ was determined with thermogravimetric (TG) analysis (Supplementary Fig. 4). The broad peaks in the powder X-ray diffraction (XRD) pattern of the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite could be indexed to layered birnessite $\\mathrm{MnO}_{2}$ (JCPDS \n\n![](images/d4422224cac7f0f62df67202867521430125be80c6f96876b54205a8b7f269a7.jpg) \nFig. 1 Preparation and characterization of the polyaniline-intercalated $\\mathsf{M n O}_{2}$ nanolayers. a Schematic illustration of expanded intercalated structure of polyaniline (PANI)-intercalated $\\mathsf{M n O}_{2}$ nanolayers. b Scanning electron microscopy image, c transmission electron microscopy (TEM) image (the inset shows the corresponding selected-area electron diffraction image), and d high-resolution (HR)-TEM image of the PANI-intercalated $\\mathsf{M n O}_{2}$ nanolayers. The red dashed outlines are used to clarify the morphology profile and particle size of the $\\mathsf{M n O}_{2}$ nanolayers. e HR-TEM image of the PANI-intercalated $\\mathsf{M n O}_{2}$ nanolayers with heat treatment at $400^{\\circ}\\mathsf C$ to remove the shield of PANI. Scale bars, b $1\\upmu\\mathrm{m}$ ; $\\mathfrak{c}500\\mathsf{n m}$ , and d, e $10\\mathsf{n m}$ , respectively \n\n13–0105), as shown in Supplementary Fig. 5. X-ray photoelectron spectroscopy (XPS) (Supplementary Fig. 6) shows a spin-energy separation of $4.81\\mathrm{eV}$ for the Mn 3 s doublet in the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers, indicating $\\mathord{\\sim}4.0$ charge state of Mn in the composite39,40. \n\nElectrochemical characterization. The electrochemical profile of the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite is characterized by the typical coin-type cell, which is composed of a PANIintercalated $\\mathrm{MnO}_{2}$ composite cathode, a Zn foil anode, and an aqueous electrolyte $(2\\mathrm{M}\\mathrm{ZnSO_{4}}+0.1\\mathrm{M}\\mathrm{MnSO_{4}})$ adsorbed with a glass fiber separator. According to Liu’s report23, the presence of 0.1 M $\\mathrm{MnSO_{4}^{-}}$ could inhibit the dissolution of $\\mathrm{Mn}^{2+}$ (from $\\mathrm{Mn}^{3+}$ disproportionation) into the electrolyte. Furthermore, the presence of $\\mathrm{\\hat{M}n}^{2+}$ can improve the $Z\\mathrm{n}$ -platting/stripping efficiency (Supplementary Fig. 7). Figure 2a shows the cyclic voltammetry (CV) data for the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite. There is an obvious cathodic peak around $1.23\\mathrm{V}$ during the first cathodic sweep, while the corresponding anode peak appears around $1.56\\mathrm{V}$ during the anodic sweep. In the following cycles, the strengths of the redox peaks mentioned above gradually decrease; meanwhile, one new pair of redox peaks emerge around 1.38 and $1.60\\mathrm{V}$ . The two-step charge storage should be attributed to the different insertion mechanism of $\\mathrm{H^{+}}$ and/or $Z\\mathrm{n}^{2+}$ during the discharge process, which will be further clarified in the mechanism investigation. The galvanostatic charge/discharge profile of the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers composite is shown in Fig. 2b, where the applied current density and the achieved capacity are calculated by mass loading of PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite in the cathode (i.e., $2\\mathrm{mg}\\mathrm{cm}^{-2}$ with an electrode area of $1{\\dot{\\mathrm{cm}}}^{-2}$ ). When tested at the low current of $50\\mathrm{mAg}^{-1}$ (0.16 C), the cell exhibits initial discharge capacity of $260\\mathrm{mA}\\mathrm{h}\\mathbf{\\bar{g}}^{-1}$ , involving a slope discharge profile from 1.5 to $1.33\\mathrm{V}$ $(\\sim50\\mathrm{mA}\\mathrm{\\bar{h}}\\mathrm{g}^{-1}$ capacity) and a consequent discharge platform about $1.36\\mathrm{V}$ $(\\sim\\dot{2}10\\dot{\\mathrm{mA}}\\mathrm{hg}^{-1}$ capacity). In the subsequent cycle, the discharge capacity is increased to $298\\mathrm{mAhg^{-1}}^{\\mathrm{\\prime}}$ which is close to the theoretical capacity of $308\\mathrm{mAhg^{-1}}$ (based on single electron transfer between $\\mathrm{Mn^{4+}}$ and $\\scriptstyle{\\dot{\\mathrm{Mn}}}^{3+}$ ). Figure 2c presents the rate performance tested at different current densities, and corresponding cycle profile is given in Fig. 2d. As shown in Fig. 2c, d, the cell exhibits a reversible discharge capacity of $280\\mathrm{mAhg^{-1}}$ at the current density of $200\\mathrm{mAg^{-1}}$ , which is very close to that achieved at the low current density of $50\\mathrm{mAg^{-1}}$ . Even at the high current density of $3000\\mathrm{mAg^{-1}}$ , the cell still can deliver a capacity of $110\\mathrm{mAh}\\dot{\\mathrm{g}}^{-1}$ , which is to the best of our knowledge among the best rate performances reported to date in this field23–25. It should be noted that the two discharge plateaus evolve to a single one at the high rate, which should be attributable to $\\mathrm{H^{+}}$ insertion that dominates the discharge process at high rate. This phenomenon can be explained by the faster $\\mathrm{H^{+}}$ insertion than $\\dot{Z}\\mathrm{n}^{2+}$ insertion, which will be confirmed by the later electrochemical impedance measurements. Cycle stability of the PANI-intercalated $\\mathrm{MnO}_{2}$ composite was evaluated at the current densities of 200 and \n\n![](images/ab0c46d2f7c740ad839a755844fb5d7e31097ff5343b9a578aea823d8062b3bf.jpg) \nFig. 2 Electrochemical performance of polyaniline-intercalated $\\boldsymbol{\\M}\\boldsymbol{\\mathsf{n O}}_{2}$ nanolayers. a Cyclic voltammetry curves of the coin-type cell (Zn/polyaniline (PANI)- intercalated $\\begin{array}{r}{{M}{\\mathsf{n}}{\\mathsf{O}}_{2};}\\end{array}$ ) using 2 M $Z n S O_{4}+0.1$ M $\\ensuremath{M n}\\ensuremath{\\mathrm{SO_{4}}}$ aqueous electrolyte at $0.1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . b Typical galvanostatic charge/discharge curves at $50\\mathrm{mAg}^{-1}$ between 1.0 and $1.8\\lor$ of the cell. c, d Rate performance and charge/discharge profiles of the cell tested with the charge/discharge current densities varying from 200 to $3000\\mathsf{m A g}^{-1}$ . e Cycling performance in terms of specific capacity (red) and the corresponding coulombic efficiency (blue) at a current density of $200\\mathsf{m A g}^{-1}$ \n\n$2000\\mathrm{mAg^{-1}}$ . From Fig. 2e, it can be seen that PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite delivers $280\\mathrm{mAhg^{-1}}$ capacity for 200 cycles with coulombic efficiency around $100\\%$ , in which an ultra-high utilization of more than $90\\%$ (based on theoretical capacity of $308\\mathrm{mAhg^{-1}}$ of $\\mathrm{MnO}_{2}^{\\cdot}$ ) is obtained. To the best of our knowledge, it is the highest utilization that can be stable for 200 cycles in an aqueous zinc-ion battery (see Supplementary Table 1 for detailed information). The charge/discharge curves at different cycles are shown in Supplementary Fig. 8 to clarify the potential evolution during the cycling test, where a slight potential evolution over 200 cycles can be detected. When tested at the high current density of $2000\\mathrm{mAg^{-1}}$ , the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers composite present a stable discharge capacity of around $\\mathrm{{\\dot{1}}25\\mathrm{mA}\\mathrm{h}^{\\circ}g^{-1}}$ (up to $40\\%$ utilization) over 5000 cycles (Supplementary Fig. 9). The stable cycle life of 5000 cycles with the utilization of $40\\%$ is superior to previous reports (see Supplementary Table 2 for detailed information). The superior performance is largely attributable to the reinforcement of the layered structure with intercalated PANI, which avoids phase transformation and collapse of the layered structure during repeated insertion/extraction of hydrated cations. Simultaneously, the presence of $\\mathrm{Mn}^{2+}$ in the electrolyte also alleviates the $\\mathrm{Mn}^{2+}$ dissolution-induced capacity fading23,24. \n\nTo further demonstrate the function of the PANI-reinforced layered structure, the cycling performance of the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers composite was also investigated using the $\\mathrm{ZnSO_{4}}$ electrolyte without $\\mathrm{Mn}^{2+}$ (Supplementary Fig. 10), and the corresponding result was compared with previous reports about $\\mathrm{MnO}_{2}$ cycled in the electrolyte without $\\mathrm{\\dot{M}n}^{2+}$ (see Supplementary Table 3). On the other hand, it should be noted that the high cycle performance shown in Fig. 2e or Supplementary Fig. 9 is achieved by using excess $Z\\mathrm{n}$ -anode (see Method section). The purpose is to exclude the effect of $Z\\mathrm{n}$ -anode fading, which is similar with previous reports about $\\mathrm{MnO}_{2}$ cathode22–36. SEM images of the cycled Zn electrode and PANIintercalated $\\mathrm{MnO}_{2}$ electrode are given in Supplementary Fig. 11 and Supplementary Fig. 12, respectively. In practical application, the issue of $Z\\mathrm{n}$ -anode is another obstacle for $Z\\mathrm{n}$ -ion batteries. The modification of an electrode developed by La Mantia et $\\mathrm{\\al^{41}}$ . and the electrolyte optimization reported by Chen’s group42 may be the potential solutions to improve the stability of $Z\\mathrm{n}$ -anode. \n\nReaction mechanism. Until now, two reaction mechanisms for a manganese dioxide cathode, involving $Z\\mathrm{n}^{2+}$ and $\\mathrm{H^{+}}$ insertion/ extraction, respectively, have been reported23–25,31. Due to various crystallographic polymorphs of manganese dioxide, the reaction mechanism during cycling in neutral aqueous electrolytes remains a topic of discussion. Here the insertion mechanism was investigated to better understand the electrochemical reaction during cycling. Ex situ XRD analysis of the PANI-intercalated $\\mathrm{MnO}_{2}$ electrode in $2\\mathrm{M}\\mathrm{\\ZnSO_{4}}+\\mathrm{0.1\\M\\MnSO_{4}}$ electrolyte was conducted during the charge/discharge cycle within the potential window of $1.0{-}1.8\\mathrm{V}$ at a current density of $50\\mathrm{mAg^{-1}}^{\\mathbf{\\mathrm{.}}}$ (Fig. 3a and Supplementary Fig. 13). During the first discharge platform (Region I, red color), only two sets of peaks (related to polytetrafluoroethylene (PTFE) binder at $18^{\\circ}$ and Ti current collector at $38.4^{\\circ}$ and $40.2\\ensuremath{^\\circ})$ could be clearly observed, and there is no obvious variation throughout Region I. However, from the beginning of the second discharge platform (Region II, blue color), some new peaks arise, including a very strong peak at $8.1^{\\circ}$ and obvious peaks at $16.2^{\\circ}$ and $24.4^{\\circ}2^{\\circ}\\theta.$ . During the subsequence charge process, the strength of arisen peaks decreases gradually (Region III, cyan color), and finally recover to the original pattern (Region IV, pink color) which is as same as Region I, indicating a good reversibility of electrode reaction. In order to analyze the evolution more clearly, several selected XRD patterns from Fig. 3a were presented in Fig. 3b. The emerging peaks (including strong peaks at $8.1^{\\circ}$ , $16.2^{\\circ}$ , and $24.4^{\\circ}2\\theta$ and other subtle peaks highlighted with inverted triangles) are indexed to (Zn $\\mathrm{(\\bar{O}H)_{2})_{3}(Z n S O_{4})(H_{2}O)_{5}}$ (zinc hydroxide sulfate hydrate, JCPDS: $78\\mathrm{-}0246)^{23}$ . The formation of zinc hydroxide sulfate is in consistence with Liu et al.’s report23. With the consumption of $\\mathrm{H^{+}}$ in the electrolyte, the increasing amount of $\\mathrm{OH^{-}}$ leads to the formation of zinc hydroxide sulfate hydrate. SEM is further conducted to monitor the morphologic evolution of the PANIintercalated $\\mathrm{MnO}_{2}$ electrode (Fig. 3c–h). For Region I, there is no obvious change on the electrode surface, but in the Region II, increasingly large flakes emerge with discharging and gradually vanish during subsequent charging. The highly reversible morphologic transformation during the charge/discharge process is well consistent with the evolution observed in XRD patterns. Energy-dispersive spectroscopy (EDS) analysis shows that the flake-like product contains abundant Zn and S, but no evident \n\n![](images/3abaa77af11cac9029d4227dd506a7db0aaf93d067e28c481a543858f5f2c6ad.jpg) \nFig. 3 Structure evolution of polyaniline-intercalated $\\mathsf{M n O}_{2}$ electrode during cycling. a Evolution of ex situ $\\mathsf{X}$ -ray powder diffraction (XRD) patterns during the charge/discharge process (the vertical bars denoted with consecutive numbers indicate the locations where the XRD patterns were recorded). b Selected ex situ XRD patterns from a (corresponding to the XRD patterns denoted with 3, 10, 13, and 19 in a), which represent the typical XRD pattern in each corresponding charge/discharge region. c–h Scanning electron microscopy (SEM) images for morphologic evolution of electrode during cycling (the SEM images were taken at the locations indicated by vertical bars 3, 5, 10, 12, 16, and 20 in a, respectively). Scale bars, c–h $10\\upmu\\mathrm{m}$ , respectively (the magnification is the same for images $\\mathbf{c-h}$ ) \n\nMn, which supports that the large flakes are zinc hydroxide sulfate hydrate (Supplementary Fig. 14), as indexed in the XRD patterns. \n\nAs demonstrated by the above observation, the electrochemical reaction of the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite definitely involved $\\mathrm{H^{+}}$ insertion, which supports the conclusion by Liu et al23. However, it does not preclude $\\dot{Z}\\dot{\\mathrm{n}}^{2+}$ insertion during the discharge process. We presume that besides $\\mathrm{H^{+}}$ insertion, $\\breve{Z}\\mathrm{n}^{2+}$ insertion plays an important role in the discharge process because the two discharge platforms cannot be satisfactorily explained by only $\\mathrm{H^{+}}$ insertion. Therefore, further investigation was performed to clarify this point. Figure 4a shows the discharge curves of the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers composite in different electrolytes (red curve: 2 M $\\mathrm{ZnSO_{4}+0.1}$ M $\\mathrm{{\\calMnSO}_{4}}.$ , blue curve: $0.1\\mathrm{{M}}$ $\\mathrm{MnSO_{4}},$ . As we know, PANI-intercalated $\\mathrm{MnO}_{2}$ exhibits two discharge platforms in $2\\mathrm{M}\\mathrm{ZnSO_{4}}+0.1\\mathrm{M}\\mathrm{MnSO_{4}}$ electrolyte (red curve). However, when $Z\\mathrm{n}^{2+}$ was eliminated, a single-slope discharge profile was observed for the $0.1\\mathrm{M}\\mathrm{MnSO_{4}}$ electrolyte (blue curve). From this result, we preliminarily conclude that the second discharge platform is related to $Z n^{2+}$ insertion. Raman spectra (Fig. 4b) are used to further characterize $Z\\mathrm{n}^{2+}$ insertion/ extraction during charge/discharge states. A band of around $650\\mathrm{cm}^{-1}$ can be observed throughout the whole charge/discharge process, which is attributed to the symmetric stretching vibration $\\bar{(\\mathrm{Mn-O})}$ of the $\\mathrm{MnO}_{6}$ groups43,44. In addition, a pair of peaks between 300 and $400\\mathrm{{cm}^{\\hat{-}1}}$ that are derived from $_{z\\mathrm{n-O}}$ vibrations45,46 arise after discharge to $1\\mathrm{V}$ and then vanish after consequent charging. This reversible $Z\\mathrm{n-O}$ band demonstrates the insertion/extraction of $Z\\mathrm{n}^{2+}$ in the PANI-intercalated $\\mathrm{MnO}_{2}$ electrode. The conclusion is supported by the observation of $Z\\mathrm{n}$ on the electrode surface with scanning electron microscopy–energy dispersive X-ray spectroscopy (SEM–EDX) analysis after discharge (Supplementary Fig. 15). Moreover, the kinetic behavior during the first and second discharge platform was investigated with electrochemical impedance spectroscopy (EIS, Supplementary Fig. 16), in which the calculated diffusion coefficient in the first discharge platform $(5.84\\times10^{-12}\\mathrm{cm}^{2}s^{-1})$ is much higher than that in the second discharge platform $(7.35\\times10^{-14}\\mathrm{cm}^{2}s^{-1})$ , indicating different insertion ions during the two different discharge platforms. \n\n![](images/8670b5702b88227e6cc5e699c0aaac5f46b86cdd3ef0c38eb2b47b710d128900.jpg) \nFig. 4 Characterization of sequential insertion of $\\mathsf{H}^{+}$ and $Z n^{2+}$ during two discharge platforms. a The discharge profile of polyaniline (PANI)-intercalated $\\mathsf{M n O}_{2}$ electrode at current density of $50\\mathsf{m A g}^{-1}$ in different electrolytes (red curve: 2 M $Z n S O_{4}+0.1$ M $\\ensuremath{\\mathsf{M n S O}}_{4},$ blue curve: 0.1 M $\\pmb{M}\\mathrm{nSO}_{4},$ . b Raman spectra of PANI-intercalated $\\mathsf{M n O}_{2}$ electrode after full discharge and full charge. c High-resolution transmission electron microscopy (HR-TEM) image of the testing electrode after the first discharge platform and the corresponding scanning transmission electron microscopy–energy dispersive spectroscopy (STEM–EDS) mappings for elements like Mn, $Z\\mathsf{n,}$ , and S. d HR-TEM image of the testing electrode after the second discharge platform and the corresponding STEM–EDS mappings for elements like Mn, Zn, and S. Red arrows indicate the PANI-intercalated $\\boldsymbol{\\M}\\boldsymbol{\\mathsf{n O}}_{2}$ nanolayers and cyan arrows indicate the acetylene black in electrode. Scale bars, c, d 10 nm for TEM images and $100\\mathsf{n m}$ for STEM–EDS mapping images \n\nHR-TEM was further employed to gain insight into the structure evolution during the two-stage discharge process. As seen in Fig. 4c, after the first discharge platform, the layered structure with large lattice spacing (see red arrows) is maintained (the cyan arrow indicates the acetylene black in the electrode), and the corresponding scanning transmission electron microscopy–energy dispersive spectroscopy (STEM–EDS) mapping reveals abundant Mn, trace amounts of Zn, and negligible S in the discharge products, indicating $\\mathrm{H^{+}}$ insertion in the initial discharge stage. The layered structure was also preserved well after the second discharge platform (Fig. 4d), but unlike the first discharge platform, zinc is abundant with homogeneous distribution in the PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers according to STEM–EDS mapping, confirming $Z\\mathrm{n}^{2+}$ insertion into the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers. Notably, the layered structure was preserved after the long cycle test (Supplementary Fig. 17), which strongly demonstrates the high stability of PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers. On the contrary, other $\\mathrm{MnO}_{2}$ crystallographic polymorphs suffer severe phase transformation, as reported by previous researchers24,31,32. \n\nBased on the above analysis, we propose a co-insertion mechanism of $\\mathrm{H^{+}}$ and $Z n^{2+}$ in PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers with a self-regulating function in the electrolyte (Fig. 5). In the first stage of discharge, $\\mathrm{H^{+}}$ initially inserts into PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers, leading to a gradual decrease of $\\mathrm{H^{+}}$ concentration in the vicinity of the electrode. During the first discharge platform, the $\\mathrm{OH^{-}}$ concentration is not high enough to form zinc hydroxide sulfate. With sustained decrease of $\\mathrm{H^{+}}$ concentration, the second discharge platform arises, which is caused by a $Z\\mathrm{n}^{2+}$ insertion reaction; meanwhile, the amount of zinc hydroxide sulfate formed on the electrode surface increases. Along with the $Z\\mathrm{n}^{2+}$ insertion, $\\mathrm{H^{+}}$ insertion is ongoing in the second discharge platform, leading to the increased formation of flake-like zinc hydroxide sulfate. Note that this “self-regulation function” consumes superfluous $\\mathrm{OH^{-}}$ , which is beneficial for high cycle stability. On recharge, the released $\\mathrm{H^{+}}$ can lead to the dissolution of the zinc hydroxide sulfate. \n\n![](images/50047b5afb92a2480f1438b68e97a8896768b936571956913c7e7fc861473ebe.jpg) \nFig. 5 Diagram showing the sequential insertion of $\\mathsf{H}^{+}$ and $Z n^{2+}$ . During the first discharge platform, $\\mathsf{H}^{+}$ insertion into polyaniline (PANI)-intercalated $\\mathsf{M n O}_{2}$ nanolayers dominates the electrode reaction, which gradually decreases $\\mathsf{H}^{+}$ concentration around the electrode. With a sustained decrease of $\\mathsf{H}^{+}$ , $Z n^{2+}$ insertion dominates the electrochemical reaction, raising the second discharge platform; meanwhile, the sustained decrease of $\\mathsf{H}^{+}$ concentration leads to the formation of zinc hydroxide sulfate on the electrode surface \n\n# Discussion \n\nIn summary, PANI-intercalated $\\mathrm{MnO}_{2}$ nanolayers were prepared and investigated as the cathode material for a rechargeable $\\mathrm{Zn}{-}\\mathrm{Mn}{\\mathrm{O}}_{2}$ battery using a mild aqueous electrolyte. With the typical nanosize, expanded interlayer space, uniform mesostructure and polymer-reinforced layered structure, the PANIintercalated $\\mathrm{MnO}_{2}$ nanolayers show a promising rate performance and an excellent cycling stability at high charge/discharge depth that is superior to previous reports. It is demonstrated that the PANI-reinforced layered structure combined with the nanoparticle-sized $(\\sim10\\mathrm{nm})$ $\\mathrm{MnO}_{2}$ can efficiently eliminate the hydrated $\\mathrm{H}^{+}/\\mathrm{Zn}^{2+}$ -insertion-induced phase transformation and the subsequent structure collapse, which is of vital significance to obtaining long cycle life along with high capacity utilization. Furthermore, the hydrated $\\mathrm{H}^{+}/\\mathrm{Zn}^{2+}$ co-insertion process in the layered $\\mathrm{MnO}_{2}$ was investigated in detail, and a self-regulating mechanism of electrolyte-involved generation/dissolution of flakelike zinc hydroxide sulfate was clarified. These achievements cast light on the design of more advanced $\\mathrm{MnO}_{2}$ cathode materials for rechargeable $\\mathrm{Zn}{-}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries using mild aqueous electrolytes. \n\n# Methods \n\nMaterial preparation. In a typical synthesis, aniline monomer ${\\mathrm{?~mL}}.$ Aldrich) was dissolved in $\\mathrm{CCl}_{4}$ organic phase $\\mathrm{:450mL,}$ Aldrich) and potassium permanganate ( $\\operatorname{i}.45\\ \\mathbf{g},$ Aldrich) was dissolved in distilled water (450 mL, pH 7). The solution was mixed to obtain an aqueous/organic stratification system with a clear interface. The reaction system was kept at $5^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . The chemical oxidation polymerization of aniline and reduction of potassium permanganate occurred simultaneously at the aqueous/organic interface, which is similar to our previous report38. By continuous diffusion of aniline from the organic phase to the aqueous phase, layer-by-layer self-assembly of layered manganese dioxide and polymer was established, and the final products were obtained after centrifugation and freeze drying. \n\nCharacterization. Powder XRD patterns were collected on a X-ray diffractometer (Bruker D8 Advance, Germany) with Cu Kα radiation $(\\lambda=0.15406\\mathrm{nm})$ ). SEM images and EDX mapping were obtained on Field-emission JEOL JSM-6390 microscope. TEM and EDS mapping were performed on JEOL JEM-2010 microscope. XPS was tested on a Thermo Escalab 250 equipped with a hemispherical analyzer. Raman spectra were obtained on RENISHAW inVia Raman Microscope using $633\\mathrm{nm}$ excitation. T.G. was measured by a STA209 PC (NETZSCH, Germany) analyzer with an $\\mathrm{O}_{2}$ flow. Fourier transform infrared spectroscopy (FT-IR) spectrum was recorded with a NICOLET 6700 FT-IR Spectrometer using KBr pellets. \n\nElectrochemical measurements. Electrochemical measurements were performed with CR2016 coin-type cells. The full cells were assembled using the PANIintercalated $\\mathrm{MnO}_{2}$ composite as the cathode, a zinc metal foil as the anode, a glass fiber as separator, and aqueous $2\\:\\mathrm{M}\\:\\mathrm{ZnSO_{4}}$ with $0.1\\mathrm{M}\\mathrm{MnSO_{4}}$ as electrolyte. The working electrode was fabricated by compressing a mixture of the active materials of PANI-intercalated $\\mathrm{MnO}_{2}$ composite, the conductive material (acetylene black, AB), and the binder (polytetrafluoroethylene, PTFE) in a weight ratio of active materials/A $\\mathrm{.B}/\\mathrm{PTFE}=80{:}10{:}10$ onto a Ti grid at $20\\mathrm{MPa}$ . The areal loading density of PANI-intercalated $\\mathrm{MnO}_{2}$ is $2.0\\mathrm{mg}\\mathrm{cm}^{-\\mathrm{\\tilde{2}}}$ , while the counter electrode (Zinc metal foil) is $20\\mathrm{mg}\\mathrm{cm}^{-2}$ with the purpose of excluding the effect of $Z\\mathrm{n}$ -anode fading. Galvanostatic charge/discharge performances were conducted on a battery test system (Neware BTS 4000). Cyclic voltammetry $(0.1\\mathrm{mV}\\mathrm{s}^{-1}),$ and electrochemical impedance spectroscopy (an AC voltage of $5\\mathrm{mV}$ amplitude) measurements were carried out using an AUTOLAB electrochemical work station (PGSTAT 302N). In order to avoid the conglutination between separator and electrode, the electrochemical tests for SEM, TEM, Raman, and XRD analysis were conducted with a simulated battery composed of a working electrode, counter electrode and electrolyte, but no separator. \n\nData availability. The authors declare that all the relevant data are available within the paper and its Supplementary Information file or from the corresponding author on reasonable request. \n\n# Received: 7 February 2018 Accepted: 25 April 2018 Published online: 25 July 2018 \n\n# References \n\n1. Armand, M. & Tarascon, J. M. Building better batteries. Nature 451, 652–657 (2008). \n2. Goodenough, J. B. Electrochemical energy storage in a sustainable modern society. Energ. Environ. Sci. 7, 14–18 (2014). \n3. Kundu, D., Adams, B. D., Duffort, V., Vajargah, S. H. & Nazar, L. F. A highcapacity and long-life aqueous rechargeable zinc battery using a metal oxide intercalation cathode. Nat. Energy 1, 16119 (2016). \n4. Chu, S. & Majumdar, A. Opportunities and challenges for a sustainable energy future. Nature 488, 294–303 (2012). \n5. Suo, L. M. et al. “Water-in-salt” electrolyte enables high-voltage aqueous lithium-ion chemistries. Science 350, 938–943 (2015). \n6. Luo, J. Y., Cui, W. J., He, P. & Xia, Y. Y. Raising the cycling stability of aqueous lithium-ion batteries by eliminating oxygen in the electrolyte. Nat. Chem. 2, 760–765 (2010). \n7. Pasta, M., Wessells, C. D., Huggins, R. A. & Cui, Y. A high-rate and long cycle life aqueous electrolyte battery for grid-scale energy storage. Nat. Commun. 3, 1149 (2012). \n8. Pasta, M. et al. Full open-framework batteries for stationary energy storage. Nat. Commun. 5, 3007 (2014). \n9. Li, Q., Li, N., Liu, Y., Wang, Y. & Zhou, H. High-safety and low-cost photoassisted chargeable aqueous sodium-ion batteries with $90\\%$ input electric energy savings. Adv. Energy Mater. 6, 1600632 (2016). \n10. Palomares, V. et al. Na-ion batteries, recent advances and present challenges to become low cost energy storage systems. Energ. Environ. Sci. 5, 5884 (2012). \n11. Kim, H. et al. Aqueous rechargeable Li and $\\mathrm{{Na}}$ ion batteries. Chem. Rev. 114, 11788–11827 (2014). \n12. Wang, Y. et al. Ti-substituted tunnel-type $\\mathrm{Na}_{0.44}\\mathrm{MnO}_{2}$ oxide as a negative electrode for aqueous sodium-ion batteries. Nat. Commun. 6, 6401 (2015). \n13. Liang, Y. L. et al. Universal quinone electrodes for long cycle life aqueous rechargeable batteries. Nat. Mater. 16, 841–848 (2017). \n14. Li, Z., Young, D., Xiang, K., Carter, W. C. & Chiang, Y.-M. Towards high power high energy aqueous sodium-ion batteries: the $\\mathrm{NaTi}_{2}(\\mathrm{PO}_{4})_{3}/$ $\\mathrm{Na}_{0.44}\\mathrm{MnO}_{2}$ system. Adv. Energy Mater. 3, 290–294 (2013). \n15. Yan, J. et al. Rechargeable hybrid aqueous batteries. J. Power Sources 216, 222–226 (2012). \n16. Yamada, Y. et al. Hydrate-melt electrolytes for high-energy-density aqueous batteries. Nat. Energy 1, 16129 (2016). \n17. Trocoli, R. & La Mantia, F. An aqueous zinc-ion battery based on copper hexacyanoferrate. ChemSusChem 8, 481–485 (2015). \n18. Canepa, P. et al. Odyssey of multivalent cathode materials: open questions and future challenges. Chem. Rev. 117, 4287–4341 (2017). \n19. Yan, M. et al. Water-lubricated intercalation in $\\mathrm{V}_{2}\\mathrm{O}_{5}{\\cdot}\\mathrm{nH}_{2}\\mathrm{O}$ for high-capacity and high-rate aqueous rechargeable zinc batteries. Adv. Mater. 30, 1703725 (2017). \n20. He, P. et al. High-performance aqueous zinc-ion battery based on layered $\\mathrm{H}_{2}\\mathrm{V}_{3}\\mathrm{O}_{8}$ nanowire cathode. Small 13, 1702551 (2017). \n21. Xu, C., Du, H., Li, B., Kang, F. & Zeng, Y. Reversible insertion properties of zinc ion into manganese dioxide and its application for energy storage. Electrochem. Solid ST 12, A61 (2009). \n22. Xu, C., Li, B., Du, H. & Kang, F. Energetic zinc ion chemistry: the rechargeable zinc ion battery. Angew. Chem. Int. Ed. 51, 933–935 (2012). \n23. Pan, H. L. et al. Reversible aqueous zinc/manganese oxide energy storage from conversion reactions. Nat. Energy 1, 1639 (2016). \n24. Zhang, N. et al. Rechargeable aqueous zinc-manganese dioxide batteries with high energy and power densities. Nat. Commun. 8, 405 (2017). \n25. Sun, W. et al. $\\mathrm{Zn/MnO}_{2}$ battery chemistry with $\\mathrm{H^{+}}$ and $\\mathrm{Zn}^{2+}$ coinsertion. $J.$ Am. Chem. Soc. 139, 9775–9778 (2017). \n26. Ingale, N. D., Gallaway, J. W., Nyce, M., Couzis, A. & Banerjee, S. Rechargeability and economic aspects of alkaline zinc–manganese dioxide cells for electrical storage and load leveling. J. Power Sources 276, 7–18 (2015). \n27. McLarnon, F. R. & Cairns, E. J. The secondary alkaline zinc electrode. J. Electrochem. Soc. 138, 645–656 (1991). \n28. Alfaruqi, M. H. et al. Enhanced reversible divalent zinc storage in a structurally stable $\\mathsf{a}{\\mathrm{-}}\\mathsf{M}\\mathsf{n}\\mathsf{O}_{2}$ nanorod electrode. J. Power Sources 288, 320–327 (2015). \n29. Alfaruqi, M. H. et al. A high surface area tunnel-type $\\mathsf{a}{\\mathrm{-}}\\mathsf{M n O}_{2}$ nanorod cathode by a simple solvent-free synthesis for rechargeable aqueous zinc-ion batteries. Chem. Phys. Lett. 650, 64–68 (2016). \n30. Lee, B. et al. Electrochemically-induced reversible transition from the tunneled to layered polymorphs of manganese dioxide. Sci. Rep. 4, 6066 (2014). \n31. Lee, B. et al. Elucidating the intercalation mechanism of zinc ions into alpha$\\mathrm{MnO}_{2}$ for rechargeable zinc batteries. Chem. Commun. 51, 9265–9268 (2015). \n32. Alfaruqi, M. H. et al. Electrochemically induced structural transformation in a $\\gamma{\\mathrm{-}}\\ensuremath{\\mathrm{MnO}_{2}}$ cathode of a high capacity zinc-ion battery system. Chem. Mater. 27, 3609–3620 (2015). \n33. Alfaruqi, M. H. et al. A layered $\\delta\\mathrm{-}\\mathrm{MnO}_{2}$ nanoflake cathode with high zincstorage capacities for eco-friendly battery applications. Electrochem. Commun. 60, 121–125 (2015). \n34. Zhang, N. et al. Cation-deficient spinel $\\mathrm{ZnMn_{2}O_{4}}$ cathode in $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte for rechargeable aqueous $Z\\mathrm{n}$ -Ion battery. J. Am. Chem. Soc. 138, 12894–12901 (2016). \n35. Wei, C., Xu, C., Li, B., Du, H. & Kang, F. Preparation and characterization of manganese dioxides with nano-sized tunnel structures for zinc ion storage. $J.$ Phys. Chem. Solids 73, 1487–1491 (2012). \n36. Lee, J., Ju, J. B., Cho, W. I., Cho, B. W. & Oh, S. H. Todorokite-type $\\mathrm{MnO}_{2}$ as a zinc-ion intercalating material. Electrochim. Acta 112, 138–143 (2013). \n37. Jiang, B. et al. Manganese sesquioxide as cathode material for multivalent zinc ion battery with high capacity and long cycle life. Electrochim. Acta 229, \n422–428 (2017). \n38. Wang, Y. G. et al. A polyaniline-intercalated layered manganese oxide nanocomposite prepared by an inorganic/organic interface reaction and its high electrochemical performance for Li storage. Adv. Mater. 20, 2166–2170 (2008). \n39. Kalubarme, R. S., Jadhav, H. S. & Park, C. J. Electrochemical characteristics of two-dimensional nano-structured $\\mathrm{MnO}_{2}$ for symmetric supercapacitor. Electrochim. Acta 87, 457–465 (2013). \n40. Chigane, M. & Ishikawa, M. Manganese oxide thin film preparation by potentiostatic electrolyses and electrochromism. J. Electrochem. Soc. 147, \n2246–2251 (2000). \n41. González, M. A., Trócoli, R., Pavlovic, I., Barriga, C. & La Mantia, F. Layered double hydroxides as a suitable substrate to improve the efficiency of Zn anode in neutral pH Zn-ion batteries. Electrochem. Commun. 68, 1–4 (2016). \n42. Sun, K. E. K. et al. Highly sustainable zinc anodes for a rechargeable hybrid aqueous battery. Chem. Eur. J. 24, 1667–1673 (2018). \n43. Hsu, Y. K., Chen, Y. C., Lin, Y. G., Chen, L. C. & Chen, K. H. Reversible phase transformation of $\\mathrm{MnO}_{2}$ nanosheets in an electrochemical capacitor investigated by in situ Raman spectroscopy. Chem. Commun. 47, 1252–1254 (2011). \n44. Polverejan, M., Viliegas, J. C. & Suib, S. L. Higher valency ion substitution into the manganese oxide framework. J. Am. Chem. Soc. 126, 7774–7775 (2004). \n45. Kim, Y. I., Page, K., Limarga, A. M., Clarke, D. R. & Seshadri, R. Evolution of local structures in polycrystalline $\\mathrm{Zn}_{1-x}\\mathrm{Mg}_{x}\\mathrm{O}$ $\\scriptstyle(0\\leq x\\leq0.15)$ studied by Raman spectroscopy and synchrotron $\\mathbf{x}$ -ray pair-distribution-function analysis. Phys. Rev. B 76, 115204 (2007). \n46. Hadzic, B. et al. Raman study of surface optical phonons in hydrothermally obtained ${\\mathrm{ZnO}}({\\mathrm{Mn}})$ nanoparticles. Opt. Mater. 58, 317–322 (2016). \n\n# Acknowledgements \n\nThe authors acknowledge funding support from the National Natural Science Foundation of China (21622303 and 21333002), National Key Research and Development Plan (2016YFB0901500 and 2016YFA0203302). \n\n# Author contributions \n\nY.W. conceived this idea and designed the experiments. Y.W. and Y.X. directed the project. J.H., Y.W. and Z.W. performed the material process and characterization. J.H., M.H., X.D. and Y.L. carried out the electrochemical measurements and data analysis. J.H. and Y.W. co-wrote the paper. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-04949-4. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1016_j.envpol.2018.02.050", + "DOI": "10.1016/j.envpol.2018.02.050", + "DOI Link": "http://dx.doi.org/10.1016/j.envpol.2018.02.050", + "Relative Dir Path": "mds/10.1016_j.envpol.2018.02.050", + "Article Title": "Adsorption of antibiotics on microplastics", + "Authors": "Li, J; Zhang, KN; Zhang, H", + "Source Title": "ENVIRONMENTAL POLLUTION", + "Abstract": "Microplastics and antibiotics are two classes of emerging contaminullts with proposed negative impacts to aqueous ecosystems. Adsorption of antibiotics on microplastics may result in their long-range transport and may cause compound combination effects. In this study, we investigated the adsorption of 5 antibiotics [sulfadiazine (SDZ), amoxicillin (AMX), tetracycline (TC), ciprofloxacin (CIP), and trimethoprim (TMP)] on 5 types of microplastics [polyethylene (PE), polystyrene (PS), polypropylene (PP), polyamide (PA), and polyvinyl chloride (PVC)] in the freshwater and seawater systems. Scanning Electron Microscope (SEM) and X-ray diffractometer (XRD) analysis revealed that microplastics have different surface characterizes and various degrees of crystalline. Adsorption isotherms demonstrated that PA had the strongest adsorption capacity for antibiotics with distribution coefficient (K-d) values ranged from 7.36 +/- 0.257 to 756 +/- 48.0 L kg(-1) in the freshwater system, which can be attributed to its porous structure and hydrogen bonding. Relatively low adsorption capacity was observed on other four microplastics. The adsorption amounts of 5 antibiotics on PS, PE, PP, and PVC decreased in the order of CIP > AMX > TMP > SDZ > TC with K-f correlated positively with octanol-water partition coefficients (Log K-OW). Comparing to freshwater system, adsorption capacity in seawater decreased significantly and no adsorption was observed for CIP and AMX. Our results indicated that commonly observed polyamide particles can serve as a carrier of antibiotics in the aquatic environment. (C) 2018 Elsevier Ltd. All rights reserved.", + "Times Cited, WoS Core": 928, + "Times Cited, All Databases": 1062, + "Publication Year": 2018, + "Research Areas": "Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000431158900047", + "Markdown": "# Adsorption of antibiotics on microplastics\\* \n\nJia Li a, b, Kaina Zhang c, Hua Zhang a, \\* \n\na Key Laboratory of Coastal Environmental Process and Ecology Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai \n264003, China \nb University of Chinese Academy of Sciences, Beijing 100049, China \nc School of Environment and Materials Engineering, YanTai University, Yantai 264003, China \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: \nReceived 31 October 2017 Received in revised form 31 January 2018 \nAccepted 16 February 2018 \nKeywords: \nAntibiotics \nMicroplastics \nAdsorption \nDistribution coefficient \n\nMicroplastics and antibiotics are two classes of emerging contaminants with proposed negative impacts to aqueous ecosystems. Adsorption of antibiotics on microplastics may result in their long-range transport and may cause compound combination effects. In this study, we investigated the adsorption of 5 antibiotics [sulfadiazine (SDZ), amoxicillin (AMX), tetracycline (TC), ciprofloxacin (CIP), and trimethoprim (TMP)] on 5 types of microplastics [polyethylene (PE), polystyrene (PS), polypropylene (PP), polyamide (PA), and polyvinyl chloride (PVC)] in the freshwater and seawater systems. Scanning Electron Microscope (SEM) and $\\mathsf{X}$ -ray diffractometer (XRD) analysis revealed that microplastics have different surface characterizes and various degrees of crystalline. Adsorption isotherms demonstrated that PA had the strongest adsorption capacity for antibiotics with distribution coefficient $(K_{d})$ values ranged from $7.36\\pm0.257$ to $756\\pm48.0\\mathrm{L}\\mathrm{kg}^{-1}$ in the freshwater system, which can be attributed to its porous structure and hydrogen bonding. Relatively low adsorption capacity was observed on other four microplastics. The adsorption amounts of 5 antibiotics on PS, PE, PP, and PVC decreased in the order of $\\mathrm{CIP}>\\mathrm{AMX}>\\mathrm{TMP}>\\mathrm{SDZ}>\\mathrm{TC}$ with $K_{f}$ correlated positively with octanol-water partition coefficients (Log $\\ensuremath{\\mathrm{K}}_{\\mathrm{ow}})$ . Comparing to freshwater system, adsorption capacity in seawater decreased significantly and no adsorption was observed for CIP and AMX. Our results indicated that commonly observed polyamide particles can serve as a carrier of antibiotics in the aquatic environment. \n\n$\\circledcirc$ 2018 Elsevier Ltd. All rights reserved. \n\n# 1. Introduction \n\nDuring the last 60 years, plastic production increased considerably from around 0.5 million tonnes in 1950 to 311 million tonnes in 2014 (Thompson et al., 2009; Plastics, 2015), which accompanied by increasing release of plastic waste to the environment. It is estimated that 4.8e12.7 million tonnes of plastic waste washed offshore in 2010 alone (Jambeck et al., 2015). Recently, microplastics (MPs) with particle size in the micrometer range have become the focus of study due to their potential toxic impact to aquatic ecosystems. MPs have been detected in surface water (Zhao et al., 2015), water column (Nel and Froneman, 2015), and bottom sediments (Browne et al., 2011). Previous studies have showed that polyethylene (PE), polystyrene (PS), polypropylene (PP), polyamide (PA), and polyvinyl chloride (PVC) are the most frequently detected \n\nMPs in the aquatic environment (Hidalgo-Ruz et al., 2012; Fok et al., 2017). It is believed that MPs can accumulate various toxins and chemical pollutants and serve as a carrier for long-range transport (Guo et al., 2012; Turner and Holmes, 2015; Hueffer and Hofmann, 2016). \n\nStudies have been conducted on the adsorption behaviors of organic pollutants or heavy metals onto different types of MPs (Bakir et al., 2014a, 2014b, Velzeboer et al., 2014; Wang et al., 2015; Hueffer and Hofmann, 2016; Wu et al., 2016) as well as the effects of plastic types and environmental factors (e.g., ionic strength and pH) on pollutants adsorption processes (Wang et al., 2015). Both the sorbent and the sorbate properties can influence the adsorption extent significantly. For instance, properties of MPs such as polarity, abundance of rubbery, and degree of crystalline have great impacts on adsorption capacities of pollutants (Guo et al., 2012; Wang et al., 2015; Brennecke et al., 2016). The hydrophobicity of organic contaminants is also important in determining their adsorption on MPs (Hueffer and Hofmann, 2016). Furthermore, adsorption of organic pollutants on MPs varied in the seawater and the freshwater (Velzeboer et al., 2014), which may be due to the impacts of salinity. \n\nAs reported by Wang et al. (2015), perfluorooctanesulfonate (PFOS) adsorption on PE and PS increased with increasing of ionic strength, while ionic strength had no effect on perfluorooctanesulfonamide (FOSA) adsorption. \n\nAs a class of emerging contaminants, antibiotics have received increasing attention due to their impacts on the microbial community as well as the generation of resistance genes (Le et al., 2005; Yang et al., 2017). A large number of antibiotics are released into the environment every year. As evaluated by Zhang et al. (2015), only in China, 53,800 tonnes of antibiotics discharged into the receiving environment in 2013. Studies reported that tetracyclines, macrolides, fluoroquinolones, and sulfonamides are the frequently detected antibiotics in the aquatic environment worldwide (Kolpin et al., 2002; Watkinson et al., 2009; Jiang et al., 2011; Li et al., 2012). Antibiotics such as trimethoprim, fluoroquinolones, and sulfonamides were found to be stable in surface water (Lunestad et al., 1995; Lin et al., 2010). More importantly, the residual antibiotics may pose relatively high ecological risk to the relevant aquatic organisms (Xu et al., 2013). If antibiotics can be absorbed by MPs, both could have higher toxic effects on aquatic life due to the combined pollution. There is evidence that persistent organic pollutants (POPs) can transfer from MPs to Artemia nauplii and further to zebrafish via a trophic food web (Batel et al., 2016). Thus, understanding the possible reactions between different kinds of antibiotics and MPs is warranted for the evaluation of their environmental risks. \n\nThe physicochemical properties such as specific surface area, degree of crystallinity, and pore size distribution vary substantially among different types of microplastic particles and may dominate their antibiotics adsorption capacities. To verify this hypothesis, experiments were conducted 1) to describe the structures and properties of 5 MPs using analytical techniques such as Scanning Electron Microscope (SEM) and X-ray diffractometer (XRD); 2) to evaluate the adsorption capacities of 5 types of commonly used antibiotics in the freshwater and seawater systems. \n\n# 2. Materials and method \n\n# 2.1. Chemicals \n\nSulfadiazine (SDZ), amoxicillin (AMX), tetracycline (TC), ciprofloxacin (CIP), and trimethoprim (TMP) were purchased from Sigma-Aldrich (USA), with ${>}99\\%$ purity. The physicochemical properties of antibiotics was shown in Table S1. Acetonitrile were high-performance liquid chromatography (HPLC) grade and were obtained from Anaqua Chemicals Supply (ACS, USA). Ultrapure water (MQ) was obtained from a Milli- $\\cdot{\\sf Q}$ water purification system (Millipore, Billerica, MA, USA). The other reagents were analytical grade or higher. Seawater was filtered through $0.45\\upmu\\mathrm{m}$ membranes and irradiated with ultraviolet light to eliminate the influences of dissolved organic matter as much as possible. TC, AMX, and TMP were dissolved in the background solutions (i.e. ultrapure water and filtered seawater) directly to prepare the stock solutions. For SDZ and CIP, methanol was added to enhance their solubility in background solutions. All the stock solutions were kept in the dark at $4^{\\circ}\\mathsf C$ for no long than one week. Stock solutions were diluted to the desired concentrations before use. \n\n# 2.2. Microplastic particles and analytical methods \n\nPolyethylene (PE), polystyrene (PS), polypropylene (PP), polyamide (PA), and polyvinyl chloride (PVC) were purchased as powders from Youngling Electromechanical Technology Co., Ltd. (Shanghai, China). The physicochemical properties of 5 MPs were shown in Table S2. The particle sizes distribution of these polymers were shown in Fig. S1. For any kinds of MPs, more than $90\\%$ of polymers fell into the $75{-}180\\upmu\\mathrm{m}$ size classes. Their point of zero charge (PZC) were analyzed based on the method described by Ferro-Garcia et al. (1998). The polymers microscopic morphological characteristics were analyzed by a Scanning Electron Microscope (SEM) (S-4800, Hitachi, Japan). The crystalline compositions of MPs were measured using X-ray diffractometer (XRD) (XRD-7000, SHIMADZU, Japan) with a $c_{u-K\\mathfrak{L}}$ as the radiation source $(\\uplambda=1.5406\\tilde{\\mathrm{A}};$ . The samples were scanned over the range of $5{\\mathrm{-}}90^{\\circ}$ of 2q at a rate of $1^{\\circ}\\operatorname*{min}^{-1}$ . \n\n# 2.3. Batch adsorption experiments \n\nBatch adsorption experiments for 5 antibiotics were undertaken with 5 concentration gradients (i.e. 0.5, 1, 5, 10, and $15\\mathrm{mgL}^{-1}.$ at room temperature $(25^{\\circ}\\mathsf{C})$ . Specifically, $_{0.02\\mathrm{g}}$ of each plastic particle was added into the glass vials. Different volumes of background solution (ultrapure water or filtered seawater) were added according to the concentration gradient. Then, antibiotic stock solution with a concentration of $50\\mathrm{mgL}^{-1}$ was added to make up the suspension volume of $5\\mathrm{mL}$ in each glass vial capped with a Teflon gasket. To minimize the effects of cosolvent, the volume ratio of methanol in the test solution was controlled below $0.1\\%$ . The glass vials were shaken in a temperature-controlled shaking incubator (HZS-HA, Harbin, China) at a shaking speed of $180\\mathrm{rpm}$ at $25^{\\circ}\\mathsf{C}$ for 4 d. After equilibrium, the sample was filtered through a $0.22\\upmu\\mathrm{m}$ syringe filter before analysis. All the adsorption experiments were conducted in triplicate. The blank sorption experiments with the reactor system containing antibiotics without MPs were carried out. The loss of antibiotics during sorption test was calculated and subtracted from the blank loss. To improve calculation accuracy, the amounts of antibiotics adsorbed on MPs were calculated using the following equation: \n\n$$\nq_{e}=\\frac{\\frac{m_{2}-m_{1}}{\\rho_{2}}\\left(c_{0}-c_{e}\\right)-\\frac{m_{1}-m_{0}}{\\rho_{1}}c_{e}-\\alpha}{m}\n$$ \n\nwhere $q_{\\mathrm{e}}(\\mathrm{mg}\\cdot\\mathbf{g}^{-1})$ is the equilibrium adsorption amount; $c_{0}$ and $c_{\\mathrm{e}}$ $(\\mathrm{mg}\\cdot\\mathrm{L}^{-1})$ are the initial concentration and the equilibrium concentration; $\\rho_{1}$ and $\\rho_{2}$ $(\\mathbf{g}\\ \\mathbf{m}\\mathbf{L}^{-1})$ are density of the background solution and the antibiotic stock solution, respectively; $m\\left({\\mathfrak{g}}\\right)$ is the mass of adsorbent; $m_{0}({\\bf g})$ is the mass of the adsorbent and the vial; $m_{1}$ (g) is the mass after adding the background solution; $m_{2}\\left({\\bf g}\\right)$ is the mass after adding the antibiotic stock solution; $\\alpha\\left(\\mathrm{mg}\\right)$ is blank loss. \n\n# 2.4. Adsorption model \n\nLinear, Freundlich, and Langmuir adsorption models were used to fit the adsorption isotherms of antibiotics. Briefly, the Linear model can be described as: \n\n$$\n\\begin{array}{r}{q=K_{d}C_{e}}\\end{array}\n$$ \n\nwhere $q(\\mathrm{mgg}^{-1})$ is the absorbed amount of antibiotic; $C_{e}(\\mathrm{mgL}^{-1})$ is antibiotic mass in the aqueous phase at equilibrium the equilibrium; and $K_{d}(\\mathrm{L}\\ \\mathrm{g}^{-1})$ is the partition coefficient. The Freundlich model is given by: \n\n$$\nq=K_{f}C_{e}^{n}\n$$ \n\nwhere $K_{f}(\\mathrm{L}\\ \\mathrm{g}^{-1})$ is the Freundlich adsorption coefficient which indicates adsorption capacity; $n$ is the Freundlich isotherm exponent that determines the non-linearity. The Langmuir isotherm model can be expressed as follow: \n\n$$\nq=q_{m a x}\\frac{k_{L}C_{e}}{1+k_{L}C_{e}}\n$$ \n\nwhere $q_{\\mathrm{max}}(\\mathrm{mgg^{-1}})$ represents the maximum adsorption capacity; $K_{L}(\\mathrm{L}\\operatorname{mg}^{-1})$ is related proportionally to the affinity between plastic particles and antibiotics. \n\n# 2.5. Detection of antibiotics \n\nAll the selected antibiotics were detected using highperformance liquid chromatography (Exformma 1600, USA) equipped with a UV detector. Chromatographic separations were performed with a SDS HYPERSIL C18 $(250\\mathrm{mm}\\times4.6\\mathrm{mm}$ , $5\\upmu\\mathrm{m}\\dot{}$ . The column temperature was $30^{\\circ}\\mathsf C$ The flow rate was $1.0\\mathrm{mL}\\mathrm{min}^{-1}$ and injection volume was $50\\upmu\\mathrm{L}$ The mobile phase and detection wavelength varied across antibiotics and were shown in Table 1. The detection limit of 5 antibiotics ranged from 0.01 to $0.05\\mathrm{mgL}^{-1},$ and the relative standard deviation (RSD) of antibiotic measurements was less than $3.0\\%$ . For each kind of antibiotics, two standard curves (one for ultrapure water and another for seawater) with seven-point (i.e. 0.1, 0.5, 1, 5, 10, 15, $20\\mathrm{mgL}^{-1}.$ ) were used for quantitative analysis. The ${\\boldsymbol{\\mathrm{r}}}^{2}$ of standard curves were between 0.990 and 1.00. \n\n# 3. Results and discussion \n\n# 3.1. Characterization of MPs \n\nFig. 1 shows the SEM micrographs of PE, PVC, PS, PP, and PA, respectively. The surface of PE particle was relatively smooth, while several micropores can be found on the surface of PVC. Reticular formation was developed on the surface of PS particles. Spherical bulges and micropores were observed on the surface and internal cross-section of PP. More importantly, the surface of PA was rough and exhibited characteristics of porous polymer. \n\nThe XRD patterns are good indications of the degree of crystalline of plastic particles. Generally, polymer with high degree of crystalline has sharp diffraction peak. As illustrated in Fig. S2, one sharp diffraction peak appeared in the XRD pattern of PE, indicating PE had high degree of crystalline. Similarly, three obvious peaks with high intensity can be found in the XRD pattern of PP. For PS and PA, their diffraction peaks showed the similar intensity. Whereas for PVC, there was no apparent diffraction peak in the 2q range of $5{-}90^{\\circ}$ . Therefore, the degree of crystallinity followed the order as: $\\mathrm{PE}>\\mathrm{PP}>\\mathrm{PA}\\approx\\mathrm{PS}>\\mathrm{PVC}$ . \n\n# 3.2. Adsorption isotherms \n\nAdsorption of antibiotics on MPs in freshwater and seawater were illustrated in Fig. 2. The estimated Linear, Freundlich, and Langmuir parameters were summarized in Table 2 and Table 3. The Freundlich parameter n was related to the non-linearity of isotherms. Previous studies showed that the sorption isotherms of perfluoroalkyl acids (PFAAs), polychlorinated biphenyls (PCBs), and pharmaceuticals and personal care products (PPCPs) on various plastic particles were highly linear (Velzeboer et al., 2014; Wang et al., 2015; Wu et al., 2016). But other study suggested that the linearity of sorption isotherms varied among chemicals and plastic types (Hueffer and Hofmann, 2016). As demonstrated in Tables 2 and 3, the adsorption isotherms of CIP, TMP, and TC on MPs were obviously non-linear with Freundlich n values ranged from 0.303 to 0.842, while adsorption of SDZ and AMX were relatively linear with the larger n values $(\\mathrm{n}>0.540),$ . Correspondingly, the non-linear models (i.e. Freundlich model and Langmuir model) exhibited better goodness-of-fit for isotherms of CIP, TMP, and TC, as indicated by the high values of ${\\boldsymbol{\\mathrm{r}}}^{2}$ . On the contrary, the Linear model was more suitable to simulate the adsorption isotherms of SDZ and AMX. Hueffer and Hofmann (2016) reported that the adsorption of seven non-polar organic compounds by PE, PS, PA, and PVC yielded a better fit with Freundlich model than Langmuir model. However, Bakir et al. (2012) suggested that Langmuir model was more suitable to explain sorption isotherm of bi-sorbates by PE and PVC than Freundlich model. Based on the ${\\boldsymbol{\\mathrm{r}}}^{2}$ (Table 2), the adsorption of CIP by PP and PA yielded a better fitness for Langmuir model, while the adsorption of CIP by PS, PE, and PVC yielded a better fitness for Freundlich model. For TMP in the seawater system, Freundlich model was suitable to describe its adsorption on PP, PS, PE, and PA. For TMP in the freshwater system, Freundlich model was suitable to describe its adsorption on PA, whereas Langmuir model described its adsorption on PP and PE well. The experiment results indicate that different reaction mechanisms are involved in the adsorption of antibiotics on MPs. More in-depth understanding of the binding mechanisms is required to establish more generalized adsorption model. \n\n# 3.3. Effects of microplastic properties \n\nTable 1 High-performance liquid chromatography conditions for the analysis of antibiotics. \n\n\n
AntibioticMobile phase AMobile phase BVolume radio (A:B)Wavelength
CIPdisodium hydrogen phosphate buffer (pH = 2.5)acetonitrile80:20277 nm
SDZ0.1% acetic acid solution acetonitrile78:22268 nm
AMOdisodium hydrogen phosphate buffer (pH = 2.5)acetonitrile85:15254 nm
TMP1% acetic acid solution acetonitrile80:20271 nm
TCdisodium hydrogen phosphate buffer (pH = 2.5)acetonitrile80:20360 nm
\n\nThe adsorption capacities of antibiotics on different MPs varied significantly (Table 2). Physicochemical properties of MPs such as specific surface area, polarity, and degree of crystallinity may affect their adsorption capacities. Wang et al. (2015) suggested that polarity of MPs can influence adsorption levels of polar chemicals. The tested antibiotics are polar compounds (Kanda et al., 2015) and is expected to have strong sorption capacity to polar MPs by the polar-polar interaction. As shown in Table 2, however, only polar PA has significant higher sorption capacity for 4 antibiotics (CIP, TMP, AMX, and TC) in the freshwater system, while polar PVC shows low affinity to polar antibiotics. This indicated that polarity of MPs alone were not capable of explaining the differences in adsorption capacities. As reported by Teuten et al. (2009) and Wang et al. (2015), the rubbery plastic PE showed higher adsorption capacity to organic pollutants than the glassier plastics (i.e. PP, PS, and PVC). However, for any kinds of antibiotics, its sorption capacity on PE was not the largest, which indicating sorption extents of antibiotics had little or no correlation with rubbery state of plastic. Guo et al. (2012) suggested that the plastic with low crystallinity could accumulated more hydrophobic organic pollutants. As shown in section 3.1, the degree of crystallinity of five types of MPs followed the order as: $\\mathrm{PE}>\\mathrm{PP}>\\mathrm{PA}\\approx\\mathrm{PS}>\\mathrm{PVC}.$ . However, this order was not consistent with the order of sorption capacity of any type of antibiotic, indicating the crystallinity of MPs was not the essential factor affecting antibiotic adsorption. \n\n![](images/5bbdc436c857a2d61b65a349d46c3a8dc343ddfd931fdea4f23691ae5595dfd0.jpg) \nFig. 1. SEM micrographs of polyethylene (PE), polystyrene (PS), polypropylene (PP), polyamide (PA), and polyvinyl chloride (PVC). \n\nAdsorption capacities of CIP, TMP, and SDZ on PS are higher than those on PE (Table 2). The reason may be that PS can undergo nonspecific vander Waals interactions and $\\pi-\\pi$ interactions at the aromatic surface, while PE can only undergo the vander Waals interactions (Velzeboer et al., 2014; Hueffer and Hofmann, 2016). As shown in Fig. 1, PS, PP, and especially PA have the developed pore structure, and this may be used to explain why these three MPs have higher sorption capacity than PE and PVC. Furthermore, PA has high adsorption for AMX, TC, and CIP, which can be attributed to the specific functional group (i.e. amide group). Hydrogen bonding can be formed between amide group (proton donor group) of PA and carbonyl group (proton acceptor group) of AMX, TC, and CIP (Antony et al., 2010). Other studies also demonstrated that hydrogen bonding between antibiotics (e.g. TC and CIP) and organic matter (e.g. humic substance and organic carbon) surfaces may contribute to antibiotics sorption (Tolls, 2001; Pils and Laird, 2007). Thus we suggested that the formation of hydrogen bonding as the mechanism underlying the high adsorption of AMX, TC, and CIP on PA. \n\nThe properties of MPs exposed to the environment may change because of environmental factors and therefore influence their adsorption behaviors (Turner and Holmes, 2015). For example, the polar functional groups, carbonyl groups, have been identified in aged plastic samples collected from beaches (Zbyszewski and \n\nCorcoran, 2011). The presence of polar functional groups may contribute to the formation of H-bonding. Furthermore, aged plastic particles tend to acquire a greater surface area through photo-oxidation, weathering, and aging (Turner and Holmes, 2011), and this will also favor the adsorption of contaminants. \n\n# 3.4. Effects of antibiotic properties \n\nAs shown in Table 2, the adsorption capacities of various antibiotics on a specific type of plastic differed greatly. Apart from PA, adsorption of 5 antibiotics on the other four MPs decreased in the order of $\\mathrm{CIP}>\\mathrm{AMX}>\\mathrm{TMP}>\\mathrm{SDZ}>\\mathrm{TC}$ . These results implied that antibiotics properties can influence their adsorptions on MPs. Previous studies indicated that the octanol-water partition coefficients $(\\mathrm{Log}K_{\\mathrm{ow}})$ of sorbates were essential in determining their adsorption extents on MPs (Hueffer and Hofmann, 2016; Wu et al., 2016). That is, the Log $K_{d}$ values of investigated sorbates were positively correlated with their Log $K_{\\mathrm{ow}}$ values. The Log $K_{\\mathrm{ow}}$ values of the investigated antibiotics decreased in the order of $\\mathrm{CIP}>\\mathrm{TMP}>\\mathrm{AMX}>\\mathrm{SDZ}>\\mathrm{TC}$ (Table S1). There was a significantly positive correlation between antibiotics’ Log $K_{\\mathrm{ow}}$ values and their average $K_{f}$ values on PP, PS, PE, and PVC $(\\mathtt{p}<0.05),$ . Our results suggested that hydrophobic antibiotics (with higher Log $K_{\\mathrm{ow}}$ values) had higher affinity to PP, PS, PE, and PVC. However, this correlation did not apply to PA, indicating hydrophobic interaction was insignificant for antibiotics adsorption on PA. \n\nAntibiotics are ionisable compounds, but the ionization constant (pKa) of various antibiotics usually differed significantly because of their specific functional groups. Thus, in a specific pH condition, various antibiotics will exhibit different speciation of the cation, zwitterion, and anion. The speciation of ionic chemicals can influence their sorption extents on MPs. As reported by Wang et al. (2015), the anionic forms of PFOS showed a higher adsorption capacity on PE with positive surface at low pH than the nonionic forms of FOSA. The pKa values of 5 antibiotics and their speciation at experimental pH condition were shown in Table S1. In the freshwater system, all the tested antibiotics were zwitterions and anions; nevertheless, CIP also had a portion of cations. In the seawater system, zwitterions and anions were the main speciation for 5 antibiotics. Because the experimental pH was higher than the PZC of 5 MPs, all the 5 MPs carried a net negative charge. Thus, for \n\n![](images/6317295d52d0344410ee94840ceb4cee4a0b037760dacc58c7920d70b36dbc8c.jpg) \nFig. 2. Adsorption of antibiotics on MPs in the freshwater system (left column) and in the seawater system (right column). Note: the values of ${\\sf q}_{\\mathrm{e}}$ less than 0 were not shown in this figure. \n\nCIP in the freshwater system, the cations of CIP enhanced its sorption capacity on negatively charged MPs surface due to electrostatic attraction. \n\n# 3.5. Freshwater and seawater systems \n\nOur results demonstrated that adsorption of antibiotics on MPs differed among freshwater and seawater systems. As shown in Fig. 2, adsorption of CIP and AMX did not occur in the seawater system. The sorption capacities of TMP, SDZ, and TC also decreased compared with the freshwater system. Differences in ionic strength and pH values may be used to explain the different sorption capacities in the freshwater and seawater systems. The pH of seawater system was higher than freshwater system (Table S2); \n\nTable 2 Estimated Linear, Freundlich, and Langmuir parameters for antibiotics adsorption on MPs in the freshwater system. \n\n\n
MPsLinearFreundlichLangmuir
Ka (L kg-1)Kf(L kg)qmax (mg g-1)K (L mg-1)
CIP
PP57.1 ± 11.50.827252 ± 33.30.3450.9380.615 ± 0.02990.8440.990
PS51.5 ± 7.760.846205 ± 17.00.3160.9680.416 ± 0.04271.670.903
PVC41.5 ± 7.830.844184 ± 6.190.3710.9980.453 ± 0.008631.150.996
PE55.1 ± 7.940.904222 ± 6.590.3930.9940.200 ± 0.01430.4430.990
PA96.5 ± 7.810.968170 ± 45.20.7410.9632.20 ± 0.6570.07400.980
TMP
PP9.71 ± 2.280.85132.3 ± 4.010.4500.9640.102 ± 0.01420.4980.934
PS9.51 ± 1.070.96332.1 ± 2.480.5070.9920.174 ± 0.03850.1580.932
PVC8.41 ± 1.20 8.38 ± 1.320.94113.4 ± 6.580.8420.9390.481 ± 0.4960.02590.944
PE17.1 ± 1.240.90822.0 ±2.590.5600.9860.154 ± 0.04130.1160.939
PASDZ0.97436.0 ± 6.150.6960.9850.468 ± 0.1280.06460.979
PP7.85 ± 0.6790.9858.00 ±7.140.9390.884nana
PS7.39 ± 0.3080.9954.10 ± 2.181.220.972na na na na
PVC6.61 ± 0.5490.9733.20 ± 2.911.270.918na na na
PE6.19 ± 0.2380.9962.20 ± 3.131.400.962nana na
PA7.36 ± 0.257 AMX0.9961.10 ± 0.1961.710.999na nana
PP17.5 ± 3.390.89560.0 ± 6.550.5400.7200.294 ± 0.07020.376
PS0.930
PVC24.7 ± 1.200.99120.0 ± 8.861.070.9690.523 ± 0.3680.0657一 0.953
PE8.40 ± 0.6750.96818.0 ± 2.270.6370.9300.131 ± 0.02840.1740.920
PA756 ± 48.00.980700 ± 31.80.9000.99122.7 ± 22.60.03610.992
PATC 356 ±38.20.945588 ± 1280.6990.9433.84 ± 0.8390.1890.977
\n\nNote: “-” means no antibiotic adsorption was occurred in the related system; “na” means fit did not converge, that is, Langmuir model failed to fit the adsorption isotherms. \n\nTable 3 Estimated Linear, Freundlich, and Langmuir parameters for antibiotics adsorption on MPs in the seawater system. \n\n\n
MPsLinearFreundlichLangmuir
Ka (L kg-1)Ky(L kg-1)qmax (mg g-1)K (L mg-1)
TMP
PP3.93 ± 0.9440.76518.4 ± 2.650.4420.7650.0597 ± 0.009260.5510.917
PS7.30 ± 0.9120.92713.9 ± 2.880.7690.6310.166 ± 0.1220.09690.724
PVC5.45 ± 0.4920.96119.0 ± 2.460.3030.4190.0341 ± 0.01351.460.170
PE6.47 ± 1.020.88823.2 ± 0.8610.5380.9630.0868 ± 0.005100.4690.989
PA5.89 ± 1.050.93810.0 ± 1.640.5600.9920.130 ± 0.03200.1130.962
PPSDZ
PS7.13 ± 0.952 6.80 ± 0.3520.948 0.9896.48 ± 8.791.020.744 0.965na nana
PVC5.37 ± 0.5980.9525.69 ± 2.911.070.994nana na
PE6.26 ± 0.6300.9610.850 ± 0.3081.730.926nana na
PA6.56 ±0.4960.9833.00 ± 2.98 2.53 ± 0.2261.29 1.380.999na na na nana
TCna
PA4.44 ± 0.9630.87112.4 ± 5.670.6000.8860.0878 ± 0.01920.1520.961
\n\nNote: “na” means fit did not converge, that is, Langmuir model failed to fit the adsorption isotherms. \n\naccordingly, the anionic speciation of antibiotics in the seawater system were more than in the freshwater system. Meanwhile, all the 5 MPs carried a net negative charge because the pH in seawater was higher than the PZC of MPs (Table S2). As a result, the enhanced electrostatic repulsions between MPs and antibiotics will reduce sorption level. Earlier study showed that sorption of PFOS on PE, PS, and PVC decreased with increasing pH (Wang et al., 2015). Tizaoui et al. (2017) also reported that increasing pH of reaction system can reduce endocrine disrupting chemicals (EDCs) adsorption on PA significantly. On the other hand, ionic strength, to a certain extent, could affect the electrostatic interactions since the electrolytes can compete with adsorbate for electrostatic sites (Shen and Gondal, 2017). When ionic strength increased, cations such as ${\\mathsf{N a}}^{+}$ and ${\\mathsf{C a}}^{2+}$ may be attracted electrostatically to the MPs surface. Further, the inorganic exchangeable cations (e.g. ${\\mathsf{N a}}^{+}$ ) can substitute the hydrogen ions of acidic groups and then inhibit the formation of Hbinding (Aristilde et al., 2010). These findings suggested that adsorption sites may decrease under high ionic strength condition. Therefore, adsorption of the tested antibiotics on MPs decreased at high ionic strength level. This result agreed with previous studies which demonstrated that the adsorption capacities of various antibiotics on different kinds of sorbents (e.g. marine sediments and soils) decreased with increasing of ionic strength (Wang et al., 2010; Xu and Li, 2010; Cao et al., 2015; Li and Zhang, 2017). Our study showed that all the tested antibiotics tend to be adsorbed by MPs in the freshwater system. The increase adsorption extents of antibiotics on MPs in the freshwater system may enhance their bioavailability and accumulation in food chain. \n\n# 3.6. Environmental implications \n\nAntibiotics and MPs are two classes of emerging contaminants and have attracted increasing public attention due to their potential toxicity to freshwater and marine ecosystems. Published studies have provided strong evidence that MPs can serve as a vector for the bioaccumulation of toxic chemicals (e.g. POPs and PPCPs) and the combination exhibit higher lethality than MPs themselves (Browne et al., 2013; Rochman et al., 2013; Chua et al., 2014). Although there is yet no available data on the combined effects of MPs and antibiotics, adsorption on MPs may result in the longrange transport of antibiotics and increase their exposure to aquatic ecosystem since antibiotics and MPs are ubiquitous in the aquatic environment and have the similar pollution resources (e.g. domestic wastewater and aquaculture pollution). Furthermore, MPs exposed to the environment may have higher affinity for antibiotics due to the increased specific surface area and polar groups from fragmentation and weathering. Interactions between MPs and antibiotics certainly need to be considered in evaluating the environmental risks associated with the two emerging contaminants. \n\n# 4. Conclusion \n\nThe adsorption behaviors of 5 antibiotics on 5 types of microplastic particles were investigated using batch type experiments. Our results showed that adsorption capacities varied among antibiotics, plastic types, and environmental conditions (e.g., ionic strength and pH). PA had high affinity for AMX, TC, and CIP in the freshwater system, potentially due to the formation of hydrogen bonding. Adsorption capacities of CIP in the freshwater system were relatively strong related to its cation speciation. All the tested antibiotics exhibited higher amount of adsorption in the freshwater than in seawater. Hydrogen bonding, hydrophobic interaction, van der Waals force, and electrostatic interaction were the main binding mechanisms between antibiotics and MPs. In the future studies, experiments should be performed 1) to investigate adsorption capacities of different speciation of antibiotics (i.e. cation, zwitterion, and anion) on MPs under different pH; 2) to reveal the effects of the major ions (e.g. $\\subset{}^{-}$ , SO3- 4, PO3- 4, ${\\mathsf{N a}}^{+}$ ) on antibiotics adsorption on MPs; 3) to evaluate the release of adsorbed antibiotics from MPs during their transport from river to ocean. \n\n# Acknowledgements \n\nThis study was financially supported by National Key R & D projects (2016YFC1402202) and the Key projects of international cooperation of Chinese Academy of Sciences (KYSB20160003). \n\n# Appendix A. Supplementary data \n\nSupplementary data related to this article can be found at https://doi.org/10.1016/j.envpol.2018.02.050. \n\n# References \n\nAntony, A., Fudianto, R., Cox, S., Leslie, G., 2010. Assessing the oxidative degradation of polyamide reverse osmosis membrane-Accelerated ageing with hypochlorite exposure. J. Membr. Sci. 347, 159e164. \nAristilde, L., Marichal, C., Miehe-Brendle, J., Lanson, B., Charlet, L., 2010. Interactions of oxytetracycline with a smectite clay: a spectroscopic study with molecular simulations. Environ. Sci. Technol. 44, 7839e7845. \nBakir, A., Rowland, S.J., Thompson, R.C., 2012. Competitive sorption of persistent organic pollutants onto microplastics in the marine environment. Mar. Pollut. Bull. 64, 2782e2789. \nBakir, A., Rowland, S.J., Thompson, R.C., 2014a. Enhanced desorption of persistent organic pollutants from microplastics under simulated physiological conditions. Environ. Pollut. 185, 16e23. \nBakir, A., Rowland, S.J., Thompson, R.C., 2014b. Transport of persistent organic pollutants by microplastics in estuarine conditions. Estuar. Coast Shelf Sci. 140, 14e21. \nBatel, A., Linti, F., Scherer, M., Erdinger, L., Braunbeck, T., 2016. Transfer of benzo a pyrene from microplastics to Artemia nauplii and further to zebrafish via a trophic food web experiment: CYP1A induction and visual tracking of persistent organic pollutants. Environ. Toxicol. Chem. 35, 1656e1666. \nBrennecke, D., Duarte, B., Paiva, F., Cacador, I., Canning-Clode, J., 2016. Microplastics as vector for heavy metal contamination from the marine environment. Estuar. Coast Shelf Sci. 178, 189e195. \nBrowne, M.A., Crump, P., Niven, S.J., Teuten, E., Tonkin, A., Galloway, T., Thompson, R., 2011. Accumulation of microplastic on shorelines woldwide: sources and sinks. Environ. Sci. Technol. 45, 9175e9179. \nBrowne, M.A., Niven, S.J., Galloway, T.S., Rowland, S.J., Thompson, R.C., 2013. Microplastic moves pollutants and additives to eorms, reducing functions linked to health and biodiversity. Curr. Biol. 23, 2388e2392. \nCao, X., Pang, H., Yang, G., 2015. Sorption behaviour of norfloxacin on marine sediments. J. Soils Sediments 15, 1635e1643. \nChua, E.M., Shimeta, J., Nugegoda, D., Morrison, P.D., Clarke, B.O., 2014. Assimilation of polybrominated diphenyl ethers from microplastics by the marine amphipod, allorchestes compressa. Environ. Sci. Technol. 48, 8127e8134. \nFerro-Garcia, M.A., Rivera-Utrilla, J., Bautista-Toledo, I., Moreno-Castilla, C., 1998. Adsorption of humic substances on activated carbon from aqueous solutions and their effect on the removal of $\\operatorname{Cr}(\\operatorname{III})$ ions. Langmuir 14, 1880e1886. \nFok, L., Cheung, P.K., Tang, G., Li, W.C., 2017. Size distribution of stranded small plastic debris on the coast of Guangdong, South China. Environ. Pollut. 220, 407e412. \nGuo, X., Wang, X., Zhou, X., Kong, X., Tao, S., Xing, B., 2012. Sorption of four hydrophobic organic compounds by three chemically distinct polymers: role of chemical and physical composition. Environ. Sci. Technol. 46, 7252e7259. \nHidalgo-Ruz, V., Gutow, L., Thompson, R.C., Thiel, M., 2012. Microplastics in the marine environment: a review of the methods used for identification and quantification. Environ. Sci. Technol. 46, 3060e3075. \nHueffer, T., Hofmann, T., 2016. Sorption of non-polar organic compounds by microsized plastic particles in aqueous solution. Environ. Pollut. 214, 194e201. \nJambeck, J.R., Geyer, R., Wilcox, C., Siegler, T.R., Perryman, M., Andrady, A., Narayan, R., Law, K.L., 2015. Plastic waste inputs from land into the ocean. Science 347, 768e771. \nJiang, L., Hu, X.L., Yin, D.Q., Zhang, H.C., Yu, Z.Y., 2011. Occurrence, distribution and seasonal variation of antibiotics in the Huangpu River, Shanghai, China. Chemosphere 82, 822e828. \nKanda, M., Nakajima, T., Hayashi, H., Hashimoto, T., Kanai, S., Nagano, C., Matsushima, Y., Tateishi, Y., Yoshikawa, S., Tsuruoka, Y., Sasamoto, T., Takano, I., 2015. Multi-residue determination of polar veterinary drugs in livestock and fishery products by liquid chromatography/tandem mass spectrometry. J. AOAC Int. 98, 230e247. \nKolpin, D.W., Furlong, E.T., Meyer, M.T., Thurman, E.M., Zaugg, S.D., Barber, L.B., Buxton, H.T., 2002. Pharmaceuticals, hormones, and other organic wastewater contaminants in US streams, 1999-2000: a national reconnaissance. Environ. Sci. Technol. 36, 1202e1211. \nLe, T.X., Munekage, Y., Kato, S., 2005. Antibiotic resistance in bacteria from shrimp farming in mangrove areas. Sci. Total Environ. 349, 95e105. \nLi, J., Zhang, H., 2017. Factors influencing adsorption and desorption of trimethoprim on marine sediments: mechanisms and kinetics. Environ. Sci. Pollut. Res. 24, 21929e21937. \nLi, W.H., Shi, Y.L., Gao, L.H., Liu, J.M., Cai, Y.Q., 2012. Occurrence of antibiotics in water, sediments, aquatic plants, and animals from Baiyangdian Lake in North China. Chemosphere 89, 1307e1315. \nLin, J.S., Pan, H.Y., Liu, S.M., Lai, H.T., 2010. Effects of light and microbial activity on the degradation of two fluoroquinolone antibiotics in pond water and sediment. J. Environ. Sci. Heal. B 45, 456e465. \nLunestad, B.T., Samuelsen, O.B., Fjelde, S., Ervik, A., 1995. Photostability of 8 antibacterial agents in seawater. Aquaculture 134, 217e225. \nNel, H.A., Froneman, P.W., 2015. A quantitative analysis of microplastic pollution along the south-eastern coastline of South Africa. Mar. Pollut. Bull. 101, 274e279. \nPils, J.R.V., Laird, D.A., 2007. Sorption of tetracycline and chlortetracycline on K- and Ca-saturated soil clays, humic substances, and clay-humic complexes. Environ. Sci. Technol. 41, 1928e1933. \nPlastics-the facts 2015. Available at: http://www.plasticseurope.org/cust/search. aspx?SearchText production. \nRochman, C.M., Hoh, E., Kurobe, T., The, S.J., 2013. Ingested plastic transfers hazardous chemicals to fish and induces hepatic stress. Sci. Rep. 3, 3263. \nShen, K., Gondal, M.A., 2017. Removal of hazardous Rhodamine dye from water by adsorption onto exhausted coffee ground. J. Saudi Chem. Soc. 21, S120eS127. \nTeuten, E.L., Saquing, J.M., Knappe, D.R.U., Barlaz, M.A., Jonsson, S., Bjorn, A., Rowland, S.J., Thompson, R.C., Galloway, T.S., Yamashita, R., Ochi, D., Watanuki, Moore, Pham Hung, V., Tana, T.S., Prudente, M., Boonyatumanond, R., Zakaria, M.P., Akkhavong, K., Ogata, Y., Hirai, H., Iwasa, S., Mizukawa, K., Hagino, Y., Imamura, A., Saha, M., Takada, H., 2009. Transport and release of chemicals from plastics to the environment and to wildlife. Philos. Trans. R. Soc. B 364, 2027e2045. \nThompson, R.C., Moore, C.J., vom Saal, F.S., Swan, S.H., 2009. Plastics, the environment and human health: current consensus and future trends. Philos. Trans. R. Soc. B 364, 2153e2166. \nTizaoui, C., Ben Fredj, S., Monser, L., 2017. Polyamide-6 for the removal and recovery of the estrogenic endocrine disruptors estrone, 17 beta-estradiol, 17 alphaethinylestradiol and the oxidation product 2-hydroxyestradiol in water. Chem. Eng. J. 328, 98e105. \nTolls, J., 2001. Sorption of veterinary pharmaceuticals in soils: a review. Environ. Sci. Technol. 35, 3397e3406. \nTurner, A., Holmes, L., 2011. Occurrence, distribution and characteristics of beached plastic production pellets on the island of Malta (central Mediterranean). Mar. Pollut. Bull. 62, 377e381. \nTurner, A., Holmes, L.A., 2015. Adsorption of trace metals by microplastic pellets in fresh water. Environ. Chem. 12, 600e610. \nVelzeboer, I., Kwadijk, C.J.A.F., Koelmans, A.A., 2014. Strong sorption of PCBs to nanoplastics, microplastics, carbon nanotubes, and fullerenes. Environ. Sci. Technol. 48, 4869e4876. \nWang, F., Shih, K.M., Li, X.Y., 2015. The partition behavior of perfluorooctanesulfonate (PFOS) and perfluorooctanesulfonamide (FOSA) on microplastics. Chemosphere 119, 841e847. \nWang, J.T., Hu, J., Zhang, S.W., 2010. Studies on the sorption of tetracycline onto clays and marine sediment from seawater. J. Colloid Interface Sci. 349, 578e582. \nWatkinson, A.J., Murby, E.J., Kolpin, D.W., Costanzo, S.D., 2009. The occurrence of antibiotics in an urban watershed: from wastewater to drinking water. Sci. Total Environ. 407, 2711e2723. \nWu, C., Zhang, K., Huang, X., Liu, J., 2016. Sorption of pharmaceuticals and personal care products to polyethylene debris. Environ. Sci. Pollut. Res. 23, 8819e8826. \nXu, W.H., Yan, W., Li, X.D., Zou, Y.D., Chen, X.X., Huang, W.X., Miao, L., Zhang, R.J., Zhang, G., Zou, S.C., 2013. Antibiotics in riverine runoff of the pearl river delta and pearl river estuary, China: concentrations, mass loading and ecological risks. Environ. Pollut. 182, 402e407. \nXu, X.R., Li, X.Y., 2010. Sorption and desorption of antibiotic tetracycline on marine sediments. Chemosphere 78, 430e436. \nYang, Y., Liu, W., Xu, C., Wei, B., Wang, J., 2017. Antibiotic resistance genes in lakes from middle and lower reaches of the Yangtze River, China: effect of land use and sediment characteristics. Chemosphere 178, 19e25. \nZbyszewski, M., Corcoran, P.L., 2011. Distribution and degradation of fresh water plastic particles along the beaches of Lake Huron, Canada. Water, Air, Soil Pollut. 220, 365e372. \nZhang, Q.Q., Ying, G.G., Pan, C.G., Liu, Y.S., Zhao, J.L., 2015. Comprehensive evaluation of antibiotics emission and fate in the river basins of China: source analysis, multimedia modeling, and linkage to bacterial resistance. Environ. Sci. Technol. 49, 6772e6782. \nZhao, S., Zhu, L., Li, D., 2015. Microplastic in three urban estuaries, China. Environ. Pollut. 206, 597e604. " + }, + { + "id": "10.1038_s41586-018-0109-z", + "DOI": "10.1038/s41586-018-0109-z", + "DOI Link": "http://dx.doi.org/10.1038/s41586-018-0109-z", + "Relative Dir Path": "mds/10.1038_s41586-018-0109-z", + "Article Title": "Thickness - independent capacitance of vertically aligned liquid-crystalline MXenes", + "Authors": "Xia, Y; Mathis, TS; Zhao, MQ; Anasori, B; Dang, A; Zhou, ZH; Cho, H; Gogotsi, Y; Yang, S", + "Source Title": "NATURE", + "Abstract": "The scalable and sustainable manufacture of thick electrode films with high energy and power densities is critical for the large-scale storage of electrochemical energy for application in transportation and stationary electric grids. Two-dimensional nullomaterials have become the predominullt choice of electrode material in the pursuit of high energy and power densities owing to their large surface area-to-volume ratios and lack of solid-state diffusion(1,2). However, traditional electrode fabrication methods often lead to restacking of two-dimensional nullomaterials, which limits ion transport in thick films and results in systems in which the electrochemical performance is highly dependent on the thickness of the film(1-4). Strategies for facilitating ion transport such as increasing the interlayer spacing by intercalation(5-8) or introducing film porosity by designing nulloarchitectures(9,10)-result in materials with low volumetric energy storage as well as complex and lengthy ion transport paths that impede performance at high charge-discharge rates. Vertical alignment of two-dimensional flakes enables directional ion transport that can lead to thickness-independent electrochemical performances in thick films(11-13). However, so far only limited success(11,12) has been reported, and the mitigation of performance losses remains a major challenge when working with films of two-dimensional nullomaterials with thicknesses that are near to or exceed the industrial standard of 100 micrometres. Here we demonstrate electrochemical energy storage that is independent of film thickness for vertically aligned two-dimensional titanium carbide (Ti3C2Tx), a material from the MXene family (two dimensional carbides and nitrides of transition metals (M), where X stands for carbon or nitrogen). The vertical alignment was achieved by mechanical shearing of a discotic lamellar liquid-crystal phase of Ti3C2Tx. The resulting electrode films show excellent performance that is nearly independent of film thickness up to 200 micrometres, which makes them highly attractive for energy storage applications. Furthermore, the self-assembly approach presented here is scalable and can be extended to other systems that involve directional transport, such as catalysis and filtration.", + "Times Cited, WoS Core": 1062, + "Times Cited, All Databases": 1129, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000432242000057", + "Markdown": "# Thickness-independent capacitance of vertically aligned liquid-crystalline MXenes \n\n$\\mathrm{{Yu}\\mathrm{{Xia}^{1}}}$ , Tyler S. Mathis2, Meng-Qiang Zhao2,3, Babak Anasori2, Alei Dang1,4, Zehang Zhou1,5, Hyesung Cho1, Yury Gogotsi2\\* & Shu Yang1\\* \n\nThe scalable and sustainable manufacture of thick electrode films with high energy and power densities is critical for the large-scale storage of electrochemical energy for application in transportation and stationary electric grids. Two-dimensional nanomaterials have become the predominant choice of electrode material in the pursuit of high energy and power densities owing to their large surfacearea-to-volume ratios and lack of solid-state diffusion1,2. However, traditional electrode fabrication methods often lead to restacking of two-dimensional nanomaterials, which limits ion transport in thick films and results in systems in which the electrochemical performance is highly dependent on the thickness of the $\\mathbf{film^{1-4}}$ . Strategies for facilitating ion transport—such as increasing the interlayer spacing by intercalation5–8 or introducing film porosity by designing nanoarchitectures9,10—result in materials with low volumetric energy storage as well as complex and lengthy ion transport paths that impede performance at high charge–discharge rates. Vertical alignment of two-dimensional flakes enables directional ion transport that can lead to thickness-independent electrochemical performances in thick films11–13. However, so far only limited success11,12 has been reported, and the mitigation of performance losses remains a major challenge when working with films of two-dimensional nanomaterials with thicknesses that are near to or exceed the industrial standard of 100 micrometres. Here we demonstrate electrochemical energy storage that is independent of film thickness for vertically aligned two-dimensional titanium carbide $(\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x})$ , a material from the MXene family (twodimensional carbides and nitrides of transition metals $(\\mathbf{M})$ , where X stands for carbon or nitrogen). The vertical alignment was achieved by mechanical shearing of a discotic lamellar liquid-crystal phase of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}.$ The resulting electrode films show excellent performance that is nearly independent of film thickness up to 200 micrometres, which makes them highly attractive for energy storage applications. Furthermore, the self-assembly approach presented here is scalable and can be extended to other systems that involve directional transport, such as catalysis and filtration. \n\nIn this work we chose ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x},$ the most widely studied MXene1, as a model material to demonstrate an electrode design that is capable of thickness-independent electrochemical energy storage (Fig. 1). Two-dimensional flakes dispersed in an aqueous solution can produce spontaneous long-range orientational order, forming mesophases known as discotic liquid crystal phases, including discotic nematic14,15, smectic (or lamellar) and columnar phases16. Among them, the discotic smectic, or lamellar, phase and the discotic columnar phase have a higher order, with molecules aligning in one- and two-dimensional lattices, respectively. First, to prepare MXene liquid crystals, we synthesized $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets with an average lateral size of approximately $219\\pm47\\mathrm{nm}$ (Fig. 2a and Extended Data Fig. 1). As shown in Extended Data Fig. 2, at a concentration of $250\\mathrm{mgm}\\bar{\\mathrm{l}}^{-1}$ the nanosheets form the discotic nematic phase in water, which can be well aligned vertically using microchannels (see Extended Data Fig. 2c, d, Supplementary Video 1) at a small liquid-crystal-cell thickness of around $6\\upmu\\mathrm{m}$ . However, the surface-anchoring effect decreases markedly with the thickness of the liquid crystal, making it challenging to maintain the vertical alignment in thicker films. \n\nTo address this, we created the higher-order discotic lamellar phase (Fig. 1c). Previous theoretical and neutron scattering studies have suggested that the coherent lamellar layers could be aligned vertically under an external mechanical shearing force17,18 (see schematic in Fig. 1d). This phenomenon is attributed to torque arising from flow-induced fluctuation in the lamellar or smectic phase, which is perpendicular to the shear direction17–20. To minimize the elastic distortion energy, lamellae reorient to be vertically aligned; this is in sharp contrast with the alignment of molecules (or discs) in the conventional nematic phase, which is mostly horizontal under the flow field18 (Extended Data Fig. 3). \n\nAlthough vertical alignment has been demonstrated in the discotic lamellar phase for decades, mainly for small-molecule organic compounds, achieving such a high-order phase in two-dimensional inorganic nanosheets is generally problematic owing to the large polydispersity in the shape and size of the nanosheets, which considerably reduces the packing symmetry of the system. To circumvent this intrinsic limitation, we introduced a non-ionic surfactant, hexaethylene glycol monododecyl ether $(\\mathrm{C}_{12}\\mathrm{E}_{6})$ , to enhance molecular interactions between the nanosheets, thereby increasing the packing symmetry (Fig. 1c). The sample preparation process is shown in Extended Data Fig. 4. Hydrophilic colloidal surfaces are known to have high affinities towards $\\mathrm{C}_{12}\\mathrm{E}_{6}$ , typically forming a double layer on the surface of the colloids21. In the case of MXene– ${\\mathrm{.C}}_{12}{\\mathrm{E}}_{6},$ it is expected that strong hydrogen bonds will form between the $-\\mathrm{OH}$ groups of $\\mathrm{\\C_{12}E_{6}}$ and –F or $^{-0}$ groups on the surface of the MXene22 (Fig. 1c). The incorporation of $\\mathrm{C}_{12}\\mathrm{E}_{6}$ between MXene nanosheets is confirmed by the observation of a new fan-like texture under a polarized optical microscope (POM; Fig. 2b), characteristic of the discotic lamellar phase; this is denoted hereafter as an MXene lamellar liquid crystal (MXLLC). Single-walled carbon nanotubes (SWCNTs; $10\\mathrm{wt\\%}$ ) were added as conductive spacers between the MXene layers to improve the structural stability and the conductivity of the electrodes5. \n\nThe birefringence of the MXene– $\\mathrm{C}_{12}\\mathrm{E}_{6}$ composite is completely different to that of the $\\mathrm{C}_{12}\\mathrm{E}_{6}{\\mathrm{-}}\\mathrm{H}_{2}\\mathrm{O}$ system (Fig. 2c), and small-angle X-ray scattering (SAXS) confirms the lamellar nature of the MXLLC (Fig. 2d). Without the MXene, $\\mathrm{C}_{12}\\mathrm{E}_{6}–\\mathrm{H}_{2}\\mathrm{O}$ is in a hexagonal phase with three characteristic peaks in a relative positional ratio of $1:{\\sqrt{3}}:2$ . These peaks nearly disappear in the MXLLC and three new peaks are present in a positional ratio of 1:2:3 (Fig. 2d), clearly indicating the lamellar structure of the MXLLC. The value of the scattering vector $q$ of the (100) peak is $0.108\\mathring\\mathrm{A}$ , from which the layer spacing $d$ is calculated to be approximately $5.8\\mathrm{nm}$ . This is consistent with the sandwiched structure illustrated in Fig. 1c, with the double-layer $\\mathrm{C}_{12}\\mathrm{E}_{6}$ (around \n\n![](images/c7fca650111a1eec35a4520ccef9754fd27a857f7e8625943d2a0571ce1bf304.jpg) \nFig. 1 | Schematic illustration of ion transport in $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ MXene films. a, b, Ion transport in horizontally stacked (a) and vertically aligned (b) $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene films. The blue lines indicate ion transport pathways. c, Illustration of the surfactant $(\\mathrm{C}_{12}\\mathrm{E}_{6})$ -enhanced lamellar structure of the MXLLC. Red indicates the hydrophilic tail and green indicates the hydrophobic part of the surfactant. The hydrogen bonding between $\\mathrm{C}_{12}\\mathrm{E}_{6}$ \nand the MXene surface is shown on the right. The director of the MXLLC is labelled with an arrow. d, Illustration of the alignment method used in this work. The blue plates at the top and bottom represent the shear plates. Under mechanical shear flow, the randomly aligned structure of the MXLLC can be aligned with the flow direction, with the director of the MXLLC being perpendicular to the shear direction. \n\n$4.9\\mathrm{nm}\\mathrm{thick}^{21}.$ ) between the MXene nanosheets (around $0.95\\mathrm{nm}$ thick23). \n\nWe then aligned the MXLLC by applying a uniaxial in-plane mechanical shear force. The required shear rate of alignment is closely related to the particle size: large particles that have slower relaxation times will align at a lower shear rate24,25 $\\langle\\dot{\\gamma};\\rangle$ see Methods). For small molecules (less than $10\\mathrm{nm}$ in diameter), vertical alignment has been obtained with shear rates of approximately $100{-}1,000{\\bar{s}}^{-1}$ in the lamellar phase18. Therefore, for our large MXene sheets, a shear rate of approximately $50-100s^{-1}$ should be sufficient. As shown in Fig. 2e, the strong mechanical shear force aligns the MXLLC almost unidirectionally, with high birefringence that is mostly maintained after the removal of $\\mathrm{C}_{12}\\mathrm{E}_{6}$ (Extended Data Fig. 5b). The stark contrast in transmitted light intensity between the POM images at polarizer angles of $45^{\\circ}$ and $0^{\\circ}$ (Extended Data Fig. 5b) clearly suggests that the liquid-crystal director is either parallel or perpendicular to the shear direction. We then imaged the same sample area using scanning electron microscopy (SEM). The top-view image (Fig. 2f) clearly shows that the majority of the MXene flakes align vertically with their lateral direction following the shear field, which is consistent with literature18, and partial are marked with blue arrows, and the hexagonal peaks are marked with red arrows. A small portion of coexisting hexagonal phase (marked with red circles) could be attributed to residual $\\mathrm{C}_{12}\\mathrm{E}_{6}$ that is not fully mixed with the MXene. a.u., arbitrary units. e, POM image of the MXLLC with shear direction at $45^{\\circ}$ to the polarizer angle. The inset illustrates the orientation of the MXLLC under shear flow. f, Top view of SEM image of the MXLLC, characterizing the structure shown in e. g, h, Bottom (g) and side ${\\bf\\Pi}({\\bf h})$ views of vertical nanosheets on the horizontally aligned MXene current collector. The red dashed line in h illustrates the ion transport path after the bending of the MXene layers in the vertical direction. The insets of f–h are illustrations of MXene orientation from different viewpoints, as labelled. \n\n![](images/cbfb7c285df3cb8904f56d987f81b4479b263dde50acb2e928b7439879677fdb.jpg) \nFig. 2 | Characterization of MXene nanosheets and the high-order MXLLC. a, SEM image of MXene flakes drop-cast from a colloidal solution on an alumina membrane, depicting the shape and size of the nanosheets. The inset shows the structure of a single MXene layer. b, POM image of the MXLLC showing the fan-like texture of the lamellar phase. The inset illustrates the assembled structure that gives rise to the birefringent image. c, POM image with the light retardation plate of the MXLLC shown in b after mechanical shear. The inset shows the $\\mathrm{C_{12}E_{6^{-}}}$ $_\\mathrm{H}_{2}\\mathrm{O}$ system after shear. $\\pmb{R}$ represents the direction of light retardation. In the case of the $\\mathrm{C}_{12}\\mathrm{E}_{6}–\\mathrm{H}_{2}\\mathrm{O}$ system, the fast axis is along the shear direction. In the MXLLC, the slow axis is parallel to the shear. d, SAXS of the $\\mathrm{C}_{12}\\mathrm{E}_{6}\\mathrm{-}\\mathrm{H}_{2}\\mathrm{O}$ system (red) and the MXLLC (blue). The lamellar peaks \n\n![](images/2279e47d192e52cfbd7f04e1daf04e3db0b1e3d7ed5d2bc91f8fad95ab5edbc9.jpg) \nFig. 3 | Electrochemical analysis of vacuum-filtered MXene papers and MXLLC films. a, Cyclic voltammograms of the indicated samples at a scan rate of $100\\mathrm{mVs^{-1}}$ . b, Cyclic voltammograms for a $200\\mathrm{-}\\upmu\\mathrm{m}$ -thick MXLLC film at different scan rates. c, Plot of the anodic peak current against the scan rate for MXLLC films with different film thickness. d, Nyquist plots for different MXene films taken at $0\\mathrm{V}$ versus the resting potential. The inset shows a magnification of the high-frequency region. \n\nreorientation of the nanosheets is attributed to capillary forces during drying. The bottom-view image (Fig. 2g) shows slightly tilted (polar tilting angle of around $20^{\\circ}$ ) vertical nanosheets relative to the bottom layer, which is purposely coated with horizontally stacked MXene as a current-collector layer to improve electron transport1. The bottom layer is designed to be extremely thin— $30\\mathrm{nm}$ as measured by atomic force microscopy (AFM, Extended Data Fig. 6)—such that it will not interfere with the electrochemical performance of the vertically aligned MXLLC. The cross-sectional views (Fig. 2h and Extended Data Fig. 5e–h; see red dashed line) show continuous bending of the MXLLC layers, which could originate from elastic distortion of MXene lamellae during mechanical shearing. Nevertheless, as we show subsequently, the slight distortion has a negligible effect on the overall electrochemical performance. \n\nTo demonstrate the possibility of using vertically aligned MXene nanosheets as electrodes in electrochemical energy storage devices, we investigated their electrochemical performance as supercapacitor electrodes. Vacuum-filtered MXene films with the same amount $(10\\mathrm{wt\\%})$ of SWCNTs as interlayer spacers were used as a reference (Extended Data Fig. 7). At a medium scan rate of $100\\mathrm{mVs}^{-1}$ (Fig. 3a), the cyclic voltammogram of a $6\\mathrm{-}\\upmu\\mathrm{m}$ -thick, filtered MXene paper shows clear redox peaks at approximately $-0.6\\:\\mathrm{V}$ and $-0.8\\mathrm{V}$ versus an $\\mathrm{Hg/}$ $\\mathrm{Hg}_{2}\\mathrm{SO}_{4}$ reference electrode, whereas a $35\\mathrm{-}\\upmu\\mathrm{m}$ -thick filtered MXene paper loses most of the pseudocapacitive characteristic of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ . This disparity, however, is not observed in the MXLLC films. The redox peaks of the MXLLC remain mostly independent of film thickness from $40\\upmu\\mathrm{m}$ to $200\\upmu\\mathrm{m}.$ a clear indication of substantially enhanced ion-transport properties and thickness-independent behaviour. Additionally, for the MXLLC samples, a pair of redox peaks appears at $-0.4\\:\\mathrm{V}$ and $-0.6\\mathrm{V},$ which could originate from additional redox reactions of the MXene (Extended Data Figs. 8, 9). In the case of the MXLLC, this process is thought to be more prominent owing to the increased amount of accessible MXene surface area. This second pair of peaks shows a similar dependence of the peak current on the scan rate (Extended Data Fig. 8a) to that of the characteristic peaks of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ seen in the MXLLC electrodes (Fig. 3c), but this second pair of peaks does deviate from the quasi-equilibrium behaviour seen previously at low scan rates19. The main reason for this is likely to be the large difference in thickness of the MXLLC electrodes $(200\\upmu\\mathrm{m})$ compared with previous reports of thin $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ electrodes $(90\\mathrm{nm})$ . It has been shown that the storage mechanism involves the reduction and oxidation of titanium26, but the precise nature of redox peak-splitting here needs further investigation. \n\n![](images/190ff889f6c60569e418bb22d9e7477c03528d21426f06f62dba744f978cd191.jpg) \nFig. 4 | Electrochemical performance of vacuum-filtered MXene papers and MXLLC films. a, Rate performance of vacuum-filtered MXene papers and MXLLC films at scan rates ranging from 10 to $100,000\\mathrm{mV}s^{-1}$ . For comparison, we replotted the specific capacitance of a $180\\mathrm{-}\\upmu\\mathrm{m}$ - thick macroporous MXene film that has been previously reported27. b, Capacitance retention of a $200\\mathrm{-}\\upmu\\mathrm{m}$ -thick MXLLC film tested by galvanostatic cycling at $20\\mathrm{Ag^{-1}}$ . The inset depicts galvanostatic cycling profiles at 2, 5, 10, 20, 50 and $\\mathbf{\\widetilde{l00Ag}^{-1}}$ , respectively. c, Areal capacitance of vacuum-filtered MXene papers and MXLLC films at scan rates ranging from 10 to $100,000\\mathrm{mV}s^{-1}$ . d, Areal capacitance as a function of the mass loading of the film at scan rates of 1,000 and $2,000\\mathrm{mVs^{-1}}$ . The orange box indicates the plateau area at which areal capacitance is almost independent of mass loading. \n\nWe then cycled the samples at scanning rates from 10 to $10,000\\mathrm{mVs^{-1}}$ (Fig. 3b and Extended Data Fig. 9c, d), and observed negligible distortion of the cyclic voltammetry curves for rates up to $\\bar{1}\\bar{,000}\\mathrm{mVs^{-1}}$ . Figure 3c shows a plot of the peak-current density against the scan rate for the pseudocapacitive peaks from films of varying thicknesses. The peak currents are directly proportional to the scan rate following the power law (see Methods), with the characteristic parameter $b$ being nearly 1 in the scan-rate window between 5 and $\\bar{2},000\\mathrm{mVs^{-1}}$ for films up to $200\\upmu\\mathrm{m}$ thick. The high values of $b$ indicate that the charge-storage kinetics of the MXLLC films are controlled by surface reactions. The diffusion-limited mechanism becomes more prominent in the thicker $(320\\upmu\\mathrm{m})$ MXLLC film with a $b$ value of around 0.69. The maximum film thickness, before ion transport limitations become considerable, is approximately $200\\upmu\\mathrm{m}$ for the present system. \n\nAnalysis of impedance measurements (Fig. 3d) offers further insights into the charge transfer and ion transport in the electrodes. As expected, the series resistance of the MXene electrodes in the acidic, aqueous electrolyte is low (approximately $0.07\\Omega\\mathrm{cm}^{2}\\rangle$ for both filtered MXene papers and MXLLC films, regardless of electrode architecture. However, there is a clear difference in ion transport between the two electrode architectures. The Nyquist plots of the filtered paper electrodes show a clear $45^{\\circ}$ Warburg-type impedance element in the mid-frequency region, whereas plots of the MXLLC electrodes are nearly vertical at all frequencies, a strong indication that fast ion diffusion is critical for thickness-independent performance. \n\nThe thickness-independent rate performance is further demonstrated in Fig. 4a. The rate performance of the MXLLC films declines only slightly when the film thickness is increased from $40\\upmu\\mathrm{m}$ to $200\\upmu\\mathrm{m}$ , especially for scan rates below $2,000\\mathrm{mVs^{-1}}$ , in sharp contrast to the pronounced decrease seen for the filtered MXene papers. All MXLLC electrodes demonstrate excellent retention of capacitance, especially when film thicknesses are less than $200\\upmu\\mathrm{m}$ : over $200\\mathrm{Fg}^{-1}$ is retained at a high scan rate of $2,000\\mathrm{mVs^{-1}}$ (also see Extended Data Fig. 10), which surpasses some of the best values reported in literature27–29. We note that, to our knowledge, this thickness-independent rate performance has not been reported previously, and for comparison we have replotted (Fig. 4a) literature data for a $180\\mathrm{-}\\upmu\\mathrm{m}$ -thick macroporous MXene $\\mathrm{film}^{27}$ , which shows a much faster decay with scan rate than is seen in the MXLLC samples. We note that the as-fabricated MXLLC electrodes are extremely stable, retaining almost $100\\%$ of their capacitance after 20,000 cycles of galvanostatic cycling at a rate of $20\\mathrm{Ag^{-\\bar{1}}}$ (Fig. 4b). Moreover, our vertically aligned MXenes have excellent areal capacitances (Fig. 4c). For the 200- $\\cdot\\upmu\\mathrm{m}$ -thick MXLLC film, an areal capacitance greater than $0.6\\mathrm{Fcm}^{-2}$ (the standard for supercapacitor electrodes) is maintained at scan rates of up to $2,000\\mathrm{mV}\\dot{\\mathrm{s}}^{-1}$ . Although higher areal capacitances are obtained from thicker $(245\\upmu\\mathrm{m}$ and $320\\upmu\\mathrm{m}\\ '$ films at low scan rates, the films lose capacitance much faster with increasing scan rate in comparison to films with thicknesses of $200\\upmu\\mathrm{m}$ or less, and finally plateau (see Fig. 4d). As a result, the areal capacitance at scan rates of $\\bar{1,000{-}2,000\\mathrm{m}\\bar{\\mathrm{V}}s^{-1}}$ is about the same for mass loadings in the range of 2.80 to $6.16\\mathrm{mgcm}^{-2}$ . Our results show the possibility of using vertically aligned MXenes to enable thick electrodes to operate at very high charge–discharge rates. \n\nThe precise control of directional ion transport is of fundamental importance to fields besides electrochemical energy storage, including filtration, fuel cells, catalysis and photovoltaics. Therefore, the vertical alignment of functional nanomaterials through the manipulation of their liquid crystal mesophase demonstrated here offers a new and powerful technique to construct advanced architectures with exceptional performance. Of equal importance is that the formation of liquidcrystal phases can be achieved by means of self-assembly, which is highly scalable for low-cost and large-area fabrication, as evidenced by the success of block copolymer nanolithography in computer chips30. \n\n# Online content \n\nAny Methods, including any statements of data availability and Nature Research reporting summaries, along with any additional references and Source Data files, are available in the online version of the paper at https://doi.org/10.1038/s41586- 018-0109-z \n\nReceived: 6 November 2017; Accepted: 5 March 2018; \nPublished online 16 May 2018. \n1. Anasori, B., Lukatskaya, M. R. & Gogotsi, Y. 2D metal carbides and nitrides (MXenes) for energy storage. Nat. Rev. Mater. 2, 16098 (2017). \n2. Raccichini, R., Varzi, A., Passerini, S. & Scrosati, B. The role of graphene for electrochemical energy storage. Nat. Mater. 14, 271–279 (2015). \n3. Gogotsi, Y. & Simon, P. Materials science. True performance metrics in electrochemical energy storage. Science 334, 917–918 (2011). \n4. Lukatskaya, M. R., Dunn, B. & Gogotsi, Y. Multidimensional materials and device architectures for future hybrid energy storage. Nat. Commun. 7, 12647 (2016). \n5. Zhao, M.-Q. et al. Flexible MXene/carbon nanotube composite paper with high volumetric capacitance. Adv. Mater. 27, 339–345 (2015). \n6. Ling, Z. et al. Flexible and conductive MXene films and nanocomposites with high capacitance. Proc. Natl Acad. Sci. USA 111, 16676–16681 (2014). \n7. Lukatskaya, M. R. et al. Cation intercalation and high volumetric capacitance of two-dimensional titanium carbide. Science 341, 1502–1505 (2013). \n8. Luo, J. et al. Pillared structure design of MXene with ultralarge interlayer spacing for high-performance lithium-ion capacitors. ACS Nano 11, 2459–2469 (2017). \n9. Sun, H. et al. Three-dimensional holey-graphene/niobia composite architectures for ultrahigh-rate energy storage. Science 356, 599–604 (2017). \n10.\t Zhu, C. et al. Supercapacitors based on three-dimensional hierarchical graphene aerogels with periodic macropores. Nano Lett. 16, 3448–3456 (2016). \n11.\t Miller, J. R., Outlaw, R. A. & Holloway, B. C. Graphene double-layer capacitor with ac line-filtering performance. Science 329, 1637–1639 (2010). \n12.\t Yoon, Y. et al. Vertical alignments of graphene sheets spatially and densely piled for fast ion diffusion in compact supercapacitors. ACS Nano 8, 4580–4590 (2014). \n13.\t Chen, J., Zheng, B. & Lu, G. Vertically-Oriented Graphene: PECVD Synthesis and Applications Ch. 7 (Springer, Cham, 2015). \n14.\t Jalili, R. et al. Processable 2D materials beyond graphene: ${\\mathsf{M o S}}_{2}$ liquid crystals and fibres. Nanoscale 8, 16862–16867 (2016). \n15.\t Narayan, R., Kim, J. E., Kim, J. Y., Lee, K. E. & Kim, S. O. Graphene oxide liquid crystals: Discovery, evolution and applications. Adv. Mater. 28, 3045–3068 (2016). \n16.\t Van der Kooij, F. M., Kassapidou, K. & Lekkerkerker, H. N. W. Liquid crystal phase transitions in suspensions of polydisperse plate-like particles. Nature 406, 868–871 (2000). \n17.\t Safinya, C. R. et al. Structure of membrane surfactant and liquid crystalline smectic lamellar phases under flow. Science 261, 588–591 (1993). \n18.\t Mang, J. T., Kumar, S. & Hammouda, B. Discotic micellar nematic and lamellar phases under shear flow. Europhys. Lett. 28, 489 (1994). \n19.\t Bruinsma, R. F. & Safinya, C. R. Landau theory of the nematic-smectic-A phase transition under shear flow. Phys. Rev. A 43, 5377–5404 (1991). \n20.\t Bruinsma, R. & Rabin, Y. Shear-flow enhancement and suppression of fluctuations in smectic liquid crystals. Phys. Rev. A 45, 994–1008 (1992). \n21.\t McDermott, D. C., Lu, J. R., Lee, E. M., Thomas, R. K. & Rennie, A. R. Study of the adsorption from aqueous solution of hexaethylene glycol monododecyl ether on silica substrates using the technique of neutron reflection. Langmuir 8, 1204–1210 (1992). \n22.\t Hu, T. et al. Interlayer coupling in two-dimensional titanium carbide MXenes. Phys. Chem. Chem. Phys. 18, 20256–20260 (2016). \n23.\t Ghidiu, M., Lukatskaya, M. R., Zhao, M.-Q., Gogotsi, Y. & Barsoum, M. W. Conductive two-dimensional titanium carbide ‘clay’ with high volumetric capacitance. Nature 516, 78–81 (2014). \n24.\t Onuki, A. & Kawasaki, K. Nonequilibrium steady state of critical fluids under shear flow: a renormalization group approach. Ann. Phys. 121, 456–528 (1979). \n25.\t De Gennes, P. G. Effect of shear flows on critical fluctuations in fluids. Mol. Cryst. Liq. Cryst. 34, 91–95 (1976). \n26.\t Lukatskaya, M. R. et al. Probing the mechanism of high capacitance in 2D titanium carbide using in situ X-ray absorption spectroscopy. Adv. Energy Mater. 5, 1500589 (2015). \n27.\t Lukatskaya, M. R. et al. Ultra-high-rate pseudocapacitive energy storage in two-dimensional transition metal carbides. Nat. Energy 2, 17105 (2017). \n28.\t Bo, Z. et al. Vertically oriented graphene bridging active-layer/current-collector interface for ultrahigh rate supercapacitors. Adv. Mater. 25, 5799–5806 (2013). \n29.\t Acerce, M., Voiry, D. & Chhowalla, M. Metallic 1T phase MoS2 nanosheets as supercapacitor electrode materials. Nat. Nanotechnol. 10, 313–318 (2015). \n30.\t Stoykovich, M. P. & Nealey, P. F. Block copolymers and conventional lithography. Mater. Today 9, 20–29 (2006). \n\nAcknowledgements We thank W.-S. Wei and Z. Davison for providing insights into the assembly of discotic liquid crystals in our experiments. We acknowledge support from the National Science Foundation Materials Science and Engineering Center Grant to the University of Pennsylvania, DMR-1120901 and DMR-1720530 (to S.Y.). Work on MXene synthesis and electrochemical characterization at Drexel University was supported by the Fluid Interface Reactions, Structures & Transport Center, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences (to Y.G.). \n\nAuthor contributions Y.X., T.S.M., M.-Q.Z., Y.G. and S.Y. conceived the idea and designed the experiments. Y.X., T.S.M. and M.-Q.Z. performed the experiments. Z.Z., A.D., H.C. and B.A. helped with the experiments. Y.G. and S.Y. supervised the work. Y.X. and T.S.M. drafted the manuscript, and all the authors contributed to the editing of the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\nAdditional information \nExtended data is available for this paper at https://doi.org/10.1038/s41586- 018-0109-z. \nSupplementary information is available for this paper at https://doi. \norg/10.1038/s41586-018-0109-z. \nReprints and permissions information is available at http://www.nature.com/ reprints. \nCorrespondence and requests for materials should be addressed to Y.G. or S.Y. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\nData reporting. No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. \n\nMaterials. Hexaethylene glycol monododecyl ether $(\\mathrm{C}_{12}\\mathrm{E}_{6})$ was purchased from TCI Chemicals. Cetyltrimethylammonium bromide (CTAB), cyclopentanone and cellulose acetate $(M_{\\mathrm{w}}\\approx30,000)$ were purchased from Sigma-Aldrich and used as received. SWCNTs (diameter ${\\sim}1{-}4\\mathrm{nm}$ , length ${\\sim}5{-}30\\upmu\\mathrm{m}$ , purity ${>}90\\mathrm{wt\\%}$ , ashes ${<}1.5\\mathrm{wt\\%}$ ) were purchased from Cheaptubes and used without further purification. Synthesis and delamination of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ MXene. $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX phase powder (average particle size $\\leq30\\upmu\\mathrm{m})$ was chemically etched by slowly adding $_{2\\mathrm{g}}$ of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ powder into a mixture of $2\\mathrm{g}$ of lithium fluoride powders in $20\\mathrm{ml}$ of $9\\mathbf{M}$ hydrochloric acid31. The reaction was kept at $35^{\\circ}\\mathrm{C}$ under magnetic stirring for $24\\mathrm{h}$ . The reaction products were washed with deionized water, then subjected to centrifugation, after which the supernatant was decanted. The washing process was repeated until the pH of the supernatant reached approximately 6, and spontaneous delamination of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ began to occur. At this point, the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ sediment was redispersed in deionized water and the resulting slurry was sonicated at $20\\mathrm{kHz}$ using a probe sonicator (Fisher Scientific) in a cooling bath at $0^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ , to ensure that the final $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ slurry contained only delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes. The resulting slurry was used without further modification or processing. \n\nPreparation of CTAB-grafted SWCNTs. CTAB-grafted SWCNTs were prepared following a procedure reported in the literature32. SWCNTs were dispersed in a $0.1\\mathrm{wt\\%}$ CTAB aqueous solution by probe sonication (Ultrasonic Processor, FS-450N) at $135\\mathrm{W}$ for $30\\mathrm{min}$ . The solution was then centrifuged at $_{10,000g}$ (Eppendorf $5804\\mathrm{R},$ , Fisher Scientific) for $20\\mathrm{min}$ to collect the SWCNT slurry at the bottom of the tube, followed by washing the slurry with distilled water. The centrifugation and washing steps were repeated three times until the residual CTAB in the solution was fully removed. The final CTAB-grafted SWCNTs were dispersed in deionized water at a concentration of around $2.{\\overset{-}{5}}\\operatorname{mg}\\operatorname{ml}^{-1}$ . \n\nPreparation of MXene films by vacuum-assisted filtration. Freestanding, binder-free $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ –SWCNT films were fabricated using vacuum-assisted filtration, in which the delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ slurry was mixed directly with CTAB-grafted SWCNTs and then filtered. The $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ slurry and SWCNTs were mixed such that the final mixture contained $10\\mathrm{{wt\\%}}$ SWCNTs. The $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ –SWCNT mixture was filtered through a surfactant-coated polypropylene membrane (Celgard 3501, Celgard). After vacuum filtration, the resulting $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ –SWCNT films were dried under vacuum at room temperature. \n\nPreparation of MXLLC films. The liquid-crystal phase that is usually observed in two-dimensional nanomaterials is the discotic nematic phase33–45, in which the nanomaterials are usually dispersed in an aqueous solution. However, nanomaterials in this phase are mostly aligned horizontally when subjected to mechanical shear fields $\\bar{3}6,46,47$ . Therefore, we intended to create high-order lamellar liquid crystals (MXLLC) in this work. \n\nTo prepare MXLLC, $10\\mathrm{mg}$ MXene and 1.1 mg SWCNTs $(10\\mathrm{wt\\%})$ ) were dispersed in an aqueous solution by mixing their corresponding solutions with calculated volumes. The SWCNTs were added to improve both the mechanical stability and the electric conductivity of the MXLLC32,48. The mixture was then sonicated using a probe sonicator for $30\\mathrm{min}$ . After fully mixing the MXene and SWCNTs, $40\\upmu\\mathrm{l}$ of the surfactant $\\mathrm{C_{12}E_{6}}$ was added, followed by additional sonication in a water bath sonicator (Branson, model 2210) for $30\\mathrm{min}$ . The mixture was then transferred to a vacuum oven to evaporate water at $40^{\\circ}\\mathrm{C}$ overnight. The final MXLLC mixture of MXene, SWCNTs and $\\mathrm{C}_{12}\\mathrm{E}_{6}$ was obtained by adding $50\\upmu\\mathrm{l}$ water, followed by sonication in a water bath for $2\\mathrm{h}$ . \n\nPreparation of liquid-crystal cells. Glass slides were rinsed twice with acetone, followed by drying with an air gun. A dilute MXene aqueous solution $({\\sim}50\\mathrm{mg}\\mathrm{ml}^{-1}),$ 1 was then spin-coated onto one of the glass slides at $^{3,000\\mathrm{rpm}}$ for 30 s (Brewer Science, Cee precision spin coater) to obtain an ultrathin layer $\\left(30\\mathrm{-}40\\mathrm{nm}\\right)$ of flat MXene coating on the glass slide. Another acetone pre-cleaned glass slide was spin-coated with $5\\mathrm{wt\\%}$ solution of cellulose acetate in cyclopentanone at $^{3,000\\mathrm{rpm}}$ for $30{\\mathsf{s}},$ , followed by drying on a hotplate at $95^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ to fully remove the solvent. The roles of the flat MXene layer and cellulose acetate will be discussed in the next section. \n\nPreparation of free-standing MXLLC films. The gel-like MXLLC was sandwiched between the flat MXene-coated and cellulose-coated slides with thickness controlled by a Mylar spacer. The liquid-crystal cell was then heated $(1^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1})$ to $42^{\\circ}\\mathrm{C}$ on a Mettler FP82 and FP90 hotplate system and slowly cooled $(1^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}),$ 1 to $32^{\\circ}\\mathrm{C}$ . This process allowed MXene liquid crystal to release internal stress in the low-order phase and then reform in the high-order phase structure at a lower temperature. \n\nAfter thermal annealing, the MXLLC cell was mechanically sheared uniaxially at a shear rate $(\\dot{\\gamma})$ of ${\\sim}50{-}100s^{-1}$ (see ‘Determination of the shear rate to align MXLLC’ for further details) to align the MXene flakes in an aqueous solution. The liquid-crystal cell was then flash-frozen in liquid nitrogen to solidify the aqueous phase, followed by opening of the cell with a razor blade. Owing to the weak layer interaction between MXene sheets, the MXLLC delaminated from the MXene coated glass, leaving them supported on the cellulose acetate layer. It should be noted that, after delamination, the flat MXene layer was bonded to MXLLC, serving as an additional current collector in the electrochemical tests. \n\nThe MXLLC along with the supported glass was immersed into acetone immediately after opening the liquid-crystal cell, and the cellulose sacrificial layer was instantly dissolved by the acetone (less than 10 s), leaving MXLLC as a free-standing film suspended in acetone. The MXLLC film was kept in acetone for $30\\mathrm{min}$ to completely remove the organic components. It was then carefully removed and transferred into ethanol for solvent exchange. \n\nThe MXLLC film suspended in ethanol was transferred to a supercritical- $\\cdot\\mathrm{CO}_{2}$ drier (Tousimis Samdri-PVT-3D), to ensure that ethanol was removed without collapse of the MXene sheets due to surface tension during the drying process. \n\nThe final MXLLC films were obtained by heating the samples in a furnace (TA Instruments SDT-Q600) under argon gas (flow rate, $100\\mathrm{ml}\\mathrm{min}^{-1}.$ ) at $550^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ to remove the surfactant. A weight loss of around $10\\mathrm{wt\\%}$ was recorded. \n\nDetermination of the shear rate to align MXLLC. Shear is known to have a profound effect on the structure of liquid crystals, and typically the change of macroscopic alignment happens when the Deborah number, $D=\\dot{\\gamma}\\tau$ , approaches one17. Here, $\\tau$ is the structural relaxation time of the molecule. The relaxation time has been found to be roughly cubically proportional19 to the molecular size a, $\\tau\\sim a^{3}$ , in simple liquids. For typical small liquid-crystal molecules with average sizes of around $1-10\\mathrm{nm}$ , reported values of $\\tau$ are between $10^{-3}$ and $10^{-4}s,$ when the liquid-crystal system approaches the nematic-to-smectic phase transition19. Considering the average size of MXene nanosheets as ${\\sim}200{-}300\\mathrm{nm}$ , the relaxation time of the MXene could be estimated to be of the order of seconds. Therefore, the critical value to achieve alignment for MXLLC could be estimated as $1{{\\mathsf{s}}}^{-1}$ . However, owing to the large size distribution of MXene nanosheets, we applied a higher shear rate $(\\dot{\\gamma}=\\frac{\\nu}{d}\\overset{-}{\\approx}50\\frac{\\-100s^{-1})}{\\~.}$ to ensure the macroscopic alignment of MXene nanosheets, where $\\nu$ is the shear velocity and $d$ is the sample thickness. \n\nFabrication of liquid-crystal cell with patterned substrates. Patterned one-dimensional microchannels made of commercially available epoxy (D.E.R. 354, Dow Chemicals) were fabricated by replica moulding from polydimethylsiloxane moulds on glass slides following a reported procedure49. An aqueous solution of MXene was sandwiched between one patterned substrate and another flat glass slide, at a thickness (controlled by the Mylar spacer) of ${\\sim}6\\upmu\\mathrm{m}$ . \n\nCharacterization. Liquid-crystal phases and alignments were confirmed from POM images under an Olympus BX61 motorized optical microscope with crossed polarizers using CellSens software. \n\nThe alignment of MXene nanosheets was also examined by SEM on a dual-beam FEI Strata DB 235 Focused Ion Beam/SEM instrument with a 5-kV electron beam. \n\nThe nanostructure of MXLLC was further characterized by SAXS with a Bruker Nonius FR591 rotating-anode X-ray generator $(\\mathrm{CuK}\\upalpha)$ together with Osmic MaxFlux optics. Samples were kept at a distance of $54\\mathrm{cm}$ from the detector, and were scanned with angles (2θ) from $0.3^{\\circ}{-5.4^{\\circ}}$ , corresponding to momentum transfer $(q)$ ranging from $0.{\\overset{\\cdot}{0}}2{-}0.38{\\overset{\\cdot}{\\mathrm{A}}}^{-1}$ . The intensity of the X-rays was measured using a 2D Bruker Hi-Star multiwire detector, and reported data were azimuthally averaged and background subtracted. \n\nElectrochemical measurements. Electrochemical measurements were performed in three-electrode Swagelok-type cells using glassy carbon as the current collector for both the working and the counter electrodes. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ –SWCNT films prepared by vacuum filtration and MXLLC films were used directly as the working electrodes, and over-capacitive activated carbon films (YP50, Kuraray) were used as the counter electrodes. An aqueous mercury sulfate $\\mathrm{(Hg/Hg_{2}S O_{4})}$ ) electrode in saturated potassium sulfate $\\mathrm{(K_{2}S O_{4})}$ was used as the reference electrode. Surfactantcoated polypropylene membranes (Celgard 3501) were used as the separators, and deaerated 3 M sulfuric acid $\\mathrm{(H}_{2}\\mathrm{SO}_{4})$ was used as the electrolyte. Electrochemical measurements, such as cyclic voltammetry, electrochemical impedance spectroscopy and galvanostatic cycling were performed using a VMP3 potentiostat (BioLogic). Scanning rates ranging from $\\bar{5}\\mathrm{mV}s^{-1}$ to $100\\mathrm{\\bar{V}}s^{-1}$ were used for the cyclic voltammetry experiments with a working potential window of $\\mathrm{\\hbar}0.9\\mathrm{V}$ ( $-0.1$ to $-1.0\\mathrm{V}$ versus $\\mathrm{Hg/Hg_{2}S O_{4)}}$ . Specific capacitances were calculated by integration of the discharge curves in the cyclic voltammetry plots using the following formula: \n\n$$\nC={\\frac{\\int I\\mathrm{d}t}{m\\Delta V}}\n$$ \n\nwhere $C$ is the specific capacitance, $I$ is the discharging current, $m$ is the mass of the working electrode and $\\Delta V$ is the voltage scan window which is $0.9\\mathrm{V}$ for all of the cyclic voltammetry scans in this work. Galvanostatic charging and discharging was performed with the same potential window of $0.9\\mathrm{V},$ and capacitance was also calculated from the discharging curve. Electrochemical impedance spectroscopy was performed at the resting potentials of the cells with a signal peak-to-peak amplitude of $10\\mathrm{mV}$ and frequencies ranging from $10\\mathrm{mHz}$ to $200\\mathrm{kHz}$ . \n\nIon-diffusion mechanism. The ion-diffusion mechanism in MXLLC films was investigated by analysing the function curves of peak current $(i_{\\mathrm{p}})$ against scan rate (v) from the cyclic voltammograms, following the power law dependence of $i_{\\mathrm{p}}$ on v, $i_{\\mathrm{p}}=a\\nu^{b}$ , where $a$ and $b$ are adjustable parameters. The value of $b$ provides important insights into the charge-storage kinetics: when $b$ is close to 1, it indicates a high-rate capacitive storage mechanism, and $b\\approx0.5$ is the signature of slow semi-infinite diffusion. The values of $^{b}$ for the MXLLC films are 0.95, 0.91 and 0.69 for film thicknesses of $40\\upmu\\mathrm{m}$ , $200\\upmu\\mathrm{m}$ and $320\\upmu\\mathrm{m},$ respectively, for scan rates ranging from 5 to $2,000\\mathrm{mVs^{-1}}$ . \n\nData availability. The data supporting the findings of this study are available within the paper, the Supplementary Information and its Extended Data files. Raw data are available from the authors upon reasonable request. \n\n31.\t Shahzad, F. et al. Electromagnetic interference shielding with 2D transition metal carbides (MXenes). Science 353, 1137–1140 (2016). \n32.\t Xie, X. et al. Porous heterostructured MXene/carbon nanotube composite paper with high volumetric capacity for sodium-based energy storage devices. Nano Energy 26, 513–523 (2016). \n33.\t Hogan, B. T., Kovalska, E., Craciun, M. F. & Baldycheva, A. 2D material liquid crystals for optoelectronics and photonics. J. Mater. Chem. C 5, 11185–11195 (2017). \n34.\t Lin, F., Tong, X., Wang, Y., Bao, J. & Wang, Z. M. Graphene oxide liquid crystals: synthesis, phase transition, rheological property, and applications in optoelectronics and display. Nanoscale Res. Lett. 10, 435 (2015). \n35.\t Aboutalebi, S. H., Gudarzi, M. M., Zheng, Q. B. & Kim, J.-K. Spontaneous formation of liquid crystals in ultralarge graphene oxide dispersions. Adv. Funct. Mater. 21, 2978–2988 (2011). \n36.\t Akbari, A. et al. Large-area graphene-based nanofiltration membranes by shear alignment of discotic nematic liquid crystals of graphene oxide. Nat. Commun. 7, 10891 (2016). \n37.\t Behabtu, N. et al. Spontaneous high-concentration dispersions and liquid crystals of graphene. Nat. Nanotechnol. 5, 406–411 (2010). \n38.\t Dan, B. et al. Liquid crystals of aqueous, giant graphene oxide flakes. Soft Matter 7, 11154–11159 (2011). \n39.\t He, L. et al. Graphene oxide liquid crystals for reflective displays without polarizing optics. Nanoscale 7, 1616–1622 (2015). \n40.\t Kim, J. E. et al. Graphene oxide liquid crystals. Angew. Chem. Int. Ed. 50, 3043–3047 (2011). \n41.\t Liu, H. et al. A lyotropic liquid-crystal-based assembly avenue toward highly oriented vanadium pentoxide/graphene films for flexible energy storage. Adv. Funct. Mater. 27, 1606269 (2017). \n42.\t Liu, Y., Xu, Z., Gao, W., Cheng, Z. & Gao, C. Graphene and other 2D colloids: Liquid crystals and macroscopic fibers. Adv. Mater. 29, 1606794 (2017). \n43.\t Shen, T.-Z., Hong, S.-H. & Song, J.-K. Electro-optical switching of graphene oxide liquid crystals with an extremely large Kerr coefficient. Nat. Mater. 13, 394–399 (2014). \n44.\t Xu, Z. & Gao, C. Graphene chiral liquid crystals and macroscopic assembled fibres. Nat. Commun. 2, 571 (2011). \n45.\t Zakri, C. et al. Liquid crystals of carbon nanotubes and graphene. Philos. Trans. R. Soc. A 371, 20120499 (2013). \n46.\t Hogan, B. T. et al. Dynamic in-situ sensing of fluid-dispersed 2D materials integrated on microfluidic Si chip. Sci. Rep. 7, 42120 (2017). \n47.\t Kravets, V. G. et al. Engineering optical properties of a graphene oxide metamaterial assembled in microfluidic channels. Opt. Express 23, 1265–1275 (2015). \n48.\t Mashtalir, O., Lukatskaya, M. R., Zhao, M.-Q., Barsoum, M. W. & Gogotsi, Y. Amine-assisted delamination of $N b_{2}C$ MXene for Li-ion energy storage devices. Adv. Mater. 27, 3501–3506 (2015). \n49.\t Zhang, Y., Lo, C.-W., Taylor, J. A. & Yang, S. Replica molding of high-aspect-ratio polymeric nanopillar arrays with high fidelity. Langmuir 22, 8595–8601 (2006). \n\n![](images/603d7a58f5a0a880266aaf98f30e1b543abd98de3b1aaf4b4230238925614244.jpg) \nExtended Data Fig. 1 | Size statistics of MXene nanosheets. \n\n
Avg. LengthAvg.widthAvg.Flake dimension (width + length)Aspect Ratio (L:W)
274.17 ± 79.53 nm163.19 ± 50.49 nm218.68 ± 47.44 nm1.68
\n\na, SEM image of the nanosheets. The flake dimensions used to report the length and width of the sheets are marked. b, Size distribution of MXene nanosheets, measured from SEM over 250 sheets. c, Average sizes of the nanosheets. \n\n![](images/72280fe62a0295536a4640962a5430ed9dee4dec0b26b6a008cd2da05cd0bd08.jpg) \n\nExtended Data Fig. 2 | POM images of MXene aqueous solutions. a, At a concentration of $50\\mathrm{mg}\\mathrm{ml}^{-1}$ , the MXene solution shows a nearly isotropic phase with low birefringence under crossed polarizers. b, At a concentration of $250\\mathrm{mg}\\mathrm{ml}^{-1}$ , higher birefringence starts to appear. A nematic phase is formed, as clearly indicated from the Schlieren texture shown in the inset. c, d, POM images of the slow-appearing MXene liquidcrystal phase on top of one-dimensional microchannels at two polarizer angles: $45^{\\circ}$ (c) and $0^{\\circ}$ (d). Higher birefringence starts to appear when water evaporates, and the resulting nematic liquid-crystal phase of MXene can be well aligned with microchannels. The microchannels used here have the following dimensions: diameter $2\\upmu\\mathrm{m}$ , spacing $2\\upmu\\mathrm{m}$ and depth $1.5\\upmu\\mathrm{m}$ . The Onsager theory of liquid crystals predicts the formation of the liquidcrystal phase as a function of the volume fraction of molecules in a media: low volume fraction gives an isotropic phase, and high volume fraction \n\ngives a liquid-crystal phase. The empirical value of the critical volume fraction of liquid-crystal phase formation can be estimated by $\\varphi\\approx\\frac{4T}{W}$ , where $\\varPhi$ is the critical volume fraction, $W$ and $T$ are the width and thickness of the nanosheet, respectively. In our MXene system, $\\varPhi$ is estimated to be around $2\\mathrm{vol}\\%$ , which is equivalent to about $80\\mathrm{mg}\\mathrm{ml}^{-1}$ of MXene nanosheets in aqueous solution. However, because the MXene nanosheets are highly polydisperse in terms of size, and the surface charges differ from system to system, the critical value of $\\varPhi$ could vary in experiments. In this work, we demonstrated the isotropic phase of MXene liquid crystal at around $50\\mathrm{mg}\\mathrm{ml}^{-1}$ , in good agreement with theory, and we showed the nematic phase of MXene at around $250\\mathrm{mg}\\mathrm{ml}^{-1}$ . This concentration was chosen to be sufficiently high above the critical value of $\\varPhi$ such that a liquid-crystal phase could be ensured. \n\n![](images/c9f9498dbb77e1b71aded14239e736e95d672a9c18c5c79e1c40230b24c59171.jpg) \nExtended Data Fig. 3 | SEM image of nematic MXene liquid crystal after mechanical shear. Horizontally aligned MXene nanosheets are obtained. \n\n# RESEARCH Letter \n\n![](images/aba2214bc623cbbe24fed02705d953c853dadc37abd9b50d35911c3bc6d6961f.jpg) \nExtended Data Fig. 4 | Schematic of the preparation of MXLLC films. a, Preparation of the MXLLC slurry. b, Fabrication of the liquid-crystal cell. c, Separation of the MXLLC layer from the liquid-crystal cell. d, The free-standing MXLLC film obtained after supercritical drying. \n\n![](images/7436bde65747d0d5b8f411f3853c679a86dde17daefe37a2add57c236cb4ac2d.jpg) \nExtended Data Fig. 5 | POM and SEM images of MXLLC films. a, b, POM images of MXLLC before (a) and after (b) shear. The inset of b shows the POM image of the MXLLC with the shear direction parallel to the polarizer. $\\mathbf{c-h}$ , Views of the MXLLC film from SEM: random alignment before shear (c), vertical alignment after shear (d), lateral views (e, f), front views $(\\mathbf{g},\\mathbf{h})$ . Dashed red lines indicate the bending directions of the MXene layers. \n\n![](images/fcb8a7d1054005c898bbe2042bbe896c35dac34bff033a9f5dc6988ee9e06fae.jpg) \nExtended Data Fig. 6 | AFM images of the spin-coated flat MXene film. a, Height map. b, Film thickness measured across the boundary of the film and the glass. The thickness of the flat MXene film is estimated to be about $30\\mathrm{nm}$ . \n\n![](images/5ce55a9e49599f4f95a6d52865aeb30fc7ea644e948f07940292aa04e611cd10.jpg) \nExtended Data Fig. 7 | SEM images of a vacuum-filtered MXene– SWCNT paper with a thickness of around $35\\upmu\\mathrm{m}$ . a, The full crosssection of the freestanding film. b, A higher-magnification image of the \n\ntop portion of a. Both images show horizontally stacked layers of MXene nanosheets interpenetrated with SWCNTs, a configuration that has been reported to facilitate ion diffusion1. \n\n![](images/e43914d8bc8398974780619aa7c789fd79b2fe1611227144fa7c8a3602b01e3d.jpg) \n\nExtended Data Fig. 8 | Plots of the anodic peak current against scan rate and peak separation against scan rate. a, Plot of the peak current of the second pair of redox peaks seen at $-0.4\\:\\mathrm{V}$ and $-0.6\\mathrm{V}$ versus $\\mathrm{Hg/HgSO_{4}}$ in the voltammograms for the MXLCC electrodes in Fig. 3a. b, Plot of the peak separation $(\\Delta E_{\\mathrm{p}})$ for the second pair of redox peaks; the dashed line corresponds to the expected trend for a quasi-electrochemical process2. From a it can be seen that the trend of the current against scan rate of the anodic peak of the second pair of redox peaks is similar (Fig. 3c) to that of the main peaks at $-0.8\\mathrm{V}$ versus $\\mathrm{Hg/HgSO_{4}}$ (Fig. 3a), which are characteristic of ${\\mathrm{Ti}_{3}}{\\mathrm{C}_{2}}{\\mathrm{T}_{x}}$ . The main difference in behaviour for this second pair of peaks compared with previous reports on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ can be seen in b. Previous characterization of the peak separation against the scan rate for the redox peaks in thin (around $90\\mathrm{nm}$ ) $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ electrodes showed a region at low scan rates that corresponds to quasi-equilibrium behaviour3; it is clear from b that this is not the case for the second pair of redox peaks of the MXLLC electrodes. The primary reason for this is probably the large difference in thickness of the MXLLC electrodes $(200\\upmu\\mathrm{m})$ compared with previous reports of thin $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ electrodes $(90\\mathrm{nm})$ ). \n\n![](images/5426bedf5025f7ae7973ad6b7b63777ff5b2e79d5da02ca998dc1bb3958be2a3.jpg) \n\nExtended Data Fig. 9 | Cyclic voltammograms of pure $\\mathbf{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ vacuum-filtered paper and MXLLC film. a, For the second pair of redox peaks at $0.6\\mathrm{V}$ versus the reference, the current grows slightly during cycling and then stabilizes during continuous cycling. b, The current will fade if the cell is allowed to rest. This pair of peaks is thought to originate from changes occurring in the transition-metal surface of the MXene during cycling and will be the subject of further studies. It is thought that these peaks are more pronounced in the cyclic voltammograms of the \n\nMXLLC samples owing to the large amount of active material surface that is exposed to the electrolyte in the MXLLC samples relative to the vacuumfiltered papers. c, d, Cyclic voltammograms of a $35\\mathrm{-}\\upmu\\mathrm{m}$ -thick vacuumfiltered MXene paper (c) and a $40\\mathrm{-}\\upmu\\mathrm{m}$ -thick MXLLC film (d). For similar film thicknesses, MXLLC films have much better rate-handling ability compared to the vacuum-filtered papers, as only a small decay of the cyclic voltammogram is observed until high scan rates are used. \n\n![](images/07faa06fd69cc896b49fecfe031ec66f33a829fc81e0757a19ead93473174eaa.jpg) \nExtended Data Fig. 10 | Capacitance retention as a function of scan rate for both vacuum-filtered films and MXLLC films. All data points are normalized to the capacitance value at $10\\mathrm{mVs}^{-1}$ for each sample curve, respectively. At $2\\hat{,}000\\mathrm{mVs^{-1}}$ , vacuum-filtered MXene papers retain around $14\\%$ ( $35\\ensuremath{\\upmu\\mathrm{m}}$ thick) and $30\\%$ ( $6\\upmu\\mathrm{m}$ thick) capacitance, whereas \nMXLLC films maintain more than $75\\%$ capacitance over a wide range of film thickness from $40\\upmu\\mathrm{m}$ to $200\\upmu\\mathrm{m}$ . However, in thicker $(320\\upmu\\mathrm{m})$ MXLLC films, the retention curve starts to behave similarly to that of thin vacuum-filtered paper $(6\\upmu\\mathrm{m})$ . These data again suggest that the optimal thickness of the working-electrode film of MXLLC is $200\\upmu\\mathrm{m}$ . " + }, + { + "id": "10.1038_s41467-018-05760-x", + "DOI": "10.1038/s41467-018-05760-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-05760-x", + "Relative Dir Path": "mds/10.1038_s41467-018-05760-x", + "Article Title": "High efficiency planar-type perovskite solar cells with negligible hysteresis using EDTA-complexed SnO2", + "Authors": "Yang, D; Yang, RX; Wang, K; Wu, CC; Zhu, XJ; Feng, JS; Ren, XD; Fang, GJ; Priya, S; Liu, SZ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Even though the mesoporous-type perovskite solar cell (PSC) is known for high efficiency, its planar-type counterpart exhibits lower efficiency and hysteretic response. Herein, we report success in suppressing hysteresis and record efficiency for planar-type devices using EDTA-complexed tin oxide (SnO2) electron-transport layer. The Fermi level of EDTA-complexed SnO2 is better matched with the conduction band of perovskite, leading to high open-circuit voltage. Its electron mobility is about three times larger than that of the SnO2. The record power conversion efficiency of planar-type PSCs with EDTA-complexed SnO2 increases to 21.60% (certified at 21.52% by Newport) with negligible hysteresis. Meanwhile, the low-temperature processed EDTA-complexed SnO2 enables 18.28% efficiency for a flexible device. Moreover, the unsealed PSCs with EDTA-complexed SnO2 degrade only by 8% exposed in an ambient atmosphere after 2880 h, and only by 14% after 120 h under irradiation at 100 mW cm(-2).", + "Times Cited, WoS Core": 1244, + "Times Cited, All Databases": 1290, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000441382000017", + "Markdown": "# High efficiency planar-type perovskite solar cells with negligible hysteresis using EDTA-complexed SnO2 \n\nDong Yang1,2, Ruixia Yang1, Kai Wang 2, Congcong Wu2, Xuejie Zhu1, Jiangshan Feng1, Xiaodong Ren1, Guojia Fang 3, Shashank Priya 2 & Shengzhong (Frank) Liu1,4 \n\nEven though the mesoporous-type perovskite solar cell (PSC) is known for high efficiency, its planar-type counterpart exhibits lower efficiency and hysteretic response. Herein, we report success in suppressing hysteresis and record efficiency for planar-type devices using EDTAcomplexed tin oxide $(\\mathsf{S n O}_{2})$ ) electron-transport layer. The Fermi level of EDTA-complexed $\\mathsf{S n O}_{2}$ is better matched with the conduction band of perovskite, leading to high open-circuit voltage. Its electron mobility is about three times larger than that of the $\\mathsf{S n O}_{2}$ . The record power conversion efficiency of planar-type PSCs with EDTA-complexed $\\mathsf{S n O}_{2}$ increases to $21.60\\%$ (certified at $21.52\\%$ by Newport) with negligible hysteresis. Meanwhile, the lowtemperature processed EDTA-complexed $\\mathsf{S n O}_{2}$ enables $18.28\\%$ efficiency for a flexible device. Moreover, the unsealed PSCs with EDTA-complexed $\\mathsf{S n O}_{2}$ degrade only by $8\\%$ exposed in an ambient atmosphere after $2880{\\mathfrak{h}},$ and only by $14\\%$ after $120{\\mathsf{h}}$ under irradiation at $100\\mathsf{m w c m}^{-2}$ . \n\nwing to the singular properties, including tuned band gap, small exciton energy, excellent bipolar carrier transport, long charge diffusion length, and amazingly high tolerance to defects1–7, organometal halide perovskites have been projected to be promising candidates for a multitude of optoelectronic applications, including photovoltaics, light emission, photodetectors, X-ray imaging, lasers, gamma-ray detection, subwavelength photonic devices in a long-wavelength region, etc.8–14. The rapid increase efficiency in a solar cell based on organometal halide perovskites validates its promise in photovoltaics. In the last few years, the power conversion efficiency (PCE) of mesoporous-type perovskite solar cells (PSCs) has increased to $23.3\\%$ by optimizing thin-film growth, interface, and absorber materials15–17. As of today, almost all PSCs with high PCE are based on mesoporous-type PSCs that often require high temperature to sinter the mesoporous layer for the best performance, compromising its low-cost advantage and limiting its application in flexible and tandem devices16,17. In order to overcome this issue, planar-type PSC comprising of stacked planar thin films has been developed18,19 using low-temperature and low-cost synthesis processes20–22 since the long charge diffusion length and bipolar carrier properties of perovskites23,24. However, compared to the mesoporous-type PSC, its planar-type counterpart suffers from significant lower certified PCE18,25. \n\nIn a typical planar-type PSC, the perovskite absorber usually inserts between the electron-transport layer (ETL) and the holetransport layer (HTL) to achieve inverted $\\operatorname{p-i-n}$ or regular $\\mathtt{n-i-p}$ configuration21. Generally, the inverted device structure utilizing fullerene ETL displays very low hysteresis, however, it usually yields lower PCE, not to mention that fullerene is very expensive26,27. Therefore, research has focused on $\\mathtt{n-i-p}$ architecture to provide low cost and high efficiency28,29. Even though ETL-free planar-type PSCs have been reported30,31, their highest PCE is only $14.14\\%$ , significantly lower than that of the cells with ETL, demonstrating the importance of the ETL in this configuration of PSCs. A suitable ETL should meet some basic requirements for high device efficiency32. For instance, decent optical transmittance to ensure enough light is transmitted into the perovskite absorber, matched energy level with the perovskite materials to produce the expected open-circuit voltage $(V_{\\mathrm{oc}})$ , and high electron mobility to extract carriers from the active layer effectively in order to avoid charge recombination, etc. Fast carrier extraction is desired to restrict charge accumulation at the interface due to ion migration for reduced hysteresis in the planar-type PSCs. Thus, emphasis has been on developing high-quality ETLs with suitable energy level and high electron mobility for high PCE devices. \n\nThus far, $\\mathrm{TiO}_{2}$ is still the most widely used ETL in highefficiency $\\mathtt{n-i-p}$ planar-type PSCs due to its excellent photoelectric properties33. However, the electron mobility of $\\mathrm{TiO}_{2}$ ETL is too low (ca. $10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1})$ to match with high hole mobility of commonly used HTLs (ca. $10^{-3}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-\\mathrm{\\check{l}}};$ , leading to charge accumulation at the $\\mathrm{TiO}_{2}.$ /perovskite interface that causes hysteresis and reduced efficiency34. There have been extensive efforts in developing low-temperature $\\mathrm{TiO}_{2}$ ETL, such as exploring low- temperature synthesis processes through doping and chemical engineering. The results shown by Tan et al. demonstrate that use of chlorine to modify the $\\mathrm{TiO}_{2}$ microstructure at low temperatures provides promising PCE of $20.1\\%$ 35. Recently, $\\mathrm{SnO}_{2}$ has been demonstrated as an alternative ETL to replace $\\mathrm{TiO}_{2}$ , owing to its more suitable energy level relative to perovskite and higher electron mobility. Ke et al. first used $\\mathrm{SnO}_{2}$ thin film as an ETL in regular planar-type PSCs and demonstrated a PCE of $16.02\\%$ with improved hysteresis36. Later, the $\\mathrm{SnO}_{2}{\\mathrm{-TiO}}_{2}$ (planar and mesoporous) composite layers were developed to enhance the performance of the $\\mathrm{PSC}s^{37,38}$ . It is noteworthy to mention that $\\mathrm{Al}^{3+}$ -doped $\\mathrm{SnO}_{2}$ provides even better performance39. Subsequently, a variety of methods, such as solution deposition, atomic layer deposition, chemical bath deposition, etc.40–42 have been developed for synthesizing $\\mathrm{SnO}_{2}$ thin film to improve the performance of planar-type $\\bar{\\mathrm{PSCs}}^{43}$ . Recently, Jiang et al. developed the $\\mathrm{SnO}_{2}$ nanoparticles as the ETL and demonstrated a certified efficiency as high as $19.9\\%$ with very low hysteresis21. However, the PCE of the planar-type PSCs is still lower than that of the mesoporous-type devices likely due to charge accumulation at the ETL/perovskite interface caused by relatively low electron mobility of the $\\mathrm{ETL^{44}}$ . It is expected that better PSC performance will be achieved by increasing electron mobility of the ETLs. \n\nEthylene diamine tetraacetic acid (EDTA) provides excellent modification of ETLs in organic solar cells owing to its strong chelation function. Li et al. have employed EDTA to passivate $\\mathrm{{}}Z\\mathrm{{nO}}$ -based ETL and demonstrated improved performance of the organic solar cells45. However, when the EDTA– $.Z\\mathrm{nO}$ layer is used in the present perovskite cells, the hydroxyl groups or acetate ligands on the $\\mathrm{\\bar{Z}n O}$ surface react with the perovskite and proton transfer reactions occur at the perovskite $/Z_{\\mathrm{{nO}}}$ interface, leading to poor device performance46. \n\nIn the present work, we realize an EDTA-complexed $\\mathrm{SnO}_{2}$ (E$\\mathrm{SnO}_{2}^{\\cdot}$ ) ETLs by complexing EDTA with $\\mathrm{SnO}_{2}$ in planar-type PSCs to attain PCE as high as $21.60\\%$ , and certified PCE reaches to $21.52\\%$ , the highest reported value to date for the planar-type PSCs. Owing to the low-temperature processing for $\\bar{\\mathrm{E}}{\\cdot}\\mathrm{SnO}_{2}$ , we fabricate flexible PSCs, and the PCE reaches to $18.28\\%$ . Besides, the PSCs based on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ show negligible hysteresis because of the eliminated charge accumulation at the perovskite/ETL interface. We find that the electron mobility of $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ increases by about three times compared to that of $\\mathrm{SnO}_{2}$ , leading to negligible current density–voltage $\\left(J-V\\right)$ hysteresis due to improved electron extraction from the perovskite absorber21. Furthermore, we find that $\\mathrm{SnO}_{2}$ surface becomes more hydrophilic upon EDTA treatment, which decreases the Gibbs free energy for heterogeneous nucleation, resulting in high quality of the perovskite film. \n\n# Results \n\nFabrication and characterization of $\\mathbf{E}{-}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ . It is well known that EDTA can react with transition metal oxide to form a complex, because it can provide its lone-pair electrons to the vacant $d$ -orbital of the transition metal atom47. Thus, EDTA was chosen to modify the $\\mathrm{SnO}_{2}$ to improve its performance. Supplementary Fig. 1a describes the chemical reaction that occurred when the $\\mathrm{SnO}_{2}$ was treated using the EDTA aqueous solution, resulting in the formation of a five-membered ring chelate. The images of EDTA, $\\mathrm{SnO}_{2}.$ , and $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ samples are shown in Supplementary Fig. 1b. It is apparent that the unmodified EDTA and $\\mathrm{SnO}_{2}$ samples are transparent, while EDTA-treated $\\mathrm{SnO}_{2}$ turned into milky white. Supplementary Fig. 2 compares the Fouriertransform infrared spectroscopy (FTIR) spectra of the $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ solution measured in the freshly prepared condition and again after it was stored in an ambient atmosphere for 2 months. It is clear that there is no obvious difference between the two solutions indicating the high stability. \n\nFigure 1a shows the X-ray photoelectron spectra (XPS) for EDTA, $\\mathrm{SnO}_{2}$ , and $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ films deposited on quartz substrates. In order to reduce the charging effect, the exposed surface of the quartz substrate was coated with a conductive silver paint and connected to the ground. We calibrated the binding energy scale for all XPS measurements to the carbon 1s line at $284.8\\mathrm{eV}$ . It is clear from these measurements that $\\mathrm{SnO}_{2}$ shows only peaks attributed to Sn and O. After the EDTA treatment, the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ film shows an additional peak located at ca. $400\\mathrm{eV}$ , ascribed to N. Meanwhile, the Sn $3d$ peaks from $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ are shifted by ca. \n\n![](images/d5e873a000290f756f289c575a005a704568c331f81d0c3965071ef3b97364b8.jpg) \nFig. 1 Characterization of the ETLs. a XPS and b FTIR spectra of EDTA, $\\mathsf{S n O}_{2},$ and $\\mathsf{E}\\mathrm{-}\\mathsf{S n O}_{2}$ films deposited on quartz substrates. c AFM topographical images of EDTA, $\\mathsf{S n O}_{2},$ and $\\mathsf{E}{-}\\mathsf{S n O}_{2}$ films. d Schematic illustration of Fermi level of EDTA, $\\mathsf{S n O}_{2},$ and $\\mathsf{E}{-}\\mathsf{S n O}_{2}$ relative to the conduction band of the perovskite layer. The Fermi level of EDTA, $\\mathsf{S n O}_{2},$ and $\\mathsf{E}{-}\\mathsf{S n O}_{2}$ is measured by KPFM, and the conduction and valence band of the perovskite materials are obtained from the previous report74. e Optical transmission spectra of EDTA, $\\mathsf{S n O}_{2},$ and $\\mathsf{E}{-}\\mathsf{S n O}_{2}$ films on ITO substrates. f Electron mobility for EDTA, $\\mathsf{S n O}_{2},$ and $\\mathsf{E}{-}\\mathsf{S n O}_{2}$ using the SCLC model, and the inset shows the device structure of ITO/Al/ETL/Al \n\n$0.16\\mathrm{eV}$ in contrast to the pristine $\\mathrm{SnO}_{2}$ (Supplementary Fig. 3), indicating that EDTA is bound to the $\\mathrm{SnO}_{2}$ . \n\nFTIR was used to study the interaction between $\\mathrm{SnO}_{2}$ and EDTA. As shown in Fig. 1b, the peaks around $2895\\mathrm{cm}^{-1}$ and $1673\\mathrm{cm}^{-1}$ belong to $\\mathrm{C}{\\mathrm{-}}\\mathrm{H}$ and $\\scriptstyle{\\mathrm{C=O}}$ stretching vibration in the EDTA, respectively. The characteristic peaks of $\\mathrm{SnO}_{2}$ observed at ca. $701\\mathrm{cm}^{-1}$ and $549\\mathrm{cm}^{-1}$ are due to $_{\\mathrm{O-Sn-O}}$ stretch and the $S\\mathrm{n-O}$ vibration, respectively48. In addition, the peak at $1040\\mathrm{cm}$ $^{-1}$ in the $\\mathrm{SnO}_{2}$ film is attributed to $_{\\mathrm{O-O}}$ stretching vibration due to oxygen adsorption on the $\\mathrm{SnO}_{2}$ surface49. For the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ sample, the characteristic peaks of $\\mathrm{SnO}_{2}$ shift to $713\\mathrm{cm}^{-1}$ and $563\\mathrm{\\bar{cm}^{-1}}$ , and the $\\mathrm{C-H}$ and $\\mathrm{C=}0$ stretching vibration peaks shift to $2913\\mathrm{cm}^{-1}$ and $1624\\mathrm{cm}^{-1}$ , further demonstrating that the EDTA is indeed complexed with $\\mathrm{SnO}_{2}$ . \n\nAtomic force microscopy (AFM) images of EDTA, $\\mathrm{SnO}_{2}$ , and $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ films deposited on the ITO substrates are shown in Fig. 1c. The data reveal that the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ film shows the smallest root-mean-square roughness of $2.88\\mathrm{nm}$ , a key figure-of-merit for the $\\mathrm{PSC}s^{50}$ . We also measured their Fermi level by Kelvin probe force microscopy (KPFM), with the surface potential images shown in Supplementary Fig. 4, and the calculated details are described in Supplementary Note 1. Figure 1d provides energy band alignment between perovskites and different ETLs. The Fermi level of $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ is very close to the conduction band of perovskite, which is beneficial for enhancing $V_{\\mathrm{oc}}^{51}$ . \n\nFigure 1e shows the optical transmission spectra of EDTA, $\\mathrm{SnO}_{2}^{\\overline{{}}}$ , and $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ films coated on ITO. All these samples display high average transmittance in the visible region, demonstrating good optical quality. In addition, the electron mobility of various \n\n![](images/8af989966cf34c7e032f301e840929863bf408be58198d7c21fdaedd78d2f2d1.jpg) \nFig. 2 The morphology of perovskite films deposited on different substrates. Top-view scanning electron microscope (SEM) images of perovskite films coated on a EDTA, b $\\mathsf{S n O}_{2},$ and c $\\mathsf{E}{-}\\mathsf{S n O}_{2}$ substrates. d The grain size distribution of perovskite deposited on various substrates \n\nETLs was measured using the space charge-limited current (SCLC) method20, as shown in Fig. 1f. It is found that electron mobility of $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ is $2.27\\times10^{-3}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}.$ , significantly larger than those of the EDTA $(3.56\\times10^{-5}\\mathrm{cm}^{2}\\mathrm{V}^{-\\ddot{\\Gamma}}s^{-1})$ and the $\\mathrm{SnO}_{2}$ $(9.92\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1})$ . It is known that the electron mobility is a key figure-of-merit for ETLs in PSCs. Supplementary Fig. 5 shows the electron injection models for $\\mathrm{ITO}/\\mathrm{SnO}_{2}$ or E$\\mathrm{SnO}_{2}/$ perovskite/PCBM/Al structures, with their corresponding current density–voltage $\\left(J-V\\right)$ curves, and the details are described in Supplementary Note 2. It is apparent that the high electron mobility effectively promotes electron transfer in the PSCs, reduces charge accumulation at the ETL/perovskite interface, improves efficiency, and suppresses hysteresis for the $\\mathrm{PSC}s^{21}$ . \n\nPerovskite growth mechanism. The quality of the perovskite films, including grain size, crystallinity, surface coverage, etc., is very important for high-performance PSCs. For a consistent microstructure, a solution deposition technique was used to fabricate perovskite films on EDTA, $\\mathrm{SnO}_{2},$ and $\\bar{\\mathrm{E}}{\\cdot}\\mathrm{SnO}_{2}$ substrates. Figure 2a–c shows the morphology of the perovskite films deposited on different ETLs. It is clear from these images that continuous pinhole-free films with full surface coverage were obtained. Figure 2d shows the distribution diagram with an average grain size of about $309\\mathrm{nm}$ for the perovskite coated on $\\mathrm{SnO}_{2}$ . The grain size increased to about $518\\mathrm{nm}$ for the EDTA sample. Surprisingly, the average perovskite grain size is further enhanced to as much as about $828\\mathrm{nm}$ (Fig. 2c, d) for the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ substrates. \n\nAccording to the established model for nucleation and growth of thin films52,53, the perovskite formation process can be divided into four steps: (i) formation of a crystal nucleus, (ii) evolution of nuclei into an island structure, (iii) formation of a networked microstructure, and (iv) growth of networks into a continuous film. The Gibbs free energy for heterogeneous nucleation in the first step can be expressed as Eq. (1) \n\n$$\n\\b\\triangle{G}_{\\mathrm{heterogeneous}}=\\triangle{G}_{\\mathrm{homogeneous}}\\times\\b{f}(\\theta)\n$$ \n\nwherein $f(\\theta)=(2{-}3\\cos\\theta+\\cos^{3}\\theta)/4^{54}$ , and $\\theta$ is the contact angle of the precursor solution. Since the magnitude of $\\theta$ varies in the range of $[0,\\pi/2]$ , the larger the $\\theta$ is, the smaller is the magnitude of cos $\\theta,$ and therefore larger is the parameter $f(\\theta)\\in[0,1]$ . In other words, a smaller contact angle results in reduced Gibbs free energy for heterogeneous nucleation, thereby assisting the nucleation process. Higher nucleation density will promote the film densification process53. Compared to EDTA and $\\mathrm{SnO}_{2}$ , E$\\mathrm{SnO}_{2}$ shows the smallest contact angle $(20.67^{\\circ}$ , Supplementary Fig. 6), resulting in the wettability interface for the perovskite $\\cdot55\\substack{-57}$ . Thus, the perovskite coated on the $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ exhibits better crystallinity (Supplementary Fig. 7) and full surface coverage (Fig. 2c). In addition, the small contact angle of the substrate provides the low surface energy58, leading to increased grain size during the growth of the networked structure53, as observed in the SEM measurements. \n\nCharge transfer dynamics. The electron-only devices with the structure of ITO/ETL/perovskite/PCBM/Ag were fabricated to evaluate the trap density of perovskite deposited on different substrates. Figure 3a shows the dark current–voltage $\\left(I-V\\right)$ curves of the electron-only devices. The linear correlation (dark yellow line) reveals an ohmic-type response at low bias voltage, when the bias voltage is above the kink point, which defines as the trapfilled limit voltage $(V_{\\mathrm{TFL}})$ , the current nonlinearly increases (cyan line), indicating that the traps are completely filled. The trap density $(N_{\\mathrm{t}})$ can be obtained using Eq. (2) \n\n$$\nN_{\\mathrm{t}}=\\frac{2\\varepsilon_{0}\\varepsilon V_{\\mathrm{TFT}}}{e L^{2}}\n$$ \n\nwhere $\\scriptstyle{\\varepsilon_{0}}$ is the vacuum permittivity, $\\varepsilon$ is the relative dielectric constant of $\\mathrm{FA}_{0.95}\\mathrm{Cs}_{0.05}\\mathrm{Pb}\\mathrm{I}_{3}$ $\\mathbf{\\dot{\\varepsilon}}=62.\\dot{2}3)^{59}$ , $e$ is the electron charge, and $L$ is the thickness of the film. The trap densities of the perovskite film coated on $\\mathrm{SnO}_{2}$ and EDTA substrates are $1.93\\times\\mathrm{\\dot{1}0^{16}}$ and $1.27\\times10^{16}\\mathrm{cm}^{-3}$ , respectively. Interestingly, the trap density is reduced to as low as $8.\\dot{97}\\times10^{1\\dot{5}}\\mathrm{cm}^{-3}$ for the film deposited on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ . The significantly lower trap density is related to low grain boundary density in the perovskite film (Fig. 2). \n\n![](images/b1d6322d1e6c81146ffd12d84e79cc6395ac9e4db9c3ce4c7141147b65b49f08.jpg) \nFig. 3 The charge transfer between perovskite and different ETLs. a Dark I–V curves of the electron-only devices with the $V_{\\mathsf{T F L}}$ kink points. The inset shows the structure of the electron-only device. b Steady-state PL and c TRPL spectra with an excitation intensity of $3\\upmu\\uptau m^{-2}$ of perovskite films deposited on different substrates \n\nFigure $^{3\\mathrm{b}}$ shows the steady-state photoluminescence (PL) spectra of the perovskite deposited on different substrates. Compared with other samples, significant PL quench is observed in the $\\mathrm{ITO/E}{\\cdot}\\mathrm{SnO}_{2}/$ /perovskite, demonstrating that the $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ has the most appealing merits as the highest electron mobility (Fig. 1f). Figure 3c shows the normalized time-resolved PL (TRPL) for perovskite coated on various ETLs. The lifetime and the corresponding amplitudes are listed in Supplementary Table 1. Generally, the slow decay component $(\\tau_{1})$ is attributed to the radiative recombination of free charge carriers due to traps in the bulk, and the fast decay component $(\\tau_{2})$ is originated from the quenching of charge carriers at the interface60. The glass/ perovskite sample shows the longest lifetime under excitation intensity of $3\\mathrm{~}\\mathrm{\\bar{\\upmu}}{\\mathrm{I}\\mathrm{cm}^{-2}}$ . For perovskite coated on the ITO substrate, the lifetime is decreased to more than half due to the charge transfer from perovskite into ITO. For EDTA/perovskite and $\\mathrm{SnO}_{2},$ perovskite samples, both the fast and slow decay lifetimes are very similar, and $\\tau_{1}$ dominates the PL decay for both samples, indicating severe recombination before they were extracted. When the perovskite is deposited on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}.$ , both $\\tau_{1}$ and $\\tau_{2}$ were shortened to 14.16 ns and 0.97 ns, with a proportion of $45.32\\%$ and $54.68\\%$ , respectively. Meanwhile, $\\tau_{2}$ appears to dominate the PL decay, indicating that electrons are effectively extracted from the perovskite layer to the $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ with minimal recombination loss. Even under smaller excitation intensity $(0.5\\upmu\\mathrm{J}\\mathsf{c m}^{-2})$ , the acceleration of the lifetime for $\\mathrm{E}{\\cdot}\\mathrm{SnO}_{2}\\dot{/}$ perovskite is observed. The lifetime increases with reduced excitation intensity (Supplementary Fig. 8 and Supplementary Table 1), in agreement with a previous report61. The electrontransport yield $(\\phi_{\\mathrm{tr}})$ of different ETLs with different excitation intensities can be estimated using equation, $\\phi_{\\mathrm{tr}}{=}1~-\\tau_{\\mathrm{p}}/\\tau_{\\mathrm{glass}}$ where $\\tau_{\\mathrm{{p}}}$ is the average lifetime for perovskite deposited on different substrates, and $\\tau_{\\mathrm{glass}}$ is the average lifetime for glass/ perovskite. With the excitation intensity of $3\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ , the electron-transport yields of ITO, EDTA, $\\mathrm{SnO}_{2}$ , and $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ are $49.72\\%$ , $67.58\\%$ , $68.31\\%$ , and $81.50\\%$ , respectively. When the excitation intensity reduces to $0.5\\upmu\\mathrm{J}\\mathrm{cm}^{-2}$ , the electron-transport yields of ITO, EDTA, $\\mathrm{SnO}_{2}$ , and $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ are increased to $60.37\\%$ , $74.46\\%$ , $80.65\\%$ , and $90.82\\%$ , respectively. It is clear that the excitation intensity can significantly increase the electrontransport yield. These results further indicate that the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ is a good electron extraction layer for planar-type PSCs. \n\nThe performance of PSCs. With the superior optoelectronic properties discussed above, it is expected that the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ would make a better ETL in the PSCs than the $\\mathrm{SnO}_{2}$ . Planar-type PSCs are therefore designed and fabricated based on different ETLs with the device structure shown in Fig. 4a inset. $\\mathrm{FAPbI}_{3}$ was used as the active absorber for its proper band gap, with a small amount of Cs doping to improve its phase stability $^{62,63}$ . Supplementary Fig. 9 presents the cross-sectional SEM images for the complete device structure. The thickness of the perovskite film is controlled at ca. $420\\mathrm{nm}$ for all devices. While the perovskite grains are not large enough to penetrate through the film thickness when the $\\mathrm{SnO}_{2}$ is used as the substrate, the grains are significantly larger when deposited on EDTA and $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ with the grains grown across the film thickness, which is consistent with top-view SEM results (Fig. 2). \n\nFigure 4a shows the $J{-}V$ curves of planar-type PSCs using different ETLs, with the key parameters, including short-circuit current density $(J_{s c})$ , $V_{\\mathrm{oc}},$ fill factor (FF), and PCE summarized in Table 1. The device based on EDTA gives a PCE of $16.42\\%$ with $J_{s c}=22.10\\mathrm{mAcm}^{-2}$ , $V_{\\mathrm{oc}}=1.08\\:\\mathrm{V}$ , and $\\mathrm{FF}=0.687$ . The device based on $\\mathrm{SnO}_{2}$ substrate shows a PCE of $18.93\\%$ with $J_{s c}=$ $22.79\\mathrm{mAcm}^{-2}$ , $V_{\\mathrm{oc}}=1.10\\:\\mathrm{V}$ , and $\\mathrm{FF}=0.755$ . Interestingly, when the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ is employed as $\\mathrm{ETL}.$ the $J_{s c},$ FF, and $V_{\\mathrm{oc}}$ are increased to $24.55\\mathrm{mAc}\\mathrm{\\bar{m}}^{-2}$ , 0.792, and 1.11 V, yielding a PCE up to $21.60\\%$ , (the certified efficiency is $21.52\\%$ , and the certificated document is shown in Supplementary Fig. 10), the highest efficiency reported to date for the planar-type PSCs. The low device performance for the EDTA is caused by small $J_{s c}$ and FF, which is related to low electron mobility and high resistance47, and the low $V_{\\mathrm{oc}}$ results from the small offset of Fermi energy between the EDTA and HTL (Fig. 1d)64. In comparison, the planar-type PSCs with $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ ETLs exhibit the best performance. The higher $J_{\\mathrm{sc}}$ and FF are attributed to the high electron mobility that promotes effective electron extraction, and the larger $V_{\\mathrm{oc}}$ due to the closer energy level between $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ and perovskite65. Figure 4b shows the incident-photon-to-charge conversion efficiency (IPCE) and the integrated current of the PSCs based on different ETLs. The integrated current values calculated by the IPCE spectra for the devices using EDTA, $\\mathrm{SnO}_{2}$ , and $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ are 21.22, 21.58, and $24.15\\mathrm{mAcm}^{-2}$ , respectively, very close to the $J{-}V$ results. It is apparent that the device based on the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ shows significantly higher IPCE due to less optical loss when perovskite is deposited on $\\bar{\\mathrm{E}}{\\cdot}\\mathrm{SnO}_{2}$ ETL (Supplementary Fig. 11), consistent with the $J{-}V$ measurement. \n\n![](images/c62f647953b418bfa3e90a3535ded3d50da0d18f7bf2ecfac8cdba9d87effed4.jpg) \nFig. 4 PSC performance using ETLs. a $J-V$ curves with the inset showing device configuration, and b the corresponding IPCE of the planar-type PSCs with various ETLs. The integrated current density from the IPCE curves with the AM $1.56$ photon flux spectrum. c Static current density and PCE measured as a function of time for the EDTA, $\\mathsf{S n O}_{2},$ and $\\mathsf{E}{-}\\mathsf{S n O}_{2}$ devices biased at $0.85\\vee$ , $0.89\\mathsf{V},$ and $0.92\\vee$ respectively. d The PCE distribution histogram of the planartype PSCs based on different ETLs \n\n
Table 1 The parameters of the rigid and flexible devices
Style ETLJsc (mA cm-2)V.c (V)FFPCE (%)
RigidEDTA 22.101.080.68716.42
SnO2 Flexible E-SnO Ro21.43 ± 1.191.05 ± 0.020.649±0.07414.60 ± 1.60
22.791.100.75518.93
22.70 ± 0.321.08 ± 0.030.735 ± 0.02218.04 ± 0.63
E-SnO2 24.571.110.79221.60
24.55 ± 0.761.11 ± 0.010.750 ± 0.01120.41± 0.55
23.421.090.716
22.64± 0.461.09 ± 0.030.699 ± 0.02818.28 17.26 ± 0.75
E-SnO2 R14-50023.421.090.71518.25
E-SnO2 R12-500 E-SnO2 R7-50023.111.080.71417.82
22.661.080.68816.84
\n\nTo further demonstrate the device characteristics, photocurrent density of the champion devices from each group based on EDTA, $\\mathrm{SnO}_{2}$ , and $\\mathrm{E}{\\mathrm{-}}\\bar{\\mathrm{SnO}}_{2}$ was measured when the devices were biased at 0.85, 0.89, and $0.92{\\mathrm{V}}$ , respectively. Figure 4c shows the corresponding curves at the maximum power point $(V_{\\mathrm{mp}})$ in the $J{-}V$ plots. The PCEs of the champion devices using the EDTA, $\\mathrm{SnO}_{2},$ and $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ stabilize at $16.34\\%$ , $18.67\\%$ , and $21.67\\%$ with photocurrent densities of 19.22, 20.98, and $23.55\\mathrm{mAcm}^{-2}$ , respectively, very close to the values measured from the $J{-}V$ curves. Next, we fabricated and measured 30 individual devices for each ETL to study repeatability. Figure 4d shows the PCE distribution histogram for devices with different ETLs, with the statistics listed in Supplementary Table 2–4. Amazingly, the devices based on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ exhibit excellent repeatability with a very small standard deviation in contrast to the devices based on EDTA and $\\mathrm{SnO}_{2};$ , indicating that the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ is an excellent ETL in the planar-type PSC. \n\n![](images/e11e89a2e417ffdf8cb4ca4b7af14b85e7720d22c8e1bc59e26c2fd2d3fec473.jpg) \nFig. 5 Charge transfer properties of the planar-type PSCs using different ETLs. a $V_{\\mathrm{{oc}}}$ decay curves, b $J_{\\mathsf{s c}}$ vs. light intensity, c $V_{\\mathsf{o c}}$ vs. light intensity, and d EIS of planar-type PSCs with various ETLs \n\nIn order to gain further insight into the charge transport mechanism, the charge transfer processes in the perovskite devices were studied in detail. The carrier recombination rate in the PSCs was evaluated by the $V_{\\mathrm{oc}}$ decay measurements. Figure $5\\mathrm{a}$ shows the $V_{\\mathrm{oc}}$ decay curves of the PSCs based on different ETLs. It is apparent that the planar-type PSC based on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ exhibits the slowest $V_{\\mathrm{oc}}$ decay time compared to the devices based on EDTA and $\\mathrm{SnO}_{2}$ , indicating that the devices with $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ have the lowest charge recombination rate and the longest carrier lifetime, consistent with the highest $V_{\\mathrm{oc}}$ for the device based on E$\\mathrm{SnO}_{2}$ by $J{-}V$ measurements. Figure 5b shows $J_{\\mathrm{sc}}$ versus light intensity of the PSCs using various ETLs. It appears that all devices show a linear correlation with the slopes very close to 1, indicating that the bimolecular recombination in the devices is negligible66. Figure 5c shows that $V_{\\mathrm{oc}}$ changes linearly with the light intensity. Prior studies have indicated that the deviation between the slope and the value of $\\left(k T/q\\right)$ reflects the trap-assisted recombination20. In the present case, the device using the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ shows the smallest slope, indicating the least trap-assisted recombination, which is in excellent agreement with the result showing the lowest trap density when the perovskite is deposited on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ (Fig. 3a). In fact, the slope is as small as $1.0\\bar{2}~k T/q;$ . implying that the trap-assisted recombination is almost negligible. \n\nThe electrical impedance spectroscopy (EIS) was employed to extract transfer resistance in the solar cells. Figure 5d shows the Nyquist plots of the devices using different ETLs measured at $V_{\\mathrm{oc}}$ under dark conditions, with the equivalent circuit shown in Supplementary Fig. 12. It is known that in the EIS analysis, the high-frequency component is the signature of the transfer resistance $(R_{\\mathrm{tr}})$ and the low-frequency one for the recombination resistance $(R_{\\mathrm{rec}})^{67}$ . In the present study, because the perovskite/ HTL interface is identical for all devices, the only variable affecting $R_{\\mathrm{tr}}$ is the perovskite/ETL interface. The numerical fitting gives the device parameters, as listed in Supplementary Table 5. Apparently, compared to PSCs based on EDTA and $\\mathrm{SnO}_{2}$ , the device with $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ shows the smallest $R_{\\mathrm{tr}}$ of $14.8\\Omega$ and the largest $R_{\\mathrm{rec}}$ of $443.3\\Omega$ . The small $R_{\\mathrm{tr}}$ is beneficial for electron extraction, and the large $R_{\\mathrm{rec}}$ effectively resists charge recombination, which is in agreement with the observations discussed above. Combined, all the results confirm that $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ is the most effective ETL for the planar-type PSC. \n\nStability and hysteresis. Stability and hysteresis are two key characteristics for the PSCs. Figure 6a shows normalized PCE measured as a function of storage time, with more detailed $J{-}V$ parameters summarized in Supplementary Table 6. It is clear that while the device based on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ maintains $92\\%$ of its initial efficiency exposed to an ambient atmosphere after $2880\\mathrm{h}$ in the dark, the device using $\\mathrm{SnO}_{2}$ only provides $74\\%$ of its initial efficiency under the same storage condition. The PSCs were also tested under continuous irradiation at $100\\mathrm{mW}\\mathrm{cm}^{-2}$ . Figure 6b shows the normalized PCE changes as a function of test time, with more detailed $J{-}V$ parameters provided in Supplementary Table 7. It is clear that after $120\\mathrm{h}$ of illumination, the device using the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ maintains $86\\%$ of its initial efficiency, while for the same test duration, the device using $\\mathrm{SnO}_{2}$ remains only $38\\%$ relative to its initial efficiency. It is apparent that the device fabricated on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ shows excellent stability under both the dark and continuous irradiation. The instability of PSC is mainly caused by degradation of the perovskite film and spiro-OMeTAD \n\n![](images/608944fe361f46cf64b86de1b13077ddeb8bde524e8950c647144cff34f426c6.jpg) \nFig. 6 Stability and hysteresis test for planar-type PSCs. Long-term stability measurements of devices without any encapsulation under a ambient condition and b illumination of $100\\mathsf{m w c m}^{-2}$ . The $J-V$ curves of the device with c $\\mathsf{S n O}_{2}$ and d $E\\mathrm{-}\\mathsf{S n O}_{2}$ measured under both reverse- and forward-scan directions \n\nHTL. In the present work, all devices used the same spiroOMeTAD HTL, therefore, the degradation from the HTL should be the same for all the devices. It is found that the grain size of the perovskite film is increased by three times when it is deposited on $\\bar{\\mathrm{E}}{\\cdot}\\mathrm{SnO}_{2}$ in comparison to that on the pristine $\\mathrm{SnO}_{2}$ (Fig. 2). The larger grain size can effectively suppress the moisture permeation at grain boundaries68, resulting in improved environmental stability for the PSCs based on the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ ETLs. \n\nFor the hysteresis test, Fig. 6c and d show the $J{-}V$ curves measured under both reverse- and forward- scan directions. It is found that the device with $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ has almost identical $J{-}V$ curves with negligible hysteresis, even when it is measured using different scan rates from 0.01 to $0.5\\mathrm{V}\\thinspace s^{-1}$ . Supplementary Fig. 13 presents $J{-}V$ curves measured for the device based on $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ at different scan rates. It is apparent that the $J{-}V$ curves almost remain the same, regardless of scan rate and direction, demonstrating that the hysteresis is negligible. Generally, the hysteresis of PSCs is ascribed to interfacial capacitance caused by charge accumulation at the interface, which originates from ion migration, high trap density, and unbalanced charge transport within the perovskite device69–71. It is found that the trap density of the perovskite film is significantly reduced when it is deposited on the $\\mathrm{\\E-SnO}_{2}$ , one of the primary reasons for reduced hysteresis. In addition, the electron mobility of the $\\mathrm{SnO}_{2}$ ETL is only $9.92\\times$ $10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ (Fig. 1f), about an order of magnitude slower than the hole mobility of the doped spiro-OMeTAD (ca. $10^{-3}$ $\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1})$ HTL. Thus, the electron flux $(F_{\\mathrm{e}})$ is ca. 10 times smaller than the hole flux $(F_{\\mathrm{h}})$ due to the same interface area of the ETL/perovskite and perovskite/HTL, that leads to charge accumulation at the $\\mathrm{SnO}_{2}.$ /perovskite interface, as shown in Supplementary Fig. 14a. The accumulated charge would cause hysteresis in the solar cells (Fig. 6c). When the high electron mobility $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ $(2.27\\times10^{-3}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1})$ is employed as the ETL, the $F_{\\mathrm{e}}$ is comparable to the $F_{\\mathrm{h}}$ of the spiro-OMeTAD HTL (Supplementary Fig. 14b), resulting in equivalent charge transport at both electrodes. Therefore, the high electron mobility of E$\\mathrm{SnO}_{2}$ would enhance electron transport from perovskite to E$\\mathrm{SnO}_{2}$ ETL, leading to no significant charge accumulation, and consequently, the devices based on the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ exhibit negligible hysteresis. \n\nHigh-efficiency flexible PSCs. Given the advantage of lowtemperature preparation, we applied the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ ETL in flexible PSCs. Figure 7a shows $J{-}V$ curves of flexible PSCs using the poly (ethylene terephthalate) (PET)/ITO substrates, with key $J{-}V$ parameters summarized in Table 1. The champion flexible device exhibits PCE of $18.28\\%$ $(J_{s c}=23.42\\mathrm{mA}\\mathrm{cm}^{-2}$ , $V_{\\mathrm{oc}}=1.09\\:\\mathrm{V}$ , and $\\mathrm{FF}=0.716\\$ ). The lower $J_{s c}$ of the flexible device is caused by the lower transparency of the PET/ITO substrate compared to the glass/ITO used for the rigid device (Supplementary Fig. 15). The lower $V_{\\mathrm{oc}}$ and FF are likely due to higher sheet resistance of the PET/ITO substrate67. Figure 7c shows the IPCE and integral current density of the flexible device. It is clear that the integral current is $23.{\\dot{1}}2\\operatorname{mA}\\operatorname{cm}^{-2}$ , in perfect agreement with the $\\bar{J}{-}V$ results. For the reproducibility test, 30 individual cells were fabricated with the PCE distribution histogram shown in Fig. 7d and detailed parameters are summarized in Supplementary Table 8, both confirming very good reproducibility. \n\nThe mechanical stability is an important quality indicator for the flexible solar cells. According to a previous report72, it is safe for ITO to be bended to a radius of $14\\mathrm{mm}$ , and when the bending radius is smaller than $14\\mathrm{mm}$ , the ITO layer starts to crack, leading to significant degradation in conductivity. In order to examine the mechanical stability of the flexible PSCs, we therefore adopted the bending radii of $14\\mathrm{mm}$ , $12\\mathrm{mm}$ , and $7\\mathrm{mm}$ to test the flexible device. Figure 7a shows device performance of the flexible solar cells measured after flexing for 500 times with different curvature radii, and the test procedure is shown in Fig. 7b. It shows that after flexing for 500 times at a bending radius of $14\\mathrm{mm}$ , the $J{-}V$ curve and the associated parameters remain the same without obvious degradation. However, when the bending radius is decreased to $12\\mathrm{mm}$ and $7\\mathrm{mm}$ , the PCE degraded to $17.82\\%$ and $16.84\\%$ , respectively, attributing to the conductivity degradation of $\\mathrm{ITO}^{72}$ . \n\n![](images/34cb664b88dc661e243493d263ce7d9e46a3b81113c0df672ff03aab5f6fd5cd.jpg) \nFig. 7 The performance of flexible PSCs based on $\\mathsf{E}\\mathrm{-}\\mathsf{S n O}_{2}$ ETLs. a $J-V$ curves of the flexible devices and after flexing at curvature radii of $14\\mathsf{m m}$ , $12\\mathsf{m m}$ , and $7\\mathsf{m m}$ for 500 cycles, respectively. b The normalized PCE measured after flexing at different curvature radii. c IPCE curves of the flexible device. d The PCE distribution histogram of the flexible PSCs \n\n# Discussion \n\nAn effective $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ ETL has been developed, and the PCE of planar-type PSCs is increased to $21.60\\%$ with negligible hysteresis, and the certified efficiency is $21.52\\%$ , this is the highest reported value for planar-type PSCs so far. By taking advantage of lowtemperature processing for $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ ETLs, flexible devices with high PCE of $18.28\\%$ are also fabricated. The significant performance of the planar-type PSCs is attributed to the superior advantages when perovskite is deposited on $\\mathbf{E}{\\cdot}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ ETLs, including larger grain size, lower trap density, and good crystallinity. The higher electron mobility facilitates electron transfer for suppressed charge accumulation at the interface, leading to high efficiency with negligible $J{-}V$ hysteresis. Furthermore, the longterm stability is significantly enhanced since the large grain size that suppressed perovskite degradation at grain boundaries. This work provides a promising direction toward developing highquality ETLs, and we believe that the present work will facilitate transition of perovskite photovoltaics. \n\n# Methods \n\nMaterials. $\\mathrm{NH}_{2}\\mathrm{CHNH}_{2}\\mathrm{I}$ (FAI) was synthesized and purified according to a reported procedure45. The $\\mathrm{SnO}_{2}$ solution was purchased from Alfa Aesar (tin (IV) oxide, $15\\mathrm{wt\\%}$ in $_\\mathrm{H}_{2}\\mathrm{O}$ colloidal dispersion). $\\mathrm{PbI}_{2}$ (purity $>99.9985\\%$ ) was purchased from Alfa Aesar. EDTA (purity $\\cdot>99.995\\%$ ), CsI (purity $>99.999\\%$ ), dimethylformamide (DMF, purity $>99\\%$ ), and dimethyl sulfoxide (DMSO, purity $>$ $99\\%$ ) were obtained from Sigma Aldrich. In total, $^{2,2^{\\prime},7,7^{\\prime}}$ -tetrakis $\\cdot N\\mathrm{,}N$ -di-pmethoxyphenylamine)-9,9′-spirobifluorene (spiro-OMeTAD) was bought from Yingkou OPV Tech Co., Ltd. All of the other solvents were purchased from Sigma Aldrich without any purification. \n\nFabrication of EDTA, $\\sin O_{2}$ and $\\pmb{\\mathrm{E}}\\pmb{\\mathrm{-}}\\pmb{\\mathrm{S}}\\pmb{\\mathrm{n}}\\pmb{\\mathrm{O}}_{2}$ films. The $0.2\\mathrm{-mg}$ EDTA was dissolved in $1\\mathrm{mL}$ of deionized water, and the $\\mathrm{SnO}_{2}$ aqueous colloidal dispersion $(15\\mathrm{wt\\%})$ was diluted using deionized water to the concentration of $2.5\\mathrm{wt\\%}$ . These solutions were stirred at room temperature for $^{2\\mathrm{h}}$ . The $\\mathrm{SnO}_{2}$ and EDTA layers were fabricated by spin-coating at $5000\\mathrm{rpm}$ for $60\\mathrm{{s}}$ using the corresponding solution, and then dried in a vacuum oven at $60^{\\circ}\\mathrm{C}$ under ca. $5\\mathrm{Pa}$ for $30\\mathrm{min}$ to remove residual solvent. The EDTA and $\\mathrm{SnO}_{2}$ solution were mixed with a volume ratio of 1:1, then put on a hot plate at $80^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ under stirring conditions, and the milky-white E$\\mathrm{SnO}_{2}$ colloidal solution (Fig. 1b) was obtained. The $\\mathbf{E}{\\mathrm{-}}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ colloidal solution was spin-coated at $5000\\mathrm{rpm}$ for $60\\ s,$ and then transferred the samples into a vacuum oven at $60^{\\circ}\\mathrm{C}$ under ca. $5\\mathrm{Pa}$ for $30\\mathrm{min}$ to remove the residual solvent. Finally, the $\\mathrm{E}{\\mathrm{-}}\\mathrm{SnO}_{2}$ films were obtained. \n\nElectron mobility of EDTA, $\\sin O_{2}$ and $\\pmb{\\mathrm{E}}\\pmb{\\mathrm{-}}\\pmb{\\mathrm{Sn}}\\pmb{0}_{2}$ films. To gain insights into the charge transport, we have measured electron mobility using different ETLs in the same device structure. Specifically, the electron-only device was designed and fabricated using ITO/Al/ETL/Al structure, as shown in the inset in Fig. 1f. In this analysis, we assumed that the current is only related to electrons. When the effects of diffusion and the electric field are neglected, the current density can be determined by the $\\mathrm{sCLC}^{73}$ . The thickness of $80\\mathrm{-nm}$ Al was deposited on ITO substrates by thermal evaporation, and then the different ETLs were spin-coated on ITO/Al. Finally, $80\\mathrm{-nm}$ -thick Al was deposited on ITO/Al/ETL samples. The dark $J{-}V$ curves of the devices were performed on a Keithley 2400 source at ambient conditions. The electron mobility $(\\mu_{\\mathrm{e}})$ is extracted by fitting the $J{-}V$ curves using the Mott–Gurney law (3) \n\n$$\n\\mu_{\\mathrm{e}}={\\frac{8J L^{3}}{9\\varepsilon_{0}\\varepsilon{\\biggl(}V_{\\mathrm{app}}-V_{\\mathrm{r}}-V_{\\mathrm{bi}}{\\biggr)}^{2}}}\n$$ \n\nwhere $J$ is the current density, $L$ the thickness of different ETLs, $\\ensuremath{\\varepsilon}_{0}$ the vacuum permittivity, $\\varepsilon_{\\mathrm{r}}$ the dielectric permittivity of various ETLs, $V_{\\mathrm{app}}$ the applied voltage, $V_{\\mathrm{r}}$ the voltage loss due to radiative recombination, and $V_{\\mathrm{bi}}$ the built-in voltage owing to the different work function between the anode and cathode. \n\nFabrication of solar cells. The perovskite absorbers were deposited on different ETL substrates using one-step solution processed. In total, $240.8\\mathrm{mg}$ of FAI, $646.8\\mathrm{mg}$ of $\\mathrm{PbI}_{2}$ , and $18.2\\mathrm{mg}$ of CsI were dissolved in $1\\mathrm{mL}$ of DMF and DMSO (4:1, volume/volume), with stirring at $60^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . The precursor solution was spin-coated on the EDTA, $\\mathrm{SnO}_{2}$ and $\\mathbf{E}{\\mathrm{-}}\\mathbf{S}\\mathbf{n}\\mathbf{O}_{2}$ substrates. The spin-coated process was divided by a consecutive two-step process, the spin rate of the first step is $1000\\mathrm{rpm}$ for $15s$ with accelerated speed of $200\\mathrm{rpm},$ and the spin rate of the second step is $4000\\mathrm{rpm}$ for 45 s with accelerated speed of $1000\\mathrm{rpm}$ . During the second step end of $15{\\mathrm{s}}_{\\mathrm{;}}$ , $200\\upmu\\mathrm{L}$ of chlorobenzene was drop-coated to treat the perovskite films, and then the perovskite films were annealed at $100^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ in a glovebox. After cooling down to room temperature, the spiro-OMeTAD solution was coated on perovskite films at $5000\\mathrm{rpm}$ for $30\\mathrm{{s}}$ with accelerated speed of $3000\\mathrm{rpm}$ . The 1-mL HTL chlorobenzene solution contains $90\\mathrm{mg}$ of spiroOMeTAD, $36\\upmu\\mathrm{L}$ of 4-tert-butylpyridine, and $22\\upmu\\mathrm{L}$ of lithium bis(trifluoromethylsulfonyl) imide of $\\bar{5}\\dot{2}0\\mathrm{mg}\\mathrm{mL}^{-1}$ in acetonitrile. The samples were retained in a desiccator overnight to oxidate the spiro-OMeTAD. Finally, $100\\mathrm{-nm}$ - thick Au was deposited using thermal evaporation. The device area of $\\mathrm{\\dot{0}}.1134\\mathrm{cm}^{2}$ was determined by a metal mask. \n\nCharacterization. The $J{-}V$ curves of the PSCs were measured using a Keithley 2400 source under ambient conditions at room temperature. The light source was a 450-W xenon lamp (Oriel solar simulator) with a Schott K113 Tempax sunlight filter (Praezisions Glas $\\&$ Optik GmbH) to match $\\mathrm{AM}1.5\\mathrm{G}$ . The light intensity was $100\\mathrm{mW}\\mathrm{cm}^{-2}$ calibrated by a NREL-traceable KG5-filtered silicon reference cell. The active area of $0.1017\\mathrm{cm}^{2}$ was defined by a black metal aperture to avoid light scattering into the device, and the aperture area was determined by the MICRO VUE sol 161 instrument. The $J{-}V$ curves for PSCs were tested both at reverse scan (from 2 to $-0.1\\mathrm{V}$ , step 0.02 V) and forward scan (from $-0.1$ to $2\\mathrm{V}$ , step 0.02 V), and the scan rate was selected from 0.01 to $0.5\\mathrm{V}\\thinspace\\mathsf{s}^{-1}$ . There was no preconditioning before the test. The IPCE was implemented on the QTest Station 2000ADI system (Crowntech. Inc., USA). AFM height images were attained by a Bruker Multimode 8 in tapping mode. KPFM was carried out on Bruker Metrology Nanoscope VIII AFM in an ambient atmosphere. The TRPL spectra were performed on an Edinburgh Instruments FLS920 fluorescence spectrometer. SEM images were gained by a field-emission scanning electron microscope (SU8020) under an accelerating voltage of $2\\mathrm{kV}$ . XPS measurements were performed on an AXISULTRA X-ray photoelectron spectrometer. The optical transmission was acquired by a Hitachi U-3900 spectrophotometer. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 16 March 2018 Accepted: 26 July 2018. Published online: xx xxx 2018 \n\n# References \n\n1. Manser, J. S. & Kamat, P. V. Band filling with free charge carriers in organometal halide perovskites. Nat. Photonics 8, 737–747 (2014). \n2. Chen, H. et al. A solvent- and vacuum-free route to large-area perovskite films for efficient solar modules. Nature 550, 92–95 (2017). \n3. Xing, G. et al. Long-range balanced electron and hole-transport lengths in organic-inorganic $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ . Science 342, 344–347 (2013). \n4. Liu, M., Johnston, M. B. & Snaith, H. J. Efficient planar heterojunction perovskite solar cells by vapour deposition. Nature 501, 395–398 (2013). \n5. Wang, Z. et al. Efficient ambient-air-stable solar cells with 2D-3D heterostructured butylammonium-caesium-formamidinium lead halide perovskites. Nat. Energy 2, 17135 (2017). \n6. Liu, Y. et al. Two-inch-sized perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Pb}\\mathrm{X}_{3}$ $\\mathrm{{\\ddot{X}=C l}},$ Br, I) crystals: growth and characterization. Adv. Mater. 27, 5176–5183 (2015). perovskite films towards efficient solar cells using vacuum deposition. J. Mater. Chem. A 3, 9401–9405 (2015). \n8. Yakunin, S. et al. Detection of gamma photons using solution-grown single crystals of hybrid lead halide perovskites. Nat. Photonics 10, 585–589 (2016). \n9. Hao, F. et al. Lead-free solid-state organic-inorganic halide perovskite solar cells. Nat. Photonics 8, 489–494 (2014). \n10. Shao, Y., Xiao, Z., Bi, C., Yuan, Y. & Huang, J. Origin and elimination of photocurrent hysteresis by fullerene passivation in $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ planar heterojunction solar cells. Nat. Commun. 5, 5784 (2015). \n11. Wei, H. et al. Sensitive X-ray detectors made of methylammonium lead tribromide perovskite single crystals. Nat. Photonics 10, 333–339 (2016). \n12. Chung, I., Lee, B., He, J., Chang, R. P. H. & Kanatzidis, M. G. All-solid-state dye-sensitized solar cells with high efficiency. Nature 485, 486–489 (2012). \n13. Kim, Y. C. et al. Printable organometallic perovskite enables large-area, lowdose X-ray imaging. Nature 550, 87–91 (2017). \n14. Liu, Y. et al. Thinness- and shape-controlled growth for ultrathin singlecrystalline perovskite wafers for mass production of superior photoelectronic devices. Adv. Mater. 28, 9204–9209 (2016). \n15. NREL. Efficiency chart. https://www.nrel.gov/pv/assets/images/efficiencychart-20180716.jpg (2018). \n16. Yang, W. S. et al. Iodide management in formamidinium-lead-halide-based perovskite layers for efficient solar cells. Science 356, 1376–1379 (2017). \n17. Cho, K. T. et al. Highly efficient perovskite solar cells with a compositionally engineered perovskite/hole transporting material interface. Energy Environ. Sci. 10, 621–627 (2017). \n18. Jiang, Q. et al. Planar-structure perovskite solar cells with efficiency beyond $21\\%$ . Adv. Mater. 29, 1703852 (2017). \n19. Zheng, X. et al. Defect passivation in hybrid perovskite solar cells using quaternary ammonium halide anions and cations. Nat. Energy 2, 17102 (2017). \n20. Yang, D. et al. Surface optimization to eliminate hysteresis for record efficiency planar perovskite solar cells. Energy Environ. Sci. 9, 3071–3078 (2016). \n21. Jiang, Q. et al. Enhanced electron extraction using $\\mathrm{SnO}_{2}$ for high-efficiency planar-structure $\\mathrm{HC}(\\mathrm{NH}_{2})_{2}\\mathrm{PbI}_{3}$ -based perovskite solar cells. Nat. Energy 2, 16177 (2016). \n22. Yang, D. et al. Hysteresis-suppressed high-efficiency flexible perovskite solar cells using solid-state ionic-liquids for effective electron transport. Adv. Mater. 28, 5206–5213 (2016). \n23. Dong, Q. et al. Electron-hole diffusion lengths ${>}175~{\\upmu}\\mathrm{m}$ in solution-grown CH3NH3PbI3 single crystals. Science 347, 967–970 (2015). \n24. Lang, F. et al. Influence of radiation on the properties and the stability of hybrid perovskites. Adv. Mater. 30, 172905 (2018). \n25. Ranjan, R. et al. Effect of tantalum doping in a $\\mathrm{TiO}_{2}$ compact layer on the performance of planar spiro-OMeTAD free perovskite solar cells. J. Mater. Chem. A 6, 1037–1047 (2018). \n26. Meng, L., You, J., Guo, T. F. & Yang, Y. Recent advances in the inverted planar structure of perovskite solar cells. Acc. Chem. Res. 49, 155–165 (2016). \n27. Nie, W. et al. Critical role of interface and crystallinity on the performance and photostability of perovskite solar cell on nickel oxide. Adv. Mater. 30, 1703879 (2018). \n28. Dong, Q., Shi, Y., Zhang, C., Wu, Y. & Wang, L. Energetically favored formation of $\\mathrm{SnO}_{2}$ nanocrystals as electron transfer layer in perovskite solar cells with high efficiency exceeding $19\\%$ . Nano Energy 40 336–344. \n29. Jung, K.-H., Seo, J.-Y., Lee, S., Shin, H. & Park, N.-G. Solution-processed $\\mathrm{SnO}_{2}$ thin film for hysteresis-less $19.2\\%$ planar perovskite solar cell. J. Mater. Chem. A 5, 24790–24803 (2017). \n30. Ke, W. et al. Efficient hole-blocking layer-free planar halide perovskite thinfilm solar cells. Nat. Commun. 6, 6700 (2015). \n31. Liu, D., Yang, J. & Kelly, T. L. Compact layer free perovskite solar cells with $13.5\\%$ efficiency. J. Am. Chem. Soc. 136, 17116 (2014). \n32. Zhang, P. et al. Perovskite solar cells with ZnO electron-transporting materials. Adv. Mater. 30, 1703737 (2018). \n33. Singh, T. & Miyasaka, T. Stabilizing the efficiency beyond $20\\%$ with a mixed cation perovskite solar cell fabricated in ambient air under controlled humidity. Adv. Energy Mater. 8, 1700677 (2018). \n34. Tress, W. et al. Understanding the rate-dependent J-V hysteresis, slow time component, and aging in $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ perovskite solar cells: the role of a compensated electric field. Energy Environ. Sci. 8, 995–1004 (2015). \n35. Tan, H. et al. Efficient and stable solution-processed planar perovskite solar cells via contact passivation. Science 355, 722–726 (2017). \n36. Ke, W. et al. Low-temperature solution-processed tin oxide as an alternative electron transporting layer for efficient perovskite solar cells. J. Am. Chem. Soc. 137, 6730–6733 (2015). \n37. Huang, X. et al. Low-temperature processed $\\mathrm{SnO}_{2}$ compact layer by incorporating $\\mathrm{TiO}_{2}$ layer toward efficient planar heterojunction perovskite solar cells. Sol. Energy Mater. Sol. Cells 164, 87–92 (2017). \n38. Dagar, J. et al. Efficient fully laser-patterned flexible perovskite modules and solar cells based on low-temperature solution-processed $\\mathrm{SnO}_{2}/$ mesoporous$\\mathrm{TiO}_{2}$ electron transport layers. Nano Res. 11, 2669–2681 (2018). \n39. Chen, H. et al. Enhanced performance of planar perovskite solar cells using low-temperature solution-processed Al-doped $\\mathrm{SnO}_{2}$ as electron transport layers. Nanoscale Res. Lett. 12, 1–6 (2017). \n40. Baena, J. P. C. et al. Highly efficient planar perovskite solar cells through band alignment engineering. Energy Environ. Sci. 8, 2928–2934 (2015). \n41. Zhu, Z. et al. Enhanced efficiency and stability of inverted perovskite solar cells using highly crystalline $\\mathrm{SnO}_{2}$ nanocrystals as the robust electrontransporting layer. Adv. Mater. 28, 6478–6484 (2016). \n42. Barbé, J. et al. Amorphous tin oxide as a low-temperature-processed electrontransport layer for organic and hybrid perovskite solar cells. ACS Appl. Mater. Interfaces 9, 11828–11836 (2017). \n43. Anaraki, E. H. et al. Highly efficient and stable planar perovskite solar cells by solution-processed tin oxide. Energy Environ. Sci. 9, 3128–3134 (2016). \n44. Park, M. et al. Low-temperature solution-processed Li-doped $\\mathrm{SnO}_{2}$ as an effective electron transporting layer for high-performance flexible and wearable perovskite solar cells. Nano Energy 26, 208–215 (2016). \n45. Li, X., Liu, X., Zhang, W., Wang, H.-Q. & Fang, J. Fullerene-free organic solar cells with efficiency over $12\\%$ based on EDTA-ZnO hybrid cathode interlayer. Chem. Mater. 29, 4176–4180 (2017). \n46. An, Q. et al. High performance planar perovskite solar cells by ZnO electron transport layer engineering. Nano Energy 39, 400–408 (2017). \n47. Li, X., Zhang, W., Wang, X., Gao, F. & Fang, J. Disodium edetate as a promising interfacial material for inverted organic solar cells and the device performance optimization. ACS Appl. Mater. Interfaces 6, 20569–20573 (2014). \n48. Majumder, S. Synthesis and characterisation of $\\mathrm{SnO}_{2}$ films obtained by a wet chemical process. Mater. Sci. 27, 123–129 (2009). \n49. Gundrizer, T. A. & Davydov, A. A. IR spectra of oxygen adsorbed on $\\mathrm{SnO}_{2}$ . React. Kinet. Catal. Lett. 3, 63–70 (1975). \n50. Yang, D., Zhou, L., Yu, W., Zhang, J. & Li, C. Work-function-tunable chlorinated graphene oxide as an anode interface layer in high-efficiency polymer solar cells. Adv. Energy Mater. 4, 1400591 (2014). \n51. Snaith, H. J. & Ducati, C. $\\mathrm{SnO}_{2}$ -based dye-sensitized hybrid solar cells exhibiting near unity absorbed photon-to-electron conversion efficiency. Nano Lett. 10, 1259–1265 (2010). \n52. Zhumekenov, A. A. et al. The role of surface tension in the crystallization of metal halide perovskites. ACS Energy Lett. 2, 1782–1788 (2017). \n53. Zhao, H. et al. Enhanced stability and optoelectronic properties of $\\mathbf{MAPbI}_{3}$ films with cationic surface active agent for perovskite solar cells. J. Mater. Chem. A 6, 10825–10834 (2018). \n54. Salim, T. et al. Perovskite-based solar cells: impact of morphology and device architecture on device performance. J. Mater. Chem. A 3, 8943–8969 (2015). \n55. Li, P. et al. Polyethyleneimine high-energy hydrophilic surface interfacial treatment toward efficient and stable perovskite solar cells. ACS Appl. Mater. Interfaces 30, 32574–32580 (2016). \n56. Wang, W. et al. Enhanced performance of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3-\\mathrm{x}}\\mathrm{Cl}_{\\mathrm{x}}$ perovskite solar cells by $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{I}$ modification of $\\mathrm{TiO}_{2}$ -perovskite layer interface. Nanoscale Res. Lett. 11, 1–9 (2016). \n57. Lee, H., Rhee, S., Kim, J., Lee, C. & Kim, H. Surface coverage enhancement of a mixed halide perovskite film by using an UV-ozone treatment. J. Korean Phys. Soc. 69, 406–411 (2016). \n58. Fu, P. et al. Efficiency improved for inverted polymer solar cells with electrostatically self-assembled BenMeIm-Cl ionic liquid layer as cathode interface layer. Nano Energy 13, 175–282 (2015). \n59. Liu, Y. et al. $20\\mathrm{-mm}$ -Large single-crystalline formamidinium-perovskite wafer for mass production of integrated photodetectors. Adv. Opt. Mater. 4, 1829–1837 (2016). \n60. Li, M. et al. High-efficiency robust perovskite solar cells on ultrathin flexible substrates. Nat. Commun. 7, 10214 (2016). \n61. Makuta, S. et al. Photo-excitation intensity dependent electron and hole injections from lead iodide perovskite to nanocrystalline $\\mathrm{TiO}_{2}$ and spiroOMeTAD. Chem. Commun. 52, 673–676 (2016). \n62. Zhu, X. et al. Superior stability for perovskite solar cells with $20\\%$ efficiency using vacuum co-evaporation. Nanoscale 9, 12316–12323 (2017). \n63. Liu, T. et al. High-performance formamidinium-based perovskite solar cells via microstructure-mediated δ-to-α phase transformation. Chem. Mater. 29, 3246–3250 (2017). \n64. Ryu, S. et al. Voltage output of efficient perovskite solar cells with high opencircuit voltage and fill factor. Energy Environ. Sci. 7, 2614–2618 (2014). \n65. Li, Y. et al. Ultra-high open-circuit voltage of perovskite solar cells induced by nucleation thermodynamics on rough substrates. Sci. Rep. 7, 46141 (2017). \n66. Cowan, S. R., Street, R. A., Cho, S. & Heeger, A. J. Transient photoconductivity in polymer bulk heterojunction solar cells: competition between sweep-out and recombination. Phys. Rev. B 83, 035205 (2011). \n67. Yang, D. et al. High efficiency flexible perovskite solar cells using superior low temperature $\\mathrm{TiO}_{2}$ . Energy Environ. Sci. 8, 3208–3214 (2015). \n68. Chu, Z. et al. Impact of grain boundaries on efficiency and stability of organicinorganic trihalide perovskites. Nat. Commun. 8, 2230 (2017). \n69. Chen, B. et al. Impact of capacitive effect and ion migration on the hysteretic behavior of perovskite solar cells. J. Phys. Chem. Lett. 6, 4693–4700 (2015). \n70. Reenen, S. V., Kemerink, M. & Snaith, H. J. Modeling anomalous hysteresis in perovskite solar cells. J. Phys. Chem. Lett. 6, 3808–3814 (2015). \n71. Heo, J. H. et al. Planar $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ perovskite solar cells with constant $17.2\\%$ average power conversion efficiency irrespective of the scan rate. Adv. Mater. \n27, 3424–3430 (2015). \n72. Zardetto, V., Brown, T. M., Reale, A. & Carlo, A. D. Substrates for flexible electronics: a practical investigation on the electrical, film flexibility, optical, temperature, and solvent resistance properties. J. Polym. Sci. Polym. A Phys. \n49, 638–648 (2011). \n73. Murgatroyd, P. N. Theory of space-charge-limited current enhanced by Frenkel effect. J. Phys. D: Appl. Phys. 3, 151–156 (1970). \n74. Ma, F. et al. Stable $\\upalpha/\\delta$ phase junction of formamidinium lead iodide perovskites for enhanced near-infrared emission. Chem. Sci. 8, 800–805 (2017). \n\n# Acknowledgements \n\nThe authors acknowledge support from the National Key Research Program of China (2016YFA0202403), the National Natural Science Foundation of China (61604090/ 91733301), the financial support from the Institute of Critical Technology and Applied Science (ICTAS), and the Shaanxi Technical Innovation Guidance Project (2018HJCG17). S.P. would like to acknowledge the financial support from the Air Force Office of Scientific Research (A. Sayir). S.L. would like to acknowledge the support from the National University Research Fund (GK261001009), the Innovative Research Team (IRT_14R33), the 111 Project (B14041), and the Chinese National 1000-Talent-Plan program. \n\n# Author contributions \n\nD.Y. designed and conducted the experiments, fabricated and characterized the devices, and analyzed the data. R.Y., K.W., C.W., X.Z., and J.F. contributed to useful comments for the paper. X.R. preformed the FTIR. D.Y. wrote the first draft of the paper. S.(F.)L. and S.P. supervised the overall project, discussed the results, and contributed to the final manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-05760-x. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 \n\n# QUERY FORM \n\n
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\n\n# SPRINGERNATURE " + }, + { + "id": "10.1126_science.aar4005", + "DOI": "10.1126/science.aar4005", + "DOI Link": "http://dx.doi.org/10.1126/science.aar4005", + "Relative Dir Path": "mds/10.1126_science.aar4005", + "Article Title": "Topological insulator laser: Experiments", + "Authors": "Bandres, MA; Wittek, S; Harari, G; Parto, M; Ren, JH; Segev, M; Christodoulides, DN; Khajavikhan, M", + "Source Title": "SCIENCE", + "Abstract": "Physical systems exhibiting topological invariants are naturally endowed with robustness against perturbations, as manifested in topological insulators-materials exhibiting robust electron transport, immune from scattering by defects and disorder. Recent years have witnessed intense efforts toward exploiting these phenomena in photonics. Here we demonstrate a nonmagnetic topological insulator laser system exhibiting topologically protected transport in the cavity. Its topological properties give rise to single-mode lasing, robustness against defects, and considerably higher slope efficiencies compared to the topologically trivial counterparts. We further exploit the properties of active topological platforms by assembling the system from S-chiral microresonators, enforcing predetermined unidirectional lasing without magnetic fields. This work paves the way toward active topological devices with exciting properties and functionalities.", + "Times Cited, WoS Core": 1042, + "Times Cited, All Databases": 1120, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000435220800001", + "Markdown": "# Topological insulator laser: Experiments \n\nMiguel A. Bandres,\\* Steffen Wittek,\\* Gal Harari,\\* Midya Parto, Jinhan Ren, Mordechai Segev, $\\cdot\\dagger$ Demetrios N. Christodoulides, $\\cdot\\dagger$ Mercedeh Khajavikhan† \n\nINTRODUCTION: Physical systems that exhibit topological invariants are naturally endowed with robustness against perturbations, as was recently demonstrated in many settings in condensed matter, photonics, cold atoms, acoustics, and more. The most prominent manifestations of topological systems are topological insulators, which exhibit scatter-free edge-state transport, immune to perturbations and disorder. Recent years have witnessed intense efforts toward exploiting these physical phenomena in the optical domain, with new ideas ranging from topology-driven unidirectional devices to topological protection of path entanglement. But perhaps more technologically relevant than all topological photonic settings studied thus far is, as proposed by the accompanying theoretical paper by Harari et al., an all-dielectric magnet-free topological insulator laser, with desirable properties stemming from the topological transport of light in the laser cavity. \n\nRATIONALE: We demonstrate nonmagnetic topological insulator lasers. The topological properties of the laser system give rise to singlemode lasing, robustness against fabrication defects, and notably higher slope efficiencies compared to those of the topologically trivial counterparts. We further exploit the properties of by observing that in the topological array, all sites emit coherently at the same wavelength, whereas in the trivial array, lasing occurs in localized regions, each at a different frequency. Also, by pumping only part of the topological array, we demonstrate that the topological edge mode always travels along the perimeter and emits light the active topological platform by assembling topological insulator lasers from $s$ -chiral microresonators that enforce predetermined unidirectional lasing even in the absence of magnetic fields. \n\nRESULTS: Our topological insulator laser system is an aperiodic array of 10 unit cell–by–10 unit cell coupled ring resonators on an InGaAsP quantum wells platform. The active lattice uses the topological architecture suggested in the accompanying theoretical paper. This twodimensional setting is composed of a square lattice of ring resonators coupled to each other by means of link rings. The intermediary links are judiciously spatially shifted to introduce a set of hopping phases, establishing a synthetic magnetic field and two topological band gaps. The gain in this laser system is provided by optical pumping. To promote lasing of the topologically protected edge modes, we pump the outer perimeter of the array while leaving the interior lossy. We find that this topological insulator laser operates in single mode even considerably above threshold, whereas the corresponding topologically trivial realizations lase in multiple modes. Moreover, the topological laser displays a slope efficiency that is considerably higher than that in the corresponding trivial realizations. We further demonstrate the topological features of this laser \n\n# ON OUR WEBSITE \n\n# TOPOLOGICAL PHOTONICS \n\nthroughtheoutputcoupler. Bycontrast,whenwepump the trivial array far from the output coupler, no light is extracted from the coupler because the lasing occurs at stationary modes. We also \n\nRead the full article at http:/ dx.doi. org/10.1126/ science.aar4005 \n\nobserve that, even in the presence of defects, the topological protection always leads to more efficient lasing compared to that of the trivial counterpart. Finally, to show the potential of this active system, we assemble a topological system based on S-chiral resonators, which can provide new avenues to control the topological features. \n\nCONCLUSION: We have experimentally demonstrated an all-dielectric topological insulator laser and found that the topological features enhancethelasingperformanceofa two-dimensional array of microresonators, making them lase in unison in an extended topologically protected scatter-free edge mode. The observed single longitudinal-mode operation leads to a considerably higher slope efficiency as compared to that of a corresponding topologically trivial system. Our results pave the way toward a new class of active topological photonic devices, such as laser arrays, that can operate in a coherent fashion with high efficiencies.▪ \n\n![](images/d73deac5be2396513eb56f64f48335b690d47ec3eedbf8c5a590ddd97b35e48d.jpg) \nTopological insulator laser. (A) Top-view image of the lasing pattern (topological edge mode) in a 10 unit cell–by–10 unit cell array of topologicall coupled resonators and the output ports. (B) Output intensity versus pump intensity for a topological insulator laser and its trivial counterpart. The enhancement of the slope efficiency is about threefold. Comparing the power emitted in the single mode of the topological array to that of the highest power mode in the trivial array, the topological outperforms the trivial by more than a factor of 10. (C) Emission spectra from a topological insulator laser and its topologically trivial counterpart. au, arbitrary units. \n\n# TOPOLOGICAL PHOTONICS \n\n# Topological insulator laser: Experiments \n\nMiguel A. Bandres,1\\* Steffen Wittek,2\\* Gal Harari,1\\* Midya Parto,2 Jinhan Ren,2 Mordechai Segev,1† Demetrios N. Christodoulides, $^{2}\\dag$ Mercedeh Khajavikhan2† \n\nPhysical systems exhibiting topological invariants are naturally endowed with robustness against perturbations, as manifested in topological insulators—materials exhibiting robust electron transport, immune from scattering by defects and disorder. Recent years have witnessed intense efforts toward exploiting these phenomena in photonics. Here we demonstrate a nonmagnetic topological insulator laser system exhibiting topologically protected transport in the cavity. Its topological properties give rise to single-mode lasing, robustness against defects, and considerably higher slope efficiencies compared to the topologically trivial counterparts. We further exploit the properties of active topological platforms by assembling the system from S-chiral microresonators, enforcing predetermined unidirectional lasing without magnetic fields.This work paves the way toward active topological devices with exciting properties and functionalities. \n\nopological insulators are a phase of matter that feature an insulating bulk while supporting conducting edge states (1–3). Notably, the transport of edge states in topological insulators is granted topological protection, a property stemming from the underlying topological invariants (2). For example, in twodimensional (2D) systems, the ensued one-way conduction along the edge of a topological insulator is, by nature, scatter free—a direct outcome of the nontrivial topology of the bulk electronic wave functions (3). Although topological protection was initially encountered in the integer quantum Hall effect (4), the field of topological physics developed rapidly after it was recognized that topologically protected transport can also be observed even in the absence of a magnetic field (5, 6). This, in turn, spurred a flurry of experimental activities in a number of electronic material systems (7). The promise of robust transport inspired studies in many and diverse fields beyond solid-state physics, such as optics, ultracold atomic gases, mechanics, and acoustics (8–25). Along these lines, unidirectional topological states were observed in microwave settings (9) in the presence of a magnetic field (the electromagnetic analog of the quantum Hall effect), and, more recently, topologically protected transport phenomena have been successfully demonstrated in optical passive all-dielectric environments by introducing artificial gauge fields (14, 15). \n\nIn photonics, topological concepts could lead to new families of optical structures and devices by exploiting robust, scatter-free light propagation. Lasers, in particular, could directly benefit from such attributes [see the accompanying theoretical paper (26)]. In general, laser cavities are prone to disorder, which inevitably arises from fabrication imperfections, operational degradation, and malfunction. Specifically, the presence of disorder in a laser gives rise to spatial light localization within the cavity, ultimately resulting in a degraded overlap of the lasing mode with the gain profile. This implies lower output coupling, multimode lasing, and reduced slope efficiency. These issues become acute in arrays of coupled laser resonators (used to yield higher power), in which a large number of elements is involved. Naturally, it would be of interest to exploit topological features in designing laser systems that are immune to disorder. In this spirit, several groups have recently studied edge-mode lasing in topological 1D Su-Schrieffer-Heeger resonator arrays (27–29). However, being one-dimensional, they lase in a zero-dimensional defect state, which inherently cannot provide protected transport. Conversely, 2D laser systems can directly benefit from topological protection. Indeed, it was shown theoretically that it is possible to harness the underlying features of topological insulators in 2D laser arrays, when lasing in an extended topological state (26, 30, 31). As indicated there, such systems can operate in a single-mode fashion with high slope efficiencies, in spite of appreciable disorder. In a following development, unidirectional edge-mode lasing was demonstrated in a topological photonic crystal configuration involving a yttrium iron garnet (YIG) substrate under the action of a magnetic field (32). In that system, lasing occurred within a narrow spectral band gap induced by magneto-optic effects. Clearly, it would be of interest to pursue magnet-free approaches that are, by nature, more compatible with fabrication procedures and photonic integration involving low-loss components. In addition, such all-dielectric systems can prove advantageous in substantially expanding the topological band gap and, in doing that, bring the topological protection of photon transport to the level at which lasing is immune to defects and disorder. \n\nHere we report the first observation of topologically protected edge-mode lasing in nonmagnetic, \n\nFig. 1. Topological insulator laser: Lattice geometry. (A) Microscope image of an active InGaAsP topological 10 unit cell–by–10 unit cell microresonator array. (B) Scanning electron microscopy (SEM) image of the outcoupling grating structures used to probe the array at the orange-outlined locations indicated in (A). (C) Magnification of the blue-outlined area indicated in (A), showing a SEM micrograph of a unit cell comprised of a primary ring site surrounded by four identical intermediary racetrack links. (D) A schematic of the topological array when \n\n![](images/17e5d3350193c8fcadf086c6b1c8498760f3e7f45a98b4381c9faf1faa05ef59.jpg) \n\npumped along the perimeter to promote lasing of the topological edge mode. \n\n2D topological cavity arrays. We show that this topological insulator laser can operate in single mode, even considerably above threshold, with a slope efficiency that is significantly higher than that achieved in their corresponding trivial realizations. Moreover, we observe experimentally that the topological protection leads to more efficient lasing in the 2D array than in the trivial counterpart, even in the presence of defects. Finally, to show the potential of this active system, we assemble a topological system based on $s.$ -chiral resonators, which can provide new avenues to control the topological features. \n\nDesign of the topological insulator laser We fabricated a 10 unit cell–by–10 unit cell coupled ring-resonator array on an active platform involving vertically stacked ${30}{\\cdot}\\mathrm{nm}$ -thick InGaAsP quantum wells [see (33), Fig. 1A]. We coupled the array to a waveguide that acts as an output coupler, which allowed us to interrogate the system using outcoupling gratings (Fig. 1B, corresponding to the yellow framed regions in Fig. 1A). The active lattice investigated here uses a topological architecture suggested in (26), which is based on adding gain and loss to the topological passive silicon platform demonstrated in (15). This 2D setting comprises a square lattice of ring resonators, which are coupled to each other through link rings (Fig. 1, A and C). The link rings are designed to be antiresonant to the main ring resonators. In this all-dielectric design, the intermediary links are judiciously spatially shifted along the $y$ axis, with respect to the ring resonators, to introduce an asymmetric set of hopping phases. The phase shift is sequentially increased along the $y$ axis in integer multiples of $\\pm2\\pi\\upalpha$ , designed here to be $\\mathrm{\\Delta}\\mathrm{a}=0.25$ , where $\\upalpha$ is proportional to the equivalent magnetic flux quanta passing through a unit cell. In this way, a round trip along any plaquette (consisting of four rings and four links) results in a total accumulated phase of $\\pm2\\pi\\upalpha$ , where the sign depends on the direction of the path along this unit cell. This provides the lattice with a synthetic magnetic field and establishes two topologically nontrivial band gaps. The cross section of each ring (500-nm width and $210\\mathrm{-nm}$ height) is designed to ensure single transverse-mode conditions at a wavelength of operation of $1550~\\mathrm{nm}$ (33). The nominal separation between the ringresonators and off-resonant links is $\\mathbf{150}\\mathrm{nm}$ , thus leading to two frequency band gaps, each having a width of 80 GHz $\\left(0.64\\mathrm{nm}\\right)$ ). The spectral size of the two band gaps was obtained by experimentally measuring the frequency splitting $(0.8\\mathrm{nm})$ in a binary system of primary resonators, linked by means of an intermediate racetrack ring [see (33), part 9]. To promote protected edge-mode lasing, we optically pumped only the outer perimeter of this array at $1064\\mathrm{nm}$ with 10-ns pulses (Fig. 1D). This was achieved using a set of appropriate amplitude masks [see (33), part 1]. The intensity structure of the lasing modes was captured by using an InGaAs infrared camera, and their spectral content was then analyzed by using a spectrometer with an array detector (33). In what follows, we compare the features of the topological insulator lasers $\\mathrm{{'a}}=0.25\\mathrm{{'}}$ with those of their trivial counterparts $\\mathbf{\\check{\\Psi}}(\\mathbf{\\boldsymbol{a}}=\\mathbf{\\boldsymbol{0}}$ ) under various conditions. \n\n![](images/029c51d6a12d687ea1e9a371b24fbbc77f3e5de5b100a3e3271bb575564ffdba.jpg) \nFig. 2. Slope efficiencies and associated spectra of topological and trivial laser arrays. (A) Output intensity versus pump intensity for a 10 unit cell–by–10 unit cell topological array with $\\upalpha=0.25$ and its corresponding trivial counterpart $\\mathrm{\\langlea=0}^{\\cdot}$ ). In this experiment, the enhancement of the slope efficiency is about threefold. (B) Emission spectra from a trivial and a topological array when pumped at $23.5\\mathsf{k W}/\\mathsf{c m}^{2}$ . au, arbitrary units. (C and D) Evolution of the spectrum as a function of the pumping intensity for (C) topological and (D) trivial arrays. Single-mode, narrow-linewidth lasing in (C) is clearly evident. \n\n# Studying the features of the topological insulator laser \n\nThe edge mode can be made to lase by pumping the boundary of the topological array (26). In this case, a clear signature of topological lasing would be highly efficient single-mode emission, even at gain values high above the threshold. To observe these features in experiments, we pumped the perimeter of the topological and trivial arrays and measured the lasing output power (integrated over the two outcoupling gratings) and its spectral content. The light-light curves measured for the topological and the trivial arrays (Fig. 2A) clearly show that the topological system lases with a higher efficiency than its trivial counterpart. From their measured spectra (Fig. 2, B and D), we observe that the topological arrays remain single moded over a wide range of pumping densities (Fig. 2C), whereas the trivial arrays (tested over multiple samples) always emit in multiple wavelengths with considerably broader linewidths (Fig. 2D). Importantly, if we only compare the power emitted in the dominant (longitudinal) mode of the topological array to the mode with the highest power in the trivial array, the topological laser outperforms the trivial one by more than an order of magnitude. This difference in performance is attributed to the physical properties of the topological edge modes. The trivial array suffers from several drawbacks. First, the trivial lasing modes extend into the lossy bulk, thus experiencing suppressed emission. Second, the trivial lasing modes try to avoid the output coupler so as to optimize their gain. And finally, because of intrinsic disorder in fabrication, the lasing mode localizes in several different parts of the trivial lattice, each lasing at a different frequency, thereby giving rise to a multimode behavior. Conversely, apart from a weak exponential penetration into the bulk, in topological arrays the edge states are strongly confined to the edge. Moreover, because they are forced to flow around the perimeter, they are always in contact with the output coupler. Finally, because of its inherent topological properties, the lasing edge mode does not suffer from localization, and therefore it uniformly extends around the perimeter (in a single mode), using all the available gain in the system by suppressing any other parasitic mode. \n\nTo demonstrate that these active lattices exhibit topological features, we compared their and exits mostly through the left output grating, whereas the lasing mode in (D) never reaches the output coupler. (C) and (G) present similar results when the pumping region at the right side is further extended into the array. In (G), the lasing edge mode again travels all the way to the output port, whereas the lasing modes of the trivial lattice never reach the extracting ports in (C). This proves that the topological mode travels around the perimeter and always reaches the output port, whereas the lasing modes of the trivial lattice are stationary. The pumping conditions are shown above the labeled panels. \n\n![](images/a164f870f751b7d6d6307f3eea0dc2b825ad120d977c5e4b659fcd1cdfbda4e0.jpg) \nFig. 3. Lasing characteristics of topological lattices versus those of their corresponding trivial counterparts under several pumping conditions. (A to D) Trivial and (E to H) topological lattices. Lasing in a (B) trivial and (F) topological array when their full perimeter is selectively pumped. (A) and (E) represent the spectral content as obtained from specific edge sites of the arrays depicted in (B) and (F), correspondingly. Notice that the topological lattice remains single moded, whereas the trivial one emits in multiple modes. Lasing transport in a (D) trivial array and (H) topological lattice when the right side is pumped. The lasing edge mode in (H) travels (blue arrow) along the unpumped perimeter \n\nlasing response against that of their trivial counterparts $\\mathbf{\\check{\\Psi}}_{\\mathrm{~}}\\mathrm{\\left(\\mathfrak{X}\\mathrm{~=~}\\mathbf{0}\\right)\\Psi}$ ) when their periphery is pumped. The emission intensity profiles obtained from these two systems are shown in Fig. 3, B and C. To check whether the lasing modes are extended or localized around the perimeter of the lattice, we measured the spectrum of the light emitted from different sites around the arrays (Fig. 3, A and E). For the trivial array, we observed that the spectrum varies around the lattice, with emission occurring over a wide wavelength range, spanning from 1543 to $1570\\mathrm{nm}$ , as shown in Fig. 3A. This is an indication that the trivial array lases in localized domains, each one at a different frequency. By sharp contrast, in the topological array, all sites emit coherently at the same wavelength (Fig. 3E). Such lasing, in a single extended topological edge mode, is a direct manifestation of topologically protected transport. These results are consistent with those presented in Fig. 2. The full spectra of Fig. 3, A and E, are given in (33). \n\nTopological transport in these structures was further investigated by selectively pumping the lattice. First, we pumped only one edge of the 2D array, as depicted in Fig. 3D (inset). Under these conditions, the lasing mode in the trivial system is confined to the pumped region (Fig. 3D). In this arrangement, the emission is heavily suppressed both in the bulk as well as along the perimeter, and, consequently, no light is extracted from any of the output grating couplers. By contrast, for the topological array, even when only one side is pumped, the edge mode flows along the periphery, finally reaching the output coupler, as shown in Fig. 3H. In this case, only one output coupler grating emits strongly. This indicates that the lasing mode that reaches the output coupler has a definite chirality in each ring. Given that the emission is in a single mode, one can conclude that lasing takes place in only one topological mode. To show that in the topological case, it is the edge mode that lases, \n\n![](images/471f9b93ac1ecf1a0c066727e00a6ec2d13f86515c7feb3827129426b524a5ca.jpg) \nFig. 4. Robust behavior of the lasing edge mode with respect to defects in a topological array. (A and B) Lasing response of a (A) topological and (B) trivial array in the presence of two defects intentionally inserted on the periphery, under the same pumping intensity. Note that the edge mode transport in (A) (blue arrow) bypasses the defects, whereas in its trivial counterpart, the lasing occurs from the three separate sections. \n\n![](images/f9475900fea50374258619b7e34e7a33bf08afed87126981c58094a407026f46.jpg) \nFig. 5. Topological active array involving chiral S-microresonator elements. (A) SEM image of a 10 unit cell–by–10 unit cell topological array. The primary resonators feature an internal S-bend for enforcing, in this case, a right spin, whereas the intermediate link design is the same as in Fig. 1C. (B) A magnification of the SEM micrograph in (A) of the basic elements involved. (C) Field distribution in an individual \n\nS-element, as obtained from finite-difference time-domain simulations. (D) Measured intensity profile associated with the lasing edge mode in a topological array with $\\upalpha=0.25$ . In this system, the perimeter is selectively pumped, and the energy in each ring circulates in a counterclockwise manner, as indicated by the radiation emerging from the extracting ports. \n\nwhereas in the trivial case the bulk states lase, we expanded the pumping region at the right edge (Fig. 3C, inset). In the trivial case, even though pumping over a larger area is now provided, still no laser light reaches the output ports (Fig. 3C). This means that there are no traveling edge modes that could reach the output ports. Conversely, for the topological array, the lasing edge mode reaches the output coupler with a fixed chirality within each ring (Fig. 3G). This shows that the topological lasing mode extends around the perimeter and travels all the way to the output ports, whereas the lasing in the trivial case occurs in stationary localized modes. In this vein, we tested multiple samples and found that the same features consistently emerged in a number of different designs (different resonance frequencies, couplings, etc.) in a universal manner. A video showing the behaviors of partially pumped topological and trivial arrays are provided as supplementary materials [see (33), part 10] and more features associated with these arrays can be found in [(33), parts 3 and 5]. \n\n# Introducing defects \n\nNext, we studied lasing in a topological structure and in its trivial counterpart, in the presence of defects, which are intentionally introduced into the structures. We removed specific microrings along the perimeter, where pumping is provided (i.e., we remove two gain elements). Figure 4 shows the light emission from these two types of structures. These results demonstrate that in a topological system (Fig. 4A), light is capable of bypassing the defects by penetrating into the bulk and displaying lasing in an extended edge mode of almost uniform intensity. Conversely, the intensity of the emitted light in the trivial structure is considerably suppressed (Fig. 4B), and the defects effectively subdivide the perimeter into separate regions that lase independently (both measurements were performed at identical pump power levels). Hence, the topological insulator laser is robust against defects, even when introduced into the gain regions. [Further evidence of this robustness in the presence of disorder is given in (33), part 8.] \n\n# Laser based on an array of chiral S-bend elements \n\nHaving established the underlying concepts of the topological insulator laser and the promise it holds for exploring new aspects of topological physics, specifically in active media, it is interesting to discuss some of the directions to which these ideas can lead. As an example, embarking on fundamental aspects such as Maxwell’s reciprocity in the presence of nonlinearity, as well as on potential applications, we modified the individual resonators in the topological insulator laser so as to break the symmetry between the clockwise (CW) and counterclockwise (CCW) modes in each ring. Instead of using conventional rings, we used a special S-bend design $\\textcircled{34}$ for each primary cavity element in the topological lattice (Fig. 5, A and B). The intermediary links remained the same as in the previous designs (Fig. 1A). In this system, each laser microresonator selectively operates in a single spinlike manner, i.e., in either the CW or the CCW direction, by exploiting gain saturation and energy recirculation among these modes. The S-chiral elements involved, in the presence of nonlinearity (gain saturation) and the spatial asymmetry of the $s$ - bends, add unidirectionality to the topological protection of transport. In the experiments described in Fig. 5, we observe suppression of more than 12 dB between the right- and left-hand spins in each resonator [see (33), part 6]. Finitedifference time-domain simulations also indicate that the differential photon lifetime between the right and left spins in these S-bend cavities is about 3 ps, corresponding to an equivalent loss coefficient of $10~\\mathrm{{cm}^{-1}}$ [more details are outlined in (33), part 7]. The field distribution in the prevalent spinning mode in these active S-resonators is shown in Fig. 5C, featuring a high degree of power recirculation through the S-structure that is responsible for the spinlike mode discrimination. The corresponding intensity profile associated with this unidirectional edge-mode energy transport is shown in Fig. 5D. In this case, energy is predominantly extracted from only one of the two outcoupling gratings (with a \\~10-dB rejection ratio), which is an indication of unidirectional energy flow in the rings of this topological array. \n\n# Discussion \n\nOur all-dielectric topological insulator laser exploits its topological features to enhance the lasing performance of a 2D array of microresonators, making them lase in unison in an extended topologically protected scatter-free edge mode. The observed single longitudinal-mode operation leads to a considerably higher slope efficiency as compared to a corresponding topologically trivial system. The systems described here are based on contemporary fabrication technologies of semiconductor lasers, without need for magnetic units of exotic materials. Our results provide a route for developing a new class of active topological photonic devices, especially arrays of semiconductor lasers, that can operate in a coherent fashion with high slope efficiencies. \n\n# REFERENCES AND NOTES \n\n1. D. J. Thouless, M. Kohmoto, M. P. Nightingale, M. Den Nijs, Quantized Hall conductance in a two-dimensional periodic potential. Phys. Rev. Lett. 49, 405–408 (1982). doi: 10.1103/PhysRevLett.49.405 \n2. M. Hasan, C. Kane, Colloquium: Topological insulators. Rev. Mod. Phys. 82, 3045–3067 (2010). doi: 10.1103/RevModPhys.82.3045 \n3. X.-L. Qi, S.-C. Zhang, Topological insulators and superconductors. Rev. Mod. Phys. 83, 1057–1110 (2011). doi: 10.1103/RevModPhys.83.1057 \n4. K. V. Klitzing, G. Dorda, M. Pepper, New method for highaccuracy determination of the fine-structure constant based on quantized Hall resistance. Phys. Rev. Lett. 45, 494–497 (1980). doi: 10.1103/PhysRevLett.45.494 \n5. C. L. Kane, E. J. Mele, Quantum spin Hall effect in graphene. Phys. Rev. Lett. 95, 226801 (2005). pmid: 16384250 \n6. B. A. Bernevig, T. L. Hughes, S.-C. Zhang, Quantum spin Hall effect and topological phase transition in HgTe quantum wells. Science 314, 1757–1761 (2006). doi: 10.1126/ science.1133734; pmid: 17170299 \n7. M. König et al., Quantum spin hall insulator state in HgTe quantum wells. Science 318, 766–770 (2007). doi: 10.1126/ science.1148047; pmid: 17885096 \n8. F. D. Haldane, S. Raghu, Possible realization of directional optical waveguides in photonic crystals with broken time-reversal symmetry. Phys. Rev. Lett. 100, 013904 (2008). doi: 10.1103/PhysRevLett.100.013904; pmid: 18232766 \n9. Z. Wang, Y. Chong, J. D. Joannopoulos, M. Soljacić, Observation of unidirectional backscattering-immune topological electromagnetic states. Nature 461, 772–775 (2009). doi: 10.1038/nature08293; pmid: 19812669 \n10. L. Lu, J. D. Joannopoulos, M. Soljačić, Topological photonics. Nat. Photonics 8, 821–829 (2014). doi: 10.1038/ nphoton.2014.248 \n11. M. Hafezi, E. Demler, M. Lukin, J. Taylor, Robust optical delay lines via topological protection. Nat. Phys. 7, 907–912 (2011). doi: 10.1038/nphys2063 \n12. K. Fang, Z. Yu, S. Fan, Realizing effective magnetic field for photons by controlling the phase of dynamic modulation. Nat. Photonics 6, 782–787 (2012). doi: 10.1038/ nphoton.2012.236 \n13. A. B. Khanikaev et al., Photonic topological insulators. Nat. Mater. 12, 233–239 (2013). doi: 10.1038/nmat3520; pmid: 23241532 \n14. M. C. Rechtsman et al., Photonic Floquet topological insulators. Nature 496, 196–200 (2013). doi: 10.1038/nature12066; pmid: 23579677 \n15. M. Hafezi, S. Mittal, J. Fan, A. Migdall, J. M. Taylor, Imaging topological edge states in silicon photonics. Nat. Photonics 7, 1001–1005 (2013). doi: 10.1038/nphoton.2013.274 \n16. L. Tarruell, D. Greif, T. Uehlinger, G. Jotzu, T. Esslinger, Creating, moving and merging Dirac points with a Fermi gas in a tunable honeycomb lattice. Nature 483, 302–305 (2012). doi: 10.1038/nature10871; pmid: 22422263 \n17. M. Atala et al., Direct measurement of the Zak phase in topological Bloch bands. Nat. Phys. 9, 795–800 (2013). doi: 10.1038/nphys2790 \n18. C. L. Kane, T. C. Lubensky, Topological boundary modes in isostatic lattices. Nat. Phys. 10, 39–45 (2013). doi: 10.1038/nphys2835 \n19. Z. Yang et al., Topological acoustics. Phys. Rev. Lett. 114, 114301 (2015). doi: 10.1103/PhysRevLett.114.114301; pmid: 25839273 \n20. R. Fleury, A. B. Khanikaev, A. Alù, Floquet topological insulators for sound. Nat. Commun. 7, 11744 (2016). doi: 10.1038/ ncomms11744; pmid: 27312175 \n21. Z. Yu, G. Veronis, Z. Wang, S. Fan, One-way electromagnetic waveguide formed at the interface between a plasmonic metal under a static magnetic field and a photonic crystal. Phys. Rev. Lett. 100, 023902 (2008). doi: 10.1103/ PhysRevLett.100.023902; pmid: 18232868 \n22. X. Cheng et al., Robust reconfigurable electromagnetic pathways within a photonic topological insulator. Nat. Mater. 15, 542–548 (2016). doi: 10.1038/nmat4573; pmid: 26901513 \n23. G. Jotzu et al., Experimental realization of the topological Haldane model with ultracold fermions. Nature 515, 237–240 (2014). doi: 10.1038/nature13915; pmid: 25391960 \n24. M. Aidelsburger et al., Measuring the Chern number of Hofstadter bands with ultracold bosonic atoms. Nat. Phys. 11, 162–166 (2015). doi: 10.1038/nphys3171 \n25. A. P. Slobozhanyuk et al., Experimental demonstration of topological effects in bianisotropic metamaterials. Sci. Rep. 6, 22270 (2016). doi: 10.1038/srep22270; pmid: 26936219 \n26. G. Harari et al., Topological insulator laser: Theory. Science 359, eaar4003 (2018). doi: 10.1126/science.aar4003 \n27. P. St-Jean, V. Goblot, E. Galopin, A. Lemaître, T. Ozawa, L. Le Gratiet, I. Sagnes, J. Bloch, A. Amo, Lasing in topological edge states of a 1D lattice. arXiv:1704.07310 [cond-mat. mes-hall] (24 April 2017). \n28. M. Parto, S. Wittek, H. Hodaei, G. Harari, M. A. Bandres, J. Ren, M. C. Rechtsman, M. Segev, D. N. Christodoulides, M. Khajavikhan, Complex edge-state phase transitions in 1D topological laser arrays. arXiv:1709.00523 [physics.optics] (2 September 2017). \n29. H. Zhao, P. Miao, M. H. Teimourpour, S. Malzard, R. El-Ganainy, H. Schomerus, L. Feng, Topological hybrid silicon microlasers. arXiv:1709.02747 [physics.optics] (8 September 2016). \n30. G. Harari et al., in Conference on Lasers and Electro-Optics (OSA Technical Digest, Optical Society of America, paper FM3A.3, 2016). \n31. S. Wittek et al., in Conference on Lasers and Electro-Optics (OSA Technical Digest, Optical Society of America, paper FTh1D.3, 2017). \n32. B. Bahari et al., Nonreciprocal lasing in topological cavities of arbitrary geometries. Science 358, 636–640 (2017). doi: 10.1126/science.aao4551; pmid: 29025992 \n33. Materials and methods are available as supplementary materials. \n34. J. P. Hohimer, G. A. Vawter, D. C. Craft, Unidirectional operation in a semiconductor ring diode laser. Appl. Phys. Lett. 62, 1185–1187 (1993). doi: 10.1063/1.108728 \n\n# ACKNOWLEDGMENTS \n\nFunding: The authors gratefully acknowledge financial support from the Israel Science Foundation, Office of Naval Research (N0001416-1-2640), NSF (ECCS1454531, DMR-1420620, ECCS 1757025), European Commission Non-Hermitian Quantum Wave Engineering (NHQWAVE) project (MSCA-RISE 691209), Air Force Office of Scientific Research (FA9550-14-1-0037), United States– Israel Binational Science Foundation (2016381), German-Israeli Project Cooperation (Deutsch-Israelische Projektkooperation) program, and Army Research Office (W911NF-16-1-0013, W911NF17-1-0481). M.S. thanks M. Karpovsky and B. Shillman for their support that came at a critical time. Author contributions: All authors contributed to all aspects of this work. Competing interests: The authors declare no competing interests. Data and materials availability: All data needed to evaluate the conclusions in this paper are available in the manuscript and in the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/359/6381/eaar4005/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S11 \nReference (35) \nMovies S1 and S2 \n3 November 2017; accepted 17 January 2018 \nPublished online 1 February 2018 \n10.1126/science.aar4005 \n\n# Science \n\n# Topological insulator laser: Experiments \n\nMiguel A. Bandres, Steffen Wittek, Gal Harari, Midya Parto, Jinhan Ren, Mordechai Segev, Demetrios N. Christodoulides and Mercedeh Khajavikhan \n\nScience 359 (6381), eaar4005. DOI: 10.1126/science.aar4005originally published online February 1, 2018 \n\n# Topological protection for lasers \n\nIdeas based on topology, initially developed in mathematics to describe the properties of geometric space under deformations, are now finding application in materials, electronics, and optics. The main driver is topological protection, a property that provides stability to a system even in the presence of defects. Harari et al. outline a theoretical proposal that carries such ideas over to geometrically designed laser cavities. The lasing mode is confined to the topological edge state of the cavity structure. Bandres et al. implemented those ideas to fabricate a topological insulator laser with an array of ring resonators. The results demonstrate a powerful platform for developing new laser systems. \n\nScience, this issue p. eaar4003, p. eaar4005 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2018/01/31/science.aar4005.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/359/6381/eaar4003.full \n\nREFERENCES \n\nThis article cites 23 articles, 3 of which you can access for free http://science.sciencemag.org/content/359/6381/eaar4005#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41567-018-0234-5", + "DOI": "10.1038/s41567-018-0234-5", + "DOI Link": "http://dx.doi.org/10.1038/s41567-018-0234-5", + "Relative Dir Path": "mds/10.1038_s41567-018-0234-5", + "Article Title": "Giant anomalous Hall effect in a ferromagnetic kagome-lattice semimetal", + "Authors": "Liu, EK; Sun, Y; Kumar, N; Muechler, L; Sun, AL; Jiao, L; Yang, SY; Liu, DF; Liang, AJ; Xu, QN; Kroder, J; Süss, V; Borrmann, H; Shekhar, C; Wang, ZS; Xi, CY; Wang, WH; Schnelle, W; Wirth, S; Chen, YL; Goennenwein, STB; Felser, C", + "Source Title": "NATURE PHYSICS", + "Abstract": "Magnetic Weyl semimetals with broken time-reversal symmetry are expected to generate strong intrinsic anomalous Hall effects, due to their large Berry curvature. Here, we report a magnetic Weyl semimetal candidate, Co3Sn2S2, with a quasi-two-dimensional crystal structure consisting of stacked kagome lattices. This lattice provides an excellent platform for hosting exotic topological quantum states. We observe a negative magnetoresistance that is consistent with the chiral anomaly expected from the presence of Weyl fermions close to the Fermi level. The anomalous Hall conductivity is robust against both increased temperature and charge conductivity, which corroborates the intrinsic Berry-curvature mechanism in momentum space. Owing to the low carrier density in this material and the considerably enhanced Berry curvature from its band structure, the anomalous Hall conductivity and the anomalous Hall angle simultaneously reach 1,130 Omega(-1) cm(-1) and 20%, respectively, an order of magnitude larger than typical magnetic systems. Combining the kagome-lattice structure and the long-range out-of-plane ferromagnetic order of Co3Sn2S2, we expect that this material is an excellent candidate for observation of the quantum anomalous Hall state in the two-dimensional limit.", + "Times Cited, WoS Core": 1020, + "Times Cited, All Databases": 1097, + "Publication Year": 2018, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000448973100019", + "Markdown": "# Giant anomalous Hall effect in a ferromagnetic kagome-lattice semimetal \n\nEnke Liu $\\textcircled{10}1,2\\star$ , Yan Sun $\\textcircled{10}1\\star$ , Nitesh Kumar1, Lukas Muechler3, Aili Sun1, Lin Jiao   1, Shuo-Ying Yang4, Defa Liu4, Aiji Liang5,6, Qiunan $\\mathsf{\\pmb{X}}\\mathsf{\\pmb{u}}^{1}$ , Johannes Kroder1, Vicky Süß1, Horst Borrmann1, Chandra Shekhar $@^{1}$ , Zhaosheng Wang7, Chuanying $\\mathsf{\\pmb{X}}\\mathsf{i}^{\\top}$ , Wenhong Wang2, Walter Schnelle1, Steffen Wirth1, Yulin Chen5,8, Sebastian T. B. Goennenwein $\\oplus9$ and Claudia Felser1\\* \n\nMagnetic Weyl semimetals with broken time-reversal symmetry are expected to generate strong intrinsic anomalous Hall effects, due to their large Berry curvature. Here, we report a magnetic Weyl semimetal candidate, $\\cos_{3}\\sin_{2}S_{2},$ with a quasi-twodimensional crystal structure consisting of stacked kagome lattices. This lattice provides an excellent platform for hosting exotic topological quantum states. We observe a negative magnetoresistance that is consistent with the chiral anomaly expected from the presence of Weyl fermions close to the Fermi level. The anomalous Hall conductivity is robust against both increased temperature and charge conductivity, which corroborates the intrinsic Berry-curvature mechanism in momentum space. Owing to the low carrier density in this material and the considerably enhanced Berry curvature from its band structure, the anomalous Hall conductivity and the anomalous Hall angle simultaneously reach $\\mathbf{1}_{r}\\mathbf{130}\\Omega^{-1}\\mathbf{cm}^{-1}$ and $20\\%$ , respectively, an order of magnitude larger than typical magnetic systems. Combining the kagome-lattice structure and the long-range outof-plane ferromagnetic order of $\\mathbf{Co_{3}S n_{2}S_{2}},$ we expect that this material is an excellent candidate for observation of the quantum anomalous Hall state in the two-dimensional limit. \n\nhe anomalous Hall effect (AHE) is an important electronic transport phenomenon1. It can arise because of two qualitatively different microscopic mechanisms: extrinsic processes due to scattering effects, and an intrinsic mechanism connected to the Berry curvature1–5. The large Berry curvature comes from the entangled Bloch electronic bands with spin–orbit coupling when the spatial-inversion or time-reversal symmetry of the material is broken6,7. The quantum AHE in two-dimensional (2D) systems is determined solely by this intrinsic contribution8,9. It manifests itself as a quantized anomalous Hall conductance due to the presence of a bulk gap in combination with dissipationless edge states10–13. A magnetic Weyl semimetal with broken time-reversal symmetry can be interpreted as a stacked heterostructure of such quantum anomalous Hall insulator layers14,15, where the coupling between the layers closes the bulk bandgap at isolated Weyl nodes. At these Weyl nodes, the Berry curvature is enhanced whereas the carrier density vanishes2–4,16,17. This suggests that an intrinsic large anomalous Hall conductivity and a large anomalous Hall angle can be expected in such systems. \n\nTo date, a number of promising candidates for magnetic Weyl semimetals have been proposed, including $\\mathrm{Y}_{2}\\mathrm{Ir}_{2}\\mathrm{O}_{7}$ (ref. 18), $\\mathrm{Hg}\\mathrm{Cr}_{2}\\mathrm{Se}_{4}$ (ref. 19) and certain $\\mathbf{Co}_{2}$ -based Heusler compounds20–22. The experimental identifications for this Weyl phase in these systems are also on the way. Indeed, an anomalous Hall angle of approximately $16\\%$ was recently observed at low temperatures in the magneticfield-induced Weyl semimetal GdPtBi (ref. 23). However, a finite external magnetic field is mandatory to make GdPtBi a Weyl semimetal. Therefore, the search for intrinsic magnetic Weyl semimetals with Weyl nodes close to the Fermi level is not only an efficient strategy to obtain materials exhibiting both a high anomalous Hall conductivity and large anomalous Hall angle, but also important for a comprehensive understanding of Weyl topological effects on the AHE in real materials. \n\nThe kagome lattice has become one of the most fundamental models for exotic topological states in condensed matter physics. In particular, the kagome lattice with out-of-plane magnetization is an excellent platform for investigating the quantum anomalous Hall effect24,25. Thus, it provides an effective guiding principle for realizing magnetic Weyl semimetals via stacking14,15. Although a Dirac dispersion with a finite spin–orbit-coupling-induced gap has recently been observed in a kagome-lattice metal26, the Weyl phase in a magnetic kagome material still remains elusive. Here, we report a timereversal-symmetry-breaking Weyl semimetal in the magnetic kagome-lattice compound $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ with out-of-plane ferromagnetic order, and demonstrate both a large intrinsic anomalous Hall conductivity $(1,130\\Omega^{-1}{\\mathrm{cm}}^{-1})$ and a giant anomalous Hall angle $(20\\%)$ . \n\n$\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ , a Shandite compound, is known to be a ferromagnet with a Curie temperature $(T_{\\mathrm{C}})$ of 177 K and a magnetic moment of $0.29\\mu_{\\mathrm{B}}/\\mathrm{Co}^{27-29}$ . Magnetization measurements have shown that the easy axis of the magnetization lies along the $\\boldsymbol{\\mathscr{c}}$ axis30, while photoemission measurements and band structure calculations revealed that, below $T_{\\mathrm{c}},\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ exhibits Type-IA half-metallic ferromagnetism in which spin-minority states are gapped31,32. Figure 1 summarizes the structural and electronic properties of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . As shown in Fig. 1a, $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ crystallizes in a rhombohedral structure of the space group, $R{-}3m$ (no. $166)^{27}$ . The crystal possesses a quasi-2D $\\mathrm{Co}_{3}\\mathrm{Sn}$ layer sandwiched between sulfur atoms, with the magnetic cobalt atoms arranged on a kagome lattice in the $a{-}b$ plane in the hexagonal representation of the space group. Owing to the strong magnetic anisotropy, this material shows a long-range quasi-2D type of magnetism30. Our magnetization measurements revealed a fairly low saturation field $({\\sim}0.05\\mathrm{T})$ along the $c$ axis and an extremely high saturation field $(>9\\mathrm{T})$ in the $a{-}b$ plane, confirming a dominantly out-of-plane magnetization in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ (see Supplementary Information). By itself, the dimensional restriction of the outof-plane magnetization may be responsible for some of the interesting electronic and magnetic properties of this compound. We discuss band structure calculations of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ with spin polarization along the $c$ axis. The calculated magnetic moments without and with spin–orbit coupling are 0.33 and $0.30\\mu_{\\mathrm{B}}/\\mathrm{Co},$ respectively, which are very close to the experimental values of $0.29\\mu_{\\mathrm{B}}/\\mathrm{Co}$ obtained from neutron diffraction29, $0.31\\mu_{\\mathrm{B}}/\\mathrm{Co}$ from magnetization measurements30, and $0.30\\mu_{\\mathrm{B}}/\\mathrm{Co}$ from our measurement (see Supplementary Information). As expected, the calculation including spin–orbit coupling yields a more accurate result. \n\n![](images/b1dc624ab55a4cb57494515eefb0e6536a84255939242f7bd339fb3d65956326.jpg) \nFig. 1 | Crystal and electronic structures of $\\mathsf{C o}_{3}\\mathsf{S n}_{2}\\mathsf{S}_{2}$ and the measured electric resistivity. a, Unit cell in a hexagonal setting. The cobalt atoms form a ferromagnetic kagome lattice with a $C_{3z}$ -rotation. The magnetic moments are shown along the c axis. b, Energy dispersion of electronic bands along highsymmetry paths without and with spin–orbit coupling, respectively. ‘SOC’ denotes ‘spin–orbit coupling’. c, Fermi surfaces of two bands (upper: electron; lower: hole) under spin–orbit coupling calculations. Different colours indicate different parts of the Fermi surface in the Brillouin zone. d, Temperature dependences of the longitudinal electric resistivity $(\\rho)$ in zero-field and in a field of $9\\mathsf{T}.$ In zero field, a residual resistivity ratio (RRR, $\\rho_{300\\mathsf{K}}/\\rho_{2\\mathsf{K}})$ value of 8.8 and a residual resistivity of $\\rho_{2\\mathrm{K}}{\\sim}50\\upmu\\Omega\\mathrm{cm}$ is observed; $\\rho_{300\\mathsf{K}}$ and $\\rho_{2\\mathsf{K}}$ are resistivities at $300\\mathsf{K}$ and $2\\mathsf{K},$ respectively. e, Magnetoresistance measured in fields up to $\\boldsymbol{14\\intercal}$ at $2\\mathsf{K},$ showing a non-saturated positive magnetoresistance. f, Hall data with a nonlinear behaviour at high fields, indicating the coexistence of electron and hole carriers at $21$ All transport measurements depicted here were performed in an out−​of−​plane configuration with $I//x//[2\\bar{1}\\bar{1}0]$ and $B//z//$ [0001]. The x and $z$ axes, respectively, are thus parallel to the a and c axes shown in a. The hexagon in the inset to d shows the crystallographic orientations of the crystal. The insets to d (right inset), e and f show the directions of the current and magnetic field in the measurements. \n\nThe band structures of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ calculated without and with spin–orbit coupling are shown in Fig. 1b. The bands corresponding to the spin-down channel are insulating in character, with a gap of $0.35\\mathrm{eV},$ whereas the spin-up channel crosses the Fermi level and thus has metallic character. This half-metallic behaviour is consistent with the results of previous studies on this compound30–32. Furthermore, for the spin-up states, we observe linear band crossings along the $\\Gamma{\\mathrm{-}}\\mathrm{L}$ and L–U paths, just slightly above and below the Fermi energy, respectively. For finite spin–orbit coupling, these linear crossings open small gaps with band anti-crossings, and make this compound semimetal-like. The relatively small Fermi surfaces (Fig. 1c), showing the coexistence of holes and electrons, further corroborate the semi-metallic character of this compound. This calculated band structure is in good agreement with our angleresolved photoemission spectroscopy (ARPES) measurements (see Supplementary Information). When these results are considered in conjunction with the ferromagnetism of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ (refs 27–30), they suggest that a time-reversal-symmetry-breaking Weyl semimetal phase might be hidden in this compound. \n\nIn order to confirm this prediction, single crystals of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ were grown for further experimental investigations (see Methods and Supplementary Information). The high quality of the crystals was confirmed by structure refinement based on single-crystal X-ray diffraction and topographic images of the hexagonal lattice array obtained using scanning tunnelling microscopy (see Supplementary Information). As shown in Fig. 1d, the longitudinal electric resistivity $(\\rho)$ decreases with decreasing temperature, showing a kink at $T_{\\mathrm{{C}}}=175\\mathrm{{K}}$ and a moderate residual resistivity of approximately $50\\upmu$ $\\Omega\\mathrm{cmat}2\\mathrm{K}$ In a high field of 9 T, a negative magnetoresistance appears around the Curie temperature owing to the spin-dependent scattering in magnetic systems. At low temperatures, the magnetoresistance increases and becomes positive (Fig. 1d). This behaviour is further demonstrated by the field-dependent resistance (Fig. 1e). Importantly, the positive magnetoresistance shows no signature of saturation even up to $^{14\\mathrm{T},}$ , which is typical of a semimetal33,34. The notable nonlinear field dependence of the Hall resistivity $(\\rho_{\\mathrm{H}})$ (Fig. 1f) further indicates the coexistence of hole and electron carriers at $2\\mathrm{K}.$ , which is in good agreement with our band structure calculations (Fig. 1b, c). By using the semiclassical two-band model35, we extract the carrier densities of holes $\\left(n_{\\mathrm{h}}\\sim9.3\\times10^{19}\\mathrm{cm}^{-3}\\right)$ and electrons $(n_{\\mathrm{e}}\\sim7.5\\times10^{19}{\\mathrm{cm}}^{-3})$ of our $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ samples. These relatively low carrier densities and a near compensation of charge carriers further confirm the semi-metallicity of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . \n\n![](images/6c72358ddfa3e618a72bd1bdc52c55062fd925b17a001e0a0a5edaea40c17079.jpg) \nFig. 2 | Theoretical calculations of the Berry curvature and anomalous Hall conductivity. a, Linear band crossings form a nodal ring in the mirror plane. b, Nodal rings and the distribution of the Weyl points in the Brillouin zone. c, Spin–orbit coupling breaks the nodal ring band structure into opened gaps and Weyl nodes. The Weyl nodes are located just $60\\mathsf{m e V}$ above the Fermi level, whereas the gapped nodal lines are distributed around the Fermi level. d, Berry curvature distribution projected to the $k_{x}-k_{y}$ plane. e, Berry curvature distribution in the $k_{y}=0$ plane. The colour bars for d and e are in arbitrary units. f, Energy dependence of the anomalous Hall conductivity in terms of the components of $\\varOmega_{y x}^{z}(\\mathbf{k})$ . \n\nIn order to further analyse the topological character of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ suggested by Fig. 1b, we now consider the linear band crossings in more detail. The space group $R{-}3m$ of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ has one mirror plane $(M_{010})$ . Without spin–orbit coupling, the interaction between spin-up and spin-down states is ignored and the mirror plane is a high-symmetry plane of the Hamiltonian. Thus, as they are protected by this mirror symmetry, the linear band crossing identified in Fig. 1b forms a nodal ring in the mirror plane based on the band inversion, as shown in Fig. 2a. Moreover, the linear crossings between the L–Γ​and L–U paths are just single points on the ring. When the $C_{3z}$ -rotation and inversion symmetries of the material are considered, one finds a total of six nodal rings in the Brillouin zone, as shown schematically in Fig. 2b. \n\nOn taking spin–orbit coupling into account, the spin $s_{z}$ is no longer a good quantum number and the mirror symmetry of the Hamiltonian is broken, which causes the linear crossings of the nodal lines to split, as presented in Fig. 2c. Interestingly, one pair of linear crossing points remains in the form of Weyl nodes along the former nodal line. These two Weyl nodes act as a monopole sink and source of Berry curvature (see Supplementary Information) and possess opposite topological charges of $+1$ and $^{-1}$ , respectively. In total, there are three such pairs of Weyl nodes in the first Brillouin zone due to the inversion and $C_{3z}$ -rotation symmetries of the crystal, and their distribution is presented in Fig. 2b. It is important to emphasize that the Weyl nodes in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ are only $60\\mathrm{meV}$ above the charge neutrality point, which is much closer to the Fermi energy than for previously proposed magnetic Weyl semimetals. These Weyl nodes and non-trivial Weyl nodal rings together make this material exhibit a simple topological band structure around the Fermi level. It is thus easy to further observe the surface Fermi arcs36. As a result, the Weyl-node-dominated physics in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ should be prominent and easy to detect in experiments. \n\nWe now address the AHE response of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ that can be expected from the particular band structure properties outlined above. In order to obtain a complete topological character, we integrated the Berry curvature $\\varOmega_{y x}^{z}(\\mathbf{k})$ along $k_{z}$ in the Brillouin zone. Our results reveal two main types of hot spot for the integrated Berry curvature: one located around the Weyl nodes, and the other located near the edge of the nodal lines (see Fig. 2d). To investigate the origin of the hot spot of the Berry curvature distribution, we choose the $k_{y}=0$ plane, which includes two nodal rings and two pairs of Weyl nodes, as shown in Fig. 2e. We note that hot spots of the integrated Berry curvature are primarily determined by the shape of the nodal lines, and both types of hot spot observed here originate from the nodal-line-like band anti-crossing behaviour. Along the nodal ring, the component of the Berry curvature parallel to $k_{z}$ leads to the larger hot spot we observe, whereas a different part around the Weyl node contributes to the smaller hot spot. Owing to the band anti-crossing behaviour and the position of the six Weyl nodal rings around the Fermi level, the calculated Berry curvature is clean and large, which should yield fascinating spin–electronic transport behaviours, including a large intrinsic $\\mathrm{AHE}^{3}$ . \n\nThe energy-dependent anomalous Hall conductivity $(\\sigma_{y x})$ calculated from the Berry curvature is shown in Fig. 2f. As one can see from the figure, a large peak in $\\sigma_{y x}$ appears around $E_{\\mathrm{{P}}}$ with a maximum of $1,100\\Omega^{-1}\\mathrm{cm}^{-1}$ . Since $\\sigma_{y x}$ depends on the location of the Fermi level (see equation (3), Methods), it usually changes sharply as a function of energy. However, the peak in $\\sigma_{y x}$ in Fig. 2f stays above $1,000\\Omega^{-1}\\mathrm{cm}^{-1}$ within an energy window of $100\\mathrm{meV}$ below $E_{\\mathrm{{F}}}$ Therefore, we expect to observe a high $\\sigma_{y x}$ in experiments for charge neutral or slightly $\\boldsymbol{p}$ -doped $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ samples. We also consider the non-collinear magnetic structure of the kagome lattice in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . During spin tilting away from the $\\mathbf{\\Psi}_{c}$ axis, the calculated $\\sigma_{y x}$ always stays above $1,000\\Omega^{-1}\\mathrm{cm}^{-1}$ . The existence of Weyl nodes and the large anomalous Hall conductivity are robust against the change of the magnetic structure of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ (see Supplementary Information). \n\n![](images/32a64e08c821858b47b3eece5bbb1539da990b4dbde1ed43df52775b13f6f5c8.jpg) \nFig. 3 | Chiral-anomaly-induced negative magnetoresistance. a, Schematic of the chiral anomaly. When the electron current I and magnetic field B are not perpendicular, charge carriers pump from one Weyl point to the other with opposite chirality, which leads to an additional contribution to the conductivity and a negative magnetoresistance. b, Angle dependence of magnetoresistance at $2\\mathsf{K}.$ For $B\\bot{}I//\\thinspace x//[2\\bar{}]\\bar{}0]$ $\\mathrm{(\\theta=90^{\\circ})}$ , the magnetoresistance curve shows a positive, non-saturated behaviour up to $\\mathbb{147.}$ The magnetoresistance decreases rapidly with decreasing angle. A negative magnetoresistance appears when $B//I//x//[2\\bar{1}\\bar{1}0]$ $\\scriptstyle(\\theta=0^{\\circ})$ . A schematic diagram of the sample geometry is shown for the configuration. c, Magnetoconductance at $2{\\sf K}$ in both cases of $B\\perp I$ and $B//I.$ . The magnetoconductance is an equivalent description for the magnetoresistance. Positive magnetoconductance is observed in $\\mathsf{C o}_{3}\\mathsf{S}\\mathsf{n}_{2}\\mathsf{S}_{2}$ when $B//I$ . The fitting of the positive magnetoconductance in the inset shows an approximately $B^{1.9}$ dependence, which is very close to the parabolic $(\\sim B^{2})$ field dependence for Weyl fermions. \n\nA Weyl semimetal is expected to exhibit the so-called chiral anomaly37 in transport, when the conservation of chiral charges is violated in the case of a parallel magnetic and electric field, as shown in Fig. 3a. We measured the impact of the magnetic field orientation on the transverse resistivity at $2\\mathrm{K}$ (Fig. 3b). For $B\\perp I\\left(\\theta=90^{\\circ}\\right)$ , a positive unsaturated magnetoresistance (also see Fig. 1e) is observed. The magnetoresistance decreases rapidly with decreasing $\\theta.$ . A clear negative magnetoresistance appears when $B//\\ I\\left(\\theta{=}0^{\\circ}\\right)$ , which again does not saturate up to $14\\mathrm{T}$ . As an equivalent description of the magnetoresistance, the magnetoconductance is shown in Fig. 3c. In the parallel case $\\left(B//I\\right)$ , the positive magnetoconductance can be described well by a near-parabolic field dependence38, approximately as $B^{1.9}$ , up to $14\\mathrm{T}$ (inset of Fig. 3c). In this case, the charge carriers are pumped from one Weyl point to the other with opposite chirality, which leads to an additional contribution to the conductance, resulting in a negative magnetoresistance37,38. The chiral anomaly evident from Fig. 3 represents an important signature of the Weyl fermions in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . \n\nOur transport measurements further verify the strong AHE induced by the Weyl band topology. An out−​of−​plane configuration of $\\dot{I}//\\mathrm{~\\rightmoon~}//[2\\bar{1}\\bar{1}0]$ and B // z // [0001] was applied in these measurements (see Fig. 1d and Methods). As we observe in Fig. 4a, the anomalous Hall conductivity $(\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}})$ (see Methods) shows a high value of $1,130\\Omega^{-1}\\mathrm{cm}^{-1}$ at $2\\mathrm{K}$ , which is in very good agreement with our predicted theoretical value ( $(\\sigma_{y x},$ Fig. 2f). We also studied the in−​plane case $\\textbf{\\em{(I)}}//\\textbf{\\em x}//$ [21̄ ̄0] and B // y // [0110]), for which the AHE disappears (not shown), due to strong magnetic and Berrycurvature anisotropies. Moreover, at temperatures below $100\\mathrm{K},$ for the out−​of−​plane case, $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}\\sim1,000\\Omega^{-1}\\mathrm{cm}^{-1}$ and is revealed to be independent of temperature (see also the inset of Fig. 4a, and note the logarithmic vertical axis). This robust behaviour against temperature indicates that the AHE is not governed by scattering events in the system. In addition, $\\sigma_{\\mathrm{H}}$ shows rectangular hysteresis loops with very sharp switching (Fig. 4b), and the coercive field is seen to increase with decreasing temperature, resulting in a value of $0.33\\mathrm{T}$ at $2\\mathrm{K}$ (also see Supplementary Information). As is evident from the figure, a large remanent Hall effect at zero field is observed in this material. \n\nWe plot $\\rho_{\\mathrm{H}}^{\\mathrm{~A~}}$ as a function of temperature in Fig. 4c. A large peak in $\\rho_{\\mathrm{H}}^{\\mathrm{~A~}}$ with a maximum of $44\\upmu\\Omega\\mathrm{cm}$ appears at $150\\mathrm{K}$ . When $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ is plotted against $\\sigma,$ as presented in Fig. 4d, we also find that $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ is nearly independent of $\\sigma$ (that is, $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}\\sim\\mathit{\\bar{(\\sigma)}}^{0}=$ constant) for temperatures below $100\\mathrm{K},$ as expected for an intrinsic AHE in the framework of the unified model for AHE physics39,40 (see Supplementary Information for more details). This independence of $\\rho_{\\mathrm{H}}^{\\mathrm{~A~}}$ with respect to both $T$ and $\\rho$ indicates that the AHE originates only from the intrinsic scattering-independent mechanism, and is thus dominated by the Berry curvature in momentum space1. This scaling behaviour is consistent with our first-principles calculations and provides another important signature for the magnetic Weyl fermions in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . \n\nIn addition to a large $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ , and arguably more importantly, the magnetic Weyl semimetal $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ also features a giant anomalous Hall angle that can be characterized by the ratio of $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma$ The temperature dependence of $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma$ is shown in Fig. 5a. With increasing temperature, $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma$ first increases from $5.6\\%$ at $2\\mathrm{K},$ reaching a maximum of approximately $20\\%$ around $120\\mathrm{K}$ , before decreasing again as the temperature increases above $T_{\\mathrm{{C}}}$ . The contour plot of $\\sigma_{\\mathrm{H}}/\\sigma$ with respect to $B$ and $T$ is depicted in Fig. 5b, and makes it intuitively clear that a giant Hall angle appears between 75 and $175\\mathrm{K}$ irrespective of the magnetic fields magnitude. This can be straightforwardly understood by considering that $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ arises from the Berry curvature of the occupied states. The band topology of these states is basically unaffected by the small energy scale of thermal excitations up to room temperature41. In other words, the topologically protected $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ is relatively robust against temperature. In contrast, the Weylnode-related charge conductivity $(\\sigma)$ is sensitive to temperature, due to electron–phonon scattering42. These behaviours are also shown in Fig. 5a. Therefore, $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma$ is expected to increase with increasing temperature in a wide temperature range below $T_{\\mathrm{{C}}}$ . The semimetallicity (low carrier density and low charge conductivity) largely improves the value of $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma$ in this system. \n\n![](images/2e7b70b82ad758d2931157fa442754b8609bdb174c370e6b21e35e148c86ac5e.jpg) \nFig. 4 | Transport measurements of the AHE. a, Temperature dependence of the anomalous Hall conductivity $(\\sigma_{\\mathsf{H}}^{\\mathsf{A}})$ at zero magnetic field. The inset shows the logarithmic temperature dependence of $\\sigma_{\\mathsf{H}}^{\\mathsf{A}}$ . b, Field dependence of the Hall conductivity $\\sigma_{\\mathsf{H}}$ at 100, 50 and $21$ with $I//x//[2\\bar{1}\\bar{1}0]$ and B $//z//$ [0001]. Hysteretic behaviour and sharp switching appears at temperatures below $1001.$ c, Temperature dependence of the anomalous Hall resistivity $(\\rho_{\\mathsf{H}}^{\\mathsf{A}})$ . A peak appears around $150\\mathsf{K}.$ Since ${\\rho}_{\\mathsf{H}}^{\\mathsf{A}}$ was derived by extrapolating the high-field part of $\\rho_{\\mathsf{H}}$ to zero field, non-zero values can be observed just above $T_{\\scriptscriptstyle\\mathrm{C}}$ due to the short-range magnetic exchange interactions enhanced by high fields. d, $\\sigma$ dependence of $\\sigma_{\\mathsf{H}}^{\\mathsf{A}}$ . The $\\sigma$ -independent $\\sigma_{\\mathsf{H}}^{\\mathsf{A}}$ (that is, $\\sigma_{\\mathsf{H}}^{\\mathsf{A}}\\tilde{\\mathbf{\\nabla}}\\tilde{}\\tilde{}(\\sigma)^{0}=0$ onstant), below $100\\mathsf{K},$ puts this system into the intrinsic regime according to the unified model of AHE physics (for more details see Supplementary Information)39,40. \n\nWhen compared to previously reported results for other AHE materials (see Fig. 5c), the value of the anomalous Hall angle in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ observed in this work is seen to be the largest by a prominent margin. For most of these materials—formed mainly of ferromagnetic transition metals and alloys—the anomalous Hall conductivities originate from topologically trivial electronic bands. A typical feature of these materials is that both $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ and $\\sigma$ are either large or small, and therefore $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma$ for these materials typically cannot be large. Although the magnetic-field-induced Weyl semimetal GdPtBi has a large $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma$ of $16\\%$ , its $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ is very small and, moreover, it requires an external field to induce the Weyl phase23. In contrast, owing to the non-trivial Berry curvature and the Weyl semi-metallic character, the kagome-lattice $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ possesses both a large $\\sigma_{\\mathrm{H}}^{\\mathrm{~A~}}$ and giant $\\sigma_{\\mathrm{H}}^{\\mathrm{\\tiny~A}}/\\sigma;$ simultaneously and at zero magnetic field, which makes this system unusual among the known AHE materials. \n\nAs a consequence, a large anomalous Hall current can be expected in thin films of this material, which may even reach the limit of a quantized AHE with dissipationless quantum Hall edge states13,24,43,44. In more general terms, a clean topological band structure induces both a large anomalous Hall conductivity and giant anomalous Hall angle (as demonstrated here for the Weyl semimetal $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2},$ , and so can be seen as a guide for the realization of strong AHE in (halfmetallic) magnetic topological Weyl semimetals. \n\nIn summary, $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ is a Weyl semimetal candidate derived from a ferromagnetic kagome lattice. It is the first material that hosts both a large anomalous Hall conductivity and a giant anomalous Hall angle that originate from the Berry curvature. This compound is an ideal candidate for developing a quantum anomalous Hall state due to its long-range quasi-2D out-of-plane ferromagnetic order and simple electronic structure near the Fermi energy. Moreover, it is straightforward to grow large, high-quality, single crystals, which makes $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ and the Shandite family an excellent platform for comprehensive studies on topological electron behaviour. Our work motivates the study of the strong anomalous Hall effect based on magnetic Weyl semimetals, and establishes the ferromagnetic kagome-lattice Weyl semimetals as a key class of materials for fundamental research and applications connecting topological physics45–48 and spintronics49,50. \n\n# Methods \n\nMethods, including statements of data availability and any associated accession codes and references, are available at https://doi. org/10.1038/s41567-018-0234-5. \n\nReceived: 22 November 2017; Accepted: 28 June 2018; Published online: 30 July 2018 \n\n![](images/3202ffa4d921fb40f27730ba121c2cba0c295bac26cbe93ef90dcbbda0b679c0.jpg) \nFig. 5 | Transport measurements of the anomalous Hall angle. a, Temperature dependences of the anomalous Hall conductivity $(\\sigma_{\\mathsf{H}}^{\\mathsf{A}})$ , the charge conductivity $(\\sigma)$ and the anomalous Hall angle $({\\sigma_{\\mathsf{H}}}^{\\mathsf{A}}/\\sigma)$ at zero magnetic field. Since the ordinary Hall effect vanishes at zero field, the anomalous Hall contribution prevails (see Supplementary Information). b, Contour plots of the Hall angle in the B–T space. c, Comparison of our $\\sigma_{\\mathsf{H}}^{\\mathsf{A}}$ -dependent anomalous Hall angle results and previously reported data for other AHE materials. ‘(f)’ denotes thin-film materials. The dashed line is a guide to the eye. The reported data were taken from references that can be found in the Supplementary Information. \n\n# References \n\n1.\t Nagaosa, N., Sinova, J., Onoda, S., MacDonald, A. H. & Ong, N. P. Anomalous Hall effect. Rev. Mod. Phys. 82, 1539–1592 (2010). \n2.\t Fang, Z. et al. The anomalous Hall effect and magnetic monopoles in momentum space. Science 302, 92–95 (2003). \n3.\t Haldane, F. D. M. Berry curvature on the Fermi surface: Anomalous Hall effect as a topological Fermi-liquid property. Phys. Rev. Lett. 93, 206602 (2004). \n4.\t Xiao, D., Chang, M. C. & Niu, Q. Berry phase effects on electronic properties. Rev. Mod. Phys. 82, 1959–2007 (2010). \n5.\t Nakatsuji, S., Kiyohara, N. & Higo, T. Large anomalous Hall effect in a non-collinear antiferromagnet at room temperature. Nature 527, \n212–215 (2015). \n6.\t Weng, H. M., Fang, C., Fang, Z., Bernevig, B. A. & Dai, X. Weyl semimetal phase in noncentrosymmetric transition-metal monophosphides. Phys. Rev. X \n5, 011029 (2015). \n7.\t Yan, B. & Felser, C. Topological materials: Weyl semimetals. Annu. Rev. Condens. Matter Phys. 8, 337–354 (2017). \n8.\t Weng, H. M., Yu, R., Hu, X., Dai, X. & Fang, Z. Quantum anomalous Hall effect and related topological electronic states. Adv. Phys. 64, 227–282 (2015). \n9.\t Liu, C.-X., Zhang, S.-C. & Qi, X.-L. The quantum anomalous Hall effect: Theory and experiment. Annu. Rev. Condens. Matter Phys. 7, 301–321 (2016). \n10.\tYu, R. et al. Quantized anomalous Hall effect in magnetic topological insulators. Science 329, 61–64 (2010). \n11.\tChang, C.-Z. et al. Experimental observation of the quantum anomalous Hall effect in a magnetic topological insulator. Science 340, 167–170 (2013). \n12.\tFang, C., Gilbert, M. J. & Bernevig, B. A. Large-Chern-number quantum anomalous Hall effect in thin-film topological crystalline insulators. Phys. Rev. Lett. 112, 046801 (2014). \n13.\tKou, X. et al. Scale-invariant quantum anomalous Hall effect in magnetic topological insulators beyond the two-dimensional limit. Phys. Rev. Lett. 113, \n137201 (2014). \n14.\tBurkov, A. A. & Balents, L. Weyl semimetal in a topological insulator multilayer. Phys. Rev. Lett. 107, 127205 (2011). \n15.\tZyuzin, A. A., Wu, S. & Burkov, A. A. Weyl semimetal with broken time reversal and inversion symmetries. Phys. Rev. B 85, 165110 (2012). \n16.\tWang, X., Vanderbilt, D., Yates, J. R. & Souza, I. Fermi-surface calculation of the anomalous Hall conductivity. Phys. Rev. B 76, 195109 (2007). \n17.\tBurkov, A. A. Anomalous Hall effect in Weyl metals. Phys. Rev. Lett. 113, \n187202 (2014). \n18.\tWan, X. G., Turner, A. M., Vishwanath, A. & Savrasov, S. Y. Topological semimetal and Fermi-arc surface states in the electronic structure of pyrochlore iridates. Phys. Rev. B 83, 205101 (2011). \n19.\tXu, G., Weng, H. M., Wang, Z. J., Dai, X. & Fang, Z. Chern semimetal and the quantized anomalous Hall effect in $\\mathrm{Hg}\\mathrm{Cr}_{2}\\mathrm{Se}_{4}.$ Phys. Rev. Lett. 107, 186806 (2011). \n20.\tKübler, J. & Felser, C. Weyl points in the ferromagnetic Heusler compound $\\mathrm{Co}_{2}\\mathrm{MnAl}.$ Europhys. Lett. 114, 47005 (2016). \n21.\tWang, Z. J. et al. Time-reversal-breaking Weyl fermions in magnetic Heusler alloys. Phys. Rev. Lett. 117, 236401 (2016). \n22.\tChang, G. Q. et al. Room-temperature magnetic topological Weyl fermion and nodal line semimetal states in half-metallic Heusler $\\mathrm{Co}_{2}\\mathrm{TiX}$ $\\mathrm{{(X=Si}}$ , Ge, or Sn). Sci. Rep. 6, 38839 (2016). \n23.\tSuzuki, T. et al. Large anomalous Hall effect in a half-Heusler antiferromagnet. Nat. Phys. 12, 1119–1123 (2016). \n24.\tOhgushi, K., Murakami, S. & Nagaosa, N. Spin anisotropy and quantum Hall effect in the kagome lattice: Chiral spin state based on a ferromagnet. Phys. Rev. B 62, R6065–R6068 (2000). \n25.\tXu, G., Lian, B. & Zhang, S.-C. Intrinsic quantum anomalous Hall effect in the Kagome lattice $\\mathrm{Cs}_{2}\\mathrm{LiMn}_{3}\\mathrm{F}_{12}$ . Phys. Rev. Lett. 115, 186802 (2015). \n26.\tYe, L. et al. Massive Dirac fermions in a ferromagnetic kagome metal. Nature 555, 638–642 (2018). \n27.\tWeihrich, R., Anusca, I. & Zabel, M. Half-antiperovskites: Structure and type-antitype relations of Shandites $\\mathrm{M}_{3/2}\\mathrm{AS}$ $\\mathrm{\\bf~M}=\\mathrm{\\bfCo},$ Ni; $\\mathrm{A}=\\mathrm{In}$ , Sn). Z. Anorg. Allg. Chem. 631, 1463–1470 (2005). \n28.\tWeihrich, R. & Anusca, I. Half antiperovskites. III - Crystallographic and electronic structure effects in $\\mathrm{Sn}_{2-x}\\mathrm{In}_{x}\\mathrm{Co}_{3}\\mathrm{S}_{2}$ Z. Anorg. Allg. Chem. 632, 1531–1537 (2006). \n29.\tVaqueiro, P. & Sobany, G. G. A powder neutron diffraction study of the metallic ferromagnet $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . Solid State Sci. 11, 513–518 (2009). \n30.\tSchnelle, W. et al. Ferromagnetic ordering and half-metallic state of $\\mathrm{Sn}_{2}\\mathrm{Co}_{3}\\mathrm{S}_{2}$ with the Shandite-type structure. Phys. Rev. B 88, 144404 (2013). \n31.\tDedkov, Y. S., Holder, M., Molodtsov, S. L. & Rosner, H. Electronic structure of shandite $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . J. Phys. Conf. Ser. 100, 072011 (2008). \n32.\tHolder, M. et al. Photoemission study of electronic structure of the half-metallic ferromagnet $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . Phys. Rev. B 79, 205116 (2009). \n33.\tAli, M. N. et al. Large, non-saturating magnetoresistance in $\\mathrm{WTe}_{2}$ . Nature 514, 205–208 (2014). \n34.\tKumar, N. et al. Extremely high magnetoresistance and conductivity in the type-II Weyl semimetals $\\mathrm{WP}_{2}$ and $\\mathrm{MoP}_{2}$ . Nat. Commun. 8, 1642 (2017). \n35.\tZiman, J. M. Electrons and Phonons: Theory of Transport Phenomena in Solid (Oxford Univ. Press, Oxford, 1960). \n36.\tXu, Q. et al. Topological surface Fermi arcs in the magnetic Weyl semimetal $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ . Phys. Rev. B 97, 235416 (2018). \n37.\tNielsen, H. B. & Ninomiya, M. The Adler–Bell–Jackiw anomaly and Weyl fermions in a crystal. Phys. Lett. B 130, 389–396 (1983). \n38.\tSon, D. T. & Spivak, B. Z. Chiral anomaly and classical negative magnetoresistance of Weyl metals. Phys. Rev. B 88, 104412 (2013). \n39.\tOnoda, S., Sugimoto, N. & Nagaosa, N. Intrinsic versus extrinsic anomalous Hall effect in ferromagnets. Phys. Rev. Lett. 97, 126602 (2006). \n40.\tMiyasato, T. et al. Crossover behavior of the anomalous Hall effect and anomalous Nernst effect in itinerant ferromagnets. Phys. Rev. Lett. 99, 086602 (2007). \n41.\tYue, D. & Jin, X. Towards a better understanding of the anomalous Hall effect. J. Phys. Soc. Jpn 86, 011006 (2016). \n42.\tGantmakher, V. F. The experimental study of electron–phonon scattering in metals. Rep. Prog. Phys. 37, 317–362 (1974). \n43.\tCheckelsky, J. G. et al. Trajectory of the anomalous Hall effect towards the quantized state in a ferromagnetic topological insulator. Nat. Phys. 10, 731–736 (2014). \n44.\tSamarth, N. Quantum materials discovery from a synthesis perspective. Nat. Mater. 16, 1068–1076 (2017). \n45.\t Chan, C.-K., Lee, P. A., Burch, K. S., Han, J. H. & Ran, Y. When chiral photons meet chiral fermions: Photoinduced anomalous Hall effects in Weyl semimetals. Phys. Rev. Lett. 116, 026805 (2016). \n46.\tIkhlas, M. et al. Large anomalous Nernst effect at room temperature in a chiral antiferromagnet. Nat. Phys. 13, 1085–1090 (2017). \n47.\tRajamathi, C. R. et al. Weyl semimetals as hydrogen evolution catalysts. Adv. Mater. 29, 1606202 (2017). \n48.\tYang, B.-J., Moon, E.-G., Isobe, H., & Nagaosa, N. Quantum criticality of topological phase transitions in three-dimensional interacting electronic systems. Nat. Phys. 10, 774–778 (2014). \n49.\tKurebayashi, D. & Nomura, K. Voltage-driven magnetization switching and spin pumping in Weyl semimetals. Phys. Rev. Appl. 6, 044013 (2016). \n50.\tTokura, Y., Kawasaki, M. & Nagaosa, N. Emergent functions of quantum materials. Nat. Phys. 13, 1056–1068 (2017). \n\n# Acknowledgements \n\nThis work was financially supported by the European Research Council (ERC) Advanced Grant (No. 291472) ‘IDEA Heusler!’ and ERC Advanced Grant (No. 742068) ‘TOPMAT’. E.L. acknowledges support from the Alexander von Humboldt Foundation of Germany for his Fellowship and from the National Natural Science Foundation of China for his Excellent Young Scholarship (No. 51722106). \n\n# Author contributions \n\nThe project was conceived by E.L. and C.F. Single crystals were grown by E.L., who performed the structural, magnetic and transport measurements with assistance from A.S., J.K., S.Y., V.S., H.B., N.K. and W.S. The STM characterizations were performed by L.J. and S.W. The ARPES measurements were conducted by D.L., A.L. and Y.C. The static high-magnetic-field measurements were performed and analysed by Z.W., C.X., N.K., C.S. and L.J. The theoretical calculations were carried out by Y.S., L.M., Q.X. and E.L. All the authors discussed the results. The paper was written by E.L., Y.S. and S.T.B.G. with feedback from all the authors. The project was supervised by C.F. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41567-018-0234-5. \nReprints and permissions information is available at www.nature.com/reprints. Correspondence and requests for materials should be addressed to E.L. or Y.S. or C.F. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\nSingle-crystal growth. The single crystals of $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ were grown by self-flux methods with Sn as flux or with the congruent composition in a graphite crucible sealed in a quartz tube (see Supplementary Information). The stoichiometric samples $\\mathrm{\\langleCo{:}S n{:}S{=}3{:}2{:}2}$ ) were heated to $1,000^{\\circ}\\mathrm{C}$ over 48 hours and kept there for 24 hours before being slowly cooled to $600^{\\circ}\\mathrm{C}$ over seven days. The samples were kept at $600^{\\circ}\\mathrm{C}$ for 24 hours to obtain homogeneous and ordered crystals. The compositions of crystals were checked by energy-dispersive X-ray spectroscopy. The crystals were characterized by powder X-ray diffraction as single phase with a Shandite-type structure. The lattice parameters at room temperature are $a=5.3689\\AA$ and $c{=}13.176\\mathrm{\\AA}$ . The single crystals and orientations were confirmed by a single-crystal X-ray diffraction technique. \n\nScanning tunnelling microscopy (STM). Topographic images of the crystal surface were characterized by cryogenic STM, taken at conditions of $T{=}2.5\\mathrm{K},$ a bias voltage of $V_{\\mathrm{b}}{=}100\\mathrm{mV}$ and a tunnel current of $I_{\\mathrm{t}}{=}500\\mathrm{pA}$ . The sample was cleaved in situ $(p\\leq2\\times10^{-9}\\mathrm{Pa})$ at $20\\mathrm{K}$ . The high quality of the single crystals was confirmed by STM (see Supplementary Information). \n\nMagnetization measurements. Magnetization measurements were carried out on oriented crystals with the magnetic field applied along both the $a$ and $c$ axes using a vibrating sample magnetometer (MPMS 3, Quantum Design). The results show an extremely strong magnetic anisotropy in $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ (see Supplementary Information). \n\nOut-of-plane transport measurements. The out-of-plane transport measurements on longitudinal charge and Hall resistivities, with $B//z//[0001]$ and I // x //[21̄ ̄0], were performed on a PPMS 9 (Quantum Design) using the low-frequency alternating current (ACT) option. The standard four-probe method was used to measure the longitudinal electrical resistivity, whereas for the Hall resistivity measurements, the five-probe method was used with a balance protection meter to eliminate possible magnetoresistance signals. The charge and Hall resistivities were measured in turn at each temperature. \n\nAngle-dependent longitudinal electric resistivity. The angle dependence of longitudinal electric resistivity was measured on a PPMS DynaCool (Quantum Design) using the ‘DC Resistivity’ option. For the angle-dependent measurements, B // θ and $I//x//[2\\bar{1}\\bar{1}0]$ , while $\\theta$ is the angle with respect to $x$ //[21̄ ̄0]. The currents were always applied along the $a$ axis, for example, I // x // [21̄ ̄0] ( $a\\mathrm{axis}=x$ axis). Different crystals, grown by two self-flux methods and with different RRR $(\\rho_{300\\mathrm{K}}/\\rho_{2\\mathrm{K}})$ values, were used in this study. \n\nAnalysis of Hall effect and semi-metallicity. At high temperatures $(50\\mathrm{K}
Table 1 Structure properties and surface chemistry of the NCNFs
R Iq/DSBET (m² g-1) Vt (cm3 g-1)aElement content (at%)% of total N 1sC (mAh g-1)b
CNN-6N-5N-Q
NCNF-6502.50.94 990.4280.613.85.633.322.744.0 368
NCNF-95003.30.98 1070.7287.8 4.194.123.8 297
76.2
a The total pore volume was determined at a relative pressure of 0.98 b Thevalues are the first chargecapacity at current density of 25 mA g-1
\n\nThe surface area and porous texture of NCNFs were analyzed using $\\mathrm{N}_{2}$ -adsorption. Figure 2f shows the nitrogen adsorption–desorption isotherms, and the inset highlights the corresponding pore size distribution. All NCNFs exhibit type IV isotherms with type H3 hysteresis loops, showing a meso/ macroporous structure. The Brunauer–Emmett–Teller (BET) surface areas were calculated to be 96, 107, and $110\\mathrm{m}^{2}\\ \\mathrm{g}^{-1}$ for NCNF-650, NCNF-950, and NCNF-1100, respectively. This indicates that carbonization temperature has minimal effect on the resultant surface area in the employed range. Pores that are smaller than $4\\mathrm{nm}$ are generated from mass loss during carbonization, and those larger than $20\\mathrm{nm}$ are ascribed to the hollow interior of the fibers. The mesopores could offer fast ion adsorption and short diffusion distance, contributing to fast charging/discharging properties of the NCNFs. \n\nElectrochemical performance as PIB anodes in half cells. The K-storage behavior of NCNFs was first tested using cyclic voltammetry (CV) in a voltage window of $0.01{-}3.0\\mathrm{V}$ (vs. $\\dot{\\mathrm{K}}/\\mathrm{K}^{+}.$ ). As shown in Fig. 3a and Supplementary Fig. 7, during the first cathodic scan, a peak appears at ${\\sim}0.55\\mathrm{V}$ and disappears in the second scan, which is ascribed to the formation of solid electrolyte interface $\\mathbf{\\left(SEI\\right)}^{42,43}$ . A slope extending to the cutoff voltage can be attributed to the K-intercalation in Super P at lowpotential range, which was also observed in our previous work44. The first anodic scan features a broad peak over a wide voltage window and a large capacity loss is observed, signaling a low first Coulombic efficiency (CE). During the following cycles, several humps appearing at $1.60\\mathrm{V}$ (NCNF-650), $0.80\\mathrm{V}$ (NCNF-950), and $0.70\\mathrm{V}$ (NCNF-1100) are attributed to the interaction of K ions with N species and may reflect various binding energy23,45– 47. Increasing carbonization temperature leads to a progressive reduction in the total area of the scan curves, as shown by the loss of the peak at higher voltage range in NCNF-950 and NCNF1100 (Supplementary Fig. 7). Since higher temperature eliminates the content of N species, the importance of N-doping in determining the total reversible capacity is evidenced. \n\n![](images/5c092bc8cab856de2373c799ff9d90b91af4708cb1faeb2e294c95f3c0a44e00.jpg) \nFig. 3 Electrochemical performance of NCNFs as PIB anodes in half cells. a CV curves of NCNF-650. b First charge and second discharge profiles of NCNFs. c Cycling performance of NCNFs at a current density of $25\\mathsf{m A g}^{-1}$ . d Rate performance of NCNFs with rates ranging from 0.05 to $20\\mathsf{A g}^{-1}$ . Long-term cycling performance of NCNF-650 at high rates of 0.5 (e), ${\\sf1}\\left({\\bf f}\\right),$ and $2\\mathsf{A g}^{-1}(\\pmb{\\mathsf{g}})$ \n\nSupplementary Fig. 8 shows the galvanostatic charge/discharge profiles of the NCNF electrodes at $25\\mathrm{\\mA\\g^{-1}}$ . A quasi-plateau located between 0.65 and $0.85\\mathrm{V}$ and a long tail extending to 0.01 V can be observed in the first discharge, being in accordance with the CV results. Since Super P maintained a low reversible capacity (Supplementary Fig. 9), its contribution to the overall capacity is expected to be very small, considering its low content $(10\\mathrm{wt\\%})$ in the electrodes. The first discharge and charge capacities are 744 and $368\\mathrm{mAhg^{-1}}$ for NCNF-650, 775, and $2{\\stackrel{\\cdot}{9}}7\\operatorname{mAh}\\mathbf{g}^{-1}$ for \n\nNCNF-950, and 790 and $281\\mathrm{mAhg^{-1}}$ for NCNF-1100, giving low first cycle CEs of $49\\%$ , $38\\%$ , and $36\\%$ , respectively. Similar trend was observed in the reported carbons in LIBs and SIBs31,48,49. Although NCNF-650 has the highest K-adsorption energy and the resultant carbon defects (will be shown later), it shows the least K-intercalating capacity below $0.25\\mathrm{~V}^{16-18}$ , owing to the largest average graphene interlayer spacing (Fig. 2a), which indicates the fewest irreversible K-intercalation50. Additionally, it has been reported that doping of nitrogen can, to some extent, suppress the electrolyte decomposition and SEI formation51,52, which also contributes to a higher first cycle CE of NCNF-650. The CE reaches $90\\%$ at cycle 6 for all the NCNF electrodes. It is worth noting that NCNF-650 exhibited a much higher first charge capacity (368 $\\mathrm{mAh~g^{-1}}.$ ) than NCNF-950 and NCNF-1100 (297 and $281\\mathrm{mAh}$ $\\mathbf{g}^{-1}$ , respectively, Fig. 3b), and the capacity is well beyond the theoretical capacity $(279\\mathrm{mAh}\\mathrm{g}^{-1}. $ ) of stage 1 $\\mathrm{KC}_{8}$ . From the second cycle, the charge/discharge profiles of all NCNFs exhibit a characteristic sloping feature, which is similar to those previously reported in soft carbons16,46,53,54. NCNF-650 delivered a reversible capacity of $248\\mathrm{mAhg^{-1}}$ after 100 cycles (Fig. 3c), being among the highest values of carbon materials in $\\mathrm{PIBs}^{\\forall6,18,21,28,29,55}$ . NCNF-950 and NCNF-1100 delivered lower capacities of 221 and $216\\mathrm{mAhg^{-1}}$ , respectively. Figure 3d shows the rate capability at various current densities, where NCNF-650 exhibited the best performance. The charge/discharge profiles of NCNF-650 can be found in Supplementary Fig. 10. It delivered capacities of 238, 217, 192, 172, 153, and $1\\dot{2}6\\mathrm{mAhg^{-1}}$ at 0.1, 0.2, 0.5, 1, 2, and $5\\mathrm{Ag^{-1}}$ , respectively. Even at current densities as high as 10 and $2\\mathsf{\\bar{0}}\\mathrm{Ag}^{-1}$ , there are still 104 and $101\\mathrm{mAhg^{-1}}$ retained. Moreover, it maintained good cyclability during the next 100 cycles at $0.2\\mathrm{Ag}^{-1}$ , delivering a stable capacity of $\\mathrm{{\\dot{1}}91\\mathrm{mAh}}$ $\\mathbf{g}^{-1}$ . NCNF-950 and NCNF-1100 delivered lower capacities than NCNF-650 at various rates, and the trend follows the order of their N-doping level. The capacity discrepancy becomes more significant with increasing current density, suggesting a critical role of N-doping at high rates. Additionally, we tested the longterm cyclability of NCNF-650 at high rates (Fig. 3e–g). Prior to high rates, NCNF-650 was cycled at $50\\mathrm{mAg^{-1}}$ for 10 cycles. As expected, it exhibited impressive cycling stability by retaining capacities of 205 $(0.5\\mathrm{Ag}^{-1})$ , 164 $(1\\mathrm{Ag^{-1}})$ , and $14\\dot{6}\\operatorname{mAh}\\mathrm{g^{-1}}$ (2 A $\\begin{array}{r}{\\mathbf{g}^{-1},}\\end{array}$ ) after 1000, 2000, and 4000 cycles, respectively. TEM measurement was performed on NCNF-650 after 4000 cycles (Supplementary Fig. 11). The nanofiber structure is well maintained, except for the less discernible hollow interior due to the SEI layer. HRTEM image shows the disordered structure and turbostratic domains. Element mapping shows even distribution of N and K over the fibers, indicating the stability of the $\\mathrm{~N~}$ dopant and the effective K-storage. Therefore, the great structural stability is evident. The long-term operation of the electrode without much degradation can be attributed to the charge storage action that is mainly on or near the surface of the nanofibers at high rates. Cycling at low rates would give more charge storage contribution in bulk and certainly do more damage to the electrode, as can be seen that NCNF-650 showed lower capacity retention after 100 cycles at $25\\mathrm{\\mAg^{-1}}$ than at high rates. \n\nQuantitative analysis of surface-dominated charge storage. We next investigated the kinetics of the electrodes using CV measurement at scan rates of 0.2 to $10\\mathrm{mVs^{-1}}$ (Fig. 4a–c). In the case of NCNF-650, broad (de)potassiation peaks are maintained at high scan rates and the peak coverage toward high potential can be clearly seen, being in contrast to NCNF-950 and NCNF-1100, whose peaks become steeper and show large polarization. These observations imply better preservation of the surface-dominated characteristic enabled by higher N-doping level in NCNF-650. The peak current obeys a power law relationship with the scan rate, according to Eq. (1)56,57: \n\n![](images/b524456bd5e0b422c159a92c31f9127bebd382e4741f30824d1356929270b3f4.jpg) \nFig. 4 Quantitative analysis of surface-dominated K-storage in NCNFs. CV curves of NCNF-650 (a), NCNF-950 (b), and NCNF-1100 (c) at various scan rates of 0.2 to $10\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . d $b$ value determination. e Contribution of the surface process in the NCNFs at different scan rates. Contribution of the surface process at scan rate of ${\\mathsf{1}}{\\mathsf{m}}{\\mathsf{V}}{\\mathsf{s}}^{-1}$ in NCNF-650 (f), NCNF-950 ${\\bf\\Pi}({\\bf g})$ , and NCNF-1100 ${\\bf\\Pi}({\\bf h})$ \n\n![](images/57a51746dedbaf10718938dce83ff3efc9bff87beef4c01268e1c45c7116bfba.jpg) \nFig. 5 Electrochemical performances of the NCNF-650/KPB full cell. Galvanostatic charge/discharge profiles (a) and cycling performance (b) at a current density of $200\\mathsf{m A}\\mathsf{g}^{-1}$ . Optical photographs of a white LED (c) and a red LED (d) lightened by the full cell \n\n$$\ni=a\\nu^{b}\n$$ \n\nwhere $i$ is peak current, $\\nu$ is scan rate, $^a$ and $b$ are adjustable constants. By plotting $\\log(i)$ against $\\log(\\nu)$ , the $b$ value can be extracted from the slope. It would be 0.5 for an ideal faradiac intercalation process controlled by semi-infinite linear diffusion while close to 1 for a surface charge storage process free of diffusion control. Figure 4d shows the plot applied on the depotassiation peak current. A good linear relationship can be seen for NCNF-650 and the $b$ value was calculated to be 0.96, suggesting a fast kinetics dominated by a surface process. As expected, this value decreases to 0.91 and 0.74 for NCNF-950 and NCNF-1100, respectively. In particular, data points collected from NCNF-1100 show the worse linear relationship at high scan rates than at low scan rates, reflecting its much lower capacities than those of NCNF-650 and NCNF-950 at high rates. The surface process contribution can be further quantitatively differentiated by separating current response $i$ at a fixed potential $V$ into a surfacedependent process (proportional to $\\nu$ ) and a diffusion-controlled process (proportional to $\\nu^{I/2}$ ) by Eq. $(2)^{56,57}$ : \n\n$$\ni=k_{1}\\nu+k_{2}\\nu^{1/2}\n$$ \n\nby determining $k_{1}$ and $k_{2}{\\mathrm{:}}$ , we can separate the fraction of the two processes. Figure $4\\mathrm{f-h}$ shows the typical CV profiles at a scan rate of $1\\mathrm{mV}s^{-1}$ for the current from surface process (red region) in comparison with the total current. A surface-dominated contribution $(90\\%)$ is obtained for NCNF-650, being higher than those of NCNF-950 $(84\\%)$ and NCNF-1100 $(73\\%)$ . Using similar analysis, the fraction enlarges with increasing scan rates (Fig. 4e) for all NCNFs. NCNF-650 possesses the highest fraction at all scan rates, which complies with the order of N-doping level. This is not surprising since more $\\mathrm{\\DeltaN}$ dopant in carbon could induce more surface defects and edges of graphene layers that could enhance K-ion adsorption and result in fast kinetics. \n\nElectrochemical performance of PIB full cells. We assembled full cells using NCNF-650 as anode and potassium Prussian blue (KPB) as cathode that was synthesized using a modified method according to our previous work44. The rationale behind this is that both materials are cost-effective and materially sustainable and, as proven in LIBs, the maturity of the commercialization has always relied on carbon-based anodes. Characterizations of KPB in a half cell are provided in Supplementary Fig. 12. The full cell was assembled in an anode-limited configuration. Figure 5a shows the charge/discharge profiles of the full cell at $0.2\\mathrm{\\check{A}g}^{-1}$ tested in a voltage window of $2.0{-}4.2\\:\\mathrm{V}$ . Two semi-plateaus can be seen in the ranges of $3.4\\substack{-3.9\\mathrm{V}}$ and $2.5\\substack{-3.0\\mathrm{V}}$ in the initial cycles, which corresponds to the two plateaus displayed in the KPB half cell (Supplementary Fig. 12c). The lowered voltages and less defined flat contours are due to the sloping discharge profiles of NCNF650. The full cell delivered a first discharge capacity of $197\\mathrm{mAh}$ $\\mathbf{g}^{-1}$ (based on the anode mass) and retained $97\\%$ of the capacity $\\bar{(}190\\mathrm{mAh}\\mathrm{g}^{-1})$ after 30 cycles (Fig. 5b). As far as we know, the presented reversible capacity is the highest among all the reported PIB full cells44,58–60. The cell is able to lighten a white (working voltage $2.9\\mathrm{-}3.3\\mathrm{V}$ , Fig. 5c) and red light-emitting diode (working voltage $1.9\\mathrm{-}2.2\\:\\mathrm{V}$ , Fig. 5d) after being fully charged. We also tested full cells in a cathode-limited configuration (Supplementary Fig. 13). Similarly, the cells displayed two semi-plateaus and a capacity of $74\\mathrm{mAhg^{-1}}$ after 50 cycles $91\\%$ of the first discharge capacity) at $0.1\\mathrm{Ag}^{-1}$ . CE is lower in the anode-limited configuration than in the cathode-limited configuration. We speculate the reason to be the relatively low CE in the KPB half cell (Supplementary Fig. 12c) and the higher amount of KPB used in the anode-limited configuration given the same amount of NCNF$650^{43}$ . Nevertheless, the results here demonstrate the applicability of N-doped soft carbons in the PIB full cell application. \n\n# Discussion \n\nThe results presented above show K-storage in the highly nitrogen-doped hollow NCNFs with both high rate capability and great cyclability rendered by a surface-dominated process. To further interpret the experimental results, we performed a theoretical investigation of K-adsorption ability of the N-doped structures using first-principles calculations, based on density functional theory (DFT). The three N-doped models, i.e., N-5, N-6, and ${\\mathrm{N}}{\\mathrm{-}}{\\mathrm{Q}},$ were employed (Fig. 6a–c). The corresponding undoped and carbon defect models, i.e., C-5, C-6, and pristine C (P-C) were also employed to differentiate the doping and defect effects on the K-adsorption ability (Supplementary Fig. 14). A single K atom was placed at different sites in each model, and the optimized geometry structures were obtained at the center of the hollow “holes” by the calculation of adsorption energy $(\\Delta E_{\\mathrm{a}})$ . First, we calculated $\\Delta E_{\\mathrm{a}}$ with one doped nitrogen atom. The $\\Delta E_{\\mathrm{a}}$ of N-5 and N-6 are $-2.63$ and $-2.86\\mathrm{eV}$ , respectively, being much higher than that of N-Q $(0.14\\mathrm{eV})$ . This indicates that the pyrrolic and pyridinic N-doping has significantly higher K-adsorption ability than the graphitic N-doping. The $\\Delta E_{\\mathrm{a}}$ of N-Q is even positive, which might be attributed to the electron-richness of the graphitic doping that shows negative effect on K-adsorption25,61. Second, the $\\Delta E_{\\mathrm{a}}$ of C-5 and C-6 (–2.42 and $-2.80\\mathrm{eV}$ , respectively) are comparable to those of their N-doped counterparts. This suggests that carbon defects could contribute to K-adsorption, together with N-doping. In fact, the structures of N-5, N-6, C-5, and C-6, all contain defects that provide an electron deficiency and a tendency to gain electron from K atoms25,62. NCNF-650 has the lowest graphitization degree that could induce smaller and more curved domains and create more defects, compared with NCNF-950 and NCNF-1100. Owing to the high pyrrolic and pyridinic N-doping level and low graphitization degree, NCNF650 exhibited the highest capacity among the three electrodes. Share et al. recently reported the capacity enhancement of the Ndoped few layer graphene and correlated it to the distributed K-ion storage at local N-5 doping sites, as opposed to carbon defect sites28. However, our simulation results shown here suggest the capacity enhancement to be related to both N-doping and carbon defects. We speculate that the different nature of carbons, i.e., high graphitic-few layer graphene in their work and low graphitic soft carbon in our work, might be responsible for the different results. Third, $\\Delta E_{\\mathrm{a}}$ remains considerably high when two doped nitrogen atoms exist in differently relative positions (Fig. 6d–f and Supplementary Fig. 15), which could represent the coexistence of $\\mathrm{N}{-}5/\\mathrm{N}{-}6$ or N-6/N-6 at the same defect point. The highest $\\Delta E_{\\mathrm{a}}$ are $-2.87$ and $-3.02\\mathrm{eV}$ for the N-5/N-6 and $\\mathrm{N}{-}6/\\mathrm{N}{-}6$ combinations, respectively, whereas the $\\Delta E_{\\mathrm{a}}$ of two N-Q atoms doping $(0.26\\mathrm{eV})$ is more positive than that of single N-Q doping. Therefore, the above calculations unambiguously support the benefits of the pyrrolic and pyridinic N-doping. To understand the bonding nature of the adsorbed K atoms, we calculated electron density difference by subtracting the charge densities of K atoms and bare carbon atoms from those of the combined compounds (Fig. 6g–i and Supplementary Fig. 16). In all cases, there is a net gain of electronic charge in the intermediate region between K atoms and the carbon layers, which indicates a charge transfer from the adsorbed K to its nearestneighboring C atoms, suggesting an ionic character of the bonding63. The charge density is transferred to the bonding carbons in P-C, whereas the charge density tends to accumulate more around the N-doping sites in the doped structures. Moreover, the tendency is more significant in N-5 and N-6 than in N-Q. Therefore, the pyrrolic and pyridinic N-doping lead to stronger K-adsorption than the graphitic N-doping, supporting the experimental results. \n\n![](images/8758946d5787f9e0171f9fdaface2af067cfbb4a49f3327f03fca7bea9521bdc.jpg) \nFig. 6 Theoretical simulations of K-adsorption in different N-doped structures. Top view of a single K atom adsorbed in the N-5 (a), N-6 (b), and N-Q (c) structures and the corresponding adsorption energy. Top view of a single K atom adsorbed in the doped structures with two nitrogen atoms and the corresponding adsorption energy: d one N-5 and one N-6 atoms; e two N-6 atoms; f two N-Q atoms. Electron density differences of K absorbed in the N-5 ${\\bf\\Pi}({\\bf g}),$ N-6 ${\\bf\\Pi}({\\bf h})$ , and N-Q (i) structures. Yellow and blue areas represent increased and decreased electron density, respectively. The isosurfaces are the 0.0015 electron bohr3 . Brown, silver, and purple balls represent carbon, nitrogen, and potassium atoms, respectively \n\n![](images/59ffd54c46eed740d8311ff1826d621cb9e3d911e7c1360c412a0002f96d9dc8.jpg) \nFig. 7 Study of the K-ion diffusion coefficient of the NCNF electrodes. a GITT profiles of the discharging process. b The K-ion diffusion coefficient as a function of the state of discharging process \n\nWith the simulation results established, we further seek understanding from a kinetic point of view by using Galvanostatic intermittent titration (GITT) technique to evaluate the K-ion diffusion coefficient $(D_{\\mathrm{k}})$ during potassiation. Figure 7a shows the potential response of the electrodes during GITT measurement. The potential change during each relaxation period represents overpotential at the corresponding potassiation stage61. In general, NCNF-650 exhibited the smallest overpotentials, whereas NCNF-1100 exhibited the largest ones. The difference is more obvious in the higher voltage range than the lower range. This implies the better kinetic property of NCNF650. The calculated values of $D_{\\mathrm{k}}$ as a function of potential are shown in Fig. 7b and the calculation can be found in Supplementary Fig. 17. All the three electrodes showed a progressively decreasing $D_{\\mathbf{k}}$ with the potassiation proceeding toward $0.5\\mathrm{V}$ , which is associated with the sloping characteristic of the discharge profiles. It is obvious that NCNF-650 exhibited the highest $D_{\\mathrm{k}},$ being 1.6–2.9 and 2.1–4.6 times higher than NCNF-950 and NCNF-1100, respectively. It suggests that the K-ion diffusion is much faster in NCNF-650, owing to the easily accessible sites in the carbon structure derived from nitrogen doping, which is in accordance with the higher capacity contribution above $0.5\\mathrm{V}$ As these sites are progressively potassiated, K ions have to overcome a repulsive charge gradient from the previously bound K ions on the defect sites in order to diffuse further inside the turbostratic domains64. This is responsible for the steep drop of $D_{\\mathbf{k}}$ below $0.5\\mathrm{V}$ . \n\nIn summary, we reported a facile and scalable process to fabricate highly nitrogen-doped soft carbon nanofibers from the polypyrrole precursor. The carbon materials, termed NCNFs, exhibited excellent electrochemical performances as anodes in PIBs, demonstrating superior rate capability and cyclability among all the reported PIB anodes. Quantitative analysis and theoretical simulations were employed to interpret the benefits of nitrogen doping and demonstrate the advantage of the pyrrolic and pyridinic N dopants over the quaternary N dopant. Moreover, full cells based on the NCNFs and potassium Prussian blue delivered the highest reversible K-ion storage capacity so far, further indicating that NCNFs should be considered as a promise candidate of anode materials to realize high performance PIBs. In addition, our work offers a practical pathway to tune K-storage performance through compositional adjustment and opens up the opportunity of using disordered carbon materials in the exciting area of PIBs. \n\n# Methods \n\nPreparation of PPy precursor. The PPy nanofibers were synthesized by a modified oxidative template assembly route. In a typical synthesis, cetrimonium bromide (CTAB, $(\\mathrm{C_{16}H_{33}})–\\mathrm{N}(\\mathrm{CH_{3}})_{3}\\mathrm{Br},0.8\\mathrm{g}$ ) was dissolved in hydrochloric acid \n\nsolution (HCl, $240\\mathrm{ml}$ , $\\mathrm{1molL^{-1}}$ ) under ice bath $(0-3^{\\circ}\\mathrm{C})$ to form a transparent solution. Ammonium persulfate (APS, $(\\mathrm{NH}_{4})_{2}\\mathrm{S}_{2}\\mathrm{O}_{8},1.2\\mathrm{g})$ was then added into the above solution under magnetic stirring, and a white suspension was formed immediately. Afterward, pyrrole monomer $(1.6\\mathrm{ml})$ was dropwise added into the white suspension, and polymerization was carried out for $^{3\\mathrm{h}}$ under stirring. A black precipitate, namely $\\mathrm{PPy}$ precursor, was obtained, collected by filtration, and washed with deionized water until the filtrate became colorless. The PPy precursor was dried at $80^{\\circ}\\mathrm{C}$ in a vacuum oven for $24\\mathrm{h}$ . \n\nPreparation of NCNFs. The NCNFs were obtained by annealing the PPy precursor in $\\Nu_{2}$ atmosphere for $^{2\\mathrm{h}}$ at temperatures of 650, 950, and $1100^{\\circ}\\mathrm{C}$ . The ramp rate was $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ . \n\nPreparation of KPB. KPB was synthesized by a facile room temperatureprecipitation method in an aqueous solution. In a typical synthesis, potassium citrate tribasic monohydrate $(\\mathrm{K}_{3}\\mathrm{C}_{6}\\mathrm{H}_{5}\\mathrm{O}_{7}{\\cdot}\\mathrm{H}_{2}\\mathrm{O}$ , $5\\mathrm{{mmol}}$ ) and iron chloride $(\\mathrm{FeCl}_{2}$ , 5 mmol) were dissolved in deionized water $(50\\mathrm{ml})$ under magnetic stirring to form solution A. Potassium hexacyanoferrate (II) trihydrate $(\\mathrm{K_{4}F e}(\\mathrm{CN})_{6}{\\cdot}3\\mathrm{H_{2}O}_{3}$ $\\mathrm{5mmol}$ ) was dissolved in deionized water $(50\\mathrm{ml})$ under magnetic stirring to form solution B. Solution B was dropwise added into solution A under stirring, and precipitation occurred immediately. The mixture was stirred for $^{2\\mathrm{h}}$ and aged for another $^{10\\mathrm{h}}$ . The obtained dark blue precipitates were collected by centrifugation, washed with deionized water and ethanol, and dried at $80~^{\\circ}\\mathrm{C}$ in a vacuum oven for $24\\mathrm{h}$ . \n\nCharacterizations. XRD analysis was performed on a 18 KW D/MAX2500V PC diffractometer using Cu Kα $(\\dot{\\lambda}=1.54\\AA\\AA$ ) radiation at a scanning rate of $2^{\\circ}\\operatorname*{min}^{-1}$ . SEM analysis was conducted using a Hitachi S4800 field emission scanning microscopy. TEM and EDS analysis was performed on a JEOL JEM-2100F transmission electron microscope. X-ray photoelectron spectra were acquired on a Thermo SCIENTIFIC ESCALAB 250Xi with Al Kα $\\mathrm{\\h\\upsilon}=1486.8\\mathrm{eV}.$ as the excitation source. The binding energies obtained in the XPS spectra analysis were corrected for specimen charging by referencing C 1s to $284.8\\mathrm{eV}$ . Raman spectra were recorded at room temperature with an inVia Raman microscope. BET measurement was conducted using a Quantachrome autosorb IQ automated gas sorption analyzer. \n\nElectrochemical measurements. Electrodes were fabricated by mixing NCNFs, Super P, and carboxymethyl cellulose (CMC) sodium salt at a weight ratio of 80:10:10, then coated uniformly (doctor-blade) on a copper foil with a mass loading of $\\sim1.5\\mathrm{mgcm}^{-2}$ . The electrodes were dried at $110^{\\circ}\\mathrm{C}$ under vacuum for $12\\mathrm{h}$ . Electrochemical tests were carried out using a coin cell configuration, CR2032, which was assembled in an $\\Nu_{2}$ -filled glovebox with oxygen and moisture concentrations kept below 0.1 ppm. K foil used as counter electrode was separated from working electrode using a glass microfiber filter (Whatman, Grade GF/B). The electrolyte was $0.8\\mathrm{M}\\mathrm{KPF}_{6}$ in ethylene carbonate and propylene carbonate $(\\mathrm{EC:PC}=1:1\\$ . CV was performed on a VSP electrochemical workstation (BioLogic, France). Galvanostatic charge/discharge was performed in a voltage range of $0.01{-}3.0\\mathrm{V}$ on a Land $\\mathrm{CT}2001\\mathrm{A}$ battery testing system (Land, China) at room temperature. The entire cell was assembled using KPB as cathode and NCNFs as anode, with the same separator and electrolyte. The cathode was fabricated in the same way as anode on an aluminum foil. The cathode-to-anode mass loading ratio was 4:1 and 2:1 in the anode-limited and cathode-limited configurations, respectively. Galvanostatic charge/discharge was performed in a voltage range of 2.0–4.2 V. \n\nDFT calculations. All calculations were performed with Vienna ab initio simulation package $(\\mathrm{VASP})^{65}$ . Generalized gradient approximation (GGA) with the function of Perdew–Burke–Ernzerhof (PBE)66 was employed to describe the \n\nelectron interaction energy of exchange correlation. Grimme’s semi-empirical DFT– $.{\\mathrm{D}}3^{67}$ scheme was used in the computations to produce a better description of the interaction in a long range. In all calculations, the plane wave cutoff was set to $450\\mathrm{eV}$ . The Hellmann–Feynman forces convergence criterion on the atoms was set to be lower than $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ during geometrical optimization. Tolerance of selfconsistency was achieved at least $0.01\\mathrm{meV}$ in the total energy. The Brillouin zone was sampled by Monkhorst- $\\mathrm{\\cdotPack^{68}}$ method, with Gamma centered to $3\\times3\\times1$ for a single-layer model and $3\\times3\\times2$ for a multiple-layer model. A vacuum layer of 14 Å was built to prevent interactions between the two repeated layers. \n\nDate availability. The data that support the findings of this study are available from the corresponding authors on reasonable request. \n\nReceived: 10 October 2017 Accepted: 9 April 2018 \nPublished online: 30 April 2018 \n\n# References \n\n1. Dunn, B., Kamath, H. & Tarascon, J.-M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n2. Tarascon, J.-M. Is lithium the new gold? Nat. Chem. 2, 510 (2010). \n3. Lin, M.-C. et al. An ultrafast rechargeable aluminium-ion battery. Nature 520, 324–328 (2015). \n4. Liang, Y. et al. Heavily n–dopable π–conjugated redox polymers with ultrafast energy storage capability. J. Am. Chem. Soc. 137, 4956–4959 (2015). \n5. Yabuuchi, N., Kubota, K., Dahbi, M. & Komaba, S. Research development on sodium–ion batteries. Chem. Rev. 114, 11636–11682 (2014). \n6. Xu, Y. et al. Enhancement of sodium ion battery performance enabled by oxygen vacancies. Angew. Chem. Int. Ed. 54, 8768–8771 (2015). \n7. Liang, L. et al. Large-scale highly ordered Sb nanorod array anodes with high capacity and rate capability for sodium-ion batteries. Energy Environ. Sci. 8, 2954–2962 (2015). \n8. Xu, Y., Zhou, M. & Lei, Y. Nanoarchitectured array electrodes for rechargeable lithium-and sodium-ion batteries. Adv. Energy Mater. 6, 1502514 (2016). \n9. Zhou, M. et al. Amorphous $\\mathrm{TiO}_{2}$ inverse opal anode for high-rate sodium ion batteries. Nano Energy 31, 514–524 (2017). \n10. Xue, L. et al. Low-cost high-energy potassium cathode. J. Am. Chem. Soc. 139, 2164–2167 (2017). \n11. Zhang, W., Mao, J., Li, S., Chen, Z. & Guo, Z. Phosphorus-based alloy materials for advanced potassium-ion battery anode. J. Am. Chem. Soc. 139, 3316–3319 (2017). \n12. Eftekhari, A., Jian, Z. & Ji, X. Potassium secondary batteries. ACS Appl. Mater. Interfaces 9, 4404–4419 (2017). \n13. Jache, B. & Adelhelm, P. Use of graphite as a highly reversible electrode with superior cycle life for sodium-ion batteries by making use of co–intercalation phenomena. Angew. Chem. Int. Ed. 53, 10169–10173 (2014). \n14. Kim, H. et al. Sodium intercalation chemistry in graphite. Energy Environ. Sci. 8, 296–2969 (2015). \n15. Kim, H. et al. Sodium storage behavior in natural graphite using ether-based electrolyte systems. Adv. Funct. Mater. 25, 534–541 (2015). \n16. Jian, Z., Luo, W. & Ji, X. Carbon electrodes for K-ion batteries. J. Am. Chem. Soc. 137, 11566–11569 (2015). \n17. Luo, W. et al. Potassium ion batteries with graphitic materials. Nano Lett. 15, 7671–7677 (2015). \n18. Zhao, J., Zou, X., Zhu, Y., Xu, Y. & Wang, C. Electrochemical intercalation of potassium into graphite. Adv. Funct. Mater. 26, 8103–8110 (2016). \n19. Xing, Z., Qi, Y., Jian, Z. & Ji, X. Polynanocrystalline graphite: a new carbon anode with superior cycling performance for K-ion batteries. ACS Appl. Mater. Interfaces 9, 4343–4351 (2017). \n20. Liu, Y. et al. In situ transmission electron microscopy study of electrochemical sodiation and potassiation of carbon nanofibers. Nano Lett. 14, 3445–3452 (2014). \n21. Jian, Z. et al. Hard–soft composite carbon as a long–cycling and high-rate anode for potassium-ion batteries. Adv. Funct. Mater. 27, 1700324 (2017). \n22. Su, F. et al. Nitrogen-containing microporous carbon nanospheres with improved capacitive properties. Energy Environ. Sci. 4, 717–724 (2011). \n23. Hou, J., Cao, C., Idrees, F. & Ma, X. Hierarchical porous nitrogen-doped carbon nanosheets derived from silk for ultrahigh–capacity battery anodes and supercapacitors. ACS Nano 9, 2556–2564 (2015). \n24. Wang, X. et al. Atomistic origins of high rate capability and capacity of N-doped graphene for lithium storage. Nano Lett. 14, 1164–1171 (2014). \n25. Ma, C., Shao, X. & Cao, D. Nitrogen-doped graphene nanosheets as anode materials for lithium ion batteries: a first-principles study. J. Mater. Chem. 22, 8911–8915 (2012). \n26. Zheng, F., Yang, Y. & Chen, Q. High lithium anodic performance of highly nitrogen-doped porous carbon prepared from a metal–organic framework. Nat. Commun. 5, 5261 (2014). \n27. Wang, H. et al. Nitrogen-doped graphene nanosheets with excellent lithium storage properties. J. Mate. Chem. 21, 5430–5434 (2011). \n28. Share, K., Cohn, A. P., Carter, R., Rogers, B. & Pint, C. L. Role of nitrogendoped graphene for improved high-capacity potassium ion battery anodes. ACS Nano 10, 9738–9744 (2016). \n29. Chen, C. et al. Nitrogen-rich hard carbon as a highly durable anode for high-power potassium-ion batteries. Energy Storage Mater. 8, 161–168 (2017). \n30. Liu, Z., Zhang, X., Poyraz, S., Surwade, S. P. & Manohar, S. K. Oxidative template for conducting polymer nanoclips. J. Am. Chem. Soc. 132, 13158–13159 (2010). \n31. Ding, J. et al. Heteroatom enhanced sodium ion capacity and rate capability in a hydrogel derived carbon give record performance in a hybrid ion capacitor. Nano Energy 23, 129–137 (2016). \n32. Sevilla, M., Valle–Vigón, P. & Fuertes, A. B. N-doped polypyrrole-based porous carbons for $\\mathrm{CO}_{2}$ capture. Adv. Funct. Mater. 21, 2781–2787 (2011). \n33. Lee, S. W. et al. High-power lithium batteries from functionalized carbon–nanotube electrodes. Nat. Nanotechnol. 5, 531–537 (2010). \n34. Shin, W. H., Jeong, H. M., Kim, B. G., Kang, J. K. & Choi, J. W. Nitrogendoped multiwall carbon nanotubes for lithium storage with extremely high capacity. Nano Lett. 12, 2283–2288 (2012). \n35. Liu, Y., Xue, J., Zheng, T. & Dahn, J. Mechanism of lithium insertion in hard carbons prepared by pyrolysis of epoxy resins. Carbon 34, 193–200 (1996). \n36. Portet, C., Yushin, G. & Gogotsi, Y. Electrochemical performance of carbon onions, nanodiamonds, carbon black and multiwalled nanotubes in electrical double layer capacitors. Carbon 45, 2511–2518 (2007). \n37. Chen, L.-F. et al. Synthesis of nitrogen-doped porous carbon nanofibers as an efficient electrode material for supercapacitors. ACS Nano 6, 7092–7102 (2012). \n38. Li, Z. et al. Mesoporous nitrogen-rich carbons derived from protein for ultrahigh capacity battery anodes and supercapacitors. Energy Environ. Sci. 6, 871–878 (2013). \n39. Li, Z. et al. Colossal pseudocapacitance in a high functionality–high surface area carbon anode doubles the energy of an asymmetric supercapacitor. Energy Environ. Sci. 7, 1708–1718 (2014). \n40. Shao, Y. et al. Surface-driven sodium ion energy storage in nanocellular carbon foams. Nano Lett. 13, 3909–3914 (2013). \n41. Kim, H. et al. Novel transition-metal-free cathode for high energy and power sodium rechargeable batteries. Nano Energy 4, 97–104 (2014). \n42. Sultana, I. et al. K-ion and Na-ion storage performances of $\\mathrm{Co_{3}O_{4}–F e_{2}O_{3}}$ nanoparticle-decorated super P carbon black prepared by a ball milling process. Nanoscale 9, 3646–3654 (2017). \n43. Xu, Y. et al. Highly ordered three-dimensional $\\mathrm{Ni-TiO}_{2}$ nanoarrays as sodium ion battery anodes. Chem. Mater. 27, 4274–4280 (2015). \n44. Zhang, C. et al. Potassium Prussian blue nanoparticles: a low-cost cathode material for potassium-ion batteries. Adv. Funct. Mater. 27, 1604307 (2017). \n45. Wang, H., Mitlin, D., Ding, J., Li, Z. & Cui, K. Excellent energy-power characteristic from a hybird sodium ion capacitor based on idential carbon nanosheets in both electrodes. J. Mater. Chem. A 4, 5149–5158 (2016). \n46. Liu, X. et al. A low-cost and one-step synthesis of N-doped monolithic quasigraphene films with porous carbon frameworks for Li-ion batteries. Nano Energy 17, 43–51 (2015). \n47. Lv, W. et al. Peanut shell derived hard carbons as ultralong cycling anodes for lithium and sodium batteries. Electrochim. Acta 176, 533–541 (2015). \n48. Zhu, J. et al. Nitrogen-doped carbon nanofibers derived from polyacrylonitrile for use as anode material in sodium-ion batteries. Carbon 94, 189–195 (2015). \n49. Mao, Y. et al. Lithium storage in nitrogen-rich mesoporous carbon materials. Energy Environ. Sci. 5, 7950–7955 (2012). \n50. Lotfabad., E. M., Kalisvaart, P., Kohandehghan, A., Karpuzov, D. & Mitlin, D. Origin of non-SEI related coulombic efficiency loss in carbons tested against Na and Li. J. Mater. Chem. A 2, 19685–19695 (2014). \n51. Wu, Z., Ren, W., Xu, L., Li, F. & Cheng, H. Doped graphene sheets as anode materials with superhigh rate and large capacity for lithium ion batteries. ACS Nano 5, 5463–5471 (2011). \n52. Hu, T. et al. Rapid synthesis of nitrogen-doped graphene for a lithium ion battery anode with excellent rate performance and super-long cyclic stability. Phys. Chem. Chem. Phys. 16, 1060–1066 (2014). \n53. Wang, H. et al. Nitrogen-doped porous carbon nanosheets as low-cost, highperformance anode material for sodium-ion batteries. ChemSusChem 6, 56–60 (2013). \n54. Luo, W. et al. Electrochemically expandable soft carbon as anodes for Na-ion batteries. ACS Cent. Sci. 1, 516–522 (2015). \n55. Jian, Z., Xing, Z., Bommier, C., Li, Z. & Ji, X. Hard carbon microspheres: potassium-ion anode versus sodium-ion anode. Adv. Energy Mater. 6, 1501874 (2016). \n56. Brezesinski, T., Wang, J., Tolbert, S. H. & Dunn, B. Ordered mesoporous $_{\\mathrm{a-MoO}_{3}}$ with iso-oriented nanocrystalline walls for thin–film pseudocapacitors. Nat. Mater. 9, 146–151 (2010). \n57. Augustyn, V. et al. High-rate electrochemical energy storage through ${\\mathrm{Li}^{+}}$ intercalation pseudocapacitance. Nat. Mater. 12, 518–522 (2013). \n58. Vaalma, C., Giffin, G. A., Buchholz, D. & Passerini, S. Non-aqueous K-ion battery based on layered $\\mathrm{K}_{0.3}\\mathrm{MnO}_{2}$ and hard carbon/carbon black. J. Electrochem. Soc. 163, A1295–A1299 (2016). \n59. Wang, X. et al. Earth abundant Fe/Mn-based layered oxide interconnected nanowires for advanced K-ion full batteries. Nano Lett. 17, 544–550 (2017). \n60. Bie, X., Kubota, K., Hosaka, T., Chihara, K. & Komaba, S. A novel K-ion battery: hexacyanoferrate (II)/graphite cell. J. Mater. Chem. A 5, 4325–4330 (2017). \n61. Xu, Y., Zhu, Y., Liu, Y. & Wang, C. Electrochemical performance of porous carbon/tin composite anodes for sodium–ion and lithium-ion batteries. Adv. Energy Mater. 3, 128–133 (2013). \n62. Lee, W. J., Lim, J. & Kim, S. O. Nitrogen dopants in carbon nanomaterials: defects or a new opportunity? Small Methods 1, 1600014 (2017). \n63. Zhou, L., Hou, Z. & Wu, L. First-principles study of lithium adsorption and diffusion on graphene with point defects. J. Phys. Chem. C 116, 21780–21787 (2012). \n64. Bommier, C., Surta, T. W., Dolgos, M. & Ji, X. New mechanistic insights on Na-ion storage in nongraphitizable carbon. Nano Lett. 15, 5888–5892 (2015). \n65. Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquidmetal-amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251–14269 (1994). \n66. Perdew, J., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n67. Grimme, S., Antony, J., Ehrlich, S. & Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT–D) for the 94 elements H–Pu. J. Chem. Phys. 132, 154104 (2010). \n68. Monkhorst, H. & Pack, J. Special points for Brillouin–zone integrations. Phys. Rev. B 13, 5188–5192 (1976). \n\n# Acknowledgements \n\nThis work was financially supported by the European Research Council (ThreeDsurface, 240144, and HiNaPc, 737616), BMBF (ZIK–3DNanoDevice, 03Z1MN11), German Research Foundation (DFG: LE 2249_4–1), National Natural Science Foundation of China (21577086 and 41430644), the Shanghai Thousand Talent Plan, and Program for Changjiang Scholars and Innovative Research Team in University (IRT13078). \n\n# Author contributions \n\nY.X. and C.L.Z. contributed equally to this work. Y.X., C.L.Z., and Y.L. conceived the idea, designed research plan, and wrote the paper. Y.X. and C.L.Z. carried out experiments and analyzed data. M.Z. and Q.F. contributed to the kinetics analysis and were involved in discussion on the electrochemical performance. C.X.Z. contributed to the theoretical simulations. Y.L., M.H.W., and Y.X. supervised the whole project. All the authors read the paper and made comments. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-04190-z. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1038_s41467-018-02978-7", + "DOI": "10.1038/s41467-018-02978-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-02978-7", + "Relative Dir Path": "mds/10.1038_s41467-018-02978-7", + "Article Title": "Efficient green light-emitting diodes based on quasi-two-dimensional composition and phase engineered perovskite with surface passivation", + "Authors": "Yang, XL; Zhang, XW; Deng, JX; Chu, ZM; Jiang, Q; Meng, JH; Wang, PY; Zhang, LQ; Yin, ZG; You, JB", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Perovskite light-emitting diodes (LEDs) are attracting great attention due to their efficient and narrow emission. Quasi-two-dimensional perovskites with Ruddlesden-Popper-type layered structures can enlarge exciton binding energy and confine charge carriers and are considered good candidate materials for efficient LEDs. However, these materials usually contain a mixture of phases and the phase impurity could cause low emission efficiency. In addition, converting three-dimensional into quasi-two-dimensional perovskite introduces more defects on the surface or at the grain boundaries due to the reduction of crystal sizes. Both factors limit the emission efficiency of LEDs. Here, firstly, through composition and phase engineering, optimal quasi-two-dimensional perovskites are selected. Secondly, surface passivation is carried out by coating organic small molecule trioctylphosphine oxide on the perovskite thin film surface. Accordingly, green LEDs based on quasi-two-dimensional perovskite reach a current efficiency of 62.4 cd A(-1) and external quantum efficiency of 14.36%.", + "Times Cited, WoS Core": 908, + "Times Cited, All Databases": 983, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000424451300015", + "Markdown": "# Efficient green light-emitting diodes based on quasi-two-dimensional composition and phase engineered perovskite with surface passivation \n\nXiaolei Yang1,2, Xingwang Zhang1,3, Jinxiang Deng2, Zema Chu1, Qi Jiang1,3, Junhua Meng1,3, Pengyang Wang1,3, Liuqi Zhang1,3, Zhigang Yin1,3 & Jingbi You 1,3 \n\nPerovskite light-emitting diodes (LEDs) are attracting great attention due to their efficient and narrow emission. Quasi-two-dimensional perovskites with Ruddlesden–Popper-type layered structures can enlarge exciton binding energy and confine charge carriers and are considered good candidate materials for efficient LEDs. However, these materials usually contain a mixture of phases and the phase impurity could cause low emission efficiency. In addition, converting three-dimensional into quasi-two-dimensional perovskite introduces more defects on the surface or at the grain boundaries due to the reduction of crystal sizes. Both factors limit the emission efficiency of LEDs. Here, firstly, through composition and phase engineering, optimal quasi-two-dimensional perovskites are selected. Secondly, surface passivation is carried out by coating organic small molecule trioctylphosphine oxide on the perovskite thin film surface. Accordingly, green LEDs based on quasi-two-dimensional perovskite reach a current efficiency of $62.4\\mathsf{c d}\\mathsf{A}^{-1}$ and external quantum efficiency of $14.36\\%$ . \n\n$\\smile$ tsihoon-wpgrocoedsspehdothoalluidme npesrcoevnsckeitequsaenmtiucmonydiuelcdtso $\\mathrm{\\lighting^{8}}$ ) . The perovskite light-emitting diodes (PeLEDs) have been reported with moderate electroluminescence (EL) efficiencies as well9–15. Their external quantum efficiencies (EQEs) have reached about $10\\%$ for near-infrared13–15 and also in green emission11,12,15. Hybrid organic–inorganic perovskites are better known for their free charge carriers with long diffusion length, which is good for solar cells. However, opposite properties are desired when they are used as emitting materials in $\\mathrm{LEDs^{11,16-18}}$ . The idea is to spatially confine charges with the insulating layers, and thus the exciton dissociation is suppressed and the radiative recombination can be enhanced in the perovskite films. Several efficient methods have been adopted, including polymer composite19, nanocrystal pinning11 and quantum dots3–7. \n\nThe exciton binding energy is enlarged in the two-dimensional (2D) perovskite and thus the emission efficiency can be enhanced20,21. In the early reports, 2D perovskite materials were used as emitting layers, while electroluminescence can only be observed at liquid nitrogen temperature20. Recently, quasi-twodimensional (quasi-2D) perovskites have been proposed by doping 2D perovskites into three-dimensional (3D) perovskite structures. The initial idea was to enhance the humidity stability of perovskite solar cells22–24. More recently, it was found that multiple quantum wells could be assembled in these quasi-2D perovskites13,14, which can facilitate the formation of exciton and reduce the possibility of exciton dissociation. This makes the quasi-2D perovskite an efficient luminescent material13–15,25. The working mechanism of quasi-2D PeLEDs has been fully discussed elsewhere13,14. Electrons and holes injected from large bandgap phases (small $n$ -phase) can rapidly transfer into small bandgap phases (large $n$ -phase), then electrons and holes recombine in large $n$ -phase and emit as photons. The EQEs of quasi-2D perovskite LEDs have achieved around $10\\%^{13,14}$ and highest EQE of $11.7\\%$ in near-infrared region was obtained14. Comparing to organic or inorganic LED counterparts26,27, there is still room for improvement in the EQE. \n\nIt is known that quasi-2D perovskite materials usually contain a mixture of phases and the phase impurity could lead to low emission efficiency, and thus fine control of the composition/ phases is critical for efficient emission. In addition, solution processed thin films of quasi-2D perovskite show reduced crystal size compared to those of 3D perovskite13,15. This could increase the concentration of the defects and traps on the film surface and grain boundaries, which will act as non-radiative recombination centers and thus decrease the emission efficiency. Surface passivation has been proved an efficient way for reducing the defects in perovskite solar cells28–30. \n\nIn this article, $\\mathrm{PEA}_{2}(\\mathrm{FAPbBr}_{3})_{n-1}\\mathrm{PbBr}_{4}$ $(n=1,~2,~...,~\\infty)$ is investigated as the emitting layer for quasi-2D perovskite LEDs, where PEA and FA are phenylethylammonium $(\\bar{\\mathrm{C}}_{6}\\mathrm{H}_{5}\\mathrm{C}_{2}\\mathrm{H}_{4}\\mathrm{NH}_{3}{}^{+})$ and formamidinium $\\mathrm{(HC(NH_{2})_{2}}^{+}\\mathrm{)}$ , respectively. Firstly, we optimize the films phase engineering/phase engineering. We find that the perovskite with $n=3$ composition shows decent phases and the obtained films show the highest photoluminescence (PL) \n\n![](images/560d7b6399bef981c5f10e5d35bfe51b6e2b642a7cdbe1c609e209673909c783.jpg) \nFig. 1 Properties of perovskite films with different compositions. a Scheme of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ phases. The black part is PEA, the blue square is $\\mathsf{P b B r}_{6}$ -octahedron and the gray dot is FA. b $\\mathsf{X}$ -ray diffraction patterns of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ films with different $\\mathfrak{n}$ -compositions. Diffraction patterns of $n=1$ phase (black vertical lines), $n=2$ phase (pink vertical lines) and $n=\\infty$ phase (marked with (100)) were labeled. The analysis details can be found in the Supplementary Table 2. c Photoluminescence of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ with different $n$ -compositions. d Photoluminescence intensity and peak of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ films with different compositions with the data collected from c. e Photoluminescence image of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ films with different compositions under ultraviolet lamp excitation \n\nyield. Secondly, we present surface passivation of quasi-2D perovskite films by trioctylphosphine oxide (TOPO) treatment31. Accordingly, the PeLEDs based on $\\mathrm{PEA}_{2}(\\mathrm{FAPbBr}_{3})_{n-1}\\mathrm{PbBr}_{4}$ with $n=3$ composition show green emission with current efficiency (CE) of $6\\dot{2}.4\\mathrm{cd}\\mathrm{A}^{-1}$ and EQE of $14.36\\%$ , which is the highest efficiency for PeLEDs reported so far. \n\n# Results \n\nProperties of quasi-2D perovskite with different compositions. The schematics of $n$ -phase $\\mathrm{PEA}_{2}(\\mathrm{FAPbBr}_{3})_{n-1}\\mathrm{PbBr}_{4}$ are drawn in Fig.1a, illustrating that the $n$ -phase unit cell contains $n{-}1$ sheets of $\\mathrm{PbBr}_{6}$ -octahedra and two PEA tiers. The perovskite films are prepared by spin-coating a precursor solution using a crystalpinning process11,32. Their compositions are controlled by the ratio PEABr:FABr: $\\mathrm{Pb}\\mathrm{Br}_{2}$ (Supplementary Table 1), and compositions $n$ ranging from 2 to 6 are discussed. Previous results suggested that the quasi-2D perovskite films are not a single phase but contain a variety of $n$ -phases13,14. For example, if the precursor solution with $n=2$ composition is spin-coated, the generated films might include $n=2$ phase but could also contain other phases such as $n=1$ or $n\\geq3$ . To avoid misunderstanding, we distinguish the composition and phase by $n$ -composition and $n$ -phase, respectively. Methylammonium chloride (MACl) is also added into the precursor to improve the morphology and enhance the emission efficiency of the formed films (Supplementary Figs. 1, 2 and 12), but most MACl escape from the film during annealing33. The role of MACl has been well investigated in solar cells33,34. First, the MACl can slow down perovskite crystallization and improve film morphology. Second, the incorporation of a very small amount of elemental Cl could passivate the grain boundary, and then enhance the emission efficiency (Supplementary Fig. 2). \n\nX-ray diffraction (XRD) measurements are carried out to determine the accurate phases in our obtained quasi-2D perovskite films. As shown in Fig. 1b, all the perovskite films with $n\\geq2$ compositions show diffraction peaks at $14.8^{\\circ}{}_{\\textrm{:}}$ , which is the same as the (100) diffraction patterns of the 3D perovskite $\\mathrm{FAPbBr}_{3}$ (refs. $^{7,35}$ ). However, the peaks become much more broadened, indicating that the diffraction peak could be from a series of $\\mathrm{PEA}_{2}(\\mathrm{FAPb}\\mathrm{Br}_{3})_{n-1}\\mathrm{Pb}\\mathrm{Br}_{4}$ phases with large $n$ $(n{\\rightarrow}\\infty)$ or 3D $\\mathrm{FAPbBr}_{3}$ with nano-size grains (Supplementary Fig.3)15. This result shows that all the quasi-2D perovskite films always contain large $n$ -phases $(n{\\rightarrow}\\infty)$ or 3D perovskite regardless of the composition of the precursor. Atomic force microscopy (AFM) images confirm the reduction of the crystal size during the transformation of 3D perovskite into quasi-2D perovskites (Supplementary Fig.3). \n\nIn addition to the diffraction peak at $14.8^{\\circ}$ , a series of Bragg reflections at low angles $(2\\theta<14.{\\overset{\\circ}{8}}^{\\circ})$ are observed for these quasi2D perovskites (Fig.1b). This indicates that the PEA group with large size is incorporated, and the size of unit cells is enlarged compared with 3D perovskite14,25,36. According to the analysis shown in Supplementary Table 2 and the unit cells of $n$ -phases shown in Fig.1a, it is found that the diffraction peaks $(2\\theta<14.8^{\\circ})$ are attributed to the $n=1$ and $n=2$ phases (diffraction patterns from $n\\geq3$ phases are not observed here). Specifically, for $n=1$ composition, only the $n=1$ phase exists; for $n=2$ composition, the $n=1$ and $n=2$ phases are both presented in the films. It is unexpected that diffraction peaks of the $n=1$ phase is absent in the $n=3$ composition, while obvious diffraction peaks from the $n=2$ phase are observed. For $n\\geq4$ compositions $\\dot{\\vert n>4}$ compositions are not shown here due to very weak small $n$ -phases diffractions), the diffraction peaks from small $n$ -phases become weak or absent. \n\nThe photoluminescence (PL) results of the quasi-2D perovskite films with different compositions are shown in Fig. 1c, and the 2D $(n=1)$ and 3D $\\left(n=\\infty\\right)$ perovskite films are also included for comparison. The 2D perovskite shows an emission at $412\\mathrm{nm}$ $(3.0\\bar{1}\\mathrm{eV})$ and the long tail21,37 at a longer wavelength, which could be due to the self-trapped exciton emission21 or the disordered structure. The 3D perovskite showed a band edge emission peak at $542\\mathrm{nm}$ $(2.2\\dot{9}\\mathrm{eV})^{38}$ . All quasi-2D perovskite films have two main emission peaks: one in the green region (approximately $532\\mathrm{nm}$ , approximately $2.33\\mathrm{eV}$ ) and another in the blue region (at $440\\mathrm{nm}$ , $2.82\\mathrm{eV}$ ). Comparing the PL with the absorption spectra (Fig.1c and Supplementary Fig. 4), it can be found that the stronger green emission at approximately $532\\mathrm{nm}$ comes from large $n$ -phases $(n{\\rightarrow}\\infty)$ or 3D perovskite, and the weaker blue emission at $440\\mathrm{nm}$ comes from the $n=2$ phase. The emission phases we find are nearly almost consistent with the XRD results. There are some exceptions: for the $n=2$ composition, we have not observed the $n=1$ phase emission, while the $n$ $=4$ composition shows an emission at $405\\mathrm{nm}$ from the 2D perovskite phase $\\begin{array}{r}{(n=1).}\\end{array}$ ), and the reason for this is not clear at present. \n\nThe relative PL intensity and emission peak wavelength in the green emission from the quasi-2D perovskites and 3D perovskite are plotted in Fig. 1d. It is found that the $n=3$ composition film shows the brightest green emission. The significant blue-shift of the green emission from quasi-2D perovskites is observed compared with the 3D perovskite. In addition, a smaller $n$ - composition showed a larger blue-shift, indicating that the blueshift is due to the quantum confinement effect. The emission images of these quasi-2D perovskite films under ultraviolet excitation (Fig. 1e) also confirms that the $n=3$ composition shows the best PL. \n\nCompared with 3D perovskites, significant enhancement of the PL is observed for quasi-2D perovskites (Fig.1c). This is due to the quantum confinement effect via the formation of quantum well structures between large bandgap phases (smaller $n$ -phases) and small bandgap phases ( $\\cdot\\ n{\\rightarrow}\\infty$ phase or 3D perovskite)13,14. The different emissions from various compositions observed in Fig.1c could be explained by the competition between confinement phase (small $n$ -phase) and emission phase (large $n$ -phase, $n{\\rightarrow}{\\infty}$ phase). Here, we use $n=2$ , 3, 4 compositions as examples. According to XRD results shown in Fig.1b, the $n=2$ confinement phase and 3D emission phase dominate in $n=2$ and $n=4$ composition, respectively, and both of these will cause weak green emission. While the amount of $n=2$ phase and 3D phase are adequate in the $n=3$ composition, this could be the reason of the highest PL of $n=3$ composition. The PLQY of the $n=3$ shows a value as high as $57.3\\%$ under low density excitation (excitation wavelength of $400\\mathrm{nm}$ , power density of $3.5\\mathrm{mW}\\mathrm{cm}^{-2}$ ). The quantum well of $n=3$ composition is mainly formed by the $n=2$ and $n{\\rightarrow}{\\infty}$ phases (Supplementary Fig. 6). \n\nPassivation of quasi-2D perovskite. Keeping in mind that the $n$ $=3$ composition of $\\mathrm{PEA}_{2}(\\mathrm{FAPbBr}_{3})_{n-1}\\mathrm{Pb}\\mathrm{\\bar{B}r}_{4}$ perovskite could be a good candidate for an emitting material, we further improve its emission by surface passivation. An organic small molecule TOPO is spin-coated onto the perovskite surface to form a thin passivation layer31. It is found that the PLQY of the $n=3$ composition film was significantly increased from $57.3\\%$ to $73.8\\%$ after coating with the TOPO layer (Fig. 2a), confirming the passivation effect of the TOPO layer. The average fluorescence lifetime of the $n=3$ composition film is also increased from 0.17 μs to $0.36\\upmu\\mathrm{s}$ after TOPO treatment (Fig. 2b). Although a small red-shift in PL spectra has been observed for the TOPO-treated 3D perovskite film previously31, no obvious modulation of PL due to TOPO treatment is observed in this study (Supplementary Fig. 7). \n\n![](images/bd60e41bf313a7c92a6bd5dc4afa8b0387c6d086050694930ed45e11bc9618ee.jpg) \nFig. 2 Passivation effect of TOPO on the perovskite with $n=3$ composition. a Photoluminescence quantum yield (PLQY) of the $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ (n $^{=3}$ composition) perovskite films with and without TOPO passivation. b Time-resolved photoluminescence (TRPL) of the $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ $\\therefore n=3$ composition) films with and without TOPO passivation layer. c Fourier transform infrared (FTIR) spectroscopy measurement for TOPO, $\\mathsf{P b B r}_{2}$ and TOPO$\\mathsf{P b B r}_{2}$ films prepared on silicon wafers \n\nThe passivation of halide perovskites is ascribed to the chemical interaction between molecular ligands and incomplete $\\mathrm{PbI}_{6}$ -octahedra in previous study39. To confirm this, Fourier transform infrared (FTIR) spectroscopy measurements were carried out, and the result is shown in Fig. 2c. An absorption peak located at $1150\\mathrm{cm}^{-1}$ is observed for TOPO, which corresponds to $\\scriptstyle\\mathrm{P=O}$ bond stretching vibrations40. This $\\scriptstyle\\mathrm{P=O}$ bond absorption peak shifts to approximately $1100\\mathrm{cm}^{-1}$ in the film comprised of TOPO and $\\mathrm{Pb}\\bar{\\mathrm{Br}}_{2}$ , indicating that the bonding between perovskite and TOPO could be formed41,42. \n\nDevice structure and performance. We configure PeLEDs as the structure $\\mathrm{glass/ITO/PEDOT:PSS/PEA_{2}(F A P b\\mathrm{\\bar{B}r_{3})_{\\scriptscriptstyle n-1}P b B r_{4}/T P B i/}}$ LiF/Al. Modified PEDOT:PSS (m-PEDOT:PSS) is used as the hole injection layer (HIL), TPBi/LiF as the electron injection layer (EIL) and the quasi-2D perovskites as the emitting layer. The band alignment for all function layers is shown in Fig. 3a, and TOPO shown in the figure acts as a thin passivation layer on the perovskite film. Br-based perovskites usually exhibit a deeper valence band (approximately $-6.0\\mathrm{eV}$ , Supplementary Fig.5) than that of PEDOT:PSS (approximately $-5.2\\mathrm{eV}.$ ). We doped PSS-Na into PEDOT:PSS to increase the work function43, which can improve hole injection as well as device performance (Supplementary Fig.13). The cross-section scanning electron microscopy (SEM) image of the completed device is shown in Fig. 3b, and a clear sandwich device structure is observed. The thicknesses of mPEDOT:PSS (HIL), the perovskite layer and TPBi (EIL) are about \n\n50, 110 and $30\\mathrm{nm}$ , respectively. The typical EL spectra of the $n=$ 3 composition-based PeLEDs under different voltage bias are shown in Fig. 3c. Although the perovskite films exhibit a mixture of many phases with different bandgaps, only single green EL is observed, even in logarithmic scale (Supplementary Fig. 8), which is different from the PL. It can be estimated that the charge density injected by EL $(10^{17}s^{-1}\\mathrm{cm}^{-2})$ is two orders higher than that excited by PL $(10^{15}\\mathrm{s}^{-1}\\mathrm{cm}^{-2})$ under injection/excitation of $5.1\\mathrm{V}$ , $30\\mathrm{mA}\\mathrm{\\dot{c}m}^{-2}$ and $1\\mathrm{mW}\\mathrm{cm}^{-2}$ , $340\\mathrm{nm}$ excitation, respectively, while the blue emission is still not observed in EL. This could be due to the different working mechanism between EL and PL. For the PL, the photo-excited charges are driven from a larger bandgap phase to a smaller bandgap phase by their conduction/ valence band energy difference. However, for EL, the driving force is not only the energy difference, but also the applied external electric field. As a result, most charges will be injected and recombined in the smallest band gap phases. This could be the reason that only green EL is observed even under high charge density injection. The EL peak is located at $532\\mathrm{nm}$ and the full width at half maximum is about $23\\mathrm{nm}$ . The emission of our PeLEDs exhibited a good color purity $(95\\%)$ in the green region, with Commission Internationale de l’Eclairage (CIE) chromaticity coordinate at (0.21, 0.75) (Fig. 3d). \n\nWe characterize the PeLEDs with different compositions (Fig. 4a, b and Supplementary Fig. 9). It is found that the $n=2$ composition showed the lowest injection current (Supplementary Fig. 9), which could be due to the poor transport properties of 2D phase. Correspondingly, the brightness and CE of $n=2$ composition-based devices are both the lowest (Fig. 4a, b). The compositions of $n=3$ and $n=4$ based PeLEDs show the maximum brightness of about $7000c\\mathrm{d}\\mathrm{m}^{-2}$ and $8700\\c{\\mathrm{cd}}\\mathrm{m}^{-2}$ respectively, while $n=3$ composition shows a higher CE (40.2 cd $\\mathbf{A}^{-1}$ ) than $n=4$ composition $\\dot{(37.6\\mathrm{cd}\\mathrm{A}^{-1}}.$ ). For the $n=5$ and $n=6$ compositions, consistent with their PL efficiency (Fig.1c, e), their EL also could not compare with that of $n=3$ composition. The detailed device performances for various compositions are summarized in Table 1. \n\n![](images/4b8d2323785e4919d6088ce9e0d3f28b14233a30e5cd697712258209768964e9.jpg) \nFig. 3 Perovskite light-emitting diodes structure and electroluminescence. a Band alignment of each function layer in the devices. b Cross-section scanning electron microscopy (SEM) image of the device, the scale bar is $100\\mathsf{n m}$ . c Typical electroluminescence (EL) spectra of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B}$ r4 ( $\\cdot n=3$ composition) based PeLEDs under different voltage bias. Inset shows the electroluminescence image of PeLEDs. d The corresponding Commission Internationale de l’Eclairage (CIE) coordinate of typical PeLEDs based on $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ ( $\\cdot n=3$ composition) \n\nWe next discuss the role of surface passivation in performance improvement for $n=3$ composition. It is found that the turn-on voltage increases and the injection current decreases after introducing a TOPO layer (Supplementary Fig.10). This is due to the insulating property of TOPO and indicates that the TOPO is successfully coated on the perovskite surface. Figure $_{4c}$ shows the brightness curve of the PeLEDs with and without TOPO. The maximum brightnesses of the PeLEDs with and without passivation are at the same level, while the devices with passivation showed higher CE (Fig. 4d). The best performing device without TOPO passivation shows a CE of $\\dot{5}2.5\\operatorname{cd}\\mathrm{A}^{-\\mathrm{i}};$ while TOPO-treated devices show a CE as high as $62.4\\mathrm{cd}\\mathrm{A}^{-1}$ , and the power efficiency also increased from $49.4\\ln\\mathrm{W^{-1}}$ to 53.3 $\\mathrm{lm}\\mathrm{W}^{-1}$ (Supplementary Fig.11). Accordingly, a high EQE of $14.36\\%$ is obtained (Fig. 4e). We also find that our devices show good reproducibility. The EQE histogram for 60 devices from five batches are presented, showing an average EQE of $13.1\\%$ with a low relative standard deviation of $4.4\\%$ (Fig. 4f). \n\nminutes, which could be due to trap $\\mathrm{\\flling^{15}}$ that results in the improvement of electrical contacts. After that, the device performance gradually decreased, and finally the devices work for approximately $120\\mathrm{min}$ . We also noticed that larger injection current induces faster degradation, which could be due to heat accumulation or ion movements. Our device showed the almost same level stability of I-related perovskite with the stability in several $100\\mathrm{{min}}^{15}$ . Compared with the Br-related perovskite with several $10\\mathrm{min}$ stability in previous reports15,44, our devices showed a little bit improvement. \n\nFurther improvement of PeLED stability is necessary, and we assume that there are several issues leading to PeLED instability. One major issue could be ion migration under voltage bias, and another issue could be the phase stability of perovskite materials under heating or moist conditions. Several strategies could be adopted to improve PeLED stability such as finding stable perovskite-emitting materials19,45, incorporating suitable groups to avoid or suppress the ion movements12,19, seeking effective ligands17,46 to bond with the grain surface and also the film surface to reduce Joule heating induced by non-radiative recombination and finding stable charge injection layers47. \n\nIn summary, by composition/phase engineering, we find that a quasi-2D perovskite of $\\operatorname{PEA}_{2}(\\operatorname{FAPbBr}_{3})_{n-1}\\operatorname{PbBr}_{4}$ with $n=3$ composition showed good PL. We also introduce surface passivation to reduce the non-radiative recombination on the perovskite surface or grain boundaries. Combining composition/phase engineering and surface passivation, high performance of quasi2D PeLEDs with a CE of $62.4\\operatorname{cd}\\mathrm{A}^{-1}$ and an external quantum efficiency of $14.36\\%$ is achieved. \n\n# Discussion \n\nDevice stability is still a critical and common issue in PeLEDs. The stability of our PeLEDs with encapsulation was tested under a constant injection current in dry air (Supplementary Fig. 14). The luminance and CE increased at the beginning for several \n\n# Methods \n\nMaterials. The modified PEDOT:PSS (m-PEDOT:PSS) solution is a mix of normal PEDOT:PSS (AI 4083) aqueous solution and $100\\mathrm{mg\\mathrm{ml^{-1}}}$ PSS-Na (Sigma Aldrich) aqueous solution by a volume ratio of 6:5. TOPO, $\\operatorname{Pb}\\mathrm{Br}_{2}$ , dimethyl sulfoxide (DMSO) and chlorobenzene (CB) were purchased from Sigma Aldrich. ${}_{2,2^{\\prime},2^{\\prime\\prime}}$ - (1,3,5-Benzinetriyl)- tris(1-phenyl-1-H-benzimidazole) (TPBi) and formamidinium bromide (FABr) and methylammonium chloride (MACl) were purchased from Xi’an Polymer Light Technology Corp. Phenylethylammonium bromide (PEABr) was purchased from Dyesol (now Greatcell Solar). \n\n![](images/91964a6bc09252d96297174e0a537a8030d5c73e721c3cb3ac3c4b00a74f090e.jpg) \nFig. 4 Device performance of perovskite LEDs with different compositions and surface passivation. a Luminance–voltage (L-V) curves of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n}$ - $\\mathsf{\\Omega}_{1}\\mathsf{P b}\\mathsf{B}\\mathsf{r}_{4}$ with different compositions. b Current efficiency–voltage (CE-V) curves of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ with different compositions. c Luminance–voltage (L-V) curves of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ $\\therefore n=3$ composition) devices with and without TOPO layer. d Current efficiency–voltage (CE-V) curves of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ ( $\\overset{\\cdot}{\\boldsymbol{n}}=3$ composition) devices with and without TOPO layer. e External quantum efficiency (EQE) of the champion device of $\\mathsf{P E A}_{2}(\\mathsf{F A P b B r}_{3})_{n-1}\\mathsf{P b B r}_{4}$ ( $\\overset{\\cdot}{\\boldsymbol{n}}=3$ composition) with TOPO passivation layer. f Histogram of maximum EQEs measured from 60 devices \n\n
Table 1 Device performance based on quasi-two- dimensional perovskites PEA(FAPbBr3)n-1PbBr4
CompositionsLmax (cd m-2)Current efficiency (cd A-1)Maximum EQE (%)
n=27175.981.54
n=3697340.209.29
n=3(best)782952.5112.12
n=4877937.618.45
n=5345220.954.82
n=6228116.774.00
n=3andTOPO912062.4314.36
\n\nDevice fabrication. The indium tin oxide (ITO)-coated glass substrates were sequentially cleaned in detergent, distilled water, acetone and isopropanol by sonication and used as anode. The cleaned substrates were ultraviolet ozone treated for $15\\mathrm{min}$ to make the surface hydrophilic, then $\\mathbf{m}$ -PEDOT:PSS (or normal PEDOT:PSS) aqueous solution was spin-coated at $9000\\mathrm{rpm}$ (or $2500\\mathrm{rpm},$ for $40\\:s$ and baked at $160^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ in ambient air. Thereafter, the substrates were transferred into a nitrogen-filled glove box, and the $0.6\\mathrm{moll^{-1}}$ $\\mathrm{Pb}^{2+}$ concentration) perovskite solution in DMSO was spin-coated onto the $\\mathbf{m}$ -PEDOT:PSS (or normal PEDOT:PSS) films at $3000\\mathrm{rpm}$ for $2\\mathrm{min}$ , and after spin coating for $40\\:s$ $100\\upmu\\mathrm{l}$ of CB was poured onto the film for pinning the perovskite crystallization, followed by annealing on a hot plate at $90^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . The perovskite precursor solution was prepared according to Supplementary Table 1. For surface passivation, $2\\mathrm{mg}\\mathrm{ml}^{-1}$ TOPO in CB was dripped onto the perovskite film for a 1 min to let TOPO passivate the film surface enough and then spin-coated at $7000\\mathrm{rpm}$ for $1\\mathrm{min}$ . Finally, the fabrication of PeLEDs was completed by depositing TPBi, LiF (less than $1\\mathrm{nm}\\dot{}$ ) and Al electrode layer by layer through a shadow mask in a high vacuum thermal evaporator. The device area was $0.1\\mathrm{08}\\mathrm{cm}^{2}$ as defined by the overlapping area of the ITO and Al electrode. The thickness of ITO and Al are $130\\mathrm{nm}$ and 60 nm, respectively. \n\nMaterial and device characterizations. XRD measurements were performed with a Rigaku $\\mathrm{D/max}2500\\mathrm{H}$ equipment with a conventional Cu target X-ray tube (Cu \n\nK-alpha, $\\lambda{=}1.5418\\mathrm{\\AA}$ ) set to $40\\mathrm{kV}$ and $200\\mathrm{{mA}.}$ Steady-state PL spectra and timeresolved fluorescence spectra (TRPL) of the perovskite films were measured at room temperature in the ambient air using a fluorescent spectrophotometer (HORIBA JY Nanolog-TCSPC). The excitation wavelength for PL and TRPL are both $340\\mathrm{nm}$ , which were provided by $450\\mathrm{W}$ xenon lamp and a pulsed diode laser (NanoLed-340), respectively. The PLQY of the perovskite films was measured using an Edinburgh FLS920 equipment with a $450\\mathrm{W}$ xenon lamp as excitation source. The following settings were applied for PLQY measurements: excitation wavelength of $400\\mathrm{nm}$ ; bandpass values of 3.00 and $0.35\\mathrm{nm}$ for the excitation and emission slits, respectively; step increments of $0.5\\mathrm{nm}$ and integration time of $0.3\\:\\mathrm{s}$ per data point. We measured the light intensity with a laser power meter and the estimated light power density incident on the samples was about $3.5\\mathrm{mW}\\mathrm{cm}^{-2}$ . The ultraviolet–visible absorbance spectra were recorded on an ultraviolet–visible spectrophotometer (Cary 5000, Varian). The FTIR spectra were recorded on an infrared spectrophotometer (Excalibur 3100, Varian) in a general mode that did not use attenuated total reflection component. AFM images of the perovskite films were collected in noncontact mode (Bruker FASTSCANBIO). The cross-sectional image of PeLEDs was made on a scanning electron/focused ion beam double-beam equipment (FEI Nova200 NanoLab) operated at $2\\mathrm{kV}$ . Ultraviolet photoelectron spectroscopy (UPS) spectra were collected on a Thermo Scientific ESCALab250Xi equipment with an applied bias of $-10\\mathrm{V}$ . He I ultraviolet radiation source $(21.22\\mathrm{eV})$ was used. The helium pressure in the analysis chamber during measurement was about 2E−8 mbar. The film samples over the ITO layer had a conductive connection with an Au sample, so the Fermi level value of the film samples is equal to that of Au sample. The work function $\\phi$ (that is the Fermi level absolute value of the free film) of the test films can be calculated from following equation: $h\\nu-\\phi=E_{\\mathrm{Fermi}}-E_{\\mathrm{cutoff}},$ where $E_{\\mathrm{Fermi}}$ and $E_{\\mathrm{cutoff}}$ are respectively the value of Fermi level position and the steep edge position in the UPS spectrum of the test film, $h\\nu{=}21.22\\mathrm{eV}$ , $E_{\\mathrm{Fermi}}$ is $21.02\\mathrm{eV}$ for Au. Two Keithley 2400 source meter units linked to a calibrated silicon photodiode were used to measure the current–voltage–brightness characteristics. The measurement system was carefully calibrated by a Hamamatsu C9920-02G equipment and a $100\\mathrm{mm}$ integrating sphere of Enli Technology using our perovskite LEDs. Lambertian profile was used in the calculation of EQE. All the device characterization tests of perovskite LEDs were carried out at room temperature in the ambient air for the un-encapsulated devices, except that operational stability test was carried in dry air for the encapsulated devices. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Received: 13 September 2017 Accepted: 11 January 2018 Published online: 08 February 2018 \n\n# References \n\n1. Deschler, F. et al. High photoluminescence efficiency and optically pumped lasing in solution-processed mixed halide perovskite semiconductors. J. Phys. Chem. Lett. 5, 1421–1426 (2014). \n2. Xing, G. et al. Low-temperature solution-processed wavelength-tunable perovskites for lasing. Nat. Mater. 13, 476–480 (2014). \n3. Protesescu, L. et al. Nanocrystals of cesium lead halide perovskites $\\mathrm{(CsPbX_{3}}$ , $\\scriptstyle\\mathrm{X=Cl},$ , Br, and I): novel optoelectronic materials showing bright emission with wide color gamut. Nano Lett. 15, 3692–3696 (2015). \n4. Zhang, F. et al. Brightly luminescent and color-tunable colloidal $\\mathrm{CH_{3}N H_{3}P b X_{3}}$ (X=Br, I, Cl) quantum dots: potential alternatives for display technology. ACS Nano 9, 4533–4542 (2015). \n5. Song, J. et al. Quantum dot light-emitting diodes based on inorganic perovskite cesium lead halides $(\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3})$ ). Adv. Mater. 27, 7162–7167 (2015). \n6. Protesescu, L. et al. Monodisperse formamidinium lead bromide nanocrystals with bright and stable green photoluminescence. J. Am. Chem. Soc. 138, 14202–14205 (2016). \n7. Levchuk, I. et al. Brightly luminescent and color-tunable formamidinium lead halide perovskite $\\mathrm{FAPb}{\\mathrm{X}}_{3}$ $\\mathrm{{X=Cl},}$ Br, I) colloidal nanocrystals. Nano Lett. 17, 2765–2770 (2017). \n8. Kovalenko, M. V. et al. Properties and potential optoelectronic applications of lead halide perovskite nanocrystals. Science 358, 745–750 (2017). \n9. Tan, Z. K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotech. 9, 687–692 (2014). \n10. Wang, J. et al. Interfacial control toward efficient and low-voltage perovskite light-emitting diodes. Adv. Mater. 27, 2311–2316 (2015). \n11. Cho, H. et al. Overcoming the electroluminescence efficiency limitations of perovskite light-emitting diodes. Science 350, 1222–1225 (2015). \n12. Zhang, L. et al. Ultra-bright and highly efficient inorganic based perovskite light-emitting diodes. Nat. Commun. 8, 15640 (2017). \n13. Yuan, M. J. et al. Perovskite energy funnels for efficient light-emitting diodes. Nat. Nanotech. 11, 872–877 (2016). \n14. Wang, N. et al. Perovskite light-emitting diodes based on solution-processed self-organized multiple quantum wells. Nat. Photon. 10, 699–704 (2016). \n15. Xiao, Z. G. et al. Efficient perovskite light-emitting diodes featuring nanometre-sized crystallites. Nat. Photon. 11, 108–115 (2017). \n16. Sutherland, B. R. & Sargent, E. H. Perovskite photonic sources. Nat. Photon. 10, 295–302 (2016). \n17. Veldhuis, S. A. et al. Perovskite materials for light-emitting diodes and lasers. Adv. Mater. 28, 6804–6834 (2016). \n18. Kim, Y. H., Cho, H. & Lee, T. W. Metal halide perovskite light emitters. Proc. Natl. Acad. Sci. USA 113, 11694–11702 (2016). \n19. Ling, Y. et al. Enhanced optical and electrical properties of polymer-assisted all-inorganic perovskites for light-emitting diodes. Adv. Mater. 28, 8983–8989 (2016). \n20. Era, M. et al. Electroluminescent device using two dimensional semiconductor $(\\mathrm{C_{6}H_{5}C_{2}H_{4}N H_{3}})_{2}\\mathrm{PbI_{4}}$ as an emitter. Synth. Met. 71, 2013–2014 (1995). \n21. Dou, L. et al. Atomically thin two-dimensional organic-inorganic hybrid perovskites. Science 349, 1518–1521 (2015). \n22. Smith, I. C. et al. A layered hybrid perovskite solar-cell absorber with enhance moisture stability. Angew. Chem. Int. Ed. 53, 11232–11235 (2014). \n23. Tsai, H. et al. High-efficiency two-dimensional Ruddlesden-Popper perovskite solar cells. Nature 536, 312–316 (2016). \n24. Quan, L. N. et al. Ligand-stabilized reduced-dimensionality perovskites. J. Am. Chem. Soc. 138, 2649–2655 (2016). \n25. Byun, J. et al. Efficient visible quasi-2D perovskite light-emitting diodes. Adv. Mater. 28, 7515–7520 (2016). \n26. Reineke, S. et al. White organic light-emitting diodes with fluorescent tube efficiency. Nature 459, 234–238 (2009). \n27. Pimputkar, S. et al. Prospects for LED lighting. Nat. Photon. 3, 180–182 (2009). \n28. Noel, N. K. et al. Enhanced photoluminescence and solar cell performance via Lewis base passivation of organic-inorganic lead halide perovskites. ACS Nano 8, 9815–9821 (2014). \n29. Wang, F. et al. Phenylalkylamine passivation of organolead halide perovskites enabling high-efficiency and air-stable photovoltaic cells. Adv. Mater. 28, 9986–9992 (2016). \n30. de Quilettes, D. W. et al. Impact of microstructure on local carrier lifetime in perovskite solar cells. Science 348, 683–686 (2015). \n31. de Quilettes, D. W. et al. Photoluminescence lifetimes exceeding $8~\\upmu s$ and quantum yields exceeding $30\\%$ in hybrid perovskite thin films by ligand passivation. ACS Energy Lett. 1, 438–444 (2016). \n32. Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n33. You, J. et al. Low-temperature solution-processed perovskite solar cells with high efficiency and flexibility. ACS Nano 8, 1674–1680 (2014). \n34. Stranks, S. D. et al. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n35. Meng, L. et al. Pure formamidinium-based perovskite light-emitting diodes with high efficiency and low driving voltage. Adv. Mater. 29, 1603826 (2017). \n36. Quan, L. N. et al. Tailoring the energy landscape in quasi-2D halide perovskites enables efficient green-light emission. Nano. Lett. 17, 3701–3709 (2017). \n37. Liang, D. et al. Color-pure violet-light-emitting diodes based on layered lead halide perovskite nanoplates. ACS Nano 10, 6897–6904 (2016). \n38. Arora, N. et al. Photovoltaic and amplified spontaneous emission studies of high-quality formamidinium lead bromide perovskite films. Adv. Funct. Mater. 26, 2846–2854 (2016). \n39. Bi, D. Q. et al. Polymer-templated nucleation and crystal growth of perovskite films for solar cells with efficiency greater than $21\\%$ . Nat. Energy 1, 16142 (2016). \n40. Bayou, N. et al. Elaboration and characterisation of a plasticized cellulose triacetate membrane containing trioctylphosphine oxyde (TOPO): application to the transport of uranium and molybdenum ions. C. R. Chim. 13, 1370–1376 (2010). \n41. Söderlind, F. et al. Synthesis and characterisation of ${\\mathrm{Gd}}_{2}{\\mathrm{O}}_{3}$ nanocrystals functionalised by organic acids. J. Colloid Interface Sci. 288, 140–148 (2005). \n42. Chang, S. M., Lo, P. H. & Chang, C. T. Photocatalytic behavior of TOPOcapped $\\mathrm{TiO}_{2}$ nanocrystals for degradation of endocrine disrupting chemicals. Appl. Catal. B Environ. 91, 619–627 (2009). \n43. Zuo, C. T. & Ding, L. M. Modified PEDOT layer makes a $1.52\\mathrm{~V~V}_{\\mathrm{OC}}$ for perovskite/PCBM solar cells. Adv. Energy Mater. 7, 1601193 (2016). \n44. Zhang, X. et al. Enhancing the brightness of cesium lead halide perovskite nanocrystal based green light-emitting devices through the interface engineering with perfluorinated ionomers. Nano. Lett. 16, 1415–1420 (2016). \n45. Kulbak, M., Cahen, D. & Hodes, G. How important is the organic part of lead halide perovskite photovoltaic cells? Efficient CsPbBr3 cells. J. Phys. Chem. Lett. 6, 2452–2456 (2015). \n46. Li, J. et al. 50-Fold EQE improvement up to $6.27\\%$ of solution-processed allinorganic perovskite $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QLEDs via surface ligand density control. Adv. Mater. 29, 1603885 (2017). \n47. You, J. et al. Improved air stability of perovskite solar cells via solutionprocessed metal oxide transport layers. Nat. Nanotech. 11, 75–81 (2016). \n\n# Acknowledgements \n\nThis work is supported by National Natural Science Foundation of China (Grant Numbers: 61574133, 61634001), National Key Research and Development Program of China (Grant No. 2016YFB0700700), National 1000 Young Talents awards and Young top-notch talent project of Beijing. \n\n# Author contributions \n\nJ.Y. conceived the idea, designed the experiment and analyzed the data. X.Y. fabricated devices and collected all data. X.Z., J.D., Z.C., Q.J., J.M., P.W., L.Z. and Z.Y. were involved in data analysis. J.Y. and X.Y. co-wrote the manuscript. J.Y. directed and supervised the project. All authors contributed to discussions and finalization of the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-02978-7. \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1038_s41467-018-04998-9", + "DOI": "10.1038/s41467-018-04998-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-04998-9", + "Relative Dir Path": "mds/10.1038_s41467-018-04998-9", + "Article Title": "Injectable antibacterial conductive nullocomposite cryogels with rapid shape recovery for noncompressible hemorrhage and wound healing", + "Authors": "Zhao, X; Guo, BL; Wu, H; Liang, YP; Ma, PX", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Developing injectable antibacterial and conductive shape memory hemostatic with high blood absorption and fast recovery for irregularly shaped and noncompressible hemorrhage remains a challenge. Here we report injectable antibacterial conductive cryogels based on carbon nullotube (CNT) and glycidyl methacrylate functionalized quaternized chitosan for lethal noncompressible hemorrhage hemostasis and wound healing. These cryogels present robust mechanical strength, rapid blood-triggered shape recovery and absorption speed, and high blood uptake capacity. Moreover, cryogels show better blood-clotting ability, higher blood cell and platelet adhesion and activation than gelatin sponge and gauze. Cryogel with 4mg/mL CNT (QCSG/CNT4) shows better hemostatic capability than gauze and gelatin hemostatic sponge in mouse-liver injury model and mouse-tail amputation model, and better wound healing performance than Tegaderm (TM) film. Importantly, QCSG/CNT4 presents excellent hemostatic performance in rabbit liver defect lethal noncompressible hemorrhage model and even better hemostatic ability than Combat Gauze in standardized circular liver bleeding model.", + "Times Cited, WoS Core": 980, + "Times Cited, All Databases": 1015, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000438857400006", + "Markdown": "# Injectable antibacterial conductive nanocomposite cryogels with rapid shape recovery for noncompressible hemorrhage and wound healing \n\nXin Zhao1, Baolin Guo 1, Hao Wu2, Yongping Liang1 & Peter X. Ma 3,4,5 \n\nDeveloping injectable antibacterial and conductive shape memory hemostatic with high blood absorption and fast recovery for irregularly shaped and noncompressible hemorrhage remains a challenge. Here we report injectable antibacterial conductive cryogels based on carbon nanotube (CNT) and glycidyl methacrylate functionalized quaternized chitosan for lethal noncompressible hemorrhage hemostasis and wound healing. These cryogels present robust mechanical strength, rapid blood-triggered shape recovery and absorption speed, and high blood uptake capacity. Moreover, cryogels show better blood-clotting ability, higher blood cell and platelet adhesion and activation than gelatin sponge and gauze. Cryogel with 4 mg/mL CNT (QCSG/CNT4) shows better hemostatic capability than gauze and gelatin hemostatic sponge in mouse-liver injury model and mouse-tail amputation model, and better wound healing performance than Tegaderm™ film. Importantly, QCSG/CNT4 presents excellent hemostatic performance in rabbit liver defect lethal noncompressible hemorrhage model and even better hemostatic ability than Combat Gauze in standardized circular liver bleeding model. \n\nHceimviolirarnh tgreaucomnat ocleinstears ancirocsasnth civilian trauma centers across the world', and uncon- erlnd1o, amnildi urnycaond$30\\%$ world-wide and more than half of those occur before emergency care can be reached2,3. Thus, employing hemostatic agents to rapidly and effectively control the hemorrhage is very important for trauma emergency. An ideal hemostatic agent should not only quickly control massive hemorrhage from large arteries, veins, and visceral organs but also should be biocompatible, ready and easy to use, lightweight, stable, and inexpensive . Although the current hemostatic agents including cyanoacrylates, glutaraldehyde cross-linked albumin2, zeolite-based QuickClot3, fibrin based bandages or gelatin-based hemostatic agents4,5 have been proven to be highly effective in stopping the hemorrhage, they are often ineffective for deep wounds incurred by small-caliber firearms, improvised explosive devices in battlefield and everyday life6, which are irregularly shaped and noncompressible7. \n\nTo address these issues, new hemostatic technologies were developed. XStat™ device, an applicator filled with numerous compressed cellulose sponges, can rapidly expand to fill and apply pressure to deep, noncompressible wounds8. Also, many other shape memory polymer foams as wound dressings or hemostatic agents were developed and presented good hemostatic capability9–11. However, XStat™ consists of miniature sponges, and need much more time to remove each individual sponge from the wound bed7. Besides, shape memory polymer foams often show inherently limited capacity for absorbing fluid7, and they need to take decades of seconds to recover their shapes7,9–11, which may prolong the hemostatic time and lose more blood. Thus, development of a user-friendly shape memory hemostatic material with instantaneous and high blood absorption capacity and fast shape recovery capacity to rapidly cease the noncompressible hemorrhage are still highly needed. \n\nCryogels possess inherent interconnected macroporous structure, and the characteristic structure allows water freely flow in and out of the cryogel, by which way the cryogel shape can be fixed by squeezing out of the free water and fast recovery to its original shape by absorbing water12–14. Thus, cryogel presents remarkable potential as shape memory hemostatic agent. However, although a lot of cryogels have been developed for biomedical applications12,15–19, there is no report about using cryogels for hemostatic application. Thus, cryogel hemostatic dressings developed by cheap materials with high inherent hemostatic ability are highly anticipated, while it still remains a challenge. \n\nThe cryogels often present relative weak mechanical strength for their macroporous morphology produced by formation of ice crystals in cryotropic gelation12,13,18,19. Nanocomposite hydrogels and cryogels were recently reported by using carbon nanotube (CNT) as the additive to enhance the mechanical property of the materials13,20–23. Moreover, the introduction of CNT can also endow the cryogel with excellent conductivity24 and NIR stimuliresponsive ability. On the other hand, the growing incidence of infection by antibiotic-resistant bacteria strains, is another challenge facing caregivers in combat trauma wounds4,25,26. Hemostatic agents with inherent antibacterial ability will show better performance than broad spectrum antibiotics in wound antiinfection under combat conditions4. Quaternized chitosan (QCS) exhibits good water solubility and enhanced antibacterial activity than chitosan27,28, and it performs good hemostatic effect and biocompatibility in vivo29,30. These properties of QCS suggest that it is an excellent candidate to prepare antibacterial cryogel hemostatic dressing, which has not been reported. Thus, developing multifunctional CNT-reinforced QCS based shape memory cryogel hemostatic dressing to stop the hemorrhage of deep noncompressible wounds is highly desirable in this field. \n\nIn this study, we aim to develop injectable antibacterial and conductive nanocomposite cryogels based on CNT-reinforced glycidyl methacrylate (GMA) functionalized quaternized chitosan (QCSG) with robust mechanical property, rapid blood-triggered shape recovery, rapid blood absorption speed, excellent NIR stimuli-responsivity, and we further demonstrate their great potential for in vivo lethal noncompressible hemorrhage hemostasis and wound healing applications. The cryogels show much better blood-clotting ability, blood cell and platelet adhesion and activation, than gauze and commercial gelatin hemostatic sponge in vitro. Furthermore, the hemostatic time and blood loss are evaluated in vivo to investigate the hemostatic effects of the cryogels in mouse liver injury model, mouse-tail amputation model, New Zealand rabbit liver defect lethal noncompressible hemorrhage model, and standardized circular New Zealand rabbit liver bleeding model, while the wound closure and histopathological examinations are evaluated in vivo to investigate the therapeutic effects of the cryogels in a mouse fullthickness skin defect model. All these results indicate the great potential of these cryogel as noncompressible hemorrhage hemostasis dressing and wound healing application. \n\n# Results \n\nSynthesis of antibacterial conductive nanocomposite cryogel. We prepared a series of CNT-reinforced antibacterial and conductive nanocomposite cryogels with rapid blood-triggered shape recovery and excellent NIR stimuli-responsivity as injectable shape memory hemostatic dressings based on QCSG and CNT (Fig. 1). Firstly, three QCSG copolymers were synthesized via one-pot reaction of chitosan (Fig. 1a, and Supplementary Table 1). QCSG3 with the quaternary amination degree of $46\\%$ showed excellent antibacterial activity (minimum inhibitory concentrations (MICs) of $20\\upmu\\mathrm{g/mL}$ for S. aureus and $40\\upmu\\mathrm{g/mL}$ for E. coli)27,30 and water solubility, and it was chosen to prepare the antibacterial cryogel in the further study (Supplementary Table 1). Secondly, CNT was well dispersed under ultrasound with the assistance of the diacrylate capped PF127 (PF127-DA) in water (Supplementary Fig. 1, and Supplementary Fig. 2). Thirdly, QCSG solution was fine mixed with PF127-DA/CNT dispersion liquid. The QCSG and PF127-DA/CNT dispersion was then placed at $-20^{\\circ}\\mathrm{C}$ for cryopolymerization after adding APS/ TEMED to form cryogel (Fig. 1c). QCSG served as the basic network of hemostatic cryogel, and QCSG with abundant positively charged quaternary ammonium groups would endow the cryogel with inherent antibacterial activity and excellent hemostatic capability3,27,30–33. Moreover, the CNT in the cryogel could provide the cryogel with hydrophobic drug encapsulation ability, NIR stimuli-responsivity, as well as good mechanical strength (Fig. 1d). Furthermore, due to the cryogel’s interconnected and macroporous structure, the cryogel could show rapid watertriggered shape memory property and high water absorption ability (Fig. 1e), as well as injectability (Supplementary Movie 1, Supplementary Movie 2, Supplementary Movie 3, Supplementary Movie 4 and Supplementary Fig. 3). Four cryogels with varying the CNT concentrations were synthesized (Supplementary Table 2). Chemical structure of the cryogels was confirmed by FTIR (Supplementary Fig. 4). \n\nSwelling ratio and mechanical properties of cryogels. Cryogels with interconnected and macroporous structure can present fast water uptake capability13,19,34. Thus the shape-fixed cryogel can be used to rapidly absorb the wound exudate to reduce the bacterial infection and promote healing7,35. Especially, the cryogel’s rapid water absorption ability was also hypothesized to concentrate clotting factors within the cryogel thus to enhance the rate of hemostasis7,36. The water absorption ability of the prepared cryogels was shown in Fig. 2a. QCSG/CNT0 had the highest swelling ratio of $4400\\%$ , and the swelling ratios of the QCSG/CNT cryogels gradually deceased from 3100 to 2500 and $2100\\%$ with the increase of PF127-DA/CNT content in the cryogels. This was due to the gradually increased crosslinking density and increased dry weight in per unit volume of the swollen cryogels when increasing PF127-DA/CNT content in the cryogel precursor. \n\n![](images/5ea452f47639843e7f2c6f2da4c81aacb513f4d8d12ea0cf31f9abfec1175c75.jpg) \nFig. 1 Schematic representation of QCSG/CNT cryogel synthesis. a Synthesis of QCSG copolymer. GTMAC and GMA with a fixed 0.5:1 molar ratio of GMA to amino groups and varying the GTMAC: amino groups from 1:1 (coded as QCSG1) to 2:1 (coded as QCSG2) and 3:1 (coded as QCSG3). b Synthesis of PF127-DA copolymer. c Preparation of QCSG/CNT cryogel. d Photographs of the compression and bending resistance capability of QCSG/CNT4 cryogels: initial state, compressed state by squeezing out of the free water, recovery state by absorbing water, bending and squeezing out of part free water, and recovery state after absorbing water. e Shape-fixed state after removing the free water (left) and expanding state after absorbing water (right). Scale bar: 1 cm \n\nCryogels prepared by pure natural product generally presented weak mechanical strength, which might hinder their application for hemostasis and wound healing. However, by incorporating CNT into the cryogel network can significantly reinforce the mechanical properties of the cryogels13. The cryogels’ compression stress–strain test was performed to evaluate the mechanical strength of the cryogels. These results in Fig. 2b demonstrated the significant reinforcement of QCSG/CNT cryogel by CNT and good mechanical stability of the cryogels. Besides, in order to further evaluate the high resilience with fast recovery and robustness of the interconnected macroporous cryogels, the dynamic stress–strain behavior of the cryogels was performed for \n\n10 cycles by applying three different strains of $40\\%$ , $60\\%$ , and $80\\%$ , respectively. As shown in Fig. 2c–f, all the four cryogels showed no obvious recovery loss when applying $40\\%$ and $60\\%$ strains, and all the cryogels still presented good shape and elasticity, suggesting their good compression resilience under small compression strains. When increasing the compression strain from $60\\%$ to $80\\%$ , all the four cryogels presented increasing recovery loss from 3.3 to 6.2, 11.8, and $12.4\\%$ with the increase of CNT in the cryogels. Moreover, their great robustness was confirmed by 100 cycles test (Supplementary Fig. 5) and were also presented in Supplementary Movie 5 and Supplementary Movie 6. The rheological properties of the cryogels in Supplementary Fig. 6 also suggested their stable cryogel networks. The CNT was stably trapped in the cryogel matrix when bearing continuous and dynamic compression (Supplementary Note 1). Furthermore, the cryogel as hemostatic agents will not cause severe pressure and additional injury to soft tissue during the application (Supplementary Note 2). \n\nThe mechanism of the high resilience and rapid recovery behavior was because of the elastic macroporous and soft-hard bicontinuous network structure of QCSG/CNT cryogel13 (Supplementary Note 3). Thus, all these results demonstrated that the CNT-reinforced cryogels possessed good mechanical strength (high resilience and rapid recovery) and stability, revealing their potential applications as injectable blood-triggered shape recovery hemostatic agent in deep wound hemostasis. \n\n![](images/75b70bfa5bf3a797e8ea20b47c4e4ee3d51b5a2ff9b3522dba73c11ce4c97a8d.jpg) \nFig. 2 Swelling and mechanical property of the cryogels. a Swelling ratios of the cryogels. b The uniaxial compression stress–strain curves of the cryogels. QCSG/CNT0 presented the lowest axial force of $2.5\\mathsf{N}$ when bearing a $93\\%$ compression strain, while the axial forces significantly increased from 3.5 to 9.6 and $\\ensuremath{12.0\\mathsf{N}}$ with the increase of CNT content from $2\\:\\mathrm{mg/mL}$ to $6\\mathrm{mg/mL}$ in the cryogel networks. Furthermore, all of the four cryogels kept stable and intact after the test. The stress–strain cycling curves of QCSG/CNT0 $\\mathbf{\\eta}(\\bullet)$ , QCSG/CNT2 (d), QCSG/CNT4 (e), and QCSG/CNT6 (f) with three different compression strains of $40\\%$ , $60\\%$ , and $80\\%$ , respectively. Error bar indicates s.d. $\\left(n=3\\right)$ ) \n\nConductivity and related photothermal property of cryogels. CNTs possess remarkable conductivity and NIR-responsive photothermal property37. Our previous reports have demonstrated the positive effect of conductive materials38–42 on tissue engineering including wound healing applications43. The wet QCSG/CNT0 cryogel presented the lowest conductivity of $8.5\\times10^{-3}\\mathrm{S/m}$ from amino groups and quaternary ammonium groups of QCSG (Fig. 3a). When introducing CNT and varying CNT content from 2 to 4 and $6\\mathrm{mg/mL}$ , the conductivity of the cryogels gradually increased from $4.0\\times10^{-2}$ to $9.5\\times\\mathrm{i}0^{-2}$ and $\\mathrm{i}.2\\times10^{-1}\\mathrm{S/m}.$ , revealing the obvious contribution of CNT to the cryogels’ conductivity. When drying the cryogels, all the cryogels’ ionic conductivity from QCSG disappeared. Thus, the conductivity of QCSG/CNT0 dramatically decreased $(2.1\\times10^{-7}\\mathrm{S/m})$ , and QCSG/CNT2 showed decreased conductivity of $5.0\\times10^{-4}\\mathrm{S/m}$ due to its lowest CNT content. However, QCSG/CNT4 and QCSG/CNT6 presented significantly higher conductivity of $8.1\\times10^{-1}\\mathrm{S/m}$ and $1.1\\mathrm{S}/\\mathrm{m}$ than their wet states, respectively, which might be explained for the higher connective network among CNT. The conductivity of $\\mathrm{\\DeltaQCSG/}$ CNT4 and QCSG/CNT6 would be effective to transmit electrical signals in wound tissue, which will promote wound healing process43. The QCSG/CNT4 presented a conductivity of $0.19\\mathrm{S}/\\mathrm{\\bar{m}}$ at ${\\bf100H z},\\quad$ while QCSG/CNT0 showed a very-low conductivity of $3.4\\times10^{-7}\\mathrm{S/m}$ from impedance curves in Supplementary Fig. 7. The results are in agreement with those from the digital 4-probe tester measurements. \n\nThe photothermal capacity of the cryogels was evaluated. The ΔT-NIR irradiation time curves of the cryogels were shown in Fig. 3b. QCSG/CNT0 showed no temperature increase after 10 min NIR irradiation $(1.4\\mathrm{W}/\\mathrm{cm}^{2})$ , while with the increase of CNT content from 2 to 4 and $6\\mathrm{mg/mL}$ , the equilibrium ΔTs increased from $14^{\\circ}\\mathrm{C}$ to $19^{\\circ}\\mathrm{C},$ demonstrating the excellent photothermal efficiency of CNT-reinforced cryogels. Besides, when QCSG/ CNT4 was irradiated by NIR varying the light intensity from \n\n![](images/775a674e5a2b59c6632f7b5730ef3589fc7a31355a9463728dea8f6a6ee5cf05.jpg) \nFig. 3 Conductivity, photothermal property, release behavior, and antibacterial activity of the cryogels. a Conductivity of the cryogels at wet state and dry state. b ΔT-NIR irradiation time curves of the cryogels using a constant light intensity of $1.4\\mathsf{W}/\\mathsf{c m}^{2}$ . c $\\Delta\\top$ -NIR irradiation time curves of QCSG/CNT4 varying the light intensity from 0.6 to 0.9, 1.1 and $1.4\\mathsf{W}/\\mathsf{c m}^{2}.$ respectively. d Spontaneous release profiles and NIR-triggered release profiles of ibuprofen from QCSG/CNT0 and QCSG/CNT4. Both QCSG/CNT0 with and without NIR irradiation and $\\mathsf{Q C S G/C N T4}$ without NIR irradiation showed similar sustained release profiles as long as 111 h in PBS. However, QCSG/CNT4 presented obvious burst release after applying 10 min NIR irradiation at each time point and completely released the drug within $74\\mathsf{h}$ . When stopping the irradiation, ibuprofen’s release profile returned to its common slow pattern. The killing-time curves of e S. aureus, ${\\pmb{\\mathrm{g}}}\\in c o l i,$ and i P. aeruginosa for the cryogel groups and PBS group after exposed to NIR irradiation $(1.4\\mathrm{W}/\\mathrm{cm}^{2})$ for 0 min, 1 min, 3 min, 5 min, 10 min, and $20\\mathsf{m i n}$ , respectively. Photographs of the survival f S. aureus, h E. coli, and j P. aeruginosa for the cryogel groups and PBS group after exposed to NIR irradiation $(1.4\\mathrm{W}/\\mathrm{cm}^{2})$ for 0 min, 1 min, 3 min, 5 min, $10\\min$ and $20\\mathrm{min}$ , respectively. Scale bar: 1 cm. $^{\\star\\star}P<0.01$ using Student's t-test (two-sided). Error bar indicates s.d. ${\\mathrm{\\Delta}n}=3{\\mathrm{\\cdot}}$ ) \n\n0.6 to 0.9, 1.1, and $1.4\\mathrm{W}/\\mathrm{cm}^{2}$ , the ΔTs gradually increased from 7 to 11, 13, and $19^{\\circ}\\mathrm{C},$ revealing the adjusted photothermal effect of CNT-reinforced cryogels (Fig. 3c). Furthermore, the heat maps of the cryogels after $10\\mathrm{min}$ NIR irradiation in Supplementary Fig. 8 were also consistent with the results in Fig. 3b, c, and a core central region with maximum temperatures from $32{\\mathrm{-}}44^{\\circ}\\mathrm{C}$ (corresponding $\\Delta\\mathrm{T}$ from $7-19^{\\circ}\\mathrm{C})$ was surrounded by zones with a large temperature gradient from the heat maps, which favors localized heat treatment44. \n\nAbove $50^{\\circ}\\mathrm{C},$ the enzymes in bacteria become denatured and their proteins and lipids on the cell membranes will be damaged, eventually causing bacterial death44,45. The NIR-assisted photothermal antibacterial activity of the QCSG/CNT4 ( $\\Delta\\mathrm{T}$ of $19^{\\circ}\\mathrm{C})$ was evaluated with QCSG/CNT0 and PBS as control groups as shown in Fig. 3e–j (Supplementary Note 4). When introducing CNT as photothermal contrast agent, QCSG/CNT4 showed significantly increased bacteria log reductions from 0.17 to 1.07 1 $92\\%$ killing ratio) for S. aureus, from 0.20 to 1.39 $96\\%$ killing ratio) for $E$ . coli, and from 0.25 to 1.31 $95\\%$ killing ratio) for $P$ . aeruginosa, respectively, after only 1 min NIR irradiation. Further increasing the irradiation time to $10\\mathrm{min}$ , QCSG/CNT4 groups showed $100\\%$ bacteria killing ratios for all the three bacteria and presented log reductions of 6.71, 7.01, and 7.06 for S. aureus, $E$ . coli and $P$ . aeruginosa, respectively. Photographs of the survival bacteria in Fig. 3 showed the similar results. The mechanism of the NIR-assisted antibacterial activity was that CNT can absorb NIR irradiation and efficiently converted it into localized heat to photothermally lyse the bacteria44. Furthermore, the short irradiation time between 1 min and $10\\mathrm{min}$ according to the wound infection degree will present negligible damage on human body but high-efficiency on antimicrobial infection. These results demonstrated that the CNT-reinforced cryogel possessed excellent NIR photothermal capacity, which greatly enhanced antibacterial activity for both gram-positive bacteria and gramnegative bacteria even when bearing a challenge of $10^{8}\\mathrm{CFU/mL}$ bacteria. \n\nFurthermore, ibuprofen as a widely used non-steroidal antiinflammatory analgesic in wound46–49 was chosen to endow the cryogel hemostatic agents with analgesic effect, and the release behavior of ibuprofen from the cryogels with and without NIR irradiation $(1.4\\dot{\\mathrm{W}}/\\mathrm{cm}^{2})$ ) was studied (Fig. 3d). These release data demonstrated the sustained release behavior of analgesic from CNT-reinforced cyrogel, and analgesic burst release on demand by NIR stimulus (Fig. 3d). Thus the CNT-reinforced cryogel could be used as potential carrier for sustained release and NIRtriggered on demand release of analgesic for relieving wound pain during hemostasis and wound healing applications. \n\nWater- and blood-triggered shape memory of cryogels. Shape memory hemostatic agents can present unique property in hemostasis application due to their capacity to be delivered to the wound site in the shape-fixed state by an injector and recover their shape to the expanded geometry upon contacting with bleeding blood in human body7,9–11. Especially, the volume expansion of the device over short period of time would allow for easy delivery into narrow, penetrating wounds, and subsequent expansion to completely fill abnormal wound boundaries7,9–11. Considering the excellent water-triggered shape memory property of cryogels7,35,50, we evaluated the shape memory property of the as-prepared cryogels qualitatively and quantitatively including the volumetric expansion ratio, shape fixity ratio, recovery ratio, and recovery time. As shown in Fig. 4, the shape-fixed state of the four cryogels could be conveniently achieved by simply compressing and absorbing the water squeezed out from the cryogels (Fig. 4b, c). Then, they immediately recovered to their original state less than 1 s by reabsorbing water (Fig. 4a and Supplementary Movie 7). Similar to the water-triggered shape recovery, QCSG/ CNT0 and QCSG/CNT4 also showed rapid shape recovery after contacting and absorbing blood (Supplementary Movie 8, Supplementary Movie 9 and Supplementary Fig. 9). These results demonstrated the excellent shape memory property and rapid recovery speed of the cryogels. Besides, the quantitatively shape memory results were shown in Supplementary Table 3. All the shape-fixed cryogels could rapidly recover their original shapes $100\\%$ recovery ratio) less than 1 s (Supplementary Movie 7). Furthermore, the shape-fixed QCSG/CNT0 and QCSG/CNT4 (with a free shape diameter of $5\\mathrm{mm}$ ) could be injected using an injector with diameter of about $1.5\\mathrm{mm}$ . After injection, the cryogels still maintained their original shapes and kept stable (Supplementary Fig. 3, Supplementary Movie 3, and Supplementary Movie 4), revealing their great injectability. \n\nThe microtopography recovery of the cryogels at their original shapes, fixed shapes and recovered shapes after fixation were further confirmed in Fig. 4e. The shape memory mechanism of the cryogel was schematically represented in Fig. 4d. The shape memory capability was attributed to the reversible collapse of the pores within the cryogel matrix, in which the macroporous sponge-like structure allowed water flow out/in freely, possessed high polarity to absorb water and good resilience for shape recovery13,14. The processes of compressing caused efflux of water from interconnected pores and collapse of the cryogel structure. After removing the compressive stress and absorbing the water, the stored elastic energy is released and the cryogel presents shape-fixed state. Then, when the shape-fixed cryogel contacts water, the water will be immediately reabsorbed into the cryogel’s matrix to recover the cryogel’s shape and structure. All these above results demonstrated that the cryogels possessed excellent water -triggered shape memory capability, especially for QCSG/ CNT0, QCSG/CNT2, and QCSG/CNT4 simultaneously possessing excellent volumetric expansion ratio, shape fixity ratio, recovery ratio, and recovery time. Thus, QCSG/CNT0, QCSG/ CNT2, and QCSG/CNT4 showed huge potential as cryogel hemostatic agent with rapid blood-triggered shape recovery for hemostasis applications. \n\nHemocompatibility and cytocompatibility of the cryogels. In vitro hemolysis assay is a universal method to evaluate the hemocompatibility of materials51. The hemolysis ratios of the four cryogels’ dispersion liquids with the concentrations varying from 625 to 1250, 2500, and $5000\\upmu\\mathrm{g/mL}$ were tested. The macroscopical color of centrifugally obtained supernatants for all the cryogel groups, negative PBS group and positive Triton $\\mathrm{X-100}$ group was shown in Fig. 5a. All the four cryogel groups presented light yellow similar to PBS control group, while the positive group was bright red. For the quantitative data as shown in Fig. 5b, QCSG/CNT4 showed the lowest hemolysis ratio of $2.3\\%$ when bearing a $5000\\upmu\\mathrm{g/mL}$ dispersion concentration, revealing its best hemocompatibility in the four cryogels due to its balanced CNT concentration. Although the cryogels presented different hemolysis ratios, they showed better hemocompatibility than the reported hemostatic materials52,53. These hemolysis results demonstrated the excellent hemocompatibility of materials as hemostatic agent and wound dressing. \n\nFor the applications of hemostatic agent and wound dressing, the materials should possess good cytocompatibility. Two methods including a leaching pattern and a direct contact test were used to evaluate the cytocompatibility of as-prepared materials43,54. As shown in Fig. 5c, all the four cryogels’ extracts as high as $20\\mathrm{mg/mL}$ had no cytotoxic leaching content. Then, the good cryogel’s cytocompatibility was further demonstrated by a direct contact test as shown in Fig. 5d–e (Supplementary Note 5). Overall, the results from the leaching pattern test demonstrated the non-cytotoxicity of all the extracts of cryogels and the results from direct contact test demonstrated that all the CNT-contained cryogels had excellent cytocompatibility allowing their application as potential trauma hemostatic agents or trauma dressings. \n\n![](images/ff7d3439ac9370e3bd626d0f8e3e6123be7d5efa36c6cdc7efc68175ee73715a.jpg) \nFig. 4 Shape memory properties of the cryogels. a–c Fast resilience and macroscopical shape memory property of the cryogels. Scale bar: 1 cm. d Schematic representation of the shape memory mechanism of the cryogel. e Microtopography of the cryogels in original state, shape-fixed state and shape recovery state after fixing. Scale bar: $400\\upmu\\mathrm{m}$ . All the four cryogels under free shape showed interconnected macroporous structure with similar pore size between $100{-}200\\upmu\\mathrm{m}$ . Compared to their shapes under free situation, all the shape-fixed cryogels presented collapsed and almost closed pores except $\\mathsf{Q C S G}/$ CNT6 still remained unclosed pores with reduced pore size. However, all the four shape-fixed cryogels still kept unbroken network. After absorbing water, all the cryogels’ morphologies were similar to those in original state \n\nIn vitro blood-clotting performance of the cryogels. The bloodclotting capability of the cryogels was evaluated by dynamic whole-blood-clotting test, in which a higher absorbance value of the hemoglobin solution indicates a slower clotting rate4,52–54. Gauze as traditional hemostatic agent and commercial gelatin hemostatic sponge were both used as control groups. Interestingly, the QCSG/CNT0 with rapid blood absorption capability showed lower BCI than that of gauze group for each time point $(P<0.05)$ in Fig. 6a, and QCSG/CNT2 and QCSG/CNT4 showed significantly higher blood-clotting capacity than QCSG/CNT0 in first $60\\:s$ $\\left(P<0.05\\right)$ , and QCSG/CNT6 presented better BCI than QCSG/CNT0 within $30\\mathrm{{s}}$ $(P<0.05)$ . These results demonstrated that QCSG/CNT0 cryogel has effective blood-clotting ability, and introducing CNT further enhanced its blood-clotting ability. \n\nThe hemostatic mechanism of the cryogels was further studied by observing the surface adhesion and morphologies of blood cells and platelets on these cryogels, and gauze and gelatin hemostatic sponge were also used as control groups (Fig. 6b, c, \n\n![](images/07d46b9f7bfa795a5ecd19115c26649577a940ec9bbe5f64ebdd3ec422f44921.jpg) \nFig. 5 Biological properties assays for the cryogels. a Photographs from hemolytic activity assay of the cryogels using PBS as negative control and Triton X-100 as positive control. A: QCSG/CNT0, B: QCSG/CNT2, C: QCSG/CNT4, and D: QCSG/CNT6, and the number after the letter stands for the cryogel dispersion liquid concentration that 1 represents $625{\\upmu\\mathrm{g}}/{\\up m},$ 2 represents $1250\\upmu\\mathrm{g/mL},$ 3 represents $2500\\upmu\\mathrm{g/mL}$ , and 4 represents $5000\\upmu\\mathrm{g/mL}$ , respectively. b Hemolytic percentage of the cryogels’ dispersion liquids at different concentrations. When the cryogel dispersion concentrations were equal to or less than $1250\\upmu\\mathrm{g/mL}$ , all the three CNT-contained cryogels just presented less than $1.8\\%$ hemolysis, which was lower than that of QCSG/CNT0 $3.6\\%$ hemolysis). When increasing the dispersion concentration to as high as $5000{\\upmu\\mathrm{g/mL}},$ , the three CNT-contained cryogels just presented no more than $4.8\\%$ hemolysis. However, the hemolysis ratio of QCSG/CNT0 reached to $7.2\\%$ . c Cytocompatibility evaluation of the cryogels’ extracts for L929 cells. When changing the cryogel extracts’ concentrations from 5 to 10, 15, and $20~{\\mathrm{mg/mL}},$ all the four cryogels presented more than $90\\%$ L929 cell viability compared with TCP control group ( $\\cdot P>0.05\\mathrm{,}$ ). d Cytocompatibility evaluation of the cryogels when contacted with the cryogel disks. e LIVE/DEAD staining of L929 cells after contacted with the cryogels for $24\\mathsf{h}$ . Scale bar: $200\\upmu\\mathrm{m}$ . $^{\\star}P<0.05$ using Student's t-test (two-sided). Error bar indicates s.d. $\\displaystyle{\\dot{\\boldsymbol{n}}}=4 $ ) \n\nSupplementary Note $6)^{52,55}$ . All the four cryogels showed a large number of blood cells adhering to the cryogel surfaces, and the blood cells presented irregularly formed aggregates. For platelet adhesion in Fig. 6c, all the four cryogels showed many platelets adhesion with activated states for their aggregating and changed shape from irregular distinctive disks to circular deformation52. With the introduction of CNT into the cryogel QCSG/CNT0, the CNT-contained cryogels showed increased number of platelet adhesion. All the four cryogels with interconnected porous structure and high expansion ratio, can absorb a large amount of blood with rapid blood absorption speed and blood-concentrating effects and enhanced absorption ability for platelets and blood cells, and all these factors contributed to its excellent in vitro blood-clotting effect. \n\nIn vivo hemostatic performance of the cryogels. The hemostatic properties of the cryogels were further evaluated by the amount of bleeding and hemostatic time both in the mouse liver injury model and mouse-tail amputation model to obtain the optimized QCSG/CNT cryogel (Fig. 7). For the mouse liver injury model (Fig. 7a–c), among the four cryogels, cryogel QCSG/CNT2 and QCSG/CNT4 presented lower blood loss than that of QCSG/ CNT6 $(P<0.05)$ . In addition, the hemostatic time of the blank group (190 s) was the longest among all the groups $(P<0.001)$ ) (Fig. 7b). Gelatin sponge, QCSG/CNT0, QCSG/CNT2, QCSG/ CNT4, and QCSG/CNT6 showed hemostatic time of 73 s, $73{\\mathrm{~s}}_{\\mathrm{{t}}}$ \n\n$83s,82s.$ , and $78~\\mathsf{s}.$ , and the hemostatic times from gelatin sponge and QCSG/CNT0 were significantly shorter than that of gauze group (101 s) $(P<0.05)$ (Fig. 7b). Besides, there was no significant difference among gelatin sponge, QCSG/CNT0, QCSG/CNT2, QCSG/CNT4, and QCSG/CNT6 $(P>0.05)$ . The photographs of the samples after hemostatic applications in Supplementary Fig. 10 were also consistent with the above quantitative data. \n\nFor the mouse-tail amputation model mimicking the bleeding situation of ruptured vein, blank group showed the highest blood loss of $204\\mathrm{mg}$ among all the groups $(P<0.001)$ (Fig. 7d–f). However, when applying hemostatic agents including gauze, gelatin sponge, cryogels QCSG/CNT0, QCSG/CNT2, QCSG/ CNT4, and QCSG/CNT6, all the six groups showed significantly decreased blood loss varying from 28 to 32, 20, 19, 23, and $19\\mathrm{mg}$ , respectively, compared to blank group $(P<0.001)$ (Fig. 7d). Figure 7e showed the hemostatic times in the mouse-tail amputation model. The cryogels QCSG/CNT0, QCSG/CNT2, QCSG/CNT4, and QCSG/CNT6 presented hemostatic time varying from 117 to 107, 91 and $60~\\mathsf{s}.$ respectively. Moreover, QCSG/CNT6 presented the shortest hemostatic time among the four cryogels $\\left(P<0.05\\right)$ . \n\nMilitary is now using Combat Gauze as their gold standard for packing. Thus, the hemostatic capacity of QCSG/CNT0 and QCSG/CNT4 were further evaluated with Combat Gauze as the control group using a standardized circular liver bleeding model (Supplementary Fig. 11). Both cryogel QCSG/CNT0 and cryogel \n\n![](images/2ce13f7b8ff866ecfd40a3d5337ad1f7297774ecc4a90a85590393486d118e5d.jpg) \nFig. 6 In vitro hemostatic capacity evaluation of the cryogels. a In vitro dynamic whole-blood-clotting evaluation of the cryogels and controls. The blank group without any hemostatic agents showed the slowest blood-clotting speed and the highest BCI (blood-clotting index) after 150 s. Compared with blank group, gelatin sponge group showed more than a $14\\%$ decrease in BCI after $150\\mathsf s$ $\\langle P<0.05\\rangle$ , while gauze group showed significantly deceased BCI compared to gelatin sponge at each time point $\\cdot P<0.001,$ . b SEM images of hemocyte adhesion on the cryogels and controls. Scale bar: $300\\upmu\\mathrm{m}$ for $\\times500;$ Scale bar: $100\\upmu\\mathrm{m}$ for $\\times2000;$ Scale bar: $40\\upmu\\mathrm{m}$ for $\\times5000$ . c SEM images of platelet adhesion on the gauze (ci), gelatin hemostatic sponge (cii), $\\mathsf{Q C S G}/$ CNT0 (ciii), QCSG/CNT2 (civ), QCSG/CNT4 (cv), and QCSG/CNT6 (cvi), respectively. Scale bar: $15\\upmu\\mathrm{m}$ . The error bars stand for s.e.m. $\\left(n=3\\right)$ ) \n\nQCSG/CNT4 presented significantly reduced blood loss than Combat Gauze group by employing a standardized circular liver bleeding model $(P<0.01)$ , suggesting better hemostatic capacity of the cryogel hemostatic agents than Combat Gauze. \n\nThe above results demonstrated that all of the four cryogels showed excellent hemostatic capacity, which were much better than gauze and commercial gelatin hemostatic sponge. Moreover, both QCSG/CNT0 and QCSG/CNT4 presented better hemostatic ability than commercial Combat Gauze. The introduction of appropriate amount of CNT also contributed to enhancing the hemostatic ability of QCSG/CNT cryogels, especially for cryogel QCSG/CNT4. During hemostasis process, both blood cell and platelet activation play important roles56–58. Especially, recent study showed that the aggregation of blood cells can change them into a polyhedron shape that can form a perfect seal3,57. Platelet adhesion will activate signaling pathways that lead to thromboxane A2 formation and secretion of platelet granule contents, which substances can cause the formation of fibrinogen receptor from integrin and glycoprotein IIb/IIIa leading to platelet aggregation59. Then, on the surface of activated platelets, coagulation is accelerated and thrombin is generated, which promotes the hemostatic process59. QCSG/CNT cryogels were prepared mainly based on QCSG, which is a chitosan derivative with a large number of positive-charged quaternary ammonium groups. The positive-charged amino groups and quaternary ammonium groups on the cryogel surface would significantly interact with blood cells or platelets via electrostatic interaction to adhere blood cells, platelets, and plasma fibronectin to induce irregular blood cell aggregation, platelet activation, and clot formation3,31–33. On the other hand, chitosan’s natural property can promote thrombin generation by shortening the lag time and increasing the maximal values at the later hemostasis31. Besides, CNT can interact with platelets, thereby triggering platelets activation and the release of platelet membrane microparticles activated by inducing extracellular $\\mathrm{Ca}^{2+}$ influx60,61. Furthermore, the shape-fixed cryogels with almost closed pores can rapid absorb the plasma and concentrate the blood to entrap aggregated hemocytes, which might immediately form blood-clotting on the material surface53. Also, the porous structure and good degree of swelling of the cryogels will improve the adsorption ability for platelets and blood cells to achieve a rapid hemostatic effect52. Thus, a synergistic effect of chitosan’s hemostatic nature, strong electrostatic interaction between positive-charged quaternary ammonium groups and blood components, CNT’s platelet activation, high blood absorption capacity, rapid plasma absorbing, and blood-concentrating effects all contributed to the excellent hemostasis performance of CNT-reinforced shape memory cryogels. \n\nIn vivo hemostasis for lethal noncompressible hemorrhage. Uncontrolled hemorrhage leads to more than $30\\%$ of trauma deaths, which has been a significant concern of military and wounds with irregular shape, which often cause noncompressible hemorrhage, such as wounds incurred by small-caliber firearms and improvised explosive devices in the battlefield6. In this study, strength, rapid blood-triggered shape recovery, high blood uptake capacity, and rapid blood absorption speed for lethal noncompressible hemorrhage hemostasis, which was evaluated by employing a rabbit liver volume defect model (Fig. 7g–i, Supplementary Note 7). When applying gelatin hemostatic sponge D1 (with a diameter similar to shape-fixed cryogels groups (with diameters of $4\\mathrm{mm}\\dot{}$ ) but slightly smaller than wound’s diameter $(5\\mathrm{mm})$ ) into the liver defect hole, the bleeding was significantly reduced, which presented a blood loss of $7.1\\mathrm{g}$ $\\mathit{\\Omega}^{\\prime}P{<}0.001)$ . The hemostatic time was also reduced to $8.6\\mathrm{min}$ when compared to blank group $(P<0.001)$ ). Furthermore, when increasing the gelatin hemostatic sponge’s diameter to $6\\mathrm{mm}$ , compared with gelatin hemostatic sponge D1, blood loss for gelatin hemostatic sponge D2 was continuously reduced to $2.6\\:\\mathrm{g}$ $(P<0.05)$ . The hemostatic time was also reduced to $3.9\\mathrm{{min}}$ when compared to gelatin hemostatic sponge D1 $(P<0.05)$ . Interestingly, when injecting QCSG/CNT0 cryogel into the liver defect hole, it presented less blood loss of $0.8\\mathrm{g}$ than both the two gelatin sponges $(P<0.05)$ and blank group $(P<0.001)$ . Moreover, cryogel QCSG/ CNT4 showed continually reduced blood loss of $0.2{\\mathrm{g}},$ which was also significantly less than blank group $(P<0.001)$ and the two gelatin sponges $(P<0.05)$ . Furthermore, all the rabbits in the four hemostatic agent groups were alive after a week observation and there was no significant difference in hemostatic time for the gelatin hemostatic sponge D2, QCSG/CNT0 and QCSG/CNT4 $\\bar{(}P>0.05)$ . However, gelatin hemostatic sponge D1 showed significantly longer hemostatic time than the other three hemostatic agents $(P<0.05)$ . The photographs in Supplementary Fig. 12 were also consistent with the above quantitative data. Compared to gelatin hemostatic sponge without shape memory property (Supplementary Note 8), the shape memory cryogel could be injected into the narrow, deep and irregular wound in a shapefixed state (Fig. 7j, Supplementary Movie 1 and Supplementary Movie 2), and they would then immediately absorb the blood, concentrate the blood, and instantly recover their initial volume to fill the irregular wound site and keep robust mechanical strength. These properties of the cryogels not only accelerated the blood-clotting speed but also severed as effective physical barriers to stop the bleeding. Especially, CNT-reinforced QCSG/CNT4 had better mechanical property to provide a stronger physical barrier, and the hemostatic ability of CNT further enhanced the blood-clotting ability of the CNT-contained cryogel, thus promoting the liver volume defect hemostasis, indicating that QCSG/ CNT4 had great potential for lethal noncompressible hemorrhage application. For clinic application, the cryogels can be fabricated into different shapes to meet the practical applications (Supplementary Note 9). Furthermore, X-ray device can be used to further confirm the complete removal of the CNT-contained cryogel after in vivo application (Supplementary Fig. 13). \n\n![](images/b0db8110b32db9c10ec0ace4cbc466edc34870c432ef40a8e5f9aed6c8903bee.jpg) \n\nIn vivo wound healing performance of the cryogels. Skin composed of dermis, epidermis, and corneum, is one of the electrical signal sensitive tissues and presents conductivity values from $2.6\\mathrm{mS}/\\mathrm{cm}$ to $1\\times10^{-4}\\mathrm{mS/cm}$ varying different skin components, and studies had demonstrated that the conductive dressings were beneficial to wound healing processes43,65,66. Thus, the wound healing performance of the conductive cryogels was investigated by in vivo test using a full-thickness skin defect model (Supplementary Note 10). As shown in Fig. $8\\mathrm{a-b}$ , after treated for five days, QCSG/CNT4 group showed smaller wound area than Tegaderm™ dressing and QCSG/CNT0 $\\left(\\mathrm{P}<0.05\\right)$ . However, there was no significant difference between QCSG/ CNT0 and Tegaderm™ dressing $(P>0.05)$ . When treated for 10 days, both QCSG/CNT4 and QCSG/CNT0 showed significantly enhanced wound contraction ratio than Tegaderm™ dressing $(P<0.05)$ , and there was no significant difference between the two cryogels $(P>0.05)$ . Besides, some of mice in the two cryogel groups showed $100\\%$ wound contraction while there were few mice showing $100\\%$ wound contraction in Tegaderm™ dressing group. At 15th day, all the mice in the three groups presented $100\\%$ wound contraction. \n\nThe histomorphological evaluation was performed to analyze inflammation and vascularization. Low level inflammation in early stage of wound healing process is a promotive factor for wound healing process but severe inflammatory response impairs the tissue in wound sites with inflammatory cells, oxidation, and fibrotic repair. In general, various degree of inflammation infiltration was observed in three different groups. Excessive amounts of inflammatory cells were recruited in wound sites in Tegaderm™ dressing group than the two cryogel groups (Fig. 8c), especially at 5th day. Inflammation was improved along with healing process, and the inflammatory cells were less in three groups at 10th day. Wound in QCSG/CNT4 groups exhibited the least inflammatory infiltration among three groups at 10th day. All wound sites were fully closed at 15th day, and inflammation was not remarkable in three groups. \n\nIt is known that vascularization plays an important role in wound healing process. The blood stream promotes fibroblast recruitment to the wound sites and helps to maintain low level of inflammation for anti-bacteria by bringing the macrophages and other monocytes. In addition, vascularization also brings different growth factors into the wound accelerating the healing process. The vascularization in both QCSG/CNT0 and QCSG/CNT4 groups were higher than the Tegaderm™ film group at 5th day (Fig. 8c). More blood vessels were seen in the two cryogel groups than that in Tegaderm™ film group. The vascularization was lessened in following days in all groups. It is concluded that the cryogel groups had a promotive effect on vascularization in the acute stage of wound healing, which helped the wound to heal. \n\nThe integrity of epithelium in wound site varied in each group. The enhanced wound healing performance of conductive QCSG/ CNT4 dressing than CNT-free QCSG/CNT0 dressing might be attributed to the transfer of electro-signals from conductive cryogel dressing to the wound site, activation of cellular activity and positive effect of CNT on the level of growth factors involved in wound healing process43. Based on the above results and discussions, it revealed that both the two cryogels could accelerate wound healing process by promoting vascularization, and QCSG/ CNT4 could further enhance the wound healing by balancing the inflammatory infiltration probably attributed to CNT’s effect, suggesting their huge potential as wound dressings. \n\n![](images/92793e6e7a142f62b73f66672e1fce65d469e9230455da7a19fb503c1ff10816.jpg) \nFig. 8 In vivo wound healing performance of the cryogels. a Wound contraction for TegadermTM film, QCSG/CNT0 and QCSG/CNT4. b Photographs of wounds at 5th, 10th, and 15th day for TegadermTM film, QCSG/CNT0 and QCSG/CNT4. Scale bar: 5 mm. c Histomorphological evaluation of wound regeneration for TegadermTM film, QCSG/CNT0 and QCSG/CNT4 at 5th, 10th, and 15th day. Smooth and complete epithelium layer was presented in two cryogel groups at 10th day, differing from the wound sites in Tegaderm™ group whose epithelium layer was still incomplete and rough. The wounds in QCSG/CNT4 group had a better formation of hair follicles. All wounds were completely healed and characterized with perfect epithelization at $15^{\\mathrm{th}}$ day. $^{\\star}P<0.05$ using Student's t-test (two-sided). Scale bar: $5\\mathsf{m m}$ . Error bar indicates s.e.m. $h=5$ ) \n\nIn vivo host response of the cryogels. In vivo host response of the cryogels showed a mild inflammatory responses from H&E staining and toluidine blue staining after implantation for 7 and 30 days (Supplementary Fig. 14 and Supplementary Note 11), indicating that these cryogels could be used as biocompatible temporary cryogel hemostatic agents for in vivo application. \n\n# Discussion \n\nWe developed a series of CNT-reinforced antibacterial and conductive nanocomposite cryogels as injectable shape memory hemostatic dressings, and demonstrated that they not only promoted the wound healing process in a full-thickness skin defect model but also presented excellent hemostatic effects in mouse liver injury model, mouse-tail amputation model, rabbit liver defect lethal noncompressible hemorrhage model, and a standardized circular liver bleeding model. The cryogels exhibited better hemostatic effect than gauze and gelatin hemostatic sponge in mouse liver injury model and mouse-tail amputation model, and better hemostatic effect than Combat Gauze in a standardized circular liver bleeding model for their good blood-clotting ability, higher blood cell and platelet adhesion and activation. Furthermore, the cryogel QCSG/CNT4 showed better hemostatic capability than QCSG/CNT0 for its optimized properties, and better in vivo wound healing performance than Tegaderm™ film and QCSG/CNT0 for the introduction of CNT. More importantly, QCSG/CNT4 also presented better hemostatic performance than gelatin hemostatic sponge and QCSG/CNT0 in rabbit liver defect lethal noncompressible hemorrhage model. All these results demonstrated that the CNT-reinforced nanocomposite cryogel hemostatic dressings with multiple functions are excellent candidates as hemostatic dressings for lethal noncompressible hemorrhage and wound dressing applications. \n\n# Methods \n\nSynthesis of GMA functionalized quaternized chitosan. The QCSG was synthesized via one-pot reaction between epoxy groups from glycidyltrimethylammonium chloride (GTMAC) and GMA and amino groups from chitosan. $_{1\\mathrm{g}}$ of chitosan (J&K Chemical, $M_{\\mathrm{n}}{}=100,000{}-300,000{}\\mathrm{Da}{})$ was suspended in $36~\\mathrm{mL}$ of deionized water, and then $180\\upmu\\mathrm{L}$ of glacial acetic acid (SigmaAldrich) was added to the suspension. After stirring at $55^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ , different molar ratios of GTMAC (Sigma-Aldrich) were added dropwise to the chitosanglacial acetic acid mixture under continuous stirring, respectively. The molar ratios of GTMAC to amino groups on chitosan backbone were varying from 1:1 to 2:1 and 3:1, respectively (Supplementary Table 1). The reaction mixtures were stirred at $55^{\\circ}\\mathrm{C}$ for $15\\mathrm{h}$ . Then, GMA (Sigma-Aldrich) was added dropwise to the above reaction mixtures with continuous stirring at $55^{\\circ}\\mathrm{C}.$ , respectively. The ratio of GMA to amino groups on the pure chitosan backbone was fixed at 0.5:1.0, and the reaction was performed for another $15\\mathrm{h}$ at $55^{\\circ}\\mathrm{C}$ in the dark condition (Supplementary Table 1). After the reaction, the undissolved polymer was removed by centrifuging the mixture at $5692\\times g$ for $20\\mathrm{min}$ at room temperature. The supernatant liquid was precipitated into pre-cooled acetone to obtain the crude product. For purifying the product, the crude product was dissolved in DI water, and then dialyzed exhaustively (MWCO 3500) against deionized water for three days in the dark condition. The pure product was obtained by lyophilization. The quaternary amination degrees of the three QCSG copolymers were determined by titrating the content of chlorine ion27. The chemical structure of QCSG was confirmed by $^1\\mathrm{H}$ NMR (Supplementary Fig. 15) and FT-IR (Supplementary Fig. 2) spectra. The parameters of the synthesized QCSG copolymers were listed in Supplementary Table 1. The chemical structure of QCSG was confirmed by $^1\\mathrm{H}$ NMR (Supplementary Fig. 15) and FT-IR (Supplementary Fig. 2) spectra. The parameters of the synthesized QCSG copolymers were listed in Supplementary Table 1. \n\nSynthesis of diacrylate functionalized PF127 (PF127-DA). The PF127-DA was prepared by acrylation of PF127 (poly(ethylene glycol)- $\\cdot b$ -poly(propylene glycol)- $\\cdot b$ - poly(ethylene glycol)) using acryloyl chloride according to reference13. A volume of $2.54\\mathrm{g}$ ( $0.2\\mathrm{mmol};$ ) of PF127 (Sigma-Aldrich) and $_{0.061\\mathrm{g}}$ of triethylamine (J&K Chemical) $0.6\\mathrm{mmol};$ were dissolved in $20~\\mathrm{mL}$ anhydrous dichloromethane in an ice bath and then degassed by pouring nitrogen for $20\\mathrm{min}$ . After that, $0.05\\mathrm{mL}$ of acryloyl chloride $\\left\\langle0.6\\mathrm{mmol}\\right\\rangle$ ) was slowly injected into the above solution under nitrogen environment. The reaction was performed at room temperature for $24\\mathrm{h}$ . Following the reaction, the solvent was removed by rotational evaporation, and the crude product was dissolved in DI water, and dialyzed exhaustively (MWCO 3500) against deionized water for three days. The pure product was obtained by lyophilization. The chemical structure of PF127-DA was confirmed by $^1\\mathrm{H}$ NMR (Supplementary Fig. 16) and FT-IR (Supplementary Fig. 17) spectra. \n\nPreparation of QCSG/CNT cryogels. The cryogels were prepared by cryopolymerization of QCSG aqueous solution and PF127-DA/CNT aqueous dispersion at $-20^{\\circ}\\mathrm{C}$ using APS/TEMED as redox initiator system. Firstly, the multi-walled CNTs (Nanjing XFNANO Materials Tech Co., the diameter, length, conductivity and special surface area of the CNT are $10{-}20~\\mathrm{nm}$ , $10{-}30~{\\upmu\\mathrm{m}}$ , $\\geq100\\mathrm{{S}}/\\mathrm{{cm}}$ , and ${\\geq}200\\mathbf{\\dot{m}}^{2}/\\mathbf{g}.$ respectively) dispersion was prepared13. Briefly, equal weights of CNT and PF127-DA were added into $\\mathrm{8\\mL}$ of deionized water. Then, the mixture was sonicated in ice bath for $^{4\\mathrm{h}}$ , and another $^{\\textrm{1h}}$ before use. QCSG was dissolved in DI water to form a $5\\mathrm{wt\\%}$ of QCSG solution. A volume of $10\\mathrm{mL}$ of QCSG solution was added into the above CNT dispersion solutions or $\\mathrm{8~mL}$ of deionized water, respectively, and then sufficiently mixed. Following that, $1\\mathrm{mL}$ of APS (SigmaAldrich) solution $\\mathrm{(100mg/mL)}$ ) and $1\\mathrm{mL}$ of TEMED (Sigma-Aldrich) solution (20 $\\upmu\\mathrm{L}/\\mathrm{mL})$ ) were added into QCSG and QCSG/CNT mixtures (pre-cooled in ice bath), and mixed sequentially in an ice bath. After that, the cryogel precursor was transferred into cylindrical mold (with a diameter of $10\\mathrm{mm}$ ) and placed in a freezer at $-20^{\\circ}\\mathrm{C}$ . The polymerization was allowed to proceed for $18\\mathrm{h}$ , and the resulting cryogels were thawed. The obtained QCSG/CNT cryogels were purified by immersed in DI water for seven days to remove the unreacted polymer and free CNT, and the purified QCSG/CNT cryogels showed no CNT leakage $(<0.1\\%$ CNT) when further immersed in DI water. Four cryogels with a constant $2.5\\mathrm{wt\\%}$ QCSG concentration and the CNT concentrations varying from 0 to 2, 4, and $6\\mathrm{mg/mL}$ were prepared in this study as shown in Supplementary Table 2. \n\n1H NMR spectrum test. The spectra of QCSG and PF127-DA were performed using a Bruker Ascend 400 MHz NMR instrument with deuteroxide and chloroform-d serving as the solvents and internal standards. \n\nFTIR spectrum test. The spectra of QCSG, PF127, PF127-DA, dried cryogel QCSG/CNT0, and dried cryogel QCSG/CNT2 were recorded in the range of $4000{-}650\\thinspace\\mathrm{cm}^{-1}$ by employing a Nicolet 6700 FT-IR spectrometer (Thermo Scientific Instrument). \n\nUV-vis spectrum test. The spectra of the supernatants of CNT aqueous dispersion, PF127-DA/CNT aqueous dispersion and PF127-DA/CNT/QCSG aqueous dispersion after placed at room temperature for $24\\mathrm{h}$ were recorded using a spectrophotometer (Lambda 35, PerkinElmer). The CNT aqueous dispersion and PF127-DA/CNT aqueous dispersion were prepared by sonicating CNT/DI water mixture and PF127/CNT/DI water mixture in ice bath for $^{4\\mathrm{h}}$ respectively. PF127- DA/CNT/QCSG aqueous dispersion was prepared by fine mixing PF127-DA/CNT aqueous dispersion and QCSG solution. The three aqueous dispersions had the same CNT concentration of $2\\mathrm{mg/mL}$ , while QCSG was $12.5\\mathrm{mg/mL}$ . \n\nScanning electron microscope (SEM) morphology observation. The morphologies of the freeze-dried cryogels (including shape-free state, shape-fixed state, and recovered shape from shape-fixed state) were observed using a field emission scanning electron microscope (FEI Quanta FEG 250). Before observation, the surface of the cryogels was sprayed with a gold layer. \n\nSwelling ratio test. The cryogels equilibrated in DI water at room temperature were firstly weighted $(W_{\\mathrm{E}})$ . Then, they were lyophilized and weighted again $(W_{\\mathrm{O}})$ . The swelling ratio (SR) was calculated as: \n\n$$\n\\mathrm{SR}=(W_{\\mathrm{E}}-W_{\\mathrm{O}})/W_{\\mathrm{O}}\\times100\\%\n$$ \n\nCryogel conductivity and impedance curve. The resistance of the cryogels under both swollen state and lyophilized state was measured by an Agilent B2900A digital 4-probe tester with a current of $1\\mathrm{mA}$ and a linear probe head ( $\\mathrm{1.0\\mm}$ space). All the cryogels were washed with DI water to remove the initiator and unreacted polymer. The conductivity of the cryogels can be calculated using the equation: \n\n$$\n\\sigma=1/\\rho\n$$ \n\nwhere $\\rho$ was resistance and $\\sigma$ was conductivity. Each sample was measured under small compressive strain, and the average results of three values measured under positive current and three data obtained under negative current were taken. Furthermore, the impedance curves of dried cryogel QCSG/CNT4 and dried cryogel QCSG/CNT0 were performed by using electrochemical workstation (CHI660E electrochemical analyzer) with the frequency from $10^{2}$ to ${10^{6}}\\mathrm{Hz}$ . \n\nX-ray detectability of cryogel. The X-ray detectable nanocomposite cryogel hemostatic was prepared by gluing a X-ray detectable line to the cryogel surface. Then, the Micro-CT analysis was performed on a 3D microfocus X-ray microcomputed tomography system (Y.CHEETAH\\*, YXLON) to confirm the X-ray detectability of the X-ray detectable line contained nanocomposite cryogel hemostatic. The nanocomposite cryogel without X-ray detectable line was used as a control. \n\nInjectability of the cryogel. The cryogels were prepared with a free shape diameter of $5\\mathrm{mm}$ . Then, the shape of the cryogels was fixed by removing the free water within the cryogels’ matrix. After that, the shape-fixed cryogels were loaded into an injector (with a blunt nozzle inner diameter of $1.5\\mathrm{mm}$ ), and the cryogels were injected into the water to recover their shapes. The injection processes were videotaped and photographed. \n\nRheological properties of the cryogel. The rheological test was performed by employing a TA rheometer (DHR-2) using two different methods. The cryogels were cut into disk shapes with diameters of $12\\mathrm{mm}$ . The oscillation-frequency experiments were conducted under a constant strain of $1\\%$ and varying the shear rate from $0.1\\mathrm{rad}/s$ to $100\\mathrm{rad}/s$ at $25^{\\circ}\\mathrm{C}$ . The strain amplitude sweep tests $(\\gamma=$ $0.01\\%100\\%)$ of the cryogels (with diameters of $12\\mathrm{mm}$ ) were also performed using constant frequency of $10\\mathrm{rad}/s$ at $25^{\\circ}\\mathrm{C}$ \n\nMinimum inhibitory concentration assay of copolymers. The copolymers’ MICs for both E. coli (ATCC 8739) and S. aureus (ATCC 29213) were evaluated according to our previous report27. Briefly, the copolymers were dissolved in deionized water and then diluted with MH broth using a twofold dilution method. $100\\upmu\\mathrm{L}$ of bacterial suspension $(10^{4}–10^{5}\\mathrm{CFUmL^{-1}},$ was added to the 96-well plate with a series $100\\upmu\\mathrm{L}$ of twofold dilution copolymers MH broth solutions and then homogeneously mixed by pipetting. After that, the 96-well clear plate (Costar) was placed in an incubator at $37^{\\circ}\\mathrm{C}$ for $^{18\\mathrm{h}}$ . MH broth without inoculum was used as the negative control, while MH broth with inoculum served as positive control. At the end of the time, the absorbance of the solutions in the 96-well plate was read using a microplate reader (Molecular Devices) at $600\\mathrm{nm}$ . The copolymers’ MICs were defined as the minimum concentrations, which inhibited over $90\\%$ of bacteria growth. \n\nMechanical properties of the cryogels. The mechanical properties of the cryogels were evaluated by compression test and cyclic compression test employing a TA rheometer (DHR-2) at room temperature. The cryogel sample was prepared as cylindrical shape with a height of $10\\mathrm{mm}$ and diameter of $8\\mathrm{mm}$ . The maximal compression strain of $93\\%$ was chosen to perform the compression-strain test with a strain speed of $100\\upmu\\mathrm{m}/s$ . For the cyclic compression test, a drop of water was added around the cryogel sample on the platform before the test, and a $40\\%$ , $60\\%$ , and $80\\%$ compression strain were also applied to perform the cyclic compression test. The compression strain was firstly performed up to the preset strain and then released to $0\\%$ strain with constant compression and release strain rate of $100\\upmu\\mathrm{m}/s$ , which were cycled for 10 times. Besides, a cyclic compression test was performed on cryogel QCSG/CNT0 and cryogel QCSG/CNT4 for 100 cycles with the compression strain up to $80\\%$ at a strain speed of $100\\upmu\\mathrm{m}/\\upnu$ , and then the tested QCSG/CNT4 was further immersed in DI water at $37^{\\circ}\\mathrm{C}$ with a $100\\mathrm{rpm}$ shaking speed for another $24\\mathrm{h}$ . The diffused CNT was determined by UV-vis13. \n\nWhen injecting or implanting the cryogel in bleeding site or wound, the cryogel would bear continuous and dynamic force loading. In order to evaluate the CNT stability of the cryogel when bearing continuous and dynamic compression, we performed two tests to simulate the in vivo application situations. First, we soaked cryogel QCSG/CNT4 (with a height of $10\\mathrm{mm}$ and diameter of $8\\mathrm{mm}$ ) in 3 mL DI water and then performed a dynamic compression test with the compression strain up to $50\\%$ at a strain speed of $50\\upmu\\mathrm{m}/\\mathrm{s}$ for $^{6\\mathrm{h}}$ . After the test, the released CNT in the DI water was determined by UV-vis13. Furthermore, the tested cryogel QCSG/CNT4 was also immersed in $3\\mathrm{mL}$ DI water at $37^{\\circ}\\mathrm{C}$ with a $100\\mathrm{rpm}$ shaking speed for another $24\\mathrm{h}$ , and then the released CNT was also determined by the UV-vis. \n\nShape memory behavior of the cryogels. The shape memory property of the cryogels was evaluated according to reference13. The as-prepared cryogel (with initial length of $10\\mathrm{mm}\\left(L_{1}\\right))$ was compressed to $80\\%$ strain at a strain rate of 100 $\\upmu\\mathrm{m}/s$ and then hold at this strain for $1\\mathrm{min}$ . Then the water squeezed out from the cryogel was absorbed away using paper completely and the compressed gauge length was set as $L_{2}$ . After that, the sample was free of any load for $5\\mathrm{{min}}$ , a fixed gauge length was measured as $L_{3}$ . Then the sample was soaked in water for rehydration for $1\\mathrm{min}$ , and the recovery gauge length was measured as $L_{4}$ The test was performed employing a TA rheometer. The $L_{2}$ was measured by instrument automatically, while $L_{1},L_{3},$ and $L_{4}$ were measured manually by fine using rheometer’s software to adjust gap distance. The test was cycled for five times. The shape memory fixity ratio and recovery ratio were calculated according to following equations: \n\n$$\n{\\mathrm{Maximum~compressive~strain:}}\\varepsilon_{\\mathrm{{m}}}=(L_{1}-L_{2})/L_{1}\\times100\\%\n$$ \n\n$$\n{\\mathrm{Fixed~strain}}:{\\varepsilon}_{\\mathrm{u}}=(L_{1}-L_{3})/L_{1}\\times100\\%\n$$ \n\n$$\n{\\mathrm{Recovery~strain:}}\\varepsilon_{\\mathrm{p}}=(L_{4}-L_{3})/L_{1}\\times100\\%\n$$ \n\n$$\n{}\\mathrm{Strainfixity~ratio:}R_{\\mathrm{f}}=\\varepsilon_{\\mathrm{u}}/\\varepsilon_{\\mathrm{m}}\\times100\\%\n$$ \n\n$$\n=\\varepsilon_{\\mathrm{p}}/\\varepsilon_{\\mathrm{u}}\\times100\\%\\ =\\ (L_{4}-L_{3})/(L_{1}-L_{3})\\times100\\%.\n$$ \n\nVolumetric expansion ratios of the cryogels. Before fixing the cryogel shape, the shape-free diameter $(D_{1})$ and length $\\left(L_{1}\\right)$ of columniform cryogel were tested. After that, the free water in the columniform cryogel was squeezed out to obtain the shape-fixed cryogel. And then the diameter $(D_{2})$ and length $(L_{2})$ of the shape-fixed cryogel was further determined. The volumetric expansion ratio was calculated using the following equation: \n\n$$\n{\\mathrm{Volumetric~expansion~ratio}}={\\frac{\\left({\\frac{D1}{2}}\\right)^{2}\\times L1}{\\left({\\frac{D2}{2}}\\right)^{2}\\times L2}}\n$$ \n\nHemolytic activity assay of the cryogels. For hemolytic activity assay, the erythrocytes were obtained by centrifuging (at $116\\times g)$ the mouse blood for $10\\mathrm{min}$ . DPBS was used to wash the obtained erythrocytes for three times, and then the purified erythrocytes was further diluted to a final concentration of $5\\%$ $\\left(\\mathbf{v}/\\mathbf{v}\\right)$ . After that, the dried cryogel was smashed into homogenate by employing a tissue grinder, and four cryogel dispersion liquids (with the concentrations varying from 5 to 2.5, 1.25, and $0.625\\mathrm{mg/mL}$ were prepared. $0.5\\mathrm{mL}$ of the cryogel dispersion liquid and $500\\upmu\\mathrm{L}$ of erythrocyte suspension $(5\\%~(\\mathrm{v/v}))$ were added into a $2{\\cdot}\\mathrm{mL}$ tube, and then they were gently mixed by pipetting. After placed at $37^{\\circ}\\mathrm{C}$ for 1 h, all the samples were centrifuged at $116\\times g$ for $10\\mathrm{min}$ . A volume of $500\\upmu\\mathrm{L}$ of the supernatants was carefully transferred into new tubes, respectively, and then the supernatants were further centrifuged at $11617\\times g$ for $10\\mathrm{min}$ allowing exhaustively to remove the cryogel particles. The obtained supernatants were transferred into a new 96-well clear plate. The absorbance of the solutions at $540\\mathrm{nm}$ was read using a microplate reader (Molecular Devices). $0.1\\%$ Triton X-100 served as the positive control and DPBS served as the negative control. The hemolysis percentage of the cryogels was calculated using the equation: \n\n$$\n\\mathrm{emolysis~(\\%){=}[(A p-A b)/(A t-A b)]\\times100\\%}\n$$ \n\nwhere Ap was the absorbance value of supernatant from the cryogel groups, At was the absorbance value of the Triton X-100 positive control and Ab was the absorbance value of DPBS. Each group contains three repeats. \n\nCytotoxicity test of the cryogels. The cytotoxicity of the cryogels on L929 (ATCC CCL-1, the L929 cell was purchased from the Shanghai Cell Bank of the Chinese Academy of Sciences) cell was evaluated using two methods including a leaching pattern and a direct contact test between cryogel and cells. The cryogel was cut into disks with $8\\mathrm{mm}$ diameter and $5\\mathrm{mm}$ thickness and sterilized by immersing in $75\\%$ alcohol. The dulbecco’s modified eagle medium (DMEM) (Gibco) supplemented with $10\\%$ fetal bovine serum (Gibco), $1.0\\times10^{5}\\mathrm{U/L}$ penicillin (Hyclone) and 100 $\\mathrm{mg/L}$ streptomycin (Hyclone) was used as the complete growth medium. L929 cells were seeded in 48-well plate at a density of 25,000 cells/well. After cultured for $24\\mathrm{h}$ , the cryogel disks equilibrated in the complete growth medium were introduced into the wells and the culture medium level was slightly lower than the cryogel upper surface by removing the excess medium to allow the fine contact between cell and cryogel. The cell viability under the cryogel was evaluated by alamarBlue® assay and LIVE/DEAD® Viability/Cytotoxicity Kit assay after cultured for $24\\mathrm{h}$ . The cryogel disks and medium were removed and $20\\upmu\\mathrm{L}$ of alamarBlue® reagent in $200\\upmu\\mathrm{L}$ complete growth medium was then added into each well. The plate was incubated for $^{4\\mathrm{h}}$ in a humidified incubator containing $5\\%$ $\\mathrm{CO}_{2}$ at $37^{\\circ}\\mathrm{C}$ . After that, $100\\upmu\\mathrm{L}$ of the medium in each well was transferred into a 96-well black plate (Costar). Fluorescence was read using $560\\mathrm{nm}$ as the excitation wavelength and $600\\mathrm{nm}$ as the emission wavelength using a microplate reader (Molecular Devices) according to the manufacturer’s instructions. Cells seeded on TCP without cryogel disc served as the positive control group. The tests were repeated four times for each group. Cell adhesion and viability were observed under an inverted fluorescence microscope (IX53, Olympus). The cell viability was evaluated by alamarBlue® assay after cultured for $24\\mathrm{h}$ . \n\nFor the leaching pattern assay, the sterilized cryogel extract solutions with the cryogel weights varying from 20 to 15, 10, and $5\\mathrm{mg/mL}$ in the culture medium were prepared by immersing the dried cryogels in medium for $24\\mathrm{h}$ at $37^{\\circ}\\mathrm{C}$ with a shaking speed of $100\\mathrm{rpm}$ . L929 cells were seeded in 96-well plate at a density of 10000 cells/well, and pre-cultured for $24\\mathrm{h}$ before replacing the culture medium with the fresh medium containing a series of different concentrations of cryogel extract solutions. After cultured for $24\\mathrm{h}$ , the cell viability was evaluated by alamarBlue® assay. The medium was removed and $10\\upmu\\mathrm{L}$ of alamarBlue® reagent in $100\\upmu\\mathrm{L}$ complete growth medium was then added into each well. The plate was incubated for $^{4\\mathrm{h}}$ in a humidified incubator containing $5\\%\\mathrm{CO}_{2}$ at $37^{\\circ}\\mathrm{C}$ . After that, $100\\upmu\\mathrm{L}$ of the medium in each well was transferred into a 96-well black plate (Costar). Fluorescence was read using $560\\mathrm{nm}$ as the excitation wavelength and $600\\mathrm{nm}$ as the emission wavelength using a microplate reader (Molecular Devices) according to the manufacturer’s instructions. Cells seeded on TCP without extract solution served as the positive control group. The tests were repeated four times for each group. \n\nWhole-blood clotting of the cryogels. The whole-blood clotting of the cryogels were tested according to the literature4,54. The cryogel was cut into cylindrical cryogel with a height of $5\\mathrm{mm}$ and a diameter of $8\\mathrm{mm}$ , and then the cylindrical cryogels were formed into shape-fixed situation. A volume of $50\\upmu\\mathrm{L}$ of recalcified whole-blood solution (0.2 M $\\mathrm{CaCl}_{2}$ , $10\\mathrm{mM}$ in the blood) was added onto the prewarmed cryogels $(37^{\\circ}\\mathrm{C})$ in polypropylene tubes, respectively. Then, the tube was incubated at $37^{\\circ}\\mathrm{C}$ for 30 s, 60 s, 90 s, 120 s, and $150s.$ respectively. The gauze and gelatin hemostatic sponge were used as control groups. After the pre-set period, 10 mL of DI water was gently added to release unbound blood without disturbing the clot. The absorbance of the supernatant was recorded at $540\\mathrm{nm}$ by using a \n\nmicroplate reader (Molecular Devices). Three to five replicates were performed. \n\nThe absorbance of $50\\upmu\\mathrm{L}$ of recalcified whole-blood in $10\\mathrm{mL}$ DI water was used as the reference value (negative control). The blood-clotting index (BCI) was calculated using equation: \n\n$$\n\\mathrm{BCI}~(\\%){=}[(I_{\\mathrm{s}}{-}I_{\\mathrm{o}})/(I_{\\mathrm{r}}{-}I_{\\mathrm{o}})]{\\times}100\\%\n$$ \n\nwhere $I_{\\mathrm{s}}$ represented the absorbance of sample and $I_{\\mathrm{r}}$ represented the absorbance of the reference value. \n\nBlood cell and platelet adhesion on the cryogels. The blood cell and platelet adhesion assay was performed according to reference52. The cryogel sample was cut into disks with a height of $5\\mathrm{mm}$ and a diameter of $8\\mathrm{mm}$ , which were further immersed into DPBS for $^{\\textrm{1h}}$ at $37^{\\circ}\\mathrm{C}$ . After that, the ACD-whole-blood was dropwise introduced onto the cryogel disks and then placed at $37^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ . Platelet-rich plasma (PRP) was obtained by centrifuging the ACD-whole-blood at $116\\times g$ for $10\\mathrm{min}$ . Then, PRP was dropwise introduced onto the cryogel disks and further placed at $37^{\\circ}\\mathrm{C}$ for $^{\\textrm{\\scriptsize1h}}$ . At the end of the time, all the test samples were washed by DPBS for three times to remove the physically adhered blood cell and platelet. Then the samples were fixed using a $2.5\\%$ glutaraldehyde for another $^{2\\mathrm{h}}$ . \n\nAfter that, blood cells and platelets in the samples were gradually dehydrated using $50\\%$ , $60\\%$ , $70\\%$ , $80\\%$ , $90\\%$ , and $100\\%$ ethanol solution with time interval of $10\\mathrm{min}$ . The dried samples were observed using SEM. \n\nPhotothermal effect of the cryogels. In order to elucidate the cryogels’ photothermal effect, the as-prepared cryogel was cut into disks (a diameter of $8\\mathrm{mm}$ and a height of $5\\mathrm{mm}$ ) and then exposed to an NIR laser (MDL-III-808nm-1000mW, Changchun New Industries Optoelectronics Tech Co., Ltd.) at a power density of $1.4\\mathrm{W}/\\mathrm{cm}^{2}$ for $20\\mathrm{min}$ . The heat maps and temperature profiles of the cryogels were recorded using an infrared (IR) thermal camera. Besides, the heat maps and temperature profiles of the QCSG/CNT4 were recorded at power density varying from 0.6 to 0.9, 1.1, and $1.4\\mathrm{W}/\\mathrm{cm}^{2}$ , respectively. \n\nNIR-stimulus responsive release behavior of ibuprofen. In order to encapsulate ibuprofen into the QCSG/CNT0 and QCSG/CNT4, $2~\\mathrm{mg}$ of ibuprofen was added into $0.4~\\mathrm{mL}$ DPBS or $0.4~\\mathrm{mL}$ DPBS containing $4~\\mathrm{mg}$ of CNT and $4~\\mathrm{mg}$ of PF127- DA, respectively. Then, the mixture was sonicated in ice bath for 4 h. $0.5~\\mathrm{mL}$ of 5 ${\\bf w t\\%}$ of QCSG solution was added into the above $0.4~\\mathrm{mL}$ of PF127-DA/CNT/ ibuprofen DPBS dispersion or $0.4~\\mathrm{mL}$ of ibuprofen DPBS dispersion, respectively, and then sufficiently mixed. After that, $50~\\upmu\\mathrm{L}$ of ammonium persulfate (APS) (100 $\\mathrm{mg/mL}$ and $50~\\upmu\\mathrm{L}$ of tetramethylethylenediamine (TEMED) $(20~\\upmu\\mathrm{L}/\\mathrm{mL})$ were added into the QCSG or QCSG/CNT mixtures (pre-cooled in ice bath) and mixed sequentially in an ice bath. Then the cryogel precursor was transferred into cylindrical mold (with a diameter of $10~\\mathrm{mm}$ ) and placed in a freezer set to $-20{}^{\\circ}\\mathrm{C}$ After reaction for $^{18\\mathrm{~h~}}$ , the resulting ibuprofen loaded QCSG/CNT0 and QCSG/ CNT4 cryogels were thawed for drug controlled release test. The drug loaded cryogels $(500~\\upmu\\mathrm{L})$ in tubes with $1.4~\\mathrm{mL}$ of DPBS ( $\\mathrm{\\dot{p}H=}7.4$ , 0.01 M) were placed at $37^{\\mathrm{~o}}\\mathrm{C}$ with a shaking speed of $100~\\mathrm{rpm}$ to perform the spontaneous drug release profiles. For the NIR triggered ibuprofen release from QCSG/CNT4, the cryogels $(500~\\upmu\\mathrm{L})$ in tubes with $1.4~\\mathrm{mL}$ of DPBS $_{\\mathrm{(pH=7.4,0.01~M}}$ ) were irradiated with 808 nm NIR light $(1.4~\\mathrm{W/cm}^{2})$ ) over a period of $10\\ \\mathrm{min}$ . The ibuprofen free cryogels were used as blank controls. At predetermined time intervals, $1~\\mathrm{mL}$ of the release buffer was taken out for further analysis. Subsequently, $1~\\mathrm{mL}$ of fresh buffer was added to the tubes in order to maintain the constant volume. The concentrations of the drugs were analyzed by the UV–vis spectrophotometer (PerkinElmer Lambda 35). The $\\lambda_{\\mathrm{max}}$ of ibuprofen was $264~\\mathrm{{nm}}$ . \n\nNIR irradiation enhanced antibacterial test of cryogels. The cryogel QCSG/ CNT4 disks (with a diameter of $8\\mathrm{mm}$ and thickness of about $5\\mathrm{mm}$ ) were sterilized by immersing the samples in $75\\%$ alcohol, and then equilibrated with sterilized Dulbecco’s phosphate-buffered saline (DPBS). A volume of $10\\upmu\\mathrm{L}$ of bacterial suspension in sterilized DPBS $(10^{8}\\mathrm{CFU}\\mathrm{mL}^{-1},$ ) was added onto the surface of the swollen cryogel disks (QCSG/CNT0 and QCSG/CNT4). Then, the cryogel was exposed to NIR laser light $(808\\mathrm{nm},1.4\\mathrm{W}/\\mathrm{cm}^{2})$ for varying periods from 0 to $1,3$ , 5, 10, and $20\\mathrm{min}$ , respectively. A volume of $10\\upmu\\mathrm{L}$ of bacterial suspension $\\cdot10^{8}$ $\\mathrm{CFU}\\mathrm{mL}^{-1}$ ) suspended in $200\\upmu\\mathrm{L}$ of DPBS was used as a negative control, which was also exposed to NIR laser light $(808\\mathrm{nm},1.4\\mathrm{W}/\\mathrm{cm}^{2})$ . After allowing all the groups contact with bacteria for $20\\mathrm{min}$ , 1 mL of sterilized DPBS was added into each well to re-suspend any bacterial survivor. Then, $10\\upmu\\mathrm{L}$ of the above bacterial survivor resuspension was added onto agar plate, the colony-forming units on the agar plate were counted after incubated for 18 to $24\\mathrm{h}$ at $37^{\\circ}\\mathrm{C}$ The tests were repeated three times for each group and the results were expressed as $\\log10$ CFU using equation: \n\nLog Reduction $\\b=$ Log cell count of control \u0002 Log survivor count on cryogel: \n\nIn vivo hemostatic performance of the cryogels. The hemostatic ability of the cryogels were evaluated by both mouse liver trauma model43 and mouse-tail amputation model54. All animal studies were approved by the animal research committee of Xi’an Jiaotong University. For mouse liver trauma model, the mice (Kunming mice, 5–6 week-old, weight of $32-38{\\mathrm{g}},$ female) were randomly and equally divided into seven groups. The animals were anesthetized by injecting 10 wt $\\%$ chloral hydrate and fixed on a surgical corkboard. The liver of the mouse was exposed by abdominal incision, and serous fluid around the liver was carefully removed to prevent inaccuracies in the estimation of the blood weight obtained by the hemostatic samples. A pre-weighted filter paper on a paraffin film was placed beneath the liver. Bleeding from the liver was induced using a $16\\mathrm{G}$ needle with the corkboard tilted at about $30^{\\circ}$ . The pre-weighted gauze, gelatin hemostatic sponge, and shape-fixed cryogels were immediately applied onto the bleeding site, respectively. No treatment after pricking the liver was used as control group. The data of bleeding time and blood loss were recorded during the hemostatic process. Each group contains ten mice. \n\nFor the mouse-tail amputation model, the mice (Kunming mice, 5–6-week-old, weighing $32-38{\\mathrm{g}},$ female) were randomly and equally divided into seven groups. The animals were anesthetized by injecting $10\\mathrm{wt\\%}$ chloral hydrate $\\mathrm{\\Delta}[0.3\\mathrm{mL}$ per 100 $\\mathbf{g}$ weight of animal) and fixed on a surgical corkboard. Fifty percent length of the tail was cut by surgical scissors. After cutting, the tail of the mouse was placed in air for $15s$ to ensure normal blood loss. Then the wound was covered with the preweighted gauze, hemostatic sponge, and shape-fixed cryogels under slight pressure. The data of bleeding time and blood loss were recorded during the hemostatic process. The wound without treatment was used as control group. Each group contains ten mice. \n\nIn vivo lethal noncompressible hemorrhage hemostasis test. New Zealand White rabbit liver volume defect was used as a lethal noncompressible hemorrhage hemostasis model to evaluate the hemostatic capacity of the cryogels. The shapefixed cryogel was injected into the liver defect hole to rapidly stop the bleeding and then cause the hemostasis. The shape of the sterilized cryogels (with diameter of 8 mm and height of $8\\mathrm{mm}$ ) was fixed as section 2.6 described, and the diameter of the shape-fixed cryogels was $4\\mathrm{mm}$ . Then the shape-fixed cryogel was loaded into syringe (with inner diameter of $4\\mathrm{mm}$ and external diameter of $5\\mathrm{mm}$ ) for further in vivo injection. Two types of gelatin hemostatic sponges (with a height of $8\\mathrm{mm}$ and diameters of $4\\mathrm{mm}$ and $6\\mathrm{mm}$ , respectively) were used as control groups. New Zealand White rabbits (male, ${\\sim}2.5\\mathrm{kg},$ were randomly and equally divided into five groups. The animals were fixed on the surgical corkboard and then $10\\%$ chloral hydrate was injected into rabbits enterocoelia to anesthetize them ( $\\mathrm{\\dot{0}}.5\\mathrm{ml}$ per 100 g). Following that, the rabbit underwent an abdominal incision to expose the liver, the serous fluid around the liver was carefully removed, and then a columniform liver volume defect (with a diameter of $5\\mathrm{mm}$ and height of $5\\mathrm{mm}$ ) was made in right lobe using biopsy needle (inner diameter of $5\\mathrm{mm}$ ) and surgical scissors. Free bleeding was allowed for $30\\mathrm{{s}}$ and then the cryogel was immediately injected into the defect hole or gelatin hemostatic sponge was immediately inserted into the defect hole. During the hemostatic process, the weighed gauze was used to absorb the flowing blood. The hemostatic time, blood loss and life state were recorded accordingly. Each group was repeated for five times. The animal experiments were approved by the animal research committee of Xi’an Jiaotong University. \n\nHemostatic test on a standardized liver bleeding model. The shape of the sterilized cryogels (with diameter of $12\\mathrm{mm}$ and height of $8\\mathrm{mm}$ ) was fixed by compressing and removing the free water. The diameter of the shape-fixed cryogels was about $16\\mathrm{mm}$ . Thirty-two layers of Combat Gauze with a diameter of about 8 mm were used as a control group. New Zealand White rabbits (male, ${\\sim}2.5\\mathrm{kg})$ were randomly and equally divided into four groups. The animals were fixed on the surgical corkboard and then $10\\%$ chloral hydrate was injected into rabbits enterocoelia to anaesthetize them $\\mathrm{\\dot{0}}.5\\mathrm{ml}$ per $\\begin{array}{r}{100\\mathrm{g})}\\end{array}$ . Following that, the rabbit underwent an abdominal incision to expose the liver, the serous fluid around the liver was carefully removed. A plastic disc (with a diameter of $12\\mathrm{mm}$ ) with biological glue was glued to the right lobe of the rabbit and then a circular surface defect (with a diameter of $12\\mathrm{mm}$ ) was made in the right lobe by cutting the liver along the inside of the disc. The hemostatic agents were immediately applied onto the defect with slight pressure for $15\\mathrm{min}$ after creating the liver surface defect. After the performance, the blood loss was recorded accordingly. The group without any treatment was used as blank group. Each group contains six rabbits. The animal experiments were approved by the animal research committee of Xi’an Jiaotong University. \n\nIn vivo wound healing test. The animal experiments were approved by the animal research committee of Xi’an Jiaotong University. Mice weighing $32{\\ensuremath{-}}38\\ \\mathrm{g}$ and 5–6-week-old were used for studies and randomly and equally divided into three groups. The mice were acclimatized for one week before surgery groups. For the surgery part, all procedures were performed under aseptic condition. After standard anesthesia procedure with intraperitoneal injection of chloral hydrate $0.3\\mathrm{mg/kg}$ body weight), the dorsal region of mouse above the tail but below the back was shaved to prepare for surgery. Two full-thickness wounds with $6\\mathrm{mm}$ diameter were created on either side of the midline. One group was dressed by Transparent Film Dressing Frame Style (3 M Health Care, USA) and QCSG/CNT0 + Transparent Film Dressing, one group was dressed by Transparent Film Dressing and QCSG/CNT4 + Transparent Film Dressing, and the other group was dressed by QCSG/CNT0 cryogel $^+$ Transparent Film Dressing and QCSG/CNT4 cryogel $^+$ Transparent Film Dressing. Each group contained five mice. For wound area monitoring, on the 5th, 10th, and 15th day, the mice were performed standard anesthesia procedure with intraperitoneal injection of chloral hydrate, then the wound area was measured by tracing the wound boundaries on plotting papers. \n\nWound regeneration $(\\%)$ was calculated using the equation: \n\n$$\n{\\mathrm{Wound~contraction}}=({\\mathrm{area~(0~day)}}-{\\mathrm{area~(}}n\\ {\\mathrm{day)}})/({\\mathrm{area~(0~day)}})\\times100\\%\n$$ \n\nHistological analysis. For evaluation of epidermal regeneration and inflammation in wound area, samples collected on 5th, 10th, and 15th day were fixed with $4\\%$ paraformaldehyde for $^{\\textrm{1h}}$ , then embedded in paraffin, cross sectioned to $40\\mathrm{-}\\upmu\\mathrm{m}$ thick slices, and then stained with Haematoxylin-Eosin (Beyotime, China). All slices were analyzed and photo-captured by microscope (IX53, Olympus, Japan). \n\nIn vivo host response evaluation of the cryogels. The in vivo host response evaluation of the cryogels was performed as we previously reported67. All of the procedures of animal experiments were performed according to the guidelines established by the animal research committee of Xi’an Jiaotong University. Before implantation, all of the materials were cut into the same shape and size (diameter of $8\\mathrm{mm}$ and height of $2\\mathrm{mm}^{\\cdot}$ ), sterilized with $75\\%$ ethanol, and rinsed in phosphate-buffered saline (PBS) overnight. Female Sprague Dawley rats (200−250 $\\mathbf{g}$ in weight, 7–8 weeks) were generally anesthetized, and a small incision was made on the same area on the back of each rat. The testing articles were placed subcutaneously into the incision, and the skin was closed following the placement. The rats returned to their own cage and permitted free access to food and water after they recovered from anesthesia. After surgery for 7 days and 30 days, the animals were sacrificed and implanted materials were excised with the adjacent tissues. After excision, the material-tissue compounds were embedded in paraffin, sectioned $(3\\upmu\\mathrm{m})$ , and mounted onto slides. The acute inflammatory response and chronic inflammatory response were evaluated from both hematoxylin and eosin (H&E) staining and toluidine blue (TB) staining. After staining, the slides were observed by microscope and the images were analyzed using Image Pro Plus software. \n\nStatistical analysis. The experimental data were analyzed using Student’s t-test. $P$ value $<0.05$ was considered statistical significance. Results are expressed as mean $\\pm$ standard error (s.e.m) for animal studies while the other results are expressed as mean $\\pm$ standard deviation $(\\mathbf{s.d.})^{62}$ . The sample size for the animal studies was validated by Gpower3 software using the post-hoc power analysis for a twotailed $t{\\mathrm{.}}$ -test68,69. The effect size index was calculated by the equation: \n\n$$\nd=\\frac{|\\mu1-\\mu2|}{\\sqrt{0.5\\times(\\sigma1^{2}+\\sigma2^{2})}}\n$$ \n\nthat made the power $(1-\\beta$ error probability) $\\ge0.8$ for sample size of 10 in mice hemostatic experiments, for sample size of five in rabbit hemostatic experiments and for sample size of five in mice wound healing experiments. For mice hemostatic experiments, average blood losses were $\\mu1$ and $\\mu2$ from QCSG/CNT2 treated mice liver group and QCSG/CNT6 treated mice liver group, and σ1 and $\\sigma2$ were standard deviations of those from QCSG/CNT2 and QCSG/CNT6 treated mice liver groups, respectively. For rabbit hemostatic experiments, average blood losses were $\\mu1$ and $\\mu2$ from gelatin sponge D2 treated rabbit liver group and QCSG/CNT0 treated rabbit liver group, and σ1 and $\\sigma2$ were standard deviations of those from gelatin sponge D2 and QCSG/CNT0 treated rabbit liver groups, respectively. For mice wound healing experiments, average wound contraction percentages were $\\mu1$ and $\\mu2$ from QCSG/CNT0 treated mice skin wound group and QCSG/CNT4 treated mice skin wound group, and σ1 and $\\sigma2$ were standard deviations of those from QCSG/CNT0 and QCSG/CNT4 treated mice skin wound groups, respectively. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 26 December 2017 Accepted: 4 June 2018 \nPublished online: 17 July 2018 \n\n# References \n\n1. Johnson, D. et al. The effects of QuikClot Combat Gauze on hemorrhage control in the presence of hemodilution and hypothermia. Ann. Med Surg. 3, \n21–25 (2014). \n2. Hee Park, D. et al. In vitro degradation and cytotoxicity of alkyl 2‐ cyanoacrylate polymers for application to tissue adhesives. J. Appl. Polym. Sci. \n89, 3272–3278 (2003). \n3. Wen, J., Weinhart, M., Lai, B., Kizhakkedathu, J. & Brooks, D. E. Reversible hemostatic properties of sulfabetaine/quaternary ammonium modified hyperbranched polyglycerol. Biomaterials 86, 42–55 (2016). \n4. Ong, S.-Y., Wu, J., Moochhala, S. M., Tan, M.-H. & Lu, J. Development of a chitosan-based wound dressing with improved hemostatic and antimicrobial properties. Biomaterials 29, 4323–4332 (2008). \n5. Revelli, L., Tempera, S. E., Bellantone, C., Raffaelli, M. & Lombardi, C. P. in Minimally Invasive Therapies for Endocrine Neck Diseases (eds Lombardi, C. P. & Bellatone, R.) 249-259 (Springer: Switzerland, 2016). \n6. Devlin, J. J., Kircher, S., Kozen, B. G., Littlejohn, L. F. & Johnson, A. S. Comparison of ChitoFlex®, CELOX™, and QuikClot® in control of hemorrhage. J. Emerg. Med 41, 237–245 (2011). \n7. Landsman, T. et al. A shape memory foam composite with enhanced fluid uptake and bactericidal properties as a hemostatic agent. Acta Biomater. 47, \n91–99 (2017). \n8. Mueller, G. R. et al. A novel sponge-based wound stasis dressing to treat lethal noncompressible hemorrhage. J. Trauma Acute Care 73, S134–S139 (2012). \n9. Rodriguez, J. N. et al. Opacification of shape memory polymer foam designed for treatment of intracranial aneurysms. Ann. Biomed. Eng. 40, 883–897 (2012). \n10. Rodriguez, J. N. et al. In vivo response to an implanted shape memory polyurethane foam in a porcine aneurysm model. J. Biomed. Mater. Res A 102, 1231–1242 (2014). \n11. Yu, Y.-J., Hearon, K., Wilson, T. S. & Maitland, D. J. The effect of moisture absorption on the physical properties of polyurethane shape memory polymer foams. Smart Mater. Struct. 20, 085010 (2011). \n12. Henderson, T. M., Ladewig, K., Haylock, D. N., McLean, K. M. & O’Connor, A. J. Cryogels for biomedical applications. J. Mater. Chem. B 1, 2682–2695 (2013). \n13. Liu, Y. et al. Highly flexible and resilient elastin hybrid cryogels with shape memory, injectability, conductivity, and magnetic responsive properties. Adv. Mater. 28, 7758–7767 (2016). \n14. Luo, R., Wu, J., Dinh, N. D. & Chen, C. H. Gradient porous elastic hydrogels with shape‐memory property and anisotropic responses for programmable locomotion. Adv. Funct. Mater. 25, 7272–7279 (2015). \n15. Koshy, S. T., Ferrante, T. C., Lewin, S. A. & Mooney, D. J. Injectable, porous, and cell-responsive gelatin cryogels. Biomaterials 35, 2477–2487 (2014). \n16. Zheng, Y. et al. Composites with macroporous poly (vinyl alcohol) cryogels with attached activated carbon microparticles with controlled accessibility of a surface. ACS Appl. Mater. Inter 4, 5936–5944 (2012). \n17. Wang, L. et al. Mussel‐inspired conductive cryogel as cardiac tissue patch to repair myocardial infarction by migration of conductive nanoparticles. Adv. Funct. Mater. 26, 4293–4305 (2016). \n18. Kumar, A. & Srivastava, A. Cell separation using cryogel-based affinity chromatography. Nat. Protoc. 5, 1737 (2010). \n19. Bencherif, S. A. et al. Injectable preformed scaffolds with shape-memory properties. Proc. Natl Acad. Sci. USA 109, 19590–19595 (2012). \n20. Shin, S. R. et al. Carbon nanotube reinforced hybrid microgels as scaffold materials for cell encapsulation. ACS Nano 6, 362–372 (2011). \n21. Li, H., Wang, D. Q., Chen, H. L., Liu, B. L. & Gao, L. Z. A novel gelatin–carbon nanotubes hybrid hydrogel. Macromol. Biosci. 3, 720–724 (2003). \n22. Shin, S. R. et al. Carbon-nanotube-embedded hydrogel sheets for engineering cardiac constructs and bioactuators. ACS Nano 7, 2369–2380 (2013). \n23. Deng, Z., Guo, Y., Zhao, X., Ma, P. X. & Guo, B. Multifunctional stimuliresponsive hydrogels with self-healing, high conductivity, and rapid recovery through host–guest interactions. Chem. Mater. 30, 1729–1742 (2018). \n24. Wu, Y., Wang, L., Guo, B., & Ma, P.X. Interwoven aligned conductive nanofiber yarn/hydrogel composite scaffolds for engineered 3D cardiac anisotropy. ACS Nano 11, 5646–5459 (2017). \n25. Murray, C. K., Roop, S. A., Hospenthal, D. R. & Dooley, D. P. Bacteriology of war wounds at the time of injury. Mil. Med 171, 826 (2006). \n26. Aronson, N. E., Sanders, J. W. & Moran, K. A. In harm’s way: infections in deployed American military forces. Clin. Infect. Dis. 43, 1045–1051 (2006). \n27. Zhao, X., Li, P., Guo, B. & Ma, P. X. Antibacterial and conductive injectable hydrogels based on quaternized chitosan-graft-polyaniline/oxidized dextran for tissue engineering. Acta Biomater. 26, 236–248 (2015). \n28. Ignatova, M., Manolova, N. & Rashkov, I. Electrospun antibacterial chitosan‐ based fibers. Macromol. Biosci. 13, 860–872 (2013). \n29. Stefan, J. et al. The current view on biological potency of cationically modified chitosan. JPP 6, 2 (2014). \n30. Hoque, J., Prakash, R. G., Paramanandham, K., Shome, B. R. & Haldar, J. Biocompatible injectable hydrogel with potent wound healing and antibacterial properties. Mol. Pharm. 14, 1218–1230 (2017). \n31. Gu, R. et al. The performance of a fly-larva shell-derived chitosan sponge as an absorbable surgical hemostatic agent. Biomaterials 31, 1270–1277 (2010). \n32. Zhong, D. et al. Effects of the gene carrier polyethyleneimines on structure and function of blood components. Biomaterials 34, 294–305 (2013). \n33. Chou, T.-C., Fu, E., Wu, C.-J. & Yeh, J.-H. Chitosan enhances platelet adhesion and aggregation. Biochem. Bioph. Res. Co. 302, 480–483 (2003). \n34. Bencherif, S. A. et al. Injectable cryogel-based whole-cell cancer vaccines. Nat. Commun. 6, 7556 (2015). \n35. Cutting, K. Managing wound exudate using a super-absorbent polymer dressing: a 53-patient clinical evaluation. J. Wound Care 18, 202–205 (2009). 200. \n36. Kozen, B. G., Kircher, S. J., Henao, J., Godinez, F. S. & Johnson, A. S. An alternative hemostatic dressing: comparison of CELOX, HemCon, and QuikClot. Acad. Emerg. Med 15, 74–81 (2008). \n37. Liu, Z., Tabakman, S., Welsher, K. & Dai, H. Carbon nanotubes in biology and medicine: in vitro and in vivo detection, imaging and drug delivery. Nano Res. 2, 85–120 (2009). \n38. Dong, R., Zhao, X., Guo, B. & Ma, P. X. Self-healing conductive injectable hydrogels with anti-bacterial activity as cell delivery carrier for cardiac cell therapy. ACS Appl. Mater. Inter 8, 17138 (2016). \n39. Wu, Y., Wang, L., Guo, B., Shao, Y. & Ma, P. X. Electroactive biodegradable polyurethane significantly enhanced Schwann cells myelin gene expression and neurotrophin secretion for peripheral nerve tissue engineering. Biomaterials 87, 18–31 (2016). \n40. Guo, B., Glavas, L. & Albertsson, A. C. Biodegradable and electrically conducting polymers for biomedical applications. Prog. Polym. Sci. 38, \n1263–1286 (2013). \n41. Guo, B. L., & Ma, P. X. Synthetic biodegradable functional polymers for tissue engineering: a brief review. Sci. China Chem. 57, 490–500 (2014). \n42. Xie, M., Wang, L., Ge, J., Guo, B. & Ma, P. X. Strong electroactive biodegradable shape memory polymer networks based on star-shaped polylactide and aniline trimer for bone tissue engineering. ACS Appl. Mater. Inter 7, 6772–6781 (2015). \n43. Zhao, X. et al. Antibacterial anti-oxidant electroactive injectable hydrogel as self-healing wound dressing with hemostasis and adhesiveness for cutaneous wound healing. Biomaterials 122, 34–47 (2017). \n44. Hsiao, C. W. et al. Effective photothermal killing of pathogenic bacteria by using spatially tunable colloidal gels with nano‐localized heating sources. Adv. Funct. Mater. 25, 721–728 (2015). \n45. Wu, M.-C., Deokar, A. R., Liao, J.-H., Shih, P.-Y. & Ling, Y.-C. Graphenebased photothermal agent for rapid and effective killing of bacteria. ACS Nano \n7, 1281–1290 (2013). \n46. Arapoglou, V. et al. Analgesic efficacy of an ibuprofen-releasing foam dressing compared with local best practice for painful exuding wounds. J. Wound Care \n20, 319–325 (2011). \n47. Fogh, K. et al. Clinically relevant pain relief with an ibuprofen‐releasing foam dressing: results from a randomized, controlled, double‐blind clinical trial in exuding, painful venous leg ulcers. Wound Repair Regen.20, 815–821 (2012). \n48. Shemesh, M. & Zilberman, M. Structure–property effects of novel bioresorbable hybrid structures with controlled release of analgesic drugs for wound healing applications. Acta Biomater. 10, 1380–1391 (2014). \n49. Argoff, C.E. Topical analgesics in the management of acute and chronic pain. Mayo Clin. Proc. 88, 195–205 (2013). \n50. Chang, K.-H., Liao, H.-T. & Chen, J.-P. Preparation and characterization of gelatin/hyaluronic acid cryogels for adipose tissue engineering: in vitro and in vivo studies. Acta Biomater. 9, 9012–9026 (2013). \n51. Sasidharan, A. et al. Hemocompatibility and macrophage response of pristine and functionalized graphene. Small 8, 1251–1263 (2012). \n52. Cheng, F. et al. Preparation and characterization of 2, 2, 6, 6- tetramethylpiperidine-1-oxyl (TEMPO)-oxidized cellulose nanocrystal/ alginate biodegradable composite dressing for hemostasis applications. ACS Sustain Chem. Eng. 5, 3819–3828 (2017). \n53. Li, G. et al. Graphene-montmorillonite composite sponge for safe and effective hemostasis. ACS Appl. Mater. Inter 8, 35071–35080 (2016). \n54. Quan, K. et al. Diaminopropionic acid reinforced graphene sponge and its use for hemostasis. ACS Appl. Mater. Inter 8, 7666–7673 (2016). \n55. Dai, C. et al. Degradable, antibacterial silver exchanged mesoporous silica spheres for hemorrhage control. Biomaterials 30, 5364–5375 (2009). \n56. Hansen, A., McMillan, L., Morrison, A., Petrik, J. & Bradley, M. Polymers for the rapid and effective activation and aggregation of platelets. Biomaterials 32, \n7034–7041 (2011). \n57. Cines, D. B. et al. Clot contraction: compression of erythrocytes into tightly packed polyhedra and redistribution of platelets and fibrin. Blood 123, \n1596–1603 (2014). \n58. Moers, A. et al. G13 is an essential mediator of platelet activation in hemostasis and thrombosis. Nat. Med 9, 1418–1422 (2003). \n59. Packham, M. A. Role of platelets in thrombosis and hemostasis. Can. J. Physiol. Pharm. 72, 278–284 (1994). \n60. Semberova, J. et al. Carbon nanotubes activate blood platelets by inducing extracellular $\\mathrm{Ca}2+$ influx sensitive to calcium entry inhibitors. Nano Lett. 9, \n3312–3317 (2009). \n61. De Paoli Lacerda, S. H. et al. Carbon nanotubes activate store-operated calcium entry in human blood platelets. ACS Nano 5, 5808–5813 (2011). \n62. Cumming, G., Fidler, F. & Vaux, D. L. Error bars in experimental biology. J. Cell Biol. 177, 7 (2007). \n63. Chan, L. W. et al. A synthetic fibrin cross-linking polymer for modulating clot properties and inducing hemostasis. Sci. Transl. Med. 7, 277ra229 (2015). \n64. Kauvar, D. S., Lefering, R. & Wade, C. E. Impact of hemorrhage on trauma outcome: an overview of epidemiology, clinical presentations, and therapeutic considerations. J. Trauma Acute Care 60, S3–S11 (2006). \n65. Gharibi, R., Yeganeh, H., Rezapourlactoee, A. & Hassan, Z. M. Stimulation of wound healing by electroactive, antibacterial and antioxidant polyurethane/ siloxane dressing membranes: in-vitro and in-vivo evaluations. ACS Appl. Mater. Inter 7, 24296 (2015). \n66. Kloth, L. C. Electrical stimulation technologies for wound healing. Adv. Wound Care 3, 81 (2014). \n67. Wu, Y. et al. Self-healing supramolecular bioelastomers with shape memory property as a multifunctional platform for biomedical applications via modular assembly. Biomaterials 104, 18–31 (2016). \n68. Faul, F., Erdfelder, E., Lang, A.-G. & Buchner, A. $G^{*}$ Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res Methods 39, 175–191 (2007). \n69. Chen, Y. et al. A novel small molecule chaperone of rod opsin and its potential therapy for retinal degeneration. Nat. Commun. 9, 1976 (2018). \n\n# Acknowledgements \n\nSupported by National Natural Science Foundation of China (grant number: 51673155) and State Key Laboratory for Mechanical Behavior of Materials (grant number: 20182002) and the Fundamental Research Funds for the Central Universities and NIH (HL 136231:PXM). \n\n# Author contributions \n\nX.Z., B.L.G., and P.X.M. conceived the idea. X.Z. and B.L.G. designed experiments and wrote the manuscript. X.Z. synthesized the cryogels, completed polymer characterization and in vitro evaluations with the help of B.L.G.. X.Z., H.W. and Y.P.L. completed the in vivo testing of materials. X.Z. and B.L.G. analyzed the results. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-04998-9. \n\nCompeting interests: The Xi’an Jiaotong University has applied for a patent for the discussed hemostatic materials with B.L.G., X.Z., and J.Q. listed as the inventors. The remaining authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1002_adma.201706758", + "DOI": "10.1002/adma.201706758", + "DOI Link": "http://dx.doi.org/10.1002/adma.201706758", + "Relative Dir Path": "mds/10.1002_adma.201706758", + "Article Title": "Nitrogen-Coordinated Single Cobalt Atom Catalysts for Oxygen Reduction in Proton Exchange Membrane Fuel Cells", + "Authors": "Wang, XX; Cullen, DA; Pan, YT; Hwang, S; Wang, MY; Feng, ZX; Wang, JY; Engelhard, MH; Zhang, HG; He, YH; Shao, YY; Su, D; More, KL; Spendelow, JS; Wu, G", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "Due to the Fenton reaction, the presence of Fe and peroxide in electrodes generates free radicals causing serious degradation of the organic ionomer and the membrane. Pt-free and Fe-free cathode catalysts therefore are urgently needed for durable and inexpensive proton exchange membrane fuel cells (PEMFCs). Herein, a high-performance nitrogen-coordinated single Co atom catalyst is derived from Co-doped metal-organic frameworks (MOFs) through a one-step thermal activation. Aberration-corrected electron microscopy combined with X-ray absorption spectroscopy virtually verifies the CoN4 coordination at an atomic level in the catalysts. Through investigating effects of Co doping contents and thermal activation temperature, an atomically Co site dispersed catalyst with optimal chemical and structural properties has achieved respectable activity and stability for the oxygen reduction reaction (ORR) in challenging acidic media (e.g., half-wave potential of 0.80 V vs reversible hydrogen electrode (RHE). The performance is comparable to Fe-based catalysts and 60 mV lower than Pt/C -60 mu g Pt cm(-2)). Fuel cell tests confirm that catalyst activity and stability can translate to high-performance cathodes in PEMFCs. The remarkably enhanced ORR performance is attributed to the presence of well-dispersed CoN4 active sites embedded in 3D porous MOF-derived carbon particles, omitting any inactive Co aggregates.", + "Times Cited, WoS Core": 975, + "Times Cited, All Databases": 1026, + "Publication Year": 2018, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000427111300028", + "Markdown": "# Nitrogen-Coordinated Single Cobalt Atom Catalysts for Oxygen Reduction in Proton Exchange Membrane Fuel Cells \n\nXiao Xia Wang, David A. Cullen, Yung-Tin Pan, Sooyeon Hwang, Maoyu Wang, Zhenxing Feng, Jingyun Wang, Mark H. Engelhard, Hanguang Zhang, Yanghua He, Yuyan Shao, Dong Su, Karren L. More, Jacob S. Spendelow,\\* and Gang Wu\\* \n\nDue to the Fenton reaction, the presence of Fe and peroxide in electrodes generates free radicals causing serious degradation of the organic ionomer and the membrane. Pt-free and Fe-free cathode catalysts therefore are urgently needed for durable and inexpensive proton exchange membrane fuel cells (PEMFCs). Herein, a high-performance nitrogen-coordinated single Co atom catalyst is derived from Co-doped metal-organic frameworks (MOFs) through a one-step thermal activation. Aberration-corrected electron microscopy combined with X-ray absorption spectroscopy virtually verifies the $\\mathsf{C o N}_{4}$ coordination at an atomic level in the catalysts. Through investigating effects of Co doping contents and thermal activation temperature, an atomically Co site dispersed catalyst with optimal chemical and structural properties has achieved respectable activity and stability for the oxygen reduction reaction (ORR) in challenging acidic media (e.g., half-wave potential of 0.80 V vs reversible hydrogen electrode (RHE). The performance is comparable to Fe-based catalysts and $60~\\mathsf{m}\\mathsf{v}$ lower than $\\mathsf{P t}/\\mathsf{C}\\cdot60\\upmu\\mathrm{g}\\mathsf{P t}\\mathsf{c m}^{-2})$ . Fuel cell tests confirm that catalyst activity and stability can translate to high-performance cathodes in PEMFCs. The remarkably enhanced ORR performance is attributed to the presence of well-dispersed $\\mathsf{C o N}_{4}$ active sites embedded in 3D porous MOF-derived carbon particles, omitting any inactive Co aggregates. \n\nPlatinum-group-metal (PGM)-free catalysts for the oxygen reduction reaction (ORR) have been studied extensively due to their potential to significantly reduce the cost of proton exchange membrane fuel cells (PEMFCs). Among studied formulations, transition metal and nitrogendoped carbon (M-N-C, M: Fe and/or Co) nanomaterials have attracted great attention because of their good electrocatalytic activity, promising stability, and lowcost scalable synthesis.[1–4] Compared to other transition metals, Fe–N–C catalysts show the best catalytic activity for the ORR with a typical half-wave potential of ${\\approx}0.8\\mathrm{~V~}$ vs reversible hydrogen electrode (RHE) in rotating disc electrode (RDE) tests.[5–7] However, Fe-based catalysts are not desirable for PEMFCs because of their tendency to form $\\mathrm{Fe}^{2+}$ or $\\mathrm{Fe}^{3+}$ , which react with $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to produce hydroxyl and hydroperoxyl radical species (Fenton’s reagent).[8,9] The free radicals generated by this process attack the PEMFC ionomer and membrane, causing serious performance degradation and cell failure. As a result, high-performance catalysts that are free of both PGMs and Fe are needed to enable durable and inexpensive PEMFCs. \n\nIt has been reported that the electrocatalytic activity of the M-N-C catalysts follows the order of $\\mathrm{Fe}>\\mathrm{Co}>\\mathrm{Mn}>\\mathrm{Cu}>\\mathrm{Ni}$ in both acid and alkaline electrolytes.[6,10] Therefore, Co appears to be the most promising alternative transition metal to replace Fe. Similar to Fe–N–C catalysts, the primary approach to synthesizing Co–N–C catalysts is through the pyrolysis of carbon and nitrogen precursors, metal salts, and carbon supports.[11,12] However, such uncontrolled heat treatment usually results in aggregation of unstable metallic compounds attached or enclosed in graphitic carbon shells. Additional acid-leaching treatment is required to remove these inactive Co species. After acid leaching, a second heat treatment is needed to repair the damaged carbon structures for further enhanced catalytic activity and stability. Despite these tedious effort, substantial metallic Co species, which are enclosed in carbon shells, remain and significantly reduce catalyst activity and stability. Moreover, the conventional synthesis route often leads to a heterogeneous distribution of active sites without accurate control of morphology and composition of the final catalyst.[13–17] Recent studies on Co-based carbon ORR catalysts are summarized in Table S1 (Supporting Information) in terms of their synthesis, structures, and resulting activity. Currently, most Co–N–C catalysts only exhibit good ORR activity in alkaline electrolytes.[18–20] Their poor ORR activity in acidic media may be attributed to the formation of inactive Co aggregates, such as metallic particles, carbides, nitrides, and oxides.[21,22] Therefore, innovative approaches to improving the density of active sites atomically dispersed in favorable carbon matrix are needed for high-performance Co catalysts for PEMFC applications. \n\nRecently, metal-organic frameworks (MOFs) have been identified as ideal precursors to prepare highly porous-nitrogendoped carbon materials for various energy applications.[23–25] Especially, zeolitic imidazolate frameworks (ZIFs) have emerged as a new platform for the synthesis of M-N-C catalysts.[24,25] ZIFs provide carbon and nitrogen atoms in the ligands, along with flexibility to dope active transition metals into the frameworks.[3,26–28] In the skeleton of the ZIF, metal atoms bridge with ligands to form 3D crystal frameworks with high porosity, surface area, and order.[27,29,30] These ZIF precursors can be converted to porous-nitrogen-doped carbon materials through heat treatment. Moreover, the original metal-nitrogen bond connected with hydrocarbon networks could directly yield $\\mathrm{MN}_{x}$ sites that are active for the ORR in acid.[30,31] Several $\\scriptstyle\\mathrm{Co-N-C}$ catalysts have been reported using Co-based ZIFs (ZIF-67) and other precursors.[18,31–33] Although the obtained catalytic activity and stability are good in alkaline media, performance is disappointing in acid media.[3,28,34–37] Therefore, achieving high density of active atomic Co sites uniformly dispersed into favorable carbon structures remains grand challenges for enhanced catalytic activity. In this work, we report a feasible chemical doping approach that enables tuning over a wide range of Co content doping $0-30\\ {\\mathrm{at}}\\%$ vs total Co and Zn metal content) within the well-defined ZIF precursors. Through elucidating the correlation between Co doping content, thermal activation conditions, and corresponding catalyst properties, we have prepared an atomically dispersed $\\mathrm{CoN}_{4}$ site catalyst with exceptional ORR activity and stability in acidic media, showing a half-wave potential $\\left(E_{1/2}\\right)$ of $0.80\\mathrm{~V~}$ vs RHE and good stability in $0.5\\mathrm{~M~}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ . It represents one of the best Co catalysts comparable to Fe–N–C catalysts and only $60~\\mathrm{mV}$ lower than $\\mathrm{Pt/C}$ in challenging acidic media. Unlike the heterogeneity in previous PGM-free catalysts, the $\\scriptstyle\\mathrm{Co-N-C}$ catalyst is in the absence of metallic aggregates and exhibits homogeneous morphology containing well-dispersed atomic Co sites coordinated with N. For the first time, such an atomic coordination between Co and N was directly observed by using high-angle annular dark-field imaging (HAADF)-scanning transmission electron microscope (STEM) images coupled with electron energy loss spectroscopy (EELS) at the atom level. X-ray absorption spectroscopy analysis further verified the $\\mathrm{CoN}_{4}$ structures, which is in good agreement with previous theoretical prediction.[38,39] The approach to chemically doping active transition metals into MOFs allows us establishing well-defined model catalysts to elucidate synthesis–structure–property correlations, which can provide valuable knowledge for advanced catalyst design and synthesis. \n\nCo-doped ZIF precursors with a wide range of Co doping contents $(0-30\\ a t\\%)$ were synthesized. The label of $n\\%$ was defined as the molar percentage of Co against the total metals (Co and $Z\\mathrm{n}$ ) in a methanol solution during the synthesis of ZIF nanocrystal precursors. One-step thermal activation directly converts the Co-doped ZIF nanocrystal precursors into nanocarbon (NC)-based Co catalysts, which were labeled as nCo-NC-heating temperature (e.g., 20Co-NC-1100). The experimental details were provided in the Supporting Information. The overall morphology of the best performing Co-doped ZIF catalysts (e.g., 20Co-NC-1100) is presented in Figure 1a–c, showing homogeneous carbon particles. The high porosity of the catalyst particles is crucial for accommodating active sites. The possible ORR active sites for Co-based catalysts have been predicted, which are associated with N-coordinated Co structures, which have a similar local chemical environment to the $\\mathrm{CoN}_{4}$ in Co–porphyrin structures.[40] However, such nitrogencoordinated atomic Co sites were never directly observed yet. Here, atomic level HAADF-STEM images coupled with EELS provided a direct evidence of $\\scriptstyle\\mathrm{Co-N}$ coordination at atomic level in the best performing 20Co-NC-1100 catalyst. Uniformly dispersed atomic Co sites (white dots) were clearly observed throughout the carbon particles carbonized from ZIF nanocrystals (Figure 1d). These Co atoms were likely coordinated with N, which directly derived from the well-defined fourfold N-coordinated Co within ZIF precursors through thermal activation. This hypothesis was verified by using EEL point spectra. As shown in Figure 1e–g, when the electron beam was placed on the bright dots (red circle), both N and Co were present in the EEL spectrum, suggesting their coexistence in the form of $\\mathrm{CoN}_{x}$ Conversely, when moving the beam over the neighboring carbon (green circle), no N or Co is observed. The original EEL spectra at different atomic spots are provided in Figure S1 (Supporting Information). This result was confirmed several times in different areas throughout the catalyst. This atomic level spectroscopic analysis clearly indicates that the well-dispersed atomic Co sites are indeed coordinated with N, and the sufficient stability of these Co–N centers under the electron beam suggests a strong interaction with the surrounding carbon. \n\n![](images/391daaf76f385ff0da380915db6d20cbd736840ead94413c98eaa38b20b13e21.jpg) \nFigure 1.  STEM images and element analysis for the best performing 20Co-NC-1100 catalysts. Aberration-corrected MAADF-STEM images a–e) with accompanying EEL point spectra $\\tt{e-g i}$ ). The point spectrum in (f) was taken at the dark neighboring support area in (e) and only shows C and no N and Co. The point spectrum g) was taken on the bright atom in (e) and shows both Co and N, indicating that Co is coordinated with N at an atomic scale. \n\nFurther evidences for Co–N coordination and chemical information were provided from X-ray absorption spectroscopy (XAS). As shown in Figure 2a, X-ray absorption near-edge structure (XANES) suggests that the oxidation state of Co of the precursor is between $^{2+}$ and $^{3+}$ when compared to reference CoO and $\\mathrm{Co}(\\mathsf{N O}_{3})_{3}$ . During heating treatments of Co-doped ZIF precursors at $600~^{\\circ}\\mathrm{C}$ , the Co oxidation state increases to $^{3+}$ higher as the XANES edge shifts toward higher energy and is at the right side of $\\mathrm{Co}(\\mathrm{NO}_{3})_{3}$ XANES edge. However, higher temperature treatment reduces the Co oxidation state as the corresponding XANES edge shifts toward lower energy, and eventually is close to that of CoO, indicating the existence of ${\\mathrm{Co}}^{2+}$ for the $1100^{\\circ}\\mathrm{C}$ treated catalyst. The change of Co oxidation state as a function of temperature is also clearly seen from the derivate of XANES in Figure 2b, which shows the shift of characteristic peaks from $\\mathrm{Co}^{(3+\\delta)+}(\\delta>0)$ $(600^{\\circ}\\mathrm{C})$ to the majority of ${\\bf C o}^{2+}\\left(1100^{\\circ}{\\bf C}\\right)$ through a coexistence of ${\\mathrm{Co}}^{2+}$ and ${\\mathsf{C o}}^{3+}$ $(800~^{\\circ}\\mathrm{C})$ . In addition, the white line $(\\approx7730\\ \\mathrm{eV})$ ) becomes broader as the heating temperature increases, suggesting less confined electron in Co local structure due to the uncertainty principle. Note that the preedge peak $(\\approx7710~\\mathrm{eV})$ is much lower for $1100^{\\circ}\\mathrm{C}$ treated catalyst compared to precursor and catalysts from 600 and $800~^{\\circ}\\mathrm{C}$ . For 3d transition metal K edge XANES, the preedge peaks are assigned to the forbidden 1s-to-3d transition[41,42] and the change of the pre-edge peak intensity is indicative of the changes in the cation symmetry, namely, less intense for higher symmetry.[43] All these evidences suggest that, for catalyst treated at $1100~^{\\circ}\\mathrm{C}.$ atomic Co is located in a more symmetric coordination, e.g., planar $\\mathrm{CoN}_{4}$ structure. As STEM images show only atomic $\\mathrm{~N~}$ surrounds Co, model-based fits (up to Co 2nd shell)[44,45] were performed on extended X-ray absorption fine structure (EXAFS) spectra for all catalysts (Figure 2c), and results are listed in Table S2 (Supporting Information). The peak located at ${\\approx}1.42$ Å for all ZIF-derived catalysts corresponds to the $\\mathrm{Co-N}$ scattering path, which closes to the spectra observed in $\\mathrm{CoN}_{4}$ containing CoTMMP presenting a dominant peak around $1.4\\mathring{\\mathrm{A}}.^{[46,47]}$ As for the metallic Co reference samples, the $\\scriptstyle\\mathbf{Co-Co}$ scattering path is located at ${\\approx}2.17$ Å.[48,49] Furthermore, through fitting CoO and CoPc EXAFS and their scattering paths (Figure S2, Supporting Information) as references, we found that Co is coordinated with ${\\approx}4\\mathrm{N}$ atoms for all catalysts in their first shell, but Co–Co scattering exists for the samples treated at relatively low temperature such as 600 and $800~^{\\circ}\\mathrm{C}$ indicating the existence of Co clusters. However, for $1100^{\\circ}\\mathrm{C}$ treated catalyst, the long-range disordering becomes weaker (lower peak amplitude for $R>2\\mathring{\\mathrm{~A~}}$ ) and only $\\mathrm{Co-N}$ scattering with large mean square disorder can be used to fit (Table S2, Supporting Information), strongly suggesting the uniform atomic $\\mathrm{CoN}_{4}$ unit for this catalyst, which is responsible for high ORR activity. This also indicates that sufficiently high temperature is favorable for forming $\\scriptstyle\\mathrm{Co-N}$ coordination, with being active sites for the ORR in acidic media. These results are also supported by soft XAS. As shown in Figure 2d, the Co L-edge is split into two peaks due to core-level spin–orbit coupling, namely, the lower energy $\\mathrm{L}_{3}$ peak $\\mathrm{(2p_{3/2}\\rightarrow3d)}$ ) and higher energy $\\mathrm{L}_{2}$ peak $(2\\mathrm{p}_{1/2}\\rightarrow3\\mathrm{d}$ ). Further splitting at $\\mathrm{L}_{3}$ peak is due to the multiplet structure from electron–electron interactions that can imply the local symmetry. The small peak at $776.4\\ \\mathrm{eV}$ is assigned to ocatehedrally coordinated $\\mathrm{(O_{h})}$ Co atoms,[50] which is the basic building block of CoO and $\\mathrm{LaCoO}_{3}$ . However, it does not show up in XAS spectra of our catalysts and precursors, indicating that these Co atoms are in different local environments. As XAS provides fingerprints of local geometric and electronic structures of the studied element, comparisons of our measured spectra with known spectra[50] suggest Co atoms in our catalysts and precursor are tetrahedrally coordinated $\\mathrm{(T_{d})}$ with a coordination number of 4: the peak at ${\\approx}777.6~\\mathrm{eV}$ is assigned to $\\mathrm{T_{d}}\\mathrm{Co}^{3+}$ , and other features match $\\mathrm{T_{d}}\\mathrm{Co}^{2+}$ . The different shapes of these XAS spectra are resulted from the variation of ligand field para­ meter value, 10Dq.[50] The mixed Co oxidation states are consistent with hard XAS measurements, and the local symmetry strongly supports Co K-edge EXAFS analyses. In addition, N K-edge XAS spectra show that the intensity of the $\\pi^{*}$ band (shaded area, ${\\approx}398\\mathrm{eV}$ assigned to pyridinic-N, cyanic-N, and graphitic-N) compared to $\\sigma^{*}$ band (shaded area, ${\\approx}404~\\mathrm{eV}$ assigned to C–N) is dramatically reduced for catalysts after high temperature annealing (Figure 2e). The low $\\pi^{*}$ features, which are very similar to copper phthalocyanine (CuPc),[51] are due to the relatively weak interaction between the cation and the phthalocyanine ligand,[51] confirming that temperature is critical to form the $\\mathrm{CoN}_{4}$ structure. No N–O peak $(\\approx402~\\mathrm{eV})^{[52]}$ is identified in Figure 2e, meaning \n\n![](images/1e60073d4d3baf6a2eb016f1a06246ff05adeafb494a45c0d58ceac92ce1d0af.jpg) \nFigure 2.  XAS spectra for precursor and catalysts annealed at different temperatures. a) Co K-edge XANES, b) the derivative of XANES, c) Co K-edge EXAFS data and fits (orange), d) Co L-edge XANES, and e) N K-edge XAS, and the shaded areas are for $\\pi^{*}$ and $\\sigma^{*}$ bands, respectively. \n\nN atoms are bonded only with C and Co for our catalysts, which is also consistent with STEM/EEL point spectra. Therefore, all XAS results demonstrate that the $\\mathrm{CoN}_{4}$ centers have been successfully embedded into the ZIF-derived carbon matrix with the assistance of high temperature treatment. \n\nORR activity is believed to stem from the codopings of Co and N into carbon structures. X-ray photoelectron spectroscopy (XPS) was proved effective to determine the chemical bonding nature of the N, C, and Co species in the catalysts. Table S3 (Supporting Information) summarizes the elemental composition of different catalysts. With an increase of Co doping level in the ZIF precursors, the atomic content of Co in the resulting catalyst is also accordingly increased from $0.07\\mathrm{at\\%}$ for 1Co-NC1100 to $0.34~{\\mathrm{at}}\\%$ for 20Co-NC-1100. But for 30Co-NC-1100, the Co content decreased slightly. The reason for this might be the formation of Co clusters as shown in Figure S3 (Supporting Information). Some Co atoms under carbon shells could not be detected by XPS. Thus, Co content in catalysts was also further analyzed by using X Ray fluorescence and ICP-MS as shown in Table S4 (Supporting Information). The Co content in catalysts is indeed increased with the doping content in precursors. Among others, the 20Co-NC-1100 catalyst contains the maximum atomic N content of $3.6\\ \\mathrm{at\\%}$ and shows the highest atomic ratio of $\\mathrm{Co}/\\mathrm{N}$ . Therefore, the highest contents for both dispersed Co and N might be one of the reasons that 20Co-NC1100 catalyst showed the best ORR activity. Compared to XPS and ICP analysis, Zn richness at surface is likely due to the accumulation of Zn during the evaporation at high temperature. \n\n![](images/108548c2d17b836d527180e9feedd0433fec624a82c274b9250014f6559325ac.jpg) \nFigure 3.  XPS analysis to elucidate the correlations between a,b) Co doping contents and c,d) thermal heating temperatures during the catalyst synthesis and a,c) the resulting N doping and b,d) Co species in surface layers of catalysts. \n\nSimilarly, richness of Zn in surface layers was also found in “Co-free” ZIF-8 catalyst after a heating treatment at $1100^{\\circ}\\mathrm{C}$ . \n\nHigh-resolution XPS was used to further explain the chemical changes resulting from different levels of Co doping. As shown in Figure 3a, the N 1s spectra of the ZIF-1100 and 1Co-NC-1100 catalysts exhibit three major components corresponding to pyridinic-N $({\\approx}398.4\\ \\mathrm{eV})$ , graphitic-N $\\mathrm{\\Phi(\\approx401.1~\\mathrm{eV})}$ , and oxidized graphitic-N (403–405 eV) (Table S5, Supporting Information). When the ${\\bf C}_{}0/({\\bf Z}{\\bf n}{+}{\\bf C}_{}0)$ ratio increased to higher than 0.06, there was an additional peak at $399.2\\mathrm{~eV}.$ This type of $\\mathrm{~N~}$ species has been attributed to nitrogen bonded to cobalt $\\mathrm{(CoN_{4})}$ ,[19,28,53] which is in good agreement with the EELS observation and XAS analysis. This peak becomes more dominant with an increase of Co doping levels reaching a maximum for the 20Co-NC-1100 catalyst. Meanwhile, the peak intensity of the Co $2\\mathrm{p}_{3/2}$ spectra increased with rising Co content (Figure 3b). Likewise, the adjacent peaks at $781.7\\ \\mathrm{eV}$ can be assigned to the $\\mathrm{CoN}_{4}$ moieties.[15,24,44–46] The percentage of $\\mathrm{CoN}_{4}$ components determined based on peak areas continuously increases with Co doping from 6Co-NC-1100 to 20Co-NC-1100. However, excess Co doping up to $30\\%$ leads to a reduced $\\mathrm{CoN}_{4}$ component (Table S6, Supporting Information). The correlation between the qualitative content of $\\mathrm{CoN}_{4}$ and Co doping is in good agreement with the N 1s peak at $399.2\\ \\mathrm{eV}$ associated with possible $\\mathrm{CoN_{4}}$ . The highest content determined with the 20CoNC-1100 catalyst would be expected for the largest density of $\\mathrm{CoN}_{4}$ active sites for the ORR. In line with the HR-TEM observations, the C 1s peak is nearly independent of the Co doping contents (Figure S4 and Table S7, Supporting Information). \n\nXPS was also employed to further understand the effect of heating temperature on the possible bonding among N, Co, and C in catalysts. As for the 20Co-ZIF derived catalysts (Figure S4 and Table S8, Supporting Information), the content of N declined from $26.4\\%$ for $20\\mathrm{Co-NC-}600$ to $3.5\\%$ for 20Co-NC-1100, while C increased from $59.1\\%$ to $92.9\\%$ . $1100^{\\circ}\\mathrm{C}$ yields the highest ratio of $\\mathrm{Co}/\\mathrm{N}$ , suggesting the largest density of active sites associated with atomic Co sites. It should be noted that the content of $Z\\mathrm{n}$ is significantly decreased with an increase in heating temperature. Especially, when the temperature reaches $1100^{\\circ}\\mathrm{C}$ , the content of $Z\\mathrm{n}$ is minimum. Due to the poor activity in Co-free catalysts similar to “metal-free” carbon catalysts,[11] Zn doped in carbon plays insignificant role in boosting ORR activity. In addition, we also carried out the acidic treatment for as-synthesized catalyst, no activity change was observed in both RDE and fuel cell tests. Thus, the remaining trace of Zn in catalyst has negligible effect on the catalytic activity. As shown in Figure 3c, the catalysts obtained below $800~^{\\circ}\\mathrm{C}$ showed two major components corresponding to pyridinic-N $({\\approx}398.4~\\mathrm{eV})$ and pyrrolic-N $(\\approx399.8\\ \\mathrm{eV})$ . When the annealing temperature reached $1000~^{\\circ}\\mathrm{C}$ , pyridinic-N and graphitic-N $\\mathrm{\\Omega}({\\approx}401.1~\\mathrm{eV})$ ) dominated in the samples and the component of $\\mathrm{CoN}_{4}$ is also clearly distinguished. The Co $2\\mathrm{p}_{3/2}$ spectra are shown in Figure 3d, and the component of $\\mathrm{CoN}_{4}$ could be discovered when the heating temperature was higher than $800^{\\circ}\\mathrm{C}$ , where ORR activity starts generating in acidic media. Also, $800~^{\\circ}\\mathrm{C}$ is found to be the starting temperature to form graphitized $\\scriptstyle{\\mathrm{C=C}}$ bond at $284.5\\ \\mathrm{eV}$ (Figure S4, Supporting Information). The carbonization degree is further increased with higher temperature evidenced by gradually narrowing peaks. \n\nElucidating the effect of Co doping content on the carbon structure and morphology is crucial during catalyst development. As for the Co-doped ZIF precursors, gradually changing color from white to purple was observed with increasing Co content (Figure S5, Supporting Information). The Co-doped ZIF precursors showed a rhombic dodecahedron crystal shape. Compared to Co-free ZIF crystals ( $\\ensuremath{\\langle35\\mathrm{~nm}\\rangle}$ , slightly increased sizes were observed for 6Co-ZIF $(40~\\mathrm{\\nm})$ and 30Co-ZIF $(50~\\mathrm{~nm})$ precursors (Figure S5, Supporting Information). Similar size dependence was also observed with Fe-doped ZIF nanocrystals.[54] After high temperature treatment at $1100~^{\\circ}\\mathrm{C}$ under $\\mathrm{N}_{2}$ flow, the Co-ZIF polyhedral crystals directly converted into shape-preserved carbon polyhedra, maintaining nearly the same size as their precursors (Figure S6a–d, Supporting Information). We found that the Co-doped ZIF crystal sizes can be tuned accurately from 20 to $200~\\mathrm{nm}$ by varying the metal concentrations of Co and $Z\\mathrm{n}$ cations between 10 and 120 mmol $\\mathrm{L}^{-1}$ in methanol solutions during Co-doped ZIF nanocrystal synthesis (Figure S6c,e–g, Supporting Information). Further reduced concentration to 5 mmol $\\mathrm{L}^{-1}$ leads to fused morphology without isolated particles (Figure S6h, Supporting Information). Thus, similar to traditional $\\mathrm{Pt}$ catalysts, tuning catalyst particle sizes for Co catalysts could realize much enhanced activity by exploring appropriate morphologies. \n\nSince ZIF-8 $(100\\%\\mathrm{Zn})$ and ZIF-67 ( $100\\%$ Co) are isomorphic, varying the ratios of ${\\mathrm{Co}}{:}{\\mathrm{Zn}}$ in the ZIF is not expected to result in a change in crystal structure, which was confirmed by X-ray diffraction (XRD) patterns in line with the simulated results (Figure S7a, Supporting Information).[18] After pyrolysis at $1100^{\\circ}\\mathrm{C}$ under $\\mathrm{N}_{2}$ flow, all the Co-ZIF-8 precursors were converted into carbon materials as shown in XRD patterns (Figure $\\mathbf{S}7\\mathbf{b}$ Supporting Information). Raman spectra (Figure S7c and Table S9, Supporting Information) further indicate that, regardless of the Co doping level, all catalysts exhibited similarly ordered carbon structures. $\\mathrm{N}_{2}$ adsorption/desorption analysis (Figure S8 and Table S10, Supporting Information) indicates similar BET surface area of around $1000{-}1200\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}$ and dominates micropores for all Co-ZIF precursors, which are independent of Co doping content. The surface areas of all catalysts are reduced to $600{-}800~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ with increased mesopores and macropores after thermal activation at $1100~^{\\circ}\\mathrm{C}$ . Notable that the best performing 20Co-NC-1100 catalyst contains the largest fractions of meso/macropores, which would be favorable for the ORR since they provide accessibility to active sites and fast $\\mathrm{O}_{2}$ transport. HR-TEM imaging and STEM imaging were performed to study Co-NC-1100 catalysts as a function of Co content from 0 to $30\\%$ Co (Figure S3, Supporting Information). Unlike the Co-free ZIF catalyst showing irregular particle shape, the Co-doped ZIF catalysts retained their polyhedral particle morphology. HR-TEM images further revealed highly disordered graphitic domain structures, which were nearly independent of Co doping content. This result contradicts previous understanding that higher Co doping would yield higher degree of graphitization in carbon.[55] The possible reason is that, unlike metallic Co, the atomic Co sites cannot catalyze the graphitization of carbon. This is in good agreement with the observation that there are no Co aggregates or cluster in the catalysts, except for those with extremely high Co doping level (e.g., 30Co-NC-1100) (Figure S9, Supporting Information). This comparison indicates that the activity decline resulting from high Co content is very likely due to the formation of significant inactive Co clusters, which may prevent the formation of active $\\mathrm{CoN}_{4}$ sites. \n\n![](images/2663e841eb507b8b01772c53173474fbe5f930b349bfee21d539d8c118e6b82b.jpg) \nFigure 4.  Electrochemical performance of different Co-ZIF derived catalysts. a) Steady-state ORR polarization plots for the best performing 20Co-NC1100, state-of-the-art Fe–N–C (0.5 m ${\\mathsf{H}}_{2}{\\mathsf{S O}}_{4})$ ), and $\\mathsf{P t}/\\mathsf{C}$ $:(0.7\\mathrm{~M~HClO_{4}})$ . b) ORR polarization plots on catalyst with various Co doping contents and c) the “volcano plot” correlation between Co doping and activity reflected by the current density at $0.8{\\mathrm{V}}.$ d) ORR polarization of Co-NC catalysts synthesized at various temperatures. e) Potential cycling (0.6–1.0 V) stability in $\\mathsf{O}_{2}$ -saturated $0.5\\mathrm{~m~}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and $\\mathsf{f})$ constant potential stability at $0.7\\mathrm{V}$ (current density is cathodic and negative). Catalyst loading for Co-NC was $0.8~\\mathsf{m g}~\\mathsf{c m}^{-2}$ . Pt loading was $60~{\\upmu\\up g_{\\mathsf{P t}}}~{\\mathsf{c m}}^{-2}$ . $\\displaystyle\\mathbf{g}_{-}\\mathbf{\\dot{l}})$ Catalyst particles and atomic Co sites are retained after potential cycling tests. \n\nThe Co doping content in the ZIF precursors and the heating temperature were varied to determine their role in governing catalyst performance. Figure 4a shows the ORR activity of the best performing 20Co-NC-1100 with optimal doping $20\\mathrm{~at\\%~}$ Co in total metals Co and $Z\\mathrm{n}$ ) and heating temperature $(1100~^{\\circ}\\mathrm{C})$ , compared to a traditional Fe–N–C catalyst prepared from polyaniline (PANI)[11] and a $\\mathrm{Pt/C}$ catalyst $(60~\\upmu\\mathrm{g}_{\\mathrm{Pt}}~\\mathrm{cm}^{-2})$ . The 20Co-NC-1100 catalyst exhibited an onset potential $[E_{\\mathrm{onset}},$ defined as the current density reaches $0.1\\mathrm{\\mA\\cm^{-2}},$ ) and an $E_{1/2}$ of 0.93 and $0.80\\mathrm{~V~}$ vs RHE, respectively, which was similar to the PANI-Fe-C catalyst.[11] To the best of our knowledge, this is the highest ORR activity achieved with a $\\scriptstyle\\mathrm{Co-N-C}$ catalyst in challenging acidic media. To elucidate the correlation between Co doping and corresponding activity, \n\nORR steady-state polarization plots were recorded as a function of Co content doped into the ZIF precursors (Figure 4b). The catalyst derived from ZIF-8 without Co doping (NC-1100) exhibited poor activity, which was similar to “metal-free” carbon catalyst reported before.[20,56,57] This suggests that remaining $Z\\mathrm{n}$ in catalyst plays insignificant role in facilitating ORR activity. The catalytic activity increased continuously with increasing Co doping up to $20a\\%$ , confirming that the formed $\\mathrm{CoN}_{4}$ sites play a key role in enhancing ORR activity in acidic media. However, further increasing the Co content in the precursors up to $30\\%$ , causing a decrease in ORR catalytic activity with a negative shift of $60~\\mathrm{mV}$ in $E_{1/2}$ and a reduced limiting current density. Interestingly, the effect of Co doping content on ORR activity follows a so-called “volcano plot.” Lower doping yields insufficient density of active sites (Figure 4c), while higher doping leads to Co agglomeration and unfavorable carbon structures (i.e., less defect and porosity). Notably, an optimal doping content of $20\\%$ corresponds to the largest $\\mathrm{Co}/\\mathrm{N}$ ratio close to 1.0 and the highest N content. This suggests that maximum atomic Co sites coordinated with $\\mathrm{\\DeltaN}$ generate largest density of active sites with the best activity. The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield was also measured using rotating ring-disk electrode (RRDE) to determine the four-electron selectivity during the ORR (Figure S10, Supporting Information). The Co-free NC-1100 showed the highest peroxide yield $(\\approx30\\%)$ among all catalysts, indicating a dominant two-electron ORR pathway. With the addition of Co, the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yields are significantly reduced especially for the 20Co-NC-1100 catalyst exhibiting the lowest peroxide yield of around $5\\%$ and indicating much improved four-electron selectivity. \n\nUsing the optimal Co doping $(20\\ a t\\%)$ , we further determined the effect of thermal activation temperatures ranging from 600 to $1100~^{\\circ}\\mathrm{C}$ on the ORR activity (Figure 4d). There was no measurable ORR activity until the heating temperature is increased to $800~^{\\circ}\\mathrm{C}$ in acid media. It reveals that $800~^{\\circ}\\mathrm{C}$ is the minimum required temperature to activate Co-doped ZIF precursors and form $\\mathrm{CoN}_{4}$ active sites embedded into electrically conductive carbon, which is in good agreement with XAS and XPS results. Continuously increasing temperatures lead to enhanced ORR activity up to $1100~^{\\circ}\\mathrm{C}$ , indicating an increase in the number of active sites in catalysts. Notably, dependences of ORR activity on the temperature and Co-doping content are found different between acidic and alkaline media (Figure S11, Supporting Information), strongly suggesting different active sites and reaction mechanism in various $\\mathrm{\\pH}$ environments. \n\nWe have developed a unique capability to tune the catalyst particle sizes by controlling the sizes of Co-doped ZIF precursor crystals, in which ORR activity was found to be closely tied to them (Figure S12, Supporting Information). With particle size decreasing from 200 to $40\\mathrm{nm}$ , ORR activity is increased in terms of continuously positive shifts of $E_{1/2}$ , indicating more exposed active sites for the ORR. However, when further reducing particle size to $20~\\mathrm{nm}$ , the ORR activity decreased dramatically because of the agglomeration of fused particles with diminished active sites and hindered mass transfer (Figure $\\mathbf{S6g,h}$ Supporting Information). The unique capability of size control for PGM-free carbon catalysts can provide a new opportunity to enhance ORR activity through engineering catalyst particle morphology. \n\nStability of the $\\scriptstyle\\mathrm{Co-N-C}$ catalysts was evaluated by using both potential cycling $(0.6{-}1.0\\mathrm{~V},\\ 50\\mathrm{~mV~}\\mathrm{s}^{-1})$ and chronoamperometry at $0.7~\\mathrm{V}$ in $\\mathrm{O}_{2}$ -saturated $0.5\\mathrm{~M~}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ . The best performing 20Co-NC-1100 catalyst demonstrated significantly enhanced stability, only a loss of $30~\\mathrm{mV}$ in $\\displaystyle{E_{1/2}}$ after $10\\ 000$ cycles (Figure 4e), compared to a loss of $80~\\mathrm{mV}$ in $E_{1/2}$ for traditional PANI-derived Fe–N–C after 5000 cycles (Figure S13, Supporting Information). Furthermore, during chronoamperometry tests at a relatively high potential of $0.7~\\mathrm{V}$ up to $100\\mathrm{~h~}$ (Figure 4f), encouraging stability is achieved with $83\\%$ retention of initial activity. It should be noted that stability at relatively high potential $(>0.6\\:\\mathrm{V})$ remains a grand challenge for PGM-free catalysts, which typically suffer a rapid degradation,[58,59] likely due to carbon corrosion and dissolution of metal sites. The catalyst after potential cycling tests was further studied by using HADDF-STEM images as shown in Figure 4g–i and Figure S14 (Supporting Information). The 3D carbon architecture was retained after 10 000 cycles, indicating sufficient stability of carbon in the catalyst. The atomic dispersed Co sites were still clearly observed and located at the edge of carbon planes. The EELS at the atomic scale further verified the coexistence of Co and N, indicating good stability of the coordination between nitrogen and atomic Co sites during the ORR in acidic media. The signal of F detected in the catalyst by using EELS is due to the use of Nafion as the binder in electrodes for stability tests. \n\nFuel cell tests were further conducted to evaluate the best performing atomic Co catalyst (20Co-NC-1100) in terms of its feasibility to be a practical PGM-free cathode in PEMFCs. Membrane assembly electrodes (MEAs) with a total catalyst loading of $4.0\\mathrm{\\mg\\cm^{-2}}$ $(\\approx0.08\\mathrm{mg}_{\\mathrm{Co}}\\mathrm{cm}^{-2})$ were tested first by using $\\mathrm{H}_{2}/\\mathrm{O}_{2}$ to minimize mass-transport losses and accurately determine catalyst activity in the fuel cell environment (Figure 5a). The open-circuit voltage is up to $0.95~\\mathrm{V},$ which is comparable to conventional ketjenblack (KJ)-supported PANIderived Fe catalyst (PANI-Fe-KJ). The fuel cell performance for both catalysts at kinetic ranges $(>0.7~\\mathrm{V})$ is nearly identical as compared to their corresponding Tafel plots (Figure S15, Supporting Information). Moreover, significantly enhanced performance was observed for the 20Co-NC-1100 catalyst at lower voltages due to improved mass transfer. Meanwhile, compared to conventional PANI-Co-KJ catalysts, dramatic improvement at all voltage ranges was achieved with the new atomic Co catalysts. The $\\mathrm{H}_{2}/\\mathrm{O}_{2}$ fuel cell using 20Co-NC-1100 as cathode catalysts exhibited the highest power density of $0.56\\mathrm{W}\\mathrm{cm}^{-2}$ . This performance enhancement was further demonstrated when $\\mathrm{H}_{2}/\\mathrm{air}$ was used for fuel cell tests (Figure 5b), indicating favorable mass transfer and robust three-phase interfaces. The power density achieved by using $\\mathrm{H}_{2}/$ air cell is $0.28\\ensuremath{\\mathrm{~W~}}\\ensuremath{\\mathrm{cm}^{-2}}$ for the 20Co-NC-1100, much higher than both PANI-Fe-KJ and PANI-Co-KJ. \n\nPrevious performance durability tests of PGM-free catalysts in fuel cells were often performed at impractically low voltages of $0.4\\mathrm{-}0.5\\ \\mathrm{V},\\mathrm{\\Omega}^{[11,46,60]}$ Here, the durability of the 20Co-NC-1100 catalyst was carried out at fully viable voltage of $0.7\\mathrm{V}$ for $100\\mathrm{{h}}$ , using air feed to the cathode (Figure 5c). The voltage-current (VI) polarization plots were recorded during the durability test to monitor the possible degradation evolution (Figure 5d). At initial stage up to $30\\mathrm{h}$ , there are insignificant losses (less than $15~\\mathrm{mV})$ ) at all current density ranges, and a $^{100\\mathrm{~h~}}$ continuous operation eventually results in a loss around $60~\\mathrm{mV}.$ The performance loss is likely due to instability of either active sites or electrode structures. Thickness of the PGM-free cathode is up to $60~\\upmu\\mathrm{m}$ when a loading is $4.0\\ \\mathrm{mg\\cm^{-2}}$ . Within such a thick cathode, optimal structures with robust three-phase interfaces and facile mass transfer $(\\mathrm{H}^{+},\\ \\mathrm{O}_{2})$ and water removal are very crucial for performance durability. Compared to other studied PGM-free cathodes in fuel cells,[58,59] significant enhancement of performance durability of the atomic Co catalysts derived from ZIF at such a relatively high voltage (i.e., 0.7 V) is very encouraging. One of future focuses will be design and fabrication of optimal PGM-free electrodes for maximum power density and performance durability. \n\nIn summary, due to Fenton reagent issues resulting from Fe, the development of PGM-free catalysts that are also free of Fe is highly desirable for low-cost and durable PEMFCs. In this work, a high-performance atomically dispersed Co site catalyst was developed by using a facile one-step thermal activation of chemically doped ZIF precursors. The nitrogen-coordinated single atomic Co sites were virtually observed, for the first time, by using advanced HAADF-STEM images coupled with EELS at an atomic scale. X-ray absorption spectroscopy fitting further verified that the $\\mathrm{Co-N}$ coordination is in the form of $\\mathrm{CoN}_{4}$ . These experimental results provided strong evidence on the structures of active sites and verified theoretical simulation predicting $\\mathrm{CoN}_{4}$ active sites for the ORR. Using the homogeneous atomic Co catalysts as the model systems, we systematically varied Co doping contents and thermal activation temperatures during the synthesis, which further linked to the resulting catalyst structure, morphology, and activity. As a result, the correlation of synthesis–structure–property was established to provide valuable knowledge for advanced catalyst design and synthesis. Both rotating disk electrode in aqueous electrolyte and fuel cell tests with solid-state proton exchange membrane (i.e., Nafion) confirmed the high ORR performance of the atomic Co catalysts in challenging acidic media. In particular, an ever-recorded $E_{1/2}$ of $0.80\\mathrm{V}$ vs RHE in $0.5\\mathrm{~M~}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte was achieved, representing one of the best $\\scriptstyle\\mathrm{Co-N-C}$ catalysts (Table S1, Supporting Information) and nearly exceeding conventional Fe–N–C catalysts.[11] Although performance degradation still occurred at a relatively high potential/voltage of $0.7{\\mathrm{~V}},$ the atomic Co catalyst has exhibited significantly improved durability in both $0.5\\textrm{\\textmu}\\mathrm{H}_{2}\\mathrm{S}\\mathrm{O}_{4}$ and MEA cathode. The high performance is associated with the highly dispersed atomic $\\mathrm{CoN}_{4}$ sites embedded into porous and partially graphitized carbon, instead of the formation of inactive metallic aggregates enclosed into graphitized carbon shells/layers. The homogeneous morphology, which is very favorable for PGM-free catalysts, is due to structurally and chemically defined Co-doped ZIF nanocrystal precursors containing Co sties coordinated with aromatic N-containing ligands. The atomic Co catalyst with remarkably enhanced activity and stability holds a great promise to address the Fenton reagent issue associated with Fe in PGM-free catalysts for future PEMFC applications. \n\n![](images/102155436b94df97dc95a0deccfafe33745fc2cb688e224ae51f173dd4f06984.jpg) \nFigure 5.  Fuel cell performance before and after durability tests. a) ${\\sf H}_{2}\\mathrm{-}{\\sf O}_{2}$ fuel cell polarization plot: cathode $4.0~\\mathsf{m g}\\mathsf{c m}^{-2}$ ; $\\mathsf{O}_{2}200\\mathsf{m L}\\mathsf{m i n}^{-1}$ ; $100\\%$ RH; $275~\\mathsf{k P a}$ (30 psi) backpressure; anode: $0.2\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2}$ $\\mathsf{P t/C}$ ; $\\mathsf{H}_{2}200\\mathsf{m L}\\mathsf{m i n}^{-1}$ ; $100\\%$ RH; membrane: Nafion 212; cell: $80^{\\circ}C$ ; $5\\mathsf{c m}^{2}$ electrode area. b) $\\mathsf{H}_{2^{-}}$ –air fuel cell polarization plot: cathode $4.0~\\mathsf{m g}\\mathsf{c m}^{-2}$ ; air $200m L\\min^{-1}$ ; $100\\%$ RH; $275~\\mathsf{k P a}$ (30 psi); anode: $0.2\\mathrm{\\mg}_{\\mathrm{Pt}}\\mathrm{cm}^{-2}$ Pt/C; $\\mathsf{H}_{2}200\\mathsf{m L}\\mathsf{m i n}^{-1}$ ; $100\\%$ RH; 30 psi; membrane: N 212; cell: $80~^{\\circ}\\mathsf{C};$ ; $5\\mathsf{c m}^{2}$ electrode area. c) $\\mathsf{100~h}$ durability test under $\\mathsf{H}_{2}.$ –air conditions at 0.7 V, $\\mathsf{l}50\\mathsf{k P a}$ (10.5 psi). d) ${\\sf H}_{2}\\mathrm{-}{\\sf O}_{2}$ polarization plots before and after the $\\mathsf{\\Omega}_{\\mathsf{l o0}\\mathsf{h}}$ life test at $0.7\\:\\mathrm{V}.$ \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThis work is financially supported from the start-up funding from the University at Buffalo, SUNY, National Science Foundation (CBET-1604392), and U.S. DOE-EERE Fuel Cell Technologies Office. Electron microscopy research was conducted at the Center for Nanophase Materials Sciences of Oak Ridge National Laboratory and the Center for Functional Nanomaterials at Brookhaven National Laboratory under Contract No. DE-SC0012704, which both are DOE Office of Science User Facilities. XAS measurements were performed at 9BM-C and 4ID-C at Advanced Photon Source of Argonne National Laboratory with support of Department of Energy under Contract No. DE-AC02-06CH11357. Z. Feng thanks the Callahan Faculty Scholar Endowment Fund from Oregon State University. X. X. Wang thanks the Shanghai Natural Science Foundation of China under Contract No. 16ZR1408600. We also thank Shiva Gupta for part of SEM analysis. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\ncarbon nanocomposites, electrocatalysis, oxygen reduction, proton exchange membrane fuel cells, single atomic Co \n\nReceived: November 19, 2017 \nRevised: December 10, 2017 \nPublished online: January 24, 2018 \n\n[1]\t H. A. Gasteiger, N. M. Markovic´, Science 2009, 324, 48. \n[2]\t G. Wu, P. Zelenay, Acc. Chem. Res. 2013, 46, 1878. \n[3]\t H.  Zhang, H.  Osgood, X.  Xie, Y.  Shao, G.  Wu, Nano Energy 2017, 31, 331. \n[4]\t N. R.  Sahraie, U. I.  Kramm, J.  Steinberg, Y.  Zhang, A.  Thomas, T.  Reier, J. P.  Paraknowitsch, P.  Strasser, Nat. Commun. 2015, 6, 8618. \n[5]\t X.  Yan, K.  Liu, T.  Wang, Y.  You, J.  Liu, P.  Wang, X.  Pan, G.  Wang, J. Luo, J. Zhu, J. Mater. Chem. A 2017, 5, 3336. [6]\t H.  Peng, F.  Liu, X.  Liu, S.  Liao, C.  You, X.  Tian, H.  Nan, F.  Luo, H. Song, Z. Fu, P. Huang, ACS Catal. 2014, 4, 3797. [7]\t Y. J. Sa, D. J. Seo, J. Woo, J. T. Lim, J. Y. Cheon, S. Y. Yang, J. M. Lee, D.  Kang, T. J.  Shin, H. S.  Shin, H. Y.  Jeong, C. S.  Kim, M. G.  Kim, T. Y. Kim, S. H. Joo, J. Am. Chem. Soc. 2016, 138, 15046. [8]\t C. Walling, Acc. Chem. Res. 1975, 8, 125. [9]\t S. F. Kang, H M. Chang, Water Sci. Technol. 1997, 36, 215. \n[10]\t J.  Masa, A.  Zhao, W.  Xia, M.  Muhler, W.  Schuhmann, Electrochim. Acta 2014, 128, 271. \n[11]\t G.  Wu, K. L.  More, C. M.  Johnston, P.  Zelenay, Science 2011, 332, 443. \n[12]\t Z. S.  Wu, L.  Chen, J.  Liu, K.  Parvez, H.  Liang, J.  Shu, H.  Sachdev, R. Graf, X. Feng, K. Müllen, Adv. Mater. 2014, 26, 1450. \n[13]\t X.  Zhang, R.  Liu, Y.  Zang, G.  Liu, G.  Wang, Y.  Zhang, H.  Zhang, H. Zhao, Chem. Commun. 2016, 52, 5946. \n[14]\t P.  Subramanian, R.  Mohan, A.  Schechter, ChemCatChem 2017, 9, 1969. \n[15]\t G.  Wu, K. L.  More, P.  Xu, H.-L.  Wang, M.  Ferrandon, A. J.  Kropf, D. J.  Myers, S.  Ma, C. M.  Johnston, P.  Zelenay, Chem. Commun. 2013, 49, 3291. \n[16]\t X. Wang, H. Fu, W. Li, J. Zheng, X. Li, RSC Adv. 2014, 4, 37779. \n[17]\t Q.  Wang, W. H.  Hu, Y. M.  Huang, ChemistrySelect 2017, 2, 3191. \n[18]\t X.  Wang, X.  Fan, H.  Lin, H.  Fu, T.  Wang, J.  Zheng, X.  Li, RSC Adv. 2016, 6, 37965. \n[19]\t S. Chao, Z. Bai, Q. Cui, H. Yan, K. Wang, L. Yang, Carbon 2015, 82, 77. \n[20]\t L.  Chen, X.  Cui, M.  Wang, Y.  Du, X.  Zhang, G.  Wan, L.  Zhang, F. Cui, C. Wei, J. Shi, Langmuir 2015, 31, 7644. \n[21]\t B.  You, N.  Jiang, M.  Sheng, W. S.  Drisdell, J.  Yano, Y.  Sun, ACS Catal. 2015, 5, 7068. \n[22]\t X.  Wang, J.  Zhou, H.  Fu, W.  Li, X.  Fan, G.  Xin, J.  Zheng, X.  Li, J. Mater. Chem. A 2014, 2, 14064. \n[23]\t A. Aijaz, N. Fujiwara, Q. Xu, J. Am. Chem. Soc. 2014, 136, 6790. \n[24]\t B.  Liu, H.  Shioyama, T.  Akita, Q.  Xu, J. Am. Chem. Soc. 2008, 130, 5390. \n[25]\t H. Wang, Q.-L. Zhu, R. Zou, Q. Xu, Chem 2017, 2, 52. \n[26]\t H.  Tang, S.  Cai, S.  Xie, Z.  Wang, Y.  Tong, M.  Pan, X.  Lu, Adv. Sci. 2016, 3, 1500265. \n[27]\t H. Furukawa, K. E. Cordova, M. O’Keeffe, O. M. Yaghi, Science 2013, 341. \n[28]\t X. Li, Q. Jiang, S. Dou, L. Deng, J. Huo, S. Wang, J. Mater. Chem. A 2016, 4, 15836. \n[29]\t J.  Cravillon, S.  Münzer, S.-J.  Lohmeier, A.  Feldhoff, K.  Huber, M. Wiebcke, Chem. Mater. 2009, 21, 1410. \n[30]\t V.  Armel, S.  Hindocha, F.  Salles, S.  Bennett, D.  Jones, F.  Jaouen, J. Am. Chem. Soc. 2017, 139, 453. \n[31]\t S. Ma, G. A. Goenaga, A. V. Call, D.-J. Liu, Chem. – Eur. J. 2011, 17, 2063. \n[32]\t B. Y.  Guan, X. Y.  Yu, H. B.  Wu, X. W. D.  Lou, Adv. Mater. 2017, 29, 1703614. \n[33]\t P. Yin, T. Yao, Y. Wu, L. Zheng, Y. Lin, W. Liu, H. Ju, J. Zhu, X. Hong, Z. Deng, Angew. Chem., Int. Ed. 2016, 55, 10800. \n[34]\t J. Long, R. Li, X. Gou, Catal. Commun. 2017, 95, 31. \n[35]\t Q.  Cheng, L.  Yang, L.  Zou, Z.  Zou, C.  Chen, Z.  Hu, H.  Yang, ACS Catal. 2017, 7, 6864. \n[36]\t W.  Liu, L.  Zhang, W.  Yan, X.  Liu, X.  Yang, S.  Miao, W.  Wang, A. Wang, T. Zhang, Chem. Sci. 2016, 7, 5758. \n[37]\t H.  Fei, J.  Dong, M. J.  Arellanojiménez, G.  Ye, N. D.  Kim, E. L. G.  Samuel, Z.  Peng, Z.  Zhu, Q.  Fan, J.  Bao, Nat. Commun. 2015, 6, 8668. \n[38]\t X. Sun, K. Li, C. Yin, Y. Wang, M. Jiao, F. He, X. Bai, H. Tang, Z. Wu, Carbon 2016, 108, 541. \n[39]\t A.  Zitolo, N. R.  Sahraie, T.  Mineva, J.  Li, Q.  Jia, S.  Stamatin, G. F.  Harrington, S. M.  Lyth, P.  Krtil, S.  Mukerjee, E.  Fonda, F. Jaouen, Nat. Commun. 2017, 8, 957. \n[40]\t Z. Xiang, Y. Xue, D. Cao, L. Huang, J. F. Chen, L. Dai, Angew. Chem., Int. Ed. 2014, 53, 2433. \n[41]\t S. Surnev, M. Ramsey, F. Netzer, Prog. Surf. Sci. 2003, 73, 117. \n[42]\t B. Kilos, A. T. Bell, E. Iglesia, J. Phys. Chem. C 2009, 113, 2830. \n[43]\t D.  Carta, M. F.  Casula, A.  Falqui, D.  Loche, G.  Mountjoy, C. Sangregorio, A. Corrias, J. Phys. Chem. C 2009, 113, 8606. \n[44]\t Z.  Feng, Q.  Ma, J.  Lu, H.  Feng, J.  Elam, P. C.  Stair, M.  Bedzyk, RSC Adv. 2015, 5, 103834. \n[45]\t Y.  Wu, J.  Jiang, Z.  Weng, M.  Wang, D. l. L.  Broere, Y.  Zhong, G. W. Brudvig, Z. Feng, H. Wang, ACS Cent. Sci. 2017, 3, 847. \n[46]\t G. Wu, C. M. Johnston, N. H. Mack, K. Artyushkova, M. Ferrandon, M.  Nelson, J. S.  Lezama-Pacheco, S. D.  Conradson, K. L.  More, D. J. Myers, J. Mater. Chem. 2011, 21, 11392. \n[47]\t J. M.  Ziegelbauer, T. S.  Olson, S.  Pylypenko, F.  Alamgir, C.  Jaye, P. Atanassov, S. Mukerjee, J. Phys. Chem. C 2008, 112, 8839. \n[48]\t Y.  Han, Y. G.  Wang, W.  Chen, R.  Xu, L.  Zheng, J.  Zhang, J.  Luo, R. A. Shen, Y. Zhu, W. C. Cheong, C. Chen, Q. Peng, D. Wang, Y. Li, J. Am. Chem. Soc. 2017, 139, 17269. \n[49]\t J. Han, Y. J. Sa, Y. Shim, M. Choi, N. Park, S. H. Joo, S. Park, Angew. Chem., Int. Ed. 2015, 54, 12622. \n[50]\t A. M. Hibberd, H. Q. Doan, E. N. Glass, F. M. De Groot, C. L. Hill, T. Cuk, J. Phys. Chem. C 2015, 119, 4173. \n[51]\t H.  Adler, M.  Paszkiewicz, J.  Uihlein, M.  Polek, R.  Ovsyannikov, T. V.  Basova, T.  Chassé, H.  Peisert, J. Phys. Chem. C 2015, 119, 8755. \n[52]\t G. R. Iyer, P. D. Maguire, J. Mater. Chem. 2011, 21, 16162. \n[53]\t Y.-Z. Chen, C. Wang, Z.-Y. Wu, Y. Xiong, Q. Xu, S.-H. Yu, H. L. Jiang, Adv. Mater. 2015, 27, 5010. \n[54]\t H.  Zhang, S.  Hwang, M.  Wang, Z.  Feng, S.  Karakalos, L.  Luo, Z.  Qiao, X.  Xie, C.  Wang, D.  Su, Y.  Shao, G.  Wu, J. Am. Chem. Soc. 2017, 139, 14143. \n[55]\t G. Wu, N. H. Mack, W. Gao, S. Ma, R. Zhong, J. Han, J. K. Baldwin, P. Zelenay, ACS Nano 2012, 6, 9764. \n[56]\t Q. L.  Zhu, W.  Xia, T.  Akita, R.  Zou, Q.  Xu, Adv. Mater. 2016, 28, 6391. \n[57]\t Q.-L.  Zhu, W.  Xia, L.-R.  Zheng, R.  Zou, Z.  Liu, Q.  Xu, ACS Energy Lett. 2017, 2, 504. \n[58]\t G.  Wu, K.  Artyushkova, M.  Ferrandon, A. J.  Kropf, D.  Myers, P. Zelenay, ECS Trans. 2009, 25, 1299. \n[59]\t M.  Ferrandona, X.  Wang, A. J.  Kropfa, D. J.  Myersa, G.  Wu, C. M.  Johnston, P.  Zelenay, Electrochim. Acta 2013, 110, 282. \n[60]\t M.  Lefèvre, E.  Proietti, F.  Jaouen, J. P.  Dodelet, Science 2009, 324, 71. " + }, + { + "id": "10.1126_science.aaq1479", + "DOI": "10.1126/science.aaq1479", + "DOI Link": "http://dx.doi.org/10.1126/science.aaq1479", + "Relative Dir Path": "mds/10.1126_science.aaq1479", + "Article Title": "3D charge and 2D phonon transports leading to high out-of-plane ZT in n-type SnSe crystals", + "Authors": "Chang, C; Wu, MH; He, DS; Pei, YL; Wu, CF; Wu, XF; Yu, HL; Zhu, FY; Wang, KD; Chen, Y; Huang, L; Li, JF; He, JQ; Zhao, LD", + "Source Title": "SCIENCE", + "Abstract": "Thermoelectric technology enables the harvest of waste heat and its direct conversion into electricity. The conversion efficiency is determined by the materials figure of merit ZT. Here we show a maximum ZT of similar to 2.8 +/- 0.5 at 773 kelvin in n-type tin selenide (SnSe) crystals out of plane. The thermal conductivity in layered SnSe crystals is the lowest in the out-of-plane direction [two-dimensional (2D) phonon transport]. We doped SnSe with bromine to make n-type SnSe crystals with the overlapping interlayer charge density (3D charge transport). A continuous phase transition increases the symmetry and diverges two converged conduction bands. These two factors improve carrier mobility, while preserving a large Seebeck coefficient. Our findings can be applied in 2D layered materials and provide a new strategy to enhance out-of-plane electrical transport properties without degrading thermal properties.", + "Times Cited, WoS Core": 960, + "Times Cited, All Databases": 1009, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000432473500046", + "Markdown": "# THERMOELECTRICS \n\n# 3D charge and 2D phonon transports leading to high out-of-plane ZT in n-type SnSe crystals \n\nCheng Chang,1 Minghui Wu,2 Dongsheng He,2 Yanling Pei,1 Chao-Feng Wu,3 Xuefeng Wu,2 Hulei $\\mathbf{Y}\\mathbf{u}$ ,4 Fangyuan $\\mathbf{z}\\mathbf{h}\\mathbf{u}$ ,5 Kedong Wang,2 Yue Chen,4 Li Huang,2 Jing-Feng Li,3 Jiaqing $\\mathbf{He,^{2\\ast}}$ Li-Dong Zhao1\\* \n\nThermoelectric technology enables the harvest of waste heat and its direct conversion into electricity. The conversion efficiency is determined by the materials figure of merit ZT. Here we show a maximum ZT of $-2.8\\pm0.5$ at 773 kelvin in n-type tin selenide (SnSe) crystals out of plane. The thermal conductivity in layered SnSe crystals is the lowest in the out-of-plane direction [two-dimensional (2D) phonon transport]. We doped SnSe with bromine to make n-type SnSe crystals with the overlapping interlayer charge density (3D charge transport). A continuous phase transition increases the symmetry and diverges two converged conduction bands. These two factors improve carrier mobility, while preserving a large Seebeck coefficient. Our findings can be applied in 2D layered materials and provide a new strategy to enhance out-of-plane electrical transport properties without degrading thermal properties. \n\nhermoelectric technology, which converts T heat into electricity, provides a promising T route to environmentally friendly power generation through the harvest of industrial waste heat $(\\boldsymbol{I},2)$ . The conversion efficiency of thermoelectric materials is determined by the dimensionless figure of merit $Z T=[(S^{2}\\upsigma)/\\upkappa]T,$ , where $S,\\upsigma,\\upkappa,$ and $T$ are the Seebeck coefficient, electrical conductivity, thermal conductivity, and absolute temperature, respectively. However, the complex interrelationships among thermoelectric parameters prevent us from maximizing the $Z T$ value and conversion efficiency (3, 4). To date, various approaches have been adopted to optimize these critical thermoelectric parameters, such as enhancing the electrical transport properties (power factor, $S^{2}\\upsigma,$ ) through engineering band structures (5–7), lowering the thermal conductivity through scattering all-scale length phonons $(\\boldsymbol{\\delta})$ , and seeking potential materials with low thermal conductivity $(9,{\\cal I O})$ . Impressive achievements have been made in various thermoelectric systems on the basis of these strategies, including bismuth $(I I)$ , lead (8, 12), tin (13) and copper $(I4)$ chalcogenides; germanium silicides $(I5)$ ; Zintl phase (16); skutterudite $(I7)$ ; half-Heusler (18); and magnesium-based systems (19–21). \n\nOver the past decade, bulk crystals with twodimensional (2D) layered structures have been studied because of their strongly anisotropic transport features. High thermoelectric performance along the in-plane direction was primarily achieved by improving charge-carrier mobility (22–24). However, the out-of-plane properties have garnered less attention because electrical transport is always impeded by the 2D interlayers. Outof-plane thermal conductivities in 2D layered materials are sufficiently low enough that they approach the amorphous limit (25, 26). Enhancing the out-of-plane electrical properties may result in excellent thermoelectric performance in this direction. \n\nVery low thermal conductivity due to strong anharmonic and anisotropic bonding was found along the in-plane direction of p-type SnSe crystals with a 2D layered structure (27–29). After hole doping, SnSe shows an exceptionally high power factor enabled by its multiple valence bands (28, 30). These results reveal that p-type SnSe is a remarkable compound with promising thermoelectric performance. However, the discrepancy of in-plane thermal conductivity observed in fully dense SnSe crystals seems to conclude that the thermal conductivity was underestimated owing to low sample density (31). On the contrary, the ultralow thermal conductivity observed in the fully dense SnSe crystals revealed the story to be more complicated (32). The continued reports elucidate the thermal conductivity discrepancy, clarifying that the low thermal conductivity in SnSe is sensitive to the vast off-stoichiometric defects (33), much softer van der Waals–like Se–Sn bonding (34), polycrystalline oxidations (35), crystal cracks (36), and so on. These investigations on in-plane thermal conductivity are enriching the physical and chemical stories behind SnSe. \n\nCompared to its in-plane thermal conductivity, SnSe exhibits a more steady and even lower thermal conductivity along the out-of-plane direction (27, 28, 32), which motivated us to investigate its power factor. We synthesized n-type SnSe crystals through the temperature gradient method and bromine doping (figs. S1 and S2). We found that the conduction bands of n-type SnSe have much more complex behavior owing to a temperature-dependent continuous phase transition from Pnma to Cmcm, which leads to an outstanding temperature-independent power factor and a maximum $Z T(Z T_{\\operatorname*{max}})$ of ${\\sim}2.8$ at $773\\mathrm{~K~}$ along the out-of-plane direction. We obtained independent tests from third-party inspection institutions to verify the high performance and reproducibility [Fig. 1A, green line (37)]. \n\n![](images/7f088e6e488ea5eb60d8c7e93b126d6a743760cd333f2dd8c055a4730bf991ab.jpg) \nFig. 1. ZT values as a function of temperature and a schematic of phonon and charge transport in n- and $p$ -type SnSe crystals along the out-of-plane direction. (A) ZT values for p- and n-type SnSe with and without phase transition; the high performance of n-type SnSe is well reproduced by third parties (green line, test reports are provided in the supplementary materials). Inset images show the SnSe crystal structure (blue, Sn atoms; red, Se atoms) with the investigated out-of-plane direction. The typical sample cleaved along the (100) plane and the diagram show how the crystals are cut for measurements (inset images, from left to right). 1.2E19, carrier concentration of $\\sim1.2\\times10^{19}~\\mathsf{c m}^{-3}$ . (B) Schematic out-of-plane charge and phonon transports in n- and p-type SnSe. The colored dots represent the charge densities. The gray blocks represent the two-atom-thick SnSe slabs along the out-of-plane direction (a axis) of SnSe. \n\n![](images/73f274efec2cb13479d9fb823fcb5f1b908a79c467615fce751bb137a4e192e2.jpg) \nFig. 2. Thermoelectric properties as a function of temperature for the out-of-plane n- and p-type SnSe crystals. \n(A) Electrical conductivity. (B) Seebeck coefficient. (C) Power factor (PF). (D) Hall carrier concentrations and (E) carrier mobilities, where both insets compare n- and p-type SnSe. (F) Total and lattice thermal conductivities. The dashed black line is the out-of-plane minimum lattice thermal conductivity. The reproduced data provided by third parties (green lines) for the high-performance n-type SnSe are also plotted for comparison. \n\nThe high performance we achieved for n-type SnSe is explained by two cumulative features. First, density functional theory (DFT) calculations and scanning tunneling microscopy (STM) observations indicate that delocalized Sn and Se p electrons near the conduction band minimum (CBM) contribute to more orbital overlap along the out-of-plane direction. When the carrier concentration is fixed at $\\sim1.2\\times10^{19}\\mathrm{cm}^{-3}$ , in contrast to p-type SnSe, the charge density of n-type SnSe overlaps to fill the crystal-structure interlayers. The overlapped charge density can facilitate electron transport through the interlayers, resulting in an expected $Z T_{\\mathrm{max}}$ of ${\\sim}2.1$ at $773\\mathrm{~K~}$ for n-type SnSe. By contrast, the $Z T_{\\mathrm{max}}$ is ${\\sim}0.5$ at $773\\mathrm{K}$ for p-type SnSe (Fig. 1A). Second, high-temperature synchrotron radiation x-ray diffraction (SR-XRD) indicates a continuous phase transition from Pnma to Cmcm starting at $\\mathord{\\sim}600\\mathrm{~K~}$ before the critical temperature $(800\\mathrm{K})$ in SnSe. This apparently continuous phase transition in n-type SnSe leads to an increased symmetry in the crystal structure, which is further confirmed by in situ spherical aberration–corrected transmission electron microscopy (Cs-corrected TEM). This phase transition also results in the divergence of two converged conduction bands at $\\sim600\\mathrm{K}$ . In contrast to the band convergence, the band divergence decreases the average inertial band mass and thus leads to higher carrier mobility. The changes in the band structure due to the continuous phase transition further increase $Z T_{\\mathrm{max}}$ from 2.1 to 2.8 at 773 K (Fig. 1A). Collectively, our findings show that the out-of-plane electrical transport properties in n-type SnSe are comparable to those along the in-plane direction (3D charge transport) (Fig. 1B), which has rarely been observed in bulk materials with a 2D structure (38, 39). For comparison, we measured thermoelectric properties as a function of temperature along the in-plane and out-of-plane directions for both p- and n-type SnSe crystals (fig. S3). \n\nTo clarify the origin of the huge difference in the out-of-plane thermoelectric performance between the n- and p-type SnSe crystals, we compared the transport properties of the n- and p-type SnSe crystals with the same carrier concentration of $\\mathrm{\\sim1.2\\times10^{19}c m^{-3}}$ (abbreviated 1.21E19, Fig. 2). The electrical conductivity of n-type SnSe is twofold higher than that of p-type SnSe (Fig. 2A), indicating a twofold-higher carrier mobility. At room temperature, the Seebeck coefficient of approximately $-180~\\upmu\\mathrm{V}~\\mathrm{K}^{-1}$ for n-type SnSe is lower than that of p-type SnSe, which is $+210\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ (Fig. 2B), indicating a lower effective mass for the n-type crystal. Interestingly, with an increasing temperature, the magnitude of the n-type Seebeck coefficient increases faster and higher than the p-type Seebeck coefficients above ${\\sim}600\\mathrm{~K~}$ This indicates that the conduction band structure is much more complex than that of the valence bands as the temperature increases (28). The power factor for p-type SnSe declines monotonically with rising temperature. By contrast, the power factor for n-type SnSe preserves a high value of $\\sim9.0~\\upmu\\mathrm{W}\\ \\mathrm{cm}^{-1}\\ \\mathrm{K}^{-2}$ over the entire temperature range. Finally, the power factor at $773\\mathrm{K}$ for n-type SnSe is five times that of p-type SnSe (Fig. 2C). The carrier concentrations for n-type SnSe show a decreasing trend with increasing temperature (Fig. 2D) and a more pronounced decline than those of p-type SnSe (Fig. 2D, inset), which is consistent with the higher carrier mobility in n-type SnSe (Fig. 2E, inset). Particularly, a distinct rise in the carrier mobility above $\\sim600~\\mathrm{K}$ is observed in all n-type SnSe with different carrier concentrations (Fig. 2E), which contributes to higher electrical transport properties above $600~\\mathrm{K}.$ The strong anharmonic and anisotropic bonding of SnSe leads to very low thermal conductivity (27, 28, 32, 40), which is expected to be even lower along the out-of-plane direction of SnSe owing to strong interlayer phonon scattering. Indeed, both the total and lattice thermal conductivities $\\bf\\tilde{\\Phi}_{\\mathrm{{K}_{\\mathrm{{tot}}}}}$ and $\\upkappa_{\\mathrm{lat}})$ along the out-of-plane direction for both the n- and p-type SnSe crystals are extremely low (Fig. 2F and fig. S4), which even reach a minimum lattice thermal conductivity $(\\kappa_{\\mathrm{lat}}^{\\mathrm{min}})$ as low as 0.18 $\\mathbf{W\\mathbf{m}^{-1}\\mathbf{K}^{-1}}$ at 773 K. These thermoelectric transport properties show good reproducibility by varying the carrier concentration (figs. S5 and S6). Moreover, the highest performance also shows good thermal stability upon temperature changes (fig. S7) and excellent reproducibility through cross-checking in independent inspections [Fig. 2, A to C and F (37)]. \n\nThe twofold-higher n-type out-of-plane electrical conductivity originates from the higher carrier mobility, which indicates that electron transport is facilitated through the interlayers. We investigated the charge density for both types of SnSe along both the out-of-plane (ab plane) and in-plane (bc plane) directions to determine the origins of the high carrier mobility (Fig. 3A). We investigated the density of states (DOS) near the band edges through DFT calculations [Fig. 3B, (37)]. Our calculations reveal that the anisotropies of the charge density in nand p-type SnSe are dominated by the partial \n\nDOS of Sn (p) and Se (p), respectively. Specifically, in the valence band maximum (VBM), Se $(\\boldsymbol{\\mathrm{p}}_{z})$ largely contributes to the total DOS, whereas Sn $(\\mathfrak{p}_{x})$ predominately contributes to the total DOS in the CBM. These contributions indicate that the charge density tends to distribute within the in-plane direction in p-type SnSe and along the out-of-plane direction in n-type SnSe. Our DFT calculations further indicate the distinct overlaps of the electron orbitals in the out-of-plane direction of n-type SnSe, which form electrical conduction pathways (Fig. 3C). However, the charge densities mainly distribute along the in-plane direction in p-type SnSe (Fig. 3D). The features in n-type SnSe become more pronounced with increasing temperature (figs. S8 and S9). We further verify the charge-density differences between n- and p-type SnSe through scanning tunneling spectroscopy (STS) and STM images. The $\\mathrm{d}I/\\mathrm{d}V$ curves describe the partial DOS distributed along the kx direction (41), where $I$ is current and $V$ is voltage, which corresponds to the outof-plane direction in SnSe (Fig. 3E). The sharp slope near the CBM and gradual slope near the VBM are in good accordance with the DOS calculations (Fig. 3B). We visualized the charge density distribution in the bc plane using the contrast STM image and dI/dV mapping, where a large difference in charge density results in strong contrast. The low contrast in the images of n-type SnSe (Fig. 3, F and G) indicates an extended charge density distribution, whereas the stronger contrast in p-type SnSe (Fig. 3, H and I) shows a localized preference in the charge density distribution. This is consistent with the DFT calculations in the bc plane (Fig. 3, C and D). In summary, overlapping charge density fills the interlayers in n-type SnSe, explaining the high carrier mobility out of plane. By contrast, the charge density for p-type SnSe prefers to fill the in-plane intralayers (42, 43). \n\nThe dynamic structural behavior of SnSe at $800\\mathrm{~K~}$ involves a reversible phase transition from Pnma to Cmcm, and the highly symmetric Cmcm phase can enhance carrier mobility and preserve the high power factor of SnSe (44). To directly capture the structural evolution of SnSe as a function of temperature, we conducted in situ Cs-corrected TEM heating experiments for both n- and p-type SnSe. We tilted both samples along the [010] direction (Fig. 4A). The Sn and Se columns are displayed as brighter and dimmer dots, clearly resolved from the [010] direction. At room temperature, the SnSe unit cell consists of two SnSe bilayers with Se atoms in a different planes from the Sn atoms. This lowers the symmetry of the crystal structure. With an increasing temperature, the Se atoms gradually move closer to the nearest Sn layers in n-type SnSe. We quantitatively identified the atomic column positions with a peak-finding program (37) and used the $d/D$ ratio to determine symmetry (Fig. 4B), where $d$ and $D$ are the Se intralayer and Se interlayer distances, respectively (an intralayer corresponds to a two-atom-thick SnSe slab along the $a$ axis). Initially, the Se-Se layer distance follows a $d-D-d-D$ sequence along the out-of-plane direction, where $d$ and $D$ are approximately 0.25 and $0.34\\mathrm{nm}$ , respectively (figs. S10 to S12). After heating, in n-type SnSe, the $d/D$ ratio increases with increasing temperature, which indicates an increase in the symmetry (Fig. 4C). This behavior is particularly obvious above $\\sim600\\mathrm{~K~}$ for n-type SnSe. We observed the same phenomenon through hightemperature SR-XRD (fig. S13). We obtained lattice parameters (fig. S14) and atomic positions (tables S1 and S2) for a range of temperatures (37). The $d/D$ ratio we calculated from SR-XRD agrees with that from the in situ TEM, indicating the larger movement of Se atoms and thus higher symmetry in n-type SnSe. Collectively, the SR-XRD results indicate a continuous phase transition initializing at $\\sim600\\mathrm{K},$ , and the experimental Cs-corrected TEM observations confirmed that this continuous phase transition is much more pronounced in n-type SnSe. We believe enhanced carrier mobility is related to the high symmetry in the crystal structure of n-type SnSe. \n\nWe performed DFT calculations based on the temperature-dependent crystal structures (figs. S15 and S16) to clarify the Seebeck coefficient enhancements above $\\sim600~\\mathrm{K}$ in n-type SnSe. Our DFT calculations indicate that the lowest CBM lies in the G-Y direction (Fig. 5A, CBM1), whereas the second CBM is located at point G (Fig. 5A, CBM2). The energy offset for these two conduction bands is ${\\sim}0.10\\mathrm{eV}$ at room temperature, and as the temperature increases, the energy offset narrows and reaches a minimum value of ${\\sim}0.04~\\mathrm{eV}$ at about $600~\\mathrm{K}.$ Above this temperature, the energy gap sharply rises and then returns to ${\\sim}0.10~\\mathrm{eV}$ again at $773\\mathrm{~K~}$ (Fig. 5B). Converging band structures can enhance thermoelectric performance by enhancing the effective mass through introduction of additional band degeneracy $(N_{\\mathrm{v}})$ from heavy band contributions $(6,7)$ . However, increasing the effective mass usually deteriorates the carrier mobility (45). Distinct band structures are desirable if they can balance the effective mass and carrier mobility. We found that the conduction bands of n-type SnSe experience energy convergence and divergence within $0.10\\ \\mathrm{eV}$ as the temperature increases. We expect the conduction band divergence to improve the carrier mobility by reducing $N_{\\mathrm{v}}.$ . Indeed, the distinct conduction band structures in n-type SnSe lead to optimization of both the Seebeck coefficient and carrier mobility, which are critical to preserving a higher power factor (Fig. 2F). \n\n![](images/16bd9d5810824275bee537e5fdaf54084deedb22c0654dd629b21a3e7d47b6a3.jpg) \nFig. 3. Crystal structures, DOS, and charge density of n- and p-type SnSe. (A) Crystal structures of SnSe in the ab and bc planes. (B) Projected DOS of SnSe near the CBM and VBM $\\mathsf{\\Gamma}\\sim0.4\\ \\mathsf{e V}.$ . The Fermi level is shifted to zero. The inset diagram shows the Brillouin zone of SnSe. Calculated charge densities of (C) ${\\mathsf{n}}-$ and (D) p-type SnSe in the ab and bc planes, given by wave functions around ${\\sim}0.2\\ \\mathrm{eV}$ for the CBM and VBM, respectively. The color scale indicates the normalized charge density. (E) STS of the undoped, n-type, and p-type SnSe crystals. The spectra are vertically shifted for clarity. STM images and corresponding dI/dV mapping for the (F and G) $\\mathsf{n-}$ and (H and I) p-type SnSe crystals in the bc plane. Image sizes are $3\\mathsf{n m}$ by 3 nm. STM and dI/dV mapping are taken at sample biases of 0.4 and $-0.2\\ V$ for the n- and p-type SnSe crystals, respectively. \n\nTo investigate the Seebeck coefficient enhancements, we conducted Seebeck coefficient calculations as a function of carrier concentration at different temperatures on the basis of the single-band model (Fig. 5C). At room temperature, the experimentally observed Seebeck coefficients with different carrier concentrations concentration with rising temperature. The triangles are the experimental values, which are compared to the calculated values (string of purple squares) with the same carrier concentrations. Both the Seebeck coefficient and carrier mobility can be optimized through band convergence and divergence. The insets show the deviations of experimental and calculated Seebeck coefficient and carrier mobility as a function of temperature, with the blue regions indicating the temperature range before the conduction band divergence. \n\n![](images/02dcf7177acbc3e6bcf225e476fa00f55d3b93ae3ccaf125ee94c7f4205953c5.jpg) \nFig. 5. DFT-calculated band structures, Seebeck coefficients, and carrier mobilities of n-type SnSe with rising temperature. (A) Electronic band structures at 323, 473, 623, and $773\\ k.$ (B) The changing energy gap (DE) between CBM1 and CBM2 at elevated temperature. Inset diagram indicates that the two conduction bands experience convergence and then divergence with rising temperature. Comparisons of the experimental and calculated (C) Seebeck coefficients and (D) carrier mobilities as a function of carrier \n\nare consistent with the Pisarenko relation (fig. S17), which indicates that the single-band characteristics dominate carrier transport at low temperature. However, with rising temperature, the experimental Seebeck coefficients gradually deviate to higher values compared to the calculated Seebeck coefficients (Fig. 5C, inset). The deviation maximizes at $\\sim600~\\mathrm{K}$ , indicative of the greatest amount of band convergence. Above ${\\sim}600\\mathrm{K},$ the contribution of CBM2 declined owing to band divergence, leading to a smaller deviation between the experimental and calculated values, which agrees with the observed considerable rise in carrier mobility at about 600 K (Fig. 5D). Considering the band convergence, the experimentally observed Seebeck coefficients in the middle temperature range agree with the calculated results. Meanwhile, the notable carrier mobility rise is attributed to the band divergence, which occurs above $600~\\mathrm{K}$ . Interestingly, our results indicate that the continuous phase transition that starts at $600\\mathrm{~K~}$ can enhance the power factor and the final ZT value (fig. S18). \n\nUtilizing the ultralow thermal conductivity of out-of-plane SnSe along with an outstanding power factor, we realized a $Z T_{\\mathrm{max}}\\sim2.8$ at 773 K in out-of-plane n-type SnSe crystals. We initially selected the very low lattice thermal conductivity in the out-of-plane direction of SnSe crystals. Then, we optimized the carrier mobility and Seebeck coefficient by modifying the temperaturedependent crystal and band structures deriving from the continuous phase transition. Our results open prospects for new strategies to improve the out-of-plane electrical transport properties in 2D layered materials, while maintaining low thermal conductivity. \n\n# REFERENCES AND NOTES \n\n1. C. Uher, Ed., Materials Aspect of Thermoelectricity (CRC Press, 2017). 2. J. He, T. M. Tritt, Science 357, eaak9997 (2017). 3. X. Zhang, L. D. Zhao, J. Materiomics 1, 92–105 (2015). \n\n4. G. Tan, L. D. Zhao, M. G. Kanatzidis, Chem. Rev. 116, 12123–12149 (2016). \n5. J. P. Heremans et al., Science 321, 554–557 (2008). \n6. Y. Pei et al., Nature 473, 66–69 (2011). \n7. W. Liu et al., Phys. Rev. Lett. 108, 166601 (2012). \n8. K. Biswas et al., Nature 489, 414–418 (2012). \n9. D. T. Morelli, V. Jovovic, J. P. Heremans, Phys. Rev. Lett. 101, 035901 (2008). \n10. L. D. Zhao et al., Energy Environ. Sci. 7, 2900–2924 (2014). \n11. B. Poudel et al., Science 320, 634–638 (2008). \n12. K. F. Hsu et al., Science 303, 818–821 (2004). \n13. H. Wu et al., Energy Environ. Sci. 8, 3298–3312 (2015). \n14. H. Liu et al., Nat. Mater. 11, 422–425 (2012). \n15. N. Mingo, D. Hauser, N. P. Kobayashi, M. Plissonnier, A. Shakouri, Nano Lett. 9, 711–715 (2009). \n16. E. S. Toberer, A. F. May, G. J. Snyder, Chem. Mater. 22, 624–634 (2010). \n17. W. Zhao et al., Nature 549, 247–251 (2017). \n18. T. J. Zhu, C. G. Fu, H. H. Xie, Y. T. Liu, X. B. Zhao, Adv. Energy Mater. 5, 1500588 (2015). \n19. H. Zhao et al., Nano Energy 7, 97–103 (2014). \n20. J. Zhang et al., Nat. Commun. 8, 13901 (2017). \n21. J. Shuai et al., Energy Environ. Sci. 10, 799–807 (2017). \n22. N. Thu Huong et al., J. Alloys Compd. 368, 44–50 (2004). \n23. J. S. Rhyee et al., Nature 459, 965–968 (2009). \n24. I. Terasaki, Y. Sasago, K. Uchinokura, Phys. Rev. B 56, R12685–R12687 (1997). \n25. C. Chiritescu et al., Science 315, 351–353 (2007). \n26. C. Wan et al., Sci. Technol. Adv. Mater. 11, 044306 (2010). \n27. L. D. Zhao et al., Nature 508, 373–377 (2014). \n28. L. D. Zhao et al., Science 351, 141–144 (2016). \n29. C. W. Li et al., Nat. Phys. 11, 1063–1069 (2015). \n30. K. L. Peng et al., Energy Environ. Sci. 9, 454–460 (2016). \n31. P. C. Wei et al., Nature 539, E1–E2 (2016). \n32. A. T. Duong et al., Nat. Commun. 7, 13713 (2016). \n33. D. Wu et al., Nano Energy 35, 321–330 (2017). \n34. G. Li et al., Chem. Mater. 29, 2382–2389 (2017). \n35. Y. X. Chen et al., Adv. Funct. Mater. 26, 6836–6845 (2016). \n36. L. D. Zhao, C. Chang, G. Tan, M. G. Kanatzidis, Energy Environ. Sci. 9, 3044–3060 (2016). \n37. Materials, methods, and test reports are available as supplementary materials. \n38. Y. L. Pei, C. Zhang, J. Li, J. Sui, J. Alloys Compd. 566, 50–53 (2013). \n39. K. Biswas, L. D. Zhao, M. G. Kanatzidis, Adv. Energy Mater. 2, 634–638 (2012). \n40. C. C. Lin, R. Lydia, J. H. Yun, H. S. Lee, J. S. Rhyee, Chem. Mater. 29, 5344–5352 (2017). \n41. M. Iavarone et al., Phys. Rev. Lett. 89, 187002 (2002). \n42. K. Kutorasinski, B. Wiendlocha, S. Kaprzyk, J. Tobola, Phys. Rev. B 91, 205201 (2015). \n43. J. Yang, G. Zhang, G. Yang, C. Wang, Y. X. Wang, J. Alloys Compd. 644, 615–620 (2015). \n44. A. Dewandre et al., Phys. Rev. Lett. 117, 276601 (2016). \n45. Y. Pei, H. Wang, G. J. Snyder, Adv. Mater. 24, 6125–6135 (2012). \n\n# ACKNOWLEDGMENTS \n\nThe authors thank BL14B1 (Shanghai Synchrotron Radiation Facility) for the SR-XRD experiments. Funding: This work was supported by the National Natural Science Foundation of China (51571007, 51772012, 11474176, 51602143, 11574128, and 51788104), the Beijing Municipal Science and Technology Commission (Z171100002017002), the Shenzhen Peacock Plan team (KQTD2016022619565991), and the 111 Project (B17002). J.H. is grateful for the Pico Center at SUSTech, supported by the Presidential fund and Development and Reform Commission of Shenzhen Municipality, and also for support from the Natural Science Foundation of Guangdong Province (grant no. 2015A030308001), the leading talents of Guangdong Province Program (grant no. 00201517). H.Y. and Y.C. are grateful for financial support from the Early Career Scheme of the Research Grants Council (27202516). Author contributions: C.C. and L.-D.Z. synthesized the samples, designed and carried out the experiments, analyzed the results, and wrote the paper. M.W., H.Y., Y.C., and L.H. carried out the DFT calculations. C.-F.W. and J.-F.L. carried out the Hall measurements. J.-F.L. provided helpful discussion. X.W. and K.W. carried out STM and STS measurements. D.H. and J.H. conducted microscopy experiments and confirmed the thermoelectric transport properties. Y.P. confirmed the thermal transport properties. F.Z. and C.C. carried out the high-temperature SR-XRDs and Rietveld refinements. All authors conceived the experiments, analyzed the results, and coedited the manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: All data are available in the manuscript or the supplementary materials. Test reports are also available in the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/360/6390/778/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S18 \nTables S1 to S6 \nReferences (46–56) \n\n9 October 2017; resubmitted 26 October 2017 \nAccepted 30 March 2018 \n10.1126/science.aaq1479 \n\n# Science \n\n# 3D charge and 2D phonon transports leading to high out-of-plane ZT in n-type SnSe crystals \n\nCheng Chang, Minghui Wu, Dongsheng He, Yanling Pei, Chao-Feng Wu, Xuefeng Wu, Hulei Yu, Fangyuan Zhu, Kedong Wang, Yue Chen, Li Huang, Jing-Feng Li, Jiaqing He and Li-Dong Zhao \n\nScience 360 (6390), 778-783.DOI: 10.1126/science.aaq1479 \n\n# SnSe doped a different way \n\nHeat can be converted into electricity by thermoelectric materials. Such materials are promising for use in solid-state cooling devices. A challenge for developing efficient thermoelectric materials is to ensure high electrical but low thermal conductivity. Chang et al. found that bromine doping of tin selenide (SnSe) does just this by maintaining low thermal conductivity in the out-of-plane direction of this layered material. The result is a promising n-type thermoelectric material with electrons as the charge carriers−−an important step for developing thermoelectric devices from SnSe. \n\nScience, this issue p. 778 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1016_j.cpc.2018.05.010", + "DOI": "10.1016/j.cpc.2018.05.010", + "DOI Link": "http://dx.doi.org/10.1016/j.cpc.2018.05.010", + "Relative Dir Path": "mds/10.1016_j.cpc.2018.05.010", + "Article Title": "BoltzTraP2, a program for interpolating band structures and calculating semi-classical transport coefficients", + "Authors": "Madsen, GKH; Carrete, J; Verstraete, MJ", + "Source Title": "COMPUTER PHYSICS COMMUNICATIONS", + "Abstract": "BoltzTraP2 is a software package for calculating a smoothed Fourier expression of periodic functions and the Onsager transport coefficients for extended systems using the linearized Boltzmann transport equation. It uses only the band and k-dependent quasi-particle energies, as well as the intra-band optical matrix elements and scattering rates, as input. The code can be used via a command-line interface and/or as a Python module. It is tested and illustrated on a simple parabolic band example as well as silicon. The positive Seebeck coefficient of lithium is reproduced in an example of going beyond the constant relaxation time approximation. Program summary Program Title: Bolt zTraP2 Program Files doi: http://dx.doLorg/10.17632/bzb9byx8g8.1 Licensing provisions: GPLv3 Programming language: Python and C++ External routines/libraries: NumPy, SciPy, Matplotlib, spglib, ase, fftw, VTK, netCDF4, Eigen Nature of problem: Calculating the transport coefficients using the linearized Boltzmann transport equation within the relaxation time approximation. Solution method: Smoothed Fourier interpolation (C) 2018 Elsevier B.V. All rights reserved.", + "Times Cited, WoS Core": 960, + "Times Cited, All Databases": 1006, + "Publication Year": 2018, + "Research Areas": "Computer Science; Physics", + "UT (Unique WOS ID)": "WOS:000437964200011", + "Markdown": "# BoltzTraP2, a program for interpolating band structures and calculating semi-classical transport coefficients✩ \n\nGeorg K.H. Madsen a,\\*, Jesús Carrete a, Matthieu J. Verstraete b,c \n\na Institute of Materials Chemistry, TU Wien, A-1060 Vienna, Austria \nb nanomat/QMAT/CESAM and Department of Physics, Université de Liège, allée du 6 août, 19, B-4000 Liège, Belgium \nc European Theoretical Spectroscopy Facility, Belgium \n\n# a r t i c l e i n f o \n\nArticle history: \nReceived 19 December 2017 \nReceived in revised form 30 April 2018 \nAccepted 4 May 2018 \nAvailable online 17 May 2018 \n\nKeywords: \nBoltzmann transport equation \nBoltzTraP \n\n# a b s t r a c t \n\nBoltzTraP2 is a software package for calculating a smoothed Fourier expression of periodic functions and the Onsager transport coefficients for extended systems using the linearized Boltzmann transport equation. It uses only the band and $k$ -dependent quasi-particle energies, as well as the intra-band optical matrix elements and scattering rates, as input. The code can be used via a command-line interface and/or as a Python module. It is tested and illustrated on a simple parabolic band example as well as silicon. The positive Seebeck coefficient of lithium is reproduced in an example of going beyond the constant relaxation time approximation. \n\n# Program summary \n\nProgram Title: BoltzTraP2 \nProgram Files doi: http://dx.doi.org/10.17632/bzb9byx8g8.1 \nLicensing provisions: GPLv3 \nProgramming language: Python and $C{+}{+}$ \nExternal routines/libraries: NumPy, SciPy, Matplotlib, spglib, ase, fftw, VTK, netCDF4, Eigen \nNature of problem: Calculating the transport coefficients using the linearized Boltzmann transport equation within the relaxation time approximation. \nSolution method: Smoothed Fourier interpolation \n\n$\\mathfrak{C}$ 2018 Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nThe first BoltzTraP program [1] provided a numerically stable and efficient method for obtaining analytic representations of quasi-particle energies. It has found broad adoption for the application of the Boltzmann transport equation (BTE) to such diverse fields as superconductors [2], transparent conductors [3] intermetallic phases [4] as well as thermoelectrics. Its application has been especially widespread for thermoelectrics research [5–12] for which it was originally conceived [13,14]. Furthermore, it has served as a reference for other methods for obtaining transport coefficients, such as maximally localized Wannier functions [15,16]. The numerical stability means that the approach can be automated [14] and the methodology has subsequently been used in several high-throughput studies [3,14,17–19]. \n\nThe usefulness of the BoltzTraP approach can partly be attributed to the numerical efficiency of the procedure when the quasi-particle energies are approximated by the Kohn–Sham (KS) eigenvalues [20]. Once the multiplicative potential has been selfconsistently calculated, calculating eigenvalues on a fine k-mesh is a comparatively simple computational step that can be trivially parallelized. An alternative approach calculates the derivatives necessary for the BTE directly from the intra-band momentum matrix elements [21]. However, within KS theory, it is often simpler to calculate a finer mesh of eigenvalues than to calculate the momentum matrix elements. When the quasi-particle energies cannot be calculated using a fixed multiplicative KS potential, as in beyond-KS methods such as hybrid functionals [22] or the GW approach [23], this argument no longer holds and calculating the momentum matrix elements [21] or using alternative interpolation methods [16,24,25] could be an advantage. \n\nWith the release of BoltzTraP2 we wish to achieve three objectives. First of all, a method to use both the eigenvalues and momentum matrix elements is introduced. This ensures that the interpolated manifolds exactly reproduce both the value and derivative at the calculated points. The advantages of the interpolation scheme of the original BoltzTraP approach [1], and the advantages of using the intra-band momentum matrix elements [21] are combined. Thereby the method becomes more suited for beyond-KS approaches. Secondly, we wish to make it more straightforward to avoid the constant relaxation time approximation (RTA) and handle e.g. a temperature-dependent transport distribution function due to electron–phonon coupling [26,27]. Finally, a further motivation for rewriting and rereleasing BoltzTraP is to provide a modular code based on the modern scripting language Python 3. While BoltzTraP is mainly thought of as a tool to evaluate the transport coefficients, the underlying algorithm can be generally useful for interpolating any periodic function. We hope that the new code can also serve as a library for further developments in this domain. \n\nThe paper is built as follows. First we present the interpolation scheme as well as the RTA-BTE. We discuss the interface to the code and provide an outlook and finally we use three examples to illustrate the methodology and results of the code. \n\n# 2. Background \n\n# 2.1. Band interpolation \n\nThe method is based on writing the quasi-particle energies and their derivatives, for each band, as Fourier sums \n\n$$\n\\tilde{\\varepsilon}_{\\mathbf{k}}=\\sum_{\\varLambda}c_{\\varLambda}\\sum_{R\\in\\varLambda}\\exp(i\\mathbf{k}\\cdot\\mathbf{R})\n$$ \n\n$$\n\\nabla\\tilde{\\varepsilon}_{\\mathbf{k}}=i\\sum_{\\varLambda}c_{\\varLambda}\\sum_{R\\in\\varLambda}\\mathbf{Rexp}(i\\mathbf{k}\\cdot\\mathbf{R})\n$$ \n\nwhere $\\varLambda$ are so-called stars representing a set of symmetryequivalent lattice vectors. BoltzTraP was based on the idea by Shankland [28–30] that the coefficients should be obtained by minimizing a roughness function under the constraints that calculated quasi-particle energies should be exactly reproduced. This in turn means that the number of coefficients should be larger than the number of calculated points. \n\nThe derivatives can also be obtained from the intra-band optical matrix elements [21,31] \n\n$$\n\\nabla\\varepsilon_{\\mathbf{k}}=-\\langle\\psi_{\\mathbf{k}}|\\mathbf{p}|\\psi_{\\mathbf{k}}\\rangle.\n$$ \n\nIn BoltzTraP2 the Shankland algorithm [28–30] is extended so that the coefficients ensure that both the quasi-particle energies and their derivatives, Eq. (3), are exactly reproduced. This corresponds to minimizing the Lagrangian \n\n$$\nI=\\frac{1}{2}\\sum_{\\bf R}c_{\\bf R}\\rho_{\\bf R}+\\sum_{\\bf k}\\left[\\lambda_{\\bf k}\\left(\\varepsilon_{\\bf k}-\\tilde{\\varepsilon}_{\\bf k}\\right)+\\sum_{\\alpha}\\lambda_{\\alpha,\\bf k}\\nabla_{\\alpha}\\left(\\varepsilon_{\\bf k}-\\tilde{\\varepsilon}_{\\bf k}\\right)\\right]\n$$ \n\nwith respect to the Fourier coefficient $\\left(c_{R}\\right)$ , and choosing the Lagrange multipliers $\\big(\\lambda_{\\mathbf{k}}\\mathrm{and}\\lambda_{\\alpha,\\mathbf{k}}\\big)$ so that the constraints are fulfilled. The index $\\alpha$ labels the three Cartesian directions and indicates that each calculated derivative, Eq. (3), adds three Lagrange multipliers. Like in the BoltzTraP code, we use the roughness function provided by Pickett et al. [32] \n\n$$\n\\rho_{\\mathrm{R}}=\\left(1-c_{1}\\frac{R}{R_{m i n}}\\right)^{2}+c_{2}\\biggl(\\frac{R}{R_{m i n}}\\biggr)^{6}.\n$$ \n\n# 2.2. Boltzmann transport equation \n\nBoltzTraP2 calculates transport coefficients based on the rigid-band approximation (RBA), which assumes that changing the temperature, or doping a system, does not change the band \n\nstructure. In the RBA the carrier concentration, for a given $T$ and $\\mu$ , in a semiconductor can be obtained directly from the density of states (DOS) \n\n$$\nn(\\varepsilon)=\\int\\sum_{b}\\delta(\\varepsilon-\\varepsilon_{b,{\\bf k}})\\frac{\\mathrm{d}{\\bf k}}{8\\pi^{3}},\n$$ \n\nwhere the subscript $b$ runs over bands, by calculating the deviation from charge neutrality \n\n$$\nc(\\mu,T)=N-\\int n(\\varepsilon)f^{(0)}(\\varepsilon;\\mu,T)\\mathrm{d}\\varepsilon.\n$$ \n\nIn Eq. (7), $N$ is the nuclear charge and $f^{(0)}$ is the Fermi distribution function. In a semiconductor where charge neutrality would place the Fermi level in the band-gap, one can thus imagine how (at $T\\ =\\ 0\\dot{.}$ ) moving $\\mu$ into the conduction bands would produce a $n$ -type material and moving $\\mu$ into the valence bands would produce a $p$ -type material. \n\nThe BTE describes the behavior of an out-of-equilibrium system in terms of a balance between scattering in and out of each possible state, with scalar scattering rates [33]. We have implemented the linearized version of the BTE under the RTA, where the transport distribution function \n\n$$\n\\sigma(\\varepsilon,T)=\\int\\sum_{b}\\mathbf{v}_{b,\\mathbf{k}}\\otimes\\mathbf{v}_{b,\\mathbf{k}}\\tau_{b,\\mathbf{k}}\\delta(\\varepsilon-\\varepsilon_{b,\\mathbf{k}}){\\frac{\\mathrm{d}\\mathbf{k}}{8\\pi^{3}}}\n$$ \n\nis used to calculate the moments of the generalized transport coefficients \n\n$$\n\\mathcal{L}^{(\\alpha)}(\\mu;T)=q^{2}\\int\\sigma(\\varepsilon,T)(\\varepsilon-\\mu)^{\\alpha}\\left(-\\frac{\\partial f^{(0)}(\\varepsilon;\\mu,T)}{\\partial\\varepsilon}\\right)\\mathrm{d}\\varepsilon\n$$ \n\nwhich give the charge and heat currents \n\n$$\n\\begin{array}{l}{{\\displaystyle j_{e}=\\mathcal{L}^{(0)}{\\bf E}+\\frac{\\mathcal{L}^{(1)}}{q T}(-\\nabla T)}}\\\\ {{\\displaystyle j_{Q}=\\frac{\\mathcal{L}^{(1)}}{q}{\\bf E}+\\frac{\\mathcal{L}^{(2)}}{q^{2}T}(-\\nabla T)}.}\\end{array}\n$$ \n\nIdentifying the two experimental situations of zero temperature gradient and zero electric current, we obtain the electrical conductivity, the Peltier coefficient, the Seebeck coefficient and the charge carrier contribution to the thermal conductivity as \n\n$$\n\\begin{array}{l}{{\\displaystyle\\sigma=\\mathcal{L}^{(0)}}}\\\\ {{\\displaystyle\\pi=\\frac{\\mathcal{L}^{(1)}}{q\\mathcal{L}^{(0)}}}}\\\\ {{\\displaystyle S=\\frac{1}{q T}\\frac{\\mathcal{L}^{(1)}}{\\mathcal{L}^{(0)}}}}\\\\ {{\\displaystyle\\kappa_{e}=\\frac{1}{q^{2}T}\\left[\\frac{(\\mathcal{L}^{(1)})^{2}}{\\mathcal{L}^{(0)}}-\\mathcal{L}^{(2)}\\right].}}\\end{array}\n$$ \n\nThe main advantage of the BoltzTraP procedure for evaluating the transport coefficients is that it is straightforward to obtain the group velocities from the $\\mathbf{k}$ -space derivatives of the quasi-particle energies, Eq. (2). \n\nBoltzTraP is often associated with the constant relaxation time approximation (CRTA). The CRTA means that the Seebeck coefficient and Hall coefficient become independent of the scattering rate [34]. Therefore, they can be obtained on an absolute scale as a function of doping and temperature in a single scan. The CRTA in combination with the RBA, which makes the group velocities independent of $\\mu$ and $T$ , also has a computational advantage as it makes the transport distribution function, Eq. (8) independent of temperature and doping. The temperature and doping dependence of the transport coefficients ${\\mathcal{L}}^{(\\alpha)}$ , Eq. (9), is solely due to the Fermi distribution function, and can be obtained via a scan over a fixed transport distribution function. \n\nClearly the CRTA will have limitations. It only delivers $\\sigma$ and $\\kappa_{e}$ dependent on $\\tau$ as a parameter. Furthermore, the independence of S and $R_{H}$ from $\\tau$ is known to break down, even qualitatively, for specific cases [26]. While it is possible to run the original BoltzTraP with a temperature-, momentum- and band-dependent relaxation time, the structure of the code makes it inconvenient, and the functional form is quite limited. BoltzTraP2 makes it much more straightforward. The interpolated quasi-particle energies are usually considered to be independent from parameters such as temperature and Fermi level, and hence the interpolation does not need to be repeated (only the integration), for instance, to estimate thermoelectric coefficients for a different doping level or temperatures. The direct interface to the interpolation routines make it straightforward to interpolate the quasi-particle energies once and for all, and to avoid duplication of work when interpolating a temperature dependent $\\tau$ . \n\n# 3. Implementation and interface \n\n# 3.1. General implementation aspects \n\nBoltzTraP2 is implemented in Python 3, using syntax and standard library features that make it incompatible with Python 2. The Fortran code base of the original BoltzTraP was taken as a reference, but the new version was written from scratch. Numerical data is handled internally in the form of arrays, making extensive use of the NumPy and SciPy libraries [35,36]. Matplotlib [37] is used for plotting. \n\nEfficiency is an important goal of this new implementation. Despite being implemented in a higher-level language, BoltzTraP2 achieves speeds comparable to the original BoltzTraP. There are several factors contributing to this. First, many of the most expensive operations are vectorized to be performed at a lower level by NumPy, avoiding expensive loops. Second, the symmetry-related code, heavy with loops over long lists of lattice points, is written in $C{+}{+}$ and calls routines from the C API of the spglib library [38]. The $C{+}{+}$ components are interfaced to Python by a Cython layer [39]. Third, fast Fourier transforms are delegated to optimized low-level libraries; specifically, the pyFFTW wrapper around FFTW [40] is used if available, with the default NumPy wrapper around FFTPACK [41] as a fallback. Finally, certain ‘‘embarrassingly parallel’’ loops can be run on several cores thanks to the multiprocessing module in the Python standard library. \n\nBoltzTraP2 allows users to save results to files in JSON format, which is both human readable and parseable with a virtually limitless variety of tools and programming libraries. Specifically, there are two different sorts of JSON-formatted files at play. The first kind, bt2 files, contain the DFT input, all information about $k$ points, the interpolation coefficients and a dictionary of metadata. The second category, btj files, contain the DFT input, the DOS, the thermoelectric coefficients for all values of temperature and chemical potential, and another metadata dictionary. Those dictionaries comprise several pieces of version information, a creation timestamp, and information about the scattering model used, if applicable. All JSON files are processed using the LZMA-based xz compressor, to drastically reduce the overhead of the text-based format. \n\nThe decision to stick with standard formats also affects other outputs of the calculations, stored in plain text with a column layout very similar to the one created by the original BoltTraP [1]. Most existing post-processing and analysis scripts can be adapted with minimal effort. \n\nRegarding input formats, the current version of the code can read the native output of Wien2k [42,43], VASP [44] and ABINIT [45]. In the case of a VASP calculation, only the vasprun.xml file is required, while for Wien2k the necessary pieces of information are read from case.struct, case.energy and case.scf. If derivatives of the bands are to be used, the output-file case.mommat2 from the OPTIC [46] program is used. The code is modular enough that support for other DFT codes can be easily implemented. Alternatively, any DFT code can be adapted (or a translation script written) to create output in BoltzTraP2’s own GENE format, designed for maximum simplicity. Examples of files in this format are provided with the source distribution, and it is only slightly modified compared to the original BoltTraP code GENE format. \n\n![](images/55b4f64c38575c2aab84ecdb2e274603da32c5df24bf8435e8725cac57faadae.jpg) \nFig. 1. Typical BoltzTraP2 workflow taking the user from the results of a DFT calculation to estimates of the thermoelectric coefficients for the system under study, and other related results, using the btp2 command-line interface. \n\nBoltzTraP2 relies on Python’s setuptools module for its build system. On many platforms, the program can be installed from source with a python setup.py install command, and no previous manual configuration. Moreover, we have uploaded it to the Python Package Index, so that even the downloading step can be bypassed in favor of a simple pip install BoltzTraP2. A copy of spglib is bundled with the BoltzTraP2, to avoid a separate installation process. Naturally, a C compiler and a $C{+}{+},$ -compliant $C{+}{+}$ compiler are still needed when building from source. \n\n# 3.2. Command-line interface \n\nThe most typical use case of BoltzTraP2 is the calculation of transport coefficients. This can be done directly through the btp2 command-line front-end, which implements the general workflow depicted in Fig. 1. It is designed to be self-documenting and controllable through command-line arguments, without the need for configuration files. \n\nThe process starts with a set of DFT results, typically from a nonself-consistent calculation using a dense $k$ -point grid. The user first calls btp2 in ‘‘interpolate’’ mode to generate a representation of the bands interpolated to an even denser grid, which is stored in a JSON file. Optional command-line parameters to the ‘‘interpolate’’ step can be used to control the grid density, the number of bins used to compute the density of states, the minimum and maximum energies, etc. By saving the result of the interpolation to a file, we avoid repeating the calculation even if the user then wants to generate results for different situations. \n\nTo obtain a set of thermoelectric coefficients, the user needs to invoke btp2 a second time, now in ‘‘integrate’’ mode. In this mode of operation, the command-line script accepts parameters such as the range of temperatures to scan, the dependence of scattering on electron energy, and so on. It then generates output in the form of text files, plus another compressed JSON file as described in the previous section. \n\nThe detailed list of command-line parameters, with their meanings, can be obtained by invoking btp2 or one of its subcommands with the -h or --help flag. \n\nIn addition to the ‘‘integrate’’ and ‘‘interpolate’’ subcommands, Fig. 1 illustrates the use of the ‘‘fermisurface’’, ‘‘plotbands’’ and ‘‘plot’’ modes of the btp2 command-line interface. Their job is to generate graphical representations of the BoltzTraP2 output: an interactive 3D plot of the Fermi surface for different values of the energy, a plot of the interpolated electron energies along a specific path in reciprocal space, and plots of the thermoelectric coefficients as functions of temperature and chemical potential, respectively. 3D plotting will only be available if the optional vtk module is detected. \n\nThe code is documented, and a set of unit tests covering all the basic functionality is provided with the source distribution. The whole battery of tests can be run with pytest. \n\n# 3.3. Using BoltzTraP2 as a module \n\nAdvanced users may prefer to skip the command-line interface and access the full feature set of BoltzTraP2 more directly. Those wanting to use the interpolation capabilities of BoltzTraP2 in their own code, or using it as part of an automated workflow, will probably fall in this category. Furthermore, the btp2 commandline interface only allows choosing between a uniform-relaxationtime model and a uniform-mean-free-path one. Users requiring custom parameterizations of the electronic scattering rates will need to bypass the interface. This is easily accomplished by calling the API of the BoltzTraP2 Python module, either from a script or from an interactive Python shell, such as the Jupyter notebook [47]. Crystal structures are represented as ase atoms objects [48], which allows for easy interfacing with many other Python libraries and external software. \n\nThe best reference about the API of the BoltzTraP2 is the source code of the btp2 interface itself, and a set of documented examples that are provided with the source distribution of BoltzTraP2. The examples illustrate how to accomplish specific tasks and reproduce several results obtained with the original BoltzTraP code as well as the three examples in the following section. \n\n# 4. Examples \n\nThe API of BoltzTraP2 is illustrated through three examples. These represent ‘‘non-standard’’ uses of the code, which cannot be accessed through the command line interface. The python source codes reproducing the plots shown below and several others can be found in the examples directory. \n\n# 4.1. Isotropic parabolic band model \n\nThe simplest way to illustrate the library functionality of BoltzTraP2 is the parabolic band model. Consider a dispersion relation expressed as, \n\n$$\n\\varepsilon(k)=\\frac{\\hbar^{2}k^{2}}{2m^{*}}\n$$ \n\nwhere $m^{*}$ is the effective mass of the electrons in the band. For an isotropic parabolic band model we can replace the outer product of group velocities, Eq. (8), by $k/m^{*}$ and the volume element dk in the \n\n![](images/e706a4316c5041ac40220bbe9b73db87cb73443754945e72f2c3495e23e22f8b.jpg) \nFig. 2. S, $\\sigma$ , and the thermoelectric $P F$ as a function of carrier concentration. The transport coefficients have been evaluated using a parabolic band model with $m^{*}=$ $m_{e}$ . The temperature and relaxation time were set to $T=500\\mathrm{K}$ and $\\tau=10^{-14}s$ respectively. \n\nthree dimensional volume integral in Eq. (8) by $4\\pi k^{2}{\\mathrm d}k$ , thereby obtaining analytic expressions for $n(\\varepsilon)$ and $\\sigma(\\varepsilon)$ \n\n$$\n\\begin{array}{l}{{n(\\varepsilon)={\\displaystyle\\frac{1}{4\\pi^{2}}}\\left(\\frac{2m^{*}}{\\hbar^{2}}\\right)^{3/2}\\varepsilon^{1/2}}}\\\\ {{\\sigma(\\varepsilon)={\\displaystyle\\frac{1}{3\\pi^{2}}}\\frac{\\sqrt{2m^{*}}}{\\hbar^{3}}}\\tau\\varepsilon^{3/2}.}}\\end{array}\n$$ \n\nEvaluating the carrier concentration, Eq. (7), and the transport coefficients, Eqs. (9)–(14), leads directly to the famous plot Fig. 2. For comparison we have created a single parabolic band numerically on a $25\\times25\\times25{\\bf k}$ -mesh for a cubic unit cell with $a=5\\mathring{\\mathsf{A}}.$ The band was interpolated onto a mesh containing 5 times the points. The resulting transport coefficients are indistinguishable from the analytic in Fig. 2. \n\nFig. 2 can be reproduced with the parabolic.py script in the examples directory of the BoltzTraP2 distribution. \n\n# 4.2. Inclusion of momentum matrix elements. Silicon \n\nThe band structure of silicon makes one of the simplest examples that is not trivial for an interpolation scheme. The conduction band minimum (CBM) of Si is made up of pockets found along the six-fold degenerate $\\boldsymbol{{\\cal T}}-\\boldsymbol{X}$ line. Furthermore, it has a nonsymmorphic space group so that the bands can cross at the zone boundary. A crossing at the zone boundary will mean that the bands will not necessarily touch the zone-boundary ‘‘horizontally’’. A purely Fourier-based interpolation scheme, as the one used in BoltzTraP2 can give false derivatives at these points, meaning that a very fine $k$ -mesh can be necessary to obtain converged results. \n\nThe CBM pocket found along the $\\boldsymbol{{\\cal{T}}}{-}\\boldsymbol{{\\cal{X}}}$ line, which will dominate the transport properties of $n$ -doped Si, is illustrated in Fig. 3. Fig. 3 compares the result of a usual DFT calculation of a band structure, with a fine set of $k$ -points along a specific direction, with that obtained by the analytic interpolation of a coarse $9\\times9\\times9k$ -point mesh, Eq. (1). $\\mathbf{A9}\\times\\mathbf{9}\\times\\mathbf{9}$ -mesh corresponds to only $35k$ -points in the irreducible part of the Brillouin zone (IBZ). A $9\\times9\\times9$ -mesh corresponds to a typical $k$ -mesh used for a self-consistent DFT calculation and is obviously not a fine $k$ -mesh, that would typically be calculated non-self-consistently for transport calculations [14] Furthermore, as the lowest conduction bands are degenerate at the $X$ -point, Fig. 3, the non-symmorphic space group does result in the derivatives of interpolated bands being incorrect at this point. However, Fig. 3 illustrates how the modified Lagrangian, Eq. (4), forces the fit to reproduce the exact derivatives at the calculated points. Thereby, both the position and derivatives of the pocket are well reproduced. On the other hand, if only the eigenvalues are included in the fit, this mesh is obviously too coarse and the algorithm fails to reproduce either the position or the derivatives at the pocket (purple dashed line in Fig. 3). \n\n![](images/292caf5e24b44e9f50e5bb6ebad4e96ad2c5692f4dfc76e600eb1ee1575e29f1.jpg) \nFig. 3. Silicon band edges along the $\\boldsymbol{{\\cal T}}-\\boldsymbol{X}$ line. The black points are calculated points along this specific direction. The colored lines correspond to the interpolated bands based on a coarse ${\\mathfrak{s}}\\times{\\mathfrak{s}}\\times{\\mathfrak{s}}k.$ -point mesh. The points belonging to this mesh are marked with larger colored points. The full lines are obtained by including the momentum matrix elements in the fit and the dashed use only the eigenvalues. Thin dashed line: chemical potential used below in Fig. 4. \n\n![](images/0dd377bad29c9e336d91edcbf7bca9a726ee84942d0bcd48e0a521cef7c33ae9.jpg) \nFig. 4. Convergence of the Seebeck coefficient and thermoelectric power factor as a function of number $k$ -points in the irreducible Brillouin zone. The full lines are obtained by including the momentum matrix elements in the fit whereas the dashed correspond to including only the eigenvalues. \n\n![](images/7fd3380e056ef70fd927fb7432889ef67f96a18252e69ac166239cef4ef3cdb2.jpg) \nFig. 5. Calculated conductivity of bcc-Li using a constant relaxation time, band and momentum dependent relaxation times due to electron–phonon coupling, and an energy dependent model $\\tau^{-1}(\\varepsilon)=c n(\\varepsilon)$ , relaxation time. \n\nThe impression obtained graphically in Fig. 3 is quantified in Fig. 4. The Seebeck coefficient and the thermoelectric power factor, $S^{2}\\sigma/\\tau$ , are calculated at a chemical potential close to the CBM (marked by the thin dashed line in Fig. 3) using the CRTA, Eqs. (8)–(14). It is seen how the results obtained by the modified Lagrangian show both a faster and more systematic trend, reaching convergence at about half the number of $k$ -points needed when the derivatives are not included in the fit. \n\nFigs. 3 and 4 can be reproduced with the Si_pocket.py and Si_conv.py scripts in the examples directory of the BoltzTraP2 distribution. Before running these two scripts, the script Si_btp.py which does the Fourier interpolation and stores the results in JSON formatted bt2 files. \n\n# 4.3. State dependent relaxation time in Lithium \n\nIn BoltzTraP2 the interpolation and integration steps are more explicitly decoupled than in BoltzTraP. This allows the interpolation capabilities of the code to be used to match quantities represented on different grids. We illustrate this possibility by considering the transport distribution function of bcc-Lithium. \n\nFirst the KS eigenvalues were obtained on a $36\\times36\\times36\\mathbf{k}$ - point mesh and interpolated onto a grid containing 60 times the number of $\\mathbf{k}$ -points. Fig. 5 illustrates how this leads to a positive slope of the CRTA transport distribution function at the Fermi level. Consequently, Eqs. (9) and (14), we find a negative Seebeck coefficient of $S=-1.9\\upmu\\mathrm{V}/\\mathrm{K}$ at $300\\mathrm{K}$ as in Ref. [26]. The obtained CRTA transport distribution function, Fig. 5, is in good agreement with a more ‘‘usual’’ BoltzTraP type calculation where the KS eigenvalues were calculated on $58\\times58\\times58$ -grid and interpolated onto a grid containing four times as many $\\mathbf{k}$ -points. This lends credibility to the interpolation of the scattering rates that we will now perform. \n\nAs a by-product of the calculations in $\\mathtt{X u}$ et al. [26], we can obtain the computationally costly relaxation times due to electron– phonon scattering, $\\tau_{n\\mathbf{k}}^{e p}$ , on a relatively coarse $24\\times24\\times24\\mathbf{k}$ -point mesh. Using our interpolation scheme, the calculated band- and momentum-dependent relaxation times were interpolated onto the same fine grid as used for the KS eigenvalues. The inclusion of $\\tilde{\\tau}_{n\\mathbf{k}}^{e p}$ leads to a change of slope at the Fermi level and consequently a positive Seebeck coefficient $(S=+2.9\\upmu\\mathrm{V}/\\mathrm{K}$ at $300\\mathrm{K}$ ). \n\nAs pointed out in the original work [26], the change of sign can be understood by a simple model where the scattering rate is proportional to the DOW. This is illustrated in the inset in Fig. 5 where a peak in the DOS is found above the Fermi level. Consequently, we fit a $\\tau^{-1}(\\varepsilon)\\ =\\ c n(\\varepsilon)$ model to the calculated $(\\tau_{n\\mathbf k}^{e p})^{-1}$ , thereby obtaining an energy dependent relaxation time. As seen in Fig. 5 a very good agreement, especially around the Fermi level, is obtained with the transport distribution calculated using the full $\\tau_{n\\mathbf{k}}^{e p}$ . \n\nFig. 5 can be reproduced with the Li_bcc.py script in the examples directory of the BoltzTraP2 distribution. \n\n# 5. Conclusion \n\nWe have presented a new a software package, BoltzTraP2, based mainly on Python 3. The methodology is based on a smoothed Fourier expression for periodic functions and uses only the band and $k$ -dependent quasi-particle energies as well as the intra-band optical matrix elements and scattering rates as input. The Onsager transport coefficients have been evaluated for a simple periodic band, as well as Silicon and Lithium using the linearized Boltzmann transport equation. The code can be used via a command-line interface and as a Python module. \n\n# Acknowledgments \n\nMJV acknowledges support from the Communauté française de Belgique through an ARC grant (AIMED 15/19-09) and the Belgian Fonds National de la Recherche Scientifique FNRS, under Grant Number PDR T.1077.15-1/7. GKHM and JC acknowledge support from M-era.net through the ICETS project (DFG: MA 5487/4-1) and the EU Horizon 2020 Grant No. 645776 (ALMA). Computational resources have been provided by the Consortium des Equipements de Calcul Intensif en Fédération Wallonie Bruxelles (CECI), funded by FRS-FNRS G.A. 2.5020.11; the Tier-1 supercomputer of the Fédération Wallonie-Bruxelles, funded by the Walloon Region under G.A. 1117545; the PRACE-3IP DECI grants, on ARCHER and Salomon (ThermoSpin, ACEID, OPTOGEN, and INTERPHON 3IP G.A. RI-312763) and the Vienna Scientific Cluster (project number 70958: ALMA). \n\n# References \n\n[1] G.K.H. Madsen, D.J. Singh, Comput. Phys. Comm. 175 (2006) 67–71. [2] D.J. Singh, M.-H. Du, Phys. Rev. Lett. 100 (2008) 237003. http://dx.doi.org/10. 1103/PhysRevLett.100.237003. [3] G. Hautier, A. Miglio, G. Ceder, G.-M. Rignanese, X. Gonze, Nature Comm. 4 (2013) 2292. [4] J. Dolinšek, M. Komelj, P. Jeglič, S. Vrtnik, D. Stanić, P. Popčević, J. Ivkov, A. Smontara, Z. Jagličić, P. Gille, Y. Grin, Phys. Rev. B 79 (2009) 184201. http: //dx.doi.org/10.1103/PhysRevB.79.184201. \n[5] A.F. May, D.J. Singh, G.J. Snyder, Phys. Rev. B 79 (2009) 153101. http://dx.doi. org/10.1103/PhysRevB.79.153101. [6] S. Ouardi, G.H. Fecher, B. Balke, X. Kozina, G. Stryganyuk, C. Felser, S. Lowitzer, D. Ködderitzsch, H. Ebert, E. Ikenaga, Phys. Rev. B 82 (2010) 085108. [7] D. Parker, X. Chen, D.J. Singh, Phys. Rev. Lett. 110 (2013) 146601. http://dx.doi. org/10.1103/PhysRevLett.110.146601. [8] D.B. Luo, Y.X. Wang, Y.L. Yan, G. Yang, J.M. Yang, J. Mater. Chem. A 2 (36) (2014) 15159–15167. http://dx.doi.org/10.1039/c4ta02452d. [9] J.Y. Kim, J.C. Grossman, Nano Lett. 15 (2015) 2830–2835. http://dx.doi.org/10. 1021/nl504257q. \n[10] A. Hong, L. Li, R. He, J. Gong, Z. Yan, K. Wang, J.-M. Liu, Z. Ren, Sci. Rep. 6 (2016) 22778. \n[11] J. He, M. Amsler, Y. Xia, S.S. Naghavi, V.I. Hegde, S. Hao, S. Goedecker, V. Ozolins, C. Wolverton, Phys. Rev. Lett. 117 (2016) 046602. http://dx.doi.org/10.1103/ PhysRevLett.117.046602. \n[12] J. Zhang, L. Song, G.K.H. Madsen, K.F.F. Fischer, W. Zhang, X. Shi, B.B. Iversen, Nature Comm. 7 (2016) 10892. \n[13] G.K.H. Madsen, K. Schwarz, P. Blaha, D.J. Singh, Phys. Rev. B 68 (2003) 125212. \n[14] G.K.H. Madsen, J. Am. Chem. Soc. 128 (2006) 12140. \n[15] J.R. Yates, X. Wang, D. Vanderbilt, I. Souza, Phys. Rev. B 75 (2007) 195121. http://dx.doi.org/10.1103/PhysRevB.75.195121. \n[16] G. Pizzi, D. Volja, B. Kozinsky, M. Fornari, N. Marzari, Comput. Phys. Comm. 185 (2014) 422–429. http://dx.doi.org/10.1016/j.cpc.2013.09.015. \n[17] J. Carrete, N. Mingo, S. Wang, S. Curtarolo, Adv. Funct. Mater. 24 (47) (2014) 7427–7432. http://dx.doi.org/10.1002/adfm.201401201. \n[18] S. Bhattacharya, G.K.H. Madsen, Phys. Rev. B 92 (2015) 085205. http://dx.doi. org/10.1103/PhysRevB.92.085205. \n[19] H. Zhu, G. Hautier, U. Aydemir, Z.M. Gibbs, G. Li, S. Bajaj, J.-H. Pöhls, D. Broberg, W. Chen, A. Jain, et al., J. Mater. Chem. C 3 (2015) 10554–10565. \n[20] W. Kohn, L.J. Sham, Phys. Rev. 140 (1965) A1133–A1138. \n[21] T.J. Scheidemantel, C. Ambrosch-Draxl, T. Thonhauser, J.V. Badding, J.O. Sofo, Phys. Rev. B 68 (2003) 125210. http://dx.doi.org/10.1103/PhysRevB.68. 125210. \n[22] A.D. Becke, J. Chem. Phys. 98 (7) (1993) 5648–5652. http://dx.doi.org/10.1063/ 1.464913. \n[23] L. Hedin, Phys. Rev. 139 (1965) A796–A823. http://dx.doi.org/10.1103/PhysRe v.139.A796. \n[24] D. Prendergast, S.G. Louie, Phys. Rev. B 80 (2009) 235126. \n[25] K. Berland, C. Persson, Comput. Mater. Sci. 134 (2017) 17–24. \n[26] B. Xu, M.J. Verstraete, Phys. Rev. Lett. 112 (2014) 196603. http://dx.doi.org/10 .1103/PhysRevLett.112.196603. \n[27] W. Li, Phys. Rev. B 92 (2015) 075405. http://dx.doi.org/10.1103/PhysRevB.92. 075405. \n[28] R.N. Euwema, D.J. Stukel, T.C. Collins, J.S. DeWitt, D.G. Shankland, Phys. Rev. 178 (1969) 1419–1423. http://dx.doi.org/10.1103/PhysRev.178.1419. \n[29] D.G. Shankland, Int. J. Quantum Chem. 5 (1971) 497–500. http://dx.doi.org/10 .1002/qua.560050857. \n[30] D.D. Koelling, J.H. Wood, J. Comput. Phys. 67 (1986) 253–262. \n[31] E. Assmann, P. Wissgott, J. Kuneš, A. Toschi, P. Blaha, K. Held, Comput. Phys. Comm. 202 (2016) 1–11. \n[32] W.E. Pickett, H. Krakauer, P.B. Allen, Phys. Rev. B 38 (1988) 2721–2726. \n[33] J.M. Ziman, Electrons and Phonons: The Theory of Transport Phenomena in Solids, Oxford University Press, 2000. \n[34] D.J. Singh, I.I. Mazin, Phys. Rev. B 56 (1997) R1650–R1653. http://dx.doi.org/1 0.1103/PhysRevB.56.R1650. \n[35] S. van der Walt, S.C. Colbert, G. Varoquaux, Comput. Sci. Eng. 13 (2011) 22–30. http://dx.doi.org/10.1109/MCSE.2011.37. \n[36] T.E. Oliphant, Comput. Sci. Eng. 9 (2007) 10–20. http://dx.doi.org/10.1109/MC SE.2007.58. \n[37] J.D. Hunter, Sci. Eng. 9 (2007) 90–95. http://dx.doi.org/10.1109/MCSE.2007.55 \n[38] A. Togo, spglib, a c library for finding and handling crystal symmetries, http: //spglib.sourceforge.net/. (Accessed 26 July 2016). \n[39] S. Behnel, R. Bradshaw, C. Citro, L. Dalcin, D. Seljebotn, K. Smith, Comput. Sci. Eng. 13 (2011) 31–39. http://dx.doi.org/10.1109/MCSE.2010.118. \n[40] M. Frigo, SIGPLAN Not. 39 (2004) 642–655. http://dx.doi.org/10.1145/989393 .989457. \n[41] P.N. Swarztrauber, in: G. Rodrigue (Ed.), Parallel Computations, Academic Press, New York, 1982, pp. 51–83. \n[42] K. Schwarz, P. Blaha, G.K.H. Madsen, Comput. Phys. Comm. 147 (2002) 71–76. \n[43] P. Blaha, K. Schwarz, G.K.H. Madsen, D. Kvasnicka, J. Luitz, . WIEN2k, WIEN2k, an Augmented Plane Wave Plus Local Orbitals Program for Calculating Crystal Properties, Vienna University of Technology, Austria, ISBN: 3-9501031-1-2, 2001. \n[44] G. Kresse, J. Furthmüller, Phys. Rev. B 54 (16) (1996) 11169–11186. http://dx. doi.org/10.1103/PhysRevB.54.11169. \n[45] X. Gonze, F. Jollet, F. Abreu Araujo, D. Adams, B. Amadon, T. Applencourt, C. Audouze, J.-M. Beuken, J. Bieder, A. Bokhanchuk, E. Bousquet, F. Bruneval, D. Caliste, M. Côté, F. Dahm, F. Da Pieve, M. Delaveau, M. Di Gennaro, B. Dorado, C. Espejo, G. Geneste, L. Genovese, A. Gerossier, M. Giantomassi, Y. Gillet, D. Hamann, L. He, G. Jomard, J. Laflamme Janssen, S. Le Roux, A. Levitt, A. Lherbier, F. Liu, I. Lukačević, A. Martin, C. Martins, M. Oliveira, S. Poncé, Y. Pouillon, T. Rangel, G.-M. Rignanese, A. Romero, B. Rousseau, O. Rubel, A. Shukri, M. Stankovski, M. Torrent, M. Van Setten, B. Van Troeye, M. Verstraete, D. Waroquiers, J. Wiktor, B. Xu, A. Zhou, J. Zwanziger, Comput. Phys. Comm. 205 (2016) 106–131. http://dx.doi.org/10.1016/j.cpc.2016.04.003. URL https: //doi.org/10.1016/j.cpc.2016.04.003. \n[46] C. Ambrosch-Draxl, J.O. Sofo, Comput. Phys. Comm. 175 (2006) 1–14. \n[47] F. Pérez, B.E. Granger, Comput. Sci. Eng. 9 (2007) 21–29. http://dx.doi.org/10.1 109/MCSE.2007.53. \n[48] A.H. Larsen, J.J. Mortensen, J. Blomqvist, I.E. Castelli, R. Christensen, M. Dułak, J. Friis, M.N. Groves, B. Hammer, C. Hargus, E.D. Hermes, P.C. Jennings, P.B. Jensen, J. Kermode, J.R. Kitchin, E.L. Kolsbjerg, J. Kubal, K. Kaasbjerg, S. Lysgaard, J.B. Maronsson, T. Maxson, T. Olsen, L. Pastewka, A. Peterson, C. Rostgaard, J. Schiøtz, O. Schütt, M. Strange, K.S. Thygesen, T. Vegge, L. Vilhelmsen, M. Walter, Z. Zeng, K.W. Jacobsen, J. Phys.: Condens. Matter 29 (2017) 273002. " + }, + { + "id": "10.1016_j.marpolbul.2017.12.061", + "DOI": "10.1016/j.marpolbul.2017.12.061", + "DOI Link": "http://dx.doi.org/10.1016/j.marpolbul.2017.12.061", + "Relative Dir Path": "mds/10.1016_j.marpolbul.2017.12.061", + "Article Title": "Validation of ATR FT-IR to identify polymers of plastic marine debris, including those ingested by marine organisms", + "Authors": "Jung, MR; Horgen, FD; Orski, SV; Rodriguez, CV; Beers, KL; Balazs, GH; Jones, TT; Work, TM; Brignac, KC; Royer, SJ; Hyrenbach, KD; Jensen, BA; Lynch, JM", + "Source Title": "MARINE POLLUTION BULLETIN", + "Abstract": "Polymer identification of plastic marine debris can help identify its sources, degradation, and fate. We optimized and validated a fast, simple, and accessible technique, attenuated total reflectance Fourier transform infrared spectroscopy (ATR FT-IR), to identify polymers contained in plastic ingested by sea turtles. Spectra of consumer good items with known resin identification codes #1-6 and several #7 plastics were compared to standard and raw manufactured polymers. High temperature size exclusion chromatography measurements confirmed ATR Fr-IR could differentiate these polymers. High-density (HDPE) and low-density polyethylene (LDPE) discrimination is challenging but a clear step-by-step guide is provided that identified 78% of ingested PE samples. The optimal cleaning methods consisted of wiping ingested pieces with water or cutting. Of 828 ingested plastics pieces from 50 Pacific sea turtles, 96% were identified by ATR FT-IR as HDPE, LDPE, unknown PE, polypropylene (PP), PE and PP mixtures, polystyrene, polyvinyl chloride, and nylon.", + "Times Cited, WoS Core": 937, + "Times Cited, All Databases": 996, + "Publication Year": 2018, + "Research Areas": "Environmental Sciences & Ecology; Marine & Freshwater Biology", + "UT (Unique WOS ID)": "WOS:000427332900078", + "Markdown": "# Validation of ATR FT-IR to identify polymers of plastic marine debris, including those ingested by marine organisms \n\nMelissa R. Junga, F. David Horgena, Sara V. Orskib, Viviana Rodriguez C.b, Kathryn L. Beersb, George H. Balazsc, T. Todd Jonesc, Thierry M. Workd, Kayla C. Brignace, Sarah-Jeanne Royerf, K. David Hyrenbacha, Brenda A. Jensena, Jennifer M. Lynchg, \n\na College of Natural and Computational Sciences, Hawai'i Pacific University, Kaneohe, HI, United States b Materials Science and Engineering Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, United States c Pacific Islands Fisheries Science Center, National Marine Fisheries Service, Honolulu, HI, United States d U.S. Geological Survey, National Wildlife Health Center, Honolulu Field Station, Honolulu, HI, United States e School of Ocean, Earth Science, and Technology, University of Hawai'i at Manoa, Honolulu, HI, United States f Daniel K. Inouye Center for Microbial Oceanography: Research and Education, University of Hawai'i at Manoa, Honolulu, HI, United States g Chemical Sciences Division, National Institute of Standards and Technology, Kaneohe, HI, United States \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nKeywords: \nSea turtles \nPacific Ocean \nMarine plastic debris \nPlastic ingestion \nFourier transform infrared spectroscopy \nPolymer identification \n\nPolymer identification of plastic marine debris can help identify its sources, degradation, and fate. We optimized and validated a fast, simple, and accessible technique, attenuated total reflectance Fourier transform infrared spectroscopy (ATR FT-IR), to identify polymers contained in plastic ingested by sea turtles. Spectra of consumer good items with known resin identification codes $\\#1{-}6$ and several $\\#7$ plastics were compared to standard and raw manufactured polymers. High temperature size exclusion chromatography measurements confirmed ATR FT-IR could differentiate these polymers. High-density (HDPE) and low-density polyethylene (LDPE) discrimination is challenging but a clear step-by-step guide is provided that identified $78\\%$ of ingested PE samples. The optimal cleaning methods consisted of wiping ingested pieces with water or cutting. Of 828 ingested plastics pieces from 50 Pacific sea turtles, $96\\%$ were identified by ATR FT-IR as HDPE, LDPE, unknown PE, polypropylene (PP), PE and PP mixtures, polystyrene, polyvinyl chloride, and nylon. \n\n# 1. Introduction \n\nPlastic is one of the most persistent and abundant types of marine debris (Rios et al., 2007). For instance, high concentrations of up to 334,271 pieces $\\ensuremath{\\mathrm{km}}^{2}$ have been estimated floating in the North Pacific central gyre, where this material is concentrated by wind-driven ocean currents (Moore et al., 2001; Howell et al., 2012). The production of plastic and associated marine plastic debris continues to rise (Geyer et al., 2017; Jambeck et al., 2015; Bakir et al., 2014; Hoarau et al., 2014), with an estimated 4.8 million metric tons to 12.7 million - metric tons of plastic debris entering the marine environment each year (Jambeck et al., 2015). As marine plastic debris continues to accumulate, long-term environmental, economic, and waste management problems grow, including significant economic costs for prevention and clean-up (Singh and Sharma, 2008; McIlgorm et al., 2011). Increasing awareness of the possible ecological impacts of marine debris has stimulated research to quantify and understand the incidence and \n\nmagnitude of plastic ingestion by marine animals (Andrady, 2011; \nProvencher et al., 2017). \n\nIngestion of plastic debris has been documented in marine species across a range of sizes and biological complexity: from microscopic zooplankton to large vertebrates (Hoss and Settle, 1990; Nelms et al., 2015; Cole and Galloway, 2015; Unger et al., 2016). The size of ingested plastic debris occupies a large range, evidenced by filter feeders, like oyster larvae, which can ingest microplastics as small as $0.16\\upmu\\mathrm{m}$ diameter (Cole and Galloway, 2015), while large items such as part of a car engine cover $\\mathbf{650mm\\times235mm}$ have been found in the gastrointestinal tracts of sperm whales (Physeter macrocephalus) (Unger et al., 2016). Sea turtles are a good indicator of plastic debris occurrence in the natural environment as studies have documented ingestion around the world including coastal Florida, southern Brazil, the Central Pacific, and Mediterranean Sea (Bjorndal et al., 1994; Bugoni et al., 2001; Clukey et al., 2017; Tomás et al., 2002). Sea turtles ingest a variety of plastic items of varying types, sizes, and morphologies, including pieces of bags, rope, fishing line, foam, and fragments of less flexible plastic that range in size from microplastics $\\AA<5\\mathrm{mm}$ on largest edge) to macroplastics $\\mathrm{(>25\\:mm)}$ ) with fragments up to $10\\mathrm{cm}$ observed (Bugoni et al., 2001; Tomás et al., 2002; Clukey et al., 2017). A study by Clukey et al. (2017) showed that a total of 2880 plastic debris items were ingested by 37 olive ridley (Lepidochelys olivacea), nine green (Chelonia mydas), and four loggerhead (Caretta caretta) pelagic sea turtles that were incidentally taken by longline fisheries in the North Pacific Ocean. Plastic fragments constituted $79.5\\%$ of the total debris while $12.5\\%$ were thin plastic sheets (e.g., bags and thin packaging material) and $6.1\\%$ were line or rope (Clukey et al., 2017). While the commercial use of some ingested plastics, such as bags and fishing line, can be easily identified by visual inspection, few pieces are found completely intact and their original origin is difficult to discern (Hoss and Settle, 1990). Fortunately, plastic manufacturers and standards organizations have developed a standard identification system for general classes of plastic that can be used to help identify their likely intended commercial use. \n\nMost plastic consumer goods are labeled with standardized resin codes marked inside a triangle (ASTM, 2013), signifying the chemical composition of the main polymer, which is used to sort and recycle compatible materials. These include polyethylene terephthalate (PETE, #1), high-density polyethylene (HDPE, #2), polyvinyl chloride (PVC, $\\#3)$ , low-density polyethylene (LDPE, #4, which also currently includes linear LDPE [LLDPE]), polypropylene (PP, $\\#5\\mathrm{\\textperthousand}$ , polystyrene (PS, $\\#6)$ , and other polymers (#7). These codes are rarely present or legible in recovered plastic debris or small plastic fragments, hence identification of the polymer must be accomplished using chemical testing. Characterizing unknown polymers helps illuminate many of the issues surrounding marine debris. Knowing the polymer structure will aid in determining the transport and fate of debris pieces in the environment, such as the effect of material density on stratification within the water column or the susceptibility of specific chemical bonds to break under environmental conditions. In addition, different polymers have different affinities for adsorbing chemical pollutants from seawater, suggesting some polymers may present a larger risk of transferring pollutants to marine organisms who ingest them (Rochman et al., 2013; Fries and Zarfl, 2012; Endo et al., 2005; Koelmans et al., 2013). Knowing the predominant polymers found in various habitats or ingested by marine organisms can help focus conservation efforts, including changes to recycling strategies, targeted waste management, or novel approaches in polymer production (Ryan et al., 2009). Furthermore, since certain polymers are more commonly recycled than others (e.g., $\\#2$ HDPE compared to $\\#4$ LDPE), it is important to be able to distinguish these to monitor the success of waste management techniques. \n\nSeveral analytical tools have been used to identify the composition of plastic debris (Andrady, 2017). For example, environmental samples from German rivers were analyzed using thermogravimetric analysis connected to solid-phase adsorbers that were subsequently analyzed by thermal desorption gas chromatography mass spectrometry (GC/MS; Dümichen et al., 2015). Fischer and Scholz-Böttcher (2017) used pyrolysis-GC/MS to identify microplastics ingested by North Sea fish. In addition, GC/MS has been utilized to identify indicator chemicals characteristic of different polymers of plastics ingested by Laysan albatross (Phoebastria immutabilis) (Nilsen et al., 2014). These methods are limited to only volatile or ionizable compounds, such as small oligomeric fragments or additives within the bulk material. Methods that can analyze the entire sample, and often require less sample preparation, are vibrational spectroscopy measurements such as Raman microspectroscopy (Frère et al., 2016) and Fourier transform infrared (FT-IR) spectroscopy. FT-IR is becoming the most common technique for marine debris polymer identification. It has been used to identify microplastics near the surface of the Ross Sea, from the English Channel, and ingested by zooplankton (Cincinelli et al., 2017; Cole et al., 2014). Recently, Mecozzi et al. (2016) used FT-IR coupled with the Independent Component Analysis (ICA) database and Mahalanobis \n\nDistance (MD) to identify marine plastics ingested by four loggerhead sea turtles in the Mediterranean Sea. \n\nFT-IR spectroscopy offers a simple, efficient, and non-destructive method for identifying and distinguishing most plastic polymers, based on well-known infrared absorption bands representing distinct chemical functionalities present in the material (Verleye et al., 2001; Coates, 2000; Asensio et al., 2009; Beltran and Marcilla, 1997; Noda et al., 2007; Nishikida and Coates, 2003; Ilharco and Brito de Barros, 2000; Guidelli et al., 2011; Rotter and Ishida, 1992; Asefnejad et al., 2011). Structural isomeric polymers, such as HDPE and LDPE, are difficult, yet important, to differentiate. Asensio et al. (2009) and Nishikida and Coates (2003) reported that LDPE had a unique characteristic (yet quite small) band at $1377\\mathrm{cm}^{-1}$ , representing a $\\mathrm{CH}_{3}$ bending deformation, suggesting that even these similar polymers can be distinguished using FT-IR spectra. This band is reportedly absent in HDPE. These polymers differ by the extent of branching with HDPE being a linear PE chain with minimal branching, LLDPE having short alkyl branches off a linear backbone, and LDPE having long PE branches that represent a significant portion of the total chain length. Increased branching will reduce material density, with HDPE densities ranging from $0.94\\ \\mathrm{g/mL}$ to $0.97\\ \\mathrm{g/mL}$ and LLDPE and LDPE densities ranging from $0.90\\mathrm{g/mL}$ to $0.94\\ \\mathrm{g/mL}$ (Peacock, 2000; Verleye et al., 2001). However, chemical weathering, natural aging, and biochemical processes affecting ingested plastics can modify their spectral features, making identification difficult (Mecozzi et al., 2016), which was evident in Brandon et al. (2016) in which $30\\%$ of marine debris polyethylene (PE) samples could not be differentiated. These particularly challenging pieces produce confusing spectra due to the similar intensities of bands at $1377\\mathrm{cm}^{-1}$ and $1368~\\mathrm{{cm}^{-1}}$ . No study has yet tested or provided criteria on how to differentiate these. \n\nThe goal of this study was to thoroughly assess the validity of attenuated total reflectance (ATR) FT-IR for identifying polymer composition of ingested plastic marine debris. This chemical technique is certainly not new and is common, but our study provides novel details that can help future studies avoid pitfalls, reduce confusion, and increase identification accuracy. We provide a clear guide with strict criteria to differentiate spectra from HDPE and LDPE. Furthermore, we identified and described the most effective cleaning method for preparing ingested plastic samples of three common polymers from pelagic, long-line caught olive ridley sea turtles to obtain high quality spectra. Sample handling was minimized to retain the original sample in a specimen bank for future additional chemical testing. To accomplish these goals, we developed an in-house spectral library from plastic consumer goods marked with resin codes. We validated our library with polymers originating from National Institute of Standards and Technology (NIST) Standard Reference Materials (SRMs) ${\\mathfrak{P}}$ , polymer standards obtained from scientific vendors, raw polymers sourced from manufacturers, and an additional set of consumer goods with polymer identity unknown to the analyst. PE materials of known density were used to confirm that ATR FT-IR is capable of discriminating between HDPE and LDPE, and to determine if a float/sink test in various dilutions of ethanol could further assist in differentiating these polymers. Using these optimized ATR FT-IR methods, we analyzed 828 ingested plastic items for polymer identity. A subset of these ingested samples was analyzed at NIST using high temperature size exclusion chromatography (HT-SEC) to confirm the accuracy of polymer identification by ATR FT-IR. \n\n# 2. Methods \n\n# 2.1. Plastic standards \n\nPlastic standards were obtained from four sources with different degrees of purity or certainty (see Supplemental material Table S1 for a complete list). Four NIST SRMs and 10 polymers that were sourced from scientific/laboratory vendors (scientifically sourced) were considered the purest or best characterized. Raw materials obtained from manufacturers were considered purer than the consumer goods collected, which could contain additives. These standards represent each resin code $\\#1$ through $\\#6$ , LLDPE, and several code $\\#7$ or other polymers (Table S1). The $\\#7$ category included polymers that could be found in marine debris, including acrylonitrile butadiene styrene (ABS), cellulose acetate (CA), ethylene vinyl acetate (EVA), latex, nitrile, nylon (represented by nylon 12 and nylon 6,6), polycarbonate (PC), poly (methyl methacrylate) (PMMA or acrylic), polytetrafluoroethylene (PTFE), fluorinated ethylene propylene (FEP), and polyurethane (PU). \n\nTwo to three consumer goods or raw materials labeled with each resin code were used to create standard spectra for each polymer. While consumer goods likely contain additives, the in-house spectral library was intentionally based on spectra from consumer goods, because they were assumed to more closely represent consumer items found in marine debris and ingested by marine organisms. \n\nTo validate the polymer identification by the analyst from ATR FTIR spectra, eleven additional consumer goods with stamped resin codes were used in a blind test (Table S1): PETE ${\\bf(n}=2)$ ), HDPE $\\left(\\mathbf{n}=3\\right)$ , LDPE ${\\bf(n=2)}$ ), PE of unknown density $(\\mathbf{n}=1)$ ), PP ${\\bf\\Pi}({\\bf n}=2)$ , and PS ${\\mathrm{(n~}}=1{\\mathrm{)}}$ ). \n\n# 2.2. ATR FT-IR instrument details \n\nA Perkin Elmer FT-IR Spectrometer Spectrum Two Universal ATR was used to collect spectra from $4000~\\mathrm{{cm}^{-1}}$ to $450~\\mathrm{cm}^{-1}$ with a data interval of $1\\mathrm{cm}^{-1}$ . Resolution was set at $4\\mathrm{cm}^{-1}$ . The ATR diamond crystal was cleaned with $70\\%$ 2-propanol and a background scan was performed between each sample. Each sample was compressed against the diamond with a force of at least $80\\mathrm{N}$ to ensure good contact between sample and ATR crystal, as recommended by Perkin Elmer. Absorption bands identified using a peak height algorithm within the Perkin Elmer software were recorded and compared to absorption bands of each polymer reported in the literature and obtained from our in-house spectral library (Tables 1 and 2). A minimum of four matching absorption bands were required for accepted identification. Spectra of consumer goods of each polymer type tested are shown in Fig. 1. No pre-existing spectral library or database was used in this study. This was intentional, because comprehensive libraries can be expensive. We wanted out approach to be available to all labs regardless of their resources. Secondly, relying solely on automated library searches and statistical methods can lead to inaccurate identifications. For example, we suspect the automated approach used by Mecozzi et al. (2016) to identify plastic fragments from a sea turtle gastrointestinal tract resulted in inaccurate results. Three fragments were identified as polyethylene oxide, which is typically a liquid at environmental temperatures. Manual assessment of the spectra may have avoided this potential mistake. \n\nWe validated the ability to differentiate HDPE and LDPE via the relative intensity of a small absorption band at $1377\\mathrm{cm}^{-1}$ , which represents the more abundant methyl group in highly branched LDPE (Asensio et al., 2009; Nishikida and Coates, 2003; Brandon et al., 2016). For samples determined to be PE, the spectral region of $1400~\\mathrm{{cm}^{-1}}$ to $1330\\mathrm{cm}^{-1}$ was examined closely by magnifying this region in Microsoft Excel scatterplots. PE spectra were binned into the following seven categories in which $1377\\mathrm{cm}^{-1}$ was 1) absent, 2) a shoulder on $1368~\\mathrm{{cm}^{-1}}$ , 3) a small bump on $1368~\\mathrm{{cm}^{-1}}$ , 4) the second largest band in this region, 5) nearly equal to $1368~\\mathrm{{cm}^{-1}}$ , 6) the strongest band in this region, 7) detected as a band by the instrument's software. The confidence of each bin to identify the PE type was assessed in three ways. Firstly, the ATR FT-IR spectral bin was recorded for each SRM, scientifically sourced or raw manufactured plastic standards of known PE. Secondly, the densities of PE standards and debris samples categorized across the bins were estimated via a float/sink test in different dilutions of ethanol (200 proof, A.C.S. reagent grade, Acros Organics, Fair Lawn, NJ) in deionized water. Dilutions were prepared volumetrically with graduated cylinders and ranged from $23\\%$ to $42\\%$ ethanol with approximately $2\\%$ increments. Density of the solutions was measured by weighing $25\\mathrm{mL}$ in a $25\\mathrm{-mL}$ graduated cylinder to the closest $_{0.0001\\ g}$ . Relative standard uncertainty in measuring the density of these solutions was $0.34\\%$ . The measured densities of all PE standards and 49 PE marine debris pieces collected from Main Hawaiian Island beaches were used to assign the piece to either HDPE or LDPE based on known densities of these polymers (Peacock, 2000; Verleye et al., 2001). The percentage of HDPE or LDPE assignments via the float test within each bin provided quantified confidence in using each bin and allowed us to set clear criteria. Thirdly, tentative ATR FT-IR assignments of ingested plastics from sea turtles (samples described below; 5 HDPE and 5 LDPE) were confirmed with HT-SEC with differential refractive index, infrared, and multi-angle light scattering detection at NIST (methods described below). \n\nDifferentiation between LLDPE and LDPE was tested by examining the regions between $650~\\mathrm{{cm}^{-1}}$ and $1000\\mathrm{cm}^{-1}$ . According to Nishikida and Coates (2003), absorbance bands at $890~\\mathrm{{cm}^{-1}}$ (vinylidene group) and $910~\\mathrm{{cm}^{-1}}$ (terminal vinyl group) should be of similar intensities and both weak for LLDPE, whereas they state that $890~\\mathrm{{cm}^{-1}}$ should be predominant in LDPE. These spectra regions from one scientifically sourced LLDPE and three consumer goods made of LLDPE were compared to several LDPE materials. \n\n# 2.3. Ingested plastic collection \n\nAs described in Clukey et al. (2017), 2880 ingested plastic pieces were found in the gastrointestinal (GI) tracts of olive ridley $\\mathrm{(n}=37\\mathrm{)}$ , green $(\\mathbf{n}=9)$ , and loggerhead ${\\bf(n=4)}$ ) sea turtles caught incidentally by the Hawaiian and American Samoan longline fishery between 2012 and 2015. Pieces were removed with hexane-rinsed forceps, rinsed with nanopore deionized water, gently cleaned with cleanroom wipers, wrapped in hexane-rinsed foil, placed in a FEP bag, and archived frozen as part of the Biological and Environmental Monitoring and Archival of Sea Turtle tissues (BEMAST) project of the NIST Marine Environmental Specimen Bank (Keller et al., 2014). \n\n# 2.4. Plastic preparation \n\nTo minimize instrument time, a subset of pieces $\\mathbf{\\tau}(\\mathbf{n}=828)$ was selected for this study that visually represented all other pieces found in each turtle. A three-category rugosity scoring system was applied to some of the pieces and defined as (1) smooth, (2) ridged, and (3) rugose (Fig. S1). Pieces were weighed before and after FT-IR analysis, repackaged and frozen for continued archival storage by BEMAST and future chemical analysis. \n\nEleven plastic fragments ingested by olive ridley sea turtles were chosen for testing five different cleaning methods, after being identified using absorption bands in Table 1 as HDPE ${\\mathrm{(n~}}=3{\\mathrm{)}}$ , LDPE $(\\mathbf{n}=5)$ , and PP $(\\mathbf{n}=3)\\AA$ . These fragments were analyzed by ATR FT-IR after undergoing five different treatments: (1) no additional cleaning, (2) wiping a small area with a dry cleanroom wiper, (3) wiping a new area with a cleanroom wiper that was wet with $70\\%$ 2-propanol from a LDPE squirt bottle, (4) wiping a third area with a cleanroom wiper wet with deionized water from a LDPE squirt bottle, and (5) cutting the piece with hexane-rinsed scissors or pliers to expose the inside surface of the fragment. Three spectra were generated for each cleaning method on each piece by analyzing the fragment on three non-overlapping sections of the cleaned area. The optimal cleaning method was determined as described below in statistical methods. These less destructive cleaning methods were chosen over chemical manipulation with acids and strong solvents as in Mecozzi et al. (2016) for green chemistry reasons and to minimize manipulation so that the samples could be archived by BEMAST and tested in the future for persistent organic pollutants. \n\nTable 1 List of important vibration modes and mode assignments for the ATR FT-IR spectra of eight of 16 polymers identified. The remaining eight polymers are in Table 2. Absorption ban listed are representative of vibrations critical for polymer identification. Please consult references for full lists of absorption bands. \n\n\n
PolymerResin codeChemical structureAbsorption bands (cm-1) used for identificationaAssignmentReference in addition to this study
Polyethylene terephthalate (PETE)11713 (a) 1241 (b)C=O stretchAsensio et al., 2009; Verleye et al., 2001; Noda et al., 2007
1094 (c) 720 (d)C-O stretch C-O stretch Aromatic CH out-of-
High-density polyethylene (HDPE)22915 (a)plane bend C-H stretchAsensio et al., 2009; Noda
n2845 (b)C-H stretchet al., 2007; Nishikida and
1472 (c)CH bendCoates,2003
1462 (d)CH bend
730 (e)CH2 rock
Polyvinyl chloride (PVC)3717 (f)CH2 rock
>1427 (a)CH2 bendBeltran and Marcilla, 1997;
n cl1331 (b)CH bendVerleye et al., 2001; Noda
1255 (c)CH bendet al.,2007
1099 (d)C-C stretch
966 (e)CH2 rock
Low-density polyethylene616 (f)C-Cl stretch
(LDPE) or linear LDPE42915 (a)C-H stretchAsensio et al., 2009; Noda
(LLDPE)I'n2845 (b)C-H stretchet al., 2007; Nishikida and
IR R = H or alkyl (LLDPE), PE (LDPE)1467 (c)CH bendCoates,2003
1462 (d)CH bend
1377 (e)CH3 bend
730 (f)CH2 rock
Polypropylene (PP)717 (g)CH2 rock
52950 (a)C-H stretchAsensio et al., 2009; Verleye
n2915 (b)C-H stretchet al., 2001; Noda et al., 2007
2838 (c)C-H stretch
1455 (d)CH2 bend
1377 (e)CH3 bend
1166 (f)CH bend, CH3 rock, C-C stretch
997 (g)CH3 rock, CH bend, CH bend
972 (h)CH3 rock, C-C stretch
840 (i)CH rock, C-CH3 stretch
808 (j)CH rock, C-C stretch,
Polystyrene (PS)63024 (a)C-CH stretch Aromatic C-H stretchAsensio et al., 2009; Verleye
n2847 (b)C-H stretchet al., 2001; Noda et al., 2007
1601 (c)Aromatic ring stretch
1492 (d)Aromatic ring stretch
1451 (e)CH bend Aromatic CH bend
1027 (f) 694 (g)Aromatic CH out-of-
plane bend
537 (h) Aromatic ring out-of-
Acrylonitrile butadiene styrene7plane bendVerleye et al., 2001
(ABS)P (1-p-β)2922 (a) 1602 (b)C-H stretch Aromatic ring stretch
N1494 (c)Aromatic ring stretch
1452 (d)CH2 bend
ABS is mixtureofcis,trans,and vinyl966 (e)=C-H bend
isomers, linear and crosslinked759 (f)Aromatic CH out-of- plane bend, =CH
bend
698 (g)Aromatic CH out-of-
Cellulose acetate (CA)71743 (a)plane bend C=O stretchIlharco and Brito de Barros,
1368 (b)CH3 bend2000; Verleye et al., 2001;
904 (c)Aromatic ring stretchNoda et al.,2007
or CH bend
600 (d)O-H bend
\n\na Resolution was $4\\mathrm{cm}^{-1}$ . Letters can be cross referenced to bands shown in ATR FT-IR spectra in Fig. 1. \n\n# 2.5. Analysis of ingested plastics for polymer type \n\nThe 828 ingested plastic pieces discovered in the turtles were analyzed by ATR FT-IR by first cleaning a small area with water and cleanroom wiper or cutting to expose a smooth clean surface. Polymers were identified based on presence of absorption bands as described in Table 1 and shown in Fig. 1. Pieces producing absorption bands consistent with both PE and PP were assigned as “mixture” (Fig. 2). Pieces that could not be identified by ATR FT-IR spectra (e.g., presence of less than four identifying absorption bands) were assigned “unknown.” A subset of pieces that were identified by ATR FT-IR was analyzed by high HT-SEC with differential refractive index, infrared, and multi-angle light scattering detection. \n\nTable 2 List of important vibration modes and mode assignments for the ATR FT-IR spectra for the remaining eight of 16 polymers identified. Absorption bands listed are representative o \n\n\n
vibrations critical for polymer identification.Please consult references for fullists of absorption bands.
PolymerResin code Chemical structureAbsorption bands (cm -1) used forAssignmentReference in addition to this study
Ethylene vinyl acetate (EVA)7identificationaC-H stretchAsensio et al., 2009; Verleye et al., 2001
[(1-p) 02917 (a) 2848 (b)C-H stretch
1740 (c)C=O stretch CH bend, CH3
1469 (d)bend
1241 (e)C(=0)0 stretch
1020 (f)C-O stretch
CH rock
720 (g)
2960 (a)C-H stretch Guidelli et al., 2011 C-H stretch
(1-p)2920 (b) 2855 (c)C-H stretch
1167 (d)C=C stretch
Mixture of cis and trans; natural latex does not1447 (e)CH bend
1376 (f)CH3 bend
contain styrene copolymer 2917 (a)=C-H stretch Coates, 2000; Verleye
Nitrile(1-p) Mixture of ci an trans2849 (b)=C-H stretchet al.,2001
2237 (C- strtreheh
1440 (e)
CH2 bend
1360 (f) 1197 (g)CH bend CH2 bend
Nylon (all polyamides)7967 (h)=C-H bendRotter and Ishida, 1992; Verleye et al., 2001;
3298 (a) 2932 (b)N-H stretch CH stretch
CH stretch Noda et al., 2007
2858 (c)
r and b vary from 0 to 12 based on monomer 1634 ()G= end, cb-N
stretch
1464 (f) 1372 (g)CH bend CH bend
Polycarbonate (PC)1274 (h)NH bend, C-N stretch
1199 (i)CH bend
687 (i) NH bend,C=O
bendAsensio et al., 2009;
2966 (a) 1768 (b)CH stretch C=O stretchVerleye et al., 2001; Noda et al., 2007
1503 (c)Aromatic ring
1409 (d)stretch Aromatic ring
stretch
1364 (e)CH3 bend
1186 (f)C-O stretch
1158 (g)C-O stretch
1013 (h)Aromatic CH in-
plane bend
828 (i)Aromatic CH out-
Poly(methyl methacrylate) (PMMA or acrylic)7'nof-plane bend
2992 (a)C-H stretchVerleye et al., 2001
2949 (b)C-H stretch
1721 (c)C=O stretch
1433 (d)CH2 bend
1386 (e)CH bend
1238 (f)C-O stretch
1189 (g) 1141 (h)CH3 rock C-O stretch CH rock
985 (i) 964 ()C-H bend
750 (k)CH rock, C=O
bendCoates, 2000; Verleye
1201 (a)CF2 stretch CF2 stretchet al.,2001
1147 (b)
(FEP) Polyurethane (PU) 7638 (d)C-C-F bend CF2 bend
554 (e)
509 (f) 2865 (a)CF2 bend C-H stretchAsefnejad et al., 2011;
1731 (b) 1531 (c)C=O stretch C-N stretch CH bendVerleye et al., 2001; Noda et al., 2007
\n\na Resolution was $4\\mathrm{cm}^{-1}$ . Letters can be cross referenced to bands shown in ATR FT-IR spectra in Fig. 1. \n\n![](images/7c69f72aabeea4e17771d1122dd2fa715406680ee1a43a99fb0611fc64d6054c.jpg) \nFig. 1. Spectra produced from plastic consumer goods labeled with resin codes of (a) polyethylene terephthalate (PETE, $\\#1\\mathrm{\\cdot}$ , (b) high-density polyethylene (HDPE, $\\#2\\rangle$ , (c) polyvinyl chloride (PVC, #3), (d) low-density polyethylene and linear low density polyethylene (LDPE and LLDPE, $\\#4)$ , (e) polypropylene (PP, $\\#5\\mathrm{\\cdot}$ , and (f) polystyrene (PS, $\\#6)$ along with ten other polymers: $\\mathbf{\\delta}(\\mathbf{g})$ acrylonitrile butadiene styrene (ABS), (h) cellulose acetate (CA), (i) ethylene vinyl acetate (EVA), (j) latex, (k) nitrile, (l) nylons, $\\mathbf{\\tau}(\\mathbf{m})$ polycarbonate (PC), (n) poly (methyl methacrylate) (PMMA), (o) polytetrafluoroethylene (PTFE) or fluorinated ethylene propylene (FEP), and (p) polyurethane (PU) using ATR FT-IR. Letters represent characteristic absorption bands $(\\mathrm{cm}^{-1})$ used to identify each polymer. \n\nSamples for HT-SEC were sonicated in ethanol for $10\\mathrm{min}$ , followed by $10\\mathrm{min}$ sonication in nanopure deionized water $(18.2\\mathrm{M}\\Omega)$ to remove aqueous soluble contaminants and minimize the addition of biological contaminants to the instrument. Approximately $10\\mathrm{mg}$ of each sample was encased in a $5\\upmu\\mathrm{m}$ stainless steel mesh and dissolved in HPLC grade $^{1,2,4}$ -trichlorobenzene under nitrogen atmosphere for $^{\\textrm{1h}}$ prior to injection in the instrument, allowing soluble polymers to dissolve and pass through the mesh, and insoluble debris, filler, or crosslinked components to remain sequestered in the mesh. The samples were injected into a Polymer Characterization (Valencia, Spain) GPC-IR instrument with an IR 4 detector consisting of two infrared IR detection bands, $2800~\\mathrm{{cm}^{-1}}$ to $3000~\\mathrm{{cm}^{-1}}$ representing the entire $\\mathsf{C}{\\mathrm{-}}\\mathsf{H}$ stretching region (CH, $\\mathrm{CH}_{2},$ , and $\\mathrm{CH}_{3})$ ), and a narrow band at $2950\\mathrm{cm}^{-1}$ for the methyl $\\mathsf{C}{\\mathrm{-}}\\mathsf{H}$ stretch absorbances, respectively, as well as a Wyatt Technology (Santa Barbara, CA) Dawn Heleos II multi-angle light scattering (MALS) detector with 18 angles and a forward monitor (zero angle detector). Separately, the samples were also injected on a Tosoh (Tokyo, Japan) HT-Eco SEC with differential refractive index detection. Both instruments ran at $160^{\\circ}\\mathrm{C}$ with a $^{1,2,4}$ -trichlorobenzene mobile phase with 300 ppm Irganox 1010 added as an antioxidant. The stationary phase columns used in both systems are a set of three Tosoh HT2 columns (two, Tosoh TSKgel GMHhr-H (S) HT2, $13\\upmu\\mathrm{m}$ mixed bed, $7.8\\:\\mathrm{mm}\\:\\mathrm{ID}\\times30\\:\\mathrm{cm}$ columns and one, Tosoh TSKgel GMHHR-H (20) HT2, $20\\upmu\\mathrm{m}$ , $7.8\\mathrm{mm}$ $\\begin{array}{l l l}{\\mathrm{ID}}&{\\times}&{30\\mathrm{cm}}\\end{array}$ column with an exclusion limit $\\approx4\\times10^{8}\\mathrm{g/mol})$ . Sample molar masses, molar mass distribution, short chain branching content (SCB), were determined by calibration with narrow molar mass distribution PS standards, NIST SRM 1475a (linear, broad, HDPE), and NIST SRM 1478 (to determine interdetector delay and normalize photodiode response of the MALS detector), and 10 blends of linear PE and PP with systematic variation of PP content, where the total degree of short chain branching (SCB) was confirmed by nuclear magnetic resonance spectroscopy (NMR). Calibration and data analysis was performed by proprietary software from each instrument vendor. HT-SEC and NMR have many advantages, but they can only measure polymer chains that are soluble under the solvent and temperature conditions used and they are not highthroughput like ATR-FTIR, which measures the bulk sample. \n\n![](images/f557dc94d1e0146966e3125e3bb16f538a0e8afa38d947f492133c8d93996e8c.jpg) \nFig. 1. (continued) \n\n![](images/849660cb500e0911401bbb4f988d690fda4a2da719767a57edb10a368e016975.jpg) \nFig. 2. ATR FT-IR spectrum of an ingested plastic fragment assigned as a mixture of polyethylene (PE) and polypropylene (PP). Wavenumbers in boxes are characteristic of PE, underlined wavenumbers are characteristic of both PE and PP, and unmarked wavenumbers are characteristic of PP. \n\n# 2.6. Data handling and statistical analysis \n\nOrdination was used to synthesize the absorbance data, in order to: 1) determine if novel absorption bands at additional wavenumbers could distinguish HDPE and LDPE, and 2) investigate if clustering of “unknown” ingested pieces near known polymers could help to identify their polymer composition. MetaboAnalyst software was used and the “normalized by sum” option was chosen so that all spectral bands had equal weight and samples could be compared. Two principal component analyses (PCAs) were performed on different sample sets. PCA1 included spectra from three consumer goods of each of the following polymers: HDPE, LDPE, and PP. PCA2 included 797 ingested plastic pieces (793 identified, 4 unknown) of nine identified polymer types. Because PCA requires at least three samples of each polymer and less than three ingested pieces of PVC and nylon were discovered, it was necessary to include the spectra of consumer good items representing PVC and nylon in PCA2. PCA1 was run using bins of four wavenumbers over the entire spectral range of $4000\\mathrm{cm}^{-1}$ to $450\\mathrm{cm}^{-1}$ while PCA2 used selected absorption bands within a range o $\\mathsf{f}\\pm1\\mathrm{cm}^{-1}$ identified in Table 1 (plus additional bands from the literature) for polymers included in the analysis. All possible absorption bands were included in PCA1 to discover novel absorption bands for distinguishing HDPE from LDPE. No transformations were performed and Pareto scaling was used for both PCAs. \n\nThe optimal cleaning method was determined in two ways: 1) determining the percent of spectra that provided visually identifiable polymer assignment (good vs. poor quality spectra), and 2) counting the number of detectable absorption bands used for identification of that particular polymer. Wavenumbers with absorption bands greater than three times the noise surrounding the absorption band were recorded as detectable wavenumbers. All variables were tested for normality using the Shapiro-Wilk tests in IBM SPSS Statistics Version 24. \n\nBecause normality could not be accomplished even after data transformations, non-parametric Friedman's ANOVA tests followed by Wilcoxon signed-rank tests were used to compare differences in cleaning methods using two different response variables: percent of identifiable spectra and number of identifiable absorption bands greater than three times the noise. A Spearman Rank Order correlation was used to determine if rugosity had an effect on the number of detectable wavenumbers. \n\n# 3. Results and discussion \n\n# 3.1. ATR FT-IR polymer identification of consumer goods, raw manufactured, or scientifically sourced polymers \n\nPlastic consumer goods from known resin codes produced spectra with expected absorption bands (Fig. 1, Table 1). When compared to the spectra of raw manufactured polymers or scientifically sourced polymers, the appearance and number of identifiable wavenumbers were nearly identical (data not shown). Absorption bands identified for these polymers were either a direct match or within four wavenumbers of the absorption bands listed in Table 1. Of the 18 polymers tested, all could be easily distinguished from each other with only three minor exceptions (Fig. 1). Spectra of FEP and PTFE showed absorbance bands at the same wavenumbers and with the same intensity for $638~\\mathrm{{cm}^{-1}}$ , $554~\\mathrm{{cm}^{-1}}$ , and $509\\mathrm{cm}^{-1}$ , but the intensity of $1201~\\mathrm{{cm}^{-1}}$ ( $\\mathrm{CF}_{2}$ stretch) and $1147~\\mathrm{{cm}}^{-1}$ ( $\\mathrm{CF}_{2}$ stretch) were $16\\%$ and $27\\%$ higher, respectively, in PTFE than FEP. All types of nylon produced the same absorbance bands, so nylon-12 cannot be distinguished from nylon 6,6 or others (Verleye et al., 2001). Differentiating among HDPE, LLDPE, and LDPE is challenging, but our goal was to develop a simple ATR FT-IR method so that discrimination by sample destructive methods, such as HT-SEC with infrared detection or differential scanning calorimetry (DSC), is not required. Our results confirm that ATR FT-IR can identify consumer goods produced from PETE, PEs, PVC, PP, PS, ABS, CA, EVA, latex, nitrile, nylons, PC, PMMA, (PTFE or FEP), and PU, but PE samples require closer inspection of the ATR FT-IR spectra to distinguish HDPE from LDPE. \n\nThe use of ATR FT-IR for polymer identification was further confirmed via a blind test, in which 11 consumer goods consisting of diverse polymers were correctly identified by an analyst without prior knowledge of the resin code (Table S1). The five PE samples were all correctly identified as PE, but some could not be further categorized as either HDPE or LDPE. Of the three HDPE samples, one was correctly assigned and two were categorized as unknown PE. Of the two LDPE, one was correctly assigned and one was assigned unknown PE. \n\nIn hopes of discovering additional absorbance bands to distinguish HDPE from LDPE, a PCA was performed including the spectra of consumer goods of HDPE ${\\bf(n=3)}$ ), LDPE $\\left(\\mathbf{n}=3\\right)$ ), and PP $\\left(\\mathbf{n}=3\\right)$ ). The PCA showed no separation between HDPE and LDPE (Fig. S2). The first two principal components (PC) explained $78.3\\%$ of the variance and the loadings are shown in Table S2. This biplot revealed absorbance bands that differentiate PE from PP $(700\\mathrm{cm}^{-1}$ to $730\\mathrm{cm}^{-1}$ , $\\mathrm{CH}_{2}$ rock), but no novel bands that could distinguish HDPE from LDPE (Fig. S2). While additional PCs explained more of the variation $(14.7\\%$ by PC3 and $6\\%$ by PC4), they did not provide any additional separation of HDPE from LDPE. This is because HDPE and LDPE share the same major structural unit, functional groups, chemical bonds (Asensio et al., 2009), and therefore have many identical wavenumbers (Table 1). However, the different degree of branching results in small, but important differences, in the spectral region of $1400\\mathrm{cm}^{-1}$ to $1330\\mathrm{cm}^{-1}$ with LDPE having greater intensity at $1377\\mathrm{cm}^{-1}$ due to methyl bending deformation of the branched chain ends (Asensio et al., 2009; Nishikida and Coates, 2003). This band may have been too small for the PCA to detect and must be magnified and compared to the intensity of $1368~\\mathrm{{cm}^{-1}}$ manually. \n\nThe differentiation between LDPE and HDPE with the presence of a \n\n![](images/f1c3b80161578ab9c7d2ceddb28b495eb187728c11d742a9f2030f2cc63e27cb.jpg) \nFig. 3. Decision flow chart for differentiating high-density polyethylene (HDPE), linear low-density polyethylene (LLDPE), and low-density polyethylene (LDPE) using ATR FT-IR spectra and float/sink tests. \n\n$1377\\mathrm{cm}^{-1}$ band is easy in some spectra, while others are more challenging. PE spectra fell into seven different bins based on the observation of the $1377\\mathrm{cm}^{-1}$ band being: 1.) absent, 2.) a tiny shoulder, 3.) a small bump, 4.) the second largest in the $1400~\\mathrm{{cm}^{-1}}$ to $1330\\mathrm{cm}^{-1}$ region, 5.) nearly equivalent to $1368~\\mathrm{{cm}^{-1}}$ band, 6.) the largest in this region, and 7.) detected by the instrument's software (Fig. 3). Bins at the extremes (1 and 2 are HDPE; 6 and 7 are LDPE) are clear, but those in the middle are ambiguous (bins 3, 4, and 5) and cause substantial confusion. \n\nTable S1 describes ATR FT-IR results of each standard and consumer good tested. All but one of the SRMs, raw manufactured plastic or scientifically sourced standards of known PE $({\\mathfrak{n}}=10$ for HDPE, $\\mathtt{n}=4$ LLDPE, and ${\\mathfrak{n}}=17$ LDPE) were correctly and easily assigned because they fell in the clear bins (Table S1). One LDPE standard, SRM 1474b, fell into bin 3. Fourteen consumer good standards were stamped with HDPE $\\mathrm{(n=6)}$ , LLDPE $\\left(\\mathbf{n}=3\\right)$ , or LDPE $(\\mathbf{n}=5)$ . Of these, eight $(57\\%)$ were accurately assigned because they produced unambiguous spectra, six $(43\\%)$ produced ambiguous spectra, and one $\\left(0.1\\%\\right)$ with a clear spectrum was inaccurately assigned. Three of the six ambiguous samples were thin bags used for produce, shopping, and shipping. The incorrect standard was a grocery shopping bag stamped with $\\#2$ resin code (HDPE), but $1377\\mathrm{cm}^{-1}$ was the strongest peak. These results suggest that thin sheet bags are consistently the most ambiguous and challenging to assign to HDPE versus LDPE for reasons currently unknown. \n\nThe other three ambiguous spectra came from all three LLDPE consumer goods tested. Because LLDPE has intermediate extents of branching, this was not surprising. Unfortunately, bins 3, 4, and 5 cannot be considered LLDPE, because materials known to be HDPE and \n\nLDPE also produced spectra in these bins. A method to distinguish LLDPE from LDPE samples was proposed using another region of the spectra $650~\\mathrm{cm}^{-1}$ to $1000~\\mathrm{{cm}^{-1}};$ by Nishikida and Coates (2003). They report that LLDPE should have equal and weak bands at $890~\\mathrm{{cm}^{-1}}$ (vinylidene group) and $910~\\mathrm{{cm}^{-1}}$ (terminal vinyl group), whereas $890~\\mathrm{{cm}^{-1}}$ is larger in LDPE. We could not confirm this method with a close examination of this spectral region with four LLDPE and 18 LDPE standards (Table S1). The four known LLDPE standards produced variable results. The LLDPE trash bag had equally weak bands, as expected. The LLDPE biohazard bag produced a band at $890~\\mathrm{{cm}^{-1}}$ was larger but nearly equal to the $910~\\mathrm{{cm}^{-1}}$ band. However, the scientifically sourced LLDPE sample produced no band at $890~\\mathrm{{cm}^{-1}}$ and a small band at $910~\\mathrm{{cm}^{-1}}$ , and the LLDPE tubing produced a larger band at $910~\\mathrm{{cm}^{-1}}$ than $890~\\mathrm{{cm}^{-1}}$ . As expected, 14 of the 18 LDPE samples $(78\\%)$ produced a more intense $890~\\mathrm{{cm}}^{-1}$ band than $910~\\mathrm{{cm}^{-1}}$ . Three materials produced equally intense peaks (SRM 1476a, a swimmer's ear bottle, and a shipping bag), and for this reason we suspect they were produced with LLDPE. One produced a very small band at $910~\\mathrm{{cm}^{-1}}$ and no band at $890~\\mathrm{{cm}}^{-1}$ (a breastmilk storage bag). The inconsistent results within the known LLDPE standards did not give enough confidence to use this distinguishing method. Therefore, we conclude that LLDPE and LDPE cannot be distinguished from each other using ATR FT-IR. \n\nIn the ambiguous bins 3, 4, and 5, the $1377\\mathrm{cm}^{-1}$ band appears as a small bump on the tail of the $1368~\\mathrm{{cm}^{-1}}$ band, a distinct but smaller band than $1368~\\mathrm{{cm}^{-1}}$ , or equivalent to the intensity of $1368~\\mathrm{{cm}^{-1}}$ respectively. Confidence to assign these bins to a particular PE was assessed, for the first time to our knowledge, by estimating the density of PE samples using a float/sink test in different dilutions of ethanol. Using a graduated cylinder to volumetrically prepare solutions resulted in inaccuracies of solution densities of up to $0.02\\mathrm{g/mL}$ . Because distinguishing between $0.93\\mathrm{g/mL}$ and $0.94~\\mathrm{g/mL}$ required better accuracy, the density of the solutions was determined by weighing $25\\mathrm{mL}$ in a graduated cylinder. Relative standard uncertainty in measuring the density of these solutions was $0.34\\%$ . Resulting estimated densities for each standard item are shown in Table S1. All PE standards that were not stamped or labeled with a resin code that were subsequently assigned LDPE because they fell in bins 6 and 7 $\\mathbf{\\rho}(\\mathbf{n}=4)$ ), floated in solutions $\\mathrm{>0.931g/mL}$ as expected. This added more confidence to our LDPE criteria. Furthermore, 19 of the 20 known LDPE or LLDPE standards $(95\\%)$ tested had estimated densities of $0.938\\mathrm{g/mL}$ or less; and all ten known HDPE standards had estimated densities of $0.938\\mathrm{g/mL}$ or greater. Unexpectedly, one LDPE thin shipping bag sank in solutions up to $0.950~\\mathrm{g/mL}$ . Its greater density may be attributed to a silver-colored inner layer of unknown polymer composition. \n\nBecause our methods to differentiate HDPE from LDPE were slightly less successful in consumer goods than in raw or scientifically sourced standards, we confirmed our method using marine debris samples. Forty-nine plastic debris items collected from Main Hawaiian Island beaches that were discovered to be PE by ATR FT-IR were categorized as bin 1 $(\\boldsymbol{\\mathrm{n}}=3)$ , bin 2 ${\\bf(n=14)}$ ), bin 3 $(\\mathbf{n}=1)$ ), bin 4 $(\\mathbf{n}=5)$ , bin 5 $(\\boldsymbol{\\mathrm{n}}=13)$ , and bin 6 ${\\mathrm{(n}}=13{\\mathrm{)}}$ ). These fragments were tested for floating or sinking in solutions with targeted densities of $0.935\\mathrm{g/mL}$ and $0.941~\\mathrm{g/mL}$ . All of bin 1 samples sank, as expected for HDPE. $86\\%$ of bin 2 samples sank, providing enough confidence to conclude spectra with a shoulder at $1377\\mathrm{cm}^{-1}$ are very likely HDPE. The one sample in bin 3 sank, suggesting samples producing a very small bump at $1377\\mathrm{cm}^{-1}$ are HDPE, but our sample size was too small to have certainty. Only $40\\%$ of bin 4 and $46\\%$ of bin 5 floated in both solutions, suggesting these polymers could be either HDPE or LDPE when $1377\\mathrm{cm}^{-1}$ is the second largest band or equivalent to $1368~\\mathrm{{cm}^{-1}}$ . $85\\%$ of bin 6 samples floated in both solutions, giving us enough confidence to confirm that spectra with $1377\\mathrm{cm}^{-1}$ as the largest band are likely LDPE, even though the instrument's software does not detect it. \n\nThe inter-laboratory comparison using HT-SEC on PE ingested plastic samples, confirmed that ATR FT-IR assignments were $100\\%$ \n\nTable 3 Comparison of identifications of ingested plastic samples analyzed by attenuated total reflectance Fourier transform infrared spectroscopy (ATR FT-IR) and high-temperature size exclusion chromatography (HT-SEC) with infrared, differential refractive index, and multi-angle light scattering detection. \n\n\n
HT-SEC results
Identification by ATR FT-IRIdentification by HT-SECRI peak magnitudeAverage CH3/ 1000 total CaMn (kg/ mol)cMw (kg/ mol)c
PETEPUb
HDPEHDPE11.2 ± 71.136.2
HDPEHDPE10.6 ± 826.6161.2
HDPEHDPE6.2±96.083.8
HDPEHDPE9.9 ± 155.032.8
HDPEHDPE5.7±915.280.4
LDPELDPE24.0 ± 542.5148.3
LDPELDPE35.8 ±170.970.9
LDPELDPE48.3 ± 162.565.6
LDPELDPE25.7 ± 932.0148.4
LDPELDPE54.7 ± 1233.2197.1
PPPP338.7 ±642.4196.4
PPPP348.4 ± 184.758.6
PPPP303.5 ±56.844.5
PSPS+15.2 ± 2321.752.5
PSPS+35.2 ± 2728.2557.2
PSPS+34.1 ± 51137.6281.7
\n\na Represents the relative methyl content of the polymer across the measured molar mass distribution. Error represents one standard deviation of the methyl content across all molar masses measured. Precision of molar mass measurements is $\\leq5\\%$ of reported value based on repeat injections of mass standards run during sample analyses. \n\nb Measured by XPS survey scan. \n\nc Polymer number average (Mn) and mass average (Mw) molar masses determined by MALS detection. \n\naccurate (Table 3). These samples all produced unambiguous spectra $({\\bf n}=5$ HDPE, $\\mathtt{n}=5$ LDPE). Taken together the results suggest there is a high confidence in unambiguous ATR FT-IR spectra to distinguish HDPE from LDPE. However, ambiguous spectra (bins 3–5) cannot be assigned to a particular PE polymer without further testing, and ATR FT-IR spectra cannot be used to distinguish LDPE from LLDPE. A detailed step-by-step decision tree outlines our criteria for distinguishing HDPE from LDPE using ATR FT-IR in addition to a float/sink test (Fig. 3). Once samples are determined to be PE based on absorbance bands listed in Table 1, the spectral region between $1330\\mathrm{cm}^{-1}$ and $1400~\\mathrm{{cm}^{-1}}$ is magnified and each sample is matched to the most similar bin. Samples falling in bins 1 and 2 are assigned HDPE. Those in bins 3–5 are considered unknown PE until further testing can be done. Those in bins 6 and 7 are assigned LDPE or LLDPE. The unknown PE samples that are not air-filled can be placed into a $0.935\\mathrm{g/mL}$ solution of ethanol. If they float, they are assigned LDPE or LLDPE. If they sink, they are assigned HDPE. The approach described in this decision tree should help future studies with the often confusing, yet very important, differentiation of HDPE and LDPE. \n\n# 3.2. Cleaning methods for polymer identification of ingested plastics \n\nTo our knowledge, no study had addressed how digestive processes affect the FT-IR spectra of polymers, so we determined an optimal cleaning method that would also preserve the samples for future chemical testing. The spectra from the 11 ingested fragments after cleaning with water were of higher quality and easier to identify than before cleaning (Fig. S3), with the noise reduced and the absorbance bands more prominent. Thus, this test suggests that this simple treatment, involving removing surface residue with a cleanroom wiper and water, increases the ability to identify plastic polymers. \n\nOnly half of the spectra were of good enough quality to identify the polymer when no cleaning was performed on the samples $(58\\%~\\pm~29\\%$ standard deviation), whereas $100\\%$ of spectra were identifiable with the other four cleaning methods (Fig. S4). Significant differences in the percent of spectra that could be identified were found among the five cleaning methods (Friedman's analysis of variance (ANOVA), $x^{2}(4)=26.20,\\mathrm{p~<~}0.0001,\\mathrm{n}=11\\mathrm{1}$ ). Post-hoc comparisons using Wilcoxon signed-rank tests revealed that all four sample treatments (wiping $(\\mathtt{p}=0.004$ , $\\mathbf{n}=11\\mathbf{\\dot{\\mathrm{.}}}$ , cleaning with 2-propanol $(\\mathtt{p}=0.004$ , $\\mathbf{n}=11\\mathbf{\\dot{\\mathrm{~.~}}}$ ), water $(\\mathtt{p}=0.004$ , $\\mathbf{n}=11\\mathbf{\\dot{\\Omega}}$ ), or cutting $(\\mathtt{p}=0.004$ , $\\mathbf{n}=11)$ ) resulted in a greater percentage of the spectra being identified, when compared to no cleaning (Fig. S4). No significant differences were found among the four cleaning methods. These results suggest that cleaning a polymer of ingested plastic fragments with any of the four methods should improve quality of ATR FT-IR spectra. \n\n![](images/dca311a6925610118e576926f36811cb01d43dc4ed3238a3ef064c93f4161920.jpg) \nFig. 4. Mean and standard deviation of the number of detected wavenumbers for five different cleaning methods on ingested high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polypropylene (PP) fragments. Different letters above bars indicate significant differences among cleaning techniques within a polymer type $(\\mathtt{p}\\ <\\ 0.05$ Wilcoxon signed-rank tests). \n\nThe number of detected peaks increased significantly for all three polymer types after performing any of the four cleaning methods (Fig. 4). The number of detected peaks and rugosity codes for each cleaning method for each fragment can be found in Table S3. Significant differences were found among the five cleaning methods for HDPE (Friedman's ANOVAs, $x^{2}(4)=27.41$ , $\\mathrm{~p~<~}0.0001\\$ , for LDPE $(x^{2}(4)=34.992,\\mathrm{p~<~}0.0001)$ and for PP $(x^{2}(4)=19.92$ , $\\begin{array}{r}{\\mathbf{p}=0.001_{-}^{}}\\end{array}$ . For HPDE, wiping (Wilcoxon $\\mathbf{p}=0.007)$ , 2-propanol $(\\mathtt{p}=0.006)$ , water $(\\mathtt{p}=0.005)$ , and cutting $(\\mathtt{p}=0.018)$ produced significantly more detectable peaks than no treatment. Cleaning HDPE fragments with water also produced significantly more detectable peaks when compared to wiping $(\\mathtt{p}=0.008)$ , 2-propanol $(\\mathtt{p}=0.008)$ , and cutting $(\\mathtt{p}=0.014)$ . Similar results were seen with PP and LDPE ingested fragments (Fig. 4). These differences suggest that cleaning the surface of ingested fragments with water will produce the spectrum with the most detectable peaks and this method might be preferred if the goal is to minimize handling so that the pieces can be used in the future for additional chemical testing, such as measuring sorbed persistent organic pollutants. \n\nLDPE fragments with a higher rugosity code yielded fewer detectable peaks $(\\mathbf{r}_{s}=-0.803$ , $\\mathbf{n}=5$ , $\\mathtt{p}=0.102)$ , although the relationship was not significant (Fig. S5). In contrast, when fragments were cut, no significant correlation was found between the number of detectable peaks and rugosity codes $(\\mathbf{r}_{s}=0.631$ , $\\mathbf{n}=5$ , $\\mathfrak{p}=0.254\\rangle$ ). This is most likely due to rugosity being reduced when a fragment is cut. Therefore, if a rugose fragment cannot be identified after being cleaned with water, cutting may be the most effective cleaning method as it can allow for the sample to come in more direct contact with the diamond and thus evanescent wave, resulting in more detectable peaks. \n\n![](images/051fdfe53902f72ceab4f5a9f8a1d914fd2540377be3ab4153548a202eda4919.jpg) \nFig. 5. PCA ordination of spectra from ingested plastic samples identified as high-density polyethylene (HDPE, $\\mathrm{~n~}=58\\mathrm{{^{\\circ}}}.$ , polyvinyl chloride (PVC, $\\mathbf{n}=1\\mathbf{\\dot{2}},$ ), low-density polyethylene (LDPE, $\\mathbf{n}=310\\mathbf{\\dot{\\Omega}}.$ ), polypropylene (PP, $\\begin{array}{r}{\\mathrm{~n~}=270_{,}^{\\circ}}\\end{array}$ , polystyrene (PS, $\\mathbf{n}=7\\mathbf{\\cdot}$ ), nylon $\\mathbf{\\rho}(\\mathbf{n}=1)$ , PE/PP mixture $\\mathrm{(n=40)}$ ), unknown PE $\\left(\\mathbf{n}=106\\right)$ , and unknown ${\\mathrm{(n}}=4{\\mathrm{)}}$ . Spectra of consumer good items representing PVC $\\left(\\mathbf{n}=3\\right)$ and nylon $(\\mathbf{n}=3) $ ) were also included. The amount of variation in the data explained by each principal component is shown in parentheses. \n\n# 3.3. Method validation with ingested polymers \n\nOnly 30 of the 828 ingested plastic pieces analyzed $(4\\%)$ produced spectra of poor quality that could not be identified by ATR FT-IR. Criteria for differentiating HDPE and LDPE (even without the float/sink test, which was not applied to these samples) allowed assignment of $77.7\\%$ of the PE pieces, while $22.3\\%$ of PE samples fell in the unknown PE category. This proportion is similar to the $70\\%$ assignment capability of oceanic microplastics by Brandon et al. (2016). \n\nPCA was performed on spectra from 797 representative ingested plastic pieces identified as HDPE $\\mathrm{(n}=58\\mathrm{)}$ ), PVC $(\\mathbf{n}=1)$ , LDPE or LLDPE $({\\mathfrak{n}}=310$ ; one outlier was removed), PP $(\\mathbf{n}=270$ ; one outlier was removed), PS $(\\mathbf{n}=7)$ , nylon $(\\mathbf{n}=1).$ , mixture of PP and PE $\\left({\\mathfrak{n}}=40\\right)$ , unknown PE ${\\mathrm{(n}}=106{\\mathrm{)}}$ ) and unknown ${\\bf\\Pi}({\\bf n}=4)$ ) along with plastic consumer goods of PVC and nylon. The PCA shows distinction between PEs and PP (Fig. 5; Table S4 for loadings) with $85.8\\%$ of the variance explained within the first two principal components. In an earlier version of the PCA, more of the ingested pieces, a total of 10, were originally identified as unknown (data not shown). The clustering of six of the unknown samples within the PCA, followed by further review of their ATR FT-IR spectra, allowed polymer assignment of these samples. These results suggest that PCA is a tool that can help interpret ambiguous spectra. Plastic pieces identified as a mixture were located between clusters for PE and PP as expected. In order to improve assignment of these predominantly olefinic polymers, HT-SEC with multiple detectors was used to definitively identify the samples as a mixture of PE and PP, and confirm results of the PCA. \n\nSixteen of 17 ingested plastic samples were positively identified by HT-SEC. All HT-SEC determined identities matched those obtained by ATR FT-IR, as shown in Table 3. Example chromatograms for three samples, identified as PS, LDPE, and HDPE are shown in Fig. 6. A number of qualitative and quantitative pieces of information were used to identify the polymers analyzed by HT-SEC. First, the injected polymer samples demonstrated a positive or negative differential refractive index (RI) peak as they eluted from the columns, indicative that the polymer had a greater or lesser refractive index than the mobile phase $(\\mathtt{n}_{0}=1.56)$ . Refractive indices of commercial polymers are available from a number of sources (Brandrup et al., 1999; Mark, 2007). This qualitative identification is used to rule out general classes of polymers; for example, polyolefins (PP, HDPE, LDPE) have a refractive index $<1.56$ , so these polymers must have a negative RI elution peak (Table 3, Fig. 6b and c). \n\n![](images/2ee659ddfb2e786eded30da6f4513b986e25c9bd1c90dd4987558767d05091a9.jpg) \nFig. 6. Representative HT-SEC chromatograms of samples run to confirm ATR-FTIR materials for ingested samples identified as (a) polystyrene (PS) (b) low-density polyethylene (LDPE) (c) high-density polyethylene (HDPE). The $\\mathrm{CH}_{3}/1000$ total C were measured by the ratio of the two IR signals, methyl stretching bands and alkyl stretching bands at $2950\\mathrm{cm}^{-1}$ and (2800 to 3000) $\\mathrm{cm}^{-1}$ (broad detector range), being represented by the orange and red traces, respectively. The asterisk $(^{*})$ denotes an added flow rate marker, dodecane, used as an internal standard. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) \n\nDifferentiation between PP, HDPE, and LDPE was based on the degree of short chain branching, which was measured using the HT-SEC IR detector. The flow-through IR detector measures alkyl and methyl $\\mathsf{C}{\\mathrm{-}}\\mathsf{H}$ stretching simultaneously as the separated polymer elutes. The ratio of the two absorption spectra at each elution volume (Fig. 6), when compared to a calibration curve, permit branching content to be determined across the molar mass distribution. As ATR FT-IR is a bulk measurement, the branching content measured by HT-SEC was averaged across the molar mass distribution for each sample and the average methyl content per 1000 total carbons ( $\\mathrm{{CH_{3}}/1000}$ total C) is shown in Table 3. HDPE is identified from samples that have $10~\\mathrm{CH}_{3}/\\$ 1000 total C or less, as the only $\\mathrm{CH}_{3}$ contributions in HDPE are from chain ends, which are negligible. This is also a convenient metric as the limit of detection for the IR detector is $10~\\mathrm{CH_{3}/1000}$ total C. PP was identified for polymers with a methyl content of $\\left(330\\pm33\\right)$ ) $\\mathrm{CH}_{3}/1000$ total C, which is determined from theoretical calculations based on the propylene repeat unit. The $10\\%$ tolerance is to include PP that may have some small degrees of degradation from the turtle digestive tract as well as account for small variations $(<10\\%)$ that were observed in HT-SEC analysis of consumer-grade PP (stamped resin code 5) when compared to reagent grade PP obtained from Sigma Aldrich. Currently, there is no documentary standard that specifies what purity a consumer polymer must have to be stamped with a specific resin code. LDPE is assigned to polymers with an average branching content between HDPE and PP, or (10 to 300) $\\mathrm{CH}_{3}/1000$ total C. For the purposes of this study, no effort was made to distinguish LLDPE from LDPE in ingested plastics, as ATR FT-IR cannot make that distinction. Future studies will address distinguishing LLDPE from LDPE in unknown polymer samples and mixtures with the addition of a differential viscometer to measure long chain branching. \n\nThree of the 17 samples were identified as PS (Fig. 6a) based on several lines of evidence. Their positive differential RI signal and minimal alkyl content lead to small IR peak areas and large standard deviations in $\\mathrm{CH}_{3}/1000$ total C determinations. Also, there was agreement between polymer number average $(\\mathbf{M}_{\\mathrm{n}})$ and mass average $(\\mathbf{M}_{\\mathrm{w}})$ molar masses determined by MALS (considered an absolute measurement technique) and those determined by relative comparison to polystyrene standards. $\\mathbf{M}_{\\mathbf{n}}$ and $\\mathbf{M}_{\\mathbf{w}}$ values were determined for all samples and are listed as information values in Table 3. \n\nOne sample measured by HT-SEC (assigned as PETE by ATR FT-IR) was completely insoluble in 1,2,4-trichlorobenzene at $160^{\\circ}\\mathrm{C}.$ , and no peaks were not observed in HT-SEC chromatograms using any detector. The second independent assignment of this sample was instead based on survey $\\mathbf{x}$ -ray photoelectron spectroscopy (XPS) to measure the elemental composition in the sample. Elemental composition of this sample was $(80.3~\\pm~0.9)~\\%~\\mathrm{C};$ $(3.6~\\pm~0.3)\\%\\mathrm{~N~}$ , and $(15.0~\\pm~0.9)\\%$ O, plus additional trace elements (silica and calcium and sodium salts), taken as an average of three locations on the sample. A tentative assignment of PU was made on the material, as the carbon, nitrogen, and oxygen content was closest to database values for PU at $78.6\\%$ , $8.4\\%$ , and $14\\%$ , respectively. As XPS only excites photoelectrons within the first $\\approx10~\\mathrm{{nm}}$ of a material, further sampling and measurements of the material will have to be performed. While this piece of brown fabric produced an ATR FT-IR spectrum with six absorption bands matching PETE, it was a poor-quality spectrum. XPS database values for PETE are $68.9\\%$ carbon, $31.1\\%$ oxygen, and do not contain nitrogen, which are generally more different from the readings of this fabric piece than those of PU. Taking all data into account, this piece was assigned PU. \n\nWith the exception of one misidentification, these novel inter-laboratory results support using ATR FT-IR to identify polymers of degraded and ingested plastics. Identifying the polymers comprising ingested plastic using this simple, accurate method can help us understand many aspects of the marine debris problem. The polymer type will dictate the transport and fate of marine debris and its affinity for other chemical pollutants. Furthermore, knowing the predominant polymer can inform better conservation and management practices. For example, LDPE and PP (resin code $\\#4$ and $\\#5$ ) represent large proportions of marine debris and are not commonly recycled in the Hawaiian Islands. Incentive programs for recycling these polymers and innovative post-use applications could be prioritized to help reduce the abundance of LDPE and PP in the marine environment. \n\n# 4. Conclusion \n\nAs the ingestion of plastic debris by threatened marine species such as sea turtles increases, the need to categorize plastic debris by polymer type and identify marine transport mechanisms and fates has become a high research priority. Here, we provide a definitive validation of ATR FT-IR to identify ingested plastic polymer types, including resin codes $\\#1$ through $\\#6$ and many polymers within code $\\#7$ without the use of a costly database. A clear, easy to follow guide of thoroughly tested criteria was presented to confidently differentiate HDPE and LDPE. Our approach has been successfully used by four additional ongoing marine debris studies with macro to microplastics found in water, on beaches, or ingested by other marine organisms. We encourage future studies to prepare ingested plastic samples by cleaning them with water or cutting rugose pieces to get a clean surface prior to ATR FT-IR analysis to produce the most accurate results. PCA can be leveraged to assign polymer types to the small proportion of pieces that present challenging ATR FT-IR spectra. This method has been used to identify the polymer composition ingested by three species of sea turtles in the pelagic Pacific. Results on polymers ingested by sea turtle species, geographical, and other comparisons will be reported in a forthcoming manuscript (Jung, 2017). The data reported in the current method development study represent only selected pieces; therefore, calculating the percentage of each polymer reported here would misrepresent the actual ingested composition. \n\nThe accuracy of using ATR FT-IR for identifying commercial polymers in marine debris, as demonstrated in this study, has the benefit of rapid analysis and minimal destruction to the collected samples, which is ideal for high throughput analysis of large repositories of marine debris. There is, however, much more detailed information about discarded plastics that can be explored by utilizing advanced polymer metrology methods, such as HT-SEC, thermal analysis, or rheological measurements. Systematic changes in chemical composition, molar mass, molar mass distribution and viscoelastic properties in a specific polymeric resin can provide better understanding of material degradation pathways and resulting byproducts. Comprehensive understanding of the origins, transport, fate, and lifetime of marine debris will ultimately require both high-throughput and fundamental studies of discarded materials, providing ample opportunities for collaboration between the life sciences and material science communities to address the challenges in marine plastics moving forward. \n\n# Disclaimer \n\nCertain commercial equipment, instruments, or materials are identified in this paper to specify adequately the experimental procedure. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose. \n\n# Acknowledgements \n\nFunding was provided by grant 60NANB15D026 from the U.S. Pacific Islands Program of the NIST Marine Environmental Specimen Bank. The ATR FT-IR instrument was supported by National Institutes of Health grant P20GM103466. We thank Stacy (Vander Pol) Schuur for providing some of the raw manufactured polymers. We thank Tracy Schock for her advice on principal component analyses. We thank the fishermen and fisheries observers for carefully assessing, storing, and transporting the sea turtle specimens. We thank Shandell Brunson, Irene Nurzia Humburg, Devon Franke, Emily Walker, Sarah Alessi, T. Todd Jones (PIFSC), Bob Rameyer (USGS), Katherine Clukey, Jessica Jacob, Frannie Nilsen, Julia Smith, Adam Kurtz, Angela Hansen, \n\nStephanie Shaw, Jennette VanderJagt, and Jessica Kent (Hawaii Pacific University) and numerous other volunteers for help in sample collection and processing. We thank the entire NIST Marine Environmental Specimen Bank team, especially Rebecca Pugh and Paul Becker, for sample archival. Finally, we thank Chris Stafford, Amanda Forster and Rebecca Pugh for comments on the draft manuscript. Mention of products and trade names does not imply endorsement by the U.S. Government. \n\n# Appendix A. Supplementary data \n\nSupplementary data to this article can be found online at https:// doi.org/10.1016/j.marpolbul.2017.12.061. \n\n# References \n\nAndrady, A.L., 2011. Microplastics in the marine environment. Mar. Pollut. Bull. 62 (8), 1596–1605. \nAndrady, A.L., 2017. The plastic in microplastics: a review. Mar. Pollut. Bull. 119 (1), 12–22. \nAsefnejad, A., Khorasani, M.T., Behnamghader, A., Farsadzadeh, B., Bonakdar, S., 2011. Manufacturing of biodegradable polyurethane scaffolds based on polycaprolactone using a phase separation method: physical properties and in vitro assay. Int. J. Nanomedicine 6, 2375. \nAsensio, R.C., Moya, M.S.A., de la Roja, J.M., Gómez, M., 2009. Analytical characterization of polymers used in conservation and restoration by ATR-FTIR spectroscopy. Anal. Bioanal. Chem. 395 (7), 2081–2096. \nASTM International, 2013. Standard Practice for Coding Plastic Manufactured Articles for Resin Identification. Designation: D7611/D7611M−13ε1. \nBakir, A., Rowland, S.J., Thompson, R.C., 2014. Enhanced desorption of persistent organic pollutants from microplastics under simulated physiological conditions. Environ. Pollut. 185, 16–23. \nBeltran, M., Marcilla, A., 1997. Fourier transform infrared spectroscopy applied to the study of PVC decomposition. Eur. Polym. J. 33 (7), 1135–1142. \nBjorndal, K.A., Bolten, A.B., Lagueux, C.J., 1994. Ingestion of marine debris by juvenile sea turtles in coastal Florida habitats. Mar. Pollut. Bull. 28 (3), 154–158. \nBrandon, J., Goldstein, M., Ohman, M.D., 2016. Long-term aging and degradation of microplastic particles: comparing in situ oceanic and experimental weathering patterns. Mar. Pollut. Bull. 110 (1), 299–308. \nBrandrup, J., Immergut, E.H., Grulke, E.A., 1999. Polymer Handbook, Fourth Edition. John Wiley & Sons, Inc., New York, pp. 2336. \nBugoni, L., Krause, L., Petry, M.V., 2001. Marine debris and human impacts on sea turtles in southern Brazil. Mar. Pollut. Bull. 42 (12), 1330–1334. \nCincinelli, A., Scopetani, C., Chelazzi, D., Lombardini, E., Martellini, T., Katsoyiannis, A., Fossi, M.C., Corsolini, S., 2017. Microplastic in the surface waters of the Ross Sea (Antarctica): occurrence, distribution and characterization by FTIR. Chemosphere 175, 391–400. \nClukey, K.E., Lepczyk, C.A., Balazs, G.H., Work, T.M., Lynch, J.M., 2017. Investigation of plastic debris ingestion by four species of sea turtles collected as bycatch in pelagic Pacific longline fisheries. Mar. Pollut. Bull. 120 (1–2), 117–125. \nCoates, J., 2000. Interpretation of infrared spectra, a practical approach. In: Meyers, R.A. (Ed.), Encyclopedia of Analytical Chemistry. John Wiley & Sons, Ltd., Chichester, pp. 10815–10837. \nCole, M., Galloway, T.S., 2015. Ingestion of nanoplastics and microplastics by Pacific oyster larvae. Environ. Sci. Technol. 49 (24), 14625–14632. \nCole, M., Webb, H., Lindeque, P.K., Fileman, E.S., Halsband, C., Galloway, T.S., 2014. Isolation of microplastics in biota-rich seawater samples and marine organisms. Sci. Rep. 4, 4528. \nDümichen, E., Barthel, A.K., Braun, U., Bannick, C.G., Brand, K., Jekel, M., Senz, R., 2015. Analysis of polyethylene microplastics in environmental samples, using a thermal decomposition method. Water Res. 85, 451–457. \nEndo, S., Takizawa, R., Okuda, K., Takada, H., Chiba, K., Kanehiro, H., Ogi, H., Yamashita, R., Date, T., 2005. Concentration of polychlorinated biphenyls (PCBs) in beached resin pellets: variability among individual particles and regional differences. Mar. Pollut. Bull. 50 (10), 1103–1114. \nFischer, M., Scholz-Böttcher, B.M., 2017. Simultaneous trace identification and quantification of common types of microplastics in environmental samples by pyrolysis-gas chromatography-mass spectrometry. Environ. Sci. Technol. 51 (9), 5052. \nFrère, L., Paul-Pont, I., Moreau, J., Soudant, P., Lambert, C., Huvet, A., Rinnert, E., 2016. A semi-automated Raman micro-spectroscopy method for morphological and chemical characterizations of microplastic litter. Mar. Pollut. Bull. 113 (1), 461–468. \nFries, E., Zarfl, C., 2012. Sorption of polycyclic aromatic hydrocarbons (PAHs) to low and high density polyethylene (PE). Environ. Sci. Pollut. Res. 19 (4), 1296–1304. \nGeyer, R., Jambeck, J.R., Law, K.L., 2017. Production, use, and fate of all plastics ever made. Sci. Adv. 3 (7), e1700782. \nGuidelli, E.J., Ramos, A.P., Zaniquelli, M.E.D., Baffa, O., 2011. Green synthesis of colloidal silver nanoparticles using natural rubber latex extracted from Hevea brasiliensis. Spectrochim. Acta A Mol. Biomol. Spectrosc. 82 (1), 140–145. \nHoarau, L., Ainley, L., Jean, C., Ciccione, S., 2014. Ingestion and defecation of marine debris by loggerhead sea turtles, Caretta caretta, from by-catches in the South-West Indian Ocean. Mar. Pollut. Bull. 84 (1), 90–96. \nHoss, D.E., Settle, L.R., 1990. Ingestion of plastics by teleost fishes. In: Proceedings of the Second International Conference on Marine Debris. NOAA Technical Memorandum. NOAA-TM-NMFS-SWFSC-154. Miami, FL, pp. 693–709. \nHowell, E.A., Bograd, S.J., Morishige, C., Seki, M.P., Polovina, J.J., 2012. On North Pacific circulation and associated marine debris concentration. Mar. Pollut. Bull. 65 (1), 16–22. \nIlharco, L.M., Brito de Barros, R., 2000. Aggregation of pseudoisocyanine iodide in cellulose acetate films: structural characterization by FTIR. Langmuir 16 (24), 9331–9337. \nJambeck, J.R., Geyer, R., Wilcox, C., Siegler, T.R., Perryman, M., Andrady, A., Narayan, R., Law, K.L., 2015. Plastic waste inputs from land into the ocean. Science 347 (6223), 768–771. \nJung, M., 2017. Polymer Identification of Plastic Debris Ingested by Pelagic-phase Sea Turtles in the Central Pacific (Master Thesis). Hawaii Pacific University, Kaneohe, HI. \nKeller, J.M., Pugh, R.S., Becker, P.R., 2014. Biological and environmental monitoring and archive of sea turtle tissues (BEMAST): rationale, protocols, and initial collections of banked sea turtle tissues. In: NIST Internal Report (NISTIR)-7996. \nKoelmans, A.A., Besseling, E., Wegner, A., Foekema, E.M., 2013. Plastic as a carrier of POPs to aquatic organisms: a model analysis. Environ. Sci. Technol. 47 (14), 7812–7820. \nMark, J.E. (Ed.), 2007. Physical Properties of Polymers Handbook. vol. 1076 Springer, New York. \nMcIlgorm, A., Campbell, H.F., Rule, M.J., 2011. The economic cost and control of marine debris damage in the Asia-Pacific region. Ocean Coast. Manag. 54 (9), 643–651. \nMecozzi, M., Pietroletti, M., Monakhova, Y.B., 2016. FTIR spectroscopy supported by statistical techniques for the structural characterization of plastic debris in the marine environment: application to monitoring studies. Mar. Pollut. Bull. 106 (1), 155–161. \nMoore, C.J., Moore, S.L., Leecaster, M.K., Weisberg, S.B., 2001. A comparison of plastic and plankton in the North Pacific central gyre. Mar. Pollut. Bull. 42 (12), 1297–1300. \nNelms, S.E., Duncan, E.M., Broderick, A.C., Galloway, T.S., Godfrey, M.H., Hamann, M., Lindeque, P.K., Godley, B.J., 2015. Plastic and marine turtles: a review and call for research. ICES J. Mar. Sci. 73 (2), 165–181. \nNilsen, F., Hyrenbach, K.D., Fang, J., Jensen, B., 2014. Use of indicator chemicals to characterize the plastic fragments ingested by Laysan albatross. Mar. Pollut. Bull. 87 (1), 230–236. \nNishikida, K., Coates, J., 2003. Infrared and Raman analysis of polymers. In: Lobo, H., Bonilla, J.V. (Eds.), Handbook of Plastics Analysis. Marcel Dekker, Inc, New York, pp. 186–316. \nNoda, I., Dowrey, A.E., Haynes, J.L., Marcott, C., 2007. Group frequency assignments for major infrared bands observed in common synthetic polymers. In: Mark, J.E. (Ed.), Physical Properties of Polymers Handbook. Springer Science $^+$ Business Media, LLC, New York, pp. 395–406. \nPeacock, A., 2000. Handbook of Polyethylene: Structures, Properties, and Applications. Marcel Dekker, Inc., New York, pp. 534. \nProvencher, J.F., Bond, A.L., Avery-Gomm, S., Borrelle, S.B., Rebolledo, E.L.B., Hammer, S., Kühn, S., Lavers, J.L., Mallory, M.L., Trevail, A., van Franeker, J.A., 2017. Quantifying ingested debris in marine megafauna: a review and recommendations for standardization. Anal. Methods 9 (9), 1454–1469. \nRios, L.M., Moore, C., Jones, P.R., 2007. Persistent organic pollutants carried by synthetic polymers in the ocean environment. Mar. Pollut. Bull. 54 (8), 1230–1237. \nRochman, C.M., Hoh, E., Hentschel, B.T., Kaye, S., 2013. Long-term field measurement of sorption of organic contaminants to five types of plastic pellets: implications for plastic marine debris. Environ. Sci. Technol. 47 (3), 1646–1654. \nRotter, G., Ishida, H., 1992. FTIR separation of nylon6 chain conformations: clarification of the mesomorphous and γcrystalline phases. J. Polym. Sci. B Polym. Phys. 30 (5), 489–495. \nRyan, P.G., Moore, C.J., van Franeker, J.A., Moloney, C.L., 2009. Monitoring the abundance of plastic debris in the marine environment. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364 (1526), 1999–2012. \nSingh, B., Sharma, N., 2008. Mechanistic implications of plastic degradation. Polym. Degrad. Stab. 93 (3), 561–584. \nTomás, J., Guitart, R., Mateo, R., Raga, J.A., 2002. Marine debris ingestion in loggerhead sea turtles, Caretta caretta, from the Western Mediterranean. Mar. Pollut. Bull. 44 (3), 211–216. \nUnger, B., Rebolledo, E.L.B., Deaville, R., Gröne, A., IJsseldijk, L.L., Leopold, M.F., Siebert, U., Spitz, J., Wohlsein, P., Herr, H., 2016. Large amounts of marine debris found in sperm whales stranded along the North Sea coast in early 2016. Mar. Pollut. Bull. 112 (1), 134–141. \nVerleye, G.A., Roeges, N.P., De Moor, M.O., 2001. Easy Identification of Plastics and Rubbers. Rapra Technology Limited, Shropshire, pp. 174. " + }, + { + "id": "10.1038_s41557-018-0141-5", + "DOI": "10.1038/s41557-018-0141-5", + "DOI Link": "http://dx.doi.org/10.1038/s41557-018-0141-5", + "Relative Dir Path": "mds/10.1038_s41557-018-0141-5", + "Article Title": "Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water", + "Authors": "Wang, XY; Chen, LJ; Chong, SY; Little, MA; Wu, YZ; Zhu, WH; Clowes, R; Yan, Y; Zwijnenburg, MA; Sprick, RS; Cooper, AI", + "Source Title": "NATURE CHEMISTRY", + "Abstract": "Nature uses organic molecules for light harvesting and photosynthesis, but most man-made water splitting catalysts are inorganic semiconductors. Organic photocatalysts, while attractive because of their synthetic tunability, tend to have low quantum efficiencies for water splitting. Here we present a crystalline covalent organic framework (COF) based on a benzobis(benzothiophene sulfone) moiety that shows a much higher activity for photochemical hydrogen evolution than its amorphous or semicrystalline counterparts. The COF is stable under long-term visible irradiation and shows steady photochemical hydrogen evolution with a sacrificial electron donor for at least 50 hours. We attribute the high quantum efficiency of fusedsulfone-COF to its crystallinity, its strong visible light absorption, and its wettable, hydrophilic 3.2 nm mesopores. These pores allow the framework to be dye-sensitized, leading to a further 61% enhancement in the hydrogen evolution rate up to 16.3 mmol g(-1) h(-1). The COF also retained its photocatalytic activity when cast as a thin film onto a support.", + "Times Cited, WoS Core": 985, + "Times Cited, All Databases": 1022, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000450790300005", + "Markdown": "# Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water \n\nXiaoyan Wang   1, Linjiang Chen1,2, Samantha Y. Chong $\\mathbb{O}^{1}$ , Marc A. Little1, Yongzhen $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{3}.$ , Wei-Hong Zhu3, Rob Clowes1, Yong Yan1, Martijn A. Zwijnenburg $\\textcircled{10}4$ , Reiner Sebastian Sprick   1 and Andrew I. Cooper1,2\\* \n\nNature uses organic molecules for light harvesting and photosynthesis, but most man-made water splitting catalysts are inorganic semiconductors. Organic photocatalysts, while attractive because of their synthetic tunability, tend to have low quantum efficiencies for water splitting. Here we present a crystalline covalent organic framework (COF) based on a benzobis(benzothiophene sulfone) moiety that shows a much higher activity for photochemical hydrogen evolution than its amorphous or semicrystalline counterparts. The COF is stable under long-term visible irradiation and shows steady photochemical hydrogen evolution with a sacrificial electron donor for at least 50 hours. We attribute the high quantum efficiency of fusedsulfone-COF to its crystallinity, its strong visible light absorption, and its wettable, hydrophilic 3.2 nm mesopores. These pores allow the framework to be dye-sensitized, leading to a further $61\\%$ enhancement in the hydrogen evolution rate up to $16.3\\mathsf{m m o l g}^{-1}\\mathsf{h}^{-1}$ . The COF also retained its photocatalytic activity when cast as a thin film onto a support. \n\nhotocatalytic solar hydrogen production—or water splitting—offers an abundant clean energy source for the future. The use of dispersed, powdered photocatalysts or thin catalyst films is attractively simple, but, so far, no catalyst satisfies the combined requirements of cost, stability and solar-to-hydrogen efficiency. Since the first report of $\\mathrm{TiO}_{2}$ as a photocatalyst1, many inorganic semiconductors have been explored for water splitting, both in photoelectrochemical cells and as photocatalyst suspensions2–4. Recently, organic semiconductors have emerged as promising materials for photocatalytic hydrogen and oxygen evolution5–7. Poly $\\mathit{\\Pi}_{p}$ -phenylene) was first reported as a photocatalyst for hydrogen evolution in $1985^{8,9}$ , but its activity was poor and limited to the ultraviolet spectrum. Since then, more active organic materials have been reported as visible-light photocatalysts for hydrogen production using sacrificial donors. This started with carbon nitrides5,10, followed by poly(azomethine)s11, conjugated microporous polymers $(\\mathbf{CMPs})^{6,12,13}$ , linear conjugated polymers12,14–16 and covalent triazine-based frameworks $(\\bar{\\mathrm{CTF}}s)^{17-\\bar{19}}$ . Carbon nitrides were further developed into hybrid systems that facilitate overall water splitting to produce both hydrogen and oxygen, for example by including metal co-catalysts20. CMPs were also claimed to exhibit overall photocatalytic water splitting21. However, while it is possible to tune semiconductor properties such as the bandgap by modular copolymerization strategies6, organic materials such as carbon nitrides, conjugated polymers and CTFs lack long-range order (they are amorphous or semicrystalline17,22). This lack of order might limit the transport of photoactive charges to the catalyst surface23. More generally, it is challenging to construct atomistic structure–property relationships for materials where the 3D architecture is poorly defined. \n\nCovalent organic frameworks $(\\mathrm{COFs})^{24-26}$ are a class of organic materials that combine crystallinity, modular synthetic versatility, highly accessible surface areas and, sometimes, good physicochemical stability27–30. With suitable building blocks and layered stacking sequences, COFs have been shown to have high chargecarrier mobilities31. So far, only a small number of COFs have been studied for their photocatalytic hydrogen evolution activity32,33. A hydrazone-based COF was reported by Lotsch and co-workers in 2014 to be active for sacrificial hydrogen production34, and this team subsequently reported a series of 2D azine COFs with impressive photocatalytic hydrogen evolution rates (HERs) of up to $1.7\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ $(\\mathbf{N}_{3}{\\bf-C O F}$ Fig. 1a) using triethanolamine (TEOA) as a sacrificial donor and a Pt co-catalyst35,36. Recently, Thomas and co-workers described a diacetylene-functionalized COF with good hydrogen evolution activity37. Kurongot and Banerjee reported a cadmium sulfide–COF composite material with a higher HER of $3.68\\mathrm{mmolg^{-1}h^{-1}}$ using lactic acid as the sacrificial agent32, although the COF was the minor component in that composite $(90\\mathrm{wt\\%}$ CdS). Porous COFs can also be modified after synthesis: for example, a molecular cobaloxime co-catalyst was introduced into an azine COF to give a HER of $0.78\\mathrm{mmolg^{-1}h^{-1}}$ (ref. 38). HERs for a given catalyst can vary substantially in different laboratories depending on the optical set-up; with that caveat in mind, ${\\bf N}_{3}$ -COF is the most active, unmodified COF for sacrificial hydrogen evolution reported so far35. COF films have also been used as carbon dioxide reduction catalysts39 and, in film form, as photoelectrodes for light-driven water splitting40. \n\nWe have shown previously that a linear conjugated copolymer, P7 (Fig. 1b), exhibits HERs of up to $1.49\\mathrm{mmolg^{-1}h^{-1}}$ with a sacrificial amine donor under visible irradiation $(\\lambda>420\\mathrm{nm})^{16}$ ; that is, close to the value reported for $\\mathbf{N}_{3}–\\mathbf{COF}^{35}$ . We ascribed this to the rigid, planar dibenzo $\\cdot b,d]$ thiophene sulfone (DBTS) unit in the P7 copolymer. Homopolymerization of this DBTS monomer gives a polymer, P10 (Fig. 1b), with an even higher HER $(3.26\\mathrm{mmolg^{-1}h^{-1}}$ \n\n![](images/2f60216c6dcd378076d334d85bb189b111c9a7c380aee5aabf4863a5f390e226.jpg) \nFig. 1 | Chemical structures of the organic photocatalysts studied here. a,b, Chemical structures of previously reported photocatalysts ${\\sf N}_{3}{\\sf-C O F}^{35}$ (a), $\\pmb{\\mathsf{P}}\\pmb{7}^{16}$ and P10 (b). c, Chemical structures of the COF photocatalysts reported in this work: S-COF, FS-COF and TP-COF. \n\nSupplementary Fig. 95). Unlike COFs, these polymers are semicrystalline: they are also non-porous and insoluble, which precludes post-synthetic modification strategies. Here, we set out to incorporate the DBTS unit into ordered COFs to investigate the influence of crystallinity and porosity on the photocatalytic activity. This led to a new crystalline organic material, FS-COF (where FS is fused sulfone), which is a better photocatalyst than equivalent amorphous or semicrystalline conjugated polymers. FS-COF also exhibits higher HERs than other COFs studied so far—up to $16.3\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ when dye-sensitized, which is almost ten times higher than $\\mathbf{N}_{3}$ -COF. \n\n# Results and discussion \n\nCOF synthesis and characterization. Three COFs—S-COF, FS-COF and TP-COF (Fig. 1c)—were synthesized via a Schiff-base condensation reaction of 1,3,5-triformylphloroglucinol with aromatic diamines (Supplementary Figs. 1–3). The products undergo an irreversible keto-enol tautomerization, which enhances their chemical stability29. We used 3,7-diaminodibenzo $[b,d]$ thiophene sulfone (SA​) as the monomer for S-COF, which is a crystalline COF analogue of semicrystalline polymers P7 and P10 (Fig. 1b). We also used 3,9-diamino-benzo[1,2-b:4,5- $\\mathbf{\\nabla}\\cdot\\mathbf{\\vec{b}^{\\prime}}$ ​]bis[1]benzothiophene sulfone (FSA​) to produce FS-COF, which has fused, extended planar linkers. TP-COF was synthesized as before41; it was prepared from $^{4,4^{\\prime\\prime}}$ ​-diamino- $\\cdot p$ -terphenyl (TPA) and it is, in essence, FS-COF minus the sulfone moieities (Fig. 1c). \n\nAll three linkers gave rise to crystalline COFs (Fig. 2 and Supplementary Figs. 24–28). Based on powder X-ray diffraction (PXRD) data, FS-COF (Fig. 2c) appeared to have more long-range orderthaneitherS-COF(Fig.2d)orTP-COF(SupplementaryFig.28). This might be because the $\\mathrm{C-N}$ bonds in the FSA monomer are parallel, whereas the angle between the C–N bonds in the SA​monomer is ${\\sim}163^{\\circ}$ (Supplementary Fig. 14), and hence the regular hexagonal framework in FS-COF may be less sensitive than S-COF to the insertion of linkers in the ‘wrong’ geometry. More effective $\\pi{-}\\pi$ stacking between the fused, planar FSA linkers might also help to stabilize FS-COF. \n\nPXRD was used to characterize the three COFs. FS-COF exhibited diffraction peaks at 2.71, 4.73, 5.52 and $7.35^{\\circ}$ , which were assigned to the (100), (110), (200) and (210) planes, respectively (Fig. 2c). The broad intensity at $25.19^{\\circ}$ was assigned to the (001) \n\n![](images/09ed04af067cf831ecb17b9f9ea669b047aa1652bad67607f91db9c8776fb8c7.jpg) \nFig. 2 | Crystal structures of FS-COF and S-COF. a,b, Structural models for FS-COF (a) and S-COF (b) with perfectly eclipsed AA stacking patterns, shown parallel to the pore channel along the crystallographic c axis (top) and parallel to the hexagonal layers (bottom). The pores of both COFs are lined with oxygen atoms. Grey, white, blue, red and yellow atoms represent carbon, hydrogen, nitrogen, oxygen and sulfur, respectively. c,d, Experimental diffraction patterns (red), profiles calculated from Le Bail fitting (black) and residual (blue), and pattern simulated from the structural model (green) for FS-COF (c) and S-COF (d). Reflection positions are shown by tick marks. \n\nplane, corresponding to a layer spacing of $3.53\\mathring\\mathrm{A}$ . Multiple reflections indicate that FS-COF has high periodicity in three dimensions. Le Bail refinements confirmed that the diffraction pattern was consistent with a primitive hexagonal lattice with unit cell parameters $(a=b=36.\\Bar{205(6)}\\mathring\\mathrm{A}$ , $c=7.285(5)\\mathring{\\mathrm{A}}$ ) similar to an idealized eclipsed model of FS-COF (Fig. 2a, top). S-COF exhibited lower crystallinity, indicated by the broadened diffraction profile. The observable diffraction intensities can be accounted for by a primitive hexagonal structure with an in-plane lattice parameter of $27.44(2)\\mathring\\mathrm{A}$ and a $\\pi$ -stacking distance of ${\\sim}3.7\\mathrm{\\AA}$ . Based on both laboratory and synchrotron XRD data (Supplementary Figs. 24–27), we propose that FS-COF and S-COF have AA layer stackings (Fig. 1c), rather than AB stacking. However, there are a variety of possible AA stacking patterns (Supplementary Fig. 93), and the X-ray data do not allow us to distinguish between these (Supplementary Figs. 25 and 26). For the purposes of structural comparisons with experimental data, we refer to the idealized, perfectly eclipsed AA stacking patterns (Fig. 2a,b) because properties such as porosity are not greatly affected by small shifts in the relative orientation of the layers. By contrast, calculations that are discussed later suggest that the electronic structure of FS-COF is quite strongly affected by small changes to the AA layer stacking. \n\nThe porosity of these COFs was assessed by nitrogen sorption measurements at $77.3\\mathrm{K}$ . The Brunauer–Emmett–Teller (BET) surface areas of FS-COF, S-COF and TP-COF were found to be 1,288, 985 and $919\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , respectively. The measured surface area for FS-COF equates to $78\\%$ of the calculated nitrogen-accessible surface area for the idealized, eclipsed structure shown in Fig. 2a $(1,652\\mathrm{m}^{2}\\mathrm{g}^{-1})$ . The experimental surface areas for the two less crystalline COFs were lower than the idealized, calculated values (1,690 and $2,172\\mathrm{m}^{2}\\mathrm{g}^{-1}$ for S-COF and TP-COF), although both materials were still microporous. The pore diameters derived for FS-COF, S-COF and TP-COF by fitting nonlocal density functional theory (DFT) models to the $\\mathrm{N}_{2}$ isotherms were 27.6, 22.8 and $29.0\\mathring\\mathrm{A}$ , respectively. All COFs gave rise to nitrogen isotherms with shapes consistent with mesoporosity and sequential, multilayer pore filling (Fig. 3a and Supplementary Figs. 18–20). \n\nHigh-resolution transmission electron microscopy (HR-TEM) images of FS-COF (Fig. 3b) confirmed that it has an ordered, hexagonal pore structure oriented along the crystallographic $\\boldsymbol{\\mathscr{c}}$ axis with a periodicity of $\\sim3.0\\mathrm{nm}$ (area outlined in red, Fig. 3b), which is consistent with the in-plane pore channels of $3.2\\mathrm{nm}$ in the proposed AA-stacked COF structure. S-COF and TP-COF exhibited no such clear, ordered domains when analysed by HR-TEM (Supplementary \n\n![](images/261d80754f1350dc38d09bbda621cea070ea8b441c5a77fb42e98721a4b2e67a.jpg) \nFig. 3 | Evidence for ordered, wettable mesopores in FS-COF. a, Nitrogen adsorption isotherm (filled symbols) and desorption isotherm (open symbols) for FS-COF recorded at $77.31.$ . Inset: profile of the calculated pore size distribution for FS-COF. b, HR-TEM image of FS-COF. The hexagonal pore structure with a periodicity of $\\sim3.0\\mathsf{n m}$ is indicated by the dashed red outline. Scale bars, $50\\mathsf{n m}$ (inset) and $100\\mathsf{n m}$ (main). c, Water adsorption isotherms (filled symbols) and desorption isotherms (open symbols) for FS-COF, S-COF and TP-COF, measured at 293 K. $P{P_{0}}^{-1}$ , vapor pressure over saturation pressure. \n\nFig. 31). Atomic force microscopy (AFM) images of FS-COF deposited onto silicon wafers from water suspensions also show that this COF can be partially exfoliated into thin stacks, albeit not single layers, with thicknesses ranging from 5 to $25\\mathrm{nm}$ (Supplementary Fig. 33). \n\nUV–vis reflectance spectra of the COFs were measured in the solid state, and the absorption onset was found to be 670, 590 and $540\\mathrm{nm}$ for FS-COF, S-COF and TP-COF, respectively (Fig. 4a). The onsets for FS-COF, S-COF and TP-COF are redshifted by 70, 45 and $90\\mathrm{nm}$ , respectively, compared to their diamine monomers. The UV–vis spectra of an amorphous analogue FS-P, discussed below, show a blueshift compared with FS-COF, but it also exhibits a redshifted absorption compared to the diamine monomer. FS-COF absorbs more light in the visible spectrum and shows a significant redshift in its absorption onset compared to the corresponding linear dibenzo $[b,d]$ thiophene sulfone-based polymers, P7 and P10, by 210 and $184\\mathrm{nm}$ . \n\nPhotocatalysis experiments. We next investigated the activity of these COFs for photocatalytic water reduction using ascorbic acid as a sacrificial electron donor (SED) and $\\mathrm{Pt}$ as a co-catalyst. All materials evolved hydrogen under visible light $(\\lambda>420\\mathrm{nm}$ , Fig. 4b) and the average HERs were determined to be $1.6\\mathrm{mmolg^{-1}h^{-1}}$ for TP-COF, $4.4\\bar{4}\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ for S-COF and $\\mathbf{l0.1mmolg^{-1}h^{-1}}$ for FS-COF. As in previous reports for porous titania glasses42, strontium titanate43 and carbon nitride5, we observed the production of smaller, although still significant, quantities of hydrogen without the addition of $\\mathrm{Pt}$ for S-COF and FS-COF with rates of 0.6 and $1.32{\\mathrm{mmol}}{\\mathrm{g}}^{-1}{\\mathrm{h}}^{-1}$ , respectively. No hydrogen production was observed for TP-COF without Pt. The mass-normalized HER for FS-COF of $10.1\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ is the highest reported for a photocatalytically active COF (Table 1). This rate is 22 times higher than for ${\\bf N}_{3}$ -COF $(0.47\\mathrm{mmolg^{-1}h^{-1}})$ , as measured by us under identical conditions over $^{5\\mathrm{h}}$ (with ascorbic acid), and around six times higher than the optimized rate reported for ${\\bf N}_{3}$ -COF by Vyas and colleagues using triethanolamine as a sacrificial donor35. \n\nAn external quantum efficiency (EQE) of $3.2\\%$ was determined for FS-COF at $420\\mathrm{nm}$ (violet light), whereas $1.3\\%$ was reported for the diacetylene $\\mathrm{COF}^{37}$ at $420\\mathrm{nm}$ and $0.44\\%$ for $\\mathbf{N}_{3}–\\mathbf{COF}$ at $450\\mathrm{nm}$ , both using TEOA as a $\\operatorname{SED}^{35}$ . At even longer wavelengths 1 $\\left[600\\mathrm{nm}\\right.$ , orange light), FS-COF still displayed an EQE of $0.6\\%$ (Supplementary Fig. 40). \n\nLonger-term photolysis experiments for FS-COF with up to 50 hours of visible light irradiation $\\dot{\\lambda}>420\\mathrm{nm}$ , Fig. 4c) showed no significant decrease in the catalytic performance over time, suggesting good stability. No changes to the PXRD patterns were observed after long-term irradiation, showing that the crystallinity was retained (Supplementary Fig. 49). For comparison, we estimate that the 50 hour photolysis reported for $\\mathbf{N}_{3}–\\mathbf{COF}^{35}$ , also using ascorbic acid as a sacrificial donor, yielded an average HER of ${\\sim}0.08\\mathrm{mmolg^{-1}h^{-1}}$ (Supplementary Fig. 63 in ref. 35), about 125 times lower than we observe for FS-COF. \n\nThe marked difference in catalytic activity between FS-COF and the isostructural framework TP-COF can be explained, at least in part, by the redshift in the absorption onset, which allows FS-COF to absorb more visible photons. The partial exfoliation of FS-COF may also contribute10,44. The higher BET surface area of $1,288\\mathrm{m}^{2}\\mathrm{g}^{-1}$ for FS-COF versus $919\\mathrm{m}^{2}\\mathrm{g}^{-1}$ for TP-COF might also enhance the availabliity of photogenerated charges for water reduction. For context, diffusion lengths of up to ${\\sim}10\\mathrm{nm}$ have been reported for thin films of conjugated polymers45–47; hence, photogenerated charges produced inside non-porous particles much larger than $10\\mathrm{nm}$ may not reach the particle surface. \n\nIntroducing sulfone groups results in much lower contact angles with pure water for FS-COF $(23.6^{\\circ})$ and S-COF $(43.7^{\\circ})$ in comparison with TP-COF $(59.7^{\\circ})$ and ${\\bf N}_{3}$ -COF $(53.4^{\\circ})$ . These contact angles are low for organic materials: for reference, most organic polymers have contact angles in the range $60{-}110^{\\circ};$ and poly(vinyl alcohol) has a contact angle of ${\\sim}51^{\\circ}$ (ref. 48). Water vapour uptake measurements (Fig. 3c) show type II isotherms for FS-COF, S-COF and TP-COF. Functionalized FS-COF and S-COF adsorb 67 and $42\\mathrm{wt\\%}$ water at $293\\mathrm{K}$ and 22.9 mbar; by comparison, TP-COF adsorbs only $16\\mathrm{wt\\%}$ water under the same conditions. This is due to water condensation49 within the mesopores of FS-COF, which are decorated with a large number of polarized heteroatoms (Fig. 2a). Wetting matters in aqueous photocatalysis because particle dispersibility and favourable interactions with water and the sacrificial donor are required for good photocatalytic performance. The water isotherm for FS-COF shows that the internal pore structure of the material is accessible to water, as well as the external surface, thus increasing the number of potential sites for photocatalytic water reduction. \n\nBesides light absorption, particle size and wettability, crystallinity might be important in the catalytic performance of FS-COF. In particular, the eclipsed AA layered structure of FS-COF (Fig. 2a) might facilitate charge carrier transport in the material, although it is not possible at this stage to deconvolute this from other factors, such as surface area. Increased long-range order in carbon nitride has been reported to improve photocatalytic activity by enhancing charge transport to active sites22. In this study, both S-COF and FS-COF strongly outperformed the corresponding semicrystalline conjugated co-polymers $\\mathbf{P}7^{16}$ and P10 that were the inspiration for these frameworks (Fig. 1 and Table 1). Under comparable conditions, FS-COF is around twelve times more active than P7, and seven times more active than P10 (Table 1). \n\n![](images/21bd62e65fa50d96df3782505d8be4354ce3b4c7594e36f6ccdb11a7df6893e6.jpg) \nFig. 4 | Optical properties, HERs and excited-state lifetimes for the photocatalysts. a, UV–vis absorption spectra for FS-COF, S-COF, TP-COF and FS-P measured in the solid state. b, Time course for photocatalytic ${\\sf H}_{2}$ production using visible light for FS-COF, S-COF, TP-COF and FS-P (5 mg catalyst in water, $5\\upmu\\upnu(8\\upnu\\upnu^{\\circ}/\\circ\\mathsf{H}_{2}\\mathsf{P}^{\\dagger}\\mathsf{C}\\mathsf{l}_{6})$ , 0.1 M ascorbic acid, $\\lambda>420\\mathsf{n m};$ . c, ${\\sf H}_{2}$ production using visible light for FS-COF over $50\\mathsf{h}$ total photolysis (5 mg catalyst in water, $5\\upmu\\upnu(\\%\\ H_{2}\\mathsf{P t C l}_{6})$ , 0.1 M ascorbic acid, $\\lambda>420\\mathsf{n m}.$ ). The sample was degassed after 5 and $10\\mathsf{h}$ to prevent saturation of the detector, then left under continuous illumination for $20\\mathsf{h}$ and again degassed after 40 and $45\\mathsf{h}$ . After $35\\mathsf{h}$ , 1.25 mmol of ascorbic acid was added. d, Time-correlated singlephoton counting experiments for TP-COF, FS-COF and FS-P in water. Samples were excited with a $\\lambda_{\\mathrm{exc}}=370.5\\mathsf{n m}$ laser and emission was measured at $\\lambda_{\\mathrm{em}}=550\\mathsf{n m}$ . \n\nTo further investigate the effect of crystallinity on photocatalytic performance, we synthesized FS-P, an almost amorphous analogue of FS-COF (Supplementary Fig. 29). We did this by carrying out the synthesis using 1,2-dichlorobenzene as the solvent, rather than a mixture of 1,4-dioxane and mesitylene (Supplementary Section 2). Amorphous FS-P showed much lower photocatalytic activity $\\lambda>420\\mathrm{nm}$ ) and a HER of only $1.12\\mathrm{mmolg^{-1}h^{-1}}$ —nine times lower than FS-COF. FS-P showed a slightly blueshifted absorption onset (Fig. 4a) relative to FS-COF, possibly because the delocalization that arises from $\\pi{-}\\pi$ stacking in FS-COF is disrupted in this amorphous analogue, although its visible light absorption profile is still more favourable than those of S-COF or TP-COF. The low activity of FS-P may also be related to its reduced surface area $(209\\mathrm{m}^{2}\\mathrm{g}^{-1})$ and a lower degree of condensation in the amorphous polymer. Weak absorption bands were observed in the Fourier transform infrared spectrum at 3,371 and $3{,}473\\mathrm{cm}^{-1}$ , which are probably due to amine end groups29. Another important factor could be the particle size of the in situ deposited Pt co-catalyst: FS-COF has well-defined $3\\mathrm{-nm}$ - sized $\\mathrm{Pt}$ nanoparticles on its surface (Supplementary Fig. 32), and it is possible that the size is controlled by the uniform mesopores in the COF. By contrast, undefined micrometre-sized Pt aggregates were formed on the surface of amorphous FS-P. \n\nWe used time-correlated single-photon counting (TCSPC) to estimate the excited-state lifetimes for these materials in aqueous suspensions (Fig. 4d). The average weighted lifetime of FS-COF $(\\tau_{\\mathrm{avg}}=5.56\\mathrm{ns})$ ) was estimated to be significantly longer than that of TP-COF $\\mathit{\\Omega}^{\\prime}\\tau_{\\mathrm{avg}}{=}0.25\\mathrm{ns})$ or FS-P ( $\\tau_{\\mathrm{avg}}=2.21\\mathrm{\\Deltat}$ s), which correlates with the higher photocatalytic performance observed for FS-COF. \n\nComputational studies. For a COF to act as a hydrogen evolution photocatalyst, it must absorb light efficiently over a broad range in the visible spectrum as well transporting the electron–hole pairs, or excitons, that are formed following light absorption. The COF must also thermodynamically drive the reduction of protons and the oxidation of water—or in this study, the SED, ascorbic acid. To achieve this, the electron affinity (EA) of the COF or its exciton ionization potential $(\\mathrm{IP^{*}})$ and the ionization potential (IP) of the COF or its exciton electron affinity $(\\mathrm{EA^{*}})$ should straddle the proton reduction and water/SED oxidation potentials50. Because the potentials of a polymer are difficult to measure experimentally51, we instead predicted them computationally using DFT. We did this using two different approaches: cluster calculations on representative fragments of the COFs embedded in a dielectric continuum to model the COF–water interface, and periodic calculations on COF crystal structures. These two approaches complement each other. By necessity, the periodic calculations approximate the IP and EA by the Kohn–Sham valence band maximum (VBM) and conduction band minimum (CBM). Hence, these calculations cannot describe the effect of immersing the COF in water, but they do take into account the influence of layer stacking. Cluster calculations are limited to a fragment, but unlike the periodic calculations, they describe the effect of water and allow us to calculate the exciton potentials and the exciton binding energy (EBE). The latter is important for polymers, where the EBE is generally large relative to $k T$ ( $26\\mathrm{meV}$ at room temperature), such that spontaneous dissociation of excitons into free electrons and holes is unlikely. \n\n
Table 1| Photophysical properties and HERs for the COF photocatalysts
PhotocatalystDegree of crystallinityOptical gapb (eV)HER (mmol g-1 h-1)HER relative to FS-COF (%)
TP-COFaCrystalline2.281.60 ±(0.08)16
S-COFaCrystalline2.104.44 ± (0.14)43
FS-COFaCrystalline1.8510.1± (0.3)-
FS-paAmorphous1.881.12 ±(0.16)11
N3-COF35Crystalline2.600.47±(0.06)4.6
P716Semicrystalline2.700.84±(0.06)d8.3
P10Semicrystalline2.551.48 ±(0.1)d15
FS-COF+WS5FaCrystalline16.3 ±(0.29)161
FS-COF+Eosin YaCrystalline16.1±(0.34)159
FS-P+WS5FaAmorphous0.23 ±(0.03)2.3
FS-P+Eosin YaAmorphouse0.58 ±(0.08)5.8
\n\naThis work. bCalculated from the onset of the solid absorption spectrum. cAll rates measured using the same instruments, optical set-up and reaction conditions: 5 mg COF catalyst, 5 µ​l (8 wt% $\\mathsf{H}_{2}\\mathsf{P t C l}_{6})$ , $25\\mathsf{m}\\mathsf{I}$ ascorbic acid aqueous solution (0.1 M), $300\\mathsf{W}\\mathsf{X e}$ light source equipped with $\\lambda>420\\mathsf{n m}$ cutoff filter. HERs based on average over 5 h irradiation and normalized to the COF mass. dAs for c, but with no additional Pt catalyst added (Supplementary Fig. 35); HER for P10 in the presence of Pt was $1.92\\mathsf{m m o l g}^{-1}\\mathsf{h}^{-1}$ . eThe effective optical gap was not measurable due to the intense absorption of the organic dye. \n\nThe cluster DFT (B3LYP) calculations on fragments embedded in a continuum with the relative dielectric permittivity of water predict that S-COF, FS-COF and TP-COF should all have substantial thermodynamic driving forces for proton reduction (Fig. 5a,b). Water oxidation is predicted to be endergonic or negligibly exergonic, providing a thermodynamic explanation for the inability of these materials to drive hydrogen evolution without a sacrificial agent. Ascorbic acid was used as a SED because its one-hole and two-hole oxidation potentials are more negative than the water oxidation potential, meaning it is more easily oxidized (Fig. 5a). \n\nCluster calculations for $\\mathbf{N}_{3}–\\mathbf{COF}$ (Fig. $^{5\\mathrm{a},\\mathrm{b}}$ ) suggest a different picture. While the IP and EA of $\\mathrm{N}_{3}(\\mathrm{L})$ straddle both water splitting half-reaction potentials, suggesting a driving force for overall water splitting, the $\\mathrm{EA^{*}}$ and $\\mathrm{IP^{*}}$ do not; this means that overall water splitting is still not thermodynamically favoured without bulk exciton dissociation—and the EBE is predicted to be as large as $0.92\\mathrm{eV.}$ Calculations using range-separated density functionals also suggest that the EBE in $\\mathbf{N}_{3}–\\mathbf{COF}$ is large (Supplementary Fig. 91). The $\\mathrm{IP^{*}}$ of $\\mathrm{N}_{3}(\\mathrm{L})$ is only marginally more negative than the potential of proton reduction, and the $\\mathrm{EA}^{*}$ is marginally more positive than the potential of the one-hole oxidation of ascorbic acid. The relatively low photocatalytic activity of $\\mathbf{N}_{3}$ -COF with ascorbic acid might therefore be linked to the combined effects of difficult exciton dissociation in the bulk material and the small driving forces associated with exciton dissociation at the photocatalyst–solution interface. \n\nNext, periodic DFT (HSE06) calculations were performed to investigate the electronic structures of the COF crystals. The position of the VBM and CBM for each COF crystal structure was referenced to a common vacuum level (Fig. 5c), determined by the value of the electrostatic potential at the centre of an internal pore. Both eclipsed (AA) and staggered (AB) stacking sequences were considered for S-COF, FS-COF and TP-COF (Fig. 5d); the eclipsed AA layered structure of ${\\bf N}_{3}$ -COF was also included for comparison. Our periodic results corroborate the molecular fragment picture; all of these COF materials are predicted, in certain AA packings, to be thermodynamically able to reduce protons and oxidize ascorbic acid, in line with experiments. The exact positions of the VBM and CBM for FS-COF were found to be sensitive to the small changes to the crystal structure, and this is most likely true for the other COFs as well. The CBM of the idealized, eclipsed AA-stacked FS-COF structure lies, in fact, below the proton reduction potential: hence, in the absence of water at least, this structure is not predicted to drive proton reduction. However, calculations show that minor levels of disorder, such as small offsets between neighbouring layers or partial/full flipping of the FS linkers in alternating layers, can alter the band-edge positions (black horizontal lines in Fig. 5c; Supplementary Fig. 93). All of these possible AA-stacked structure models are close in computed total lattice energy (Supplementary Table 7) and we cannot distinguish between them using either laboratory or synchrotron PXRD data (Supplementary Fig. 26). These calculations, coupled with the photocatalytic proton reduction observed for FS-COF, suggest that the crystal packing might not be exclusively the idealized AA stacking, although we note that the effect of water, as discussed above, cannot be included in these periodic calculations. \n\nAs observed experimentally, calculations predict correctly that FS-COF has the smallest optical gap among the four COF materials studied here and thus, probably, the largest rates of visible photon absorption and exciton generation. This is combined with favourably positioned $\\mathrm{IP/EA^{*}/\\mathrm{VBM}}$ and $\\mathrm{EA/IP^{*}/C B M}$ levels, at least for certain AA packings, to sustain a driving force for both redox half-reactions. Other factors may also contribute to the photocatalytic performance of FS-COF, such as, as discussed above, its strong affinity for water (Fig. 3c), good wettability (Supplementary Fig. 34), well-dispersed Pt co-catalyst particles (Supplementary Fig. 32), and the longer excited-state lifetime in this material (Fig. 4d). \n\nDye sensitization. The ordered mesoporosity in these frameworks offers various opportunities for post-synthetic modification. For example, we explored the dye sensitization of FS-COF with the goal of further enhancing its photocatalytic performance52. Addition of $^{2^{\\prime},7^{\\prime}}$ ​-dichlorofluorescein (Supplementary Fig. 75) reduced the photocatalytic performance of FS-COF, while Rose Bengal (sodium salt of 4,5,6,7-tetrachloro- $^{2^{\\prime},4^{\\prime},5^{\\prime},7^{\\prime}}$ ​-tetraiodofluorescein) slightly improved the performance. However, when Eosin Y $(2^{\\prime},4^{\\prime},5^{\\prime})$ $7^{\\prime}$ ​-tetrabromofluorescein) was added, the HERs for FS-COF were enhanced by up to $60\\%$ ; from 10.1 to $13\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ ( $\\mathrm{10mg}$ dye, $5\\mathrm{mg}$ of FS-COF) and to $16.1\\mathrm{mmolg^{-1}h^{-1}}$ when $20\\mathrm{mg}$ of the dye was added. Further increases in the dye loading reduced the catalytic rate (Supplementary Fig. 76). By contrast, the HER of $5\\mathrm{mg}$ of amorphous FS-P was reduced from 1.1 to $0.58\\mathrm{mmolg^{-1}h^{-1}}$ in the presence of $20\\mathrm{mg}$ of Eosin Y. The absorption spectrum of Eosin Y overlaps with the absorption spectrum of FS-COF, so the addition of dye probably enhances the total absorption cross-section of the system. Similarly, when a larger amount of FS-COF was used with no dye, then a similar increase in the HER was observed $(12.9\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ for $10\\mathrm{mg}$ FS-COF versus $10.1\\mathrm{mmolg^{-1}h^{-1}}$ for $5\\operatorname*{mg}\\mathbf{FS-COF})$ . \n\n![](images/2f67e7f0fa2662af93279fefbd176149f7696110202e4833cbbd262dac87bac4.jpg) \nFig. 5 | Electronic structure calculations provide insights into the photocatalytic water splitting activities of the COFs. a,b, (TD-)B3LYP predicted IP, EA, $\\mathsf{I P^{\\star}}$ and $\\mathsf{E A}^{\\star}$ adiabatic potentials (a) of representative fragments of the different COFs (b) in water; S(L), FS(L), TP(L) and ${\\sf N}_{3}(\\lfloor)$ are representative fragments of S-COF, FS-COF, TP-COF and ${\\sf N}_{3}$ -COF, respectively. c,d, Periodic DFT (HSE06) predicted VBM (red) and CBM (blue) of the COFs with respect to a common vacuum level (c). Both eclipsed (AA) and staggered (AB) stacking arrangements (d) were considered. For FS-COF, multiple AA-stacked structures were generated, with the calculated VBM and CBM for each individual stacking shown as black horizontal lines in $\\bullet,$ for which the assignment is shown in Supplementary Fig. 93. Dashed coloured lines in a and c indicate the potentials for different solution reactions: green, proton reduction; orange, two-hole $(A/{H_{2}}\\mathsf{A})$ and one-hole $(H\\mathsf{A}\\cdot/\\mathsf{H}_{2}\\mathsf{A})$ oxidation of ascorbic acid; magenta, overall water oxidation. All solution potentials shown are for ${\\mathsf{p H}}2.6$ the experimentally measured pH of a $0.1M$ ascorbic acid solution. \n\nEosin Y has a similar absorption spectrum to FS-COF, so it does not harvest additional photons in the energy-rich near-infrared region of the solar spectrum where FS-COF does not absorb. A greater enhancement in the HER was observed when a near-infrared absorbing dye, WS5F​, was used. Unlike the previous dyes, WS5F does not dissolve well in water, so it was pre-loaded into the COF using acetone before the photocatalytic tests (loading conditions: $5\\operatorname*{mg}\\ \\mathbf{FS-COF+5}\\operatorname*{mg}$ WS5F​). When $5\\mathrm{mg}$ of this dye-sensitized material, $\\mathbf{FS-COF+WS5F}$ was used, we observed a visible-light HER of $16.3\\mathrm{mmolg^{-1}h^{-1}}$ , again normalized to the mass of the COF. We ascribe this enhancement to the absorption of more photons at higher wavelengths by the dye-loaded composite, as expressed in the EQE at 600 and $700\\mathrm{nm}$ when using monochromatic light. At $600\\mathrm{nm}$ , FS-COF has an EQE of $0.6\\%$ , which is increased to $2.2\\%$ for the FS $\\mathbf{\\mathbf{-COF+WS5F}}$ composite. At $700\\mathrm{nm}$ , the composite has an EQE of $0.7\\%$ , while FS-COF is completely inactive. \n\nWe attribute the dye sensitization effect to host–guest interactions in the large, hydrophilic 1D mesopore channels (Supplementary Fig. 94), which may help to explain why dye sensitization with Eosin Y and WS5F​ was unsuccessful for the less porous FS-P material. Control experiments using the neat dyes, Eosin Y and WS5F​, in the absence of FS-COF, showed negligible hydrogen production under visible light ${\\bf\\dot{0.1M}}$ ascorbic acid solution plus Pt). Similarly, WS5F supported on mesoporous silica (SBA-15) showed no hydrogen evolution under the same conditions. \n\nThe photoluminescence spectra of $\\mathbf{FS-COF+WS5F}$ were measured to investigate the interaction between FS-COF and WS5F​. As shown in Supplementary Fig. 70, WS5F solution in acetone excited at $410\\mathrm{nm}$ exhibits an intense emission peak at $630\\mathrm{nm}$ , which can be quenched by increasing the concentration of colloidal FS-COF. As there is no obvious overlap between the absorption spectrum of FS-COF and the photoluminescence emission of WS5F​, the fluorescence quenching in WS5F+FS-COF is likely to be the result of interfacial electron transfer from the excited dye to FS-COF. This is supported by calculations that suggest a favourable energy alignment (Fig. 6d): for example, one possible scheme is that the photoexcited dye transfers electrons to FS-COF and is then regenerated by the sacrificial electron donor53. \n\nPhotocatalysis experiments with thin COF films. Sacrificial hydrogen production is a step on the path to overall water splitting, but the latter may require the construction of more sophisticated architectures, such as Z schemes54–56. Z schemes comprise two separate, coupled semiconductor phases, where each phase carries out one of the half-reactions in overall water splitting. To create such architectures, processability is important57. We found that FS-COF can be dispersed as a colloidal solution in various solvents (Fig. 6f), and we used this to dropcast platinized FS-COF onto glass supports. Photocatalytic HERs $\\lambda>420\\mathrm{nm}$ , $0.1\\mathrm{M}$ ascorbic acid, $5\\mathrm{h}$ irradiation) were found to increase with the number of dropcasting cycles (Supplementary Fig. 84), presumably due to increased film thickness, to up to $24.9\\mathrm{mmol}\\mathrm{h}^{-1}\\mathrm{m}^{-2}$ after 20 successive depositions of the colloidal solution. Longer-term hydrogen evolution experiments for a COF film produced with just a single dropcast cycle showed steady hydrogen production over 20 hours, indicating that the film was stable under the reaction condition ( $\\lambda>420\\mathrm{nm}$ , 0.1 M ascorbic acid) (Fig. 6e). We also tested hydrogen evolution of this film under solar simulator irradiation (AM1.5G, classification ABA, ASTM E927-10), which gave a HER of $15.8\\mathrm{mmolh^{-1}m^{-2}}$ $(\\sim0.361\\mathrm{h}^{-1}\\mathrm{m}^{-2})$ . This can be compared with data obtained at laboratory scale for carbon nitride films $(0.191\\mathrm{h}^{-1}\\mathrm{m}^{-2})^{58}$ . Scanning electron micrographs (Supplementary Fig. 81) show that these COF films had smooth, uniform morphologies, and AFM analysis (Supplementary Fig. 82) indicates that the film, after one dropcasting cycle, is ${\\sim}10\\mathrm{nm}$ thick. \n\n# Conclusions \n\nAlthough crystallinity is not required for all applications of porous materials59, here we see a dramatic enhancement in photocatalytic HERs for ordered, crystalline COFs over structurally related amorphous or semicrystalline solids. Organic building blocks that function well in amorphous polymers, such as dibenzo $[b,d]$ thiophene sulfone, lead to materials with better catalytic function when incorporated into COFs. A fused building block, benzo[1,2-b:4,5 - $\\mathbf{\\nabla}_{b^{\\prime}}$ ​]bis[b]benzothiophene sulfone, forms a COF with a sacrificial HER that exceeds our best linear polymers, P7 and P10, under comparable conditions, and that is also higher than for other reported $\\mathrm{COFs}^{32-37}$ . Because FS-COF is mesoporous, it can be dye-sensitized to give even higher HERs of up to $16.3\\mathrm{mmolg^{-1}h^{-1}}$ . FS-COF is also stable for at least $50\\mathrm{h}$ of photolysis in water under visible light $(\\lambda>420\\mathrm{nm})$ , and can be cast as a colloid onto planar supports to form thin films while still retaining its photocatalytic activity and stability. \n\n![](images/3a15773d37722541bffc0aa24db1c69c4f743ed69169178e28b6055c4c5e5687.jpg) \nFig. 6 | Dye sensitization of FS-COF and hydrogen evolution from an FS-COF film. a, Time course for photocatalytic ${\\sf H}_{2}$ production using visible light for FS-COF, a neat, near-infrared dye (WS5F​) and a dye-sensitized COF (FS-COF $^+$ WS5F); $5\\mathsf{m g}$ material in water, $5\\upmu\\upnu(\\%\\mathsf{H}_{2}\\mathsf{P}\\mathsf{t}\\mathsf{C}\\mathsf{l}_{6})$ $0.1M$ ascorbic acid, $\\lambda>420\\mathsf{n m},$ ). b, EQEs at three different incident light wavelengths for FS-COF and FS-COF $^+$ WS5F ( $5\\mathsf{m g}$ catalyst in water, $5\\upmu\\upnu(\\%\\mathsf{H}_{2}\\mathsf{P}\\mathsf{t}\\mathsf{C}\\mathsf{l}_{6})$ , 0.1 M ascorbic acid, $\\lambda=420\\pm10,$ $\\lambda=600\\pm45$ and $700\\pm10\\mathsf{n m}$ irradiation; Supplementary Fig. 43). c, Solid-state UV–vis spectra for FS-COF, WS5F​and $\\mathsf{F S-C O F+W S5F}.$ . d, Relative energy levels as calculated for ascorbic acid, FS-COF and a near-infrared dye, WS5F​; dashed green and orange lines indicate potentials for proton reduction and the two-hole oxidation of ascorbic acid in solution, respectively. e,f, Photocatalytic ${\\sf H}_{2}$ production using FS-COF films: longer-term hydrogen evolution experiments for a COF film produced with a single dropcast cycle (e); photographs showing (left to right) solid FS-COF and colloidal dispersions in DMF, water and acetone, respectively (f, left; see also Supplementary Figs. 33 and 87) and FS-COF film on glass producing hydrogen (f, right) (20 dropcasting cycles, $0.1M$ ascorbic acid, solar simulator AM1.5G, class ABA; see also Supplementary Movie 1 with two times original playing speed). \n\nComputation suggests that the fine detail of the AA layer stacking in FS-COF, and by analogy other COF materials, may determine the prospects for thermodynamic proton reduction and water oxidation. To improve our understanding of structure–property relationships, it would be helpful to produce COFs with greater degrees of long-range order. Recent synthetic developments, such as seeded growth strategies60, offer one way forward. \n\nProton reduction using a sacrificial electron donor is only the first step towards overall water splitting61, but the mesoporous morphology of these COFs, their processability into films, and their high native photocatalytic activity make them attractive platforms for developing hybrid photocatalysts. For example, the internal pore structure of COFs such as FS-COF could be decorated with quantum dots, photoactive organic molecules, fullerenes or single-site molecular catalysts. COFs with even larger mesopores might be designed to accommodate a second organic or inorganic semiconductor in the pore channels to produce a Z-scheme photocatalyst for overall water splitting62. \n\n# Methods \n\nCOF synthesis. All COFs were prepared using a procedure based on the method described here for the synthesis of FS-COF. A Pyrex tube was charged with 2,4,6-triformylphloroglucinol $(10.5\\mathrm{mg},0.05\\mathrm{mmol})$ , 3,9-diamino-benzo[1,2-b:4,5- $b^{\\prime}$ ​]bis[1]benzothiophene-5,5,11,11-tetraoxide $(28.8\\mathrm{mg},0.075\\mathrm{mmol}$ ), mesitylene $(1.5\\mathrm{ml})$ , 1,4-dioxane $(1.5\\mathrm{ml})$ and aqueous acetic acid $(0.3{\\mathrm{ml}},\\$ , 6 M). This mixture was homogenized by sonication for $10\\mathrm{min}$ and the tube was then flash-frozen at $77.3\\mathrm{K}$ (liquid $\\Nu_{2}$ bath) and degassed by three freeze–pump–thaw cycles, before evacuating to a pressure of $100\\mathrm{mtorr}$ . The tube was sealed and then heated at $120^{\\circ}\\mathrm{C}$ for 3 days. The brown precipitate was collected by centrifugation and washed with N,Ndimethylformamide $(100\\mathrm{ml})$ and acetone $(200\\mathrm{ml})$ . After drying at $120^{\\circ}\\mathrm{C}.$ the product was obtained as a deep red powder (21 mg, $58\\%$ ). Anal. calcd for $\\left(\\mathrm{C}_{30}\\mathrm{H}_{22}\\mathrm{N}_{2}\\mathrm{O}_{8}\\mathrm{S}_{2}\\right)_{r}$ : C, 61.42; H, 3.78; N, 4.78; S, 10.93. Found: C, 44.80; H, 3.21; N, 3.95; S, 9.93. \n\nDye sensitization. For water-insoluble dyes such as WS5F​, the dye was loaded into the COF using an organic solvent before hydrogen evolution experiments. To do this, $5\\mathrm{mg}\\mathbf{W}\\mathbf{S}\\mathbf{5}\\mathbf{F}$ ​was dissolved in $10\\mathrm{ml}$ acetone and then $5\\mathrm{mg}$ FS-COF was added to the solution and stirred for 12 h. The resulting mixture was filtered, and the filtrate was dried at $80^{\\circ}\\mathrm{C}$ overnight. Amorphous FS-P was loaded with WS5F​in the same way. For water-soluble dyes, the dye was added directly into the photocatalytic mixture. In a typical procedure, a flask was charged with COF powder (or amorphous polymer) $(5\\mathrm{mg})$ , aqueous $0.1\\mathrm{M}$ ascorbic acid solution $(25\\mathrm{ml})$ and hexachloroplatinic acid ${\\mathrm{?5\\upmul,}}$ $8\\mathrm{wt\\%}$ aqueous solution). In the case of dye sensitization experiments with water-soluble dyes (Eosin $\\mathrm{Y},2^{\\prime}$ ​, \n\n$7^{\\prime}$ ​-dichlorofluorescein or Rose Bengal), the dye was added directly to the flask. \nHERs were normalized to the mass of the COF (or amorphous polymer) in all cases. \n\nHydrogen evolution experiments. A flask was charged with the photocatalyst powder $\\mathrm{\\langle5mg\\rangle}$ , $0.1\\mathrm{M}$ ascorbic acid water solution $(25\\mathrm{ml})$ , hexachloroplatinic acid $(5\\upmu\\upmu$ , 8 wt% aqueous solution) as a Pt precursor and water-soluble dye (if any). The resulting suspension was ultrasonicated for $20\\mathrm{min}$ before degassing by $\\Nu_{2}$ bubbling for $30\\mathrm{min}$ . The reaction mixture was illuminated with a 300 W Newport Xe light source (model 6258, ozone-free) for the period specified, using appropriate filters. The lamp was cooled by water circulating through a metal jacket. Gas samples were taken with a gas-tight syringe and analysed using a Bruker 450-GC gas chromatograph (GC). Hydrogen was detected with a thermal conductivity S3 detector referencing against a standard gas of known concentration. Hydrogen dissolved in the reaction mixture was not measured and the pressure increase generated by the evolved hydrogen was neglected in the calculations. The rates were determined from a linear regression fit. After 5 h of photocatalysis, no carbon monoxide associated with framework or ascorbic acid decomposition could be detected on a GC system equipped with a pulsed discharge detector. After the photocatalysis experiment, the FS-COF was recovered by washing with water and acetone before drying at $120^{\\circ}\\mathrm{C}$ . \n\nCalculations. For the different molecular fragments representing the COFs, we calculated the standard reduction potentials of half-reactions for free electrons/ holes and excitons, using DFT and time-dependent DFT (TD-DFT). The B3LYP63,64 density functional was used for all DFT and TD-DFT calculations (unless otherwise stated), together with the Def2-SVP basis set65, using Gaussian 16 software66. S1 optimizations for calculations of exciton potentials $\\mathrm{{.IP^{*}}}$ and EA\\*) used the Tamm–Dancoff approximation67. The effect of solvation by water was accounted for using the PCM/SMD solvation model68,69. The potentials of the solution reactions for one- and two-hole oxidation of ascorbic acid were calculated as described in Supplementary Section 22, while the experimental values were used for the proton reduction and water oxidation reactions. \n\nPeriodic DFT calculations on the COF crystal structures were carried out within the plane-wave pseudopotential formalism, using the Vienna ab initio Simulation Package (VASP) $\\mathrm{code^{70}}$ . Geometry optimizations were performed with the Perdew–Burke–Ernzerhof exchange–correlation functional with the DFT-D3(BJ) dispersion correction $^{71-73}$ . A kinetic-energy cutoff of $500\\mathrm{eV}$ was used to define the plane-wave basis set. The electronic structure of each optimized COF structure was then computed using a screened hybrid exchange–correlation functional $(\\mathrm{HSE06})^{74-76}$ , giving key electronic properties, such as bandgap and electrostatic potential. To achieve valence band alignment so that band energies could be compared for the different COF structures, we followed an approach devised for determining the vacuum level of porous structures77. Further computational details are provided in Supplementary Section 22. \n\n# Data availability \n\nCrystallographic data for the structures reported in this Article have been deposited at the Cambridge Crystallographic Data Centre, under deposition nos. CCDC 1818058 (fused sulfone diamine, FSA​) and 1818059 (sulfone diamine, SA​). Copies of the data can be obtained free of charge from www.ccdc.cam.ac.uk/ structures/. All other data supporting the findings of this study are available within the Article and its Supplementary Information and/or from the corresponding authors upon reasonable request. \n\n# Received: 2 May 2018; Accepted: 13 August 2018; Published online: 1 October 2018 \n\n# References \n\n1.\t Fujishima, A. & Honda, K. Electrochemical photolysis of water at a semiconductor electrode. Nature 238, 37–38 (1972). \n2.\t Kudo, A. & Miseki, Y. Heterogeneous photocatalyst materials for water splitting. Chem. Soc. Rev. 38, 253–278 (2009). \n3.\t Sivula, K. & van de Krol, R. Semiconducting materials for photoelectrochemical energy conversion. Nat. Rev. Mater. 1, 15010 (2016). \n4.\t Chen, S., Takata, T. & Domen, K. Particulate photocatalysts for overall water splitting. Nat. Rev. Mater. 2, 17050 (2017). \n5.\t Wang, X. et al. A metal-free polymeric photocatalyst for hydrogen production from water under visible light. Nat. Mater. 8, 76–80 (2009). \n6.\t Sprick, R. S. et al. Tunable organic photocatalysts for visible-light-driven hydrogen evolution. J. Am. Chem. Soc. 137, 3265–3270 (2015). \n7.\t Zhang, G., Lan, Z.-A. & Wang, X. Conjugated polymers: catalysts for photocatalytic hydrogen evolution. Angew. Chem. Int. Ed. 55, 2–18 (2016). \n8.\t Yanagida, S., Kabumoto, A., Mizumoto, K., Pac, C. & Yoshino, K. Poly(para) phenylene-catalyzed photoreduction of water to hydrogen. Chem. Commun. 8, 474–475 (1985). \n9.\t Shibata, T. et al. Novel visible-light-driven photocatalyst. Poly $(p$ -phenylene)- catalyzed photoreductions of water, carbonyl compounds, and olefins. J. Phys. Chem. 94, 2068–2076 (1990). \n10.\tSchwinghammer, K. et al. Crystalline carbon nitride nanosheets for improved visible-light hydrogen evolution. J. Am. Chem. Soc. 136, 1730–1733 (2014). \n11.\tSchwab, M. G. et al. Photocatalytic hydrogen evolution through fully conjugated poly(azomethine) networks. Chem. Commun. 46, 8932 (2010). \n12.\tYang, C. et al. Molecular engineering of conjugated polybenzothiadiazoles for enhanced hydrogen production by photosynthesis. Angew. Chem. Int. Ed. 55, 9202–9206 (2016). \n13.\tLi, L. et al. Rational design of porous conjugated polymers and roles of residual palladium for photocatalytic hydrogen production. J. Am. Chem. Soc. 138, 7681–7686 (2016). \n14.\t Woods, D. J., Sprick, R. S., Smith, C. L., Cowan, A. J. & Cooper, A. I. A solution-processable polymer photocatalyst for hydrogen evolution from water. Adv. Energy Mater. 7, 1700479 (2017). \n15.\tSprick, R. S. et al. Extended conjugated microporous polymers for photocatalytic hydrogen evolution from water. Chem. Commun. 52, 10008–10011 (2016). \n16.\tSprick, R. S. et al. Visible-light-driven hydrogen evolution using planarized conjugated polymer photocatalysts. Angew. Chem. Int. Ed. 55, 1792–1796 (2016). \n17.\tWang, k et al. Covalent triazine frameworks via a low temperature polycondensation approach. Angew. Chem. Int. Ed. 56, 14337–14341 (2017). \n18.\tMeier, C. B. et al. Structure–property relationships for covalent triazine-based frameworks: the effect of spacer length on photocatalytic hydrogen evolution from water. Polymer 126, 283–290 (2017). \n19.\tBi, J. et al. Covalent triazine-based frameworks as visible light photocatalysts for the splitting of water. Macromol. Rapid Commun. 36, 1799–1805 (2015). \n20.\t Zhang, G., Lan, Z.-A., Lin, L., Lin, S. & Wang, X. Overall water splitting by $\\mathrm{Pt/g–C_{3}N_{4}}$ photocatalysts without using sacrificial agents. Chem. Sci. 7, 3062–3066 (2016). \n21.\tWang, L. et al. Conjugated microporous polymer nanosheets for overall water splitting using visible light. Adv. Mater. 29, 1702428 (2017). \n22.\tZhang, G. et al. Optimizing optical absorption, exciton dissociation, and charge transfer of a polymeric carbon nitride with ultrahigh solar hydrogen production activity. Angew. Chem. Int. Ed. 56, 13445–13449 (2017). \n23.\tCoropceanu, V. et al. Charge transport in organic semiconductors. Chem. Rev. 107, 926–952 (2007). \n24.\t Ockwig, N. W., Cote, A. P., Keeffe, M. O., Matzger, A. J. & Yaghi, O. M. Porous, crystalline, covalent organic frameworks. Science 310, 1166–1171 (2005). \n25.\tEl-Kaderi, H. M. et al. Designed synthesis of 3D covalent organic frameworks. Science 316, 268–272 (2007). \n26.\tDiercks, C. S. & Yaghi, O. M. The atom, the molecule, and the covalent organic framework. Science 355, eaal1585 (2017). \n27.\t Spitler, E. L. et al. Lattice expansion of highly oriented 2D phthalocyanine covalent organic framework films. Angew. Chem. Int. Ed. 51, 2623–2627 (2012). \n28.\tSpitler, E. L. & Dichtel, W. R. Lewis acid-catalysed formation of twodimensional phthalocyanine covalent organic frameworks. Nat. Chem. 2, 672–677 (2010). \n29.\tKandambeth, S. et al. Construction of crystalline 2D covalent organic frameworks with remarkable chemical (acid/base) stability via a combined reversible and irreversible route. J. Am. Chem. Soc. 134, 19524–19527 (2012). \n30.\t Huang, N., Wang, P. & Jiang, D. Covalent organic frameworks: a materials platform for structural and functional designs. Nat. Rev. Mater. 1, 16068 (2016). \n31.\tWan, S. et al. Covalent organic frameworks with high charge carrier mobility. Chem. Mater. 23, 4094–4097 (2011). \n32.\tThote, J. et al. A covalent organic framework–cadmium sulfide hybrid as a prototype photocatalyst for visible-light-driven hydrogen production. Chem. Eur. J. 20, 15961–15965 (2014). \n33.\tZhou, J. et al. A (001) dominated conjugated polymer with high-performance of hydrogen evolution under solar light irradiation. Chem. Commun. 53, 10536–10539 (2017). \n34.\tStegbauer, L., Schwinghammer, K. & Lotsch, B. V. A hydrazone-based covalent organic framework for photocatalytic hydrogen production. Chem. Sci. 5, 2789–2793 (2014). \n35.\tVyas, V. S. et al. A tunable azine covalent organic framework platform for visible light-induced hydrogen generation. Nat. Commun. 6, 8508 (2015). \n36.\tHaase, F. et al. Structure–property–activity relationships in a pyridine containing azine-linked covalent organic framework for photocatalytic hydrogen evolution. Faraday Discuss. 162, 165–169 (2017). \n37.\tPachfule, P. et al. Diacetylene functionalized covalent organic framework (COF) for photocatalytic hydrogen generation. J. Am. Chem. Soc. 140, 1423–1427 (2018). \n38.\tBanerjee, T. et al. Single site photocatalytic $\\mathrm{H}_{2}$ evolution from covalent organic frameworks with molecular cobaloxime co-catalysts. J. Am. Chem. Soc. 139, 16228–16234 (2017). \n39.\tLin, S. et al. Covalent organic frameworks comprising cobalt porphyrins for catalytic $\\mathrm{CO}_{2}$ reduction in water. Science 349, 1208–1213 (2015). \n40.\tSick, T. et al. Oriented films of conjugated 2D covalent organic frameworks as photocathodes for water splitting. J. Am. Chem. Soc. 140, 2085–2092 (2018). \n41.\tZhu, Y. & Zhang, W. Reversible tuning of pore size and $\\mathrm{CO}_{2}$ adsorption in azobenzene functionalized porous organic polymers. Chem. Sci. 5, 4957–4961 (2014). \n42.\tKruczynski, L. et al. Porous titania glass as a photocatalyst for hydrogen production from water. Nature 291, 399–401 (1981). \n43.\tWagner, F. T. & Somorjai, G. A. Photocatalytic hydrogen production from water on Pt-free $\\mathrm{SrTiO}_{3}$ in alkali hydroxide solutions. Nature 285, 559–560 (1980). \n44.\tCorp, K. L., Schlenker, C. W., Corp, K. L. & Schlenker, C. W. Ultrafast spectroscopy reveals electron transfer cascade that improves hydrogen evolution with carbon nitride photocatalysts. J. Am. Chem. Soc. 139, 7904–7912 (2017). \n45.\tKroeze, J. E., Savenije, T. J., Vermeulen, M. J. W. & Warman, J. M. Contactless determination of the photoconductivity action spectrum, exciton diffusion length, and charge separation efficiency in polythiophene-sensitized $\\mathrm{TiO}_{2}$ bilayers. J. Phys. Chem. B 107, 7696–7705 (2003). \n46.\tBruno, A., Reynolds, L. X., Dyer-Smith, C., Nelson, J. & Haque, S. A. Determining the exciton diffusion length in a polyfluorene from ultrafast fluorescence measurements of polymer/fullerene blend films. J. Phys. Chem. C 117, 19832–19838 (2013). \n47.\tShaw, P. E., Ruseckas, A. & Samuel, I. D. W. Exciton diffusion measurements in poly(3-hexylthiophene). Adv. Mater. 20, 3516–3520 (2008). \n48.\tTezuka, Y., Fukushima, A., Matsui, S. & Imai, K. Surface studies on poly(vinyl alcohol)-poly(dimethylsiloxane) graft copolymers. J. Colloid Interface Sci. 114, 16–25 (1986). \n49.\tBiswal, B. P. et al. Pore surface engineering in porous, chemically stable covalent organic frameworks for water adsorption. J. Mater. Chem. A 3, 23664–23669 (2015). \n50.\tGuiglion, P., Butchosa, C. & Zwijnenburg, M. A. Polymer photocatalysts for water splitting: insights from computational modeling. Macromol. Chem. Phys. 217, 344–353 (2016). \n51.\tGuiglion, P., Monti, A. & Zwijnenburg, M. A. Validating a density functional theory approach for predicting the redox potentials associated with charge carriers and excitons in polymeric photocatalysts. J. Phys. Chem. C 121, 1498–1506 (2017). \n52.\tBach, U. et al. Solid-state dye-sensitized mesoporous $\\mathrm{TiO}_{2}$ solar cells with high photon-to-electron conversion efficiencies. Nature 395, 583–585 (1998). \n53.\tWillkomm, J. et al. Dye-sensitised semiconductors modified with molecular catalysts for light-driven $\\mathrm{H}_{2}$ production. Chem. Soc. Rev. 45, 9–23 (2016). \n54.\tAbe, R., Sayama, K., Domen, K. & Arakawa, H. A new type of water splitting system composed of two different $\\mathrm{TiO}_{2}$ photocatalysts (anatase, rutile) and a $\\mathrm{IO}_{3}{}^{-}/\\mathrm{I}^{-}$ shuttle redox mediator. Chem. Phys. Lett. 344, 339–344 (2001). \n55.\tWang, Q. et al. Scalable water splitting on particulate photocatalyst sheets with a solar-to-hydrogen energy conversion efficiency exceeding $1\\%$ . Nat. Mater. 15, 611–615 (2016). \n56.\t Tada, H., Mitsui, T., Kiyonaga, T., Akita, T. & Tanaka, K. All-solid-state Z-scheme in $\\mathrm{CdS}{\\mathrm{-Au}}{\\mathrm{-TiO}}_{2}$ three-component nanojunction system. Nat. Mater. 5, 782–786 (2006). \n57.\tGoto, Y. et al. A particulate photocatalyst water-splitting panel for large-scale solar hydrogen generation. Joule 2, 509–520 (2018). \n58.\tSchröder, M. et al. Hydrogen evolution reaction in a large-scale reactor using a carbon nitride photocatalyst under natural sunlight irradiation. Energy Technol. 3, 1014–1017 (2015). \n59.\tSlater, A. G. & Cooper, A. I. Function-led design of new porous materials. Science 348, aaa8075 (2015). \n60.\tEvans, A. M. et al. Seeded growth of single-crystal two-dimensional covalent organic frameworks. Science 361, 52–57 (2018). \n61.\tTeets, T. S. & Nocera, D. G. Photocatalytic hydrogen production. Chem. Commun. 47, 9268–9274 (2011). \n62.\tHisatomi, T., Kubota, J. & Domen, K. Recent advances in semiconductors for photocatalytic and photoelectrochemical water splitting. Chem. Soc. Rev. 43, 7520–7535 (2014). \n63.\tBecke, A.D. Density-functional thermochemistry. III. The role of exact exchange. J. Chem. Phys. 98, 5648–5652 (1993). \n64.\tStephens, P., Devlin, F., Chabalowski, C. & Frisch, M. J. Ab initio calculation of vibrational absorption and circular dichroism spectra using density functional force fields. J. Phys. Chem. 98, 11623–11627 (1994). \n65.\tWeigend, F. & Ahlrichs, R. Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: design and assessment of accuracy. Phys. Chem. Chem. Phys. 7, 3297–3305 (2005). \n66.\tFrisch, M. J. et al. Gaussian 16 revision A.03 (Gaussian, 2016). \n67.\tHirata, S. & Head-Gordon, M. Time-dependent density functional theory within the Tamm–Dancoff approximation. Chem. Phys. Lett. 314, 291–299 (1999). \n68.\tScalmani, G. & Frisch, M. J. Continuous surface charge polarizable continuum models of solvation. I. General formalism. J. Chem. Phys. 132, 114110 (2010). \n69.\tMarenich, A. V., Cramer, C. J. & Truhlar, D. G. Universal solvation model based on solute electron density and a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J. Phys. Chem. B 113, 6378–6396 (2009). \n70.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n71.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n72.\tGrimme, S., Antony, J., Ehrlich, S. & Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 132, 154104 (2010). \n73.\t Grimme, S., Ehrlich, S. & Goerigk, L. Effect of the damping function in dispersion corrected density functional theory. J. Comp. Chem. 32, 1456 (2011). \n74.\tHeyd, J., Scuseria, G. E. & Ernzerhof, M. Hybrid functionals based on a screened Coulomb potential. J. Chem. Phys. 118, 8207–8215 (2003). \n75.\tHeyd, J. & Scuseria, G. E. Efficient hybrid density functional calculations in solids: assessment of the Heyd-Scuseria-Ernzerhof screened Coulomb hybrid functional. J. Chem. Phys. 121, 1187–1192 (2004). \n76.\tHeyd, J., Scuseria, G. E. & Ernzerhof, M. Erratum: ‘Hybrid functionals based on a screened Coulomb potential’. J. Chem. Phys. 124, 219906 (2006). \n77.\tButler, K. T., Hendon, C. H. & Walsh, A. Electronic chemical potentials of porous metal–organic frameworks. J. Am. Chem. Soc. 136, 2703–2706 (2014). \n\n# Acknowledgements \n\nThe authors acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC) (EP/N004884/1), the European Union’s Seventh Framework Programme through grant agreement nos. 321156 (ERC-AG-PE5-ROBOT) and 692685, and the Leverhulme Trust via the Leverhulme Research Centre for Functional Materials Design. X.W. thanks the China Scholarship Council for a PhD studentship. Y.W. and W.-H.Z. acknowledge financial support from the NSFC for Creative Research Groups (21421004) and Key Project (21636002), NSFC/China and a Shanghai Oriental Scholarship. The authors thank M. Bilton for help with HR-TEM, F. McBride for help with AFM, and G.-H. Ning and H. Niu for useful discussions. The authors acknowledge the Diamond Light Source for access to beamlines I19 (MT15777) and I11 (EE12336), the ARCHER UK National Supercomputing Service, access provided via a Programme Grant (EP/N004884/1) and the EPSRC funded UK Materials Chemistry Consortium (EP/L000202/1), and the use of the facilities of the N8 HPC Centre of Excellence, provided and funded by the N8 Research Partnership and EPSRC (EP/K000225/1). \n\n# Author contributions \n\nA.I.C. and X.W. conceived the project. X.W. synthesized the COFs and performed the characterization and photocatalysis experiments. L.C. and M.A.Z. conceived the modelling strategy and performed the calculations. S.Y.C. carried out PXRD analyses. M.A.L. carried out single-crystal X-ray structure analysis. R.S.S. performed the TCSPC experiments and co-supervised, with A.I.C., the work on COF synthesis, characterization and photocatalysis. Y.Y. collected the water sorption isotherms. R.C., X.W. and L.C. interpreted the gas sorption isotherms. Y.W. and W.-H.Z. synthesized and characterized the WS5F​dye. All authors interpreted the data and contributed to preparation of the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41557-018-0141-5. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to A.I.C. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2018 " + }, + { + "id": "10.1109_MCOM.2018.1700659", + "DOI": "10.1109/MCOM.2018.1700659", + "DOI Link": "http://dx.doi.org/10.1109/MCOM.2018.1700659", + "Relative Dir Path": "mds/10.1109_MCOM.2018.1700659", + "Article Title": "A New Wireless Communication Paradigm through Software-Controlled Metasurfaces", + "Authors": "Liaskos, C; Nie, S; Tsioliaridou, A; Pitsillides, A; Ioannidis, S; Akyildiz, I", + "Source Title": "IEEE COMMUNICATIONS MAGAZINE", + "Abstract": "Electromagnetic waves undergo multiple uncontrollable alterations as they propagate within a wireless environment. Free space path loss, signal absorption, as well as reflections, refractions, and diffractions caused by physical objects within the environment highly affect the performance of wireless communications. Currently, such effects are intractable to account for and are treated as probabilistic factors. This article proposes a radically different approach, enabling deterministic, programmable control over the behavior of wireless environments. The key enabler is the so-called HyperSurface tile, a novel class of planar meta-materials that can interact with impinging electromagnetic waves in a controlled manner. The HyperSurface tiles can effectively re-engineer electromagnetic waves, including steering toward any desired direction, full absorption, polarization manipulation, and more. Multiple tiles are employed to coat objects such as walls, furniture, and overall, any objects in indoor and outdoor environments. An external software service calculates and deploys the optimal interaction types per tile to best fit the needs of communicating devices. Evaluation via simulations highlights the potential of the new concept.", + "Times Cited, WoS Core": 840, + "Times Cited, All Databases": 878, + "Publication Year": 2018, + "Research Areas": "Engineering; Telecommunications", + "UT (Unique WOS ID)": "WOS:000444843900029", + "Markdown": "# A New Wireless Communication Paradigm through Software-Controlled Metasurfaces \n\nChristos Liaskos, Shuai Nie, Ageliki Tsioliaridou, Andreas Pitsillides, Sotiris Ioannidis, and Ian Akyildiz \n\nElectromagnetic waves undergo multiple uncontrollable alterations as they propagate within a wireless environment. Free space path loss, signal absorption, as well as reflections, refractions, and diffractions caused by physical objects within the environment highly affect the performance of wireless communications. Currently, such effects are intractable to account for and are treated as probabilistic factors. The authors propose a radically different approach, enabling deterministic, programmable control over the behavior of wireless environments. \n\n# Abstract \n\nElectromagnetic waves undergo multiple uncontrollable alterations as they propagate within a wireless environment. Free space path loss, signal absorption, as well as reflections, refractions, and diffractions caused by physical objects within the environment highly affect the performance of wireless communications. Currently, such effects are intractable to account for and are treated as probabilistic factors. This article proposes a radically different approach, enabling deterministic, programmable control over the behavior of wireless environments. The key enabler is the so-called HyperSurface tile, a novel class of planar meta-materials that can interact with impinging electromagnetic waves in a controlled manner. The HyperSurface tiles can effectively re-engineer electromagnetic waves, including steering toward any desired direction, full absorption, polarization manipulation, and more. Multiple tiles are employed to coat objects such as walls, furniture, and overall, any objects in indoor and outdoor environments. An external software service calculates and deploys the optimal interaction types per tile to best fit the needs of communicating devices. Evaluation via simulations highlights the potential of the new concept. \n\n# Introduction \n\nWireless communications are rapidly evolving toward a software-based functionality paradigm, where every part of the device hardware can adapt to changes in the environment. Beamforming-enabled antennas, cognitive spectrum usage, adaptive modulation, and encoding are but a few of the device aspects that can now be tuned to optimize communication efficiency [1]. In this optimization process, however, the environment remains an uncontrollable factor: it remains unaware of the communication process going on within it. In this article we make the environmental effects controllable and optimizable via software. \n\nA wireless environment is defined as the set of physical objects that significantly alter the propagation of electromagnetic (EM) waves among communicating devices. In general, emitted waves undergo attenuation and scattering before reaching an intended destination. Attenuation is due to material absorption losses, and the natural spreading of power within space, that is, the distribution of power over an ever increasing spherical surface. Wave scattering is due to the diffraction, reflection, and refraction phenomena, which result in a multiplicity of propagation paths between devices. The geometry, positioning, and composition of objects define the propagation outcome, which is, however, intractable to calculate except for simple cases. \n\nApart from being uncontrollable, the environment has a generally negative effect on communication efficiency. The signal attenuation limits the connectivity radius of nodes, while multi-path propagation results in fading phenomena, a well-studied effect that introduces drastic fluctuations in the received signal power. The signal deterioration is perhaps the major consideration in forthcoming millimeter-wave (mmWave) and THz communications. While these extremely high communication frequencies offer unprecedented data rates and device size minimization, they suffer from acute attenuation due to molecular absorption, multi-path fading, and Doppler shift even at pedestrian speeds, limiting their present use in short line-of-sight distances [1]. Existing mitigation approaches propose massive multiple-input multiple-output (MIMO) and 3D beamforming at the device side [2], and passive reflectors/ active reflect arrays carefully placed at intermediate points within a space [3, 4]. However, while these approaches provide a good degree of control over the directivity of wireless transmissions, they pose mobility and hardware scalability issues. Moreover, the control is limited to directivity and does not extend to full EM manipulation. As a result, the wireless environment as a whole remains unaware of the ongoing communications within it, and the channel model continues to be treated as a probabilistic process rather than as a software-defined service. \n\nThe key enabler for building a programmable wireless environment is the concept of metamaterials and metasurfaces [5]. Metamaterials are artificial structures with engineered EM properties across any frequency domain. In their most common form, they comprise a basic simple structure, the meta-atom, which is repeated periodically within a volume. Metasurfaces are the 2D counterparts of metamaterials, in the sense of having small — but not negligible — depth. While materials found in nature derive their properties from their molecular structure, the properties of metamaterials stem from the form of their meta-at \n\nMetamaterials are artificial structures, with engineered EM properties across any frequency domain. In their most common form, they comprise a basic, simple structure, the meta-atom, which is repeated periodically within a volume. Metasurfaces are the 2D counterparts of metamaterials, in the sense of having small-but not negligible-depth. \n\n![](images/f2e1b9c6f3a49eec99297c8127bf67e9cee839dc0c7969ebf6abee0d0de0e26e.jpg) \nFigure 1. Programmable wireless environments can exhibit user-adapting, unnatural wireless behavior, manipulating EM waves to match the requirements of users. Wireless power transfer, quality of service (QoS), and security scenarios are illustrated. \n\nom design. Thus, when treated macroscopically, metamaterials exhibit custom permittivity and permeability values locally, even beyond those found in natural materials. As a consequence, metamaterials enable exotic interactions with impinging EM waves, being able to fully re-engineer incoming waves. Finally, dynamic meta-atom designs can be altered with simple external bias (e.g., a binary switch), endowing metamaterials and metasurfaces with adaptivity. The naming of metamaterials is a testament to their simple and scalable internal structure, which classifies them as materials rather than as antenna arrays. \n\nThe methodology for introducing software control over the EM behavior of a wireless environment consists of coating objects, such as walls, furniture, and overall any objects in indoor or outdoor environments, with HyperSurfaces, a forthcoming class of software-controlled metasurfaces [6]. HyperSurfaces merge networked control elements with adaptive metasurfaces. The control elements apply the proper bias to adaptive metasurface meta-atoms, thereby attaining a desired macroscopic EM behavior. Additionally, the HyperSurface has interconnectivity capabilities, which allow it to enter control loops for adapting their performance. In this article we introduce the HyperSurface tile architecture and the process of using them to build programmable wireless environments. We discuss the high-level programming interfaces for interacting with tiles, and detail the enabling of a new class of software that will treat wireless propagation as an application. We proceed further to study practical incorporation in existing networking infrastructures and to evaluate the novel capabilities of the programmable environments via ray-tracing-based simulations. \n\nThe remainder of this article is organized as follows. The next section presents the programmable wireless environment concept, and then we detail its architecture. Evaluation via simulations takes place. Research challenges are then discussed, and the article is concluded in the final section. \n\n# Programmable Wireless Environments: The Concept \n\nConsider a scenario of wireless communications within a space, as shown in Fig. 1. Several users require connectivity, each with different requirements. Users A and D are interested in optimal connection quality, user B is interested in wireless power transfer, and user C requires eavesdropping avoidance measures. Finally, user E represents unauthorized access or interference attempts, which may be deliberate or random. In the common passive environment, such objectives cannot be met efficiently. Devices employ beamforming to find promising wave transmission directions, but the environment remains oblivious to the process. EM waves scatter uncontrollably upon objects, sharply losing their focus and carried power, causing interference, performance drop, and security concerns. \n\nIn the case of a programmable wireless environment, objects including walls, ceilings, and so on receive HyperSurface-tile coating that enables them to re-engineer impinging waves in a software-defined manner. Each tile incorporates a lightweight Internet of Things (IoT) gateway, which enables it to receive commands from a central configuration service and set its custom EM behavior accordingly. In collaboration with existing device beamforming mechanisms and location discovery services, the programmable environment allows for novel capabilities, essentially treating EM propagation in a manner reminiscent of routers and firewalls in classical networking. As shown in Fig. 1, users A and D receive maximum signal-to-interference power levels by carefully focusing the EM waves in a lenslike manner and avoiding mutual interference. Moreover, the wave propagation is groomed further to achieve constructive superposition at the user devices, optimizing their power-delay profile (PDP) and avoiding the negative effects of multi-path fading. The environmental response for user B targets maximum wireless power transfer using a combination of custom wave steering and focusing, but without PDP concerns. For user $C,$ the environment establishes a “private air route,” that avoids all other users to reduce the risk of eavesdropping. Finally, the unauthorized user E is blocked by instructing the environment to absorb his/her emissions, potentially using the harvested energy in a constructive way, such as powering some HyperSurface tiles. \n\n![](images/5e64b1e07246878b289a946ee91a31e3ad33eb90077086d3d6dba75d2abc13a0.jpg) \nFigure 2. Meta-atom patterns that have been commonly employed and investigated in metasurface research. \nFig. 2. The operating principle of metasurfaces is as follows. When EM waves impinge on a metasurface, it creates currents in it via induction. In the case of static meta-atoms (Fig. 2a), the total current pattern within the surface is fully defined by the meta-atom geometry and composition. In dynamic designs (Fig. 2d), the current pattern also depends on the states of the switching elements. The inducted current also creates a response field, following the laws of electromagnetism. The meta-atoms are engineered to yield a custom response field. \n\nWe proceed to detail the architecture of the HyperSurface tiles that comprise a programmable environment. Moreover, we discuss its incorporation in existing network infrastructures, as well as the process for modeling and treating wireless propagation as an app. \n\n# The Architecture of Programmable Environments \n\nWe begin by presenting some prerequisite knowledge on the structure and properties of metasurfaces. Here we focus on the basics required to subsequently describe the HyperSurfaces. \n\nA metasurface is a composite material layer, designed and optimized to function as a tool to control and transform EM waves [5]. They commonly comprise a conductive pattern repeated over a dielectric substrate. Examples of meta-atom patterns constituting the building blocks of some of the most common metasurfaces are shown in \n\nThe meta-atom size and the thickness of the tile are important design factors that define the maximum frequency for EM wave interaction. As a rule of thumb, meta-atoms are bounded within a square region of $\\lambda/10\\leftrightarrow\\lambda/5,\\lambda$ being the EM interaction wavelength. The minimal HyperSurface thickness is also in the region of $\\lambda/10\\stackrel{\\cdot}{\\leftrightarrow}\\lambda/5$ . Thus, for an interaction frequency of $5\\mathrm{\\GHz},$ the meta-atom would have a side of $\\sim8\\ m\\mathrm{m},$ , with similar thickness. \n\nWe note that dynamic meta-atom designs constitute an extensively studied subject in the literature, offering a wide variety of choices. An extremely wide array of EM interaction types (denoted as functions) have been achieved across many spectra (e.g., wave steering, polarizing, absorbing, filtering, and collimation) resulting from fascinating metasurface properties such as near zero permittivity and/or permeability response, peculiar anisotropic response leading, for example, to hyperbolic dispersion relation, giant chirality, nonlinear response, and more [5, 7, 8]. \n\n# The HyperSurface \n\nA HyperSurface tile is envisioned as a planar, rectangular structure that can host metasurface functions over its surface with programmatic control. It comprises a stack of virtual and physical components, shown in Fig. 3, which are detailed below. \n\nThe Functionality and Configuration Layers: A HyperSurface tile supports software descriptions of metasurface EM functions, allowing a programmer to customize, deploy, or retract them on demand via a programming interface with appropriate callbacks. These callbacks have the following general form: \n\noutcome $\\leftarrow$ callback(action_type, parameters) \n\nThe action_type is an identifier denoting the intended function to be applied to the impinging waves, such as STEER or ABSORB. Each action type is associated with a set of valid parameters. For instance, STEER commands require an incident wave direction, an intended reflection direction, and the applicable wave frequency band. ABSORB commands require no incident or reflected wave direction parameters. \n\nThe functionality layer is exposed to programmers via an application programming interface (API) that serves as a strong layer of abstraction. It hides the internal complexity of the HyperSurface and offers general-purpose access to metasurface functions without requiring knowledge of the underlying hardware and physics. Thus, the configuration of the phase switch materials that matches the intended EM function is derived automatically, without the programmer’s intervention. \n\nThe Metasurface Layer: It is the metasurface hardware comprising dynamic meta-atoms, whose states are altered to yield an intended EM function. This layer comprises both the passive and active elements of meta-atoms. For instance, the example of Fig. 3 comprises conductive square patches (passive) and switches (active). It is noted that even simple ON (most conductive)/OFF (most insulating) switches are sufficient for building metasurfaces supporting an impressive range of EM functions [5]. \n\nLarge area electronics (LAE) constitutes a very promising approach for manufacturing the metasurface layers [9]. LAE can be manufactured using conductive ink-based printing methods on flexible and transparent polymer films, and incorporate polymer switches (diodes) [9]. Apart from minimal cost, the LAE approach favors scalability and deployment of HyperSurfaces. Tiles can be manufactured as large films with metasurface patterns and diode switches printed on them, and be placed on common objects (e.g., glass, doors, walls, desks), which may also play the role of the dielectric substrate for the metasurface. \n\nThe Intra-Tile Control Layer: This layer describes the hardware components and wiring that enable the programmatic control over the switches of the metasurface layer. A very promising, cost-effective, and highly scalable approach is to control the metasurface switches as a diode array [10]; that is, as a common light-emitting diode (LED) display works. Meta-atoms are treated as very simple “pixels,” with just two “colors” (ON/OFF). The diode array approach results in a very simple control layer, which comprises just the wiring to connect each meta-atom switch to the gateway (discussed below). Moreover, it entails a very low power drain. For instance, assume a meta-atom with size $8\\times8~\\mathrm{mm}$ , which can interact with waves modulated at $5\\mathrm{\\CHz}$ . A total number of 324,375 meta-atoms are required for coating a $5\\times3~\\mathrm{m}$ wall. As shown in [10, p. 497], a single elastic diode exhibits a drain of $\\bar{5}\\mathrm{~V~}\\cdot1.6\\mathrm{~}\\upmu\\mathrm{A}=\\mathrm{~8~}$ $\\upmu\\mathrm{W}$ when powered. Thus, the total coating of the wall will drain ${\\sim}1.88~\\mathrm{W}$ at a maximum — that is, when all diodes are set to $^{\\prime\\prime}\\mathrm{ON^{\\prime\\prime}}-$ or $125\\mathrm{\\mW/}$ $\\mathsf{m}^{2}$ , which constitutes a very promising indicative value. \n\nApart from the presently realizable diode array control approach, forthcoming nanonetwork technologies may also be considered as control agents in the future [11]. A nanonetwork comprises a network of wireless nano-sized electronic controllers, each with responsibility for one active meta-atom element. The controllers are able to exchange information in order to propagate switch configuration information within the tile. Nano-controllers are envisioned to be autonomic in terms of power supply. While still in its early stages, the nanonetwork approach promotes the seamless integration of control elements within a material, while it may also enable materials with embedded intelligence, able to tune their EM behavior in an autonomous fashion. \n\nThe Tile Gateway Layer: It specifies the hard ware (gateway) and protocols that enable the bidirectional communication between the controller network and the external world (e.g., the Internet), as well as the communication between tiles. This provides flexibility in the HyperSurface operation workflow, as follows. In general, multiple tiles are expected to be used as coating of large areas, as discussed earlier. Moreover, the tile hardware is intended to be inexpensive, favoring massive deployments. Based on these specifications, existing IoT platforms can constitute promising choices for tile gateways [1]. The sensing capabilities of existing IoT platforms may optionally facilitate the monitoring of the tile environment, such as the impinging wave power measurements, enabling the adaptive tuning of the tile functions [12]. \n\n![](images/c20e6698d1c02cc2ba3806e03a6c2b1989b37c74bd6a25765bc082990b48a1e9.jpg) \nFigure 3. The functional and physical architecture of a single HyperSurface tile. A desired and supported EM function is attained by a switch state configuration setup. Inter-tile and external communication is handled by standard gateway hardware. \n\nThe described interconnectivity approach can also be employed during the tile design phase for the automatic definition of the supported EM functions and their input parameter range. Since deriving the tile behavior via analysis is challenging in all but static meta-atom cases, an approach based on learning heuristics can also be employed instead [5]. According to it, an intended EM function is treated as an objective function, and subsequently the tile is checked for compliance via illumination by an external wave (input) and reflection/absorption measurements (output). A learning heuristic is then employed to detect iteratively the best switch configuration that optimizes the output of the objective function. Once detected, the best configuration is stored in a lookup table for any future use. It is noted that metasurfaces are generally not known to exhibit an inherent limitation regarding the EM functions that they can support. \n\n# Incorporation to Networking Infrastructure \n\nProgrammable wireless environments can be incorporated in existing network infrastructures without altering their workflow. Especially in the case of software-defined networks (SDNs) [1], the programmable environments can be clearly modeled as a set of software services, as shown in Fig. 4. SDN has gained significant momentum in the past years due to the clear separation it enforces between the network control logic and the underlying hardware. An SDN controller abstracts the hardware specifics (“southbound” direction) and presents a uniform programming interface (“northbound”) that allows the modeling of network functions as applications. \n\n![](images/ce2a21f973088596e72bde9eb620c47043011a466f1c212d87f711bc7bc0f9bd.jpg) \nFigure 4. Schematic of the programmable wireless environment incorporation principles to existing SDN infrastructures. \n\n![](images/dad17100aef6cf16729e3726a2669fa04816f17202efd4dfeb8c79997e94b24c.jpg) \nFigure 5. The wireless environment configuration process as a routing problem. The illustrated case corresponds to the scenario of Fig. 1. \n\nUsing the SDN paradigm, HyperSurface tiles can be considered as wave routing hardware. Notice that the tiles employ common IoT devices as gateways, whose communication protocols are mainstream and typically supported by SDN controllers. The custom environmental behavior to serve a set of users is calculated by a wireless environment configuration application. The application receives the device positions, the user objectives, and the global policies as inputs and calculates the fitting air paths. A control loop is established with existing device position discovery and access control SDN applications, constantly adapting to changes in the security policies and user device location updates. \n\n# Workflow of the \n\n# Environment Configuration Service \n\nA HyperSurface-coated environment can treat the EM wave propagation similar to the routing process in classic networking. Connecting two wireless devices becomes a problem of finding a route over HyperSurface tiles, while blocking access to a wireless device is achieved by absorbing or deflecting its EM emissions. An example is given in Fig. 5, which studies a possible EM routing configuration to serve the objectives of the scenario shown in Fig. 1. Software commands are combined and sent to the proper tile gateways, manipulating EM waves, steering, absorbing, and focusing them as needed. Finding the air routes that fulfill the objectives of multiple users can be treated as a network embedding problem. When an EM beam from a device impinges on, for example, a wall, the affected tiles can be seen as the user entry points in the graph of connectable tiles. The tile graph comprises a node for each tile, and a link between any two tiles can steer EM waves to each other. User objectives can be treated as air route requirements, for example, selecting the $K$ -shortest paths to connect the device entry points, using routes that avoid other users for increased security, and so on. These requirements can then be embedded to the tile graph using well-known techniques [13]. \n\nHaving described the tile configuration process as an embedding problem, we proceed to outline the total workflow of the configuration service. The service forms a continuous loop with device location discovery systems: it receives the updated locations of user devices and tunes the behavior of the wireless environment accordingly. It is noted that tiles can facilitate the device location discovery process [12]. The existing user access mechanisms of the network infrastructure are executed. If a device is deemed unauthorized, a “block” objective is formed for it. Authorized devices that are aware of the programmable environment can express their specific objectives by posting a request to the configuration service. Unaware devices are treated by global policies. The environment configuration service produces the matching air routes and proceeds to deploy them by sending corresponding EM manipulation commands to the tile gateways. The continuous control loop is established to adapt to localization errors or changes. It is noted that the configuration service may have control over the beam-forming capabilities of the infrastructure access points. The user device-side beam-forming adapts automatically by scanning and selecting the best beam direction automatically using the device’s standard process. \n\n# Evaluation \n\nIn this section, we present preliminary results to show the potential of HyperSurfaces in mitigating undesired path loss effects in a real-world wireless communication scenario. Specifically, we demonstrate the performance improvement with the focus and steer function implemented in a typical indoor environment. \n\nAs shown in Fig. 6, the indoor space shows a dimension of $15~\\mathrm{{\\dot{m}}}$ in length and $10\\mathrm{~m~}$ in width and a height of $3\\mathrm{~m~}$ . The room is divided by a middle wall (with a length of $12~\\mathrm{m}$ and a thickness of $1\\mathrm{~m~}$ ) into two sections (i.e., line-of-sight and non-line-of-sight sections, respectively), each with a width of $4.5~\\mathrm{m}$ . All walls are coated with HyperSurface tiles with a size of $1\\times1\\mathrm{~m~}$ . An EM transmitter, with a height of $2\\textrm{m}$ as shown in red in Fig. 6, is located on one side of the room and equipped with a half-dipole antenna and transmits at $60\\mathrm{\\GH}z$ with $25~M H z$ bandwidth. The transmission power is set to 100 dBm. In total 12 receivers (shown in blue in Fig. 6) are uniformly distributed on the non-line-of-sight side of the room with the same height of $1.5\\mathrm{~m~}$ and half-dipole antennas. \n\nThe evaluation is performed on a three-dimensional dynamic ray-tracer developed for map-based channel modeling [14], specifically customized to implement the focus and steer functionalities. This map-based ray-tracer is built based on 3D channel models in both microwave and mmWave frequency bands and is validated against field measurements. The implemented functions are designed to be applicable to any receiver position, in either the line-of-sight (right room) or non-line-of-sight (left room) section. In the simulated scenario, the functions are applied to maximize the minimum received power over the 12 receivers in the non-line-of-sight area. \n\n![](images/b87532e1c1ab880d49ed59d5e7553b2af0c29be48358dd13aef8654153cdfd77.jpg) \nFigure 6. Simulation results for wireless environment optimization study at 60 GHz. The baseline non-HyperSurface setup (top) shows poor coverage. The use of HyperSurfaces (middle) shows significantly improved signal coverage and received power overall. An illustration of the deployed focus and steer functions is shown at the bottom. \n\nThe baseline scenario, as shown in Fig. 6 (top), shows a plain setup where the norms of \n\nThe HyperSurface concept is applicable to any frequency spectrum and wireless architecture. Therefore, solving the corresponding path loss, fading, interference, and non-line-of-sight problems in general using HyperSurfaces constitutes a promising research path. Such directions can further focus on indoor and outdoor communication environments. \n\ntiles are naturally perpendicular to the tile surfaces without any HyperSurface functionality activated. The average received power over the 12 receivers is $-75\\mathrm{\\dBm}$ , while the minimum power is $-250$ dBm and is below the threshold allowed by the ray-tracer, implying disconnected areas. The receivers in the upper right and bottom left corners are not covered in this setup. In comparison, with the HyperSurfaces enabled, as shown in Fig. 6 (middle), all receivers are in good coverage with the obvious leverage of an average received power of 20.6 dBm. Also, there are maximum and minimum received powers of 32.5 dBm and 12.4 dBm, respectively. \n\nThe work principle of tuning the HyperSurface tiles in the example is the following: we begin with the most distant receiver (top right position) and assign focus and steer commands to the tiles that offer the shortest air route. The used tiles are marked and are not used again for other receivers. We note that this is a simplification, as metasurfaces can achieve beam splitting functionalities [5]. Thus, in reality, a single tile could be tuned to affect more than one user. The process is repeated for the rest of the users. In the context of the studied static scenario, the number of tiles to be used for each user is deduced by a generic optimizer [15], which seeks to maximize the minimum received power over all receivers. As discussed below, however, real-time operation is expected to require specialized optimization processes. Figure 6 (bottom) provides an example of a single focus and steer function deployment. The tiles with green paths, impinged upon, will adjust their azimuth and elevation angles to focus the signals from transmitter to desired receiver. \n\n# Challenges and Research Directions \n\nFurther research in programmable wireless environments can target the tile architecture and the inter-tile networking, the tile control software, and many applications such as mmWave, device-todevice, and fifth generation (5G) systems. \n\nRegarding the tile architecture, the optimization of the dynamic meta-atom design constitutes a notable goal toward maximizing the supported function range of a tile. Ultra-wideband meta-atom designs able to interact concurrently with a wide variety of frequencies (e.g., from 1 to 60 GHz) constitute a notable research goal [7]. Formal tile sounding procedures need to be defined, that is, simulation-based and experimental processes for measuring the supported functions and parameters per tile design. Additionally, the tile reconfiguration speed needs to be studied in order to yield the adaptivity bounds of the programmable environments. In this sense, inter-tile networking protocols need to be designed to offer fast, energy-efficient wireless environment reconfiguration, supporting a wide range of user mobility patterns. Adaptation to user mobility can also target the mitigation of Doppler shift effects. \n\nThe HyperSurface control software needs to be optimized regarding its complexity, modularity, and interfacing capabilities. Low-complexity, fast configuration optimizers can increase the environment’s maximum adaptation speed. Toward this end, both analysis-based and heuristic optimization processes need to be studied. Additionally, following the network functions virtualization paradigm [1], the various described and evaluated optimization objectives can be expressed in a modular form, allowing their reuse and combination. For example, the tiles may be configured to maximize the minimum received power within a room, subject to delay spread restrictions. Well-defined tile software interfaces can allow for close collaboration with user devices and external systems. For instance, the power delay profile toward a user can be matched to the MIMO arrangement of his/her device. It is noted that such joint optimization can be aligned to the envisioned 5G objectives of ultra-low latency, high bandwidth, and support for massive numbers of devices within an environment [1]. \n\nWe note that the HyperSurface concept is applicable to any frequency spectrum and wireless architecture. Therefore, solving the corresponding path loss, fading, interference, and non-line-of-sight problems in general using HyperSurfaces constitute promising research paths. Such directions can further focus on indoor and outdoor communication environments. In indoor settings, the HyperSurface tiles can cover large parts of the wireless environment, such as walls, ceilings, furniture, and other objects, and offer more precise control over electromagnetic waves. In outdoor settings, the HyperSurface tiles can be placed on key points, such as building facades, highway polls, and advertising panels, and utilized to boost the communication efficiency. In both settings (i.e., indoor and outdoor), the automatic tile location and orientation discovery can promote the ease of deployment toward “plug-and-play” levels. Moreover, the joint optimization of antenna beam-forming and tile configurations need to be studied to achieve the maximum performance. \n\nStudying the use of HyperSurfaces in mmWave systems, 5G systems, and THz communications is of particular interest. For example, mmWave and THz systems are severely limited in terms of very short distances and line-of-sight scenarios. The HyperSurfaces can mitigate the acute path loss by enforcing the lens effect and any custom reflection angle per tile, avoiding the ambient dispersal of energy and non-line-of-sight effects, extending the effective communication range. Dynamic meta-atoms that can interact with THz modulated waves need to be designed. This has been shown to be possible for graphene-based metasurfaces [8]. The tile sensing accuracy and re-configuration speed must also match the extremely high spatial sensitivity of THz communications, calling for novel, highly distributed tile control processes. Optical tile internetworking is another approach to ensure that the tile adaptation service is fast enough for the THz communication needs. \n\nFinally, the control of EM waves via HyperSurfaces can find applications beyond classic communications. EM interference constitutes a common problem in highly sensitive hardware, such as medical imaging and radar technology. In these cases, the internals of, for example, a medical device can be treated as an EM environment, with the objective of cancelling the interference to the imaging component caused by unwanted internal EM scattering. Such interference can be mitigated only up to a degree during the design of the equipment. Common discrepancies that occur during manufacturing can give rise to unpredictable interference, resulting in reduced equipment performance. However, assuming HyperSurface-coated device internals, interference can be mitigated, or even negated, after the device manufacturing via simple software commands. \n\n# Conclusion \n\nThe present study introduces software control over the electromagnetic behavior of a wireless environment. The methodology consists of coating size-able objects, such as walls, with HyperSurface tiles, a novel class of planar materials that can interact with impinging waves in a programmable manner. Interaction examples include wave absorbing and steering toward custom directions. The tiles are networked and controlled by an external service, which defines and deploys a configuration that benefits the end users. Notable applications are the mitigation of propagation loss and multi-path fading effects in virtually any wireless communication system, including mmWave and THz setups. The study defines the HyperSurface tile architecture and the structure of the programmable wireless environments that incorporate them. Evaluation via simulations demonstrates the exceptional potential of this novel concept. \n\n# Acknowledgment \n\nThis work was partially funded by the European Union via the Horizon 2020: Future Emerging Topics call (FETOPEN), grant EU736876, project VISORSURF (http://www.visorsurf.eu). \n\n# References \n\n[1] I. F. Akyildiz et al., “5G Roadmap: 10 Key Enabling Technologies,” Computer Networks, vol. 106, 2016, pp. 17–48. \n[2] Y. Kim et al., “Full Dimension Mimo (FD-MIMO): The Next Evolution of MIMO in LTE Systems,” IEEE Wireless Commun., vol. 21, no. 2, 2014, pp. 26–33. \n[3] S. Han and K. G. Shin, “Enhancing Wireless Performance Using Reflectors,” Proc. IEEE INFOCOM 2017, pp. 1–9. \n[4] X. Tan et al., “Increasing Indoor Spectrum Sharing Capacity Using Smart Reflect-Array,” Proc. 2016 IEEE ICC, 2016, pp. 1–6. \n[5] H. Yang et al., “A Programmable Metasurface with Dynamic Polarization, Scattering and Focusing Control,” Scientific Reports, vol. 6, 2016, p. 35692. \n[6] The VISORSURF Project, “A Hardware Platform for Software-Driven Functional Metasurfaces,” Horizon 2020 Future Emerging Technologies; http://visorsurf.eu, accessed Jan. 15, 2018. \n[7] J. Su et al., “Ultrawideband, Wide Angle and Polarization-Insensitive Specular Reflection Reduction by Metasurface Based on Parameter-Adjustable Meta-Atoms,” Scientific Reports, vol. 7, 2017, p. 42283. \n[8] S. H. Lee et al., “Switching Terahertz Waves with Gate-Controlled Active Graphene Metamaterials,” Nature Materials, vol. 11, no. 11, 2012, pp. 936–41. \n[9] M. Caironi, Large Area and Flexible Electronics, Wiley, 2015. \n[10] T. Sekitani et al., “Stretchable Active-Matrix Organic Light-Emitting Diode Display Using Printable Elastic Conductors,” Nature Materials, vol. 8, no. 6, 2009, pp. 494–99. \n[11] C. Liaskos et al., “Design and Development of Software Defined Metamaterials for Nanonetworks,” IEEE Circuits and Systems Mag., vol. 15, no. 4, 2015, pp. 12–25. \n[12] A. Tsioliaridou et al., “A Novel Protocol for Network-Controlled Metasurfaces,” Proc. ACM NANOCOM ’17, ser. NanoCom ’17, 2017, pp. 3:1–6. \n[13] A. Fischer et al., “Virtual Network Embedding: A Survey,” IEEE Commun. Surveys & Tutorials, vol. 15, no. 4, 2013, pp. 1888–1906. \n[14] I. F. Akyildiz and S. Nie, “TeraRays: The 3D Channel Simulation Platform for 5G and Beyond,” 2016; http://bwn. ece.gatech.edu/projects/terarays/index.html, accessed Jan. 23, 2018 \n[15] M. Laguna and R. Marti, “The Optquest Callable Library,” Optimization Software Class Libraries, Springer, 2003, pp. 193–218. \n\n# Biographies \n\nChristos Liaskos received his Diploma in electrical engineering from Aristotle University of Thessaloniki (AUTH), Greece, in 2004, his M.Sc. degree in medical informatics in 2008 from the Medical School, AUTH, and his Ph.D. degree in computer networking from the Department of Informatics, AUTH in 2014. He is currently a researcher at the Foundation of Research and Technology, Hellas (FORTH). His research interests include computer networks, traffic engineering and novel control schemes for wireless communications. \n\nShuai Nie received her B.S. degree in electrical engineering from Xidian University in 2012 and her M.S. degree in electrical engineering from New York University in 2014. Currently, she is working toward a Ph.D. degree at Georgia Institute of Technology under the supervision of Prof. Ian F. Akyildiz. Her research interests include the 5G wireless system and terahertz band communication networks. \n\nAgeliki Tsioliaridou received her Diploma and Ph.D. degrees in electrical and computer engineering from the Democritus University of Thrace, Greece, in 2004 and 2010, respectively. Her research interests lie in the area of nanonetworks, with specific focus on architecture, protocols, and security/authorization issues. She has contributed to a number of EU, ESA, and national research projects. She is currently a researcher at FORTH. \n\nAndreas Pitsillides is a professor in the Department of Computer Science, University of Cyprus, and heads the Networks Research Laboratory. He holds a visiting professorship at the University of Witwatersrand (Wits) and previously at the University of Johannesburg. His research interests include communication networks, the Internet and Web of Things, smart spaces, and nanonetworking. He has published over 270 referred papers in flagship journals (e.g., IEEE, Elsevier, IFAC, Springer), international conferences, and books. \n\nSotiris Ioannidis received a B.Sc. degree in mathematics and an M.Sc. degree in computer science from the University of Crete in 1994 and 1996, respectively. In 1998 he received an M.Sc. degree in computer science from the University of Rochester. He received his Ph.D. from the University of Pennsylvania (2005). His research interests are in the area of systems and security. He has authored more than 100 publications in international conferences, journals, and book chapters. \n\nCommon discrepancies that occur during manufacturing can give rise to unpredictable interference, resulting into reduced equipment performance. However, assuming HyperSurface-coated device internals, interference can be mitigated, or even negated, after the device manufacturing, via simple software commands. \n\nIan F. Akyildiz [F] received his B.Sc., M.Sc., and Ph.D. degrees in computer engineering from the University of Erlangen-Nuremberg, Germany, in 1978, 1981, and 1984, respectively. He is the Ken Byers Distinguished Chair Professor with the School of Electrical and Computer Engineering, Georgia Institute of Technology. He is an ACM Fellow and has received numerous awards from both organizations. His work has attracted more than 96,000 citations. " + }, + { + "id": "10.1038_s41467-017-02529-6", + "DOI": "10.1038/s41467-017-02529-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-017-02529-6", + "Relative Dir Path": "mds/10.1038_s41467-017-02529-6", + "Article Title": "MXene molecular sieving membranes for highly efficient gas separation", + "Authors": "Ding, L; Wei, YY; Li, LB; Zhang, T; Wang, HH; Xue, J; Ding, LX; Wang, SQ; Caro, J; Gogotsi, Y", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Molecular sieving membranes with sufficient and uniform nullochannels that break the permeability-selectivity trade-off are desirable for energy-efficient gas separation, and the arising two-dimensional (2D) materials provide new routes for membrane development. However, for 2D lamellar membranes, disordered interlayer nullochannels for mass transport are usually formed between randomly stacked neighboring nullosheets, which is obstructive for highly efficient separation. Therefore, manufacturing lamellar membranes with highly ordered nullochannel structures for fast and precise molecular sieving is still challenging. Here, we report on lamellar stacked MXene membranes with aligned and regular subnullometer channels, taking advantage of the abundant surface-terminating groups on the MXene nullosheets, which exhibit excellent gas separation performance with H-2 permeability > 2200 Barrer and H-2/CO2 selectivity > 160, superior to the state-of-the-art membranes. The results of molecular dynamics simulations quantitatively support the experiments, confirming the subnullometer interlayer spacing between the neighboring MXene nullosheets as molecular sieving channels for gas separation.", + "Times Cited, WoS Core": 895, + "Times Cited, All Databases": 938, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000419947200002", + "Markdown": "# MXene molecular sieving membranes for highly efficient gas separation \n\nLi Ding1, Yanying Wei1, Libo Li1, Tao Zhang1, Haihui Wang $\\textcircled{6}$ 1, Jian Xue1,2, Liang-Xin Ding1, Suqing Wang1, Jürgen Caro2 & Yury Gogotsi 3,4 \n\nMolecular sieving membranes with sufficient and uniform nanochannels that break the permeability-selectivity trade-off are desirable for energy-efficient gas separation, and the arising two-dimensional (2D) materials provide new routes for membrane development. However, for 2D lamellar membranes, disordered interlayer nanochannels for mass transport are usually formed between randomly stacked neighboring nanosheets, which is obstructive for highly efficient separation. Therefore, manufacturing lamellar membranes with highly ordered nanochannel structures for fast and precise molecular sieving is still challenging. Here, we report on lamellar stacked MXene membranes with aligned and regular subnanometer channels, taking advantage of the abundant surface-terminating groups on the MXene nanosheets, which exhibit excellent gas separation performance with ${\\sf H}_{2}$ permeability $>2200$ Barrer and ${\\sf H}_{2}/{\\sf C}{\\sf O}_{2}$ selectivity $>160$ , superior to the state-of-the-art membranes. The results of molecular dynamics simulations quantitatively support the experiments, confirming the subnanometer interlayer spacing between the neighboring MXene nanosheets as molecular sieving channels for gas separation. \n\nas separation with membrane technology is attractive because of its high efficiency, low energy consumption, and simple operation1–3. Membranes with high permeability and high selectivity are urgently required3. The recent use of two-dimensional (2D) materials4,5, such as graphene and graphene oxide $(\\mathrm{GO})^{6-13}$ , zeolite or metal–organic framework (MOF) nanosheets14–16, has led to innovative membrane designs. Previous studies have shown that MOF nanosheets are promising for membrane assembly15,16 and a pioneering breakthrough work on zeolite nanosheets based membrane was also conducted by Tsapatsis14,17–19, where the molecules were mainly transported through the intrinsic pores in the 2D nanosheets. But the types of zeolite or MOFs that can be easily exfoliated are rather limited due to the structural deterioration in exfoliation process15,16. Similarly, the monolayer graphene with artificial sub-nanopores created by selective etching or ion bombardment is emerged as selective membrane for gas separation or ion sieving20–22. However, it is difficult to fabricate the graphene sheets with controllable and uniform pores due to the stochastic nature, which limits the industrial applications. In contrast to the membranes with intrinsic or artificial pores on the nanosheets as the main molecular sieving channels, another kind of 2D laminar membrane has attracted increasing attention due to its simple preparation and easy to large-scale fabrication, in which the molecules are transported and sieved through the interlayer nanochannels between the neighboring nanosheets6–8,23. Therefore, for the latter 2D laminar membranes, the stacking structure of the nanosheets strongly affects the separation performance6–8. For instance, a GO membrane with randomly stacked structure exhibited only Knudsen diffusion during gas separation, while a membrane with an ordered structure exhibited molecular sieving with a greatly increased gas separation factor6. Moreover, many other well-ordered GO laminates exhibited enhanced gas or water separation performance in terms of their selectivity and permeability compared to the disordered ones7,8. However, since the oxygen-containing functional groups that decorate the defects in GO sheets are difficult to control, random laminar structures are easily formed when such sheets are stacked into membranes7,8. Another young family of 2D materials named “MXenes” with the formula of $\\begin{array}{r}{{\\bf M}_{n+1}\\mathrm{X}_{n}\\mathrm{T}_{\\mathrm{X}},}\\end{array}$ are usually produced by selectively etching the A-group (mainly group IIIA or IVA elements) layers from $\\mathbf{M}_{n}$ $\\phantom{}_{+1}\\mathrm{AX}_{n}$ phases ${\\mathit{n}}=1,2 $ or 3), where M is an early transition metal and X is carbon and/or nitrogen. More importantly, abundant of surface-terminating groups $(\\mathrm{\\bar{T}}_{\\mathrm{X}}{:=}\\mathrm{0}$ , $-\\mathrm{OH}$ and $\\mathrm{-F}.$ ) are formed evenly on the entire surface of the nanosheets during the etching and delaminating processes24–31. Interestingly, the variety of $\\mathrm{T_{X}}$ species can create open narrow nanochannels between the neighboring nanosheets in stacked MXene laminates, making MXene a promising material to assemble highly efficient membranes27. \n\nHere, exfoliated MXene nanosheets were used as building blocks to construct 2D laminated membranes for selective gas separation for the first time, as demonstrated using a model system of $\\mathrm{H}_{2}$ and $\\mathrm{CO}_{2}$ . The MXene membranes exhibit excellent performance in terms of the hydrogen permeability and $\\mathrm{H}_{2}/\\mathrm{CO}_{2}$ selectivity, transcending the state-of-the-art membranes. Such highpermeability hydrogen-selective membranes are desired in many fields, such as hydrogen production and carbon dioxide capture. \n\n# Results \n\nPreparation of MXene nanosheets. The most common MXene, ${\\mathrm{Ti}_{3}}{\\mathrm{C}_{2}}{\\mathrm{T}_{\\mathrm{X}}},$ is obtained after selectively etching Al from the corresponding MAX $(\\mathrm{Ti}_{3}\\mathrm{AlC}_{2})$ phase using hydrochloric acid and lithium fluoride24–26,29, the structures are displayed in Supplementary Fig. 1 and explained in Supplementary Note 1. \n\nThe Tyndall scattering effect in the as-prepared MXene colloidal suspension is clearly observed (Fig. 1a, inset, Supplementary Fig. 2, and Supplementary Note 2). The scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images (Fig. 1a and Supplementary Fig. 3) show that the exfoliated MXene nanosheets are very thin and nearly transparent to the electron beams. High-resolution TEM (HRTEM) image and selected-area electron diffraction (SAED) patterns (Fig. 1b and Supplementary Figs. 4 and 5) indicate the hexagonal structure of the basal planes and high crystallinity of the MXene flakes without obvious nanometer-scale defects or carbide amorphization. As indicated from the atomic force microscopy (AFM) measurements (Fig. 1c and Supplementary Fig. 6), most of the MXene nanosheets have a uniform thickness of $1.5\\mathrm{nm}$ with a lateral size of $1{-}2\\upmu\\mathrm{m}$ . Considering that the theoretical thickness of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{X}}$ single layer is ${\\sim}1\\mathrm{nm}^{29,32}$ , and MXene nanosheets adsorb water and other molecules that also contribute to the total thickness, the $1.5\\mathrm{-nm}$ -thick nanosheet should be monolayer Ti3C2TX26,32. \n\nPreparation of 2D MXene membranes. The MXene membranes were fabricated using vacuum-assisted filtration on anodic aluminum oxide (AAO) support (Fig. 1a and Supplementary Fig. 7). After detaching the MXene layers from the substrate, freestanding MXene membranes were directly obtained with good flexibility (Fig. 1e and Supplementary Figs. 8 and 9). From the top-view SEM and AFM images (Fig. 1d and Supplementary Fig. 10), the membrane is determined to be intact, and the terminating groups were also detected on the MXene membrane (see Supplementary Figs. 11–17 and Supplementary Tables 1–3 for the Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), energy dispersive X-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS) results). The cross-sectional SEM image and elemental distribution (Fig. 1e and Supplementary Figs. 13–15) indicate a homogeneous laminar structure throughout the membrane. The crosssectional TEM images (Fig. 1f and Supplementary Fig. 18) reveal well-organized, highly ordered subnanometer channels resulting from the evenly distributed terminating groups on the MXene nanosheet surface30,33,34. The sharp (002) peak with high intensity in the powder X-ray diffraction (XRD, Fig. 1g) results further confirms the ordered stacking in the MXene membrane. The (002) peak at $2\\theta=6.6^{\\circ}$ indicates the $d$ -spacing of ${\\sim}1.35\\mathrm{nm}$ , based on Bragg’s law (Supplementary Fig. 19, Supplementary Note 3, and Supplementary Equation (2)). After deducting the monolayer thickness of $\\sim1\\ \\mathrm{nm}^{29,32}$ , the free spacing between the neighboring MXene nanosheets is estimated to be ${\\sim}0.35\\mathrm{nm}$ (Fig. 1h), which could serve as a molecular sieve to separate gases by membrane permeation. \n\nGas separation performance of 2D MXene membranes. The MXene membranes were sealed into Wicke–Kallenbach permeation cells to measure the gas separation performance (Supplementary Figs. 20 and 21). For our MXene membrane, the permeability of the small gas molecules (2164 Barrer for He and 2402 Barrer for $\\mathrm{H}_{2}$ ) is much higher than that of the gases with bigger kinetic diameters (Fig. 2a and Supplementary Table 4), showing a clear cutoff in between. The ideal selectivity (238.4) of the single-gas permeation and the separation factor (166.6) of the mixed-gas permeation of $\\mathrm{H}_{2}/\\mathrm{CO}_{2}$ are much higher than the corresponding Knudsen coefficient (4.7). Obviously, the gas permeation is mainly dominated by the gas kinetic diameter rather than its molecular weight (Fig. 2a and Supplementary Fig. 22), known as the molecular sieving (size exclusion) mechanism. Very interestingly, the permeability of $\\mathrm{CO}_{2}$ (10 \n\n![](images/8de43d2521d69f3c649b0e4db102482467519f36abbd94cf2417a99da54bb23c.jpg) \nFig. 1 Morphology and structure of exfoliated MXene $(\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\mathsf{X}})$ nanosheets and stacked MXene membrane. a SEM image of the delaminated MXene nanosheets on porous anodic aluminum oxide (AAO) (scale bar, $1\\upmu\\mathrm{m}\\mathrm{;}$ . Inset is the Tyndall scattering effect in MXene colloidal solution in water. b HRTEM image of the MXene nanosheet with SAED pattern in the inset (scale bar, $5\\mathsf{n m}$ inset b, $5\\mathsf{n m}^{-1},$ ). c AFM image of the MXene nanosheet on cleaved mica. The height profile of the nanosheet corresponds to the blue dashed line (scale bar, $500\\mathsf{n m}$ ). Note that the adsorbed molecules, such as ${\\mathsf{H}}_{2}{\\mathsf{O}},$ also contribute the detected thickness of $1.5\\mathsf{n m}$ . d SEM image of the MXene membrane surface (scale bar, $500\\mathsf{n m}.$ ). Inset is a photograph of a MXene membrane. e Cross-sectional SEM image of the MXene membrane (scale bar, $1\\upmu\\mathrm{m})$ . Inset is a tweezer bent membrane. f Cross-sectional TEM image of the MXene membrane with 2D channels (scale bar, $10\\mathsf{n m},$ . $\\mathbf{g}\\times\\mathsf{R D}$ patterns of the MAX $(\\mathsf{T i}_{3}\\mathsf{A l C}_{2})$ powder and MXene $(\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\mathsf{X}})$ membrane with inset of the magnified XRD pattern at low Bragg angles. h Illustration of the spacing between the neighboring MXene nanosheets in the membrane \n\nBarrer) is approximately half of $\\Nu_{2}$ (19 Barrer), although its kinetic diameter $(0.33\\mathrm{nm})$ is $9\\%$ smaller than that of $\\Nu_{2}$ (0.364 nm). Here, adsorption modifies the molecular sieving process. Because $\\mathrm{CO}_{2}$ has a much larger quadrupole moment than $\\Nu_{2}$ , it interacts with the MXene membrane stronger (the interaction energy values of MXene with $\\mathrm{CO}_{2}$ and ${\\mathrm{N}}_{2}.$ , as calculated by molecular dynamics (MD) simulations, are $-175.1$ and $-97.5\\mathrm{k}\\dot{\\mathrm{J}}$ $\\mathrm{mol^{-1}}$ , respectively, see Supplementary Note 4 and 5), which considerably suppress the $\\mathrm{CO}_{2}$ diffusion in the MXene subnanometer channels6,7. The adsorption isotherms of the gases on the MXene membranes at $25^{\\circ}\\mathrm{C}$ also indicate a preferential adsorption of $\\mathrm{CO}_{2}$ compared to $\\mathrm{N}_{2}$ or other gases (Supplementary Fig. 23), even though the adsorption capacities of the MXene nanosheets are quite small15,16,35. The adsorbed $\\mathrm{CO}_{2}$ molecules in the subnanochannels can even block the passing molecules and increase the resistance to $\\mathrm{CO}_{2}$ diffusion, while such phenomenon is absent for $\\mathrm{H}_{2}$ , resulting a high separation factor of $\\mathrm{\\tilde{{H}}}_{2}/\\mathrm{CO}_{2}$ . For $\\mathrm{O}_{2}$ , its kinetic diameter $(0.346\\mathrm{nm})$ is just slightly smaller than the interlayer spacing of the MXene membrane $(0.35\\mathrm{nm})$ . Although $\\mathrm{O}_{2}$ can pass through the subnanochannels in the membrane, but with a much larger mass transfer resistance due to the confinement of the neighboring MXene nanosheets. That is why the $\\mathrm{O}_{2}$ permeability is significantly lower than that of much smaller molecules, such as He and $\\mathrm{H}_{2}$ . \n\nGas separation mechanism. To elucidate the gas separation mechanism, two sets of atomistic MD simulations (total simulation time $>5\\upmu\\mathrm{s})$ were performed to study the gas transport through the MXene membrane, as schematically shown in Supplementary Fig. $24^{16,36}$ . First, the confined diffusion coefficients of He, $\\mathrm{H}_{2}$ , $\\mathrm{CO}_{2}\\mathrm{:}$ $\\mathrm{O}_{2}$ , $\\mathrm{N}_{2}\\mathrm{:}$ , and $\\mathrm{CH}_{4}$ in two neighboring MXene channels with $0.35\\mathrm{nm}$ free spacing were calculated by MD simulations (Supplementary Fig. 25 and Supplementary Note 4)37. The simulation yields a diffusivity ratio of 175:238:1.0:4.1:1.4:0.1. Furthermore, hundreds-nanosecond (ns)-long MD simulations were carried out to study the passage of the gas molecules through the MXene membrane16,36. In simulations of single-gas permeation (Fig. 2b, c, Supplementary Fig. 26, and Supplementary Note 5), the fluxes of $\\mathrm{H}_{2}$ , $\\mathrm{CO}_{2}$ , $\\mathrm{O}_{2}$ , and $\\Nu_{2}$ transporting from the feed to permeate chamber are 0.75, 0.0038, 0.0071, and 0.0063 molecule $\\mathrm{n}s^{-1}$ , respectively (each value are estimated from the average of four 200-ns-long MD simulations, except for the $\\mathrm{H}_{2}$ flux) (Supplementary Table 5). The simulated selectivities of $\\mathrm{H}_{2}/$ $\\mathrm{CO}_{2}$ (200) and $\\mathrm{H}_{2}/\\mathrm{N}_{2}$ (120) are comparable to their respective experimental values of 238 and 129 (Fig. 2b). From the mixed-gas separation simulations (Fig. 2d), the selectivities of $\\mathrm{H}_{2}/\\mathrm{CO}_{2}$ (162) and $\\mathrm{H}_{2}/\\mathrm{N}_{2}$ (90), averaged from four 300-ns-long MD simulations, are close to the corresponding experimental selectivities of 167 and 78 (Fig. 2b and Supplementary Table 6). Both the MD simulations and experiments show that the gas molecules with sizes much smaller than the free spacing between the neighboring nanosheets (e.g., $\\mathrm{H}_{2}$ and He) move through the membrane quickly. By contrast, the gas molecules with sizes larger (or only slightly smaller) than the free spacing $(\\mathrm{O}_{2},\\mathrm{N}_{2},$ and $\\mathrm{CH}_{4}$ ) move 100 times slower because of the molecular sieving mechanism, resulting in gas separation selectivity above 100. For the gas molecule with specific adsorptive property, such as $\\mathrm{CO}_{2}.$ , its interaction with MXene considerably affects the gas transport rate, which further increases the $\\mathrm{H}_{2}/\\mathrm{CO}_{2}$ selectivity. The quantitative agreement between the MD simulations and experiments indicates that molecular sieving occurs during gas separation through the MXene membrane. Generally, terminations on the surface of a 2D membrane may affect the separation performance in some cases, therefore, another model using $-\\mathrm{F}$ termination (i.e., $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{F}_{2},$ has also been built to investigate the effect of different terminations on the MD simulated gas permeation (Supplementary Table 7, Supplementary Fig. 27, and Supplementary Note 6). The results show that there is no significant difference between the gas permeation in two simulation systems. \n\n![](images/e14d9734e5c5821487d85045d3c71d7e2fe54632b4ca5ae39b539b74b3b0d616.jpg) \nFig. 2 MD simulations of the gas permeation through the MXene membrane compared with the experimental results. a Single-gas permeabilities through a $2-\\upmu\\mathrm{m}$ -thick MXene membrane as a function of the gas kinetic diameter at $25^{\\circ}\\mathsf{C}$ and 1 bar. Inset shows the selectivity of ${\\sf H}_{2}$ relative to the other gases in both the single-gas and equimolar mixed-gas permeation studies. b Comparison of the experimental and MD simulated selectivities of ${\\sf H}_{2}/{\\sf C}{\\sf O}_{2}$ and $H_{2}/N_{2}$ in both the single-gas and mixed-gas permeations. c The number of gas molecules that passed through the MXene membrane in MD simulation as a function of simulation time for single-gas permeation. For $\\mathsf{H}_{2},$ only the first 10 ns of the simulation are shown because of its fast permeation. By contrast, only two molecules pass through the MXene membrane during the 200-ns-long simulation for ${\\mathsf{C O}}_{2}$ or ${\\sf N}_{2}$ . The ${\\mathsf{C O}}_{2}$ curve fluctuates because of ${\\mathsf{C O}}_{2}$ adsorption–desorption on the MXene membrane. d Simulation snapshots at 0, 30, 100, and 300 ns for two sets of mixed-gas permeation systems: $(\\mathsf{H}_{2}+$ $C O_{2})$ and $(\\mathsf{H}_{2}+\\mathsf{N}_{2})$ . Note that ${\\sf H}_{2}$ was modeled by united-atom force field. The MXene membrane was composed of two nanosheets with a free spacing of $0.35{\\mathsf{n m}}$ located in the middle of the simulation system. In the beginning $\\mathit{\\Psi}_{:t=0}$ ns), $30\\mathsf{H}_{2}$ and $30\\mathsf{C O}_{2}$ (or ${\\sf N}_{2})$ molecules were present in the feed chamber, which permeated through the MXene membrane to the evacuated permeate chamber. The details can be found in section of “Methods” \n\n# Discussion \n\nMoreover, the gas separation performance of the MXene membranes can be optimized by adjusting the membrane thickness, temperature, feeding $\\mathrm{H}_{2}$ concentration, and feed gas pressure (Fig. 3a, b, Supplementary Figs. 28–33, and Supplementary Note 7). The MXene membrane shows stable performance during a $700\\mathrm{{h}}$ continuous separation of $\\mathrm{H}_{2}/\\mathrm{CO}_{2}$ mixture (Fig. 3c). No deterioration was observed even when the feed gas contained 3 $\\mathbf{vol\\%}$ steam (Supplementary Fig. 34). And the MXene membranes also show good reproducibility (Supplementary Table 8). Further, the $2\\cdot\\upmu\\mathrm{m}$ -thick MXene membrane also exhibits tensile strength above $50\\mathrm{MPa}$ and Young’s modulus of $3.8\\mathrm{GPa}$ , showing good mechanical properties (Supplementary Fig. 35 and Supplementary Note 8). Compared with various previously reported membranes (Fig. 3d, Supplementary Table 9, and Supplementary Note 9), the MXene membrane exhibits both great $\\mathrm{H}_{2}$ permeability ${\\tt>}2200\\$ Barrer) and high $\\mathrm{H}_{2}/\\mathrm{CO}_{2}$ selectivity $\\left(>160\\right)$ , which considerably exceeds the latest upper bound of most current membranes. This promising separation performance is attributed to the regular subnanometer channels in the stacked MXene membrane, and the pivotal role of the regular structure in separation have also been further verified using MD simulation (Supplementary Note 6). \n\n![](images/82389ad4ed470957b596519dbe751e88302bb7ba266d865907010f6249b4fa38.jpg) \nFig. 3 Gas separation performance of the MXene membrane. a Single-gas permeabilities through the MXene membranes with different thicknesses at $25^{\\circ}$ C and 1 bar. b ${\\sf H}_{2}/{\\sf C}{\\sf O}_{2}$ separation performance of a $2-\\upmu\\mathrm{m}$ -thick MXene membrane as a function of temperature in the equimolar mixed-gas permeation. c Long-term separation of equimolar ${\\sf H}_{2}/{\\sf C}{\\sf O}_{2}$ mixture through a $2-\\upmu\\mathrm{m}$ -thick MXene membrane at $25^{\\circ}\\mathsf{C}$ and 1 bar. d ${\\sf H}_{2}/{\\sf C}{\\sf O}_{2}$ separation performance of the MXene membrane compared with state-of-the-art gas separation membranes. The black line indicates the Robeson 2008 upper bound of polymeric membranes for ${\\sf H}_{2}/{\\sf C}{\\sf O}_{2}$ separation58, and the orange dashed line represents the 2017 upper bound of the best current membranes for ${\\sf H}_{2}/{\\sf C}{\\sf O}_{2}$ separation. Information on the data points is given in Supplementary Table 9 \n\nThe 2D structure and tunable physicochemical properties of MXene offer an exciting opportunity to develop a new class of molecular sieving membranes. Considering that more than 30 MXenes are already available30 and dozens more can be produced, there is certainly plenty of room for improving the performance even further. This work is significant for gas separation, such as $\\mathrm{H}_{2}$ purification, e.g., in methanol reforming process, $\\mathrm{CO}_{2}$ capture for zero-emission fossil fuel power generation, $\\mathrm{H}_{2}$ recovery in ammonia production, etc. Furthermore, it also demonstrates a general concept for 2D membrane design with highly ordered nanochannels enabling fast and precise molecular sieving for mixture separation. \n\n# Methods \n\nPreparation of the MXene membranes. The MXene solution was synthesized as follows29: one gram of LiF (purchased from Aladdin) was dissolved in $20\\mathrm{ml}$ HCl ( $\\begin{array}{r}{{6}\\mathbf{M},}\\end{array}$ purchased from Sinopharm Chemical Reagent Co., Ltd.,) solution in a $250\\mathrm{ml}$ Teflon beaker. Then, $\\mathrm{1g\\Ti_{3}A l C_{2}}$ (purchased from Beijing Jinhezhi Materials Co., Ltd.) was added to the solution with magnetic stirring at $35^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . The resulting product was washed using deionized (DI) water and centrifugated at $3500\\mathrm{rpm}$ several times until the $\\mathrm{\\pH}$ of the supernatant ${>}6,$ , and a clay-like sediment was obtained. The sediment was then dispersed in DI water with ultrasonication for $10\\mathrm{min}$ in order to delaminate the MXene flakes. Most of the unexfoliated MXene was removed after centrifugation at $3500\\mathrm{rpm}$ for $^{\\textrm{1h}}$ . The concentration of the obtained MXene solution was ${\\sim}0.5\\mathrm{mg}\\mathrm{ml}^{-1}$ . The MXene membranes were prepared by filtering a certain amount of the MXene solution on \n\nAAO $0.2\\upmu\\mathrm{m}$ pore size and a diameter of $35\\mathrm{mm}$ , purchased from Puyuannano Co., Ltd.) substrates using vacuum-assisted filtration (Supplementary Fig. 7). All membranes were dried at $70^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ and could be easily detached from the substrate (Supplementary Fig. 8). During the membrane preparation process, Ar was used to prevent the oxidation. \n\nCharacterization of the MXene nanosheets and membranes. SEM images were obtained using a Hitachi SU8220 device. The SEM elemental mapping analysis was conducted using an EDX (Oxford EDS, with INCA software). TEM images were obtained using a JEOL JEM-2100F microscope with an acceleration voltage of $200\\mathrm{kV}$ . Elemental mapping in TEM was conducted using the Bruker EDS System. The XRD analysis was carried out using a Bruker D8 Advance with filtered $\\mathrm{Cu-K}\\upalpha$ radiation $40\\mathrm{kV}$ and $40\\mathrm{mA}$ , $\\lambda{=}0.154\\mathrm{\\nm}$ ); the step scan was $0.02^{\\circ}$ , the 2θ range was $2{-}10^{\\circ}$ or $2{-}70^{\\circ}$ , and the step time was 2 s. FTIR was conducted by Bruker VERTEX 33 units in the wavenumber range of $400{-}4000\\mathrm{cm}^{-1}$ . The XPS analysis was performed using an ESCALAB 250 spectrometer (Thermo Fisher Scientific) with monochromated Al-Kα radiation $(1486.6\\mathrm{eV})$ under a pressure of $2\\times10^{-9}$ Torr. The AFM images were obtained using a Bruker Multi Mode 8 scanning probe microscope (SPM, VEECO) in tapping mode. The TG measurement was analyzed on a Netzsch STA 449F3 instrument under the flow of $\\Nu_{2}$ . The adsorption isotherms of $\\mathrm{H}_{2}$ , $\\mathrm{CO}_{2}$ , $\\Nu_{2}$ , and $\\mathrm{CH}_{4}$ on the MXene membranes were measured using a Micromeritics (ASAP 2460) instrument. The mechanical tests were performed using an Instron-5565 universal testing machine (USA). \n\nGas permeation measurements. All the gas permeation measurements were conducted by a homemade membrane module (Supplementary Fig. 20). Silicone gaskets were used to avoid the leakage and the direct contact between the stainlesssteel module and membranes. The gas transport through the membrane was measured using the constant pressure, variable volume method. A calibrated gas chromatograph (GC, Agilent 7890A) was used to analyze the composition of the permeate gas. During single-gas permeation, a flow rate of $50\\mathrm{ml}\\mathrm{{\\dot{min}}^{-1}}$ gas was used in the feed side of the membrane, and sweep gas with a flow rate of $50\\mathrm{ml}\\mathrm{min}$ −1 was used to remove the permeated gas on the permeate side. During mixed-gas permeation, a gas mixture with a ratio of 1:1 was applied at the feed side of the MXene membrane, and the total flow rate of the feed gas was maintained at $100\\mathrm{ml}$ $\\mathrm{min^{-1}}$ (each gas at $50\\mathrm{ml}\\mathrm{min}^{-1}$ ). The gas flow was controlled using mass flow controllers (MFCs). The pressures on both the feed and permeate side were \n\nmaintained at 1 bar. In most cases, $\\Nu_{2}$ was used as the sweep gas, except when using a $\\mathrm{N}_{2}.$ -containing gas as the feed, then $\\mathrm{CH}_{4}$ was employed as the sweep gas. The gas separation measurements were carried out at different temperatures. The membrane module was packed with heating tape and thermocouple and temperature controller devices were used to control the temperature and heating rate $\\left(2\\mathrm{^{\\circ}C}\\operatorname*{min}^{-1\\cdot}\\right)$ ). Feed gases containing different $\\mathrm{H}_{2}$ concentrations were obtained by adjusting the flow rates of $\\mathrm{H}_{2}$ and $\\mathrm{CO}_{2}$ , which were controlled using the MFCs and calibrated using a bubble flowmeter. Steam $(3\\mathrm{vol\\%})$ was introduced into the feed gas after passing it through a water tank at room temperature. The different gas pressures at the feed side of the MXene membranes were controlled with a backpressure valve. \n\nAll of the gas permeation tests were carried out at least three times. The permeability of each gas was calculated from the following equation6: \n\n$$\nP=\\frac{1}{\\Delta p}\\times\\frac{273.15}{273.15+T}\\times\\frac{P_{\\mathrm{atm}}}{76}\\times\\frac{L}{A}\\times\\frac{\\mathrm{d}\\nu}{\\mathrm{d}t},\n$$ \n\nwhere $P$ is the permeability (1 Barrer $\\ensuremath{\\mathbf{\\cdot}}=1\\times10^{-10}\\ensuremath{\\mathrm{cm}}^{3}\\ensuremath{\\mathrm{cm}}\\ensuremath{\\mathrm{cm}}^{-2}s^{-1}\\ensuremath{\\mathrm{cmHg}}^{-1}$ at standard temperature and pressure (STP)); $\\Delta p$ is the transmembrane pressure (atm); $P_{\\mathrm{atm}}$ is the atmospheric pressure (atm); $T$ is the temperature $(^{\\circ}\\mathrm{C})$ ; $L$ is the thickness of the membrane $(\\mathrm{cm})$ ; dv/dt is the volumetric displacement rate in the bubble flowmeter; and $A$ is the effective area of the MXene membrane $(1.13\\mathrm{cm}^{2})$ . \n\nThe selectivity of two components in the single-gas permeation (ideal selectivity) was calculated as follows: \n\n$$\n\\alpha=\\frac{P_{i}}{P_{j}},\n$$ \n\nwhere $P_{i}$ and $P_{j}$ are the permeability of each component. \n\nThe selectivity of two components in the mixed-gas permeation (separation factor) was calculated as follows: \n\n$$\n\\alpha_{i/j}{=}\\frac{\\d y_{i}/\\d y_{j}}{\\d x_{i}/\\d x_{j}},\n$$ \n\nwhere $x$ and $y$ are the volumetric fractions of the corresponding component in the feed and permeate side, respectively7. \n\nMD simulations. Classical MD simulations, which have been proven to be an efficient tool in similar studies16,36,38, were utilized to gain theoretical insight into the gas (e.g., $\\begin{array}{r}{\\mathbb{H}_{2},}\\end{array}$ He, $\\Nu_{2}$ , $\\mathrm{O}_{2}$ , $\\mathrm{CO}_{2}$ , and $\\mathrm{CH}_{4}^{\\cdot}$ ) permeation through the MXene membrane. Two sets of simulations were carried out: one to study the gas molecule permeation through the MXene membrane (Supplementary Fig. 26, denoted as the flux simulation)16,36, and another to calculate the gas diffusion coefficient in the MXene subnanometer channels (Supplementary Fig. 25, denoted as the confined diffusion simulation)37,39. In the flux simulation, 30 gas molecules were placed in the feed chamber on the left side of (along the $z$ direction) the MXene membrane $\\left(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{O}_{2}\\right)$ using a structure taken from the literature40. The free spacing between the MXene nanosheets was ${\\sim}3.5\\mathrm{\\AA}$ (see main text in Fig. 1h), and $2.4\\mathrm{wt\\%}$ water as adsorbate was added randomly between the MXene nanosheets, as determined from the experiments (see the experimental TG in Supplementary Fig. 12). In order to investigate the effect of the surface functional groups on gas separation, gas permeation through the MXene membranes with another model $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{F}_{2})$ has also been simulated and simulations of gas permeation were conducted through the MXene membrane again $\\mathrm{\\tilde{H}}_{2}$ and $\\mathrm{CO}_{2}$ as examples) (Supplementary Fig. 27 and Supplementary Table 7). \n\nThe MXene nanosheets were modeled by the UFF force field (FF) with QEq charge41,42, which has been proven to accurately simulate the interactions of gas molecules with nanoporous materials. The water was described using the SPC/E model43. The $\\Nu_{2}$ , $\\mathrm{O}_{2}$ , $\\mathrm{CO}_{2}.$ , and $\\mathrm{CH}_{4}$ gas molecules were modeled using the TraPPE $\\mathrm{FF}^{44,45}$ , and the united-atom parameters of $\\mathrm{H}_{2}$ and He were taken from other publications46,47. These FF parameters have been proven to accurately simulate the transport of these five gases in nanoporous materials39,48–50. In both the flux or diffusion simulation, the system was subjected to a 500-step steepest-descent energy minimization. Then, a 200–300 ns (flux) or 40 ns (diffusion) NVT (constant particle number, volume and temperature) simulation was performed (leap-frog algorithm with a time step of 2 fs). The Nose–Hoover thermostat51 was employed to maintain a constant simulation temperature of $300\\mathrm{K}$ The MXene atoms were frozen in the simulations since the nanosheets were rather rigid. The short-range interactions were evaluated using a neighbor list of $10\\mathrm{\\AA}$ that was updated every ten steps, and the Lennard–Jones interactions were switched off smoothly between 8 and $9\\mathrm{\\AA}.$ A long-range analytical dispersion correction was applied to the energy to account for the truncation of these interactions52. The electrostatic interactions were evaluated using the reaction-field method53. \n\nDuring the flux simulation, the gas molecules passed through the membrane to the permeate chamber (along the $z$ direction), driven by the concentration difference, and the flux was calculated as the ratio of the number of gas molecules passing through the membrane to the simulation time. The MXene membrane was $5.5\\mathrm{nm}\\times5.3\\mathrm{nm}$ in the primary simulation box, and a periodic boundary condition (PBC) was applied to the $x{-}y$ direction (thus, the MXene membrane was essentially infinite in the $x{-}y$ direction). The $z$ length of the flux simulation box was $32\\mathrm{nm}$ , and the MXene membrane (length ${\\sim}5.3\\mathrm{nm}$ ) was placed approximately in the \n\nmiddle, leading to the feed chamber of ${\\sim}12.6\\mathrm{nm}$ long, and the permeate chamber of \\~14.1 nm long. \n\nConsidering the lateral size of the MXene flakes in the experiments was $1{-}2\\upmu\\mathrm{m}$ confined diffusion simulations were also performed, in which six gas molecules $\\left(\\mathrm{H}_{2}\\right)$ , He, $\\Nu_{2}$ , $\\mathrm{O}_{2}$ , $\\mathrm{CO}_{2}$ , and $\\mathrm{CH_{4}}$ ) diffused between two MXene nanosheets (without the presence of a feed chamber or permeate chamber). These two MXene nanosheets with a free spacing of $0.35\\mathrm{nm}$ were essentially infinite since the PBC was applied during the MD simulations, although they were $5.5\\mathrm{nm}\\times5.3\\mathrm{nm}$ in the primary simulation box. During the confined diffusion simulation, the gas molecules diffused in two neighboring MXene nanosheets (a confined subnanochannel), and for each gas, a 40 ns NVT calculation was carried out and using the Einstein relation, \n\n$$\nD=\\operatorname*{lim}_{t\\to\\infty}\\frac{1}{6t}\\left(\\frac{1}{N}{\\sum_{N}^{k=1}|r_{k}(t)-r_{k}(0)|^{2}}\\right),\n$$ \n\nwhere $r_{k}(t)$ is the position of the $k\\mathrm{th}$ molecule at time $t$ and $N$ is the number of molecules. \n\nAll MD simulations in this work were performed using the GROMACS 4.6.7 package54,55, while the simulation trajectories were analyzed using the GROMACS utilities and home-written codes. The interaction energies of the gas molecules with the MXene nanosheets were calculated from the diffusion simulation trajectories. Figures of the simulated systems were produced using VMD software56. Each flux simulation $200\\mathrm{ns}$ for the single-gas permeation of $\\dot{\\mathrm{H}}_{2}$ $\\Nu_{2}$ , $\\mathrm{O}_{2},$ $\\mathrm{CO}_{2}$ with 30 gas molecules in the simulation system; 300 ns for the mixed-gas permeation of $\\mathrm{H}_{2}+$ $\\mathrm{N}_{2}$ and $_\\mathrm{H}_{2}+\\mathrm{CO}_{2}$ with 60 gas molecules in the simulation system, 30 for each gas species) was repeated four times, and the averaged flux was reported. The flux simulations of the single-gas permeation (in which only one gas was used, e.g., $\\mathrm{H}_{2}$ , $\\Nu_{2}$ , $\\mathrm{O}_{2}$ or $\\mathrm{CO}_{2}$ ) were also performed with a very long permeate cell $(\\sim60\\mathrm{nm}$ , denoted as the long-box simulations) to mimic the experiments more closely. The long-box simulations yielded very similar results compared to the normal-box simulation with a $14.1\\mathrm{nm}$ long permeate cell (except for $\\mathrm{H}_{2}$ in which the flux changed a little from 0.75 to 0.90 molecule $\\mathrm{n}\\mathrm{s}^{-1}$ ). Thus, the flux simulation refers to the normal size box $_z$ length of the $\\mathbf{box}=32\\mathrm{nm}$ , permeate cell length $=12.6\\ \\mathrm{nm}$ , permeate cell length $=14.1\\ \\mathrm{nm}$ , main text Fig. 2d and Supplementary Fig. 26) in this work unless otherwise specified. Each diffusion simulation $\\left(\\mathrm{H}_{2}\\right)$ , He, $\\Nu_{2}$ , $\\mathrm{O}_{2}$ , $\\mathrm{CO}_{2}$ , and $\\mathrm{CH}_{4}$ ) was 40 ns long. Thus, the total simulation time was $5\\upmu\\mathrm{s}$ or more $(4\\times3\\times200\\mathrm{ns}+4\\times2\\times300\\mathrm{ns}+5\\times40\\mathrm{ns}=5\\upmu\\mathrm{s})$ . See our previous publications for further simulation details57. \n\nData availability. The data sets generated and analyzed during the current study are available from the corresponding authors on reasonable request. \n\nReceived: 26 August 2017 Accepted: 6 December 2017 \nPublished online: 11 January 2018 \n\n# References \n\n1. Sholl, D. S. & Lively, R. P. Seven chemical separations to change the world. Nature 532, 435 (2016). \n2. Gin, D. L. & Noble, R. D. Designing the next generation of chemical separation membranes. Science 332, 674–676 (2011). \n3. Park, H. B., Kamcev, J., Robeson, L. M., Elimelech, M. & Freeman, B. D. Maximizing the right stuff: the trade-off between membrane permeability and selectivity. Science 356, eaab0530 (2017). \n4. Liu, G., Jin, W. & Xu, N. Two-dimensional-material membranes: a new family of high-performance separation membranes. Angew. Chem. Int. Ed. 55, 13384–13397 (2016). \n5. Gao, J., Feng, Y., Guo, W. & Jiang, L. Nanofluidics in two-dimensional layered materials: inspirations from nature. Chem. Soc. Rev. 46, 5400–5424 (2017). \n6. Kim, H. W. et al. Selective gas transport through few-layered graphene and graphene oxide membranes. Science 342, 91–95 (2013). \n7. Shen, J. et al. Subnanometer two-dimensional graphene oxide channels for ultrafast gas sieving. ACS Nano 10, 3398–3409 (2016). \n8. Xu, W. L. et al. Self-assembly: a facile way of forming ultrathin, highperformance graphene oxide membranes for water purification. Nano Lett. 17, 2928–2933 (2017). \n9. Geim, A. K. & Novoselov, K. S. The rise of graphene. Nat. Mater. 6, 183–191 (2007). \n10. Koenig, S. P., Wang, L., Pellegrino, J. & Bunch, J. S. Selective molecular sieving through porous graphene. Nat. Nanotechnol. 7, 728–732 (2012). \n11. Wang, L. et al. Molecular valves for controlling gas phase transport made from discrete ångström-sized pores in graphene. Nat. Nanotechnol. 10, 785–790 (2015). \n12. Abraham, J. et al. Tunable sieving of ions using graphene oxide membranes. Nat. Nanotechnol. 12, 546–550 (2017). 13. Chen, sieving in graphen mbra via cationic control of interlayer spacing. Nature 550, 380–383 (2017). \n14. Tsapatsis, M. 2-Dimensional zeolites. AIChE J. 60, 2374–2381 (2014). \n15. Peng, Y. et al. Metal-organic framework nanosheets as building blocks for molecular sieving membranes. Science 346, 1356–1359 (2014). \n16. Wang, X. et al. Reversed thermo-switchable molecular sieving membranes composed of two-dimensional metal-organic nanosheets for gas separation. Nat. Commun. 8, 14460 (2017). \n17. Varoon, K. et al. Dispersible exfoliated zeolite nanosheets and their application as a selective membrane. Science 334, 72–75 (2011). \n18. Jeong, H.-K., Nair, S., Vogt, T., Dickinson, L. C. & Tsapatsis, M. A highly crystalline layered silicate with three-dimensionally microporous layers. Nat. Mater. 2, 53–58 (2003). \n19. Jeon, M. Y. et al. Ultra-selective high-flux membranes from directly synthesized zeolite nanosheets. Nature 543, 690–694 (2017). \n20. Celebi, K. et al. Ultimate permeation across atomically thin porous graphene. Science 344, 289–292 (2014). \n21. O’Hern, S. C. Selective ionic transport through tunable subnanometer pores in single-layer graphene membranes. Nano Lett. 14, 1234–1241 (2014). \n22. Jain, T. Heterogeneous sub-continuum ionic transport in statistically isolated graphene nanopores. Nat. Nanotechnol. 10, 1053–1057 (2015). \n23. Tsou, C.-H. et al. Effect of microstructure of graphene oxide fabricated through different self-assembly techniques on 1-butanol dehydration. J. Membr. Sci. 477, 93–100 (2015). \n24. Naguib, M. et al. Two-dimensional nanocrystals produced by exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 23, 4248–4253 (2011). \n25. Naguib M. in Nanomaterials Handbook 2nd edn (Ed. Gogotsi, Y.) Ch. 4 (CRC Press, Boca Raton, 2017). \n26. Lukatskaya, M. R. et al. Cation intercalation and high volumetric capacitance of two-dimensional titanium carbide. Science 341, 1502–1505 (2013). \n27. Ding, L. et al. A two-dimensional lamellar membrane: MXene nanosheet stacks. Angew. Chem. Int. Ed. 56, 1825–1829 (2017). \n28. Shahzad, F. et al. Electromagnetic interference shielding with 2D transition metal carbides (MXenes). Science 353, 1137–1140 (2016). \n29. Alhabeb, M. et al. Guidelines for synthesis and processing of two-dimensional titanium carbide $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{X}}$ MXene). Chem. Mater. 29, 7633–7644 (2017). \n30. Anasori, B., Lukatskaya, M. R. & Gogotsi, Y. 2D metal carbides and nitrides (MXenes) for energy storage. Nat. Rev. Mater. 2, 16098 (2017). \n31. Magne, D., Mauchamp, V., Célérier, S., Chartier, P. & Cabioc’h, T. Site-projected electronic structure of two-dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene: the role of the surface functionalization groups. Phys. Chem. Chem. Phys. 18, 30946–30953 (2016). \n32. Lipatov, A. et al. Effect of synthesis on quality, electronic properties and environmental stability of individual monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene flakes. Adv. Electron. Mater. 2, 1600255 (2016). \n33. Halim, J. et al. X-ray photoelectron spectroscopy of select multi-layered transition metal carbides (MXenes). Appl. Surf. Sci. 362, 406–417 (2016). \n34. Hope, M. A. et al. NMR reveals the surface functionalisation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene. Phys. Chem. Chem. Phys. 18, 5099–5102 (2016). \n35. Li, H. et al. Ultrathin, molecular-sieving graphene oxide membranes for selective hydrogen separation. Science 342, 95–98 (2013). \n36. Joshi, R. et al. Precise and ultrafast molecular sieving through graphene oxide membranes. Science 343, 752–754 (2014). \n37. Sholl, D. S. Understanding macroscopic diffusion of adsorbed molecules in crystalline nanoporous materials via atomistic simulations. Acc. Chem. Res. 39, 403–411 (2006). \n38. Nair, R. R., Wu, H. A., Jayaram, P. N., Grigorieva, I. V. & Geim, A. K. Unimpeded permeation of water through helium-leak-tight graphene-based membranes. Science 335, 442–444 (2012). \n39. Verploegh, R. J., Nair, S. & Sholl, D. S. Temperature and loading-dependent diffusion of light hydrocarbons in ZIF-8 as predicted through fully flexible molecular simulations. J. Am. Chem. Soc. 137, 15760–15771 (2015). \n40. Khazaei, M. et al. Novel electronic and magnetic properties of two-dimensional transition metal carbides and nitrides. Adv. Funct. Mater. 23, 2185–2192 (2013). \n41. Rappé, A. K., Casewit, C. J., Colwell, K. S., Goddard III, W. A. & Skiff, W. M. UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J. Am. Chem. Soc. 114, 10024–10035 (1992). \n42. Kadantsev, E. S., Boyd, P. G., Daff, T. D. & Woo, T. K. Fast and accurate electrostatics in metal organic frameworks with a robust charge equilibration parameterization for high-throughput virtual screening of gas adsorption. J. Phys. Chem. Lett. 4, 3056–3061 (2013). \n43. Berendsen, H., Grigera, J. & Straatsma, T. The missing term in effective pair potentials. J. Phys. Chem. 91, 6269–6271 (1987). \n44. Potoff, J. J. & Siepmann, J. I. Vapor-liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen. AIChE J. 47, 1676–1682 (2001). \n45. Martin, M. G. & Siepmann, J. I. Transferable potentials for phase equilibria. 1. United-atom description of n-alkanes. J. Phys. Chem. B 102, 2569–2577 (1998). \n46. Darkrim, F. & Levesque, D. Monte Carlo simulations of hydrogen adsorption in single-walled carbon nanotubes. J. Chem. Phys. 109, 4981–4984 (1998). \n47. Talu, O. & Myers, A. L. Molecular simulation of adsorption: Gibbs dividing surface and comparison with experiment. AIChE J. 47, 1160–1168 (2001). \n48. Rankin, R. B., Liu, J., Kulkarni, A. D. & Johnson, J. K. Adsorption and diffusion of light gases in ZIF-68 and ZIF-70: a simulation study. J. Phys. Chem. C 113, 16906–16914 (2009). \n49. Liu, J., Keskin, S., Sholl, D. S. & Johnson, J. K. Molecular simulations and theoretical predictions for adsorption and diffusion of $\\mathrm{CH_{4}/H_{2}}$ and $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ mixtures in ZIFs. J. Phys. Chem. C 115, 12560–12566 (2011). \n50. Wang, H. & Cao, D. Diffusion and separation of $\\mathrm{H}_{2}$ , $\\mathrm{CH}_{4}$ $\\mathrm{CO}_{2}$ , and $\\Nu_{2}$ in diamond-like frameworks. J. Phys. Chem. C 119, 6324–6330 (2015). \n51. Feller, S. E., Zhang, Y., Pastor, R. W. & Brooks, B. R. Constant pressure molecular dynamics simulation: the Langevin piston method. J. Chem. Phys. 103, 4613–4621 (1995). \n52. Shirts, M. R., Pitera, J. W., Swope, W. C. & Pande, V. S. Extremely precise free energy calculations of amino acid side chain analogs: comparison of common molecular mechanics force fields for proteins. J. Chem. Phys. 119, 5740–5761 (2003). \n53. Tironi, I. G., Sperb, R., Smith, P. E. & van Gunsteren, W. F. A generalized reaction field method for molecular dynamics simulations. J. Chem. Phys. 102, 5451–5459 (1995). \n54. Hess, B., Kutzner, C., van der Spoel, D. & Lindahl, E. GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput. 4, 435–447 (2008). \n55. Berendsen, H. J., van der Spoel, D. & van Drunen, R. GROMACS: a messagepassing parallel molecular dynamics implementation. Comput. Phys. Commun. 91, 43–56 (1995). \n56. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996). \n57. Li, L., Fennell, C. J. & Dill, K. A. Field-SEA: a model for computing the solvation free energies of nonpolar, polar, and charged solutes in water. J. Phys. Chem. B 118, 6431 (2014). \n58. Robeson, L. M. The upper bound revisited. J. Membr. Sci. 320, 390–400 (2008). \n\n# Acknowledgements \n\nWe gratefully acknowledge the funding from the NSFC (21536005, 51621001, 21506066 and 21606086), NSFC-DFG (GZ-678), the 1000 Talents program, Natural Science Foundation of the Guangdong Province (2014A030312007) and Guangdong Natural Science Funds for Distinguished Young Scholar (2017A030306002). CPU hours allocated by the Guangzhou Supercomputer Center of China and the kind help of Dr Zhiwei Qiao in calculating the QEq charge are gratefully acknowledged. \n\n# Author contributions \n\nL.D. conducted the experiments. L.D., Y.W. and H.W. conceived the idea and designed the experiments. L.D., L.L., Y.W., H.W., J.C. and Y.G. analyzed the data and interpreted the results. L.L. and T.Z. performed the molecular simulations. J.X., S.W. and L.-X.D. participated in discussions and data analysis. H.W., J.C. and Y.G. supervised the project. L.D., L.L. and Y.W. co-wrote the manuscript. All authors contributed to discussions and the writing of the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 017-02529-6. \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1016_j.joule.2018.06.007", + "DOI": "10.1016/j.joule.2018.06.007", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2018.06.007", + "Relative Dir Path": "mds/10.1016_j.joule.2018.06.007", + "Article Title": "Boron-Doped Graphene for Electrocatalytic N2 Reduction", + "Authors": "Yu, XM; Han, P; Wei, ZX; Huang, LS; Gu, ZX; Peng, SJ; Ma, JM; Zheng, GF", + "Source Title": "JOULE", + "Abstract": "Electrochemical N-2 reduction in aqueous solutions at ambient conditions is extremely challenging and requires rational design of electrocatalytic centers. We demonstrate a boron-doped graphene as an efficient metal-free N-2 reduction electrocatalyst. Boron doping in the graphene framework leads to redistribution of electron density, where the electron-deficient boron sites provide enhanced binding capability to N-2 molecules. Density functional theory calculations reveal the catalytic activities of different boron-doped carbon structures, in which the BC3 structure enables the lowest energy barrier for N-2 electroreduction to NH3. At a doping level of 6.2%, the boron-doped graphene achieves a NH3 production rate of 9.8 mu g.hr(-1).cm(-2) and one of the highest reported faradic efficiencies of 10.8% at -0.5 V versus reversible hydrogen electrode in aqueous solutions at ambient conditions. This work suggests the strong potential of atomic-scale design for efficient electrocatalysts for N-2 reduction.", + "Times Cited, WoS Core": 830, + "Times Cited, All Databases": 866, + "Publication Year": 2018, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000441627400023", + "Markdown": "# Article Boron-Doped Graphene for Electrocatalytic N Reduction \n\nXiaomin Yu, Peng Han, Zengxi Wei, ..., Sijia Peng, Jianmin Ma, Gengfeng Zheng \n\nnanoelechem@hnu.edu.cn (J.M.) gfzheng@fudan.edu.cn (G.Z.) \n\n# HIGHLIGHTS \n\n![](images/88f641db5aca6304d00df329c6d97cb7f0ce687b971e365e82530adb440ea4be.jpg) \n\nDFT data showed that B doping led to electron redistribution and better ${\\sf N}_{2}$ adsorption \n\nExperiments and DFT data revealed that ${\\mathsf{B C}}_{3}$ enabled the lowest energy barrier for NRR \n\nExcellent $N H_{3}$ production rate and faradic efficiency were achieved at $-0.5\\vee$ versus RHE \n\nBoron-doped graphene with different boron structures was rationally synthesized to enhance the adsorption of $\\mathsf{N}_{2},$ thus enabling an efficient metal-free electrocatalyst for electrochemical ${\\sf N}_{2}$ reduction in aqueous solution at ambient conditions. At a doping level of $6.2\\%,$ boron-doped graphene achieved a $N H_{3}$ production rate of $9.8~\\upmu\\up g\\cdot\\mathsf{h}\\mathsf{r}^{-1}\\cdot\\mathsf{c m}^{-2}$ and an excellent faradic efficiency ( $10.8\\%$ at $-0.5\\vee$ versus reversible hydrogen electrode). \n\n# Article Boron-Doped Graphene for Electrocatalytic N2 Reduction \n\nXiaomin Yu,1,3 Peng Han,1,3 Zengxi Wei,2,3 Linsong Huang,1 Zhengxiang Gu,1 Sijia Peng,1 Jianmin $\\mathsf{M a},2,^{\\star}$ and Gengfeng Zheng1,4,\\* \n\n# SUMMARY \n\nElectrochemical $\\ensuremath{\\mathsf{N}}_{2}$ reduction in aqueous solutions at ambient conditions is extremely challenging and requires rational design of electrocatalytic centers. We demonstrate a boron-doped graphene as an efficient metal-free $\\ensuremath{\\mathsf{N}}_{2}$ reduction electrocatalyst. Boron doping in the graphene framework leads to redistribution of electron density, where the electron-deficient boron sites provide enhanced binding capability to $\\ensuremath{\\mathsf{N}}_{2}$ molecules. Density functional theory calculations reveal the catalytic activities of different boron-doped carbon structures, in which the $B C_{3}$ structure enables the lowest energy barrier for $N_{2}$ electroreduction to $N H_{3}$ . At a doping level of $6.2\\%$ , the boron-doped graphene achieves a $N H_{3}$ production rate of $9.8~\\upmu\\mathfrak{g}\\cdot\\mathsf{h}\\mathsf{r}^{-1}\\cdot\\mathsf{c}\\mathsf{m}^{-2}$ and one of the highest reported faradic efficiencies of $10.8\\%$ at $_{-0.5\\mathrm{~V~}}$ versus reversible hydrogen electrode in aqueous solutions at ambient conditions. This work suggests the strong potential of atomic-scale design for efficient electrocatalysts for $\\ensuremath{\\mathsf{N}}_{2}$ reduction. \n\n# INTRODUCTION \n\nAmmonia $(N H_{3})$ is an essential chemical that is widely used in agriculture and industry applications.1 In addition to natural biological synthetic processes,2 ammonia is predominantly synthesized via the Haber-Bosch process with Fe-based catalysts,3 by which nitrogen $(\\mathsf{N}_{2})$ and hydrogen $(\\mathsf{H}_{2})$ molecules are processed at high pressures (150–350 atm) and temperatures $\\langle400^{\\circ}\\mathsf{C}\\mathrm{-}600^{\\circ}\\mathsf{C}\\rangle$ . Due to the extreme inertness of ${\\sf N}_{2}$ and carbon emission for producing the ${\\sf H}_{2}$ precursor, the Haber-Bosch process accounts for ${\\sim}1.5\\%$ of global energy consumption and a significant ${\\mathsf{C O}}_{2}$ emission annually.4 The electrocatalytic ${\\sf N}_{2}$ reduction reaction (NRR), ideally under ambient conditions and using water as the hydrogen source, has been proposed as a sustainable alternative for nitrogen fixation and ammonia production, while its efficiency has generally been extremely low.5 \n\nIn an aqueous electrolyte, the major competing side reaction of NRR is the hydrogen evolution reaction (HER), in which water (or $\\mathsf{H}^{+})$ is reduced to form gaseous ${\\sf H}_{2}$ .6,7 Substantial theoretical studies have been proposed to discover and optimize new NRR electrocatalyst candidates, predominantly metals8,9 and their oxides10 or nitrides,11 with the focus on designing crystal facets,12 defects,13 and interfaces.14 These studies were echoed by recent developments of electrocatalysts based on $\\mathsf{R}\\mathsf{u},^{15}\\mathsf{A}\\mathsf{u},^{16-18}\\mathsf{M}\\mathsf{o},^{19}\\mathsf{F}\\mathsf{e}_{2}\\mathsf{O}_{3},^{20,21}$ and $\\mathsf{B i}_{4}\\mathsf{V}_{2}\\mathsf{O}_{11}$ .22 It was also reported that the ${\\mathsf{L i}}^{+}$ incorporation in poly(N-ethyl-benzene-1,2,4,5-tetracarboxylic diimide) can suppress HER and thus enhance NRR.23 Very recently, N-doped porous carbon obtained by pyrolysis of a zeolite imidazolate framework was reported for electrocatalytic ammonia synthesis,24 while its NRR efficiency against HER remained below $1.5\\%$ . To date, the use of metal-free electrocatalysts for NRR under ambient \n\n# Context & Scale \n\nAmmonia $(N H_{3})$ is an essential chemical that is widely used in agriculture and industry applications. The industry-scale Haber-Bosch process accounts for $\\sim1.5\\%$ of global energy consumption and a significant ${\\mathsf{C O}}_{2}$ emission annually, due to the extreme inertness of $N_{2}$ and carbon emission for producing ${\\sf H}_{2}$ precursor. The electrochemical reduction of ${\\sf N}_{2}$ (NRR) in aqueous solutions at ambient conditions is extremely challenging and requires rational design of electrocatalytic centers. Previous reports predominantly used metal-based electrocatalysts, and the efficiency has generally been extremely low. In this work, we demonstrate for the first time boron-doped graphene as an efficient metal-free NRR electrocatalyst in aqueous solutions at ambient conditions. \n\n![](images/9f2ec881d3c677792fd2d02308a8c5e4b1c979440d94ba87791b44391ceadcd1.jpg) \nFigure 1. Electron Densities of BG (A) Schematic of the atomic orbital of $B C_{3}$ for binding ${\\sf N}_{2}$ . (B) LUMO (blue) and HOMO (red) of undoped G $(\\mathsf{G})$ and BG (right). The position of a single doped boron atom was labeled. See also Figures S1 and S2. \n\nconditions, both in theoretical and experimental studies, has remained largely unexplored. \n\nThe mechanism of NRR can be generally considered as the adsorption of ${\\sf N}_{2}$ on catalyst surfaces, followed by successive cleavage of N–N and formation of N–H bonds with consecutive proton additions. The key design strategy for a potential NRR electrocatalyst should enable a good density of active catalytic centers, which can facilitate the adsorption and activation of ${\\sf N}_{2}$ molecules.25 In contrast, the adsorption of two H adatoms in a vicinity can result in significant formation of ${\\sf H}_{2}$ and lower NRR efficiency and should be inhibited. As ${\\sf N}_{2}$ is a weak Lewis base; it is thus ideal to create a Lewis acid catalytic site with an empty orbital to bind ${\\sf N}_{2}$ . \n\nHere, we demonstrate that two-dimensional (2D), boron-doped graphene (BG) features as an ideal NRR electrocatalyst that can promote adsorption of ${\\sf N}_{2}$ . The graphene (G) framework doped with boron atoms can retain its original $\\scriptstyle s p^{2}$ hybridization and conjugated planar structure. Boron is an important doping element that induces electron deficiency in G, leading to a much improved electrocatalytic activity. For instance, BG exhibits superior oxygen reduction reaction (ORR) catalytic performance because the electron-deficient B dopants can facilitate chemisorption of negatively polarized O atoms and promote O–O cleavage during ORR.26 The formation of BG was also reported to present good oxygen evolution reaction activity in alkaline solution.27 Furthermore, it was also demonstrated that BG exhibited ${\\mathsf{C O}}_{2}$ electroreduction capability at low overpotentials to produce formate.28 The electronegativity of boron (2.04) is smaller than that of carbon (2.55), leading to a clear differentiation of electron densities on the carbon ring structure (Figure 1A). The positively charged boron atoms are beneficial for adsorbing $\\mathsf{N}_{2}$ , thus providing excellent catalytic centers for the B–N bond formation and the subsequent production of $N H_{3}$ . These electron-deficient boron sites can also prohibit the binding of Lewis acid $\\mathsf{H}^{+}$ at these sites (under acidic conditions), which can promote the NRR faradic efficiency (FE) and decrease of HER. At a boron doping concentration of $6.2\\%$ , BG exhibited an excellent $N H_{3}$ yield $(9.8~\\upmu\\up g\\cdot\\mathsf{h}\\mathsf{r}^{-1}\\cdot\\mathsf{c m}^{-2})$ and one of the highest FEs for $N H_{3}$ production (FE $N H3$ , $10.8\\%)$ in aqueous solutions at ambient conditions at $-0.5\\vee$ versus reversible hydrogen electrode (RHE), corresponding to 5-fold and 10-fold increases of the $N H_{3}$ yield and $F E_{N H3}$ , respectively, of undoped G. \n\n# Joule \n\n![](images/3ef46ec1e2f19a73543a43c5244494681c1ba53dc9344fc04c25a1108fd57665.jpg) \nFigure 2. Characterization of BG \n\n(A) TEM image of BG-1. \n(B) EDS mappings of BG-1 for B (green), C (red) and O (purple). \n(C) Raman spectra of BG-1, BOG, BG-2, and G. \n(D) FT-IR spectra of BG-1, BOG, BG-2, and G. \nSee also Figures S3. \n\n# RESULTS \n\n# Synthesis and Characterization of BG \n\nThe molecular orbitals of BG were first modeled by density functional theory (DFT; calculation details in the Experimental Procedures), and compared with those of undoped G. For undoped G (Figure 1B, left), the highest occupied molecular orbital (HOMO; red) and the lowest unoccupied molecular orbital (LUMO; blue) present a non-localized, symmetric electron distribution. In contrast, for BG (in which a single boron atom is substituted for a carbon site; Figure 1B, right), the electron densities of both HOMO and LUMO are clearly redistributed to break the intrinsic equilibrium. The 3D charge density difference and the Mulliken population of BG indicate that the boron dopant introduces inhomogeneity for G (Figure S1A). The positively charged boron dopant $\\left(+0.59~\\mathrm{e}\\right)$ is beneficial for adsorbing ${\\sf N}_{2}$ to boost the NRR performance. \n\nBG was synthesized by thermal reduction of $\\mathsf{H}_{3}\\mathsf{B O}_{3}$ with graphene oxide in a mixed ${\\sf H}_{2}/{\\sf A}{\\sf r}$ gas (Experimental Procedures). The mass ratios of ${\\sf H}_{3}{\\sf B}{\\sf O}_{3}$ to graphene oxide were set as 5:1, 1:10, and 0:1, and the products were designated as BG-1, BG-2, and G (i.e., undoped G), respectively. For comparison, a $H_{3}B O_{3},$ graphene oxide mixture (5:1) was also annealed in Ar instead of ${\\sf H}_{2}/{\\sf A}{\\sf r}$ to obtain a higher oxygen content, designated as BOG. All these samples (BG-1, BOG, BG-2, and G) appeared as black powder (Figure S2A). Transmission electron microscopy (TEM) images of these samples clearly displayed a typical and similar 2D morphology, both before (Figure S2B) and after boron doping (Figure 2A). Energy dispersive $\\mathsf{X}$ -ray spectroscopy (EDS) \n\nmapping of BG (Figure 2B) showed uniform elemental distributions of boron (green), carbon (red), and O (purple). \n\nThe structures of the B-doped G were further characterized by Raman spectroscopy (Figure 2C). The peaks centered at $\\sim1{,}350$ and $1,590{\\mathsf{c m}}^{-1}$ are designated as D and G bands, respectively, corresponding to the defect and well-ordered $\\scriptstyle s p^{2}$ carbon atoms that are consistent with conventional G.28 The ratios of $I_{D}/I_{G}$ were calculated as 1.3, 1.3, 1.1, and 0.91, for the samples of BG-1, BOG, BG-2, and G, respectively, suggesting that the substitution of boron for carbon induces more defects in G. Fourier transform infrared (FTIR) spectroscopy was also carried out on these samples to confirm the boron doping (Figure 2D). In all these samples, the broad peak centered at ${\\sim}3,437~{\\ c m}^{-1}$ was attributed to the $0{\\cdot}\\mathsf{H}$ stretching vibration, and the peak at $\\sim1.566~{\\mathsf{c m}}^{-1}$ was assigned to the $C=C$ stretching vibration.29 Except for G, two additional peaks emerging at 1,383 and 1, $,115\\mathsf{c m}^{-1}$ in all the three B-doped samples were assigned to the $_{\\mathsf{B-O}}$ and B–C stretching vibrations, respectively,30 confirming the successful substitution of boron in the G structure. \n\nThe atomic structure of those boron dopants in G was further interrogated by X-ray photoelectron spectroscopy (XPS). Representative XPS survey spectra of BG-1, BOG, BG-2, and G are shown in Figure S3, where all samples presented the C 1s peak at ${\\sim}284.5~\\mathsf{e V}$ and the $\\bigcirc$ 1s peak at ${\\sim}532.5\\ \\mathrm{eV}$ . For each sample, three sets of data were measured and are listed in Tables S1 and S2. The peak at ${\\sim}190.1\\ \\mathrm{eV}$ was associated with the B 1s peak, providing the reproducible boron atom percentages of BG-1, BOG, and BG-2 as $6.2\\%$ , $6.4\\%$ , and $3.0\\%$ , respectively (Table S1). The B content in BG did not change when the ${\\sf H}_{3}{\\sf B}{\\sf O}_{3}/{\\sf G}$ ratio was further increased to 10:1 and 20:1, suggesting the maximum boron doping level was already achieved at the BG-1 or BOG samples (with the $H_{3}B O_{3}/G$ ratio of 5:1). The high-resolution C 1s spectrum of BG-1 consisted of five characteristic peaks (Figure 3A), corresponding to the C–B $(284~\\mathrm{eV})$ , C–C $(284.6~\\mathsf{e V})$ , C–O $(285.6~\\mathsf{e V})$ , $C=0$ $286.5~\\mathsf{e V})$ , and $0-C=0$ $287.5\\mathsf{e V}$ structures, respectively.31 The high-resolution B 1s peaks for all three boron-doped samples were fitted into four peaks (Figures 3B–3D), assigned to structures of $\\mathsf{B}_{4}\\mathsf{C}$ $(187.8~\\mathrm{eV})$ , $B C_{3}$ $189.9~\\mathrm{eV}$ , ${\\tt B C}_{2}\\mathrm{O}$ $(191.2~\\mathrm{eV})$ , and ${\\mathsf{B C O}}_{2}$ $\\cdot192.3\\ \\mathrm{eV})$ .32 As schematically shown in Figure S4, the $\\mathtt{B_{4}C}$ -type bond is ascribed to the defect of G lattice; the $B C_{3}$ structure indicates that a boron atom replaces a carbon atom in G framework, while the $B C_{2}O$ and ${\\mathsf{B C O}}_{2}$ structures indicate that a B atom replaces the C atom at the edge or defect sites of the G framework. The ratios of these four types of B-doped structures are summarized in Figure 3E and Table S2. All samples only had negligible amounts of the $\\mathsf{B}_{4}\\mathsf{C}$ structure but significant ${\\mathsf{B C}}_{2}{\\mathsf{O}}$ and ${\\mathsf{B C O}}_{2}$ percentages, suggesting the existence of boron doping at the G edges or defect sites. The reproducible percentages of the $B C_{3}$ structure in BG-1, BOG, and BG-2 were $63.0\\%$ , $35.2\\%$ , and $55.3\\%$ , respectively (Table S2). The various boron structures have different electron density distributions, and thus may play different roles for their corresponding electrocatalytic NRR activities. \n\nTemperature-programmed desorption (TPD) was further carried out to investigate the capability of these samples for ${\\sf N}_{2}$ adsorption (Figure 3F), which is a prerequisite step of NRR. The adsorption peak centered at ${\\sim}100^{\\circ}\\mathsf C$ was assigned to the physisorption, and the wide adsorption centered at ${\\sim}260^{\\circ}\\mathsf C$ corresponded to the chemisorption of ${\\sf N}_{2}$ .33 For G, the physisorption was predominant, while its chemisorption was almost negligible. For the BG-1 and BG-2 samples, the chemisorption was significantly enhanced and also showed dependence on the boron doping percentage, suggesting that boron dopants induce the chemical adsorption sites for ${\\sf N}_{2}$ molecules. \n\n# Joule \n\n![](images/3211645341a9abe58088a425689a4691c61fbf90b7d1a55300543b270a90d2c9.jpg) \nFigure 3. Structure Analysis of BG \n\n(A) C 1s XPS spectra of BG-1. \n(B) B 1s $\\mathsf{X P S}$ spectra of BG-1. \n(C) B 1s XPS spectra of BOG. \n(D) B 1s $\\mathsf{X P S}$ spectra of BG-2. \n(E) Percentages of different B types in the three BG samples. \n(F) ${\\sf N}_{2}$ TPD curve of BG-1, BOG, BG-2, and G. \nSee also Figures S4 and S5 and Tables S1 and S2. \n\n# Electrocatalytic NRR Activity of the BG Catalysts \n\nThe NRR electrocatalytic activities of all these samples (BG-1, BOG, BG-2, and G) were carried out in a ${\\sf N}_{2}$ -saturated 0.05 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solution in an H-shape electrochemical cell (Experimental Procedures). Unless otherwise specified, all the potentials in this manuscript were converted and reported as values versus RHE. The scanning electron microscopy images of BG samples on the modified electrode confirmed that their two-dimensional, ultrathin nanosheet structure was retained without any apparent aggregation (Figure S5). The linear sweep voltammetry (LSV) curves of BG-1 in Ar-saturated (black curve) and ${\\sf N}_{2}$ -saturated (red curve) electrolytes demonstrated different current densities from $-0.45$ to $-0.70\\mathrm{\\:V}$ (Figure 4A), indicating the reduction of ${\\sf N}_{2}$ . In order to minimize the experimental error in quantifying $F E_{N H3},$ the current density threshold for the onset of electrocatalysis was set as $0.1\\ m A\\cdot\\mathsf{c m}^{-2}$ , corresponding to an applied potential of $-0.5\\vee$ . The LSV curves of all samples in Ar-saturated solution showed that the increase of boron doping level led to the increased ${\\sf H}_{2}$ overpotentials and reduced conductivity (Figure S6). The electrochemically active surface areas (ECSAs) of all samples were calculated and compared based on the double-layer capacitances $(C_{d I})$ . The highest electrochemical capacitance of G indicated its largest effective electrochemical area for HER among these samples (Figure S7). Compared with those of BG-1, BOG, and BG-2, the G sample showed both the largest ECSAs and the highest overall current density, thus suggesting that boron doping in $\\mathsf{G}$ can retard the HER process. \n\n![](images/d3a70c595bde017c5677feeb13683c050da36fe498099b94ca4aa2d1cd212a0b.jpg) \nFigure 4. Electrocatalytic NRR Activity of the BG Samples \n(A) LSV curves of BG-1 in Ar- and ${\\sf N}_{2}$ -saturated solutions at the scan rate of $1\\mathrm{mV}\\cdot\\mathsf{s}^{-1}$ . (B) The $N H_{3}$ production rates (left y axis) and $F E_{N H3}$ (right y axis) of BG-1. The error bars represent the average of three independent measurements. (C) The $N H_{3}$ production rates of BG-1, BOG, BG-2, and G at different potentials. (D) The $F E_{N H3}$ values of BG-1, BOG, BG-2, and G at different applied potentials. (E) Chronoamperometric curves of BG-1 at different applied potentials. (F) NRR stability test of BG-1 at $-0.5\\vee$ versus RHE. See also Figures S6–S15, and Tables S3–S5. \n\nThe two potential reduction products, $N H_{3}$ and $N_{2}H_{4},$ were quantified by both the sodium salicylate-sodium hypochlorite method (Figure $58)^{17,19,23}$ and Nessler’s reagent spectrophotometry and the 4-(dimethylamino) benzaldehyde spectrophotometric method,16 respectively (Figure S9). In this work, $N H_{3}$ was the only product \n\n# Joule \n\nwithout the presence of $N_{2}H_{4}$ . The ammonia production rates and the calculated $F E_{N H3}$ values obtained from these two methods were in good consistency. In order to ensure that no false signals existed from impurities that reacted with color reagents, four sets of control experiments were always conducted: (1) immersing samples in a ${\\sf N}_{2}$ -saturated electrolyte without applied potentials for $2\\mathsf{h r};$ (2) immersing samples in an $\\mathsf{A r}$ -saturated electrolyte at $-0.5{\\mathrm{~V~}}$ for $2\\ h r;$ (3) immersing Nafion dispersed carbon paper in a ${\\sf N}_{2}.$ -saturated electrolyte at $-0.5{\\mathrm{~V~}}$ for $2\\ h r;$ and (4) immersing samples at $-0.5\\mathrm{~V~}$ with alternating $2-h r$ cycles between ${\\sf N}_{2}$ -saturated and Ar-saturated electrolytes, for a total of $12\\mathsf{h r}$ . In the former three control experiments, no ammonia was detected and the photographs of their colorimetric assay showed no color difference (Figure S10). For the last control experiment, the positive NRR results were only obtained in the durations of ${\\sf N}_{2}$ -saturated electrolyte, while the measurement in $\\mathsf{A r}$ -saturated electrolytes only provided blank results, further confirming NRR on the BG samples (Figure S11). \n\nThe $N H_{3}$ yields and the $F E_{N H3}$ values at different applied potentials for the BG-1, BOG, BG-2, and $\\mathsf{G}$ electrocatalysts were then measured (Figure S12, Table S3) and compared (Figures 4B–4D). The BG-1 sample exhibited the best performance, with a $N H_{3}$ production rate of $9.8~\\upmu\\up g\\cdot\\mathsf{h}\\mathsf{r}^{-1}\\cdot\\mathsf{c m}^{-2}$ and an $F E_{N H3}$ of $10.8\\%$ at $-0.5\\vee$ , which were 5 and 10 times higher than those of the undoped G, respectively. The other two BG samples (BOG and BG-2) also showed significant increase of both $N H_{3}$ production rates and the $F E_{N H3}$ values. Compared with other NRR electrocatalysts in aqueous solutions at ambient conditions reported to date (Table S4), our BG-1 sample demonstrated one of the highest $N H_{3}$ production rates and $F E_{N H3}$ values. \n\nIn addition, the $F E_{H2}$ values at different applied potentials for the BG-1, BOG, BG-2, and G electrocatalysts were measured by in-line gas chromatography (Figure S13A), which added the $F E_{N H3}$ values to over $95\\%$ . The ${\\sf H}_{2}$ partial current densities of all BG were lower than that of undoped G (Figure S13B). In addition, the BG-1 sample exhibited stable current densities at various potentials, with an excellent retention of $89.4\\%$ at $-0.5{\\mathrm{~V~}}$ after $2h r$ of continuous electrochemical tests (Figure 4E). Both the $N H_{3}$ production rates and the $F E_{N H3}$ values were also well maintained for $10\\ \\mathsf{h r}$ of continuous electrochemical NRR tests, with a stability retaining of ${\\sim}96\\%$ (Figure 4F). In addition, the B dopants were stable in all the BG samples, which was revealed by the TEM (Figure S14), Raman (Figure S15), and XPS tests (Table S5) of the BG samples after the 10-hr electrochemical stability test. \n\n# DISCUSSION \n\nThe remarkable activity of BG can be rationally attributed to the introduction of boron into G structures (Figure 5A). The local electron-deficient environment at the B-doping position offers a strong binding site for a Lewis base, thus leading to a significant increase of ${\\sf N}_{2}$ adsorption for subsequent NRR. The performance of BG-1 shows a significant enhancement compared with that of BG-2, indicating that the increase of the boron content improves the NRR electrocatalytic property. While BG-1 and BOG have almost the same B-doping level, the distinct difference observed for $N H_{3}$ yield and $F E_{N H3}$ can be ascribed to the distribution of different boron structures. The most significant percentage of $B C_{3}$ in the BG-1 sample suggests that $B C_{3}$ serves as a major electrocatalytic NRR site compared with other boron types. \n\nIn order to illustrate the NRR effect of different boron structures, we further carried out first-principle calculations (calculation details in the Experimental Procedures). Among different NRR pathways, the distal pathway in the association mechanism is more feasible than other pathways in the metal-free catalysts, as it allows stabilizing the intermediates.34 Thus, the distal pathway is considered as a possible NRR process in our work, which can be described as16,34: \n\n![](images/c32ebadd404a994fa60bc04054c7d08dd00f18121d3406b34821440d20c7dc18.jpg) \nFigure 5. Theoretical Calculations of NRR for BG Samples \n(A) Schematic illustration of NRR for BG. (B) Reaction pathways and the corresponding energy changes of NRR on $B C_{3},$ , ${\\mathsf{B C}}_{2}{\\mathsf{O}}_{\\cdot}$ , ${\\mathsf{B C O}}_{2}$ , and C, respectively. The dotted rectangular box indicates the steps that cannot take place. (C) Free energy diagrams of NRR on ${\\mathsf{B C}}_{3}$ , ${\\mathsf{B C}}_{2}{\\mathsf{O}},$ ${\\mathsf{B C O}}_{2},$ , and $\\mathsf{C},$ , respectively. See also Figure S16. \n\n$$\nN_{2}{\\rightarrow}N_{2}^{*}{\\stackrel{H^{+}}{\\rightarrow}}N N H^{*}{\\stackrel{H^{+}}{\\rightarrow}}N N H_{2}^{*}{\\stackrel{H^{+}}{\\rightarrow}}N^{*}+N H_{3(g)}{\\stackrel{H^{+}}{\\rightarrow}}N H^{*}{\\stackrel{H^{+}}{\\rightarrow}}N H_{2}^{*}{\\stackrel{H^{+}}{\\rightarrow}}N H_{3}^{*}\\rightarrow N H_{3(g)}\n$$ \n\nThis pathway was calculated for $\\mathsf{G}$ and three BG structures (i.e., $B C_{3}$ , ${\\mathsf{B C}}_{2}{\\mathsf{O}}_{\\cdot}$ , and $B C O_{2})$ , respectively (Figures 5B and 5C). Several key results can be seen from these calculations. \n\nFirst, the nitrogen binding energies and equilibrium distances between an adsorbed ${\\sf N}_{2}$ and a boron (or carbon) atom are $0.01\\ \\mathrm{eV},3.40\\ \\mathring{\\mathsf{A}}$ (for $\\mathsf{B C}_{3})$ ; 0.40 eV, 3.20 A˚ (for \n\n# Joule \n\n${\\mathsf{B C}}_{2}{\\mathsf{O}})$ ; $-0.44\\ \\mathsf{e V},$ , 3.00 A˚ (for $B C O_{2})$ ; and $0.1\\ \\mathrm{eV},3.50\\ \\mathring{\\mathsf{A}}\\ (\\mathrm{for~G})$ , respectively. The reduced distance of adsorbed ${\\sf N}_{2}$ on BG structures and the more negative nitrogen binding energies suggest that, with the incorporation of boron dopant in $\\mathsf{G}$ , the adsorption of ${\\sf N}_{2}$ is increased and the $B{-}N_{2}$ interaction becomes more stable, thus enhancing the NRR. \n\nSecond, compared with ${\\mathsf{B C}}_{3}$ , the B atom becomes more positive by the introduction of oxygen (Figures S1B and S1C), due to the oxygen’s higher electronegativity (3.04) than those of carbon (2.55) and boron (2.04), which leads to even higher binding capability of ${\\sf N}_{2}$ . The B–N lengths become shorter and the ${\\sf N}_{2}$ binding energies become more negative due to oxygen, also indicating stronger ${\\sf N}_{2}$ binding capability. However, this stronger B–N interaction is not beneficial for the release of the second $N H_{3}$ and regeneration of the active B catalytic centers. \n\nIn addition, the C slab cannot anchor ${\\sf N}_{2}$ with the N–C length of $3.37\\mathring{\\mathsf{A}}$ in the first protonation process $(\\mathsf{N}_{2}^{\\star}\\to\\mathsf{N}_{2}\\mathsf{H}^{\\star})$ . The adsorption of ${\\sf N}_{2}$ onto the undoped $\\mathsf{G}$ (without any defect) needs an additional energy of $0.10\\mathsf{V}.$ , and the subsequent addition of the second proton needs an uphill energy of $0.70\\mathsf{V}.$ , which is energy unfavorable and prohibits continuing the NRR. Thus, the NRR cannot proceed on the ideal G without any defect. The electrochemical data also showed that the undoped G only had minimal NRR capability that was much smaller than those of the BG (Figures 4B and 4C). The slight NRR performance of undoped G was attributed to the defects introduced by thermal reduction of graphene oxide. \n\nFurthermore, the formation of adsorbed intermediate $N H^{\\star}$ is the limiting step for both $\\mathsf{B C O}_{2}(1.04\\mathrm{eV},\\mathsf{N}^{\\star}\\to\\mathsf{N H}^{\\star})$ and ${\\mathsf{B C}}_{2}{\\mathsf{O}}$ ( $1.30\\:\\mathrm{eV}.$ , $\\mathsf{N}^{\\star}\\to\\mathsf{N}\\mathsf{H}^{\\star}$ ) for the largest uphill energy, while the formation of adsorbed intermediate $N H_{2}{^\\star}$ is the limiting step for $B C_{3}$ $\\mathsf{.O.43\\ e V}.$ , ${\\mathsf{N H}}^{\\star}{\\to}{\\mathsf{N H}}_{2}^{\\star})$ . The $B C_{3}$ possesses the lowest reaction energy barrier $(0.43\\ \\mathsf{e V})$ , indicating its best catalytic NRR performances among these structures. The optimized geometry structure of the reaction pathway for the $B C_{3}$ slab is displayed in Figure S16. \n\nIn summary, we successfully developed a BG by thermal annealing of graphene oxide and boric acid, which features a metal-free electrocatalyst for electrochemical NRR in aqueous solution at ambient conditions. This BG shows a significant enhancement compared with undoped ${\\mathsf{G}},$ with an excellent $N H_{3}$ production rate of $9.8~\\upmu\\up g\\cdot\\mathsf{h}\\mathsf{r}^{-1}\\cdot\\mathsf{c m}^{-2}$ and the highest reported $F E_{N H3}$ $10.8\\%$ at $-0.5\\vee$ versus RHE) in aqueous solutions at ambient conditions. Combining experimental observations with theoretical investigations, the $\\mathsf{G}$ -like ${\\mathsf{B C}}_{3}$ -type bond plays a key role in enhanced ${\\sf N}_{2}$ fixation among several types of boron-doped carbon structures (i.e., ${\\mathsf{B C}}_{3},{\\mathsf{B C}}_{2}{\\mathsf{O}},{\\mathsf{B C O}}_{2})$ , which has benefits for both ${\\sf N}_{2}$ adsorption and ammonia production. This work suggests many new opportunities for the development of efficient metal-free catalysts for NRR and other electrocatalytic reactions. \n\n# EXPERIMENTAL PROCEDURES \n\n# Synthesis of Boron-Doped G (BG-1, BG-2, and BOG) \n\n${\\sf H}_{3}{\\sf B}{\\sf O}_{3}$ and graphene oxide with different mass ratios were dispersed in deionized (DI) water under sonication for 1 hr to obtain a uniform mixture. The mixture was frozen overnight, dried, and then heated to $900^{\\circ}\\mathsf{C}$ under a ${\\mathsf H}_{2^{-}}{\\mathsf A}{\\mathsf r}$ atmosphere for 3 hr at a heating rate of $5^{\\circ}C\\cdot\\mathsf{m i n}^{-1}$ . Afterward, the sample was cooled to room temperature naturally. The product was washed in DI water four times to remove the residue of ${\\sf B}_{2}{\\sf O}_{3}$ and dried under a vacuum at $40^{\\circ}\\mathsf{C}$ . BOG was prepared in the same way, except for annealing in Ar gas instead of ${\\mathsf H}_{2}{\\mathsf{-A r}}$ gas. \n\n# Electrochemical Measurements \n\nBefore the NRR tests, Nafion 211 membrane was boiled in $5\\%$ ${\\sf H}_{2}{\\sf O}_{2}$ solution for 1 hr at $80^{\\circ}\\mathsf{C},$ rinsed in DI water, boiled in DI water for $1\\:\\mathrm{hr}$ and then in 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solution for 1 hr at $80^{\\circ}\\mathsf{C}.$ and then rinsed in DI water again. After being rinsed in DI water several times, the membrane was ready for cell fabrication. The electrocatalytic ${\\sf N}_{2}$ reduction reaction was carried out using an Autolab electrochemical workstation in 0.05 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solution with a typical three-electrode system. In brief, a platinum $(\\mathsf{P t})$ foil and a saturated $\\mathsf{A g/A g C l}$ electrode were used as counter and reference electrodes, respectively. All potentials were referred to the RHE by adding a value of $(0.21+0.059\\times\\mathsf{p H})$ V. For the preparation of the working electrode, $5\\mathrm{\\mg}$ of the sample was dispersed in $1\\mathsf{m L}$ of ethanol and $0.12\\mathsf{m L}$ of 5 wt $\\%$ Nafion aqueous solution. The mixed solution was sonicated for $30~\\mathrm{min}$ to form a homogeneous ink. Twenty microliters of the mixed solution was drop cast onto carbon paper with an area of $0.5~\\mathsf{c m}^{2}$ , followed by drying under room temperature. All electrochemical tests were carried out at $25^{\\circ}\\mathsf{C}\\pm1^{\\circ}\\mathsf{C}$ . A flow of ${\\sf N}_{2}$ was swept through the electrolyte during the tests. The electrolyte was $0.05\\mathsf{M}\\mathsf{H}_{2}\\mathsf{S}\\mathsf{O}_{4}$ aqueous solution purged with ${\\sf N}_{2}$ for $0.5\\mathsf{h r}$ before use. For NRR experiments, the potentiostatic test was conducted in ${\\sf N}_{2}$ -saturated 0.05 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solution $\\boldsymbol{30}\\mathrm{mL})$ ). LSV and cyclic voltammetry (CV) were carried out in a voltage window from $-1.1$ to $-0.2\\:\\forall$ versus RHE at scan rates of $1\\mathsf{m}\\mathsf{V}{\\cdot}\\mathsf{s}^{-1}$ and $10\\mathrm{mV}\\cdot\\mathsf{s}^{-1}$ , respectively. All the polarization curves were steady state after several CV cycles. The current density was normalized to the geometrical area. \n\n# Quantification of Ammonia \n\nThe amount of ammonia was measured by the reaction of salicylate and nitroprusside into the intense blue indophenol complex. The colored solutions formed had the absorption peak centered at $660\\ \\mathsf{n m}$ . A $0.1~\\mathrm{\\mg}\\cdot\\mathrm{mL}^{-1}$ stock solution was prepared in 0.05 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solution. The standard solutions were prepared freshly. Sodium salicylate $(5~{\\mathfrak{g}})$ , sodium hydroxide $(1.47~\\mathfrak{g})$ , and potassium sodium tartrate tetrahydrate $(5{\\mathfrak{g}})$ were dissolved in DI water and diluted to $100~\\mathrm{{mL}}$ as the color reagent. Sodium nitroferricyanide $_{(0.1\\ \\mathfrak{g})}$ was dissolved in $10~\\mathrm{mL}$ of water. Different concentrations of ammonium solutions were added to $10\\mathrm{-}m L$ colorimetric tubes. Then, these solutions were mixed with the color reagent, nitroprusside solution, liquid sodium hypochlorite solution, and NaOH solution, and were set aside for 1 hr for full color development. \n\n# Quantification of Hydrazine \n\nThe amount of hydrazine was measured based on the condensation of hydrazine with 4-(dimethylamino)benzaldehyde. The colored solutions formed had the absorption peak centered at $458\\ \\mathsf{n m}$ . A $0.1~\\mathrm{mg}\\cdot\\mathrm{mL}^{-1}$ stock solution of hydrazine monohydrate was prepared in $0.05\\textsf{M}\\mathsf{H}_{2}\\mathsf{S}\\mathsf{O}_{4}$ solution. The standard solutions were prepared freshly. A solution of color reagent was prepared by dissolving $5.99\\mathfrak{g}$ of 4-(dimethylamino) benzaldehyde with a mixture of $30~\\mathrm{mL}$ of HCl solution and $300~\\mathrm{mL}$ of ethyl alcohol. Five milliliters of different concentrations of hydrazine solutions were added into $10\\mathrm{-}\\mathsf{m L}$ colorimetric tubes. Then, these solutions were mixed with $5~\\mathrm{mL}$ of color reagent and were set aside for 20 min for full color development. \n\n# Faradic Efficiency \n\nThe FE of $N H_{3}$ production was calculated using the following equation: $\\mathsf{F E}=3\\mathsf{F}\\times$ $\\mathsf{m}_{\\mathsf{N H}4+}/(18\\times\\mathsf{O})$ , where F is the Faraday constant, $\\mathsf{m}_{\\mathsf{N H4}+}$ is the measured ${\\mathsf{N H}}_{4}^{+}$ mass, and $\\bigcirc$ is the quantity of applied electricity. \n\n# Joule \n\n# Calculation Details \n\nFirst-principles calculations were carried out by using the DFT with the projector augmented wave pseudo-potentials as implemented in the Vienna Ab initio Simulation Package.35 The exchange-correlation functional was described by the Perdew-Burke-Ernzerhof of the generalized gradient approximation (PBEGGA) method.36 The cutoff energy for the plane wave-basis expansion was set to $400~\\mathrm{eV}$ and the convergence criterion was set to $10^{-5}~\\mathsf{e V}$ between two ionic steps for the self-consistency process, and $0.02\\ \\mathrm{eV}/\\mathring{A}$ was adopted for the total energy calculations. The Brillouin zone was set to $3\\times3\\times1$ Monkhorst-Pack k-point mesh. To avoid interactions between adjacent images, a vacuum region of $15\\mathrm{~\\AA~}$ was added along the normal direction to the slab. The Gibbs free energy $(\\Delta\\mathsf{G})$ for all ${\\sf N}_{2}$ reduction reactions on boron structures were defined as follows: \n\n$$\n\\Delta\\mathsf{G}=\\Delta\\mathsf{E}_{\\mathrm{ad}}+\\Delta\\mathsf{E}_{\\mathsf{z p e}}-\\mathsf{T}\\Delta\\mathsf{S}+\\Delta\\mathsf{G}_{\\mathsf{p H}}\n$$ \n\n(Equation 1) \n\nwhere DE, $\\Delta\\mathsf{E}_{z\\mathsf{p e}},\\mathsf{T}\\Delta\\mathsf{S},$ and $\\Delta G_{\\mathsf{p H}}$ are the adsorption energy, zero point energy difference, the entropy difference between the adsorbed state and the gas phase, and the free energy contribution due to the variations in H concentration, respectively; the value of pH was assumed to be zero for acidic medium. For each system of our work, the energy contribution from the configurational entropy in the adsorbed state and the vibrations of every boron-structure are negligible. We assumed that the Gibbs free energy $(\\Delta\\mathsf{G})$ is roughly equal to the adsorption energy $(\\Delta\\mathsf{E}_{\\mathsf{a d}})$ , where the adsorption energy can be directly determined by analyzing the total energies. $\\Delta\\mathsf{E}_{\\mathsf{a d}}$ can be defined as \n\n$$\n\\mathsf{E}_{\\mathrm{ad}}=\\mathsf{E}_{\\mathrm{total}}-\\mathsf{E}_{\\mathsf{s l a b}}-\\mathsf{E}_{\\mathsf{a d s}}\n$$ \n\n(Equation 2) \n\nwhere $\\mathsf{E}_{\\mathrm{total}},\\mathsf{E}_{\\mathsf{s l a b}},$ and $\\mathsf{E}_{\\mathsf{a d s}}$ are the total energies for the different adsorption sites, for the clean slab, and for the adsorbent, respectively. \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information includes Supplemental Experimental Procedures, 16 figures, and five tables and can be found with this article online at https://doi.org/10. 1016/j.joule.2018.06.007. \n\n# ACKNOWLEDGMENTS \n\nWe thank the following funding agencies for supporting this work: the National Key Research and Development Program of China (2017YFA0206901, 2018YFA0209401), the Natural Science Foundation of China (21773036, 21473038), the Key Basic Research Program of Science and Technology Commission of Shanghai Municipality (17JC1400100), and the Collaborative Innovation Center of Chemistry for Energy Materials (2011-iChem). We are thankful for the computational resources provided by the National Supercomputer Center in Changsha, China. \n\n# AUTHOR CONTRIBUTIONS \n\nG.Z. proposed, designed, and supervised the project. G.Z., J.M., X.Y., and Z.W. wrote the manuscript. X.Y., P.H., L.H., Z.G., and S.P. performed the experiments and analyzed the data. Z.W. and J.M. performed the theoretical calculations. G.Z. and J.M. acquired funding support for this project. All the authors discussed, commented on, and revised the manuscript. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: March 19, 2018 \nRevised: April 13, 2018 \nAccepted: June 5, 2018 \nPublished: June 26, 2018 \n\n# REFERENCES \n\n1. Rafiqul, I., Weber, C., Lehmann, B., and Voss, A. (2005). Energy efficiency improvements in ammonia production-perspectives and uncertainties. Energy 30, 2487–2504. \n2. Liu, C., Sakimoto, K.K., Colo´ n, B.C., Silver, P.A., and Nocera, D.G. (2017). Ambient nitrogen reduction cycle using a hybrid inorganicbiological system. Proc. Natl. Acad. Sci. USA 114, 6450–6455. \n3. Kandemir, T., Schuster, M.E., Senyshyn, A., Behrens, M., and Schlogl, R. (2013). The HaberBosch process revisited: on the real structure and stability of ‘‘ammonia iron’’ under working conditions. Angew. Chem. Int. Ed. 52, 12723– 12726. \n4. Renner, J.N., Greenlee, L.F., Herring, A.M., and Ayers, K.E. (2015). Electrochemical synthesis of ammonia: a low pressure, low temperature approach. Electrochem. Soc. 24, 51–57. \n5. Cao, N., and Zheng, G. (2018). Aqueous electrocatalytic ${\\sf N}_{2}$ reduction under ambient conditions. Nano Res. 11, 2992–3008. \n6. Wang, L.L., Liu, X., Luo, J.M., Duan, X.D., Crittenden, J., Liu, C.B., Zhang, S.Q., Pei, Y., Zeng, Y.X., and Duan, X.F. (2017). Selfoptimization of the active site of molybdenum disulfide by an irreversible phase transition during photocatalytic hydrogen evolution. Angew. Chem. Int. Ed. 56, 7610–7614. \n7. Lu, Q.L., Yu, L.F., Ma, Q.L., Chen, B., and Zhang, H. (2016). 2D transition-metaldichalcogenide-nanosheet-based composites for photocatalytic and electrocatalytic hydrogen evolution reactions. Adv. Mater. 28, 1917–1933. \n8. Montoya, J.H., Tsai, C., Vojvodic, A., and Norskov, J.K. (2015). The challenge of electrochemical ammonia synthesis: a new perspective on the role of nitrogen scaling relations. ChemSusChem 8, 2180–2186. \n9. Skulason, E., Bligaard, T., Gudmundsdottir, S., Studt, F., Rossmeisl, J., Abild-Pedersen, F., Vegge, T., Jonsson, H., and Norskov, J.K. (2012). A theoretical evaluation of possible transition metal electro-catalysts for ${\\sf N}_{2}$ reduction. Phys. Chem. Chem. Phys. 14, 1235– 1245. \n10. H ¨oskuldsson, A´ .B., Abghoui, Y., Gunnarsdo´ ttir, A.B., and Sku´ lason, E. (2017). Computational screening of rutile oxides for electrochemical ammonia formation. ACS Sustain. Chem. Eng. 5, 10327–10333. \n11. Abghoui, Y., Garden, A.L., Hlynsson, V.F., Bjorgvinsdottir, S., Olafsdottir, H., and Skulason, E. (2015). Enabling electrochemical reduction of nitrogen to ammonia at ambient conditions through rational catalyst design. Phys. Chem. Chem. Phys. 17, 4909– 4918. \n12. Abghoui, Y., and Skulason, E. (2017). Onset potentials for different reaction mechanisms of nitrogen activation to ammonia on transition metal nitride electro-catalysts. Catal. Today 286, 69–77. \n13. Sangiovanni, D.G., Mei, A.B., Hultman, L., Chirita, V., Petrov, I., and Greene, J.E. (2016). Ab initio molecular dynamics simulations of nitrogen/VN(001) surface reactions: vacancy-catalyzed $\\mathsf{N}_{2}$ dissociative chemisorption, N adatom migration, and $N_{2}$ desorption. J. Phys. Chem. C 120, 12503– 12516. \n14. Li, Q.Y., He, L.Z., Sun, C.H., and Zhang, X.W. (2017). Computational study of MoN2 monolayer as electrochemical catalysts for nitrogen reduction. J. Phys. Chem. C 121, 27563–27568. \n15. Kordali, $\\mathsf{V}_{\\cdot,\\prime}$ Kyriacou, G., and Lambrou, C. (2000). Electrochemical synthesis of ammonia at atmospheric pressure and low temperature in a solid polymer electrolyte cell. Chem. Commun. 0, 1673–1674. \n16. Bao, D., Zhang, $\\Omega.,$ and Meng, F.L. (2017). Electrochemical reduction of ${\\sf N}_{2}$ under ambient conditions for artificial $N_{2}$ fixation and renewable energy storage using N2/NH3 cycle. Adv. Mater. 29, 1604799. \n17. Shi, M.M., Bao, D., and Wulan, B.R. (2017). Au sub-nanoclusters on $T i O_{2}$ toward highly efficient and selective electrocatalyst for ${\\sf N}_{2}$ conversion to $N H_{3}$ at ambient conditions. Adv. Mater. 29, 1606550. \n18. Yao, Y., Zhu, S., Wang, H., Li, H., and Shao, M. (2018). A spectroscopic study on the nitrogen electrochemical reduction reaction on gold and platinum surfaces. J. Am. Chem. Soc. 140, 1496–1501. \n19. Yang, D., Chen, T., and Wang, Z. (2017). Electrochemical reduction of aqueous nitrogen $(\\mathsf{N}_{2})$ at a low overpotential on (110)-oriented Mo nanofilm. J. Mater. Chem. A 5, 18967– 18971. \n20. Chen, S., Perathoner, S., Ampelli, C. Mebrahtu, C., Su, D., and Centi, G. (2017). Electrocatalytic synthesis of ammonia at room temperature and atmospheric pressure from water and nitrogen on a carbon-nanotube based electrocatalyst. Angew. Chem. Int. Ed. 129, 2743–2747. \n21. Chen, S., Perathoner, S., Ampelli, C., Mebrahtu, C., Su, D., and Centi, G. (2017). Room-temperature electrocatalytic synthesis of NH3 from $H_{2}O$ and $N_{2}$ in a gas–liquid–solid three-phase reactor. ACS Sustain. Chem. Eng. 5, 7393–7400. \n22. Lv, C., Yan, C., Chen, G., and Yu, D. (2018). An amorphous noble-metal-free electrocatalyst enables $N_{2}$ fixation under ambient conditions. Angew. Chem. Int. Ed. 130, 6181–6184. \n23. Chen, G.F., Cao, X., and Wu, S. (2017). Ammonia electrosynthesis with high selectivity under ambient conditions via a Li+ incorporation strategy. J. Am. Chem. Soc. 139, 9771–9774. \n24. Liu, Y., Su, Y., and Quan, $x.$ (2018). Facile ammonia synthesis from electrocatalytic ${\\sf N}_{2}$ reduction under ambient conditions on N-doped porous carbon. ACS Catal. 8, 1186– 1191. \n25. Guo, C., Ran, J., Vasileff, A., and Qiao, S.Z. (2018). Rational design of electrocatalysts and photo(electro)catalysts for nitrogen reduction to ammonia $(N H_{3})$ under ambient conditions. Energy Environ. Sci. 11, 45–56. \n26. Jiao, Y., Zheng, $\\Upsilon_{\\cdot,\\cdot}$ Jaroniec, M., and Qiao, S.Z. (2014). Origin of the electrocatalytic oxygen reduction activity of graphene-based catalysts a roadmap to achieve the best performance. J. Am. Chem. Soc. 136, 4394– 4403. \n27. Vineesh, T.V., Kumar, M.P., Takahashi, C., Kalita, G., Alwarappan, S., Pattanayak, D.K. and Narayanan, T.N. (2015). Bifunctional electrocatalytic activity of boron-doped graphene derived from boron carbide. Adv. Energy Mater. 5, 1500658. \n28. Sreekanth, N., Nazrulla, M.Z., Vineesh, T.V., Sailaja, K., and Phani, K.L. (2015). Metal-free boron-doped graphene for selective electroreduction of carbon dioxide to formic acid/formate. Chem. Commun. 51, 16061– 16064. \n29. Guo, D.C., Mi, J., Hao, G.P., Dong, W., Xiong, G., and Li, W. (2013). Ionic liquid C16mimBF4 assisted synthesis of poly(benzoxazine-co-resol)-based hierarchically porous carbons with superior performance in supercapacitors. Energy Environ. Sci. 6, 652–659. \n30. Wang, S., Zhang, L., Xia, Z., Roy, A., Chang, D.W., Baek, J.B., and Dai, L. (2012). BCN graphene as efficient metal-free electrocatalyst for the oxygen reduction reaction. Angew. Chem. Int. Ed. 51, 4209–4212. \n31. Fan, Z.J., Kai, W., Yan, J., Wei, T., Zhi, L., Feng, J., Ren, Y., Song, L., and Wei, F. (2011). Facile \n\n# Joule \n\nsynthesis of graphene nanosheets via Fe reduction of exfoliated graphite oxide. ACS Nano 5, 191–198. \n\n32. Wang, C., Guo, Z.Y., Shen, W., Xu, Q.J., Liu, H.M., and Wang, Y.G. (2014). B-doped carbon coating improves the electrochemical performance of electrode materials for Li-ion batteries. Adv. Funct. Mater. 24, 5511–5521. \n\n33. Ma, H.Q., Shi, Z.Y., Li, Q., and Li, S. (2016). Preparation of graphitic carbon nitride with large specific surface area and outstanding $N_{2}$ photofixation ability via a dissolveregrowth process. J. Am. Chem. Soc. 126, 8576–8584. \n34. Kumar, C.V.S., and Subramanian, V. (2017). Can boron antisites of BNNTs be an efficient metalfree catalyst for nitrogen fixation? - A DFT investigation. Phys. Chem. Chem. Phys. 19, 15377–15387. \n35. Kresse, G., and Hafner, J. (1993). Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561. \n36. Perdew, J.P., Burke, K., and Ernzerhof, M. (1996). Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868. " + }, + { + "id": "10.1038_s41557-018-0092-x", + "DOI": "10.1038/s41557-018-0092-x", + "DOI Link": "http://dx.doi.org/10.1038/s41557-018-0092-x", + "Relative Dir Path": "mds/10.1038_s41557-018-0092-x", + "Article Title": "Dopant-induced electron localization drives CO2 reduction to C2 hydrocarbons", + "Authors": "Zhou, YS; Che, FL; Liu, M; Zou, CQ; Liang, ZQ; De Luna, P; Yuan, HF; Li, J; Wang, ZQ; Xie, HP; Li, HM; Chen, PN; Bladt, E; Quintero-Bermudez, R; Sham, TK; Bals, S; Hofkens, J; Sinton, D; Chen, G; Sargent, EH", + "Source Title": "NATURE CHEMISTRY", + "Abstract": "The electrochemical reduction of CO2 to multi-carbon products has attracted much attention because it provides an avenue to the synthesis of value-added carbon-based fuels and feedstocks using renewable electricity. Unfortunately, the efficiency of CO2 conversion to C-2 products remains below that necessary for its implementation at scale. Modifying the local electronic structure of copper with positive valence sites has been predicted to boost conversion to C-2 products. Here, we use boron to tune the ratio of Cu delta+ to Cu-0 active sites and improve both stability and C-2-product generation. Simulations show that the ability to tune the average oxidation state of copper enables control over CO adsorption and dimerization, and makes it possible to implement a preference for the electrosynthesis of C-2 products. We report experimentally a C-2 Faradaic efficiency of 79 +/- 2% on boron-doped copper catalysts and further show that boron doping leads to catalysts that are stable for in excess of similar to 40 hours while electrochemically reducing CO2 to multi-carbon hydrocarbons.", + "Times Cited, WoS Core": 886, + "Times Cited, All Databases": 924, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000442395200013", + "Markdown": "# Dopant-induced electron localization drives CO2 reduction to $C_{2}$ hydrocarbons \n\nYansong Zhou1,2,10, Fanglin Che1,10, Min Liu1,3,4,10, Chengqin Zou $\\textcircled{1}$ 1, Zhiqin Liang1, Phil De Luna $\\textcircled{1}$ 5, Haifeng Yuan1,6, Jun Li   1,7, Zhiqiang Wang8, Haipeng Xie3, Hongmei $L i^{3}$ , Peining Chen1, Eva Bladt9, Rafael Quintero-Bermudez1, Tsun-Kong Sham8, Sara Bals   9, Johan Hofkens6, David Sinton   7, Gang Chen $\\textcircled{10}2\\star$ and Edward H. Sargent   1\\* \n\nThe electrochemical reduction of $\\pmb{\\ c o_{2}}$ to multi-carbon products has attracted much attention because it provides an avenue to the synthesis of value-added carbon-based fuels and feedstocks using renewable electricity. Unfortunately, the efficiency of $\\pmb{\\mathrm{co}}_{2}$ conversion to $c_{2}$ products remains below that necessary for its implementation at scale. Modifying the local electronic structure of copper with positive valence sites has been predicted to boost conversion to $c_{2}$ products. Here, we use boron to tune the ratio of ${\\bf\\mathbb{C}}{\\bf u}^{\\delta+}$ to ${\\bf c}{\\bf u}^{0}$ active sites and improve both stability and $\\pmb{C}_{2}$ -product generation. Simulations show that the ability to tune the average oxidation state of copper enables control over CO adsorption and dimerization, and makes it possible to implement a preference for the electrosynthesis of $\\pmb{C}_{2}$ products. We report experimentally a $\\pmb{C}_{2}$ Faradaic efficiency of $79\\pm2\\%$ on boron-doped copper catalysts and further show that boron doping leads to catalysts that are stable for in excess of \\~40 hours while electrochemically reducing $\\pmb{\\mathrm{co}}_{2}$ to multi-carbon hydrocarbons. \n\nmong $\\mathrm{CO}_{2}$ reduction products, $\\mathrm{C}_{2}$ hydrocarbons including ethylene $\\mathrm{(C_{2}H_{4})}$ and ethanol $(\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH})$ benefit from impressive energy densities and thus higher economic value per unit \nmass compared with $\\mathrm{C}_{1}$ counterparts1–3. To date, copper is one of the \nmost promising candidates for electroreducing $\\mathrm{CO}_{2}$ to multi-carbon \nhydrocarbons. Previous research has shown that judiciously modified \ncopper is especially selective for $\\mathbf{C}_{2}$ electroproduction $^{4-6}$ ; however, \n$\\mathrm{C}_{1}$ and $\\mathrm{C}_{3}$ species are generated simultaneously4,7. It is of interest to \nmodify copper to narrow the distribution of the products of the elec \ntrochemical reduction of carbon dioxide $(\\mathrm{CO}_{2}\\mathrm{RR}),$ ) ultimately towards \na single class of target hydrocarbons, and achieving such high selectiv \nity combined with high activity is an important frontier for the field. \n\nSurface ${\\mathrm{Cu}}^{\\delta+}$ sites in copper catalysts have been suggested to be active sites for $\\mathrm{CO}_{2}\\mathrm{RR}^{8-10}$ : indeed, high Faradaic efficiencies for $\\mathbf{C}_{2}$ products have been achieved by introducing ${\\mathrm{Cu}}^{\\mathfrak{s}+}$ into copper catalysts11–13. ${\\mathrm{Cu}}^{\\mathfrak{s}+}$ has previously been introduced using oxygencontained species, such as by deriving copper catalysts from oxidized copper14–17. However, the resultant ${\\bar{\\mathrm{Cu}}}^{\\delta+}$ species are prone to being reduced to ${\\mathrm{Cu}}^{0}$ under $\\mathrm{CO}_{2}\\mathrm{RR},$ especially given the high applied reducing potentials needed to electrosynthesize $\\mathbf{C}_{2}$ compounds18. This has made the study of the role of ${\\mathrm{Cu}}^{\\mathfrak{s}+}$ challenging and, at an applied level, it probably contributes to the loss in $\\mathrm{CO}_{2}\\mathrm{RR}$ to multi-carbon performance over the first few hours of reaction19,20. \n\nWe therefore took the view that introducing modifier elements—atoms that could tune and increase the stability of ${\\mathrm{Cu}}^{\\mathfrak{d}+}$ in a lasting fashion, even following protracted $\\mathbf{CO}_{2}\\mathrm{RR}.$ —would contribute to the understanding of $\\mathrm{CO}_{2}$ reduction to $\\mathrm{C}_{2},$ as well as its practical implementation. \n\n# Results and discussion \n\nDensity functional theory (DFT) studies establish boron doping as a promising and stable candidate to modify copper in light of its adsorption behaviour on the $\\mathsf{C u}(111)$ surface (Fig. 1 and Supplementary Fig. 1). By a margin of $0.78\\mathrm{eV},$ it is more favourable for boron to diffuse into the subsurface of a $\\mathrm{Cu}(111)$ slab than for it to remain on the surface (Fig. 1a)21. In addition to studying the boron-modified $\\mathrm{Cu}(111)$ surface, we also examined computationally the boron-doped $\\mathtt{C u}(100)$ surface (see Supplementary Information)—the more thermodynamically favourable surface for producing $\\mathbf{C}_{2}$ products during $\\mathrm{CO}_{2}\\mathrm{RR}$ . The results show that the subsurface sites are more favourable than the top or bridge adsorption sites. In contrast, oxygen is—by a margin of $1.5\\mathrm{eV}.$ —adsorbed on the $\\mathrm{Cu}(111)$ surface rather than diffusing into the subsurface22. Together, these findings suggest that boron doping could offer a strategy for stable modulation of the copper catalyst. \n\nWe queried the projected density of states (PDOS) of $\\mathrm{Cu}_{3d}$ and $\\mathrm{C}_{2p}$ and carried out Bader charge analysis to investigate the electronic properties of boron-doped copper. When boron is doped into the subsurface of the copper slab, it exhibits a higher overlap among the binding states between $\\mathrm{C}_{2p}$ and $\\mathrm{Cu}_{3d}$ when CO adsorbs on the surface (Supplementary Figs. 4 and 5) compared with pristine copper, leading to a stronger binding energy of CO over a boron-doped copper surface. The d-band centre of the nearby copper atom shifts away from the Fermi level compared with pristine copper. This indicates that copper atoms adjacent to boron are more positively charged (Fig. 1a). The PDOS result agrees with Bader charge analysis: copper transfers electrons to boron, resulting in a positively charged copper oxidation state, indicating that the changes in the oxidation state of copper include the interaction between boron and copper, as well as the surface geometrical changes. Consequently, the boron-doped copper $\\operatorname{\\mathrm{(Cu(B))}}$ system has both ${\\mathrm{Cu}}^{\\mathfrak{d}+}$ and ${\\mathrm{Cu}}^{0}$ regions, exhibiting a motif analogous to the $\\mathrm{{Cu}}_{2}\\mathrm{{O}}/\\mathrm{{Cu}}$ catalyst reported by Goddard et al.8. \n\n![](images/0302a63a333863ace63d951e4027b443c2f0ff8ef0dafbdaf8b298a64bb60efd.jpg) \nFig. 1 | DFT calculations on enhancing $\\mathsf{C}_{2}$ electroproduction. a, PDOS plot of $\\mathsf{C u}_{3d}$ and $\\mathsf C_{2p}$ orbitals in pure copper and boron-doped copper catalysts, suggesting CO has greater electronic interaction with copper in the $\\mathsf{C u}(\\mathsf{B})$ system. b, The CO adsorption energy $(E_{\\mathrm{ad}})$ is monotonically increased as the partial positive oxidation state of copper is increased. MAE, mean absolute error. c, The $C O=C O$ dimerization energy as a function of the average adsorption energy of two adsorbed CO molecules. This shows that an ‘optimal’ average adsorption energy of CO $(\\sim0.8\\substack{-1.0\\mathsf{e V}})$ can improve $\\mathsf{C O}{=}\\mathsf{C O}$ dimerization during ${\\mathsf{C O}}_{2}{\\mathsf{R R}}.$ . d, When the ‘optimal’ average adsorption energy of CO is ${\\sim}0.8{-}1.0\\mathsf{e V},$ a larger difference in the $E_{\\mathrm{ad}}$ values of two CO molecules further enhances $\\mathsf{C O}{=}\\mathsf{C O}$ dimerization. In b–d, 1[B], 2[B], 3[B], 4[B] and 8[B] refer to boron-doped copper catalysts with subsurface boron concentrations of 1/16, 1/8, 3/16, 1/4 and 1/2 monolayer, respectively. \n\nWe then simulated the Gibbs free energy of two key reaction pathways for a catalyst comprising boron-doped copper (1/16 monolayer) (Supplementary Fig. 10). We compared $\\mathrm{CO}_{2}$ reduction with $\\mathbf{C}_{1}$ (for example, methane) versus $\\mathrm{C}_{2}$ products (for example, $\\mathrm{C_{2}H_{4}}$ and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH})$ at $298\\mathrm{K}$ and 1 atm. The boron dopant suppresses the reaction path of $\\mathrm{CO}_{2}{\\rightarrow}\\mathrm{C}_{1}$ , increasing the reaction energy requirements for the (rate-limiting) $\\mathrm{CO^{*}+H^{*}{\\rightarrow}C H O^{*}}$ step. Furthermore, it enhances $\\mathrm{CO}_{2}{\\rightarrow}\\mathrm{C}_{2}$ by decreasing the reaction energy required for the rate-limiting $\\mathrm{CO^{*}+C O^{*}\\to O C C O^{*}}$ step. \n\nWe then proceeded to tune, still in computational studies, the partial copper oxidation state from $-0.1\\mathrm{e}$ to $+0.3\\mathrm{e}$ by varying the copper facets (that is, Cu(100), Cu(111), $\\operatorname{Cu}(110)$ or ${\\mathrm{Cu}}(211)$ ), changing the concentration of boron dopants (from 1/16 monolayer to 1/2 monolayer, as shown in Supplementary Fig. 4 and Supplementary Table 1) and providing a range of applied external electric fields (Fig. 1b). The CO adsorption energy increases monotonically as the copper oxidation state is increased. A volcano plot of the energy for the $\\scriptstyle{\\mathrm{CO=CO}}$ dimerization (the rate-limiting step for ${\\mathrm{CO}}_{2}{\\rightarrow}{\\mathrm{C}}_{2}$ ) as a function of the average CO adsorption energy $\\begin{array}{r}{\\left(E_{\\mathrm{ad}_{\\mathrm{avg}}}^{\\mathrm{-}}=\\frac{E_{\\mathrm{ad}}(\\mathrm{CO}_{1s t})+E_{\\mathrm{ad}}(\\mathrm{CO}_{2\\mathrm{nd}})}{2}\\right)}\\end{array}$ (Fig. 1c) indicates that—per the Sabatier principle—optimized average binding energies $(\\sim0.8\\mathrm{-}1.0\\mathrm{eV})$ of two CO molecules improve $\\scriptstyle{\\mathrm{CO=CO}}$ dimerization and thus support the generation of $\\mathrm{C}_{2}$ products. When we applied a range of external electric fields and charged the surface23–26 via the Neugebauer and Scheffler method27, we found that the volcano plot of the $\\scriptstyle{\\mathrm{CO=CO}}$ dimerization retains its profile and overall trends (Supplementary Fig. 11). Furthermore, when the optimal average binding energies of two CO molecules are achieved, a larger difference in the adsorption energies of these two CO molecules $(\\Delta E_{\\mathrm{ad}}=|E_{\\mathrm{ad}}\\left(\\mathrm{CO_{\\mathrm{1st}}}\\right)-\\bar{E_{\\mathrm{ad}}}\\left(\\mathrm{CO_{\\mathrm{2nd}}}\\right)\\bar{|})$ further enhances $\\mathrm{CO}=$ CO dimerization (Fig. 1d). To increase $\\mathbf{C}_{2}$ production during the $\\mathrm{CO}_{2}\\mathrm{RR}$ process, an optimal average oxidation state $(\\sim8^{0.2+})$ for copper is desired and is driven by providing a local admixture of two different oxidation states of copper ( $\\langle{\\delta}^{0}$ and ${{\\delta}^{+}}$ ). We find similar results on the (100) surface: boron-doped copper has a higher propensity to form $\\mathbf{C}_{2}$ products compared with pristine copper (see Supplementary Information). Taken together, these computational simulations point towards boron doping as a strategy to enhance $\\mathrm{C}_{2}$ production. \n\nIn light of these findings, we sought to synthesize boron-doped copper (Fig. 2a). The as-synthesized sample is of the cubic copper phase (Joint Committee on Powder Diffraction Standards (JCPDS) number 85-1326) with a dominant (111) peak (Supplementary Fig. 13). The $\\operatorname{Cu}({\\mathrm{B}})$ sample has a porous dendritic morphology with nanostructured features on the scale of $30{-}40\\mathrm{nm}$ (Supplementary Fig. 14). The presence of boron in $\\operatorname{Cu}({\\mathrm{B}})$ samples was confirmed using X-ray photoelectron spectroscopy (XPS) (Fig. 2b and Supplementary Fig. 15). Other elements including sodium and chlorine were not detected before or after reaction (Supplementary Figs. 16 and 17), suggesting that only boron is incorporated into copper during the synthesis. The presence of boron in $\\operatorname{Cu}(\\mathrm{B})$ samples was further confirmed using inductively coupled plasma optical emission spectroscopy (ICP-OES) (Fig. 2c and Supplementary Fig. 18). We found the boron concentration inside the copper samples to be tunable when we varied the amount of the $\\mathrm{CuCl}_{2}$ precursor (Supplementary Table 8). \n\nWe sought to probe the distribution, as a function of depth within the copper-based catalyst, of the incorporated boron. We employed time-dependent ICP-OES (Fig. 2c), which revealed that the boron concentration drops from $5.7\\%$ (B/Cu atomic ratio) to \n\n![](images/e2fc15f020a6d57aea4a8531ee935d1cbc59b7f39f29202f4ac4dd58942cfff8.jpg) \nFig. 2 | Preparation and characterization of $\\mathsf{C u}(\\mathsf{B})$ . a, Schematic of the wetchemical process to synthesize $\\mathsf{C u}(\\mathsf{B})$ samples. b,c, Boron XPS spectrum (magenta circle, raw data; blue line, fitted peak plot; cyan line, background) (b) and dissolving-time-dependent boron concentrations of the $\\mathsf{C u}(\\mathsf{B})$ sample as measured by ICP-OES (c), indicating that boron is present on the surface of copper. The error bars represent the standard deviation of the results of three separate channels for each sample. \n\n$2.7\\%$ over an estimated depth of $7.5\\mathrm{nm}$ . We found that the boron concentration is highest within $2.5\\mathrm{nm}$ of the surface of the copper catalyst (Supplementary Fig. 19). \n\nWe used ultraviolet photoelectron spectroscopy to investigate the impact of boron doping on the electronic states of copper. We found that boron doping produces a shift in the valence band to a deeper level, in agreement with computational simulations (Supplementary Fig. 20). We then used $\\mathrm{\\DeltaX}$ -ray absorption near-edge spectroscopy (XANES) to further investigate the impact of boron incorporation on the copper oxidation state. To exclude oxygen-containing species, we electrochemically reduced the $\\operatorname{Cu}(\\mathrm{B})$ samples by applying a highly negative potential ( $_{-0.5}$ to $-2\\mathrm{V}$ versus reversible hydrogen electrode (RHE), $0.1\\mathrm{V}\\mathrm{s}^{-1}$ , 5 cycles). The absorption edges of all the $\\operatorname{Cu}({\\mathrm{B}})$ samples reside between those of pristine copper $(\\mathrm{Cu^{0}})$ and $\\mathrm{{Cu}}_{2}\\mathrm{{O}}$ $\\mathrm{(Cu^{1+})}$ (Fig. 3a and Supplementary Fig. 21). To give a direct comparison of the oxidation state of copper in the $\\operatorname{Cu}(\\mathrm{B})$ samples, we acquired the copper oxidation state as a function of copper K-edge energy shift (Fig. 3b). The average oxidation state of copper in the $\\operatorname{Cu}({\\mathrm{B}})$ samples is found to vary from 0 to $+1$ as a function of the energy shift (Supplementary Table 9). The average oxidation state of copper increased from 0.25 to 0.78 as the boron concentration varied from 1.3 to $2.2\\%$ . \n\nWe investigated the oxidation state of samples under $\\mathrm{CO}_{2}\\mathrm{RR}$ using in situ XANES. The oxidation state of copper increases with boron content under $\\mathbf{CO}_{2}\\mathrm{RR}$ (Supplementary Fig. 22). To directly compare the copper oxidation state changes during the $\\mathbf{CO}_{2}\\mathrm{RR}$ process, copper XANES spectra of $\\operatorname{Cu}(\\mathrm{B})-2$ at different time points (immediately after cyclic voltammetry (CV) reduction, and 15 and $30\\mathrm{min}$ later) relative to the onset of $\\mathrm{CO}_{2}\\mathrm{RR}$ were recorded (Fig. 3c). We found the average oxidation state of copper in $\\mathrm{Cu}(\\mathrm{B}){\\-}2$ during the in situ measurements to be $+0.32$ , which is similar to the value obtained from the ex situ XANES results of $\\mathrm{Cu}(\\mathrm{B}){\\-}2$ (0.35). These results indicate we observed a stable slightly positive oxidation state for copper in the $\\operatorname{Cu}(\\mathrm{B})$ samples over the course of $\\mathrm{CO}_{2}\\mathrm{RR}$ (Supplementary Fig. 23). \n\nNext, we sought to verify whether the copper oxidation state correlated with total $\\mathbf{C}_{2}$ Faradaic efficiency (Fig. 4a). When we plotted the experimental $\\mathbf{C}_{2}$ Faradaic efficiency versus the experimental average copper oxidation state, we obtained a volcano plot that peaks with an impressive Faradaic efficiency of $79\\pm2\\%$ at an average copper valence of $+0.35$ , showing agreement with our DFT predictions. \n\n![](images/2c65c103e9967af76becddc63a02f98d1db83a6ecd73338e0b93d7964a5db868.jpg) \nFig. 3 | Oxidation state of copper in $\\mathsf{C u}(\\mathsf{B})$ samples. a, Copper K-edge XANES spectra of $\\mathsf{C u}(\\mathsf{B})$ samples after being electrochemically reduced. b, Average oxidation state of copper in $\\mathsf{C u}(\\mathsf{B})$ with different contents of boron obtained from copper K-edge XANES, suggesting that the oxidation states of copper in $\\mathsf{C u}(\\mathsf{B})$ samples are tunable. The error bars represent the standard deviation of three separate measurements for each sample. c, In situ copper K-edge XANES spectra of $C u(B)-2$ immediately after CV reduction (orange), 15 min later (dark yellow) and $30\\mathsf{m i n}$ later (magenta). Pristine copper (red) and $C\\mathsf{u}_{2}\\mathsf{O}$ (purple) are included as references. The edge position of each sample is determined from the intercept of the main edge and pre-edge contributions. \n\n
Table1|Summaryof thecurrent density and product distributions overCu(B)-2and controlsamples using 0.1MKClasan electrolyte under their respective optimal potentials
Sample J(mA cm-2)a Faradaic efficiency (%)a
HCH4CH4HCOOH CH5OHCH,OH
Cu(B)-27020±20.0852±227±10
Cu(H)51 44±210±18±122±16±18±12±0.5
Cu(C)7066.48±16±133±22±0.514±14±0.5
\n\naThese values were obtained under the optimal potentials for ${\\mathsf C}_{2}$ of each sample $(\\mathsf{C u}(\\mathsf{B})-2\\colon-1.1\\vee$ versus RHE; $\\mathsf{C u}(\\mathsf{H})$ : −​1.0 V versus RHE; $\\mathsf{C u}(\\mathsf{C})\\colon$ −​1.0 V versus RHE) \n\nAs controls, we also produced pristine copper $\\mathrm{{Cu}(H))}$ , which was synthesized following a previously reported procedure based on hydrazine hydrate28. We also produced reference catalysts that consisted of oxidized nano-copper $\\mathrm{(Cu(C))}$ (Supplementary Fig. 24). The Faradaic efficiencies for $\\mathbf{C}_{2}$ were $29\\pm2\\%$ for $\\mathrm{{Cu(H)}}$ and $37\\pm2\\%$ for $\\mathrm{Cu(C)}$ under their respective optimal potentials for $\\mathbf{C}_{2}$ electroproduction. The extreme selectivity of the boron-doped catalyst in favour of $\\mathbf{C}_{2}$ over $\\mathbf{C}_{1}$ is particularly striking: we achieved a maximum selectivity ratio of $\\mathbf{C}_{2}{:}\\mathbf{C}_{1}$ of 932 (Supplementary Table 10). Improved selectivity of $\\mathbf{C}_{2}$ over $\\mathbf{C}_{1}$ was further achieved on boron-doped $\\mathrm{Cu}(111)$ single crystals (Supplementary Table 11) and in ${\\mathrm{K}}_{2}{\\mathrm{HPO}}_{4}$ electrolyte (Supplementary Table 12), indicating the generalizable concept that boron stabilizes the oxidation state of copper and drives electrochemical reduction of $\\mathrm{CO}_{2}$ to $\\mathbf{C}_{2}$ products. \n\nThe improved performance of the boron-doped catalyst is accompanied by a reduced onset potential for $\\mathbf{C}_{2}$ hydrocarbon electroproduction: $-0.57\\mathrm{V}$ (versus RHE) (Fig. 4c and Supplementary Fig. 25) for the best samples— $0.1\\mathrm{V}$ and $0.18\\mathrm{V}$ lower than those of $\\mathrm{Cu(C)}$ and $\\mathrm{{Cu(H)}}$ , respectively. \n\nThe presence of ${\\mathrm{Cu}}^{\\delta+}$ sites on the copper surface is also predicted to increase the energy requirement for direct reduction of $\\mathrm{CO}_{2}$ to methane. For the $\\operatorname{Cu}(\\mathrm{B})-2$ sample, the onset potential of methane is determined to be $-1.1\\mathrm{V}$ (versus RHE), which is $0.1\\mathrm{V}$ higher than those of $\\mathrm{Cu(C)}$ and $\\mathrm{{Cu(H)}}$ $(-1.0\\mathrm{V}$ versus RHE). Interestingly, less than $0.5\\%$ of methane was detected during potentials ranging from $-0.6$ to $-1.2\\mathrm{V}$ (versus RHE). Moreover, only a slight increase of methane Faradaic efficiency $(0.3\\%)$ was observed when we increased the potential by $0.1\\mathrm{V}$ over and above the onset potential of methane. In contrast, the corresponding methane Faradaic efficiency increase was found to be ${\\sim}2.0\\%$ for the $\\mathrm{Cu(C)}$ and $\\mathrm{{Cu(H)}}$ samples (Supplementary Fig. 25). \n\nIn summary, the direct reduction of $\\mathrm{CO}_{2}$ to methane is almost completely suppressed on the $\\mathrm{Cu}(\\mathrm{B}){\\-}2$ sample. The onset potential of $\\mathrm{CO}_{2}\\mathrm{RR}$ to $\\mathrm{C}_{2}$ hydrocarbons decreases to $-0.57\\mathrm{V}$ versus RHE while that for methane is substantially higher at $-1.1\\mathrm{V}$ versus RHE, showing a more favourable potential window for ethylene production. \n\nThe conversion efficiency of $\\mathrm{CO}_{2}$ to $\\mathbf{C}_{2}$ products increases dramatically as the applied voltage is rendered even more negative, towards $-0.9\\mathrm{V}$ versus RHE (Fig. 4b). The high $\\mathrm{C}_{2}$ selectivity is maintained over a wide potential window that spans $-0.9$ to $-1.2\\mathrm{V}$ versus RHE. The maximum Faradaic efficiency to ethylene $(53\\pm1\\%)$ is achieved at $-1.0\\mathrm{V}$ versus RHE, which is $0.1\\mathrm{V}$ lower than the onset potential for methane, accounting for the excellent selectivity of ethylene over methane in gas products (Supplementary Fig. 26). \n\nNarrowing the product distribution is desired in the electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ process. The product distributions for the $\\mathrm{Cu}(\\mathrm{B}){\\-}2$ sample versus the control samples were further investigated (Supplementary Fig. 27). Ethylene and ethanol are the major hydrocarbons from $\\mathrm{CO}_{2}\\mathrm{RR}$ on $\\mathrm{Cu}(\\mathrm{B}){-}2$ , with a maximum Faradaic efficiency for $\\mathrm{C}_{2}$ products of $79\\pm2\\%$ and less than $0.1\\%$ of $\\mathrm{C}_{1}$ product (Table 1 and Supplementary Figs. 28 and 29) at $-1.1\\mathrm{V}$ versus RHE. Similar promoting effects that have the effect of narrowing the product distribution were also observed on other samples with different boron-doping concentrations (Supplementary Table 13). In contrast, in the case of the control samples, we obtained $\\mathrm{C}_{1}$ products with Faradaic efficiency of $24\\pm1\\%$ $\\mathrm{(Cu(H))}$ and $16\\%$ $\\mathrm{(Cu(C))}$ at their optimized applied potentials for the formation of $\\mathbf{C}_{2}$ products (Table 1). The ratios were $\\mathrm{C}_{2}/\\mathrm{C}_{1}{=}1.2$ for $\\mathrm{{Cu(H)}}$ and $\\mathrm{C_{2}}/\\mathrm{C_{1}}{=}2.3$ for $\\mathrm{Cu(C)}$ . Formic acid and $\\mathrm{C}_{3}$ products were not detected on the $\\operatorname{Cu}(\\mathrm{B})-2$ sample (Supplementary Figs. 30 and 31). Thus, the $\\operatorname{Cu}(\\mathrm{B})$ sample selectively generates $\\mathbf{C}_{2}$ products with a narrow product distribution. \n\nPartial current density reports the activity of an electrocatalyst. A partial current density $J_{\\scriptscriptstyle\\mathrm{C}2}$ of $10\\mathrm{mAcm}^{-2}$ is achieved for the case of the $\\operatorname{Cu}(\\mathrm{B})-2$ sample when the applied potential is $-0.74\\mathrm{V}.$ This is much lower than the potentials to reach this same current for the cases of $\\mathrm{Cu(C)}$ $(-0.90\\mathrm{V}$ versus RHE) and $\\mathrm{{Cu(H)}}$ ( $_{-0.95}$ versus RHE). \n\nWe obtained a maximum $J_{\\mathrm{C}2}$ $(55\\mathrm{mAcm^{-2}})$ ) when operating the $\\mathrm{Cu}(\\mathrm{B}){\\-}2$ sample at $-1.1\\mathrm{V}$ versus RHE. This is 3.7 and 1.7 times higher than the maximum $J_{\\mathrm{{C}}2}$ for $\\mathrm{{Cu(H)}}$ and $\\mathrm{Cu(C)}$ , respectively. We also report the current density normalized to the electrochemically active surface area (ECSA) (Supplementary Table 14 and Supplementary Figs. 32–34). Once the current is renormalized to the ECSA, the peak $J_{\\mathrm{C}2}$ value is 3.0 and 1.9 times higher than those of the $\\mathrm{{Cu(H)}}$ and $\\mathrm{Cu(C)}$ cases. \n\nWe investigated charge transfer processes at the electrode/electrolyte interface using electrochemical impedance spectroscopy. Compared with $\\mathrm{{Cu(H)}}$ and $\\mathrm{Cu(C)}$ , the diameter of the Nyquist circle for $\\operatorname{Cu}(\\mathrm{B})-2$ is the smallest, indicating an acceleration in the charge transfer process between $\\mathrm{Cu}(\\mathrm{B}){-}2$ and electrolyte (Supplementary Fig. 35). The improved charge transfer process reveals the low activation energy for the reactions on $\\mathrm{Cu}(\\mathrm{B}){\\-}2$ which is further confirmed by linear sweep voltammetry and related Arrhenius plots (Supplementary Fig. 36). These results confirm the stability of the ${\\mathrm{Cu}}^{\\mathfrak{d}+}$ sites and corroborate the ${\\mathrm{Cu}}^{0}$ and ${\\mathrm{Cu}}^{\\mathfrak{s}+}$ favourability of the $\\operatorname{Cu}({\\mathrm{B}})$ surface for the electroproduction of $\\mathrm{C}_{2}$ hydrocarbons. \n\nLong-term stability remains a challenge for copper or modified copper despite their effectiveness in the electroreduction of $\\mathrm{CO}_{2}$ to multi-carbon hydrocarbons. We found that pristine copper $\\mathrm{{'Cu(H))}}$ shows only modest stability for $\\mathrm{CO}_{2}\\mathrm{RR}$ to ethylene following $6\\mathrm{h}$ of operation (Supplementary Fig. 37). $\\mathrm{Cu(C)}$ shows slightly higher durability over this same time period (Fig. 4d). \n\nThe boron-doped copper showed superior stability, achieving $40\\mathrm{{h}}$ of continuous operation at $-1.1\\mathrm{V}$ versus RHE (Supplementary Fig. 38) without loss of performance. This indicates that boron is stable as a dopant in copper (Supplementary Figs. 39–41). The ${\\mathrm{Cu}}^{\\delta+}$ sites induced by boron doping are stable at high applied potential during the $\\mathrm{CO}_{2}\\mathrm{RR}$ process (Fig. 3c), enabling its relative stability in performance. \n\n![](images/b43e093addda93e967e87d59f617991ecb7b9b54f74a3069d44fc25ce5da9bfb.jpg) \nFig. 4 $|\\mathsf{C O}_{2}\\mathsf{R R}$ performance on $\\mathsf{C u}(\\mathsf{B})$ and control samples. a, Faradaic efficiency of ${\\mathsf C}_{2}$ and $C_{1}$ at different copper oxidation states on $\\mathsf{C u}(\\mathsf{B})$ . All samples were tested using the same potential of $-1.1\\vee$ versus RHE. b, Conversion efficiency of reacted ${\\mathsf{C O}}_{2}$ to ${\\mathsf C}_{2}$ and $C_{1}$ products at different potentials on $C u(B)-2$ . c, Partial current density of ${\\mathsf C}_{2}$ at different potentials on Cu(B)-2, $\\mathsf{C u}(\\mathsf{C})$ and ${\\mathsf{C u}}({\\mathsf{H}}).{\\mathsf{d}},$ Faradaic efficiency of ethylene on Cu(B)-2, $\\mathsf{C u}(\\mathsf{C})$ and $\\mathsf{C u}(\\mathsf{H})$ . The boron-doped copper catalyst showed the highest selectivity, conversion efficiency and partial current density of ${\\mathsf C}_{2}$ hydrocarbons. Error bars represent the standard deviation of three separate measurements for an electrode. \n\n# Conclusion \n\nIn summary, highly selective $\\mathbf{C}_{2}$ products from $\\mathbf{CO}_{2}\\mathrm{RR}$ were obtained on boron-doped copper with stable electron localization. The electroreduction of $\\mathrm{CO}_{2}$ to $\\mathbf{C}_{2}$ hydrocarbons, and its link with the oxidation state of copper, were theoretically and experimentally confirmed. At the average copper valence state of $+0.35$ , a high Faradaic efficiency for $\\mathbf{C}_{2}$ hydrocarbons of ${\\sim}80\\%$ was achieved. Under these conditions, $\\mathrm{C}_{1}$ products are completely suppressed in both gas and liquid products. Boron-doped copper showed superior stability for $\\mathrm{CO}_{2}\\mathrm{RR}$ to $\\mathrm{C}_{2},$ achieving ${\\sim}40\\mathrm{h}$ of initial sustained efficient operation. \n\n# Methods \n\nDFT calculations. DFT calculations were performed using Vienna Ab initio Simulation Package code29,30. Full computational simulation details are provided in the Supplementary Information. \n\nPreparation of catalyst samples. $\\operatorname{Cu}(\\mathrm{B})$ samples were prepared through a facile one-step process using copper(II) chloride $\\mathrm{(CuCl}_{2}\\mathrm{)}$ and sodium borohydride $\\mathrm{(NaBH_{4})}$ as precursors. Since boron solubility in copper is low, $\\mathrm{CuCl}_{2}$ was added into highly concentrated sodium borohydride solution instantly in order to alloy the boron with copper at as high loading as possible31,32. First, $\\mathrm{CuCl}_{2}$ and $\\mathrm{NaBH_{4}}$ were prepared using frozen water $({\\sim}0^{\\circ}\\mathrm{C})$ . Next, $2\\mathrm{ml}\\mathrm{CuCl_{2}}$ solution with a certain concentration was injected rapidly into the $\\mathrm{NaBH_{4}}$ $5\\mathrm{M},2\\mathrm{ml})$ solution until no bubbles formed. The precipitates obtained were subsequently washed three times with $150\\mathrm{ml}$ of water $50\\mathrm{ml}$ each time) and once with $50\\mathrm{ml}$ of acetone to completely remove the unreacted precursors and other possible byproducts. Then, the powder was immediately dried under vacuum overnight. Different amounts of $\\mathrm{CuCl}_{2}$ (namely, $400\\mathrm{mg}$ for $\\mathrm{{Cu}(B)\\mathrm{{-}1}}$ , $300\\mathrm{mg}$ for $\\mathrm{Cu}(\\mathrm{B}){-}2$ , $200\\mathrm{mg}$ for $\\operatorname{Cu}(\\mathrm{B})$ -3, $100\\mathrm{mg}$ for $\\mathrm{Cu(B)\\mathrm{-}4}$ and $25\\mathrm{mg}$ for $\\mathrm{Cu}(\\mathrm{B}){-}5)$ were used. The control sample $\\mathrm{{Cu(H)}}$ was synthesized following a similar procedure but using an equal amount of hydrazine hydrate instead of $\\mathrm{NaBH_{4}}$ as the reducing reagent. Some $25\\mathrm{nm}$ partially oxidized nano-copper (Sigma) was also used as a control sample in this work. \n\nThe boron-doped $\\mathrm{Cu}(111)$ surface sample was synthesized by incipient wetness impregnation of single-crystal $\\mathrm{Cu}(111)$ foil with boric acid aqueous solutions. After impregnation, the copper foil was dried and then calcinated at $500^{\\circ}\\mathrm{C}$ in $\\mathrm{\\mathrm{H}}_{2}/\\mathrm{Ar}$ gas (5 vol.% $\\mathrm{H}_{2}$ ) for 6 h. The presence of boron was confirmed by XPS testing (Supplementary Fig. 42). \n\nECSA measurement. All electrodes were electrochemically reduced using the CV method $(-0.5\\mathrm{V}$ to $^{-2}$ versus RHE, $0.1\\mathrm{V}\\mathrm{\\mathsf{s}}^{-1}$ , 5 cycles) before ECSA measurements. The lead under-potential deposition method was used to estimate the ECSA of boron-doped copper and control samples. Briefly, a freshly prepared $50\\mathrm{ml}$ solution containing $100\\mathrm{mM}$ of $\\mathrm{HClO_{4}}$ with $0.5\\mathrm{mM}$ of $\\mathrm{PbCl}_{2}$ and $50\\mathrm{mM}$ KCl was used. Next, the electrode was held at $-0.375\\mathrm{V}$ for $10\\mathrm{min}$ before the stripping of lead by sweeping the potential from $-0.5$ to $-0.1\\mathrm{V}$ (versus $\\mathrm{Ag/AgCl)}$ at $10\\mathrm{mVs^{-1}}$ . The copper ECSA calculations assume a monolayer of lead adatom coverage over copper and $2e^{-}$ lead oxidation with a conversion factor of $310\\upmu\\mathrm{C}\\mathrm{cm}^{-2}$ . \n\nThe ECSA values of the as-made electrodes were also evaluated by CV using the ferri-/ferrocyanide redox couple $\\mathrm{[Fe(CN)_{6}]^{3-/4-}}\\}$ as a probe. Cyclic voltammetry was carried out in a nitrogen-purged 5 mM $\\mathrm{K}_{3}\\mathrm{Fe(CN)}_{6}/0.1\\mathrm{M}$ KCl solution with platinum gauze as the counter electrode. ECSA values were calculated using the Randles–Sevcik equation:9 \n\n$$\nI_{\\mathrm{p}}{=}(2.36{\\times}10^{5})n^{3/2}A D^{1/2}C\\nu^{1/2}\n$$ \n\n$I_{\\mathrm{p}}$ is peak current (A), $n=1$ , $D{=}4.34{\\times}10^{-6}\\mathrm{cm}^{2}s^{-1}$ , A is the electrochemical active surface area $(\\mathrm{cm}^{2})$ , $C$ is the concentration of potassium ferricyanide $(5\\times10^{-6}\\mathrm{molcm^{-3}},$ ) and $\\nu$ is the scan rate $(5\\mathrm{mVs^{-1}};$ . \n\nCharacterization. The crystal structures of the samples were characterized with a powder X-ray diffractometer (MiniFlex600) using $\\operatorname{Cu}\\ K\\upalpha$ ​radiation $(\\lambda{=}0.15406\\mathrm{nm}$ ). A scanning electron microscope (Hitachi SU8230) and electron tomography in a transition electron microscope (TEM) (FEI Tecnai G2) were employed to observe the morphology of the samples. A tilt series of two-dimensional TEM images for electron tomography was acquired from $-75$ to $+75^{\\mathrm{o}}$ with a tilt increment of $3^{\\mathrm{o}}$ at $200\\mathrm{kV}.$ The series was used as an input for three-dimensional reconstruction using the SIRT algorithm implemented in the ASTRA toolbox33. XPS measurements were carried out on a K-Alpha XPS spectrometer (PHI 5700 ESCA System) using Al Kα​X-ray radiation $(1,486.6\\mathrm{eV})$ \n\nfor excitation. The line of carbon C1s with the position at $284.6\\mathrm{eV}$ was used as a reference to correct the charging effect. Ultraviolet photoelectron spectroscopy spectra were measured using He I excitation $(21.2\\mathrm{eV})$ with a SPECS PHOIBOS 150 hemispherical energy analyser in the ultrahigh vacuum chamber of the XPS instrument. Angle-dependent XPS measurements were also carried out using this same XPS instrument. ICP-OES (Optima 7300 DV) was carried out to determine the boron contents doped into copper. In total, $\\mathrm{1\\mg}$ of the samples was completely dissolved into $50\\mathrm{ml}$ trace metal ${\\mathrm{HNO}}_{3}$ $(5\\mathrm{mM})$ using a sonication bath for $30\\mathrm{min}$ for the ICP-OES test. Dissolving-time-dependent ICP-OES experiments were carried out by withdrawing $10\\mathrm{ml}$ of the solution at time 0 $(\\sim10s)$ , 2 min, $5\\mathrm{{min}}$ , $10\\mathrm{min}$ and $30\\mathrm{min}$ . Ex situ X-ray absorption measurements at the copper K-edges were performed at the 20-BM-B beamline at the Advanced Photon Source (APS) at Argonne National Laboratory. In situ X-ray absorption spectroscopy (XAS) measurements at the copper K-edges were performed at the Soft X-ray Microcharacterization Beamline 06B1-1 at Canadian Light Source (CLS). \n\nPreparation of cathode electrodes. The catalyst ink was prepared by ultrasonic dispersion of $10\\mathrm{mg}$ of the sample powder with $20\\upmu\\mathrm{l}$ Nafion solution $(5\\%)$ in $\\mathrm{1ml}$ methanol for $30\\mathrm{min}$ . Next, ${5\\upmu\\mathrm{l}}$ of the as-prepared ink was drop-coated on the glass carbon electrode with a surface area of $0.07\\mathrm{cm}^{2}$ . The electrode was then dried under methanol atmosphere slowly for the subsequent electrochemical testing experiments. \n\nCatalytic evaluation. All $\\mathrm{CO}_{2}$ reduction experiments were performed in a gas-tight two-compartment H-cell separated by an ion exchange membrane (Nafion117). The anode and cathode sides were filled with $55\\mathrm{ml}$ of 0.1 M ${\\mathrm{KHCO}}_{3}$ and $0.1\\mathrm{M}\\mathrm{KCl},$ respectively. The reaction was performed at constant iR-corrected potential. First, the cathode side was electrochemically reduced using the CV method, which ranged from $-0.5$ to $-2.0\\mathrm{V}$ (versus RHE) at a rate of $0.1\\mathrm{V}\\mathrm{s}^{-1}$ for 5 cycles to completely reduce the possible oxidized species. The gas products from $\\mathrm{CO}_{2}$ reduction were analysed using the gas chromatograph (PerkinElmer Clarus 600) equipped with thermal conductivity and flame ionization detectors. The liquid samples were collected and analysed by NMR instruments by taking (Agilent DD2 500) dimethylsulfoxide as a reference. The potential (versus $\\mathrm{Ag/AgCl})$ was converted to RHE using the following equations: \n\n$$\n\\begin{array}{r l}&{E_{\\mathrm{RHE}}=E_{\\mathrm{AgCl}}+0.059~\\mathrm{pH}+E_{\\mathrm{AgCl}}^{0}}\\\\ &{E_{\\mathrm{AgCl}}^{0}~(3.0~\\mathrm{M}~\\mathrm{KCl})=0.209~\\mathrm{V}(25~^{\\circ}\\mathrm{C})}\\end{array}\n$$ \n\nData availability. The data supporting the findings of this study are available within the article and its Supplementary Information files. All other relevant source data are available from the corresponding author upon request. \n\nReceived: 2 October 2017; Accepted: 29 May 2018; Published: xx xx xxxx \n\n# References \n\n1.\t Farrell, A. E. et al. Ethanol can contribute to energy and environmental goals. Science 311, 506–508 (2006). \n2.\t Hill, J., Nelson, E., Tilman, D., Polasky, S. & Tiffany, D. Environmental, economic, and energetic costs and benefits of biodiesel and ethanol biofuels. Proc. Natl Acad. Sci. USA 103, 11206–11210 (2006). \n3.\t Bushuyev, O. S. et al. What should we make with $\\mathrm{CO}_{2}$ and how can we make it?. Joule 5, 825–832 (2017). \n4.\t Loiudice, et al. Tailoring copper nanocrystals towards $\\mathbf{C}_{2}$ products in electrochemical $\\mathrm{CO}_{2}$ reduction. Angew. Chem. Int. Ed. 55, 5789–5792 (2016). \n5.\t Mistry, H. et al. Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene. Nat. Commun. 7, 12123 (2016). \n6.\t Yano, H., Tanaka, T., Nakayama, M. & Ogura, K. Selective electrochemical reduction of $\\mathrm{CO}_{2}$ to ethylene at a three-phase interface on copper(I) halide-confined Cu-mesh electrodes in acidic solutions of potassium halides. J. Electroanal. Chem. 565, 287–293 (2004). \n7.\t Kuhl, K. P., Cave, E. R., Abram, D. N. & Jaramillo, T. F. New insights into the electrochemical reduction of carbon dioxide on metallic copper surfaces. Energy Environ. Sci. 5, 7050 (2012). \n8.\t Xiao, H., Goddard, W. A. 3rd, Cheng, T. & Liu, Y. Cu metal embedded in oxidized matrix catalyst to promote $\\mathrm{CO}_{2}$ activation and CO dimerization for electrochemical reduction of $\\mathrm{CO}_{2}$ . Proc. Natl Acad. Sci. USA 114, 6685–6688 (2017). \n9.\t Allen, J. & Bard, L. R. F. Electrochemical Methods: Fundamentals and Applications (Wiley, New York, NY, 2000). \n10.\tDe Luna, P. et al. Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction. Nat. Catal. 1, 103–110 (2018). \n11.\tRen, D. et al. Selective electrochemical reduction of carbon dioxide to ethylene and ethanol on copper(I) oxide catalysts. ACS Catal. 5, 2814–2821 (2015). \n12.\tLee, S. & Lee, J. Electrode build-up of reducible metal composites toward achievable electrochemical conversion of carbon dioxide. ChemSusChem 9, 333–344 (2016). \n13.\tEilert, A., Roberts, F. S., Friebel, D. & Nilsson, A. Formation of copper catalysts for $\\mathrm{CO}_{2}$ reduction with high ethylene/methane product ratio investigated with in situ X-ray absorption spectroscopy. J. Phys. Chem. Lett. 7, 1466–1470 (2016). \n14.\t Li, C. W. & Kanan, M. W. $\\mathrm{CO}_{2}$ reduction at low overpotential on Cu electrodes resulting from the reduction of thick $\\mathrm{{Cu}_{2}O}$ films. J. Am. Chem. Soc. 134, 7231–7234 (2012). \n15.\tRoberts, F. S., Kuhl, K. P. & Nilsson, A. High selectivity for ethylene from carbon dioxide reduction over copper nanocube electrocatalysts. Angew. Chem. Int. Ed. 127, 5268–5271 (2015). \n16.\tGao, D. et al. Plasma-activated copper nanocube catalysts for efficient carbon dioxide electroreduction to hydrocarbons and alcohols. ACS Nano 11, 4825–4831 (2017). \n17.\tFavaro, M. et al. Subsurface oxide plays a critical role in $\\mathrm{CO}_{2}$ activation by $\\mathrm{Cu}(111)$ surfaces to form chemisorbed $\\mathrm{CO}_{2}$ , the first step in reduction of $\\mathrm{CO}_{2}$ . Proc. Natl Acad. Sci. USA 114, 6706–6711 (2017). \n18.\tLee, S., Kim, D. & Lee, J. Electrocatalytic production of $\\mathrm{C}_{3}–\\mathrm{C}_{4}$ compounds by conversion of $\\mathrm{CO}_{2}$ on a chloride-induced bi-phasic $\\mathrm{Cu}_{2}\\mathrm{O-Cu}$ catalyst. Angew. Chem. Int. Ed. 54, 14701–14705 (2015). \n19.\tLarrazabal, G. O., Martin, A. J., Krumeich, F., Hauert, R. & Perez-Ramirez, J. Solvothermally-prepared $\\mathrm{{Cu}}_{2}\\mathrm{{O}}$ electrocatalysts for $\\mathrm{CO}_{2}$ reduction with tunable selectivity by the introduction of $\\mathsf{p}$ -block elements. ChemSusChem 10, 1255–1265 (2017). \n20.\tGrace, A. N. et al. Electrochemical reduction of carbon dioxide at low overpotential on a polyaniline $/\\mathrm{Cu}_{2}\\mathrm{O}$ nanocomposite based electrode. Appl. Energy 120, 85–94, (2014). \n21.\tTrinh, Q. T., Banerjee, A., Yang, Y. H. & Mushrif, S. H. Sub-surface boron-doped copper for methane activation and coupling: first-principles investigation of the structure, activity, and selectivity of the catalyst. J. Phys. Chem. C 121, 1099–1112 (2017). \n22.\tSoon, A., Todorova, M., Delley, B., & Stampfl, C. Oxygen adsorption and stability of surface oxides on $\\mathrm{Cu}(111)$ : a first-principles investigation. Phys. Rev. B 73, 165424 (2006). \n23.\tGoodpaster, J. D., Bell, A. T. & Head-Gordon, M. Identification of possible pathways for C–C bond formation during electrochemical reduction of $\\mathrm{CO}_{2}$ : new theoretical insights from an improved electrochemical model. J. Phys. Chem. Lett. 7, 1471–1477 (2016). \n24.\tMontoya, J. H., Peterson, A. A. & Nørskov, J. K. Insights into C–C coupling in $\\mathrm{CO}_{2}$ electroreduction on copper electrodes. ChemCatChem 5, 737–742 (2013). \n25.\tCheng, T., Xiao, H. & Goddard, W. A. III Free-energy barriers and reaction mechanisms for the electrochemical reduction of CO on the $\\mathrm{Cu}(100)$ surface, including multiple layers of explicit solvent at pH 0. J. Phys. Chem. Lett. 6, 4767–4773 (2015). \n26.\tFilhol, J. S. & Neurock, M. Elucidation of the electrochemical activation of water over Pd by first principles. Angew. Chem. Int. Ed. 45, 402–406 (2006). \n27.\tNeugebauer, J. & Scheffler, M. Adsorbate–substrate and adsorbate–adsorbate interactions of Na and K adlayers on Al(111). Phys. Rev. B 46, 16067–16080 (1992). \n28.\tGawande, M. B. et al. Cu and Cu-based nanoparticles: synthesis and applications in catalysis. Chem. Rev. 116, 3722–3811 (2016). \n29.\tKresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993). \n30.\tKresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mat. Sci. 6, 15–50 (1996). \n31.\tMassalski, T. B., Okamoto, H., Subramanian, P. R. & Kacprzak, L. Binary Alloy Phase Diagrams 2nd edn (ASM International, OH, 1990). \n32.\tCarenco, S., Portehault, D., Boissiere, C., Mezailles, N. & Sanchez, C. Nanoscaled metal borides and phosphides: recent developments and perspectives. Chem. Rev. 113, 7981–8065 (2013). \n33.\tVan Aarle, W. et al. The ASTRA Toolbox: a platform for advanced algorithm development in electron tomography. Ultramicroscopy 157, 35–47 (2015). \n\n# Acknowledgements \n\nThis work was supported financially by funding from TOTAL S.A., the Ontario Research Fund: Research Excellence Program, the Natural Sciences and Engineering Research Council of Canada, the CIFAR Bio-Inspired Solar Energy programme, a University of Toronto Connaught grant, the Ministry of Science, Natural Science Foundation of China (21471040, 21271055 and 21501035), the Innovation-Driven Plan in Central South University project (2017CX003), a project from State Key Laboratory of Powder Metallurgy in Central South University, the Thousand Youth Talents Plan of China and Hundred Youth Talents Program of Hunan and the China Scholarship Council programme. This work benefited from the soft X-ray microcharacterization beamline at CLS, sector 20BM at the APS and the Ontario Centre for the Characterisation of Advanced Materials at the University of Toronto. H.Y. acknowledges financial support from the \n\nResearch Foundation-Flanders (FWO postdoctoral fellowship). C.Z. acknowledges support from the International Academic Exchange Fund for Joint PhD Students from Tianjin University. P.D.L. acknowledges financial support from the Natural Sciences and Engineering Research Council in the form of the Canada Graduate Scholarship—Doctoral award. S.B. and E.B. acknowledge financial support from the European Research Council (ERC Starting Grant #335078-COLOURATOMS). The authors thank B. Zhang, N. Wang, C. T. Dinh, T. Zhuang, J. Li and Y. Zhao for fruitful discussions, as well as Y. Hu and Q. Xiao from CLS, and Z. Finfrock and M. Ward from APS for their help during the course of study. Computations were performed on the SOSCIP Consortium’s Blue Gene/Q computing platform. SOSCIP is funded by the Federal Economic Development Agency of Southern Ontario, the Province of Ontario, IBM Canada, Ontario Centres of Excellence, Mitacs and 15 Ontario academic member institutions. \n\n# Author contributions \n\nE.H.S. and G.C. supervised the project. Y.Z. and M.L. conceived the idea, designed the experiments and analysed the results. Y.Z. synthesized the samples, performed the electrochemical experiments and analysed the results. F.C. carried out the simulations and wrote the corresponding section. M.L., P.C. and P.D.L. conducted the XAS measurements. J.L., Z.W., T.-K.S. and D.S. assisted in analysing the XAS results. C.Z., \n\nY.Z. and Z.L. ran the NMR tests. M.L. and C.Z. carried out the scanning electron microscope measurements. Y.Z. and H.Y. designed the ICP-OES experiments. C.Z. performed the ICP-OES tests. Z.L. ran the X-ray diffractometer tests. R.Q.-B., H.X. and H.L. performed the XPS measurements. E.B. conducted the TEM measurements. E.B., H.Y., S.B. and J.H. assisted in analysing the TEM results. All authors read and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41557-018-0092-x. \n\nReprints and permissions information is available at www.nature.com/reprints. Correspondence and requests for materials should be addressed to G.C. or E.H.S. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1038_s41560-018-0219-8", + "DOI": "10.1038/s41560-018-0219-8", + "DOI Link": "http://dx.doi.org/10.1038/s41560-018-0219-8", + "Relative Dir Path": "mds/10.1038_s41560-018-0219-8", + "Article Title": "Visualization and suppression of interfacial recombination for high-efficiency large-area pin perovskite solar cells", + "Authors": "Stolterfoht, M; Wolff, CM; Márquez, JA; Zhang, SS; Hages, CJ; Rothhardt, D; Albrecht, S; Burn, PL; Meredith, P; Unold, T; Neher, D", + "Source Title": "NATURE ENERGY", + "Abstract": "The performance of perovskite solar cells is predominulltly limited by non-radiative recombination, either through trap-assisted recombination in the absorber layer or via minority carrier recombination at the perovskite/transport layer interfaces. Here, we use transient and absolute photoluminescence imaging to visualize all non-radiative recombination pathways in planar pintype perovskite solar cells with undoped organic charge transport layers. We find significant quasi-Fermi-level splitting losses (135 meV) in the perovskite bulk, whereas interfacial recombination results in an additional free energy loss of 80 meV at each individual interface, which limits the open-circuit voltage (V-oc) of the complete cell to similar to 1.12 V. Inserting ultrathin interlayers between the perovskite and transport layers leads to a substantial reduction of these interfacial losses at both the p and n contacts. Using this knowledge and approach, we demonstrate reproducible dopant-free 1 cm(2) perovskite solar cells surpassing 20% efficiency (19.83% certified) with stabilized power output, a high V-oc (1.17 V) and record fill factor (>81%).", + "Times Cited, WoS Core": 814, + "Times Cited, All Databases": 846, + "Publication Year": 2018, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000446724600014", + "Markdown": "# Visualization and suppression of interfacial recombination for high-efficiency large-area pin perovskite solar cells \n\nMartin Stolterfoht1,6\\*, Christian M. Wolff   1,6, José A. Márquez2, Shanshan Zhang1,3, Charles J. Hages2, Daniel Rothhardt1, Steve Albrecht4, Paul L. Burn3, Paul Meredith5, Thomas Unold2\\* and Dieter Neher1\\* \n\nThe performance of perovskite solar cells is predominantly limited by non-radiative recombination, either through trap-assisted recombination in the absorber layer or via minority carrier recombination at the perovskite/transport layer interfaces. Here, we use transient and absolute photoluminescence imaging to visualize all non-radiative recombination pathways in planar pintype perovskite solar cells with undoped organic charge transport layers. We find significant quasi-Fermi-level splitting losses $(135\\mathrm{meV})$ in the perovskite bulk, whereas interfacial recombination results in an additional free energy loss of $\\mathbf{80meV}$ at each individual interface, which limits the open-circuit voltage $(v_{\\mathrm{oc}})$ of the complete cell to \\~1.12 V. Inserting ultrathin interlayers between the perovskite and transport layers leads to a substantial reduction of these interfacial losses at both the $p$ and n contacts. Using this knowledge and approach, we demonstrate reproducible dopant-free $1\\mathsf{c m}^{2}$ perovskite solar cells surpassing $20\\%$ efficiency ( $19.83\\%$ certified) with stabilized power output, a high $\\pmb{v_{\\mathrm{oc}}}$ (1.17 V) and record fill factor $(>81\\%)$ . \n\nhe solution processability and potential for simple manufacturing from earth-abundant materials drives research into perovskite solar cells in the search for cheap, printable photovoltaic devices. The discovery that perovskites effectively sensitize titanium dioxide $\\left(\\mathrm{TiO}_{2}\\right)$ in dye-sensitized solar cells in $2009^{1}$ , and the demonstration of the first thin-film solid-state perovskite solar cells in $2012^{2,3}$ has spurred tremendous research efforts concerning the understanding and optimization of perovskite-based optoelectronic devices. Though power conversion efficiencies (PCEs) of perovskite solar cells4 are rapidly approaching industrially engineered silicon and inorganic thin-film solar cells5, several key issues remain that need to be understood and overcome. These include fundamental questions regarding recombination losses6, long-term stability7 and difficulties in scaling to large electrode areas8. Today it is well known that to unlock the full thermodynamic potential of perovskite solar cells it is imperative to suppress all non-radiative recombination losses, which manifest as increased dark currents and ideality factors greater than one, limiting both the cells’ open-circuit voltage $(V_{\\mathrm{oc}})^{}$ and fill factor6,9. One of the most challenging tasks in this regard is being able to pinpoint the origin of these losses in a complete device under operational conditions. In general, recombination losses may occur either in the perovskite bulk4,6,10 or close to the interface of an adjacent transport layer as a result of a higher density of trap states at the surface11,12. Likewise, recombination may also occur across interfaces13–15 between charges in the transport layer and minority carriers in the perovskite, or in the transport layers themselves15. The situation becomes more challenging for cells with a comparatively large area (for example, $1\\mathrm{cm}^{2},$ ), where additional losses come from inhomogeneities of the active perovskite absorber as well as at the interfaces to the transport layers, with transport \n\nresistances also becoming an issue8. Knowing the origin of the non-radiative recombination losses would greatly facilitate targeted improvements in device performance13. This is particularly relevant for planar perovskite devices in the pin configuration, which still lag behind the most efficient nip cells4,11,16–19 due to their lower opencircuit voltage and higher non-radiative recombination losses (for example, $1.15\\mathrm{V}$ for record pin cells11 compared to more than $1.23\\mathrm{V}$ for nip cells13,17). Nevertheless, pin-type cells are very attractive for single-junction solar cells as they require only ultrathin undoped charge transport layers (for example, $8\\mathrm{nm}$ poly[bis(4-phenyl) (2,4,6-trimethylphenyl)amine] (PTAA), $30\\mathrm{nm}~\\mathrm{C}_{60})^{9}$ without the need for extensive chemical doping9 and annealing at temperatures above $100^{\\circ}\\mathrm{C}$ . This renders their fabrication compatible with rollto-roll deposition on flexible plastic substrates. Moreover, a pin perovskite device architecture is required for $\\mathrm{Si}/$ perovskite tandem applications in combination with well-established solar cell technologies based on p-type silicon20,21. Thus, a detailed investigation of non-radiative recombination losses and which interface represents the bottleneck for cell efficiency is urgently needed. \n\nWe use a combination of steady-state and time-resolved photoluminescence (PL and TRPL) measurements to pinpoint the origin of non-radiative recombination losses in pin-type perosvkite solar cells. In particular, we determine the recombination kinetics and quasi-Fermi-level splitting (QFLS) in sample stacks consisting of the perovskite absorber-only, and perovskite/charge transport layer heterojunctions on length scales relevant to our solar cells $(1\\mathsf{c m}^{2})$ . We identify the main limitation to higher performance to be minority carrier recombination at the heterojunction with the organic charge transport layers. These losses are found to be surprisingly similar at the electron- and hole-selective interfaces. We therefore optimized the hole-selective interface through the use of a conjugated polyelectrolyte, which almost entirely suppressed interfacial recombination while simultaneously improving the wetting of the perovskite solution on the hole transport layer surface, delivering reproducible $1\\mathrm{cm}^{2}$ devices. With the knowledge that the $V_{\\mathrm{OC}}$ of the final device is now largely defined by the QFLS of the inferior perovskite $\\mathrm{\\DeltaC_{60}}$ heterojunction we introduced an ultrathin layer of LiF $(0.6\\mathrm{-}1\\mathrm{nm})$ between the absorber and the electron transport layer. This allowed us to reduce the interfacial recombination loss at the electron-selective interface by $35\\mathrm{meV.}$ Suppressing the nonradiative recombination at both interfaces directly resulted in critical $V_{\\mathrm{OC}}$ and fill factor improvements in complete devices, allowing $1\\mathrm{cm}^{2}$ cells with ${\\sim}20\\%$ efficiency, stabilized maximum power output and high reproducibility. This is currently the highest certified efficiency for a published $1\\mathrm{cm}^{2}$ perovskite solar cell structure. Last, numerical simulations highlight the importance of interface optimizations versus bulk optimizations for further perovskite solar cell developments. \n\n# Device architecture \n\nOur work builds on recent advancements in the understanding and improvement of pin devices11,19,22. The chemical structures of PTAA, perovskite and $\\mathrm{C}_{60}$ as used in our standard cells with architecture [(indium tin oxide, ITO ( $150\\mathrm{nm}\\cdot$ )/PTAA $(8\\mathrm{nm})$ /perovskite $(400-$ $500\\mathrm{nm})/\\mathrm{C}_{60}$ $\\left(30\\mathrm{nm}\\right)$ /bathocuproine, BCP $(8\\mathrm{{nm})/C u(100\\mathrm{{nm})]}}$ are shown in Fig. 1a. For the active layer material, we chose the previously reported ‘triple cation perovskite’ mixture with the composition $\\mathrm{Cs\\\"PbI_{0.05}[(F A P b I_{3})_{0.89}(M A P b B r_{3})_{0.11}]_{0.95}},$ as it delivers among the best photovoltaic performance. We note that though we focus on triple cation cells we have also generalized the results to methylammonium lead iodide $\\mathbf{MAPbI}_{3}$ and caesium formamidinium lead iodide $(\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.95})\\mathrm{PbI}_{3}$ absorber layers, as discussed at the end of the manuscript. Figure 1b displays a schematic energy level diagram based on the results from ultraviolet and inverse photoemission spectroscopy15, and proposes possible recombination mechanisms. \n\nOne of the most important considerations for scaling the device area is the electrode architecture, due to the relatively high sheet resistance of the transparent conducting electrode (TCE)8. It is thus essential to minimize the distance carriers have to traverse through the comparatively high resistance electrode (that is, ITO versus copper). Figure 2a shows the current–voltage characteristics of optimized $1\\mathrm{cm}^{2}$ cells with electrode widths of $8\\mathrm{mm}$ and $4\\mathrm{mm}$ , which demonstrate that the fill factor can be increased from $69\\%$ to $77.9\\%$ simply by reducing the width of the active area. This is also in agreement with numerical solutions of the Shockley equation for different electrode aspect ratios, as illustrated in Fig. 2b, which confirm a roughly $2\\%$ absolute efficiency gain through the fill factor (Supplementary Fig. 1). This approach is in principle scalable, as the rectangular cells can be connected using laser patterning23 while the electrode width may be slightly increased using a lower-resistance ITO substrate (for instance, $10\\Omega\\mathrm{sq}^{-1}.$ ). \n\n# Non-radiative recombination losses \n\nAmong the most widely used and trusted techniques in the community to study the fate of photogenerated charges in perovskite solar cells is $\\mathrm{TRPL}^{24,25}$ . At sufficiently low fluences a mono-exponential decay is usually observed, indicative of an underlying non-radiative trap-induced recombination that gradually reduces the density of emitting species, and hence the PL signal6,10,26. The fluence dependence of the TRPL signals is illustrated in Supplementary Fig. 2. Figure 3 shows the result of such an experiment on a neat perovskite film, which displays a long PL lifetime of approximately half a microsecond, comparable to previously reported16 perovskite films on $\\mathrm{TiO}_{2}$ . Considerably longer lifetimes have been reported in exceptional cases; for example, a lifetime of ${8\\upmu\\mathrm{s}}$ was recently realized through surface passivation of the perovskite with tri- $\\cdot n$ -octyl­ phosphine $(\\mathrm{TOPO})^{26}$ . As demonstrated6, the achievable $V_{\\mathrm{OC}}$ in the case of dominant Shockley–Read–Hall (SRH) recombination can be predicted from the monoexponential carrier lifetime $(\\tau_{\\mathrm{SRH}})$ . As we detail in Supplementary Note 1, a SRH lifetime of 500 ns (as deduced from the exponential PL decay of the neat perovskite layer) should limit the open-circuit voltage to approximately $1.215\\mathrm{V}$ at room temperature. The measured $V_{\\mathrm{OC}}$ of the device is significantly lower, which suggests that addition of the charge transport layers induces substantial non-radiative recombination losses. \n\nFigure 3 demonstrates the large impact of the addition of charge transporting layers on the TRPL decay, which is consistent with other previously reported studies16. Notably, large reductions in PL lifetimes are seen independent of whether the PTAA is added between the glass and the active material or coated on top of the perovskite film (on glass), indicating that differences in perovskite morphology related to the nature of the underlying substrate are of minor importance in determining the PL lifetime (see Supplementary Fig. 3). Interestingly, all samples comprising one or two transport layers exhibited a similar and fast bi-exponential decay. As pointed out previously6,27, this may be due either to the rapid extraction of charges on (sub)nanosecond timescales (quenching) or increased non-radiative recombination losses—two processes that are inherently difficult to disentangle from the TRPL signal alone. However, unless one transport layer completely depletes the perovskite bulk of one carrier type, the impact of non-radiative interface recombination will still be visible in the signal. As the bulk recombination happens at rather long timescales (lifetimes of approximately 500 ns), it can be concluded that the TRPL signals from the films with the transport layers present are subjected to additional non-radiative interface recombination. Following this line of reasoning, we attribute the fast initial decay to the loss of carriers at the interfaces due to charge extraction to the transport layers and/or to interface recombination, and the second decay (for which the mono-exponential lifetimes are provided in Fig. 3) to interface recombination. In accordance with this, the initial decay becomes less pronounced and smeared out when increasing the excitation wavelength— that is, when light penetrates deeper into the perovskite layer (see Supplementary Fig. 2). The rather similar decays after the initial drop in the samples with either PTAA or $\\mathrm{C}_{60}$ indicate that the two perovskite/organic heterojunctions equally limit the $V_{\\mathrm{OC}}$ due to additional non-radiative recombination losses at the interfaces. After carriers reach a quasi-equilibrium distribution, the lifetime of the second decay $(\\tau_{\\mathrm{II}})$ can be described by an equilibrium between the bulk decay time $(\\tau_{\\mathrm{bulk}})$ , the diffusion time to the surface $\\scriptstyle\\left({\\frac{4d^{2}}{\\pi^{2}D}}\\right)$ and interface loss velocity $(S_{1})$ , that is, $\\begin{array}{r}{\\frac{1}{\\tau_{\\mathrm{II}}}=\\frac{1}{\\tau_{\\mathrm{bulk}}}+\\left(\\frac{4d^{2}}{\\pi^{2}D}+\\frac{d}{S_{1}}\\right)^{-1}}\\end{array}$ , where $d$ is the perovskite film thickness and $D$ the diffusion constant24,27. Using the bulk lifetime of 500–785 ns, a mobility of $30\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ (ref. 28), $d=400\\mathrm{nm}$ and the measured $\\tau_{\\mathrm{II}}$ value of 20–30 ns would result in an interface loss velocity of $S_{1}\\sim1.6\\times10^{3}–2.1\\times10^{3}\\mathrm{cm}s^{-1}$ at the interface between the charge transport layer and the perovskite. However, other processes may potentially influence the TRPL signal as well, such as a decelerating charge extraction, light-soaking effects29, photon recycling24,25, or a graded generation profile. Thus, it is clear that though TRPL is a useful guide to recombination losses, it by no means provides a definitive mechanistic insight. \n\n![](images/829c9352113f11a08f15c8ab2e8b4daefba9e63079ed8bccd50a7028902fe6d6.jpg) \nFig. 1 | Schematic device architecture and energetics. a, Cross-section of a full device comprising, from bottom to top: the glass and transparent conducting electrode (ITO), the hole-selective polymeric layer of PTAA, the perovskite absorber layer, the electron selective ${\\sf C}_{60}$ layer and the metallic top electrode (copper). Chemical structures are shown for PTAA, ${\\mathsf C}_{60}$ and a schematic perovskite crystal structure. The violet sphere represents ${\\mathsf{P b}}^{2+},$ and the blue sphere represents I–. b, Schematic energy level diagram and pathways of non-radiative recombination via traps in the perovskite bulk or at the interfaces as a minority carrier loss. Also shown is the extraction of majority carriers to the transport layers, the quasi-Fermi levels of electrons $(E_{\\mathfrak{r},\\mathtt{e}})$ and holes $(E_{\\mathfrak{r},\\mathfrak{h}}),$ the resulting quasi-Fermi-level splitting $\\langle\\Delta E_{\\mathsf{F},\\mathsf{p e r o}}\\rangle$ in the perovskite, and the recombination-limited $V_{\\mathrm{OC}}$ VBM, valence band maximum; CBM, conduction band minimum; HOMO, highest occupied molecular orbital; LUMO, lowest unoccupied molecular orbital. \n\n![](images/3bfae55f6e77629d02be86bc8e8a595a51bf65e2188ee67478d4051c3a9dca9b.jpg) \nFig. 2 | Optimization of electrode design. a, Experimental $J-V$ curves of $\\mathsf{1c m^{2}}$ cells comprising a PTAA/perovskite $\\prime C_{60}$ stack with different electrode aspect ratios. Reducing the active area width from $8\\mathsf{m m}$ (aspect ratio 0.64) to $4\\mathsf{m m}$ (aspect ratio 0.16) while keeping the active area the same improved the fill factor by approximately $9\\%$ , as indicated by the arrow. b, Simulated solar cell efficiencies using a combination of optical simulations of the obtainable short-circuit current, and the Shockley equation with a finite ITO series resistance depending on its thickness and the device aspect ratio. An internal cell resistance of $1.5\\Omega\\mathsf{c m}^{2}$ (for a $1{\\mathsf{c m}}^{2}$ cell) and an ideality factor of approximately 1.5 were assumed, as previously determined9. The two circled points correspond to the two devices from a. \n\n![](images/d026747ad9d82f0773f2c96f64fb212358d99b387754b6bedab0c69bd7940026.jpg) \nFig. 3 | Impact of transport layers on kinetics of charge recombination. Mono-exponential TRPL decay of a neat perovskite film indicating the dominance of trap-assisted recombination in the bulk or the surface. The corresponding mono-exponential lifetime is around 500 ns, potentially allowing a $V_{\\mathrm{OC}}$ of 1.215 V (see Supplementary Note 1) if no additional interface recombination losses were present. The TRPL signals of perovskite/transport layer heterojunctions show a bi-exponential decay, indicating rapid charge extraction and interfacial recombination on different timescales. The films were illuminated at $470\\mathsf{n m}(\\mathsf{-}30\\mathsf{n J}\\mathsf{c m}^{-2})$ through the organic layer, and through ${\\mathsf C}_{60}$ in the case of the pin stack. \n\n# Photoluminescence and QFLS \n\nA much more direct way to quantify the additional non-radiative recombination losses at the perovskite/organic interfaces is steadystate PL, as the absolute PL intensity $(I_{\\mathrm{pL}})$ is a direct measure of the QFLS (or $\\Delta E_{\\mathrm{F}})^{30-35}$ . Here, we use hyperspectral absolute photoluminescence imaging to create depth-averaged maps of the QFLS on the neat perovskite films in comparison to multilayer samples comprising one or both types of transport layer. This approach has been recently used by El-Hajje et al.31 to spatially resolve the opto-electronic quality of evaporated methylammonium lead iodide junctions, and to study the hole blocking of different electron transport layers. Moreover, absolute PL has been recently applied to disentangle interfacial and bulk recombination losses in nip cells by Sarritzu et al.33, though the QFLS was not compared to the device voltage, and thus open-circuit voltage losses were not directly quantified. As recently discussed32, there are different approaches to calculate $\\Delta E_{\\mathrm{{F}}}$ from absolute PL spectra, which are all based on Würfel’s generalized Planck law30, which describes the non-thermal radiation of a semiconductor: \n\n$$\nI_{\\mathrm{PL}}\\left(E\\right)=\\frac{2\\pi E^{2}a\\left(E\\right)}{h^{3}c^{2}}\\frac{1}{\\exp{\\left(\\frac{E-\\Delta E_{\\mathrm{F}}}{k_{\\mathrm{B}}T}-1\\right)}}\n$$ \n\nHere, $a(E)$ is the photon energy $(E)$ -dependent absorptivity, $c$ is the speed of light, $h$ is the Planck constant and $k_{\\mathrm{{B}}}$ is the Boltzmann constant. Under the assumption that for emission energies above the PL maximum, $a(E)$ approaches unity, equation (1) can be simplified to \n\n$$\n\\ln\\left(\\frac{I_{\\mathrm{PL}}\\left(E\\right)h^{3}c^{2}}{2\\pi E^{2}}\\right)=-\\frac{E}{k_{\\mathrm{B}}T}+\\frac{\\Delta E_{\\mathrm{F}}}{k_{\\mathrm{B}}T}\n$$ \n\nEquation (2) allows one to deduce $\\Delta E_{\\mathrm{{F}}}$ simply from fitting the high-energy slope of the PL emission36. By applying equation (2) to every spectrum associated with each pixel ( $10\\upmu\\mathrm{m}$ in diameter) of the hyperspectral images, $\\Delta E_{\\mathrm{{F}}}$ distribution maps can be created. Figure 4 shows the depth-averaged QFLS maps $(1\\thinspace{\\mathrm{cm}}^{2})$ of the neat triple cation perovskite film, with either PTAA or $\\mathrm{C}_{60}$ alone, or both transport layers being present. The perovskite absorber exhibits a homogenous profile with a QFLS of approximately $1.21\\mathrm{eV}$ (we note a $20\\mathrm{meV}$ global systematic error on all maps). Though this value is remarkably close to the $V_{\\mathrm{OC}}$ obtained from the TRPL lifetime according to Supplementary Note 1, it is substantially below the radiative $V_{\\mathrm{OC}}$ of approximately $1.345\\mathrm{eV.}$ The latter was estimated from the dark generation current $J_{\\mathrm{0,rad}}\\approx4\\times10^{-21}\\mathrm{Acm}^{-2}$ (see Supplementary Fig. 4). This approach for calculating the radiative $V_{\\mathrm{OC}}$ limit has been extensively applied to perovskite solar cells, as shown in refs 37–39, and dates back to Shockley and Queisser40. We also note that the emitted PL can be influenced by photon recy$\\mathrm{cling^{24,25}}$ . However, this does not affect our conclusions, because it is the external PL quantum yield that determines the QFLS and maximum achievable device $V_{\\mathrm{OC}}$ (ref. 41). Figure 4 also shows that the QFLS of the perovskite $\\mathrm{{'C}_{60}}$ film is reduced to approximately $1.136\\mathrm{eV}\\pm10\\mathrm{mV}$ and the PTAA/perovskite film exhibits a QFLS of approximately $1.125\\mathrm{eV}\\pm10\\mathrm{mV}.$ It is important to note that, compared to the neat absorber material with a PL quantum yield of ${\\sim}0.5\\%$ , addition of PTAA or $\\mathrm{C}_{60}$ results in a large reduction of the average photoluminescence efficiency (for example, $0.017\\%$ for a perovskite $/\\mathrm{C}_{60}$ film), which also means a large increase in the nonradiative loss current (approximately 30-fold in case of perovskite/ $\\mathrm{C}_{60}$ compared to the neat absorber material). Yet, despite the different nature of these two interfaces, the non-radiative recombination losses at both interfaces are surprisingly similar (lowering the QFLS by ${\\sim}80\\mathrm{meV}$ compared to the neat absorber), which is consistent with the TRPL results. For the (unoptimized) pin stack (glass/PTAA/perovskite $/C_{60,}^{}$ ) we obtain a $\\Delta E_{\\mathrm{{F}}}$ of approximately $1.121\\mathrm{V}\\pm10\\mathrm{mV},$ which perfectly matches the average $V_{\\mathrm{OC}}$ in complete cells under comparable illumination intensities (see below). Interestingly, this value lies only slightly below the QFLS of samples with only one transport layer present, which indicates that the non-radiative recombination losses at each individual interface are both reducing the $I_{\\mathrm{PL}}(E)$ , yet the QFLS only through the logarithm in equation (2). We also note a good reproducibility and homogeneity of the QFLS on the neat perovskite film and all films with $\\mathrm{C}_{60},$ except for the glass/PTAA/perovskite heterojunctions, for which we observed a relatively large batch-to-batch variation (with the average QFLS ranging from $1.09\\mathrm{eV}$ to $1.16\\mathrm{eV},$ see Supplementary Table 1). On the other hand, no difference in the QFLS was observed between a PTAA/perovskite film on a glass or an ITO substrate, which suggests no additional non-radiative recombination losses at the ITO/ PTAA interface (see Supplementary Fig. 5). \n\n![](images/bf82cf8a46d27cf52f8107cb574ed34b54744802ef6e43e3fad3bf05f051638a.jpg) \nFig. 4 | Visualization of non-radiative interfacial recombination through absolute photoluminescence imaging. a,b, Quasi-Fermi level splitting maps $(1\\mathsf{c m}^{2})$ (a) and corresponding energy histograms $(\\pmb{\\ b})$ on perovskite-only, perovskite $\\prime{\\mathsf{C}}_{60},$ PTAA/perovskite and PTAA/perovskite $'C_{60}$ films on glass. The neat perovskite absorber allows a QFLS (and thus potential $V_{\\mathrm{OC}})$ of approximately $1.208\\mathsf{e V}$ (at $300\\mathsf{K})$ , which is consistent with the transient photoluminescence decay (Fig. 3) but significantly below the QFLS in the radiative limit $(1.345\\mathrm{eV})$ , as indicated by the arrow. Addition of only one transport layer (either PTAA or $\\mathsf C_{60})$ induces additional non-radiative recombination pathways, which lower the QFLS to approximately 1.125–1.135 eV. The pin junction with both transport layers adjacent to the perovskite absorber still has an average QFLS of approximately 1.121 eV. The arrow shows that interfacial recombination dominates the non-radiative recombination losses in the stack. The films were excited at $450\\mathsf{n m}$ with a 1 Sun equivalent intensity and the histograms were recorded on $5\\mathsf{m m}\\times5\\mathsf{m m}$ squares in the middle of the films without edge effects (PL quenching) due to the encapsulation glue, as visible in samples 1, 3 and 4. \n\nThough Fig. 4 shows that the perovskite absorber imposes a substantial limitation on the $V_{\\mathrm{OC}},$ we would expect that it is the weakest component of the (pin) stack that dominates the non-radiative loss current and sets the upper limit for the device $V_{\\mathrm{OC}}$ (in our case both interfaces equally). To further clarify the importance of interfacial optimizations in relation to bulk optimizations depending on the selectivity of the interlayers, we numerically simulated the opencircuit voltage of a pin device stack by varying the interface recombination velocities and the bulk lifetime using a drift-diffusion simulator (Supplementary Fig. $6)^{42}$ . Applying the measured interface-recombination velocity in our structures before optimization (that is, $\\sim2,000\\mathsf{c m s^{-1}}.$ ) and bulk lifetime $(500\\mathrm{ns})$ as input para­ meters, the simulation accurately describes the $V_{\\mathrm{OC}}$ of our standard cells. The simulations clearly show that even if we improved the perovskite bulk lifetime multiple times (to much greater than $500\\mathrm{ns})$ , no $V_{\\mathrm{OC}}$ improvements are possible when the interface recombination velocities stay at $2{,}000\\mathsf{c m}s^{-1}$ . We therefore conclude that the $V_{\\mathrm{OC}}$ of our cells is entirely limited by the interfaces, and any improvement of the bulk would be lost due to rapid interfacial recombination. Thus, it is essential to systematically improve the interfaces, as we discuss in the following. \n\n# Suppression of interfacial recombination \n\nFollowing the approach proposed by Lee et al.43 to improve the wettability of hydrophobic charge transport layers, we functionalized the PTAA layer with the interface compatibilizer poly[(9,9-bis(30- ((N,N-dimethyl)-N-ethylammonium)-propyl)-2,7-fluorene)- alt-2,7-(9,9-dioctylfluorene)] dibromide (PFN-P2)—a conjugated polyelectrolyte (CPE). In line with their findings43, the amphiphilic properties of PFN-P2 improved the wetting of the perovskite film on the hydrophobic PTAA, thus greatly enhancing the fabri­cation yield of our cells without frequent pinhole formation. To reveal possible changes of the layer morphology as a function of the underlying substrate, we performed top and cross-sectional scanning electron microscopy (SEM) measurements of perovskite films deposited on glass, glass/ITO/PTAA and glass/ITO/PTAA/PFN-P2. The images shown in Supplementary Fig. 7 demonstrate perovskite grains ranging from tens of nanometres to micrometres in size and indicate, at least qualitatively, only small changes of the perovskite bulk morphology across these substrates. Importantly, we find that PFN-P2 causes a substantial reduction of the recombination at the hole transport layer contact, as shown in Fig. 5a,b. This resulted in an average QFLS value $\\left(\\sim1.19\\mathrm{eV}\\right)$ very close to the value for the neat perovskite $(\\mathrm{\\sim}1.21\\mathrm{eV})$ while simultaneously improving the homogeneity of the absolute PL image. To check whether PFN-P2 itself passivates the perovskite surface by reducing trap-assisted recombination independent of the presence of the hole transport layer/ perovskite interface, we compared QFLS maps of glass/perovskite and glass/PFN-P2/perovskite samples (Supplementary Table 1). No differences in the QFLS were found, which allows us to assign the increased QFLS of the hole transport layer/PFN-P2/perovskite junction to suppressed interfacial recombination. In accordance with this, we recorded a significantly slower TRPL decay on samples including PFN-P2 (Fig. 5c). Motivated by this success, we aimed to reduce the detrimental recombination at the perovskite/electron transport layer interface. Different strategies have been reported to block holes at the $\\mathfrak{n}$ -interface, such as polystyrene44 or choline chloride11 for pin cells or $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ for nip cells13. However, for our triple cation pin perovskite solar cells we found the most significant effect on the QFLS and device efficiency when inserting an ultrathin layer $(0.6\\mathrm{-}1\\mathrm{nm})$ of LiF between the perovskite and $\\mathrm{C}_{60},$ causing a reduction of the non-radiative interfacial recombination loss by $35\\mathrm{meV}$ (Fig. $\\mathrm{5d,e}$ ). Again, as shown in Fig. 5f, the increase in QFLS was correlated with a slower mono-exponential TRPL decay (with a lifetime that increased from 26 ns to 180 ns for a perovskite $\\mathrm{{'C}_{60}}$ and perovskite $/\\mathrm{LiF}/\\mathrm{C}_{60}$ film on glass, respectively.) \n\n# Photovoltaic performance \n\nIntroducing both interlayers led to considerable improvements of the cell efficiency (from an average of $18\\%$ to $20\\%$ ) through an increase in $V_{\\mathrm{OC}}$ and fill factor (see Supplementary Fig. 8 for the performance of $6\\mathrm{mm}^{2}$ devices). Importantly, the average $V_{\\mathrm{OC}}$ of cells with both interlayers present is $1.16\\mathrm{V},$ which compares well with the average QFLS of the perovskite $/\\mathrm{LiF}/\\mathrm{C}_{60}$ stack and the complete device stack $(\\sim1.17\\mathrm{eV},$ see Supplementary Table 1). Measuring the $V_{\\mathrm{OC}}$ as a function of light intensity on cells with and without both interlayers reveals a similar ideality factor but a smaller dark recombination current density for the interlayer-containing device, indicating that these additional layers do affect the rate but not the overall nature of the recombination process (Supplementary Fig. 9). From the device manufacturing perspective, introducing PFN-P2 greatly improved the homogeneity of the perovskite films, allowing us to manufacture $1\\mathrm{cm}^{2}$ cells without the frequent pinhole formation encountered in our standard cells (without the interlayers), resulting in reproducible high efficiencies. Typically, without PFN-P2, only one out of three $1\\mathrm{cm}^{2}$ cells resulted in efficiencies above $18\\%$ , while this PCE could be safely achieved with 17 out of 18 cells in two batches with 9 cells each if PFN-P2 was included. Cells with PFN-P2 (but without LiF) reached efficiencies up to $19.6\\%$ $(J_{\\mathrm{sc}}{=}21.85\\mathrm{mAcm^{-2}}$ $V_{\\mathrm{OC}}{=}1.143\\mathrm{V},$ fill factor $=78.6\\%$ Supplementary Fig. 10) when measured with an aperture mask $(1.018\\mathsf{c m}^{2})$ at $25^{\\circ}\\mathrm{C}$ The short-circuit current matched the integrated external quantum efficiency (EQE) and solar spectrum product $(21.5\\mathrm{mAcm^{-2}},$ within an error of less than $2\\%$ (Supplementary Fig. 11). This cell was certified by an independent accredited institute (Institute for Solar Energy, Fraunhofer Freiburg), which gave a stabilized PCE of $19.22\\%$ Supplementary Fig. 12) with a negligible mismatch to our $J{-}V$ measurement in terms of current. Moreover, encapsulated cells were stable for at least $100\\mathrm{{h}}$ under maximum power point (MPP) tracking conditions in air and constant illumination from a white light-emitting diode (LED) with $1\\sin$ equivalent light intensity, with only a small loss in efficiency $0.6\\%$ absolute) (Supplementary Fig. 13). We also note that using $10\\Omega\\mathrm{sq}^{-1}$ ITO substrates instead of our standard $15\\Omega\\mathrm{sq}^{-1}$ ITO substrates allowed us to achieve fill factors above $81\\%$ ; values which, to our knowledge, are $3\\%$ higher than the highest reported fill factors for $1\\mathrm{cm}^{2}$ size cells (Supplementary Fig. 14)45. As expected from the QFLS analysis, the $V_{\\mathrm{OC}}$ of the cells is significantly increased through the introduction of the LiF interlayer $(\\mathrm{{\\sim}1.17\\mathrm{{V})}}$ , pushing the PCE of our $1\\mathrm{cm}^{2}$ cells up to a value of $20.0\\%$ , with virtually no hysteresis and a stable power output, as shown in Fig. 6. \n\nHowever, compared to the highest certified $1\\mathrm{cm}^{2}$ cells46 with a PCE of $20.9\\%$ $(J_{\\mathrm{SC}}$ of $24.9\\mathrm{mAcm}^{-2}$ , geometry and structure currently unpublished) a remaining limitation of our cells is their relatively low short-circuit current. Thus, to lower the bandgap of the perovskite layer, we optimized the ratio of $\\mathrm{FAPbI}_{3}$ to $\\mathbf{MAPbBr}_{3}$ . We found that using a ratio of 89:11 allows a significant improvement in short-circuit current $(0.5{-}1\\operatorname*{mA}{\\mathsf{c m}^{-2}}.$ ) with surprisingly minimal loss in $V_{\\mathrm{OC}}$ and efficiencies up to $21.6\\%$ for small $6\\mathrm{{mm}}^{2}$ cells $(J_{\\mathrm{sc}}{=}23.2\\mathrm{mAcm}^{-2}$ , $V_{\\mathrm{OC}}{=}1.156\\mathrm{V},$ fill factor $=80.4\\%$ (Supplementary Fig. 8). As for the $1\\mathrm{cm}^{2}$ devices, Supplementary Fig. 15a shows our present hero device with both interlayers included (PFN-P2 and LiF) fabricated from a $\\mathrm{CsPbI}_{0.05}[(\\mathrm{FAPbI}_{3})$ $_{0.89}(\\mathrm{MAPbBr}_{3})_{0.11}]_{0.95}$ perovskite with an efficiency of $20.3\\%$ , again with very small mismatch versus the integrated EQE–solar spectrum product (Supplementary Fig. 15b). This cell was certified by Fraunhofer-ISE, resulting in a PCE of $19.83\\%$ , which is currently the highest certified efficiency of a $1\\mathrm{cm}^{2}$ perovskite cell with published geometry and structure (Supplementary Figs. 16 and 17)4. We also highlight the important fact that the efficiency of our cells is stabilized, in contrast to most previous perovskite solar cell certifications, which are denoted as ‘not stabilized’4,46. \n\n![](images/e68d329335b7a03e669397ca9eb876d2cc0c7234b63f2bd3f1325e53a1707981.jpg) \nFig. 5 | Suppression of interfacial recombination through interlayers. a,b, QFLS map $(1\\times1\\mathsf{c m})$ (a) and QFLS histogram (b) of a PTAA/PFN-P2/perovskite film on glass, demonstrating a comparatively high average QFLS of approximately $1.19\\mathrm{eV}.$ This represents a significant enhancement of approximately 65 meV compared to the QFLS of the PTAA/perovskite film and approaches the QFLS potential of the neat perovskite within $20\\mathsf{m}\\mathsf{V}.$ d,e, QFLS map $(1\\times1\\mathsf{c m}^{2})$ (d) and QFLS histogram (e) of a perovskite/LiF ${'}C_{60}$ film on glass, demonstrating the reduced interfacial recombination loss at the n-contact. Importantly, the average QFLS of the perovskite/LiF $\\prime{\\mathsf{C}}_{60}$ stack $\\langle1.169\\mathrm{eV}\\rangle$ and the pin device stack $(1.173\\mathrm{eV})$ are both almost identical to the $V_{\\mathrm{OC}}$ of our optimized cells (1.16–1.17 V). The histograms were recorded on a $5\\mathsf{m m}\\times5\\mathsf{m m}$ square in the middle of the films, without edge effects (PL quenching) due to the encapsulation glue. c,f, TRPL transients highlighting the significant prolongation of the carrier lifetime when either PFN-P2 (c) or LiF $(\\pmb{\\uparrow})$ is added as an interlayer. \n\n![](images/f05e5c82eb03e820769f8638fc4c1b5593db7a75497f044fee763940ef9bf86c.jpg) \nFig. 6 | $20\\%$ efficient pin-type perovskite cells with $\\mathsf{1c m}^{2}$ active area. a, Photograph of a fabricated $\\mathsf{1c m^{2}}$ cell with a rectangular active electrode area b, $\\mathsf{1c m^{2}}$ perovskite cells reaching $20\\%$ PCE were achieved using a combination of PFN-P2 and LiF interlayers $(J_{5\\mathsf{c}}=21.7\\mathsf{m A c m}^{-2}$ , fill factor $=78.6\\%$ , $V_{\\mathrm{OC}}=1.17\\:\\mathrm{V};$ as measured with an aperture mask $(1.018\\mathsf{c m}^{2})$ at $25^{\\circ}\\mathsf{C}$ . The inset shows the stabilized power output at $20.1\\%$ . \n\nLast, we note that our concept to identify and suppress interfacial recombination can be successfully generalized to other perovskite compositions, including the standard methylammonium lead iodide absorber (MAPI), where we reached efficiencies slightly above $20\\%$ ; as well as Cs-containing formamidinium lead iodide perovskite cells $(\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.95})\\mathrm{PbI}_{3}$ with close to $20\\%$ PCE (Supplementary Fig. 18). \n\nThe latter system is particularly interesting as pure $\\mathrm{FAPbI}_{3}$ exhibits a bandgap of $1.47\\mathrm{eV},$ which is closer to the optimum bandgap in the Shockley–Queisser model47. However, reports of $\\mathrm{FAPbI}_{3}$ cells are rare and the efficiencies of such devices lag significantly behind the mixed perovskite systems47–49. Measurement of the absolute PL from the individual perovskite/charge transport layer junctions proves once again substantial reduction of interfacial recombination by the addition of PFN-P2 and LiF at the p- and $\\mathfrak{n}$ -interfaces, respectively (Supplementary Table 2). Notably, this allowed the devices to reach record efficiencies for MA/Br-free $\\mathrm{FAPbI}_{3}$ perovskite solar cells, which further underlines the potential of our recombination analysis and interfacial engineering approach (Supplementary Fig. 18). \n\n# Conclusions \n\nHyperspectral photoluminescence imaging allowed us to identify the origin of non-radiative recombination loss channels through mapping of the QFLS of the relevant perovskite/transport layer combinations. We found significant non-radiative recombination losses in the neat perovskite layer that reduce the potential $V_{\\mathrm{OC}}$ by approximately $135\\mathrm{mV}$ compared to the radiative limit of this type of perovskite (1.345 V). However, interface recombination at each individual hybrid interface (PTAA/perovskite and perovskite $/C_{60}\\mathrm{\\dot{,}}$ ) dominates the non-radiative loss current in the stack and results in a significant reduction of the QFLS down to ${\\sim}1.13\\mathrm{eV}.$ In line with this interpretation, we achieved a considerable improvement of the device performance by applying PFN-P2 and LiF as interfacial layers, which suppressed the recombination losses by $65\\mathrm{meV}$ and $35\\mathrm{meV}$ at the p- and n-interfaces, respectively. The reduced recombination and increased QFLS splitting resulted in significant $V_{\\mathrm{OC}}$ and fill factor gains, which in combination with an optimized composition of the perovskite layer led to a PCE above $20\\%$ for $1\\mathrm{cm}^{2}$ cells, with a certified PCE of $19.83\\%$ and stabilized power output. This work demonstrates how interfacial recombination losses can be unambiguously identified and suppressed, and paves the way to reach the thermodynamic limit for perovskite solar cells through further minimization of interface and trap-assisted recombination in the absorber layer. \n\n# Methods \n\nHyperspectral absolute photoluminescence imaging. Excitation for the PL imaging measurements was performed with two $450\\mathrm{nm}$ LEDs equipped with diffuser lenses. The intensity of the LEDs was adjusted to ${\\sim}1$ Sun by illuminating a contacted perovskite solar cell (short circuit) and matching the current density to the short-circuit current measured in the J–V sun simulator (the measured shortcircuit current density of the solar cell under this illumination was $22.2\\mathrm{mAcm^{-2}}$ ). The photoluminescence image detection was performed with a charge-coupled device (CCD) camera (Allied Vision) coupled with a liquid crystal tunable filter. The system was calibrated to absolute photon numbers in two steps in a similar way to the process described by Delamarre and colleagues50. For this purpose an infrared laser diode and a spectrally calibrated halogen lamp were coupled to an integrating sphere. The pixel resolution of the images corresponds to about $10\\upmu\\mathrm{m}$ in diameter. Sets of images from $650\\mathrm{nm}$ to $1,100\\mathrm{nm}$ taken at a step size of $5\\mathrm{nm}$ were recorded. All absolute PL measurements were performed on films with the same thicknesses as used in the operational solar cells. A global systematic error of $20\\mathrm{meV}$ (or equivalently an approximate factor of two in PL efficiency) was estimated on the basis of uncertainties in the optimum approach to calculate the QFLS (equation (2)), as well as small uncertainties in the estimation of the bandga and the temperature. \n\nTime-resolved PL. PL data was acquired with a TCSPC system (Berger & Lahr) after excitation with a pulse-picked and frequency-doubled output from a modelocked Ti:sapphire oscillator (Coherent Chameleon) with nominal pulse durations ${\\sim}100$ fs and a fluence of $\\sim30\\mathrm{nJ}\\mathrm{cm}^{-2}$ at a wavelength of $470\\mathrm{nm}$ . The samples were excited from the side of the interface we sought to investigate (that is, the glass side for PTAA and the top side for the other samples). The short-wavelength excitation was chosen to specifically excite the samples close to the interface we were interested in. All TRPL measurements were performed on films with the same thicknesses as used in the operational solar cells. \n\nDevice fabrication. Pre-patterned $2.5\\times2.5\\mathrm{cm}^{2}15\\Omega\\mathrm{sq}^{-1}$ ITO substrates (Automatic Research) were cleaned with acetone, $3\\%$ Hellmanex solution, deionized water and isopropanol, by sonication for $10\\mathrm{min}$ in each solution. After a microwave plasma treatment $3\\mathrm{min},200\\mathrm{W}$ , the samples were transferred to a $\\Nu_{2}$ -filled glovebox. A thin $(\\sim8\\mathrm{nm})$ PTAA (Sigma-Aldrich) layer was spin-coated from a $1.5\\mathrm{mg}\\mathrm{ml}^{-1}$ toluene solution at $6,000\\mathrm{r.p.m}$ . for 30 s using an acceleration of 2,000 r.p.m. per second. The layers were subsequently annealed inside a nitrogenfilled glovebox $<1\\mathrm{ppmH}_{2}\\mathrm{O}$ and $\\mathbf{O}_{2})$ at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . After the substrate was allowed to cool for $5\\mathrm{{min}}$ a $60\\upmu\\mathrm{l}$ solution of PFN-P2 $(0.5\\mathrm{mg}\\mathrm{ml^{-1}}$ in methanol) purchased from 1-Material was added to the spinning substrate at $5{,}000\\mathrm{r.p.m}$ . for $20s$ resulting in a film with thickness below the detection limit of our atomic force microscopy (less than $5\\mathrm{nm}$ ). The perovskite layer was prepared using an anti-solvent treatment and the concentration of the perovskite components in the solution and solvent ratios were detailed in a previous work9. We found an improvement in $V_{\\mathrm{OC}}$ and reproducibility by switching the anti-solvent from diethyl ether (DEE) to ethyl acetate, which is miscible with dimethylformamide:dimethyl sulfoxide (DMF:DMSO) mixtures and has a higher boiling point $(77.1^{\\circ}\\mathrm{C})$ and an optimal polarity of approximately 4.5. Therefore, all cells reported here were fabricated using ethyl acetate as the anti-solvent. The perovskite layer was deposited by spin-coating at $4{,}000\\mathrm{r.p.m}$ for 35 s. Ten seconds after the start of the spinning process, the spinning substrate was washed with $300\\upmu\\mathrm{l}$ ethyl acetate for approximately 1 s (the anti-solvent was placed in the centre of the film). The perovskite film was then annealed at $100^{\\circ}\\mathrm{C}$ for $^\\mathrm{1h}$ on a preheated hotplate. The samples were transferred to an evaporation chamber and LiF ( ${}_{6\\dot{\\mathrm{A}}}$ to $1\\mathrm{nm}$ ), $\\mathrm{C}_{60}$ ( $30\\mathrm{nm})$ , BCP $(8\\mathrm{nm})$ and copper $(100\\mathrm{nm})$ were deposited under vacuum $P=10^{-7}\\mathrm{{mbar})}$ . After completion, the glass side of the $1\\mathrm{cm}^{2}$ cells was coated with a Brisbane Materials Technology (Australia Pty Ltd) anti-reflection coating optimized for a broadband spectral response in the AM1.5 window. \n\nCurrent density–voltage characteristics. $J{-}V$ curves were obtained in a two-wire source-sense configuration with a Keithley 2400. An Oriel class AAA Xenon lamp-based sun simulator was used for illumination, providing approximately $100\\mathrm{mW}\\mathrm{cm}^{-2}$ of AM1.5 G irradiation, and the intensity was monitored simultaneously with a Si photodiode. The exact illumination intensity was used for efficiency calculations, and the simulator was calibrated with a KG5-filtered silicon solar cell (certified by Fraunhofer ISE). A spectral mismatch calculation was performed based on the spectral irradiance of the solar simulator, the EQE of the reference silicon solar cell and three typical EQEs of our cells. This resulted in three mismatch factors of $\\scriptstyle M=0.9949$ , 0.9996 and 0.9976. Given the very small deviation from unity, the measured $J_{\\scriptscriptstyle\\mathrm{SC}}$ was not corrected by the factor $1/M$ . All EQEs presented in this work were measured by ISE-Fraunhofer. \n\nCoupled optical and Shockley–Queisser modelling. We employed an optical modelling tool51 to calculate the photogenerated current inside the perovskite material depending on the thickness of the ITO layer. To this end, we kept the other layer thicknesses constant (8 nm PTAA, $450\\mathrm{nm}$ perovskite, $20\\mathrm{nm}\\mathrm{C}_{60},8\\mathrm{nm}$ BCP, $100\\mathrm{nm}$ copper). We employed measured spectral refractive indices $n$ and $k$ for all layers under normal incident illumination. The resulting short-circuit current was used to numerically solve the modified Shockley–Queisser equation (typical voltage steps are $1\\mathrm{mV}.$ ) including an ideality factor of 1.5 (ref. 9), a shunt resistance of ${4,000\\Omega,}$ a luminescent efficiency of $0.1\\%$ (ref. 15) a radiative current of $\\mathbf{8}\\times10^{-20}\\mathbf{A}\\mathbf{cm}^{-2}$ and an internal series resistance of $1.5\\Omega\\mathrm{cm}^{2}$ in addition to the series resistance imposed by the ITO for any given thickness and geometry. Our standard ITO (Automatic Research GmbH, Germany) has a nominal sheet resistance of $15\\Omega\\mathrm{sq}^{-1}$ with a thickness of $150\\mathrm{nm}$ . We extrapolated the resulting sheet resistance starting from this value. \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request. \n\nReceived: 31 December 2017; Accepted: 2 July 2018; Published: xx xx xxxx \n\n# References \n\n1.\t Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n2.\t Kim, H. S. et al. Lead iodide perovskite sensitized all-solid-state submicron thin film mesoscopic solar cell with efficiency exceeding $9\\%$ . Sci. Rep. 2, 591 (2012). \n3.\t Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n4.\t Yang, W. S. et al. Iodide management in formamidinium-lead-halide–based perovskite layers for efficient solar cells. Science 356, 1376–1379 (2017). \n5.\t Yoshikawa, K. et al. Silicon heterojunction solar cell with interdigitated back contacts for a photoconversion efficiency over $26\\%$ . Nat. Energy 2, 17032 (2017). \n6.\t Tress, W. Perovskite solar cells on the way to their radiative efficiency limit—insights into a success story of high open-circuit voltage and low recombination. Adv. Energy Mater. 7, 1602358 (2017). \n7.\t Grancini, G. et al. One-year stable perovskite solar cells by 2D/3D interface engineering. Nat. Commun. 8, 15684 (2017). \n8. Lin, Q., Nagiri, R. C. R., Burn, P. L. & Meredith, P. Considerations for upscaling of organohalide perovskite solar cells. Adv. Opt. Mater. 5, 1600819 (2017). \n9.\t Stolterfoht, M. et al. Approaching the fill factor Shockley–Queisser limit in stable, dopant-free triple cation perovskite solar cells. Energy Environ. Sci. 10, \n1530–1539 (2017). \n10.\tZhang, W. et al. Enhanced optoelectronic quality of perovskite thin films with hypophosphorous acid for planar heterojunction solar cells. Nat. Commun. 6, \n10030 (2015). \n11.\t Zheng, X. et al. Defect passivation in hybrid perovskite solar cells using quaternary ammonium halide anions and cations. Nat. Energy 2, 17102 (2017). \n12.\t Sherkar, T. S., Momblona, C., Gil-Escrig, L., Bolink, H. J. & Koster, L. J. A. Improving perovskite solar cells: Insights from a validated device model. Adv. Energy Mater. 7, 1602432 (2017). \n13.\tCorrea-Baena, J.-P. et al. Identifying and suppressing interfacial recombination to achieve high open-circuit voltage in perovskite solar cells. Energy Environ. Sci. 10, 1207–1212 (2017). \n14.\tTvingstedt, K. et al. Removing leakage and surface recombination in planar perovskite solar cells. ACS Energy Lett. 2, 424–430 (2017). \n15.\t Wolff, C. M. et al. Reduced interface-mediated recombination for high open-circuit voltages in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ solar cells. Adv. Mater. 29, 1700159 (2017). \n16.\tTan, H. et al. Efficient and stable solution-processed planar perovskite solar cells via contact passivation. Science 355, 722–726 (2017). \n17.\tSaliba, M. et al. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). \n18.\tHou, Y. et al. A generic interface to reduce the efficiency–stability–cost gap of perovskite solar cells. Science 358, 1192–1197 (2017). \n19.\tMomblona, C. et al. Efficient vacuum deposited p-i-n and n-i-p perovskite solar cells employing doped charge transport layers. Energy Environ. Sci. 9, \n3456–3463 (2016). \n20.\t Bush, K. A. et al. $23.6\\%$ -efficient monolithic perovskite/silicon tandem solar cells with improved stability. Nat. Energy 2, 17009 (2017). \n21.\tAlbrecht, S. et al. Monolithic perovskite/silicon-heterojunction tandem solar cells processed at low temperature. Energy Environ. Sci. 9, 81–88 (2016). \n22.\t Wu, Y. et al. Thermally stable $\\mathbf{MAPbI}_{3}$ perovskite solar cells with efficiency of $19.19\\%$ and area over $\\scriptstyle1\\cos^{2}$ achieved by additive engineering. Adv. Mater. 29, \n170173 (2017). \n23.\tPalma, A. L. et al. Laser-patterning engineering for perovskite solar modules with $95\\%$ aperture ratio. IEEE J. Photovolt. 7, 1674–1680 (2017). \n24.\tStaub, F. et al. Beyond bulk lifetimes: Insights into lead halide perovskite films from time-resolved photoluminescence. Phys. Rev. Appl. 6, 044017 (2016). \n25.\t Richter, J. M. et al. Enhancing photoluminescence yields in lead halide perovskites by photon recycling and light out-coupling. Nat. Commun. 7, 13941 (2016). \n26.\tdeQuilettes, D. W. et al. Photoluminescence lifetimes exceeding ${8\\upmu\\mathrm{s}}$ and quantum yields exceeding $30\\%$ in hybrid perovskite thin films by ligand passivation. ACS Energy Lett. 1, 438–444 (2016). \n27.\tAhrenkiel, R. K. Minority-carrier lifetime in III–V semiconductors. Semicond. Semimet. 39, 39–150 (1993). \n28.\tHerz, L. M. Charge-carrier mobilities in metal halide perovskites: Fundamental mechanisms and limits. ACS Energy Lett. 2, 1539–1548 (2017). \n29.\tdeQuilettes, D. W. et al. Photo-induced halide redistribution in organic– inorganic perovskite films. Nat. Commun. 7, 11683 (2016). \n30.\tWurfel, P. The chemical potential of radiation. J. Phys. C 15, 3967–3985 (1982). \n31.\tEl-Hajje, G. et al. Quantification of spatial inhomogeneity in perovskite solar cells by hyperspectral luminescence imaging. Energy Environ. Sci. 131, \n6050–6051 (2016). \n32.\tBraly, I. L. & Hillhouse, H. W. Optoelectronic quality and stability of hybrid perovskites from $\\mathbf{MAPbI}_{3}$ to $\\mathrm{MAPbI}_{2}\\mathrm{Br}$ using composition spread libraries. J. Phys. Chem. C. 120, 893–902 (2016). \n33.\tSarritzu, V. et al. Optical determination of Shockley–Read–Hall and interface recombination currents in hybrid perovskites. Sci. Rep. 7, 44629 (2017). \n34.\tJohnston, S. & Unold, T. Correlations of $\\mathrm{Cu(In,Ga)Se}_{2}$ imaging with device performance, defects, and microstructural properties. J. Vac. Sci. Technol. A \n30, 4–9 (2012). \n35.\tBauer, G. H., Gütay, L. & Kniese, R. Structural properties and quality of the photoexcited state in $\\mathrm{Cu}(\\mathrm{In}_{1-x}\\mathrm{Ga}_{x})\\mathrm{Se}_{2}$ solar cell absorbers with lateral submicron resolution. Thin Solid Films 480–481, 259–263 (2005). \n36.\tRau, U., Abou-Ras, D. & Kirchartz, T. (eds) Advanced Characterization Techniques for Thin Film Solar Cells (Wiley, Weinheim, 2011). \n37.\tTress, W. et al. Predicting the open-circuit voltage of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite solar cells using electroluminescence and photovoltaic quantum efficiency spectra: the role of radiative and non-radiative recombination. Adv. Energy Mater. 5, 1400812 (2015). \n38.\tTvingstedt, K. et al. Radiative efficiency of lead iodide based perovskite solar cells. Sci. Rep. 4, 6071 (2014). \n39.\tKirchartz, T. & Rau, U. Detailed balance and reciprocity in solar cells. Phys. Status Solidi A 205, 2737–2751 (2008). \n40.\tShockley, W. & Queisser, H. J. Detailed balance limit of efficiency of p-n junction solar cells. J. Appl. Phys. 32, 510–519 (1961). \n41.\t Kirchartz, T., Staub, F. & Rau, U. Impact of photon recycling on the open-circuit voltage of metal halide perovskite solar cells. ACS Energy Lett. 1, 731–739 (2016). \n42.\tBurgelman, M., Nollet, P. & Degrave, S. Modelling polycrystalline semiconductor solar cells. Thin Solid Films 362, 527–532 (2000). \n43.\tLee, J. et al. Achieving large-area planar perovskite solar cells by introducing an interfacial compatibilizer. Adv. Mater. 29, 1606363 (2017). \n44.\tWang, Q., Dong, Q., Li, T., Gruverman, A. & Huang, J. Thin insulating tunneling contacts for efficient and water-resistant perovskite solar cells. Adv. Mater. 28, 6734–6739 (2016). \n45.\tWu, Y. et al. Perovskite solar cells with $18.21\\%$ efficiency and area over $\\scriptstyle{1\\mathrm{~cm}^{2}}$ fabricated by heterojunction engineering. Nat. Energy 1, 16148 (2016). \n46.\tGreen, M. A. et al. Solar cell efficiency tables (version 51). Prog. Photovolt. Res. Appl. 26, 3–12 (2018). \n47.\tYang, W. S. et al. High-performance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237 (2015). \n48.\tLiu, T. et al. High-performance formamidinium-based perovskite solar cells via microstructure-mediated δ​-to- $\\mathbf{\\nabla}\\cdot\\mathbf{\\vec{a}}$ phase transformation. Chem. Mater. 29, \n3246–3250 (2017). \n49.\tYu, Y. et al. Improving the performance of formamidinium and cesium lead triiodide perovskite solar cells using lead thiocyanate additives. ChemSusChem 9, 3288–3297 (2016). \n50.\tDelamarre, A., Lombez, L. & Guillemoles, J. F. Contactless mapping of saturation currents of solar cells by photoluminescence. Appl. Phys. Lett. 100, \n131108 (2012). \n51.\tBurkhard, G. F., Hoke, E. T. & McGehee, M. D. Accounting for interference, scattering, and electrode absorption to make accurate internal quantum efficiency measurements in organic and other thin solar cells. Adv. Mater. 22, \n3293–3297 (2010). \n\n# Acknowledgements \n\nWe thank P. Caprioglio for SEM measurements, L. Fiedler for laboratory assistance and F. Jaiser, F. Dornack and A. Pucher for providing measurement and laboratory equipment. P.M. is a Sêr Cymru Research Chair funded by the Welsh European Funding Office (Sêr Cymru II Program) and is formerly an Australian Research Council Discovery Outstanding Researcher Award Fellow. P.L.B is an Australian Research Council Laureate Fellow (FL160100067). S.Z is partly funded by a Chinese Scholarship Council studentship and the Australian Government through the Australian Renewable Energy Agency (ARENA) Australian Centre for Advanced Photovoltaics. Responsibility for the views, information or advice expressed herein is not accepted by the Australian Government. We thank M. Harvey and Brisbane Materials Technology Pty Ltd for the provision of their proprietary anti-reflection coating formulation. J.A.M. acknowledges A. Redinger for fruitful discussions. S.A. acknowledges funding from the German Federal Ministry of Education and Research (BMBF), within the project ‘Materialforschung für die Energiewende’ (grant no. 03SF0540), and the German Federal Ministry for Economic Affairs and Energy (BMWi) through the ‘PersiST’ project (grant no. 0324037C). Support by the joint University Potsdam–HZB graduate school ‘hypercells’ is acknowledged. \n\n# Author contributions \n\nM.S. planned the project together with C.M.W. and D.N., drafted the manuscript and reviewer response, fabricated most cells and films with help of S.Z. and D.R., performed electrical measurements, measured TRPL with C.J.H. and absolute PL on FAPI cells. C.M.W. provided main conceptual ideas regarding the identification of the recombination losses, contributed to device fabrication and TRPL measurements, and performed coupled optical and Shockley–Queisser modelling. J.A.M. performed all hyperspectral PL measurements and performed corresponding data analysis and interpretation. S.Z. helped with device optimization and fabrication. C.J.H. performed fluence- and wavelengthdependent TRPL measurements and analysed data. T.U. performed numerical drift diffusion simulations with SCAPS1D and analysed and interpreted the optical measurements. D.R. fabricated certified $1\\mathrm{cm}^{2}$ cells with M.S., as well as MAPI/FAPI cells and films. D.N. supervised the study, analysed and interpreted all electrical and optical measurements, and contributed to manuscript drafting. All co-authors contributed to data analysis, interpretation, proof reading and addressing reviewer comments. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-018-0219-8. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to M.S. or T.U. or D.N. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# natureresearch \n\n# Solar Cells Reporting Summary \n\nNature Research wishes to improve the reproducibility of the work that we publish. This form is intended for publication with all accepted papers reporting the characterization of photovoltaic devices and provides structure for consistency and transparency in reporting. Some list items might not apply to an individual manuscript, but all fields must be completed for clarity. \n\nFor further information on Nature Research policies, including our data availability policy, see Authors & Referees. \n\n# Experimental design \n\n# Please check: are the following details reported in the manuscript? \n\n![](images/0c99870b3454ff78d2ff13561527d5141b33ed06e6c93d7cd1ad51de8ff73a1a.jpg) \n\n5. Calibration \n\nLight source and reference cell or sensor used for the characterization \n\n![](images/13070f7ac520f0e48a6058828b1d53e12df360369a9039a510fc766cdcbf502a.jpg) \n\nAn Oriel class AAA Xenon lamp-based sun simulator was used for illumination providing approximately 100 mWcm-2 of simulated AMI.5G irradiation and the intensity was monitored simultaneously with a Si photodiode. The exact illumination intensity was used for efficiency calculations. \n\nConfirmation that the reference cell was calibrated and certified \n\nThe simulator was recently calibrated with a KG5 filtered silicon solar cell (certified by Fraunhofer ISE). \n\nCalculation of spectral mismatch between the reference cell and the devices under test \n\n![](images/73bbd127e6b67d4d7eb56a1c1deaead4c4d52a4d8f9fdf440feb744ef81ed2c1.jpg) \n\nA spectral mismatch calculation was performed based on the spectral irradiance of the solar simulator, the EQE of the reference silicon solar cell and 3 typical EQEs of our cells. This resulted in 3 mismatch factors of $\\mathsf{M}=0.9949$ , 0.9996 and 0.9976. Given the very small deviation from unity the measured JSC was not corrected by the factor 1/M. \n\n6. Mask/aperture \n\nSize of the mask/aperture used during testing \n\n![](images/4504fff88dfccdae14269c900c07046d020fc13726655b018a0146963a43c9b2.jpg) \n\nAn aperture mask of approximately 1.018 cm2 was used for measuring the large cells. The same aperture mask was used (and re-measured) by the calibration lab Fraunhofer-ISE. \n\nVariation of the measured short-circuit current density with the mask/aperture area \n\n![](images/a35932d3fd3d1bf51e222d66d4ccc38d53756d8ee689dab45bcf69ddabc3f30d.jpg) \n\nNo significant variations were observed. The correctness of the short-circuit current was confirmed by the calibration lab. \n\n7. Performance certification \n\nIdentity of the independent certification laboratory that confirmed the photovoltaic performance \n\nInstitute for Solar Energy, Fraunhofer Freiburg (Germany) \n\n![](images/dcfc18624d0c8448bc64dd9711f29dd666f656d79e1e6ddc3adb6123c3762f1a.jpg) \n\nA copy of any certificate(s) Provide in Supplementary Information \n\nCertified measurements are shown in Supplementary Figures 10, 12, 16 and 17. \n(One certificate in Supplementary Figure 16). \n\n8. Statistics \n\nNumber of solar cells tested \n\n![](images/135cf392270133323228f6110439584ea23f376a285d1512271996b8df570a20.jpg) \n\nOverall we fabricated and tested more than 250 cells for this study. As for the small area (6 mm2-size) cells, we fabricated approximately 40 cells for each of the 4 studied device architectures. Supplementary Figure 8 shows the results of three fabricated device batches with 20 cells per device architecture. In addition, we fabricated approximately 20 1cm2-size cells for each of these 4 device configurations. We note that we observed very small efficiency losses when increasing the active area from $6\\mathsf{m m}2$ to 1 cm2, thus the results in Supplementary Figure 8 are also representative for the large cells (with the exception of the standard device architecture without interlayers where we experienced scaling difficulties due to the formation of pinholes as we discuss in the text). \n\nStatistical analysis of the device performance \n\n![](images/d767398310036018fa8d1f92a013bb5374fa814fa6cfc0f7a18e1062846215ff.jpg) \n\nIn Supplementary Figure 8. \n\n9. Long-term stability analysis \n\nType of analysis, bias conditions and environmental conditions For instance: illumination type, temperature, atmosphere humidity, encapsulation method, preconditioning temperature \n\n![](images/9fa100634fbd84ede60253346d59d1a9edcfe853bd282a132c0f63fe0d83ee70.jpg) \n\nLong term MPP tracking was performed on encapsulated cells under 1 Sun equivalent white LED irradiation in air $25\\%$ relative humidity) for 100 hours. Thereby the cell is continuously held at $25^{\\circ}\\mathsf{C}$ and its maximum power voltage which was obtained from an initial JV scan. Maximum power output was ensured by applying a small voltage perturbation $(+/-5\\mathsf{m V})$ to the cell every 5 seconds. Depending on which voltage gave a higher power output, the applied voltage was either increased or decreasing by $5\\mathsf{m V}$ and then held at this voltage for the next 5 seconds. " + }, + { + "id": "10.1126_science.aao1797", + "DOI": "10.1126/science.aao1797", + "DOI Link": "http://dx.doi.org/10.1126/science.aao1797", + "Relative Dir Path": "mds/10.1126_science.aao1797", + "Article Title": "Evidence for Majorana bound states in an iron-based superconductor", + "Authors": "Wang, DF; Kong, LY; Fan, P; Chen, H; Zhu, SY; Liu, WY; Cao, L; Sun, YJ; Du, SX; Schneeloch, J; Zhong, RD; Gu, GD; Fu, L; Ding, H; Gao, HJ", + "Source Title": "SCIENCE", + "Abstract": "The search for Majorana bound states (MBSs) has been fueled by the prospect of using their non-Abelian statistics for robust quantum computation. Two-dimensional superconducting topological materials have been predicted to host MBSs as zero-energy modes in vortex cores. By using scanning tunneling spectroscopy on the superconducting Dirac surface state of the iron-based superconductor FeTe0.55Se0.45, we observed a sharp zero-bias peak inside a vortex core that does not split when moving away from the vortex center. The evolution of the peak under varying magnetic field, temperature, and tunneling barrier is consistent with the tunneling to a nearly pure MBS, separated from nontopological bound states. This observation offers a potential platform for realizing and manipulating MBSs at a relatively high temperature.", + "Times Cited, WoS Core": 821, + "Times Cited, All Databases": 886, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000447680100046", + "Markdown": "# TOPOLOGICAL MATTER \n\n# Evidence for Majorana bound states in an iron-based superconductor \n\nDongfei $\\mathbf{Wang^{1,2\\times}}$ , Lingyuan $\\mathbf{Kong^{1,2*}}$ , Peng $\\mathbf{Fan^{1,2\\ast}}$ , Hui Chen1, Shiyu $\\mathbf{zhu^{1,2}}$ , Wenyao ${\\bf L i u^{1,2}}$ , $\\mathbf{Lu\\thinspacecao^{1,2}}$ , Yujie $\\mathbf{Sun^{1,3}}$ , Shixuan $\\bf{D u^{1,3,4}}$ , John Schneeloch5, Ruidan $\\mathbf{zhong}^{5}$ , Genda $\\mathbf{G}\\mathbf{u}^{5}$ , Liang $\\mathbf{Fu}^{6}$ , Hong $\\mathbf{Ding^{1,2,3,4}}\\dagger$ , Hong-Jun Gao1,2,3,4† \n\nThe search for Majorana bound states (MBSs) has been fueled by the prospect of using their non-Abelian statistics for robust quantum computation. Two-dimensional superconducting topological materials have been predicted to host MBSs as zero-energy modes in vortex cores. By using scanning tunneling spectroscopy on the superconducting Dirac surface state of the iron-based superconductor $\\mathsf{F e T e}_{0.55}\\mathsf{S e}_{0.45},$ we observed a sharp zero-bias peak inside a vortex core that does not split when moving away from the vortex center. The evolution of the peak under varying magnetic field, temperature, and tunneling barrier is consistent with the tunneling to a nearly pure MBS, separated from nontopological bound states. This observation offers a potential platform for realizing and manipulating MBSs at a relatively high temperature. \n\najorana bound states (MBSs) in condensedmatter systems have attracted tremenM sdtoautissitnictseraesntdopwoitnegntoiatlhaeiprpnliocna-tiAobnels ain topological quantum computation $(\\boldsymbol{I},2)$ . A MBS is theoretically predicted to emerge as a spatially localized zero-energy mode in certain $p$ -wave topological superconductors in one and two dimensions (3, 4). Although the material realization of such $p$ -wave superconductors has remained elusive, other platforms for MBSs have recently been proposed, using heterostructures between conventional $s$ -wave superconductors and topological insulators (5), nanowires (6–8), quantum anomalous Hall insulators $({\\mathcal{G}})_{;}$ or atomic chains $(I O),$ where the proximity effect on a spinnondegenerate band creates a superconducting (SC) topological state. Various experimental signatures of MBSs (11–14) or Majorana chiral modes $(I5)$ have been observed in these heterostructures, but clear detection and manipulation of MBSs are often hindered by the contribution of nontopological bound states and complications of material interface. \n\nVery recently, using high-resolution angleresolved photoemission spectroscopy (ARPES), a potential platform for MBSs was discovered in the bulk superconductor $\\mathrm{FeTe}_{0.55}\\mathrm{Se}_{0.45},$ , with a SC transition temperature $T_{\\mathrm{c}}=14.5\\:\\mathrm{K}$ and a simple crystal structure (Fig. 1A). Because of the topological band inversion between the $p_{z}$ and $d_{x z}/d_{y z}$ challenging interface problems in previous proposals and offers clear advantages for the detection and manipulation of MBSs. \n\nMotivated by the above considerations, we carried out a high-resolution scanning tunneling microscopy/spectroscopy (STM/S) experiment on the surface of $\\mathrm{FeTe}_{0.55}\\mathrm{Se}_{0.45},$ which has a good atomic resolution that reveals the lattice formed by Te/Se atoms on the surface (Fig. 1D). We started with a relatively low magnetic field of $0.5\\mathrm{T}$ along the $\\scriptstyle{c}$ axis at a low temperature of $0.55~\\mathrm{K},$ with a clear observation of vortex cores in Fig. 1E. At the vortex center, we observed a strong zero-bias peak (ZBP) with a full width at half maximum (FWHM) of $0.3~\\mathrm{meV}$ and an amplitude of 2 relative to the intensity just outside the gapped region. Outside of the vortex core, we clearly observed a SC spectrum with multiple gap features, similar to the ones observed in previous STM studies on the same material (21, 22). These different SC gaps correspond well with the SC gaps on different Fermi surfaces of this material observed in previous ARPES studies (table S1) (23, 24). A similar ZBP was reported previously (22). \n\nbands around the $\\bar{\\Gamma}$ point (16, 17) and the multiband nature (Fig. 1B), this single material naturally has a spin-helical Dirac surface state, with an induced full SC gap and a small Fermi energy (Fig. 1C) (18); these properties would create favorable conditions for observing a pure MBS (5) that is isolated from other nontopological Caroli–de Gennes– Matricon bound states (CBSs) (19, 20). The combination of high- ${\\cdot}T_{\\mathrm{c}}$ superconductivity and Dirac surface states in a single material removes the \n\nWe next demonstrate in Fig. 2 and fig. S4 (24) that across a large range of magnetic fields, the observed ZBP does not split when moving away from a vortex center. It can be clearly seen from Fig. 2, A to D, that the ZBP remains at the zero energy, while its intensity fades away when moving away from the vortex center. The nonsplit ZBP contrasts sharply with the split ZBP originating from CBS observed in conventional superconductors (19, 20) and is consistent with tunneling into an isolated MBS in a vortex core of a SC topological material (5, 25–27). We then extracted the position-dependent values of the ZBP height and width using simple Gaussian fits of the data in Fig. 2C and obtained the spatial profile shown in Fig. 2E; the decaying profile has a nearly constant line width of ${\\sim}0.3\\mathrm{meV}$ in the center, which is close to the total width $\\mathrm{({\\sim}0.28~m e V)}$ contributed from the STM energy resolution $[\\mathrm{\\sim}0.23\\mathrm{meV}$ as shown in part I of (24)] and the thermal broadening $[3.5k_{\\mathrm{B}}T$ at $0.55\\mathrm{K}\\sim0.17\\mathrm{meV}_{;}$ , where $k_{\\mathrm{B}}$ is the Boltzmann constant]. We further compared the observed ZBP height with a theoretical MBS spatial profile obtained by solving the Bogoliubov–de Gennes equation analytically (5, 25) or numerically (26, 27). By using the parameters of $E_{\\mathrm{{F}}}{=}4.4\\mathrm{{meV}}$ $\\Delta_{\\mathrm{sc}}{=}1.8\\mathrm{meV},$ , and $\\begin{array}{r}{\\xi_{0}=\\mathrm{V_{F}}/\\Delta_{\\mathrm{sc}}=12\\mathrm{nm},}\\end{array}$ which are obtained directly from the topological surface state by our scanning tunneling spectroscopy (STS) and ARPES results (Fig. 2F) $(I8)$ , the theoretical MBS profile matches well the experimental one (Fig. 2G). \n\n![](images/e889d558f61424510201f56ce1528b2c06982561b99202943a5b1baa2fc5b3a5.jpg) \nFig. 1. Band structure and vortex cores of $\\mathsf{F e T e}_{0.55}\\mathsf{S e}_{0.45}$ . (A) Crystal structure of $\\mathsf{F e T e}_{0.55}\\mathsf{S e}_{0.45}$ . Axis a or b indicates one of the Fe–Fe bond directions. (B) A first-principle calculation of the band structure along the G-M direction. In the calculations, $t=100$ meV, whereas $t\\sim12$ to $25\\mathrm{\\meV}$ from ARPES experiments, largely depending on the bands (23). [Adapted from (18), figure 1C] (C) Summary of SC topological surface states on this material observed by ARPES from (18). (D) STM topography of FeTe0.55Se0.45 (scanning area, $17\\mathsf{n m}$ by $17\\:\\mathrm{nm}$ ). (E) Normalized zero-bias conductance (ZBC) map measured at a magnetic field of $0.5{\\top}$ , with the area $120\\mathsf{n m}$ by $120{\\mathsf{n m}}$ . (F) A sharp ZBP in a dI/dV spectrum measured at the vortex core center indicated in the red box in (E). Settings are sample bias, $V_{\\mathrm{s}}=-5~\\mathrm{mV};$ ; tunneling current, $I_{\\mathrm{t}}=200$ pA; and temperature, $T=0.55\\mathsf{K}.$ . \n\n![](images/6124e7f584ce2d02d4fd1b4b60289d8443691b801c115aacea122a98a7e30b4b.jpg) \nFig. 2. Energetic and spatial profile of ZBPs. (A) A ZBC map (area, $15\\:\\mathrm{nm}$ by $15\\:\\mathsf{n m}$ ) around vortex cores. (B) A line-cut intensity plot along the black dashed line indicated in (A). (C) A waterfall-like plot of (B) with 65 spectra, with the black curve corresponding to the one in the core center. (D) An overlapping display of eight dI/dV spectra selected from (C). (E) Spatial dependence of the height (top) and FWHM (bottom) of the ZBP. (F) Comparison between ARPES and STS results. (Left) ARPES results on the topological surface states. [Adapted from (18)] Black dashed \ncurves are extracted from a first-principle calculation (37), with the calculated data rescaled to match the energy positions of the Dirac point and the top of the bulk valence band (BVB). (Right) A dI/dV spectrum measured from $-20$ to 10 meV. (G) Comparison between the measured ZBP peak intensity with a theoretical calculation of MBS spatial profile [(24), part VIII]. The data in (B) to (G) are normalized by the integrated area of each dI/dV spectrum. Settings are $V_{\\mathsf{s}}=-5~\\mathsf{m V}$ , $I_{\\mathrm{t}}=200$ pA, $T=0.55~\\mathsf{K}$ , and perpendicular magnetic field $(B_{\\perp})=0.5\\intercal$ . \n\nThe observation of a nonsplit ZBP, which is different from the split ZBP observed in a vortex of the $\\mathrm{Bi_{2}T e_{3}/N b S e_{2}}$ heterostructure (13, 28, 29), indicates that the MBS peak in our system is much less contaminated by nontopological CBS peaks, which is made possible by the large $\\Delta_{\\mathrm{sc}}/E_{\\mathrm{F}}$ ratio in this system. In a usual topological insulator/ superconductor heterostructure, this ratio is tiny, on the order of ${{10}^{-3}}$ to ${\\boldsymbol{10}}^{-2}$ (28). This has been shown to induce, in addition to the MBS at the zero energy, many CBSs, whose level spacing is proportional to ${\\Delta_{\\mathrm{sc}}}^{2}/E_{\\mathrm{F}}.$ As a result, these CBSs were crowded together very close to the zero energy, making difficult a clean detection of MBS from the dI/dV spectra (29). However, on the surface of $\\mathrm{FeTe}_{0.55}\\mathrm{Se}_{0.45},$ the value of ${\\Delta_{\\mathrm{sc}}}^{2}/E_{\\mathrm{F}}$ is ${\\sim}0.74~\\mathrm{meV}$ , which is sufficiently large to push most CBSs away from the zero energy (24), leaving the MBS largely isolated and unspoiled. A large energy separation $\\mathrm{(0.7meV)}$ between the ZBP and the CBS was observed in fig. S3, E to H, which is in agreement with ${\\Delta_{\\mathrm{sc}}}^{2}/E_{\\mathrm{F}}$ of the topological surface states [(24), part IV]. Also, all the bulk bands in this multiband material have fairly small values of $E_{\\mathrm{F}}$ owing to large correlation-induced mass renormalization, ranging from a few to a few tens of milli– electron volts; thus, their values of ${\\Delta_{\\mathrm{sc}}}^{2}/{E_{\\mathrm{F}}}$ are also quite large $(>0.2\\mathrm{meV})$ (table S1) (24). These large bulk ratios enlarge the energy-level spacing of CBSs inside the bulk vortex line, which helps reduce quasiparticle poisoning of the MBS at low temperature [(24), part II]. \n\nIt has been predicted (30) that the width of the ZBP from tunneling into a single isolated MBS is determined by thermal smearing $(3.5k_{\\mathrm{B}}T),$ tunneling broadening, and STM instrumentation resolution. We measured the tunneling barrier evolution of the ZBP (Fig. 3A). Robust ZBPs can be observed over two orders of magnitude in tunneling barrier conductance, with the width barely changing (Fig. 3B). Also, the line width of ZBPs is almost completely limited by the combined broadening of energy resolution and STM thermal effect, suggesting that the intrinsic width of the MBS is much smaller, and our measurements are within the weak tunneling regime. \n\nHowever, we did observe some other ZBPs with a larger broadening (Fig. 3C). A larger ZBP broadening is usually accompanied with a softer SC gap, or the FWHM of ZBP increases with increasing subgap background conductance. The subgap background conductance, which is determined by factors such as the strength of scattering from disorder and quasiparticle interactions (31–33), introduces a gapless fermion bath that can poison the MBS, as explained previously $(34)$ . The effect of quasiparticle poisoning is to reduce the MBS amplitude and increase its width. This scenario is likely the origin of a larger broadening of ZBP accompanied by a softer gap. \n\n![](images/38f65deca1c671761e7b4bc4f956c5d912d88da80f426b10b996cdb2d497c12e.jpg) \nFig. 3. Temperature and tunneling barrier evolution of ZBPs. (A) Evolution of ZBPs, with tunneling barrier measured at $0.55~\\mathsf{K}.$ $G_{\\N}\\equiv I_{\\mathrm{t}}/V_{\\mathrm{s}}$ , which corresponds to the energy-averaged conductance of normal states and represents the conductance of the tunneling barrier. $I_{\\mathrm{t}}$ and $V_{\\mathrm{s}}$ are the STS setpoint parameters. (B) FWHM of ZBPs at $0.55~\\mathsf{K}$ under different tunneling barriers. The black solid line is the combined effect of energy resolution $(0.23\\ \\mathrm{meV})$ (24) and tip thermal broadening $(3.5k_{\\mathrm{B}}T)$ at $0.55~\\mathsf{K}.$ (C) FWHM of ZBP at the center of the vortex core is larger when the SC gap around the vortex core is softer. Background is defined as an integrated area from $^{-1}$ to $+1$ meV of the spectra at the core edge. (D) Temperature evolution of ZBPs in a vortex core. The gray curves are numerically broadened $0.55\\mathsf{K}$ data at each temperature. (E) Amplitude of the ZBPs shown in (D) and fig. S6 (24) under different temperatures. The amplitude is defined as the peakvalley difference of the ZBP. (F) Schematic of a possible way for realizing non-Abelian statistics in an ultralow-temperature STM experiment that may have an ability to exchange MBSs on the surface of Fe(Te, Se). (A) and (B) show the absolute value of conductance; $B_{\\bot}=2.5{\\top}$ . In (D) and (E), the data are normalized by integrated area; $V_{\\mathrm{s}}=-10~\\mathrm{mV}$ $I_{\\mathrm{t}}=100$ pA, $T=0.55~\\mathsf{K}$ , and $B_{\\bot}=4$ T. \n\nIt has been pointed out by previous theoretical studies (35–37) that the condition of a bulk vortex line, such as its chemical potential, has substantial influences on the Majorana mode on the surface by the vortex phase transition. In order to further characterize the effects of bulk vortex lines, we have monitored the temperature evolution of a ZBP. As shown in Fig. 3D, the ZBP intensity measured at a vortex center decreases with increasing temperature and becomes extremely weak at $4.2\\mathrm{K}$ and totally invisible at $6.0~\\mathrm{K}$ A peak associated with a CBS would persist to higher temperatures and exhibit simple Fermi-Dirac broadening up to about $T_{\\mathrm{c}}/2$ $(\\sim8~\\mathrm{K})$ , below which the SC gap amplitude is almost constant, as observed in our previous ARPES measurement (18). Our observation (Fig. 3D) contradicts this expectation and indicates an additional suppression mechanism that is likely related to the poisoning of MBS by thermally excited quasiparticles. From the extraction of ZBP amplitude measured on several different vortices (three cases are shown in Fig. 3E), we found that most of the observed ZBPs vanish around $3\\mathrm{K},$ , which is higher than the temperature in many previous Majorana platforms (11, 38). This vanishing temperature is comparable with the energy level spacing of the bulk vortex line as discussed above; thus, the temperature dependence we found is consistent with a case of a MBS poisoned by thermally induced quasiparticles inside the bulk vortex line (24). \n\nOur observations provide strong evidence for tunneling to an isolated MBS; many alternative trivial explanations [(24), part III] cannot account for all the observed features. It is technically possible to move a vortex by a STM tip, which in principle can be used to exchange MBSs inside vortices (Fig. 3F), consequently demonstrating non-Abelian statistics under a sufficiently low $(k_{\\mathrm{B}}T{\\ll}{\\Delta_{\\mathrm{sc}}}^{2}/E_{\\mathrm{F}})$ temperature (2). The high transition temperature and large SC gaps in this superconductor offer a promising platform to fabricate robust devices for topological quantum computation. \n\n# REFERENCES AND NOTES \n\n1. A. Y. Kitaev, Ann. Phys. 303, 2–30 (2003). \n2. C. Nayak, S. H. Simon, A. Stern, M. Freedman, S. Das Sarma, Rev. Mod. Phys. 80, 1083–1159 (2008). \n3. A. Y. Kitaev, Phys. Uspekhi 44 (10S), 131–136 (2001). \n4. N. Read, D. Green, Phys. Rev. B 61, 10267–10297 (2000). \n5. L. Fu, C. L. Kane, Phys. Rev. Lett. 100, 096407 (2008). \n6. R. M. Lutchyn, J. D. Sau, S. Das Sarma, Phys. Rev. Lett. 105, 077001 (2010). \n7. Y. Oreg, G. Refael, F. von Oppen, Phys. Rev. Lett. 105, 177002 (2010). \n8. A. C. Potter, P. A. Lee, Phys. Rev. Lett. 105, 227003 (2010). \n9. X.-L. Qi, T. L. Hughes, S.-C. Zhang, Phys. Rev. B 82, 184516 (2010). \n10. S. Nadj-Perge, I. K. Drozdov, B. A. Bernevig, A. Yazdani, Phys. Rev. B 88, 020407 (2013). \n11. V. Mourik et al., Science 336, 1003–1007 (2012). \n12. S. Nadj-Perge et al., Science 346, 602–607 (2014). \n13. H.-H. Sun et al., Phys. Rev. Lett. 116, 257003 (2016). \n14. M. T. Deng et al., Science 354, 1557–1562 (2016). \n15. Q.-L. He et al., Science 357, 294–299 (2017). \n16. Z.-J. Wang et al., Phys. Rev. B 92, 115119 (2015). \n17. X.-X. Wu, S. Qin, Y. Liang, H. Fan, J. Hu, Phys. Rev. B 93, 115129 (2016). \n18. P. Zhang et al., Science 360, 182–186 (2018). \n19. C. Caroli, P. G. de Gennes, J. Matricon, Phys. Lett. 9, 307–309 (1964). \n20. H. F. Hess, R. B. Robinson, J. V. Waszczak, Phys. Rev. Lett. 64, 2711–2714 (1990). \n21. T. Hanaguri, S. Niitaka, K. Kuroki, H. Takagi, Science 328, 474–476 (2010). \n22. F. Massee et al., Sci. Adv. 1, e1500033 (2015). \n23. H. Miao et al., Phys. Rev. B 85, 094506 (2012). \n24. Materials and methods are available as supplementary materials. \n25. Y. Wang, L. Fu, Phys. Rev. Lett. 119, 187003 (2017). \n26. C.-K. Chiu, M. J. Gilbert, T. L. Hughes, Phys. Rev. B 84, 144507 (2011). \n27. L.-H. Hu, C. Li, D.-H. Xu, Y. Zhou, F.-C. Zhang, Phys. Rev. B 94, 224501 (2016). \n28. J.-P. Xu et al., Phys. Rev. Lett. 112, 217001 (2014). \n29. J.-P. Xu et al., Phys. Rev. Lett. 114, 017001 (2015). \n30. F. Setiawan, C.-X. Liu, J. D. Sau, S. Das Sarma, Phys. Rev. B 96, 184520 (2017). \n31. S. Das Sarma, A. Nag, J. D. Sau, Phys. Rev. B 94, 035143 (2016). \n32. Y. Yin et al., Phys. Rev. Lett. 102, 097002 (2009). \n33. C. Renner, A. D. Kent, P. Niedermann, O. Fischer, F. Lévy, Phys. Rev. Lett. 67, 1650–1652 (1991). \n34. J. R. Colbert, P. A. Lee, Phys. Rev. B 89, 140505 (2014). \n35. P. Hosur, P. Ghaemi, R. S. K. Mong, A. Vishwanath, Phys. Rev. Lett. 107, 097001 (2011). \n36. H.-H. Hung, P. Ghaemi, T. L. Hughes, M. J. Gilbert, Phys. Rev. B 87, 035401 (2013). \n37. G. Xu, B. Lian, P. Tang, X.-L. Qi, S.-C. Zhang, Phys. Rev. Lett. 117, 047001 (2016). \n38. F. Nichele et al., Phys. Rev. Lett. 119, 136803 (2017). \n\n# ACKNOWLEDGMENTS \n\nWe thank Q. Huan, H. Isobe, X. Lin, X. Wu, and K. Yang for technical assistance and P. A. Lee, T. K. Ng, S. H. Pan, G. Xu, J.-X. Yin, F. C. Zhang, and P. Zhang for useful discussions. Funding: This work at IOP is supported by grants from the Ministry of Science and Technology of China (2013CBA01600, 2015CB921000, 2015CB921300, and 2016YFA0202300), the National Natural Science Foundation of China (11234014, 11574371, and 61390501), and the Chinese Academy of Sciences (XDPB08-1, XDB07000000, and XDPB0601). L.F. and G.G. are supported by the U.S. Department of Energy (DOE) (DE-SC0010526 and DE-SC0012704, respectively). J.S. and R.Z. are supported by the Center for Emergent Superconductivity, an Energy Frontier Research Center funded by the U.S. DOE. Author contributions: H.D., H.-J.G., L.K., Y.S., and S.D. designed the experiments. D.W., L.K., P.F., H.C., S.Z., W.L., and L.C. performed the STM experiments. J.S., R.Z., and G.G. provided the samples. L.F. provided theoretical models and explanations. All the authors participated in analyzing the experimental data, plotting the figures, and writing the manuscript. H.D. and H.-J.G. supervised the project. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The data presented in this paper can be found in the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/362/6412/333/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S7 \nTable S1 \nReferences (39–69) \nData File S1 \n22 June 2017; resubmitted 11 December 2017 \nAccepted 27 July 2018 \nPublished online 16 August 2018 \n10.1126/science.aao1797 \n\n# Science \n\n# Evidence for Majorana bound states in an iron-based superconductor \n\nDongfei Wang, Lingyuan Kong, Peng Fan, Hui Chen, Shiyu Zhu, Wenyao Liu, Lu Cao, Yujie Sun, Shixuan Du, John Schneeloch, Ruidan Zhong, Genda Gu, Liang Fu, Hong Ding and Hong-Jun Gao \n\nScience 362 (6412), 333-335. DOI: 10.1126/science.aao1797originally published online August 16, 2018 \n\n# An iron home for Majoranas \n\nThe surface of the iron-based superconductor $\\mathsf{F e T e}_{0.55}\\mathsf{S e}_{0.45}$ has been identified as a potential topological superconductor and is expected to host exotic quasiparticles called the Majorana bound states (MBSs). Wang et al. looked for signatures of MBSs in this material by using scanning tunneling spectroscopy on the vortex cores formed by the application of a magnetic field. In addition to conventional states, they observed the characteristic zero-bias peaks associated with MBSs and were able to distinguish between the two, owing to the favorable ratios of energy scales in the system. \n\nScience, this issue p. 333 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41929-018-0044-2", + "DOI": "10.1038/s41929-018-0044-2", + "DOI Link": "http://dx.doi.org/10.1038/s41929-018-0044-2", + "Relative Dir Path": "mds/10.1038_s41929-018-0044-2", + "Article Title": "Efficient hydrogen peroxide generation using reduced graphene oxide-based oxygen reduction electrocatalysts", + "Authors": "Kim, HW; Ross, MB; Kornienko, N; Zhang, L; Guo, JH; Yang, PD; McCloskey, BD", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Electrochemical oxygen reduction has garnered attention as an emerging alternative to the traditional anthraquinone oxidation process to enable the distributed production of hydrogen peroxide. Here, we demonstrate a selective and efficient non-precious electrocatalyst, prepared through an easily scalable mild thermal reduction of graphene oxide, to form hydrogen peroxide from oxygen. During oxygen reduction, certain variants of the mildly reduced graphene oxide electrocatalyst exhibit highly selective and stable peroxide formation activity at low overpotentials (<10 mV) under basic conditions, exceeding the performance of current state-of-the-art alkaline catalysts. Spectroscopic structural characterization and in situ Raman spectroelectrochemistry provide strong evidence that sp(2)-hybridized carbon near-ring ether defects along sheet edges are the most active sites for peroxide production, providing new insight into the electrocatalytic design of carbon-based materials for effective peroxide production.", + "Times Cited, WoS Core": 816, + "Times Cited, All Databases": 870, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000430451900015", + "Markdown": "# Efficient hydrogen peroxide generation using reduced graphene oxide-based oxygen reduction electrocatalysts \n\nHyo Won Kim1,2, Michael B. Ross   3, Nikolay Kornienko3, Liang Zhang4, Jinghua Guo4,5, Peidong Yang3,6,7 and Bryan D. McCloskey1,2\\* \n\nElectrochemical oxygen reduction has garnered attention as an emerging alternative to the traditional anthraquinone oxidation process to enable the distributed production of hydrogen peroxide. Here, we demonstrate a selective and efficient nonprecious electrocatalyst, prepared through an easily scalable mild thermal reduction of graphene oxide, to form hydrogen peroxide from oxygen. During oxygen reduction, certain variants of the mildly reduced graphene oxide electrocatalyst exhibit highly selective and stable peroxide formation activity at low overpotentials $(<10m\\forall)$ under basic conditions, exceeding the performance of current state-of-the-art alkaline catalysts. Spectroscopic structural characterization and in situ Raman spectroelectrochemistry provide strong evidence that $\\scriptstyle\\pmb{s p}^{2}$ -hybridized carbon near-ring ether defects along sheet edges are the most active sites for peroxide production, providing new insight into the electrocatalytic design of carbon-based materials for effective peroxide production. \n\nydrogen peroxide $\\mathrm{(H}_{2}\\mathrm{O}_{2})$ is a valuable chemical with rapidly growing demand in a variety of industries, including the paper and pulp, textile, and electronic industries, wastewater treatment, chemical oxidation (including the large-scale production of propene oxide from propene oxidation) and others1. The global $\\mathrm{H}_{2}\\mathrm{O}_{2}$ market demand was 3,850 kilotonnes in 2015 and is expected to reach roughly 6,000 kilotonnes in 2024, corresponding to $\\mathrm{US}\\$6.4$ billion (www.gminsights.com/pressrelease/hydrogen-peroxide-market). $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is currently generated at an industrial scale through the wellestablished anthraquinone oxidation process1. However, this process is a multi-step method involving expensive palladium hydrogenation catalysts that generate substantial organic byproduct waste1. Furthermore, the transport, storage and handling of bulk $\\mathrm{H}_{2}\\mathrm{O}_{2}$ are hazardous and therefore expensive, making the distributed ondemand production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ highly desirable1. Thus, electrochemical routes to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production through the oxygen reduction reaction (ORR) have attracted attention because of the advantages afforded by such processes, including low energy utilization and cost-effective$\\mathrm{ness^{1-5}}$ . We focus on $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis in alkaline environments, where the reaction bath may be directly used in certain applications, such as bleaching and the treatment of acidic waste streams6. However, for electrochemical ORR to achieve these advantages, selective, efficient and cost-effective electrocatalysts need to be developed. \n\nIn general, electrochemical ORRs can proceed through one of two reactions in an alkaline electrolyte: the $4\\mathrm{e}^{-}$ process to convert $\\mathrm{O}_{2}$ to $\\mathrm{H}_{2}\\mathrm{O}$ (equation (1)) or the $2e^{-}$ process to form $\\mathrm{HO}_{2}^{-}$ (equation (2))7. \n\n$$\n\\mathrm{O}_{2}+2\\mathrm{H}_{2}\\mathrm{O}+4\\mathrm{e}^{-}\\to4\\mathrm{OH}^{-}\\qquad\\mathrm{U}^{\\circ}=1.23\\mathrm{~V~versus~RHE}\n$$ \n\n$$\n\\mathrm{O}_{2}+\\mathrm{H}_{2}\\mathrm{O}+2\\mathrm{e}^{-}\\to\\mathrm{HO}_{2}^{-}+\\mathrm{OH}^{-}\\qquad\\mathrm{U}^{\\circ}=0.76\\mathrm{~V}\\mathrm{\\versus~RHE}\n$$ \n\nUo is the standard equilibrium potential for each reaction, calculated from the free energy of each reaction7,8, and RHE is the reversible hydrogen electrode. The reaction shown in equation (1) is important for alkaline fuel cell cathodes, where the energy from fuel oxidation is harnessed electrochemically1,9,10, whereas the reaction shown in equation (2) forms the environmentally friendly oxidant $\\mathrm{HO}_{2}^{-}$ $\\mathrm{(H}_{2}\\mathrm{O}_{2}$ in acidic media or its deprotonated anion but $\\mathrm{HO}_{2}^{-}$ in alkaline media; we will use $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and $\\mathrm{HO}_{2}^{-}$ interchangeably throughout this article)2–6. Of course, both reactions are extremely useful, especially if they can occur exclusively. The focus of this study is the efficient and selective catalysis of the reaction in equation (2). Electrode compositions that efficiently and selectively catalyse either reaction are desired with an overpotential as close to zero as possible. Numerous materials have been explored as potential electrocatalysts for the production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ from $\\mathrm{~O}_{2}$ reduction, including precious metals, transition metals, metal oxides, bimetallic alloys and carbon materials3,4,11–23. Of note, the state-of-the-art electrocatalysts for the reaction in equation (2) in acidic conditions are palladium–mercury alloys3,4. \n\nAs a result, an important goal is to develop a practical, cost-effective $\\mathrm{H}_{2}\\mathrm{O}_{2}$ formation electrocatalyst that exhibits high activity, selectivity and stability. To this end, we report a robust, metal-free catalyst formed through an easily scalable mild reduction of graphene oxide (mrGO), and present a simple method for preparing a few-layered mrGO electrode ( $\\cdot F{\\mathrm{-mrGO}})$ that disallows catalyst aggregation. We annealled the $F{\\mathrm{-}}\\mathrm{mrGO}$ electrodes at $600^{\\circ}\\mathrm{C}$ $(F{\\cdot}\\operatorname*{mr}G0(600)),$ and found further improvement of the mrGO electrocatalytic oxygen reduction performance. Both the $F{\\mathrm{-}}\\mathrm{mrGO}$ and $F\\mathrm{-mrGO}(600)$ catalysts exhibited highly selective and stable $\\mathrm{HO}_{2}^{-}$ formation activity with virtually no applied overpotential in alkaline electrolytes under pure $\\mathrm{O}_{2}$ or ambient air conditions. Ex situ materials characterization in combination with in situ Raman spectroelectrochemistry were performed on both materials and indicated that defects related to ether groups, such as epoxides, along the basal plane or at the sheet edges are active sites for $\\mathrm{HO}_{2}^{-}$ production, thereby providing insights into potential optimization for these and related carbonbased catalysts. \n\n# Results \n\nElectrocatalytic peroxide production using mrGO catalysts. Initially, we focused on the synthesis of mrGO and the preparation of $F.$ -mrGO electrodes. Unlike graphene oxide (GO), typical reduced graphene oxide $(\\mathrm{rGO})$ easily aggregates in solution due to strong hydrophobic interactions between the rGO sheets24. However, our mrGO synthesis procedure was optimized to prevent this aggregation (see Methods for a detailed procedure). This method resulted in slight reduction (oxygen loss) of the GO (Supplementary Fig. 1) and produced an aqueous solution of well-dispersed single or fewlayered mrGO (Supplementary Fig. 2). rGO aggregation is also a typically overlooked issue when preparing electrodes to characterize rGO, as rGO can aggregate during the drying process, thereby substantially reducing the accessibility of the rGO basal planes to reactants24. We therefore optimized electrode preparation to disrupt mrGO aggregation, allowing active sites along the mrGO basal plane to remain accessible. We used AvCarb P50 carbon paper—a porous conductive carbon—as a substrate for our electrochemical measurements given its poor ORR activity above $0.6\\mathrm{V}$ versus RHE (Supplementary Fig. 3), ease of processing and cost. After trials consisting of various deposition techniques, we found that simply dipcoating P50 sheets into the well-dispersed mrGO solution, followed by quickly removing water from the coated substrate and drying at ${\\sim}100^{\\circ}\\mathrm{C},$ provided an optimal, non-aggregated mrGO coating. The mrGO loading weight was about $10\\upmu\\mathrm{gcm}^{-2}$ , which is similar to the mass loading typically used in electrocatalyst characterization studies (Supplementary Table 1). We envision that this method could be easily modified to enable a simple traditional roll-to-roll process (Supplementary Fig. 4). \n\nAs confirmation of the few-layered mrGO coating, Raman spectroscopy on dip-coated electrodes exhibited a relatively sharp and single 2D Raman peak shift at $1{,}680\\mathsf{c m}^{-1}$ (Supplementary Fig. 5), as has previously been observed for few-layered (under 5) rGO assemblies25. In contrast, using a more conventional drop-casting method for mrGO electrode preparation, where an excess of the well-dispersed mrGO solution was dropped onto a P50 substrate and subsequently dried, no 2D Raman shifts were observed (Supplementary Figs. 5 and $6)^{24}$ , indicating mrGO aggregation $(A{\\mathrm{-mrGO}})$ on the electrode surface (Supplementary Fig. 7). Oxygen reduction measurements using linear sweep voltammetry (LSV) in well-mixed oxygen-saturated alkaline electrolytes confirmed that the $F$ -mrGO electrode had a higher specific activity at a given applied voltage, as well as a higher onset potential, than the $A$ -mrGO sample (Fig. 1a), although both outperformed a standard carbon black-based electrode with high surface area (Vulcan XC72 carbon). These combined results indicate that more active sites are accessible on the $F{\\mathrm{-}}\\mathrm{mrGO}$ electrodes compared with the $A{\\mathrm{-mrGO}}$ electrodes. High activities were also observed when $F{\\mathrm{-mrGO}}$ was deposited onto a glassy carbon electrode (Supplementary Fig. 8) and characterized using LSV at a rotating disk electrode (RDE; inset of Fig. 1a). In fact, higher activities were observed at the RDE compared with the porous P50 electrodes, presumably due to a reduction in mass transport limitations. Of note, a P50 electrode coated with non-reduced GO exhibited a similar current response to a pristine P50 electrode (Supplementary Fig. 9), indicating that the synthesized GO in this study had no metal impurities (Supplementary Fig. 10) that may have influenced ORR activity. Both the P50 substrate and a GO-coated P50 electrode have little activity above $0.6\\mathrm{V},$ implying that GO only becomes catalytically active after being slightly reduced. \n\nThe estimated equilibrium potential for $2\\mathrm{e}^{-}$ ORR (equation (2)) is $0.825\\mathrm{V}$ versus RHE when taking into account the non-idealities of a 0.1 M KOH solution (see the Supplementary Information for the equilibrium potential calculation). Therefore, at the onset potential for the $F{\\mathrm{-mrGO}}$ electrode $(\\sim0.8\\mathrm{V})$ , ORR can theoretically proceed through either $4\\mathrm{e}^{-}$ or $2\\mathrm{e^{-}}$ ORR (equation (1) or (2), respectively), such that the characterization of selectivity between the two reactions is important. To do so, we used a modified hermetically sealed electrochemical H-cell (Supplementary Fig. 11) that allowed direct quantification of oxygen consumption, as well as a quantitative peroxide titration. The modified H-cell had an easily calibrated headspace volume and an in-line pressure transducer to quantify $\\mathrm{O}_{2}$ pressure decay during ORR (Supplementary Fig. 12). This H-cell therefore afforded direct quantitative oxygen consumption detection during electrochemical measurements, providing accurate determination of ORR selectivity, which we report as Faradaic efficiency: total electrons consumed per oxygen molecule $(\\mathrm{e}^{-}/\\mathrm{O}_{2})$ . This setup is unique for ORR characterization as it also allows selectivity measurements immediately at the onset potential for ORR. In contrast, typical ORR catalyst selectivity analyses use a RDE or rotating ring disk electrode (RRDE), which relies on achieving mass transport limitations at modest to high overpotentials. Furthermore, when characterizing selectivity using RDE or RRDE, the hydrodynamic boundary layer can be influenced by the surface roughness inherent in attaching the catalyst to the electrode surface, which can reduce the accuracy of the analytical solution of the coupled momentum and mass balances initially derived by Levich for a smooth electrode surface26,27. Our analysis provided accurate measurements of selectivity through the direct quantitative measurement of oxygen consumption, regardless of catalyst surface roughness. For example, we measured a $4.0\\ \\mathrm{e}^{-}/\\mathrm{O}_{2}$ process during oxygen reduction at a commercial platinum/carbon catalyst in an alkaline electrolyte (Supplementary Fig. 13). \n\nThe cumulative $\\mathrm{e^{-}}$ and $\\mathrm{~O}_{2}$ consumptions during chronoamperometry (constant potential: $780{-}820\\mathrm{torr}\\mathrm{O}_{2}$ ) measurements are shown at a variety of applied voltages over time scales (Fig. 1b and Supplementary Fig. 14) that allow excellent accuracy for Faradaic efficiency calculations. Two important conclusions were gleaned from these results. First, regardless of the applied potential, $\\mathrm{a}2.0\\mathrm{e}^{-}/\\mathrm{O}_{2}$ process was observed (the average of all measurements in Fig. 1b is $2.00{\\pm}0.03{\\mathrm{e}}^{-}/\\mathrm{O}_{2})$ . This observation was supported by monitoring $\\mathrm{O}_{2}$ consumption during LSV, where a ${\\sim}2\\mathrm{e}^{-}/\\mathrm{O}_{2}$ process was observed at potentials as low as $0.1\\mathrm{V}$ (Supplementary Fig. 15). Second, a $2{\\mathrm{e}}^{-}/{\\mathrm{O}}_{2}$ process was observed for potentials as high as $0.80\\mathrm{V}.$ In a wellpoised cell $\\mathrm{(0.01M\\HO_{2}^{-}}$ ; 0.1 M KOH and $800\\mathrm{torr}\\mathrm{O}_{2})$ , where the equilibrium potential of the peroxide formation reaction (equation (2)) could be precisely calculated $(0.796\\mathrm{V}$ at these concentrations and pressures), we observed $\\mathrm{HO}_{2}^{-}$ formation activity onset at $0.78\\mathrm{V}$ (Supplementary Fig. 16), corresponding to a remarkably small overpotential of $16\\mathrm{mV}.$ Although we did not attempt ORR measurements at overpotentials less than $10\\mathrm{mV},$ the actual onset potential for $2\\mathrm{e}^{-}\\mathrm{ORR}$ on $F{\\mathrm{-mrGO}}$ is probably in this range. An iodometric $\\mathrm{H}_{2}\\mathrm{O}_{2}$ titration (see Methods for a description of the titration procedure) was also performed on the electrolyte after the chronoamperometry measurements to confirm $\\mathrm{HO}_{2}^{-}$ formation consistent with oxygen consumption measurements (that is, a $1.0\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}_{2}$ process was observed; see inset of Fig. 1b). Of note, we observed the selective $2\\mathrm{e^{-}}$ process regardless of the catalyst loading weight, and no additional peroxide reduction properties at modest $(>0.4\\mathrm{V}$ versus RHE) potentials (Supplementary Fig. 17). This indicates that our mrGO materials did not catalyse a $2+2$ electron transfer mechanism, as has been observed on some electrocatalysts, such as those based on Fe–N–C motifs, where loading-dependent selectivities were observed28. \n\n![](images/9cfa13be20a9fd36eb91af455512d6ff3d9d5539ef94772be3682defcae77fcd.jpg) \nFig. 1 | F-mrGO electrocatalytic properties for the ORR. a, Electrochemical $\\mathsf{O}_{2}$ reduction behaviour of the as-prepared $F{\\mathrm{-}}\\mathsf{m r G O}$ $A//B r G0$ and XC72- based electrodes (P50 porous carbon paper as a catalyst support) measured by cathodic LSV $2.0\\mathsf{m V s^{-1}})$ in an $\\mathsf{H}$ -cell (\\~800 torr $\\mathsf{O}_{2}$ saturated $0.1{\\ensuremath{\\mathsf{M}}}$ KOH solution). Inset is the cathodic LSV $(10.0\\mathsf{m V}\\mathsf{s}^{-1})$ at a glassy carbon (GC) rotating disk coated with $\\mathsf{m r G O}$ (rotation rates noted in rpm). An uncoated GC electrode LSV (2,800 rpm) is shown for comparison. Typical $\\mathsf{m r G O}$ powder loading is $10\\upmu\\upxi{\\mathsf{c m}}^{-2}$ for $F//\\mathsf{m r G O}$ in both RDE and porous electrode configurations, $200\\upmu\\upxi{\\mathsf{c m}}^{-2}$ for $A//B r G0$ and $200\\upmu\\upxi{\\mathsf{c m}}^{-2}$ for $\\times(72.6,$ Chronoamperometry in the same electrolyte at an $F//\\mathsf{m r G O}$ electrode at various potentials. The inset table is the corresponding ${\\bf e}^{-}/\\mathsf{O}_{2}$ from in situ pressure decay measurements and ${\\mathsf O}_{2}/{\\mathsf H}{\\mathsf O}_{2}^{-}$ where $H O_{2}^{-}$ was quantified from iodometric ${\\mathsf{H O}}_{2}^{-}$ titrations on the electrolyte extracted from the working electrode chamber after each measurement. c, Long-term stability of $F-\\mathsf{m r G O}$ in either $\\mathsf{O}_{2}$ saturated (\\~800 torr $\\mathsf{O}_{2})$ or air-exposed 0.1 M KOH. The potential was cycled using the voltage programme shown in the inset: repeating cycles of 1 min at various potentials—0.63 or $0.58\\mathsf{V},$ followed by 1 min at $0.83\\mathsf{V},$ at which no measurable current was observed. The electrode surface area was $0.5\\mathsf{c m}^{2}$ $(10\\upmu\\mathrm{g}\\mathsf{c m}^{-2}\\mathsf{m r}\\mathsf{G}\\mathsf{O})$ . d, Structural changes in $F-m r G O$ before and after long-term stability measured at 0.63 and $0.58\\mathsf{V}$ (versus RHE) in either $\\mathsf{O}_{2}$ or air. XPS data were collected on the $F//\\mathsf{m r G O}$ electrodes before and after the long-term stability tests shown in c. \n\nThe catalyst current response at $0.63\\mathrm{V}$ under pure $\\mathrm{~O}_{2}$ also remained constant during the course of a long-term measurement (Fig. 1c; the current plotted was that measured at the end of each 1 min cycle), implying good stability of the catalyst over long operational periods at these modest overpotentials. Although catalyst instability was observed at larger overpotentials in pure $\\mathrm{O}_{2}$ conditions (for example, an applied potential of $0.58\\mathrm{V}$ ; Fig. 1c), $F$ -mrGO stability improved at lower oxygen partial pressures (for example, in ambient air) at applied potentials down to $0.45\\mathrm{V}$ 1 $\\mathrm{\\Delta}0.58\\mathrm{V}$ is shown in Fig. 1c and $0.45\\mathrm{V}$ is shown in Supplementary Fig. 18), allowing larger current rates to be achieved while still maintaining catalyst stability. In support of these electrochemical stability observations, X-ray photoelectron spectroscopy (XPS) characterization of the electrodes indicated no structural changes in the catalyst composition during a $16\\mathrm{h}$ chronoamperometry cycling measurement (using the programme shown in the inset of Fig. 1c) when operated at $0.63\\mathrm{V}$ in pure $\\mathrm{O}_{2}$ or $0.58\\mathrm{V}$ in ambient air (Fig. 1d), although large changes were observed in the electrode operated at $0.58\\mathrm{V}$ in pure $\\mathrm{O}_{2}$ (Fig. 1d and Supplementary Fig. 19). From an iodometric $\\mathrm{H}_{2}\\mathrm{O}_{2}$ titration performed on the electrolyte, the total amount of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ formed during the measurement that provided an optimal current rate and stability $(0.45\\mathrm{V}$ under ambient air for $15\\mathrm{h}$ ) corresponds to $37\\mathrm{mg}\\mathrm{H}_{2}\\mathrm{O}_{2}$ produced per $10\\upmu\\mathrm{g}$ of mrGO. Taken together, these results confirm that $F{\\mathrm{-mrGO}}$ is an excellent catalyst for $\\mathrm{HO}_{2}^{-}$ formation: it is highly selective, active at overpotentials as low as ${\\sim}0.01\\mathrm{V}$ and stable at potentials where $\\mathrm{HO}_{2}^{-}$ is formed at high rates. \n\nIn situ Raman spectroelectrochemical analysis of F-mrGO. In general, the structural heterogeneity of $\\mathrm{rGO}$ materials makes the identification of catalytically active sites difficult29–31, and our $F{\\mathrm{-mrGO}}$ catalysts were no different. XPS indicated that numerous oxygen-containing functional groups, including ether, hydroxyl, ketone and carboxylic acid groups, were present in the mrGO catalyst (Supplementary Fig. 1). In an attempt to identify the active site in our mrGO catalysts for $\\mathrm{HO}_{2}^{-}$ formation, we pursued two approaches: in situ Raman characterization, which we used to probe catalyst–adsorbate interactions during catalysis, and further thermal treatment to modify the mrGO oxygen defect composition. \n\nRaman spectroscopy has been used extensively to characterize the structure of carbon-based materials32. Thus, we used in situ Raman spectroelectrochemistry to probe any transient adsorbate– catalyst interactions that occurred during oxygen reduction. Such spectroscopic characterization of carbon electrolcatalysts during oxygen reduction is lacking, thereby limiting the understanding of how to improve electrocatalyst activity15–23. We employed a cell configuration that allowed Raman spectroscopy to be performed at a biased electrode immersed at a very shallow depth in the cell’s electrolyte (Supplementary Fig. 20). The $F{\\mathrm{-mrGO}}$ electrode was characterized at various applied potentials (using chronoamperometry) in an $\\mathrm{O}_{2}$ −​saturated electrolyte. Of note, no changes in the Raman spectra were observed at these same potentials in an $\\Nu_{2}$ −​saturated electrolyte (Supplementary Fig. 21), and the Raman spectra of the $F{\\mathrm{-mrGO}}$ electrode at open circuit voltage (OCV) with $\\mathrm{O}_{2}$ - saturated electrolyte and of a dry $F{\\mathrm{-mrGO}}$ electrode were similar (Supplementary Fig. 22). We also observed almost identical Raman spectra between an immersed $F{\\mathrm{-mrGO}}$ in electrolyte with and without peroxide added (Supplementary Fig. 23), indicating that any spectra differences during voltage bias were due to interactions between the catalyst and adsorbed reaction intermediates and not between the $\\mathrm{HO}_{2}^{-}$ product and the catalyst. In addition, the Raman spectra of the pristine P50 electrodes were nearly identical at OCV and the lowest applied potential we probed $(0.63\\mathrm{V}$ Supplementary Fig. 24), indicating that any changes in the Raman spectra were due exclusively to the mrGO catalysts. All fits reported in this study follow the Voigt deconvolution method31. \n\nRaman spectra of disordered carbon materials typically exhibit four major Raman bands, which are referred to as the G band $(\\sim1,580\\mathrm{cm}^{-1})$ , D band $(\\sim1,350\\mathrm{cm}^{-1})$ ), $\\mathbf{D^{\\prime}}$ band (or sometimes $\\mathbf{G^{\\prime}}$ band; $\\sim1{,}620\\ c m^{-1},$ ) and 2D band $(2,680\\mathsf{c m}^{-1})$ . The 2D band is generally related to interactions between neighbouring graphitic planes, indicating variations in sheet stacking or the total number of graphene layers32. Although the oxygen atom surface coverage also slightly influences the 2D band, it is difficult to decouple this effect from interplane interactions in rGO-based materials32. We therefore focused on the relative intensities and peak broadening of the D and $\\mathbf{D^{\\prime}}$ ​bands relative to the ubiquitous G band. Numerous studies have shown that each of these bands is related to certain defects in oxidized disordered carbon. Of particular importance, the $\\mathbf{D^{\\prime}}$ ​band has been previously ascribed to $s p^{2}$ basal plane carbon oxidation in graphene-based materials32, whereas the D band appears as a result of carbon disorder (for example, $s p^{3}$ disorder in graphene basal planes) and graphene planar edge site defects30. Therefore, any changes in these Raman peaks during ORR probably indicate an interaction between the corresponding $\\mathrm{\\mrGO}$ carbon sites and intermediates for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ formation—probably ${\\mathrm{O}}_{2}^{-*}$ or ${\\mathrm{OOH}}^{*}$ $^{\\circ}\\ast$ indicating an adsorbed species)20,32. \n\nAs the applied potential decreased from 0.83 to $0.63\\mathrm{V},$ noticeable changes in the spectra began to evolve at $0.78\\mathrm{V}$ (Fig. 2a,b), indicating the occurrence of an mrGO–adsorbate interaction consistent with the onset of ORR (Fig. 2b and Supplementary Fig. 16). At low overpotentials (where the applied potential was above $0.68\\mathrm{V})$ , several interesting trends were observed: as the overpotential increased, the characteristic $\\mathbf{D^{\\prime}}$ ​band peak area increased and broadened from $42.5{-}59.2\\mathrm{cm}^{-1}$ at the full-width at half peak maximum (FWHM). However, both the D and G band FWHM and peak area remained relatively constant (Fig. 2b). Given that the D band remained unchanged in the $0.83{-}0.68\\mathrm{V}$ region, the low-overpotential active sites on $F$ -mrGO appeared to not be associated with edge site defects or $s p^{3}$ -hybridized carbon (the defects ascribed to the D band by others)32. Instead, broadening of the $\\mathbf{D^{\\prime}}$ band in this same voltage region implied that basal plane $s p^{2}$ carbon sites interacted with adsorbed ORR intermediates at low overpotentials, resulting in a Raman response similar to what is observed when such $s p^{2}$ carbon is oxidized. This observation suggests that certain $s p^{2}$ basal plane carbon sites were catalytically active for $2e^{-}\\mathrm{ORR}$ . These are unusual results because most believe that edge sites are more active than basal plane sites in carbon-based materials33–35, although through mrGO annealing, we will show later that edge sites can also be highly active for $\\mathrm{HO}_{2}^{-}$ formation. Of note, the Raman spectra at OCV before and after an ORR measurement at $0.63\\mathrm{V}$ were statistically similar (Supplementary Fig. 21), indicating that no irreversible oxidation of these sites was observed (as is consistent with the results shown in Fig. $^{\\mathrm{1c,d}}.$ ). At lower applied potentials (0.63 V), all three peaks (D, $\\mathbf{D^{\\prime}}$ and G) broadened and the intensity of the D band substantially increased relative to the G and $\\mathbf{D^{\\prime}}$ bands (as observed in the ratio of the peak areas in Fig. 2b), implying that edge site and/or $s p^{3}$ -hybridized carbon defects also interact with adsorbed intermediates at these lower voltages. \n\nCharacterization of thermally annealed F-mrGO. Based on these results, we hypothesized that the highly active (low overpotential) $F{\\mathrm{-mrGO}}$ sites were basal plane $s p^{2}$ carbons adjacent to certain oxygen functional groups. This hypothesis was tested by electrochemical and physical characterization of thermally annealed $F$ -mrGO electrodes. Thermal annealing of GO has previously been shown to substantially reduce GO’s oxygen content and influence its oxygen defect site composition30,31. In this study, the $F$ -mrGO electrodes (with P50 carbon paper as a catalyst support) were first prepared to ensure the electrodes comprised non-aggregated, few-layered mrGO without any binders. These electrodes were then thermally annealed under an $\\mathrm{N}_{2}$ atmosphere. This procedure disallowed the facile preparation of annealed mrGO RDE electrodes, and hence electrochemistry was only performed on porous electrodes. Thermal treatment temperatures were selected to be 300 and $600^{\\circ}\\mathrm{C},$ as thermogravimetric analysis-mass spectrometry indicated that substantial $\\mathrm{CO}_{2}$ evolution occurred around these temperatures (Supplementary Fig. 25), indicating the removal of oxygen from the mrGO. Although thermal treatment led to the decomposition of oxygen-containing functional groups, the annealed samples maintained their few-layered structure (Supplementary Fig. 26). Of note, the P50 substrate appeared to be thermally stable up to $650^{\\mathrm{{o}C}}$ under $\\mathrm{N}_{2}$ (Supplementary Fig. 27), as no weight change was observed during a thermal gravimetric analysis measurement. Furthermore, annealing of the pristine P50 substrate at 300 or $600^{\\circ}\\mathrm{C}$ did not change its catalytic activity (Supplementary Fig. 28). \n\nXPS confirmed that thermal annealing substantially reduced the presence of C–O and $\\scriptstyle{\\mathrm{C=O}}$ bonds in the mrGO, with their atomic percentages dropping from 21.8 and 6.1 for mrGO to 1.4 and 1.4 for mrGO annealed at $300^{\\circ}\\mathrm{C}$ , respectively (Fig. 3a). $s p^{2}$ carbon bonding in the mrGO annealed at $300^{\\circ}\\mathrm{C}$ increased to $66\\%$ from $32\\%$ in unannealed mrGO. These results indicate that thermal treatment at $300^{\\mathrm{o}}\\mathrm{C}$ results in a significant reduction of carbon defects associated with oxygen functional groups on the mrGO basal planes31. \n\nAlthough mrGO annealed at $300^{\\circ}\\mathrm{C}$ and coated on P50 $\\left(F{\\cdot}\\operatorname*{mr}G\\mathrm{O}(300)\\right).$ ) still catalysed a $2\\mathrm{e}^{-}$ ORR process at all applied potentials (Supplementary Fig. 29), ${\\cal F}{\\mathrm{-mrGO}}(300)$ exhibited a lower onset potential and lower specific activity at a given applied potential than unannealed $F$ -mrGO (Fig. 3b). This observation, coupled with the smaller oxygen-atomic composition in $F{\\mathrm{-mrGO}}(300)$ (Supplementary Fig. 30) compared with unannealed $F{\\mathrm{-mrGO}}$ (Supplementary Fig. 1), suggests that the reduction of oxygen defects during the $300^{\\circ}\\mathrm{C}$ thermal annealing results in a material with lower catalytic activity. XPS (Fig. 3a) indicated that among the oxygen defects initially present, the $C{\\mathrm{-}}\\mathrm{O}$ and $\\scriptstyle{\\mathrm{C=O}}$ concentration in the mrGO catalysts was substantially reduced during the $300^{\\mathrm{o}}\\mathrm{C}$ annealing, implying that active sites for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production may be related to one (or both) of these groups. \n\nSurprisingly, $F\\mathrm{-mrGO}(600)$ exhibited a higher onset potential during ORR than unannealed $F$ -mrGO (Fig. 3b) while still maintaining a $2e^{-}$ process at all potentials, including $0.815\\mathrm{V}$ versus \n\n![](images/97c36af6132e33c8938f71f12ca698a973a2006c1ca748189b50d5161b648acd.jpg) \nFig. 2 | Raman spectroelectrochemistry during ORR measurements at F-mrGO and F-mrGO(600) electrodes. a, In situ Raman spectra—with calculated Voigt deconvolutions—of $F\\mathrm{-}\\mathsf{m r G O}$ at various potentials. ORR occurs below 0.80 V. b, FWHM and $\\mathsf{D}/(\\mathsf{G}+\\mathsf{D}^{\\prime})$ ratio of $F-\\mathsf{m r G O}$ electrodes as a function of applied potentials. c, FWHM and the $\\mathsf{D}/(\\mathsf{G}+\\mathsf{D}^{\\prime})$ ratio of $F-\\mathsf{m r G O}(600)$ electrodes as a function of applied potentials. In b and c, the error bars represent the s.d. of three trials. d, In situ Raman spectra of $F-\\mathsf{m r G O}(600)$ at various potentials. Oxygen-saturated (\\~760 torr) 0.1 M KOH was used as the electrolyte. \n\nRHE (Supplementary Fig. 31). In a well-poised cell $(0.01\\mathrm{M}\\mathrm{HO}_{2}^{-}$ , $0.1\\mathrm{MKOH}$ and 800 torr $\\mathrm{O}_{2}^{\\cdot}$ ), activity was observed at a statistically similar potential to the equilibrium potential $(\\sim0.80\\mathrm{V})$ , implying activity with only millivolts of applied overpotential (Supplementary Fig. 32). $F{\\mathrm{-mrGO}}(600)$ showed high mass activity for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production that exceeded current state-of-the-art electrocatalysts in either acidic or alkaline electrolytes (Fig. 4), although we note that the comparison between electrocatalysts in acidic and alkaline media is not straightforward given the differences in required design criteria between the two systems. The high catalytic activity of $F\\mathrm{-mrGO}(600)$ was unexpected given that the oxygen content in mrGO annealed at $600^{\\mathrm{{o}C}}$ was much lower than in either mrGO annealed at $300^{\\circ}\\mathrm{C}$ or unannealed mrGO (Supplementary Figs. 1 and 30). However, a combination of structural characterization using XPS, Fourier-transform infrared spectroscopy (FTIR) and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, as well as in situ Raman spectroscopy, implicated ring ether defect formation along the mrGO sheet edges as the possible origin for this increase in catalytic activity, as is discussed below. \n\nCombined spectroscopic analyses to identify active sites in F-mrGO.FromXPScharacterizationofthemrGOmaterials(Fig.3a), mrGO annealed at $600^{\\circ}\\mathrm{C}$ showed a dramatic decrease in carboxylic acid group content and a modest increase in ether C–O group content compared with mrGO annealed at $300^{\\circ}\\mathrm{C}$ . This result implies that carboxylic acid groups decompose to generate new ether functional groups, which is consistent with previous reports30,31. Carboxylic acid functionalities are known to primarily exist at rGO sheet edges29, such that we would expect ether groups in $F\\mathrm{-mrGO}(600)$ to be located primarily at sheet edges. In support of this theory, FTIR spectroscopy (Fig. 3c) on powders of annealed and unannealed mrGO showed that a strong and sharp infrared absorption band at $800\\mathrm{cm}^{-1}$ appears in $\\mathrm{\\mr{GO}}$ annealed at $600^{\\circ}\\mathrm{C},$ which was ascribed in recent reports to ether functionalities at the sheet edges of thermally reduced $\\mathrm{GO}^{30,31}$ . Furthermore, from the O K-edge NEXAFS spectra of dry mrGO powders, sharp and intense peaks at 534.5 and $540.4\\mathrm{eV}$ arose in mrGO annealed at $600^{\\circ}\\mathrm{C}$ (Fig. 3d), even though it had low oxygen content compared with unannealed mrGO and mrGO annealed at $300^{\\mathrm{o}}\\mathrm{C}$ (Supplementary Figs. 1 and 30). These peaks can be ascribed to transitions of O1s core-level electrons to antibonding $\\pi^{*}$ states and $\\sigma^{*}$ states from $C{\\mathrm{-}}0$ bonding from ring ether functionalities at the rGO sheet edges36,37. These distinct features are explained by locally ordered arrangements of ring ether groups at the sheet edges of the mrGO annealed at $600^{\\mathrm{o}}\\mathrm{C}$ that result in constructive interference35. Combined, our XPS, FTIR and NEXAFS data strongly suggest that mrGO thermal treatment at $600^{\\mathrm{o}}\\mathrm{C}$ produces ring ether groups at mrGO sheet edges30,31,36,37. Furthermore, thermal treatment at $600^{\\circ}\\mathrm{C}$ generates a high concentration of these active ring ether edge sites compared with unannealed mrGO, resulting in higher peroxide formation activity (Fig. 3b). Of note, although the annealing process may influence the electrical conductivity of the mrGO samples, four-point probe measurements on each of the electrodes indicate that the electrical conductivities of $F{\\mathrm{-}}\\mathrm{mrGO}$ and $F\\mathrm{-mrGO}(600)$ electrodes are similar to that of the bare P50 substrate and in the range of $\\sim4{,}000\\mathsf{S m}^{-1}$ We are therefore confident that conductivity differences probably do not influence our catalytic trends, but further studies would be helpful to rule this possibility out entirely. Furthermore, the longterm activity of $F\\mathrm{-mrGO}(600)$ was equally as stable as unannealed $F{\\mathrm{-mrGO}}$ under a variety of $\\mathrm{O}_{2}$ partial pressures and applied potentials, including relatively large overpotentials $(0.45\\mathrm{V})$ under either $\\mathrm{O}_{2}$ or ambient conditions (Supplementary Fig. 33). \n\n![](images/fc49d78c7cf4720b68bb4c5a8508e8d71c160496c81e89d18f078bac3f8edc87.jpg) \nFig. 3 | Structural characterization and electrocatalytic activity of thermally annealed F-mrGO electrodes. a, Atomic ratio of the as-prepared, unannealed mrGO and annealed (300 and $600^{\\circ}\\mathsf{C}\\$ ) mrGO powders measured by C1s XPS. The error bars represent the s.d. of three measurements. b, Electrochemical $\\mathsf{O}_{2}$ reduction behaviour of the as-prepared $\\mathsf{m r G O}$ and annealed mrGOs measured by cathodic LSV $(2.0\\mathsf{m V}\\mathsf{s}^{-1})$ in $\\mathsf{O}_{2}$ -saturated (\\~800 torr $\\mathrm{O}_{2}^{\\cdot}$ ) 0.1 M KOH solution. c, FTIR spectra of various $\\mathsf{m r G O}$ powder samples. Peak assignments are discussed in more detail in the Methods. d, High-resolution oxygen K-edge NEXAFS spectra of unannealed and annealed $\\mathsf{m r G O}$ powder samples. e, Idealized schemes of proposed low-overpotential active sites on $F-m r G O$ and F-mrGO(600). \n\nIn situ Raman spectra of the $F\\mathrm{-mrGO}(600)$ electrode during ORR (Fig. $^{2\\mathrm{c},\\mathrm{d})}$ ) also support the suggestion that the active site for $\\mathrm{HO}_{2}^{-}$ formation is related to edge site defects in $F$ -mrGO(600). In contrast with the unannealed $F$ -mrGO sample, a substantial increase in D band peak intensity was observed once small cathodic overpotentials were applied; that is, $\\mathrm{D}/(\\mathrm{G}+\\mathrm{D}^{\\prime})$ substantially increased from OCV to $0.78\\mathrm{V}$ ( $\\ensuremath{\\mathrm{\\T}}\\ensuremath{\\mathrm{40}}\\ensuremath{\\mathrm{mV}}$ overpotential for $\\mathrm{HO}_{2}^{-}$ formation; Fig. 2c). In fact, broadening and increasing peak areas of both the $\\mathrm{~D~}$ and $\\mathbf{D^{\\prime}}$ ​ bands were clearly observed at low overpotentials (Fig. $^{2\\mathrm{c},\\mathrm{d}},$ , indicating that $s p^{2}$ -hybridized carbon (as has been ascribed to $\\mathrm{D^{\\prime}}$ band broadening) located at the sheet edges (as has been ascribed to D band broadening) interacts with adsorbed intermediates in this potential regime. Given the XPS, FTIR and NEXAFS results (Fig. 3), which suggest that ring ether groups are present at sheet edges in $F{\\mathrm{-mrGO}}(600)$ , the Raman results strongly suggest that the active sheet edge $s p^{2}$ carbon sites for $\\mathrm{HO}_{2}^{-}$ formation are related to ring ether groups. As for the unannealed mrGO electrode, the Raman spectra at OCV were similar before and after an ORR measurement at lower overpotentials $\\operatorname{\\rho}_{0.63\\mathrm{V}}$ applied potential), confirming the reversibility of this interaction (Supplementary Fig. 34). \n\n![](images/512ac29e4f710ae4d0da1f60a2edec533ba3d01c9a4fa28a0f43b48730999b58.jpg) \nFig. 4 | Mass activity of different electrocatalysts for ${\\sf H}_{2}{\\sf O}_{2}$ production. Mass activity was calculated using electrochemical data and catalyst loading values from the literature. Further details of these calculations are available in Supplementary Table 1. The data presented as dashed lines were measured in acidic conditions $\\langle0.1M\\ H{\\subset}|0_{4}\\rangle$ and the data presented as solid lines were measured in basic conditions $(0.1M\\mathsf{K O H})$ . Data were taken from precious metals and their alloys3,4,11,13 and carbonbased catalysts10,14. Data for XC72, A-mrGO, F-mrGO at RDE, F-mrGO at PE and $F\\mathrm{-}\\mathsf{m r G O}(600)$ at PE are from the present study, where ‘at RDE’ and 'at PE' denote values measured in a rotating disk and porous electrode configuration, respectively. \n\n# Conclusions \n\nIn conclusion, carbon-based materials show great promise for electrochemical $\\mathrm{HO}_{2}^{-}$ production from $\\mathrm{O}_{2}$ given their potential affordability and excellent electrocatalytic performance compared to other $\\mathrm{HO}_{2}^{-}$ formation catalysts. Here, we show how to appropriately design a carbon-based electrocatalyst for $\\mathrm{HO}_{2}^{-}$ formation using a suite of capabilities aimed at understanding defect structure and property relationships for rGO catalysts. We suggest that carbon catalysts with high concentrations of epoxy or ring ether groups located either on their basal planes or at plane edges exhibit outstanding electrochemical $\\mathrm{HO}_{2}^{-}$ production in terms of activity $\\mathrm{(HO}_{2}^{-}$ production at ${<}10\\mathrm{mV}$ overpotential), selectivity $(\\sim100\\%$ $2\\mathrm{e}^{-}\\mathrm{ORR})$ and stability (over $15\\mathrm{h}$ at $0.45\\mathrm{V}$ ) in alkaline conditions. The best catalyst reported here, $F–\\mathrm{mrGO}(600)$ , exhibited activity and selectivity towards $\\mathrm{HO}_{2}^{-}$ production exceeding reported stateof-the-art catalysts. As such, these and related catalysts are very promising candidates for the electrochemical production of $\\mathrm{HO}_{2}^{-}$ . Furthermore, carbon materials are typically used as supports for high-surface-area $4\\mathrm{e}^{-}$ ORR catalysts8,9, and the knowledge gained here indicates that the design and synthesis of any such materials should involve the elimination of ether-based defects from carbon substrates to improve the $4\\mathrm{e}^{-}$ ORR selectivity. \n\n# Methods \n\nMaterials. Fine-grade synthetic graphite powder (SP-1) was supplied by Bay Carbon and used as received. Sulphuric acid $(\\mathrm{H}_{2}\\mathrm{SO}_{4};97\\%)$ , hydrochloric acid (HCl; $35\\%$ in water) and acetone ( $\\mathrm{CH_{3}C O C H_{3}}$ ; $99.5\\%$ ) from Daejung Chemicals and Metals, hydrogen peroxide $\\mathrm{(H}_{2}\\mathrm{O}_{2};50\\%$ in water), phosphorous pentoxide $(\\mathrm{P}_{2}\\mathrm{O}_{5};98\\%)$ and ethylenediaminetetraacetic acid (ACS reagent) from Aldrich Chemical, and potassium permanganate $\\mathrm{(KMnO_{4})}$ ) from Junsei Chemical were also used as received. \n\nGO synthesis and purification. GO was synthesized using the modified Hummers method. Briefly, sulphuric acid $(450\\mathrm{ml})$ was added to graphite powder $(10\\mathrm{g})$ and the temperature of the solution was maintained below $10^{\\circ}\\mathrm{C}$ and stirred for $90\\mathrm{min}$ . A small amount $(1.5\\mathrm{g})$ of potassium permanganate was added to the mixture and stirred for $90\\mathrm{min}$ . Then, a large amount of potassium permanganate $(30\\mathrm{g})$ was added to the mixture and stirred for $\\ensuremath{1\\mathrm{h}}$ at ${<}10^{\\circ}\\mathrm{C}$ The solution changed in colour from black to dark green. The solution was then heated to $40^{\\circ}\\mathrm{C}$ and stirred for 1 h. Deionized water $(450\\mathrm{ml})$ was added to the solution in a dropwise fashion and the temperature was maintained below $50^{\\mathrm{{o}C}}$ to prevent a rapid increase in temperature that could result in a thermal explosion. The solution turned brown. The solution was then heated to $95^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ , and hydrogen peroxide solution $(10\\mathrm{\\wt.\\%}$ : $300\\mathrm{ml},$ was slowly added to the solution and stirred for $30\\mathrm{min}$ . The solution changed to light yellow. Synthesized GO was purified with hydrochloric acid and acetone. The GO solution was filtered and washed with hydrochloric acid $(10\\mathrm{wt\\%}$ ; $\\left.5,000\\mathrm{ml}\\right)$ five times. Inductively coupled plasma optical emission spectrometry measurements after each rinse cycle indicated that only after five rinses were no metal impurities present in the GO (Supplementary Fig. 10). Filtered GO cake was dried over phosphorous pentoxide at $40^{\\circ}\\mathrm{C}$ for 24 h under vacuum. The GO powder was redispersed in acetone $(5,000\\mathrm{ml})$ and filtered and washed five times. The cake layer was dried at $40^{\\mathrm{{o}C}}$ for 24 h under vacuum. \n\nSynthesis of mrGO. The synthesized and purified GO was dispersed homogeneously in water using a sonication bath. The dispersed GO solution (0.1 wt. $\\%$ ) was added to a round-bottom flask $(500\\mathrm{ml})$ and stirred under flowing nitrogen. The prepared solution was maintained at $100^{\\circ}\\mathrm{C}$ and stirred overnight. After completion, the mrGO was filtered and rinsed several times with ultrapure water, and the mrGO was suspended in ultrapure water before use. \n\nCatalyst structural characterization. Raman spectra were recorded using a Horiba Jobin-Yvon LabRAM $\\mathrm{HR}800\\upmu$ ​-Raman instrument. All Raman spectra were acquired with $532\\mathrm{nm}$ excitation from a $250\\mathrm{mW}$ diode laser. The incident laser power was decreased by a factor of 100 to avoid sample damage. For analysis, the D/G ratio and FWHM of D, G and $\\mathbf{D^{\\prime}}$ ​were calculated by deconvoluting the Raman spectra using Gaussian, Lorentz and Voigt (combining Gaussian and Lorentz) peak fitting (Origin 8.5) to allow a comparison of peak areas. All deconvolution methods provided similar results, and the Voigt fitting method is reported throughout this study. Peak fitting and deconvolution followed wellestablished methods for such analyses38–40. \n\nElectrical conductivity was measured using a home-built probe station setup. Unannealed and annealed mrGO-coated P50 and pristine P50 $(\\sim0.5\\mathrm{cm}\\times1.0\\mathrm{cm};$ $0.17\\mathrm{mm}$ thick) were used to measure the electrical conductivity. The sheet resistance of each film was measured using Keithley 2400 source meters in fourwire van-der-Pauw configuration. Ohmic contacts were confirmed before all measurements, and data were acquired using homemade LabVIEW programmes. Electrical conductivity was extracted from the sheet resistance and thickness measurements. \n\nXPS was performed using a monochromatized Al Kα​X-ray source (Quantum 2000; Physical Electronics). C1s and O1s peak data were collected to analyse the extent of oxidation of GO, mrGO and annealed mrGO, and all C/O ratios provided were based on the relative peak areas of the C1s and O1s peaks. For detailed analysis, the peaks were deconvoluted into five or six Gaussian peaks to allow a comparison of peak areas after performing a Shirley baseline correction. Deconvolution followed well-established techniques for XPS analysis41–43. \n\nFTIR spectra of modified GOs were measured using a Bruker model IFS $66\\mathrm{V}$ equipped with a liquid nitrogen cooled mercury cadmium telluride detector (Kolmar model KMPV8-1-J2) with an ${8\\upmu\\mathrm{m}}$ band gap in the range $4,000{-}1,000{\\mathrm{cm}}^{-1}$ . Various functional groups were observed, including hydroxyls (broad peak at $3,050{-}3,800\\mathrm{cm^{-1}}$ ), carbonyls $(1,750-1,850\\mathrm{cm}^{-1},$ , carboxyls (1,650– $1{,}750\\mathsf{c m}^{-1},$ ), $\\scriptstyle{\\mathrm{C}}={\\mathrm{C}}$ $(1,500{-}1,600{\\mathrm{cm}}^{-1})$ , and ethers and epoxides $(1,000{-}1,280\\mathrm{cm^{-1}})$ , along with an unusual sharp and strong asymmetric ring ether $(\\sim800\\mathrm{cm}^{-1},$ ) after $600^{\\mathrm{o}}\\mathrm{C}$ thermal treatment, and regions of spectral overlap involving mostly C–O and $\\scriptstyle{\\mathrm{C=O}}$ contributions ( $\\upalpha$ -region, $\\upbeta$ ​-region and $\\boldsymbol{\\upgamma}$ -region). \n\nNEXAFS experiments were performed on the undulator beamline 8.0.1.4 (wet-resonant inelastic X-ray scattering (RIXS) endstation) at the Advanced Light Source, Lawrence Berkeley National Laboratory. The NEXAFS measurements were recorded in total-electron-yield mode by monitoring the sample drain current. The NEXAFS resolution was set to $0.2\\mathrm{eV}$ for oxygen. The energy scales of the oxygen K-edge NEXAFS spectra were calibrated by the spectrum of a standard $\\mathrm{TiO}_{2}$ sample. The NEXAFS spectra were first divided by the incident beam intensity and then normalized to the absorption pre- and post-edges. The surface morphologies of \n\nthe prepared electrodes were determined using a field emission scanning electron microscope (JSM-7500F; JEOL). The thermal stabilities of mrGO, P50 and coated P50 were measured by thermal gravimetric analysis coupled with mass spectroscopy (TA Instruments) under an argon atmosphere at a heating rate of $10^{\\mathrm{{o}C\\operatorname*{min}^{-1}}}$ . \n\nCatalyst-coated porous electrode preparation. The $F{\\mathrm{-mrGO}}$ electrodes were prepared by immersing a pre-cut strip $(2\\mathsf{c m}\\times0.5\\mathsf{c m})$ of AvCarb P50 carbon paper (Fuel Cell Store) in a prepared mrGO solution $(0.05\\mathrm{wt.\\%})$ for 1 min, followed by immediate drying using a heat gun and then drying under ambient conditions at $100^{\\mathrm{o}}\\mathrm{C}$ overnight. We note that no polymer binders were used in the preparation of the $F{\\mathrm{-mrGO}}$ electrodes to further avoid unwanted aggregation of mrGO in the casting solution. mrGO adhesion was never problematic during any electrochemical measurements (in particular, constant activity was observed over long-duration measurements). \n\nThermal annealing of the prepared $F{\\mathrm{-mrGO}}$ electrodes was performed using a tube furnace at $300^{\\mathrm{o}}\\mathrm{C}$ $F\\mathrm{-mrGO}(300))$ or $600^{\\mathrm{oC}}$ ( $F\\mathrm{-mrGO}(600))$ under $\\Nu_{2}$ . The loading weight of the few-layered mrGO electrodes was measured using a microbalance (XS3DU Microbalance; Mettler Toledo). To more accurately measure the $F{\\mathrm{-mrGO}}$ electrode loading weight, dip-casting of the large-surface-area P50 $(20\\mathsf{c m}^{2})$ was performed. Other catalysts, such as A-mrGO and XC72, were dropcast onto P50 using 0.05 wt $\\%$ catalyst in water solutions. \n\nThe dip-coating procedure is reminiscent of—although certainly more basic than—Langmuir–Blodgett deposition, which has been used to form single-layer GO films on substrates24. During the dip-coating procedure, the mrGO physically adsorbed to the immersed P50 carbon substrate, while the individual mrGO sheets were electrostatically repelled from each other due to the presence of oxygen functionalities on their surface. It is likely that the combination of these two effects results in a uniform $F$ -mrGO coating while eliminating mrGO aggregation24. It is worth noting that no 2D Raman shift was observed when characterizing the mrGO powder (Supplementary Fig. 6), as the powder was also expected to aggregate in its dried state. Comparison of the scanning electrode microscopy images of these electrodes also indicated stark differences in the mrGO morphology on dip-coated and drop-cast electrodes (Supplementary Fig. 7). \n\nRDE preparation. Electrochemical RDE studies were carried out in a conventional three-electrode cell using a Bio-Logic VSP potentiostat. A Pt wire and an $\\mathrm{\\Ag/\\Omega}$ AgCl electrode filled with saturated KCl aqueous solution were used as the counter electrode and reference electrode, respectively. The electrolyte was 0.1 M aqueous KOH solution, which was purged with oxygen for $10\\mathrm{min}$ before the electrochemical test. To prepare the $F$ -mrGO-coated glassy carbon electrode, the mrGO was dispersed in water (0.025 wt. $\\%$ mrGO) by sonication. Some $10.00\\upmu\\mathrm{l}$ of this dispersion was transferred onto a glassy carbon electrode ( $5\\mathrm{mm}$ diameter; $0.196\\mathrm{cm}^{2}$ geometric area) embedded in a polytetrafluoroethylene sheath and then dried in air at $80^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . The mrGO loading was calculated to be $10\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ . LSV was measured using an RDE (MSR analytical rotator; Pine Instrument) at a scan rate of $10\\mathrm{mVs^{-1}}$ . \n\nElectrochemical measurements. Electrochemical measurements were performed using a Bio-Logic SP-300 potentiostat and a custom-built modified electrochemical H-cell (Adams and Chittenden; Supplementary Fig. 11). The voltages of both the counter electrode (Pt wire) and working electrode (catalyst-coated P50; $\\mathord{\\sim}1.0\\mathrm{cm}^{2}$ exposed to the electrolyte) were recorded simultaneously. An $\\mathrm{Hg/HgO}$ reference electrode with $1\\mathrm{MNaOH}$ as the electrolyte (Bio-Logic) was used for all measurements. A liquid junction potential of $35\\mathrm{mV},$ as calculated from the Henderson equation for a continuous-mixture junction44, was expected from a 0.1 M KOH/1 M NaOH junction and has been included in all reported potentials. All potentials are reported against the RHE and are corrected for ohmic losses. All electrochemical measurements were performed in $0.1\\mathrm{M}$ KOH saturated with pure $\\mathrm{O}_{2},$ typically at ${\\sim}800$ torr unless stated otherwise, or exposed air at ${\\sim}760$ torr. LSV was performed by cathodically sweeping the working electrode potential from open circuit potential (OCV) at a scan rate of $2.0\\mathrm{mVs^{-1}}$ . Chronoamperometry was conducted to accurately identify $\\mathrm{e}^{-}/\\mathrm{O}_{2}$ values, as well as onset potentials for ORR. \n\nQuantification of $\\mathbf{O}_{2}$ consumption. The electrochemical H-cell used in this study was custom built to ensure hermetic integrity of both the counter and working electrode chambers, which were separated using a Nafion 117 membrane (Supplementary Fig. 11). The pressure on each side of the cell was analysed individually using an in-line pressure transducer (PX419; Omega Engineering; Supplementary Fig. 12). An Al electrode holder was used to hold the catalystcoated P50 working electrode. No portion of the Al holder was immersed in the electrolyte. The working electrode chamber electrolyte was stirred vigorously using a magnetic stir bar over the course of the experiment to limit mass transport effects. The volume of each chamber of the H-cell was calibrated using a volumeexpansion technique and the ideal gas law. The volumes of the three-port chamber (working electrode and $\\mathrm{Hg/HgO}$ as a reference electrode) and the two-port chamber (Pt wire as a counter electrode) of the H-cell were $13.4\\pm0.3\\mathrm{ml}$ and $10.6\\pm0.2\\mathrm{ml}$ , respectively. The uncertainty in the volume arises from the Nafion membrane deflecting when the pressure difference between each chamber of the H-cell increased. The three-port and two-port chambers of the H-cell were each filled with $5\\mathrm{ml}$ of electrolyte during each experiment so that the total headspace above the electrolyte in the three-port chamber was calculated to be $8.4\\pm0.3\\mathrm{ml}$ . As $\\mathrm{~O}_{2}$ was consumed during ORR at the working electrode, the pressure transducer measured changes in the working electrode chamber pressure. Knowing the pressure decay and calibrated headspace volume, the ideal gas law was used to calculate the total moles of $\\mathrm{O}_{2}$ consumed during ORR. \n\nHydrogen peroxide quantification. An iodometric titration was conducted to quantify the $\\mathrm{HO}_{2}^{-}$ produced and followed procedures previously used in our laboratory to quantify lithium peroxide formation in Li-air batteries45 After an ORR measurement, $1.0\\mathrm{ml}$ of the electrolyte, along with $1.0\\mathrm{ml}$ of $2\\mathrm{wt.\\%}$ potassium iodide solution, $\\mathrm{1ml}$ of $3.5\\mathrm{M}$ sulphuric acid and two or three drops of a molybdate catalyst, was added to a vial. $\\mathrm{H}_{2}\\mathrm{O}_{2}$ oxidizes iodide to iodine per the following reaction: \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}_{2}+2\\mathrm{\\KI}+\\mathrm{H}_{2}\\mathrm{SO}_{4}\\to\\mathrm{I}_{2}+\\mathrm{K}_{2}\\mathrm{SO}_{4}+2\\mathrm{\\H}_{2}\\mathrm{O}\n$$ \n\nThe iodine formed was then titrated with a thiosulfate solution of known concentration. \n\n$$\n\\mathrm{I}_{2}+2\\ \\mathrm{Na}_{2}\\mathrm{S}_{2}\\mathrm{O}_{3}\\to\\mathrm{Na}_{2}\\mathrm{S}_{4}\\mathrm{O}_{6}+2\\ \\mathrm{NaI}\n$$ \n\nEarly in the titration, the presence of iodine was easily observed by a characteristic yellow-brown solution colour. In the final stages of the titration (after the solution had reached a pale, yellow colour), starch was added as an indicator to determine the final end point. The end point was achieved when the characteristic blue colour of the starch–iodine complex completely vanished to yield a clear solution. \n\nIn situ Raman spectroscopy. In situ Raman measurements were performed using a Jobin-Yvon LabRAM HR confocal microscope with $20\\times(0.25\\mathrm{NA})$ objective and a custom-made Teflon electrochemical cell (Supplementary Fig. 20). A $532\\mathrm{nm}$ laser $(1{-}20\\mathrm{mW})$ was focused on the electrode, and the Raman scattered photons were dispersed by a $1,800\\mathrm{gcm^{-1}}$ grating and collected by a spectrometer. In situ spectroelectrochemistry was performed using a Gamry Interface 1000 potentiostat, a Pt counter electrode (Alfa Aesar; Pt gauze 52 mesh woven from $0.1\\mathrm{mm}$ diameter wire, $99.9\\%$ trace metals basis) and a $\\mathrm{Hg/HgO}$ reference electrode in $\\sim30\\mathrm{ml}$ of 0.1 M KOH. During a measurement, high-purity $\\mathrm{O}_{2}$ or $\\Nu_{2}$ was bubbled at $\\sim5{-}10\\mathrm{ml}\\mathrm{min}^{-1}$ , after which Raman spectra were collected using chronoamperometry at the potential of interest. For analysis, Raman spectra were normalized by laser power and collection time, and corrected by a linear background subtraction. The $\\mathrm{D}/\\mathrm{G}$ and $\\mathrm{D}/(\\mathrm{D}^{\\prime}+\\mathrm{G})$ ratios were obtained by deconvoluting the Raman spectra using a multi-peak Voigt fit. \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 24 August 2017; Accepted: 21 February 2018; Published: xx xx xxxx \n\n# References \n\n1.\t Campos-Martin, J. M., Blanco-Brieva, G. & Fierro, J. L. G. Hydrogen peroxide synthesis: an outlook beyond the anthraquinone process. Angew. Chem. Int. Ed. 45, 6962–6984 (2006). \n2.\t Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science 355, eaad4998 (2017). \n3.\t Siahrostami, S. et al. Enabling direct $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production through rational electrocatalyst design. Nat. Mater. 12, 1137–1143 (2013). \n4.\t Verdaguer-Casadevall, A. et al. Trends in the electrochemical synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2};$ : enhancing activity and selectivity by electrocatalytic site engineering. Nano Lett. 14, 1603–1608 (2014). \n5.\t Viswanathan, V., Hansen, H. A., Rossmeisl, J. & Norskov, J. K. Unifying the $2e^{-}$ and $4e^{-}$ reduction of oxygen on metal surfaces. J. Phys. Chem. Lett. 3, 2948–2951 (2012). \n6.\t Chen, Z. et al. Development of a reactor with carbon catalysts for modularscale, low-cost electrochemical generation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . React. Chem. Eng. 2, 239–245 (2017). \n7.\t Wagman, D. D. et al. The NBS tables of chemical thermodynamic properties. J. Phys. Chem. Ref. Data 11, 2-37–2-355 (1982). \n8.\t Mukerjee, S. & Srinivasan, S. Enhanced electrocatalysis of oxygen reduction on platinum alloys in proton exchange membrane fuel cells. J. Electroanal. Chem. 357, 201–224 (1993). \n9.\t Gasteiger, H. A., Kocha, S. S., Sompalli, B. & Wagner, F. T. Activity benchmarks and requirements for Pt, Pt-alloy, and non-Pt oxygen reduction catalysts for PEMFCs. Appl. Catal. B 56, 9–35 (2005). \n10.\tPark, J., Nabae, Y., Hayakawa, T. & Kakimoto, M. A. Highly selective two-electron oxygen reduction catalyzed by mesoporous nitrogen-doped carbon. ACS Catal. 4, 3749–3754 (2014). \n11.\tJirkovsky, J. S. et al. Single atom hot-spots at Au–Pd nanoalloys for electrocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. J. Am. Chem. Soc. 133, 19432–19441 (2011). \n12.\t Yang, S., Kim, J., Tak, Y. J., Soon, A. & Lee, H. Single-atom catalyst of platinum supported on titanium nitride for selective electrochemical reactions. Angew. Chem. Int. Ed. 55, 2058–2062 (2016). \n13.\tZheng, Z., Ng, Y. H., Wang, D.-W. & Amal, R. Epitaxial growth of Au–Pt–Ni nanorods for direct high selectivity $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Adv. Mater. 28, 9949–9955 (2016). \n14.\tLee, Y.-H., Li, F., Chang, K.-H., Hu, C.-C. & Ohsak, T. Novel synthesis of N-doped porous carbons from collagen for electrocatalytic production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Appl. Catal. B Environ. 126, 208–214 (2012). \n15.\tPaliteiro, C., Hamnett, A. & Goodenough, J. B. The electroreduction of oxygen on prolytic graphite. J. Electroanal. Chem. 233, 147–159 (1987). \n16.\t Tammeveski, K., Kontturi, K., Nichols, R. J., Potter, R. J. & Schiffrin, D. J. Surface redox catalysis for $\\mathrm{O}_{2}$ reduction on quinone-modified glassy carbon electrodes. J. Electroanal. Chem. 515, 101–112 (2001). \n17.\tAlvarez-Gallegos, A. & Pletcher, D. The removal of low level organics via hydrogen peroxide formed in a reticulated vitreous carbon cathode cell, Part 1. The electrosynthesis of hydrogen peroxide in aqueous acidic solutions. Electrochim. Acta 44, 853–861 (1998). \n18.\tSarapuu, A., Vaik, K., Schiffrin, D. J. & Tammeveski, K. Electrochemical reduction of oxygen on anthraquinone-modified glassy carbon electrodes in alkaline solution. J. Electroanal. Chem. 541, 23–29 (2003). \n19.\tYang, H. H. & McCreery, R. L. Elucidation of the mechanism of dioxygen reduction on metal-free carbon electrodes. J. Electrochem. Soc. 147, 3420–3428 (2000). \n20.\tXu, J., Huang, W. H. & McCreery, R. L. Isotope and surface preparation effects on alkaline dioxygen reduction at carbon electrodes. J. Electroanal. Chem. 410, 235–242 (1996). \n21.\tHasche, F., Oezaslan, M., Strasser, P. & Fellinger, T.-P. Electrocatalytic hydrogen peroxide formation on mesoporous non-metal nitrogen-doped carbon catalyst. J. Energy Chem. 25, 251–257 (2016). \n22.\tTao, L. et al. Edge-rich and dopant-free graphene as a highly efficient metal-free electrocatalyst for the oxygen reduction reaction. Chem. Commun. 52, 2764–2767 (2016). \n23.\tYan, D. et al. Defect chemistry of nonprecious-metal electrocatalysts for oxygen reactions. Adv. Mater. 29, 1606459 (2017). \n24.\tCote, L. J., Kim, F. & Huang, J. Langmuir–Blodgett assembly of graphite oxide single layers. J. Am. Chem. Soc. 131, 1043–1049 (2009). \n25.\tEda, G., Fanchini, G. & Chhowalla, M. Large-area ultrathin films of reduced graphene oxide as a transparent and flexible electronic material. Nat. Nanotechnol. 3, 270–274 (2008). \n26.\tLevich, B. The theory of concentration polarisation. Discuss. Faraday Soc. 1, 37–49 (1947). \n27.\tZhou, R. F., Zheng, Y., Jaroniec, M. & Qiao, S. Z. Determination of the electron transfer number for the oxygen reduction reaction: from theory to experiment. ACS Catal. 6, 4720–4728 (2016). \n28.\tBonakdarpour, A. et al. Impact of loading in RRDE experiments on Fe–N–C catalysts: two- or four-electron oxygen reduction? Electron. Solid State Lett. 11, B105–B108 (2008). \n29.\tLerf, A., He, H., Forster, M. & Klinowski, J. Structure of graphite oxide revisited. J. Phys. Chem. B 102, 4477–4482 (1998). \n30.\tAcik, M. et al. Unusual infrared-absorption mechanism in thermally reduced graphene oxide. Nat. Mater. 9, 840–845 (2010). \n31.\tAcik, M. et al. The role of oxygen during thermal reduction of graphene oxide studied by infrared absorption spectroscopy. J. Phys. Chem. C 115, 19761–19781 (2011). \n32.\tVijayarangamuthu, K. et al. Temporospatial control of graphene wettability. Adv. Mater. 28, 661–667 (2016). \n33.\tBowling, R. J., Packard, R. T. & Mccreery, R. L. Activation of highly ordered pyrolytic-graphite for heterogeneous electron-transfer: relationship between electrochemical performance and carbon microstructure. J. Am. Chem. Soc. 111, 1217–1223 (1989). \n34.\tWang, Y., Alsmeyer, D. C. & Mccreery, R. L. Raman-spectroscopy of carbon materials: structural basis of observed spectra. Chem. Mater. 2, 557–563 (1990). \n35.\tShen, A. L. et al. Oxygen reduction reaction in a droplet on graphite: direct evidence that the edge is more active than the basal plane. Angew. Chem. Int. Ed. 53, 10804–10808 (2014). \n36.\tSchultz, B. J., Dennis, Lee, V. & Banerjee, S. An electron structure perspective of graphene interfaces. RSC Adv. 4, 634–644 (2014). \n37.\tLee, V. et al. In situ near-edge X-ray absorption fine structure spectroscopy investigation of the thermal defunctionalization of graphene oxide. J. Vac. Sci. Technol. B 30, 061206 (2012). \n38.\tKaniyoor, A. & Ramaprabhu, S. The Raman spectroscopic investigation of graphene oxide derived graphene. AIP Adv. 2, 032183 (2012). \n39.\tDiez-Betriu, X. et al. Raman spectroscopy for the study of reduction mechanisms and optimization of conductivity in graphene oxide thin films. J. Mater. Chem. C 1, 6905–6912 (2013). \n40.\tFerrari, A. C. Raman spectroscopy of graphene and graphite: disorder, electron-phonon coupling, doping and nonadiabatic effects. Solid State Commun. 143, 47–57 (2007). \n41.\tAkhavan, O. The effect of heat treatment on formation of graphene thin films from graphene oxide nanosheets. Carbon 48, 509–519 (2010). \n42.\tGao, Y. et al. Combustion synthesis of graphene oxide- $\\cdot\\mathrm{TiO}_{2}$ hybrid materials for photodegradation of methyl orange. Carbon 50, 4093–4101 (2012). \n43.\tLin, Y.-C., Lin, C.-Y. & Chiu, P.-W. Controllable graphene N-doping with ammonia plasma. Appl. Phys. Lett. 96, 133110 (2010). \n44.\tNewman, J. & Thomas-Alyea, K. E. Electrochemical Systems. (John Wiley & Sons, Hoboken, 2004). \n45.\tMcCloskey, B. D. et al. Combining accurate $\\mathrm{O}_{2}$ and $\\mathrm{Li}_{2}\\mathrm O_{2}$ assays to separate discharge and charge stability limitations in nonaqueous Li– ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ batteries. J. Phys. Chem. Lett. 4, 2989–2993 (2013). \n\n# Acknowledgements \n\nB.D.M. and H.W.K. gratefully acknowledge support from the National Science Foundation under grant number CBET-1604927. H.W.K. also acknowledges support from the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (2016R1A6A3A03012382). N.K. gratefully acknowledges the Royal Society Newton International Fellowship. P.Y. acknowledges support from the Director of the Office of Science, Office of Basic Energy Sciences as part of the Chemical Sciences, Geosciences, and Biosciences Division of the US Department of Energy, under contract number DE-AC02-05CH11231 within the Catalysis Research Program (FWP number CH030201). The work at Molecular Foundry (XPS and scanning electron microscope) and Advanced Light Source (NEXAFS) was supported by the Office of Science, Office of Basic Energy Sciences of the US Department of Energy under contract number DE-AC02-05CH11231. H.W.K. gratefully acknowledges H. B. Park for guidance on graphene oxide synthesis, W. Kim for FTIR measurement and Y. Hwa for scanning electron microscope analysis. A. C. Luntz is also acknowledged for fruitful discussions on the potential mechanisms of ORR on mrGO materials. \n\n# Author contributions \n\nH.W.K. contributed to the experimental planning, experimental measurements, data analysis and manuscript preparation. M.B.R. and N.K. performed the Raman spectroscopy, including in situ and ex situ measurements. L.Z. measured NEXAFS. J.G. and P.Y. provided experimental guidance for the NEXAFS and Raman measurements, respectively. B.D.M. contributed to the experimental planning, data analysis and manuscript preparation. All authors reviewed and commented on the manuscript before publication. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-018-0044-2. \n\nReprints and permissions information is available at www.nature.com/reprints \n\nCorrespondence and requests for materials should be addressed to B.D.M. \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1038_s41467-018-05774-5", + "DOI": "10.1038/s41467-018-05774-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-05774-5", + "Relative Dir Path": "mds/10.1038_s41467-018-05774-5", + "Article Title": "High entropy oxides for reversible energy storage", + "Authors": "Sarkar, A; Velasco, L; Wang, D; Wang, QS; Talasila, G; de Biasi, L; Kübel, C; Brezesinski, T; Bhattacharya, SS; Hahn, H; Breitung, B", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "In recent years, the concept of entropy stabilization of crystal structures in oxide systems has led to an increased research activity in the field of high entropy oxides. These compounds comprise the incorporation of multiple metal cations into single-phase crystal structures and interactions among the various metal cations leading to interesting novel and unexpected properties. Here, we report on the reversible lithium storage properties of the high entropy oxides, the underlying mechanisms governing these properties, and the influence of entropy stabilization on the electrochemical behavior. It is found that the stabilization effect of entropy brings significant benefits for the storage capacity retention of high entropy oxides and greatly improves the cycling stability. Additionally, it is observed that the electrochemical behavior of the high entropy oxides depends on each of the metal cations present, thus providing the opportunity to tailor the electrochemical properties by simply changing the elemental composition.", + "Times Cited, WoS Core": 924, + "Times Cited, All Databases": 980, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000442594800002", + "Markdown": "# High entropy oxides for reversible energy storage \n\nAbhishek Sarkar $\\textcircled{1}$ 1, Leonardo Velasco1, Di Wang1,2, Qingsong Wang1, Gopichand Talasila1, Lea de Biasi1, Christian Kübel $\\textcircled{1}$ 1,2,3, Torsten Brezesinski 1, Subramshu S. Bhattacharya4, Horst Hahn1,3 & Ben Breitung 1,2 \n\nIn recent years, the concept of entropy stabilization of crystal structures in oxide systems has led to an increased research activity in the field of “high entropy oxides”. These compounds comprise the incorporation of multiple metal cations into single-phase crystal structures and interactions among the various metal cations leading to interesting novel and unexpected properties. Here, we report on the reversible lithium storage properties of the high entropy oxides, the underlying mechanisms governing these properties, and the influence of entropy stabilization on the electrochemical behavior. It is found that the stabilization effect of entropy brings significant benefits for the storage capacity retention of high entropy oxides and greatly improves the cycling stability. Additionally, it is observed that the electrochemical behavior of the high entropy oxides depends on each of the metal cations present, thus providing the opportunity to tailor the electrochemical properties by simply changing the elemental composition. \n\nT shteatidoenmaaryndafnod emnoebriglye satpoprlaigcea idoenvis ehsas(bianttcerreiaese)d orrapbiodtlhy during the past years and it is expected to continue to grow in the future. The most commonly used electrochemical energy storage devices are intercalation based Li-ion batteries, which exhibit very high efficiency and reversibility1,2. Nonetheless, other Li-storage schemes are being presently pursued especially conversion or alloying modification approaches since they hold the promise for achieving very high capacity storage systems. Unfortunately, many of these systems have been found to lack both good reversibility and efficiency3,4. \n\nRecently, a new class of oxide systems, also known as high entropy oxides (HEO), was formulated and reported with first demonstrations for transition-metal-based HEO $(\\mathrm{TM-HEO})^{5-7}$ , rare-earth-based HEO (RE-HEO)8 and mixed HEO (TM-RE$\\mathrm{HEO})^{9}$ . HEO are based on a new, quite revolutionary concept of entropy stabilization, that is, to stabilize a certain crystal structure that can differ from the typical crystal structures of the constituent elements, thereby increasing the configurational entropy of the resulting compounds. This concept was first reported for metallic high entropy alloys (HEA). In recent years, the study of HEA has grown into an independent field of materials research, as evidenced by numerous publications10. \n\nSeveral reports on $\\mathrm{TM-H\\bar{E}O^{5,6}}$ , $\\mathrm{RE-HEO^{8}}$ , and mixed TM-RE$\\mathrm{HEO}^{9}$ have demonstrated that high entropy stabilization in oxides with 5 or more cations in equiatomic concentrations leads to the formation of single-phase rock-salt, fluorite, or perovskite structures. These compounds often show interesting and unexpected properties, such as extraordinarily high room temperature Li-ion conductivities for solid state electrolytes in ${\\mathrm{TM}}{\\mathrm{-}}{\\mathrm{HE}}{\\dot{\\mathrm{O}}}^{5}$ , very narrow and tailored band gaps in $\\mathrm{RE-HEO}^{8}$ and colossal dielectric constants in $\\mathrm{TM-HEO^{\\mathrm{11}}}$ . The main driver for the growing interest in HEO is the potential to obtain novel properties by exploiting the enormous number of possible elemental combinations5,12. The fast growth of the field of HEO is being facilitated by the availability of many synthesis and processing routes, which were shown to provide highly reproducible material systems6,7. \n\nAs previously mentioned, one of the unexpected properties of the TM-HEO is the high Li-ion conductivity $(>10^{-\\frac{5}{3}}\\mathrm{S}\\dot{\\mathrm{cm}}^{-1})$ , as reported by Bérardan et al.5. The possible insertion of Li-ions into a rock-salt structure opens several diffusion pathways for Li-ions through the crystal lattice, giving rise to the increased conductivity. \n\nHere we present new results on the electrochemical properties of several TM-HEO, such as storage capacity and the cycling stability of HEO structures. The concept of high entropy crystal structure stabilization enables us to build conversion-based electrodes, which can be cycled over 500 times without significant capacity degradation. It is shown that the reduction of the entropy by removal of a single element leads to a completely different electrochemical behavior and cycling degradation. Additionally, unique possibilities to fine-tune the electrochemical performance of high-entropy materials is demonstrated, by making use of the different effects of each individual element on the electrochemical characteristics. Moreover, based on TEM investigations a possible reaction mechanism is proposed, which considers the entropy stabilization and the supporting rock-salt matrix structure during the entire conversion process. \n\n# Results \n\nAs-prepared TM-HEO characterization. The morphology of the various TM-HEO powders, as reported in an earlier publication6, comprises both hollow and filled spheres with sizes in the nanoto-micrometer range. The overview scanning electron microscopy (SEM) image in Figure 1a shows the variety of particle morphologies and sizes. A higher magnification view of the individual particles, both hollow and filled, can be seen in the inset. The crystallinity and the phase purity (rock-salt structure) of the TM-HEO $((\\mathrm{Co_{0.2}C u_{0.2}M g_{0.2}N i_{0.2}Z n_{0.2}})\\mathrm{O})$ were examined by means of powder $\\mathrm{\\DeltaX}$ -ray diffraction (XRD), followed by Rietveld refinement analysis. More details about Rietveld refinement can be found in the supporting information (Supplementary Figure 1). The prepared TM-HEO was subsequently used as active material for application in Li-cells without any further heat treatment step. \n\nThe $(\\mathrm{Co_{0.2}C u_{0.2}M g_{0.2}N i_{0.2}Z n_{0.2}})\\mathrm{O}$ electrodes were tested in secondary Li-based battery cells, using $63\\mathrm{wt\\%}$ of the TM-HEO as active material and evaluated at different specific currents during cycling. Figure 1b, c depict representative data for this TM-HEO system. Galvanostatic cycling experiments were performed in the voltage range from 0.01 to $3\\mathrm{V}$ with respect to $\\bar{\\mathrm{Li^{+}/L i}}$ . The most probable reaction mechanisms are insertion of Li into the rocksalt HEO crystal structure, or a conversion reaction forming metals and $\\mathrm{\\dot{L}i}_{2}\\mathrm{O}^{3,13}$ . The most prominent materials for Liinsertion (intercalation)2 are represented by layered structures like graphite, lithium cobalt oxide $(\\mathrm{LCO})^{\\mathrm{i}}$ , or lithium nickel cobalt manganese oxide (NCM) which are frequently used as electrode materials in Li-ion batteries, whereas insertion processes in rock-salt structures have been rarely reported14. The precondition for insertion in the TM-HEO would be that the Li-ion fits into the rock-salt lattice, where all octahedral positions are occupied by cations. As per Pauling’s rule, the possibility of accommodating ${\\mathrm{Li}}^{+}$ in the tetrahedral position is energetically costly considering that the ratio of ionic radii $(\\mathrm{Li^{+}}$ to $\\mathbf{\\bar{O}}^{2-}$ ) is greater than 0.414 (the upper limit for accommodating an ion in the tetrahedral position)15. Additionally, this would lead to strong repulsive interactions between the cations in the lattice15. As known from the literature, transition metal oxides are prone to conversion reactions, i.e., during the charging-discharging cycle complete phase transformations may occur14,16. Consequently, it is reasonable to assume that reversible conversion reactions take place in TM-HEO, which either completely or partially reduce the metal ions upon lithiation. \n\nThe measured capacities at various specific currents of the TMHEO are presented in Fig. 1b. Conversion electrodes often show substantial capacity degradation at high currents due to kinetic limitations of diffusion driven processes during de-/lithiation. For conversion type materials, the theoretical capacity is directly related to the amount of electrons transferred per formula unit (Supplementary Equation 1). The basic reaction for a binary metal oxide can be represented as $\\mathrm{MO}_{x}+2x\\mathrm{Li}\\xrightarrow{}\\mathrm{M}+x\\mathrm{Li}_{2}\\mathrm{O}$ . Because it is not known what reactions are occurring during the redox processes in the case of TM-HEO (additional processes might be alloying of $Z\\mathrm{n}$ with Li, formation of intermetallic phases etc.), we cannot predict with high accuracy the theoretical capacity of our compounds. However, we believe that it is in the range of capacities reported for divalent oxide conversion materials $(70\\bar{0}-1000\\mathrm{mA}\\bar{\\mathrm{h}}\\mathrm{g}^{-1};$ ). \n\nAlthough some conversion materials have been reported to show high specific capacities and high degrees of reversibility, most of them are tediously modified, e.g., regarding morphology and structure or they are coated with additional functional materials to enhance their electrochemical performance17–19. Usually, the particle size in conversion materials has a considerable influence on the electrochemical properties, since large size particles usually lead to low capacity as well as low rate capability and reversibility. Nevertheless, despite the large size particles present in the TM-HEO, the material shows high specific capacities even when applying high specific currents. Furthermore, it is able to fully recover and even increase the initial capacity after raising the current to $3\\mathrm{Ag^{-1}}$ for 5 cycles, so that after 100 cycles a specific capacity of $770\\mathrm{mAhg^{-1}}$ is reached. Capacity increase over prolonged cycling is typical of conversion type materials and can be attributed to activation processes, occurring in electrodes with large particle sizes14,17. Figure 1c shows the cycling performance of the TM-HEO over 300 cycles at $200\\mathrm{mA}\\dot{\\mathrm{g}}^{-1}$ with two initial formation cycles at 50 mA $\\mathbf{g}^{-1}$ . Even with the micrometer-sized particles, as shown in Fig. 1a, and without any optimization of the other components in the electrochemical cell (i.e., electrolyte, binder and electrode composition), the cells display good stability at high capacity values, especially when considering the conversion type of reaction involved. The aforementioned increase in capacity is also observed during the first 75 cycles. The initial discharge capacity amounts to ${\\mathsf{P}}80{\\mathrm{~mAh~g^{-1}}}_{\\mathrm{~:~}}$ and after stabilization at the third cycle, the cell reaches a capacity of ${\\sim}600\\ \\mathrm{mAhg^{-1}}$ , which even increases to around $650\\mathrm{\\bar{mAhg}^{-1}}$ after 70 cycles; the voltage profiles can be found in the supporting information (Supplementary Figure 2). The fluctuations in capacity seen between the 75th and 150th cycles were observed for several different cells. However, after around 150 cycles, the capacity was found to stabilize, therefore we attribute this behavior to structural changes associated with the active material. The conversion reactions of individual transition metal oxides (CuO, NiO, CoO etc.) with similar particle sizes and shapes show comparable initial specific capacities $(500{-}700\\mathrm{mAh}\\mathrm{g}^{-1}\\mathrm{\\overline{{\\Omega}}}^{\\cdot}$ ) 14,20,21, but they fall short when it comes to capacity retention and efficiency22,23. \n\n![](images/99040e8e6215245d42ab6bc5bf9d679dfa412c4cda0a1631e95937cf63102cbc.jpg) \nFig. 1 TM-HEO particles and their specific capacities. a SEM micrograph of the as-synthesized TM-HEO powder with typical particle sizes from the nano-tomicrometer range. The inset shows that the powder contains both hollow and filled spheres. The scalebars shown in a and the inset correspond to $2\\upmu\\mathrm{m}$ and $1\\upmu\\mathrm{m}$ , respectively. b Galvanostatic rate capability test (current values given in units of $\\mathsf{A}\\mathsf{g}^{-1})$ . The capacity decreases as the specific current is increased stepwise up to $3\\mathsf{A}\\mathsf{g}^{-1},$ but it recovers at $0.1\\mathsf{A g}^{-1}$ and even increases after 100 cycles to $770m A\\mathfrak{h}\\mathfrak{g}^{-1}$ . c Long-term cycling performance at $0.2\\mathsf{A g}^{-1}$ \n\nComparison between high entropy and medium entropy compounds. The substantial number of cation metals in the TMHEO makes it possible to remove specific elements and to then investigate the resulting change of the electrochemical behavior, thus allowing to assign certain electrochemical characteristics to specific elements. Additionally, the exclusion of one of the elements from a 5-cation system results in a significant decrease of the configurational entropy from ${\\sim}1.61\\mathrm{~R~}$ to ${\\sim}1.39\\mathrm{R},$ which necessitates a post annealing treatment to obtain a single-phase oxide, as explained in the experimental section of the paper. To compare the 4-cation systems with the 5-cation system, the latter was subjected to the identical additional heat treatment as that used for the 4-cation oxides to facilitate comparison. In fact, in a long-term experiment (Fig. 2a), it was shown that, at a specific current of $200\\mathrm{mAg^{-1}}$ , the 5-cation sintered system can be cycled over hundreds of cycles with specific capacities of up to $590\\mathrm{mAh}\\mathrm{g}^{-1}$ . The typical electrochemical behavior of conversion materials discussed above (decaying/increasing capacity with cycling) is also apparent in this experiment. As anticipated, the first drop in capacity is more prominent since the calcined TMHEO sample comprises even bigger particle sizes and agglomerates than the as-prepared TM-HEO (Supplementary Figure 3). The Coulombic efficiency in the stable region (cycle no. 60–400) stabilizes between 99.4 and $99.95\\%$ . Because of the heat treatment, slightly different capacity values for the 5-cation system were expected, as shown in Fig. 2a. According to the established nomenclature, 4-cation systems belong to the “medium entropy” \n\n![](images/0861f720df6c4675f8d71bc78f7897c8bd5dcf734e3fd885bede1eab07e79ee8.jpg) \nFig. 2 Specific capacities and lithiation profiles of TM-HEO and TM-MEO. Comparison of the different medium and high entropy oxides under investigation. a Long-term cycling stability of the calcined TM-HEO at $200\\mathsf{m A}\\mathsf{g}^{-1}$ together with the corresponding Coulombic efficiency. b It can be seen that the TMHEO shows stable capacity retention at $50\\mathsf{m A g}^{-1}$ , while the materials without Zn and $\\mathsf{C u}$ reveal severe capacity degradation. The material without Co fails completely after 10 cycles. c Discharge (lithiation) profiles of the first cycle for the different compounds. The material without Cu shows a significantly lower discharge potential and it might be interesting as anode material for primary batteries \n\n
Table 1 Synthesized single-phase compounds used for electrochemical testing
EntropyRemoved elementAbbreviation
(C00.2Cuo.2Mgo.2Nio.2Zn0.2)O1.61R-TM-HEO
(C00.25Cuo.25Mgo.25Nio.25)O1.39 RZnTM-MEO(-Zn)
(C00.25Mg0.25Nio.25Zno.25)O1.39 RCuTM-MEO(-Cu)
(Cuo.25Mgo.25Nio.25Zno.25)O1.39 RCoTM-MEO(-Co)
\n\ngroup, while 5-cation systems belong to the “high entropy” group24. It should be noted that all “medium entropy” oxides (MEO) showed a completely different and rather unstable electrochemical behavior when compared to the “high entropy” oxides (Fig. 2b). The electrochemical behavior of the “medium entropy” oxides, initially displaying high specific capacities, but then showing varying degrees of degradation with increasing numbers of cycles, compares well with that of established conversion materials with large particle sizes. By contrast, the 5- cation high entropy oxide displays a high capacity value that does not degrade with increasing cycle number. The capacity comparison between the 5-cation TM-HEO and the 4-cation oxides leads us to conclude that the “high entropy” material exhibits a novel and interesting electrochemical behavior, probably related to the entropy stabilization. Such an observation has not been previously reported. Figure 2b shows a comparison of the electrochemical performance of the 5-cation TM-HEO and three of the 4-cation systems, without $Z\\mathrm{n}$ , Cu, or Co, respectively (see Table 1). Despite efforts to synthesize every possible MEO structure, both TM-MEO(-Mg) and TM-MEO(-Ni) (i.e., $(\\mathrm{Co_{0.25}C u_{0.25}Z n_{0.25}N i_{0.25}})\\mathrm{O}$ and $(\\mathrm{Co_{0.25}C u_{0.25}M g_{0.25}Z n_{0.25}})\\mathrm{O}$ , respectively) could not be stabilized as single-phase compounds, even at much higher temperatures. Therefore, we refrain from including them in the comparison of the entropy-stabilized oxides, since we believe that simple mixtures of different compounds are not comparable to the single-phase materials. Nevertheless, the electrochemical and XRD characterization results of the multiphase compounds are depicted separately in Supplementary Figure 4. \n\nThe configurational entropy was calculated using the following formula:24 \n\n$$\nS_{\\mathrm{config}}=-R\\left[\\left(\\sum_{i=1}^{N}x_{i}\\mathrm{ln}x_{i}\\right)_{\\mathrm{cation-site}}+\\left(\\sum_{j=1}^{N}x_{j}\\mathrm{ln}x_{j}\\right)_{\\mathrm{anion-site}}\\right]\n$$ \n\nwhere $x_{i}$ and $x_{j}$ represent the mole fractions of ions present in the cation- and anion-site, respectively. The contribution of the anion-site is expected to have a minor influence on $S_{\\mathrm{confg}},$ given that only one anion is present. More details about the entropy calculation for the TM-HEO and one of the TM-MEO materials are given in Supplementary Equation 2. \n\nAlthough every composition was synthesized as single-phase rock-salt structure (the XRD patterns of all the compounds can be found in Supplementary Figure 5), significant differences in the electrochemical behavior between the TM-HEO and the “medium entropy” materials are clearly evident. The individual compounds are cycled at $50\\mathrm{mAg^{-1}}$ in a potential range between 0.01 and $3\\mathrm{V}$ with respect to $\\mathrm{Li^{+}/L i}$ Figure 2b shows the TMHEO with a specific capacity of $555\\mathrm{mAhg^{-1}}$ after the initial formation cycles, which decreases to $520\\mathrm{mA}\\bar{\\mathrm{h}}\\mathrm{g}^{-1}$ after 50 cycles. The removal of Co (TM-MEO(-Co)) leads to a complete failure of the cell after approx. 10 cycles, with no signs of recovery during the subsequent cycles (Fig. 2b). This seems to imply that Co can be considered as a critical and necessary element for TM-HEO to have high specific capacity and good cycling stability, whereas the removal of Zn (TM-MEO(-Zn)) and Cu (TM-MEO(-Cu)) does not impede the overall reversibility. Nevertheless, the cells deliver lower capacities after 30–35 cycles, even though the initial capacity of both oxides is higher than that of the 5-cation system, but with a rapid drop after only a few cycles. Similar electrochemical behavior has been reported for large particle size conversion materials and has often been explained by side reactions, which occur during the redox processes, such as particle fracture/pulverization and increased solid-electrolyte interphase formation2. Another aspect discussed in the literature is the potential improvement in conductivity when metallic species like Cu dendrites are present25, which might lead to better cycling stability, too. To examine whether Cu dendrites are formed during the conversion process, energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDX) measurements were conducted on electrodes after 100 cycles. However, the data show no indication of any Cu aggregation in the materials (Supplementary Figure $6)^{26}$ . \n\nTherefore, the 4-cation systems can serve as reference materials when the entropy stabilization is not as large as in the HEO. Such effects were not observed during TM-HEO cycling. SEM examination of the cycled materials revealed fully intact spheres, embedded in the carbon/polymer matrix of the electrode (Supplementary Figure 7). \n\nThe above results demonstrate that an increase in concentration $25\\mathrm{at\\%}$ in 4-cation systems vs. $20\\mathrm{at\\%}$ in 5-cation systems) of constituent elements, which are known for their electrochemical activity (e.g., Co), leads to the expected increase in capacity, but the 4-cation systems do not exhibit the stability of the 5-cation system. Another interesting effect due to removal of Cu from the TM-HEO has been noted. As seen in Fig. 2c, the initial (average) discharge potential is significantly decreased. The large capacity of this compound at the low potential could be an interesting option for primary anode applications (around $800\\mathrm{mAh}\\mathrm{g}^{-1}$ in the $0.03\\substack{-0.13\\mathrm{V}}$ range). \n\nThe cyclic voltammograms (CVs) are depicted for all the systems in Supplementary Figure 8. The CV curves look very different for the different materials, which is another clear indication that the reaction mechanism and the electrochemical behavior can be tailored by changing the elemental composition. Removal of $Z\\mathrm{n}$ from the TM-HEO causes a completely different electrochemical behavior during the oxidation of the compound. The CVs and differential capacity plots establish that the absence of Zn leads to a two-step oxidation process, rather than a single one as for all the other samples (Supplementary Figure 9). These two oxidation peaks, centered around $1.7\\mathrm{V}$ and $2.2\\mathrm{V}_{:}$ resemble the formation of individual NiO and $\\mathrm{CoO^{17,27}}$ . This suggest that, in the case of TM-MEO(-Zn), the parent rock-salt structure is apparently not regained upon Li extraction, but instead separates into different phases. \n\nDespite potential alloying of elemental $Z\\mathrm{n}$ with $\\operatorname{Li}^{28}$ , we did not find any signs of this reaction. Usually, the formation of ZnLi occurs at a low potential of around $0.2{\\dot{\\mathrm{V}}}^{28}$ and would lead to an additional gain in capacity of ${\\sim}40\\ \\mathrm{mAh\\g^{-1}}$ for the TM-HEO29. Although the CV curves (Supplementary Figure 8) for TM-MEO $(-Z\\mathrm{n})$ and the $Z\\mathrm{n}$ -containing materials do not show significant differences, alloying of $Z\\mathrm{n}$ with Li cannot be ruled out completely, especially for TM-MEO(-Cu), where the vast majority of Li uptake occurs at low potential. However, even if this reaction takes place in the TM-HEO, the capacity gain will only account for ${\\sim}6.7\\%$ of the total capacity. \n\nThese examples for TM-MEO(- $\\lvert\\mathrm{Cu}\\rvert$ , TM-MEO(-Zn), and TMMEO(-Co) demonstrate that even the removal of a single element leads to significant changes in the electrochemical properties. However, the changes are different for each element removed. On the other hand, the addition of other cations into the single-phase structure (e.g., Fe, Mn, Cr, V) could open new possibilities for developing a modular method to tailor electrodes suited to particular needs. The opportunities to tailor the electrochemical properties in such a flexible way (countless cation combinations are possible), as offered by HEO, are unique compared to conventional conversion or intercalation electrodes. In the following sections of the paper, a possible interpretation, related to the entropy stabilization of the crystal structure, is presented. \n\nStructural investigations and influence on the reaction mechanism. To better understand the reactions and the underlying mechanism of reversible lithium storage, a comprehensive characterization using XRD and transmission electron microscopy (TEM) was performed. Two possible pathways exist for a reversible conversion reaction: (1) the initial TM-HEO phase/ structure is being (re)transformed with each lithiation/delithiation cycle or (2) only a few distinct elements are participating in the phase transformation, while the others are keeping the rocksalt structure intact. A full transformation of the stable singlephase TM-HEO with a rock-salt structure is not expected, considering the high synthesis temperature of above $1000^{\\circ}\\mathrm{C}$ in an oxygen atmosphere. \n\nTo gather more information on the lithiation mechanisms, operando XRD was conducted during the first two cycles of the cell. These measurements were correlated with high-resolution (HR) TEM and selected area electron diffraction (SAED) studies. The operando XRD measurements were performed on a TMHEO electrode in transmission geometry. Figure 3 depicts the initial discharge/charge cycle. The intense reflections appearing over the whole cycle originate from the Cu current collector. This is clearly inferred, since the reflections of the initial rock-salt structure vanish during the lithiation and do not reappear after delithiation. This behavior is typical of conversion materials and it is a result of the formation of small crystallites, which have sizes below the detection threshold of XRD13,14. Nevertheless, SAED measurements conducted on the as-prepared, lithiated and delithiated particles show that the reflections, originating from the rock-salt structure, corresponding to the (111) and (200) plane do not disappear, even when the sample is fully lithiated. The preservation of the rock-salt structure (if only partially) over the entire redox process, is identified as a likely reason for the observed stable cycling behavior. No reflections of other crystal structures were detected based on the XRD patterns. The presence of completely unreacted TM-HEO regions, which would appear as spots or sharper diffraction rings in the SAED in the lithiated and cycled state, can be ruled out. From the combined structural characterization, it becomes evident that the entire volume of the TM-HEO is modified, giving rise to a reduction of the size of the coherently scattering regions and their chemical composition initiated by the exchange of Li ions. As will be described in the model below, the diffuse SAED rings, observed after the first cycle, thus belong to the material, which participated in the conversion reaction as host matrix. \n\nTEM micrographs of the as-prepared TM-HEO (Fig. 4a) show a high degree of crystallinity and reveal the long-range order, as also evident from the XRD pattern in Supplementary Figure 1. TEM investigations of cycled TM-HEO confirm the presence of small crystalline regions, which still exhibit a long-range order that is visible in the diffraction rings. However, grain boundaries and defects reduce the size of the uniform structures below the coherence length for the XRD and, thus, these structures are not visible in the operando XRD patterns14,18. \n\nIn a typical conversion reaction, metal oxides are being reduced to zero-valent metals and lithium oxide with lithiation. Since, these compounds are likely to have different crystal structures, compared to the as-prepared rock-salt structure of TM-HEO, a completely disordered structure after the delithiation cycle or separation into distinct elements could be expected. However, a pseudo long-range “ordered” structure, containing many defects, is observed (Fig. 4b, c).The lattice spacings, corresponding to the (111) and (200) planes of the rock-salt structure, are still clearly visible in the high-resolution image (Fig. 4b) and in its fast Fourier transform (FFT) (Fig. 4c). The experimental observations indicate that, even in the lithiated state, the rock-salt lattice is preserved and serves as a host structure for the conversion reactions. The cations involved in the conversion reactions can diffuse back during the lithiation and delithiation cycles. For the conversion reactions to occur, it is necessary that, during the lithiation process, some of the cations are reduced to the metallic state. However, it appears that these reduced cations remain “trapped” inside the crystal structure of the TM-HEO. It is suggested that the rock-salt structure is preserved by the remaining unreduced cations, which facilitates the reoccupation of the previously reduced cations to the original sites of the HEO lattice during the subsequent oxidation reaction. The observed defect structure is most likely the result of stresses in the crystal lattice (due to the conversion reactions of the participating metal elements), which leads to the size reduction of the crystallites and their disappearance in the diffraction signals. \n\n![](images/c2677adffa27bc72b033509b8bca26890f2730764a424b3c2acef0528188a787.jpg) \nFig. 3 Operando XRD on TM-HEO. a XRD results obtained during the first full lithiation/delithiation cycle. The black lines with arrows indicate the asprepared, fully lithiated and fully delithiated states as a function of time, with the corresponding potential curve shown on the left side. The XRD reflections fade with lithiation over the first few hours and, after the first full cycle, the reflections are not visible anymore. In the SAED patterns on the right side, crystallites, much smaller than the starting size, are still visible due to the shorter wavelength of the electrons. The asterisk indicates the (200) lattice plane of the rock-salt structure, which is maintained during the entire process. The presence of a very faint SAED ring in the lithiated samples in b and c (d-spacing $2.68\\mathring{\\mathsf{A}}_{\\iota}$ , scalebars $21/\\mathsf{n m}\\cdot$ ) could be attributed to the (111) diffraction of $\\mathsf{L i}_{2}\\mathsf{O}$ . From the combined XRD and TEM results, it can be concluded that the rock-salt structure is preserved during cycling and serves as a host matrix for the redox processes. Unreacted TM-HEO can be ruled out since otherwise, the corresponding diffraction spots should be visible in the SAED and the XRD reflections should not disappear completely. Supplementary Figure 10 shows an SAED pattern obtained on an electrode after 10 full cycles, still showing the rock-salt structure. The voltage profile seen for the operando XRD measurement is plotted versus the dis/charge time. The first cycle discharge capacity amounts to around $1030\\mathsf{m A h g}^{-1}$ , which corresponds to an uptake of roughly 2 Li per formula unit. The initial charge capacity is lower, being $459m A\\mathsf{h}\\:\\mathsf{g}^{-1}$ \n\nTo support the above hypothesis, the products of the conversion reaction $\\mathrm{[i}_{2}\\mathrm{O}$ and metallic species) were analyzed via TEM. Interestingly, no metallic phases were found, which seems to be the consequence of the aforementioned reaction mechanism (i.e., reduction inside the rock-salt matrix). Although $\\mathrm{Li}_{2}\\mathrm O$ is known to be highly sensitive to the electron beam, the presence of $\\mathrm{Li}_{2}\\mathrm O$ could be rationalized from the samples after the first and second lithiation cycles (see SAED patterns in Fig. 3a, b). The d-spacing of $2.68\\mathring{\\mathrm{A}}$ could be attributed to the (111) reflection of $\\mathrm{Li}_{2}\\mathrm O$ . Because $\\mathrm{Li}_{2}\\mathrm O$ is only forming due to the conversion reaction, this can be seen as an indirect support of the proposed reaction scheme. \n\nAdditionally, to support the hypothesis of a fully recovered TM-HEO rock-salt structure, spatially resolved EDX spectroscopy measurements were performed to rule out any segregation of elements and/or possible changes in the elemental composition of the materials during cycling. Figure 4d depicts scanning TEM (STEM)-EDX maps of the TM-HEO after the initial cycle. As shown in Supplementary Figure 11, EDX of the as-prepared material does not show any qualitative differences compared to the cycled TM-HEO. \n\nThe stability of the “high entropy” materials, when compared to the “medium entropy” compounds, can be explained in terms of the higher absolute value of configurational entropy, which decreases the Gibbs free energy in the TM-HEO structure. While the conversion of the lithiated TM-HEO back to the original rock-salt structure will be favored by the reduced Gibbs free energy, the TM-MEO with one element removed are not sufficiently entropy stabilized to ensure full transformation. The argument of higher stability is also evident from the fact that significantly longer heating times during or after synthesis are required for stable medium entropy oxides compared to the high entropy oxides. Supporting this assumption is the altered oxidation process presented in Supplementary Figure 9 for TM$\\mathrm{MEO(-Zn)}$ . This material undergoes similar conversion reactions, exhibiting the well-known drawbacks of limited capacity retention and low cycling stability. By contrast, the TM-HEO shows a much more stable electrochemical performance, likely associated with entropy stabilization. Additional support for this hypothesis is also provided by the details of the Coulombic efficiency during cycling. While the TM-HEO provides values in the range between 98.5 and $99.5\\%$ , the TM-MEO(- $-Z\\mathrm{n})$ ) exhibits Coulombic efficiencies substantially lower $(85-95\\%)$ over the first 50 cycles (Fig. 5a). This difference alone is already indicative of important side reactions, reducing the efficiency when the entropy stabilization of the active material is not sufficient. For comparison of the “high entropy materials”, “medium entropy materials” and “multiphase materials”, the Coulombic efficiencies over the first 50 cycles are depicted in Fig. 5a. As is seen, only the “high entropy material” shows stable behavior and can be cycled for hundreds of times. Even higher loading of TM-HEO cells reveals Coulombic efficiencies of ${>}98.5\\%$ (Fig. 5b). In addition, Fig. 5b shows results from the respective rate performance test, where the areal capacity after 30 cycles amounts to $1.3\\mathrm{mAh}\\mathrm{cm}^{-2}$ . Despite the fact that the loading was increased by a factor of ${\\sim}5$ (0.5 vs. 2.3 $\\mathrm{mgcm}^{-2},$ ), the specific capacity decreased only slightly (see also electrochemical performance of an electrode containing $80\\mathrm{wt\\%}$ of TM-HEO in Supplementary Figure 12). \n\n![](images/b1a33021a237b6b184fefa3f269941016fade8a6d5e85260fbc1113c8d1a6ab0.jpg) \nFig. 4 HRTEM and EDX analysis of the active material. a, b HRTEM images of the as-prepared and cycled TM-HEO, respectively. The crystallites in b are substantially smaller and do not show order over longer distances. The lattice fringes in b are not completely straight, but show a small divergence from the original axis. Nevertheless, the small regions with dimensions on the order of a few nanometers exhibit lattice fringes oriented in a specific direction, likely due to the former long-range order, which is partially lost during the conversion reaction. c FFT of a HRTEM image of a few crystallites. The arcs in the FFT correspond to the cubic rock-salt structure, but they indicate a certain texture. The lattice fringes are discontinuous between different crystallites; however, the misorientation is small, caused probably by large amounts of defects or low angle boundaries. d STEM image showing the spheres consist of small particles and the respective elemental maps of the area indicated by the red rectangle. No apparent segregation occurs at the length scale of aggregates of nanoparticles. The scalebars in a and b correspond to 1 nm, in c to $51/$ nm, in d to $200\\mathsf{n m}$ and for the compared EDX analysis to $60\\mathsf{n m}$ \n\nProposed conversion-based mechanism. A schematic of the proposed reaction mechanism is illustrated in Fig. 6. Within the large as-prepared TM-HEO particles, which are poly-/nanocrystalline, lithiation induces conversion reactions of some of the cations (e.g., $\\mathrm{Co}^{2+},\\mathrm{Cu}^{2+})$ while the other cations stabilize the rock-salt structure, thereby acting as a kind of matrix. We believe that the instance that single-phase compounds without $\\mathrm{Mg^{2+}}$ or $\\mathrm{Ni}^{2+}$ apparently cannot be synthesized is an indication of the stabilizing role of those ions to keep the structure intact during the redox processes. The pivotal role of $\\mathrm{Mg^{2+}}$ in keeping the HEO structure intact can be explained by the fact that $\\mathbf{Mg}$ is inactive in the given potential range. The conversion reactions occur on much smaller length scales, on the order of several $\\mathrm{nm}$ , while the crystallite sizes in the as-prepared powder are much larger. A phase separation of the elements, forming known conversion materials such as $\\mathrm{ZnCo}_{2}\\mathrm{O}_{4};$ can be ruled out, since the corresponding crystal structures could not be identified, even in the SAED measurements. \n\nThe preservation of the rock-salt structure even during lithiation is completely new and is unexpected from the traditional conversion reaction point of view. The fact that the TEM and SAED results reveal highly disordered defect-rich rocksalt regions, without any second phase being present, is in good agreement with the proposed mechanism (Fig. 6). The reincorporation of the metal ions into the TM-HEO rock-salt structure at room temperature upon electrochemical cycling, facilitated by high entropy stabilization, is expected to add a new dimension to the traditional conversion based lithiation mechanism. \n\n# Discussion \n\nIn this study, to our knowledge for the first time, it is shown that high entropy oxides are very promising materials for reversible electrochemical energy storage. The variation of the composition of the oxides allows tailoring the Li-storage properties of the active material. The incorporation of different elements into HEO offers a modular approach for the systematic design of the electrode material. Additionally, it is shown that entropy-stabilized oxides have high capacity retention and exhibit a de-/lithiation behavior, which is drastically different from classical conversion materials. The new effect is attributed to configurational entropy stabilization of the lattice, which conserves the original rock-salt structure while serving as a permanent host matrix for the conversion cycles. Based on these—necessarily limited—first, but promising results, further investigations toward high entropy oxide electrode materials should be pursued to explore their full potential for energy storage applications. \n\n# Methods \n\nSynthesis. A versatile synthesis technique proven to yield highly crystalline HEO is the Nebulized Spray Pyrolysis (NSP) method, the details of which have been reported elsewhere6. In the NSP method, a solution, containing metal salts, is sprayed as a mist and then transported by means of a carrier gas (typically containing oxygen) into the hot zone of a tubular furnace. At the elevated temperature, the precursor solution transforms into the desired crystalline oxide. As the composition of the final product, a nanocrystalline oxide powder, is determined by the composition of the precursor solution, the process is highly reproducible and \n\n![](images/517226391024f91fa9075bb37d72edc15f65e219dd19e88ebf27c70ac30c8ba7.jpg) \nFig. 5 Coulombic efficiencies of the TM-MEO and TM-HEO compounds and rate test of a higher-loaded TM-HEO electrode. a Coulombic efficiency vs. cycle number for all the tested electrode materials at $50\\mathsf{m A}\\mathtt{g}^{-1}$ . Only TM-HEO reveals stable cycling behavior. The multiphase material without Ni exhibits comparable efficiencies, but with much lower specific capacities (below $250\\mathsf{m A h g}^{-1}$ after 40 cycles) (Supplementary Figure 4). b Rate performance test performed on a TM-HEO cell with an overall higher loading (2.3 mgTM-HEO $\\mathsf{c m}^{-2}.$ ). The current values in $\\boldsymbol{\\mathbf{b}}$ are given in units of $\\mathsf{A}\\mathsf{g}^{-1}$ \n\n![](images/758f511016aff2410607dfca5fc40f27253bc925e4b07268ac3d285d7ca239b6.jpg) \nFig. 6 Schematics of the proposed de-/lithiation mechanism during the conversion reaction of TM-HEO. M in the figure stands only for the cations Co, Cu, Zn, and Ni, since Mg is electrochemically inactive in the potential range applied here. The as-prepared TM-HEO is made of poly-/nanocrystallites, exhibiting an ordered structure, as evidenced by SAED, TEM, and XRD. During the lithiation, some of the divalent metals of the TM-HEO react with Li to form nano- $_{-\\mathrm{i}_{2}\\mathrm{O}}$ and nano-M nuclei via a conversion reaction. The SAED measurements clearly show that the rock-salt structure is preserved in this state. The nanosized nuclei grow inside the rock-salt host structure, causing stresses to build up, thus resulting in the introduction of defects. Consequently, the reflections in the XRD pattern disappear—the nuclei “destroy” the long-range order; nevertheless, the participating ions remain “trapped” inside the host matrix and can easily diffuse back into the crystal structure in the subsequent oxidation process. Hence, the parent HEO structure is restored after delithiation \n\nprovides quantities on the scale of $1{-}2\\ \\mathrm{gh}^{-1}$ for a laboratory reactor. In the present study, the respective transition metal ions were dissolved in an aqueous-based solvent using the corresponding nitrates ( $(\\mathrm{Co}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ (Sigma Aldrich, $99.9\\%$ ), $\\mathrm{Cu(NO_{3})_{2}}{\\cdot}2.5\\mathrm{H}_{2}\\mathrm{O}$ (Sigma Aldrich, $99.9\\%$ ), $\\mathrm{Mg(NO_{3})_{2}.6H_{2}O}$ (Sigma Aldrich, $99.9\\%$ , $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ (Sigma Aldrich, $99.9\\%$ ), and $\\mathrm{Zn(NO_{3})_{2}{\\cdot}6H_{2}O}$ (Alfa Aesar, $99.9\\%\\right)\\$ ). The particles are formed in the gas phase of the hot-wall reactor, operated at $1150^{\\circ}\\mathrm{C}$ . For the 5-cation system, a single-phase structure was obtained directly during the synthesis process. By contrast, the 4-cation systems (see Table 1) required a post annealing treatment $\\mathrm{~\\textit~{~1~h~}~}$ at $1000^{\\circ}\\mathrm{C}$ under ambient atmosphere) to form a single-phase compound. This annealing step was also applied to the 5- cation system, to make sure that all the compounds had the same synthesis/heat treatment history to facilitate comparison of the electrochemical properties among the different systems. \n\nElectrode processing. TM-HEO electrodes were prepared by casting a water slurry containing $63\\mathrm{wt\\%}$ TM-HEO, $22\\mathrm{wt\\%}$ Super C65 carbon black additive (Timcal) and $15\\mathrm{wt\\%}$ Selvol 425 poly(vinyl alcohol) (Sekisui)30 onto Cu foil (Gould Electronics). The resulting electrode tapes were dried in vacuum at $80^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ . The typical areal loading of active material was $0.5{-}1\\mathrm{mgcm}^{-2}$ unless mentioned otherwise $(2.3\\mathrm{mg}\\mathrm{cm}^{-2}$ for high-loading electrodes). Coin-type cells with $600\\upmu\\mathrm{m}$ - thick Li metal foil (Albemarle Germany GmbH) and glass microfiber separator (Whatman, GF/A; GE Healthcare Life Sciences) were assembled inside an argonfilled glovebox $([\\mathrm{O}_{2}]<0.5\\:\\mathrm{ppm}$ , $\\mathrm{[H_{2}O]}<0.5\\mathrm{ppm}_{\\mathrm{.}}$ ). The electrolyte used was $1\\mathrm{M}$ $\\mathrm{LiPF}_{6}$ in a 3:7 weight mixture of ethylene carbonate and either dimethyl carbonate or ethyl methyl carbonate (BASF SE). All capacities given are related to the mass of the active material. \n\nCharacterization. Operando XRD was performed using a high-intensity laboratory Mo- $\\mathrm{Ka}_{1,2}$ diffractometer, optimized for battery research. Details of the setup as well as a description of calibration procedures can be found elsewhere31–33. Powder XRD patterns were recorded using a Bruker D8 Advance diffractometer with a CuKα radiation source and a LYNXEYE detector having a fixed divergence slit $(0.3^{\\circ})$ . For operando XRD, coin cells, equipped with polyimide windows, were assembled inside a glovebox by stacking electrode $\\phantom{+}\\varnothing12\\mathrm{mm},$ , glass fiber separator $\\cdot017\\mathrm{mm}$ ) and Li metal foil anode ( $\\mathrm{~\\'~}\\mathrm{~O~}16\\:\\mathrm{mm},$ ) and using $150\\upmu\\mathrm{l}$ of electrolyte33. During the operando XRD experiment, the cell was cycled at $\\mathrm{100\\mA\\g^{-1}}$ in the voltage range between 0.01 and $3\\mathrm{V}$ . 2D diffraction patterns were collected in transmission geometry with an exposure time of $300\\mathrm{s}.$ The intensities of two consecutive patterns were added up and then integrated to obtain 1D data, resulting in a total time resolution of $600\\mathrm{{s}}$ . Transmission electron microscopy (TEM) experiments were conducted on powder samples dispersed onto a carbon-coated gold grid. The samples were loaded onto a Gatan TEM vacuum transfer holder inside a glovebox and transferred to the TEM without exposure to air. The TEM samples were examined using a Titan 80–300 electron microscope (FEI), equipped with a CEOS image spherical aberration corrector, high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) detector (Fischione model 3000) and a Tridiem Gatan image filter (GIF). The microscope was operated at an accelerating voltage of $300\\mathrm{kV}$ . SEM was performed on a ZEISS Gemini Leo 1530. Galvanostatic charge/discharge measurements were performed at room \n\ntemperature and at various specific currents of $50{-}3000\\mathrm{mAg^{-1}}$ in the voltage range between 0.01 and $3.0\\mathrm{V}$ vs. $\\mathrm{Li^{+}/L i}$ using a MACCOR battery cycler. \n\nData availability. The data used for this study are available from the corresponding authors upon request. \n\n# Received: 8 March 2018 Accepted: 25 July 2018 Published online: 24 August 2018 \n\n# References \n\n1. Mizushima, K., Jones, P. C., Wiseman, P. J. & Goodenough, J. B. $\\mathrm{Li}_{\\mathrm{x}}\\mathrm{CoO}_{2}$ $(0<\\mathbf{x}<-1)$ : a new cathode material for batteries of high energy density. Mater. Res. Bull. 15, 783–789 (1980). \n2. Nitta, N., Wu, F., Lee, J. T. & Yushin, G. Li-ion battery materials: present and future. Mater. Today 18, 252–264 (2015). \n3. Reddy, M. A. et al. $\\mathrm{CF_{x}}$ derived carbon- ${\\mathrm{.FeF}}_{2}$ nanocomposites for reversible lithium storage. Adv. Energy Mater. 3, 308–313 (2013). Breitung, B., Baumann, P., Sommer, H., Janek, J. & Brezesinski, T. In situ and operando atomic force microscopy of high-capacity nano-silicon based electrodes for lithium-ion batteries. Nanoscale 8, 14048–14056 (2016). \n5. Bérardan, D., Franger, S., Meena, A. K. & Dragoe, N. Room temperature lithium superionic conductivity in high entropy oxides. J. Mater. Chem. A 4, 9536–9541 (2016). \n6. Sarkar, A. et al. Nanocrystalline multicomponent entropy stabilised transition metal oxides. J. Eur. Ceram. Soc. 37, 747–754 (2017). \n7. Rost, C. M. et al. Entropy-stabilized oxides. Nat. Commun. 6, 8485 (2015). \n8. Sarkar, A. et al. Multicomponent equiatomic rare earth oxides with a narrow band gap and associated praseodymium multivalency. Dalton Trans. 46, 12167–12176 (2017). \n9. Sarkar, A. et al. Rare earth and transition metal based entropy stabilised perovskite type oxides. J. Eur. Ceram. Soc. 38, 2318–2327 (2018). \n10. Miracle, D. B. & Senkov, O. N. A critical review of high entropy alloys and related concepts. Acta Mater. 122, 448–511 (2017). \n11. Bérardan, D., Franger, S., Dragoe, D., Meena, A. K. & Dragoe, N. Colossal dielectric constant in high entropy oxides. Phys. Status Solidi Res. Lett. 10, 328–333 (2016). \n12. Dąbrowa, J. et al. Synthesis and microstructure of the $(\\mathrm{Co},\\mathrm{Cr},\\mathrm{Fe},\\mathrm{Mn},\\mathrm{Ni})_{3}\\mathrm{O}_{4}$ high entropy oxide characterized by spinel structure. Mater. Lett. 216, 32–36 (2018). \n13. Wang, F. et al. Conversion reaction mechanisms in lithium ion batteries: study of the binary metal fluoride electrodes. J. Am. Chem. Soc. 133, 18828–18836 (2011). \n14. Poizot, P., Laruelle, S., Grugeon, S., Dupont, L. & Tarascon, J. M. Nano-sized transition-metal oxides as negative-electrode materials for lithium-ion batteries. Nature 407, 496–499 (2000). \n15. Chiang, Y.-M., Birnie, D. P. & Kingery, W. D. Physical Ceramics: Principles for Ceramic Science and Engineering (John Wiley & Sons, Inc., New York, 1997). \n16. Helen, M. et al. Single step transformation of sulphur to $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ in Li-S batteries. Sci. Rep. 5, 12146 (2015). \n17. Ding, C. et al. A bubble-template approach for assembling Ni–Co oxide hollow microspheres with an enhanced electrochemical performance as an anode for lithium ion batteries. Phys. Chem. Chem. Phys. 18, 25879–25886 (2016). \n18. Sun, Y., Hu, X., Luo, W. & Huang, Y. Ultrathin CoO/graphene hybrid nanosheets: a highly stable anode material for lithium-ion batteries. J. Phys. Chem. C 116, 20794–20799 (2012). \n19. Suchomski, C. et al. Microwave synthesis of high-quality and uniform $4\\ \\mathrm{nm}$ $\\mathrm{ZnFe}_{2}\\mathrm{O}_{4}$ nanocrystals for application in energy storage and nanomagnetics. Beilstein J. Nanotechnol. 7, 1350–1360 (2016). \n20. Liu, H., Wang, G., Liu, J., Qiao, S. & Ahn, H. Highly ordered mesoporous NiO anode material for lithium ion batteries with an excellent electrochemical performance. J. Mater. Chem. 21, 3046 (2011). \n21. Wang, C. et al. Morphology-dependent performance of CuO anodes via facile and controllable synthesis for lithium-ion batteries. ACS Appl. Mater. Interfaces 6, 1243–1250 (2014). \n22. Goriparti, S. et al. Review on recent progress of nanostructured anode materials for Li-ion batteries. J. Power Sources 257, 421–443 (2014). \n23. Ji, L., Lin, Z., Alcoutlabi, M. & Zhang, X. Recent developments in nanostructured anode materials for rechargeable lithium-ion batteries. Energy Environ. Sci. 4, 2682 (2011). \n24. Murty, B. S., Yeh, J. W. & Ranganathan, S. High-Entropy Alloys (ButterworthHeinemann, London, 2014) \n25. Morcrette, M. et al. A reversible copper extrusion-insertion electrode for rechargeable Li batteries. Nat. Mater. 2, 755–761 (2003). \n26. Débart, A., Dupont, L., Patrice, R. & Tarascon, J. M. Reactivity of transition metal (Co, Ni, Cu) sulphides versus lithium: the intriguing case of the copper sulphide. Solid State Sci. 8, 640–651 (2006). \n27. Wang, Y. F. & Zhang, L. J. Simple synthesis of CoO-NiO-C anode materials for lithium-ion batteries and investigation on its electrochemical performance. J. Power Sources 209, 20–29 (2012). \n28. Mueller, F. et al. Iron-doped ZnO for lithium-ion anodes: impact of the dopant ratio and carbon coating content. J. Electrochem. Soc. 164, A6123–A6130 (2017). \n29. Bresser, D. et al. Transition-metal-doped zinc oxide nanoparticles as a new lithium-ion anode material. Chem. Mater. 25, 4977–4985 (2013). \n30. Reitz, C. et al. Hierarchical carbon with high nitrogen doping level: a versatile anode and cathode host material for long-life lithium-ion and lithium-sulfur batteries. ACS Appl. Mater. Interfaces 8, 10274–10282 (2016). \n31. de Biasi, L. et al. Between Scylla and Charybdis: balancing among structural stability and energy density of layered NCM cathode materials for advanced lithium-ion batteries. J. Phys. Chem. C. 121, 26163–26171 (2017). \n32. Kondrakov, A. O. et al. Anisotropic lattice strain and mechanical degradation of high- and low-nickel NCM cathode materials for Li-ion batteries. J. Phys. Chem. C. 121, 3286–3294 (2017). \n33. de Biasi, L. et al. Unravelling the mechanism of lithium insertion into and extraction from trirutile-type LiNiFeF $\\dot{\\mathbf{\\up}}_{6}$ cathode material for Li-ion batteries. CrystEngComm 17, 6163–6174 (2015). \n\n# Acknowledgements \n\nOne of the authors (Q.W.) acknowledges financial support by EnABLES. This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 730957. H.H. and A.S. acknowledge financial support from the Helmholtz Association and the Deutsche Forschungsgemeinschaft (DFG) project HA/1344/43-1. We acknowledge support by Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of Karlsruhe Institute of Technology. \n\n# Author contributions \n\nA.S. synthesized the materials, fabricated the electrodes and performed the electrochemical experiments and analysis. L.V. synthesized the materials and analyzed HRTEM micrographs. D.W. and C.K. conducted and analyzed HRTEM and EDX measurements. G.T. supported the synthetic efforts. L.d.B. performed and analyzed operando XRD measurements. Q.W. prepared the electrodes with higher loading and helped with CV analysis. T.B. supervised the XRD measurements and co-wrote the manuscript. S.B. developed the material synthesis and supported the synthesis efforts. H.H. and B.B. supervised the synthesis and experiments, directed the project and co-wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-05774-5. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1038_s41467-018-04635-5", + "DOI": "10.1038/s41467-018-04635-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-04635-5", + "Relative Dir Path": "mds/10.1038_s41467-018-04635-5", + "Article Title": "Engineering triangular carbon quantum dots with unprecedented narrow bandwidth emission for multicolored LEDs", + "Authors": "Yuan, FL; Yuan, T; Sui, LZ; Wang, ZB; Xi, ZF; Li, YC; Li, XH; Fan, LZ; Tan, ZA; Chen, AM; Jin, MX; Yang, SH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Carbon quantum dots (CQDs) have emerged as promising materials for optoelectronic applications on account of carbon's intrinsic merits of high stability, low cost, and environment-friendliness. However, the CQDs usually give broad emission with full width at half maximum exceeding 80 nm, which fundamentally limit their display applications. Here we demonstrate multicolored narrow bandwidth emission (full width at half maximum of 30 nm) from triangular CQDs with a quantum yield up to 54-72%. Detailed structural and optical characterizations together with theoretical calculations reveal that the molecular purity and crystalline perfection of the triangular CQDs are key to the high color-purity. Moreover, multicolored light-emitting diodes based on these CQDs display good stability, high color-purity, and high-performance with maximum luminullce of 1882-4762 cd m(-2) and current efficiency of 1.22-5.11 cd A(-1). This work will set the stage for developing nextgeneration high-performance CQDs-based light-emitting diodes.", + "Times Cited, WoS Core": 825, + "Times Cited, All Databases": 862, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000434648400005", + "Markdown": "# Engineering triangular carbon quantum dots with unprecedented narrow bandwidth emission for multicolored LEDs \n\nFanglong Yuan1, Ting Yuan1, Laizhi Sui2,3, Zhibin Wang4, Zifan Xi1, Yunchao Li $\\textcircled{1}$ 1, Xiaohong Li1, Louzhen Fan1, Zhan’ao Tan4,5, Anmin Chen2, Mingxing Jin2 & Shihe Yang6 \n\nCarbon quantum dots (CQDs) have emerged as promising materials for optoelectronic applications on account of carbon’s intrinsic merits of high stability, low cost, and environment-friendliness. However, the CQDs usually give broad emission with full width at half maximum exceeding $80\\mathsf{n m}$ , which fundamentally limit their display applications. Here we demonstrate multicolored narrow bandwidth emission (full width at half maximum of 30 nm) from triangular CQDs with a quantum yield up to $54\\mathrm{-}72\\%$ . Detailed structural and optical characterizations together with theoretical calculations reveal that the molecular purity and crystalline perfection of the triangular CQDs are key to the high color-purity. Moreover, multicolored light-emitting diodes based on these CQDs display good stability, high color-purity, and high-performance with maximum luminance of $1882\\mathrm{-}4762\\mathrm{cdm}^{-2}$ and current efficiency of $1.22{\\-}5.11{\\mathsf{c d}}\\mathsf{A}^{-1}$ . This work will set the stage for developing nextgeneration high-performance CQDs-based light-emitting diodes. \n\n二 etting light from carbon has long been a dream of the scientific community. Carbon-based highly efficient light一 emitting materials will not only raise the prospect of the next-generation technological frontiers of carbon photonics and optoelectronics, but also offer an alternative to traditional semiconductor inorganic quantum dots (QDs) such as the $\\mathrm{Cd}^{2+}/\\mathrm{Pb}^{2+}$ -based QDs in light-emitting applications taking advantage of carbon’s high stability, low cost, high abundance and environment-friendliness1–7. The discovery of room temperature light emission from quantum sized carbon $(<10\\mathrm{nm})$ in $\\dot{2}006^{8}$ triggered intensive researches on light-emitting carbon quantum dots (CQDs) to realize their wide potential applications9–14. In the last few years, great progress has been made in designing and synthesizing highly tunable bandgap fluorescent CQDs with a quantum yield (QY) as high as $75\\%$ , even comparable to the best performing $\\mathrm{Cd}^{2+}/\\mathrm{Pb}^{2+}$ -based QDs, through a variety of strategies such as heteroatom doping, surface engineering or passivation, and product separation and purification15–18. Meanwhile, the wide potential optoelectronic applications of the CQDs have also been demonstrated17–23. For instance, light-emitting diodes (LEDs) from blue to red based on the bandgap fluorescent CQDs have been reported most recently18, laying a solid foundation for the development of a new display technology based on the CQDs. However, despite the intensive work on the electronic and optical properties of CQDs, it has until now remained a widely accepted belief that CQDs can only give broad emission and inferior color-purity with full width at half maximum (FWHM) commonly exceeding $80\\mathrm{nm}^{15-19,23}$ Indeed, such a broad bandwidth emission is far inferior to that of $\\mathrm{Cd}^{2+}/\\mathrm{Pb}^{2+}$ -based QDs (FWHM ${<}40\\mathrm{nm}\\backslash$ ), which has severely hindered the application of CQDs-based LEDs in high colorpurity displays24,25. \n\nThe exact mechanism of the broadband fluorescence spectra of CQDs has been a longstanding unsettled issue. It has been generally believed that the broadband fluorescence spectra of CQDs stem from a broad size distribution. However, even after narrowing the size distribution through elaborate separation and purification, the fluorescence spectra still remains broad (FWHM $\\dot{>}80\\mathrm{nm})^{15-19,26}$ . This indicates that the broadband fluorescence spectra cannot be simply ascribed to the dot size polydispersity, but may be intrinsic to the CQDs. For instance, the complex nonradiative excited-state relaxation processes arising from specific structure-associated phenomena, such as self-localized charges and surface defect-trapped carriers observed in traditional inorganic QDs, are probably the main origin of the broadband fluorescence spectra of $\\mathrm{CQDs^{1-3}}$ . The former can be considered as transient defects formed in the excited states where photogenerated charge carriers are stabilized through largeamplitude vibrations and distortions driven by strong electron–phonon coupling27–29, while the latter is usually induced by the numerous electron-withdrawing oxygen-containing groups such as carboxyl, carbonyl, and epoxy groups at edge or basal plane sites of the $\\mathrm{CQDs}^{26,30-33}$ . Consequently, weakening the electron–phonon coupling and reducing the surface defects by structural engineering may be a feasible way to realize narrow bandwidth emission of CQDs with high color-purity. \n\nResorting to common sense, the fact that triangle is the most stable structure in nature offers a hint in the structural engineering along the direction. Indeed, the physical properties including band-gap renormalization, electron–hole attraction, oscillator strength, and exciton polarization of model triangular graphene quantum dots (T-GQDs) containing 168 and $132^{\\mathrm{{\\omega}}}\\mathrm{sp}^{2}$ - hybridized C atoms have been theoretically investigated34. Shortly thereafter, the biexciton binding of Dirac fermions of T-GQDs containing $168~{\\mathrm{sp}}^{2}$ -hybridized C atoms has also been probed by transient absorption measurements and microscopic theory35. \n\nHere, we report the synthesis of high color-purity, narrow bandwidth (FWHM of $29-30~\\mathrm{nm}$ ), and multicolored (from blue to red) emission triangular CQDs (T-CQDs) with a quantum yield up to $54\\mathrm{-}72\\%$ . The synthesis is conducted by judiciously choosing a three-fold symmetric phloroglucinol (PG) as the reagent (a triangulogen) together with a tri-molecular reaction route designed into the neighboring active -OH and -H groups for six-membered ring cyclization, propagating to the target high color-purity narrow bandwidth emission T-CQDs (NBE-TCQDs) (Fig. 1a–e). The triangular structure and the narrow bandwidth emission of NBE-T-CQDs have been rigorously established, and their correlation manifest that the triangular structural rigidity dramatically reduces electron-phonon coupling, giving rise to the free-excitonic emission with negligible trap states. This has been borne out by elaborate theoretical calculations, which show highly delocalized charges and high structural stability of the T-CQDs. The multicolored LEDs based on the NBE-T-CQDs dispaly high color-purity (FWHM of 30 nm) and high-performance with a maximum luminance $\\left(L_{\\mathrm{max}}\\right)$ of $4762\\ c\\mathrm d\\mathrm m^{-2}$ and current efficiency $(\\eta_{\\mathrm{c}})$ of 5.11 cd $\\mathrm{A}^{-1}$ . Moreover, the LEDs demonstrate outstanding stability both on shelf and in operation. \n\n# Results \n\nSynthesis of NBE-T-CQDs. Synthesis of the NBE-T-CQDs, as shown in Fig. 1a, involves the solvothermal treatment of threefold symmetric PG triangulogen at $200^{\\circ}\\mathrm{C}$ with different reaction time, followed by purifying via silica column chromatography using a mixture of dichloromethane and methanol as the eluent. The starting material PG triangulogen possesses a unique structure with three highly reactive hydrogen atoms at the three metapositions activated by three electron-donating hydroxyl groups in a single molecule, which is a key point for the synthesis of the NBE-T-CQDs. For tuning their emission color, an appropriate amount of concentrated sulfuric acid was added as catalyst in the ethanol solution to control the size of NBE-T-CQDs (see Methods for more details). The preparation yield for NBE-T-CQDs is estimated to be about $8\\mathrm{-}13\\%$ . The typical aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) images of the NBE-T-CQDs (Fig. 1b–e) clearly demonstrate the almost defect-free graphene crystalline structure with an obvious triangular shape. To the best of our knowledge, this is the first time that the exquisite aberration-corrected HAADF-STEM images of carbon materials were obtained. The bright multicolored emissions of blue (B), green (G), yellow (Y), and red (R) were observed from the NBET-CQDs solutions with gradually increasing sizes from $1.9\\mathrm{nm}$ , to 2.4, 3.0, and $3.9\\mathrm{nm}$ , respectively (Fig. 1f), as expected from the quantum confinement effect7,16–18. Significantly, the tunable emission colors from blue to red could be observed even under daylight excitation (Fig. 1f), which is a clear signature of the strong emission. And the emission colors are brighter under UV light irradiation (excited at $365\\mathrm{nm}$ , Fig. 1g) due to the pronounced absorption of NBE-T-CQDs at $365\\mathrm{nm}$ (Supplementary Figs. 1-2). \n\nOptical properties of NBE-T-CQDs. The most important and distinctive features of the NBE-T-CQDs that set them apart from all other previous reported CQDs are the extremely narrow excitonic absorption and emission peaks. Figure 1h shows the absorption spectra of the NBE-T-CQDs with strong and narrow excitonic absorption peaks centered at 460 (B-), 498 (G-), 521 (Y), and $582\\mathrm{nm}$ (R-NBE-T-CQDs), which is quite different from that of the previous reported CQDs with ultrabroad absorption bands $7-18,23,26$ . The fluorescence spectra of NBE-T-CQDs (Fig. 1i) also show sharp excitonic emission peaks centered at 472 (B-), 507 (G-), 538 (Y-), and $598\\mathrm{nm}$ (R-NBE-T-CQDs) with extremely narrow FWHM values of only 30, 29, 30, and $30\\mathrm{nm}$ , respectively, which is far superior to previous reported CQDs with broadband fluorescence spectra (FWHM ${>}80\\mathrm{nm}$ ) and even superior to the best $\\mathrm{Cd}^{2+}/\\mathrm{Pb}^{2+}$ -based QDs (FWHM $<40\\mathrm{nm})^{5-18,23,26}$ . The weak shoulder emission peaks at longer wavelengths in the photoluminescence (PL) spectra may be ascribed to the excimer emission of the NBE-T-CQDs, which is often observed in highly delocalized polyaromatic systems36,37. Moreover, the NBE-T-CQDs also exhibit ultrasmall Stokes shifts of 12, 9, 17, and $16\\mathrm{nm}$ for the B-, G-, Y-, and R-NBE-T-CQDs, respectively (Supplementary Figs. 1-2), much smaller than those of the common CQDs (Stokes shifts $>80\\mathrm{nm})^{15-18}$ , implying the band edge direct exciton recombination of the optical transitions as well as the weak electron–phonon coupling of the NBE-TCQDs. The maximum peak wavelength of the FL excitation spectra are centered at about 460 (B-), 498 (G-), 521 (Y-), and $582\\mathrm{nm}$ (R-NBE-T-CQDs), and agree well with the corresponding excitonic absorption peak wavelengths (Supplementary Figs. 3-4), clearly suggesting that the emission of NBE-T-CQDs originates from band-edge exciton-state decay rather than from defect-state decay. The unusually narrow emission peaks of the NBE-T-CQDs are irrespective of the wide excitation wavelength range (Supplementary Fig. 5). These results further confirm that the PL emissions of the NBE-T-CQDs originate from direct exciton recombination. This is very different from the traditional CQDs whose excitation-dependent fluorescence is dominated by surface defects15–18. The gradually red-shifted narrow bandwidth excitonic emission peak of the NBE-T-CQDs from $472\\mathrm{nm}$ (blue) to $598\\mathrm{nm}$ (red) are well consistent with the corresponding increased size from 1.9 to $3.9\\mathrm{nm}$ . Significantly, such a correlation is almost linear as shown in Supplementary Fig. 6, a very clear characteristic of the bandgap transitions of the NBE-T-CQDs. \n\n![](images/aaf87ca83d43440b5f37bd25936931c70dc41e31f116cb051e8473c9e1edb1a7.jpg) \nFig. 1 Design and synthesis of narrow bandwidth emission triangular CQDs. a Synthesis route of the NBE-T-CQDs by solvothermal treatment of PG triangulogen. The typical aberration-corrected HAADF-STEM images of B- (b), G- (c), Y- (d), and R-NBE-T-CQDs (e), respectively. Scale bar, $2{\\mathsf{n m}}$ . Photographs of the NBE-T-CQDs ethanol solution under daylight $(\\pmb{\\uparrow})$ and fluorescence images under UV light (excited at $365\\mathsf{n m}$ ) ${\\bf\\Pi}({\\bf g})$ . The normalized UVvis absorption ${\\bf\\Pi}({\\bf h})$ and PL (i) spectra of B-, G-, Y-, and R-NBE-T-CQDs, respectively \n\nTo gain more insight into the exciton recombination dynamics, we measured time-resolved PL spectra at emission and excitation wavelengths of about 472/460, 507/500, 538/520, and $598/580\\mathrm{nm}$ for B-, G-, Y-, and R-NBE-T-CQDs, respectively, and the results are shown in Fig. 2a, which evidence monoexponential decay with fluorescence lifetimes of about 7.3, 8.3, 7.0, and 6.6 ns for the B-, G-, Y-, and R- NBE-T-CQDs, respectively (Supplementary Fig. 7). The monoexponential decay characteristics indicate that the excitons are highly stable and the radiative decay is extremely pure with a minimal nonradiative contribution17,18, which is conducive to efficient fluorescence emission and again strikingly different from those reported CQDs with multi-exponential decay10,30–33. The absolute QY was determined to be 66, 72, 62, and $54\\%$ in ethanol for the high color-purity B-, G-, Y-, and RNBE-T-CQDs with the corresponding excitation wavelength being 460, 500, 520, and $580\\mathrm{nm}$ , respectively. Notably, these QYs are among the highest values for CQDs reported to date, despite the fact that almost no fluorescence was detected in the macroscopic solid powder state due to the strong $\\pi{-}\\pi$ interactions between the highly crystalline NBE-T-CQDs with a large π- conjugated structure. What is more, the NBE-T-CQDs also show the rarely seen strong high color-purity two-photon fluorescence (TPF) from blue to red (FWHM of $29\\mathrm{nm}$ ) (Supplementary Figs. 8-14), which may enable them to be used as excellent optical-gain media for high-performance frequency-upconversion tunable lasers38. \n\n![](images/6b521e849f730419babddba8583fa3f4a7ce08836e111c4666529b7908a88c33.jpg) \nFig. 2 Ultrafast dynamics of the photoexcited states and temperature-dependent PL spectra of the NBE-T-CQDs. a Time-resolved PL spectra of the NBE-TCQDs. b Two-dimensional pseudocolor map of TA spectra of B-NBE-T-CQDs expressed in ΔOD (the change of the absorption intensity of the sample after excitation) as a function of both delay time and probe wavelength excited at $400\\mathsf{n m}$ . c TA spectra of B-NBE-T-CQDs at indicated delay times from $0.5{\\mathsf p}{\\mathsf s}$ to 1 ns. d Results of the global fitting with four exponent decay functions. e The normalized temperature-dependent PL spectra of B-NBE-T-CQDs. f The normalized PL spectra of the NBE-T-CQDs acquired at $85\\mathsf{K}.\\mathsf{g}$ The plots of the emission peak energy and FWHM of B-NBE-T-CQDs as a function of temperature $(85-295\\mathsf{K})$ . h The plots of integrated PL emission intensity of the NBE-T-CQDs as a function of temperature (175–295 K) \n\nBandgap energies of the NBE-T-CQDs were further calculated using the equation $E_{\\mathrm{g}}^{\\mathrm{\\scriptsize~opt}}=1240/\\lambda_{\\mathrm{edge}},$ where $\\lambda_{\\mathrm{edge}}$ is the onset value of the first excitonic absorption peaks in the direction of longer wavelengths. The calculated bandgap energies gradually decreased from 2.63 to $2.07\\mathrm{eV}$ with the excitonic emission peak red-shifting from 472 to $598\\mathrm{nm}$ and the size increasing from 1.9 to $3.9\\mathrm{nm}$ (Supplementary Fig. 15), further demonstrating the obvious size-dependent property of bandgap energies18. Meanwhile, the up-shifted highest occupied molecular orbital (HOMO) levels from $-5.18$ to $-4.92\\mathrm{eV}$ determined by means of ultraviolet photoelectron spectroscopy (UPS) and the down-shifted lowest unoccupied molecular orbital (LUMO) levels from $-2.55$ to $-2.85\\mathrm{eV}$ (Supplementary Figs. 16-18, Supplementary Table 1) of the NBE-T-CQDs from blue to red directly reveal that the quantum confinement effect dominates the electronic and optical properties of the NBE-T-CQDs. \n\nTo further scrutinize the bright and high color-purity excitonic emission of the NBE-T-CQDs from the perspective of transfer and recombination dynamics of the photogenerated charges, femtosecond transient absorption (fs-TA) spectroscopy measurement was carried out at $400\\mathrm{nm}$ excitation. The TA spectra of BNBE-T-CQDs are depicted in Fig. 2b in pseudo-3D with probe in the $430{\\mathrm{-}}710\\ \\mathrm{nm}$ range and scan delay time from 0.1 ps to $2\\mathrm{ns}$ . The negative (blue) features from 430 to $550\\mathrm{nm}$ correspond to the ground state bleaching (GSB) and stimulated emission (SE) according to the steady-state absorption and PL spectra, and the relatively weaker positive (red) features from 600 to $710\\mathrm{nm}$ correspond to the excited state absorption (ESA). The TA spectra at different time delays are shown in Fig. 2c. The negative peaks of SE centered at 466 and $524\\mathrm{nm}$ gradually increase in the first picosecond. The kinetic traces at different wavelengths as a function of delay time are also presented in Supplementary Fig. 19. To unravel the detailed relaxation channels of the excited carriers of B-NBE-T-CQDs, global analyses were performed on the TA data, and four distinctive decay components were derived. The four fitted lifetimes of carriers are $0.54\\pm0.01$ ps, $31.5\\pm0.8$ ps, $77\\pm2$ ps, and $7.3\\pm0.08\\mathrm{ns}$ , respectively. The fitted decay associated difference spectra (DADS) are shown in Fig. 2d. It can be observed that during the first lifetime, the GSB decays accompanied by the rise of SE, then the signal of SE continues to increase within the second lifetime, but in the third and fourth lifetime, the SE signal decays. The weaker DADS at around ESA were enlarged to reveal more clearly the changes of different components. In order to analyze the four different carrier relaxation channels, the DADS at different wavelengths are normalized to evaluate the proportion of the decay dynamics (Supplementary Fig. 20). Different regions with distinct relaxation dynamics can be clearly observed as follows: the percentage of both the first and second component is zero at about $468\\mathrm{nm}$ the percentage of the second component at about 506 and $605\\mathrm{nm}$ is zero; the percentage of the fourth component at about $598\\mathrm{nm}$ is zero; the percentage of the third component at about $590\\mathrm{nm}$ and from 632 to $700\\mathrm{nm}$ are zero. On the basis of the different regions and DADS, we can ascribe the four components to the corresponding relaxation channels. Since the pump $(400\\mathrm{nm})$ is higher in energy than the bandgap of B-NBE-T-CQDs, the excited carriers in the $\\mathsf{s p}^{2}$ cluster have excess energy after excitation, and will experience Coulomb-induced thermalization within the first few tens of femtoseconds, which is shorter than our instrumental response time (about 100 fs)39. The hot carriers will release the excess energy into the surrounding environment via optical phonon scattering $(0.54\\mathrm{ps})^{40}$ and acoustic phonon scattering $(31.5\\mathrm{ps})^{41}$ . Part of the cooled carriers, whose dyanmics is distributed at about $598\\mathrm{nm}$ , will experience nonradiative transition into the ground state within $77\\mathrm{ps}$ . The remaining part will emit fluorescence (7.3 ns) via recombination of electrons and holes, and the ESA of this part is mainly distributed at $590\\mathrm{nm}$ and $632\\mathrm{-}700\\mathrm{nm}$ . Intriguingly, the strong emission of the NBE-TCQDs is directly demonstrated here by the much higher amplitude of emissive component than that of nonradiative decay component, with the latter accounting for only a small percentage of about $15\\mathrm{-}20\\%$ (Fig. 2d, Supplementary Fig. 20). Furthermore, contrary to the complex nonradiative excited-state relaxation processes commonly responsible for the broadening of PL peaks, the quite simple excited state relaxation channels we obtained from the TA spectra naturally explain the high colorpurity excitonic emission of NBE-T-CQDs42,43. \n\nTo acquire more intrinsic characteristics of the photogenerated excitons in the high color-purity NBE-T-CQDs, temperaturedependent PL spectra were also recorded, and the resulting emission narrowing was analyzed, as has long been used to assess mechanisms of electron–phonon coupling in a wide range of bandgap emitting inorganic $\\mathrm{QDs^{44,45}}$ . As the temperature is decreased from 295 to $8\\bar{5}\\mathrm{K}$ , all the PL peaks of the NBE-T-CQDs show continuous narrowing and blue-shift (Fig. 2e, Supplementary Figs. 21-22). Remarkably, the PL spectra acquired at $85\\mathrm{K}$ exhibit extremely narrow FWHM of 16, 11, 16, and $9\\mathrm{nm}$ for the B-, G-, Y-, and R-NBE-T-CQDs, respectively (Fig. 2f), indicating that the narrow emission is attributable to the lowest state freeexcitonic emission with negligible trap states. As shown in Fig. $^{2\\mathrm{g},}$ the FWHM reduces from 164.7 $\\left(30\\mathrm{nm}\\right)$ to $95.4\\mathrm{meV}$ $\\left(16\\mathrm{{nm}}\\right)$ and the emission peak energy of the B-NBE-T-CQDs shifts toward higher energy from 2.627 to $2.725\\mathrm{eV}$ with decreasing temperature from 295 to $85\\mathrm{K}$ . The narrowed FWHM and blue-shifted emission peaks of the NBE-T-CQDs with decreasing temperature are well described by traditional empirical Varshni models, which can be explained by the reduced electron–phonon coupling due to the restricted structural vibrations and distortions at the lower temperatures44–46. It has been demonstrated that the electron–phonon coupling resulting from structural vibrations and distortions plays a dominating role in determining the FWHM of the PL spectra of inorganic $\\mathrm{QDs^{44,45}}$ . Therefore, it is reasonable to conclude that the dramatically reduced electron–phonon coupling demonstrated by the temperaturedependent PL spectra leads to the high color-purity, freeexcitonic emission of the NBE-T-CQDs. \n\nApart from the temperature-dependent PL peak wavelengths and FWHM, the integrated PL intensity of NBE-T-CQDs shows a slight decrease with increasing temperature (Fig. 2h), which can be ascribed to thermally activated exciton dissociation and nonradiative trapping47. Importantly, the thermal quenching of the integrated PL intensity of the NBE-T-CQDs with increasing temperature from 175 to $295\\mathrm{K}$ is $<20\\%$ , indicating the high thermostability and the minimal nonradiative recombination centers or defects. To extract the important physical parameter of exciton binding energy, we plot in Fig. 2h the integrated PL emission intensity as a function of temperature (175–295 K). The curves can be fitted using the following equation: \n\n$$\nI(T)=\\frac{I_{0}}{1+A e^{-E_{\\mathrm{b}}/k_{\\mathrm{B}}T}}\n$$ \n\nwhere $I_{0}$ is the intensity at $0\\mathrm{K},E_{\\mathrm{b}}$ is the exciton binding energy, and $k_{\\mathrm{B}}$ is the Boltzmann constant. From the fitting analysis, the NBE-T-CQDs have a relatively large exciton binding energy of 139.2, 128.2, 110.8, and $100.6\\mathrm{meV}$ for the B-, G-, Y-, and R-NBET-CQDs, respectively (Supplementary Figs. 23-26), which is even larger than those of many inorganic QDs and thus contributes to the high color-purity of the NBE-T-CQDs. The relatively large exciton binding energy of NBE-T-CQDs decreased from 139.2 (B-NBE-T-CQDs) to $100.6\\mathrm{meV}$ (R-NBE-T-CQDs) in a way conforming to the corresponding bandgap decrease, which is probably due to confinement effect associated with the unique quantum-sized high crystalline triangular graphene structure involving the size-dependent coulomb interaction48 and bandgap energy49. To the best of our knowledge, this is the first time that the important physical parameters of exciton binding energy are obtained for the CQDs. Moreover, besides the high thermostability concluded from the temperature-dependent PL spectra, the NBE-T-CQDs also showed more robust photostability than the best protected core-shell inorganic QDs such as $\\mathrm{CdZnS}@Z\\mathrm{nS}$ and organic dyes such as fluorescein (2-(6-hydroxy-3-oxo-3hxanthen-9-yl)-benzoicacid) under continuous radiation of a UV lamp for $10\\mathrm{{h}}$ (Supplementary Fig. 27), giving them more competitive edges for LED applications. \n\nStructural characterizations. Detailed structural characterizations were conducted so as to further shed light on the high colorpurity and reveal its intrinsic relation with the structure of the NBE-T-CQDs. It should be emphasized again that the aberrationcorrected HAADF-STEM images of the NBE-T-CQDs were obtained for the first time, which clearly demonstrate the high crystalline triangular structure of the NBE-T-CQDs (Fig. 3a). The wide-area TEM images of NBE-T-CQDs all show a narrow size distribution with the distinctive highly crystalline triangular structure as highlighted by the white contour lines (Fig. 3b, Supplementary Fig. 28). The sixfold symmetric fast Fourier transform (FFT) patterns of the HRTEM images as well as the identical well-resolved lattice fringes with a spacing of $0.21\\mathrm{nm}$ corresponding to the (100) inter-planar spacing further demonstrate the almost defect-free graphene crystalline structure of the NBE-T-CQDs (Supplementary Fig. 29)3,7,10,18. The gradually increased average sizes from 1.9 to $3.9\\mathrm{nm}$ are well consistent with the red-shifted emission colors from blue to red of the triangular CQDs, manifesting the quantum confinement effect18. The $\\mathrm{\\DeltaX}$ -ray powder diffraction (XRD) patterns of the NBE-T-CQDs show a narrow (002) peak centered at around $24^{\\circ}({\\mathrm{Fig}}.\\ 3{\\mathrm{c}})$ in contrast to the ultrabroad (002) peak of the previously reported $\\mathrm{CQDs}^{9-11,15-18}$ , which confirms the graphene structure of the NBE-T-CQDs with high crystallinity. The high degree of graphitization of the NBE-T-CQDs is reflected in their Raman spectra (Supplementary Fig. 30), where the crystalline G band at $1\\dot{6}15\\mathrm{cm}^{-1}$ is much stronger than the disordered D band at 1380 $\\mathrm{cm}^{-1}$ with a large G to D intensity ratio $(I_{\\mathrm{G}}/I_{\\mathrm{D}})$ of about 1.5–1.8, indicating the high quality of the graphene structure of the NBET-CQDs, and is well consistent with the high crystalline graphene structure determined by HAADF-STEM and HRTEM images. To the best of our knowledge, the $I_{\\mathrm{G}}/I_{\\mathrm{D}}$ values of the NBE-T-CQDs are among the largest ever reported to date for $\\mathrm{CQDs^{18}}$ . \n\nIn the $^1\\mathrm{H}$ -nuclear magnetic resonance (NMR) spectra (acetone-d6, ppm) (Fig. 3d, Supplementary Figs. 31-33), apart from the obvious aromatic hydrogen signals detected in the range of $7{-}8\\mathrm{ppm}$ , active hydrogen signals from hydroxy groups with broad peaks as black arrow indicated in Fig. 3d are also observed50. Moreover, $^{13}\\mathrm{C}$ -NMR spectra (methanol-d4, ppm) of the NBE-T-CQDs (Fig. 3e, Supplementary Figs. 34-37) further confirm the functionalization with pure electron-donating hydroxy groups at the edge sites. The clearly observed resonance signals in the range of 155 to $170\\mathrm{ppm}$ are indicative of the $\\mathsf{s p}^{2}$ carbon atoms bonded with hydroxy groups at the edge sites of the NBE-T-CQDs50. In addition, the emerging numerous signals observed in the range of $115{-}140\\mathrm{ppm}$ in the $^{13}\\mathrm{C}$ -NMR spectra compared with that of PG (Supplementary Fig. 34) further demonstrates the formation of intact $\\mathsf{s p}^{2}$ domains during the synthesis of the NBE-T-CQDs. Note that the NBE-T-CQDs with different emission colors all exhibit similar Fourier transform infrared (FT-IR) spectra, attesting to their similar chemical compositions. Besides, the strong stretching vibration bands of OH, $\\bar{\\mathrm{C}}\\mathrm{=}\\mathrm{C},$ and C-O, characteristic of the NBE-T-CQDs are also observed at 3435, 1630, and $1100\\mathrm{cm}^{-1}$ , respectively (Fig. 3f, Supplementary Fig. 38). The X-ray photoelectron spectroscopy (XPS) surveys further confirm the FT-IR data and demonstrate that the NBE-T-CQDs all have the same elemental composition (i.e. C and O) (Supplementary Fig. 39). The deconvoluted highresolution XPS spectra for C1s (Fig. 3g, Supplementary Fig. 40) and O1s (Supplementary Fig. 41) indicate that they contain the same $\\scriptstyle{\\mathrm{C=C}}$ and O-H chemical bonds. The similar structure and chemical compositions indicate that the optical properties of the NBE-T-CQDs are dominated by their sizes due to the quantum confinement effect18. \n\n![](images/7de3096f7855feb03d08c4b9c266806834954255336694fc52fdc79738f52101.jpg) \nFig. 3 Structural characterizations of the NBE-T-CQDs. a The typical aberration-corrected HAADF-STEM image of R-NBE-T-CQDs (the inset is the corresponding high-resolution image). b The wide-area TEM image of G-NBE-T-CQDs. Scale bar, $2{\\mathsf{n m}}$ . (The triangular projections are highlighted by white contour lines). XRD patterns (c) and FT-IR spectra $(\\pmb{\\uparrow})$ of NBE-T-CQDs. $^1\\mathsf{H}$ -NMR (d), $^{13}{\\mathsf C}$ -NMR (e), and C1s $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ spectra of B-NBE-T-CQDs \n\nTaken together, it is evident that under the given reaction conditions in tandem with the elaborate separation and purification, the as-prepared NBE-T-CQDs are highly crystalline and have a unique triangular structure functionalized with pure electron-donating hydroxyl groups at the edge sites. Significantly, the NBE-T-CQDs show almost no surface defects due to the highly crystalline structure and the absence of such electronwithdrawing oxygen-containing groups as carboxyl, carbonyl and epoxy groups, which could act as surface defects and trap sites usually observed in conventional CQDs. The sharply reduced electron–phonon coupling confirmed by detailed optical characterizations coupled with the absence of surface defects due to the unique triangular structure of the NBE-T-CQDs yield the strong high color-purity excitonic emission27–33. \n\nTheoretical investigation. Our proposal that the unique highly crystalline triangular structure functionalized with pure electrondonating hydroxyl groups at the edge sites are responsible for the high color-purity excitonic emission of the NBE-T-CQDs was further confirmed by DFT theory calculations. The optical properties of different kinds of model CQDs with triangular structure consisting of 4, 10, and 19 fused benzene rings functionalized with electron-donating hydroxyl groups (T-CQDsOH) (Fig. 4a, e, i) or electron-withdrawing carboxyl groups (T-CQDs-COOH) (Fig. 4c, g, k) or without functionalization (T-CQDs) (Fig. 4b, f, j) as well as the square-like structure consisting of 4, 10, and 20 fused benzene rings (S-CQDs) (Fig. 4d, h, l) were all calculated for comparison (Supplementary Fig. 42-45, Supplementary Table 2-14)51. Remarkably, the T-CQDs-OH and T-CQDs show distinct charge delocalization and optical properties compared with T-CQDs-COOH and S-CQDs. The degree of delocalization of the HOMO and LUMO can be qualitatively judged, for instance, by their corresponding electron cloud density distributions around the whole molecular structure. In this sense, a more uniformly distributed electron cloud density would indicate a higher degree of delocalization. Clearly, the calculated electron cloud densities of HOMO and LUMO for both T-CQDsOH and T-CQDs are more uniformly distributed across the whole molecular structure than those for T-CQDs-COOH and SCQDs (Fig. $\\scriptstyle4\\mathrm{m-X},$ , Supplementary Fig. 46-52). Therefore, it can be reasonably concluded that the HOMOs and LUMOs of T-CQDsOH and T-CQDs show higher degrees of delocalization than those of T-CQDs-COOH and S-CQDs. For the optical properties of different kinds of model CQDs, apart from the differences in the emission peaks and energy levels such as the HOMO, LUMO, and bandgap energies (Fig. $\\scriptstyle4\\mathrm{m-X},$ Supplementary Fig. 46-52), the FWHM of the PL spectra of T-CQDs-OH is slightly smaller than that of T-CQDs, but much smaller than those of T-CQDs-COOH and S-CQDs. At the fundamental level, it stands as a universal law that the T-CQDs-OH and T-CQDs show much higher colorpurity emission than T-CQDs-COOH and S-CQDs, which is observed by all these different kinds of model CQDs consisting of different number of fused benzene rings (Supplementary Fig. 53- 56). Take for example, the PL spectra of T-CQDs-OH-3 consisting of 19 fused benzene rings shows a narrow FWHM of 64 nm (Fig. 4o), which is slightly smaller than that of T-CQDs-3 (FWHM: $73\\mathrm{nm}\\mathrm{.}$ ) (Fig. 4r), but is even smaller than half of the FWHM of the PL spectra of T-CQDs-COOH-3 (FWHM: 135 nm) (Fig. 4u) and S-CQDs-3 (FWHM: $149\\mathrm{nm}$ ) (Fig. 4x). More significantly, the increased thermodynamic stability of T-CQDsOH compared with T-CQDs and S-CQDs are also demonstrated by theoretical calculations (Supplementary Table 15), which directly show the outstanding structural stability of T-CQDs-OH. These elaborately designed theoretical calculations demonstrate that the triangular structure and electron-donating hydroxyl groups play significant roles in determining the high color-purity of the NBE-T-CQDs which can be explained in detail as follows: first, the higher degree of delocalization leads to higher structural stability of the unique triangular structure of the NBE-T-CQDs, which in turn results in dramatically reduced electron–phonon coupling. This contributes to the high color-purity excitonic emission and narrow FWHM of PL spectra of NBE-T-CQDs as demonstrated by the temperature-dependent PL spectra. Second, the pure electron-donating hydroxyl groups at the edge sites of the NBE-T-CQDs can also greatly increase the $\\pi$ electron cloud density and facilitate the pure radiative recombination of confined electrons and holes. On the contrary, the electronwithdrawing carboxyl groups on $\\mathsf{s p}^{2}$ -hybridized carbons can induce significant local distortions as well as acting as surface defects simultaneously, which could trap carriers and finally result in dramatically increased FWHM of the PL spectra of CQDs (Fig. 4s–u, Supplementary Fig. 54, 56). Summarizing the above, the theoretical investigation demonstrates that the unique highly crystalline triangular structure functionalized with pure electron-donating hydroxyl groups at the edge sites show highly delocalized charges, outstanding structural stability, and thus dramatically reduced electron–phonon coupling, which are responsible for the high color-purity excitonic emission of the NBE-T-CQDs. \n\n![](images/fb05df60cdb5826900ed448c7f9686dd8b550c8378465ee06b3fc17d7ff45633.jpg) \nFig. 4 Time-dependent DFT calculation results. The triangular structure model CQDs consisting of 4, 10, and 19 fused benzene rings: (1) functionalized with pure electron-donating hydroxyl groups (T-CQDs-OH-1 (a), T-CQDs-OH-2 (e), T-CQDs-OH-3 (i)), (2) without functionalization (T-CQDs-1 (b), T-CQDs2 (f), T-CQDs-3 (j)), (3) functionalized with pure electron-withdrawing carboxyl groups (T-CQDs-COOH-1 (c), T-CQDs-COOH-2 ${\\bf\\Pi}({\\bf g})$ , T-CQDs-COOH-3 $(\\pmb{\\upkappa});$ . The square-like structure model CQDs without functionalization consisting of 4 (S-CQDs-1 (d)), 10 (S-CQDs-2 $\\mathbf{\\eta}(\\mathbf{h})$ ) and 20 (S-CQDs-3 (l)) fused benzene rings. The calculated HOMO $(\\mathbf{m},\\mathbf{\\nabla\\mathsf{p}},\\{\\mathsf{s},\\mathbf{\\nabla\\mathsf{u}}\\}$ , LUMO (n, $\\mathbf{q},\\mathbf{t},\\mathbf{w})$ , and $P L$ spectra $(\\bullet,\\pmb{\\mathsf{r}},\\{\\pmb{\\mathsf{u}},\\{\\pmb{\\mathsf{x}}\\}$ of T-CQDs-OH-3, T-CQDs-3, T-CQDs-COOH-3, and SCQDs-3, respectively \n\n![](images/0275a256feaca5147936a21bcbe94ea25eae1995ea3214a17879f8b559343937.jpg) \nFig. 5 LED structure, energy diagram, and performance characterization. The device structure (a) and energy level diagram (b) of the NBE-T-CQDs-based LEDs. EL spectra of the B- (c), $G-$ (d), Y- (e), and R-LEDs $\\mathbf{\\eta}(\\bullet)$ at different bias voltage, respectively. (Insets are the operation photographs of the B-, G-, Y-, and R-LEDs with the logo of BNU). The maximum luminance–current–voltage $(L-1-V)$ characteristic of B- $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ , G- (h), Y- (i), and R-LEDs $(\\mathbf{j})$ , respectively. The current efficiency versus current density ${\\bf\\Pi}({\\bf k})$ and the stability plots (l) of the B-, G-, Y-, and R-LEDs \n\nLED performance. The bright and high color-purity excitonic emission of the NBE-T-CQDs has prompted us to exploit their applications in LEDs for the development of next-generation display technology. A conventional simple structure was used for fabrication of the LEDs from blue to red with the NBE-T-CQDs blended poly $\\mathrm{~N~}$ -vinyl carbazole) (PVK) as the active emission layer, as shown in Fig. 5a. PVK was selected as host material due to its excellent hole transporting properties as well as favorable film forming properties52. Atomic force microscopy (AFM) measurements show that the NBE-T-CQDs blended PVK film has a smooth and uniform surface coverage with small rootmean-square (rms) roughness in the range of $1.31\\mathrm{-}1.80\\mathrm{nm}$ (Supplementary Fig. 57). The QY of B-, G-, Y-, and R-NBE-TCQDs blended PVK films were determined to be about 56, 62, 48, and $42\\%$ , respectively. The device structure consists of, from the bottom up, a ITO glass substrate anode, a poly(3,4-ethylenedioxythiophene): poly(styrene-sulfonate) (PEDOT:PSS) hole injection layer (HIL), an active NBE-T-CQDs:PVK blended emission layer, a 1,3,5-tris $N$ -phenylbenzimidazol-2-yl) benzene (TPBI) electron transport layer (ETL), and a Ca/Al doublelayered cathode. The thickness of PEDOT:PSS, PVK:NBE-TCQDs, and TPBI layers in LED devices are determined to be about 24 to 28, 19 to 22, and 30 to $32\\mathrm{nm}$ , respectively, as confirmed by the cross-sectional TEM images and the EDX maps of LED devices (Supplementary Fig. 58-59). As observed in the energy level diagram of the NBE-T-CQDs-based LEDs shown in Fig. 5b, the HOMO and LUMO energy levels of NBE-T-CQDs are located within those of the PVK, and have a small energy barrier for charge injection from both electrodes to the PVK host52. Then, the electrons and holes can be efficiently transferred from PVK to NBE-T-CQDs emitter in the active layer. The transferred electrons and holes can undergo radiative recombination in the NBE-T-CQDs, giving rise to the electroluminescence (EL) 52. \n\nThe EL spectra of the NBE-T-CQDs-based LEDs are presented in Fig. 5c–f. They exhibit peak wavelengths at 476, 510, 540, and $602{\\mathrm{nm}}$ , respectively, and are in good agreement with the PL emission peaks measured in the solution, indicating the excellent dispersion of the NBE-T-CQDs in the host material of PVK (Supplementary Fig. 60-61). More significantly, the NBE-TCQDs-based LEDs show high color-purity EL emission with narrow FWHM of 30, 32, 38, and $39\\mathrm{nm}$ for the B-, G-, Y-, and RLEDs, respectively, which is even comparable to the welldeveloped high color-purity inorganic QDs-based LEDs53,54. The operation photographs with Beijing Normal University (BNU) logo (insets of Fig. 5c–f, Supplementary Fig. 61) display the close-up view of the bright, uniform and defect-free surface high color-purity EL emission from blue, green, yellow, to red of the NBE-T-CQDs-based LEDs. The apparently voltageindependent emission color (Fig. 5c–f) indicates the high colorstability of the LEDs, which is of great significance for display technology. To the best of our knowledge, this is the first report for the fabrication of high color-purity CQDs-based LEDs (FWHM ${<}40\\mathrm{nm}\\backslash$ ) with stable emission color from blue to red with the NBE-T-CQDs blended PVK as active emission layer. \n\n
Table 1 The performances of high color-purity NBE-T-CQDs- based LEDs from blue to red
LEDsPL/FWHM (nm)EL/FWHM (nm)Von(V)Lmax (cd m-2)nc (cd A-1)
B-LEDs472/30476/304.318821.22
G-LEDs507/29510/323.747625.11
Y-LEDs538/30540/383.527842.31
R-LEDs598/30602/393.123441.73
\n\nThe typical luminance and current density curves as a function of applied voltage for the NBE-T-CQDs-based LEDs are shown in Fig. 5g-j and Supplementary Fig. 62. The performances of the LEDs are summarized in Table 1. The $V_{\\mathrm{on}},$ defined as the bias voltage applied to a LEDs producing a brightness of $1{\\mathrm{cd}}\\mathrm{m}^{-2}$ , decreased from 4.3 to $3.1\\mathrm{V}$ for the LEDs from blue to red, which are much lower than the previous reported CQDs-based $\\mathrm{LEDs}^{18,52}$ due to the maching energy levels of the related materials (Fig. 5b). The $L_{\\mathrm{max}}$ and $\\eta_{\\mathrm{c}}$ reach about $4762{\\ c d}\\mathrm{m}^{-2}$ and $5.1\\mathrm{cd}\\mathrm{A}^{-1}$ for green LEDs (G-LEDs) (Fig. 5h, k), respectively, which are the best performance ever reported for the CQDs-based LEDs, and is about 50 and 110 times higher than our previous reported G-LEDs which directly used bandgap fluorescent CQDs as the active emission layer without using the PVK host18. Other colored high color-purity LEDs based on the NBE-T-CQDs fabricated with the same device structure also show highperformance with $L_{\\mathrm{max}}$ reaching 1882, 2784, and $2344\\csc\\mathrm{d}\\mathrm{m}^{-2}$ for the B-, Y-, and R-LEDs coupled with corresponding $\\eta_{\\mathrm{c}}$ of 1.22, 2.31, and $1.73\\mathrm{cd}\\mathrm{A}^{-1}$ (Fig. 5g, i–k, Supplementary Fig. 63), respectively, which are to some extent comparable to the QDsbased LEDs (Supplementary Table 16). Compared with the NBET-CQDs-based LEDs fabricated without using the PVK polymer host, the one with PVK exhibited greatly improved $L_{\\mathrm{max}}$ and $\\eta_{\\mathrm{c}}$ by 12 to 25 and 17 to 28 times, respectively, as shown in Supplementary Table 17. Besides the bright fluorescence inherent to the NBE-T-CQDs, the hole-transport PVK polymer as a host material also contributed to the remarkable performance of our LEDs due to the resulting optimized charge balance in the emission layer. As an ultrastable feature of the fluorescence of the NBE-T-CQDs, the high color-purity NBE-T-CQDs-based LEDs exhibit outstanding ambient stability. After operation for $40\\mathrm{{h}}$ , more than $85\\%$ of initial luminance $\\dot{(L_{0};500\\ c d\\ m^{-2})}$ are retained (Fig. 5l) without degradation of the high color-purity (Supplementary Fig. 64). Moreover, the LEDs also show high stability at extremely high voltage, further demonstrating the great potential applications of the NBE-T-CQDs-based LEDs for the development of next-generation display technology (Supplementary Fig. 65). \n\n# Discussion \n\nWe report the subversive demonstration of high color-purity NBE-T-CQDs (FWHM of $29-30~\\mathrm{nm}$ ) from blue to red with a QY up to $54\\mathrm{-}72\\%$ . The NBE-T-CQDs were prepared by facilely controlling the fusion and carbonization of three-fold symmetric PG triangulogen which possesses a unique structure with three highly reactive hydrogen atoms at the three meta-positions activated by three electron-donating hydroxyl groups in a single molecule. Detailed structural and optical characterizations together with elaborate theoretical calculations revealed that the unique rigid triangular structure, molecular purity, crystalline perfection and most importantly, the resulting weak electron–phonon interaction of the NBE-T-CQDs surrounded by hydroxy groups are the key points to the high color-purity. The multicolored LEDs based on the NBE-T-CQDs demonstrated high color-purity (FWHM of $30{-}39~\\mathrm{nm},$ , a $L_{\\mathrm{max}}$ of 1882–4762 cd $\\mathrm{m}^{-2}$ and $\\eta_{\\mathrm{c}}$ of 1.22–5.11 cd $\\mathrm{A}^{-1}$ , rivaling the well-developed inorganic QDs-based LEDs. Moreover, the LEDs demonstrate outstanding stability. We anticipate that this work will inspire further research on and more optimizations of the charge injection (holes and electrons) as well as better designed devices, leading to a greatly improved performance for the high colorpurity NBE-T-CQDs-based LEDs ideal for next-generation display technology. Detailed follow-up work along this line is underway in our laboratory. \n\n# Methods \n\nSynthesis of high color-purity NBE-T-CQDs. The highly tunable and high colorpurity NBE-T-CQDs from blue to red can be synthesized by solvothermal treatment or refluxing of phloroglucinol (PG) in various common solvents. In a typical preparation procedure for the synthesis of blue and green NBE-T-CQDs: PG (500 mg) was dissolved in ethanol $(10\\mathrm{mL})$ . The clear precursor solution after $10\\mathrm{min}$ ultrasonic dissolving was then transferred to a poly(tetrafluoroethylene) (Teflon)- lined autoclave $(25\\mathrm{mL}$ ) and heated at $200^{\\circ}\\mathrm{C}$ for 9 and $24\\mathrm{h}$ After the reaction, the reactors were cooled to room temperature by water or naturally. For yellow and red NBE-T-CQDs: PG $(500\\mathrm{mg})$ was dissolved in ethanol $(10\\mathrm{mL})$ , followed by adding concentrated hydrochloric acid or sulfuric acid $(2\\mathrm{mL})$ as catalyst. The clear precursor solution was then transferred to a poly(tetrafluoroethylene) (Teflon)-lined autoclave $(25\\mathrm{mL})$ and heated at $200^{\\circ}\\mathrm{C}$ for 2 and $^{5\\mathrm{h}}$ . After the reaction, the reactors were cooled to room temperature by water or naturally, the hydrochloric acid was removed by direct heating of the solution for $30\\mathrm{min}$ , or the solution was neutralized by sodium hydroxide and the supernatant was collected by centrifugation. The solvent ethanol for the synthesis of NBE-T-CQDs can also be changed to various other common solvents such as formamide, N, N-dimethyl formamide, water, and so on. In addition, refluxing of PG in various common solvents such as ethanol, formamide, N, $N$ -dimethyl formamide can also produce tunable fluorescent NBE-T-CQDs through optimization of reaction conditions. For example, the red NBE-T-CQDs can be prepared by refluxing of PG in ethanol with concentrated hydrochloric acid or sulfuric acid as catalyst. The green and yellow NBE-T-CQDs can be prepared by refluxing of PG in $N$ N-dimethyl formamide and formamide with small amount of concentrated hydrochloric acid as catalyst. The NBE-T-CQDs are purified via silica column chromatography using a mixture of dichloromethane and methanol as the eluent. During the silica column chromatography purification process, the polarity of eluent should be changed dynamically by changing the volume ratio of dichloromethane to methanol in order to ensure the effectiveness of the separation and purification process. Specifically, the volume ratio was dynamically changed during the silica column chromatography purification process from 6:1 to 2:1 (blue NBE-T-CQDs), 10:1 to 4:1 (green NBET-CQDs), 16:1 to 8:1 (green NBE-T-CQDs), and 25:1 to 10:1 (red NBE-T-CQDs). Typically, the silica column chromatography purification process should be repeated several times in order to obtain pure NBE-T-CQDs. \n\nQuantum yield measurements. An absolute method, using Varian FLR025 spectrometer equipped with a $120\\mathrm{mm}$ integrating sphere, was employed to determine the QY of NBE-T-CQDs. We conducted the test light from FLR025 spectrometer to the sphere. The QY was determined by the ratio between photons emitted and absorbed by NBE-T-CQDs. The ethanol solution was placed in a UV quarts cuvette with a light path of $10\\mathrm{mm}$ to measure its QY, while the solvent ethanol filled in the quarts cuvette was used as a blank sample for the reference measurement. The spectral correction curve which relates to the sensitivity of the monochromator, detector, sphere coating, and optics to wavelength was provided by Edinburgh Instruments. \n\nFemtosecond transient absorption setup. A regeneratively amplified Ti:sapphire laser system (Coherent Libra, 50 fs, $1\\mathrm{kHz}$ ) provides the fundamental light source. The pump pulse $\\scriptstyle\\left(400\\mathrm{nm}\\right)$ is generated by focusing a portion of fundamental light into BBO crystal. In order to avoid the influence of rotational relaxation effects on dynamics, the polarization of pump pulse is randomized by depolarizing plate. The other fundamental pulse provides broadband probe pulse (white light continuum) that is produced by focusing ${800}\\mathrm{nm}$ fundamental light into sapphire plate ( $3\\mathrm{mm}^{\\cdot}$ . The pump and probe beams are overlapped in the sample with crossing areas of 600 and $150\\upmu\\mathrm{m}$ . After passing through the sample, the probe pulse is focused into optical fiber that is coupled to spectrometer (AvaSpec-1650F). The energy of 400 nm excitation pulse is adjusted to about $1\\upmu\\mathrm{J}$ per pulse by a neutral density optical filter. The pump pulse is chopped at ${500}\\mathrm{Hz}$ to acquire pumped (signal) and unpumped (reference) probe spectra, and the ΔOD spectrum can be obtained by \n\nprocessing them. The solutions are placed in $2\\mathrm{mm}$ optical path length quartz cuvette. Both the instrument response function (100 fs) and temporal chirp in the probe light are determined by measuring the cross modulation of solvent. The group velocity dispersion effect is corrected by home-made chirp program. For each measurement, the pump-probe delay scan is repeated three times to give the averaged experiment data. \n\nUltraviolet photoelectron spectroscopy measurement. UPS measurement was performed with an $\\mathrm{h}\\mathbf{v}=21.22\\mathrm{eV}$ , He I source (AXIS ULTRA DLD, Kratos). The analysis room vacuum was $3.0\\times10^{-8}$ Torr, and the bias voltage for measurement was $-9\\mathrm{V}$ . The NBE-T-CQDs thin films were prepared from spin-coating on ITO substrates for UPS measurement. \n\nCharacterization method. A JEOL JEM 2100 transmission electron microscope (TEM) was used to investigate the morphologies of the NBE-T-CQDs. X-ray diffraction (XRD) patterns were carried out by an X-ray diffraction using Cu-Ka radiation (XRD, PANalytical X’Pert Pro MPD). Absorption spectra were recorded on UV-2450 spectrophotometry. The fluorescence spectra of NBE-T-CQDs were measured on a PerkinElmer-LS55 luminescence spectrometer with slit width at $2.5\\mathrm{-}2.5\\mathrm{nm}$ . The photographs were taken with camera (Nikon, D7200) under UV light excited at $365\\mathrm{nm}$ (UV light: SPECTROLINE, ENF-280C/FBE, 8 W). The FTIR spectra were measured using a Nicolet 380 spectrograph. X-ray photoelectron spectroscopy (XPS) was performed with an ESCALab220i-XL electron spectrometer from VG Scientific using 300 W Al Ka radiation. The Raman spectrum was measured using Laser Confocal Micro-Raman Spectroscopy (LabRAM Aramis). Lowtemperature-dependent PL spectra measurements were performed in the temperature range of 85–295 K using a liquid nitrogen cooler. The TPF spectra of NBET-CQDs ethanol solution placed in the $1\\mathrm{cm}$ fluorescence cuvette were recorded on the fiber spectrometer (Ocean Optics USB2000 CCD) with a Ti:sapphire femtosecond laser (Spitfire, Spectra-Physics, 100 fs, $80\\mathrm{MHz}$ , $880\\mathrm{nm}$ ) for excitation. \n\nSTEM-HAADF images characterization. A JEM-ARM200F transmission electron microscope (TEM) was used to investigate the STEM-HAADF images of the NBET-CQDs. Ultrathin carbon film supported by a lacey on a 400 mesh copper grid (product no. 01824, bought from Beijing Xinxing Braim Technology Co., Ltd) was used to disperse the NBE-T-CQDs. The purified diluted NBE-T-CQDs ethanol solution with ${5\\upmu\\mathrm{L}}$ was dropped on the surface of ultrathin carbon film, and then dried at room temperature. Finally, the STEM-HAADF images of NBE-T-CQDs samples were measured at $200\\mathrm{KV}$ . \n\nTheoretical calculations. All the optical properties of different kinds of model CQDs were calculated using time-dependent density functional theory (TDDFT) method as implemented in the Gaussian09 software package. The 6-311G(d) basis set was selected to combine with the functional B3LYP throughout all calculations (B3LYP/6-311G(d)). The first excited state was optimized in vacuum to calculate the emission energy (wavelength) which is the energy difference between the ground and the first excited state. The pink and violet colors in the HOMO and LUMO molecular orbitals represent the positive and negative phases of the molecular orbital wavefunctions. \n\nDevice fabrication and characterization. Indium-tin-oxide (ITO)-coated glass substrates was cleaned ultrasonically in organic solvents (acetone and isopropyl alcohol), rinsed in deionized water, and then dried in an oven at $150^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . The substrates were cleaned with a UV-ozone treatment to enrich the ITO surface with oxygen to increase the ITO work function. The poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS) hole injection layer (HIL) was spin-coated at $2000\\mathrm{rpm}$ for $35s$ on the ITO with a thickness of about $30\\mathrm{nm}$ , followed by annealing in an oven at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ . Subsequently, the emissive layer of NBE-T-CQDs blended poly(N-vinyl carbazole) (PVK) was spin-coated at $3000\\mathrm{rpm}$ for $45\\mathrm{~s~}$ over the surface of PEDOT:PSS film from the mixed solution of $o$ -dichlorobenzene and ethanol solution, followed by baking on a hot plate at $80^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ to form the active region of the NBE-T-CQDs-based monochrome LEDs. Finally, the substrates were transferred to a vacuum chamber and a $30\\mathrm{nm}$ thick 1,3,5-tris(N-phenylbenzimidazol-2-yl) benzene (TPBI) electron transport layer (ETL) was thermally deposited with base pressure of $3\\times10^{-4}\\mathrm{Pa}$ . After that, a $20\\mathrm{nm}\\mathrm{Ca}$ and $100\\mathrm{nm}$ thick Al cathode was deposited using a shadow mask with 2 mm width. The active area of the devices was thus $4\\mathrm{mm}^{2}$ . The thermal deposition rates for TPBI and $\\mathrm{Ca}/\\mathrm{Al}$ are 1, 1, and $3\\mathrm{\\AA}\\ s^{-1}$ , respectively. PEDOT:PSS was used as a buffer layer on the anode mainly to increase the anode work function from 4.7 (ITO) to $5.0\\mathrm{eV}$ and to reduce the surface roughness of the anode to obtain stable and pinhole-free electrical conduction across the device. TPBI was chosen as the ETL because of its good electron transport capability and its interfacial phase compatibility with the active emission layer. The thickness of films was measured using a Dektak XT (Bruker) surface profilometer and a spectroscopic ellipsometer (Suntech). The luminance–current–voltage (L–I–V) characteristics were measured using a computer-controlled Keithley 236 SMU and Keithley 200 multimeter coupled with a calibrated Si photodiode. Electroluminescence (EL) spectra were measured by an Ocean Optics 2000 spectrometer, which couples a linear chargecoupled device (CCD)-array detector ranging from 350 to $1100\\mathrm{nm}$ . \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request \n\nReceived: 3 January 2018 Accepted: 9 May 2018 \nPublished online: O8 June 2018 \n\n# References \n\nLim, S. Y., Shen, W. & Gao, Z. Q. Carbon quantum dots and their applications. Chem. Soc. Rev. 44, 362–381 (2015). \n2. Ding, C., Zhu, A. W. & Tian, Y. Functional surface engineering of C-Dots for fluorescent biosensing and in vivo bioimaging. Acc. Chem. Res. 47, 20–30 (2014). \n3. Yuan, F. L. et al. Shining carbon dots: synthesis and biomedical and optoelectronic applications. Nano Today 11, 565–586 (2016). \n4. Liu, J. et al. Metal-free efficient photocatalyst for stable visible water splitting via a two-electron pathway. Science 347, 970–974 (2015). \n5. Hola, K. et al. Carbon dots-emerging light emitters for bioimaging, cancer therapy and optoelectronics. Nano Today 9, 590–603 (2014). \n6. Choi, H. et al. Versatile surface plasmon resonance of carbon-dot-supported silver nanoparticles in polymer optoelectronic devices. Nat. Photonics 7, 732–738 (2013). \n7. Wang, L. et al. Gram-scale synthesis of single-crystalline graphene quantum dots with superior optical properties. Nat. Commun. 5, 5357 (2014). \n8. Sun, Y.-P. et al. Quantum-sized carbon dots for bright and colorful photoluminescence. J. Am. Chem. Soc. 128, 7756–7757 (2006). Zhang, M. et al. Facile synthesis of water-soluble, highly fluorescent graphene quantum dots as a robust biological label for stem cells. J. Mater. Chem. 22, 7461–7467 (2012). \n10. Yuan, F. L. et al. Multicolor fluorescent graphene quantum dots colorimetrically responsive to all-pH and a wide temperature range. Nanoscale 7, 11727–11733 (2015). \n11. Fan, Z. T. et al. pH-Responsive fluorescent graphene quantum dots for fluorescence-guided cancer surgery and diagnosis. Nanoscale 9, 4928–4933 (2017). \n12. Hutton, G. A. M. et al. Carbon dots as versatile photosensitizers for solardriven catalysis with redox enzymes. J. Am. Chem. Soc. 138, 16722–16730 (2016). \n13. Jiang, K. et al. Triple-mode emission of carbon dots: applications for advanced anti-counterfeiting. Angew. Chem. Int. Ed. 55, 7231–7235 (2016). \n14. Martindale, B. C. M., Joliat, E., Bachmann, C., Alberto, R. & Reisner, E. Clean donor oxidation enhances the H-2 evolution activity of a carbon quantum dot-molecular catalyst photosystem. Angew. Chem. Int. Ed. 55, 9402–9406 (2016). \n15. Wang, Z. F. et al. $53\\%$ efficient red emissive carbon quantum dots for high color rendering and stable warm white-light-emitting diodes. Adv. Mater. 29, 1702910 (2017). \n16. Jiang, K. et al. Red, green, and blue luminescence by carbon dots: full-color emission tuning and multicolor cellular imaging. Angew. Chem. Int. Ed. 54, 5360–5363 (2015). \n17. Qu, S. N. et al. Toward efficient orange emissive carbon nanodots through conjugated $\\mathsf{s p}^{2}$ -domain controlling and surface charges engineering. Adv. Mater. 28, 3516–3521 (2016). \n18. Yuan, F. L. et al. Bright multicolor bandgap fluorescent carbon quantum dots for electroluminescent light-emitting diodes. Adv. Mater. 29, 1604436 (2017). \n19. Zhu, Z. et al. Efficiency enhancement of perovskite solar cells through fast electron extraction: the role of graphene quantum dots. J. Am. Chem. Soc. 136, 3760–3763 (2014). \n20. Ye, K.-H. et al. Carbon quantum dots as a visible light sensitizer to significantly increase the solar water splitting performance of bismuth vanadate photoanodes. Energy Environ. Sci. 5, 772–779 (2017). \n21. Tang, Q. W., Zhu, W. L., He, B. L. & Yang, P. Z. Rapid conversion from carbohydrates to large-scale carbon quantum dots for all-weather solar cells. ACS Nano 11, 1540–1547 (2017). \n22. Li, H. et al. Carbon quantum dots/TiOx electron transport layer boosts efficiency of planar heterojunction perovskite solar cells to 19. Nano Lett. 17, 2328–2335 (2017). \n23. Lu, S. Y. et al. Near-infrared photoluminescent polymer-carbon nanodots with two-photon fluorescence. Adv. Mater. 29, 1603443 (2017). \n24. Dai, X. L. et al. Solution-processed, high-performance light-emitting diodes based on quantum dots. Science 515, 96–99 (2014). \n25. Li, G. G. & Lin, J. Recent progress in low-voltage cathodoluminescent materials: synthesis, improvement and emission properties. Chem. Soc. Rev. 43, 7099–7131 (2014). \n26. Li, H., Yu, S. B., Wei, J. S. & Xiong, H. M. Full-color light-emitting carbon dots with a surface-state-controlled luminescence mechanism. ACS Nano 10, 484–491 (2016). \n27. Cortecchia, D. et al. Broadband emission in two-dimensional hybrid perovskites: the role of structural deformation. J. Am. Chem. Soc. 139, 39–42 (2017). \n28. Emma, R. D., Jaffe, A., Bradshaw, L. R. & Karunadasa, H. I. Intrinsic whitelight emission from layered hybrid perovskites. J. Am. Chem. Soc. 136, 13154–13157 (2014). \n29. Yuan, Z. et al. One-dimensional organic lead halide perovskites with efficient bluish white-light emission. Nat. Commun. 8, 14051 (2017). \n30. Khan, S., Gupta, A., Verma, N. C. & Nandi, C. K. Time-resolved emission reveals ensemble of emissive states as the origin of multicolor fluorescence in carbon dots. Nano Lett. 15, 8300–8305 (2015). \n31. Bao, L., Liu, C., Zhang, Z. L. & Pang, D. W. Photoluminescence-tunable carbon nanodots: surface-state energy-gap tuning. Adv. Mater. 27, 1663–1667 (2015). \n32. Pan, L. L. et al. Truly fluorescent excitation-dependent carbon dots and their applications in multicolor cellular imaging and multidimensional sensing. Adv. Mater. 27, 7782–7787 (2015). \n33. Hu, S. L., Trinchi, A., Atkin, P. & Cole, I. Tunable photoluminescence across the entire visible spectrum from carbon dots excited by white light. Angew. Chem. Int. Ed. 54, 2970–2974 (2015). \n34. Ozfidan, I. et al. Microscopic theory of the optical properties of colloidal graphene quantum dots. Phys. Rev. B 89, 085310 (2014). \n35. Sun, C. et al. Biexciton binding of dirac fermions confined in colloidal graphene quantum dots. Nano Lett. 15, 5472–5476 (2015). \n36. Povie, G., Segawa, Y., Nishihara, T., Miyauchi, Y. & Itami, K. Synthesis of a carbon nanobelt. Science 356, 172–175 (2017). \n37. Fleetham, T., Li, G. J. & Li, J. Phosphorescent Pt(II) and Pd(II) complexes for efficient, high-color-quality, and stable OLEDs. Adv. Mater. 29, 1601861 (2017). \n38. Xu, Y. Q. et al. Two-photon-pumped perovskite semiconductor nanocrystal lasers. J. Am. Chem. Soc. 138, 3761–3768 (2016). \n39. George, P. A. et al. Ultrafast optical-pump terahertz-probe spectroscopy of the carrier relaxation and recombination dynamics in epitaxial graphene. Nano Lett. 8, 4248–4251 (2008). \n40. Gao, B. et al. Studies of intrinsic hot phonon dynamics in suspended graphene by transient absorption microscopy. Nano Lett. 11, 3184–3189 (2011). \n41. Wen, X. M., Yu, P., Toh, Y. R., Hao, X. T. & Tang, J. Intrinsic and extrinsic fluorescence in carbon nanodots: ultrafast time-resolved fluorescence and carrier dynamics. Adv. Opt. Mater. 1, 173–178 (2013). \n42. Li, Q. et al. Silicon nanoparticles with surface nitrogen: $90\\%$ quantum yield with narrow luminescence bandwidth and the ligand structure based energy law. ACS Nano 10, 8385–8393 (2016). \n43. Sui, L. Z. et al. Ultrafast carrier dynamics of carbon nanodots in different pH environments. Phys. Chem. Chem. Phys. 18, 3838–3845 (2016). \n44. Adam, D. W. et al. Electron-phonon coupling in hybrid lead halide perovskites. Nat. Commun. 7, 11755 (2016). \n45. Balan, A. D. et al. Effect of thermal fluctuations on the radiative rate in core/ shell quantum dots. Nano Lett. 17, 1629–1636 (2017). \n46. Villegas, C. E. P., Rocha, A. R. & Marini, A. Anomalous temperature dependence of the band gap in black phosphorus. Nano Lett. 16, 5095–5101 (2016). \n47. Wang, Y. et al. Blue liquid lasers from solution of $\\mathrm{CdZnS/ZnS}$ ternary alloy quantum dots with quasi-continuous pumping. Adv. Mater. 27, 169–175 (2015). \n48. Elward, J. M. & Chakraborty, A. Effect of dot size on exciton binding energy and electron−hole recombination probability in CdSe quantum dots. J. Chem. Theory Comput. 9, 4351–4359 (2013). \n49. Manser, J. S., Christians, J. A. & Kamat, P. V. Intriguing optoelectronic properties of metal halide perovskites. Chem. Rev. 116, 12956–13008 (2016). \n50. Arcudi, F., Dordevic, L. & Prato, M. Synthesis, separation, and characterization of small and highly fluorescent nitrogen-doped carbon nanodots. Angew. Chem. Int. Ed. 55, 2107–2112 (2016). \n51. Güçlü, A. D., Potasz, P., Korkusinski, M. & Hawrylak, P. Graphene Quantum Dots (Springer Verlag, 2014). \n52. Kim, J. K. et al. Origin of white electroluminescence in graphene quantum dots embedded host/guest polymer light emitting diodes. Sci. Rep. 5, 11032 (2015). \n53. Dai, X. L., Deng, Y. Z., Peng, X. G. & Jin, Y. Z. Quantum-dot light-emitting diodes for large-area displays: towards the dawn of commercialization. Adv. Mater. 29, 1607022 (2017). \n54. Sun, Q. J. et al. Bright multicolored light-emitting diodes based on quantum dots. Nat. Photonics 1, 717–722 (2007). \n\n# Acknowledgements \n\nThis work is supported by NSFC of China (21573019), the Major Research Plan of NSFC (21233003), Shenzhen Peacock Plan Program (KQTD2016053015544057), NSFC of China (11674124), National Basic Research Program of China (973 Program, Grant No. 2013CB922200), and the Fundamental Research Funds for the Central Universities. \n\n# Author contributions \n\nL.F. and F.Y. had the idea for and designed the experiments. L.F., Z.T., and S.Y. supervised the work. F.Y. conducted the synthesis and characterization of NBE-T-CQDs. Z.X. conducted the NMR characterization of NBE-T-CQDs. T.Y. participated in the purification of NBE-T-CQDs. T.Y. performed the theoretical calculations. L.S. measured the femtosecond transient absorption spectroscopy. L.S., F.Y., M.J., and A.C. analyzed the femtosecond transient absorption date. F.Y. carried out the LED device fabrication and characterizations. Z.T., and Z.W. participated in the LED device structure designation, fabrication, and characterizations. F.Y. wrote the first draft of the manuscript. L.F., Z.T. and S.Y. participated in data analysis and provided major revisions. All authors discussed the results and contributed to the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-04635-5. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1038_s41929-017-0018-9", + "DOI": "10.1038/s41929-017-0018-9", + "DOI Link": "http://dx.doi.org/10.1038/s41929-017-0018-9", + "Relative Dir Path": "mds/10.1038_s41929-017-0018-9", + "Article Title": "Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction", + "Authors": "De Luna, P; Quintero-Bermudez, R; Dinh, CT; Ross, MB; Bushuyev, OS; Todorovic, P; Regier, T; Kelley, SO; Yang, PD; Sargent, EH", + "Source Title": "NATURE CATALYSIS", + "Abstract": "The reduction of carbon dioxide to renewable fuels and feedstocks offers opportunities for large-scale, long-term energy storage. The synthesis of efficient CO2 reduction electrocatalysts with high C2:C1 selectivity remains a field of intense interest. Here we present electro-redeposition, the dissolution and redeposition of copper from a sol-gel, to enhance copper catalysts in terms of their morphology, oxidation state and consequent performance. We utilized in situ soft X-ray absorption spectroscopy to track the oxidation state of copper under CO2 reduction conditions with time resolution. The sol-gel material slows the electrochemical reduction of copper, enabling control over nulloscale morphology and the stabilization of Cu+ at negative potentials. CO2 reduction experiments, in situ X-ray spectroscopy and density functional theory simulations revealed the beneficial interplay between sharp morphologies and Cu+ oxidation state. The catalyst exhibits a partial ethylene current density of 160 mA cm(-2) (-1.0 V versus reversible hydrogen electrode) and an ethylene/methane ratio of 200.", + "Times Cited, WoS Core": 799, + "Times Cited, All Databases": 839, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000428621500008", + "Markdown": "# Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction \n\nPhil De Luna $\\textcircled{10}1,2,3$ , Rafael Quintero-Bermudez4, Cao-Thang Dinh4, Michael B. Ross   2,3, Oleksandr S. Bushuyev4, Petar Todorović4, Tom Regier5, Shana O. Kelley6,7, Peidong Yang2,3,8,9,10,11 and Edward H. Sargent2,4\\* \n\nThe reduction of carbon dioxide to renewable fuels and feedstocks offers opportunities for large-scale, long-term energy storage. The synthesis of efficient $\\pmb{\\mathrm{co}}_{2}$ reduction electrocatalysts with high C2:C1 selectivity remains a field of intense interest. Here we present electro-redeposition, the dissolution and redeposition of copper from a sol–gel, to enhance copper catalysts in terms of their morphology, oxidation state and consequent performance. We utilized in situ soft X-ray absorption spectroscopy to track the oxidation state of copper under $\\pmb{\\mathrm{co}}_{2}$ reduction conditions with time resolution. The sol–gel material slows the electrochemical reduction of copper, enabling control over nanoscale morphology and the stabilization of ${\\pmb{\\mathsf{c}}}{\\pmb{\\mathsf{u}}}^{+}$ at negative potentials. $\\mathbf{co}_{2}$ reduction experiments, in situ X-ray spectroscopy and density functional theory simulations revealed the beneficial interplay between sharp morphologies and ${\\pmb{\\complement}}{\\pmb{\\ u}}^{+}$ oxidation state. The catalyst exhibits a partial ethylene current density of $\\mathbf{160mAcm^{-2}}$ (−​1.0 V versus reversible hydrogen electrode) and an ethylene/methane ratio of 200. \n\ns energy demand continues to increase, so too do anthropogenic carbon emissions and global temperatures. Renewable energy sources such as solar, wind and hydroelectricity displace fossil fuel carbon emissions and continue to progress to wider deployment. However, long-term (seasonal) energy storage remains a challenge that must be addressed for renewables to meet a major fraction of global energy demand1. Carbon dioxide electroreduction to renewable fuels and feedstocks provides an energy storage solution to the seasonal variability of renewable energy sources2. When coupled with carbon capture technology, the carbon dioxide reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ offers a means to close the carbon cycle. \n\n$\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalysts lower energetic barriers to $\\mathrm{CO}_{2}$ reduction by stabilizing intermediates and transition states in the multistep electrochemical reduction process3. Copper reduces $\\mathrm{CO}_{2}$ to a wide range of hydrocarbon products such as methane, ethylene, ethanol and propanol4. Unfortunately, bulk copper is not selective among various carbon products, and it also suffers Faradaic efficiency (FE) losses to the competing hydrogen evolution reaction. \n\nAmong possible products, $^{C2+}$ hydrocarbons are highly sought in view of their commercial value. Ethylene, for example, is a precursor to the production of polyethylene, a major plastic. Selectively producing ethylene over methane circumvents costly paraffin–olefin separation5. Developing catalysts that work at ambient conditions to produce C2 selectively over C1 gaseous products will increase the relevance of renewable feedstocks in the chemical sector. \n\nOxide-derived copper is one class of catalyst that has shown enhanced $\\mathbf{CO}_{2}\\mathrm{RR}$ activity and increased selectivity towards multi-carbon products6–8. The selectivity of these catalysts is dependent on structural morphology and copper oxidation state9–17. Electrochemical reduction of copper oxide catalyst films can lead to grain boundaries, undercoordinated sites and roughened surfaces that are hypothesized to be catalytically active sites8,18. Residual oxides, proposed to play a key role in catalysis, may exist after electrochemical reduction7. A recent report of oxygen plasma-activated oxide-derived copper catalysts achieved an ethylene FE of $60\\%$ at $-0.9\\mathrm{V}$ versus reversible hydrogen electrode $(\\mathrm{RHE})^{\\circ}$ , with activity attributed to the presence of $\\mathrm{Cu^{+}}$ species. In situ hard $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy (hXAS) experiments have suggested stable ${\\mathrm{Cu^{+}}}$ species exist at highly negative $\\mathrm{CO}_{2}\\mathrm{RR}$ potentials of ${\\sim}-1.0$ versus $\\mathrm{RHE^{9}}$ . However, the presence of $\\mathrm{Cu^{+}}$ species during $\\mathrm{CO}_{2}\\mathrm{RR}$ is still the subject of debate;7,19 and in situ tracking of the copper oxidation state with time resolution during $\\mathrm{CO}_{2}\\mathrm{RR}$ has remained elusive. \n\nMorphological effects of copper nanostructures have a significant effect on the selectivity of $\\mathrm{CO}_{2}\\mathrm{RR}$ to multi-carbon products20–24. Copper catalysts with different morphologies have been synthesized through annealing, chemical treatments on thin films, colloidal synthesis and electrodeposition from solution6,17,25,26. For example, recent work reported selective ethylene production on bromide-promoted copper dendrites with a maximum ethylene FE of $57\\%$ (ref. 26). The selectivity of this catalyst was attributed to the high-index facets and undercoordinated sites on the high-curvature structures26. Furthermore, high-curvature structures, such as nano­ needles, promote nucleation of smaller gas bubbles27, and benefit from field-induced reagent concentration28–32, where high local negative electric fields concentrate positively charged cations to help stabilize $\\mathrm{CO}_{2}$ reduction intermediates33, enhancing ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ However, combining high-curvature morphology with $\\mathrm{Cu^{+}}$ promotion to enable selective chemical conversion has yet to be explored. \n\n![](images/c7a02a328bd8763de9ae7fa7bd2738ba1cd90a883623127e4dd520a944e4845d.jpg) \nFig. 1 | Catalytic activity of ERD Cu catalysts. a, FEs of ERD Cu at a range of applied potentials showing all products. b, Current densities of the catalyst over 1 h of operation at different applied potentials. c, $C O_{2}R R$ gas product FEs. d, Plot of ethylene/methane ratio versus ethylene partial current density for a range of catalysts (for further details, see Supplementary Table 1). \n\nHere we report the electro-redeposition of copper from a sol– gel precursor. This process enables simultaneous control over morphology and oxidation state. Time-resolved tracking of the copper oxidation state under in situ $\\mathrm{CO}_{2}$ reduction conditions showed the presence of $\\mathrm{Cu^{+}}$ at highly negative potentials (less than $-1.0\\mathrm{V}$ versus RHE). Electro-redeposition exhibits simultaneous in situ dissolution and redeposition of copper from a sol–gel copper oxychloride, enabling a broad range of nanostructures of varying sharpness to be grown from within the bulk material itself. By using in situ soft X-ray absorption (sXAS) spectroscopy, we tracked over time the reduction of copper, revealing the ratio of copper species under different applied potentials. We find the transition from ${\\mathrm{Cu}}^{2+}$ to $\\mathrm{Cu^{+}}$ occurs rapidly (within $5\\mathrm{{min}}^{\\cdot}$ ) whereas the ${\\mathrm{Cu^{+}}}$ to ${\\mathrm{Cu}}^{0}$ transition is much slower. Surprisingly, $23\\%$ of the catalyst existed as $\\mathrm{Cu^{+}}$ species under a negative applied bias as low as $-1.2\\mathrm{V}$ versus RHE for over an hour of operation. The copper oxychloride sol– gel slowed the reduction kinetics of copper, stabilizing $\\mathrm{Cu^{+}}$ at more negative applied potentials. At $-1.2\\mathrm{V}$ versus RHE, the electroredeposited (ERD) copper catalyst exhibited a FE of $54\\%$ for $^{\\mathrm{C2+}}$ products (ethylene, acetate, ethanol) compared with a FE of $18\\%$ for C1 products (carbon monoxide, methane, formate). ERD copper displayed a high ethylene partial current density, within H-cell $(22\\mathrm{mA}\\mathrm{cm}^{-2}$ at $-1.2\\mathrm{V}$ versus RHE) and flow-cell ( $161\\mathrm{mAcm}^{-2}$ at $-1.0\\mathrm{V}$ versus RHE) configurations with significant methane suppression and a high ethylene/methane ratio of 200. Density functional theory (DFT) calculations revealed that the formation energy of the ethylene intermediate $(\\mathrm{OCCOH^{*}})$ is substantially lowered compared with the methane intermediate $(\\mathrm{COH^{*}})$ on a high-curvature surface with $\\mathrm{Cu^{+}}$ species. The in situ XAS and DFT studies, taken together, portray a catalyst in which stabilization of $\\mathrm{Cu^{+}}$ improves selectivity and high-curvature morphology improves activity of C2 production. \n\n# Results \n\nSynthesis and $\\mathbf{CO_{2}R R}$ activity of ERD Cu. We synthesized the sol– gel copper oxychloride $\\mathrm{(Cu_{2}(O H)_{3}C l)}$ precursor using an epoxide gelation approach to yield a polycrystalline porous material with amorphous regions34,35. Scanning electron microscopy (SEM) micrographs of the surface of $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}$ deposited on carbon paper revealed aggregated clusters with $10\\mathrm{nm}$ pores and micrometre void spaces consistent with previous sol–gel reports (Supplementary Fig. 1)35. To form the active catalyst, a constant potential was applied in the presence of $\\mathrm{CO}_{2}$ -saturated $0.1\\mathrm{M}\\mathrm{KHCO}_{3}$ electrolyte to reduce $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}$ \n\nDuring ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ the $\\mathrm{FE}_{\\mathrm{H}2}$ was found to range from 20 to $36\\%$ depending on applied potential (Fig.  1a). The total $\\mathrm{FE}_{\\mathrm{co2RR}}$ was steady at $70\\%\\pm5\\%$ . However, the product distribution changed: the major $\\mathrm{CO}_{2}\\mathrm{RR}$ products were C1 products (CO and formate) at lower potentials; and $^{\\mathrm{C2+}}$ products (ethylene, acetate and ethanol) at higher negative potentials. The current densities ranged from 10 to $90\\mathrm{mAcm}^{-2}$ depending on applied potential (Fig. 1b). The optimal potential for $^{\\mathrm{C2+}}$ ​products (ethylene, acetate, ethanol and propanol) was $-1.2\\mathrm{V}$ versus RHE (Supplementary Fig. 2) with a peak FE of $52\\%$ and $^{C2+}$ partial current density of $31\\mathrm{mA}\\mathrm{cm}^{-2}$ . The $\\mathrm{FE}_{\\mathrm{co}}$ starts at $20\\%$ at $-0.7\\mathrm{V}$ versus RHE and decreases to $<1\\%$ at $-1.4\\mathrm{V}$ versus RHE concomitant with an increase in $\\mathrm{FE}_{\\mathrm{c}2\\mathrm{H4}}$ (Fig. 1c). The maximum $\\mathrm{FE}_{\\mathrm{c}2\\mathrm{H}4}$ was $38\\%$ . It was found that ERD Cu consistently supresses $\\mathrm{FE}_{\\mathrm{CH4}}$ to below $1\\%$ . \n\n![](images/25083ec46d98660f191a57cca0f6ed8b1e74b43b02f255c85e2e9f21db9c97ef.jpg) \nFig. 2 | Growth of ERD Cu nanostructures. a, Schematic of the electrogrowth process, whereby simultaneous dissolution and redeposition of Cu results in structured deposits. b, SEM images of the key structure features at their specific applied potentials after at least 1 h of reaction. Scale bars are $5\\upmu\\mathrm{m}$ . c, Evolution of nanoclusters $(-0.7\\vee)$ , nanoneedles $(-1.0\\vee)$ , nanowhiskers $(-1.2\\lor)$ and dendrites $(-1.4\\lor)$ at increasing negative potential. All potentials are IR corrected and versus RHE. \n\nStructural characterization. We then sought to increase the absolute production of ethylene using a gas flow-cell electrolyser. Increased $\\mathrm{CO}_{2}$ gas diffusion in these configurations have resulted in absolute partial ethylene current densities as high as $150\\mathrm{mAcm}^{-2}$ (refs $^{26,36}$ ). A maximum $\\mathrm{FE}_{\\mathrm{c}2\\mathrm{H4}}$ of $36\\%$ at an ethylene partial current of $161\\mathrm{mAcm}^{-2}$ at $-1.0\\mathrm{V}$ versus RHE was observed with extremely strong methane suppression $\\left(\\mathrm{FE}_{\\mathrm{CH4}}<0.2\\%\\right)$ (Supplementary Fig. 3). A plot of ethylene/methane ratio versus partial current density of ethylene (Fig. 1d), representative of both selectivity and activity, of various Cu catalysts shows ERD Cu exhibits a partial ethylene current density in H-cell and flow-cell systems of $22\\mathrm{mAcm}^{-2}$ and $161\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively, with a ethylene/methane ratio of 200. \n\nTo understand the formation of the catalyst structure, we carried out SEM, dark-field optical microscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD) and scanning Auger microscopy (SAM) experiments to study ERD Cu over the course of reaction. Depending on the applied potential, different structural morphologies emerged. This growth is due to the simultaneous dissolution and redeposition of $\\mathrm{Cu}$ ions from the bulk of the material (Fig.  2a). At $-0.7\\mathrm{V}$ versus RHE, rounded nanostructures of approximately 0.5 to ${5\\upmu\\mathrm{m}}$ in size formed on the surface (Fig. $^{2\\mathrm{b},\\mathrm{c})}$ . At $-1.0\\mathrm{V}$ versus RHE, sharper needles approximately 5 to $10\\upmu\\mathrm{m}$ in length formed. At the more negative potential of $-1.2\\mathrm{V}$ versus RHE, sharper nanowhiskers of ${\\sim}5$ to $10\\upmu\\mathrm{m}$ with high length-to-diameter ratios were dominant. Finally, at the highest applied potential of $-1.4\\mathrm{V}$ versus RHE, dendrites with rounded tips appeared. SEM images were taken after the course of at least 1 h of reduction. The structural features were homogeneously dispersed on the surface of the carbon paper substrate (Supplementary Fig. 4). \n\nDark field microscope images of blue $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}$ as deposited on carbon paper showed uniform coverage (Supplementary Fig.  5a). Images taken after $\\boldsymbol{1\\mathrm{h}}$ of reaction at $-0.7\\mathrm{V}$ versus RHE and $-1.2\\mathrm{V}$ versus RHE (Fig. 3a,b) show that regions of metallic Cu form on the electrode edges. Microscope images taken of the ERD Cu at $-1.4\\mathrm{V}$ versus RHE show the surface dominated by metallic \n\nCu (Supplementary Fig. 5b). TEM images of the catalyst before and after reaction (Fig.  3c,d) reveal the change in the morphology of the material. Before reaction, regions of both polycrystalline and porous disordered material are present in the sol–gel, but after reaction only reduced polycrystalline material remains. XRD spectra were taken of the ERD Cu before and after reaction (Fig. 3e). The precursor sol–gel was found to have some amorphous regions with broad peaks that correspond primarily to $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}$ (ref. 35). At an applied potential of $-0.7\\mathrm{V}$ versus RHE all peaks associated with the precursor have disappeared but notably there are peaks corresponding to $\\mathrm{Cu}_{2}\\mathrm{O}$ and metallic Cu. At more negative potentials, the peaks corresponding to Cu begin to increase while the $\\mathrm{Cu}_{2}\\mathrm{O}$ peak disappears. Using Scherrer’s equation37, we calculated the crystallite sizes to be approximately 18, 25 and $57\\mathrm{nm}$ , for the $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}$ $\\{004\\}$ (ref. 38), $\\mathrm{Cu}_{2}\\mathrm{O}$ $\\{111\\}$ (ref. 39) and Cu $\\{111\\}$ (ref. 40) phases, respectively (Supplementary Table 2), indicating that the crystal grain size increased with applied negative potential. Additional SEM images were taken at 2, 5, 20 and $40\\mathrm{min}$ of Cu electro-redeposition to study the onset growth of sharp nanostructures at $-1.0\\mathrm{V}$ versus RHE (Fig. 3f ). At $2\\mathrm{min}$ , needle morphologies had begun to form in the sol–gel matrix (Supplementary Fig. 6) and continued to increase in size with respect to time. By $20\\mathrm{min}$ , the needles were fully formed. SAM analysis was performed to determine that the elemental composition of the nanostructures consisted of primarily Cu (Fig. 3g). A line survey scan (Supplementary Fig. 7) showed the presence of Cu and oxygen in the region that the needles grow from. While we cannot exclude the effects of re-oxidation in air, XRD and SAM results, taken together, reveal the morphological evolution of ERD Cu under applied negative potential. \n\nIn situ $\\mathbf{X}$ -ray spectroscopy and surface characterization. The structural evidence for $\\mathrm{Cu^{+}}$ prompted us to investigate further the electronic structure of the catalyst during ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ . We performed in situ sXAS experiments on ERD $\\mathtt{C u}$ under $\\mathrm{CO}_{2}$ reduction conditions. Previously, in situ hXAS experiments measuring the metal K-edge were reported for $\\mathrm{CO}_{2}\\mathrm{RR}$ catalysis9,19,41. hXAS measurements at the Cu K-edge probe high-energy $(9\\mathrm{keV})$ transitions but do not provide a robust determination of the narrow-band transition metal $3d$ electronic structure because direct excitation of $\\mathtt{C u}$ 1s electrons into $3d$ orbitals are dipole forbidden. In contrast, sXAS directly measures the dipole-allowed, low-energy $(0.93\\mathrm{keV})$ excitation of a metal $2p$ electron to the partially filled $3d$ shell. Thus, lower-energy transitions can be measured with higher spectral resolution, allowing for the acquisition of more feature-rich spectra that show greater contrast with electronic structure changes. \n\nEx situ sXAS Cu L-edge measurements of reference standards Cu metal, $\\mathrm{Cu}_{2}\\mathrm{O}$ and $\\mathtt{C u O}$ were taken (Fig. 4a and Supplementary Fig.  8). These spectra match well in both peak position and line shape with previously published reports42,43. The Cu L-edge spectra of the $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}$ precursor at open-circuit potential shows an $\\mathrm{L}_{3}$ -edge peak at $930.7\\mathrm{eV}$ and an $\\mathrm{L}_{2}$ -edge peak at $950.7\\mathrm{eV},$ which matches well with $\\mathrm{CuO},$ clearly indicating that Cu begins in the $+2$ oxidation state (Supplementary Fig. 9). We began by applying a constant potential of 1.13 V versus RHE and measuring the Cu L-edge over the course of $5\\mathrm{{min}}$ (5 scans $\\times1$ min each) under $\\mathrm{CO}_{2}\\mathrm{RR}$ conditions. We then applied a more negative constant potential and remeasured the Cu L-edge for another $5\\mathrm{min}$ continuing in a step-wise fashion up to $-1.87\\mathrm{V}$ versus RHE. \n\nThe evolution of the Cu $\\mathrm{L}_{3}$ -edge as a function of potential was tracked (Fig.  4a). We found that at applied potentials more positive than $0.28\\mathrm{V}$ versus RHE, the Cu L-edge exhibits a distinct peak at $931\\mathrm{eV},$ which is consistent with ${\\mathrm{Cu}}^{2+}$ (ref. 43). At $0.28\\mathrm{V}$ versus RHE, we observed that the sXAS spectra changed rapidly between each 1 min scan (Fig. 4b). We tracked, in real-time, the transition of Cu from ${\\mathrm{Cu}}^{2+}$ to ${\\mathrm{Cu}}^{+}$ as the $\\mathrm{L}_{3}$ -edge peak associated with ${\\mathrm{Cu}}^{2+}$ at $931\\mathrm{eV}$ decreased while another higher-energy peak around \n\n![](images/1daf6cb8c1a50d164c58a8746bf338ad896bd96238470635dc89063264418f98.jpg) \nFig. 3 | Surface characterization of ERD Cu. a,b, Dark-field microscope images of ERD Cu after 1 h of reaction at $-0.7\\vee$ versus RHE (a) and $-1.2\\vee$ versus RHE (b). c,d, TEM images of ERD Cu before reaction (c) and after (d) reaction. e, XRD plot of the ERD $\\mathsf{C u}$ before reaction (red) and after reaction at varying applied potentials. f, SEM images of ERD Cu under $-1.0\\vee$ versus RHE taken at 2, 5, 20 and $40\\min$ from left to right. g, SAM images of ERD Cu showing the Cu nanostructures (red) on carbon (green). \n\n$934\\mathrm{eV}$ began to emerge, consistent with an $\\mathrm{L}_{3}$ -edge peak of $933.7\\mathrm{eV}$ for $\\mathrm{Cu}_{2}\\mathrm{O}$ (ref. 43). By observing the change in sXAS spectra with respect to time, we found the structural change of Cu from ${\\mathrm{Cu}}^{2+}$ to ${\\mathrm{Cu^{+}}}$ occurred rapidly within 5 min. At applied potentials more negative than $0.28\\mathrm{V}$ versus RHE, we continued to observe a prominent sharp peak at $933\\mathrm{eV},$ which is consistent with ${\\mathrm{Cu}}^{+}$ . As the potentials approached reducing conditions lower than $0\\mathrm{V}$ versus RHE, the high-energy intensity past the adsorption $\\mathrm{L}_{3}$ -edge increased, characteristic of bulk $\\begin{array}{r}{\\mathrm{Cu},}\\end{array}$ and can be explained by transitions into 4s states unhybridized with $3d$ states43. Finally, at the applied potential of $-1.87\\mathrm{V}$ versus RHE, we found that the spectrum matched bulk Cu, indicating a complete transition from $\\mathrm{Cu^{+}}$ to ${\\mathrm{Cu}}^{0}$ . There was little variation between scans of the same applied potential, indicating the transition from ${\\mathrm{Cu}}^{+}$ to ${\\mathrm{Cu}}^{0}$ was not as rapid as the ${\\mathrm{Cu}}^{2+}$ to ${\\mathrm{Cu^{+}}}$ transition. \n\nTo provide a more quantitative analysis of the oxidation state changes during $\\begin{array}{r}{\\mathrm{CO}_{2}\\mathrm{RR},}\\end{array}$ we fitted the in situ spectra with a linear combination of the Cu metal, $\\mathrm{Cu}_{2}\\mathrm{O}$ and $\\mathtt{C u O}$ standards. A linear combination of the sXAS spectra was fitted to the Cu $\\mathrm{L}_{3}$ - edge spectra taken at $0.43\\mathrm{V},\\ 0.13\\mathrm{V}$ and $-1.87\\mathrm{V}$ versus RHE (Supplementary Fig. 10 and $R^{2}$ values in Supplementary Table 3). From the linear combination, we calculated the ratio of Cu oxidation species present at each applied potential (Fig. 4d), assuming the reference measurements provide an accurate representation of the 0, $+1$ and $+2$ oxidation states. Remarkably, we found that $\\mathtt{C u(I)}$ existed even at the negative potential of $-1.47\\mathrm{V}$ versus RHE under $\\mathrm{CO}_{2}\\mathrm{RR}$ conditions. \n\nWe tracked the change, over time and under applied bias (required for ethylene production $(-1.2\\mathrm{V}$ versus RHE), to determine the Cu species present during reaction (Fig. 4c). After $2\\mathrm{min}$ , the majority of $\\mathrm{Cu}\\left(84\\%\\right)$ was in the ${\\mathrm{Cu^{+}}}$ oxidation state (Fig. 4e). After a further $10\\mathrm{min}$ , this had decreased to $77\\%$ . The decrease of $7\\%$ of $\\mathrm{Cu^{+}}$ over $10\\mathrm{{min}}$ is consistent with the potential-dependent in situ data, which reveal that the transition between ${\\mathrm{Cu}}^{2+}$ and $\\mathrm{Cu^{+}}$ is a rapid one, while the transition between ${\\mathrm{Cu}}^{+}$ and ${\\mathrm{Cu}}^{0}$ is much slower. After $^\\mathrm{1h}$ under applied potential of $-1.2\\mathrm{V}$ versus RHE, $23\\%$ of $\\mathrm{Cu^{+}}$ remained. In situ hXAS experiments also showed a more oxidized $\\mathtt{C u}$ species on ERD Cu after $^\\mathrm{1h}$ of operation compared with Cu foil (Supplementary Fig. 11). These results show that $\\mathrm{Cu^{+}}$ may be stabilized under an applied potential of $-1.2\\mathrm{V}$ versus RHE for over $^{\\textrm{1h}}$ . \n\nTwo-dimensional contour maps of the $\\mathrm{CuL_{\\alpha,\\beta}}$ fluorescence intensity (Fig. $\\mathrm{4f,g}$ ) revealed that the Cu signal is dispersed throughout the sample area before reaction. After reduction, localized regions of higher intensity appear; suggesting Cu aggregation. Because halides are known to impact $\\begin{array}{r}{\\mathrm{CO}_{2}\\mathrm{RR},}\\end{array}$ X-ray photoelectron spectropscopy (XPS) was performed to study the presence of chlorine on the surface of the catalyst. XPS results (Supplementary Fig.  12) showed that no chlorine remained on the surface of the sample after reaction. Furthermore, the oxygen intensity also decreased substantially after reaction, indicating the reduction of $\\mathtt{C u O}$ The change in the Cu $2p$ peak is most indicative of reaction: before reaction, a sharp chemical shift is observed typical of a copper hydroxide species like $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}^{44}$ , while after reaction, the Cu $2p_{3/2}$ exhibits a signature difficult to distinguish between $\\mathrm{Cu}_{2}\\mathrm{O}$ and metallic $\\mathtt{C u}$ (refs 45,46). These results, taken together with the sXAS measurements, provide evidence for the presence of $\\mathrm{Cu^{+}}$ in ERD Cu during $\\mathrm{CO}_{2}\\mathrm{RR}$ . \n\n![](images/adda1cb7732a0da404db6e5be38ddd675e2bce7bcceaed866b1e8f5a00ec50f9.jpg) \nFig. 4 | X-ray spectroscopy measurements. a, In situ Cu $\\mathsf{L}_{3}$ -edge sXAS spectra of ERD Cu at different applied potentials (solid lines) and ex situ sXAS spectra of reference standards Cu metal (red dotted), $C\\mathsf{u}_{2}\\mathsf{O}$ (green dotted) and CuO (purpled dotted). b, Cu $\\mathsf{L}_{3}$ -edge spectra with respect to time of ERD Cu under a constant applied potential of $0.28\\mathsf{V}$ versus RHE. c, ERD $\\mathsf{C u}$ under an applied potential of $-1.2\\vee$ versus RHE over the course of 1 h. d, Calculated ratio of Cu oxidation states from linear combination fitting as a function of applied potential. e, Calculated ratio of Cu oxidation states with respect to time during 1 h of reaction at $-1.2\\vee$ versus RHE. f,g, ${\\mathsf{s}}\\mathsf{X A S}$ two-dimensional mapping of the $\\mathsf{C u}$ intensity with the region of interest set to $940\\mathrm{eV}$ with a width of $100\\mathsf{e V}$ before $(\\pmb{\\uparrow})$ and after $\\mathbf{\\sigma}(\\mathbf{g})$ running $C O_{2}R R$ \n\nInvestigating structure–property relationships. To explore further structure–property relationships, we examined the role of morphology and oxidation state in the catalytic performance of ERD Cu. \n\nFirst, we synthesized a dendritic $\\mathtt{C u}$ catalyst via electrodeposition47 that exhibits a highly porous structure with nanoneedles of high curvature as a control sample representative of a Cu catalyst with sharp morphologies but with no ${\\mathrm{Cu^{+}}}$ present. SEM images show that the high-curvature morphology of the $\\mathrm{Cu}$ nanoneedles remained consistent before and after reaction at $-1.2\\mathrm{V}$ versus RHE for over an hour (Supplementary Fig.  13a–d). This electrode was synthesized using a copper chloride deposition solution onto carbon paper, using the same $\\mathtt{C u}$ precursor as ERD Cu. \n\nWe then performed electrocatalytic experiments to determine the $\\mathrm{CO}_{2}\\mathrm{RR}$ activity of the $\\mathtt{C u}$ nanoneedle control. Major products for the Cu nanoneedles were hydrogen and formate (Supplementary Fig. 14a). The majority of products were C1; there was no applied potential at which $\\mathrm{FE}_{\\scriptscriptstyle{\\mathrm{C}2+}}$ exceeded $\\mathrm{FE}_{\\scriptscriptstyle\\mathrm{C1}}$ (Supplementary Fig. 14b). Cu nanoneedles performed considerably worse in ethylene selectivity with a max $\\mathrm{FE}_{\\mathrm{c}2\\mathrm{H4}}$ of only $14\\%$ , but retained a relatively low $\\mathrm{FE}_{\\mathrm{CH4}}$ of $4\\%$ (Supplementary Fig. 14d). Despite the decreased selectivity, the current densities of Cu nanoneedles remained similarly high to ERD $\\mathrm{cu}$ (Supplementary Fig.  14c). We propose that the highcurvature morphology is responsible for the enhancement in catalytic rate, leading to increased current densities and high local pH. \n\nTo provide mechanistic insights into the selectivity of ERD Cu, we used DFT calculations to explore the production of $\\mathrm{C_{2}H_{4}}$ versus $\\mathrm{CH_{4}}$ . Previous mechanistic studies revealed that the reaction pathways for $\\mathrm{CH}_{4}$ and $\\mathrm{C}_{2}\\mathrm{H}_{4}$ differ at the bound $\\mathrm{CO^{*}}$ intermediate48–51. \n\nHydrogenation of bound $\\mathrm{CO^{*}}$ to form bound $\\mathrm{COH^{*}}$ leads towards the formation of methane while the dimerization of two bound $\\mathrm{CO^{*}}$ intermediates leads to the formation of ethylene (Fig. 5a). Another recent study showed that the interface between surface $\\mathrm{Cu^{+}}$ and ${\\mathrm{Cu}}^{0}$ stabilizes CO–CO dimerization while impeding C1 pathways. This stabilization is due to the electrostatic attraction between oppositely charged carbon atoms induced by the ${\\mathrm{Cu^{+}}}$ and ${\\mathrm{Cu}}^{0}$ interface, promoting $C{\\mathrm{-}}C$ coupling52. We therefore concentrate on the Gibbs free energy of formation for $\\mathrm{COH^{*}}$ and ${\\mathrm{OCCOH^{*}}}$ as descriptors for methane formation and CO–CO dimerization to ethylene53. \n\nWe began by constructing $\\mathtt{C u}(111)$ and ${\\mathrm{Cu}}(211)$ slabs as model systems of flat and high-curvature $\\mathrm{Cu}$ surfaces, respectively. To model ERD Cu, we constructed a mixed $_\\mathrm{Cu:Cu_{2}O}$ slab with $25\\%$ $\\mathrm{Cu^{+}}$ species, closely matching the optimal amount of $\\mathrm{Cu^{+}}$ determined from sXAS studies. The ERD $\\mathrm{Cu}(111)$ and ERD ${\\mathrm{Cu}}(211)$ slabs serve as model systems for flat and high-curvature ERD Cu surfaces, respectively28. It was found that the Gibbs free energy of formation of the ${\\mathrm{OCCOH^{*}}}$ intermediate was lowest $(1.13\\mathrm{eV})$ on the ERD ${\\mathrm{Cu}}(211)$ system, $0.76\\mathrm{eV}$ lower than the ${\\mathrm{Cu}}(211)$ system, suggesting the presence of $\\mathrm{Cu^{+}}$ is favourable for ethylene production (Fig.  5b). The only surface where the formation of $\\mathrm{COH^{*}}$ was favoured was on $\\mathrm{Cu}(111)$ . ERD ${\\mathrm{Cu}}(211)$ also exhibited the strongest CO binding with a binding energy of $-1.45\\mathrm{eV}$ (Fig.  5c and Supplementary Table  6). Interestingly, DFT calculations also suggested that $\\mathrm{CH_{4}}$ is more favourable on ERD Cu than bulk Cu. However, experimentally, we observe severe methane suppression, which suggests that methane suppression cannot be explained fully by thermodynamic effects alone. Rather, methane suppression can be rationalized by the morphology-induced high current densities, which results in high local $\\mathrm{\\pH}$ and unfavourable kinetics for CO hydrogenation to $\\mathrm{COH^{*}}$ . These DFT results suggest that $\\mathrm{Cu^{+}}$ plays a crucial role in stabilizing the ${\\mathrm{OCCOH^{*}}}$ intermediate, shifting the reaction towards C2 rather than C1 products, and is consistent with experimental observations of ERD Cu. \n\n![](images/41351b751537c6143daea5b812af5709aa27615a11a0c548eb3a444c93fd46c0.jpg) \nFig. 5 | DFT studies of C1 and C2 electroproduction as a function of metal oxidation state. a, The reaction mechanisms for the hydrogenation of bound CO to $C\\mathsf{H}_{4}$ (red) and the CO–CO dimerization pathway to $C_{2}H_{4}$ (blue). b, The Gibbs free energy of formation of ${\\mathsf{C O H}}^{\\star}$ and ${\\mathsf{O C C O H}}^{\\star}$ on Cu(111), $\\mathsf{C u}(211)$ , ERD Cu(111) and ERD $\\mathsf{C u}(211)$ representative of flat $\\mathsf{C u}$ , high-curvature Cu, flat ERD Cu and high-curvature ERD Cu respectively. c, Optimized structure of bound ${\\mathsf{O C C O H}}^{\\star}$ on ERD Cu at the interface of $\\mathsf{C u^{+}}$ and ${\\mathsf{C u}}^{0}$ species. $G_{\\mathrm{form}^{\\prime}}$ Gibbs free energy of formation; $E_{\\mathrm{{binding}\\prime}}$ binding energy. \n\n# Discussion \n\nIn this study, we present electro-redeposition to realize stabilization of $\\mathrm{Cu^{+}}$ species and optimal morphologies for highly active ethylene production. We found, using in situ sXAS, that the ERD Cu promoted the stability of $\\mathrm{Cu^{+}}$ species at negative potentials far lower than previously reported for up to one hour of reaction. In situ sXAS is  experimentally challenging due to the requirement of an ultra-high vacuum environment, and the in situ soft XAS measurements of $\\mathrm{CO}_{2}$ reduction electrocatalysts in this study were enabled only by advanced reaction cells. \n\nWe found a catalytic trend where sharper structures with highercurvature surfaces favour $C2+$ production. It has been shown previously that sharp tips can improve bubble nucleation, concentrate stabilizing cations and exhibit high local fields, all of which increase current densities27–30. This high current density also promotes high local $\\mathrm{\\pH}$ , limiting the protonation of bound CO that leads to methane formation54. \n\nERD Cu exhibited almost no methane and low carbon monoxide production at the optimal ethylene production potential, highlighting the selectivity of ERD Cu for C2 over C1 gas products. Recent atomistic mechanistic studies have shown that C2 versus C1 selectivity is highly dependent on $\\mathrm{\\pH}$ and adsorbed surface water50,55. The CO dimerization is the preferred pathway at high $\\mathrm{\\pH}$ because hydrogenation of bound CO is kinetically limited. Local pH on the electrode surface is ${>}11$ when total current densities reach above $20\\mathrm{mAcm}^{-2}$ due to the rapid consumption of protons27. Comparison with Cu nanoneedle controls suggest that the sharp morphology of ERD Cu primarily increases the current density. ERD Cu shows extremely high current densities ( $60\\mathrm{mAcm}^{-2}$ in H-cell, $450\\mathrm{mAcm}^{-2}$ in flow cell), and consequently a high local $\\mathrm{\\pH}$ . Thus, methane suppression is likely enabled by the high local pH provided by ERD Cu. In studies of ${\\mathrm{Cu}}^{+}$ catalytic enhancement, DFT shows CO binding is stronger on ERD Cu, providing a greater probability of bound CO to interact and dimerize. Simulations also provide evidence that ${\\mathrm{Cu^{+}}}$ stabilizes the ${\\mathrm{OCCOH^{*}}}$ intermediate along the ethylene pathway, favouring the electrosynthesis of C2 products. \n\nIn summary, we present ERD Cu as a means to control morphology and oxidation state to suppress methane production and increase ethylene production. We investigated the electronic structure of ERD Cu using in situ sXAS under $\\mathrm{CO}_{2}\\mathrm{RR}$ conditions and varying applied potentials with time resolution to reveal the presence of ${\\mathrm{Cu^{+}}}$ at highly negative reducing potentials. A correlation between $^{\\mathrm{C2+}}$ selectivity, morphology and oxidation state is elucidated whereby sharp features kinetically limit methane formation through local pH effects while the presence of ${\\mathrm{Cu^{+}}}$ stabilizes ethylene intermediates. The result is an ethylene partial current density of $161\\mathrm{mAcm}^{-2}$ at $-1.0\\mathrm{V}$ versus RHE with an ethylene/methane ratio of 200. This study presents electro-redeposition as an unexplored materials strategy to exploit electronic and morphological effects for increased activity and selectivity of $\\mathrm{CO}_{2}$ reduction catalysts. \n\n# Methods \n\nDFT calculations. DFT calculations were performed with the Vienna Ab initio Simulation Package $(\\mathrm{VASP})^{56}$ . Full details are in the Supplementary Information. \n\nSynthesis of ERD Cu and Cu nanoneedle catalysts. The sol–gel precursor was prepared using an epoxide gelation synthesis (further details are in the Supplmentary Information)34,35. The active catalyst was then formed by reducing the sol–gel at a specific applied potential in $\\mathrm{CO}_{2}$ saturated $0.1\\mathrm{M}$ ${\\mathrm{KHCO}}_{3}$ electrolyte $(\\mathrm{pH}7.2)$ . The colour of the catalyst began to change from blue to black within $5\\mathrm{{min}}$ and was completely black by $10\\mathrm{min}$ regardless of potential applied, resulting in the active ERD Cu catalyst. The Cu nanoneedle catalysts were synthesized following a modified procedure47. Cu nanoneedles were electrodeposited on carbon paper from a deposition solution of $0.15\\ensuremath{\\mathrm{M}}\\ensuremath{\\mathrm{CuCl_{2}}}$ in $0.5\\mathbf{M}$ HCl using an applied potential of $-0.7\\mathrm{V}$ versus $\\mathrm{\\Ag/AgCl}$ for $1{,}000s$ . \n\nIn situ X-ray absorption. X-ray absorption measurements at the Cu L-edge and K-edge were performed at the spherical grating monochromator beamline 11ID-1 and soft X-ray microcharacterization beamline at the Canadian Light Source. All in situ fluorescence yield mode measurements were performed using a custom flow cell with the catalyst immersed in $\\mathrm{CO}_{2}$ saturated 0.1 M ${\\mathrm{KHCO}}_{3}$ electrolyte at open-circuit potential for at least $30\\mathrm{min}$ before applying a potential. The window of the sample cells was mounted at an angle of roughly $45^{\\circ}$ with respect to both the incident beam and the detectors. The bodies of the sample cells were fabricated on an SLA NEXT 3D printer. Silicon nitride membrane windows ( $1\\mathrm{mm}\\times1\\mathrm{mm}\\times100\\mathrm{nm}\\mathrm{,}$ in Si frames $\\mathrm{^5mm}\\times5\\mathrm{mm}\\times525\\upmu\\mathrm{m}\\mathrm{,}$ were purchased from SPI Supplies. Catalyst ink $(20\\upmu\\mathrm{L})$ was drop-casted onto the windows and allowed to dry in air. For electrochemical flow cells, the windows were treated by HF, and then coated by electron-beam evaporated titanium $(10\\mathrm{nm})$ and gold $(30\\mathrm{nm})$ , which served as the working electrode. Silver and platinum wires were used as reference and counter electrodes, respectively. The calibration of $\\mathrm{Ag}$ wire reference electrode was conducted in the standard three-electrode system (the same system as that for performance measurements) as reference electrodes, using Pt foil as working and counter electrodes. The 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte $(\\mathrm{pH}=0.3$ was pre-purged with Grade 4 $\\mathrm{H}_{2}$ overnight and continuously bubbled with $\\mathrm{H}_{2}$ with a flow rate of $25\\mathrm{ml}\\mathrm{min}^{-1}$ during calibrations. Linear sweep voltammetry (LSV) was run around $\\pm100\\mathrm{mV}$ between hydrogen evolution and oxidation, and the potential of zero current was recorded. The potential of zero current was around 0.2198 V (including pH correction of $0.3\\times0.0591{=}0.0177\\mathrm{V},$ for $\\mathrm{Ag/AgCl}$ electrode and $0.3306\\mathrm{V}$ (including $\\mathrm{\\pH}$ correction) for Ag wire electrode, resulting in a calibration of $E_{\\mathrm{Ag/AgCl(KCl,sat)}}+0.1108\\mathrm{V}=E_{\\mathrm{Agwire}},$ which is the same as the previous reported value57. The windows were then screwed onto the cell forming an air-tight electrolyte chamber of $\\mathrm{\\sim}1\\mathrm{mm}$ height. \n\nAll measurements were made at room temperature in the fluorescence mode using Amptek silicon drift detectors (SDDs) with an energy resolution of approximately $120\\mathrm{eV}.$ Four SDDs were employed simultaneously. The scanning time was $1\\mathrm{min}$ and repeated five times. The sample measurement spot was moved $0.1\\mathrm{mm}$ between measurements at different applied potentials to minimize the effect of the X-ray beam on the sample. The scanning energy range of the Cu L-edge was from 920 to $960\\mathrm{eV}.$ The partial fluorescence yield was extracted from all SDDs by summation of the corresponding Cu L-emission lines. \n\nTo determine the concentration of different Cu species, the XAS spectra of Cu standards (Cu, $\\mathrm{{Cu}_{2}O}$ and $\\mathrm{CuO}_{\\mathrm{;}}$ representing the 0, $^{1+}$ ​and $^{2+}$ oxidation states of Cu, respectively) were measured. Each in situ XAS measurement was then decomposed into a linear combination of these three Cu standards with a simple linear least squares script written in MATLAB. An $R^{2}$ value was obtained as a metric for the quality of the fitting. To determine the magnitude of each species’ \n\nXAS spectrum, the standards were normalized by matching the pre-edge and postedge values simultaneously to account for potential changes in the cross-section of the material throughout the measurement. In addition, to account for selfabsorption and other measurement artifacts that lead to the appearance of a linear term in the XAS spectrum, a linear term was subtracted from the signal before fitting. Despite all measures taken, it is worth noting that changes in the density of the material could occur, potentially distorting the fitting; however, these effects are considered to be negligible. \n\n$\\mathrm{\\DeltaX}$ -ray fluorescence mapping was performed on the spherical grating monochromator beamline by rastering the sample across the beam while collecting X-ray fluorescence spectra. The sample is slewed across the beam and the detectors are read out continuously. For the microscopy, the beamspot size was focused to approximately $50\\upmu\\mathrm{m}$ using a Kirkpatrick-Baez mirror system. \n\nCharacterization. SEM images were acquired using a Quanta FEG 250 or JEOL FE-SEM. TEM images were taken with a Hitachi H-7650 microscope. Dark-field microscopy images were taken with an Olympus BXFM microscope. Powder XRD patterns were obtained with MiniFlex600 instrument. Data were collected in Bragg–Brentano mode using $0.02^{\\circ}$ divergence with a scan rate of $0.1^{\\circ}\\:s^{-1}$ . XPS measurements were carried out in a Thermo Scientific K-Alpha system with an Al $\\mathrm{K}\\alpha$ source with a $400\\upmu\\mathrm{m}$ spot size, $50\\mathrm{eV}$ pass energy and energy steps of $0.05\\mathrm{eV.}$ SAM imaging was performed with the PHI 710 Scanning Auger Nanoprobe system, with a cylindrical mirror analyzer and a $25\\mathrm{kV}$ coaxial field emission electron gun. \n\nElectrochemical reduction of $\\mathbf{CO}_{2}$ . The $\\mathrm{CO}_{2}\\mathrm{RR}$ activity of the ERD Cu catalysts was investigated by performing electrolysis in a two-compartment H-cell in $\\mathrm{CO}_{2}$ saturated $0.1\\mathrm{{M}}$ potassium bicarbonate $\\mathrm{(KHCO_{3})}$ ) electrolyte (see the Supplementary Information for details on flow-cell configuration and long-term stability). The three-electrode set-up was connected to a potentiostat (Autolab PGSTAT302N). $\\mathrm{Ag/AgCl}$ (saturated KCl) was used as the reference electrode and platinum foil was used as the counter electrode. The reaction was performed at constant IR-corrected potential and the products were taken after at least 1 h of continuous run time. Potentiostatic electrochemical impedance spectroscopy with a potential range of $^{-5}$ to 5 V, $100\\mathrm{kHz}$ frequency and sinus amplitude of $10\\mathrm{mV}$ was used to calculate the IR correction. The resistance values were $34\\Omega$ ​and $4.5\\Omega$ ​for H-cell and flow-cell configurations, respectively. Reaction products were quantitatively determined using gas chromatography and nuclear magnetic resonance for gas and liquid products, respectively. Electrode potentials were converted to RHE using the following equation, $\\begin{array}{r}{E_{\\mathrm{{RHE}}}=E_{\\mathrm{{Ag/AgCl}}}+0.197\\mathrm{{V}}+0.0591\\times\\mathrm{{pH}}.}\\end{array}$ . \n\nThe experiments were performed in a gas-tight, two-compartment H-cell separated by an ion exchange membrane (Nafion 117). The electrolyte in the cathodic compartment was stirred at a rate of $300\\mathrm{r.p.m}$ . during electrolysis. $\\mathrm{CO}_{2}$ gas was delivered into the cathodic compartment at a rate of $20.00\\ s c c\\mathrm{m}$ and was routed into a gas chromatograph (PerkinElmer Clarus 600). The gas chromatograph was equipped with a Molecular Sieve 5A capillary column and a packed Carboxen-1000 column. Argon (Linde, $99.999\\%$ ) was used as the carrier gas. The gas chromatography columns led directly to a thermal conductivity detector and a flame ionization detector. The number of moles of gas product were calculated from gas chromatography peak areas with conversion factors for CO, $\\mathrm{H}_{2}$ and ethylene based on calibration with standard samples at 1.013 bar and $300\\mathrm{K}$ . NMR was used to determine the liquid products. $^{1}\\mathrm{H}$ NMR spectra were collected on Agilent DD2 500 spectrometer in $10\\%$ $_{\\mathrm{~D_{2}O~}}$ using water suppression mode, with DMSO as an internal standard. A 10 s relaxation time between the pulses was used to allow for complete proton relaxation. The Faradaic efficiency (FE) was calculated as follows: $\\mathrm{FE}{=}\\mathrm{eF}{\\times}\\mathrm{n}/\\mathrm{Q}{=}2\\mathrm{F}{\\times}\\mathrm{n}/(\\mathrm{I}{\\times}\\mathrm{t})$ , where $e$ is the number of electrons transferred, $F$ is the Faraday constant, Q is the charge, $I$ is the current, t is the running time and $n$ is the total amount of product (in moles). \n\nData availability. The data that support the findings of this study are available from the corresponding author on reasonable request. \n\n# Received: 14 June 2017; Accepted: 24 November 2017; Published online: 15 January 2018 \n\n# References \n\n1.\t Armstrong, R. C. et al. The frontiers of energy. Nat. Energy 1, 15020 (2016). \n2.\t Montoya, J. H. et al. Materials for solar fuels and chemicals. Nat. Mater. 16, 70–81 (2017). \n3.\t Peterson, A. A., Abild-Pedersen, F., Studt, F., Rossmeisl, J. & Nørskov, J. K. How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels. Energy Environ. Sci. 3, 1311 (2010). \n4.\t Kuhl, K. P. et al. New insights into the electrochemical reduction of carbon dioxide on metallic copper surfaces. Energy Environ. Sci. 5, 7050 (2012). \n5.\t Van Miltenburg, A., Zhu, W., Kapteijn, F. & Moulijn, J. A. Adsorptive separation of light olefin/paraffin mixtures. Chem. Eng. Res. Des. 84, 350–354 (2006). \n6. Li, C. W. & Kanan, M. W. $\\mathrm{CO}_{2}$ reduction at low overpotential on Cu electrodes resulting from the reduction of thick $\\mathrm{Cu}_{2}\\mathrm{O}$ films. J. Am. Chem. Soc. 134, 7231–7234 (2012). \n7. Eilert, A. et al. Subsurface oxygen in oxide-derived copper electrocatalysts for carbon dioxide reduction. J. Phys. Chem. Lett. 8, 285–290 (2017). \n8.\t Verdaguer-Casadevall, A. et al. Probing the active surface sites for CO reduction on oxide-derived copper electrocatalysts. J. Am. Chem. Soc. 137, \n9808–9811 (2015). \n9.\t Mistry, H. et al. Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene. Nat. Commun. 7, 12123 (2016). \n10.\tLoiudice, A. et al. Tailoring copper nanocrystals towards $\\mathbf{C}_{2}$ products in electrochemical $\\mathrm{CO}_{2}$ reduction. Angew. Chem. Int. Ed. 55, 5789–5792 (2016). \n11.\tLee, S., Kim, D. & Lee, J. Electrocatalytic production of C3-C4 compounds by conversion of $\\mathrm{CO}_{2}$ on a chloride-induced bi-phasic $\\mathrm{{Cu}_{2}\\mathrm{{O}}}$ -Cu catalyst. Angew. Chem. Int. Ed. 54, 14701–14705 (2015). \n12.\tChen, C. S. et al. Stable and selective electrochemical reduction of carbon dioxide to ethylene on copper mesocrystals. Catal. Sci. Technol. 5, \n161–168 (2015). \n13.\tKas, R. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction on $\\mathrm{{Cu}_{2}\\mathrm{{O}}}$ -derived copper nanoparticles: controlling the catalytic selectivity of hydrocarbons. Phys. Chem. Chem. Phys. 16, 12194 (2014). \n14.\tHandoko, A. D. et al. Mechanistic insights into the selective electroreduction of carbon dioxide to ethylene on $\\mathrm{Cu}_{2}\\mathrm{O}$ -derived copper catalysts. J. Phys. Chem. C. 120, 20058–20067 (2016). \n15.\tGao, D. et al. Plasma-activated copper nanocube catalysts for efficient carbon dioxide electroreduction to hydrocarbons and alcohols. ACS Nano 11, \n4825–4831 (2017). \n16.\tHori, Y., Takahashi, I., Koga, O. & Hoshi, N. Selective formation of C2 compounds from electrochemical reduction of $\\mathrm{CO}_{2}$ at a series of copper single crystal electrodes. J. Phys. Chem. B 106, 15–17 (2002). \n17.\t Kwon, Y., Lum, Y., Clark, E. L., Ager, J. W. & Bell, A. T. $\\mathrm{CO}_{2}$ electroreduction with enhanced ethylene and ethanol selectivity by nanostructuring polycrystalline copper. ChemElectroChem 3, 1012–1019 (2016). \n18.\tFeng, X., Jiang, K., Fan, S. & Kanan, M. W. Grain-boundary-dependent $\\mathrm{CO}_{2}$ electroreduction activity. $J.$ Am. Chem. Soc. 137, 4606–4609 (2015). \n19.\tEilert, A., Roberts, F. S., Friebel, D. & Nilsson, A. Formation of copper catalysts for $\\mathrm{CO}_{2}$ reduction with high ethylene/methane product ratio investigated with in situ X-ray absorption spectroscopy. J. Phys. Chem. Lett. 7, \n1466–1470 (2016). \n20.\tLi, Y. et al. Structure-sensitive $\\mathrm{CO}_{2}$ electroreduction to hydrocarbons on ultrathin 5-fold twinned copper nanowires. Nano Lett. 17, \n1312–1317 (2017). \n21.\tKim, D., Resasco, J., Yu, Y., Asiri, A. M. & Yang, P. Synergistic geometric and electronic effects for electrochemical reduction of carbon dioxide using gold–copper bimetallic nanoparticles. Nat. Commun. 5, 4948 (2014). \n22.\tRoberts, F. S., Kuhl, K. P. & Nilsson, A. High selectivity for ethylene from carbon dioxide reduction over copper nanocube electrocatalysts. Angew. Chem. Int. Ed. 54, 5179–5182 (2015). \n23.\tRaciti, D., Livi, K. J. & Wang, C. Highly dense Cu nanowires for lowoverpotential $\\mathrm{CO}_{2}$ reduction. Nano Lett. 15, 6829–6835 (2015). \n24.\tMistry, H., Varela, A. S., Kühl, S., Strasser, P. & Cuenya, B. R. Nanostructured electrocatalysts with tunable activity and selectivity. Nat. Rev. Mater. 1, \n16009 (2016). \n25.\tHuan, T. N. et al. Porous dendritic copper: an electrocatalyst for highly selective $\\mathrm{CO}_{2}$ reduction to formate in water/ionic liquid electrolyte. Chem. Sci. 8, 742–747 (2017). \n26.\tReller, C. et al. Selective electroreduction of $\\mathrm{CO}_{2}$ toward ethylene on nano dendritic copper catalysts at high current density. Adv. Energy Mater. 7, \n1602114 (2017). \n27.\tBurdyny, T. et al. Nanomorphology-enhanced gas-evolution intensifies $\\mathrm{CO}_{2}$ reduction electrochemistry. ACS Sustain. Chem. Eng. 5, 4031–4040 (2017). \n28.\tLiu, M. et al. Enhanced electrocatalytic $\\mathrm{CO}_{2}$ reduction via field-induced reagent concentration. Nature 537, 382–386 (2016). \n29.\tKlinkova, A. et al. Rational design of dfficient palladium catalysts for electroreduction of carbon dioxide to formate. ACS Catal. 6, \n8115–8120 (2016). \n30.\tSaberi Safaei, T. et al. High-density nanosharp microstructures enable efficient $\\mathrm{CO}_{2}$ electroreduction. Nano Lett. 16, 7224–7228 (2016). \n31.\tZheng, X. et al. Theory-driven design of high-valence metal sites for water oxidation confirmed using in situ soft X-ray absorption. Nat. Chem. https://doi.org/10.1038/nchem.2886 (2017). \n32.\tZheng, X. et al. Sulfur-modulated tin sites enable highly selective electrochemical reduction of $\\mathrm{CO}_{2}$ to formate. Joule 1, 794–805 (2017). \n33.\tChen, L. D., Urushihara, M., Chan, K. & Nørskov, J. K. Electric field effects in electrochemical $\\mathrm{CO}_{2}$ reduction. ACS Catal. 6, 7133–7139 (2016). \n34.\tZhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n35.\tSisk, C. N. & Hope-Weeks, L. J. Copper(ii) aerogels via 1,2-epoxide gelation. J. Mater. Chem. 18, 2607 (2008). \n36.\tMa, S. et al. One-step electrosynthesis of ethylene and ethanol from $\\mathrm{CO}_{2}$ in an alkaline electrolyzer. J. Power Sources 301, 219–228 (2016). \n37.\tPatterson, A. L. The Scherrer formula for X-Ray particle size determination. Phys. Rev. 56, 978–982 (1939). \n38.\tMalcherek, T. et al. Structures of the pseudo-trigonal polymorphs of $\\mathrm{Cu}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl}$ . Acta Crystallogr. Sect. B Struct. Sci. 65, 334–341 (2009). \n39.\tNeuburger, M. C. Prazisionsmessung der Gitterkonstante von Cuprooxyd $\\mathrm{{Cu}_{2}\\mathrm{{O}}}$ . Z. Phys. 67, 845–850 (1931). \n40.\tFortes, A. D., Suard, E., Lemée-Cailleau, M.-H., Pickard, C. J. & Needs, R. J. Crystal structure of ammonia monohydrate phase II. J. Am. Chem. Soc. 131, 13508–13515 (2009). \n41.\tRosen, J. et al. Electrodeposited $Z\\mathrm{n}$ dendrites with enhanced CO selectivity for electrocatalytic $\\mathrm{CO}_{2}$ reduction. ACS Catal. 5, 4586–4591 (2015). \n42.\tJiang, P. et al. Experimental and theoretical investigation of the electronic structure of $\\mathrm{{Cu}_{2}O}$ and $\\mathtt{C u O}$ thin films on $\\mathtt{C u}(110)$ using X-ray photoelectron and absorption spectroscopy. $J.$ Chem. Phys. 138, 24704 (2013). \n43.\tGrioni, M. et al. Studies of copper valence states with $\\mathrm{Cu}\\mathrm{L}_{3}$ X-ray-absorption spectroscopy. Phys. Rev. B 39, 1541–1545 (1989). \n44.\tMcIntyre, N. S., Sunder, S., Shoesmith, D. W. & Stanchell, F. W. Chemical information from XPS—applications to the analysis of electrode surfaces. J. Vac. Sci. Technol. 18, 714–721 (1981). \n45.\t Fuggle, J. C., Källne, E., Watson, L. M. & Fabian, D. J. Electronic structure of aluminum and aluminum-noble-metal alloys studied by soft-X-ray and X-ray photoelectron spectroscopies. Phys. Rev. B 16, 750–761 (1977). \n46.\t McIntyre, N. S. & Cook, M. G. X-ray photoelectron studies on some oxides and hydroxides of cobalt, nickel, and copper. Anal. Chem. 47, 2208–2213 (1975). \n47.\tZhang, X., Wang, G., Liu, X., Wu, H. & Fang, B. Copper dendrites: synthesis, mechanism discussion, and application in determination of l-tyrosine. Cryst. Growth Des. 8, 1430–1434 (2008). \n48.\t Schouten, K. J. P., Kwon, Y., van der Ham, C. J. M., Qin, Z. & Koper, M. T. M. A new mechanism for the selectivity to C1 and C2 species in the electrochemical reduction of carbon dioxide on copper electrodes. Chem. Sci. 2, 1902 (2011). \n49.\t Nie, X., Esopi, M. R., Janik, M. J. & Asthagiri, A. Selectivity of $\\mathrm{CO}_{2}$ reduction on copper electrodes: the role of the kinetics of elementary steps. Angew. Chem. Int. Ed. 52, 2459–2462 (2013). \n50.\tXiao, H., Cheng, T. & Goddard, W. A. Atomistic mechanisms underlying selectivities in $\\mathrm{C}_{1}$ and $\\mathbf{C}_{2}$ products from electrochemical reduction of CO on $\\mathrm{{Cu}(111)}$ . J. Am. Chem. Soc. 139, 130–136 (2017). \n51.\tCheng, T., Xiao, H. & Goddard, W. A. Full atomistic reaction mechanism with kinetics for CO reduction on $\\mathrm{{Cu}(100)}$ from ab initio molecular dynamics free-energy calculations at 298 K. Proc. Natl Acad. Sci. USA 114, 1795–1800 (2017). \n52.\t Xiao, H., Goddard, W. A., Cheng, T. & Liu, Y. Cu metal embedded in oxidized matrix catalyst to promote $\\mathrm{CO}_{2}$ activation and CO dimerization for electrochemical reduction of $\\mathrm{CO}_{2}$ . Proc. Natl Acad. Sci. USA 114, 6685–6688 (2017). \n53.\tCheng, T., Xiao, H. & Goddard, W. A. Nature of the active sites for CO reduction on copper nanoparticles; suggestions for optimizing performance. J. Am. Chem. Soc. 139, 11642–11645 (2017). \n54.\t Kortlever, R., Shen, J., Schouten, K. J. P., Calle-Vallejo, F. & Koper, M. T. M. Catalysts and reaction pathways for the electrochemical reduction of carbon dioxide. J. Phys. Chem. Lett. 6, 4073–4082 (2015). \n55.\tXiao, H., Cheng, T., Goddard, W. A. III. & Sundararaman, R. Mechanistic explanation of the pH dependence and onset potentials for hydrocarbon products from electrochemical reduction of CO on Cu (111). J. Am. Chem. Soc. 138, 483–486 (2016). \n56.\tHafner, J. Ab-initio simulations of materials using VASP: density-functional theory and beyond. J. Comput. Chem. 29, 2044–2078 (2008). \n57.\tRiskin, M., Basnar, B., Katz, E. & Willner, I. Cyclic control of the surface properties of a monolayer-functionalized electrode by the electrochemical generation of $\\mathrm{Hg}$ nanoclusters. Chem. Eur. J. 12, 8549–8557 (2006). \n\n# Acknowledgements \n\nThis work was supported by the Canadian Institute for Advanced Research (CIFAR) Bioinspired Energy Program, the Ontario Research Fund (ORF-RE-08-034), and the Natural Sciences and Engineering Research Council (NSERC) of Canada. This work was also supported by the Director, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, of the US Department of Energy under contract no. DE-AC02-05CH11231 within the Catalysis Research Program (FWP No. CH030201). The authors thank the Canadian Light Source (CLS) for support in the form of a travel grant. The authors acknowledge Y. Li for valuable scientific discussion and assistance with TEM measurements, A. Kiani for assistance with SEM measurements, Y. Hu and M. Norouzi Banis for assistance with in situ XAS cell set-up, and P. Brodersen from the Ontario Centre for the Characterisation of Advanced Materials (OCCAM) Center for assistance with Auger microscopy measurements. P.D.L thanks the Research Council (NSERC) of Canada for the Canadian Graduate Scholarship — Doctoral award and the Michael Smith Foreign Supplement award. M.B.R. gratefully acknowledges support from the CIFAR Bio-Inspired Solar Energy Program. Computations were performed on the SOSCIP Consortium’s Blue Gene/Q computing platform. SOSCIP is funded by the Federal Economic Development Agency of Southern Ontario, the Province of Ontario, IBM Canada Ltd., Ontario Centres of Excellence, Mitacs and 15 Ontario academic member institutions. \n\n# Author contributions \n\nP.D.L. synthesized the catalyst, performed DFT calculations, SEM, TEM, XAS and electrochemical experiments, and data analysis, and wrote the manuscript. R.Q.-B. performed XAS, XPS and SAM experiments and data analysis, and edited the manuscript. C.-T.D. performed flow-cell experiments and edited the manuscript. M.B.R. edited the manuscript and guided the design of experiments. O.S.B. performed NMR experiments and analysis. P.T. performed XRD experiments. T.R. supervised and guided XAS experiments. P.Y. and S.O.K. supervised experiments. E.H.S designed the study, edited the manuscript and supervised experiments. \n\n# Competing interests \n\nThe authors declare no competing financial interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-017-0018-9. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to E.H.S. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1038_s41467-018-04467-3", + "DOI": "10.1038/s41467-018-04467-3", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-04467-3", + "Relative Dir Path": "mds/10.1038_s41467-018-04467-3", + "Article Title": "nulloparticle-templated nullofiltration membranes for ultrahigh performance desalination", + "Authors": "Wang, ZY; Wang, ZX; Lin, SH; Jin, HL; Gao, SJ; Zhu, YZ; Jin, J", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "nullofiltration (NF) membranes with ultrahigh permeance and high rejection are highly beneficial for efficient desalination and wastewater treatment. Improving water permeance while maintaining the high rejection of state-of-the-art thin film composite (TFC) NF membranes remains a great challenge. Herein, we report the fabrication of a TFC NF membrane with a crumpled polyamide (PA) layer via interfacial polymerization on a single-walled carbon nullotubes/polyether sulfone composite support loaded with nulloparticles as a sacrificial templating material, using metal-organic framework nulloparticles (ZIF-8) as an example. The nulloparticles, which can be removed by water dissolution after interfacial polymerization, facilitate the formation of a rough PA active layer with crumpled nullostructure. The NF membrane obtained thereby exhibits high permeance up to 53.5 l m(-2)h(-1) bar(-1) with a rejection above 95% for Na2SO4, yielding an overall desalination performance superior to state-of-the-art NF membranes reported so far. Our work provides a simple avenue to fabricate advanced PA NF membranes with outstanding performance.", + "Times Cited, WoS Core": 797, + "Times Cited, All Databases": 840, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000432535300008", + "Markdown": "# Nanoparticle-templated nanofiltration membranes for ultrahigh performance desalination \n\nZhenyi Wang1,2, Zhangxin Wang3, Shihong Lin3, Huile Jin4, Shoujian Gao1, Yuzhang Zhu1 & Jian Jin1 \n\nNanofiltration (NF) membranes with ultrahigh permeance and high rejection are highly beneficial for efficient desalination and wastewater treatment. Improving water permeance while maintaining the high rejection of state-of-the-art thin film composite (TFC) NF membranes remains a great challenge. Herein, we report the fabrication of a TFC NF membrane with a crumpled polyamide (PA) layer via interfacial polymerization on a single-walled carbon nanotubes/polyether sulfone composite support loaded with nanoparticles as a sacrificial templating material, using metal-organic framework nanoparticles (ZIF-8) as an example. The nanoparticles, which can be removed by water dissolution after interfacial polymerization, facilitate the formation of a rough PA active layer with crumpled nanostructure. The NF membrane obtained thereby exhibits high permeance up to $53.5\\mathsf{I m}^{-2}\\mathsf{h}^{-1}\\mathsf{b a r}^{-1}$ with a rejection above $95\\%$ for ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4},$ yielding an overall desalination performance superior to state-of-the-art NF membranes reported so far. Our work provides a simple avenue to fabricate advanced PA NF membranes with outstanding performance. \n\nggravated by rapid population and economic growth, water contamination and scarcity have evolved to be a global challenge1,2. Extensive research has been devoted to developing advanced materials3,4 and technologies5 to augment fresh water supply by either seawater/brackish desalination or wastewater reuse. Of all existing desalination technologies, pressure-driven membrane-based technologies, such as reverse osmosis (RO) and nanofiltration (NF), are the most energyefficient and technologically mature. In particular, NF membrane rejects multivalent salts and organic molecules with molecular weight cut-off $\\mathrm{(MWCO)}>200\\mathrm{D}\\mathbf{\\bar{a}},^{6,7}$ rendering NF an ideal water treatment technology for low-energy, high-throughput desalination applications in which ultra-high rejection of monovalent ions is not required. These applications include, but are not limited to, treating industrial process streams8, decontaminating wastewater9, and softening brackish groundwater10. State-of-the-art NF membranes are based on a thin film composite (TFC) design11, which deposits a polyamide (PA) active layer, formed by interfacial polymerization, on top of a porous support layer that is typically an ultrafiltration (UF)12 or a microfiltration (MF) membrane13,14. Such a TFC structure yields high performance membranes with strong mechanical integrity, and enables costeffective and scalable membrane manufacturing. Although significant improvement has been made over the past decades to improving the performance of TFC NF membrane, the current permeance of TFC NF membranes is still not high. Further enhancing the permeance while maintaining a high-solute rejection rate can significantly reduce the membrane area required to achieve a target water production rate, thereby reducing the capital cost of NF and rendering it more affordable. \n\nThe performance of TFC NF membrane, in terms of permeance and selectivity, is primarily determined by the PA active layer that is responsible for solute rejection. The regulation and control of the molecular and structural characteristics of the PA layer are thus of great importance in improving the performance of TFC NF membranes. Extensive effort has been dedicated to enhance the permeance of this active layer without sacrificing its selectivity. One viable strategy is to tailor the intrinsic properties of the active layer through either designing the polymer structure at the molecular level15–18 or incorporating hydrophilic nanomaterials into the layer19–21. The main rationale of this strategy is to reduce the resistance of water transport across the active layer and thereby improve permeance. However, significant change of water transport properties in the PA-based active layers is hard to achieve because water transport is heavily restricted by the highly cross-linked polymer chains in a tortuous manner22. \n\nAnother strategy to achieve a high permeance is to make thinner active layers to reduce water transport resistance23–26. This may be achieved by controlling the interfacial polymerization process where amine monomers diffusing from the aqueous phase rapidly react with the acid chloride diffusing from the organic phase. However, precise control of the interfacial polymerization process is challenging as the interfacial reaction on conventional polymeric UF/MF membranes is diffusion limited. Therefore, the typical thickness of PA active layer ranges from tens to hundreds of nanometers. A possible strategy to obtain a thin PA active layer with controlled interfacial reaction is to introduce interlayer media, such as inorganic nanostrands $\\mathrm{flm}^{27}$ , carbon nanotube network layer28,29, and cellulose nanocrystals $\\mathrm{{flm}}^{30}$ , etc. on top of commercial polymeric UF/MF membrane as the support layer. These interlayer media provide more uniform substrate pores and optimized water wetting property than conventional polymeric UF/MF membranes, which in turn enable more homogeneous distribution of the monomer solutions and more effective control of monomer release in interfacial polymerization. Using this approach, thin PA active layers with thickness near $10\\mathrm{nm}$ have been achieved successfully. The resulting membranes with ultrathin PA layers exhibited substantially higher permeance. While this strategy of reducing active layer is effective in enhancing membrane permeance, further improvement of membrane performance following this strategy is limited, as it will become extremely challenging to prepare defectfree active layers that are even thinner than the state-of-the-art. \n\nUndoubtedly, increasing the effective permeable area of ultrathin PA active layer is a preferred route on the premise of no other features losing. Here we report a novel strategy of designing a TFC NF membrane with an unprecedented permeance via a nanostructure-mediated interfacial polymerization process in which nanoparticles are preloaded as sacrificial templating materials on a support porous membrane. These preloaded nanoparticles create rough and irregular nanostructure on the surface of support membrane. Thus, the interfacial polymerization of piperazine and trimesoyl chloride occurs over such a rugged surface with nanoscale roughness. After polymerization, these nanoparticles can be readily removed by water dissolution, forming a thin PA active layer with extensive crumpled nanoscale structures. This crumpled structure significantly increases the available area for water permeation per projected area on the support. The resulting PA TFC membrane exhibits an unprecedentedly high permeance up to $53.21\\mathrm{m}^{-2}\\mathrm{h}^{-1}\\mathrm{bar}^{-1}$ while maintaining a high rejection of $95.2\\ \\%$ for ${\\ N a}_{2}{\\ S}{\\ O}_{4}$ . This is the most permeable TFC PA NF membrane with a satisfactory level of rejection (for NF applications), outperforming all existing NF membranes to the best of our knowledge. \n\n# Results \n\nFabrication of crumple nanofiltration membrane. The key to achieve the crumpled active layer structure is to pre-load nanoparticles as a sacrificial template on the porous support membrane for interfacial polymerization. Here, polydopamine (PD) decorated MOF ZIF-8 nanoparticles (PD/ZIF-8) with controlled particle sizes of $30{-}400~\\mathrm{nm}$ are used as representative sacrificial templates, as schematically illustrated in Fig. 1a. In order to ensure homogeneous and well-controlled loading of PD/ZIF-8 nanoparticles, a composite membrane, prepared by depositing an ultrathin layer of single-walled carbon nanotube (SWCNTs) network onto a commercial polyether sulfone (PES) MF membrane, was used as the porous support. Then a typical interfacial polymerization process, in which diamine monomer piperazine (PIP) and trimesoyl chloride (TMC) reacts at water–hexane interface to form the PA selective layer, was induced on the surface of such a support loaded with PD/ZIF-8 nanoparticles. Upon the completion of the polymerization reaction, the asprepared NF composite membrane was immersed into water to dissolve the PD/ZIF-8 nanoparticles. A TFC PA NF membrane with crumpled structure was formed after the PD/ZIF-8 nanoparticles were completely removed. We have previously reported that deposition of a thin layer of SWCNTs film on traditional MF membranes greatly improves the quality of the obtained PA active layer thanks to the high porosity, smoothness, and narrowly distributed pores of the SWCNT-coated support layer28. To enhance the quality of the PA active layer, every SWCNT was wrapped by a thin PD layer before forming the SWCNTs network film (see Supplementary Figure 1). The PD-wrapped SWCNTs film enhanced the surface hydrophilicity to promote homogeneous distribution of the monomer solution for more controlled release of monomers during interfacial reaction. As a result, an ultrathin and defect-free PA layer was obtained. The thickness of PD/SWCNTs film used in this work was around 75 nm as confirmed by atomic force microscope (AFM) measurement (see Supplementary Figure 2a and 2b). The SWCNTs film shows a uniform network structure with the effective pore size ranging from 10 to $20\\mathrm{nm}$ (see Supplementary Figure 2c). The surface chemical components of the SWCNTs film as analyzed by XPS confirms the existence of PD on carbon nanotubes (see Supplementary Figure 2d and 2e). This PD layer renders the SWCNTs film hydrophilic as confirmed by a water contact angle (CA) of $22^{\\circ}$ . The evolution of the crumpled active layer of the TFC NF membrane was revealed by monitoring the change of membrane surface morphology at different stages during membrane fabrication process. The SEM image of the pristine SWCNTs film, covering the PES MF membrane before interfacial polymerization, suggests a smooth and transparent network structure formed by interconnected SWCNTs on the surface of PES MF membrane (Fig. 1b). PD/ZIF-8 nanoparticles with an average diameter of ${\\sim}150\\mathrm{nm}$ were then loaded on this composite membrane to serve as the support layer as shown in Fig. 1c. The loading mass of PD/ZIF-8 nanoparticles on SWCNTs/PES composite membrane was $4.3\\upmu\\mathrm{g}c\\dot{\\mathrm{m}}^{-2}$ . The pristine ZIF-8 nanoparticles have smooth and sharp boundaries, whereas the PD/ ZIF-8 nanoparticles, which are slightly larger, have rough and irregular boundaries due to the presence of the amorphous PD layer (see Supplementary Figure 3). The XRD spectroscopy reveals that the crystal structure of the ZIF-8 nanoparticles was unaffected by the PD coating (see Supplementary Figure 3). The thin PD coating was applied to improve the wetting property of ZIF-8 nanoparticles, which was confirmed by comparing the water CAs of different surfaces before and after modifications. Specifically, the CAs of the SWCNTs/PES composite membrane loaded with uncoated ZIF-8 nanoparticles and the SWCNTs/PES composite membrane loaded with PD/ZIF-8 nanoparticles were $53^{\\circ}$ and $36^{\\circ}$ , respectively (see Supplementary Figure 4). This result confirms that the PD layer effectively enhances the hydrophilicity of ZIF-8 nanoparticle. The improved hydrophilicity of the support layer could enhance interfacial polymerization reaction and consequently the quality of the PA layer (see Supplementary Figure 5, Supplementary Figure 6 and Supplementary Table 1). After interfacial polymerization on the PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane, the membrane was immersed into water to release the ZIF-8 nanoparticles. Figure $1\\mathrm{d-g}$ are SEM images of the membrane with different immersion time. Before immersed into water, the PD/ZIF-8 nanoparticles and SWCNTs film could be clearly observed under the PA layer, indicating the top PA layer was rather thin and transparent (Fig. 1d). The morphology of the PD/ZIF-8 nanoparticle was similar before and after interfacial polymerization reaction, which suggests that the PD/ZIF-8 nanoparticles were stable during the polymerization reaction (see Supplementary Figure 7). Immersion the membrane into water after polymerization promotes the gradual dissolution of the PD/ZIF-8 nanoparticles (Fig. 1e–g). As the dissolution process continued, the crumpled surface morphology started to emerge and became growingly prominent until the PD/ZIF-8 nanoparticles dissolved completely (Fig. 1g). The dissolution of ZIF-8 nanoparticles is ascribed to their instability in water at a low mass ratio of ZIF-8 to water31,32. A series of experiments were done to confirm such a dissolution mechanism. PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membranes were immersed into pure water, water containing 1 M Hmim and alkaline solution (pH: 13), respectively, for different time to observe whether the loaded PD/ZIF-8 nanoparticles dissolve or not. As shown in Supplementary Figure 8, the PD/ZIF-8 nanoparticles were quickly dissolved and totally disappeared after $10\\mathrm{min}$ when immersed the membrane in water. However, the PD/ZIF-8 nanoparticles could not dissolve at all in 1 M Hmim and alkaline solution even for a long immersing time up to $^{5\\mathrm{h}}$ (see Supplementary Figure 9). When the PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane after interfacial polymerization was immersed in $1\\mathrm{M}$ Hmim solution, no PD/ZIF-8 nanoparticles were dissolved (see Supplementary Figure 10). This is because the existence of either Hmim ligand or $\\mathrm{OH^{-}}$ in the immersion solution could effectively suppress the hydrolysis of ZIF-8. In addition, the surface morphology of the NF membrane prepared from the SWCNTs/PES composite membranes without nanoparticles and with residual PD on the surface were also examined for comparison. No crumpled structure was observed in these cases (see Supplementary Figure 11-13), confirming that the formation of crumpled structure in the presence of PD/ZIF-8 nanoparticles was indeed induced by the PD/ZIF-8 nanoparticles. \n\n![](images/748b03bda44f43e23c50d5d6e46de46f06571df92d1223f6533b1860779a9b09.jpg) \nFig. 1 Evolution process of PA NF membrane with crumpled structures. a A schematic illustration showing the preparation process of nanoparticlesinduced crumpled PA NF membrane. Top-view SEM images of b pristine SWCNTs/PES composite membrane, c PD/ZIF-8 nanoparticles loaded SWCNTs/ PES composite membrane. d–g Morphology change of the membrane immersed into water in different time after interfacial polymerization reaction on PD/ ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane (The scale bar of images is $1\\upmu\\mathrm{m}\\mathrm{;}$ . The PD/ZIF-8 nanoparticles loading mass is $4.3\\upmu\\upxi{\\mathsf{c m}}$ $^{-2}$ . (TMC trimesoyl chloride, PIP piperazine, SWCNTs single-wall carbon nanotubes, PD polydopamine) \n\n![](images/27171c29a511fbec2cad5635dae7f02347fe75eea9a509a741ef32dfb0b2194d.jpg) \nFig. 2 Morphology and chemical analysis of PA NF membranes. a, b AFM images (scale bar: $2\\upmu\\mathrm{m}\\dot{}$ ). c $\\mathsf{X P S}$ survey spectra. d Surface zeta potential of PA NF membranes prepared from SWCNTs/PES composite membrane without PD/ZIF-8 nanoparticles loading and PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane. The PD/ZIF-8 nanoparticles loading mass is $4.3\\upmu\\upxi{\\mathsf{c m}}^{-2}$ \n\nAFM was also applied to further evaluate the effect of PD/ZIF8 nanoparticles on the morphology of PA active layer. Because commercial PES membranes have relatively significant intrinsic larger-scale roughness that would eclipse the smaller-scale roughness of the active layer to be formed, commercial anodic aluminum oxide (AAO) membrane (average pore diameter: 0.2 $\\upmu\\mathrm{m})$ with a smooth surface, instead of the rough PES membrane, was used as the support layer for surface characterization using AFM. Following the same approach for fabricating the NF membrane with PES composite support, a thin SWCNTs film was deposited onto the AAO membrane as a composite support for interfacial polymerization. The AFM images of PA NF membranes prepared using this SWCNTs/AAO composite support without and with PD/ZIF-8 nanoparticles as the sacrificial template are shown in Fig. 2a, b, respectively. In the absence of PD/ZIF-8 nanoparticles, the PA NF membrane prepared using the SWCNTs/AAO composite membrane yields a relatively smooth surface with root mean square (RMS) roughness of $14.3\\mathrm{nm}$ (Fig. 2a), with the underlying SWCNTs film clearly observable through the active layer. In comparison, the PA NF membrane prepared using the SWCNTs/AAO composite membrane with PD/ZIF-8 nanoparticles forms a crumpled surface structure full of ridges, with an RMS roughness of $28.4\\mathrm{nm}$ (Fig. 2b). The thickness of crumpled PA layer was estimated by using focus ion beam-scanning electron microscope (FIB-SEM) technology (see Supplementary Figure 14). As shown in Supplementary Figure 14, the thickness of PA active layer is around $8{-}14\\mathrm{nm}$ . This value is similar to the thickness of PA layer prepared without PD/ZIF-8 nanoparticles as reported in our previous work28. The chemical composition of the PA active layers obtained thereby was analyzed by $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS). The XPS spectra of the two PA active layers, one formed with PD/ZIF-8 nanoparticles and the other without, suggest that they have the same chemical composition with equal abundance of C, N, and O (Fig. 2c). No Zn element was detected (the $Z\\mathrm{n}2p$ peak is usually centered at $1044.8\\mathrm{eV},$ ) in these spectra, confirming that all ZIF-8 nanoparticles were removed and no residual remained in the final PA active layer. Based on the O/N elemental ratio from the XPS spectra, the degrees of crosslinking of the PA active layers were calculated33,34. The degrees of crosslinking of PA active layers prepared from SWCNTs/PES composite support without and with PD/ZIF-8 nanoparticles loading are $77.6\\%$ and $60.3\\%$ , respectively (Table 1), suggesting that the presence of PD/ZIF-8 nanoparticles reduces the degree of crosslinking of the PA active layer. It is worth to noting that the crosslinking degree is still high, which ensures the rejection performance of PA NF. In addition, the MWCO of PA NF membranes prepared with and without PD/ZIF-8 nanoparticles loading was measured to investigate the effect of crosslinking degree. Our results show that the MWCO for PA NF membrane without PD/ZIF-8 is 400 and the MWCO for PA NF membrane with PD/ZIF-8 is 410 (see Supplementary Figure 15). It indicates that the two membranes have similar MWCO. \n\nThe C1s, O1s, and N1s peaks of the XPS spectra (see Supplementary Figure 16), which provide more detailed information of the chemical compositions of PA active layer, are summarized in Table 1. The fractions of carboxylic acid groups and unreacted amine groups in the PA active layer prepared with the PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite support were $19.5\\%$ and $6.3\\%$ , respectively; whereas the corresponding fractions of the PA active layer prepared using SWCNTs/PES composite membrane without PD/ZIF-8 nanoparticles were $13.4\\%$ and $5.4\\%$ , respectively. We also measured the zeta potential of the PA active layers due to its significant impact on solute rejection. The results suggest that the presence of PD/ZIF-8 nanoparticles, which drastically affects the morphology of the PA active layer, does not seem to have significant impact on the zeta potential of the PA active layer. Both PA active layers are negatively charged to a similar extent when $\\mathsf{p H}$ was above 3.5 (Fig. 2d). The PA active layers acquire very strong negative zeta potentials at neutral and high $\\mathsf{p H}$ , which is beneficial to the rejection of divalent or multivalent ions via the Donnan effect35–37. \n\n
Table1Surfacechemical components of PA NF membranes preparedfrom SWCNTs/PEScomposite membrane with and without PD/ZIF-8 nanoparticles loading
SamplesSurface chemical species from C1sCOOH (%) NH (%)
Without PD/ZIF-8B.E. (eV)SpeciesContent (%)Crosslinking degree (%)Contact angle (°)
284.8C-H/C-C57.5 13.45.477.642
With PD/ZIF-8286.0C-N31.1
287.9O-C=0/0-C=N11.2
284.8C-H/C-C54.36.360.341
286.0C-N 0-C=0/0-C=N19.5 33.7 12.0
\n\n![](images/0c4422bd16641c76b76a3c10619f5e2cbe5777eec307d167936591263002b30b.jpg) \nFig. 3 Influence of PD/ZIF-8 nanoparticles loading mass on crumple structure and membrane performance. SEM images of (a–d) PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane (scale bar: $1\\upmu\\mathrm{m})$ and $(\\bullet-h)$ corresponding PA NF membranes with different PD/ZIF-8 nanoparticles loading mass (scale bar: $1\\upmu\\mathrm{m})$ : (a, e) $0.9\\upmu\\upxi\\mathsf{c m}^{-2}$ ; (b, f) $2.2\\upmu\\upxi\\mathsf{c m}^{-2}$ ; (c, g) $4.3\\upmu\\upxi{\\mathsf{c m}}^{-2},$ and (d, h) $6.4\\upmu\\upxi\\mathsf{c m}^{-2}$ . i Surface area difference between PA NF membranes prepared from SWCNTs/PES composite membrane with and without PD/ZIF-8 nanoparticles loading as a function of different loading mass. j Flux and rejection of PA NF membranes prepared with different PD/ZIF-8 nanoparticles loading mass. $(N a_{2}S O_{4}$ concentration: 1000 ppm; applied pressure: 4 bar) \n\nEffect of loading mass and size of nanoparticles on crumple structure. The effect of loading mass and size of PD/ZIF-8 nanoparticles on the structure of PA active layer was also investigated in detail. Figure 3a–d show the SEM images of PD/ ZIF-8 nanoparticles loaded SWCNTs/PES composite support with the loading mass systematically increasing from $0.9\\upmu\\mathrm{g}\\dot{\\mathrm{cm}}^{-2}$ to $6.4\\upmu\\mathrm{g}c m^{-2}$ . The morphologies of the resulting PA active layers (Fig. 3e–h) suggest that more crumpled structure resulted from higher loading mass of PD/ZIF-8 nanoparticles. Based on their AFM images, we also compared the surface area (i.e., actual area per projected area) of the PA active layers prepared with different loading mass of PD/ZIF-8 nanoparticles (see Supplementary Figure 17), using a built-in function of the AFM software that estimates the surface area based on the tortuous paths the AFM tip travels under tapping mode. While such an approach for area estimation has its limitations (e.g., it cannot measure area of the down-facing regions), it nonetheless provides useful information for a semi-quantitative comparison to elucidate the impact of PD/ZIF-8 loading on enhancing the PA active layer area. Here, we compare the area difference between the PD/ZIF-8 templated PA active layer and PA active layer prepared without PD/ZIF-8, and express this area difference as a function of mass loading of PD/ZIF-8 nanoparticles (Fig. 3i). Such surface area differences for PA active layers with PD/ZIF-8 nanoparticles loading mass of $0.9\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ , $2.2\\upmu\\mathrm{g}c\\mathrm{m}^{-2}$ , and $4.3\\upmu\\mathrm{g}c\\mathrm{m}^{-2}$ were $10\\upmu\\mathrm{m}^{\\tilde{2}}$ , $20\\upmu\\mathrm{m}^{2}$ , and ${\\bar{2}}7\\upmu\\mathrm{m}^{2}$ , respectively, suggesting that surface area increases with increasing PD/ZIF-8 nanoparticles loading mass. However, further increasing the loading mass to $6.4\\upmu\\mathrm{gcm}$ −2 reduces the surface area difference to 19 μm2. NF experiments with $1000\\mathrm{ppm}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ solution suggests that the change of membrane flux positively correlates with the change in surface area, with only a slight compromise in salt rejection as the surface area increases (Fig. 3j). For example, with a PD/ZIF-8 mass loading of $4.3\\upmu\\mathrm{g}c\\bar{\\mathrm{m}}^{-2}$ , the permeating flux reaches a maximum of $214\\mathrm{\\overline{{l}}m}^{-2}\\mathrm{h}^{-1}$ , with the rejection of $\\bar{\\bf N}{\\bf a}_{2}\\mathrm{SO}_{4}$ slightly reduced to ${\\sim}95\\%$ . Interestingly, the measured percentage increase of permeance was more significant than the percentage increase of actual PA active layer area. One possible explanation is that the templated active layer has a weakened binding with the underlying support, which increases the fraction of highly permeable PA active layer compared to that prepared using a conventional non-templating approach. Hereafter, we chose to fix the PD/ZIF8 nanoparticle mass loading at $4.3\\upmu\\mathrm{g}c\\mathrm{m}^{-2}$ to prepare PA NF membranes for further comprehensive investigation, as such a loading yields the most permeable membrane with a satisfactory rejection. \n\nZIF-8 nanoparticles with other sizes, $\\sim30\\mathrm{nm}$ , ${\\sim}100\\mathrm{nm}$ , ${\\sim}200$ nm, and ${\\sim}400\\mathrm{nm}$ were also used to fabricate PA NF membrane with same loading mass as ZIF-8 nanoparticles of ${\\sim}150\\mathrm{nm}$ (see Supplementary Figure 18 and Supplementary Table 2). These PD/ ZIF-8 nanoparticles were loaded onto SWCNTs/PES composite membranes for interfacial polymerization, respectively. Supplementary Figure 19 shows that all PD/ZIF-8 nanoparticles were successfully dissolved and crumpled PA layer were achieved especially when the ZIF-8 nanoparticles larger than $30\\mathrm{nm}$ . With the increase of PD/ZIF-8 nanoparticle size, larger crumple structures were generated. The desalination performance of the corresponding PA NF membranes were tested (see Supplementary Figure 20). The permeating fluxes are 213, 200, and $2141\\mathrm{m}$ $^{-2}\\mathrm{h}^{-1}$ corresponding to the ZIF-8 nanoparticle size of 30, 100, and $150\\mathrm{nm}$ , respectively. Meanwhile, the corresponding rejections to $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ are 95, 96, and $95.3\\%$ , respectively. Further increasing the nanoparticles size to $200\\mathrm{nm}$ and $400\\mathrm{nm}$ , the corresponding permeating flux decreases to 157 and $1711\\mathrm{m}^{-2}\\mathrm{h}$ −1 with rejection of 92% and 95.7%, respectively. \n\nDesalination performance of PA NF membranes. The impacts of applied pressure on the permeate flux and salt rejection were also investigated using $1000\\mathrm{ppm}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ for both PA NF membranes with and without PD/ZIF-8 nanoparticles templating. For both membranes, the permeating fluxes increase proportionally with increasing applied pressure at low pressure range, but level off at higher pressure range due to concentration polarization (Fig. 4a)36,38. The PA NF membrane templated with PD/ZIF-8 nanoparticles exhibits higher fluxes than the membrane without PD/ZIF-8 nanoparticles templating throughout the whole pressure range, while they exhibit similar rejection rate to $\\bar{\\bf N}{\\bf a}_{2}\\mathrm{SO}_{4}$ . With increasing applied pressure, the rejection rates for both membranes decrease slightly from $97\\%$ at 2 bar to $92\\%$ at 6 bar. For the PA NF membrane prepared without PD/ZIF-8 template, the rejection rate was relatively independent of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ feed concentration, remaining ${\\sim}97\\%$ as the feed concentration increased from $1000\\mathrm{ppm}$ to $6000\\mathrm{ppm}$ . For PA NF membrane prepared with PD/ZIF-8 nanoparticles loading, the rejection rate decreased slightly from ${\\sim}97\\%$ at $1000\\mathrm{ppm}$ to ${\\sim}94\\%$ at $6000\\mathrm{ppm}$ (see Supplementary Figure 21). Filtration performance of our PA NF membrane with other salts was also evaluated (Fig. 4b). While the templated PA NF membrane exhibit similar permeating fluxes with all salts tested, the salt rejections for $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ and $\\mathrm{MgSO_{4}}$ are much higher than for $\\mathrm{MgCl}_{2}$ , $\\mathrm{CaCl}_{2}$ , and NaCl possibly due to the synergistic effect of strong Donnan exclusion and size sieving with the sulfate salts. The performance of the templated PA NF membrane is also stable over time. In experiments with $1000\\mathrm{ppm\\Na_{2}S O_{4}}$ feed solution and an applied pressure of 4 bar, no appreciable change of permeating flux and salt rejection was observed in continuous filtration up to a permeate volume per area of $360\\mathrm{ml}\\mathrm{cm}^{-2}$ (Fig. 4c). \n\n![](images/8adaa26f778ceb539d5c7a17b4432e6fe23e706a258095551546b012b977400e.jpg) \nFig. 4 Desalination performance of PA NF membranes. a Flux and rejection of the PA NF membranes prepared from the SWCNTs/PES composite membrane with and without PD/ZIF-8 nanoparticles loading with respect to applied pressure $(N a_{2}S O_{4}$ concentration: 1000 ppm). b Variation of flux and rejection of PA NF membranes prepared from PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane with respect to different salt solutions (salt concentration: 1000 ppm; applied pressure: 4 bar). c Variation of flux and rejection of PA NF membrane prepared from PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane as a function of permeating volume $\\langle N a_{2}S O_{4}$ concentration: 1000 ppm; applied pressure: 4 bar). d Summary of the filtration performance of the state-of-the-art NF membranes reported in literature in consideration of permeance and rejection for ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ \n\nThe NF performance in terms of permeance and salt rejection of our PD/ZIF-8 templated PA NF membrane is compared with the performance of the state-of-the-art NF membranes reported in literatures14,28–30,39–55 (Fig. 4d, Supplementary Figure 22 and Supplementary Ref. 1-21). The comparison suggests that the performance of templated PA NF membrane is, to a large extent, superior to all other membranes recently developed by others including thin film nanocomposite membranes39–42 (marked as green circle of 1–4 in Fig. 4d, see also Supplementary Ref. 1-4), 2D nanomaterials-assembled membranes43–46 (marked as purple triangle of 5–8 in Fig. 4d, see Supplementary Ref. 5-8), PA NF membranes prepared with various monomers47–51 (marked as orange rhombus of 9–13 in Fig. 4d, see Supplementary Ref. 9-13), membranes prepared with modification of support layers28–30,52,53 (marked as black square of 14–18 in Fig. 4d, see Supplementary Ref. 14-18), and commercial NF membrane (e.g., NF270 by Dow). The templated PA NF membrane shows several folds of increase in permeance compared to most other NF membranes, while maintaining a high salt rejection simultaneously. It is worth noting that a large applied pressure around 6 to 8 bar is usually required to operate with common NF membranes. However, the templated PA NF membrane developed in this work could be operated with a much lower applied pressure, e.g., generating a permeating flux of $90\\mathrm{lm}^{-2}\\mathrm{h}^{-1}$ with only 2 bar. To further demonstrate the role of PD/ZIF-8 nanoparticles as sacrificial template, a control experiment was done where water-stable UiO-66 MOF nanoparticles was synthesized and loaded onto the SWCNTs/PES composite membrane to fabricate PA NF membrane (see Supplementary Figure 23 and 24). Our results show that the introduction of PD/ UiO-66 nanoparticles on the SWCNTs/PES composite membrane could improve the flux of the resulting PA NF membrane also at a certain extent (see Supplementary Figure 25). A maximum permeance of $\\dot{3}6.71\\mathrm{m}^{-2}\\mathrm{h}^{-1}\\mathrm{bar}^{-1}$ meanwhile a rejection of ${\\sim}97\\%$ for $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ at the nanoparticles loading mass of $8.6\\upmu\\up g\\up c\\mathrm{m}$ $^{-2}$ was achieved (marked as UiO-66 in Fig. 4d). This permeance is slightly higher than the PA NF membrane prepared from SWCNTs/PES composite membrane without nanoparticles loading, but still much lower than that of PA NF membrane prepared from PD/ZIF-8 nanoparticles. It confirms that the crumple structure is beneficial to the increase of available area for water permeation. \n\n# Discussion \n\nWe described above the use of ZIF-8 nanoparticle as sacrificial template to induce the formation of crumpled structure on PA NF membrane. The results reveal that the geometric structure of ZIF-8 nanoparticles provides a rough surface structure on support layer and dominates the formation of the crumpled structure. From this point of view, other kinds of nanoparticles those can be easily removed by mild post-treatment can also be used as sacrificial template instead of ZIF-8 nanoparticle. Here, ZIF-67 nanoparticles $300{-}500\\mathrm{nm}$ in diameter) and calcium carbonate $\\mathrm{(CaCO_{3})}$ nanoparticles ( ${\\sim}100\\mathrm{nm}$ in diameter) were chosen as sacrificial nanomaterials. Our results show that the crumpled PA layers could also be obtained as shown in Supplementary Figure 26 and 27. The permeating flux of the two membranes are $\\mathrm{183}\\mathrm{lm}^{-2}\\mathrm{h}^{-1}$ for PD/ ZIF-67 nanoparticles loading and $191\\mathrm{lm}^{-2}\\mathrm{h}^{-1}$ for ${\\mathrm{PD}}/{\\mathrm{CaCO}}_{3}$ nanoparticles loading, with $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ rejection of 97.2 and $96.5\\%$ , respectively (see Supplementary Table 3). These values are still much higher than that of the membrane without nanoparticles loading. These results indicate that other soluble nanoparticles could also be used as sacrificial template to play the same role as ZIF-8 nanoparticles. \n\nOverall, we have developed a strategy to design sacrificial nanoparticles templated PA NF membranes with unprecedentedly high permeance and a satisfactorily high rejection for desalination. The nanoparticles, preloaded to the SWCNTs/PES support, acted as a sacrificial template to create a PA active layer with extensive crumpled surface morphology, which consequently yielded a higher specific surface area and a larger fraction of highly permeable PA skin layer. The morphology of the crumpled surface and the surface area of PA active layer can be fine-tuned by controlling the loading mass and particle size of sacrificial nanoparticles. As a result, an ultrahigh permeance, up to 53.5 l $\\mathrm{m}^{-2}\\mathrm{\\dot{h}^{-1}\\mathrm{bar}^{-1}}$ , together with a reasonably high rejection of $95.3\\%$ was achieved for a feed solution of $1000\\mathrm{ppmNa}_{2}\\mathrm{SO}_{4}$ when PD/ZIF-8 was used as sacrificial template. This work provides a strategy to design TFC membrane with extremely high permeance that is radically different from those by modifying the molecular structure of the active layer, which could only achieve a higher permeance at the cost of comprising rejection. An NF membrane with ultrahigh permeance and reasonably high salt rejection is very promising for more energetically and kinetically efficient treatment of low-salinity water, which has great potential in advancing brackish groundwater desalination, water softening, household RO/NF, and wastewater reuse. In consideration of the easy and scalable synthesis process of various nanoparticles, the use of them as sacrificial nanomaterials should be feasible for scaling up the resulting PA NF membranes. From the practical application viewpoint, one of the main issue is to develop more effective technology for nanoparticle loading to replace the present filtration based deposition process. \n\n# Methods \n\nGeneral. Materials used in this work and detailed synthesis of PD decorated nanoparticles, such as PD/ZIF-8, PD/ZIF-67, $\\mathrm{PD/CaCO_{3}}$ and PD/UiO-66, have been shown as Materials and Synthesis in Supplementary methods. \n\nPreparation of SWCNTs/PES composite membrane. PD/SWCNTs dispersion was prepared as follows: $20\\mathrm{mg}$ SWCNT and $200\\mathrm{mg}$ sodium dodecyl benzene sulfonate was added into $200\\mathrm{ml}$ deionized water and sonicated for $36\\mathrm{h}$ by using ultrasonic cleaning machine with $300\\mathrm{W}$ power. The SWCNT dispersion was then centrifuged for $30\\mathrm{min}$ at $10,000\\mathrm{rpm}$ and $150\\mathrm{ml}$ supernatant was collected. The $150\\mathrm{ml}$ supernatant was diluted into $300\\mathrm{ml}$ by using pure water and $30\\mathrm{mg}$ dopamine was then added into it. After stirring for $^{\\textrm{1h}}$ at $40^{\\circ}\\mathrm{C},$ $30\\mathrm{ml}0.1\\mathrm{\\bar{mol}l^{-1}}$ Tris buffer $\\mathrm{(pH~}8.5\\mathrm{)}$ was added into the system to further react for $36\\mathrm{h}$ at $40^{\\circ}\\mathrm{C}$ . The obtained PD/SWCNT dispersion was centrifuged for $30\\mathrm{min}$ at $10,000\\mathrm{rpm}$ , the supernatant was collected and preserved at $4^{\\circ}\\mathrm{C}$ . The SWCNTs/PES composite membrane was prepared by depositing the PD/SWCNTs onto PES microfiltration membrane via vacuum filtration process according to our previously report56,57. Specifically in this work, a certain amount of collected PD/SWCNTs supernatant was diluted by 40 times with ethanol and vacuum-filtrated onto PES microfiltration membrane at $0.02\\mathrm{MPa}$ vacuum pressure. The resulting density of PD/SWCNTs on PES microfiltration membrane is $5\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ . \n\nPreparation of nanoparticles loaded SWCNTs/PES composite membrane. PD/ ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane was prepared as follows: Taking $4.3\\upmu\\mathrm{g}c\\mathrm{m}^{-2}$ loading mass as an example, $1\\mathrm{ml}0.05\\mathrm{m}\\dot{\\mathrm{g}}\\mathrm{m}\\dot{\\mathrm{l}}^{-1}\\mathrm{PD}/$ \n\nZIF-8 nanoparticles dispersion was diluted to $50\\mathrm{ml}$ with ethanol and then deposited onto a $11.6\\mathrm{cm}^{2}$ SWCNTs/PES composite membrane via vacuum filtration at $0.02\\mathrm{MPa}$ . After dried at $60^{\\circ}\\mathrm{C}$ for $2\\mathrm{min}$ , PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane was obtained. PD/UiO-66 nanoparticles loaded SWCNTs/PES composite membrane, PD/ZIF-67 nanoparticles loaded SWCNTs/PES composite membrane, and $\\mathrm{PD/CaCO_{3}}$ nanoparticles loaded SWCNTs/PES composite membrane were all prepared in the same procedure as PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membrane with same loading mass. As for the PD/ZIF-8 nanoparticles loaded SWCNTs/PES composite membranes with different PD/ZIF-8 nanoparticles loading mass, different volumes of $0.05\\mathrm{mg}\\mathrm{ml}^{-1}$ PD/ZIF-8 nanoparticles dispersion were used: $0.21\\mathrm{ml}$ for achieving $\\mathsf{0.9}\\upmu\\mathrm{gcm}^{-2}$ , $0.51\\mathrm{ml}$ for achieving $2.2\\upmu\\mathrm{g}c m^{-2}$ , and $1.49\\mathrm{ml}$ for achieving $6.4\\upmu\\mathrm{g}c\\mathrm{m}^{-2}$ . \n\nInterfacial polymerization. Interfacial polymerization was conducted at $25^{\\circ}\\mathrm{C}$ and relative humidity of about $60\\%$ . In a typical procedure, a piece of nanoparticles loaded SWCNTs/PES composite membrane was put onto a glass plate where a few drops of PIP aqueous solution $(\\sim0.5\\mathrm{ml})$ was preloaded. An aliquot of $2\\mathrm{ml}$ aqueous solution containing $2.5\\mathrm{mg}\\mathrm{ml}^{-1}$ PIP and $0.{\\dot{7}}5\\mathrm{mg}\\mathrm{ml}^{-1}$ polyvinyl pyrrolidone (K30) was dropped onto the membrane and stood for $30\\mathrm{{s}}$ . The excess PIP solution was removed by drained glass plate vertically in air until no obvious water spot can be observed on the membrane. An aliquot of $2\\mathrm{ml}$ hexane containing $2\\mathrm{mg}\\mathrm{ml}^{-1}$ TMC was then dropped onto the above wetted membrane where the edge of the membrane was sealed by a filter cup and stood for $30\\mathrm{s}.$ . After removing the excess TMC solution, the membrane was immersed into hexane for $30\\mathrm{{s}}$ to remove unreacted TMC and then oven-cured at $60^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ to obtain PA NF membrane. In order to remove nanoparticles, the obtained PA NF membrane was immersed in water in a prescribed time and then washed by water for three to five times. The resulting membrane was stored in water at $4^{\\circ}\\mathrm{C}$ for use. \n\nCharacterization. SEM images were taken from a Hitachi S4800 cold fieldemission scanning electron microscopy. TEM images were acquired from a FEI Tecnai G2 F20 S-TWIN 200KV field-emission transmission electron microscopy. AFM images were obtained in tapping mode of a Bruker Dimension Icon atomic force microscopy. XRD was tested by a Bruker AXS D8 Advance powder X-Ray diffractomer. Surface Zeta potential was tested on an Anton Paar Surpass solid surface analysis. Water CA was measured on a Data-Physics OCA 20 with $2\\upmu\\mathrm{l}$ water droplet. XPS was taken from a Thermo Fisher Scientific ESCALAB 250Xi XRay photoelectron spectrometer. Total organic carbon (TOC) was detected by OI Analytical Aurora Model 1030. FIB-SEM images were obtained from a FEI fieldemission type scanning electron microscope equipped with focus ions beam device (Scios). \n\nThe effective membrane pore size of membranes were determined by filtration of a group of polyethylene glycol (PEG) molecules with different molecular weights (200, 400, 600, and 1000 Da, respectively)58. An aliquot of $200\\mathrm{ppm}$ PEG aqueous solutions were used as feed solutions to permeate the membrane at applied pressure of 4 bar. Rejection was calculated from the contents of TOC of feed and filtrate solutions, respectively, as obtained by a TOC Analyzer. MWCO was obtained according to the molecular weight where the rejection is $90\\%$ . Stokes radius of PEG can be calculated according to its average molecular weight based on the following equation (Eq. 1): \n\n$$\nr_{\\mathrm{p}}=16.73\\times10^{-12}\\times M^{0.557}\n$$ \n\nwhere $M$ is molecular weight of solutes, and $r_{\\mathrm{p}}$ is the Stokes radius. \n\nMembrane performance test. A cross-flow NF apparatus with a separation area of $7.1\\mathrm{cm}^{2}$ was used to test the membrane performance at room temperature. Rejection was calculated from conductivity of feed and filtrate solutions using Eq. (2), where $C_{\\mathrm{f}}$ and $C_{\\mathrm{p}}$ represent conductivity of feed solution and permeate, respectively. \n\n$$\nR=\\bigl(1-\\frac{C_{\\mathrm{p}}}{C_{\\mathrm{f}}}\\bigr)\\times100\\%\n$$ \n\nFlux $J$ is determined by Eq. (3), where $\\Delta w$ is weight increase of permeate during filtration time $\\Delta t,A$ is the separation area of the cell, $\\rho$ is density of permeate and we here consider it to be $1\\mathrm{g}\\mathrm{ml}^{-1}$ because its low salt concentration. \n\n$$\nJ=\\frac{\\Delta w}{\\rho\\mathrm{A}\\Delta t}\n$$ \n\nHere, Permeance is defined as flux per unit applied pressure, see in Eq (4), where $\\Delta P$ is the applied transmembrane pressure for filtration experiment. \n\n$$\n{\\mathrm{Permeance}}={\\frac{J}{\\Delta P}}\n$$ \n\nData availability. The authors declare that all of the data supporting the finding of this study are available within the paper and supplementary information and also are available from the corresponding author upon reasonable request. \n\n# Received: 7 November 2017 Accepted: 10 April 2018 Published online: 21 May 2018 \n\n# References \n\n1. Mekonnen, M. M. & Hoekstra, A. Y. Four billion people facing severe water scarcity. Sci. Adv. 2, e1500323 (2016). \n2. Haddeland, I. et al. Global water resources affected by human interventions and climate change. Proc. Natl Acad. Sci. USA 111, 3251–3256 (2014). \n3. Werber, J. R., Osuji, C. O. & Elimelech, M. Materials for next-generation desalination and water purification membranes. Nat. Rev. Mater. 1, 16018 (2016). \n4. Gu, J. E. et al. Molecular layer‐by‐layer assembled thin‐film composite membranes for water desalination. Adv. Mater. 25, 4778–4782 (2013). \n5. Elimelech, M. & Phillip, W. A. The future of seawater desalination: energy, technology, and the environment. Science 333, 712–717 (2011). \n6. Petersen, R. J. Composite reverse osmosis and nanofiltration membranes. J. Membr. Sci. 83, 81–150 (1993). \n7. Hilal, N., Al-Zoubi, H., Darwish, N. A., Mohamma, A. W. & Abu Arabi, M. A comprehensive review of nanofiltration membranes:Treatment, pretreatment, modelling, and atomic force microscopy. Desalination 170, 281–308 (2004). \n8. Mohammad, A. W. et al. Nanofiltration membranes review: recent advances and future prospects. Desalination 356, 226–254 (2015). \n9. Efligenir, A. et al. Decontamination of polluted discharge waters from surface treatment industries by pressure-driven membranes: removal performances and environmental impact. Chem. Eng. J. 258, 309–319 (2014). \n10. Van der Bruggen, B. & Vandecasteele, C. Removal of pollutants from surface water and groundwater by nanofiltration: overview of possible applications in the drinking water industry. Environ. Pollut. 122, 435–445 (2003). \n11. Lau, W. J., Ismail, A. F., Misdan, N. & Kassim, M. A. A recent progress in thin film composite membrane: a review. Desalination 287, 190–199 (2012). \n12. Lianchao, L., Baoguo, W., Huimin, T., Tianlu, C. & Jiping, X. A novel nanofiltration membrane prepared with PAMAM and TMC by in situ interfacial polymerization on PEK-C ultrafiltration membrane. J. Membr. Sci. 269, 84–93 (2006). \n13. Subramanian, S. & Seeram, R. New directions in nanofiltration applications — are nanofibers the right materials as membranes in desalination? Desalination 308, 198–208 (2013). \n14. Yoon, K., Hsiao, B. S. & Chu, B. High flux nanofiltration membranes based on interfacially polymerized polyamide barrier layer on polyacrylonitrile nanofibrous scaffolds. J. Membr. Sci. 326, 484–492 (2009). \n15. Qiu, W.-Z., Zhong, Q.-Z., Du, Y., Lv, Y. & Xu, Z.-K. Enzyme-triggered coatings of tea catechins/chitosan for nanofiltration membranes with high performance. Green Chem. 18, 6205–6208 (2016). \n16. Jimenez-Solomon, M. F., Song, Q., Jelfs, K. E., Munoz-Ibanez, M. & Livingston, A. G. Polymer nanofilms with enhanced microporosity by interfacial polymerization. Nat. Mater. 15, 760–767 (2016). \n17. Villalobos, L. F., Huang, T. & Peinemann, K. V. Cyclodextrin films with fast solvent transport and shape‐selective permeability. Adv. Mater. 29, 1606641 (2017). \n18. Qian, H., Zheng, J. & Zhang, S. Preparation of microporous polyamide networks for carbon dioxide capture and nanofiltration. Polymer 54, 557–564 (2013). \n19. Sorribas, S., Gorgojo, P., Tellez, C., Coronas, J. & Livingston, A. G. High flux thin film nanocomposite membranes based on metal-organic frameworks for organic solvent nanofiltration. J. Am. Chem. Soc. 135, 15201–15208 (2013). \n20. Jeong, B.-H. et al. Interfacial polymerization of thin film nanocomposites: a new concept for reverse osmosis membranes. J. Membr. Sci. 294, 1–7 (2007). \n21. Chan, W.-F. et al. Zwitterion functionalized carbon nanotube/polyamide nanocomposite membranes for water desalination. ACS Nano 7, 5308–5319 (2013). \n22. Ma, H., Burger, C., Hsiao, B. S. & Chu, B. Highly permeable polymer membranes containing directed channels for water purification. ACS Macro Lett. 1, 723–726 (2012). \n23. Karan, S., Samitsu, S., Peng, X., Kurashima, K. & Ichinose, I. Ultrafast viscous permeation of organic solvents through diamond-like carbon nanosheets. Science 335, 444–447 (2012). \n24. Gorgojo, P. et al. Ultrathin polymer films with intrinsic microporosity: anomalous solvent permeation and high flux membranes. Adv. Funct. Mater. 24, 4729–4737 (2014). \n25. Peng, X., Jin, J., Nakamura, Y., Ohno, T. & Ichinose, I. Ultrafast permeation of water through protein-based membranes. Nat. Nanotechnol. 4, 353–357 (2009). \n26. Striemer, C. C., Gaborski, T. R., McGrath, J. L. & Fauchet, P. M. Charge- and size-based separation of macromolecules using ultrathin silicon membranes. Nature 445, 749–753 (2007). \n27. Karan, S., Jiang, Z. & Livingston, A. G. Sub–10 nm polyamide nanofilms with ultrafast solvent transport for molecular separation. Science 348, 1347–1351 (2015). \n28. Zhu, Y. et al. Single-walled carbon nanotube film supported nanofiltration membrane with a nearly $10\\ \\mathrm{nm}$ thick polyamide selective layer for high-flux and high-rejection desalination. Small 12, 5034–5041 (2016). \n29. Wu, M.-B. et al. Thin film composite membranes combining carbon nanotube intermediate layer and microfiltration support for high nanofiltration performances. J. Memb. Sci. 515, 238–244 (2016). \n30. Wang, J.-J., Yang, H.-C., Wu, M.-B., Zhang, X. & Xu, Z.-K. Nanofiltration membranes with cellulose nanocrystals as an interlayer for unprecedented performance. J. Mater. Chem. A 5, 16289–16295 (2017). \n31. Zhang, H., Liu, D., Yao, Y., Zhang, B. & Lin, Y. S. Stability of ZIF-8 membranes and crystalline powders in water at room temperature. J. Membr. Sci. 485, 103–111 (2015). \n32. Liu, X. et al. Improvement of hydrothermal stability of zeolitic imidazolate frameworks. Chem. Commun. 49, 9140–9142 (2013). \n33. Tang, C. Y., Kwon, Y.-N. & Leckie, J. O. Effect of membrane chemistry and coating layer on physiochemical properties of thin film composite polyamide RO and NF membranes: I. FTIR and XPS characterization of polyamide and coating layer chemistry. Desalination 242, 149–167 (2009). \n34. Tang, C., Kwon, Y. & Leckie, J. Probing the nano- and micro-scales of reverse osmosis membranes—a comprehensive characterization of physiochemical properties of uncoated and coated membranes by XPS, TEM, ATR-FTIR, and streaming potential measurements. J. Membr. Sci. 287, 146–156 (2007). \n35. Bowen, W. R. & Welfoot, J. S. Modelling the performance of membrane nanofiltration—critical assessment and model development. Chem. Eng. Sci. 57, 1121–1137 (2002). \n36. Baker, R. W. in Membrane Technology and Application 2nd edn, Vol. 8 (Wiley Online Library, Hoboken, NJ, USA, 2004). \n37. Van der Bruggen, B., Schaep, J., Wilms, D. & Vandecasteele, C. Influence of molecular size, polarity and charge on the retention of organic molecules by nanofiltration. J. Membr. Sci. 156, 29–41 (1999). \n38. Wang, J. et al. A critical review of transport through osmotic membranes. J. Membr. Sci. 454, 516–537 (2014). \n39. Hu, D., Xu, Z.-L. & Chen, C. Polypiperazine-amide nanofiltration membrane containing silica nanoparticles prepared by interfacial polymerization. Desalination 301, 75–81 (2012). \n40. Wu, H., Tang, B. & Wu, P. Optimizing polyamide thin film composite membrane covalently bonded with modified mesoporous silica nanoparticles. J. Membr. Sci. 428, 341–348 (2013). \n41. Zheng, J. et al. Sulfonated multiwall carbon nanotubes assisted thin-film nanocomposite membrane with enhanced water flux and anti-fouling property. J. Membr. Sci. 524, 344–353 (2017). \n42. Tang, Y.-J., Xu, Z.-L., Huang, B.-Q., Wei, Y.-M. & Yang, H. Novel polyamide thin-film composite nanofiltration membrane modified with poly (amidoamine) and SiO 2 gel. RSC Adv. 6, 45585–45594 (2016). \n43. Bano, S., Mahmood, A., Kim, S.-J. & Lee, K.-H. Graphene oxide modified polyamide nanofiltration membrane with improved flux and antifouling properties. J. Mater. Chem. A 3, 2065–2071 (2015). \n44. Han, Y., Xu, Z. & Gao, C. Ultrathin graphene nanofiltration membrane for water purification. Adv. Funct. Mater. 23, 3693–3700 (2013). \n45. Xu, X.-L. et al. Graphene oxide nanofiltration membranes stabilized by cationic porphyrin for high salt rejection. ACS Appl. Mater. Interfaces 8, 12588–12593 (2016). \n46. Han, Y.., Jiang, Y.., & Gao, C.. High-flux graphene oxide nanofiltration membrane intercalated by carbon nanotubes. ACS Appl. Mater. Interfaces 7, 8147–8155 (2015). \n47. Chen, G. E. et al. Preparation and characterization of a composite nanofiltration membrane from cyclen and trimesoyl chloride prepared by interfacial polymerization. J. Appl. Polym. Sci. 132, 42345 (2015). \n48. Chen, G.-E. et al. Fabrication and characterization of a novel nanofiltration membrane by the interfacial polymerization of 1, 4-diaminocyclohexane (DCH) and trimesoyl chloride (TMC). RSC Adv. 5, 40742–40752 (2015). \n49. Tang, Y.-J., Wang, L.-J., Xu, Z.-L., Wei, Y.-M. & Yang, H. Novel high-flux thin film composite nanofiltration membranes fabricated by the NaClO preoxidation of the mixed diamine monomers of PIP and BHTTM in the aqueous phase solution. J. Membr. Sci. 502, 106–115 (2016). \n50. Pan, Y. et al. Enhanced both perm-selectivity and fouling resistance of poly (piperazine-amide) nanofiltration membrane by incorporating sericin as a coreactant of aqueous phase. J. Membr. Sci. 523, 282–290 (2017). \n51. Tang, Y.-J., Xu, Z.-L., Xue, S.-M., Wei, Y.-M. & Yang, H. A chlorine-tolerant nanofiltration membrane prepared by the mixed diamine monomers of PIP and BHTTM. J. Membr. Sci. 498, 374–384 (2016). \n52. Yang, X., Du, Y., Zhang, X., He, A. & Xu, Z. K. Nanofiltration membrane with a mussel-inspired interlayer for improved permeation performance. Langmuir 33, 2318–2324 (2017). \n53. Soyekwo, F. et al. Cellulose nanofiber intermediary to fabricate highlypermeable ultrathin nanofiltration membranes for fast water purification. J. Membr. Sci. 524, 174–185 (2017). \n54. An, Q.-F., Sun, W.-D., Zhao, Q., Ji, Y.-L. & Gao, C.-J. Study on a novel nanofiltration membrane prepared by interfacial polymerization with zwitterionic amine monomers. J. Membr. Sci. 431, 171–179 (2013). \n55. Chiang, Y.-C., Hsub, Y.-Z., Ruaan, R.-C., Chuang, C.-J. & Tung, K.-L. Nanofiltration membranes synthesized from hyperbranched polyethyleneimine. J. Membr. Sci. 326, 19–26 (2009). \n56. Gao, S. J., Zhu, Y. Z., Zhang, F. & Jin, J. Superwetting polymer-decorated SWCNT composite ultrathin films for ultrafast separation of oil-in-water nanoemulsions. J. Mater. Chem. A 3, 2895–2902 (2015). \n57. Hu, L. et al. Photothermal-responsive single-walled carbon nanotube-based ultrathin membranes for on/off switchable separation of oil-in-water nanoemulsions. ACS Nano 9, 4835–4842 (2015). \n58. Lin, J. et al. Tight ultrafiltration membranes for enhanced separation of dyes and $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ during textile wastewater treatment. J. Membr. Sci. 514, 217–228 (2016). \n\n# Acknowledgements \n\nThis work was financially supported by the National Natural Science Funds for Distinguished Young Scholar (51625306), the Key Project of National Natural Science Foundation of China (21433021), Joint Research Fund for Overseas Chinese, Hong Kong and Macao Scholars (21728602), and the National Natural Science Foundation of China (51603229, 21406258), the Natural Science Foundation of Jiangsu Province (BE2015072). We would like to thank Dr. Liu and the Vacuum Interconnected Nanotech Workstation of Suzhou Institute of Nano-Tech and Nano-Bionics for FIB-SEM characterization. \n\n# Author contributions \n\nY.Z. and J.J. conceived the idea and designed the research. Zhen.W. carried out the experiment. S.G. helped the synthesis of PD/SWCNTs. Z.W. performed the surface zeta potential measurement. S.L. provided constructive suggestion and discussion. All authors participated in discussion. Y.Z., Zhen.W., S.L., and J.J. co-wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-04467-3. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1021_jacs.7b10647", + "DOI": "10.1021/jacs.7b10647", + "DOI Link": "http://dx.doi.org/10.1021/jacs.7b10647", + "Relative Dir Path": "mds/10.1021_jacs.7b10647", + "Article Title": "Bidentate Ligand-Passivated CsPbI3 Perovskite nullocrystals for Stable Near-Unity Photoluminescence Quantum Yield and Efficient Red Light-Emitting Diodes", + "Authors": "Pan, J; Shang, YQ; Yin, J; De Bastiani, M; Peng, W; Dursun, I; Sinatra, L; El-Zohry, AM; Hedhili, MN; Emwas, AH; Mohammed, OF; Ning, ZJ; Bakr, OM", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Although halide perovskite :nullocrystals (NCs) are promising materials for optoelectronic devices, they suffer severely from chemical and phase instabilities. Moreover, the common capping'.ligands like oleic acid and oleylamine that encapsulate the NCs will form an insulating layer, precluding their futility in optoelectronic devices. To overcome these limitations, we develop a postsynthesis passivation process for CsPbI3 NCs by using a bidentate ligand, namely 2,2'-iminodibenzoic acid. Our passivated NCs exhibit narrow red photoluminescence with exceptional quantum yield (close to unity) and substantially improved stability. The passivated NCs enabled us to realize red light-emitting diodes (LEDs) with 5.02% external quantum efficiency and 748 cd/m(2) luminullce, surpassing by far LEDs made from the nonpassivated NCs.", + "Times Cited, WoS Core": 790, + "Times Cited, All Databases": 826, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000423012600009", + "Markdown": "# Bidentate Ligand-passivated CsPbI3 Perovskite Nanocrystals for Stable Near-unity Photoluminescence Quantum Yield and Efficient Red Light-emitting Diodes \n\nJun Pan, Yuequn Shang, Jun Yin, Michele De Bastiani, Wei Peng, Ibrahim Dursun, Lutfan Sinatra, Ahmed M. El-Zohry, Mohamed N. Hedhili, Abdul-Hamid Emwas, Omar F. Mohammed, Zhijun Ning, and Osman M. Bakr \n\nJ. Am. Chem. Soc., Just Accepted Manuscript $\\cdot$ DOI: 10.1021/jacs.7b10647 $\\cdot$ Publication Date (Web): 17 Dec 2017 \n\nDownloaded from http://pubs.acs.org on December 17, 2017 \n\n# Just Accepted \n\n“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier $(\\mathsf{D O}|\\oplus)$ . “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts. \n\n# Bidentate Ligand-passivated $\\mathbf{Cs}\\mathbf{Pb}\\mathbf{I}_{3}$ Perovskite Nanocrystals for Stable Near-unity Photoluminescence Quantum Yield and Efficient Red Light-emitting Diodes \n\nJun Pan,†#• Yuequn Shang,‡• Jun Yin,† Michele De Bastiani,† Wei Peng,† Ibrahim Dursun,†# Lutfan Sinatra,† Ahmed M. El-Zohry,# Mohamed N. Hedhili,§ Abdul-Hamid Emwas,§ Omar F. Mohammed,† Zhijun Ning,\\*,‡ and Osman M. Bakr\\*,†# \n\n† King Abdullah University of Science and Technology (KAUST), KAUST Catalysis Center (KCC), #KAUST Solar Center (KSC), Division of Physical Science and Engineering (PSE), § Imaging and Characterization Laboratory, Thuwal 23955, Saudi Arabia. ‡ School of Physical Science and Technology, ShanghaiTech University, 100 Haike Road, Shanghai 201210, China \n\nSupporting Information Placeholder \n\nABSTRACT: Although halide perovskite nanocrystals (NCs) are promising materials for optoelectronic devices, they suffer severely from chemical and phase instabilities. Moreover, the common capping ligands like oleic acid and oleylamine that encapsulate the NCs will form an insulating layer, precluding their utility in optoelectronic devices. To overcome these limitations, we develop a post-synthesis passivation process for $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ NCs by using a bidentate ligand, namely $^{2,2^{\\prime}}$ -Iminodibenzoic acid. Our passivated NCs exhibit narrow red photoluminescence with exceptional quantum yield (close to unity) and substantially improved stability. The passivated NCs enabled us to realize red light-emitting diodes (LEDs) with $5.02\\%$ external quantum efficiency and $748\\ \\mathrm{cd}/\\mathrm{m}^{2}$ luminance, surpassing by far LEDs made from the non-passivated NCs. \n\nThe development of solution-processed halide perovskites has disrupted the global roadmap of semiconductors.1-4 While research on halide perovskites was solely motivated by solar cell technologies, it has quickly grown to encompass the whole optoelectronic research community. The use of all-inorganic cesium lead halide perovskite $\\mathrm{(Cs{Pb}{X_{3}}}$ , $\\Chi=\\mathbf{C}\\mathbf{l}$ , Br, and I) nanocrystals (NCs) exhibiting high photoluminescence quantum yields (PLQY), narrow emission,6 and tunable absorption/emission wavelengths7 has accelerated the emergence and development of perovskite-based nanomaterials for applications such as light-emitting diodes (LED),8-10 solar cells,11 lasers, 1 2 photodetectors, and visible-light communication.14 \n\nSince the first reported synthesis of nearly monodispersed $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs using a hot-injection approach,15 many efforts have been expended on optimizing NC synthesis procedures to facilitate the fabrication of \n\nLEDs.8-10 Despite significant advancements in the development of LEDs based on perovskite NCs,16-18 especially for green LEDs for which external quantum efficiencies (EQE) have exceeded $10\\%$ ,19 device performances are still far from meeting application requirements, particularly when red LEDs are needed A common issue is the intrinsic chemical instability of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs due to the dynamic nature of the bonding between the inorganic surface and the long-chain capping ligands. 23-26 Furthermore, common capping ligands like oleylamine (OAm) and oleic acid (OA) act as electrically insulating layers on the NC’s surface which hinder significantly charge carrier injection and transport at the interface of the ensuing device. To add to this list of challenges afflicting perovskites, $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}\\mathrm{NCs}$ in particular suffer from a non-perovskite phase transition at room temperature.27 While recent efforts have led to considerable stabilization of iodide perovskite NCs,11, 28-29 there is still a critical need for a NC passivation strategy that combines stability and high PLQY with surface ligands that are compatible with the charge transport requirements of LEDs and optoelectronic applications in general.30 \n\nIn this communication, we explore a bidentate ligand, namely 2,2’-Iminodibenzoic acid (IDA, Figure 1a), to passivate the NC surface. Theoretical calculations (vide infra) show much stronger bonding between the pervoskite surface and this ligand in comparison to OA. The IDA-treated NCs display a PLQY of over $95\\%$ (much higher than untreated NCs), significantly enhanced stability in the desired cubic perovskite phase, as well as enhanced electronic coupling between ligands and NCs. As a result, we were able to fabricate red LEDs with broadly superior characteristics (i.e., twofold higher EQE and luminescence intensity) to those of LEDs based on pristine NCs. \n\n![](images/8b98432057b8701c98e2a66ddc24104b77a6f15c9657aa57509fd7880de33ddd.jpg) \nFigure 1. a) Molecular structure of OA (1), and IDA (2) ligands. b) Low- and high- c) magnification TEM images of untreated QDs. d) Low- and high- e) magnification SEM images for IDA-treated NCs. (f) Powder XRD patterns of untreated (blue) and IDA-treated NCs (red). (g) Absorption and PL spectra for untreated (blue) and IDA-treated NCs (red) from equimolar concentrated solutions, with the relative PL quantum yield in the inset. \n\n$\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ perovskite NCs were synthesized following a well-established synthesis process with minor modificaitons11, 31 (see SI for details). The purified NCs (labelled as “untreated” NCs) had a cubic shape with an average dimension of $13.6{\\pm}2.9\\ \\mathrm{nm}$ (Figure S1a) determined by high-resolution transmission electron microscopy (HRTEM) (Figure 1b). Passivated NCs were obtained by adding a small amount of IDA powder directly into a solution of untreated NCs (see SI for details). After treatment, the excess IDA was removed by centrifugation. The IDA-treated NCs were cubic shaped (Figure 1d) with an average size of $12{\\pm}1.5~\\mathrm{nm}$ (Figure S1b). It should be noted that the particles are easily aggregated if IDA is used directly in the synthesis (Figure S2). Both the untreated and treated NCs have a lattice distance of $0.31~\\mathrm{nm}$ , corresponding to the (200) crystal plane of the cubic phase perovskite (Figure 1c and 1e), suggesting that the crystal structure remained unchanged during treatment process, which was further confirmed by Xray diffraction (XRD, Figure 1f). \n\nHowever, significant changes in optical properties were observed. With IDA treatment, PLQY increased to near unity $(95\\pm2\\%)$ compared with that of the untreated NCs $(80\\pm5\\%)$ . Accompanying the rise in PLQY, PL emission retained the same peak position at $680\\ \\mathrm{nm}.$ , while no significant change was observed in the absorption spectrum (Figure 1g). Moreover, the PL lifetime exhibited a slight improvement from 10.5 ns to 12.8 ns after IDA treatment (Figure S3), suggesting that a reduction in surface trap states occurred through IDA pas \n\n32,33 sivation. \n\nTo investigate how IDA affects the NC surface, we performed $\\mathrm{\\Delta}X$ -ray photoelectron spectroscopy (XPS), solution $\\mathrm{^{1}H}$ nuclear magnetic resonance $(^{1}\\mathrm{H-NMR})$ , and infrared spectroscopy (IR) experiments on untreated and treated NCs. The XPS analysis revealed no significant changes in the Cs $3d$ , Pb 4f, $\\mathrm{~I~}3d$ core-level spectra of both samples (Figure SI4); yet, the high-resolution spectra of the N 1s core-level exhibited a noticeable variation (Figure SI5). We fitted the $\\mathrm{~N~}1s$ core level for untreated NCs to a single peak at $401.8\\ \\mathrm{eV}.$ , corresponding to protonated amine groups $(\\mathrm{NH_{3}}^{+})$ from oleyl ammonium. An additional peak at $399.4\\mathrm{eV}$ appeared in the IDA-treated NC N 1s core-level spectrum, attributed to -NH- group from IDA.34-35 Indeed, the ratio of the two different $\\mathrm{~N~}1s$ core levels $\\mathrm{(NH_{3}}^{+}$ and -NH-) by comparing the integrated area of the two peaks suggests that the OAm to IDA ratio in the passivated NCs was 3.3:1. The existence of the -NH- group after IDA treatment was further verified by $\\mathrm{^1H}$ -NMR with a signal at $10.9\\mathrm{ppm}$ , while the proton signal of the -COOH group from IDA at $13\\ \\mathrm{ppm}$ disappeared. This suggests that the -COOH functional groups in IDA were converted to carboxyls (Figure S6). Quantitative NMR analysis also reveals a significant reduction in OA after IDA treatment (Figure S7 and Table S1). We also investigated the binding mode of IDA on the NCs by IR spectroscopy. Four additional IR peaks are recorded for IDA treated NCs. The peaks at 1602 $\\mathrm{cm}^{-1}$ and $1496~\\mathrm{{cm}^{-1}}$ are ascribed to aromatic $\\scriptstyle{\\mathrm{C=C}}$ vibration, while $1575~\\mathrm{{cm}^{-1}}$ is ascribed to the conjugated aromatic ring and $750~\\mathrm{cm}^{-1}$ is ascribed to aromatic C-H bending, respectively36 (Figure S8). Thus, we conclude that IDA binds to the NC surface via coordination with the carboxyl group. \n\n![](images/467e7064cb73035ec1d2f1cec68d6e0049e59a0d145785bd3525ce9b76e0e145.jpg) \nFigure 2. a), b) Surface charge redistributions of optimized $\\mathrm{PbI}_{2}$ -rich $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ surfaces with OA and IDA ligand modification. c) Normalized PLQY intensities as a function of days for untreated (blue) and IDA-treated NCs (red). d) Photograph of untreated and treated QDs as-synthesized and aged for 15 days. \n\n![](images/1464d2f448d40b0dcde1d484080503aa912d367234496251cd593222d605815b.jpg) \nFigure 3. a) Schematic of the device structure of the light emitting diode. b) Electroluminescence (EL) spectra at various applied voltages. The inset shows a photograph of a working PLED. c) Current density-voltage (J-V) and luminance-voltage (L-V). d) Luminous power efficiency - current density and external quantum efficiency - current density (EQE-J) curves of original and IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ PLED. \n\nTo further understand the binding nature of IDA on the NC surface, we performed density functional theory (DFT) calculations assuming a $\\mathrm{PbI}_{2}$ -rich (positive charged) $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ surface with both OA and IDA passivation (see Figure 2a, b). In both cases, the carboxylic groups can bind to surface $\\mathrm{Pb}$ atoms with similar charge redistributions after ligand attachment, where the negative charge (blue cloud) is localized on the carboxylic group and the positive charge (red cloud) delocalizes along surface $\\mathrm{Pb}$ atoms. In the case of the IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ surface, the double carboxylic groups can separately bind to two surface-exposed $\\mathrm{Pb}$ atoms, resulting in a much larger binding energy $(1.4~\\mathrm{eV})$ as compared to the single carboxylic-capped surface using an OA ligand $(1.14~\\mathrm{eV})$ . Moreover, the double carboxylic groups in the IDA ligand could efficiently stabilize the NC surface with fewer surface structural distortions, avoiding the conversion to the undesirable yellow phase at room temperature. \n\nTo demonstrate the stability of IDA-treated NCs, we tracked the PL emission over several days (Figure 2c). The PL emission of untreated NCs was almost completely quenched after five days. On the other hand, IDA-treated NCs maintained a constant PL emission with a record value of $90\\%$ even after 15 days. Moreover, according to XRD data, no phase change was observed for IDA-treated NCs after 40 days, while untreated NCs essentially transformed into $\\mathrm{PbI}_{2}$ (Figure S9). Significant ligand loss was also confirmed by FTIR for the untreated NCs (Figure S10). A photograph of assynthesized and 15-days-old NC and IDA-treated NC solutions is presented in Figure 2d. The stability of IDAtreated NCs is also apparent when purifying the samples by anti-solvent wash (see SI). Ethyl acetate (EA) washed untreated NCs exhibit a drop in PLQY down to $60\\%$ , while the emission of treated NCs remains relatively unchanged. We ascribe the obvious reduction in PLQY in untreated NCs to the loss of surface ligands from the washing step, due to the more labile nature of the OA surface ligand.24The amount of OAm on the surface is also reduced after washing (as ascertained from the signal of the two different $\\mathrm{~N~}1s$ core levels of ${\\mathrm{NH_{3}}}^{+}$ to -NH) reaching a 1:1 ratio with IDA (Figure S11), further confirming the highly stable binding of IDA. We also note, the IDA ligand passivation process that we devised works well with other halide (Br and $\\mathrm{Br/I}$ mixtures) perovskite NCs (Figure S12 and Table S2). \n\nFinally, we explored the ability of IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ NCs to perform in light emitting devices (PLEDs). We used poly (3,4- ethylenedioxythiophene): poly styrene sulphonate (PEDOT: PSS) on an indium–tin oxide (ITO) glass substrate as the hole-injection layer (HIL) and Poly[bis(4-phenyl) (4-butylphenyl) amine] (Poly-TPD) as a hole-transporting layer (HTL). The electron transporting layer was $^{2,2^{\\circ},2^{\\circ}}$ -(1,3,5-Benzinetriyl)-tris(1- phenyl-1-H-benzimidazole) (TPBi). The PLED structure is shown in Figure 3a. The PLEDs show sharp EL peaks under various biases (Figure 3b) with peak wavelengths of $688~\\mathrm{nm}$ and a narrow full width at half-maximum of ${\\sim}33~\\mathrm{nm}$ . The peak position is slightly red shifted compared with the PL peak, which we attribute to the interdot interaction37 and Stark effect.38 A photograph of the working PLED based on IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ shows uniform emission (inset to Figure 3b). Relative to the control NCs, the PLEDs based on IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ NCs exhibit higher current density (Figure 3c). This can be explained by the effective electronic coupling between unoccupied molecular orbital (LUMO) of IDA and the conduction band edge of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ NCs (see the calculated project density of states in Figure S13), but not ascribed to the conductive nature of IDA (since IDA has a low conductivity, Figure S14). The turn-on voltages (where luminance is ${\\mathrm{>}}1{\\mathrm{~cd}}{\\cdot}{\\mathrm{m}}^{-2},$ ) of the original and IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ PLEDs are $4.1~\\mathrm{V}$ and $4.5~\\mathrm{V},$ respectively. The slightly reduced turn-on voltage indicates better carrier injection into the IDA-treated NCs layer. The maximum luminance of IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ PLED reaches 748 cd· $\\mathrm{m}^{-2}$ under the applied voltage of ${7\\mathrm{~V}},$ which is over two times higher than the control device $(314\\mathrm{\\cd}\\cdot\\mathrm{m}^{-2}$ under the same applied voltage). The IDA-treated NC PLED device has a maximum luminous power efficiency of $0.47\\ \\mathrm{lm}{\\cdot}\\mathrm{W}^{-1}$ , corresponding to a max EQE of $5.02\\%$ $(8.70\\mathrm{\\mA}{\\cdot}\\mathrm{cm}^{-2})$ , which is a factor of two better than $0.22\\ \\mathrm{lm}{\\cdot}\\mathrm{W}^{-1}$ power efficiency and $2.26\\%$ EQE exhibited by the control device (Figure 3d). \n\nIn conclusion, we described bidentate ligand passivation of $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ NCs that effectively increases their PLQY, leading to near-unity values with a good stability. Our results also suggest that IDA ligands can bind firmly to $\\mathrm{PbI}_{2}$ -rich surfaces through dual carboxyl groups, which can reduce the surface traps and inject extra electrons into NCs. In addition, we achieved similar results with the other halide perovskite NCs, clearly indicating the positive role induced by the bidentate ligand. Moreover, fabricated LED devices based on the IDA-treated $\\mathrm{Cs}\\mathrm{Pb}{}_{3}$ NCs are broadly superior to devices based on untreated NCs. We believe that our work paves the way for new strategies to increase the stability and charge transport of lead halide perovskite nanostructures with potential applications across optoelectronics devices. \n\n# ASSOCIATED CONTENT \n\nSupporting Information. \nMaterials, synthesis, XPS, NMR, FTIR, HUMO-LUMO calculation and film conductivity measurement. \n\n# AUTHOR INFORMATION \n\nCorresponding Author ningzhj $@$ shanghaitech.edu.cn osman.bakr $@$ kaust.edu.sa \n\n# Author Contributions \n\n•J.P. and Y.Q.S. contributed equally \n\n# Acknowledgement \n\nThe authors acknowledge funding support from KAUST. Ning, Z. J. and Shang Y. Q. acknowledge financial support from the Shanghai International Cooperation Project (16520720700), National Key Research and Development Program of China (under Grants No. 2016FYA0204000), and Shanghai key research program (16JC1402100). \n\n# REFERENCES \n\n1. Burschka, J.; Pellet, N.; Moon, S. J.; Humphry-Baker, R.; Gao, P.; Nazeeruddin, M. K.; Gratzel, M. Nature 2013, 499, 316-319. \n2. Xing, G. C.; Mathews, N.; Lim, S. S.; Yantara, N.; Liu, X. F.; Sabba, D.; Gratzel, M.; Mhaisalkar, S.; Sum, T. C. Nat. Mater. 2014, 13, 476- 480. \n3. Zhou, H. P.; Chen, Q.; Li, G.; Luo, S.; Song, T. B.; Duan, H. S.; Hong, Z. R.; You, J. B.; Liu, Y. S.; Yang, Y. Science 2014, 345, 542-546. 4. Tsai, H.; Nie, W.; Blancon, J.-C.; Stoumpos, C. C.; Asadpour, R.; Harutyunyan, B.; Neukirch, A. J.; Verduzco, R.; Crochet, J. J.; Tretiak, S.; Pedesseau, L.; Even, J.; Alam, M. A.; Gupta, G.; Lou, J.; Ajayan, P. M.; Bedzyk, M. J.; Kanatzidis, M. G.; Mohite, A. D. Nature 2016, 536, 312- 316. \n5. Manser, J. S.; Christians, J. A.; Kamat, P. V. Chem. Rev. 2016, 116, 12956-13008. \n6. Begum, R.; Parida, M. R.; Abdelhady, A. L.; Murali, B.; Alyami, N. M.; Ahmed, G. H.; Hedhili, M. N.; Bakr, O. M.; Mohammed, O. F. J. Am. Chem. Soc. 2017, 139, 731-737. \n7. Akkerman, Q. A.; D’Innocenzo, V.; Accornero, S.; Scarpellini, A.; Petrozza, A.; Prato, M.; Manna, L., J Am Chem Soc 2015, 137, 10276- 10281. \n8. Song, J. Z.; Li, J. H.; Li, X. M.; Xu, L. M.; Dong, Y. H.; Zeng, H. B. Adv. Mater. 2015, 27, 7162-7167. \n9. Pan, J.; Quan, L. N.; Zhao, Y. B.; Peng, W.; Murali, B.; Sarmah, S. P.; Yuan, M. J.; Sinatra, L.; Alyami, N. M.; Liu, J. K.; Yassitepe, E.; Yang, Z. Y.; Voznyy, O.; Comin, R.; Hedhili, M. N.; Mohammed, O. F.; Lu, Z. H.; Kim, D. H.; Sargent, E. H.; Bakr, O. M. Adv. Mater. 2016, 28, 8718-8725. \n10. Yassitepe, E.; Yang, Z.; Voznyy, O.; Kim, Y.; Walters, G.; Castañeda, J. A.; Kanjanaboos, P.; Yuan, M.; Gong, X.; Fan, F.; Pan, J.; Hoogland, S.; Comin, R.; Bakr, O. M.; Padilha, L. A.; Nogueira, A. F.; Sargent, E. H. Adv. Func. Mater. 2016, 26, 8757-8763. \n11. Swarnkar, A.; Marshall, A. R.; Sanehira, E. M.; Chernomordik, B. D.; Moore, D. T.; Christians, J. A.; Chakrabarti, T.; Luther, J. M. Science 2016, 354, 92-95. 12. Yakunin, S.; Protesescu, L.; Krieg, F.; Bodnarchuk, M. I.; Nedelcu, G.; Humer, M.; De Luca, G.; Fiebig, M.; Heiss, W.; Kovalenko, M. V. Nat. Commun. 2015, 6, 8056. \n13. Li, X. M.; Yu, D. J.; Chen, J.; Wang, Y.; Cao, F.; Wei, Y.; Wu, Y.; Wang, L.; Zhu, Y.; Sun, Z. G.; Ji, J. P.; Shen, Y. L.; Sun, H. D.; Zeng, H. B. Acs Nano 2017, 11, 2015-2023. \n14. Dursun, I.; Shen, C.; Parida, M. R.; Pan, J.; Sarmah, S. P.; Priante, D.; Alyami, N.; Liu, J.; Saidaminov, M. I.; Alias, M. S.; Abdelhady, A. L.; Ng, T. K.; Mohammed, O. F.; Ooi, B. S.; Bakr, O. M. Acs Photonics 2016, 3, 1150-1156. \n15. Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Krieg, F.; Caputo, R.; Hendon, C. H.; Yang, R. X.; Walsh, A.; Kovalenko, M. V. Nano Lett. 2015, 15, 3692-3696. \n16. Cho, H.; Jeong, S.-H.; Park, M.-H.; Kim, Y.-H.; Wolf, C.; Lee, C.- L.; Heo, J. H.; Sadhanala, A.; Myoung, N.; Yoo, S.; Im, S. H.; Friend, R. H.; Lee, T.-W. Science 2015, 350, 1222-1225. \n17. Chiba, T.; Hoshi, K.; Pu, Y. J.; Takeda, Y.; Hayashi, Y.; Ohisa, S.; Kawata, S.; Kido, J. Acs Appl. Mater. Interf. 2017, 9, 18054-18060. 18. Shi, Z.; Li, Y.; Zhang, Y.; Chen, Y.; Li, X.; Wu, D.; Xu, T.; Shan, C.; Du, G. Nano Lett. 2017, 17, 313-321. \n19. Wang, N. N.; Cheng, L.; Ge, R.; Zhang, S. T.; Miao, Y. F.; Zou, W.; Yi, C.; Sun, Y.; Cao, Y.; Yang, R.; Wei, Y. Q.; Guo, Q.; Ke, Y.; Yu, M. T.; Jin, Y. Z.; Liu, Y.; Ding, Q. Q.; Di, D. W.; Yang, L.; Xing, G. C.; Tian, H.; Jin, C. H.; Gao, F.; Friend, R. H.; Wang, J. P.; Huang, W. Nat. Photonics 2016, 10, 699-704. \n20. Tan, Z. K.; Moghaddam, R. S.; Lai, M. L.; Docampo, P.; Higler, R.; Deschler, F.; Price, M.; Sadhanala, A.; Pazos, L. M.; Credgington, D.; Hanusch, F.; Bein, T.; Snaith, H. J.; Friend, R. H. Nat. Nanotech. 2014, 9, 687-692. \n21. Wang, J.; Wang, N.; Jin, Y.; Si, J.; Tan, Z.-K.; Du, H.; Cheng, L.; Dai, X.; Bai, S.; He, H.; Ye, Z.; Lai, M. L.; Friend, R. H.; Huang, W. Adv. Mater. 2015, 27, 2311-2316. \n22. Zhang, S.; Yi, C.; Wang, N.; Sun, Y.; Zou, W.; Wei, Y.; Cao, Y.; Miao, Y.; Li, R.; Yin, Y.; Zhao, N.; Wang, J.; Huang, W. Adv. Mater. 2017, 29, 1606600. \n23. Pan, A. Z.; He, B.; Fan, X. Y.; Liu, Z. K.; Urban, J. J.; Alivisatos, A. P.; He, L.; Liu, Y. Acs Nano 2016, 10, 7943-7954. \n24. De Roo, J.; Ibáñez, M.; Geiregat, P.; Nedelcu, G.; Walravens, W.; Maes, J.; Martins, J. C.; Van Driessche, I.; Kovalenko, M. V.; Hens, Z. ACS Nano 2016, 10, 2071-2081. \n25. Ahmed, G. H.; Liu, J. K.; Parida, M. R.; Murali, B.; Bose, R.; AlYami, N. M.; Hedhili, M. N.; Peng, W.; Pan, J.; Besong, T. M. D.; Bakr, O. M.; Mohammed, O. F. J. Phys. Chem. Lett. 2016, 7, 3913-3919. 26. Ahmed, G. H.; Yin, J.; Bose, R.; Sinatra, L.; Alarousu, E.; Yengel, E.; AlYami, N. M.; Saidaminov, M. I.; Zhang, Y.; Hedhili, M. N.; Bakr, O. M.; Brédas, J.-L.; Mohammed, O. F. Chem. Mater. 2017, 29, 4393- 4400. \n27. Trots, D. M.; Myagkota, S. V. J. Phys. Chem. Solids 2008, 69, 2520- 2526. \n28. Wang, C. J.; Chesman, A. S. R.; Jasieniak, J. J. Chem. Commun. 2017, 53, 232-235. \n29. Liu, F.; Zhang, Y.; Ding, C.; Kobayashi, S.; Izuishi, T.; Nakazawa, N.; Toyoda, T.; Ohta, T.; Hayase, S.; Minemoto, T.; Yoshino, K.; Dai, S.; Shen, Q. ACS Nano 2017, 11, 10373-10383. \n30. Li, G.; Rivarola, F. W. R.; Davis, N. J. L. K.; Bai, S.; Jellicoe, T. C.; de la Peña, F.; Hou, S.; Ducati, C.; Gao, F.; Friend, R. H.; Greenham, N. C.; Tan, Z.-K. Adv. Mater. 2016, 28, 3528-3534. \n31. Pan, J.; Sarmah, S. P.; Murali, B.; Dursun, I.; Peng, W.; Parida, M. R.; Liu, J.; Sinatra, L.; Alyami, N.; Zhao, C.; Alarousu, E.; Ng, T. K.; Ooi, B. S.; Bakr, O. M.; Mohammed, O. F. J. Phys. Chem. Lett. 2015, 6, 5027- 5033. \n32. Nag, A.; Kovalenko, M. V.; Lee, J.-S.; Liu, W.; Spokoyny, B.; Talapin, D. V. J. Am. Chem. Soc. 2011, 133, 10612-10620. \n33. Tang, J.; Kemp, K.; Hoogland, S.; Jeong, K.; Liu, H.; Levina, L.; Furukawa, M.; Wang, X.; Debnath, R.; Cha, D.; Chou, K. W.; Fischer, A.; Amassian, A.; B Asbury, J.; Sargent, E. Nat. Mater. 2011, 10, 765-771. 34. Liao, B.; Long, P.; He, B.; Yi, S.; Ou, B.; Shen, S.; Chen, J. J. Mater. Chem. C 2013, 1, 3716-3721. \n35. Yang, D. Q.; Meunier, M.; Sacher, E. Appl. Surf. Sci. 2005, 252, 1197-1201. \n36. Mayo, D. W. In Course Notes on the Interpretation of Infrared and Raman Spectra, Wiley, Inc.: Hoboken, NJ, 2004; pp 101-140. \n37. Kagan, C. R.; Murray, C. B.; Bawendi, M. G. Phys Rev B Condens Matter 1996, 54, 8633-8643. \n38. Caruge, J. M.; Halpert, J. E.; Bulovic, V.; Bawendi, M. G. Nano Lett. 2006, 6 , 2991-2994. \n\n![](images/e647381cf1ff57d9f9cf2c9ff134b0d64462081e1c02b1c4abbd096cf03d0ef5.jpg) " + }, + { + "id": "10.1126_sciadv.aat0491", + "DOI": "10.1126/sciadv.aat0491", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.aat0491", + "Relative Dir Path": "mds/10.1126_sciadv.aat0491", + "Article Title": "Elastic properties of 2D Ti3C2Tx MXene monolayers and bilayers", + "Authors": "Lipatov, A; Lu, HD; Alhabeb, M; Anasori, B; Gruverman, A; Gogotsi, Y; Sinitskii, A", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Two-dimensional (2D) transition metal carbides and nitrides, known as MXenes, are a large class of materials that are finding numerous applications ranging from energy storage and electromagnetic interference shielding to water purification and antibacterial coatings. Yet, despite the fact that more than 20 different MXenes have been synthesized, the mechanical properties of a MXene monolayer have not been experimentally studied. We measured the elastic properties of monolayers and bilayers of the most important MXene material to date, Ti3C2Tx (T-x stands for surface termination). We developed a method for preparing well-strained membranes of Ti3C2Tx monolayers and bilayers, and performed their nulloindentation with the tip of an atomic force microscope to record the force-displacement curves. The effective Young's modulus of a single layer of Ti3C2Tx was found to be 0.33 +/- 0.03 TPa, which is the highest among the mean values reported in nulloindentation experiments for other solution-processed 2D materials, including graphene oxide. This work opens a pathway for investigating the mechanical properties of monolayers and bilayers of other MXenes and extends the already broad range of MXenes' applications to structural composites, protective coatings, nulloresonators, and membranes that require materials with exceptional mechanical properties.", + "Times Cited, WoS Core": 800, + "Times Cited, All Databases": 837, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000443175500060", + "Markdown": "# M A T E R I A L S S C I E N C E \n\n# Elastic properties of 2D $\\boldsymbol{\\Gamma}\\mathbf{i}_{3}\\mathbf{C}_{2}\\boldsymbol{\\mathsf{T}}_{x}$ MXene monolayers and bilayers \n\nAlexey Lipatov1, Haidong ${\\mathbf{L}}{\\mathbf{u}}^{2}.$ , Mohamed Alhabeb3,4, Babak Anasori3,4, Alexei Gruverman2,5, Yury Gogotsi3,4\\*, Alexander Sinitskii $^{1,5_{*}}$ \n\nCopyright $\\circledcirc$ 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\nTwo-dimensional (2D) transition metal carbides and nitrides, known as MXenes, are a large class of materials that are finding numerous applications ranging from energy storage and electromagnetic interference shielding to water purification and antibacterial coatings. Yet, despite the fact that more than 20 different MXenes have been synthesized, the mechanical properties of a MXene monolayer have not been experimentally studied. We measured the elastic properties of monolayers and bilayers of the most important MXene material to date, $\\bar{\\Pi}_{3}\\mathsf C_{2}\\bar{\\Pi}_{x}$ $(\\overline{{\\mathsf{T}}}_{x}$ stands for surface termination). We developed a method for preparing well-strained membranes of $\\ensuremath{\\boldsymbol{\\mathsf{T}}}\\ensuremath{\\mathsf{i}}_{3}\\ensuremath{\\mathsf{C}}_{2}\\ensuremath{\\boldsymbol{\\mathsf{T}}}_{x}$ monolayers and bilayers, and performed their nanoindentation with the tip of an atomic force microscope to record the force-displacement curves. The effective Young’s modulus of a single layer of $\\bar{\\Pi}_{3}\\mathsf C_{2}\\bar{\\mathsf T}_{x}$ was found to be $\\pm0.33\\pm0.03$ TPa, which is the highest among the mean values reported in nanoindentation experiments for other solution-processed 2D materials, including graphene oxide. This work opens a pathway for investigating the mechanical properties of monolayers and bilayers of other MXenes and extends the already broad range of MXenes’ applications to structural composites, protective coatings, nanoresonators, and membranes that require materials with exceptional mechanical properties. \n\n# INTRODUCTION \n\nBecause of its Young’s modulus of about $\\boldsymbol{1}\\operatorname{TPa}\\left(\\boldsymbol{1}\\right)$ , graphene is considered the strongest material known, which makes it relevant for applications in structural composites, protective coatings, fibers, etc. (2–4). The elastic moduli of mechanically exfoliated and chemical vapor deposition–grown transition metal dichalcogenides, such as $\\ensuremath{\\mathrm{MoS}}_{2}$ and $\\mathrm{WS}_{2}$ , have also been measured and found to be about a third that of graphene (5–7). Among other two-dimensional (2D) materials, only hexagonal boron nitride (h-BN) showed mechanical characteristics approaching graphene (8). However, it should be recognized that many of the record-breaking properties of graphene have been measured on small samples prepared by micromechanical exfoliation, a method relevant to fundamental studies but not to large-scale structural applications. Another limitation of pristine graphene is its poor solubility in conventional solvents, which complicates its processability and miscibility with other materials, such as polymers, for the preparation of composites. \n\nGraphene oxide (GO) is often viewed as a low-cost and scalable alternative to pristine graphene for large-scale mechanical applications (2, 3) and can be prepared by oxidative exfoliation of graphite in acid solutions (9). GO sheets can reach hundreds of micrometers in lateral size (10), and because of their surface and edge functionalization with oxygen-containing moieties, they are highly soluble in water and other solvents and can be blended with various polymers. Despite some degradation of integrity of the graphene lattice during oxidation $(l l)$ , the Young’s modulus values of GO and reduced GO (rGO) monolayers are still considerably high $(>200\\ \\mathrm{GPa})$ , as determined in nanoindentation (12, 13) and wrinkling experiments (14), and are about one-fifth of the Young’s modulus of pristine graphene. GO sheets can also be processed into mechanically stable macroscopic structures, such as “graphene oxide paper” (15), or used as the reinforcement in various polymer matrix composites (3, 4). \n\nIn searches for other 2D crystals with promising elastic characteristics, it is natural to consider transition metal carbides (TMCs), which are known for their exceptional bulk mechanical properties (16). Since 2011, TMCs have been available in a 2D form, known as MXenes (17). More than 20 different MXenes have been synthesized by selective metal extraction and exfoliation of ternary TMCs and nitrides, known as MAX phases, in fluorine-containing etchants (18), and many other MXenes have been studied theoretically (18, 19). MXenes have a general formula of $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x}$ where M represents a transition metal (Ti, Zr, V, Nb, Ta, Cr, Mo, Sc, etc.), X is carbon or nitrogen, and $n=1,2$ , or 3 (20). This chemical synthesis of MXenes adds surface functionalities such as fluorine, oxygen, and hydroxyl groups, denoted as $\\mathrm{T}_{x}$ in the MXenes’ general formula. Examples of widely studied MXenes include $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ $\\mathrm{\\tilde{Ti}_{2}C T_{\\it x},N b_{2}C T_{\\it x},V_{2}C T_{\\it x},M o_{2}T i C_{2}T_{\\it x}}$ and $\\mathrm{Nb}_{4}\\mathrm{C}_{3}\\mathrm{T}_{\\boldsymbol{x}},$ all of which have surface functional groups. Similar to GO, the synthesis of MXenes is scalable (21), and materials are processable in water and a variety of polar organic solvents (22). \n\n$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ is the first discovered and the most widely studied MXene material to date. It shows higher electrical conductivity than solutionprocessed graphene (23), outstanding electrochemical properties (24), and great promise for various applications ranging from energy storage (18) to electromagnetic interference shielding (25). Large uniform monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes of several square micrometers in lateral size can now be prepared in high yields (21, 23), but the mechanical properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayers, or any other MXenes for that matter, have not been measured yet. To date, only a few theoretical studies are available on mechanical properties of MXenes (26–30), predicting them to be stiffer than their MAX phase precursors (31) and bulk TMCs (16). MXene paper and composites have been tested (32), but their properties are determined by weak interfaces. \n\nHere, we report mechanical measurements of the elastic modulus and breaking strength of monolayer and bilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene flakes by the atomic force microscopy (AFM) indentation. We also compare the MXene flakes to GO flakes, as both materials can be solution-processed because of their surface functionalization and are often discussed with regard to similar applications, such as conductive coatings, filtration membranes, composites, porous scaffolds, and energy storage (3, 18). As shown in Fig. 1A, a monolayer of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ consists of three layers of close-packed Ti atoms stacked in the ABC ordering, with carbon atoms occupying the octahedral sites; the flakes are terminated with –F, $^{-0}$ , or $-\\mathrm{OH}$ groups. Our results show that a single layer of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ has an effective elastic modulus of $330\\pm30\\mathrm{GPa},$ , which exceeds considerably the mean values previously found in the nanoindentation experiments on GO and rGO monolayers (12, 13) and other solution-processed 2D materials. \n\n# RESULTS \n\nThe synthesis of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ was performed by in situ hydrofluoric acid (HF) etching of aluminum from $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ , as described by Alhabeb et al. (21) and Lipatov et al. (23). This method produces high-quality MXene flakes with lateral sizes up to $10~{\\upmu\\mathrm{m}}$ (23). The final product is a dark green solution of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes in water, which could be directly dropcasted on a $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate with prefabricated microwells. However, this deposition method yields fractured and surface-contaminated flakes after drying (fig. S1). Flake fracture is caused by the hydrophilicity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and the high surface tension of water, which drags MXene flakes into wells upon drying. Flakes that only partially cover microwells survive drying, but become crumpled and therefore unusable for indentation experiments. \n\nWe developed a deposition technique, which produces very clean, tautly stretched $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ membranes (Fig. 1B). First, MXene solution is drop-casted on a PDMS support and air-dried, leaving multiple MXene flakes on a surface. The surface of a PDMS support with MXene flakes is washed with running deionized (DI) water to remove possible salt contaminants from the original solution. After drying, the PDMS support is placed on a $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate with prefabricated microwells with flakes facing down. No pressure was applied to the support to avoid damaging the flakes. Then, the PDMS film is gently peeled from the substrate, leaving some of the MXene flakes on the $\\mathrm{SiO}_{2}$ surface. The rationale behind this technique is that hydrophilic MXene flakes should have stronger attractive interaction with the hydrophilic silica surface than with the hydrophobic PDMS. This method should also be applicable to other solution-processed 2D materials, such as GO, and MXenes other than $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ . We also tested several other approaches for membrane fabrication, but all of them had certain drawbacks, while the direct PDMS transfer method consistently produced MXene membranes of excellent quality. \n\nA representative scanning electron microscopy (SEM) image in Fig. 1C shows a transferred MXene flake that fully covers five microwells. According to noncontact AFM images (Fig. 1D), the MXene membranes are stretched across the openings and adhere to the well walls because of the attractive interaction between MXene flakes and $\\mathrm{SiO}_{2}$ (see the AFM height profile in Fig. 1E). The step height at the edge of the flake shown in Fig. 1D is about $3.0\\mathrm{nm}$ (Fig. 1F), which includes trapped water molecules between the flake and the substrate. This flake folds at its edge, which adds a layer to itself, and measuring its height reveals a thickness of $1.6\\mathrm{nm}$ for noncontact AFM mode (Fig. 1F), which matches the thickness that we observed in AFM measurements of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayers in our previous study (23). While the procedure that we used for the synthesis of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ provides monolayer flakes at high yields, we also found several suspended bilayer structures, which consisted of two monolayer flakes overlapping over a well. \n\n![](images/f2ee46a2a02e43aa30da59ca7bd37740d9d0e4dc5161b01660357bad7d3f9895.jpg) \nFig. 1. Preparation of MXene membranes. (A) Structure of a $\\ensuremath{\\boldsymbol{\\mathrm{Ti}}}_{3}\\ensuremath{\\boldsymbol{\\mathrm{C}}}_{2}\\ensuremath{\\boldsymbol{\\mathrm{T}}}_{x}$ monolayer. Yellow spheres, Ti; black spheres, C; red spheres, O; gray spheres, H. (B) Scheme of the polydimethylsiloxane (PDMS)–assisted transfer of MXene flake on a $\\mathsf{S i}/\\mathsf{S i O}_{2}$ substrate with prefabricated microwells. See text for details. (C) SEM image of a $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ flake covering an array of circular wells in a $\\mathsf{S i}/\\mathsf{S i O}_{2}$ substrate with diameters of $0.82\\upmu\\mathrm{m}.$ . (D) Noncontact AFM image of $\\mathrm{Ti}_{3}C_{2}\\bar{\\Gamma}_{x}$ membranes. (E and F) Height profiles along the dashed blue (E) and red (F) lines shown in (D). \n\nSince the thickness of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayers is an important parameter for analysis of the results of nanoindentation experiments, it is necessary to comment on the limitations of AFM for the determination of thicknesses of monolayers of 2D materials. For example, while the nominal thickness of graphene is $0.335\\mathrm{nm}$ , in various experiments, the AFM measurements of monolayer graphene flakes produced thickness values in the range of 0.4 to $1.7\\mathrm{nm}$ , as summarized by Shearer et al. (33). This inaccuracy could be affected by a number of factors that include the AFM imaging mode (tapping, contact, etc.), tip-surface interactions, presence of various surface adsorbates, and trapped interfacial molecules, among others. Therefore, nominal thicknesses, rather than AFM-measured thicknesses, were used in other works on mechanical indentation of 2D materials for calculations of mechanical characteristics $(\\boldsymbol{{1}},\\boldsymbol{{5}})$ . Here, likewise, AFM produced a largely overestimated thickness value of $1.6\\ \\mathrm{nm}$ , and for the Young’s modulus calculation, we instead used the thickness of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayer of $0.98~\\mathrm{nm}$ , which was determined by atomically resolved transmission electron microscopy (TEM) and supported by theoretical calculations (34, 35). It should be pointed out that high-resolution TEM is a preferred method for the determination of the thickness of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayer compared to x-ray diffraction (XRD) analysis. When $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ is produced in a bulk form, XRD could be used to determine the interlayer spacing between the MXene sheets; this spacing can vary considerably, depending on the amount and chemical nature of species intercalated between the sheets (36). However, in the monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ membrane, there are no interlayer spacings with intercalated species, and similarly to AFM, the XRD measurements may overestimate the nominal thickness of a MXene monolayer. \n\nThe scheme of the nanoindentation experiment is shown in Fig. 2A. The surface of a substrate was scanned for MXene flakes suspended over wells using AFM in tapping mode. At least two AFM scans of the same well were performed to confirm that no drift of a sample occurred. Then, the AFM tip was positioned directly in the center of a selected well and slowly moved downward, providing controlled stretching of a MXene flake. Two to four cycles of loading and unloading were performed on the same MXene flake, with an incremental loading increase of $50\\mathrm{nN}$ (see the corresponding curves in Fig. 2B). The bottom inset in Fig. 2B illustrates the behavior of the membrane in the beginning of the indentation experiment. The tip first snaps down to the membrane attracted by van der Waals forces and then begins to deflect the membrane as the tip presses downward. We extrapolate the linear force versus deflection (F-d) dependence before snapping until it crosses the curve and consider this point as a center of origin where the force and displacement are both zero, which is necessary to obtain the correct $F{-}\\delta$ relationship. The extension and retraction curves within each loading cycle, as well as the curves for different loads, retrace each other, indicating high elasticity of MXene flakes and that no flake detachment occurs during the measurements. The fracture of this bilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ membrane occurred at a load force of about $200\\mathrm{nN}$ and a deflection of $38\\mathrm{nm}$ . Even at the maximum deflection, the center of the membrane is far from the bottom of the well that is ${\\approx}300\\mathrm{nm}$ deep. The AFM tip punctures the membrane, leaving a small hole as seen in the top inset in Fig. 2B. Unlike in graphene membranes $(I)$ , in which the breaks extend over the entire well (fig. S3, B and C), the punctures in suspended $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes were very local, in agreement with noncatastrophic fracture of MXene sheets predicted by molecular dynamics simulations (37). \n\n![](images/498e69f86c35e75ccb0f9fe8846457383a9a3c0d27f141beded45cfcd172eeff.jpg) \nFig. 2. Elastic response and indentation test results. (A) Scheme of nanoindentation of a suspended $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ membrane with an AFM tip. (B) Force-deflection curves of a bilayer $\\ensuremath{\\boldsymbol{\\mathsf{T}}}\\ensuremath{\\mathsf{i}}_{3}\\ensuremath{\\mathsf{C}}_{2}\\ensuremath{\\mathsf{T}}_{x}$ flake at different loads. The bottom inset is a detailed view of the same curves showing the center of origin. The top inset shows AFM image of the fractured membrane. (C) Comparison of loading curves for monolayer (1L) and bilayer (2L) $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ membranes and the least squares fit to the experimental indentation curves by Eq. 1. Hole diameter is $820~\\mathsf{n m}$ . The inset shows the same experimental curve for bilayer $\\mathrm{Ti}_{3}C_{2}\\mathsf{T}_{x}$ in logarithmic coordinates. The curve shows a linear behavior in the first $10\\ \\mathsf{n m}$ of indentation (blue line) and approaches the cubic behavior at high loads (red line). (D) Histogram of elastic stiffness for monolayer and bilayer membranes. Solid lines represent Gaussian fits to the data. (E) Histogram of pretensions of monolayer membranes. (F) Histogram and Gaussian distribution of breaking forces for monolayer membranes. Tip radius is $7\\:\\mathsf{n m}$ . \n\nWe consider the system under investigation as isotropic because of circular wells, the spherical tip, and close-packed structure of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{{\\boldsymbol{x}}}.$ Therefore, we can parametrize the membrane using Young’s modulus $E_{\\mathrm{Young}},$ Poisson’s ratio $\\nu$ [0.227 for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (38)], and thickness $h$ and fit the experimental $F{-}\\delta$ data using the formula \n\n$$\nF=\\upsigma_{0}^{\\mathrm{2D}}\\pi\\updelta+E^{\\mathrm{2D}}\\frac{q^{3}\\updelta^{3}}{r^{2}}\n$$ \n\nwhere $\\upsigma_{0}^{\\mathrm{2D}}$ represents prestress in the membrane, $E^{\\mathrm{2D}}$ is the 2D elastic modulus, and $r$ is the radius of the well $(1,5)$ . The dimensionless constant $q$ is related to v as $q=1/(1.049-0.15\\nu-0.16\\nu^{2})=0.9933.$ The first term in Eq. 1 corresponds to the prestretched membrane regime and is valid for small loads. The second term for the nonlinear membrane behavior is characterized by a cubic $F\\sim\\delta^{3}$ relationship with a coefficient of $E^{\\mathrm{2D}}$ , which dominates at large loads. The applicability of this formula is demonstrated in the inset in Fig. 2C, where the $F{-}\\delta$ dependence for a bilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flake is shown in logarithmic scale. At small loads (less than $10\\mathrm{nN}$ ), the dependence is linear and shown by the blue solid line, while above $10\\mathrm{nN}_{\\mathrm{:}}$ the coefficient is 3 (red solid line), meaning that the dependence is cubic. The latter fits a considerable amount of the experimental data, confirming that most of the mechanical response is expected to be in the region characterized by a cubic $\\boldsymbol{F}\\sim\\boldsymbol{\\delta}^{3}$ relationship. It is possible to use this relationship to determine the corresponding coefficient $E^{\\mathrm{2D}}$ with high precision. Other nonlinear effects in F-d dependence can be ignored if the AFM tip radius is much smaller than the radius of a well, that is, $r_{\\mathrm{tip}}\\ll r\\left(l,5\\right)$ . In our case, the diameter of the well measured by SEM is $a=2r=820\\mathrm{nm}$ , and according to the manufacturer’s specifications, the AFM tip radius is $7\\ \\mathrm{nm}$ , which results in $r_{\\mathrm{tip}}/r=0.017\\ll1$ . Figure 2C shows the experimental and fitting curves for single- and double-layer MXene flakes. Good fitting $\\cdot R^{\\tilde{2}}>0.995$ for all measurements) is an indicator that the model is appropriate. \n\nIn our experiments, we measured 18 membranes from 16 different monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene flakes. For each membrane, two curves at different loads were collected before the rupture, totaling 36 experimental points. For monolayer MXene membranes, the $E^{\\mathrm{\\tilde{2D}}}$ elasticity ranged from 278 to ${393}\\mathrm{{N/m}}$ , with an average of $326\\pm29\\mathrm{N}/\\mathrm{m}$ (Fig. 2D). A narrow distribution of the experimental $E^{2\\mathrm{D}}$ values was achieved even though the measurements were performed on 16 different flakes. For each MXene flake that covered two wells, the nanoindentation experiments were even more reproducible. For one pair of wells covered by the same flake, we found $E^{2\\mathrm{D}}$ elasticities of 344 and $341~\\mathrm{N/m}.$ , and for another such pair of wells, we measured $E^{2\\mathrm{D}}$ values of 318 and $323\\mathrm{N/m}$ (fig. S2). These results show great reproducibility of data measured within the same flake. The corresponding distribution of membrane pretensions is shown in Fig. 2E. The values of $\\upsigma_{0}^{\\mathrm{2D}}$ lay in the range from 0.14 to $0.34~\\mathrm{N/m}$ for monolayer MXene flakes, showing strong interaction between the membrane and the well walls. These values are comparable with those obtained for graphene and $\\mathrm{MoS}_{2}$ membranes $(1,5)$ . \n\nThe procedure used for the synthesis of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ provides monolayer flakes (23). Two monolayer flakes may overlap or one flake may fold on top of a well, in both cases resulting in bilayer membranes. The $F{-}\\delta$ curve for one of the bilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ membranes is presented in Fig. 2C, in comparison with the curve for a monolayer MXene flake. We measured four different bilayer membranes, collecting a total of 10 experimental points, which are presented in the histogram plot in Fig. 2D. The $E^{2\\mathrm{D}}$ values determined for bilayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes ranged from 632 to $683\\mathrm{N/m}$ , with an average of $655\\pm19\\mathrm{N/m}$ . This number is exactly twice that determined for monolayer MXene membranes, suggesting a strong interaction between layers that is likely associated with the hydrogen bonding between the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ surface groups. Similar effects were observed for overlapping GO membranes (12) and multilayer h-BN flakes (8), where a strong interaction between layers was caused by either hydrogen bonding or interlayer B-N interaction, respectively. In contrast, multilayer graphene exhibits lower $E^{2\\mathrm{D}}$ than expected from multiplying monolayer $E^{2\\mathrm{D}}$ by the number of layers due to weaker interlayer interaction and therefore a greater tendency of layers to slide relative to each other upon indentation $(\\boldsymbol{l},\\boldsymbol{\\delta})$ . \n\nSuspended MXene membranes can be deformed elastically up to a certain stress when mechanical failure occurs. Figure 2F presents the distribution of fracture forces for monolayer MXene membranes ranging from 50 to $102~\\mathrm{nN}$ and averaging at $F_{f}=77\\pm15{\\mathrm{~nN}}$ . As shown in the inset in Fig. 2B, the fracture occurred in the center of a membrane where the stress was applied by the AFM tip. We can extract the maximum stress at the central part of the sheet using the expression for the indentation of a linearly elastic circular membrane under a spherical indenter (39) \n\n$$\n\\upsigma_{\\mathrm{max}}^{\\mathrm{2D}}=\\sqrt{\\frac{F_{f}E^{\\mathrm{2D}}}{4\\pi r_{\\mathrm{tip}}}}\n$$ \n\nIn our work, we used a diamond AFM tip with a radius of $7\\mathrm{nm}$ , rendering $\\upsigma_{\\mathrm{max}}^{\\mathrm{2D}}$ to be between 14 and $20~\\mathrm{N/m}$ . On average, these values correspond to $5.2\\%$ of the Young’s modulus $E^{2\\mathrm{D}}$ for monolayer MXene membranes, which is lower than the theoretical upper limit of a material’s breaking strength (37) due to the presence of defects in the material (40). \n\nConsidering that graphene is a benchmark 2D material, we decided to directly compare $F{-}\\delta$ curves for suspended $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and graphene monolayers (Fig. 3A). The elasticity of graphene in our experiment was found to be $341\\pm28\\mathrm{N}/\\mathrm{m}.$ , obtained from three monolayer membranes (see details in fig. S3), which is very close to the previously reported values of $340\\pm50\\mathrm{N}/\\mathrm{m}\\left(l\\right)$ and thus reconfirms the validity of our experimental approach. \n\n![](images/38f0d56c74646ba0aee28af6330a272e4b7f41349a89df107325a60950246ed0.jpg) \nFig. 3. Comparison of indentation tests on $\\Pi_{3}\\mathbf{C}_{2}\\mathbf{T}_{x}$ with other 2D materials. (A) Comparison of experimental $F{-}8$ curves for monolayer graphene and $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ membranes. (B) Comparison of effective Young’s moduli for several 2D materials: GO (12), rGO (13), $M o S_{2}$ (5), h-BN (8), and graphene (1). In this chart, we compare values produced on membranes of monolayer 2D materials in similar nanoindentation experiments. \n\n# DISCUSSION \n\nThe effective Young’s modulus $E_{\\mathrm{Young}}$ and breaking strength $\\upsigma_{\\mathrm{max}}$ can be calculated from $E^{2\\mathrm{D}}$ and $\\upsigma_{\\mathrm{max}}^{\\mathrm{2D}}$ , respectively, by dividing them by the membrane’s thickness. As we explained previously, for the Young’s modulus calculation, we used the nominal thickness of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayer of $0.98{\\mathrm{nm}}$ , which was obtained from high-resolution TEM analysis and theoretical calculations (34, 35); the same approach was used in other works on indentation of 2D materials $(\\boldsymbol{{l}},\\boldsymbol{{5}})$ . The effective Young’s modulus for MXene membranes is $333\\pm30\\mathrm{GPa}$ , and the breaking strength is $17.3\\pm1.6\\mathrm{GPa}$ (taking the average tip radius of $7\\ \\mathrm{nm}\\cdot$ ). It is interesting to note that according to the molecular dynamics simulations, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ has a Young’s modulus of $502\\mathrm{GPa}$ (27). As expected, the experimentally determined value for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ of $333\\pm$ $30\\mathrm{GPa}$ is lower because of surface functionalization and the presence of defects. However, the difference in the Young’s moduli of the “ideal” $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and the experimentally realized $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ is not as dramatic as in the case of graphene and GO ( $1050\\mathrm{GPa}$ versus $210\\mathrm{GPa},$ ). This could be rationalized by the fact that surface functionalization has a stronger effect on the mechanical properties of one-atom-thick monolayer graphene compared to thicker $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes. In the future studies, it would be interesting to compare mechanical properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ with different functional groups and, ultimately, without functionalization. It should be pointed out that in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayers used in this study, a considerable fraction of the nominal thickness of $0.98{\\mathrm{nm}}$ is occupied by the surface functionalities (34), such as $\\mathrm{-F}$ and –OH, and thinner flakes of pristine $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ are expected to have a Young’s modulus approaching the theoretically predicted value of 502 GPa (27). \n\nComparison of $E_{\\mathrm{Young}}$ values with other benchmark 2D materials is presented in Fig. 3B. At $330\\pm30\\mathrm{GPa}$ , the effective Young’s modulus of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene exceeds the previously reported mean values for GO, rGO, and $\\ensuremath{\\mathrm{MoS}}_{2}$ that were produced in similar nanoindentation experiments (5, 12, 13) but is lower than those of h-BN and graphene $(1,8)$ . While the values for graphene, h-BN, and $\\ensuremath{\\mathrm{MoS}}_{2}$ were reported for defect-free flakes, the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene flakes tested here are solutionprocessed. There is potential to develop methods to synthesize $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes of higher quality to reach a larger Young’s modulus closer to the theoretical value. In addition, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ is just one of more than 20 synthesized MXenes, and MXenes with a different number of atomic layers or a different transition metal may have higher elasticity. This study suggests great potential of MXenes for structural composites, protective coatings, nanoresonators, membranes, textiles, and other applications that require bulk quantities of solution-processable materials with exceptional mechanical properties. \n\n# MATERIALS AND METHODS \n\n# Synthesis of $\\mathbf{\\Tilde{\\Pi}_{3}C_{2}T_{\\boldsymbol{x}}}$ \n\nMAX phase precursor, $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ , was produced as described elsewhere (17, 21). $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene was synthesized via selective etching of Al from $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ using in situ HF etchant solution as described elsewhere (21). The etchant solution was prepared by adding $0.8\\mathrm{g}$ of LiF to $10\\mathrm{ml}$ of 9 M HCl and allowing the solution to mix thoroughly at room temperature for a few minutes. After that, $0.5\\mathrm{g}$ of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ was slowly added over the course of 5 min to avoid initial overheating due to the exothermic nature of the reaction. Then, the reaction was allowed to proceed at ambient conditions $({\\sim}23^{\\circ}\\mathrm{C})$ under continuous stirring $(550~\\mathrm{rpm})$ for 24 hours. The resulting MXene was repeatedly washed with DI water until an almost neutral pH $\\left(\\geq6\\right)$ was achieved. The product was then collected using vacuum-assisted filtration through a polyvinylidene difluoride membrane ${(0.45\\mathrm{-}\\upmu\\mathrm{m}}$ pore size; Millipore) and dried in a vacuum desiccator at room temperature for 24 hours. To delaminate $0.2\\mathrm{g}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ a freshly produced powder was redispersed in $50~\\mathrm{ml}$ of DI water and stirred continuously for 1 hour. Then, the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ solution was centrifuged at $3500~\\mathrm{rpm},$ and the supernatant, a dark green colloidal solution of MXene, was collected. Previous studies have shown that this solution contains primarily monolayer flakes (23, 40). \n\n# Materials characterization Scanning electron microscopy \n\nSEM analysis was performed using a Zeiss Supra 40 Field-Emission SEM at an accelerating voltage of $5\\mathrm{kV}$ . \n\n# Atomic force microscopy \n\nSurface topography imaging and force-indentation curve measurements were performed on an Asylum Research MFP-3D system. Single-crystal diamond tips (D80, SCD Probes) with tip radii of 5 to $10\\mathrm{nm}$ and a spring constant of ${\\sim}3.5\\mathrm{N/m}$ , according to the manufacturer’s specifications, were used for force-indentation experiments. The spring constant of each AFM cantilever was calibrated via thermal noise method (41) before indentation experiments. During the force-indentation experiments, the $z$ -piezo displacement speed was controlled at a rate of $100~\\mathrm{{nm/s}}$ . Different rates ranging from 50 to $1000\\ \\mathrm{nm/s}$ were also tested and showed no clear difference for the force-indentation curves. \n\n# Analysis of force-indentation curves \n\nDuring the indentation experiments, the cantilever bending and $z$ -piezo displacement were recorded as the tip moved downward. The cantilever bending was calibrated by measuring a force-displacement curve on a hard $\\mathrm{Si}/\\mathrm{SiO}_{2}$ surface in advance. The loading force was obtained by multiplying the cantilever bending by the cantilever spring constant, and the deflection of the membrane was obtained by subtracting the cantilever bending from the $z$ -piezo displacement. \n\nIn the real force-deflection data, there is a negative force section due to the tip jump-to-surface effect, where the tip snaps down to the membrane attracted by van der Waals forces when it is very close to the surface. We extrapolated the zero force line in the force-deflection dependence before snapping until it crossed the curve and considered this point as a center of origin where the force and displacement are both zero, which is necessary to obtain the correct force-deflection relationship. \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/4/6/eaat0491/DC1 \nfig. S1. $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ MXene membranes prepared by drop-casting from an aqueous solution. fig. S2. Mechanical properties of $\\ensuremath{\\boldsymbol{\\mathsf{T}}}\\ensuremath{\\mathsf{i}}_{3}\\ensuremath{\\mathsf{C}}_{2}\\ensuremath{\\boldsymbol{\\mathsf{T}}}_{x}$ MXene monolayer on a single flake. \nfig. S3. Mechanical properties of graphene monolayers. \n\n# REFERENCES AND NOTES \n\n1. C. Lee, X. Wei, J. W. Kysar, J. Hone, Measurement of the elastic properties and intrinsic strength of monolayer graphene. Science 321, 385–388 (2008). \n2. K. S. Novoselov, V. I. Fal’ko, L. Colombo, P. R. Gellert, M. G. Schwab, K. Kim, A roadmap for graphene. Nature 490, 192–200 (2012). \n3. A. C. Ferrari, F. Bonaccorso, V. Fal’ko, K. S. Novoselov, S. Roche, P. Bøggild, S. Borini, F. H. L. Koppens, V. Palermo, N. Pugno, J. A. Garrido, R. Sordan, A. Bianco, L. Ballerini, M. Prato, E. Lidorikis, J. Kivioja, C. Marinelli, T. Ryhänen, A. Morpurgo, J. N. Coleman, V. Nicolosi, L. Colombo, A. Fert, M. Garcia-Hernandez, A. Bachtold, G. F. Schneider, F. Guinea, C. Dekker, M. Barbone, Z. Sun, C. Galiotis, A. N. Grigorenko, G. Konstantatos, A. Kis, M. Katsnelson, L. Vandersypen, A. Loiseau, V. Morandi, D. Neumaier, E. Treossi, V. Pellegrini, M. Polini, A. Tredicucci, G. M. Williams, B. Hee Hong, J.-H. Ahn, J. Min Kim, H. Zirath, B. J. van Wees, H. van der Zant, L. Occhipinti, A. Di Matteo, I. A. Kinloch, T. Seyller, E. Quesnel, X. Feng, K. Teo, N. Rupesinghe, P. Hakonen, S. R. T. Neil, Q. Tannock, T. Löfwander, J. Kinaret, Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems. Nanoscale 7, 4598–4810 (2015). \n4. K. Hu, D. D. Kulkarni, I. Choi, V. V. Tsukruk, Graphene-polymer nanocomposites for structural and functional applications. Prog. Polym. Sci. 39, 1934–1972 (2014). \n5. S. Bertolazzi, J. Brivio, A. Kis, Stretching and breaking of ultrathin $M o S_{2}$ . ACS Nano 5, 9703–9709 (2011). G. Rubio-Bollinger, Elastic properties of freely suspended $M o S_{2}$ nanosheets. Adv. Mater. 24, 772–775 (2012). \n7. K. Liu, Q. M. Yan, M. Chen, W. Fan, Y. Sun, J. Suh, D. Fu, S. Lee, J. Zhou, S. Tongay, J. Ji, J. B. Neaton, J. Wu, Elastic properties of chemical-vapor-deposited monolayer $M o S_{2},$ $\\mathsf{W S}_{2},$ and their bilayer heterostructures. Nano Lett. 14, 5097–5103 (2014). \n8. A. Falin, Q. Cai, E. J. G. Santos, D. Scullion, D. Qian, R. Zhang, Z. Yang, S. Huang, K. Watanab e, T. Taniguchi, M. R. Barnett, Y. Chen, R. S. Ruoff, L. H. Li, Mechanical properties of atomically thin boron nitride and the role of interlayer interactions. Nat. Commun. 8, 15815 (2017). \n9. D. R. Dreyer, S. Park, C. W. Bielawski, R. S. Ruoff, The chemistry of graphene oxide. Chem. Soc. Rev. 39, 228–240 (2010). \n10. J. Zhao, S. Pei, W. Ren, L. Gao, H.-M. Cheng, Efficient preparation of large-area graphene oxide sheets for transparent conductive films. ACS Nano 4, 5245–5252 (2010). \n11. K. Erickson, R. Erni, Z. Lee, N. Alem, W. Gannett, A. Zettl, Determination of the local chemical structure of graphene oxide and reduced graphene oxide. Adv. Mater. 22, 4467–4472 (2010). \n12. J. W. Suk, R. D. Piner, J. An, R. S. Ruoff, Mechanical properties of monolayer graphene xide. ACS Nano 4, 6557–6564 (2010). \n13. C. Gómez-Navarro, M. Burghard, K. Kern, Elastic properties of chemically derived single graphene sheets. Nano Lett. 8, 2045–2049 (2008). \n14. D. A. Kunz, P. Feicht, S. Gödrich, H. Thurn, G. Papastavrou, A. Fery, J. Breu, Space-resolved in-plane moduli of graphene oxide and chemically derived graphene applying a simple wrinkling procedure. Adv. Mater. 25, 1337–1341 (2013). \n15. D. A. Dikin, S. Stankovich, E. J. Zimney, R. D. Piner, G. H. B. Dommett, G. Evmenenko, S. T. Nguyen, R. S. Ruoff, Preparation and characterization of graphene oxide paper. Nature 448, 457–460 (2007). \n16. Y. Gogotsi, R. A. Andrievski, Materials Science of Carbides, Nitrides and Borides (NATO Science Series, Kluwer, 1999). \n17. M. Naguib, M. Kurtoglu, V. Presser, J. Lu, J. Niu, M. Heon, L. Hultman, Y. Gogotsi, M. W. Barsoum, Two-dimensional nanocrystals produced by exfoliation of $\\mathsf{T i}_{3}\\mathsf{A l C}_{2}$ . Adv. Mater. 23, 4248–4253 (2011). \n18. B. Anasori, M. R. Lukatskaya, Y. Gogotsi, 2D metal carbides and nitrides (MXenes) for energy storage. Nat. Rev. Mater. 2, 16098 (2017). \n19. M. Khazaei, A. Ranjbar, M. Arai, T. Sasaki, S. Yunoki, Electronic properties and applications of MXenes: A theoretical review. J. Mater. Chem. C 5, 2488–2503 (2017). \n20. M. Naguib, Y. Gogotsi, Synthesis of two-dimensional materials by selective extraction. Acc. Chem. Res. 48, 128–135 (2015). \n21. M. Alhabeb, K. Maleski, B. Anasori, P. Lelyukh, L. Clark, S. Sin, Y. Gogotsi, Guidelines for synthesis and processing of two-dimensional titanium carbide $(\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{\\times}$ MXene). Chem. Mater. 29, 7633–7644 (2017) \n22. K. Maleski, V. N. Mochalin, Y. Gogotsi, Dispersions of two-dimensional titanium carbide MXene in organic solvents. Chem. Mater. 29, 1632–1640 (2017). \n23. A. Lipatov, M. Alhabeb, M. R. Lukatskaya, A. Boson, Y. Gogotsi, A. Sinitskii, Effect of synthesis on quality, electronic properties and environmental stability of individual monolayer $\\mathsf{T i}_{3}\\mathsf{C}_{2}$ MXene flakes. Adv. Electron. Mater. 2, 1600255 (2016). \n24. M. R. Lukatskaya, S. Kota, Z. Lin, M.-Q. Zhao, N. Shpigel, M. D. Levi, J. Halim, P.-L. Taberna, M. W. Barsoum, P. Simon, Y. Gogotsi, Ultra-high-rate pseudocapacitive energy storage in two-dimensional transition metal carbides. Nat. Energy 2, 17105 (2017). \n25. F. Shahzad, M. Alhabeb, C. B. Hatter, B. Anasori, S. Man Hong, C. M. Koo, Y. Gogotsi, Electromagnetic interference shielding with 2D transition metal carbides (MXenes). Science 353, 1137–1140 (2016). \n26. M. Kurtoglu, M. Naguib, Y. Gogotsi, M. W. Barsoum, First principles study of two-dimensional early transition metal carbides. MRS Commun. 2, 133–137 (2012). \n27. V. N. Borysiuk, V. N. Mochalin, Y. Gogotsi, Molecular dynamic study of the mechanical properties of two-dimensional titanium carbides ${\\bar{\\Pi}}_{n+1}{\\mathsf C}_{n}$ (MXenes). Nanotechnology 26, 265705 (2015). \n28. X.-H. Zha, K. Lou, Q. Li, Q. Huang, J. He, X. Wen, S. Du, Role of the surface effect on the structural, electronic and mechanical properties of the carbide MXenes. Europhys. Lett. 111, 26007 (2015). \n29. X.-H. Zha, J. Yin, Y. Zhou, Q. Huang, K. Luo, J. Lang, J. S. Francisco, J. He, S. Du, Intrinsic structural, electrical, thermal, and mechanical properties of the promising conductor $M O_{2}C$ MXene. J. Phys. Chem. C 120, 15082–15088 (2016). \n30. L. Feng, X.-H. Zha, K. Luo, Q. Huang, J. He, Y. Liu, W. Deng, S. Du, Structures and mechanical and electronic properties of the $\\bar{\\mathsf{T i}}_{2}\\mathsf{C O}_{2}$ MXene incorporated with neighboring elements (Sc, V, B and N). J. Electron. Mater. 46, 2460–2466 (2017). \n31. M. W. Barsoum, Nanolayered of kinking linear elastic solids, in Nanomaterials Handbook, Y. Gogotsi, Ed. (CRC Press, 2006), pp. 385–403. \n32. Z. Ling, C. E. Ren, M.-Q. Zhao, J. Yang, J. M. Giammarco, J. Qiu, M. W. Barsoum, Y. Gogotsi, Flexible and conductive MXene films and nanocomposites with high capacitance. Proc. Natl. Acad. Sci. U.S.A. 111, 16676–16681 (2014). \n33. C. J. Shearer, A. D. Slattery, A. J. Stapleton, J. G. Shapter, C. T. Gibson, Accurate thickness measurement of graphene. Nanotechnology 27, 125704 (2016). \n34. X. Wang, X. Shen, Y. Gao, Z. Wang, R. Yu, L. Chen, Atomic-scale recognition of surface structure and intercalation mechanism of ${\\mathrm{Ti}}_{3}{\\mathsf{C}}_{2}{\\mathsf{X}}.$ J. Am. Chem. Soc. 137, 2715–2721 (2015). \n35. J. Halim, M. R. Lukatskaya, K. M. Cook, J. Lu, C. R. Smith, L. A. Näslund, S. J. May, L. Hultman, Y. Gogotsi, P. Eklund, M. W. Barsoum, Transparent conductive two-dimensional titanium carbide epitaxial thin films. Chem. Mater. 26, 2374–2381 (2014). \n36. M. Ghidiu, M. R. Lukatskaya, M.-Q. Zhao, Y. Gogotsi, M. W. Barsoum, Conductive two-dimensional titanium carbide ‘clay’ with high volumetric capacitance. Nature 516, 78–81 (2014). \n37. V. N. Borysiuk, V. N. Mochalin, Y. Gogotsi, Bending rigidity of two-dimensional titanium carbide (MXene) nanoribbons: A molecular dynamics study. Comput. Mater. Sci. 143, 418–424 (2018). \n38. Z. H. Fu, Q. F. Zhang, D. Legut, C. Si, T. C. Germann, T. Lookman, S. Y. Du, J. S. Francisco, R. F. Zhang, Stabilization and strengthening effects of functional groups in two-dimensional titanium carbide. Phys. Rev. B 94, 104103 (2016). \n39. N. M. Bhatia, W. Nachbar, Finite indentation of an elastic membrane by a spherical indenter. Int. J. Non Linear Mech. 3, 307–324 (1968). \n40. X. Sang, Y. Xie, M.-W. Lin, M. Alhabeb, K. L. Van Aken, Y. Gogotsi, P. R. C. Kent, K. Xiao, R. R. Unocic, Atomic defects in monolayer titanium carbide $(\\boldsymbol{\\Pi}_{3}\\boldsymbol{\\mathsf{C}}_{2}\\boldsymbol{\\mathsf{T}}_{x})$ MXene. ACS Nano 10, 9193–9200 (2016). \n41. J. L. Hutter, Comment on tilt of atomic force microscope cantilevers: Effect on spring constant and adhesion measurements. Langmuir 21, 2630–2632 (2005). \n\n# Acknowledgments \n\nFunding: This work was supported by the NSF through ECCS-1509874 with a partial support from the Nebraska Materials Research Science and Engineering Center (DMR-1420645). The materials characterization was performed in part in the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure and the Nebraska Center for Materials and Nanoscience, which are supported by NSF (ECCS-1542182) and the Nebraska Research Initiative. M.A. was supported by the Libyan-North America Scholarship Program funded by the Libyan Ministry of Higher Education and Scientific Research. B.A and Y.G. were supported by U.S. Army Research Office grants W911NF-17-S-0003 and W911NF-17-2-0228. Author contributions: A.S., B.A., and Y.G. initiated the project. M.A., B.A., and Y.G. synthesized and characterized MAX and MXene samples. A.L. fabricated MXene and graphene membranes. H.L. and A.G. performed AFM imaging and nanoindentation experiments. A.L. performed the data analysis. A.L. and A.S. wrote the manuscript with contributions from all other authors. Y.G. and A.S. supervised the project. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 18 January 2018 \nAccepted 27 April 2018 \nPublished 15 June 2018 \n10.1126/sciadv.aat0491 \n\nCitation: A. Lipatov, H. Lu, M. Alhabeb, B. Anasori, A. Gruverman, Y. Gogotsi, A. Sinitskii, Elastic properties of 2D $\\ensuremath{\\boldsymbol{\\mathsf{T}}}\\ensuremath{\\mathsf{i}}_{3}\\ensuremath{\\mathsf{C}}_{2}\\ensuremath{\\boldsymbol{\\mathsf{T}}}_{x}$ MXene monolayers and bilayers. Sci. Adv. 4, eaat0491 (2018). \n\n# ScienceAdvances \n\nElastic properties of 2D $\\bar{\\mathsf{T i}}_{3}\\mathsf{C}_{2}\\bar{\\mathsf{T}}_{X}$ MXene monolayers and bilayers \n\nAlexey Lipatov, Haidong Lu, Mohamed Alhabeb, Babak Anasori, Alexei Gruverman, Yury Gogotsi and Alexander Sinitskii \n\nSci Adv 4 (6), eaat0491. DOI: 10.1126/sciadv.aat0491 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 39 articles, 3 of which you can access for free http://advances.sciencemag.org/content/4/6/eaat0491#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41560-018-0207-z", + "DOI": "10.1038/s41560-018-0207-z", + "DOI Link": "http://dx.doi.org/10.1038/s41560-018-0207-z", + "Relative Dir Path": "mds/10.1038_s41560-018-0207-z", + "Article Title": "Evolution of redox couples in Li- and Mn-rich cathode materials and mitigation of voltage fade by reducing oxygen release", + "Authors": "Hu, EY; Yu, XQ; Lin, RQ; Bi, XX; Lu, J; Bak, SM; Nam, KW; Xin, HLL; Jaye, C; Fischer, DA; Amine, K; Yang, XQ", + "Source Title": "NATURE ENERGY", + "Abstract": "Voltage fade is a major problem in battery applications for high-energy lithium- and manganese-rich (LMR) layered materials. As a result of the complexity of the LMR structure, the voltage fade mechanism is not well understood. Here we conduct both in situ and ex situ studies on a typical LMR material (Li1.2Ni0.15Co0.1Mn0.55O2) during charge-discharge cycling, using multi-lengthscale X-ray spectroscopic and three-dimensional electron microscopic imaging techniques. Through probing from the surface to the bulk, and from individual to whole ensembles of particles, we show that the average valence state of each type of transition metal cation is continuously reduced, which is attributed to oxygen release from the LMR material. Such reductions activate the lower-voltage Mn3+/Mn4+ and Co2+ /Co3+ redox couples in addition to the original redox couples including Ni2+/Ni3+, Ni3+/Ni4+ and O2-/O-, directly leading to the voltage fade. We also show that the oxygen release causes microstructural defects such as the formation of large pores within particles, which also contributes to the voltage fade. Surface coating and modification methods are suggested to be effective in suppressing the voltage fade through reducing the oxygen release.", + "Times Cited, WoS Core": 789, + "Times Cited, All Databases": 836, + "Publication Year": 2018, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000441098100018", + "Markdown": "# Evolution of redox couples in Li- and Mn-rich cathode materials and mitigation of voltage fade by reducing oxygen release \n\nEnyuan Hu   1,7, Xiqian $\\mathsf{Y u}\\oplus1,2,7\\star$ , Ruoqian Lin1,3,7, Xuanxuan $B i^{4}$ , Jun Lu $\\textcircled{10}4\\star$ , Seongmin Bak1, Kyung-Wan Nam $\\textcircled{10}5$ , Huolin L. Xin $\\textcircled{10}3\\star$ , Cherno Jaye6, Daniel A. Fischer6, Kahlil Amine4 and Xiao-Qing Yang1 \n\nVoltage fade is a major problem in battery applications for high-energy lithium- and manganese-rich (LMR) layered materials. As a result of the complexity of the LMR structure, the voltage fade mechanism is not well understood. Here we conduct both in situ and ex situ studies on a typical LMR material $(\\mathbf{Li}_{1,2}\\mathbf{Ni}_{0,15}\\mathbf{Co}_{0,1}\\mathbf{Mn}_{0,55}\\mathbf{O}_{2})$ during charge–discharge cycling, using multi-lengthscale $\\pmb{x}$ -ray spectroscopic and three-dimensional electron microscopic imaging techniques. Through probing from the surface to the bulk, and from individual to whole ensembles of particles, we show that the average valence state of each type of transition metal cation is continuously reduced, which is attributed to oxygen release from the LMR material. Such reductions activate the lower-voltage $\\pmb{M}\\mathbf{n}^{3+}/\\pmb{M}\\mathbf{n}^{4+}$ and $\\cos^{2+}/\\cos^{3+}$ redox couples in addition to the original redox couples including $\\pmb{\\|}\\bar{\\pmb{\\|}}^{2+}/\\pmb{\\|}\\bar{\\pmb{\\|}}^{3+}$ , $\\pmb{\\Lambda}\\pmb{\\vert i^{3}+}/\\pmb{\\Lambda}\\pmb{\\vert i^{4+}}$ and $\\bullet^{2-}/\\bullet^{-}$ , directly leading to the voltage fade. We also show that the oxygen release causes microstructural defects such as the formation of large pores within particles, which also contributes to the voltage fade. Surface coating and modification methods are suggested to be effective in suppressing the voltage fade through reducing the oxygen release. \n\nithium- and manganese-rich (LMR) layer-structured cathode materials have been considered as one of the most promising candidates for high-energy-density lithium-ion batteries1–4. They can deliver reversible capacities of over $280\\mathrm{mAhg^{-1}}$ , which almost double those of conventional cathode materials such as $\\operatorname{LiCoO}_{2}$ (ref. 5) or $\\mathrm{LiFePO_{4}}$ (ref. 6). However, these materials are still facing significant challenges for commercialization in large scale. One of the major problems is known as voltage fade, which means that on cycling, the discharge voltage of LMR materials keeps decreasing7–9. To overcome this problem, we need to acquire a fundamental understanding of the mechanism for voltage fade. \n\nNumerous studies have been carried out to investigate this problem and the ‘layered-to-spinel phase transition’ has been considered as one of the main reasons for voltage fade. Xu et al.10 observed the formation of a spinel phase on the surface of cycled LMR electrodes using aberration-corrected scanning transmission electron microscopy (STEM). Moreover, Gu et al.11 observed spinel domains with different orientations within the same particle of cycled samples. On the basis of this observation, they proposed that the layeredto-spinel phase transition follows a nucleation and growth mechanism. In addition to these electron microscopy studies, Raman spectroscopic studies by Hong et al.12 also provide evidence for such phase transition. \n\nSince layered and spinel phases differ in how lithium and transition metal cations are arranged in each metal layer, layered-to-spinel phase transition indicates that the transition metal migration must be involved in this phase transition process13. Sathiya et al.7 observed the trapping of transition metal ions in tetrahedral sites in cycled lithium-rich and ruthenium-rich samples (having very similar structure as LMR) using the STEM technique for comparative studies on two samples of $\\mathrm{Li}_{2}\\mathrm{Ru}_{0.75}\\mathrm{Ti}_{0.25}\\mathrm{O}_{3}$ and $\\mathrm{Li}_{2}\\mathrm{Ru}_{0.75}\\mathrm{Sn}_{0.25}\\mathrm{O}_{3}$ . They found that there are more metal ions trapped in the $\\mathrm{Li}_{2}\\mathrm{Ru}_{0.75}\\mathrm{Ti}_{0.25}\\mathrm{O}_{3}$ sample than in the $\\mathrm{Li}_{2}\\mathrm{Ru}_{0.75}\\mathrm{Sn}_{0.25}\\mathrm{O}_{3}$ sample and attributed this result to the smaller ionic size of $\\mathrm{Ti^{4+}}$ versus $S\\mathrm{n^{4+}}$ . Recently, Dogan et al.8 identified the presence of tetrahedral occupation of the transition metal in the LMR material after the first charge using nuclear magnetic resonance spectroscopy and suggested that such local structural reorganization can lead to both voltage fade and hysteresis. \n\nThese studies provide valuable insight into the crystal structural changes relating to the voltage fade in LMR materials. However, the detailed relationship between such crystal structural changes and the voltage fade, the contribution to such fade by each element in the material during cycling, and how and where such structural reorganization starts and propagates through the particles of the cathode material during cycling have not been thoroughly studied yet. \n\nHere, we carry out a systematic study on a typical LMR material $\\mathrm{Li}_{1.2}\\mathrm{Ni}_{0.15}\\mathrm{Co}_{0.1}\\mathrm{Mn}_{0.55}\\mathrm{O}_{2}$ by combining synchrotron X-ray absorption spectroscopy (XAS) with high penetration power and the capability to average through the whole cathode, STEM with atomic-level spatial resolution and the newly developed three-dimensional (3D) electron tomography14. A very large number of in situ and ex situ synchrotron X-ray spectra, from both hard XAS at transition metal K-edges and soft XAS at oxygen and carbon K-edges, were collected at various charge–discharge cycles and the capacity contribution from each transition metal redox couple was calculated for a certain cycle number from these spectra. Comparing the charge–discharge profiles, we demonstrated that the origin of voltage fade is the redox couple evolution during cycling. We also investigated the evolution of microstructure during cycling and studied how that relates to the chemical degradation of the material. In addition, we demonstrated that the surface coating or other surface modifications are quite effective in suppressing the voltage fade through reducing the oxygen release during charge–discharge cycling. \n\n# Evolution of the redox couples during cycling \n\nThe electrochemistry of $\\mathrm{Li_{1.2}N i_{0.15}C o_{0.1}M n_{0.55}O_{2}}$ is plotted in Fig. 1, showing the typical voltage fade problem associated with LMR materials. The details are provided in Supplementary Note 1. The X-ray absorption near-edge structure spectra at the K-edges of Mn, Co and Ni were collected in situ during the 1st, 2nd, 25th, 46th and 83rd charge–discharge cycles. Detailed in situ data showing how the spectra of each transition metal element change during the charging and discharging process are shown in Supplementary Figs. 1–5. The results of these data at the end of charge and discharge for each of these cycles are plotted in Fig. 2 together with the ex situ data for the O K-edge for the same sample at the end of charge and discharge for each of these cycles. It can be seen clearly that with an increased number of cycles, the average valence states for all of these three transition metals are continuously reduced. \n\nThe oxygen fluorescence yield (FY) spectra show that most of the changes occur in the pre-edge region. There are continuous decreases in pre-edge peak intensity during cycling, indicating the weakening of the hybridization strength between the transition metal and the oxygen in the bulk. One thing to note is that in the post-edge region (peak centre at about $542\\mathrm{eV}$ ), the spectrum of the first cycle is different from other spectra of the subsequent cycles. This is probably due to the presence of oxygen vacancies in the materials, as has been discussed in previous reports15,16. A semi-quantitative analysis was carried out on the XAS data from the 1st, 2nd, 25th, 46th and 83rd cycles and the results are shown in Fig. 3a. The detailed analysis procedure is provided in Supplementary Note 2. In particular, the method of calculating the Mn oxidization state is shown in Supplementary Fig. 6. \n\nIn the initial cycle, oxygen and nickel are the two major contributors to the capacity, with $128\\mathrm{mAhg^{-1}}$ and $94\\mathrm{mAhg^{-1}}$ delivered capacity, respectively. However, on cycling, their roles become minor, with the capacity from oxygen decreasing to only $50\\mathrm{mAhg^{-1}}$ and the capacity from nickel decreasing to only $66\\mathrm{{mAhg^{-1}}}$ at the 83rd cycle. It is interesting to note that while the contributions from oxygen and nickel diminish, the contributions from manganese and cobalt steadily increase with their respective capacities going from $14\\mathrm{mAhg^{-1}}$ and $26\\mathrm{mAhg^{-1}}$ in the initial cycle to $66\\mathrm{{mAhg^{-1}}}$ and $53\\mathrm{mAhg^{-1}}$ in the 83rd cycle. \n\nOn the one hand, such a capacity increase from manganese and cobalt compensates the capacity loss from oxygen and nickel, maintaining the overall capacity during cycling. On the other hand, shifting the redox couples from oxygen and nickel to manganese and cobalt has a significant impact on the voltage profile, as illustrated in Fig. 3b, which shows how the density of states of the cathode material changes during cycling. The open-circuit voltage (OCV) in the Li battery is determined by the relative Fermi level energy with respect to the $\\mathrm{Li^{+}/L i^{0}}$ energy level, which is related to the workfunction required to move the electrons from the cathode (LMR material) to the anode (lithium metal)17. For the pristine sample, the Fermi level lies just above the $\\mathrm{Ni^{2+}/N i^{3+}}$ redox couple. As the cycle goes on, oxygen loss occurs and leads to transition metal reduction. Specifically, nickel is likely to be reduced on the surface first, forming an electrochemically inactive rock-salt phase and decreasing the capacity contribution from nickel. Such a surface reconstruction process has been investigated in detail previously by Lin et al.18. For manganese and cobalt, their reduction resulted in the activation of the $\\mathrm{Mn}^{3+}/\\mathrm{Mn}^{4+}$ and $\\mathrm{Co}^{2+}/\\mathrm{Co}^{3+}$ redox couples. Such reductions shift the Fermi level higher and resulted in lower OCV and operating voltages. In fact, such process can also explain why the capacity contribution from oxygen is decreased: as transition metal is reduced, the covalency between the transition metal and oxygen is consequently weakened, causing less oxygen involvement in the redox reactions. One may notice that the difference between the energy levels is minimal for $\\mathrm{Ni^{2+}/N i^{3+}}$ and $\\mathrm{Ni^{3+}/N i^{4+}}$ redox couples but is very large for $\\mathrm{Co}^{2+}/\\mathrm{Co}^{3+}$ and $\\mathrm{Co}^{3+}/\\mathrm{Co}^{4+}$ and even larger for $\\mathrm{Mn}^{3+}/\\$ $\\mathrm{Mn^{4+}}$ and $\\mathrm{Mn^{4+}/M n^{5+}}$ . The reason for these larger differences can be explained by the schematic illustration of the electronic structures shown in Fig. 3c. It shows that for Mn and Co, different orbitals are involved when going from one redox couple to the other. For example, the $\\mathrm{Co}^{2+}/\\mathrm{Co}^{3+}$ redox couple involves losing (oxidizing) or adding (reducing) an electron in the spin-up $e_{\\mathrm{g}}$ orbital. However, the $\\mathrm{Co}^{3+}/\\mathrm{Co}^{4+}$ redox couple involves losing (oxidizing) or adding (reducing) an electron in the spin-down $t_{2\\mathrm{g}}$ orbital. However, for Ni, the same orbital (spin-up $e_{\\mathrm{g}}^{\\mathrm{\\Delta}}$ ) is involved in both $\\mathrm{Ni^{2+}/N i^{3+}}$ and $\\mathrm{Ni}^{3+}/$ $\\mathrm{Ni^{4+}}$ redox couples. Therefore, it is the reduction of Mn and Co that is mainly responsible for the drop in OCV or so-called voltage fade. \n\n![](images/1a9cc98459829ec2adb5413384b67663ccfda0eec9bd83ca7e2dcb822ddfca70.jpg) \nFig. 1 | Electrochemical characterization of $\\mathrm{Li}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ . a, Charge–discharge curves for $\\mathsf{L i}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ for the 1st, 2nd, 25th, 50th and 75th cycles. b, ${\\mathsf{d Q}}/{\\mathsf{d V}}$ plot of $\\mathsf{L i}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ for the charge–discharge curves for the 1st, 2nd, 25th, 50th and 75th cycles. \n\n# Surface reactions probed by soft XAS \n\nWhile hard X-ray absorption provides rich information on the reaction in the bulk, the partial electron yield (PEY) mode of soft X-ray absorption can give complementary information about the surface. Spectra of O K-edge and C K-edge XAS collected in PEY mode are shown in Fig. 4a,b respectively. In O K-edge XAS, the pre-edge peaks (from 528 to $533\\mathrm{eV}$ ) arise from exciting an oxygen core shell 1s electron to unoccupied states that feature hybridization between oxygen $2p$ and transition metal $3d$ states. It is obvious that the preedge peak of the pristine sample is very similar to that of $\\mathrm{MnO}_{2},$ featuring a strong intensity. This was clearly explained by Luo et al.4, who attributed such similarity to the high concentration of manganese at the surface and the great number of unoccupied $3d$ orbitals in tetravalent manganese. For the first cycle, when the sample was firstly charged, there is an increase in the pre-edge intensity, which arises both from the stronger hybridization between the oxygen $2p$ and the higher-valent transition metal and from the anionic redox reaction. \n\nAfter the sample was discharged, the pre-edge intensity decreases reversibly (lower panel of Fig. 4a), suggesting that the top layer (around $5\\mathrm{nm}$ , which is the probing depth of the PEY mode19) is still mostly made up of active cathode materials during the 1st cycle. As the cycles goes on, the pre-edge peaks keep decreasing, which can be explained through two aspects. First, the surface reconstruction can take place during cycling, leading to the formation of rock-salt/ spinel phases. This is supported by the PEY data for the transition metal L-edge shown in Supplementary Figs. 7–9. The transition metal valences are lower in these phases and consequently the hybridization strength between the transition metal $3d$ orbitals and the oxygen $2p$ orbitals is weakened. The second reason for the continuous decrease in the pre-edge intensity is the formation of various inorganic/organic compounds such as $\\mathrm{Li}_{2}\\mathrm{CO}_{3}.$ $\\mathrm{Li}_{2}\\mathrm{O};$ LiOH, $\\mathrm{RCO}_{2}\\mathrm{Li}$ and $\\mathrm{R}(\\mathrm{OCO}_{2}\\mathrm{Li})_{2}$ (ref. 20) as a result of electrolyte decomposition21,22. This argument is supported by the increase in the high-energy shoulder peaks ( $535\\mathrm{eV}$ and above), a typical signature of surface OH species23,24. These oxygen-containing species do not have available orbitals to hybridize with oxygen $2p$ orbitals, leading to the absence of pre-edge peaks in their own O K-edge XAS spectra and an overall decrease in the pre-edge of the measured spectra. \n\n![](images/04b18bcf36c83ae027ac0733fe98cdc2b017b1c21fe25a2f14c2775cebca70a6.jpg) \nFig. 2 | XAS results of various elements in $\\mathrm{Li}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ at different cycles. K-edge XAS of Mn, Co, Ni and O for $\\mathsf{L i}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ collected after the 1st, 2nd, 25th, 46th and 83rd cycles. For transition metals (Mn, Co and Ni), XAS is collected in the transmission mode; for oxygen, it is collected in the FY mode. For each element, charged and discharged graphs are plotted using the same scale. \n\n![](images/fa6daf302f09db5f4c8db8f8087371d1b67061881ef481536abdfeefdb319e07.jpg) \nFig. 3 | Redox couple evolution of $\\mathrm{Li}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ during cycling. a, The contribution towards the discharge capacity from each element at various cycles. b, An illustration of the Fermi level being lifted up as a result of electronic structure change. As the voltage is determined by the energy gap between the Fermi level and the $\\mathsf{L i^{+}/L i^{\\circ}}$ energy level, it is lowered accordingly. $U_{3d}$ is the on-site Coulombic repulsion energy that splits up successive redox potentials. c, A diagram showing that, for different redox couples, Mn and Co would involve different energy levels. However, for Ni, the energy level is mostly the same. h.s. and l.s. are high spin and low spin, respectively. \n\n![](images/e2b740d9212dfad8bd8c16d6bfcb259ce0834bbbbc282be7b1cb7186b8f56efa.jpg) \nFig. 4 | Surface degradation of $\\mathrm{Li}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ leading to larger overpotential. a, PEY O K-edge XAS of samples from different cycles (charged state) with the reference spectra of $\\mathsf{M n O}_{2},$ and NiO and $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ shown. Note that during cycling, the pre-edge peaks (525—535 eV) keep decreasing and the shoulder peak around $537\\mathrm{eV}$ keeps increasing. b, PEY O K-edge XAS spectra of charged (circle symbols) and discharged (lines) samples from the 1st and the 130th cycles. c, PEY C K-edge XAS spectra of samples from different cycles. d, An illustration of the interface formation and surface reconstruction of $\\mathsf{L i}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ active material, as well as the degradation of carbon additive during cycling. \n\nThe surface reconstruction and the formation of the layer containing electrolyte decomposition compounds at the cathode/electrolyte interface (CEI) lead to a surface with gradually reduced electrochemical activity, as suggested by the greater and greater overlap between the spectrum of the charged sample and the discharged sample (Fig. 4b). The thickness of this inactive surface layer grows on cycling. By comparing the PEY data with the FY data (shown in Supplementary Figs. 10 and 11), it is estimated that the thickness can be up to tens of nanometres after 100 cycles. \n\nThe spectra of C K-edge XAS are shown in Fig. 4c. The peaks at $284.8\\mathrm{eV}$ and at $292.6\\mathrm{eV}$ are attributed to the $\\pi$ anti-bonding and the $\\upsigma$ ​anti-bonding of the carbon additive25,26. The peak at $290.2\\mathrm{eV}$ is attributed to the $\\mathrm{CO}_{3}{}^{2-}$ in $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ (refs 27,28). During cycling, there is a clear decrease in the peaks characteristic of the carbon additive. These observations suggest that the carbon additive keeps degrading during cycling, presumably caused by intercalation of $(\\mathrm{PF}_{6})^{-}$ into graphite at high voltage, which has been studied by Seel and Dahn29. In contrast, there is an increase in the peak belonging to $\\mathrm{Li}_{2}\\mathrm{CO}_{3},$ which is a major product in the CEI layer28,30,31. This peak intensity increase suggests that the CEI layer may grow during cycling, which is in agreement with previous O K-edge XAS results. The growth of the CEI layer can potentially make the whole electrochemical reaction more and more kinetically sluggish, causing an increase in the overpotential and a decrease in the observed discharge voltages. \n\nThe above results can be summarized in the illustration shown in Fig. 4d and are consistent with galvanostatic intermittent titration technique (GITT) measurements for cycled samples as shown in Supplementary Fig. 12, showing that surface degradation leads to an overpotential increase. Detailed discussions on GITT results are provided in Supplementary Note 3. \n\n![](images/b274915dee20c86e73a454964b7aa99c3ebf68cd22e12863e253ddfb5ce4b08d.jpg) \nFig. 5 | 3D electron tomography reconstruction of $\\mathrm{Li}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ materials. a,b, A volume rendition and a progressive cross-sectional view of cathode particles in the pristine state (a) and after 15 cycles (b). c,d, The internal pore size distribution of the pristine sample weighted by occurrence (c) and by volume (d). e,f, The internal pore size distribution of the cycled sample (15 cycles) weighted by occurrence (e) and by volume (f). The green and orange lines in c and e are single-Gaussian and bi-Gaussian fitting of the pore size histogram. The reweighting by volume in d and f is applied to the fitted curves. \n\n# Initiation and propagation of microstructural degradation \n\nAll of the spectroscopic evidence stated above and the results reported in the literature point out that the voltage fade is caused by the oxygen loss and consequential transition metal reduction during cycling. However, where and how the oxygen-loss-induced microstructure changes take place in cathode material and propagate have not been thoroughly studied. To pinpoint the structure nucleation and evolution, we performed atomic-resolution annular dark-field STEM (ADF-STEM) imaging, spatially resolved electron energy-loss spectroscopy (EELS) and ADF-STEM tomography. \n\nUsing ADF-STEM tomography, the 3D internal structures of the cathode material before and after 15 charge–discharge cycles were reconstructed (Fig. 5a,b). The 3D rendered reconstructions shown in Fig. 5b qualitatively show that a new population of large pores had formed in the interior of the cycled particle after 15 cycles. By analysing the pore size distributions (Fig. 5c–f), it can be quantitatively concluded that the large pores observed in Fig. 5b belong to a new mode that did not appear in the pristine samples. The volume-weighted distribution shows that the large pores contribute to the majority of porosity in the material. As the formation of the large pores is correlated with charge cycles, they are very likely formed by nucleating vacancies that had been left behind by oxygen loss, agreeing well with the ‘lattice densification’ model proposed by Delmas and co-workers32. To estimate how much oxygen is lost from the lattice to create these pores, we selected several particles and calculated their pore fractions. It is found that the pore fraction varies from $1.5\\%$ to $5.2\\%$ , indicating that the maximum amount of oxygen loss can be as large as $9\\%$ after cycling (the detailed methodology to evaluate the amount of oxygen loss is provided in Supplementary Note 4). It is worth noting that the pore distribution evolution is found in multiple particles (Supplementary Fig. 13). \n\nTherefore, the results presented here are statistically reliable. In addition to the estimation, we performed differential electrochemical mass spectrometry (DEMS) to directly observe whether the oxygen loss is in the form of gas release from the material lattice, shown in Supplementary Fig. 14a. A trace amount of oxygen was detected after full charge of each cycle (Supplementary Fig. 14b), indicating continuous oxygen loss during cycling. The detailed DEMS measurement is explained in Supplementary Note 5. \n\nTo further clarify the origin of these pores, STEM-EELS mapping of a concealed pore and an exposed pore was performed as shown in Fig. 6. Figure 6a shows the STEM-EELS mapping results over a concealed pore in the bulk and the exposed pore at the surface of the particle. The EELS map of the concealed pore shows that there is only a very thin shell of $\\mathrm{Mn}^{2+}$ build-up around the pore (Fig. 6a). Since a significant number of small pores were observed in the pristine sample before cycling, it is assumed that these internal concealed pores are formed during synthesis and may keep their size and shape unchanged during cycling until oxygen release is initiated near them. In contrast, for the opposite extreme situation in an exposed pore, the entire pore surface area is exposed to the electrolyte, as shown in Fig. 6b, and a thick layer of spinel/rock-salt structure phase was formed through the interaction between the pore surface and the electrolyte. The EELS relative concentration mapping shows that there is a significant increase in Mn relative concentration close to the surface volume. Based on the fact that the number of large pores increases during cycling as shown in Fig. 5, we can speculate that a large number of pores are neither completely concealed nor completely exposed. Instead, they are ­partially exposed pores with oxygen diffusion pathways nearby in the form of microstructural defects such as dislocation, grain boundaries and micro cracks. During cycling, these partially exposed pores will grow in size and number, together with those completely exposed pores at the surface, contributing to the propagation of the structural phase transitions, facilitating the further oxygen loss and selffeeding the further microstructural defect formation, as well as accelerating the voltage fade. \n\n![](images/e9923153ad3d7b31c8ab0f082767b62425e0bb4af1c160afa8814c7b07beccf2.jpg) \nFig. 6 | Spatially resolved EELS mapping of concealed and exposed pores. a, STEM-EELS mapping of a concealed pore. Top left: an ADF-STEM image of a concealed pore. Bottom left: the reference spectra used for linear composition of the $\\mathsf{M n L}_{2,3}$ spectra in the middle panel. Middle: the EELS spectra of Mn $\\mathsf{L}_{2,3}$ -edges across the surface and the concealed pore. Right: the linear decomposition coefficient as a function of the vertical spatial location. b, STEM-EELS mapping and atomic-resolution imaging of an exposed pore. Top left: an ADF-STEM image of an opened pore. Middle and bottom left: the Mn (middle) and oxygen (bottom) composition extracted from the quantification of the EELS map. Right: atomic-resolution image of the open pore. \n\n# Discussion \n\nThe role of manganese in voltage fade has been well studied and it is understood that manganese goes through reduction on oxygen loss and the $\\mathrm{Mn}^{2+}$ cations resulting from the disproportionation reaction $(\\mathrm{Mn^{3+}}\\to\\mathrm{Mn^{2+}}+\\mathrm{Mn^{4+}})$ migrate more easily to the tetrahedral site8,33,34. However, not enough attention has been paid to the role of cobalt on such voltage fade. As a matter of fact, cobalt has been known to be beneficial in stabilizing the layer structure, and it is widely used in layer-structured cathode materials35,36. Therefore, the role of Co in voltage fade is quite important. \n\nHere, it is clearly shown that during cycling, cobalt also experiences reduction and directly contributes to the voltage fade by shifting the redox couple from $\\mathrm{{\\dot{C}o^{3+}}/\\mathrm{{Co^{4+}}}}$ to $\\mathrm{Co}^{2+}/\\mathrm{Co}^{3+}$ . \n\nThe continued transition metal reduction during cycling indicates on-going oxygen loss at the same time. This is unambiguously confirmed by the 3D TEM electron tomography and spatially resolved EELS mapping. Most of the TEM studies reported in the literature are 2D, limited to provide the statistics of the pore size distribution. Powered by the newly developed 3D electron tomography, we are able to visualize the growing size of the pores during cycling and the nucleation and propagation of the new spinel phase at the interface between the surface of the exposed pore and the electrolyte. It has been proposed that microstructural defects, oxygen release and spinel phase formation are closely related factors and they can facilitate each other during cycling9. Results from this work are in very good agreement with those reported in our previously published papers using 3D transmission X-ray microscopic tomography37,38. A schematic illustration of the comprehensive spectroscopic techniques used and the results obtained from these studies are shown in Supplementary Fig. 15. The morphological change induced by oxygen release can influence the voltage fade in two ways. First, it exposes more surfaces and creates more defects in the particle, both of which promote further oxygen loss. Oxygen loss, in turn, leads to transition metal reduction that contributes to voltage fade. Second, a porosity increase can give rise to more cracks within the particle, weakening the contact between the active material and the carbon additive/current collector39–41. This would lead to an electric resistance increase in the cell and contribute to the deteriorated electrochemical performance through the increased overpotential. \n\n![](images/d4a353782f12bb7060f1c08dd92379fd11b14bae0fb589521f26591288802c7d.jpg) \nFig. 7 | Thermal stability comparison between uncoated and ${\\sf A I F}_{3}$ -coated $\\mathrm{Li}_{1.2}\\mathsf{N i}_{0.15}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.55}\\mathsf{O}_{2}$ . a, XRD results of the two materials (both are in charged states) during the in situ heating experiment, showing that the uncoated sample goes through the phase transition earlier than the coated one. R stands for rhombohedral phase $(\\mathsf{R}\\overline{{3}}\\mathsf{m})$ and S stands for spinel phase $(F d\\bar{3}m)$ . b, Oxygen gas evolution of the two samples during the in situ heating experiment, showing that the uncoated sample releases oxygen at a lower temperature than the coated one. \n\nFrom the above discussion, it is clear that oxygen loss plays a critical role in voltage fade. It contributes to voltage fade by reducing manganese and cobalt followed by activating the $\\mathrm{Mn}^{3+}/\\mathrm{Mn}^{4+}$ and $\\mathrm{Co}^{2+}/\\mathrm{Co}^{3+}$ redox couples at lower voltages. In addition, it slows down the charge transfer across the CEI and deteriorates the electrochemical performance by reducing nickel and facilitates the surface reconstruction. Therefore, suppressing oxygen loss would be a very effective approach to reduce voltage fade in LMR materials. \n\nPractically, there are two good approaches to tackle oxygen loss. First, surface modification is a relatively simple process to reduce oxygen release at the surface of particles. For example, there are several reports showing how surface coating can suppress voltage fade in LMR materials. Considering that oxygen loss can be facilitated by defects causing larger electrolyte-interacting areas, it would be even more desirable to have the coating at the primary particle level, not just at the secondary particle level. It is interesting to note that there is recent progress in this direction as reported by Kajiyama et al.42. Aside from coating, there are other surface treatment methods. For example, Qiu et al.43 recently demonstrated that a surface treatment that introduces more oxygen vacancy on the particle’s surface can significantly decrease the scale of oxygen loss and effectively suppress voltage fade. \n\nSecond, as oxygen loss is usually associated with phase transition of the bulk material, it is possible to indirectly suppress oxygen loss by kinetically manipulating the phase transition. This can be achieved by introducing appropriate foreign elements into the bulk material. This argument is supported by a recent example reported by Nayak et al.44. These authors demonstrate the effectiveness of aluminium doping in suppressing voltage fade. Another example is a paper published by Hu et al.45 that pointed out that oxygen loss during heating can be suppressed by doping the material with cations that have tendencies to occupy tetrahedral sites. The tetrahedral site occupation of these cations could hinder the transition metal cation migration through tetrahedral sites, which is considered as a parallel process for the phase transition to the spinel structure accompanied with oxygen loss. \n\nAlthough these design principles provide important directions for material design, the practical optimization of the LMR material synthesis still involves many trial-and-error efforts. It would be highly desirable to predict the long cycling behaviour of LMR materials by some simple methods without going through the longtime cycling. It is interesting to note that similar oxygen release and transition metal reduction processes are also observed in experiments when heating up the charged cathode materials46,47. In those thermal stability studies, it was found that transition metals, particularly manganese and cobalt, migrate to tetrahedral sites, leading to the formation of spinel phases. Such migration has also been observed in the cycling experiments, but at a smaller scale and usually takes more effort to characterize7. The similar responses of the cathode material to external forces (voltage in the case of cycling or temperature in the case of heating) have been explored by Schilling and Dahn48, Ceder and co-workers49 and Yang and co-workers50. On the basis of these studies, it might be possible to speed up the material screening test by associating the electrochemical cycling performance with the thermal stability. Instead of characterizing the stability of the cathode material by going through many electrochemical cycles, a heating experiment (within hours) can be performed on the material to reveal its thermal stability. This can serve as a strong indicator of the electrochemical performance. There are several examples in the literature showing that doping and surface coating can effectively mitigate the voltage fade problem in LMR materials44,51–53. For example, previous work by Zheng et al.53 indicates that ${\\mathrm{AlF}}_{3}$ coating can effectively suppress the voltage fade in LMR material as shown in Supplementary Fig. 16. \n\nTo summarize, we demonstrated in this work that such performance improvement in reducing the voltage fade during electrochemical cycling can be well correlated with the improvement in thermal stability. As shown in Fig. 7 (detailed in situ XRD data covering the full $2\\theta$ range is shown in Supplementary Fig. 16), the uncoated LMR material experiences layered-to-spinel phase transition (illustrated by the appearance of the (220) peak that is characteristic of spinel) and oxygen release at a much lower temperature than the temperature observed for oxygen release in the $\\mathrm{AlF}_{3}$ -coated system, indicating that coated LMR is more thermally stable. Such a correlation between electrochemical cycling and thermal stability is not a coincidence but intrinsically caused by the fact that both cycling and heating can involve oxygen loss, and transition metal reduction and migration. This correlation provides a simple and quick procedure to test the effectiveness of a new surface modification or a new material developed to suppress voltage fade without having to conduct time-consuming multiple cycling: if the material for surface modification has a better thermal stability (meaning that oxygen is released only at high temperature), it would have a better structural stability in resisting voltage fade during cycling. \n\n# Methods \n\nElectrochemical measurement. The $\\mathrm{Li_{1.2}N i_{0.15}C o_{0.1}M n_{0.55}O_{2}}$ cathode electrodes were prepared by slurrying the active material, carbon black and polyvinylidene fluoride with a weight ratio of 86:6:8 in N-methyl pyrrolidone solvent, and then coating the mixture onto an Al foil. High-purity lithium foil was used as the anode. The electrolyte was $1.2\\mathrm{mol}\\mathrm{LiPF}_{6}$ in ethylene carbonate and dimethyl carbonate solvent (3:7 by volume, Novolyte Inc.). The 2032-type button cells for electrochemical studies were assembled in an argon-filled glove box and tested on a VMP3 BioLogic electrochemistry workstation. GITT experiments (Biologic Inc.) were performed by charging/discharging the cell for 1 h at a current density of $21\\mathrm{mAg^{-1}}$ and relaxing it for $12\\mathrm{h}$ to reach a quasi-equilibrium state and then repeating this process until the voltage limitation was reached. \n\nX-ray absorption spectroscopy. The hard XAS experiments were carried out at beamline X18A of the National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory. The in situ XAS experiments were performed in transmission mode using a Si (111) double-crystal monochromator detuned to $35\\mathrm{-}45\\%$ of its original maximum intensity to eliminate the high-order harmonics. A reference spectrum for each element was simultaneously collected with the corresponding spectrum of the in situ cells using transition metal foil. The energy calibration was carried out using the first inflection point of the K-edge spectrum of the transition metal foil as a reference. The XANES and extended X-ray absorption fine-structure data were analysed using the ATHENA54 software package. The soft XAS measurements were performed in both FY and PEY modes at beamline U7A of the NSLS. The beam size was $1\\mathrm{mm}$ in diameter. The estimated incident X-ray energy resolution was ${\\sim}0.15\\mathrm{eV}$ at the O K-edge. The monochromator absorption features and beam instabilities were normalized out by dividing the detected FY and PEY signals by the photoemission current of a clean gold Io mesh placed in the incident beam. The energy calibration was carried out by initially calibrating the principal monochromator Io oxygen absorption feature to $531.2\\mathrm{eV}$ using an oxygen gas-phase absorption cell. An additional Io mesh of Ni was also placed in the incident beam to ensure energy calibration (based on the oxygen calibration above) and energy-scale reproducibility of the many PEY or FY spectra presented. The PEY data were recorded using a channel electron multiplier equipped with a three-grid high-pass electron kinetic energy filter, while the FY data were recorded using a windowless energy dispersive Si (Li) detector. A linear background fit to the pre-edge region was subtracted from the spectra. The O K-edge spectra are normalized between 585 and $630\\mathrm{eV}.$ . \n\nIn situ time-resolved XRD and mass spectroscopy. The charged cells were transferred to a glove box for disassembly. The charged cathodes were washed in dimethyl carbonate solvent in the glove box and the fine cathode powders (including the binder and conductive carbon) were obtained by scratching away the electrode from the current collector. They were loaded into $0.5\\mathrm{-mm}$ -diameter quartz capillaries in the glove box and the capillary tip was sealed temporarily \n\nwith vacuum grease in the glove box. The capillary then was transferred from the glove box and hermetically sealed using an oxygen torch before being mounted on the thermal stage of beamline X7B, at the National Synchrotron Light Source (NSLS), Brookhaven National Laboratory. The detailed experimental procedure is described in a previous report39. \n\nTEM characterization. Atomic-resolution annular dark-field STEM imaging, and spatially resolved electron energy-loss spectroscopic mapping were performed on $\\mathtt{a200-k e V}$ probe-corrected dedicated STEM equipped with a cold field emitter and an Enfina spectrometer. The electron tomography results were acquired in a $200\\mathrm{keV}$ S/TEM with a Schottky field emitter. For each 3D reconstruction, a tilt series of 71 images were acquired in the annular dark-field STEM mode from $-70$ degrees to $+70$ degrees with 2-degree intervals. The tomograms were reconstructed using a custom-written MATLAB script that implements a multiplicative simultaneous iterative reconstruction technique. \n\nData availability. The data that support the plots within this paper and other finding of this study are available from the corresponding author upon reasonable request. \n\nReceived: 30 October 2017; Accepted: 19 June 2018; Published online: 30 July 2018 \n\n# References \n\n1.\t Lu, Z. & Dahn, J. R. Understanding the anomalous capacity of $\\mathrm{Li}/\\mathrm{Li}[\\mathrm{NixLi}_{(1/3-2\\mathrm{x}/3)}$ $\\mathrm{Mn}_{(2/3-\\mathrm{x}/3)}]\\mathrm{O}_{2}$ cells using in situ X-ray diffraction and electrochemical studies. J. Electrochem. Soc. 149, A815–A822 (2002). \n2.\t Thackeray, M. M. et al. $\\mathrm{Li}_{2}\\mathrm{MnO}_{3}$ -stabilized $\\mathrm{LiMO}_{2}$ ( $\\mathbf{M}=\\mathbf{M}\\mathbf{n}$ , Ni, Co) electrodes for lithium-ion batteries. J. Mater. Chem. 17, 3112–3125 (2007). \n3.\t Sathiya, M. et al. Reversible anionic redox chemistry in high-capacity layered-oxide electrodes. Nat. Mater. 12, 827–835 (2013). \n4.\t Luo, K. et al. Charge-compensation in $3d$ -transition-metal-oxide intercalation cathodes through the generation of localized electron holes on oxygen. Nat. Chem. 8, 684–691 (2016). \n5.\t Mizushima, K., Jones, P., Wiseman, P. & Goodenough, J. B. ${\\mathrm{Li}}_{x}{\\mathrm{CoO}}_{2}$ ( $\\scriptstyle\\cdot0$ 1) with layer number $(n)$ ranging from 1 to 4. We describe two new DJ perovskite series based on bivalent $(+2)$ organic cations deriving from a piperidinium $\\left(\\mathrm{C}_{5}\\mathrm{NH}_{12}\\right)$ organic backbone (Figure 1b). The new DJ perovskites are built from 3AMP $\\mathbf{\\bar{3AMP}}=3$ -(aminomethyl)piperidinium) and 4AMP ( $\\mathbf{\\partial}_{4\\mathrm{AMP}}=$ 4-(aminomethyl)piperidinium) cations between the layers (“spacers”) and methylammonium (MA) cations inside the 2D layers (“perovskitizers”) to form $\\left(\\mathrm{A^{\\prime}}\\right)$ $\\left(\\mathrm{MA}\\right)_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ ( $\\mathbf{\\bar{A}}^{\\prime}$ $\\mathbf{\\Lambda}=3\\mathbf{AMP}$ or 4AMP, $n=1{-}4,$ homologous series.51 With the exception of the $n=1$ members, the 3AMP and 4AMP series have a representative crystal structure sequence shown in Figure 1b. We find that the difference in the position of the ${-}\\mathrm{CH}_{2}\\mathrm{NH}_{3}^{+}$ group on the piperidine chair (3- and 4- position with respect to the piperidine nitrogen) influences the crystal structure through different hydrogen-bonding modes, which is further reflected on the distortion of the inorganic layers. This difference has a major impact on the optical and electronic properties, which see a narrowing of the bandgap and an enhanced charge transport performance for the least distorted structure (3AMP). Density functional theory (DFT) calculations are in good agreement with the observed trends. We further demonstrate the superior optoelectronic properties of these materials on photovoltaic (PV) devices. Because of the less distorted crystal structure, the 3AMP series shows a superior performance ( $(\\sim7\\%$ champion efficiency for $n=4$ ) to the 4AMP series ( $(\\sim5\\%$ champion efficiency for $n=4$ ). These two series of examples showcase the power of utilizing different templating organic cations to influence the semiconducting properties of the inorganic part of the perovskites, which broaden the horizons of 2D perovskites for achieving new solar cells and other optoelectronic devices with better characteristics. \n\n# RESULTS AND DISCUSSION \n\nThe structural differences between RP and DJ halide perovskites are mainly caused by the interlayer cations (spacers), where RP phases have two sheets of interdigitating cations $(1+)$ while the DJ phases only have one sheet of interlayer cations $(2+)$ between the inorganic slabs. The influence of the spacers on inorganic slabs is exerted in many levels, depending on the cation size and shape (steric effect), charge (electrostatic attraction), and the position of the functional groups (H-bonding and dispersion forces). This difference between RP and DJ perovskites is also reflected in the general formula, where the RP phase has a general formula of $\\mathbf{A}^{\\prime}{}_{2}\\mathbf{A}_{n-1}\\mathbf{M}_{n}\\mathbf{X}_{3n+1}$ and the DJ phase has a general formula of $\\mathbf{A}^{\\prime}\\mathbf{A}_{n-1}\\mathbf{M}_{n}\\mathbf{X}_{3n+1}$ ( $\\mathbf{A}^{\\prime}=\\mathbf{\\partial}$ interlayer cation). In hybrid DJ phases, the interlayer organic cations are $^{2+}$ , having less degrees of freedom, making the layers closer to each other. In RP phases, the organic cations are $^{1+}$ , which results in more flexible layer stacking. \n\nTable 1. Crystal Data and Structure Refinement for $\\mathbf{A}^{\\prime}\\mathbf{M}\\mathbf{A}_{n-1}\\mathbf{P}\\mathbf{b}_{n}\\mathbf{I}_{3n+1}$ (A′ = 3AMP or 4AMP) \n\n\n
compound
(3AMP)PbI4(3AMP) (MA)PbI(3AMP) (MA)Pb3I10(3AMP) (MA)PbI13
empirical formulaCNH6PbI4(CNH6)(CHNH)PbI(CNH6)(CHNH)PbI0(CNH6)(CHNH)Pb4I13
crystal systemmonoclinicIaPaIa
space group unit cell dimensionsP2/c a = 8.6732(6)Aa = 8.8581(11) Aa = 8.8616(3) Aa = 8.8627(18) A
b = 18.4268(9) Ab = 8.8607(4) Ab = 8.8624(3) Ab = 8.8689(18) A
C = 23.0316(7)AC = 58.842(12) A
c = 20.4522(14)AC = 33.4749(5) A
β = 99.306(6)°β=90°β=90°β=90°
3225.67(35)2627.4(3)1808.79(10)4625.1(16)
Z8 424
density (g/cm3)3.42243.66813.80243.8645
ind. refln5033[Rint = 0.1102]4422[Rint = 0.0202]8035[Rint = 0.0361]5893[Rint = 0.0405]
data/restraints/param5033/32/1454422/17/1158035/28/1635893/19/201
final R indices [I > 20(1)] R indices [all data]Robs = 0.0869Robs = 0.0323Robs = 0.0395Robs = 0.0901
wRobs = 0.1622wRobs = 0.0922wRobs = 0.1063wRobs = 0.2062
Ral = 0.1471Rall = 0.0365Rall = 0.0612Ral = 0.1136
largest diff. peak and holewRal = 0.1686 3.97 and -4.88 e A-3wRal = 0.0941 1.44 and -1.23 e A-3wRal = 0.1296wRal = 0.2138
2.014 and -1.382 e A-3 11.07 and -5.34 e A-3 compound
empirical formula(4AMP)PbI4(4AMP)(MA)PbI7(4AMP) (MA)Pb3I0(4AMP) (MA)Pb4I13
crystal systemCoNH16PbI4 monoclinic(CNH6)(CHNH)PbI7(CNH6)(CHNH)PbI10(CNH6)(CHNH)Pb4I13
space groupPcIaPcIa
unit cell dimensionsa = 10.4999(13) Aa = 8.8412(11)Aa = 23.1333(7)Aa = 8.8587(18) A
b = 12.5429(9) Ab = 8.8436(4) Ab = 8.8365(3) Ab = 8.8571(18) A
c = 12.5289(13)AC = 33.6045(5)Ac = 8.8354(3)Ac = 58.915(12) A
β = 89.984(9)°β=90°β=90°β=90°
1650.05(43)2627.5(4)1806.11(10)4622.6(16)
442
Z density (g/cm3)4
3.34413.66813.80813.8666
ind. refln4646 [Rint = 0.1198]4558[Rint = 0.028]7954 [Rint = 0.0291]8002[Rint = 0.1339]
data/restraints/param final R indices [I > 20(1)]4646/36/1414558/17/1167954/18/1588002/19/202
R indices [all data]Robs = 0.0797Robs = 0.0330Robs = 0.0351Robs = 0.0585
wRobs = 0.1093wRobs = 0.0915wRobs = 0.0889wRobs = 0.0839
Ra = 0.1618Rall = 0.0410Ral = 0.0559Ral = 0.1700
largest diff. peak and holewRall = 0.1275wRal = 0.0949wRall = 0.0970wRall = 0.1000
4.48 and -4.31 e A31.69 and -1.20 e A-31.80 and -1.39 e A-34.23 and -2.94 e A-3
\n\nThe Dion−Jacobson series of layered perovskites, $\\left(\\mathrm{A^{\\prime}}\\right)$ - $\\left(\\mathrm{MA}\\right)_{n-1}\\mathrm{Pb}_{n}\\mathrm{I}_{3n+1}$ $\\mathit{\\check{A}}^{\\prime}=3\\mathrm{AMP}$ or 4AMP, $n=1{-}4,$ ), produce uniform, square plate-like crystals, except for $(3\\mathrm{AMP})\\mathrm{PbI}_{4},$ which is an elongated plate as seen in Figure 1c. For the 3AMP series, the color of the crystal gets progressively darker from $n=$ 1 (red) to $n=4$ (black). The 4AMP has a similar trend, but it starts from lighter colors than the 3AMP for the $n=1$ (orange) and $\\textit{n}=\\textit{2}$ (red) members. The bulk crystals exhibit good stability in ambient environment and can be handled without any protection during characterizations. \n\nBoth $(\\mathbf{A}^{\\prime})(\\mathbf{MA})_{n-1}\\mathbf{\\bar{P}b}_{n}\\mathbf{I}_{3n+1}$ series form isostructural analogues for $n>1$ . Detailed crystallographic data and structural refinements for all eight compounds reported here are listed in Table 1. They consist of $n$ layers $\\mathrm{\\sim}6.3\\mathrm{\\bar{A}}$ is the thickness of one octahedron) of corner-sharing $\\mathrm{[PbI_{6}]^{4-}}$ octahedra with $x\\mathrm{AMP}^{2+}$ $\\left(x=3,4\\right)$ ) separating the perovskite slabs and $\\mathrm{\\mathbf{MA}^{+}}$ filling in the perovskite voids (Figure 1b). The difference between the two \n\nDJ perovskite families is highlighted in Figure 2a and b, where specific crystallographic characteristics are stressed. The $n=1$ and $\\textit{n}=\\textit{2}$ members of each AMP series are selected as representative examples. For $n=1$ , the layers stack almost exactly on top of one another from the top-down viewing direction. $(3\\mathrm{AMP})\\mathrm{PbI_{4}}$ is somewhat mismatched due to an outof-plane tilting. $(4\\mathrm{AMP})\\mathrm{PbI}_{4}$ matches perfectly as it displays exclusively large in-plane tilting. The 3AMP and 4AMP behave alike when it comes to $n=2.$ , where the difference only lies in the $\\mathrm{Pb-I-Pb}$ angle. The trend continues for the higher numbers ${\\mathit{\\acute{n}}}=3$ and 4). Viewing along the inorganic layers (Figure 2b), the hydrogen-bonding networks for 3AMP and 4AMP are drastically different. In $(3\\mathrm{AMP})\\mathrm{(MA)Pb_{2}I_{7}},$ the 3AMP cation forms weak H-bonds (highlighted in red) with the terminal $\\mathrm{I}^{-}$ . Bonding with the terminal $\\mathrm{I}^{-}$ has a small effect on the in-plane $\\mathrm{Pb-I-Pb}$ angles as the terminal $\\mathrm{I}^{-}$ does not contribute to the in-plane distortion directly. On the contrary, in $(4\\mathrm{AMP})(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7},$ the H-bonds are formed with the bridging $\\mathrm{I}^{-}$ anions deeper inside the layers as seen in Figure 2b, which amplify the in-plane distortion. \n\n![](images/c48e8639f1a09d3c0d3719220cdb05221c400d62fec2e64980fb9bb71a213e6d.jpg) \nFigure 2. (a) Top-view of $\\mathrm{(3AMP)PbI_{4},}$ $\\left(4\\mathrm{AM}\\right)\\mathrm{PPbI}_{4},$ (3AMP) $(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7},$ and $(4\\mathrm{AMP})(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7}.$ (b) Side-view of $(3\\mathrm{AMP})(\\mathrm{MA})\\mathrm{Pb}_{2}\\mathrm{I}_{7}$ and $(4\\mathrm{\\bar{A}M P)(M A)P b_{2}I_{7};}$ hydrogen bonding is marked in red. (c) Average equatorial $\\mathrm{Pb-I-Pb}$ angles for 3AMP and 4AMP series from $n=1$ to 4. (d) Average axial and equatorial angles for 3AMP and 4AMP. (e) Definition of axial and equatorial $\\mathrm{Pb-I-Pb}$ angles. (f) I···I distance trend in 3AMP and 4AMP, where the 3AMP series has closer distance. \n\nThe differences in hydrogen bonding have an impact on the $\\mathrm{Pb-I-Pb}$ angles, which are directly related to the optical and electrical properties of these materials (see below). To illustrate this point, we classify the $\\mathrm{Pb-I-Pb}$ angles into two categories, the axial (along the longest crystallographic axis) and the equatorial (along the inorganic plane) as shown in Figure 2e. In these systems, the axial $\\mathrm{Pb-I-Pb}$ angles are very close to $180^{\\circ}.$ , as they are much less affected by the interaction (e.g., hydrogen bonding) with the spacing cations. On the other hand, the equatorial $\\mathrm{Pb-I-Pb}$ angles are much more distorted because they are directly exposed to the spacing cations, especially for the case of $n=1$ and $n=2$ . The evolution of the $\\mathrm{Pb-I-Pb}$ angles is summarized in Figure 2c and ${\\textsc{d}},$ where Figure 2c shows only the averaged equatorial angles and Figure 2d shows the averaged (both axial and equatorial) $\\mathrm{Pb-I-Pb}$ angles. From Figure 2c, it is clear the gap between the average of the equatorial angles of the 3AMP and 4AMP gradually closes as the layer thickness increases from $n=1$ to 4. For 3AMP, the averaged equatorial Pb−I−Pb decreases from $165.1^{\\circ}$ to $162.2^{\\circ}\\ .$ , while for 4AMP it increases from $155.1^{\\circ}$ to $159.7^{\\circ}$ . This indicates that the effect of organic cation on the inorganic slabs is gradually diminished as they get thicker (increasing n number). As the axial $\\mathrm{Pb-I-Pb}$ angles in both series are close to $180^{\\circ}$ , when they are averaged with the equatorial angles as shown in Figure 2d, the average is increased for both series up to $n=4$ . \n\nAnother interesting structural feature is that the I···I distance between the inorganic layers is very short. Because the layers lay exactly on top of each other (eclipsed configuration), the I··· I distance essentially defines the closest interlayer distance. The 3AMP series has a generally smaller I···I distance than 4AMP (Figure 2d), while for both series the I···I distance gradually decreases slightly as the layer gets thicker. This is possibly a result of increased stacking fault formation in the perovskite layers as n increases, expressed indirectly in the determined average crystallographic structure. The close I···I interlayer distance $({\\stackrel{\\cdot}{\\sim}}4.0\\ \\bar{\\mathrm{A}})$ is one of the shortest among reported 2D lead iodide perovskites and plays a crucial role in affecting the electronic band structure of these materials, which will be discussed below. \n\nThe optical band gaps of both 3AMP and 4AMP series follow a general trend that has the energy gap $(E_{\\mathrm{g}})$ decreasing as the layer number $(n)$ increases (Table 2). From $n=1$ to $n=$ ∞ $\\left(\\mathrm{MAPbI}_{3}\\right)$ , the band gap decreases from 2.23 to $1.52\\ \\mathrm{eV}$ for the 3AMP series, while for the 4AMP the range is much wider (from 2.38 to $1.52\\mathrm{eV},$ ) (Figure 3a,b). The spectra of both series show clear excitonic features similar to those of other 2D perovskites,13,18,28,51,52 which become less prominent as the $n$ number increases and finally disappear for $n=\\infty$ . The steadystate photoluminescence (PL) spectra of these materials, shown in Figure $^{3c,\\mathrm{d},}$ , exhibit an analogous trend with the band gaps. The 3AMP series demonstrates constantly lower PL emission energy than the 4AMP, until $n=5$ when they become equal. The evolution of the band gaps of both series follows a similar trend as the PL as shown in (Figure 3f). The lifetimes of both AMP series (Figure S6) are comparable to the previously reported 2D layered perovskite PEA series, for which the lifetimes lie in the $0.1\\mathrm{-}0.2\\$ ns range.53 Overall, the 3AMP series has a longer lifetime than the 4AMP (except $n=1\\dot{\\bar{\\mathbf{\\rho}}}$ ), which indicates slower carrier combination, more ideal for the PV devices. \n\nTable 2. Optical Properties and Color of the $(\\mathbf{A}^{\\prime})(\\mathbf{MA})_{n-1}\\mathbf{Pb}_{n}\\mathbf{I}_{3n+1}$ ( $\\mathbf{\\DeltaA}^{\\prime}=3\\mathbf{AMP}$ or 4AMP, $n=1{-}4$ ) DJ Perovskites \n\n\n
compoundEg (eV)PL (eV)colorcompoundEg (eV)PL (eV)color
n=1(3AMP)PbI42.232.22red(4AMP)PbI42.382.33orange
n=2(3AMP)(MA)PbI2.022.00dark red(4AMP)(MA)PbI72.172.13red
n=3(3AMP)(MA)Pb3I101.921.90black(4AMP)(MA)PbIo1.991.97black
n=4(3AMP)(MA)Pb4I131.871.84black(4AMP)(MA)Pb4I131.891.88black
\n\n![](images/972bda5f903cdd9120fd98a81a8c7ab397e95f230750904c083243b1fed41a7d.jpg) \nFigure 3. Optical properties of the 3AMP and 4AMP series. (a,b) Optical absorption spectra of 3AMP and 4AMP series. $^{\\mathrm{(c,d)}}$ Steadystate photoluminescence (PL) spectra of 3AMP and 4AMP series. $\\mathrm{(e,f)}$ Summary of absorption and $\\mathrm{PL}$ in energy from $n=1$ to 5. \n\nThe optical properties of the DJ iodide perovskites are quite different from those observed in RP perovskites.51 Relative to the corresponding RP perovskites (Figure 4), the emission energy observed in PL is characteristically red-shifted by ${\\sim}0.1$ eV in the case of 3AMP $(1.90\\ \\mathrm{eV})$ and $0.03\\ \\mathrm{eV}$ in the case of 4AMP $\\left(1.97~\\mathrm{eV}\\right)$ with respect to the BA analogue $(2.00\\ \\mathrm{eV})$ , taking $n=3$ as the reference example.51 The absorption edges of the compounds containing AMPs $\\ensuremath{(1.70~\\mathrm{eV})}$ are also $0.1\\ \\mathrm{eV}$ lower than the BA analogue. The recently reported structural type ACI perovskite $(\\mathrm{G}\\bar{\\mathrm{A}})(\\mathrm{MA})_{3}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ falls between the RP and DJ perovskites, with an $E_{\\mathrm{g}}$ of $1.73\\mathrm{eV}$ and PL emission peak at 1.96 eV.29 \n\nThe optical properties of these materials correlate very well with their structural characteristics. As discussed above, the $\\mathrm{Pb-I-Pb}$ angles for 3AMP are systematically larger than those for the 4AMP. The larger are the $\\mathrm{Pb-I-Pb}$ bond angles (closer to $180^{\\circ}$ ), the more the Pb s and $\\mathtt{I}\\mathtt{p}$ orbitals overlap.54−56 The strong antibonding interaction pushes up the valence band maximum (VBM), resulting in a reduced band gap. Thus, the systematically narrower band gap observed for 3AMP versus 4AMP can be attributed to the more linear $\\mathrm{Pb-I-Pb}$ angles (i.e., smaller octahedral tilting (Figure S7)) for the former. \n\nThe results of density functional theory (DFT) electronic structure calculations are shown in Figure $\\mathsf{S a-h}$ . Corresponding projected densities of states are shown in Figure S10, revealing the above mentioned hybridization of Pb s and $\\mathsf{~I~p~}{}$ orbitals in the valence bands and the Pb p dominant characteristic of the low-lying conduction bands. The calculated band gap for $(3\\mathrm{AMP})\\mathrm{PbI_{4}}$ is determined at the $\\Gamma$ point (1.13 eV) (Figure 5a), whereas the band gap of $(4\\mathrm{AMP})\\mathrm{PbI_{4}}$ is determined at the BZ edge $(1.14~\\mathrm{{\\eV})}$ (Figure $\\left.5\\mathrm{b}\\right|$ ). The calculated band gaps for the higher numbers between the 3AMP and 4AMP series have larger differences, where $E_{\\mathrm{g}}$ is $0.48~\\mathrm{eV}$ for $n=2,$ , 3AMP, and $0.70\\mathrm{eV}$ for $n=2$ , 4AMP (Figure 5c,d). For $n=3$ , the band gaps at $Z$ point for 3AMP and 4AMP are 0.47 and $0.74~\\mathrm{eV},$ , respectively (Figure $5\\mathrm{e,f,}$ ). The calculated gap for 3AMP $\\left(n=4\\right)$ ) is very small $(0.07\\ \\mathrm{eV})$ , much lower than $0.54~\\mathrm{eV}$ for $n=4$ , 4AMP as seen in Figure ${5}\\mathrm{g,h}$ . Noteworthy, qualitative trends of band gap variations are well captured considering octahedral tilt angles (Figure S7). The DFT computed band gaps do not include many-body interactions needed to properly assess optical response, which is why calculated values are systematic underestimated without GW corrections.55,57 The band gaps of 3AMP series DJ are systematically smaller than those computed for 4AMP series as shown in Figure S8, in agreement with experimental findings. The stacking of perovskite sheets in the DJ structure type, which aligns the perovskite layers, allows for a better interlayer electronic coupling through van der Waals I···I interactions. These I···I contacts participate in antibonding interactions that further destabilize the VBM (Figure S9), contributing to the reduction of the band gap as compared to RP phases with respect to the same $n$ -value, as discussed above. \n\n![](images/6948dda87323a741a3509c7bc307e425665aeb1805fc43d866a6403150604c0a.jpg) \nigure 4. Comparison of the (a) optical absorption spectra and (b) PL spectra between $\\big(3\\mathrm{AMP}\\big)\\big(\\mathrm{MA}\\big)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ $\\mathrm{(4AMP)(MA)_{2}P b_{3}I_{10}},$ (GA) $)(\\mathrm{MA})_{3}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ and $(\\mathrm{BA})_{2}(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}.$ \n\n![](images/e730a88e1f1927fa68d284fc28e02fed2ad524a471f45d59c359893e09d1e204.jpg) \nFigure 5. $\\left(\\mathsf{a}\\mathrm{-}\\mathsf{h}\\right)$ DFT calculations of band structures for the 3AMP and 4AMP series with SOC. The calculated gaps are $1.13\\mathrm{eV}$ for $(3\\mathrm{AMP})\\mathrm{PbI}_{4}$ (at $\\Gamma^{\\protect\\overrightarrow{}}$ ), $1.14~\\mathrm{eV}$ for $(4\\mathrm{AMP})\\mathrm{PbI}_{4}$ (at B), $0.48~\\mathrm{{\\eV}}$ for $(3\\mathrm{AMP})\\mathrm{(MA)Pb_{2}I_{7}}$ (at $\\textstyle Y_{_{0}})$ , $0.70~\\mathrm{{~eV}}$ for $(4\\mathrm{AMP})\\mathrm{(MA)Pb_{2}I_{7}}$ (at $\\mathbf{\\nabla}{Y_{\\mathrm{o},\\mathrm{\\ell}}}$ , $0.47~\\mathrm{\\eV}$ for (3AMP) $\\left(\\mathrm{MA}\\right)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ (at $Z,$ ), $0.74~\\mathrm{{\\eV}}$ for (4AMP) $\\left(\\mathrm{MA}\\right)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ (at $Z,$ ), $0.07~\\mathrm{eV}$ for (3AMP) $\\left(\\mathrm{MA}\\right)_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13}$ (at $\\left.Y_{\\mathrm{o}}\\right\\rangle$ , and $0.54~\\mathrm{{\\eV}}$ for $(4\\mathrm{AMP})(\\mathrm{MA})_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13}$ (at $\\mathbf{\\nabla}{Y_{\\mathrm{o},\\mathrm{\\Omega}}}$ ). \n\nOn the basis of the attractive properties of the new 2D DJ perovskites, in a preliminary study, we investigated the higher layer numbers ( ${\\mathit{\\acute{n}}}=3$ and 4) as light absorbers for solar cells. A planar solar cell structure was adopted for device fabrication (Figure 6a), consisting of a fluorine doped tin oxide (FTO) substrate, a poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS) hole transport layer (HTL), a 2D perovskite light absorber, a $\\mathrm{C}_{60}/\\mathrm{BCP}$ electron transport layer (ETL), and an $\\mathrm{Ag}$ electrode. The devices were fabricated using a modified solvent engineering method (see Methods). The photocurrent density−voltage $\\left(J-V\\right)$ curves of the solar cells using the 2D DJ perovskites are in Figure $6\\ensuremath{\\mathrm{b}}$ (measured using a reverse voltage scan). The thickness of the perovskite films was ${\\sim}250\\ \\mathrm{nm}$ . Among the $n=3$ and 4 for 3AMP and 4AMP, (3AMP) $(\\mathrm{MA})_{3}\\mathrm{Pb}_{4}\\mathrm{\\bar{I}}_{13}$ achieved the highest power conversion efficiency (PCE) of $7.32\\%$ with a short-circuit current density $(J_{s c})$ of $10.17~\\mathrm{mA~cm}^{-2}$ , an open-circuit voltage $(V_{\\mathrm{oc}})$ of $1.06\\mathrm{V},$ and a fill factor (FF) of $67.60\\%$ . This value is significantly higher than the corresponding $n=3$ and $n=4$ RP perovskites prepared using a regular mesoporous $\\mathrm{TiO}_{2}$ device structure. \n\n![](images/a55e5926f6bdb3556ae13dbec2fed248d7b53abb896a6613ae94689efa6187a2.jpg) \nFigure 6. Solar cell architecture for the higher layer numbers ${\\bf{\\dot{\\rho}}}_{n}=3$ and 4) of 3AMP and 4AMP. (a) Scheme of the adopted inverted device structure. (b) $J{-}V$ curves of the 2D perovskite solar cell devices. (c) External quantum efficiency (EQE) spectra. (d) PXRD of the thinfilms. (e) Steady-state PL spectra, where the emission peaks are 746 nm, 1.66 eV $(3\\mathrm{AMPPb}_{3}\\mathrm{I}_{10})$ , $764~\\mathrm{nm}$ , $1.62\\ \\mathrm{eV}$ $\\left(3\\mathrm{AMPPb}_{4}\\mathrm{I}_{13}\\right)$ , and 752 $\\mathrm{nm},1.65\\ \\mathrm{eV}$ $\\mathbf{\\langle4AMPPb_{3}I_{10}}$ and $4\\mathrm{AMPPb}_{4}\\mathrm{I}_{13},$ . (f) Absorption spectra for the thin-films. \n\nThe remarkable performance of (3AMP) $\\mathbf{\\left(MA\\right)}_{3}\\mathbf{Pb}_{4}\\mathbf{I}_{13}$ can be mainly attributed to the reduced band gap and the improved mobility originating from the increased band dispersion (see above). The device based on $(3\\mathrm{AMP})(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}^{-}\\mathrm{I}_{10}$ has the lowest PCE of $2.02\\%$ with a $J_{\\mathrm{sc}}$ of $3.05~\\mathrm{mA}~\\mathrm{cm}^{-2}$ , a $V_{\\mathrm{oc}}$ of 0.99 $\\mathrm{v},$ and a FF of $66.54\\%$ , attributed to the largest band gap and the intense presence of a secondary phase, identified as the $n=$ 2 member $2\\theta={\\sim}11^{\\circ}$ and ${\\sim}16^{\\circ}$ ). $(4\\mathrm{AMP})(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ and (4AMP) $\\mathbf{\\left(MA\\right)}_{3}\\mathbf{Pb}_{4}\\mathbf{I}_{13}$ have PCE below $5\\%_{\\cdot}$ mainly due to the much lower $J_{\\mathrm{sc}}$ relative to the 3AMP. The average photovoltaic parameters of the devices using the various absorbers are summarized in Table S6. The $J_{\\mathrm{sc}}$ integrated from the external quantum efficiency (EQE) curves (Figure 6c) of the devices based on $\\big(3\\mathrm{AMP}\\big)\\big(\\mathrm{MA}\\big)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ (3AMP) $\\big(\\mathrm{MA}\\big)_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13},$ $\\big(4\\mathrm{AMP}\\big)\\big(\\mathrm{MA}\\big)_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10},$ and $(4\\mathrm{AMP})(\\mathrm{MA})_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13}$ are 2.92, 10.16, 5.83, and $7.08\\:\\mathrm{\\mA}\\:\\mathrm{\\cm}^{-2}$ , respectively, which are in good agreement with the trend of the $J_{\\mathrm{sc}}$ obtained from the $J{-}V$ curves. In Figure 6d, powder X-ray diffraction (PXRD) of the (3AMP) $(\\mathrm{MA})_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13},$ $\\mathrm{(4AMP)(MA)_{2}P b_{3}I_{10}},$ and (4AMP)- $(\\mathbf{MA})_{3}\\mathbf{Pb}_{4}\\mathrm{I}_{13}$ films shows preferred orientation in the “perpendicular” direction judging from the strongest hkl (110) and (220) at ${\\sim}14^{\\circ}$ and ${\\sim}28^{\\circ}$ , which facilitates the carriers to travel through the layers.8,13 Further results of the fabrication of higher quality films and higher efficiency solar cells will be reported in the future. \n\nPL emission properties of the films (Figure 6e) are quite different (red-shifted) from those of the bulk materials, which can be attributed to the so-called “edge effect”.52 The edge effect is observed in single crystals of both $(3\\mathrm{AMP})\\mathrm{PbI}_{4}$ and $(3\\mathrm{AMP})(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ as seen in Figure S11. The second PL emission at lower energy was observed when exciting the sample through “the edge”, which is parallel to the layers. The results show larger separation of the higher $2.21\\mathrm{eV}$ from bulk) and lower energy emissions $\\mathrm{~\\widetilde{~}1.64~e V}$ edge) of the $n=1$ than for $n=3$ (1.91 and $1.68\\ \\mathrm{eV},$ ) for 3AMP. The lower energy emission $\\left(1.68\\mathrm{~eV}\\right)$ is very close to the emission of the thin film $\\left(1.66\\mathrm{~\\eV}\\right)$ . This result is similar to the previously reported $(\\mathrm{BA})_{2}(\\mathrm{MA})_{2}\\mathrm{Pb}_{3}\\mathrm{I}_{10}$ example, where the higher energy emission is $2.00\\mathrm{eV}$ and lower energy emission is $1.{\\overset{\\vartriangle}{7}}0\\ {\\mathrm{eV}}.^{52}$ Attempts for measuring edge states of the other layered number crystals such as $n=2$ and 4 were not successful due to the thin crystal morphology, which has caused handling difficulty. \n\nThe absorption edges of the films have the same trend as in the EQE spectra, although multiple slopes appear, indicating the formation of some lower layer numbers (Figure 6f). Even though these 2D DJ perovskite devices are not completely optimized, the initial results show great promise as they compare well with the corresponding 2D RP perovskites, which lead to the 2D perovskite solar cells field.8,15,58 \n\n# CONCLUSIONS \n\nWe have shown that a new crystal motif based on the DJ class of perovskites forms 2D hybrid lead iodide perovskites. The special spacer cations using 3AMP and 4AMP have a strong influence on the overall properties. Detailed crystallographic investigations on all eight compounds ${\\mathit{\\Omega}}(n=1{-}4,$ for 3AMP and 4AMP) have provided the structural insights for understanding the structure−property relationships. In particular, by understanding the angular distortion $(\\bar{\\mathrm{Pb-I-Pb}}$ angle) within the system, we manage to show the subtle difference in the cations causes large differences in the optical properties by affecting the $\\mathrm{Pb-I-Pb}$ angles, where the 3AMP series has systematically larger angles and smaller band gaps than the 4AMP series. As compared to the most common 2D RP perovskites, the BA series, the 3AMP and 4AMP series possess lower band gaps because of a less distorted inorganic framework and closer I···I interlayer distances. Our analysis suggests more superior optoelectronic properties of the 3AMP over the 4AMP series, which was demonstrated in the actual device fabrication, where the preliminary result shows the champion device has a PCE over $7\\%$ . The strong correlation between the materials and their applications’ performance validates the importance of understanding structure−property relationships and discovering new materials in the halide perovskite systems. \n\n# METHODS \n\nMaterials. PbO $(99.9\\%$ ), 3-(aminomethyl)piperidine (AldrichCPR), 4-(aminomethyl)piperidine $(96\\%)_{\\cdot}$ hydroiodic acid (57 wt $\\%$ in $\\mathrm{H}_{2}\\mathrm{O},$ distilled, stabilized, $99.95\\%$ ), and hypophosphorous acid solution (50 wt $\\%$ in $\\mathrm{H}_{2}\\mathrm{O}\\dot{_{\\circ}}$ ) were purchased from Sigma-Aldrich and used as received. Methylammonium iodide $\\left(>99.{\\bar{5}}\\%\\right)$ was purchased from Luminescence Technology Corp. and used as received. \n\nSynthesis of (3AMP) $(\\boldsymbol{\\mathsf{M A}})_{n-1}\\mathsf{P b}_{n}\\mathsf{I}_{3n+1}$ . For $n=1$ , an amount of $669~\\mathrm{mg}$ (3 mmol) of $99.9\\%$ PbO powder was dissolved in $6~\\mathrm{mL}$ of hydroiodic acid and $1~\\mathrm{mL}$ of hypophosphorous acid solution by heating under stirring for $5{\\mathrm{-}}10\\ \\operatorname*{min}$ at ${\\sim}130\\ ^{\\circ}\\mathrm{C}$ until the solution turned clear bright yellow. $0.5~\\mathrm{mL}$ of hydroiodic acid was added to 342 mg $3\\mathrm{mmol})$ ) of 3-(aminomethyl)piperidine (3AMP) in a separate vial under stirring. The protonated 3AMP solution was added into the previous solution under heating at $240~^{\\circ}\\mathrm{C}$ and stirring for 5 min. Red plate-like crystals precipitate during slow cooling to room temperature. Yield: $963~\\mathrm{{mg}}$ ( $38.6\\%$ based on total $\\mathrm{Pb}$ content). For $n=2,$ an amount of $669\\mathrm{{mg}}$ (3 mmol) of $99.9\\%$ PbO powder was dissolved in 6 mL of hydroiodic acid and $1~\\mathrm{mL}$ of hypophosphorous acid solution by heating under stirring for $5{\\mathrm{-}}10\\ \\mathrm{min}$ at $130~^{\\circ}\\mathrm{C}$ until the solution turned clear bright yellow. $318{\\mathrm{~mg}}$ (2 mmol) of methylammonium iodide (MAI) was added directly to the above solution under heating. $0.5~\\mathrm{mL}$ of hydroiodic acid was added to $57\\mathrm{mg}\\left(0.5\\mathrm{mmol}\\right)$ of 3AMP in a separate vial under stirring. The protonated 3AMP solution was added into the previous solution under heating and stirring for $\\textsf{S m i n}$ . Dark red plate-like crystals precipitated (Figure 1c) during slow cooling to room temperature. Yield: $487\\mathrm{mg}$ ( $22.4\\%$ based on total $\\mathrm{Pb}$ content). For the synthesis of higher numbers, they follow the same route except the ratio was changed to $37.6~\\mathrm{mg}$ $\\left(0.33\\mathrm{mmol}\\right)$ of 3AMP, $477\\ \\mathrm{mg}$ ( $\\left(3\\mathrm{mmol}\\right)$ of MAI, $669~\\mathrm{{mg}}$ ( $\\mathrm{3~mmol}\\AA,$ ) of $\\mathrm{PbO}$ for $n=3.$ , yield $252~\\mathrm{mg}$ $12.2\\%$ based on total $\\mathrm{Pb}$ content), and $34.2~\\mathrm{mg}$ ( $\\left\\langle0.3\\mathrm{\\mmol}\\right\\rangle$ ) of 3AMP, $636~\\mathrm{mg}$ ( $\\left(4\\mathrm{mmol}\\right)$ of MAI, $892\\mathrm{mg}$ ( $\\mathbf{\\dot{\\phi}}_{4\\mathrm{mmol}})$ of $\\mathrm{PbO}$ for $n=$ 4, yield $301~\\mathrm{mg}$ ( $11.2\\%$ based on total Pb content). \n\nSynthesis of (4AMP) $(\\boldsymbol{\\mathsf{M A}})_{n-1}\\boldsymbol{\\mathsf{P b}}_{n}\\boldsymbol{\\mathsf{I}}_{3n+1}$ . Similar synthetic procedures were used to synthesize the 4AMP series. However, the amount of 4AMP was reduced as the 4AMP series precipitated faster than the 3AMP. The experimental ratios (4AMP:MAI:PbO) (in mmol) of the 4AMP are 3:0:3 for $n=1$ , 0.5:2:3 for $n=2$ , 0.33:3:3 for $n=3,$ and 0.27:4:4 for $n=4$ . Yield: 1155 mg $(46.3\\%)$ , 684 mg $\\left(31.5\\%\\right)$ , 531 mg $(25.6\\%)$ , and $477\\mathrm{\\mg}$ ( $17.7\\%$ based on total Pb content), respectively. Powder X-ray Diffraction. PXRD analysis was performed using a Rigaku Miniflex600 powder X-ray diffractometer ( $\\operatorname{Cu}\\operatorname{K}\\alpha$ graphite, $\\lambda=$ 1.5406 Å) operating at $40\\ \\mathrm{kV}/15\\ \\mathrm{mA}$ with a $\\boldsymbol{\\mathrm{K}\\beta}$ foil filter. \n\nSingle-Crystal X-ray Diffraction. Full sphere data were collected after screening for a few frames using either a STOE IPDS 2 or an IPDS 2T diffractometer with graphite-monochromatized Mo $\\mathrm{K}\\alpha$ radiation $\\left(\\lambda\\ =\\ 0.71073\\ \\mathring\\mathrm{\\mathrm{~A~}}\\right.$ ) $\\mathrm{\\Omega}50\\ \\mathrm{\\kV}/40\\ \\mathrm{\\mA})$ under $\\mathbf{N}_{2}$ at $293\\mathrm{~K~}$ $\\left(3\\mathrm{AMPPbI_{4}},\\right.$ $4\\mathrm{AMPPbI}_{4},$ and $(3\\mathrm{AMP})(\\mathrm{MA})_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13})$ . The collected data were integrated and applied with numerical absorption corrections using the STOE X-AREA programs. The rest of the compounds were collected using a Bruker Molly instrument with MoKα IμS microfocus source $\\left(\\lambda\\overset{\\smile}{=}0.71073\\:\\mathring{\\mathrm{A}}\\right)$ ) with MX Optics at 250 K. The collected data were integrated and applied with numerical absorption corrections using the APEX3 software. Crystal structures were solved by charge flipping and refined by full-matrix least-squares on $F^{2}$ with the Jana2006 package. \n\nOptical Absorption Spectroscopy. Optical diffuse reflectance measurements were performed using a Shimadzu UV-3600 UV−vis− NIR spectrometer operating in the $200{-}1000~\\mathrm{nm}$ region using ${\\tt B a S O}_{4}$ as the reference of $100\\%$ reflectance. The band gap of the material was estimated by converting reflectance to absorption according to the \n\nKubelka−Munk equation: $\\alpha/S=(1-R)^{2}(2R)^{-1}.$ , where $R$ is the reflectance and $\\alpha$ and S are the absorption and scattering coefficients, respectively. \n\nSteady-State and Time-Resolved Photoluminescence. Steady-state PL spectra were collected using HORIBA LabRAM HR Evolution confocal RAMAN microscope. $473\\ \\mathrm{nm}$ laser ( $0.1\\%$ power) was used to excite all samples at $50\\times$ magnification. Time-resolved photoluminescence (TRPL) spectra were acquired using HORIBA Fluorolog-3 equipped with a 450 W xenon lamp and a TCSPC module (diode laser excitation at $\\lambda\\:=\\:375\\ \\mathrm{nm}$ ) and an integrating sphere (Horiba Quanta- $\\cdot\\varphi$ ) for absolute photoluminescence quantum yield determination. The spectra were corrected for the monochromator wavelength dependence and photomultiplier response functions provided by the manufacturer. \n\nElectronic Structure Calculations. First-principles calculations are based on density functional theory (DFT) as implemented in the VASP package.59−61 All calculations are carried out on the experimentally determined crystal structures. We used the GGA functional in the PBE form, the projector augmented wave (PAW) method62,63 with the PAW data set supplied in the VASP package with the following valence orbitals: Pb $\\mathrm{[5d^{10}}6s^{2}6\\mathrm{p}^{2}]$ , I $\\left[5s^{2}5\\mathrm{p}^{5}\\right]$ , N $[2\\mathsf{s}^{2}2\\mathsf{p}^{3}]$ , $\\mathrm{~H~}[1s^{1}],$ and C $[2s^{2}2\\mathrm{p}^{2}]$ . In addition, the wave functions are expanded using a plane-wave basis set with an energy cutoff of $500~\\mathrm{eV}$ Spin− orbit coupling is systematically taken into account. For band structures $\\left(\\mathrm{pDOS}\\right)$ , the reciprocal space integration is performed over a $4\\times4\\times$ 1 $(8\\times8\\times2)$ Monkhorst-Pack grid for compounds with $n=1$ and $n=$ 3, and over a $4\\times4\\times4$ $(6\\times6\\times6)$ grid for compounds with $n=2$ and $\\textbf{\\textit{n}}=\\textbf{\\textit{4}}$ in their primitive cells.64,65 For pDOS, the localized augmentation charges are calculated with a second finer FFT-mesh smaller than $0.06\\overset{\\leftarrow}{\\mathrm{A}}$ . \n\nDevice Fabrication. FTO glass substrates were coated with PEDOT:PSS by spin-coating at $4000~\\mathrm{rpm}$ for $30\\ \\mathrm{s},$ and then annealed at $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ in air. The 2D perovskite precursors with a molar concentration of $0.6\\mathbf{M}$ were prepared by dissolving the 2D perovskite crystal powders in a mixed solvent of DMF and DMSO with a volume ratio of 4:1. After the crystal powders dissolved, $0.8\\mathrm{\\vol\\\\%\\HI}$ was added into the perovskite precursors. The precursors then were coated on the substrates with a spin rate of $4000~\\mathrm{rpm}$ for $60\\mathrm{~s~}$ in a $\\Nu_{2}$ -filled glovebox. During the spin-coating, $0.7~\\mathrm{\\mL}$ of diethyl ether was dropped on the rotating substrates at $20~\\mathrm{s}$ . After spin-coating, the films were annealed at $100~^{\\circ}\\dot{\\mathrm{C}}$ for $10~\\mathrm{min}$ in the glovebox. To complete the devices, C60 $(20\\ \\mathrm{nm})/\\mathrm{BCP}$ $(5\\ \\mathrm{nm})/\\mathrm{Ag}$ $\\cdot100\\ \\mathrm{nm})$ were sequentially thermally evaporated on top of the perovskites. The active area of the solar cells was $0.09~\\mathrm{cm}^{2}$ . \n\nDevice Characterization. $J{-}V$ curves were measured by a Keithley model 2400 instrument under AM1.5G simulated irradiation with a standard solar simulator (Abet Technologies). The light intensity of the solar simulator was calibrated by a National Renewable Energy Laboratory-certified monocrystalline silicon solar cell. EQE curves were measured by an Oriel model QE-PV-SI instrument equipped with a National Institute of Standards and Technologycertified Si diode. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/jacs.8b00542. \n\nThermal analysis (DSC, TGA, and DTA), calculations, crystallographic details, and device data (PDF) \nX-ray crystallographic data for $\\mathbf{A}^{\\prime}\\mathbf{M}\\mathbf{A}_{n-1}\\mathbf{Pb}_{n}\\mathbf{I}_{3n+1}$ $\\left(\\mathbf{A}^{\\prime}\\ =\\ \\right.$ 3AMP) (CIF) \nX-ray crystallographic data for $\\mathbf{A}^{\\prime}\\mathbf{M}\\mathbf{A}_{n-1}\\mathbf{P}\\mathbf{b}_{n}\\mathbf{I}_{3n+1}$ $\\mathbf{\\langleA^{\\prime}=}$ 4AMP) (CIF) \n\n# \\*konstantinos.stoumpos@northwestern.edu \n\n# ORCID \n\nLingling Mao: 0000-0003-3166-8559 \nWeijun Ke: 0000-0003-2600-5419 \nLaurent Pedesseau: 0000-0001-9414-8644 \nYilei Wu: 0000-0001-6756-1855 \nClaudine Katan: 0000-0002-2017-5823 \nJacky Even: 0000-0002-4607-3390 \nMichael R. Wasielewski: 0000-0003-2920-5440 \nConstantinos C. Stoumpos: 0000-0001-8396-9578 \nMercouri G. Kanatzidis: 0000-0003-2037-4168 \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Department of Energy, Office of Science, Basic Energy Sciences, under Grant SC0012541 (synthesis and structural characterization of materials, M.G.K.). The device assembly and PL lifetime measurements were supported by the ANSER Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, and Office of Basic Energy Sciences under award DESC0001059 (W.K., M.R.W.). The work at FOTON was performed using HPC resources from GENCI-TGCC/ CINES (Grant 2017-0906724). Y.W. thanks the Fulbright Scholars Program for a Graduate Research Fellowship and gratefully acknowledges support of a Ryan Fellowship from the NU International Institute for Nanotechnology (IIN). This work made use of the IMSERC at Northwestern University, which has received support from the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF ECCS-1542205), the State of Illinois, and the International Institute for Nanotechnology (IIN). This work made use of the EPIC, Keck-II, and SPID facilities of Northwestern University’s NUANCE Center, which has received support from the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF ECCS-1542205); the MRSEC program (NSF DMR1121262) at the Materials Research Center; the International Institute for Nanotechnology (IIN); the Keck Foundation; and the State of Illinois, through the IIN. \n\n# REFERENCES \n\n(1) Kojima, A.; Teshima, K.; Shirai, Y.; Miyasaka, T. J. Am. Chem. Soc. 2009, 131, 6050−6051. \n(2) Yang, W. S.; Park, B.-W.; Jung, E. H.; Jeon, N. J.; Kim, Y. C.; Lee, D. U.; Shin, S. S.; Seo, J.; Kim, E. K.; Noh, J. H.; Seok, S. I. Science 2017, 356, 1376−1379. \n(3) Jeon, N. J.; Noh, J. H.; Kim, Y. C.; Yang, W. S.; Ryu, S.; Seok, S. I. Nat. Mater. 2014, 13, 897−903. \n(4) Mei, A.; Li, X.; Liu, L.; Ku, Z.; Liu, T.; Rong, Y.; Xu, M.; Hu, M.; Chen, J.; Yang, Y.; Grätzel, M.; Han, H. Science 2014, 345, 295−298. (5) Lee, M. M.; Teuscher, J.; Miyasaka, T.; Murakami, T. N.; Snaith, H. J. Science 2012, 338, 643−647. \n(6) Green, M. A.; Ho-Baillie, A.; Snaith, H. J. Nat. Photonics 2014, 8, 506−514. \n(7) Li, X.; Ibrahim Dar, M.; Yi, C.; Luo, J.; Tschumi, M.; Zakeeruddin, S. M.; Nazeeruddin, M. K.; Han, H.; Grätzel, M. Nat. Chem. 2015, 7, 703−711. \n(8) Tsai, H.; Nie, W.; Blancon, J.-C.; Stoumpos, C. C.; Asadpour, R.; Harutyunyan, B.; Neukirch, A. J.; Verduzco, R.; Crochet, J. J.; Tretiak, S.; Pedesseau, L.; Even, J.; Alam, M. A.; Gupta, G.; Lou, J.; Ajayan, P. M.; Bedzyk, M. J.; Kanatzidis, M. G.; Mohite, A. D. Nature 2016, 536, 312−316. \n\n(9) Yuan, M.; Quan, L. N.; Comin, R.; Walters, G.; Sabatini, R.; Voznyy, O.; Hoogland, S.; Zhao, Y.; Beauregard, E. M.; Kanjanaboos, P.; Lu, Z.; Kim, D. H.; Sargent, E. H. Nat. Nanotechnol. 2016, 11, 872− 877. (10) Saparov, B.; Mitzi, D. B. Chem. Rev. 2016, 116, 4558−4596. (11) (a) Stoumpos, C. C.; Kanatzidis, M. G. Acc. Chem. Res. 2015, 48, 2791−802. (b) Stoumpos, C. C.; Kanatzidis, M. G. Adv. Mater. 2016, 28, 5778−5793. (12) Pedesseau, L.; Sapori, D.; Traore, B.; Robles, R.; Fang, H.-H.; Loi, M. A.; Tsai, H.; Nie, W.; Blancon, J.-C.; Neukirch, A.; Tretiak, S.; Mohite, A. D.; Katan, C.; Even, J.; Kepenekian, M. ACS Nano 2016, 10, 9776−9786. (13) Cao, D. H.; Stoumpos, C. C.; Farha, O. K.; Hupp, J. T.; Kanatzidis, M. G. J. Am. Chem. Soc. 2015, 137, 7843−50. (14) Smith, I. C.; Hoke, E. T.; Solis-Ibarra, D.; McGehee, M. D.; Karunadasa, H. I. Angew. Chem., Int. Ed. 2014, 53, 11232−11235. (15) Quan, L. N.; Yuan, M.; Comin, R.; Voznyy, O.; Beauregard, E. M.; Hoogland, S.; Buin, A.; Kirmani, A. R.; Zhao, K.; Amassian, A.; Kim, D. H.; Sargent, E. H. J. Am. Chem. Soc. 2016, 138, 2649−2655. (16) Liao, Y.; Liu, H.; Zhou, W.; Yang, D.; Shang, Y.; Shi, Z.; Li, B.; Jiang, X.; Zhang, L.; Quan, L. N.; Quintero-Bermudez, R.; Sutherland, B. R.; Mi, $\\mathrm{Q.;}$ Sargent, E. H.; Ning, Z. J. Am. Chem. Soc. 2017, 139, 6693−6699. (17) Mao, L.; Tsai, H.; Nie, W.; Ma, L.; Im, J.; Stoumpos, C. C.; Malliakas, C. D.; Hao, F.; Wasielewski, M. R.; Mohite, A. D.; Kanatzidis, M. G. Chem. Mater. 2016, 28, 7781−7792. (18) Dohner, E. R.; Jaffe, A.; Bradshaw, L. R.; Karunadasa, H. I. J. Am. Chem. Soc. 2014, 136, 13154−13157. (19) Mao, L.; Wu, Y.; Stoumpos, C. C.; Wasielewski, M. R.; Kanatzidis, M. G. J. Am. Chem. Soc. 2017, 139, 5210−5215. (20) Congreve, D. N.; Weidman, M. C.; Seitz, M.; Paritmongkol, W.; Dahod, N. S.; Tisdale, W. A. ACS Photonics 2017, 4, 476−481. (21) Lanzetta, L.; Marin-Beloqui, J. M.; Sanchez-Molina, I.; Ding, D.; Haque, S. A. ACS Energy Lett. 2017, 2, 1662−1668. (22) (a) Tsai, H.; Nie, W.; Blancon, J. C.; Stoumpos, C. C.; Soe, C. M. M.; Yoo, J.; Crochet, J.; Tretiak, S.; Even, J.; Sadhanala, A. Adv. Mater. 2018, 30, 1704217. (b) Tsai, H.; Nie, W. Y.; Blancon, J. C.; Stoumpos, C. C.; Soe, C. M. M.; Yoo, J.; Crochet, J.; Tretiak, S.; Even, J.; Sadhanala, A.; Azzellino, G.; Brenes, R.; Ajayan, P. M.; Bulovic, V.; Stranks, S. D.; Friend, R. H.; Kanatzidis, M. G.; Mohite, A. D. Adv. Mater. 2018, DOI: 10.29363/nanoge.abxpvperopto.2018.053. (23) Stoumpos, C. C.; Mao, L.; Malliakas, C. D.; Kanatzidis, M. G. Inorg. Chem. 2017, 56, 56−73. (24) Du, K.-z.; Tu, Q.; Zhang, X.; Han, $\\mathrm{Q.;}$ Liu, J.; Zauscher, S.; Mitzi, D. B. Inorg. Chem. 2017, 56, 9291−9302. (25) Hautzinger, M. P.; Dai, J.; Ji, Y.; Fu, Y.; Chen, J.; Guzei, I. A.; Wright, J. C.; Li, Y.; Jin, S. Inorg. Chem. 2017, 56, 14991−14998. (26) Calabrese, J.; Jones, N. L.; Harlow, R. L.; Herron, N.; Thorn, D. L.; Wang, Y. J. Am. Chem. Soc. 1991, 113, 2328−2330. (27) Stoumpos, C. C.; Cao, D. H.; Clark, D. J.; Young, J.; Rondinelli, J. M.; Jang, J. I.; Hupp, J. T.; Kanatzidis, M. G. Chem. Mater. 2016, 28, 2852−2867. (28) Stoumpos, C. C.; Soe, C. M. M.; Tsai, H.; Nie, W.; Blancon, J.- C.; Cao, D. H.; Liu, F.; Traoré, B.; Katan, C.; Even, J.; Mohite, A. D.; Kanatzidis, M. G. Chem. 2017, 2, 427−440. (29) Soe, C. M. M.; Stoumpos, C. C.; Kepenekian, M.; Traoré, B.; Tsai, H.; Nie, W.; Wang, B.; Katan, C.; Seshadri, R.; Mohite, A. D.; Even, J.; Marks, T. J.; Kanatzidis, M. G. J. Am. Chem. Soc. 2017, 139, 16297−16309. (30) Mitzi, D. B.; Feild, C. A.; Harrison, W. T. A.; Guloy, A. M. Nature 1994, 369, 467−469. (31) Papavassiliou, G. C.; Mousdis, G. A.; Raptopoulou, C.; Terzis, A. Z. Naturforsch., B: J. Chem. Sci. 2000, 55, 536−540. (32) Mercier, N. CrystEngComm 2005, 7, 429−432. (33) Zhu, X.-H.; Mercier, N.; Riou, A.; Blanchard, P.; Frère, P. Chem. Commun. 2002, 2160−2161. (34) Mao, L.; Wu, Y.; Stoumpos, C. C.; Traore, B.; Katan, C.; Even, J.; Wasielewski, M. R.; Kanatzidis, M. G. J. Am. Chem. Soc. 2017, 139, 11956−11963. \n\n(35) Luo, J.; Li, L.; Sun, Z.; Wang, P.; Hu, W.; Wang, S.; Ji, C.; Hong, M. Angew. Chem. 2017, 129, 12318−12322. \n(36) Nazarenko, O.; Kotyrba, M. R.; Wörle, M.; Cuervo-Reyes, E.; Yakunin, S.; Kovalenko, M. V. Inorg. Chem. 2017, 56, 11552−11564. (37) Schaak, R. E.; Mallouk, T. E. Chem. Mater. 2002, 14, 1455− 1471. \n(38) Battle, P. D.; Green, M. A.; Lago, J.; Millburn, J. E.; Rosseinsky, M. J.; Vente, J. F. Chem. Mater. 1998, 10, 658−664. \n(39) Dion, M.; Ganne, M.; Tournoux, M. Mater. Res. Bull. 1981, 16, 1429−1435. \n(40) Hojamberdiev, M.; Bekheet, M. F.; Zahedi, E.; Wagata, H.; Kamei, Y.; Yubuta, K.; Gurlo, A.; Matsushita, N.; Domen, K.; Teshima, K. Cryst. Growth Des. 2016, 16, 2302−2308. \n(41) Kendall, K. R.; Navas, C.; Thomas, J. K.; zur Loye, H.-C. Chem. Mater. 1996, 8, 642−649. \n(42) Mousdis, G. A.; Papavassiliou, G. C.; Raptopoulou, C.; Terzis, A. J. Mater. Chem. 2000, 10, 515−518. \n(43) Rayner, M. K.; Billing, D. G. Acta Crystallogr., Sect. E: Struct. Rep. Online 2010, 66, m660−m660. \n(44) Tang, Z.; Guan, J.; Guloy, A. M. J. Mater. Chem. 2001, 11, 479− 482. \n(45) Lemmerer, A.; Billing, D. G. CrystEngComm 2012, 14, 1954− 1966. \n(46) Bulou, A.; Nouet, J. J. Phys. C: Solid State Phys. 1982, 15, 183. (47) Tilley, R. J. Perovskites: Structure-Property Relationships; John Wiley & Sons: New York, 2016; pp 123−155. \n(48) Jacobson, A. J.; Lewandowski, J. T.; Johnson, J. W. Mater. Res. Bull. 1990, 25, 679−686. \n(49) Gopalakrishnan, J.; Bhat, V. Inorg. Chem. 1987, 26, 4299−4301. (50) Jacobson, A. J.; Johnson, J. W.; Lewandowski, J. T. Inorg. Chem. 1985, 24, 3727−3729. \n(51) Stoumpos, C. C.; Cao, D. H.; Clark, D. J.; Young, J.; Rondinelli, J. M.; Jang, J. I.; Hupp, J. T.; Kanatzidis, M. G. Chem. Mater. 2016, 28, 2852−2867. \n(52) Blancon, J.-C.; Tsai, H.; Nie, W.; Stoumpos, C. C.; Pedesseau, L.; Katan, C.; Kepenekian, M.; Soe, C. M. M.; Appavoo, K.; Sfeir, M. Y.; Tretiak, S.; Ajayan, P. M.; Kanatzidis, M. G.; Even, J.; Crochet, J. J.; Mohite, A. D. Science 2017, 355, 1288−1292. \n(53) Peng, W.; Yin, J.; Ho, K.-T.; Ouellette, O.; De Bastiani, M.; Murali, B.; El Tall, O.; Shen, C.; Miao, X.; Pan, J. Nano Lett. 2017, 17, 4759−4767. \n(54) Knutson, J. L.; Martin, J. D.; Mitzi, D. B. Inorg. Chem. 2005, 44, 4699−4705. \n(55) Katan, C.; Pedesseau, L.; Kepenekian, M.; Rolland, A.; Even, J. J. Mater. Chem. A 2015, 3, 9232−9240. \n(56) Liu, G.; Kong, L.; Guo, P.; Stoumpos, C. C.; Hu, $\\mathrm{Q.;}$ Liu, Z.; Cai, Z.; Gosztola, D. J.; Mao, H.-k.; Kanatzidis, M. G.; Schaller, R. D. ACS Energy Lett. 2017, 2, 2518−2524. \n(57) Even, J.; Pedesseau, L.; Dupertuis, M.-A.; Jancu, J.-M.; Katan, C. Phys. Rev. B: Condens. Matter Mater. Phys. 2012, 86, 205301. \n(58) Zhou, N.; Shen, Y.; Li, L.; Tan, S.; Liu, N.; Zheng, G.; Chen, $\\mathrm{Q.;}$ Zhou, H. J. Am. Chem. Soc. 2018, 140, 459−465. \n(59) Kresse, G.; Furthmüller, J. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 11169. \n(60) Kresse, G.; Furthmüller, J. Comput. Mater. Sci. 1996, 6, 15−50. (61) Shishkin, M.; Kresse, G. Phys. Rev. B: Condens. Matter Mater. Phys. 2006, 74, 035101. \n(62) Blöchl, P. E. Phys. Rev. B: Condens. Matter Mater. Phys. 1994, 50, 17953. \n(63) Kresse, G.; Joubert, D. Phys. Rev. B: Condens. Matter Mater. Phys. 1999, 59, 1758. \n(64) Monkhorst, H. J.; Pack, J. D. Phys. Rev. B 1976, 13, 5188. (65) Pack, J. D.; Monkhorst, H. J. Phys. Rev. B 1977, 16, 1748. " + }, + { + "id": "10.1038_s41467-018-07160-7", + "DOI": "10.1038/s41467-018-07160-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-07160-7", + "Relative Dir Path": "mds/10.1038_s41467-018-07160-7", + "Article Title": "High-entropy high-hardness metal carbides discovered by entropy descriptors", + "Authors": "Sarker, P; Harrington, T; Toher, C; Oses, C; Samiee, M; Maria, JP; Brenner, DW; Vecchio, KS; Curtarolo, S", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "High-entropy materials have attracted considerable interest due to the combination of useful properties and promising applications. Predicting their formation remains the major hindrance to the discovery of new systems. Here we propose a descriptor-entropy forming ability-for addressing synthesizability from first principles. The formalism, based on the energy distribution spectrum of randomized calculations, captures the accessibility of equally-sampled states near the ground state and quantifies configurational disorder capable of stabilizing high-entropy homogeneous phases. The methodology is applied to disordered refractory 5-metal carbides-promising candidates for high-hardness applications. The descriptor correctly predicts the ease with which compositions can be experimentally synthesized as rock-salt high-entropy homogeneous phases, validating the ansatz, and in some cases, going beyond intuition. Several of these materials exhibit hardness up to 50% higher than rule of mixtures estimations. The entropy descriptor method has the potential to accelerate the search for high-entropy systems by rationally combining first principles with experimental synthesis and characterization.", + "Times Cited, WoS Core": 765, + "Times Cited, All Databases": 823, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000451176100005", + "Markdown": "# High-entropy high-hardness metal carbides discovered by entropy descriptors \n\nPranab Sarker1, Tyler Harrington2, Cormac Toher1, Corey Oses $\\textcircled{1}$ 1, Mojtaba Samiee3, Jon-Paul Maria4, Donald W. Brenner4, Kenneth S. Vecchio2,3 & Stefano Curtarolo5,6 \n\nHigh-entropy materials have attracted considerable interest due to the combination of useful properties and promising applications. Predicting their formation remains the major hindrance to the discovery of new systems. Here we propose a descriptor—entropy forming ability—for addressing synthesizability from first principles. The formalism, based on the energy distribution spectrum of randomized calculations, captures the accessibility of equally-sampled states near the ground state and quantifies configurational disorder capable of stabilizing high-entropy homogeneous phases. The methodology is applied to disordered refractory 5-metal carbides—promising candidates for high-hardness applications. The descriptor correctly predicts the ease with which compositions can be experimentally synthesized as rock-salt high-entropy homogeneous phases, validating the ansatz, and in some cases, going beyond intuition. Several of these materials exhibit hardness up to $50\\%$ higher than rule of mixtures estimations. The entropy descriptor method has the potential to accelerate the search for high-entropy systems by rationally combining first principles with experimental synthesis and characterization. \n\nHigehn-eonutsr pcryysmt altlienrie s hnaglvei gpha shei (hplyotdeinstoiarldley sdtahbiolimzeoda great deal of research interest1–3. Remarkable properties have been reported: high strength (yield stress ${>}1$ GPa) combined with ductility4–11, hardness5,12,13, superconductivity14, colossal dielectric constant15, and superionic conductivity16. Entropy is thought to play a key-stabilizing role in high-entropy alloys1, entropy-stabilized oxides17,18, high-entropy borides19, and highentropy carbides20–23. The latter three classes consist of disordered metal cation sublattices with several species at equiconcentration combined with oxide15,17,18,24, boride19, or carbide20–23 anion sublattices. These systems offer the potential to combine excellent thermo-mechanical properties and resilient thermodynamic stability given by entropy stabilization with the higher oxidation resistance of ceramics25. The resistance of disordered carbides to extreme heat26–28, oxidation23, and wear makes them promising ultra-high-temperature ceramics for thermal protection coatings in aerospace applications29, and as high-hardness, relatively low-density high-performance drill bits and cutting tools in mining and industry. \n\nSuper-hard transition metal carbides have been known since the 1930s to exhibit significant levels of solid solution26,30,31, and to display high melting temperatures26,27. $\\mathrm{Ta}_{x}\\mathrm{Hf}_{1-x}\\mathrm{C}$ forms a homogeneous solid solution across all composition ranges28,32,33, with $\\mathrm{\\bar{Ta}}_{4}\\mathrm{HfC}_{5}$ exhibiting one of the highest experimentally reported melting points $(\\breve{T}_{\\mathrm{m}}\\sim4263\\mathrm{K}^{26,27})$ . In this case, the two refractory metals randomly populate one of the two rock-salt sublattices28. More recent measurements indicate that the maximum melting point of $4232\\mathrm{K}$ occurs without Ta at the composition $\\operatorname{HfC}_{0.98}{}^{34}$ . Investigation of new carbide compositions will help elucidate the high temperature behavior of these materials, and will provide an avenue to settle the discrepancies in the experimental literature. To discover materials with even more advantageous properties, including increased thermal stability, enhanced strength and hardness, and improved oxidation resistance23, more species and configurations have to be considered. Unfortunately, the lack of a rational, effective, and rapid method to find and characterize the disordered crystalline phase makes it impossible to pinpoint the right combination of species/compositions and the discovery continues by slow and relatively expensive trial and error. \n\nComputationally, the hindrance in in-silico disordered materials development can be attributed to entropy—a very difficult quantity to parameterize when searching through the immense space of candidates (even with efficient computational methods, e.g., Monte Carlo and ab-initio lattice energies in the WangLandau35 or nested sampling36 formalisms). CALPHAD has also been applied successfully2,13,37–39, although it is dependent on the availability of sufficient experimental data. This is the perfect challenge for ab-initio high-throughput computing40 as long as reasonable entropy descriptors—the set of parameters capturing the underlying mechanism of a materials property—can be found. \n\nIn this article, we undertake the challenge by formulating an entropy-forming-ability (EFA) descriptor. It captures the relative propensity of a material to form a high-entropy single-phase crystal by measuring the energy distribution (spectrum) of configurationally randomized calculations up to a given unit-cell size. A narrow spectrum implies a low energy cost for accessing metastable configurations, hence promoting randomness (i.e., entropy) into the system (high-EFA) at finite temperature. In contrast, a wide spectrum suggests a composition with a high energy barrier for introducing different configurations (low-EFA), and thus with a strong preference for ordered phases. The method is benchmarked by the matrix of possible carbides. Given a set of eight refractory metals (Hf, Nb, Mo, Ta, Ti, V, W, and $\\mathrm{zr}$ ) plus carbon, the formalism predicts the matrix of synthesizable fivemetal high-entropy carbides. Candidates are then experimentally prepared, leading to a novel class of systems. In particular, it is demonstrated that the descriptor is capable of reliably distinguishing between the compositions that easily form homogeneous single phases and the ones that do not, including identifying compositions that form single phases despite incorporating multiple binary carbide precursors with different structures and stoichiometric ratios. Note that because of the differing stoichiometries of the non-rock-salt phase binary carbide precursors $\\mathrm{Mo}_{2}\\mathrm{C}$ and ${\\mathrm{W}}_{2}{\\mathrm{C}},$ the compositions listed in this work are nominal. There are extensive carbon vacancies in the anion sublattice in the synthesized materials, further contributing to the configurational entropy. Several of these materials display enhanced mechanical properties, e.g., Vickers hardness up to $50\\%$ higher than predicted by a rule of mixtures (ROM). Thus, this class of materials has strong potential for industrial uses where dense and wearresistant impactors are needed, particularly for extreme temperature applications. The successful outcome demonstrates the strength of the synergy between thermodynamics, highthroughput computation, and experimental synthesis. \n\n# Results \n\nEFA formalism. To accelerate the search in the chemical space, the entropy content of a compound is estimated from the energy distribution spectrum of metastable configurations above the zero-temperature ground state. At finite $T,$ any disordered state can be present with a probability given by the Boltzmann distribution and the state’s degeneracy. Note that configurations are randomly sampled up to a given unit-cell size: the larger the size, the more accurately the spectrum represents the real thermodynamic density of states. \n\nThe energy distribution $\\left(H_{i}\\right)$ spectrum can be quantitatively characterized by its standard deviation $\\sigma_{:}$ , so that the $\\sigma$ becomes the descriptor for S: the smaller $\\sigma_{:}$ the larger S. The descriptor for an $N.$ -species system, called the EFA, is defined as the inverse of the $\\sigma$ of the energy spectrum above the ground state of the $N.$ -system at zero temperature: \n\n$$\n\\mathrm{EFA}(N)\\equiv\\left\\{\\sigma[\\mathrm{spectrum}(H_{i}(N))]_{T=0}\\right\\}^{-1}\n$$ \n\nwhere \n\n$$\n\\sigma\\{H_{i}(N)\\}=\\sqrt{\\frac{\\displaystyle\\sum_{i=1}^{n}g_{i}(H_{i}-H_{\\operatorname*{mix}})^{2}}{\\displaystyle\\left(\\sum_{i=1}^{n}g_{i}\\right)-1}},\n$$ \n\nwhere $n$ is the total number of sampled geometrical configurations and $g_{i}$ are their degeneracies. $H_{\\mathrm{mix}}$ is the mixed-phase enthalpy approximated by averaging the enthalpies $H_{i}$ of the sampled configurations: \n\n$$\nH_{\\mathrm{mix}}=\\frac{\\displaystyle\\sum_{i=1}^{n}g_{i}H_{i}}{\\displaystyle\\sum_{i=1}^{n}g_{i}}.\n$$ \n\nThe broader the spectrum, the more energetically expensive it will be to introduce configurational disorder into the system, and thus the lower the EFA. EFA is measured in $(\\mathrm{eV/atom})^{-1}$ . \n\nEFA calculation. A total of 56 five-metal compositions can be generated using the eight refractory metals ${\\bar{(}}8!/5!3!=56{\\mathrm{~}}$ of interest (Hf, Nb, Mo, Ta, Ti, V, W, and $\\mathrm{Zr}^{\\cdot}$ ). For each composition, the Hermite normal form superlattices of the Automatic FLOW (AFLOW) partial occupation (AFLOWPOCC) method41 generate 49 distinct 10-atom-cell configurations, resulting in a total of 2744 configurations needed to determine the EFA of this composition space (Methods section). The ab-initio calculated EFA values for the full set of 56 fivemetal compositions are provided in Table 1. Nine candidates are chosen from this list for experimental synthesis and investigation: (i) the three candidates with the highest value of EFA (MoN${\\mathsf{b T a V W C}}_{5}$ $\\mathrm{\\DeltaEFA}=125$ $(\\mathrm{eV/atom})^{-1},$ ), $\\mathrm{{HfNbTaTiZrC}}_{5}$ $\\mathrm{\\EFA=}$ 100 $\\left(\\mathrm{eV/atom}\\right)^{-1}.$ ), $\\mathrm{HfNbTaTiVC}_{5}$ $\\mathrm{EFA}=100$ $\\left(\\mathrm{eV/atom}\\right)^{-1}.$ ), high probability of forming high-entropy single phases), (ii) the two candidates with the lowest value of EFA $\\mathrm{(HfMoVWZrC_{5}}$ (37 $(\\mathrm{eV/atom})^{-1};$ ), HfMoTi $\\mathrm{WZrC}_{5}$ (38 $\\mathrm{(eV/atom)^{-1}},$ , low probability of forming high-entropy single phases), and (iii) four chosen at random with intermediate EFA $(\\mathrm{NbTaTiVWC}_{5}$ (77 (eV/atom) $^{-1})$ , HfNbTaTiWC5 (67 $(\\mathrm{eV/atom)^{-1}}_{.}$ ), HfTaTiWZrC5 (50 (eV/ $\\mathsf{a t o m})^{-1}$ ), and $\\mathrm{HfMoTaWZrC}_{5}$ (45 $(\\mathrm{eV/atom})^{-1})$ ). Figure 1a shows the energy distribution and EFA values obtained ab initio from configurations generated with AFLOW for the nine chosen systems. For $\\mathrm{MoNbTaVWC}_{5}$ , $\\mathrm{HfNbTaTiZrC}_{5},$ and HfNbTa${\\dot{\\mathrm{TiVC}}}_{5},$ , most of the configurations are within 20 meV/atom of the lowest energy state, and the distributions have an EFA of at least 100 $)\\mathrm{(eV/atom)^{-1}}$ . Therefore, at finite temperature, most of the configurations should have a high probability of being formed, so that a high level of configurational randomness is expected to be accessible in the three systems, making them promising candidates to form a high-entropy homogeneous single phase. Achieving a similar level of configurational randomness would be progressively more difficult in NbTaTiVWC5, HfNbTaTiWC5, and $\\mathrm{\\Delta\\bar{Hf{Ta}T i W Z r C{_{5}}}}$ as the different configurations display a broader energy distribution, with EFAs ranging from 50 to 77 $(\\mathrm{eV/atom})^{-1}$ . A higher energy cost is needed to incorporate configurational entropy into these three compositions, so forming a homogeneous single phase will be more difficult. For HfMo$\\mathrm{TaWZr}\\bar{\\mathrm{C}}_{5}$ , $\\mathrm{HfMoTi\\bar{W}Z r C}_{5}$ , and $\\mathrm{HfMoVWZrC}_{5}$ , the spread of energies for the configurations is very wide, with EFA values from 45 down to 37 $(\\mathrm{eV/atom})^{-1}$ . These materials would be expected to be very difficult to synthesize as a homogeneous single phase. \n\nCompeting ordered phases. The phase diagrams for the fivemetal carbide systems were generated to investigate the existence of binary and ternary ordered structures that could compete with the formation of the high-entropy single phase. First, prototypes for experimentally reported binary and ternary carbide structures42,43 are used to calculate the formation enthalpies of additional ordered phases for the AFLOW database. The results are used to generate the convex hull phase diagrams for all 56 compositions using the AFLOW-CHULL module44. The relevant binary and ternary convex hulls are illustrated in Supplementary Figures 1–36. The distance along the enthalpy axis of the lowest energy AFLOW-POCC configuration from the convex hull, $\\Delta H_{\\mathrm{f}},$ is listed in Table 1 (the decomposition reaction products are summarized in Supplementary Table 2). A rough estimation of the synthesis temperature $T_{s}$ (see the analogous EntropyStabilized Oxides case, Fig. 2 of ref.17)—can be calculated by dividing $\\Delta H_{\\mathrm{f}}$ by the ideal configuration entropy (Supplementary Table 1, with the ideal entropy per atom evaluated as $0.5k_{\\mathrm{B}}\\dot{\\times}$ $\\log0.2$ , since $k_{\\mathrm{B}}\\times\\log0.2$ is the entropy per metal carbide atomic pair). A precise characterization of the disorder requires more expensive approaches, such as the LTVC method45, and is beyond the scope of this article. The highest temperature is $2254\\mathrm{K}.$ which is less than the synthesis temperature of $2200^{\\circ}\\mathrm{C}$ (2473 K), indicating that during sintering the disordered phases are thermodynamically accessible with respect to decomposition into ordered compounds. In analogy to the formation of metallic glasses where energetic confusion obstructs crystalline growth46,47 once the temperature is reduced, systems with high EFA remain locked into ensembles of highly degenerate configurations, retaining the disorder achieved at high temperature. Hence, EFA provides a measure of the relative synthesizability of the disordered composition. \n\nFrom enthalpy to entropy. It is important to consider that the metal carbide precursors have very strong covalent/ionic bonds, and are therefore enthalpy stabilized48. However, the same might not be the case for their mixture. In fact, a statistical analysis of the AFLOW.org enthalpies44 indicates that the gain in formation enthalpy by adding mixing species, $\\Delta H_{\\mathrm{f}}(\\boldsymbol{N}+1)-\\Delta H_{\\mathrm{f}}(\\boldsymbol{N}).$ decreases with $N,$ and can easily be overcome by the monotonic increase in entropy-gain for the disordered systems (to go from order to complete or partial disorder). In the AFLOW analysis, the threshold between low- and high-entropy systems is around four mixing species. To have completely entropy-stabilized materials, five mixing species are required (similar to the Entropy-Stabilized Oxides17). For carbides in which only the metal-sublattice is randomly populated, five metals should be enough to achieve carbide entropy stabilization, especially at equi-composition. Notably, if other sublattices were also allowed to contain disorder, (e.g., reciprocal systems like $\\mathrm{Ta}_{x}\\mathrm{Hf}_{1-x}\\mathrm{C}_{1}$ $-y^{26,27})$ , then the overall number of species might reduce. In this example, entropy was increased by introducing point defects (vacancies)—a promising strategy to improve high temperature performance. In $\\mathrm{HfC}_{1-x},$ the reduction of C to sub-stoichiometry enhances the stabilizing effect of the configurational entropy on the solid phase, offsetting its Gibbs free energy (vacancies can only exist in the solid phase) leading to an overall increase in melting point (see ref.28). \n\n
Table1Resultsforthecalcuatedentrofring-abilty(EFA)descrptorengeticdistancefromsix-dimensionalcexhull (△H)and vibrationalfreeenergy at 2oK(△Fvib)for thefive-metalcarbide systems,arranged indescendingorder of EFA
FvibExp.SystemH
SystemEFA△HEFAFvibExp.εSystemEFAH FvibExp.ε
MoNbTavWC5125156 -14sss0.063HfNbTaVWC567110TaTiVWZrCs5096
HfNbTaTiZrC510019-120.094HfMoTaTiVC56782NbTiVWZrC55093
HfNbTaTiVC510056-310.107HfMoNbTiZrC56753HfMoTiVZrC55096
MoNbTaTiVC510082MoNbTaWZrC563133HfMoTaVZrC55092
NbTaTiVZrC58364 48HfMoTaTiZrC56355HfMoNbVZrC55089
HfMoNbTaTiC58392-19S0.124NbTaTiWZrC5 MoTaTiVZrC55961MoTaVWZrC548148
NbTaTiVWC577111.MoNbTiVZrCs59 5992MoTaTiWZrC5 MoNbVWZrC54894
MoNbTaTiWC577 71122MoNbTaVZrC55987.MoNbTiWZrC548 48146
MoNbTiVWC57157HfNbTiVWC559108 81HfMoNbWZrC54889 101
MoNbTaTiZrCs7173HfNbTaWZrC55953HfTiVWZrC54599
HfTaTiVZrC5 HfNbTiVZrCs7173NbTaVWZrC556119HfNbVWZrC54594
HfMoNbTiVC57177HfTaTiVWC55684HfMoTiVWC54597
HfMoNbTaZrC57148HfMoTaVWC556139HfMoTaWZrC545105M0.271
HfMoNbTaWC571126 99HfMoNbVWC556137HfTaVWZrCs4397
HfMoNbTaVC57153S0.171HfNbTiWZrCs53 5356MoTiVWZrCs HfMoTiWZrC540 38107
HfNbTaTiWC567128HfMoTaTiWC5 HfMoNbTiWC55384HfMoVWZrC53783 141M0.315
MoTaTiVWC567605081M0.325
HfNbTaVZrC567HfTaTiWZrC559S0.169
\n\nNine compositions are selected for experimental investigation. The lattice distortion, ε, is obtained from the peak broadening in XRD. S: single-phase formed; M: multi-phase formed in experiment. Note that the compositions listed here are nominal, and the actual synthesized compositions can vary due to the presence of carbon vacancies in the anion sublattice. Units: EFA in $(\\mathsf{e V}/\\mathsf{a t o m})^{-1}$ ; $\\Delta H_{\\mathrm{f}}$ and $\\Delta F_{\\mathrm{vib}}$ in (meV/atom); and $\\varepsilon$ in $\\%$ \n\n![](images/0d720a4bfc3c6573009bf07c0caeb614f56c659f086fd0252c43940328ae7cf6.jpg) \nFig. 1 Schematics of high-entropy carbides predictions. a The energy distribution of different configurations of the $9$ five-metal carbides: MoNbTaVWC5, HfNbTa $\\Gamma_{1}\\ Z r{\\mathsf C}_{5},$ HfNbTaT $\\because V C_{5},$ NbTaTiVWC5, HfNbTaTiWC5, HfTaTiW $/Z_{r}C_{5},$ HfMoTa $\\mathsf{W Z r C}_{5},$ HfMoT $\\mathsf{i W Z r C}_{5},$ and ${\\mathsf{H f f}}M{\\mathsf{o}}{\\mathsf{V W}}Z{\\mathsf{r}}{\\mathsf{C}}_{5};$ spectrum is shifted so that the lowest energy configuration for each composition is at zero. The energy spectrum for each composition indicates its propensity to form the high-entropy single phase: the narrower the distribution, the more likely it is to form a high-entropy single phase at finite T. b The $\\mathsf{X}$ -ray diffraction patterns for the same 9 five-metal carbides, where the first six compositions exhibit only the desired fcc structure peaks, whereas the additional peaks for remaining three compositions indicate the presence of secondary phases. The small peaks at $2\\theta=31.7^{\\circ}$ , marked by the diamond symbol in the spectra of HfNbTaTiZrC5, HfNbTaTiWC $_5$ and HfTaTiW $\\mathsf{Z r C}_{5},$ are from the (111) plane of a monoclinic $(\\mathsf{H f},\\mathsf{Z r})\\mathsf{O}_{2}$ phase that remains due to processing \n\nExperimental results. To validate the predictions, the nine chosen carbides are experimentally synthesized and characterized (see Methods section). The chemical homogeneity of each sample is measured using energy-dispersive X-ray spectroscopy (EDS), whereas the crystalline structure is determined via $\\mathrm{\\DeltaX}$ -ray diffraction (XRD). \n\nAn example of the evolution of a sample of composition HfNbTa $\\mathrm{TiV}\\bar{\\mathrm{C}}_{5}$ through each processing step is given in Fig. 2a, demonstrating the densification and homogenization into a single rock-salt structure. At least three distinct precursor phases are distinguishable in the mixed powder pattern. Following ball milling, the individual phases are still present, however, the peaks are considerably broadened, which is due to particle size reduction and mechanical alloying. Following the final spark plasma sintering (SPS) step at $2200^{\\circ}\\mathrm{C},$ the sample consolidates into a bulk solid pellet of the desired single rock-salt phase indicating the successful synthesis of a high-entropy homogeneous carbide. \n\nResults of XRD analysis for each sample following SPS at 2200 ${}^{\\circ}\\mathrm{C},$ presented in Fig. 1b, demonstrate that compositions MoN${\\mathsf{b T a V W C}}_{5}$ , HfNbTa $\\mathrm{TiZrC}_{5}$ , HfNbTaTiVC5, HfNbTaTiWC5, NbTaTiVWC5, and HfTaTi $\\mathrm{.WZrC_{5}}$ (the top 6) only exhibit single fcc peaks of the desired high-entropy phase (rock-salt), whereas HfMoTa $.{\\mathrm{WZrC}}_{5} $ HfMoTiWZrC5, and $\\mathrm{\\bar{HfMoVWZrC}}_{5}$ (the bottom 3) show multiple structures. The small peaks at $2\\theta=31.7^{\\circ}$ , marked by the diamond symbol in the spectra of $\\mathrm{HfNbTaTiZrC}_{5}$ , HfNbTaT $\\mathrm{\\ddot{i}W C}_{5}$ , and $\\mathrm{\\dot{H}f T a T i W Z r C}_{5}$ in Fig. 1b, are from the (111) plane of a monoclinic (Hf, $\\phantom{+}Z\\mathbf{r})\\mathrm{O}_{2}$ phase that remains due to processing. The volume fraction of this phase is $<5\\%$ and does not significantly alter the composition of the carbide phase. The distinguishable second phase in HfMoTa $\\mathrm{WZrC}_{5}$ is identified as a hexagonal phase. One and two secondary fcc phases are observed for $\\mathrm{\\bar{HfMoVWZrC}}_{5}$ and HfMoTi $\\mathrm{WZrC}_{5}$ , respectively. Microstructure analysis and selected elemental mapping (Figs. 2c–d) confirm that the systems displaying single phases are chemically homogeneous, whereas the multi-phase samples undergo chemical segregation. For example, only grain orientation contrast is present in the HfNbTa $\\mathrm{{IiZrC}}_{5}$ microstructure, and no indication of notable clustering or segregation is visible in its compositional maps. On the contrary, a clear chemical phase contrast is observable in the microstructure of the multi-phase HfMoT $\\mathsf{I W Z r C}_{5}$ sample, and the compositional maps demonstrate that the secondary phase, apparent in XRD, is W- and Mo-rich. \n\n![](images/462c79cfebfc9778345157dece2f28d3ea5ef3f30f1fb746c381504d7e6cdc21.jpg) \nFig. 2 Experimental results for high-entropy carbides synthesis and characterization. a Progression of a sample of HfNbTaTiVC5 through each processing step: hand mixing (magenta spectrum, bottom), ball milling (blue spectrum, center), and spark plasma sintering (green spectrum, top), depicting the evolution towards the desired rock-salt crystal structure $(a_{\\mathrm{exp}}=4.42\\AA)$ . b Linear relationship between $\\mathsf{E F A}^{-1}$ and the distortion of experimental lattice parameters $\\varepsilon$ . Green circles and red squares indicate homogeneous high-entropy single- and multi-phase compounds, respectively. c, d Electron micrographs of single-phase HfNbTa $\\mathtt{T i Z r C}_{5}$ and multi-phase HfMoTa $\\mathsf{V Z r C}_{5}$ specimens. e, f Selected EDS compositional maps of the HfNbTaTiZrC5 and HfMoTaWZrC5 specimens. The micrographs show the presence of the secondary phase in HfMoTaWZrC5 (circles) that is also present in XRD results, which is revealed to be a W- and Mo-rich phase. Scale bars, $10\\upmu\\mathrm{m}$ (c–f) \n\nHomogeneity analysis. Peak broadening in XRD patterns (Fig. 1b) is used to quantify the level of structural homogenization achieved in the samples. According to the Williamson–Hall formulation49, broadening in XRD is principally due to crystallite size $(\\propto1/\\cos\\theta_{\\mathrm{:}}$ $\\theta=$ Bragg angle) and lattice strain $(\\propto1/\\tan\\theta)$ . For multi-component systems, significant broadening is expected to occur due to local lattice strains and variations in the interplanar spacings throughout the sample50. The latter can be attributed to the inhomogeneous distribution of the elements, the extent of which can be evaluated by applying the analysis to a multicomponent system, which has only a single lattice structure and is assumed strain free50. \n\nThe lattice distortion of the rock-salt phase in the single-phase materials (or the most prevalent in the multi-phase ones) is determined by using the relationship between broadening $\\beta_{\\mathrm{{S}}}$ and Bragg angle $\\theta$ (Methods section): \n\n$$\n\\beta_{\\mathrm{{S}}}\\mathrm{cos}\\theta=4\\varepsilon\\mathrm{sin}\\theta+\\frac{K\\lambda}{D},\n$$ \n\nwhere $\\varepsilon$ is the lattice strain or variation in interplanar spacing due to chemical inhomogeneity, $K$ is a constant (dependent on the grain shape), $\\lambda$ is the incident $\\mathrm{\\DeltaX}$ -ray wavelength, and $D$ is the crystallite size. Since materials are assumed strain free, $\\varepsilon-$ obtained by inverting Eq. 4—represents the relative variation of the lattice parameter due to inhomogeneity. Thus, $\\varepsilon$ is both a measure of homogeneity and of the effective mixing with respect to the ideal scenario. The results for the EFA descriptor, the experimental characterization, as well as the values for ε for all nine carbides compositions are given in Table 1. The values for ε range from $0.063\\%$ for $\\mathrm{MoNbTaVWC}_{5}$ and $0.094\\%$ for $\\mathrm{HfNbTaTiZrC}_{5}$ (the most homogeneous materials) to $0.325\\%$ for $\\mathrm{HfMoVWZrC}_{5}$ (the least homogeneous material). Overall, the experimental findings agree well with the predictions of EFA descriptor, validate its ansatz and indicate a potential threshold for our model of five-metal carbides: EFA $\\sim\\dot{5}0(\\mathrm{eV/atom})^{-1}\\Rightarrow$ homogeneous disordered single phase (high entropy). \n\nHigh-entropy synthesizability. The comparison between the EFA predictions and the homogeneity of the samples is analyzed in Fig. 2b. Although the Williamson–Hall formalism does not provide particularly accurate absolute values of $\\varepsilon_{\\mathrm{{i}}}$ it is effective for comparing similarly processed samples, determining the relative homogeneity. The lattice distortion ε (capturing homogeneity) decreases linearly with the increase of EFA. The Pearson (linear) correlation of $\\mathrm{EFA}^{-1}$ with $\\varepsilon$ is 0.97, whereas the Spearman (rank order) correlation is 0.98. As such, the EFA takes the role of an effective high-entropy synthesizability descriptor. \n\nThree facts are relevant. (i) Intuitively, several of the carbide compositions that easily form a highly homogeneous phase, particularly HfNbTaT $\\mathrm{\\ddot{i}\\dot{V}C_{5}}$ and HfNbTaT $\\mathrm{\\because\\mathrm{zr}C}_{5}$ , come from binary precursors having the same structure and ratio of anions to cations as the final high-entropy material. (ii) Counterintuitively, the highest-EFA and most homogeneous phase $\\mathrm{MoNbTaVWC}_{5}$ is made with two precursors having different structures and stoichiometric ratios from the high-entropy material, specifically orthorhombic $\\alpha{\\mathrm{-}}\\mathrm{Mo}_{2}\\mathrm{C}$ and hexagonal $\\alpha$ - ${\\mathrm{W}}_{2}{\\mathrm{C}},$ leading to a final sub-stoichiometric $\\mathrm{MoNbTa}\\bar{\\mathrm{VW}}\\mathrm{C}_{5-x}$ . \n\nThe additional disorder provided by the presence of vacancies in the C-sublattice is advantageous: it allows further entropy stabilization, potentially increasing the melting point vis- $\\cdot\\dot{\\mathbf{a}}$ -vis the stoichiometric composition28. An investigation of the effect of carbon stoichiometry is clearly warranted, although it is outside of the scope of this study. (iii) For tungsten and molybdenum, metal-rich carbides are used because of the difficulties in obtaining molybdenum monocarbide (MoC) powder, or tungsten monocarbide (WC) powder in the particle sizes compatible with the other precursors, hindering consistent mixing, sintering and homogenization. It should be noted that additional samples of $\\mathrm{MoNb7aVWC}_{5}$ were also synthesized using hexagonal WC with a smaller particle size, and the homogeneous rock-salt phase was again successfully obtained (see Supplementary Figure 37). The existence of phase-pure MoNbTaVWC5 indicates that, similar to the rock-salt binary carbides, the multi-component carbide is stable over a range of stoichiometry. From experimental/ phenomenological grounds, the formation of such a phase is surprising. The equi-composition binary carbides MoC and WC have hexagonal ground states, and their rock-salt configurations have significantly higher formation enthalpy51. Considering these facts, there are no experimental indications that adding Mo and W would contribute to stabilizing the most homogeneous rocksalt five-metal carbide that was predicted by the EFA and later validated experimentally. The arguments demonstrate the advantage of a descriptor that quantifies the relative EFA over simple empirical/phenomenological rules, in that it correctly identifies this composition as having a high propensity to form a single phase, while simultaneously correctly predicting that several other systems having both Mo and W subcomponents undergo phase separation. \n\nMechanical properties. The Vickers hardness, $H_{\\mathrm{V}},$ and elastic modulus, $E,$ of both the binary carbide precursors and the synthesized five-metal single-phase compositions are measured using nanoindentation, where the properties are extracted from loaddisplacement curves (see Supplementary Figure 38(a)). The binary precursor samples for these measurements are prepared and analyzed using the same protocol to ensure the validity of the comparisons (see Methods section for more details). The results for the five-metal compositions are in Table 2, whereas those for the binary carbides are listed in Table 3. It is found that, for the five-metal compositions, the measured $H_{\\mathrm{V}}$ and $E$ values exceed those predicted from a ROM based on the binary precursor measurements. The enhancement of the mechanical properties is particularly strong in the case of $\\mathrm{HfNbTaTiZrC}_{5},$ where the measured $E$ and $H_{\\mathrm{V}}$ exceed the ROM predictions by 10 and $50\\%$ , respectively (see Supplementary Figure 38(b) for a comparison between the $H_{\\mathrm{V}}$ results obtained from calculation, experiment, and ROM). Mass disorder is one possible source of the enhanced hardness: deformation is caused by dislocation movements and activation energy is absorbed and released at each lattice step. An ideal ordered system can be seen as a dislocation-wave-guide with matched (uniform) impedance along the path: propagation occurs without any relevant energy reflection and/or dispersion. This is not the case for disordered systems: mass inhomogeneity causes impedance mismatch, generating reflections and disturbing the transmission by dispersing (scattering) its group energy. Macroscopically the effect is seen as increased resistance to plastic deformations—more mechanical work is required—i.e., increase of hardness. Other possible causes of increased hardness include solid solution hardening5,13,20, where the atomic size mismatch results in lattice distortions, limiting the motion of dislocations necessary for plastic deformation; and changes in the slip systems and the ease with which slip can occur20,52. \n\n
Table 2Resultsformechanicalproperties(bulk:hear:Gandelastcmduli:EandVickershardness:H)forsixinglehase high-entropy carbides
B SystemGEHv,Chen Hv,Teter
AFLOWExp.AFLOWExp.AFLOWExp. (ROM)AFLOWAFLOW Hv,TianAFLOW Exp. Hv,exp
(ROM) MoNbTaVWC5(ROM)(ROM) 183 (183)(ROM) 226(-)(ROM) 460 (459)533±32 (-)(ROM)(ROM)(ROM) (ROM)
HfNbTaTiZrC5312 (321) 262 (267)278 (-) 235192 (165) 188464 (455) 443 ±4020 (20) 27 (25)28 (28) 29 (28)20 (20) 27 (25)27±3(-) 32±2
HfNbTaTiVC5(232)(184)(436±30)(23±2)
276 (279)267196 (196) 212475 (476) 503±4026 (26)30 (30)26 (26)29±3 (24±2)
HfNbTaTiWC5291 (296)(239) 252 (-)203 (186)(189) 205 (-)493 (459)(449 ±30) 483±24 (-)26 (22)31 (28)26 (22) 31±2(-)
NbTaTiVWC5305 (304)253 (-)199 (189)206 (-)490 (460)485±36 (-) 24 (22)30 (29)24 (23)28±2(-)
HfTaTiWZrC5274 (280)246 (-)191 (178)200 (-)466 (438)473±26 (-)25 (21)29 (27)25 (21) 33±2 (-)
\n\nThree different models: Chen et al. 54, Teter 55, and Tian et al. 56 are used to calculate theoretical hardness values (only for the two non-W-containing compositions) from B and G. The ROM values ar obtained from the results in this work for rock-salt structure binary carbide s listed in Table 3. Since Mo and WC do not form a stable rock-salt phase at room temperature, the experimental ROMs for Mo- and W-containing compositions are not available, as indicated by (–). Units: $B,G,E,$ and $H_{\\lor}$ in $(\\mathsf{G P a})$ \n\n
Table3Resultsformchanical properties(bulkBshear:Gandelastic:Emduli,andVickershardnessHforeight roksalt structure binary carbides
B
SystemAFLOWExp.aG AFLOW Exp.Exp.aE AFLOWExp.Exp.aHv ChenTeterTianExp.Exp.a
Exp.
HfC239 241223186179-193181443316-461428±3229282819-2525±2
MoC33515239612231327-83b
NbC297296-378246 199197-245 177488330-537429 ± 4625302519-2517±3
TaC326248-343 219213215-227184525241-722431± 4425322516-2314±2
TiC251241255 181186207438447-451489 ± 132627253231±2
VC283389250 199157196484268-420465± 1326302620-2929±1
WC365153403112312> 28℃
ZrC221220216 157172169381385-406402± 1323282223-2524±1
\n\nThe AFLOW values are calculated using the Voigt-Reuss-Hill average and the Automatic Elasticity Library (AEL) module53, whereas $H_{\\vee}$ is estimated using three different models described in the literature. These results are compared with two sets of available measured data, obtained from the literature72,73 and the current experiments. Units: B, G, E, and $H_{\\vee}$ in $(\\mathsf{G P a})$ aThis work $^{\\mathsf{b}}\\alpha\\mathbf{-}M\\circ\\mathsf{C}_{1-x}+\\eta$ -MoC + γ-MoC composite74 ${^\\mathrm{c}W}\\mathsf{C}_{1-x};x=0.36\\substack{-0.41}^{75}$ \n\nElastic properties are calculated using AFLOW41,53 for the fivemetal compositions $\\mathrm{MoNbTaVWC}_{5}$ , HfNbTa $\\mathrm{{IiZrC}}_{5}$ , HfNbTa${\\mathrm{TiVC}}_{5},$ , HfNbTaTiWC5, $\\mathrm{NbTaTiVWC}_{5}$ , and $\\mathrm{HfTaTiWZrC}_{5}$ (Table 2) and their precursors. In general, results are within the experimentally reported ranges for the binary carbides (Table 3 in the Methods section). $H_{\\mathrm{V}}$ values are estimated from the bulk and shear moduli using the models introduced by Chen et al.54, Teter55, and Tian et al.56. Computational models do not consider plastic deformation mechanisms in inhomogeneous systems and thus $H_{\\mathrm{V}}$ predictions underestimate experiments, leading to results consistent with the ROM of binary carbides (Table 2). The outcome further corroborates that the experimentally observed enhancement of the mechanical properties is due to disorder. \n\nVibrational contribution to formation free energy. The vibrational contributions to the formation Gibbs free energy, $\\Delta F_{\\mathrm{vib}},$ at $2000\\mathrm{K}$ are listed in Table 1 for the six compositions synthesized as a single phase. The vibrational free energies, $F_{\\mathrm{vib}},$ are calculated using the Debye–Grüneisen model implemented in the AFLOW–Automatic GIBBS Library (AGL) module57, using the Poisson ratio calculated with AFLOW–Automatic Elasticity Library (AEL)53. The average $F_{\\mathrm{vib}}$ for the five-metal compositions are calculated, weighted according to the Boltzmann distribution at $2000\\mathrm{K}$ . The vibrational contribution to the formation Gibbs free energy, $\\Delta F_{\\mathrm{vib}},$ for each composition is obtained from the difference between its average $F_{\\mathrm{vib}}$ and the average $F_{\\mathrm{vib}}$ of its component binary carbides. $\\Delta F_{\\mathrm{vib}}$ at $2000\\mathrm{K}$ ranges from $\\mathrm{\\sim}0\\mathrm{meV},$ atom for HfNbTaTiWC5 to $-31\\mathrm{meV}/\\mathrm{atom}$ for HfNbTa $\\mathrm{TiVC}_{5}.$ which are significantly less than the total entropy contribution (mostly configurational plus vibrational) required to overcome the values of $50\\mathrm{meV}/\\$ atom to $150\\mathrm{meV}/\\$ atom for the formation enthalpy $\\Delta H_{\\mathrm{f}}.$ These results are in agreement with previous observations that the vibrational formation entropy is generally an order of magnitude smaller than the configuration entropy39,58. \n\n# Discussion \n\nIn this article, an EFA descriptor has been developed for the purpose of capturing synthesizability of high-entropy materials. The framework has been applied to refractory metal carbides, leading to the prediction and subsequent experimental discovery of homogeneous high-entropy single phases. The method is able to quantitatively predict the relative propensity of each composition to form a homogeneous single phase, thus identifying the most promising candidates for experimental synthesis. In particular, the experiments validate the prediction that the composition MoNbTa $\\mathrm{.VWC}_{5}$ should have a very high propensity to form a homogeneous single phase, despite incorporating both $\\mathrm{\\tilde{Mo}}_{2}\\mathrm{C}$ and ${\\mathrm{W}}_{2}{\\mathrm{C}},$ which have different structures (hexagonal and/or orthorhombic instead of rock-salt) and stoichiometric ratios from the five-metal high-entropy material. \n\nFurthermore, it is demonstrated that disorder enhances the mechanical properties of these materials: $\\mathrm{IfNbTaTiZrC}_{5}$ and HfTaT $\\mathrm{WZrC}_{5}$ are measured to have hardness of $32\\mathrm{GPa}$ (almost $50\\%$ higher than the ROM prediction) and $33\\mathrm{GPa}$ , respectively, suggesting a new avenue for designing super-hard materials. The formalism could become the long-sought enabler of accelerated design for high-entropy functional materials with enhanced properties for a wide range of different technological applications. \n\n# Methods \n\nSpectrum generation. The different possible configurations required to calculate the energy spectrum are generated using the AFLOW-POCC algorithm41 implemented within the AFLOW computational materials design framework51,59,60. The algorithm initially generates a superlattice of the minimum size necessary to obtain the required partial occupancies within some user-specified accuracy. For each unique superlattice, the AFLOW-POCC algorithm then generates the complete set of possible supercells using Hermite normal form matrices41. Non-unique supercell combinations are eliminated from the ensemble by first estimating the total energies of all configurations using a Universal Force Field41,61 based method, and then identifying duplicates from their identical energies. \n\nStructure generation. In the case of the high-entropy carbide17 systems investigated here, the AFLOW-POCC algorithm starts with the rock-salt crystal structure (spacegroup: $F m\\bar{3}m$ ; $\\#225$ ; Pearson symbol: cF8; AFLOW Prototype: AB_c$\\mathrm{F8}_{-}22\\bar{5}_{-}\\mathrm{a}_{-}\\bar{\\mathrm{b}}^{62})$ as the input parent lattice. Each anion site is occupied with a C atom (occupancy probability of 1.0), whereas the cation site is occupied by five different refractory metal elements, with a 0.2 occupancy probability for each. The AFLOW-POCC algorithm then generates a set of configurations (49 in total in the case of the rock-salt based five-metal carbide systems, once structural duplicates are excluded), each containing 10 atoms: one atom of each of the metals, along with five carbon atoms. This is the minimum cell size necessary to accurately reproduce the required stoichiometry. All configurations have $g_{i}=10$ , except for one where $g_{i}$ $=120$ , so that $\\textstyle\\sum_{i=1}^{n}g_{i}=^{\\cdot}600$ for the rock-salt-based five-metal carbide systems. Note that computational demands increase significantly with the number of elements: AFLOW-POCC generates 522, 1793, and 7483 for six-, seven-, and eightmetal carbide compositions, respectively. \n\nEnergies calculation. The energy of each configuration is calculated using density functional theory (Vienna Ab-initio Simulation Package63) within the AFLOW framework59 and the standard settings60. Each configuration is fully relaxed using the Perdew, Burke, Ernzerhof (PBE) parameterization of the generalized gradient approximation exchange-correlation functional64, projector augmented wave potentials, at least $8000{\\textbf{k}}$ -points per reciprocal atom (KPPRA), and a plane-wave cut-off of at least 1.4 times the cut-off values of constituent species’ pseudopotentials60. The formation enthalpy $(H_{\\mathrm{f}})$ of each configuration along with the link to AFLOW.org entry page is provided in Supplementary Tables 4–10. \n\nMechanical properties. Elastic properties are calculated using the AEL module53 of the AFLOW framework, which applies a set of independent directional normal and shear strains to the structure, and fits the resulting stress tensors to obtain the elastic constants. From this, the bulk: $B$ , and shear: G, moduli are calculated in the Voigt, Reuss and Voigt-Reuss-Hill (VRH) approximations, with the average being used for the purposes of this work. The elastic or Young’s modulus: $E_{i}$ , is calculated using the approximation $E=9B G/(3B+G)$ , which can be derived starting from the expression for Hooke’s Law in terms of $E$ and the Poisson ratio, $\\nu;\\varepsilon_{11}=1/E[\\sigma_{11}-\\nu$ $(\\overbar{\\sigma_{22}}+\\sigma_{33})]^{65}$ , and similarly for $\\varepsilon_{22}$ and $\\varepsilon_{33}$ . For a cubic system, $\\varepsilon_{11}=S_{11}\\sigma_{11}+$ $S_{12}\\sigma_{22}+S_{12}\\sigma_{33}$ (similarly for $\\ensuremath{\\varepsilon}_{22}$ and $\\varepsilon_{33,}$ ), where $S_{i j}$ are the elements of the elastic compliance tensor, so that $1/E=S_{11}$ and $-\\nu/E=\\dot{S_{12}}$ . For a cubic system, the bulk modulus is $B=1/[3(S_{11}+2S_{12})]=E/[3(1-2\\nu)]$ . The Poisson ratio can be written as $\\nu=(3B-2G)/(6B+2G)$ , and combining with the expression for $B$ and rearranging gives the required $E=9B G/(3B+G)$ . \n\nThe elastic properties for the five-metal compositions are first calculated for each of the 49 configurations generated by AFLOW-POCC. The VRH approximated values of $B$ and $G$ for these configurations are listed in Supplementary Table 3, along with the AFLOW-POCC ensemble averaged electronic density of states (see Supplementary Figure 39). The average elastic moduli are then obtained, weighted according to the Boltzmann distribution at a temperature of $2200^{\\circ}\\mathrm{C}$ (the experimental sintering temperature). These calculated values are compared with those obtained using a ROM (average of the binary components, weighted according to fractional composition in the sample). \n\nThree different models are used for predicting the Vickers hardness based on the elastic moduli: Chen et al. $(H_{\\mathrm{V}}=2(\\dot{k}^{2}G)^{0.585}-3$ ; $k=G/B)^{54}$ , Teter $\\textstyle(H_{\\mathrm{V}}=$ $0.151G)^{55}$ , and Tian et al. $(H_{\\mathrm{V}}=0.92k^{1.137}G^{0.708}$ ; $k=G/B)^{56}$ . Note, however, that these models are based on the elastic response of the materials, and do not take into account phenomena such as plastic deformation, slip planes, and lattice defects. \n\nSample preparation. Initial powders of each of the eight binary precursor carbides (HfC, NbC, TaC, TiC, ${\\bf\\cal M}{\\bf o}_{2}{\\bf C},$ VC, ${\\mathrm{W}}_{2}{\\mathrm{C}},$ ZrC) are obtained in $599\\%$ purity and $-325$ mesh $(<44\\upmu\\mathrm{m})$ particle size (Alfa Aesar). Samples are weighed out in $_{15\\mathrm{g}}$ batches and mixed to achieve the desired five-metal carbide compositions. To ensure adequate mixing, each sample is ball milled in a shaker pot mill for a total of $^{2\\mathrm{h}}$ in individual $30\\mathrm{-min}$ intervals intersected by 10-min rest times to avoid heating and consequent oxide formation. All milling is done in tungsten carbide-lined stainless steel milling jars with tungsten carbide grinding media. \n\nBulk sample pellets are synthesized via solid-state processing routes. The fieldassisted sintering technique (FAST), also called SPS, is employed to simultaneously densify and react the compositions into single-phase materials. For all samples, sintering is done at $2200^{\\circ}\\mathrm{C}$ with a heating rate of $100\\ {^{\\circ}\\mathrm{C/min}}.$ 30 MPa uniaxial pressure, and a 5-min dwell at temperature. Samples are heated in vacuum atmosphere to $1300^{\\circ}\\mathrm{C}$ followed by flowing argon to $2200^{\\circ}\\mathrm{C}$ . All sintering is done in $20\\mathrm{mm}$ graphite die and plunger sets with graphite foil surrounding the samples to prevent reaction with the die. \n\nSample analysis. Elemental analysis is performed using an FEI Quanta 600 SEM equipped with a Bruker e-Flash EDS detector at an accelerating voltage of $20\\mathrm{kV}$ . Microstructural scanning electron microscope (SEM) imaging is carried out using an FEI Apreo FE-SEM at an accelerating voltage of $5\\mathrm{kV}$ , with a combination of secondary and back-scattered electron detectors to show phase contrast. Crystal phase analysis is performed using a Rigaku Miniflex X-ray Diffractometer with a stepsize of $0.02^{\\circ}$ and 5-s dwells, using $\\operatorname{Cu}\\mathrm{K}\\alpha$ radiation (wavelength $\\lambda{=}1.54059\\mathrm{\\AA}$ ) for all measurements and calculation of the lattice parameter. All sample patterns are fitted in Materials Data Incorporated’s (MDI) Jade 9 software66 with a residual of fit $R<8\\%$ . Lattice parameter, ${a_{\\mathrm{exp}}},$ values of $4.353\\mathrm{\\AA}$ , $4.500\\mathrm{\\AA}$ , $4.415\\mathring{\\mathrm{A}}$ , $4.434\\mathring{\\mathrm{A}}$ , $4.355\\mathring{\\mathrm{A}},$ $4.502\\mathrm{\\AA}$ , $4.50\\bar{6}\\mathrm{\\AA}$ , $4.534\\mathrm{\\AA}$ , and $4.476\\mathrm{\\AA}$ were measured for MoNbTaVWC5, HfNbTa $\\mathrm{TiZrC}_{5}$ , HfNbTa ${\\mathrm{TiVC}}_{5},$ , HfNbTa $\\mathrm{IiWC}_{5}$ , $\\mathrm{NbTaTiVWC}_{5}$ , $\\mathrm{HfTaTiWZrC}_{5},$ HfMoTa $\\mathrm{WZrC}_{5}$ , $\\mathrm{HfMoVWZrC}_{5}$ , and $\\mathrm{HfMoTiWZrC}_{5}$ , respectively (for multiphase samples, $a_{\\mathrm{exp}}$ refers to the primary cubic phase). \n\nFor analysis of sample peak broadening $\\beta_{\\mathrm{S}},$ instrumental broadening $\\beta_{\\mathrm{I}}$ must first be determined. For this, a NIST 660b $\\mathrm{LaB}_{6}$ standard is run under the same conditions as each carbide sample. The instrumental profile is then fitted, and $\\beta_{\\mathrm{I}}$ is determined to vary with Bragg angle $\\theta$ as: \n\n$$\n\\beta_{\\mathrm{I}}=0.1750985-0.001560626\\theta+0.00001125342\\theta^{2}.\n$$ \n\n$\\beta_{\\mathrm{{S}}}$ is determined by subtracting $\\beta_{\\mathrm{I}}$ from the measured broadening $\\beta_{\\mathrm{{M}}}$ : $\\dot{\\beta}_{\\mathrm{S}}^{x}=\\beta_{\\mathrm{M}}^{x}-\\beta_{I}^{x}$ . $\\beta_{\\mathrm{{M}}}$ is measured as a function of $\\theta,$ and $x$ is a constant between 1.0 and 2.0. In the current analysis, $x$ is set to 2.0 due to the Gaussian-like shape of the instrument peaks, as this value leads to the lowest standard deviation of linear fits to the peak broadening data. \n\nBoth crystallite size and lattice strain contribute to $\\beta_{\\mathrm{S}}{}^{49,67,68}$ : \n\n$$\n\\beta_{\\mathrm{S}}=4\\varepsilon\\mathrm{tan}\\theta+\\frac{K\\lambda}{D\\mathrm{cos}\\theta},\n$$ \n\nwhere $\\varepsilon$ is the lattice strain or variation in interplanar spacing due to chemical inhomogeneity, $K$ is a constant (dependent on the grain shape), $\\lambda$ is the incident $\\mathrm{X}\\mathrm{\\mathrm{\\Omega}}$ ray wavelength and $D$ is the crystallite size. Rearranging Eq. 6 gives: \n\n$$\n\\beta_{\\mathrm{s}}\\mathrm{cos}\\theta=4\\varepsilon\\mathrm{sin}\\theta+\\frac{K\\lambda}{D}.\n$$ \n\nThe slope of a linear fit to the plot of $\\beta_{\\mathrm{{s}}}\\mathrm{{cos}}\\theta$ against $\\mathrm{\\sin}\\theta$ is equal to the strain, or lattice distortion, whereas the $y$ -intercept of a linear fit with zero slope determines the crystallite size. \n\nMechanical testing. Mechanical properties of each of the single-phase compositions are tested using a Keysight NanoIndenter G200 with a Berkovich indenter tip. To rule out indentation size effects, testing is carried out at loads of both $50\\mathrm{mN}$ and $300\\mathrm{mN}$ , and no significant deviation in hardness or modulus is observed. To allow valid cross-comparison, each of the high entropy carbides is compared with the binary carbides, which were hot-pressed and indentation tested under identical conditions. For the reported values, tests are carried out according to the standard method outlined in ISO 14577 using a maximum load of $50\\mathrm{mN}$ . Values are calculated as an average of 40 indents, and are reported with errors of plus or minus one standard deviation. A fused crystal silica standard is run prior to each test to ensure proper equipment calibration is maintained. Samples are polycrystalline with grain sizes between $10\\upmu\\mathrm{m}$ and $30\\upmu\\mathrm{m}$ . Prior to indentation testing each sample is vibratory polished using $0.05\\upmu\\mathrm{m}$ colloidal silica for $12\\mathrm{h}$ to ensure minimal surface roughness. All tests are carried out at a temperature of $27^{\\circ}\\mathrm{C}\\pm0.5$ $^{\\circ}\\mathrm{C}$ . Indentation data are analyzed according to the methods of Oliver and $\\mathrm{Pharr}^{69,70}$ . The elastic (i.e., Young’s) modulus is determined using $1/E_{\\mathrm{eff}}=\\big(1-\\nu^{2}\\big)/E+\\big(1-\\nu_{\\mathrm{I}}^{2}\\big)/\\bar{E}_{\\mathrm{I}}$ , where $E_{\\mathrm{eff}}$ is the effective modulus (sometimes called the reduced modulus) obtained from nanoindentation, $E$ and $\\nu$ are the Young’s modulus and Poisson’s ratio, respectively, for the specimen, whereas $E_{\\mathrm{I}}$ and $\\nu_{\\mathrm{I}}$ are the same parameters for the indenter. A Poisson’s ratio for each of the binary carbides is obtained from literature71 where available. For five-metal carbide samples where data for each of the constituents is available, the value used for Poisson’s ratio is taken as the average of the constituent binaries. If this average is unavailable (i.e., when Mo and/or W are present), Poisson’s ratio is assumed to be equal to 0.18. \n\n# Data availability \n\nAll the ab-initio data are freely available to the public as part of the AFLOW online repository and can be accessed through AFLOW.org following the REST-API interface59 and AFLUX search language76. \n\nReceived: 29 June 2018 Accepted: 18 October 2018 \nPublished online: 26 November 2018 \n\n# References \n\n1. Gao, M. C, Yeh, J. W, Liaw, P. K. & Zhang, Y. High-Entropy Alloys: Fundamentals and Applications. (Springer, Cham, Switzerland, 2016). \n2. Senkov, O. N., Miller, J. D., Miracle, D. B. & Woodward, C. Accelerated exploration of multi-principal element alloys with solid solution phases. Nat Commun. 6, 6529 (2015). \n3. Widom, M. Modeling the structure and thermodynamics of high-entropy alloys. J. Mater. Res. 33, 2881–2898 (2018). \n4. Lim, X. Mixed-up metals make for stronger, tougher, stretchier alloys. Nature 533, 306–307 (2016). \n5. Ye, Y. F., Wang, Q., Lu, J., Liu, C. T. & Yang, Y. High-entropy alloy: challenges and prospects. Mater. Today 19, 349–362 (2016). \n6. Gludovatz, B. et al. A fracture-resistant high-entropy alloy for cryogenic applications. Science 345, 1153–1158 (2014). \n7. Gali, A. & George, E. P. Tensile properties of high- and medium-entropy alloys. Intermetallics 39, 74–78 (2013). \n8. Senkov, O. N., Wilks, G. B., Scott, J. M. & Miracle, D. B. Mechanical properties of $\\mathrm{Nb}_{25}\\mathrm{Mo}_{25}\\mathrm{Ta}_{25}\\mathrm{W}_{25}$ and $\\mathrm{V}_{20}\\mathrm{Nb}_{20}\\mathrm{Mo}_{20}\\mathrm{Ta}_{20}\\mathrm{W}_{20}$ refractory high entropy alloys. Intermetallics 19, 698–706 (2011). \n9. Li, Z., Pradeep, K. G., Deng, Y., Raabe, D. & Tasan, C. C. Metastable highentropy dual-phase alloys overcome the strength-ductility trade-off. Nature 534, 227–230 (2016). \n10. Tsao, T.-K. et al. The high temperature tensile and creep behaviors of high entropy superalloy. Sci. Rep. 7, 12658 (2017). \n11. Li, Z., Tasan, C. C., Springer, H., Gault, B. & Raabe, D. Interstitial atoms enable joint twinning and transformation induced plasticity in strong and ductile high-entropy alloys. Sci. Rep. 7, 40704 (2017). \n12. Senkov, O. N., Wilks, G. B., Miracle, D. B., Chuang, C. P. & Liaw, P. K. Refractory high-entropy alloys. Intermetallics 18, 1758–1765 (2010). \n13. Senkov, O. N., Senkova, S. V., Woodward, C. & Miracle, D. B. Low-density, refractory multi-principal element alloys of the Cr-Nb-Ti-V-Zr system: microstructure and phase analysis. Acta Mater. 61, 1545–1557 (2013). \n14. von Rohr, F., Winiarski, M. J., Tao, J., Klimczuk, T. & Cava, R. J. Effect of electron count and chemical complexity in the Ta-Nb-Hf-Zr-Ti highentropy alloy superconductor. Proc. Natl Acad. Sci. USA 113, E7144–E7150 (2016). \n15. Bérardan, D., Franger, S., Dragoe, D., Meena, A. K. & Dragoe, N. Colossal dielectric constant in high entropy oxides. Phys. Status Solidi RRL 10, 328–333 (2016). \n16. Bérardan, D., Franger, S., Meena, A. K. & Dragoe, N. Room temperature lithium superionic conductivity in high entropy oxides. J. Mater. Chem. A 4, 9536–9541 (2016). \n17. Rost, C. M. et al. Entropy-stabilized oxides. Nat Commun. 6, 8485 (2015). \n18. Rak, Z. et al. Charge compensation and electrostatic transferability in three entropy-stabilized oxides: results from density functional theory calculations. J. Appl. Phys. 120, 095105 (2016). \n19. Gild, J. et al. High-entropy metal diborides: a new class of high-entropy materials and a new type of ultrahigh temperature ceramics. Sci. Rep. 6, 37946 (2016). \n20. Castle, E., Csanádi, T., Grasso, S., Dusza, J. & Reece, M. Processing and properties of high-entropy ultra-high temperature carbides. Sci. Rep. 8, 8609 (2018). \n21. Dusza, J. et al. Microstructure of (Hf-Ta-Zr-Nb)C high-entropy carbide at micro and nano/atomic level. J. Eur. Ceram. Soc. 38, 4303–4307 (2018). \n22. Yan, X. et al. $\\mathrm{(Hf_{0.2}Z r_{0.2}T a_{0.2}N b_{0.2}T i_{0.2})C}$ high-entropy ceramics with low thermal conductivity. J. Am. Ceram. Soc. 101, 4486–4491 (2018). \n23. Zhou, J. et al. High-entropy carbide: a novel class of multicomponent ceramics. Ceramics Int. 44, 22014–22018 (2018). \n24. Meisenheimer, P. B., Kratofil, T. J. & Heron, J. T. Giant enhancement of exchange coupling in entropy-stabilized oxide heterostructures. Sci. Rep. 7, 13344 (2017). \n25. Rohrer, G. S. et al. Challenges in ceramic science: a report from the workshop on emerging research areas in ceramic science. J. Am. Ceram. Soc. 95, 3699–3712 (2012). \n26. Agte, C. & Alterthum, H. Untersuchungen über systeme hochschmelzender carbide nebst beiträgen zum problem der kohlenstoffschmelzung [Investigations of high-melting point carbide systems and their contribution to the problem of carbon fusion]. Z. Tech. Phys. 11, 182–191 (1930). \n27. Andrievskii, R. A., Strel’nikova, N. S., Poltoratskii, N. I., Kharkhardin, E. D. & Smirnov, V. S. Melting point in systems ZrC-HfC, TaC-ZrC, TaC-HfC. Poroshk. Metall. 1, 85–88 (1967). \n28. Hong, Q.-J. & van de Walle, A. Prediction of the material with highest known melting point from ab initio molecular dynamics calculations. Phys. Rev. B 92, 020104 (2015). \n29. Wuchina, E., Opila, E., Opeka, M., Fahrenholtz, W. & Talmy, I. UHTCs: ultra-high temperature ceramic materials for extreme environment applications. Electrochem. Soc. Interface 16, 30–36 (2007). \n30. Rudy, E. Ternary Phase Equilibria in Transition Metal-Boron-Carbon-Silicon Systems. Part II. Ternary Systems. (Air Force Materials Laboratory, WrightPatterson Air Force Base, Ohio, USA, 1965). \n31. Rudy, E. Ternary Phase Equilibria in Transition Metal-Boron-Carbon-Silicon Systems. Part V. Compendium of Phase Diagram Data. (Air Force Materials Laboratory, Wright-Patterson Air Force Base, Ohio, USA, 1969). \n32. Gusev, A. I. Phase diagrams of the pseudo-binary TiC-NbC, TiC-TaC, ZrCNbC, ZrC-TaC, and HfC-TaC carbide systems. Russ. J. Phys. Chem. 59, 336–340 (1985). \n33. Cedillos-Barraza, O. et al. Sintering behaviour, solid solution formation and characterisation of TaC, HfC and TaC-HfC fabricated by spark plasma sintering. J. Eur. Ceram. Soc. 36, 1539–1548 (2016). \n34. Cedillos-Barraza, O. et al. Investigating the highest melting temperature materials: a laser melting study of the TaC-HfC system. Sci. Rep. 6, 37962 (2016). \n35. Landau, D. P., Tsai, S.-H. & Exler, M. A new approach to Monte Carlo simulations in statistical physics: Wang-Landau sampling. Am. J. Phys. 72, 1294–1302 (2004). \n36. Baldock, R. J. N., Pártay, L. B., Bartók, A. P., Payne, M. C. & Csányi, G. Determining pressure-temperature phase diagrams of materials. Phys. Rev. B 93, 174108 (2016). \n37. Gao, M. C. & Alman, D. E. Searching for next single-phase high-entropy alloy compositions. Entropy 15, 4504–4519 (2013). \n38. Zhang, F. et al. An understanding of high entropy alloys from phase diagram calculations. Calphad 45, 1–10 (2014). \n39. Gao, M. C. et al. Thermodynamics of concentrated solid solution alloys. Curr. Opin. Solid State Mater. Sci. 21, 238–251 (2017). \n40. Curtarolo, S. et al. The high-throughput highway to computational materials design. Nat. Mater. 12, 191–201 (2013). \n41. Yang, K., Oses, C. & Curtarolo, S. Modeling off-stoichiometry materials with a high-throughput ab-initio approach. Chem. Mater. 28, 6484–6492 (2016). \n42. Bergerhoff, G., Hundt, R., Sievers, R. & Brown, I. D. The inorganic crystal structure data base. J. Chem. Inf. Comput. Sci. 23, 66–69 (1983). \n43. Massalski, T. B., Okamoto, H., Subramanian, P. R. & Kacprzak, L. Binary Alloy Phase Diagrams. (ASM International, Materials Park, Ohio, USA, 1990). \n44. Oses, C. et al. AFLOW-CHULL: cloud-oriented platform for autonomous phase stability analysis. J. Chem. Inf. Model. https://doi.org/10.1021/acs. jcim.8b00393 (2018). \n45. Lederer, Y., Toher, C., Vecchio, K. S. & Curtarolo, S. The search for high entropy alloys: a high-throughput ab-initio approach. Acta Mater. 159, 364–383 (2018). \n46. Perim, E. et al. Spectral descriptors for bulk metallic glasses based on the thermodynamics of competing crystalline phases. Nat. Commun. 7, 12315 (2016). \n47. Greer, A. L. Confusion by design. Nature 366, 303–304 (1993). \n48. Kuo, K. & Hägg, G. A new molybdenum carbide. Nature 170, 245–246 (1952). \n49. Williamson, G. K. & Hall, W. H. X-ray line broadening from filed aluminium and wolfram. Acta Metall. 1, 22–31 (1953). \n50. Freudenberger, J. et al. Face centred cubic multi-component equiatomic solid solutions in the Au-Cu-Ni-Pd-Pt system. Metals 7, 135 (2017). \n51. Curtarolo, S. et al. AFLOWLIB.ORG: a distributed materials properties repository from high-throughput ab initio calculations. Comput. Mater. Sci. 58, 227–235 (2012). \n52. Smith, C. J., Yu, X.-X., Guo, Q., Weinberger, C. R. & Thompson, G. B. Phase, hardness, and deformation slip behavior in mixed $\\mathrm{Hf}_{x}\\mathrm{Ta}_{1-x}\\mathrm{C}$ . Acta Mater. 145, 142–153 (2018). \n53. Toher, C. et al. Combining the AFLOW GIBBS and elastic libraries to efficiently and robustly screen thermomechanical properties of solids. Phys. Rev. Mater. 1, 015401 (2017). \n54. Chen, X.-Q., Niu, H., Li, D. & Li, Y. Modeling hardness of polycrystalline materials and bulk metallic glasses. Intermetallics 19, 1275–1281 (2011). \n55. Teter, D. M. Computational alchemy: the search for new superhard materials. MRS Bull. 23, 22–27 (1998). \n56. Tian, Y., Xu, B. & Zhao, Z. Microscopic theory of hardness and design of novel superhard crystals. Int. J. Refract. Met. Hard Mater. 33, 93–106 (2012). \n57. Toher, C. et al. High-throughput computational screening of thermal conductivity, Debye temperature, and Grüneisen parameter using a quasiharmonic Debye model. Phys. Rev. B 90, 174107 (2014). \n58. van de Walle, A. & Ceder, G. The effect of lattice vibrations on substitutional alloy thermodynamics. Rev. Mod. Phys. 74, 11–45 (2002). \n59. Curtarolo, S. et al. AFLOW: an automatic framework for high-throughput materials discovery. Comput. Mater. Sci. 58, 218–226 (2012). \n60. Calderon, C. E. et al. The AFLOW standard for high-throughput materials science calculations. Comput. Mater. Sci. 108 Part A, 233–238 (2015). \n61. Rappe, A. K., Casewit, C. J., Colwell, K. S., Goddard, W. A. III & Skiff, W. M. UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J. Am. Chem. Soc. 114, 10024–10035 (1992). \n62. Mehl, M. J. et al. The AFLOW library of crystallographic prototypes: part 1. Comput. Mater. Sci. 136, S1–S828 (2017). \n63. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n64. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n65. Suh, N. P. & Turner, A. P. L. Elements of the Mechanical Behavior of Solids (McGraw-Hill, New York, 1975). \n66. Materials Data, Inc. Jade 9. https://materialsdata.com/prodjd.html (Materials Data Inc., 2016). \n67. Cullity, B. D. Elements of X-Ray Diffraction. (Addison-Wesley, Reading, MA, USA, 1956). \n68. Mote, V. D., Purushotham, Y. & Dole, B. N. Williamson-Hall analysis in estimation of lattice strain in nanometer-sized ZnO particles. J. Theor. Appl. Phys. 6, 6 (2012). \n69. Oliver, W. C. & Pharr, G. M. An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments. J. Mater. Res. 7, 1564–1583 (1992). \n70. Oliver, W. C. & Pharr, G. M. Measurement of hardness and elastic modulus by instrumented indentation: advances in understanding and refinements to methodology. J. Mater. Res. 19, 3–20 (2004). \n71. Kral, C., Lengauer, W., Rafaja, D. & Ettmayer, P. Critical review on the elastic properties of transition metal carbides, nitrides and carbonitrides. J. Alloy. Compd. 265, 215–233 (1998). \n72. American Society for Metals. ASM Engineered Materials Reference Book (ASM International, Materials Park, Ohio, USA, 1989). \n73. Oyama, S. T. (ed.) The Chemistry of Transition Metal Carbides and Nitrides (Blackie Academic & Professional, Glasgow, UK, 1996). \n74. Dubitsky, G. A. et al. Superhard superconductor composites obtained by sintering of diamond, $\\boldsymbol{\\mathscr{c}}$ -BN and $\\mathrm{C}_{60}$ powders with superconductors. Z. Naturforsch. B 61, 1541–1546 (2006). \n75. Caron, P. & Tremblay, A. Method for treating tungsten carbide particles. US patent 7981394 B2 (2011). \n76. Rose, F. et al. AFLUX: The LUX materials search API for the AFLOW data repositories. Comput. Mater. Sci. 137, 362–370 (2017). \n\n# Acknowledgements \n\nThe authors acknowledge support by DOD-ONR (N00014-15-1-2863, N00014-17-1- 2090, N00014-16-1-2583, N00014-17-1-2876) and by Duke University—Center for Materials Genomics—for computational support. S.C. acknowledges the Alexander von Humboldt Foundation for financial support. C.O. acknowledges support from the National Science Foundation Graduate Research Fellowship under grant no. DGF1106401. The authors thank Axel van de Walle, Matthias Scheffler, Claudia Draxl, Ohad Levy, Yoav Lederer, Amir Natan, Omar Cedillos Barraza, Joshua Gild, Olivia Dippo, and Cameron McElfresh for helpful discussions. \n\n# Author contributions \n\nS.C. proposed the entropy spectral descriptor and the phase stabilization mechanism. C.T. wrote the AEL–AGL codes under the supervision of S.C. C.O. wrote the AFLOWPOCC and AFLOW-CHULL codes under the supervision of C.T. and S.C. P.S. and C.T. performed the AFLOW-POCC and AEL–AGL calculations for the single-phase systems. C.O. performed the convex hull analysis. T.H. made the samples under the supervision of K.V. T.H. and M.S. performed the experimental characterization. All authors—P.S., T.H., C.T., C.O., M.S., J.-P.M., D.B., K.V., S.C.—discussed the results and contributed to the writing of the article. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-07160-7. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1038_s41467-018-03236-6", + "DOI": "10.1038/s41467-018-03236-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-03236-6", + "Relative Dir Path": "mds/10.1038_s41467-018-03236-6", + "Article Title": "The influence of the molecular packing on the room temperature phosphorescence of purely organic luminogens", + "Authors": "Yang, J; Zhen, X; Wang, B; Gao, XM; Ren, ZC; Wang, JQ; Xie, YJ; Li, JR; Peng, Q; Pu, KY; Li, Z", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Organic luminogens with persistent room temperature phosphorescence (RTP) have attracted great attention for their wide applications in optoelectronic devices and bioimaging. However, these materials are still very scarce, partially due to the unclear mechanism and lack of designing guidelines. Herein we develop seven 10-phenyl-10H-phenothiazine-5,5dioxide- based derivatives, reveal their different RTP properties and underlying mechanism, and exploit their potential imaging applications. Coupled with the preliminary theoretical calculations, it is found that strong pi-pi interactions in solid state can promote the persistent RTP. Particularly, CS-CF3 shows the unique photo-induced phosphorescence in response to the changes in molecular packing, further confirming the key influence of the molecular packing on the RTP property. Furthermore, CS-F with its long RTP lifetime could be utilized for real-time excitation-free phosphorescent imaging in living mice. Thus, our study paves the way for the development of persistent RTP materials, in both the practical applications and the inherent mechanism.", + "Times Cited, WoS Core": 810, + "Times Cited, All Databases": 832, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000426049300007", + "Markdown": "# The influence of the molecular packing on the room temperature phosphorescence of purely organic luminogens \n\nJie Yang1, Xu Zhen2, Bin Wang3, Xuming Gao1, Zichun Ren1, Jiaqiang Wang1, Yujun Xie1, Jianrong Li3, Qian Peng4, Kanyi Pu 2 & Zhen Li1 \n\nOrganic luminogens with persistent room temperature phosphorescence (RTP) have attracted great attention for their wide applications in optoelectronic devices and bioimaging. However, these materials are still very scarce, partially due to the unclear mechanism and lack of designing guidelines. Herein we develop seven 10-phenyl-10H-phenothiazine-5,5- dioxide-based derivatives, reveal their different RTP properties and underlying mechanism, and exploit their potential imaging applications. Coupled with the preliminary theoretical calculations, it is found that strong $\\pi{-}\\pi$ interactions in solid state can promote the persistent RTP. Particularly, $C S\\mathrm{-}C F_{3}$ shows the unique photo-induced phosphorescence in response to the changes in molecular packing, further confirming the key influence of the molecular packing on the RTP property. Furthermore, CS-F with its long RTP lifetime could be utilized for real-time excitation-free phosphorescent imaging in living mice. Thus, our study paves the way for the development of persistent RTP materials, in both the practical applications and the inherent mechanism. \n\numinogens with room temperature phosphorescence (RTP) have attracted great attention for their full utilization of the excited state energy and long lifetime1–14. However, most of the RTP systems contain noble metals, which might suffer some intrinsic problems, including high cost, potential toxicity, and instability in aqueous environments. The alternative metal-free phosphors were seldom reported, especially those with persistent RTP effect. Recently, Kabe and Adachi have developed a purely organic host–guest doping system with unexpected but excited long persistent luminescence, continuing for more than $^\\mathrm{1h}$ at room temperature15. This could be even comparable to the most outstanding inorganic phosphors and has fully displayed the vast development prospect of purely organic RTP luminogens16. \n\nGenerally, unlike the relative complexity with the very careful control of dosage concentration for the host–guest doping system, utilization of organic RTP luminogens with single component should be more convenient, in addition to the corresponding easy exploration of inherent mechanisms. Thanks to the enthusiasm of scientists, enumerable pure organic single-component RTP systems have been developed, along with the proposed mechanisms17,18. For example, Huang and colleagues19,20,] proposed that H-aggregation stabilized the triplet excitons through enhancing intersystem crossing process, in pursuit of ultralong phosphorescence at room temperature. Tang and colleagues21,22,] suggested the crystallization-induced phosphorescence mechanism might be mainly responsible for the RTP character because of its effective inhibition of non-radiative decays. Chi and colleagues23 identified the key role of the intermolecular electronic coupling for achieving efficient persistent RTP. Based on these excellent pioneering works, systematical investigations are still needed to well understand the origin of persistent RTP. \n\nAccording to the previous works, there are two main prerequisites that should be satisfied: the functional groups favoring $n{-}\\pi^{*}$ transitions and the special packing in the solid state for the stabilization of the excited triplet state2. Relatively, the former is easier to be realized through the rational molecular design. The constructing blocks of sulfonyldibenzene and carbazole groups are two star ones to achieve the good communication between singlet and triplet states, because the existence of $\\mathrm{~O~}$ or N atoms with lone pair electrons is capable of promoting $n{-}\\pi^{*}$ transitions to populate triplet excitons (Supplementary Fig. 1)3–14,17–30. Here, we integrate 9-phenyl-9H-carbazole and sulfonyldibenzene groups together, and design a series of 10-phenyl-10Hphenothiazine 5,5-dioxide derivatives ( ${\\mathrm{CS-CH}}_{3}{\\mathrm{O}}_{3}$ , ${\\mathrm{CS-CH}}_{3}$ , CSH, CS-Br, CS-Cl, and CS-F) (Supplementary Fig. 2), with the aim to carefully investigate the structure–property relationship. Excitedly, accompanying with the adjustment of the substituent groups on the 10-phenyl ring from a methoxyl or methyl group to the hydrogen atom, then to the bromine, chlorine, or fluorine atoms, the RTP lifetimes in crystals of the corresponding luminogens increase from $88~\\mathrm{ms}$ (millisecond) $(\\mathrm{CS-CH}_{3}\\mathrm{{O})}$ and $96\\mathrm{m}s$ $(\\mathrm{C}\\bar{\\mathrm{S}}\\ –\\mathrm{CH}_{3})$ ) to $188\\mathrm{ms}$ (CS-H), then to $268\\mathrm{ms}$ (CS-Br), 256 ms (CSCl) and $410\\mathrm{ms}$ (CS-F). Seemingly, the introduction of the electron-withdrawing substituents would be beneficial to the $\\pi{-}\\pi$ interactions, which could stabilize the excited triplet state accompanying with the ultralong RTP effect in this system. Then, another substituent, the trifluoromethyl group, with even stronger withdrawing ability is introduced to yield ${\\mathrm{CS-CF}}_{3}$ . Although the longer RTP lifetime could not be observed, ${\\mathrm{CS-CF}}_{3}$ crystal is found to possess another interesting character of reversible photo-induced RTP, which also should be originated from the reversible changes of molecular packing. Thus, the subtle change in the molecular structure does affect the molecular packing in crystal, resulting in the different RTP behaviors. \n\n# Results \n\nRTP phenomena and the proposed mechanism. ${\\mathrm{CS-CH}}_{3}\\mathrm{O}$ CS$\\mathrm{CH}_{3}$ , CS-H, CS-Br, CS-Cl, CS-F, and ${\\mathrm{CS-CF}}_{3}$ were facilely prepared through $\\mathrm{C-N}$ coupling reactions, followed by the oxidation reaction with the aid of hydrogen peroxide (Supplementary Fig. 3). Upon the illumination of a $365\\mathrm{nm}$ ultraviolet (UV) lamp, their as-prepared powders and crystals show blue or green emissions (Fig. 1). After stopping the photo-excitation, green or sky blue RTP emissions lasting for more than $1.5s$ could be visually seen for CS-H, CS-Br, CS-Cl, and CS-F, while those of ${\\mathrm{CS-CH}}_{3}{\\mathrm{O}}$ and ${\\mathrm{CS-CH}}_{3}$ would die out quickly. In the powder X-ray diffraction (PXRD) spectra of their as-prepared samples (Supplementary Fig. 4), CS-H, CS-Br, CS-Cl, and CS-F exhibit more sharp peaks than those of ${\\mathrm{CS-CH}}_{3}\\mathrm{O}$ and ${\\mathrm{CS-CH}}_{3}$ , indicating their better crystallinity. Their room temperature fluorescence, phosphorescence spectra, and the corresponding lifetimes in powder and crystal states were measured (Fig. 2, Supplementary Figs. 5–8, Supplementary Table 1). Particularly, the lifetimes of their room temperature phosphorescence in crystal state are much different from each other, ranging from $88\\mathrm{ms}$ 1 $\\mathrm{'CS-CH}_{3}\\mathrm{O})$ and $96\\mathrm{m}s$ $\\mathrm{(CS-CH_{3})}$ to $188\\mathrm{ms}$ (CS-H), then to 268 ms (CS-Br), 256 ms (CS-Cl), and $410\\mathrm{ms}$ (CS-F), demonstrating some relation to the different substituent groups on the 10-phenyl ring. \n\nIn order to figure out the origin of the different RTP effect for these six compounds, their UV–visible absorption spectra at room temperature, low temperature phosphorescence, and the corresponding lifetimes in dichloromethane solutions were measured. As shown in Supplementary Fig. 9a, they share the similar UV–visible absorption spectra in solutions with three absorption peaks at about 275, 300, and $330\\mathrm{nm}$ . Also, they all present two emission peaks at about 390 and $405\\mathrm{nm}$ in their low temperature phosphorescence, with moderate differences of their corresponding lifetimes, ranging from 222 to $268\\mathrm{ms}$ . These results are totally different from their photoluminescence (PL) behaviors in solid state, that is, the RTP spectra and the corresponding phosphorescence lifetimes are much different from each other (Fig. 2). These experimental results displayed that the packing modes, rather than the molecular electronic structures, should mainly account for the different RTP behaviors in solid state. \n\nGenerally, most of pure organic molecules are fluorophores with very short-lived singlet exciton for fluorescence. Only a small part could realize the transition from the excited singlet state to the triplet one, which then decays from the $T_{1}$ state to the $S_{0}$ state through the phosphorescent process with the lifetime short than $10\\mathrm{m}s$ . In order to obtain the ultralong phosphorescence, a stable excited triplet state $(T_{1}^{\\mathbf{\\alpha}*})$ should be formed, which could either lower energy levels to decrease the radiative decay rate or restrain the molecular motion to result in the diminished non-radiative decay rate (Fig. 2e). In this system, the stable $T_{1}{^*}$ state must have been formed in view of the observed persistent RTP effect. \n\nMolecular packing. In order to find out what kind of packing mode could lead to the stabilized $T_{1}{^*}$ state in this system and make a deep insight into the persistent RTP, we cultured the single crystals of these six compounds (Supplementary Table 2). Figure 3 shows the entire and local packing modes of these crystals, which are different from each other according to the subtly different substituent groups on the 10-phenyl ring. Analyzing carefully, the compounds of CS-Br, CS-Cl, and CS-F, with electron-withdrawing groups, show much stronger $\\pi{-}\\pi$ stackings with the involved two phenyl rings paralleling to each other. And the centroid–centroid distances between them are much shorter (ranging from 3.677 to 3.732 and $3.773\\mathring\\mathrm{A}$ ). However, the $\\pi{-}\\pi$ interactions between the adjacent phenyl rings are too weak to be considered for the compounds with electron-donating substituents. For ${\\mathrm{CS-CH}}_{3}\\mathrm{O};$ , there are four molecules in a minimum repeat unit, and the centroid–centroid distances between two adjacent benzenes are $4.251\\mathring{\\mathrm{A}}$ , while their dihedral angles are all about $30^{\\mathrm{o}}$ . In ${\\mathrm{CS-CH}}_{3}$ , there are two different kinds of molecular configurations of $\\mathrm{CS-CH}_{3}(\\mathrm{a})$ and $\\mathrm{CS\\mathrm{-CH}}_{3}(\\mathrm{b})$ ; a is in thin bonds and $\\boldsymbol{\\mathbf{b}}$ is in thick bonds. Every two of the same configurations are coupled together, with the distance and dihedral angle between two adjacent benzenes of $4.296\\mathring{\\mathrm{A}}$ and $24.39^{0}$ in ${\\mathrm{CS-CH}}_{3}$ (a) respectively, while they are $4.116\\mathring{\\mathrm{A}}$ and $13.50^{\\mathrm{o}}$ for $\\mathrm{CS\\mathrm{-CH}}_{3}(\\mathrm{b})$ . As for CS-H, it shows a medium centroid distance and dihedral angel between the adjacent phenyl rings, namely $3.994\\mathring{\\mathrm{A}}$ and $18.\\dot{08}^{0}$ respectively. These crystal data demonstrate that the phosphors with acceptor substituents (CS-Br, CS-Cl, and CS-F) show much enhanced $\\pi{-}\\pi$ interactions, rather than CS-H without substituent and those $\\mathrm{CS-CH}_{3}\\mathrm{O}$ and ${\\mathrm{CS-CH}}_{3}^{\\prime}$ ) with donor substituents, in good accordance to the decreasing tendency in their RTP lifetimes for crystals. Thus, the packing mode with strong $\\pi{-}\\pi$ interactions could be considered as the main origin for the formation of the stabilized $T_{1}{^*}$ state, accompanying with the persistent RTP effect. This phenomenon could be termed as one of Molecular Uniting Set Identified Characteristic (MUSIC). \n\nFurther on, we took two molecules in our system as examples to study their aggregate mode: one was $\\mathrm{C}\\dot{\\mathsf{S}}\\ –\\mathrm{CH}_{3}\\mathrm{O}$ with the shortest RTP lifetime of $88~\\mathrm{{ms}}$ and another was CS-F with the longest RTP lifetime up to $410\\mathrm{ms}$ . Also, a famous RTP luminogen of DEOPh with H-aggregation was studied for comparison. According to the experimental results, it was clear that ${\\mathrm{CS-CH}}_{3}{\\mathrm{O}}$ and CS-F were all J-aggregates for the bathochromic-shifted absorption from solution to aggregation, while DEOPh was H-aggregate for the hypochromatic-shifted absorption from solution to aggregation (Supplementary Fig. 10). \n\nThus, it is the $\\pi{-}\\pi$ stacking rather than $\\mathrm{~H~}$ -aggregation that should be mainly responsible for the RTP effect in our system. On the other hand, the absorptions of both ${\\mathrm{CS-CH}}_{3}\\mathrm{O}$ and CS-F were equally affected by aggregation, but they show marked different RTP responses in their crystal forms, and thus it was concluded that the aggregates in ground state were not the main origin, at least not the sole origin responsible for their different RTP behaviors in the crystals. \n\nAlso, the strength of intermolecular interactions (C-H…π, CH…O, C-H…N, C-H…F, and so on) should also be taken into consideration for the persistent RTP effect, because of its effective suppression to the non-radiative decay20,31,32. For compounds CS-F, its longest phosphorescence lifetime $(410\\mathrm{ms})$ in crystal might mainly be originated from the enhancement of intermolecular interactions, although their centroid–centroid distance $(3.773\\mathring\\mathrm{A})$ in $\\pi{-}\\pi$ stacking is a little longer than those of $\\mathrm{CS\\mathrm{-}B r}$ $(3.677\\mathring\\mathrm{A})$ and CS-Cl $\\breve{(}3.732\\mathrm{\\AA})$ . The raised PXRD peaks (Supplementary Fig. 4) and melting points from $224^{\\circ}\\mathrm{C}$ (CS-Br) to $242^{\\circ}\\mathrm{C}$ (CS-Cl) and $247^{\\circ}\\mathrm{C}$ (CS-F) could also well suggest the enhancement of intermolecular interactions from CS-Br and CS$\\mathrm{\\DeltaCl}$ to $\\mathrm{CS-F}^{33}$ . Thus, the synergistic effect of strong $\\pi{-}\\pi$ stacking and efficient intermolecular interactions promotes the persistent RTP character in this system. \n\nEffect of $\\pi{-}\\pi$ interaction on excited state. In order to reveal the internal mechanism of why strong $\\pi{-}\\pi$ interactions could stabilize the excited triplet state, the research on molecular orbitals of molecules with the strong $\\pi-\\pi$ stacking was carried out (Supplementary Table 3). As shown in Fig. 4a, when two $\\pi$ systems are colliding, the main electronic interactions will involve their highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital $(\\mathrm{LUMO})^{34}$ . According to the perturbation theory, the HOMOs of two $\\pi$ systems interact with each other, then produce two new HOMO orbitals, while the same process occurs for their LUMO orbitals. The newly formed HOMOs and LUMOs are split in energy relative to the original HOMOs and LUMOs, one of the new orbital is lower in energy than the original one, while another is higher. Thus, when a photon, absorbed by one $\\pi$ system, jumps to the excited state, the electrons would redistribute in the new excited state for the $\\pi{-}\\pi$ interactions. Then three electrons are stabilized (two on the lower energy HOMO, one on the lower energy LUMO), while only one electron is destabilized in the higher energy HOMO. Thus, a new excited state with lower energy could be achieved for the $\\pi{-}\\pi$ interactions. On the other hand, no vibrational energy sub-levels exist for this excited state and the corresponding ground state of vertical energy transition, which could inhibit the non-radiative transition. Thus, it is proposed that the $\\pi{-}\\pi$ interaction could lead to the formation of a new particular excited state with slow radiative decay and non-radiative decay rate, just like $T_{1}{^*}$ state. Then, the slower radiative decay $(k_{\\mathrm{P}})$ and restricted non-radiative decay $(k_{\\mathrm{TS}})$ from $T_{1}$ to $S_{0}$ could both stabilize the excited triplet state and lead to the longer phosphorescence lifetime $(\\tau_{\\mathrm{P}})$ ; see Eq. (1) below: \n\n![](images/f0905fe84db7b5108a1b6121e1f9184cd2fb44a0c4e8d73129edbcf5ca779d6c.jpg) \nFig. 1 The room temperature phosphorescence (RTP) behavior of the six target compounds. The molecular structures of the six compounds of ${\\mathsf{C S-C H}}_{3}{\\mathsf{O}},$ ${\\mathsf{C S-C H}}_{3},$ CS-H, CS-Br, CS-Cl, and CS-F, and their corresponding phosphorescence lifetimes in crystals at room temperature (RT). The photographs were taken at different times, before and after turning off the $365\\mathsf{n m}$ UV irritation under ambient conditions \n\n![](images/78cf9043ce40a357fa8f991057a8abe8e014507c40515b8a5e931e63a6441f31.jpg) \nFig. 2 The phosphorescence spectra and corresponding time-resolved decay curves for the six compounds. a The normalized room temperature phosphorescence spectra of ${\\mathsf{C S-C H}}_{3}{\\mathsf{O}},$ , $C S-C H_{3},$ CS-H, CS-Br, CS-Cl, and CS-F in crystal state. b Time-resolved PL-decay curves for their room temperature phosphorescence in crystal state. c The normalized low temperature $(77\\mathsf{K})$ phosphorescence spectra in dichloromethane solution, concentration: $10^{-5}M$ . d Time-resolved PL-decay curves for their low temperature phosphorescence in dichloromethane solution, concentration: $10^{-5}M$ e The proposed mechanism for organic persistent RTP: the strong $\\pi{-}\\pi$ interaction could decrease the radiative transition $(k_{\\mathsf{P}})$ and non-radiative transition $(k_{\\mathsf{T S}})$ from ${{T}_{1}}$ to $S_{0}$ state, thus achieving the persistent room temperature phosphorescence \n\n$$\n\\tau_{\\mathrm{P}}=1/(k_{\\mathrm{P}}+k_{\\mathrm{TS}}).\n$$ \n\nTo obtain a deep insight into the RTP process, the energy levels of excited states were calculated for the isolated molecules and coupled units with $\\pi{-}\\pi$ interaction derived from the single-crystal structures (Supplementary Table $4)^{35}$ . All of the six compounds give the similar $T_{1}$ energies in the range of $3.8256{-}3.9760\\ensuremath{\\mathrm{~eV}}$ , just like the case observed in their low temperature phosphorescence, indicating the reliability of theory calculations to some extent. When two molecules couple together, the energies of $T_{1}{^*}$ for coupled units show varying degrees of decline, in comparison with that of $T_{1}$ for isolated molecules. For ${\\mathrm{CS-CH}}_{3}\\mathrm{O}$ and $\\bar{\\mathrm{CS-CH}_{3}}$ with electron-donating substituents and weak $\\pi{-}\\pi$ interactions, the declines in the coupled ones are much less, ranging from 0.0281 to $0.0573\\mathrm{eV}$ . On the contrary, the compounds of CS-Br, CS-Cl, and CS-F with electron-withdrawing substituents and stronger $\\pi{-}\\pi$ interactions exhibit much larger declines from the $T_{1}$ of isolated molecules to $T_{1}{^*}$ of coupled units, ranging from 0.0865 to $0.1186\\mathrm{eV}$ . These calculated results could well certify the strong $\\pi{-}\\pi$ interactions as the main origin to lower the energy and reducing the radiative decay from $T_{1}{}^{*}$ to $S_{0}$ state, thus leading to the promotion of RTP lifetimes. Also, calculations on energy levels of these compounds in the crystalline state were carried out by combined quantum mechanics and molecular mechanics (QM/MM) method (Supplementary Figs. 11–16, Supplementary Table 4–6). As shown in Supplementary Table 4, the energies for the central monomer molecules in crystalline states were similar to those of the isolated molecules, while those in coupled units were much different, which could prove the great effect on energy levels for the formation of coupled ones once more. The calculations in gas state were also carried out (Supplementary Figs. 11–16, Supplementary Table 5), and the optimized structures were similar to those in crystals. \n\n![](images/2a53e351958e727f5c823eb53bac5cd54751100a00326d5a6e9ab6d32124dd10.jpg) \nFig. 3 Single-crystal structures of the six target compounds. Entire and local packing modes of the crystals for ${\\mathsf{C S-C H}}_{3}{\\mathsf{O}},$ ${\\mathsf{C S-C H}}_{3},$ CS-H, CS-Br, CS-Cl, and CS-F: the local packing pictures were selected from the parts in cycles of corresponding entire ones, in which the centroid–centroid distances and the dihedral angles of the involved phenyl rings are listed and the phenyl rings involved in the stronger $\\pi{-}\\pi$ interactions in entire are labeled by pink color \n\nEffect of electronic effect on $\\pi{-}\\pi$ interactions. It is interesting that, in this system, the compounds with electron-withdrawing substituents would favor the stronger $\\pi{-}\\pi$ interactions, while others with electron-donating substituents not. Considering the close relationship between molecular packing and property, it would be of great importance to make clear how the substituents affect the $\\pi{-}\\pi$ interaction. Actually, in 1990, the pioneering works of Hunter and Sanders36 have provided an intuitive physical model of the substituent effect on the $\\pi{-}\\pi$ interaction37. They proposed that the strength and preferred orientations of $\\pi{-}\\pi$ interactions between adjacent aromatic rings could be understood and predicted based on a simple electrostatic model. As shown in Fig. 4b, the electron-withdrawing substituents (–Br, –Cl, $-\\mathrm{F}_{:}$ , and so on) could enhance $\\pi{-}\\pi$ interactions by decreasing the $\\pi$ -electron density of the substituted $\\pi$ -system and relieving the $\\pi{-}\\pi$ repulsion between the two involved rings. On the other hand, the electron-donating substituent $\\left(-\\mathrm{OCH}_{3}\\right)$ . ${\\mathrm{-CH}}_{3}$ , and so on) would lead to the dense $\\pi$ -electron density, and hinder $\\pi{-}\\pi$ interactions. Just according to the Hunter–Sanders model, the above explanation could be given for the preferred molecular packing in crystals of these six compounds, which could guide the molecular design of persistent RTP materials to some extent. \n\nFurthermore, the calculations on the electrostatic potential (ESP) were carried out, which have often been used to explore the origin for different strengths of $\\pi{-}\\pi$ interactions38,39. The ESP is the electrostatic interaction that a positive test charge would experience at that position at a given point in space in the vicinity of a molecule, and it could reflect the difference of the electron density distribution. As presented in Fig. 4c and Supplementary Table 7, the potential energy range is from $-0.015$ to $\\mathsf{0.015H\\mathsf{q}^{-1}}$ for all surfaces demonstrated; the red color shows areas with the dense electron density, yellow for normal, while blue areas suggest less electron density. The detailed comparison of the electrostatic potential surfaces of these six compounds suggests that $\\mathrm{CS-CH}_{3}\\mathrm{O}$ and ${\\mathrm{CS-CH}}_{3}$ with electron-donating substituents present the dense electron density (in red color) on the phenyl rings involved in the $\\pi{-}\\pi$ interactions, then CS-H without substituent. As for CS-Br, CS-Cl, and CS-F with electron-withdrawing substituents, their electron densities of the corresponding phenyl rings are largely reduced (in yellow color) for the induction effect of Br, Cl, and F atoms. The reduced electron density on the face of rings would relieve the $\\pi{-}\\pi$ repulsion between the two involved rings, thus resulting in the shorter $\\pi{-}\\pi$ distance and stronger $\\pi{-}\\pi$ interaction. \n\nPhoto-induced phosphorescence effect. According to the above results, it could be proposed that the introduction of stronger electron-withdrawing substituent on the 10-phenyl ring would relieve the $\\pi{-}\\pi$ repulsion and lead to the effective $\\pi{-}\\pi$ interaction, thus resulting in the stronger persistent RTP effect. To further check this point, the trifluoromethyl group with even stronger electron-withdrawing ability was introduced to yield ${\\mathrm{CS-}}{\\bar{\\mathrm{CF}}}_{3}$ (Fig. 5, Supplementary Fig. 17). Unexpectedly, the as-prepared ${\\mathrm{CS-CF}}_{3}$ powder did not show visible RTP, and even no RTP was observed in its single crystal, totally out of the rule summarized from the above six compounds. Excitedly, it turned to show obvious persistent RTP effect upon UV irradiation for $5\\mathrm{min}$ , accompanying with increased RTP lifetime to $299\\mathrm{{ms}}$ (Fig. 5a). Then it would return to the initial state after several hours of standing under natural conditions at room temperature. This has never been reported before, and could be termed as photoinduced room temperature phosphorescence. Thus, we monitored the excitation and relaxation procedure of RTP intensity and lifetimes, and it was found that transition from crystal (i) to crystal (p) was finished within $4\\mathrm{{min}}$ under the UV irradiation at \n\n![](images/e62e46ad1eb33892a62390420ba988ea165ab882b2d38b14a89582d4f8033d40.jpg) \nFig. 4 The influence of $\\pi{-}\\pi$ interactions on the electron redistribution and RTP behavior. a The orbital interaction of $\\pi{-}\\pi$ stacking in excited state: the electrons would redistribute in new orbitals for the $\\pi{-}\\pi$ interactions, then three electrons are stabilized and one electron is destabilized, and thus the net stabilization is two electrons. b Depiction of the electrostatic model of substituent effects on $\\pi{-}\\pi$ interactions from Hunter–Sanders model: electronwithdrawing substituents could enhance $\\pi{-}\\pi$ interactions by decreasing the $\\pi$ -electron density of the substituted $\\pi$ -system and relieving the $\\pi{-}\\pi$ repulsion, while electron-donating substituents hinder $\\pi{-}\\pi$ stacking through the opposite mechanism. c Difference electrostatic potential (ESP) analysis of isolated ${\\mathsf{C S-C H}}_{3}{\\mathsf{O}},$ $C S-C H_{3}$ (a), CS-H, CS-Br, CS-Cl, and CS-F. The potential energy range is $-0.015$ to $0.015{\\mathsf{H}}{\\mathsf{q}}^{-1}$ for all surfaces shown, red indicates areas with dense electron density, yellow for normal, while blue areas suggest less electron density \n\n$365\\mathrm{nm}$ (Supplementary Fig. 18). Over $4\\mathrm{{min}}$ , the RTP intensity and lifetime would nearly not change. After stopping the UV irradiation, they both decreased with standing time, then returned to the initial state after several hours (Supplementary Fig. 19). \n\nTo explore the origin of this unique property, the UV–visible absorptions of ${\\mathrm{CS-CF}}_{3}$ crystal before and after $5\\mathrm{min}$ of UV irradiation were measured but without obvious change, indicating no molecular structure change during this process (Fig. 5b). Similarly, the phosphorescence excitation peaks retained before and after UV irradiation at $365\\mathrm{nm}$ for $5\\mathrm{min}$ , and just the enhanced excitation intensity could be observed (Supplementary Fig. 20). As reported in the literatures, for some molecules, there were some molecular motions present in their single crystals under UV irradiation, which could lead to big changes of the photophysical properties, such as the fluorescence or morphology change, but not concerning the phosphorescent change40–44. \n\nIn order to make clear whether there are molecular motions in ${\\mathrm{CS-CF}}_{3}$ crystal under UV light, we measured the single-crystal structures of ${\\mathrm{CS}}{\\mathrm{-CF}}_{3}$ before and after UV irradiation for $5\\mathrm{{min}}$ . As shown in Fig. 5d, Supplementary Table 8 and Supplementary Fig. 21, the distance between two adjacent phenyl rings in the coupled ${\\mathrm{CS}}{\\mathrm{-CF}}_{3}$ changed from $3.999\\mathring{\\mathrm{A}}$ at the initial state to 3.991 $\\mathring\\mathrm{A}$ after UV irradiation for $5\\mathrm{{min}}$ in the phosphorescence state. Although the change of the $\\pi{-}\\pi$ distance in crystal between the initial and phosphorescence states is too small and nearly ignorable, the apparent RTP process could confirm the significant variation. In the process of UV stimulation, enhanced $\\pi{-}\\pi$ interactions might have been achieved, which led to the appearance of persistent RTP character. Considering the long time needed in the measurement of single crystal (about $^{\\textrm{1h}}$ ), the relaxation would happen from the phosphorescence state to initial one, and thus the minor changes in the crystal packing might be reasonable. On the other hand, the X-ray might make some influences on the molecular packing under test conditions. \n\nFurthermore, based on the model in Fig. 4a, molecules tend to form enhanced $\\pi{-}\\pi$ interactions for the lower energy effect in the excited state, and thus when ${\\mathrm{CS-CF}}_{3}$ in crystal was excited under UV irradiation, the molecular motion processed. After a period of time, the crystal moved to a more stable packing status in the excited state, in which the $\\pi{-}\\pi$ interactions were enhanced, thus achieving the ultralong RTP character. However, about $^{2\\mathrm{h}}$ later without the excitation of UV irradiation, the phosphorescence crystal would return to the initial state for its more stable ground state. Thus, the reversible photo-induced phosphorescence could be certainly ascribed to the reversible change of crystal packing. As for the as-prepared ${\\mathrm{CS-CF}}_{3}$ powder, no required $\\pi{-}\\pi$ interactions could be formed even after a long time of UV irradiation for the irregular molecular arrangement (Supplementary Fig. 22). Thus, no significant RTP character could be observed after the UV irradiation. \n\nTo further confirm the change of molecular packing as the main origin for its photo-induced phosphorescence effect, the control experiments under low temperature (i.e., 77 K) were conducted45. As shown in Supplementary Fig. 23, no obvious changes including RTP intensity and lifetime could be observed before and after $5\\mathrm{{min}}$ of UV irradiation on the initial ${\\mathrm{CS-CF}}_{3}$ crystal at 77 K. This should be ascribed to the effective inhibition effect on molecular motion under low temperature. Further on, the low temperature (i.e., 77 K) could restrict the decay for phosphorescence state to initial state of crystal ${\\mathrm{CS-CF}}_{3}$ : the RTP lifetime could retain at $256\\mathrm{ms}$ after $^{2\\mathrm{h}}$ of standing at $77\\mathrm{K}$ while it decreased to just $37\\mathrm{ms}$ at room temperature (Fig. 5c). Similarly, much less damping for RTP intensity was observed after $^{2\\mathrm{h}}$ of standing at $77\\mathrm{K}$ in comparison with that at room temperature (Supplementary Fig. 24). Thus, these control experiments could certify significant influence of molecular motion and molecular packing on the unique photo-induced phosphorescence effect. \n\n![](images/73651237d73f8a2aaf9c6c530cf530fd5acb4f381bc0579d8fbc12970ab6ab36.jpg) \nFig. 5 The photo-induced phosphorescence property of ${\\mathsf{C S-C F}}_{3}$ . a The room temperature phosphorescence spectra of $C S\\mathrm{-}C F_{3}$ crystal before and after 365 $\\mathsf{n m}\\cup\\mathsf{V}$ irradiation for $3\\mathrm{{min}}$ . b The UV–visible spectra of the $C S\\mathrm{-}C F_{3}$ crystal before and after UV irradiation for $5\\min$ . c Time-resolved PL-decay curves for the room temperature phosphorescence of $C S\\mathrm{-}C F_{3}$ crystal under $\\mathsf{\\bar{m i n}}365\\mathsf{n m}\\mathsf{U V}$ irradiation and after 1 or 2 or $4\\ h$ of standing at $77\\mathsf{K}$ or $298\\mathsf{K}$ . d The crystal structures of coupled $C S\\mathrm{-}C F_{3}$ before and after UV irradiation for 5 min. e Double security protection applications by using three kinds of components of ${\\mathsf{C S-C F}}_{3},$ CS-F and (4-methoxyphenyl)(phenyl)methanone. Under $365\\mathsf{n m}\\mathsf{U V}$ irradiation, it presents blue pattern 8; then switching off the UV light suddenly, it turns to green pattern 7; if the UV irradiation could be kept for about $5\\min$ , it would appear green pattern 9 after turning off the UV light \n\nGiven the interesting reversible photo-induced RTP characteristic of ${\\mathrm{CS-CF}}_{3}$ , it is a good candidate as double document security. As shown in Fig. 5e and Supplementary Fig. 25, the original pattern of 8 was made of three kinds of components, one was ${\\mathrm{CS}}{\\mathrm{-CF}}_{3}$ with the characteristic of the reversible photoinduced phosphorescence, the second was CS-F with normally persistent RTP characteristic, and the last one was (4-methoxyphenyl)(phenyl)methanone without the RTP property. Once the pattern was excited under a $365\\mathrm{nm}$ UV lamp, it presented a blue 8. Switching off the UV light suddenly, the green 7, encrypted by CS-F molecule with the ultralong RTP, could be readily visualized, while the other parts made of ${\\mathrm{CS}}{\\mathrm{-CF}}_{3}$ and (4- methoxyphenyl)(phenyl)methanone lightness. However, if keeping the UV irradiation for about $5\\mathrm{{min}}$ , the part of ${\\mathrm{CS-CF}}_{3}$ would be turned to be RTP active. Then, switching off the UV source, a totally different pattern of a green 9 would arise and disappear gradually, which was the integration of CS-F and ${\\mathrm{CS}}{\\mathrm{-}}{\\mathrm{\\bar{C}F}}_{3}$ Furthermore, this process is reversible and the persistent RTP pattern of green 7 could be recovered after about $\\bar{2}\\mathrm{h}$ of standing without UV irradiation. This reversible process at room temperature without any other external stimulation makes CS$\\mathrm{CF}_{3}$ a promising candidate for double security protection material. \n\nIn vivo phosphorescent imaging. Furthermore, compounds CSF and ${\\mathrm{CS}}{\\mathrm{-CF}}_{3}$ were selected to test the potential applications in in vivo phosphorescent imaging. Top-down approach was utilized to prepare water-soluble organic nanoparticles based on CS$\\mathrm{~F~}{}$ or ${\\mathrm{CS-CF}}_{3}$ with ultralong phosphorescence, which could take advantage of strong molecular packing of RTP luminogens to generate aggregates within nanoparticles (Fig. 6a and Supplementary Figs. 26–27)10. It was a little pity that photo-induced RTP effect could not be achieved in the ${\\mathrm{\\dot{C}S\\mathrm{-}C F_{3}}}$ nanoparticles (Supplementary Figs. 28–30), partially due to the opaqueness of nanoparticles. Thus, particular attention was paid to the CS-F nanoparticles with the longer RTP lifetime. First, the solution of CS-F nanoparticles was irradiated with UV light for $1\\mathrm{min}$ to activate nanoparticles, then the ultralong phosphorescence can be easily detected even at $t=10s$ after removal of light source (Supplementary Figs. 29–30). Also, the ability of the CS-F nanoparticles for in vivo imaging was validated in living mice. CS-F $(0.5\\mathrm{mg}\\mathrm{ml}^{-1}$ , $50\\upmu\\mathrm{l})$ were administered to the forepaws of living mice anesthetized using $2\\%$ isoflurane in oxygen via intradermal injection. At $t=1\\mathrm{h}$ post injection, nanoparticles were activated by irradiation with $365\\mathrm{nm}$ hand-held UV lamp for 1 min. Then the image was acquired at $t=10s$ after removal of light source using IVIS living imaging system under the bioluminescence mode. As shown in Fig. 6b, the ultralong phosphorescence could be easily detected with RTP intensity up to $1\\dot{2},000\\mathrm{p}s^{-1}\\mathrm{cm}^{-2}\\mathrm{sr}^{-1}$ , comparable to the previous report about organic RTP luminogens10. For comparison, the in vivo fluorescence imaging of mice was also carried out (excitation: 430 $\\pm15\\mathrm{nm}$ ; emission: $600\\pm10\\mathrm{nm}\\mathrm{\\Omega}$ ) and the background fluorescence was too strong to distinguish the signal of the CS-F nanoparticles. Thus, these results well demonstrated the potential of CS-F for real-time excitation-free in vivo phosphorescent imaging. \n\n![](images/7ebddb65cb46f2e62d23b9ac975175e70b92eb41e9d9eda1cf60e79d16809122.jpg) \nFig. 6 In vivo real-time excitation-free phosphorescent imaging of lymph nodes. a Top-down approach to synthesize the water-soluble nanoparticles of CS-F: the crystal was added to the aqueous solution of PEG-b-PPG-bPEG (F127) under continuous sonication, then the aqueous solution was filtered through a $0.22\\upmu\\mathrm{m}$ polyvinylidene fluoride (PVDF) (Millipore). b Ultralong phosphorescence and fluorescence imaging of lymph node in living mice $1h$ after the intradermal injection of CS-F nanoparticles into the forepaw of mice \n\n# Discussion \n\nAs revealed by our experimental data, the intermolecular $\\pi{-}\\pi$ interaction plays an important role for the RTP effect. Actually, this viewpoint is applicable to other RTP systems in which the $\\pi-$ $\\pi$ distances in single crystals are found to have direct relationship with RTP lifetimes (Supplementary Figs. 31–32), further confirming the accuracy of the statement21,46. Based on our research and other successful cases reported so far, mainly three issues should be taken into consideration to design the persistent RTP materials. \n\nFirst, the N, O atoms and so on with lone pair electrons should be introduced, which would contribute much to the $n{-}\\pi^{*}$ transition and intersystem crossing, thus achieving the efficient $\\mathrm{RTP^{7-}}$ 28,47 \n\nSecondly, the strong $\\pi{-}\\pi$ stacking in solid state should be considered as one of the main origin for the ultralong lifetime of RTP materials, since it could decrease the radiative decay rate $(k_{\\mathrm{P}})$ or non-radiative decay rate $(k_{\\mathrm{TS}})$ from $T_{1}$ to $S_{0}$ state, and lead to the longer RTP lifetime through the Eq. (1)18,48,49. \n\nThe third one is how to enhance the $\\pi{-}\\pi$ interactions in solid state from the initial molecular design. There are mainly two ways: one is to relieve the $\\pi{-}\\pi$ repulsion, while another is to increase the $\\pi{-}\\pi$ attraction (Supplementary Fig. 33). In our system, the introduction of electron-withdrawing substituents (Br, Cl, F, and so on) decreases the $\\pi$ -electron density of the substituted $\\pi$ -system and relieves the $\\pi{-}\\pi$ repulsion between the two involved rings, thus realizing the strong $\\pi{-}\\pi$ stacking. Alternatively, the reduction of the steric hindrance is also an efficient way to relieve $\\pi{-}\\pi$ repulsion, and thus the molecule with a planar conformation seems a good choice19,46. Then, the electrostatic interaction, dipole–dipole interaction an so on are considered as the main driving forces to enhance the $\\pi{-}\\pi$ attraction with the dense $\\pi{-}\\pi$ stacking. The Integration of the electron donor and acceptor in one molecule would be much beneficial to the intermolecular electrostatic interaction or dipole–dipole interaction and so on, possibly leading to the enhanced $\\pi{-}\\pi$ attraction and strong $\\pi{-}\\pi$ stacking19,20,50. Eventually, the strong $\\pi{-}\\pi$ stacking in solid state might lead to the persistent RTP effect. \n\nHowever, it is still not clear that either the aggregates in ground state or the formed excimer in excited state should be mainly responsible for the persistent RTP effect in this system. In the beginning, it is believed the triplet excimers have been formed in the crystals through the following scheme: \n\n$$\nh\\nu+\\mathrm{R}\\longrightarrow\\mathrm{^1R^{*}}\\longrightarrow\\mathrm{^1E^{*}}\\longrightarrow\\mathrm{^3E^{*}},\n$$ \n\nin which $\\mathrm{~R~}$ is the ground-state molecule, $^{1}\\mathrm{R^{*}}$ is the excited singlet state molecule, $^{1}\\mathrm{{E^{*}}}$ is the singlet excimer, $^3\\mathrm{E}^{*}$ is the triplet excimer. Then, the $^3\\mathrm{E}^{*}$ would lead to their ultralong RTP lifetimes. If it is, the phosphorescence excitation spectra should match the absorption spectra51. Unfortunately, the absorption and phosphorescence excitation spectra do not match each other as expected (Supplementary Fig. 34). The excitation spectra show a pronounced contribution to the phosphorescence emission from states that may exist at the onset of the absorption but seem to have very low oscillator strength to be observed. These can be aggregates. The triplet excimer mechanism therefore cannot be confirmed in this way. It cannot be simply discarded either as reabsoprtion/satuartion effects in crystals may be the cause of this mismatch. \n\nHowever, the absorption spectrum of ${\\mathrm{CS}}{\\mathrm{-CF}}_{3}$ crystal in Fig. 5b does not show significant differences upon irradiation, and this indicates that no new ground-state species are being formed. Once more, the phosphorescence excitation spectrum of ${\\mathrm{CS-CF}}_{3}$ crystals is entirely different when compared with absorption spectra, and again shows a red-shifted absorption band at the onset of the absorption spectrum. This agrees with the mismatch between the absorption and excitation spectra observed in the other molecules, and indicates the underlying phenomena to explain the long-lived RTP should be the same. However, it is clear that some sort of molecular rearrangement is involved on the observation of long-lived RTP in ${\\mathrm{CS}}{\\mathrm{-}}{\\mathrm{CF}}_{3}$ crystals (Fig. 5d) and upon irradiation, the ${\\mathrm{CS-CF}}_{3}$ molecules have to rearrange themselves to form the species that gives origin to the long-lived phosphorescence. Such interaction does not occur in the nonirradiated molecules as the lifetime of the RTP is much shorter in the non-irradiated samples. Therefore, we can conclude that the irradiation in ${\\mathrm{CS-CF}}_{3}$ molecules may create sandwich type species which give origin to the long-lived RTP. This is very similar to the formation of excimers; i.e., immediately upon irradiation the CS$\\mathrm{CF}_{3}$ molecules are locked in the excimer configuration and continue giving origin to the long-lived RTP, but once the irradiation is turned off and as time passes, the excimer configuration is being lost due to dissociation induced by thermal-assisted vibrations, and the long-lived RTP disappears over time after irradiation has been turned off. Hence, the scenario in ${\\mathrm{CS-CF}}_{3}$ crystals seems to favor the formation of the excimer mechanism. However, with the data presented, it is not possible to completely discard the formation of ground-state species (aggregates) to explain the long-lived RTP. Thus, if we want to clarify the internal mechanism absolutely, more works should be done. \n\nIn summary, a series of 10-phenyl-10H-phenothiazine 5,5- dioxide derivatives have been synthesized, which demonstrate different phosphorescence properties at room temperature. Detailed investigation confirmed that the strong intermolecular interactions in solid state, inherited from the molecular electronic property and mainly determined by the molecular packing, accounted for their persistent RTP, exhibiting the effect of MUSIC. Excitedly, ${\\mathrm{CS}}{\\mathrm{-}}{\\mathrm{{CF}}}_{3}$ crystal shows unique reversible photoinduced phosphorescence effect due to the change of the molecular packing under UV irradiation. Furthermore, CS-F can be used for real-time excitation-free phosphorescent imaging of lymph nodes in living mice. \n\n# Methods \n\nIn vivo afterglow imaging. Preparation of nanoparticles: The solids of CS-F or ${\\mathrm{CS-CF}}_{3}$ $\\mathrm{\\Delta}\\cdot\\mathrm{\\Omega}^{\\mathrm{\\tiny1\\mg})}$ were added to the aqueous solution of PEG-b-PPG-b-PEG (F127) $(3.33\\mathrm{mg}\\mathrm{ml}^{-1}$ , $3\\mathrm{ml}$ ) under continuous sonication with a microtip-equipped probe sonicator (Branson, S-250D) for $10\\mathrm{min}$ . Finally, the aqueous solution was filtered through a $0.22\\upmu\\mathrm{m}$ polyvinylidene fluoride (PVDF) syringe-driven filter (Millipore). \n\nDynamic light scattering was performed on the Malvern Nano-ZS Particle Size. Ultraviolet–visible (UV–Vis) and fluorescence spectra were obtained using a SHIMADZU UV-3600 UV-VIS-NIR spectrophotometer and a RF-5301PC spectrofluorophotometer, respectively. \n\nAll animal studies were performed in compliance with the guidelines set by the Institutional Animal Care and Use Committee, Sing Health. Female nude mice were used for in vivo subcutaneous imaging and lymph node imaging. For subcutaneous in vivo optical imaging, mice were anesthetized using $2\\%$ isoflurane in oxygen, and then received two subcutaneous injections of organic nanoparticles or fluorescein $(1.6\\upmu\\mathrm{M})$ into the dorsal areas of mice. After subcutaneous injection of nanoparticles, in situ activation of ultralong phosphorescence was conducted by irradiation with a $365\\mathrm{nm}$ hand-held UV lamp for 1 min. The power density of the UV lamp was measured to be $10\\mathrm{mW}\\mathrm{cm}^{-2}$ using a Thorlab PM100D power meter equipped with a $\\mathrm{{\\sfS130VC}}$ power head with Si detector. It is lower than the maximum power exposure allowed for skin irradiation with 1 min of UV light (315 to $400\\mathrm{nm}$ ) $(18\\mathrm{mW}\\mathrm{cm}^{-2},$ ). The UV lamp was put $1\\mathrm{cm}$ above the injection sites of RTP nanoparticles. Then, the images were acquired at $t=10s$ after removal of light source using IVIS living imaging system. The signal acquisition was conducted for $10s$ under the bioluminescence mode with open filter setting. During the imaging, the mice were warmed with a heating pad under continued isoflurane anesthesia. For comparison, the in vivo fluorescence imaging of mice was also carried out (excitation: $430\\pm15\\mathrm{nm}$ ; emission: $500\\pm10\\mathrm{nm}$ ). \n\nData availability. The authors declare that the data supporting the findings of this study are available within the article and its Supplementary Information file. All data are available from the authors upon reasonable request. \n\n# Received: 1 February 2017 Accepted: 30 January 2018 Published online: 26 February 2018 \n\n# References \n\n1. Zhao, J., Wu, W., Sun, J. & Guo, S. Triplet photosensitizers: from molecular design to applications. Chem. Soc. Rev. 42, 5323–5351 (2013). \n2. Xu, S., Chen, R., Zheng, C. & Huang, W. Excited state modulation for organic afterglow: materials and applications. Adv. Mater. 28, 9920–9940 (2016). \n3. Kabe, R., Notsuka, N., Yoshida, K. & Adachi, C. Afterglow organic lightemitting diode. Adv. Mater. 28, 655–660 (2016). \n4. Bolton, O., Lee, K., Kim, H., Lin, K. & Kim, J. Activating efficient phosphorescence from purely organic materials by crystal design. Nat. Chem. \n3, 205–210 (2011). \n5. Wuest, J. Co-crystals give light a tune-up. Nat. Chem. 4, 74–75 (2012). \n6. Baroncini, M., Bergamini, G. & Ceroni, P. Rigidification or interactioninduced phosphorescence of organic molecules. Chem. Commun. 53, \n2081–2093 (2017). \n7. Shoji, Y. et al. Unveiling a new aspect of simple arylboronic esters: long-lived room-temperature phosphorescence from heavy-atom-free molecules. J. Am. Chem. Soc. 139, 2728–2733 (2017). phosphorescence of N-Phenyl-2-naphthylamine molecules by confinement in a crystalline dibromobiphenyl matrix. Angew. Chem. Int. Ed. 55, 15589–15593 (2016). \n9. Kuno, S. et al. Long persistent phosphorescence of crystalline phenylboronic acid derivatives and its mechanistic study. ChemPhotoChem 1, 102–106 (2017). \n10. Zhen, X. et al. Ultralong phosphorescence of water-soluble organic nanoparticles for in vivo afterglow imaging. Adv. Mater. 29, 1606665 (2017). \n11. Hirata, S. Recent advances in materials with room temperature phosphorescence: photophysics for triplet exciton stabilization. Adv. Opt. Mater. 5, 1700116 (2017). \n12. Fateminia, S. et al. Organic nanocrystals with bright red persistent room temperature phosphorescence for biological applications. Angew. Chem. Int. Ed. 56, 12160–12164 (2017). \n13. Lucenti, E. et al. H-aggregates granting crystallization-induced emissive behavior and ultralong phosphorescence from a pure organic molecule. J. Phys. Chem. Lett. 8, 1894–1898 (2017). \n14. Zhang, X. et al. General design strategy for aromatic ketone-based single component dual-emissive materials. ACS Appl. Mater. Interfaces 6, 2279–2284 (2014). \n15. Kabe, R. & Adachi, C. Organic long persistent luminescence. Nature 550, 384–387 (2017). \n16. Matsuzawa, T., Aoki, Y., Takeuchi, N. & Murayama, Y. A new long phosphorescent phosphor with high brightness, SrAl2O4:Eu2+, $\\mathrm{Dy}^{\\breve{3}+}$ . Electrochem. Soc. 143, 2670–2673 (1996). \n17. Ma, H. et al. Electrostatic interaction-induced room-temperature phosphorescence in pure organic molecules from QM/MM calculations. J. Phys. Chem. Lett. 7, 2893–2898 (2016). \n18. Kuno, S., Akeno, H., Ohtani, H. & Yuasa, H. Visible room-temperature phosphorescence of pure organic crystals via a radical-ion-pair mechanism. Phys. Chem. Chem. Phys. 17, 15989–15995 (2015). \n19. An, Z. et al. Stabilizing triplet excited states for ultralong organic phosphorescence. Nat. Mater. 14, 685–690 (2015). \n20. Cai, S. et al. Visible-light-excited ultralong organic phosphorescence by manipulating intermolecular interactions. Adv. Mater. 29, 1701244 (2017). \n21. Yuan, W. Z. et al. Crystallization-induced phosphorescence of pure organic luminogens at room temperature. J. Phys. Chem. C 114, 6090–6099 (2010). \n22. Gong, Y. et al. Achieving persistent room temperature phosphorescence and remarkable mechanochromism from pure organic luminogens. Adv. Mater. 27, 6195–6201 (2015). \n23. Yang, Z. et al. Intermolecular electronic coupling of organic units for efficient persistent room-temperature phosphorescence. Angew. Chem. 128, 2221–2225 (2016). \n24. Zhao, W. et al. Rational molecular design for achieving persistent and efficient pure organic room-temperature phosphorescence. Chem 1, 592–602 (2016). \n25. Xue, P. et al. Luminescence switching of a persistent room-temperature phosphorescent pure organic molecule in response to external stimuli. Chem. Commun. 51, 10381–10384 (2015). \n26. Mao, Z. et al. Linearly tunable emission colors obtained from a fluorescent–phosphorescent dual-emission compound by mechanical stimuli. Angew. Chem. 127, 6368–6371 (2015). \n27. Xu, B. et al. White-light emission from a single heavy-atom-free molecule with room temperature phosphorescence, mechanochromism and thermochromism. Chem. Sci. 8, 1909–1914 (2017). \n28. Li, C. et al. Reversible luminescence switching of an organic solid: controllable on–off persistent room temperature phosphorescence and stimulated multiple fluorescence conversion. Adv. Opt. Mater. 3, 1184–1190 (2015). \n29. Tao, Y. et al. Thermally activated delayed fluorescence materials towards the breakthrough of organoelectronics. Adv. Mater. 26, 7931–7958 (2014). \n30. Li, Y. et al. Design strategy of blue and yellow thermally activated delayed fluorescence emitters and their all-fluorescence white OLEDs with external quantum efficiency beyond $20\\%$ . Adv. Funct. Mater. 26, 6904–6912 (2016). \n31. Mei, J., Leung, N., Kwok, R., Lam, J. & Tang, B. Aggregation-induced emission: together we shine, united we soar! Chem. Rev. 115, 11718–11940 (2015). \n32. Qian, H. et al. Suppression of Kasha’s rule as a mechanism for fluorescent molecular rotors and aggregation-induced emission. Nat. Chem. 9, 83–87 (2017). \n33. Wang, C. et al. A stable tetraphenylethene derivative: aggregation-induced emission, different crystalline polymorph, and totally different mechanoluminescent property. Mater. Horiz. 3, 220–225 (2016). \n34. Turro, N. J. Modern Molecular Photochemistry (University Science Books, Mill Valley, 1991). \n35. Petersilka, M., Gossmann, U. & Gross, E. Excitation energies from timedensity functional theory. Phys. Rev. Lett. 76, 1212–1215 (1996). \n36. Hunter, C. & Sanders, J. The nature of π-π interactions. J. Am. Chem. Soc. 112, 5525–5534 (1990). \n37. Cozzi, F., Cinquini, M., Annuziata, R. & Siegel, J. Dominance of polar $/\\pi$ over charge-transfer effects in stacked phenyl interactions. J. Am. Chem. Soc. 115, 5330–5331 (1993). \n38. Rashkin, M. & Waters, M. Unexpected substituent effects in offset π-π stacked interactions in water. J. Am. Chem. Soc. 124, 1860–1861 (2002). \n39. Parrish, R. & Sherrill, C. Quantum-mechanical evaluation of $\\pi-\\pi$ versus substituent−π interactions in π stacking: direct evidence for the Wheeler −Houk picture. J. Am. Chem. Soc. 136, 17386–17389 (2014). \n40. Conyard, J., Cnossen, A., Browne, W., Feringa, B. & Meech, S. Chemically optimizing operational efficiency of molecular rotary motors. J. Am. Chem. Soc. 136, 9692–9700 (2014). \n41. Chung, J. et al. Shear- and UV-induced fluorescence switching in stilbenic π- dimer crystals powered by reversible [2+2] cycloaddition. J. Am. Chem. Soc. 131, 8163–8172 (2009). \n42. Zhou, H. et al. Photoswitching of glass transition temperatures of azobenzenecontaining polymers induces reversible solid-to-liquid transitions. Nat. Chem. 9, 145–151 (2017). \n43. Zhao, D., Leeuwen, T., Cheng, J. & Feringa, B. Dynamic control of chirality and self-assembly of double-stranded helicates with light. Nat. Chem. 9, 250–256 (2017). \n44. Iwaso, K., Takashima, Y. & Harada, A. Fast response dry-type artificial molecular muscles with [c2] daisy chains. Nat. Chem. 8, 625–632 (2016). \n45. Houjou, H., Ikedo, H. & Yoshikawa, I. Single-crystal UV-vis spectroscopic examination of a striking odd–even effect on structure and chromic behaviour of salicylidene alkylamines. Chem. Commun. 53, 10898–10901 (2017). \n46. Gong, Y. et al. Crystallization-induced dual emission from meta and heavy atom-free aromatic acids and esters. Chem. Sci. 6, 4438–4444 (2015). \n47. Mukherjee, S. & Thilagar, P. Recent advances in purely organic phosphorescent materials. Chem. Commun. 51, 10988–11003 (2015). \n48. Chaudhuri, D. et al. Enhancing long-range exciton guiding in molecular nanowires by H-aggregation lifetime engineering. Nano Lett. 11, 488–492 (2011). \n49. Weller, A. Electron-transfer and complex formation in the excited state. Pure Appl. Chem. 16, 115–124 (1968). \n50. Janiak, C. A critical account on π-π stacking in metal complexes with aromatic nitrogen-containing ligands. J. Chem. Soc. Dalton Trans. 21, 3885–3896 (2000). \n51. Lim, E. C. Molecular triplet excimers. Acc. Chem. Res. 20, 8–17 (1987). \n\n# Acknowledgements \n\nWe are grateful to the National Science Foundation of China (no. 21325416, 51573140), the Open Fund of the State Key Laboratory of Luminescent Materials and Device in South China University of Technology (no. 2017-skllmd-04), Hubei Province \n\n(2017CFA002), Special funds for basic scientific research services in central colleges and Universities (2042017kf0247), Nanyang Technological University (start-up grant: NTUSUG: M4081627.120), and Singapore Ministry of Education (Academic Research Fund Tier 1: RG133/15 M4011559 and Academic Research Fund Tier 2 MOE2016-T2-1- 098) for the financial support. \n\n# Author contributions \n\nAll the experiments were conducted by J.Y., X.G., Z.R., and J.W. with input and under the supervision of Z.L. The in vivo phosphorescent imaging was conducted by X.Z. under the supervision of K.P. All the crystal structures were measured by B.W. under the supervision of J.L. All the computational work was conducted by J.Y. and Y.X. with the help of Q.P. The manuscript was written jointly by J.Y. and Z.L. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-03236-6. \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1016_j.mattod.2017.11.004", + "DOI": "10.1016/j.mattod.2017.11.004", + "DOI Link": "http://dx.doi.org/10.1016/j.mattod.2017.11.004", + "Relative Dir Path": "mds/10.1016_j.mattod.2017.11.004", + "Article Title": "Dislocation network in additive manufactured steel breaks strength-ductility trade-off", + "Authors": "Liu, LF; Ding, QQ; Zhong, Y; Zou, J; Wu, J; Chiu, YL; Li, JX; Zhang, Z; Yu, Q; Shen, ZJ", + "Source Title": "MATERIALS TODAY", + "Abstract": "Most mechanisms used for strengthening crystalline materials, e.g. introducing crystalline interfaces, lead to the reduction of ductility. An additive manufacturing process - selective laser melting breaks this trade-off by introducing dislocation network, which produces a stainless steel with both significantly enhanced strength and ductility. Systematic electron microscopy characterization reveals that the pre-existing dislocation network, which maintains its configuration during the entire plastic deformation, is an ideal modulator that is able to slow down but not entirely block the dislocation motion. It also promotes the formation of a high density of nullo-twins during plastic deformation. This finding paves the way for developing high performance metals by tailoring the microstructure through additive manufacturing processes.", + "Times Cited, WoS Core": 777, + "Times Cited, All Databases": 822, + "Publication Year": 2018, + "Research Areas": "Materials Science", + "UT (Unique WOS ID)": "WOS:000433264200014", + "Markdown": "# Dislocation network in additive manufactured steel breaks strength– ductility trade-off \n\nLeifeng Liu 1,†, Qingqing Ding 2,†, Yuan Zhong 1, Ji Zou 3, Jing Wu 3, Yu-Lung Chiu 3, Jixue Li 2, Ze Zhang 2, Qian Yu 2,⇑, Zhijian Shen 1,⇑ \n\n1 Department of Materials and Environmental Chemistry, Arrhenius Laboratory, Stockholm University, 10691 Stockholm, Sweden \n2 Department of Materials Science & Engineering, Center of Electron Microscopy and State Key Laboratory of Silicon Materials, Zhejiang University, Hangzhou \n310027, China \n3 School of Metallurgy and Materials, University of Birmingham, B15 2TT, UK \n\nMost mechanisms used for strengthening crystalline materials, e.g. introducing crystalline interfaces, lead to the reduction of ductility. An additive manufacturing process – selective laser melting breaks this trade-off by introducing dislocation network, which produces a stainless steel with both significantly enhanced strength and ductility. Systematic electron microscopy characterization reveals that the pre-existing dislocation network, which maintains its configuration during the entire plastic deformation, is an ideal “modulator” that is able to slow down but not entirely block the dislocation motion. It also promotes the formation of a high density of nano-twins during plastic deformation. This finding paves the way for developing high performance metals by tailoring the microstructure through additive manufacturing processes. \n\n# Introduction \n\nThe motion of dislocations governs the plastic deformation, hence the mechanical properties of many metals [1–3]. The strength of the metals can be improved by hindering dislocation motion through the designing of microstructure including introducing secondary phases, grain boundaries, and other internal interfaces [4]. Unfortunately most of such strategies that effectively strengthen materials sacrifice ductility, resulting in the so called strength–ductility trade-off [5]. Although a few methods have shown the capability of improving strength while retaining the ductility of materials (for instance by introducing coherent twin boundaries [2,6], introducing bimodal grain sizes [7] and by controlling the size, morphology and distribution of secondary phases [8,9]), making final parts with complex shapes from these methods requires intensive additional machining and may even not be feasible in some cases. \n\nSelective laser melting (SLM) is a type of additive manufacturing (AM) processes which is now rapidly changing the ecosystem of manufacturing by enabling the manufacturing of complex components directly from digital files, thus benefiting the customized production and the freedom of designing [10]. During SLM, particle granules are fused directly into 3D components by repetitive scanning of a high energy laser beam over each layer of powder granules, thereby consolidating them via partial or full melting. Another important feature of AM is the ultrafast cooling rate $(10^{3}–10^{8}\\mathrm{K}/{\\mathrm{s}})$ . Unlike the other rapid cooling techniques e.g. splat quenching and melt spinning which can produce only metals in low dimensional shapes e.g. metal powder, ribbon and foil, AM can produce metals in 3-dimensional shapes (bulk parts) with an extraordinarily high cooling rate [11–14]. The bulk metal parts show microstructures distinct from those produced by traditional manufacturing routes such as casting and wrought processes [15–21]. In this study, we show that a dislocation network structure with the accompanying segregation of the alloying elements produced during SLM manufacturing of 316L stainless steel (316LSS) leads to unprecedented mechanical properties of a combination of enhanced yield strength and ductility compared to those with the same composition but produced in the other manufacturing processes [22–28]. In-situ SEM and TEM study reveals that the dislocation network with the accompanying segregation provides a high density of “flexible interfaces” that significantly tunes the dislocation behaviors, resulting in the ameliorated mechanical properties. The results indicate the possibility to directly manufacture products with a good combination of strength and ductility while retaining the benefits of the process in manufacturing parts with complex or customized geometries. \n\n# Materials and methods \n\n# Sample manufacturing process \n\nAs received gas-atomized spherical 316LSS powder with granular sizes ranging from 10 to $45\\ \\upmu\\mathrm{m}$ was purchased from Carpenter powder products AB, Torshälla, Sweden. The standard build was performed by a selective laser melting facility EOSINT M270 (EOS GmbH, Krailling, Germany) equipped with a continuous Nd:YAG fiber laser generator with maximum 200 W power output and typically ${70}{\\cdot}{\\upmu\\mathrm{m}}$ diameter laser spot. During the building process, a layer of powder $20\\upmu\\mathrm{m}$ in thickness) was laid by a recoating blade on a steel building plate which was preheated to $80~^{\\circ}\\mathrm{C}$ . The full laser power of 200 W was used and the laser beam was moving at the speed of $850\\mathrm{mm}/\\mathrm{s}$ . The laser scanned line by line along the same direction at the same layer and with the line spacing of $100\\upmu\\mathrm{m}$ . After the scanning was complete, a new layer of powder was laid and the laser scanned the new layer with the scanning direction rotated by $67^{\\circ}$ . The sample was built up by repeating this process. \n\nTo investigate the effect of scanning speed on dislocation cell size, the samples were built up using standard parameters and the last layer of each sample was scanned by laser with different scanning speeds and line spacings $(7000\\mathrm{mm}/\\mathrm{s},$ $10\\upmu\\mathrm{m}$ ; 4250 $\\mathrm{mm}/{\\mathsf s}$ , $20\\upmu\\mathrm{m}$ ; $283\\mathrm{mm}/\\mathrm{s}$ , $300\\upmu\\mathrm{m})$ . The corresponding SEM images were taken from the area within the top layers. \n\n# Tensile tests \n\nTensile test specimens (as-build size $\\Phi8\\times52\\mathrm{mm}$ ) were prepared by SLM using standard building parameters and machined to cylindrical test specimens (Gage length: $12\\mathrm{mm}$ ; gage diameter: $3\\mathrm{mm}\\mathrm{\\dot{\\Omega}}$ ). All the tensile test bars were built in the same build and with the longitudinal axes along the building direction. Tensile tests were performed according to ASTM E8 with a strain rate of $0.015\\mathrm{{min}^{-1}}$ up to yield point, and afterward $0.05\\mathrm{{min}^{-1}}$ till failure. An extensometer was used to measure the elongation. The reported values in this study for tensile properties were the average values of 5 tests. \n\n# Micropillar tests \n\nFor the micropillar compression test, two pellets were cut from the same bar built with the longitudinal axis along the building direction. One of them was packed in the stainless steel envelop and heated to $1050^{\\circ}\\mathrm{C}$ with the ramp rate of $10\\ \\mathrm{^{\\circ}C/m i n}$ , kept for $^{2\\mathrm{h}}$ and followed by water quench. The other one was kept in the as-SLMed state. Two pellets were ground and polished before micropillar experiment. A commercial Hysitron PI85 PicoIndenter installed inside a Tescan Mira-3 scanning electron microscope was used for micropillar compressions. The micropillars with a diameter of about $5\\upmu\\mathrm{m}$ , length of about $10\\upmu\\mathrm{m}$ and tapering angle less than 5 degree were fabricated in a FEI Quanta 3D FEG Focus Ion Beam (FIB) by $\\boldsymbol{{\\mathrm{Ga}}^{+}}$ ion beam with the current ranging from $30\\mathrm{nA}$ to $0.1\\mathrm{nA}$ at $30\\mathrm{kV}$ . Both of the two micropillars were fabricated from the grains with the (056) plane parallel to the top surface. The micropillars were then compressed using a flat punch diamond tip with a diameter of $20\\upmu\\mathrm{m}$ and a constant loading rate of $100\\upmu\\mathrm{N}/\\up s^{-1}$ . \n\n# TEM analysis \n\nTEM specimens were twin-jet electropolished in an alcoholic solution containing $5\\mathrm{vol.\\%}$ perchloric acid at $30\\mathrm{mA}$ and $-25$ $^{\\circ}\\mathrm{C}$ . Equipped with both bright field and annular dark field detectors, a Cs-corrected FEI $80{-}200\\mathrm{G}^{2}$ with Super-X operated at 200 $\\mathbf{kV}$ is employed to analyze the microstructure and elemental distribution of the SLMed 316LSS. The in-situ tensile tests were achieved by a Gatan model 654 single-tilt straining holder in a FEI Tecnai G2 F20 TEM operated at $200\\mathrm{kV}$ . \n\nSEM images were taken on the etched surfaces. Etching was done by submerging the mechanical polished samples into the etching agent $(\\mathrm{HF};\\mathrm{HNO}_{3};\\mathrm{H}_{2}\\mathrm{O}=1{:}4{:}45)$ for $60\\mathrm{{s}}$ \n\n# Results and discussion \n\nTensile properties of the SLMed 316LSS and TEM characterization of the dislocation network structure \n\nFigure 1b shows a component with the dimensions of $28\\mathrm{cm}\\times$ $16\\mathrm{cm}\\times16\\mathrm{cm}$ and a built-in complex internal cooling channel system manufactured using SLM process from 316LSS powders (particle size: $10-45\\upmu\\mathrm{m}\\mathrm{};$ for the potential application as the first wall panel part in the International Thermonuclear Experimental Reactor (ITER). Tensile tests reveal that the SLMed 316LSS shows notable improvement in both strength and ductility compared to the fully dense 316LSS processed by the other manufacturing methods (Figure 1a) [22–28]. The tensile yield strength of $552\\pm$ $4\\mathrm{MPa}$ and elongation to failure of $83.2\\pm0.7\\%$ , was obtained for the SLMed 316LSS (along the building direction). In contrast, the wrought-annealed 316LSS with an average grain size of $17.5\\upmu\\mathrm{m}$ from Ref. [22] shows yield strength of $244\\mathrm{MPa}$ and failure elongation of $63\\%$ [22]. A number of previous research on SLMed 316L reported that the process improves the yield strength but reduces or has little effect on ductility [11,29,30]. The ductility of metals is sensitive to the defects like voids and cracks whose presence largely depends on the process parameters. Only when the defects are suppressed, the contribution from the other factors would be revealed. \n\nResidual stress can be generated during SLM process, but it was not considered as the major factor affecting the tensile results in this work. Previous studies show that residual stress in SLMed sample can be comparable to the yield strength of the material near the top surface but is much lower in the lower part of the sample [31–33]. The gage section of the tensile test bar in this study is far below the top surface. Moreover the building plate was preheated to $80~^{\\circ}\\mathrm{C}$ during the process to reduce residual stress. The microstructure of the material is then considered as the main reason for the ameliorated mechanical properties. The SLMed 316LSS is composed of mainly columnar grains with diameters ranging from a few to tens of micrometers and lengths up to hundreds of micrometers. TEM analysis reveals a unique \n\n![](images/90b0bc9117462507019d3df8968fe2f358d6bb6249a0ba3741c3916226638d33.jpg) \n\n# FIGURE 1 \n\nThe dislocation network with the accompanying segregation of the alloying elements in SLMed 316LSS. (a) The yield strength and ductility data of the SLMed 316LSS and the fully dense 316LSS from literature. The elongation to failure was used. (b) A photo of the ITER first wall penal part manufactured by SLM. (c) A bright field (BF) STEM image of the dislocation network in the SLMed 316LSS with the corresponding selected area electron diffraction (SAED) pattern which shows the single grain signal. (d–i) An annular dark field (ADF) STEM image and elemental distribution maps of the selected area in (c). \n\nTABLE 1 \n\n\n
The content of the elements at the cell wall and inside the cell (wt.%) from EDS analysis.
PositionElement
FeCrNiMoMn
Cell wall 65.9 ± 1.3018.5 ± 0.6511.0 ± 0.162.8 ± 0.501.74 ± 0.06
Cell inner69.9 ±0.1116.7 ± 0.2410.3 ± 0.141.59 ± 0.111.42 ± 0.05
\n\ndislocation network embedded in individual grains. The dislocation network has been previously found only in 1D or 2D structures (e.g. the welding track or laser treated metal surface [34,35]), but not in bulk metals produced by any other manufacturing methods. Figure 1c shows the typical dislocation network within a coarse grain, with dislocations concentrated as the wall of columnar cells. SEM analysis shows that the cells have an average diameter of around $500\\mathrm{nm}$ and lengths ranging from a few micrometers to a few tens of micrometers. The dislocation cells are often aligned with the temperature gradient direction in the solidification process. The elemental maps (Figure 1e–i) from energy dispersive spectroscopy (EDS) analysis show that the element distribution on the dislocation network is fairly uniform with slight segregation of $\\mathrm{Cr}$ , Mo and Mn at the walls. Quantitative EDS analysis was performed on five random spots at the dislocation walls and in the other areas, respectively. The results (Table 1) show that Mo, Mn, Cr and Ni content at the dislocation network are all higher than those in the other areas. The formation of dislocation network structure with the accompanying segregation of the alloying elements is due to the cellular growth mode under the high temperature gradient and high growth rate condition [35]. Slight orientation differences for the neighboring cells cause the dense dislocation walls to form when cells grow together into coarse single grains. Meanwhile, the solidification front rejects the alloying elements to the liquid phase leading to higher content of alloying elements at the later solidified region – the cell boundaries [36]. Dislocation cells also form after plastic deformation in a wide range of metals [37]. The flow stress of the deformed metal is inversely linked to the size of such dislocation cells [38]. Therefore the presence of the dislocation cells in SLMed 316LSS is presumably the main reason of the improved mechanical property. \n\n# The strengthening effect of dislocation network confirmed by micropillar compression tests \n\nTo examine the role of this characteristic dislocation network in affecting the mechanical properties, we performed micropillar compression tests on two samples, viz. the as-SLMed 316LSS whose microstructure was decorated by dislocation network and SLMed-annealed 316LSS which was free of dislocation network after annealing at $1050^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ (Figure 2a, b, d, e). \n\nBoth single crystal micropillar samples were of the same size ( ${\\langle}5\\upmu\\mathrm{m}$ in diameter) before pressing and were compressed along the [056] direction. As shown in Figure ${\\displaystyle2}\\mathbf{g},$ the yield strength is about $240\\mathrm{MPa}$ for the annealed sample in contrast to $460\\mathrm{MPa}$ for the as-SLMed sample. The three remarkable plateaus on the stress–strain curve correspond to the three slip traces on the surface of the annealed micropillar (Figure 2f), indicating that catastrophic shear-off happened quite often due to the escape of a large number of dislocations from the intersections of the same slip planes and the surface. In contrast, the as-SLMed pillar had smoother plastic flow behavior. It indicates that with the dislocation network, the as-SLMed pillar had much better ability of dislocation storage where dislocations found significant difficulty during glide before they eventually slipped out from the surface therefore displayed both higher strength and better plastic stability. \n\n![](images/6e655c5d4b9e94aa59fd0e2f7b220a25eb43003f22677775f521d456859e1d9d.jpg) \nFIGURE 2 \n\nEffects of the dislocation network on dislocation motion and twin formation revealed by in-situ TEM analysis \n\nThe details of the dynamic motion and interaction of dislocations within such dislocation network were further investigated by performing in-situ TEM mechanical testing at room temperature using a Gatan in-situ straining holder. The major carrier for plastic deformation was partial dislocations, whose motion was significantly but not fully impeded by the dislocation network. Dislocations widely dissociated into Shockley partials with jerky motion when they were temporarily trapped by the dislocation walls and would move forward again with the increase in applied stress (Video 1). For instance, as shown in Figure 3a–d, the partial dislocations within a cell in the as-SLMed sample have Burgers vector 1/6 [211] and $1/6[12-1]$ , respectively. The dislocations in the cell walls are also mostly dissociated partial dislocations with Burgers vector $1/6{<}112{>}$ . Figure 3e shows the dynamic evolution of stacking fault, which corresponds to the motion of partial dislocation pairs through the dislocation cells. When the external stress was high enough, a leading partial was emitted from a cell wall ${^{\\prime\\prime}\\mathrm{A}}^{\\prime\\prime}$ and stopped at the cell wall $\\mathrm{^{\\prime\\prime}B^{\\prime\\prime}}$ against it. At this moment, the trailing partial was still trapped by the cell wall ${\\bf\\ddot{\\Pi}}^{\\prime\\prime}$ . As the applied stress increased gradually, the leading partial overcame the impediment of wall $\\mathrm{^{\\prime\\prime}B^{\\prime\\prime}}$ and glided into the neighboring cell. The trailing partial glided to wall ${}^{\\prime\\prime}\\mathrm{B}^{\\prime\\prime}$ as well. Clearly the motion of dislocations in SLMed 316LSS was hindered but not fully stopped by these cell walls. Slip transferred across the cells with increasing strain; therefore the strength was enhanced without sacrificing the ductility. This is a scenario similar to the coherent twin boundaries reported before [2]. Besides the impediment effect, the complex dislocation network with mostly dissociated partial dislocations might also have supplied sites for nucleation of dislocation loops, with which the dislocation interactions became even more prolific and complicated. \n\n![](images/4cff400f0804bb1741e444c990126bb793f874cc7017cf7a51055c1f2f37b846.jpg) \nMicropillar compression test result. (a and b) SEM and TEM images of the microstructure of the as-SLMed 316LSS. (c) Compression tested micropillar of the asSLMed 316LSS. (d and e) SEM and TEM images of the microstructure of the annealed 316LSS. (f) Compression tested micropillar of the annealed 316LSS. (g) The engineering stress–strain curves obtained from two micropillars. The as-SLMed sample shows almost doubled yield strength and much smoother plastic flow behavior than the annealed sample. \n\n# Video 1. \n\nMeanwhile, the cell walls could also trap partial dislocations so that some of the paired dislocations lost their partners. Consequently deformation twinning formed as the same type of partial dislocations glided on the adjacent planes. Figure 4a shows nano-twins formed after deformation. The dislocation network was found in the whole visible region; however, due to the slight orientation difference, the network on the left side was less visible under this imaging condition. The slim nano-twins oriented along the same direction and usually propagated through several cells. It was also observed that the nanotwins were bunched and initiated from the cell walls and not necessarily from the grain boundaries. Figure 4b shows a HR-STEM image of the nano-twin structure; the thickness of twins ranged from $2\\mathrm{nm}$ to $6\\mathrm{nm}$ in general. However as shown in Figure 4c, the stable twin can be as thin as two atomic layers, which supports the layer-by-layer growth mechanism of twins in this case, and it experimentally confirms the theoretical simulation which proposed that the minimum thickness of a stable twin in FCC structure is 2 atomic layers [39]. \n\n![](images/55ada9b2e8558d10e833be1321d4faa148a21c11b05646e3549c020d5ad13065.jpg) \nFIGURE 3 \n\nThose nano-twins should have significant influence on dislocation motion, resulting in stable plastic deformation by strain hardening through the dynamic Hall–Petch effect similar to that in nanotwined copper and TWIP steels [40,41]. \n\n# The mechanism of simultaneous improvements of strength and ductility \n\nCombining the multiscale mechanical property–structure characterizations and in-situ TEM testing, it is confirmed that the pre-existing dislocation network structure has significant contribution to the high strength and ductility of as-SLMed 316LSS. Firstly the pre-existing dislocation network impedes dislocation motion and thus increases dislocation storage resulting in the high yield strength. Secondly, with the increase in stress, the impeded dislocations are allowed to transmit through the dislocation walls; meanwhile the pinning effect from the segregated atoms effectively stabilizes the dislocation network to maintain its size during the entire plastic deformation, enabling the stable plastic flow. In addition, the misorientation between cells can also contribute to the stability of the dislocation network. The good stability of pre-existing dislocation network structure even at an ultra-high stress level in our as-SLMed 316LSS is crucial for the enhancement of ductility. \n\n![](images/52bd1a00578d5239219bdbfcf1ce1c060b470ad21b454e9c2aacd3e4f8d219a5.jpg) \nDislocations in SLMed 316LSS. (a) A high-angle annular dark field (HAADF)-STEM image of a partial dislocation pair within a cell in the as-SLMed sample. (b–d) High resolution annular dark field (ADF)-STEM images showing the stacking fault, trailing partial dislocation and leading partial dislocation in (a). (e) Screenshots from the Video 1 showing interaction between partial dislocations and dislocation cell walls. \nFIGURE 4 \nSTEM micrographs of the SLMed 316LSS after deformation. (a) High density of nano-twins in a BF-STEM image. The inset is the selected area electro diffraction pattern obtained from the left side of the sample in (a). (b and c) High resolution (HR)-STEM micrographs showing the atomic structures of th bunched nano-twins and twin boundary with a step. The twin and matrix are colorized into blue and yellow, respectively. \n\nIn general, the increase in ductility is achieved by delaying the onset of necking. The necking caused by plastic instability takes place when the Hart criterion is satisfied $\\begin{array}{r}{(\\frac{\\mathrm{d}\\sigma}{\\mathrm{d}\\varepsilon}+m\\cdot\\sigma\\leqslant\\sigma,}\\end{array}$ where $\\sigma$ is the true stress, e is the true strain and m is the strain rate sensitivity). So both the strain hardening $\\textstyle{\\bigl(}{\\frac{\\mathrm{d}\\sigma}{\\mathrm{d}\\varepsilon}}{\\bigr)}$ and strain rate hardening $(m\\cdot\\sigma)$ contribute to the delay of necking [42]. The evolution of strain hardening rate is the main reason for the high tensile elongation of SLMed 316LSS. The strain hardening rate of SLMed \n\n316LSS starts at a low value, but remains stable, and even gradually increases during the entire plastic deformation till failure. While the wrought-annealed 316LSS shows initially a high strain hardening rate,it shows a substantial decrease afterward (Figure 5c). The difference in the strain hardening rate is highly related to the distinct microstructural evolution processes in the two 316L stainless steels due to the different stability of the dislocation cellular structure. In SLMed $316\\mathrm{L}$ , the pre-existing dislocation network structure formed during manufacturing is pinned by the element segregation and the misorientation across the cell walls. The characteristic size of the dislocation network structure is retained even at the late stage of the plastic deformation when high flow stress is reached. The defects induced from the misorientation across the cell walls can also act as dislocation source. These enable continuous dislocation motion, nanotwin formation, and thus the stable plastic flow during the entire plastic deformation. Meanwhile the formation of nano-twins promoted by the dislocation network also contributes to the strain hardening through dynamic Hall–Petch effect to delay the necking. On the contrary, in wrought-annealed 316LSS, dislocation network structure forms during plastic deformation, which contributes to strain hardening rate in the beginning. However, the \n\n# FIGURE 5 \n\n![](images/ab01bc6571d0dd0398dbfeb72d6154992f356ca91e861add8a24eb699cce0da3.jpg) \n \nTensile properties of the SLMed 316LSS from the present work and the wrought-annealed 316LSS with an average grain size of $17.5\\upmu\\mathrm{m}$ from Ref. [22]. (a) Engineering tensile stress–strain curves. (b) True stress–strain curves. (c) Strain hardening rate curves. (d) Comparison of the strain hardening rate and true stress of both SLMed and wrought-annealed 316LSS. Bar specimens with gage diameter and length of $3\\mathsf{m m}$ and $12~\\mathsf{m m}$ were used for tensile test of SLMed samples. Plate specimens with gage dimensions of $12.5\\times57\\times0.75\\:\\mathrm{mm}$ were used in Ref. [22] for the tensile test of wrought-annealed samples. \n\n![](images/d52fc86375ce9c6bbf20fc5620dad1e9ce9584710929ccb1abe4f8337abdf7ad.jpg) \nFIGURE 6 \nifferent scanning speeds result in different sizes of the dislocation cells. (a–d) SEM images from the etched surfaces of the samples built with a lase canning speed of (a) $7000~\\mathrm{{mm/s};}$ (b), $4250\\ \\mathrm{mm}/\\mathsf{s};$ (c) $850~\\mathrm{mm}/s$ and (d) $283~\\mathrm{mm/s}$ . \n\ncells later shrink to small sizes and the dynamic recovery at cell boundaries leads to the decrease in work hardening rate [43,44]. Besides strain hardening, strain rate hardening also helps to stabilize the plastic deformation as a considerable amount of elongation is observed after flow stress outweighs the strain hardening rate in SLMed 316LSS (Figure 5d). The non-negligible strain rate hardening effect is presumably due to the reduced activation volume by the high density of dislocations at the cell wall and the formation of nanotwins [45,46]. \n\nImportantly the cell size and morphology of the dislocation network which are sensitive to the cooling rate and temperature gradient are also tunable by changing the cooling speed. As shown in Figure 6, the cell size of the dislocation network is effectively adjusted to be around $200\\mathrm{nm}$ , $250\\mathrm{nm}$ , $500\\mathrm{nm}$ and $1\\upmu\\mathrm{m}$ , respectively, using different scanning speeds (7000, 4250, 850 and $283\\mathrm{mm}/\\mathrm{s}$ ) to tune the cooling speed. It indicates that the mechanical properties of SLMed alloys can be designed purposefully based on their controllable microstructure–-property relationship. \n\n# Conclusions \n\nTo sum, besides the ability to produce complex-shaped parts, the AM processes also provide ultra-fast cooling rate during solidification, which results in a unique microstructure that consequently leads to outstanding mechanical properties in bulk metal parts that is not possible to be achieved by any other so far established manufacturing method. A systematic SEM and TEM work reveals that the dislocation network with the accompanying segregation of alloying elements acts as stable and “soft” barriers that hinder dislocation motion for strength, but meanwhile guarantee a continuous plastic flow by allowing dislocations from transmitting. This strategy to improve both the strength and ductility by introducing a dislocation network can be applied to other alloys with low-stacking fault energy. In addition, the mechanical properties can potentially be designed purposefully since its microstructure is directly tuneable by scanning parameters. This work paves the way for developing high-performance metals with desired mechanical properties by in-situ tailoring the microstructure during the manufacturing process, thus further boosting the AM as a disruptive technology to reshape manufacturing. \n\n# Author contributions \n\nZ.S., Q.Y. and L.L. designed the research; Y.Z. and L.L. fabricated the samples; Q.D. performed the in-situ TEM work and the data analysis; J.Z. and J.W. carried out the micropillar compression tests; L.L., Q.D., Q.Y., L.C and Z.S. wrote the manuscript; all the authors contributed to the discussions and commented the manuscript. \n\n# Competing financial interests statement \n\nThe authors declare no competing financial interests. \n\n# Acknowledgements \n\nThanks to Dr. Mirva Erikson and Jon Olsen for the proof reading. \n\nThis work is financially supported by Fusion for Energy (F4E) [F4E-GRT-516]; Chinese 1000-Youth-Talent Plan [Qian Yu]; 111 project [No.B16042]; National Natural Science Foundation of China [51671168]; and the State Key Program for Basic Research in China [No. 2015CB65930]. \n\n# References \n\n[1] W.F. Smith, J. Hashemi, Foundations of Materials Science and Engineering, McGraw-Hill, New York, 2005. \n[2] D. Hull, D.J. Bacon, Introduction to Dislocations, fourth ed., Elsevier, Amsterdam, 2001. \n[3] Q. Yu et al., Science 347 (2015) 635–639. \n[4] K. Lu, L. Lu, S. Suresh, Science 324 (2009) 349–652. \n[5] K. Kumar, H. Van Swygenhoven, S. Suresh, Acta Mater. 51 (2003) 5743–5774. \n[6] L. Lu et al., Science 304 (2004) 422–426. \n[7] Y. Wang et al., Nature 419 (2002) 912–915. \n[8] X. Wu et al., Proc. Natl. Acad. Sci. 112 (2015) 14501–14505. \n[9] S.H. Kim, H. Kim, N.J. Kim, Nature 518 (2015) 77–79. \n[10] B. Berman, Bus. Horiz. 55 (2012) 155–162. \n[11] D. Herzog et al., Acta Mater. 117 (2016) 371–392. \n[12] S.A. Khairallah et al., Acta Mater. 108 (2016) 36–45. \n[13] E.W. Collings et al., J. Mater. Sci. 25 (1990) 3677–3682. \n[14] D. Pavuna, J. Mater. Sci. 16 (1981) 2419–2433. \n[15] X.P. Li et al., Acta Mater. 95 (2015) 74–82. \n[16] B. Qian et al., Dent. Mater. 31 (2015) 1435–1444. \n[17] G.A. Ravi, C. Qiu, M.M. Attallah, Mater. Lett. 179 (2016) 104–108. \n[18] L. Thijs et al., Acta Mater. 58 (2010) 3303–3312. \n[19] B. Vrancken et al., Acta Mater. 68 (2014) 150–158. \n[20] J. Wu et al., Acta Mater. 117 (2016) 311–320. \n[21] Y. Zhong, L. Liu, et al., J. Nucl. Mater. 470 (2016) 170–178. [22] W.A. Poling, Grain Size Effects in Micro-Tensile Testing of Austenitic Stainless Steel (MS thesis), Colorado School of Mines, 2012. \n[23] X.H. Chen et al., Scr. Mater. 52 (2005) 1039–1044. \n[24] S. Maloy et al., J. Nucl. Mater. 296 (2001) 119–128. \n[25] F.K. Yan et al., Acta Mater. 60 (2012) 1059–1071. \n[26] A.M. Brass, J. Chêne, Corros. Sci. 48 (2006) 3222–3242. \n[27] V. Ganesan, M.D. Mathew, K.B. Sankara Rao, Mater. Sci. Technol. 25 (2009) 614–618. \n[28] G.S. Langdon, G.K. Schleyer, J. Strain Anal. 39 (2015) 71–86. \n[29] H.D. Carlton et al., Mater. Sci. Eng. A 651 (2016) 406–414. \n[30] A. Riemer et al., Eng. Fract. Mech. 120 (2014) 15–25. \n[31] X. Song et al., Int. J. Mater. Form. 8 (2015) 245–254. \n[32] M. Shiomi et al., CIRP Ann. 53 (2004) 195–198. \n[33] I.A. Roberts, Investigation of Residual Stresses in the Laser Melting of Metal Powders in Additive Layer Manufacturing (Ph.D. thesis), University of Wolverhampton, 2012. \n[34] V. Shankar et al., Mater. Sci. Eng. A 343 (2003) 170–181. \n[35] S. Kou, Welding Metallurgy, John Wiley & Sons, New Jersey, 2003. \n[36] E. Kannatey-Asibu, Principles of Laser Materials Processing, John Wiley & Sons, New Jersey, 2009. \n[37] M. Nabil Bassim, R.J. Klassen, Mater. Sci. Eng. 81 (1986) 163–167. \n[38] D. Kuhlmann-Wilsdorf, Mater. Sci. Eng. A 113 (1989) 1–41. \n[39] S. Ogata, J. Li, S. Yip, Phys. Rev. B 71 (2005) 224102. \n[40] L. Lu et al., Science 323 (2009) 607–610. \n[41] Z. Li et al., Nature 534 (2016) 227–230. \n[42] E.W. Hart, Acta Metall. 15 (1967) 351–355. \n[43] R.N. Gardner, T.C. Pollock, H.G.F. Wilsdorf, Mater. Sci. Eng. 29 (1977) 169–174. \n[44] X. Feaugas, Acta Mater. 47 (1999) 3617–3632. \n[45] Y.M. Wang, A.V. Hamza, E. Ma, Acta Mater. 54 (2006) 2715–2726. \n[46] L. Lu et al., Acta Mater. 53 (2005) 2169–2179. " + }, + { + "id": "10.1038_s41467-018-05341-y", + "DOI": "10.1038/s41467-018-05341-y", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-05341-y", + "Relative Dir Path": "mds/10.1038_s41467-018-05341-y", + "Article Title": "Atomic-level insight into super-efficient electrocatalytic oxygen evolution on iron and vanadium co-doped nickel (oxy)hydroxide", + "Authors": "Jiang, J; Sun, FF; Zhou, S; Hu, W; Zhang, H; Dong, JC; Jiang, Z; Zhao, JJ; Li, JF; Yan, WS; Wang, M", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "It is of great importance to understand the origin of high oxygen-evolving activity of state-of the-art multimetal oxides/(oxy)hydroxides at atomic level. Herein we report an evident improvement of oxygen evolution reaction activity via incorporating iron and vanadium into nickel hydroxide lattices. X-ray photoelectron/absorption spectroscopies reveal the synergistic interaction between iron/vanadium dopants and nickel in the host matrix, which subtly modulates local coordination environments and electronic structures of the iron/vanadium/nickel cations. Further, in-situ X-ray absorption spectroscopic analyses manifest contraction of metal-oxygen bond lengths in the activated catalyst, with a short vanadium-oxygen bond distance. Density functional theory calculations indicate that the vanadium site of the iron/ vanadium co-doped nickel (oxy)hydroxide gives near-optimal binding energies of oxygen evolution reaction intermediates and has lower overpotential compared with nickel and iron sites. These findings suggest that the doped vanadium with distorted geometric and disturbed electronic structures makes crucial contribution to high activity of the trimetallic catalyst.", + "Times Cited, WoS Core": 798, + "Times Cited, All Databases": 816, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000439426100012", + "Markdown": "# Atomic-level insight into super-efficient electrocatalytic oxygen evolution on iron and vanadium co-doped nickel (oxy)hydroxide \n\nJian Jiang1, Fanfei Sun2, Si Zhou3, Wei Hu4, Hao Zhang2, Jinchao Dong5, Zheng Jiang $\\textcircled{1}$ 2, Jijun Zhao3, Jianfeng Li $\\textcircled{1}$ 5, Wensheng Yan4 & Mei Wang1 \n\nIt is of great importance to understand the origin of high oxygen-evolving activity of state-ofthe-art multimetal oxides/(oxy)hydroxides at atomic level. Herein we report an evident improvement of oxygen evolution reaction activity via incorporating iron and vanadium into nickel hydroxide lattices. X-ray photoelectron/absorption spectroscopies reveal the synergistic interaction between iron/vanadium dopants and nickel in the host matrix, which subtly modulates local coordination environments and electronic structures of the iron/vanadium/ nickel cations. Further, in-situ X-ray absorption spectroscopic analyses manifest contraction of metal–oxygen bond lengths in the activated catalyst, with a short vanadium–oxygen bond distance. Density functional theory calculations indicate that the vanadium site of the iron/ vanadium co-doped nickel (oxy)hydroxide gives near-optimal binding energies of oxygen evolution reaction intermediates and has lower overpotential compared with nickel and iron sites. These findings suggest that the doped vanadium with distorted geometric and disturbed electronic structures makes crucial contribution to high activity of the trimetallic catalyst. \n\nHiyderaolgaelntearsnatniventeorgtyh-edelinsmeitaenddfocsasriblofnu-enlseutto aslufsutaeilni tahne Water splitting to hydrogen and oxygen $\\mathrm{(H}_{2}\\mathrm{{O}}\\rightarrow\\mathrm{H}_{2}+1/2\\mathrm{{O}}_{2})$ , driven by electric power generated from renewable energy sources, is known as a promising approach to hydrogen production in a large-scale1,2. To this end, one of the crucial challenges is to develop inexpensive electrocatalysts that are highly active and durable for water oxidation and proton reduction. \n\nAmong the reported non-noble metal catalysts for oxygen evolution reaction (OER), Ni-based bimetal oxides3–8, especially NiFe layered-double-hydroxides (LDHs) (refs. 9–16), have drawn intensive attention due to their excellent OER performance in alkaline media. Much recent research revealed that the incorporation of a third transition metal into NiFe oxides/hydroxides to form NiFeM $\\mathbf{\\DeltaM=Co}$ (refs. 17‒19), Mn (ref. 20), $\\mathrm{Cr}$ (refs. 21,22), and Al (refs. 23,24)) ternary composites could further enhance the intrinsic OER activity of the Ni–Fe (oxy)hydroxide catalyst in different extents25. In another aspect, the unary vanadium (oxy) hydroxide was demonstrated to be a highly active OER electrocatalyst in alkaline solution26. Some very recent studies discovered that incorporation of V into Ni- or/and Fe-based oxides/ (oxy)hydroxides could effectively enhance the OER activity of the catalysts27–30. However, the questions remain on whether V has substitutionally doped into the lattices of host materials and if so, how V dopant interplays with other metal ions co-existing in a catalyst material, and how the doped V cations contribute to the high OER activity of the host materials. To our knowledge, to date, there is no report on in-depth spectroscopic studies of local coordination environments and electronic structures for the Vcontaining bi- and trimetal (oxy)hydroxide OER catalysts in both rest and activated states. In very recent years, several groups made in-depth studies on NiFe (refs. 10,14,31‒34), CoFe (ref. 35), NiFeCo (ref. 36), FeCoW (ref. 37), and NiFeCoCe (ref. 38) oxides/(oxy) hydroxides by employing X-ray absorption spectroscopy (XAS), especially operando XAS measured during electrolysis of a catalyst at a preset applied potential. The results obtained from these significant studies provided some crucial information for understanding the origin of high activity of these catalysts and for identifying the authentic active sites in the catalysts. \n\nIn light of the reports mentioned above, we prepared a series of $\\mathrm{Fe/V}$ co-doped, Fe- or V-doped, and pure Ni (oxy)hydroxides as ultrathin nanosheets (NSs) on hydrophilic carbon fiber paper (CFP), and made comparative studies on these OER catalysts by X-ray photoelectron spectroscopy (XPS) and ex-situ/in-situ XAS, combined with density functional theory (DFT) calculations. The Fourier and wavelet transform (FT/WT) analyses of the extended X-ray absorption fine structure (EXAFS) data demonstrate the substitutional occupation sites of Fe and V dopants in $\\mathrm{Ni(OH)}_{2}$ lattices, consistent with the results obtained from theoretical calculations. Moreover, XPS and XAS analyses reveal the synergetic interaction of Fe, V, and Ni cations in the $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ catalyst, which subtly modulates local coordination environments and electronic structures of $_{\\mathrm{Ni/Fe/V}}$ cations in the catalyst. Further in-situ XAS studies manifest a different extent of shrinkage of metal–oxygen bond lengths in the activated catalyst, with a short V–O1 bond distance of $1.65\\mathring{\\mathrm{A}}$ . DFT calculations indicate that the $\\mathrm{\\DeltaV}$ site of the $\\mathrm{Fe/V}$ co-doped Ni (oxy)hydroxide gives near-optimal binding energies (BEs) of OER intermediates, and point to the higher OER activity of $\\mathrm{v}$ site compared to that of Ni and Fe sites. \n\n# Results \n\nFabrication and characterization of $\\mathbf{Ni}_{3}\\mathbf{Fe}_{1-x}\\mathbf{V}_{x}$ . A series of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x}$ (oxy)hydroxide catalysts $\\begin{array}{r}{0\\leq x\\leq1,}\\end{array}$ ), namely ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ , $\\mathrm{Ni}_{3}\\mathrm{V}$ , $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.67}\\mathrm{V}_{0.33}$ , $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}.$ $\\mathrm{Ni_{3}F e_{0.33}V_{0.67}}$ , and pure Ni (oxy)hydroxides were directly grown on hydrophilic CFPs by hydrothermal synthesis (Fig. 1 and Supplementary Fig. 1). The atomic ratios of different metals in the as-prepared catalysts were determined by analyses of inductively coupled plasma optical emission spectroscopy (ICP-OES, Supplementary Table 1). \n\nThe powder $\\mathrm{\\DeltaX}$ -ray diffraction (PXRD) patterns (Supplementary Fig. 2) indicate that $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x}$ are isostructural to $\\alpha$ -Ni $(\\mathrm{OH})_{2}$ (JCPDS Card No. 38-0715). The reflections at $2\\theta=11.4^{\\circ}$ and $22.7^{\\circ}$ , corresponding to the (003) and (006) lattice planes of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x},$ slightly shift to larger $2\\theta$ values by $0.2^{\\circ}$ and $0.6^{\\circ}$ , respectively, relative to those of $\\bar{\\alpha}{\\cdot}\\mathrm{Ni}(\\mathrm{OH})_{2}$ . The $d$ -spacing values obtained from the (003) and (006) reflections are about 7.65 and $3.81\\mathrm{\\AA}$ , respectively, with a small contraction compared to those for pure $\\bar{\\alpha}{\\cdot}\\mathrm{Ni}(\\mathrm{OH})_{2}$ $\\langle d(003)=7.79\\mathrm{~\\AA~}$ and $d(\\hat{0}06)=3.91\\ \\mathring{\\mathrm{A}}$ , which is most possibly caused by the substitution of Fe and $\\mathrm{\\DeltaV}$ atoms for $\\mathrm{\\DeltaNi}$ in the lattice sites of the $\\mathrm{Ni(OH)}_{2}$ matrix32,39,40. Because no extra diffraction peaks are observed in the PXRD pattern, it could be deduced that no separated crystalline phases, such as unary Ni-, Fe-, or V-based oxides/(oxy)hydroxides, are formed during the doping process12,28,41. \n\nScanning electron microscopic (SEM) images of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}/$ CFP (Fig. 2a) clearly show that the entire surface of each carbon fiber is uniformly coated with the densely interlaced NSs, forming a sharp contrast to the smooth surface of pristine carbon fibers (Supplementary Fig. 3). A close inspection (Fig. 2b) reveals that the interlaced NSs form a porous network structure. Such an open nanoarchitecture built by $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ ultrathin NSs would afford a mass of electrochemically active sites, an easy penetration of electrolyte, and a good mechanical strength, so as to improve the OER activity and stability of the electrodes4. The quantitative SEM energy dispersive X-ray spectrum (SEM-EDX) of $\\mathrm{Ni_{3}F e_{0.5}V_{0.5}/C F P}$ discloses the presence of Ni, Fe, V, and O elements with a $_{\\mathrm{Ni/Fe/V}}$ atomic ratio of 74.12:12.83:13.05, which is close to the stoichiometric metal ratio of $\\mathrm{Ni}/\\mathrm{Fe}/\\mathrm{V}=3{:}0.5{:}0.5$ . Moreover, the corresponding elemental mappings (Supplementary Fig. 4) illustrate that the Ni, Fe, V, and O elements distribute homogenously on the surface of carbon fibers. \n\nThe bright-field TEM (BF-TEM) image (Fig. 2c) of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ NSs illustrates a rippled sheet structure with a dimension around $500\\mathrm{nm}.$ and the lateral TEM image (Fig. 2d) shows the ultrathin $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ NSs with the thickness of $2.7{-}4.2\\:\\mathrm{nm}$ . Furthermore, the atomic-resolution BF-TEM image (Fig. 2e) displays clear lattice fringes with an interplanar spacing of $2.67\\mathring\\mathrm{A}$ , indexed to the (101) plane of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{\\bar{V}}_{0.5}$ NSs. The interplanar spacing of lattice fringes is slightly smaller than that of $\\partial\\mathrm{-Ni(OH)_{2}^{-}}$ $(2.6\\overset{\\smile}{8}\\mathring{\\mathrm{A}})$ due to the doping of Fe and $\\mathrm{\\DeltaV}$ for Ni in $\\mathrm{Ni(OH)}_{2}$ lattices. Single atoms, clusters, and small particles of Fe and $\\mathrm{v}$ species are not observed in aberration-corrected high-angle annular dark-field scanning TEM (HAADF-STEM) images of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ NSs (Supplementary Fig. 5). Meanwhile, both the EDX elemental mappings and linear scanning analysis of the HAADF-STEM image of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ NSs with sub-nanometer resolution (Fig. 2f and Supplementary Fig. 6) provide direct-viewing evidence for the uniform distribution of Ni, Fe, V, and O elements in the asprepared NSs. \n\nIn order to clarify the occupation sites of Fe and V dopants in $\\mathrm{Ni}(\\mathrm{OH})_{2}$ lattices, we display in Fig. 3 the FT curves of the Fe and V $K$ -edge EXAFS $k^{2}\\dot{\\chi}(k\\dot{)}$ functions for ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}_{\\mathrm{:}}$ , $\\mathrm{Ni}_{3}\\mathrm{V}$ , and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . As references, their Ni $K$ -edge FT curves are also plotted (Fig. 3a). The FT curves of the Fe $K\\cdot$ -edge data of ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ exhibit two prominent coordination peaks at 1.5 and $2.7\\mathring\\mathrm{A}$ that are identical to those of their Ni $K$ -edge data (Fig. 3b), suggesting the substitutional doping of Fe in the Ni $(\\mathrm{OH})_{2}$ host. Similarly, the FT curves of $\\mathrm{Ni}_{3}\\mathrm{V}$ and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ each display a prominent $_{\\mathrm{V-O}}$ peak at $1.4\\mathring\\mathrm{A}$ and a $_{\\mathrm{V-M}}$ ( $\\mathbf{\\dot{M}}=\\mathbf{Fe}$ , $\\mathrm{Ni},$ or V) peak at about $2.8\\mathring\\mathrm{A}$ (Fig. 3c), and the high-shell peak of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ is weaker than that of $\\mathrm{Ni}_{3}\\mathrm{V}$ . The significant decrease in the intensity of the $_{\\mathrm{V-M}}$ coordination peak in the FT curve of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ is most likely caused by the highly distorted local structure of $\\mathrm{\\DeltaV}$ substituting for the site of Ni. To confirm the substitution of $\\mathrm{\\DeltaV}$ for $\\mathrm{\\DeltaNi}$ in $\\mathrm{Ni(OH)}_{2}$ lattices, the WT analysis of the V $K\\mathbf{\\cdot}$ -edge data was performed. A maximum at the cross point of $R=2.8\\AA$ and $k=7.8\\mathring{\\mathrm{A}}^{-1}$ appears in the EXAFS WT map at the V $K$ -edge for $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ (Supplementary Fig. 7), just like that for $\\mathrm{Ni}_{3}\\mathrm{V}$ . This implies the presence of V–Fe/Ni scatterings at a distance of around $2.8\\mathring\\mathrm{A}$ surrounding $\\mathrm{\\DeltaV}$ atoms and affords direct evidence for the substitution of $\\mathrm{v}$ atoms for the Ni sites in $\\mathrm{Ni(OH)}_{2}$ lattices. We also made the calculation of the EXAFS spectra by assuming $\\mathrm{\\DeltaV}$ adsorption on the Ni–Fe LDH layer or occupying the interstitial position. It turns out that in both cases the calculated spectra are quite different from the experimental V $K\\cdot$ -edge EXAFS spectra of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ (Supplementary Fig. 8). Furthermore, DFT calculations suggest that $\\mathrm{\\DeltaV}$ atoms initially placed on the top site of surface Ni or $\\mathrm{~o~}$ atoms are relaxed to the interstitial between two LDH layers after structure optimization. The LDH structure with interstitial doping is noticeably buckled, with formation energy of $-3.73\\mathrm{eV}$ per $\\mathrm{v}$ atom, less stable with regard to LDH with substitutional doping $(-5.07\\mathrm{eV}$ per $\\mathrm{v}$ atom) (Supplementary Figs. 9, 10), supporting that $\\mathrm{\\DeltaV}$ atoms occupy Ni positions in $\\mathrm{Ni(OH)}_{2}$ lattices rather than the interstitial or top positions of LDH layers. On the other side, from Supplementary Fig. 11, the nearest-neighbor FT peak position of V is shifted to the lower- $R$ side and the second coordination peak to higher- $R$ side with apparently reduced intensity as compared to that of Fe. This implies the remarkable different local environment of the substitutional $\\mathrm{\\DeltaV}$ from that of Fe in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . The quantitative parameters extracted from EXAFS curve-fitting (Supplementary Figs. 12‒14 and Supplementary Tables 2‒4) further show that the bond length of $\\bar{\\mathrm{V-O}}$ (1.72 Å) is significantly contracted with regard to those of Fe–O $(2.00\\mathring\\mathrm{A})$ and Ni–O $(\\Dot{2}.03\\mathring\\mathrm{A})$ . \n\n![](images/02d909f97132c1222298860f2b92ca5002f4cade0c20e0f75c61f9c4d8bbc5e9.jpg) \nFig. 1 Fabrication of ${\\sf N i}_{3}\\sf Y e_{1-x}\\sf V_{x}/C F P$ $\\mathsf{O}_{2}$ -evolving electrodes. Schematic illustration of the fabrication procedure by directly growing $\\mathsf{N i}_{3}\\mathsf{F e}_{1-x}\\mathsf{V}_{x}$ NSs on pretreated CFP substrate \n\n![](images/a38bc29a21faa62e8e4ce2286c4563e50fdd9fd4313f79df6bbc6f906c83008a.jpg) \nFig. 2 Microscopy measurements of $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ NSs. a, b Top-view SEM images of the carbon fiber coated with $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ NSs with low (a) and high (b) magnification. Scale bars, $1\\upmu\\mathrm{m}$ in a and $100\\mathsf{n m}$ in b. The inset in a shows the hierarchically structured 3D integrated electrode. Scale bar in the inset in a, 5 $\\upmu\\mathrm{m}$ . c, d TEM images of $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ NSs scratched off from the as-prepared CFP electrode. Scale bars, $100\\mathsf{n m}$ in c and $40\\mathsf{n m}$ in d.e Atomic-resolution BFTEM image of $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ NSs. Scale bar, 1 nm. f Aberration-corrected HAADF-STEM image of $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ NSs, the corresponding EDX elemental mappings of Ni, Fe, $\\mathsf{V},$ O and the mixed elemental mapping of Ni, Fe, V, and O. Scale bar, $2{\\mathsf{n m}}$ \n\n![](images/c333086e5a4985d7c416679515dba7bff35f1eed7d1fd9250a8e9d6b12de9bde.jpg) \nFig. $3\\times A S$ spectra of the as-prepared Ni-based (oxy)hydroxide catalysts. FT curves of a Ni $K$ -edge, b Fe $K$ -edge, and c V $K$ -edge EXAFS $k^{2}\\chi(k)$ functions \n\nUnderstanding the electronic interaction in $\\mathbf{Ni}_{3}\\mathbf{Fe}_{1-x}\\mathbf{V}_{x}$ . The electronic states of Fe and $\\mathrm{\\DeltaV}$ in catalysts were investigated by exsitu hard X-ray absorption near-edge spectroscopy (XANES). Generally, in XANES spectra the intensity of the pre-edge peak depends predominantly on central site symmetry, while the absorption edge position is correlated to the oxidation state of central sites42. The absorption edges of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{\\mathrm{:}}$ , $\\mathrm{Ni}_{3}\\mathrm{V}_{\\mathrm{:}}$ and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ in the XANES curves of Ni $K$ -edge (Supplementary Fig. 15a) are all alike to that of the original $\\mathrm{Ni(OH)}_{2}$ , indicative of nearly identical average oxidation states of $\\mathrm{Ni}$ in the catalysts. Similarly, the XANES curves of Fe $K\\mathrm{\\Omega}$ -edge in Supplementary Fig. 15b show that the adsorption edges of Fe for ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ , $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5},$ and ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ reference are almost overlapped, manifesting that the average valence states of Fe are close to $+3$ in the as-prepared catalysts. Importantly, the V $K$ -edge XANES spectra of $\\mathrm{Ni}_{3}\\mathrm{V}$ and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ exhibit intense pre-edge peaks (Supplementary Fig. 15c), indicating the distorted coordination environment around $\\mathrm{\\DeltaV}$ atoms in these materials42. More interestingly, $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ shows a higher pre-edge peak than that of $\\mathrm{Ni}_{3}\\mathrm{V}$ in the V $K\\mathrm{\\Omega}$ -edge XANES, implying a higher degree of octahedral geometry distortion at the $\\mathrm{\\DeltaV}$ sites in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ compared to those in $\\mathrm{Ni}_{3}\\mathrm{V}$ . Additionally, the $K$ -edge absorption positions of $\\mathrm{Ni}_{3}\\mathrm{V}$ and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ are more close to those of $\\mathrm{VO}_{2}$ and $\\mathrm{V}_{2}\\mathrm{O}_{5}$ than to that of $\\mathrm{V}_{2}\\mathrm{O}_{3}$ (inset of Supplementary Fig. 15c), suggesting that the majority of $\\mathrm{v}$ ions are in the formal valences of $+4$ and $+5$ in both catalysts. \n\nThe as-prepared $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{\\dot{V}}_{x}$ films were further studied by XPS and ex-situ soft XAS to gain an insight into the electronic interaction between $\\mathrm{Fe/V}$ dopants and Ni atoms at the surface of catalysts. For $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ NSs, the Ni $2p$ spectrum (Fig. 4a) exhibits two fitting peaks at 872.3 and $854.4\\mathrm{eV}$ along with two shakeup satellites at 878.4 and $860.1\\mathrm{eV}$ , which are characteristic spin-orbit peaks of $\\mathrm{Ni}^{2+}$ (refs. 13,28,43). In the Fe $2p$ region (Fig. 4b), Fe $2p_{1/2}$ and Fe $2p_{3/2}$ peaks arise at 724.8 and $711.5\\mathrm{eV}$ , indicative of Fe in the $+3$ oxidation state (refs. 16,29). The $\\mathrm{~V~}2p_{3/2}$ peak (Fig. 4c) can be deconvoluted into three peaks located at $\\bar{5}16.2\\mathrm{eV}\\mathrm{~(V}^{5+})$ , $515.1\\mathrm{eV}$ $\\mathrm{(V^{4+})}$ , and $514.4\\mathrm{eV}$ $(\\mathrm{V}^{3+})$ (refs. 26,28,29), demonstrating that the $\\mathrm{v}$ atoms are predominantly in high oxidation states ( $_{+4}$ and $+5$ in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5},$ together with a minority of $\\mathrm{V}^{3+}$ , which is consistent with the results obtained from V $K$ -edge XANES spectra. \n\nIt is worthy of note that the Ni $2p$ BEs for the Fe or/and V doped binary and ternary materials are shifted apparently to higher BEs compared to those of pure Ni (oxy)hydroxide, with the shift extent in an increasing order of $\\mathrm{Ni}_{3}\\mathrm{Fe}<\\mathrm{Ni}_{3}\\mathrm{V}<$ $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ (Fig. 4a, Supplementary Fig. 16a, and Supplementary Table 5). In contrast, the V $2p$ peaks for $\\mathrm{Ni}_{3}\\mathrm{V}$ are shifted to lower BEs relative to the corresponding peaks for $\\mathrm{VO}_{2}$ (ref. 44), and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ displays V $2p_{3/2}$ peaks at BEs ${\\sim}0.2\\mathrm{eV}$ lower than those of $\\mathrm{Ni}_{3}\\mathrm{V}$ (Fig. 4c and Supplementary Fig. 16c). Of particular interest is that the BEs of Fe $2{p}_{1/2}$ and $2p_{3/2}$ for ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ are lower than those for $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ (ref. 45), but when half amount of Fe in ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ is replaced by V, $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ exhibits Fe $2p$ peaks at BEs not only considerably higher than those of ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ but also higher than ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ (Fig. 4b and Supplementary Fig. 16b), implying that the Fe dopant acts as an electron accepting site in $\\mathrm{Ni}_{3}\\mathrm{Fe}$ but an electron donating site in an integrated effect when V is co-doped with Fe into $\\mathrm{Ni(OH)}_{2}$ lattices. These observations suggest the partial electron transfer from Ni to Fe or $\\mathrm{\\DeltaV}$ in the bimetal (oxy) hydroxides through oxygen bridges $(\\mathrm{O}^{2-})$ between metal ions, and from Ni and Fe to $\\mathrm{\\DeltaV}$ in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5},$ which is in good agreement with the calculated Mulliken charges for V, Fe, and Ni ions in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x}$ (Supplementary Table 6). \n\nThese speculations are further supported by the Ni, Fe, and V $L$ -edge XANES spectra shown in Fig. 4d‒f. Figure 4d illustrates that doping Fe or $\\mathrm{\\DeltaV}$ could intensify the Ni $L_{3}$ -edge peak (852.5 $\\mathrm{eV},$ , indicative of partial electron transfer from Ni to the substitutional Fe or V. The intensity of the Fe $L_{3}$ -edge peak at $709.8\\mathrm{eV}$ for ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ is also enhanced when $\\mathrm{\\DeltaV}$ is doped into ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ (Fig. 4e). On the contrary, the $\\mathrm{v}$ $L_{3}$ -edge peak $(518.3\\mathrm{eV})$ of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ is considerably weakened and shows a red-shift, as compared with that of $\\mathrm{Ni}_{3}\\mathrm{\\dot{V}}$ (Fig. 4f). The comparative analyses of XPS and XANES spectra suggest that co-doping of Fe together with $\\mathrm{\\DeltaV}$ into $\\mathrm{Ni(OH)}_{2}$ lattices results in more electron transfer to the $\\mathrm{\\DeltaV}$ in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ compared to that in $\\mathrm{Ni}_{3}\\mathrm{V}$ (Fig. 4c, f and Supplementary Fig. 16c). The strong interaction among these $3d$ metal ions results in synergistic modulation of the electronic structure of the metal centers of $\\mathrm{Fe/V}$ co-doped $\\mathrm{Ni(OH)}_{2}$ (refs. 12,22,36,43), and the concerted effect of Ni, Fe, and V metals with different energy levels of $d$ -band centers could make crucial contribution to the evident enhancement of OER activity of hybridized materials. Moreover, we calculated the branching ratio, ${L_{3}}/({L_{2}}+{L_{3}})$ , at the Fe $L$ -edges of ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5};$ which is approximately 0.74, implying the high-spin of $\\mathrm{Fe}^{3+}$ (ref. 46). And we also calculated the Fe $\\mathbf{{{L}}}_{2,3}$ -edge XAS for the high-spin and low-spin models of $\\mathrm{Fe}^{3+}$ (Supplementary Note 1 and Supplementary Methods). Obviously, the calculated highspin $L_{2,3}$ -edge XAS could well produce the experimental data (Supplementary Fig. 17), affording more evidence for the highspin configuration of $\\mathrm{Fe}^{3+}$ substituting the Ni sites. Thus, the valence electronic configurations of $\\mathrm{Ni}^{2\\bar{+}}$ , $\\mathrm{Fe}^{3+}$ , $\\mathrm{V}^{4+}$ , and $\\mathrm{V}^{5+}$ are $3d^{8}$ $(t_{2\\mathrm{g}}{}^{6}e_{\\mathrm{g}}{}^{2})$ , $3d^{5}$ $(t_{2\\mathrm{g}}^{3}e_{\\mathrm{g}}^{\\ 2})$ , $3d^{1}$ $(t_{2\\mathrm{g}}{}^{1}e_{\\mathrm{g}}{}^{0})$ , and $3d^{0}$ $(t_{2\\mathrm{g}}{}^{0}e_{\\mathrm{g}}{}^{0})$ respectively, which are adopted in the following analysis of valence electron structures of metal ions in ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ , $\\mathrm{Ni}_{3}\\mathrm{V}$ , and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . \n\nThe synergistically electronic interplay of Ni, Fe, and $\\mathrm{v}$ cations in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ is well explained in light of the analysis of valence electron structures of metal ions. In term of the result obtained from DFT calculations that the $(\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5})$ -OOH models with some aggregated Fe and $\\mathrm{\\DeltaV}$ atoms have lower formation energy and higher OER activity than the models with isolated Fe and V atoms (vide infra), a Ni–O–Fe–O–V–O–Ni unit (Fig. 4g) is used to analyze the electronic interaction of $\\mathrm{\\DeltaNi,}$ Fe, and $\\mathrm{\\DeltaV}$ cations in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . For ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ , the three unpaired electrons in the $\\pi$ -symmetry $(t_{2\\mathrm{g}})$ $d$ -orbitals of $\\mathrm{Fe}^{3+}$ interplay with the bridging $\\mathrm{O}^{2-}$ via $\\pi$ -donation, while the dominant interaction between the fully occupied $\\pi$ -symmetry $(t_{2\\mathrm{g}})$ $d.$ -orbitals of $\\mathrm{Ni}^{2+}$ and the bridging $\\mathrm{O}^{2-}$ is electron–electron repulsion, leading to partial electron transfer from $\\mathrm{Ni}^{2+}$ to $\\mathrm{Fe}^{3+}$ (refs. $^{12,40})$ . The partial electron transfer from $\\pi$ -symmetry lone pairs of the bridging $\\mathrm{O}^{2-}$ to $\\mathrm{V}^{4+}$ and $\\mathrm{V}^{5+}$ in $\\mathrm{Ni}_{3}\\mathrm{V}$ should be stronger than that from the bridging $\\mathrm{O}^{2-}$ to $\\mathrm{Fe}^{3+}$ in ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ , as $\\mathrm{V}^{4+}$ and $\\mathrm{V}^{5+}$ have rather low $t_{2\\mathrm{g}}$ occupancy while $\\mathrm{Fe}^{3+}$ has a half $t_{2\\mathrm{g}}$ occupancy. As for the Fe/V co-doped $\\mathrm{Ni(OH)}_{2}$ with some of the $\\mathrm{\\DeltaV}$ and Fe atoms aggregated in the host lattices, when $\\mathrm{Fe}^{3+}$ accepts partial electrons from $\\mathrm{Ni}^{2+}$ through the bridging $\\mathrm{O}^{2-}$ via $\\pi$ -donation as exampled by the NiFe (oxy)hydroxide reference, the electron-riched $t_{2\\mathrm{g}}$ $d$ -orbitals of $\\mathrm{Fe}^{3+}$ could relay electrons to the strongly electron-deficient $t_{2\\mathrm{g}}$ $d.$ -orbitals of $\\dot{\\mathrm{V}}^{4+}$ and $\\mathrm{V}^{5+}$ through the bridging $\\mathrm{O}^{2-}$ ions between them, which leads to better delocalization of the $\\pi$ -symmetry electrons among $\\mathrm{Ni,}$ Fe, and $\\mathrm{\\DeltaV}$ in the host matrix. This argument is in good agreement with the XPS and soft XANES results. In $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x},$ the $\\mathrm{Fe}^{3+}$ and $\\mathrm{Ni}^{2+}$ with half-full $e_{\\mathrm{g}}$ orbitals would have very weak bonding with adsorbed oxygen species, whereas the $\\mathrm{V}^{4+}$ and $\\mathrm{V}^{5+}$ with $e_{\\mathrm{g}}^{\\mathrm{~\\widetilde{0}~}}$ orbitals would form too strong bonding with adsorbed oxygen species. To get high OER activity, the bonding strength between transition metal and adsorbed oxygen species should be optimized to fulfill the Sabatier principle47. With increase of the electron density on V by partial electron transfer from Fe and $\\mathrm{\\DeltaNi}$ to $\\mathrm{v}$ through the bridging $\\mathrm{O}^{2-}$ ions, the high valence states of V could be stabilized under OER conditions, and more importantly, the strong bond strength between $\\mathrm{\\DeltaV}$ and adsorbed oxygen species could be tuned to a moderate bond strength, which would benefit for releasing $\\mathrm{O}_{2}$ from the $\\mathrm{\\DeltaV}$ site in OER. \n\n![](images/588a4608f811a18449ac1a4dfde54b08c03f21181141d91e576229828a4c14b9.jpg) \nFig. 4 High-resolution XPS and XANES spectra of the as-prepared Ni-based (oxy)hydroxide catalysts. XP spectra of a Ni $2p$ for $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5},$ $N i_{3}F e$ , $N i_{3}V,$ and pure Ni (oxy)hydroxides, b Fe $2p$ for ${\\sf N i}_{3}\\sf{F e}$ and $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5},$ and c V $2p$ for $N i_{3}V$ and $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ (the dashed lines shown in $a-c$ indicate the shifts of BEs of $3d$ metal ions caused by the hybridization of Fe or/and V dopants). d–f Ni, Fe, and V L-edge XANES spectra. g Schematic representations of the electronic coupling among Ni, Fe, and $\\vee$ in Ni3Fe, $N i_{3}V,$ and Ni3Fe0.5V0.5 \n\nEvaluating the electrochemical OER performance of $\\mathbf{Ni}_{3}\\mathbf{Fe}_{1-x}\\mathbf{V}_{x}$ . The electrocatalytic OER performance of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1}$ $_{-x}\\mathrm{V}_{x}/\\mathrm{CFP}$ were studied in $\\mathrm{O}_{2}$ -saturated 1 M KOH. The linear sweep voltammograms (LSVs, Fig. 5a) of all as-prepared Ni-based (oxy)hydroxide catalysts show the $\\mathrm{Ni}^{2+}/\\mathrm{Ni}^{3+}$ oxidation in the potential range of $1.3\\dot{3}\\substack{-1.42\\mathrm{V}}$ (all potentials are versus reversible hydrogen electrode $(\\mathrm{RHE}))^{5,7,43}$ . \n\n![](images/f4e4e8b68be936b4366592e6660efcba33cee962d73e5b27beb4bfedbb4661b1.jpg) \nFig. 5 Electrochemical tests for OER and Nyquist plots of the Ni-based (oxy)hydroxide catalysts. a LSV curves of $\\mathsf{N i}_{3}\\mathsf{F e}_{1-x}\\mathsf{V}_{x}$ and pure Ni (oxy) hydroxide catalysts on CFP, as well as bare CFP in $\\mathsf{O}_{2}$ -saturated $1M\\mathsf{K O H}$ at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . b Tafel plots derived from the polarization curves in a. c Chronopotentiometric curves obtained with $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ at constant current densities of 10 and $100\\mathsf{m A c m}^{-2}$ . d Nyquist plots of $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5},\\mathsf{N i}_{3}\\mathsf{F e},$ $N i_{3}V,$ and Ni (oxy)hydroxides and the bare CFP at $300\\mathsf{m V}$ overpotential in 1 M KOH \n\nFigure 5a illustrates that the electrocatalytic activity of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1}$ ${}_{-x}\\mathrm{V}_{x}$ depends largely on the co-doping level of Fe and $\\mathrm{v}$ atoms. Among the as-prepared Fe- or/and V-doped Ni-based binary and ternary catalysts, $\\bar{\\mathrm{Ni}}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ exhibits the best OER performance, with low overpotentials of 264 and $291\\mathrm{mV}$ to achieve 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ current density, respectively (Supplementary Fig. 18). The LSV of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{\\dot{V}}_{0.5},$ scanning from positive to negative direction to exclude the influence of the $\\mathrm{\\hat{Ni}}^{2+}/\\mathrm{Ni}^{3+}$ oxidation event on the catalytic current, shows that only $200\\mathrm{mV}$ overpotential is required to attain $10\\mathrm{mA}\\mathrm{cm}^{-2}$ current density. The OER performance of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ is on a par with or even surpasses that of the first-class earth-abundant catalysts reported to date (Supplementary Table 7). \n\nMoreover, the turnover frequency (TOF, based on total amount of metals) of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ $(0.{\\dot{5}}74s^{-1})$ at $\\eta=300\\mathrm{mV}$ in 1 M KOH is significantly larger than those of ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ $(0.018s^{-1})$ , $\\mathrm{Ni}_{3}\\mathrm{V}$ $(0.097s^{-\\mathrm{\\bar{1}}})$ , $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.67}\\mathrm{\\dot{V}}_{0.33}$ $(0.116s^{-1})$ , and $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.33}\\mathrm{V}_{0.67}$ $(0.195s^{-1})$ . Figure 5b manifests that the Tafel slope of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ $(3{\\bar{9}}\\mathrm{mV}\\mathrm{dec^{-1}}),$ is considerably smaller than those of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.67}\\mathrm{V}_{0.33}$ $(59\\mathrm{mV}\\mathrm{dec}^{-1})_{,}$ ), $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.33}\\mathrm{\\dot{V}}_{0.67}$ $(54\\mathrm{mV}\\mathrm{dec^{-1}})$ , ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ $(67\\mathrm{mV}\\mathrm{dec}^{-1})$ ), and $\\mathrm{Ni}_{3}\\mathrm{V}$ $(67\\mathrm{mV}\\mathrm{dec}^{-1}),$ . The apparently larger TOF value and smaller Tafel slope of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ as compared to those of ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ and $\\mathrm{Ni}_{3}\\mathrm{V}$ indicate that the synergetic effect of co-doped Fe and $\\mathrm{v}$ plays an important role in facilitating the kinetics of OER and enhancing the intrinsic activity. \n\nThe stability of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ was assessed by repeated cyclic voltammetry scanning, multi-current step test, and long-term chronopotentiometric experiments. After being subjected to 4000 CV cycles, the OER polarization curve of $\\bar{\\mathrm{Ni}}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ almost overlaps with the initial one (Supplementary Fig. 20a), indicating no noticeable loss in catalytic current, and thus, the good accelerated stability of the electrode. Supplementary Fig. 20b shows the $E-t$ plot of two cycles of multi-current step curves for $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ with current density being enhanced from 50 to 500 $\\operatorname{mA}{\\mathrm{cm}}^{-2}$ by five steps. In each step, once a certain current density is set, the potential promptly levels off and maintains constant for $500s$ ; the multi-current step curve is well repeated in the subsequent cycle. This observation signifies fast mass transportation and good electronic conductivity of the 3D $\\mathrm{Ni_{3}F e_{0.5}V_{0.5}/C F P}$ matrix13. Additionally, the $\\mathrm{Ni_{3}F e_{0.5}V_{0.5}/C F P}$ electrode displays good stability at fixed current densities of 10 and $100\\mathrm{mA}\\mathrm{\\dot{c}m}\\mathrm{\\dot{^{-2}}}$ , respectively, over $60\\mathrm{h}$ of electrolysis (Fig. 5c), indicating excellent stability of the electrode under testing conditions. The Faradaic efficiency of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ evaluated from a chronopotentiometric experiment at a constant current density of $10\\mathrm{\\mA}\\mathrm{cm}^{-2}$ for $^{2\\mathrm{h}}$ is close to $100\\%$ (Supplementary Fig. 21). \n\nTo have a general understanding on the superior activity of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5},$ we estimated the roughness factors (RF) and measured the electrochemical impedance spectroscopy (EIS) of all as-prepared Ni-based electrodes. Based on the estimated RF values (Supplementary Fig. 22 and Supplementary Note 2), the OER polarization curves of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x}$ were ploted with $J$ normalized by RF values (Supplementary Fig. 23) to estimate the improvement of intrinsic OER activity for the Ni-based (oxy) hydroxides with different Fe and $\\mathrm{\\DeltaV}$ doping levels3. The specific current density $(J_{s}=61.6\\mathrm{mA}\\mathrm{cm}^{-2})$ of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ at $300\\mathrm{mV}$ overpotential is about 3, 16, and 71 times higher than those of $\\mathrm{Ni}_{3}\\mathrm{\\bar{V}}$ , $_\\mathrm{Ni}_{3}\\mathrm{Fe}$ , and pure Ni (oxy)hydroxides, respectively, which reveals that the co-doping of Fe and $\\mathrm{v}$ into $\\mathrm{Ni(OH)}_{2}$ lattices is much more effective than separately doping Fe or $\\mathrm{\\DeltaV}$ for improving the specific activity of Ni-based catalysts, and the improved specific activity contributed largely to the high OER activity of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . The Nyquist plots (Fig. 5d) are fitted to a simplified Randles equivalent circuit model (Supplementary Note 3). The very small semicircles in the high frequency zone are attributed to the internal charge-transfer resistances $(R_{\\mathrm{ct(int)}})$ of electrodes, and the second semicircles represent the chargetransfer resistances $(R_{\\mathrm{ct(s-l)}})$ at the electrode/electrolyte interface. Both $R_{\\mathrm{ct(int)}}$ and $R_{\\mathrm{ct(s-l)}}$ values apparently decreased as Fe and V were co-doped into $\\mathrm{Ni(OH)}_{2}$ lattices. The total charge-transfer resistances $(R_{\\mathrm{ct}})$ measured at $300\\mathrm{mV}$ overpotential are 4.2, 7.2, 10.0, and $17.2\\Omega$ for the CFP-supported $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ , $\\mathrm{Ni}_{3}\\mathrm{V}$ , ${\\mathrm{Ni}}_{3}{\\mathrm{Fe}}$ , and pure Ni (oxy)hydroxides, respectively (Supplementary Table 9). The excellent charge-transfer capability of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ makes a crucial contribution to the superior intrinsic OER activity of the electrode48. \n\n![](images/e5f6ba9c42a61702da4418dcd321e5d2317e434a889993db11908ecc436148f0.jpg) \nFig. 6 In-situ EC-Raman and hard XAS spectra. a In-situ EC-Raman spectra of $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ at the potentials of $1.0\\substack{-1.8\\vee}$ in 1 M KOH. b, d, f In-situ Ni, Fe, and V K-edge XANES spectra at the potentials of 1.15–1.75 V. c, e, g FT curves of Ni, Fe, and V $K$ -edge EXAFS $k^{2}\\chi(k)$ functions obtained from the XANES spectra in b, d, f, respectively. The orange and pink circles represent the fitting values \n\nIn-situ EC-Raman/XAS studies and theoretical calculations. To have an in-depth insight into the origin of high activity of the Fe/ V co-doped $\\mathrm{Ni(OH)}_{2}$ , the changes in electronic structures and local atomic environments of $\\mathrm{Ni}_{3}\\mathrm{\\bar{F}e}_{0.5}\\mathrm{V}_{0.5}$ under OER conditions were studied by in-situ electrochemical Raman (EC-Raman) spectroscopy and in-situ XAS. The measurements of in-situ ECRaman spectra were carried out at the potential range of 1.0–1.8 $\\mathrm{\\DeltaV}$ in a spectroelectrochemical (PEC) cell filled with $1\\mathrm{M\\KOH}$ electrolyte (Fig. 6a). When the applied potential was higher than $1.4\\mathrm{V}$ , a pair of well-defined Raman peaks at around 470 and 550 $\\mathsf{c m}^{-1}$ appeared, which were correlated respectively with the $e_{\\mathrm{g}}$ bending and the $A_{\\mathrm{{lg}}}$ stretching vibration of Ni–O in the NiOOHtype phase49,50. On the basis of EC-Raman spectra, the host phase of $\\mathrm{\\DeltaNi^{\\mathrm{{\\hat{III}}_{-}O O H}}}$ formed during the OER process, could provide an electrically conductive, chemically stable, and electrolytepermeable framework for the Fe and $\\mathrm{\\DeltaV}$ dopants48,51, which would benefit the electrochemical OER. \n\nFurthermore, the alteration in the local coordination environment of Ni–O/Fe–O/V–O units and the average oxidation states of Ni, Fe, and V centers in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ were investigated by insitu hard XAS (Supplementary Fig. 24). The in-situ Ni $K$ -edge XANES spectra (Fig. 6b) show that the Ni absorption-edge and the white-line are gradually shifted to the higher-energy side as the applied potential is increased from 1.15 to $1.75\\mathrm{V}$ . Accordingly, the Ni–O distance is shortened from $2.04\\mathring{\\mathrm{A}}$ at $1.15\\mathrm{V}$ to \n\n$1.90\\mathring\\mathrm{A}$ at $1.75\\mathrm{V}$ (Fig. 6c and Supplementary Table 8). The former is close to the $_\\mathrm{Ni-O}$ bond length $(2.05\\mathring\\mathrm{A})\\big^{\\cdot}$ in $\\mathrm{Ni(OH)}_{2}$ , and the latter is almost identical with the Ni–O bond length $({\\bar{1}}.88{\\mathrm{\\AA}})$ in NiOOH, which contains a mixture of $\\mathrm{Ni}^{3+}$ and $\\mathrm{Ni^{\\bar{4}+}}$ sites10. This is in line with the results of in-situ EC-Raman spectroscopy. A similar shift of the Fe white-line peak toward the higher-energy side is also observed with increasing applied potential (Fig. 6d), and the Fe–O distance is shortened slightly from $2.00\\mathring\\mathrm{A}$ at $1.15\\mathrm{V}$ to $1.97\\mathring{\\mathrm{A}}$ at $1.75\\mathrm{V}$ (Fig. 6e and Supplementary Table 8), signifying that the oxidation state of Fe is increased from $+3$ to nearly $+4$ during the OER electrolysis process of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . These FT-EXAFS fit results of Ni and Fe $K\\mathrm{\\Omega}$ -edges of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ in both rest and activated states are consistent with the previous reports10,14. More interestingly, with increasing the applied potential from 1.15 to $1.75\\mathrm{V}$ , the pre-edge peak is slightly decreased in intensity in the in-situ V K-edge XANES spectrum (inset of Fig. 6f), however, it shows identical spectral features to those measured before OER. Similarly, except for the decrease in the intensity of the characteristic peaks, no other obvious change is visible at the ex-situ V $L$ -edge spectra (Supplementary Fig. 25) after OER measurement at $1.75\\mathrm{V}$ . This evidence suggests partial electron transfer to the $\\mathrm{~V~}3d$ orbitals, as their peak intensity is proportional to the unoccupied density of $3d$ states. Meanwhile, the $_{\\scriptstyle\\mathrm{{V-O1}}}$ distance is also shrunk from $1.70\\mathrm{\\AA}$ at $1.15\\mathrm{V}$ to $1.65\\mathring{\\mathrm{A}}$ at $1.75\\mathrm{V}$ (Fig. 6g and Supplementary Table 8), which is close to that of the shortest $_{\\mathrm{V-O}}$ bond length reported for $\\mathrm{V}^{5+}$ oxides $(1.59\\mathrm{\\AA})$ while much shorter than that reported for $\\mathrm{V}^{4+}$ oxides $(1.76\\mathring{\\mathrm{A}})^{42}$ . The $\\mathrm{\\DeltaV}$ atoms with such a short $_\\mathrm{V-O}$ bond may have optimal binding capability with oxygen intermediates relative to Ni and Fe atoms, and exhibit enhanced OER activity, as will be illustrated by following theoretical calculations. These in-situ XAS analyses manifest for the first time the contraction of $\\mathbf{M}{-}\\mathbf{M}^{\\prime}$ and $\\bf{M}(\\dot{M}^{\\prime}){-}O$ bond lengths and the short $_{\\mathrm{V-O}}$ bond distance in the activated $\\mathrm{v}$ -containing (oxy)hydroxide OER catalysts. \n\nDFT plus Hubbard U $(\\mathrm{DFT+U})$ calculations were conducted to have a theoretical understanding on the evident enhancement of OER activity of the $\\mathrm{Fe/V}$ co-doped $\\mathrm{Ni(OH)}_{2}$ from atomic level. It is known that $\\mathrm{Ni(OH)}_{2}$ experiences phase transformations during charging and discharging, and its oxyhydroxides are proposed to be the active phase for $\\mathrm{OER}^{14,52,53}$ . Thus, we consider $\\beta$ -NiOOH co-doped by $\\mathrm{\\DeltaV}$ and Fe atoms with the experimentally optimized doping concentration of $\\mathrm{Ni\\mathrm{:}F e\\mathrm{:}V=}$ 6:1:1, as well as the systems doped by only V or Fe atom with Ni: $\\mathrm{~V~}\\left(\\mathrm{Fe}\\right)=3{:}1$ (Fig. 7a and Supplementary Fig. 26). The model surfaces are covered by either water molecules or oxygen species that are possibly present in the reaction media. These models with different covered species give very similar results on the catalytic properties (Fig. 7c and Supplementary Table 6). \n\n![](images/10a2ce1a3fa9275705b38dbec707e8844858a591cd1cda4b293068d397a8dfbc.jpg) \nFig. 7 DFT theoretical models. a Side views of the Fe/V co-doped Ni (oxy)hydroxide model for DFT calculations, whose (101) surface is exposed for OER catalysis. b Structures and BEs of an ${\\mathsf{O H}}^{\\star}$ , $0^{\\star}$ , and ${\\mathsf{O O H}}^{\\star}$ intermediates adsorbed on the V site of the model in a with the lowest OER overpotential of 0.25 V. The surface metal atoms are covered by O species. c Volcano plot of OER overpotential versus BE difference between ${\\mathsf{O H}}^{\\star}$ and $0^{\\star}$ species for various sites of $\\mathsf{N i}_{3}\\mathsf{F e}_{1-x}\\mathsf{V}_{x}$ (oxy)hydroxide models. For each type of reaction site, various structural models are considered, whose detailed information is given in Supplementary Fig. 28 and Supplementary Table 6. The dashed line is a guide for eyes. d Left panel: DOS of the model in a and the projected DOS on s, $p,$ and $d$ orbitals. Right panel: projected DOS on the $3d$ orbitals of Ni, Fe, and V atoms in the model. The dashed lines represent the $d$ -band center for each element. The Fermi level is shifted to zero. e Calculated free-energy diagram of OER on the most active site of $\\mathsf{N i}_{3}\\mathsf{F e}_{0.5}\\mathsf{V}_{0.5}$ (oxy)hydroxide in pH 14 solutions at different potentials ${\\cal T}=298\\mathsf{K})$ . The two-way arrow indicates the overpotential of the rate-limiting step \n\nIn the optimized models, the bond lengths between metals and oxygen intermediates are 1.60–1.84, 1.63–1.95, and $1.77{-}2.05\\mathring\\mathrm{A}$ for V, Fe, and Ni, respectively, which are in good agreement with the trend of experimental XAS results. The distinct bond length between O atom and V, Fe, or Ni element is a reflection of their different bond order and bond strength, which is fundamentally governed by the electronic band structure of the material. As revealed by the density of states (DOS) in Fig. 7d, the V, Fe, and Ni atoms in the co-doped $\\mathrm{Ni(OH)}_{2}$ have the $d$ -band center of \n\n0.09, $-2.55$ , and $-2.78\\mathrm{eV}$ , respectively. On the basis of the $d$ - band theory54, the V atoms with higher $d$ -band center possess less occupancy of the antibonding states with adsorbed oxygen intermediates, and thus exhibit optimal binding with regard to Ni and Fe atoms (Fig. 7c). \n\nMulliken charge analysis55 shows partial charges of ${\\sim}1.6$ 1.0, and $0.8e$ on the V, Fe, and Ni sites, respectively, signifying the stronger metallicity of $\\mathrm{\\DeltaV}$ atoms and higher chemical activity. Although DFT calculations cannot identify the exact valence for each metal in multi-metal materials, the trend of the partial charges on the V, Fe, and Ni sites obtained from Mulliken charge analysis is consistent with that of the valences of $\\mathrm{V}^{4+/5+}$ , $\\mathrm{Fe}^{3\\mp}$ , and $\\mathrm{\\dot{Ni}}^{2+}$ estimated on the basis of XANES and XPS. Moreover, the Ni (oxy)hydroxide systems without $\\mathrm{\\DeltaV}$ doping are half-metal (Supplementary Fig. 27), while the $\\mathrm{\\DeltaV}$ doping induces finite DOS for the spin-down states near the Fermi level (Fig. 7d), which may help improve the electrical conductivity of the material. \n\nIn the previously reported mechanism for $3d$ metal-based (oxy) hydroxide catalysts in alkaline media, the OER undergoes through following four elementary steps56,57: \n\n$$\n^{*}+\\mathrm{OH}^{-}\\longrightarrow\\mathrm{OH}^{*}+e^{-}\n$$ \n\n$$\n\\mathrm{OH}^{*}{+}\\mathrm{OH}^{-}\\rightarrow\\mathrm{O}^{*}+\\mathrm{H}_{2}\\mathrm{O}(1)+e^{-}\n$$ \n\n$$\n\\mathrm{O}^{*}+\\mathrm{OH}^{-}\\rightarrow\\mathrm{OOH}^{*}+e^{-}\n$$ \n\n$$\n\\mathrm{OOH}^{*}+\\mathrm{OH}^{-}\\longrightarrow^{*}+\\mathrm{O}_{2}(\\mathbf{g})+\\mathrm{H}_{2}\\mathrm{O}(1)+e^{-}\n$$ \n\nwhere \\* represents an active site on the catalyst surface; $\\mathrm{OH^{*}}$ , ${{\\mathrm{O^{*}}}}$ , and $\\mathrm{{OOH^{*}}}$ are the oxygen intermediates. To evaluate the OER activity of the Fe and/or $\\mathrm{\\DeltaV}$ doped or pure Ni (oxy)hydroxide systems, we computed the BEs of oxygen intermediates on various metal sites. The Gibbs free energy for each reaction step and theoretical OER overpotentials were calculated with the standard hydrogen electrode (SHE) method58. \n\nAs displayed by Fig. 7c, the OER overpotentials of doped Ni (oxy)hydroxides follow a volcano-shape relation with the BE difference between ${\\mathrm{OH^{*}}}$ and ${{\\cal O}^{*}}$ (or $\\mathrm{\\Gamma_{OOH}*}$ ) species59. In particular, oxygen binding on the Fe and Ni sites is relatively weak, i.e. $E_{\\mathrm{OH^{*}}}{>}1.15\\mathrm{eV}$ and $E_{\\mathrm{O^{*}}}–E_{\\mathrm{OH^{*}}}>2.24\\mathrm{eV}$ . As a consequence, formation of $\\mathrm{OH^{*}}$ and ${\\cal O}^{*}$ species encounters large potential barriers (Supplementary Fig. 29a, b) and will limit the reaction rate of OER process. Large overpotentials of $0.72\\mathrm{-}0.79$ and $0.84\\mathrm{-}1.08\\mathrm{V}$ are obtained for the Fe and Ni sites, respectively, indicating their low activity for OER. By contrast, the $\\mathrm{\\DeltaV}$ sites provide much stronger but moderate oxygen binding strength $\\bar{(E_{\\mathrm{OH^{*}}}=0.47\\mathrm{-}0.79\\mathrm{eV}}$ and $E_{\\mathrm{O^{*}}}–E_{\\mathrm{OH^{*}}}=1.6\\overset{\\cdot}{1}–2.23\\:\\mathrm{eV})$ and give near-optimal BEs of OER intermediates. Reactions to the formation of $\\mathrm{OH^{*}}$ and ${{\\cal O}^{*}}$ species are readily accessible, while formation of $\\mathrm{{OOH^{*}}}$ experiences the largest potential barrier and limits the OER rate, giving overpotentials of $0.25{-}0.63\\mathrm{V}$ , which are much lower than those for $\\mathrm{\\DeltaNi}$ and Fe sites. Therefore, the highest activity is predicted on the $\\mathrm{v}$ site of the co-doped Ni (oxy) hydroxide with some of the V and Fe atoms aggregated (Fig. 7b). Such V sites provide strong $\\mathrm{{OOH^{*}}}$ binding relative to ${{\\mathrm{O^{*}}}}$ species, and the overpotential is even lower than that of the benchmark catalyst $\\mathrm{RuO}_{2}^{-}$ , i.e., $0.40\\mathrm{V}$ for the (110) surface according to our calculations. The origin of overpotentials is clearly revealed by the free-energy diagrams as shown in Fig. 7e and Supplementary Fig. 29. The largest potential step at the equilibrium potential ( $U$ $=0.402\\mathrm{V}.$ ) indicates the rate-limiting step (RLS) and corresponding overpotential, by overcoming which all the OER steps become downhill and thus can occur spontaneously from the thermodynamic point of view (Supplementary Note 4). In general, the theoretical OER overpotentials follow the same trend as the experimental values: $\\mathrm{Fe/V}$ co-doped $<\\mathrm{V}$ -doped $<$ Fe-doped $<$ undoped Ni (oxy)hydroxide (Supplementary Fig. 28 and Supplementary Table 6). DFT calculations show that the OER activity of $\\mathrm{v}$ sites doped in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ was greatly enhanced by the surrounding Ni/Fe next-nearest neighbors, and more importantly, the $(\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5})$ -OOH models with some of Fe and V atoms aggregated in NiOOH lattices have lower formation energy and higher OER activity than the models with isolated Fe and $\\mathrm{v}$ atoms. This inference is agree with the statement made by Bell and Calle-Vallejo et al. that for Fe-doped Ni (oxy)hydroxides the surrounding Ni neighbors increase the activity of Fe sites10,60,61. \n\n# Discussion \n\nIn summary, comparative studies on a series of binary and ternary OER catalysts of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x}$ $\\left\\langle0\\leq x\\leq1\\right\\rangle,$ ) demonstrate that synergistically modulating electronic structure of $\\mathrm{Ni(OH)}_{2}$ by codoping of Fe and $\\mathrm{\\DeltaV}$ with optimal doping levels could boost the OER activity of Ni (oxy)hydroxides in alkaline solutions. Notably, $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ features an apparently smaller charge transfer resistance and displays considerably higher specific activity compared to $\\mathrm{Ni}_{3}\\mathrm{V}$ and $\\mathrm{Ni}_{3}\\mathrm{Fe},$ which implies a concerted effect of Fe and V on the OER performance of Ni-based (oxy)hydroxides. The FT and WT analyses of EXAFS data attest the substitution of Fe and V atoms for the Ni sites in $\\mathrm{Ni(OH)}_{2}$ lattices, which is supported by the results obtained from theoretical calculations. The comparative studies of $\\mathrm{Fe/V}$ co-doped, Fe- or V-doped, and pure Ni (oxy)hydroxides by XPS and soft XAS reveal the synergistic interaction among Fe, V, and Ni cations, rooted from quite different valence electronic configurations of these $3d$ metals. Such interaction subtly influences the electronic structures and local coordination environments of the metals in the ternary catalyst. Accordingly, the XAS results unveil the highly distorted local coordination structure of $\\mathrm{\\DeltaV}$ and short $\\mathrm{v-O}$ bond length in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5},$ which is further shortened under OER conditions. The notable changes in the electronic and geometric structures of V observed in XPS and XAS are echoed by $\\mathrm{DFT+U}$ calculations, which indicate that the $\\mathrm{\\DeltaV}$ site has the lowest theoretical overpotential for OER compared with the Ni and Fe sites in $\\bar{\\mathrm{Ni}}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . Co-doping of Fe and V into $\\mathrm{Ni}(\\mathrm{OH})_{2}$ lattices results not only in better metallicity of the material relative to that of solely Fe- or $\\mathrm{v}$ -doped Ni (oxy)hydroxide, but also in the nearoptimal BEs of oxygen intermediates. More importantly, the theoretical calculations indicate that the Fe neighbors near to the V play a crucial role in the enhancement of catalytic activity of the V sites in $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ . These findings provide atomic-level insight into the origin of evident enhancement of OER activity of $\\mathrm{Ni}_{3}\\mathrm{\\bar{F}e}_{0.5}\\mathrm{V}_{0.5}$ . On the basis of the in-depth understanding of the intrinsic relation between electronic structure and OER performance of Ni-based ternary metal (oxy)hydroxide catalysts, it can be envisaged that by using co-doped metals other than Fe, such as $\\mathrm{Cr}$ , Mn, and Co with different atomic radius, electronegativity, and $d$ -band center from those of Fe, the modulation for the local coordination environment and electronic structure of $\\mathrm{\\DeltaV}$ in Ni $(\\mathrm{OH})_{2}$ lattices could be regulated, which may further improve the catalytic activity of the $\\mathrm{\\DeltaNi/M/V}$ trimetallic catalysts and expand the scope of highly-active $\\mathrm{Ni}(\\mathrm{OH})_{2}$ -based OER electrocatalysts. \n\n# Methods \n\nHydrophilic pretreatment of CFP. Both sides of the cut-out CFP (thickness of $0.18\\mathrm{mm}\\dot{},$ were first activated by oxygen plasma treatment with RF frequency of 40 kHz for $3\\mathrm{min}$ (Diener Electronic Plasma-Surface-Technology, Germany), to make the CFP substrate have good hydrophilicity. Subsequently, the pretreated CFP was cleaned by sonication in concentrated nitric acid, deionized water, isopropanol, and acetone for $20\\mathrm{min}$ , respectively, and then kept at $45^{\\circ}\\mathrm{C}$ in a vacuum drier for $^{5\\mathrm{h}}$ . \n\nFabrication of $\\mathbb{N}\\mathbb{i}_{3}\\mathbb{F}\\mathbb{e}_{1-x}\\mathbb{V}_{x}$ NS arrays on CFP. Fe/V co-doped Ni (oxy)hydroxide NS array on CFP was prepared by a hydrothermal method. In a typical fabrication process of $\\mathrm{Ni_{3}F e_{0.5}V_{0.5}/C F P}$ , the solution of $\\mathrm{NiCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ $\\mathrm{(0.6\\mmol.}$ $142.62\\mathrm{mg},$ , $\\mathrm{FeCl}_{3}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ ( $0.1\\mathrm{mmol}$ , $27.03\\mathrm{mg}$ , and $\\mathrm{\\DeltaVCl}_{3}$ (0.1 mmol, $15.73\\mathrm{mg})$ in deionized water $(40~\\mathrm{mL})$ was magnetically stirred for $10\\mathrm{min}$ to form a homogenous solution, to which urea (4 mmol, $240.24\\mathrm{mg}$ ) was added with subsequent stirring for $10\\mathrm{min}$ . Afterwards, the prepared solution was transferred to a $50~\\mathrm{mL}$ stainless-steel Teflonlined autoclave and a piece of the pretreated hydrophilic CFP $(3\\times4\\mathrm{cm})$ was placed upright in the middle of autoclave. Next, the autoclave was sealed and heated in an electric oven at $120^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . After cooling the system to room temperature naturally, the resulting CFP with $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ (oxy)hydroxide NS array was washed with deionized water and ethanol by the assistance of ultrasonication for three times to remove the loosely attached materials, and then dried in vacuum oven at $50^{\\circ}\\mathrm{C}$ overnight. A series of reference electrodes, $\\mathrm{Ni(OH)}_{2},$ $\\mathrm{\\OH)}_{2},\\mathrm{Ni}_{3}\\mathrm{Fe},\\mathrm{Ni}_{3}$ , $\\mathrm{Ni_{3}F e_{0.33}V_{0.67}},$ and $\\mathrm{Ni_{3}F e_{0.67}V_{0.33}}$ (oxy)hydroxide NS arrays on CFP, were prepared by the essentially identical procedure. The doping level of Fe and $\\mathrm{\\DeltaV}$ atoms in the host structure of Ni (oxy)hydroxide was controlled by precisely regulating the molar ratio of $\\mathrm{Ni/Fe/V}$ salts in the precursor solution, while with the same total amount of metal ions in the initial solutions $(\\mathrm{Ni^{2+}+F e^{3+}+V^{3+}}=0.8\\mathrm{mmol})$ . For each hydroxide catalyst, at least three electrodes were prepared and used for the spectroscopic and catalytic measurements. \n\nPhysical and chemical characterizations. SEM images, EDX, and elemental mappings were measured on a Hitachi SU8220 cold field-emission scanning electron microscope operated at an acceleration voltage of 5 and $15\\mathrm{kV}$ , respectively. BF-TEM and HRTEM were collected on a FEI Tecnai G2 F30 S-TWIN transmission electron microscope with an acceleration voltage of $300\\mathrm{kV}$ . Aberration-corrected HAADF-STEM images, EDX elemental mappings and linear scanning analysis were collected on JEOL ARM200F microscope with STEM aberration corrector operated at $200\\mathrm{kV}$ . XP spectra were taken on a ThermoFisher ESCALABTM 250Xi surface analysis system using a monochromatized Al Kα small-spot source, and the corresponding BEs were calibrated by referencing the C 1s to $284.8\\mathrm{eV}$ . PXRD patterns were obtained with a Rigaku SmartLab 9.0 using Cu Kα radiation $(\\lambda=1.5\\dot{4}056\\mathring\\mathrm{A}$ ), and the data were collected in Bragg–Brettano mode in the 2θ range from $10^{\\circ}$ to $70^{\\circ}$ at a scan rate of $5^{\\circ}\\operatorname*{min}^{-1}$ . The loading amounts and elemental compositions of catalysts were determined by ICP-OES on an Optima 2000 DV spectrometer (Perkin-Elmer). The as-prepared bi- or trimetallic (oxy) hydroxide array on CFP was immersed in aqua regia for $10\\mathrm{{h}}$ to completely dissolve the catalyst, and the solution was diluted to $20~\\mathrm{mL}$ by deionized water and sonicated for $15\\mathrm{min}$ . All reported ICP-OES results were the average values of at least three independent experiments. \n\nIn-situ EC-Raman measurements. In-situ EC-Raman spectra were recorded with an XploRA confocal microprobe Raman system. A $50\\times$ magnification long working distance $(8\\mathrm{mm})$ objective was used. The wavelength of excitation laser was $785\\mathrm{nm}$ from a He–Ne laser (power was about $4\\mathrm{mW}$ ). Raman frequencies were calibrated using Si wafer. The Raman spectra shown in the experiment were collected during $30\\mathrm{{s}}$ for one single spectrum curve one time, accumulation four times. A custommade PEC cell with a GCE covered with $\\mathrm{Ni}_{3}\\mathrm{Fe}_{0.5}\\mathrm{V}_{0.5}$ (oxy)hydroxide catalyst film, a platinum wire counter electrode, and a saturated calomel reference electrode (SCE, $0.242\\mathrm{V}$ versus SHE) was used for EC-Raman measurements. The electrolyte solution (1 M KOH) was saturated with Ar gas before injected into the cell. \n\nEx-situ soft and hard XAS measurements. The soft XAS of Ni $L_{2,3}$ -edge, Fe $L_{2,3}$ - edge, and V $L_{2,3}.$ -edge were measured on beamline B12b at the National Synchrotron Radiation Laboratory (NSRL, China) in the total electron yield (TEY) mode by collecting the sample drain current under a vacuum better than $1\\times10^{-7}$ Pa. The beam from the bending magnet was monochromatized by utilizing a varied line-spacing plane grating and refocused by a toroidal mirror. The energy range is $100\\mathrm{-}1000\\mathrm{eV}$ with an energy resolution of ${\\sim}0.2\\mathrm{eV}$ . To optimize the XAS measurements, we collected several XAS spectra at different positions on each sample. No big difference was found among these XAS spectra due to the uniformity of the sample. For annihilating the effect of different sample concentration and measurement conditions on the intensity of characteristic XAS peaks, the data at Ni, Fe, and V L-edges were normalized following the method proposed in literature62. The Ni, Fe, and V $K$ -edge XANES and EXAFS spectra were performed on beamline BL14W1 at Shanghai Synchrotron Radiation Facility (SSRF, China) with a ring electron current of $250\\mathrm{mA}$ at $3.5\\mathrm{GeV}$ . The Ni, Fe, and V $K$ -edge XAS spectra of $\\mathrm{Ni}_{3}\\mathrm{Fe}_{1-x}\\mathrm{V}_{x}$ (oxy)hydroxide materials were performed in the fluorescence mode using a Lytle detector, while the reference samples $\\mathrm{(V}_{2}\\mathrm{O}_{3}$ , $\\mathrm{VO}_{2}$ , $\\mathrm{V}_{2}\\mathrm{O}_{5},$ FeO, and $\\mathrm{Fe}_{2}\\mathrm{O}_{3},$ with appropriate absorption edge jump were measured in transmission mode. In these conventional fluorescence detection measurements, the background from elastic and Compton scattering was reduced using a combination of Z-1 filters (three absorption lengths of Ti (Mn, Co) for V (Fe, Ni) K-edge spectra) with Soller slits. \n\nIn-situ XAS measurements. The in-situ XANES and EXAFS data were obtained on beamline BL14W1 at SSRF in the fluorescence mode using a Lytle detector with a step-size of $0.25\\mathrm{eV}$ at room temperature. For the in-situ XAS measurements, an electrochemical workstation $\\left(\\mathrm{CHI}~660\\mathrm{E}\\right)$ and a custom-made PEC cell were used. The PEC cell was equipped with a copper frame induced working electrode, a platinum plate counter electrode, and a $\\mathrm{Hg/HgO}$ (1 M KOH) reference electrode in $1\\mathrm{M}\\mathrm{KOH}$ (Supplementary Fig. 24). For installation of in-situ XAS setup, the side of $\\mathrm{Ni_{3}F e_{0.5}V_{0.5}/C F P}$ electrode covered with a layer of Kapton film was faced to the incident X-rays, while the other side of the CFP covered with catalyst was put in contact with the electrolyte, and the edges of the CFP were fixed to the copper frame electrode with a close contact. Next, the interface was immobilized by a layer of Kapton film, and the inner part of Kapton film was carefully pushed toward the bare side of CFP as close as possible, so as to minimize the influence of electrolyte and bubbles to the acquisition of X-ray signal. Finally, the surface of Kapton film was encapsulated by a flat tool with a coaxial elliptical hole with the assistance of four screws to prevent the electrolyte leakage. During the experiments, the different potentials of 1.15, 1.45, 1.65, and $1.75\\mathrm{V}$ versus RHE were applied to the system. \n\nElectrochemical measurements. All electrochemical measurements were carried out at $25^{\\circ}\\mathrm{C}$ on a CHI 660E potentiostat. A three-electrode H-shape cell was used with the as-prepared Ni-based (oxy)hydroxide/CFP $(0.2\\thinspace\\mathrm{cm}^{2})$ as the working \n\nelectrode, a platinum mesh (Tjaida) as the counter electrode, and a $\\mathrm{Hg/HgO}$ (1 M KOH, Tjaida) as the reference electrode. Prior to each electrochemical experiment, the cell was washed and stored in $0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4};$ ; the counter electrode was cleaned in aqua regia for $30\\mathrm{{s}}$ to remove any oxidative and deposited species during OER process; the electrolyte (1 M KOH) was degassed by bubbling oxygen for $30\\mathrm{min}$ ; the reference electrode was corrected against another unused $\\mathrm{Hg/HgO}$ electrode stored in $1\\mathrm{M}\\mathrm{KOH}$ solution. The measured potentials versus $\\mathrm{Hg/HgO}$ were converted to the potentials versus RHE by the following equation: \n\n$$\nE_{\\mathrm{RHE}}=E_{\\mathrm{Hg/HgO}}+0.059\\mathrm{pH}+E_{\\mathrm{Hg/HgO}}^{\\mathrm{o}}(E_{\\mathrm{Hg/HgO}}^{\\mathrm{o}}=0.098\\mathrm{V}\\mathrm{versus~SHE})\n$$ \n\nFive cycles of CV were executed at a scan rate of $50\\mathrm{mVs^{-1}}$ prior to the measurement of OER polarization curves at $5\\mathrm{mVs^{-1}}$ , and the Tafel slopes were derived from the corresponding OER polarization curves. For all polarization curves presented in the paper, the $i R$ values were manually corrected with the series resistance $(R_{s})$ on the basis of the equation: \n\n$$\nE_{\\mathrm{RHE}}{=}E_{\\mathrm{Hg/HgO}}{+}0.059\\mathrm{pH}{+}E_{\\mathrm{Hg/HgO}}^{\\mathrm{o}}{-}i R_{s}\n$$ \n\nThe compensated ohmic $R_{s}$ values were obtained from the fittings of electrochemical impedance spectra. \n\nComputational method. Spin-polarized DFT calculations were performed by the Vienna ab initio simulation package (VASP), using the planewave basis with energy cutoff of $500\\mathrm{eV}$ (ref. 63), the projector augmented wave (PAW) potentials64, and the PBE functional for the exchange-correlation energy65. Grimme’s semiempirical DFT-D3 scheme of dispersion correction was adopted to describe the van der Waals (vdW) interactions in layered materials66. The Hubbard-U correction was applied for better description of the localized $d$ -electrons of Ni, Fe, and $\\mathrm{\\DeltaV}$ in their (oxy)hydroxides67. We chose an effective $U_{-}J$ value of $3.0\\mathrm{eV}$ for V and Fe and $5.5\\mathrm{eV}$ for Ni atoms, close to the literature values56,68,69. Mulliken charge analysis55 was performed by CASTEP code70 using the planewave basis with an energy cutoff of $1000\\mathrm{eV}$ and norm-conserving pseudopotentials. \n\nData availability. The data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\nReceived: 11 January 2018 Accepted: 2 July 2018 \nPublished online: 23 July 2018 \n\n# References \n\n1. Hunter, B. M., Gray, H. B. & Müller, A. M. Earth-abundant heterogeneous water oxidation catalysts. Chem. Rev. 116, 14120–14136 (2016). \n2. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science 355, 6321 (2017). \n3. McCrory, C. C. L., Jung, S., Peters, J. C. & Jaramillo, T. F. Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 135, 16977–16987 (2013). \n4. Bae, S.-H. et al. Seamlessly conductive 3D nanoarchitecture of core–shell Ni–Co nanowire network for highly efficient oxygen evolution. Adv. Energy Mater. 7, 1601492 (2017). \n5. Ng, J. W. D. et al. Gold-supported cerium-doped $\\mathrm{NiO}_{x}$ catalysts for water oxidation. Nat. Energy 1, 16053 (2016). \n6. Zhao, Y. et al. Ultrafine NiO nanosheets stabilized by $\\mathrm{TiO}_{2}$ from monolayer NiTi-LDH precursors: an active water oxidation electrocatalyst. J. Am. Chem. Soc. 138, 6517–6524 (2016). \n7. Trotochaud, L., Ranney, J. K., Williams, K. N. & Boettcher, S. W. Solution-cast metal oxide thin film electrocatalysts for oxygen evolution. J. Am. Chem. Soc. 134, 17253–17261 (2012). \n8. Morales-Guio, C. G., Liardet, L. & Hu, X. Oxidatively electrodeposited thinfilm transition metal (oxy)hydroxides as oxygen evolution catalysts. J. Am. Chem. Soc. 138, 8946–8957 (2016). \n9. Yin, S. et al. A highly efficient oxygen evolution catalyst consisting of interconnected nickel–iron-layered double hydroxide and carbon nanodomains. Adv. Mater. 30, 1705106 (2017). \n10. Friebel, D. et al. Identification of highly active Fe sites in $(\\mathrm{Ni,Fe})\\mathrm{OOH}$ for electrocatalytic water splitting. J. Am. Chem. Soc. 137, 1305–1313 (2015). \n11. Louie, M. W. & Bell, A. T. An investigation of thin-film Ni–Fe oxide catalysts for the electrochemical evolution of oxygen. J. Am. Chem. Soc. 135, 12329–12337 (2013). \n12. Chen, J. Y. C. et al. Operando analysis of NiFe and Fe oxyhydroxide electrocatalysts for water oxidation: detection of $\\mathrm{Fe^{4+}}$ by Mössbauer spectroscopy. J. Am. Chem. Soc. 137, 15090–15093 (2015). dimensional nickel–iron electrodes for efficient oxygen evolution at high current densities. Nat. Commun. 6, 6616 (2015). \n14. Görlin, M. et al. Tracking catalyst redox states and reaction dynamics in Ni–Fe oxyhydroxide oxygen evolution reaction electrocatalysts: the role of catalyst support and electrolyte pH. J. Am. Chem. Soc. 139, 2070–2082 (2017). \n15. Zhang, W., Wu, Y., Qi, J., Chen, M. & Cao, R. A thin NiFe hydroxide film formed by stepwise electrodeposition strategy with significantly improved catalytic water oxidation efficiency. Adv. Energy Mater. 7, 1602547 (2017). \n16. Yu, L. et al. Cu nanowires shelled with NiFe layered double hydroxide nanosheets as bifunctional electrocatalysts for overall water splitting. Energy Environ. Sci. 10, 1820‒1827 (2017). \n17. Wang, A.-L., Xu, H. & Li, G.-R. NiCoFe layered triple hydroxides with porous structures as high-performance electrocatalysts for overall water splitting. ACS Energy Lett. 1, 445–453 (2016). \n18. Qian, L. et al. Trinary layered double hydroxides as high-performance bifunctional materials for oxygen electrocatalysis. Adv. Energy Mater. 5, 1500245 (2015). \n19. Maruthapandian, V., Mathankumar, M., Saraswathy, V., Subramanian, B. & Muralidharan, S. Study of the oxygen evolution reaction catalytic behavior of $\\mathrm{Co}_{x}\\mathrm{Ni}_{1-x}\\mathrm{Fe}_{2}\\mathrm{O}_{4}$ in alkaline medium. ACS Appl. Mater. Interfaces 9, 13132–13141 (2017). \n20. Detsi, E. et al. Mesoporous $\\mathrm{Ni}_{60}\\mathrm{Fe}_{30}\\mathrm{Mn}_{10}$ -alloy based metal/metal oxide composite thick films as highly active and robust oxygen evolution catalysts. Energy Environ. Sci. 9, 540–549 (2016). \n21. Schwanke, C. et al. Correlating oxygen evolution catalysts activity and electronic structure by a high throughput investigation of $\\mathrm{Ni}_{1-y-z}\\mathrm{Fe}_{y}\\mathrm{Cr}_{z}\\mathrm{O}_{x}.$ Sci. Rep. 7, 44192 (2017). \n22. Liu, J. et al. Electron delocalization boosting highly efficient electrocatalytic water oxidation in layered hydrotalcites. J. Phys. Chem. C 121, 21962–21968 (2017). \n23. Liu, H. et al. The effects of Al substitution and partial dissolution on ultrathin NiFeAl trinary layered double hydroxide nanosheets for oxygen evolution reaction in alkaline solution. Nano Energy. 35, 350‒357 (2017). \n24. Chen, J. Y. C., Miller, J. T., Gerken, J. B. & Stahl, S. S. Inverse spinel $\\mathrm{NiFeAlO_{4}}$ as a highly active oxygen evolution electrocatalyst: promotion of activity by a redox-inert metal ion. Energy Environ. Sci. 7, 1382–1386 (2014). \n25. Gerken, J. B., Shaner, S. E., Massé, R. C., Porubsky, N. J. & Stahl, S. S. A survey of diverse earth abundant oxygen evolution electrocatalysts showing enhanced activity from Ni–Fe oxides containing a third metal. Energy Environ. Sci. 7, 2376–2382 (2014). \n26. Shi, H., Liang, H., Ming, F. & Wang, Z. Efficient overall water-splitting electrocatalysis using lepidocrocite VOOH hollow nanospheres. Angew. Chem. Int. Ed. 56, 573–577 (2017). \n27. Singh, A. A. & Singh, R. N. Effect of V substitution at B-site on the physicochemical and electrocatalytic properties of spinel-type $\\mathrm{NiFe}_{2}\\mathrm{O}_{4}$ towards $\\mathrm{O}_{2}$ evolution in alkaline solutions. Int. J. Hydrog. Energy 35, 3243–3248 (2010). \n28. Fan, K. et al. Nickel–vanadium monolayer double hydroxide for efficient electrochemical water oxidation. Nat. Commun. 7, 11981 (2016). \n29. Fan, K. et al. Hollow iron–vanadium composite spheres: a highly efficient iron-based water oxidation electrocatalyst without the need for nickel or cobalt. Angew. Chem. Int. Ed. 56, 3289–3293 (2017). \n30. Dinh, K. N. et al. Ultrathin porous NiFeV ternary layer hydroxide nanosheets as a highly efficient bifunctional electrocatalyst for overall water splitting. Small. 14, 1703257 (2017). \n31. Wang, D. et al. In situ X‑ray absorption near-edge structure study of advanced $\\mathrm{NiFe(OH)}_{x}$ electrocatalyst on carbon paper for water oxidation. J. Phys. Chem. C 119, 19573–19583 (2015). \n32. Görlin, M. et al. Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni–Fe oxide water splitting electrocatalysts. J. Am. Chem. Soc. 138, 5603–5614 (2016). \n33. Hsu, C.-S. et al. Valence- and element-dependent water oxidation behaviors: in situ X-ray diffraction, absorption and electrochemical impedance spectroscopies. Phys. Chem. Chem. Phys. 19, 8681–8693 (2017). \n34. Fabbri, E., Abbott, D. F., Nachtegaal, M. & Schmidt, T. J. Operando X-ray absorption spectroscopy: a powerful tool toward water splitting catalyst development. Curr. Opin. Electrochem. 5, 20–26 (2017). \n35. Hung, S.-F. et al. Unraveling geometrical site confinement in highly efficient iron-doped electrocatalysts toward oxygen evolution reaction. Adv. Energy Mater. 8, 1701686 (2018). \n36. Bates, M. K., Jia, Q., Doan, H., Liang, W. & Mukerjee, S. Charge-transfer effects in Ni–Fe and Ni–Fe–Co mixed-metal oxides for the alkaline oxygen evolution reaction. ACS Catal. 6, 155–161 (2016). \n37. Zhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n38. Favaro, M. et al. An operando investigation of $(\\mathrm{Ni-Fe-Co-Ce})\\mathrm{O}_{x}$ system as highly efficient electrocatalyst for oxygen evolution reaction. ACS Catal. 7, 1248–1258 (2017). \n39. Long, X. et al. Metallic iron–nickel sulfide ultrathin nanosheets as a highly active electrocatalyst for hydrogen evolution reaction in acidic media. J. Am. Chem. Soc. 137, 11900–11903 (2015). \n40. Xu, X., Song, F. & Hu, X. A nickel iron diselenide-derived efficient oxygenevolution catalyst. Nat. Commun. 7, 12324 (2016). \n41. Gong, M. et al. An advanced Ni–Fe layered double hydroxide electrocatalyst for water oxidation. J. Am. Chem. Soc. 135, 8452–8455 (2013). \n42. Wong, J., Lytle, F. W., Messmer, R. P. & Maylotte, D. H. K-edge absorption spectra of selected vanadium compounds. Phys. Rev. B 30, 5596–5610 (1984). \n43. Zhao, S. et al. Ultrathin metal–organic framework nanosheets for electrocatalytic oxygen evolution. Nat. Energy 1, 16184 (2016). \n44. Sawatzky, G. A. & Post, D. X-ray photoelectron and Auger spectroscopy study of some vanadium oxides. Phys. Rev. B 20, 1546–1555 (1979). \n45. Yamashita, T. & Hayes, P. Analysis of XPS spectra of $\\mathrm{Fe}^{2+}$ and $\\mathrm{Fe}^{3+}$ ions in oxide materials. Appl. Surf. Sci. 254, 2441–2449 (2008). \n46. Wang, H. et al. Iron L-edge X-ray absorption spectroscopy of myoglobin complexes and photolysis products. J. Am. Chem. Soc. 119, 4921–4928 (1997). \n47. Sabatier, P. Hydrogenations et deshydrogenations par catalyse. Ber. Dtsch. Chem. Ges. 44, 1984–2001 (1911). \n48. Burke, M. S., Kast, M. G., Trotochaud, L., Smith, A. M. & Boettcher, S. W. Cobalt–iron (oxy)hydroxide oxygen evolution electrocatalysts: the role of structure and composition on activity, stability, and mechanism. J. Am. Chem. Soc. 137, 3638–3648 (2015). \n49. Yeo, B. S. & Bell, A. T. In situ Raman study of nickel oxide and gold-supported nickel oxide catalysts for the electrochemical evolution of oxygen. J. Phys. Chem. C 116, 8394–8400 (2012). \n50. Trześniewski, B. J. et al. In situ observation of active oxygen species in Fecontaining Ni-based oxygen evolution catalysts: the effect of pH on electrochemical activity. J. Am. Chem. Soc. 137, 15112–15121 (2015). \n51. Stevens, M. B. et al. Measurement techniques for the study of thin film heterogeneous water oxidation electrocatalysts. Chem. Mater. 29, 120–140 (2017). \n52. Lyons, M. E. G. & Brandon, M. P. The oxygen evolution reaction on passive oxide covered transition metal electrodes in aqueous alkaline solution. Part 1 nickel. Int. J. Electrochem. Sci. 3, 1386–1424 (2008). \n53. Lu, P. W. T. & Srinivasan, S. J. Electrochemical-ellipsometric studies of oxide film formed on nickel during oxygen evolution. J. Electrochem. Soc. 125, 1416–1422 (1978). \n54. Nørskov, J. K., Abild-Pedersen, F., Studt, F. & Bligaard, T. Density functional theory in surface chemistry and catalysis. Proc. Natl. Acad. Sci. USA 108, 937–943 (2011). \n55. Segall, M. D., Shah, R., Pickard, C. J. & Payne, M. C. Population analysis of plane-wave electronic structure calculations of bulk materials. Phys. Rev. B 54, 16317–16320 (1996). \n56. Li, Y. & Selloni, A. Mechanism and activity of water oxidation on selected surfaces of pure and Fe-doped $\\mathrm{NiO}_{x}.$ ACS Catal. 4, 1148–1153 (2014). \n57. Rossmeisl, J., Logadottir, A. & Nørskov, J. K. Electrolysis of water on (oxidized) metal surfaces. Chem. Phys. 319, 178–184 (2005). \n58. Nørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuelcell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n59. Man, I. C. et al. Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem 3, 1159–1165 (2011). \n60. Diaz-Morales, O., Ledezma-Yanez, I., Koper, M. T. M. & Calle-Vallejo, F. Guidelines for the rational design of Ni-based double hydroxide electrocatalysts for the oxygen evolution reaction. ACS Catal. 5, 5380–5387 (2015). \n61. Dionigi, F. & Strasser, P. NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes. Adv. Energy Mater. 6, 1600621 (2016). \n62. Crocombette, J. P., Pollak, M., Jollet, F., Thromat, N. & Gautier-Soyer, M. Xray-absorption spectroscopy at the Fe $L_{2,3}$ threshold in iron oxides. Phys. Rev. B 52, 3143–3150 (1995). \n63. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n64. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n65. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n66. Grimme, S., Antony, J., Ehrlich, S. & Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 132, 154104 (2010). \n67. Dudarev, S. L., Botton, G. A., Savrasov, S. Y., Humphreys, C. & Sutton, A. Electron-energy-loss spectra and the structural stability of nickel oxide: an LSDA+U study. Phys. Rev. B 57, 1505–1509 (1998). \n68. Conesa, J. C. Electronic structure of the (undoped and Fe-doped) NiOOH $\\mathrm{O}_{2}$ evolution electrocatalyst. J. Phys. Chem. C 120, 18999–19010 (2016). \n69. Wei, J., Ji, H., Guo, W., Nevidomskyy, A. H. & Natelson, D. Hydrogen stabilization of metallic vanadium dioxide in single-crystal nanobeams. Nat. Nanotechnol. 7, 357–362 (2012). \n70. Clark, S. J. et al. First principles methods using CASTEP. Z. Kristallogr. Cryst. Mater. 220, 567–570 (2005). \n\n# Acknowledgements \n\nThe authors acknowledge financial support from the Natural Science Foundation of China (Grant Nos. 21673028, 11435012, and 21373040) and the Basic Research Program of China (Grant No. 2014CB239402). \n\n# Author contributions \n\nJ.J. conceived the project, performed most of the experimental work, and drafted part of the manuscript. M.W. conceived and supervised the project, wrote the main part of the paper, and revised the entire paper. J.J., F.S., H.Z., Z.J., W.H., and W.Y. conducted the XAS experiments and analyzed the data. W.Y. wrote the part on XAS results. S.Z. and J.Z. performed the DFT calculations, and S.Z. wrote the part on DFT calculations. J.D. and J. L. made the EC-Raman experiments. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-05341-y. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1126_science.aat4191", + "DOI": "10.1126/science.aat4191", + "DOI Link": "http://dx.doi.org/10.1126/science.aat4191", + "Relative Dir Path": "mds/10.1126_science.aat4191", + "Article Title": "Anomalously low dielectric constant of confined water", + "Authors": "Fumagalli, L; Esfandiar, A; Fabregas, R; Hu, S; Ares, P; Janardanull, A; Yang, Q; Radha, B; Taniguchi, T; Watanabe, K; Gomila, G; Novoselov, KS; Geim, AK", + "Source Title": "SCIENCE", + "Abstract": "The dielectric constant epsilon of interfacial water has been predicted to be smaller than that of bulk water (epsilon approximate to 80) because the rotational freedom of water dipoles is expected to decrease near surfaces, yet experimental evidence is lacking. We report local capacitance measurements for water confined between two atomically flat walls separated by various distances down to 1 nullometer. Our experiments reveal the presence of an interfacial layer with vanishingly small polarization such that its out-of-plane e is only similar to 2. The electrically dead layer is found to be two to three molecules thick. These results provide much-needed feedback for theories describing water-mediated surface interactions and the behavior of interfacial water, and show a way to investigate the dielectric properties of other fluids and solids under extreme confinement.", + "Times Cited, WoS Core": 758, + "Times Cited, All Databases": 812, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000436040600041", + "Markdown": "# WATER PROPERTIES \n\n# Anomalously low dielectric constant of confined water \n\nL. Fumagalli1,2\\*, A. Esfandiar3, R. Fabregas4,5, S. $\\bf{H u^{1,2}}$ , P. Ares1,2, A. Janardanan1,2, Q. Yang1,2, B. Radha1,2, T. Taniguchi6, K. Watanabe6, G. Gomila4,5, K. S. Novoselov1,2, A. K. Geim1,2\\* \n\nThe dielectric constant e of interfacial water has been predicted to be smaller than that of bulk water $(\\varepsilon\\approx80)$ ) because the rotational freedom of water dipoles is expected to decrease near surfaces, yet experimental evidence is lacking. We report local capacitance measurements for water confined between two atomically flat walls separated by various distances down to 1 nanometer. Our experiments reveal the presence of an interfacial layer with vanishingly small polarization such that its out-of-plane e is only $\\sim2.$ . The electrically dead layer is found to be two to three molecules thick. These results provide much-needed feedback for theories describing water-mediated surface interactions and the behavior of interfacial water, and show a way to investigate the dielectric properties of other fluids and solids under extreme confinement. \n\nC ltecrtmriicnpeos tarhiezasbtirlietnygotfh notferwfatciearl-mweatdeiratdedintermolecular forces, which in turn affects phenomena such as surface hydration, ion solvation, molecular transport through nanopores, chemical reactions, and macromolecular assembly (1–3). The dielectric properties of interfacial water have attracted intense interest for many decades (4–7), yet no clear understanding has been reached (8–11). Theoretical (12–14) and experimental studies (15–17) have shown that water exhibits layered structuring near surfaces, which suggests that it may form ordered (ice-like) phases under ambient conditions. Such ordered water is generally expected to exhibit small polarizability because of surface-induced alignment of water molecular dipoles, which are then difficult to reorient by applying an electric field (7–10). Despite these extensive studies, the dielectric constant e of interfacial water and its depth remain essentially unknown because measurements are challenging. \n\nPrevious experiments to assess e of interfacial water mostly relied on broadband dielectric spectroscopy applied to large-scale naturally occurring systems such as nanoporous crystals, zeolite powders, and dispersions (4, 5, 10, 18, 19). These systems allow sufficient amounts of interfacial water for carrying out capacitance measurements, but the complex geometries require adjustable parameters and extensive modeling, which results in large and poorly controlled experimental uncertainties. For example, the extracted values of e depended strongly on assumptions about the interfacial layer thickness. Given the lack of direct probes for measuring the polarizability of interfacial water, most evidence has come from molecular dynamics (MD) simulations, which also involve certain assumptions. These studies generally predict that the polarizability should be reduced by approximately an order of magnitude (7–9), but the quantitative accuracy of these predictions is unclear because the same simulation approach struggles to reproduce the known e for bulk water phases (20). \n\nHere, we used slit-like channels of various heights $h$ that could be filled controllably with water. The channels were incorporated into a capacitance circuit with exceptionally high sensitivity to local changes in dielectric properties, which allowed us to determine the out-of-plane dielectric constant $\\ensuremath{\\varepsilon}_{\\bot}$ of the water confined inside. We fabricated our devices by van der Waals assembly (21) of three atomically flat crystals of graphite and hexagonal boron nitride (hBN) following a method reported previously (22–24) (fig. S1). Graphite was used as a bottom layer for the assembly as well as the ground electrode in capacitance measurements (Fig. 1A). Next, a spacer layer was placed on top of graphite, an hBN crystal patterned into parallel stripes. The assembly was completed by placing another hBN crystal on top (Fig. 1, B and C). The spacer determined the channels’ height $h,$ and the other two crystals served as top and bottom walls. The reported channels were usually ${\\sim}200\\mathrm{nm}$ wide and several micrometers long. Each of our devices for a given $h$ contained several channels in parallel (Fig. 1), which ensured high reproducibility of our measurements and reduced statistical errors. When required, the channels could be filled with water through a micrometer-size inlet etched in graphite from the back (22, 23) (Fig. 1A). \n\nTo probe e of water inside the channels, we used scanning dielectric microscopy based on electrostatic force detection with an atomic force microscope (AFM), adapting the approach described in (25). Briefly, by applying a low-frequency ac voltage between the AFM tip and the bottom electrode, we could detect the tip-substrate electrostatic force, which translated into the first derivative of the local capacitance $d C/d z$ in the out-of-plane direction $z.$ . By raster-scanning the tip, a $d C/d z$ (or “dielectric”) image was acquired, from which local dielectric properties could be reconstructed (24). The device design allowed the AFM tip to be fully isolated from water inside the channels and to operate in a dry atmosphere. Note that the use of hBN is essential for these experiments. First, hBN is highly insulating, which allows the electric field generated by the AFM tip to reach the subsurface water without being screened. It is also highly beneficial to have hBN as the side walls (spacers) because this material provides a straightforward reference for comparison between the dielectric properties of hBN $\\langle\\varepsilon_{\\perp}\\approx3.5\\rangle$ (26) and the nearby water of the same thickness (Fig. 1C). As shown below, the latter arrangement yielded an unambiguous dielectric contrast, revealing that e of confined water strongly changes with decreasing $h$ independently of the modeling. \n\nUnlike the previous reports (22, 23), we chose to use relatively thin (30 to $80~\\mathrm{{nm}}$ ) top crystals, which allowed us not only to reach closer to the subsurface water but also to ensure that the channels were fully filled during the capacitance measurements (see below) (fig. S2) (24). When there was no water inside, the top hBN exhibited notable sagging (22) (Fig. 1B). In Fig. 1, E to G, we show AFM topographic images for representative devices with $h\\approx10\\mathrm{nm}$ , $3.8\\mathrm{nm}$ , and $1.4\\mathrm{nm}$ , respectively, under dry conditions. All devices exhibited some sagging, the extent of which depended on the thickness of the top hBN (22) (black curves in Fig. 1, H to J). We used the areas that were not covered by the top hBN layer (cyan curves) to determine the channel heights $h$ from the same images. Such initial imaging, as well as dielectric imaging after filling the channels, was carried out at low relative humidity (below $3\\%$ ) and at room temperature. \n\nFigure 2, A to C, shows AFM topographic images for the same three devices and the same scan areas as in Fig. 1, E to G, but after filling the channels with water, which was done by exposing the backside of our devices to deionized water (22) (Fig. 1A). After the channels were filled, the adhesion between the side and top walls decreased and the sagging diminished (Fig. 1C). The top hBN layer covering water-filled channels became straight with little topographic contrast remaining, independently of $h$ (red curves in Fig. 1, H to J). The corresponding dielectric images for the discussed devices after their filling are shown in Fig. 2, D to F. They show very strong contrast that reverses with decreasing $h$ . For the $_{\\mathrm{10-nm}}$ channels, the red regions containing subsurface water indicate $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ greater than that of hBN, as expected (Fig. 2, D and G, red). For the $3.8–\\mathrm{nm}$ -thick water, the dielectric contrast disappeared (Fig. 2, E and G, cyan), whereas the \n\n1.4-nm-thick water exhibited the opposite, negative contrast (Fig. 2, F and G, blue). The images show that the polarizability of confined water strongly depends on its thickness $h$ and reaches values less than that of hBN with its already \n\nTo quantify the measured local capacitance and find $\\ensuremath{\\varepsilon}_{\\bot}$ for different water thicknesses, we used a three-dimensional electrostatic model that takes into account the specific geometry of the measured devices and the AFM tips chosen (24) \n\nFig. 1. Experimental setup for dielectric imaging. (A) Schematic illustration. The top layer and side walls made of hBN are shown in light blue; graphite serving as the ground electrode is in black. The three-layer assembly covers an opening in a silicon nitride membrane (light brown). The channels are filled with water from the back. The AFM tip served as the top electrode and was kept in a dry nitrogen atmosphere. (B and C) Cross-sectional schematics before (B) and after (C) filling the channels with water (not to scale). (D) Threedimensional topography image of one of our devices. (E to G) AFM topography of the sagged top hBN for devices with different modest $\\mathfrak{E}_{\\perp}\\approx3.5$ . As mentioned above, a reduction in $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ for strongly confined water is generally expected from atomistic simulations (7–9), but the observed decrease is much stronger than predicted $(\\varepsilon_{\\perp}\\approx10)$ or commonly assumed (24). \n\n![](images/9ec62d09148e67e1d9e0d1f8a7502c9673c9caf047e90a2ab6f6cc914b2eabda.jpg) \nvalues of $h$ before filling them with water. Scale bars, $500~\\mathsf{n m}$ . (H to J) Corresponding topography profiles for the top layer (black) and the part not covered by hBN (cyan) as indicated by color-coded lines in (D). Red curves: Same after filling with water. \n\n![](images/a5649b5a5b66a6df42fe140e9246fe61d272af53cff479e3c13d228c9810935f.jpg) \nFig. 2. Dielectric imaging of confined water. (A to C) Topographic dielectric profiles across the channels in (D) to (F). (H) Simulated $d C/d z$ images of the three devices in Fig. 1 after filling them with water. Scale curves as a function of $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ for the known geometries of the three studied bars, $500~\\mathsf{n m}$ . (D to F) Corresponding dC/dz images obtained by applying devices (shown are the peak values in the middle of the channels). Symbols a tip voltage of $4\\lor$ at $1\\mathsf{k}\\mathsf{H}z$ (other voltages and frequencies down to are the measured values of $d C/d z$ from (G). Their positions along the $300{\\mathsf{H z}}$ yielded similar images). Commercial cantilevers with tip radii of 100 to $x$ axis are adjusted to match the calculated curves. Bars and light-shaded $200\\mathsf{n m}$ were used to maximize the imaging sensitivity (24). (G) Averaged regions denote standard errors as defined in (24). \n\n(figs. S3 and S4). The model allows numerical calculation of $d C/d z$ as a function of $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ for a dielectric material inside the channels. Figure 2H shows the resulting curves for the three studied devices in Fig. 2, A to C. By projecting the measured capacitive signals (symbols on the $y$ axis of Fig. 2H) onto the $x$ axis, we find $\\varepsilon_{\\perp}\\approx15.5$ , 4.4, and 2.3 for $h\\approx$ $10\\ \\mathrm{nm}.$ , $3.8~\\mathrm{nm}$ , and $1.4\\ \\mathrm{nm}$ , respectively. We emphasize that $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ is the only unknown in our model, as all the other parameters were determined experimentally. Also, some devices exhibited small (1 to $3\\mathrm{\\AA}$ ) residual sagging in the filled state (see, e.g., Fig. 2, A to C). If not taken into account, this effect could lead to systematic albeit small errors in determining $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ (by effectively shifting the calculated curves in the $y$ direction). Our calculations included this residual sagging (fig. S5). \n\nWe repeated such experiments and their analysis for more than 40 devices with $h$ ranging from ${\\sim}1$ to ${300}\\mathrm{nm}$ . The results are summarized in Fig. 3, which shows the observed $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ as a function of $h_{*}$ . The bulk behavior $(\\varepsilon_{\\perp}\\approx80)$ ) was recovered only for water as thick as ${\\sim}100\\mathrm{nm}$ , which shows that confinement could affect the dielectric properties of even relatively thick water layers (fig. S6). At smaller thicknesses, $\\ensuremath{\\varepsilon}_{\\perp}$ evolved posed simple model describes well the experimental data, allowing an estimate for the thickness $h_{i}$ of interfacial water with the suppressed polarization (24) (fig. S8). Within experimental error, our data yield $h_{i}\\approx7.5\\pm1.5\\mathrm{\\AA},$ in agreement with the expected layered structure of water (14–17). In other words, the electrically dead layer extends two to three molecular diameters away from the surface. This result is also consistent with the thickness $h=1.5$ to $2\\mathrm{nm}$ where the limiting value $\\mathbf{\\varepsilon}_{\\mathbf{\\varepsilon}_{\\perp}}\\approx$ 2.1 is reached (see Fig. 3). This $h$ is approximately twice $h_{i}$ and can be understood as the distance at which the near-surface layers originating from top and bottom walls merge. \n\n![](images/ec25bb9d7c4c3a2ee605233fa3bec6adccb91ade1d7dc525c36e2023de57be40.jpg) \nFig. 3. Dielectric constant of water under strong confinement. \nSymbols denote $\\ensuremath{\\varepsilon}_{\\bot}$ for water inside channels with different values of $h$ . The $y$ -axis error is the uncertainty in $\\mathfrak{E}_{\\perp}$ found from the analysis as described in Fig. 2H.The $x$ -axis error bars show the uncertainty in the water thickness including the residual sagging. Red curves: Calculated $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}(h)$ behavior for the model sketched in the inset. It assumes the presence of a near-surface layer with $\\mathbf{\\varepsilon}_{\\mathbf{\\varepsilon}_{\\mathbf{\\varepsilon}_{\\mathbf{\\varepsilon}}}}=2.1$ and thickness $h_{i}.$ , whereas the remainder of the channel contains the ordinary bulk water. Solid curve: Best fit yielding $h_{i}=7.4\\textrm{\\AA}$ . The dotted, dashed, and dashed-dotted curves are for $h_{i}=3\\textrm{\\AA}$ , $6\\textup{\\AA}$ , and $9\\textup{\\AA}$ , respectively. Horizontal lines: Dielectric constants of bulk water (solid) and hBN (dashed). The dielectric constant of water at optica frequencies (square of its refractive index) is shown by the dotted line. The inset explains our capacitance model with different e values for the bulk and interfacial water. \n\nWe have measured the dielectric constant of water confined at the nanoscale and found it to be anomalously low. Because water exhibits a distinct layered structure near all surfaces, independently of their hydrophilicity (31), it is reasonable to expect that confined and interfacial water have a strongly suppressed $\\varepsilon_{\\perp}$ not only near moderately hydrophobic surfaces (such as those studied in this work) but in most cases. Our results are important for better understanding of long-range interactions in biological systems, including those responsible for the stability of macromolecules such as approximately linearly with $h$ and approached a limiting value of ${\\sim}2.1\\pm0.2$ at $h<2\\mathrm{nm}$ , where only a few layers of water could fit inside the channels. Note that the functional dependence in Fig. 3 was found independent of details of our experimental geometries such as thickness of the top hBN layer and the AFM tip radius (fig. S7). \n\nThe dielectric constant $\\ensuremath{\\varepsilon}_{\\perp}\\approx2.1$ measured for few-layer water is exceptionally small. Not only is it much smaller than that of bulk water $(\\varepsilon_{\\mathrm{bulk}}\\approx$ 80) and proton-disordered ice phases such as ordinary ice $\\mathrm{I_{h}}$ $\\dot{\\varepsilon}\\approx99\\dot{}$ ) (27, 28), but the value is also smaller than that in low-temperature proton-ordered ices ${\\mathrm{\\hat{\\varepsilon}}}_{}^{}\\varepsilon\\approx3$ to 4) (27). Moreover, the observed $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ is small even in comparison with the high-frequency dielectric constant $\\scriptstyle\\mathbf{\\varepsilon}_{\\mathbf{\\varepsilon}_{\\infty}}$ resulting from dipolar relaxation $[\\varepsilon_{\\infty}\\approx4$ to 6 for liquid water (29, 30) and $\\varepsilon_{\\infty}\\approx3.2$ for ice $\\mathrm{I_{h}}$ (27, 28)]. Nonetheless, $\\ensuremath{\\varepsilon}_{\\perp}\\approx2.1$ lies (as it should) above $\\varepsilon\\approx$ 1.8 for water at optical frequencies (27, 30), which is the contribution resulting from the electronic polarization. The above comparison implies that the dipole rotational contribution is completely suppressed, at least in the direction perpendicular to the atomic planes of the confining channels. This result agrees with the MD simulations that find water dipoles to be oriented preferentially parallel to moderately hydrophobic surfaces such as hBN and graphite (12–14). The small $\\mathbf{\\varepsilon}_{\\varepsilon_{\\perp}}$ suggests that the hydrogen-bond contribution, which accounts for the unusually large $\\varepsilon_{\\infty}\\approx4$ to \n\n6 in bulk water (29, 30), is also suppressed. The remaining polarizability can be attributed mostly to the electronic contribution (which is not expected to change under the confinement) plus a small contribution from atomic dipoles, similar to the case of nonassociated liquids (30). \n\nAlthough the observed $\\ensuremath{\\varepsilon}_{\\bot}$ remains anomalously small $(<20)$ over a wide range of $h$ up to $20\\mathrm{nm}$ (Fig. 3), polarization suppression does not necessarily extend over the entire volume of the confined water. Indeed, the capacitance response can come from both interfacial and inner molecules, effectively averaging their contributions over the channel thickness. To this end, we recall that water near solid surfaces is believed to have a pronounced layered structure that extends ${\\sim}10\\mathrm{~\\AA~}$ into the bulk (12–17). Accordingly, the observed dependence $\\mathfrak{E}_{\\perp}(h)$ could be attributed to a cumulative effect from the thin near-surface layer with the low dielectric constant $\\mathbf{\\varepsilon}_{\\varepsilon_{i},}$ whereas the rest of the water has the normal, bulk polarizability, $\\ensuremath{\\varepsilon}_{\\mathrm{bulk}}\\approx80$ . The overall effect can be described by three capacitors in series (inset of Fig. 3). This model yields the effective $\\ensuremath{\\varepsilon}_{\\perp}=h/$ $[2h_{i}/{\\upvarepsilon}_{i}+(h-2h_{i})/{\\upvarepsilon}_{\\mathrm{bulk}}],$ where $h_{i}$ is the thickness of the near-surface layer. Its $\\boldsymbol{\\varepsilon}_{i}$ can be taken as ${\\sim}2.1$ in the limit of small $h$ if we assume that the layered structure does not change much with increasing $h$ (13) and is similar at both the graphite and hBN surfaces, as predicted by MD simulations $(I4)$ . Figure 3 shows that the pro \n\nDNA and proteins, and of the electric double layer that plays a critical role in areas such as electrochemistry and energy storage. The results can also be used to fine-tune parameters in future atomistic simulations of confined water. \n\n# REFERENCES AND NOTES \n\n1. J. N. Israelachvili, Intermolecular and Surface Forces (Academic Press, ed. 3, 2011). \n2. S. Leikin, V. A. Parsegian, D. C. Rau, R. P. Rand, Annu. Rev. Phys. Chem. 44, 369–395 (1993). \n3. B. Honig, A. Nicholls, Science 268, 1144–1149 (1995). \n4. O. Stern, Elektrochem. Angew. Phys. Chem. 30, 508–516 (1924). \n5. B. E. Conway, J. O’M. Bockris, I. A. Ammar, Trans. Faraday Soc. 47, 756–766 (1951). \n6. J. B. Hubbard, L. J. Onsager, J. Chem. Phys. 67, 4850–4857 (1977). \n7. A. Chandra, J. Chem. Phys. 113, 903–905 (2000). \n8. C. Zhang, F. Gygi, G. Galli, J. Phys. Chem. Lett. 4, 2477–2481 (2013). \n9. A. Schlaich, E. W. Knapp, R. R. Netz, Phys. Rev. Lett. 117, 048001 (2016). \n10. D. Ben-Yaakov, D. Andelman, R. Podgornik, J. Chem. Phys. 134, 074705 (2011). \n11. D. J. Bonthuis, R. R. Netz, Langmuir 28, 16049–16059 (2012). \n12. C. Y. Lee, J. A. McCammon, P. J. Rossky, J. Chem. Phys. 80, 4448–4455 (1984). \n13. G. Cicero, J. C. Grossman, E. Schwegler, F. Gygi, G. Galli, J. Am. Chem. Soc. 130, 1871–1878 (2008). \n14. G. Tocci, L. Joly, A. Michaelides, Nano Lett. 14, 6872–6877 (2014). \n15. J. N. Israelachvili, R. M. Pashley, Nature 306, 249–250 (1983). \n16. M. F. Toney et al., Nature 368, 444–446 (1994). \n17. J.-J. Velasco-Velez et al., Science 346, 831–834 (2014). \n18. H.-B. Cui et al., Angew. Chem. Int. Ed. 44, 6508–6512 (2005) \n19. A. R. Haidar, A. K. Jonscher, J. Chem. Soc. Faraday Trans. I 82, 3535–3551 (1986). \n20. J. L. Aragones, L. G. MacDowell, C. Vega, J. Phys. Chem. A 115, 5745–5758 (2011). \n21. A. K. Geim, I. V. Grigorieva, Nature 499, 419–425 (2013). \n22. B. Radha et al., Nature 538, 222–225 (2016). \n23. A. Esfandiar et al., Science 358, 511–513 (2017). \n24. See supplementary materials. \n25. L. Fumagalli, D. Esteban-Ferrer, A. Cuervo, J. L. Carrascosa, G. Gomila, Nat. Mater. 11, 808–816 (2012). \n26. K. K. Kim et al., ACS Nano 6, 8583–8590 (2012). \n27. V. F. Petrenko, R. W. Whitworth, Physics of Ice (Oxford Univ. Press, 1999). \n28. G. P. Johari, Contemp. Phys. 22, 613–642 (1981). \n29. N. E. Hill, Trans. Faraday Soc. 59, 344–346 (1963). \n\n30. N. E. Hill, W. E. Vaughan, A. H. Price, M. Davies, Dielectric Properties and Molecular Behaviour (Van Nostrand Reinhold, 1969). 31. O. Björneholm et al., Chem. Rev. 116, 7698–7726 (2016). \n\n# ACKNOWLEDGMENTS \n\nWe thank N. Walet, P. Carbone, L. Lue, and A. Michaelides for useful discussions. Funding: Supported by the Engineering and Physical Sciences Research Council, Lloyd’s Register Foundation, Graphene Flagship, European Research Council, and Royal Society. G.G. acknowledges support from Ministerio de Industria, Economia y Competitividad (MINECO, grant TEC2016-79156-P) and ICREA Academia Award. Author contributions: L.F. proposed and directed the research with help from A.K.G. and K.S.N.; A.E. fabricated most of the devices with contributions from S.H., A.J., Q.Y., and B.R.; L.F. carried out experiments and data analysis; P.A. helped with image acquisition and processing; R.F., G.G., \n\nand L.F. implemented finite-element numerical calculations; T.T. and K.W. provided hBN; L.F. and A.K.G. wrote the manuscript; and all authors contributed to discussions. Competing interests: We declare no such interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/360/6395/1339/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S8 \nReferences (32–45) \n24 February 2018; accepted 3 May 2018 \n10.1126/science.aat4191 \n\n# Science \n\n# Anomalously low dielectric constant of confined water \n\nL. Fumagalli, A. Esfandiar, R. Fabregas, S. Hu, P. Ares, A. Janardanan, Q. Yang, B. Radha, T. Taniguchi, K. Watanabe, G Gomila, K. S. Novoselov and A. K. Geim \n\nScience 360 (6395), 1339-1342. DOI: 10.1126/science.aat4191 \n\n# Water's surface dielectric \n\nTheoretical studies predict that the inhibition of rotational motion of water near a solid surface will decrease its local dielectric constant. Fumagalli et al. fabricated thin channels in insulating hexagonal boron nitride on top of conducting graphene layers (see the Perspective by Kalinin). The channels, which varied in height from 1 to 300 nanometers, were filled with water and capped with a boron nitride layer. Modeling of the capacitance measurements made with an atomic force microscope tip revealed a surface-layer dielectric constant of 2, compared with the bulk value of 80 for water. \n\nScience, this issue p. 1339; see also p. 1302 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/360/6395/1339 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2018/06/20/360.6395.1339.DC1 \n\nRELATED CONTENT \n\nREFERENCES \n\nThis article cites 40 articles, 4 of which you can access for free http://science.sciencemag.org/content/360/6395/1339#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41586-018-0336-3", + "DOI": "10.1038/s41586-018-0336-3", + "DOI Link": "http://dx.doi.org/10.1038/s41586-018-0336-3", + "Relative Dir Path": "mds/10.1038_s41586-018-0336-3", + "Article Title": "Ferroelectric switching of a two-dimensional metal", + "Authors": "Fei, ZY; Zhao, WJ; Palomaki, TA; Sun, BS; Miller, MK; Zhao, ZY; Yan, JQ; Xu, XD; Cobden, DH", + "Source Title": "NATURE", + "Abstract": "A ferroelectric is a material with a polar structure whose polarity can be reversed (switched) by applying an electric field(1,2). In metals, itinerant electrons screen electrostatic forces between ions, which explains in part why polar metals are very rare(3-7). Screening also excludes external electric fields, apparently ruling out the possibility of ferroelectric switching. However, in principle, a thin enough polar metal could be sufficiently penetrated by an electric field to have its polarity switched. Here we show that the topological semimetal WTe2 provides an embodiment of this principle. Although monolayer WTe2 is centro-symmetric and thus non-polar, the stacked bulk structure is polar. We find that two-or three-layer WTe2 exhibits spontaneous out-of-plane electric polarization that can be switched using gate electrodes. We directly detect and quantify the polarization using graphene as an electric-field sensor(8). Moreover, the polarization states can be differentiated by conductivity and the carrier density can be varied to modify the properties. The temperature at which polarization vanishes is above 350 kelvin, and even when WTe2 is sandwiched between graphene layers it retains its switching capability at room temperature, demonstrating a robustness suitable for applications in combination with other two-dimensional materials(9-12).", + "Times Cited, WoS Core": 752, + "Times Cited, All Databases": 814, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000441673400033", + "Markdown": "# Ferroelectric switching of a two-dimensional metal \n\nZaiyao Fei1,5, Wenjin Zhao1,5, Tauno A. Palomaki1,5, Bosong $\\mathrm{{\\calS}u n^{1}}$ , Moira K. Miller1, Zhiying Zhao2,3, Jiaqiang $\\mathrm{Yan^{2}}$ Xiaodong $\\mathrm{Xu^{1,4}}$ & David H. Cobden1\\* \n\nA ferroelectric is a material with a polar structure whose polarity can be reversed (switched) by applying an electric field1,2. In metals, itinerant electrons screen electrostatic forces between ions, which explains in part why polar metals are very rare3–7. Screening also excludes external electric fields, apparently ruling out the possibility of ferroelectric switching. However, in principle, a thin enough polar metal could be sufficiently penetrated by an electric field to have its polarity switched. Here we show that the topological semimetal $\\mathbf{WTe}_{2}$ provides an embodiment of this principle. Although monolayer ${\\bf W T e}_{2}$ is centro-symmetric and thus non-polar, the stacked bulk structure is polar. We find that two- or three-layer ${\\bf W T e}_{2}$ exhibits spontaneous out-of-plane electric polarization that can be switched using gate electrodes. We directly detect and quantify the polarization using graphene as an electric-field sensor8. Moreover, the polarization states can be differentiated by conductivity and the carrier density can be varied to modify the properties. The temperature at which polarization vanishes is above 350 kelvin, and even when ${\\bf W T e}_{2}$ is sandwiched between graphene layers it retains its switching capability at room temperature, demonstrating a robustness suitable for applications in combination with other twodimensional materials9–12. \n\nA polar material contains an axis (referred to as the polar axis) along which the two opposite directions are distinguishable. This property is necessary for the existence of a spontaneous electric polarization. Of the 32 three-dimensional crystal classes, the ten that have a polar axis are known as the pyroelectrics, because heating them changes any electric polarization along this axis to produce a voltage. When Anderson and Blount introduced3 the term ‘ferroelectric metal’ in 1965, they were referring to the possibility of polar structure appearing in certain metallic crystals upon cooling. However, they assumed that, even if such polar metals existed, the polarity would not be switchable. Definite cases of metals with polar structure have been identified only very recently4–7. \n\nSeveral ferroelectric insulators have been found to maintain ferroelectric characteristics in ultrathin $\\mathrm{{films}}^{13-17}$ . However, when materials with a layered structure are thinned towards the monolayer limit their properties often change qualitatively. This is illustrated by, for example: graphene, which becomes a two-dimensional Dirac metal11,12; $\\mathrm{MoS}_{2}.$ which changes from an indirect- to a direct-gap semiconductor10; and $\\mathrm{CrI}_{3}$ , which varies between being antiferromagnetic and ferromagnetic9. Another example is the topological semimetal $\\mathrm{WTe}_{2}{}^{18}$ , which becomes either a two-dimensional topological insulator19–22 or a superconductor at low temperatures in the monolayer limit, depending on the level of electrostatic doping. Here we focus on another aspect of $\\mathrm{WTe}_{2}$ : the fact that it is a polar metal. Its three-dimensional $(1\\mathrm{T}^{\\prime})$ structure has a polar space group7, $P n m2_{1},$ , and it remains metallic down to a thickness of three layers when undoped23 and a monolayer when electrostatically doped20. We show here that as $\\mathrm{WTe}_{2}$ approaches this limit the polarity can be switched, making it effectively ferroelectric even when it is metallic in the plane. \n\nThe $\\Pi^{\\prime}$ structure (Fig. 1a) contains $b{-}c$ mirror (M) and $_{a-c}$ glide (G) planes, so the polar axis, which must be parallel to both of them, is the $c$ axis, perpendicular to the layers7,18. We apply an electric field along this axis using the device geometry indicated in Fig. 1b. An electrically contacted thin $\\mathrm{WTe}_{2}$ flake is sandwiched between two hexa­ gonal boron nitride (h-BN) dielectric sheets, with thicknesses of $d_{\\mathrm{t}}$ (top) and $d_{\\mathrm{b}}$ (bottom). Above and below are gate electrodes, usually of few-layer graphene, to which voltages $V_{\\mathrm{t}}$ and $V_{\\mathrm{b}}$ are applied relative to the grounded $\\mathrm{WTe}_{2}$ (see Methods, Extended Data Fig. 1 and Extended Data Table 1 for device fabrication and characterization). \n\nWe define the applied electric field passing upwards through the layer, which will couple to out-of-plane polarization, as $E_{\\perp}{=}(-V_{\\mathrm{t}}/d_{\\mathrm{t}}+V_{\\mathrm{b}}/d_{\\mathrm{b}})/2$ . When $E_{\\perp}$ is swept up and down, in the conductance of trilayer (Fig. 1c) and bilayer (Fig. 1d) devices we observe bistability near $E_{\\perp}=0$ , characteristic of ferroelectric switching, at all temperatures $T$ from 4 K to above room temperature. No bistability is seen in monolayer $\\mathrm{WTe}_{2}$ (Fig. 1e), consistent with its structure having a centre of symmetry (Fig. 1e inset, red circles) and hence being nonpolar; this symmetry also rules out instabilities involving charge injection into the $\\mathbf{h}$ -BN. Nor is bistability seen in thicker crystals, including when one is used as a gate electrode (Extended Data Fig. 2). This, and the larger field required to switch the trilayer device than the bilayer device, can be explained by screening of $E_{\\perp}$ on a length scale of nanometres. \n\nWe saw similar bistability in all bilayer devices (Extended Data Fig. 3). To prove that it is associated with out-of-plane electric polarization, we made devices in which the top gate is replaced by monolayer graphene, the conductivity of which is sensitive to the precise electric field $E_{\\mathrm{t}}$ in the upper h-BN. In Fig. 2 we present measurements at a series of temperatures on such a bilayer $\\mathrm{WTe}_{2}$ device (B2) with four gold contacts to the top graphene (Fig. 2a; Extended Data Fig. 4). If the $\\mathrm{WTe}_{2}$ acts as a conducting sheet then it will screen out any electric field due to a voltage applied to the bottom gate. Indeed, Fig. 2b demonstrates that the conductance $G_{\\mathrm{gr}}$ of the graphene depends only very weakly on $V_{\\mathrm{b}},$ except in a certain interval where it jumps between two states. The conductance of the $\\mathrm{WTe}_{2}$ is bistable in precisely the same interval (Extended Data Fig. 4). The two states must correspond to different values of $E_{\\mathrm{t}}$ that can occur for exactly the same set of applied bias voltages. This implies the existence of two different vertical distributions of charge in the bilayer $\\mathrm{WTe}_{2}$ . We deduce that sweeping the bottom gate changes $E_{\\perp}$ (here $E_{\\perp}=V_{\\mathrm{b}}/(2d_{\\mathrm{b}})$ because $V_{\\mathrm{t}}{=}0$ ), which at the ends of the hysteresis loop flips the polarization state (henceforth denoted by $\\mathrm{\\bfP\\uparrow}$ or ${\\mathrm{P\\downarrow}}$ ), changing $E_{\\mathrm{t}}$ by an amount $\\updelta E_{\\mathrm{t}},$ and so changing $G_{\\mathrm{gr}}$ \n\nWe infer $\\updelta E_{\\mathrm{t}}$ by applying a bias $V_{\\mathrm{{W}}}$ to the $\\mathrm{WTe}_{2}$ and measuring the change $\\updelta V=d_{\\mathrm{t}}\\updelta E_{\\mathrm{t}}$ that is required to produce the same change in $G_{\\mathrm{gr}}$ (Fig. 2c). For the simplified case of $d_{\\mathrm{t}}=d_{\\mathrm{b}}$ and all voltages at zero, the electrostatic potential profile is inverted between $\\mathrm{\\bfP\\uparrow}$ (red) and $\\mathrm{P\\downarrow}$ (green), as sketched in Fig. 2d, and the areal polarization density is $P\\approx\\varepsilon_{0}\\delta V$ (Methods), where $\\scriptstyle{\\varepsilon_{0}}$ is the vacuum permittivity. At $20~\\mathrm{K}.$ this gives $P\\approx1\\times10^{4}~e$ per $c\\mathrm{m}$ , which is equivalent to transferring about $2\\times10^{11}$ electrons per $\\mathrm{cm}^{2}$ between the two layers, a distance of about $0.7\\mathrm{nm}$ . This is three orders of magnitude lower than the volume polarization density of around $0.2\\mathrm{C}\\mathrm{m}^{-2}\\approx10^{14}$ electrons per $\\mathrm{cm}^{2}$ in the classic ferroelectric1 ${\\mathrm{BaTiO}}_{3}$ . Combined with the micrometre-scale device size, such a small polarization makes it very hard to detect the ferroelectricity using standard displacement current measurements. \n\n![](images/db2b8c7ea3c9ccfdfa2a74dfb6d9b306dc13cdd5f6c41177317cc44c42ea89b0.jpg) \nFig. 1 | Evidence for ferroelectric switching in ${\\bf W T e}_{2}$ . a, Structure of three-dimensional $1\\mathrm{T}^{\\prime}\\mathrm{WTe}_{2}$ , showing the mirror plane (M; dashed), glide plane $\\mathrm{\\ddot{G};}$ dotted) and polar $c$ axis (red arrow, up; green arrow, down). W atoms are blue; Te atoms are orange. b, Schematic cross-section of the device geometry used to apply an electric field $E_{\\perp}$ normal to an atomically thin $\\mathrm{WTe}_{2}$ flake. c, d, Conductance $G$ of undoped trilayer device T1 (c) and bilayer device B1 (d) as $E_{\\perp}$ is swept up and down (black arrows), setting $V_{\\mathrm{{t}}}/d_{\\mathrm{{t}}}=-V_{\\mathrm{{b}}}/d_{\\mathrm{{b}}}$ to avoid net doping. The plots show bistability associated with electric polarization up (red arrow) or down \n(green arrow), at temperatures from $4\\mathrm{K}$ to $300\\mathrm{K}$ (as labelled). Here the conductance is the reciprocal of the four-terminal resistance. The undoped trilayer has a metallic temperature dependence, the bilayer an insulating one. Inset to c, optical image of a representative double-gated device. The $\\mathrm{WTe}_{2}$ flake has been artificially coloured red. Scale bar, $10\\upmu\\mathrm{m}$ . e, Similar measurements on a monolayer $\\mathrm{WTe}_{2}$ device (M1), showing no bistability. At 4 K, conduction is in the quantum spin Hall regime. Insets, location (red circle) of a centre of symmetry in the monolayer, viewed along the $b$ (left) and $a$ (right) axes. \n\nIn Fig. 2e we plot $\\updelta V$ as a function of $T$ . Between about $60\\mathrm{K}$ and $300\\mathrm{K}$ it decreases roughly linearly with $T,$ extrapolating to zero at roughly $450~\\mathrm{K}$ . However, above about $340\\mathrm{~K~}$ the signal becomes unstable and we can no longer identify a hysteresis loop, suggesting that a transition to a non-polar state occurs in this temperature range. \n\nWe also made a simpler device with no top $\\mathbf{h}$ -BN and monolayer graphene directly encapsulating the bilayer $\\mathrm{WTe}_{2}$ . It exhibited highly reproducible hysteresis in the conductance, visible up to $300~\\mathrm{K}$ (Extended Data Fig. 5). This result demonstrates that the ferroelectric switching is robust enough for potential applications at room temperature that use it in combination with other two-dimensional materials. \n\nWe also investigated the effect of gate-induced charge doping, defined by $n_{\\mathrm{e}}=\\varepsilon_{\\mathrm{hBN}}\\varepsilon_{0}(V_{\\mathrm{t}}/d_{\\mathrm{t}}+V_{\\mathrm{b}}/d_{\\mathrm{b}})/e$ , where $e$ is the electron charge and $\\varepsilon_{\\mathrm{h-BN}}$ is the relative permittivity of $\\mathbf{h}$ -BN. If the material were a simple metal, $n_{\\mathrm{e}}$ would be the areal density of added electrons. In Fig. 3a, b we plot the conductance $G$ at $7\\mathrm{K}$ for device B1 (the same bilayer as in Fig. 1d), as a joint function of $V_{\\mathrm{t}}$ and $V_{\\mathbf{b}},$ measured with $V_{\\mathrm{t}}$ stepped and $V_{\\mathrm{b}}$ swept up or down. Each sweep was started in the same fully polarized state. The black dashed lines in Fig. 3a, b denote $E_{\\perp}=0$ and the white dashed lines denote $n_{\\mathrm{e}}=0$ . The two plots differ only in the central hysteretic region, as is made clearer by plotting the difference between them (Fig. 3c). Similar behaviour is seen at higher temperature (Fig. 3d, at $200\\mathrm{K})$ ). At $E_{\\perp}=0$ , $G$ is a similar function of $n_{\\mathrm{e}}$ for both $\\mathrm{P\\uparrow}$ and ${\\mathrm{\\mathbf{P}}}\\downarrow$ (Fig. 3e), with a temperature dependence that is insulating near $n_{\\mathrm{e}}=0$ and metallic for $n_{\\mathrm{e}}>n_{\\mathrm{c}}$ , with critical density $n_{c}{\\approx}2\\times10^{12}\\mathrm{cm}^{-2}$ , as reported previously20. In Fig. 3f we show traces obtained by sweeping $E_{\\perp}$ repeatedly up and down for selected values of $n_{\\mathrm{e}}$ at $7\\mathrm{K}$ . In each case the single conductance level at large $E_{\\perp}$ evolves smoothly and reproducibly into one of the two stable levels as $E_{\\perp}$ is reduced to zero, implying that the state remains uniformly polarized, without domain structure, at $E_{\\perp}=0$ . For small or negative $n_{\\mathrm{e}},$ the effect of $E_{\\perp}$ is large and of opposite sign for $\\mathrm{P\\uparrow}$ and P↓, producing butterfly-shaped hysteresis loops. For $n_{\\mathrm{e}}$ well above $n_{\\mathrm{c}},E_{\\perp}$ has less effect on the conductance and the hysteresis is smaller, but still present. Hence, the doped bilayer device, like the trilayer device, is simultaneously ferroelectric and metallic. \n\nAt low temperatures (Fig. 3c) we observe an increase in the width of the hysteresis loop for increasingly negative $n_{\\mathrm{e}},$ whereas at $200\\mathrm{K}$ (Fig. 3d) it is almost independent of $n_{\\mathrm{e}}$ . When the conductance jumps there is some stochastic variation in the positions and substructure of the jumps, which is indicative of domain dynamics. If the surrounding gates were not present to screen the depolarization field, domains would inevitably form to limit the electrostatic energy24, as observed in other ultrathin ferroelectrics13,16,25,26. In our devices, defects such as rips, bubbles and folds could nucleate domains or pin domain walls. In addition, $E_{\\perp}$ is not completely uniform, because above and near the platinum contacts it is reduced by screening. Indeed, the pattern of switching depends on the choice of measurement contacts within a given device (Extended Data Fig. 6). We also observe that in some bilayer devices, such as B2 (Fig. 2), the switching field is not symmetric about $E_{\\perp}=0$ . A possible explanation for this is that sometimes, despite all precautions, during device fabrication one side of the $\\mathrm{WTe}_{2}$ flake was exposed to mild oxidation, producing asymmetric trapped charge. \n\nThe fact that the conductance is sensitive to the polarization is consistent with the expectation that the polarization redistributes charge between the layers, which are inequivalent when $E_{\\perp}$ is non-zero. Although the specific mechanisms for the sensitivity to $n_{\\mathrm{e}},E_{\\perp}$ and $P$ are still under investigation, we remark on the following. First, the monolayer conductance at $4\\mathrm{K}$ in Fig. 1e, which we know is due to edge conduction because this is the established quantum spin Hall regime, is almost independent of $E_{\\perp}$ . Second, in bilayers at large positive or negative $n_{\\mathrm{e}}^{}$ , the reversal of $P$ has a similar effect on the conductance to that of changing $E_{\\perp}$ , changing it by approximately $0.15\\mathrm{V}\\mathrm{nm}^{-1}$ at $7\\mathrm{K}$ (indicated by the dotted horizontal line in Fig. 3f). This change in $E_{\\perp}$ corresponds to a change in the electrostatic potential difference between the two $\\mathrm{WTe}_{2}$ layers by about $100\\mathrm{mV}.$ This is of the same order as the estimated change in the potential difference associated with the polarization reverse, $28V\\approx40\\mathrm{mV},$ suggesting that the potential imbalance between the layers governs the sensitivity of the conductance to both $E_{\\perp}$ and $P$ . It is also roughly the same as the width of the hysteresis loop; that is, the polarization flips roughly when the applied potential difference exceeds the potential due to the spontaneous polarization. This is another indicator that electron transfer between the layers may be involved. Third, the very sharp minimum seen in G close to $n_{\\mathrm{e}}=0$ in bilayers (Fig. 3e) presumably marks the compensation point at which electron and hole densities are exactly equal, suggesting that electron–hole correlation may be important. Taken together, the above observations raise the possibility that electron–hole correlation effects, rather than a lattice instability27, drive the spontaneous polarization in $\\mathrm{WTe}_{2}$ . If this is the case, then the polarization could principally involve a relative motion of the electron cloud relative to the ion cores, rather than a lattice distortion, in which case the switching would be intrinsically very fast. \n\n![](images/9e7aaa90743fc70a1bf28ce120590619ae3a8141166701672dd10314872faf1d.jpg) \nFig. 2 | Detecting the out-of-plane polarization. a, Micrograph (left) and schematic cross-section (right) of a bilayer $\\mathrm{WTe}_{2}$ device (B2) with multiply contacted graphene in place of the top gate, indicating separately the electric fields in the h-BN above $(E_{\\mathrm{t}})$ and below $(E_{\\mathrm{{b}}})$ the $\\mathrm{WTe}_{2}$ . Scale bar, $5\\upmu\\mathrm{m}$ . b, The graphene conductance $G_{\\mathrm{gr}}$ is measured when a bias $V_{\\mathrm{b}}$ is applied to the bottom gate with the intervening $\\mathrm{WTe}_{2}$ grounded, at a series of temperatures (as labelled). The two conductance states seen for the two sweep directions (black arrows) are associated with different outof-plane polarization states of the $\\mathrm{WTe}_{2}$ (red and green arrows as in Fig. 1). c, The behaviour of $G_{\\mathrm{gr}}$ (the $y$ axis is the same as in b) when a voltage $\\boldsymbol{V_{\\mathrm{W}}}$ is applied directly to the $\\mathrm{WTe}_{2}$ provides a mapping to the difference $\\updelta E_{\\mathrm{t}}=\\updelta V/d_{\\mathrm{t}}$ in $E_{\\mathrm{t}}$ between the two states. d, Sketch indicating how the reversal of the polarization changes the electrostatic potential (from red to green) and $E_{\\mathrm{t}}$ (see text). e, Temperature dependence of $\\updelta V_{;}$ , which is proportional to the polarization. \n\nFerroelectricity adds another ingredient to the intriguing combination of quantum spin Hall edges, correlation effects and superconductivity already seen in atomically thin $\\mathrm{WTe}_{2}$ . Although the quantum spin Hall behaviour and superconductivity are restricted to the centro-symmetric monolayer and ferroelectricity occurs only for two or more layers, it is possible that these diverse phenomena are connected in ways that may also be relevant to understanding the properties that emerge in the three-dimensional limit, including extreme and anisotropic magnetoresistance28,29, a polar axis and Weyl points18,30. \n\n![](images/0cdae61bf0159ace2b43de6f54da21a7f78a7be2a455f33049185732bf8f6e8e.jpg) \nFig. 3 | Gate tuning of the ferroelectric behaviour. a, b, Conductance $G$ of bilayer device B1 at $7\\mathrm{K}$ as a function of both gate voltages, for the two sweep directions of $V_{\\mathrm{b}}$ as indicated by the white arrows. c, Difference between a and b at $^{7\\mathrm{K},}$ which is non-zero in the hysteretic regime. d, Same measurement as in c, but at $200\\mathrm{K}$ . In a–d, black and white dashed lines indicate contours of zero perpendicular field $E_{\\perp}$ and zero charge density $n_{\\mathrm{e}},$ respectively. e, Variation in $G$ with $n_{\\mathrm{e}}$ at $E_{\\perp}=0$ for both polarization states (up, dashed; down, solid) at two temperatures (as labelled). The dashed bar near the bottom indicates the range of $n_{\\mathrm{e}}$ in a–d, and $n_{\\mathrm{c}}$ is the critical density (see text). f, Sweeps of $E_{\\perp}$ for fixed $n_{\\mathrm{e}}$ (as labelled) at $7\\mathrm{K}.$ The dotted bar near the bottom indicates the magnitude of the approximate shift in $E_{\\perp}$ of the conductance minimum between the opposite polarization states. \n\n# Online content \n\nAny Methods, including any statements of data availability and Nature Research reporting summaries, along with any additional references and Source Data files, are available in the online version of the paper at https://doi.org/10.1038/s41586- 018-0336-3 \n\nReceived: 14 February 2018; Accepted: 25 May 2018; \nPublished online 23 July 2018. \n1. Dawber, M., Rabe, K. M. & Scott, J. F. Physics of thin-film ferroelectric oxides. Rev. Mod. Phys. 77, 1083–1130 (2005). \n2. Scott, J. F. Applications of modern ferroelectrics. Science 315, 954–959 (2007). \n3. Anderson, P. W. & Blount, E. I. Symmetry considerations on martensitic transformations: ‘ferroelectric’ metals? Phys. Rev. Lett. 14, 217–219 (1965). \n4. Shi, Y. et al. A ferroelectric-like structural transition in a metal. Nat. Mater. 12, 1024–1027 (2013). \n5. Benedek, N. A. & Birol, T. ‘Ferroelectric’ metals reexamined: fundamental mechanisms and design considerations for new materials. J. Mater. Chem. C 4, 4000–4015 (2016). \n6. Kim, T. H. et al. Polar metals by geometric design. Nature 533, 68–72 (2016). \n7. Sakai, H. et al. Critical enhancement of thermopower in a chemically tuned polar semimetal MoTe2. Sci. Adv. 2, e1601378 (2016). \n8. Rajapitamahuni, A., Hoffman, J., Ahn, C. H. & Hong, X. Examining graphene field effect sensors for ferroelectric thin film studies. Nano Lett. 13, 4374–4379 (2013). \n9. Huang, B. et al. Layer-dependent ferromagnetism in a van der Waals crystal down to the monolayer limit. Nature 546, 270–273 (2017). \n10.\t Mak, K. F., Lee, C., Hone, J., Shan, J. & Heinz, T. F. Atomically thin ${\\mathsf{M o S}}_{2}$ : a new direct-gap semiconductor. Phys. Rev. Lett. 105, 136805 (2010). \n11.\t Novoselov, K. S. et al. Two-dimensional gas of massless Dirac fermions in graphene. Nature 438, 197–200 (2005). \n12.\t Zhang, Y., Tan, Y. W., Stormer, H. L. & Kim, P. Experimental observation of the quantum Hall effect and Berry’s phase in graphene. Nature 438, 201–204 (2005). \n13.\t Bune, A. V. et al. Two-dimensional ferroelectric films. Nature 391, 874–877 (1998). \n14.\t Martin, L. W. & Rappe, A. M. Thin-film ferroelectric materials and their applications. Nat. Rev. Mater. 2, 16087 (2017). \n15.\t Shirodkar, S. N. & Waghmare, U. V. Emergence of ferroelectricity at a metal-semiconductor transition in a 1T monolayer of MoS2. Phys. Rev. Lett. 112, 157601 (2014). \n16.\t Liu, F. et al. Room-temperature ferroelectricity in $\\mathsf{C u l n P_{2}S_{6}}$ ultrathin flakes. Nat. Commun. 7, 12357 (2016). \n17.\t Fei, R. X., Kang, W. & Yang, L. Ferroelectricity and phase transitions in monolayer group-IV monochalcogenides. Phys. Rev. Lett. 117, 097601 (2016). \n18.\t Soluyanov, A. A. et al. Type-II Weyl semimetals. Nature 527, 495–498 (2015). \n19.\t Qian, X., Liu, J., Fu, L. & Li, J. Quantum spin Hall effect in two-dimensional transition metal dichalcogenides. Science 346, 1344–1347 (2014). \n20.\t Fei, Z. et al. Edge conduction in monolayer WTe2. Nat. Phys. 13, 677–682 (2017). \n21.\t Tang, S. et al. Quantum spin Hall state in monolayer 1T′-WTe2. Nat. Phys. 13, 683–687 (2017). \n22.\t Wu, S. et al. Observation of the quantum spin Hall effect up to 100 kelvin in a monolayer crystal. Science 359, 76–79 (2018). \n23.\t Fatemi, V. et al. Magnetoresistance and quantum oscillations of an electrostatically tuned semimetal-to-metal transition in ultrathin $\\mathsf{W T e}_{2}$ . Phys. Rev. B 95, 041410(R) (2017). \n24.\t Strukov, B. A. & Levanyuk, A. P. Ferroelectric Phenomena in Crystals: Physical Foundations 193–224 (Springer, Berlin, 1998). \n25.\t Catalan, G., Seidel, J., Ramesh, R. & Scott, J. F. Domain wall nanoelectronics. Rev. Mod. Phys. 84, 119–156 (2012). \n26.\t Chang, K. et al. Discovery of robust in-plane ferroelectricity in atomic-thick SnTe. Science 353, 274–278 (2016). \n27.\t Cochran, W. Crystal stability and the theory of ferroelectricity. Adv. Phys. 9, 387–423 (1960). \n28.\t Ali, M. N. et al. Large, non-saturating magnetoresistance in WTe2. Nature 514, 205–208 (2014). \n29.\t Zhao, Y. F. et al. Anisotropic magnetotransport and exotic longitudinal linear magnetoresistance in WTe2 crystals. Phys. Rev. B 92, 206803(R) (2015). \n30.\t Wu, Y. et al. Observation of Fermi arcs in the type-II Weyl semimetal candidate WTe2. Phys. Rev. B 94, 121113 (2016). \n\nAcknowledgements We thank J. Folk, E. Sajadi, A. Levanyuk, T. Birol and A. Andreev for substantial insights. D.H.C. and X.X. were supported by the US Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering, under awards DE-SC0002197 and DE-SC0018171, respectively. Synthesis efforts at ORNL were also supported by the same division of the Department of Energy. Z.Z. was partially supported by the CEM, and NSF MRSEC, under grant DMR-1420451. T.A.P. was supported by AFOSR FA9550-14-1-0277. Z.F., W.Z. and B.S. were supported by the above awards and also by NSF EFRI 2DARE 1433496 and NSF MRSEC 1719797. \n\nReviewer information Nature thanks L. Bartels, T. Birol and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\nAuthor contributions D.H.C. conceived the experiments; Z.Z. and J.Y. grew the crystals; W.Z., T.A.P., Z.F. and M.K.M. fabricated the devices; Z.F., W.Z., T.A.P. and B.S. performed the measurements; D.H.C., X.X., Z.F., W.Z. and T.A.P. analysed the results; and D.H.C., Z.F., T.A.P. and X.X. wrote the paper with comments from all authors. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nExtended data is available for this paper at https://doi.org/10.1038/s41586- 018-0336-3. \n\nReprints and permissions information is available at http://www.nature.com/ reprints. \n\nCorrespondence and requests for materials should be addressed to D.H.C. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\nPreparation and characterization of ${\\bf W T e}_{2}$ devices. We measured devices with four different layouts: (1) $\\mathrm{WTe}_{2}$ with graphite gates above and below (M1, B1, B4, T1); (2) bilayer $\\mathrm{WTe}_{2}$ with monolayer graphene as a top gate (B2); (3) a bilayer WTe2/graphene heterostructure (B3); and (4) a monolayer graphene device gated by few-layer $\\mathrm{WTe}_{2}$ (F1). In the following, we describe fabrication of the first type; the others are similar. \n\nFirst, graphite and h-BN crystals were mechanically exfoliated under ambient conditions onto substrates consisting of $285\\mathrm{-nm}$ thermal $\\mathrm{SiO}_{2}$ on highly p-doped silicon. Graphite flakes $2\\mathrm{-}6\\mathrm{nm}$ thick were chosen for the top and bottom gates and $5{-}30{\\cdot}\\mathrm{nm}$ -thick h-BN flakes (a layered electrical insulator free of trapped charges and dangling bonds) were chosen for the top and bottom dielectric31. The top and bottom parts were prepared separately using a polymer-based dry transfer technique32. For the bottom part, an h-BN flake was picked up on a polymer stamp and placed on the bottom graphite. After dissolving the polymer, Pt metal contacts (about $8\\mathrm{nm}$ ) were patterned on the h-BN by standard e-beam lithography, e-beam evaporation and lift-off. For the top part, the top graphite was picked up first, then the top h-BN. Both stacks were then transferred to an oxygen- and water-free glovebox. $\\mathrm{WTe}_{2}$ crystals were exfoliated inside the glovebox and flakes from monolayer to trilayer thickness were optically identified and quickly picked up with the top part; the stack was then completed by transferring onto the lower contacts/h-BN/ graphite stack before taking out of the glovebox. Finally, after dissolving the polymer, another step of e-beam lithography and metallization was used to define electrical bonding pads $\\mathrm{(Au/V)}$ connecting to the metal contacts and the top and bottom gates. Extended Data Fig. 1 shows schematics of the fabrication processes and optical and atomic force microscope (AFM) images of a typical bilayer $\\mathrm{WTe}_{2}$ device (B4). Estimate of the electric polarization. We use the following simplified model to estimate the spontaneous polarization of the bilayer $\\mathrm{WTe}_{2}$ from the measurements in Fig. 2b. We assume that $d_{\\mathrm{t}}=d_{\\mathrm{b}}\\gg d$ , where $d$ is the thickness of the $\\mathrm{WTe}_{2}$ that all conductors (bottom graphite gate, top graphene and bilayer $\\mathrm{WTe}_{2},$ ) are grounded and have infinite electronic compressibility, and that the areal polarization density $P$ is associated with two thin sheets of areal charge density $\\pm P/d$ separated by $d$ . Under these assumptions, when the polarization reverses there is no net flow of charge between the conductors and the $\\mathrm{WTe}_{2}$ remains neutral, and the potential profile between the gates is simply reversed when the polarization flips (Fig. 2d). By Gauss’s law \n\n$$\n\\varepsilon_{0}\\varepsilon_{\\mathrm{hBN}}E_{\\mathrm{t}}=\\varepsilon_{0}E_{\\mathrm{i}}+P/d\n$$ \n\nwhere $E_{\\mathrm{t}}$ is the electric field in the h-BN (equal on both sides because the bilayer is neutral) and $E_{\\mathrm{i}}$ is the field between the two charge sheets. Because the top graphene and the centre of the bilayer are both at zero potential, \n\n$$\n2E_{\\mathrm{t}}d_{\\mathrm{t}}+E_{\\mathrm{i}}d=0\n$$ \n\nFrom equations (1) and (2): \n\n$$\nE_{\\mathrm{t}}=\\frac{P}{\\varepsilon_{0}(2d_{\\mathrm{t}}+\\varepsilon_{\\mathrm{hBN}}d)}\n$$ \n\nThe change in $E_{\\mathrm{t}}$ when the polarization reverses is then $\\S E_{\\mathrm{t}}=2E_{\\mathrm{t}}=2P/$ $[\\varepsilon_{0}(2d_{\\mathrm{t}}+\\varepsilon_{\\mathrm{hBN}}d)]$ . With $d_{\\mathrm{t}}{\\approx}10\\mathrm{nm}$ and $d{\\approx}1\\ensuremath{\\mathrm{nm}}$ , the first term in the denominator dominates so $\\updelta E_{\\mathrm{t}}{\\approx}P/(\\varepsilon_{0}d_{\\mathrm{t}})$ and thus $P{\\approx}{\\varepsilon}_{0}d_{\\mathrm{t}}{\\updelta}E_{\\mathrm{t}}{=}{\\varepsilon}_{0}{\\updelta}V.$ . In reality, $d_{\\mathrm{b}}$ and $d_{\\mathrm{t}}$ can differ by a factor of up to three, the conductors have finite compressibility and the polarization charge is more spread out, which taken together introduce an extra numerical coefficient of order unity. \n\nRemoving parallel (parasitic) conduction through the graphene in device B2. In device B2 the graphene extends over regions with no $\\mathrm{WTe}_{2}$ underneath so that it acts as a uniform gate for the entire $\\mathrm{WTe}_{2}$ sheet. The quantity that we call $G_{\\mathrm{gr}}$ is the result of the following measurement, which maximizes sensitivity to only a central region of graphene above the $\\mathrm{WTe}_{2}$ . First, we ground two opposing contacts to the graphene and measure only the current that flows from the biased contact to the one opposite, as shown in Fig. 2a. However, because of finite contact resistance, a small portion of this current still flows through graphene not above the $\\mathrm{WTe}_{2}$ . To remove this parasitic current component, we set the $\\mathrm{WTe}_{2}$ voltage $V_{\\mathrm{{W}}}$ such that the graphene is at its Dirac-point minimum in the region over the $\\mathrm{WTe}_{2}$ Because the minimum is quite broad, the graphene over the $\\mathrm{WTe}_{2}$ is then insensitive to $V_{\\mathrm{b}}$ and the measured dependence on $V_{\\mathrm{b}}$ comes from only the parasitic component, which can then be subtracted out. Note that removing it has no effect on the magnitude of the hysteresis. \n\nIn Extended Data Fig. 4b, we illustrate this procedure at $220\\mathrm{K}$ . From the inset of Extended Data Fig. 4b, we determine that the graphene above the $\\mathrm{WTe}_{2}$ is at its Dirac point at $V_{\\mathrm{W}}{=}129\\mathrm{mV}.$ The red curve shows the conductance of the graphene $G_{\\mathrm{gr}}$ when $V_{\\mathrm{W}}{=}129\\mathrm{mV}$ the dependence on the back gate is from only the parasitic contribution. Conversely, in Fig. 2b and the blue curve in Extended Data Fig. 4b we measure $G_{\\mathrm{gr}}$ at $V_{\\mathrm{W}}{=}0~\\mathrm{mV},$ at which the graphene is most sensitive to changes in the electric field in the top h-BN $E_{\\mathrm{t}},$ yet also contains the parasitic conductance. The difference between these two curves (at $V_{\\mathrm{W}}{=}129~\\mathrm{mV}$ and $V_{\\mathrm{W}}{=}0~\\mathrm{mV}.$ ) is shown in black. The hysteresis remains, whereas the $\\mathbf{\\mathcal{}^{*}V}^{\\ }$ shape is mostly removed. The remaining small slope can be explained by the finiteness of the electronic compressibility of the bilayer $\\mathrm{WTe}_{2}$ . \n\nUsing Extended Data Fig. 4b we can estimate the ratio of the parasitic current to that flowing above the $\\mathrm{WTe}_{2}$ . The area with no $\\mathrm{WTe}_{2}$ has a h-BN thickness of $d_{\\mathrm{t}}+d_{\\mathrm{b}}=33$ nm between the graphene and bottom gate. The red curve (with a parasitic $V_{\\mathrm{b}}$ dependence) has a maximum slope of $\\mathrm{d}G_{\\mathrm{gr}}/\\mathrm{d}V_{\\mathrm{b}}=17\\upmu\\mathrm{S}\\mathrm{V}^{-1}$ or $\\mathrm{d}G_{\\mathrm{gr}}/$ $\\mathrm{\\Delta\\bar{d}E_{t}}{\\approx}560\\upmu\\mathrm{SV}^{-1}\\mathrm{nm}$ after taking into account the h-BN thickness. From the inset curve, using voltage $V_{\\mathrm{{W}}}$ applied to the $\\mathrm{WTe}_{2}$ for gating (with 8 nm h-BN) gives $\\mathrm{d}G_{\\mathrm{gr}}/\\mathrm{d}E_{\\mathrm{t}}{=}12,300\\upmu\\mathrm{SV}^{-1}\\mathrm{nm}$ . Thus, the parasitic component is only about $5\\%$ of the total current. \n\nData availability. The data presented in this paper and that support the findings of this study are available from the corresponding author on reasonable request. \n\n31.\t Dean, C. R. et al. Boron nitride substrates for high-quality graphene electronics. Nat. Nanotechnol. 5, 722–726 (2010). \n32.\t Zomer, P. J., Guimaraes, M. H. D., Brant, J. C., Tombros, N. & van Wees, B. J. Fast pick up technique for high quality heterostructures of bilayer graphene and hexagonal boron nitride. Appl. Phys. Lett. 105, 013101 (2014). \n\n![](images/c7c1ab498d22d588ba2019947453aee2108bf02219f3ded7413706e2c3d4378b.jpg) \nExtended Data Fig. 1 | Bilayer ${\\bf W T e}_{2}$ device. a, Essential steps in device fabrication. b, Optical image of device B4. The red dashed line outlines the bilayer flake. Scale bar, $5\\upmu\\mathrm{m}$ . c, AFM topography image of the central \nregion in b. Scale bar, $2\\upmu\\mathrm{m}$ . d, Line cut along the white dashed line in c. The step height matches the expected bilayer thickness, about $1.4\\mathrm{nm}$ . \n\n![](images/5bd876f92805ae6839bff18540dc5582141b933aab398af39b277ed0b5c7f183.jpg) \nExtended Data Fig. 2 | Thick $\\mathbf{WTe}_{2}$ used as a gate. a, Optical image of device F1, in which a thick ( $\\mathrm{{\\dot{8}n m}})$ $\\mathrm{WTe}_{2}$ flake under 24-nm h-BN is used as a gate for a top graphene sheet. Scale bar, $10\\upmu\\mathrm{m}$ . b, Schematic crosssection of the device. c, Two-terminal conductance $G$ of the graphene \n\nas a function of voltage $V_{\\mathrm{g}}$ applied to the $\\mathrm{WTe}_{2}$ flake. There is no sign of switching or bistability at any temperature, indicating that no polarization reversal occurs on the $\\mathrm{WTe}_{2}$ surface for fields of up to $E_{\\perp}{\\approx}0.\\bar{1}25\\mathrm{Vnm}^{-1}$ . Inset, close-ups of the graphene Dirac point at $4\\mathrm{K}$ and $300\\mathrm{K}$ . \n\n![](images/2f05c3be51780c25a143422ec72fe36b1c421dbbcf2128a7726bb63424bb4802.jpg) \nExtended Data Fig. 3 | Switching of an additional bilayer device. a, Conductance $G$ versus perpendicular electric field $E_{\\perp},$ , at temperatures from $4\\mathrm{K}$ to $300\\mathrm{K}$ and a gate doping level of $n_{\\mathrm{e}}{=}{-}4\\times10^{12}\\mathrm{cm}^{-2}$ , \nfor device B4. b, Conductance difference $\\Delta G$ between the two sweep directions of $V_{\\mathfrak{b}}$ at $200\\mathrm{K},$ as plotted in Fig. 3d for device B1. \n\n![](images/1c07d3529504aedeed018475448906d4607715a9cdc6ac47b1295f4a6c12ed79.jpg) \nExtended Data Fig. 4 | Additional transport measurements and removal of parasitic effects in the polarization measurements. a, Conductance $G$ versus $V_{\\mathfrak{b}}$ for the bilayer $\\mathrm{WTe}_{2}$ in device B2, measured with the top graphene grounded. The hysteresis occurs in exactly the same range of $E_{\\perp}$ as it does in the graphene conductance in Fig. 2b. Note that both $n_{\\mathrm{e}}$ and $E_{\\perp}$ change when $V_{\\mathfrak{b}}$ is swept. The inset shows a schematic configuration of the measurement. b, Graphene conductance $G_{\\mathrm{gr}}$ at $220\\mathrm{K}$ as a function \n\nof $V_{\\mathfrak{b}}$ with the voltage $\\boldsymbol{V_{\\mathrm{W}}}$ on the bilayer $\\mathrm{WTe}_{2}$ at $0\\mathrm{mV}$ (blue) and $129\\mathrm{mV}$ (red). The black curve is the difference between the blue and red curves. This subtraction removes most of the $V_{\\mathrm{b}}$ dependence of the parasitic current that flows through the top graphene, which is not screened from the bottom gate by the $\\mathrm{WTe}_{2}$ . Inset, graphene conductance showing the minimum at $V_{\\mathrm{{W}}}{=}129~\\mathrm{{mV}}.$ \n\n![](images/f43ec6ed78cacb1a1767384762719e9c7b32521f5264c0cf1ffe9920919f274e.jpg) \nExtended Data Fig. 5 | Graphene/bilayer ${\\bf W T e}_{2}$ heterostructure showing both $5\\mathrm{K}$ and room temperature (300 K), implying that the polarization of hysteresis up to room temperature. a, b, Device image (a) and schematic the $\\mathrm{WTe}_{2}$ is still present in this hybrid structure. cross-section (b). c, The two-terminal conductance $G$ shows bistability at \n\n![](images/48fcacb7418f061ec654e8ae42f6d968f2025a04a7b30a35b0eb3bac606326dc.jpg) \nExtended Data Fig. 6 | Length-dependent ferroelectric behaviour in trilayer ${\\bf W T e}_{2}$ for temperatures from $_{2\\mathbf{K}}$ to ${\\bf300~K}$ . All measurements are performed at $V_{\\mathrm{b}}=0$ in two-terminal configurations, where the contact separation ranges from $200\\mathrm{nm}$ to $1{,}490\\mathrm{nm}$ . For all devices mentioned above and in the main text, the contacts are separated by $1{-}2\\upmu\\mathrm{m}$ . However, if we reduce the contact separation to a few hundred nanometers \n1 $270\\mathrm{nm})$ , the metal contacts prevent the polarization from switching. For a contact separation $(L)$ of more than $480\\mathrm{nm}$ , the transfer characteristics show similar hysteric behaviour as in Fig. 1c, d and Extended Data Fig. 3a. Because $V_{\\mathfrak{b}}$ is always grounded, $E_{\\perp}$ and $n_{\\mathrm{e}}$ change simultaneously as we sweep $V_{\\mathrm{t}}$ . \n\nExtended Data Table 1 | Thickness of h-BN dielectrics and corresponding areal capacitances for the $\\ensuremath{\\mathsf{W T e}}_{2}$ devices \n\n\n
Device labelWTe2top hBN (nm)bottom hBN (nm)Ct (1×10-F/m²)Cb (1×10-F/m²)
M1 monolayer6285.91.3
B1bilayer12203.01.8
B2bilayer8254.41.4
B3bilayerNA24NA1.5
B4bilayer10213.51.7
T1trilayer5.5236.41.1*
F18 nm24NA1.5NA
\n\nWe define the gate-induced density imbalance to be $n_{\\mathrm{e}}{=}(C_{\\mathrm{f}}V_{\\mathrm{t}}{+}C_{\\mathrm{b}}V_{\\mathrm{b}})/{e}$ and $\\begin{array}{r}{{\\cal E}_{\\bot}=(-C_{\\mathrm{t}}V_{\\mathrm{t}}+C_{\\mathrm{b}}V_{\\mathrm{b}})/(2\\varepsilon_{\\mathrm{h}\\cdot\\mathrm{BN}}\\varepsilon_{0}),}\\end{array}$ where the geometric areal capacitances are $C_{\\mathrm{t}}=\\varepsilon_{\\mathsf{h B N}}\\varepsilon_{0}/d_{\\mathrm{t}}$ and $C_{\\mathrm{b}}=\\varepsilon_{\\mathrm{hBN}}\\varepsilon_{0}/d_{\\mathrm{b}}$ $\\varepsilon_{\\mathsf{h B N}}\\approx4$ is th dielectric constant of h-BN, and $d_{\\mathrm{t}}$ and $d_{\\mathrm{b}}$ are the thicknesses of the top and bottom h-BN flakes, respectively. All thicknesses were obtained from AFM images. In device B3, the WTe2 flake is directly under the top graphene (no top h-BN). In device F1, the thick WTe2 is directly on the bottom graphite (no bottom h-BN). \\*For device T1, there is no bottom graphite; instead, we used the metallic silicon substrate as the bottom gate, the areal capacitance then being $C_{\\mathsf{b}}=\\varepsilon_{0}/(d_{\\mathsf{b}}/\\varepsilon_{\\mathsf{h B N}}+d_{{\\mathsf{S i O2}}}/\\varepsilon_{{\\mathsf{S i O2}}})$ . We did not make a four-layer device so we do not know at exactly what thickness polarization switching ceases to be possible. " + }, + { + "id": "10.1038_s41563-018-0040-6", + "DOI": "10.1038/s41563-018-0040-6", + "DOI Link": "http://dx.doi.org/10.1038/s41563-018-0040-6", + "Relative Dir Path": "mds/10.1038_s41563-018-0040-6", + "Article Title": "Electric-field switching of two-dimensional van der Waals magnets", + "Authors": "Jiang, SW; Shan, J; Mak, KF", + "Source Title": "NATURE MATERIALS", + "Abstract": "Controlling magnetism by purely electrical means is a key challenge to better information technology(1). A variety of material systems, including ferromagnetic (FM) metals(2-4), FM semiconductors(5), multiferroics(6-8) and magnetoelectric (ME) materials(9,10), have been explored for the electric-field control of magnetism. The recent discovery of two-dimensional (2D) van der Waals magnets(11,12) has opened a new door for the electrical control of magnetism at the nullometre scale through a van der Waals heterostructure device platform(13). Here we demonstrate the control of magnetism in bilayer CrI3, an antiferromagnetic (AFM) semiconductor in its ground state(12), by the application of small gate voltages in field-effect devices and the detection of magnetization using magnetic circular dichroism (MCD) microscopy. The applied electric field creates an interlayer potential difference, which results in a large linear ME effect, whose sign depends on the interlayer AFM order. We also achieve a complete and reversible electrical switching between the interlayer AFM and FM states in the vicinity of the interlayer spin-flip transition. The effect originates from the electric-field dependence of the interlayer exchange bias.", + "Times Cited, WoS Core": 742, + "Times Cited, All Databases": 810, + "Publication Year": 2018, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000430942800015", + "Markdown": "# Electric-field switching of two-dimensional van der Waals magnets \n\nShengwei Jiang1,2, Jie Shan1,2,3\\* and Kin Fai Mak1,2,3\\* \n\nControlling magnetism by purely electrical means is a key challenge to better information technology1. A variety of material systems, including ferromagnetic (FM) metals2–4, FM semiconductors5, multiferroics6–8 and magnetoelectric (ME) materials9,10, have been explored for the electric-field control of magnetism. The recent discovery of two-dimensional (2D) van der Waals magnets11,12 has opened a new door for the electrical control of magnetism at the nanometre scale through a van der Waals heterostructure device platform13. Here we demonstrate the control of magnetism in bilayer $\\left.\\mathsf{c r l}_{3},\\right.$ an antiferromagnetic (AFM) semiconductor in its ground state12, by the application of small gate voltages in field-effect devices and the detection of magnetization using magnetic circular dichroism (MCD) microscopy. The applied electric field creates an interlayer potential difference, which results in a large linear ME effect, whose sign depends on the interlayer AFM order. We also achieve a complete and reversible electrical switching between the interlayer AFM and FM states in the vicinity of the interlayer spin-flip transition. The effect originates from the electric-field dependence of the interlayer exchange bias. \n\nThe recent discovery of 2D van der Waals magnetic semiconductors, such as $\\mathrm{CrI}_{3}$ (ref. 12) and ${\\mathrm{Cr}}_{2}{\\mathrm{Ge}}_{2}{\\mathrm{Te}}_{6}$ (ref. 11), has attracted much attention. These materials provide unprecedented opportunities to study magnetism in the 2D limit and engineer interface phenomena through van der Waals heterostructures13,14. In particular, $\\mathrm{CrI}_{3}$ is a model Ising ferromagnet with strong out-of-plane anisotropy15,16, whose magnetic properties remain robust down to the monolayer limit12. The low-temperature bulk structure of $\\mathrm{CrI}_{3}$ is rhombohedral15,16, that is, an ABCABC… stack of $\\mathrm{CrI}_{3}$ monolayers. In each monolayer, the Cr atoms form a honeycomb structure in an edgesharing octahedral coordination by six I atoms (Fig. 1a). Below a Curie temperature of 61 K (refs 15–17), the magnetic moment of ${\\mathrm{Cr}}^{3+}$ cations is aligned within each monolayer and between the layers in the out-of-plane direction by superexchange interactions through the $\\mathrm{I^{-}}$ anions15,16. Intriguing layer-dependent magnetic order was reported recently in atomically thin $\\operatorname{CrI}_{3}$ films12; whereas monolayer and trilayer $\\mathrm{CrI}_{3}$ remain FM, bilayer $\\operatorname{CrI}_{3}$ becomes AFM with FM monolayers coupled antiferromagnetically (Fig. 1b). In contrast to FM monolayers and trilayers, the AFM bilayers present a unique possibility for an efficient electrical control of magnetism through the linear ME effect18. The linear ME effect (the induction of the magnetization (polarization) by an electric (magnetic) field) requires the breaking of both time-reversal and spatial-inversion symmetries1,19–21. The latter is satisfied only in AFM bilayers given the magnetic symmetry15,18,19, although spatial inversion is a fundamental crystal symmetry for $\\mathrm{CrI}_{3}$ of any thickness in the rhombohedral structure15. \n\nWe fabricated dual-gate bilayer $\\mathrm{CrI}_{3}$ field-effect devices to investigate the electric-field effect on its magnetic order (Methods). In short, $\\operatorname{CrI}_{3}$ bilayers were exfoliated from bulk crystals (Supplementary Section 1 gives the characterization) and encapsulated in hexagonal boron nitride (hBN) thin films by the layerby-layer dry-transfer method22,23. Few-layer graphene was used as both the top- and back-gate electrodes and contact electrodes. Schematics and optical images of representative devices are shown in Supplementary Section 2. These devices, with a total thickness of ${\\sim}40\\mathrm{nm}$ , allowed the application of giant out-of-plane electric fields $\\begin{array}{r}{(E\\approx1\\mathrm{V}\\mathrm{nm}^{-1},}\\end{array}$ ) by moderate gate voltages. The dual-gate structure also enables an independent control of the net doping density and electric field on bilayer $\\mathrm{CrI}_{3}$ (ref. 24). Here we consider the electricfield effect only. To probe the magnetic order, we employed MCD microscopy with a HeNe laser at $633\\mathrm{nm}$ (Methods). The photon energy was chosen to be near the absorption edge in $\\mathrm{CrI}_{3}$ (ref. 12) to increase the detection sensitivity. The MCD signal is proportional to the sample’s magnetization $M$ \n\nFigure 1c illustrates the MCD signal of bilayer $\\mathrm{CrI}_{3}$ as a function of the out-of-plane magnetic field $\\mu_{\\scriptscriptstyle0}H$ under zero electric field ( $\\langle\\mu_{0}$ is the vacuum permeability). The observed dependence is largely consistent with the reported result12. Namely, at low temperatures no MCD signal was observed for small magnetic fields, and the bilayer is in the AFM phase. A sharp rise in the MCD signal, which corresponds to a spin-flip transition into the FM phase, was observed at a moderate critical field of $\\mu_{0}H_{\\scriptscriptstyle\\mathrm{C}}\\approx0.4–0.5\\mathrm{T}$ due to the relatively weak interlayer-exchange interaction. The occurrence of hysteresis on forward and backward sweeps of the magnetic field suggests a first-order nature of the transition at ${}^{4\\mathrm{K}}{}_{:}$ similar to the behaviour in bulk ${\\mathrm{FeCl}}_{2}$ (ref. 25), a known interlayer antiferromagnet with FM monolayers15,25. There are small discrepancies between our results and a report of the absence of hysteresis and a slightly higher critical field12. The potential origins for this are discussed in Supplementary Section 3. The result here also suggests that in the AFM phase, bilayer $\\mathrm{CrI}_{3}$ has two distinct spin configurations12, which are timereversal copies of one another and can be prepared by raising the magnetic field above $\\mu_{\\scriptscriptstyle0}H_{\\scriptscriptstyle\\mathrm{C}}$ (see below for direct experimental evidence). At higher temperatures, the spin-flip transition broadens and occurs at lower critical fields. The contour plot in Fig. 1d for the MCD signal as a function of magnetic field and temperature clearly shows the distinct FM, AFM and paramagnetic (PM) phases. The dashed line is the temperature dependence of the critical field for the spin-flip transition and the vertical bars denote the transition width (Supplementary Section 4 gives an analysis). The critical field drops to zero around $T_{\\mathrm{c}}{\\approx}57\\mathrm{k}$ (vertical dotted line). Three devices were examined in this study. Small sample-to-sample variations were observed, but the qualitative dependence of the MCD on temperature, magnetic field and electric field is practically identical for all the devices (Supplementary Sections $5{-}8$ give more details and Supplementary Section 11 gives the results for other devices). \n\n![](images/cb4748a9dcd7b0ea796711e9011126fb9b4e8c640aa9c1b83bf451af6b77919a.jpg) \nFig. 1 | Crystal structure and magnetic phase diagram of bilayer $\\mathsf{C r l}_{3}$ . a, Top view of monolayer $\\mathsf{C r l}_{3},$ where Cr atoms (red balls) form a honeycomb structure in an edge-sharing octahedral coordination by six I atoms (blue balls), and side view of bilayer $\\mathsf{C r l}_{3}$ of the rhombohedral stacking order. b, AFM bilayer $\\mathsf{C r l}_{3}$ consists of two FM monolayers with an AFM interlayer coupling. The net magnetization is zero. A potential difference between the two layers under a vertical electric field E leads to a non-zero net magnetization. c, MCD signal as a function of applied magnetic field at different temperatures (device no. 3). Black and red lines show the forward and backward sweeps of the field, respectively. Insets (top) depict the magnetic ground states of bilayer $\\mathsf{C r l}_{3}$ under different magnetic fields. d, H–T phase diagram of the magnetic order in bilayer $\\mathsf{C r l}_{3}$ determined from the magnitude of the MCD. The dashed line is the temperature dependence of the critical magnetic field of the spin-flip transition with the transition width denoted by the vertical bars (Supplementary Section 4 gives an analysis). The dotted line indicates the critical temperature for the magnetic transition. \n\nFigure 2 shows the effect of an externally applied electric field on the magnetic properties of bilayer $\\operatorname{CrI}_{3}$ . Three interesting features are observed in the magnetic-field dependence of the MCD signal in Fig. 2a. First, in the AFM phase, the electric field $E$ induces a constant magnetization that increases with $E$ and has hysteresis under magnetic field sweeps. Magnetization as large as ${\\sim}30\\%$ of the saturation magnetization $M_{0}$ was observed. Second, the spin-flip transition is pushed out to larger magnetic fields when $E$ is applied. Finally, in the FM phase, $M_{0}$ is nearly independent of $E$ . These observations are summarized in Fig. $^{2\\mathrm{b},\\mathrm{c}}$ . Figure $2c$ shows that the critical magnetic fields (for both forward and backward sweeps) increase with $E$ and reach a maximum at around $0.5\\mathrm{Vnm^{-1}}$ . Figure 2b illustrates the electric-field induced change in sheet magnetization $\\Delta M$ and normalized magnetization $\\Delta M/M_{0}$ as a function of the applied electric field. The magnetization was calculated from the MCD signal by assuming that each ${\\mathrm{Cr}}^{3+}$ cation carries a magnetic moment of ${\\sim}3\\mu_{\\mathrm{B}}$ $\\mathrm{{'}}\\mu_{\\mathrm{{B}}}$ denoting the Bohr magneton) in pristine samples under saturation15,16 (Methods). In the FM phase, $\\Delta M$ (measured at 1 T) is negligible under small electric fields and increases in magnitude nonlinearly with $E$ . In contrast, in the AFM phase a substantially larger $\\Delta M$ (measured at $0\\mathrm{T}\\cdot$ ) is observed, which depends linearly on $E$ and changes sign at $E{=}0\\mathrm{V}\\mathrm{nm}^{-1}$ (the broad lines in Fig. 2b are linear fits). There are two magnetization values of opposite sign for any non-zero $E$ . They arise from the two AFM configurations, as mentioned above. We can quantify the effect using a linear volumetric ME coefficient $\\alpha_{z z},$ defined as $\\mu_{0}\\varDelta M/2t\\equiv\\alpha_{z z}E$ in the International System of units1,19–21,26. Here $t{\\approx}0.7\\mathrm{nm}$ is the interlayer separation in bilayer $\\operatorname{CrI}_{3}$ (refs 15,16). We obtain $\\alpha_{z z}{\\approx}110\\mathrm{ps}\\mathrm{m}^{-1}$ for AFM bilayers at $4\\mathrm{K}$ , which can also be given as $\\alpha_{z z}/\\mu_{0}\\approx90~\\upmu\\mathrm{S}$ or $c\\alpha_{z z}\\approx0.034$ $\\dot{\\mathbf{\\zeta}}_{c}$ denoting the speed of light in vacuum) in non-rationalized Gaussian units. The observed effect is substantially larger than that in many single-phase materials (the largest known value is $735\\mathrm{psm^{-1}}$ in $\\mathrm{TbPO_{4}}$ at $1.5\\mathrm{K}$ (refs $^{26,27})$ ). \n\nTo compare the ME response of bilayer $\\mathrm{CrI}_{3}$ in different phases, we compute the ratio $\\mu_{0}\\varDelta M/E$ using the experimental $M(H)$ results at $0.81\\mathrm{Vnm^{-1}}$ and $0\\mathrm{Vnm^{-1}}$ (Fig. 3). In the AFM phase, the ratio is just the linear sheet ME coefficient, which does not depend on magnetic field. In the FM phase, the ME response is substantially smaller. A large enhancement is observed near the critical magnetic field. This arises from the electric-field dependence of $H_{\\mathrm{C}}$ (Fig. 2c). The application of an electric field can tip the balance between the AFM and FM phases and cause a large change in the sample’s magnetization due to the spin-flip transition. As we demonstrate below, such an enhanced ME response could be employed for the electrical switching of magnetic order. In Fig. 3, we also include the result of a control experiment on monolayer $\\mathrm{CrI}_{3}$ . The behaviour is diametrically different with a negligible ME response in monolayer $\\mathrm{CrI}_{3}$ . Additional data at varying temperatures are included in Supplementary Sections 8 and 13 for bilayer and monolayer $\\mathrm{CrI}_{3},$ respectively. \n\nThe observed ME effect in bilayer $\\mathrm{CrI}_{3}$ is consistent with the material’s magnetic symmetry19. The time-reversal symmetry is broken in both the FM and AFM phases. In the FM phase, the spatial-inversion symmetry is present15 so that no linear ME effect is allowed. By the same token, neither is the effect allowed in the centrosymmetric monolayer $\\mathrm{CrI}_{3}$ . (A nonlinear ME effect can still occur20, which is, indeed, observed in Fig. 2b under large electric fields.) In the AFM phase, however, the spatial-inversion symmetry is broken (Fig. 1b) and a non-zero linear ME tensor $\\upalpha$ is allowed18,28. In particular, the $\\alpha_{z z}$ component is directly proportional to the AFM order parameter9,28–30 $M_{\\mathrm{t}}-M_{\\mathrm{b}}$ $\\cdot M_{\\mathrm{t}}$ and $M_{\\mathrm{b}}$ denote the sheet magnetizations of the top and bottom layer, respectively). As there are two distinct configurations of the AFM state with opposite AFM order parameters (Fig. 1c, inset), two $\\alpha_{z z}$ values of opposite sign are expected. This is a general phenomenon for AFM $\\mathrm{\\bar{MEs}}^{28}$ . The observation of two $\\alpha_{z z}$ values of opposite sign is thus an experimental verification of two distinct AFM configurations in bilayer $\\operatorname{CrI}_{3}$ . As discussed above, these two AFM configurations can be prepared by raising the magnetic field above $\\mu_{\\scriptscriptstyle0}H_{\\scriptscriptstyle\\mathrm{C}}$ (Fig. 1c). They can also be prepared by cooling the samples from above $T_{\\mathrm{{C}}}$ under both magnetic and electric fields, that is, ME annealing9 (Supplementary Section 9). The microscopic mechanism for the ME effect in bilayer $\\mathrm{CrI}_{3},$ however, remains unknown. A plausible mechanism involves charge transfer for (unintentionally) doped samples18, for instance, from the top to the bottom layer under an up electric field $E$ (Fig. 1b). The intralayer FM exchange coupling means the transferred particles would align their spins parallel to the existing ones to minimize the system’s total free energy. The AFM bilayer thus acquires an up net magnetization, which corresponds to a positive $\\alpha_{z z}.$ For the second AFM configuration with a reversed AFM order parameter, the net magnetization would point down, which corresponds to a negative $\\alpha_{z z}$ This is consistent with our experiment. We estimate the magnitude of the ME coefficient based on this simple picture by assuming that each transferred electron carries a magnetic moment of $\\mu_{\\mathrm{{B}}}$ (Supplementary Section 12). Under an applied field of $0.81\\mathrm{Vnm^{-1}}$ , the net carrier density in bilayer $\\operatorname{CrI}_{3}$ is $\\sim10^{14}~\\mathrm{cm}^{-2}$ from the parallel-plate capacitance model. This gives rise to a volumetric ME coefficient of ${\\sim}10\\mathrm{ps}\\mathrm{m}^{-1}$ , which is smaller but compatible with the experimental result. Future studies, including other effects, are needed to understand the phenomenon fully. \n\n![](images/b67e9c9f800bf0bc27fe965f1bf4df72964d1589d6aa2654c2d0fdb4f6fa047e.jpg) \nFig. 2 | Linear ME effect in AFM bilayer $\\mathsf{\\pmb{C r l}}_{3}$ . a, MCD signal as a function of magnetic field under representative electric fields at $4\\mathsf{K}$ (device no. 1). b, Relative and absolute changes in the sheet magnetization $(\\Delta M/M_{\\mathrm{0}}$ and $\\Delta M,$ respectively) as a function of applied electric field measured under a fixed magnetic field at $0\\mathsf{T}$ (open red and black symbols for systems prepared under 1 T and $-17,$ respectively) and at 1 T (filled symbols). The broad lines are linear fits to the data at 0 T. c, Critical magnetic fields for the spin-flip transition for forward (black symbols) and backward (red symbols) sweeps of the magnetic field as a function of the applied electric field. The vertical bars represent the transition width (Supplementary Section 4 gives an analysis). The blue line is the prediction of equation (1). \n\nThe observed electric-field dependence of the critical magnetic field (Fig. 2c) for the spin-flip transition from the AFM to the FM phase is more complex. Several effects could contribute to it. The electric field can lower the free energy of the AFM phase through the ME effect9,20 and lead to a higher critical field for the spin-flip transition. It can also change the interlayer-exchange coupling and the free energies through the electron-wavefunction overlap in the vertical direction. Furthermore, the electric field can change the magnetic anisotropy, for instance, through the Rashba spin–orbit interaction18 or a change in the electron occupancy in the $3d$ orbitals3,4. As discussed elsewhere25, magnetic anisotropy can act as an energy barrier for the spin-flip transition at $H_{\\mathrm{{C}}},$ which leads to hysteresis. Below we evaluate the importance of the ME effect in the spin-flip transition. First, at zero electric field, the free energy per unit area in the zero-temperature limit can be expressed as $F=2F_{0}{-}J$ in the AFM phase, and $F{=}2F_{0}{+}J{-}{\\mu}_{0}M_{0}(H{-}M_{0}/2t)$ in the FM phase (for $M_{0}>0$ ) (ref. 9). Here $F_{0}$ denotes the free energy of the constituent monolayer, which is identical in the FM and AFM phases; $J(>0)$ is the interlayer-exchange constant, which adds to the free energy $+J$ in the FM phase because the spins are parallel, and $-J$ in the AFM phase because the spins are antiparallel; the magnetic energy under an applied vertical magnetic field $\\mu_{\\scriptscriptstyle0}H$ is non-zero only in the FM phase. (Higher order terms in $H$ have been ignored; Supplementary Section 7 gives the analysis for finite temperatures). The critical field is thus determined as $\\begin{array}{r}{\\dot{\\mu}_{0}H_{\\mathrm{C}}=\\frac{2J+\\mu_{0}M_{0}^{2}/2\\dot{t}}{M_{0}}}\\end{array}$ by setting the two free energies equal. The expression is reminiscent of that for the exchange bias field at the FM–AFM interfaces9,31. In fact, the critical field here can be regarded as the exchange bias field provided by one of the FM monolayers. From the measured critical field value, we estimate the exchange-coupling energy to be $J{\\approx}25{\\upmu}\\mathrm{m}^{-2}$ . When an electric field $E$ is turned on, the AFM phase acquires an additional ME energy ${\\approx}-\\alpha_{z z}E H$ (refs $^{9,20}$ ), which leads to a new critical magnetic field: \n\n![](images/33a7343f3b8b0b868578a8c1628f16d2552f20215fb6389f56291171a8cf390e.jpg) \nFig. 3 | ME response of bilayer (2L) and monolayer (1L) $\\mathsf{\\pmb{C r l}}_{3}$ . For bilayer $\\mathsf{C r l}_{3}$ (device no. 1), the ME response was obtained by subtracting $M-H$ curves under $0.8\\mathsf{V}\\mathsf{n m}^{-1}$ and $0\\vee\\mathsf{n m}^{-1}$ . This was then normalized by the electric-field difference. Black and red solid lines are the forward and backward sweeps of the magnetic field, respectively. For monolayer $\\mathsf{C r l}_{3}$ (symbols), this was obtained by subtracting $M-H$ curves under $0.34\\vee\\mathsf{n m}^{-1}$ and $-0.34\\mathsf{V}\\mathsf{n m}^{-1}$ . All the measurements were performed at $4\\mathsf{K}$ \n\n$$\n\\mu_{0}H_{\\scriptscriptstyle\\mathrm{C}}=\\frac{2J+\\mu_{0}M_{0}^{2}/2t}{M_{0}-\\alpha_{z z}E/\\mu_{0}}\n$$ \n\nThe prediction of equation (1) using the measured values for the parameters is shown in Fig. $2c$ as a blue line. The simple model captures the correct magnitude for the electric-field-dependent $H_{\\mathrm{{C}}}$ . The ME effect thus plays a major role in the critical field for the spinflip transition. However, more careful measurements with variable doping density and models that include other effects, such as the electric-field-induced change in the interlayer coupling energy and/ or magnetic anisotropy, are needed to understand this problem fully for future studies. \n\nFinally, we demonstrate a pure electrical switching of magnetic order in bilayer $\\operatorname{CrI}_{3}$ by taking advantage of the large ME response near the critical field. Figure 4a shows the sheet magnetization $M$ and the normalized magnetization $M/M_{0}$ of bilayer $\\operatorname{CrI}_{3}$ as a function of forward and backward sweeps of the electric field under two fixed magnetic fields $(\\pm0.44\\mathrm{T}$ (Supplementary Section 10 gives the results under other magnetic fields). Remarkably, the electric field switches the material from a ferromagnet $(<0.2\\mathrm{V}\\mathrm{nm}^{-1})$ to an antiferromagnet $(>0.7\\mathrm{Vnm^{-1}})$ ) and the magnetization varies from ${\\sim}0.8M_{0}$ to ${\\sim}0.2M_{0}$ . The hysteresis, again, indicates the first-order nature of the transition25. In Fig. 4b, we further show that the switching operation can be repeated many times by turning the electric field on and off periodically. The magnetization is seen to follow the applied electric field with no sign of fatigue. \n\nIn conclusion, a large linear ME effect has been observed in the AFM bilayer $\\mathrm{CrI}_{3}$ , which enables the electrical control of magnetism in the material. Near the AFM–FM spin-flip transition, a reversible electrical switching of magnetic order has been demonstrated using a field-effect-device geometry. Our results demonstrate the unique potential of 2D van der Waals magnets for electrically controlled nonvolatile memory and spintronic and valleytronic device applications through proximity coupling in van der Waals heterostructures13,14. \n\n![](images/e2b2738905dbfeeb9324647ef8e5150f2366c9c0d292eb52c8e24fd1bfb6edae.jpg) \nFig. 4 | Electrical switching of the magnetic order in bilayer $\\mathsf{C r l}_{3}$ . a, Magnetization $M$ and normalized magnetization by the saturation magnetization ${M}/{M_{\\mathrm{0}}}$ as a function of an applied electric field E under fixed magnetic fields near the critical value at $4\\mathsf{K}$ (device no. 1). The top and bottom panels are measurements at $0.44\\intercal$ and $-0.44\\top,$ respectively. Black and red symbols are the forward and backward sweeps of $E,$ respectively. Insets depict the magnetic states under different magnetic and electric fields. b, Repeated switching of the magnetization (top panel) by the application of a periodic electric field (bottom panel) under a constant magnetic field of $0.44\\intercal.$ . \n\n# Methods \n\nMethods, including statements of data availability and any associated accession codes and references, are available at https://doi. org/10.1038/s41563-018-0040-6. \n\nReceived: 5 September 2017; Accepted: 12 February 2018; Published online: 12 March 2018 \n\n# References \n\n1.\t Matsukura, F., Tokura, Y. & Ohno, H. Control of magnetism by electric fields. Nat. Nanotech. 10, 209–220 (2015). \n2.\t Weisheit, M. et al. Electric field-induced modification of magnetism in thin-film ferromagnets. Science 315, 349–351 (2007). \n3.\t Maruyama, T. et al. Large voltage-induced magnetic anisotropy change in a few atomic layers of iron. Nat. Nanotech. 4, 158–161 (2009). \n4. Wang, W.-G., Li, M., Hageman, S. & Chien, C. L. Electric-field-assisted switching in magnetic tunnel junctions. Nat. Mater. 11, 64–68 (2012). \n5.\t Ohno, H. et al. Electric-field control of ferromagnetism. Nature 408, 944–946 (2000). \n6.\t Chu, Y.-H. et al. Electric-field control of local ferromagnetism using a magnetoelectric multiferroic. Nat. Mater. 7, 478–482 (2008). \n7. Heron, J. T. et al. Electric-field-induced magnetization reversal in a ferromagnet–multiferroic heterostructure. Phys. Rev. Lett. 107, 217202 (2011). \n8.\t Wu, S. M. et al. Reversible electric control of exchange bias in a multiferroic field-effect device. Nat. Mater. 9, 756–761 (2010). \n9.\t Borisov, P., Hochstrat, A., Chen, X., Kleemann, W. & Binek, C. Magnetoelectric switching of exchange bias. Phys. Rev. Lett. 94, 117203 (2005). \n10.\tHe, X. et al. Robust isothermal electric control of exchange bias at room temperature. Nat. Mater. 9, 579–585 (2010). \n11.\tGong, C. et al. Discovery of intrinsic ferromagnetism in two-dimensional van der Waals crystals. Nature 546, 265–269 (2017). \n12.\tHuang, B. et al. Layer-dependent ferromagnetism in a van der Waals crystal down to the monolayer limit. Nature 546, 270–273 (2017). \n13.\tGeim, A. K. & Grigorieva, I. V. Van der Waals heterostructures. Nature 499, 419–425 (2013). \n14.\tZhong, D. et al. Van der Waals engineering of ferromagnetic semiconductor heterostructures for spin and valleytronics. Sci. Adv. 3, 1603113 (2017). \n15.\tMcGuire, M. A. Crystal and magnetic structures in layered, transition metal dihalides and trihalides. Crystals 7, 121 (2017). \n16.\t McGuire, M. A., Dixit, H., Cooper, V. R. & Sales, B. C. Coupling of crystal structure and magnetism in the layered, ferromagnetic insulator $\\operatorname{CrI}_{3}$ . Chem. Mater. 27, 612–620 (2015). \n17.\tDillon, J. F. & Olson, C. E. Magnetization, resonance, and optical properties of the ferromagnet $\\mathrm{CrI}_{3}$ . J. Appl. Phys. 36, 1259–1260 (1965). \n18.\tSivadas, N., Okamoto, S. & Xiao, D. Gate-controllable magneto-optic Kerr effect in layered collinear antiferromagnets. Phys. Rev. Lett. 117, 267203 (2016). \n19.\tCracknell, A. P. Magnetism in Crystalline Materials: Applications of the Theory of Groups of Cambiant Symmetry (Pergamon: New York, NY, 1975). \n20.\tManfred, F. Revival of the magnetoelectric effect. J. Phys. D 38, R123 (2005). \n21.\tEerenstein, W., Mathur, N. D. & Scott, J. F. Multiferroic and magnetoelectric materials. Nature 442, 759–765 (2006). \n22.\tWang, L. et al. One-dimensional electrical contact to a two-dimensional material. Science 342, 614–617 (2013). \n23.\tCui, X. et al. Multi-terminal transport measurements of $\\mathbf{MoS}_{2}$ using a van der Waals heterostructure device platform. Nat. Nanotech. 10, 534–540 (2015). \n24.\tWang, Z., Shan, J. & Mak, K. F. Valley- and spin-polarized Landau levels in monolayer ${\\mathrm{WSe}}_{2}$ . Nat. Nanotech. 12, 144–149 (2017). \n25.\tJacobs, I. S. & Lawrence, P. E. Metamagnetic phase transitions and hysteresis in $\\mathrm{FeCl}_{2}$ . Phys. Rev. 164, 866–878 (1967). \n26.\tRivera, J.-P. A short review of the magnetoelectric effect and related experimental techniques on single phase (multi-) ferroics. Eur. Phys. J. B 71, 299–313 (2009). \n27.\tWeiglhofer, W. S. & Lakhtakia, A, (eds) Introduction to Complex Mediums for Optics and Electromagnetics. 175 (SPIE: Bellingham, 2003). \n28.\tO’Dell, T. H. The Electrodynamics of Magneto-Electric Media (North-Holland, Amsterdam, 1970). \n29.\tRado, G. T. Mechanism of the magnetoelectric effect in an antiferromagnet. Phys. Rev. Lett. 6, 609–610 (1961). \n30.\tRado, G. T. Magnetoelectric evidence for the attainability of time-reversed antiferromagnetic configurations by metamagnetic transitions in $\\mathrm{DyPO_{4}}$ . Phys. Rev. Lett. 23, 644–647 (1969). \n31.\tNogués, J. & Schuller, I. K. Exchange bias. J. Magn. Magn. Mater. 192, 203–232 (1999). \n\n# Acknowledgements \n\nThe research was supported the Air Force Office of Scientific Research under grant FA9550-16-1-0249 and the Army Research Office under grant W911NF-17-1-0605 for sample and device fabrication, and the Air Force Office of Scientific Research under grant FA9550- 14-1-0268 for optical spectroscopy measurements. Support for data analysis and modelling was provided by the National Science Foundation DMR-1410407 (J.S.), and a David and Lucille Packard Fellowship and a Sloan Fellowship (K.F.M.). \n\n# Author contributions \n\nAll the authors conceived and designed the experiments, analysed the data and co-wrote the manuscript. S.J. fabricated the devices and performed the measurements. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41563-018-0040-6. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to J.S. or K.F.M. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\nDevice fabrication and characterization. Dual-gate field-effect devices of atomically thin $\\mathrm{CrI}_{3}$ with hBN as the gate dielectric and few-layer graphene as the gate and contact electrodes were fabricated by the layer-by-layer dry-transfer method22,23. Atomically thin flakes of $\\mathrm{CrI}_{3}$ (HQ Graphene), hBN and graphene were mechanically exfoliated from their bulk crystals onto silicon substrates covered by a $300\\mathrm{nm}$ thermal oxide layer. Owing to the instability of $\\mathrm{CrI}_{3}$ in air, $\\mathrm{CrI}_{3}$ was handled exclusively inside a glovebox under a controlled atmosphere with less than 1 ppm oxygen and moisture11,12. Outside the glovebox, stamps for transfer, which consisted of a thin layer of polycarbonate (PC) on polydimethylsiloxane supported by a glass slide, were prepared. The back graphene gate electrode and hBN gate dielectric were first transferred onto a silicon substrate with pre-patterned gold electrodes. The residual PC was dissolved in chloroform. The top graphene gate electrode, hBN gate dielectric and graphene contact electrodes were picked up by a stamp. The stamp and the substrate with the finished back gate were then introduced into the glovebox. Inside the glovebox, the stamp picked up $\\mathrm{CrI}_{3}$ and released the entire stack onto the substrate with the back gate. After this step, the device was safe to be removed from the glovebox because $\\mathrm{CrI}_{3}$ was encapsulated fully in hBN. The residual PC on the device surface was dissolved in chloroform before the optical measurements. \n\nThe thickness of atomically thin materials was initially estimated from their optical reflectance contrast on silicon substrates and later verified by the atomic force microscopy measurements. The layer thickness of $\\mathrm{CrI}_{3}$ was further confirmed from the magnetization measurement under a varying out-of-plane magnetic field. The typical thickness of the hBN gate dielectric was ${\\sim}20\\mathrm{nm}$ and nearly identical for the top and back gates. The applied electric field was varied by changing the difference between the top- and back-gate voltages, referred to simply as the gate voltage in the main text. More details on the device structure are provided in Supplementary Sections 2 and 12. All three devices studied here showed a built-in electric field, probably due to the asymmetry in the fabrication procedure for the two gates. An electric field at a level of ${\\sim}0.4\\mathrm{Vnm^{-1}}$ was typically required to cancel the built-in field. We subtracted this value from the applied electric field in all the presented results so that, in the pristine state, bilayer $\\mathrm{CrI}_{3}$ is an antiferromagnet (that is, zero net magnetization under a zero magnetic field). \n\nMCD microscopy. The MCD measurements were performed in an Attocube closed-cycle cryostat (attoDry1000) down to 4 K and up to 1 T in the out-of-plane direction with a HeNe laser at $633\\mathrm{nm}$ . Optical radiation with a power of ${\\sim}5\\upmu\\mathrm{W}$ was coupled into and out of the system using free-space optics. A high numerical aperture (0.8) objective was used to focus the excitation beam onto the device with a submicrometre spot size. The optical excitation was modulated between left and right circular polarization by a photoelastic modulator at $50.1\\mathrm{kHz}$ . The reflected beam was collected by the same objective and detected by a photodiode. The MCD was determined as the ratio of the a.c. component at $50.1\\mathrm{kHz}$ (measured by a lockin amplifier) and the d.c. component (measured by a multimeter) of the reflected light intensity. \n\nData analysis. The critical magnetic field for the spin-flip transition was determined from the peak position of the differential magnetic susceptibility32, which was calculated numerically from the measured magnetic-field dependence of the MCD signal (Supplementary Section 4 gives examples). The full-width-athalf-maximum of the peak was taken to be the transition width, as shown by the full length of the vertical bars centred on the symbols in Figs. 1d and 2c. The MCD signal was converted into sheet magnetization by assuming that the MCD signal is linearly proportional to the sheet magnetization and the saturation magnetization is $M_{0}=0.274\\mathrm{mA}$ . The latter was obtained by assuming that under saturation each $\\mathrm{Cr^{3+}}$ cation carries a magnetic moment of $3\\mu_{_{\\mathrm{B}}}$ in pristine samples15,16. The density of Cr was calculated using the crystallographic data of bulk $\\mathrm{CrI}_{3}$ (space group $R^{\\dot{3}}$ with unit-cell parameters of $a=0.6867~\\mathrm{nm}$ , $b=0.6867~\\mathrm{nm}$ , $c=1.9807\\ \\mathrm{nm}$ and $\\beta=90^{\\circ}$ ) (refs 15,16). \n\nData availability. The data supporting the plots within this paper and other findings of this study are available from the corresponding authors on request. \n\n# References \n\n32.\tMiyake, A., Sato, Y., Tokunaga, M., Jatmika, J. & Ebihara, T. Different metamagnetism between paramagnetic Ce and Yb isomorphs. Phys. Rev. B 96, 085127 (2017). " + }, + { + "id": "10.1038_s41467-018-03712-z", + "DOI": "10.1038/s41467-018-03712-z", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-03712-z", + "Relative Dir Path": "mds/10.1038_s41467-018-03712-z", + "Article Title": "Ultrathin bismuth nullosheets from in situ topotactic transformation for selective electrocatalytic CO2 reduction to formate", + "Authors": "Han, N; Wang, Y; Yang, H; Deng, J; Wu, JH; Li, YF; Li, YG", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electrocatalytic carbon dioxide reduction to formate is desirable but challenging. Current attention is mostly focused on tin-based materials, which, unfortunately, often suffer from limited Faradaic efficiency. The potential of bismuth in carbon dioxide reduction has been suggested but remained understudied. Here, we report that ultrathin bismuth nullosheets are prepared from the in situ topotactic transformation of bismuth oxyiodide nullosheets. They process single crystallinity and enlarged surface areas. Such an advantageous nullostructure affords the material with excellent electrocatalytic performance for carbon dioxide reduction to formate. High selectivity (similar to 100%) and large current density are measured over a broad potential, as well as excellent durability for >10 h. Its selectivity for formate is also understood by density functional theory calculations. In addition, bismuth nullosheets were coupled with an iridium-based oxygen evolution electrocatalyst to achieve efficient full-cell electrolysis. When powered by two AA-size alkaline batteries, the full cell exhibits impressive Faradaic efficiency and electricity-to-formate conversion efficiency.", + "Times Cited, WoS Core": 750, + "Times Cited, All Databases": 776, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000429004500013", + "Markdown": "# Ultrathin bismuth nanosheets from in situ topotactic transformation for selective electrocatalytic CO2 reduction to formate \n\nNa Han1, Yu Wang2, Hui Yang1, Jun Deng1, Jinghua Wu1, Yafei Li2 & Yanguang Li1 \n\nElectrocatalytic carbon dioxide reduction to formate is desirable but challenging. Current attention is mostly focused on tin-based materials, which, unfortunately, often suffer from limited Faradaic efficiency. The potential of bismuth in carbon dioxide reduction has been suggested but remained understudied. Here, we report that ultrathin bismuth nanosheets are prepared from the in situ topotactic transformation of bismuth oxyiodide nanosheets. They process single crystallinity and enlarged surface areas. Such an advantageous nanostructure affords the material with excellent electrocatalytic performance for carbon dioxide reduction to formate. High selectivity $(\\sim100\\%)$ and large current density are measured over a broad potential, as well as excellent durability for $>10\\mathsf{h}$ . Its selectivity for formate is also understood by density functional theory calculations. In addition, bismuth nanosheets were coupled with an iridium-based oxygen evolution electrocatalyst to achieve efficient full-cell electrolysis. When powered by two AA-size alkaline batteries, the full cell exhibits impressive Faradaic efficiency and electricity-to-formate conversion efficiency. \n\nElrecptreosceanttaslyatinc represents an attractive route to the capture and utilization $\\mathrm{CO}_{2}$ druocutieo tn tho cuasepftul cahnedmiuctialli ftuieolns $\\mathrm{CO}_{2}{}^{1,2}$ energy sources such as solar energy, this process could potentially enable a sustainable energy economy and chemical industry3,4. One key technological challenge in this process remains the development of active, durable and selective electrocatalysts for $\\mathrm{CO}_{2}$ reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})^{5-12}$ . Formate (or formic acid) is a common $\\mathrm{CO}_{2}\\mathrm{RR}$ product. It is an important chemical intermediate in many industrial processes, and can be used as the chemical fuel in direct formate (or formic acid) fuel cells13,14. In 1980s, Hori et al. first reported that several II B, III A, and IV A metals (Pb, Cd, Hg, In, $\\mathsf{S n}$ , and Tl) could reduce $\\mathrm{CO}_{2}$ to formate15–17. They have high hydrogen overpotentials, and weak affinity toward $\\mathrm{CO}_{2}\\cdot^{-}$ intermediate, which then tends to be protonated at the carbon atom and ultimately transforms to formate as the major reduction product17. Unfortunately, many of these heavy metals $\\mathrm{\\cdot}$ Cd, $\\mathrm{Hg}$ and Tl) are highly toxic and environmentally hazardous, and therefore are out of consideration for practical applications. Sn-based materials have gained major interest for formate production, but usually suffer from limited reaction selectivity (peak selectivity $50\\sim80\\%$ ) accompanied by the significant cogeneration of $\\mathrm{H}_{2}$ and $\\mathrm{CO}^{18-20}$ . \n\nBi locates close to traditional formate-producing metals in the periodic table. It is therefore suggested to be also active for $\\mathrm{CO}_{2}$ reduction to formate, yet is significantly less toxic and more environmentally benign than many of its neighbors. Previous studies on Bi-based materials were mostly conducted in ionic liquids or aprotic electrolytes with CO as the end product21–23. Its potential for $\\mathrm{CO}_{2}\\mathrm{RR}$ in aqueous solution just starts to be unveiled24–26. To further improve its performance would require structural engineering at the nanoscale to enlarge its surface areas. \n\nBi is consisted of stacked layers of buckled honeycomb structure similar to black phosphorus. This permits Bi to be potentially exfoliated to its two-dimensional (2D) mono- or few-layers with enlarged surface area and enhanced electrochemical activity. Stable Bi monolayer (i.e., bismuthene) was in fact theoretically predicted27. Nevertheless, the direct preparation of Bi mono- or few-layers via conventional top-down (mechanical exfoliation) or bottom-up (chemical synthesis) methods is highly challenging, and successful examples are very sparse in literature as far as we know. \n\nWe report here an indirect approach to prepare ultrathin Bi nanosheets via in situ topotactic transformation of bismuth oxyiodide (BiOI) naonsheet template. Most remarkably, the 2D morphology is largely preserved during the structural transformation of Bi atoms. These ultrathin Bi nanosheets can act as an efficient $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalyst for the conversion of $\\mathrm{CO}_{2}$ to formate with impressive activity and selectivity close to $100\\%$ over a broad potential window, as well as satisfactory durability. \n\n# Results \n\nTopotactic reduction from BiOI nanosheets to Bi nanosheets. We started with the preparation of BiOI nanosheets. As shown in the insert of Fig. 1a, BiOI possesses a layered tetragonal structure where $\\left[\\mathrm{Bi}_{2}\\mathrm{O}_{2}\\right]$ slabs are sandwiched between anionic iodide layers. A facile hydrothermal method was adopted here for its synthesis by reacting $\\mathrm{Bi}(\\mathrm{NO}_{3})_{3}$ and KI at $160^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ (see Methods for details). Figure 1a shows the X-ray diffraction (XRD) pattern of as-prepared product. All the diffraction peaks were assignable to tetragonal BiOI. Based on the (001) peak width, we estimated that the thickness along the $c$ -direction was ${\\sim}16\\mathrm{nm}$ . Scanning electron microscopy (SEM) \n\n![](images/c640c6fa8849cbb2f2b3eb0c07bc227eb4e7c7eae6b513fa550c7a5f76a06ea9.jpg) \nFig. 1 Structural characterizations of BiOI nanosheets. a XRD pattern and (inserted) schematic crystal structure; b SEM image; c, d TEM images at differen magnifications; e SAED pattern; f AFM image and corresponding height profile. Scale bar, $200\\mathsf{n m}$ $(\\pmb{\\ b})$ ; $50\\mathsf{n m}$ $(\\pmb{\\mathscr{c}})$ ; $5\\mathsf{n m}$ (d) \n\nimage of the as-prepared product showed that it was comprised of hierarchical microflowers that were assembled from very thin nanosheets oriented to different angles (Fig. 1b). The nanosheet thickness was so small that they were almost transparent to the electron beam. To better understand the microstructure, we broke BiOI microflowers into individual nanosheets by gentle sonication, and then examined them under transmission electron microscopy (TEM). As shown in Fig. 1c, these nanosheets had uniform contrast. High-resolution TEM study revealed obvious lattice fringes corresponding to the (110) plane of tetragonal BiOI (Fig. 1d). Selected area electron diffraction (SAED) pattern over a large piece of nanosheet displayed a single set of diffraction spots with a fourfold symmetry (Fig. 1e). Its zone axis was found to be along the $\\boldsymbol{c}$ -direction, indicating that BiOI nanosheets were terminated with the relatively stable (001) plane. Furthermore, BiOI nanosheet pieces were analyzed by atomic force microscopy (AFM) (Fig. 1f). From a typical height profile as shown, the nanosheet thickness was measured to be ${\\sim}8.7\\mathrm{nm}$ —corresponding to 9–10 layers. The influences of different synthetic parameters on the product morphology were also explored and summarized in Supplementary Fig. 1. \n\nBiOI is stable under ambient conditions, but undergoes a reductive transformation at cathodic potentials. We attempted to electrochemically reduce BiOI and interrogate the composition and microstructure of its reduced counterpart. As-prepared BiOI was loaded onto carbon fiber paper as the working electrode. Figure 2a shows the typical cyclic voltammetry (CV) curve of BiOI in $0.5{\\mathrm{M}}{}$ ${\\mathrm{NaHCO}}_{3}$ electrolyte. It exhibited a pair of pronounced and roughly symmetric redox waves between $-1.4$ $\\mathrm{~\\stackrel{-}{\\sim}0.6~V~}$ versus saturated calomel electrode (SCE) as contributed by the reversible interconversion between $\\mathrm{Bi}^{3+}$ and metallic Bi (supported by the Pourbaix diagram of Bi in $\\mathrm{H}_{2}\\mathrm{O}^{28}$ ). Reduced material supported on the working electrode was taken out of the electrolyte, briefly rinsed with distilled water, and immediately subjected to spectroscopic and microscopic characterizations. Its XRD measurement unveiled diffraction peaks assignable to rhombohedral Bi, overlaid on the top of intense signals from the carbon fiber paper substrate (Fig. 2b). There was no detectable signal from original tetragonal BiOI phase suggesting the complete conversion from BiOI to metallic Bi. X-ray photoelectron spectroscopy (XPS) analysis of the reduced product indicated that its surface was free of iodine (Supplementary Fig. 2). Most remarkably, this reductive transformation did not seem to significantly compromise or degrade the microstructure despite the considerably different atomic arrangements between tetragonal BiOI and rhombohedral Bi. SEM image showed that the reduced Bi retained the 2D nanosheet morphology (accordingly denoted as BiNS hereafter, Fig. 2c). Compared to the BiOI nanosheet template, BiNS appeared to be even thinner and more transparent to electron beam. Some nanosheets were curved or folded, presumably due to the soft nature of metallic Bi. TEM image of BiNS showed that reduced nanosheets had no sign of pulverization (Fig. 2d). High-resolution TEM analysis revealed obvious lattice fringes with $60^{\\circ}$ intersection angle that corresponded to (110) planes of rhombohedral Bi (Fig. 2e). SAED pattern over an entire sheet showed a single set of diffraction spots with a sixfold symmetry. Its zone axis was indexed along [001] direction (Fig. 2f). \n\nAbove microscopic results corroborated that BiNS preserved its 2D structure integrity and single crystallinity, and the reductive transformation from layered tetragonal BiOI to layered rhombohedral Bi was likely topotactic with $[001]_{\\mathrm{BiOI}}//[001]_{\\mathrm{Bi}}$ . To better understand this topotactic transformation, we further compare their crystal structures (Supplementary Fig. 3a). Despite the different arrangements of Bi atoms within each layer, they actually shared similar lattice parameters: $a^{\\prime}=b^{\\prime}=8.06\\mathrm{\\dot{A}}$ for $2\\times$ 2 supercell (8 atoms) of BiOI and $a^{\\prime}{=}7.97\\mathring\\mathrm{A}$ and $b^{\\prime}{=}9.20\\mathring\\mathrm{A}$ for ${\\sqrt{2\\times2{\\sqrt{2}}}}$ supercell (8 atoms) of Bi. The conversion from tetragonal BiOI to rhombohedral Bi could be achieved by simply sliding some Bi atoms along the $\\mathbf{\\nabla}_{b}\\cdot\\mathbf{\\nabla}_{\\mathbf{\\mu}}$ -direction as shown in Supplementary Fig. 3b, which involved no significant volume change and no appreciable energy barrier according to our density functional theory (DFT) simulation (Supplementary Fig. 3c). Furthermore, we performed first-principles molecular dynamic (FPMD) simulations using an optimized $6\\times6$ supercell of tetragonal Bi at $300\\mathrm{K},$ and found that a large number of hexatomic Bi rings form after 1000 steps (1 ps) (Supplementary Fig. 3d). It suggested that once reduced, the conversion from BiOI to rhombohedral Bi was energetically favored and kinetically fast. Ultrathin nanosheets of metallic Bi presented an ideal material for $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalysis due to its enlarged surface area. We estimated the surface active Bi sites by integrating the cathodic peak area from the CV curve, and found that it accounted for ${\\sim}12\\%$ of total Bi sites (Supplementary Fig. 4). \n\n![](images/63f4a40bb7e78f85c067c0bb04810670bec55d2deccd105d1bdcf390a0117d86.jpg) \nFig. 2 Structural characterizations of topotactically reduced BiNS. a CV curve of BiOI showing its reduction to metallic Bi at cathodic potentials; b XRD and (inserted) schematic crystal structure of Bi; c SEM image; d, e TEM images at different magnifications; f SAED pattern of BiNS. Scale bar, $200\\mathsf{n m}$ (c); 20 nm (d); 5 nm (e) \n\n![](images/b94e3c8a9e60c36ac79a21aea0e63fe9bef828d2b8db97ae4d1018982fbdf7c8.jpg) \nFig. 3 Electrochemical measurements of BiNS. a Polarization curves of BiNS and commercial Bi nanopowder in $\\mathsf{N}_{2^{-}}$ or ${\\mathsf{C O}}_{2}$ -saturated 0.5 M ${\\mathsf{N a H C O}}_{3};$ b potential-dependent Faradaic efficiencies of ${\\mathsf{H}}{\\mathsf{C}}{\\mathsf{O}}{\\mathsf{O}}^{-}$ , CO, and ${\\sf H}_{2}$ on BiNS in comparison with the Faradaic efficiency of ${\\mathsf{H}}{\\mathsf{C}}{\\mathsf{O}}{\\mathsf{O}}^{-}$ on commercial Bi nanopowder; c potential-dependent ${\\mathsf{H}}{\\mathsf{C}}{\\mathsf{O}}{\\mathsf{O}}^{-}$ partial current density on BiNS and commercial Bi nanopowder; d amperometric $(j\\sim t)$ stability of BiNS at $\\eta=680\\:\\mathrm{mV}$ for $10\\mathrm{~h~}$ \n\n$\\mathbf{CO}_{2}\\mathbf{RR}$ performance of BiNS. We next investigated the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of topotactically reduced BiNS within a gas-tight two-compartment electrochemical cell (see Methods for details). Its polarization curve in $\\mathrm{CO}_{2}$ -saturated $0.5\\mathrm{M}\\mathrm{NaHCO}_{3}$ exhibited a cathodic current onset at approximately $-1.3\\mathrm{V}$ versus SCE due to ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ and beyond that, the current density continuously increased and reached $11\\mathrm{mA}\\mathrm{cm}^{-2}$ at $-1.5\\mathrm{V}$ (Fig. 3a). Such an activity was markedly enhanced over commercial Bi nanopowder measured under identical conditions. Control experiments suggested that in the absence of any $\\mathrm{CO}_{2}$ feed gas, hydrogen evolution reaction (HER) became the dominant cathodic process, and its current density was much diminished—in line with the poor HER activity of Bi. In order to identify and quantify the reduction products, electrolysis was performed at different potentials between $-1.2$ and $-1.8\\mathrm{V}$ for $^{2\\mathrm{h}}$ . Resultant gaseous products were periodically sampled and examined using gas chromatography (GC), and the liquid products were analyzed by nuclear magnetic resonance (NMR) spectroscopy and ion chromatography (IC) at the end of each electrolysis. We found that formate was the dominant reduction product, accompanied by the cogeneration of a small amount of CO and $\\mathrm{H}_{2}$ . Faradaic efficiency of different products at various potentials were calculated (see Methods for details) and summarized in Fig. 3b. Formate was first reliably and reproducibly detected at as positive as $-1.27\\mathrm{V}_{:}$ , translating to a small overpotential of $0.4\\mathrm{V}$ . Initially, its Faradaic efficiency was ${\\sim}16\\%$ , then quickly rose to $595\\%$ at $\\sim$ $-1.5\\mathrm{V}$ , and maintained close to $100\\%$ until $-1.7\\mathrm{V}$ . Faradaic efficiency for the two gaseous products remained small $(<5\\%)$ at low-to-medium overpotentials. Only beyond $-1.7\\mathrm{V}$ was a considerable amount of $\\mathrm{H}_{2}$ detected presumably because $\\mathrm{CO}_{2}\\mathrm{RR}$ became diffusion-limited under this condition. By contrast, the Faradaic efficiency for formate on commercial Bi nanopowder took off at $-1.33\\mathrm{V}$ , reached the peak value at $-1.46\\mathrm{V}$ and then started to decline at potentials negative to $-1.5\\mathrm{V}$ . Furthermore, the formate partial current density of BiNS and commercial Bi nanopowder was calculated and plotted against the working potential as shown in Fig. 3c. The former delivered a maximum value of $j_{\\mathrm{HCOO}^{-}}=24\\mathrm{mAcm}^{-2}$ at $-1.74\\mathrm{V}$ , whereas that of the latter did not exceed $6\\mathrm{mA}\\mathrm{cm}^{-2}$ . Their mass-specific current density was also compared in Supplementary Fig. 5. The combination of large catalytic current density and high-formate selectivity over a broad potential observed for BiNS was highly desirable for practical applications, and attributed to its advantageous nanostructure with enlarged surface area and abundant under-coordinated Bi sites. It placed our electrocatalyst on the top of Bi-based $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalysts24,25,29. Noteworthy was that BiNS also outperformed most Sn-based $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalysts, which were more frequently investigated for formate production but often plagued with limited Faradaic efficiency (see Supplementary Fig. 6)18,19,30. In addition, we found that similar Bi nanosheets could be prepared from the cathodic reduction of BiOCl and BiOBr nanostructures (Supplementary Fig. 7). Electrochemical measurements revealed no noticeable difference in their formate selectivity or partial current density. \n\n![](images/bf3447c6a34f65d5b564189be54d775c19df033514e19c648cb1262c002a15c2.jpg) \nFig. 4 DFT simulation of the ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ process on Bi (001) plane. a–c Optimized geometric structure of a $C{\\mathsf{O}}_{2}$ b ${\\mathsf{O C H O}}^{\\star}$ adsorbate and $\\pmb{\\mathsf{c}}\\mathsf{O}0^{-}$ , where Bi, $\\mathsf{C},\\mathsf{O},$ and H atoms were presented by purple, gray, red, and green spheres, respectively; d free-energy diagrams for ${\\mathsf{H}}{\\mathsf{C}}{\\mathsf{O}}{\\mathsf{O}}^{-}$ , $\\mathsf{C O},$ and ${\\sf H}_{2}$ formation on Bi (001) plane; e projected $p$ -orbital DOS of the Bi site with ${\\mathsf{O C H O}}^{\\star}.$ ${\\mathsf{C O O H}}^{\\star}$ , or $\\mathsf{H}^{\\star}$ adsorbate, the Fermi level $(E_{\\mathsf{F}})$ was at 0 eV, $E_{\\mathsf{p}}$ in ${\\mathsf{O C H O}}^{\\star}$ , and ${\\mathsf{C O O H}}^{\\star}$ and $\\mathsf{H}^{\\star}$ were highlighted with yellow, blue, and green dashed lines, respectively \n\nFinally, the operation durability of BiNS was assessed by bulk electrolysis at $-1.5\\mathrm{V}$ $(\\eta=680\\:\\mathrm{mV})$ for $\\mathrm{10h}$ . Our catalyst delivered a stable cathodic current density of $15{\\mathrm{-}}16\\operatorname*{mA}{\\mathrm{cm}}^{\\cdot-2}$ with no apparent sign of activity loss (Fig. 3d). Analysis of the formate in the catholyte after the $\\mathrm{10h}$ electrolysis led to an incredible average Faradaic efficiency of ${\\sim}95\\%$ , suggesting that the $\\mathrm{CO}_{2}\\mathrm{RR}$ selectivity was preserved during the long-term electrolysis. The $^{10\\mathrm{h}}$ durability test here was far from reaching the possible end of the catalyst life. Postmortem analysis after the long-term electrolysis revealed that BiNS preserved its composition and 2D morphology (Supplementary Fig. 8). \n\nTo gain further insights into the excellent $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of BiNS, DFT calculations were carried out via the computational hydrogen electrode methodology31. Rhombohedral Bi was represented using a trilayer structure in a $3\\times3$ supercell. Its optimized lattice constants were $a=b=4.60\\mathring\\mathrm{A}$ , consistent with experimental values. The simulation of $\\mathrm{CO}_{2}$ reduction to formate was performed on the Bi (001) plane since it was the predominantly exposed crystal plane on BiNS. Optimized geometric structures of various states along the catalytic pathway were depicted in Fig. $\\mathtt{4a\\mathrm{-c}}_{:}$ , and corresponding energy profiles were summarized in Fig. 4d. $\\mathrm{CO}_{2}$ reduction initiated with a proton-coupled electron transfer, leading to the protonation of C or $\\mathrm{~O~}$ atom. Here, we found that the protonation of C atom to the ${\\mathrm{OCHO^{*}}}$ intermediate was mildly endothermic $(+0.49\\mathrm{eV})$ . Upon the second proton-coupled electron transfer that was exothermic $(-0.17\\mathrm{eV})$ , this intermediate transformed to $\\mathrm{HCOO^{-}}$ , and finally was spontaneously released from the catalyst surface as formate. By stark contrast, we found that the protonation of $\\mathrm{~O~}$ atom in $\\mathrm{CO}_{2}$ to $\\scriptstyle{\\mathrm{COOH^{*}}}$ —which was the intermediate to CO—was significantly uphill in energy $\\left(+1.16\\mathrm{eV}\\right)$ , and that the free energy of H adsorption on Bi (001) was likewise too positive $(+0.95\\mathrm{eV})$ to allow active HER. The binding strength of different intermediates could also be inferred from comparing $\\boldsymbol{p}$ -projected density of states (DOS) of the active Bi site with adsorbates (Fig. 4e). The highest peak of active Bi DOS $(E_{\\mathrm{p}})$ of ${\\mathrm{OCHO^{*}}}$ was the closest to the Fermi level, corresponding to the lowest filling of anti-bonding states and hence stronger adsorbate binding relative to $\\mathrm{{COOH^{*}}}$ and $\\mathrm{H}^{*32}$ . As a result, $\\mathrm{CO}_{2}$ reduction to formate was the most energetically favorable among the three competing cathodic processes. It rationalized the observed high Faradaic efficiency for formate. The reaction overpotential was estimated to be $\\mathrm{\\dot{0}}.30\\mathrm{V}$ and agreed reasonably well with our experimental finding $(\\mathrm{{\\sim}0.4V)}$ . Worth noting was that the binding strength of these three intermediates on Sn was reported to be relatively comparable, which thereby explained its inferior formate selectivity33,34. \n\n![](images/5c7ada11b46ddc14ed62e42e64c5c9389da4b58e4e52b500b711f66378a596e8.jpg) \nFig. 5 Full-cell electrolysis by coupling BiNS ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ with $\\mathsf{I r/C}$ OER. a Polarization curve for the full cell $C\\mathsf{O}_{2}\\mathsf{R R}_{-}\\mathsf{O}\\mathsf{E}\\mathsf{R}$ electrolysis; b photograph of the setup for the $C{\\mathsf{O}}_{2}{\\mathsf{R R-O E R}}$ electrolysis powered by two AA-size alkaline batteries; c current evolution for the battery-powered $C{\\mathsf{O}}_{2}{\\mathsf{R R-O E R}}$ electrolysis \n\nCoupling $\\mathbf{CO}_{2}\\mathbf{RR}$ and OER in full cells. Encouraged by the excellent $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of BiNS in aqueous solution, we further pursued full-cell electrolysis to assess its practical implications. A total of $20\\mathrm{wt\\%}$ Ir nanoparticles on Vulcan carbon black $\\mathrm{(Ir/C)}$ was employed as the electrocatalyst for oxygen evolution reaction (OER). Despite its high cost, $\\mathrm{Ir/C}$ was valued for its excellent OER activity at all $\\mathrm{\\ttpH}$ conditions (particularly in neutral and acidic solution), and therefore chosen as the benchmark material to couple with BiNS ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ Its OER polarization curve was first collected using the standard three-electrode setup and measured to reach $1\\mathrm{mA}\\mathrm{cm}^{-2}$ at $0.82\\mathrm{V}$ and $10\\mathrm{mA}\\mathrm{cm}^{-2}$ at $0.99\\mathrm{V}$ versus SCE (corresponding to an overpotential of $\\eta_{1\\mathrm{mA}\\mathrm{cm}-2}$ $=0.34\\mathrm{V}$ and $\\eta_{10\\mathrm{{mAcm-2}}}=0.51\\mathrm{{V}}.$ respectively) in $0.5{\\mathrm{M}}{}$ ${\\mathrm{NaHCO}}_{3}$ (Supplementary Fig. 9). Full cells were then constructed by pairing BiNS cathode and $\\mathrm{Ir/C}$ anode in a two-compartment cell, and their typical non-iR-compensated polarization curve was depicted in Fig. 5a. The $\\mathrm{CO}_{2}\\mathrm{RR}{\\mathrm{-OER}}$ reaction couple became turned on under the external voltage of ${\\sim}2.1\\mathrm{V}$ (in good agreement with the combined performance of these two electrocatalysts), and was able to deliver a current density of $\\sim10\\mathrm{mAcm}^{-2}$ at $3.2\\mathrm{V}$ . Next, we used two AA-size alkaline batteries as the external power source (with open circuit voltage of ${\\sim}3.1\\mathrm{V})$ ) to drive the $\\mathrm{CO}_{2}\\mathrm{RR}$ -OER electrolysis (Fig. 5b). A source-meter was connected in series to continuously monitor the current evolution. As shown in Fig. 5c, the current density started at ${\\sim}8\\mathrm{mAcm}^{-2}$ , and after an initial decay over the first half an hour, roughly stabilized at $6\\sim7~\\mathrm{mAcm}^{-2}$ . We noted that the noticeable activity loss was mostly contributed from the anode side. The average Faradaic efficiency for formate during a typical $^{3\\mathrm{h}}$ full-cell electrolysis was measured to be ${\\sim}95\\%$ . The electricity-to-formate conversion efficiency was calculated to be $47\\%$ based on the relative ratio of the stored chemical energy in formate to the electricity energy input (see Methods for details). Both efficiency values were remarkable. Based on these results, we estimated that if proper solar cells with matching $I{-}V$ parameters and solar-toelectricity energy efficiency of $10\\mathrm{-}20\\%$ could be identified for powering the $\\mathrm{\\bar{CO}}_{2}\\mathrm{RR}{\\cdot}\\mathrm{OER}$ electrolysis in future, one could readily achieve an overall solar-to-fuel conversion efficiency of $5\\mathrm{-}10\\%$ . Here, the precious $\\mathrm{Ir/C}$ OER electrocatalyst might also be replaced with non-precious metal based materials (such as CoPi) —of course at the price of significantly lower activity. \n\n# Discussion \n\nIn summary, we reported that ultrathin BiNS could be prepared via the in situ topotactic transformation of BiOI nanosheet template under cathodic electrochemical environments. Resultant nanosheets preserved the extended 2D structure and single crystallinity. They processed enlarged surface area and abundant under-coordinated Bi sites. The topotactic transformation was understood based on the intrinsic structural correlation between BiOI and $\\mathrm{Bi,}$ and supported by our theoretical simulations. When evaluated as the $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalyst in 0.5 M ${\\mathrm{NaHCO}}_{3}$ , BiNS enabled high-performance $\\mathrm{CO}_{2}$ reduction to formate with excellent selectivity (Faradaic efficiency $590\\%$ over a broad potential), activity (large $\\mathrm{HCOO^{-}}$ partial current density of 24 $\\mathrm{\\dot{m}A}\\mathrm{cm}^{-2}$ at $-1.74\\mathrm{V})$ and durability (no loss in activity or selectivity for at least ${\\mathrm{10h}})$ . Such a performance was more attractive than many other $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalysts for formate production19,20,30,35,36. DFT calculations suggested that the highreaction selectivity toward formate was due to its stabilized intermediate ${\\mathrm{(OCHO^{*}}},$ ) on Bi (001) surface relative to $\\scriptstyle{\\mathrm{COOH^{*}}}$ or $\\mathrm{H^{*}}$ . At last, we demonstrated BiNS could be coupled with $\\mathrm{Ir/C}$ to achieve efficient $\\mathrm{CO}_{2}$ RR-OER electrolysis when powered by two AA alkaline batteries. A Faradaic efficiency of ${\\sim}95\\%$ and electricity-to-formate conversion efficiency of $47\\%$ were reported. \n\n# Methods \n\nPreparation of BiOI nanosheets. In a typical synthesis, $0.97\\ \\mathrm{g}$ of $\\mathrm{Bi}(\\mathrm{NO}_{3})_{3}{\\cdot}5\\mathrm{H}_{2}\\mathrm{O}$ was first dissolved in $20~\\mathrm{mL}$ of $1.2\\mathrm{M}$ glacial acetic acid and vigorously stirred for $20\\mathrm{min}$ . It was then added dropwise with $1.66\\mathrm{g}\\mathrm{KI}$ dissolved in $5\\mathrm{mL}$ of deionized water, followed by the addition of $1\\mathrm{M}\\mathrm{NaOH}$ for adjusting the solution $\\mathsf{p H}$ to 6. Thus formed orange suspension was stirred for another $30\\mathrm{min}$ before it was transferred to a $50~\\mathrm{mL}$ Teflon-lined autoclave and hydrothermally treated at $160^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . The final product was collected by centrifugation, repetitively washed with deionized water, and finally lyophilized. \n\nMaterial characterizations. XRD was performed on a PANalytical X-ray diffractometer. SEM images were taken using a Zeiss scanning electron microscope. TEM was conducted on a FEI Tecnai F20 transmission electron microscope operating at an acceleration voltage of $200\\mathrm{kV}$ . AFM images were taken using a Veeco (MultiMode V) atomic force microscope. \n\nElectrochemical measurements. For the reductive transformation to BiNS, and subsequent $\\mathrm{CO}_{2}\\mathrm{RR}$ measurements, $1\\mathrm{mg}$ of BiOI prepared above and $0.5\\mathrm{mg}$ of Ketjenblack carbon were dispersed in $250\\upmu\\mathrm{L}$ of ethanol and $6{\\upmu\\mathrm{L}}$ of $5\\mathrm{wt\\%}$ Nafion solution, and bath-sonicated for $30\\mathrm{min}$ to form a uniform catalyst ink. The ink was then dropcast onto a $1\\times1\\mathrm{cm}^{2}$ Teflon-treated carbon fiber paper (AvCarb P75 from Fuel Cell Store) and naturally dried. Commercial Bi nanopowder was purchased from Shanghai Macklin Biochemical Co. with a nominal purity of $99.99\\%$ and average particle size of ${\\sim}200$ mesh (corresponding SEM and XRD data were available in Supplementary Fig. 10). Its working electrode was prepared under the identical condition except for using $1\\mathrm{mg}$ of Bi nanopowder for the catalyst ink preparation. Electrochemical experiments were carried out in a custom-designed gas-tight H-type electrochemical cell with a Nafion-117 proton exchange membrane as the separator. Catalyst loaded carbon fiber paper and saturated calomel electrode (SCE) were used as the working and reference electrode respectively and placed in the cathodic compartment; a $\\mathrm{Pt}$ gauze counter electrode was used as the counter electrode and placed in the anodic compartment. Each compartment contained $\\sim30~\\mathrm{mL}$ of $\\bar{0.5}\\mathrm{M}\\mathrm{NaHCO}_{3}$ electrolyte, and their headspace was ${\\sim}25\\mathrm{mL}$ . The electrolyte was pre-saturated with $\\Nu_{2}$ $\\mathrm{\\Phi}_{\\cdot\\mathrm{PH}}=8.4\\mathrm{\\Phi}_{\\cdot}$ ) or $\\mathrm{CO}_{2}$ $\\mathrm{\\boldmath~\\cdot~}\\mathrm{\\boldmath~\\pH=7.4\\mathrm{\\boldmath~\\cdot~}}$ . CV and polarization curves were collected at a scan rate of $10\\mathrm{mVs^{-1}}$ using CHI 660E potentiostat. All the potential readings were iR-corrected, and reported against SCE unless otherwise specified. For the complete topotactic transformation of BiOI to BiNS, the working electrode was biased at $-1.55\\mathrm{V}$ for $^{2\\mathrm{h}}$ . Resultant working electrode was immediately taken out of the electrolyte, briefly rinsed with deionized water and subjected to microscopic characterizations as described in the main text. For $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalysis on BiNS or commercial Bi nanopowder, a flow of 20 sccm of $\\mathrm{CO}_{2}$ was continuously bubbled into the electrolyte to maintain its saturation. For the full-cell measurements, $20\\mathrm{wt\\%}$ Ir/C was used as the OER electrocatalyst and similarly loaded onto $1\\times1\\mathrm{cm}^{2}$ carbon fiber paper electrode to achieve an areal loading of $1\\mathrm{mg}\\mathrm{cm}^{-2}$ . $\\mathrm{CO}_{2}\\mathrm{RR}$ -OER electrolysis was performed in the same two-compartment cell controlled by the potentiostat in the two electrode configuration or powered by two AA-sized alkaline batteries. Current density during electrolysis was measured by 2461-digital source-meter (Keithley). All electrochemical results for this part were non-iR-compensated. \n\nProduct analysis. In order to determine the reduction products and their Faradaic efficiency, electrolysis was conducted at selected potentials for $_{1-2\\mathrm{h}}$ . Gaseous products in the headspace of the cathodic compartment were periodically vented into the gas-sampling loop of a gas chromatograph (GC, Aligent 7890B). The GC was equipped with a molecular sieve $5\\mathrm{A}$ and two porapak Q columns. Nitrogen was used as the carrier gas. Reduction products were first analyzed by a thermal conductivity detector (TCD) for the $\\mathrm{H}_{2}$ concentration, and then analyzed by flame ionization detector (FID) with a methanizer for CO. The concentration of gaseous products was quantified by the integral area ratio of the reduction products to standards. Their Faradaic efficiency was calculated as follows: \n\n$$\n\\mathrm{FE}(\\mathcal{Y}_{\\mathrm{0}})=\\frac{Q_{\\mathrm{co}}}{Q_{\\mathrm{tot}}}\\times100\\%=\\frac{\\left(\\frac{\\nu}{60s/\\mathrm{min}}\\right)\\times\\left(\\frac{y}{24,000\\mathrm{cm}^{3}/\\mathrm{mol}}\\right)\\times N\\times F\\times100\\%}{j},\n$$ \n\nwhere $\\nu=20$ sccm is the flow rate of $\\mathrm{CO}_{2},$ y is the measured concentration of product in $1\\mathrm{mL}$ sample loop based on the calibration of the GC with a standard gas, $N=2$ is the number of electrons required to form a molecule of CO or $\\mathrm{H}_{2}$ , $F$ is the Faraday constant $(96,500{\\mathrm{C}}{\\mathrm{mol}}^{-1}$ ), $j$ is the recorded current. \n\nThe liquid products were collected at the conclusion of each electrocatalysis, and first identified to only contain formate by NMR (Aligent DD2–600), and then quantitatively analyzed using an ion chromatograph (Dionex ICS-600). The concentration of formate was determined from its IC peak area using the calibration curve from a series of standard HCOONa solutions. Its Faradaic efficiency was calculated as follows: \n\n$$\n\\mathrm{FE}_{\\mathrm{HCOO^{-}}}\\left(\\%\\right)=\\frac{Q_{\\mathrm{HCOO^{-}}}}{Q_{\\mathrm{tot}}}\\times100\\%=\\frac{n_{\\mathrm{HCOO^{-}}}\\times N\\times F\\times100\\%}{j\\times t},\n$$ \n\nwhere $n_{\\mathrm{HCOO}^{-}}$ is the measured amount of formate in the cathodic compartment \n\nand t is the reaction time. The $\\mathrm{HCOO^{-}}$ partial current density at different potentials was calculated by multiplying the overall geometric current density and its corresponding Faradaic efficiency. \n\nThe electricity-to-formate conversion efficiency of full cells was calculated as follows: \n\n$$\n\\eta=\\frac{\\Delta r G_{m}^{\\theta}\\times n_{\\mathrm{HCOO^{-}}}}{Q_{\\mathrm{tot}}\\times V},\n$$ \n\n$$\n\\Delta_{r}G_{m}^{\\theta}(298.15\\mathrm{K})=\\Delta_{f}G_{m}^{\\theta}(\\mathrm{HCOO^{-}})+\\frac{1}{2}\\Delta_{f}G_{m}^{\\theta}(\\mathrm{O}_{2})-\\Delta_{f}G_{m}^{\\theta}(\\mathrm{CO}_{2})-\\Delta_{f}G_{m}^{\\theta}(\\mathrm{H}_{2}\\mathrm{O}),\n$$ \n\nwhere $\\Delta r G_{m}^{\\theta}(=270.138\\mathrm{kJ\\cdotmol^{-1}})$ is the energy gain during ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ and $V\\left(\\sim3\\mathrm{V}\\right)$ is the working voltage. \n\nComputation details. First-principle DFT calculations were carried out using the plane-wave technique with exchange–correlation interactions modeled by GGA$\\mathrm{\\DeltaPBE}^{37}$ functional, as implemented in the VASP code38,39. The ion–electron interactions were described by the projector-augmented plane-wave approach40,41. A plane-wave cutoff energy of $420\\mathrm{eV}$ with Fermi-level smearing of $0.05\\mathrm{eV}$ for slabs and $0.01\\mathrm{eV}$ for gas-phase species was used in all calculations. The $k$ -space samplings were set as $3\\times3\\times1$ for the geometry optimization of Bi (001) slab, and $13\\times13\\times1$ for the computation of electronic structure. The convergence thresholds of energy and forces were set as $1\\times10^{-5}\\mathrm{eV}$ and $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ , respectively. The Bi (001) slab was constructed with six atomic layers and a vacuum space of $1\\dot{5}\\mathring{\\mathrm{A}}$ along the $z$ -direction, of which the top two layers were allowed to relax. The FPMD simulation was performed using an optimized $6\\times6$ supercell of tetragonal Bi and NVT ensemble, where the time step was 1.0 fs and the temperature $(300\\mathrm{K})$ was controlled by Nosé–Hoover method42. \n\nThe free energy (G) for each species was expressed as: \n\n$$\nG=E_{\\mathrm{DFT}}+E_{\\mathrm{ZPE}}-T S,\n$$ \n\nwhere $E_{\\mathrm{DFT}},E_{\\mathrm{ZPE}},$ S, and $T$ were electronic energy, zero point energy, entropy, and system temperature (298.15 K), respectively. For absorbates, $E_{\\mathrm{ZPE}}$ and S were determined by vibrational frequencies calculations, where all 3N degrees of freedom were treated as harmonic vibrational motions without considering contributions from the slab. For molecules, those were taken from the NIST database43. The relevant contributions to $G$ were listed in Supplementary Table 1. Note that the dipole and solvent corrections were also included in surface calculations. The solvent effect on adsorbates was achieved using the Poissson–Boltzmann implicit solvation model with a dielectric constant of $80^{44}$ . Moreover, a series of gas-phase thermochemical reaction enthalpies (Supplementary Table 2) were tested to correct the $E_{\\mathrm{DFT}}$ of $\\mathrm{CO}_{2}$ , CO, and $\\mathrm{{HCOO^{-}}}$ due to the inaccuracy of the PBE functional to describe those molecules31. From the Supplementary Table 2, the energy errors for $\\mathrm{CO}_{2},$ CO, and $\\mathrm{HCOO^{-}}$ were about $+0.17$ , $-0.24$ , and $+0.17\\mathrm{eV}$ , respectively. Accordingly, $+0.17\\mathrm{eV}$ correction was applied in the electronic energies of $\\mathrm{CO}_{2}$ and $\\mathrm{HCOO^{-}}$ , whereas $-0.24\\mathrm{eV}$ correction was applied to CO. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Received: 25 October 2017 Accepted: 7 March 2018 Publishedonline: 03 April2018 \n\n# References \n\n1. Whipple, D. T. & Kenis, P. J. A. Prospects of $\\mathrm{CO}_{2}$ utilization via direct heterogeneous electrochemical reduction. J. Phys. Chem. Lett. 1, 3451–3458 (2010). \n2. Mikkelsen, M., Jørgensen, M. & Krebs, F. C. The teraton challenge. A review of fixation and transformation of carbon dioxide. Energy Environ. Sci. 3, 43–81 (2010). \n3. Liu, C. et al. Water splitting-biosynthetic system with $\\mathrm{CO}_{2}$ reduction efficiencies exceeding photosynthesis. Science 352, 1210–1213 (2016). \n4. Schreier, M. et al. Solar conversion of $\\mathrm{CO}_{2}$ to CO using earth-abundant electrocatalysts prepared by atomic layer modification of CuO. Nat. Energy 2, \n17087 (2017). \n5. Zhu, D., Liu, J. & Qiao, S.-Z. Recent advances in inorganic heterogeneous electrocatalysts for reduction of carbon dioxide. Adv. Mater. 28, 3423–3452 (2016). \n6. Qiao, J., Liu, Y., Hong, F. & Zhang, J. A review of catalysts for the electroreduction of carbon dioxide to produce low-carbon fuels. Chem. Soc. Rev. 43, 631–675 (2014). \n7. Wu, J., Huang, Y., Ye, W. & Li, Y. $\\mathrm{CO}_{2}$ reduction: from the electrochemical to photochemical approach. Adv. Sci. 4, 1700194 (2017). \n8. Gao, S. et al. Partially oxidized atomic cobalt layers for carbon dioxide electroreduction to liquid fuel. Nature 529, 68–71 (2016). \n9. Mistry, H. et al. Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene. Nat. Commun. 7, 12123 (2016). \n10. Jiang, K., Wang, H., Cai, W.-B. & Wang, H. Li electrochemical tuning of metal oxide for highly selective $\\mathrm{CO}_{2}$ reduction. ACS Nano 11, 6451–6458 (2017). \n11. Weng, Z. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction to hydrocarbons on a heterogeneous molecular Cu catalyst in aqueous solution. J. Am. Chem. Soc. 138, 8076–8079 (2016). \n12. Han, N. et al. Supported cobalt polyphthalocyanine for high-performance electrocataltyic $\\mathrm{CO}_{2}$ reduction. Chem 3, 652–664 (2017). \n13. Agarwal, A. S., Zhai, Y., Hill, D. & Sridhar, N. The electrochemical reduction of carbon dioxide to formate/formic acid: engineering and economic feasibility. ChemSusChem 4, 1301–1310 (2011). \n14. Enthaler, S., von Langermann, J. & Schmidt, T. Carbon dioxide and formic acid—the couple for environmental-friendly hydrogen storage? Energy Environ. Sci. 3, 1207–1217 (2010). \n15. Hori, Y., Kikuchi, K. & Suzuki, S. Production of CO and $\\mathrm{CH}_{4}$ in electrochemical reduction of $\\mathrm{CO}_{2}$ at metal electrodes in aqueous hydrogen carbonate solution. Chem. Lett. 15, 1695–1698 (1985). \n16. Hori, Y., Wakebe, H., Tsukamoto, T. & Koga, O. Electrocatalytic process of CO selectivity in electrochemical reduction of $\\mathrm{CO}_{2}$ at metal electrodes in aqueous media. Electrochim. Acta 39, 1833–1839 (1994). \n17. Hori, Y. Electrochemical $\\mathrm{CO}_{2}$ reduction on metal electrodes. Mod. Asp. Electrochem. 42, 89–189 (2008). \n18. Zhang, S., Kang, P. & Meyer, T. J. Nanostructured tin catalysts for selective electrochemical reduction of carbon dioxide to formate. J. Am. Chem. Soc. 136, 1734–1737 (2014). \n19. Chen, Y. & Kanan, M. W. Tin oxide dependence of the $\\mathrm{CO}_{2}$ reduction efficiency on tin electrodes and enhanced activity for tin/tin oxide thin-film catalysts. J. Am. Chem. Soc. 134, 1986–1989 (2012). \n20. Lei, F. et al. Metallic tin quantum sheets confined in graphene toward highefficiency carbon dioxide electroreduction. Nat. Commun. 7, 12697 (2016). \n21. DiMeglio, J. L. & Rosenthal, J. Selective conversion of $\\mathrm{CO}_{2}$ to CO with high efficiency using an inexpensive bismuth-based electrocatalyst. J. Am. Chem. Soc. 135, 8798–8801 (2013). \n22. Zhang, Z. et al. Rational design of Bi nanoparticles for efficient electrochemical $\\mathrm{CO}_{2}$ reduction: the elucidation of size and surface condition effects. ACS Catal. 6, 6255–6264 (2016). \n23. Medina-Ramos, J., DiMeglio, J. L. & Rosenthal, J. Efficient reduction of $\\mathrm{CO}_{2}$ to CO with high current density using in situ or ex situ prepared Bi-based materials. J. Am. Chem. Soc. 136, 8361–8367 (2014). \n24. Kim, S. et al. Shape-controlled bismuth nanoflakes as highly selective catalysts for electrochemical carbon dioxide reduction to formate. Nano Energy 39, 44–52 (2017). \n25. Koh, J. H. et al. Facile $\\mathrm{CO}_{2}$ electro-reduction to formate via oxygen bidentate intermediate stabilized by high-index planes of Bi dendrite catalyst. ACS Catal. 7, 5071–5077 (2017). \n26. Lee, C. W. et al. Selective electrochemical production of formate from carbon dioxide with bismuth-based catalysts in an aqueous electrolyte. ACS Catal. 8, 931–937 (2018). \n27. Pizzi, G. et al. Performance of arsenene and antimonene double-gate MOSFETs from first principles. Nat. Commun. 7, 12585 (2016). \n28. Pourbaix, M. Electrochemical corrosion of metallic biomaterials. Biomaterials 5, 122–134 (1984). \n29. Lv, W. et al. Electrodeposition of nano-sized bismuth on copper foil as electrocatalyst for reduction of $\\mathrm{CO}_{2}$ to formate. Appl. Surf. Sci. 393, 191–196 (2017). \n30. Kumar, B. et al. Reduced $\\mathrm{SnO}_{2}$ porous nanowires with a high density of grain boundaries as catalysts for efficient electrochemical $\\mathrm{CO}_{2}$ -into-HCOOH conversion. Angew. Chem. Int. Ed. 56, 3645–3649 (2017). \n31. Peterson, A. A. et al. How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels. Energy Environ. Sci. 3, 1311–1315 (2010). \n32. Jiao, Y., Zheng, Y., Davey, K. & Qiao, S.-Z. Activity origin and catalyst design principles for electrocatalytic hydrogen evolution on heteroatom-doped graphene. Nat. Energy 1, 16130 (2016). \n33. Lee, C. W., Cho, N. H., Yang, K. D. & Nam, K. T. Reaction mechanisms of the electrochemical conversion of carbon dioxide to formic acid on tin oxide electrodes. ChemElectroChem 4, 2130–2136 (2017). \n34. Yoo, J. S. et al. Theoretical insight into the trends that guide the electrochemical reduction of carbon dioxide to formic acid. ChemSusChem 9, 358–363 (2016). \n35. Wang, H. et al. Efficient electrocatalytic reduction of $\\mathrm{CO}_{2}$ by nitrogen-doped nanoporous carbon/carbon nanotube membranes: A step towards the electrochemical $\\mathrm{CO}_{2}$ refinery. Angew. Chem. Int. Ed. 56, 7847–7852 (2017). \n36. Detweiler, Z. M., White, J. L., Bernasek, S. L. & Bocarsly, A. B. Anodized indium metal electrodes for enhanced carbon dioxide reduction in aqueous electrolyte. Langmuir 30, 7593–7600 (2014). \n37. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n38. Kresse, G. & Hafner, J. Ab initio molecular dynamics of liquid metals. Phys. Rev. B 47, 558–561 (1993). \n39. Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. \n6, 15–50 (1996). \n40. Bloechl, P. E. Projector augmented-wave method. Phys. Rev. B 50, \n17953–17979 (1994). \n41. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n42. Martyna, G. J., Klein, M. L. & Tuckerman, M. Nosé–Hoover chains: the canonical ensemble via continuous dynamics. J. Chem. Phys. 97, 2635–2643 (1992). \n43. Johnson III, R. D. Computational chemistry comparison and benchmark database. http://cccbdb.nist.gov/ (2016). \n44. Mathew, K., Sundararaman, R., Letchworth-Weaver, K., Arias, T. A. & Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 140, 084106 (2014). \n\n# Acknowledgements \n\nWe acknowledge the support from the Ministry of Science and Technology of China (2017YFA0204800), the National Natural Science Foundation of China (51472173, 51522208, and 21522305), the National Natural Science Foundation of Jiangsu Province (SBK2015010320 and BK20150045), the Priority Academic Program Development of Jiangsu Higher Education Institutions, Collaborative Innovation Center of Suzhou Nano Science and Technology and the “111” project. \n\n# Author contributions \n\nYanguang L. conceived the project and designed the experiments. N.H. and H.Y. synthesized the material and conducted electrochemical measurements. Y.W. and Yafei L. carried out theoretical calculations. J.D. collected TEM images. J.W. collected AFM images. N.H., Y.W., and Yanguang L. co-wrote the paper. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-03712-z. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1038_s41467-018-03207-x", + "DOI": "10.1038/s41467-018-03207-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-03207-x", + "Relative Dir Path": "mds/10.1038_s41467-018-03207-x", + "Article Title": "A low cost and high performance polymer donor material for polymer solar cells", + "Authors": "Sun, CK; Pan, F; Bin, HJ; Zhang, JQ; Xue, LW; Qiu, BB; Wei, ZX; Zhang, ZG; Li, YF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "The application of polymer solar cells requires the realization of high efficiency, high stability, and low cost devices. Here we demonstrate a low-cost polymer donor poly[(thiophene)-alt(6,7-difluoro-2-(2-hexyldecyloxy)quinoxaline)] (PTQ10), which is synthesized with high overall yield of 87.4% via only two-step reactions from cheap raw materials. More importantly, an impressive efficiency of 12.70% is obtained for the devices with PTQ10 as donor, and the efficiency of the inverted structured PTQ10-based device also reaches 12.13% (certificated to be 12.0%). Furthermore, the as-cast devices also demonstrate a high efficiency of 10.41% and the devices exhibit insensitivity of active layer thickness from 100 nm to 300 nm, which is conductive to the large area fabrication of the devices. In considering the advantages of low cost and high efficiency with thickness insensitivity, we believe that PTQ10 will be a promising polymer donor for commercial application of polymer solar cells.", + "Times Cited, WoS Core": 734, + "Times Cited, All Databases": 773, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000425594200003", + "Markdown": "# A low cost and high performance polymer donor material for polymer solar cells \n\nChenkai Sun 1,2, Fei Pan1,2, Haijun Bin1,2, Jianqi Zhang3, Lingwei Xue1, Beibei Qiu1, Zhixiang Wei3, Zhi-Guo Zhang1 & Yongfang Li1,2,4 \n\nThe application of polymer solar cells requires the realization of high efficiency, high stability, and low cost devices. Here we demonstrate a low-cost polymer donor poly[(thiophene)-alt(6,7-difluoro-2-(2-hexyldecyloxy)quinoxaline)] (PTQ10), which is synthesized with high overall yield of $87.4\\%$ via only two-step reactions from cheap raw materials. More importantly, an impressive efficiency of $12.70\\%$ is obtained for the devices with PTQ10 as donor, and the efficiency of the inverted structured PTQ10-based device also reaches $12.13\\%$ (certificated to be $12.0\\%$ . Furthermore, the as-cast devices also demonstrate a high efficiency of $10.41\\%$ and the devices exhibit insensitivity of active layer thickness from $100\\mathsf{n m}$ to $300\\mathsf{n m}$ , which is conductive to the large area fabrication of the devices. In considering the advantages of low cost and high efficiency with thickness insensitivity, we believe that PTQ10 will be a promising polymer donor for commercial application of polymer solar cells. \n\nPaoldnyvdmanhetravsgeoelsdarevcoefl losps(eoPlduStqCiuosi)nchklapyvreionrcercsesicivneengd,t ywleiagdrehstpbrewcaeadiugishne eorfaesintds flexibility in comparison with the traditional silicon-based solar cells1,2. Active layer of the PSCs is composed of a $\\boldsymbol{p}$ -type conjugated polymer as donor blending with a fullerene derivative or a nonfullerene $n$ -type organic semiconductor ( $\\overset{\\cdot}{n}$ -OS) as acceptor3–5. Photovoltaic power conversion efficiency (PCE), stability, and cost are the three most crucial issues that must be taken into account for the commercial application of PSCs. And the donor and acceptor photovoltaic materials play essential role for increasing PCE, improving stability and decreasing cost of the PSCs. \n\nThe concept of bulk-heterojunction PSCs was first proposed in 1995 (ref. 3), and PCE of the PSCs at that time was only ca. $1\\%$ which is far from considering application. Since then, therefore, the researchers mainly focused on increasing PCE of the PSCs by developing efficient photovoltaic materials (donor6–8 and acceptor9,10) and efficient electrode buffer layer materials11–16, and optimizing active layer morphology17–19, etc. For the PSCs with fullerene derivatives (especially $\\mathrm{PC}_{71}\\mathrm{BM}$ ) as acceptors, PCE has gradually increased to over $10\\%$ recently by designing lowbandgap polymer donors such as PTB7- $\\cdot\\mathrm{Th}^{\\dot{2}0}$ , PNTz4T21, and PffBT4T- $\\mathbf{\\sigma}.\\mathbf{C}_{9}\\mathbf{C}_{13}$ (ref. 22), etc. In recent 2 years, low-bandgap nonfullerene $n$ -OS acceptors, such as IDTBR23, $\\scriptstyle{m-\\operatorname{ITIC}^{24}}$ , IDIC25, etc., have attracted great attention owing to their advantages of broad and strong absorption, easy tuning electronic energy levels, and high morphology stability in comparison with the fullerene derivative acceptors26. PCE of the PSCs with $n$ -OS as acceptors has rapidly increased to over $11\\%$ by using medium bandgap polymer donors such as J71 (ref. 27), PBDB- $\\cdot\\mathrm{T}^{28}$ , $\\mathrm{PB}3\\mathrm{T}^{29}$ , etc. \n\nNow, the PCE has reached the threshold for application. Next step, we should consider the stability and cost issues for commercial application of the PSCs. However, very few efforts have been made on reducing the costs of the photovoltaic materials, and costs of the efficient polymer donors reported so far were too high to meet commercial application of the PSCs due to their complicated molecular structures, verbose multi-steps synthesis, and multiple purifications30. Actually, poly(3-hexylthiophene) (P3HT) is still the main donor material for the fabrication of large area $\\mathrm{PSC}s^{31}$ , because it can be synthesized in large scale with relatively low cost. However, the photovoltaic performance of P3HT is poor32,33. Hence, developing low-cost and efficient polymer donors becomes one of the greatest challenges for the application of PSCs. \n\nHerein, we design and synthesize a low-cost polymer donor poly [(thiophene)-alt-(6,7-difluoro-2-(2-hexyldecyloxy)quinoxaline)] (PTQ10) (Fig. 1a). The molecular design strategy of PTQ10 is based on the donor–acceptor (D–A) copolymerization concept, using simple thiophene ring as donor unit and difluorinesubstituted quinoxaline as acceptor unit. The alkoxy side chain on quinoxaline unit is to ensure good solubility and to enhance absorption of the polymer, while the difluorine substituents are for down-shifting the highest occupied molecular orbital (HOMO) energy level and increasing hole mobility of the polymer donor34. PTQ10 possesses a simple molecular structure and can be synthesized with low cost and high overall yield of $87.4\\%$ via only two-step reactions from cheap raw materials. More importantly, the optimized PSCs with PTQ10 as donor and an $n{\\mathrm{-}}\\mathrm{OS}$ IDIC as acceptor demonstrate an impressive PCE of $12.70\\%$ which is one of the highest PCE among the singlejunction PSCs reported so far, and the as-cast devices without any post-processing also demonstrate a high PCE of $10.41\\%$ . Furthermore, the devices have good reproducibility and have high tolerance of the active layer thickness with a PCE over $10\\%$ even at an active layer thickness of $310\\mathrm{nm}$ . The results indicate that PTQ10 is a promising polymer donor for commercial products, and it will make the application of PSCs highly promising. \n\n# Results \n\nSynthesis and characterization of PTQ10. The synthetic route of PTQ10 is depicted in Fig. 1c, and the detailed synthesis procedures are described in the Methods section. The synthetic route of monomer 2 was carefully designed with cheap raw material and efficient reaction for realizing low-cost synthesis. PTQ10 possesses good solubility in common organic solvents. Its thermal decomposition temperature $(T_{\\mathrm{d}})$ at $5\\%$ weight loss is measured to be $383^{\\circ}\\mathrm{C}$ (Supplementary Fig. 1a), indicating its good thermal stability for the application in PSCs. \n\nElectronic energy levels of PTQ10 were measured by electrochemical cyclic voltammetry. The $E_{\\mathrm{HOMO}}$ and $E_{\\mathrm{LUMO}}$ of PTQ10 were calculated to be $-5.54\\mathrm{eV}$ and $-2.98\\mathrm{eV}$ (Fig. 1d) from onset oxidation and onset reduction potentials, respectively (Supplementary Fig. 1b). Figure 1e shows UV–vis absorption spectra of PTQ10 in chloroform solution and in thin film, and the absorption spectrum of IDIC film for comparison. PTQ10 film displays a strong absorption from 450 to $620\\mathrm{nm}$ with an absorption edge at $645\\mathrm{nm}$ which corresponds to an optical bandgap of $1.92\\mathrm{eV}$ . PTQ10 and IDIC films display complementary absorption in the wavelength region from 400 to $800\\mathrm{nm}$ , which will benefit to the solar light harvest for the PSCs with PTQ10 as donor and IDIC as acceptor. \n\nPhotovoltaic properties. In order to investigate photovoltaic properties of PTQ10, we fabricated the traditional structured PSCs with PTQ10 as donor, $n$ -OS IDIC as acceptor, PEDOT: PSS (poly(3,4-ethylenedioxythiophene):poly(styrene-sulfonate) as anode buffer layer and PDINO (perylene diimide functionalized with amino N-oxide) as cathode buffer layer16 (Fig. 1b). It should be mentioned that $\\dot{\\mathrm{IDIC}}^{25,35}$ was selected as acceptor because it possesses a simpler structure with alkyl side chains on its smaller fused ring core and relatively low-cost synthesis in comparison with the widely used $n$ -OS acceptors $\\mathrm{I}\\dot{\\mathrm{TIC}}^{10}$ , etc. Photovoltaic performances of the PSCs were optimized by using different donor/acceptor weight ratio and different active layer thickness, and by the treatment of thermal annealing (TA) and solvent vapor annealing (SA). The optimized device fabrication conditions include the donor/acceptor weight ratio of 1:1, active layer thickness of $130\\mathrm{nm}$ , TA at $\\bar{1}40^{\\circ}\\mathrm{C}$ for $5\\mathrm{min}$ , and SA by chloroform solvent for $30{\\mathrm{~s}}.$ Figure 2a shows current density–voltage $\\left(J-$ $V_{\\sun}$ curves of the optimal PSCs based on PTQ10: IDIC with or without TA and SA treatments, and the corresponding photovoltaic parameters are listed in Table 1. \n\nIt can be seen from Table 1 that all of the PSCs exhibit high $V_{\\mathrm{oc}}$ of $0.960{\\sim}0.995\\mathrm{V}$ , which should be benefitted from the lowerlying $E_{\\mathrm{HOMO}}$ $(-5.54\\mathrm{eV})$ of PTQ10. The $V_{\\mathrm{oc}}$ decreased from $0.995\\mathrm{V}$ to $0.972{\\mathrm{V}}$ and $0.969\\mathrm{V}$ when the devices were treated with TA and $\\mathrm{TA}+\\mathrm{SA}$ , respectively, which could be ascribed to the red-shifted absorption (the reduced optical band gap) of PTQ10 and IDIC treated with TA and $\\mathrm{TA}+\\mathrm{SA}$ (Supplementary Fig. 2a and 2b). The as-cast PSCs without post-processing show an impressive PCE of $10.41\\%$ , and the PCE increased to $\\bar{1}1.65\\%$ and $12.70\\%$ , respectively, after TA and $\\mathrm{TA}+\\mathrm{SA}$ treatments. To our knowledge, the PCE of $12.70\\%$ is one of the highest efficiencies among the single-junction PSCs reported to date. In addition, it is worth noticing that PCE of $10.41\\%$ for the as-cast devices is the highest efficiency in the PSCs without posttreatments, and the simple device fabrication process for the ascast devices will significantly reduce device fabrication costs, which is very important for future industrial production of the PSCs. \n\n![](images/64b36506df5669c2b256ef9299814e57758d8f58e6063c2db5a8b10d8d2334af.jpg) \nFig. 1 Photovoltaic materials and device structure of the PSCs. a Molecular structures of the polymer donor PTQ10 and the $\\mathfrak{n}$ -OS acceptor IDIC. b Devices architecture of the traditional structured PSCs. c Synthetic route of PTQ10. d Energy level diagram of the related materials used in the PSCs. e Normalized absorption spectra of the donor PTQ10 and the acceptor IDIC \n\nThe external quantum efficiency (EQE) spectra of the optimized devices with different post-processing treatments are shown in Fig. 2b. All the three PSCs exhibit broad light response with high EQE values over $50\\%$ from 450 to $730\\mathrm{nm}$ , which means high photoelectric conversion efficiency in the PTQ10: IDIC blend films. The current density values integrated from the EQE spectra under the AM 1.5G spectrum are $15.{\\overset{\\smile}{3}}0\\operatorname*{mA}\\operatorname{cm}^{-2}$ for the as-cast device, $16.01\\mathrm{mA}\\mathrm{cm}^{-2}$ for the TA-treated device, and $17.08\\mathrm{mAcm}^{-2}$ for the $\\mathrm{TA}+\\mathrm{SA}$ -treated device, which are consistent quite well with the $J_{\\mathrm{sc}}$ values obtained from $J{-}V$ curves within $4\\%$ mismatch, indicating the reliability of the measured $J_{\\mathrm{sc}}$ data. The enhanced EQE value and current density of the PSCs with the TA or $\\mathrm{TA}+\\mathrm{SA}$ treatments should be ascribed to its redshifted absorption, enhanced absorption coefficient (Supplementary Fig. 2c), and the broadened EQE spectra (Fig. 2b) in comparison with that of the blend films without the treatment (as-cast). \n\nIn order to confirm the high PCE of the PTQ10-based PSCs, we fabricated the inverted structured PSCs with the device structure of ITO/ZnO/PTQ10: $\\mathrm{IDIC/MoO_{3}/A g},$ in considering the better stability of the inverted PSCs for sending the devices out to the National Institute of Metrology (NIM) of China for the efficiency confirmation. The inverted PSC based on PTQ10: IDIC (1:1.5, w/w) with active layer thickness of $130\\mathrm{nm}$ and with the treatment of TA at $140^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ and SA by chloroform solvent for $30\\mathrm{{s}}$ showed a PCE of $12.13\\%$ with a $V_{\\mathrm{oc}}$ of $0.960\\mathrm{V}$ a $J_{\\mathrm{sc}}$ of $19.65\\mathrm{mAcm}^{-2}$ , and an fill factor (FF) of $64.29\\%$ , as shown in Table 1 and in Supplementary Fig. 3. The PCE of the inverted PSCs was confirmed to be $12.0\\%$ by NIM (see the Test Report of NIM in Supplementary Fig. 4 and the last line in Table 1). The slightly lower PCE of the inverted device is due to its lower fill factor which could be ascribed to the un-optimized cathode and anode buffer layer materials of the inverted PSCs. \n\nBatch to batch variation of the polymers is an unfavorable factor to the commercial application of $\\mathrm{PSC}s^{36}$ . Supplementary Table 1 lists the photovoltaic parameters of the optimized traditional structured PSCs based on PTQ10: IDIC with using the PTQ10 samples synthesized in five batches to investigate the photovoltaic repeatability of PTQ10. The photovoltaic performance of PTQ10 show less batch to batch variation with the PCE values ranging from $11.90\\%$ to $12.70\\%$ , which indicates the good photovoltaic repeatability of PTQ10. \n\nThe hole mobility $(\\mu_{\\mathrm{h}})$ and electron mobility $(\\mu_{\\mathrm{e}})$ of the PTQ10: IDIC blend layers without (as-cast) and with the TA and $\\mathrm{TA}+\\mathrm{SA}$ treatments were measured using space charge limited current (SCLC) method with hole-only (ITO/PEDOT: PSS /PTQ10: IDIC/Au) and electron-only $(\\mathrm{ITO}/\\mathrm{ZnO}/\\mathrm{PTQ10}$ : IDIC/ PDINO/Al) devices, and the measurement results are shown in Supplementary Fig. 5. For the as-cast PTQ10: IDIC blend films, $\\mu_{\\mathrm{h}}$ and $\\mu_{\\mathrm{e}}$ are $0.3\\check{6}\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ and $3.43\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}s$ $-1$ , respectively, with $\\mu_{\\mathrm{e}}/\\mu_{\\mathrm{h}}$ of 9.53. While $\\mu_{\\mathrm{h}}$ and $\\mu_{\\mathrm{e}}$ increased to $3.21\\times\\dot{1}0^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\dot{s}^{-1}$ and $4.80\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{\\dot{-}1}s^{-1}$ , respectively, after TA treatment with a balanced $\\mu_{\\mathrm{e}}/\\mu_{\\mathrm{h}}$ of 1.50. With TA $+\\operatorname{SA}$ treatment, the $\\mu_{\\mathrm{h}}$ and $\\mu_{\\mathrm{e}}$ values were further improved to $5.04\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\dot{s}^{-1}$ and $6.72\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}s^{-1}$ , respectively, with more balanced $\\mu_{\\mathrm{e}}/\\mu_{\\mathrm{h}}$ ratio of 1.33. The increased and more balanced charge mobility suggests better charge transfer capability of the PTQ10: IDIC blend films after TA or $\\mathrm{TA}+\\mathrm{SA}$ treatments. This finding together with the enhanced absorption and the reduced charge carrier recombination after $\\mathrm{TA}{\\bar{+}}\\mathrm{SA}$ treatment could be collectively responsible for the improved $J_{\\mathrm{sc}}$ and FF of the optimized devices. \n\n![](images/4619fc88d0221d1dc184e3b02c1affff17c30f63962d10710af242b11949d292.jpg) \nFig. 2 Photovoltaic performance of the PSCs based on PTQ10: IDIC. a $J-V$ curves of the traditional structured PSCs based on PTQ10: IDIC (1:1, $\\mathsf{w}/\\mathsf{w},$ , under the illumination of AM1.5G, $100\\mathsf{m w c m}^{-2}$ . b EQE spectra of the corresponding PSCs. The dependence of $J_{\\mathsf{s c}}$ $\\mathbf{\\sigma}_{\\left(\\bullet\\right)}$ and $V_{\\mathsf{o c}}$ (d) on light intensity $(P_{\\mathrm{Iight}})$ of the optimized PSCs \n\n
Table 1 Photovoltaic parameters of the PSCs based on PTQ1O: IDIC
DevicesVoc (V) Jsc (mA cm-2)FF (%)PCE (%)
As-casta0.995 (0.995 ± 0.003)d16.07 (15.70 ± 0.16)65.10 (64.89 ± 0.45)10.41 (10.14 ± 0.14)
TAa0.972 (0.962 ± 0.004)16.61 (16.61± 0.22)72.13 (71.55 ± 0.71)11.65 (11.43 ± 0.10)
TA+SAa0.969 (0.962± 0.005)17.81 (17.44 ± 0.30)73.60 (73.26 ± 0.63)12.70 (12.29 ± 0.18)
TA+SAb0.960 (0.960 ±0.003)19.65 (19.69 ± 0.27)64.29 (63.55 ± 1.30)12.13 (12.01± 0.10)
TA+SAC0.9620.1262.112.0
aTraditional structured PSCs with donor:acceptor weight ratio of 1:1 blnvertedstructuredPSCswithadevicestructureofITO/ZnO/PTQ:DIC/MoO/Agandwithdonoracceptorweightratiof1:1.5 cConfirmed photovoltaic performance of the inverted PSCs by NIM
\n\nFor application of the PSCs, stability of the devices is one of the crucial issues besides photovoltaic performance and cost37. Here, the device stability was tested for the inverted PSCs based on \n\nPTQ10: IDIC with simple encapsulation by ultraviolet-curable epoxy and thin glass slides. Supplementary Fig. 6 shows the results of devices stability experiments. The PCE of the invertedstructured PSCs based on PTQ10: IDIC remained $88.27\\%$ and $87.82\\%$ of their initial value after approximately $\\boldsymbol{1000}\\mathrm{h}$ of storage under $\\mathrm{N}_{2}$ and air atmosphere, respectively. Then the efficiency remain almost unchanged in the following $1000\\mathrm{h}$ . The results indicate good stability of the PSCs based on PTQ10: IDIC. \n\nCharge carrier recombination. To understand the effect of TA or $\\mathrm{TA}+\\mathrm{SA}$ treatments on the enhanced photovoltaic performance, the charge carrier recombination behavior in the traditional structured PSCs was studied by measuring the dependence of $J_{\\mathrm{sc}}$ and $V_{\\mathrm{oc}}$ on light intensity $(P_{\\mathrm{light}})$ . The relationship of $\\dot{J}_{s c}$ and $P_{\\mathrm{light}}$ can be depicted by the formula $J_{\\mathrm{sc}}\\propto(P_{\\mathrm{light}})^{\\alpha}$ , where the value of $\\alpha$ indicates the degree of bimolecular recombination. The value of $\\alpha$ should be 1 when bimolecular recombination do not occur in donor/acceptor blend films, and there is some bimolecular recombination if $\\alpha$ value is smaller than 1 (ref. 38). Figure 2c displays the plots of $\\log{J_{\\mathrm{sc}}}$ versus log $P_{\\mathrm{light}},$ and $\\alpha$ values are 0.95, 0.96, and 1.00 for the devices without (as-cast), with TA, and with $\\mathrm{TA}+\\mathrm{SA}$ treatments, respectively. The gradually increased values of $\\alpha$ indicate the reduced bimolecular recombination when the blend films are processed with TA and $\\mathrm{TA}+\\mathrm{SA}$ compared to the as-cast devices. Especially, $\\alpha$ value of 1 for the PSCs with $\\mathrm{TA}+\\mathrm{SA}$ treatment indicates that there is no bimolecular recombination in the $\\mathrm{TA}+\\mathrm{SA}$ treated devices. For the as-cast devices and TAtreated devices, another plausible reason for the deviation of the $\\alpha$ values from unity, can be understood in term of the build-up of space-charge in the device due to the unbalanced electron-hole mobility as indicated by Blom’s work39,40. Figure 2d shows the plots of $V_{\\mathrm{oc}}$ versus ln $(\\dot{P}_{\\mathrm{light}})$ of the PSCs. If bimolecular recombination is the exclusive recombination form, the slope of the fitting straight line of $V_{\\mathrm{oc}}$ versus ln $(P_{\\mathrm{light}})$ should be $k T/e$ (where $e$ is the elementary charge, $k$ is the Boltzmann constant, and $T$ is the Kelvin temperature)41. The slopes of the fitting lines for the as-cast, TA-treated, and $\\mathrm{TA}+\\mathrm{SA}$ -treated devices are $0.920k T/e$ , $0.924k T/e_{\\mathrm{:}}$ , and $0.988k T/e$ , respectively. The slope very close to $k T/$ $e$ for the $\\mathrm{TA}+\\mathrm{SA}$ -treated PSCs indicates that almost no other recombination occurs in the devices with $\\mathrm{TA}+\\mathrm{SA}$ treatment. The results of $J_{s c}$ and $V_{\\mathrm{oc}}$ dependence on $P_{\\mathrm{light}}$ indicate that there are very little charge carrier recombination in the optimized PSCs treated with $\\mathrm{TA}+\\mathrm{SA}$ , which consequently results in the best PCE of $12.70\\%$ for the PSCs with $\\mathrm{TA}+\\mathrm{SA}$ treatment. \n\n![](images/2a47860e6b5f97428177792eb2ade5a53541ad7adb6b1baa2a8b774c2874bccf.jpg) \nFig. 3 Plots and images of the GIWAXS measurements. Line cuts of the GIWAXS images of neat PTQ10 film (a), neat IDIC film $(\\pmb{6})$ , and PTQ10: IDIC blend films without (as-cast) (c), with TA treatment (d), and with ${\\mathsf{T A}}+{\\mathsf{S A}}$ treatment (e). GIWAXS images of neat PTQ10 film $\\mathbf{\\eta}(\\bullet),$ neat IDIC film ${\\bf\\Pi}({\\bf g})$ and PTQ10: IDIC blend films without (as-cast) ${\\bf\\Pi}({\\bf h})$ , with TA treatment (i), and with $\\mathsf{T A}+\\mathsf{S A}$ treatment $\\mathbf{\\eta}(\\mathbf{j})$ \n\nMorphological characterization. Morphology of the active layer is a critical factor to determine the photovoltaic performance of the $\\mathrm{PSCs}^{42,43}$ . Here, the grazing incident wide-angle X-ray diffraction (GIWAXS) was employed to study the effect of different post treatments on the molecular packing and material crystallinity features within the PTQ10: IDIC blend films. Figure 3 shows the plots and images of GIWAXS measurements. For the neat PTQ10 film, the laminar diffraction peaks and $\\pi-\\pi$ stacking diffraction peaks located at $0.28\\mathring{\\mathrm{A}}^{-1}$ and $1.76\\mathring{\\mathrm{A}}^{-1}$ (Fig. 3a, f) respectively, corresponding to the lamellar distance of $22.44\\mathring{\\mathrm{A}}$ and $\\pi{-}\\pi$ stacking distance of $3.57\\mathring\\mathrm{A}$ , and the neat IDIC film shows the lamellar distance of $15.71\\mathring\\mathrm{A}$ and $\\pi{-}\\pi$ stacking distance of $3.50\\mathrm{\\AA}$ (Fig. 3b, g). The strong $\\pi{-}\\pi$ stacking diffraction peaks in the out-of-plane (OOP) direction and weak $\\pi{-}\\pi$ stacking diffraction peaks in the in-plane (IP) direction of both neat PTQ10 and IDIC film suggest strong preference of face-on orientation in the vertical direction of substrate for the molecular packing, which is beneficial for efficient charge transport. The GIWAXS plots of blend films demonstrate microstructural features of its individual components. For the PTQ10: IDIC blend films with TA treatment (Fig. 3d, i), the molecular packing exhibit preferred and enhanced face-on orientation at $1.8\\dot{1}\\mathring{\\mathrm{A}}^{-1}$ with stronger and sharper $\\pi{-}\\pi$ stacking peaks in OOP direction in comparison with the as-cast films. Moreover, the $\\pi{-}\\pi$ stacking diffraction peaks intensity at $1.81\\mathring{\\mathrm{A}}^{-1}$ in OOP direction was further improved with $\\mathrm{TA}+\\mathrm{S}\\dot{\\mathrm{A}}$ treatment (Fig. 3e, j), indicating the enhanced charge transport behavior in the vertical direction of substrate in the devices treated by TA or $\\mathrm{TA}+\\mathrm{SA}$ . Furthermore, the $\\pi{-}\\pi$ stacking distance is decreased to $3.47\\mathring\\mathrm{A}$ for the TA-treated and $\\mathrm{TA}+\\mathrm{SA}-$ treated blend films in comparison with the as-cast films with the $\\pi{-}\\pi$ stacking distance of $\\dot{3}.53\\mathring\\mathrm{A}$ , suggesting more tighter molecular packing after the treatment. The results indicate that the preferred face-on orientation, the closer $\\pi{-}\\pi$ stacking, and the higher crystalline characteristics of the post-treated blend films (especially for the $\\mathrm{TA}+\\mathrm{SA}$ -treated blend films), assisted charge transport, suppressed charge carrier recombination, and eventually improved the photovoltaic performance. Furthermore, transmission electron microscope (TEM) measurements were carried out to study the effect of processing conditions on the morphology. From the TEM images (Supplementary Fig. 7), the \n\nPTQ10: IDIC blend films show obviously fibrillary networks and increased domain size after TA or $\\mathrm{TA}+\\mathrm{SA}$ treatments. \n\nIn addition, photoinduced force microscopy (PiFM)44, an emergent technology that demonstrates the spatially nm-scale patterns of the individual chemical components in their blend films45, was used to study the effect of processing conditions on the morphology. The PiFM images at the characteristic Fourier transform infrared (FTIR) wavelengths corresponding to absorption peaks of polymer donor PTQ10 $(805\\mathrm{cm}^{-1})$ and acceptor IDIC $(1703\\mathrm{cm}^{-1}\\mathrm{\\underline{{{\\cdot}}}}$ ) with different post treatments are shown in Fig. 4. From the PiFM images, the TA-treated PTQ10: IDIC blend films (Fig. 4b) show obviously increased phase separation and domain size in comparison with the as-cast films (Fig. 4a), and the further increased phase separation and domain size was observed in the $\\mathrm{TA}+\\mathrm{SA}$ -treated films (Fig. 4c). The PiFM results are consistent with the GIWAX and TEM measurements. The results indicate that the gradually enhanced photovoltaic properties of the devices with TA and $\\mathrm{TA}+\\mathrm{SA}$ treatment could be ascribed to the larger phase domains and the more continuous donor/acceptor nano-scale phase-separated interpenetrating networks. \n\nThickness dependence of the photovoltaic performance. For large area fabrication of the PSCs, the active layer thickness is difficult to be precisely controlled46. Therefore, it is crucial to develop the thickness-insensitive polymer donors with excellent photovoltaic performance. Here, we investigated the effect of active layer thickness on the photovoltaic performance of the traditional structured PSCs based on PTQ10: IDIC with active layer thickness ranging from 60 to $310\\mathrm{nm}$ . Figure 5a, b shows the thickness dependence of photovoltaic performance, and Supplementary Table 2 lists the corresponding photovoltaic parameters of the devices. The $V_{\\mathrm{oc}}$ values are nearly constant with a slightly decrease for the active layers thicker than $130\\mathrm{nm}$ (Fig. 5a). The $J_{\\mathrm{sc}}$ values show an increasing trend from approximately 15 to 19 $\\operatorname{mA}{\\mathrm{cm}^{-2}}$ with the increase of the active layer thickness. The changes of $J_{s c}$ should be the trade-off results between absorbance and charge recombination, the thicker PTQ10: IDIC active layers will enhance the light harvest which is beneficial to higher $J_{s c},$ but it also increases charge recombination which will decrease $J_{\\mathrm{sc}}$ FF shows relatively significant thickness-dependent behavior, the FF values remain high and close to $72\\%$ even with the active layer thickness of up to $210\\mathrm{nm}$ , but it sharply decreased to ca. $58\\%$ as the active layer thickness increased to $310\\mathrm{nm}$ (Fig. 5b), which could be due to the increased series resistance of the PSCs with the too thick active layer. As a result, the highest PCE of $12.70\\%$ is obtained for the device with the active layer thickness of $130\\mathrm{nm}$ . It should be noted that the high PCE of $11.59\\%$ was also obtained even the active layer thickness increased to $210\\mathrm{nm}$ . Amazingly, even for the PSCs with a thicker active layer of $310\\mathrm{nm}$ , its PCE still reached a high value of $10.31\\%$ . The excellent and thicknessinsensitive photovoltaic performance of the PSCs based on PTQ10: IDIC makes it a strong candidate for large area fabrication and commercial applications of the PSCs. \n\nCost and PCE analysis. PTQ10 has extremely simple molecular structure (Fig. 1a) in comparison with the efficient polymer donors reported in literatures, and it can be easily synthesized via only two-step reactions from initial raw materials and once purification. Besides, all of the raw materials, such as 3,6- dibromo-4,5-difluorobenzene-1,2-diamine, glyoxylic acid, 1- bromo-2-hexyldecane, and 2,5-bis(trimethylstannyl)thiophene, are inexpensive and available from bulk chemical suppliers. Consequently, PTQ10 exhibits extremely high synthetic accessibility and low cost for commercial production, potentially reducing the energy pay back times. \n\n![](images/c1748b4075bd6fdacaa78a16cb67dfdad36ce9277329746e6ed702fbef16f91a.jpg) \nFig. 4 FTIR spectra and PiFM topography images. FTIR spectra and PiFM images of PTQ10: IDIC blend films based on FTIR absorption at different wave numbers (PTQ10, $805\\mathsf{c m}^{-1}$ and IDIC, $1703\\ c m^{-1};$ : without (as-cast) (a), with TA treatment (b), and with $\\mathsf{T A}+\\mathsf{S A}$ treatment (c) \n\n![](images/fe592709418e69aa56b23069dbcf7bad045bd6656bbdee90c81097814ca65c88.jpg) \nFig. 5 Thickness dependence of the photovoltaic performance. Plots of $V_{\\mathrm{oc}}$ or $J_{\\mathsf{s c}}$ (a) and FF or PCE $(\\pmb{6})$ vs. the active layer thickness ranging from 60 to 310 nm for the traditional structured PSCs \n\n![](images/1f3ef4fa2423c58eca80e33050647bcac1cb313c7ae51c2b32ac9c708c580fd9.jpg) \nFig. 6 Cost and PCE analysis of the PSCs. Plots of PCE vs. synthesis steps (a) and overall yield $(\\pmb{6})$ of the polymer donors reported in literatures with PC over $10\\%$ \n\nFigure 6a, b displays the plots of PCE values versus synthesis steps and overall yield of PTQ10 respectively in comparison with the efficient polymer donors with PCE over $10\\%$ reported in literatures. The corresponding statistical photovoltaic parameters are listed in Supplementary Table 3. It can be seen from the figures that the PTQ10-based PSCs has the highest PCE $(12.70\\%)$ with the minimum synthesis steps of 2 steps (which is ca. onethird or one-fifth of that for the other efficient polymer donors) and the highest overall yield of $87.4\\%$ (which is ca. 5–20 times of that for the other efficient polymer donors). The less synthetic steps of PTQ10 should be ascribed to its simplest D–A structure, and the high overall yield is benefitted from the high yield of its two stepwise reactions ( $91\\%$ and $96\\%$ ) and only once purification. The ultimate cost of organic photovoltaic materials reduces linearly with the reduction of the number of synthetic steps30, thus the ultimate cost of PTQ10 is only few tenths of other efficient donors. Besides, the high overall yield further increases its low-cost advantages. Obviously, PTQ10 possesses great superiority in both cost and photovoltaic performance, which will lead to a bright future for the commercial application of PSCs. \n\n# Discussion \n\nIn conclusion, a low-cost polymer donor PTQ10 with only two synthetic steps and high yield of $87.4\\%$ was designed and synthesized in pursuing low-cost polymer donor materials for future application of PSCs. PTQ10 possesses a broad and strong absorption band in the wavelength range of $450{-}620\\mathrm{nm}$ with a medium bandgap of $1.92\\mathrm{eV}$ and lower lying HOMO energy level of $-5.54\\mathrm{eV}$ . The traditional structured PSCs using PTQ10 as donor and a narrow bandgap $n$ -OS IDIC as acceptor demonstrated a high PCE of $12.70\\%$ , and its photovoltaic performance exhibits insensitivity of active layer thickness between 100 and ${300}\\mathrm{nm}$ , which is conductive to the large area fabrication of PSCs. The PCE of the inverted structured PSCs based on PTQ10: IDIC also reached $12.13\\%$ which was confirmed to be $12.0\\%$ by NIM. In comparison with the polymer donors reported in literatures with PCE over $10\\%$ , PTQ10 shows the great advantages of low cost (benefiting by less synthetic steps and high overall yield) and high photovoltaic performance. Therefore, we believe that PTQ10 is a highly promising polymer donor for large area fabrication of PSCs, and it will push the commercial application of PSCs forward. \n\n# Methods \n\nMaterials and synthesis. IDIC was purchased from Solarmer Materials Inc. Other chemicals and solvents were obtained from J&K, Alfa Aesar, and TCI Chemical Co., respectively. The monomer compound 2 and polymer PTQ10 was synthesized according to the synthetic route shown in Fig. 1c. The detailed synthesis procedures are described in the following47. \n\n5,8-dibromo-6,7-difluoro-2-(2-hexyldecyloxy)quinoxaline (compound 2): \n\nTo a two-necked, round-bottom flask, 3,6-dibromo-4,5-difluorobenzene-1,2- diamine (compound 1) $(906\\mathrm{mg},3\\mathrm{mmol})$ , glyoxylic acid $(222\\mathrm{mg},3\\mathrm{mmol}$ ), and acetic acid $\\mathrm{(30mL)}$ are added. The mixture is warmed to $40^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ , and then the solution is stirred at room temperature for $^{3\\mathrm{h}}$ . The precipitate is collected by filtration and dried to get a white solid without further purification. The white solid $\\mathrm{^{'19,2.94mmol}},$ , potassium tert-butanolate $(395\\mathrm{mg},3.53\\mathrm{mmol})$ , and 1-bromo-2- hexyldecane (897 mg, $2.94\\mathrm{mmol}\\dot{}$ ) are dissolved in methanol $\\mathrm{\\Omega}_{\\mathrm{30}\\mathrm{mL}}$ ). The mixture is refluxed for $^{12\\mathrm{h}}$ , then cooled to room temperature. After that, the reaction mixture is poured into saturated $\\mathrm{\\DeltaNH_{4}C l}$ solution, extracted with dichloromethane, and washed with water. The organic extraction is dried over anhydrous $\\mathrm{{MgSO_{4}};}$ and the solvent is evaporated under reduced pressure. Compound 2 is obtained as colorless oil $(1.54~\\mathrm{g},2.73~\\mathrm{mmol})$ from the product through column chromatography on silica gel, with an overall yield of $91\\%$ . $^1\\mathrm{H}$ NMR $(400\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3},$ : $\\delta$ (p.p.m.) 8.50 (s, 1H), 4.49 (d, $J{=}5.7\\mathrm{Hz}$ , 2H), 1.95–1.86 $\\mathrm{(m,1H)}$ , 1.55–1.36 (m, 8H), 1.35–1.18 (m, 16H), 0.92–0.83 $(\\mathrm{m},6\\mathrm{H})$ ). $^{13}\\mathrm{C}$ NMR ${}^{\\prime}100\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3})$ : δ (p.p.m.) 158.69, 151.82, 149.33, 146.88, 140.66, 136.31, 133.26, 109.75, 107.60, 70.50, 37.46, 31.87, 31.36, 29.98, 29.61, 29.31, 26.84, 22.67, 14.09. \n\nPoly[(thiophene)-alt-(6,7-difluoro-2-(2-hexyldecyloxy)quinoxaline] (PTQ10): \n\nThe polymer PTQ10 is synthesized according to still-coupling polycondensation between compound 2 and 2,5-bis(trimethylstannyl)thiophene under protection of argon. Compound 2 $(112.8\\mathrm{mg},0.2\\mathrm{mmol}$ ), 2,5-bis(trimethylstannyl) thiophene $(82\\mathrm{mg},0.2\\mathrm{mmol})$ ), and anhydrous toluene $\\mathrm{\\Omega}^{\\mathrm{'10}\\mathrm{mL})}$ are added to a 25- mL double-neck round-bottom flask. The flask is flushed with argon for $10\\mathrm{min}$ , and then tetrakis(triphenylphosphine)palladium(0) $\\mathrm{(Pd(PPh}_{3})_{4}.$ , 8 mg) is added. After another flushing with argon for $15\\mathrm{min}$ , the reactant is heated to reflux for 32 h. Then the reactant is cooled down to room temperature, and extracted by Soxhlet extractor with methanol, hexane, and chloroform one by one. The polymer $\\mathbf{93\\mg}{\\mathrm{.}}$ yield $96\\%$ ) is recovered from the chloroform extract by precipitation in methanol and dried under vacuum. GPC: $M\\mathrm{n}=39.1\\mathrm{kDa}$ ; $M\\mathrm{w}/M\\mathrm{n}=2.1$ . Anal. Calcd for $\\mathrm{C}_{28}\\mathrm{H}_{36}\\mathrm{F}_{2}\\mathrm{N}_{2}\\mathrm{OS}$ $(\\%)$ : C, 69.10; H, 7.46; N, 5.76. Found $(\\%)$ : C, 68.08; H, 7.48; N, 5.71. $^1\\mathrm{H}$ NMR $\\mathrm{CDCl}_{3}$ , $400\\mathrm{MHz}$ ): $\\delta$ (p.p.m.) 8.81–7.72 (br, 3H), 4.89–4.03 (br, 2H), 2.43–0.53 (br, 31H). \n\nGeneral characterization. $^1\\mathrm{H}$ NMR and $^{13}\\mathrm{C}$ NMR spectra of the corresponding compounds were measured on a Bruker DMX-400 spectrometer using $d.$ –chloroform as solvent and trimethylsilane as the internal reference. Hightemperature gel permeation chromatography (GPC) measurements were carried out on Agilent PL-GPC 220 instrument, using 1,2,4-trichlorobenzene as the eluent at $160^{\\circ}\\mathrm{C}$ . Thermogravimetric analysis (TGA) was measured on a Perkin-Elmer TGA-7 thermogravimetric analyzer with a heating rate of $10^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ under a nitrogen flow rate of $100\\mathrm{mL}\\mathrm{min}^{-1}$ . UV–visible absorption spectra were measured on a Hitachi U-3010 UV–vis spectrophotometer. Electrochemical cyclic voltammograms was measured on a Zahner IM6e Electrochemical Workstation under a nitrogen atmosphere, with a Pt disk as working electrode, a $\\mathrm{\\Ag/AgCl}$ as reference electrode, and a $\\mathrm{Pt}$ wire as counter electrode in acetonitrile solution of tetrabutylammonium hexafluorophosphate $(n\\mathrm{-Bu_{4}N P F}_{6})$ , and ferrocene/ferrocenium $(\\mathrm{Fc}\\dot{/}\\mathrm{Fc}^{+})$ couple was used as an internal reference. \n\nMobility measurements. Hole mobility and electron mobility were measured using the space charge limited current (SCLC) method. The hole-only device with the device structure of ITO /PEDOT: PSS/PTQ10: IDIC/Au was used to measure the hole mobility, and the electron-only device with the device structure of ITO/ ZnO/PTQ10: IDIC/PDINO Al was used to measure the electron mobility. The hole and electron mobilities were calculated by MOTT–Gurney equation: \n\n$$\nJ=\\frac{9\\varepsilon_{0}\\varepsilon_{\\mathrm{r}}\\mu V^{2}}{8L^{3}},\n$$ \n\nwhere $J$ is the current density, $\\ensuremath{\\varepsilon}_{0}$ the dielectric constant of empty space, $\\varepsilon_{\\mathrm{r}}$ the relative dielectric constant of active layer materials which is taken to be 3 in the calculation, $\\mu$ the charge mobility, $V$ the internal voltage in the device, and $V=$ $V_{\\mathrm{appl}^{-}}V_{\\mathrm{bi}^{-}}\\dot{V}_{\\mathrm{s}},$ where $V_{\\mathrm{appl}}$ is the voltage applied to the devices, $V_{\\mathrm{bi}}$ the built-in voltage from the relative work function difference between the two electrodes (0.2 V for the hole-only device and $0\\mathrm{V}$ for the electron-only device), $V_{s}$ the voltage drop from the series resistance, and $L$ the thickness of the active layers. \n\nGIWAXS measurements. GIWAXS measurements were carried out using small angle X-ray scattering system (XEUSS, FRANCE Xenocs SA). The samples for the GIWAXS measurements were prepared on Si substrates using chloroform solutions of the samples. The $10\\mathrm{keV}$ X-ray beam was incident at a grazing angle of $0.13\\substack{-0.17^{\\circ}}$ . The scattered X-rays were detected using a Dectris Pilatus 2M photon counting detector. \n\nTEM characterization. The TEM images were obtained on JEM-1011. The active layer films for the TEM measurements were spin-coated onto ITO/PEDOT: PSS substrates, and the substrates with the active layers were submerged in deionized water to make the active layers fall off, then the active layer films were picked up by copper grids for TEM measurements. \n\nDevice fabrication and characterization. The PSCs based on PTQ10: IDIC were fabricated with a device structure of ITO/PEDOT: PSS/PTQ10: IDIC/PDINO/Al. A thin layer of PEDOT: PSS was prepared on precleaned ITO glass through spincoating a PEDOT: PSS aqueous solution (Baytron P VP AI 4083 from H. C. Starck) at $2000\\mathrm{rpm}$ and dried subsequently at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ in air. Then the device was transferred to a glove box filled with nitrogen, in which the active layer of PTQ10: IDIC was spin-coated from its chloroform solution onto the PEDOT: PSS layer at $3500\\mathrm{rpm}$ . After spin-coating, the active layers were annealed at $140^{\\circ}\\mathrm{C}$ for $5\\mathrm{min}$ for the devices with TA treatment, and then the active layers were treated by chloroform solvent for $30\\mathrm{{s}}$ for the devices with solvent annealing treatment. The thickness of the active layer is ca. $130\\mathrm{nm}$ . Then methanol solution of PDINO at a concentration of $1.0\\mathrm{mg}\\mathrm{{\\dot{m}L^{-1}}}$ was deposited upon the active layer at $3000\\mathrm{rpm}$ to afford a PDINO cathode buffer layer with thickness of ca. $10\\mathrm{nm}$ . Finally, cathode metal Al was deposited onto the cathode buffer layer PDINO at a pressure of ca. $5.0\\times10^{-5}\\mathrm{Pa}$ . The effective area of the devices was $4.7\\mathrm{mm}^{2}$ which was defined by \n\nOptical microscope (Olympus BX51). The current density–voltage $\\left(J-V\\right)$ curves of the PSCs were measured by scanning voltage from $-1.5\\mathrm{V}$ to $1.5\\mathrm{V}$ with a voltage step of $10\\mathrm{mV}$ and delay time of 1 ms on Keithley 2450 Source-Measure Unit in a glove box filled with nitrogen (oxygen and water contents are smaller than 0.1 ppm). Oriel Sol3A Class AAA Solar Simulator (model, Newport 94023A) with a 450 W xenon lamp and an air mass (AM) 1.5 filter was used as the light source. The light intensity was calibrated to be $100\\mathrm{mW}\\mathrm{cm}^{-2}$ by a Newport Oriel 91150V reference cell. For accurately measuring the photocurrent, mask with an area of 2.2 $\\mathrm{mm}^{2}$ was used to define the effective area of the devices. The results with or without mask showed consistent values with relative errors within $0.5\\%$ (the devices with mask give slightly higher PCE due to its slightly higher FF). The PCE results in the manuscript are obtained from the measurement without mask and PCE statistics were obtained using more than 20 individual devices fabricated under the same conditions. The EQE was measured by Solar Cell Spectral Response Measurement System QE-R3-011 (Enli Technology Co., Ltd., Taiwan). The light intensity at each wavelength was calibrated with a standard single-crystal Si photovoltaic cell. \n\nInverted devices were fabricated with a structure of $\\mathrm{ITO/ZnO/PTQ10}$ : IDIC $/\\mathrm{MoO}_{3}/\\mathrm{Ag}$ . The $Z\\mathrm{nO}$ precursor solution was prepared by dissolving $0.14{\\mathrm{g}}$ of zinc acetate dehydrate $\\mathrm{(Zn(CH_{3}C O O)_{2}{\\cdot}2H_{2}O}$ , $99.9\\%$ , Aldrich) and $0.5{\\mathrm{g}}$ of ethanolamine $\\mathrm{(NH_{2}C H_{2}C H_{2}O H}$ , $99.5\\%$ , Aldrich) in $5\\mathrm{ml}$ of 2-methoxyethanol $(\\mathrm{CH}_{3}\\mathrm{OCH}_{2}\\mathrm{CH}_{2}\\mathrm{OH}$ , $99.8\\%$ , J&K Scientific). A thin layer of $\\mathrm{znO}$ was deposited through spin-coating the $Z\\mathrm{nO}$ precursor solution on precleaned ITO glass at 5000 rpm and baked subsequently at $200^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . Then the device was transferred into a glove box filled with nitrogen, in which the active layer of PTQ10: IDIC (1: $1.5,\\mathrm{w/w})$ was spin-coated from its chloroform solution onto the $Z\\mathrm{nO}$ at $3500\\mathrm{rpm}$ . After that, the active layers were annealed at $140^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ for the devices with TA treatment, and treated by chloroform solvent for $30\\mathrm{{s}}$ for the devices with solvent annealing treatment. The thickness of the active layer is ca. $130\\mathrm{nm}$ . Finally, a layer of ca. 5 nm $\\mathrm{MoO}_{3}$ and then a $\\mathrm{Ag}$ layer of ca. $160\\mathrm{nm}$ were evaporated subsequently under high vacuum. \n\nDevice stability measurements. The inverted structured PSCs with device structure of ITO/ZnO/PTQ10: IDIC $/\\mathrm{MoO}_{3}/\\mathrm{Ag}$ for stability measurements were encapsulated by ultraviolet-curable epoxy and thin glass slides and stored in nitrogen and air atmosphere, respectively. \n\nData availability. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 29 November 2017 Accepted: 27 January 2018 \nPublished online: 21 February 2018 \n\n# References \n\n1. Service, R. F. Outlook brightens for plastic solar cells. Science 332, 293 (2011). \n2. Li, C., Liu, M., Pschirer, N. G., Baumgarten, M. & Mullen, K. Polyphenylenebased materials for organic photovoltaics. Chem. Rev. 110, 6817–6855 (2010). \n3. Yu, G., Gao, J., Hummelen, J. C., Wudl, F. & Heeger, A. J. Polymer photovoltaic cells: enhanced efficiencies via a network of internal donoracceptor heterojunctions. Science 270, 1789–1791 (1995). \n4. Thompson, B. C. & Frechet, J. M. Polymer-fullerene composite solar cells. Angew. Chem. Int. Ed. 47, 58–77 (2008). \n5. Li, G., Zhu, R. & Yang, Y. Polymer solar cells. Nat. Photon. 6, 153–161 (2012). \n6. Kim, Y. et al. A strong regioregularity effect in self-organizing conjugated polymer films and high-efficiency polythiophene:fullerene solar cells. Nat. Mater. 5, 197–203 (2006). \n7. Liang, Y. et al. For the bright future-bulk heterojunction polymer solar cells with power conversion efficiency of $7.4\\%$ . Adv. Mater. 22, E135–E138 (2010). \n8. Huo, L. et al. Replacing alkoxy groups with alkylthienyl groups: a feasible approach to improve the properties of photovoltaic polymers. Angew. Chem. Int. Ed. 50, 9697–9702 (2011). \n9. He, Y., Chen, H.-Y., Hou, J. & Li, Y. Indene−C60 bisadduct: a new acceptor for high-performance polymer solar cells. J. Am. Chem. Soc. 132, 1377–1382 (2010). \n10. Lin, Y. et al. An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174 (2015). \n11. Brabec, C. J., Shaheen, S. E., Winder, C., Sariciftci, N. S. & Denk, P. Effect of LiF/metal electrodes on the performance of plastic solar cells. Appl. Phys. Lett. 80, 1288–1290 (2002). \n12. Kim, J. Y. et al. New architecture for high-efficiency polymer photovoltaic cells using solution-based titanium oxide as an optical spacer. Adv. Mater. 18, 572–576 (2006). \n13. Sun, Y., Seo, J. H., Takacs, C. J., Seifter, J. & Heeger, A. J. Inverted polymer solar cells integrated with a low-temperature-annealed sol-gel-derived ZnO Film as an electron transport layer. Adv. Mater. 23, 1679–1683 (2011). \n14. He, Z. et al. Simultaneous enhancement of open-circuit voltage, short-circuit current density, and fill factor in polymer solar cells. Adv. Mater. 23, 4636–4643 (2011). \n15. Page, Z. A., Liu, Y., Duzhko, V. V., Russell, T. P. & Emrick, T. Fulleropyrrolidine interlayers: tailoring electrodes to raise organic solar cell efficiency. Science 346, 441–444 (2014). \n16. Zhang, Z.-G. et al. Perylene diimides: a thickness-insensitive cathode interlayer for high performance polymer solar cells. Energy Environ. Sci. 7, 1966 (2014). \n17. Li, G. et al. High-efficiency solution processable polymer photovoltaic cells by self-organization of polymer blends. Nat. Mater. 4, 864–868 (2005). \n18. Campoy-Quiles, M. et al. Morphology evolution via self-organization and lateral and vertical diffusion in polymer:fullerene solar cell blends. Nat. Mater. 7, 158–164 (2008). \n19. Ye, L. et al. From binary to ternary solvent: morphology fine-tuning of D/A blends in PDPP3T-based polymer solar cells. Adv. Mater. 24, 6335–6341 (2012). \n20. Chen, J. D. et al. Single-junction polymer solar cells exceeding $10\\%$ power conversion efficiency. Adv. Mater. 27, 1035–1041 (2015). \n21. Vohra, V. et al. Efficient inverted polymer solar cells employing favourable molecular orientation. Nat. Photon. 9, 403–408 (2015). \n22. Zhao, J. et al. Efficient organic solar cells processed from hydrocarbon solvents. Nat. Energy 1, 15027 (2016). \n23. Holliday, S. et al. High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor. Nat. Commun. 7, 11585 (2016). \n24. Yang, Y. et al. Side-chain isomerization on an n-type organic semiconductor ITIC acceptor makes $11.77\\%$ high efficiency polymer solar cells. J. Am. Chem. Soc. 138, 15011–15018 (2016). \n25. Lin, Y. et al. A facile planar fused-ring electron acceptor for as-cast polymer solar cells with $8.71\\%$ efficiency. J. Am. Chem. Soc. 138, 2973–2976 (2016). \n26. Li, S. et al. A spirobifluorene and diketopyrrolopyrrole moieties based nonfullerene acceptor for efficient and thermally stable polymer solar cells with high open-circuit voltage. Energy Environ. Sci. 9, 604–610 (2016). \n27. Bin, H. et al. $11.4\\%$ Efficiency non-fullerene polymer solar cells with trialkylsilyl substituted 2D-conjugated polymer as donor. Nat. Commun. 7, 13651 (2016). \n28. Zhao, W. et al. Fullerene-free polymer solar cells with over $11\\%$ efficiency and excellent thermal stability. Adv. Mater. 28, 4734–4739 (2016). \n29. Liu, D. et al. Molecular design of a wide-bandgap conjugated polymer for efficient fullerene-free polymer solar cells. Energy Environ. Sci. 10, 546–551 (2017). \n30. Osedach, T. P., Andrew, T. L. & Bulović, V. Effect of synthetic accessibility on the commercial viability of organic photovoltaics. Energy Environ. Sci. 6, 711–718 (2013). \n31. Dang, M. T., Hirsch, L. & Wantz, G. P3HT:PCBM, best seller in polymer photovoltaic research. Adv. Mater. 23, 3597–3602 (2011). \n32. Baran, D. et al. Reducing the efficiency-stability-cost gap of organic photovoltaics with highly efficient and stable small molecule acceptor ternary solar cells. Nat. Mater. 16, 363–369 (2017). \n33. Guo, X. et al. High efficiency polymer solar cells based on poly(3- hexylthiophene)/indene-C70 bisadduct with solvent additive. Energy Environ. Sci. 5, 7943 (2012). \n34. Zhang, Q., Kelly, M. A., Bauer, N. & You, W. The curious case of fluorination of conjugated polymers for solar cells. Acc. Chem. Res. 50, 2401–2409 (2017). \n35. Lin, Y. et al. Mapping polymer donors toward high-efficiency fullerene free organic solar cells. Adv. Mater. 29, 1604155 (2017). \n36. Chen, Y., Wan, X. & Long, G. High performance photovoltaic applications using solution-processed small molecules. Acc. Chem. Res. 46, 2645–2655 (2013). \n37. Jørgensen, M. et al. Stability of polymer solar cells. Adv. Mater. 24, 580–612 (2012). \n38. Koster, L. J., Kemerink, M., Wienk, M. M., Maturova, K. & Janssen, R. A. Quantifying bimolecular recombination losses in organic bulk heterojunction solar cells. Adv. Mater. 23, 1670–1674 (2011). \n39. Koster, L. J. A., Mihailetchi, V. D., Ramaker, R. & Blom, P. W. M. Light intensity dependence of open-circuit voltage of polymer:fullerene solar cells. Appl. Phys. Lett. 86, 123509 (2005). \n40. Koster, L. J. A., Mihailetchi, V. D., Xie, H. & Blom, P. W. M. Origin of the light intensity dependence of the short-circuit current of polymer:fullerene solar cells. Appl. Phys. Lett. 87, 203502 (2005). \n41. Kyaw, A. K. K. et al. Intensity dependence of current–voltage characteristics and recombination in high-efficiency solution-processed small-molecule solar cells. ACS Nano 7, 4569–4577 (2013). \n42. Huang, Y., Kramer, E. J., Heeger, A. J. & Bazan, G. C. Bulk heterojunction solar cells: morphology and performance relationships. Chem. Rev. 114, 7006–7043 (2014). \n43. Tumbleston, J. R. et al. The influence of molecular orientation on organic bulk heterojunction solar cells. Nat. Photon. 8, 385–391 (2014). \n44. Jahng, J. et al. Linear and nonlinear optical spectroscopy at the nanoscale with photoinduced force microscopy. Acc. Chem. Res. 48, 2671–2679 (2015). \n45. Qiu, B. et al. All-small-molecule nonfullerene organic solar cells with high fill factor and high efficiency over $10\\%$ . Chem. Mater. 29, 7543–7553 (2017). \n46. Sun, k et al. A molecular nematic liquid crystalline material for highperformance organic photovoltaics. Nat. Commun. 6, 6013 (2015). \n47. Wang, K., Zhang, Z.-G., Fu, Q. & Li, Y. Synthesis and photovoltaic properties of a D-A copolymer based on the 2,3-di(5-hexylthiophen-2-yl)quinoxaline acceptor unit. Macromol. Chem. Phys. 215, 597–603 (2014). \n\n# Acknowledgements \n\nThe work was supported by the Ministry of Science and Technology of China (973 project, No. 2014CB643501) and NSFC (Nos. 91633301, 91433117, 91333204, and 51673200) and the Strategic Priority Research Program of the Chinese Academy of Sciences, Grant No. XDB12030200. The authors would like to thank B.S. Runkun Huang from Institute of Chemistry, Chinese Academy of Sciences, for the help in TEM measurements, and to thank Dr. William Morrison from Molecular Vista, United States, for the help in the PiFM measurements. \n\n# Author contributions \n\nC.S., Z.Z., and Y.L. designed the polymer PTQ10, C.S. synthesized and characterized PTQ10. F.P. carried out the PSCs fabrication and characterization. H.B. and B.Q. participated in the discussion of the polymer synthesis. L.X. provided the cathode buffer layer material. J.Z. and Z.W. measured the GIWAXS diffraction patterns and provided the device fabrication conditions for the inverted structured PSCs. Y.L. supervised the project. C.S. and Y.L. wrote the paper. The first two authors contributed equally to this work. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-03207-x. \n\nCompeting interests: The authors declare no competing financial interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1002_aenm.201702019", + "DOI": "10.1002/aenm.201702019", + "DOI Link": "http://dx.doi.org/10.1002/aenm.201702019", + "Relative Dir Path": "mds/10.1002_aenm.201702019", + "Article Title": "Highly Reproducible Sn-Based Hybrid Perovskite Solar Cells with 9% Efficiency", + "Authors": "Shao, SY; Liu, J; Portale, G; Fang, HH; Blake, GR; ten Brink, GH; Koster, LJA; Loi, MA", + "Source Title": "ADVANCED ENERGY MATERIALS", + "Abstract": "The low power conversion efficiency (PCE) of tin-based hybrid perovskite solar cells (HPSCs) is mainly attributed to the high background carrier density due to a high density of intrinsic defects such as Sn vacancies and oxidized species (Sn4+) that characterize Sn-based HPSCs. Herein, this study reports on the successful reduction of the background carrier density by more than one order of magnitude by depositing near-single-crystalline formamidinium tin iodide (FASnI(3)) films with the orthorhombic a-axis in the out-of-plane direction. Using these highly crystalline films, obtained by mixing a very small amount (0.08 m) of layered (2D) Sn perovskite with 0.92 m (3D) FASnI(3), for the first time a PCE as high as 9.0% in a planar p-i-n device structure is achieved. These devices display negligible hysteresis and light soaking, as they benefit from very low trap-assisted recombination, low shunt losses, and more efficient charge collection. This represents a 50% improvement in PCE compared to the best reference cell based on a pure FASnI(3) film using SnF2 as a reducing agent. Moreover, the 2D/3D-based HPSCs show considerable improved stability due to the enhanced robustness of the perovskite film compared to the reference cell.", + "Times Cited, WoS Core": 741, + "Times Cited, All Databases": 769, + "Publication Year": 2018, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000424152200018", + "Markdown": "# Highly Reproducible Sn-Based Hybrid Perovskite Solar Cells with 9% Efficiency \n\nShuyan Shao, Jian Liu, Giuseppe Portale, Hong-Hua Fang, Graeme R. Blake, Gert H. ten Brink, L. Jan Anton Koster, and Maria Antonietta Loi\\* \n\nThe low power conversion efficiency (PCE) of tin-based hybrid perovskite solar cells (HPSCs) is mainly attributed to the high background carrier density due to a high density of intrinsic defects such as Sn vacancies and oxidized species $(\\mathsf{S}\\mathsf{n}^{4+})$ that characterize Sn-based HPSCs. Herein, this study reports on the successful reduction of the background carrier density by more than one order of magnitude by depositing near-single-crystalline formamidinium tin iodide $(F A S n l_{3})$ films with the orthorhombic $\\pmb{a}$ -axis in the out-of-plane direction. Using these highly crystalline films, obtained by mixing a very small amount $(0.08~\\mathsf{M})$ of layered (2D) Sn perovskite with $0.92\\ m$ (3D) $\\mathsf{F A S n l}_{3}$ , for the first time a PCE as high as $9.0\\%$ in a planar p–i–n device structure is achieved. These devices display negligible hysteresis and light soaking, as they benefit from very low trap-assisted recombination, low shunt losses, and more efficient charge collection. This represents a $50\\%$ improvement in PCE compared to the best reference cell based on a pure $\\mathsf{F A S n l}_{3}$ film using $\\mathsf{S n F}_{2}$ as a reducing agent. Moreover, the 2D/3D-based HPSCs show considerable improved stability due to the enhanced robustness of the perovskite film compared to the reference cell. \n\n![](images/32ab3359169bcc77d6b873f8882140035b084c99561bccaabf4de10c593f1fc2.jpg) \n\nThe ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/aenm.201702019. \n\n$\\circledcirc$ 2017 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. \n\nDOI: 10.1002/aenm.201702019 \n\nThree dimensional (3D) perovskite materials with an $\\mathrm{AB}\\mathrm{X}_{3}$ structure (where A is either an organic or an inorganic cation, B is a divalent metal cation, and X is a halide anion) have demonstrated superb properties as light absorbers in photovoltaic devices. Thanks to the intensive research efforts of a large scientific community over the past 7 years, lead (Pb)-based hybrid perovskite solar cells (HPSCs) have achieved an impressive (up to $22\\%$ power conversion efficiency (PCE).[1] At the same time, researchers have also demonstrated progress in improving the thermal and photostability of this kind of solar cell by using more stable precursors and robust hole/electron transport layers.[2–5] Despite these outstanding achievements, the toxicity of lead causes concerns about the possible large-scale utilization of this new type of solar cell. \n\nTherefore, attention has recently turned towards lead-free HPSCs with the idea of replacing lead by less toxic metals. Among the various alternatives to lead, tin (Sn) has great potential as the Sn-based hybrid perovskites display excellent optical and electrical properties such as high absorption coefficients, small exciton binding energies, and high charge carrier mobilities.[6–11] However, the record PCE of tinbased HPSCs has remained at about $6\\%$ for more than 3 years since the very first reports by the groups of Snaith and Kanatzidis, who reported methylammonium tin halide $(\\mathrm{MASnI}_{3}$ and $\\mathrm{MASnI}_{3-x}\\mathrm{Br}_{x})$ solar cells with an $\\mathtt{n-i-p}$ structure and $\\mathrm{TiO}_{2}$ mesoporous scaffold in 2014, which showed PCE of $6.4\\%$ and $5.73\\%$ , respectively.[12,13] In an attempt to improve the PCE, research efforts have been directed towards optimization of the tin-perovskite film morphology, tuning the film composition, use of a reducing agent, and modification of the device structure.[14–21] \n\nThe main challenges for further improving the PCE lie in preventing the easy formation of Sn vacancies due to their small formation energy and the fast oxidation of divalent $\\mathrm{Sn}^{2+}$ into more stable $\\mathrm{Sn^{4+}}$ . This causes high levels of self-p-doping in Sn-based perovskite films, with consequent severe recombination losses for charge carriers. Therefore, attempts to reduce the background carrier (hole) density have been made by incorporating $\\mathrm{SnF}_{2}$ into such films to fill tin vacancies and suppress oxidation of $\\mathrm{Sn}^{2+}$ [14–17] For example, Mathews and co-workers reported the use of cesium tin iodide $\\left(\\mathrm{Cs}\\mathrm{SnI}_{3}\\right)$ and formamidinium tin iodide $(\\mathrm{FASnI}_{3})$ as light absorbers in an n–i–p device structure (with the n-type layer being mesoscopic) and demonstrated a PCE of ${\\approx}2\\%$ using tin fluoride $(\\mathrm{SnF}_{2})$ as a reducing agent.[14] Later, Seok and co-workers demonstrated a PCE of $4.8\\%$ by improving the $\\mathrm{FASnI}_{3}$ film morphology using pyrazine to form a complex with $\\mathrm{SnF}_{2}$ and slowing down the thin film crystallization.[15] More recently, Yan and co-workers reported a PCE of $6.22\\%$ in an inverted p–i–n planar device structure.[16] \n\nHowever, an excess of $\\mathrm{SnF}_{2}$ deteriorates the perovskite film morphology and the device performance,[14–16] implying that the $\\mathrm{SnF}_{2}$ concentration must be kept low with the consequence that the background carrier density in these HPSCs is still too high to achieve equivalent performance to the lead-based perovskites. Therefore, it is necessary to develop new and more effective strategies to further reduce the background carrier density and improve the device performance of tin-based HPSCs. \n\nSuch alternative strategies have been explored by only a handful of research groups. Kanatzidis and co-workers showed that processing the perovskite film containing $\\mathrm{SnF}_{2}$ under a reducing vapor atmosphere helps to reduce the hole carrier density in $\\boldsymbol{\\mathrm{MASnI}_{3}}$ films.[19] Unlike $\\mathrm{SnF}_{2}$ , the reducing vapor protects the tin-perovskite film from oxidation during the film-forming process but is absent in the HPSCs themselves. The best device created using this method, however, displayed a PCE of around $3.8\\%$ , i.e., inferior to previously reported devices processed without a reducing atmosphere. Hatton and co-workers reported that adding an excess of tin chloride $(\\mathrm{{SnCl}}_{2})$ and tin iodide $(\\mathrm{SnI}_{2})$ to $\\mathrm{CsSnI}_{3}$ films improves both the stability and PCE of the corresponding solar cells, which displayed a PCE of $\\approx3\\%$ .[20,21] Just before the submission of this manuscript, Zhao et al. reported tinbased HPSCs with a PCE of $8.12\\%$ by using mixed cation tin perovskite $(\\mathrm{FA}_{0.75}\\mathrm{MA}_{0.25}\\mathrm{SnI}_{3})$ ) as light harvesting layer.[22] Despite the relatively high efficiency, the resistance to moisture of $\\mathrm{FA}_{0.75}\\mathrm{MA}_{0.25}\\mathrm{SnI}_{3}$ -based HPSCs should be quite limited because of the hydrophilic $\\mathrm{FA^{+}}$ and $\\mathrm{MA^{+}}$ cations. \n\nA lesson learned from lead-based perovskite is that lowdimensional perovskite formed by replacing the small hydrophilic cations with much bulkier organic ones can help to improve the stability of the HPSCs upon exposure to moisture.[23–25] Unlike the comprehensive studies on lead-based perovskite, only two papers about tin-based HPSCs using lowdimensional perovskite such as $\\left(\\mathrm{CH}_{3}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3}\\right)_{2}(\\mathrm{CH}_{3}\\mathrm{NH}_{3})_{n-1}$ $\\mathrm{Sn}_{n}\\mathrm{I}_{3n+1}$ and $\\mathrm{PEA}_{2}\\mathrm{FA}_{n-1}\\mathrm{Sn}_{n}\\mathrm{I}_{3n+1}$ (n is the number of the inorganic $\\mathrm{SnI}_{6}$ octahedra layers encapsulated by the $\\mathrm{PEA}^{+}$ $(\\mathrm{PEA}=\\mathrm{C}_{6}\\mathrm{H}_{5}(\\mathrm{CH}_{2})_{2}\\mathrm{NH}_{3}{}^{+})$ double layer, the increase (decrease) in $n$ value means increase (decrease) in the dimension; $n=\\infty3\\mathrm{D}$ perovskite, $n=1\\ 2\\mathrm{D}$ perovskite) were published during the preparation of this manuscript.[26,27] In both papers, the PCE of the tin-based HPSCs are still lower than $6\\%$ . Cao et al. reported a PCE of $2.5\\%$ by using $\\mathrm{(CH_{3}(C H_{2})_{3}N H_{3})_{2}(C H_{3}N H_{3})_{3}S n_{4}I_{13}}$ $(n=4)$ as light harvesting layer.[26] Ning and co-workers reported a PCE of $5.9\\%$ using $\\mathrm{PEA_{2}F A_{8}S n_{9}I_{28}}$ $(n=9)$ as light harvesting layer.[27] For the low-dimensional tin-based perovskite family $(\\mathrm{CH}_{3}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3})_{2}(\\mathrm{CH}_{3}\\mathrm{NH}_{3})_{n-1}\\mathrm{Sn}_{n}\\mathrm{I}_{3n+1}$ and $\\mathrm{PEA}_{2}\\mathrm{FA}_{n-1}\\mathrm{Sn}_{n}\\mathrm{I}_{3n+1}$ , how the device using tin perovskite with lower content of bulkier organic cations $(\\infty>n>5$ for $\\mathrm{CH}_{3}(\\mathrm{CH}_{2})_{3}\\mathrm{NH}_{3})_{2}(\\mathrm{CH}_{3}\\mathrm{N}$ $\\mathrm{H}_{3})_{n-1}\\mathrm{Sn}_{\\mathrm{n}}\\mathrm{I}_{3\\mathrm{n}+1},\\infty>n>9$ for $\\mathrm{PEA}_{2}\\mathrm{FA}_{n-1}\\mathrm{Sn}_{\\mathrm{n}}\\mathrm{I}_{3n+1})$ as light harvesting layer behaves, remains an open question. \n\nHerein, for the first time, we report a PCE as high as $9\\%$ for tin-based HPSCs in a $\\mathtt{p-i-n}$ planar device structure. These devices show negligible hysteresis and light soaking, with the background carrier density lowered by more than one order of magnitude compared to a reference cell incorporating an $\\mathrm{SnF}_{2}$ reducing agent. We demonstrate that addition of a very small amount $(0.08\\mathrm{~M})$ of layered (2D) tin perovskite in $0.92\\ensuremath{\\mathrm{~M~}}3\\ensuremath{\\mathrm{D}}$ tin perovskite induces superior crystallinity and a well-defined orientation of the 3D $\\mathrm{FASnI}_{3}$ grains (hereafter referred to as 2D/3D mixture perovskite). The extended ordering and packing of crystal planes improves the robustness and integrity of the perovskite structure and helps to suppress the formation of tin vacancies and therefore the background carrier density. The high degree of crystallinity and the preferential crystal orientation are fundamental for the improved solar cell performance. The champion reference solar cell gives a PCE of about $6\\%$ , i.e., $50\\%$ inferior to the record device fabricated with 2D/3D perovskite, due to the high leakage current and severe trap-assisted recombination caused by the high p-doping $(10^{17}~\\mathrm{cm}^{-3})$ level. Moreover, the 2D/3D-based HPSCs have much higher stability upon exposure to light and ambient conditions due to the enhanced robustness of the perovskite film. \n\nWe prepared the tin-based perovskite films via a single-step spin-coating method with antisolvent dripping.[10] The films were subsequently annealed at $65~^{\\circ}\\mathrm{C}$ for $20~\\mathrm{min}$ . We obtained pristine 3D $\\mathrm{FASnI}_{3}$ perovskite films, acting in this work as the reference, from a precursor solution comprising formamidinium iodide (FAI), $\\mathrm{SnI}_{2}$ , and $\\mathrm{SnF}_{2}$ with a 1:1:0.1 molar ratio, in a mixture of dimethyl sulfoxide (DMSO) and $N,N.$ dimethylformamide (DMF). \n\nOur 2D/3D samples were made from a precursor solution containing mixtures of stoichiometric 2-phenylethylammonium iodide (PEAI) xm, FAI $(1-x)$ m and $1\\mathrm{~M~}\\mathrm{SnI}_{2}$ and $0.1\\mathrm{~M~}\\mathrm{SnF}_{2}$ where $x$ is 0, 0.04, 0.08, 0.12, and 0.16, corresponding to stoichiometric $\\mathrm{FASnI}_{3}$ , $\\mathrm{PEA}_{2}\\mathrm{FA}_{49}\\mathrm{Sn}_{50}\\mathrm{I}_{151}$ $(n=50)$ , $\\mathrm{PEA_{2}F A_{24}S n_{25}I_{76}}$ $\\left(n\\ =\\ 25\\right)$ , $\\mathrm{PEA_{2}F A_{15}S n_{16}I_{49}}$ $(n~=~16)$ , and $\\mathrm{PEA_{2}F A_{11}S n_{12}I_{37}}$ $(n=12)$ . In our case, the $\\mathrm{PEA^{+}}$ content in the perovskite film is much lower than what reported in previous works. In the following section, we show that the 2D/3D samples are most probably the mixtures of 2D materials and 3D materials rather than a stoichiometric pure phase as shown here. \n\nFigure S1a (Supporting Information) shows X-ray diffraction (XRD) patterns of the different films. The reference $\\mathrm{FASnI}_{3}$ film shows five dominant diffraction peaks at angles of $14.0^{\\circ}$ , $24.4^{\\circ}$ , $28.22^{\\circ}$ , $31.65^{\\circ}$ , $40.37^{\\circ}$ assigned to the crystallographic planes (100), (120)/(102), (200), (122), (222), respectively. This diffraction pattern is in agreement with previous reports[13] and is consistent with the orthorhombic (Amm2) crystal structure of $\\mathrm{FASnI}_{3}$ , the presence of all the above peaks indicating that the reference film is composed of grains with random orientations. The 2D/3D perovskite films all exhibit the (100) and (200) peaks at angles of $14.0^{\\circ}$ and $28.22^{\\circ}$ , as well as a weaker peak at $42.9^{\\circ}$ assigned to the (300) plane, indicating the same orthorhombic 3D crystal structure as the reference film (see Figure 1a). However, the suppression of the 120/102, 122 and 222 peaks together with the enhanced $h00$ peak intensities suggests preferential crystallization with $(h00)$ planes parallel to the film surface. This observation is further confirmed by the grazing incidence X-ray scattering data discussed below. The 100 peak of the $\\mathrm{FASnI}_{3}$ film with $2\\mathrm{D}/3\\mathrm{D}$ perovskite $(0.08\\mathrm{~M~})$ is about 40 times more intense than for the reference film (Figure S1b, Supporting Information), with a decreased full-width at halfmaximum (FWHM). These data indicate significantly improved crystallinity and more perfect packing of the (100) and (200) planes upon incorporation of PEAI into the $\\mathrm{FASnI}_{3}$ film. \n\n![](images/c63f8fe5a19b45dc3ae9a7e9c39f79f1646e6c52a0bd578fab5bdaf369ca4672.jpg) \nFigure 1.  Crystal structure and morphology. Schematic crystal structure of a) 3D reference $\\mathsf{F A S n l}_{3}$ , b) 2D/3D mixture $(2\\mathsf{D}0.08~\\mathsf{M})$ , with the unit cells of each component outlined in red, and c) 2D ${\\mathsf{P E A}}_{2}{\\mathsf{S n l}}_{4}$ . Respective GIWAXS images of samples annealed at $65~^{\\circ}C$ recorded at an incident angle of $0.25^{\\circ}$ : d) 3D reference, e) 2D/3D mixture, and f) 2D film. $\\begin{array}{r}{\\mathsf{g}_{-\\mathrm{j}}^{})}\\end{array}$ SEM images of $\\mathsf{F A S n l}_{3}$ films with different 2D Sn perovskite concentrations (0, 0.08; 0.012, 0.16 m). \n\nIn addition, several very weak peaks (magnified 100 times in Figure S1a in the Supporting Information to make them observable) appear at lower 2θ values $(<12^{\\circ})$ . These new peaks do not belong to either $\\mathrm{SnI}_{2}$ or $\\mathrm{SnF}_{2}$ (see Figure S1c in the Supporting Information). Instead, they may indicate formation of a layered tin perovskite (for the probable structure, see Figure 1b). The low diffraction intensity indicates a limited proportion of 2D tin perovskite in the 3D matrix of $\\mathrm{FASnI}_{3}$ . Figure S1d (Supporting Information) shows the XRD pattern of the pure 2D material $(\\mathrm{PEA}_{2}\\mathrm{SnI}_{4})$ , which shows strongly preferential crystallization with $(h00)$ planes parallel to the film surface. The $a$ -axis periodicity of ${\\sim}32\\mathrm{~\\AA~}$ is in agreement with the monoclinic structure (space group $C2/m\\}$ reported by Papavassiliou et al.[28] However, the first peak in the XRD pattern of the $2\\mathrm{D}/3\\mathrm{D}$ sample $(0.08~\\mathrm{M})$ at $2\\theta=3.8^{\\circ}$ indicates an $a$ -axis of ${\\sim}23\\mathrm{\\AA}$ . In the reported $\\mathrm{PEA}_{2}\\mathrm{SnI}_{4}$ structure, a double layer of PEA molecules occupies approximately $10.0\\mathrm{~\\AA~}$ in the $a$ -direction, whereas a single layer of $\\mathrm{SnI}_{6}$ octahedra in both $\\mathrm{PEA}_{2}\\mathrm{SnI}_{4}$ and $\\mathrm{FASnI}_{3}$ occupies \n\n$6.3\\substack{-6.4\\mathrm{~\\AA~}}$ . Therefore, we speculate that the part of the 2D/3D film $(0.08\\mathrm{~M})$ that gives rise to the weak diffraction peaks in Figure S1a in the Supporting Information comprises double layers of $\\mathrm{SnI}_{6}$ octahedra separated by double layers of PEA mole­cules, as shown schematically in Figure 1b. \n\nWe further assessed the effects of adding a small amount of 2D perovskite and of thermal annealing on the structure and orientation of the $\\mathrm{FASnI}_{3}$ crystals with respect to the substrate using grazing incidence wide-angle X-ray scattering (GIWAXS). Figure 1d–f shows the GIWAXS patterns of the pure 3D, 2D/3D mixture and pure 2D perovskite films (annealed at $65~^{\\circ}\\mathrm{C})$ ) recorded using an incident angle of $0.25^{\\circ}$ . The reference 3D film exhibits Debye–Scherrer-like rings whose positions correspond to those of the dominant peaks in the XRD pattern. The rings actually consist of many isotropically distributed spots, indicating significant randomness in the orientations of the grains within the polycrystalline $\\mathrm{FASnI}_{3}$ film. In contrast, the $\\mathrm{2D}/3\\mathrm{D}$ film $(0.08\\mathrm{~M})$ exhibits Bragg spots located around the same rings, indicating a strongly textured film morphology with preferential orientation of the grains with respect to the substrate. All the Bragg spots can be indexed using an orthorhombic structure in agreement with the XRD data, confirming that the crystal structure of the $\\mathrm{FASnI}_{3}$ perovskite in the 2D/3D mixed film is the same as that of the reference 3D material. The location of the 100 and 200 Bragg spots along the $q_{z}$ direction indicates that the grains orient preferentially with (h00) planes parallel to the substrate, i.e., the $a$ -axis is oriented perpendicular to the substrate. The structure and orientation of the $\\mathrm{FASnI}_{3}$ grains is homogeneous throughout the entire film thickness, as GIWAXS patterns recorded using an incident angle of $2^{\\circ}$ and shown in Figure S2a–c in the Supporting Information (full X-ray penetration of the film) are similar to those recorded at an incident angle of $0.25^{\\circ}$ (low X-ray penetration depth). Note that two weak diffraction peaks originating from the 2D material become visible only when full penetration of the film by the X-rays is achieved (Figure S2b, Supporting Information), suggesting that the 2D material is mostly located in the proximity of the substrate. The positions of these peaks are in agreement with the two lowest angle peaks in the XRD data. In order to understand whether the thermal treatment at $65~^{\\circ}\\mathrm{C}$ affects the structure, GIWAXS images were also recorded for the same set of samples without any thermal annealing (Figure S3, Supporting Information); no significant changes were observed. This implies that the alignment of the $\\mathrm{SnI}_{6}$ octahedra parallel to the substrate is thermodynamically stable. This is an important result as low-temperature processing is fundamental to reduce trap states in the $\\mathrm{FASnI}_{3}$ films, especially if one considers the low formation energy of tin vacancies and $\\mathrm{Sn^{4+}}$ . \n\nThe Pb-based 2D perovskite $\\mathrm{BA}_{2}\\mathrm{MA}_{3}\\mathrm{Pb}_{4}\\mathrm{I}_{13}$ , which contains another large organic cation $n$ -butylammonium, forms randomly oriented grains at room temperature and hot casting of the film is necessary to obtain high crystallinity and grains oriented with the layer stacking direction parallel to the film surface.[25] The host casting method is unfavorable for tinbased HPSCs because the high temperature may induce a high density of tin vacancies in the perovskite film. Therefore, our finding is very important as it demonstrates that a very small amount of 2D perovskite inserted into the 3D material is able to induce a highly uniform orientation of the 3D $\\mathrm{FASnI}_{3}$ grains at room temperature. \n\nIn summary, the 2D tin perovskite functions as a seed layer to induce large-scale crystallization and orientation of the 3D $\\mathrm{FASnI}_{3}$ grains (see Figure 1b). The strong tendency of the 2D perovskite to form highly ordered, aligned structures is confirmed by GIWAXS patterns of the pure $\\mathrm{PEA}_{2}\\mathrm{SnI}_{4}$ films (Figure 1f; Figure S3c,f in the Supporting Information). The 2D structure could be indexed according to the reported monoclinic unit cell with an $a$ -axis of $32\\mathrm{~\\AA~}$ , highly oriented perpendicular to the substrate.[28] We speculate that the organic $\\mathrm{PEA}^{+}$ cations are oriented perpendicularly to the substrate, and the van der Waals interactions of the benzene ring between the interdigitate $\\mathrm{PEA}^{+}$ cations may facilitate self-assembly of the inorganic $\\mathrm{SnI}_{6}$ layers parallel to the substrate, inducing strong orientation and crystallization of the 2D $\\mathrm{PEA}_{2}\\mathrm{SnI}_{4}$ . \n\nFigure 1g–j shows scanning electron microscopy (SEM) images of the different perovskite films. The reference film has compact morphology with very few pinholes. The $\\mathrm{FASnI}_{3}$ grains range from 0.5 to $2\\ \\upmu\\mathrm{m}$ and pack together irregularly with rather sharp grain boundaries. Previous work has shown that grain boundaries in lead perovskite films have high concentrations of structural defects such as dangling bonds or vacancies.[29–31] Therefore, grain boundaries function as trap centers for nonradiative recombination. Moreover, they give rise to energy disorder which is an obstacle for charge transport.[32–34] This may also apply to the case of $\\mathrm{FASnI}_{3}$ films, in which the tin vacancies are the dominant defects due to their low formation energy.[7,8] The addition of very small amounts of 2D perovskite seems to fuse the $\\mathrm{FASnI}_{3}$ grains together and blurs the grain boundaries. This observation is consistent with the improved crystallinity and larger grains indicated by the XRD patterns of the 2D/3D films. However, when the concentration of 2D perovskite increases up to $0.16\\mathrm{~M~}$ , many pinholes appear in the $\\mathrm{FASnI}_{3}$ film, making the morphology far from ideal for the fabrication of solar cells. \n\nTo test the effects of the morphological and crystallographic changes in our $\\mathrm{FASnI}_{3}$ films on solar cell performance, we implemented them in devices using structures of the type $\\mathrm{ITO}/$ poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT: PSS) $\\mathrm{\\langleFASnI_{3}/C_{60}~+~}2,9$ -dimethyl-4,7-diphenyl-1,10-phenanthroline (BCP)/Al as depicted in Figure 2.[16] We chose $\\mathrm{C}_{60}$ as it produces not only a more uniform and dense electron transport layer but also avoids the need for solvents. \n\nFor the fabrication of the reference cell based on 3D $\\mathrm{FASnI}_{3}$ we used $\\mathrm{SnF}_{2}$ as a reducing agent to reduce the background carrier density. The reference device has an optimum PCE when the concentration of $\\mathrm{SnF}_{2}$ is $0.1\\mathrm{~M~}$ and beyond this concentration the device performance deteriorates (Figure S4, Supporting Information). This is because the excess $\\mathrm{SnF}_{2}$ forms aggregates in the $\\mathrm{FASnI}_{3}$ film as indicated by previous studies. We further investigated the effect of thermal annealing on the device performance. Optimum performance was obtained when the active layer was annealed at $65~^{\\circ}\\mathrm{C}$ (Figure S5, Supporting Information). The performance dropped significantly at higher annealing temperatures, most probably due to the formation of tin vacancies. This again highlights the importance of depositing high-quality $\\mathrm{FASnI}_{3}$ films at low temperature for efficient tin-based HPSCs. \n\n![](images/3ef88cc60777ce25f4cd7da2dc42b11922a1e4fcdc4306c7d62e10d0c5fef848.jpg) \nFigure 2.  Device structure and characterization. a) $J{-}V$ curves under one sun AM $\\mathsf{I}.5\\mathsf{C}$ condition for the champion devices containing pure 3D and 2D $(0.008~\\mathsf{M})/3\\mathsf{D}$ perovskite (the inset shows the device structure), b) forward and reverse sweeps of the $J-V$ characteristics of the champion 2D/3D perovskite cell measured at different rates, c) histogram of the reference cell reproducibility, and d) of the 2D/3D perovskite devices. \n\nFigure 2a shows the current density $(J)$ –voltage (V) characteristics under one sun illumination of the best performing reference cell, displaying a $V_{\\mathrm{OC}}$ of 0.458, a $J_{\\mathrm{sc}}$ of $22.5\\mathrm{\\mA\\cm^{-2}}$ , fill factor (FF) of 0.58 and PCE of $6.0\\%$ . We list all the device parameters in Table 1. Figure 2c shows the distribution of PCE for the reference cells; the broad variation indicates poor reproducibility over the 20 fabricated devices. \n\nWe used the same experimental conditions to fabricate devices with 2D/3D films where PEAI was added to the active layer with different concentrations (Figure S6 in the Supporting Information shows the corresponding $J{-}V$ curves). We obtained the best performing devices with a $0.08\\mathrm{~M~}$ concentration of 2D perovskite in the $\\mathrm{FASnI}_{3}$ film, and we observed a significant drop in performance for higher concentrations of 2D perovskite. This is because the pin holes in the perovskite active layer (see Figure 1j) give rise to shunt paths and direct contact between the cathode and anode, with consequent high leakage current (see Figure S7 in the Supporting Information). \n\nTable 1.  Figures of merit for devices with 3D tin perovskite and 2D/3D tin perovskite layers under one sun condition. \n\n\n
DeviceVoc MJsc [mA cm-2]FFPCE [%]
3D0.45822.50.586.0
2D/3D0.52524.10.719.0
\n\nFigure 2a shows the $J{-}V$ characteristics of the best performing device with the 2D/3D film and a comparison with the best reference cell. The 2D/3D device shows a $V_{\\mathrm{OC}}$ of $0.525~\\mathrm{V},$ a $J_{\\mathrm{SC}}$ of $24.1\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ and an FF of 0.71 resulting in a PCE of $9.0\\%$ . It is important to note that this is the highest FF and PCE reported so far for all-tin-based perovskite solar cells. Moreover, the $J{-}V$ curves of these solar cells are identical for forward and reverse scans and different sweeping rates (negligible $J V$ hysteresis), as shown in Figure 2b. We also point out that this device shows no obvious light-soaking effect, which is confirmed by the fast saturation of the steady state photoluminescence (PL) upon photoexcitation with a $400\\ \\mathrm{nm}$ laser (Figure S8, Supporting Information). The absence of hysteresis and light-soaking effects in these devices is very important, as it represents a sign of their reliability. These phenomena often affect Pb-based HPSCs and render the device performance unreliable.[5,35,36] To further confirm our observations, we independently tested the steady state PCE of the device using 2D/3D mixture (see Figure S9 in the Supporting Information). The 2D/3D-based device from a different batch with a PCE of $8.8\\%$ (from $J{-}V$ measurement) has a very similar steady state PCE of $8.5\\%$ , confirming the reliable device performance. The PCE statistics (Figure 2d) of more than 20 devices demonstrates the small variation and good reproducibility of our 2D/3D devices compared to the reference devices. \n\nThe device containing the 2D/3D film shows substantially improved performance parameters with respect to the 3D reference: $15\\%$ higher $V_{\\mathrm{OC}},$ $7\\%$ higher $J_{\\mathrm{SC:}}$ $20\\%$ higher FF and $50\\%$ higher PCE. The integrated $J_{\\mathrm{SC}}$ values $(23.8~\\mathrm{mA}~\\mathrm{cm}^{-2}$ for 2D/3D-based device and $22.2\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ for 3D-based device) from the external quantum efficiency of incident photons to electrons (EQE) measurement confirm the value of the photocurrent density measured using the $J{-}V$ characteristics (Figure S10, Supporting Information). \n\n![](images/50288df42d2a40369dfb64e7a162f0f0cd42a813eeb953e59d019383fb3d6947.jpg) \nFigure 3.  Spectroscopy and light intensity dependent characterization. a) Steady state PL and b) time-resolved PL for perovskite films with different concentrations of 2D perovskite (black line for $0\\mathrm{~w~}$ , blue line for $0.04~\\mathrm{M}$ , red line for $0.08~\\mathsf{M}$ and green line for $0.12\\mathrm{~m}^{\\cdot}$ ). c) Light intensity dependence of $V_{\\mathsf{O C}}$ for devices with 2D $(0.08~\\mathsf{M})/3\\mathsf{D}$ perovskite (red) and 3D perovskite (black). \n\nThe 2D/3D film (0.08 m) has the same absorption onset as the 3D film (see Figure S11a in the Supporting Information), but it has higher optical constants (extinction coefficient and refractive index) than the 3D film due to its superior crystallinity (Figure S11b, Supporting Information). Optical simulations performed using transfer matrix formalism provide photocurrent generation profiles for both devices, showing similar theoretical photocurrent densities and excluding optical absorption as the dominant factor for the improvement in the experimental $J_{\\mathrm{SC}}$ of the device with the 2D/3D film (Figure S11c, Supporting Information). \n\nIn order to gain deeper insight into the $50\\%$ improvement in device performance with the 2D/3D film, we performed steadystate and time-resolved PL measurements on the different $\\mathrm{FASnI}_{3}$ films. In Figure 3a, we observe that all the $\\mathrm{FASnI}_{3}$ films have emission peaks around $895\\ \\mathrm{nm}$ . The reference sample displays the lowest emission intensity, implying higher nonradiative trap-assisted recombination losses of charge carriers. Due to the capture of free carriers by the defect sites, the photogenerated carriers decay rather fast and the emission lifetime is as short as 4.1 ns. A consequence of this short lifetime is that the charge carriers can only diffuse a short distance and have a high probability of recombination with the opposite charge carriers before they reach the respective electrodes. Therefore, the inefficient charge collection efficiency leads to lower $J_{\\mathrm{SC}}$ and FF in the reference device. The reference $\\mathrm{FASnI}_{3}$ films are affected by large fluctuations in the number of defects due to the randomly packed grains or sensitivity to the atmosphere in the $\\mathrm{N}_{2}$ -filled glove box. As a result, the reference cell shows a broad distribution of PCEs. \n\nThe 2D/3D film has significantly improved emission intensity and lifetime (up to $9.47~\\mathrm{ns}^{\\prime}$ , indicating much lower trap density than the pure 3D film. These results confirm that the extended ordering of the crystal planes and the reduced number of grain boundaries help to reduce the trap density in the perovskite film. As mentioned earlier, the highly ordered and oriented crystal planes parallel to the substrate may form fast transport pathways for the charge carriers in the device. In this case, the long-lived charge carriers can be transported efficiently to the respective electrodes before recombination occurs, which leads to the improved FF and $J_{\\mathrm{SC}}$ in the device. Because of the negligible hysteresis and light soaking, we further performed the $J{-}V$ measurements under various light intensities with an interval of $5\\mathrm{-}10~\\mathrm{s}$ between the $J{-}V$ sweeps. Figure 3c shows that the device containing the 2D/3D film exhibits a lower slope of $V_{\\mathrm{OC}}$ versus semilogarithmic light intensity, further confirming that trap-assisted recombination losses are suppressed compared to the reference device. Previous studies indicate that the severe trap-assisted recombination loss of charge carriers is one of the main reasons for the loss in $V_{\\mathrm{OC}}$ of the HPSCs.[5,28,29] Therefore, the device based on the 2D/3D tin perovskite exhibits higher $V_{\\mathrm{OC}}$ than the reference device. \n\n![](images/04830d6b1f6ac39a42c2576676b36a555c448c81a789081f224ea3ff67aad5c8.jpg) \nFigure 4.  Electrical characteristics of perovskite films. a) Thermal voltage as a function of temperature gradient for the pristine $\\mathsf{F A S n l}_{3}$ film. b) Twopoint probe electrical conductivity for $\\mathsf{F A S n l}_{3}$ films with different amounts of 2D tin perovskite (black line for 0, blue line for $0.04~\\mathsf{M}$ , red line for $0.08\\mathrm{~M~}$ and green line for $0.12\\mathrm{~M~}$ ). c) $C^{-2}$ as a function of bias voltage. d) $J{-}V$ curves under dark condition for devices with 2D $(0.08~\\mathsf{M})/3\\mathsf{D}$ perovskite (red line) and 3D perovskite (black line) layers. \n\nFigure 4a shows the thermal voltage versus temperature gradient for the 3D and 2D/3D perovskite films, which demonstrate a positive Seebeck coefficient (p-type) of 504 and $796~\\upmu\\mathrm{V}~\\mathrm{K}^{-1}$ confirming that holes are the dominant carriers. The larger Seebeck coefficient of 2D/3D sample is a signature of lower charge carrier density compared to the pure 3D sample. To further probe how the 2D perovskite influences the p-doping level in $\\mathrm{FASnI}_{3}$ films, we carried out electrical conductivity measurements. Figure 4b shows that the reference film has the highest conductivity $(1.72\\times10^{-2}\\mathrm{~S~cm^{-1}})$ of all the samples. This is a further indication of self-doping by the large density of background holes generated by tin vacancies and oxidized species $(\\mathrm{Sn^{4+}})$ and highlights the limitation of $\\mathrm{SnF}_{2}$ as a reducing agent in suppressing these defects. As discussed earlier, the high p-doping level leads to high leakage current and device shorts. The 2D/3D perovskite films have much lower electrical conductivity, indicating de-doping of the $\\mathrm{FASnI}_{3}$ film and reduction of the background charge carrier density. We believe that this is related to the increased crystallinity and smaller number of grain boundaries in the 2D/3D perovskite film, which lowers the possibility of forming tin vacancies and $\\mathrm{Sn^{4+}}$ . The $2\\mathrm{D}/3\\mathrm{D}$ perovskite film $(0.08\\mathrm{~M~})$ exhibits a hole conductivity of $2.1\\times10^{-4}\\mathrm{~S~cm^{-1}}$ , which is more than two orders of magnitude lower than the reference sample. \n\nFigure 4c shows the variation of the background charge carrier density in the devices containing 3D and 2D/3D perovskite layers obtained from capacitance $(C)$ –voltage (V) measurements under dark conditions. Using Mott–Schottky analysis \n\n$$\nC^{-2}={\\frac{2}{q\\varepsilon_{\\mathrm{r}}\\varepsilon_{0}N}}{\\binom{V-V_{\\mathrm{fb}}-{\\frac{k T}{q}}}{N}}\n$$ \n\nthe background charge carrier density can be obtained from the slope of $C^{-2}$ versus the applied voltage $V$ in the depletion region. The hole carrier density $(2.76\\times10^{16}~\\mathrm{{cm}^{-3})}$ in solar cells with layered tin perovskite is reduced by more than 20 times compared to the reference cell $(5.83\\times10^{17}\\mathrm{cm}^{-3})$ ), in agreement with the conductivity measurements. \n\nFigure 4d shows the dark $J{-}V$ curves of the devices containing 3D and $\\mathrm{2D}/3\\mathrm{D}$ tin perovskite layers, from which we extracted the shunt resistances $(R_{\\mathrm{P}})$ . The reference solar cell has a small $R_{\\mathrm{P}}$ $(9.7\\ \\mathrm{k}\\Omega\\ \\mathrm{cm}^{2})$ and suffers significantly from a high leakage current due to the high p-doping level. In contrast, the device with the 2D/3D perovskite layer has a much higher shunt resistance $(175\\mathrm{~k}\\Omega\\mathrm{~cm}^{2},$ ) and very good diode behavior, which originates from the low background carrier density. In addition, the improved crystallinity and the highly oriented packing of the crystal planes in the out-of-plane direction favor charge transport and collection in the device. This provides more evidence that the high device performance is correlated with the crystallographic and morphological characteristics of the 2D/3D film. In addition, the highly crystalline and oriented structure of the 2D/3D film is also the reason for the good reproducibility of the device performance. \n\nBeside the efficiency, the stability is equally important for practical applications of perovskite solar cells. We firstly tested the device stability under one sun illumination in an $\\mathrm{N}_{2}.$ filled glove box (Figure S12, Supporting Information). During $^{2\\mathrm{~h~}}$ exposure to the solar light, both the reference and 2D/3D devices show relatively constant $V_{\\mathrm{OC}}$ . However, the reference device shows considerable degradation of both $J_{\\mathrm{SC}}$ and FF with time. In contrast, the $2\\mathrm{D}/3\\mathrm{D}$ perovskite device has relatively stable $J_{\\mathrm{SC}}$ and FF. As a consequence, the efficiency of the reference cell is reduced to $75\\%$ of its initial efficiency after $^{2\\mathrm{~h~}}$ whereas the $\\mathrm{2D}/3\\mathrm{D}$ device does not show any obvious degradation. The improved crystallinity of the perovskite film may enable higher resistance to light illumination and reduce the possibility for formation of the defects in the 2D/3D-based device, leading to enhanced stability. \n\nFurthermore, we tested the stability of the devices $(\\mathrm{C}_{60}\\ 70\\$ nm) without any encapsulation in ambient condition with humidity about $20\\%$ (temperature about $20^{\\circ}\\mathrm{C})$ as shown in Figure S13 in the Supporting Information. Between the intervals of the test, the devices were stored in dark condition. The device based on $2\\mathrm{D}/3\\mathrm{D}$ sample shows much higher stability compared to the device using pure 3D sample. After $76\\mathrm{{h}}$ exposure to air, the device using pure 3D perovskite completely failed, whereas the device using $\\mathrm{2D}/3\\mathrm{D}$ mixture retained $59\\%$ of the original PCE. In order to understand the discrepancy in the stability of the devices, we further performed XRD measurements for the perovskite samples stored in nitrogen filled glove box $\\mathrm{(H}_{2}O\\mathrm{~<~}0.1$ ppm, $\\mathrm{O}_{2}<0.1$ ppm) and in air (humidity about $70\\%$ , temperature $22~^{\\circ}\\mathrm{C})$ . Both the 3D and $2\\mathrm{D}/3\\mathrm{D}$ samples do not show obvious decomposition after $6\\textup{h}$ in inert atmosphere, whereas the 3D sample undergoes faster chemical degradation than the 2D/3D sample when stored in ambient conditions (Figure  S14, Supporting Information). The improved ambient stability of the 2D/3D-based device is probably due to higher resistance to oxygen and moisture as a result of the improved crystallinity and the higher hydrophobicity of the perovskite film. \n\nIn conclusion, we have demonstrated all-tin-based HPSCs with efficiencies of up to $9\\%$ . The addition of a trace amount of 2D tin perovskite initiates the homogenous growth of highly crystalline and oriented $\\mathrm{FASnI}_{3}$ grains at low temperature. The high degree of order has three positive consequences: (i) a reduced number of grain boundaries; (ii) the suppression of tin vacancies or $\\mathrm{Sn^{4+}}$ and a consequent reduction in background carrier density by more than one order of magnitude compared to pristine $\\mathrm{FASnI}_{3}$ films; (iii) a longer lifetime of the charge carriers. Therefore, devices based on a 2D/3D tin perovskite layer benefit from low trap-assisted recombination, low shunt losses of the charge carriers and efficient charge collection. Moreover, the improved crystallinity of the active layer results in more stable HPSCs. \n\nIn stark contrast, reference films using only $\\mathrm{SnF}_{2}$ as a reducing agent have a high degree of structural disorder, a high density of sharp grain boundaries and randomly oriented 3D grains. This facilitates the formation of a high density of tin vacancies and causes a high p-doping level. As a consequence, the best reference cell has a PCE of $6\\%$ , and suffers from severe trap-assisted recombination and high leakage current. \n\nFinally, by adding trace amount of 2D tin perovskite in $\\mathrm{FASnI}_{3}$ we overcome the bottleneck that has long been faced by tin-based HPSCs and demonstrate a way forward to further improve their performance. \n\n# Experimental Section \n\nMaterials: PEDOT:PSS water dispersion (Clevios VP AI 4083) was acquired from Heraeus. PEAI $(>98\\%)$ and FAI $(>98\\%)$ were purchased from TCI EUROPE N.V. $\\mathsf{S n l}_{2}$ $(99.999\\%)$ , $\\mathsf{S n F}_{2}$ $(>99\\%)$ , ${\\mathsf C}_{60}$ $(>99.9\\%)$ , BCP $(99.99\\%)$ , DMF $(99.8\\%)$ , and DMSO $(99.8\\%)$ were purchased from Sigma Aldrich. All the materials were used as received without further purification. \n\nSEM Measurement: SEM images were recorded in air on an FEI NovaNano SEM 650 with an acceleration voltage of $\\mathsf{l o k V.}$ \n\nXRD: XRD patterns (Figure S1, Supporting Information) of the perovskite films were recorded in air (RH about $20\\%$ , $\\tau$ about $20^{\\circ}\\mathsf{C})$ on a Bruker D8 Advance X-ray diffractometer with a $\\mathsf{C u}\\ \\mathsf{K}\\alpha$ source $(\\lambda=1.54\\mathrm{~\\AA})$ and a Lynxeye detector. The perovskite samples were encapsulated by Kapton thin film. The XRD patterns for the stability test (Figure S14, Supporting Information) were performed for the samples aged in glove box and in air with ambient RH about $70\\%$ and $\\tau$ about $22^{\\circ}\\mathsf{C}$ . \n\nGIWAXS Measurement: GIWAXS measurements were performed using a MINA X-ray scattering instrument built on a $\\mathsf{C u}$ rotating anode source $(\\lambda=7.5473\\hat{\\mathsf{A}})$ . 2D patterns were collected using a Vantec500 detector ( $1024\\times1024$ pixel array with pixel size $136\\times$ $136~\\upmu\\mathrm{m})$ located $93m m$ away from the sample. The perovskite films were placed in reflection geometry at certain incident angles $\\alpha_{\\mathrm{i}}$ with respect to the direct beam using a Huber goniometer. GIWAXS patterns were acquired using incident angles from $0.25^{\\circ}$ to $2^{\\circ}$ in order to probe the thin film structure at different $\\mathsf{X}$ -ray penetration depths. For an ideally flat surface, the value of the X-ray penetration depth (i.e., the depth into the material measured along the surface normal where the intensity of $\\mathsf{X}$ -rays falls to $\\rceil/e$ of its value at the surface) depends on the X-ray energy (wavelength $\\lambda$ ), the critical angle of total reflection, $\\alpha_{\\mathrm{c}},$ and the incident angle, $\\alpha_{\\mathrm{i}}$ , and can be estimated using the relation: Λ = 4π (αi2 −αc2 2 + 42β2 −(αi2 −αc2) , where $\\beta$ is the imaginary part of the complex refractive index of the compound. The estimated $\\mathsf{X}$ -ray penetration depth is 10 and $40\\ \\mathsf{n m}$ at incident angle of $0.25^{\\circ}$ , and 350 and $600\\ \\mathsf{n m}$ at incident angle of $2.0^{\\circ}$ for the pure 3D and 2D perovskites, respectively. For the calculation, the densities of 3.56 and $2.35\\ \\mathrm{g}\\ \\mathsf{c m}^{-3}$ were used for the pure 3D and 2D perovskites, respectively. The direct beam center position on the detector and the sample-to-detector distance were calibrated using the diffraction rings from standard silver behenate and ${\\mathsf{A l}}_{2}{\\mathsf{O}}_{3}$ powders. All the necessary corrections for the GIWAXS geometry were applied to the raw patterns using the GIXGUI Matlab toolbox.[37] The reshaped GIWAXS patterns, taking into account the inaccessible part in reciprocal space (wedge-shaped corrected patterns), are presented as a function of the vertical and parallel scattering vectors $q_{z}$ and $q_{r}.$ The scattering vector coordinates for the GIWAXS geometry are given by[38] \n\n$$\nq=\\left\\{\\begin{array}{c}{\\displaystyle q_{x}=\\frac{2\\pi}{\\lambda}\\big(\\cos(2\\theta_{\\mathrm{f}})\\cos(\\alpha_{\\mathrm{f}})-\\cos(\\alpha_{\\mathrm{i}})\\big)}\\\\ {\\displaystyle q_{\\gamma}=\\frac{2\\pi}{\\lambda}\\big(\\sin(2\\theta_{\\mathrm{f}})\\cos(\\alpha_{\\mathrm{f}})\\big)}\\\\ {\\displaystyle q_{z}=\\frac{2\\pi}{\\lambda}\\big(\\sin(\\alpha_{\\mathrm{i}})+\\sin(\\alpha_{\\mathrm{f}})\\big)}\\end{array}\\right.\n$$ \n\nwhere $2\\theta_{\\mathsf{f}}$ is the scattering angle in the horizontal direction and $\\alpha_{\\mathsf{f}}$ is the exit angle in the vertical direction. The parallel component of the scattering vector is thus calculated as $q_{r}=\\sqrt{q_{x}^{2}+q_{\\gamma}^{2}}$ . \n\nSteady-State and Time-Resolved PL Measurement: Steady-state and time-resolved PL measurements were conducted by exciting the samples with the second harmonic $(400~\\mathsf{n m})$ of a mode-locked Ti:Sapphire femtosecond laser (Mira 900, Coherent). The repetition rate of the laser is $76M H z$ ; a pulse picker was inserted in the optical path to decrease the repetition rate of the laser pulses. The laser power $(0.7~\\upmu)~\\mathsf{c m}^{-2})$ was adjusted using neutral density filters. The excitation beam was focused with a $150~\\mathsf{m m}$ focal length lens, and the emission was collected and coupled into a spectrometer with a 50 lines $\\mathsf{m}\\mathsf{m}^{-1}$ grating. The steady-state PL was recorded with an Image EM CCD camera from Hamamatsu (Hamamatsu, Japan). Time-resolved PL was measured with a Hamamatsu streak camera working in single sweep mode. \n\nElectrical Conductivity, Seebeck Coefficient, and C–V Measurement: For the electrical conductivity measurements, parallel line-shaped Au electrodes with a width $(\\boldsymbol{w})$ of $13m m$ and a channel length (L) of $200\\upmu\\mathrm{m}$ were deposited on cleaned glass substrates as bottom contacts. Different perovskite films were spin-coated on the patterned glass following the same recipe used for photovoltaic device fabrication. Voltage-sourced two-point conductivity measurements were conducted using a probe station in a $\\mathsf{N}_{2}$ glovebox. The electrical conductivity (σ) was calculated according to the formula $\\sigma=(J/V)\\times L/(w\\times d)$ , where $d$ is the thickness of the perovskite films. The Seebeck coefficient was measured with a home-built setup[39] in a vacuum probe station. Temperature steps were imposed across the devices to measure the thermal voltages of perovskite thin films at different temperatures, which were detected by a standard constantan wire ( $727\\ \\upmu\\mathrm{m}$ from Omega, Seebeck coefficient of $-39\\upmu\\up V\\up K^{-1})$ ). \n\nThe capacitance–voltage $(C-V)$ measurements were conducted under dark condition at a frequency of $70~\\mathsf{k H z}$ with an ac drive voltage of $20~\\mathsf{m V}$ and DC bias in the range of $-0.6$ to $0.6\\mathrm{\\:V}$ on a Solarton 1260 impedance gain-phase analyzer. \n\nUV–vis Measurement: UV–vis spectra of the perovskite films were recorded on Shimatzu UV-Vis-NIR spectrophotometer (UV 3600). The perovskite samples were encapsulated with quartz using UV light curing adhesive. \n\nDevice Fabrication: ITO glasses were cleaned using an ultra-sonication bath in soap water and rinsed sequentially with de-ionized water, acetone and isopropyl alcohol. A PEDOT:PSS layer was then spin-coated onto the ITO substrates at 4000 rpm for $60~\\mathsf{s}$ and dried at ${140^{\\circ}\\mathsf C}$ for $20~\\mathrm{min}$ . The coated substrates were then transferred to a nitrogen-filled glove-box. The reference $\\mathsf{F A S n l}_{3}$ film was spin-coated from a precursor solution comprising 1 m FAI, 1 m $\\mathsf{S n l}_{2}$ and $0.1\\mathsf{\\Omega}\\mathsf{M}\\mathsf{S}\\mathsf{n}\\mathsf{F}_{2}$ in mixed solvents of DMSO and DMF (1:4 volume ratio) at 4000 rpm for $60\\ s$ Diethyl ether was used as the antisolvent during the spin-coating process. The $\\mathsf{F A S n l}_{3}$ film was then annealed at $65~^{\\circ}C$ for $20~\\mathrm{min}$ . The 2D/3D tin perovskite films were obtained under the same conditions from solutions containing $\\boldsymbol{x}\\mathrm{~}\\mathsf{M}$ PEAI $(x=0.04$ , 0.06, 0.08, 0.12, $0.76\\mathrm{~M~}$ ), $(7-x)$ m FAI, $\\rceil\\bowtie\\mathsf{S n l}_{2}$ and $0.1\\mathsf{\\Omega}\\mathsf{M}\\mathsf{S}\\mathsf{n}\\mathsf{F}_{2}$ . Next, $30\\mathrm{~nm~C_{60}}$ , $6\\mathsf{n m}\\mathsf{B C P}$ , and $700\\ \\mathsf{n m}\\ \\mathsf{A l}$ layers were sequentially evaporated on top of the perovskite film under vacuum of $<10^{-6}$ mbar. The $J-V$ curves of the perovskite solar cells were measured at $295~\\mathsf{K}$ using a Keithley 2400 source meter under simulated AM $\\mathsf{I}.5\\mathsf{C}$ solar illumination using a Steuernagel Solar constant 1200 metal halide lamp in a nitrogen-filled glove box. The light intensity was calibrated to be $\\mathsf{l}00\\mathsf{m}\\mathsf{W}\\mathsf{c m}^{-2}$ by using a Si reference cell and correcting the spectral mismatch. A shadow mask $(0.04~\\mathsf c m^{2})$ ) was used to exclude lateral contributions beyond the device area. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThe authors would like to thank the financial support from European Commission, Marie Curie Actions—Intra-European Fellowships (IEF) “SECQDSC” No. 626852 and European Research Council, ERC Starting Grant “HySPOD” No. 306983. The authors also appreciate the technical supports of A. Kamp and T. Zaharia. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\nbackground charge carrier density, crystallinity, grain boundaries, tin perovskite solar cells, tin vacancies \n\nReceived: July 24, 2017 Revised: August 21, 2017 Published online: \n\n[1]\t Best efficiency-chart at https://www.nrel.gov/pv/assets/images/ efficiency-chart. [2]\t R. E.  Beal, D. J.  Slotcavage, T.  Leijtens, A. R.  Bowring, R. A.  Belisle, W. H. Nguyen, G. F. Burkhard, E. T. Hoke, M. D. McGehee, J. Phys. Chem. Lett. 2016, 7, 746. [3]\t M.  Saliba, T.  Matsui, J.-Y.  Seo, K.  Domanski, J.-P.  Correa-Baena, M. K.  Nazeeruddin, S. M.  Zakeeruddin, W.  Tress, A.  Abate, A. Hagfeldt, M. Grätzel, Energy Environ. Sci. 2016, 9, 1989. \n[4]\t A.  Mei, X.  Li, L.  Liu, Z.  Ku, T.  Liu, Y.  Rong, M.  Xu, M.  Hu, J.  Chen, Y. Yang, M. Grätzel, H. Han, Science 2014, 345, 295. [5]\t S.  Shao, M.  Abdu-Aguye, L.  Qiu, L.-H.  Lai, J.  Liu, S.  Adjokatse, F.  Jahani, M. E.  Kamminga, G. H.  ten  Brink, T. T. M.  Palstra, B. J.  Kooi, J. C.  Hummelen, M. A.  Loi, Energy Environ. Sci. 2016, 9, 2444. \n[6]\t I.  Chung, B.  Lee, J.  He, R. P. H.  Chang, M. G.  Kantatzidis, Nature 2012, 485, 486. \n[7]\t H. Yu, H. Lu, F. Xie, S. Zhou, N. Zhao, Adv. Funct. Mater. 2016, 26, 1411. \n[8]\t C.  Yu, Z.  Chen, J. J.  Wang, W.  Pfenninger, N.  Vockic, J. T.  Kenney, K. Shum, J. Appl. Phys. 2011, 110, 063526. [9]\t Z.  Chen, C.  Yu, K.  Shum, J. J.  Wang, W.  Pfenninger, N.  Vockic, J. Midgley, J. T. Kenney, J. Lumin. 2012, 132, 345. \n[10]\t H.-J. Du, W.-C. Wang, J.-Z. Zhu, Chin. Phys. B 2016, 25, 1. \n[11]\t M.  Konstantakou, T.  Stergiopoulos, J. Mater. Chem. A 2017, 5, 11518. \n[12]\t N. K. Noel, S. D. Stranks, A. Abate, C. Wehrenfennig, S. Guarnera, A.-A.  Haghighirad, A.  Sadhanala, G. E.  Eperon, S. K.  Pathak, M. B.  Johnston, A.  Petrozza, L. M.  Herz, H. J.  Snaith, Energy Environ. Sci. 2014, 7, 3061. \n[13]\t F.  Hao, C. C.  Stoumpos, D. H.  Cao, R. P. H.  Chang, M. G. Kanatzidis, Nat. Photonics 2014, 8, 489. \n[14]\t M. H.  Kumar, S.  Dharani, W. L.  Leong, P. P.  Boix, R. R.  Prabhakar, T.  Baikie, C.  Shi, H.  Ding, R.  Ramesh, M.  Asta, M.  Graetzel, S. G. Mhaisalkar, N. Mathews, Adv. Mater. 2014, 26, 7122. \n[15]\t S. J.  Lee, S. S.  Shin, Y. C.  Kim, D.  Kim, T. K.  Ahn, J. H.  Noh, J.  Seo, S. Il Seok, J. Am. Chem. Soc. 2016, 138, 3974. \n[16]\t W.  Liao, D.  Zhao, Y.  Yu, C. R.  Grice, C.  Wang, A. J.  Cimardi, P. Schulz, W. Meng, K. Zhu, R.-G. Xiong, Y. Yan, Adv. Mater. 2016, 28, 9333. \n[17]\t D.  Moghe, L.  Wang, C. J.  Traverse, A.  Redoute, M.  Sponseller, P. R. Brown, V. Bulovic, R. R. Lunt, Nano Energy 2016, 28, 469. \n[18]\t N.  Wang, Y.  Zhou, M.-G.  Ju, H. F.  Garces, T.  Ding, S.  Pang, X. C.  Zeng, N. P.  Padture, X. W.  Sun, Adv. Energy Mater. 2016, 6, 1601130. \n[19]\t T. B.  Song, T.  Yokoyama, C. C.  Stoumpos, J.  Logsdon, D. H.  Cao, M. R. Wasoelewski, S. Aramsk, M. G. Kanatzidis, J. Am. Chem. Soc. 2017, 139, 836. \n[20]\t K. P.  Marshall, R. I.  Walton, R. A.  Hatton, J. Mater. Chem. A 2015, 3, 1163. \n[21]\t K. P.  Marshall, M.  Walker, R. I.  Walton, R. A.  Hatton, Nat. Energy 2016, 1, 16178. \n[22]\t Z.  Zhao, F.  Gu, Y.  Li, W.  Sun, S.  Ye, H.  Rao, Z.  Liu, Z.  Bian, C. Huang, Adv. Sci. https://doi.org/10.1002/advs.201700204. \n[23]\t I. C.  Smith, E. T.  Hoke, D.  Solis-Ibarra, M. D.  McGehee, H. I. Karunadasa, Angew. Chem. 2014, 126, 11414. \n[24]\t D. H.  Cao, C. C.  Stoumpos, O. K.  Farha, J. T.  Hupp, M. G. Kanatzidis, J. Am. Chem. Soc. 2015, 137, 7843. \n[25]\t H.  Tsai, W.  Nie, J.-C.  Blancon, C. C.  Stoumpos, R.  Asadpour, B.  Harutyunyan, A. J.  Neukirch, R.  Verduzco, J. J.  Crochet, S.  Tretiak, L.  Pedesseau, J.  Even, M. A.  Alam, G.  Gupta, J.  Lou, P. M. Ajayan, M. J. Bedzyk, M. G. Kanatzidis, A. D. Mohite, Nature 2016, 536, 312. \n[26]\t D. H. Cao, C. C. Stoumpos, T. Yokoyama, J. L. Logsdon, T.-B. Song, O. K.  Farha, M. R.  Wasielewski, J. T.  Hupp, M. G.  Kanatzidis, ACS Energy Lett. 2017, 2, 982. \n[27]\t Y.  Liao, H.  Liu, W.  Zhou, D.  Yang, Y.  Shang, Z.  Shi, B.  Li, X.  Jiang, L.  Zhang, L. N.  Quan, R.  Quintero-Bermudez, B. R.  Sutherland, Q. Mi, E. H. Sargent, Z. Ning, J. Am. Chem. Soc. 2017, 139, 6693. \n[28]\t G. C.  Papavassiliou, I. B.  Koutselas, A.  Terzis, M.-H.  Whangbo, Solid State Commun. 1994, 91, 695. \n[29]\t S.  Shao, M.  Abdu-Aguye, T. S.  Sherkar, H.-H.  Fang, S.  Adjokatse, G. ten Brink, B. J. Kooi, L. J. A. Koster, M. A. Loi, Adv. Funct. Mater. 2016, 26, 8094. \n[30]\t X. Jia, L. Zhang, Q. Luo, H. Lu, X. Li, Z. Xie, Y. Yang, Y.-Q. Li, X. Liu, C.-Q. Ma, ACS Appl. Mater. Interfaces 2016, 8, 18410. \n[31]\t W. Wang, J. Yuan, G. Shi, X. Zhu, S. Shi, Z. Liu, L. Han, H.-Q. Wang, W. Ma, ACS Appl. Mater. Interfaces 2015, 7, 3994. \n[32]\t A.  Walsh, D. O.  Scanlon, S.  Chen, X. G.  Gong, S.-H.  Wei, Angew. Chem., Int. Ed. 2014, 54, 1791. \n[33]\t J. S.  Yun, J.  Seidel, J.  Kim, A. M.  Soufiani, S.  Huang, J.  Lau, N. J.  Jeon, S.  SeokII, M. A.  Green, A.  Ho-Baillie, Adv. Energy Mater. 2016, 6, 1600330. \n[34]\t P.  Xu, S.  Chen, H.-J.  Xiang, X.-G.  Gong, S.-H.  Wei, Chem. Mater. 2014, 26, 6068. \n[35]\t E. L.  Unger, E. T.  Hoke, C. D.  Bailie, W. H.  Nguyen, A. R.  Bowring, T.  Heumüller, M. G.  Christoforo, M. D.  McGehee, Energy Environ. Sci. 2014, 7, 3690. \n[36]\t W.  Tress, N.  Marinova, T.  Moehl, S. M.  Zakeeruddin, M. K. Nazeeruddin, M. Grätzel, Energy Environ. Sci. 2015, 8, 995. \n[37]\t J. Zhang, J. App. Cryst. 2015, 48, 917. \n[38]\t G. Renaud, R. Lazzari, F. Leroy, Surf. Sci. Rep. 2009, 64, 255. \n[39]\t J.  Liu, L.  Qiu, R.  Alessandri, X.  Qiu, W.  Talsma, G.  Ye, M. A.  Loi, R. C. Chiechi, J. C. Hummelen, L. J. A. Koster, unpublished. " + }, + { + "id": "10.1039_c8ee00220g", + "DOI": "10.1039/c8ee00220g", + "DOI Link": "http://dx.doi.org/10.1039/c8ee00220g", + "Relative Dir Path": "mds/10.1039_c8ee00220g", + "Article Title": "A salt-rejecting floating solar still for low-cost desalination", + "Authors": "Ni, G; Zandavi, SH; Javid, SM; Boriskina, SV; Cooper, TA; Chen, G", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "Although desalination technologies have been widely adopted as a means to produce freshwater, many of them require large installations and access to advanced infrastructure. Recently, floating structures for solar evaporation have been proposed, employing the concept of interfacial solar heat localization as a high-efficiency approach to desalination. However, the challenge remains to prevent salt accumulation while simultaneously maintaining heat localization. This paper presents an experimental demonstration of a salt-rejecting evaporation structure that can operate continuously under sunlight to generate clean vapor while floating in a saline body of water such as an ocean. The evaporation structure is coupled with a low-cost polymer film condensation cover to produce freshwater at a rate of 2.5 L m(-2) day(-1), enough to satisfy individual drinking needs. The entire system's material cost is $3 m(-2) - over an order of magnitude lower than conventional solar stills, does not require energy infrastructure, and can provide cheap drinking water to water-stressed and disaster-stricken communities.", + "Times Cited, WoS Core": 743, + "Times Cited, All Databases": 780, + "Publication Year": 2018, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000435351000014", + "Markdown": "# A salt-rejecting floating solar still for low-cost desalination† \n\nGeorge Ni, $\\textcircled{1}$ ‡a Seyed Hadi Zandavi,‡a Seyyed Morteza Javid,b Svetlana V. Boriskina, $\\textcircled{1}$ a Thomas A. Cooper $\\textcircled{1}$ a and Gang Chen\\*a \n\nReceived 22nd January 2018, Accepted 12th March 2018 \n\nDOI: 10.1039/c8ee00220g \n\nrsc.li/ees \n\nAlthough desalination technologies have been widely adopted as a means to produce freshwater, many of them require large installations and access to advanced infrastructure. Recently, floating structures for solar evaporation have been proposed, employing the concept of interfacial solar heat localization as a high-efficiency approach to desalination. However, the challenge remains to prevent salt accumulation while simultaneously maintaining heat localization. This paper presents an experimental demonstration of a salt-rejecting evaporation structure that can operate continuously under sunlight to generate clean vapor while floating in a saline body of water such as an ocean. The evaporation structure is coupled with a low-cost polymer film condensation cover to produce freshwater at a rate of $2.5\\mathsf{L}\\mathsf{m}^{-2}\\mathsf{d}\\mathsf{a}\\mathsf{y}^{-1}.$ enough to satisfy individual drinking needs. The entire system’s material cost is $\\$3,456$ – over an order of magnitude lower than conventional solar stills, does not require energy infrastructure, and can provide cheap drinking water to water-stressed and disaster-stricken communities. \n\n# Broader context \n\nWater scarcity is an increasingly urgent challenge, especially impacting populations living in low development regions. Although various desalination technologies are mature and available, they are often inaccessible due to requiring advanced infrastructure, large-scale installations, and unsustainably intensive fuel consumption. This leaves populations living in small villages and remote locations without affordable options for clean water. Often, the most cost-effective solution is a solar still, essentially a glass-covered box for purifying contaminated water. However, even this simple solution produces freshwater at $10\\times$ the cost of advanced desalination plants. Thus, new approaches are needed to improve accessibility of sustainable and affordable desalination to distributed populations with low infrastructure. Our work demonstrated a small-scale floating desalination system capable of satisfying daily individual drinking needs, suitable for rapid deployment in low development regions that lack clean water. We capitalize on recent research into floating solar structures for enhanced evaporation, which generates vapor that can be condensed into freshwater. Our system simultaneously rejects excess salts left from evaporation, while critically maintaining heat localization. This low-cost approach to solar energy harvesting holds tantalizing potential for distributed and rapidly deployable desalination in disaster relief missions and in low infrastructure areas. \n\n# Introduction \n\nWater is an increasingly scarce resource around the world, with current projections estimating a staggering 3.9 billion people living in water-stressed areas increasing by 2025.1 A quarter of the world’s population, 1.6 billion, lives under economic water scarcity,2 and are unable to afford commercialized desalination technologies available in wealthier countries. Commercial desalination, which extracts fresh water from saline waters, include membrane-based designs such as reverse osmosis (RO),3 and thermal-based designs like multi-stage flash (MSF).4 Despite the maturity of these technologies, they are still unfeasible in developing regions due to high energy consumption, and they require advanced supporting infrastructure and large centralized installations, which introduce a high economic barrier-to-entry.5,6 Existing desalination technology is particularly unsuitable for economically challenged populations living in distributed small villages, or remote regions. In these situations, advanced desalination technologies like RO and MSF are often $10\\times$ as expensive due to small economy-of-scale and scarcity of fuel sources. Rudimentary options such as a solar still7 are often competitive. Low-cost, small-scale desalination technologies that operate using freely available solar energy have the potential to improve water security for the economically water stressed. \n\nRecently, high-efficiency solar evaporation was achieved using floating structures, which do not require high-cost permanent construction or land use, and can be deployed directly on water surfaces.8–14 To achieve high evaporation rates, these structures localize heat generation to the water–air interface to avoid heating an entire large volume of water (such as the ocean). Our group previously demonstrated a heat-localizing solar evaporation approach using a floating double-layer structure, composed of exfoliated graphite as a solar thermal absorber and a porous carbon foam as the thermally insulating layer. The double-layer structure achieved steam and vapor generation at efficiencies as high as $85\\%$ under low solar concentrations $\\left(\\leq10~\\mathrm{~kW~}\\mathrm{~m~}^{-2}\\right)$ . The heat localization concept8,9 was subsequently extended to incorporate plasmonic materials for solar absorption,15–19 paper-based carbon black coatings for cheaper solar absorption,14,20 improved thermal insulation through controlled water delivery strategies,11,14,21 as well as graphene oxide and other exotic materials as absorbers.13,22,23 Ni et al. even demonstrated high temperature $\\left(100^{\\circ}\\mathbf{C}\\right)$ steam generation under unconcentrated sunlight $\\cdot1\\ensuremath{~\\mathrm{kW}\\mathrm{~m}^{-2}}$ , or 1 sun) with a floating solar receiver made of inexpensive household materials such as bubble wrap and styrofoam.11 \n\nThese floating solar evaporation structures can potentially improve existing solar still designs. A low-intensity desalination technology for low infrastructure and remote regions,7 conventional solar stills have typical performances of around 2–4 liters of water per square meter per day, or annually averaged solar efficiencies of $\\sim20\\text{\\textperthousand}$ . Despite being invented centuries ago, conventional single-basin solar stills have not been widely adopted due to their comparatively high unit cost of production (\\$15–150 per $\\mathbf{m}^{3}$ water).24 This high cost comes from the usage of materials such as steel, concrete, and glass to construct the solar still, coupled with the relatively low water production. A rich history of improvements have only increased system complexity and water costs, including usage of porous sponge cubes,25 floating absorbers,26,27 isolated evaporation wicks,28–31 and separate condensation chambers.32–34 Most importantly, conventional solar stills have not been able to solve the problem of fouling (an extensive review on solar stills can be found in ref. 35). Additional key shortcomings include the need to heat an entire volume of water, regularly cleaning of accumulated contaminants, and the generous land area needed to collect adequate sunlight. \n\nDespite the potential improvements from coupling solar evaporation structures with solar stills, several unresolved challenges remain. Among these challenges are: (i) avoiding salt accumulation in the structure under continuous operation, (ii) maintaining high evaporation rates while condensing vapor, (iii) maintaining high temperatures under real seawater conditions, (iv) and shrinking desalination costs of conventional solar stills. Salt build-up remains a significant and poorly studied challenge for floating solar evaporation structures that employ heat localization. Seawater contains $3{-}3.5\\ \\mathrm{wt\\%}$ total dissolved solids, including NaCl and $\\mathbf{CaCO}_{3}$ , which can clog structures after evaporation. Previous works used hydrophobic surfaces to prevent salt from adhering.36 However, the structure needed to be thin to avoid clogging, and thus sacrificed thermal insulation. This is fundamentally because thermal insulation separates the evaporation interface from the cold saline water underneath, where salt needs to be rejected. Inadequate rejection can lead to clogged structures, ultimately deteriorating the optical and wicking properties of the structures. Furthermore, water collection and desalination performance reported for floating evaporation structures $(\\sim5\\%)$ are far below the reported evaporation performance $(\\sim90\\%)$ .14,17 The addition of a vapor collection system stifles the vapor flow conditions from those of open evaporation, and can suppress the evaporation and water collection rates. In addition, real seawater conditions have convective cooling from waves and currents, and this effect has been poorly studied in the literature. Most prior solar evaporation experiments were performed in beakers with still water, which adds extraneous thermal insulation. Lastly, even if solar evaporation structures can improve solar still water production $(2-3\\times)$ , at negligible cost, the conventional solar still itself must be made an order of magnitude cheaper in order to compete with commercial desalination approaches like RO and MSF. Significant challenges remain before solar evaporation structures can be utilized competitively for desalination. \n\nHere, we present a new approach to address fundamental challenges of salt rejection in solar evaporation for desalination. We demonstrate a floating multi-layer solar evaporation structure that rejects excess salts while preserving heat localization. In particular, salt rejection experiments revealed a strong resistance to fouling from NaCl, the most prevalent salt in ocean water. This work has ultimately yielded a low-cost floating solar still, made from commercially available materials, that is capable of producing drinkable water continuously in saline waters, without the need for periodic cleaning. The floating solar still can produce water at $2.5~\\mathrm{L}~\\mathrm{m}^{-2}~\\mathrm{day}^{-1}$ , or a daily-averaged solarto-water efficiency of $22\\%$ , enough to satisfy daily individual drinking needs. In addition, the traditional glass and steel solar still was replaced with a fully polymeric lightweight design expected to have a materials cost of $\\sim\\mathbb{S}3\\mathrm{m}^{-2}$ , and 10–100 times lower than current solar still systems. Water collection tests were conducted both in a controlled rooftop setup and in the ocean. A heat transfer model of the solar still was also developed to identify areas for improvement. We believe this improved floating solar still design, capable of simultaneously rejecting salt and localizing heat, has the potential to significantly expand access to affordable clean water for off-grid communities, thus addressing one of the most pressing challenges in the waterenergy nexus. \n\n# Solar evaporation structure and design \n\nFig. 1 shows the salt-rejection evaporation structure designed to float on saline bodies of water, absorb and convert incident solar flux (nominally $1\\ \\mathrm{kW}\\ \\mathrm{m}^{-2}$ , $250{-}2500\\ \\mathrm{nm}$ into thermal energy, and transfer this heat to water for vapor generation, while rejecting excess salts to the water underneath. The evaporation structure is composed of multiple layers. The top layer is a solar flux absorbing layer of hydrophilic black cellulose fabric $\\left(\\mathrm{Zorb}^{\\mathfrak{R}}\\right)$ , which also wicks up water. Heating only a restricted layer of water enhances evaporation, but also increases the local salinity due to excess salt ions left behind. \n\n![](images/318a6c73f972ca6bc691b761d8084c3c98204d27ef8ae6fc96b0cdd8fdc842e6.jpg) \nFig. 1 An evaporation structure with simultaneous salt rejection and heat localization ability. (a) Shows the evaporation structure’s design, with a black fabric for solar absorption, and a composite white fabric wick and polystyrene foam insulation. The wick both delivers water for evaporation, and rejects excess salt. (b) Shows the advection flow of salt rejection due to denser, salter water at the evaporation surface. (c) Photograph of the evaporation structure. (d) Schematic of the evaporation structure in a fabricated polymer-film based condensation cover operating in an ocean. \n\nBeneath the black fabric is an insulating structure that serves to simultaneously thermally insulate the evaporation layer and to reject excess salts back to the water below. The insulating structure is made from alternating layers of expanded polystyrene foam and white cellulose fabric $(\\mathrm{Zorb}^{\\mathrm{\\textregistered}})$ . The expanded polystyrene has low thermal conductivity $\\left(\\sim0.02\\mathrm{~W~m}^{-1}\\mathrm{~K}^{-1}\\right)$ , and limits thermal conduction of heat down from the evaporation surface above. The white fabric is porous and hydrophilic, allowing it to wick water to the solar-absorbing evaporation structure above, while advecting and diffusing concentrated salt down back into the body of water (Fig. 1b). The evaporation structure (Fig. 1c) is designed to operate with a condensation cover to collect the produced vapor (Fig. 1d). \n\nMaterial selection is important to balance competing thermal and salt rejecting properties needed. The expanded polystyrene is thermally insulating, but impermeable to water, whereas the fabric wick is permeable to water. However, water itself leaks heat, having thermal conductivity $30\\times$ higher than foam $\\left(0.58~\\nu s.~0.02~\\mathrm{W~m}^{-1}~\\mathrm{K}^{-1}\\right)$ . As such, the fabric wick and expanded polystyrene used in the insulation structure have competing thermal and salt rejecting properties, and the area ratio of fabric wick to expanded polystyrene must be optimized to reject salt while maintaining efficient insulation. In addition, different time-scales for salt rejection and thermal insulation must be accounted for. Salt is rejected over 24 hours, while thermal insulation is only needed during daylight hours. \n\nSalt rejection can occur via two modes, diffusion and advection, down the fabric wick. The driving force results from an accumulation of salt ions as water is evaporated. The salt concentration at the evaporation structure increases above the ambient ocean concentration. For this experimental work, the salt-rejection evaporation structure was designed conservatively assuming only diffusion as the main salt-rejection mechanism, though both diffusion and advection play a role in the salt-rejection. \n\nUsing the diffusion assumption, the fabric wick area was chosen to be $\\sim20\\%$ of the total insulation structure area, leaving $80\\%$ remaining area for expanded polystyrene. This area ratio was selected by calculating the daily mass of salt to be rejected, based on an estimated daily evaporation. We then use Fick’s law of diffusion to determine the area needed to diffuse out the daily mass of salt. The final expression for the ratio of wick to total area is given below, \n\n$$\n\\frac{A_{\\mathrm{wick}}}{A_{\\mathrm{evap}}}=\\frac{\\frac{\\eta_{\\mathrm{evap}}E_{\\mathrm{solar}}}{h_{\\mathrm{fg}}}\\times\\frac{3~\\mathrm{wt}^{\\%}_{0}}{97~\\mathrm{wt}^{\\%}_{0}}}{D_{\\mathrm{NaCl}}\\rho_{\\mathrm{w}}\\frac{\\left(C_{\\mathrm{evap}}-C_{\\infty}\\right)}{l_{\\mathrm{w}}}t_{\\mathrm{day}}}\n$$ \n\nwhere $A_{\\mathrm{wick}}$ and $A_{\\mathrm{{evap}}}$ are the areas for salt rejection and evaporation, $\\eta_{\\mathrm{evap}}$ is the estimated daily evaporation efficiency, $E_{\\mathrm{solar}}$ is the total daily insolation, $D_{\\mathrm{NaCl}}$ is the mass diffusion coefficient of NaCl in water, $\\rho_{\\mathrm{w}}$ is the partial density of water in seawater, $l_{\\mathrm{w}}$ is the length of the wick, $\\ensuremath{t_{\\mathrm{day}}}$ is the time length of one day, $C_{\\mathrm{evap}}$ and $C_{\\infty}$ are the mass fraction of NaCl at the evaporation surface and ocean. $C_{\\mathrm{evap}}$ is conservatively chosen to be the saturation condition for NaCl $(26~\\mathrm{wt\\%})$ , which minimizes the thermally detrimental wick area required. More details are given in the ESI. $\\dagger$ \n\n# Laboratory experiments \n\nThe solar-vapor performance of a lab-scale evaporation structure $(21\\mathrm{cm}\\times20\\mathrm{cm})$ was tested under representative laboratory conditions, using both salt and freshwater (details in $\\mathrm{ESI\\dag}\\$ ). A solar simulator was used to supply simulated sunlight, and a calibrated power meter to measure incoming radiative flux. The mass of the evaporation structure and water reservoir was continuously monitored using a balance to determine the rate of vapor generation (Fig. 2a). The efficiency of solar-vapor conversion is defined as: \n\n$$\n\\eta_{\\mathrm{evap}}=\\frac{\\dot{m}_{\\mathrm{v}}h_{\\mathrm{fg}}}{q_{\\mathrm{solar}}A_{\\mathrm{evap}}},\n$$ \n\nwhere $\\dot{m}_{\\nu}$ is the mass flux under steady state conditions, $h_{\\mathrm{fg}}$ is the temperature-dependent latent heat of vaporization of water, $q_{\\mathrm{solar}}$ is the incoming solar flux, and $A_{\\mathrm{{evap}}}$ is the area of the evaporation structure exposed to the incoming solar flux. The sensible heat is neglected because cold water was not piped in to replace generated vapor. To isolate the effects of solar input, the evaporation rate in the dark was subtracted from the measured evaporation rate. \n\nFloating in freshwater and under peak sunlight $\\left(1\\mathrm{kW}\\mathrm{m}^{-2}\\right).$ , the evaporation structure can generate vapor at $42\\ ^{\\circ}\\mathrm{C}$ and $57\\pm2.5\\%$ efficiency. Importantly, when floating in simulated seawater ${3.5~\\mathrm{wt\\%}}$ NaCl), the evaporation structure generated vapor at comparable efficiencies $(56\\pm2.5\\%)$ . To understand the evaporation structure performance under variable sunlight conditions, we further measured the efficiency at solar intensities ranging from $600\\mathrm{W}\\mathrm{m}^{-2}$ to $1000\\mathrm{W}\\mathrm{m}^{-2}$ (Fig. 2b). Predictably, the evaporation efficiency reduces slightly $52\\pm2.5\\%$ at $600\\mathrm{W}\\mathrm{m}^{-2}.$ 1 with lower sunlight, due to lower evaporation temperatures reached. \n\nOur experiments revealed that the composite wicking– insulation structure succeeded in minimizing heat conduction downward from the liquid–air interface. Fig. 2c shows the temperatures recorded at different locations (Fig. 2d) in the evaporation structure. After 4 hours of peak solar illumination $(1~\\mathrm{kW}~\\mathrm{m}^{-2}).$ , the water temperature underneath increased by only $4{\\bf\\Sigma}^{\\circ}{\\bf C}$ , due to reduced heat flux through the insulation structure. The heat conduction losses through the insulation structure are calculated to be $110\\mathrm{W}\\mathrm{m}^{-2}$ , corresponding to an \n\n![](images/3e184fce1af7c3665151df9e158a2a89dd04178eb3f130f516ed2ff0716b787d.jpg) \nFig. 2 Performance of the evaporation structure in solar vapor generation under lab conditions. (a) Shows the evaporation rate of the evaporation structure in fresh (dashed) and salt water (solid, 3.5 wt% NaCl). (b) Shows the performance of the evaporation structure in freshwater at different solar fluxes below 1 sun $(1\\mathsf{k W}\\mathsf{m}^{-2})$ ). There is a slight decrease in efficiency at lower solar fluxes. (c) Shows the temperatures measured at different locations of the evaporation structure shown in (d). The large temperature drop from the solar absorbing fabric to the water underneath indicates the insulating ability of the expanded polystyrene. \n\n$11\\%$ loss relative to the incoming solar energy. Radiative and convective losses from the top of the evaporation structure account for $11\\%$ and $9\\%$ of peak sunlight, respectively (see $\\mathrm{ESI\\dag}\\$ ). The remaining major losses are reflective optical losses of $15\\%$ from the wetted black fabric of the evaporation structure (measurement in $\\mathrm{ESI\\dag}$ ). \n\nThe evaporation structure’s salt rejection capability was characterized by several complementary experiments. In the first experiment, we exposed the evaporation structure to simulated sunlight while floating in a $3.5~\\mathrm{wt\\%}$ NaCl simulated seawater reservoir for 7 days (details in $\\mathrm{ESI\\dag}$ ). Each day, the evaporation structure was exposed to 5 hours of peak sunlight $(1\\mathrm{~kW~m}^{-2}$ ), and then allowed to cool and reject salt ‘‘overnight’’. No salt was observed to form at the end of 7 days, indicating adequate NaCl rejection over extended periods of evaporation. After the seventh day, the structure was illuminated continuously for 30 hours at $1~\\mathrm{kW}~\\mathrm{m}^{-2}$ without detectable salt crystal formation. \n\nThe second salt rejection experiment demonstrated the evaporation structure’s ability to reject salt crystals under steady-state evaporation conditions under 1 sun illumination. The evaporation structure was placed in $3.5\\ \\mathrm{wt\\%}$ NaCl simulated seawater, and 40 grams of additional solid NaCl, enough to saturate the entire wick structure with $26\\mathrm{\\ut{\\%}}$ NaCl, were placed directly on the evaporation structure. The structure was then illuminated with the solar simulator $(1~\\mathrm{kW}~\\mathrm{m}^{-2}$ . Despite the extreme amount of salt placed on top, the evaporation structure fully rejected the salt after just ${\\sim}1$ hour (Fig. 3a–f and supplementary video, $\\mathrm{ESI\\dag}$ ), while generating vapor. After 20 hours of illumination, the NaCl concentration at the wick was found to be $4.2\\ \\mathrm{wt\\%}$ , using an optical refractometer, indicating that salt was rejected and not merely dissolved in the structure (details in the $\\mathrm{ESI\\dag}$ ). Fig. 3g visually illustrates the flow of higher concentration salt water leaving the structure. These two salt rejection experiments indicate that (1) the evaporation structure can reject NaCl for several days of solar evaporation, and (2) the evaporation structure can dissolve and reject salt deposits even under constant sunlight. \n\nThe NaCl concentration at the top of the wick was below the saturation condition $\\left(4.2~\\nu s.~26~\\mathrm{wt\\%}\\right)$ , indicating an additional mass transfer mechanism to complement diffusion. We show this lowered salt gradient to be caused by advection, via theory and a CFD model (details in $\\mathbf{ESI\\dagger}_{\\mathbf{\\lambda}}$ . Following the detailed analysis shown in the ESI, $\\dagger$ we use a material parameter, which determines whether diffusion or advection results in lower heat losses, as the ratio of the corresponding thermal losses under the two salt rejection scenarios: \n\n$$\n\\frac{\\frac{\\varrho_{\\mathrm{d}}}{J_{\\mathrm{d}}}}{\\frac{\\varrho_{\\mathrm{conv}}}{J_{\\mathrm{conv}}}}=\\frac{\\alpha_{\\mathrm{w}}}{D_{\\mathrm{NaCl}}}\n$$ \n\nHere $Q_{\\mathrm{d}}$ and $J_{\\mathrm{d}}$ represent heat loss due to thermal conduction through the water and salt rejection due to chemical diffusion of NaCl, and $Q_{\\mathrm{conv}}$ and $J_{\\mathrm{conv}}$ represent the heat loss and salt rejection due to advection of hot brine away, and $\\mathcal{I}_{\\mathrm{w}}$ is the thermal diffusivity of water. In diffusion, a wick with static water has salt diffusing down a concentration gradient. Simultaneously, heat conducts through the water from the hot evaporation surface to the ocean underneath. For salt rejection via advection, a volume of hot concentrated brine is exchanged with relatively dilute seawater. The stored sensible heat in the hot brine is lost to the ocean. Ultimately, the choice of using advection or diffusion to reject salt comes down to which mechanism has a lower associated heat loss, thus enabling higher evaporation efficiency. \n\n![](images/9deadc31bcbe61564e86cb5e95ec5dd0a4eac01de40e298a0f3965395b5e2f29.jpg) \nFig. 3 (a–f) Show a progression of salt rejection from the evaporation structure, while under 1 sun illumination. The evaporation structure is placed in a reservoir of 3.5 wt% NaCl, and enough solid NaCl is placed on the evaporation structure to saturate $(26~\\mathsf{w t\\%})$ the structure. This hour-long test displays the ability to reject salt during operation. (g) Shows a separate test to visualize saltwater rejected by the evaporation structure. Excess salt at the evaporation surface forms a denser solution, which sinks into the water reservoir. A blue dye was added to help visualize the flow, which occurs without the dye as well. \n\nSubsequently, a numerical thermo-fluid simulation code was used to model the fluid flow, salt transport and temperature distribution in a single wick $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ . The simulation results confirm that advection dominates the salt rejection process, and that there are counter-rotating two-dimensional advection currents in the salt rejecting wick (Fig. 1b). \n\nSeawater contains many additional dissolved salts and ions beyond Na and Cl, such as Ca, K, Mg, Sr, which upon evaporation potentially form numerous sulfates and carbonates that can also clog the evaporation structure. Understanding that salt rejection occurs primarily through advection, the expected increase in concentration in these salts is expected to be similar to NaCl in the salt rejection experiments (from $3.5~\\mathrm{wt\\%}$ to $4.2~\\mathrm{wt\\%}$ . We expect potential sulfates still to be rejected under continuous operation, and while carbonates have the potential for build-up, they are at minute enough concentrations to possibly not affect the system. Details are in the Supplementary, Note S.8 $\\left(\\mathrm{ESI\\dag}\\right)$ . Further study is needed to assess the impact of sulfates and carbonates on fouling, as well as biological fouling. \n\n# Condensation structure \n\nA large condensation cover $55\\ \\mathrm{cm}\\times55\\ \\mathrm{cm}$ ) was developed to surround the evaporation structure, and capture and condense the solar-generated vapor (Fig. 4a). The condensation structure is transparent in the solar spectrum, allowing solar flux to reach the evaporation structure within. The condensed droplets on the cover coalesce and eventually drip into a catch tube. The water produced is typically very pure $(\\sim50\\:\\mathrm{ppm})$ .37 However, maximizing collection of all condensed droplets is a major challenge, as not all condensation surfaces are easily collectable. \n\nThe large condensation cover $55\\ \\mathrm{cm}\\ \\times\\ 55\\ \\mathrm{cm})$ was tested in tandem with a large evaporation structure, forming the floating solar still. The floating solar still was deployed in a shallow basin filled with water on the roof of MIT, Cambridge, USA, and water collection was measured over several days during the summer. The condensate was collected in a nearby beaker. The instantaneous vapor temperature, incident sunlight, and ambient wind temperature and humidity were recorded. Here, the collection efficiency is defined as \n\n$$\n\\eta_{\\mathrm{water}}=\\frac{m_{\\mathrm{cond}}h_{\\mathrm{fg}}}{A_{\\mathrm{evap}}\\int q_{\\mathrm{solar}}(t)\\mathrm{d}t},\n$$ \n\nwhere $\\eta_{\\mathrm{water}}$ is the solar-water efficiency, $m_{\\mathrm{cond}}$ is the mass of condensate collected daily, $q_{\\mathrm{solar}}(t)$ is the time-dependent solar flux, and the denominator is the total daily solar insolation. \n\nIn this rooftop system, the maximum daily solar-water efficiency measured was $24\\%$ , while the maximum condensate collected was $2.81~\\mathrm{L~m}^{-2}$ per day. Fig. 4b shows similar performance between cloudy (Fig. 4c) and sunny days (Fig. 4d). The condensate produced from our $0.30~\\mathrm{m}^{2}$ still is 3.5 times higher compared to a previous work on floating solar stills,14 and is adequate for daily individual drinking needs. \n\n# Ocean testing \n\nWe also tested the floating solar still in an ocean (Pleasure Bay, Boston, USA) to accurately assess the effect of ocean circulation on heat loss underneath the evaporation structure. The Pleasure Bay test location provides representative conditions of salinity $(3~\\mathrm{wt\\%}$ NaCl), tides, and currents. The floating solar still was deployed on the bay from 10:30 am to $3{:}00\\ \\mathrm{pm}$ on August 1, 2017 (Fig. 5a), a representative sunny day (insolation shown in Fig. 5b). A total of $0.39\\mathrm{L}$ of water was collected, corresponding to a solar-water efficiency of $22\\%$ during that time period $\\left(3.7\\mathrm{kWh}\\mathrm{m}^{-2}\\right)$ . For a sunny Boston summer day (7 k $\\mathrm{Wh}\\mathrm{m}^{-2}\\mathrm{day}^{-1},$ , $2.5\\mathrm{L}\\mathrm{m}^{-2}\\mathrm{day}^{-1}$ of water can be produced. However, the daily production depends on the total daily insolation, which varies dramatically $\\left(2{-}10\\mathrm{~kW}\\mathrm{~h~m}^{-2}\\mathrm{~day}^{-1}\\right.$ , or $0.7–3.6\\mathrm{~L~m~}^{-2}\\mathrm{~day}^{-1},$ depending on weather, location, and season. Ideally, some kind of water storage can be incorporated for dispatchability. The ocean system’s production is slightly lower than the rooftop system due to additional convection heat losses under the solar still from ocean currents. A system heat transfer model of the entire solar still was developed to analyze sources of heat loss and areas for improvement (details in $\\mathrm{ESI\\dag}$ ). \n\n![](images/478039bc0a248bac422a3eba1492b655bef0087a92a777a6522b9007428cc00f.jpg) \nFig. 4 Rooftop experiments with the floating solar still under natural sunlight. A shallow basin of freshwater supplied the water. (a) Testing location on MIT’s roof, in May–June 2017. Liquid water was collected, and the solar flux measured. (b) The water collection efficiency of the floating solar still with different solar intensities. The performance of the structure is relatively invariant with solar insolation. (c) The solar flux on a partly cloudy day. (d) The solar flux on a sunnier day. $E_{\\mathsf{s o l a r}}$ is the daily solar insolation per $m^{2}$ . \n\n![](images/744382d50f0ad4e0994f3bff953dbb9a136be8423239d1ffe28ee9e9f0fb4283.jpg) \nFig. 5 Testing the floating solar still in the ocean (3 wt% NaCl) under natural sunlight. (a) Photograph of the solar still in operation at the test location Pleasant Bay, MA, on the coast of the Atlantic Ocean. (b) The solar flux during measurement. (c) The temperature evolution at different locations on the evaporation structure. (d) The evaporation structure and condensation cover breakdown of materials. The entire system can be assembled and disassembled by hand, and stored in a compact space. \n\nTesting in the ocean displayed the floating solar still’s effectiveness in limiting heat conduction loss even with cold ocean water underneath. The temperatures of the evaporation structure floating in the ocean (on a different date) are shown in Fig. 5c. The temperature of the thermal insulation’s bottom surface is nearly constant as it exchanges heat with the bulk of the ocean water. \n\n# Discussion \n\nWe designed and experimentally demonstrated a new floating solar evaporation structure engineered to simultaneously reject salt while maintaining heat localization for enhanced evaporation. The salt rejection was proven in several lab and ocean experiments. Design guidelines are given to determine whether advection or diffusion should be used in salt rejection, and a thermofluid model was developed to guide future work. A collection cover was developed and paired with the evaporation structure, and freshwater was extracted from various saline waters. Lab-scale and ocean-scale testing was conducted to characterize the performance of the system, resulting in $22\\%$ solar-water performance. Coupled with the floating solar still’s low-cost design $\\left(\\sim\\$3\\mathrm{~m}^{-2}\\right)$ , and an estimated life-cycle of 2 years, water production cost is $\\$1.5\\:\\mathrm{m}^{-3}$ (breakdown in Fig. 5d and $\\mathrm{ESI\\dag}$ ). This is $10\\times$ lower than those of conventional solar stills $(\\sim\\$15\\mathrm{~m}^{-3})$ . Though we only include the material cost here, the floating solar still is potentially cheaper than small-scale RO $(\\$5-10\\mathrm{m}^{-3})$ , such as those used in the Maldives.38 State of the art large-scale RO desalination plants still produce fresh water at lower cost $(\\sim\\mathbb{S}0.5\\ \\mathrm{m}^{-3})$ ,6 but require high capital funding, access to the grid, and large production capacities. \n\nThere is still ample room for improvement of this technology. Higher collection efficiency can be reached by reducing the optical losses due to droplet formation on the cover. Substituting glass covers with polyester covers in our floating still has resulted in high optical loss $(35\\%)$ , due to the higher contact angle that water makes with hydrophobic polymers. This is in agreement with previous work that revealed that water collection efficiency of solar stills with the glass cover consistently exceeds that of identical stills with plastic covers by over $30\\%$ .39,40 Reduction of the optical transparency due to poor wettability of plastics has also been studied previously in simulations, which show that the droplet contact angle should be reduced below $\\sim50^{\\circ}$ to reduce optical losses.41,42 One strategy may be using hydrophilic transparent polyesters, though the durability of this solution in water must be assessed. Another area for improvement is reduction of the wick area considering the prevalence of advective flow revealed in our study. The total wick area chosen in this study was based on the conservative assumption of diffusion-based salt rejection, and could be reduced to further minimize backside heat losses. The individual wick width is also important, as it affects the manufacturability (number of wicks needed), advection flow (due to viscous losses), and salt rejection (due to horizontal inter-wick salt flow at the evaporation surface). The wick width cannot be too narrow as to suppress the advective flow, nor can it be too wide such that the inter-wick mass transport will dominate the salt rejection, rather than within the wick. There is an upper limit to how wide the wick can be, as it will increase the inter-wick spacing. At some point the interwick mass transport will dominate the salt rejection, rather than within the wick. Another area is reducing reflective losses at the fabric absorber $(\\sim15\\%,\\ \\mathrm{ESI}\\dagger)$ ). Other sources of loss include partial collection of all the condensate formed on the cover. In a traditional single-slope solar still, a glass cover tilted at $30^{\\circ}$ accounts for only $38\\%$ of the total condensable surface. In our floating solar still, we collect from $85\\%$ of the total condensable area, using a double-sloped design and wicks to collect from the sides. If all of these losses are addressed, our system model predicts that $42\\%$ solar-water collection efficiency is achievable. \n\nfilled with fresh water or saline water. The mass loss of the water was measured using a balance with $_{\\mathrm{~0.1~g~}}$ resolution (A&D, EJ3000). Steady-state evaporation rates were measured for 30 minutes once steady conditions were reached. \n\n# Experimental \n\nThe temperatures were measured at five different locations of the evaporation structure shown in Fig. 2d ( $\\stackrel{\\cdot}{T}_{1}$ : at the black absorber, $T_{2}$ : at the wick below the absorber, $T_{3}$ : underneath the thermal insulation, $T_{4}$ : in the wick bottom of the evaporation structure, and $T_{5}$ : in the bulk of the liquid) using thermocouples (Omega Engineering, 5TC-TT-K-40-36), and recorded using an Omega Engineering DAQPRO. The absorber temperature was measured by a thermocouple inserted into the evaporation fabric. Thermocouples were placed at the center, to represent the temperature of a sufficiently large absorber where side effects would be negligible. In Fig. 5c, only four different temperatures are measured, with the bottom of the thermal insulation not measured. The temperatures measured are: $T_{1}$ at the black absorber, $T_{2}$ at the wick below the absorber, $T_{3}$ in the wick bottom of the evaporation structure, and $T_{4}$ in the bulk of the liquid. \n\nThe floating solar still was designed to be low cost and easily manufactured from widely available materials. The evaporation structure was constructed from cellulose-based fabric $(\\mathrm{Zorb}^{\\mathrm{\\textregistered}})$ , and expanded polystyrene (Owen-Corning Foamulars 150). The condensation structure was constructed from lightweight and cheap polymer films. We evaluated several polymer films, eventually settling on commercial polyester films (McMaster-Carr $\\#8567\\mathrm{K}32$ , $0.003^{\\prime\\prime}$ thick). The film was cut into several pieces, and welded together using a heat sealer (McMaster-Carr $\\#2054\\mathrm{T}35\\$ ). Droplet collection was facilitated using flaps of polyester film and fabric wicks $\\left(\\mathrm{Zorb}^{\\mathrm{\\textregistered}}\\right)$ , as an alternative to typical rubber drip edges and tubes. The polyester film was supported by plastic rods and joints. The wholesale materials cost of the entire floating solar still including the evaporation structure and cover is $\\sim\\$3\\m\\mathrm{m}^{-2}$ . \n\nFor the day-to-day salt rejection experiments, water with $3.5~\\mathrm{wt\\%}$ NaCl was premixed and placed in the basin, which acted as a salt reservoir. For the week-long salt rejection experiment, the evaporation structure and salt reservoir were exposed to sunlight at $1~\\mathrm{kW}~\\mathrm{m}^{-2}$ for 5 hours each day, then allowed to cool and reject salt for 19 hours. The mass of the entire system was monitored to determine the amount of water evaporated. Fresh water was added, as needed to the bottom of the salt reservoir at the beginning of the experiment each day, to ensure that the reservoir’s NaCl concentration remained constant at the start of each day. The evaporation structure surface was photographed daily to monitor the nucleation of NaCl crystals. \n\nThe evaporation structure was tested in the lab using a solar simulator (ScienceTech, SS-1.6K) outputting simulated solar flux between 600–1000 W $\\mathrm{m}^{-2}$ (1 sun). The solar flux was measured using a thermopile (Newport, 818P-040-55) connected to a power meter (Newport, 1918-C). Because the solar flux varies across the beam area, and the thermopile detector is smaller in area than the solar receiver, the solar flux was measured over 5 distributed locations and averaged. The evaporation structure was placed in a polycarbonate basin $(21~\\mathrm{cm}\\times22~\\mathrm{cm}\\times3.5~\\mathrm{cm})$ , \n\nThe saturation salt rejection experiments were conducted using a glass container with $2.9\\mathrm{~L~}$ capacity ( $\\mathrm{18~cm}$ in diameter). Water with $3.5~\\mathrm{wt\\%}$ NaCl was premixed and placed in the glass container, which acted as a salt reservoir. A small $(14\\ \\mathrm{cm}\\times7\\ \\mathrm{cm})$ evaporation structure was used. The small size was chosen to ensure that the NaCl rejected to the reservoir wouldn’t significantly change the reservoir’s NaCl concentration. The area between the structure and the container was covered with a plastic cover. The entire setup was exposed to $1\\mathrm{kW}\\mathrm{m}^{-2}$ of sunlight, and then $40{\\mathrm{g}}$ of salt crystals were deposited on top of the evaporation structure. A camera periodically photographed the evaporation structure surface to show salt dissolving and rejecting over the course of a few hours. The salt concentration of the reservoir and evaporation structure top was measured using an optical refractometer with a resolution of $0.1~\\mathrm{wt\\%}$ NaCl (ATC SSA0010). A few drops (3 to 4) of liquid were sucked from the measurement location, and deposited onto the optical window of the refractometer. The final salt concentration in the salt water was $4.6\\mathrm{wt\\%}$ after the salt rejection experiment. \n\nRooftop water collection measurements were performed with the large solar still $(55~\\mathrm{cm}\\times55~\\mathrm{cm})$ . The solar intensity (global horizontal irradiance) was measured using a Hukseflux LP-02 thermal pyranometer. The floating solar still was placed in a shallow basin of water (3 cm deep), placed on a table to avoid conductive heating from the rooftop surface. The floating solar still was oriented with the sloped panels facing south. Water collected from the still was routed via a tube to several sealed beakers. The beakers were emptied 2–3 times throughout the day, and the mass of water collected was recorded. The water collection was recorded through a 24 hour period, starting after sunset when the solar still had equilibrated to ambient temperature. \n\nThe ocean experiments were conducted in Pleasure Bay, located in South Boston, MA. The bay is connected to the Atlantic Ocean, and has a salinity of $3\\ \\mathrm{wt\\%}$ , as measured by the optical refractometer. The temperatures at different locations of the evaporation structure (shown in Fig. 5d of manuscript) and the ocean water were measured using thermocouples (Omega Engineering, 5TC-TT-K-40-36) and the Omega DAQPRO. The solar flux data were provided using a local weather station maintained by the MIT Sustainable Design Lab. The liquid water produced by the floating solar still was collected in submerged water bottles. The collected water was weighed at the end of the experiment to determine the amount produced, and the salinity was measured to ensure that no seawater had leaked in. \n\n# Conclusions \n\nA low-cost solar evaporation structure has been developed, which rejects excess salt while simultaneously maintaining heat localization for enhanced evaporation rates. Experiments were conducted to characterize the evaporation performance and salt rejection performances. A condensation system was developed to collect the generated vapors. The condensation system coupled with the evaporation structure formed a low-cost solar still, capable of seawater desalination at a rate of $2.5~\\mathrm{L}~\\mathrm{m}^{-2}~\\mathrm{day}^{-1}$ , enough water for individuals to drink. \n\nFloating deployment of our system directly on sea, ocean or lake surfaces helps save agriculturally important land and natural ecosystems from being developed for energy and water production, and eliminates the need for water delivery infrastructure or manual labor. A small individual- or family-size floating still does not require larger community cooperation or external control over fair distribution of distilled water, making it a fast-to-deploy, simple-to-use, and conflict-free technology for disaster relief missions and sparsely-populated areas. \n\n# Author contributions \n\nG. N., S. H. Z. and G. C. developed the concept. G. N. and S. H. Z. conducted the experiments. G. N., S. M. J., S. H. Z., S. V. B. and T. C. prepared the models. G. N., S. H. Z., S. V. B., T. C. and G. C. wrote the paper. G. C. directed the overall research. \n\n# Conflicts of interest \n\nThere are no conflicts to declare. \n\n# Acknowledgements \n\nWe gratefully acknowledge funding support from the Abdul Latif Jameel World Water and Food Security Lab (J-WAFS, a center created to coordinate and promote water and food research at MIT under Agreement DTD 04/21/2015, for water desalination applications) and the support from MIT S3TEC Center (an Energy Frontier Research Center funded by the Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-FG02- 09ER46577 for basic experimental infrastructure). S. H. Z. thanks Natural Sciences and Engineering Research Council of Canada (NSERC) for their support. We thank William Wang for assistance in setting up the ocean experiments. \n\n# References \n\n1 S. Hoffman, Planet water: investing in the world’s most valuable resource, John Wiley & Sons, 2009. \n2 D. D. Molden, International Water Management Institute & Program, C. A. O. W. M. I. A. Water for food, water for life: a comprehensive assessment of water management in agriculture, Choice Reviews Online, Earthscan, Sterling, VA, London, 2007, vol. 45, p. 45-0867. \n3 L. Malaeb and G. M. Ayoub, Reverse osmosis technology for water treatment: state of the art review, Desalination, 2011, 267, 1–8. \n4 A. D. Khawaji, I. K. Kutubkhanah and J.-M. Wie, Advances in seawater desalination technologies, Desalination, 2008, 221, 47–69. \n5 Energy, U. R. Water Desalination Using Renewable Energy, IRENA, 2012. \n6 N. Ghaffour, T. M. Missimer and G. L. Amy, Technical review and evaluation of the economics of water desalination: current and future challenges for better water supply sustainability, Desalination, 2013, 309, 197–207. \n7 A. E. Kabeel and S. A. El-Agouz, Review of researches and developments on solar stills, Desalination, 2011, 276, 1–12. \n8 H. Ghasemi, et al., Solar steam generation by heat localization, Nat. Commun., 2014, 5, 1–7. \n9 Z. Wang, et al., Bio-inspired evaporation through plasmonic film of nanoparticles at the air-water interface, Small, 2014, 10, 3234–3239. \n10 Y. Ito, et al., Multifunctional porous graphene for highefficiency steam generation by heat localization, Adv. Mater., 2015, 27, 4302–4307. \n11 G. Ni, et al., Steam generation under one sun enabled by a floating structure with thermal concentration, Nat. Energy, 2016, 1, 16126. \n12 L. Zhou, et al., Self-assembly of highly efficient, broadband plasmonic absorbers for solar steam generation, Sci. Adv., 2016, 2, e1501227. \n13 J. Yang, et al., Functionalized graphene enables highly efficient solar thermal steam generation, ACS Nano, 2017, 11, 5510–5518. \n14 Z. Liu, et al., Extremely cost-effective and efficient solar vapor generation under nonconcentrated illumination using thermally isolated black paper, Global Challenges, 2017, 1, 1600003. \n15 L. Tian, et al., Plasmonic biofoam: a versatile optically active material, Nano Lett., 2016, 16, 609–616. \n16 D. Zhao, et al., Enhancing localized evaporation through separated light absorbing centers and scattering centers, Sci. Rep., 2015, 1–10, DOI: 10.1038/srep17276. \n17 L. Zhou, et al., 3D self-assembly of aluminium nanoparticles for plasmon-enhanced solar desalination, Nat. Photonics, 2016, 1–7, DOI: 10.1038/nphoton.2016.75. \n18 C. Chang, et al., Efficient solar-thermal energy harvest driven by interfacial plasmonic heating-assisted evaporation, ACS Appl. Mater. Interfaces, 2016, 8, 23412–23418. \n19 X. Wang, Y. He, X. Liu, G. Cheng and J. Zhu, Solar steam generation through bio-inspired interface heating of broadband-absorbing plasmonic membranes, Appl. Energy, 2017, 195, 414–425. \n20 Y. Liu, J. Chen, D. Guo, M. Cao and L. Jiang, Floatable, selfcleaning, and carbon-black-based superhydrophobic gauze for the solar evaporation enhancement at the air–water interface, ACS Appl. Mater. Interfaces, 2015, 7, 13645–13652. \n21 X. Li, et al., Graphene oxide-based efficient and scalable solar desalination under one sun with a confined 2D water path, Proc. Natl. Acad. Sci. U. S. A., 2016, 113, 13953–13958. \n22 N. Xu, et al., Mushrooms as Efficient Solar Steam-Generation Devices, Adv. Mater., 2017, 10, 1606762. \n23 X. Hu, et al., Tailoring graphene oxide-based aerogels for efficient solar steam generation under one sun, Adv. Mater., 2016, 29, 1604031. \n24 A. E. Kabeel, A. M. Hamed and S. A. El-Agouz, Cost analysis of different solar still con, Energy, 2010, 35, 2901–2908. \n25 B. A. Abu-Hijleh and H. M. Rababa’h, Experimental study of a solar still with sponge cubes in basin, Energy Convers. Manage., 2003, 44, 1411–1418. \n26 A. S. Nafey, M. Abdelkader, A. Abdelmotalip and A. A. Mabrouk, Enhancement of solar still productivity using floating perforated black plate, Energy Convers. Manage., 2002, 43, 937–946. \n27 W. Delano, Solar still with floating slab-supporting particulate radiant energy receptor, 1970. \n28 A. A. Al-Karaghouli and A. N. Minasian, A floating-wick type solar still, Renewable Energy, 1995, 1, 77–79. \n29 A. N. Minasian and A. A. Al-Karaghouli, An improved solar still: the wick-basin type, Energy Convers. Manage., 1995, 36, 213–217. \n30 B. Janarthanan, J. Chandrasekaran and S. Kumar, Performance of floating cum tilted-wick type solar still with the effect of water flowing over the glass cover, Desalination, 2006, 190, 51–62. \n31 J. T. Mahdi, B. E. Smith and A. O. Sharif, An experimental wick-type solar still system: design and construction, Desalination, 2011, 267, 233–238. \n32 B. A. Abu-Hijleh, Enhanced solar still performance using water film cooling of the glass cover, Desalination, 2002, 107, 235–244. \n33 A. El-Bahi and D. Inan, Analysis of a parallel double glass solar still with separate condenser, Renewable Energy, 1999, 17, 509–521. \n34 S. Kumar and G. N. Tiwari, Life cycle cost analysis of single slope hybrid (PV/T) active solar still, Appl. Energy, 2009, 86, 1995–2004. \n35 J. Lienhard, M. A. Antar, A. Bilton and J. Blanco, Solar desalination, Annu. Rev. Heat Transfer, 2012, 277–347. \n36 V. Kashyap, et al., A flexible anti-clogging graphite film for scalable solar desalination by heat localization, $J.$ Mater. Chem. A, 2017, 5, 15227–15234. \n37 B. Van der Bruggen and C. Vandecasteele, Distillation vs. membrane filtration: overview of process evolutions in seawater desalination, Desalination, 2002, 143, 207–218. \n38 S. A. Ibrahim, M. R. Bari and L. M. M. W. Sanitation Authority, Water resources management in Maldives with an emphasis on desalination, 2002, academia.edu. \n39 B. W. Tleimat and E. D. Howe, Comparison of plastic and glass condensing covers for solar distillers, Sol. Energy, 1969, 12, 293–304. \n40 M. K. Phadatare and S. K. Verma, Effect of cover materials on heat and mass transfer coefficients in a plastic solar still, Desalin. Water Treat., 2012, 2, 254–259. \n41 E. W. Tow, The antireflective potential of dropwise condensation, J. Opt. Soc. Am. A, 2014, 31, 493. \n42 K. Zhu, Y. Huang, J. Pruvost, J. Legrand and L. Pilon, Transmittance of transparent windows with non-absorbing cap-shaped droplets condensed on their backside, J. Quant. Spectrosc. Radiat. Transfer, 2017, 194, 98–107. " + }, + { + "id": "10.1038_s41467-018-04953-8", + "DOI": "10.1038/s41467-018-04953-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-04953-8", + "Relative Dir Path": "mds/10.1038_s41467-018-04953-8", + "Article Title": "Very large tunneling magnetoresistance in layered magnetic semiconductor CrI3", + "Authors": "Wang, Z; Gutiérrez-Lezama, I; Ubrig, N; Kroner, M; Gibertini, M; Taniguchi, T; Watanabe, K; Imamoglu, A; Giannini, E; Morpurgo, AF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Magnetic layered van der Waals crystals are an emerging class of materials giving access to new physical phenomena, as illustrated by the recent observation of 2D ferromagnetism in Cr2Ge2Te6 and CrI3. Of particular interest in semiconductors is the interplay between magnetism and transport, which has remained unexplored. Here we report magneto-transport measurements on exfoliated CrI3 crystals. We find that tunneling conduction in the direction perpendicular to the crystalline planes exhibits a magnetoresistance as large as 10,000%. The evolution of the magnetoresistance with magnetic field and temperature reveals that the phenomenon originates from multiple transitions to different magnetic states, whose possible microscopic nature is discussed on the basis of all existing experimental observations. This observed dependence of the conductance of a tunnel barrier on its magnetic state is a phenomenon that demonstrates the presence of a strong coupling between transport and magnetism in magnetic van der Waals semiconductors.", + "Times Cited, WoS Core": 748, + "Times Cited, All Databases": 802, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000436548700007", + "Markdown": "# Very large tunneling magnetoresistance in layered magnetic semiconductor CrI3 \n\nZhe Wang 1,2, Ignacio Gutiérrez-Lezama1,2, Nicolas Ubrig 1,2, Martin Kroner3, Marco Gibertini1,2, Takashi Taniguchi4, Kenji Watanabe $\\textcircled{1}$ 4, Ataç Imamoğlu3, Enrico Giannini 1 & Alberto F. Morpurgo 1,2 \n\nMagnetic layered van der Waals crystals are an emerging class of materials giving access to new physical phenomena, as illustrated by the recent observation of 2D ferromagnetism in $\\mathsf{C r}_{2}\\mathsf{G e}_{2}\\mathsf{T e}_{6}$ and $C r l_{3}$ . Of particular interest in semiconductors is the interplay between magnetism and transport, which has remained unexplored. Here we report magnetotransport measurements on exfoliated $\\mathsf{C r l}_{3}$ crystals. We find that tunneling conduction in the direction perpendicular to the crystalline planes exhibits a magnetoresistance as large as $10,000\\%$ . The evolution of the magnetoresistance with magnetic field and temperature reveals that the phenomenon originates from multiple transitions to different magnetic states, whose possible microscopic nature is discussed on the basis of all existing experimental observations. This observed dependence of the conductance of a tunnel barrier on its magnetic state is a phenomenon that demonstrates the presence of a strong coupling between transport and magnetism in magnetic van der Waals semiconductors. \n\nnvestigations of layered van der Waals compounds are revealing a wealth of electronic phenomena, which can be controlled by varying the material thickness at the atomic scale1–4. Among these compounds, magnetic van der Waals semiconductors5–19 have remained virtually unexplored. These materials possess a unique potential for new physical phenomena, because magnetism occurs spontaneously without the need to introduce magnetic dopants as done in conventional magnetic semiconductors20–22, allowing—at least in principle—perfect crystalline order to be preserved. Indeed, the potential of magnetic van der Waals semiconductors has been made apparent by very recent experiments showing the occurrence of 2D ferromagnetism in atomically thin layers of Cr2Ge2Te616 and CrI317. So far however, essentially no experiment has been done to probe the transport and opto-electronic properties of these materials, and it remains to be determined whether their behavior deviates from that of conventional semiconductors, i.e., whether magnetism causes new interesting physical phenomena to appear. This can be expected because ab initio calculations predict the valence and conduction band of several ferromagnetic van der Waals semiconductors to be fully spin polarized15,23–26, implying a very strong coupling between the magnetic state and other electronic properties. Here we investigate experimentally these issues by performing transport and optical measurements on nano-fabricated devices based on exfoliated $\\mathrm{CrI}_{3}$ crystals. In all devices investigated we find a very large tunneling magnetoresistance—as large as $10{,}000\\%$ —originating from abrupt transitions between different magnetic states of $\\mathrm{CrI}_{3}$ that shows directly how the transport and magnetic properties are strongly coupled. \n\n# Results \n\nSemiconducting characteristics of $\\mathbf{CrI}_{3}$ devices. Past studies5,6,10 have shown that $\\mathrm{CrI}_{3}$ exhibits a transition to an anisotropic ferromagnetic state with easy axis perpendicular to the layers (Curie temperature $T_{\\mathrm{c}}=61\\mathrm{\\:K},$ , accompanied by a singular behavior of the magnetic susceptibility below $T\\sim50\\mathrm{K}$ suggestive of a transition to a more complex magnetic state that remains to be understood (Supplementary Note 2). In contrast to the magnetic properties, virtually nothing is known about the optoelectronic response of this material and—to start exploring it—we have fabricated and investigated different types of devices (Fig. 1a–d, see Methods section and Supplementary Note 3 for details of the fabrication process). Figure 1a, b shows the schematics and an optical microscope image of a structure with graphene contacts attached to the bottom of an exfoliated $\\mathrm{CrI}_{3}$ crystal, which we realized to implement a field-effect transistor (the doped Si substrate acts as gate). The observed gate and bias dependence of the current are shown in Fig. 1e and its inset: they conform to the expected transistor behavior and indicate that transport in $\\mathrm{CrI}_{3}$ is mediated by electrons in the conduction band (since the transistor turns on at positive gate voltages). Figure 1c, d shows a second type of devices with contacts connected on opposite sides of an exfoliated thin $\\mathrm{CrI}_{3}$ crystal, enabling photocurrent measurements. The photocurrent sets in sharply when the photon energy exceeds $1.2\\mathrm{eV}$ (Fig. 1f), corresponding to the $\\mathrm{CrI}_{3}$ band-gap5,6. This value is consistent with that inferred from the $\\mathrm{CrI}_{3}$ photoluminescence spectrum that peaks at the same energy (see red line in Fig. 1f). Notably, the magnitude of the photocurrent is comparable to that measured on analogous devices based on crystals of more established van der Waals semiconductors, such as $\\mathrm{WS}_{2}^{27}$ or $\\mathrm{WSe}_{2}{}^{28}$ . In contrast to the field-effect transistors, whose resistance was found in all cases to become unmeasurably high below $100\\mathrm{K}.$ the photocurrent in vertical junctions persists down to low temperature. This suggests that the measurement of vertical transport in the direction perpendicular to the layers is possible at low temperature, and may be used to probe phenomena of magnetic origin. \n\n![](images/306204eaf1897dcea80bf88f5332248992fc4034f6e441bd885806b44c0709da.jpg) \nFig. 1 Semiconducting characteristics of $\\mathsf{C r l}_{3}$ . Scheme (a) and false-color optical micrograph (b) of a $\\mathsf{C r l}_{3}$ field-effect transistor realized using few-layer graphene contacts, encapsulated between hexagonal boron nitride (hBN) crystals. The highly doped Silicon substrate covered by a $285\\mathsf{n m}\\mathsf{S i O}_{2}$ layer is used as gate (the scale bar in $\\boldsymbol{\\textbf{b}}$ is $5\\upmu\\mathrm{m}$ long). Scheme $\\mathbf{\\eta}(\\bullet)$ and false-color optical micrograph $({\\pmb d})$ of a heterostructure consisting of bottom and top multilayer graphene contacts attached to an exfoliated $\\mathsf{C r l}_{3}$ crystal $\\mathord{\\sim}7\\mathsf{n m}$ thick (the entire structure is encapsulated between hBN crystals; the scale bar in d is $5\\upmu\\mathrm{m}$ long). e Transfer characteristics of the field-effect transistor shown in b measured at room temperature with $V_{\\mathsf{D S}}=3\\mathsf{V}$ applied between the two multilayer graphene contacts. The transistor turns on for positive gate voltage indicating electron conduction. The inset shows the source-drain current flowing between the graphene contacts as a function of $V_{\\mathsf{D S}},$ for three values of gate voltage $(V_{\\mathsf{G}}=-70\\mathsf{V},0\\mathsf{V},$ and $+70\\vee$ ). f Dependence of the zero-bias photocurrent (black solid line) and photoluminescence (PL) intensity (red solid line) on the photon excitation energy (data taken at ${\\boldsymbol{T}}=4{\\sf K},$ on a device analogous to that shown in $\\blacktriangleleft$ with $\\mathsf{C r l}_{3}$ of $\\mathord{\\sim}10\\mathsf{n m}$ thick) \n\n![](images/a981d78a933f22fc111907a738f3586ee6d8314bdd4fbc1d05d7aacc0aac60ad.jpg) \nFig. 2 Electron tunneling in few-layer $\\mathsf{C r l}_{3}$ vertical junctions. a Current measured on the device shown in Fig. 1d as a function of bias applied between the graphene contacts for $\\tau$ ranging from 0.25 to $70\\mathsf{K}$ (the intermediate temperatures are 10, 20, 30, 40, 50, and $60\\mathsf{K})$ . Below $\\scriptstyle{\\overline{{I}}}=$ $20\\mathsf{K},$ the $1-V$ curves become temperature independent as shown in the inset, indicating that transport is determined by tunneling (the overlapping area of the graphene contacts is $4\\upmu\\mathrm{m}^{2}$ and the thickness of the $\\mathsf{C r l}_{3}$ layer is ${\\sim}7\\mathsf{n m}.$ ). b Arrhenius plot of the resistance measured at different bias voltages (0.35, 0.5, and 0.7 V). c In the tunneling regime (i.e., for $T<201<)$ , $\\mathsf{I n}(I/V^{2})$ is linearly proportional to $1/V,$ as expected for Fowler-Nordheim tunneling (charge carriers tunnel into the conduction band through bandgap of $\\mathsf{C r l}_{3}$ that is tilted by the applied bias forming a triangular barrier, as illustrated schematically in the inset). The different curves correspond to measurements performed at the same temperatures as in a \n\nTunneling transport in vertical junctions. We investigated vertical transport from room temperature down to $T=0.25{\\mathrm{~\\AA~}}$ , by measuring the $I{-}V$ curves of devices such as the one in Fig. 1d. Representative data from one of these devices (Fig. 2a, thickness of $\\mathrm{CrI}_{3}$ is ${\\sim}7\\mathrm{nm}$ , corresponding to ${\\sim}10$ monolayers) show strongly nonlinear $I{-}V$ curves that are temperature independent for $T<20\\mathrm{K},$ whereas for larger $T$ the current $I$ at any given bias $V$ increases with increasing temperature. The temperature evolution of the resistance $R\\ (=V/I)$ measured at three different biases 1 $V{=}0.35\\:\\mathrm{V}$ , $0.5\\mathrm{V}$ , and $0.7\\mathrm{V}$ ) is summarized in Fig. 2b: starting from room temperature, the resistance first increases in a thermally activated way down to $T\\sim70\\mathrm{K}$ (the typical value of activation energy found in different devices is $E_{\\mathrm{a}}\\sim0.15\\mathrm{eV})$ , where it starts to level off, and eventually saturates becoming temperature independent for $T<20~\\mathrm{K}$ . \n\nThe observed temperature independence indicates that for $T<$ $20\\mathrm{K}$ vertical transport is due to tunneling. Indeed, Fig. 2c shows that, for $T<20\\mathrm{K},$ $\\mathrm{{{in}}}(I/V^{2})$ scales proportionally to $1/V,$ the trend expected in the Fowler-Nordheim (FN) tunneling regime29,30. This regime occurs when the electric field generated by the applied voltage tilts the bands in the semiconductor, allowing carriers to tunnel from the electrode into the material31 (see the inset of Fig. 2c). Increasing the electric field effectively decreases the barrier thickness and causes an exponential increase of current. Theory predicts: \n\n$$\n\\ln\\frac{I}{V^{2}}\\sim-\\frac{8\\pi\\sqrt{2m*}\\phi_{B}^{3/2}d}{3\\mathrm{hq}V},\n$$ \n\nwhere $h$ is Planck’s constant, $q$ the electron charge, $d$ the barrier thickness, $m^{*}$ the effective mass and $\\phi_{\\mathrm{B}}$ the barrier height determined by the distance between the Fermi energy in the contact and the edge of the conduction band in $\\mathrm{CrI}_{3}$ (the transistor measurements in Fig. 1e imply that electrons—and not holes—are responsible for the vertical tunneling current). If the effective mass is taken to be equal to the free electron mass—a plausible assumption in view of the rather narrow bands of $\\dot{\\mathrm{CrI}}_{3}{}^{10,23,24}$ —we find that the barrier height is $0.25\\mathrm{eV}$ , roughly comparable to the activation energy extracted from the measured temperature dependence of the resistance. \n\nLarge tunneling magnetoresistance in vertical junctions. Having established the mechanism of vertical transport and seen that measurements can be done well below the Curie temperature, we look at the effect of an applied magnetic field. The magnetoresistance measured at different temperatures between 10 and $65\\mathrm{K}$ with the magnetic field applied perpendicular to the plane of $\\mathrm{CrI}_{3}$ is shown in Fig. 3a–f (extra data are discussed in Supplementary Notes 4 and 5). Extremely large jumps are observed at low temperature, resulting in a total magnitude change up to $10,000\\%$ as $\\mathbf{B}$ is increased from 0 to just above $2\\mathrm{T}$ (Fig. 3a). The jumps pointed by the vertical arrows (J1, J2, and J3) are seen in all four measured devices. Jumps J2 and J3 occur at the same values of B irrespective of the $\\mathrm{CrI}_{3}$ thickness, which in our experiments ranged from 5.5 to $14\\mathrm{nm}$ (additional fine structure in the data depend on the specific device measured). Such a large magnetoresistance is striking as it is not commonly observed for electrons tunneling through non-magnetic materials. The sharp and well-defined values of applied magnetic field at which the resistance jumps are seen strongly suggest that the phenomenon originates from changes in the magnetic state of the $\\mathrm{CrI}_{3}$ layers. \n\nMagnetic states of $\\mathbf{CrI}_{3}$ and tunneling magnetoresistance. Identifying the nature of the magnetic states responsible for the tunneling magnetoresistance, and checking consistency with the known magnetic properties of bulk $\\mathrm{CrI}_{3}$ is subtle. We start addressing these issues by investigating how the magnetoresistance depends on temperature. Upon increasing $T,$ the resistance jumps shift position (compare Fig. 3a, c), with J2 and J3 becoming less sharp (Fig. 3d), and all features eventually disappear around $50\\mathrm{K},$ well below the Curie temperature of $\\mathrm{CrI}_{3}$ ( $\\bar{T}_{\\mathrm{c}}=61\\mathrm{K})$ at which the magnetization of the material appears. More detailed information is obtained by looking at the dependence of the magnetoresistance on both temperature and magnetic field. The color plot in Fig. 4a clearly shows that the resistance jumps define three states (that we label as I, II, and III). For $T$ lower than ${\\sim}40\\mathrm{K}$ the states are separated by clear boundaries in the B- $T$ plane, and well-defined transitions are seen irrespective of whether the boundary is crossed by varying $\\mathbf{B}$ at fixed $T$ or by changing $T$ at fixed B (as shown in Fig. 4b), as expected for veritable phase transitions. This confirms that different magnetic states in $\\mathrm{CrI}_{3}$ are responsible for the observed magnetoresistance. \n\n![](images/4dca00dbf1ff5235efc7ba9f744c523fafe3f6c08d317480ba43a74d731f203c.jpg) \nFig. 3 Large tunneling magnetoresistance in vertical junctions. a–f Tunneling resistance (left axis) and resistance ratio $R(B)/R(2\\top)$ (right axis) of the device shown in Fig. 1d, measured at the temperature indicated in each panel (with $V=0.5\\:\\mathrm{V}$ and B applied perpendicular to the $\\mathsf{C r l}_{3}$ layers). The red and black dots correspond to data measured upon sweeping the field in opposite directions as indicated by the horizontal arrows of the corresponding color. The resistance ratio increases upon lowering temperature and reaches $8,000\\%$ at $10\\mathsf{K}.$ The arrows of different color point to the magnetoresistance jumps that are seen in all devices, irrespective of the thickness of the $\\mathsf{C r l}_{3}$ crystal. Jump J1 is always accompanied by hysteresis; at low temperature, jumps J2 and J3 occur in all devices at the same value of the applied magnetic field, irrespective of sweeping direction. All jumps shift to lower field values upon increasing temperature, and disappear above $50\\mathsf{K}$ \n\n![](images/69b31e468730dcdad5bf5056bc4f9910e0b28cc7be3b07e722b9b943756654dc.jpg) \nFig. 4 Temperature and magnetic field evolution of magnetic states in $\\mathsf{C r l}_{3}$ . a Color plot of the resistance of the device shown in Fig. 1d (in logarithmic scale), as a function of B and T. At low temperature, three clear plateaus signal the presence of different magnetic states (labeled I, II, III). The white triangles and red circles, obtained from the position of the resistance jumps as described in the text, outline the boundaries of these states, and show that the magnetoresistance features appear at $T\\cong51\\mathsf{K}$ (i.e., in correspondence of the anomaly seen in the low-field magnetization; Supplementary Fig. 1c-d). b T-dependence of the resistance (in logarithmic scale) at different fixed values of B: three different values are attained at low-temperature, corresponding to the different magnetic states of $\\mathsf{C r l}_{3}$ . c $\\tau$ -dependence of the resistance measured at $\\pmb{8}=0\\tau$ . The kink at $T\\cong51\\ K$ originates from the evolution of the boundaries between II and III; the ferromagnetic transition manifests itself as a kink around $61\\mathsf{K}.$ d Temperature dependence of the position of jump J1 (clearly seen in Fig. 3 in linear scale; the logarithmic scale in Fig. 4a makes jump J1 difficult to discern). The blue and red symbols—measured 8 months after each other—demonstrate the excellent reproducibility and stability of encapsulated $\\mathsf{C r l}_{3}$ devices \n\nDetermining the precise onset temperature for the occurrence of tunneling magnetoresistance is also instructive. For $T{>}40\\mathrm{K}$ the jumps are rounded into kinks whose position can be determined as shown in Fig. 4c. By following their evolution in the $B.$ - and $T$ -plane we find that jump J3 (see the red circles in Fig. 4a) and J1 (see Fig. 4d, the feature associated to the small field hysteretic behavior visible in Fig. 3) start at the same temperature, $T\\cong51\\mathrm{K}$ (rounding prevents the precise evolution of jump J2 to be followed above $40\\mathrm{K}$ ). Notably, 51 K corresponds exactly to the temperature of the singular behavior observed in the magnetic susceptibility of bulk crystals (Supplementary Fig. 1), indicative of a transition to a complex magnetic state different from a simple ferromagnet. This quantitative agreement therefore suggests that one of the states responsible for the large tunneling magnetoresistance observed in the experiments is the same state that manifests itself in the magnetic properties of bulk $\\mathrm{CrI}_{3}$ . The relation between the properties of bulk crystals and magnetoresistance is however more complex, as shown by magneto-optical Kerr effect (MOKE) measurements. \n\n![](images/36d54cffaa711cf82b2876a4761ce9721c67bbf01dcf90a07ba164caf4f28a85.jpg) \nFig. 5 Magneto-optical Kerr effect in few-layer $\\mathsf{C r l}_{3}$ . a Comparison between the Kerr angle (solid lines, left axis) and the magnetoresistance (dashed lines; data plotted as resistance ratio $R(B)/R(2\\top).$ , right axis) measured on a same device at $5{\\sf K}.$ Kerr angle is measured in Faraday geometry with magnetic field applied perpendicular to the plane of $\\mathsf{C r l}_{3}$ . Black and red curves correspond to sweeping the magnetic field in the direction pointed by the arrows of the corresponding color. The Kerr angle exhibits jumps at magnetic field values that coincide perfectly with the jumps observed in the magnetoresistance. b, c Kerr angle measured at $20\\mathsf{K}$ and $40\\mathsf{K},$ respectively, as a function of magnetic field. The evolution with temperature is virtually identical to that observed for the magnetoresistance (Fig. 3), with features shifting to lower fields and becoming broader as temperature is increased \n\nMOKE measurements exhibit a behavior analogous to that observed in transport, with sharp jumps in Kerr angle that are seen upon the application of a magnetic field perpendicular to the plane of $\\mathrm{CrI}_{3}$ layers (Faraday geometry;32 see Fig. 5a). The jumps occur precisely at the same B-values at which the J2 and J3 magnetoresistance jumps are found. At $T=5\\mathrm{K}$ a well-developed hysteresis in the magnetoresistance measurements is observed upon sweeping $\\mathbf{B}$ up and down, and the same hysteresis is seen in the measurements of Kerr angle. The evolution of the B-dependence of the Kerr angle upon increasing $T$ (Fig. 5b, c) also resembles what is observed in the magnetoresistance, with the jumps in the two quantities shifting and smearing in a very similar way. All the trends that we observed are qualitatively identical to the one reported earlier in atomically thin layers17, which—after submission of this manuscript—have also been reported to exhibit a tunneling magnetoresistance virtually identical to the one reported here33,34. \n\nIn thin atomic layers, MOKE measurements have been interpreted in terms of individual crystalline planes of $\\mathrm{CrI}_{3}$ antiferromagnetically coupled at $\\mathbf{B}=0$ , switching to a ferromagnetic ordering upon application of an external magnetic field. Switching from antiferro- to ferromagnetic coupling may account for the occurrence of sharp jumps in the tunneling magnetoresistance, but is at odds with bulk magnetic properties. Indeed, if transitions from antiferromagnetic to ferromagnetic ordering of $\\mathrm{CrI}_{3}$ layers would occur in crystals of all thicknesses, very large jumps should be observed in the bulk magnetization. Direct measurements (Supplementary Fig. 1) however show a near complete saturation of bulk magnetization occurring already at B $\\sim0.\\bar{3}\\mathrm{T}$ , and no change at $\\mathbf{B}\\sim0.9\\mathrm{T}$ and ${\\sim}1.8\\mathrm{T}$ in correspondence of the magnetoresistance jumps. \n\nWe conclude that the comparison of different experiments ( $\\`T-$ and B-dependence of the resistance, magnetic susceptibility, MOKE) indicate that the tunneling magnetoresistance originates from transitions in the magnetic state of $\\mathrm{CrI}_{3}$ . As for the details of the magnetic states involved, however, no simple interpretation straightforwardly reconciles all observations made on both bulk crystals and thin exfoliated layers. More work is needed to clarify this issue and two potentially important points are worth mentioning. One is that the evidence for the possible antiferromagnetic coupling proposed for exfoliated layers is inferred from the MOKE measurements, under the assumption of a direct relation between Kerr angle and total magnetization. However, it is known that in semiconducting systems a finite Kerr effect can be observed in the absence of a net magnetization as long as time reversal and inversion symmetry are broken35,36. Hence, transitions in the magnetic state without any change in magnetization (see illustrative examples in Supplementary Fig. 8 and discussion in Supplementary Note 6) could—at least in principle—cause jumps in Kerr rotation. This implies that to establish conclusively that an antiferromagnetic coupling is present it is very important to measure the magnetization of atomically thin $\\mathrm{CrI}_{3}$ layers directly without simply relying on MOKE. \n\nA second point to be made is that the jumps observed in MOKE and magnetoresistance could indeed originate from an antiferromagnetic coupling of adjacent $\\mathrm{CrI}_{3}$ layers, but that interlayer antiferromagnetism only occurs in an interfacial region close to the crystal surface. If sufficiently thin, such an interfacial region would not be detected in bulk magnetization measurements, explaining why no magnetization jump is observed at $0.9\\mathrm{T}$ and $\\bar{1.8\\mathrm{T}}$ . Our observations that magnetoresistance occurs always at the same magnetic field values irrespective of applied bias, polarity, and thickness of the $\\mathrm{CrI}_{3}$ flake up to 20 monolayers indicate that if an interfacial region is invoked, this region is rather thick. We estimate that crystals between 10 and 20 monolayers thick are still fully antiferromagnetically coupled, and understanding why such thick crystals exhibit a behavior that is very different from the one observed in the bulk is not obvious. One possibility is that the crystal structure of exfoliated layers in the surface region is different from that of bulk crystals. Interestingly, ab initio calculations show that if individual layers are stacked according to the high-temperature crystalline phase of $\\mathrm{CrI}_{3}$ , an antiferromagnetic interlayer coupling is energetically favorable as compared to the ferromagnetic coupling found in the low-temperature crystalline structure (see Supplementary Fig. 9 and discussion in Supplementary Note 7). \n\n![](images/690376715bf9688f058558b6f85a1dc5f65b2db2dec452eb30d8edd299737485.jpg) \nFig. 6 Coupling between magnetic state and tunneling resistance of $\\mathsf{C r l}_{3}$ a, Plot of $\\mathsf{I n}(I/V^{2})$ as a function of $1/V$ for B ranging between 0 and 3 T showing a nearly linear behavior with a B-dependent slope $\\cdot T=10\\mathsf{K})$ . All data collapse on three different curves. b Magnetic field dependence of the barrier height extracted from the slopes of the curves in a, using Eq. (1) \n\nCoupling between magnetic state and tunneling resistance. Irrespective of the microscopic details of the underlying magnetic structure, finding that a step-like large modulation in the tunneling resistance of a magnetic insulator can be induced by a change in its magnetic state is a physical phenomenon that has not been reported earlier. It is therefore useful to look in detail at the $I{-}V$ curves of our devices to see whether the experiments provide any indication as to the microscopic mechanism responsible for the change in tunneling resistance in the different magnetic states. This is done in Fig. 6a where $\\ln(I/V^{2})$ is plotted versus $1/V$ for many different values of magnetic field. It is apparent that for different magnetic field intervals $\\operatorname{I}\\colon0{-}0.9\\operatorname{T}$ ; II: $1{-}1.8\\mathrm{T}$ ; III: 1.9–3 T) the $I{-}V$ curves collapse on top of each other. In all cases the overall behavior is consistent with that expected from FN tunneling, but with a constant of proportionality between $\\ln(I/V^{2})$ and $1/V$ (i.e., the slope of the three dashed lines in Fig. 6a) that is different in the three cases. \n\nMicroscopically, the constant of proportionality between $\\ln(I/$ $V^{2}$ ) and $1/\\Bar{V}$ is determined by the transmission probability, i.e., to the extinction of the electron wavefunction tunneling through the $\\mathrm{CrI}_{3}$ barrier. Within the simplest model of a uniform (i.e. layer independent) gap of $\\operatorname{CrI}_{3}$ , this quantity is determined by the electron effective mass and by the height of the tunnel barrier (Eq. (1)). Using Eq. (1) under the assumption that the effective mass remains unchanged, we can extract the height of the tunnel barrier from the slope of the $\\ln(I/V^{2})$ versus $1/V$ relation. We find that—as shown in Fig. 6b—the barrier height is different in different magnetic states. The effect can be due to either a change in the band-gap or in the work-function of $\\mathrm{CrI}_{3}$ , consistently with ab initio calculations which shows that the occurrence of magnetism is accompanied by a modification in the material band structure10,23,24. \n\nA similar conclusion—namely that different magnetic states have different transmission probability because of a difference in tunnel barrier height—holds true even if the change in tunneling magnetoresistance is due to a switch from an antiferromagnetic to a ferromagnetic interlayer ordering of the magnetization. The simplest model to describe this scenario consists in assuming that each layer has different barrier height for spin up and down37,38 (i.e., the height of the tunnel barrier is not spatially uniform). Calculations based on this model lead to $I{-}V$ curves that also approximately satisfy Fowler-Nordheim behavior, with proportionality constant between $\\ln(I/V^{2})$ versus $1/V$ that is different for a ferromagnetic or antiferromagnetic alignment of the magnetization in the individual $\\mathrm{CrI}_{3}$ layers (Supplementary Fig. 10). This behavior is easy to understand qualitatively, because—despite not being spatially uniform—the average height of the tunnel barrier for the tunneling process that gives the dominant contribution to the current also depends on the magnetic state. Specifically, for ferromagnetic alignment, tunneling is dominated by the majority spin and the barrier height is the same—the smallest possible—in all layers. For antiferromagnetic coupling, electrons experience a barrier height that is alternating (depending on the layer) between the value expected for majority and minority spins, larger on average that the height experienced by the majority spins in the case of ferromagnetic alignment. These considerations imply that—at least at the simplest level—the analysis of the FN tunneling regime in the measured $I{-}V$ curves cannot discriminate between different magnetic states. Nevertheless, they also do indicate that the magnetic state is coupled to the band structure, which is why the height of the tunnel barrier depends on the specific magnetic state. \n\n# Discussion \n\nThe observation that the tunneling conductance through a $\\mathrm{CrI}_{3}$ barrier depends strongly on the magnetic state of the material—a phenomenon that had not be observed previously in other systems—showcases the richness of physical phenomena hosted by van der Waals semiconductors. So far, these materials have attracted attention mainly for their opto-electronic and transport properties, but it is becoming apparent that their magnetoelectronic response also exhibits fascinating and possibly unique properties. Inasmuch as $\\mathrm{CrI}_{3}$ is concerned, future experiments should identify which other electronic phenomena, besides the tunneling conductance, are strongly affected by the magnetic state of the material. They should also aim at improving the quality of field-effect transistors (whose operation for $\\mathrm{CrI}_{3}$ has been demonstrated here) to enable the investigation of gate-controlled transport at low temperature, in the magnetic state of the material. Obviously, however, experiments should be performed on a broader class of van der Waals magnetic systems, starting with those for which past measurements of the bulk magnetic response indicate the occurrence of transitions between states that can be controlled by the application of an experimentally reachable magnetic field. \n\nAfter the submission of our manuscript different preprints have appeared on the cond-mat archive reporting observations closely related to the ones discussed here (refs. 33,34,39). \n\n# Methods \n\nCrystal growth. High-quality crystals of $\\mathrm{CrI}_{3}$ have been grown by the chemical vapor transport method in a horizontal gradient tubular furnace. To avoid degradation of the precursors and synthesized crystals the 1:3 mixture of Cr and I was sealed in a quartz tube (later placed in the furnace) under inert conditions (Supplementary Note 1). \n\nSample fabrication. Multilayer graphene, h-BN $\\mathrm{10-30~nm},$ ) and few-layer $\\mathrm{CrI}_{3}$ flakes were exfoliated in a nitrogen gas filled glove box with $\\mathtt{a}<0.5$ ppm concentration of oxygen and water to avoid degradation of the few-layer $\\mathrm{CrI}_{3}$ crystals, which are very sensitive to ambient conditions (Supplementary Note 3). The heterostructures were then assembled in the same glove box with a conventional pick-up and release technique based on either PPC/PDMS or PC/PDMS polymer stacks placed on glass slides. Once encapsulated, the multilayer graphene electrodes were contacted electrically by etching the heterostructures by means of reactive ion etching (in a plasma of a $\\mathrm{CF_{4}/O_{2}}$ mixture) followed by evaporation of a $10\\mathrm{nm}/$ $50\\mathrm{nm}\\mathrm{Cr/Au}$ thin film. \n\nTransport measurements. Transport measurements were performed either in a Heliox $^3\\mathrm{He}$ insert system (Oxford Instruments, base temperature of $0.25\\mathrm{K},$ ) equipped with a $14\\mathrm{T}$ superconducting magnet, or in the variable temperature insert of a cryofree Teslatron cryostat (Oxford Instruments, base temperature of $1.5\\mathrm{K})$ ) equipped with a $12\\mathrm{T}$ superconducting magnet. The latter system is also equipped with a sample rotator making it possible to align the sample so that the magnetic field is either parallel or perpendicular to the $\\mathrm{CrI}_{3}$ layers. The $I{-}V$ curves and magnetoresistance were measured with a Keithley 2400 source/measure unit and/or home-made low-noise voltage sources and current amplifiers. \n\nOptical measurements and MOKE. Photoluminescence measurements were performed in a home tailored confocal micro-photoluminescence setup in backscattering geometry (i.e., collecting the emitted light with the same microscope used to couple the laser beam onto the device). The light collected from the sample was sent to a Czerny–Turner monochromator and detected with a liquid nitrogen cooled Si CCD-array (Andor emCCD). The sample was illuminated with the $647.1\\mathrm{nm}$ laser line of an Ar–Kr laser at a power of $30\\upmu\\mathrm{W}$ . The data were corrected to account for the nonlinear CCD response in this spectral region. The same setup was used for the photocurrent measurement but in this case the devices were illuminated using a Fianium supercontinuum laser coupled to a monochromator, providing a beam of tunable wavelength with spectral width of $2\\mathrm{nm}$ and stabilized power. \n\nThe magneto-optical Kerr effect (MOKE) measurements were performed in a cryostat with a $12\\mathrm{T}$ superconducting split-coil magnet. The sample was illuminated with linear polarized light at $632.8\\mathrm{nm}$ and $50\\upmu\\mathrm{W}$ provided by a power stabilized HeNe laser. The reflected beam was split using a polarizing beam splitter cube and the s- and $\\mathtt{p}$ -components measured simultaneously with Si-photodiodes and lock-in detection. A linear contribution to the measured Kerr angle, which stems from Faraday rotation in the cold objective lens, has been measured independently and was subtracted from the data in order to obtain the traces shown in Fig. 4. \n\nData availability. All relevant data are available from the corresponding authors on request. \n\nReceived: 24 January 2018 Accepted: 5 June 2018 \nPublished online: 28 June 2018 \n\n# References \n\n1. Castro Neto, A. H., Guinea, F., Peres, N. M. R., Novoselov, K. S. & Geim, A. K. The electronic properties of graphene. Rev. Mod. Phys. 81, 109–162 (2009). \n\n2. Wang, Q. H., Kalantar-Zadeh, K., Kis, A., Coleman, J. N. & Strano, M. S. Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. Nat. Nanotech. 7, 699–712 (2012). \n3. Xu, X., Yao, W., Xiao, D. & Heinz, T. F. Spin and pseudospins in layered transition metal dichalcogenides. Nat. Phys. 10, 343–350 (2014). \n4 Novoselov, K. S., & Mishchenko, A. & Carvalho, A. & Castro Neto, A. H. 2D materials and van der Waals heterostructures. Science 353, aac9439 (2016). \n5. Dillon, J. F. & Olson, C. E. Magnetization resonance and optical properties of ferromagnet $\\mathrm{CrI}_{3}$ . J. Appl. Phys. 36, 1259–1260 (1965). \n6. Dillon, J. F., Kamimura, H. & Remeika, J. P. Magneto-optical properties of ferromagnetic chromium trihalides. J. Phys. Chem. Solids 27, 1531–1549 (1966). \n7. Carteaux, V., Moussa, F. & Spiesser, M. 2D ising-like ferromagnetic behavior for the lamellar $\\mathrm{Cr}_{2}\\mathrm{Si}_{2}\\mathrm{Te}_{6}$ compound: a neutron-scattering investigation. Europhys. Lett. 29, 251–256 (1995). \n8. Li, X., Cao, T., Niu, Q., Shi, J. R. & Feng, J. Coupling the valley degree of freedom to antiferromagnetic order. Proc. Natl Acad. Sci. USA 110, 3738–3742 (2013). \n9. Sachs, B., Wehling, T. O., Novoselov, K. S., Lichtenstein, A. I. & Katsnelson, M. I. Ferromagnetic two-dimensional crystals: single layers of $\\mathrm{K_{2}C u F_{4}}$ Phys. Rev. B 88, 201402 (2013). \n10. McGuire, M. A., Dixit, H., Cooper, V. R. & Sales, B. C. Coupling of crystal structure and magnetism in the layered, ferromagnetic insulator $\\mathrm{CrI}_{3}$ . Chem. Mater. 27, 612–620 (2015). \n11. Sivadas, N., Daniels, M. W., Swendsen, R. H., Okamoto, S. & Xiao, D. Magnetic ground state of semiconducting transition-metal trichalcogenide monolayers. Phys. Rev. B 91, 235425 (2015). \n12. Du, K.-Z. et al. Weak van der Waals stacking, wide-range band gap, and raman study on ultrathin layers of metal phosphorus trichalcogenides. ACS Nano 10, 1738–1743 (2016). \n13. May, A. F., Calder, S., Cantoni, C., Cao, H. B. & McGuire, M. A. Magnetic structure and phase stability of the van der Waals bonded ferromagnet $\\mathrm{Fe}_{3\\mathrm{-x}}\\mathrm{Ge}\\mathrm{Te}_{2}$ . Phys. Rev. B 93, 014411 (2016). \n14. Lee, S., Choi, K. Y., Lee, S., Park, B. H. & Park, J. G. Tunneling transport of mono- and few-layers magnetic van der Waals $\\ensuremath{\\mathrm{MnPS}}_{3}$ . Apl. Mater. 4, 086108 (2016). \n15. Lin, M. W. et al. Ultrathin nanosheets of $\\mathrm{CrSiTe}_{3}$ : a semiconducting twodimensional ferromagnetic material. J. Mater. Chem. C 4, 315–322 (2016). \n16. Gong, C. et al. Discovery of intrinsic ferromagnetism in two-dimensional van der Waals crystals. Nature 546, 265–269 (2017). \n17. Huang, B. et al. Layer-dependent ferromagnetism in a van der Waals crystal down to the monolayer limit. Nature 546, 270–273 (2017). \n18. Zhong, D. et al. Van der Waals engineering of ferromagnetic semiconductor heterostructures for spin and valleytronics. Sci. Adv. 3, e1603113 (2017). \n19. Xing, W. et al. Electric field effect in multilayer $\\mathrm{Cr}_{2}\\mathrm{Ge}_{2}\\mathrm{Te}_{6}{\\mathrm{:}}$ a ferromagnetic 2D material. 2D Mater. 4, 024009 (2017). \n20. Furdyna, J. K. Diluted magnetic semiconductors. J. Appl. Phys. 64, R29–R64 (1988). \n21. MacDonald, A. H., Schiffer, P. & Samarth, N. Ferromagnetic semiconductors: moving beyond $(\\mathrm{Ga},\\mathrm{Mn})\\mathrm{A}s$ . Nat. Mater. 4, 195 (2005). \n22. Dietl, T. & Ohno, H. Dilute ferromagnetic semiconductors: physics and spintronic structures. Rev. Mod. Phys. 86, 187–251 (2014). \n23. Wang, H., Eyert, V. & Schwingenschlögl, U. Electronic structure and magnetic ordering of the semiconducting chromium trihalides $\\mathrm{CrCl}_{3}$ , $\\mathrm{CrBr}_{3},$ and $\\mathrm{CrI}_{3}$ . J. Phys. Condens. Matter 23, 116003 (2011). \n24. Liu, J. Y., Sun, Q., Kawazoe, Y. & Jena, P. Exfoliating biocompatible ferromagnetic Cr-trihalide monolayers. Phys. Chem. Chem. Phys. 18, 8777–8784 (2016). \n25. Zhang, W. B., Qu, Q., Zhua, P. & Lam, C. H. Robust intrinsic ferromagnetism and half semiconductivity in stable two-dimensional single-layer chromium trihalides. J. Mater. Chem. C 3, 12457–12468 (2015). \n26. Li, X. X. & Yang, J. L. $\\mathrm{CrXTe}_{3}$ $\\mathrm{(X=Si,}$ Ge) nanosheets: two dimensional intrinsic ferromagnetic semiconductors. J. Mater. Chem. C 2, 7071–7076 (2014). \n27. Yu, W. J. et al. Highly efficient gate-tunable photocurrent generation in vertical heterostructures of layered materials. Nat. Nanotech. 8, 952 (2013). \n28. Britnell, L. et al. Strong light-matter interactions in heterostructures of atomically thin films. Science 340, 1311–1314 (2013). \n29. Fowler, R. H. & Nordheim, L. Electron emission in intense electric fields. Proc. R. Soc. Lond. A 119, 173–181 (1928). \n30. Lenzlinger, M. & Snow, E. H. Fowler-nordheim tunneling into thermally grown $\\mathrm{SiO}_{2}$ . J. Appl. Phys. 40, 278–283 (1969). \n31. Sze S. M. & Ng, K. K. Physics of Semiconductor Devices, 3rd edn (John Wiley & Sons, Inc., New Jersey, 2007). \n32. Palik, E. D. & Furdyna, J. K. Infrared and microwave magnetoplasma effects in semiconductors. Rep. Prog. Phys. 33, 1193–1322 (1970). \n33. Song, T., et al. Giant tunneling magnetoresistance in spin-filter van der Waals heterostructures. Science 360, 1214–1218 (2018). \n34. Klein, D. R., et al. Probing magnetism in 2D van der Waals crystalline insulators via electron tunneling. Science, 360, 1214–1218 (2018). \n35. Feng, W., Guo, G.-Y., Zhou, J., Yao, Y. & Niu, Q. Large magneto-optical Kerr effect in noncollinear antiferromagnets $\\mathrm{Mn}_{3}\\mathrm{X}$ $\\mathrm{\\ddot{X}=R h}$ , Ir, Pt). Phys. Rev. B 92, 144426 (2015). \n36. Sivadas, N., Okamoto, S. & Xiao, D. Gate-controllable magneto-optic Kerr effect in layered collinear antiferromagnets. Phys. Rev. Lett. 117, 267203 (2016). \n37. Worledge, D. & Geballe, T. Magnetoresistive double spin filter tunnel junction. J. Appl. Phys. 88, 5277–5279 (2000). \n38. Miao, G.-X., Müller, M. & Moodera, J. S. Magnetoresistance in double spin filter tunnel junctions with nonmagnetic electrodes and its unconventional bias dependence. Phys. Rev. Lett. 102, 076601 (2009). \n39. Kim, H. H., et al. One million percent tunnel magnetoresistance in a magnetic van der Waals heterostructure. Preprint at https://arxiv.org/abs/1804.00028 (2018). \n\n# Acknowledgements \n\nWe gratefully acknowledge A. Ferreira for continuous technical support, D.-K. Ki for fruitful discussions, and A. Ubaldini for early work on the growth of $\\mathrm{CrI}_{3}$ crystals. Z.W. thanks C. Handschin for sharing his experience in device fabrication. Z.W., I.G.-L., and A.F.M. gratefully acknowledge financial support from the Swiss National Science Foundation, the NCCR QSIT and the EU Graphene Flagship Project. N.U. and M.G. gratefully acknowledge support through an Ambizione fellowship of the Swiss National Science Foundation. M.K. and A.I. acknowledge NCCR QSIT for financial support. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT, Japan and JSPS KAKENHI Grant Numbers JP15K21722. \n\n# Author contributions \n\nZ.W. fabricated the devices with the collaboration of I.G.-L., Z.W. performed the transport measurements and analyzed the data, N.U. performed photoluminescence and photocurrent measurements. M.K. carried out the optical Kerr measurements with help of N.U.; M.K. and A.I. participated in discussion of the Kerr measurements. E.G. grew and characterized the $\\mathrm{CrI}_{3}$ crystals. M.G. contributed to the discussion of the possible magnetic states of $\\mathrm{CrI}_{3}$ and performed ab initio calculations to identify when the interlayer coupling is antiferromagnetic. T.T. and K.W. provided hBN crystals. A.F.M. initiated and supervised the project. Z.W., I.G.-L., N.U., M.G., and A.F.M. wrote the manuscript with input from all authors. All authors discussed the results. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-04953-8. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2018 " + }, + { + "id": "10.1126_science.aan6003", + "DOI": "10.1126/science.aan6003", + "DOI Link": "http://dx.doi.org/10.1126/science.aan6003", + "Relative Dir Path": "mds/10.1126_science.aan6003", + "Article Title": "Observation of the quantum spin Hall effect up to 100 kelvin in a monolayer crystal", + "Authors": "Wu, SF; Fatemi, V; Gibson, QD; Watanabe, K; Taniguchi, T; Cava, RJ; Jarillo-Herrero, P", + "Source Title": "SCIENCE", + "Abstract": "A variety of monolayer crystals have been proposed to be two-dimensional topological insulators exhibiting the quantum spin Hall effect (QSHE), possibly even at high temperatures. Here we report the observation of the QSHE in monolayer tungsten ditelluride (WTe2) at temperatures up to 100 kelvin. In the short-edge limit, the monolayer exhibits the hallmark transport conductance, similar to e(2)/h per edge, where e is the electron charge and h is Planck's constant. Moreover, a magnetic field suppresses the conductance, and the observed Zeeman-type gap indicates the existence of a Kramers degenerate point and the importance of time-reversal symmetry for protection from elastic backscattering. Our results establish the QSHE at temperatures much higher than in semiconductor heterostructures and allow for exploring topological phases in atomically thin crystals.", + "Times Cited, WoS Core": 667, + "Times Cited, All Databases": 746, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000419324700070", + "Markdown": "# TOPOLOGICAL MATTER \n\n# Observation of the quantum spin Hall effect up to 100 kelvin in a monolayer crystal \n\nSanfeng $\\mathbf{Wu},^{1*}\\dag$ Valla Fatemi,1\\*† Quinn D. Gibson,2 Kenji Watanabe,3 Takashi Taniguchi,3 Robert J. Cava,2 Pablo Jarillo-Herrero1† \n\nA variety of monolayer crystals have been proposed to be two-dimensional topological insulators exhibiting the quantum spin Hall effect (QSHE), possibly even at high temperatures. Here we report the observation of the QSHE in monolayer tungsten ditelluride $(\\mathsf{W T e}_{2})$ at temperatures up to 100 kelvin. In the short-edge limit, the monolayer exhibits the hallmark transport conductance, $\\scriptstyle\\mathtt{\\sim e}^{2}/h$ per edge, where e is the electron charge and $h$ is Planck’s constant. Moreover, a magnetic field suppresses the conductance, and the observed Zeeman-type gap indicates the existence of a Kramers degenerate point and the importance of time-reversal symmetry for protection from elastic backscattering. Our results establish the QSHE at temperatures much higher than in semiconductor heterostructures and allow for exploring topological phases in atomically thin crystals. \n\ntime-reversal (TR) invariant topological insulator (TI) in two dimensions, also known as a quantum spin Hall (QSH) insulator, can be identified by its helical edge modes . (1–4). So far, evidence for the helical edge mode in two-dimensional (2D) TIs, particularly quantized transport, has been limited to very low temperatures (i.e., near liquid helium temperature) in HgTe and InAs/GaSb quantum wells $(5,6)$ . In the search for high-temperature TIs, substantial efforts have focused on a variety of atomically thin materials (7–14), which hold the promise of advancing the field of topological physics using the tools developed for 2D crystals. However, experimental observation of the quantum spin Hall effect (QSHE) in monolayer systems is challenging, often owing to structural or chemical instabilities $(9,15\\mathrm{-}I7)$ . Indications of a hightemperature QSH phase in bulk-attached bismuth bilayers have been reported (7, 18, 19), but a conclusive demonstration is still lacking. \n\nAmong the proposals for atomically thin TIs are monolayer transition metal dichalcogenides (TMDs), materials that are either 2D semiconductors or semimetals depending on their structural phase $(\\boldsymbol{g})$ . Calculations suggest that an inverted band gap can develop in 1T′ TMD monolayers, resulting in a nontrivial $Z_{2}$ topological phase (9, 20). Recent experiments have shown promising results (12–14), including that monolayer $\\mathrm{WTe_{2}}$ exhibits a ground state with an insulating interior and conducting edges associated with a zero-bias anomaly (12), distinct from its multilayer counterparts (12, 21). Here we observe the QSHE in $\\mathrm{WTe_{2}}$ monolayers and identify this 2D material as an atomically layered TI with conductance ${\\sim}e^{2}/h$ per edge at high temperatures, where $e$ is the electron charge and $h$ is Planck’s constant. \n\nQSH transport through a 2D TR-invariant TI should exhibit the following characteristics: (i) helical edge modes, characterized by an edge conductance that is approximately the quantum value of $e^{2}/h$ per edge (5); (ii) saturation to the conductance quantum in the short-edge limit (22); and (iii) suppression of conductance quantization upon application of a magnetic field, owing to the loss of protection by TR symmetry (5, 23, 24). Signatures of a Zeeman gap should be seen if the Kramers degeneracy (Dirac point) is located inside the bulk band gap. To date, simultaneous observation of the above criteria in existing 2D TI systems is still lacking (5, 6, 22, 23, 25), prompting the search for new QSH materials. \n\nTo check the above criteria in monolayer $\\mathrm{WTe_{2}}$ , we fabricated devices with the structure depicted in Fig. 1A [see (26) and figs. S1 and S2]. The goal of the design was threefold: to ensure an atomically flat, chemically protected channel (no flake bending or exposure) by fully encapsulating the flake with hexagonal boron nitride (15, 21); to minimize the effect of contact resistance; and to enable a length-dependence study on a single device. Our devices generally contain eight contact electrodes, a top graphite gate, and a series of in-channel local bottom gates with length $L_{\\mathrm{c}}$ varying from 50 to $900\\mathrm{nm}$ . The monolayer flakes are carefully selected to have a long strip shape, typically a few $\\upmu\\mathrm{m}$ wide and about $10\\upmu\\mathrm{m}$ long (table S1). Figure 1B shows a typical measurement of the four-probe conductance (in device 1) across all the local gates ${\\bf\\langle{\\sim}}8\\upmu\\mathrm{m}$ long) as a function of top-gate voltage, $V_{\\mathrm{tg}}$ . A finite conductance plateau develops around $V_{\\mathrm{tg}}=$ \n\n$0\\mathrm{V}$ . This characteristic feature for monolayer $\\mathrm{WTe_{2}}$ stems from conduction along the edges (12). The measured value is highly sensitive to contact properties (12), which prevents observation of the intrinsic edge conductance. We overcome this obstacle in our devices through selective doping of the flake using a combination of global top and local bottom gates. A short transport channel with length $L_{\\mathrm{c}}$ can be selectively defined by a local gate voltage $V_{\\mathrm{c}},$ whereas the rest of the flake is highly doped by $V_{\\mathrm{tg}}$ to secure good contact to the electrodes (see fig. S3 for $\\mathrm{d}I/\\mathrm{d}V$ characteristics, where $\\mathrm{d}I\\sim$ 1 nA is the applied ac current). Figure 1C maps out the resistance $R$ in the same device as a function of $V_{\\mathrm{tg}}$ and $V_{\\mathrm{c}}$ (for a local gate with $L_{\\mathrm{c}}=\\$ $100~\\mathrm{{nm}}$ ). The step structure indicates a transition from a bulk-metallic state (doped) to a bulkinsulating state (undoped) within the locally gated region. We define the offset resistance, $\\Delta R=R(V_{\\mathrm{c}})-R(V_{\\mathrm{c}}=-1\\mathrm{V})$ , as the resistance change from the value in the highly doped limit $\\mathrm{\\langle{}V_{c}=-I V_{:}}$ , in this case). Figure 1D shows a $\\Delta R$ trace (red curve) extracted from Fig. 1C (dashed white line in Fig. 1C), where $V_{\\mathrm{tg}}$ is fixed at $3.5\\mathrm{V}.$ . The average value of $\\Delta R$ at the plateau, which measures the step height, saturates when $V_{\\mathrm{tg}}$ is high enough (Fig. 1D, inset, and figs. S4 to S7). \n\nThis saturated value, $\\Delta R_{\\mathrm{s}}$ , thus measures the resistance of the undoped channel, which can only originate from the edges because the monolayer interior is insulating (12–14). Notably, $\\Delta R_{\\mathrm{s}}$ is approximately equal to $\\scriptstyle h/2e^{2}$ for both this $\\scriptstyle100-\\mathrm{nm}$ channel and the 60- and $70\\mathrm{-nm}$ channels on device 2 (Fig. 1D). Fluctuations in the range of a few kilohm, which may originate from residual disorder or correlation effects (12, 27, 28), are visible, but decrease substantially above $4\\mathrm{K}$ Given that the sample has two edges, the observed conductance per edge is therefore ${\\sim}e^{2}/h,$ pointing to helical edge modes as the source of the conductance (5, 6). To confirm this scenario, one must rule out the possibility of trivial diffusive edge modes that happen to exhibit the quantized conductance value for some particular length (22). We thus performed a length-dependence study using a series of local gates with different $L_{\\mathrm{c}}.$ Detailed analysis of measurements from representative devices and gates at ${\\sim}4\\mathrm{~K~}$ can be found in figs. S3 to S5. In Fig. 2, we summarize the data by plotting the undoped-channel resistance, $\\Delta R_{\\mathrm{s}},$ as a function of $L_{\\mathrm{c}}$ . For long edges, the resistance generally decreases with decreasing length, which is arguably captured by a linear trend. The behavior, however, clearly deviates from the trend when $L_{\\mathrm{c}}$ is reduced to $\\boldsymbol{100}\\mathrm{nm}$ or less, where the resistance saturates to a value close to $\\scriptstyle h/2e^{2}$ . Such behavior is present in all three devices that enter this short-length regime, independent of the width of the monolayer flake (varying from 1 to $4~{\\upmu\\mathrm{m}}$ ). These observations reveal the intrinsic conductance as $e^{2}/h$ per edge, as per the abovementioned criteria (i) and (ii) for the QSHE. \n\nTo check criterion (iii), regarding TR symmetry protection from elastic scattering, we performed magnetoconductance measurements. The data \n\nFig. 1. Device structure and resistance near $h/2e^{2}$ . (A) Schematic of the device structure. BN, boron nitride. (B) Fourprobe conductance measurement at $4\\mathsf{K}$ of device 1 as a function of $V_{\\mathrm{tg}}$ across all the local gates, which are floating. Inset shows the optical image of device 1 (left) and the corresponding monolayer ${\\sf W T e}_{2}$ flake before fabrication (right). (C) Color map of the flake resistance tuned by $V_{\\mathrm{tg}}$ and the $100\\cdot\\mathsf{n m}$ -wide local gate $V_{\\mathrm{c}}$ at $4~\\mathsf{K}.$ . Two regions are separated by a step in the resistance, which distinguishes the doped and undoped local channels, as depicted by the inset schematics. $\\Omega$ , ohm. (D) DR versus $V_{\\mathrm{c}}$ for the 100-nm-wide gate on device 1 at $V_{\\mathrm{tg}}=3.5$ V [white dashed line in (C)] and the 60- and 70-nmtaken from the 100-nm-long channel in device 1 in the QSHE regime (i.e., gate range of the plateau) are shown in Fig. 3. We define $G_{\\mathrm{s}}$ as $1/\\l$ $\\Delta R_{\\mathrm{s}},$ which measures the conductance of the edges in the short channel limit. $G_{\\mathrm{s}}$ is plotted as a function of $V_{\\mathrm{c}}$ in Fig. 3A for a series of magnetic fields $B$ applied perpendicular to the monolayer at $1.6\\mathrm{K}$ . $G_{\\mathrm{s}}$ decreases substantially once $B$ is turned on, in contrast to the bulk state, which is hardly affected (fig. S8). For all $V_{\\mathrm{c}},G_{\\mathrm{s}}$ decreases rapidly for low magnetic fields $\\cdot B<2$ T). After this initial stage, two types of behavior are observed, depending on $V_{\\mathrm{c}},$ , as shown in Fig. 3B. When $V_{\\mathrm{c}}$ is near $-6.44\\mathrm{V}$ , $G_{\\mathrm{s}}$ decreases exponentially without saturation, up to $8\\mathrm{T}$ . For other values of $V_{\\mathrm{c}},G_{\\mathrm{s}}$ saturates at high $B$ . These behaviors are notably different from the previous observations for resistive channels (12). \n\n![](images/717f4b6d9b6ab577d34d7626bf9376fe81bee100010c83fcb30053a0821e4cfa.jpg) \nwide gates on device 2 at $V_{\\mathrm{tg}}=4.1\\mathrm{V}$ (taken at $5\\mathsf{K})$ . For clarity, the two curves from device 2 are offset by $+3V$ along the $x$ axis. Inset shows the average step height ${<}\\Delta R>$ , extracted from (C), as a function of $V_{\\mathrm{tg}}$ , showing a clear saturation toward $h/2e^{2}$ for large $V_{\\mathrm{tg}}$ . \n\nBoth types of behavior can be understood in the context of the QSHE. The 1D edge state of the QSH phase consists of two species: left and right movers associated with opposite spin polarization. The two linearly dispersing bands cross at the Kramers degeneracy point (Fig. 3B, inset I). Magnetic fields applied nonparallel to the spin polarization are expected to open an energy gap at the Kramers point owing to the Zeeman effect (29). For a homogeneous chemical potential close to the degeneracy point (Fig. 3B, inset II), one would expect an exponential decay of the conductance without saturation. To reveal the existence of the gap, we performed temperaturedependence measurements of the magnetoconductance at $V_{\\mathrm{c}}=-6.44\\:\\mathrm{V}.$ . The exponential decay of $G_{\\mathrm{s}}$ persists up to high temperatures (measured up to $34\\mathrm{\\K},$ inset of Fig. 3C). Moreover, all the curves collapse onto a single universal trend when renormalized by plotting the dimensionless values $-\\mathrm{log}(G_{\\mathrm{s}}/G_{0})$ versus $\\upmu_{\\mathrm{B}}B/k_{\\mathrm{B}}T$ (Fig. 3C), where $G_{0}$ is the zero-field conductance, $\\upmu_{\\mathrm{B}}$ is the Bohr magneton, $k_{\\mathrm{B}}$ is the Boltzmann constant, and $T$ is the temperature. The slope of the trend \n\n![](images/261dc49770e44a45f7d392086491fb74a7a68424f323f19f91195a675aa023db.jpg) \nFig. 2. Length dependence of the undoped-channel resistance. Data taken at $4\\mathsf{K}$ from five different devices (table S1), each denoted by a different color and symbol. The device numbers and associated colors are: 1, black; 2, green; 3, purple; 4, red; and 5, blue. The $\\Delta R_{\\mathrm{s}}$ values approach a minimum of $h/2e^{2}$ in the short-channel limit, confirming a total conductance of $2e^{2}/h$ for the undoped channel, i.e., a conductance of $e^{2}/h$ per edge in the device, in agreement with QSHE. Detailed analysis of raw data can be found in figs. S4 to S7. \n\nFig. 3. Magnetoconductance and Zeeman-like gap at the Dirac point. (A) The evolution of the edge conductance $G_{\\mathrm{s}}$ versus local gate voltage $V_{\\mathrm{c}}$ under the application of a perpendicular magnetic field, B (from 0 T, thick blue curve, to $B\\intercal,$ , thick red curve, in $0.2\\cdot T$ steps) at $1.8~\\mathsf{K}$ , for device 1, $100-\\mathsf{n m}$ channel. (B) Traces of $G_{\\mathrm{s}}$ versus $B$ for a few selected $V_{\\mathrm{c}}$ , showing two types of behavior, saturation and nonsaturation, associated with whether the Fermi energy $(E_{\\mathsf{F}})$ is in the Zeeman gap, as depicted in the band schematics inset I (linear bands at zero $B$ , $E_{\\mathsf{F}}$ at Dirac point), II (gapped bands at finite B, $E_{\\mathsf{F}}$ at Dirac point), and III (gapped bands at finite $B$ , $E_{\\mathsf{F}}$ away from Dirac point). Red and blue spheres illustrate the opposite spin polarization of the edge bands, respectively. Purple areas indicate the filled bands. (C) Inset shows temperature dependence of $G_{\\mathrm{s}}$ versus B for the nonsaturating curves $V_{\\mathrm{c}}=-6.44\\:\\mathrm{V})$ . All the curves in the inset collapse to a single trend in the normalized plot of $-\\log(G_{\\mathrm{s}}/G_{0})$ versus $\\upmu_{\\mathsf{B}}B/k_{\\mathsf{B}}T.$ . The black line is a linear fit. Additional temperature and magnetic field dependence is shown in figs. S9 to S11. \n\n![](images/92e3e42e2adfa14bc6f9bfc9e5699b641cb6a314b8c06818c889c5bf75ac8275.jpg) \nFig. 4. Quantum spin Hall effect up to 100 K. (A) Temperature dependence of the edge conductance at a few representative gate voltages for the $100\\cdot\\mathsf{n m}$ channel in device 1. The conductance is dominated by the QSHE up to about 100 K. The right schematic depicts the onset of bulk-state contribution to the conductance. Inset shows gate dependence of $\\Delta R$ at various temperatures. (B) Temperature dependence of the resistance of the whole flake (full length) when the Fermi energy in the local channel is in the doped $\\cdot V_{\\mathrm{c}}=-1$ V, red) and undoped $(V_{\\mathrm{c}}=-5.7~\\mathrm{V},$ blue) regimes, at $V_{\\mathrm{tg}}=3.5$ V. The difference between the curves yields the temperaturedependent channel resistance $\\Delta R_{\\mathrm{s}}$ (yellow). The vertical dashed line highlights the kink in the undoped regime at $100\\mathsf{K},$ , indicating the transition to the QSHE edge-dominated regime. \n\nyields an effective $\\mathbf{g}$ -factor ${\\sim}4.8$ for the out-ofplane field in this device [i.e., the device conductance obeys $G_{\\mathrm{s}}=G_{0}\\exp(-\\mathrm{g}\\mathrm{\\verta_{B}}B/2k_{\\mathrm{B}}T)]$ . This observation confirms a Zeeman-type gap opening in the edge bands. \n\nIf the Fermi energy at the edge is gated away from the Kramers degeneracy point (Fig. 3B, inset III), the Zeeman gap will not be directly observed, and the magnetoconductance should be determined by the scattering mechanisms at the edge allowed by the TR symmetry breaking. For example, in our devices, the presence of local charge puddles can be natural. According to theoretical calculations, the edge conductance will be reduced to $\\boldsymbol{\\alpha e^{2}/h}$ , where $\\mathfrak{a}$ is a fielddependent coefficient determined by the microscopic details of the edge (24, 30). Calculations show that, at high magnetic fields, an individual puddle can reduce transmission along an edge by $50\\%$ (24, 31), leading to a saturated $\\upalpha$ determined by the distribution of the puddles along the edges. We find the conductance saturation is consistent with this picture (fig. S9). In addition to vertical magnetic fields, we have also found considerably reduced edge conductance when inplane magnetic field is applied (fig. S10). We expect that both in- and out-of-plane magnetic fields will suppress the conductance: TR symmetry removes protection of the edge conduction, and the edge-mode spin-polarization axis is not necessarily normal or parallel to the layer because the monolayer lacks out-of-plane mirror symmetry. The exact spin-polarization axis may be influenced by multiple factors, such as the direction of the crystallographic edge and the existence of displacement electric fields. The irregular edge of the exfoliated monolayer makes the situation more complex. Overall, the magnetoconductance behavior is consistent with criterion (iii). Therefore, the QSHE is indeed observed in monolayer $\\mathrm{WTe_{2}}$ . \n\nNotably, the distinctive zero-field conductance value survives up to high temperatures. Figure 4A plots the temperature dependence of $G_{\\mathrm{s}}$ at different $V_{\\mathrm{c}}$ in the QSHE regime; $G_{\\mathrm{s}}$ stays approximately constant and close to $2e^{2}/h$ up to $100~\\mathrm{K},$ indicating that the conductance is dominated by the QSHE up to this temperature. In terms of $\\Delta R$ , the resistance plateau starts to drop at around $100~\\mathrm{K}$ (Fig. 4A, inset). We note that it is not obvious a priori what the temperature dependence of the QSH edge conductance should be, and some proposed mechanisms indicate weak (32) or even negative temperature dependence (27). Above $100~\\mathrm{K},$ the channel conductance increases rapidly with temperature, indicating the activation of bulk-conduction channels. To reveal the transition more clearly, in Fig. 4B we plot the temperature dependence of the resistance $R$ of the whole flake (i.e., the entire length, which consists of the locally gated region in series with the rest of the flake) when the chemical potential in the local channel is placed in the metallic regime $\\cdot V_{\\mathrm{c}}=-1\\:\\mathrm{V})$ and the QSH regime $\\cdot V_{\\mathrm{c}}<-5.3~\\mathrm{V})$ ). A clear kink at $100~\\mathrm{K}$ can be seen in the QSH regime. The difference between the two curves yields the channel resistance, which drops above the transition temperature. \n\nThis high-temperature QSHE is consistent with the prediction of a large inverted band gap $\\left(\\mathrm{\\sim}\\mathrm{100~meV}\\right)$ in monolayer $\\mathrm{WTe_{2}}$ (20) as well as recent experiments that observe a ${\\sim}45\\mathrm{-meV}$ bulk band gap in spectroscopy (13, 14) and a similar onset temperature for bulk conduction (12). We suspect the $100~\\mathrm{K}$ transition temperature may not be an intrinsic limit. Improvements in device quality may enable observation of the QSHE at even higher temperatures and for longer edges. \n\nOur observations have confirmed the nontrivial TR invariant topological phase in monolayer $\\mathrm{WTe_{2}}$ and demonstrated the QSHE at high temperatures in an isolated 2D monolayer device. The exploration of 2D topological physics and device performance above liquid nitrogen temperatures has therefore become possible. Distinct from quantum well systems, the exposed nature of isolated monolayers may allow for engineering topological phases in unprecedented ways. In particular, $\\mathrm{WTe_{2}}$ can be readily combined with other 2D materials to form van der Waals heterostructures, a promising platform for studying the proximity effect between a QSH system and superconductors or magnets (3, 4) at the atomic scale. \n\n# REFERENCES AND NOTES \n\n1. C. L. Kane, E. J. Mele, Phys. Rev. Lett. 95, 226801 (200 \n2. B. A. Bernevig, S.-C. Zhang, Phys. Rev. Lett. 96, 106802 (2006). \n3. M. Z. Hasan, C. L. Kane, Rev. Mod. Phys. 82, 3045–3067 (2010). \n4. X.-L. Qi, S.-C. Zhang, Rev. Mod. Phys. 83, 1057–1110 (2011). \n5. M. König et al., Science 318, 766–770 (2007). \n6. I. Knez, R.-R. Du, G. Sullivan, Phys. Rev. Lett. 107, 136603 (2011). \n7. S. Murakami, Phys. Rev. Lett. 97, 236805 (2006). \n8. Y. Xu et al., Phys. Rev. Lett. 111, 136804 (2013). \n9. X. Qian, J. Liu, L. Fu, J. Li, Science 346, 1344–1347 (2014). \n10. J.-J. Zhou, W. Feng, C.-C. Liu, S. Guan, Y. Yao, Nano Lett. 14, 4767–4771 (2014). \n11. S. S. Li et al., Sci. Rep. 6, 23242 (2016). \n12. Z. Fei et al., Nat. Phys. 13, 677–682 (2017). \n13. S. Tang et al., Nat. Phys. 13, 683–687 (2017). \n14. Z.-Y. Jia et al., Phys. Rev. B 96, 041108 (2017). \n15. Y. Cao et al., Nano Lett. 15, 4914–4921 (2015). \n16. L. Wang et al., Nat. Commun. 6, 8892 (2015). \n17. F. Ye et al., Small 12, 5802–5808 (2016). \n18. C. Sabater et al., Phys. Rev. Lett. 110, 176802 (2013). \n19. I. K. Drozdov et al., Nat. Phys. 10, 664–669 (2014). \n20. F. Zheng et al., Adv. Mater. 28, 4845–4851 (2016). \n21. V. Fatemi et al., Phys. Rev. B 95, 041410 (2017). \n22. F. Nichele et al., New J. Phys. 18, 083005 (2016). \n23. E. Y. Ma et al., Nat. Commun. 6, 7252 (2015). \n24. S. Essert, K. Richter, 2D Mater 2, 024005 (2015). \n25. L. Du, I. Knez, G. Sullivan, R.-R. Du, Phys. Rev. Lett. 114, 096802 (2015). \n26. See supplementary materials. \n27. J. Maciejko et al., Phys. Rev. Lett. 102, 256803 (2009). \n28. T. Li et al., Phys. Rev. Lett. 115, 136804 (2015). \n29. M. König et al., J. Phys. Soc. Jpn. 77, 031007 (2008). \n30. J. Maciejko, X.-L. Qi, S.-C. Zhang, Phys. Rev. B 82, 155310 (2010). \n31. A. Roth et al., Science 325, 294–297 (2009). \n32. J. I. Väyrynen, M. Goldstein, Y. Gefen, L. I. Glazman, Phys. Rev. B 90, 115309 (2014). \n\n# ACKNOWLEDGMENTS \n\nWe thank L. Fu and X. Qian for helpful discussions. This work was partly supported through Air Force Research Laboratory grant no. FA9550-16-1-0382 as well as the Gordon and Betty Moore Foundation’s Emergent Phenomena in Quantum Systems (EPiQS) Initiative through grant no. GBMF4541 to P.J.-H. Device nanofabrication was partly supported by the Center for Excitonics, an Energy Frontier Research Center funded by the U.S. Department of Energy, Basic Energy Sciences Office, under award no. DE-SC0001088. This work made use of the Materials Research Science and Engineering Center’s shared experimental facilities supported by the NSF under award no. DMR-0819762. Sample fabrication was performed in part at the Harvard Center for Nanoscale Science supported by the NSF under grant no. ECS-0335765. S.W. acknowledges the support of the MIT Pappalardo Fellowship in Physics. The ${\\mathsf{W T e}}_{2}$ crystal growth performed at Princeton University was supported by the NSF Materials Research Science and Engineering Center (MRSEC) grant DMR-1420541. Growth of hexagonal boron nitride crystals was supported by the Elemental Strategy Initiative conducted by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; and the Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI) through grant nos. JP15K21722 and JP25106006. The data presented in this paper are available from the corresponding authors upon reasonable request. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/359/6371/76/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S11 \nTable S1 \nReferences (33, 34) \n7 May 2017; accepted 17 November 2017 \n10.1126/science.aan6003 \n\n# Science \n\n# Observation of the quantum spin Hall effect up to 100 kelvin in a monolayer crystal \n\nSanfeng Wu, Valla Fatemi, Quinn D. Gibson, Kenji Watanabe, Takashi Taniguchi, Robert J. Cava and Pablo Jarillo-Herrero \n\nScience 359 (6371), 76-79. DOI: 10.1126/science.aan6003 \n\n# Heating up the quantum spin Hall effect \n\nTaking practical advantage of the topologically protected conducting edge states of topological insulators (TIs) has proven difficult. Semiconductor systems that have been identified as two-dimensional TIs must be cooled down to near liquid helium temperatures to bring out their topological character. Wu et al. fabricated a heterostructure consisting of a monolayer of WTe 2 placed between two layers of hexagonal boron nitride and found that its topological properties persisted up to a relatively high temperature of $100~\\mathsf{K}$ . Engineering this so-called quantum spin Hall effect in a van der Waals heterostructure makes it possible to apply many established experimental tools and functionalities. \n\nScience, this issue p. 76 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/359/6371/76 \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.aar3617", + "DOI": "10.1126/science.aar3617", + "DOI Link": "http://dx.doi.org/10.1126/science.aar3617", + "Relative Dir Path": "mds/10.1126_science.aar3617", + "Article Title": "Probing magnetism in 2D van der Waals crystalline insulators via electron tunneling", + "Authors": "Klein, DR; MacNeill, D; Lado, JL; Soriano, D; Navarro-Moratalla, E; Watanabe, K; Taniguchi, T; Manni, S; Canfield, P; Fernández-Rossier, J; Jarillo-Herrero, P", + "Source Title": "SCIENCE", + "Abstract": "Magnetic insulators are a key resource for next-generation spintronic and topological devices. The family of layered metal halides promises varied magnetic states, including ultrathin insulating multiferroics, spin liquids, and ferromagnets, but device-oriented characterization methods are needed to unlock their potential. Here, we report tunneling through the layered magnetic insulator CrI3 as a function of temperature and applied magnetic field. We electrically detect the magnetic ground state and interlayer coupling and observe a field-induced metamagnetic transition. Themetamagnetic transition results in magnetoresistances of 95, 300, and 550% for bilayer, trilayer, and tetralayer CrI3 barriers, respectively. We further measure inelastic tunneling spectra for our junctions, unveiling a rich spectrum consistent with collective magnetic excitations (magnons) in CrI3.", + "Times Cited, WoS Core": 732, + "Times Cited, All Databases": 798, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000435360400050", + "Markdown": "# MAGNETISM \n\n# Probing magnetism in 2D van der Waals crystalline insulators via electron tunneling \n\nD. R. $\\mathbf{KIeim^{1*}}$ , D. MacNeill1\\*, J. L. Lado2,3, D. Soriano2, E. Navarro-Moratalla4, \nK. Watanabe5, T. Taniguchi5, S. Manni6,7,8, P. Canfield6,7, \nJ. Fernández-Rossier2, P. Jarillo-Herrero1† \n\nMagnetic insulators are a key resource for next-generation spintronic and topological devices. The family of layered metal halides promises varied magnetic states, including ultrathin insulating multiferroics, spin liquids, and ferromagnets, but device-oriented characterization methods are needed to unlock their potential. Here, we report tunneling through the layered magnetic insulator $\\mathsf{c r l}_{3}$ as a function of temperature and applied magnetic field. We electrically detect the magnetic ground state and interlayer coupling and observe a fieldinduced metamagnetic transition.The metamagnetic transition results in magnetoresistances of 95, 300, and $550\\%$ for bilayer, trilayer, and tetralayer $\\mathsf{c r l}_{3}$ barriers, respectively. We further measure inelastic tunneling spectra for our junctions, unveiling a rich spectrum consistent with collective magnetic excitations (magnons) in $\\mathsf{c r l}_{3}$ . \n\nan der Waals magnetic insulators are a V materials system that may enable designer topological states $(I)$ and spintronic technologies (2). The recent isolation (3, 4) of few-layer magnets with either ferromagnetic $\\mathrm{(CrI_{3},C r_{2}G e_{2}T e_{6})}$ or antiferromagnetic order $(5,6)$ is just the tip of the iceberg. The vast family of layered metal halides (7) contains spin orders from multiferroics (8) to proximate spin liquids (9), of key interest to both fundamental and applied physics. Existing studies have focused on magneto-optical effects $(3,4,I O,I I)$ as a characterization tool, but a more general, device-oriented, approach is needed. \n\nHere we demonstrate that tunneling through layered insulators is a versatile probe of magnetism on the nanoscale in these materials. We report the conductance of graphite $\\mathrm{^{\\prime}C r I_{3}},$ /graphite junctions (Fig. 1A) as a function of magnetic field and temperature and electrically detect an antiferromagnetic ground state and a field-induced metamagnetic transition. The metamagnetic transition is revealed by large magnetoresistances (up to $550\\%$ ) arising from the antiparallel-to-parallel reorientation of chromium spins in adjacent crystal layers. A similar effect was previously proposed $(I2)$ for synthetic multilayer magnets, but experimental realizations (13) were limited to magnetoresistances below $70\\%$ . The performance of our devices is an order of magnitude higher, corresponding to estimated spin polarization above $95\\%$ . Furthermore, the two-dimensional magnetism of $\\mathrm{CrI}_{3}$ enables ultrathin tunnel barriers $\\cdot<3\\ \\mathrm{nm}\\rangle$ and a concomitant 10,000-fold increase in conductance (per unit area) compared to previous results (13). The noninvasive van der Waals transfer of the magnetic layer ensures substrate-independent device integration, and together with high magnetoresistance, spin polarization, and conductance, may enable noninvasive spin injectors and detectors for next-generation spintronics experiments incorporating topological insulators (14), superconductors $(I5)$ , antiferromagnets (16), and low-symmetry crystals (17–20). \n\nTunneling through magnetic insulators was first studied in the pioneering experiments of (21) and later in (22, 23). When electrons tunnel through a ferromagnetic insulator, spin-up and spin-down electrons see different barrier heights (Fig. 1B). As a result, the tunneling rate can vary by orders of magnitude for electrons of opposite spins (12, 22), called the spin filter effect. The smaller gap for spin-up electrons tends to decrease the junction resistance as the barrier is cooled below its Curie temperature, $T_{\\mathrm{C}}$ . The situation is more complicated for spatially textured magnetism. For example, the resistance of $\\mathrm{Ag/}$ EuSe/Al tunnel junctions increases significantly when the EuSe becomes antiferromagnetic (23). However, the exponential dependence of the tunneling current on the barrier electronic structure generally provides a clear resistive signature of magnetism. We will use these effects to electrically detect the magnetic ground state and field-induced metamagnetic transition of fewlayer $\\mathrm{CrI}_{3}$ . \n\nThe resistance of a graphite/tetralayer $\\mathrm{{CrI}_{3}/}$ graphite junction (device D1) as a function of temperature is shown in Fig. 1C. We measure the resistance in a four-point geometry using a $30\\mathrm{-mV}$ root-mean-square AC excitation (24). The temperature dependence was measured by cooling the sample down with (purple line) and without (black line) the application of an external magnetic field. The magnetic field is applied perpendicular to the layers, along the magnetic easy axis of $\\mathrm{{CrI}_{3}}$ . Above $90\\mathrm{K},$ the resistance is independent of the applied field and shows Arrhenius behavior with a thermal activation gap of roughly 159 meV (fig. S1). The resistance becomes fielddependent as the temperature approaches the bulk $T_{\\mathrm{C}}$ of 61 K. When the sample is cooled in a $2.5\\mathrm{-T}$ magnetic field, the resistance plateaus below $80~\\mathrm{K},$ signaling the onset of tunneling conductance (21, 23). By contrast, when the sample is cooled without an external field, the resistance exhibits a kink near $T_{\\mathrm{C}}$ and continues to increase below $60~\\mathrm{K}$ . The dependence of the tunneling resistance on magnetic field and temperature shows that the tunnel conductance is sensitive to the magnetization of the barrier. \n\nTo further investigate the magnetic phase diagram, we study the zero-bias conductance $(500\\mathrm{-}\\upmu\\mathrm{V}$ AC excitation) of devices with two- to four-layer $\\mathrm{CrI}_{3}$ barriers as a function of applied magnetic field at low temperatures $300\\mathrm{mK}$ to $4.2\\:\\mathrm{K},$ . We start with an analysis of a graphite/bilayer $\\mathrm{{CrI}_{3}/}$ graphite junction (D2, Fig. 2A). For this device, the junction conductance increases almost twofold in a sharp step as the external field is increased above $0.85\\mathrm{T}$ . The corresponding magnetoresistance is $95\\%$ , defined as \n\n$$\nM R=100\\%\\times{\\frac{(G_{\\mathrm{HI}}-G_{\\mathrm{LO}})}{G_{\\mathrm{LO}}}}\n$$ \n\nwhere $G_{\\mathrm{HI}}$ is the high-field conductance maximum and $G_{\\mathrm{LO}}$ is the low-field conductance minimum. No further steps are observed up to the largest fields studied (8 T; see fig. S2). As the field is reduced from $2.4\\mathrm{~T~}$ , the conductance decreases to its original zero-field value in a sharp step at $0.35~\\mathrm{T}$ . The well-defined steps and hysteretic field dependence demonstrate that the conductance changes originate from switching events of the magnetization. The tunneling current is most sensitive to the interlayer magnetization alignment, so the large steps we observe likely arise from vertical domains, i.e., regions where the magnetization points in different directions in different layers of $\\mathrm{{CrI}_{3}}$ . \n\nRecently, magneto-optical Kerr effect (MOKE) data have revealed an antiferromagnetic state in bilayer $\\mathrm{CrI}_{3}$ for fields below about $0.6\\mathrm{T}$ (4). In this state, the $\\mathrm{cr}$ moments order ferromagnetically within each layer but point in opposite directions in adjacent layers (Fig. 2B). The layers are fully aligned when the external magnetic field is increased above a critical value (Fig. 2C); i.e., it undergoes a metamagnetic transition to a ferromagnetic state. When the field is reduced, the magnetization spontaneously reverts to the antiparallel configuration. The switching behavior we observe in magnetoconductance reflects these previous MOKE data, confirming that the conductance change arises from the metamagnetic \n\nFig. 1. Experimental setup. (A) Optical micrograph of a tetralayer CrI3 tunnel junction device (device D1, false color).The dashed line encloses the tunnel junction area.The graphite contacts are themselves contacted by $\\mathsf{A u/C r}$ wires in a four-point geometry. Inset: Schematic of the van der Waals heterostructures studied in this work. Electrons tunnel between two graphite sheets separated by a magnetic $\\mathsf{C r l}_{3}$ tunnel barrier. The entire stack is encapsulated in hexagonal boron nitride. (B) Schematic energy diagram of a metal/ ferromagnetic insulator/metal junction.The red and blue lines in the barrier region represent the spin-up and spin-down energy barriers, respectively. The lower barrier for spin-up electrons leads to spin-polarized tunneling and reduced resistance for a ferromagnetic barrier. (C) Zero-bias junction resistance versus temperature for device D1 cooled with (purple) and without (black) an applied magnetic field. The curves begin to deviate around the bulk Curie temperature (61 K), giving evidence for magnetic order in the $\\mathsf{C r l}_{3}$ barrier and for spin-polarized tunneling.The magnetic field was applied perpendicular to the $\\mathsf{C r l}_{3}$ layers. \n\n![](images/66bc5ed14a3b93cc03b9682a457920c2df82411a8295cacda247fb7177cabc9f.jpg) \n\n![](images/6a57c0ed4ac6c6561d8d8bc681d69e07b4b8601ede79e57117a4c024a00adda6.jpg) \n\nFig. 2. Magnetoconductance of few-layer $\\mathsf{c r l}_{3}$ . (A) Conductance through a bilayer $\\mathsf{C r l}_{3}$ tunnel barrier (device D2) as a function of an out-of-plane applied magnetic field with $500\\mathrm{-}\\upmu\\mathrm{V}$ AC excitation.The data were taken both for decreasing (purple line, left arrow) and increasing (black line, right arrow) magnetic field. The magnetoconductance traces are consistent with previous magnetometry data (4) for bilayer CrI3 showing that the two layers are antiparallel at zero field but can be aligned with an external field below 1 T. (B and C) Schematic of barriers experienced by spin-up and spin-down electrons tunneling through bilayer $\\mathsf{C r l}_{3}$ in the low-field (B) and high-field (C) states. In the low-field state, the two layers are antiparallel, and both spins see a high barrier. In the high-field state, the layers are aligned and up spins see a low-energy barrier, leading to increased conductance. (D to F) Analogous data and schematics for a tetralayer $\\mathsf{C r l}_{3}$ barrier device (device D3). In both cases, the sample temperature was $300\\mathsf{m}\\mathsf{k}.$ . \n\ntransition. We note, however, that little to no hysteresis was previously observed in the MOKE results for bilayer $\\mathrm{CrI_{3}}\\left(4\\right)$ , whereas we observe a clear hysteresis in the tunneling measurements. The reasons for this may be related to the lower temperature for these tunneling experiments as well as the fact that the $\\mathrm{CrI}_{3}$ remains closer to equilibrium (no photoexcitation). \n\nWe have also studied tunnel junctions with three- and four-layer $\\mathrm{CrI}_{3}$ as the barrier. The zero-bias junction resistance of a graphite/4L $\\mathrm{CrI}_{3},$ /graphite junction (D3) is shown as a function of external magnetic field in Fig. 2D. The overall phenomenology is similar to that of junctions with a bilayer barrier, with well-defined steps and a total magnetoresistance of $550\\%$ . In addition to the large jump around $1.8\\mathrm{T}$ , we see multiple smaller steps that may correspond to lateral domains within the junction. This is consistent with a lateral domain size on the order of $2\\upmu\\mathrm{m}$ observed in previous optical studies (2, 4). The behavior of our trilayer junctions is again similar, with magnetoresistances up to \n\n$300\\%$ (fig. S3). On the basis of these results, we hypothesize that few-layer $\\mathrm{CrI}_{3}$ is antiferromagnetic without an external magnetic field (Fig. 2E). Such behavior is consistent with magneto-optical data for bilayer $\\mathrm{CrI}_{3}$ (4), but those MOKE data suggested a ferromagnetic configuration for thicker crystals (e.g., 3L $\\mathrm{CrI}_{3}$ ). Nevertheless, our data strongly support an antiparallel alignment between layers extending over most of the junction area. Once more, the different temperatures and absence of photoexcitation may be responsible for the different behavior observed. \n\nTo understand the large magnetoresistance and its thickness dependence, we analyze a spin filter model (12) for transmission through a $\\mathrm{CrI}_{3}$ barrier. The model treats each crystal layer of the $\\mathrm{CrI}_{3}$ as an independent tunnel barrier, with a transmission coefficient of $T_{\\mathrm{P}}$ and $T_{\\mathrm{AP}}$ for spins parallel and antiparallel to the local spin direction, respectively. Ignoring multiple reflections and quantum interference effects, the transmission through the entire crystal is then a product of the transmission coefficients for each layer. For example, for a $\\mathrm{CrI}_{3}$ bilayer in the high-field magnetization configuration (Fig. 2C), spin-up electrons have a transmission probability $T_{\\mathrm{P}}^{2}$ whereas spindown electrons have transition probability ${T_{\\mathrm{AP}}}^{2}$ The high-field conductance is $G_{\\mathrm{HI}}\\propto{T_{\\mathrm{P}}}^{2}+{T_{\\mathrm{AP}}}^{2}$ Similarly, for the low-field configuration with antiparallel magnetizations (Fig. 2B), the conductance is $G_{\\mathrm{LO}}\\propto2T_{\\mathrm{P}}T_{\\mathrm{AP}}$ . The ratio of high-field to low-field conductances is then $G_{\\mathrm{HI}}/G_{\\mathrm{LO}}=({T_{\\mathrm{P}}}^{2}+$ $T_{\\mathrm{AP}}^{\\mathrm{~2~}})/2T_{\\mathrm{P}}T_{\\mathrm{AP}}\\approx T_{\\mathrm{P}}/2T_{\\mathrm{AP}}$ . We have carried out similar calculations for $N=3$ - and 4-layer $\\mathrm{CrI}_{3}$ barriers, summarized in the supplementary text. In Fig. 3A, we plot the measured magnetoresistance (black circles) as a function of $N_{:}$ along with a one-parameter fit to the spin filter model (purple stars). The model reproduces the overall experimental trend with a best-fit value of $T_{\\mathrm{P}}/T_{\\mathrm{AP}}=3.5$ . For a summary of all measured devices, see table S1. \n\n![](images/9a4958900c5f7f6c20ced8b67f471fcb8eb557b9adf5aa3427f921dff7ab4439.jpg) \nFig. 3. Origin of magnetoresistance in $\\mathsf{c r l}_{3}.$ . (A) Magnetoresistance ratio (black circles) versus $\\mathsf{C r l}_{3}$ layer number for multiple devices at $300~\\mathsf{m K}.$ . We also plot a fit to the spin filter model (purple stars). The only fitting parameter, $T_{\\mathsf{P}}/T_{\\mathsf{A P}}=3.5$ , gives the ratio of spin-up to spin-down transmission through a $\\mathsf{C r l}_{3}$ monolayer. (B) Resistance-area product versus $\\mathsf{C r l}_{3}$ layer number for multiple devices. The resistances are measured in the fully aligned magnetic configuration and were taken at zero bias. (C) Electronic structure of a trilayer graphite/trilayer $\\mathsf{C r l}_{3}$ heterostructure calculated with density functional theory. The $\\mathsf{C r l}_{3}$ is in the fully ferromagnetic configuration, and its bands are projected on the spin-up and spin-down channels. Although the minority spins do not show states close to the Fermi energy, there are a large number of states in the majority channel. The difference establishes a microscopic basis for the large $T_{\\mathsf{P}}/T_{\\mathsf{A P}}$ that we observe. \n\nWe can also estimate the spin polarization of the current within the spin filter model. When the $\\mathrm{CrI}_{3}$ is fully polarized, the transmission probability of up and down spins through an $N_{\\mathbf{\\delta}}$ -layer $\\mathrm{{CrI}_{3}}$ barrier is $T_{\\mathrm{P}}^{N}$ and $T_{\\mathrm{AP}}^{\\phantom{\\dagger}N},$ , respectively. Therefore, the ratio of spin-up to spin-down conductance is approximately $G_{\\uparrow}/G_{\\downarrow}=(T_{\\mathrm{P}}/T_{\\mathrm{AP}})^{N}$ . From $T_{\\mathrm{P}}/T_{\\mathrm{AP}}\\approx3.5$ , we estimate a spin polarization of $(G_{\\uparrow}-G_{\\downarrow})/(G_{\\uparrow}+G_{\\downarrow})\\approx85,$ 95, and $99\\%$ for $N=2$ , 3, and 4, respectively. These values are comparable to the largest values obtained with EuSe and EuS magnetic insulator barriers (13, 23), so that $\\mathrm{CrI}_{3}$ tunnel barriers can enable future spin-sensitive transport devices. \n\nIn the spin filter approximation, the calculation of the magnetoresistance is reduced to a calculation of $T_{\\mathrm{P}}/T_{\\mathrm{AP}}{:}$ , related to the different barrier heights for spin-up and spin-down electrons. To investigate the barrier heights, we carried out density functional theory (DFT) calculations for three layers of $\\mathrm{CrI}_{3}$ and three layers of graphite (see the supplementary text). Calculations portray $\\mathrm{CrI}_{3}$ as a ferromagnetic insulator with magnetic moments localized on the chromium atoms and spin-split energy bands (Fig. 3C). Notably, when the magnetization of the three layers is aligned, we find that spin-up bands of $\\mathrm{{CrI}_{3}}$ lie very close to the graphite Fermi energy, whereas the nearest spin-down bands are much higher in energy (>1 eV). Therefore, the transparency of the barrier has to be much smaller for spin-down electrons and provides a microscopic foundation for the large $T_{\\mathrm{P}}/T_{\\mathrm{AP}}$ . Note that even though the DFT calculations show a $\\mathrm{CrI}_{3}$ majority band very close to or crossing the graphite Fermi energy, the exponential thickness dependence of the junction resistance (Fig. 3B) shows that our junctions are in the tunneling-dominated regime with a finite barrier height. Further transport calculations should elucidate the precise tunneling pathways in $\\mathrm{{CrI}_{3}/}$ graphite junctions leading to finite energy barriers with chromium 3d orbital bands very close to the Fermi level. \n\nIn addition to the zero-bias conductance, we measured the differential conductance $\\mathrm{d}I/\\mathrm{d}V$ as a function of the applied DC offset $V_{\\mathrm{DC}}$ . The $\\mathrm{d}I/\\mathrm{d}V$ versus $V_{\\mathrm{DC}}$ traces reveal a rich spectrum, whose most prominent features are a series of steplike increases, symmetric in bias, below $25\\mathrm{meV}$ (Fig. 4 and figs. S4 and S5). These steps are characteristic of inelastic electron tunneling where electrons lose energy to collective excitations of the barrier or electrodes. When the tunneling energy $(e V_{\\mathrm{DC}})$ exceeds the collective excitation energy, the introduction of these additional tunneling pathways results in steps in the $\\mathrm{d}I/\\mathrm{d}V$ versus $V_{\\mathrm{DC}}$ trace. The energies of phonons (25–27) and magnons (28–31) can therefore be measured as peaks (dips) in $\\mathrm{d}^{2}I/\\mathrm{d}V^{2}$ versus $V_{\\mathrm{DC}}$ for positive (negative) $V_{\\mathrm{DC}}$ . The bottom panel of Fig. 4A shows $\\vert\\mathrm{d}^{2}I/\\mathrm{d}V^{2}\\vert$ obtained by numerical differentiation of the $\\mathrm{d}I/\\mathrm{d}V$ data for a bilayer $\\mathrm{CrI}_{3}$ barrier device (D2). The inelastic tunneling spectrum (IETS) reveals three peaks at 3, 7 , and $17\\mathrm{meV}.$ . These features were visible in every $\\mathrm{CrI}_{3}$ tunneling device that we measured (figs. S4 to S6). Past IETS data on graphite/boron nitride/graphite heterostructures in a geometry similar to that of our junctions (26) do not contain any inelastic contributions from graphite phonons below $17\\mathrm{meV}.$ . Earlier scanning tunneling studies of graphite surfaces similarly find an onset of prominent graphite inelastic peaks at $16~\\mathrm{meV}$ (27). Thus, the inner two peaks must arise from $\\mathrm{CrI}_{3}$ phonons or magnons. The inelastic features start forming just below the onset of magnetism (fig. S7), suggesting a magnon excitation origin. \n\n![](images/9ade0145bf9d0eb00abc91366040f497852b8b2e367f170c4eecf4f9d2c10a0f.jpg) \nFig. 4. Inelastic tunneling spectroscropy. (A) Top panel: Differential conductance versus a DC bias voltage for a bilayer $\\mathsf{C r l}_{3}$ barrier device (D2) at zero applied magnetic field. The AC excitation was $200~\\upmu\\upnu$ and the temperature was $300~\\mathrm{mK}$ . Bottom panel: Absolute value of ${\\mathsf{d}}^{2}I/{\\mathsf{d}}V^{2}$ versus a DC bias voltage, obtained via numerical differentiation of the data in the top panel. According to the theory of inelastic tunneling spectroscopy, the peaks in ${\\mathsf{d}}^{2}I/{\\mathsf{d}}V^{2}$ correspond to phonon or magnon excitations of the barrier or electrodes. (B) $\\vert\\mathsf{d}^{2}I/\\mathsf{d}V^{2}\\vert$ (color scale at right) versus applied magnetic field and DC bias voltage. All three inelastic peaks increase in energy as the applied field is increased. (C) Energy of the two lowest-energy inelastic peaks versus applied magnetic field. The zero-field \nenergy is subtracted from both peaks for clarity. The peak locations were determined by Gaussian fits to the data. The error bars represent estimated standard deviations calculated from the least-squares fitting procedure. The dashed gray line shows the Zeeman energy shift of a $2\\upmu_{\\mathsf{B}}$ magnetic moment (0.12 meV/T), which roughly matches the evolution of the 3-meV peak. (D) Calculated magnon density of states (DOS) for $\\mathsf{C r l}_{3}$ . The details of the calculations are described in the supplementary text. (E) Calculated dispersion of magnons with applied magnetic field at zero temperature. (F) Calculated renormalized magnon dispersion with magnetic field at finite temperature $\\cdot T=0.033J$ , where $\\jmath$ is the nearest-neighbor exchange). \n\nAnother signature of magnon-assisted tunneling is the stiffening of the magnon modes as an external magnetic field is applied (29, 30). A single magnon corresponds to a delocalized spinflip ( $\\begin{array}{r}{|S_{\\mathrm{z}}|=1\\rangle}\\end{array}$ within the $\\mathrm{CrI}_{3}$ barrier, which carries a magnetic moment of approximately $2\\upmu_{\\mathrm{B}}$ (where $\\upmu_{\\mathrm{B}}$ is the Bohr magneton) antiparallel to the external magnetic field. Therefore, magnon IETS peaks should blueshift at $0.12\\mathrm{meV/T}$ by the Zeeman effect. Figure 4B shows $\\ensuremath{|\\mathrm{d}^{2}I/\\mathrm{d}V^{2}|}$ as a function of both applied magnetic field and bias voltage. Even to the eye, a strong linear increase of all three IETS peaks is visible. In Fig. 4C, we plot the peak energies (determined by Gaussian fits) of the innermost peaks versus magnetic field. We also plot the expected energy shift $2\\upmu_{\\mathrm{B}}B$ due to the Zeeman effect (dashed gray line). This line roughly fits the magnetic field dependence of the 3-meV peak, but the 7-meV peak clearly has much higher dispersion corresponding to $8\\upmu_{\\mathrm{B}}$ . The latter effect might be caused by magnon renormalization effects, as discussed below. \n\nTo model the magnon spectrum, we write an effective spin Hamiltonian for $\\mathrm{CrI}_{3}$ (32) that includes nearest- and next-nearest–neighbor exchange, together with an easy axis anisotropy term (see supplementary text for details). Using this model, we find that the calculated magnon density of states (Fig. 4D) can qualitatively reproduce the experimental inelastic spectrum. We used a nearest-neighbor exchange parameter consistent with previous first principles calculations and experiment (32–34) and chose the next-nearest–neighbor value to match our data (see supplementary text). At zero temperature, the magnon energies are still expected to blueshift at $0.12\\mathrm{meV/T}$ in an applied magnetic field (Fig. 4E). However, at finite temperature and $B=0$ , thermally excited magnons deplete the magnetization, resulting in an effective reduction of the spin stiffness and a redshift of the magnon spectrum with respect to the case without thermal renormalization of the exchange constants. Application of a magnetic field increases the spin wave gap, decreasing the population of thermal spin waves and increasing the spin stiffness. This renormalizes the effective magnon hopping parameters, leading to a shift of the spin wave spectrum that adds to the Zeeman term and results in a nonlinear field dependence (Fig. 4F and supplementary text). \n\nOur devices are an example of a “double spin filter” where a magnetic tunnel barrier with decoupled magnetic layers is used as a magnetic memory bit (12). We overcome the limitations of previous double spin filters (13) owing to the unique decoupling of magnetic layers across the atomic-scale van der Waals gap. This decoupling provides electrical readout of the $\\mathrm{CrI}_{3}$ magnetization state without additional ferromagnetic sensor layers, enabling facile detection of spin-orbit torques on layered magnetic insulators. Further exploration is required to understand the electron-magnon coupling in these devices and to potentially study bosonic topological matter in honeycomb ferromagnets (35, 36). \n\n# REFERENCES AND NOTES \n\n1. W.-K. Tse, Z. Qiao, Y. Yao, A. H. MacDonald, Q. Niu, Phys. Rev. \nB 83, 155447 (2011). \n2. D. Zhong et al., Sci. Adv. 3, e1603113 (2017). \n3. M. A. McGuire, H. Dixit, V. R. Cooper, B. C. Sales, Chem. Mater. \n27, 612–620 (2015). \n4. B. Huang et al., Nature 546, 270–273 (2017). \n5. X. Wang et al., 2D Mater. 3, 031009 (2016). \n6. J.-U. Lee et al., Nano Lett. 16, 7433–7438 (2016). \n7. M. A. McGuire, Crystals (Basel) 7, 121 (2017). \n8. T. Kurumaji et al., Phys. Rev. Lett. 106, 167206 (2011). \n9. A. Banerjee et al., Science 356, 1055–1059 (2017). \n10. C. Gong et al., Nature 546, 265–269 (2017). \n11. K. L. Seyler et al., Nat. Phys. 14, 277–281 (2018). \n12. D. C. Worledge, T. H. Geballe, J. Appl. Phys. 88, 5277–5279 (2000). \n13. G.-X. Miao, M. Müller, J. S. Moodera, Phys. Rev. Lett. 102, \n076601 (2009). \n14. A. R. Mellnik et al., Nature 511, 449–451 (2014). \n15. T. Wakamura et al., Nat. Mater. 14, 675–678 (2015). \n16. P. Wadley et al., Science 351, 587–590 (2016). \n17. D. MacNeill et al., Nat. Phys. 13, 300–305 (2017). \n\n18. D. MacNeill et al., Phys. Rev. B 96, 054450 (2017). \n19. Q. Shao et al., Nano Lett. 16, 7514–7520 (2016). \n20. T. D. Skinner et al., Nat. Commun. 6, 6730 (2015). \n21. L. Esaki, P. J. Stiles, S. von Molnar, Phys. Rev. Lett. 19, 852–854 (1967). \n22. J. S. Moodera, X. Hao, G. A. Gibson, R. Meservey, Phys. Rev. Lett. 61, 637–640 (1988). \n23. J. S. Moodera, R. Meservey, X. Hao, Phys. Rev. Lett. 70, 853–856 (1993). \n24. Materials and methods are available as supplementary materials. \n25. R. C. Jaklevic, J. Lambe, Phys. Rev. Lett. 17, 1139–1140 (1966). \n26. S. Jung et al., Sci. Rep. 5, 16642 (2015). \n27. L. Vitali, M. A. Schneider, K. Kern, L. Wirtz, A. Rubio, Phys. Rev. B 69, 121414 (2004). \n28. D. C. Tsui, R. E. Dietz, L. R. Walker, Phys. Rev. Lett. 27, 1729–1732 (1971). \n29. C. F. Hirjibehedin, C. P. Lutz, A. J. Heinrich, Science 312, 1021–1024 (2006). \n30. A. Spinelli, B. Bryant, F. Delgado, J. Fernández-Rossier, A. F. Otte, Nat. Mater. 13, 782–785 (2014). \n31. K. Yamaguchi, Phys. Status Solidi, B Basic Res. 236, 634–639 (2003). \n32. J. L. Lado, J. Fernández-Rossier, 2D Mater. 4, 035002 (2017). \n33. W.-B. Zhang, Q. Qu, P. Zhu, C.-H. Lam, J. Mater. Chem. C Mater. Opt. Electron. Devices 3, 12457–12468 (2015). \n34. A. Narath, Phys. Rev. 140, A854–A862 (1965). \n35. S. A. Owerre, Sci. Rep. 7, 6931 (2017). \n36. S. S. Pershoguba et al., Phys. Rev. X 8, 011010 (2018). \n37. D. Klein, Replication Data for: Probing magnetism in 2D van der Waals crystalline insulators via electron tunneling, Version 1, Harvard Dataverse (2018); https://doi.org/10.7910/ DVN/4RUPNW. \n\n# ACKNOWLEDGMENTS \n\nWe thank V. Fatemi and Y. Cao for helpful discussions and assistance with measurements. Funding: This work was supported by the Center for Integrated Quantum Materials under NSF grant DMR-1231319 as well as the Gordon and Betty Moore \n\nFoundation’s EPiQS Initiative through grant GBMF4541 to P.J.-H. Device fabrication was partly supported by the Center for Excitonics, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Basic Energy Sciences (BES), under award no. DESC0001088. D.R.K. acknowledges partial support by the NSF Graduate Research Fellowship Program under grant no. 1122374. J.L.L. acknowledges financial support from the ETH Zurich Postdoctoral Fellowship program. D.S. acknowledges the Marie Curie Cofund program at INL. J.F.-R. acknowledges support from PTDC/FIS-NAN/3668/2014. Growth of hexagonal boron nitride crystals at NIMS was supported by the Elemental Strategy Initiative conducted by the MEXT, Japan, and JSPS KAKENHI grant nos. JP15K21722 and JP25106006. Work done at Ames Laboratory (P.C. and S.M.) was supported by the DOE BES Division of Materials Sciences and Engineering. Ames Laboratory is operated for the DOE by Iowa State University under contract no. DE-AC02-07CH11358. S.M. was funded by the Gordon and Betty Moore Foundation’s EPiQS Initiative through grant GBMF4411. Author contributions: D.R.K., D.M., and P.J.-H. conceived the project. D.R.K. and D.M. fabricated and measured devices and analyzed the data. K.W., T.T., S.M., and P.C. supplied the boron nitride crystals. E.N.-M. supplied the $\\mathsf{C r l}_{3}$ crystals. J.L.L., D.S., and J.F.-R. carried out theoretical calculations. All authors contributed to writing the manuscript. Competing interests: The authors declare no competing financial interests. Data and materials availability: The data shown in the paper are available at Harvard Dataverse (37). \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/360/6394/1218/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S8 \nTable S1 \nReferences (38–41) \n\n21 November 2017; accepted 24 April 2018 \nPublished online 3 May 2018 \n10.1126/science.aar3617 \n\n# Science \n\n# Probing magnetism in 2D van der Waals crystalline insulators via electron tunneling \n\nD. R. Klein, D. MacNeill, J. L. Lado, D. Soriano, E. Navarro-Moratalla, K. Watanabe, T. Taniguchi, S. Manni, P. Canfield, J. Fernández-Rossier and P. Jarillo-Herrero \n\nScience 360 (6394), 1218-1222. DOI: 10.1126/science.aar3617originally published online May 3, 2018 \n\n# An intrinsic magnetic tunnel junction \n\nAn electrical current running through two stacked magnetic layers is larger if their magnetizations point in the same direction than if they point in opposite directions. These so-called magnetic tunnel junctions, used in electronics, must be carefully engineered. Two groups now show that high magnetoresistance intrinsically occurs in samples of the layered material CrI $3$ sandwiched between graphite contacts. By varying the number of layers in the samples, Klein et al. and Song et al. found that the electrical current running perpendicular to the layers was largest in high magnetic fields and smallest near zero field. This observation is consistent with adjacent layers naturally having opposite magnetizations, which align parallel to each other in high magnetic fields. \n\nScience, this issue p. 1218, p. 1214 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/360/6394/1214.full \n\nREFERENCES \n\nThis article cites 39 articles, 5 of which you can access for free http://science.sciencemag.org/content/360/6394/1218#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41560-017-0067-y", + "DOI": "10.1038/s41560-017-0067-y", + "DOI Link": "http://dx.doi.org/10.1038/s41560-017-0067-y", + "Relative Dir Path": "mds/10.1038_s41560-017-0067-y", + "Article Title": "Tailored interfaces of unencapsulated perovskite solar cells for >1,000 hour operational stability", + "Authors": "Christians, JA; Schulz, P; Tinkham, JS; Schloemer, TH; Harvey, SP; de Villers, BJT; Sellinger, A; Berry, JJ; Luther, JM", + "Source Title": "NATURE ENERGY", + "Abstract": "Long-term device stability is the most pressing issue that impedes perovskite solar cell commercialization, given the achieved 22.7% efficiency. The perovskite absorber material itself has been heavily scrutinized for being prone to degradation by water, oxygen and ultraviolet light. To date, most reports characterize device stability in the absence of these extrinsic factors. Here we show that, even under the combined stresses of light (including ultraviolet light), oxygen and moisture, perovskite solar cells can retain 94% of peak efficiency despite 1,000 hours of continuous unencapsulated operation in ambient air conditions (relative humidity of 10-20%). Each interface and contact layer throughout the device stack plays an important role in the overall stability which, when appropriately modified, yields devices in which both the initial rapid decay (often termed burn-in) and the gradual slower decay are suppressed. This extensively modified device architecture and the understanding developed will lead towards durable long-term device performance.", + "Times Cited, WoS Core": 744, + "Times Cited, All Databases": 799, + "Publication Year": 2018, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000419976100016", + "Markdown": "# Tailored interfaces of unencapsulated perovskite solar cells for >1,000 hour operational stability \n\nJeffrey A. Christians $\\textcircled{1}$ 1, Philip Schulz $\\oplus1$ , Jonathan S. Tinkham2, Tracy H. Schloemer   2, Steven P. Harvey $\\oplus1$ , Bertrand J. Tremolet de Villers $\\left.\\frac{\\mathfrak{d}}{\\mathfrak{p}}\\right|$ 1, Alan Sellinger $\\textcircled{10}1,2$ , Joseph J. Berry   1\\* and Joseph M. Luther   1\\* \n\nLong-term device stability is the most pressing issue that impedes perovskite solar cell commercialization, given the achieved $22.7\\%$ efficiency. The perovskite absorber material itself has been heavily scrutinized for being prone to degradation by water, oxygen and ultraviolet light. To date, most reports characterize device stability in the absence of these extrinsic factors. Here we show that, even under the combined stresses of light (including ultraviolet light), oxygen and moisture, perovskite solar cells can retain $94\\%$ of peak efficiency despite 1,000 hours of continuous unencapsulated operation in ambient air conditions (relative humidity of $10-20\\%$ ). Each interface and contact layer throughout the device stack plays an important role in the overall stability which, when appropriately modified, yields devices in which both the initial rapid decay (often termed burn-in) and the gradual slower decay are suppressed. This extensively modified device architecture and the understanding developed will lead towards durable long-term device performance. \n\nScolountidounc-t1op,2rsocoefsstehde ocrhgeamnica–linforgmaunliac $\\mathrm{ABX}_{3}$ e hpaevreovbsekeitne ‘rsedmisi3- covered’ for their remarkable optoelectronic properties , most notably the ability to produce a large photopotential even with substantial structural defects. The power conversion efficiency (PCE) of perovskite solar cells is now on par with that of commercial photovoltaic modules4, but long-term stability remains a critical hurdle for commercialization5,6. Significant attention has been brought towards improving the stability of the devices6–10, but the combined effects of moisture, oxygen and light remain problematic. Key factors in understanding the fundamental degradation mechanisms of the various perovskite active layers (PALs) are now being discovered. In the case of methylammonium $\\mathrm{'CH_{3}N H_{3}^{+}}$ (MA)) lead triiodide, the thermal degradation11–13, reactions with oxygen, atmospheric water14–16 and light- and radiation-induced instability17,18 have been extensively studied. Formamidinium $\\mathrm{(CH(NH_{2})_{2}^{+}}$ (FA)) lead triiodide and caesium lead triiodide, although compositionally more stable than $\\mathrm{MAPbI}_{3},$ have both a photoactive phase and a wider bandgap, but undesired hexagonal or orthorhombic phases, respectively19,20. Although phase stabilization of $\\mathrm{CsPbI}_{3}$ has been achieved through nanostructuring21, the highest-efficiency singlejunction solar cells benefit from complexed A- and $\\mathrm{X}$ -site compositions of $\\mathrm{FAPbI}_{3}$ (for example, $\\mathrm{FA}_{x}\\mathrm{MA}_{y}\\mathrm{Cs}_{1-x-y}\\mathrm{Pb}(\\mathrm{I}_{1-z}\\mathrm{Br}_{z})_{3}.$ where $x$ is large and $z$ is small) because of the improved compositional stability compared with that of $\\mathbf{MAPbI}_{3}$ and improved phase stability compared with those of $\\mathrm{FAPbI}_{3}$ and $\\mathrm{CsPbI}_{3}$ (refs 8,19,22). \n\nAn improved PAL stability is integral to an improved device reliability23, yet further gains are necessary and can be achieved within the device stack as a whole. Previous studies have indicated that the electron transport and hole transport materials (ETM and HTM, respectively)—which serve as charge-selective extraction layers— and the metal electrodes used in the devices are critical to device stability6,24–26, which makes it critical to address all of these components in concert to understand their relative importance towards degradation and mitigate the prominent interface-specific degradation mechanisms. \n\nUsing a single formulation PAL, beginning at the most common perovskite solar cell device architecture, $\\mathrm{TiO}_{2}/\\mathrm{PAL}/$ spiro-OMeTAD/Au (spiro-OMeTAD, $^{2,2^{\\prime},7,7^{\\prime}}$ ​-tetrakis( $.N,N.$ -di$\\boldsymbol{p}$ -methoxyphenylamino)- $^{.9,9^{\\prime}}$ ​-spirobifluorene), we systematically addressed solar cell degradation mechanisms related to the chargetransport layers, interfaces, contact choices and their integration to arrive at a modified device architecture of $\\mathrm{SnO_{2}/P A L/E H}\\bar{4}4/\\mathrm{MoO_{\\itx}}/$ Al (EH44, 9-(2-ethylhexyl)- $.N,N,N,N.$ -tetrakis(4-methoxyphenyl)- 9H-carbazole-2,7-diamine). This modified architecture produces a device that retains over $94\\%$ of its peak performance after 1,000 hours of accelerated degradation testing through continuous illumination near the maximum power point in ambient air conditions (relative humidity was monitored at approximately $10{-}20\\%$ ), without encapsulation. Although the added stresses of oxygen and moisture certainly accelerate degradation, the understanding gained by exposing devices to these extrinsic degradation factors will guide the future development of encapsulation methods and layers designed for specific applications, which will further extend the device lifetime. \n\n# Device performance \n\nThe PAL used in this study contains a combination of $\\mathrm{FA^{+}}$ , $\\mathrm{MA^{+}}$ and $C s^{+}$ , as well as both $\\mathrm{I^{-}}$ and $\\mathrm{Br^{-}}$ anions (hereafter referred to as FAMACs), and was deposited following a method reported in the literature8. The stoichiometry of the precursor solution was $\\mathrm{(FA_{0.79}M}$ $\\mathrm{A_{0.16}C s_{0.05})_{0.97}P b(I_{0.84}B r_{0.16})_{2.97}},$ whereas the stoichiometry at the surface of these FAMACs films was determined by XPS to be $(\\mathrm{FA}_{0.76}\\mathrm{M}$ $\\mathrm{A_{0.21}C s_{0.03})_{0.67}P b(I_{0.89}B r_{0.11})_{2.56}}$ (Supplementary Fig. 1). This deviation from $\\mathrm{ABX}_{3}$ stoichiometry indicates that the $\\mathrm{PbX}_{2}$ species are preferentially present at the surface of the films. \n\nIn HTMs, such as the commonly used spiro-OMeTAD, lithium bis(trifluoromethylsulfonyl)imide (LiTFSI) is prevalent as a $\\boldsymbol{p}$ -dopant to enhance the conductivity and hole mobility. However, the $\\mathrm{Li^{+}}$ cations are highly mobile and can migrate throughout the device stack during the operation, which results in the unintentional modification of other materials in the device stack, increased device hysteresis27 and the potential for redox reactions with the $\\mathrm{PAL}^{28}$ , and the hygroscopic $\\mathrm{Li^{+}}$ salts facilitate moisture-induced degradation29,30. Thus, for the device configuration used in this study, we prepared a $\\mathrm{Li^{+}}$ -free hydrophobic HTM based on EH44 (Supplementary Fig. 2). EH44 was previously demonstrated to yield a PCE of $13.2\\%$ with a stabilized power output (SPO) of $7.9\\%^{30}$ . As this HTM system does not contain $\\mathrm{Li^{+}}$ it could prove a more reliable HTM if the performance can be improved, as demonstrated in this work. \n\n![](images/8baced6b1351fe6a5876a588f068a064e4f87ea5299039b8237bf5cc80d02536.jpg) \nFig. 1 | Champion FAMAs device characterization. Beginning with the general device architecture $\\Gamma_{1}\\bigcirc_{2},$ /FAMACs/HTM/Au, the optimized performance of two HTMs are compared. a, Photograph of a typical device on a $1\\times1$ inch substrate. b,c, Schematic that shows the device architecture of the solar cells $\\mathbf{(6)}$ and false-colour cross-section SEM micrograph of a $\\mathsf{T i O}_{2},$ FAMACs/EH44/Au device (c). As illustrated here, the EH44 HTM layer shows the best performance when thinned to ${\\sim}60\\mathsf{n m}$ . d, Chemical structure of neat EH44. e, Current density–voltage curves for the champion FAMACs perovskite devices that contain either EH44 (yellow) or spiro-OMeTAD (black) as the HTM. f, EQEs have a similar spectral response for the devices with EH44 and spiro-OMeTAD. $\\scriptstyle\\mathbf{g},$ Chemical structure of spiro-OMeTAD. \n\nTo eliminate $\\mathrm{Li^{+}}$ from the device stack, we used EH44, which contains $\\pi$ -conjugated methoxyphenyl groups that enable electronic and charge-transport properties similar to those of spiroOMeTAD, but with fluorene core of the spiro-OMeTAD replaced by a carbazole, which allows for further hydrophobic alkyl functionalization at the N position30. In this study, we used silver bis(trifluoromethanesulfonyl)imide (AgTFSI) to oxidize EH44 and yield $\\mathrm{EH44^{+}T F S I^{-}}$ (termed EH44-ox)30,31. As $\\mathrm{Ag^{0}}$ precipitates during this reaction, EH44-ox is obtained as a purified and isolated material (Supplementary Fig. 2b), which can be blended with neat EH44 in variable ratios to control the conductivity (and optical transparency if desired) and optimize the device performance. We found that the overall device performance was quite sensitive to the EH44 film thickness, concentration of the HTM additive 4-tert-butylpyridine $(\\mathrm{tBP})^{32}$ and the relative amount of EH44-ox (Supplementary Fig. 3 and Supplementary Table 1). \n\nEH44 layers of ${\\sim}60\\mathrm{nm}$ thickness doped with 14wt% EH44-ox and $25\\mathrm{mg}\\mathrm{\\dot{m}l^{-1}}$ tBP show a comparable device performance to spiro-OMeTAD (Fig.  1) and high near-infrared transmission (Supplementary Fig.  2d). The champion $\\mathrm{TiO}_{2}/$ FAMACs/EH44 device had a short-circuit current density $(J_{\\mathrm{SC}})$ of $21.71\\mathrm{mAcm}^{-2}$ , an open-circuit voltage $(V_{\\mathrm{OC}})$ of $1.091\\mathrm{V},$ a fill factor (FF) of 0.779 and a PCE of $18.5\\%$ , whereas the champion device made with spiroOMeTAD had a $J_{\\scriptscriptstyle\\mathrm{SC}}$ of $22.16\\mathrm{mAcm^{-2}}$ , $V_{\\mathrm{OC}}$ of $1.108\\mathrm{V},$ a FF of 0.796 and a PCE of $19.6\\%$ . The EH44 device had a SPO of approximately $17.5\\mathrm{mW}\\mathrm{cm}^{-2}$ $18.5\\mathrm{mW}\\mathrm{cm}^{-2}$ for the spiro-OMeTAD device) when held at a constant bias of $0.90\\mathrm{V}$ under $100\\mathrm{mW}\\mathrm{cm}^{-2}$ AM1.5G illumination (Supplementary Fig. 4). PCEs of $16.8\\%$ were achieved with $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite layers, which demonstrates the flexibility of this HTM for a range of perovskite absorbers (Supplementary Fig. 5). \n\n# Operational stability and burn-in degradation \n\nIn light of the improved hydrophobicity of EH44 relative to LiTFSIdoped spiro-OMeTAD30, we anticipate an improved stability of unencapsulated devices in the presence of atmospheric moisture because of a reduction in the kinetics of moisture-induced degradation mechanisms. To probe the operational stability, ISOS-L-1 (International Summit on Organic Photovoltaic Stability) testing conditions were used33. The ISOS protocols were developed by a broad swathe of the organic photovoltaic community and represent standardized test protocols that are also directly applicable to perovskite solar cell research. The broad use of such standard procedures will facilitate the standardization in degradation testing across the community and enable direct comparisons between laboratories. For these stability measurements, unencapsulated devices were fabricated with a common architecture of $\\mathrm{FTO/TiO}_{2}/$ FAMACs/HTM/Au (FTO, fluorine-doped tin oxide) in which the HTM is either a standard LiTFSI-doped spiro-OMeTAD or EH44. As outlined in the ISOS-L-1 protocols, during testing the devices remained in ambient conditions (Fig. 2) under approximately $77\\%$ of a 1 Sun irradiation (irradiance integrated from $300\\mathrm{nm}$ to $1,650\\mathrm{nm}$ ) using a lamp with a spectrum closely matched to the standard solar spectrum (Supplementary Fig. 6). The devices were held at a static load resistance of $510\\Omega$ ​ and every 30 minutes a current–voltage scan was acquired by sweeping the voltage at ${\\sim}60\\mathrm{mVs^{-1}}$ from forward to reverse bias conditions (reverse sweep). \n\n![](images/c5e23beffd21e197ebdd844df668d2c99343dd970caff5cec2ecf284c84baee1.jpg) \nFig. 2 | Operational stability of $\\Tilde{\\Pi}\\Tilde{\\mathbf{0}}_{z},$ /FAMACs/HTM/Au devices in ambient conditions. Unencapsulated perovskite solar cells of the structure FTO/TiO /FAMACs/HTM/Au, in which the HTM layer is either spiro-OMeTAD (black) or EH44 (yellow), were subjected to continuous operation (resistive load of $510\\Omega,$ in ambient conditions. The initial 1 Sun performance of these devices is shown in Supplementary Table 2. The ambient relative humidity (RH, black, left axis) and room temperature (red, right axis) were monitored during the course of the experiments (top) and the average efficiency obtained as a function of time from seven devices for each HTM is shown with error bars that represent the standard deviation of the devices (bottom). The devices were actively cooled using a circulating bath set to $20^{\\circ}\\mathsf{C}$ with the device surface measuring approximately $30^{\\circ}\\mathsf{C}$ . norm., normalized. \n\n
Table 1l Short- and long-timescale decay kinetics of TiOz-based devices
HTMA1t1 (h)A2T2 (h)
Spiro-OMeTAD0.2061.350.794171
EH440.2051.510.795749
\n\nBiexponential fitting parameters for accelerated degradation of the efficiency in $T i O_{2}/F A M A C s/$ HTM/Au devices. Biexponential fitting equation: norm. power $=A_{1}\\mathrm{exp}(-t/\\tau_{1})+A_{2}\\mathrm{exp}(-t/\\tau_{2})$ . A and $A_{2}$ are coefficients which represent the contribution of each time constant to the normalized biexponential decay. \n\nThe normalized PCE for the devices with spiro-OMeTAD (seven devices, initial $\\mathrm{PCE}{=}17.23{\\pm}0.26\\%)$ and EH44 (seven devices, initial $\\mathrm{PCE}=16.35\\pm0.23\\%)$ is shown in Fig. 2 (Supplementary Table 2 gives the initial 1 Sun performance parameters). All the device parameters recorded during the degradation study, along with representative current density–voltage (JV) scans, are shown in Supplementary Fig. 7. In both cases, the solar cells exhibited a biexponential decay with time constants that represent a rapid initial burn-in $(\\tau_{1})$ followed by a much slower second decay component $(\\tau_{2})$ (Supplementary Fig. 7). During the initial burn-in, the devices showed the loss of $J_{\\mathrm{SC}}$ and FF with similar decay kinetics and magnitude (Table 1). Although the initial burn-in was similar, EH44 led to a factor-of-four improvement in $\\tau_{2}$ from 171 hours with spiro-OMeTAD to 749 hours with EH44, because of the much slower loss of $J_{\\scriptscriptstyle\\mathrm{SC}}$ and also FF. \n\nDevices with both spiro-OMeTAD and EH44 exhibited a burn-in decay of similar magnitude and lifetime, which indicates that the initial decay is not directly related to the HTM, perovskite/HTM interface, LiTFSI migration or the kinetics of moisture ingress. Similar device burn-in was observed in perovskite solar cells of various architectures operated in an inert atmosphere, where it has been ascribed to the migration of A-site cations34, although, as discussed subsequently, this burn-in is dependent on the contact-layer interfaces. \n\nTo better understand compositional changes and ion migration related to the device degradation, we performed time-of-flight secondary ion mass spectrometry (ToF–SIMS) after periodic increments of accelerated degradation (Fig.  3). This technique allows for depth profiling of atomic as well as molecular A-site constituents throughout the device stack. We first performed a ToF–SIMS analysis on pristine $\\mathrm{TiO}_{2}$ -based devices that feature either spiroOMeTAD or EH44 as the HTM with sputtering parameters that are well tested for the investigation of hybrid perovskite thin-films27. We observe no significant difference in the initial profiles that relate to the FAMACs compared to the devices with spiro-OMeTAD and EH44 HTM layer (Supplementary Fig. 8). \n\nToF–SIMS measurements were used to assess the compositional changes in $\\mathrm{TiO_{2}/F A M A C s/H T M/A u}$ devices that had been under continuous operation for 0, 25 and 50 hours, the full results of which are shown in Supplementary Fig.  9. The spiro-OMeTAD devices show dramatic changes at the perovskite/HTM interface which are not present in the EH44 devices and are ascribed to degradation of the PAL; however, there are changes in the EH44-based devices in the component distribution in the PAL during the first 25 hours of operation (Fig. 3c), which do not then modify significantly over the next 25 hours of operation. Operated devices were kept in the dark for 1–2 days before the ToF–SIMS measurements, and thus the changes observed do not appear to be reversible, at least on this timescale. Although we do not observe any marked differences in the distribution of the halides or $\\mathrm{MA^{+}}$ , there is a redistribution of both $\\mathrm{FA^{+}}$ and ${\\mathrm C}s^{+}$ . Most strikingly, the concentration of ${\\mathrm{C}}s^{+}$ throughout the layer stack, except at the FAMACs/HTM interface, is significantly reduced after operation. \n\nThe degradation of $\\mathrm{TiO}_{2}$ -based perovskite solar cells in the presence of ultraviolet illumination is well known35–37. The wider bandgap $\\mathrm{SnO}_{2}$ is demonstrated to result in a dramatically improved stability under illumination, including an ultraviolet component37 and a decreased initial burn- $\\cdot\\mathrm{in}^{34}$ . In contrast to the results obtained on $\\mathrm{TiO}_{2}$ , when these same ToF–SIMS experiments are performed with devices that feature a $\\mathrm{SnO}_{2}$ nanoparticle $\\mathrm{ETL}^{38}$ , we find no evidence for cation redistribution (Fig. 3d). These results suggest that the compositional redistribution of the perovskite layer is closely tied to the burn-in that is often observed in perovskite solar cell degradation, and that the $\\mathrm{SnO}_{2}$ ETL layer utilized in this work can help to preserve the PAL composition under operation and mitigate this burn-in. The initial burn-in of a perovskite solar cell must be minimized  to obtain stable devices at their highest efficiency. Corroborating these findings, X-ray photoemission spectroscopy of FAMACs films before and after 20 hours of uninterrupted $\\mathrm{\\DeltaX}$ -ray exposure identified ${\\mathrm{C}}s^{+}$ as the most mobile component in the PAL and showed that FAMACs films are significantly more robust when on $\\mathrm{SnO}_{2}$ than on $\\mathrm{TiO}_{2}$ substrates (Supplementary Fig. 10). \n\nTo better understand the implications of this redistribution and the differences seen with $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ ETLs on device functionality, we performed external quantum efficiency (EQE) analysis of fresh and operated devices with each ETL (Supplementary Fig. 11). The operated devices with $\\mathrm{TiO}_{2}$ show a decrease, relative to fresh devices, in quantum efficiency at wavelengths shorter than $500\\mathrm{nm}$ , which suggests increased recombination at the $\\mathrm{TiO}_{2}/$ perovskite interface39. On the other hand, the operated devices with $\\mathrm{SnO}_{2}$ show a nearly constant decrease across the spectrum, which indicates that the charge separation at the ETL/perovskite is not affected with $\\mathrm{SnO}_{2}$ as it is with $\\mathrm{TiO}_{2}$ . Combined with the ToF–SIMS results presented in Fig. 3, this correlates the degradation at the $\\mathrm{TiO}_{2}/$ perovskite interface with irreversible cation redistribution in the PAL, which can be mitigated by using $\\mathrm{SnO}_{2}$ . \n\n![](images/01924dcf1b576dd56c8634f626f32fe8c3d696a364ed61f6351acc203a49649f.jpg) \nFig. 3 | ToF–SIMS profiling of operated devices. a, Schematic diagram that shows the measurement protocol for ToF–SIMS. b, ToF–SIMS profiles of a fresh TiO2/FAMACs/EH44/Au device. c,d, Key ToF–SIMS profiles of PAL components measured in fresh and degraded devices of the type $\\Gamma_{1}\\bigcirc_{2^{\\prime}}$ /FAMACs/ EH44/Au $\\mathbf{\\eta}(\\bullet)$ and $\\mathsf{S n O}_{2},$ /FAMACs/EH44/Au (d). a.u., arbitrary units. \n\n# Stable perovskite solar cell architectures \n\nAlthough the second portion of the decay seen in Fig. 2 is at least partially the result of moisture ingress and subsequent PAL degradation, as seen from the marked reduction in decay kinetics with EH44, using ToF–SIMS we also observed that the Au electrode diffuses into the rest of the device stack (Supplementary Fig. 9), which makes it necessary to utilize a different electrode material40,41. As we have previously demonstrated, although $\\mathrm{MoO}_{x}$ does not interface well with the $\\mathrm{PAL^{42}}$ , $\\mathrm{MoO}_{\\scriptscriptstyle x}/\\mathrm{Al}$ electrodes enable a significant stability improvement over Au electrodes while providing a similar $\\mathrm{PCE}^{25,43}$ . The stability of these electrodes is believed to be a result of the self-passivating nature of the aluminium oxide formed at the $\\mathrm{MoO}_{\\mathrm{\\itx}}/\\mathrm{Al}$ interface25. Importantly, the $\\mathrm{MoO}_{x}$ layer does not serve primarily as an encapsulant, because thicker $\\mathrm{MoO}_{x}$ layers lead to a reduced stability25. To enable long-term testing with $\\mathrm{MoO}_{x}/\\mathrm{Al}$ contacts $\\mathrm{15nm~MoO}_{x}$ and $200\\mathrm{nm}$ Al), patterned indium-doped tin oxide (ITO) substrates were used in place of FTO (Supplementary Fig. 12). \n\nDevices of the type $\\mathrm{ETL}/\\mathrm{FAMACs}/\\mathrm{EH44}/\\mathrm{MoO}_{x}/\\mathrm{Al},$ in which the ETL was either $\\mathrm{TiO}_{2}$ or $\\mathrm{SnO}_{2}.$ , were subjected to operational stability tests following ISOS-L-1 test protocols33, analogous to those described in Fig.  2, as shown schematically in Fig.  4a (the initial 1 Sun performance parameters are shown in Supplementary Table 3). A scanning electron microscopy (SEM) cross-section image of a $\\mathrm{SnO_{2}/F A M A C s/E H44/M o O_{{x}}/A l}$ device is shown in Fig. 4b. All the device parameters recorded during the degradation study, along with representative JV scans, are shown in Supplementary Fig. 13. With $\\mathrm{TiO}_{2}$ as the ETL (four devices, initial $\\mathrm{PCE}{=}13.7{\\pm}0.7\\%)$ , replacing Au with $\\mathrm{MoO}_{\\scriptscriptstyle x}/\\mathrm{Al}$ resulted in a similar biexponential decay of the PCE as seen previously, although the overall decay rate was slowed considerably so that the devices took, on average, approximately 300 hours to decay to $80\\%$ of their peak efficiency. These devices remained at $61\\pm4\\%$ of their peak efficiency after 1,000 hours of continuous operation. Replacement of the $\\mathrm{TiO}_{2}$ with $\\mathrm{SnO}_{2}$ allowed for the preservation of the ETL/perovskite interface, and thus the PAL composition, which extended the stability even further (Fig. 4c). Even though these $\\mathrm{SnO}_{2}/\\mathrm{FAMACs}/\\mathrm{EH}44/\\mathrm{MoO}_{x}/$ Al devices (15 devices, initial $\\mathrm{PCE}=12.2\\pm0.1\\%)$ were subjected to continuous operation with no ultraviolet filtering and were held in ambient conditions, they retained, on average, $88\\pm4\\%$ of their peak efficiency after 1,000 hours with the best device retaining over $94\\%$ of its peak efficiency, which compares favourably with some of the best-reported operational stability results achieved in inert atmosphere7,9,10. Both $\\mathrm{SnO_{2}/F A M A C s/E H44/M o O_{{z}}/A l}$ and $\\mathrm{TiO_{2}/F A M A C s/E H44/M o O_{\\it x}/A l}$ devices can readily exceed $16\\%$ PCE (Supplementary Fig.  14). Degradation studies were repeated for a $\\mathrm{SnO_{2}/F A M A C s/E H44/M o O_{\\it x}/A l}$ device with $16.52\\%$ initial PCE which was found to retain over $95\\%$ of its performance after operation under the same test conditions for 500 hours (Supplementary Fig.  15 and Supplementary Table  4), consistent with the results presented in Fig. 4. \n\n![](images/9539d5bafb73ae5af02176659103f24b5f9ff26ba30d201d1dbb0f81ddc3e613.jpg) \nFig. 4 | Operational stability of ETL/FAMACs/EH44/MoOx/Al devices in ambient. a, Schematic that shows the test conditions for the devices, the same as used for Fig. 2. Yellow arrows represent illumination and red and white spheres the oxygen and hydrogen atoms, respectively. b, SEM cross-section image of a $S_{n}O_{2}/F A M A C s/E H44/M o O_{3}/A l$ device. c, The ambient relative humidity and room temperature were monitored during the course of the experiments (top). Normalized average efficiency obtained from current–voltage scans over time (bottom) for devices of the type ETL/FAMACs/EH44/MoOx/Al in which the ETL layer is either $\\mathsf{T i O}_{2}$ (four devices) or $\\mathsf{S n O}_{2}$ (15 devices). The initial 1 Sun performance of these devices is shown in Supplementary Table 3. The champion stability for a $\\mathsf{S n O}_{2}/\\mathsf{F A M A C s}/\\mathsf{E H}44/\\mathsf{M o O}_{x}/\\mathsf{A l}$ device is shown as a black line. The devices were held under a constant resistive load $(510\\Omega)$ and actively cooled using a circulating bath set to $20^{\\circ}\\mathsf{C}$ with the device surface measuring approximately $30^{\\circ}\\mathsf{C}$ . \n\nAlthough the EH44 layers used no longer contain mobile ions, they do contain tBP as an additive. To clarify the role of tBP in the device stability we performed a stability assessment of devices with and without tBP added to the EH44 HTM (Supplementary Fig. 16). We found a near-identical evolution in the normalized $J_{\\mathrm{SC}},\\ V_{\\mathrm{OC}}$ and FF of these devices, which allows us to conclude that tBP in the HTM layer does not have a large effect on stability under these test conditions over the timescales investigated. In tests conducted following ISOS-L-2 protocols33, which include both high temperature $({\\sim}70^{\\circ}\\mathrm{C})$ and humidity (ambient humidity $\\sim50\\%$ , the best unencapsulated $\\mathrm{SnO_{2}/F A M A C s/E H44/M o O_{\\it x}/A l}$ devices retained over $60\\%$ of their initial performance after 100 hours of operation (Supplementary Fig.  17). Further study is required to disentangle fully the effects of humidity and temperature. \n\n# Conclusions \n\nWe demonstrated that perovskite solar cells can be made resilient to external stress factors with carefully adjusted contact layers even without encapsulation, and elucidated the major degradation mechanisms associated with each of the contact layers (ETM, HTM and electrode). For this, we first chose the FAMACs absorber paired with a LiTFSI-free HTM, EH44 (ref. 30). We developed EH44-based devices that can yield PCEs in excess of $18\\%$ and comparable to state-of-the-art spiro-OMeTAD-based perovskite solar cells. We examined compositional changes in the perovskite films in devices with $\\mathrm{TiO}_{2}$ ETMs and demonstrated the mitigation of such effects by replacing this common ETM with $\\mathrm{SnO}_{2}$ . Finally, we utilized $\\mathrm{MoO}_{x}/\\$ Al to reduce the degradation caused by the Au electrode. These changes, from an initial device architecture of $\\mathrm{TiO}_{2}/\\mathrm{FAMACs}/$ spiro-OMeTAD/Au to a final architecture of $\\mathrm{SnO_{2}/F A M A C s/E H44/}$ $\\mathrm{MoO}_{x}/\\mathrm{Al}.$ resulted in devices that are significantly more stable and retained $94\\%$ of their peak power conversion efficiency after 1,000 hours of continuous, unencapsulated ambient operation. We found the majority of the degradation is in the device $V_{\\mathrm{OC}},$ rather than in $J_{\\mathrm{SC}}$ and FF, which suggests that the primary instabilities have moved from the contact interfaces to the PAL and are now dominated by environmental degradation mechanisms, such as $\\mathrm{H}_{2}\\mathrm{O}$ . This conclusion was reinforced by the stability of these devices when these external degradation mechanisms were eliminated. When stability tests were conducted in an inert atmosphere, we found degradation of only ${\\sim}2\\%$ over the course of 1,500 hours of continuous operation (Supplementary Fig. 18). \n\nWe have developed a device architecture that can be utilized more broadly in the future to evaluate the stability of any of the specific components or interfaces (for example, PAL, HTM, electrode and so on) while minimizing complications that arise from instabilities related to the other device layers/interfaces. This work highlights the role of interfaces in perovskite solar cell degradation and demonstrates a path towards the further advances required for their commercial adoption. The ability of these unencapsulated perovskite solar cells to remain largely unchanged for 1,000 hours despite exposure to the combined stresses of ultraviolet light, oxygen and moisture points to a bright future. \n\n# Methods \n\nMaterials. Methylammonium iodide $\\mathrm{(CH_{3}N H_{3}I}$ (MAI)), methylammonium bromide $\\mathrm{'CH_{3}N H_{3}B r}$ (MABr)), formamidinium iodide $\\mathrm{(CH(NH_{2})_{2},}$ (FAI)) and the cobalt complex $\\mathrm{Co}[t{\\mathrm{-BuPyPz}}]_{3}[\\mathrm{TFSI}]_{3}$ (FK209) were purchased from Dyesol and used as received. Lead (ii) iodide $(99.9985\\%$ metals basis) and the $\\mathrm{SnO}_{2}$ colloid precursor $(\\mathrm{Tin}(\\mathrm{IV})$ oxide, $15\\%$ in $\\mathrm{H}_{2}\\mathrm{O}$ colloidal dispersion) were purchased from Alfa Aesar. Spiro-OMeTAD was purchased from Lumtec. 2,7-Dibromocarbazole was provided by A. Paquin and F. Bélanger of PCAS Canada. Bis(4-methoxyphenyl)amine was purchased from TCI America. Catalysts were purchased from Strem Chemicals. All other chemicals were purchased from Sigma-Aldrich and used as received. \n\nSynthesis of EH44. The synthesis of EH44 was carried out following the reaction scheme in Supplementary Fig. 1 as described previously30. Briefly, 2,7-dibromo-9- (2-ethylhexyl)-9H-carbazole (1. $.76\\mathrm{g},4.0\\mathrm{mmol},$ , bis(4-methoxyphenyl)amine $(2.0{\\mathrm{g}},$ $8.8\\mathrm{mmol};$ , sodium $t$ -butoxide $(1.15\\mathrm{g}$ , 12 mmol) and bis(tri-t-butylphosphine) palladium (50 mg, $100\\upmu\\mathrm{mol}\\dot{}$ ) were added to an oven-dried Schlenk flask, degassed by evacuation and refilled with argon three times. Anhydrous 1,4-dioxane was added via a syringe and the reaction was heated to $80^{\\circ}\\mathrm{C}.$ After 24 h the reaction was completed via thin-layer chromatography analysis and was cooled to room temperature, poured into excess deionized water and extracted with ethyl acetate. The organic portions were dried with anhydrous magnesium sulfate, filtered and concentrated by rotary evaporation. The crude reaction mixture was purified using flash chromatography, and concentrated fractions were precipitated in acidic methanol (1–2 drops $5\\%$ HCl in $200\\mathrm{ml}$ of MeOH) to afford a pale-yellow solid $(1.55\\mathrm{g}.$ , $52\\%$ ). Ultraviolet–visible (UV-vis) absorption spectroscopy, $^{1}\\mathrm{H}$ NMR and $^{13}\\mathrm{C}$ NMR spectroscopy, differential scanning calorimetry and matrix-assisted laser desorption/ionization were used to characterize the synthesized product, as published previously30. \n\nPreparation of EH44-ox. Oxidation of EH44 to the oxidized $\\mathrm{EH44^{+}T F S I^{-}}$ salt (EH44-ox) was carried out as described previously30. Briefly, EH44 $\\left(0.40\\mathrm{g}\\right.$ , $54.5\\mathrm{mmol};$ and $(\\mathrm{AgTFSI})$ $(0.25\\mathrm{g}$ 65.4 mmol) were added to a dry Schlenk flask, degassed by evacuation and refilled with argon. Argon sparged dichloromethane (DCM) was added via a syringe and the reaction was stirred at room temperature. After $24\\mathrm{h}$ , the reaction mixture was filtered through a $0.2\\upmu\\mathrm{m}$ pore polytetrafluoroethylene filter. After concentrating with a rotary evaporator, to the remaining solution $200\\mathrm{ml}$ of warm hexanes were added and cooled at $3^{\\circ}\\mathrm{C}$ overnight. The product, a black powder, was collected by filtration, dissolved in warm ethylene glycol and cooled at $3^{\\circ}\\mathrm{C}$ overnight. After filtration, the product was dissolved in DCM and centrifuged for $5\\mathrm{{min}}$ at 5,000 revolutions per minute (r.p.m.) $(3,354g)$ to remove any remaining Ag particles. The decanted solution was concentrated and dried under vacuum at $75^{\\circ}\\mathrm{C}$ overnight to afford a green–black solid $(0.27\\mathrm{g},50\\%$ ). \n\nEH44 characterization. UV–vis absorption spectra were recorded using a Beckman Coulter DU 800 Spectrophotometer. Cyclic voltammetry was performed on a Princeton Applied Research Versatek3 potentiostat in a three-electrode setup with an $\\mathrm{\\Ag/Ag^{+}}$ reference electrode, platinum wire auxiliary electrode and platinum disk working electrode. Measurements were conducted as films on a platinum disk electrode in propylene carbonate with $0.1\\mathrm{M}$ tetrabutylammonium hexafluorophosphate as a supporting electrode, with ferrocene used as the external standard. The voltage sweep rate was $0.1\\mathrm{V}\\mathrm{s}^{-1}$ . \n\nDeposition of electron-transport layer. Patterned FTO glass was cleaned by sonication in acetone and isopropanol, followed by ultraviolet–ozone cleaning for $15\\mathrm{min}$ . A $20{-}40\\mathrm{nm}$ thick compact $\\mathrm{TiO}_{2}$ layer was deposited by spin coating a $0.15\\mathrm{M}$ solution of titanium diisopropoxide bis(acetylacetonate) (TAA) in 1-butanol with the following procedure: $700\\mathrm{r.p.m}$ . for 10 s, $1,000\\mathrm{r.p.m}$ . for 10 s and $2{,}000\\mathrm{r.p.m}$ . for $30s\\mathrm{.}$ . The films were dried at $125^{\\circ}\\mathrm{C}$ for at least 5 min and then a $100{-}150\\mathrm{nmTiO}_{2}$ nanoparticle layer was deposited by spin coating an ethanolic $\\mathrm{TiO}_{2}$ nanoparticle solution (Dyesol 30NR-D diluted at $60\\mathrm{mg}\\mathrm{ml}^{-1}$ in ethanol) using the same spin-coating procedure. The $\\mathrm{TiO}_{2}$ films were then annealed at $500^{\\circ}\\mathrm{C}$ for $\\operatorname{1h}.$ , allowed to cool to room temperature and immersed in a $20\\mathrm{mM}$ aqueous $\\mathrm{TiCl_{4}}$ solution at $90^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . The films were then rinsed with deionized $\\mathrm{H}_{2}\\mathrm{O}$ and annealed at $500^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . The $\\mathrm{TiO}_{2}$ films were cleaned for $15\\mathrm{min}$ by ultraviolet–ozone immediately before use. \n\nFor extended-stability testing, patterned ITO substrates were used to avoid degradation, dramatically observed with $\\mathrm{MoO}_{x}/\\mathrm{Al}$ contacts, induced by layer inhomogeneities that result from the ${>}1.5{\\upmu}\\mathrm{m}$ step edge, introduced during the patterning of typical FTO substrates (Supplementary Fig. 12). The ITO glass was cleaned by the same procedure outlined for the FTO glass. $\\mathrm{TiO}_{2}$ layers were deposited using a low-temperature $\\mathrm{TiO}_{2}$ process44. $\\mathrm{TiO}_{2}$ nanoparticles were synthesized by adding $2\\mathrm{ml}$ of $\\mathrm{TiCl_{4}}$ dropwise to $\\mathrm{8ml}$ of cold ethanol. $40\\mathrm{ml}$ of benzyl alcohol was added to the cold solution causing the solution to change from pale yellow to dark red. The flask was then sealed and heated at $80^{\\circ}\\mathrm{C}$ for $16\\mathrm{h}$ in an oven. Next, $5\\mathrm{ml}$ of the reaction solution was mixed with $40\\mathrm{ml}$ of diethyl ether and the $\\mathrm{TiO}_{2}$ nanoparticles were precipitated by centrifugation. The particles were re-dispersed in ethanol and washed a second time by precipitation with diethyl ether. The resulting $\\mathrm{TiO}_{2}$ was then dried under vacuum. The $\\mathrm{TiO}_{2}$ nanoparticles were dispersed in ethanol at a concentration of $1.18\\mathrm{wt\\%}$ along with $20\\mathrm{mol\\%}$ TAA (based on the concentration of $\\mathrm{TiO}_{2}\\mathrm{,}$ ). This ethanolic $\\mathrm{TiO}_{2}$ suspension was spin cast onto the ITO substrates using the same spin-coating procedure used for the high-temperature $\\mathrm{TiO}_{2}$ films. Tin oxide electron-transport layers were deposited on cleaned ITO substrates38. The aqueous $\\mathrm{SnO}_{2}$ colloid solution, obtained from Alfa Aesar, was diluted to a concentration of $2.67\\mathrm{wt\\%}$ in water, and spin cast at $_{3,000\\mathrm{r.p.m}}$ . for 30 s. Both the $\\mathrm{TiO}_{2}$ and $\\mathrm{SnO}_{2}$ films were then dried at $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ and cleaned for $15\\mathrm{min}$ by ultraviolet–ozone immediately before use. \n\nPerovskite film deposition. Deposition of all the perovskite layers was carried out in a nitrogen glovebox. $\\mathbf{MAPbI}_{3}$ perovskite layers were deposited, as reported elsewhere45, from a precursor solution that contained $461\\mathrm{mg}\\mathrm{PbI}_{2}$ and $159\\mathrm{mg}$ MAI dissolved in $78\\mathrm{mg}$ dimethylsulfoxide (DMSO) (1:1:1 mole ratio) and $600\\mathrm{mg}$ dimethylformamide (DMF). This precursor solution was deposited by spin coating at $^{4,000\\mathrm{rpm}}$ for 25 s. Although the substrate was spinning, $0.5\\mathrm{ml}$ of diethyl ether was rapidly dripped onto the film with approximately 15 s remaining in the spincoating procedure, to form a transparent colourless film, which was then annealed for $3\\mathrm{min}$ at $100^{\\circ}\\mathrm{C}$ to form $\\mathbf{MAPbI}_{3}$ . \n\nTriple cation films of the form $\\mathrm{FA}_{x}\\mathrm{MA}_{y}\\mathrm{Cs}_{1\\ldots y}\\mathrm{Pb}(\\mathrm{I}_{z},\\mathrm{Br}_{1\\ldots})_{3}$ (FAMACs) were formed following a reported method8. The precursor solution was made by dissolving $172\\mathrm{mg}$ FAI, 507 mg $\\mathrm{PbI}_{2}$ , $22.4\\mathrm{mg}$ MABr and $73.4\\mathrm{mg}$ $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ (1:1.1:0.2:0.2 mole ratio) and $40\\upmu\\mathrm{l}$ of CsI stock solution $(1.5\\mathrm{M}$ in DMSO) in $627\\mathrm{mg}$ DMF and $183\\mathrm{mg}\\mathrm{DMSO}$ $\\left(4{:}1\\mathrm{v}/\\mathrm{v}\\right)$ ). The films were deposited by spin coating this precursor solution with the following procedure: $1,000{\\mathrm{r.p.m}}$ . for 10 s, and $6,000\\mathrm{r.p.m}$ . for $20\\mathrm{s}$ Although the substrate was spinning, $0.1\\mathrm{ml}$ of chlorobenzene was rapidly dripped onto the film with approximately 6 s remaining in the spin-coating procedure, to form a transparent orange film. The films were then annealed for 1 h at $100^{\\circ}\\mathrm{C}$ to form highly specular FAMACs perovskite films. \n\nDeposition of hole-transport layer. Spiro-OMeTAD films were deposited from a solution that contained $72\\mathrm{mg}$ spiro-OMeTAD, $28.8\\upmu\\mathrm{l}$ of tBP, $17.5\\upmu\\mathrm{l}$ of a LiTFSI stock solution $(520\\mathrm{mg}\\mathrm{ml^{-1}}$ in acetonitrile) and $29\\upmu\\mathrm{l}$ of a tris(2-(1H-pyrazol-1-yl)- 4-tert-butylpyridine)cobalt(iii)-tris(bis(trifluoromethylsulfonyl)imide) (FK209) stock solution $300\\mathrm{mg}\\mathrm{ml}^{-1}$ in acetonitrile) dissolved in $\\mathrm{1ml}$ of chlorobenzene. \n\nEH44 films were deposited from a solution that contained EH44, EH44-ox and tBP in chlorobenzene. Optimization of the HTM layer was achieved by varying the concentration of $\\mathrm{EH}44+\\mathrm{EH}44-\\mathrm{ox}$ , the volume of tBP added to the solution and \n\nthe ratio of EH44:EH44-ox (Supplementary Fig. 2 and Supplementary Table 1). Optimized EH44 layers were deposited from a solution containing 25.8 mg EH44, $4.2\\mathrm{mg}$ EH44-ox and $25\\upmu\\mathrm{L}$ of tBP dissolved in $\\mathrm{1ml}$ of chlorobenzene. EH44 and spiro-OMeTAD films were deposited on top of the PALs by spin coating at $_{5,000\\mathrm{r.p.m}}$ . for 30 s. \n\nCharacterization. Devices were tested using a Newport Oriel Sol3A solar simulator with a xenon lamp. The intensity of the solar simulator was calibrated to $100\\mathrm{mW}\\mathrm{cm}^{-2}$ AM1.5G using a KG2 filtered NREL-certified mono-Si reference solar cell. JV scans were taken from forward bias to reverse bias with the following scan parameters: step size, $10\\mathrm{mV};$ delay time, $10\\mathrm{ms}$ ; number of power-line cycles, 0.1. The devices were approximately $0.1\\mathrm{cm}^{2}$ and were masked with a metal aperture to define an active area of $0.059\\mathrm{cm}^{2}$ . The SPO of the devices was measured by recording the current output of the illuminated device while holding it at a constant voltage near the maximum power point of the JV scan. EQE measurements were taken using a Newport Oriel IQE200. Scanning electron microscopy was performed on cleaved devices using a FEI Nova NanoSEM 630. X-ray photoemission spectroscopy measurements were performed on a Kratos NOVA spectrometer calibrated to the Fermi edge and core-level positions of sputter-cleaned metal (Au, Ag, Cu and Mo) surfaces. Spectra were taken using monochromated Al Kα​radiation $(1486.7\\mathrm{eV})$ at a resolution of $400\\mathrm{meV}$ (pass energy $10\\mathrm{{eV}}$ ) and fit using pseudo-Voigt profiles. \n\nSecondary ion mass spectrometry (SIMS) is a powerful analytical technique to determine elemental and isotopic distributions in solids, as well as the structure and composition of organic materials46–48. A TOF.SIMS V time-of-flight SIMS spectrometer was utilized to depth profile the perovskite materials and completed devices. Analysis was completed utilizing a three-lens $30\\mathrm{kV}$ BiMn primary ion gun, the $\\mathrm{Bi^{+}}$ primary-ion beam (operated in bunched mode, $10\\mathrm{ns}$ pulse width, analysis current $1.0\\mathrm{pA}\\mathrm{\\cdot}$ ) was scanned over a $25\\times25\\upmu\\mathrm{m}$ area. Depth profiling was accomplished with a 1 kV oxygen-ion sputter beam $(10.8\\mathrm{nA}$ sputter current) raster of are $150\\times150\\upmu\\mathrm{m}$ . During profiling, all the spectra were collected at or below a primary-ion dose density of $1\\times10^{12}$ ions $c\\mathrm{m}^{-2}$ to remain at the static SIMS limit. The data are plotted with the intensity for each signal at each data point normalized to the total ion counts measured at that data point, which diminishes artefacts from a changing ion yield in different layers when profiling through completed devices. \n\nStability testing. For lifetime measurements, unencapsulated solar cells were exposed to constant illumination from a ‘triple A class’ sulfur plasma lamp, Plasma-I AS 1300 Light Engine (http://www.plasma-i.com/plasma-i-products. htm). The intensity of the illumination at the sample was measured to be ${\\sim}77\\mathrm{mW}$ $c\\mathrm{m}^{-2}$ using an NREL-certified (National Renewable Energy Laboratory) mono-Si reference photodiode (without regard to spectral mismatch factors). The lamp spectrum is shown in Supplementary Fig. 6. Each cell was covered by a metal mask with a $0.059\\mathrm{cm}^{2}$ square opening (total active area of the cell was $\\sim0.1\\mathrm{cm}^{2}$ ). Custom-built electronics were used to measure the current–voltage response of the solar cells at $30\\mathrm{min}$ time intervals. Between measurements, the devices were held at a static load of $510\\Omega$ to ensure they remained near their maximum power point. Lifetime studies were carried out in an ambient environment following laboratory test protocols ISOS-L-1 and ISOS-L-2 (ref. 33). An EXTECH Instruments RH520A humidity and temperature recorder recorded the relative humidity and room temperature during device operation. Samples were actively cooled by contact with underlying copper tubing filled with water circulated by a chiller set to $20^{\\circ}\\mathrm{C}$ , with the device surface under test measuring approximately $30^{\\circ}\\mathrm{C}$ For high-temperature measurements, the water circulated at a set point of $65^{\\circ}\\mathrm{C}.$ with the device surface under test measuring approximately $70^{\\circ}\\mathrm{C}$ . Throughout the article, devices fabricated in the same batch are used for a direct comparison and were measured concurrently to control for test humidity, light intensity and PAL stoichiometry. Devices fabricated in different batches and measured at different times showed results consistent with those presented (Supplementary Table 4). \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding author on reasonable request. \n\nReceived: 18 May 2017; Accepted: 28 November 2017; Published online: 9 January 2018 \n\n# References \n\n1.\t Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n2.\t Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. \n131, 6050–6051 (2009). \n3.\t Manser, J. S., Christians, J. A. & Kamat, P. V. Intriguing optoelectronic properties of metal halide perovskites. Chem. Rev. 116, 12956–13008 (2016). \n4.\t Best Research Cell Efficiences (NREL, 2017); https://www.nrel.gov/pv/assets/ images/efficiency-chart.png Making and breaking of lead halide perovskites. Acc. Chem. Res. 49, 330–338 (2016). \n6. Habisreutinger, S. N., McMeekin, D. P., Snaith, H. J. & Nicholas, R. J. Research update: strategies for improving the stability of perovskite solar cells. APL Mater. 4, 91503 (2016). \n7. Tan, H. et al. Efficient and stable solution-processed planar perovskite solar cells via contact passivation. Science 355, 722–726 (2017). \n8.\t Saliba, M. et al. Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency. Energy Environ. Sci. 9, 1989–1997 (2016). \n9.\t Shin, S. S. et al. Colloidally prepared La-doped ${\\mathrm{BaSnO}}_{3}$ electrodes for efficient, photostable perovskite solar cells. Science 356, 167–171 (2017). \n10.\tSaliba, M. et al. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). \n11.\tDualeh, A., Gao, P., Seok, S. Il, Nazeeruddin, M. K. & Grätzel, M. Thermal behavior of methylammonium lead-trihalide perovskite photovoltaic light harvesters. Chem. Mater. 26, 6160–6164 (2014). \n12.\tNenon, D. et al. Structural and chemical evolution of methylammonium lead halide perovskites during thermal processing from solution. Energy Environ. Sci. 9, 2072–2082 (2016). \n13.\tConings, B. et al. Intrinsic thermal instability of methylammonium lead trihalide perovskite. Adv. Energy Mater. 5, 1500477 (2015). \n14.\tChristians, J. A., Miranda Herrera, P. A. & Kamat, P. V. Transformation of the excited state and photovoltaic efficiency of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite upon controlled exposure to humidified air. J. Am. Chem. Soc. 137, 1530–1538 (2015). \n15.\t Yang, J., Siempelkamp, B. D., Liu, D. & Kelly, T. L. An investigation of $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ degradation rates and mechanisms in controlled humidity environments using in situ techniques. ACS Nano 9, 1955–1963 (2015). \n16.\tAristidou, N. et al. Fast oxygen diffusion and iodide defects mediate oxygen-induced degradation of perovskite solar cells. Nat. Commun. 8, 15218 (2017). \n17.\tHoye, R. L. Z. et al. Perovskite-inspired photovoltaic materials: toward best practices in materials characterization and calculations. Chem. Mater. 29, 1964–1988 (2017). \n18.\tSteirer, K. X. et al. Defect tolerance in methylammonium lead triiodide perovskite. ACS Energy Lett. 1, 360–366 (2016). \n19.\tLi, Z. et al. Stabilizing perovskite structures by tuning tolerance factor: formation of formamidinium and cesium lead iodide solid-state alloys. Chem. Mater. 28, 284–292 (2016). \n20.\tSutton, R. J. et al. Bandgap-tunable cesium lead halide perovskites with high thermal stability for efficient solar cells. Adv. Energy Mater. 6, 1502458 (2016). \n21.\tSwarnkar, A. et al. Quantum dot-induced phase stabilization of $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{(.}}\\mathbf{{c}}\\mathbf{{s}}\\mathbf{{Pb}}\\mathbf{{I}}_{3}}}$ perovskite for high-efficiency photovoltaics. Science 354, 92–95 (2016). \n22.\tMcMeekin, D. P. et al. A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells. Science 351, 151–155 (2016). \n23.\tWang, Z. et al. Efficient ambient-air-stable solar cells with 2D–3D heterostructured butylammonium-caesium-formamidinium lead halide perovskites. Nat. Energy 6, 17135 (2017). \n24.\tManspeaker, C., Venkatesan, S., Zakhidov, A. & Martirosyan, K. S. Role of interface in stability of perovskite solar cells. Curr. Opin. Chem. Eng. 15, 1–7 (2017). \n25.\tSanehira, E. M. et al. Influence of electrode interfaces on the stability of perovskite solar cells: reduced degradation using MoOx/Al for hole collection. ACS Energy Lett. 1, 38–45 (2016). \n26.\tZhao, L. et al. Redox chemistry dominates the degradation and decomposition of metal halide perovskite optoelectronic devices. ACS Energy Lett. 1, 595–602 (2016). \n27.\tLi, Z. et al. Extrinsic ion migration in perovskite solar cells. Energy Environ. Sci. 10, 1234–1242 (2017). \n28.\tDawson, J. A. et al. Mechanisms of lithium intercalation and conversion processes in organic–inorganic halide perovskites. ACS Energy Lett. 2, 1818–1824 (2017). \n29.\tHabisreutinger, S. N. et al. Carbon nanotube/polymer composite as a highly stable charge collection layer in perovskite solar cells. Nano Lett. 14, 5561–5568 (2014). \n30.\tLeijtens, T. et al. Hydrophobic organic hole transporters for improved moisture resistance in metal halide perovskite solar cells. Appl. Mater. Interfaces 8, 5981–5989 (2016). \n31.\tNguyen, W. H., Bailie, C. D., Unger, E. L. & McGehee, M. D. Enhancing the hole-conductivity of spiro-OMeTAD without oxygen or lithium salts by using spiro $\\left(\\mathrm{TFSI}\\right)_{2}$ in perovskite and dye-sensitized solar cells. J. Am. Chem. Soc. 136, 10996–11001 (2014). \n32.\t Habisreutinger, S. N., Noel, N. K., Snaith, H. J. & Nicholas, R. J. Investigating the role of 4-tert-butylpyridine in perovskite solar cells. Adv. Energy Mater. 7, 1601079 (2016). \n33.\tReese, M. O. et al. Consensus stability testing protocols for organic photovoltaic materials and devices. Sol. Energy Mater. Sol. Cells 95, 1253–1267 (2011). \n34.\tDomanski, K. et al. Migration of cations induces reversible performance losses over day/night cycling in perovskite solar cells. Energy Environ. Sci. 10, 604–613 (2017). \n35.\tLeijtens, T. et al. Overcoming ultraviolet light instability of sensitized $\\mathrm{TiO}_{2}$ with meso-superstructured organometal tri-halide perovskite solar cells. Nat. Commun. 4, 2885 (2013). \n36.\tAhn, N. et al. Trapped charge-driven degradation of perovskite solar cells. Nat. Commun. 7, 13422 (2016). \n37.\tRoose, B. et al. Mesoporous $\\mathrm{SnO}_{2}$ electron selective contact enables UV-stable perovskite solar cells. Nano Energy 30, 517–522 (2016). \n38.\tJiang, Q. et al. Enhanced electron extraction using $\\mathrm{SnO}_{2}$ for high-efficiency planar-structure $\\mathrm{HC(NH_{2})_{2}P b I_{3}}$ -based perovskite solar cells. Nat. Energy 2, 16177 (2016). \n39.\tIhly, R. et al. Efficient charge extraction and slow recombination in organic–inorganic perovskites capped with semiconducting single-walled carbon nanotubes. Energy Environ. Sci. 9, 1439–1449 (2016). \n40.\tDomanski, K. et al. Not all that glitters is gold: metal-migration-induced degradation in perovskite solar cells. ACS Nano 10, 6306–6314 (2016). \n41.\tCacovich, S. et al. Gold and iodine diffusion in large area perovskite solar cells under illumination. Nanoscale 9, 4700–4706 (2017). \n42.\tSchulz, P. et al. High work function molybdenum oxide hole extraction contacts in hybrid organic–inorganic perovskite solar cells. ACS Appl. Mater. Interfaces 8, 31491–31499 (2016). \n43.\tZhao, Y., Nardes, A. M. & Zhu, K. Effective hole extraction using $\\mathrm{MoO}_{x}.$ –Al contact in perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ solar cells. Appl. Phys. Lett. 104, 213906 (2014). \n44.\t Wojciechowski, K., Saliba, M., Leijtens, T., Abate, A. & Snaith, H. J. Sub- $150^{\\circ}\\mathrm{C}$ processed meso-superstructured perovskite solar cells with enhanced efficiency. Energy Environ. Sci. 7, 1142–1147 (2014). \n45.\tAhn, N. et al. Highly reproducible perovskite solar cells with average efficiency of $18.3\\%$ and best efficiency of $19.7\\%$ fabricated via Lewis base adduct of lead(ii) iodide. J. Am. Chem. Soc. 137, 8696–8699 (2015). \n46.\tDe Souza, R. A. & Martin, M. Probing diffusion kinetics with secondary ion mass spectrometry. MRS. Bull. 34, 907–914 (2009). \n47.\tStevie, F. A. Secondary Ion Mass Spectrometry: Applications for Depth Profiling and Surface Characterization (Momentum, London, 2015). \n48.\tWilson, R. G., Stevie, F. A. & Magee, C. W. Secondary Ion Mass Spectrometry: a Practical Handbook for Depth Profiling and Bulk Impurity Analysis (Wiley-Interscience, Hoboken, NJ, 1989). \n\n# Acknowledgements \n\nThis work was supported by the Hybrid Perovskite Solar Cell Program, and B.T.V. was supported by the Organic Photovoltaic Program, which are funded by the US Department of Energy (DOE) under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory through the US DOE Solar Energy Technologies Program. J.A.C. was supported by the DOE Office of Energy Efficiency and Renewable Energy (EERE) Postdoctoral Research Award through the Solar Energy Technologies Office under DOE contract number DE-SC00014664. We thank B. To for the SEM imaging, A. Hicks for assistance with the graphics, and A. Paquin and F. Bélanger of PCAS Canada for supplying 2,7-dibromocarbazole as a precursor for the synthesis of the EH44 HTM used in this study. \n\n# Author Contributions \n\nJ.A.C, J.M.L. and J.J.B. conceived the project. J.A.C. fabricated the devices and thin-film samples. P.S. designed and performed the photoemission experiments and analysed the data. J.S.T. and T.H.S. synthesized and characterized EH44, and A.S. supervised. J.A.C. and B.J.T.V. performed the stability experiments. S.P.H. performed the ToF–SIMS measurements and S.P.H., J.A.C. and P.S. analysed the ToF–SIMS data. J.M.L. supervised the entire project. J.A.C. wrote the first draft of the paper. All the authors discussed the results and contributed to the writing of the paper. \n\n# Competing interests \n\nThe authors declare no competing financial interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-017-0067-y. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to J.J.B. or J.M.L. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1021_acsenergylett.8b00035", + "DOI": "10.1021/acsenergylett.8b00035", + "DOI Link": "http://dx.doi.org/10.1021/acsenergylett.8b00035", + "Relative Dir Path": "mds/10.1021_acsenergylett.8b00035", + "Article Title": "Colloidal CsPbX3 (X = CI, Br, I) nullocrystals 2.0: Zwitterionic Capping Ligands for Improved Durability and Stability", + "Authors": "Krieg, F; Ochsenbein, ST; Yakunin, S; ten Brinck, S; Aellen, P; Suess, A; Clerc, B; Guggisberg, D; Nazarenko, O; Shynkarenko, Y; Kumar, S; Shih, CJ; Infante, I; Kovalenko, MV", + "Source Title": "ACS ENERGY LETTERS", + "Abstract": "Colloidal lead halide perovskite nullocrystals (NCs) have recently emerged as versatile photonic sources. Their processing and optoelectronic applications are hampered by the loss of colloidal stability and structural integrity due to the facile desorption of surface capping molecules during isolation and purification. To address this issue, herein, we propose a new ligand capping strategy utilizing common and inexpensive long-chain zwitterionic molecules such as 3-(N,N-dimethyloctadecylammonio)propanesulfonate, resulting in much improved chemical durability. In particular, this class of ligands allows for the isolation of clean NCs with high photoluminescence quantum yields (PL QYs) of above 90% after four rounds of precipitation/redispersion along with much higher overall reaction yields of uniform and colloidal dispersible NCs. Densely packed films of these NCs exhibit high PL QY values and effective charge transport. Consequently, they exhibit photoconductivity and low thresholds for amplified spontaneous emission of 2 mu J cm(-2) under femtosecond optical excitation and are suited for efficient light-emitting diodes.", + "Times Cited, WoS Core": 715, + "Times Cited, All Databases": 753, + "Publication Year": 2018, + "Research Areas": "Chemistry; Electrochemistry; Energy & Fuels; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000427444300021", + "Markdown": "# Colloidal CsPbX3 $(X=C l$ , Br, I) Nanocrystals 2.0: Zwitterionic Capping Ligands for Improved Durability and Stability \n\nFranziska Krieg, Stefan Ochsenbein, Sergii Yakunin, Stephanie ten Brinck, Philipp Aellen, Adrian Süess, Baptiste Clerc, Dominic Guggisberg, Olga Nazarenko, Yevhen Shynkarenko, SUDHIR KUMAR, Chih-Jen Shih, Ivan Infante, and Maksym V. Kovalenko \n\nACS Energy Lett., Just Accepted Manuscript $\\cdot$ DOI: 10.1021/acsenergylett.8b00035 $\\cdot$ Publication Date (Web): 09 Feb 2018 Downloaded from http://pubs.acs.org on February 10, 2018 \n\n# Just Accepted \n\n“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier $(\\mathsf{D O}|\\oplus)$ . “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts. \n\n# Colloidal $\\mathbf{Cs}\\mathbf{Pb}\\mathbf{X}_{3}$ $\\mathbf{\\sigma}(\\mathbf{X}\\mathbf{=}\\mathbf{Cl}$ , Br, I) Nanocrystals 2.0: Zwitterionic Capping Ligands for Improved Durability and Stability \n\nFranziska Krieg,†,‡ Stefan T. Ochsenbein,†,‡ Sergii Yakunin,†,‡ Stephanie ten Brinck,# Philipp Aellen,†,‡ Adrian Süess,†,‡ Baptiste Clerc,†,‡ Dominic Guggisberg,†,‡ Olga Nazarenko,†,‡ Yevhen Shynkarenko,†,‡ Sudhir Kumar,¥ Chih-Jen Shih,¥ Ivan Infante, # and Maksym V. Kovalenko†,‡\\* \n\n† Institute of Inorganic Chemistry, Department of Chemistry and Applied Bioscience, ETH Zürich, Vladimir Prelog \nWeg 1, CH-8093 Zürich, Switzerland \n‡ Laboratory for Thin Films and Photovoltaics, Empa – Swiss Federal Laboratories for Materials Science and \nTechnology, Überlandstrasse 129, CH-8600 Dübendorf, Switzerland \n¥Institute of Chemical and Bioengineering, Department of Chemistry and Applied Bioscience, ETH Zürich, Vladimir \nPrelog Weg 1, CH-8093 Zürich, Switzerland \n#Department of Theoretical Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, de Boelelaan 1083, 1081 HV \nAmsterdam, The Netherlands \n\n\\*mvkovalenko@ethz.ch Supporting Information Placeholder \n\nABSTRACT: Colloidal lead halide perovskite nanocrystals (NCs) have recently emerged as versatile photonic sources. Their processing and optoelectronic applications are hampered by the loss of colloidal stability and structural integrity due to the facile desorption of surface capping molecules during isolation and purification. To address this issue, herein, we propose a new ligand capping strategy utilizing common and inexpensive long-chain zwitterionic molecules such as $_3$ -(N,Ndimethyloctadecylammonio) propanesulfonate, resulting in much improved chemical durability. In particular, this class of ligands allows for the isolation of clean NCs with high photoluminescence quantum yields (PL QY) of above $90\\%$ after 4 rounds of precipitation/redispersion along with much higher overall reaction yields of uniform and colloidal dispersible NCs. Densely packed films of these NCs exhibit high PL QY values and effective charge transport. Consequently, they exhibit photoconductivity and low thresholds for amplified spontaneous emission of $2\\ \\upmu\\mathrm{J}\\ \\mathrm{cm}^{-2}$ under femtosecond optical excitation and are suited for efficient light-emitting diodes. \n\n![](images/cc392c38b9926a37206944ad6ed061f48a59acb352b5c741f484faf57f21bc05.jpg) \n\nSemiconducting lead halides with the perovskite crystal structure, recently known as photovoltaic materials showing power conversion efficiencies exceeding $22\\%,$ also hold great promise as versatile photonic sources in the form of colloidal nanocrystals (NCs). Fully inorganic $\\mathsf{C s P b X}_{3}$ $\\scriptstyle(\\mathrm{X=Cl}$ , Br, or I, or a mixture thereof) have become popular choices owing to their chemical stability and broadly tunable photoluminescence (PL $,400\\mathrm{-}700\\mathrm{nm},$ ), small PL full-width at half-maxima (FWHM, 12–40 nm for blue-to-red), and high PL quantum yields $(\\mathrm{QYs}{=}50{-}90\\%)$ .3-4 Their intrinsic defecttolerance,5-6 i.e., the rather benign nature of surfaces with respect to PL efficiency, is a particularly important asset for employing these NCs in displays,7 light-emitting diodes8-13 and potentially in lasers.14-15 \n\nA highly pressing challenge related to organic-inorganic interfaces was identified in the early days of $\\mathsf{C s P b X}_{3}$ NCs. Highly dynamic binding exists between the surface capping ligands, typically a pair consisting of an anion $\\mathrm{\\cdot}\\mathrm{Br}^{-}$ or oleate, OA-) and a cation (oleylammonium, $\\mathrm{OLAH^{+}}$ ), and the oppositely charged NC surface ions (Scheme 1a).3, 16 Together with a mutual equilibrium between the ionized and molecular forms of these ligands $(\\mathrm{OA}^{-}+\\mathrm{OLAH}^{+}\\leftrightarrow\\mathrm{OLA}+$ OAH or $\\mathrm{OLAH^{+}+B r\\Sigma^{-}\\leftrightarrows O L A+H B r}$ , Scheme 1a), these dynamics cause the rapid desorption of the protective ligand shell upon the isolation and purification of colloids, which is practically observed as a loss of colloidal stability and a rapid decrease in PL QY. This eventually also leads to the loss of structural integrity; i.e., the sintering of NCs into bulk polycrystalline materials. Thus far the strategies to address such problems included embedding of NCs into a solid matrix7, 9, 17-24 or using molecular additives in colloidal solutions of NCs.25-29 \n\nIn this work, we present a general approach for the efficient surface ligand capping of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs, using zwitterionic long-chain molecules, which are readily available commercially (i.e., sulfobetaines, phosphocholines, $\\gamma\\cdot$ -amino acids, etc., Scheme 1b). For instance, $_3\\cdot$ -(N,Ndimethyloctadecylammonio)propane- sulfonate is a longchain sulfobetaine, broadly used as a low-cost detergent in, for example, shower gels, protein isolation, and antibacterial coatings. There are two major structural differences with respect to conventional carboxylate and ammonium capping ligands (e.g., ${\\mathrm{OLA}}{+}{\\mathrm{OAH}},$ ), both favoring stronger adhesion to the NC surface. Firstly, the cationic and anionic groups have no possibility of mutual or external neutralization by Brønsted acid-base equilibria. Secondly, the binding to the NC surface is kinetically stabilized by the chelate effect.30 In agreement to this argument, one can explain also an effective bi-carboxylate binding reported recently by Bakr et al. for CsPbI3 NCs.29 \n\n![](images/1699d37ae0de5536c537ce9fdc05f704d9e23866072c2368eb53d34537273de4.jpg) \n\nScheme 1. (a) Depiction of conventional ligand capping of perovskite NCs using long-chain molecules with single head groups, in the ionized form (OA- or Br-, OLAH+). The net effect of two possible sets of equilibria is a facile ligand desorption during purification. (b) A novel strategy, wherein cationic and anionic groups are combined in a single zwitterionic molecule. Examples of long-chain sulfobetaines, phosphocholines and γ-amino acids tested in this work are depicted left to right $\\scriptstyle(\\mathrm{n=1})$ : $_3$ -(N,Ndimethyloctadecylammonio) propanesulfonate, N-hexadecylphosphocholine and N,N-dimethyldodecylammoniumbutyrate. \n\nIn the proof-of-principle experiment, we fully replaced the OAH and OLA by a zwitterionic ligand (Figures 1a and b; see detailed methods in the Supporting Information and related Figures $\\mathrm{S}_{1}{-}\\mathrm{S}_{7}$ ). In a typical synthesis of 10-nm $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs, cesium $^2$ -ethylhexanoate (0.2 mmol), lead(II) 2- ethylhexanoate (0.24 mmol), and $_{3^{-}}(N,N-$ dimethyloctadecylammonio) propanesulfonate (0.1 mmol, ligand) were combined in dried mesitylene $({\\sim}6~\\mathrm{mL})$ and heated to 130 $^{\\circ}C$ under inert gas. At this point, trioctylphosphine- ${\\bf B r}_{2}$ adduct $\\mathrm{\\TOP-Br}_{2}$ , 0.3 mmol) dissolved in toluene $\\mathrm{(o.5~mL)}$ was injected into the reaction mixture, which was then immediately cooled. The crude solution was centrifuged to remove insolubles (if any) and mixed with ethyl acetate $\\left({\\bf{12}}\\ \\mathrm{~mL}\\right)$ to precipitate NCs. The NCs were isolated by centrifuging, redispersed in toluene $(_{3}~\\mathrm{mL})$ and centrifuged again to remove a fraction of larger NCs (below $10\\%$ by weight; if any). Afterwards, higher purity could be attained without the loss of structural integrity and high PL QY could be retained by repeatedly (i.e., up to $^3$ more times) adding a non-solvent (e.g., $6~\\mathrm{mL}$ of ethyl acetate, $3~\\mathrm{mL}$ of acetone, or $\\mathbf{\\Omega_{1}}~\\mathrm{mL}$ of acetonitrile), centrifuging the mixture, and redispersing the precipitate in toluene $(3~\\mathrm{\\mL})$ . In contrast, conventional OA/OLA-capped $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs fully transform into poorly luminescent bulk material upon analogous washing. Zwitterionic-ligand-capped $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs can form much more concentrated colloids (up to 50–100 $\\mathrm{mg/mL})$ ) than their OA/OLA-capped counterparts. Furthermore, the typical synthesis yield of clean dispersible $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs is ca. $80\\%$ compared to only $10\\mathrm{-}20\\%$ for rather impure NCs prepared with the conventional OA/OLAcapping. The obtained $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs showed a phase-pure orthorhombic crystal structure, identical to NCs received by the OA/OLA synthesis3, 31-32 (Pnma space group, see powder Xray diffraction patterns in Figure S4). The mass fraction of organic ligands was estimated to be ca. $11\\%$ using thermogravimetric analysis (Figure $S_{5}\\mathrm{\\overline{{{\\Omega}}}}$ ), corresponding to a ligand density of $c a.1.7\\mathrm{nm}^{-2}$ (for 11-nm NCs). \n\nSolution nuclear magnetic resonance (NMR) spectra were acquired at various stages of the purification, confirming the formation of $\\mathsf{R}_{3}\\mathsf{P}(\\mathrm{OOCR})_{2}$ [trioctyl- $\\cdot\\lambda^{5}.$ -phosphanediyl bis(2- ethylhexanoate), Figure S6] and the complete removal of the (Figure $S_{7}$ ). Since solution NMR fails to accurately resolve the resonances attributed to surface-immobilized ligand molecules because the slow tumbling of NCs in solution results in significant signal broadening, the purified NCs were decomposed to liberate the ligands by their complete ionic dissolution in deuterated dimethyl sulfoxide (DMSO$\\mathsf{d}^{6})$ . The NMR spectra of the resulting solution point to the zwitterionic ligand as the sole surface-bound species (Figure $S_{7}\\mathrm{\\overline{{{\\Omega}}}}$ ).Analogous findings on the preferential and exclusive binding of sulfobetaine and on colloidal durability were obtained when $^{2}$ -ethylhexanoate was replaced with the oleate in the synthesis (Figure S8). We also tested halide sources such as oleylammonium bromide (OLAHBr) as alternatives to $\\mathrm{TOP\\mathrm{-}B r}_{2}$ . The OLA was found as a co-ligand at the surface (Figure S9), presumably in the form of OLAHBr. The sulfobetaine-to-OLA ratio was ca. 1.5. Diffusion-ordered NMR spectroscopy (DOSY NMR, Table S2), which probes the diffusion speed of the detected molecules, estimated that the diffusion coefficients for the broad resonances obtained from the zwitterionic ligand were nearly identical to the value independently calculated using the Einstein-Stokes equation for the actual size of the NCs (i.e., 5.17 vs. 4.99 10 $^{-11}\\mathrm{m}^{2}/\\mathbf{s}$ for the $\\mathrm{\\mathbf{u}}\\mathrm{\\mathbf{m}}\\ \\mathrm{N}\\mathrm{Cs},$ ). The motion of a free ligand molecule, on contrary, is two orders of magnitude faster (Table S2).The photophysical qualities (i.e., PL QYs, PL FWHM and PL lifetimes) of the sulfobetaine-capped $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs were commensurate with those of standard OLA-OA-capped NCs. (See Figure 1c for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs, Figure S10 for time resolved PL and Figures S11-12 for chlorides and iodides). The utility of other zwitterionic ligands—phosphocholines and $\\gamma\\mathrm{.}$ -amino acids—is illustrated in Figure S13. The decisive role of zwitterionic surface capping for improving the chemical durability33 of perovskite NCs can be illustrated by a comprehensive study relating the optical characteristics, foremost the PL QYs, to the variation in the number of washing steps, solvents, and aging period; see Figures 1d, S14- 15, and additional discussions and details in the Supporting Information. The retention of PL QYs above $60\\%$ for the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs was considered a benchmark for stability. Briefly, standard OLA/OA-capped NCs exhibited such PL QYs $(\\sim8\\mathrm{o\\%})$ only when the number of washing steps did not exceed two and only for one antisolvent: ethyl acetate. Even in this best case, the PL QY dropped to ca. $20\\%$ after 28 days of storage under ambient conditions. On contrary, the sulfobetaine-capped $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs, washed twice with ethyl acetate, acetone, or acetonitrile as antisolvents, retained PL QYs in the range $70\\mathrm{-}90\\%$ for $28\\mathrm{-}50$ days. These NCs could even moderately tolerate washing with alcohol (i.e., ethanol), showing a PL QY of $65\\%$ after 2 washings and ca. $40\\%$ after 28 days. The absorption and PL spectra as well as PL lifetimes of the zwitterionic-capped NCs remained largely unchanged during intense washing for up to $^4$ times (Figure S16). \n\n![](images/38aeb73a0ac315ca0784081672ec29b5f47ea76d0627867c878f0e28f358bb73.jpg) \nFigure1. Synthesis of zwitterionic-capped $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ NCs, exemplified for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ : (a) reaction equation, (b) typical TEM images of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs, (c) absorbance and emission spectra, (d) QY of NCs covered with the $^3$ -(N,N-dimethyloctadecylammonio) propanesulfonate and OA/OLA after two steps of purification on day 1 and after storage for 28 days. \n\nBy means of density functional theory (DFT), we analyzed the passivation of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}_{3}}$ NCs capped with $\\mathrm{OLAH^{+}B r}^{-}$ , $\\mathrm{OLAH^{+}O A^{-}}$ , and $C_{3}$ -sulfobetaine (Figure 2). The details on the methodology employed are provided in the Supporting Information. All the relaxed species comfortably fit the perovskite crystal structure, with the ammonium group in the ${\\mathrm{OLAH}}^{+}{\\mathrm{Br}}^{-}$ and $\\mathrm{OLAH^{+}O A^{-}}$ engaging in hydrogen bond interactions with the corresponding anion.34 Remarkably, the dimethyl ammonium group of the zwitterion, which can be expected as rather bulky, also can be easily accommodated in a cation site at the surface. For all species, the binding energy was computed to be ca. $40{-}45\\ \\mathrm{kcal/mol}\\$ , suggesting a good affinity of all the ion pairs to the surface. However, there is no substantial energetic difference between the conventional and zwitterionic passivation. This supports the theory proposed earlier in the introduction that the experimentally observed improvements are due to the chelate effect. We also analyzed the electronic structure to verify whether the different kinds of passivation could lead to the formation of localized surface states. For all cases, the bandgap of the perovskite remained intact and free of midgap states. The HOMO-LUMO levels of the ligands used were calculated and found to reside within the valence band and conduction band, respectively (Figure S17). \n\n![](images/9773430b7b25d45fed4a1cfcb8bfabfdbac9c9d9105f0e78e3317a811b5cd575.jpg) \nFigure 2. Top and side views of a binding site in a model $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NC $({\\sim}3~\\mathrm{nm})$ computed at the DFT/PBE level of theory35, using the CP2k software package.36 All structures have been fully relaxed. Cs atoms are drawn in grey, Pb in orange, Br in magenta, N in blue, C in light blue, O in red, S in yellow, and H in white. The binding site is circled in white for different ligands: (from left to right) the conventional ligands $\\mathrm{OLAH^{+}B r}$ and $\\mathrm{OLAH^{+}O A^{-}}$ and the zwitterionic $C_{3}$ -sulfobetaine. For computational advantage, the ${\\mathrm{OLAH}}^{+}$ is replaced by methylammonium, the OA- by acetate, and the side chain in the zwitterion by a butyl group. At the bottom, the electronic structure of each NC is shown by depicting the molecular orbitals (MOs) close to the valence and conduction bands. The contribution of each atom type to a given MO is represented with a different a color (Cs in grey, Pb in orange, and Br in magenta). In this plot, the contribution from the ligands is negligible compared to the full NC due the large number of MOs of the latter. In Figure S17 we, however, illustrate the relative energy alignment of the NC versus the frontier orbitals of the ligands. \n\nInterestingly, the spacing between the cationic and anionic head groups of the sulfobetaines; namely, three or four carbon atoms, has observable experimental effects. The $C_{3}$ - sulfobetaines were better suited for the synthesis of the Cland Br-containing perovskites, while their $\\mathrm{C}_{4}$ -counterparts performed better for synthesizing the iodides, presumably owing to the larger cation-anion distances at the NC surface. This comparison held true for both the oleyl and octadecyl side chains; see the discussion in the Supporting Information and Figures S12-13. \n\nA major and very typical issue for $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NCs is facile room-temperature sintering, which quickly renders the material polycrystalline and non-luminescent.37 In contrast, zwitterionic-capped $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ in the form of thin, denselypacked films retains in the range $70\\mathrm{-}80\\%$ of the solution PL QY values and almost $60\\%$ of the initial QY in films stored under ambient conditions is retained even after 10 months. The retention of the quantum confinement in the thin films and the absence of sintering are apparent from the optical absorption spectra (Figure S18). Strong coupling between neighboring NCs facilitates exciton-exciton interactions, enabling multiexciton processes, which favor optical gain in the compact NC medium. When the optical pumping levels substantially exceed one exciton per NC, the population inversion of biexcitonic states is observed as an emergence of an amplified spontaneous emission band (ASE, Figure 3a). The ASE threshold of $2\\ {\\upmu}\\ {\\mathrm{cm}}^{-2}$ (with 100-fs pulses, Figure 3b) is one of the lowest values reported for solution-processed NC films.14, 38-41 \n\nDense NC packing and hence improved electronic coupling enable the observation of photoconductivity. In $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ NC films, the photoresponsivity spectrum closely resembles the optical absorption spectrum, with typical responsivities $(R)$ of about $\\mathbf{0.5\\A/W}$ (Figure 3c). Hence, a photoconductive gain close to unity can be estimated (from $G=R\\cdot h\\nu\\cdot e^{-1}$ , where $h\\nu$ and $e$ are the photon energy and electron charge, respectively). This finding is corroborated by the observation of high PL QYs in these films. $G{>}1$ can be expected only in the presence of secondary, i.e., trap-assisted, photocurrent. The photocurrent vs. bias dependence shows saturation above 30–40 V (Figure $3\\mathrm{d},$ ), indicating efficient charge collection. The apparently trap-free photoconductivity is also revealed in the linearity of the photocurrent vs. incident light intensity plot (at least over 3 orders of magnitude in the intensity) and in the relatively large bandwidth of about 90 $\\mathrm{Hz}$ (Figure S19). \n\nEfficient charge transport and high PL QYs are required characteristics for the eventual use of perovskite NC films in light-emitting diodes (LEDs). To assess the potential of the sulfobetaine-capped NCs, we used a device structure similar to Li et al. (Figure 3e).12 The current density passing through the devices was rather high, limiting the peak external quantum efficiency (EQE) to $2.5\\%$ at $3.5\\mathrm{V}\\:(J=21.7\\mathrm{mA/cm}^{2},$ $L$ $\\mathbf{\\Sigma}=1641~\\mathrm{cd/m}^{2}$ , Figure 3f; see the statistics in Figure S20 and the plot of EQE/current efficiency vs. voltage in Figure S21), trailing behind the most efficient $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}_{3}}$ NC LEDs in terms of EQEs $(6.27\\%$ and $8.73\\%$ ).10, 12 At the same time, the peak luminance of such devices exceeded 24,000 $\\operatorname{cd}/\\mathrm{m}^{2}$ (Figure 3f), significantly brighter than the aforementioned efficient LEDs $(15,185$ and $1,660~\\mathrm{cd/m}^{2}$ , respectively),10, 12 but lagging behind the Cs/formamidinium mixed-cation bromide perovskite NC LED $(55,005~\\mathrm{cd}/\\mathrm{m}^{2})$ .42 The electroluminescence wavelength and FWHM were $5^{16}$ and $16\\ \\mathrm{nm}$ , respectively (at $_{3\\cdot5}\\mathrm{~V~}$ ; inset in Figure 3f). In spite of sulfobetaine being a long-chain ligand, the charge transport is not severely impeded, seen as high photoconductivity and high current densities in the LEDs. The current densities in our LEDs (current-voltage characteristics, Figures 3f and $S_{22}$ ) are higher than reported in LEDs from Li et al. $(\\mathrm{EQE{=}8.73\\%})$ );12 however, without concomitant increase in luminance, thus leading to lower EQE $(2.5\\%)$ . This reduced efficiency may be due to imbalance between electrons and holes at higher current densities. \n\nIn conclusion, a novel class of capping ligands for perovskite NCs is proposed, wherein each ligand molecule is capable of coordinating simultaneously to the surface cations and anions. Colloidal perovskite NCs prepared with tightly bound ligands and without large quantities of excessive capping ligands will serve as an ideal platform for further engineering these NCs. This may include the development of core-shell NC morphologies with enhanced thermal and environmental stability, as critically needed for applications in displays and lighting, or even for rendering perovskite NCs water-compatible for biomedical applications. \n\n![](images/12c29c3b7bce87e54a784c7076ae4e58a13265003a7d4480d1b4e60a94d73a40.jpg) \nFigure 3. (a) Amplified spontaneous emission (ASE) spectra showing evolution of ASE band and (b) the threshold behavior for the intensity of the ASE band. (c) Photoconductivity spectrum inset: photo of colloidal solution and drop-casted film of standard OA/OLA NCs (left) and $C_{3}.$ - Sulfobetaine-covered NCs (right). (d) Bias dependence of photo response with inset showing the scheme of a photodetector made from the substrate with an interdigitated electrode and a drop-casted film of NCs. (e) Corresponding work functions and HOMO-LUMO gaps and (f) current density and luminance vs. applied voltage of an LED. Inset: electroluminescence spectrum measured at $_{3.5}\\mathrm{V}$ . \n\n# ASSOCIATED CONTENT \n\nSupporting Information Experimental methods and supplementary figures. \n\n# AUTHOR INFORMATION \n\nCorresponding Author \\*Email: mvkovalenko@ethz.ch \n\n# ACKNOWLEDGMENT \n\nThis work was financially supported by the European Union through the $\\mathrm{FP7}$ (ERC Starting Grant NANOSOLID, GA No. $_{306733})$ , by the Swiss Federal Commission for Technology and Innovation (CTI-No. 18614.1 PFNM-NM). The authors thank ScopeM for use of the electron microscope and Manfred Fiebig and his research group for access to their femtosecond laser facility and for experimental assistance. I.I. acknowledges The Netherlands Organization of Scientific Research (NWO) for financial support through the Innovational Research Incentive (Vidi) Scheme (Grant No. 723.013.002). The computational work was carried out on the Dutch national e-infrastructure with the support of the SURF Cooperative. \n\n# REFERENCES \n\n1. Saliba, M.; Matsui, T.; Seo, J. Y.; Domanski, K.; CorreaBaena, J. P.; Nazeeruddin, M. K.; Zakeeruddin, S. M.; Tress, W.; Abate, A.; Hagfeldt, A.; Gratzel, M., Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency. Energy Environ. Sci. 2016, 9, 1989-1997. 2. Swarnkar;, A.; Marshall;, A. R.; Sanehira;, E. M.; Chernomordik;, B. D.; Moore;, D. T.; Christians;, J. A.; Chakrabarti;, T.; Luther;, J. M., Quantum dot–induced phase stabilization of aCsPbI3 perovskite for high-efficiency photovoltaics. Science 2016, 354, 92-97. 3. Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Krieg, F.; Caputo, R.; Hendon, C. H.; Yang, R. X.; Walsh, A.; Kovalenko, M. V., Nanocrystals of Cesium Lead Halide Perovskites (CsPbX3, $\\mathbf{X}=\\mathbf{Cl}$ , Br, and I): Novel Optoelectronic Materials Showing Bright Emission with Wide Color Gamut. Nano Lett. 2015, 15, 3692-3696. 4. Kovalenko, M. V.; Protesescu, L.; Bodnarchuk, M. I., Properties and potential optoelectronic applications of lead halide perovskite nanocrystals. Science 2017, 358, 745-750. 5. Correa-Baena, J.-P.; Saliba, M.; Buonassisi, T.; Grätzel, M.; Abate, A.; Tress, W.; Hagfeldt, A., Promises and challenges of perovskite solar cells. Science 2017, 358, 739-744. 6. Stephanie ten Brinck; Infante, I., Surface Termination, Morphology, and Bright Photoluminescence of Cesium Lead Halide Perovskite Nanocrystals. ACS Energy Lett. 2016, 1, 1266-1272. 7. Zhou, Q.; Bai, Z.; Lu, W. G.; Wang, Y.; Zou, B.; Zhong, H., In Situ Fabrication of Halide Perovskite Nanocrystal-Embedded Polymer Composite Films with Enhanced Photoluminescence for Display Backlights. Adv. Mater. 2016, 9163–9168. 8. Pan, J.; Quan, L. N.; Zhao, Y.; Peng, W.; Murali, B.; Sarmah, S. P.; Yuan, M.; Sinatra, L.; Alyami, N. M.; Liu, J.; Yassitepe, E.; Yang, Z.; Voznyy, O.; Comin, R.; Hedhili, M. N.; Mohammed, O. F.; Lu, Z. H.; Kim, D. H.; Sargent, E. H.; Bakr, O. M., Highly Efficient Perovskite-Quantum-Dot Light-Emitting Diodes by Surface Engineering. Adv. Mater. 2016, 28, 8718-8725. 9. Zhang, X.; Sun, C.; Zhang, Y.; Wu, H.; Ji, C.; Chuai, Y.; Wang, P.; Wen, S.; Zhang, C.; Yu, W. W., Bright Perovskite \n\nNanocrystal Films for Efficient Light-Emitting Devices. J. Phys. Chem. Lett. 2016, 7, 4602-4610. \n10. Chiba, T.; Hoshi, K.; Pu, Y. J.; Takeda, Y.; Hayashi, Y.; Ohisa, S.; Kawata, S.; Kido, J., High-Efficiency Perovskite QuantumDot Light-Emitting Devices by Effective Washing Process and Interfacial Energy Level Alignment. ACS Appl. Mater. Interfaces 2017, 9, 18054-18060. \n11. Deng, W.; Xu, X.; Zhang, X.; Zhang, Y.; Jin, X.; Wang, L.; Lee, S.-T.; Jie, J., Organometal Halide Perovskite Quantum Dot Light-Emitting Diodes. Adv. Funct. Mater. 2016, 26, 4797-4802. 12. Li, J.; Xu, L.; Wang, T.; Song, J.; Chen, J.; Xue, J.; Dong, Y.; Cai, B.; Shan, Q.; Han, B.; Zeng, H., 50-Fold EQE Improvement up to $6.27\\%$ of Solution-Processed All-Inorganic Perovskite CsPbBr3 QLEDs via Surface Ligand Density Control. Adv. Mater. 2017, 29, $1603885$ . \n13. Li, G.; Rivarola, F. W.; Davis, N. J.; Bai, S.; Jellicoe, T. C.; de la Pena, F.; Hou, S.; Ducati, C.; Gao, F.; Friend, R. H.; Greenham, N. C.; Tan, Z. K., Highly Efficient Perovskite Nanocrystal Light-Emitting Diodes Enabled by a Universal Crosslinking Method. Adv. Mater. 2016, 28, 3528-34. \n14. Yakunin, S.; Protesescu, L.; Krieg, F.; Bodnarchuk, M. I.; Nedelcu, G.; Humer, M.; De Luca, G.; Fiebig, M.; Heiss, W.; Kovalenko, M. V., Low-threshold amplified spontaneous emission and lasing from colloidal nanocrystals of caesium lead halide perovskites. Nat. Commun. 2015, 6, 8056. \n15. Pan, J.; Sarmah, S. P.; Murali, B.; Dursun, I.; Peng, W.; Parida, M. R.; Liu, J.; Sinatra, L.; Alyami, N.; Zhao, C.; Alarousu, E.; Ng, T. K.; Ooi, B. S.; Bakr, O. M.; Mohammed, O. F., Air-Stable Surface-Passivated Perovskite Quantum Dots for Ultra-Robust, Single- and Two-Photon-Induced Amplified Spontaneous Emission. J. Phys. Chem. Lett. 2015, 6, 5027-5033. \n16. De Roo, J.; Ibáñez, M.; Geiregat, P.; Nedelcu, G.; Walravens, W.; Maes, J.; Martins, J. C.; Van Driessche, I.; Kovalenko, M. V.; Hens, Z., Highly Dynamic Ligand Binding and Light Absorption Coefficient of Cesium Lead Bromide Perovskite Nanocrystals. ACS Nano 2016, 10, 2071-2081. \n17. Guhrenz, C.; Benad, A.; Ziegler, C.; Haubold, D.; Gaponik, N.; Eychmüller, A., Solid-State Anion Exchange Reactions for Color Tuning of CsPbX3 Perovskite Nanocrystals. Chem. Mater. 2016, 28, 9033-9040. \n18. Huang, H.; Chen, B.; Wang, Z.; Hung, T. F.; Susha, A. S.; Zhong, H.; Rogach, A. L., Water resistant CsPbX3 Nanocrystals Coated with Polyhedral Oligomeric Silsesquioxane and their Use as Solid State Luminophores in All-Perovskite White Light-Emitting Devices. Chem. Sci. 2016, 7, 5699-5703. \n19. Liu, Z.; Bekenstein, Y.; Ye, X.; Nguyen, S. C.; Swabeck, J.; Zhang, D.; Lee, S. T.; Yang, P.; Ma, W.; Alivisatos, A. P., Ligand Mediated Transformation of Cesium Lead Bromide Perovskite Nanocrystals to Lead Depleted $\\mathrm{Cs}_{4}\\mathrm{Pb}\\mathrm{Br}_{6}$ Nanocrystals. J. Am. Chem. Soc. 2017, 139, 5309-5312. \n20. Meyns, M.; Peralvarez, M.; Heuer-Jungemann, A.; Hertog, W.; Ibanez, M.; Nafria, R.; Genc, A.; Arbiol, J.; Kovalenko, M. V.; Carreras, J.; Cabot, A.; Kanaras, A. G., Polymer-Enhanced Stability of Inorganic Perovskite Nanocrystals and Their Application in Color Conversion LEDs. ACS Appl. Mater. Interfaces 2016, 8, 19579-86. 21. Quan, L. N.; Quintero-Bermudez, R.; Voznyy, O.; Walters, G.; Jain, A.; Fan, J. Z.; Zheng, X.; Yang, Z.; Sargent, E. H., Highly Emissive Green Perovskite Nanocrystals in a Solid State Crystalline Matrix. Adv. Mater. 2017, 29, 1605945-1605951. \n22. Raja, S. N.; Bekenstein, Y.; Koc, M. A.; Fischer, S.; Zhang, D.; Lin, L.; Ritchie, R. O.; Yang, P.; Alivisatos, A. P., Encapsulation of Perovskite Nanocrystals into Macroscale Polymer Matrices: Enhanced Stability and Polarization. ACS Appl. Mater. Interfaces 2016, 8, 35523-35533. \n23. Xu, L.; Chen, J.; Song, J.; Li, J.; Xue, J.; Dong, Y.; Cai, B.; Shan, Q.; Han, B.; Zeng, H., Double-Protected All-Inorganic Perovskite Nanocrystals by Crystalline Matrix and Silica for TripleModal Anti-Counterfeiting Codes. ACS Appl. Mater. Interfaces 2017, 9, 26556-26564. \n24. Li, Z.; Kong, L.; Huang, S.; Li, L., Highly Luminescent and Ultrastable $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ Perovskite Quantum Dots Incorporated into a Silica/Alumina Monolith. Angew. Chem., Int. Ed. 2017, 56, 8134-8138. 25. Koscher, B. A.; Swabeck, J. K.; Bronstein, N. D.; Alivisatos, A. P., Essentially Trap-Free $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ Colloidal Nanocrystals by Postsynthetic Thiocyanate Surface Treatment. J. Am. Chem. Soc. 2017, 139, 6566-6569. \n26. Lu, C.; Li, H.; Kolodziejski, K.; Dun, C.; Huang, W.; Carroll, D.; Geyer, S. M., Enhanced Stabilization of inorganic Cesium Lead Triiodide (CsPbI3) Perovskite Quantum Dots with TriOctylphosphine. Nano Research 2017, 11, 762-768. \n27. Pan, J.; Quan, L. N.; Zhao, Y.; Peng, W.; Murali, B.; Sarmah, S. P.; Yuan, M.; Sinatra, L.; Alyami, N. M.; Liu, J.; Yassitepe, E.; Yang, Z.; Voznyy, O.; Comin, R.; Hedhili, M. N.; Mohammed, O. F.; Lu, Z. H.; Kim, D. H.; Sargent, E. H.; Bakr, O. M., Highly Efficient Perovskite-Quantum-Dot Light-Emitting Diodes by Surface Engineering. Adv. Mater. 2016, 28, 8718–8725. \n28. Wang, C.; Chesman, A. S.; Jasieniak, J. J., Stabilizing the Cubic Perovskite Phase of $\\mathrm{Cs}\\mathrm{PbI}_{3}$ Nanocrystals by Using an Alkyl Phosphinic Acid. Chem. Commun. 2016, 53, 232-235. \n29. Pan, J.; Shang, Y.; Yin, J.; De Bastiani, M.; Peng, W.; Dursun, I.; Sinatra, L.; El-Zohry, A. M.; Hedhili, M. N.; Emwas, A.-H.; Mohammed, O. F.; Ning, Z.; Bakr, O. M., Bidentate LigandPassivated $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ Perovskite Nanocrystals for Stable Near-Unity Photoluminescence Quantum Yield and Efficient Red Light-Emitting Diodes. J. Am. Chem. Soc. 2018, 140, 562–565. \n30. Schwarzenbach, G., Der Chelateffekt. Helv. Chim. Acta 1952, 35, 2344-2359. \n31. Bertolotti, F.; Protesescu, L.; Kovalenko, M. V.; Yakunin, S.; Cervellino, A.; Billinge, S. J. L.; Terban, M. W.; Pedersen, J. S.; Masciocchi, N.; Guagliardi, A., Coherent Nanotwins and Dynamic Disorder in Cesium Lead Halide Perovskite Nanocrystals. ACS Nano 2017, 11, 3819-3831. \n32. Swarnkar, A.; Chulliyil, R.; Ravi, V. K.; Irfanullah, M.; Chowdhury, A.; Nag, A., Colloidal $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ Perovskite Nanocrystals: Luminescence beyond Traditional Quantum Dots. Angew. Chem., Int. Ed. 2015, 54, 15424-15428. \n33. Wang, Q.; Zheng, X.; Deng, Y.; Zhao, J.; Chen, Z.; Huang, J., Stabilizing the $\\upalpha$ -Phase of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ Perovskite by Sulfobetaine Zwitterions in One-Step Spin-Coating Films. Joule 2017, 1, 371-382. 34. Ravi, V. K.; Santra, P. K.; Joshi, N.; Chugh, J.; Singh, S. K.; Rensmo, H.; Ghosh, P.; Nag, A., Origin of the Substitution Mechanism for the Binding of Organic Ligands on the Surface of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ Perovskite Nanocubes. J. Phys. Chem. Lett. 2017, 8, 4988- 4994. \n35. Jhon P. Perdew; Kieron Burke; Erzerhof, M., Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 78, 1396. \n$36$ . Jürg Hutter; Marcella Iannuzzi; Florian Schiffmann; VandeVondele, J., cp2k: atomistic simulations of condensed matter systems. WIREs Comput. Mol. Sci. 2013, 4, 15-25. \n37. Hoffman, J. B.; Schleper, A. L.; Kamat, P. V., Transformation of Sintered $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ Nanocrystals to Cubic $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ and Gradient $\\mathrm{CsPbBr_{x}I_{3^{-x}}}$ through Halide Exchange. J. Am. Chem. Soc. 2016, $^{138}$ , 8603-11. \n$^{38}$ . Grim, J. Q.; Christodoulou, S.; Di Stasio, F.; Krahne, R.; Cingolani, R.; Manna, L.; Moreels, I., Continuous-wave biexciton lasing at room temperature using solution-processed quantum wells. Nat. Nanotechnol. 2014, 9, 891-895. \n39. She, C.; Fedin, I.; Dolzhnikov, D. S.; Dahlberg, P. D.; Engel, G. S.; Schaller, R. D.; Talapin, D. V., Red, Yellow, Green, and Blue Amplified Spontaneous Emission and Lasing Using Colloidal CdSe Nanoplatelets. ACS Nano 2015, 9, 9475-9485. \n40. Wang, Y.; Leck, K. S.; Ta, V. D.; Chen, R.; Nalla, V.; Gao, Y.; He, T.; Demir, H. V.; Sun, H., Blue liquid lasers from solution of CdZnS/ZnS ternary alloy quantum dots with quasi-continuous pumping. Adv. Mater. 2015, 27, 169-75. \n41. Wang, Y.; Yang, S.; Yang, H.; Sun, H., Quaternary Alloy Quantum Dots: Toward Low-Threshold Stimulated Emission and All-Solution-Processed Lasers in the Green Region. Adv. Opt. Mater. 2015, 3, $652\\substack{-657}$ . \n42. Zhang, X.; Liu, H.; Wang, W.; Zhang, J.; Xu, B.; Karen, K. L.; Zheng, Y.; Liu, S.; Chen, S.; Wang, K.; Sun, X. W., Hybrid Perovskite Light-Emitting Diodes Based on Perovskite Nanocrystals with Organic–Inorganic Mixed Cations. Adv. Mater. 2017, 29, 1606405. " + }, + { + "id": "10.1126_science.aav1910", + "DOI": "10.1126/science.aav1910", + "DOI Link": "http://dx.doi.org/10.1126/science.aav1910", + "Relative Dir Path": "mds/10.1126_science.aav1910", + "Article Title": "Tuning superconductivity in twisted bilayer graphene", + "Authors": "Yankowitz, M; Chen, SW; Polshyn, H; Zhang, YX; Watanabe, K; Taniguchi, T; Graf, D; Young, AF; Dean, CR", + "Source Title": "SCIENCE", + "Abstract": "Materials with flat electronic bands often exhibit exotic quantum phenomena owing to strong correlations. An isolated low-energy flat band can be induced in bilayer graphene by simply rotating the layers by 1.1 degrees, resulting in the appearance of gate-tunable superconducting and correlated insulating phases. In this study, we demonstrate that in addition to the twist angle, the interlayer coupling can be varied to precisely tune these phases. We induce superconductivity at a twist angle larger than 1.1 degrees-in which correlated phases are otherwise absent-by varying the interlayer spacing with hydrostatic pressure. Our low-disorder devices reveal details about the superconducting phase diagram and its relationship to the nearby insulator. Our results demonstrate twisted bilayer graphene to be a distinctively tunable platform for exploring correlated states.", + "Times Cited, WoS Core": 1693, + "Times Cited, All Databases": 1844, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000460750100038", + "Markdown": "# Tuning superconductivity in twisted bilayer graphene \n\nMatthew Yankowitz,1\\* Shaowen Chen,'2\\*Hryhoriy Polshyn,3\\* Yuxuan Zhang, K. Watanabe,+T.Taniguchi,+ David Graf,5 Andrea F. Young,3+ Cory R. Dean't \n\ne High Magnetic Field Laboratory,Tallahassee,FL 32310, USA. \n\n\\*These authors contributed equally to this work. tCorresponding author. Email: afy2003@ucsb.edu (A.F.Y.); cd2478@columbia.edu (C.R.D.) \n\nMaterials with flat electronic bands often exhibit exotic quantum phenomena owing to strong correlations.An isolated low-energy flat band can be induced in bilayer graphene by simply rotating the layers to $\\bf{1.1^{\\circ}}$ , resulting in the appearance of gate-tunable superconducting and correlated insulating phases.Here, we demonstrate that in addition to the twist angle,the interlayer coupling can be varied to precisely tune these phases. We induce superconductivity at a twist angle larger than $\\bf{1.1^{\\circ}}.$ —in which correlated phases are otherwise absent-by varying the interlayer spacing with hydrostatic pressure. Our low disorder devices reveal details about the superconducting phase diagram and its relationship to the nearby insulator. Our results demonstrate twisted bilayer graphene to be a uniquely tunable platform for exploring correlated states. \n\nThe electronic properties of many materials are well described by assuming that non-interacting electrons simply fill the available energy bands. However, for systems with narrowly dispersing flat bands in which the kinetic energy is small relative to the Coulomb energy, the assumption that electrons are non-interacting is no longer valid. Instead, the electronic ground state is driven by minimizing the mutual Coulomb repulsion between electrons. It has recently been demonstrated that heterostructures consisting of layered two-dimensional materials—where narrow isolated bands can be realized simply by tuning the rotational ordering between layers (I-4)—provide a remarkably simple avenue to reach this condition. Bilayer graphene, which normally consists of two vertically stacked monolayer graphene layers ar ranged in an AB (Bernal) stacking configuration, provides a dramatic example. Upon rotating the layers away from Ber nal stacking to the so-called “magic angle\" of ${\\sim}1.1^{\\circ}$ , the interplay between the resulting moiré superlattice and hybridization between the layers leads to the formation of an isolated flat band at the charge neutrality point $(I)$ . Near this flat band angle, recent experiments have observed correlated insulator phases at half band filling (5) and superconductivity upon doping slightly away from half band filling for hole-type carriers $\\left(6\\right)$ . \n\nThe discovery of superconductivity in twisted bilayer graphene (tBLG) has sparked intense interest owing in part to the possibility that it arises from an unconventional electron mediated pairing mechanism. The material composition is remarkably simple, comprising only carbon atoms. Unlike most unconventional superconductors, where exploring different carrier density requires growing different samples. in tBLG the entire correlated phase diagram can be accessed in a single device by field effect gating. Additionally, the available degrees of freedom in tBLG, including twist angle control $(I)$ , interlayer separation (7, 8), and displacement fieldinduced layer imbalance $(\\boldsymbol{I},\\boldsymbol{g})$ , provide opportunities to experimentally tune the electronic structure in ways that are difficult or impossible to access in previously investigated superconductors. \n\nHere we present measurements of both the superconducting and correlated insulating states in tBLG at the flat-band condition. We study three separate devices, fabricated in a fully-encapsulated, dual-graphite gate structure in order to enhance device mobility and minimize effects of charge inhomogeneity (1O). Two devices have twist angles close to $1.1^{\\circ}$ and exhibit superconductivity and correlated insulating phases. The third device is fabricated at a twist angle of $1.27^{\\circ}$ , and although correlated phases are absent we demonstrate the ability to induce them by applying hydrostatic pressure $(I I)$ \n\n# Correlated phases in twisted bilayer graphene \n\nWe fabricate BN-encapsulated tBLG using the “tear and stack\" method to control the graphene alignment (12), and additionally include top and bottom graphite gates (Fig. 1A). The all-van der Waals device geometry has previously been shown to significantly increase charge homogeneity as compared with the evaporated metal or degenerately doped silicon gates (1O). Additionally, the dual-gate structure allows us to independently vary the charge carrier density and transverse displacement field, and experimentally investigate the effects of interlayer bias on the correlated states $(\\boldsymbol{\\cal I},\\boldsymbol{\\vartheta},\\boldsymbol{\\cal I}3)$ . \n\nFigure 1B shows the density-dependent resistance of device Dl, with interlayer twist angle $\\Theta\\approx1.14^{\\circ}$ . The device exhibits low charge carrier inhomogeneity of $\\mathrm{5}n<2\\times10^{10}\\mathrm{{cm^{-2}}}$ measured by the full width at half maximum of the resistance peak at the charge neutrality point (CNP). The low charge disorder is further confirmed by the emergence of fractional quantum Hall states at magnetic fields as low as \\~4 T (14). In Fig. lB, the resistance is plotted over nearly the full density range of the flat band. We identify the boundaries of the flat band by the appearance of strongly insulating response at densities symmetrically located around the CNP (l4). We then use a normalized density scale to define partial band filling with $+n_{s}$ and $-n_{s}$ corresponding the electron- and holedoped band edges with $\\pm4$ electrons per moiré unit cell, respectively. Within the flat band we observe resistive states at the CNP, as well as at $\\pm n_{s}/2$ and $+3n_{s}/4.$ . At base temperature of $\\mathrm{\\sim}10~\\mathrm{mK},$ , regions of superconductivity appear both in the hole- and electron-doped regions, with the resistance drop ping to zero for densities near $\\pm n_{s}/2$ . \n\nIn the hole band, the density and magnetic field dependence of the superconducting response resembles previous observations $\\textcircled{6}$ , whereas the electron band superconductivity was not previously reported. In both bands superconductivity appears more robust on the high density side of the insulator, $\\left\\lvert n\\right\\rvert>\\left\\lvert\\pm n_{s}/2\\right\\rvert$ , and is much weaker or absent on the low density side, $\\left\\vert n\\right\\vert<\\left\\vert\\pm n_{_s}/2\\right\\vert$ . In the hole band the low density pocket is not fully superconducting at $10~\\mathrm{mK}$ ,whereas in the similar doping range for the electron band no signature of superconductivity appears at all down to base temperature. \n\nFigure 1C shows the resistance versus temperature measured at optimal doping of both the hole- and electron-type superconducting pockets.The critical temperature is $\\sim0.25\\mathrm{K}$ for electron-type carriers and ${\\sim}0.4\\mathrm{~K~}$ for hole-type carriers, defined as the crossover point of linear fits to the low and high temperature portions of the resistance curves on a logarithmic scale.The hole-band $T_{c}$ is similar to that reported previously for a similar twist angle $\\left(6\\right)$ ,however superconductivity for electron-type carriers in tBLG was not observed in that work. Although the band structure of tBLG is not anticipated to be precisely particle-hole symmetric, the observation of superconductivity over similar ranges of den sity for both electron and hole carriers suggests a connection between the mechanisms driving the superconducting phases of the two carrier types. \n\n# Influence of structural inhomogeneity \n\nDespite the reduction of charge disorder effects in our dualgraphite gated structure, we observe strong signatures of in homogeneity in the transport response. Most obviously, the carrier density corresponding to full-filling is observed to vary between different pairs of contacts (fig. SiF) (14). This suggests that the moiré unit cell area is not uniform over the whole device, and we have observed variations of the moiré unit cell area by as much as ${\\sim}30\\%$ within a single device (14). This is consistent with recent TEM imaging of tBLG devices with similar twist angles (15), suggesting spatial variations in the moiré period may be ubiquitous in these structures. \n\nAdditionally, we can utilize our dual-gated structure to investigate the device response with applied displacement field (Fig. 1D). The transport properties of graphene bilayers are typically strongly dependent on $D$ $\\left({\\cal I}\\delta\\right)$ ; however theoretical modeling of flat-band tBLG suggests that transverse field should have little to no consequence because of the strong interlayer hybridization $(1,9,13)$ . The superconducting regions in our device appear to be largely insensitive to $D$ ,exhibiting for instance similar $T_{c}$ at large positive and large negative values of $D$ (fig. S9) (14). In contrast, the insulating state at $-n_{s}/2$ shows a strong dependence on $D$ ,with resistance exceeding $10\\mathrm{k}\\Omega$ for positive $D$ but appearing to drop to zero for negative $D$ . Similarly, the peak resistance at $+3n_{s}/4$ in the electron band also varies strongly but exhibits the opposite dependence, becoming less resistive at large, positive $D$ .This opposite trend with $D$ between the electron and hole bands suggests that the insulating state is suppressed when the carriers of either sign are polarized toward the same (top) graphene layer. Because freestanding tBLG is expected to be symmetric under layer interchange, this response is unexpected and likely to be extrinsic. \n\nWe conjecture that the superconductor to insulator transition observed at $-n_{s}/2$ is another consequence of structural inhomogeneity. In particular, polarizing carriers to a more strained graphene layer may favor formation of a percolating superconducting network that short-circuits the insulating phase at $-n_{s}/2$ . Although this may also arise as a consequence of charge disorder, the measured charge inhomogeneity is $\\sim10^{10}\\mathrm{cm^{-2}}$ , insufficient to mix these phases across their native separation in carrier density, which is an order of magnitude larger. \n\nFinally, evidence of a percolating superconducting network is provided by measurements of the differential re sistance $d V/d I$ as a function of applied current $I_{d c}$ and $B$ Figure 1, E to G, shows three different measurements, sampling different regions of the $D$ versus $n$ response shown in Fig. 1D. Periodic oscillations in the critical current $I_{c},$ resembling Fraunhofer interference, suggest quantum phase coherent transport arising from interspersed regions of superconducting and metallic/insulating phases within the device. The period of the oscillations $\\Delta B$ varies from 2 to 4 mT, indicating an effective junction area of $S\\approx0.5{\\mathrm{-1~}}\\upmu\\mathrm{m}^{2}$ ,using $S={\\Phi_{0}}/{\\Delta B}$ ,where $\\Phi_{0}=h/2e$ is the superconducting flux quantum, $h$ is Planck's constant, and $e$ is the charge of the electron. This constitutes as much as $\\sim40\\%$ of the device area. Strikingly, Fig. 1G, measured at $-n_{s}/2$ and negative $D$ , shows a minimum in $I_{c}$ at $B=0$ ,with $I_{c}$ increasing to a maximum near $\\pm4\\:\\mathrm{mT}$ , indicative of an additional $\\pi$ phase emerging between the junctions of the device $(I4)$ . The variations among the quantum interference patterns appearing in Fig. 1, E to G, confirm that the microscopic structure of superconducting regions are tunable with $n$ and $D$ . The prevalence of disorderinduced experimental features we identify in our device sug gests that the correlated physics of tBLG is extremely sensitive to the structural details of the moiré pattern. \n\n# Bandwidth tuning with pressure \n\nThe width of the flat bands in tBLG is determined by an in terplay between the momentum-space mismatch of the Dirac cones between the graphene layers (set by the twist angle) and the strength of the layer hybridization (set by the interlayer spacing) (1).The graphene interlayer spacing can be decreased by applying hydrostatic pressure $(I I)$ ,while leaving the interlayer rotation fixed (I4). Pressure can therefore theoretically be used to achieve the flat band condition at arbi trary twist angle, relaxing the need for precise angle tuning $(7,8)$ and potentially reducing the impact of structural inho mogeneity of the moiré pattern. Furthermore, inducing the flat band at higher twist angle has been proposed as a route toward increasing the energy scale of the superconductor ( $\\left[6-\\right]$ 8). \n\nFigure 2A shows the conductance $G$ versus density for a device, D2, with twist angle $\\Theta\\approx1.27^{\\circ}$ . The gray curve in Fig. 2A shows the ambient-pressure response. Strongly insulating states appear at full filling of the moiré unit cell $\\pm n_{s},$ indicating the presence of an isolated low-energy band. However only very weakly insulating states (conductance minima) are observed at $\\pm n_{s}/2$ and around $\\pm3n_{s}/4$ , and no evidence of superconductivity is present, suggesting at this angle the low energy band does not support strong correlations. The blue curve shows the conductance of the same device under 2.21 GPa of hydrostatic pressure. Insulating states at several rational fillings of the moiré unit cell become evident—most notably at $\\pm n_{s}/2$ and $+3n_{s}/4$ , as well as more weakly at $+n_{s}/4$ Figure 2B plots the conductance of the device at $-n_{s}/2$ as a function of temperature for three values of pressure, illustrating the crossover from metallic to insulating behavior under pressure and consistent with pressure-induced bandwidth tuning. \n\nIn addition to strong insulating phases, we also observe a pressure-induced emergence of superconductivity. For hole doping slightly beyond $-n_{s}/2$ (see caption to Fig. 2C), the device exhibits metallic temperature dependence under ambi ent pressure but superconducting behavior at high pressure, with the resistance rapidly dropping to the experimental noise floor of ${\\sim}10~\\Omega$ (Fig. 2C). In the pressure range that we study, the insulating gaps (measured by thermal activation, Fig.2D) and $T_{c}$ of the superconductor (Fig.2E) vary non-monotonically with pressure, with both reaching their highest measured values at 1.33 GPa. We also observe the onset of electron-type superconductivity for electron-doping just larger than $+n_{s}/2$ , as evidenced by a sharp drop in the device magnetoresistance around $B=0$ (fig. S4B) (14).However it appears to have a much lower $T_{c}$ than its hole-doping counterpart, preventing detailed study in pressure experiments where our base temperature was limited to $300~\\mathrm{{mK}}$ \n\nRecent bandstructure calculations indicate that the relation between bandwidth and pressure depends on the twist angle $(7,8)$ .For a $1.27^{\\circ}$ tBLG the minimum bandwidth is theoretically predicted to be in the range of 1.3 GPa to 1.5 GPa (7 $\\delta{\\ '}$ , in remarkably good agreement with the pressure value where we observed maximum $T_{c}$ . We note that the largest measured $T_{c}$ we induce with pressure is ${\\sim}3\\mathrm{K}$ , nearly an order of magnitude larger than observed in Device D1 and roughly a factor 2 larger than reported in $\\left(6\\right)$ . This relative increase in $T_{c}$ could result from an increase in the Coulomb interaction energy scale resulting from the reduced moiré wavelength at the larger twist angle of this device $(6-8)$ , but may also relate to differences in sample disorder. \n\nFigures 3, A and B plot the device resistance around $-n_{s}/2$ as a function of temperature $T$ and magnetic field $B_{i}$ ,respectively, under a pressure of 1.33 GPa. We observe a state with strongly insulating temperature dependence at $-n_{s}/2$ ,with a pocket of superconductivity at slightly larger hole doping and metallic behavior at slightly smaller hole doping. Our results differ from those of our device D1 and of the devices reported in Ref. $\\left(6\\right)$ in several ways. First, the device resistance in Fig. 3A grows quickly as the temperature is lowered, whereas in prior devices it drops toward zero (e.g., for negative values of $D$ for device D1). Second, we observe a pocket of superconductivity only for $n<-n_{s}/2$ ,whereas prior devices additionally exhibit superconductivity for $n>-n_{s}/2$ . Third, we find evidence for a metallic phase separating the superconducting and insulating phases. Although this is partially obscured in Fig. 3A by an anomalous region of apparent negative resistance in this region arising from a measurement artifact (colored in white), measurements using other contacts (as well similar measurements at 2.2l GPa) exhibit clearer evidence of the metallic phase (figs. S2 and S3) (14). However, small remnant disorder may also be responsible for this apparent metallic phase, and further investigation is necessary to probe the potential existence of a quantum critical point around this doping. \n\nFigure 3C shows a comparison of the resistance versus temperature of the insulating (red) and superconducting (blue) state, measured at 2.2l GPa. The two phases onset at remarkably similar temperatures with the resistance in both cases diverging at around $5\\mathrm{~K~}$ from the high temperature metallic behavior. Similar behavior is also observed in device D1, where additionally we found that similar critical currents quench each phase to the normal state resistance (fig. S8) (14). These observations suggest that the insulating and superconducting phases share similar energy scales, constraining models in which the superconductivity arises as a daughter-state of the insulator. \n\nThe lack of strong magnetoresistance oscillations in Fig 3B suggests that sample D2 is highly homogeneous. To confirm this, we plot $d V/d I$ as a function of $B$ and $I_{\\mathrm{dc}}$ in Fig. 3D, and find that $I_{c}$ decreases roughly linearly with $B$ and, unlike device Dl, does not exhibit quantum interference patterns associated with junction-limited superconductivity. We have additionally measured the phase diagram of this device as a function of $D_{i}$ ,and do not observe a significant displacement field dependence (in particular there is a robust insulating state at $-n_{s}/2$ for all $D$ )(fig. S4A) (14).We interpret these observations to indicate that this device is less disordered than those previously reported, suggesting that details of the associated superconducting and insulating response may more faithfully represent the disorder-free phase diagram. The reasons for the reduced disorder in this sample are not fully un derstood. This may be emblematic of larger twist angle devices where the combination of smaller moiré period and applied pressure minimize the contribution of spatial inhomogeneity. However, owing to the limited sample size we also can not rule out random sample-to-sample variation.A systematic study of the interplay between twist angle and pressure-preferably in a single device (1l, 17)-will be needed to resolve these issues. \n\n# Quantum oscillations and new Fermi surfaces \n\nThe high degree of structural and charge homogeneity in our samples further allows high resolution measurements of magnetoresistance oscillations associated with cyclotron motion of electrons. Quantum oscillations at low magnetic fields give detailed information about electronic band structure, as their periodicity can be used to infer the areal size of the Fermi surface. Moreover, their degeneracy reflects the pres ence of spin, valley, and layer degrees of freedom. Figure 4A shows magnetoresistance data from device D2 at 1.33 GPa. Several sets of seemingly independent Landau fans are observed, indicated schematically in Fig. 4B. In contrast to devices with larger twist angle, none of the quantum oscillations show $D$ -tuned Landau level crossings (fig. S4, C and D) $(I4)$ . Near the CNP, we observe a 4-fold degenerate sequence of quantum oscillations, with dominant minima at $\\upnu=\\pm{4},\\pm{8},\\pm{12},...$ at low magnetic field, where $\\upnu=n h/(e B)$ is the Landau level filling factor relative to charge neutrality. \n\nAt $+n_{s}/4$ , $\\pm n_{s}/2$ ,and $\\pm3n_{s}/4$ , the carrier density extracted from the Hall effect approaches zero (fig. S5) (14), indicating the formation of new, small Fermi surfaces. These fillings also spawn independent series of quantum oscillations. At $\\pm n_{s}/2$ , oscillations clearly exhibit 2-fold degeneracy at very low fields, suggesting that the combined spin- and valley- degeneracy is partially lifted $\\textcircled{6}$ . In contrast, the sequences of quantum oscillations emerging from $\\pm3n_{s}/4$ exhibit no additional degeneracy, suggesting that all degeneracies are lifted in these Fermi surfaces.Notably, the associated quantum oscillations disperse only in a single direction for each carrier type (away from the CNP) and abruptly terminate at the next com mensurate filling, consistent with strong, asymmetric renormalization of the effective mass across the gap. \n\nThe sequence emerging from $+n_{s}/4$ appears to be 2-fold degenerate but, interestingly, is odd-dominant with primary oscillations observed at $\\mathsf{v}=+1$ , $+3$ , $+5,\\ldots$ ,where $\\upnu$ is defined relative to $+n_{s}/4.$ Although neither a resistive state nor quantum oscillations are observed originating from $-n_{s}/4$ ,we observe a shift in the dominant filling sequence for the CNP fan when the carrier density reaches $-n_{s}/4$ . Around this density, the most pronounced oscillations transition from a $\\upnu=-4$ , -8, -l2,... sequence near the CNP to $\\upnu=-10$ , $-14$ , $-18,\\dots$ for $n<-n_{s}/4$ . Figure 4,C and D, show a detailed view of this transition highlighting the crossover of the dominant se quence. Notably, a qualitatively identical sequence of quantum oscillations was observed in another device at ambient pressure but with twist angle $\\Theta\\:=\\:1.08^{\\circ}$ , close to the native flat-band angle (fig. S6A) (see $(I4)$ for details of this device, labeled D5). The concordance between quantum oscillations patterns-a detailed probe of the Fermi surface-for both angle- and pressure-tuned flat-band devices supports the hypothesis that interlayer coupling and twist angle are equivalent electron structure control parameters $(\\boldsymbol{{I}},\\boldsymbol{{7}},\\boldsymbol{{8}})$ . \n\nThe agreement between the fine structure of the quantum oscillations across devices suggests they are a universal feature of the tBLG electronic structure near the flat-band condition; however, several features of the observed patterns are not captured by available theoretical models. Available models predict eight-fold degeneracy near the CNP, arising from spin, valley, and layer degrees of freedom (18), however, we observe only a four-fold quasi-degeneracy. Our observed filling sequence (defined as the sequence of best-resolved quantum oscillations) is identical to that in Bernal stacked bilayer graphene, where interlayer tunneling leads to band hybridization and parabolically dispersing low-energy bands. Quadratic band touching reminiscent of Bernal bilayer graphene does feature in several recent models of tBLG flat bands (19, 20), although these models also feature additional Dirac crossings at low energy whose effect on the quantum oscillations has not been discussed in detail. \n\nThe phase shifts of the dominant oscillations observed near $\\pm n_{s}/4$ are also not anticipated theoretically. Quantum oscillation measurements in a tilted magnetic field (figs. S6) C and D) (14) for the Landau fan originating at the CNP reveal that the dominant symmetry breaking term splits the valleys rather than the spins, implying that the phase shift observed near $-n_{s}/4$ arises from a crossing between spin-degenerate Landau level doublets. This implies that within a nominally spin- and valley-degenerate Landau level, the valley degeneracy is lifted the most strongly at the single particle level. Assuming valley to be a good quantum number, a magnetic field-induced valley splitting precludes perfect inversion symmetry-in contrast most band structure models of this system feature inversion symmetry. \n\n# Isospin ordering ofthe correlated insulators \n\nOur observation that superconductivity appears only at den sities coincident with lower-degeneracy quantum oscillations near half-filling—but not near insulating states at quarter and three-quarter filling—suggests that the nature of sym metry breaking may be integral to superconductivity. A wide array of candidate states have already been proposed in the literature to describe the correlated insulating states, including antiferromagnetic Mott insulators, charge density waves Wigner crystals, and isospin ferromagnetic band insulators (18, 21-27). Parallel magnetic field measurements offer a simple probe of isospin physics, as a primary effect of $B_{||}$ is to increase the Zeeman energy. Under applied $B_{\\parallel}$ , the gap of a spin-unpolarized (valley-polarized) ground state should decrease linearly, whereas the gap is expected to increase linearly, or remain unchanged, for spin-polarized (valleyunpolarized) ground state ordering. \n\nFigure 5A shows the parallel magnetic-field response of the conductance of device D3, with twist angle $\\Theta\\approx1.10^{\\circ}$ .The conductance at zero magnetic field exhibits minima at the CNP, $\\pm n_{s}/2$ , and $+3n_{s}/4$ band filling, along with more weakly developed features at $-3n_{s}/4$ and $+n_{s}/4$ .At $\\pm n_{s}/2$ filling, the conductance minimum fades with increasing $B_{\\parallel}$ ,whereas the opposite behavior is observed at $\\pm n_{s}/4$ . The $\\pm3n_{s}/4$ states are insensitive to magnetic field (fig. SllB) (14). Qualitatively, our observations suggest that the $\\pm n_{s}/2$ insulators are spin-unpolarized, whereas both the $\\pm n_{s}/4$ and $\\pm3n_{s}/4$ are spin-polarized. \n\nWe explore this picture quantitatively using the thermal activation gap of the $\\pm n_{s}/2$ state-the only commensurate insulator that shows clear thermal activation in this device-as a function of $B_{||}$ (Fig. 5B). Unexpectedly, it closes non-linearly with $B_{\\parallel}$ , inconsistent with either full spin- or valley-polarization. The approximately parabolic decrease is also not consistent with antiferromagnetically aligned spins in opposite valleys, which would lead to an increasing gap at larger $B_{\\parallel}$ Our finding suggests that isospin ordering alone, without additional symmetry breaking that lifts the degeneracy of the Dirac band touching, may be insufficient to understand the nature of the half-filling insulators. \n\n# Discussion \n\nAccurate modeling of twisted bilayer graphene is compli cated by the large size of the moiré unit cell, which prevents reliable band structure calculations. Moreover, emerging literature suggests a wide variety of plausible mechanisms and ground states for both the superconducting and insulating states. Many of these models predict unconventional all-electronic pairing mechanisms (21, 23-25, 28-34, 35-39) whereas others are either explicitly or implicitly consistent with conventional phonon-mediated superconductivity (27, 40-44). Our data, taken together, highlight a number of con straints any successful theory of tBLG should satisfy, which we summarize here. \n\nFirst, our experiments confirm the basic notion that correlation physics in tBLG arises from the interplay of angular misalignment and interlayer tunneling $(I)$ .We observe insulating and superconducting states in the same regime of an gles as in $(5,6)$ at ambient pressure, and our finite-pressure experiments show the anticipated trend, with flat-band phys ics appearing at larger angles for larger applied pressure. The small and likely extrinsic effect of displacement field is similarly consistent with expectations of strong interlayer hybridization. \n\nHowever, our data reveal several important new details of the resulting correlated states themselves. Most importantly, our data suggest that the intrinsic domain of superconductivity in this system is restricted to a narrow range of charge density at higher absolute density-but not lower-than halffilling (i.e., $\\left\\vert n\\right\\vert>\\left\\vert\\pm n_{_s}/2\\right\\vert)$ . Superconductivity occurs for both electron- and hole-doping, and is nearly adjacent to a strongly insulating state. The domain of superconductivity coincides with that of two-fold degenerate quantum oscillations, indicating that a small Fermi surface with reduced degeneracy is nucleated at $n_{s}/2$ . Although we cannot exclude superconducting states with transitions at temperatures lower than our experimental base temperature, we fail to observe superconductivity near other commensurate fillings, including several which host similar insulating states. This suggests that the nature of the Fermi surface nucleated $\\pm n_{s}/2$ may be essential to the onset of nearby superconductivity, although whether this is via a purely electronic mechanism, an enhancement of density of states that favor a phonon-mediated mechanism, or some mechanism yet to be proposed is unknown. \n\nFinally, our results suggest that future work should focus on improving the spatial homogeneity of the tBLG moiré pattern. In this study, we realized a small electronic bandwidth in a device with a smaller moiré period by applying pressure. Local strains in the graphene lattice result in smaller fluctuations of the moiré period as the overall moiré period is reduced (15), therefore we anticipate that applying higher pressure to a device with even larger twist angle could result in further improvements to the device homogeneity. Additionally, the smaller moiré period is anticipated to drive stronger Coulomb repulsion, potentially leading to larger energy scales for the superconducting and correlated insulating phases (6-8). Reliable fabrication of highly homogeneous samples will be critical for further progress in understanding the mechanisms driving the correlated phases observed in these systems, especially in experiments performed without the use of pressure. \n\n# REFERENCESAND NOTES \n\n1. R. Bistritzer,A. H.MacDonald, Moire bands in twisted double-layer graphene. Proc. Natl. Acad. Sci. U.S.A.108,12233-12237 (2011). doi:10.1073/pnas.1108174108 Medline \n2. G.Chen et al., arXiv:1803.01985 (2018). \n3.F.Wu,T. Lovorn, E. Tutuc, A. H. MacDonald, Hubbard Model Physics in Transition Metal Dichalcogenide Moiré Bands. Phys. Rev. Lett. 121, O264O2 (2018). doi:10.1103/PhysRevLett.121.026402 Medline \n4.Y.-H. Zhang, D.Mao,Y. Cao, P. Jarillo-Herrero, T.Senthil, arXiv:1805.08232 (2018) \n5.Y. Cao, V. Fatemi, A. Demir, S. Fang,S.L. Tomarken, J.Y. Luo, J. D.SanchezYamagishi, K. Watanabe,T.Taniguchi,E.Kaxiras, R.C.Ashoori, P. Jarillo-Herrero, Correlated insulatorbehaviour athalf-filing in magic-angle graphene superlattices.Nature 556,80-84(2018).doi:10.1038/nature26154 Medline \n6.Y.Cao,V.FatemiS.Fang,K.Watanabe,T.Taniguchi,E.Kaxiras,P.JariloHer Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43-50 (2018).doi:10.1038/nature26160 Medline \n7. S. Carr,S.Fang, P. Jarilo-Herrero,E. Kaxiras, Pressure dependence of the magic twist angle in graphene superlatices. Phys. Rev. B 98, O85144 (2018). doi:10.1103/PhysRevB.98.085144 \n8.B. L. Chittari, N. Leconte,S. Javvaji, J. Jung, Pressure induced compression of flatbands in twisted bilayer graphene. Electron. Struct. 1, O15oo1 (2019). doi:10.1088/2516-1075/aaead3 \n9.G.Trambly De Laissardiere, O. F. Namarvar, D. Mayou, L. Magaud, Electronic properties of asymmetrically doped twisted graphene bilayers. Phys. Rev. B 93, 235135 (2016).doi:10.1103/PhysRevB.93.235135 \n10.A.A. Zibrov, C. Kometter, H. Zhou,E.M.Spanton, T.Taniguchi, K.Watanabe, M. P. Zaletel,A.F.Young,Tunable interacting composite fermion phases in a half-filled bilayer-grapheneLandaulevel.Nature549,360-364(2017). doi:10.1038/nature23893 Medline \n11.M.Yankowitz, J. Jung, E. Laksono, N. Leconte, B. L.Chittari, K.Watanabe,T. Taniguchi, S. Adam, D. Graf, C. R. Dean, Dynamic band-structure tuning of graphene moiré superlattices with pressure. Nature 557, 404-408 (2018) doi:10.1038/s41586-018-0107-1Medline \n12.K.Kim, M.Yankowitz, B.Fallhazad,S.Kang,H.C.P.Movva,S.Huang,S. Larentis, C.M.Corbet,T.Taniguchi, K.Watanabe,S.K.Banerjee, B.J. LeRoy,E.Tutuc,van der Waals Heterostructures with High Accuracy Rotational Alignment. Nano Lett. 16,1989-1995(2016).doi:10.1021/acs.nanolett.5b05263 Medline \n13.K.Kim,AaluangB.FallhzadS.atisTanguchiKab B.J.LeRoy,A. H.MacDonald, E.Tutuc,Tunable moire bands and strong correlations in smal-twist-angle bilayer graphene. Proc. Natl. Acad. Sci. U.S.A. 114, 3364-3369 (2017).doi:10.1073/pnas.1620140114 Medline \n14. See supplementary materials. \n15. H. Yoo et al.,arXiv:1804.03806 (2018). \n16.Y. Zhang, T.-T. Tang, C. Girit, Z. Hao, M. C. Martin, A. Zettl, M.F. Crommie,Y. R. Shen,F. Wang, Direct observation of a widely tunable bandgap in bilayer graphene. Nature 459,820-823(2009).doi:10.1038/nature08105 Medline \n17. R. Ribeiro-Palau, C. Zhang, K.Watanabe, T.Taniguchi, J. Hone,C. R. Dean, Twistable electronics with dynamically rotatable heterostructures. Science 361, 690-693 (2018).doi:10.1126/science.aat6981 \n18.N. F. Q. Yuan, L. Fu, Model for the metal-insulator transition in graphene superlatticesandbeyond.Phys.Rev.B98,045103(2018). doi:10.1103/PhysRevB.98.045103 \n19. Z. Songet al. arXiv:1807.10676 (2018). \n20.K. Hejazi,C. Liu, H.Shapourian,X.Chen, L.Balents,arXiv:1808.01568 (2018) \n21.C.Xu,LBalentsopologicalSuperconductivityinistedMutlayeraene. Phys. Rev. Lett. 121, 087001 (2018).doi:10.1103/PhysRevLett.121.087001 Medline \n22.H.C.Po,L.Zou,A.Vishwanath,T.Senthil,Origin of Mott Insulating Behaviorand Superconductivity in Twisted Bilayer Graphene. Phys. Rev.X 8, O31089 (2018). doi:10.1103/PhysRevX.8.031089 \n23.B. Roy, V. Juricic,arXiv:1803.1190 (2018) \n24. G. Baskaran, arXiv:1804.00627 (2018). \n25.H.Isobe,N.F.QYuan,L.Fu,Unconventional Superconductivityand Density Waves in Twisted Bilayer Graphene. Phys. Rev. X 8, O41041 (2018). doi:10.1103/PhysRevX.8.041041 \n26.B. Padhi, C. Setty, P. W. Phillips, Doped Twisted Bilayer Graphene near Magic Angles: Proximity to Wigner Crystallization, Not Mott Insulation. Nano Lett. 18, 6175-6180 (2018). doi:10.1021/acs.nanolett.8b02033 Medline \n27.M.Ochi,M.Koshino,K.KurokiPossiblecrelatedinsulatingstatesinmagicangle twisted bilayer graphene under strongly competinginteractions.Phys. Rev.B98, 081102(R)(2018).doi:10.1103/PhysRevB.98.081102 \n28.H.GuoXZhuFngR.TcaletarPgmetrofteactg on a twisted bilayer graphene superlattice. Phys. Rev. B 97, 235453 (2018). doi:10.1103/PhysRevB.97.235453 \n29.T. Huang, L.Zhang,T.Ma, arXiv:1804.06096 (2018). \n30. L. Zhang, arXiv:1804.09047 (2018). \n31. S. Ray, T. Das, arXiv:1804.09674 (2018) \n32.C.-C. Liu, L.-D. Zhang,W.-Q. Chen, F.Yang, Chiral Spin Density Wave and $d+i d$ Superconductivity in the Magic-Angle-Twisted Bilayer Graphene. Phys. Rev. Lett. 121, 217001(2018).doi:10.1103/PhysRevLett.121.217001Medline \n33.M. Fidrysiak, M. Zegrodnik,J. Spatek,Unconventional topological superconductivity and phase diagram for an effective two-orbital model as applied to twisted bilayer graphene. Phys. Rev. B 98, O85436 (2018). doi:10.1103/PhysRevB.98.085436 \n34.L.Rademaker,P.MelldoCharge-transferinsulationintwisted bilayergraphene. Phys. Rev. B98,235158 (2018).doi:10.1103/PhysRevB.98.235158 \n35.D. M. Kennes, J. Lischner, C. Karrasch, Strong correlations and ${\\textsf{d}}+$ id superconductivity in twisted bilayer graphene.Phys. Rev.B98,24l407(R)(2018). doi:10.1103/PhysRevB.98.241407 \n36.Y.You,A. Vishwanath, arXiv:1805.06867 (2018). \n37. J. Gonzalez, T. Stauber,arXiv:1807.01275(2018) \n38.Y.Su,S-Z.Linairingsymmetryandspotaneousrtex-antivoteatticein superconducting twisted-bilayer graphene: Bogoliubov-de Gennes approach. Phys. Rev. B98,195101(2018).doi:10.1103/PhysRevB.98.195101 \n39.Y.Sherkunov,J. J.Betouras, Electronic phases in twisted bilayer grapheneat magic angles as a result of Van Hove singularities and interactions. Phys. Rev. B 98,205151(2018).doi:10.1103/PhysRevB.98.205151 \n40.J. F. Dodaro, S. A. Kivelson, Y. Schattner, X.-Q. Sun, C.Wang, Phases of a phenomenological model of twisted bilayer graphene. Phys. Rev. B 98, 075154 (2018).doi:10.1103/PhysRevB.98.075154 \n41.T. J.Peltonen,R.jajarvi, T.T.Heikkila,Mean-field theory for superconductivity in twistedbilayergraphene.Phys.Rev.B 98,220504(R)(2018). doi:10.1103/PhysRevB.98.220504 \n42.F.Wu,A.H.acDonaldI.artinTheoryofhono-Mediatedupercodvi in Twisted Bilayer Graphene. Phys. Rev.Lett. 121, 257001 (2018). doi:10.1103/PhysRevLett.121.257001 Medline \n43.B. Lian, Z.Wang,B.Andrei Bernevig, arXiv:1807.04382 (2018). \n44.E.Laksono, J. N.Leaw, A. Reaves,M. Singh, X. Wang, S.Adam, X. Gu, Singlet superconductivityenhanced bycharge order in nestedtwisted bilayer graphene Fermisurfaces. SolidStateCommun.282.38-44 (2018). doi:10.1016/j.ssc.2018.07.013 \n45.M.Yankowitzetal.Replication Data for:Tuning superconductivity intwisted bilayergrapheneVersion1.0HarvardDataverse(209).10.7910/D/FIMUEY \n46.L.WangI.MericP.YuangQ.GaoYGaoH.TanTanigucha L. M.Campos, D.A.Muller, J. Guo, P.Kim, J. Hone,K. L. Shepard, C. R. Dean, One dimensional electrical contact to a two-dimensional material. Science 342, 614- 617 (2013).doi:10.1126/science.1244358 Medline \n47.V.V.RyazanovV.A.bozov,A.YRusanov,A.V.eretennikov,A.AGob. Aarts,Coupling of two superconductors through a ferromagnet: Evidence for a I junction. Phys. Rev. Lett. 86, 2427-2430 (2001) doi:10.1103/PhysRevLett.86.2427 Medline \n48.S.M.Frolov, D. J.Van Harlingen,V.V.Bolginov, V.A.Oboznov, V.V. Ryazanov. Josephson interferometry and Shapiro step measurements of superconductorferromagnet-superconductor $0-\\uppi$ junctions. Phys. Rev. B 74, 020503 (2006) doi:10.1103/PhysRevB.74.020503 \n49.D.J. Van Harlingen, Phase-sensitive tests of the symmetry of the pairing state in the high-temperature superconductors-Evidence for $d\\times2-y2$ symmetry. Rev. Mod. Phys.67,515-535 (1995).doi:10.1103/RevModPhys.67.515 \n50.C.C.Tsuei, J. R.Kirtley, Pairing symmetry in cuprate superconductors.Rev. Mod. Phys.72,969-1016 (2000).doi:10.1103/RevModPhys.72.969 \n51.J. Kang, O. Vafek,Symmetry, Maximally Localized Wannier States, and a LowEnergy Model for Twisted Bilayer Graphene Narrow Bands.Phys. Rev.X8,031088 (2018).doi:10.1103/PhysRevX.8.031088 \n52.M. Koshino, N.F. Q.Yuan, T. Koretsune,M. Ochi, K. Kuroki, L. Fu, Maximally Localized Wannier Orbitals and the Extended Hubbard Model for Twisted Bilayer Graphene. Phys. Rev. X8, 031087 (2018). doi:10.1103/PhysRevX.8.031087 \n53.H. K.Pal, arXiv:1805.08803 (2018). \n54. F. Guinea, N. R. Walet, Electrostatic effects, band distortions, and superconductivity in twisted graphene bilayers.Proc. Natl. Acad.Sci. U.S.A.115. 13174-13179 (2018).doi:10.1073/pnas.1810947115 Medline \n55.L.Zou, H.C. Po, A. Vishwanath, T. Senthil, Band structure of twisted bilayer graphene: Emergent symmetries,commensurate approximants, and Wannier obstructions.Phys. Rev.B98,085435(2018).doi:10.1103/PhysRevB.98.085435 \n56.H.C.Po,L.Zou,T.Senthil,A.Vishwanath,arXiv:1808.02482 (2018) \n57.G.Tarnopolsky,A. J.Kruchkov,A. Vishwanath,arXiv:1808.05250 (2018). \n58. J.Ahn,S.Park, B.-J.Yang,arXiv:1808.05375 (2018). \n59.X.Y. Xu, K.T.Law, P.A. Lee, Kekulé valence bond order in an extended Hubbard model on the honeycomb lattice with possible applications to twisted bilayer graphene.Phys. Rev. B98,121406(R)(2018).doi:10.1103/PhysRevB.98.121406 \n60.X.-C.Wu, K.A. Pawlak,C.-M.Jian,C.Xu, arXiv:1805.06906 (2018). \n61.J. M. Pizarro, M. J. Calderon,E.Bascones,arXiv:1805.07303 (2018). \n62. A. Thomson, S. Chatterjee, S. Sachdev, M. S. Scheurer, Triangular antiferromagnetism on the honeycomb lattice of twisted bilayer graphene. Phys. Rev. B98,075109 (2018).doi:10.1103/PhysRevB.98.075109 \n\n# ACKNOWLEDGMENTS \n\nThe authors acknowledge experimental assistance from Jiacheng Zhu and Haoxin Zhou,and helpful discussions with Dan Shahar,Andrew Millis, Oskar Vafek,Mike Zaletel, Leon Balents, Cenke Xu,Andrei Bernevig, Liang Fu,Mikito Koshino,and Pilkyung Moon. Funding: Work at both Columbia and UCSB was funded by the Army Research Office under W911NF-17-1-O323. Sample device design and fabrication was partially supported by DoE Pro-QM EFRC (DE-SC0019443).AFY and CRD separately acknowledge the support of the David and Lucile Packard Foundation. A portion of this work was performed at the National High Magnetic Field Laboratory, which is supported by the National Science Foundation Cooperative Agreement No.DMR-1644779 and the State of Florida. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT,Japan and the CREST (JPMJCR15F3), JST.Author contributions: M.Y.,S.C., H.P.and Y.Z.fabricated the devices. M.Y., S.C. and H.P.performed the measurements and analyzed the data. D.G.loaded the pressure cell. K.W.and T.T.grew the hBN crystals.A.F.Y. and C.R.D.advised on the experiments.The manuscript was written with input from all authors.Competing interests: The authors declare no competing financial interests. Data and materials availability: The data shown in the paper are available at (45). \n\nSUPPLEMENTARY MATERIALS \nwww.sciencemag.org/cgi/content/full/science.aavl910/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S11 \nTable S1 \nReferences (46-62) \n\n24 August 2018; accepted 15 January 2019 \nPublished online 24 January 2019 \n10.1126/science.aav1910 \n\n![](images/8b31d81b0d1db94aed66ad3170cb6f44d3d1207faae3687d4d8f9277872eef1b.jpg) \nFig. 1. Superconductivity in a $\\underline{{1.14^{\\circ}}}$ device.(A) Schematic of an all-van der Waals tBLG heterostructure. tBLG is encapsulated between flakes of BN,with encapsulating flakes of few-layer graphite (FLG)acting as gates.(B) Temperature dependence of the resistance of device Dl over the density range necessary to fil the moiré unit cell, $\\boldsymbol{\\eta}\\in[-{n}_{s},{n}_{s}]$ at $D=0$ . The resistance drops to zero over a finite range of $\\boldsymbol{\\mathsf{\\Pi}}_{n}$ for electron (n $>n_{s}/2)$ )and hole $(n<-{n_{s}}/{2})$ ) doping. (C) Resistance as a function of temperature at optimal doping of the hole-and electron-doped superconductors in blue and red,respectively.(D) Resistance of device Dl as a function of displacement field. At $-n_{s}/2$ an insulating phase develops at positive $D$ ,whereas a superconducting phase develops at negative $D$ . (E to G) Fraunhofer-like quantum interferences of the critical current, arising from one or more Josephson weak links within the sample, measured at: (E) $n=-2.03\\times10^{12}$ $\\mathsf{c m}^{-2}$ and $D=+0.61\\:\\mathrm{V/nm}$ (F) $\\eta=-1.76\\times10^{12}{\\mathsf{c m}}^{-2}$ and $D=-0.59\\lor/\\mathsf{n m}$ and (G) $\\ensuremath{n}=-1.52\\times10^{12}\\mathsf{c m}^{-2}$ and $D$ $=-0.17\\lor/\\mathsf{n m}$ An anomalous quantum interference pattern with a minimum in $I_{c}$ at zero field is observed in (G). The measured temperature is $T\\approx10\\:\\mathrm{mK}$ for all data sets unless otherwise noted. \n\n![](images/dbf935a1b738e20ef92df5824c55c8665bc8c53ac7ccf5798dfbc945f7db4f36.jpg) \n\nFig. 2. Driving superconductivity and correlated insulating states with pressure.(A) Conductance of device D2 $(1.27^{\\circ})$ measured over the entire density range necessary to fillthe moiré unit cellat two values of pressure: O GPa (gray) and 2.21 GPa (blue) at $T=300~\\mathsf{m K}$ . Correlated insulating phases are only very weakly resistive at O GPa, but develop into strongly insulating states at high pressure. The conductance is measured in a twoterminal voltage bias configuration and includes the contact resistance. (lnset) Schematic illustrating the decrease in interlayer spacing of the tBLG under high pressure.(B) Device conductance versus $T^{-1}$ at $-n_{s}/2$ , normalized to its value at $T=25\\mathsf{K}$ (acquired at the density of the orange arrow in panel A). (C) Four-terminal device resistance versus $\\tau$ for hole doping slightly larger than $-n_{s}/2$ , normalized to its value at $T=4.5\\mathsf{K}$ .The device is a metal at O GPa,but becomes a superconductor at high pressure. The two curves at high pressure are taken at optimal doping of the superconductor, and the curve at O GPa is taken at the same density as the 1.33 GPa curve (i.e., acquired roughly at the density marked by the blue arrow in panel A). (D) Energy gaps $\\Delta$ of the correlated insulating phases versus pressure, extracted from the thermal activation measurements in (B) and fit according to $G(T)\\propto e^{-{\\frac{\\Delta}{2k T}}}$ ,where $k$ is the Boltzmann constant. Error bars in the gaps represent the uncertainty arising from determining the linear (thermally activated) regime for the fit. (E) ${{T}_{c}}$ of the superconducting phase versus pressure. ${{T}_{c}}$ is defined as the crossover point between low and high temperature linear fits to the curves in (C). The upper bound for the O GPa curve represents the base temperature of the fridge. \n\n![](images/ffa0ab1b6eba5945030c41cee90a7c56720992c39d0665c97800058ff59cc958.jpg) \nFig.3. Phase diagram of tBLG under pressure.(A) Resistance of device D2 $(1.27^{\\circ})$ over a small range of carrier density near $-n_{s}/2$ versus $\\tau$ .An insulating phase at $-n_{s}/2$ neighbors a superconducting pocket at slightly larger hole doping.An apparent metallic phase separates the two (14), but is obscured by a region of artificially negative resistance in the contacts used for this measurement (colored in white). (B) Similar map as a function of B.(C) Resistance as a function of $\\tau$ at 2.21 GPa at $-n_{s}/2$ (red) and at optimal doping of the superconductor (blue). (D)Map of $d V/d I$ versus $I_{d c}$ and $B$ at $\\eta=-2.1\\times10^{12}{\\mathsf{c m}}^{-2}$ $T=300\\mathsf{m K}$ , and 1.33 GPa. The map is acquired using different contacts from panels (A) and (B), and in particular exhibits a lower upper critical field $H_{c2}$ \n\n![](images/80ee9720857150ea21ee004c741bf8c26ff1431fc1f02751d96e5fbbbc28a45e.jpg) \nFig. 4. Quantum oscillations in flat-band twisted BLG.(A) Landau fan diagram of device D2 $(1.27^{\\circ})$ at 1.33 GPa up to full-filling of the moiré unit cell at $T=300~\\mathrm{mK}$ . Quantum oscillations emerge from the CNP with dominant degeneracy sequence of $\\upnu=\\pm4$ , $^{\\pm8}$ 12,… at low field. Separate sequences of quantum oscillations emerge from +ns/4 with dominant sequence of quantum oscillations emerge from $+n_{s}/4$ with dominant sequence of $\\mathsf{v}=+1$ $+3$ $+5$ ,...,. from $\\pm n_{s}/2$ with dominant sequence of $\\upnu=\\pm2$ $\\pm4$ $\\pm6$ , .., and from $\\pm3n_{s}/4$ with dominant sequence of $\\upnu=\\pm1$ $\\pm2$ , $\\pm3,\\ldots$ Regions of negative measured voltage are set to zero resistance for clarity, most prominently affecting the high-field region of the map between $+n_{s}/2$ and $+3n_{s}/4$ . (B) Schematic Landau level structure corresponding to the observations in (A). Only the Landau levels persisting to the lowest fields are plotted; by $6\\intercal$ , states at all filling factors are observed. (C) Zoom-in of (A) around $-n_{s}/4$ (D) Schematic Landau level structure corresponding to the observations in (C). The dominant degeneracy sequence evolves smoothly from $\\upnu=-4$ $^{-8}$ ,-12.... at low density to $\\upnu=-10$ ,-14,-18.... at high density, switching around $-n_{s}/4$ \n\n![](images/7cd8c5ace2808ce36544f8fc9278f88991508eb4348fe954182fe01d15c4148d.jpg) \nFig. 5. Parallel field dependence of correlated insulating states. (A) Conductance of device D3 $(1.10^{\\circ})$ as a function of carrier density and $B_{||}$ at $T=300\\mathsf{m K}$ . Correlated insulating states at $\\pm n_{s}/2$ are less insulating at large $B_{||}$ ,whereas states at $\\pm n_{s}/4$ are more insulating. The conductance of states at $\\pm3n_{s}/4$ and at the CNP are roughly independent of $B_{||}$ . (B) Energy gap of the correlated insulating state at $+n_{s}/2$ at various $B_{\\parallel}$ measured by thermal activation (fig. SllA). Error bars in the gaps represent the uncertainty arising from determining the linear (thermally activated) regime for the fit. \n\n# Science \n\n# Tuning superconductivity in twisted bilayer graphene \n\nMatthew Yankowitz, Shaowen Chen, Hryhoriy Polshyn, Yuxuan Zhang, K. Watanabe, T. Taniguchi, David Graf, Andrea F. Young and Cory R. Dean \n\npublished online January 24, 2019originally published online January 24, 2019 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 51 articles, 5 of which you can access for free http://science.sciencemag.org/content/early/2019/01/25/science.aav1910#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41928-018-0058-4", + "DOI": "10.1038/s41928-018-0058-4", + "DOI Link": "http://dx.doi.org/10.1038/s41928-018-0058-4", + "Relative Dir Path": "mds/10.1038_s41928-018-0058-4", + "Article Title": "Field-effect transistors made from solution-grown two-dimensional tellurene", + "Authors": "Wang, YX; Qiu, G; Wang, RX; Huang, SY; Wang, QX; Liu, YY; Du, YC; Goddard, WA ; Kim, MJ; Xu, XF; Ye, PD; Wu, WZ", + "Source Title": "NATURE ELECTRONICS", + "Abstract": "The reliable production of two-dimensional (2D) crystals is essential for the development of new technologies based on 2D materials. However, current synthesis methods suffer from a variety of drawbacks, including limitations in crystal size and stability. Here, we report the fabrication of large-area, high-quality 2D tellurium (tellurene) using a substrate-free solution process. Our approach can create crystals with process-tunable thickness, from a monolayer to tens of nullometres, and with lateral sizes of up to 100 mu m. The chiral-chain van der Waals structure of tellurene gives rise to strong in-plane anisotropic properties and large thickness-dependent shifts in Raman vibrational modes, which is not observed in other 2D layered materials. We also fabricate tellurene field-effect transistors, which exhibit air-stable performance at room temperature for over two months, on/off ratios on the order of 10(6), and field-effect mobilities of about 700 cm(2) V-1 s(-1). Furthermore, by scaling down the channel length and integrating with high-k dielectrics, transistors with a significant on-state current density of 1 A mm(-1) are demonstrated.", + "Times Cited, WoS Core": 701, + "Times Cited, All Databases": 758, + "Publication Year": 2018, + "Research Areas": "Engineering", + "UT (Unique WOS ID)": "WOS:000444074900011", + "Markdown": "# Field-effect transistors made from solution-grown two-dimensional tellurene \n\nYixiu Wang1,9, Gang $\\mathsf{Q i u}^{2,3,9}$ , Ruoxing Wang1,9, Shouyuan Huang4, Qingxiao Wang5, Yuanyue Liu6,7,8, Yuchen ${\\tt D u}^{2,3}$ , William A. Goddard ${\\|\\|}^{6}$ , Moon J. Kim4, Xianfan $\\mathsf{X}\\mathsf{u}^{3,4}$ , Peide D. $\\forall e^{2,3\\star}$ and Wenzhuo $\\mathsf{\\pmb{W}}\\mathsf{\\pmb{u}}^{\\oplus1,3\\star}$ \n\nThe reliable production of two-dimensional (2D) crystals is essential for the development of new technologies based on 2D materials. However, current synthesis methods suffer from a variety of drawbacks, including limitations in crystal size and stability. Here, we report the fabrication of large-area, high-quality 2D tellurium (tellurene) using a substrate-free solution process. Our approach can create crystals with process-tunable thickness, from a monolayer to tens of nanometres, and with lateral sizes of up to $100\\upmu\\mathrm{m}$ . The chiral-chain van der Waals structure of tellurene gives rise to strong in-plane anisotropic properties and large thickness-dependent shifts in Raman vibrational modes, which is not observed in other 2D layered materials. We also fabricate tellurene field-effect transistors, which exhibit air-stable performance at room temperature for over two months, on/off ratios on the order of $\\pmb{10^{6}}$ , and field-effect mobilities of about $700c m^{2}V^{-1}s^{-1}$ . Furthermore, by scaling down the channel length and integrating with high- $\\pmb{k}$ dielectrics, transistors with a significant on-state current density of $1\\mathsf{A}\\mathsf{m}\\mathsf{m}^{-1}$ are demonstrated. \n\nhe continuing exploration of the properties of two-dimensional (2D) materials $^{1-4}$ and the integration of these materials into new technologies5–8 requires reliable synthesis methods. The potential of scaling up existing approaches, however, remains uncertain9,10. This is due to factors such as the growth substrates and conditions11–13, small crystal sizes14 and the instability of the synthesized materials11,15,16. For example, top-down liquid-phase exfoliation is a promising approach for the production of large quantities of various atomically thin layered materials14, including graphene, transition metal dichalcogenides and boron nitride. However, poor control over thickness uniformity and the small size of the derived materials undermines the viability of the approach. Control of nucleation and growth during the bottom-up chemical vapour deposition (CVD) process can lead to high-quality crystals of graphene9 and $\\mathrm{MoS}_{2}$ (ref. 10) with controlled thicknesses over a centimetre-sized lateral area. However, the method requires high growth temperatures and delicate control of the growth atmosphere, which limits its potential for scale-up. The epitaxial growth of ultrathin materials with exotic electronic properties, such as silicene11, borophene12 and stanene13, has also been explored, although the need for substrates suitable for epitaxial growth and the stringent requirements of an ultrahigh-vacuum system increase the complexity of the synthesis. \n\nGroup VI tellurium has a unique chiral-chain crystal lattice in which individual helical chains of Te atoms are stacked together by van der Waals type bonds and spiral around axes parallel to the [0001] direction at the centre and corners of the hexagonal elementary cell17 (Fig. 1a). Each tellurium atom is covalently bonded with its two nearest neighbours on the same chain. Earlier studies revealed that bulk Te has small effective masses and high hole mobilities due to spin–orbit coupling18. The lone-pair and anti-bonding orbitals give rise to a slightly indirect bandgap in the infrared regime $(\\sim0.35\\mathrm{eV})$ in bulk $\\mathrm{Te^{19}}$ , which has a conduction band minimum (CBM) located at the H point of the Brillouin zone, and a valence band maximum (VBM) that is slightly shifted from the H point along the chain direction, giving rise to hole pockets near the H point20. When the thickness is reduced, the indirect feature becomes more prominent, as shown by our first-principles calculations (see Methods for computation details). For example, the VBM of fourlayer Te is further shifted to (0.43, 0.34) (in the unit of the surface reciprocal cell), while the CBM remains at $(1/2,1/3)$ (Fig. 1b, inset). Accompanied by the shift of the VBM, the bandgap also increases (see Methods and Supplementary Fig. 1) due to the quantum confinement effect, and eventually reaches $\\mathord{\\sim}1\\mathrm{eV}$ for monolayer $\\mathrm{Te}^{21}$ . Te has other appealing properties, such as its photoconductivity22, thermoelectricity20 and piezoelectricity23, for applications in sensors, optoelectronics and energy devices. A wealth of synthetic methods have been developed to derive Te nanostructures24–26, which favour the 1D form due to the inherent structural anisotropy in Te. Much less is known about the 2D form of Te and its related properties. \n\nIn this Article, we report a substrate-free solution process for synthesizing large-area, high-quality 2D Te crystals (termed tellurene) with a thickness of a monolayer to tens of nanometres and a unique chiral-chain van der Waals structure that is fundamentally different from layered van der Waals materials. \n\nSynthesis and structural characterization of 2D tellurene We use the term X-ene to describe 2D forms of elemental materials without considering the specific bonding21,27. The samples are grown through the reduction of sodium tellurite $\\left({\\mathrm{Na}}_{2}{\\mathrm{TeO}}_{3}\\right)$ by hydrazine hydrate $\\mathrm{(N}_{2}\\mathrm{H}_{4}\\mathrm{)}$ in an alkaline solution at temperatures from 160 to $200^{\\circ}\\mathrm{C},$ in the presence of crystal-face-blocking ligand polyvinylpyrrolidone (PVP) (see Methods). The inset to Fig. 1c presents an optical image of a typical tellurene solution dispersion after reactions at $180^{\\circ}\\mathrm{C}$ for $20\\mathrm{h}$ when the $\\mathrm{Na}_{2}\\mathrm{TeO}_{3}{:}\\mathrm{PVP}$ mole ratio is 52.4:1 (see Methods). The 2D Te flakes can be transferred and assembled at large scale into a single-layer continuous thin film through a Langmuir–Blodgett (LB) process28 or into a networked continuous thin $\\mathrm{film}^{8,29,30}$ through ink-jet printing (see Methods) onto various substrates (Supplementary Fig. 2) for future characterization and device integration. It should be noted that current LB approaches still lack certain desired capabilities in terms of film continuity and uniformity when compared to other methods such as ink-jet printing8,29,30 for assembling solution-derived 2D materials into high-performance devices. These preliminary results (Supplementary Fig. 2) show potential and warrant more systematic work for future large-scale assembly and applications of solutionderived 2D functional materials. \n\n![](images/97aa9dcf7882e248ee96b63f39dfbbaed38ce96f807b53beac3f8c5a8c40fbde.jpg) \nFig. 1 | Solution-grown large-area 2D Te and material characterization. a, Atomic structure of Te. b, Band structure of four-layer Te, calculated using the Perdew–Burke–Ernzerhof (PBE) functional. Valence bands are shown in blue, and conduction bands are in red. Inset, Local band structure near the VBM; Γ,​ (0,0); X, (0.5, 0); Y, (0, 0.5); S, (0.5, 0.5); all in units of the surface reciprocal lattice vectors. See the Methods section entitled ‘first-principles calculations’ for further information about the electronic structure. c, Optical image of solution-grown Te flakes. Inset, Optical image of the Te solution dispersion. Scale bar, $20\\upmu\\mathrm{m}$ . d, Atomic force microscope (AFM) image of a $10\\mathsf{n m}2\\mathsf{D}$ Te flake. Scale bar, $30\\upmu\\mathrm{m}$ . e, HAADF–STEM image of tellurene. False-coloured (in blue) atoms are superimposed on the original STEM image to highlight the helical structure. f, Diffraction pattern of tellurene. g, 3D illustration of the structure of tellurene. \n\nOur individual 2D flakes have edge lengths ranging from 50 to $100\\upmu\\mathrm{m}$ and thicknesses from 10 to $100\\mathrm{nm}$ (Fig. 1d and Supplementary Fig. 3). The structure, composition and quality of these tellurene crystals were analysed by high-angle annular darkfield scanning transmission electron microscopy (HAADF–STEM), high-resolution transmission electron microscopy (HRTEM), energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) and $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) (Fig. 1e,f and Supplementary Fig. 4). Figure 1e shows a typical atomically resolved HAADF–STEM image of a tellurene flake (see Methods). The helical chains and a threefold screw symmetry along $\\left\\langle0001\\right\\rangle$ ​are visible (Fig. 1e). The interplanar spacings are $2.2\\mathring\\mathrm{A}$ and $\\mathbf{\\bar{6.0\\AA}}$ , corresponding to Te ( ̄10) and (0001) planes31, respectively. Figure 1f presents a selective area electron diffraction (SAED) pattern along the [1010] zone axis, which is perpendicular to the top surface of the flake. No point defects or dislocations were observed over a large area within single crystals (Supplementary Fig. 4). EDS result confirmed the chemical composition of Te (Supplementary Fig. 4). Similar characterizations and analyses of dozens of 2D flakes with different sizes indicate that all samples grow laterally along the $\\left\\langle0001\\right\\rangle$ ​ and $\\langle1{\\overline{{2}}}10\\rangle$ ​directions, with vertical stacking along the 〈​1010〉​direction (Fig. 1g). \n\n# Growth mechanism and geometric control of 2D tellurene \n\nControl of PVP concentration is key to obtaining 2D tellurene. Figure 2a shows the productivity (see Methods) of tellurene grown at $180^{\\circ}\\mathrm{C}$ versus time for a broad range of $\\mathrm{Na_{2}T e O_{3}/P V P}$ mole ratios. When a smaller amount of PVP is used, the first 2D structures appear after a shorter reaction time (Fig. 2a and Supplementary Fig. 5). A closer examination of reactions with different PVP concentrations reveals an intriguing morphology evolution in growth products with time. For each PVP concentration, the initial growth products are dominantly 1D nanostructures (Fig. 2b and Supplementary Fig. 5), similar to previous reports24–26. After a certain period of reaction, structures possessing both 1D and 2D characteristics start to emerge (Fig. 2b and Supplementary Fig. 5). TEM characterizations indicate that the long axes (showing 1D characteristics) of these flakes are $\\left\\langle0001\\right\\rangle$ ​oriented, and the lateral protruding regions (showing 2D characteristics) grow along the $\\langle1{\\overline{{2}}}10\\rangle$ ​ direction, with the $\\{1\\bar{0}\\bar{1}0\\}$ facets as the top/bottom surfaces (Supplementary Fig. 6). The 2D regions are enclosed by edges with atomic-level step roughness (Supplementary Fig. 6). These high energy edges are not specific to certain planes during the intermediate states. These structures also have more uneven surfaces than 2D tellurene (Supplementary Fig. 6), further manifesting their intermediate nature. Finally, the ratio of 2D tellurene flakes with a straight $\\{1\\overline{{2}}10\\}$ edge increases with a reduction in 1D and intermediate structures (Supplementary Fig. 5), and reaches a plateau after an extended period of growth, for example, $\\mathord{\\sim}30\\mathrm{h}$ (Fig. 2a and Supplementary Fig. 5). Growth with a lower level of PVP has a smaller final productivity (Fig. 2a and Supplementary Fig. 5). The observed morphology evolution suggests that the balance between kinetic and thermodynamic growth dictates the transformation from 1D structures to 2D forms (Fig. 2b). In the initial growth, PVP is preferentially adsorbed on the $\\{10\\bar{1}0\\}$ surfaces of the nucleated seeds26, which promotes kinetic-driven 1D growth (Supplementary Fig. 5). As the reaction continues, $\\{10\\bar{1}0\\}$ surfaces of the formed structures would become partially covered due to insufficient PVP capping. Because the $\\{10\\bar{1}0\\}$ surfaces have the lowest free energy in tellurium32, the growth of $\\{10\\bar{1}0\\}$ surfaces along the $\\langle1{\\overline{{2}}}10\\rangle$ ​direction significantly increases through thermodynamic-driven assembly, giving rise to the observed intermediate structures. Enhanced growth along the $\\langle1{\\overline{{2}}}10\\rangle$ ​ direction together with continued $\\left\\langle0001\\right\\rangle$ ​growth (Supplementary Fig. 6) leads to the formation of 2D tellurene (Supplementary Fig. 5 and Fig. 2b). \n\nThe sizes and thicknesses of tellurene can also be effectively modulated by controlling the ratio between sodium tellurite and PVP (Fig. 2c and Supplementary Fig. 7). The width of tellurene monotonically decreases with a reduction in PVP level. This thickness is minimized when a medium level of PVP is used (for example, a $\\mathrm{Na_{2}T e O_{3}/P V P}$ ratio of $\\sim52.4{:}1$ , group 12 in Fig. 2c and Supplementary Fig. 7), and increases with both an increase and decrease of PVP from this medium level (Fig. 2c). With a small amount of PVP, the solution is supersaturated with Te source, and homogeneous nucleation of Te can occur on a large scale, consuming resources for subsequent growth. As a result, the Ostwald ripening of Te nuclei is shortened, and the final tellurene crystals have smaller sizes than samples grown at higher PVP concentrations. The low PVP level also leads to more significant growth along thickness directions. On the other hand, when the PVP level is high, the fewer nucleation events allow a sufficient supply of Te source for subsequent growth, leading to increased width and thickness. Also, the productivity of tellurene increases with the reaction temperature from 160 to $180^{\\circ}\\mathrm{C}$ (Supplementary Fig. 8). This is probably because a higher temperature promotes the forward reaction rate in the half reaction of endothermic hydrazine oxidation (Supplementary Notes). However, when the temperature increases from 180 to $200^{\\circ}\\mathrm{C},$ possible breaking of the van der Waals bonds between Te chains by the excessive energy could lead to saturated productivity. \n\nTellurene crystals with a thickness smaller than $10\\mathrm{nm}$ and ultimately a monolayer structure can be further derived through a solvent-assisted post-growth thinning process (see Methods). The thickness of the tellurene decreases with time after acetone is introduced into the growth solution (Supplementary Fig. 9). After $6\\mathrm{h}$ , the average thickness of tellurene is reduced to ${\\sim}10\\mathrm{nm}$ , with the thinnest flake $4\\mathrm{nm}$ thick ( $_{\\sim10}$ layers) (Supplementary Fig. 9). Due to their poor solubility in acetone, PVP molecules tend to desorb from the tellurene and undergo aggregation33, giving rise to the sedimentation of tellurene over time in acetone (Supplementary Fig. 9). Lacking the protection of PVP, the tellurene surfaces become exposed and react with the alkaline growth solution (pH of ${\\sim}11.5)^{34}$ , leading to the reduced thickness. We also performed control experiments using other types of solvent in the growth solution (Supplementary Fig. 10), the results of which suggest that PVP solubility in the solvent significantly affects the above process. Large-area (up to $100\\upmu\\mathrm{m}$ in lateral dimensions) tellurene crystals with monolayer, bilayer, trilayer and few-layer thickness can also be obtained (Fig. 2d and Supplementary Fig. 11) by controlling the pH values of the tellurene dispersion solution in the above post-growth thinning process (see Methods, Fig. 2d and Supplementary Fig. 12). \n\n# Thickness- and angle-dependent Raman spectra \n\nThese high-quality ultrathin tellurene crystals with controlled thickness provide an ideal system to explore their intrinsic properties in the 2D limit. We first characterized the optical properties of as-synthesized tellurene with a wide range of thickness (from monolayer to $37.4\\mathrm{nm}\\mathrm{,}$ ) by angle-resolved polarized Raman spectroscopy at room temperature (see Methods). The incident light enters along the [1010] direction and is polarized into the [0001] helical chain direction of the tellurene. The Raman spectra of tellurene samples with different thickness (Fig. 3a) exhibit three main \n\n![](images/93f37ac86068e5e28571e2b7998d1f5f8102c5a7daa092e17697740cd6b3ae3d.jpg) \nFig. 2 | Solution processing for tellurene. a, Growth outcome for different PVP concentrations with different reaction times. Mean values from five technical replicates are shown. Error bars represent s.d. b, Morphology evolution from 1D Te structures to 2D Te. c, Thickness and width modulation of 2D Te. Mean values from eight technical replicates are shown. Error bars represent s.d. d, Post-growth thinning process with solution ${\\mathsf{p H}}10.5$ to obtain ultrathin few-layer and monolayer tellurene. Scale bars, $5\\upmu\\mathrm{m}$ . Mean values from eight technical replicates are shown. Error bars represent s.d. \n\nRaman-active modes—one A-mode and two E-modes—which correspond to chain expansion in the basal plane, bond-bending around the [ ̄10] direction, and asymmetric stretching mainly along the [0001] helical chain35, respectively (Supplementary Fig. 13). For 2D Te samples thicker than $20.5\\mathrm{nm}$ , three Ramanactive modes located at $92c m^{-1}$ ( $\\mathrm{\\cdot}\\mathrm{E}_{1}$ transverse (TO) phonon mode), $121\\mathrm{cm}^{-1}$ $\\mathbf{A}_{1}$ mode) and $143\\mathrm{cm}^{-1}\\left(\\mathrm{E}_{2}\\mathrm{mode}\\right)$ were identified (Fig. 3a), which agree well with previous observations in bulk and nanostructured tellurium36–38, indicating that although these thicker crystals possess 2D morphology, their symmetric properties can still be characterized as bulk. The appreciable effective dynamic charge induced for the $\\mathrm{E}_{1}$ mode in tellurium leads to a split of $\\mathrm{E}_{1}$ doublets at $92c m^{-1}$ and $105\\mathrm{cm}^{-1}$ for transverse (TO) or longitudinal (LO) phonons, respectively37. The absence of the $\\mathrm{E}_{1}$ (LO) mode in our observed results for 2D Te thicker than $20.5\\mathrm{nm}$ , similar to previous reports on bulk and nanostructured tellurium36–38, may be attributed to the different signs in the deformation potential and the electro-optic contribution to the Raman scattering tensor, giving rise to cancellation if both contributions have the same magnitude39. As the thickness decreases from 20.5 to $9.1\\mathrm{nm}$ (Fig. 3a), the deformation potential in the tellurene lattice increases while the electro-optic effect weakens40, leading to the appearance of the $\\mathbf{E}_{1}$ (LO) mode in the Raman spectra for 2D Te crystals with intermediate thickness. When the thickness of the 2D Te further reduces (smaller than $9.1\\mathrm{nm}$ in Fig. 3a), degeneracy in the $\\mathrm{E}_{1}$ TO and LO modes occurs with peak broadening, possibly due to the intrachain atomic displacement, the electronic band structure changes and the symmetry assignments for each band41, all of which are affected by the sample thickness. \n\nWhen the thickness of tellurene decreases, there are significant blueshifts for both $\\mathbf{A}_{1}$ (shift to $136\\mathrm{cm^{-1}}$ for monolayer) and $\\mathrm{E}_{2}$ (shift to $149\\mathrm{cm}^{-1}$ for monolayer) modes (Fig. 3a). The hardened in-plane $\\mathrm{E}_{2}$ vibration mode in thinner tellurene, similar to reported observations for black phosphorus42 and $\\mathbf{MoS}_{2}$ (ref. 43), may be attributed to the enhanced interlayer long-range Coulombic interactions when thinned down. The observed blueshift for the $\\mathbf{A}_{1}$ mode in 2D Te, in strong contrast to 2D layered van der Waals materials, which usually show a redshift for the outof-plane vibration mode when thinned down15,42,43, is thought to be closely related to the unique chiral-chain van der Waals structure of tellurene. When thinned down, the lattice deformation within the 2D plane gives rise to the attenuated inter-chain van der Waals interactions and enhanced intra-chain covalent interactions in the individual tellurene layer, leading to more effective restoring forces on tellurium atoms and hence a hardened outof-plane $\\mathbf{A}_{1}$ vibration mode (Supplementary Fig. 13). This unique structure of tellurene also results in the giant thickness-dependent shift in Raman vibrational modes, which is unseen in 2D layered van der Waals materials42–44. The interaction between the substrate $\\mathrm{(SiO_{2}/S i)}$ and 2D Te flakes could also contribute to the hardened $\\mathbf{A}_{1}$ and $\\mathrm{E}_{2}$ modes36. Stiffening of vibrational modes in monolayer tellurene (Fig. 3a) is consistent with its structure reconstruction, where extra bonds are formed between neighbouring chains in the single-layer tellurium21,27,45. \n\n![](images/0567f54a1ff51ef70f71e78ecc668e9adde248cfe06523b95fda0adfa711d9b3.jpg) \nFig. 3 | Angle-resolved Raman spectra for 2D tellurene with different thicknesses. a, Raman spectra for 2D Te with different thicknesses. b–f, Angleresolved Raman spectra for a $13.5\\cdot\\mathsf{n m}$ -thick flake: evolution with angles between crystal orientation and incident laser polarization (b) and polar figures of Raman intensity corresponding to $\\mathsf{A}_{1}$ and two E modes located at 94 (E1 TO), 105 (E1 LO), 125 (A1) and 143 $(\\mathsf{E}_{2})\\mathsf{c m}^{-1}(\\mathsf{c}-\\mathsf{f})$ . Fitting curves are described in the Supplementary Methods. \n\nReduced in-plane symmetry in the chiral-chain van der Waals structure of tellurene indicates a strong in-plane anisotropy for its material properties. We further characterized the anisotropic optical properties of as-synthesized tellurene with three different thicknesses (28.5, 13.5 and $9.7\\mathrm{nm}\\mathrm{\\}$ ) by angle-resolved polarized Raman spectroscopy at room temperature (see Methods). By rotating the tellurene flakes in steps of $15^{\\circ}$ , we observed changes in the angle-resolved Raman peak intensities (Fig. 3b and Supplementary Figs 14a and 15a). We extracted the peak intensities of different modes by fitting with a Lorentz function and plotted them into the corresponding polar figures (Fig. 3c–f, Supplementary Figs. 14b–e and 15b–d) (see Methods). Although all the modes change in intensity with polarization angle, we find that the peak for the $\\mathbf{A}_{1}$ mode in all samples exhibits the largest sensitivity to the relative orientation between the [0001] direction and the polarization of the excitation laser (middle panels of Fig. 3b and Supplementary Figs. 14a and 15a). It is worth noting that the direction of maximum intensity in the $\\mathbf{A}_{1}$ polar plot changes with sample thickness. More specifically, $\\mathbf{A}_{1}$ polar plots for the 13.5 and $28.5\\mathrm{nm}$ samples show the maximum intensity at 90 and $270^{\\circ}$ along the [1 ̄10] direction (Fig. 3e and Supplementary Fig. 15c). However, when the thickness decreases to $9.7\\mathrm{nm}$ , the maximum intensity direction switches to $0^{\\circ}$ and $180^{\\circ}$ along the [0001] direction (Supplementary Fig. 14d). A similar phenomenon also occurs for $\\mathrm{E}_{1}$ LO modes in the 13.5 and $9.7\\mathrm{nm}$ samples (Fig. 3d and Supplementary Fig. 14c). Such thickness-dependent anisotropic Raman scattering could be attributed to the different absorption spectral range in the [0001] and [1 ̄10] directions46 and the anisotropic interference effect41. The angleresolved Raman results also confirm that the helical Te atom chains in the as-synthesized tellurene are oriented along the growth direction of the tellurene flake, matching the TEM results (Fig. 1e). \n\n# 2D tellurene field-effect transistors \n\nFinally, we explored the electrical performance of tellurene fieldeffect transistors (FETs) to demonstrate their great potential for logic electronics application. Back-gate devices were fabricated on high$k$ dielectric substrates, and source–drain regions were patterned by electron-beam lithography with the channel parallel to the [0001] direction of the tellurene (for details see Methods). We chose Pd/Au ${\\mathrm{'}}50/50{\\mathrm{nm}})$ for the metal contacts because Pd has a relatively high workfunction that can reduce the contact resistance in p-type transistors47–49. Long-channel devices were first examined (channel length, ${3\\upmu\\mathrm{m}},$ ), where the contact resistance is negligible and the transistor behaviour is dominated by the intrinsic electrical properties of the channel material. Figure 4a presents the transfer curve of a typical $7.5\\mathrm{-nm}$ -thick 2D Te FET measured at room temperature. The device exhibits p-type characteristics with slight ambipolar transport behaviour due to its narrow-bandgap nature, with large drain current over $300\\mathrm{mA}\\mathrm{mm}^{-1}$ (Supplementary Fig. 23) and high on/off ratio on the order of ${\\sim}1\\times10^{5}$ . The p-type behaviour originates from the high level of the Te valence band edge, as shown by our first-principles calculations (Supplementary Fig. 16). Meanwhile, the process-tunable thickness of tellurene allows modulation of the electrical performance in tellurene transistors. Overall, the important metrics of tellurene-based transistors, such as on/off ratio, mobility and on-state current level, are superior or comparable to those of transistors based on other 2D materials11,15,16,50. We further investigated the thickness dependence of two key metrics of device performance—on/off ratio and fieldeffect mobility—for more than fifty 2D Te long-channel devices, with flake thickness ranging from over $35\\mathrm{nm}$ to a monolayer $(\\sim0.5\\mathrm{nm})$ , to elucidate the transport mechanism of 2D Te FETs (Fig. 4b). The linear behaviour of the output curves in the low $V_{\\mathrm{ds}}$ region (Supplementary Fig. 23) suggests that the contact resistance is low (see Supplementary Notes and Supplementary Fig. 19 for the extracted contact resistance), which ensures the soundness of the extraction of field-effect mobility from the slope of the linear region of the transfer curves (see Methods). The field-effect mobilities of 2D Te transistors peak at ${\\sim}700\\ c m^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ at room temperature at a thickness of about $16\\mathrm{{nm}}$ and decrease gradually with a further increase in thickness. The transfer curves of thin devices with thickness of $2.8\\mathrm{nm}$ (approximately six layers), $1.7\\mathrm{nm}$ (approximately four layers), $1.0\\mathrm{nm}$ (bilayer) and $0.5\\mathrm{nm}$ (monolayer) are presented in Supplementary Fig. 24. A benchmark comparison with black phosphorus, which is also a narrow-bandgap p-type 2D material, shows that solution-synthesized 2D Te has approximately two to three times higher mobility than black phosphorus when the same device structure, geometry and mobility extraction method are adopted15 (Supplementary Fig. 21). This thickness dependence is similar to that of other layered materials that experience screening and interlayer coupling15,16 (Supplementary Notes and Supplementary Fig. 20). The field-effect mobility is also affected by the contribution of the carriers from layers near the semiconductor–oxide interface. Thinner samples are more susceptible to charge impurities at the interface and surface scattering, which explains the decrease in the mobility of the few-layer tellurene transistors. We expect to be able to improve the mobility of tellurene through approaches such as improving the interface quality with high- $k$ dielectrics51 or hexagonal boron nitride encapsulation to reduce the substrate phonon scattering and charge impurity. For bilayered tellurene transistors, the external field-effect mobility is reduced to ${\\sim}1\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ . This is due to the bandgap increasing in few-layer tellurene to form a much higher Schottky barrier, which may introduce a large deviation in extracting mobility due to the drastically increased contact resistance. Because of the reduced gate electrostatic control in thicker flakes, the thickness-dependent on/ off ratios (Supplementary Notes) steeply decrease from ${\\sim}1\\times10^{6}$ to less than 10 once the crystal thickness approaches the maximum depletion width of the films, with a trend similar to other reported narrow-bandgap depletion-mode 2D FETs15,16. \n\n![](images/b9070e09263c7b8eed8103371cf34ea7b030b2f6bbdebee35066422060d8632b.jpg) \nFig. 4 | 2D tellurene FET device performance. a, Transfer curve of a typical long-channel 2D tellurene transistor with a thickness of $7.5\\mathsf{n m}$ . b, Thicknessdependent on/off ratio (orange triangles) and field-effect mobility (grey circles) for 2D tellurene transistors. The non-monotonic dependence of mobility on thickness can be fitted using the Thomas–Fermi screening model (Supplementary Notes and Supplementary Fig. 20). c, Anisotropic mobility measurements along [0001] and [ ̄10] directions. Inset, Optical image of a typical device for anisotropic transport measurement. Scale bar, $10\\upmu\\mathrm{m}$ . d, Transfer curves of a typical 2D tellurene transistor with a thickness of $15\\mathsf{n m}$ , with stability measured for up to 55 days. Inset, False-coloured SEM image of a tellurene transistor. The scale bar is $10\\upmu\\mathrm{m}$ ) \n\n![](images/3d975b5ee1ac5eeb86385774db8e208a0675009d7d1aaf854d9e2b695e69e38f.jpg) \nFig. 5 | High on-state current density in short-channel tellurene devices. a,b, Output (a) and transfer (b) curves of an 11.1-nm-thick tellurene transistor with $300\\mathsf{n m}$ channel. c, Trade-off between on/off ratio and maximum drain current measured in over 30 short-channel devices with the same geometry and dimension as in a and b. The maximum drain current of several devices surpassed 1 A $\\mathsf{m}\\mathsf{m}^{-1}$ . \n\nThe in-plane anisotropic electrical transport properties were also studied at room temperature. To minimize flake-to-flake variation and geometric non-ideality, we applied a dry-etching method (see Methods) to trim two identical rectangles from the same 2D Te flake. One of the rectangles was aligned along the 1D atomic chain [0001] direction and the other along the [1 ̄10] direction (Fig. 4c, inset). Long-channel FETs (channel length, ${8\\upmu\\mathrm{m}},$ ) were fabricated to minimize contact influence and manifest the intrinsic material properties. The extracted field-effect mobilities along these two primary directions from seven 2D Te samples exhibit an average anisotropic mobility ratio of $1.43\\pm0.10$ (Fig. 4c). A typical set of results measured from a $22\\mathrm{-nm}$ -thick sample is shown in Supplementary Fig. 22. This anisotropic ratio in mobility is slightly lower than that reported for bulk tellurium52, possibly due to the enhanced surface scattering in our ultrathin Te samples. Our first-principles calculations show a similar degree of anisotropy in the effective masses along these two orthogonal directions (Fig. 1b, $0.32m_{0}$ perpendicular to the chain and $0.30m_{0}$ along the chain; see Methods). \n\nGreat air stability was also demonstrated in tellurene transistors with different flake thicknesses. The electrical performance of a $15\\mathrm{-nm}$ -thick transistor was monitored after being exposed in air for two months without any encapsulation, as shown in Fig. 4d. No significant degradation was observed in the device during the twomonth period, except a slight threshold voltage shift probably arising from sequential measurement variation. We also demonstrated that this good air stability is valid for almost the entire thickness range from thick flakes down to $3\\mathrm{nm}$ (Supplementary Fig. 25). For flakes thinner than this, the films no longer conduct after the first couple of days. \n\nMore strikingly, by scaling down the channel length and integrating with our atomic-layer-deposition-grown high- $\\mathbf{\\nabla}\\cdot k$ dielectric, we achieved a record-high drive current of over $1\\mathrm{A}\\mathrm{mm}^{-1}$ at a relatively low $V_{\\mathrm{ds}}{=}1.4\\:\\mathrm{V}.$ Figure 5a,b presents $I{-}V$ curves for a short-channel device with channel length of $300\\mathrm{nm}$ fabricated on an $11\\mathrm{-nm}$ -thick Te flake. The on/off ratio at small drain bias ( $\\dot{V}_{\\mathrm{d}s}=$ $-0.05\\mathrm{V})$ is over $1\\times10^{3}$ , which is still a decent value considering its narrow bandgap of ${\\sim}0.4\\mathrm{eV}$ (Supplementary Fig. 1). The off-state performance deteriorates slightly at large drain voltage $\\cdot}_{\\mathrm{{}}V_{\\mathrm{{ds}}}=-1}\\mathrm{{}}V,$ blue circles in Fig. 5b) due to the short-channel effect. A large drain voltage reduces the barrier height for n-type electron transport and the electron current is unhindered, which is also reflected in the upswing of drain current at large $V_{\\mathrm{d}s}$ in the output curve (Fig. 5a). Such an effect is common in narrow-bandgap short-channel devices53,54 and can be mediated through proper contact engineer$\\mathrm{ing^{54}}$ . Figure 5c shows the relationship between two key transistor parameters—on/off ratio and maximum drain current—for over 30 devices with different channel thicknesses. Generally speaking, a short-channel device with a flake thickness of around $7-8\\mathrm{nm}$ offers the best performance, with an on/off ratio of ${\\sim}1\\times10^{4}$ and maximum drain current of ${>}600\\mathrm{mAmm^{-1}}$ . It is also worth mentioning that the maximum drain current we achieved was $1.06\\mathrm{Amm^{-1}}$ , with several devices exceeding $1\\mathrm{A}\\mathrm{mm}^{-1}$ , which is the highest value achieved in any two-dimensional material transistor reported, to the best of our knowledge53,55,56. This number is also comparable to that of conventional semiconductor devices. \n\n# Conclusions \n\nWe have developed a simple, low-cost, solution-based approach for the scalable synthesis and assembly of 2D Te crystals. These highquality 2D Te crystals have high carrier mobility and are air-stable (measured up to two months). Our prototypical 2D Te device shows a good all-around figure of merit (Supplementary Fig. 26 and Supplementary Table 1) compared to existing 2D materials, and record-high on-state current capacity. Our approach has the potential to produce stable, high-quality, ultrathin semiconductors with good control of composition, structure and dimensions, opening up opportunities for applications in electronics, optoelectronics, energy conversion and energy storage. 2D tellurene, as a chiral-chain van der Waals solid, adds a new class of nanomaterials to the large family of 2D crystals. \n\n# Methods \n\nSynthesis of 2D tellurene crystals. In a typical procedure, analytical-grade $\\mathrm{Na}_{2}\\mathrm{TeO}_{3}$ $\\left(0.00045\\mathrm{mol}\\right)$ and an amount of PVP were placed into double-distilled water $(33\\mathrm{ml})$ at room temperature under magnetic stirring to form a homogeneous solution. The resulting solution was poured into a Teflon-lined stainless-steel autoclave, which was then filled with an aqueous ammonia solution $25\\%$ , wt/wt%) and hydrazine hydrate $(80\\%,\\mathrm{wt}/\\mathrm{wt}\\%)$ ). The autoclave was sealed and maintained at the reaction temperature for a designed time. The autoclave was then cooled to room temperature naturally. The resulting solid silver-grey products were precipitated by centrifugation at $_{5,000\\mathrm{r.p.m}}$ . for $5\\mathrm{{min}}$ and washed three times with distilled water (to remove any ions remaining in the final product). \n\nLB transfer of tellurene. The hydrophilic 2D Te nanoflake monolayers can be transferred to various substrates by the LB technique. The washed nanoflakes were suspended in a mixture solvent comprising $N,N$ -dimethylformamide (DMF) and $\\mathrm{CHCl}_{3}$ (for example, in the ratio 1.3:1). The mixture solvent was then dropped into the deionized water. Too much DMF will result in the 2D Te sinking in the water. It is difficult to mix the DMF, $\\mathrm{CHCl}_{3}$ and 2D Te when there is too much $\\mathrm{CHCl}_{3}$ . After evaporation of the solvent, a monolayer assembly of 2D Te flakes was observed at the air/water interface; this monolayer assembly of 2D Te could then be transferred onto a substrate. \n\nFirst-principles calculations. Density functional theory calculations were performed using the Vienna Ab-initio Simulation Package $(\\mathrm{VASP})^{57}$ with projector augmented-wave (PAW) pseudopotentials58. We used $500\\mathrm{eV}$ for the plane-wave cutoff, 5x5x1 Monkhorst–Pack sampling, and fully relaxed the systems until the final force on each atom was less than $0.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . The Perdew–Burke–Ernzerhof exchange-correlation functional was used for relaxation of the system, and the Heyd–Scuseria–Ernzerhof functional was used to calculate the bandgaps (Supplementary Fig. 1) and band-edge levels (Supplementary Fig. 10). We found a significant structural reconstruction for monolayer Te, in agreement with reported results21, but for bilayer and thicker Te the structure was similar to that of bulk Te. Our calculations show lattice parameters of $4.5\\mathring\\mathrm{A}$ and $6.0\\mathring\\mathrm{A}$ for multilayers, in agreement with experiments. The adsorption of O on bilayer Te and P was modelled using a $4\\mathbf{x}3$ cell (Supplementary Fig. 12). \n\nStructural characterization. The morphology of the ultrathin tellurene crystals was identified by optical microscopy (Olympus BX-60). The thickness was determined by atomic force microscopy (Keysight 5500). High-resolution STEM/TEM imaging and SAED were performed using a probe-corrected JEMARM 200F (JEOL USA) operated at $200\\mathrm{kV},$ and EDS data were collected by an X-MaxN100TLE detector (Oxford Instruments). In HAADF–STEM mode, the convergence semi-angle of the electron probe was 24 mrad, and the collection angle for the ADF detector was set to 90–370 mrad. \n\nDetermination of tellurene productivity. To quantify the 2D tellurene flake ratio, we measured all products using the same process. Freshly prepared 2D tellurene solution $(1\\mathrm{ml})$ was centrifuged at $5,000\\mathrm{r.p.m}$ . for $5\\mathrm{{min}}$ after adding acetone $(2\\mathrm{ml})$ , and washed twice with alcohol and double-distilled water. The 2D tellurene flakes were dispersed into $3\\mathrm{ml}$ double-distilled water, then $100\\upmu\\mathrm{l}$ dispersed solution was dropped onto a $1\\times1\\mathrm{cm}^{2}\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate. After water evaporation, an optical microscope recorded several images, randomly covering the $5\\times5\\mathrm{mm}^{2}$ area. Finally, we analysed the areas covered by 2D tellurene using ImageJ, a publicdomain, Java-based image-processing program developed at the National Institutes of Health. We defined the productivity as the ratio of the 2D tellurene area with respect to the entire image area. \n\nSolvent-assisted post-growth thinning process. For the thinning process using alkaline growth solution, as-synthesized 2D tellurene solution (1 ml) was mixed with acetone $(3\\mathrm{ml})$ at room temperature. After a specific time (for example, 6 h), thin 2D tellurene was obtained by centrifugation at $5,000\\mathrm{r.p.m}$ . for $5\\mathrm{{min}}$ . Following application of the LB process, the 2D tellurene could be transferred onto a substrate. \n\nFor the thinning process using tellurene solution with controlled $\\mathrm{\\pH}$ values, the suspension of as-synthesized 2D tellurene (1 ml) was centrifuged once with the addition of $3\\mathrm{ml}$ deionized water. The 2D Te was dispersed into a solution of $\\mathrm{1ml}$ $\\mathrm{\\DeltaNaOH}$ and $3\\mathrm{ml}$ acetone. The concentration of $\\mathrm{\\DeltaNaOH}$ was varied to control the pH value of this $\\mathrm{4ml}$ of solution. The solution was kept at room temperature for $2\\mathrm{-}10\\mathrm{h}$ . Finally, the thinned tellurene samples were precipitated by centrifugation. \n\nFET device fabrication and characterization. A high- $\\mathbf{\\nabla}_{\\cdot}k$ dielectric stack consisting of $20\\mathrm{nm}$ hafnium zirconium oxide $(\\mathrm{Hf_{0.5}}\\mathrm{Zr_{0.5}O_{2}})$ and 2 nm $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ was first deposited by atomic layer deposition onto heavily doped $\\mathrm{n}^{++}$ silicon wafer. After transferring the tellurene flakes onto the substrate, source and drain regions were patterned by electron-beam lithography (EBL). We chose $50/50\\mathrm{nm}\\mathrm{Pd/Au}$ for the contact metal because Pd has a relatively high workfunction that benefits p-type transistors by reducing the Schottky contact resistance. Electrical measurements were performed using a Keithley 4200A semiconductor characterization system. \n\nBy inserting numbers into the formula $\\mu_{_{\\mathrm{FE}}}{=}g_{_{\\mathrm{m}}}L/W C_{_{\\mathrm{ox}}}V_{_{\\mathrm{ds}}},$ where $g_{\\mathrm{m}},L$ , $W$ and $C_{\\mathrm{ox}}$ are the transconductance, channel length, channel width and gate oxide capacitance, we can derive the field-effect mobilities for the tellurene transistors. Field-effect mobilities extracted from devices fabricated on tellurene crystals with various thicknesses are displayed in Fig. 4b. Devices for anisotropic transport measurement were first patterned with EBL into two perpendicular rectangles along the two principal in-plane directions of tellurene, and dry-etched into desired shapes with $\\mathrm{BCl}_{3}$ and argon plasma. The remainder of the fabrication process followed the same route as in high- $\\mathbf{\\nabla}\\cdot k$ integrated FET devices53. \n\nRaman spectra. Angle-resolved Raman spectra were measured at room temperature. The crystal symmetry of Te renders one $\\mathbf{A}_{1}$ mode, one $\\mathbf{A}_{2}$ mode (Raman-inactive) and two doublet E modes at the $\\Gamma$ ​point of the Brillouin zone. The Raman signal was excited by a 633 nm He–Ne laser. Incident light entered along the [1010] direction, which is perpendicular to the Te flake surface and polarized into the [0001] direction, which is parallel to spiral atom chains (we denote this configuration as $0^{\\circ}$ ). A linear polarizer was placed in front of the spectrometer to polarize reflected light into the same direction with incident light. The polarized Raman signal can eliminate all other superimposed Raman signals and manifests a clear trace of angle-dependent Raman spectrum evolution. By rotating the Te flake, we observed an angle-resolved Raman peak intensity change (Fig. 3a). We extracted the peak intensities of different modes by fitting with a Lorentz function and plotted them into polar figures (Fig. 3b–f). These angledependent behaviours were then fitted by carrying out matrix multiplication, $\\mathbf{e}_{\\mathrm{i}}\\times\\mathbf{R}\\times\\mathbf{e}_{\\mathrm{r}},$ where $\\mathbf{e_{i}}$ and $\\mathbf{e_{r}}$ are unit vectors of the incident and reflected light direction and R is the Raman tensor of the corresponding Raman modes2. The angle-resolved Raman results confirm that the helical Te atom chain is indeed along the long axis of the Te flake, which matches our previous TEM results. \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. \n\n# Received: 25 October 2017; Accepted: 16 March 2018; Published online: 17 April 2018 \n\n# References \n\n1.\t Castro Neto, A. H., Guinea, F., Peres, N. M. R., Novoselov, K. S. & Geim, A. K. The electronic properties of graphene. Rev. Mod. Phys. 81, 109–162 (2009). \n2.\t Qian, X., Liu, J., Fu, L. & Li, J. Quantum spin Hall effect in two-dimensional transition metal dichalcogenides. Science 346, 1344–1347 (2014). \n3.\t Chhowalla, M. et al. The chemistry of two-dimensional layered transition metal dichalcogenide nanosheets. Nat. Chem. 5, 263–275 (2013). \n4.\t Fiori, G. et al. Electronics based on two-dimensional materials. Nat. Nanotech. 9, 768–779 (2014). \n5.\t Wang, Q. H., Kalantar-Zadeh, K., Kis, A., Coleman, J. N. & Strano, M. S. Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. Nat. Nanotech. 7, 699–712 (2012). \n6.\t Wu, W. et al. Piezoelectricity of single-atomic-layer $\\mathbf{MoS}_{2}$ for energy conversion and piezotronics. Nature 514, 470–474 (2014). \n7.\t Smith, R. J. et al. Large-scale exfoliation of inorganic layered compounds in aqueous surfactant solutions. Adv. Mater. 23, 3944–3948 (2011). \n8.\t Bonaccorso, F., Bartolotta, A., Coleman, J. N. & Backes, C. 2D-crystal-based functional inks. Adv. Mater. 28, 6136–6166 (2016). \n9.\t Hao, Y. et al. The role of surface oxygen in the growth of large single-crystal graphene on copper. Science 342, 720 (2013). \n10.\tNajmaei, S. et al. Vapour phase growth and grain boundary structure of molybdenum disulphide atomic layers. Nat. Mater. 12, 754–759 (2013). \n11.\tTao, L. et al. Silicene field-effect transistors operating at room temperature. Nat. Nanotech. 10, 227–231 (2015). \n12.\tMannix, A. J. et al. Synthesis of borophenes: anisotropic, two-dimensional boron polymorphs. Science 350, 1513–1516 (2015). \n13.\tZhu, F.-F. et al. Epitaxial growth of two-dimensional stanene. Nat. Mater. 14, 1020–1025 (2015). \n14.\tColeman, J. N. et al. Two-dimensional nanosheets produced by liquid exfoliation of layered materials. Science 331, 568–571 (2011). \n15.\tLiu, H. et al. Phosphorene: an unexplored 2D semiconductor with a high hole mobility. ACS Nano 8, 4033–4041 (2014). \n16.\tLi, L. et al. Black phosphorus field-effect transistors. Nat. Nanotech. 9, 372–377 (2014). \n17.\tvon Hippel, A. Structure and conductivity in the VIb group of the periodic system. J. Chem. Phys. 16, 372–380 (1948). \n18.\tDoi, T., Nakao, K. & Kamimura, H. The valence band structure of tellurium. I. The k·p perturbation method. J. Phys. Soc. Jpn 28, 36–43 (1970). \n19.\tCoker, A., Lee, T. & Das, T. P. Investigation of the electronic properties of tellurium energy-band structure. Phys. Rev. B 22, 2968–2975 (1980). \n20.\tPeng, H., Kioussis, N. & Snyder, G. J. Elemental tellurium as a chiral p-type thermoelectric material. Phys. Rev. B 89, 195206 (2014). \n21.\tZhu, Z. et al. Tellurene—a monolayer of tellurium from first-principles prediction. Preprint at https://arxiv.org/abs/1605.03253 (2016). \n22.\tLiu, J.-W., Zhu, J.-H., Zhang, C.-L., Liang, H.-W. & Yu, S.-H. Mesostructured assemblies of ultrathin superlong tellurium nanowires and their photoconductivity. J. Am. Chem. Soc. 132, 8945–8952 (2010). \n23.\tLee, T. I. et al. High-power density piezoelectric energy harvesting using radially strained ultrathin trigonal tellurium nanowire assembly. Adv. Mater. 25, 2920–2925 (2013). \n24.\tMo, M. et al. Controlled hydrothermal synthesis of thin single-crystal tellurium nanobelts and nanotubes. Adv. Mater. 14, 1658–1662 (2002). \n25.\tMayers, B. & Xia, Y. One-dimensional nanostructures of trigonal tellurium with various morphologies can be synthesized using a solution-phase approach. J. Mater. Chem. 12, 1875–1881 (2002). \n26.\t Qian, H.-S., Yu, S.-H., Gong, J.-Y., Luo, L.-B. & Fei, L.-f High-quality luminescent tellurium nanowires of several nanometers in diameter and high aspect ratio synthesized by a poly(vinyl pyrrolidone)-assisted hydrothermal process. Langmuir 22, 3830–3835 (2006). \n27.\tXian, L., Paz, A. P., Bianco, E., Ajayan, P. M. & Rubio, A. Square selenene and tellurene: novel group VI elemental 2D semi-Dirac materials and topological insulators. 2D Mater. 4, 041003 (2017). \n28.\tZasadzinski, J. A., Viswanathan, R., Madsen, L., Garnaes, J. & Schwartz, D. K. Langmuir–Blodgett films. Science 263, 1726–1733 (1994). \n29.\tHu, G. et al. Black phosphorus ink formulation for inkjet printing of optoelectronics and photonics. Nat. Commun. 8, 278 (2017). \n30.\tKelly, A. G. et al. All-printed thin-film transistors from networks of liquid-exfoliated nanosheets. Science 356, 69–73 (2017). \n31.\tCherin, P. & Unger, P. Two-dimensional refinement of the crystal structure of tellurium. Acta Crystallogr. 23, 670–671 (1967). \n32.\tTran, R. et al. Surface energies of elemental crystals. Sci. Data 3, 160080 (2016). \n33.\t Lan, W.-J., Yu, S.-H., Qian, H.-S. & Wan, Y. Dispersibility, stabilization, and chemical stability of ultrathin tellurium nanowires in acetone: morphology change, crystallization, and transformation into $\\mathrm{TeO}_{2}$ in different solvents. Langmuir 23, 3409–3417 (2007). \n34.\tLiu, J.-W., Wang, J.-L., Wang, Z.-H., Huang, W.-R. & Yu, S.-H. Manipulating nanowire assembly for flexible transparent electrodes. Angew. Chem. Int. Ed. 53, 13477–13482 (2014). \n35.\tMartin, R. M., Lucovsky, G. & Helliwell, K. Intermolecular bonding and lattice dynamics of Se and Te. Phys. Rev. B 13, 1383–1395 (1976). \n36.\tDu, Y. et al. One-dimensional van der Waals material tellurium: Raman spectroscopy under strain and magneto-transport. Nano Lett. 17, 3965–3973 (2017). \n37.\tPine, A. & Dresselhaus, G. Raman spectra and lattice dynamics of tellurium. Phys. Rev. B 4, 356–371 (1971). \n38.\tWang, Q. et al. Van der Waals epitaxy and photoresponse of hexagonal tellurium nanoplates on flexible mica sheets. ACS Nano 8, 7497–7505 (2014). \n39.\tRichter, W. Extraordinary phonon Raman scattering and resonance enhancement in tellurium. J. Phys. Chem. Solids 33, 2123–2128 (1972). \n40.\tQiu, J. & Jiang, Q. Film thickness dependence of electro-optic effects in epitaxial $\\mathrm{Ba}_{0.7}\\mathrm{Sr}_{0.3}\\mathrm{TiO}_{3}$ thin films. J. Appl. Phys. 102, 074101 (2007). \n41.\tLing, X. et al. Anisotropic electron–photon and electron–phonon interactions in black phosphorus. Nano Lett. 16, 2260–2267 (2016). \n42.\tWang, X. et al. Highly anisotropic and robust excitons in monolayer black phosphorus. Nat. Nanotech. 10, 517–521 (2015). \n43.\tLee, C. Anomalous lattice vibrations of single- and few-layer $\\mathbf{MoS}_{2}$ . ACS Nano 4, 2695–2700 (2010). \n44.\tFerrari, A. C. et al. Raman spectrum of graphene and graphene layers. Phys. Rev. Lett. 97, 187401 (2006). \n45.\tHuang, X. et al. Epitaxial growth and band structure of Te film on graphene. Nano Lett. 17, 4619–4623 (2017). \n46.\tIsomäki, H. & von Boehm, J. Optical absorption of tellurium. Phys. Scripta 25, 801–803 (1982). \n47.\tDeng, Y. et al. Towards high-performance two-dimensional black phosphorus optoelectronic devices: the role of metal contacts. 2014 IEEE Int. Electron Devices Meet. https://doi.org/10.1109/IEDM.2014.7046987 (IEEE, 2015). \n48.\tLiu, Y., Xiao, H. & Goddard, W. A. Schottky-barrier-free contacts with two-dimensional semiconductors by surface-engineered MXenes. J. Am. Chem. Soc. 138, 15853–15856 (2016). \n49.\tLiu, Y., Stradins, P. & Wei, S.-H. Van der Waals metal–semiconductor junction: weak Fermi level pinning enables effective tuning of Schottky barrier. Sci. Adv. 2, e1600069 (2016). \n50.\t Radisavljevic, B., Radenovic, A., Brivio, J., Giacometti, V. & Kis, A. Single-layer $\\mathbf{MoS}_{2}$ transistors. Nat. Nanotech. 6, 147–150 (2011). \n51.\tJena, D. & Konar, A. Enhancement of carrier mobility in semiconductor nanostructures by dielectric engineering. Phys. Rev. Lett. 98, 136805 (2007). \n52.\tRothkirch, L., Link, R., Sauer, W. & Manglus, F. Anisotropy of the electric conductivity of tellurium single crystals. Phys. Status Solidi (b) 31, \n147–155 (1969). \n53.\tSi, M., Yang, L., Du, Y. & Ye, P. D. Black phosphorus field-effect transistor with record drain current exceeding 1 A/mm. 2017 75th Ann. Device Res. Conf. https://dx.doi.org/10.1109/DRC.2017.7999395 (IEEE, 2017). \n54.\tYang, L. et al. How important is the metal–semiconductor contact for Schottky barrier transistors: a case study on few-layer black phosphorus? ACS Omega 2, 4173–4179 (2017). \n55.\t McClellan, C. J., Yalon, E., Smithe, K. K. H., Suryavanshi, S. V. & Pop, E. Effective n-type doping of monolayer $\\mathbf{MoS}_{2}$ by $\\mathrm{AlO}_{x}$ . 2017 75th Ann. Device Res. Conf. https://dx.doi.org/10.1109/DRC.2017.7999392 (IEEE, 2017). \n56.\tLiu, Y. et al. Pushing the performance limit of sub- $100~\\mathrm{{nm}}$ molybdenum disulfide transistors. Nano Lett. 16, 6337–6342 (2016). \n57.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, \n11169–11186 (1996). \n58.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n\n# Acknowledgements \n\nW.Z.W. acknowledges the College of Engineering and School of Industrial Engineering at Purdue University for startup support. W.Z.W. was partially supported by a grant from the Oak Ridge Associated Universities (ORAU) Junior Faculty Enhancement Award Program. Part of the solution synthesis work was supported by the National Science Foundation (grant no. CMMI-1663214). P.D.Y. was supported by the NSF/AFOSR 2DARE Program, ARO and SRC. Q.W. and M.J.K. were supported by the Center for Low Energy Systems Technology (LEAST) and the South West Academy of Nanoelectronics (SWAN). Y.L. acknowledges support from Resnick Prize Postdoctoral Fellowship at \n\nCaltech, and startup support from UT Austin. Y.L. and W.A.G. were supported as part of the Computational Materials Sciences Program funded by the US Department of Energy (DOE), Office of Science, Basic Energy Sciences (award no. DE-SC00014607). This work used the computational resources of NREL (sponsored by DOE EERE), XSEDE (NSF ACI-1053575), NERSC (DOE DE-AC02-05CH11231) and the Texas Advanced Computing Center (TACC) at UT Austin. The authors thank F. Fan for discussions. \n\n# Author contributions \n\nW.Z.W. and P.D.Y. conceived and supervised the project. W.Z.W., P.D.Y., Y.X.W. and G.Q. designed the experiments. Y.X.W. and R.X.W. synthesized the material. G.Q. and Y.X.W. fabricated the devices. G.Q. and Y.C.D. performed the electrical and optical characterization. S.Y.H. and Y.X.W. performed the Raman measurements under the supervision of X.F.X. and W.Z.W. Q.W. and M.J.K. performed TEM characterization. Y.L. carried out the first-principles calculations under the supervision of W.A.G. Y.X.W. and G.Q. conducted the experiments. W.Z.W., P.D.Y., Y.X.W., G.Q. and R.X.W. analysed the data. W.Z.W. and P.D.Y. wrote the manuscript. Y.X.W., G.Q. and R.X.W. contributed equally to this work. All authors discussed the results and commented on the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41928-018-0058-4. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to P.D.Y. or W.W. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. " + }, + { + "id": "10.1126_sciadv.aar4206", + "DOI": "10.1126/sciadv.aar4206", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.aar4206", + "Relative Dir Path": "mds/10.1126_sciadv.aar4206", + "Article Title": "nullophotonic particle simulation and inverse design using artificial neural networks", + "Authors": "Peurifoy, J; Shen, YC; Jing, L; Yang, Y; Cano-Renteria, F; DeLacy, BG; Joannopoulos, JD; Tegmark, M; Soljacic, M", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "We propose a method to use artificial neural networks to approximate light scattering by multilayer nulloparticles. We find that the network needs to be trained on only a small sampling of the data to approximate the simulation to high precision. Once the neural network is trained, it can simulate such optical processes orders of magnitude faster than conventional simulations. Furthermore, the trained neural network can be used to solve nullophotonic inverse design problems by using back propagation, where the gradient is analytical, not numerical.", + "Times Cited, WoS Core": 681, + "Times Cited, All Databases": 748, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000443175500028", + "Markdown": "# C O M P U T E R S C I E N C E \n\n# Nanophotonic particle simulation and inverse design using artificial neural networks \n\nCopyright $\\circledcirc$ 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\nJohn Peurifoy,1\\* Yichen Shen,1\\* Li Jing,1 Yi Yang,1,2 Fidel Cano-Renteria,3 Brendan G. DeLacy,4 \nJohn D. Joannopoulos,1 Max Tegmark,1 Marin Soljačić1 \n\nWe propose a method to use artificial neural networks to approximate light scattering by multilayer nanoparticles. We find that the network needs to be trained on only a small sampling of the data to approximate the simulation to high precision. Once the neural network is trained, it can simulate such optical processes orders of magnitude faster than conventional simulations. Furthermore, the trained neural network can be used to solve nanophotonic inverse design problems by using back propagation, where the gradient is analytical, not numerical. \n\n# INTRODUCTION \n\nInverse design problems are pervasive in physics (1–4). Quantum scattering theory (1), photonic devices (2), and thin film photovoltaic materials (3) are all problems that require inverse design. A typical inverse design problem requires optimization in high-dimensional space, which usually involves lengthy calculations. For example, in photonics, where the forward calculations are well understood with Maxwell’s equations, solving one instance of an inverse design problem can often be a substantial research project. \n\nThere are many different ways to solve inverse design problems, which can be classified into two main categories: the genetic algorithm (5, 6) (searching the space step by step) and adjoint method (7) (mathematically reversing the equations). For problems with many parameters, solving these with genetic algorithms takes a lot of computation power and time, and this time grows exponentially as the number of parameters increases. On the other hand, the adjoint method is far more efficient than the genetic algorithms; however, setting up the adjoint method often requires a deep knowledge in photonics and can be quite nontrivial, even with such knowledge. \n\nNeural networks (NNs) have previously been used to approximate many physics simulations with high degrees of precision. Recently, Carleo et al. (8) used NNs to solve many-body quantum physics problems, and Faber et al. (9) used NNs to approximate density functional theory. Here, we propose a novel method to further simulate light interaction with nanoscale structures and solve inverse design problems using artificial NNs. In this method, an NN is first trained to approximate a simulation; thus, the NN is able to map the scattering function into a continuous, higher-order space where the derivative can be found analytically, based on our earlier work presented in the study of Peurifoy et al. (10). The “approximated” gradient of the figure of merit with respect to input parameters is then obtained analytically with standard back propagation $(l l)$ . The parameters are then optimized efficiently with the gradient descent method. Finally, we compare our performance with the standard gradient-free optimization method and find that our method can be more effective and orders of magnitude faster than traditional methods. \n\nWhile we focus here on a particular problem of light scattering from nanoparticles, the approach presented here can be fairly easily generalized to many other nanophotonic problems. This approach offers both the generality present in numerical optimization schemes (where only the forward calculation must be found) and the speed of an analytical solution (owing to the use of an analytical gradient). Conceptually, there are a number of reasons why the approach used here is useful for a myriad of branches of physics. After the NN is trained, there are three key uses discussed here. \n\n# Approximate \n\nOnce the NN is trained to approximate a complex physics simulation (such as density functional theory or finite-difference time-domain simulation), it can approximate the same computation in orders of magnitude less time. \n\n# Inverse design \n\nOnce trained, the NN can solve inverse design problems more quickly than its numerical counterpart because the gradient can be found analytically instead of numerically. Furthermore, the series of calculations for inverse design can be computed more quickly due to the faster backward calculation. Finally, the NN can search more easily for a global minimum possibly because the space might be smoothed in the approximation. \n\n# Optimization \n\nSimilarly to inverse design, the network can be asked to optimize for a desired property. This functionality can be implemented simply by changing the cost function used for the design and without retraining the NN. \n\n# RESULTS \n\n# NNs can learn and approximate Maxwell interactions \n\nWe evaluate this method by considering the problem of light scattering from a multilayer (denoting the nanoparticle layer by shell from here on) dielectric spherical nanoparticle (Fig. 1). Our goal is to use an NN to approximate this simulation. For definiteness, we choose a particle that has a lossless silica core $\\begin{array}{r}{(\\epsilon=5.913+\\frac{0.2441}{\\lambda^{2}-0.0803})}\\end{array}$ and lossless silica shells. Specifically, we con- ${\\bf\\Psi}(\\epsilon=2.04\\$ ) and then alternating lossless $\\mathrm{TiO}_{2}$ sider eight shells between 30- and $70\\mathrm{-nm}$ thicknesses per shell. Thus, the smallest particle we consider is $480\\mathrm{nm}$ in diameter, and the largest is $1120~\\mathrm{nm}$ . \n\nThis problem can be solved analytically or numerically with the Maxwell equations, although for multiple shells, the solution becomes involved. The analytical solution is well known (12). We used the simulation to generate 50,000 examples from these parameters with the Monte Carlo sampling. \n\n![](images/48613275eec0dd21867e5c296fbb7819521424da2379cef00efaf9df6c19eccf.jpg) \nFig. 1. The NN architecture has as its inputs the thickness of each shell of the nanoparticle, and as its output the scattering cross section at different wavelengths of the scattering spectrum. Our actual NN has four hidden layers. \n\nNext, we trained the NN using these examples. We used a fully connected network, with four layers and 250 neurons per layer, giving us 239,500 parameters. The input was the thickness of each nanomaterial shell (the materials were fixed), and the output was the spectrum sampled at points between 400 and $800\\mathrm{nm}$ . The training error is graphed in Fig. 2A, and a table of cross-validation responses for various particle configurations is presented in Table 1. For each nanoparticle configuration, a hyperparameter search (that is, changing learning rates and the number of neurons per layer) was performed to minimize the validation error. In our experience, changing the architecture of the model, such as the number of neurons, by a small amount did not affect the mean relative error (MRE) significantly. Additional details about the network architecture, training data, and loss computation are discussed in the Methods section, and all codes used to generate the simulations and results, as well as implement the model discussed here for a general problem, can be accessed at https://github.com/iguanaus/ScatterNet. Once the training was complete, the weights of the NN were fixed and saved into files, which can be easily loaded and used. Next, we began to experiment with applications and uses of this NN. \n\nThe first application was to test the forward computation of the network to see how well it approximates the spectra it was not trained on (for an example, see Fig. 2B). Impressively, the network matches the sharp peaks and high Q features with much accuracy, although the model was only trained with 50,000 examples, which is equivalent to sampling each shell thickness between 30 and $70\\mathrm{nm}$ only four times. \n\nTo study whether the network learned anything about the system and can produce features it was not trained on, we also graphed the closest examples in the training set. The results show that the network is able to match quite well spectra even outside of the training set. Furthermore, the results from Fig. 2B visually demonstrate that the network is not simply interpolating, or averaging together the closest training spectra. This suggests that the NN is not simply fitting to the data, but instead discovering some underlying pattern and structure to the input and output data such that it can solve problems it had not encountered and, to some extent, generalize the physics of the system. \n\nThis method is similar to the well-known surrogate modeling (13), where it creates an approximation to solve the computationally expensive problem, instead of the exact solution. However, the result indicates that NNs can be very powerful in approximating linear optical phenomena (such as nanoparticle scattering phenomena shown here). \n\n# NNs solve nanophotonic inverse design \n\nFor an inverse design, we want to be able to draw any arbitrary spectrum and find the geometry that would most closely produce this spectrum. Results demonstrate that NNs are able to efficiently solve inverse design problems. With the weights fixed, we set the input as a trainable variable and used back propagation to train the inputs of the NN. In simple terms, we run the NN “backward.” To do this, we fix the output to the desired output and let the NN slowly iterate the inputs to provide the desired result. After a few iterations, the NN suggests a geometry to reproduce the spectrum. \n\nWe test this inverse design on the same problem as above—an eightshell nanoparticle made of alternating shells of $\\mathrm{TiO}_{2}$ and silica. We choose an arbitrary spectrum and have the network learn what inputs would generate a similar spectrum. We can see an example optimization in Fig. 3. To ensure that we have a physically realizable spectra, the desired spectrum comes from a random valid nanoparticle configuration. \n\nWe also compare our method to state-of-the-art numerical nonlinear optimization methods. We tested several techniques and found that interior-point methods (14) were most effective for this problem. We then compared these interior-point methods to our results from the NN, shown in Fig. 3. Visually, we can see that the NN is able to find a much closer minimum than the numerical nonlinear optimization method. This result is consistent across many different spectra, as well as for particles with different materials and numbers of shells. \n\nWe found that for a few parameters to design over (for three to five dielectric shells), the numerical solution presented a more accurate inverse design than the NN. However, as more parameters were added (regimes of 5 to 10 dielectric shells), the numerical solution quickly became stuck in local minima and was unable to solve the problem, while the NN still performed well and found quite accurate solutions to inverse design. Thus, for difficult inverse design problems involving many parameters, NNs can often solve inverse design easily. We believe \n\n![](images/bbf3cc13d59b05f9cc84bf4af0615599f20e0cbfc080c6bcdb73aae65f165584.jpg) \nFig. 2. NN results on spectrum approximation. (A) Training loss for the eight-shell case. The loss has sharp declines occasionally, suggesting that the NN is finding a pattern about the data at each point. (B) Comparison of NN approximation to the real spectrum, with the closest training examples shown here. One training example is the most similar particle larger than desired, and the other is the most similar particle smaller than desired. These results were consistent across many different spectra. \n\nTable 1. Network architecture and cross-validation results for various sizes of nanoparticles. The common architecture throughout is a fourlayer densely connected network. The errors are presented as the mean percent off per point on the spectrum (subtracting the output by desired and dividing by the magnitude). The validation set was used to select the best model; the test was never seen until final evaluation. The errors are close, suggesting that not much overfitting is occurring, although the effects become more pronounced for more shells. \n\n
Nanoparticle shellsNeurons per layerMRE (train)MRE (validation)MRE (test)
82501.4%1.5%1.5%
7225 2250.98% 0.97%1.0% 1.0%1.0% 1.0%
6
52000.45%0.46%0.46%
41250.60%0.60%0.60%
31000.32%0.33%0.32%
21000.29%0.30%0.29%
\n\nthat this might be because the optimization landscape might be smoothed in the approximation. \n\nWe further studied how the NN behaves in regions where D has a strong dependence on w, such as the case of J aggregates (15). This material produced complex and sharp spectra, and it is interesting to study how well the NN approximated these particles, particularly for particles that it had not trained on. Results demonstrate that the network was able to behave fine in these situations (see the Supplementary Materials for more details). \n\n# NNs can be used as an optimization tool for broadband and specific-wavelength scattering \n\nFor optimization, we want to be able to give the boundary conditions for a model (for instance, how many shells, how thick of a particle, and what materials it could be) and find the optimal particle to produce $\\upsigma(\\lambda)$ as close as possible to the desired $\\left[\\upsigma_{\\mathrm{desired}}(\\lambda)\\right]$ . Now that we can design an arbitrary spectrum using our tool with little effort, we can further use this as an optimization tool for more difficult problems. Here, we consider two: how to maximize scattering at a single wavelength while minimizing the rest, and how to maximize scattering across a broad spectrum while minimizing scattering outside of it. \n\nTo do this, we fix the weights of the NN and create a cost function that will produce the desired results. We simply compute the average of the $\\upsigma(\\lambda)$ inside of the range of interest and compute the average of the points outside the range and then maximize this ratio. This cost function $J$ is given by \n\n$$\nJ=\\frac{\\overline{{\\upsigma_{\\mathrm{in}}}}}{\\overline{{\\upsigma_{\\mathrm{out}}}}}\n$$ \n\nIdeally, this optimization would be performed using metals and other materials with plasmonic resonances (15) in the desired spectrum range. These materials are well suited for having sharp, narrow peaks and, as such, can generate spectra that are highly efficient at scattering at precisely a single wavelength. Our optimization here uses alternating layers of silver and silica, although we also found that using solely dielectric materials, we were able to force the NN to find a total geometry that still scatters at a single peak, despite the underlying materials being unable to. A figure showing the results of this for a narrow set of wavelengths close to $465\\mathrm{nm}$ can be seen in Fig. 4A. \n\nNext, we consider the case of broadband scattering, where we want a flat spectrum across a wide array of wavelengths. For this case, we allow the optimization to consider metal layers as well (modeled by silver, with the inner core still silica). In this case, we choose the same $J$ as above, maximizing the ratio of values inside to outside. After training the network for a short number of iterations, we achieve a geometry that will broadband scatter across the desired wavelengths. A figure of this can be seen in Fig. 4B. \n\n# Comparison of NNs with some conventional inverse design algorithms \n\nAs mentioned, we tested several techniques and found that interiorpoint methods (14) were most suited for nanoparticle inverse design. \n\n![](images/a1f0dc517b7a195fe7fa636ee2a5fe87da1186012e500733444f7cd945c7ca79.jpg) \nFig. 3. Inverse design for an eight-shell nanoparticle. The legend gives the dimensions of the particle, and the blue is the desired spectrum. The NN is seen to solve he inverse design much more accurately. \n\nTo compare this numerical nonlinear optimization method to our NN, we use the same cost function for both, namely, that of the mean square distance between points on the spectra. For definiteness, we code both the NN and simulation in Matlab. This allows for reasonably fair comparisons of speed and computation resources. \n\nWe train a different NN on each number of particle shells from 2 to 10. The networks’ size increased as we increased the number of shells, and the training can often require substantial time. However, once the networks were trained, the runtime of these was significantly less than the forward computation time of the simulation. We tested this by running 100 spectra and then finding the average time required for the computation. These were run on a 2.9-GHz Intel Core i5 processor, and all were parallelized onto two CPUs. A plot of these results is shown in Fig. 5. Once fitting with lines, it is evident that if the problem becomes complex, then the simulation would struggle to run more than a few shells, while the NN would be able to handle more. Thus, the NN approach has much to offer to physics and inverse design even in just speeding up and approximating simulations. \n\nNext, we looked at the optimization runtime versus the complexity of the problem, once again comparing our method against interiorpoint algorithms. To find the speed of this optimization, we chose a spectrum, set a threshold cost, and timed how long it took for the methods to find a spectrum that is below that cost or converged into a local minimum. On a number of spectra, we found that both methods were often sensitive to initialization points. To investigate these results rigorously, and not be influenced by the choice of initial conditions, we took 50 starting points for each spectrum and tested three spectra for each number of shells. Results demonstrate that inverse design using the NN was able to handle more complex problems than the numerical inverse design (see the Supplementary Materials for more details). \n\n# DISCUSSION \n\nThe results of this method suggest that it can be easily used and implemented, even for complex inverse design problems. The architecture used in the examples above—a fully connected layer—was chosen without much optimization and still performs quite well. Our preliminary testing with other architectures (convolutions, dropouts, and residual networks) appeared to have further promise as well. \n\nPerhaps the two most surprising results were how few examples it takes for the network to approximate the simulation, as well as how complex the approximation can really be. For instance, in the eight-shell case, the NN only saw 50,000 examples over eight independent inputs. This means that, on average, it sampled only four times per shell thickness and yet could reproduce the entire range of 30- to $70\\mathrm{-nm}$ shell thickness continuously. The approximation was even able to handle quite sharp features in the spectrum that it otherwise had not seen. \n\nPromising and effective results have been seen by applying this method to other nanophotonic inverse design problems. Recently, Liu et al. (16) demonstrated that by using a bidirectional NN (17), optimization and inverse design can be performed for one-dimensional shells of dielectric mediums. The approach was to first train the network to approximate the forward simulation and then do a second iteration of training (in the inverse direction) to further improve the accuracy of the results. By using a second iteration of training, Liu et al. (16) was able to overcome degeneracy problems wherein the same spectrum can be generated by particles of different geometrical arrangements. Overall, this and similar work are promising to the idea that experimenting with different architectures, and adding more training data, can allow these NNs to be useful for solving inverse design in many more scenarios. \n\nAnother interesting aspect of this method is to study the smoothness and robustness of these networks. The validation results show the network to be likely smooth—in particular that there is not much difference in the cross-validation errors. On the other hand, the optimization methods and results can be used to investigate the robustness of the networks. In particular, the optimization presented here was done by an ensemble optimization, wherein the network was initialized several times at different starting points, and each time allowed to converge to a single point. In a typical run, several different initialization points were found to converge to similar error amounts (with possibly different parameters), the lowest of which was chosen as global minimum for the inverse design problem. This finding is consistent with other findings in the field of machine learning, where almost all local minima have similar values to the global optimum of the NN (18). These experiments showed that the NN was not entirely accurate—still getting stuck in local minima on some trial—but preliminary testing suggested that this performs more robustly than the numerical counterpart, as depicted above. \n\n![](images/8673ab4862024d78ca9d3f1344d5a737e5aea43bc073f32af6512719959cefa4.jpg) \nFig. 4. Spectra produced by using our approach as an optimization tool. (A) Scattering at a narrow range close to a single wavelength. Here, we force the NN to find a total geometry that scatters around a single peak, using alternating layers of silver and silica. (B) Scattering across a broadband of wavelengths. The legend specifies the thickness of each shell in nanometers, alternating silica and silver shells. The network here was restricted to fewer layers of material (only five shells) but given a broader region of shell sizes than previously (from 10 to $70~\\mathsf{n m}$ ). \n\n![](images/9b2b1159c5f4ddc5bfbadbc9b0b788bb7c0f25a9b4624b7ddda804bd84da22ca.jpg) \nFig. 5. Comparison of forward runtime versus complexity of the nanoparticle. The simulation becomes infeasible to run many times for large particles, while the NN’s time increases much more slowly. Conceptually, this is logical as the NN is using pure matrix multiplication—and the matrices do not get much bigger—while the simulation must approximate higher and higher orders. The scale is log-log. The simulation was fit with a quadratic fit, while the NN was a linear fit. See the Supplementary Materials for more details and inverse design speed comparison. \n\nOne clear concern with the method is that we still have to generate the data for each network, and this takes up time for each inverse design problem. It is true that generating the data takes significant effort, but there are two reasons why this method is still very useful. First, hardware is cheap, and the generation of data can be done easily in parallel across machines. This is not true for inverse design. Inverse design must often be done in a serial approach as each step gets a little closer to the optimal, so the time cannot be reduced significantly by parallel computation. The second reason this method is highly valuable is while the forward propagation is linear in complexity, the optimization is often polynomial. Specifically, by looking at Fig. 5 and the inverse design runtimes (see the Supplementary Materials), we can see that the inverse design speed is growing much faster than the forward runtime. This is important because it means that for complex simulations, the numerical inverse design could take an infeasible amount of time (especially when one needs to solve many inverse design problems for the same physical system), while the NN inverse design may not take long; it will simply have many variables. \n\nThis method could be used in many other fields of computational physics; it would allow us to approximate physics simulations in fractions of the time. Furthermore, owing to the robustness of back propagation, this method allows us to solve many inverse design problems without having to manually calculate the inverse equations. Instead, we simply have to write a simulation for the forward calculation and then train the model on it to easily solve the inverse design. \n\n# METHODS \n\nAnalytically solving scattering via the transfer matrix method We use the transfer matrix method, described in the study of Qiu et al. (19). We consider a multishell nanoparticle. Because of spherical symmetry, we decompose the field into two parts: transverse electric (TE) and transverse magnetic (TM). Both these potentials satisfy the Helmholtz equation, and each scalar potential can be decomposed into a discrete set of spherical modes \n\n$$\n\\Phi_{l m}=R_{l}(r)P_{l}^{|m|}(\\cos{\\theta})e^{i m\\Phi}\n$$ \n\nFor a specific wavelength, because the dielectric constant is constant within each shell, $R_{l}(r)$ is a linear combination of the first and second kinds of spherical Bessel functions within the two respective shells \n\n$$\nR_{l}(r)|_{i}=A_{i}j_{l}(k_{i}r)+B_{i}y_{l}(k_{i}r)\n$$ \n\nWe can solve for these coefficients with the transfer matrix of the interface. Thus, we can calculate the transfer matrix of the whole system by simply telescoping these solutions to individual interfaces \n\n$$\n\\left[\\begin{array}{l}{A_{n+1}}\\\\ {B_{n+1}}\\end{array}\\right]=M_{n+1,n}M_{n,n-1}...M_{3,2}M_{2,1}\\left[\\begin{array}{l}{A_{1}}\\\\ {B_{1}}\\end{array}\\right]=M\\left[\\begin{array}{l}{A_{1}}\\\\ {B_{1}}\\end{array}\\right]\n$$ \n\nFor the first shell, the contribution from the second kind of Bessel function must be zero because the second kind of Bessel function is singular at the origin. Thus, $A_{1}=1$ and $B_{1}=0$ . The coefficients of the surrounding shell are given by the transfer matrix element $A_{n+1}=M_{11}$ and $B_{n+1}=M_{21}$ . To find the coefficients of this surrounding medium, we write the radical function as a linear combination of spherical Hankel functions \n\n$$\nR_{l}(r)\\vert_{n+1}=C_{n+1}h_{l}^{1}(k_{n+1}r)+D_{n+1}h_{l}^{2}(k_{n+1}r)\n$$ \n\nHere, $h_{l}^{1}(k_{n+1}r)$ and $h_{l}^{2}(k_{n+1}r)$ are the outgoing and incoming waves, respectively, using the convention that fields vary in time as $e^{-i\\omega t}$ . The reflection coefficients $r_{l}$ are given by \n\n$$\nr_{l}=\\frac{C_{n+1}}{D_{n+1}}=\\frac{M_{11}-i M_{21}}{M_{11}+i M_{21}}\n$$ \n\nBy solving for the reflection coefficients $r_{l},$ we can find the scattered power in each channel \n\n$$\nP_{l,m=\\pm1}^{\\mathrm{sca}}=\\frac{\\uplambda^{2}}{16\\pi}(2l+1)I_{0}\\lvert1-r_{l}\\rvert^{2}\n$$ \n\nLast, by summing overall channel contributions of the TE and TM polarization (both of the $\\upsigma$ terms), we find the total scattering cross section \n\n$$\n\\upsigma_{\\mathrm{sca}}=\\sum_{\\upsigma}\\sum_{l=1}^{\\infty}\\frac{\\uplambda^{2}}{8\\pi}(2l+1)|1-r_{\\upsigma,l}|^{2}\n$$ \n\nFor practical reasons, the $l$ summation did not go to $\\infty$ . Instead, before the training data were generated, the order of $l$ was slowly increased until the spectrum had converged, and adding more orders would not change the result. For a typical calculation here, the order ranged from $4l$ terms to $18~l$ terms. \n\n# Inverse design with NNs \n\nThe arrangement of the network was a fully connected dense feedforward network. This smallest network we used had four layers, with 100 neurons per layer, which gave the network around 50,300 parameters. The network size was increased as the number of layers increased, with the maximum size being four layers with 300 neurons each for the particle with 10 alternating shells. The input to this network was the normalized (subtracting the mean and dividing by the SD) thickness of each shell of the particle (with the materials fixed), and the output was an unnormalized spectrum sampled at 200 points between 400 and $800\\ \\mathrm{nm}.$ . As a common practice, we found that normalizing the inputs helped training, but equivalent results were found with unnormalized inputs—just taking longer to converge. We intentionally did not normalize the output to not give any outside knowledge of what the range of outputs should be. \n\nBetween each layer was an activation function of a rectified linear unit (20). There was also one last matrix multiplication after the final layer of the network to map the output to the 200 dimensional desired output. This transformation had no nonlinearity. To initialize the weights, we used a simple normal distribution around 0 with an SD of 0.1 for all weights and biases. \n\nWe trained the network using a batch size of 100 and a root mean square prop optimizer (21). We split the data into three categories: train, validation, and test (80, 10, and 10, respectively). The train loss was used to generate the gradients, while we stopped training when the validation loss stopped improving. Several different architectures and models (for example, neuron counts) were tested, and the model with the lowest validation loss was chosen. The test loss was used as a final marker that was never trained to ensure cross-validation accuracy. Note that all figures in the paper are from the validation set, so the model was never trained on these particular examples, but we did optimize the model to ensure suitable performance. Most trials took around 1000 to 2000 epochs of 50,000 data points to train, using a learning rate of 0.0006 and decay of 0.99. These parameters were not heavily optimized, and more efficient schemes can certainly be found. \n\nThere were two cost functions used for training. One was used in actual training and back propagation, and the other was used for illustrative purposes in this paper. The first cost function that we used is the mean square error between each point on the spectrum and the 200 dimensional output of the NN. This cost function was consistent between the training and inverse design; for the training data set, each input had a unique and different output, but for the inverse design, we fixed what we wanted the output to be and modified the input. \n\nThe other cost function used for illustrative purposes, and presented in Table. 1, was the mean percent off per point on the spectrum. This meant that we found the error between the output of the NN and the desired spectrum, then normalized by the value of the desired spectrum, and found the mean over the whole spectrum. The idea of this function is to offer a more physically meaningful interpretation of how the network is performing—in giving how much each “average point on the spectrum is off by.” All codes can be found at https://github.com/ iguanaus/ScatterNet. \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/4/6/eaar4206/DC1 \nsection S1. Details for the comparison of NNs with inverse design algorithms \nsection S2. J aggregates \nfig. S1. Comparison of inverse design runtime versus complexity of the nanoparticle. fig. S2. Comparison of NN approximation to the real spectrum for a particle made with a J-aggregate material. \nfig. S3. Optimization of scattering at a particular wavelength using the J-aggregate material. \n\n# REFERENCES AND NOTES \n\n1. B. Apagyi, G. Endredi, P. Levay, Inverse and Algebraic Quantum Scattering Theory (Springer-Verlag, 1996). \n2. A. Y. Piggott, J. Lu, K. G. Lagoudakis, J. Petykiewicz, T. M. Babinec, J. Vučković, Inverse design and demonstration of a compact and broadband on-chip wavelength demultiplexer. Nat. Photonics 9, 374–377 (2015). \n3. L. Yu, R. S. Kokenyesi, D. A. Keszler, A. Zunger, Inverse design of high absorption thin-film photovoltaic materials. Adv. Energy Mater. 3, 43–48 (2013). \n4. E. Martín, M. Meis, C. Mourenza, D. Rivas, F. Varas, Fast solution of direct and inverse design problems concerning furnace operation conditions in steel industry. Appl. Therm. Eng. 47, 41–53 (2012). \n5. R. L. Johnston, Evolving better nanoparticles: Genetic algorithms for optimising cluster geometries. Dalton Trans. 0, 4193–4207 (2003). \n6. N. S. Froemming, G. Henkelman, Optimizing core-shell nanoparticle catalysts with a genetic algorithm. J. Chem. Phys. 131, 234103 (2009). \n7. M. B. Giles, N. A. Pierce, An introduction to the adjoint approach to design. Flow, Turbul. Combust. 65, 393–415 (2000). \n8. G. Carleo, M. Troyer, Solving the quantum many-body problem with artificial neural networks. Science 355, 602–606 (2017). \n9. F. A. Faber, L. Hutchison, B. Huang, J. Gilmer, S. S. Schoenholz, G. E. Dahl, O. Vinyals, S. Kearnes, P. F. Riley, O. A. von Lilienfeld, Machine learning prediction errors better than DFT accuracy. arXiv:1702.05532 (2017). \n10. J. E. Peurifoy, Y. Shen, L. Jing, F. Cano-Renteria, Y. Yang, J. D. Joannopoulos, M. Tegmark, M. Soljacic, Nanophotonic inverse design using artificial neural network, in Frontiers in Optics 2017 (Optical Society of America, 2017), pp. FTh4A.4. \n11. D. E. Rumelhart, G. E. Hinton, R. J. Williams, Learning representations by back-propagating errors. Nature 323, 533–536 (1986). \n12. C. F. Bohren, D. R. Huffman, Absorption and Scattering of Light by Small Particles (Wiley, 1998). \n13. Y. S. Ong, P. B. Nair, A. J. Keane, Evolutionary optimization of computationally expensive problems via surrogate modeling. AIAA J. 41, 687–696 (2003). \n14. A. S. Nemirovski, M. J. Todd, Interior-point methods for optimization. Act. Num. \n17, 191–234 (2008). \n15. B. G. DeLacy, O. D. Miller, C. W. Hsu, Z. Zander, S. Lacey, R. Yagloski, A. W. Fountain, E. Valdes, E. Anquillare, M. Soljačić, S. G. Johnson, J. D. Joannopoulos, Coherent plasmon-exciton coupling in silver platelet-J-aggregate nanocomposites. Nano Lett. \n15, 2588–2593 (2015). \n16. D. Liu, Y. Tan, E. Khoram, Z. Yu, Training deep neural networks for the inverse design of nanophotonic structures. arXiv: 1710.04724 (2018). \n17. K. Hornik, M. Stinchcombe, H. White, Multilayer feedforward networks are universal approximators. Neural Netw. 2, 359–366 (1989). \n18. A. Choromanska, M. Henaff, M. Mathieu, G. B. Arous, Y. LeCun, The Loss Surfaces of Multilayer Networks, in Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS), San Diego, CA, USA, 9 to 12 May 2015. \n19. W. Qiu, B. G. DeLacy, S. G. Johnson, J. D. Joannopoulos, M. Soljačić, Optimization of broadband optical response of multilayer nanospheres. Opt. Express 20, 18494–18504 (2012). \n20. V. Nair, G. E. Hinton, Rectified linear units improve restricted boltzmann machines, in Proceedings of the 27th International Conference on International Conference on Machine Learning (ICML’10), Haifa, Israel, 21 to 24 June 2010. \n21. S. Ruder, An overview of gradient descent optimization algorithms, arXiv:1609.04747 (2016). \n\nAcknowledgments: We thank S. Kim for code review and suggestions to improve the code base, and we furthermore thank S. Peurifoy for reviewing and revising this work. Funding: This material is based on work supported in part by the NSF under grant no. CCF-1640012 and in part by the Semiconductor Research Corporation under grant no. 2016-EP-2693-B. This work is also supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office through the Institute for Soldier Nanotechnologies, under contract numbers W911NF-18-2-0048 and W911NF-13-D-0001, and in part by the MRSEC (Materials Research Science and Engineering Center) Program of the NSF under award number DMR-1419807. Author contributions: M.S., J.D.J., Y.S., and L.J. conceived the method of using NNs to solve photonics problems. Y.Y. suggested studying the scattering spectra design of nanoparticles. J.P. performed the network modeling and data analysis. F.C.-R. and J.P. analyzed different architectures and particle sizes. Y.Y. developed the mathematical models and theoretical background for the nanoparticle solutions. M.T. and B.G.D. gave technical support and conceptual assistance with directions on how the research should proceed. J.P. prepared the manuscript. M.S. and Y.S. supervised the project. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 9 November 2017 \nAccepted 23 April 2018 \nPublished 1 June 2018 \n10.1126/sciadv.aar4206 \n\nCitation: J. Peurifoy, Y. Shen, L. Jing, Y. Yang, F. Cano-Renteria, B. G. DeLacy, J. D. Joannopoulos, M. Tegmark, M. Soljačić, Nanophotonic particle simulation and inverse design using artificial neural networks. Sci. Adv. 4, eaar4206 (2018). \n\n# ScienceAdvances \n\n# Nanophotonic particle simulation and inverse design using artificial neural networks \n\nJohn Peurifoy, Yichen Shen, Li Jing, Yi Yang, Fidel Cano-Renteria, Brendan G. DeLacy, John D. Joannopoulos, Max Tegmark and Marin Soljacic \n\nSci Adv 4 (6), eaar4206. DOI: 10.1126/sciadv.aar4206 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 13 articles, 1 of which you can access for free http://advances.sciencemag.org/content/4/6/eaar4206#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1002_anie.201803262", + "DOI": "10.1002/anie.201803262", + "DOI Link": "http://dx.doi.org/10.1002/anie.201803262", + "Relative Dir Path": "mds/10.1002_anie.201803262", + "Article Title": "From Metal-Organic Frameworks to Single-Atom Fe Implanted N-doped Porous Carbons: Efficient Oxygen Reduction in Both Alkaline and Acidic Media", + "Authors": "Jiao, L; Wan, G; Zhang, R; Zhou, H; Yu, SH; Jiang, HL", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "It remains highly desired but a great challenge to achieve atomically dispersed metals in high loadings for efficient catalysis. Now porphyrinic metal-organic frameworks (MOFs) have been synthesized based on a novel mixed-ligand strategy to afford high-content (1.76wt%) single-atom (SA) iron-implanted N-doped porous carbon (Fe-SA-N-C) via pyrolysis. Thanks to the single-atom Fe sites, hierarchical pores, oriented mesochannels and high conductivity, the optimized Fe-SA-N-C exhibits excellent oxygen reduction activity and stability, surpassing almost all non-noble-metal catalysts and state-of-the-art Pt/C, in both alkaline and more challenging acidic media. More far-reaching, this MOF-based mixed-ligand strategy opens a novel avenue to the precise fabrication of efficient single-atom catalysts.", + "Times Cited, WoS Core": 734, + "Times Cited, All Databases": 762, + "Publication Year": 2018, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000437668700027", + "Markdown": "# From Metal–Organic Frameworks to Single-Atom Fe Implanted Ndoped Porous Carbons: Efficient Oxygen Reduction in Both Alkaline and Acidic Media \n\nLong Jiao+, Gang Wan+, Rui Zhang, Hua Zhou, Shu-Hong Yu, and Hai-Long Jiang\\* \n\nAbstract: It remains highly desired but a great challenge to achieve atomically dispersed metals in high loadings for efficient catalysis. Now porphyrinic metal–organic frameworks (MOFs) have been synthesized based on a novel mixed-ligand strategy to afford high-content $({\\cal I}.76w{}\\nu t\\%)$ single-atom (SA) iron-implanted N-doped porous carbon $(F e_{S A}–N–C)$ via pyrolysis. Thanks to the single-atom $F e$ sites, hierarchical pores, oriented mesochannels and high conductivity, the optimized $F e_{S A}–N–C$ exhibits excellent oxygen reduction activity and stability, surpassing almost all non-noble-metal catalysts and state-of-the-art Pt/C, in both alkaline and more challenging acidic media. More far-reaching, this MOF-based mixedligand strategy opens a novel avenue to the precise fabrication of efficient single-atom catalysts. \n\nSingle-atom catalysts (SACs), a new research frontier in heterogeneous catalysis, have been intensively investigated in diverse reactions, including electrocatalysis, photocatalysis, and organic catalysis.[1–4] Given that only the coordinatively unsaturated metal atoms on the surface of solid catalysts contribute to the catalytic process, SACs would realize the utmost utilization of metal sites and thus greatly benefit the catalytic efficiency.[2] Furthermore, SACs are able to overcome the complicated multiple components in traditional supported metal catalysts and are regarded as ideal model catalysts to identify active sites and understand reaction process at a molecular level.[2,3] Though great progress has been achieved, the rational fabrication of SACs with high metal loadings $(>1\\mathrm{\\wt\\%}$ ) remains a grand challenge.[4] Along with the introduction of more active metals, the optimized pore structure, large surface area, and excellent conductivity in SACs, which would facilitate mass/electron transfer, are also desirable to improve the activity.[5] \n\nTo meet these challenges, metal–organic frameworks (MOFs),[6] a class of crystalline porous materials constructed by metal ions/clusters and versatile organic linkers, are promising candidates. MOFs have been demonstrated to be great precursors/templates to produce porous carbon-based materials via pyrolysis.[7,8] More importantly, their periodic structures give rise to spatial separation of building units and thus inhibit potential agglomeration of metal sites during pyrolysis, enabling MOFs ideal precursors to create SACs. Currently, the reports on MOF-pyrolyzed materials are mostly focused on the regulation of their pore features and compositions.[7d–g,8] The precise fabrication of active sites at the molecular level based on MOF precursors has been rarely reported. Very recently, zeolitic imidazolate frameworks (ZIFs) were reported as precursors to produce SACs based on structural tailorability, high nitrogen content, and the pore confinement effect.[4b,9] Unfortunately, the microporous feature of ZIFs and their derivatives hamper mass transfer and the accessibility of the active site.[9b] Therefore, it is imperative to develop SACs (providing efficient active sites) with hierarchical pores (benefitting mass transfer and active site accessibility) via the rational design of MOFs for improved catalytic performance. \n\nWith the above in mind, a porphyrinic MOF, PCN-222 (also called MOF-545 or MMPF-6),[10] featuring 1D mesochannels with a diameter of $3.2\\mathrm{nm}$ (Supporting Information, Scheme S1), was chosen as a representative precursor. The ratio modulation between Fe-TCPP ( $\\mathbf{\\mathrm{TCPP}=}$ tetrakis (4- carboxyphenyl)porphyrin) and $\\mathrm{H}_{2}$ -TCPP mixed ligands affords a series of isostructural MOFs, denoted as $\\mathrm{Fe}_{x}$ -PCN222 ( $(x\\%$ : molar percentage of Fe-TCPP in both ligands) (Supporting Information, Scheme S2). The assembly of FeTCPP into 3D networks of $\\mathrm{Fe}_{x}{\\mathrm{-PCN-}}222$ effectively inhibits the molecular stacking, and the mixed-ligand strategy further expands the distance of adjacent Fe-TCPP ligands. Upon pyrolysis, the optimized $\\mathrm{Fe}_{20}–\\mathrm{PCN}–222$ can be converted into single-atom (SA) Fe sites implanted porous N-doped carbon, denoted as $\\mathrm{Fe}_{\\mathrm{sA}^{-}}\\mathrm{N}.C$ , with the unique mesopore character (Scheme 1). By integrating single Fe atoms (highly active sites) and hierarchically porous structure with oriented mesopores (facilitating active site access and mass transfer), the optimized $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}$ exhibits superb oxygen reduction activity and ultrahigh stability, surpassing almost all reported non-noble-metal catalysts and the state-of-the-art $\\mathbf{Pt/C}$ , under both alkaline and acidic conditions. \n\n![](images/13da1b408c0ebd95832b4c5afa320461c64810cf1ba472851ba030ace61742b0.jpg) \nScheme 1. Illustration of the rational fabrication of single Fe atomsinvolved $F e_{S A}\\cdot N\\cdot C$ catalyst via a mixed-ligand strategy. \n\nA series of $\\mathrm{Fe}_{x}{\\mathrm{-PCN-}}222$ , including $\\mathrm{Fe_{0}}{\\mathrm{-}}\\mathrm{PCN}{\\mathrm{-}}222$ , $\\mathrm{Fe}_{20}.$ - PCN-222, and $\\mathrm{Fe}_{40}–\\mathrm{PCN}–222$ , have been prepared and all present similarly high surface areas with uniform pore size distribution (Supporting Information, Figures S1, S2). Taking $\\mathrm{Fe}_{20}–\\mathrm{PCN}–222$ as a representative, its typical type-IV ${\\bf N}_{2}$ isotherms suggest a Brunauer–Emmett–Teller (BET) surface area as high as $2062{\\mathrm{m}}^{2}{\\mathrm{g}}^{-1}$ and two types of pores, with sizes of $1.2\\mathrm{nm}$ and $3.2\\mathrm{nm}$ , corresponding to the triangular microchannels and hexagonal mesochannels, respectively. SEM and TEM images present a uniform rod-shaped morphology with a diameter of about $200\\mathrm{nm}$ (Figure 1a; Supporting Information, Figure S3a). The highly oriented mesopores with a size of about $3.2\\mathrm{nm}$ along the $c$ -axis can be well identified in the TEM image (Figure 1a, inset), in good agreement with the size distribution analysis above (Supporting Information, Figure S2). Upon pyrolysis at $800^{\\circ}\\mathrm{C}$ , an $\\mathrm{Fe}_{\\mathrm{{SA}}^{-}}\\mathrm{N}{\\cdot}\\mathrm{C}/\\mathrm{ZrO}_{2}$ composite with two $\\mathbf{Z}\\mathbf{r}\\mathbf{O}_{2}$ phases has been obtained (Supporting Information, Figure S4). Upon subsequent $\\mathbf{Z}\\mathbf{r}\\mathbf{O}_{2}$ removal, $\\mathrm{Fe}_{20}–\\mathrm{PCN}–222$ can be finally converted into $\\mathrm{Fe}_{\\mathrm{{SA}}}–\\mathbf{N}–\\mathbf{C}$ without any identifiable metallic particles, and the rod shape and highly oriented mesopores in $\\mathrm{Fe}_{20}–\\mathrm{PCN}–222$ are inherited in the resultant $\\mathrm{Fe}_{\\mathrm{{SA}}^{-\\mathrm{{N}-\\mathrm{{C}}}}}$ to a large extent (Figure 1b–e). ${\\bf N}_{2}$ sorption for $\\mathrm{Fe}_{\\mathrm{{SA}}^{-}}\\mathrm{N}.C$ suggests its high BET surface area of $532\\mathrm{m}^{2}\\mathrm{g}^{-1}$ and the evident hysteresis loop $(P/{P_{0}};~0.6–0.8)$ indicates its mesoporous structure (Supporting Information, Figure S5a), which is recognizable in the cross-section SEM and TEM images (Figure $_{1\\mathrm{c-e}}$ ; Supporting Information, Figure S3b). The pore size distribution analysis further manifests its hierarchical pores in $1{-}2\\mathrm{nm}$ and about $9\\mathrm{nm}$ diameters (Supporting Information, Figure S5b). It is generally believed that micropores would increase the density of active sites and mesopores are beneficial to the mass transfer, thus improving catalytic activity.[5d,9b] \n\n![](images/d3e309925db0b2b64f30c7e0ec6109c2e96a91104d731cb4ff954a32adcb803e.jpg) \nFigure 1. a) Scanning electron microscopy (SEM) image of $\\mathsf{F e}_{20}{\\mathsf{\\Pi}}^{\\mathsf{P C N}}$ - 222 (inset: transmission electron microscopy (TEM) image showing the mesochannels in $\\mathsf{F e}_{20}{\\mathsf{-P C N-}}222;$ . b) SEM and c) TEM images of $F e_{S A}-N-C$ . d) Cross-section SEM, e) enlarged TEM images of the mesoporous structure, and f) aberration-corrected high-angle annular darkfield scanning transmission electron microscope (HAADF-STEM) images of $F e_{S A}\\cdot N\\cdot C$ . \n\nThe powder X-ray diffraction (PXRD) pattern of $\\mathrm{Fe}_{\\mathrm{SA}^{-}}\\mathrm{N}.$ - C presents two broad diffraction peaks in the ranges of $20{-}30^{\\circ}$ and $40{-}45^{\\circ}$ , corresponding respectively to the (002) and (101) reflections of graphitized carbon, and no peak associated with iron-based species can be detected (Supporting Information, Figure S6). The Raman scattering spectrum for $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ gives low intensity ratio $(I_{\\mathrm{D}}/I_{\\mathrm{G}}=0.95)$ of $\\mathrm{~\\bf~D~}$ band (ca. $1345\\mathrm{cm}^{-1}.$ ) and $\\mathbf{G}$ band (ca. $1590\\mathrm{cm}^{-1}$ ), further indicating its high graphitization degree, which favors electron transfer (Supporting Information, Figure S7). X-ray photoelectron spectroscopy (XPS) results reveal that C, N, O, and Fe elements are included in $\\mathrm{Fe}_{\\mathrm{{SA}}}–\\mathrm{N}–\\mathrm{{C}}$ (Supporting Information, Figure S8a). High-resolution N 1s spectrum can be fitted into five characteristic peaks, pyridinic $\\mathbf{N}$ $(398.5\\mathrm{eV})$ , Fe- $\\mathbf{\\cdotN}_{x}$ $(399.2\\mathrm{eV})$ , pyrrolic N $(400.3\\mathrm{eV})$ , graphitic N $(401.2\\mathrm{eV})$ , and oxidized N $\\mathsf{I}\\left(402.7\\mathrm{eV}\\right)$ , in which the Fe- $\\mathbf{\\cdotN}_{x}$ peak suggests the good inheritance of $\\mathrm{Fe-N}_{x}$ units from Fe-TCPP after pyrolysis (Figure 2a). The high-resolution Fe 2p spectrum with two relatively weak peaks centered at $710.7\\mathrm{eV}$ (Fe $\\mathrm{2p_{3/2,}}$ ) and $723.1\\mathrm{eV}$ $(\\mathrm{Fe}2\\mathsf{p}_{1/2})$ illustrates partially oxidized Fe species in $\\mathrm{Fe}_{\\mathrm{sA}}$ -N-C, further supporting the existence of Fe- $\\mathbf{\\nabla}\\cdot\\mathbf{N}_{x}$ species (Supporting Information, Figure S8b).[8c] The existence of abundant $\\mathbf{N}$ (4.67 wt $\\%$ ) and high loading of Fe (up to $1.76~\\mathrm{wt}\\%$ ), strikingly consistent with XPS results, have been quantified by elemental analysis and inductively coupled plasma atomic emission spectrometry (ICP-AES; Supporting Information, Table S1, S2). Aberration-corrected HAADFSTEM observation unambiguously identifies single Fe atoms from the bright spots in randomly selected areas, but no Fe particles are found (Figure 1 f; Supporting Information, Figure S9). \n\n![](images/f7128585da1433c236430273a5a9f0b312c690ff19e485b3cd6544d7c262dc1d.jpg) \nFigure 2. a) High-resolution XPS spectrum of N 1s for $\\mathsf{F e}_{\\mathsf{S A}}{\\mathsf{-N-C}}.$ b) Fe K-edge X-ray absorption near-edge structure (XANES) and c) Fourier transform-extended X-ray absorption fine structure (FT-EXAFS) spectra of $\\mathsf{F e}_{\\mathsf{S A}}$ -N-C, 5,10,15,20-tetraphenylporphineiron(III) chloride (FeTPPCl), and iron phthalocyanine (FePc), $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ , and Fe foil. d) EXAFS fitting for $F e_{S A}\\cdot N\\cdot C$ (inset: model of $F e_{S A}{\\cdot}N{\\cdot}C$ . Fe red, N blue, C gray spheres). \n\nIn addition to the localized microstructrual information above, X-ray absorption spectroscopy (XAS) was further used to unveil the electronic and structural information of Feinvolved species in $\\mathrm{Fe}_{\\mathrm{sA}}$ -N-C. From the Fe K-edge XANES spectra, the energy absorption threshold of $\\mathrm{Fe}_{\\mathrm{sA}}$ -N-C locates between Fe foil and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ and is closer to that of FeTPPCl and FePc, implying the positively charged $\\mathrm{Fe}^{\\delta+}$ stabilized by N atoms in $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}$ (Figure 2b). Furthermore, the absence of the edge peak at about $7117.1\\mathrm{eV};$ , which is the fingerprint of $D_{4h}$ symmetry, suggests the lower symmetry of $\\mathrm{Fe-N}_{x}$ sites in $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}.$ .[3b] FT-EXAFS spectrum of $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}$ at Fe K-edge presents only a main peak at about $1.44\\mathring{\\mathrm{A}}$ , which is attributed to the Fe-N scattering path, and no Fe-Fe bond at about $2.13\\mathring{\\mathrm{A}}$ can be detected, manifesting that the evolution of single-atom Fe sites in $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ (Figure 2 c). To further verify the coordination structure around Fe centers, EXAFS fitting has been performed (Figure $2\\mathrm{d}$ ; Supporting Information, Figure S10, Table S3). The best fitting result for the first shell shows that each Fe atom is coordinated by about $4\\mathrm{N}$ atoms in average, illustrating that all atomic Fe sites are four-coordinated by nitrogen species (Figure 2 d, inset). It is noteworthy that when the molar percentage of Fe-TCPP increases to $40\\%$ in PCN-222, Fe-Fe peak is identifiable in the resultant catalyst (denoted as $\\mathrm{Fe_{NP}{-}N{-}C)}$ , manifesting that Fe atoms might aggregate to nanoparticles (NPs) upon pyrolysis with a higher percentage of Fe-TCPP, in consistent with high-resolution TEM observation results (Supporting Information, Figure S11). \n\nThe above results confirm that $\\mathrm{Fe}_{20}–\\mathrm{PCN}–222$ might possess an appropriate Fe-TCPP content $(20\\mathrm{mol\\%})$ to prepare single Fe atoms. The fabrication mechanism for single Fe atoms and Fe NPs has been proposed (Supporting Information, Scheme S3). First, the mixed ligands of $\\mathrm{H}_{2}.$ - TCPP and Fe-TCPP (Fe is coordinated by $\\mathbf{N}$ atoms) are employed to construct PCN-222. Its 3D skeleton composed of metal nodes and organic ligands creates the average distance (d) of adjacent Fe-TCPP ligands by simply changing the ratio of the mixed ligands. When the distance reaches to a critical value (for example, in $\\mathrm{Fe}_{20}–\\mathrm{PCN}–222$ , the formation of Fe NPs is effectively inhibited in pyrolysis process. Upon the $\\mathbf{Z}\\mathbf{r}\\mathbf{O}_{2}$ removal, single Fe atoms anchored N-doped carbon can be successfully obtained (Supporting Information, Scheme S3b). Conversely, when more Fe-TCPP is loaded and $\\mathrm{Fe}\\cdots\\mathrm{Fe}$ distance is shortened, Fe aggregation would be inevitable during the MOF pyrolysis (Supporting Information, Scheme S3c). \n\nIn view of the intrinsic activity of Fe- ${\\bf\\cdot N_{4}}$ sites for efficient oxygen reduction reaction (ORR),[3,5e,11] the performance of $\\mathrm{Fe}_{\\mathrm{SA}}$ -N-C was first investigated in $0.1\\mathrm{{M}\\ K O H}$ . The CV curve of $\\mathrm{Fe_{0}{-}N{-}C}$ sample (obtained from $\\mathrm{Fe_{0}}{\\mathrm{-}}\\mathrm{PCN}{\\mathrm{-}}222$ ) without Fe doping displays a much lower oxygen reduction peak than that of $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ and $\\mathrm{Fe_{NP}{\\bf-N-C}}$ , reflecting an indispensable role of Fe-N sites on boosting ORR activity (Supporting Information, Figure S12). Linear sweep voltammetry (LSV) curves indicate the best performance of $\\mathrm{Fe}_{\\mathrm{{SA}}}–\\mathrm{N}–\\mathrm{{C}}$ among all related catalysts, featuring a higher half-wave potential ${\\bf\\nabla}[E_{1/2}=$ 0.891 V) than $\\mathrm{Fe_{0}{-}N{-}C}$ (0.795 V), $\\mathrm{Fe}_{\\mathrm{NP}}$ -N-C (0.889 V), and the commercial $\\mathrm{Pt/C}$ (0.848 V) (Figure 3 a,b). Furthermore, the superb activity of $\\mathrm{Fe}_{\\mathrm{sA}}$ -N-C is supported by the much higher kinetic current density $(J_{\\mathrm{k}})$ at $0.85\\mathrm{V}$ $(23.27\\mathrm{mAcm}^{-2},$ than that of $\\mathrm{Fe_{0}}{\\cdot}\\mathrm{N}{\\cdot}\\mathrm{C}$ $(0.98\\mathrm{mAcm}^{-2},$ , $\\mathrm{Fe_{NP}{\\bf-N-C}}$ $(18.43\\mathrm{mAcm}^{-2},$ ) and $\\mathrm{Pt/C}$ $(5.61\\mathrm{mAcm}^{-2})$ , signifying its much more favorable kinetics (Figure 3 b). The LSV curve of $\\mathrm{Fe}_{\\mathrm{{SA}}}–\\mathrm{N}–\\mathrm{{C}}/\\mathrm{{ZrO}}_{2}$ was also obtained and its inferior performance to $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ illustrates the importance of HF etching (Supporting Information, Figure S13). Furthermore, $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ also shows better activity than mix-Fe-N-C, which is derived from the physical mixture of Fe-TCPP and $\\mathrm{H}_{2}$ -TCPP, further demonstrating the superiority of MOFs as precursors (Supporting Information, Figure S13). All of the above results suggest that $\\mathrm{Fe}_{\\mathrm{sA}^{-1}}\\mathrm{N}{-}\\mathrm{C}$ possesses the optimal activity. \n\n![](images/e58eb4c5e08b1c8c67cbddb64f5fb563ce6512601709cf56c94a8755c2ce79c3.jpg) \nFigure 3. a) LSV curves and b) $E_{\\scriptscriptstyle{1/2}}$ and $J_{\\mathrm{k}}$ at $0.85\\mathrm{V}$ for various catalysts in 0.1 m KOH. c) LSV curves of $F e_{S A}{\\cdot}N{\\cdot}C$ at different rotating rates in $0.7\\ensuremath{\\mathsf{m}}$ KOH (inset: K-L plots and electron transfer number). d) Stability test of $F e_{S A}\\cdot N\\cdot C$ (inset: methanol tolerance test) in $0.1\\ensuremath{\\mathsf{m}}$ KOH. e) LSV curves of various catalysts in $0.1\\mathrm{~w~HClO}_{4}$ . $\\mathsf{f})$ LSV curves of $F e_{S A}\\cdot N\\cdot C$ in 0.1m ${\\mathsf{H C l O}}_{4}$ before and after the addition of $\\mathsf{S C N}^{-}$ . g) SAXS pattern of $F e_{S A}{\\cdot}N{\\cdot}C$ . \n\nTo gain more insight into the electron-transfer mechanism of $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C},$ LSV curves at different rotating rates of rotating disk electrode (RDE) were recorded (Figure 3c). The K-L plots obtained from the LSV curves exhibit excellent linearity, presenting the first-order reaction kinetics for ORR with a potential-independent electron transfer rate (Figure 3c, inset). Based on the K-L equation, the electron transfer number is determined to be about 4.0, manifesting an ideal $4\\mathrm{e}^{-}$ ORR mechanism. Rotating ring disk electrode (RRDE) \n\nmeasurement for $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathbf{N}–\\mathbf{C}$ was further performed to show the very low $(<5.5\\%)$ ) $\\mathbf{H}_{2}\\mathbf{O}_{2}$ yields with an electron transfer number larger than 3.9 (Supporting Information, Figure S14), similar to the results from the K-L plots. Furthermore, the negligible decay of activity after stability tests and the methanol addition experiments for $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}$ demonstrate its excellent durability and strong tolerance against methanolcrossover effect, in stark contrast to the significant decline of $\\mathrm{Pt/C}$ (Figure $3\\mathrm{d}$ ; Supporting Information, Figure S15). The results suggest that $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathbf{N}–\\mathbf{C}$ possesses the best ORR performance among all non-noble metal catalysts ever reported under alkaline condition (Figure $3\\mathrm{a-d}$ ; Supporting Information, Table S4). \n\nThe excellent ORR performance of $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathbf{N}–\\mathbf{C}$ in alkaline media prompted our further exploration under the more challenging acidic condition. Strikingly, superior ORR activity with a $E_{1/2}$ of $0.776\\mathrm{V}$ in $\\mathrm{0.1M\\HClO_{4}}$ can be achieved for $\\mathrm{Fe}_{\\mathrm{SA}^{-}}\\mathrm{N}.C$ , which is much higher than that of $\\mathrm{Fe_{0}{-}N{-}C}$ , $\\mathrm{Fe_{NP}-N}.$ - C, $\\mathrm{Fe}_{\\mathrm{sA}^{-}}\\mathrm{N}{\\cdot}\\mathrm{C}/\\mathrm{ZrO}_{2}$ , mix-Fe-N-C and even comparable to 1 $\\mathrm{5}\\mathrm{mV}$ lower) that of benchmark $\\mathrm{Pt/C}$ (Figure 3e; Supporting Information, Figures S16, S17). The high kinetic current density $(9.60\\mathrm{mAcm}^{-2})$ ) at $0.75\\mathrm{V}$ manifests the favorable kinetics of $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}$ (Supporting Information, Figure S16b). Further RRDE test suggests a $\\mathbf{H}_{2}\\mathbf{O}_{2}$ yield lower than $1.0\\%$ with an ideal $4\\mathrm{e}^{-}$ transfer process, in consistence with the result from K-L plots (Supporting Information, Figure S18). Moreover, $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ exhibits excellent durability with only $6\\mathrm{mV}$ decay after 5000 cycles and $4\\%$ drop after the i-t test, which is much better than for $\\mathrm{Pt/C}$ , which is possibly due to the strong affinity between atomic Fe sites and coordination $\\mathbf{N}$ within carbon (Supporting Information, Figure S19a,c,e). Additionally, $\\mathrm{Fe}_{\\mathrm{{SA}}^{-}}\\mathrm{N}.\\mathrm{C}$ demonstrates a superior tolerance to the crossover effect of methanol compared with $\\mathrm{Pt/C}$ , making it a promising candidate for direct application in methanol fuel cells (Supporting Information, Figure S19b,d,f). Furthermore, a preliminary constant-current test for $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}$ was conducted in real fuel cell device (Supporting Information, Figure S20). It is noteworthy that, although much endeavor has been devoted, a very limited number of catalysts were reported simultaneously possessing comparable performance with $\\mathrm{Pt/C}$ in both alkaline and acidic media, further highlighting the conspicuous advantage of the single Fe atominvolved $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{N}–\\mathrm{C}$ over other reported catalysts (Supporting Information, Table S5). \n\nTo understand the origin of the excellent ORR performance of $\\mathrm{Fe}_{\\mathrm{sA}^{-1}}\\mathrm{N}.\\mathrm{C}$ , more investigations were carried out. The $\\mathbf{SCN}^{-}\\left(0.01\\mathbf{M}\\right)$ , with strong affinity to Fe ion, was employed as a probe to poison $\\mathrm{Fe-N_{4}}$ sites.[9c] As a result, the half-wave potential of $\\mathrm{Fe}_{\\mathrm{{SA}}^{-\\mathrm{{N}-\\mathrm{{C}}}}}$ for ORR in 0.1m $\\mathrm{HClO}_{4}$ decreased significantly by $50\\mathrm{mV}$ (Figure 3 f). The $\\mathsf{S C N^{-}}$ -poisoned electrode was subsequently rinsed with pure water and remeasured in $0.1\\mathrm{{w}\\ \\ K O H}$ . The $E_{1/2}$ of the first LSV curve negatively shifts by $10\\mathrm{mV}$ as compared to the original catalyst. With increasing cycle numbers, the LSV curves gradually overlap with the original one obtained before $\\mathsf{S C N^{-}}$ treatment, which should be ascribed to the desorption of $\\mathsf{S C N^{-}}$ from Fe site in 0.1m KOH (Supporting Information, Figure S21). The activity recovery accompanied by the release of $\\mathsf{S C N^{-}}$ from blocked $\\mathrm{Fe-N_{4}}$ sites clearly reflects that single Fe atoms are responsible for the high ORR activity of $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ . \n\nFurthermore, the hierarchically porous structure in $\\mathrm{Fe}_{\\mathrm{sA}}$ - N-C is generally believed to affect the accessibility of active sites and mass transfer in catalytic process. Small-angle X-ray scattering (SAXS) for $\\mathrm{Fe}_{\\mathrm{SA}}–\\mathrm{C}–\\mathrm{N}$ gives a broad hump between 0.28 to $0.84\\ \\mathrm{nm}^{-1}$ , hinting the ordering of pore structure with size distribution from 7 to $22{\\mathrm{nm}}$ (Figure $3\\mathrm{g}$ ), in good agreement with the above microstructure observation and ${\\bf N}_{2}$ sorption data (Figure 1d,e; Supporting Information, Figure S5). It should be pointed out that although reported MOF-derived carbon materials exhibit high surface areas, their pore structures are usually disordered and non-interconnected after uncontrollable pyrolysis, which is not favorable to mass transfer in catalysis.[7e,8e] Therefore, the development of porous carbon with oriented channels, which remains to be a long-term target yet a great challenge to date, has been achieved for the first time. The hierarchically porous $\\mathrm{Fe}_{\\mathrm{SA}^{-}}\\mathrm{N}.$ C, possessing abundant micropores (accommodating highdensity $\\mathrm{Fe-N_{4}}$ active sites) and open mesoporous channels with particular orientation (facilitating the high-flux mass transfer), would greatly accelerate the ORR process (Supporting Information, Figure S22). This is in sharp contrast to sluggish mass transfer in traditional MOF-derived carbons with non-interconnected pores. Taking jointly the above Fe${\\bf N}_{4}$ active sites and pore structure merits, we may come to the conclusion that single-atom Fe sites accessible by hierarchal pores in $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ mainly contribute to the superb ORR performance. \n\nIn summary, we have developed a novel mixed-ligand strategy in MOF system to fabricate SACs. The ratio optimization of the mixed porphyrin ligands with and without $\\mathrm{Fe}^{\\mathrm{III}}$ centers gives rise to long spatial distance of $\\mathrm{Fe}^{\\mathrm{III}}$ ions in the MOF skeleton, favoring the formation of single Fe atoms upon pyrolysis. Benefiting from periodic and tailorable MOF structures, the spatial distance control of $\\mathrm{Fe}^{\\mathrm{III}}$ in porphyrinic MOFs effectively suppresses the Fe aggregation during pyrolysis, leading to atomic dispersion of Fe with a high loading $(1.76\\mathrm{wt}\\%)$ in porous carbon. Thanks to the singleatom Fe sites (superior activity), hierarchically porous structure (accessible active sites) with oriented mesopores (fast diffusion of $\\mathbf{O}_{2}$ and electrolyte), and high conductivity (fast electron transfer), $\\mathrm{Fe}_{\\mathrm{sA}}–\\mathrm{N}–\\mathrm{C}$ demonstrates excellent ORR performance in both alkaline and acidic media, surpassing any other reported non-noble-metal catalysts and even the Pt/C. In light of the tremendous diversity and tailorability of MOFs, this work opens up an avenue to the rational synthesis of efficient SACs via multiscale control. \n\n# Acknowledgements \n\nThis work is supported by the NSFC (21725101, 21673213 and 21521001), the 973 program (2014CB931803), the Fundamental Research Funds for the Central Universities (WK2060030029), and the Recruitment Program of Global Youth Experts. Use of the Advanced Photon Source is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. \n\nDE-AC02-06CH11357. We are grateful to the reviewers for valuable suggestions, and Dr. Chenxi Xu at Hefei Univ. Technol. for great help on the testing of the fuel cell device. \n\n# Conflict of interest \n\nThe authors declare no conflict of interest. \n\nKeywords: metal–organic frameworks $\\cdot$ oxygen reduction reaction $\\cdot\\cdot$ porous carbon $\\cdot\\cdot$ single-atom catalysts \n\n[1] a) C. Zhu, S. Fu, Q. Shi, D. Du, Y. Lin, Angew. Chem. Int. Ed. 2017, 56, 13944 – 13960; Angew. Chem. 2017, 129, 14132 – 14148; b) H. Zhang, G. Liu, L. Shi, J. Ye, Adv. Energy Mater. 2018, 8, 1701343; c) Z. Zhang, Y. Zhu, H. Asakura, B. Zhang, J. Zhang, M. Zhou, Y. Han, T. Tanaka, A. Wang, T. Zhang, N. Yan, Nat. Commun. 2017, 8, 16100; d) Y. Zheng, Y. Jiao, Y. Zhu, Q. Cai, A. Vasileff, L. H. Li, Y. Han, Y. Chen, S. Z. Qiao, J. Am. Chem. Soc. 2017, 139, 3336 – 3339. \n[2] a) B. Qiao, A. Wang, X. Yang, L. F. Allard, Z. Jiang, Y. Cui, J. Liu, J. Li, T. Zhang, Nat. Chem. 2011, 3, 634 – 641; b) J. Liu, ACS Catal. 2017, 7, 34 – 59; c) L. Fan, P. F. Liu, X. Yan, L. Gu, Z. Z. Yang, H. G. Yang, S. Qiu, X. Yao, Nat. Commun. 2016, 7, 10667. \n[3] a) Y. J. Sa, D.-J. Seo, J. Woo, J. T. Lim, J. Y. Cheon, S. Y. Yang, J. M. Lee, D. Kang, T. J. Shin, H. S. Shin, H. Y. Jeong, C. S. Kim, M. G. Kim, T.-Y. Kim, S. H. Joo, J. Am. Chem. Soc. 2016, 138, 15046 – 15056; b) A. Zitolo, V. Goellner, V. Armel, M.-T. Sougrati, T. Mineva, L. Stievano, E. Fonda, F. Jaouen, Nat. Mater. 2015, 14, 937 – 942. \n[4] a) P. Liu, Y. Zhao, R. Qin, S. Mo, G. Chen, L. Gu, D. M. Chevrier, P. Zhang, Q. Guo, D. Zang, B. Wu, G. Fu, N. Zheng, Science 2016, 352, 797 – 800; b) P. Yin, T. Yao, Y. Wu, L. Zheng, Y. Lin, W. Liu, H. Ju, J. Zhu, X. Hong, Z. Deng, G. Zhou, S. Wei, Y. Li, Angew. Chem. Int. Ed. 2016, 55, 10800 – 10805; Angew. Chem. 2016, 128, 10958 – 10963. \n[5] a) L. Jiao, Y.-X. Zhou, H.-L. Jiang, Chem. Sci. 2016, 7, 1690 – 1695; b) H. Fei, J. Dong, M. J. Arellano-Jim\u0003nez, G. Ye, N. D. Kim, E. L. G. Samuel, Z. Peng, Z. Zhu, F. Qin, J. Bao, M. J. Yacaman, P. M. Ajayan, D. Chen, J. M. Tour, Nat. Commun. 2015, 6, 8668; c) H. W. Liang, X. Zhuang, S. Bruller, X. Feng, K. M\u0004llen, Nat. Commun. 2014, 5, 4973; d) Z. Qian, Z. Hu, Z. Zhang, Z. Li, M. Dou, F. Wang, Catal. Sci. Technol. 2017, 7, 4017 – 4023; e) M. Lef\u0005vre, E. Proietti, F. Jaouen, J.-P. Dodelet, Science 2009, 324, 71 – 74; f) J. Zhang, L. Dai, ACS Catal. 2015, 5, 7244 – 7253. \n[6] a) H.-C. Zhou, J. R. Long, O. M. Yaghi, Chem. Rev. 2012, 112, 673 – 674; b) H.-C. Zhou, S. Kitagawa, Chem. Soc. Rev. 2014, 43, 5415 – 5418; c) T. Islamoglu, S. Goswami, Z. Li, A. J. Howarth, O. K. Farha, J. T. Hupp, Acc. Chem. Res. 2017, 50, 805 – 813; d) B. Li, H.-M. Wen, Y. Cui, W. Zhou, G. Qian, B. Chen, Adv. Mater. 2016, 28, 8819 – 8860; e) L. Jiao, Y. Wang, H.-L. Jiang, Q. Xu, Adv. Mater. 2018, https://doi.org/10.1002/adma.201703663; f) M. Zhao, K. Yuan, Y. Wang, G. Li, J. Guo, L. Gu, W. Hu, H. Zhao, Z. Tang, Nature 2016, 539, 76 – 80. \n[7] a) B. Liu, H. Shioyama, T. Akita, Q. Xu, J. Am. Chem. Soc. 2008, 130, 5390 – 5391; b) S. Ma, G. A. Goenaga, A. V. Call, D.-J. Liu, Chem. Eur. J. 2011, 17, 2063 – 2067; c) B. Y. Xia, Y. Yan, N. Li, H. B. Wu, X. W. Lou, X. Wang, Nat. Energy 2016, 1, 15006; d) Y.- Z. Chen, C. Wang, Z.-Y. Wu, Y. Xiong, Q. Xu, S.-H. Yu, H.-L. Jiang, Adv. Mater. 2015, 27, 5010 – 5016; e) K. Shen, X. Chen, J. Chen, Y. Li, ACS Catal. 2016, 6, 5887 – 5903; f) H. Zhang, S. Hwang, M. Wang, Z. Feng, S. Karakalos, L. Luo, Z. Qiao, X. Xie, C. Wang, D. Su, Y. Shao, G. Wu, J. Am. Chem. Soc. 2017, 139, 14143 – 14149; g) Q. Lin, X. Bu, A. Kong, C. Mao, X. Zhao, F. Bu, P. Feng, J. Am. Chem. Soc. 2015, 137, 2235 – 2238; h) Z. Zhu, Y. Yang, Y. Guan, J. Xue, L. Cui, J. Mater. Chem. A 2016, 4, 15536 – 15545. \n[8] a) Y. V. Kaneti, J. Tang, R. R. Salunkhe, X. Jiang, A. Yu, C.-W. Wu, Y. Yamauchi, Adv. Mater. 2017, 29, 1604898; b) F. Meng, H. Zhong, D. Bao, J. Yan, X. Zhang, J. Am. Chem. Soc. 2016, 138, 10226 – 10231; c) Y. Ye, F. Cai, H. Li, H. Wu, G. Wang, Y. Li, S. Miao, S. Xie, R. Si, J. Wang, X. Bao, Nano Energy 2017, 38, 281 – 289; d) Y. Qian, I. A. Khan, D. Zhao, Small 2017, 13, 1701143; e) W. Xia, R. Zou, L. An, D. Xia, S. Guo, Energy Environ. Sci. 2015, 8, 568 – 576; f) K. J. Lee, J. H. Lee, S. Jeoung, H. R. Moon, Acc. Chem. Res. 2017, 50, 2684 – 2692; g) H. B. Wu, X. W. Lou, Sci. Adv. 2017, 3, eaap9252. \n[9] a) Q. Lai, L. Zheng, Y. Liang, J. He, J. Zhao, J. Chen, ACS Catal. 2017, 7, 1655 – 1663; b) X. Sun, A. I. Olivos-Suarez, D. Osadchii, M. J. V. Romero, F. Kapteijn, J. Gascon, J. Catal. 2018, 357, 20 – 28; c) Y. Chen, S. Ji, Y. Wang, J. Dong, W. Chen, Z. Li, R. Shen, L. Zheng, Z. Zhuang, D. Wang, Y. Li, Angew. Chem. Int. Ed. 2017, 56, 6937 – 6941; Angew. Chem. 2017, 129, 7041 – 7045. \n[10] a) D. Feng, Z.-Y. Gu, J.-R. Li, H.-L. Jiang, Z. Wei, H.-C. Zhou, Angew. Chem. Int. Ed. 2012, 51, 10307 – 10310; Angew. Chem. 2012, 124, 10453 – 10456; b) W. Morris, B. Volosskiy, S. Demir, F. G\u0006ndara, P. L. McGrier, H. Furukawa, D. Cascio, J. F. Stoddart, O. M. Yaghi, Inorg. Chem. 2012, 51, 6443 – 6445; c) Y. Chen, T. Hoang, S. Ma, Inorg. Chem. 2012, 51, 12600 – 12602. \n[11] a) L. Cui, G. Lv, X. He, J. Power Sources 2015, 282, 9 – 18; b) S. Gupta, D. Tryk, I. Bae, W. Aldred, E. Yeager, J. Appl. Electrochem. 1989, 19, 19 – 27; c) C. W. B. Bezerra, L. Zhang, K. Lee, H. Liu, A. L. B. Marques, E. P. Marques, H. Wang, J. Zhang, Electrochim. Acta 2008, 53, 4937 – 4951; d) M. Zhou, H.- L. Wang, S. Guo, Chem. Soc. Rev. 2016, 45, 1273 – 1307; e) J.-C. Li, Z.-Q. Yang, D.-M. Tang, L. Zhang, P.-X. Hou, S.-Y. Zhao, C. Liu, M. Cheng, G.-X. Li, F. Zhang, H.-M. Cheng, NPG Asia Mater. 2018, 10, e461. \n\n# Communications \n\n# Metal–Organic Frameworks \n\nL. Jiao, G. Wan, R. Zhang, H. Zhou, S.-H. Yu, H.-L. Jiang\\* &&&&—&&&& \n\nFrom Metal–Organic Frameworks to Single-Atom Fe Implanted N-doped Porous Carbons: Efficient Oxygen Reduction in Both Alkaline and Acidic Media \n\n![](images/dcaf79f09e01dcc40cdcfe94cd4e9416518e65f6e9dcb45e718f2a56267f96f0.jpg) \n\nIron islands: Based on a mixed-ligand strategy, a porphyrinic MOF was pyrolyzed to afford high-content single-atom iron-implanted N-doped porous carbon $(F e_{S A}-N-C)$ . Thanks to the $\\mathsf{F e}_{\\mathsf{S A}}$ sites, hierarchical pores, oriented mesochannels, and high conductivity, $F e_{S A}\\cdot N\\cdot C$ exhibits excellent oxygen reduction activity and stability, surpassing almost all non-noble-metal catalysts and $\\mathsf{P t/C}$ , in both alkaline and the more challenging acidic media. " + }, + { + "id": "10.1016_j.joule.2019.01.004", + "DOI": "10.1016/j.joule.2019.01.004", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2019.01.004", + "Relative Dir Path": "mds/10.1016_j.joule.2019.01.004", + "Article Title": "Single-Junction Organic Solar Cell with over 15% Efficiency Using Fused-Ring Acceptor with Electron-Deficient Core", + "Authors": "Yuan, J; Zhang, YQ; Zhou, LY; Zhang, GC; Yip, HL; Lau, TK; Lu, XH; Zhu, C; Peng, HJ; Johnson, PA; Leclerc, M; Cao, Y; Ulanski, J; Li, YF; Zou, YP", + "Source Title": "JOULE", + "Abstract": "Recently, non-fullerene n-type organic semiconductors have attracted significant attention as acceptors in organic photovoltaics (OPVs) due to their great potential to realize high-power conversion efficiencies. The rational design of the central fused ring unit of these acceptor molecules is crucial to maximize device performance. Here, we report a new class of non-fullerene acceptor, Y6, that employs a ladder-type electron-deficient-core-based central fused ring (dithienothiophen[3.2-b]-pyrrolobenzothiadiazole) with a benzothiadiazole (BT) core to fine-tune its absorption and electron affinity. OPVs made from Y6 in conventional and inverted architectures each exhibited a high efficiency of 15.7%, measured in two separate labs. Inverted device structures were certified at Enli Tech Laboratory demonstrated an efficiency of 14.9%. We further observed that the Y6-based devices maintain a high efficiency of 13.6% with an active layer thickness of 300 nm. The electron-deficient-core-based fused ring reported in this work opens a new door in the molecular design of high-performance acceptors for OPVs.", + "Times Cited, WoS Core": 4849, + "Times Cited, All Databases": 5037, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000465149000023", + "Markdown": "# Article Single-Junction Organic Solar Cell with over 15% Efficiency Using Fused-Ring Acceptor with Electron-Deficient Core \n\n![](images/f4c715a5531ea999b666f67ac358491f1838dc21bfbeefc036084a714887e116.jpg) \n\nJun Yuan, Yunqiang Zhang, Liuyang Zhou, ..., Jacek Ulanski, Yongfang Li, Yingping Zou yingpingzou@csu.edu.cn \n\n# HIGHLIGHTS \n\nAn electron-deficient-core-based fused ring acceptor with benzothiadiazole unit \n\nConventional and inverted devices each exhibit a high efficiency of $15.7\\%$ \n\nA new class of non-fullerene acceptor, Y6, by employing a ladder-type electrondeficient-core-based central fused ring with a benzothiadiazole core is reported. Organic photovoltaics made from Y6 in conventional and inverted architectures each exhibited a high efficiency of $15.7\\%$ , measured in two separate labs. Inverted device structures certified at Enli Tech Laboratory demonstrated an efficiency of $14.9\\%$ . Y6-based devices maintained the efficiency of $13.6\\%$ with an active layer thickness of $300~\\mathsf{n m}$ . \n\nThe certified efficiency of $14.9\\%$ has been demonstrated \n\nSolar cells with an active layer thickness of $300\\mathsf{n m}$ achieve the efficiency of $13.6\\%$ \n\n# Article Single-Junction Organic Solar Cell with over 15% Efficiency Using Fused-Ring Acceptor with Electron-Deficient Core \n\nJun Yuan,1 Yunqiang Zhang,1 Liuyang Zhou,1,2 Guichuan Zhang,3 Hin-Lap Yip,3 Tsz-Ki Lau,4 Xinhui Lu,4 Can Zhu,1,2 Hongjian Peng,1 Paul A. Johnson,5 Mario Leclerc,5 Yong Cao,3 Jacek Ulanski,6 Yongfang Li,2 and Yingping Zou1,7,\\* \n\n# SUMMARY \n\nRecently, non-fullerene n-type organic semiconductors have attracted significant attention as acceptors in organic photovoltaics (OPVs) due to their great potential to realize high-power conversion efficiencies. The rational design of the central fused ring unit of these acceptor molecules is crucial to maximize device performance. Here, we report a new class of non-fullerene acceptor, Y6, that employs a ladder-type electron-deficient-core-based central fused ring (dithienothiophen[3.2-b]- pyrrolobenzothiadiazole) with a benzothiadiazole (BT) core to fine-tune its absorption and electron affinity. OPVs made from Y6 in conventional and inverted architectures each exhibited a high efficiency of $15.7\\%.$ measured in two separate labs. Inverted device structures were certified at Enli Tech Laboratory demonstrated an efficiency of $14.9\\%$ . We further observed that the Y6-based devices maintain a high efficiency of $13.6\\%$ with an active layer thickness of $300~\\mathsf{n m}$ . The electron-deficient-core-based fused ring reported in this work opens a new door in the molecular design of high-performance acceptors for OPVs. \n\n# INTRODUCTION \n\nIn the last few decades, considerable progress has been made in the development of bulk-heterojunction (BHJ) organic photovoltaics (OPVs) based on a blend of a $p$ -type organic semiconductor as donor and an $\\mathfrak{n}$ -type organic semiconductor (n-OS) as acceptor.1–3 This is due to their low cost, light weight, and capability to be fabricated into flexible and semitransparent devices.4–6 In general, to produce efficient ${\\mathsf{O P V s}},$ one needs donor and acceptor materials with high charge-carrier mobility, complementary absorption bands in the Vis-NIR range, and a small energy offset to minimize voltage losses.7 The blend composition and morphology must also be optimized to maximize charge generation and transport.8,9 Although one can increase the active layer thickness (for example, up to $300\\mathsf{n m}$ ) to improve light absorption, severe charge recombination could then occur that limits the fill factor (FF) of the devices due to increased distance of charge transport pathways.10 In addition, most of the high-performance OPV materials absorb light with wavelength shorter than $800~\\mathsf{n m}$ ,11 which is not optimal for solar light utilization. In the last 2–3 years, rapid development of low-bandgap non-fullerene acceptors (NFAs) has provided effective ways to improve the performance of OPVs due to their tunable energy levels and strong absorption in the near-infrared region (NIR).12–27 New acceptors have led to power conversion efficiencies (PCEs) over $13\\%$ when combined with a careful choice of polymeric donors.28–34 \n\n# Context & Scale \n\nNon-fullerene acceptors based organic photovoltaics (OPVs) have attracted considerable attention in the last decade due to their great potential to realize highpower conversion efficiencies. To achieve higher performance OPVs, the fundamental challenges are in enabling efficient charge separation/ transport and a low voltage loss at the same time. Here, we have designed and synthesized a new class of non-fullerene acceptor, Y6, that employs an electrondeficient-core-based central fused ring with a benzothiadiazole core, to match with commercially available polymer PM6. By this strategy, the Y6-based solar cell delivers a high-power conversion efficiency of $15.7\\%$ with both conventional and inverted architecture. By this research, we provide new insights into employing the electron-deficientcore-based central fused ring when designing new nonfullerene acceptors to realize improved photovoltaic performance in OPVs. \n\n# Joule \n\nAlong these lines, desired NFAs should have highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels that are correctly positioned with respect to the energy levels of the used donor material. In this work, we choose the commercially available polymer PM6 (as illustrated in Figure 1D) as the donor,35 which has a HOMO energy level of $-5.56\\mathrm{~eV}$ and a LUMO energy level of $-3.50\\ \\mathrm{eV}$ , as determined from cyclic voltammetry (CV). In order to maximize the open-circuit voltage $(V_{\\mathrm{oc}})$ and the short-circuit current density $(\\boldsymbol{J}_{\\mathrm{sc}}),$ the HOMO levels of NFAs should be close to that of donor polymer together with adequate LUMO levels to achieve ideal optical bandgap derived from the Shockley-Queisser efficiency limit mode.36 \n\nOur acceptor’s design is based on our recently reported strategy of using a laddertype multi-fused ring with an electron-deficient core as a central unit that showed a narrow bandgap.37 Moreover, electron affinity can be fine-tuned by the introduction of an electron-withdrawing moiety in the middle of the central core to create a charge-deficient region.38 In this regard, one of the most commonly employed electron-poor units is 2, 1, 3-benzothiadiazole (BT).39 Indeed, because of its commercial availability and $\\mathsf{s p}^{2}$ -hybridized nitrogen atoms endowing electron-withdrawing character, BT has been popular in constructing low-bandgap conjugated materials and polymers.40 Moreover, BT-based polymers can potentially offer highly efficient thick-active-layer OPVs due to their good mobility.41 One can therefore consider using BT as a core of the central fused ring unit in high-performance NFAs. \n\nBased on the above considerations, a new BT-core-based fused-unit dithienothiophen[3.2-b]-pyrrolobenzothiadiazole, TPBT, was designed. Then, a new NFA molecule based on the TPBT central unit, Y6 $^{2,2^{\\prime}}$ -((2Z,20Z)-((12,13-bis(2- ethylhexyl)-3,9-diundecyl-12,13-dihydro-[1,2,5]thiadiazolo[3,4-e]thieno[2,\"30’:4’,50] thieno[20,30:4,5]pyrrolo[3,2-g]thieno[20,30:4,5]thieno[3,2-b]indole-2,10-diyl)bis(methanylylidene))bis(5,6-difluoro-3-oxo-2,3-dihydro-1H-indene-2,1-diylidene))dimalononitrile) (Figure 1A), was synthesized for photovoltaic applications. The fused TPBT central unit preserves conjugation along the length of the molecule, which allows tuning of the electron affinity. 2-(5,6-Difluoro-3-oxo-2,3-dihydro-1H-inden-1-ylidene)malononitrile (2FIC) units were used as flanking groups to enhance absorption and promote intermolecular interactions by forming noncovalent F\\$\\$\\$S and F\\$\\$\\$H bonds and, hence, facilitate charge transport.42–44 Moreover, long alkyl side chains were introduced on the terminal of the central unit to increase the solubility of the resulting small-molecule acceptor. This strategy increases the solubility in common organic solvents for NFAs.45 Optimized photovoltaic devices showed a PCE of up to $15.7\\%$ . These remarkable results demonstrate that Y6 is an excellent acceptor for high-efficiency OPVs. \n\n# RESULTS AND DISCUSSION Synthesis and Characterization \n\nAs fully described in the Supplemental Experimental Procedures, Y6 can be easily synthesized in 4 steps (Scheme 1). Compound 3 was prepared through Stille couplings of compounds 1 and 2. The ladder-type fused ring backbone (compound 4) was obtained by the double intramolecular Cadogan reductive cyclization of compound 3 in the presence of triethyl phosphate, followed by the addition of 1-bromo-2-ethylhexane under alkaline conditions. The dialdehyde compound 5 was prepared by Vilsmeier-Haack reaction as an orange-red solid. The target small molecule Y6 was obtained through a Knoevenagel condensation of the compound 5 with 2FIC. Nuclear magnetic resonance (NMR) spectra and the high-resolution mass \n\n![](images/5d3d54980c5e3e7edb033dcffd1005ad7e17f34d673c2c90f7ebea76a1e2464a.jpg) \nFigure 1. Molecular Structures and Photophysical Properties of Y6 and PM6 \n\n(A) Molecular structure of the acceptor Y6. \n(B) Side view of the optimized geometry of Y6 computed with uB97X-D/6-31+G(d,p). \n(C) Top view of the optimized geometry of Y6 with $\\omega\\mathsf{B}97\\mathsf{X}\\mathrm{-}\\mathsf{D}/6\\mathrm{-}31\\mathrm{+}\\mathsf{G}(\\mathsf{d},\\mathsf{p});$ planes are drawn to highlight the coplanar centers. \n(D) Molecular structure of the donor PM6. \n(E) Absorption spectra of thin films of PM6 and Y6. \n(F) Energy diagrams of Y6 and PM6 in OPVs. \n\nspectrum (MALDI-TOF) of the intermediates and Y6 are shown in Figures S1–S12. In order to better understand the 3D structure of Y6, density functional theory (DFT) calculations at the $\\cup B97\\times-\\square/6-31+\\square$ (d,p) level were carried out with Gaussian 16 revision B.01.46,47 To simplify the calculations, the alkyl side chains on the thiophene units were replaced by $-C H_{3}$ groups, but the whole 2-ethylhexyl side chains on the two nitrogen atoms were included. As shown in Figures 1B and 1C (side and top views, respectively), the acceptor consists of two planar units, with a twist in the center due to the alkyl groups attached to the nitrogens. This result in an N-C-C-N dihedral of –17.5 degree with the side chains on the nitrogen atoms orthogonal to the main plane. There is a C2 axis through the core of the molecule, and a degenerate structure exists with the core twisted in the opposite manner. There are three possible arrangements of the N-alkyl side chains, and the most stable has the two largest side chains directed toward the central core (Tables S4–S8). Without the need to synthesize spiro-like structures, the central conjugated core is sterically hindered to prevent over-aggregation with the presence of the alkyl side chains onto the nitrogen atoms while maintaining an intramolecular charge transport channel. Y6 is soluble in some common organic solvents such as chloroform and tetrahydrofuran at room temperature. Thermogravimetric analysis (TGA) (Figure S13) indicates Y6 has good thermal stability with decomposition temperatures at $318^{\\circ}\\mathsf C.$ , which can meet the requirements of device fabrication. Figures 1E and S14 show the normalized absorption spectra of Y6 in chloroform solution and as thin film (corresponding optical data; Table S1). Compared to solution absorption spectrum, an important bathochromic shift of ${\\sim}90\\mathsf{n m}$ in the thin film indicates some aggregation of the molecular backbone and $\\pi-\\pi$ interactions in the solid state. The absorption onset for Y6 is located at $931{\\mathsf{n m}}$ , corresponding to an optical bandgap $(E_{\\mathfrak{g}}^{\\circ\\mathsf{p t}})$ of $1.33\\mathrm{eV}$ with an absorption coefficient of $1.07\\times10^{5}\\mathrm{cm}^{-1}$ (Figure S15). As shown in Figure S16, the absorption maxima of PM6:Y6 blend film exhibits a small blue shift compared to the neat film of Y6. The post-treated blend film gives a small red shift, which might be due to the changed morphology of blend film.48 For the measurements of HOMO and LUMO energy levels of Y6, cyclic voltammetry was performed in anhydrous $C H_{3}C N$ solution with $\\mathsf{A g}/\\mathsf{A g C l}$ as reference electrode and the ferrocene/ferrocenium $(F C/F C^{+})$ (0.436 eV versus $\\mathsf{A g/A g C l}_{\\mathsf{i}}^{\\mathsf{\\prime}}$ ) redox couple as internal reference. The results are collected in Table S1. From the results reported in Figure S17, the HOMO and LUMO energy levels of Y6 were estimated to be at $-5.65\\ \\mathrm{eV}$ and $-4.10\\ \\mathsf{e V}.$ , respectively. As shown in Figure 1F, the small $\\Delta E_{\\mathsf{H O M O}}$ offset $(0.09\\ \\mathrm{eV})$ between the PM6 donor and Y6 acceptor should be able to afford enough driving force for charge separation and maintain a low energy loss.49,50 \n\n![](images/8350aec045557a8b2a6fc7cde8cf206e60917b29df0f5cf4ad8c1b3c283fbeb1.jpg) \nScheme 1. Synthetic Routes for Y6 \n\n# Photovoltaic Properties \n\nThe Y6 molecule was applied as acceptor in BHJ-type organic solar cells with the medium bandgap $(E_{9}^{\\mathrm{\\scriptsize~opt}}=1.81\\mathrm{\\eV})$ conjugated polymer PM6 as $p$ -type donor for complementary absorption with acceptor (Figure 1E), with the conventional device architecture of ITO/PEDOT:PSS/PM6:Y6/PDINO/Al. The fabrication conditions including the donor/acceptor weight ratios, blend film thickness, and thermal annealing in the active layer were carefully optimized. The key device parameters and all detailed photovoltaic data are summarized in Tables 1, S2, and S3. Devices based on the as-cast PM6:Y6 (1:1.2) blend achieved an impressive PCE of $15.3\\%$ with $V_{\\mathrm{{oc}}}$ of $0.86\\mathsf{V},$ $J_{\\mathsf{s c}}$ of $24.3\\mathsf{m A c m}^{-2}$ , and an FF of $73.2\\%$ . On the basis of D:A weight ratio of 1:1.2, by thermal annealing at $110^{\\circ}\\mathsf C$ for $10\\mathrm{\\min}$ , the PCE of the device decreased from $15.3\\%$ to $14.7\\%$ due to the decreased $V_{\\mathrm{{oc}}}$ from $0.86\\mathrm{\\:V}$ to $0.84\\mathrm{~V},$ although the device showed a slightly higher $J_{\\mathsf{s c}}$ . Subsequently, the high boiling point processing additive 1-chloronaphthalene (CN) was used to optimize the morphology of the active layer. The result showed that the additive concentration of 0.5 wt% CN led to a PCE of $15.4\\%$ with a $V_{\\mathrm{{oc}}}$ of $0.86\\mathsf{V}.$ , a $J_{\\mathsf{s c}}$ of $23.86~\\mathsf{m A}~\\mathsf{c m}^{-2}$ , and an FF of $75\\%$ . Figure 2A shows the best current density versus voltage $(J-V)$ curve of the PM6:Y6-based device with the additive and thermal annealing treatment at $110^{\\circ}\\mathsf C$ for $10\\mathrm{\\min}$ . This optimized device demonstrated a record high PCE of $15.7\\%$ with a higher $J_{\\mathsf{s c}}$ of $25.3\\mathsf{m A c m}^{-2}$ and an FF of $74.8\\%$ . When the active layer thickness increased to $250\\mathsf{n m}$ , the Y6-based device still exhibits a high PCE of $14.1\\%$ with a notably even larger $J_{\\mathsf{s c}}$ of $27.1\\mathsf{m A}\\mathsf{c m}^{-2}$ but a slightly lower FF of $62.8\\%$ (Figure 2C). Upon a further increase of the thickness to $300\\mathsf{n m}$ , a relatively higher PCE of $13.6\\%$ was still obtained with a $J_{\\mathsf{s c}}$ of $26.5~{\\mathsf{m A}}~{\\mathsf{c m}}^{-2}$ and an FF of $62.3\\%$ . Figure 2B shows the EQE spectra of the solar cells, and the maximum EQE plateau reached about $70\\%-80\\%$ from 450 to $830~\\mathsf{n m}$ . The integrated $J_{\\mathsf{s c}}$ of the device based on \n\nTable 1. Photovoltaic Performance of the PM6:Y6 (1:1.2, w/w)-Based Devices (the Average Values for 10 Devices in the Brackets), under the Illumination of AM 1.5 G, 100 mW/cm2 \n\n\n
Device TypeThickness (nm)Voc (V) Jsc (mA cm-2)FF (%)PCE (%)
Conventional150a0.8624.373.215.3 (15.2 ± 0.1)
150b0.8325.374.815.7 (15.6 ± 0.1)
200b0.8325.866.914.3 (14.2 ± 0.1)
250b0.8227.162.814.1 (13.9 ± 0.2)
300b0.8226.562.313.6 (13.3 ± 0.3)
Inverted100b0.8225.276.115.7 (15.5 ± 0.2)
100°0.8323.276.814.9
\n\naAs-cast. bUnder $0.5\\%$ chloronaphthalene (CN) with thermal annealing at $110^{\\circ}\\mathsf C$ for $10\\min$ . cThe certified results from Enli Tech Optoelectronic Calibration Lab (an ISO-approved PV Efficiency Verification Laboratory in Taiwan) (aperture area: $3.99\\mathrm{mm}^{2}$ ). \n\nPM6:Y6 from EQE spectra with AM $1.5\\mathsf{G}$ reference spectrum is $24.6\\mathsf{m A c m}^{-2}$ , which agrees quite well with the $J_{\\mathsf{s c}}$ value from the $J-V$ curve within a $4\\%$ mismatch. \n\nThe dependence of $J_{\\mathsf{s c}}$ on light intensity $(P)$ was measured to gain some insight into the photocurrent transport and charge recombination in the blend films.51 If the bimolecular recombination is negligible in the devices, then the value of $a$ in the relation $J_{\\mathsf{s c}}\\propto P^{\\alpha}$ tends to the limit 1. For the solvent and thermal-annealing treated devices, $\\alpha=0.99$ , which is close to 1 and higher than that $(\\alpha=0.96)$ ) of the as-cast device (Figure S18). These results indicate that there is almost no bimolecular recombination in the optimized devices, which agrees with the high $J_{\\mathsf{s c}}$ and FF of the optimized devices. \n\nWe also fabricated inverted devices with the device structure of ITO/ZnO/PM6:Y6/ ${\\mathsf{M o O}}_{3}/{\\mathsf{A g}}$ for better long-term ambient stability. Again, an excellent PCE of $15.7\\%$ with a remarkably high $J_{\\mathsf{s c}}$ of $25.2\\mathsf{m A c m}^{-2}$ and FF of $76.1\\%$ was achieved in the inverted solar cells. The internal quantum efficiency (IQE) of the Y6-based inverted devices $\\left\\langle100\\mathsf{n m}\\right\\rangle$ has been calculated based on reflection and EQE (the integrated $J_{\\mathsf{s c}}$ is $24.7\\ m\\mathsf{A}\\mathsf{c m}^{-2}.$ ) shown in Figure S19B; the IQE spectrum shows a very high value of over $80\\%$ in a range from 450 to $860\\mathsf{n m}$ (Figure S19C). The high IQE curve suggests that most absorbed photons create charge carriers that are collected at the electrodes. To confirm the reliability of the high PCE of the PM6:Y6-based device, we sent the optimized inverted device to Enli Tech Optoelectronic Calibration Laboratory (an ISO-approved PV Efficiency Verification Laboratory in Taiwan) for certification (Figures S20 and S21). They measured a PCE of $14.9\\%$ (with a $V_{\\mathrm{{oc}}}$ of $0.83\\mathrm{V}.$ , a $J_{\\mathsf{s c}}$ of $23.2~\\mathsf{m A}~\\mathsf{c m}^{-2}$ , and an FF of $76.8\\%$ ). The photovoltaic parameters of the inverted devices are summarized in Table 1 and the $J_{-}V$ characteristics are shown in Figure S19A. \n\nTo elucidate the charge carrier mobilities in the OPV devices, we have determined electron and hole mobilities in the PM6:Y6 blends by the space charge limited current (SCLC) method.52 We measured the charge carrier mobilities in neat Y6 film and PM6:Y6 blend film with different layer thicknesses as reported in Figure S22 and Tables S9 and S10. These results show that the charge mobility can increase with enhanced thicknesses, especially the electron mobility. The unbalanced charge transport property facilitates the formation of space-charge transportation, especially in thick-film devices, which limits their performance. Since the charge transport in the blend is also dependent on its morphology and orientation, we will discuss the charge transport in terms of morphology and orientation of blend films as follows. \n\n![](images/232fc0c8e6392782fa242c9490832b045d71070c7701fe20bf5f500f485db33f.jpg) \nFigure 2. Photovoltaic Characteristics of the Y6-Based OPVs with Conventional Architectures (A) J-V curve. (B) EQE curve. (C) Normalized value of all photovoltaic parameters with different active layer thickness. \n\n# Morphology Characterization \n\nGrazing incidence wide-angle X-ray scattering (GIWAXS) was employed to investigate the bulk molecular packing information of neat and blend films. The 2D GIWAXS patterns of neat Y6 films, neat PM6, and blend PM6:Y6 are shown in Figures 3A–3C. The corresponding intensity profiles in the out-of-plane (OOP) and in-plane (IP) directions are presented in Figure 3D. The neat Y6 film (Figure 3A) exhibits a strong $\\pi-\\pi$ stacking peak in the OOP direction at $\\mathsf{q}=1.76\\mathsf{\\mathring{A}}^{-1}$ $\\mathrm{\\Delta}\\langle\\mathrm{d}\\sim3.57\\mathring{\\mathsf{A}}\\rangle$ , indicating a preferential face-on orientation of Y6. Interestingly, there exist two diffraction peaks in the IP direction at $\\mathsf{q}=0.285\\mathring{\\mathsf{A}}^{-1}$ $(\\mathsf{d}\\sim21.9\\mathring{\\mathsf{A}})$ and $0.420\\mathring{\\mathsf{A}}^{-1}$ $(\\mathsf{d}\\sim15.0\\mathring{\\mathsf{A}})$ , suggesting the co-existence of two distinct structure orders. Since one of them could be assigned to the lamellar peak, the other is mostly likely to originate from the backbone ordering due to the end-group $\\pi-\\pi$ stacking, which was recently discovered in ITIC and ITIC-Th and facilitates the intermolecular electron transport.53 The neat PM6 film (Figure 3B) presents a weaker $\\pi-\\pi$ peak in the OOP direction at $\\mathsf{q}=1.68\\mathsf{\\mathring{A}}^{-1}$ $(\\mathsf{d}\\sim3.74\\mathrm{~\\AA})$ and bimodal lamellar peaks in both IP and OOP directions at $\\mathsf{q}~=~0.300~\\mathring{\\mathsf{A}}^{-1}$ $(\\mathsf{d}\\sim20.9\\mathring{\\mathsf{A}})$ . The optimized blend PM6:Y6 film (Figure 3C) displays a strong diffraction peak in the OOP direction at $\\mathsf{q}=1.74\\mathring{\\mathsf{A}}^{-1}$ $(\\mathsf{d}\\sim3.61\\mathring{\\mathsf{A}})$ , associated with the $\\pi-\\pi$ stacking of Y6. In the IP direction, the scattering peak at $\\mathsf{q}=0.295\\mathring{\\mathsf{A}}^{-1}(\\mathsf{d}\\sim21.3\\mathring{\\mathsf{A}})$ could be assigned to the lamellar stacking of either PM6 or Y6. The peak at $\\mathsf{q}=0.420\\mathring{\\mathsf{A}}^{-1}$ $(\\mathsf{d}\\sim15.0\\mathring{\\mathsf{A}})$ , which was observed in the neat Y6, is still present, implying that the backbone ordering of Y6 is maintained in the blend PM6:Y6 film. GISAXS measurements were also carried out. The 2D GISAXS images and the in-plane scattering profiles are presented in Figure S23. $\\mathsf{q}^{-4}$ dependence is used to fit the uplift in the small q $(<0.\\dot{0}06\\mathring{\\mathsf{A}}^{-1})$ regions due to scattering either from the surface roughness of the film or from the tail of a large amorphous regime. A fractal-like network model was adopted to account for the scattering contribution from the acceptor domain. The domain size of the Y6 phase in the optimized PM6:Y6 film was estimated to be $43.9\\:\\mathrm{nm}$ . \n\nThe morphologies were further investigated by atomic force microscopy (AFM) and transmission electron microscopy (TEM). The height images of the surface were observed by AFM for the blend films with different scan sizes (Figures 3E and S24), indicating good miscibility between PM6 and Y6. The root-mean-square $(R_{\\mathrm{q}})$ surface roughness value for the films is $0.93~\\mathsf{n m}$ . The phase separation was further visualized by TEM under the same conditions. As shown in Figures 3F and S25, the suitable nano-fibrillar structures in the blends suggest ideal phase separation between charge transport and recombination. These morphological features will in turn contribute to the remarkably high $J_{\\mathsf{s c}},$ FF, and PCE achieved by the devices. \n\n![](images/31b13f61929d76ca3d035f85859fccbb919dca21de8062d7bc0eb406eef0d988.jpg) \nFigure 3. Film Morphologies \n\n(A and B) GIWAXS images of neat Y6 and PM6. \n(C) GIWAXS image of PM6:Y6 optimized blend films. \n(D) GIWAXS intensity profiles along the in-plane (dotted line) and out-of-plane (solid line) directions. \n(E) AFM images $\\mathrm{5\\upmum\\times5\\upmum})$ of PM6:Y6 optimized blend films. \n(F) TEM image of PM6:Y6 optimized blend films. \n\n# Conclusion \n\nIn summary, we have designed and synthesized a new class of NIR-absorbing NFA (Y6) based on multi-fused ring central unit with electron-deficient benzothiadiazole core. The resulting electron affinity of Y6 combined with a low $E_{\\mathfrak{g}}^{\\mathrm{\\circpt}}$ of $1.33\\mathsf{e V}$ led to a record efficiency of $15.7\\%$ when blended with commercially available polymer PM6 donor for the devices with both conventional and inverted architecture. In addition, a certified PCE of $14.9\\%$ was obtained with an inverted device structure. More importantly, the Y6-based solar cells maintained a PCE of $14.1\\%$ and $13.6\\%$ with a thicker active layer of $250~\\mathsf{n m}$ and $300~\\mathsf{n m}$ , respectively. The high values of $J_{\\mathsf{s c}},$ exceeding $25\\mathsf{m A c m}^{-2}$ , and high FF around $75\\%$ should result from the broad absorption and high charge carrier mobilities, high IQE in the range from 450 to $860~\\mathsf{n m}$ , and nano-segregated structure with preferred orientation. These results indicate that the electron-deficient-core-based fused ring reported in this work opens a new way in the molecular design of high-performance $\\mathfrak{n}$ -OS acceptors for OPVs. \n\n# EXPERIMENTAL PROCEDURES \n\n# Characterization of Materials \n\n$^1\\mathsf{H}$ NMR and $^{13}\\mathsf{C}$ NMR spectra were recorded using a Bruker AV-400 spectrometer in deuterated chloroform solution at $298\\mathsf{K},$ unless specified otherwise. Chemical shifts \n\n# Joule \n\nwere reported as d values (ppm) with tetramethylsilane (TMS) as the internal reference. The molecular mass was confirmed by using an Autoflex III matrix-assisted laser desorption ionization mass spectrometer (MALDI-TOF-MS). Thermogravimetric analysis (TGA) was conducted on a Perkin-Elmer TGA-7 with a heating rate of 20 K/min under nitrogen. \n\n# UV-Vis Absorption Spectra and Cyclic Voltammetry Measurement \n\nUV-Vis absorption spectra were recorded on the SHIMADZU UV-2600 spectrophotometer. For the solid-state measurements, Y6 solutions in chloroform were spincoated on quartz plates. \n\nCyclic voltammetry results were obtained with a computer-controlled CHI 660E electrochemical workstation using polymer or non-fullerene acceptor films on platinum $(1.0\\ c m^{2})$ as the working electrode, a platinum wire as the counter electrode, and $\\mathsf{A g/A g C l}$ (0.1 M) as the reference electrode in an anhydrous argon-saturated solution of $0.1~\\mathsf{M}$ tetrabutylammonium hexafluorophosphate $(B u_{4}N P F_{6})$ in acetonitrile, at a scanning rate of $50~\\mathrm{mV}\\cdot\\mathsf{s}^{-1}$ . Electrochemical onsets were determined at the position where the current started to rise from the baseline. \n\n# Fabrication and Characterization of the OPVs \n\nOPVs were fabricated in the configuration of the traditional sandwich structure with an indium tin oxide (ITO) glass positive electrode and a PDINO/Al negative electrode in ICCAS. The ITO glass was pre-cleaned in an ultrasonic bath of detergent, deionized water, acetone, and isopropanol, and UV-treated in ultraviolet-ozone chamber (Jelight Company) for 15 min. A thin layer of PEDOT:PSS (poly(3,4-ethylene dioxythiophene): poly(styrene sulfonate)) (Baytron PVP Al 4083) was prepared by spin-coating the PEDOT:PSS solution filtered through a $0.45~{\\upmu\\mathrm{m}}$ poly(tetrafluoroethylene) (PTFE) filter at 3,000 rpm for 40 s on the ITO substrate. Subsequently, PEDOT:PSS film was baked at $\\boldsymbol{150^{\\circ}C}$ for $15\\mathrm{min}$ in the air, and the thickness of the PEDOT:PSS layer was about $40\\ensuremath{\\mathrm{~\\textrm~{~~}~}}\\ensuremath{\\mathrm{nm}}$ . The polymer PM6:Y6 $(\\mathsf{D}{:}\\mathsf{A}\\ =\\ \\mathsf{1}{:}1.2$ , $16~\\mathrm{mg}~\\mathrm{mL}^{-1}$ in total) was dissolved in chloroform (CF) with the solvent additive of 1-chloronaphthalene (CN) $(0.5\\%,\\upnu/\\upnu)$ and spin-cast at 3,000 rpm for 30 s onto the PEDOT:PSS layer. The thickness of the photoactive layer is about $150\\mathsf{n m}$ measured by Ambios Technology XP-2 profilometer. A bilayer cathode consisting of PDINO $(\\sim15\\ \\mathsf{n m})$ capped with Al $(\\sim150\\ \\mathsf{n m})$ was thermally evaporated under a shadow mask with a base pressure of ca. $10^{-5}$ Pa. Finally, top electrodes were deposited in a vacuum onto the active layer. The active area of the device was $5~\\mathrm{mm}^{2}$ . \n\nThe inverted devices were fabricated and tested in SCUT. The ITO glass substrates were cleaned sequentially under sonication with acetone, detergent, deionized water, and isopropyl alcohol and then dried at $60^{\\circ}\\mathsf{C}$ in a baking oven overnight, followed by a 4-min oxygen plasma treatment. For inverted devices, a $Z n O$ electron transport layer (a thickness of ${\\sim}30~\\mathsf{n m}.$ ) was prepared by spin-coating at 5,000 rpm for $30\\mathrm{~s~}$ from a $Z n O$ precursor solution (diethyl zinc, $1.5\\mathsf{M}$ solution in toluene purchased from Acros, diluting in tetrahydrofuran) on ITO substrates, followed by thermal annealing at $\\textstyle150^{\\circ}C$ for $30\\mathrm{min}$ . The active layers were deposited as mentioned above; at a vacuum level of $1\\times10^{-7}$ Torr, a thin layer $10\\mathsf{n m})$ of ${\\mathsf{M o O}}_{3}$ was then thermally deposited as the anode interlayer, followed by thermal deposition of $100~\\mathsf{n m}$ Ag as the top electrode through a shadow mask. The active area of all devices was $0.07~\\mathsf{c m}^{2}$ . The $J_{-}V$ curves were measured on a computer-controlled Keithley 2400 source meter under 1 sun, the AM $1.5\\mathsf{G}$ spectra came from a class solar simulator (Enlitech), and the light intensity was $100\\mathrm{\\mwcm}^{-2}$ as calibrated by a China General Certification Center-certified reference monocrystal silicon cell (Enlitech). \n\nBefore the $J_{-}V$ test, a physical mask with an aperture with precise area of $0.04~\\mathsf{c m}^{2}$ was used to define the device area. \n\nDevice characterization was carried out under AM 1.5G irradiation with the intensity of $100\\ m\\mathsf{W\\ c m}^{-2}$ (Oriel 67005, 500 W), calibrated by a standard silicon cell. J-V curves were recorded with a Keithley 236 digital source meter. A xenon lamp with AM 1.5 filter was used as the white light source and the optical power was $100\\ m\\mathsf{W\\ c m}^{-2}$ . The EQE measurements of organic solar cells were performed by Stanford Systems model SR830 DSP lock-in amplifier coupled with WDG3 monochromator and 500 W xenon lamp. A calibrated silicon detector was used to determine the absolute photosensitivity at different wavelengths. All of these fabrications and characterizations were conducted in a glove box. \n\n# The Certificated PCE of the Devices Test Method \n\nThe certification was performed by Enli Tech Optoelectronic Calibration Lab, which is accredited by Taiwan Accreditation Foundation (TAF) to ISO/IEC 17025. TAF is a full member of ILAC MRA (International Laboratory Accreditation Cooperation Mutual Recognition Arrangement) and IAF MLA (International Accreditation Forum Multilateral Recognition Arrangement). The testing of the sample was performed at standard testing conditions (STC) in accordance with IEC 60904-1:2006 Photovoltaic devices – Part 1: Measurement of photovoltaic current-voltage characteristics and test standard operation procedure of maximum power measurement of solar cells under the irradiation with a steady-state class AAA solar simulator according to IEC 60904-9:2007 Photovoltaic devices – part 9: Solar simulator performance requirements. The spectral mismatch is calculated according to IEC 60904-7:2008 Photovoltaic devices – Part 7: Computation of the spectral mismatch correction for measurements of photovoltaic devices. The spectrum of the solar simulator is measured with a spectroradiometer. The spectral responsivity (or quantum efficiency) of the device under test is measured with a grating monochromatic according to IEC 60904-8:2014 Photovoltaic devices – Part 8: Measurement of spectral responsivity of a photovoltaic (PV) device. \n\n# The Details of Testing Procedures \n\nThe device under test (DUT) was an organic polymer solar cell. Each sample had 3 devices on one glass substrate. The device contact structure was of superstrate type. The active area of DUT was covered with an area-calibrated metal shadow mask. Before the measurement of current and voltage, the spectral responsivity (or quantum efficiency) was measured according to IEC60904-8:2014. The traceability to SI units was achieved by using a calibrated photodetector (ISO/IEC 17025, lab calibrated and traceable to NIST). The spectral mismatch correction factor, MMF, was calculated based on IEC 60904-7:2008. The temperature was controlled with the simulator’s mechanical shutter and a TE air-cooler with an RTD temperature sensor to achieve STC. The current and voltage data were taken by Keithley 2400 SMU with ISO/IEC 17025:2005 calibration report (no. K1509300201, traceable to NML). Kelvin Probe 4-wire connection method was adopted to remove all wire resistance in the circuit loop, which may affect the current and fill-factor accuracy of test results. The model of solar simulator is SS-F5-3A. The 1-sun intensity of SS-F5-3A was set by the WPVS-type reference cell with KG5 optical filter, which is calibrated by NREL (NREL calibration no. 1239.02, NIST traceability) and corrected by the MMF calculated before. The spectroradiometer (model: SPR-3011-SP; ISO/IEC 17025, lab calibrated and traceable to NML) was used to measure and monitor the spectrum of solar simulator. \n\n# Joule \n\n# Hole Mobility and Electron Mobility Measurements \n\nThe hole-only or electron-only diodes were fabricated using the following architectures: ITO/PEDOT:PSS/active layer/gold (Au) for holes and ITO/ZnO/active layer/ PDINO/Al for electrons. Mobilities were extracted by fitting the current densityvoltage curves using the Mott-Gurney relationship (space charge limited current). The mobilities were obtained by taking current-voltage curves and fitting the results to a space charge limited form. \n\n# Grazing Incidence Wide-Angle and Small-Angle X-Ray Scattering Measurements \n\nGIWAXS and GISAXS measurements were carried out with a Xeuss 2.0 SAXS/WAXS laboratory beamline using a Cu X-ray source $(8.05\\mathsf{k e V},1.54\\mathring{\\mathsf{A}})$ and a Pilatus3R 300K detector. The incidence angle is $0.2^{\\circ}$ . All measurements were conducted under a vacuum environment to reduce air scattering. \n\n# Atomic Force Microscopy and Transmission Electron Microscopy \n\nThe morphologies of the polymer/acceptor blend films were investigated by AFM (Agilent Technologies, 5500 AFM/SPM System) in contacting under normal air conditions at room temperature with a $1~{\\upmu\\mathrm{m}}$ , $3~{\\upmu\\mathrm{m}}$ , and $5~{\\upmu\\mathrm{m}}$ scanner. Samples for the TEM measurements were prepared as follows: the active layer films were spin-casted on ITO/poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) substrates, and the substrates with active layers were submerged in deionized water to make the active layers float onto the air-water interface. Then, the floated films were picked up on an unsupported 200 mesh copper grid for the TEM measurements. TEM measurements were performed in a JEM-2100F. \n\n# Calculations \n\nDFT calculations were performed with the uB97X-D functional using the $6.31+5(d,mathsf{p})$ basis set.2 Gaussian 16, revision B.010 was used for all calculations.3 The molecule Y6 was studied, with the N-alkyl chains replaced with N-secButyl groups, and the side alkyl chains replaced with $-C H_{3}$ . The geometry of Y6 was optimized and the vibrational frequencies were verified. \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information includes Supplemental Experimental Procedures, 25 figures, and 11 tables and can be found with this article online at https://doi. org/10.1016/j.joule.2019.01.004. \n\n# ACKNOWLEDGMENTS \n\nY. Zou acknowledges the National Key Research & Development Projects of China (2017YFA0206600), National Natural Science Foundation of China (21875286), and Science Fund for Distinguished Young Scholars of Hunan Province (2017JJ1029). Y.L. thanks the financial support of NSFC (91633301). H.-L.Y. acknowledges the National Natural Science Foundation of China (21761132001 and 91633301). X.L. acknowledges the financial support from CUHK direct grant and NSFC/RGC Joint Research Scheme (grant no. N_CUHK418/17), and M.L. and P.A.J. acknowledge financial support from NSERC, CIFAR, and Sentinelle Nord. This research was enabled in part by Calcul Qu ´ebec, Compute Ontario, SHARCNET, and Compute Canada. \n\n# AUTHOR CONTRIBUTIONS \n\nJ.Y. and Y. Zou conceived the idea; J.Y., Y. Zou, and Y. Zhang designed the synthetic route of the small-molecule acceptor and synthesized the molecule, and carried out the NMR and high-resolution mass spectrum measurements, and ultraviolet and cyclic voltammetry; L.Z. fabricated the conventional solar cell devices and performed the atomic force microscopy and TEM supervised by Y. Zou and Y.L.; T.-K.L. performed the GIWAXS and GISAXS experiment supervised by X.L.; G.Z. fabricated the inverted solar cell devices and performed the IQE experiments under the supervision of H.-L.Y.; P.A.J. and M.L. performed theoretical calculations of the small-molecule acceptor; J.Y. wrote the original draft; and all authors, including C.Z., H.P., Y.C., and J.U., contributed to analysis and writing. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: October 30, 2018 \nRevised: December 5, 2018 \nAccepted: January 10, 2019 \nPublished: January 17, 2019 \n\n# REFERENCES \n\n1. Yu, G., Gao, J., Hummelen, J.C., Wudl, F., and Heeger, A.J. (1995). Polymer photovoltaic cells - enhanced efficiencies via a network of internal donor-acceptor heterojunctions. Science 270, 1789–1791. 2. Halls, J.J.M., Pichler, K., Friend, R.H., Moratti, S.C., and Holmes, A.B. (1996). Exciton diffusion and dissociation in a poly(p-phenylenevinylene)/C60 heterojunction photovoltaic cell. Appl. Phys. Lett. 68, 3120– 3122. \n3. Thompson, B.C., and Fr ´echet, J.M. (2008). Polymer-fullerene composite solar cells. Angew. Chem. Int. Ed. 47, 58–77. 4. Li, G., Zhu, R., and Yang, Y. (2012). Polymer solar cells. Nat. Photonics 6, 153–161. 5. Li, Y., and Zou, Y. (2008). Conjugated polymer photovoltaic materials with broad absorption band and high charge carrier mobility. Adv. Mater. 20, 2952–2958. 6. Li, C., Liu, M., Pschirer, N.G., Baumgarten, M., and M ¨ullen, K. (2010). Polyphenylene-based materials for organic photovoltaics. Chem. Rev. 110, 6817–6855. \n7. Qian, D., Zheng, Z., Yao, H., Tress, W., Hopper, T.R., Chen, S., Li, S., Liu, J., Chen, S., Zhang, J., et al. (2018). Design rules for minimizing voltage losses in high-efficiency organic solar cells. Nat. Mater. 17, 703–709. 8. Liu, Y., Zhao, J., Li, Z., Mu, C., Ma, W., Hu, H., Jiang, K., Lin, H., Ade, H., and Yan, H. (2014). Aggregation and morphology control enables multiple cases of high-efficiency polymer solar cells. Nat. Commun. 5, 5293. \n9. Huang, Y., Kramer, E.J., Heeger, A.J., and Bazan, G.C. (2014). Bulk heterojunction solar cells: morphology and performance relationships. Chem. Rev. 114, 7006–7043. \n10. Hu, H., Chow, P.C.Y., Zhang, G., Ma, T., Liu, J., Yang, G., and Yan, H. (2017). Design of donor polymers with strong temperature-dependent aggregation property for efficient organic photovoltaics. Acc. Chem. Res. 50, 2519–2528. \n11. Zhao, W., Li, S., Yao, H., Zhang, S., Zhang, Y., Yang, B., and Hou, J. (2017). Molecular optimization enables over $13\\%$ efficiency in organic solar cells. J. Am. Chem. Soc. 139, 7148–7151. \n12. Lin, Y., Wang, J., Zhang, Z.G., Bai, H., Li, Y., Zhu, D., and Zhan, X. (2015). An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174. \n13. Luo, Z., Bin, H., Liu, T., Zhang, Z.G., Yang, Y. Zhong, C., Qiu, B., Li, G., Gao, W., Xie, D., et al. (2018). Fine-tuning of molecular packing and energy level through methyl substitution enabling excellent small molecule acceptors for nonfullerene polymer solar cells with efficiency up to 12.54. Adv. Mater. 30, 1706124. \n14. Xu, X., Bi, Z., Ma, W., Wang, Z., Choy, W.C.H. Wu, W., Zhang, G., Li, Y., and Peng, Q. (2017). Highly efficient ternary-blend polymer solar cells enabled by a nonfullerene acceptor and two polymer donors with a broad composition tolerance. Adv. Mater. 29, 1704271. \n15. Zhou, Y., Kurosawa, T., Ma, W., Guo, Y., Fang, L., Vandewal, K., Diao, Y., Wang, C., Yan, Q., Reinspach, J., et al. (2014). High performance all-polymer solar cell via polymer side-chain engineering. Adv. Mater. 26, 3767–3772. \n16. Baran, D., Ashraf, R.S., Hanifi, D.A. Abdelsamie, M., Gasparini, N., Ro¨ hr, J.A., Holliday, S., Wadsworth, A., Lockett, S., Neophytou, M., et al. (2017). Reducing the efficiency-stability-cost gap of organic photovoltaics with highly efficient and stable small molecule acceptor ternary solar cells. Nat. Mater. 16, 363–369. \n17. Li, Y., Lin, J.D., Che, X., Qu, Y., Liu, F., Liao, L.S., and Forrest, S.R. (2017). High efficiency nearinfrared and semitransparent non-fullerene acceptor organic photovoltaic cells. J. Am. Chem. Soc. 139, 17114–17119. \n18. Meng, D., Sun, D., Zhong, C., Liu, T., Fan, B., Huo, L., Li, Y., Jiang, W., Choi, H., Kim, T., et al. (2016). High-performance solution-processed non-fullerene organic solar cells based on selenophene-containing perylene bisimide acceptor. J. Am. Chem. Soc. 138, 375–380. \n19. Wu, Q., Zhao, D., Schneider, A.M., Chen, W., and Yu, L. (2016). Covalently bound clusters of alpha-substituted PDI-rival electron acceptors to fullerene for organic solar cells. J. Am. Chem. Soc. 138, 7248–7251. \n20. Yao, Z., Liao, X., Gao, K., Lin, F., Xu, X., Shi, X., Zuo, L., Liu, F., Chen, Y., and Jen, A.K. (2018). Dithienopicenocarbazole-based acceptors for efficient organic solar cells with optoelectronic response over 1000 nm and an extremely low energy loss. J. Am. Chem. Soc. 140, 2054–2057. \n21. Ma, Y., Zhang, M., Yan, Y., Xin, J., Wang, T., Ma, W., Tang, C., and Zheng, Q. (2017). Laddertype dithienonaphthalene-based smallmolecule acceptors for efficient nonfullerene organic solar cells. Chem. Mater. 29, 7942– 7952. \n22. Liu, Y., Zhang, Z., Feng, S., Li, M., Wu, L., Hou, R., Xu, X., Chen, X., and Bo, Z. (2017). Exploiting noncovalently conformational locking as a design strategy for high performance fusedring electron acceptor used in polymer solar cells. J. Am. Chem. Soc. 139, 3356–3359. \n23. Xia, D., Gehrig, D., Guo, X., Baumgarten, M., Laquai, F., and Mu¨ llen, K. (2015). A spirobifluorene based 3D electron acceptor with dicyanovinylene substitution for solutionprocessed non-fullerene organic solar cells. J. Mater. Chem. A Mater. Energy Sustain. 3, 11086–11092. \n24. Jiang, W., Yu, R., Liu, Z., Peng, R., Mi, D., Hong, L., Wei, Q., Hou, J., Kuang, Y., and Ge, Z. (2018). Ternary nonfullerene polymer solar cells with $12.16\\%$ efficiency by introducing one acceptor with cascading energy level and complementary absorption. Adv. Mater. 30, 1703005. \n25. Kan, B., Zhang, J., Liu, F., Wan, X., Li, C., Ke, X., Wang, Y., Feng, H., Zhang, Y., Long, G., et al. (2018). Fine-tuning the energy levels of a nonfullerene small-molecule acceptor to achieve a high short-circuit current and a power \n\nconversion efficiency over $12\\%$ in organic solar \n\ncells. Adv. Mater. 30, 1704904. \n26. Guo, $\\times.,$ Facchetti, A., and Marks, T.J. (2014). Imide- and amide-functionalized polymer semiconductors. Chem. Rev. 114, 8943–9021. \n27. Cheng, P., Li, G., Zhan, X., and Yang, Y. (2018). Next-generation organic photovoltaics based on non-fullerene acceptors. Nat. Photonics 12, 131–142. \n28. Zhang, S., Qin, Y., Zhu, J., and Hou, J. (2018). Over $14\\%$ efficiency in polymer solar cells enabled by a chlorinated polymer donor. Adv. Mater. 30, e1800868. \n29. Fei, Z., Eisner, F.D., Jiao, X., Azzouzi, M., Rohr, J.A., Han, Y., Shahid, M., Chesman, A.S.R., Easton, C.D., McNeill, C.R., et al. (2018). An alkylated indacenodithieno[3,2-b]thiophenebased nonfullerene acceptor with high crystallinity exhibiting single junction solar cell efficiencies greater than $13\\%$ with low voltage losses. Adv. Mater. 30, 1705209. \n30. Li, W., Ye, L., Li, S., Yao, H., Ade, H., and Hou, J. (2018). A High-efficiency organic solar cell enabled by the strong intramolecular electron push-pull effect of the nonfullerene acceptor. Adv. Mater. 30, e1707170. \n31. Sun, J., Ma, X., Zhang, Z., Yu, J., Zhou, J., Yin, X., Yang, L., Geng, R., Zhu, R., Zhang, F., and Tang, W. (2018). Dithieno[3,2-b:20,30-d]pyrrol fused nonfullerene acceptors enabling over $13\\%$ efficiency for organic solar cells. Adv. Mater. 30, e1707150. \n32. Zhou, Z., Xu, S., Song, J., Jin, Y., Yue, Q., Qian, Y., Liu, F., Zhang, F., and Zhu, X. (2018). Highefficiency small-molecule ternary solar cells with a hierarchical morphology enabled by synergizing fullerene and non-fullerene acceptors. Nat. Energy 3, 952–959. \n33. Wang, J., Zhang, J., Xiao, Y., Xiao, T., Zhu, R., Yan, C., Fu, Y., Lu, G., Lu, X., Marder, S.R., and Zhan, X. (2018). Effect of isomerization on highperformance nonfullerene electron acceptors. J. Am. Chem. Soc. 140, 9140–9147. \n34. Huang, C., Liao, X., Gao, K., Zuo, L., Lin, F., Shi, $\\times.,$ Li, C.-Z., Liu, H., Li, X., Liu, F., et al. (2018). Highly efficient organic solar cells based on S,N-heteroacene non-fullerene acceptors. Chem. Mater. 30, 5429–5434. \n35. Zhang, M., Guo, X., Ma, W., Ade, H., and Hou, J. (2015). A large-bandgap conjugated \n\npolymer for versatile photovoltaic applications \n\nwith high performance. Adv. Mater. 27, 4655– 4660. \n36. R ¨uhle, S. (2016). Tabulated values of the Shockley–Queisser limit for single junction solar cells. Sol. Energy 130, 139–147. \n37. Feng, L., Yuan, J., Zhang, Z., Peng, H., Zhang, Z.G., Xu, S., Liu, Y., Li, Y., and Zou, Y. (2017). Thieno[3,2-b]pyrrolo-fused pentacyclic benzotriazole-based acceptor for efficient organic photovoltaics. ACS Appl. Mater. Interfaces 9, 31985–31992. \n38. Wu, J.S., Cheng, S.W., Cheng, Y.J., and Hsu, C.S. (2015). Donor-acceptor conjugated polymers based on multifused ladder-type arenes for organic solar cells. Chem. Soc. Rev. 44, 1113–1154. \n39. Hu, H., Jiang, K., Yang, G., Liu, J., Li, Z., Lin, H., Liu, Y., Zhao, J., Zhang, J., Huang, F., et al. (2015). Terthiophene-based D-A polymer with an asymmetric arrangement of alkyl chains that enables efficient polymer solar cells. J. Am. Chem. Soc. 137, 14149–14157. \n40. Park, S.H., Roy, A., Beaupre´ , S., Cho, S., Coates, N., Moon, J.S., Moses, D., Leclerc, M., Lee, K., and Heeger, A.J. (2009). Bulk heterojunction solar cells with internal quantum efficiency approaching $100\\%$ . Nat. Photonics 3, 297–302. \n41. Chen, Z., Cai, P., Chen, J., Liu, X., Zhang, L., Lan, L., Peng, J., Ma, Y., and Cao, Y. (2014). Low band-gap conjugated polymers with strong interchain aggregation and very high hole mobility towards highly efficient thick-film polymer solar cells. Adv. Mater. 26, 2586–2591. \n42. Lei, T., Xia, X., Wang, J.Y., Liu, C.J., and Pei, J. (2014). ‘‘Conformation locked’’ strong electrondeficient poly(p-phenylene vinylene) derivatives for ambient-stable n-type fieldeffect transistors: synthesis, properties, and effects of fluorine substitution position. J. Am. Chem. Soc. 136, 2135–2141. \n43. Uddin, M.A., Lee, T.H., Xu, S., Park, S.Y., Kim, T., Song, S., Nguyen, T.L., Ko, S.-j., Hwang, S., Kim, $\\mathsf{J.Y.},$ and Woo, H.Y. (2015). Interplay of intramolecular noncovalent coulomb interactions for semicrystalline photovoltaic polymers. Chem. Mater. 27, 5997–6007. \n44. Huang, H., Yang, L., Facchetti, A., and Marks, T.J. (2017). Organic and polymeric semiconductors enhanced by noncovalent \n\nconformational locks. Chem. Rev. 117, 10291– \n\n10318. \n45. Zhang, Z., Yu, J., Yin, X., Hu, Z., Jiang, Y., Sun, J., Zhou, J., Zhang, F., Russell, T.P., Liu, F., and Tang, W. (2018). Conformation locking on fused-ring electron acceptor for highperformance nonfullerene organic solar cells. Adv. Funct. Mater. 28, 1705095. \n46. Chai, J.-D., and Head-Gordon, M. (2008). Longrange corrected hybrid density functionals with damped atom-atom dispersion corrections. Phys. Chem. Chem. Phys. 10, 6615–6620. \n47. Frisch, M.J., Trucks, G.W., Schlegel, H.B., Scuseria, G.E., Robb, M.A., Cheeseman, J.R., Scalmani, G., Barone, V., Petersson, G.A., Nakatsuji, H., et al. (2016). Gaussian 16, Revision B.01 (Gaussian, Inc.). \n48. Long, G., Wu, B., Solanki, A., Yang, X., Kan, B., Liu, X., Wu, D., Xu, Z., Wu, W.R., and Jeng, U.S. (2016). New insights into the correlation between morphology, excited state dynamics, and device performance of small molecule organic solar cells. Adv. Energy Mater. 6, 1600961. \n49. Yuan, J., Qiu, L., Zhang, Z.-G., Li, Y., Chen, Y., and Zou, Y. (2016). Tetrafluoroquinoxaline based polymers for non-fullerene polymer solar cells with efficiency over $9\\%$ . Nano Energy 30, 312–320. \n50. Liu, J., Chen, S., Qian, D., Gautam, B., Yang, G., Zhao, J., Bergqvist, J., Zhang, F., Ma, W., and Ade, H. (2016). Fast charge separation in a nonfullerene organic solar cell with a small driving force. Nat. Energy 1, 16089. \n51. Gong, X., Tong, M., Brunetti, F.G., Seo, J., Sun, Y., Moses, D., Wudl, F., and Heeger, A.J. (2011). Bulk heterojunction solar cells with large opencircuit voltage: electron transfer with small donor-acceptor energy offset. Adv. Mater. 23, 2272–2277. \n52. Rao, A., Chow, P.C.Y., Ge´ linas, S., Schlenker, C.W., Li, C.-Z., Yip, H.-L., Jen, A.K.Y., Ginger, D.S., and Friend, R.H. (2013). The role of spin in the kinetic control of recombination in organic photovoltaics. Nature 500, 435–439. \n53. Mai, J., Xiao, Y., Zhou, G., Wang, J., Zhu, J., Zhao, N., Zhan, X., and Lu, X. (2018). Hidden structure ordering along backbone of fusedring electron acceptors enhanced by ternary bulk heterojunction. Adv. Mater. 30, e1802888. " + }, + { + "id": "10.1126_science.aaw3780", + "DOI": "10.1126/science.aaw3780", + "DOI Link": "http://dx.doi.org/10.1126/science.aaw3780", + "Relative Dir Path": "mds/10.1126_science.aaw3780", + "Article Title": "Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene", + "Authors": "Sharpe, AL; Fox, EJ; Barnard, AW; Finney, J; Watanabe, K; Taniguchi, T; Kastner, MA; Goldhaber-Gordon, D", + "Source Title": "SCIENCE", + "Abstract": "When two sheets of graphene are stacked at a small twist angle, the resulting flat superlattice minibands are expected to strongly enhance electron-electron interactions. Here, we present evidence that near three-quarters (3/4) filling of the conduction miniband, these enhanced interactions drive the twisted bilayer graphene into a ferromagnetic state. In a narrow density range around an apparent insulating state at 3/4, we observe emergent ferromagnetic hysteresis, with a giant anomalous Hall (AH) effect as large as 10.4 kilohms and indications of chiral edge states. Notably, the magnetization of the sample can be reversed by applying a small direct current. Although the AH resistance is not quantized, and dissipation is present, our measurements suggest that the system may be an incipient Chern insulator.", + "Times Cited, WoS Core": 1346, + "Times Cited, All Databases": 1481, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000483195200043", + "Markdown": "# Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene \n\nAaron L. Sharpe1,2\\*, Eli J. $\\mathbf{Fox^{2,3*}}$ , Arthur W. Barnard3, Joe Finney3, Kenji Watanabe4, Takashi Taniguchi4, M. A. Kastner2,3,5,6, David Goldhaber-Gordon2,3† \n\n1Department of Applied Physics, Stanford University, 348 Via Pueblo Mall, Stanford, CA 94305, USA. 2Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025, USA. 3Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA. 4National Institute for Materials Science, Namiki 1-1, Tsukuba, Ibaraki 305-0044, Japan. 5Science Philanthropy Alliance, 480 California Avenue #304, Palo Alto, CA 94306, USA. 6Department of Physics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. \\*These authors contributed equally to this work. \n\n†Corresponding author. Email: goldhaber-gordon@stanford.edu \n\nWhen two sheets of graphene are stacked at a small twist angle, the resulting flat superlattice minibands are expected to strongly enhance electron-electron interactions. Here we present evidence that near three-quarters (3/4) filling of the conduction miniband these enhanced interactions drive the twisted bilayer graphene into a ferromagnetic state. In a narrow density range around an apparent insulating state at 3/4, we observe emergent ferromagnetic hysteresis, with a giant anomalous Hall (AH) effect as large as $10.4\\:\\mathsf{k}\\Omega$ and indications of chiral edge states. Surprisingly, the magnetization of the sample can be reversed by applying a small DC current. Although the AH resistance is not quantized and dissipation is significant, our measurements suggest that the system may be an incipient Chern insulator. \n\nIn weakly dispersing bands, electron-electron interactions dominate over kinetic energy, often leading to interesting correlated phases. Graphene has emerged as a preeminent platform for investigating such flat bands because of the control of the band structure enabled by stacking multiple layers and the tunability of the band filling via electrostatic gating. In particular, the moiré superlattice of so-called “magic-angle” twisted bilayer graphene (TBG), in which one monolayer graphene sheet is stacked on top of another with a relative angle of rotation between the two crystal lattices of near one degree, is predicted to host nearly flat bands of ${\\sim}10\\ \\mathrm{meV}$ width (1–3). \n\nIn the single-particle picture, the flat bands are four-fold degenerate because of spin and valley symmetries (4). However, magic-angle TBG has recently been shown to exhibit high-resistance states at half $(1/2)$ and three-quarter $(3/4)$ filling of the conduction and valence bands $(5,\\ 6)$ and at onequarter $(1/4)$ filling of the conduction band $\\textcircled{6}$ , all cases where metallic behavior would be expected in the absence of interactions. Surprisingly, magic-angle TBG can become superconducting when doped slightly away from $1/2$ filling of either the conduction or valence band $(6,7)$ . \n\nTheoretical calculations have raised the possibility of magnetic order as a result of interactions lifting spin and valley degeneracies (8–15). Here, we present unambiguous experimental evidence of emergent ferromagnetism at $3/4$ filling of the conduction band in TBG: a giant anomalous Hall (AH) effect that displays hysteresis in magnetic field. We also find evidence of chiral edge conduction. Our results suggest that the 3/4-filling state is a correlated Chern insulator. \n\nWe used a “tear-and-stack” dry-transfer method $(4,\\ 16)$ and standard lithographic techniques to fabricate a TBG Hall bar device (Fig. 1, inset) with a target twist angle $\\theta=1.17^{\\circ}$ . The graphene is encapsulated in two hexagonal boron nitride (hBN) cladding layers to protect the channel from disorder and to act as dielectrics for electrostatic gating. With both a silicon back gate and $\\mathrm{Ti/Au}$ top gate, we can independently tune the charge density $n$ in the TBG and the perpendicular displacement field $D$ (17, 18). \n\nWe measured the longitudinal and Hall resistances using standard lock-in techniques with a 5 nA RMS AC bias current. A complicated electronic structure is revealed by the behavior of the longitudinal resistance as a function of $n$ and $D$ (Fig. 1, upper panel). We observe strong resistance peaks at the charge neutrality point (CNP) [identified from Landau fan diagrams (17)] and at densities $\\pm n_{\\mathrm{s}}=3.37\\times10^{12}~\\mathrm{cm^{-2}}$ corresponding to full filling of the mini-Brillouin zone (mBZ) of the TBG superlattice, with four electrons (or holes) per superlattice unit cell. This value of $n_{\\mathrm{s}}$ is consistent with a twist angle $\\uptheta=1.20^{\\circ}\\pm0.01^{\\circ}$ in the TBG heterostructure (19), very near our target angle of $1.17^{\\circ}$ . A slight kink in the positions of the CNP and other features as a function of displacement field is noticeable but not repeatable between cool-downs (17). \n\nBeyond the peaks expected from a single-particle picture of the TBG band structure, we observe additional high resistance states at $1/4,1/2$ , and $3/4$ fillings of the mBZ. These fillings, corresponding to one, two, and three electrons per superlattice unit cell, respectively, have previously been attributed to correlated insulating states $(6,7)$ . Another unexpected peak at $n/n_{\\mathrm{s}}=-1.15$ and a corresponding shoulder on the full filling peak of the electron side (seen in Fig. 1, lower panel) do not correspond to expectations for TBG alone. They likely result from the lattice alignment of the top graphene sheet with the top hBN layer, with the density $1.15n_{\\mathrm{s}}$ corresponding to an angle $\\mathbf{\\theta}\\mathbf{\\theta}\\mathbf{=}\\mathbf{0.81^{\\circ}\\pm0.02^{\\circ}}$ (19). Such near-alignment with the top hBN layer is confirmed in an optical image of the heterostructure [fig. S1 in (17)] by the rotational alignment of straight edges of the hBN and graphene flakes; the bottom hBN is far from aligned with the bottom graphene sheet. This vertical asymmetry in the heterostructure may play a role in the strong dependence of the peak structure on the sign and magnitude of the displacement field $(I7)$ . \n\nMagnetotransport in graphene-based heterostructures typically does not depend on the history of the applied field. Surprisingly, we find that in a narrow range of $n$ near $n/n_{\\mathrm{s}}=$ $3/4$ , transport is hysteretic with respect to an applied out-ofplane magnetic field $B$ (Fig. 2A). When the applied field is swept to zero from a large negative value, a large AH resistance $R_{y x}\\approx\\pm6~\\mathrm{k}\\Omega$ remains, with the sign depending on the direction of the field sweep, indicating that the sample has a remanent magnetization. This large AH signal is especially striking given the absence of both transition metals (typically associated with magnetism) and heavy elements (to give spinorbit coupling) in TBG. If the field is left at zero, the magnetization is very stable, with no significant change in the Hall resistance observed over the course of six hours (17). As the field is increased beyond a coercive field of order $100~\\mathrm{mT}$ opposite to the direction of the training field, the Hall signal changes sign, pointing to a reversal of the magnetization. \n\nMultiple intermediate jumps appear near the coercive field; these are very repeatable over successive hysteresis loops $(I7)$ and likely correspond to either a mixed domain structure with varying coercivities or a repeatable pattern of domain wall motion and pinning. This behavior may result from inhomogeneity caused by local variations in the twist angle between the graphene sheets, which has recently been directly imaged using transmission electron microscopy (20), or by local variations in electrostatic potential (21). \n\nHysteresis loops of $R_{y x}$ and $R_{x x}$ would ideally be antisymmetric and symmetric, respectively (in the sense that $R_{i j}(B)=\\pm\\tilde{R}_{i j}(-B)$ , where $R_{i j}$ and $\\tilde{R}_{{}_{i j}}$ are measured with the field sweeping in opposite directions). We find that $R_{y x}$ hysteresis loops are roughly antisymmetric but offset vertically by $-1\\mathtt{k}\\Omega$ . $R_{x x}$ is nearly flat with field, but has an antisymmetric component, presumably because of mixing in of the large changes in $R_{y x}$ . \n\nWe define the coercive field as half the difference between the fields where the largest jumps in $R_{y x}$ occur on the upward and downward sweeps. With increasing temperature $T,$ , the coercive field steadily decreases before vanishing at $3.9\\mathrm{~K~}$ (Fig. 2, C and D). This monotonic dependence could be expected because flipping individual domains or moving domain walls in a magnet is usually thermally activated (22). \n\nThe Hall signal appears to be the sum of two parts: an anomalous component that reflects the sample magnetization (23), and a conventional component linear in field with a Hall slope $R_{\\mathrm{H}}$ [Fig. 2B; see $(I7)$ for how we separate these two components]. Unlike the coercive field, the magnitude of the residual anomalous Hall resistance at zero field, which we denote by $R_{y x}^{\\mathrm{AH}}$ , does not vary monotonically with temperature: $R_{y x}^{\\mathrm{AH}}$ rises slightly with increasing $T\\mathrm{up}$ to $2.8~\\mathrm{K}$ , before rapidly falling to zero by $5\\mathrm{K}$ (Fig. 2, C and D). \n\nAlthough the hysteresis is observable over a wide range of displacement fields $(I7)$ , it only emerges in a narrow range of densities near $3/4$ filling of the mBZ. $R_{y x}^{\\mathrm{AH}}$ displays a sharp peak as a function of $n/n_{\\mathrm{s}}$ , reaching $6.6~\\mathrm{k}\\Omega$ for $n/n_{\\mathrm{s}}=0.758$ with a full width at half maximum of $0.04n_{\\mathrm{s}}$ (Fig. 2B). These measurements were made along a trajectory for which $D$ changes by approximately $10\\%$ coincident with the primary intended change in $n$ (17). In a separate measurement, we observed hysteresis loops with $R_{y x}^{\\mathrm{AH}}$ up to $10.4~\\mathrm{k}\\Omega$ [fig. S7B in (17)]. \n\nThe gate-voltage dependence of the conventional linear Hall slope $R_{\\mathrm{H}}(I7)$ appears typical for a transition from $p$ -typeto $n$ -type-dominated conduction in a semimetal or small-gap semiconductor, with $\\left|R_{\\mathrm{H}}\\right|$ rising when approaching the transition from either side, then turning over and crossing through zero (Fig. 2B). Recent studies of near-magic-angle TBG have reported high resistance at $3/4$ filling $(6,7)$ (cf. our Fig. 1), suggesting that spin and valley symmetries are spontaneously broken, resulting in a low density of states (or a gap) at this filling. Our results similarly indicate a possible correlated insulating state, here with an AH effect in a narrow range of densities around this same filling. \n\nThe presence of a giant AH effect in an apparent insulator is reminiscent of a ferromagnetic topological insulator approaching a Chern insulator state (24–26), where it would exhibit a quantum anomalous Hall (QAH) effect: longitudinal resistivity $\\uprho_{x x}$ approaches zero and Hall resistivity $\\uprho_{y x}$ is quantized to $h/C e^{2}$ (27, 28), where $h$ is Planck’s constant, $e$ is the electron charge, and $c$ is the Chern number arising from the Berry curvature of the filled bands $C=\\pm1$ in presently available QAH materials). Chiral edge modes associated with a quantized Hall system manifest in nonlocal transport measurements (29, 30). In an ideal QAH system described by the Büttiker edge state model (31), floating metallic contacts equilibrate with the chiral edge states that propagate into them. Clearly our results are not those of an ideal QAH system. Dissipation can cause deviations from the ideal behavior, while still giving results differing from classical diffusive transport. Below we present and analyze our experimental evidence for nonlocal transport in the magnetic state. \n\nThe three-terminal resistance $R_{54,149}$ where $R_{i j,k\\ell}=V_{k\\ell}/I_{i j}$ with $\\boldsymbol{V_{k\\ell}}$ the voltage between terminals $k$ and $\\ell$ when a current $I_{i j}$ flows from terminal $\\mathbf{\\omega}_{i}$ to $j,$ is shown in Fig. 3A for two values of $n/n_{\\mathrm{s}}$ . When the density is tuned away from the center of the magnetic regime, $R_{54,14}$ is ${\\sim}5~\\mathrm{k}\\Omega$ and nearly independent of applied field. We ascribe this behavior to diffusive bulk transport and a finite contact resistance to ground. By contrast, at the center of the magnetic regime we observe a hysteresis loop with $R_{54,14}^{\\downarrow}=3.3~\\mathrm{k}\\Omega$ and $R_{54,14}^{\\uparrow}=9.1~\\mathrm{k}\\Omega$ , where $R_{i j,k\\ell}^{\\uparrow(\\downarrow)}$ are the remanent resistances at zero field after the sample has been magnetized by an upward (downward) applied field [more precisely defined in $(I7)$ in the discussion of calculating $R_{y x}^{\\mathrm{AH}}]$ . The difference $\\left|R_{54,14}^{\\uparrow}-R_{54,14}^{\\downarrow}\\right|$ is largest near the peak in $R_{y x}^{\\mathrm{AH}}$ shown in Fig. 2B. For a QAH effect, we would expect $R_{54,14}$ to be either 0 or $h/C e^{2}$ (25,813 $\\Omega$ for $C=1_{.}^{\\cdot}$ ). Although the difference $\\left|R_{54,14}^{\\uparrow}-R_{54,14}^{\\downarrow}\\right|=5.8~\\mathrm{k}\\Omega$ is smaller than the ideal $C=1$ QAH case by a factor of 4, it could be consistent with a QAH state in combination with other dissipative transport mechanisms or a complex network of domain walls (in addition to contact resistance). These three-terminal measurements alone cannot rule out diffusive bulk transport with a very large (anomalous) Hall coefficient, but four-terminal measurements suggest this is unlikely. \n\nIn contrast to the three-terminal case, four-terminal nonlocal resistances where the voltage is measured far from the current path are exponentially small in the case of homogeneous diffusive conduction (32). For $n/n_{\\mathrm{s}}=0.725$ , away from the peak in $R_{y x}^{\\mathrm{AH}}$ , the measured $R_{45,12}=10\\Omega$ (Fig. 3B) is indeed small. In the magnetic regime at $n/n_{\\mathrm{s}}=0.749$ , however, the four-terminal resistance is two orders of magnitude larger than the $3\\Omega$ expected from homogeneous bulk conduction, with a hysteresis loop yielding $R_{54,12}^{\\downarrow}=42\\Omega$ and $\\boldsymbol{R}_{54,12}^{\\uparrow}=240\\Omega$ . Although in an ideal QAH state with pure chiral edge conduction this four-terminal resistance would be zero, the presence of additional conduction paths, such as extra non-chiral edge states (33), parallel bulk conduction, or transport along magnetic domain walls (34, 35), can result in large, hysteretic nonlocal resistances [we elaborate on this discussion in $(I7)]$ . \n\nSurprisingly, we find that the $n/n_{\\mathrm{s}}=3/4$ state is extremely sensitive to an applied DC current. All of the measurements described above were performed with a 5 nA RMS AC bias current, but we observed curious behavior when we added a DC bias $I_{\\mathrm{DC}}$ to this small AC signal. Sweeping $\\scriptstyle I_{\\mathrm{DC}}$ between $\\pm50$ nA with $B=0$ (Fig. 4), we found that the differential Hall resistance $d V_{y x}/d I$ follows a hysteresis loop reminiscent of its magnetic field dependence. This loop was very repeatable after a slight deviation from the first trace (black trace, Fig. 4), for which $\\scriptstyle I_{\\mathrm{DC}}$ was ramped from 0 to $-50\\ \\mathrm{nA}$ after first magnetizing the sample in a $-500\\ \\mathrm{mT}$ field. Additional details about the nature of the jumps in differential resistance and the effect of external magnetic field on the hysteresis loops are presented in $(I7)$ . \n\nThe switching of $d V_{y x}/d I$ is clear evidence that, like the external magnetic field, the applied DC current bias modifies the magnetization. This phenomenon might be similar to switching in other ferromagnetic materials, in which spintransfer or spin-orbit torques can influence the magnetization. However, the current necessary to flip the moment appears to be very small (36). It has also been proposed that a current could efficiently drive domain wall motion in a QAH system due to quantum interference effects from the edge states (37). \n\nOur observation of a large hysteretic AH effect establishes a ferromagnetic moment associated with the apparent $3/4$ correlated insulating state. Specifically, we suggest that this state is a Chern insulator, with the AH effect arising intrinsically from Berry curvature in the band structure. Extrinsic mechanisms for AH, based on scattering rather than band topology, cannot contribute to the Hall resistance of an insulator (23), yet the measured $R_{y x}^{\\mathrm{AH}}$ is largest at an apparent insulating state. Furthermore, our measurements yield a Hall angle $\\uprho_{y x}/\\uprho_{x x}$ up to 1.4, almost an order of magnitude larger than any other reported AH (38) apart from magnetic topological insulators exhibiting a QAH effect (here we convert our measured resistances to resistivities which we approximate as spatially homogeneous). With $\\rho_{y x}\\lesssim0.4h/e^{2}$ and $\\rho_{x x}\\approx0.3h/e^{2}$ the present device is clearly not an ideal Chern insulator. Yet after early magnetically doped topological insulators showed comparable values (39–41), growth improvements in those materials soon yielded QAH (24–26). If the present device is a nascent Chern insulator, the largest measured $R_{y x}^{\\mathrm{AH}}\\approx h/2.5e^{2}$ limits the possible Chern number to $C=$ 1 or 2. \n\nIn combination with nonlocal transport that appears incompatible with homogeneous bulk conduction, the sheer magnitudes of the Hall and longitudinal resistances suggest a picture of chiral edge modes in combination with a poorly conducting bulk or a network of magnetic domain walls resulting from inhomogeneity [see $(I7)$ for additional discussion]. These possibilities can be directly explored in future experiments using spatially resolved magnetometry to search for domains and transport in a Corbino geometry to measure bulk conduction independent of chiral edge modes if domain walls can be removed. \n\nAchieving a Chern insulator state by definition requires opening a topologically nontrivial gap. The low energy flat minibands in magic-angle TBG are empirically isolated from higher order bands (4), which is expected when taking into account mutual relaxation of the two layers’ lattices (3). The low energy conduction and valence minibands have been variously predicted to meet at Dirac points at the CNP, which may (42, 43) or may not $(44,45)$ be symmetry protected. The rotational alignment of the TBG to one of the hBN cladding layers in our device could thus be key to the observed AH effect: the associated periodic moiré potential should on average break A-B sublattice symmetry, opening or enhancing a gap at the mini-Dirac points. A gap associated with such symmetry breaking has been seen (19, 46, 47) and explained (48–50) in heterostructures of monolayer or Bernal-stacked bilayer graphene aligned with hBN. At $3/4$ filling of the conduction band of thus-gapped magic angle TBG, spin and valley symmetry may be spontaneously broken, and 3 of the 4 flavors filled with the other empty. This scenario could account for our observation of an apparent Chern insulator. Indeed, Ref. (9) predicts a QAH effect arising in TBG (without aligned hBN) at $3/4$ filling from such a mechanism [see Ref. (51) for a prediction of a similar situation in graphene-based moiré systems]. \n\nAside from the topological aspect, the appearance of magnetism in this system is striking. Unlike previous studies of graphitic carbon exhibiting magnetism owing to adsorbed impurities (52) or defects $(53,54)$ [including Ref. (55), where the magnetism observed in bulk graphite has since been attributed to defects $(56,57)]$ , the order in the present device appears to emerge because of interactions in a clean graphene-based system; the anomalous Hall signal appears only in a narrow range of densities around a state that may be spin and valley polarized. Such intrinsic magnetism also stands in contrast to the magnetic topological insulators, where exchange coupling is induced through doping with transition metals (24, 28, 30). Further experiment and theory will be needed to elucidate the order parameter, which may have both spin and orbital components or break spatial symmetry [cf. Ref. (58) for a model in which an antiferromagnet is a Chern insulator]. \n\nThe discovery of a possible platform for QAH physics, less disordered than the familiar magnetic chalcogenide alloys, may offer hope for more robust quantization, with applications in metrology (27), quantum computation (59–61), or low-power-consumption electronics. The ability to switch the magnetization in TBG with an applied DC current might have practical applications in extremely low-power magnetic memory architectures, given the orders-of-magnitude smaller critical current density required for flipping the magnetization compared to prior devices (36). More broadly, understanding the magnetic order and topological character of the correlated insulating states will be crucial to unraveling the rich phase diagram of TBG. \n\nNote added in proof: After submission of this manuscript, two theoretical works appeared (62, 63) where the alignment of TBG to a cladding hBN layer is specifically considered and possible mechanisms for ferromagnetism and an AH effect are discussed. \n\n# REFERENCES AND NOTES \n\n1. R. Bistritzer, A. H. MacDonald, Moire bands in twisted double-layer graphene. Proc. Natl. Acad. Sci. U.S.A. 108, 12233–12237 (2011). doi:10.1073/pnas.1108174108 Medline \n2. S. Fang, E. Kaxiras, Electronic structure theory of weakly interacting bilayers. Phys. Rev. B 93, 235153 (2016). doi:10.1103/PhysRevB.93.235153 \n3. N. N. Nam, M. Koshino, Lattice relaxation and energy band modulation in twisted bilayer graphene. Phys. Rev. B 96, 075311 (2017). doi:10.1103/PhysRevB.96.075311 \n4. Y. Cao, J. Y. Luo, V. Fatemi, S. Fang, J. D. Sanchez-Yamagishi, K. Watanabe, T. Taniguchi, E. Kaxiras, P. Jarillo-Herrero, Superlattice-induced insulating states and valley-protected orbits in twisted bilayer graphene. Phys. Rev. Lett. 117, 116804 (2016). doi:10.1103/PhysRevLett.117.116804 Medline \n5. Y. Cao, V. Fatemi, A. Demir, S. Fang, S. L. Tomarken, J. Y. Luo, J. D. SanchezYamagishi, K. Watanabe, T. Taniguchi, E. Kaxiras, R. C. Ashoori, P. Jarillo-Herrero, Correlated insulator behaviour at half-filling in magic-angle graphene superlattices. Nature 556, 80–84 (2018). doi:10.1038/nature26154 Medline \n6. M. Yankowitz, S. Chen, H. Polshyn, Y. Zhang, K. Watanabe, T. Taniguchi, D. Graf, A. F. Young, C. R. Dean, Tuning superconductivity in twisted bilayer graphene. Science 363, 1059–1064 (2019). doi:10.1126/science.aav1910 Medline \n7. Y. Cao, V. Fatemi, S. Fang, K. Watanabe, T. Taniguchi, E. Kaxiras, P. Jarillo-Herrero, Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43–50 (2018). doi:10.1038/nature26160 Medline \n8. J. Kang, O. Vafek, Strong coupling phases of partially filled twisted bilayer graphene narrow bands. Phys. Rev. Lett. 122, 246401 (2019). doi:10.1103/PhysRevLett.122.246401 \n9. M. Xie, A. H. MacDonald, On the nature of the correlated insulator states in twisted bilayer graphene. arXiv:1812.04213 [cond-mat.str-el] (11 December 2018). \n10. M. Ochi, M. Koshino, K. Kuroki, Possible correlated insulating states in magic-angle twisted bilayer graphene under strongly competing interactions. Phys. Rev. B 98, 081102 (2018). doi:10.1103/PhysRevB.98.081102 \n11. J. F. Dodaro, S. A. Kivelson, Y. Schattner, X. Q. Sun, C. Wang, Phases of a phenomenological model of twisted bilayer graphene. Phys. Rev. B 98, 075154 (2018). doi:10.1103/PhysRevB.98.075154 \n12. A. Thomson, S. Chatterjee, S. Sachdev, M. S. Scheurer, Triangular antiferromagnetism on the honeycomb lattice of twisted bilayer graphene. Phys. Rev. B 98, 075109 (2018). doi:10.1103/PhysRevB.98.075109 \n13. J. W. F. Venderbos, R. M. Fernandes, Correlations and electronic order in a twoorbital honeycomb lattice model for twisted bilayer graphene. Phys. Rev. B 98, 245103 (2018). doi:10.1103/PhysRevB.98.245103 \n14. K. Seo, V. N. Kotov, B. Uchoa, Ferromagnetic Mott state in twisted graphene bilayers at the magic angle. Phys. Rev. Lett. 122, 246402 (2019). doi:10.1103/PhysRevLett.122.246402 \n15. B. Padhi, P. Phillips, Pressure-induced metal-insulator transition in twisted bilayer graphene. Phys. Rev. B 99, 205141 (2019). doi:10.1103/PhysRevB.99.205141 \n16. K. Kim, M. Yankowitz, B. Fallahazad, S. Kang, H. C. P. Movva, S. Huang, S. Larentis, C. M. Corbet, T. Taniguchi, K. Watanabe, S. K. Banerjee, B. J. LeRoy, E. Tutuc, van der Waals heterostructures with high accuracy rotational alignment. Nano Lett. 16, 1989–1995 (2016). doi:10.1021/acs.nanolett.5b05263 Medline \n17. See supplementary materials. \n18. J. B. Oostinga, H. B. Heersche, X. Liu, A. F. Morpurgo, L. M. K. Vandersypen, Gateinduced insulating state in bilayer graphene devices. Nat. Mater. 7, 151–157 (2008). doi:10.1038/nmat2082 Medline \n19. B. Hunt, J. D. Sanchez-Yamagishi, A. F. Young, M. Yankowitz, B. J. LeRoy, K. Watanabe, T. Taniguchi, P. Moon, M. Koshino, P. Jarillo-Herrero, R. C. Ashoori, Massive Dirac fermions and Hofstadter butterfly in a van der Waals heterostructure. Science 340, 1427–1430 (2013). doi:10.1126/science.1237240 Medline \n20. H. Yoo, R. Engelke, S. Carr, S. Fang, K. Zhang, P. Cazeaux, S. H. Sung, R. Hovden, A. W. Tsen, T. Taniguchi, K. Watanabe, G.-C. Yi, M. Kim, M. Luskin, E. B. Tadmor, E. Kaxiras, P. Kim, Atomic and electronic reconstruction at the van der Waals interface in twisted bilayer graphene. Nat. Mater. 18, 448–453 (2019). doi:10.1038/s41563-019-0346-z Medline \n21. J. Xue, J. Sanchez-Yamagishi, D. Bulmash, P. Jacquod, A. Deshpande, K. Watanabe, T. Taniguchi, P. Jarillo-Herrero, B. J. LeRoy, Scanning tunnelling microscopy and spectroscopy of ultra-flat graphene on hexagonal boron nitride. Nat. Mater. 10, 282–285 (2011). doi:10.1038/nmat2968 Medline \n22. S. Emori, C. K. Umachi, D. C. Bono, G. S. Beach, Generalized analysis of thermally activated domain-wall motion in Co/Pt multilayers. J. Magn. Magn. Mater. 378, 98–106 (2015). doi:10.1016/j.jmmm.2014.10.147 \n23. N. Nagaosa, J. Sinova, S. Onoda, A. H. MacDonald, N. P. Ong, Anomalous Hall effect. Rev. Mod. Phys. 82, 1539–1592 (2010). doi:10.1103/RevModPhys.82.1539 \n24. C.-Z. Chang, J. Zhang, X. Feng, J. Shen, Z. Zhang, M. Guo, K. Li, Y. Ou, P. Wei, L.-L. Wang, Z.-Q. Ji, Y. Feng, S. Ji, X. Chen, J. Jia, X. Dai, Z. Fang, S.-C. Zhang, K. He, Y. Wang, L. Lu, X.-C. Ma, Q.-K. Xue, Experimental observation of the quantum anomalous Hall effect in a magnetic topological insulator. Science 340, 167–170 (2013). doi:10.1126/science.1234414 Medline \n25. J. G. Checkelsky, R. Yoshimi, A. Tsukazaki, K. S. Takahashi, Y. Kozuka, J. Falson, M. Kawasaki, Y. Tokura, Trajectory of the anomalous Hall effect towards the quantized state in a ferromagnetic topological insulator. Nat. Phys. 10, 731–736 (2014). doi:10.1038/nphys3053 \n26. X. Kou, S.-T. Guo, Y. Fan, L. Pan, M. Lang, Y. Jiang, Q. Shao, T. Nie, K. Murata, J. Tang, Y. Wang, L. He, T.-K. Lee, W.-L. Lee, K. L. Wang, Scale-invariant quantum anomalous Hall effect in magnetic topological insulators beyond the twodimensional limit. Phys. Rev. Lett. 113, 137201 (2014). doi:10.1103/PhysRevLett.113.137201 Medline \n27. E. J. Fox, I. T. Rosen, Y. Yang, G. R. Jones, R. E. Elmquist, X. Kou, L. Pan, K. L. Wang, D. Goldhaber-Gordon, Part-per-million quantization and current-induced breakdown of the quantum anomalous Hall effect. Phys. Rev. B 98, 075145 (2018). doi:10.1103/PhysRevB.98.075145 Medline \n28. R. Yu, W. Zhang, H.-J. Zhang, S.-C. Zhang, X. Dai, Z. Fang, Quantized anomalous Hall effect in magnetic topological insulators. Science 329, 61–64 (2010). doi:10.1126/science.1187485 Medline \n29. A. J. Bestwick, E. J. Fox, X. Kou, L. Pan, K. L. Wang, D. Goldhaber-Gordon, Precise quantization of the anomalous Hall effect near zero magnetic field. Phys. Rev. Lett. 114, 187201 (2015). doi:10.1103/PhysRevLett.114.187201 Medline \n30. C.-Z. Chang, W. Zhao, D. Y. Kim, P. Wei, J. K. Jain, C. Liu, M. H. W. Chan, J. S. Moodera, Zero-field dissipationless chiral edge transport and the nature of dissipation in the quantum anomalous Hall state. Phys. Rev. Lett. 115, 057206 (2015). doi:10.1103/PhysRevLett.115.057206 Medline \n31. M. Büttiker, Absence of backscattering in the quantum Hall effect in multiprobe conductors. Phys. Rev. B 38, 9375–9389 (1988). doi:10.1103/PhysRevB.38.9375 Medline \n32. L. J. van der Pauw, Philips Res. Rep. 13, 1 (1958). \n33. J. Wang, B. Lian, H. Zhang, S.-C. Zhang, Anomalous edge transport in the quantum anomalous Hall state. Phys. Rev. Lett. 111, 086803 (2013). doi:10.1103/PhysRevLett.111.086803 Medline \n34. I. T. Rosen, E. J. Fox, X. Kou, L. Pan, K. L. Wang, D. Goldhaber-Gordon, Chiral transport along magnetic domain walls in the quantum anomalous Hall effect. npj Quantum Mater. 2, 69 (2017). doi:10.1038/s41535-017-0073-0 \n35. K. Yasuda, M. Mogi, R. Yoshimi, A. Tsukazaki, K. S. Takahashi, M. Kawasaki, F. Kagawa, Y. Tokura, Quantized chiral edge conduction on domain walls of a magnetic topological insulator. Science 358, 1311–1314 (2017). doi:10.1126/science.aan5991 Medline \n36. D. Apalkov, B. Dieny, J. M. Slaughter, Magnetoresistive random access memory. Proc. IEEE 104, 1796–1830 (2016). doi:10.1109/JPROC.2016.2590142 \n37. P. Upadhyaya, Y. Tserkovnyak, Domain wall in a quantum anomalous Hall insulator as a magnetoelectric piston. Phys. Rev. B 94, 020411 (2016). doi:10.1103/PhysRevB.94.020411 \n38. E. Liu, Y. Sun, N. Kumar, L. Müchler, A. Sun, L. Jiao, S.-Y. Yang, D. Liu, A. Liang, Q. Xu, J. Kroder, V. Süß, H. Borrmann, C. Shekhar, Z. Wang, C. Xi, W. Wang, W. Schnelle, S. Wirth, Y. Chen, S. T. B. Goennenwein, C. Felser, Giant anomalous Hall effect in a ferromagnetic Kagomé-lattice semimetal. Nat. Phys. 14, 1125–1131 (2018). doi:10.1038/s41567-018-0234-5 Medline \n39. J. G. Checkelsky, J. Ye, Y. Onose, Y. Iwasa, Y. Tokura, Dirac-fermion-mediated ferromagnetism in a topological insulator. Nat. Phys. 8, 729–733 (2012). doi:10.1038/nphys2388 \n40. C.-Z. Chang, J. Zhang, M. Liu, Z. Zhang, X. Feng, K. Li, L.-L. Wang, X. Chen, X. Dai, Z. Fang, X.-L. Qi, S.-C. Zhang, Y. Wang, K. He, X.-C. Ma, Q.-K. Xue, Thin films of magnetically doped topological insulator with carrier-independent long-range ferromagnetic order. Adv. Mater. 25, 1065–1070 (2013). doi:10.1002/adma.201203493 Medline \n41. X. Kou, M. Lang, Y. Fan, Y. Jiang, T. Nie, J. Zhang, W. Jiang, Y. Wang, Y. Yao, L. He, K. L. Wang, Interplay between different magnetisms in Cr-doped topological insulators. ACS Nano 7, 9205–9212 (2013). doi:10.1021/nn4038145 Medline \n42. H. C. Po, L. Zou, A. Vishwanath, T. Senthil, Origin of Mott insulating behavior and superconductivity in twisted bilayer graphene. Phys. Rev. X 8, 031089 (2018). doi:10.1103/PhysRevX.8.031089 \n43. L. Zou, H. C. Po, A. Vishwanath, T. Senthil, Band structure of twisted bilayer graphene: Emergent symmetries, commensurate approximants, and Wannier obstructions. Phys. Rev. B 98, 085435 (2018). doi:10.1103/PhysRevB.98.085435 \n44. J. Kang, O. Vafek, Symmetry, maximally localized Wannier states, and a lowenergy model for twisted bilayer graphene narrow bands. Phys. Rev. X 8, 031088 (2018). doi:10.1103/PhysRevX.8.031088 \n45. M. Koshino, N. F. Q. Yuan, T. Koretsune, M. Ochi, K. Kuroki, L. Fu, Maximally localized Wannier orbitals and the extended Hubbard model for twisted bilayer graphene. Phys. Rev. X 8, 031087 (2018). doi:10.1103/PhysRevX.8.031087 \n46. F. Amet, J. R. Williams, K. Watanabe, T. Taniguchi, D. Goldhaber-Gordon, Insulating behavior at the neutrality point in single-layer graphene. Phys. Rev. Lett. 110, 216601 (2013). doi:10.1103/PhysRevLett.110.216601 Medline \n47. F. Amet, thesis, Stanford University (2014). \n48. P. Moon, M. Koshino, Electronic properties of graphene/hexagonal-boron-nitride moiré superlattice. Phys. Rev. B 90, 155406 (2014). doi:10.1103/PhysRevB.90.155406 \n49. M. Mucha-Kruczyński, J. R. Wallbank, V. I. Fal’Ko, Heterostructures of bilayer graphene and h -BN: Interplay between misalignment, interlayer asymmetry, and trigonal warping. Phys. Rev. B 88, 205418 (2013). doi:10.1103/PhysRevB.88.205418 \n50. J. Jung, A. M. DaSilva, A. H. MacDonald, S. Adam, Origin of band gaps in graphene on hexagonal boron nitride. Nat. Commun. 6, 6308 (2015). doi:10.1038/ncomms7308 Medline \n51. Y.-H. Zhang, D. Mao, Y. Cao, P. Jarillo-Herrero, T. Senthil, Nearly flat Chern bands in moiré superlattices. Phys. Rev. B 99, 075127 (2019). doi:10.1103/PhysRevB.99.075127 \n52. N. Yeh, K. Sugihara, M. S. Dresselhaus, G. Dresselhaus, Transport properties and magnetic interactions in acceptor-type magnetic graphite intercalation compounds. Phys. Rev. B 40, 622–635 (1989). doi:10.1103/PhysRevB.40.622 Medline \n53. P. Esquinazi, D. Spemann, R. Höhne, A. Setzer, K.-H. Han, T. Butz, Induced magnetic ordering by proton irradiation in graphite. Phys. Rev. Lett. 91, 227201 (2003). doi:10.1103/PhysRevLett.91.227201 Medline \n54. A. W. Mombrú, H. Pardo, R. Faccio, O. F. de Lima, E. R. Leite, G. Zanelatto, A. J. C. Lanfredi, C. A. Cardoso, F. M. Araújo-Moreira, Multilevel ferromagnetic behavior of room-temperature bulk magnetic graphite. Phys. Rev. B 71, 100404 (2005). doi:10.1103/PhysRevB.71.100404 \n55. Y. Kopelevich, J. C. Medina Pantoja, R. R. da Silva, F. Mrowka, P. Esquinazi, Anomalous Hall effect in graphite. Phys. Lett. A 355, 233–236 (2006). doi:10.1016/j.physleta.2006.02.034 \n56. J. Červenka, M. I. Katsnelson, C. F. J. Flipse, Room-temperature ferromagnetism in graphite driven by two-dimensional networks of point defects. Nat. Phys. 5, 840–844 (2009). doi:10.1038/nphys1399 \n57. P. Esquinazi, J. Krüger, J. Barzola-Quiquia, R. Schönemann, T. Herrmannsdörfer, N. García, On the low-field Hall coefficient of graphite. AIP Adv. 4, 117121 (2014). doi:10.1063/1.4902099 \n58. P. Zhou, C. Q. Sun, L. Z. Sun, Two dimensional antiferromagnetic Chern insulator: NiRuCl6. Nano Lett. 16, 6325–6330 (2016). doi:10.1021/acs.nanolett.6b02701 Medline \n59. B. Lian, X.-Q. Sun, A. Vaezi, X.-L. Qi, S.-C. Zhang, Topological quantum computation based on chiral Majorana fermions. Proc. Natl. Acad. Sci. U.S.A. 115, 10938–10942 (2018). doi:10.1073/pnas.1810003115 Medline \n60. Q. L. He, L. Pan, A. L. Stern, E. C. Burks, X. Che, G. Yin, J. Wang, B. Lian, Q. Zhou, E. S. Choi, K. Murata, X. Kou, Z. Chen, T. Nie, Q. Shao, Y. Fan, S.-C. Zhang, K. Liu, J. Xia, K. L. Wang, Chiral Majorana fermion modes in a quantum anomalous Hall insulator-superconductor structure. Science 357, 294–299 (2017). doi:10.1126/science.aag2792 Medline \n61. A. C. Mahoney, J. I. Colless, L. Peeters, S. J. Pauka, E. J. Fox, X. Kou, L. Pan, K. L. Wang, D. Goldhaber-Gordon, D. J. Reilly, Zero-field edge plasmons in a magnetic topological insulator. Nat. Commun. 8, 1836 (2017). doi:10.1038/s41467-017- 01984-5 Medline \n62. N. Bultinck, S. Chatterjee, M. P. Zaletel, Anomalous Hall ferromagnetism in twisted bilayer graphene. arXiv:1901.08110 [cond-mat.str-el] (23 January 2019). \n63. Y.-H. Zhang, D. Mao, T. Senthil, Twisted Bilayer Graphene Aligned with Hexagonal Boron Nitride: Anomalous Hall Effect and a Lattice Model. arXiv:1901.08209 [cond-mat.str-el] (24 January 2019). \n64. A. L. Sharpe, E. Fox, A. Barnard, J. Finney, K. Watanabe, T. Taniguchi, M. Kastner, D. Goldhaber-Gordon, Data for: Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene, Version 1.0, Stanford Digital Repository (2019); https://doi.org/10.25740/bg095cp1548. \n65. S. Bhandari, G.-H. Lee, A. Klales, K. Watanabe, T. Taniguchi, E. Heller, P. Kim, R. M. Westervelt, Imaging cyclotron orbits of electrons in graphene. Nano Lett. 16, 1690–1694 (2016). doi:10.1021/acs.nanolett.5b04609 Medline \n66. L. Wang, I. Meric, P. Y. Huang, Q. Gao, Y. Gao, H. Tran, T. Taniguchi, K. Watanabe, L. M. Campos, D. A. Muller, J. Guo, P. Kim, J. Hone, K. L. Shepard, C. R. Dean, Onedimensional electrical contact to a two-dimensional material. Science 342, 614– 617 (2013). doi:10.1126/science.1244358 Medline \n67. A. A. Zibrov, C. Kometter, H. Zhou, E. M. Spanton, T. Taniguchi, K. Watanabe, M. P. Zaletel, A. F. Young, Tunable interacting composite fermion phases in a half-filled bilayer-graphene Landau level. Nature 549, 360–364 (2017). doi:10.1038/nature23893 Medline \n68. I. Martin, C. D. Batista, Itinerant electron-driven chiral magnetic ordering and spontaneous quantum Hall effect in triangular lattice models. Phys. Rev. Lett. 101, 156402 (2008). doi:10.1103/PhysRevLett.101.156402 Medline \n69. S. Kivelson, D.-H. Lee, S.-C. Zhang, Global phase diagram in the quantum Hall effect. Phys. Rev. B 46, 2223–2238 (1992). doi:10.1103/PhysRevB.46.2223 Medline \n70. M. Hilke, D. Shahar, S. H. Song, D. C. Tsui, Y. H. Xie, D. Monroe, Experimental evidence for a two-dimensional quantized Hall insulator. Nature 395, 675–677 (1998). doi:10.1038/27160 \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge fruitful discussions with Michael Zaletel, Allan MacDonald, Ming Xie, Todadri Senthil, Steve Kivelson, Yoni Schattner, Nick Bultinck, Patrick Gallagher, Feng Wang, Matt Yankowitz, and Guorui Chen. Yuan Cao and Pablo JarilloHerrero generously taught us about their fab process and their insights into TBG. Hava Schwartz and Sungyeon Yang helped with device fabrication, and they and Anthony Chen performed preliminary measurements as part of a project-based lab class at Stanford. Funding: Device fabrication, measurements, and analysis were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, under Contract DE-AC02-76SF00515. Infrastructure and cryostat support were funded in part by the Gordon and Betty Moore Foundation through Grant GBMF3429. Part of this work was performed at the Stanford Nano Shared Facilities (SNSF), supported by the National Science Foundation under award ECCS-1542152. A. L. \n\nS. acknowledges support from a Ford Foundation Predoctoral Fellowship and a National Science Foundation Graduate Research Fellowship. E. F. acknowledges support from an ARCS Foundation Fellowship. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT, Japan and the CREST (JPMJCR15F3), JST. Author contributions: A.S. and J.F. fabricated devices. K.W. and T.T. provided the hBN crystals used for fabrication. A.S. and E.F. performed transport measurements. A.S., E.F., A.B., and J.F. analyzed the data. M.K. and D.G.-G. supervised the experiments and analysis. The manuscript was prepared by A.S. and E.F. with input from all authors. Competing interests: M.K. is a member of the Science Advisory Board of the Gordon and Betty Moore Foundation and is chair of the Basic Energy Science Advisory Committee. Both the Moore Foundation and Basic Energy Sciences provided funding for this work. Data and materials availability: The data from this study are available at the Stanford Digital Repository (64). \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/cgi/content/full/science.aaw3780/DC1 \n\nMaterials and Methods Supplementary Text Figs. S1 to S10 References (65–70) \n\n15 December 2018; accepted 3 July 2019 \nPublished online 25 July 2019 \n10.1126/science.aaw3780 \n\n![](images/cc14ff9857e9e5b213c80cc59d3224c0e810dbf574e704b6cdfac158fd826485.jpg) \n\nFig. 1. Correlated states in near-magic-angle TBG. (A) Longitudinal resistance $R_{x x}$ of the TBG device (measured between contacts separated by 2.15 squares) as a function of carrier density $n$ (shown on the top axis) and perpendicular displacement field $D$ (left axis), which are tuned by the top- and back-gate voltages, at 2.1 K. $n$ is mapped to a filling factor relative to the superlattice density $\\boldsymbol{{n}_{s}}$ , corresponding to four electrons per moiré unit cell, shown on the bottom axis. Inset: Optical micrograph of the completed device showing the top-gated Hall bar region (gold), electrical contacts (gold), regions of the heterostructure that have been etched to remove the TBG (green), and regions of the heterostructure that have not been etched (brown). The scale bar is $5\\upmu\\mathrm{m}$ . (B) Line cut of $R_{x x}$ with respect to $n$ taken at $D/\\in{\\mathfrak{o}}$ $=~-0.22$ V/nm showing the resistance peaks at full filling of the superlattice, and additional peaks likely corresponding to correlated states emerging at intermediate fillings. \n\n![](images/4deddc2a4fceee82b02c91cc1061deb44c55ebe6015bca1c89aee846929a2383.jpg) \n\nFig. 2. Emergent ferromagnetism near three-quarters filling. (A) Magnetic field dependence of the longitudinal resistance $R_{x x}$ (upper panel) and Hall resistance $R_{y x}$ (lower panel) with $n/n_{s}=0.746$ and $D/\\epsilon_{0}=-0.62$ $V/\\mathsf{n m}$ at $30~\\mathsf{m K}$ , demonstrating a hysteretic anomalous Hall effect resulting from emergent magnetic order. The solid and dashed lines correspond to measurements taken while sweeping the magnetic field $B$ up and down, respectively. (B) Zero-field anomalous Hall resistance $R_{y x}^{\\mathrm{AH}}$ (red) and ordinary Hall slope $R_{\\mathsf{H}}$ (blue) as a function of $n/n_{s}$ for $D/\\in\\L_{0}\\approx-0.6$ $v/\\mathsf{n m}$ . $R_{y x}^{\\mathrm{AH}}$ is peaked sharply with a maximum around $n/n_{s}=0.758$ , coincident with $R_{\\mathsf{H}}$ changing sign. These parameters are extracted from line fits of $R_{y x}$ versus $B$ on the upward and downward sweeping traces in a region where the $B$ -dependence appears dominated by the ordinary Hall effect (17). The error bars reflect fitting parameter uncertainty along with the effect of varying the fitting window, and are omitted when smaller than the marker. (C) Temperature dependence of $R_{y x}$ versus $B$ at $D/\\epsilon_{0}=-0.62$ V/nm and $n/n_{s}=0.746$ between $46~\\mathsf{m K}$ and $5.0\\mathsf{K}$ , showing the hysteresis loop closing with increasing temperature. Successive curves are offset vertically by $20~\\mathsf{k}\\Omega$ for clarity. (D) Coercive field and anomalous Hall resistance (extracted using the same fitting procedure as above) plotted as a function of temperature from the same data partially shown in (C). Data in Fig. 2 were taken during a separate cooldown from that of the data in the rest of the figures, but show representative behavior (17). \n\n![](images/c5d7a1b238393610e93513075de6b868e34776741609eec5aa87ee9785f797f2.jpg) \nFig. 3. Nonlocal resistances providing evidence of chiral edge states. (A and B) Three- and four-terminal nonlocal resistances $R_{54,14}$ (A) and $R_{54,12}$ (B), measured at $2.1\\mathsf{K}$ with $D/\\in_{0}=-0.22\\:\\forall/\\eta\\mathrm{m}$ on upward and downward sweeps of the magnetic field (solid and dashed traces, respectively). For $n/n_{s}=0.725$ (blue) away from the peak in AH resistance $R_{y x}^{\\mathrm{AH}}$ , the nonlocal resistances are consistent with diffusive bulk transport. However, with $n/n_{s}=$ 0.749 (red) in the magnetic regime where $R_{y x}^{\\mathrm{AH}}$ is maximal, large, hysteretic nonlocal resistances suggest chiral edge states are present. Insets: Schematics of the respective measurement configurations. Green arrows in the upper inset represent the apparent edge state chirality for positive magnetization, whereas in the lower inset they reflect negative magnetization. \nFig. 4. Current-driven switching of the magnetization. Differential Hall resistance $d V_{y x}/d I$ measured with a 5 nA AC bias as a function of an applied DC current $I_{\\mathrm{DC}}$ at $2.1\\mathsf{K}$ with $D/\\epsilon_{0}=$ $-0.22\\lor/\\mathsf{n m}$ and $n/n_{s}=0.749$ . After magnetizing the sample in a $-500\\mathrm{m}\\mathrm{T}$ field and returning to $B=0$ , $I_{\\mathsf{D C}}$ was swept from 0 to $-75$ nA (black trace), resulting in $d V_{y x}/d I$ changing sign. Two successive loops in $I_{\\mathsf{D C}}$ between $\\pm75$ nA demonstrate reversible and repeatable switching of the differential Hall resistance (red and blue, with solid and dashed traces corresponding to opposite sweep directions). Note that $d V_{y x}/d I$ is plotted against $-I_{\\mathrm{{DC}}}$ for better comparison with magnetic field hysteresis loops. \n\n# Science \n\n# Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene \n\nAaron L. Sharpe, Eli J. Fox, Arthur W. Barnard, Joe Finney, Kenji Watanabe, Takashi Taniguchi, M. A. Kastner and David Goldhaber-Gordon \n\npublished online July 25, 2019 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 67 articles, 9 of which you can access for free http://science.sciencemag.org/content/early/2019/07/24/science.aaw3780#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41560-019-0356-8", + "DOI": "10.1038/s41560-019-0356-8", + "DOI Link": "http://dx.doi.org/10.1038/s41560-019-0356-8", + "Relative Dir Path": "mds/10.1038_s41560-019-0356-8", + "Article Title": "Data-driven prediction of battery cycle life before capacity degradation", + "Authors": "Severson, KA; Attia, PM; Jin, N; Perkins, N; Jiang, B; Yang, Z; Chen, MH; Aykol, M; Herring, PK; Fraggedakis, D; Bazan, MZ; Harris, SJ; Chueh, WC; Braatz, RD", + "Source Title": "NATURE ENERGY", + "Abstract": "Accurately predicting the lifetime of complex, nonlinear systems such as lithium-ion batteries is critical for accelerating technology development. However, diverse aging mechanisms, significant device variability and dynamic operating conditions have remained major challenges. We generate a comprehensive dataset consisting of 124 commercial lithium iron phosphate/graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2,300 cycles. Using discharge voltage curves from early cycles yet to exhibit capacity degradation, we apply machine-learning tools to both predict and classify cells by cycle life. Our best models achieve 9.1% test error for quantitatively predicting cycle life using the first 100 cycles (exhibiting a median increase of 0.2% from initial capacity) and 4.9% test error using the first 5 cycles for classifying cycle life into two groups. This work highlights the promise of combining deliberate data generation with data-driven modelling to predict the behaviour of complex dynamical systems.", + "Times Cited, WoS Core": 1569, + "Times Cited, All Databases": 1690, + "Publication Year": 2019, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000467965700011", + "Markdown": "# Data-driven prediction of battery cycle life before capacity degradation \n\nKristen A. Severson $\\textcircled{10}1,5$ , Peter M. Attia $\\textcircled{10}2,5$ , Norman Jin $\\textcircled{10}2$ , Nicholas Perkins $\\oplus2$ , Benben Jiang $\\oplus1$ , Zi Yang $\\textcircled{10}2$ , Michael H. Chen $\\textcircled{10}2$ , Muratahan Aykol $\\textcircled{10}3$ , Patrick K. Herring $\\textcircled{10}3$ , Dimitrios Fraggedakis $\\oplus1$ , Martin Z. Bazant $\\textcircled{15}$ 1, Stephen J. Harris $\\textcircled{10}2,4$ , William C. Chueh $\\textcircled{10}2\\star$ and Richard D. Braatz   1\\* \n\nAccurately predicting the lifetime of complex, nonlinear systems such as lithium-ion batteries is critical for accelerating technology development. However, diverse aging mechanisms, significant device variability and dynamic operating conditions have remained major challenges. We generate a comprehensive dataset consisting of 124 commercial lithium iron phosphate/ graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2,300 cycles. Using discharge voltage curves from early cycles yet to exhibit capacity degradation, we apply machine-learning tools to both predict and classify cells by cycle life. Our best models achieve $9.1\\%$ test error for quantitatively predicting cycle life using the first 100 cycles (exhibiting a median increase of $0.2\\%$ from initial capacity) and $4.9\\%$ test error using the first 5 cycles for classifying cycle life into two groups. This work highlights the promise of combining deliberate data generation with data-driven modelling to predict the behaviour of complex dynamical systems. \n\nithium-ion batteries are deployed in a wide range of applications due to their low and falling costs, high energy densities and long lifetimes1–3. However, as is the case with many chemical, mechanical and electronic systems, long battery lifetime entails delayed feedback of performance, often many months to years. Accurate prediction of lifetime using early-cycle data would unlock new opportunities in battery production, use and optimization. For example, manufacturers can accelerate the cell development cycle, perform rapid validation of new manufacturing processes and sort/ grade new cells by their expected lifetime. Likewise, end users could estimate their battery life expectancy4–6. One emerging application enabled by early prediction is high-throughput optimization of processes spanning large parameter spaces (Supplementary Figs. 1 and 2), such as multistep fast charging and formation cycling, which are otherwise intractable due to the extraordinary time required. The task of predicting lithium-ion battery lifetime is critically important given its broad utility but challenging due to nonlinear degradation with cycling and wide variability, even when controlling for operating conditions7–11. \n\nMany previous studies have modelled lithium-ion battery lifetime. Bloom et al.12 and Broussely et al.13 performed early work that fitted semi-empirical models to predict power and capacity loss. Since then, many authors have proposed physical and semi-empirical models that account for diverse mechanisms such as growth of the solid–electrolyte interphase14,15, lithium plating16,17, active material loss18,19 and impedance increase20–22. Predictions of remaining useful life in battery management systems, summarized in these reviews5,6, often rely on these mechanistic and semi-empirical models for state estimation. Specialized diagnostic measurements such as coulombic efficiency23,24 and impedance spectroscopy25–27 can also be used for lifetime estimation. While these chemistry and/or mechanism-specific models have shown predictive success, developing models that describe full cells cycled under relevant operating conditions (for example, fast charging) remains challenging, given the many degradation modes and their coupling to thermal28,29 and mechanical28,30 heterogeneities within a cell30–32. \n\nApproaches using statistical and machine-learning techniques to predict cycle life are attractive, mechanism-agnostic alternatives. Recently, advances in computational power and data generation have enabled these techniques to accelerate progress for a variety of tasks, including prediction of material properties33,34, identification of chemical synthesis routes35 and material discovery for energy storage36–38 and catalysis39. A growing body of literature6,40,41 applies machine-learning techniques for predicting the remaining useful life of batteries using data collected in both laboratory and online environments. Generally, these works make predictions after accumulating data corresponding to degradation of at least $25\\%$ along the trajectory to failure42–48 or using specialized measurements at the beginning of life11. Accurate early prediction of cycle life with significantly less degradation is challenging because of the typically nonlinear degradation process (with negligible capacity degradation in early cycles) as well as the relatively small datasets used to date that span a limited range of lifetimes49. For example, Harris et al.10 found a weak correlation $(\\rho=0.1)$ between capacity values at cycle 80 and capacity values at cycle 500 for 24 cells exhibiting nonlinear degradation profiles, illustrating the difficulty of this task. Machine-learning approaches are especially attractive for high-rate operating conditions, where first-principles models of degradation are often unavailable. In short, opportunities for improving upon state-of-the-art prediction models include higher accuracy, earlier prediction, greater interpretability and broader application to a wide range of cycling conditions. \n\nIn this work, we develop data-driven models that accurately predict the cycle life of commercial lithium iron phosphate (LFP)/ graphite cells using early-cycle data, with no prior knowledge of degradation mechanisms. We generated a dataset of 124 cells with cycle lives ranging from 150 to 2,300 using 72 different fast-charging conditions, with cycle life (or equivalently, end of life) defined as the number of cycles until $80\\%$ of nominal capacity. For quantitatively predicting cycle life, our feature-based models can achieve prediction errors of $9.1\\%$ using only data from the first 100 cycles, at which point most batteries have yet to exhibit capacity degradation. Furthermore, using data from the first 5 cycles, we demonstrate classification into low- and high-lifetime groups and achieve a misclassification test error of $4.9\\%$ . These results illustrate the power of combining data generation with data-driven modelling to predict the behaviour of complex systems far into the future. \n\n![](images/c2d039e0ea934f4326cf9a2a09491e74d2f8beb3253238333d4da8f40c730c80.jpg) \nFig. 1 | Poor predictive performance of features based on discharge capacity in the first 100 cycles. a, Discharge capacity for the first 1,000 cycles of LFP/ graphite cells. The colour of each curve is scaled by the battery’s cycle life, as is done throughout the manuscript. b, A detailed view of a, showing only the first 100 cycles. A clear ranking of cycle life has not emerged by cycle 100. c, Histogram of the ratio between the discharge capacity of cycle 100 and that of cycle 2. The cell with the highest degradation $(90\\%)$ is excluded to show the detail of the rest of the distribution. The dotted line indicates a ratio of 1.00. Most cells have a slightly higher capacity at cycle 100 relative to cycle 2. d, Cycle life as a function of discharge capacity at cycle 2. The correlation coefficient of capacity at cycle 2 and log cycle life is $-0.06$ (remains unchanged on exclusion of the shortest-lived battery). e, Cycle life as a function of discharge capacity at cycle 100. The correlation coefficient of capacity at cycle 100 and log cycle life is 0.27 (0.08 excluding the shortest-lived battery). f, Cycle life as a function of the slope of the discharge capacity curve for cycles 95–100. The correlation coefficient of this slope and log cycle life is 0.47 (0.36 excluding the shortest-lived battery). \n\n# Data generation \n\nWe expect the space that parameterizes capacity fade in lithiumion batteries to be high dimensional due to their many capacity fade mechanisms and manufacturing variability. To probe this space, commercial LFP/graphite cells (A123 Systems, model \n\nAPR18650M1A, 1.1 Ah nominal capacity) were cycled in a temperature-controlled environmental chamber $\\left(30^{\\circ}\\mathrm{C}\\right)$ under varied fast-charging conditions but identical discharging conditions ( $4C$ to $2.0\\mathrm{V},$ where $1C$ is $1.1\\mathrm{A}$ ; see Methods for details). Since the graphite negative electrode dominates degradation in these cells, these results could be useful for other lithium-ion batteries based on graphite32,50–54. We probe average charging rates ranging from $3.6C_{\\mathrm{;}}$ the manufacturer’s recommended fast-charging rate, to $6C$ to probe the performance of current-generation power cells under extreme fast-charging conditions $\\mathord{\\sim}10\\mathrm{min}$ charging), an area of significant commercial interest55. By deliberately varying the charging conditions, we generate a dataset that captures a wide range of cycle lives, from approximately 150 to 2,300 cycles (average cycle life of 806 with a standard deviation of 377). While the chamber temperature is controlled, the cell temperatures vary by up to $10^{\\circ}\\mathrm{C}$ within a cycle due to the large amount of heat generated during charge and discharge. This temperature variation is a function of internal impedance and charging policy (Supplementary Figs. 3 and 4). Voltage, current, cell can temperature and internal resistance are continuously measured during cycling (see Methods for additional experimental details). The dataset contains approximately 96,700 cycles; to the best of the authors’ knowledge, our dataset is the largest publicly available for nominally identical commercial lithium-ion batteries cycled under controlled conditions (see Data availability section for access information). \n\n![](images/d1eca78c24e09eb054c27bf474e84d200f6462643ae296b000c149741dad74b0.jpg) \nFig. 2 | High performance of features based on voltage curves from the first 100 cycles. a, Discharge capacity curves for 100th and 10th cycles for a representative cell. b, Difference of the discharge capacity curves as a function of voltage between the 100th and 10th cycles, $\\Delta Q_{100-10}(V).$ , for 124 cells. c, Cycle life plotted as a function of the variance of $\\Delta Q_{100-10}(V)$ on a log–log axis, with a correlation coefficient of $-0.93$ . In all plots, the colours are determined based on the final cycle lifetime. In c, the colour is redundant with the y-axis. In b and c, the shortest lived battery is excluded. \n\n![](images/f796de77dedac78c191b9a6fce2eda97ae1d156a50beb63eb6f4f55d45409c60.jpg) \nFig. 3 | Observed and predicted cycle lives for several implementations of the feature-based model. The training data are used to learn the model structure and coefficient values. The testing data are used to assess generalizability of the model. We differentiate the primary test and secondary test datasets because the latter was generated after model development. The vertical dotted line indicates when the prediction is made in relation to the observed cycle life. The inset shows the histogram of residuals (predicted – observed) for the primary and secondary test data. a, ‘Variance’ model using only the log variance of $\\Delta Q_{100-10}(V).{\\bf b}$ , ‘Discharge’ model using six features based only on discharge cycle information, described in Supplementary Table 1. c, ‘Full’ model using the nine features described in Supplementary Table 1. Because some temperature probes lost contact during experimentation, four cells are excluded from the full model analysis. \n\nFig. 1a,b shows the discharge capacity as a function of cycle number for the first 1,000 cycles, where the colour denotes cycle life. The capacity fade is negligible in the first 100 cycles and accelerates near the end of life, as is often observed in lithium-ion batteries. The crossing of the capacity fade trajectories illustrates the weak relationship between initial capacity and lifetime; indeed, we find weak correlations between the log of cycle life and the discharge capacity at the second cycle $(\\rho=-0.06,$ , Fig. 1d) and the 100th cycle $_{\\mathscr{\\rho}=0.27}$ , Fig. 1e), as well as between the log of cycle life and the capacity fade rate near cycle 100 ( $_{\\mathscr{S}}\\mathscr{\\mathrm{~\\tiny~(~2~)~}}$ , Fig. 1f ). These weak correlations are expected because capacity degradation in these early cycles is negligible; in fact, the capacities at cycle 100 increased from the initial values for $81\\%$ of cells in our dataset (Fig. 1c). Small increases in capacity after a slow cycle or rest period are attributed to charge stored in the region of the negative electrode that extends beyond the positive electrode56,57. Given the limited predictive power of these correlations based on the capacity fade curves, we employ an alternative data-driven approach that considers a larger set of cycling data including the full voltage curves of each cycle, as well as additional measurements including cell internal resistance and temperature. \n\n# Machine-learning approach \n\nWe use a feature-based approach to build an early-prediction model. In this paradigm, features, which are linear or nonlinear transformations of the raw data, are generated and used in a regularized linear framework, the elastic net58. The final model uses a linear combination of a subset of the proposed features to predict the logarithm of cycle life. Our choice of a regularized linear model allows us to propose domain-specific features of varying complexity while maintaining high interpretability. Linear models also have low computational cost; the model can be trained offline, and online prediction requires only a single dot product after data preprocessing. \n\nWe propose features from domain knowledge of lithium-ion batteries (though agnostic to chemistry and degradation mechanisms), such as initial discharge capacity, charge time and cell can temperature. To capture the electrochemical evolution of individual cells during cycling, several features are calculated based on the discharge voltage curve (Fig. 2a). Specifically, we consider the cycle-to-cycle evolution of $Q(V)_{\\sun}$ , the discharge voltage curve as a function of voltage for a given cycle. As the voltage range is identical for every cycle, we consider capacity as a function of voltage, as opposed to voltage as a function of capacity, to maintain a uniform basis for comparing cycles. For instance, we can consider the change in discharge voltage curves between cycles 20 and 30, denoted $\\Delta Q_{30-20}(V){=}Q_{30}(V)\\ -\\ Q_{20}(V)$ , where the subscripts indicate cycle number. This transformation, $\\Delta Q(V)$ , is of particular interest because voltage curves and their derivatives are a rich data source that is effective in degradation diagnosis50,51,53,59–64. \n\nTable 1 | Model metrics for the results shown in Fig. 3 \n\n\n
RMSE (cycles) Mean percent error (%)
TrainPrimary testSecondary test TrainPrimary testSecondary test
'Variance' model103138 (138)19614.114.7 (13.2) 11.4
'Discharge' model7691(86)1739.813.0 (10.1)8.6
'Full' model51118 (100)2145.614.1 (7.5)10.7
\n\nTrain and primary/secondary test refer to the data used to learn the model and evaluate model performance, respectively. One battery in the test set reaches $80\\%$ state-of-health rapidly and does not match other observed patterns. Therefore, the parenthetical primary test results correspond to the exclusion of this battery. \n\nThe $\\varDelta Q(V)$ curves for our dataset are shown in Fig. 2b using the 100th and 10th cycles, that is, $\\Delta Q_{100-10}(V)$ . We discuss our selection of these cycle numbers at a later point. Summary statistics, for example minimum, mean and variance, were then calculated for the $\\Delta Q(V)$ curves of each cell. Each summary statistic is a scalar quantity that captures the change in voltage curves between two cycles. In our data-driven approach, these summary statistics are selected for their predictive ability, not their physical meaning. Immediately, a clear trend emerges between cycle life and a summary statistic, specifically variance, applied to $\\Delta\\dot{Q}_{100-10}(V)$ (Fig. 2c). \n\nBecause of the high predictive power of features based on $\\Delta Q_{100-10}(V)$ , we investigate three different models using (1) only the variance of $\\Delta Q_{100-10}(V)$ , (2) additional candidate features obtained during discharge and (3) features from additional data streams such as temperature and internal resistance. In all cases, data were taken only from the first 100 cycles. These three models, each with progressively more candidate features, were chosen to evaluate both the cost–benefit of acquiring additional data streams and the limits of prediction accuracy. The training data (41 cells) are used to select the model features and set the values of the coefficients, and the primary testing data (43 cells) are used to evaluate the model performance. We then evaluate the model on a secondary testing dataset (40 cells) generated after model development. Two metrics, defined in the ‘Machine-learning model development’ section, are used to evaluate our predictive performance: root-mean-squared error (RMSE), with units of cycles, and average percentage error. \n\n# Performance of early prediction models \n\nWe present three models to predict cycle life using increasing candidate feature set sizes; the candidate features are detailed in Supplementary Table 1 and Supplementary Note 1. The first model, denoted as the ‘variance’ model, does not consider subset selection and uses only the log variance of $\\Delta Q_{100-10}(V)$ for prediction. Surprisingly, using only this single feature results in a model with approximately $15\\%$ average percentage error on the primary test dataset and approximately $11\\%$ average percentage error on the secondary test dataset. We stress the error metrics of the secondary test dataset, as these data had not been generated at the time of model development and are thus a rigorous test of model performance. The second, ‘discharge’ model, considers additional information derived from measurements of voltage and current during discharge in the first 100 cycles (row blocks 1 and 2 of Supplementary Table 1). Of 13 features, 6 were selected. Finally, the third, ‘full’ model con­ si­ders all available features (all rows blocks of Supplementary Table 1). In this model, 9 out of 20 features were selected (Supplementary Fig. 5). As expected, by adding additional features, the primary test average percentage error decreases to $7.5\\%$ and the secondary test average percentage error decreases slightly to $10.7\\%$ . The error for the secondary test set is slightly higher for the full model when compared with the discharge model (Supplementary Note 2 and Supplementary Figs. 6–7). In all cases, the average percentage error is less than $15\\%$ and decreases to as little as $7.5\\%$ in the full model, excluding an anomalous cell. Table 1 and Fig. 3 display the performance of the ‘variance’, ‘discharge’ and ‘full’ models applied to our three datasets. \n\nTable 2 | Model metrics for the classification setting with a cycle life threshold of 550 cycles \n\n\n
Classification accuracy (%)
TrainPrimary testSecondary test
Variance classifier82.178.697.5
Full classifier97.492.797.5
\n\nTrain and primary/secondary test refer to the data used to learn the model and evaluate model performance, respectively. \n\nWe benchmark the performance of our cycle life prediction using early-cycle data against both prior literature and naïve models. A relevant metric is the extent of degradation that has to occur before an accurate prediction can be made. In our work, accurate prediction was achieved using voltage curves from early cycles corresponding to a capacity increase of $0.2\\%$ (median) relative to initial values (with the first and third quartile percentiles being $0.06\\%$ and $0.34\\%$ , respectively; see Fig. 1c). We are unaware of previous early-prediction demonstrations that do not require degradation in the battery capacity or specialized measurements. In fact, published models42–48 generally require data corresponding to at least $25\\%$ capacity degradation before making predictions at an accuracy comparable to that of this work. We also benchmark our model performance using naïve models, for example univariate models and/or models that only utilize information from the capacity fade curve (Supplementary Note 3, Supplementary Figs. 8–13 and Supplementary Tables 2–3). Notably, if the average cycle life of the training data is used for prediction, the average percentage error is approximately $30\\%$ and $36\\%$ for the primary and secondary test sets, respectively. Using data from the first 100 cycles, the most complex benchmark model using only features from the discharge capacity fade curve has errors of $23\\%$ and $50\\%$ for the primary and secondary test sets, respectively. In fact, a similar model that uses discharge capacity fade curve data from the first 300 cycles achieves comparable performance $27\\%$ and $46\\%$ for the primary and secondary test data, respectively), highlighting the difficulty of prediction without using voltage features. \n\nWe also consider contexts in which predictions are required at very low cycle number but the accuracy requirements are less stringent, such as sorting/grading and pack design applications. As an example, we develop a logistic regression model to classify cells into either a ‘low-lifetime’ or a ‘high-lifetime’ group, using only the first five cycles for various cycle life thresholds. For the ‘variance classifier’, we use only the $\\Delta Q(V)$ variance feature between the fourth and fifth cycles, $\\operatorname{var}(\\Delta Q_{5-4}(V))$ , and attain a test classification accuracy of $88.8\\%$ . For the ‘full classifier’, we use regularized logistic regression with 18 candidate features to achieve a test classification accuracy of $95.1\\%$ . These results are summarized in Table 2 and detailed in Supplementary Note 4, Supplementary Fig. 14–17 and Supplementary Tables 4–6. This approach illustrates the predictive ability of $\\Delta Q(V)$ even if data from the only first few cycles are used, and, more broadly, showcases our flexibility to tailor data-driven models to various use cases. \n\n![](images/dcf4c6a75db6002c44d3c4aea3451e514b61901cbb36e123d471c6386bcd37ea.jpg) \nFig. 4 | Transformations of voltage–capacity discharge curves for three fast-charged cells that were tested with periodic slow diagnostic cycles. a–c, dQ/dV at C/10; d–f, dV/dQ at C/10; g–i, dQ/dV at $4C;$ j–l, $\\Delta Q(V)$ at 4 C. a,d,g,j, 4 C/4 C; b,e,h,k, $6C/4C;$ c,f,i,l, $8C/4C$ The solid black line is the first cycle (cycle 10 for fast cycling), the dotted grey line is cycle 101 or 100 (fast and slow, respectively) and the coloured thick line is the end-of-life cycle $80\\%$ state-of-health). The colour of the end-of-life cycle is consistent with the colour scale in Figs. 1 and 2. For $\\Delta Q(V),$ , a thin dotted grey line is added every 100 cycles. The patterns observed using slow cycling are consistent with $\\mathsf{L A M}_{\\mathrm{deNE}}$ and loss of lithium inventory (Supplementary Fig. 18). The features are smeared during fast charging. The log variance $\\Delta Q(V)$ model dataset predicts the lifetime of these cells within $15\\%$ . \n\n# Rationalization of predictive performance \n\nWhile models that include features from all available data streams generally have the lowest errors, our predictive ability primary comes from features based on transformations of the voltage curves, as evidenced by the performance of the single-feature ‘variance’ model. This feature is consistently selected in both models with feature selection (‘discharge’ and ‘full’). Other transformations of the voltage curves can also be used to predict cycle life; for example, the full model selects both the minimum and variance of $\\Delta Q_{100-10}(V)$ . In particular, the physical meaning of the variance feature is associated with the dependence of the discharged energy dissipation on voltage, which is indicated by the grey region between the voltage curves in Fig. 2a. The integral of this region is the total change in energy dissipation between cycles under galvanostatic conditions and is linearly related to the mean of $\\Delta Q(V)$ . Zero variance would indicate energy dissipations that are independent of voltage. Thus, the variance of $\\Delta Q(V)$ reflects the extent of non-uniformity in the energy dissipation with voltage, due to either open-circuit or kinetic processes, a point that we return to later. \n\n![](images/f8acb35d04e4215cf970c6ad5e6dd605042b65503ea41c84614661073077152e.jpg) \nFig. 5 | Prediction error as a function of cycle indices. RMSE error, in units of cycles, is presented for training (a) and testing $(\\pmb{\\ b})$ datasets using only the log variance of $\\Delta Q_{i-j}(V),$ , where indices i and j are varied. These errors are averaged over 20 random partitions of the data into equal training and testing datasets. The errors are relatively flat after cycle 80. The increases in error around cycles $\\scriptstyle{j=55}$ and $i{=}70$ are due to temperature fluctuations of the environmental chamber (see Supplementary Fig. 25). \n\nWe observe that features derived from early-cycle discharge voltage curves have excellent predictive performance, even before the onset of capacity fade. We rationalize this observation by investigating degradation modes that do not immediately result in capacity fade yet still manifest in the discharge voltage curve and are also linked to rapid capacity fade near the end of life. \n\nWhile our data-driven approach has successfully revealed predictive features from early-cycle discharge curves, identification of degradation modes using only high-rate data is challenging because of the convolution of kinetics with open-circuit behaviour. Thus, we turn to established methods for mechanism identification using low-rate cycling data. Dubarry et al.61 mapped degradation modes in LFP/graphite cells to their resultant shift in $\\mathrm{d}Q/\\mathrm{d}V$ and dV/dQ derivatives for diagnostic cycles at $C/20$ . One degradation mode—loss of active material of the delithiated negative electrode $\\left(\\mathrm{LAM}_{\\mathrm{deNE}}\\right)$ —results in a shift in discharge voltage with no change in capacity. This behaviour is observed when the negative electrode capacity is larger than that of the positive electrode, as is the case in these LFP/graphite cells. Thus, a loss of delithiated negative electrode material changes the potentials at which lithium ions are stored without changing the overall capacity50,61. As proposed by Anséan et al.50, at high rates of $\\mathrm{LAM}_{\\mathrm{deNE}}.$ , the negative electrode capacity will eventually fall below the remaining lithium-ion inventory. At this point, the negative electrode will not have enough sites to accommodate lithium ions during charging, inducing lithium plating50. Since plating is an additional source of irreversibility, the capacity loss accelerates. Thus, in early cycles, $\\mathrm{LAM}_{\\mathrm{deNE}}$ shifts the voltage curve without affecting the capacity fade curve and induces rapid capacity fade at high cycle number. This degradation mode, in conjunction with loss of lithium inventory, is widely observed in commercial LFP/graphite cells operated under similar conditions32,50–54. We note that the graphitic negative electrode is common to nearly all commercial lithium-ion batteries in use today. \n\nTo investigate the contribution of $\\mathrm{LAM}_{\\mathrm{deNE}}$ we perform additional experiments for cells cycled with varied charging rates (4 C, $6C$ and $8C$ ) and a constant discharge rate $(4C)$ , incorporating slow cycling at the 1st, 100th and end-of-life cycles. Derivatives of diagnostic discharge curves at $C/10$ (Fig. 4, rows 1 and 2) are compared with these, and $\\Delta Q(V)$ , at $4C$ at the 10th, 101st and end-of-life cycles (rows 3 and 4). The shifts in $\\mathrm{d}Q/\\mathrm{d}V$ and dV/dQ observed in diagnostic cycling correspond to a shift of the potentials at which lithium is stored in graphite during charging and are consistent with $\\mathrm{LAM}_{\\mathrm{deNE}}$ and loss of lithium inventory operating concurrently (Supplementary Fig. 18)50,51,61. The magnitude of these shifts from the 1st to 100th cycle increases with charging rate (Supplementary Note 5 and Supplementary Fig. 19). These observations rationalize why models using features based on discharge curves have lower errors than models using only features based on capacity fade curves, since $\\mathrm{LAM}_{\\mathrm{deNE}}$ does not manifest in capacity fade in early cycles. We note that $\\mathrm{LAM}_{\\mathrm{deNE}}$ alters a fraction of, rather than the entire, discharge voltage curve, consistent with the strong correlation between the variance of $\\Delta Q(V)$ and cycle life (Fig. 2c). In summary, we attribute the success of our predictive models to features that capture changes in both the capacity fade curves and voltage curves, since degradation may be silent in discharge capacity but present in voltage curves. \n\nAs noted above, differential methods such as dQ/dV and dV/dQ are used extensively to pinpoint degradation mechanisms50,51,53,59–61. These approaches require low-rate diagnostic cycles, as higher rates smear out features due to heterogeneous de(intercalation)32, as seen by comparing row 1 with row 3 in Fig. 4. However, these diagnostic cycles often induce a temporary capacity recovery, commonly observed in cells when the geometric area of the negative electrode exceeds that of the positive electrode56,57. As such, they interrupt the trajectory of capacity fade (Supplementary Fig. 20). Therefore, by applying summary statistics to $\\Delta Q(V)$ collected at high rate, we simultaneously avoid both low-rate diagnostic cycles and numerical differentiation, which decreases the signalto-noise ratio65. However, these high-rate discharge voltage curves can additionally reflect both kinetic degradation modes and heterogeneities that are not observed in $\\mathrm{d}Q/\\mathrm{d}V$ and $\\mathrm{d}V/\\mathrm{d}Q$ curves at $C/10$ . We consider the influence of kinetic degradation modes in Supplementary Note 6, Supplementary Fig. 21 and Supplementary Tables 7–8); briefly, we estimate that low-rate modes such as $\\mathrm{LAM}_{\\mathrm{deNE}}$ primarily contribute $(50-80\\%)$ to $\\Delta Q(V)$ . We also mention that low-rate degradation modes such as $\\mathrm{LAM}_{\\mathrm{deNE}}$ influence the kinetics at high rate, in this case by increasing the local current density of the active regions. \n\nFinally, additional analysis was performed to understand the impact of the cycle indices chosen for $\\Delta Q(V)$ features in the regression setting. Univariate linear models using only the variance of $Q_{i}(V)\\ –\\ Q_{j}(V)$ for the training and primary testing datasets were investigated and are displayed in Fig. 5. We find that the model is relatively insensitive to the indexing scheme for $i>60$ , suggesting that quantitative cycle life prediction using even earlier cycles is possible. This trend is further validated by the model coefficients shown in Supplementary Fig. 22. We hypothesize that the insensitivity of the model to the indexing scheme implies linear degradation with respect to cycle number, which is often assumed for LAM modes50,61. Relative indexing schemes based on cycles in which a specified capacity fade was achieved were also investigated and did not result in improved predictions. Furthermore, because the discharge capacity initially increases, specified decreases in capacity require more cycles to develop than fixed indexing (Supplementary Note 7 and Supplementary Figs. 23–25). \n\n# Conclusions \n\nData-driven modelling is a promising route for diagnostics and prognostics of lithium-ion batteries and enables emerging applications in their development, manufacturing and optimization. We develop cycle life prediction models using early-cycle discharge data yet to exhibit capacity degradation, generated from commercial LFP/graphite batteries cycled under fast-charging conditions. In the regression setting, we obtain a test error of $9.1\\%$ using only the first 100 cycles; in the classification setting, we obtain a test error of $4.9\\%$ using data from the first 5 cycles. This level of accuracy is achieved by extracting features from high-rate discharge voltage curves as opposed to only from the capacity fade curves, and without using data from slow diagnostic cycles or assuming prior knowledge of cell chemistry and degradation mechanisms. The success of the model is rationalized by demonstrating consistency with degradation modes that do not manifest in capacity fade during early cycles but impact the voltage curves. In general, our approach can complement approaches based on physical and semi-empirical models and on specialized diagnostics. Broadly speaking, this work highlights the promise of combining data generation and data-driven modelling for understanding and developing complex systems such as lithium-ion batteries. \n\n# Methods \n\nCell cycling and data generation. 124 commercial high-power LFP/graphite A123 APR18650M1A cells were used in this work. The cells have a nominal capacity of 1.1 Ah and a nominal voltage of $3.3\\mathrm{V}.$ The manufacturer’s recommended fast-charging protocol is $3.6C$ constant current–constant voltage (CC-CV). The rate capability of these cells during charge and discharge is shown in Supplementary Fig. 27. \n\nAll cells were tested in cylindrical fixtures with four-point contacts on a 48-channel Arbin LBT battery testing cycler. The tests were performed at a constant temperature of $30^{\\circ}\\mathrm{C}$ in an environmental chamber (Amerex Instruments). Cell can temperatures were recorded by stripping a small section of the plastic insulation and contacting a type T thermocouple to the bare metal casing using thermal epoxy (OMEGATHERM 201) and Kapton tape. \n\nThe cells were cycled with various candidate fast-charging policies (Supplementary Table 9) but identically discharged. Cells were charged from $0\\%$ to $80\\%$ state-of-charge (SOC) with one of 72 different one-step and two-step charging policies. Each step is a single $C$ rate applied over a given SOC range; for example, a two-step policy could consist of a $6C$ charging step from $0\\%$ to $50\\%$ SOC, followed by a $4C$ step from $50\\%$ to $80\\%$ SOC. The 72 charging polices represent different combinations of current steps within the $0\\%$ to $80\\%$ SOC range. The charging time from $0\\%$ to $80\\%$ SOC ranged from 9 to $13.3\\mathrm{min}$ . An internal resistance measurement was obtained during charging at $80\\%$ SOC by averaging 10 pulses of $\\pm3.6C$ with a pulse width of 30 or $33\\mathrm{ms}$ , where $1C$ is $1.1\\mathrm{A}$ , or the current required to fully (dis)charge the nominal capacity (1.1 Ah) in 1 h. All cells then charged from $80\\%$ to $100\\%$ SOC with a uniform 1 C CC-CV charging step to $3.6\\mathrm{V}$ and a current cutoff of $C/50$ . All cells were subsequently discharged with a CC-CV discharge at $4C$ to $2.0\\mathrm{V}$ with a current cutoff of $C/50$ . The voltage cutoffs used in this work follow those recommended by the manufacturer. \n\nOur dataset is described in Supplementary Table 9. In total, our dataset consists of three ‘batches’, or cells run in parallel. Each batch has slightly different testing conditions. For the $^{<}2017–05–12^{,}$ batch, the rests after reaching $80\\%$ SOC during charging and after discharging were $1\\mathrm{min}$ and 1 s, respectively. For the $^{<}2017–06–30^{3}$ batch, the rests after reaching $80\\%$ SOC during charging and after discharging were both $5\\mathrm{{min}}$ . For the ‘2018-04-12’ batch, 5 s rests were placed after reaching $80\\%$ SOC during charging, after the internal resistance test and before and after discharging. \n\nA histogram of cycle life for the three datasets is presented in Supplementary Fig. 28. We note that four cells had unexpectedly high measurement noise and were excluded from analysis. \n\nTo standardize the voltage–capacity data across cells and cycles, all $4C$ discharge curves were fitted to a spline function and linearly interpolated (Supplementary Fig. 29). Capacity was fitted as a function of voltage and evaluated at 1,000 linearly spaced voltage points from $3.5\\mathrm{V}$ to $2.0\\mathrm{V}.$ These uniformly sized vectors enabled straightforward data manipulations such as subtraction. \n\nMachine-learning model development. This study involved both model fitting (setting the coefficient values) and model selection (setting the model structure). To perform these tasks simultaneously, a regularization technique was employed. A linear model of the form \n\n$$\n\\hat{y}_{i}=\\hat{\\mathbf{w}}^{\\mathrm{T}}\\mathbf{x}_{i}\n$$ \n\nwas proposed, where $\\hat{y}_{i}$ is the predicted number of cycles for battery i, $\\mathbf{X}_{i}$ is a $\\boldsymbol{p}$ -dimensional feature vector for battery i and $\\hat{\\mathbf{w}}$ is a $p$ -dimensional model coefficient vector. When applying regularization techniques, a penalty term is added to the least-squares optimization formulation to avoid overfitting. Two regularization techniques, the lasso66 and the elastic net58, simultaneously perform model fitting and selection by finding sparse coefficient vectors. The formulation is \n\n$$\n\\begin{array}{r}{\\hat{\\mathbf{w}}=\\operatorname*{argmin}_{\\mathbf{w}}\\left\\|\\mathbf{y}-\\mathbf{X}\\mathbf{w}\\right\\|_{2}^{2}+\\lambda P(\\mathbf{w})}\\end{array}\n$$ \n\nwhere the argmin function represents finding the value of w that minimizes the argument, $\\mathbf{y}$ is the $n$ -dimensional vector of observed battery lifetimes, $\\mathbf{X}$ is the $n\\times p$ matrix of features, and $\\lambda$ is a non-negative scalar. The first term \n\n$$\n\\begin{array}{r}{\\left\\|\\mathbf{y}-\\mathbf{Xw}\\right\\|_{2}^{2}}\\end{array}\n$$ \n\nis found in ordinary least squares. The formulation of the second term, $P(\\mathbf{w})$ , depends on the regularization technique being employed. For the lasso, \n\n$$\nP\\left(\\mathbf{w}\\right)=\\left\\|\\mathbf{w}\\right\\|_{1},\n$$ \n\nand for the elastic net, \n\n$$\nP\\left(\\mathbf{w}\\right)=\\frac{1-\\alpha}{2}\\ \\left\\|\\mathbf{w}\\right\\|_{2}^{2}+\\alpha\\ \\left\\|\\mathbf{w}\\right\\|_{1}\n$$ \n\nwhere $\\alpha$ is a scalar between 0 and 1. Both formulations will result in sparse models. The elastic net has been shown to perform better when $p\\gg n^{58}$ , as is often the case in feature engineering applications, but requires fitting an additional hyperparameter ( $\\mathbf{\\chi}_{(\\alpha}$ and $\\lambda$ , as opposed to only λ in the lasso). The elastic net is also preferred when there are high correlations between the features, as is the case in this application. To choose the values of the hyperparameters, we apply four-fold cross-validation and Monte Carlo sampling. \n\nThe model development dataset is divided into two equal sections, referred to as the training and primary testing sets. These two sections are chosen such that each spans the range of cycle lives (see Supplementary Table 9). The training data are used to choose the hyper-parameters $\\alpha$ and $\\lambda$ and determine the values of the coefficients, w. The training data are further subdivided into calibration and validation sets for cross-validation. The primary test set is then used as a measure of generalizability. The secondary test dataset was generated after model development. \n\nRMSE and average percentage error are chosen to evaluate model performance. RMSE is defined as \n\n$$\n\\mathrm{RMSE}=\\sqrt{\\frac{1}{n}\\sum_{i=1}^{n}\\left(y_{i}-\\hat{y}_{i}\\right)^{2}}\n$$ \n\nwhere $\\boldsymbol{y}_{i}$ is the observed cycle life, $\\hat{y}_{i}$ is the predicted cycle life and $n$ is the total number of samples. The average percentage error is defined as \n\n$$\n\\%\\ \\mathrm{err}=\\frac{1}{n}\\sum_{i=1}^{n}\\frac{|y_{i}-\\hat{y}_{i}|}{y_{i}}\\times100\\\n$$ \n\nwhere all variables are defined as above. \n\nTo summarize our procedure, we first divide the data into training and test sets. We then train the model on the training set using the elastic net, yielding a linear model with downselected features and coefficients. Finally, we apply the model to the primary and secondary test sets. \n\nThe data processing and elastic net prediction is performed in MATLAB, while the classification is performed in Python using the NumPy, pandas and sklearn packages. \n\n# Data availability \n\nThe datasets used in this study are available at https://data.matr.io/1. \n\n# Code availability \n\nCode for data processing is available at https://github.com/rdbraatz/data-drivenprediction-of-battery-cycle-life-before-capacity-degradation. Code for the modelling work is available from the corresponding authors upon request. \n\nReceived: 2 October 2018; Accepted: 18 February 2019; Published: xx xx xxxx \n\n# References \n\n1.\t Dunn, B., Kamath, H. & Tarascon, J.-M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n2.\t Nykvist, B. & Nilsson, M. Rapidly falling costs of battery packs for electric vehicles. Nat. Clim. Change 5, 329–332 (2015). \n3.\t Schmuch, R., Wagner, R., Hörpel, G., Placke, T. & Winter, M. Performance and cost of materials for lithium-based rechargeable automotive batteries. Nat. Energy 3, 267–278 (2018). \n4.\t Peterson, S. B., Apt, J. & Whitacre, J. F. Lithium-ion battery cell degradation resulting from realistic vehicle and vehicle-to-grid utilization. J. Power Source 195, 2385–2392 (2010). \n5.\t Ramadesigan, V. et al. Modeling and simulation of lithium-ion batteries from a systems engineering perspective. J. Electrochem. Soc. 159, R31–R45 (2012). \n6.\t Waag, W., Fleischer, C. & Sauer, D. U. Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles. J. Power Sources 258, 321–339 (2014). \n7.\t Paul, S., Diegelmann, C., Kabza, H. & Tillmetz, W. Analysis of ageing inhomogeneities in lithium-ion battery systems. J. Power Sources 239, 642–650 (2013). \n8.\t Schuster, S. F. et al. Nonlinear aging characteristics of lithium-ion cells under different operational conditions. J. Energy Storage 1, 44–53 (2015). \n9. Schuster, S. F., Brand, M. J., Berg, P., Gleissenberger, M. & Jossen, A. Lithium-ion cell-to-cell variation during battery electric vehicle operation. J. Power Sources 297, 242–251 (2015). \n10.\t Harris, S. J., Harris, D. J. & Li, C. Failure statistics for commercial lithium ion batteries: a study of 24 pouch cells. J. Power Sources 342, 589–597 (2017). \n11.\tBaumhöfer, T., Brühl, M., Rothgang, S. & Sauer, D. U. Production caused variation in capacity aging trend and correlation to initial cell performance. J. Power Sources 247, 332–338 (2014). \n12.\tBloom, I. et al. An accelerated calendar and cycle life study of Li-ion cells. J. Power Sources 101, 238–247 (2001). \n13.\tBroussely, M. et al. Aging mechanism in Li ion cells and calendar life predictions. J. Power Sources 97–98, 13–21 (2001). \n14.\tChristensen, J. & Newman, J. A mathematical model for the lithium-ion negative electrode solid electrolyte interphase. J. Electrochem. Soc. 151, A1977 (2004). \n15.\tPinson, M. B. & Bazant, M. Z. Theory of SEI formation in rechargeable batteries: capacity fade, accelerated aging and lifetime prediction. J. Electrochem. Soc. 160, A243–A250 (2012). \n16.\tArora, P. Mathematical modeling of the lithium deposition overcharge reaction in lithium-ion batteries using carbon-based negative electrodes. J. Electrochem. Soc. 146, 3543 (1999). \n17.\tYang, X.-G., Leng, Y., Zhang, G., Ge, S. & Wang, C.-Y. Modeling of lithium plating induced aging of lithium-ion batteries: transition from linear to nonlinear aging. J. Power Sources 360, 28–40 (2017). \n18.\tChristensen, J. & Newman, J. Cyclable lithium and capacity loss in Li-ion cells. J. Electrochem. Soc. 152, A818–A829 (2005). \n19.\tZhang, Q. & White, R. E. Capacity fade analysis of a lithium ion cell. J. Power Sources 179, 793–798 (2008). \n20.\tWright, R. B. et al. Power fade and capacity fade resulting from cycle-life testing of advanced technology development program lithium-ion batteries. J. Power Sources 119–121, 865–869 (2003). \n21.\tRamadesigan, V. et al. Parameter estimation and capacity fade analysis of lithium-ion batteries using reformulated models. J. Electrochem. Soc. 158, A1048–A1054 (2011). \n22.\tCordoba-Arenas, A., Onori, S., Guezennec, Y. & Rizzoni, G. Capacity and power fade cycle-life model for plug-in hybrid electric vehicle lithium-ion battery cells containing blended spinel and layered-oxide positive electrodes. J. Power Sources 278, 473–483 (2015). \n23.\t Burns, J. C. et al. Evaluation of effects of additives in wound Li-ion cells through high precision coulometry. J. Electrochem. Soc. 158, A255–A261 (2011) \n24.\tBurns, J. C. et al. Predicting and extending the lifetime of Li-ion batteries. J. Electrochem. Soc. 160, A1451–A1456 (2013). \n25.\tChen, C. H., Liu, J. & Amine, K. Symmetric cell approach and impedance spectroscopy of high power lithium-ion batteries. J. Power Sources 96, 321–328 (2001). \n26.\tTröltzsch, U., Kanoun, O. & Tränkler, H.-R. Characterizing aging effects of lithium-ion batteries by impedance spectroscopy. Electrochim. Acta 51, 1664–1672 (2006). \n27.\t Love, C. T., Virji, M. B. V., Rocheleau, R. E. & Swider-Lyons, K. E. State-of-health monitoring of 18650 4S packs with a single-point impedance diagnostic. J. Power Sources 266, 512–519 (2014). \n28.\tWaldmann, T. et al. A mechanical aging mechanism in lithium-ion batteries. J. Electrochem. Soc. 161, A1742–A1747 (2014). \n29.\tWaldmann, T. et al. Influence of cell design on temperatures and temperature gradients in lithium-ion cells: an in operando study. J. Electrochem. Soc. 162, A921–A927 (2015). \n30.\tBach, T. C. et al. Nonlinear aging of cylindrical lithium-ion cells linked to heterogeneous compression. J. Energy Storage 5, 212–223 (2016). \n31.\tHarris, S. J. & Lu, P. Effects of inhomogeneities—nanoscale to mesoscale—on the durability of Li-ion batteries. J. Phys. Chem. C 117, 6481–6492 (2013). \n32.\tLewerenz, M., Marongiu, A., Warnecke, A. & Sauer, D. U. Differential voltage analysis as a tool for analyzing inhomogeneous aging: a case study for LiFePO4|graphite cylindrical cells. J. Power Sources 368, 57–67 (2017). \n33.\tRaccuglia, P. et al. Machine-learning-assisted materials discovery using failed experiments. Nature 573, 73–77 (2016). \n34.\tWard, L., Agrawal, A., Choudhary, A. & Wolverton, C. A general-purpose machine learning framework for predicting properties of inorganic materials. NPJ Comput. Mater. 2, 16028 (2016). \n35.\tSegler, M. H. S., Preuss, M. & Waller, M. P. Planning chemical syntheses with deep neural networks and symbolic AI. Nature 555, 604–610 (2018). \n36.\tJain, A. et al. Commentary: The Materials Project: a materials genome approach to accelerating materials innovation. APL Mater. 1, 011002 (2013). \n37.\tAykol, M. et al. High-throughput computational design of cathode coatings for Li-ion batteries. Nat. Commun. 7, 13779 (2016). \n38.\tSendek, A. D. et al. Holistic computational structure screening of more than 12000 candidates for solid lithium-ion conductor materials. Energy Environ. Sci. 10, 306–320 (2017). \n39.\tUlissi, Z. W. et al. Machine-learning methods enable exhaustive searches for active bimetallic facets and reveal active site motifs for $\\mathrm{CO}_{2}$ reduction. ACS Catal. 7, 6600–6608 (2017). \n40.\t Si, X.-S., Wang, W., Hu, C.-H. & Zhou, D.-H. Remaining useful life estimation—a review on the statistical data driven approaches. Eur. J. Oper. Res. 213, 1–14 (2011). \n41.\tWu, L., Fu, X. & Guan, Y. Review of the remaining useful life prognostics of vehicle lithium-ion batteries using data-driven methodologies. Appl. Sci. 6, 166 (2016). \n42.\tSaha, B., Goebel, K. & Christophersen, J. Comparison of prognostic algorithms for estimating remaining useful life of batteries. Trans. Inst. Meas. Control 31, 293–308 (2009). \n43.\tNuhic, A., Terzimehic, T., Soczka-Guth, T., Buchholz, M. & Dietmayer, K. Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods. J. Power Sources 239, 680–688 (2013). \n44.\tHu, C., Jain, G., Tamirisa, P. & Gorka, T. Method for estimating the capacity and predicting remaining useful life of lithium-ion battery. Appl. Energy 126, 182–189 (2014). \n45.\t Miao, Q., Xie, L., Cui, H., Liang, W. & Pecht, M. Remaining useful life prediction of lithium-ion battery with unscented particle filter technique. Microelectron. Reliab. 53, 805–810 (2013). \n46.\tHu, X., . & Jiang, J. & Cao, D. & Egardt, B. Battery health prognosis for electric vehicles using sample entropy and sparse Bayesian predictive modeling. IEEE Trans. Ind. Electron. 63, 2645–2656 (2016). \n47.\tZhang, Y., . & Xiong, R. & He, H. & Pecht, M. Lithium-ion battery remaining useful life prediction with Box–Cox transformation and Monte Carlo simulation. IEEE Trans. Ind. Electron. 66, 1585–1597 (2019). \n48.\tZhang, Y., & Xiong, R. & He, H. & Pecht, M. Long short-term memory recurrent neural network for remaining useful life prediction of lithium-ion batteries. IEEE Trans. Veh. Technol. 67, 5695–5705 (2018). \n49.\tSaha, B. & Goebel, K. Battery data set. NASA Ames Progn. Data Repos. (2007). \n50.\tAnseán, D. et al. Fast charging technique for high power LiFePO4 batteries: a mechanistic analysis of aging. J. Power Sources 321, 201–209 (2016). \n51.\tAnseán, D. et al. Operando lithium plating quantification and early detection of a commercial $\\mathrm{LiFePO_{4}}$ cell cycles under dynamic driving schedule. J. Power Sources 356, 36–46 (2017). \n52.\tLiu, P. et al. Aging mechanisms of $\\mathrm{LiFePO_{4}}$ batteries deduced by electrochemical and structural analyses. J. Electrochem. Soc. 157, A499–A507 (2010). \n53.\tSafari, M. & Delacourt, C. Aging of a commercial graphite/LiFePO4 cell. J. Electrochem. Soc. 158, A1123–A1135 (2011). \n54.\tSarasketa-Zabala, E. et al. Understanding lithium inventory loss and sudden performance fade in cylindrical cells during cycling with deep-discharge steps. J. Phys. Chem. C 119, 896–906 (2015). \n55.\tAhmed, S. et al. Enabling fast charging—a battery technology gap assessment. J. Power Sources 367, 250–262 (2017). \n56.\tGyenes, B., Stevens, D. A., Chevrier, V. L. & Dahn, J. R. Understanding anomalous behavior in Coulombic efficiency measurements on Li-ion batteries. J. Electrochem. Soc. 162, A278–A283 (2015). \n57.\tLewerenz, M. et al. Systematic aging of commercial LiFePO4|graphite cylindrical cells including a theory explaining rise of capacity during aging. J. Power Sources 345, 254–263 (2017). \n58.\tZou, H. & Hastie, T. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67, 301–320 (2005). \n59.\tBloom, I. et al. Differential voltage analyses of high-power, lithium-ion cells: 1. Technique and application. J. Power Sources 139, 295–303 (2005). \n60.\tSmith, A. J., Burns, J. C. & Dahn, J. R. High-precision differential capacity analysis of $\\mathrm{LiMn}_{2}\\mathrm{O}_{4^{\\prime}}$ /graphite cells. Electrochem. Solid-State Lett. 14, A39–A41 (2011). \n61.\tDubarry, M., Truchot, C. & Liaw, B. Y. Synthesize battery degradation modes via a diagnostic and prognostic model. J. Power Sources 219, 204–216 (2012). \n62.\tBerecibar, M. et al. Online state of health estimation on NMC cells based on predictive analytics. J. Power Sources 320, 239–250 (2016). \n63.\tBerecibar, M., Garmendia, M., Gandiaga, I., Crego, J. & Villarreal, I. State of health estimation algorithm of LiFeP $)_{4}$ battery packs based on differential voltage curves for battery management system application. Energy 103, 784–796 (2016). \n64.\t Birkl, C. R., Roberts, M. R., McTurk, E., Bruce, P. G. & Howey, D. A. Degradation diagnostics for lithium ion cells. J. Power Sources 341, 373–386 (2017). \n65.\tRichardson, R. R., Birkl, C. R., Osborne, M. A. & Howey, D. A. Gaussian process regression for in-situ capacity estimation of lithium-ion batteries. IEEE Trans. Ind. Inform. 15, 127–138 (2019). \n66.\tTibshirani, R. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58, 267–288 (1996). \n\n# Author contributions \n\n# Acknowledgements \n\nP.M.A., N.J., N.P., M.H.C. and W.C.C. conceived of and conducted the experiments. K.A.S., Z.Y. and B.J. performed the modelling. M.A., Z.Y. and P.K.H. performed data management. P.M.A., K.A.S., N.J., B.J., D.F., M.Z.B., S.J.H., W.C.C. and R.D.B. interpreted the results. All authors edited and reviewed the manuscript. W.C.C. and R.D.B. supervised the work. \n\nThis work was supported by Toyota Research Institute through the Accelerated Materials Design and Discovery programme. P.M.A. was supported by the Thomas V. Jones Stanford Graduate Fellowship and the National Science Foundation Graduate Research Fellowship under Grant No. DGE-114747. N.P. was supported by SAIC Innovation Center through Stanford Energy 3.0 industry affiliates programme. S.J.H. was supported by the Assistant Secretary for Energy Efficiency, Vehicle Technologies Office of the US Department of Energy under the Advanced Battery Materials Research Program. We thank E. Reed, S. Ermon, Y. Li, C. Bauemer, A. Grover, T. Markov, D. Deng, A. Baclig and H. Thaman for discussions. \n\n# Competing interests \n\nK.A.S., R.D.B., W.C.C., P.M.A., N.J., S.J.H. and N.P. have filed a patent related to this work: US Application No. 62/575,565, dated 16 October 2018. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-019-0356-8. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to W.C.C. or R.D.B. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 " + }, + { + "id": "10.1038_s41586-019-1695-0", + "DOI": "10.1038/s41586-019-1695-0", + "DOI Link": "http://dx.doi.org/10.1038/s41586-019-1695-0", + "Relative Dir Path": "mds/10.1038_s41586-019-1695-0", + "Article Title": "Superconductors, orbital magnets and correlated states in magic-angle bilayer graphene", + "Authors": "Lu, XB; Stepanov, P; Yang, W; Xie, M; Aamir, MA; Das, I; Urgell, C; Watanabe, K; Taniguchi, T; Zhang, GY; Bachtold, A; MacDonald, AH; Efetov, DK", + "Source Title": "NATURE", + "Abstract": "Superconductivity can occur under conditions approaching broken-symmetry parent states(1). In bilayer graphene, the twisting of one layer with respect to the other at 'magic' twist angles of around 1 degree leads to the emergence of ultra-flat moire superlattice minibands. Such bands are a rich and highly tunable source of strong-correlation physics(2-5), notably superconductivity, which emerges close to interaction-induced insulating states(6,7). Here we report the fabrication of magic-angle twisted bilayer graphene devices with highly uniform twist angles. The reduction in twist-angle disorder reveals the presence of insulating states at all integer occupancies of the fourfold spin-valley degenerate flat conduction and valence bands-that is, at moire band filling factors nu = 0, +/- 1, +/- 2, +/- 3. At nu approximate to -2, superconductivity is observed below critical temperatures of up to 3 kelvin. We also observe three new superconducting domes at much lower temperatures, close to the nu = 0 and. = +/- 1 insulating states. Notably, at nu = +/- 1 we find states with non-zero Chern numbers. For nu = -1 the insulating state exhibits a sharp hysteretic resistance enhancement when a perpendicular magnetic field greater than 3.6 tesla is applied, which is consistent with a field-driven phase transition. Our study shows that broken-symmetry states, interaction-driven insulators, orbital magnets, states with non-zero Chern numbers and superconducting domes occur frequently across a wide range of moire flat band fillings, including close to charge neutrality. This study provides a more detailed view of the phenomenology of magic-angle twisted bilayer graphene, adding to our evolving understanding of its emergent properties.", + "Times Cited, WoS Core": 1191, + "Times Cited, All Databases": 1283, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000493807800038", + "Markdown": "# Article \n\n# Superconductors, orbital magnets and correlated states in magic-angle bilayer graphene \n\nhttps://doi.org/10.1038/s41586-019-1695-0 \n\nReceived: 15 March 2019 \n\nAccepted: 12 August 2019 \n\nPublished online: 30 October 2019 \n\nXiaobo Lu1, Petr Stepanov1, Wei Yang1, Ming Xie2, Mohammed Ali Aamir1, Ipsita Das1, Carles Urgell1, Kenji Watanabe3, Takashi Taniguchi3, Guangyu Zhang4, Adrian Bachtold1, Allan H. MacDonald2 & Dmitri K. Efetov1\\* \n\nSuperconductivity can occur under conditions approaching broken-symmetry parent states1. In bilayer graphene, the twisting of one layer with respect to the other at ‘magic’ twist angles of around 1 degree leads to the emergence of ultra-flat moiré superlattice minibands. Such bands are a rich and highly tunable source of strong-correlation physics2–5, notably superconductivity, which emerges close to interaction-induced insulating states6,7. Here we report the fabrication of magic-angle twisted bilayer graphene devices with highly uniform twist angles. The reduction in twist-angle disorder reveals the presence of insulating states at all integer occupancies of the fourfold spin–valley degenerate flat conduction and valence bands—that is, at moiré band filling factors $\\nu{=}0,\\pm1,\\pm2,\\pm3.\\mathrm{At}\\nu{\\approx}{-2}$ superconductivity is observed below critical temperatures of up to 3 kelvin. We also observe three new superconducting domes at much lower temperatures, close to the $\\scriptstyle\\nu=0$ and $\\scriptstyle\\nu=$ ±1 insulating states. Notably, at $\\scriptstyle\\nu=\\pm1$ we find states with non-zero Chern numbers. For $\\scriptstyle\\nu=$ −1 the insulating state exhibits a sharp hysteretic resistance enhancement when a perpendicular magnetic field greater than 3.6 tesla is applied, which is consistent with a field-driven phase transition. Our study shows that broken-symmetry states, interaction-driven insulators, orbital magnets, states with non-zero Chern numbers and superconducting domes occur frequently across a wide range of moiré flat band fillings, including close to charge neutrality. This study provides a more detailed view of the phenomenology of magic-angle twisted bilayer graphene, adding to our evolving understanding of its emergent properties. \n\nInteractions dominate over single-particle physics in flat-band electronic systems, and can give rise to insulating states at partial band fillings3,4, superconductivity8 and magnetism9–14. Recently, correlated insulating phases and strongly coupled superconducting domes have been found in ultra-flat bands of magic-angle twisted bilayer graphene (MAG) close to half-filling $(\\nu=\\pm2)$ , establishing graphene as a platform for the investigation of strongly correlated two-dimensional electrons6,15–18. MAG has several advantages that should enable new insights into these systems: the correlations can be accurately controlled by varying the twist angle between the two graphene layers; techniques for the fabrication of ultra-clean graphene layers are well-established; and the electron density $(n_{0}=\\bar{A_{0}^{-1}}\\tilde{\\approx}10^{12}~\\mathrm{cm}^{-2}$ , where $A_{0}$ is the area of the moiré unit cell) that is required to fill a moiré superlattice band can be adequately supplied by electrical gates. \n\nHere we report the observation of correlated states at all integer fillings of $\\nu=n/n_{0}$ (where $n$ is the gate-modulated carrier density), including at charge neutrality, and the occurrence of new superconducting domes and orbital magnetic states in MAG. When interactions are neglected, the two low-energy moiré bands of MAG have fourfold spin–valley flavour degeneracies, which implies that the density measured from the carrier neutrality point (CNP) is $4n_{0}$ when the flat conduction band is full and $-4n_{0}$ when the valence band is empty2,19. Interactions can lift the flavour degeneracies and give rise to completely empty or full spin–valley polarized flat bands—with interaction-induced gaps at all integer values of ν—in place of the symmetry-protected Dirac points that connect the conduction and valence bands for each flavour10. The many-body physics of these bands is highly sensitive to the twist angle $\\theta$ and the interaction strength $\\varepsilon^{-1}$ (where $\\varepsilon$ is the effective dielectric constant in MAG). In some cases— depending on the details of the electronic structure—bands can have non-zero Chern numbers9,10,20–23, allowing for the possibility of orbital magnetism and anomalous Hall effects. \n\n![](images/817a003b1bc910dc9af9604d97de7b1f939c88b511d8c9522c0260a065695898.jpg) \nFig. 1 | Integer-filling correlated states and new superconducting domes. a, Schematic of a typical MAG device. b, Atomic force microscopy image and schematic of how various measurements are obtained. Scale bar, $2\\upmu\\mathrm{m}$ . c, Four-terminal longitudinal resistance plotted against carrier density at different perpendicular magnetic fields from 0 T (black trace) to $480\\mathrm{mT}$ (red trace). d, Colour plot of longitudinal resistance against carrier density and temperature, showing different phases including metal, band insulator (BI), correlated state (CS) and superconducting state (SC). The boundaries of the superconducting domes—indicated by yellow lines—are defined by $50\\%$ resistance values relative to the normal state. Note that the transition from the metal to the superconducting state is not sharp at some carrier densities, which adds uncertainty to the value of $T_{\\mathrm{c}}$ extracted. e, Longitudinal resistance at optimal doping of the superconducting domes as a function of temperature. The resistance is normalized to its value at 8 K. Note that data points for \n$\\pmb{n=-7.5\\times10^{11}}\\pmb{\\mathrm{cm}}^{-2}$ are overlaid by the data points for $\\scriptstyle n=5\\times10^{11}\\mathsf{c m}^{-2}$ , as both curves follow a very similar line. f, Conductance $G_{x x}$ plotted against inverse temperature at carrier densities corresponding to $\\nu{=}0,1,\\pm2$ and 3. The straight lines are fits to $G_{x x}\\propto\\exp(-\\Delta/2k T)$ (where Δ is the size of the correlation-induced gap and $k$ is the Boltzmann constant), for temperature-activated behaviour, and give gap values of $\\cdot0.35\\mathrm{meV}(\\nu=-2),0.14\\mathrm{meV}(\\nu=1),0.37\\mathrm{meV}(\\nu=2),0.27\\mathrm{meV}$ $(\\nu=3)$ and $0.86\\mathrm{meV}(\\nu=0;\\mathrm{CNP}).$ g, Mean-field phase diagram for neutral $\\scriptstyle\\nu=0$ (CNP) twisted bilayer graphene, as a function of twist angle and interaction strength, showing different configurations of $C_{2}T$ symmetry and Chern number (C). Red and blue regions with solid outlines indicate states that do not break symmetry, and therefore have bands with no Berry curvature and vanishing Chern number. Blue indicates a gapped state and red indicates a gapless state. Zones filled with other colours indicate gapped states that break $C_{2}T$ symmetry and have bands with different Chern numbers, as shown. \n\nFigure 1a is a schematic of a typical graphite-gated, hexagonal boron nitride (hBN)-encapsulated MAG heterostructure device. The atomic force microscopy image in Fig. 1b shows the high structural homogeneity of the device. Figure 1c shows four-terminal resistance $R_{x x}$ as a function of $n$ at different out-of-plane magnetic fields $B_{\\perp}$ , measured at a temperature T of 16 mK. We find strong resistance peaks at $n=4n_{0}$ $\\approx\\pm3\\times10^{12}\\mathrm{cm}^{-2}$ that mark the edges of the flat bands, consistent with previous studies3,6,18. The full-band density corresponds to an average twist angle across the device of about $1.10^{\\circ}$ . By comparing $2n_{0}$ values extracted from two-terminal measurements between different contact pairs (Extended Data Fig. 4), we estimate that the variation in twist angle $(\\Delta\\theta)$ is only around $0.02^{\\circ}$ over a span of about $10\\upmu\\mathrm{m}$ . Such homogeneity in the twist angle is, to our knowledge, unprecedented in a MAG device. \n\nIn addition to the resistance peaks at the CNP and at $\\nu=\\pm4$ , we also observe interaction-induced resistance peaks at all non-zero integer fillings of the moiré bands $(\\nu=\\pm1,\\pm2,\\pm3)$ , corresponding to 1, 2 and \n\n3 electrons $(+)$ or holes $(-)$ per moiré unit cell (Fig. 1c). Signatures of some of these resistive states have been observed previously3,6,18,24, but they are much more strongly developed here. From temperaturedependent transport behaviour over a range of 10 K (Fig. 1f), it is possible to extract the activated gap size of the correlated insulator states. We obtain values of $0.34\\mathrm{meV}(\\nu{=}\\ensuremath{-}2),0.37\\mathrm{meV}(\\nu{=}2)$ and $0.25\\mathrm{meV}(\\nu=3)$ . Evidence for thermally activated transport is much weaker for the $\\scriptstyle\\nu=1$ state $\\langle0.14\\mathrm{meV}\\rangle$ and is entirely absent for the $\\scriptstyle\\nu=-3$ and $\\scriptstyle\\nu=-1$ states, which might indicate that these are correlated semi-metallic states rather than insulating states25. \n\nOur device also shows clear temperature-activated transport behaviour below $33\\mathsf{K}$ at the CNP, with an extracted gap size of 0.86 meV. Gaps at the CNP do not require broken flavour symmetries, but they do require that at least one of the emergent $C_{3}$ and $C_{2}T$ symmetries—which prevent CNP bands from touching—be broken. These symmetries can be explicitly broken by crystallographic alignment of the MAG and hBN layers; however, careful inspection of the angle between these (see Supplementary Information) allows us to rule out this scenario. As we also do not observe any other signatures of hBN alignment, such as satellite resistance peaks9, we conclude that the gap at CNP probably originates as a result of interactions. \n\n![](images/bde5e436512e4c74ba50972ed6676b2d708d9b56bed4b33adf01d400b965ae5f.jpg) \nFig. 2 | The superconducting dome at fillings between $\\pmb{\\nu}\\mathbf{=}\\mathbf{0}$ and $\\pmb{\\nu}\\mathbf{=}\\mathbf{1}.$ . a, Differential resistance plotted against d.c. bias current at various temperatures from $60\\mathrm{{mK}}$ (black trace) to $160\\mathrm{mK}$ (red trace). The blue dashed line is a fit to the $V_{x x}{\\approx}I^{3}$ power law, and identifies a BKT transition at a temperature $(T_{\\mathrm{BKT}})$ of around $110\\mathsf{m K}$ . b, Longitudinal resistance plotted against temperature at various out-of-plane magnetic fields, showing that normal levels of resistance are restored at magnetic fields greater than $300\\mathrm{mT}$ . c, Twodimensional colour plot of the differential resistance as a function of magnetic field and excitation current at $16\\mathrm{mK}$ . The orange traces show differential resistance plotted against current at magnetic field values of $225\\ensuremath{\\mathrm{mT}},150\\ensuremath{\\mathrm{mT}}$ , $75\\mathsf{m T}$ and 0 T (top to bottom). d, Values of the critical magnetic field at various temperatures. The straight line is a fit to the Ginzburg–Landau expression. For all measurements in a–d, the carrier density was fixed at optimal doping of the dome $n=5\\times10^{11}\\mathrm{cm}^{-2}$ . \n\nThe existence of a non-trivial gap at the CNP has strong implications for the properties of other gapped MAG states. Mean-field theory (Fig. 1g, Supplementary Information), predicts gapped states at neutrality over a wide range of twist angles and interaction strengths. Gapped states at non-zero integer values of ν are expected only when the moiré superlattice band width is smaller than the exchange shift produced by band occupation, and this occurs only near the magic angle. Overall our calculations demonstrate that insulating—or for weak interactions, semi-metallic states—are common at all integer values of ν, as observed experimentally. This mean-field phase diagram does not allow for broken translational symmetry, which appears not to be required for our experiments. If broken translational symmetry did have a key role in establishing insulating states, they would be expected at moiré band fillings $\\scriptstyle\\nu=n+p/3$ where $p$ and $n$ are integers; this is not consistent with our experimental observations. \n\nNotably, in four distinct carrier-density intervals between integer filling factors, we observe sharp decreases in the resistance of the device with decreasing temperature (Fig. 1e), which can be restored by the application of a small perpendicular magnetic field $B_{\\perp}{<}500\\mathrm{mT}$ (Fig. 2b). Figure 1d shows a colour plot of resistance against temperature and carrier density, in which four dome-shaped pockets of low resistance flank the most resistive states. In three of these domes, the resistance decreases to zero (Fig. 1e, Extended Data Figs. 5, 7), which is consistent with superconductivity. In the fourth region (at $n=5\\times10^{11}\\mathrm{cm}^{-2})$ 1 the resistance remains slightly greater than zero, owing to insufficient cooling of electrons below $100\\mathrm{mK}$ in the cryostat7,18. \n\nIn the dome close to $-2n_{0}$ we observe a superconducting transition. Although this has been reported previously, the superconducting transition temperature $T_{\\mathrm{c}}$ (defined as half the normal-state resistance) of 3 K that we observe here is considerably higher than the previous value6 of around 1.7 K. The other superconducting domes, which to our knowledge are all observed here for the first time, have much lower $T_{\\mathrm{c}}$ values and much sharper transitions. We identify a superconducting dome between $n_{0}$ and $2n_{0}$ with $T_{\\mathrm{c}}{\\approx}650\\mathrm{mK}$ , and two domes between the CNP and $\\pm n_{0}$ with $T_{\\mathrm{c}}{\\approx}160\\:\\mathrm{mK}$ and $T_{\\mathrm{c}}{\\approx}140\\:\\mathrm{mK}$ , respectively. As can be seen in Fig. 1d and Extended Data Fig. 6, it is likely that additional superconducting domes are developing between other filling factors; however, these are not fully developed, and are presumably obscured by the inhomogeneity that remains in our improved samples. \n\nFigure 2 shows the signatures of the newly observed superconducting domes (exemplified by the state between CNP and $n_{0}^{\\mathrm{~~}}$ all other states are described in detail in Extended Data Fig. 7 and Extended Data Table 1). In Fig. 2a, the differential resistance $\\mathrm{d}V_{x x}/\\mathrm{d}I$ is plotted against the d.c. bias current I at various temperatures. At $60\\mathrm{mK}$ , the traces display the nonlinear resistance typical of two-dimensional superconductivity, with a sharp resistive transition for $I{>}I_{\\mathrm{c}}{\\approx}3$ nA (where $I_{\\mathrm{c}}$ is the critical supercurrent). The blue dashed line is a power-law fit to $\\mathrm{d}V_{x x}/\\mathrm{d}I\\approx I^{2}$ , consistent with two-dimensional superconductivity described by the Berezinskii–Kosterlitz–Thouless (BKT) theory, showing a transition temperature $T_{\\mathrm{BKT}}$ of around $110\\mathsf{m}\\mathsf{K}$ . \n\nThe temperature dependence of the resistance $R_{x x}$ at various magnetic fields is illustrated in Fig. 2b. The superconductivity signal is gradually weakened upon increasing the applied field, and $R_{x x}$ varies almost linearly with temperature above a critical field $B_{\\mathrm{c}}{\\approx}300\\mathrm{mT}$ . The suppression of superconductivity by the magnetic field is further exemplified by Fig. 2c, which shows a plot of the differential resistance as a function of the magnetic field and the excitation current I at $16\\mathrm{mK}$ . The critical supercurrent $I_{\\mathrm{c}}$ is reduced by application of a magnetic field, reaching zero when $B_{\\mathrm{c}}{>}300{\\mathrm{mT}}$ . From these measurements, we extract the temperature-dependent critical magnetic field $B_{\\mathrm{c}}$ (defined by $50\\%$ of the normal state $R_{x x}$ value). By fitting to the expression from Ginzburg– Landau theory, $B_{\\mathrm{c}}{=}[\\phi_{0}/(2\\uppi\\xi^{2})](1-T/T_{\\mathrm{c}})$ , we extract a coherence length $\\xi_{\\mathrm{GL}(T=0\\ K)}$ of around $32{\\mathsf{n m}}$ . Here $\\scriptstyle\\phi_{0}=h/(2e)$ is the superconducting flux quantum, $h$ is Planck’s constant and $e$ is the electron charge. \n\nWe have studied the response of the flat bands to an applied magnetic field at a temperature of $100\\mathrm{mK}$ . Figure 3a shows a colour map of the resistance as a function of carrier density and magnetic field, and the corresponding schematic highlights the trajectories of the resistance maxima. We find sets of Landau fans that originate from the CNP and from most of the resistive states with an integer filling factor. In previous studies, Landau levels were identified only on the high-carrier-density sides of insulating states3,18. Here, we also observe Landau levels dispersing to lower densities. The vanishing carrier densities near most integer filling factors—as evidenced by both Landau fans and weak field Hall resistivities (Extended Data Fig. 3)—suggest that the fourfold spin–valley band degeneracy of the non-interacting state is lifted over a large range of filling factors, resetting the carrier density per band. \n\nOur observations suggest that a rich variety of spin–valley brokensymmetry states occur as a function of carrier density and magnetic field. Landau levels that can be traced to the CNP exhibit fourfold degeneracy with a filling-factor sequence of $\\nu_{\\mathrm{{L}}}{=}\\pm4,\\pm8,\\pm12$ …, as well as spin– valley broken-symmetry states with $\\nu_{\\mathrm{{L}}}=\\pm2$ . The Landau levels that fan out from $v=2(-2)$ follow a sequence of $\\nu_{\\mathrm{{L}}}=2(-2),4(-4),6(-6),\\ldots$ at low magnetic field, indicating partially lifted degeneracy for either spin or valley. Quantum oscillations from $\\scriptstyle\\nu=-2$ exhibit a dominant degeneracy sequence of $\\cdot_{\\nu_{\\mathrm{L}}=-3,-5,-7,\\dots}$ at high magnetic field. Near $\\scriptstyle\\nu=-3$ , quantum oscillations exhibit fully lifted degeneracy of Landau levels with filling factors $\\nu_{\\mathrm{{L}}}=-1,-2,-3,-4,.$ …. The Landau fans that emerge from insulating \n\n# Article \n\n![](images/7b78d74092dfe49fc5f946f9529e31326850ba0ec4f0616ab58b8dc710c6cd6a.jpg) \nFig. 3 | Shubnikov–de Haas oscillations in the MAG flat bands. a, Top, colour map of longitudinal resistance plotted against carrier density and magnetic field. Bottom, the corresponding schematic that identifies visible Landau level fans with a dominant degeneracy. The Landau fan diagram diverging from the CNP $(\\nu=0)$ follows a fourfold degenerate sequence with $\\nu_{{\\scriptscriptstyle\\mathrm{L}}}=\\pm4,\\pm8,\\pm12,\\ldots$ , with symmetry-broken states at $\\nu_{\\mathrm{{L}}}=\\pm2$ . The fans from $\\scriptstyle\\nu=2(-2)$ follow a twofold degenerate $\\nu_{\\mathrm{{L}}}=-2(2),-4(4),-6(6),...$ sequence, with broken-symmetry states at \n$\\nu_{\\mathrm{{L}}}=-3$ , −5, −7,…. The $\\scriptstyle\\nu=-3$ fan follows a single degenerate $\\nu_{{\\scriptscriptstyle1}}=-1,-2,-3,-4,-...$ sequence. Emergent correlated phases at all integer moiré fillings, including the CNP $(\\nu=0)$ , are highlighted in dark red. Chern insulating states are highlighted in orange. b, Magnification of a around the $\\scriptstyle\\nu=-3$ state, showing signatures similar to a Hofstadter butterfly spectrum with criss-crossing Landau levels fanning out from $\\scriptstyle\\nu=-3$ and $v=-2$ filling states. \n\nstates all extrapolate to a carrier density that vanishes at integer moiré band filling factors. \n\nWe also find that the degeneracies of Landau levels originating from the CNP and $\\scriptstyle\\nu=-2$ change when crossing the $\\nu=-1$ and $\\scriptstyle\\nu=-3$ states, suggestive of first-order phase transitions that change band degeneracies. In particular, as is shown in Fig. 3b, Landau levels from the $\\scriptstyle\\nu=-2$ and $\\scriptstyle\\nu=-3$ states display a criss-crossing pattern—superficially similar to that of a Hofstadter butterfly, but distinct in that the Landau level indices that can be traced to the $\\scriptstyle\\nu=-3$ state are spaced by one filling, whereas those that can be traced to the $\\scriptstyle\\nu=-2$ state are spaced by two fillings. \n\nIt is noteworthy that neither of the $\\scriptstyle\\nu=\\pm1$ correlated states show clear formation of Landau levels. The positions of their resistance maxima do, however, exhibit clear dependencies on the magnetic field and the carrier density. At $\\scriptstyle\\nu=-1$ the resistance state has no slope $(\\mathrm{d}n/\\mathrm{d}B)$ at low field; however, above a critical field $B_{\\mathrm{T}}{\\approx}3.6\\mathrm{T}$ , we observe the sudden development of a slope that is consistent with a Chern number of 1. Furthermore, at $\\scriptstyle\\nu=1$ the position of the resistance peak shifts to lower carrier density, with a slope that is consistent with a Chern number of 2. The slope of $\\mathrm{d}n/\\mathrm{d}B$ in the absence of a Landau-level fan in the $\\nu{=}\\pm1$ correlated states is consistent with Chern insulating states from spin and valley symmetry breaking at odd values of $\\nu.$ As discussed earlier and as predicted by mean-field theory, valley-projected bands in insulating states can have non-zero Chern numbers that compete closely with states with zero Chern numbers. Although we cannot resolve quantized values in $R_{x y}$ nor zero resistance in $\\begin{array}{r}{R_{x x},}\\end{array}$ as expected for a Chern insulating state, we do not do so for the other Landau levels in Fig. 3a either. We therefore conclude that our devices are still too inhomogeneous to observe quantization over the entire device. \n\n![](images/236669cdbe70aff8e1120f8e70ac3d4b8813f4c197644f8821ca8ef3f1af71da.jpg) \nFig. 4 | Field-driven phase transition near the $\\pmb{\\nu}=$ −1 state. a, Longitudinal resistance plotted as a function of carrier density and out-of-plane magnetic field measured at $16\\mathrm{mK}$ . The orange traces show longitudinal resistance plotted against carrier density with the magnetic field (from top to bottom) fixed at 4 T, 3.8 T, 3.6 T and 3.4 T. b, Longitudinal resistance plotted against temperature at various magnetic fields. c, Longitudinal resistance plotted against magnetic field at various temperatures, with dashed and solid lines corresponding to \nincreasing and decreasing magnetic field, respectively. d, Dependence of the critical magnetic field (extracted from up sweeps) and the hysteresis value on temperature. Note that the transition above $800\\mathrm{mK}$ is not sharp, adding uncertainty to the extracted critical field values. In b–d, the carrier density is fixed at $-8.43\\times10^{11}\\mathrm{cm}^{2}$ . e, Dependence of the critical magnetic field and the hysteresis value on the carrier density at $100\\mathrm{mK}$ . \n\nExactly at the transition at which the slope of the $\\scriptstyle\\nu=$ −1 resistive state in Fig. 3a changes from $\\mathrm{d}n/\\mathrm{d}B=0$ to a dn/dB consistent with Chern number 1, we find a strong hysteretic increase of ${\\mathrm{\\dot{\\prime}}}R_{x x}$ and $R_{x y};$ this is indicative of a possible magnetic-field-induced first-order phase transition. Figure 4a displays a plot of $\\cdot_{R_{x x}}$ as a function of $n$ and $B_{\\perp}$ . Figure 4b displays the temperature-dependent resistance ${\\cal R}_{x x}(T)$ near $\\scriptstyle\\nu=-1$ (or $\\scriptstyle n=-8.43$ $\\times10^{11}\\mathsf{c m}^{-2})$ for a series of magnetic field values. Whereas at $B_{\\perp}=0$ T, ${\\cal R}_{x x}(T)$ shows a typical metal-superconductor phase transition, above $B_{\\perp}>3.6$ T and below $T<0.9\\mathsf{K},R_{x x}(T)$ has a sharp jump and an insulating temperature dependence. \n\nFigure 4c shows plots of $\\mathrm{~\\~}^{\\mathrm{~\\prime~}}R_{x x}$ against the magnetic field at $\\nu{=}{-}1$ for up and down sweeps of the magnetic field. Below $800\\mathrm{mK}$ , the curves show sharp jumps in resistance at associated critical transition fields $B_{\\mathrm{{\\scriptsize{T}}}},$ and demonstrate strong hysteretic behaviour that is dependent on the sweeping direction of the magnetic field; the width of the magnetic field of the hysteresis loop is denoted by $\\Delta B_{\\textup r}$ . The critical field $B_{\\mathrm{r}}$ is always higher for up sweeps than for down sweeps. \n\nBoth $B_{\\mathrm{r}}$ and $\\Delta B_{\\mathrm{T}}$ are highly temperature-dependent, with $B_{\\mathrm{r}}$ shifting to higher values and $\\Delta B_{\\mathrm{T}}$ becoming smaller as the temperature increases. At $T{>}800\\mathsf{m K}$ , the hysteresis almost disappears and the transition becomes broader. The temperature dependencies of $\\dot{\\boldsymbol{B}}_{\\mathrm{{I}}}$ and $\\Delta B_{\\textup I}$ were extracted and are shown in Fig. 4d. The phase transition and hysteresis occur over a narrow range of carrier densities from around $-8.3\\times10^{11}\\mathsf{c m}^{-2}$ to $-9\\times10^{11}\\mathsf{c m}^{-2}$ (Extended Data Fig. 8b, c) with $B_{\\mathrm{r}}$ and $\\Delta B_{\\textup I}$ at different carrier densities shown in Fig. 4e. Overall, we observe similar behaviour in Hall resistance measurements (Extended Data Fig. 8d). These observations indicate that the origin of the change in the slope $\\mathrm{d}n/\\mathrm{d}B$ of the resistance maximum is a first-order phase transition, and is probably due to a competition between correlated states with zero and non-zero Chern numbers at high magnetic fields26, suggesting the emergence of a fieldstabilized orbital magnetic state. \n\nNotably, we have observed superconducting domes close to charge neutrality. To our knowledge, these states represent the lowest carrier density $(n\\approx3\\times10^{11}\\mathrm{cm}^{-2}$ ; counting from CNP) at which superconductivity has been observed. The existence of superconducting domes across a wide range of moiré band fillings must have important implications for our understanding of their origin. Because the density of states diminishes close to the CNP, the appearance of superconductivity seems not to be simply related to a high density of states of the non-interacting bands. Superconductivity occurs adjacent to insulating states that seem—on the basis of Landau fan patterns—to break spin–valley degeneracy, and adjacent to insulating states that do not. Nevertheless, its consistent association with nearby correlated insulator states suggests an exotic pairing mechanism. Conversely, at this point our observation cannot rule out the possibility of conventional electron–phonon coupling superconductivity in metallic states with quasiparticles that evolve adiabatically from those of the non-interacting system and compete with a rich variety of distinct insulating states from which they are separated by first-order phase transition lines24,27,28. In this case, it is possible that the consistent high density of states over a broad range of filling factors helps to support superconductivity in the metallic state. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-019-1695-0. \n\n. Lee, P. A., Nagaosa, N. & Wen, X.-G. Doping a Mott insulator: physics of high-temperature superconductivity. Rev. Mod. Phys. 78, 17 (2006). \n2. Bistritzer, R. & MacDonald, A. H. Moire bands in twisted double-layer graphene. Proc. Natl Acad. Sci. USA 108, 12233–12237 (2011). \n3. Cao, Y. et al. Correlated insulator behaviour at half-filling in magic-angle graphene superlattices. Nature 556, 80–84 (2018). \n4. Chen, G. et al. Evidence of a gate-tunable Mott insulator in a trilayer graphene moiré superlattice. Nat. Phys. 15, 237–241 (2019). \n5. Tarnopolsky, G., Kruchkov, A. J. & Vishwanath, A. Origin of magic angles in twisted bilayer graphene. Phys. Rev. Lett. 122, 106405 (2019). \n6. Cao, Y. et al. Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43–50 (2018). \n7. Chen, G. et al. Signatures of gate-tunable superconductivity in trilayer graphene moiré superlattice. Nature 572, 215–219 (2019). \n8. Kopnin, N., Heikkilä, T. & Volovik, G. High-temperature surface superconductivity in topological flat-band systems. Phys. Rev. B 83, 220503 (2011). \n9. Sharpe, A. L. et al. Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene. Science 365, 605–608 (2018). \n10.\t Xie, M. & MacDonald, A. H. On the nature of the correlated insulator states in twisted bilayer graphene. Preprint at https://arxiv.org/abs/1812.04213 (2018). \n11. Ochi, M., Koshino, M. & Kuroki, K. Possible correlated insulating states in magic-angle twisted bilayer graphene under strongly competing interactions. Phys. Rev. B 98, 081102 (2018). \n12. Dodaro, J. F., Kivelson, S. A., Schattner, Y., Sun, X.-Q. & Wang, C. Phases of a phenomenological model of twisted bilayer graphene. Phys. Rev. B 98, 075154 (2018). \n13.\t Thomson, A., Chatterjee, S., Sachdev, S. & Scheurer, M. S. Triangular antiferromagnetism on the honeycomb lattice of twisted bilayer graphene. Phys. Rev. B 98, 075109 (2018). \n14.\t Nandkishore, R., Levitov, L. & Chubukov, A. Chiral superconductivity from repulsive interactions in doped graphene. Nat. Phys. 8, 158 (2012). \n15. Cao, Y. et al. Strange metal in magic-angle graphene with near Planckian dissipation. Preprint at https://arxiv.org/abs/1901.03710 (2019). \n16. Po, H. C., Zou, L., Senthil, T. & Vishwanath, A. Faithful tight-binding models and fragile topology of magic-angle bilayer graphene. Phys. Rev. B 99, 195455 (2019). \n17. Kim, K. et al. Tunable moiré bands and strong correlations in small-twist-angle bilayer graphene. Proc. Natl Acad. Sci. USA 114, 3364–3369 (2017). \n18. Yankowitz, M. et al. Tuning superconductivity in twisted bilayer graphene. Science 363, 1059–1064 (2019). \n19. Cao, Y. et al. Superlattice-induced insulating states and valley-protected orbits in twisted bilayer graphene. Phys. Rev. Lett. 117, 116804 (2016). \n20.\t Lian, B., Xie, F. & Bernevig, B. A. The Landau level of fragile topology. Preprint at https:// arxiv.org/abs/1811.11786 (2018). \n21. Song, Z. et al. All magic angles in twisted bilayer graphene are topological. Phys. Rev. Lett. 123, 036401 (2019). \n22.\t Bultinck, N., Chatterjee, S. & Zaletel, M. P. Anomalous Hall ferromagnetism in twisted bilayer graphene. Preprint at https://arxiv.org/abs/1901.08110 (2019). \n23.\t Zhang, Y.-H., Mao, D. & Senthil, T. Twisted bilayer graphene aligned with hexagonal boron nitride: anomalous Hall effect and a lattice model. Preprint at https://arxiv.org/ abs/1901.08209 (2019). \n24.\t Polshyn, H. et al. Phonon scattering dominated electron transport in twisted bilayer graphene. Preprint at https://arxiv.org/abs/1902.00763 (2019). \n25. Kondo, T. et al. Quadratic Fermi node in a 3D strongly correlated semimetal. Nat. Commun. 6, 10042 (2015). \n26. Kagawa, F., Itou, T., Miyagawa, K. & Kanoda, K. Magnetic-field-induced Mott transition in a quasi-two-dimensional organic conductor. Phys. Rev. Lett. 93, 127001 (2004). \n27. Lian, B., Wang, Z. & Bernevig, B. A. Twisted bilayer graphene: a phonon driven superconductor. Phys. Rev. Lett. 122, 257002 (2019). \n28.\t Wu, F., Hwang, E. & Sarma, S. D. Phonon-induced giant linear-in-T resistivity in magic angle twisted bilayer graphene: ordinary strangeness and exotic superconductivity. Phys. Rev. B 99, 165112 (2019). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Article Methods \n\n# Device fabrication \n\nExtended Data Fig. 1 displays a step-by-step stacking process for the fabrication of twisted bilayer graphene (tBLG) with a graphite bottom gate. The hBN/tBLG/hBN/graphite stacks were exfoliated and assembled using a van der Waals assembly technique. Monolayer graphene, thin graphite and hBN flakes (around $_{10\\cdot\\mathsf{n m}}$ thick) were first exfoliated on $\\mathsf{S i O}_{2}$ (around $300\\mathsf{n m}$ )/Si substrate, followed by the ‘tear and stack’ technique29 with a polycarbonate (PC)/polydimethylsiloxane (PDMS) stamp to obtain the final hBN/tBLG/hBN/graphite stack. The separated graphene pieces were rotated manually by a twist angle of around $1.2{-}1.3^{\\circ}$ . We purposefully chose a larger twist angle during the assembly of the heterostructure owing to the high risk of relaxation of the twist angle to random lower values. To increase the structural homogeneity, we further carried out a mechanical cleaning process to squeeze the trapped blister out and release the local strain30 (Extended Data Fig. 2). To avoid the uncertainty induced by thermal expansion of the transfer stage, all the stacking process were carried out at a fixed temperature of $100^{\\circ}\\mathsf{C}$ , except that the final stacks were released at $180^{\\circ}\\mathrm{C}$ (the melting point of polycarbonate). We did not perform subsequent high-temperature annealing to avoid relaxation of the twist angle. We further patterned the stacks with PMMA resist and $\\mathrm{CHF}_{3}{+}\\mathbf{0}_{2}$ plasma and exposed the edges of graphene, which was subsequently contacted by $\\mathbf{Cr}/\\mathbf{Au}\\left(5/50\\mathbf{nm}\\right)$ metal leads using electron-beam evaporation (Cr) and thermal evaporation (Au). \n\n# Measurement \n\nTransport measurements were carried out in a dilution refrigerator with a base temperature of $16\\mathrm{mK}$ and a perpendicular magnetic field of up to 5 T. The dilution refrigerator was well filtered to avoid heating of the electrons in our devices. We use superconducting-type coaxial cables (around 2 m long; Lakeshore) from the room-temperature plate to the mixing chamber plate of the cryostat. We add on each line a pi filter (RS 239-191) at room temperature, and a powder filter (Leiden Cryogenics) as well as a two-stage resistor–capacitor filter on a printed circuit board $(R=1{\\sf k}\\Omega$ , $C{=}100\\mathsf{n F}$ ) at the mixing chamber plate. The total resistance of each line is about $2\\mathsf{k}\\Omega$ . The sample is located in a copper box with coaxial feedthroughs. \n\nStandard low-frequency lock-in techniques were used to measure the resistance $R_{x x}$ and $R_{x y}$ with an excitation current of about 1 nA at a frequency of 19.111 Hz. In the measurement of differential resistance dV/dI, an a.c. excitation current (around ${\\bf0.5\\eta n A})$ was applied through an a.c. signal (0.5 V) generated by the lock-in amplifier in combination with a 1/100 divider and a 10-MΩ resistor. Before combining with the excitation, the applied d.c. signal passed through a 1/100 divider and a 1-MΩ resistor. As-induced differential voltage was further measured at the same frequency of 19.111 Hz with standard lock-in technique. For measurements in strong magnetic fields we found that the increased contact resistance made it difficult to obtain accurate values of the device resistance. To resolve this issue, we applied a global gate voltage $(+20\\mathsf{V})$ through Si $/\\mathsf{S i O}_{2}$ (around ${300}\\mathsf{n m},\\mathsf{\\Gamma}$ to tune the charge carrier density separately in the device leads. \n\n# Twist angle extraction \n\nThe total carrier density n tuned by gate is calibrated by Hall measurements at low field (Extended Data Fig. 3). Near charge neutrality and band insulating states, Hall charge carrier density $(n_{\\mathrm{H}}{=}{-}B/(e}R_{x y}))$ should closely follow gate-induced carrier density $n$ ; that is, $\\mathrm{d}n_{\\mathrm{H}}/\\mathrm{d}n{=}1$ , providing accurate measurements of the carrier density $n$ . \n\nFor different integer (ν) moiré filling states, the total carrier density can be described by $\\nu n_{0}=\\nu A_{0}^{-1}=4\\nu(1-\\mathrm{cos}\\theta)/\\sqrt{3}a^{2},$ where $A_{0}$ is the unit cell area of the periodic moiré pattern, $\\theta$ is the twist angle and $a{=}0.246\\mathrm{nm}$ is the lattice constant of graphene. The local twist angles between different contacts are extracted with the carrier densities of $\\scriptstyle\\nu=2$ states shown in Extended Data Fig. 4. The carrier density difference between CNP and $\\nu=2$ states in device D1 ranges from $1.38\\times10^{12}{\\mathrm{cm}}^{-2}$ to $1.45\\times10^{12}\\mathrm{cm}^{-2}$ , corresponding to local twist angles ranging from $1.09^{\\circ}$ to $1.12^{\\circ}$ . For device D2, the local twist angles range from $1.08^{\\circ}\\mathrm{to}1.10^{\\circ}$ . \n\n# Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n29.\t Kim, K. et al. van der Waals heterostructures with high accuracy rotational alignment. Nano Lett. 16, 1989–1995 (2016). \n30.\t Purdie, D. G. et al. Cleaning interfaces in layered materials heterostructures. Nat. Commun. 9, 5387 (2018). \n\nAcknowledgements We are grateful for discussions with P. Jarillo-Herrero, A. Bernevig, M. Yankowitz, A. Young, C. Dean, L. Levitov, A. Vishwanath, M. Fisher, M. Allan and F. Koppens. D.K.E. acknowledges support from the Ministry of Economy and Competitiveness of Spain through the ‘Severo Ochoa’ program for Centres of Excellence in R&D (SE5-0522), Fundació Privada Cellex, Fundació Privada Mir-Puig, the Generalitat de Catalunya through the CERCA program, the H2020 Programme under grant agreement number 820378, Project: 2D·SIPC and the La Caixa Foundation. A.H.M. and M.X. acknowledge support from Department of Energy grant DE-FG02-02ER45958 and Welch Foundation grant TBF1473. A.B. acknowledges support from the Plan Nacional (RTI2018-097953-B-I00) of MICINN. G.Z. acknowledges support from the National Science Foundation of China under grant numbers 11834017 and 61888102, and the Strategic Priority Research Program of the Chinese Academy of Sciences under grant number XDB30000000. \n\nAuthor contributions D.K.E. and X.L. conceived and designed the experiments; X.L., W.Y. and P.S. performed the experiments; X.L. and D.K.E. analysed the data; M.X. and A.H.M. performed the theoretical modelling of the data; T.T. and K.W. contributed materials; D.K.E., A.B., M.A.A., I.D., C.U. and G.Z. supported the experiments; X.L., D.K.E., P.S., X.M. and A.H.M. wrote the paper. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41586-019- 1695-0. Correspondence and requests for materials should be addressed to D.K.E. Peer review information Nature thanks David Goldhaber-Gordon and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/fc7e5c7e6a44f33827257164c059b126dd5a589c470425377a5cdcf83ae73179.jpg) \nExtended Data Fig. 1 | Schematic of the stacking process for the fabrication of twisted bilayer graphene with graphite bottom gate. a–h, Sequential devic fabrication method, describing the tear-and-stack co-lamination process used to create the hBN/tBLG/hBN/graphite stacks. \n\n# Article \n\n![](images/31b844f4c67fe8ce99bd3925ce110c3b853c973990a22d1a7d514c67299150e8.jpg) \nExtended Data Fig. 2 | Mechanical cleaning of twisted bilayer graphene. a–d, Optical images of the final stacks before mechanical cleaning (a, c) and after mechanical cleaning (b, d). \n\n![](images/5a619e827871b7c7ffb164adadf0762d5cc915d46012b7b46185160987bfcd0b.jpg) \ntended Data Fig. 3 | Hall measurements of device D1. Coloured vertical bars neutrality, $n_{\\mathrm{H}}=n$ . Beyond the band insulator regions $(\\nu=\\pm4)$ , the Hall density rrespond to filling factors $\\scriptstyle\\nu=-4,-2,2$ and 4. Hall charge carrier density strictly follows $\\ensuremath{n_{\\mathrm{H}}}=\\ensuremath{n}\\pm4\\ensuremath{n_{0}}$ . $(n_{\\mathrm{H}}{=}{-}B/(e}R_{x y}))$ closely follows the gate-induced carrier density n. Near charge \n\n![](images/363c68479d0fd135f3729fbc58a727ea44a8683884ecd032f2fc79ab927bd34b.jpg) \nExtended Data Fig. 4 | Measuring the homogeneity of the twist angle. a–d, Atomic force microscopy images of a set of twisted bilayer graphene samples. Scale bar, $2\\upmu\\mathrm{m}$ . Dashed-line arrows correspond to the height profiles shown below the topographies. e, f, Two-terminal conductance measurements \ntaken between contacts shown in a and b. Colours correspond to the bars shown in a and b, respectively. The difference in carrier density between the CNP and the $\\scriptstyle\\nu=2$ state is used to extract the local twist angle. \n\n![](images/b8c3b5344dc3648ac60b06adc7225547144e2f3ce7b8c280e77da5d86163e1e5.jpg) \nExtended Data Fig. 5 | Four-terminal longitudinal resistance as a function of carrier density at different temperatures. The four-terminal longitudinal resistance is plotted against carrier density n for different temperatures, from \n\n69 K (black trace) to $16\\mathrm{mK}$ (red trace). Coloured vertical bars correspond to the filling factors ν as shown. \n\n![](images/3a07944eb2c983301038e998b18d6b2156c8e2156af30daf884c4de8e7a72e45.jpg) \nExtended Data Fig. 6 | Additional measurements of other possible superconducting domes. a–d, Differential resistance measurements for additional domes between $-4n_{0}$ and $-3n_{0}$ (a), $-2n_{0}$ and $-n_{0}(\\mathbf{b})2n_{0}$ and $3n_{0}$ (c) and \n$3n_{0}$ and $4n_{0}$ (d). $\\mathbf{e}\\mathbf{-}\\mathbf{h}$ , Corresponding thermal activation measurements of resistance against temperature for the same carrier densities as in a–d, respectively. \n\n![](images/ce01edfd1272838e5a50bfdfe4431ae77aa60611b9847cfd56839a0a9ba764f7.jpg) \nExtended Data Fig. 7 | Full characterization of all four superconducting pockets in sample D1. a–d, Thermal activation measurements of resistance against carrier density. The inset shows magnified images, demonstrating that in three superconducting states the resistance drops completely to zero (a, b, d) and in one superconducting state the resistance saturates at about $80\\Omega$ (c). \ne–h, Differential resistance is plotted against d.c. bias current at various temperatures in order to establish BKT transition temperatures. i–l, Two-dimensional colour plots of the differential resistance as a function of magnetic field and excitation current at 16 mK. \n\n![](images/f68d2db836c349961350fad0c6e911fe0696761e86102b89e232773ae7f4df99.jpg) \nExtended Data Fig. 8 | Additional magnetic hysteresis data. a, Four-terminal longitudinal resistance as a function of carrier density at different temperatures from $50\\mathrm{mK}$ (black trace) to 5.2 K (red trace). b, c, Plots of longitudinal resistance $R_{x x}$ and transverse resistance $R_{x y}$ against magnetic field at different charge carrier densities and $100\\mathrm{mK}$ . Arrows indicate the sweep direction of the \nmagnetic field. Data from b is used to extract data for Fig. 4e. d, Transverse resistance plotted against magnetic field at different temperatures (the same dataset as in Fig. 4c). Dashed and solid lines correspond to ascending and descending magnetic fields, respectively. \n\nExtended Data Table 1 | Full dataset for all observed superconducting states in device D1 \n\n\n
SC pocket densityTc (mK)TBKT (mK)Bc(T=0) (mT){GL(T=0) (nm)
-1.73 × 1012 cm-23000600~180~41
-7.6 × 1011 cm-214075~100~55
5 × 1011 cm-2160110~300~32
1.11 × 1012 cm-2650580~400~27
" + }, + { + "id": "10.1126_sciadv.aav0693", + "DOI": "10.1126/sciadv.aav0693", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.aav0693", + "Relative Dir Path": "mds/10.1126_sciadv.aav0693", + "Article Title": "New tolerance factor to predict the stability of perovskite oxides and halides", + "Authors": "Bartel, CJ; Sutton, C; Goldsmith, BR; Ouyang, RH; Musgrave, CB; Ghiringhelli, LM; Scheffler, M", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Predicting the stability of the perovskite structure remains a long-standing challenge for the discovery of new functional materials for many applications including photovoltaics and electrocatalysts. We developed an accurate, physically interpretable, and one-dimensional tolerance factor, 'r, that correctly predicts 92% of compounds as perovskite or nonperovskite for an experimental dataset of 576 ABX(3) materials (X = O2-, F-, Cl-, Br-, I-) using a novel data analytics approach based on SISSO (sure independence screening and sparsifying operator). tau is shown to generalize outside the training set for 1034 experimentally realized single and double perovskites (91% accuracy) and is applied to identify 23,314 new double perovskites (A(2)BB'X-6) ranked by their probability of being stable as perovskite. This work guides experimentalists and theorists toward which perovskites are most likely to be successfully synthesized and demonstrates an approach to descriptor identification that can be extended to arbitrary applications beyond perovskite stability predictions.", + "Times Cited, WoS Core": 1070, + "Times Cited, All Databases": 1158, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000460145700051", + "Markdown": "# M A T E R I A L S S C I E N C E \n\nChristopher J. Bartel1\\*, Christopher Sutton2, Bryan R. Goldsmith3, Runhai Ouyang2, Charles B. Musgrave1,4,5, Luca M. Ghiringhelli2\\*, Matthias Scheffler2 \n\n# New tolerance factor to predict the stability of perovskite oxides and halides \n\nCopyright $\\circledcirc$ 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). \n\nPredicting the stability of the perovskite structure remains a long-standing challenge for the discovery of new functional materials for many applications including photovoltaics and electrocatalysts. We developed an accurate, physically interpretable, and one-dimensional tolerance factor, $\\mathfrak{r},$ that correctly predicts $92\\%$ of compounds as perovskite or nonperovskite for an experimental dataset of 576 $A B X_{3}$ materials $(X=0^{2-}$ , $\\mathsf{F}^{-},$ Cl−, Br−, I−) using a novel data analytics approach based on SISSO (sure independence screening and sparsifying operator). $\\boldsymbol{\\uptau}$ is shown to generalize outside the training set for 1034 experimentally realized single and double perovskites $(91\\%$ accuracy) and is applied to identify 23,314 new double perovskites $(A_{2}B B^{\\prime}X_{6})$ ranked by their probability of being stable as perovskite. This work guides experimentalists and theorists toward which perovskites are most likely to be successfully synthesized and demonstrates an approach to descriptor identification that can be extended to arbitrary applications beyond perovskite stability predictions. \n\n# INTRODUCTION \n\nCrystal structure prediction from chemical composition continues as a persistent challenge to accelerated materials discovery $(1,2)$ . Most approaches capable of addressing this challenge require several computationally demanding electronic-structure calculations for each material composition, limiting their use to a small set of materials (3–6). Alternatively, descriptor-based approaches enable high-throughput screening applications because they provide rapid estimates of material properties (7, 8). Notably, the Goldschmidt tolerance factor, $t$ (9), has been used extensively to predict the stability of the perovskite structure based only on the chemical formula, $A B X_{3}$ , and the ionic radii, $r_{i},$ of each ion $(A,B,X)$ \n\nstudies, its accuracy is often insufficient (16). Considering $576A B X_{3}$ solids experimentally characterized at ambient conditions and reported in (17–19) (see Fig. 1C for the $A,B,$ and $X$ elements in this set), t correctly distinguishes between perovskite and nonperovskite for only $74\\%$ of materials and performs considerably worse for compounds containing heavier halides [chlorides ( $51\\%$ accuracy), bromides $(56\\%)$ , and iodides $(33\\%)]$ than for oxides $(83\\%)$ and fluorides $(83\\%)$ (Fig. 2A, fig. S1, and table S1). This deficiency in generalization to halide perovskites severely limits the applicability of $t$ for materials discovery. \n\nIn this work, we present a new tolerance factor $\\mathbf{\\eta}(\\uptau)$ , which has the form \n\n$$\nt={\\frac{r_{A}+r_{X}}{{\\sqrt{2}}(r_{B}+r_{X})}}\n$$ \n\n$$\n\\uptau={\\frac{r_{X}}{r_{B}}}-n_{A}\\left(n_{A}-{\\frac{r_{A}/r_{B}}{\\ln(r_{A}/r_{B})}}\\right)\n$$ \n\nThe perovskite crystal structure, as shown in Fig. 1A, is defined as any $A B X_{3}$ compound with a network of corner-sharing $B X_{6}$ octahedra surrounding a larger $A$ -site cation $(r_{A}>r_{B})$ , where the cations, $A$ and $B_{:}$ , can span the periodic table and the anion, $X,$ is typically a chalcogen or halogen. Distortions from the cubic structure can arise from size mismatch of the cations and anion, which results in additional perovskite structures and nonperovskite structures. The $B$ cation can also be replaced by two different ions, resulting in the double perovskite formula, $A_{2}B B^{\\prime}X_{6}$ (Fig. 1B). Single and double perovskite materials have exceptional properties for a variety of applications such as electrocatalysis (10), proton conduction $(l I)$ , ferroelectrics (12) (using oxides, $X=\\mathrm{O}^{2-}$ ), battery materials (13) (using fluorides, $X=\\operatorname{F}^{-\\cdot}$ ), as well as photovoltaics (14) and optoelectronics (15) (using the heavier halides, $X=\\mathrm{Cl}^{-},\\mathrm{Br}^{-},\\Gamma^{-})$ . \n\nThe first step in designing new perovskites for these applications is typically the assessment of stability using $t,$ which has informed the design of perovskites for over 90 years. However, as reported in recent where $n_{A}$ is the oxidation state of $\\dot{}A$ , $r_{i}$ is the ionic radius of ion $i,r_{A}>r_{B}$ by definition, and $\\tau<4.18$ indicates perovskite. A high overall accuracy of $92\\%$ for the experimental set $94\\%$ for a randomly chosen test set of 116 compounds) and nearly uniform performance across the five anions evaluated [oxides $92\\%$ accuracy), fluorides $(92\\%)$ , chlorides $(90\\%)$ , bromides $(93\\%)$ , and iodides $(91\\%)]$ is achieved with $\\boldsymbol{\\tau}$ (Fig. 2B, fig. S1, and table S1). Like $t,$ the prediction of perovskite stability using t requires only the chemical composition, allowing the tolerance factor to be agnostic to the many structures that are considered perovskite. In addition to predicting if a material is stable as perovskite, $\\boldsymbol{\\uptau}$ also provides a monotonic estimate of the probability that a material is stable in the perovskite structure. The accurate and probabilistic nature of $\\tau$ , as well as its generalizability over a broad range of single and double perovskites, allows new physical insights into the stability of the perovskite structure and the prediction of thousands of new double perovskite oxides and halides, 23,314 of which are provided here and ranked by their probability of being stable in the perovskite structure. \n\n# RESULTS AND DISCUSSION \n\n# Finding an improved tolerance factor to predict perovskite stability \n\nOne key aspect of the performance of $t$ is how well the sum of ionic radii estimates the interatomic bond distances for a given structure. \n\n![](images/bb1301b3c4c5b0d6d169bd7a842edc89c5d503b3d6d3668b8f582f8803a55d96.jpg) \nFig. 1. Perovskite structure and composition. (A) $A B X_{3},$ in the cubic single perovskite structure $(P m\\bar{3}m)$ , where the A cation is surrounded by a network of cornersharing $B X_{6}$ octahedra. (B) $A_{2}B B^{\\prime}X_{6},$ in the rock salt double perovskite structure $(F m\\bar{3}m)$ , where the A cations are surrounded by an alternating network of $B X_{6}$ and $B^{\\prime}X_{6}$ octahedra. In this structure, inverting the $B$ and $B^{\\prime}$ cations results in an equivalent structure. While the ideal cubic structures are shown here, perovskites may also adopt various noncubic structures. (C) Map of the elements that occupy the A, B, and/or $\\boldsymbol{\\chi}$ sites within the 576 compounds experimentally characterized as perovskite or nonperovskite at ambient conditions and reported in (17–19). \n\n![](images/8e7f5844e532dc805d05642dbb589ba4f7a428194081c997244283317ff96457.jpg) \nFig. 2. Assessing the performance of the improved tolerance factor, $\\tau.$ . (A) A decision tree classifier determines that the optimal bounds for perovskite formability using the Goldschmidt tolerance factor $(t)$ are $0.82513$ are correctly labeled as nonperovskite and are not shown to highlight the decision boundary. The outlying compounds at $\\tau>10$ that are labeled perovskite yet have large t are ${\\mathsf{P u V O}}_{3},$ $\\mathsf{A m V O}_{3},$ and ${\\mathsf{P u C r O}}_{3},$ , which may indicate poorly defined radii or incorrect experimental characterization. (C) Comparison of Platt-scaled classification probabilities, $P(\\tau)$ , versus t. ${\\mathsf{L a A l O}}_{3}$ and NaBeC $\\mid_{3}$ are labeled to highlight the variation in $P(\\tau)$ at nearly constant t. (D) Comparison between $P(\\tau)$ and the decomposition enthalpy $(\\Delta H_{\\mathrm{d}})$ for 36 double perovskite halides calculated using density functional theory (DFT) in the $F m\\bar{3}m$ structure in (32) and 37 single and double perovskite chalcogenides and halides in thePm\u00013mstructure in (33). The legend corresponds with the anion, X. Positive decomposition enthalpy $(\\Delta H_{\\mathrm{d}}>0)$ indicates that the structure is stable with respect to decomposition into competing compounds. The green and white shaded regions correspond with agreement and disagreement between the calculated $\\Delta H_{\\mathrm{d}}$ and the classification by t. Points of disagreement are outlined in red. $\\mathsf{C a Z r O}_{3}$ and ${\\mathsf{C a H f O}}_{3}$ are labeled because they are known to be stable in the perovskite structure, although they are unstable in the cubic structure (34, 35). For this reason, the best-fit line for the chalcogenides $(X=0^{2-},5^{2-},5\\ensuremath{\\mathrm{e}}^{2-})$ excludes these two points. \n\nShannon’s revised effective ionic radii (20) based on a systematic empirical assessment of interatomic distances in nearly 1000 compounds are the typical choice for radii because they provide ionic radius as a function of ion, oxidation state, and coordination number for the majority of elements. Most efforts to improve $t$ have focused on refining the input radii (17, 19, 21, 22) or increasing the dimensionality of the descriptor through two-dimensional (2D) structure maps (18, 23, 24) or high-dimensional machine-learned models (25–27). \n\nHowever, all hitherto applied approaches for improving the Goldschmidt tolerance factor are only effective over a limited range of $A B X_{3}$ compositions. Despite its modest classification accuracy, t remains the primary descriptor used by experimentalists and theorists to predict the stability of perovskites. \n\nThe SISSO (sure independence screening and sparsifying operator) approach (28) was used to identify an improved tolerance factor for predicting whether a given compound is perovskite [determined by experimental realization of any structure with corner-sharing $B X_{6}$ octahedra (21) at ambient conditions] or nonperovskite [determined by experimental realization of any structure(s) without corner-sharing $B X_{6}$ octahedra, including, in some cases, failed synthesis of any $A B X_{3}$ compound]. Of the 576 experimentally characterized $A B X_{3}$ solids, $80\\%$ were used to train and $20\\%$ were used to test the SISSO-learned descriptor. Several alternative atomic properties were considered as candidate features, and among them, SISSO determined that the best performing descriptor, $\\boldsymbol{\\tau}$ (Eq. 2 and Fig. 2B), depends only on oxidation states and Shannon ionic radii (see Materials and Methods for an explanation of the approach used for descriptor identification and a discussion of alternative approaches). For the set of $576A B X_{3}$ compositions, t correctly labels $94\\%$ of the perovskites and $89\\%$ of the nonperovskites compared with 94 and $49\\%$ , respectively, using t. The primary advantage of $\\tau$ over $t$ is the remarkable reduction in compounds that are predicted to be perovskite but are not experimentally identified as stable perovskites, with false-positive rates for $\\boldsymbol{\\uptau}$ and $t$ of 11 and $51\\%$ , respectively. Full confusion matrices along with additional performance metrics for $\\boldsymbol{\\uptau}$ and $t$ are provided in table S2. The large decrease in false-positive rate (from $51\\%$ to $11\\%$ ) while substantially increasing the overall classification accuracy (from $74\\%$ to $92\\%$ ) demonstrates that t improves significantly upon $t$ as a reliable tool to guide experimentalists toward which compounds can be synthesized in perovskite structures. \n\nBeyond the improved accuracy, a crucial advantage of $\\tau$ is the monotonic (continuous) dependence of perovskite stability on $\\boldsymbol{\\tau}$ . As $\\boldsymbol{\\uptau}$ decreases, the $\\boldsymbol{\\tau}$ -based probability of being perovskite, $P(\\tau)$ , increases, where perovskites are expected for an empirically determined range of $\\tau<4.18$ (Fig. 2B; Materials and Methods for details). Probabilities are obtained using Platt’s scaling (29), where the binary classification of perovskite/nonperovskite is transformed into a continuous probability estimate of perovskite stability, $P(\\tau)$ , by training a logistic regression model on the $\\tau$ -derived binary classification. Probabilities cannot similarly be obtained with $t$ because the stability of the perovskite structure does not increase or decrease monotonically with $t,$ where $0.825500,000$ double perovskite formulas, $A_{2}B B^{\\prime}X_{6},$ can be constructed. Comparison with the Inorganic Crystal Structure Database (ICSD) (30, 41) reveals only 918 compounds $(<0.2\\%)$ with known crystal structures, 868 of which are perovskite. \n\nAlthough $\\boldsymbol{\\tau}$ was only trained on $A B X_{3}$ compounds, it is readily adaptable to double perovskites because it depends only on composition and not structure. To extend $\\boldsymbol{\\uptau}$ to $A_{2}B B^{\\prime}X_{6}$ formulas, $r_{B}$ is approximated as the arithmetic mean of the two $B$ -site radii $(r_{B},r_{B^{\\prime}})$ . t correctly classifies $91\\%$ of these 918 $A_{2}B B^{\\prime}X_{6}$ compounds in the ICSD (compared with $92\\%$ on $576A B X_{3}$ compounds), recovering 806 of 868 known double perovskites (table S4). The geometric mean has also been used to approximate the radius of a site with two ions (42). We find that this has little effect on classification with $\\tau,$ as $91\\%$ of the 918 $A_{2}B B^{\\prime}X_{6}$ compounds are also correctly classified using the geometric mean for $r_{B},$ and the classification label differs for only 14 of 918 compounds using the arithmetic or geometric mean. Although t was identified using 460 $A B X_{3}$ compounds, the agreement with experiment on these compounds $(92\\%)$ is comparable to that on the 1034 compounds $(91\\%)$ that span $A B X_{3}$ (116 compounds) and $A_{2}B B^{\\prime}X_{6}$ (918 compounds) formulas and was completely excluded from the development of t (i.e., test set compounds). This result indicates pronounced generalizability to predicting experimental realization for single and double perovskites that are yet to be discovered. With $\\boldsymbol{\\tau}$ thoroughly validated as being predictive of experimental stability, the space of yet-undiscovered double perovskites was explored to identify 23,314 charge-balanced double perovskites that t predicts to be stable at ambient conditions (of $>500,000$ candidates). These compounds are provided in table S4 including assigned oxidation states and radii along with $t$ and $\\tau,$ predictions made using each tolerance factor, and classification in the ICSD where available. There are thousands of additional compounds with substitutions on the $A$ and/or $X$ sites, $A A^{\\prime}B B^{\\prime}(X X^{\\prime})_{3}$ , that are expected to be similarly rich in yetundiscovered perovskite compounds. \n\nTwo particularly attractive classes of materials within this set of $A_{2}B B^{\\prime}X_{6}$ compounds are double perovskites with $A=\\mathrm{C}s^{+}$ , $X=\\mathrm{Cl}^{-}$ and $A=\\mathrm{La}^{3+}$ , $X=\\bar{\\mathrm{O}}^{2-}$ , which have garnered substantial interest in a number of applications including photovoltaics, electrocatalysis, and ferroelectricity. The ICSD contains 45 compounds (42 perovskites) with the formula $\\mathrm{Cs}B B^{\\prime}\\mathrm{Cl}_{6},$ 43 of which are correctly classified as perovskite or nonperovskite by $\\uptau.$ . From the high-throughput analysis using $\\mathfrak{r},$ we predict an additional 420 perovskites to be stable with 164 having at least the probability of perovskite formation as the recently synthesized perovskite, ${\\mathrm{Cs}}_{2}{\\mathrm{AgBiCl}}_{6}$ $[P(\\tau)=69.6\\%]$ (43). A map of perovskite probabilities for charge-balanced $\\mathrm{Cs}_{2}B B^{\\prime}\\mathrm{Cl}_{6}$ compounds is shown in Fig. 3 (lower triangle). Within this set of 164 probable perovskites, there is an opportunity to synthesize double perovskite chlorides that contain $3d$ transition metals substituted on one or both $B$ sites, as 83 new compounds of this type are predicted to be stable as perovskite with high probability. \n\nWhile double perovskite oxides have been explored extensively for a number of applications, the small radius and favorable charge of $\\mathrm{O}^{2-}$ yields a massive design space for the discovery of new compounds. For $\\mathrm{La}_{2}B B^{\\prime}\\mathrm{O}_{6},$ ${\\sim}63\\%$ of candidate compositions are found to be charge-balanced compared with only ${\\sim}24\\%$ of candidate $\\mathrm{Cs}_{2}B B^{\\prime}\\mathrm{Cl}_{6}$ compounds. The ICSD contains 8 $\\mathrm{~5~La_{2}}B B^{\\prime}\\mathrm{O}_{6}$ compounds, all of which are predicted to be perovskite by $\\boldsymbol{\\uptau}$ in agreement with the experiment. We predict an additional 1128 perovskites to be discoverable in this space, with a remarkable 990 having $P(\\tau)\\geq85\\%$ (Fig. 3, upper triangle). All $128A B X_{3}$ compounds in the experimental set that meet this threshold are experimentally realized as perovskite, suggesting that there is ample opportunity for perovskite discovery in lanthanum oxides. \n\n# Compositional mapping of perovskite stability \n\nIn addition to enabling the rapid exploration of stoichiometric perovskite compositions, $\\boldsymbol{\\uptau}$ provides the probability of perovskite stability, $P(\\tau)$ , for an arbitrary combination of $n_{A},r_{A},r_{B},$ and $r_{X},$ which is shown in Fig. 4. For each grouping shown in Fig. 4, experimentally realized perovskites and nonperovskites are shown as single points to compare with the range of values in the predictions made from $\\boldsymbol{\\uptau}$ . Doping at various concentrations presents a nearly infinite number of $A_{I-x}A^{\\prime}{}_{x}B_{1-y}B^{\\prime}{}_{y}(X_{1-z}X^{\\prime}{}_{z})_{3}$ compositions that allows the tuning of technologically useful properties. $\\uptau$ suggests the size and concentration of dopants on the $A,B_{:}$ , or $X$ sites that likely lead to improved stability in the perovskite structure. Conversely, compounds that lie in the highprobability region are likely amenable to ionic substitutions that decrease the probability of forming a perovskite but may improve a desired property for another application. For example, $\\mathrm{LaCoO}_{3}$ , with $P(\\tau)=98.9\\%$ , should accommodate reasonable ionic substitutions (i.e., A sites of comparable size to La or $B$ sites of comparable size to $\\mathrm{Co}^{\\cdot}$ ) and was recently shown to have enhanced oxygen exchange capacity and nitric oxide oxidation kinetics with stable substitutions of $\\mathrm{sr}$ on the $A$ site (44). \n\n![](images/c838788cc09e4328e75e808b11766c79acac0824ebab8e0540a1233b1be498b6.jpg) \nFig. 3. Map of predicted double perovskite oxides and halides. Lower triangle: Probability of forming a stable perovskite with the formula $C s_{2}B B^{\\prime}C\\vert_{6}$ as predicted by t. Upper triangle: Probability of forming a stable perovskite with the formula $\\mathsf{L a}_{2}B B^{\\prime}\\mathsf{O}_{6}$ as predicted by $\\tau.$ White spaces indicate $B/B^{\\prime}$ combinations that do not result in charge-balanced compounds with $r_{A}>r_{B}$ . The colors indicate the Platt-scaled classification probabilities, $P(\\tau)$ , with higher $P(\\tau)$ indicating a higher probability of forming a stable perovskite. $B/B^{\\prime}$ sites are restricted to ions that are labeled as $B$ sites in the experimental set of 576 $A B X_{3}$ compounds. \nBSSTOZYRRAP \n\nThe probability maps in Fig. 4 arise from the functional form of $\\boldsymbol{\\tau}$ (Eq. 2) and provide insights into the stability of the perovskite structure as the size of each ion is varied. The perovskite structure requires that the $A$ and $B$ cations occupy distinct sites in the $A B X_{3}$ lattice, with $A$ 12-fold and $B6$ -fold coordinated by $X.$ . When $r_{A}$ and $r_{B}$ are too similar, nonperovskite lattices that have similarly coordinated $A$ and $B$ sites, such as cubic bixbyite, become preferred over the perovskite structure. On the basis of the construct of $\\tau,$ as $r_{A}/r_{B}\\rightarrow1,P(\\uptau)\\rightarrow0$ , which arises from the $+x/\\ln(x)$ $(x=r_{A}/r_{B})$ term, where $\\begin{array}{r}{\\operatorname*{lim}_{x\\to1}\\frac{x}{\\ln(x)}=+\\infty}\\end{array}$ and larger values of $\\boldsymbol{\\tau}$ lead to lower probabilities of forminð gÞ perovskites. When $r_{A}=r_{B},\\tau$ is undefined, yet compounds where $A$ and $B$ have identical radii are rare and not expected to adopt perovskite structures $\\stackrel{\\cdot}{t}{=}0.71$ ). \n\nThe octahedral term in $\\uptau\\left(r_{X}/r_{B}\\right)$ also manifests itself in the probability maps, particularly in the lower bound on $r_{B}$ where perovskites are expected as $r_{X}$ is varied. As $r_{X}$ increases, $r_{B}$ must similarly increase to enable the formation of stable $B X_{6}$ octahedra. This effect is noticeable when separately comparing compounds containing $\\mathrm{Cl^{-}}$ (left), $\\mathrm{Br}^{-}$ (center), and ${\\boldsymbol{\\mathrm{I}}}^{-}$ (right) (bottom row of Fig. 4), where the range of allowed cation radii decreases as the anion radius increases. For $r_{B}<0.414$ . Because the cation radii ratios strongly affect the probability of perovskite, as discussed in the context of $x/\\mathrm{ln}(x)$ , $r_{X}$ also has a noticeable indirect effect on the lower bound of $r_{A:}$ , which increases as $r_{X}$ increases. \n\nThe role of $n_{A}$ in $\\boldsymbol{\\tau}$ is more difficult to parse, but its placement dictates two effects on stability—as $A$ is more oxidized (increasing $n_{A}$ ), $-{n_{A}}^{2}$ increases the probability of forming the perovskite structure, but $n_{A}$ also magnifies the effect of the $x/\\mathrm{ln}(x)$ term, increasing the importance of the cation radii ratio. Notably, $n_{A}=1$ for most halides and some oxides (245 of the 576 compounds in our set), and in these cases, $\\uptau=$ $\\begin{array}{r}{\\frac{r_{X}}{r_{B}}+\\frac{r_{A}/r_{B}}{\\ln(r_{A}/r_{B})}-1}\\end{array}$ for all combinations of $\\cdot_{A,B,}$ and $X$ and $n_{A}$ plays no role as the composition is varied. \n\nThis analysis illustrates how data-driven approaches not only can be used to maximize the predictive accuracy of new descriptors but also can be leveraged to understand the actuating mechanisms of a target property—in this case, perovskite stability. This attribute distinguishes $\\boldsymbol{\\uptau}$ from other descriptors for perovskite stability that have emerged in recent years. For instance, three recent works have shown that the experimental formability of perovskite oxides and halides can be separately predicted with high accuracy using kernel support vector machines (26), gradient boosted decision trees (25), or a random forest of decision trees (27). While these approaches can yield highly accurate models, the resulting descriptors are not documented analytically, and therefore, the mechanism by which they make the perovskite/nonperovskite classification is opaque. \n\n![](images/6bb0c27ef8688e3bf1e1e955f1f044cf9b8c434e24df03bcef0937ac175fe966.jpg) \nFig. 4. The effects of ionic radii and oxidation states on the stability of single and double perovskite oxides and halides. Top row: $\\ X=0^{2-}$ (left to right: ${n_{A}}=3^{+},2^{+},1^{+})$ . Bottom row: ${\\cal n}_{A}=1^{+}$ (left to right: $\\b{X}=\\b{\\mathrm{Cl}}^{-}$ , $\\mathsf{B r}^{-}$ , I−). The experimentally realized perovskites $\\mathsf{L a G a O}_{3},$ ${\\mathsf{S r}}_{2}{\\mathsf{F e M o O}}_{6},$ $\\mathsf{A g N b O}_{3},$ ${\\mathsf{C s}}_{2}{\\mathsf{A g l n C l}}_{6},$ $(M\\mathsf{A})_{2}\\mathsf{A g B i B r}_{6},$ and $M A P b\\mathsf{I}_{3}$ are shown as open circles in the corresponding plot, which are all predicted to be stable by $\\boldsymbol{\\tau}$ . The experimentally realized nonperovskites $\\mathsf{I n G a O}_{3},$ ${\\mathsf{C o M n O}}_{3},$ $\\mathsf{L i B i O}_{3},$ $\\mathsf{L i M g C l}_{3},\\mathsf{C s N i B r}_{3},$ and ${\\mathsf{R b}}{\\mathsf{P b}}|_{3}$ are shown as open triangles and predicted to be unstable in the perovskite structure by $\\tau.$ The organic molecule, methylammonium (MA), is shown in the last two panels. While $(M A)_{2}{\\mathsf{A g B i B r}}_{6}$ and $M A P b\\mathsf{I}_{3}$ are correctly classified with $\\tau,$ only inorganic cations were used for descriptor identification; therefore, $r_{A}=1.88\\mathring{\\mathsf{A}}({\\mathsf{C}}s^{+})$ is the largest cation considered. The gray region where $r_{B}>r_{A}$ is not classified because, when this occurs, A becomes B and vice versa based on our selection rule $r_{A}>r_{B}$ . \n\n# CONCLUSIONS \n\nWe report a new tolerance factor, $\\tau,$ that enables the prediction of experimentally observed perovskite stability significantly better than the widely used Goldschmidt tolerance factor, $t,$ and the 2D structure map using $t$ and the octahedral factor, $\\upmu$ . For $576A B X_{3}$ and 918 $A_{2}B B^{\\prime}X_{6}$ compounds, the prediction by $\\boldsymbol{\\uptau}$ agrees with the experimentally observed stability for $590\\%$ of compounds, with $>1000$ of these compounds reserved for testing generalizability (prediction accuracy). The deficiency of $t$ arises from its functional form and not the input features, as the calculation of t requires the same inputs as $t$ (composition, oxidation states, and Shannon ionic radii). Thus, $\\boldsymbol{\\uptau}$ enables a superior prediction of perovskite stability with negligible computational cost. The monotonic and 1D nature of $\\tau$ allows the determination of perovskite probability as a continuous function of the radii and oxidation states of $A,B_{\\mathrm{i}}$ , and $X$ . These probabilities are shown to linearly correlate with DFT-computed decomposition enthalpies and help clarify how chemical substitutions at each of the sites modulate the tendency for perovskite formation. Using $\\tau,$ we predict the probability of double perovskite formation for thousands of unexplored compounds, resulting in a library of stable perovskites ordered by their likelihood of forming perovskites. Because of the simplicity and accuracy of $\\tau,$ we expect its use to accelerate the discovery and design of state-of-the-art perovskite materials for applications ranging from photovoltaics to electrocatalysis. \n\n# MATERIALS AND METHODS \n\n# Radii assignment \n\nTo develop a descriptor that takes as input the chemical composition and outputs a prediction of perovskite stability, the features that comprise the descriptor must also be based only on composition. However, it is not known a priori which cation will occupy the $A$ or $B$ site given only a chemical composition, $C C X_{3}$ ( $C$ and $C^{\\prime}$ being cations). Therefore, we developed a systematic method for determining which cation is $A$ or $B$ to enable $\\boldsymbol{\\tau}$ to be applied to an arbitrary new material. First, a list of allowed oxidation states is defined for each cation based on Shannon’s radii (20). All pairs of oxidation states for $C$ and $C^{\\prime}$ that charge-balance $X_{3}$ are considered. If more than one charge-balanced pair exists, a single pair is chosen on the basis of the electronegativity ratio of the two cations $(\\chi_{\\mathrm{C}}/\\chi_{\\mathrm{C}^{\\prime}})$ . If $0.9<\\chi_{\\mathrm{C}}/\\chi_{\\mathrm{C^{\\prime}}}<1.1$ , the pair that minimizes $\\left|n_{C}-n_{C^{\\prime}}\\right|$ is chosen, where $n_{C}$ is the oxidation state for $C$ . Otherwise, the pair that maximizes $\\left|n_{C}-n_{C^{\\prime}}\\right|$ is chosen. With the oxidation states of $C$ and $C^{\\prime}$ assigned, the values of the Shannon radii for the cations occupying the $A$ and $B$ sites are chosen to be closest to the coordination number of 12 and 6, which are consistent with the coordination environments of the $A$ and $B$ cations in the perovskite structure. Last, the radii of the $C$ and $C^{\\prime}$ cations were compared, and the larger cation is assigned as the $A$ -site cation. This strategy reproduced the assignment of the $A$ and $B$ cations for $100\\%$ of 313 experimentally labeled perovskites. \n\n# Selection of $\\pmb{\\tau}$ \n\nFor the identification of $\\boldsymbol{\\uptau}$ among the offered candidates, the oxidation states $(n_{A},n_{B},n_{X})$ , ionic radii $(r_{A},r_{B},r_{X})$ , and radii ratios $(r_{A}/r_{B},r_{A}/r_{X},r_{B}/r_{X})$ comprise the primary features, $\\Phi_{0}$ , where $\\Phi_{n}$ refers to the descriptor space with $n$ iterations of complexity as defined in (28). For example, $\\Phi_{1}$ refers to the primary features $(\\Phi_{0})$ , together with one iteration of algebraic/functional operations applied to each feature in $\\Phi_{0}$ . $\\Phi_{2}$ then refers to the application of algebraic/ functional operations to all potential descriptors in $\\Phi_{1:}$ , and so forth. \n\nNote that $\\Phi_{m}$ contains all potential descriptors within $\\Phi_{n9^{\\circ}\\mathrm{C}$ during the night and ${>}4^{\\circ}\\mathrm{C}$ during midday (between 11 a.m. and ${\\mathrm{~2~p.m.}}$ ). Both the natural wood and the cooling wood exhibit similar thermal conductivities between their top and bottom surfaces (fig. S20), and these values are higher than that of thermal insulation wood $(I5)$ because of the densified structure created by mechanical pressing. We observed the scattered clouds during the measurement, which slightly reduced the net radiative cooling effects (16). In addition, we used fluorosilane treatment, which can be used to make the wood superhydrophobic with a water contact angle of ${\\sim}150^{\\circ}$ (fig. S21) and further improves the weatherability and protects the cooling wood from water condensate. \n\nThe cooling wood is also mechanically stronger and tougher than natural wood because of the larger interaction area between exposed hydroxyl groups of the aligned cellulose nanofibers in the growth direction after lignin removal (Fig. 3A) (17). The cooling wood demonstrates a tensile strength as high as $404.3\\mathrm{MPa}$ , which is ${\\sim}8.7$ times that of natural wood. An improved toughness of $\\mathrm{3.7MJ/m^{3}}$ was also observed, which is 10.1 times that of natural wood (Fig. 3B). We observed a simultaneous enhancement in mechanical toughness (fig. S22), which is desirable in structural material design (17–19). We attributed this to the energy dissipation enabled by repeated hydrogen-bond formation and/or breaking at the molecular scale in the delignified and mechanically pressed material. \n\nThe ratio of mechanical strength to weight is a critical parameter in buildings, especially because of cost considerations (20). The specific tensile strength of the cooling wood reaches up to $334.2\\ \\mathrm{MPa\\cm^{3}/g}$ (Fig. 3C), surpassing that of most structural materials, including Fe–Mn– Al–C steel, magnesium, aluminum alloys, and titanium alloys (21–23). The mechanical scratch hardness of the cooling wood also shows great improvement compared with that of the untreated natural wood. As characterized by a linear reciprocating tribometer (fig. S23), the scratch hardness of the cooling wood reaches up to 175.0 MPa in direction C, which is 8.4 times that of natural wood (Fig. 3, D and E). Compared with natural wood, the scratch hardness of the cooling wood also increased by a factor of 5.7 and 6.5 in directions A and B, respectively. The flexural strength of cooling wood is $\\mathbf{\\tilde{\\Gamma}}^{\\sim3.3}$ times as high as that of natural wood (fig. S24, A to C). The axial compressive strength of the cooling wood is also much higher than that of natural wood. The cooling wood shows a high axial compressive strength of $96.9\\ \\mathrm{MPa}$ , which is 3.2 times as high as that of natural wood (fig. S24, D to F). Cooling wood also exhibits a toughness that is 5.7 times as high as that of natural wood (fig. S24, G and H). \n\n![](images/5316f96e350cb875e03fcbceb457a001dca1fb585598bcf590c8fe50556832e0.jpg) \n\nThe cooling wood is superior to natural wood for building efficiency applications in terms of continuous cooling capability and mechanical strength (Fig. 3F). The properties of cooling wood, including continuous subambient cooling, high mechanical strength, bulk structure, low density, sustainability, and bulk fabrication process, make it attractive as a structural material when compared with other radiative cooling materials (7–9, 24–27). Raman et al. (7) demonstrated a photonic approach to meet the stringent demands of high thermal emission in the mid-infrared and strong solar reflection using seven alternating layers of $\\mathrm{{HfO}_{2}}$ and $\\mathrm{SiO_{2}}$ of varying thicknesses. However, the material is difficult to execute at the scale required for buildings. Another metamaterial thin film was demonstrated to have the potential for scalable manufacturing (9) but cannot be used as a structural component. The influence on radiative cooling performance from local weather conditions, including wind speed, precipitable water, and cloud cover, has been investigated on large-scale radiative cooling metamaterial and systems (16). Durability for long-term outdoor applications must be considered if the cooling wood is to be utilized as a structural material on the external surfaces of buildings in the future. Surface treatment methods could improve the resistivity of the cooling wood against water (28), fire (29), ultraviolet exposure (30), and biological factors (31) to satisfy the need for long-term outdoor durability. \n\nThe combination of the visible white (i.e., high solar reflectance) and infrared black (i.e., high infrared emissivity) properties of the cooling wood leads to a highly efficient radiative cooling material (Fig. 4, A and B). The mechanical strength also allows the cooling wood to be used as both roof and siding material without other mechanical support. We used EnergyPlus version 8 and the parameters listed in table S1 to model the potential energy savings of using cooling wood on exterior surfaces (wall siding and roofing membranes) of buildings. Our energy model accounts for a total heat balance on both the internal and external building enclosure surfaces, the heat transfer through the building enclosures, and heat sources and sinks, such as internal loads generated by equipment, occupants, and lighting. This modeling is governed by energy-balance equations for both the outside and inside surfaces of the building, as shown in table S2, which are solved simultaneously. To determine an annual rate of energy consumption, we solved the governing equations iteratively with an hourly time step over a year. The internal boundary conditions used an indoor air temperature set point of $24^{\\circ}\\mathrm{C},$ and the external boundary conditions used hourly weather data for a typical meteorological year (32). These models use ray tracing for all components of radiative heat transfer, including direct and indirect fluxes, and fluxes reflected from both the ground and surrounding building surfaces. \n\n![](images/61b62f2d6da70d495aec95c94703d0accce9258e6132b535cf44af5199aa262a.jpg) \nFig. 3. Cooling wood as a multifunctional structural material. (A) Schematics showing the origin of the high mechanical strength from the molecular bonding of the aligned cellulose nanofibers. The (B) tensile strength and (C) specific ultimate strength of the cooling wood are compared with those of natural wood and some common metals and alloy (21–23). (D and E) Scratch-hardness characterization of the natural wood and the cooling wood in three different directions. A, B, and C denote directions parallel, perpendicular, and at a $45^{\\circ}$ angle to the tree growth direction, respectively. (F) Performance comparison of cooling wood and natural wood. Error bars in (C) and (D) indicate measurement variations among the samples. \n\nThe building models that we used in this study are midrise apartment buildings across the United States, based on data from old (built before 1980) and new (built after 2004) structures provided by the U.S. Department of Energy Commercial Reference Buildings database (33). This building type is the most suitable among the reference buildings because of the importance of weather-related loads on the total building energy consumption (34). The energy modeling process established a baseline energy-consumption pattern for these old and new buildings and then modified the wall siding and roof membrane material properties on the basis of the cooling-wood performance to predict an energy-consumption pattern (figs. S25 and S26). \n\nSixteen cities in the United States were selected for this study: Albuquerque (NM), Atlanta (GA), Austin (TX), Boulder (CO), Chicago (IL), Duluth (MN), Fairbanks (AK), Helena (MT), Honolulu (HI), Las Vegas (NV), Los Angeles (CA), Minneapolis (MN), New York City (NY), Phoenix (AZ), San Francisco (CA), and Seattle (WA) (35). These cities are representative of all U.S. climate zones, allowing us to extend the results of this study to the entire country. The modified building models use cooling wood in place of common wood siding, which is a layer of the roofing and siding assembly, to determine the passive cooling power generated as a result of the local weather. \n\nWe determined the total cooling energy-saving patterns for the selected 16 cities and the percent savings relative to the baseline (Fig. 4, C and D). The midrise apartments built before 1980 and after 2004 are end members for assessing the energy savings, and buildings built in between will be between these two bounds. We found that an average of $\\sim35\\%$ in cooling energy savings can be obtained for old midrise apartment buildings, and an average of ${\\sim}20\\%$ can be obtained for new midrise apartments (Fig. 4E). \n\nThe energy savings from the installation of the cooling wood on the exterior surface of these buildings show that, on average for old and new midrise apartments, Austin $(22.9\\mathrm{MJ/m^{2}})$ , Honolulu $(28.2\\mathrm{MJ/m^{2}}\\cdot$ ), Las Vegas $(21.1\\mathrm{MJ/m^{2}};$ ), Atlanta $(\\mathrm{17.1MJ/m^{2}},$ , and Phoenix $(32.1\\mathrm{MJ/m}^{2})$ \n\n![](images/f4ce7dc505d45fd7e2af84db7be6ea17ef34ce96f74ce45c1a5c5d2060c46d65.jpg) \nFig. 4. Modeling energy savings by installing cooling-wood panels on roofing and external siding of midrise apartment buildings. (A) When used as a building material, the cooling wood exhibits high solar reflectance and high infrared emissivity. (B) Photo of a 5-cm-thick piece of cooling wood. (C) Total cooling energy savings per year and (D) percentage among all 16 cities. (E) Average cooling energy savings and percentage among all 16 cities. (F) Total predicted cooling energy savings of midrise buildings extended for all U.S. cities based on local climate zones. \n\nwould have the highest energy savings among the selected 16 cities. Phoenix had the highest potential cooling savings because of its hot and dry climate. Therefore, cities in the Southwest may be the most suitable for the installation of this material to reduce energy consumption for cooling. However, if the cooling wood remains exposed during the winter months, the heating energy cost would subsequently increase. The offset of the increased heating energy costs and a more detailed analysis of the overall energy savings can be found in fig. S26. We predicted the cooling energy savings of midrise buildings extended for all U.S. cities on the basis of local climate zones. The results show that cities with hot and dry climates have the largest potential cooling energy savings. The energy-savings effect of cooling wood has the potential to relax the energy load associated with conditioning indoor spaces that accounts for $31\\%$ of the total building primary energy consumption (36). We also evaluated the effect of neighboring structures on the energy performance (figs. S27 to S30). Surrounding buildings decrease the cooling energy demand of the building covered with cooling wood because of the shading that the surrounding structures provide. Therefore, the potential cooling energy savings \n\n# REFERENCES AND NOTES \n\n1. Heating & Cooling | Department of Energy; www.energy.gov/ heating-cooling. \n2. S. Catalanotti et al., Sol. Energy 17, 83–89 (1975). \n3. C. G. Granqvist, A. Hjortsberg, J. Appl. Phys. 52, 4205–4220 (1981). \n4. E. M. Lushiku, C.-G. Granqvist, Appl. Opt. 23, 1835–1843 (1984). \n5. M. Tazawa, P. Jin, K. Yoshimura, T. Miki, S. Tanemura, Sol. Energy 64, 3–7 (1998). \n6. S. Taylor, Y. Yang, L. Wang, J. Quant. Spectrosc. Radiat. Transf. 197, 76–83 (2017). \n7. A. P. Raman, M. A. Anoma, L. Zhu, E. Rephaeli, S. Fan, Nature 515, 540–544 (2014). \n8. Z. Chen, L. Zhu, A. Raman, S. Fan, Nat. Commun. 7, 13729 (2016). \n9. Y. Zhai et al., Science 355, 1062–1066 (2017). \n10. G. Wimmers, Nat. Rev. Mater. 2, 17051 (2017). \n11. H. Yang, R. Yan, H. Chen, D. H. Lee, C. Zheng, Fuel 86, 1781–1788 (2007). \n12. D. S. Wiersma, Nat. Photonics 7, 188–196 (2013). \n13. R. Hillenbrand, T. Taubner, F. Keilmann, Nature 418, 159–162 (2002). \n14. Z. Huang, X. Ruan, Int. J. Heat Mass Transfer 104, 890–896 (2017). \n15. T. Li et al., Sci. Adv. 4, eaar3724 (2018). \n16. D. Zhao et al., Joule 3, 111–123 (2019). \n17. Y. Wei et al., Nat. Commun. 5, 3580 (2014). \n18. R. O. Ritchie, Nat. Mater. 10, 817–822 (2011). \n19. Y. Wang, M. Chen, F. Zhou, E. Ma, Nature 419, 912–915 (2002). \n20. P. Fratzl, Nature 554, 172–173 (2018). \n21. S.-H. Kim, H. Kim, N. J. Kim, Nature 518, 77–79 (2015). \n22. A. A. Luo, J. Magnes. Alloys 1, 2–22 (2013). \n23. T. Dursun, C. Soutis, Mater. Des. 56, 862–871 (2014). \n24. E. Rephaeli, A. Raman, S. Fan, Nano Lett. 13, 1457–1461 (2013). \n25. A. R. Gentle, G. B. Smith, Adv. Sci. 2, 1500119 (2015). \n26. S. Atiganyanun et al., ACS Photonics 5, 1181–1187 (2018). \n27. J. Mandal et al., Science 362, 315–319 (2018). \n28. S. Oyola-Reynoso, J. Chen, B. S. Chang, J.-F. Bloch, M. M. Thuo, RSC Adv. 6, 82233–82237 (2016). \n29. V. Merk, M. Chanana, T. Keplinger, S. Gaan, I. Burgert, Green Chem. 17, 1423–1428 (2015). \n30. H. Guo et al., Holzforschung 70, 699–708 (2016). \n31. P. E. Laks, P. A. McKaig, R. W. Hemingway, Holzforschung 42, 299–306 (2009). \n32. National Solar Radiation Data Base, 1991-2005 Update: Typical Meteorological Year 3; https://rredc.nrel.gov/solar/old_data/ nsrdb/1991-2005/tmy3/. \n33. M. Deru et al., “U.S. Department of Energy commercial reference building models of the national building stock” (Tech. Rep. NREL/TP-5500-46861, National Renewable Energy Lab, 2011). \n34. M. Heidarinejad et al., Energy Convers. Manage. 144, 164–180 (2017). \n35. M. Heidarinejad, D. A. Dalgo, N. W. Mattise, J. Srebric, J. Clean. Prod. 171, 491–505 (2017). \n36. J. Huang, K. R. Gurney, Energy 111, 137–153 (2016). \n\nobtained by using cooling wood changes, on average, from $35\\%$ for an isolated building to $51\\%$ for the highest urban density in pre-1980 buildings and changes from 21 to $39\\%$ for post2004 buildings. \n\nWe developed a multifunctional, passive radiative cooling material composed of wood that can be fabricated by using a scalable bulk process to engineer its spectral response. The cooling wood exhibits superior whiteness, which originates from the low optical loss of the cellulose fibers and the material’s disordered photonic structure. The energy emitted within the infrared range of the cooling wood overwhelms the amount of solar energy received. We confirmed this cooling effect by real-time temperature measurements of natural and cooling-wood samples, in which the materials were exposed to the sky. Additionally, cooling wood is 8.7 times as strong as and 10.1 times as tough as natural wood. The intrinsic lightweight nature of the cooling wood has a specific strength three times that of widely used Fe–Mn–Al–C structural steel. This multifunctional, scalable cooling-wood material holds promise for future energy-efficient and sustainable building applications, enabling a substantial reduction in carbon emission and energy consumption. \n\n# ACKNOWLEDGMENTS \n\nFunding: This project is not directly funded. L.H. and T.L. acknowledge the support of the A. James & Alice B. Clark Foundation and the A. James School of Engineering at the University of Maryland. X.Y. acknowledges the support of the Gordon and Betty Moore Foundation. Author contributions: T.L., Y.Z., and S.H. contributed equally to this work. L.H., T.L., Y.Z., S.H., and X.Y. designed the experiments. T.L., S.H., W.G., R.M., J.So., J.D., C.C., A.V., and A.M. performed the material preparation and characterization as well as mechanical measurements and analysis. Y.Z., Z.W., X.Z., A.A., X.Y., and R.Y. contributed to the thermal and optical measurement and analysis. M.H., D.D., and J.Sr. performed the modeling for building efficiency. Y.Z., Z.W., and T.L. went to Arizona for field tests. L.H., T.L., Y.Z., and X.Y. collectively wrote the manuscript. Competing interests: L.H., T.L., and S.H. are the inventors on a patent currently pending at the international stage (WO 2019/ 055789; filed 14 September 2018). All the other authors declare that they have no competing interests. Data and materials availability: All data are available in the manuscript or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/364/6442/760/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S30 \nTables S1 and S2 \nReferences (37–39) \n27 July 2018; resubmitted 8 November 2018 \nAccepted 22 April 2019 \n10.1126/science.aau9101 \n\n# Science \n\n# A radiative cooling structural material \n\nTian Li, Yao Zhai, Shuaiming He, Wentao Gan, Zhiyuan Wei, Mohammad Heidarinejad, Daniel Dalgo, Ruiyu Mi, Xinpeng Zhao, Jianwei Song, Jiaqi Dai, Chaoji Chen, Ablimit Aili, Azhar Vellore, Ashlie Martini, Ronggui Yang, Jelena Srebric, Xiaobo Yin and Liangbing Hu \n\nScience 364 (6442), 760-763. DOI: 10.1126/science.aau9101 \n\n# A stronger, cooler wood \n\nOne good way to reduce the amount of cooling a building needs is to make sure it reflects away infrared radiation. Passive radiative cooling materials are engineered to do this extremely well. Li et al. engineered a wood through delignification and re-pressing to create a mechanically strong material that also cools passively. They modeled the cooling savings of their wood for 16 different U.S. cities, which suggested savings between 20 and $50\\%$ . Cooling wood would be of particular value in hot and dry climates. \n\nScience, this issue p. 760 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/364/6442/760 \n\nSUPPLEMENTARY MATERIALS \n\nRELATED CONTENT file:/content \n\nREFERENCES \n\nThis article cites 36 articles, 3 of which you can access for free http://science.sciencemag.org/content/364/6442/760#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.aaw7493", + "DOI": "10.1126/science.aaw7493", + "DOI Link": "http://dx.doi.org/10.1126/science.aaw7493", + "Relative Dir Path": "mds/10.1126_science.aaw7493", + "Article Title": "Engineering bunched Pt-Ni alloy nullocages for efficient oxygen reduction in practical fuel cells", + "Authors": "Tian, XL; Zhao, X; Su, YQ; Wang, LJ; Wang, HM; Dang, D; Chi, B; Liu, HF; Hensen, EJM; Lou, XW; Xia, BY", + "Source Title": "SCIENCE", + "Abstract": "Development of efficient and robust electrocatalysts is critical for practical fuel cells. We report one-dimensional bunched platinum-nickel (Pt-Ni) alloy nullocages with a Pt-skin structure for the oxygen reduction reaction that display high mass activity (3.52 amperes per milligram platinum) and specific activity (5.16 milliamperes per square centimeter platinum), or nearly 17 and 14 times higher as compared with a commercial platinum on carbon (Pt/C) catalyst. The catalyst exhibits high stability with negligible activity decay after 50,000 cycles. Both the experimental results and theoretical calculations reveal the existence of fewer strongly bonded platinum-oxygen (Pt-O) sites induced by the strain and ligand effects. Moreover, the fuel cell assembled by this catalyst delivers a current density of 1.5 amperes per square centimeter at 0.6 volts and can operate steadily for at least 180 hours.", + "Times Cited, WoS Core": 1197, + "Times Cited, All Databases": 1246, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000496946200049", + "Markdown": "# ELECTROCHEMISTRY \n\n# Engineering bunched Pt-Ni alloy nanocages for efficient oxygen reduction in practical fuel cells \n\nXinlong Tian1,2\\*, Xiao Zhao3\\*, Ya-Qiong $\\mathsf{\\pmb{S u}}^{\\mathbf{4}\\ast}$ , Lijuan Wang1, Hongming Wang5, Dai Dang6, Bin Chi7, Hongfang Liu1, Emiel J.M. Hensen4, Xiong Wen (David) ${\\mathsf{L o u}}^{8}\\dag$ , Bao Yu Xia1† \n\nDevelopment of efficient and robust electrocatalysts is critical for practical fuel cells. We report one-dimensional bunched platinum-nickel (Pt-Ni) alloy nanocages with a Pt-skin structure for the oxygen reduction reaction that display high mass activity (3.52 amperes per milligram platinum) and specific activity (5.16 milliamperes per square centimeter platinum), or nearly 17 and 14 times higher as compared with a commercial platinum on carbon (Pt/C) catalyst. The catalyst exhibits high stability with negligible activity decay after 50,000 cycles. Both the experimental results and theoretical calculations reveal the existence of fewer strongly bonded platinum-oxygen (Pt-O) sites induced by the strain and ligand effects. Moreover, the fuel cell assembled by this catalyst delivers a current density of 1.5 amperes per square centimeter at 0.6 volts and can operate steadily for at least 180 hours. \n\nP latinum (Pt) is the most active electrocatalyst for the oxygen reduction reaction (ORR) in fuel cells and metal-air batteries with promising stability (1–3). Nevertheless, the state-of-the-art Pt catalysts still lack activity and stability with respect to the cost and availability for large-scale commercial implementation (4, 5). Engineering the near-surface composition of nanostructured Pt alloys represents one promising approach to enhance the electrocatalytic performance of Pt-based electrocatalysts, in which the exposure of highly active sites with optimum performance can be maximized $(6,7)$ . Adding other transition metals can enhance the catalytic performance via ligand and strain effects through modifying the binding strength of Pt-oxygen intermediates (8–10). \n\nThe introduction of open nanostructures, including hollow and porous nanoparticles such as nanocages (NCs) and nanoframes, may help in achieving this goal and also enhance mass transfer $(I I)$ . Porous metal structures usually exist as nanoparticles and typically do not display long-term stability because they agglomerate or detach from the (usually carbon) support (12, 13). By contrast, onedimensional (1D) nanostructures and their assemblies can exhibit enhanced stability because of their inherent anisotropic, higher flexibility and higher conductivity (14). The anisotropy of 1D nanostructures can lead to greater surface contact with the usual carbon support, thus resulting in high stability (15). Recently, 1D Pt-based alloy nanostructures have been explored for their promising ORR activity and stability (16, 17). However, these solid 1D nanostructures contain a substantial proportion of noble metals in the bulk versus at the surface, which limits the noble-metal utilization (18). Moreover, although desirable ORR performance has been established in model studies with, for example, rotating disk electrodes (RDEs), relatively few works have studied nanostructured Pt electrocatalysts in a complete cell configuration (19). The limitations in comparing performance at the RDE level with those at the cell level are known (20). To this end, it follows that optimum ORR catalysts based on Pt should be designed by having a high Pt utilization efficiency (porous nanostructures), a favorable nanoscale chemical environment for ORR (chemical alloying) with an optimized structure in terms of the exposure of active sites, and stability derived from both the nanostructure itself as well as its interface with the support. \n\nWe demonstrate Pt-Ni bunched NCs (BNCs) in 1D form that exhibit superior ORR activity and durability compared with conventional Pt electrocatalysts. We first prepared 1D Pt-Ni bunched nanospheres (BNSs) by reducing Pt and Ni precursors with varying ratios in oleylamine by a one-pot solvothermal method. Treatment under acidic conditions selectively removed Ni species to leave 1D PtNi BNCs with ultrathin walls composed of a \n\nPt skin and a residual $\\mathrm{Pt-Ni}$ alloy below this skin (Fig. 1A). The nanostructures with a $\\mathrm{Pt}_{1.5}\\mathrm{Ni}$ starting composition exhibited the highest mass and specific activities of $3.52\\mathrm{~A~mg_{Pt}}^{-1}$ and $5.16\\mathrm{mAcm_{Pt}}^{-2}$ , respectively. These values are more than one order of magnitude higher than those of a commercial $\\mathrm{Pt/C}$ catalyst [60 weight $\\%$ (wt $\\%$ ), Johnson Matthey (JM)] and comparable to those of very recently reported Pt nanostructure catalysts (table S1). The catalyst also exhibited superb durability with a negligible activity decay (less than $1.5\\%\\rangle$ after 50,000 potential-scanning cycles. In addition, the Pt-Ni BNC electrocatalyst showed improved performance in a fuel cell test compared with commercial $\\mathrm{Pt/C},$ , both in a hydrogen-air proton exchange membrane fuel cell (PEMFC) and an air-breathing PEMFC setup at room temperature and ambient pressure. In situ x-ray absorption fine structure (XAFS) and theoretical calculations revealed that the Pt-Ni alloy nanostructures had optimal adsorption energies of oxygen intermediates with respect to Pt. \n\n# Bunched nanospheres \n\nThe Pt-Ni BNSs were synthesized in nearly $100\\%$ yield from platinum(II) acetylacetonate $\\mathrm{[Pt(acac)_{2}]}$ , nickel(II) acetylacetonate $\\mathrm{[Ni(acac)_{2}]}$ , cetyltrimethylammonium bromide (CTAB), and oleylamine mixtures that were ultrasonicated and then heated at $180^{\\circ}\\mathrm{C}$ for several hours (see supplementary materials and fig. S1). Composition studies included $\\mathrm{Pt_{3}N i,P t_{2}N i,P t_{1.5}N i,}$ $\\mathrm{Pt_{1}N i_{1}},$ and $\\mathrm{PtNi}_{2}$ samples, and the transmission electron microscopy– energy-dispersive spectroscopy (TEM-EDS) profiles, together with inductively coupled plasma optical emission spectrometry (ICPOES) results, suggest complete reduction of the precursors because the $\\mathrm{{Pt/Ni}}$ ratios of the final products were nearly the same as the ratios used in the synthesis mixture (fig. S2). We further studied the effect of the concentration of the various reagents, including CTAB and glucose, and the $\\mathrm{Pt/Ni}$ ratio in the synthesis solution on the formation of the structures (figs. S3 to S6). The x-ray diffraction (XRD) patterns of Pt-Ni BNSs with varying Pt-Ni composition $\\mathrm{(Pt}_{x}\\mathrm{Ni}_{y}$ -BNSs) confirmed the efficient alloy formation (fig. S5), indicating that the composition can be adjusted by judicious choice of the amount of Pt and Ni precursors (21). Only when no Ni was present during the synthesis were Pt nanowires (NWs) with a smooth surface obtained. The surfaces became rougher with the increasing $\\mathrm{{Ni/Pt}}$ feeding ratio (fig. S6). We used TEM-EDS to monitor timedependent reaction progress, which revealed the formation of Pt NWs before Ni inclusion. This sequence is expected, given the higher redox potential of Pt (figs. S7 and S8). Finally, stable Pt-Ni alloys were formed under solvothermal conditions (22). \n\n![](images/48b9b06d13c9f7a949d7625e11d2f4049fe56f5583bf2842b36879272377286b.jpg) \nFig. 1. Structural and compositional characterizations of $\\mathsf{P t}_{1.5}\\mathsf{N i}$ -BNSs. \n\n(A) Schematic illustration of the preparation of PtNiBNCs. (B and C) TEM images of PtNi-BNSs. (D) Enlarged TEM image of the area indicated in (C) and the corresponding HRTEM images of the areas marked by yellow squares. The white dots and arrows indicate the lattice spacing. (E and F) Atomic-resolution HRTEM images. Orange bars indicate the edges of the lattice planes, yellow arrows indicate the surface steps, and yellow circles indicate the outermost atoms. (G) Highangle annular dark-field (HAADF)–STEM image and the corresponding EDS elemental mapping of PtNiBNSs. (H) EDS profile of PtNi-BNSs (top) and STEMEDS line-scanning profile (bottom) of a single nanoparticle. The inset shows the studied nanoparticle and the line-scanning analysis along the yellow arrow. a.u., arbitrary units. \n\nRepresentative scanning electron microscopy (SEM) and TEM images emphasize the uniform 1D morphology of the as-synthesized samples for the $\\mathrm{Pt}_{1.5}\\mathrm{Ni}$ composition (labeled as PtNiBNSs, and this one, after etching, leads to the best ORR activity) with a length of hundreds of nanometers consisting of BNSs (Fig. 1, B and C). High-resolution TEM (HRTEM) images reveal lattice fringes of $0.227{\\mathrm{nm}}$ at the stems and $0.216\\mathrm{nm}$ at the shells (Fig. 1D), corresponding to (111) planes of Pt and Pt-Ni alloys (23), respectively, suggesting that the alloyed Pt-Ni nanospheres would be connected by Pt-rich NWs. Scanning transmission electron microscopy (STEM)–EDS line scanning of the stems of different regions showed the existence of Ni in the stems and an average $\\mathrm{Pt/Ni}$ ratio of roughly $5/1$ (fig. S9). It seems that the nanospheres were Ni-rich compared with the stems, because the scans may not reveal the overall compositions, whereas $\\mathrm{\\bf{Pt}}$ -rich alloys can be confirmed at the stems. Atomic-resolution HRTEM images depict the uneven surface of the PtNi-BNSs (i.e., $\\mathrm{Pt}_{1.5}\\mathrm{Ni}$ composition) and the occurrence of high-index (211) and (311) facets (Fig. 1, E and F). The presence of abundant high-index facets is favorable for ORR, because they exhibit distinct binding energies with oxygen-containing surface intermediates in the ORR mechanism (24). The presence of alloyed features is verified by STEM-EDS elemental mapping analysis, emphasizing the homogeneous distribution of Pt and Ni across the analyzed zone, which contains a Ni-rich core (Fig. 1G). The line-scanning analysis of PtNi-BNSs demonstrates that both Pt and Ni elements are dispersed uniformly across the whole sphere, with an atomic $\\mathrm{{Pt/Ni}}$ ratio near 60/40, according to TEM-EDS profile (Fig. 1H). This result is consistent with the bulk elemental ICP-OES analysis that informed a $\\mathrm{\\Pt/Ni}$ ratio of 62/38. \n\n# Bunched nanocages \n\nWe obtained Pt-enriched BNCs by selectively removing the more reactive Ni species through a simple acid-etching method. TEM images of the PtNi-BNCs (this sample is from the PtNiBNSs after the etching) showed that the products were still highly dispersed without structural collapse after the etching treatment (Fig. 2A). The presence of internal voids was deduced from the observation of the darker walls of the NCs (Fig. 2B). The average wall thickness was ${\\sim}2.2\\ \\mathrm{nm}$ (Fig. 2C), roughly corresponding to 11 atomic Pt layers. The lattice fringe of $0.221\\mathrm{nm}$ was consistent with the (111) plane of a Pt-Ni alloy (23) and was slightly larger than that of PtNi-BNSs because of the decreased Ni content after etching. In addition, the high density of steps and edges was well preserved during the etching step (Fig. 2D). STEM-EDS elemental mapping analysis indicated that the skin structure of the wall in the Pt-Ni NCs was Pt-rich (Fig. 2E). Figure 2F shows the EDS-line scanning of a single sphere in PtNi-BNCs, further confirming a well-defined Pt-skin structure of the NCs formed after the Ni etching. The thickness of the outer shell was ${\\sim}0.63~\\mathrm{{nm}}$ , corresponding to roughly two to three atomic Pt layers (25). \n\nOn the basis of the above analysis, we propose that the walls of NCs are heterogeneous in composition, with Pt-rich skins on both the outer and inner surfaces and Pt-Ni alloy in the inner region of the wall. The precise $\\mathrm{Pt/Ni}$ atomic ratio of PtNi-BNCs was revealed by the TEM-EDS profile as 80.7/19.3 (fig. S10, A and B), consistent with the ICP-OES result (81/19). The increased $\\mathrm{Pt/Ni}$ ratio was likely caused by selective Ni leaching. The XRD diffraction peaks of PtNi-BNCs showed a small shift to lower angles compared with PtNi-BNSs (fig. S10C), which is consistent with the lower overall Ni content of the former. X-ray photoelectron spectroscopy (XPS) of Pt 4f revealed a shift of the Pt core levels to lower binding energies compared with $\\mathrm{Pt/C}$ , likely because of electron donation from Ni to Pt (fig. S10D). The ligand effect would downshift the Pt d-band center, lowering the binding affinity between Pt and oxygen intermediates and thus enhancing the ORR activity (5). \n\n![](images/62a0a3acdb963ca95ebb2f181aac8dc1da4f4a3e225db93c2afb82dccdb40d8b.jpg) \nFig. 3. Electrochemical and fuel-cell performance of various Pt-based samples. (A to D) CVs (A), LSVs (B), corresponding Tafel plots (C), and mass and specific activities (D) of Pt/C, Pt NWs/C, PtNi-BNSs/C, and PtNi-BNCs/C at $0.9\\mathrm{\\V}$ (versus RHE). J, current density. (E) ${\\sf H}_{2}$ -air fuel cell polarization plots with Pt/C, PtNi-BNSs/C, and PtNi-BNCs/C as the cathode catalysts. (F) Stability test of ${\\sf H}_{2}$ -air and air-breathing fuel cells at $0.6\\mathrm{\\:V}$ . \n\n# Electrocatalytic activity \n\nWe evaluated PtNi-BNCs as ORR catalysts, and Fig. 3A presents cyclic voltammetry (CV) results of $\\mathrm{Pt/C}$ (60 wt $\\%$ , JM), Pt NWs/C, PtNi$\\mathrm{BNSs}/\\mathrm{C},$ , and PtNi-BNCs/C in a $\\mathrm{{N_{2}}}$ -saturated $0.1\\mathrm{MHCl}0_{4}$ solution (fig. S11). The CV curves for carbon-supported PtNi-BNCs were investigated as a function of the $\\mathrm{Pt/Ni}$ ratio (fig. S12). The electrochemically active surface area (ECSA) measured by hydrogen underpotential deposition $\\mathrm{(H_{UPD})}$ of PtNi-BNCs/C was $68.2\\mathrm{m}^{2}{\\mathrm{g}_{\\mathrm{Pt}}}^{-1}$ which is substantially higher than that of PtNi-BNSs/C $\\langle43.5\\mathrm{m}^{2}\\mathrm{g_{Pt}}^{-1}\\rangle$ , confirming the advantage of a hollow structure created by acid leaching. Moreover, the ECSA values for $\\mathrm{Pt/C_{\\mathrm{:}}}$ Pt NWs/C, $\\mathrm{Pt_{3}N i-B N C s/C}$ , $\\mathrm{Pt_{2}N i-B N C s/C,}$ $\\mathrm{Pt}_{1.5}\\mathrm{Ni-BNCs/C}$ , $\\mathrm{Pt_{1}N i_{1}{-}B N C s/C}$ , and $\\mathrm{PtNi}_{2}$ - BNCs/C (for convenience, all $x$ and $y$ values in the names of BNCs were labeled the same values as in the starting BNSs) were 56.5, 46.3, 37.4, 59.1, 68.2, 70.7, and $80.3\\mathrm{~m}^{2}\\mathrm{~g_{Pt}}^{-1}$ respectively, demonstrating the enhanced ECSA of Pt-Ni BNCs with increasing Ni content. TEM images of Pt-Ni BNCs with varying Ni contents demonstrate the increased porosity with increasing Ni/Pt ratio (fig. S13), in agreement with the larger ECSA values. \n\nWe also measured the ECSA from the electrooxidation of CO (CO stripping), given the sensitive nature of the $\\mathrm{Pt}$ -alloyed surface, because the ECSA derived from the $\\mathrm{H}_{\\mathrm{UPD}}$ method would be lower than the real values because of the weakened binding interaction caused by the alloying effects (the ECSA obtained from the CO stripping should be unaffected, fig. S14). The ECSA values of $\\mathrm{Pt/C}$ and PtNi-BNCs/C obtained from the CO stripping are 56.7 and $101.5\\mathrm{m^{2}g_{P t}}^{-1}$ , respectively; thus, the $\\mathrm{ECSA_{CO}/}$ $\\mathrm{ECSA_{HUPD}}$ ratio measured for $\\mathrm{Pt/C}$ was equal to 1 but was 1.49 for PtNi-BNCs/C, verifying the formation of a Pt-skin structure of PtNi-BNCs (4, 26). Figure 3, B and C, shows the linear sweep voltammetry (LSV) curves and Tafel plots, respectively, of Pt NWs/C, PtNi-BNSs/C, PtNiBNCs/C, and the commercial $\\mathrm{Pt/C}$ reference. The smaller Tafel slope obtained for PtNi$\\mathrm{BNCs/C}$ (54 mV decade−1) as compared with that of the other samples demonstrates the enhanced kinetics for the ORR. The mass and specific activities of $\\mathrm{Pt{NWS}/C(\\mathrm{1.02A}\\mathrm{mg}_{\\mathrm{Pt}})^{-1}}$ and $2.20\\mathrm{mAcm_{Pt}}^{-2})$ and $\\mathrm{PtNi{-}B N S s/C\\left(1{.}89A\\mathrm{mg_{Pt}}^{-1}\\right.}$ and $4.34\\mathrm{mAcm_{Pt}}^{-2}\\mathrm{\\Omega}$ at $0.9\\mathrm{V}$ [versus reversible hydrogen electrode (RHE)] were much higher than those of the $\\mathrm{Pt/C}$ reference $(0.21\\mathrm{Amg_{Pt}}^{-1}$ and $0.36\\mathrm{{mAcm_{Pt}}^{-2})}$ . Furthermore, PtNi-BNCs/C shows mass and specific activities of $3.52\\mathrm{Amg_{Pt}}^{-1}$ and $5.16\\mathrm{mAcm_{Pt}}^{-2}$ , which are respectively \\~17 and \\~14 times higher than those of the $\\mathrm{Pt/C}$ reference. In general, the catalytic performance was enhanced with increasing Ni/Pt ratio, which can be ascribed to the higher amount of exposed active sites achieved by Ni leaching (fig. S12). The inferior ORR activities of $\\mathrm{Pt_{1}N i_{\\mathrm{I}}}-$ BNCs/C and $\\mathrm{PtNi_{2}{\\cdot}B N C s/C}$ were ascribed to the structural collapse upon excessive Ni dissolution (fig. S13). \n\nTo further corroborate the ORR performance obtained at the RDE level, practical $\\mathrm{{H_{2}}}$ -air and air-breathing PEMFC tests were conducted (fig. S15) with fuel cells containing PtNi-BNSs/C and PtNi-BNCs/C at a loading of $0.15\\mathrm{mgcm^{-2}}$ as a cathode catalyst material. The $\\mathrm{H}_{2}$ -air fuel cell of PtNi-BNCs/C delivers a current density of $1.5\\mathrm{Acm^{-2}}$ at $0.6\\mathrm{V}$ and achieves a peak power density of $920\\ \\mathrm{mW\\cm^{-2}}$ (Fig. 3E), outperforming the PtNi-BNSs/C-based (1.0 A $\\mathrm{cm}^{-2}$ and $770\\mathrm{mW}\\mathrm{cm}^{-2}.$ ) and $\\mathrm{Pt/C}$ -based $(0.8\\mathrm{Acm^{-2}}$ and $600\\mathrm{{mW}c m^{-2}}.$ ) systems. Considering comparable Pt loadings, this performance is among the best reported performance for $\\mathrm{\\mathrm{Pt}}$ -based catalysts (table S1). In addition, the air-breathing PEMFC operated at room temperature and ambient pressure exhibited a current density of $170\\mathrm{\\mA\\cm^{-2}}$ at $0.6\\mathrm{V}_{:}$ , compared with $100\\mathrm{mAcm^{-2}}$ for $\\mathrm{Pt/C},$ resulting in an improvement of $70\\%$ (fig. S15E). The $\\mathrm{{H_{2}}}$ -air and airbreathing PEMFCs were stably operated at a constant working voltage of $0.6\\mathrm{V}$ for at least 180 hours with a negligible decay $(<3\\%)$ of the output current densities (Fig. 3F). \n\n# Structural changes under electrochemical operation \n\nTo evaluate the stability under better defined conditions, $\\mathrm{Pt/C},$ PtNi-BNSs/C, and $\\mathrm{PtNi-BNCs/C}$ were subjected to continuous cycling for 20,000 cycles between 0.6 and $\\mathrm{1.1V}$ in an $\\mathbf{O}_{2}$ - saturated 0.1 M $\\mathrm{HClO_{4}}$ solution. The ORR performance variations recorded every 4000 cycles show that the mass activity and ECSA of $\\mathrm{\\Pt/C}$ declined by 61.9 and $59.4\\%$ , respectively, and the half-wave potential shifted by $54~\\mathrm{mV}$ to more negative values compared with that of the fresh sample (Fig. 4, A and B). By contrast, the high durability of PtNi-BNSs/C was evidenced by the much smaller loss in mass activity and ECSA by 13.7 and $9.4\\%$ , respectively, along with a $6{\\cdot}\\mathrm{mV}$ negative-shifted half-wave potential (Fig. 4, C and D). The PtNi-BNSs/C sample became hollow and porous after the stability test through electrochemical leaching (dealloying) (fig. S16, A to C), whereas the bunched architecture was destroyed to some degree compared with PtNi-BNCs/C. These results suggest a strong chemical difference between electrochemical dealloying and chemical etching, because structural collapse and Ni leaching caused substantial performance loss of PtNi-BNSs/C (fig. S16D). Comparatively, the performance loss of PtNi-BNCs/C is negligible, even after the prolonged durability test for 50,000 cycles (Fig. 4, E and F). The mass activity and ECSA only dropped by 1.3 and $1.1\\%$ , respectively, after the durability test compared with that of the fresh one, demonstrating the robustness of PtNi-BNCs/C as an ORR electrocatalyst. The composition and structure of the PtNi-BNCs/C catalysts after the durability test were further investigated. The hollow and core-shell (Pt-rich surface) structures of PtNi-BNCs/C were retained during the durability test (fig. S17), and TEMEDS results revealed that Ni loss was negligible (fig. S18). The Pt-skin structure may have protected the electrocatalysts against further Ni leaching from the inner region of the wall. \n\n![](images/f1402af6a80b73d966858f60aeeb69bfc7c2d5573082f5e6823fa1b76fee88c2.jpg) \nFig. 4. Durability performance of various catalysts. (A, C, and E) LSV evolutions. The insets show the CV variations. (B, D, and F) Mass and specific activity evolutions for Pt/C [(A) and (B)], PtNi-BNCs/C [(C) and (D)], and PtNi-BNCs/C [(E) and (F)] before and after the durability test for various potential-scanning cycles. \n\nWe probed the dynamic changes in oxidation state and local coordination environment at ORR-relevant potentials by in situ XAFS. Figure 5A shows the potential-dependent $\\mathrm{Pt}\\mathrm{-}\\mathrm{L}_{3}$ edge x-ray absorption near-edge spectra (XANES) of PtNi-BNCs/C, emphasizing the metallic state of Pt at applied potentials of 0.54, 0.7, and $0.9\\mathrm{V}$ (versus RHE). A $\\scriptstyle5-\\mathrm{nm}\\mathrm{Pt}/\\mathrm{C}$ (TEC10E50E-HT) reference was used for comparison to reduce the influence of the size effect. For comparison, the $\\mathrm{Pt}\\mathrm{-}\\mathrm{L}_{3}$ edge XANES of PtNi-BNSs/C is depicted in fig. S19. The normalized white-line intensities $(\\upmu_{\\mathrm{norm}})$ at the $\\mathrm{Pt}\\mathrm{-}\\mathrm{L}_{3}$ edge increased with increasing applied potentials because of the chemisorption of surface oxygenated species (Fig. 5B) (27, 28). The trends in $\\upmu_{\\mathrm{{norm}}}$ with potential differed between the catalysts and were used to understand the mechanistic origins of ORR activity (29). At $0.54\\mathrm{V}$ , both PtNi-BNCs/C and PtNiBNSs/C showed a higher $\\upmu_{\\mathrm{norm}}$ than $\\mathrm{Pt/C}$ , probably because of the chemisorption of $^{*}\\mathrm{OH}$ and/or $^{*}0$ species in the double layer region (30). With an increase of the potential to $0.7\\mathrm{V}$ , the increase of $\\upmu_{\\mathrm{norm}}$ [i.e., $\\Delta{\\upmu}_{\\mathrm{norm}}$ $(0.7_{-}0.54\\mathrm{V})=\\upmu_{\\mathrm{norm}}\\left(0.7\\mathrm{V}\\right)-\\upmu_{\\mathrm{norm}}\\left(0.54\\mathrm{V}\\right)]$ was larger for PtNi-BNSs/C and smaller for PtNi-BNCs/C in comparison to the change for $\\mathrm{Pt/C}$ . When the potential was increased to $0.9{\\mathrm{V}}$ , a negligible $\\Delta\\upmu_{\\mathrm{norm}}\\left(0.9_{-}0.7\\mathrm{V}\\right)$ was seen for PtNi-BNSs/C and PtNi-BNCs/C relative to $\\mathrm{Pt/C}$ (Fig. 5, B and C). Together, PtNiBNSs/C showed an initially higher $\\Delta\\upmu_{\\mathrm{norm}}$ from 0.54 to $0.7\\mathrm{V}$ and subsequently an inhibited $\\Delta\\upmu_{\\mathrm{norm}}$ from 0.7 to $0.9\\mathrm{V}$ relative to that of $\\mathrm{Pt/C,}$ similar with previous reports (28, 30). However, $\\mathrm{PtNi-BNCs/C}$ only showed a higher $\\upmu_{\\mathrm{norm}}$ at $0.54\\mathrm{~V~}$ and subsequently the suppressed $\\Delta{\\upmu}_{\\mathrm{norm}}$ over the whole range of 0.54 to $0.9{\\mathrm{~V~}}$ compared with that of PtNi-BNSs/C and $\\mathrm{Pt/C}$ . Thus, the in situ XANES characteristic of PtNi-BNCs/C may partly account for its particularly high ORR activity and durability through the inhibition of strongly bonded oxygenated species from $0.54$ to $0.9{\\mathrm{V}}$ relative to $\\mathrm{Pt/C}$ and PtNi-BNSs/C. \n\n![](images/1ac569eb4cabada85713f1fce1774d3c818d75095d5e33adf63bd7f81be4af46.jpg) \nFig. 5. In situ XAFS and XANES analysis. (A) In situ $P t-L_{3}$ edge XANES spectra for PtNi-BNCs, with an enlarged view of the area marked by the green square. (B) In situ potential-dependent normalized white-line peak intensities $\\mathsf{\\Pi}[\\upmu(\\mathsf{E})_{\\mathsf{n o r m}}]$ . (C) $\\Delta\\mu\\times\\times A N E S$ spectra (0.9_0.7 V) of PtNi-BNSs and PtNi-BNCs. (D) First-shell EXAFS fitting in R space for spectral data at $0.54\\mathrm{\\:V}.$ . $\\mathsf{F T}[\\mathsf{k}^{2}\\chi(\\mathsf{k})]$ , Fourier-transformed $\\mathsf{k}^{2}$ -weighted EXAFS. Exp., experimental. \n\nThe fitted extended $\\mathbf{\\boldsymbol{x}}$ -ray absorption fine structure (EXAFS) spectra conducted at $0.54\\mathrm{V}$ (Fig. 5D, figs. S19 to S21, and tables S2 to S5), a potential in the double-layer region with the minimum interference from the adsorption of $^{*}\\mathrm{OH}$ and/or $^{*}0$ species, showed bond lengths of Pt-Pt $\\mathrm{(BL_{Pt-Pt})}$ and coordination numbers of Pt-Ni $\\mathrm{(CN_{Pt-Ni})}$ in the PtNi-BNCs/C $\\mathrm{\\DeltaBL_{Pt-Pt}=}$ 2.69 Å; $\\mathrm{CN}_{\\mathrm{Pt-Ni}}=0.6\\$ , PtNi-BNSs/C $\\begin{array}{r l}{\\lefteqn{\\mathrm{(BL_{Pt-Pt}=}}}\\end{array}$ 2.71 Å; $\\mathrm{CN}_{\\mathrm{Pt-Ni}}=1.0\\AA,$ , and $\\mathrm{Pt/C}$ $(\\mathrm{BL}_{\\mathrm{Pt-Pt}}=2.76\\mathrm{\\AA},$ . The evidently shorter $\\scriptstyle\\mathrm{\\mathrm{BL}}_{\\mathrm{Pt-Pt}}$ for both PtNiBNCs/C and PtNi-BNSs/C than that for $\\mathrm{Pt/C}$ could be well ascribed to the smaller size of Ni atoms compared with Pt thus inducing the global stress for PtNi-BNCs and PtNi-BNSs. However, compared with PtNi-BNSs/C, PtNi$\\mathrm{BNCs/C}$ exhibited a slightly smaller $\\mathrm{CN}_{\\mathrm{Pt-Ni}}$ but a slightly shorter $\\scriptstyle\\mathrm{\\mathrm{BL}}_{\\mathrm{Pt-Pt}},$ which indicated an additional source of strain, presumably induced by structural defects, as demonstrated in a recent report (7). Additionally, the fitting results of EXAFS at $0.9\\mathrm{V}$ revealed the absence of a definite Pt-O path for both PtNi-BNCs/C and PtNi-BNSs/C (tables S3 and S5), despite a clear electrochemical adsorption of oxygenated species on their surface. This lack of a Pt-O scattering peak in the EXAFS spectra for both PtNi-BNCs/C and PtNi-BNSs/C agrees with their XANES results and may be correlated with the surface disorder produced by the defects (steps and grain boundaries; see TEM analysis) and the corresponding disturbance to interfacial water structures (28, 30). \n\nInterestingly, TEM examinations after the ORR stability test showed a nearly hollow structure but irregular shape for PtNi-BNSs/ C, whereas dimensionally uniform hollow structures were observed for PtNi-BNCs/C (figs. S16 and S17). The differences in hollow microstructures between PtNi-BNSs/C and PtNi-BNCs/C were likely caused by the different corrosion methods for the Ni dissolution and the accompanied restructuring, that is, a moderate acid corrosion for PtNi$\\mathrm{\\BNCs/C}$ versus an electrochemical corrosion for PtNi-BNSs/C. Expectedly, these microstructural differences induced the distinct density and distribution of defects and correlated microstrain on the surface of catalysts, causing different electrocatalytic in situ \n\n![](images/c150b57735eb606c929696652ef9aa48e7d68a700aa19ebeb3dff78606603dd3.jpg) \nFig. 6. Disentangling the correlation of lattice strain and ligand effects on the d-band center, and the atomic O adsorption energy from DFT calculations. (A) DFT-determined correlation of d-band center and atomic O adsorption energy with the compressive lattice strain of Pt(111) facet. ${\\mathsf{R}}^{2}$ , coefficient of determination. (B) DFT-determined correlation between the d-band center and the generalized coordination number of surface Pt atoms of various Pt(hkl) planes. (C) DFT-determined correlation of atomic O adsorption energy with d-band center of surface sites. Pt(211)-B and Pt(311)-B denote the bridge sites of Pt(211) and Pt(311) planes, respectively. (D) Illustration of the synergistic effects derived from both the lattice strain and ligand effects in the catalysts. \n\nXANES and EXAFS behaviors between PtNiBNSs/C and PtNi-BNCs/C. Specifically, the irregular hollow structures in PtNi-BNSs/C easily created local overstrained domains that undermined the electrochemical stability of PtNi-BNSs/C to some extent, whereas the dimensionally uniform hollow structures in PtNi$\\mathrm{\\BNCs/C}$ were observed to be stable under the conditions we investigated. Thus, our work suggests that the fine regulation of microstructures by tailored synthesis could produce electrochemically durable hollow-structured ORR catalysts, although discrete hollow particles are generally less stable because of their high free energy. \n\n# Theoretical studies \n\nOn the basis of these experimental data, we performed density functional theory (DFT) calculations to understand the high ORR performance of PtNi-BNCs, using $\\mathrm{Pt_{3}N i}$ -skin and $\\mathrm{Pt_{4}N i}$ -skin models (Fig. 6). It is generally accepted that the atomic O adsorption energy $\\Delta\\mathrm{E}_{\\mathrm{O}^{\\ast}}$ can be used to evaluate the ORR activity, and the optimal value of $\\Delta\\mathrm{E}_{\\mathrm{O}^{\\ast}}$ is ${\\sim}0.2\\mathrm{eV}$ weaker than the one for Pt(111) (5, 31). $\\Delta\\mathrm{E}_{\\mathrm{O^{*}}}$ is modusolution, the bridge sites of high-index crystal planes are preferentially occupied by water molecules, and the other sites account for the observed high ORR activity (figs. S23 to S26). In addition, the determined potential energy profiles demonstrate that $\\mathrm{Pt_{4}N i}$ -skin has a lower overpotential for ORR than $\\mathrm{Pt_{3}N i}$ -skin and Pt(111) (fig. S27 and table S8). On the basis of the above analysis, we propose that the synergistic effects of strain and coordination environment, incorporation of Ni, and the appropriate $\\mathrm{Pt/Ni}$ ratio provide a properly weakened Pt-O binding strength, thus leading to the superior ORR activity of PtNi-BNCs (Fig. 6D). Furthermore, DFT calculations were also conducted to gain insight into the high stability of PtNi-BNCs (fig. S28). The binding energy of the surface Pt atoms in $\\mathrm{Pt_{4}N i}$ or $\\mathrm{Pt_{3}N i}$ -skin models is higher compared with that of other $\\scriptstyle{\\mathrm{[Pt(111)}}$ , Pt(211), and $\\mathrm{Pt}(311)]$ models, indicating higher stability of the Ptskin structures under the condition of lattice strain and coordination environment. Also, it was found that the required activation energy for the spillover of surface Pt atoms is substantial, indicating that dissolution of surface Pt atoms is kinetically prohibited for Pt-skin structures, even in the presence of oxygen adsorbates (table S9). The above results agreed well with the observed robust structure of our catalyst during the durability test. \n\nlated by the d-band center (labeled as $\\varepsilon_{\\mathrm{d}}.$ ) of Pt, whereas the downshift or upshift of $\\varepsilon_{\\mathrm{d}}$ is tuned by surface lattice strain (noted as $\\chi)$ and coordination environment (coordination number, noted as CN) (32–34). High-index crystal facets such as $\\operatorname*{Pt}(211)$ and Pt(311) exhibit a compressive lattice strain $(\\chi)$ relative to Pt(111), which brings a downshift of $\\varepsilon_{\\mathrm{d}}$ of surface Pt atoms and weakening of $\\Delta\\mathrm{E}_{\\mathrm{O^{*}}}$ . Herein, DFT calculation is focused on investigating the synergistic effect of $\\boldsymbol{\\chi}$ and CN on $\\varepsilon_{\\mathrm{{d}}},$ and finally on $\\Delta\\mathrm{E}_{\\mathrm{O^{*}}}$ , and the correlations between them (Fig. 6, A and B). Figure 6C corroborates that the $\\mathrm{Pt_{4}N i}$ -skin has higher ORR activity than the $\\mathrm{Pt_{3}N i}$ -skin, but activities of both are substantially improved relative to that of Pt(111). $\\Delta\\mathrm{E}_{\\mathrm{O^{*}}}$ values are 0.17 and 0.11 eV weaker on $\\mathrm{Pt_{4}N i}.$ and $\\mathrm{Pt_{3}N i}$ -skin, respectively, than on $\\mathrm{Pt(111)}$ , which are near the optimal $\\Delta\\mathrm{E}_{\\mathrm{O^{*}}}$ value (table S6). Both skins have a $2.5\\%$ compressive lattice strain (fig. S22 and table S7). The bridge sites of $\\operatorname*{Pt}(211)$ and Pt(311) have a stronger O binding than those on $\\mathrm{Pt}(\\mathrm{111})$ , whereas the hexagonal close-packed sites of them adsorb O slightly less strongly. For the ORR that happened at the electrode surface in aqueous \n\n# Discussion \n\nWe prepared bunched Pt-Ni NCs and demonstrated that they are efficient and durable ORR electrocatalysts for fuel cells. The as-obtained bunched Pt-Ni alloy NCs showed high mass and specific activities of $3.52\\mathrm{A}\\mathrm{mg_{Pt}}^{-1}$ and $5.16\\mathrm{mAcm_{Pt}}^{-2}$ , respectively, which are 16.8 times and 14.3 times higher than those of a commercial $\\mathrm{Pt/C}$ catalyst. Our catalyst also exhibited robust stability with negligible activity decay even after 50,000 potential-scanning cycles. The $\\mathrm{{H_{2}}}$ -air fuel cell assembled by this Pt-Ni catalyst achieves a peak power density of $920\\mathrm{{mW}c m^{-2}}$ and delivers a current density of $\\mathrm{{1.5Acm^{-2}}}$ at a voltage of $0.6\\mathrm{V}$ for at least 180 hours, demonstrating the great potential for practical application. In situ XAFS, theoretical calculation, and experimental results reveal that such excellent performance could be ascribed to the integration of a hollow structure and dimensional architecture in the bunched PtNi alloy NCs. This work provides an effective strategy for the rational design of Pt alloy nanostructures and will help guide the future development of catalysts for their practical applications in energy conversion technologies and beyond. \n\n# REFERENCES AND NOTES \n\n1. Z. W. Seh et al., Science 355, eaad4998 (2017). \n2. A. Kulkarni, S. Siahrostami, A. Patel, J. K. Nørskov, Chem. Rev. \n118, 2302–2312 (2018). \n3. M. K. Debe, Nature 486, 43–51 (2012). \n\n4. C. Chen et al., Science 343, 1339–1343 (2014). \n5. J. Greeley et al., Nat. Chem. 1, 552–556 (2009). \n6. D. F. van der Vliet et al., Nat. Mater. 11, 1051–1058 (2012). \n7. R. Chattot et al., Nat. Mater. 17, 827–833 (2018). \n8. P. Strasser et al., Nat. Chem. 2, 454–460 (2010). \n9. L. Bu et al., Science 354, 1410–1414 (2016). \n10. B. Lim et al., Science 324, 1302–1305 (2009). \n11. D. S. He et al., J. Am. Chem. Soc. 138, 1494–1497 (2016). \n12. L. Zhang et al., Science 349, 412–416 (2015). \n13. L. Wang, Y. Yamauchi, J. Am. Chem. Soc. 135, 16762–16765 \n(2013). \n14. M. Li et al., Science 354, 1414–1419 (2016). \n15. C. Koenigsmann, M. E. Scofield, H. Liu, S. S. Wong, \nJ. Phys. Chem. Lett. 3, 3385–3398 (2012). \n16. L. Bu et al., Adv. Mater. 27, 7204–7212 (2015). \n17. B. Y. Xia et al., J. Am. Chem. Soc. 135, 9480–9485 (2013). \n18. V. R. Stamenkovic et al., Nat. Mater. 6, 241–247 (2007). \n19. L. Chong et al., Science 362, 1276–1281 (2018). \n20. D. Banham, S. Ye, ACS Energy Lett. 2, 629–638 (2017). \n21. P. Wang, K. Jiang, G. Wang, J. Yao, X. Huang, Angew. Chem. \nInt. Ed. 55, 12859–12863 (2016). \n22. C. Cui, L. Gan, M. Heggen, S. Rudi, P. Strasser, Nat. Mater. 12, \n765–771 (2013). \n23. K. Jiang et al., Adv. Funct. Mater. 27, 1700830 (2017). \n24. M. Luo et al., Adv. Mater. 30, 1705515 (2018). \n25. X. Wang et al., Nat. Commun. 6, 7594 (2015). \n26. N. Becknell et al., J. Am. Chem. Soc. 137, 15817–15824 (2015) \n27. S. W. Lee et al., J. Phys. Chem. Lett. 1, 1316–1320 (2010). \n28. X. Zhao et al., J. Am. Chem. Soc. 141, 8516–8526 (2019). \n29. Q. Jia et al., ACS Nano 9, 387–400 (2015). \n30. Q. Jia et al., Nano Lett. 18, 798–804 (2018). \n31. S. J. Hwang et al., J. Am. Chem. Soc. 134, 19508–19511 \n(2012). \n32. J. Li et al., J. Am. Chem. Soc. 140, 2926–2932 (2018). \n33. L. Wang et al., Science 363, 870–874 (2019). \n34. Y. Feng et al., Sci. Adv. 4, eaap8817 (2018). \n\n# ACKNOWLEDGMENTS \n\nWe thank S. Liao from South China University of Technology for support with the fuel cell test. We thank X. Guo from Huazhong University of Science and Technology for valuable discussions. We thank Y. Iwasawa for support with XAFS measurements and the New Energy and Industrial Technology Development Organization (NEDO), Ministry of Economy, Trade, and Industry (METI), Japan; XAFS measurements were performed with SPring-8 subject numbers 2018B7800 and 2019A7800. Supercomputing facilities were provided by Netherlands Organisation for Scientific Research (NWO). The authors also acknowledge the support of the Analytical and Testing Center of Huazhong University of Science and Technology for XRD, XPS, ICP-OES, SEM, and TEM measurements. Funding: This work is funded by the National Natural Science Foundation of China (21805104 and 21802048), the National 1000 Young Talents Program of China and the Fundamental Research Funds for the Central Universities (2018KFYXKJC044, 2018KFYYXJJ121, and 2017KFXKJC002), and the Start-up \n\nResearch Foundation of Hainan University [KYQD(ZR)1908]. X.W.L. acknowledges funding support from the National Research Foundation (NRF) of Singapore via the NRF Investigatorship (NRF-NRFI2016-04). Author contributions: B.Y.X. and X.W.L. conceived the idea and designed the experiments. X.T. and L.W. carried out the sample synthesis, characterization, and measurements. X.Z. performed the in situ XAFS measurements. Y.-Q.S. and E.J.M.H. provided theoretical calculations. X.T. and D.D. performed the fuel cell measurements. B.C., H.W., and H.L. participated in the discussion of the experimental results. X.T., X.W.L., and B.Y.X. co-wrote and revised the manuscript. All the authors contributed to the overall scientific interpretation and edited the manuscript. X.T., X.Z., and Y.-Q.S. contributed equally to this work. Competing interests: The authors declare no competing financial interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/366/6467/850/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S28 \nTables S1 to S9 \nReferences (35–54) \n21 January 2019; resubmitted 9 August 2019 \nAccepted 22 October 2019 \n10.1126/science.aaw7493 \n\n# Science \n\n# Engineering bunched Pt-Ni alloy nanocages for efficient oxygen reduction in practical fuel cells \n\nXinlong Tian, Xiao Zhao, Ya-Qiong Su, Lijuan Wang, Hongming Wang, Dai Dang, Bin Chi, Hongfang Liu, Emiel J.M. Hensen, Xiong Wen (David) Lou and Bao Yu Xia \n\nScience 366 (6467), 850-856. DOI: 10.1126/science.aaw7493 \n\n# Nanocage-chain fuel cell catalysts \n\nThe expense and scarcity of platinum has driven efforts to improve oxygen-reduction catalysts in proton-exchange membrane fuel cells. Tian et al. synthesized chains of platinum-nickel alloy nanospheres connected by necking regions. These structures can be etched to form nanocages with platinum-rich surfaces that are highly active for oxygen reduction. In fuel cells running on air and hydrogen, these catalysts operated for at least 180 hours. \n\nScience, this issue p. 850 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.aav9051", + "DOI": "10.1126/science.aav9051", + "DOI Link": "http://dx.doi.org/10.1126/science.aav9051", + "Relative Dir Path": "mds/10.1126_science.aav9051", + "Article Title": "3D bioprinting of collagen to rebuild components of the human heart", + "Authors": "Lee, A; Hudson, AR; Shiwarski, DJ; Tashman, JW; Hinton, TJ; Yerneni, S; Bliley, JM; Campbell, PG; Feinberg, AW", + "Source Title": "SCIENCE", + "Abstract": "Collagen is the primary component of the extracellular matrix in the human body. It has proved challenging to fabricate collagen scaffolds capable of replicating the structure and function of tissues and organs. We present a method to 3D-bioprint collagen using freeform reversible embedding of suspended hydrogels (FRESH) to engineer components of the human heart at various scales, from capillaries to the full organ. Control of pH-driven gelation provides 20-micrometer filament resolution, a porous microstructure that enables rapid cellular infiltration and microvascularization, and mechanical strength for fabrication and perfusion of multiscale vasculature and tri-leaflet valves. We found that FRESH 3D-bioprinted hearts accurately reproduce patient-specific anatomical structure as determined by micro-computed tomography. Cardiac ventricles printed with human cardiomyocytes showed synchronized contractions, directional action potential propagation, and wall thickening up to 14% during peak systole.", + "Times Cited, WoS Core": 1229, + "Times Cited, All Databases": 1394, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000485768400044", + "Markdown": "# BIOMEDICINE \n\n# 3D bioprinting of collagen to rebuild components of the human heart \n\nA. Lee1\\*, A. R. Hudson1\\*, D. J. Shiwarski1, J. W. Tashman1, T. J. Hinton1, S. Yerneni1, J. M. Bliley1, P. G. Campbell1,2, A. W. Feinberg1,3† \n\nCollagen is the primary component of the extracellular matrix in the human body. It has proved challenging to fabricate collagen scaffolds capable of replicating the structure and function of tissues and organs. We present a method to 3D-bioprint collagen using freeform reversible embedding of suspended hydrogels (FRESH) to engineer components of the human heart at various scales, from capillaries to the full organ. Control of pH-driven gelation provides 20-micrometer filament resolution, a porous microstructure that enables rapid cellular infiltration and microvascularization, and mechanical strength for fabrication and perfusion of multiscale vasculature and tri-leaflet valves. We found that FRESH 3D-bioprinted hearts accurately reproduce patient-specific anatomical structure as determined by micro–computed tomography. Cardiac ventricles printed with human cardiomyocytes showed synchronized contractions, directional action potential propagation, and wall thickening up to $14\\%$ during peak systole. \n\n■ toirssbuieofsacbafrfiocladtisotno, trheeatgdoiasleiasetso eorngwinhiecehr there are limited options, such as end-stage organ failure. Three-dimensional (3D) bioprinting has achieved important milestones including microphysiological devices $(I)$ , patterned tissues (2), perfusable vascular-like netrequired to recreate complex 3D structure and function. Recently, Dvir and colleagues 3Dprinted a decellularized ECM hydrogel into a heart-like model and showed that human cardiomyocytes and endothelial cells could be integrated into the print and were present as spherical nonaligned cells after 1 day in culture (8). However, no further structural or functional analysis was performed. \n\nWe report the ability to directly 3D-bioprint collagen with precise control of composition and microstructure to engineer tissue components of the human heart at multiple length scales. Collagen is an ideal material for biofabrication because of its critical role in the ECM, where it provides mechanical strength, enables structural organization of cell and tissue compartments, and serves as a depot for cell adhesion and signaling molecules (9). However, it is difficult to 3D-bioprint complex scaffolds using collagen in its native unmodified form because gelation is typically achieved using thermally driven self-assembly, which is difficult to control. Researchers have used approaches including works (3–5), and implantable scaffolds (6). However, direct printing of living cells and soft biomaterials such as extracellular matrix (ECM) proteins has proved difficult (7). A key obstacle is the problem of supporting these soft and dynamic biological materials during the printing process to achieve the resolution and fidelity \n\nFig. 1. High-resolution 3D bioprinting of collagen using FRESH v2.0. (A) Time-lapse sequence of 3D bioprinting of the letters “CMU” using FRESH v2.0. (B) Schematic of acidified collagen solution extruded into the FRESH support bath buffered to pH 7.4, where rapid neutralization causes gelation and formation of a collagen filament. (C and D) Representative images of the gelatin microparticles in the support bath for (C) FRESH v1.0 and (D) v2.0, showing the decrease in size and polydispersity. (E) Histogram of Feret diameter distribution for gelatin microparticles in FRESH v1.0 (blue) and v2.0 (red). (F) Mean Feret diameter of gelatin microparticles for FRESH v1.0 chemically modifying collagen into an ultraviolet (UV)–cross-linkable form (10), adjusting pH, temperature, and collagen concentration to control gelation and print fidelity (11, 12), and/or denaturing it into gelatin (13) to make it thermoreversible. However, these hydrogels are typically soft and tend to sag, and they are difficult to print with high fidelity beyond a few layers in height. Instead, we developed an approach that uses rapid pH change to drive collagen selfassembly within a buffered support material, enabling us to (i) use chemically unmodified collagen as a bio-ink, (ii) enhance mechanical properties by using high collagen concentrations of 12 to $24~\\mathrm{mg/ml}$ , and (iii) create complex structural and functional tissue architectures. To accomplish this, we developed a substantially improved second generation of the freeform reversible embedding of suspended hydrogels (FRESH v2.0) 3D-bioprinting technique used in combination with our custom-designed opensource hardware platforms (fig. S1) (14, 15). FRESH works by extruding bio-inks within a thermoreversible support bath composed of a gelatin microparticle slurry that provides support during printing and is subsequently melted away at $37^{\\circ}\\mathrm{C}$ (Fig. 1, A and B, and movie S1) (16). \n\n![](images/ae227099d1ce1ebaf1290d48ded333dc3ba152542e1dbf83489dfce89833458c.jpg) \nand $\\mathsf{v}2.0$ $[N>1200$ , data are means $\\pm$ SD, $\\ast\\ast\\ast\\ast P<0.0001$ (Student t test)]. (G) Storage (Gʹ) and loss $(\\mathsf{G}^{\\prime\\prime})$ moduli for FRESH v1.0 and $\\mathsf{v}2.0$ support baths showing yield stress fluid behavior. (H) A “window-frame” print construct with single filaments across the middle, comparing G-code (left), FRESH v1.0 (center), and FRESH $\\mathsf{v}2.0$ (right). (I) Single filaments of collagen showing the variability of the smallest diameter $(\\sim250\\upmu\\mathrm{m})$ that can be printed using FRESH v1.0 (top) compared to relatively smooth filaments 20 to $200~{\\upmu\\mathrm{m}}$ in diameter using FRESH $\\mathsf{v}2.0$ (bottom). (J) Collagen filament Feret diameter as a function of extrusion needle internal diameter for FRESH $\\mathsf{v}2.0$ , showing a linear relationship. \n\nThe original version of the FRESH support bath, termed FRESH v1.0, consisted of irregularly shaped microparticles with a mean diameter of ${\\sim}65~\\upmu\\mathrm{m}$ created by mechanical blending of a large gelatin block (Fig. 1C) (16). In FRESH v2.0, we developed a coacervation approach to generate gelatin microparticles with (i) uniform spherical morphology (Fig. 1D), (ii) reduced polydispersity (Fig. 1E), (iii) decreased particle diameter of $\\sim25\\upmu\\mathrm{m}$ (Fig. 1F), and (iv) tunable storage modulus and yield stress (Fig. 1G and fig. S2). FRESH v2.0 improves resolution with the ability to precisely generate collagen filaments and accurately reproduce complex G-code, as shown with a window-frame calibration print (Fig. 1H). Using FRESH v1.0, the smallest collagen filament reliably printed was $\\sim250\\upmu\\mathrm{m}$ in mean diameter, with highly variable morphology due to the relatively large and polydisperse gelatin microparticles (Fig. 1I). In contrast, FRESH v2.0 improves the resolution by an order of magnitude, with collagen filaments reliably printed from $200~{\\upmu\\mathrm{m}}$ down to $20~{\\upmu\\mathrm{m}}$ in diameter (Fig. 1, I and J). Filament morphology from solid-like to highly porous was controlled by tuning the collagen gelation rate using salt concentration and buffering capacity of the gelatin support bath (fig. S3). A pH 7.4 support bath with $50~\\mathrm{mM}$ HEPES was the optimal balance between individual strand resolution and strand-to-strand adhesion and was versatile, enabling FRESH printing of multiple bio-inks with orthogonal gelation mechanisms including collagen-based inks, alginate, fibrinogen, and methacrylated hyaluronic acid in the same print by adding $\\mathrm{CaCl_{2}}$ , thrombin, and UV light exposure (fig. S4) (15). \n\nWe first focused on FRESH-printing a simplified model of a small coronary artery–scale linear tube from collagen type I for perfusion with a custom-designed pulsatile perfusion system (Fig. 2A and fig. S5). The linear tube had an inner diameter of $1.4~\\mathrm{mm}$ (fig. S6A) and a wall thickness of ${\\sim}300~\\upmu\\mathrm{m}$ (fig. S6B), and was patent and manifold as determined by dextran perfusion (fig. S6, C to E, and movie S2) (15). C2C12 cells within a collagen gel were cast around the printed collagen tube to evaluate the ability to support a volumetric tissue. The static nonperfused controls showed minimal compaction over 5 days (Fig. 2B), and a cross section revealed dead \n\n![](images/bd10783bbf2ffdbddba71124475cf92c89aebf693bf9fc3428a5edbd8f11ace1.jpg) \nFig. 2. FRESH 3D bioprinting of perfusable collagen vessels and microporous collagen scaffolds that promote in vivo microvascularization. \n(A) FRESH-printed collagen tube construct. (B) C2C12 cell and collagen gel mixture cast around the collagen tube and static-cultured for 5 days. (C) Cross section of the tissue from (B) stained for live (green) and dead (red) cells. (D) C2C12 cell and collagen gel mixture cast around the collagen tube and perfused for 5 days. (E) Cross section of the tissue from (D) stained for live and dead cells. (F) Percent cell viability as a function of depth from the top surface of the tissues from the static and perfused collagen tube constructs $[N=3$ , data are means $\\pm$ SD, ${^{\\ast}P}<0.05$ (two-way ANOVA followed by Bonferroni multiple-comparisons posttest)]. (G) Multiphoton imaging showing microscale porosity in FRESH-printed collagen constructs after removal of the gelatin microparticle support bath. (H and I) Collagen \nconstructs cast (H) and FRESH-printed (I) without VEGF 7 days after subcutaneous implantation. (J and K) Masson’s trichrome staining to visualize cells (red) and collagen (blue) in cast (J) and FRESH-printed (K) collagen disks after 7 days of subcutaneous implantation. (L) Cell density after implantation as a function of depth for the cast and FRESH-printed collagen disks. (M and N) Collagen constructs cast (M) and FRESH-printed (N) with VEGF $\\mathrm{{100}\\ n g/m l},$ ) 10 days after subcutaneous implantation. (O and P) CD31 staining (brown) and cells (blue) of cast (O) and FRESHprinted (P) collagen disks doped with VEGF $\\scriptstyle\\mathrm{(100~ng/ml)}$ ) after 10 days of subcutaneous implantation. (Q) Host vascular infiltration of vessels (diameter 8 to $50\\upmu\\mathrm{m}\\dot{},$ ) in the FRESH-printed collagen disk labeled by lectin tail vein injection (red). (R) Multiphoton image $70\\upmu\\mathrm{m}$ into the FRESH-printed construct, showing red blood cells within the lumen of the microvasculature. \n\nFig. 3. Contractile FRESH 3D-bioprinted human cardiac ventricle model. (A) Schematic of dual-material FRESH printing using a collagen ink and a high-concentration cell ink. (B) Ventricle model with a central section of cardiac cells (pink), internal and external collagen shells (green), and a collagen-only section (yellow). (C) Micrograph of FRESH-printed ventricle. (D) Side view of FRESHprinted ventricle stained with calcium-sensitive dye showing uniform cell distribution. (E) Calcium mapping of the subregion [yellow box in (D)] showing spontaneous, directional calcium wave propagation with conduction velocity of $1.97\\mathrm{cm/s}$ . (F) Top view of FRESH-printed ventricle stained with calcium-sensitive dye. (G) Calcium mapping showing spontaneous circular calcium wave propagation around the ventricle with conduction velocity of $1.31\\mathrm{cm/s}$ . (H) Point stimulation of FRESH-printed ventricle stained with calciumsensitive dye (red asterisk indicates electrode location). (I) Calcium mapping of the subregion [yellow box in (H)] showing anisotropic calcium wave propagation with longitudinal conduction velocity of $2.0~\\mathsf{c m/s}$ . (J) Calcium transient traces during spontaneous contractions (top), 1-Hz field stimulation (middle), and $2-H z$ field stimulation (bottom). Calcium fluorescence intensity $(F)$ is normalized by dividing by baseline fluorescence intensity $(F_{0})$ . (K) Top-down image of the FRESHprinted ventricle with inner (yellow) and outer (red) walls outlined. (L) A subregion of the ventricular wall analyzed for displacement during $1-1-12$ field stimulation, showing inner and outer wall motion; magnitude and direction are indicated by red arrows. (M) Cross-sectional area of the ventricle interior chamber at peak systole $N=4$ , data are means $\\pm\\mathsf{S D}_{.}^{\\cdot}$ ). \n\n![](images/7b35bfdfd613426057cf47de51ef7a1e7f419aa5da432e5045b3cb045fe4aee1.jpg) \n\ncells throughout the interior volume with a layer of viable cells only at the surface (Fig. 2C). In contrast, after active perfusion for 5 days, C2C12 cells compacted the collagen gel around the collagen tube (Fig. 2D), demonstrating viability and active remodeling of the gel through cell-driven compaction. The cross section showed cells alive throughout the entire volume (Fig. 2E), and quantitative analysis using LIVE/DEAD staining confirmed high viability within the perfused vascular construct (Fig. 2F). Others have 3D-bioprinted vasculature by casting cell-laden hydrogels around fugitive filaments, which become the vessel lumens $(4,5)$ . In comparison, we directly print collagen to form the walls of a functional vascular channel, serving as the foundation for engineering more complex architectures. \n\nEngineering smaller-scale vasculature, especially on the order of capillaries (5 to $10\\upmu\\mathrm{m}$ in diameter), has been a challenge for extrusionbased 3D bioprinting because this is far below common needle diameters. However, at this length scale, endothelial and perivascular cells can self-assemble vascular networks through angiogenesis (17). We reasoned that the gelatin microparticles in the FRESH v2.0 support bath could be incorporated into the 3D-bioprinted collagen to create a porous microstructure, specifically because pores on the order of $30~{\\upmu\\mathrm{m}}$ in diameter have been shown to promote cell infiltration and microvascularization (18). FRESH v2.0–printed constructs contained micropores ${\\sim}25\\upmu\\mathrm{m}$ in diameter resulting from the melting and removal of the gelatin microparticles purposely entrapped during the printing process (Fig. 2G and movie S3). Collagen disks $5\\mathrm{mm}$ thick and $10~\\mathrm{mm}$ in diameter were cast in a mold or printed and implanted in an in vivo murine subcutaneous vascularization model (Fig. 2, H and I, and fig. S7, A and B) to observe cellular infiltration. After implantation for 3 and 7 days, collagen disks were extracted and assessed for gross morphology, cellularization, and collagen structure (fig. S7, C to E). The solid-cast collagen showed minimal cell infiltration (Fig. 2J), whereas the printed collagen had extensive cell infiltration and collagen remodeling (Fig. 2K). Quantitative analysis revealed that cells infiltrated throughout the printed collagen disk within 3 days (Fig. 2L and fig. S8) and that the number of cells in the constructs was significantly greater for the printed collagen at 3 and 7 days compared to cast control $[N=6$ , $P<0.0001$ , two-way analysis of variance (ANOVA)] (15). \n\nTo promote vascularization, we incorporated fibronectin and the proangiogenic molecule recombinant vascular endothelial growth factor (VEGF) into our collagen bio-ink (19). Collagen disks that were FRESH-printed with VEGF and extracted after 10 days in vivo showed enhanced vascularization relative to cast controls (Fig. 2, M and N). By histology, the addition of VEGF to the cast collagen increased cell infiltration without promoting microvascularization (Fig. 2O and fig. S9). In contrast, the addition of VEGF to the printed collagen resulted in widespread vascularization, with CD31-positive vessels and red blood cells visible within the lumens (Fig. 2P). Tail vein injection of fluorescent lectin confirmed an extensive host-derived vascular network with vessels ranging from 8 to $50~{\\upmu\\mathrm{m}}$ in diameter throughout the printed collagen disk (Fig. $^{2\\mathrm{Q},}$ fig. S10, and movie S4). Multiphoton microscopy enabled deeper imaging into the printed constructs and showed vessels containing red blood cells at depths of at least $200~{\\upmu\\mathrm{m}}$ (Fig. 2R and movie S5). \n\nWe next FRESH-printed a model of the left ventricle of the heart using human stem cell– derived cardiomyocytes. We used a dual-material printing strategy with collagen bio-ink as the structural component in combination with a highdensity cell bio-ink (Fig. 3A) (15). A test print design (fig. S11A) verified that the collagen pH was neutralized quickly enough to maintain $\\sim96\\%$ post-printing viability by LIVE/DEAD staining (fig. S11B). The ventricle was designed as vessels, which decrease in diameter according to distance from the coronary artery (red to blue). (L) Left ventricle with the left anterior descending artery (red), computationally generated vasculature (purple), and subregion of interest (pink). $(\\pmb{\\mathsf{M}})$ Transparent subregion showing 3D structure of the vascular network. (N) The subregion FRESH-bioprinted with collagen, showing reproduction of the vascular network. (O) Perfusion of the vascular network with glycerol (red) through the coronary artery, showing interconnectivity. (P) Collagen was optically cleared and perfused with glycerol (red), showing perfusion down to vessels ${\\sim}100~\\upmu\\mathrm{m}$ in diameter. (Q) MRI-derived 3D human heart scaled to neonatal size. (R) FRESH-printed collagen heart. (S) Cross-sectional view of the collagen heart, showing left and right ventricles and interior structures. (T and U) High-fidelity image of the trabeculae in the left ventricle (T) showing reproduction of the complex anatomical structure from the G-code (U). (V and $\\boldsymbol{\\mathsf{w}}$ ) High-fidelity image of the septal wall between ventricles (V) showing reproduction of the square-lattice infill from the G-code (W). \n\n![](images/7ecedbce4807f2b29688e5f6b2b93aedb9b04986af98f864419d8649dde89282.jpg) \nFig. 4. Organ-scale FRESH 3D bioprinting of tri-leaflet heart valve, multiscale vasculature, and neonatal-scale human heart. (A) Tri-leaflet heart valve 3D model at adult human scale. (B and C) Top and side views of FRESH-printed collagen heart valve with barium sulfate added for $\\mathsf{x}$ -ray contrast. (D) $\\upmu\\mathsf{C T}$ reconstruction showing the full printed valve. (E) Lateral cross section of the wall and leaflets. (F) Quantitative gauging of the $\\upmu\\mathsf{C T}$ 3D surface compared to the 3D model, showing average overprinting of $+0.55$ mm and underprinting of $-0.80\\mathrm{mm}$ . (G) Sequence of valve opening under pulsatile flow over ${\\displaystyle-1\\ s}$ . (H) Doppler flow velocimetry of a single cycle: (i) closed, (ii) half-open, and (iii) open. (I) Same as (H) over multiple cycles. (J) Maximum transvalvular pressure of printed alginate and collagen valves compared to operating pressure for native valves $[N=3$ , data are means $\\pm$ SD, n.s. indicates $P>0.05$ (Student t test)]. (K) MRI-derived 3D human heart model (gray) with computationally derived multiscale vascular network shown for the the left ventricle. The left anterior descending coronary artery (red) is the template to guide the formation of smaller-scale \n\nan ellipsoidal shell (Fig. 3B) with inner and outer walls of collagen and a central core region containing human embryonic stem cell–derived cardiomyocytes (hESC-CMs) and $2\\%$ cardiac fibroblasts (fig. S11, C to H). Ventricles were printed and cultured for up to 28 days, during which the collagen inner and outer walls provided sufficient structural integrity to maintain their intended geometry (Fig. 3C). After 4 days, the ventricles visibly contracted, and after 7 days they became synchronous with a dense layer of interconnected and striated hESC-CMs, as confirmed by immunofluorescent staining of sarcomeric $\\mathbf{\\alpha}_{\\mathrm{~\\mathfrak{~a~}~}}$ -actinin–positive myofibrils (fig. S11, I to K). Calcium imaging revealed contracting hESC-CMs throughout the entire printed ventricles, with directional wave propagation in the direction of the printed hESC-CMs observed from the side (Fig. 3, D and E) and top (Fig. 3, F and G) during spontaneous contractions in multiple ventricles $\\left(N=3\\right)$ ) (movie S6). Point stimulation enabled visualization of anisotropic calcium wave propagation with longitudinal conduction velocity of ${\\sim}2~\\mathrm{cm/s}$ and a longitudinal-to-transverse anisotropy ratio of ${\\sim}1.5$ (Fig. 3, H and I). The ventricles had a baseline spontaneous beat rate of ${\\sim}0.5\\ \\mathrm{Hz}$ and could be captured and paced at 1 and $2\\mathrm{Hz}$ by means of field stimulation (Fig. 3J). We imaged the ventricles top-down to quantify motion of the inner and outer walls (Fig. 3K). Wall thickening is a hallmark of normal ventricular contraction. The printed ventricle expanded both inward and outward during a contraction, as determined by particle tracking to map the deformation field (Fig. 3L). The decrease in crosssectional area of the interior chamber during peak systole showed a maximum of ${\\sim}5\\%$ at 1-Hz pacing $\\left(N=4\\right)$ (Fig. 3M and movie S6). We also observed electrophysiologic behavior associated with arrhythmogenic disease states, including multiple propagating waves (fig. S12, A and B) and pinned rotors (fig. S12, C and D). \n\nTo demonstrate the mechanical integrity and function of collagen constructs at adult human scale, we printed a tri-leaflet heart valve $28~\\mathrm{mm}$ in diameter (Fig. 4A). We first prototyped the valve using alginate, a material previously used to build valve models (20), and then printed a collagen valve and improved the mechanical properties by adapting published fixation protocols for decellularized porcine heart valves (fig. S13A) $(I5,2I)$ . The collagen valve had wellseparated leaflets, was robust enough to be handled in air (Fig. 4, B and C, and movie S7), and was imaged by micro–computed tomography $(\\upmu\\mathrm{{CT})}$ (Fig. 4, D and E, and movie S8). Print fidelity was quantified using gauging to overlay the $\\upmu\\mathrm{CT}$ data on the 3D model (fig. S13B), showing average overprinting of $+0.55\\ \\mathrm{mm}$ and underprinting of $-0.80\\ \\mathrm{mm}$ (Fig. 4F and fig. S13, C and D). Mechanical function was demonstrated by mounting the valve in a flow system with a pulsatile pump to simulate physiologic pressures, and we observed cyclical opening and closing of the valve leaflets (Fig. 4G and movie S7). We quantified flow through the valves (Fig. 4H) and demonstrated $<15\\%$ regurgitation (Fig. 4I) with a maximum area opening of $19.5\\%$ (Fig. 4G). Additionally, the maximum transvalvular pressure was greater than $40\\mathrm{mmHg}$ for the collagen and alginate valves (Fig. 4J), exceeding standard physiologic pressures for the tricuspid and pulmonary valves but less than the aortic and mitral valves (22). Further, human umbilical vein endothelial cells (HUVECs) cultured on unfixed collagen leaflets formed a confluent monolayer (fig. S13E). \n\nA magnetic resonance imaging (MRI)–derived computer-aided design (CAD) model of an adult human heart was created, complete with internal structures such as valves, trabeculae, large veins, and arteries, but lacking smaller-scale vessels. To address this, we developed a computational method that uses the coronary arteries as the template to generate multiscale vasculature (fig. S14 and movie S9). We created a space-filling branching network based on a 3D Voronoi lattice, where vessels further from the left coronary arteries (red to blue) have a denser network and smaller diameters, down to ${\\sim}100\\upmu\\mathrm{m}$ (Fig. 4K). A subregion of the generated vasculature containing the left anterior descending artery (LAD) was selected, rendered, and printed from collagen at adult human scale (Fig. 4, L to N). Patency of large vessels was demonstrated by perfusing the multiscale vasculature through the root of the LAD (Fig. 4O). We confirmed the patency of vessels ${\\sim}100~\\upmu\\mathrm{m}$ in diameter by optically clearing and reperfusing the multiscale vasculature (Fig. 4P, fig. S14, N to P, and movie S9). \n\nFinally, to demonstrate organ-scale FRESH v2.0 printing capabilities and the potential to engineer larger scaffolds, we printed a neonatalscale human heart from collagen (Fig. 4, $\\mathbf{Q}$ and R, and fig. S15, A to C). To highlight the microscale internal structure, we printed half the heart (Fig. 4S). Structures such as trabeculae were printed from collagen with the same architecture as defined in the G-code file (Fig. 4, T and U). The square-lattice infill pattern within the ventricular walls was similarly well defined (Fig. 4, V and W). We used $\\upmu\\mathrm{CT}$ imaging to confirm reproduction of all the anatomical structures contained within the 3D model of the heart, including the atrial and ventricular chambers, trabeculae, and pulmonary and aortic valves (fig. S15, D to I, and movie S10). \n\nWe have used the human heart for proof of concept; however, FRESH v2.0 printing of collagen is a platform that can build advanced tissue scaffolds for a wide range of organ systems. There are still many challenges to overcome, such as generating the billions of cells required to 3D-bioprint large tissues, achieving manufacturing scale, and creating a regulatory process for clinical translation (23). Although the 3D bioprinting of a fully functional organ is yet to be achieved, we now have the ability to build constructs that start to recapitulate the structural, mechanical, and biological properties of native tissues. \n\n# REFERENCES AND NOTES \n\n1. J. U. Lind et al., Nat. Mater. 16, 303–308 (2017). \n2. X. Ma et al., Proc. Natl. Acad. Sci. U.S.A. 113, 2206–2211 (2016). \n\n3. B. Grigoryan et al., Science 364, 458–464 (2019). \n4. J. S. Miller et al., Nat. Mater. 11, 768–774 (2012). \n5. D. B. Kolesky, K. A. Homan, M. A. Skylar-Scott, J. A. Lewis, Proc. Natl. Acad. Sci. U.S.A. 113, 3179–3184 (2016). \n6. H.-W. Kang et al., Nat. Biotechnol. 34, 312–319 (2016). \n7. T. J. Hinton, A. Lee, A. W. Feinberg, Curr. Opin. Biomed. Eng. 1 31–37 (2017). \n8. N. Noor et al., Adv. Sci. 6, 1900344 (2019). \n9. C. Frantz, K. M. Stewart, V. M. Weaver, J. Cell Sci. 123, 4195–4200 (2010). \n10. K. E. Drzewiecki et al., Langmuir 30, 11204–11211 (2014). \n11. N. Diamantides et al., Biofabrication 9, 034102 (2017). \n12. S. Rhee, J. L. Puetzer, B. N. Mason, C. A. Reinhart-King, L. J. Bonassar, ACS Biomater. Sci. Eng. 2, 1800–1805 (2016). \n13. B. Duan, E. Kapetanovic, L. A. Hockaday, J. T. Butcher, Acta Biomater. 10, 1836–1846 (2014). \n14. K. Pusch, T. J. Hinton, A. W. Feinberg, HardwareX 3, 49–61 (2018). \n15. See supplementary materials. \n16. T. J. Hinton et al., Sci. Adv. 1, e1500758 (2015). \n17. M. Potente, H. Gerhardt, P. Carmeliet, Cell 146, 873–887 (2011). \n18. L. R. Madden et al., Proc. Natl. Acad. Sci. U.S.A. 107, 15211–15216 (2010). \n19. A.-K. Olsson, A. Dimberg, J. Kreuger, L. Claesson-Welsh, Nat. Rev. Mol. Cell Biol. 7, 359–371 (2006). \n20. B. Duan, L. A. Hockaday, K. H. Kang, J. T. Butcher 3rd, J. Biomed. Mater. Res. A 101, 1255–1264 (2013). \n21. H.-G. Lim, G. B. Kim, S. Jeong, Y. J. Kim, Eur. J. Cardiothorac. Surg. 48, 104–113 (2015). \n22. A. Hasan et al., J. Biomech. 47, 1949–1963 (2014). \n23. J. S. Miller, PLOS Biol. 12, e1001882 (2014). \n\n# ACKNOWLEDGMENTS \n\nWe thank D. Trumble and K. Cook for access to and assistance with pulsatile flow setup, Doppler flow velocimetry, and pressure transducer measurements; Y. L. Wang for use of the Form 2 3D printer; S. Sohn for time-lapse imaging of the “CMU” print; and K. Verdelis for assistance with $\\upmu\\mathsf{C T}$ analysis. Funding: Supported by NIH grants DP2HL117750, F32HL142229, and R21HD090679, FDA grant R01FD006582, NSF grant CMMI 1454248, Office of Naval Research grant N00014-17-1-2566, Congressional Directed Medical Research Program grant W81XWH1610018, and the College of Engineering at Carnegie Mellon University under the Bioengineered Organs Initiative and the Manufacturing Futures Initiative. Author contributions: A.L., A.R.H., T.J.H., D.J.S., J.W.T., S.Y., J.M.B., and A.W.F. designed the overall experimental plan; A.L., A.R.H., and T.J.H. developed FRESH v2.0 support material and performed validation experiments; S.Y., J.W.T., and D.J.S. designed experiments and performed FRESH printing and in vivo testing of collagen constructs; A.L., J.M.B., D.J.S., and J.W.T. designed experiments, developed hardware and software, and performed FRESH printing and culture of vascular constructs and ventricles; A.R.H. and T.J.H. designed experiments, developed hardware and software, and performed organ-scale FRESH printing of whole heart, multiscale perfusable vasculature, and tri-leaflet heart valve; and A.L., A.R.H., T.J.H., D.J.S., J.W.T., S.Y., J.M.B., P.G.C., and A.W.F. interpreted data and wrote the manuscript. Competing interests: A.L., A.R.H., T.J.H., and A.W.F. all have an equity stake in FluidForm Inc., which is a startup company commercializing FRESH 3D printing. FRESH 3D printing is the subject of patent protection including U.S. Patent 10,150,258 and others. A.W.F. has an equity stake in Biolife4D Inc. and is a member of its scientific advisory board. Data and materials availability: All data are available in the main text and the supplementary materials. FRESH v2.0 support material is available from A.W.F. under a material agreement with Carnegie Mellon University. The STL files for 3D bioprinter hardware modifications, collagen constructs, and perfusion systems are available under an open-source CC-BY-SA license at https://3dprint.nih.gov/users/awfeinberg. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/365/6452/482/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S15 \nTable S1 \nMovies S1 to S10 \nReferences (24–27) \n3 November 2018; accepted 5 June 2019 \n10.1126/science.aav9051 \n\n# Science \n\n# 3D bioprinting of collagen to rebuild components of the human heart \n\nA. Lee, A. R. Hudson, D. J. Shiwarski, J. W. Tashman, T. J. Hinton, S. Yerneni, J. M. Bliley, P. G. Campbell and A. W Feinberg \n\nScience 365 (6452), 482-487. DOI: 10.1126/science.aav9051 \n\n# If I only had a heart \n\n3D bioprinting is still a fairly new technique that has been limited in terms of resolution and by the materials that can be printed. Lee et al. describe a 3D printing technique to build complex collagen scaffolds for engineering biological tissues (see the Perspective by Dasgupta and Black). Collagen gelation was controlled by modulation of pH and could provide up to 10-micrometer resolution on printing. Cells could be embedded in the collagen or pores could be introduced into the scaffold via embedding of gelatin spheres. The authors demonstrated successful 3D printing of five components of the human heart spanning capillary to full-organ scale, which they validated for tissue and organ function. \n\nScience, this issue p. 482; see also p. 446 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/365/6452/482 \n\nSUPPLEMENTARY MATERIALS \n\nhttp://science.sciencemag.org/content/suppl/2019/07/31/365.6452.482.DC1 \n\nRELATED CONTENT \n\nhttp://science.sciencemag.org/content/sci/365/6452/446.full \n\nREFERENCES \n\nThis article cites 27 articles, 8 of which you can access for free http://science.sciencemag.org/content/365/6452/482#BIBL \n\nPERMISSIONS \n\nhttp://www.sciencemag.org/help/reprints-and-permissions \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41467-018-07850-2", + "DOI": "10.1038/s41467-018-07850-2", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-07850-2", + "Relative Dir Path": "mds/10.1038_s41467-018-07850-2", + "Article Title": "Enhanced oxygen reduction with single-atomic-site iron catalysts for a zinc-air battery and hydrogen-air fuel cell", + "Authors": "Chen, YJ; Ji, SF; Zhao, S; Chen, WX; Dong, JC; Cheong, WC; Shen, RA; Wen, XD; Zheng, LR; Rykov, AI; Cai, SC; Tang, HL; Zhuang, ZB; Chen, C; Peng, Q; Wang, DS; Li, YD", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Efficient, durable and inexpensive electrocatalysts that accelerate sluggish oxygen reduction reaction kinetics and achieve high-performance are highly desirable. Here we develop a strategy to fabricate a catalyst comprised of single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron from a metal-organic framework@polymer composite. The polymer-based coating facilitates the construction of a hollow structure via the Kirkendall effect and electronic modulation of an active metal center by long-range interaction with sulfur and phosphorus. Benefiting from structure functionalities and electronic control of a single-atom iron active center, the catalyst shows a remarkable performance with enhanced kinetics and activity for oxygen reduction in both alkaline and acid media. Moreover, the catalyst shows promise for substitution of expensive platinum to drive the cathodic oxygen reduction reaction in zinc-air batteries and hydrogenair fuel cells.", + "Times Cited, WoS Core": 747, + "Times Cited, All Databases": 774, + "Publication Year": 2018, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000454137600003", + "Markdown": "# Enhanced oxygen reduction with single-atomic-site iron catalysts for a zinc-air battery and hydrogenair fuel cell \n\nYuanjun Chen1, Shufang Ji1, Shu Zhao2, Wenxing Chen1, Juncai Dong 3, Weng-Chon Cheong1, Rongan Shen1, Xiaodong Wen4, Lirong Zheng3, Alexandre I. Rykov5, Shichang Cai6, Haolin Tang6, Zhongbin Zhuang7, Chen Chen1, Qing Peng1, Dingsheng Wang 1 & Yadong Li1 \n\nEfficient, durable and inexpensive electrocatalysts that accelerate sluggish oxygen reduction reaction kinetics and achieve high-performance are highly desirable. Here we develop a strategy to fabricate a catalyst comprised of single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron from a metal-organic framework@polymer composite. The polymer-based coating facilitates the construction of a hollow structure via the Kirkendall effect and electronic modulation of an active metal center by long-range interaction with sulfur and phosphorus. Benefiting from structure functionalities and electronic control of a single-atom iron active center, the catalyst shows a remarkable performance with enhanced kinetics and activity for oxygen reduction in both alkaline and acid media. Moreover, the catalyst shows promise for substitution of expensive platinum to drive the cathodic oxygen reduction reaction in zinc-air batteries and hydrogenair fuel cells. \n\nEfslfiucgieginst fukiel tcieclsl anndd imghe ol-vaeir btaetntteirailes af t leimciattehd biyc has been a bottleneck for the implementation of these energy technologies1–3. Although Pt-based materials have served as the most efficient catalysts for ORR, the high cost and scarcity of precious metal platinum as well as the issue of methanol crossover have motivated the exploration of efficient and durable nonnoble metal catalysts4–9. Among them, metal-nitrogen-carbon (M-N-C) catalysts have been regarded as promising alternatives to $\\mathrm{\\Pt}$ -based materials10–12. However, their catalytic performance is still far from satisfactory, partly because active sites are not primarily and preferentially formed during synthesis13,14. Most synthetic routes to M-N-C catalysts necessitate high-temperature pyrolysis, which often leads to the coexistence of active species and a large amount of less-active metal particles or carbide phases15. Such heterogeneity in structure and composition not only contributes to unsatisfactory performance due to the low number of active sites, but also hinders an in-depth understanding of active sites and further establishment of definitive correlation with catalytic properties13,16,17. \n\nThe performance of catalysts depends on rational design and optimization of their structural and electronic properties. Downsizing active species of $_\\mathrm{M-N-C}$ catalysts to single-atom scale can promote maximum atom-utilization efficiency and make active sites fully exposed, which can enhance intrinsic nature of catalysts18–23. It is well accepted that doping with heteroatoms within the skeleton of a carbon matrix can efficiently improve electronic features and electrical conductivity of catalysts24–29. Modifying the electronic structures of active centers is a powerful approach to enhance catalytic properties30–33; however, it is difficult to achieve merely through introducing heteroatoms due to poor control over dispersion and uniformity of dopant heteroatoms. Constructing hollow structures with hierarchical pore distribution to enhance substrate structure functionalities is another effective approach to boost catalytic performance because it benefits the accessibility of active sites and the mass transport properties34–36. The ORR catalytic efficiency and kinetics are correlated with multiple steps, including the adsorption and activation of substrates, charge transfer, and desorption of products4,37. Remarkable ORR enhancement is difficult to achieve by optimizing only one aspect of a catalyst. Therefore, developing an effective synthetic strategy to preferentially generate uniform and atomically dispersed active sites, and simultaneously achieve electronic modification and structure functionalities is highly desirable but remains challenging. \n\nHere, a novel strategy is developed to construct a functionalized hollow structure from a metal-organic framework (MOF) $@$ polymer via Kirkendall effect and achieve electronic modulation of an active center by near-range coordination with nitrogen and long-range interaction with sulfur and phosphorus. The designed catalyst comprised of single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron (Fe-SAs/NPS-HC) exhibits superior ORR performance in alkaline media with a positive half-wave potential $(E_{1/2})$ of 0.912 V vs. reversible hydrogen electrode (RHE), the highest kinetic current density $(J_{\\mathrm{k}})$ of $\\bar{7}1.9\\mathrm{mV}\\mathrm{cm}^{-2}$ at $0.85\\mathrm{V}$ , and a Tafel slope of $36\\mathrm{mV}\\mathrm{dec}^{-1}$ that is record-level among previously reported ORR catalysts, to the best of our knowledge. Outstanding catalytic performance for ORR in acidic media is also achieved in FeSAs/NPS-HC with an $E_{1/2}$ of $0.791\\mathrm{V}$ , which approaches that of the $\\mathrm{Pt/C}$ and surpasses that of most reported nonprecious metal catalysts. Furthermore, it possesses outstanding methanol tolerance and electrochemical stability. The control experiments reveal that the designed hollow structure plays an important role in accelerating ORR kinetics and enhancing performance. Density functional theory (DFT) calculations demonstrate that high efficiency and satisfactory kinetics of Fe-SAs/NPS-HC are attributed to atomic dispersion of N-coordinated Fe and electronic effects from the surrounding S and $\\mathrm{\\DeltaP}$ atoms, which can donate electrons to single-atom Fe centers to make the charge of Fe $(\\mathrm{Fe}^{\\delta+})$ less positive to weaken the binding of adsorbed OH species. Moreover, $Z\\mathrm{n}$ -air battery and $\\mathrm{H}_{2}$ -air fuel cell tests demonstrate that FeSAs/NPS-HC exhibits competitive performance compared with $\\mathrm{Pt/C,}$ suggesting its potential application in energy storage and conversion devices. \n\n# Results \n\nSynthesis and characterization. The synthetic route for Fe-SAs/ NPS-HC is illustrated in Fig. 1a. The monomers of poly(cyclotriphospazene-co- $^{4,4^{\\prime}}$ -sulfonyldiphenol) (PZS) and iron precursors were mixed with a zeolitic imidazolate framework (ZIF-8) to form ZIF-8/Fe@PZS core-shell composites via polymerization. A transmission electron microscopy (TEM) image (Fig. 1b) shows that ZIF-8/Fe@PZS sample displays a polyhedral morphology with uniform size. A high-resolution TEM (HRTEM) image of ZIF-8/Fe@PZS reveals that PZS is uniformly coated on the surface of ZIF-8 with shell thickness of $20\\mathrm{nm}$ (inset of Fig. 1b). As observed in energy-dispersive spectroscopy (EDS) mappings, Fe, C, N, P, and S elements are uniformly distributed throughout the entire coating layer (Supplementary Figure 1). The final catalyst Fe-SAs/NPS-HC was obtained by pyrolyzing ZIF-8/Fe@PZS at $900^{\\circ}\\mathrm{C}$ in Ar. \n\nTEM and high angle annular dark field scanning TEM (HADDF-STEM) images show that Fe-SAs/NPS-HC has a uniform hollow morphology (Fig. 1c, d). The hierarchical porous structure of Fe-SAs/NPS-HC is revealed by the pore-size distribution plots (Supplementary Figure 2). A powder $\\mathrm{\\DeltaX}$ -ray diffraction (PXRD) pattern of Fe-SAs/NPS-HC shows one broad peak at about $25^{\\circ}$ (2θ) assigned to graphitic carbon and no obvious signals for metallic Fe species are detected (Supplementary Figure 3). The content of Fe is determined as $1.54\\mathrm{wt\\%}$ by inductively coupled plasma optical emission spectrometry (ICPOES). The homogeneous spatial distribution of Fe, C, N, P, and S elements throughout the entire hollow shell is evidenced by EDS mappings (Fig. 1e). Furthermore, atomic dispersion of Fe is directly observed and confirmed by aberration-corrected HAADF-STEM (AC HAADF-STEM) analysis (Fig. 1f, g), which shows some individual bright dots (marked with yellow circles), corresponding to isolated single Fe atoms. \n\nThe binding states of C, N, P, and S in Fe-SAs/NPS-HC were investigated by X-ray photoelectron spectroscopy (XPS) in Supplementary Figure 4. The C 1s spectrum can be deconvoluted into four peaks at the binding energy of 288.3, 285.6, 284.5, and $284.8\\mathrm{eV}$ , corresponding to C−N, $\\mathsf{C}\\mathrm{-}\\mathsf{P}$ , C−S, and $\\mathrm{C}=\\mathrm{C},$ respectively (Supplementary Figure 4a). The $\\mathrm{~N~}$ 1s spectrum reveals the coexistence of four types of nitrogen species, pyridinic N $(398.7\\mathrm{eV})$ , pyrrolic N $(400.3\\mathrm{eV})$ , graphitic N $(401.3\\mathrm{eV})$ and pyridinic $\\mathrm{N^{+}{-}O^{-}}$ $(403.7\\mathrm{eV})$ (Supplementary Figure 4b). The $\\mathrm{~P~}2p$ spectrum displays two peaks located at 132.8 and $133.9\\mathrm{eV}$ , indexing to $\\mathsf{P{\\mathrm{-}}C}$ and $\\mathrm{P\\mathrm{-}O}$ (Supplementary Figure 4c). Supplementary Figure 4d shows that the $\\mathrm{~S~}2p$ spectrum can fit well with three peaks at 164.0, 165.2, and $168.3\\mathrm{eV}$ , assigned to $2p3/2$ , $2p1/2$ splitting of the $\\ensuremath{\\mathrm{~S~}}2p$ spin orbital $(-\\mathrm{C}-\\mathrm{S}-\\mathrm{C}-)$ and oxidized S, respectively. \n\nFormation process of functionalized hollow structure. To understand the formation mechanism of the hollow structure of FeSAs/NPS-HC, a series of control experiments were carried out. Firstly, we investigated the effect of the PZS shell layer. As verified by thermogravimetric analysis in Supplementary Figure 5, the onset of decomposition of ZIF-8/Fe@PZS occurs at about $400^{\\circ}\\mathrm{C},$ which is lower compared with that of pure ZIF-8 at $550^{\\circ}\\mathrm{C}$ This result reveals the PZS layer can induce decomposition of ZIF-8, as further confirmed by the obviously different degrees of attenuation of characteristic XRD peaks of ZIF-8 (Supplementary Figure 6). Furthermore, the designed sample ZIF-8/Fe@PZM was synthesized by the same preparation process as for ZIF-8/Fe@PZS except for changing $^{4,4^{\\prime}}$ -sulfonyldiphenol into bis(4-aminophenyl) ether (see details), where no S element is contained. Single iron atomic sites supported on nitrogen and phosphorus co-doped carbon polyhedron (Fe-SAs/NP-C) and nitrogen-doped carbon (N-C) catalysts were obtained by pyrolysis of ZIF-8/Fe@PZM and ZIF-8. As shown in Supplementary Figure 7, the morphology of Fe-SAs/ NP-C and N-C is similar with a porous solid structure, indicating the critical role of sulfur for the formation of the hollow structure. Finally, we collected and characterized the intermediates at different pyrolysis stages at 400, 500 and $600^{\\circ}\\mathrm{C}$ to track the evolutionary trajectory of hollow structure, as schematically illustrated in Fig. 2a based on TEM observations (Fig. 2b–d). At the pyrolysis temperature of $400^{\\circ}\\mathrm{C},$ the plane surfaces of ZIF-8 of ZIF $-8/\\mathrm{Fe@PZS}$ are partially etched (Fig. 2b), leading to the emergence of concave morphology with rough and shrinking surfaces, while their edges still maintain pristine structure. By pyrolysis at $500^{\\circ}\\mathrm{C},$ the surfaces and interior region of ZIF-8 are further removed away and the framework structure with hollow interior and interconnecting edges is formed, as evidenced by TEM image in Fig. 2c. The construction of framework provides a support to prevent the collapse and fracture of shell layers during the evolution process of hollow structure. Then, the edges of ZIF-8 are gradually etched out and thick hollow structure is obtained at $600^{\\circ}\\mathrm{C}$ (Fig. 2d). To more clearly display the morphology and spatial distribution of elements, the corresponding HAADF-STEM images and EDS mappings in various stages are shown in Fig. 2e–g, which strongly supports the above analysis. This process may follow the Kirkendall effect38. $S^{2-}$ ion from PZS shell induces decomposition of ZIF-8 for releasing $Z\\mathrm{n}^{2+}$ ion. Because of smaller ionic radius of $Z\\mathrm{n}^{2+}$ ion compared with $S^{2-}$ ion, the outward spread of $\\mathrm{Zn}^{2+}$ ion is faster than the inward transport of $S^{2-}$ . Then, the continuous unequal interdiffusion of the $\\S^{2-}$ ion and $Z\\mathrm{n}^{2+}$ ion in the interface of ZIF-8 core and PZS shell results in the emergence of Kirkendall voids. As Kirkendall effect process goes on, the inner ZIF-8 gradually decomposes and forms a thick hollow shell structure. When the pyrolysis temperature continues to be elevated and maintains at $900^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ , residual Zn in thick hollow shell vaporizes and escapes, resulting in the construction of final hollow structure of Fe-SAs/NPS-HC. \n\n![](images/5af85d7988e045e1ab2b57146627d054e0ea445144cc8e4a497b16b1057a9f83.jpg) \nFig. 1 Synthesis and structural characterizations. a Illustration of preparation process of single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron (Fe-SAs/NPS-HC). b Transmission electron microscopy (TEM) image of Fe-SAs/NPS-HC predecessor, marked as zeolitic imidazolate framework-8 (ZIF-8)/Fe@poly(cyclotriphospazene-co- $4,4^{\\prime}$ -sulfonyldiphenol) (PZS). Scale bar, $2\\upmu\\mathrm{m}$ . Inset: high-resolution TEM (HRTEM) image of ZIF-8/Fe $\\ @\\mathsf{P}Z\\mathsf{S}$ , indicating that the thickness of the PZS shell is approximately $20\\mathsf{n m}$ ; scale bar, 100 nm. c TEM image of Fe-SAs/NPSHC. Scale bar, $500\\mathsf{n m}$ . d High angle annular dark field scanning TEM (HAADF-STEM) image of Fe-SAs/NPS-HC. Scale bar, $200\\mathsf{n m}$ . e The enlarged HAADF-STEM image and corresponding element maps (Fe: yellow, C: blue, N: cyan, S: orange, P: green). Scale bar, $100\\mathsf{n m}$ . f, g Aberration-corrected (AC) HAADF-STEM image and enlarged image of Fe-SAs/NPS-HC catalyst. Scale bar, 5 nm (f); 1 nm (g) \n\nAtomic structure analysis. To investigate the local structure of Fe-SAs/NPS-HC, X-ray absorption fine structure (XAFS) measurements were performed. As shown in Fig. 3a, the absorption edge of X-ray absorption near-edge structure (XANES) spectroscopy of Fe-SAs/NPS-HC is situated between those of Fe foil and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ reference, elucidating that isolated Fe atoms carry partially positive charges (Supplementary Figure 8). As shown in Fig. 3b, the Fourier transform (FT) curve of extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) of Fe-SAs/ NPS-HC only presents $\\mathrm{Fe-N}$ coordination with a peak at about ${\\sim}1.5\\mathrm{\\AA}$ (without phase correction) and an Fe−Fe path at ${\\sim}2.2\\mathrm{\\AA}$ is not detected, which clearly indicates that Fe atoms are atomically dispersed and stabilized by nitrogen. Furthermore, wavelet transform (WT) analysis was carried out, which can discriminate the backscattering atoms and provide powerful resolution in $k$ space and $R$ space39. As shown in Fig. 3c, the WT contour plot of Fe-SAs/NPS-HC exhibits only one intensity maximum at approximately $4.2\\mathring\\mathrm{A}^{-1}$ , ascribed to Fe−N contribution. And no intensity maximum indexed to Fe−Fe coordination can be observed compared with the WT contour plot of Fe foil in Fig. 3c. The above results well confirm that Fe species exist as isolated atoms in Fe-SAs/NPS-HC. \n\nIn order to further confirm the Fe state of Fe-SAs/NPS-HC, we performed Mössbauer spectroscopy measurements, which reveal the spectra with isomer shift (IS) of $\\mathrm{Fe}^{3+}$ or low/intermediate spin state of $\\mathrm{Fe}^{2+}$ . Mössbauer spectra of Fe-SAs/NPS-HC at $292\\mathrm{K}$ and at $78\\mathrm{K}$ are presented in Supplementary Figure 9, and the corresponding hyperfine parameters are listed in Supplementary Table 1. The room temperature (RT) spectra are clearly of relaxational nature revealed by slowly decaying wings (Supplementary Figure $9\\mathrm{a}$ ). From the RT-spectra fitted with a single asymmetric component, implying either magnetic Blume40 or electron-hopping relaxation mechanisms41, the average IS of 0.48 and $0.45\\mathrm{min}\\mathrm{s}^{-1}$ could be determined, which are clearly higher than the IS of high-spin $\\mathrm{Fe}^{3+}$ . Measurements at $78\\mathrm{K}$ revealed indeed the absence of high-spin $\\mathrm{Fe}^{3+}$ (Supplementary Figure 9b). Two magnetic sextet subspectra evolved at $78\\mathrm{K}$ from the relaxational RT-spectra were assigned to $\\mathrm{Fe}^{\\mathrm{III}}\\mathrm{N}_{4}~\\left(S=1/2\\right)$ and $\\mathrm{Fe^{II}N_{4}}$ $(S=1)$ ) species identified by the hyperfine fields $(B_{\\mathrm{hf}})$ of 10.5(1) T and 17.3(1) T, respectively, according to the general rule for the saturation fields $B^{\\mathrm{sat}}{}_{\\mathrm{hf}}/S\\approx20\\ \\AA^{.}$ T. Ferromagnetic ordering in the dilute system of $S=1/2$ and $S=1$ species below Curie temperature $(T_{\\mathrm{C}})$ of $215\\mathrm{K}$ was observed in the temperature dependence of magnetic susceptibility (Supplementary Figure 10) measured at the applied field of $1\\mathrm{kOe}$ and in $\\mathrm{M-H}$ loops at 2, 77 and $300\\mathrm{K}$ (Supplementary Figure 11). Supplementary Figure 12 shows indeed that the measured $B_{\\mathrm{hf}}$ are close to saturation $B_{\\mathrm{sat}}$ (at 0 K). A minor $(20\\%)$ doublet species was identified with lowspin $\\mathrm{Fe}^{2+}$ , because the signal from single-atom dispersed diamagnetic $S=0$ species may only experience the line broadening, but not Zeeman splitting below $T_{\\mathrm{C}}$ . The average oxidation state of Fe in Fe-SAs/NPS-HC is near $+2.5$ . The axial orientations of both fields $B_{\\mathrm{hf}}$ (parallel to $\\begin{array}{r}{\\mathrm{Vzz}}\\end{array}$ reveal that only $\\mathrm{Fe^{III}N_{4}}$ and $\\mathrm{Fe^{II}N_{4}}$ species are confirmed, and no other Fe-related phases (such as Fe, $\\mathrm{Fe}_{x}\\mathrm{C},$ $\\mathrm{Fe}_{x}S,$ and $\\mathrm{Fe}_{x}\\mathrm{P}_{\\mathrm{\\scriptscriptstyle.}}$ ) are detected, indicating that isolated Fe atoms are only coordinated by $\\mathrm{\\DeltaN}$ atoms, consistent with the XAFS analysis. \n\nAccording to the EXAFS fitting curve in Fig. 3d and fitting parameters in Supplementary Table 2, the best-fitting results clearly demonstrate that the first shell peak at $1.5\\mathring\\mathrm{A}$ is ascribed to isolated Fe atoms coordinated four N atoms as $\\mathrm{Fe-N_{4}}$ structure in comparison with the fitting results for Fe foil and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ (Supplementary Figures 13 and 14). Based on the hyperfine parameters of Mössbauer spectra and the best-fitting EXAFS results as well as the element content analysis by XPS (Supplementary Figure 15), DFT calculations were used to construct and optimize the structural model of Fe-SAs/NPS-HC (Fig. 3e). \n\nElectrocatalytic performance. To evaluate ORR performance of the as-prepared catalysts, rotating disk electrode (RDE) measurements in $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{M}$ KOH were carried out. As indicated by the linear sweep voltammetry (LSV) tests in Fig. 4a, Fe-SAs/NPS-HC exhibits superior ORR activity with a more positive half-wave $(E_{1/2})$ potential of $0.912\\mathrm{V}$ than that of the state-of-art commercial $\\mathrm{Pt/C}$ $(E_{1/2},0.840\\mathrm{V})$ . As shown in Fig. 4b, the kinetic current density $\\left(J_{\\mathrm{k}}\\right)$ of $71.9\\mathrm{mA}\\mathrm{cm}^{-2}$ at $0.85\\mathrm{V}$ for FeSAs/NPS-HC is a record value, to the best of our knowledge, and is higher than that of $\\mathrm{Pt/C}$ $(4.78\\mathrm{mA}\\mathrm{cm}^{-2},$ by a factor of 15. Strikingly, the better ORR kinetics of Fe-SAs/NPS-HC is further confirmed by a smaller Tafel slope of $36\\mathrm{mV}\\mathrm{dec}^{-1}$ compared with that of $\\mathrm{Pt/C}$ $(70\\mathrm{mV}\\mathrm{dec}^{-1}),$ . As listed in Supplementary Table 3, the ORR activity and kinetics of Fe-SAs/NPS-HC outperform most of the reported nonprecious catalysts, suggesting Fe-SAs/NPS-HC is one of the best ORR electrocatalysts to date. For comparison, the iron-free N, P, S co-doped hollow carbon polyhedron (NPS-HC) catalyst was synthesized (see details and Supplementary Figure 16) and exhibits significantly lower ORR performance. To investigate the effect of the hollow structure, we prepared N, P, S co-doped solid carbon polyhedron with isolated Fe atomic sites (Fe-SAs/NPS-C) catalyst (see details and Supplementary Figure 17). The as-prepared Fe-SAs/NPS-C exhibits apparently degraded ORR activity with a negatively shifted $E_{1/2}$ of $0.894\\mathrm{mV}$ , which is $18\\mathrm{mV}$ lower than Fe-SAs/NPS-HC (Fig. 4a). The slower ORR kinetics in Fe-SAs/NPS-C is revealed by smaller $J_{\\mathrm{k}}$ $(34.6\\operatorname{mA}\\mathrm{cm}^{-2}$ at 0.85 V) and larger Tafel slope $(51\\mathrm{mV}\\mathrm{dec^{-1}}),$ ) (Fig. 4b, c). These results demonstrate the construction of hollow structure can efficiently improve ORR activity and accelerate ORR kinetics. As shown in Supplementary Figure 18, the electrochemical double-layer capacitance $\\mathrm{(C_{dl})}$ of Fe-SAs/NPS-HC \n\n![](images/681673f7f33cd2fb04dc167054165a8a0e989c2ced5f78f40cd0771cac489b33.jpg) \nFig. 2 The formation process of functionalized hollow structure. a Schematic illustration of evolutionary trajectory of hollow structure. b–d Transmission electron microscopy (TEM) images, scale bar, $200\\mathsf{n m},$ and $\\e-\\mathbf{g}$ the corresponding energy-dispersive spectroscopy (EDS) element maps (Fe: yellow, C: blue, N: cyan, S: orange, P: green) at different pyrolysis temperatures of 400, 500, and $600^{\\circ}\\mathsf C$ for 30 min with a heating rate of $5^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ under flowing Ar atmosphere, respectively, scale bar: 100 nm \n\n1 $117.5\\mathrm{mFcm}^{-2}.$ ) is higher than that of Fe-SAs/NPS-C $(72.3\\mathrm{mF}$ $c\\mathrm{m}^{-2},$ ) and NPS-HC $(\\bar{6}4.9\\mathrm{mF}\\mathrm{cm}^{-2},$ ), suggesting Fe-SAs/NPS-HC possesses a larger electrochemically active surface area (ESCA). The Nyquist plots of electrochemical impedance spectroscopy (EIS) demonstrate that Fe-SAs/NPS-HC exhibits a much smaller semicircle diameter than $\\mathrm{Pt/C}$ and other reference catalysts, which represents a lower charge transfer resistance for $\\mathrm{Fe-SAs}/$ NPS-HC, consistent with its more favorable charge transfer process (Fig. 4d). \n\nTo assess ORR pathway of Fe-SAs/NPS-HC, the RDE measurements at various rotation rates were carried out (Fig. 4e). The nearly parallel Koutecky−Levich $\\left(\\mathrm{K-L}\\right)$ plots (inset of Fig. 4e) indicate the first-order reaction kinetics toward the concentration of dissolved oxygen. According to the $\\mathrm{K-L}$ equation, the electron-transfer number $(n)$ is calculated to be in the range $3.96-3.99$ over the whole potential range, approaching the theoretical value of 4 for the $4\\mathrm{e}^{-}$ ORR process (Supplementary Figure 19). Moreover, rotating ring disk electrode (RRDE) tests reveal $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield of Fe-SAs/NPS-HC remains below $4.2\\ \\%$ in the potential range $0.3\\mathrm{-}0.9\\:\\mathrm{V}$ (Fig. 4f), corresponding to a high electron-transfer number of 3.90–4.00. For comparison, the $n$ value of 3.93–4.00 is achieved for the $\\mathrm{Pt/C}$ These results confirm Fe-SAs/NPS-HC undergoes a high-efficiency catalytic process via a $4\\mathrm{e}^{-}$ ORR pathway. Unlike the Pt/C, Fe-SAs/NPS-HC exhibits outstanding tolerance to methanol crossover (Fig. $4\\mathrm{g}$ and Supplementary Figure 20). As shown in Fig. 4h, no obvious decay in $E_{1/2}$ is detected after 5000 cycles, indicating the excellent stability of Fe-SAs/NPS-HC. Furthermore, the detailed characterization of the used catalyst after durability test demonstrates atomic dispersion of iron atoms still remains (Supplementary Figures 21 to 24). \n\nFe-SAs/NPS-HC also exhibits outstanding ORR performance in acidic media (Supplementary Figure 25). By RDE measurements in $0.5{\\bf M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}{\\mathrm{;}}$ an excellent ORR activity with an $E_{1/2}$ of $0.791\\mathrm{V}$ is observed in Fe-SAs/NPS-HC, which approaches that of the commercial $\\mathrm{Pt/C}$ (0.800 V), and is much better than those of Fe-SAs/NPS-C and NPS-HC (Supplementary Figure 25a,b). The favorable ORR kinetics of Fe-SAs/NPS-HC is verified by higher $J_{\\mathrm{k}}$ of $18.8\\mathrm{mA}\\mathrm{cm}^{-2}$ and lower Tafel slope of $54\\mathrm{mV}\\mathrm{dec}^{-1}$ compared to $\\mathrm{Pt/C}$ and Fe-SAs/NPS-C and NPS-HC (Supplementary Figure 25c). As shown in Supplementary Table 4, the ORR performance of Fe-SAs/NPS-HC surpasses that of most reported nonprecious metal ORR electrocatalysts. RRDE measurements demonstrate that Fe-SAs/NPS-HC exhibits a low $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield below $2.8\\%$ with a high electron-transfer number of 3.95, suggesting its high-efficiency $4\\mathrm{e}^{-}$ ORR pathway (Supplementary Figure 25d and Supplementary Figure 26). The accelerated durability test reveals Fe-SAs/NPS-HC shows an outstanding stability with a little negative $E_{1/2}$ shift of $5\\mathrm{mV}$ after 5000 cycles (Supplementary Figure 25e). Moreover, Fe-SAs/NPS-HC has a superior tolerance to carbon monoxide and methanol crossover compared to $\\mathrm{Pt/C}$ (Supplementary Figure 25f and Supplementary Figure 27). \n\n![](images/d1081adeb70c8461e00c29d9fe746d19ea97d26a4af6631c89ffeef6f62939c6.jpg) \nFig. 3 Atomic structural analysis. a, b Fe $K$ -edge X-ray absorption near-edge structure (XANES) spectra (a) and Fe $K$ -edge $k^{3}$ -weighted Fourier transform (FT) spectra (b) of single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron (Fe-SAs/NPS-HC), $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ and Fe foil samples, respectively. c Wavelet transform (WT) of Fe-SAs/NPS-HC in comparison with $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ and Fe foil samples, respectively. d The corresponding extended X-ray absorption fine structure (EXAFS) R space fitting curves; inset: The corresponding EXAFS $k$ space fitting curves of $\\mathsf{F e-S A s/}$ $N P S-H C$ . e Schematic model of Fe-SAs/NPS-HC, Fe (orange), N (blue), P (green), S (yellow) and C (gray) \n\nTo investigate the effect of composition on ORR performance, iron-based single-atom catalysts with different content of Fe were prepared (Supplementary Figure 28 and Supplementary Table 5). As shown in Supplementary Figure 29, as the content of Fe increases, the corresponding ORR polarization curves gradually positively shifted and the values of $\\boldsymbol{E}_{1/2}$ gradually increase, suggesting enhanced ORR activity is attributed to the increase of the amount of Fe in catalysts. The rising $J_{\\mathrm{k}}$ and decreasing Tafel slope indicate that the crucial role of Fe component in accelerating ORR kinetics. The similar results are verified in acidic ORR tests. With the increase of the content of Fe, the ORR activity and kinetics are gradually enhanced in term of better $\\boldsymbol{E}_{1/2}$ , higher $J_{\\mathbf{k}}$ and smaller Tafel slope. These results suggest that Fe component as isolated atoms plays the key role in ORR performance in both alkaline and acidic media. To further reinforce the above conclusion, control experiments are designed and performed. It is known that $\\mathsf{S C N^{-}}$ ion has a strong affinity for Fe and can poison $\\mathrm{Fe-N_{4}}$ coordination in catalyzing $\\mathrm{ORR}^{4\\dot{2}}$ . When 0.01 M KSCN is added in $\\mathrm{O}_{2}$ -saturated $0.5\\dot{\\mathrm{M}}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}.$ the onset potential and half-wave potential exhibit obviously negative shifts, along with the visible decrease of diffuse-limited current (Supplementary Figure 30a). Then we rinsed this electrode with water and re-measured it in $0.1\\mathrm{~M~O~}_{2}$ -saturated KOH. It can be seen that ORR polarization curve gradually recovers to the pristine level as the LSV tests go on, which is ascribed to the recovery of the blocked $\\mathrm{Fe-N_{4}}$ sites owing to the dissociation of $\\mathsf{S C N^{-}}$ ion on the Fe active centers in 0.1 M KOH (Supplementary Figure 30b). These results unambiguously reveal that Fe component is essential to display outstanding ORR performance. \n\nMoreover, we carried out in situ XAFS to investigate the electronic structure of active sites under ORR operating conditions. As shown in Fig. 4i, the Fe $K$ -edge XANES curves of Fe-SAs/NPS-HC demonstrate the potential-dependent change in the oxidation states of Fe. The Fe $K$ -edge XANES of in situ electrode above the onset potential at $1.0\\mathrm{V}$ is similar to that of ex situ electrode, suggesting the excellent stability of active sites in electrolyte. With the applied potential from 1.0 to $0.3\\mathrm{V}$ to increase ORR current density, the Fe $K\\cdot$ -edge XANES shifts toward lower energy, indicating the oxidation state of Fe species gradually decreases. The in situ XAFS analysis clearly reveals that ORR performance closely correlates with the electronic structure of active sites. \n\n![](images/9f0501b2aed37cfd80ff6f0e7e97cea2452cf99a8109ee7f35a7532bdb6e06f1.jpg) \nFig. 4 Electrocatalytic oxygen reduction reaction performance. a Oxygen reduction reaction (ORR) polarization curves for single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron (Fe-SAs/NPS-HC), N, P, S co-doped solid carbon polyhedron with isolated Fe atomic sites (Fe-SAs/NPS-C), iron-free N, P, S co-doped hollow carbon polyhedron (NPS-HC) and $20\\%$ Pt/C. b Comparison of $J_{\\mathrm{k}}$ at $0.85\\vee$ and $E_{1/2}$ of Fe-SAs/NPS-HC and the corresponding reference catalysts. c The Tafel plots for Fe-SAs/NPS-HC and the corresponding reference catalysts. d Nyquist plots of electrochemical impedance spectroscopy (EIS) over Fe-SAs/NPS-HC, Fe-SAs/NPS-C, NPS-HC and $20\\%$ Pt/C catalysts in $0.1{\\ensuremath{M}}$ KOH. e The ORR polarization curves at different rotating rates of Fe-SAs/NPS-HC (inset: K−L plots and electron-transfer numbers). f Electron-transfer number $(n)$ (top) and $H_{2}O_{2}$ yield (bottom) vs. potential. g Cyclic voltammetry (CV) data for Fe-SAs/NPS-HC in $\\mathsf{O}_{2}$ -saturated $0.1M\\mathsf{K O H}$ without and with $1.0{\\ensuremath{\\mathsf{M}}}$ $C H_{3}O H$ . h ORR polarization curves of Fe-SAs/NPS-HC before and after 5000 cycles. i Fe $K$ -edge X-ray absorption near-edge structure (XANES) spectra of Fe-SAs/NPS-HC at various potentials during ORR catalysis in $\\mathsf{O}_{2}$ -saturated 0.1 M KOH (inset: the enlarged Fe $K$ -edge XANES spectra) \n\nElectronic control effect. To understand the nature of excellent ORR reactivity kinetics of Fe-SAs/NPS-HC, DFT calculations were carried out to investigate the free energetics of four-electron ORR reaction mechanism. To investigate the synergistic effects of nonmetal dopants, N-doped single-atom Fe sample (Fe-SAs/NC), N, P co-doped single-atom Fe sample (Fe-SAs/NP-C), and N, P, S co-doped single-atom Fe sample (Fe-SAs/NPS-C) are considered; the free energy diagrams are presented in Fig. 5a. The optimized structures of different doped types of single-atomic-site Fe catalysts and the structures of the corresponding adsorbed intermediates are shown in Supplementary Figures 31 and 32. Among these three catalysts, all the intermediates have the strongest binding energy on Fe-SAs/N-C, followed by $_{\\mathrm{Fe-SAs}/}$ NP-C, while Fe-SAs/NPS-C has the weakest binding energy for the intermediates. On Fe-SAs/N-C, the last step is endothermic by $0.13\\mathrm{eV}_{:}$ indicating that too strong binding of $\\mathrm{OH^{*}}$ intermediate makes it not easy to be removed to produce $\\mathrm{OH^{-}}$ . On Fe-SAs/NP-C, the first three electron-transfer steps are exothermic, while the last step is almost thermo-neutral $\\bar{(}-0.02\\mathrm{eV})$ . All reaction steps are down-hilled in the $4\\mathrm{e}^{-}$ reduction path on FeSAs/NPS-C, suggesting ORR process is more thermodynamically favorable on Fe-SAs/NPS-C. As shown in Fig. 5a, when the electrode potential $U=1.0\\mathrm{V}$ vs. RHE (i.e. $U=0.23\\:\\mathrm{V}$ vs. normal hydrogen electrode (NHE) at ${\\mathrm{pH}}=13{\\mathrm{,}}$ is applied on ${\\mathrm{Fe-SAs}}/$ NPS-C, all the elementary steps become thermo-neutral, except the second one $(\\mathrm{OOH^{*}+O H^{-}+H_{2}O}(l)+3\\mathrm{e^{-}\\rightarrow O^{*}+2O H^{-}+}$ $\\mathrm{H}_{2}\\mathrm{O}(l)+2\\mathrm{e}^{-})$ , which is exothermic by $-0.91\\mathrm{eV}$ . On the contrary, on both Fe-SAs/N-C and Fe-SAs/NP-C catalysts, the last two electrochemical steps become relatively strong endothermic (Supplementary Figure 33) at $U^{\\mathrm{RHE}}=1.0\\dot{\\mathrm{V}}$ , therefore slowing down the whole reaction kinetics. This result suggests that FeSAs/N-C and Fe-SAs/NP-C exhibit less reactivity and lower kinetics than Fe-SAs/NPS-C. According to the free energetics (Supplementary Tables 6–8), the rate-determining step on FeSAs/N-C and Fe-SAs/NP-C is the final electrochemical step, which is correlated with $\\mathrm{OH^{*}}$ binding energy. Therefore, a weakening of the ${\\mathrm{OH^{*}}}$ binding is expected to improve the ORR activity and kinetics43. The charge density differences (Fig. 5b–d) and Bader charge (Fig. 5e) analysis revealed that the electron donation from the surrounding sulfur and phosphorus can make the charge of metal center Fe $(\\mathrm{Fe}^{\\delta+})$ of Fe-SAs/NPS-C become less positive, resulting in a less intense combination with $\\mathrm{OH^{*}}$ . As shown in Fig. 5e, it is well demonstrated that as the Bader charge of the single-atom $\\mathrm{Fe}^{\\delta+}$ decreases, the $\\mathrm{OH^{*}}$ binding energy decreases linearly. Thus, Fe-SAs/NPS-C has a better $\\mathrm{^{\\infty}4e^{-}}$ reduction” catalytic performance and kinetics. The calculated free energy diagram on different doped types of Fe-SAs samples at $1.23{\\dot{\\mathrm{V}}}$ (thermodynamic equilibrium potential) was presented in Supplementary Figure 34. The result is consistent with the results of computation at the $U^{\\mathrm{RHE}}=0\\mathrm{V}$ and $1.0\\mathrm{V}$ vs. RHE at the pH $=13$ condition. Based on the above analysis, the proposed reaction pathway has been demonstrated in Supplementary Figure 35. The catalytic properties of these three catalysts under acidic conditions are similar to that under alkaline conditions. At $U=$ $1.23\\mathrm{V}$ , the first two reduction steps on Fe-SAs/N-C are exothermic, and the last two steps are endothermic by 0.48 and 0.59 $\\mathrm{eV}$ , respectively (Supplementary Figures 36 and 37). When P and S are doped, only the second step $\\mathrm{\\bar{(OOH^{*}+3H^{+}+3e^{-}\\to O^{*}+}}$ $2\\mathrm{H}^{+}+\\bar{\\mathrm{H}}_{2}\\mathrm{O}\\left(l\\right)+2\\mathrm{e}^{-})$ is exothermic, while the other three steps are endothermic. On Fe-SAs/NPS-C, the last two steps are endothermic by 0.23 and $0.27\\mathrm{eV}$ , respectively, which are smaller than Fe-SAs/N-C and Fe-SAs/NP-C, indicating that the ORR process of Fe-SAs/NPS-C is thermodynamically favorable. \n\n![](images/df3b64e14bc8cd43e421940c29d0fc4469dd24de3b39fc1a8b50aa04ad83b403.jpg) \nFig. 5 Electronic control effect. a Free energy diagram of the oxygen reduction reaction (ORR) on single-atom iron (Fe-SAs)/nitrogen-doped carbon (N-C), Fe-SAs/nitrogen, phosphorus co-doped carbon (NP-C) and Fe-SAs/nitrogen, phosphorus, sulfur co-doped carbon (NPS-C) $(U^{\\mathsf{R H E}}=U^{\\mathsf{N H E}}+0.0591\\mathsf{\\Omega}_{\\mathsf{H}}$ H; $U^{\\mathsf{R H E}}=0\\`$ V, $\\begin{array}{r}{U^{\\mathsf{N H E}}=-0.77\\mathsf{V};}\\end{array}$ $U^{\\mathsf{R H E}}=1\\vee$ , $U^{\\mathsf{N H E}}=0.23\\vee)$ . b−d Calculated charge density differences of Fe-SAs/N-C (b), Fe-SAs/NP-C (c), and ${\\mathsf{F e-S A s/}}$ NPS-C (d). Yellow and blue areas represent charge density increase and reduction, respectively. The cutoff of the density-difference isosurfaces is equal to 0.01 electrons $\\mathbb{A}^{-3}$ . (C: gray, N: blue, Fe: orange, S: yellow, P: green). e Linear relationship between ${\\mathsf{O H}}^{\\star}$ binding energy and Bader charge of single-atom iron in Fe-SAs/N-C, Fe-SAs/NP-C and Fe-SAs/NPS-C, respectively. Insets: The corresponding schematic models of samples, Fe (orange), N (blue), P (green), S (yellow) and C (gray). f, g Comparison of $J_{\\mathrm{k}}$ at $0.85\\vee$ and $\\bar{E}_{1/2}$ (f) and the Tafel plots $\\mathbf{\\sigma}(\\mathbf{g})$ for Fe-SAs/N-C, Fe-SAs/NP-C, Fe-SAs/NPS-C, and single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron (Fe-SAs/NPS-HC) \n\nTo further confirm that modulating the electronic properties of metal center by the doping of S, P atoms enables optimization of ORR kinetics and activity, we designed the control samples and evaluated their ORR performance. As shown in Fig. 5f and Supplementary Figure 38, the doping of heteroatoms leads to different degree of enhancement of ORR activity in view of $E_{1/2}$ : N-doped Fe-SAs/N-C $(0.870\\mathrm{V})<\\mathrm{N}$ , $\\mathrm{~\\bf~P~}$ co-doped Fe-SAs/NP-C $(0.881\\mathrm{V})<\\mathrm{N},$ , P, S co-doped Fe-SAs/NPS-C (0.894 V). Regarding the ORR kinetics, Fe-SAs/NPS-C exhibit higher $J_{\\mathrm{k}}$ of $34.6\\mathrm{m}\\mathrm{\\check{A}}\\mathrm{cm}^{-\\check{2}}$ at $0.85\\mathrm{V}$ than those of Fe-SAs/NP-C $(19.7\\mathrm{mA}\\mathrm{cm}^{-2})$ and ${\\mathrm{Fe}}{\\mathrm{-}}S{\\mathrm{A}}s/$ N-C $(11.7\\mathrm{mA}\\mathrm{cm}^{-2}.$ ). The better ORR kinetics of Fe-SAs/NPS-C is further confirmed by smaller Tafel slope of $51\\mathrm{mV}\\mathrm{dec}^{-1}$ compared with $\\mathrm{Fe-SAs/NP-C}$ $\\dot{(54\\mathrm{mV}\\mathrm{dec}^{-1},}$ ) and Fe-SAs/N-C $(59\\mathrm{mV}\\dot{\\mathrm{dec}}^{-1}\\dot{\\phantom{0}},$ ) (Fig. 5g). This strategy of electronic modulation of active center also applies to boost acidic ORR performance. As shown in Supplementary Figures 39 and 40, the N, P, S co-doped Fe-SAs/NPS-C exhibits obvious enhancement in activity with more positive $E_{1/2}$ of $0.764\\mathrm{V}$ compared with N-doped Fe-SAs/N-C $\\left(0.666\\mathrm{V}\\right)$ and N, P co-doped Fe-SAs/NP-C $(0.725\\mathrm{V})$ along with higher $J_{\\mathrm{k}}$ and better Tafel slope compared with Fe-SAs/N-C and Fe-SAs/NP-C. The above experimental observations are in agreement with the DFT results. It is worth mentioning that further strengthened ORR performance is observed over Fe-SAs/NPS-HC, which is attributed to its multiple advantages in synergistically improving ORR activity and kinetics. The larger electrochemically active surface area can expose more active sites and promote the adsorption and activation of ORR-relevant species on Fe-SAs/NPS-HC (Supplementary Figure 18). The lower charge transfer resistance is conducive to enhancing the efficiency of charge transfer (Supplementary Figure 41). The unique structure with atomically dispersed Fe $\\mathrm{-N_{4}}$ sites and electronic control effect from the surrounding S and P atoms contribute to improving the intrinsic activity of active sites, leading to enhanced reaction efficiency of ORR-relevant species on Fe-SAs/NPS-HC, as supported by its higher mass activity (MA) and turnover frequency (TOF) compared with other previously reported non-noble single-atom catalysts (Supplementary Table 9). The hollow structure functionalities with hierarchical porous of Fe-SAs/ NPS-HC improve the accessibility of active sites and facilitate mass transport properties3,44. \n\nZinc-air battery and hydrogen-air fuel cell performance. To assess the potential application of Fe-SAs/NPS-HC in energy storage and conversion devices, the Zn-air battery was assembled by applying Fe-SAs/NPS-HC as the air cathode and zinc foil as the anode with 6 M KOH electrolyte. For comparison, the $Z\\mathrm{n}$ -air battery by using $20\\mathrm{wt\\%}$ $\\mathrm{Pt/C}$ as the air cathode was also made and tested in an identical condition. As shown in Fig. 6a, the FeSAs/NPS-HC-based battery exhibits a higher open circuit voltage of $1.45\\mathrm{V}$ compared with the $\\mathrm{Pt/C}$ -based battery, suggesting the Fe-SAs/NPS-HC-based battery can output higher voltage. The maximum power density of Fe-SAs/NPS-HC-based battery achieves as high as $195.0\\operatorname*{mW}{\\mathrm{cm}^{-2}}$ with a high current density of $375\\mathrm{mAcm}^{-2}$ (Fig. 6b). Both power density and current density of Fe-SAs/NPS-HC-based battery outperforms that of $\\mathrm{Pt/C}$ -based battery $(177.7\\mathrm{mW}\\mathrm{cm}^{-2}$ , $283\\mathrm{m}\\mathrm{\\dot{A}}\\mathrm{cm}\\bar{-}2$ ). The rechargeability and cyclic durability of catalysts are of great significance for the practical applications of $Z\\mathrm{n}$ -air battery. As shown in Fig. 6c, FeSAs/NPS-HC-based battery exhibits an initial charge potential of $2.07\\mathrm{V}$ and a discharge potential of $1.11\\mathrm{V}$ . Obviously, Fe-SAs/ NPS-HC-based battery delivers a lower charge−discharge voltage gap compared with the $\\mathrm{Pt/C}$ -based battery, indicating the better rechargeability of Fe-SAs/NPS-HC-based battery. Unlike the $\\mathrm{Pt}/\\$ C-based battery with obvious voltage change, Fe-SAs/NPS-HCbased battery exhibits the negligible variation in voltage after 500 charging/discharging cycle tests with $200{,}000{\\mathrm{~s}}.$ suggesting the outstanding long-term durability. \n\nMoreover, we exploited Fe-SAs/NPS-HC catalyst as a cathode to evaluate its performance in acidic proton exchange membrane fuel cells (PEMFCs). The Fe-SAs/NPS-HC-based membrane electrode assembly (MEA) was measured under realistic fuel cell operations with the cathode operated on air. Figure 6d shows the polarization and power density curves of PEMFCs at the testing temperature of $60^{\\circ}\\mathrm{C}$ . Fe-SAs/NPS-HC-based MEA exhibits a remarkable current density of ${\\sim}50\\mathrm{mAcm}^{-2}$ at $0.8\\mathrm{V}$ which is comparable to the highest current density of $75\\mathrm{mAcm}^{-2}$ reported to date3. The maximum power density of ${\\mathrm{Fe-SAs}}/$ NPS-HC-based MEA is $333\\mathrm{mW}\\mathrm{cm}{\\bar{-2}}$ at $0.41\\mathrm{V}$ , which is ${\\sim}92\\%$ the power density of the commercial $\\mathrm{Pt/C}$ -based MEA under identical test conditions. When testing at $80^{\\circ}\\mathrm{C}$ , Fe-SAs/NPS-HCbased MEA reaches a high power density of $400\\mathrm{mW}\\mathrm{cm}^{-2}$ at $0.40\\mathrm{V}$ , approaching that of the commercial $\\mathrm{Pt/C}$ -based MEA (Supplementary Figure 42). The fuel cells performance of ${\\mathrm{Fe-}}S{\\mathrm{A}}s/$ NPS-HC-based MEA is compared favorably to that of most reported $\\mathrm{\\Pt}$ -free catalysts (Supplementary Table 10), which is attributed to its unique structure functionalities with hierarchically porous property and highly active single Fe atomic sites. These results demonstrate that Fe-SAs/NPS-HC catalyst holds great promise in the application of PEMFC devices and $Z\\mathrm{n}$ -air batteries. The mass production of catalysts is highly desirable for further commercial application. Indeed, our synthetic method is easily scaled up to grams of Fe-SAs/NPS-HC (Supplementary Figure 43). Furthermore, we extended our synthetic method to other metal single-atom catalysts and discovered the generality of our synthetic method (Supplementary Figures 44–47). \n\n# Discussion \n\nIn summary, we develop a novel $\\operatorname{MOF}@$ polymer strategy to fabricate an Fe-SAs/NPS-HC catalyst. Benefiting from a rational, optimized protocol via structure functionalities and electronic control of single iron atomic sites, Fe-SAs/NPS-HC accelerates sluggish ORR kinetics and achieves excellent ORR performance in both alkaline and acidic media. Moreover, Fe-SAs/NPS-HC exhibits great promise for $Z\\mathrm{n}$ -air battery and $\\mathrm{H}_{2}$ -air fuel cell devices. The vital role of the hollow structure for enhanced kinetics is disclosed by the experiments. DFT calculations reveal atomic dispersion of Fe coordinated by N atoms and an electronic effect from surrounding S and $\\mathrm{~\\bf~P~}$ atoms that contributes to high efficiency and satisfactory kinetics for ORR. This work provides a successful paradigm to strengthen catalytic kinetics and activity via structure functionalities and electronic control of active sites, which may be extended to the design and optimization of other catalysts with high efficiency. \n\n# Methods \n\nCatalyst preparation. Typically, for the synthesis of ZIF-8, $\\mathrm{Zn(NO_{3})_{2}{\\cdot}6H_{2}O}$ $(2.380\\mathrm{g},8\\mathrm{mmol})$ was dissolved in $60~\\mathrm{mL}$ mixture solvent of $N,N$ -dimethylformamide $(36~\\mathrm{mL})$ , ethyl alcohol $(12\\mathrm{mL})$ , and methanol $(12{\\mathrm{mL}})$ . Subsequently, 2- methylimidazole $(2.627\\mathrm{g}$ , 32 mmol), dissolved in the mixture solvent of N,Ndimethylformamide $(12\\mathrm{mL})$ and methanol $(8\\mathrm{mL})$ , was added into the above solution with vigorous stirring for $24\\mathrm{h}$ at room temperature. The as-obtained ZIF8 product was centrifuged and washed with methanol for twice and finally dried at $80^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . Then, for the synthesis of ZIF- ${\\cdot}8/\\mathrm{Fe}@\\mathrm{P}Z S$ bis(4-hydroxyphenyl) sulfone $(325\\mathrm{mg})$ and phosphonitrilic chloride trimer $\\mathrm{152mg}$ were dissolved in $100~\\mathrm{mL}$ of methanol, marked as solution A. Then, the as-obtained powder of ZIF-8 $\\langle400\\mathrm{mg}\\rangle$ was dispersed in methanol $\\mathrm{(40~mL)}$ , followed by injecting $1.73\\mathrm{mL}$ methanol solution of iron (III) nitrate nonahydrate $(10\\mathrm{mg}\\mathrm{mL}^{-1}$ ). Subsequently, the dispersion and $N,N.$ -diethylethanamine $(1\\mathrm{mL})$ ) were respectively added into the solution A, following by stirring for $15\\mathrm{h}$ . The resulting precipitate marked as ZIF$8/\\mathrm{Fe@PZS}$ was collected, washed and finally dried in vacuum at $80~^{\\circ}\\mathrm{C}$ for $12\\mathrm{{h}}$ . ZIF$8@\\mathrm{PZS}$ was prepared with the same synthesis procedure of ZIF-8/Fe@PZS except that iron (III) nitrate nonahydrate was not added. ZIF-8/Fe was prepared with the same synthesis procedure of ZIF-8/Fe@PZS except that $3.50\\mathrm{mL}$ methanol solution of iron (III) nitrate nonahydrate $(10\\mathrm{mg}\\mathrm{mL}^{-1}$ ) was used and solution A and $N,N-$ diethylethanamine (1 mL) were not added. ZIF-8/Fe@PZM was prepared following the above synthesis procedure of ZIF- $8/\\mathrm{Fe@PZS}$ except that bis(4-hydroxyphenyl) sulfone $(325\\mathrm{mg})$ was replaced by bis(4-aminophenyl) ether $320\\mathrm{mg}$ . The obtained powders of ZIF-8/Fe@PZS, ZIF- ${\\cdot}8@\\mathrm{PZS}.$ ZIF-8/Fe, and ZIF-8/Fe@PZM were placed in quartz boat, respectively, and then maintained at $900^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ in a tube furnace with a heating rate of $5^{\\circ}\\dot{\\mathrm{C}}\\operatorname*{min}^{-1}$ under flowing Ar atmosphere. When these samples cooled to room temperature, the as-prepared samples, Fe-SAs/NPS-HC, NPS-HC, Fe-SAs/N-C, and Fe-SAs/NP-C, were respectively collected and without any treatment for further use. In addition, for the synthesis of Fe-SAs/NPS-C, the obtained powder of Fe-SAs/NP-C ( $25\\mathrm{mg}$ ) was fully mixed with bis(4- \n\n![](images/40e31e1d0cf8e4b0701c2f6e9e26c29a64691c674c8e760478083f486783f1d4.jpg) \nFig. 6 Zinc-air battery and hydrogen-air fuel cell performances. a The open circuit voltage curves of $Z n$ -air batteries by applying single iron atomic sites supported on a nitrogen, phosphorus and sulfur co-doped hollow carbon polyhedron (Fe-SAs/NPS-HC) and $20\\upnu\\up t\\%$ Pt/C as the air cathode catalyst, respectively. b Discharging polarization curves and the corresponding power density plots of Fe-SAs/NPS-HC-based and $20\\upnu\\up t\\%$ $\\mathsf{P t/C}$ -based $Z n$ -air batteries. c Charge−discharge cycling performance of Fe-SAs/NPS-HC-based and $20\\mathrm{wt\\%}$ Pt/C-based Zn-air batteries. d ${\\sf H}_{2}$ -air fuel cell polarization curves and power density plots of membrane electrode assemblies (MEAs) using $F e-S A s/N P S-H C$ (loading of $0.8\\mathsf{m g c m}^{-2}.$ ) and $20\\mathrm{wt\\%}\\mathsf{P t/C}$ (loading of $0.8\\mathsf{m g c m}^{-2},$ ) as cathode catalysts, respectively. Membrane Nafion 211, cell $60^{\\circ}\\mathsf C,$ electrode area $5\\mathsf{c m}^{2}$ \n\nhydroxyphenyl) sulfone $(16\\mathrm{mg})$ and then placed in quartz boat and maintained at $800^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ in a tube furnace under flowing Ar atmosphere, and the as-prepared sample was collected and without any treatment for further use. The synthesis of other Fe-SAs/NPS-HC samples with different Fe loadings are the same as that of Fe-SAs/NPS-HC except that the one-eighth of iron precursor, one-quarter of iron precursor, half of iron precursor, and double iron precursor are used, respectively, which are denoted as Fe-SAs/NPS-HC-1/8, Fe-SAs/NPS-HC-1/4, Fe-SAs/NPS-HC1/2, and Fe-SAs/NPS-HC-2. Various $\\mathrm{M{-}S A s{/}N P S{-}H C}$ catalysts $\\mathbf{M}=\\mathbf{Ni},$ Cu, Ru, Ir) were synthesized through similar synthetic procedures, just by employing other metal precursors $\\mathrm{(Ni(NO_{3})_{2}{\\cdot}6H_{2}O}$ , $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ , $\\mathrm{RuCl}_{3}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{IrCl}_{4}^{\\cdot}$ ) to replace iron precursor. \n\nCharacterization. The crystalline structure and phase purity were assessed using PXRD (Rigaku RU-200b with $\\mathrm{Cu}\\ \\mathrm{Ka}$ radiation $(\\bar{\\lambda}=1.\\bar{5}406\\mathrm{~\\dot{A})}$ ). XPS experiments were performed on a ULVAC PHI Quantera microscope. The sizes and morphologies of samples were obtained on a Hitachi H-800 TEM. The highresolution TEM and elemental mappings were collected on a JEOL JEM-2100F with electron acceleration energy of $200\\mathrm{kV}$ . HAADF-STEM images were measured by using a JEOL 200F transmission electron microscope operated at $200\\mathrm{keV}$ , equipped with a probe spherical aberration corrector. TGA was carried out using a Q5000. $\\mathrm{N}_{2}$ adsorption−desorption measurements were performed at $77\\mathrm{K}$ on a Quantachrome SI-MP Instrument. The metal concentrations of the samples were measured by ICP-OES (Optima 7300 DV). 57Fe Mössbauer spectra were recorded at room temperature and at $78\\mathrm{K}$ with a conventional constant-acceleration spectrometer using a $^{57}\\mathrm{Co}(\\mathrm{Rh})$ source. Doppler velocity and isomer shift (IS) were calibrated by metallic $\\mathfrak{a}$ -Fe foil. The XAFS spectra at Fe $K.$ -edge was acquired at 1W1B station in Beijing Synchrotron Radiation Facility (BSRF, operated at $2.5\\mathrm{GeV}$ with a maximum current of $250\\mathrm{mA}$ ). The data of Fe-SAs/NPS-HC sample were recorded in fluorescence excitation mode using a Lytle detector. Fe foil and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ were used as references and measured in a transmission mode using ionization chamber. The detailed ex situ XAFS and in situ XAFS analysis were given in Supplementary Information. \n\nElectrochemical measurement. All the measurements were performed on a CHI 760E electrochemical station (CH Instruments, Inc., Shanghai) with a standard three-electrode system in 0.1 M KOH and 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte, respectively. To prepare a homogeneous dispersion, $5\\mathrm{mg}$ catalyst samples (Fe-SAs/NPS-HC, NPSHC) were dispersed in $1\\mathrm{mL}$ of a mixture containing ethanol $(0.495\\mathrm{mL})$ ), water $(0.495\\mathrm{mL}$ , and $0.5\\mathrm{wt\\%}$ Nafion solution $(10\\upmu\\mathrm{L})$ , followed by sonicated for $^{\\textrm{1h}}$ to form a homogeneous catalyst ink. For Fe-SAs/N-C, Fe-SAs/NP-C, and Fe-SAs/ NPS-C, a certain amount of samples was prepared and dispersed in $1\\mathrm{mL}$ of the above mixture solution to make the corresponding catalyst inks with the same Fe content as Fe-SAs/NPS-HC. One milligram of the commercial $20\\mathrm{wt\\%\\Pt/C}$ was used to obtain catalyst ink. Then $20\\upmu\\mathrm{L}$ of the catalyst suspension was pipetted onto a fresh glassy carbon (GC) electrode surface. A rotating disk electrode (RDE) with a GC disk $\\mathrm{\\Delta}5\\mathrm{mm}$ in diameter) and a rotating ring-disk electrode (RRDE) with a Pt ring ( $6.5\\mathrm{mm}$ inner diameter and $8.5\\mathrm{mm}$ outer diameter) and a GC disk of $5.5\\mathrm{mm}$ diameter were used as the substrate for the working electrode. $\\mathrm{\\Ag/AgCl}$ (saturated KCl solution) was used as reference and graphite rod as a counter electrode. The cyclic voltammetry (CV) tests were measured in $\\mathrm{N}_{2}.$ and $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{{M}}$ KOH solution or $0.5{\\bf M}$ ${\\mathrm{\\mathrm{H}}}_{2}{\\mathrm{SO}}_{4}$ with a sweep rate of $50\\mathrm{mVs^{-1}}$ . RDE/RRDE tests were carried out in an $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{M}$ KOH solution or $0.5{\\bf M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ with $\\mathrm{O}_{2}$ purging with a scan rate of $10\\mathrm{mVs^{-1}}$ at different rotation rates. LSV polarization curves were obtained via RDE tests at a rotating speed of $1600\\mathrm{rpm}$ . The ESCA of catalyst is estimated from electrochemical double-layer capacitance $\\left(C_{\\mathrm{dl}}\\right)$ , which is obtained by measuring double-layer charging from the CVs at different scan rates in non-Faradaic potential range in $0.1\\mathrm{{M}}$ KOH. The linear slope of charging current vs. the scan rate represents $C_{\\mathrm{dl}}$ . EIS was measured in the frequency range from $10^{6}$ to $0.01\\mathrm{Hz}$ . The long-term durability was measured by the accelerated durability test with continuously cycling between 0.6 and $1.0\\mathrm{V}$ (vs. RHE) in $\\mathrm{O}_{2}$ - saturated $0.1\\mathrm{{M}}$ KOH or $0.5{\\mathrm{M}}{}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ . To test the tolerance to CO poisoning, chronoamperometric measurements at $0.45\\mathrm{V}$ vs. RHE in a $\\mathrm{O}_{2}$ -saturated mixed solution containing $0.5{\\bf M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ along with the injection of CO were performed. In this test process, CO gas (flow $50\\mathrm{mLs^{-1}}$ ) was purged through the GC surface at the time of $300s$ and removed at the time of $600s,$ followed by injection of $\\mathrm{O}_{2}$ gas (flow $100\\mathrm{mLs^{-1}}$ ) for the removal of CO gas. To test the tolerance to $\\mathrm{CH}_{3}\\mathrm{OH}$ , chronoamperometric measurements at $0.45\\mathrm{V}$ vs. RHE in a $\\mathrm{O}_{2}$ -saturated mixed solution containing $0.5{\\mathrm{M}}{}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ along with the injection of $\\mathrm{CH}_{3}\\mathrm{OH}$ were performed. In this test process, $\\mathrm{CH_{3}O H}$ $\\mathrm{\\Delta}5\\mathrm{mL})$ was added into the 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ (125 mL) at the time of $250s$ . All the potentials reported in this work were converted to the RHE. The detailed analysis was given in Supplementary Information. \n\nHydrogen-air fuel cell measurements. Membrane: Nafion211. MEA: 1 g catalysts were mixed with $10\\mathrm{mL}$ deionized water under vigorous stirring. Then $75\\mathrm{mL}$ Nafion 520 PFSA $5\\mathrm{wt\\%}$ in isopropyl alcohol, EW\\~790, Dupont) solution was added to the mixture, followed by ultrasonic treatment for $30\\mathrm{min}$ and a high-speed homogenizer $(20,000\\mathrm{rpm})$ for $^{\\textrm{1h}}$ to form catalyst slurry. Then the catalyst slurry was applied to PTFE thin film by spraying; after drying at $60^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ followed with at $90^{\\circ}\\mathrm{C}$ in $\\Nu_{2}$ atmosphere for $3\\mathrm{min}$ , the catalyst layer was then transferred onto the membrane at $130^{\\circ}\\mathrm{C}$ and 5 MPa by the decal method to form the catalyst-coated membrane (CCM). The GDL (Toray TGP-H-060) was placed on the anode and cathode side of the CCM to form the MEA. Catalyst loading: Sample $\\#1$ , $0.8\\mathrm{mg}\\mathrm{cm}^{-2}$ (Pt) $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%Pt/C})$ in cathode and $0.15\\mathrm{{\\dot{m}g}}\\mathrm{{cm}}^{-2}$ (Pt) $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%Pt/C})$ in anode. Sample $\\#2$ , $0.8\\mathrm{mg}\\mathrm{cm}^{-2}$ (total) the Fe-SAs/NPS-HC catalyst in cathode and $0.15\\mathrm{mg}\\mathrm{cm}\\dot{^{-2}}$ (Pt) $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%Pt/C})$ in anode. Single cell performance: The fuel cell performance was measured with G50 Fuel Cell Test Station (GreenLight Company) with back pressure of $0.2\\mathrm{MPa}$ (absolute pressure), using $\\mathrm{H}_{2}$ as the fuel and air as the oxidant. The MEA was mounted in a single-cell test fixture with a serpentine flow field and a fuel cell clamp (with an active area of $25c m^{2},$ ). To control the RH of fuel gases, a water vapor saturated at a controlled dew point, was inflow slowly into gas inlet. After the cell activates to a stable value, polarization curves were recorded with the increase in current density regularly. \n\nThe assembled cell having active area of $5\\times5\\mathrm{cm}^{2}$ was operated at $60^{\\circ}\\mathrm{C}$ or $80^{\\circ}\\mathrm{C}$ under relative humidity of $100\\%$ for both anode and cathode. The gas stoichiometry was set to 1.5 for hydrogen in anode and 2.5 for air in cathode. \n\nZinc-air battery measurements. The $Z\\mathrm{n}$ -air battery tests were performed in home-made electrochemical cells. The Fe-SAs/NPS-HC catalyst or the 20 wt% Pt/C catalyst was mixed with acetylene carbon black and polyvinylidene fluoride with the mass ratio of 8:1:1. Next, the mixed slurry was sprayed on the hydrophobic carbon paper uniformly as the air cathode. The mass loading of Fe-SAs/NPS-HC and the $\\mathrm{Pt/C}$ was $1\\mathrm{mg}\\mathrm{cm}^{-2}$ . A polished Zn foil was used as the anode electrode and $6\\mathrm{M}$ KOH with $0.2\\mathbf{M}$ zinc acetate dissolved was prepared as the electrolyte in the measurement. \n\nComputational details. All theoretical calculations were performed using DFT, as implemented in the Vienna ab initio simulation package (VASP)45,46. The electron exchange and correlation energy was treated within the generalized gradient approximation in the Perdew−Burke−Ernzerhof functional (GGA-PBE)47. Iterative solutions of the Kohn–Sham equations were done using a plane-wave basis set defined by a kinetic energy cutoff of $400\\mathrm{eV}$ . The $k$ -point sampling was obtained from the Monkhorst−Pack scheme with a $(2\\times2\\times1)$ mesh. The convergence criteria for the electronic self-consistent iteration and force were set to $10^{-4}\\mathrm{eV}$ and $0.03\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ , respectively. The two-dimensional graphene support was modeled with a $6\\times6$ supercell consisting of 72 carbon sites separated by a vacuum region of $15\\mathrm{\\AA}$ along the direction normal to the sheet plane to avoid strong interactions between two adjacent layers. Two neighboring carbon atoms were removed to anchor an Fe atom, and four of carbon atoms were replaced by N atom, forming the $\\mathrm{Fe-N_{4}}$ site. \n\nThe adsorption energies were calculated according to the equation, $E_{\\mathrm{ads}}=E$ (adsorbate/substrate) − [E(substrate) $+E($ (adsorbate)], where E(adsorbate/ substrate), $E$ (substrate), and $E$ (adsorbate) represent the total energy of substrate with adsorbed species, the clean substrate, and the molecule in the gas phase, respectively. The charge density differences were evaluated using the formula $\\Delta\\rho=$ $\\rho_{\\mathrm{A+B-}}\\rho_{\\mathrm{A-}}\\rho_{\\mathrm{B}},$ where $\\rho_{\\mathrm{X}}$ is the electron density of X. Atomic charges were computed using the atom-in-molecule (AIM) scheme proposed by Bader48,49. \n\nThe change in Gibbs free energy $(\\Delta G)$ for all the ORR steps are calculated based on the computational hydrogen electrode method developed by Nørskov et al.50. At standard condition ( $U=0$ , $\\mathrm{\\pH\\0}$ , $p=1$ bar, $\\begin{array}{r}{T=298\\mathrm{K},}\\end{array}$ ), the free energy $\\Delta G_{0}$ is defined as $\\Delta G_{0}=\\Delta E+\\Delta Z\\mathrm{PE}+\\Delta_{0}\\rightarrow_{298\\mathrm{K}}\\Delta H-T\\Delta S,$ , where $\\Delta E$ is the energy change obtained from DFT calculations; ΔZPE, $\\Delta H,$ and ΔS denote the difference in zero point energy, enthalpy, and entropy due to the reaction, respectively. The enthalpy and entropy of the ideal gas molecule were taken from the standard thermodynamic tables51. Therefore, reaction free energy is further calculated by the equation: ΔG ( $\\mathbf{\\partial}U,\\mathbf{pH}$ , $\\begin{array}{r}{p=1}\\end{array}$ bar, $T=298\\mathrm{K})=\\Delta G_{0}+\\Delta G_{\\mathrm{pH}}+\\Delta G_{U},$ where $\\Delta G_{\\mathrm{pH}}$ is the correction of the free energy of $\\mathrm{H^{+}}$ -ions at a $\\mathrm{\\pH}$ different from 0: $\\Delta G_{\\mathrm{pH}}=$ $-k\\mathrm{Tln}[\\mathrm{H}^{+}]=k\\mathrm{Tln}10\\times\\mathrm{pH}$ . $\\Delta G_{U}=-n\\mathrm{e}U;$ , where $U$ is the applied electrode potential, $n$ is the number of electrons transferred. Hence, the equilibrium potential ${\\bar{U}}^{0}$ for ORR at $\\mathrm{pH}=13$ was determined to be $0.462\\mathrm{V}$ (vs. NHE). The free energy of $\\mathrm{O}_{2}(g)$ was derived as $G_{\\mathrm{O2}(g)}=2G_{\\mathrm{H2O}(l)}-2G_{\\mathrm{H2}}+4.92\\:\\mathrm{eV},$ , and the free energy of OH $^-$ was calculated by $G_{\\mathrm{OH-}}=G_{\\mathrm{H2O}(l)}-G_{\\mathrm{H+}}$ . The overall reaction of $\\mathrm{O}_{2}$ reduction to $\\mathrm{OH^{-}}$ in alkaline environment is: $\\mathrm{O}_{2}+2\\mathrm{H}_{2}\\mathrm{O}+4\\mathrm{e}^{-}\\rightarrow4\\mathrm{OH}^{-}$ , which is divided into the following steps4,52: \n\n$$\n\\begin{array}{r l}&{\\mathrm{O}_{2}\\left(g\\right)+2\\mathrm{H}_{2}\\mathrm{O}\\left(l\\right)+4\\mathrm{e}^{-}+^{\\ast}\\rightarrow\\mathrm{OOH}^{\\ast}+\\mathrm{OH}^{-}+\\mathrm{H}_{2}\\mathrm{O}\\left(l\\right)+3\\mathrm{e}^{-}}\\\\ &{\\mathrm{OOH}^{\\ast}+\\mathrm{OH}^{-}+\\mathrm{H}_{2}\\mathrm{O}\\left(l\\right)+3\\mathrm{e}^{-}\\rightarrow\\mathrm{O}^{\\ast}+2\\mathrm{OH}^{-}+\\mathrm{H}_{2}\\mathrm{O}\\left(l\\right)+2\\mathrm{e}^{-}}\\\\ &{\\mathrm{O}^{\\ast}+2\\mathrm{OH}^{-}+\\mathrm{H}_{2}\\mathrm{O}\\left(l\\right)+2\\mathrm{e}^{-}\\rightarrow\\mathrm{OH}^{\\ast}+3\\mathrm{OH}^{-}+\\mathrm{e}^{-}}\\end{array}\n$$ \n\n(4) $\\mathrm{OH^{*}+3O H^{-}+e^{-}\\rightarrow4O H^{-}+^{*}}$ $^*$ indicates the adsorption site. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon request. \n\nReceived: 17 March 2018 Accepted: 30 November 2018 \nPublished online: 21 December 2018 \n\n# References \n\n1. Debe, M. K. Electrocatalyst approaches and challenges for automotive fuel cells. Nature 486, 43–51 (2012). \n2. Mistry, H., Varela, A. S., Kühl, S., Strasser, P. & Cuenya, B. R. Nanostructured electrocatalysts with tunable activity and selectivity. Nat. Rev. Mater. 1, 16009 (2016). \n3. Chung, H. T. et al. Direct atomic-level insight into the active sites of a highperformance PGM-free ORR catalyst. Science 357, 479–484 (2017). \n4. Jiao, Y., Zheng, Y., Jaroniec, M. & Qiao, S. Z. Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions. Chem. Soc. Rev. 44, 2060–2086 (2015). \n5. Li, Y. et al. An oxygen reduction electrocatalyst based on carbon nanotubegraphene complexes. Nat. Nanotechnol. 7, 394–400 (2012). \n6. Yang, W., Liu, X., Yue, X., Jia, J. & Guo, S. Bamboo-like carbon nanotube $/\\mathrm{Fe}_{3}\\mathrm{C}$ nanoparticle hybrids and their highly efficient catalysis for oxygen reduction. J. Am. Chem. Soc. 137, 1436–1439 (2015). \n7. Strickland, K. et al. Highly active oxygen reduction non-platinum group metal electrocatalyst without direct metal-nitrogen coordination. Nat. Commun. 6, 7343 (2015). \n8. Tang, H. et al. Molecular architecture of cobalt porphyrin multilayers on reduced graphene oxide sheets for high-performance oxygen reduction reaction. Angew. Chem. Int. Ed. 52, 5585–5589 (2013). \n9. Chen, Z., Higgins, D., Yu, A., Zhang, L. & Zhang, J. A review on non-precious metal electrocatalysts for PEM fuel cells. Energy Environ. Sci. 4, 3167–3192 (2011). \n10. Jiang, W. J. et al. Understanding the high activity of Fe-N-C electrocatalysts in oxygen reduction: $\\mathrm{Fe}/\\mathrm{Fe}_{3}\\mathrm{C}$ nanoparticles boost the activity of Fe-Nx. J. Am. Chem. Soc. 138, 3570–3578 (2016). \n11. Xia, B. Y. et al. A metal–organic framework-derived bifunctional oxygen electrocatalyst. Nat. Energy 1, 15006 (2016). \n12. Shen, M., Wei, C., Ai, K. & Lu, L. Transition metal–nitrogen–carbon nanostructured catalysts for the oxygen reduction reaction: from mechanistic insights to structural optimization. Nano Res. 10, 1449–1470 (2017). \n13. Kramm, U. I. et al. On an easy way to prepare metal-nitrogen doped carbon with exclusive presence of $\\mathrm{MeN_{4}}$ -type sites active for the ORR. J. Am. Chem. Soc. 138, 635–640 (2016). \n14. Sa, Y. J. et al. A general approach to preferential formation of active Fe-Nx sites in Fe-N/C electrocatalysts for efficient oxygen reduction reaction. J. Am. Chem. Soc. 138, 15046–15056 (2016). \n15. Chung, H. T., Won, J. H. & Zelenay, P. Active and stable carbon nanotube/ nanoparticle composite electrocatalyst for oxygen reduction. Nat. Commun. 4, 1922 (2013). \n16. Zitolo, A. et al. Identification of catalytic sites for oxygen reduction in ironand nitrogen-doped graphene materials. Nat. Mater. 14, 937–942 (2015). \n17. Chen, Y. et al. Isolated single iron atoms anchored on N-doped porous carbon as an efficient electrocatalyst for the oxygen reduction reaction. Angew. Chem. Int. Ed. 56, 6937–6941 (2017). \n18. Yang, X. F. et al. Single-atom catalysts: a new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748 (2013). \n19. Hu, M. et al. $50\\mathrm{ppm}$ of Pd dispersed on $\\mathrm{Ni}(\\mathrm{OH})_{2}$ nanosheets catalyzing semihydrogenation of acetylene with high activity and selectivity. Nano Res. 11, 905–912 (2017). \n20. Zitolo, A. et al. Identification of catalytic sites in cobalt-nitrogen-carbon materials for the oxygen reduction reaction. Nat. Commun. 8, 957 (2017). \n21. Zhu, C., Fu, S., Shi, Q., Du, D. & Lin, Y. Single-atom electrocatalysts. Angew. Chem. Int. Ed. 56, 13944–13960 (2017). \n22. Zhang, L. et al. Graphene defects trap atomic Ni species for hydrogen and oxygen evolution reactions. Chem 4, 285–297 (2018). \n23. Fei, H. et al. General synthesis and definitive structural identification of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n24. Zhang, W., Wu, Z. Y., Jiang, H. L. & Yu, S. H. Nanowire-directed templating synthesis of metal-organic framework nanofibers and their derived porous doped carbon nanofibers for enhanced electrocatalysis. J. Am. Chem. Soc. 136, 14385–14388 (2014). \n25. Wang, Y.-C. et al. S-doping of an Fe/N/C ORR catalyst for polymer electrolyte membrane fuel cells with high power density. Angew. Chem. Int. Ed. 54, \n9907–9910 (2015). \n26. Zhang, J. et al. N,P-codoped carbon networks as efficient metal-free bifunctional catalysts for oxygen reduction and hydrogen evolution reactions. Angew. Chem. Int. Ed. 55, 2230–2234 (2016). \n27. Yan, D. et al. N, P-dual doped carbon with trace Co and rich edge sites as highly efficient electrocatalyst for oxygen reduction reaction. Sci. China Mater. \n61, 679–685 (2017). \n28. Shen, H. et al. Synergistic effects between atomically dispersed Fe-N-C and CS-C for the oxygen reduction reaction in acidic media. Angew. Chem. Int. Ed. \n56, 13800–13804 (2017). \n29. Jia, Y., Chen, J. & Yao, X. Defect electrocatalytic mechanism: concept, topological structure and perspective. Mater. Chem. Front. 2, 1250–1268 (2018). \n30. Yang, M. et al. Catalytically active Au- $\\mathrm{O}(\\mathrm{OH})\\mathbf{x}$ -species stabilized by alkali ions on zeolites and mesoporous oxides. Science 346, 1498–1501 (2014). \n31. Stamenkovic, V. et al. Changing the activity of electrocatalysts for oxygen reduction by tuning the surface electronic structure. Angew. Chem. Int. Ed. 45, \n2897–2901 (2006). \n32. Chen, G. et al. Interfacial electronic effects control the reaction selectivity of platinum catalysts. Nat. Mater. 15, 564–569 (2016). \n33. Zhou, Y. et al. Dopant-induced electron localization drives $\\mathrm{CO}_{2}$ reduction to C2 hydrocarbons. Nat. Chem. 10, 974–980 (2018). \n34. Liang, H. W., Zhuang, X. D., Bruller, S., Feng, X. L. & Mullen, K. Hierarchically porous carbons with optimized nitrogen doping as highly active electrocatalysts for oxygen reduction. Nat. Commun. 5, 4973 (2014). \n35. Tan, Q. et al. Hollow MOx- ${\\mathrm{RuO}}_{2}$ $\\mathbf{\\tilde{M}=C o}$ , Cu, Fe, Ni, CuNi) nanostructures as highly efficient electrodes for supercapacitors. Sci. China Mater. 59, \n323–336 (2016). \n36. He, P., Yu, X.-Y. & Lou, X. W. D. Carbon-incorporated nickel-cobalt mixed metal phosphide nanoboxes with enhanced electrocatalytic activity for oxygen evolution. Angew. Chem. Int. Ed. 56, 3897–3900 (2017). \n37. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: Insights into materials design. Science 355, eaad4998 (2017). \n38. Jin Fan, H. et al. Monocrystalline spinel nanotube fabrication based on the Kirkendall effect. Nat. Mater. 5, 627–631 (2006). \n39. Funke, H., Scheinost, A. C. & Chukalina, M. Wavelet analysis of extended Xray absorption fine structure data. Phys. Rev. B 71, 094110–094117 (2005). \n40. Blume, M. & Tjon, J. A. Mössbauer spectra in a fluctuating environment. Phys. Rev. 165, 446–456 (1968). \n41. Herber, R. H. & Eckert, H. Electron hopping in FeOCl intercalation compounds: a Mössbauer relaxation study. Phys. Rev. B 31, 34–41 (1985). \n42. Thorum, M. S., Hankett, J. M. & Gewirth, A. A. Poisoning the oxygen reduction reaction on carbon-supported Fe and Cu electrocatalysts: evidence for metal-centered activity. J. Phys. Chem. Lett. 2, 295–298 (2011). \n43. Zheng, Y. et al. Rational design of common transition metal-nitrogen-carbon catalysts for oxygen reduction reaction in fuel cells. Nano Energy 30, 443–449 (2016). \n44. Tang, H., Wang, S., Pan, M. & Yuan, R. Porosity-graded micro-porous layers for polymer electrolyte membrane fuel cells. J. Power Sources 166, 41–46 (2007). \n45. Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. \n6, 15–50 (1996). \n46. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n47. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phy. Rev. Lett. 77, 3865–3868 (1996). \n48. Tang, W., Sanville, E. & Henkelman, G. A grid-based Bader analysis algorithm without lattice bias. J. Phys. Condens. Matter 21, 084204–084210 (2009). \n49. Bader, R. F. W. A quantum theory of molecular structure and its applications. Chem. Rev. 91, 893–928 (1991). \n50. Nørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuelcell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n51. Stull, D. R. & Prophet, H. JANAF Thermochemical Tables (U.S. National Bureau of Standards, Washington, DC, 1971). \n52. Jiao, Y., Zheng, Y., Jaroniec, M. & Qiao, S. Z. Origin of the electrocatalytic oxygen reduction activity of graphene-based catalysts: a roadmap to achieve the best performance. J. Am. Chem. Soc. 136, 4394–4403 (2014). \n\n# Acknowledgements \n\nThis work was supported by China Ministry of Science and Technology under Contract of 2016YFA (0202801), and the National Natural Science Foundation of China (21521091, 21390393, U1463202, 21471089, 21671117). We thank Beijing Light Source for use of the instruments. \n\n# Author contributions \n\nY.C. performed the experiments, collected, analyzed the data and wrote the manuscript. S.J. carried out the characterizations of samples, analyzed the data and wrote the manuscript. S.Z. contributed to the computational results and helped to revise the paper. W.C. and J.D. performed XAFS data analysis. W.-C.C. helped to test and analyzed HAADF-STEM results. R.S. and Z.Z. helped to test the catalytic performance and analysis. X.W. provided the resource for DFT calculations. L.Z. helped to perform XAFS measurements of samples. A.I.R. helped to test the Mössbauer spectroscopy measurements and analyze data and also helped to revise the manuscript. S.C. and H.T. helped to test the $Z\\mathrm{n}$ -air battery and $\\mathrm{H}_{2}/\\mathrm{air}$ fuel cell performance and analyze data. C.C. and Q.P. helped to analyze the data and contributed to the revising of the manuscript. D.W. and Y.L. conceived the experiments, planned synthesis, analyzed results, designed the research project and wrote the manuscript. All the authors commented on the manuscript and have given approval to the final version of the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-07850-2. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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" + }, + { + "id": "10.1103_PhysRevLett.122.027001", + "DOI": "10.1103/PhysRevLett.122.027001", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevLett.122.027001", + "Relative Dir Path": "mds/10.1103_PhysRevLett.122.027001", + "Article Title": "Evidence for Superconductivity above 260 K in Lanthanum Superhydride at Megabar Pressures", + "Authors": "Somayazulu, M; Ahart, M; Mishra, AK; Geballe, ZM; Baldini, M; Meng, Y; Struzhkin, VV; Hemley, RJ", + "Source Title": "PHYSICAL REVIEW LETTERS", + "Abstract": "Recent predictions and experimental observations of high T-c superconductivity in hydrogen-rich materials at very high pressures are driving the search for superconductivity in the vicinity of room temperature. We have developed a novel preparation technique that is optimally suited for megabar pressure syntheses of superhydrides using modulated laser heating while maintaining the integrity of sample-probe contacts for electrical transport measurements to 200 GPa. We detail the synthesis and characterization of lanthanum superhydride samples, including four-probe electrical transport measurements that display significant drops in resistivity on cooling up to 260 K and 180-200 GPa, and resistivity transitions at both lower and higher temperatures in other experiments. Additional current-voltage measurements, critical current estimates, and low-temperature x-ray diffraction are also obtained. We suggest that the transitions represent signatures of superconductivity to near room temperature in phases of lanthanum superhydride, in good agreement with density functional structure search and BCS theory calculations.", + "Times Cited, WoS Core": 955, + "Times Cited, All Databases": 1036, + "Publication Year": 2019, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000455687700008", + "Markdown": "# Evidence for Superconductivity above $260\\mathrm{~K~}$ in Lanthanum Superhydride at Megabar Pressures \n\nMaddury Somayazulu,1,\\* Muhtar Ahart,1 Ajay K. Mishra,2,‡ Zachary M. Geballe,2 Maria Baldini,2,§ Yue Meng,3 Viktor V. Struzhkin,2 and Russell J. Hemley1,† 1Institute for Materials Science and Department of Civil and Environmental Engineering, The George Washington University, Washington, DC 20052, USA 2Geophysical Laboratory, Carnegie Institution of Washington, Washington, DC 20015, USA 3HPCAT, X-ray Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA \n\n(Received 23 August 2018; revised manuscript received 3 December 2018; published 14 January 2019) \n\nRecent predictions and experimental observations of high $T_{c}$ superconductivity in hydrogen-rich materials at very high pressures are driving the search for superconductivity in the vicinity of room temperature. We have developed a novel preparation technique that is optimally suited for megabar pressure syntheses of superhydrides using modulated laser heating while maintaining the integrity of sample-probe contacts for electrical transport measurements to $200\\mathrm{GPa}$ . We detail the synthesis and characterization of lanthanum superhydride samples, including four-probe electrical transport measurements that display significant drops in resistivity on cooling up to $260\\mathrm{K}$ and $180{-}200\\mathrm{GPa}$ , and resistivity transitions at both lower and higher temperatures in other experiments. Additional current-voltage measurements, critical current estimates, and low-temperature x-ray diffraction are also obtained. We suggest that the transitions represent signatures of superconductivity to near room temperature in phases of lanthanum superhydride, in good agreement with density functional structure search and BCS theory calculations. \n\nDOI: 10.1103/PhysRevLett.122.027001 \n\nThe search for superconducting metallic hydrogen at very high pressures has long been viewed as a key problem in physics [1,2]. The prediction of very high (e.g., room temperature) $T_{c}$ superconductivity in hydrogen-rich materials [3] has opened new possibilities for realizing high critical temperatures but at experimentally accessible pressures (i.e., below $300\\mathrm{GPa})$ where samples can be characterized with currently available tools. Following the discovery of novel compound formation in the $_\\mathrm{S-H}$ system at modest pressures [4], theoretical calculations predicted that hydrogen sulfide would transform on further compression to a superconductor with a $T_{c}$ up to the $200~\\mathrm{K}$ range [5,6]. High $T_{c}$ of $203\\mathrm{~K~}$ at $150\\mathrm{GPa}$ in samples formed by compression of $\\mathrm{H}_{2}\\mathrm{S}$ was subsequently found [7,8], with x-ray measurements consistent with cubic $\\mathrm{H}_{3}\\mathrm{S}$ as the superconducting phase [9]. \n\nGiven that the higher hydrogen content in many simple hydride materials is predicted to give still higher $T_{c}$ values [3], we have extended our studies to higher hydrides, the socalled superhydrides, $X\\mathrm{H}_{n}$ with $n>6$ . Systematic, theoretical structure search in the La─H and $\\mathrm{Y-H}$ systems reveals numerous hydrogen-rich compounds with strong electronphonon coupling and $T_{c}$ in the neighborhood of room temperature (above $270\\ \\mathrm{K}$ ) [10] (see also Ref. [11]). Of these superhydrides, $\\mathrm{LaH}_{10}$ and $\\mathrm{YH}_{10}$ have a novel clathratetype structure with 32 hydrogen atoms surrounding each La or Yatom, and $T_{c}$ near $270\\mathrm{K}$ at 210 GPa for $\\mathrm{LaH}_{10}$ and $300\\mathrm{K}$ at $250\\ \\mathrm{GPa}$ in $\\mathrm{YH}_{10}$ ; see Ref. [12] for a recent review. Notably, in these phases the $_\\mathrm{H-H}$ distances are ${\\sim}1.1\\mathrm{~\\AA~}$ , which are close to those predicted for solid atomic metallic hydrogen at these pressures [13]. \n\nRecently, our group successfully synthesized a series of superhydrides in the La─H system up to $200\\ \\mathrm{GPa}$ pressures. Specifically, we reported $\\mathbf{X}$ -ray diffraction and optical studies demonstrating that the lanthanum superhydrides can be synthesized. The diffraction reveals that La atoms have a face centered cubic (fcc) lattice at $170~\\mathrm{GPa}$ upon heating to ${\\sim}1000~\\mathrm{K}$ [14], and a structure with compressibility close to that for the predicted cubic metallic phase of $\\mathrm{LaH}_{10}$ . Experimental and theoretical constraints on the hydrogen content give a stoichiometry of $\\mathrm{LaH}_{10\\pm x}$ , where $x$ is between $+2$ and $^{-1}$ [14]. On decompression, the fccbased structure undergoes a rhombohedral distortion of the La sublattice to form a structure that has subsequently been predicted to also have a high $T_{c}$ [13]. Here we report the use of a novel synthesis route for megabar pressure syntheses of such superhydrides using pulsed laser heating and ammonia borane $\\mathrm{(NH_{3}B H_{3}}$ , AB) as the hydrogen source. We detail the synthesis and characterization of several samples of the material using x-ray diffraction and electrical resistance measurements at 180–200 GPa. The transport measurements reveal a clear resistance drop at $260\\mathrm{~K~}$ using four-probe measurements and other experiments. Consistent with low-temperature x-ray diffraction, we infer that the transition is a signature of near room-temperature superconductivity in $\\mathrm{LaH}_{10}$ and not related to any structural transition. \n\n![](images/fb0446ad0dffe03331e1fe35b840c1a9e818440c9a8780a8466f6345f03a45e1.jpg) \nFIG. 1. (a) Schematic of the assembly used for synthesis and subsequent conductivity measurements. The sample chamber consisted of a tungsten outer gasket (W) with an insulating cBN insert (B). The piston diamond (P) was coated with four $1\\mathrm{-}\\mu\\mathrm{m}$ thick Pt electrodes which were pressure-bonded to $25\\mathrm{-}\\mu\\mathrm{m}$ thick Pt electrodes (yellow). The ${5-\\mu\\mathrm{m}}$ thick La sample (red) was placed on the Pt electrodes and packed in with ammonia borane (AB, green). Once the synthesis pressure was reached, single-sided laser heating (L) was used to initiate the dissociation of AB and synthesis of the superhydride. To achieve optimal packing of AB in the gasket hole, we loaded AB with the gasket fixed on the cylinder diamond (C). (b) Optical micrograph of a sample at 178 GPa after laser heating using the above procedure (sample A). \n\nSamples were prepared using a variety of diamond-anvil cells (DACs), depending on the measurement [15]. For the electrical conductivity measurements, we used a multistep process with piston-cylinder DACs [33] (Fig. 1). Composite gaskets consisting of a tungsten outer annulus and a cubic boron nitride epoxy mixture (cBN) insert were employed to contain the sample at megabar pressures while isolating the platinum electrical leads [15]. We synthesized the superhydride from a mixture of La and $\\mathrm{H}_{2}$ loaded in the gasket assembly as in our previous work [14] and found that maintaining good contact between the synthesized material and electrodes is not guaranteed. To overcome this problem, we also used AB as the hydrogen source [34–36]. When completely dehydrogenated, one mole of AB yields three moles of $\\mathrm{H}_{2}$ plus insulating cBN, the latter serving both as a solid pressure medium and support holding the hydride sample firmly against the electrical contacts (Fig. 1). \n\nThe synthesis and structural characterization of samples were carried out in situ at high pressure using a versatile diode-pumped ytterbium fiber laser heating system [37] that was adapted for our experiments. In all runs, we observed very good coupling of the laser with the sample and subsequent sharpening of La diffraction peaks; above $175\\ \\mathrm{GPa}$ and temperatures of $1000{-}1500\\ \\mathrm{K}$ , this resulted in the formation of cubic $\\mathrm{LaH}_{10\\pm x}$ [14]. To complete the transformation but avoid the formation of additional phases [15], we needed to maintain sample temperatures below $1800\\mathrm{K}$ . This was achieved by varying the combination of laser power and pulse width of the heating laser. Typically, we found that a 300-ms pulse and a $30\\mathrm{-}\\mu\\mathrm{m}$ laser spot size resulted in optimal transformation and sample coverage, and minimal anvil or electrode damage. Repeated checks on the two-probe resistance between the four electrodes between heating cycles were performed to ensure that electrodes in a given run were not damaged. \n\n![](images/69cc022275321f60813137d546bdc30b3734c3d998363370e698d376358d81d3.jpg) \nFIG. 2. Synchrotron $\\mathbf{\\boldsymbol{x}}$ -ray diffraction patterns obtained from three samples in which $\\mathrm{LaH}_{10\\pm x}$ was synthesized by laser heating at pressures above 175 GPa. (a) $\\mathrm{\\DeltaX}$ -ray diffraction following laser heating of a mixture of La and $\\mathrm{H}_{2}$ (Au pressure marker); (b,c) results obtained following laser heating of La and $\\mathrm{NH}_{3}\\mathrm{BH}_{3}$ (samples A and C; Pt pressure marker). The data were obtained from three separate runs with an $\\mathbf{X}$ -ray spot size of $5\\times5\\ \\mu\\mathrm{m}$ . In all three panels, the pattern in black is from unreacted La, and that in red is fcc-based $\\mathrm{LaH}_{10\\pm x}$ obtained after laser heating. The sample corresponding to (c) was nominally ${5-\\mu\\mathrm{m}}$ thick and exhibited a high degree of anisotropic stress as indicated by the relative intensities, broadening, and shift of the La peaks prior to the reaction. The diffraction peak marked by the green symbol in (a) is due to residual $\\mathrm{WH}_{\\boldsymbol{x}}$ which forms when $\\mathrm{H}_{2}$ is present. This hydride also gives rise to the tail above 10.5 degrees. $\\mathrm{WH}_{x}$ features are absent in the other two patterns because insulating cBN gaskets were used. Further details are provided in Ref. [15]. \n\n![](images/b41c73bafeaad06de382a4052995a7b6d852d0478ea938e22b1e59050f76fdd3.jpg) \nFIG. 3. Normalized electrical resistance of the $\\mathrm{LaH}_{10\\pm x}$ sample characterized by $\\mathbf{X}$ -ray diffraction and radiography (Figs. 1 and 2) and measured with the four-probe technique (sample A). The initial pressure determined from Raman measurements of the diamond anvil edge was $188\\mathrm{GPa}$ . The lowest resistance we could record was $20\\mu\\Omega$ , whereas the 300-K value was $50~\\mathrm{m}\\Omega$ . The measurements were performed at $10~\\mathrm{mA}$ and $10\\mathrm{kHz}$ ; for further details see Ref. [15]. \n\nRepresentative diffraction patterns of three samples are shown in Fig. 2, including a $\\mathrm{LaH}_{10\\pm x}$ sample that was verified to have the four-probe geometry intact at $188~\\mathrm{GPa}$ [Figs. 1 and 2(c)]. The characteristic diffraction peaks of $\\mathrm{LaH}_{10\\pm x}$ identified previously in synthesis from La and $\\mathrm{H}_{2}$ are observed, demonstrating that the superhydride phase can indeed be synthesized from La and AB using the techniques described above. Further, the results show that synthesis can be carried out while maintaining the electrical leads intact. All the samples for which conductivity data are presented were also characterized by $\\mathbf{X}$ -ray diffraction. \n\nFigure 3 shows electrical resistance measurements as a function of temperature for the sample presented in Fig. 1 at an initial 300-K pressure of 188 GPa. On cooling, the resistance was observed to decrease around $275\\mathrm{~K~}$ and to drop appreciably at $260\\mathrm{K}$ , as first reported in Ref. [38]. The resistance abruptly dropped by ${>}10^{3}$ and remained constant from 253 to $150\\mathrm{~K~}$ . Upon warming, the resistance increased steeply at $245\\mathrm{~K~}$ , indicating the change was reversible but shifted to lower temperature. Upon subsequent warming to $300\\mathrm{K}$ , the pressure was measured to be $196\\mathrm{GPa}$ . Since the pressure was not measured as a function of temperature during thermal cycling, the pressure at which the resistance change occurred was not directly determined. No dependence of the applied current on the transition temperature could be detected in this run, but the sample appeared to degrade with repeated thermal cycling at higher current levels (i.e., $10~\\mathrm{mA}$ ) [15]. \n\n![](images/af5901d594864281a7b54acf104a0e4d841730cdcfc5655818d82ad8a8f681d2.jpg) \nFIG. 4. Electrical resistance measurements using the four-probe technique (sample F). At the lowest current of $0.1\\mathrm{mA}$ , the sample resistance displays an abrupt drop (grey curve, first heating cycle), and the transition temperature decreases with increasing current, as shown for $1\\mathrm{mA}$ (blue curve, third heating cycle) and $10\\ \\mathrm{mA}$ (red curve, fifth heating cycle). The inset shows $I{-}V$ curves obtained from this experiment and compares data measured at $300\\mathrm{K}$ $\\operatorname{inV}$ scale, left axis) and at $180\\mathrm{K}$ $\\mathrm{\\Delta}\\cdot\\mathrm{\\Delta}\\mu\\mathrm{V}$ scale, right axis), well below the transition temperature. These data were obtained in situ on the synchrotron beam line with different instrumentation and data collection protocols compared to the data presented in Fig. 3 (sample A). The flat response for temperatures above the transition reflects the dynamic range setting of the instrument needed for these smaller samples, and there is a lower density of points on the $R–T$ curves; see Ref. [15] for further details. \n\nIn a second four-probe conductivity measurement, we performed the laser heating synthesis, x-ray diffraction, and electrical conductivity in situ on samples in the cryostat on the $\\mathbf{\\boldsymbol{x}}$ -ray beam line. Although these samples were considerably smaller and mixed phase [15], we also more carefully monitored possible changes in transition temperature with applied current and measured the $I{-}V$ characteristics of the material. We observed a 10-K decrease in transition temperature upon increasing the current from $0.1\\ \\mathrm{mA}$ to $1\\mathrm{mA}$ , and it appeared to decrease further at higher currents (Fig. 4). Distinct $I{-}V$ characteristics were observed above and below the transition temperature. The measurements suggest that well into the superconducting phase, $\\mathrm{LaH}_{10\\pm x}$ could exhibit very large critical current densities [15,39]. In this experiment, part of the sample had spread outside the central culet, giving rise to the formation of lower pressure phases with their own transition temperatures. The high transition temperature observed here (resistivity) in several thermal cycles was also obtained from measurements on other samples using pseudo-four-probe geometries (Fig. S4). Further discussion of these experiments is provided in Ref. [15]. \n\nAn alternative explanation for the resistivity change is a temperature-induced, iso-structural electronic transition with a dramatic increase in conductivity in the low-temperature phase. Consistent with our previous optical observations [14], the resistance measurements indicate that the hightemperature phase (i.e., normal state) is a metal, so this would be a metal-metal transition. However, calculations reported to date do not predict such a transition within metallic $\\mathrm{LaH}_{10}$ [10,13]. Nevertheless, low-temperature x-ray diffraction was measured to determine whether the resistance change is due to a temperature-induced structural transition. The $\\mathbf{X}$ -ray diffraction patterns reveal no change in volume, and the available data show no indication of structural changes over the range of temperatures explored [15]. \n\nThe complexity of the experiments prevents us from accurately determining the pressure dependence of the possible superconducting $T_{c}$ . We did not attempt to determine the intrinsic resistivity of the superhydride samples because of their complex geometries, and some of the samples are clearly mixed phase, possibly with varying hydrogen stoichiometry [10,15]. In the three-point (pseudo-four-probe) geometry, the contact resistance plays a major role, and such low resistance values cannot be measured [40,41]. The samples could consist of layers of $\\mathrm{LaH}_{x}$ starting from $x=10$ on the laser heated side and $x<10$ toward the electrodes. The samples could also have a complicated toroidal geometry consisting of a central region of $\\mathrm{LaH}_{10\\pm x}$ with a peripheral ring of untransformed La arising from the need to preserve the electrodes during laser heating and differential thermal heat transport for the sample in contact with the diamond vs the electrodes. Thus, variability in the observed transition temperatures may also arise from a changing network of the superconducting component on thermal cycling as well as the presence of multiple phases produced within a sample as a result of $P-T$ gradients during synthesis [15]. Indeed, after our work was completed, a report appeared of possible $T_{c}$ in lanthanum hydride at $215\\mathrm{K}$ at slightly lower pressure [42], which we suggest may be a signature of another phase [13,15]. \n\nIn summary, we report four-probe, ac resistance measurements on $\\mathrm{LaH}_{10\\pm x}$ synthesized at pressures of $180-$ $200\\ \\mathrm{GPa}$ by a modulated, pulsed laser heating technique that preserves the integrity of multiprobe electrical contacts on the sample after synthesis. Our multiple measurements reveal the signature of superconductivity at temperatures above $260~\\mathrm{K}$ at pressures of $180{-}200~\\mathrm{GPa}$ . The transition temperature is close to that predicted for the superconducting $T_{c}$ based on BCS-type calculations for $\\mathrm{LaH}_{10}$ at comparable pressures. Whereas diamagnetic measurements are needed to confirm the present results, we note the magnitude of the resistance drops repeatedly observed in our experiments is comparable to that observed in previous high-pressure studies where the transition was subsequently found to be correctly identified as signatures of superconductivity by magnetic susceptibility (e.g., Refs. [40,43]). Extending and applying the latter technique for the smaller and more complex superhydride samples is progress. Infrared, optical, and $\\mathbf{X}$ -ray spectroscopy [44,45] would also provide useful characterization, including identifying different superconducting phases and establishing the pressure dependence of $T_{c}$ for each component. A recent report of similar measurements of high $T_{c}$ in lanthanum superhydride samples, including the observation of a decrease in transition temperature in an external magnetic field [46], further validates this discovery of very high $T_{c}$ superconductivity in this system. The results reported here thus provide the first experimental evidence of $T_{c}$ near room temperature, as exhibited in this new class of hydride materials. \n\nWe are grateful to H. Liu, S. Sinogeikin, I. I. Naumov, R. Hoffmann, N. W. Ashcroft, and S. A. Gramsch for their help in many aspects of this work. The authors would like to acknowledge the support of Paul Goldey and honor his memory. This research was supported by EFree, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences (BES), under Award No. DE-SC0001057. The instrumentation and facilities used were supported by DOE/BES (DE-FG02-99ER45775, VVS), the U.S. DOE/ National Nuclear Security Administration (DE-NA0002006, CDAC; and DE-NA0001974, HPCAT), and the National Science Foundation (DMR-1809783). The Advanced Photon Source is operated by the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. \n\n\\*zulu58@gwu.edu †rhemley@gwu.edu ‡Present address: HPPD, Bhabha Atomic Research Center, Mumbai, 400 085, India. §Present address: Fermilab, Batavia, Illinois 60510, USA. \n[1] N. W. Ashcroft, Metallic Hydrogen—A High-Temperature Superconductor, Phys. Rev. Lett. 21, 1748 (1968). \n[2] V. L. Ginzburg, What problems of physics and astrophysics seem now to be especially important and interesting (thirty years later, already on the verge of XXI century)? Phys. Usp. 42, 353 (1999). \n[3] N. W. Ashcroft, Hydrogen Dominant Metallic Alloys: High Temperature Superconductors? Phys. Rev. Lett. 92, 187002 (2004). \n[4] T. A. Strobel, P. Ganesh, M. Somayazulu, P. R. C. Kent, and R. J. Hemley, Novel Cooperative Interactions and Structural Ordering in ${\\mathrm{H}}_{2}{\\mathrm{S}}{-}{\\mathrm{H}}_{2}$ , Phys. Rev. Lett. 107, 255503 (2011). \n[5] Y. Li, J. Hao, H. Liu, Y. Li, and Y. Ma, The metallization and superconductivity of dense hydrogen sulfide, J. Chem. Phys. 140, 174712 (2014). [6] D. Duan, Y. Liu, F. Tian, D. Li, X. Huang, Z. Zhao, H. Yu, B. Liu, W. Tian, and T. Cui, Pressure-induced metallization of dense $(\\mathrm{H}_{2}\\mathrm{S})_{2}\\mathrm{H}_{2}$ with high- $\\mathbf{\\nabla}\\cdot\\boldsymbol{T}_{c}$ superconductivity, Sci. Rep. 4, 6968 (2014). [7] A. P. Drozdov, M. I. Eremets, and I. A. Troyan, Conventional superconductivity at $190~\\mathrm{K}$ at high pressures, arXiv: 1412.0460. [8] A. P. Drozdov, M. I. Eremets, I. A. Troyan, V. Ksenofontov, and S. I. Shylin, Conventional superconductivity at $203{\\mathrm{K}}$ at high pressures, Nature (London) 525, 73 (2015). [9] M. Einaga, M. Sakata, T. Ishikawa, K. Shimizu, M. I. Eremets, A. P. Drozdov, I. A. Troyan, N. Hirao, and Y. Ohishi, Crystal structure of the superconducting phase of sulfur hydride, Nat. Phys. 12, 835 (2016). \n[10] H. Liu, I. I. Naumov, R. Hoffmann, N. W. Ashcroft, and R. J. Hemley, Potential high-superconducting lanthanum and yttrium hydrides at high pressure, Proc. Natl. Acad. Sci. U.S.A. 114, 6990 (2017). \n[11] F. Peng, Y. Sun, C. J. Pickard, R. J. Needs, Q. Wu, and Y. Ma, Hydrogen Clathrate Structures in Rare Earth Hydrides at High Pressures: Possible Route to Room-Temperature $T_{c}$ Superconductivity, Phys. Rev. Lett. 119, 107001 (2017). \n[12] T. Bi, N. Zarifi, T. Terpstra, and E. Zurek, The search for superconductivity in high pressure hydrides, arXiv: 1806.00163. \n[13] H. Liu, I. I. Naumov, Z. M. Geballe, M. Somayazulu, J. S. Tse, and R. J. Hemley, Dynamics and superconductivity in compressed lanthanum superhydride, Phys. Rev. B 98, 100102(R) (2018). \n[14] Z. M. Geballe, H. Liu, A. K. Mishra, M. Ahart, M. Somayazulu, Y. Meng, M. Baldini, and R. J. Hemley, Synthesis and stability of lanthanum superhydrides, Angew. Chem., Int. Ed. 57, 688 (2018). \n[15] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevLett.122.027001 for further details concerning the experimental techniques and results, including Refs. [16–32]. \n[16] A. Dewaele, P. Loubeyre, and M. Mezouar, Equations of state of six metals above 94 GPa, Phys. Rev. B 70, 094112 (2004). \n[17] D. L. Heinz and R. Jeanloz, The equation of state of the gold calibration standard, J. Appl. Phys. 55, 885 (1984). \n[18] M. Somayazulu, Z. M. Geballe, A. K. Mishra, M. Ahart, Y. Meng, and R. J. Hemley, Crystal structures of La to megabar pressures (to be published). \n[19] F. Porsch and W. B. Holzapfel, Novel Reentrant High Pressure Phase Transition in Lanthanum, Phys. Rev. Lett. 70, 4087 (1993). \n[20] G. K. Samudrala, S. A. Thomas, J. M. Montgomery, and Y. K. Vohra, High pressure phase transitions in the rare earth metal erbium to 151 GPa, J. Phys. Condens. Matter 23, 315701 (2011). \n[21] G. K. Samudrala and Y. K. Vohra, Structural properties of lanthanides at ultra high pressure, in Handbook on the Physics and Chemistry of Rare Earths, edited by J. G. Bünzli and V. K. Pecharsky (Elsevier Press, New York, 2013), Vol. 43, pp. 275–319. \n[22] R. J. Husband, I. Loa, K. Munro, and M. I. McMahon, The distorted-fcc phase of samarium, J. Phys. Conf. Ser. 500, 032009 (2014). \n[23] R. Černý, Y. Filinchuk, H. Hagemann, and K. Yvon, Magnesium borohydride: Synthesis and crystal structure, Angew. Chem., Int. Ed. 46, 5765 (2007). \n[24] W. W. Zhan, Q. L. Zhu, and Q. Xu, Dehydrogenation of ammonia borane by metal nanoparticle catalysts, ACS Catal. 6, 6892 (2016). \n[25] L. J. van der Pauw, A method of measuring specific resistivity and Hall effect of discs of arbitrary shape, Philips Res. Rep. 13, 1 (1958). \n[26] R. J. Hemley, M. I. Eremets, and H. K. Mao, Progress in experimental studies of insulator-metal transitions at multimegabar pressures, in Frontiers of High Pressure Research II, edited by H. D. Hochheimer et al. (Kluwer, Amsterdam, 2001), pp. 201–216. \n[27] M. I. Eremets, V. V. Viktor, V. Struzhkin, H. K. Mao, and R. J. Hemley, Exploring superconductivity in low-Z materials at megabar pressures, Physica (Amsterdam) 329–333B, 1312 (2003). \n[28] A. G. Gavriliuk, A. A. Mironovich, and V. V. Struzhkin, Miniature diamond anvil cell for broad range of high pressure measurements, Rev. Sci. Instrum. 80, 043906 (2009). \n[29] Y. A. Timofeev, V. V. Struzhkin, R. J. Hemley, H. K. Mao, and E. A. Gregoryanz, Improved techniques for measurement of superconductivity in diamond anvil cells by magnetic susceptibility, Rev. Sci. Instrum. 73, 371 (2002). \n[30] P. Loubeyre, R. LeToullec, D. Hausermann, M. Hanfland, R. J. Hemley, H. K. Mao, and L. W. Finger, X-ray diffraction and equation of state of hydrogen at megabar pressure, Nature (London) 383, 702 (1996). \n[31] Y. Akahama and H. Kawamura, Pressure calibration of diamond anvil Raman gauge to 310 GPa, J. Appl. Phys. 100, 043516 (2006). \n[32] W. A. Grosshans, Y. K. Vohra, and W. B. Holzapfel, Evidence for a Soft Phonon Mode and a New Structure in Rare-Earth Metals Under Pressure, Phys. Rev. Lett. 49, 1572 (1982). \n[33] H. K. Mao, R. J. Hemley, and A. L. Mao, Recent design of ultrahigh-pressure diamond cell, in High Pressure Science and Technology, edited by S. C. Schmidt et al. (AIP Press, New York, 1994), pp. 1613–1616. \n[34] R. S. Chellappa, M. Somayazulu, V. V. Struzhkin, T. Autrey, and R. J. Hemley, Pressure-induced complexation of $\\mathrm{NH}_{3}\\mathrm{BH}_{3}{\\mathrm{-H}}_{2}$ , J. Chem. Phys. 131, 224515 (2009). \n[35] Y. Song, New perspectives on potential hydrogen storage materials using high pressure, Phys. Chem. Chem. Phys. 15, 14524 (2013). \n[36] R. G. Potter, M. Somayazulu, G. D. Cody, and R. J. Hemley, High pressure equilibria of dimethylamine borane, dihydridobis(dimethylamine)boron(III) tetrahydridoborate(III), and hydrogen, J. Phys. Chem. C 118, 7280 (2014). \n[37] Y. Meng, G. Shen, and H. K. Mao, Double-sided laser heating system at HPCAT for in situ x-ray diffraction at high pressures and high temperatures, J. Phys. Condens. Matter 18, S1097 (2006). \n[38] R. J. Hemley, Progress on hydride, superhydride, and hydrogen superconductors, in Proceedings of the International Symposium on Pressure and Superconductivity, Fundacion Ramon Areces, Madrid, Spain (2018) https://www.fundacionareces.tv/watch/superconductividad? as=5b485ea9fe7e8150088b45fe. \n[39] J. P. Rush, C. J. May-Miller, K. G. B. Palmer, N. A. Rutter, A. R. Dennis, Y. H. Shi, D. A. Cardwell, and J. H. Durrell, Transport in bulk superconductors: A practical approach? IEEE Trans. Appl. Supercond. 26, 1 (2016). \n[40] V. V. Struzhkin, M. I. Eremets, W. Gan, H. K. Mao, and R. J. Hemley, Superconductivity in dense lithium, Science 298, 1213 (2002). \n[41] A. M. Schaeffer, S. R. Temple, J. K. Bishop, and S. Deemyad, High-pressure superconducting phase diagram of $^6\\mathrm{Li}$ : Isotope effects in dense lithium, Proc. Natl. Acad. Sci. U.S.A. 112, 60 (2015). \n[42] A. P. Drozdov, V. S. Minkov, S. P. Besedin, P. P. Kong, M. A. Kuzovnikov, D. A. Knyazev, and M. I. Eremets, Superconductivity at $215\\mathrm{~K~}$ in lanthanum hydride at high pressures, arXiv:1808.07039. \n[43] R. Dias, C. S. Yoo, V. V. Struzhkin, M. Kim, T. Muramatsu, T. Matsuoka, Y. Ohishi, and S. Sinogeikin, Superconductivity in high disordered dense carbon disulfide, Proc. Natl. Acad. Sci. U.S.A. 110, 11720 (2013). \n[44] I. Troyan, A. Gavriliuk, R. Rüffer, A. Chumakov, A. Mironovich, I. Lyubutin, D. Perekalin, A. P. Drozdov, and M. I. Eremets, Observation of superconductivity in hydrogen sulfide from nuclear resonant scattering, Science 351, 1303 (2016). \n[45] J. P. Carbotte, E. J. Nicol, and T. Timusk, Detecting Superconductivity in the High Pressure Hydrides and Metallic Hydrogen from Optical Properties, Phys. Rev. Lett. 121, 047002 (2018). \n[46] A. P. Drozdov, P. P. Kong, V. S. Minkov, S. P. Besedin, M. A. Kuzovnikov, S. Mozaffari, L. Balicas, F. Balakirev, D. Graf, V. B. Prakapenka, E. Greenberg, D. A. Knyazev, M. Tkacz, and M. I. Eremets, Superconductivity at $250\\mathrm{~K~}$ in lanthanum hydride under high pressures, arXiv:1812.01561. " + }, + { + "id": "10.1038_s41566-019-0390-x", + "DOI": "10.1038/s41566-019-0390-x", + "DOI Link": "http://dx.doi.org/10.1038/s41566-019-0390-x", + "Relative Dir Path": "mds/10.1038_s41566-019-0390-x", + "Article Title": "Rational molecular passivation for high-performance perovskite light-emitting diodes", + "Authors": "Xu, WD; Hu, Q; Bai, S; Bao, CX; Miao, YF; Yuan, ZC; Borzda, T; Barker, AJ; Tyukalova, E; Hu, ZJ; Kawecki, M; Wang, HY; Yan, ZB; Liu, XJ; Shi, XB; Uvdal, K; Fahlman, M; Zhang, WJ; Duchamp, M; Liu, JM; Petrozza, A; Wang, JP; Liu, LM; Huang, W; Gao, F", + "Source Title": "NATURE PHOTONICS", + "Abstract": "A major efficiency limit for solution-processed perovskite optoelectronic devices, for example light-emitting diodes, is trap-mediated non-radiative losses. Defect passivation using organic molecules has been identified as an attractive approach to tackle this issue. However, implementation of this approach has been hindered by a lack of deep understanding of how the molecular structures influence the effectiveness of passivation. We show that the so far largely ignored hydrogen bonds play a critical role in affecting the passivation. By weakening the hydrogen bonding between the passivating functional moieties and the organic cation featuring in the perovskite, we significantly enhance the interaction with defect sites and minimize non-radiative recombination losses. Consequently, we achieve exceptionally high-performance near-infrared perovskite light-emitting diodes with a record external quantum efficiency of 21.6%. In addition, our passivated perovskite light-emitting diodes maintain a high external quantum efficiency of 20.1% and a wall-plug efficiency of 11.0% at a high current density of 200 mA cm(-2), making them more attractive than the most efficient organic and quantum-dot light-emitting diodes at high excitations.", + "Times Cited, WoS Core": 1058, + "Times Cited, All Databases": 1112, + "Publication Year": 2019, + "Research Areas": "Optics; Physics", + "UT (Unique WOS ID)": "WOS:000468752300019", + "Markdown": "# Rational molecular passivation for highperformance perovskite light-emitting diodes \n\nWeidong Xu $\\textcircled{1}$ 1,2, Qi Hu3, Sai Bai $\\oplus1$ , Chunxiong Bao1,4, Yanfeng Miao2, Zhongcheng Yuan1, Tetiana Borzda5, Alex J. Barker5, Elizaveta Tyukalova6, Zhangjun Hu1, Maciej Kawecki   7,8, Heyong Wang1, Zhibo Yan1,9, Xianjie Liu1, Xiaobo Shi1, Kajsa Uvdal1, Mats Fahlman1, Wenjing Zhang4, Martial Duchamp $\\textcircled{\\textcircled{\\scriptsize{1}}}6$ , Jun-Ming Liu   9, Annamaria Petrozza5, Jianpu Wang   2, Li-Min Liu $\\textcircled{10}3,10\\star$ , Wei Huang $\\textcircled{10}2,11\\star$ and Feng Gao   1\\* \n\nA major efficiency limit for solution-processed perovskite optoelectronic devices, for example light-emitting diodes, is trapmediated non-radiative losses. Defect passivation using organic molecules has been identified as an attractive approach to tackle this issue. However, implementation of this approach has been hindered by a lack of deep understanding of how the molecular structures influence the effectiveness of passivation. We show that the so far largely ignored hydrogen bonds play a critical role in affecting the passivation. By weakening the hydrogen bonding between the passivating functional moieties and the organic cation featuring in the perovskite, we significantly enhance the interaction with defect sites and minimize non-radiative recombination losses. Consequently, we achieve exceptionally high-performance near-infrared perovskite light-emitting diodes with a record external quantum efficiency of $21.6\\%$ . In addition, our passivated perovskite light-emitting diodes maintain a high external quantum efficiency of $20.1\\%$ and a wall-plug efficiency of 11. $0\\%$ at a high current density of $200m\\mathbf{A}c m^{-2}$ making them more attractive than the most efficient organic and quantum-dot light-emitting diodes at high excitations. \n\nSromelcuatenicovend-oprstiogcenelisefscietcrdaontimcientdtaelvriechsetasl1if–d4o.erIncpoeasrdto-dveifstfikeoictnteistvoe,(tMheiHgPhrs-e)pate rhsfauovcrecesses in photovoltaics (PVs), their excellent luminescence and charge transport properties also make them promising for lightemitting diodes (LEDs)5. To achieve high-efficiency perovskite LEDs (PeLEDs), extensive efforts have been carried out to enhance radiative recombination rates by confining the electrons and holes6. These confinement efforts include the use of ultra-thin emissive layers7, the fabrication of nanoscaled polycrystalline features8, the design of low-dimensional or multiple quantum well structures9,10, and the synthesis of perovskite quantum dots11. As a result, the external quantum efficiency (EQE) values of PeLEDs have improved from less than $1\\%$ to $14\\%^{7-11}$ , a value that is still much lower than that predicted by optical simulations4. \n\nIn addition to enhancing radiative recombination rates, it is equally important to decrease the non-radiative recombination for improving the device performance. Unfortunately, state-of-the-art solution-processed perovskite semiconductors suffer from severe trap-mediated non-radiative losses12–14, which have been identified as a major efficiency-limiting factor for both PVs and LEDs15,16. The trap states are generally believed to be associated with ionic defects, such as halide vacancies17. Defect passivation through a molecular passivation agent (PA), which can chemically bond with the defects, is an attractive methodology to tackle this issue18. A few functional groups (for example $\\mathrm{-NH}_{2}$ , ${\\mathrm{P}}{=}{\\mathrm{O}}{\\mathrm{\\Omega}},$ ) have been identified to passivate perovskite semiconductors for PV applications19–21. It is found that these PAs show strong structure-dependent performance, even though they share identical functional groups to interact with the perovskite defects18–21. A lack of deep understanding of how the PA chemical structures influence the passivation effects prevents rational design of PAs to minimize the non-radiative recombination losses. These functional groups have also been borrowed to improve the efficiency of LEDs, resulting in limited success so far. For example, the use of trioctylphosphine oxide (TOPO) treatment in green PeLEDs can result in only moderate EQE enhancement from $12\\%$ to $14\\%^{22}$ . \n\nHere, we demonstrate high efficiencies for PeLEDs through the rational design of passivation molecules. We demonstrate that the candidate amino-functionalized PAs which form stronger hydrogen bonds with organic cations in perovskites are less effective in healing defect sites. Firmly based on our findings, we design new passivation molecules with decreased hydrogen-bonding ability, and hence improve their interaction with defects. In particular, we exploit O atoms within the PAs to polarize the passivating amino groups through the inductive effect, reducing their electrondonating ability and hence relevant hydrogen-bonding ability. This results in enhanced coordination of the PA functional groups with the perovskite defect sites and hence much improved passivation efficiency. As a result, we are able to substantially decrease the trapmediated non-radiative recombination and boost the electroluminescence (EL) performance of PeLEDs, giving an average EQE of $19.0\\pm0.8\\%$ and a record value of $21.6\\%$ . \n\n![](images/94a6931393cfa900892114ed7d31696cd20c48318bbf5b6f85b307f5924e6f5a.jpg) \nFig. 1 | PeLED architecture, performance and perovskite film characteristics. a, The molecular structures of HMDA and EDEA. b, HAADF-STEM crosssectional image of an EDEA-treated device (left, scale bar $500\\mathsf{n m}.$ ) and a zoom-in image (right, scale bar $100\\mathsf{n m}.$ . c–e, Representative characteristics for the optimized control, EDEA- and HMDA-treated devices: EL spectra at $2.5\\mathsf{V}$ (c); EQE–current density $(J)$ curves $(\\blacktriangleleft)$ ; current density–voltage–radiance (J–V–R) characteristics (e). f, ToF-SIMS dual-beam depth profiling conducted on the 0.25 EDEA-treated perovskite film on the $170/Z\\mathsf{n O};\\mathsf{P E}|\\mathsf{E}$ substrate, showing depth profiles of unfragmented EDEA $(M^{+}=\\mathsf E\\mathsf{D}\\mathsf E\\mathsf{A}^{+})$ and two characteristic fragment ions ([M– $\\cdot N H_{3}]^{+}$ and $[M-H]^{+})$ . u, atomic mass unit. $\\scriptstyle\\mathbf{g},$ ATRFTIR (N–H stretching) for EDEA and $\\mathsf{P b l}_{2}$ :EDEA mixture. h, XRD patterns for the control, EDEA- $\\left(x=0.25\\right)$ ) and HMDA-treated $\\left(x=0.25\\right)$ ) films on the ITO/ ZnO:PEIE substrates. $\\alpha$ and # denote the diffraction peaks corresponding to $\\left.\\alpha-F\\mathsf{A P b l}_{3}\\right.$ and ITO, respectively. a.u., arbitrary units. \n\n# Results and discussion \n\nPerovskite film characterization and device performance. Amino groups have been frequently employed to passivate perovskite semiconductors due to their coordination bonding to unsaturated $\\mathrm{PbI}_{6}$ -octahedral20. Here, we select two similar amino-functionalized PAs—that is, $^{2,2^{\\prime}}$ -(ethylenedioxy)diethylamine (EDEA) and hexamethylenediamine (HMDA) (Fig. 1a), which have identical length of alkyl chains; the difference is that EDEA has two additional O atoms within the chain. We perform first-principles calculations to demonstrate that both of them can help to passivate the surface iodide vacancy $\\mathrm{(V_{I})}$ through $\\mathrm{\\DeltaPb{-}N}$ coordination bonding, and thus show the potential to improve the EL performance (Supplementary Figs. 1 and 2). The formamidinium lead tri-iodide $({\\mathrm{FAPbI}}_{3})$ perovskite layers are deposited by spin-casting the precursors with a molar ratio of $\\mathrm{PbI}_{2}$ : formamidinium iodide (FAI): $\\mathrm{PA}=1$ : 2: $x$ $\\scriptstyle\\left.x=0\\sim0.3\\right)$ , where an FAI excess is used to eliminate the non-perovskite $\\delta$ -phase (Supplementary Fig. 3)23. We fabricate PeLEDs with the device architecture of indium tin oxide (ITO)/polyethylenimine ethoxylated (PEIE): modified zinc oxide nanocrystals (ZnO:PEIE)/perovskite/ poly(9,9-dioctyl-fluorene-co-N-(4-butylphenyl)diphenyl-amine) (TFB)/molybdenum oxide $(\\mathrm{MoO}_{3})/\\mathrm{Au}$ , as depicted in the highangle annular dark-field scanning transmission electron microscope (HAADF-STEM) cross-sectional images in Fig. 1b. Both HAADF-STEM and scanning electron microscope (SEM) images (Supplementary Fig. 4) show the formation of separated nanoisland features in the perovskite emissive layer. These nano-island features have not resulted in strong leakage currents (Fig. 1e), possibly due to the different TFB thickness on perovskite nano-islands and on $Z_{\\mathrm{nO:PEIE}}$ , as well as unfavourable charge injection from $\\mathrm{{}}Z\\mathrm{{nO}}$ to TFB (Supplementary Fig. 5). All the devices show EL peaks at $800\\mathrm{nm}/1.55\\mathrm{eV}$ (Fig. 1c) and low turn-on voltages around $1.25\\mathrm{V}$ (see Supplementary Fig. 6 for the characterization set-up), where the measurements were performed in a $\\Nu_{2}$ -filled glovebox. In spite of the small difference between the chemical structures of EDEA and HMDA, we notice a significant difference in the EQE values of the devices treated with these two PAs (Fig. 1d). The peak EQE is $10.9\\%$ for the HMDA-treated devices and $17.9\\%$ for the EDEAtreated ones. The EDEA-treated devices show high efficiencies even if we make significant changes to the emissive layer morphologies (Supplementary Figs. 7 and 8), indicating that the difference in the device performance of HMDA- and EDEA-treated devices results from the different intrinsic passivation effects of these two PAs. \n\n![](images/3380d820b06a33a3be792cb02d71b0ed2a38e3ff2a74f1c06105b3d05248e978.jpg) \nFig. 2 | Passivation effects of EDEA treatment. a, Temperature dependence of $C{-}f$ plots for control, HMDA- and EDEA-treated devices (in the range 320– $240\\mathsf{K})$ . b,c, Trap density deduced from the room-temperature $C{-}f$ plots for the control $(\\pmb{6})$ and the HMDA-treated (c) samples. d, Fluence-dependent PLQY. e, TCSPC probed PL lifetime. The excitation density for the ${\\mathsf{T C S P C}}$ measurement is around $10^{15}\\mathsf{c m}^{-3}$ . \n\nTo elucidate the different passivation effects between EDEA and HMDA, we first gather information on the molecular interactions of these moieties with perovskites. The first question that arises is whether these molecules are retained in the perovskite films after the annealing process. We performed time-of-flight secondary ion mass spectrometry (ToF-SIMS) depth profiling (Fig. 1f) and $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) characterizations (Supplementary Fig. 9) on perovskite films treated with EDEA, which has the lower boiling point of $105^{\\circ}\\mathrm{C}$ and thus represents the most critical sample. From ToF-SIMS we observe the depth distribution of EDEA across the perovskite film by monitoring the unfragmented positive molecular ion $\\mathrm{(C_{6}H_{16}N_{2}O_{2}^{+}}$ ; $\\mathrm{m}{=}148.1\\mathrm{u}$ ), and from XPS we observe changes in line shape of C1s, O1s, N1s core-level spectra in the resulting perovskite films compared to the control ones. Both results confirm the adsorption of EDEA molecules in the perovskite films, thus providing the opportunities for passivation. Passivation through coordination bonding is first evidenced by the strong interaction between $\\mathrm{PbI}_{2}$ and EDEA, leading to a change of the solution colour in their mixture, followed by the formation of a white precipitate (Supplementary Fig. 10). We further performed attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy on the EDEA: $\\mathrm{PbI}_{2}$ mixture. As shown in Fig. 1g, the stretching absorption $(\\nu)$ bands from the $\\mathrm{-NH}_{2}$ of the mixture shift to a lower wavenumber with respect to those from the pure EDEA, indicating the formation of coordination bonds between $\\mathrm{Pb}^{2+}$ and $\\mathrm{-NH}_{2}$ . \n\nNotably, the molecules used as potential PAs could also be used as templating molecules to synthesize low-dimensional perovskites24,25. Thus, it is worth investigating whether these PAs affect the three-dimensional (3D) crystal structure of $\\mathrm{FAPbI}_{3}$ . X-ray diffraction (XRD) measurements indicate no additional diffraction peaks other than those from 3D $\\mathrm{FAPbI}_{3}$ in the treated perovskite films (Fig. 1h). In addition, no features indicating the presence of Ruddlesden–Popper phases in the ground-state adsorption and photoluminescence (PL) spectra are observed (Supplementary Fig. 11). To further confirm the 3D structure in the treated films, we performed transient absorption (TA) spectroscopy (Supplementary Fig. 12) on the control and EDEAtreated films to detect any possible charge transfer kinetics from layered perovskite to the bulk 3D phases, which in principle would present a cascade system in terms of energy levels26,27. No additional spectral feature which could be related to low-dimensional phases (that is, of short-lived photobleach) is observed in the treated films, confirming that their photophysics is fundamentally similar to the control samples in this regard. \n\nPassivation mechanism. Assured about the presence of molecular interactions and a lack of structural changes in the thin films, we have investigated the defect physics of the samples. We reveal that the remarkable performance improvement of EDEA-treated PeLEDs origins from the significantly reduced defects in the perovskite emissive layer. Thermal admittance spectroscopy (TAS) was performed to probe the trap density and the energy depth of trap states in the PeLEDs (Fig. 2a). The control and HMDA-treated devices show typical temperature-dependent capacitance versus frequency $(C-f)$ plots28,29. The sub-gap energy deduced from the temperature dependent $C-f$ plots shows a trap energy depth of $0.40\\mathrm{eV}$ and $0.16\\mathrm{eV}$ for the control and HMDA-treated devices, respectively (Supplementary Fig. 13). Figure $^{2\\mathrm{b},\\mathrm{c}}$ shows the trap density deduced from the room-temperature $C-f$ plots, giving a peak trap density of $7.8\\times10^{15}\\mathrm{cm}^{-3}\\mathrm{eV}^{-1}$ and $5.9\\times10^{15}\\mathrm{cm}^{-3}\\mathrm{eV}^{-1}$ for the control and HMDA-treated devices, respectively. These results indicate a moderate passivation effect of HMDA. In contrast, the EDEA-treated devices show almost temperature-independent $C{-}f$ plots, indicating a negligible influence from trap states, and hence excellent passivation. \n\nExcellent defect passivation, which results in significantly reduced trap states in EDEA-treated perovskites, eventually also results in much enhanced external photoluminescence quantum yields (PLQYs) across a large range of excitation fluence, showing a peak PLQY of $56\\%$ (Fig. 2d). Even at a low fluence of $0.02\\mathrm{mW}\\mathrm{cm}^{-2}$ , the EDEA-treated films maintain a high PLQY of $40\\%$ , consistent with a low defect density. In contrast, the PLQYs of the control and HMDA-treated films show a strong intensity dependence due to trap-mediated non-radiative recombination. Low trap-mediated recombination in the EDEA-treated samples is also confirmed by the time-correlated single-photon counting (TCSPC) measurements (Fig. 2e), which show a prolonged PL lifetime of $1330\\mathrm{ns}$ compared to the control $(130\\mathrm{ns})$ and HMDA-treated films $(690\\mathrm{ns})$ . \n\n![](images/5dca76a01f0c9253cbc7cd22bd5f105758c3c98b5bd00abab4d8c7a17ff4c67e.jpg) \nFig. 3 | The influence of hydrogen bonds on passivation effects. a, ATR-FTIR spectra of FAI, EDEA and FAI:EDEA (1:1) mixture. $\\nu_{a s}(C-N)$ denotes the C–N antisymmetric stretching vibration from FAI32. b, Calculated electron distribution (valence band maximum) of HMDA and EDEA. c, $^1\\mathsf{H}$ NMR spectra of FAI in DMSO and FAI with $15\\%$ EDEA or HMDA. Peaks a and b are characteristic of H (a) and H (b) as labelled in the molecular structure of FAI in the inset. $\\mathbf{d}\\mathbf{-}\\mathbf{g},$ Adsorption configurations of HMDA (d,e) and EDEA $\\mathbf{\\Gamma}(\\mathbf{f},\\mathbf{g})$ on a perfect $\\mathsf{F A P b l}_{3}$ 110 slab (d,f) and on a defect-containing structure (e,g). The red, blue, cyan and white spheres represent O, N, C and H atoms, respectively. The hydrogen and coordination bonds are denoted by red dotted lines and blue squares, respectively. \n\nThe remarkable difference in the passivation effects between EDEA and HMDA indicates the significance of O atoms in EDEA for efficient passivation. A straightforward possibility for the O atoms to affect the passivation is that the two pairs of lone pair electrons at the O atom in EDEA can coordinate with $\\mathrm{Pb}^{2+}$ and hence passivate the defects. To examine this possibility, we employed ethylene glycol diethyl ether (EGDE) as the PA molecule (Supplementary Fig. 14). The only difference between EGDE and EDEA is that the former does not contain amino groups. Compared with the control samples, we observe no improvement on the PL properties as well as the device performance in the EGDE-treated ones (Supplementary Fig. 14), indicating no passivation effects of EGDE. Our first-principles calculations confirm that the O atom in EGDE cannot effectively passivate $\\mathrm{FAPbI}_{3}$ for the following two reasons: the O atoms lie in the middle of the molecule chain of EGDE, causing a strong lattice distortion energy when coordinated with $\\mathrm{Pb}^{2+}$ ; the molecular dynamics shows that even if the O atom initially bonds with $\\mathrm{Pb}^{2+}$ , the coordination bonds could be quickly broken to form hydrogen bonds between $\\mathrm{~O~}$ and $\\mathrm{FA^{+}}$ , destroying the passivation effects. \n\nHaving excluded direct passivation mechanisms through the O atom, we proceed to investigate other reasons for the different passivation effects between EDEA and HMDA. We notice that there are strong intermolecular interactions between FAI and PAs, resulting in the formation of gel-like mixtures (Supplementary Fig. 15a). The ATR-FTIR spectra (Fig. 3a) show obvious broadened absorption from $\\nu(\\mathrm{N-H})$ and $\\nu(\\mathrm{C-H})$ of the EDEA/FAI mixture compared to those in pure FAI and EDEA. In addition, the $_\\mathrm{N-H}$ scissoring vibration $(\\delta(\\mathrm{N\\mathrm{-}H})),$ absorption bands greatly weaken in the mixture, suggesting the restriction of $_\\mathrm{N-H}$ bending caused by intermolecular interactions. A similar phenomenon is also observed in the ATRFTIR spectra of the HMDA/FAI mixture (Supplementary Fig. 15b). All these results confirm the formation of hydrogen bonds between PAs and $\\mathrm{FAI}^{30,31}$ . \n\nSince both hydrogen bonds and passivating coordination bonds result from the lone pair electrons at the N atoms in the amino groups, changes in the hydrogen-bonding ability will influence the passivation effects. Importantly, the hydrogen bonds between the amino groups and $\\mathrm{FA^{+}}$ can be affected by the O atom because of the electron-withdrawing inductive effect of O atoms. Figure 3b shows the electron distributions of the EDEA and HMDA. Compared with HMDA, the electrons at the N atoms of EDEA polarize toward the $\\mathrm{~O~}$ atoms due to the inductive effects, which hence reduce the electron-donating ability of the amino groups and the relevant hydrogen-bonding ability33. The stronger hydrogen-bonding ability of HMDA is first evidenced by its higher melting point $(43^{\\circ}\\mathrm{C})$ compared to EDEA (liquid at room temperature) due to the enhanced intermolecular interactions. We further confirm that hydrogenbonding abilities of EDEA and HMDA with FAI are different by using $^{1}\\mathrm{H}$ nuclear magnetic resonance $\\mathrm{\\Omega^{\\prime1}H\\ N M R}\\mathrm{\\rangle}$ ) measurements. Generally, strong hydrogen bonding causes large chemical shifts to low-field (high ppm) because of de-shielding. As shown in Fig. 3c, the proton chemical shift at $8.9\\mathrm{ppm}$ from pure FAI corresponds to the resonance from the active protons at its amino groups20. This peak is broadened and moves to $7.7\\mathrm{ppm}$ and $5.9\\mathrm{ppm}$ with the introduction of $15\\%$ HMDA and EDEA, respectively. These results not only confirm the formation of new hydrogen bonds for both PA molecules, but also demonstrate weaker hydrogen-bonding ability of EDEA with respect to HMDA. \n\n![](images/09454f2b8a7097d4a156e08a79d5bdbe9d59be2a0d9e10fe19f07948a8d68b73.jpg) \nFig. 4 | The dependence of EL performance on passivation effects determined by the hydrogen bonds. a, Molecular structures of selected PAs (ODEA, TTDDA, DDDA). The letters a, b and c highlight the different lengths of the carbon chain between the N and O atoms. b, Dependence of the average peak EQE values from various PA-treated PeLEDs on $\\Delta E_{\\mathrm{ad}}$ . Each value is an average of 60 devices. The error bars represent the standard deviation. c, Histograms of the peak EQEs for control and ODEA-treated devices. $\\mathbf{d-f},$ Device characteristics for the best-performing ODEA-treated device: $J-V-R$ characteristics (d); EQE and wall-plug efficiency as a function of the current density (e); steady-state EQE for the control and ODEA-treated devices at $25\\mathsf{m A c m^{-2}}$ (f). We select the maximum EQE as the initial value for the calculation of $T_{50}$ . The device shown in d–f was fabricated using a different batch of ZnO nanocrystals, and hence is not included in the statistics of b,c. \n\nTo quantify how the hydrogen bonds affect the passivation mechanism, we investigate the adsorption configurations of the PAs on a perfect $110\\mathrm{FAPbI}_{3}$ slab (Figs. 3d,f) and on a defect-containing surface (iodide vacancy, $\\mathrm{\\DeltaV_{I}^{\\prime}}$ ) (Figs. 3e,g) by first-principles calculations. The adsorption energy difference $(\\Delta E_{\\mathrm{ad}})$ between these two surfaces is calculated to probe the preferred PA adsorption location, and hence to quantify the competition between the passivation and hydrogen bonding. The adsorption energy on the perfect surface $(E_{\\mathrm{ad,P}})$ is determined by van der Waals interactions and the hydrogen bonds (between $\\mathrm{FA^{+}}$ and all the electron-rich groups (N, O)). As a result of the inductive effect, we find a decrease of the absolute $E_{\\mathrm{ad,P}}$ value of EDEA, even considering that its O atoms can provide an additional hydrogen bond with $\\mathrm{FA^{+}}$ (Fig. 3f). This result is consistent with the $^{1}\\mathrm{H}$ NMR measurements in which HMDA shows stronger hydrogen bonding with $\\mathrm{FA^{+}}$ . For the surface with ${\\mathrm{V}}_{\\mathrm{I}},$ coordination bonds also contribute to the adsorption energy $(E_{\\mathrm{ad},\\mathrm{V}})$ in addition to hydrogen bonding and van der Waals interaction. The $\\Delta E_{\\mathrm{ad}}$ is then determined by $\\Delta E_{\\mathrm{ad}}{=}E_{\\mathrm{ad},V}{-}E_{\\mathrm{ad},P}$ . Negative $\\Delta E_{\\mathrm{ad}}$ values indicate a preferred interaction with the defect-contained structure through coordination bonds; while positive $\\Delta E_{\\mathrm{ad}}$ values indicate a preferred interaction with the perfect perovskite surface through hydrogen bonds. The $\\Delta E_{\\mathrm{ad}}$ for EDEA is $-0.23\\mathrm{eV}$ and that for HMDA is $0.45\\mathrm{eV},$ indicating that it is much easier for EDEA to break down the hydrogen bonds and turn to work with defects. The significant difference of the $\\Delta E_{\\mathrm{ad}}$ values between EDEA and HMDA explains the remarkable effect of O atoms in manipulating the passivation effects. An additional advantage of the O atom in EDEA is that it might help to improve the stability. The extra hydrogen bonds provided by the O atoms can stabilize the rotating $\\mathrm{FA^{+}}$ (Fig. 3f) and hence mitigate the negative effects from thermal vibration and the relevant lattice distortion (as shown in the HMDA adsorbed structure, Fig. 3d). In reality, the PA–perovskite interactions could be much more complex, involving van der Waals and hydrogen bonding between neighbouring surface modifiers; regardless, the experimental data confirm that EDEA is more effective at reducing non-radiative recombination. \n\nThe dependence of device performance on the passivation. Having established the role that the O atom plays in influencing the passivation effects, we proceed to explore new PAs, aiming to both further validate our conclusions and improve the device performance. We designed three PAs (Fig. 4a) with different strengths of inductive effects, which are expected to result in different hydrogen-bonding abilities and hence different passivation effects. Compared with EDEA, the inductive effect can be increased by introducing one additional O atom (as in $^{2,2^{\\prime}}$ -[oxybis(ethylenoxy)]diethylamine (ODEA)), and reduced by increasing the length of the alkyl chain between the $\\mathrm{~N~}$ and \n\nO atoms (as in 4,9-dioxa-1,12-dodecanediamine (DDDA) and 4,7,10-trioxa-1,13-tridecanediamine (TTDDA))33. Among all the PAs with O atoms, the inductive effect in DDDA is the least effective since its N and O atoms are almost isolated from each other, resulting in the strongest hydrogen-bonding ability of the amino groups. The morphological and optical characterizations for each PA-passivated perovskite film are shown in Supplementary Figs. 16 and 17. The adsorption configurations and $E_{\\mathrm{ad}}$ values are depicted in Supplementary Fig. 18 and summarized in Supplementary Table 1. Figure 4b shows the average peak EQE values for all the passivated systems as a function of $\\Delta E_{\\mathrm{ad}}$ (see representative device characteristics in Supplementary Figs. 19 and 20). It clearly shows that the EL performance is strongly dependent on the $\\Delta E_{\\mathrm{ad}}$ and hence the hydrogen-bonding ability of amino groups. As expected, ODEA, which shows a $\\Delta E_{\\mathrm{ad}}$ value of $-0.42\\mathrm{eV},$ delivers the highest average peak EQE of $19.0\\pm0.8\\%$ (Fig. $^{\\mathrm{4b,c}}$ and Supplementary Fig. 21). The excellent passivation effects of the ODEA are also confirmed by the fluence-dependent PLQY measurements and TAS measurements (Supplementary Fig. 22). \n\nWe show the characteristics for the best-performing ODEAtreated device, which gives a peak EQE up to $21.6\\%$ (Fig. 4e), approaching the best organic and quantum dot $\\mathrm{LEDs}^{34,35}$ . The radiance rises rapidly after the device turns on, reaching a high radiance of $308\\mathrm{W}\\mathrm{sr}^{-1}\\mathrm{m}^{-2}$ at $3.3\\mathrm{V}$ (Fig. 4d). The high EQE and low driving voltage result in an exceptionally high peak wall-plug efficiency up to $15.8\\%$ (Fig. 4e). High efficiencies at high current densities have been challenging in other low-temperature processed LED techniques (for example, organic LEDs) due to low charge carrier mobilities and strong exciton-induced quenching effects. Our device exhibits a low efficiency roll-off, maintaining a high EQE of $20.1\\%$ and a wallplug efficiency of $11.0\\%$ at a high current density of $200\\mathrm{mAcm}^{-2}$ , which makes them much more efficient than OLEDs and QLEDs at high excitations34,35. We also tested the operation lifetime $\\cdot T_{50},$ time to half of the initial radiance) of these devices in the glovebox without encapsulation. The ODEA-treated devices are among the most stable PeLEDs to date8–11,22,36,37, showing a long lifetime of $20\\mathrm{h}$ at $25\\mathrm{mAcm}^{-2}$ compared with the control devices ( $T_{50}{=}1.5\\mathrm{h}$ at $25\\mathrm{mAcm^{-2}}.$ ) (Fig. 4f). The improved lifetime may result from the reduced Joule heating due to the high efficiency, or the suppression of ion migration due to the low defect density12,38. We also notice a rapid degradation at high current densities ( $T_{50}=18\\mathrm{{min}}$ at $200\\mathrm{mAcm}^{-2}$ ) (Supplementary Fig. 23). Future research on the degradation mechanisms, especially at high current densities, will be of key importance to practical applications of PeLEDs. \n\n# Conclusions \n\nIn summary, we have demonstrated high-efficiency near-infrared PeLEDs with a peak EQE of $21.6\\%$ , which represents the most efficient PeLEDs to date. Our devices also show low-efficiency rolloff, maintaining a high EQE of $20.1\\%$ and a wall-plug efficiency of $11.0\\%$ at a high current density of $200\\mathrm{mAcm}^{-2}$ . Our results indicate a unique opportunity for PeLEDs to achieve solution-processed large-scale LEDs with high efficiencies at high brightness. The high efficiencies stem from our deep understanding of the passivation mechanisms of perovskites by organic molecules. We reveal the critical role of hydrogen bonds in influencing the passivation effects. By weakening the hydrogen bonding between the passivating functional groups and the organic cations of perovskites, we significantly reduce the non-radiative recombination. Our findings provide a broad avenue to explore the potential of molecular passivation for improving various perovskite applications where nonradiative losses should be minimized. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, statements of data availability and asso \n\nciated accession codes are available at https://doi.org/10.1038/ s41566-019-0390-x. \n\nReceived: 22 September 2018; Accepted: 11 February 2019; Published: xx xx xxxx \n\n# References \n\n1.\t Tan, Z.-K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n2.\t Akkerman, Q. A. et al. Strongly emissive perovskite nanocrystal inks for high-voltage solar cells. Nat. Energy 2, 16194 (2017). \n3.\t Dou, L. et al. Solution-processed hybrid perovskite photodetectors with high detectivity. Nat. Commun. 5, 5404 (2014). \n4.\t Shi, X. et al. Optical energy losses in organic–inorganic hybrid perovskite light-emitting diodes. Adv. Opt. Mater. 6, 1800667 (2018). \n5.\t Stranks, S. D. & Snaith, H. J. Metal-halide perovskites for photovoltaic and light-emitting devices. Nat. Nanotechnol. 10, 391–402 (2015). \n6.\t Xing, G. et al. Transcending the slow bimolecular recombination in lead-halide perovskites for electroluminescence. Nat. Commun. 8, 14558 (2017). \n7.\t Li, G. et al. Efficient light-emitting diodes based on nanocrystalline perovskite in a dielectric polymer matrix. Nano Lett. 15, 2640–2644 (2015). \n8.\t Xiao, Z. et al. Efficient perovskite light-emitting diodes featuring nanometresized crystallites. Nat. Photon. 11, 108–115 (2017). \n9.\t Wang, N. et al. Perovskite light-emitting diodes based on solution-processed self-organized multiple quantum wells. Nat. Photon. 10, 699–704 (2016). \n10.\tZou, W. et al. Minimising efficiency roll-off in high-brightness perovskite light-emitting diodes. Nat. Commun. 9, 608 (2018). \n11.\tLi, G. et al. Surface ligand engineering for near-unity quantum yield inorganic halide perovskite QDs and high-performance QLEDs. Chem. Mater. 30, 6099–6107 (2018). \n12.\tAbdi-Jalebi, M. et al. Maximizing and stabilizing luminescence from halide perovskites with potassium passivation. Nature 555, 497–501 (2018). \n13.\tStranks, S. D. Nonradiative losses in metal halide perovskites. ACS Energy Lett. 2, 1515–1525 (2017). \n14.\tTress, W. Perovskite solar cells on the way to their radiative efficiency limit—insights into a success story of high open-circuit voltage and low recombination. Adv. Energy Mater. 7, 1602358 (2017). \n15.\tCorrea-Baena, J.-P. et al. Promises and challenges of perovskite solar cells. Science 358, 739–744 (2017). \n16.\tBraly, I. L. et al. Hybrid perovskite films approaching the radiative limit with over $90\\%$ photoluminescence quantum efficiency. Nat. Photon. 12, 355–361 (2018). \n17.\tAgiorgousis, M. L., Sun, Y. Y., Zeng, H. & Zhang, S. Strong covalencyinduced recombination centers in perovskite solar cell material $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ . J. Am. Chem. Soc. 136, 14570–14575 (2014). \n18.\tNoel, N. K. et al. Enhanced photoluminescence and solar cell performance via Lewis base passivation of organic–inorganic lead halide perovskites. ACS Nano 8, 9815–9821 (2014). \n19.\tDequilettes, D. W. et al. Photoluminescence lifetimes exceeding ${8\\upmu\\mathrm{s}}$ and quantum yields exceeding $30\\%$ in hybrid perovskite thin films by ligand passivation. ACS Energy Lett. 1, 438–444 (2016). \n20.\tWang, F. et al. Phenylalkylamine passivation of organolead halide perovskites enabling high-efficiency and air-stable photovoltaic cells. Adv. Mater. 28, 9986–9992 (2016). \n21.\tZheng, X. et al. Defect passivation in hybrid perovskite solar cells using quaternary ammonium halide anions and cations. Nat. Energy 2, 17102 (2017). \n22.\tYang, X. et al. Efficient green light-emitting diodes based on quasi-twodimensional composition and phase engineered perovskite with surface passivation. Nat. Commun. 9, 570 (2018). \n23.\t Ma, F. et al. Stable $\\upalpha/\\updelta$ phase junction of formamidinium lead iodide perovskites for enhanced near-infrared emission. Chem. Sci. 8, 800–805 (2016). \n24.\tCortecchia, D. et al. Broadband emission in two-dimensional hybrid perovskites: the role of structural deformation. J. Am. Chem. Soc. 139, 39–42 (2017). \n25.\tChen, Z. et al. High-performance color-tunable perovskite light emitting devices through structural modulation from bulk to layered film. Adv. Mater. 29, 1603157 (2017). \n26.\tNeutzner, S., Srimath Kandada, A. R., Lanzani, G. & Petrozza, A. A dual-phase architecture for efficient amplified spontaneous emission in lead iodide perovskites. J. Mater. Chem. C 4, 4630–4633 (2016). \n27.\tYuan, M. et al. Perovskite energy funnels for efficient light-emitting diodes. Nat. Nanotechnol. 11, 872–877 (2016). \n28.\tDuan, H. S. et al. The identification and characterization of defect states in hybrid organic–inorganic perovskite photovoltaics. Phys. Chem. Chem. Phys. 17, 112–116 (2015). \n29.\tBi, C. et al. Non-wetting surface-driven high-aspect-ratio crystalline grain growth for efficient hybrid perovskite solar cells. Nat. Commun. 6, \n7747 (2015). \n30.\tDai, H. et al. A temperature-responsive copolymer hydrogel in controlled drug delivery. Macromolecules 39, 6584–6589 (2006). \n31.\tChen, H. et al. A solvent-and vacuum-free route to large-area perovskite films for efficient solar modules. Nature 550, 92–95 (2017). \n32.\tTaylor, V. C. A. et al. Investigating the role of the organic cation in formamidinium lead iodide perovskite using ultrafast spectroscopy. J. Phys. Chem. Lett. 9, 895–901 (2018). \n33.\tGero, A. Inductive effect and hydrogen bonding as factors in the base strength of polymethylenediamines. J. Am. Chem. Soc. 76, 5159–5160 (1954). \n34.\tDai, X. et al. Solution-processed, high-performance light-emitting diodes based on quantum dots. Nature 515, 96–99 (2014). \n35.\tLy, K. T. et al. Near-infrared organic light-emitting diodes with very high external quantum efficiency and radiance. Nat. Photon. 11, 63–68 (2016). \n36.\tCao, Y. et al. Perovskite light-emitting diodes based on spontaneously formed submicrometre-scale structures. Nature 562, 249–253 (2018). \n37.\tLin, K. et al. Perovskite light-emitting diodes with external quantum efficiency exceeding 20 per cent. Nature 562, 245–248 (2018). \n38.\tXiao, X. et al. Suppressed ion migration along the in-plane. ACS Energy Lett. \n3, 684–688 (2018). \n\n# Acknowledgements \n\nWe thank O. Inganäs, T.C. Sum, S.S. Lim, J. Zhang, W. Tress, W. Chen, Y. Puttisong, Y.T. Gong, C.Y. Kuang and C. Deibel for useful discussions. This work is supported by the ERC Starting Grant (717026), the National Basic Research Program of China (973 Program, grant number 2015CB932200), the National Natural Science Foundation of China (61704077, 51572016, 51721001, 61634001, 61725502, 91733302 and U1530401), the Joint Research Program between China and the European Union (2016YFE0112000), the Natural Science Foundation of Jiangsu Province (BK20171007), the National Key Research and Development Program of China (grant number 2016YFB0700700), the European Commission Marie Skłodowska-Curie Actions (691210), the Swiss National Science Foundation (CR23I2-162828), Nanyang Technological University start-up grant M4081924, and the Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linköping University (Faculty Grant SFO-Mat-LiU no. 2009-00971). The TEM measurements were performed at the Facility for Analysis, Characterization, Testing and Simulation (FACTS) in Nanyang Technological University, Singapore. A.P. and T.B. acknowledge financial support from the ERC Consolidator grant SOPHY (grant agreement number 771528). A.P. and A.J.B. acknowledge the \n\nproject PERSEO-‘Perovskite-based solar cells: towards high efficiency and long-term stability’ (Bando PRIN 2015-Italian Ministry of University and Scientific Research (MIUR) Decreto Direttoriale 4 novembre 2015 n. 2488, project number 20155LECAJ) for funding. W.X. is a Wenner-Gren Postdoc Fellow; F.G. is a Wallenberg Academy Fellow. \n\n# Author contributions \n\nF.G. and W.X. conceived the idea and designed the experiments; W.X. performed the experiments and analysed the data under the supervision of F.G. and W.H.; Q.H. performed first-principles calculations on the molecular passivation under the supervision of L.-M.L.; Y.M., Z.C.Y., H.W., X.S. and Z.B.Y. contributed to device fabrication and measurements; Y.M. performed fluence-dependent PLQY and TCSPC measurements and analysed the data under the supervision of J.W. and W.H.; Y.M. and J.W. cross-checked the device performance at Nanjing Tech University; S.B. and Z.C.Y. synthesized and modified the $z_{\\mathrm{{nO}}}$ nanocrystals and contributed to the device development; C.B. performed the TAS measurements and analysed the data; Z.H. performed the FTIR measurements and analysed the data; X.L. performed XPS tests and analysed the data; E.T. prepared the STEM specimen using FIB and performed the STEM imaging under the supervision of M.D.; T.B. and A.J.B. performed the transient absorption measurements and analysed the data under the supervision of A.P.; M.K. performed the ToF-SIMS measurements and analysed the data; J.-M.L., M.F., K.U. and W.Z. contributed to the data analysis; W.X. and F.G. wrote the manuscript; S.B., J.W. and A.P. provided revisions to the manuscript; F.G. supervised the project. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nF.G. and W.X. have filed a patent application related to this work (application no. SE1950272-3). \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41566-019-0390-x. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to L.-M.L., W.H. \nor F.G. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 \n\n# Methods \n\nMaterials. The passivation agents (PAs), including hexamethylenediamine (HMDA), $^{2,2^{\\prime}}$ -(ethylenedioxy)diethylamine (EDEA), 4,9-dioxa-1,12- dodecanediamine (DDDA), $^{2,2^{\\prime}}$ -[oxybis(ethylenoxy)]diethylamine (ODEA), 4,7,10-trioxa-1,13-tridecanediamine (TTDDA), ethylene glycol diethyl ether (EGDE) were purchased from Sigma-Aldrich. Formamidinium iodide (FAI) was purchased from Dyesol. $\\mathrm{PbI}_{2}$ (beads, $99.999\\%$ ) was purchased from Alfa Aesar. Poly(9,9-dioctyl-fluorene-co-N-(4-butylphenyl)diphenylamine) (TFB) was purchased from Ossila. Other materials for device fabrication were all purchased from Sigma-Aldrich. \n\nPreparation of the perovskite solution. Perovskite precursors (FAI: $\\mathrm{PbI}_{2}$ : PA molar ratio of 2: 1: $\\therefore x=0-0.3;$ were prepared with dimethylformamide (DMF) as the solvent. A $10\\mathrm{mg}\\mathrm{ml}^{-1}$ PA solution was prepared at first, and then was diluted according to the required molar ratio to $\\mathrm{Pb}^{2+}$ . The optimal concentration for $\\mathrm{PbI}_{2}$ was $0.13\\mathrm{M}$ . The solution precursors were stirred at $50^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ before spincoating. Colloidal $\\mathrm{znO}$ nanocrystal was synthesized by a solution–precipitation process, the details of which can be found in the literature39. \n\nPeLED fabrication. The indium tin oxide (ITO) glass substrates were sequentially cleaned by detergent and TL-1 (a mixture of water, ammonia $(25\\%)$ and hydrogen peroxide $(28\\%)$ (5:1:1 by volume)). The clean substrates were then treated by ultraviolet-ozone for $10\\mathrm{min}$ . The $\\mathrm{znO}$ nanocrystal solutions were spin-cast onto the substrates at $4{,}000\\mathrm{r.p.m}$ . for 30 s in air. Then the substrates were moved into a $\\mathrm{N}_{2}$ - filled glovebox. Next, a layer of polyethylenimine ethoxylated (PEIE) was deposited at ${5,000}\\mathrm{r.p.m}$ . $(0.05\\mathrm{wt\\%}$ , in IPA), followed by annealing at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . After cooling down to room temperature, the perovskite films were deposited from the precursors with various PA contents and $\\mathrm{Pb}^{2+}$ concentrations at a spin-coating speed of $^{3,000\\mathrm{r.p.m}}$ ., followed by annealing at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . For the control perovskite films prepared by anti-solvent treatment, the spin-casting rate is $5,000\\mathrm{r.p.m}$ . In addition, $150\\upmu\\mathrm{l}$ chlorobenzene (CB) was dropped after 5 s spinning. The TFB layer was deposited from its CB solution $(12\\mathrm{mg}\\mathrm{ml}^{-1},$ at $_{3,000\\mathrm{r.p.m}}$ . Finally, the $\\mathrm{MoO}_{x}/\\mathrm{Au}$ electrode was deposited by a thermal evaporation system through a shadow mask under a base pressure of ${\\sim}1\\times10^{-7}$ torr. The device area was $7.25\\mathrm{mm}^{-2}$ , as defined by the overlapping area of the ITO films and top electrodes. \n\nPeLED characterization. All PeLED device characterizations were carried out at room temperature in a nitrogen-filled glovebox. A Keithley 2400 sourcemeter and a fibre integration sphere (FOIS-1) coupled with a QE Pro spectrometer (Ocean Optics) were used for the measurements. The PeLED devices are tested on top of the integration sphere and only forward light emission can be collected, consistent with the standard OLED characterization method. The absolute radiance was calibrated by a standard Vis–NIR light source (HL-3P-INT-CAL plus, Ocean Optics). The devices were swept from zero bias to forward bias. The time evolution of the EQE was measured using the same testing system. To verify the accuracy of our characterization set-up, we crosschecked our results at Nanjing Tech University. The performances obtained in the two laboratories are in good agreement (Supplementary Table 2). \n\nFirst-principles calculations. We used the CP2K/Quickstep package to carry out the first-principles calculations. The exchange correlation energy was described with the generalized gradient approximation (GGA) of Perdew–Burke–Ernzerhof (PBE)40. The norm-conserving Goedecker–Teter–Hutter (GTH) pseudopotentials were used to describe the core electrons41. Gaussian functions with molecularly optimized double-zeta polarized basis sets ( $\\mathbf{m}$ -DZVP) were adopted for expanding the wavefunction of Pb $6s^{2}6p^{2}$ , $\\textbf{I}5s^{2}5p^{5}$ , $\\mathrm{~H~}1s^{2}$ , C $2s^{2}2p^{2}$ , O $2s^{2}2p^{4}$ and $\\mathrm{~N~}2s^{2}2p^{3}$ electrons42. The auxiliary basis set of plane waves was set as a 500 Ry cut-off energy. We modelled the $\\mathrm{FAPbI}_{3}$ (110) surface as a two-layer slab with a $2\\times2$ surface supercell $(25.74\\times25.13\\mathrm{\\AA}$ ). We used a vacuum of $\\dot{1}5\\mathrm{\\AA}$ to separate images along the surface normal direction. \n\nThe adsorption energies were calculated with the following equation: \n\n$$\nE_{\\mathrm{ad}}{=}E_{\\mathrm{adsorbed}}{-}E_{\\mathrm{decoupled}}\n$$ \n\nHere, $E_{\\mathrm{adsorbed}}$ is the energy of the adsorption configuration, while $E_{\\mathrm{decoupled}}$ is the energy of the decoupled system, including the clean system and the single molecule. \n\nPerovskite film characterizations. X-ray diffraction patterns were obtained from an X-ray diffractometer (Panalytical X’Pert Pro) with an X-ray tube (Cu Kα, $\\lambda{=}1.540\\dot{6}\\mathring\\mathrm{A}$ ). Steady-state PL spectra of the perovskite films were recorded by means of a fluorescent spectrophotometer (F-4600, HITACHI) with a 200 W Xe lamp as an excitation source. Absorption spectra were measured with a PerkinElmer model Lambda 900. The XRD patterns, UV and PL spectra for DDDA-, ODEA- and TTDDA-treated perovskite films are shown in Supplementary Figs. 16 and 17. Similarly, we find no evidence for the formation of low-dimensional perovskite within the resulting films from XRD, UV and PL measurements. The perovskite film morphology was characterized by a scanning electron microscope (SEM, LEO 1550 Gemini). \n\nXPS tests were carried out using a Scienta ESCA 200 spectrometer in ultrahigh vacuum $\\cdot{\\sim}1\\times10^{-10}$ mbar) with a monochromatic Al (Kɑ) X-ray source providing photons with $1,486.6\\mathrm{eV}.$ The XPS experimental condition was set so that the full-width at half-maximum of the clean Au $4f_{7/2}$ line (at the binding energy of $84.00\\mathrm{eV},$ ) was $0.65\\mathrm{eV}.$ . All spectra were measured at a photoelectron take-off angle of $0^{\\circ}$ (normal emission). \n\nToF-SIMS tests were performed on a ToF-SIMS.5 instrument from IONTOF, operated in the spectral mode using a $25\\mathrm{keV}$ ${\\mathrm{Bi}_{3}}^{+}$ primary ion beam with an ion current of $0.78\\mathrm{pA}$ . A mass-resolving power of approximately $6{,}000\\mathrm{m}/\\Delta\\mathrm{m}$ was reached. For depth profiling a $1\\mathrm{keV}\\mathrm{C}s^{+}$ sputter beam with a current of $39.81\\mathrm{nA}$ was used to remove the material layer-by-layer in interlaced mode from a raster area of $500\\times500\\upmu\\mathrm{m}$ . This raster area was chosen to ensure a flat crater bottom over an area of $100\\times100\\upmu\\mathrm{m}$ used for the mass spectrometry. The position of the ITO substrate interface in the sputter depth profile was defined by the half-maximum of the $\\mathrm{In}_{2}^{+}$ secondary ion count rate. \n\n${}^{1}\\mathbf{H}$ nuclear magnetic resonance (NMR). The $^{1}\\mathrm{H}$ NMR spectra were recorded on a Bruker Ultra Shield Plus 400 MHz NMR system. All the samples were prepared by dissolving 5 mg FAI in $0.4\\mathrm{ml}$ dimethyl sulfoxide-d6 (DMSO-d6). For the blend samples, $15\\%$ EDEA or HMDA (molar ratio compared to FAI) was added. \n\nAttenuated total reflectance-Fourier transform infrared (ATR-FTIR). The ATRFT-IR spectra were recorded from a PIKE MIRacle ATR accessory with a diamond prism in a Vertex 70 Spectrometer (Bruker) using a DLaTGS detector at room temperature. The measuring system was continuously kept in $\\Nu_{2}$ atmosphere. The spectra were acquired at $2\\mathrm{cm}^{-1}$ resolution and 30 scans between $^{4,000}$ and $800\\mathrm{cm}^{-1}$ . The presented spectra were baseline-corrected by subtracting a linear baseline over the spectral ranges. \n\nAberration-corrected scanning transmission electron microscope (STEM). An FEI dual-beam FIB Helios workstation equipped with an in-situ micromanipulator and Pt gas injection system was used to prepare thin samples for STEM imaging. The final milling was performed at $3\\mathrm{kV.}$ STEM investigations were conducted using JEOL ARM200F TEM equipped with a spherical aberration corrector at the condenser plane. A semi-convergence angle of 32 mrad was used. HAADF and annular bright-field (ABF) STEM were recorded with semi-angles in the range 68–280 mrad and 7–18 mrad, respectively. \n\nFluence-dependent PLQY and time-correlated single-photon counting (TCSPC) measurements. The fluence-dependent PLQY was measured by a typical three-step technique with a combination of $445\\mathrm{nm}$ continuous wave (CW) laser, spectrometer and an integrating sphere43. The TCSPC measurements were performed on an Edinburgh Instruments spectrometer (FLS980) with a $638\\mathrm{nm}$ pulsed laser (less than $100\\mathrm{{ps},0.1M H z}$ . The total instrument response function (IRF) was less than 130 ps and the temporal resolution was less than $20\\mathrm{ps}$ . All the perovskite films were deposited on $\\mathrm{ITO/ZnO:}$ PEIE substrates under identical spin-casting conditions for the optimized devices, and encapsulated by ultravioletcurable resin and glass slides. \n\nTransient absorption (TA). The perovskite film samples were mounted in a chamber under dynamic vacuum ( $\\cdot<10^{-5}\\mathrm{mbar})$ . TA spectroscopy was conducted in transmission geometry. An amplified Ti:sapphire laser (Quantronix Integra-C) generated ${\\sim}130$ fs pulses centred at $800\\mathrm{nm}$ , at a repetition rate of 1 kHz. A broadband white light probe was generated by focusing the pulses into a thin $\\mathrm{CaF}_{2}$ plate, and pump light at $400\\mathrm{nm}$ was obtained via second-harmonic generation in a beta barium borate (BBO) crystal. After interaction with the sample, a grating spectrometer was used to disperse the probe light on to a fast charge-coupled device (CCD) array, enabling broadband shot-to-shot detection. \n\nTrap density measurements by thermal admittance spectroscopy (TAS). For the device capacitance measurement, we used 0.4 M $\\mathrm{Pb}^{2+}$ for all the cases to increase the signals. A sinusoidal voltage with a peak-to-peak value of $30\\mathrm{mV}$ generated from a Tektronix AFG 3000 function generator was applied to the device. The current signal of the devices was amplified with a SR570 low-noise-current preamplifier (Stanford Research Systems) and then analysed using a SR830 lockin amplifier (Stanford Research Systems), where the amplitude and phase of the current can be measured. Based on the amplitude and phase of the current signal, the capacitance of the device was calculated using the parallel equivalent circuit model. The capacitance spectra of the device were measured by scanning the frequency of the sinusoidal voltage from 0.01 to $100\\mathrm{kHz}$ in logarithmic steps. The temperature of the device was controlled using a DE202AE closed cycle cryocooler (Advanced Research Systems). The capacitance–voltage curve was obtained by measuring the capacitance as the applied d.c. bias voltage was scanned from $-0.5$ to $1.0\\mathrm{V}.$ Based on the capacitance spectra measured at different temperatures, the trap density $(N_{\\mathrm{T}})$ distribution in energy $(E_{\\omega})$ was calculated with the following relations: \n\n$$\nN_{\\mathrm{T}}(E_{\\omega})=-\\frac{V_{b i}}{q W}\\frac{\\mathrm{d}C}{\\mathrm{d}\\omega}\\frac{\\omega}{k T}\n$$ \n\n$$\nE_{\\omega}=k T\\ln\\left(\\frac{2\\pi\\nu_{0}T^{2}}{\\omega}\\right)\n$$ \n\nwhere $V_{\\mathrm{bi}}$ is the built-in potential and $W$ is the depletion width ( $V_{\\mathrm{bi}}$ and W are derived from capacitance–voltage measurements), $C$ is the capacitance measured at an angular frequency $\\omega$ and temperature $T$ , $k$ is the Boltzmann constant, and $\\nu_{\\mathrm{0}}$ is the attempt-to-escape frequency, which can be obtained by fitting the relation of characteristic frequency with different $T$ based on equation (3). \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request. \n\n# References \n\n39.\tBai, S. et al. High-performance planar heterojunction perovskite solar cells: preserving long charge carrier diffusion lengths and interfacial engineering. Nano Res. 7, 1749–1758 (2014). \n40.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n41.\tGoedecker, S. & Teter, M. Separable dual-space Gaussian pseudopotentials. Phys. Rev. B 54, 1703–1710 (1996). \n42.\tVandeVondele, J. & Hutter, J. Gaussian basis sets for accurate calculations on molecular systems in gas and condensed phases. J. Chem. Phys. 127, 114105 (2007). \n43.\tDe Mello, J. C., Wittmann, H. F. & Friend, R. H. An improved experimental determination of external photoluminescence quantum efficiency. Adv. Mater. 9, 230–232 (1997). " + }, + { + "id": "10.1038_s41560-019-0382-6", + "DOI": "10.1038/s41560-019-0382-6", + "DOI Link": "http://dx.doi.org/10.1038/s41560-019-0382-6", + "Relative Dir Path": "mds/10.1038_s41560-019-0382-6", + "Article Title": "Cation and anion immobilization through chemical bonding enhancement with fluorides for stable halide perovskite solar cells", + "Authors": "Li, NX; Tao, SX; Chen, YH; Niu, XX; Onwudinullti, CK; Hu, C; Qiu, ZW; Xu, ZQ; Zheng, GHJ; Wang, LG; Zhang, Y; Li, L; Liu, HF; Lun, YZ; Hong, JW; Wang, XY; Liu, YQ; Xie, HP; Gao, YL; Bai, Y; Yang, SH; Brocks, G; Chen, Q; Zhou, HP", + "Source Title": "NATURE ENERGY", + "Abstract": "Defects play an important role in the degradation processes of hybrid halide perovskite absorbers, impeding their application for solar cells. Among all defects, halide anion and organic cation vacancies are ubiquitous, promoting ion diffusion and leading to thin-film decomposition at surfaces and grain boundaries. Here, we employ fluoride to simultaneously passivate both anion and cation vacancies, by taking advantage of the extremely high electronegativity of fluoride. We obtain a power conversion efficiency of 21.46% (and a certified 21.3%-efficient cell) in a device based on the caesium, methylammonium (MA) and for-mamidinium (FA) triple-cation perovskite (Cs(0.05)FA(0.54)MA(0.41))Pb(I0.98Br0.02)(3) treated with sodium fluoride. The device retains 90% of its original power conversion efficiency after 1,000 h of operation at the maximum power point. With the help of first-principles density functional theory calculations, we argue that the fluoride ions suppress the formation of halide anion and organic cation vacancies, through a unique strengthening of the chemical bonds with the surrounding lead and organic cations.", + "Times Cited, WoS Core": 951, + "Times Cited, All Databases": 992, + "Publication Year": 2019, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000467965700014", + "Markdown": "# Cation and anion immobilization through chemical bonding enhancement with fluorides for stable halide perovskite solar cells \n\nNengxu Li1,11, Shuxia Tao $\\textcircled{10}2,11$ , Yihua Chen1, Xiuxiu Niu3, Chidozie K. Onwudinanti4, Chen ${\\mathsf{H}}{\\mathsf{u}}^{5}$ , Zhiwen Qiu1, Ziqi $\\mathsf{\\pmb{X}}\\mathsf{\\pmb{u}}^{1}$ , Guanhaojie Zheng1, Ligang Wang1, Yu Zhang1, Liang Li1, Huifen Liu1, Yingzhuo Lun6, Jiawang Hong $\\textcircled{10}6$ , Xueyun Wang $\\textcircled{10}6$ , Yuquan Liu7, Haipeng Xie7, Yongli Gao7,8, Yang Bai3, Shihe Yang5,9, Geert Brocks2,10, Qi Chen $\\oplus3$ and Huanping Zhou   1\\* \n\nDefects play an important role in the degradation processes of hybrid halide perovskite absorbers, impeding their application for solar cells. Among all defects, halide anion and organic cation vacancies are ubiquitous, promoting ion diffusion and leading to thin-film decomposition at surfaces and grain boundaries. Here, we employ fluoride to simultaneously passivate both anion and cation vacancies, by taking advantage of the extremely high electronegativity of fluoride. We obtain a power conversion efficiency of $21.46\\%$ (and a certified 21. $3\\%$ -efficient cell) in a device based on the caesium, methylammonium (MA) and formamidinium (FA) triple-cation perovskite $(\\mathsf{C}\\mathsf{s}_{_{0.05}}\\mathsf{F A}_{_{0.54}}\\mathsf{M A}_{_{0.41}})\\mathsf{P b}(\\mathsf{I}_{_{0.98}}\\mathsf{B}\\mathsf{r}_{_{0.02}})_{3}$ treated with sodium fluoride. The device retains $90\\%$ of its original power conversion efficiency after 1,000 h of operation at the maximum power point. With the help of firstprinciples density functional theory calculations, we argue that the fluoride ions suppress the formation of halide anion and organic cation vacancies, through a unique strengthening of the chemical bonds with the surrounding lead and organic cations. \n\nrganic–inorganic halide perovskites $\\langle\\operatorname{ABX}_{3},$ where A is an organic cation, such as methylamine (MA) or formamidine (FA); B is lead or tin; X is a halide ion) have emerged as exciting new materials for solar cells due to their unique combination of properties, such as strong light absorption1, superb charge carrier mobility2 and low-cost fabrication3. Power conversion efficiencies (PCEs) of perovskite solar cells (PSCs) have risen from $3.8\\%$ to a certified $23.7\\%^{1,4-10}$ , close to that of crystalline silicon solar cells. In spite of the unparalleled growth in photovoltaic performance, the industrial application of PSCs is hampered by instability issues. One of the main sources of the instability is the defect chemistry of perovskites. In particular, owing to the ionic nature of perovskite materials11, as well as their solution-based fabrication processes, numerous defects are formed at the surfaces and grain boundaries of polycrystalline perovskite films12–15. In particular, point defects such as halide anion vacancies and organic cation vacancies are easily produced in perovskite materials due to their low formation energies16–18. Although these defects mostly create shallow electronic levels near the band edges8,19, they still have profound unwanted effects on carrier dynamics and the $I{-}V$ hysteresis of $\\mathrm{PSC}s^{20-23}$ . Even more importantly, such defects are believed to play an important role in the chemical degradation of the perovskite material and of the interfaces with the charge transport layers, leading to long-term instability of \n\nthe $\\mathrm{PSC}s^{24-27}$ . Ion vacancies diffuse into the crystallites, and promote the diffusion of cations and anions to the surfaces and grain boundaries. Decomposition reactions at these locations, such as evaporation of the organic species MA or FA, then lead to degradation of the material. Therefore, control and mitigation of the number of organic cation or halide anion vacancies has become an important research direction towards more efficient and stable PSCs. \n\nAs organic components such as MA or FA easily evaporate from the surface during the thermal annealing process11,28, thereby creating organic cation vacancies, one way to suppress the formation of such vacancies is to use excess MA/FA during or after the perovskite annealing process29. Another approach to prevent the formation of organic cation vacancies is to create a two-dimensional layered structure by introducing a small amount of larger organic molecules, such as phenethylamine, polyethylenimine and trifluoroethylamine, which are difficult to evaporate30. Similar methods have also been reported to be effective for passivating or suppressing halide anion vacancies8,31,32. Previously, iodide ions have been introduced into the organic cation solution, which decreases the concentration of iodide vacancies8. Elsewhere, guanidinium, an organic ion that probably forms hydrogen bonds, has been used to suppress the formation of iodide vacancies31. Addition of KI to perovskites has also demonstrated a positive effect of small alkali ions on passivating $\\mathrm{I^{-}}$ vacancies, which consequently improves the efficiency and stability of $\\mathrm{PSC}s^{33-35}$ . In addition, small ions (Cl and Cd) were doped into the perovskite lattice to suppress the formation of halide vacancies via lattice strain relaxation26. Although significant advances have been made in defect engineering of the bulk and grain boundaries of perovskites, most strategies focus on passivating or preventing only one type of defect, either the organic cation or the halide anion vacancy. Only recently, choline chloride was used to passivate both positive and negative charged defects by quaternary ammonium and halide ions11. This ‘charged components compensation’ provides a possible method of multi-vacancy defects passivation. \n\n![](images/8822076586604e32cec8793131134c4648d256e36ce1a1d582ae75064ef0cbb3.jpg) \nFig. 1 | The characterization of perovskite thin films (CsFAMA and CsFAMA-X). a, A schematic illustration of enhancing the hydrogen bond between the halogen and MA/FA ions, and strengthening the ionic bond between the halogen and metal ions through increasing the electronegativity of halogen. b, Reflectance micro-Fourier transform infrared spectroscopy. The black dotted line indicates the N–H vibrations of the MA/FA ions. c, Ultraviolet–visible absorption spectra and steady-state PL spectra. d, TRPL spectra with a log scale for the y axis. e, The evolution of the relative content of the $\\mathsf{P b l}_{2}$ phase in the perovskite film, expressed as the ratio of the X-ray diffraction peak areas for the $\\mathsf{P b l}_{2}$ and the perovskite signals; the results are for films maintained at $85^{\\circ}C$ in nitrogen $(456\\mathsf{h})$ and subsequently annealed at $100^{\\circ}\\mathsf{C}$ (12 h) in air. f, Top-view FE-SEM images of perovskite films. Scale bars, $2\\upmu\\mathrm{m}$ . \n\nHere we report a chemical bonding modulation of perovskite films by tuning the bond strength of the additives with the perovskites. We start from the state-of-the-art triple-cation perovskite $(\\mathrm{Cs_{_{0.05}}F A_{0.54}M A_{0.41}})\\mathrm{Pb}(\\mathrm{I_{0.98}B r_{0.02}})_{3}$ absorber and add a small amount of alkali halide, NaX $\\mathrm{X=I}$ , Br, Cl or F), using a twostep solution process (for details, see Methods). Although all alkali halides improve the quality of the perovskite, the fluoride-containing material gives by far the best performance. Planar $\\mathtt{n-i-p}$ solar cells made on the basis of the fluoride-containing perovskite yield a PCE of $21.46\\%$ (and a certified $21.3\\%$ -efficient solar cell). More importantly, non-encapsulated PSCs using the fluoride-containing materials exhibit an excellent long-term stability. They retain $90\\%$ of their original PCE after $1,000\\mathrm{h}$ of continuous illumination under maximum power point (MPP) operating conditions, or under thermal stress of $85^{\\circ}\\mathrm{C}$ . From results obtained with a wide range of experimental characterization techniques and density functional theory (DFT) calculations, we argue that the fluoride ions are very effective in passivating both the organic cation and halide anion vacancies by forming strong hydrogen bonds (N–H···F) with organic cations (MA/FA) and strong ionic bonds with lead in the perovskite films. \n\n# Properties of CsFAMA-X films \n\nPassing through the halide series I, Br, Cl and F (Fig. 1a), the electronegativity increases and the ionic radius becomes smaller. This leads to an increased chemical bonding between the halide anions with the A and B cations. In the following, we first compare the properties of the $(\\mathrm{Cs_{0.05}F A_{0.54}M A_{0.41}})\\mathrm{Pb}(\\mathrm{I_{0.98}\\bar{B}r_{0.02}})_{3}$ perovskite, modified by adding $0.1\\%$ NaX $\\mathrm{{\\cdot}}\\mathrm{{{X}}}{=}\\mathrm{{{I}}},$ Br, Cl, or F), to those of the unmodified perovskite as a reference. We denote the reference perovskite as ‘CsFAMA’ and the NaX-containing perovskite as ‘CsFAMA-X’. \n\nFigure 1b shows the reflectance micro-Fourier transform infrared spectra of CsFAMA and CsFAMA-X films. Compared to the reference CsFAMA, the spectrum of the CsFAMA-F film shows a substantial shift of the $_\\mathrm{N-H}$ vibration modes $(3,500{-}3,350\\mathrm{cm^{-1}})$ towards a lower wavenumber. This kind of shift is absent in the CsFAMA-X $\\mathrm{X=I}$ , Br, Cl) samples. We attribute this shift to the formation of hydrogen bonds $\\mathrm{\\partialN{\\mathrm{-}}H{\\cdot}{\\cdot}F}$ between the FA/MA and F species36. This hydrogen bond results in a delocalization of the electronic cloud of the $_\\mathrm{N-H}$ bond. It weakens the $_\\mathrm{N-H}$ chemical bond, which decreases the corresponding vibrational frequency. Our solid-state $\\mathrm{^{1}H}$ NMR measurements also confirm the formation of hydrogen bonds between the fluoride and the MA ions, as evidenced by the larger chemical shift of $\\mathrm{NH}_{3}$ protons in the CsFAMA-F sample (Supplementary Fig. 1). \n\n![](images/c3b50bcbaf002463111dc69228cd67e0e6454e15a1e7124f699ec63a4f503841.jpg) \nFig. 2 | Surface and bulk characterization of perovskite films. a, ToF-SIMS depth profile analysis of a CsFAMA-F perovskite sample. b, A scheme of the possible location of NaF (pink circles) across the perovskite films. c,d, Scanning Kelvin probe microscopy measurements: combining topography spatial maps and surface potential values of CsFAMA (c) and CsFAMA-F (d) perovskites. Scale bars, $1\\upmu\\mathrm{m}$ . The colour scale bar from black to white represents the surface potential varied from $-21\\mathsf{m}\\mathsf{V}$ to $21\\mathsf{m}\\mathsf{V}$ in c and d. \n\nThese experimental findings are supported by DFT calculations (Supplementary Fig.  2). Our calculations show that the presence of a fluoride ion at the surface induces the reorientation of several adjacent FA cations, and the formation of N–H···F hydrogen bonds. As a result, the stretching modes of the corresponding $_\\mathrm{N-H}$ groups shift to lower frequencies. Averaged over the stretching modes of all $_\\mathrm{N-H}$ groups of the affected FA ions, this leads to an overall shift of $63\\mathrm{cm}^{-1}$ . DFT results also indicate that the inclusion of a sodium ion has negligible effects on these vibration modes, confirming that fluoride is responsible for the change in the vibration dynamics of the FA cations. As we will discuss later, the strong fluoride–organic cation interaction significantly stabilizes the perovskite surface and suppresses the formation of organic cation vacancies. \n\nThe effects of NaX additives on the optical properties and the structure of the perovskite thin films are carefully investigated by a range of techniques. The bandgap of the CsFAMA-X films is the same as that of the reference CsFAMA, according to ultraviolet–visible and photoluminescence (PL) spectra (Fig. 1c). Neither shifts in the peaks, nor new peaks are observed in the X-ray diffraction patterns (Supplementary Fig. 3), indicating that addition of NaX does not alter the crystal structure of the perovskite films. Whereas these basic optical and crystal structural properties of all CsFAMA-X films are similar, time-resolved PL (TRPL) results (Fig.  1d and Supplementary Table  1) reveal an important difference in the lifetime of free charge carriers between the CsFAMA and the CsFAMA-X films. The CsFAMA-F sample exhibits carrier lifetimes $(\\pmb{\\tau}_{1};97.16$ ns, $\\tau_{2}$ : $401.64\\mathrm{ns}\\mathrm{,}$ ) that are much longer than those of the CsFAMA reference $(\\tau_{1};30.82\\mathrm{ns}$ , $\\tau_{2}$ : $193.29\\mathrm{ns}$ ). In contrast, the carrier lifetimes of the other CsFAMA-X ( $\\mathrm{X=I}.$ , Br, Cl) samples are much closer to those of the reference. This implies that non-radiative recombination is effectively suppressed by the addition of fluoride. \n\nIt should be noted here that another difference between the CsFAMA-X films can be found from field-emission scanning electron microscopy (FE-SEM) images (Fig.  1f). We observe that CsFAMA-Cl and CsFAMA-F films exhibit a slightly larger grain size than that of CsFAMA-Br and CsFAMA-I, which is probably due to the fact that the chloride and fluoride may influence the crystal nucleation and crystallization kinetics of perovskites (Supplementary Figs.  4 and 5). As shown from the TRPL results above and thermal stability properties in the following paragraph, the effect of the NaF additive is much more pronounced than that of $\\mathrm{{NaCl},}$ implying that the larger grain size, while a contributing factor, does not explain all of the improvements found in CsFAMA-F films. \n\nWe explore the thermal stability of the perovskite films by maintaining them at $85^{\\circ}\\mathrm{C}$ in a nitrogen atmosphere, followed by a thermal annealing at $100^{\\circ}\\mathrm{C}$ in air. During these ageing tests, we monitor the relative content of $\\mathrm{PbI}_{2}$ via $\\mathrm{\\DeltaX}$ -ray diffraction patterns (Supplementary Fig. 3), given that $\\mathrm{PbI}_{2}$ is one of the known decomposition products of perovskites. Figure  1e summarizes the relative X-ray diffraction intensity of $\\mathrm{PbI}_{2}$ and perovskite in the films. Clearly the CsFAMA-F film has a much lower $\\mathrm{PbI}_{2}$ content than all of the other films, which confirms the outstanding thermal stability of this material. The main degradation reactions caused by thermal stress are the deprotonation and desorption of volatile organic cations37. The improvement in thermal stability observed in the CsFAMA-F sample is attributed to the hydrogen bonds between the fluoride and MA/FA ions inhibiting the diffusion and dissociation of organic cations. \n\nIn short, of the halide salts studied, NaF enables the greatest improvements in terms of thermal stability and carrier lifetimes in CsFAMA perovskites. Therefore, in the following, we focus on CsFAMA-F and the role played by the fluoride in the context of photovoltaics performance of solar cells made with this material. \n\n![](images/0637291f3631ce78ed2dd696ace6bb097c03ba492c29d1ccf5b23378cc76d694.jpg) \nFig. 3 | Location of Na and F ions and effects on chemical bonding strength and formation energy of FA vacancies. a,b, Optimized structures of a Na–I unit (a) and a Na–F unit (b) adjacent to the $\\mathsf{F A P b l}_{3}$ surface. The yellow, blue, purple, black, grey, brown and orange spheres denote the Na, F, I, Pb, N, C and H ions, respectively. c, Net atomic charges of I and $\\mathsf{P b}$ ions on the $\\mathsf{F A P b l}_{3}$ surface with incorporation of NaI species (FA-I) or NaF species (FA–F), and without any incorporation (FA). d, Formation energy of a surface FA vacancy in the clean $\\mathsf{F A P b l}_{3}$ (FA), and in the NaI (FA–I) or NaF (FA–F) species incorporated surfaces. \n\n# Possible location of fluoride and its passivation effects \n\nTo investigate the presence and distribution of NaF in the perovskite film, time-of-flight secondary-ion mass spectroscopy (ToF-SIMS) is employed to probe the depth profiles of the atomic species in the CsFAMA-F perovskite sample (Fig.  2a). The maximum signals of Na and F are observed on the surface of the perovskite thin film and at the perovskite/ITO interface. Nevertheless, signals with appreciable intensity are observed along the entire film thickness. The presence of NaF in the film is also confirmed by the energy-dispersive X-ray spectroscopy results, as shown in Supplementary Fig. 6. As no significant peak shifts are observed in X-ray diffraction results, it rules out the possibility of NaF entering the CsFAMA crystal lattice (Supplementary Fig. 3). As analysed above, we therefore suggest that NaF is indeed in the film, possibly concentrated at the surface, as illustrated by Fig. 2b. \n\nTo probe the effect of NaF at the surface of the perovskite film, we apply scanning Kelvin probe microscopy38,39, and combine a threedimensional spatial map of the topography and a map of the surface potential. In the reference sample (CsFAMA), the surface potential at the boundaries of the grains is $40\\mathrm{mV}$ higher than in the middle of the grains (see Fig. 2c). In the CsFAMA-F sample (Fig. 2d), this surface potential difference is only about $20\\mathrm{mV}.$ We conclude that NaF modifies the surface potential (Supplementary Fig. 7), which further suggests that NaF species are probably located at the surface. \n\nTo gather more atomistic information regarding the possible location of NaF and its effect on the stability of the perovskite, we calculate the relative energies of incorporation of Na and F ions in the bulk and on surfaces, using DFT. The Na ion is found to be more stable on surfaces than in the bulk by 0.2 to $0.3\\mathrm{eV}.$ On both FAI- and $\\mathrm{PbI}_{2}$ -terminated surfaces, Na preferentially occupies an interstitial site, rather than an A site (Supplementary Fig. 8). A detailed chemical analysis (Fig. 3c) shows that incorporation of a Na ion increases the ionic charge on the nearby I ions. It indicates that Na may play a role in suppressing the diffusion of halide ions. \n\nWe find that incorporating a F ion into the perovskite lattice is extremely difficult, and it has a strong preference for staying at the surface. By far the most energetically favourable position of a F ion is substitution of an I ion at an FAI-terminated surface. Positions of F ions either in the perovskite bulk, or in a $\\mathrm{PbI}_{2}$ -terminated surface, have an energy that is about $3.5\\mathrm{eV}$ higher (Supplementary Fig. 9). The size mismatch between I and F ions probably prevents the latter from being incorporated comfortably inside the perovskite lattice, as it would induce too much strain. This is avoided by incorporating F ions on the FAI surface. \n\nHowever, the incorporation of F ions on the FAI surface changes the local bonding at the surface and subsurface layers. The most dramatic change is that the FA cations surrounding a F site reorient towards the F ion, in such a way as to maximize their interactions with this ion (Fig. 3a,b). This is in agreement with the $_\\mathrm{N-H}$ vibration mode analysis discussed above (Fig.  1b and Supplementary Fig. 2), supporting the finding that FA ions closest to a F site form hydrogen bonds with the F ion. In addition, the ionic charge on the Pb ions surrounding a F site also increases (Fig. 3c), indicating that the F ions form stronger ionic bonds. In summary, the introduction of F at FAI-terminated surfaces stabilizes the local structure via increased bonding with $\\mathrm{{Pb}}.$ and via hydrogen bonds with FA ions. \n\nTo further elucidate the effect of incorporation of F ions, we calculate the formation energies of FA cation vacancies on the surface of the clean perovskite, and that on the surfaces incorporated with NaI or NaF species (Fig. 3d and Supplementary Fig. 10). Whereas the FA vacancy formation energy close to a NaI species increases by a mere $0.12\\mathrm{eV},$ compared to the pristine perovskite, close to a F ion it increases by a sizeable $0.55\\mathrm{eV.}$ The presence of F therefore significantly prevents the formation of FA vacancies at the surface. This result supports the excellent thermal stability of the CsFAMA-X perovskite films (Fig.  1e), where the creation of organic cation vacancies is typically believed to be responsible for the degradation of the perovskites under thermal stress. \n\n# Solar cell performance \n\nTo investigate the photovoltaics performance based on our improved material, we fabricate $\\mathsf{n-i-p}$ planar PSCs using CsFAMA and CsFAMA-F perovskites as the absorbers. The cross-sectional SEM image in Fig. 4a shows the device structure, which comprises an ITO glass substrate covered by a $50\\mathrm{-nm}$ -thick $\\mathrm{SnO}_{2}$ electron transport layer. On top of that we deposit a ${600}\\mathrm{-nm}$ -thick perovskite film, covered with a layer of Spiro-OMeTAD as the hole transport layer $(200\\mathrm{nm})$ ), and an $80\\mathrm{-nm}$ -thick gold electrode as the back contact. \n\n![](images/0bbad42c6ccf2ec0b791b4dc28bca3f6b498da1fdcdf67cae1b085355103b1cd.jpg) \nFig. 4 | Performance of PSCs. a, A cross-sectional SEM image. b, J–V curves with reverse $(1.2\\lor$ to $-0.2\\mathsf{V},$ and forward $(-0.2\\lor$ to $1.2\\ V.$ ) scans of devices made with the untreated material (CsFAMA) and with the NaF-treated perovskite (CsFAMA-F). The scan rate is $100\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . c, Stabilized PCEs at the MPP (voltage $0.92\\mathrm{V}$ for the CsFAMA sample, $0.94\\mathrm{V}$ for the CsFAMA-F sample). d, Arrhenius plots (obtained by linear fitting of data points) of the characteristic transition frequencies determined from the derivative of the admittance spectra. e, Trap state density $(N_{\\top})$ of the perovskite solar devices measured at 290 K. f, PLQE of perovskite films as a function of excitation power. \n\nAs summarized in Table 1 and shown in Fig. 4b, the CsFAMA-F cells give rise to a PCE of $21.46\\%$ (average value from reverse and forward scan results) with negligible $J{-}V$ hysteresis. This is to be compared to the reference CsFAMA with an average PCE of $19.03\\%$ with moderate $J{-}V$ hysteresis. Examples of CsFAMA and CaFAMA-X cells with stabilized PCEs of $19.37\\%$ and $20.96\\%$ , respectively, are shown in Fig. 4c. The statistics of 60 devices with or without NaF are shown in Supplementary Fig. 11 and Supplementary Table 2. The average PCEs for the CsFAMA and CaFAMA-F devices are $18.86\\%$ and $20.56\\%$ , respectively. The short-circuit current density $(J_{s c})$ increases only slightly in CsFAMA-F cells (the spectral responses of the external quantum efficiency of these devices are shown in Supplementary Fig.  13), while the most dramatic enhancement is found in the open-circuit voltage $(V_{\\mathrm{oc}})$ and fill factor (FF). We attribute this improvement to the immobilization of mobile ions and vacancy defects such as iodide and MA (FA) due to the incorporation of fluoride ions. The best CsFAMA-F device has been certified by a third party (Supplementary Fig.  12). The certified PCEs are $21.7\\%$ under the reverse scan direction (1.2 to $-0.1\\mathrm{V})$ and $20.8\\%$ under the forward scan direction $(-0.1$ to $1.2\\mathrm{V},$ ), with a slow scan rate $(33\\mathrm{mV}\\mathrm{s}^{-1})$ under AM1.5G full-sun illumination $(1,000\\mathrm{W}\\mathrm{m}^{-2})$ . This certified efficiency of $21.3\\%$ (average value from certified reverse and forward scan results) agrees well with measured performances in our own laboratory. \n\nTo examine the effects of incorporation of NaF on the defects in the perovskite absorber, we use admittance spectroscopy, and conduct a Mott−Schottky analysis to analyse the defects profile. We first conduct temperature-dependent admittance spectroscopy measurements on the CsFAMA and CsFAMA-F devices with the temperature rising from 210 to $350\\mathrm{K}$ without illumination (Supplementary Fig. 14a,b). Subsequently, the defect activation energies $\\left(E_{\\mathrm{a}}\\right)$ in the CsFAMA and CsFAMA-F samples are calculated to be 0.275 and $0.201\\mathrm{eV},$ respectively (Fig. 4d). The trap density-of-states distribution and their energy levels are presented in Fig. 4e. Incorporation of fluoride effectively reduces the energy level of trap states from 0.26 to $0.18\\mathrm{eV},$ as well as their density of states from $22.4\\times10^{15}$ to $14.9\\times10^{15}\\mathrm{cm}^{-3}\\mathrm{eV}^{-1}$ . \n\nTable 1 | Photovoltaics parameters for the best CsFAMA solar cell and the best CsFAMA-F cell under the forward $(-0.2$ to 1.2 V) and reverse (1.2 to −0.2 V) scan directions \n\n\n
SampleV. (V)Jsc (mA cm-2)FF (%)PCE (%)
CsFAMA, forward1.07923.7271.7918.38
CsFAMA, reverse1.09524.0374.7719.68
CsFAMA-F, forward1.11224.0178.6220.99
CsFAMA-F, reverse1.12624.2380.3521.92
\n\nWe have further carried out PL quantum efficiency (PLQE) measurements. Figure  4f shows that the CsFAMA-F sample has a higher PLQE compared to the CsFAMA sample. Moreover, its PLQE increases more rapidly with increasing laser intensity. Spacecharge-limited current measurements, transient photovoltage, transient photocurrent decay experiments and ultraviolet photoelectron spectroscopy (UPS) measurements all show agreement with our finding that NaF effectively passivates electronic defects in PSCs, which is responsible for the improved PCE (see Supplementary Notes 11–13 and Supplementary Figs. 15–17). \n\n![](images/b2b669cb3fd52db8ddce5a1fc0c79f5b82b65248b5ee40b6b3228658c1fc124e.jpg) \nFig. 5 | Stability performance of PSCs under various conditions. All devices are unencapsulated and CsFAMA devices are compared with NaF-containing devices. a, Evolution of normalized PCEs of devices on continuous one-sun illumination in a nitrogen atmosphere. b, Devices kept at $85^{\\circ}C$ in a nitrogen atmosphere. In a and b, the error bars represent the standard deviation for six devices. c, Devices in ambient air with a relative humidity of about $25\\%-45\\%$ , and a temperature of about $25\\mathrm{-}40^{\\circ}C$ . The error bars represent the standard deviation for eight devices. d, Devices under MPP tracking and continuous light irradiation with a white LED lamp, $100\\mathsf{m w c m}^{-2}$ in a nitrogen atmosphere. Note that the initial efficiencies of these PSCs are about $19\\%$ for CsFAMA, and $20\\%$ for CsFAMA-F. \n\nTo establish the stability of our improved CsFAMA-F material, we carry out a series of investigations on unencapsulated devices. The results of stability tests under continuous one-sun illumination, or at a fixed temperature of $85^{\\circ}\\mathrm{C}$ in a nitrogen atmosphere, are shown in Fig.  5a,b. The photo-stability of CsFAMA-F-based cells is superior to that of the reference cells, maintaining $95\\%$ of their original PCE after $1,000\\mathrm{{h}}$ of illumination. As shown in Fig. 5b, the thermal stability of F-containing devices shows an even more significant improvement. The CsFAMA-F-based devices retain $90\\%$ of their initial PCE after annealing at $85^{\\circ}\\mathrm{C}$ for $1,000\\mathrm{h}$ , while CsFAMA PSCs retain only $50\\%$ of their initial PCE. We attribute this to the excellent thermal stability of NaF-containing perovskite films (Fig. 1e). \n\nIn addition, we probe the storage lifetime of devices in an environment with humidity of about $25\\%-45\\%$ at a temperature of about $25\\mathrm{-}40^{\\circ}\\mathrm{C}$ (Fig. 5c). The evolution of the normalized PCE shows that CsFAMA-F cells exhibit a significantly improved long-term stability, retaining $90\\%$ of their original PCE after over $6{,}000\\mathrm{h}$ of storage in ambient air. \n\nMost importantly, we investigate the operational stability of unencapsulated devices under MPP tracking with a continuous one-sun irradiation in a nitrogen atmosphere (Fig.  5d). The reference cells show a rapid loss of PCE (below $40\\%$ of the original PCE after working for $600\\mathrm{{h}}$ ), while the CsFAMA-F cell exhibits a long lifetime, retaining over $90\\%$ of its initial PCE after $1{,}000\\mathrm{h}$ . In addition, we also investigate the operational stability of unencapsulated PSCs under MPP tracking with continuous light irradiation (solar simulator source, $100\\mathrm{mW}\\mathrm{cm}^{-2}.$ ) in air (Supplementary Fig. 18). It can be found that CsFAMA-F PSCs exhibit superior stability performance compared with reference cells (CsFAMA): the CsFAMA-F cells retain $85\\%$ of their PCE after $350\\mathrm{min}$ , while the PCE of the CsFAMA reference cells drops below $60\\%$ in less than $50\\mathrm{min}$ , which further confirms that the incorporation of NaF in the perovskite film brought about remarkable improvements in the long-term stability of PSCs. \n\nIt is important to emphasize that the effect of NaF is different from that of other sodium halides NaX $\\mathrm{{\\cdot}}\\mathrm{{X}}{=}\\mathrm{{Cl}}.$ , Br, I). To demonstrate this, we fabricate PSCs based on CsFAMA absorbers treated with other sodium halides. The corresponding PCEs are then slightly improved compared to the untreated CsFAMA (Supplementary Fig.  19a), which is in line with other reports40. However, these devices exhibit an obvious $J{-}V$ hysteresis (larger hysteresis index), while the NaF-containing devices show an almost negligible $J{-}V$ hysteresis (Supplementary Fig.  19b). It is possible that the Na ion can penetrate the perovskite film under an external bias because of its small $\\mathrm{size}^{34}$ (about $0.102\\mathrm{nm}$ ). Mobile ions and their accumulation at interfaces are reported to be responsible for the $J{-}V$ hysteresis41. When using NaF, however, Na is bonded more closely to F, and is therefore localized mostly. The above analysis emphasizes the uniqueness of fluoride to immobilize the counter ions, as compared to other halides. \n\nTo test the generality of these findings, we also consider the use of KF as an additive. We fabricate KF-containing PSCs (CsFAMA-K), using the same procedure as for NaF-containing PSCs (CsFAMA-Na). Supplementary Fig.  20 shows that KF-containing PSCs exhibit almost the same PCE as NaF-containing PSCs. In addition, both KF- and NaF-containing PSCs show negligible hysteresis, indicating that KF is also effective in passivating both anions and cations for efficient and stable PSC devices. The analysis above highlights the fact that fluoride ions are desirable for both chemical and electronic passivation in perovskites, and can be combined with a number of alkali metals. \n\n# Conclusions \n\nIn summary, we have explored an effective approach for simultaneous passivation of both the cation and anion vacancy defects in perovskite materials via chemical bonding enhancement, to improve the efficiency and stability of PSCs. By adding NaF to the triple-cation perovskite absorber, we obtain a PCE of $21.46\\%$ (and a certified efficiency of $21.3\\%$ ) in planar PSCs, which is among the top efficiencies for this type of solar cells. Without any encapsulation, these solar cells exhibit remarkable long-term stability, retaining $90\\%$ of their original PCE after $1,000\\mathrm{{h}}$ under MPP operation conditions at continuous illumination. The addition of NaF also results in a superb thermal and environmental stability of materials as well as devices. It is found that NaF is indeed present in the perovskite film and forms hydrogen bonds with organic cations within the perovskite crystals, which effectively retards the diffusion of these cations and their dissociation. Fluoride ions also increase the ionic bonding, thus immobilizing both organic cations and halide anions. Passivating the surfaces and grain boundaries through increased chemical bonding, the fluoride ions effectively block the materials degradation pathway at the corresponding interfaces. The present passivation approach that makes use of the high electronegativity of F is generally applicable for improving the stability of perovskite materials by suppressing the formation of halide anion and organic cation vacancies. These findings provide a new approach to the fabrication of highly efficient and stable PSCs. \n\n# Methods \n\nMaterials. Materials used in experiments include $\\mathrm{PbI}_{2}$ ( $99.999\\%$ , Sigma-Aldrich), CsI $(99.9\\%$ , Sigma-Aldrich), NaF (AR $98\\%$ , Aladdin Industrial Corporation), spiro-OMeTAD (Lumtec), $\\mathrm{SnO}_{2}$ colloid precursor (Alfa Aesar, tin(iv) oxide, $15\\%$ in $\\mathrm{H}_{2}\\mathrm{O}$ colloidal dispersion), $N,N$ -dimethylformamide (DMF; $99.99\\%$ , SigmaAldrich), dimethylsulfoxide (DMSO; $99.5\\%$ , Sigma-Aldrich), isopropanol $(99.99\\%$ , Sigma-Aldrich), chlorobenzene $(99.9\\%$ , Sigma-Aldrich), acetone (AR Beijing Chemical Works), ethanol (AR Beijing Chemical Works), aminomethane (CP Beijing Chemical Works), hydrogen iodide $57\\%$ , Aladdin Industrial Corporation) and ITO substrate (Shanghai B-Tree Tech. Consult.). \n\nMAX (MAI, MACl, MABr) and FAI were synthesized using the methods reported previously42. The details are as follows: $16\\mathrm{ml}$ methylamine water solution $\\mathrm{(0.1mol)}$ ) was added to a $\\boldsymbol{100}\\mathrm{ml}$ three-neck flask immersed in a water/ice bath. A certain amount $\\left(0.1\\mathrm{mol}\\right)$ of HX acid was slowly dropped into the bottle with continuous stirring. The mixture was refluxed for $2\\mathrm{h}$ under a $\\Nu_{2}$ atmosphere. Subsequently, the solution was concentrated to a dry solid by using rotary evaporation at $80^{\\circ}\\mathrm{C}$ . This crude product was re-dissolved into $20\\mathrm{ml}$ ethanol, then $100\\upmu\\mathrm{l}$ diethyl ether was slowly dropped along the bottle wall and a white product deposited. This recrystallization was repeated three times, and the obtained precipitate was dried in a vacuum oven for $10\\mathrm{h}$ at $40^{\\circ}\\mathrm{C}$ . The final products were sealed in a $\\Nu_{2}$ -filled glovebox for future use. The synthesis procedure for FAI was similar to MAI, except that HI acid was added into an $8.8\\mathrm{g}$ formamidine acetate $(0.10\\mathrm{mol}),$ ethanol solution. \n\nSolar cell device fabrication. The ITO substrate was cleaned with ultrapure water, acetone, ethanol and isopropanol successively. After $45\\mathrm{min}$ of ultraviolet– $\\mathrm{~O}_{3}$ treatments, a $\\mathrm{SnO}_{2}$ nanocrystal solution was spin-coated on the substrate at $4{,}000\\mathrm{r.p.m}$ . for 30 s to form a $50\\mathrm{-nm}$ -thick film, which was then annealed at $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ in air. The reference perovskite film was fabricated by a two-step solution process: the $\\mathrm{PbI}_{2}$ ( $1.3\\mathrm{M}.$ , dissolved in DMF/DMSO $(9{:}1,\\mathbf{v}/\\mathbf{v})$ ) mixed with $5\\%$ CsI was spin-coated on $\\mathrm{ITO}/\\mathrm{SnO}_{2}$ at $2{,}500\\mathrm{r.p.m}$ . for 30 s and annealed at $70^{\\circ}\\mathrm{C}$ for 1 min in a nitrogen glovebox. After cooling the $\\mathrm{PbI}_{2}$ -coated substrate to room temperature in a nitrogen glovebox, a mixed organic cation solution (MAI $0.12\\ensuremath{\\mathrm{M}}$ ; MABr $0.05\\mathrm{M}$ ; MACl 0.07 M; FAI $0.23\\mathrm{M}$ , dissolved in isopropanol) was spin-coated at $^{2,300\\mathrm{r.p.m}}$ . for $30\\mathrm{s}$ and then annealed at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ in air. Then the HTM solution, in which a spiro-OMeTAD/chlorobenzene $(75\\mathrm{mgml^{-1}},$ ) solution was employed with the addition of $35\\upmu\\mathrm{l}$ Li-TFSI/acetonitrile $(260\\mathrm{mgml^{-1}},$ ), and $30\\upmu\\mathrm{l}$ 4-tertbutylpyridine, was deposited by spin-coating at $^{3,500\\mathrm{r.p.m}}$ . for 30 s. The device was finished by thermal evaporation of Au $\\mathrm{80nm})$ under vacuum. For the NaX-containing perovskite film, we dissolved a certain amount of $\\mathrm{NaX}$ with DMF/ DMSO $(9{:}1,\\mathbf{v}/\\mathbf{v})$ , and used it as a solvent to dissolve the $\\mathrm{PbI}_{2}$ powder. The optimal content for NaF was about $0.1\\%$ mol relative to $\\mathrm{PbI}_{2}$ (Supplementary Fig. 21), and we assumed that all NaF added was successfully incorporated in the final perovskite films because of its high vaporization enthalpy. The other steps are all the same as for the reference sample. For PSC stability tests, we changed the organic cation solution components (MABr 0.05 M; MACl 0.07 M; FAI $0.35\\mathrm{M}$ , dissolved in isopropanol), and the HTM solution was replaced by polymer-modified spiroMeOTAD to achieve better performance and stability. The other steps are all the same as for the reference and NaF-containing perovskite films. \n\nMaterial characterization. The morphology of perovskite and $\\mathrm{PbI}_{2}$ thin films and cross-sectional SEM image were measured using a cold field-emission scanning electron microscope (Hitachi S-4800). The X-ray diffraction patterns were collected using a PANalytical X’Pert Pro X-ray powder diffractometer with Cu Kα radiation $(\\lambda=1.54050\\mathrm{\\AA}$ ). PL was measured by the FLS980 (Edinburgh Instruments Ltd) with an excitation at $470\\mathrm{nm}$ . The ultraviolet–visible absorption spectra were obtained using an UV–visible diffuse reflectance spectrophotometer (UV–vis DRS, Japan Hitachi UH4150). UPS measurements were carried out on an XPS AXIS Ultra DLD (Kratos Analytical). The transient photovoltage and transient photocurrent measurements were performed on a Molex 180081-4320 simulating one-sun working conditions, and the carriers were excited by a $532\\mathrm{nm}$ pulse laser. The electrochemical impedance spectroscopy measurements were determined on an electrochemical workstation (Zahner Company), employing light-emitting diodes (LEDs) driven by Export (Zahner Company). The thermal admittance spectroscopy analyses were conducted on a Zahner Zennium pro Electrochemical Workstation at various temperatures ( $\\mathrm{\\Delta}T=210{-}350\\mathrm{K}\\mathrm{\\rangle}$ in the dark from $10^{\\circ}$ to $10^{6}\\mathrm{Hz}$ . A small a.c. voltage of $50\\mathrm{mV}$ was used, and the d.c. bias was kept at zero to avoid the influence of the ferroelectric effect for perovskite material during measurement. For temperature-dependent characterization, the sample was mounted in Cryo Industries Liquid Nitrogen Dewars with a Lake Shore model 335 cryogenic temperature controller. The current density–voltage characteristics of the perovskite devices were obtained using a Keithley 2400 source-measure unit under AM1.5G illumination at $1,000\\mathrm{W}\\mathrm{m}^{-2}$ with a Newport Thermal Oriel 91192 ${}^{1,000\\mathrm{W}}$ solar simulator. The shading mask and one of our best devices were sent to the National Institute of Metrology, China for certification. The active area was defined as $0.09408\\mathrm{cm}^{2}$ . External quantum efficiencies were measured by an Enli Technology EQE measurement system. Scanning Kelvin probe force microscopy was performed on perovskite samples in ambient conditions using an MFP 3D-Classic Scanning Probe Microscope (Asylum Research, Inc.). This technique relies on an a.c. bias applied to the tip to produce an electric force on the cantilever that is proportional to the potential difference between the tip and the sample. The scanning was carried out in a dual-pass scan mode; during the first scan the spatial variations in the surface potential were directly measured, and the second scang gives the workfunction by nulling the local electrostatic force gradient arising from the contact potential differences between the AFM tip and the sample surface. The conductive AFM probe was ASYELEC-01-R2 with a $\\mathrm{Ti/Ir}$ coating and a resonant frequency of $75\\mathrm{kHz}$ . The PLQE data were obtained from a three-step technique through the combination of a $445\\mathrm{nm}$ continuous wave laser, a spectrometer, an optical fibre and an integrating sphere. \n\nComputational methods. Since FA as a cation and I as an anion are the most abundant species in the experimentally studied $(\\mathrm{Cs_{_{0.05}}F A_{_{0.54}}M A_{_{0.41}}})\\mathrm{Pb}(\\mathrm{I_{_{0.98}}B r_{_{0.02}}})_{3}$ system, the incorporation of Na and F ions at different locations on the surfaces and bulk was investigated using $\\mathrm{FAPbI}_{3}$ as a model system. The DFT-optimized lattice parameter of cubic $\\mathrm{FAPbI}_{3}$ is $6.3\\dot{6}0\\mathring\\mathrm{A}$ . The surfaces were modelled using slab models consisting of $(2\\times2)$ cells in the $x$ and y direction and 5 repeating $\\mathrm{FAPbI}_{3}$ units constructed from the bulk structure with a vacuum of $15\\mathrm{\\AA}$ in the $z$ direction. Structural optimizations of all structures were performed using DFT implemented in the Vienna ab initio simulation package43,44. The Perdew, Burke and Ernzerhof functional within the generalized gradient approximation was used45. The outermost s, $\\boldsymbol{p}$ and $d$ (in the case of Pb) electrons were treated as valence electrons, whose interactions with the remaining ions were modelled by pseudopotentials generated within the projector-augmented wave method46,47. During the structural optimization, all ions were allowed to relax. An energy cutoff of $500\\mathrm{eV}$ and a $k$ -point scheme of $3\\times3\\times1$ were used to achieve energy and force convergence of $0.1\\mathrm{meV}$ and $20\\mathrm{meV}\\mathring{\\mathrm{A}}^{-1}$ , respectively. Information on chemical bonding analysis and formation energies of $\\mathrm{FA^{+}}$ vacancies in the reference, NaI- and NaF-containing perovskites is presented in Supplementary Notes 7 and 8. \n\nReporting Summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 2 August 2018; Accepted: 27 March 2019; Published online: 13 May 2019 \n\n# References \n\n1.\t Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n2.\t Wehrenfennig, C., Eperon, G. E., Johnston, M. B., Snaith, H. J. & Herz, L. M. High charge carrier mobilities and lifetimes in organolead trihalide perovskites. Adv. Mater. 26, 1584–1589 (2013). \n3.\t Snaith, H. J. Perovskites: the emergence of a new era for low-cost, highefficiency solar cells. J. Phys. Chem. Lett. 4, 3623–3630 (2013). \n4.\t Kim, H.-S. et al. Lead iodide perovskite sensitized all-solid-state submicron thin film mesoscopic solar cell with efficiency exceeding $9\\%$ . Sci. Rep. 2, 591 (2012). \n5.\t Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n6.\t Zhou, H. et al. Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). \n7.\t Yang, W. S. et al. High-performance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237 (2015). \n8.\t Yang, W. S. et al. Iodide management in formamidinium-lead-halide–based perovskite layers for efficient solar cells. Science 356, 1376–1379 (2017). \n9.\t Tan, H. et al. Efficient and stable solution-processed planar perovskite solar cells via contact passivation. Science 355, 722–726 (2017). \n10.\tBest Research-Cell Efficiencies (NREL, 2018); https://www.nrel.gov/pv/assets/ pdfs/pv-efficiency-chart.20181221.pdf \n11.\t Zheng, X. et al. Defect passivation in hybrid perovskite solar cells using quaternary ammonium halide anions and cations. Nat. Energy 2, 17102 (2017). \n12.\tBall, J. M. & Petrozza, A. Defects in perovskite-halides and their effects in solar cells. Nat. Energy 1, 16149 (2016). \n13.\tSherkar, T. S. et al. Recombination in perovskite solar cells: significance of grain boundaries, interface traps, and defect ions. ACS Energy Lett. 2, 1214–1222 (2017). \n14.\t Kim, J., Lee, S.-H., Lee, J. H. & Hong, K.-H. The role of intrinsic defects in methylammonium lead iodide perovskite. J. Phys. Chem. Lett. 5, 1312–1317 (2014). \n15.\tDuan, H.-S. et al. The identification and characterization of defect states in hybrid organic-inorganic perovskite photovoltaics. Phys. Chem. Chem. Phys. 17, 112–116 (2015). \n16.\tEames, C. et al. Ionic transport in hybrid lead iodide perovskite solar cells. Nat. Commun. 6, 7497 (2015). \n17.\t Azpiroz, J. M., Mosconi, E., Bisquert, J. & Angelis, F. D. Defect migration in methylammonium lead iodide and its role in perovskite solar cell operation. Energy Environ. Sci. 8, 2118–2127 (2015). \n18.\tMeggiolaro, D. et al. Iodine chemistry determines the defect tolerance of lead-halide perovskites. Energy Environ. Sci. 11, 702–713 (2018). \n19.\tYin, W.-J., Shi, T. & Yan, Y. Unique properties of halide perovskites as possible origins of the superior solar cell performance. Adv. Mater. 26, 4653–4658 (2014). \n20.\tDu, M. H. Efficient carrier transport in halide perovskites: theoretical perspectives. J. Mater. Chem. A 2, 9091–9098 (2014). \n21.\tYu, H., Lu, H., Xie, F., Zhou, S. & Zhao, N. Native defect-induced hysteresis behavior in organolead iodide perovskite solar cells. Adv. Funct. Mater. 26, 1411–1419 (2016). \n22.\tXiao, Z. et al. Giant switchable photovoltaic effect in organometal trihalide perovskite devices. Nat. Mater. 14, 193–198 (2015). \n23.\tWetzelaer, G.-J. A. H. et al. Trap-assisted non-radiative recombination in organic–inorganic perovskite solar cells. Adv. Mater. 27, 1837–1841 (2015). \n24.\tBerhe, T. A. et al. Organometal halide perovskite solar cells: degradation and stability. Energy Environ. Sci. 9, 323–356 (2016). \n25.\t Aristidou, N. et al. Fast oxygen diffusion and iodide defects mediate oxygeninduced degradation of perovskite solar cells. Nat. Commun. 8, 15218 (2017). \n26.\tSaidaminov, M. I. et al. Suppression of atomic vacancies via incorporation of isovalent small ions to increase the stability of halide perovskite solar cells in ambient air. Nat. Energy 3, 648–654 (2018). \n27.\tWang, S., Jiang, Y., Juarez-Perez, E. J., Ono, L. K. & Qi, Y. Accelerated degradation of methylammonium lead iodide perovskites induced by exposure to iodine vapour. Nat. Energy 2, 16195 (2016). \n28.\tJuarez-Perez, E. J., Hawash, Z., Raga, S. R., Ono, L. K. & Qi, Y. Thermal degradation of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite into $\\mathrm{NH}_{3}$ and $\\mathrm{CH}_{3}\\mathrm{I}$ gases observed by coupled thermogravimetry–mass spectrometry analysis. Energy Environ. Sci. 9, 3406–3410 (2016). \n29.\tYang, M. et al. Facile fabrication of large-grain $\\mathrm{CH_{3}N H_{3}P b I_{3-x}B r_{x}}$ films for high-efficiency solar cells via $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{B}\\mathrm{\\cdot}$ r-selective Ostwald ripening. Nat. Commun. 7, 12305 (2016). \n30.\tWang, F. et al. Phenylalkylamine passivation of organolead halide perovskites enabling high-efficiency and air-stable photovoltaic cells. Adv. Mater. 28, 9986–9992 (2016). \n31.\tMarco, N. D. et al. Guanidinium: a route to enhanced carrier lifetime and open-circuit voltage in hybrid perovskite solar cells. Nano Lett. 16, 1009–1016 (2016). \n32.\tNoel, N. K. et al. Enhanced photoluminescence and solar cell performance via Lewis base passivation of organic–inorganic lead halide perovskites. ACS Nano 8, 9815–9821 (2014). \n33.\tAbdi-Jalebi, M. et al. Maximizing and stabilizing luminescence from halide perovskites with potassium passivation. Nature 555, 497–501 (2018). \n34.\tSon, D.-Y. et al. Universal approach toward hysteresis-free perovskite solar cell via defect engineering. J. Am. Chem. Soc. 140, 1358–1364 (2018). \n35.\t Cao, J., Tao, S. X., Bobbert, P. A., Wong, C.-P. & Zhao, N. Interstitial occupancy by extrinsic alkali cations in perovskites and its impact on ion migration. Adv. Mater. 30, 1707350 (2018). \n36.\tYang, D., Yang, Y. & Liu, Y. A theoretical study on the red- and blue-shift hydrogen bonds of cis-trans formic acid dimer in excited states. Cent. Eur. J. Chem 11, 171–179 (2013). \n37.\tPhilippe, B. et al. Chemical and electronic structure characterization of lead halide perovskites and stability behavior under different exposures—a photoelectron spectroscopy investigation. Chem. Mater. 27, 1720–1731 (2015). \n38.\tChen, Q. et al. Controllable self-induced passivation of hybrid lead iodide perovskites toward high performance solar cells. Nano Lett. 14, 4158–4163 (2014). \n39.\tChen, Q. et al. The optoelectronic role of chlorine in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}(\\mathrm{Cl})$ -based perovskite solar cells. Nat. Commun. 6, 7269 (2015). \n40.\tAbdi-Jalebi, M. et al. Impact of monovalent cation halide additives on the structural and optoelectronic properties of $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite. Adv. Energy Mater. 6, 1502472 (2016). \n41.\tSnaith, H. J. et al. Anomalous hysteresis in perovskite solar cells. J. Phys. Chem. Lett. 5, 1511–1515 (2014). \n42.\tWang, L. et al. A-site cation effect on growth thermodynamics and photoconductive properties in ultrapure lead iodine perovskite monocrystalline wires. ACS Appl. Mater. Interfaces 9, 25985–25994 (2017). \n43.\tKresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n44.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n45.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n46.\tBlöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n47.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n\n# Acknowledgements \n\nThis work is supported by the National Natural Science Foundation of China (51722201; 51672008; 91733301), National Key Research and Development Program of China grant no. 2017YFA0206701, the Natural Science Foundation of Beijing, China (grant no. 4182026), the Young Talent Thousand Program, National Key Research and Development Program of China grant no. 2016YFB0700700, the National Natural Science Foundation of China (51673025) and Beijing Municipal Science and Technology Project no. Z181100005118002. S.T. acknowledges funding from the Computational Sciences for Energy Research tenure track programme of Shell, NWO and FOM (project no. 15CST04-2). The authors would like to thank W. Zou and J. Wang (Nanjing Tech University) for the PLQE measurement during the revision process, and Z. Dai for providing the dynamic light scattering measurement. \n\n# Author contributions \n\nH.Z. and N.L. conceived the idea and designed the experiments. S.T. designed and performed the DFT calculations. Both N.L. and X.N. were involved in all of the experimental parts. Y.C., Z.X., L.W. and H.L. contributed to the fabrication of highperformance PSCs. Z.Q., Y.Z. and L.L. helped to modify the experiments. Y.Lun, X.W. and J.H. performed the KPFM measurements, while Y.Liu, H.X. and Y.G. carried out the UPS and XPS measurement. G.Z. provided the film microstructure analysis. G.B. and C.K.O. assisted in DFT calculations. C.H., Y.B. and S.Y. performed ToF-SIMS measurements. H.Z., Q.C., S.T. and N.L. wrote the manuscript. C.K.O., X.N. and G.B. revised the manuscript. All authors were involved in the discussion of data analysis and commented on the manuscript. N.L. and S.T. have contributed equally to this work. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-019-0382-6. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to H.Z. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 \n\n# natureresearch \n\n# Solar Cells Reporting Summary \n\nNature Research wishes to improve the reproducibility of the work that we publish. This form is intended for publication with all accepted papers reporting the characterization of photovoltaic devices and provides structure for consistency and transparency in reporting. Some list items might not apply to an individual manuscript, but all fields must be completed for clarity. \n\nFor further information on Nature Research policies, including our data availability policy, see Authors & Referees. \n\n# Experimental design \n\n# Please check: are the following details reported in the manuscript? \n\n![](images/0ed5852fc094eb1feb33ec8ec4992d1cea715513b7c176e090381ea8177a6eed.jpg) \n\nCalculation of spectral mismatch between the reference cell and the devices under test \n\nMismatch factor of 1 was used in our measurements \n\n6. Mask/aperture \n\nSize of the mask/aperture used during testing \n\n0.09408 cm2 (Methods, Material Characterization) \n\nVariation of the measured short-circuit current density with the mask/aperture area \n\nWe haven't measure the cells with apertures of different sizes \n\n7. Performance certification \n\nIdentity of the independent certification laboratory that confirmed the photovoltaic performance \n\nCertified by the National Institute of Metrology, China (NIM, China) \n\nA copy of any certificate(s) Provide in Supplementary Information \n\n![](images/dfc5eab17da13de289ca63013058c6892faec67148d1f9a2d36f19e7c9170aa2.jpg) \n\n8. Statistics \n\nNumber of solar cells tested \n\nAt least 30 devices for each composition were tested (Supplementary Figure 11) \n\nStatistical analysis of the device performance \n\nSupplementary Figure 11 \n\n9. Long-term stability analysis \n\nType of analysis, bias conditions and environmental conditions For instance: illumination type, temperature, atmosphere humidity, encapsulation method, preconditioning temperature \n\n![](images/e2bc007a2730cab2f2d3b9856d688cf7a77edf2045ae4656c4be7fc5f1466332.jpg) \n\nLong-term stability including illumination stability, thermal stability, humidity stability and MPP (detailed conditions are shown in main text) " + }, + { + "id": "10.1017_S0885715619000812", + "DOI": "10.1017/S0885715619000812", + "DOI Link": "http://dx.doi.org/10.1017/S0885715619000812", + "Relative Dir Path": "mds/10.1017_S0885715619000812", + "Article Title": "The Powder Diffraction File: a quality materials characterization database", + "Authors": "Gates-Rector, S; Blanton, T", + "Source Title": "POWDER DIFFRACTION", + "Abstract": "The ICDD' s Powder Diffraction File (TM) (PDF (R)) is a database of inorganic and organic diffraction data used for phase identification and materials characterization by powder diffraction. The PDF has been available for over 75 years and finds application in X-ray, synchrotron, electron, and neutron diffraction analyses. With entries based on powder and single crystal data, the PDF is the only crystallographic database where every entry is editorially reviewed and marked with a quality mark that alerts the user to the reliability/quality of the submitted data. The editorial processes of ICDD' s quality management system are unique in that they are ISO 9001:2015 certified. Initially offered as text on paper cards and books, the PDF evolved to a computer-readable database in the 1960s and today is both computer and web accessible. With data mining and phase identification software available in PDF products, and the databases' compatibility with vendor (third party) software, the 1 000 000+ published PDF entries serve a wide range of disciplines covering academic, industrial, and government laboratories. Details describing the content of database entries are presented to enhance the use of the PDF. (C) 2019 International Centre for Diffraction Data.", + "Times Cited, WoS Core": 961, + "Times Cited, All Databases": 1003, + "Publication Year": 2019, + "Research Areas": "Materials Science", + "UT (Unique WOS ID)": "WOS:000500163500010", + "Markdown": "# CRYSTALLOGRAPHY EDUCATION ARTICLE \n\n# The Powder Diffraction File: a quality materials characterization database \n\nStacy Gates-Rector $\\textcircled{1}$ ,a) and Thomas Blanton $\\textcircled{1}$ International Centre for Diffraction Data, 12 Campus Blvd, Newtown Square, Pennsylvania 19073-3273, USA (Received 10 May 2019; accepted 9 September 2019) \n\nThe ICDD’s Powder Diffraction File $(\\mathrm{PDF}^{\\mathfrak{P}})$ is a database of inorganic and organic diffraction data used for phase identification and materials characterization by powder diffraction. The PDF has been available for over 75 years and finds application in X-ray, synchrotron, electron, and neutron diffraction analyses. With entries based on powder and single crystal data, the PDF is the only crystallographic database where every entry is editorially reviewed and marked with a quality mark that alerts the user to the reliability/quality of the submitted data. The editorial processes of ICDD’s quality management system are unique in that they are ISO 9001:2015 certified. Initially offered as text on paper cards and books, the PDF evolved to a computer-readable database in the 1960s and today is both computer and web accessible. With data mining and phase identification software available in PDF products, and the databases’ compatibility with vendor (third party) software, the $1\\ 000\\ 000+$ published PDF entries serve a wide range of disciplines covering academic, industrial, and government laboratories. Details describing the content of database entries are presented to enhance the use of the PDF. $\\mathfrak{C}$ 2019 International Centre for Diffraction Data. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. \n[doi:10.1017/S0885715619000812] \n\nKey words: powder X-ray diffraction, XRD database, quality mark, subfiles, PDF card \n\n# I. INTRODUCTION \n\nThe Powder Diffraction File (PDF) is a database produced and maintained by the International Centre for Diffraction Data $\\mathrm{(ICDD^{\\circledast})}$ ), a non-profit scientific organization committed to meeting the needs of the scientific community through the collection, editing, publishing, and distribution of powder X-ray diffraction (PXRD) data for the identification of materials (Fawcett et al., 2017). The primary purpose of the PDF is to serve as a quality reference tool for the powder diffraction community. This tool provides insight into the structural and crystallographic properties of a material, which allows for phase identification using powder diffraction techniques. The PDF has been the primary qualitative crystalline phase identification reference for powder diffraction data since 1941 (Jenkins et al., 1987) and, in recent years, has expanded its coverage to include semi-crystalline and amorphous materials (Gates et al., 2014). \n\nDatabases, like the PDF, that provide structural details, such as lattice parameters, space group, atomic coordinates, and thermal parameters, can be used for a range of tasks, including (but not limited to) structure modeling, phase identification, and quantification [Belsky et al., 2002 (ICSD); Downs and Hall-Wallace, 2003 (AMCSD); Gražulis et al., 2012 (COD); Groom et al., 2016 (CSD); Villars and Cenzual, 2018 (PCD)]. As a result, structural databases are one of the key tools used in the crystallographic community (Kuzel and Danis, 2007). Though these databases do tend to have some common applications, they often differ in content, format, and functionality. In PDF-4 products, structure details, when available, are provided on a designated tab of the PDF card, as will be discussed later in the text. \n\n# A. Creation of the PDF \n\nIn 1941, the American Society for Testing and Materials (ASTM) published the first official set (Set 1) of the PDF; each entry was printed on a $3^{\\prime\\prime}\\times5^{\\prime\\prime}$ paper card [Figure 1(a)]. The Joint Committee on Powder Diffraction Standards (JCPDS) was evolved from ASTM in 1969 and renamed to ICDD in 1978. The inaugural PDF database consisted of 978 cards displaying a collection of $d{-}I$ data pairs, where the $d.$ -spacing $(d)$ was determined from the angle of diffraction, and the relative peak intensity $(I)$ was obtained experimentally under the best possible conditions for a phase pure material. The list of $d{-}I$ data pairs is often described as the diffraction “fingerprint” of a compound. Each $3^{\\prime\\prime}\\times5^{\\prime\\prime}$ PDF file card was formatted so that the $d{-}I$ pairs of the three most intense peaks were placed at the top-left edge of the card, which was ideal when using the Hanawalt search method (Hanawalt et al., 1938) for phase identification. The full $d{-}I$ list and supporting information were presented on the remaining space of each card. In 1967, a computer-based version of the PDF (PDF-1) became available on magnetic tape, with limited data provided for search-match only. However, it was not until 1985 that the first digital version containing all of the data that appeared on a PDF card image was made available in computer-readable format on CD-ROM (PDF-2) (Messick, 2011). \n\nThe increased use of the computer-based PDF database, and the problems associated with the storage of the classic cards, prompted the ICDD to discontinue the production of \n\n
(a)
d5.52.853.03##
#1.001.000.800.50 1.00
505040
2.8550
Z=
a.= b= c.=3.15 2.0Y
A= C=
D=
n= w= =N
\n\n![](images/72c6e6ee5534a0db5716745cbe859f2ed084000d3115483abe2536c96b5a0fc3.jpg) \nFigure 1. (Color online) PDF card image for $\\mathrm{Ce}_{2}(\\mathrm{SO}_{4})_{3}$ from PDF Set 1 as issued (a) in 1941 and (b) in 2019. \n\ncards in 1987, leaving books as the only hardcopy form published (Smith and Jenkins, 1996). Over the years, various seminal events have transformed the original card catalog/ index styled database into an electronic resource, having a relational database format (Faber and Fawcett, 2002). The initial design of the PDF “card” supported the primary purpose of the database, phase identification by search-match processing. Thus, the core design was retained upon conversion from printed to digital cards and has progressively been enhanced over time [Figure 1(b)]. With reduced limitations on presentation space, pivotal information pertaining to the phase(s) of interest were added to PDF card entries, which greatly enriched the comprehensiveness of the database. By 2015, benefits associated with the computer-based PDF significantly outweighed those of hardcopy versions. Thus, as of 2017, all printed PDF database products were discontinued. \n\nHaving a comprehensive database that houses all PDF patterns allows users to carry out single and multi-phase identification. The capacity of the database has evolved over time in order to support innovative analyses methods and instrumentation advances that have been developed in the field of diffraction. Currently, the PDF contains data to support analysis pertaining to X-ray, electron, and neutron diffraction, which may include entries for crystalline, semi-crystalline, amorphous, modulated, disordered clays, and nanomaterials (Bruno et al., 2017). \n\n# II. DATABASE DEVELOPMENT \n\nThe PDF is continuously enhanced, and maintained, by ICDD staff and members. An updated, revised, and new version of the database is released annually providing users a contemporary reference tool that helps them to obtain “correct” answers – not just “any” answer. Each new PDF release comes with an increased number of entries (Figure 2), as well as enhanced functionality via new software features. In recent years, there have been expectations for reference data to be freely available, but often times this comes at the sacrifice of quality. \n\n![](images/afd96bae8dd6844a2dcad21132e95e327cf7cb5e0334aa49afa79d3ef778f21c.jpg) \nFigure 2. (Color online) Graphical representation of the lifetime growth of PDF-4, with the number of new entries for the specified annual release shown on top (red). The spike in newly published entries observed in 1998 and 2005 reflect the onset of collaborations with FIZ (ICSD) and MPDS (LPF), respectively. \n\nThe overall quality of the PDF improves progressively as higher quality entries are included in the database. Subsequently, the number of low-quality patterns has decreased by ${\\sim}10\\%$ in the last 15 years. Though some believe that low-quality entries can undesirably influence the overall statistics of the database and they should be removed, these patterns are editorially reviewed and included with significant details. The mindset being, even a partial match of data may be crucial in assisting users in proper phase identification, or even elimination of certain phases/possibilities. \n\n# A. Data acquisition (data sources) \n\nThe PDF is a compilation of diffraction data from various sources, including ICDD and contributions from collaborative databases: Inorganic Crystal Structure Database (ICSD), the Linus Pauling File (LPF), the National Institute of Standards & Technology (NIST) Crystal Data, and Cambridge Structural Database (CSD). As a result, much of the diffraction data originates from the literature and originally lacked uniformity. The quality of the data is generally limited by both the diffraction technique used during experimentation and the instrument capabilities at the time of publication. Therefore, when utilizing data from multiple sources, ICDD processes entries in a manner that converts data into a common format and requires every entry to undergo editorial review and be classified based on their level of quality. Various databases offer calculated PXRD data, including the PDF. However, a unique feature of the PDF is the availability of actual experimental raw powder data acquired primarily through ICDD’s grant-in-aid program. This type of data is useful during materials’ characterization as the calculated PXRD data may not always clearly explain the observed diffraction pattern and can be significantly different from what is observed during the experiment. Therefore, theoretical, or calculated, patterns may not always properly represent what is truly observed during experimental data collection. Some examples of where this discrepancy is evident are materials of small crystallite size, polymeric materials, and clays. When the phase of interest is amorphous or semi-crystalline, a d–I list and/or atomic coordinates will not adequately define the amorphous profile observed in a diffraction pattern (Figure 3). To allow for improved whole pattern analysis, particularly when amorphous phases are present, the PDF also includes digital raw data patterns, referred to as PDF experimental patterns (PD3s), for amorphous, semi-crystalline, and crystalline phases (Gates et al., 2014). \n\n# B. Data standardization (quality system) \n\nAnother distinct attribute of the PDF is its quality system. Once the data are obtained from a source, prior to inclusion in the PDF, each entry is reviewed for appropriateness and quality. In the past, the evaluation of quality was somewhat subjective until 1965 when the $d$ -values and intensities were first entered into computer-readable files (Smith and Jenkins, 1996). This allowed data to be checked based on crystallographic principles in a timely and efficient manner. Over time, important criteria could be added, or removed, based on the knowledge of the crystallographic field and experimental capabilities of the time. As a result, the review process has become more rigorous, with multiple computer algorithms utilized to aid in pattern assessment and quality determination. The benefit being an objective uniformity of quality mark assignments. \n\n![](images/39e9bd6e45602ffba0cddc98a6a4b36a36c232a3ae47df58c60f4a7601d4ae7d.jpg) \nFigure 3. (Color online) (a) Stick pattern $\\scriptstyle(d-I$ list) and (b) raw data (PD3) representation of cellulose Iβ. This example demonstrates how raw data patterns fo polymers cannot always be accurately represented from a $d{-}I$ list alone. \n\nICDD has developed a multi-tiered editorial process that enables the categorization of each entry based on the quality and comprehensiveness of the data. Subsequently, a quality mark (QM) is assigned to each entry to distinguish for PDF users the high-quality $\\mathrm{\\nabla{QM}=^{*}}$ or G), medium-quality (QM ${\\bf\\varepsilon}={\\bf I}$ , C, P, or M), low-quality $\\mathbf{\\mathrm{QM}}=\\mathbf{B}$ or O), or hypothetical $\\mathrm{(QM=H)}$ patterns. The original criteria for quality mark assignment were somewhat broad and designed for single phase crystalline patterns. As the database grew and evolved in both content and format, so did the quality system. The original five quality marks and criteria, shown in Table I (Jenkins and Smith, 1987), have expanded in order to reflect processed/refined data patterns, as well amorphous and semicrystalline materials (Bruno et al., 2017). The current quality marks and major criteria are shown in Table II, along with a brief description of any commonly associated warnings. \n\nAnother benefit resulting from ongoing editorial review of the PDF is the designation of subfile(s) and subclass(es). The PDF subfiles are generated based on (1) chemical definitions and/or (2) field application (via expert opinion). Subfiles are powerful tools in the database, as they allow users to target their searches in order to save time and reduce the frequency of false matches during the identification process. Some of the editorial improvements, not available in other databases, result from specialized task groups. These expert-lead groups focus on specific classes of materials (i.e. Ceramics, Metals & Alloys, Minerals, Zeolites, etc.) and make detailed recommendations based on the field of study (subfile), for specific PDF entries. These recommendations are then submitted for final review before being incorporated into the database(s). The \n\nTABLE I. Original major criteria in the assignment of quality marks for PDF entries. \n\n\n
MarkAverage △ 2-ThetaCrystallographic informationSignificant figures in “d\"Other
0.03Cell known, no unindexed linesd<2.5 (3), d<1.2 (4) I's measured quantitatively chemistry confirmed
I0.06Cell known, two unindexed linesd<2 (3)I's measured quantitatively
CCell knownd<2.5 (3), d<1.2 (4)Structure factor R<0.1
\n\nNotes: (1) An “O” indicates: low precision, no cell quoted, poorly chemically characterized, and possible mixture (or a combination of the above). (2) A “Blank” indicates patterns which do not meet the criteria for a $\\star^{,,}$ , an “I”, or an “O” or patterns for which no cell is known and, therefore, cannot be assessed fo consistency and line indexing. \n\n
TABLEI. Major criteria for PDF quality mark assignment.
Mark20Crystallographic informationWarningsOther
Sor (★)Average ≤ 0.03°·High-quality diffractometer or Guinier data · Known unit cell · Complete indexing· NoneSpecific to experimentally based patterns
Gn/a· Significant amorphous component present · Good signal-to-noise ratio in digital diffraction pattern (PD3) providedn/a(i.e. spectroscopy, pair distribution functions, commercial source, etc.)
IAverage ≤ 0.06° Absolute ≥ 0.20° for individual reflectioncomposition of a material · Indexed pattern · Known unit cell · Reasonable range and uniform distribution in intensities· No serious systematic errors · Maximum of two unindexed, space group extinct, or impurity reflections; none of theseCompleteness of the pattern is sensible. Reflections with d-value less than or equal to 2.000 A have at least three significant figures after the decimal point
C· Pattern calculated from single crystal structural parameters for which the structural refinement R-factor was <0.10 ·lF(calc)l data have been checked against the corresponding IF(obs)l -OR— ·A complete check of the bond· If the calculated pattern does not meet the“S” quality mark parameters, it is assigned QM=BIf the structure is derived by X-ray Rietveld methods, the calculated pattern is accepted only in unusual cases; the original powder pattern is preferred.
M· The number of required significant digits is the same as for an “S\" quality mark · Amorphous component present · Good signal-to-noise ratio in digitalNo chemical analysis data to support the materials composition provided
Blankdiffraction pattern (PD3) provided No cell No indexingDoes not meet criteria for higher quality mark (\"T' or “O\")
0data are known (or suspected) to be of low precision · Number of unindexed, space group extinct, or impurity· Poorly characterized material or the· Usually, the editor has inserted a comment to explain why the“O” was assignedA low-precision quality mark means that the diffraction data remain questionable and user's should evaluate closely if used
\n\n![](images/35654f892ece0846a562da3a351291a983a340f7347275337959215d17e4c716.jpg) \nFigure 4. (Color online) Digital PDF card 00-045-0338: calcium iron phosphate, $\\mathrm{Ca_{9}F e(P O_{4})_{7}}$ with designators corresponding to descriptions in Tables III and IV \n\nTABLE III. Overview of contents of a PDF entry. \n\n\n
1PDFIDEntry number
2Diffraction dataDiffraction type (X-ray, electron, and neutron), wavelength apertures, intensity variables
3 d-I listInterplanar spacings (d) and intensities (I). Miller indices are listed when available
4Tick marksGraphical representation of peak position
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Supplemental information tabsfor this entry
Provides additional details pertaining to: (A)“PDF\"- chemistry & general info(F) “Classification\"- subfile(s), structure type(s)
(B)“Experimental”- diffraction experiment(G)“Cross-references”- correlated PDF entries
(C)“Physical’- unit cell data (from the author)(H)“Reference”-- bibliographic references
(D)“Crystal”-- ICDD calculated unit cell data (E)“Structure”- atomic structure(I)“Comments\"- database comments
\n\nPDF subfiles are continuously edited, reviewed, and classified by ICDD, and can be used with any software system that recognizes ICDD subfile designations, to improve the efficiency and accuracy of the identification process when using the PDF. \n\n# III. THE PDF CARD \n\nIndividual entries of the PDF are often referred to as “PDF cards”, which is a term carried over from the original “hardcopy” format of the database. The “cards” are categorically numbered (AA-BBB-XXXX) to indicate the data source (where AA means “00” – ICDD; “01” – ICSD; “02” – CSD; “03” – NIST; $^{\\cdot\\cdot}04^{,3}\\mathrm{~-~}\\mathrm{LPF}$ ; and $\\mathrm{\\ddot{\\mathrm{05^{,9}}}-I C D D_{\\mathrm{(cry}}}$ stal data)). Each data source has set numbers, BBB, corresponding to the annual publication, and a pattern number (XXXX). As a result, one can surmise from the PDF card in Figure 4 (00-045-0338) that this entry contains data from an ICDD pattern (data source $=00^{\\cdot}$ ) that was first included in set 45 (published in 1995) and is pattern number 0338. The PDF entries also contain extensive chemical, physical, bibliographic, and crystallographic data. The red labels in Figure 4 highlight the different components of the PDF card and corresponding details can be found in Tables III and IV. \n\nWhen available, much of the crystallographic data resides on the “Physical” tab of the PDF card (Figure 5). This is where the basic information pertaining to the unit cell can be found (i.e. crystal symmetry, lattice parameters, space group, etc.). \n\nTABLE IV. Details for fields on the “PDF” supplemental information tab (Tab A in Figure 4). \n\n\n
Editorial designationsStatus- primary, alternate,or deletedQuality mark- See Table II: Major criteria for PDFquality mark assgnment
A1 A2Sample conditionsSpecifies the environment, temperature, and pressure of data collection
A3 ChemistryIndicatesthe polymorphicdesignation of agiven phase,as wellas the formula(e),weight percent, and atomic percent
associate with entry, as available
A4 A5Compound identifier(s) HistoryNames and registry numbers used to identify the compound Specifics pertaining to the entries initial publication, and recent modifications, if applicable
\n\n![](images/76b9d0fe3f2c07562a195c70dc9aca787eb865037f46f8d1cefc794b44e44326.jpg) \nFigure 5. (Color online) “Physical” tab with designators showing where to locate (C1) unit cell settings, (C2) lattice parameters, (C3) unit cell volume, (C4) axial ratio(s), (C5) density values (calculated, measured, and structural), and (C6) data validation values. \n\n![](images/c30aaeb0939fc634a1a918259bda0b5f6ef14101e0301a3b37709d287dc35e1d.jpg) \nFigure 6. (Color online) “Structure” tab with designations pertaining to (E1) the original source of the atomic coordinates (if cross-referenced), (E2) symmetry operators, (E3) thermal parameter type, (E4) fractional/atomic coordinates, (E5) anisotropic displacement parameters, (E6) and (E7) unit cell information derived from the single crystal experiment (which can be different from powder unit cell information on the “Physical” tab). \n\nAtomic coordinates are included for a significant number of PDF entries and can be located on the “Structure” tab, shown in Figure 6. The information provided on this tab enables users to perform qualitative and/or semi-quantitative analyses using the PDF-4 products. Additionally, users have the option to export the crystallographic information in several different formats for use in third party pattern fitting software including quantitative analysis techniques. \n\n# IV. AVAILABILITY \n\nThe PDF is available for individual or collaborative use. ICDD provides numerous database products that are specifically designed to meet the needs of those in a variety of areas in the diffraction community, ranging from phase identification (PDF-2) to semi-quantification or full pattern fitting using atomic coordinates (PDF-4). Product summaries, licensing info, and operating specifications for each member of the PDF product line are available on the ICDD website (www.icdd.com). \n\nCurrently, ICDD collaborates with licensed software developers, including equipment manufacturers and independent developers, and works diligently to cultivate commercial data analysis programs that work seamlessly with our databases. PDF products include their own front-end software that allows the use of the stored PDF entry data for data mining, compound and structure visualization, and data simulations. Use of the PDF front-end software offers valuable features, and information that may not always be seen through vendor’s software. This factor can be of benefit to users looking for additional details or supplemental information pertaining to a material, or group of materials. Also available is ICDD’s search indexing programs, SIeve or SIeve+, that are operable through the PDF front-end software. SIeve/SIeve+ is designed to search and identify unknown materials by engaging data mining interfaces, searches, sorting, and then applying various algorithms to optimize the phase identification process. \n\n![](images/77e5a46bf1a055742b525a60853fad5d4e0ae0b41ceefb7901de1eec458e5b37.jpg) \nFigure 7. (Color online) Composition graph displaying PDF entries as points on the phase diagram of Zn, $\\mathtt{C u}$ , and Ni. \n\n# V. SIGNIFICANCE OF UPDATING PDF (CONCLUSION) \n\nTechnological advances in instrumentation over the years have undoubtedly influenced the manner in which PXRD data are collected, reviewed, stored, and presented in PDF products. These advances play a role in the quality of diffraction data inserted into the database. The data collection capabilities of newer instruments, combined with meticulous editorial processes, have greatly improved the overall quality of the PDF database. Though the initial creation the PDF was intended for phase identification, over the years the database has transitioned into a high-quality, comprehensive, materials’ identification tool whose increased size and functionality has also improved its quality and usefulness. Recent developments include the addition of composition graphing, 2D diffraction pattern overlay capability, 2D diffraction phase identification analysis $(i n\\ S I e\\nu e+)$ , and microanalysis (XRF) searches. The phase composition graph/search feature allows the user the ability to data mine based on binary or ternary compositions, and generate a resultant plot (Figure 7) where the user can select any data point on the graph to open the corresponding PDF entry. This new functionality has reduced the necessary steps it takes to compare and contrast binary and/or ternary phases in the PDF and has proven quite useful for individuals working with metals and alloys. With significant changes made annually, it is of benefit to all PDF users to keep their PDF databases up-to-date in order to ensure comprehensiveness and relevancy. \n\n![](images/a8373f27b396e2fce60768d3840703520945e6f8ecfa6d865d085db57d7c825b.jpg) \nFigure 8. (Color online) Lifetime growth of the PDF- $^{4+}$ (teal) and PDF-4/Organics (purple) databases. \n\nThe current release of PDF products (Release 2019) contains a combined total of 1 004 568 published entries (Figure 8) that can be used in analyses of powder diffraction data. Using PDF product that are several years old omits recently added entries and prevents users from taking advantage of the latest features and capabilities of the PDF. The Powder Diffraction File continues to grow and evolve concurrently with the community and remains the world’s most comprehensive source of inorganic and organic diffraction data for phase identification and materials’ characterization. \n\nBelsky, A., Hellenbrandt, M., Karen, V. L., and Luksch, P. (2002). “New developments in the inorganic crystal structure database (ICSD): \n\naccessibility in support of materials research and design,” Acta Crystallogr. Sect. A. 58(3), 364–369. \nBruno, I., Gražulis, S., Helliwell, J. R., Kabekkodu, S. N., McMahon, B., and Westbrook, J. (2017). “Crystallography and databases,” Data Sci. J. 16, 1–17. \nDowns, R. and Hall-Wallace, M. (2003). “The American Mineralogist crystal structure database,” Am. Mineral. 88, 247–250. \nFaber, J. and Fawcett, T. (2002). “The powder diffraction file: present and future,” Acta Crystallogr. Sect. B. 58, 325–332. \nFawcett, T. G., Kabekkodu, S. N., Blanton, J. R., and Blanton, T.™N. (2017). “Chemical analysis by diffraction: the powder diffraction file ,” Powder Diffr. 32, 63–71. \nGates, S. D., Blanton, T. N., and Fawcett, T. G. (2014)™. “A new ‘Chain’ of events: polymers in the powder diffraction file $(\\mathrm{PDF}^{\\mathfrak{B}})$ ,” Powder Diffr. 29, 102–107. \nGražulis, S., Daškevič, A., Merkys, A., Chateigner, D., Lutterotti, L., Quirós, M., Serebryanaya, N. R., Moeck, P., Downs, R. T., and Le Bail, A. (2012). “Crystallography open database (COD): an open-access collection of crystal structures and platform for World-Wide Collaboration,” Nucleic Acids Res. 40, D420–D427. \nGroom, C. R., Bruno, I. J., Lightfoot, M. P., and Ward, S. C. (2016). “The Cambridge structural database,” Acta Crystallogr. Sect. B. 72, 171–179. \nHanawalt, J. D., Rinn, H. W., and Frevel, L. K. (1938). “Chemical analysis by X-ray diffraction,” Ind. Eng. Chem. Anal. Ed. 10, 457–512. \nJenkins, R. and Smith, D. (1987). “Powder Diffraction File,” in Crystallographic Databases, edited by F. H. Allen, G. Bergerhoff, and R. Sievers (Data Commission of the International Union of Crystallography, UK), pp. 159-174. \nJenkins, R., Holomany, M., and Wong-Ng, W. (1987). “On the need for users of the powder diffraction file to update regularly,” Powder Diffr. 2, 84–87. \nKuzel, R. and Danis, S. (2007). “Structural databases of inorganic materials,” Mater. Struct. Chem., Biol., Phys. Technol. 14, 89–96. \nMessick, J. (2011). “The history of the international centre for diffraction data,” Powder Diffr. 27(1), 36–44. \nSmith, D. and Jenkins, R. (1996). “The powder diffraction file: past, present, and future,” J. Res. Natl. Inst. Stand. Technol. 101(3), 259–271. \nVillars, P. and Cenzual, K. (2018). Pearson’s Crystal Data: Crystal Structure Database for Inorganic Compound (ASM International and Material Phases Data System, Materials Park, OH). " + }, + { + "id": "10.1126_science.aay9698", + "DOI": "10.1126/science.aay9698", + "DOI Link": "http://dx.doi.org/10.1126/science.aay9698", + "Relative Dir Path": "mds/10.1126_science.aay9698", + "Article Title": "Constructive molecular configurations for surface-defect passivation of perovskite photovoltaics", + "Authors": "Wang, R; Xue, JJ; Wang, KL; Wang, ZK; Luo, YQ; Fenning, D; Xu, GW; Nuryyeva, S; Huang, TY; Zhao, YP; Yang, JL; Zhu, JH; Wang, MH; Tan, S; Yavuz, I; Houk, KN; Yang, Y", + "Source Title": "SCIENCE", + "Abstract": "Surface trap-mediated nonradiative charge recombination is a major limit to achieving high-efficiency metal-halide perovskite photovoltaics. The ionic character of perovskite lattice has enabled molecular defect passivation approaches through interaction between functional groups and defects. However, a lack of in-depth understanding of how the molecular configuration influences the passivation effectiveness is a challenge to rational molecule design. Here, the chemical environment of a functional group that is activated for defect passivation was systematically investigated with theophylline, caffeine, and theobromine. When N-H and C=O were in an optimal configuration in the molecule, hydrogen-bond formation between N-H and I (iodine) assisted the primary C=O binding with the antisite Pb (lead) defect to maximize surface-defect binding. A stabilized power conversion efficiency of 22.6% of photovoltaic device was demonstrated with theophylline treatment.", + "Times Cited, WoS Core": 1015, + "Times Cited, All Databases": 1051, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000503861000054", + "Markdown": "# SOLAR CELLS \n\n# Constructive molecular configurations for surface-defect passivation of perovskite photovoltaics \n\nRui Wang1\\*, Jingjing $\\mathsf{x u e}^{1\\ast}\\dag$ , Kai-Li Wang2\\*, Zhao-Kui Wang1,2†, Yanqi Luo3, David Fenning3, Guangwei ${\\tt X}{\\tt u}^{1}$ , Selbi Nuryyeva1,4, Tianyi Huang1, Yepin Zhao1, Jonathan Lee Yang5, Jiahui Zhu1, Minhuan Wang1, Shaun Tan1, Ilhan Yavuz $^{6}\\dag$ , Kendall N. Houk4†, Yang Yang1,7† \n\nSurface trap–mediated nonradiative charge recombination is a major limit to achieving high-efficiency metal-halide perovskite photovoltaics. The ionic character of perovskite lattice has enabled molecular defect passivation approaches through interaction between functional groups and defects. However, a lack of in-depth understanding of how the molecular configuration influences the passivation effectiveness is a challenge to rational molecule design. Here, the chemical environment of a functional group that is activated for defect passivation was systematically investigated with theophylline, caffeine, and theobromine. When N-H and $\\complement=0$ were in an optimal configuration in the molecule, hydrogen-bond formation between N-H and I (iodine) assisted the primary $\\complement=0$ binding with the antisite $\\mathsf{P b}$ (lead) defect to maximize surface-defect binding. A stabilized power conversion efficiency of $22.6\\%$ of photovoltaic device was demonstrated with theophylline treatment. \n\nD teifvectchparsgseivraetciomnbtionarteidouncies aun epfrfeocdtiuvce- strategy to increase the power conversion efficiency (PCE) of polycrystalline metal-halide perovskite thin-film photovoltaics (PVs) (1–6). The ionic nature of the perovskite lattice enables molecular passivation through coordinate binding based on Lewis acid-base chemistry (7–10). Organic molecules containing various functional groups, such as carbonyl groups, can passivate defects (11–17). The selection of molecules with optimal binding configurations for defect passivation would benefit from molecular design rules. \n\nWe demonstrate high efficiencies for $(\\mathrm{FAPbI_{3}})_{\\mathrm{x}}(\\mathrm{MAPbBr_{3}})_{1-x}$ (where FA is formamidinium and MA is methylammonium; $x$ is 0.92 in the precursor) perovskite PV devices through defect identification followed by rational design and comprehensive investigation of the chemical environment around the active functional group for defect passivation (18). In high-quality perovskite polycrystalline thin films that have monolayered grains (19–21), interior defects of perovskite are negligible compared with the surface defects. We used density functional theory (DFT) calculations to compare the formation energies of selected native defects on the perovskite surface. Particularly taken into consideration were Pband I-involving point defects, Pb vacancy $(\\mathrm{V_{Pb}})$ , I vacancy $(\\mathrm{V_{I}})$ , and $\\mathrm{Pb\\mathrm{-}I}$ antisite $\\mathrm{\\cdot}\\mathrm{\\mathbf{P}}\\mathrm{b}_{\\mathrm{I}}$ and $\\mathrm{{I_{Pb}}},$ corresponding to I site substitution by Pb and Pb site substitution by I, respectively) because the band edges of perovskite were reported to be composed of Pb and I orbitals (22, 23). \n\nAs confirmed by x-ray photoelectron spectroscopy (XPS), the surface of the as-fabricated perovskite thin film synthesized by a two-step method was $\\mathrm{Pb}$ -rich (fig. S1), and we focused on the (100) surface with $\\mathrm{PbI_{2}}$ termination in a Pb-rich condition. The types of surface defects studied and their corresponding top-layer view of atomic structures are shown in Fig. 1A. Using the Dispersion Correction 3 (DFT-D3) method, we calculated the defect formation energies (DFEs) (table S1) of $\\mathrm{\\DeltaV_{Pb}}$ , $\\mathrm{\\DeltaV_{I},}$ $\\mathrm{Pb}_{\\mathrm{I}},$ and $\\mathrm{I_{Pb}}$ on the surface to be 3.20, 0.51, 0.57, and $3.15\\mathrm{eV}$ , respectively. Compared with the values reported in bulk perovskite, ${\\mathrm{\\DeltaV_{Pb},V_{I},}}$ and $\\mathrm{I_{Pb}}$ defects show similar DFEs (24), whereas the $\\mathrm{Pb}_{\\mathrm{I}}$ antisite defect exhibited particularly lower formation energy than that in the bulk. Thus, the $\\mathrm{\\sfPb}_{\\mathrm{I}}$ antisite defect should form more readily and predominate on the surface. We did not consider $\\mathrm{\\DeltaV_{I}}$ further despite its DFE being as low as that of $\\mathrm{Pb}_{\\mathrm{I}},$ because the interaction of molecules with the $\\mathrm{\\DeltaV_{I}}$ turned out to be not energy favorable (fig. S2). \n\nOn the basis of these results, we focused on the interaction between the surface $\\mathrm{\\Pb}_{\\mathrm{I}}$ antisite defect and candidate molecules for defect passivation. A set of small molecules sharing the identical functional groups but with strategically varying chemical structure were investigated, namely theophylline, caffeine, and theobromine, interacting with the defects (Fig. 1B). These molecules are found in natural products (tea, coffee, and chocolate, respectively) and are readily accessible. In these molecules, the conjugated structure as well as the dipoles induced by the hetero atoms tend to increase the intermolecular interaction. This renders them nonvolatile in nature, which is key to the investigation of their interactions with defects in perovskite and long-term stability of the devices. The xanthine core also helps maintain the coplanarity of the carbonyl group and the N–H. Unlike other small molecules with flexible alkyl chains, this rigidity allows us to define the configuration and distance between the carbonyl group and N–H when they are interacting with the defects, as a result of which the constructive molecular configuration for defect passivation can be unraveled. \n\n![](images/fcaccc56dd858d4bfa1935efc899d28133be5c6cda2462a277b9c237ff29c4e9.jpg) \nFig. 1. Surface-defect identification and constructive configuration of the $\\scriptstyle\\mathbf{c}=\\mathbf{0}$ group in three different chemical environments. (A) Top view of the various types of surface defects. (B) Theoretical models of perovskite with molecular surface passivation of $\\mathsf{P b}_{\\mathsf{I}}$ antisite with theophylline, caffeine, and theobromine. (C) $J-V$ curves of perovskite solar cells with or without small-molecules treatment under reverse scan direction. \n\nWe incorporated theophylline onto the surface of perovskite thin film using a posttreatment method, and a PCE enhancement from $21.02\\%$ (stabilized $20.36\\%$ ) to $23.48\\%$ (stabilized $22.64\\%$ ) was observed in the PV devices with ITO $\\mathrm{\\SnO_{2}/}$ perovskite/SpiroOMeTAD/Ag structure under reverse scan direction [where ITO is indium tin oxide, $\\mathrm{{snO}_{2}}$ is tin oxide, and Spiro-OMeTAD is $^{2,2^{\\prime}7,7^{\\prime}}$ - tetrakis-(N,N-di- $p$ -methoxyphenyl amine)-9,9′- spirobifluorene]. Current density-voltage $\\left(J\\mathbf{-}V\\right)$ curves of the PV devices with and without theophylline treatment are compared in Fig. 1C and table S2. The control device showed an open-circuit voltage ( $\\mathrm{\\Delta}V_{\\mathrm{OC}})$ of $1.164\\mathrm{V}$ , a shortcircuit current $(J_{\\mathrm{SC}})$ of $24.78\\mathrm{mAcm^{-2}}$ , and a fill factor (FF) of $72.88\\%$ , whereas the target device showed a $V_{\\mathrm{OC}}$ of 1.191 V, a $J_{\\mathrm{SC}}$ of $25.24\\mathrm{mAcm^{-2}}$ , and an FF of $78.11\\%$ . The enhancement in the $V_{\\mathrm{OC}}$ was attributed to the surface passivation by theophylline through the Lewis base-acid interaction between $\\scriptstyle\\mathbf{C=O}$ group and the antisite Pb. As shown in the surface structure model of perovskite with theophylline (Fig. 1B), the $\\scriptstyle\\mathrm{C=O}$ group on theophylline strongly interacted with the antisite $\\mathrm{\\Pb}$ . The neighboring $\\mathbf{N}{\\cdot}\\mathbf{H}$ on the imidazole ring also interacted with the \n\nI of $\\mathrm{PbI}_{6}^{2-}$ octahedron through a hydrogen bond (H-bond), which strengthened the absorption of theophylline onto the $\\mathrm{\\DeltaPb_{I}}$ defect, resulting in an interaction energy $(E_{\\mathrm{int}},$ defined as Emolecule-perovskite $-E_{\\mathrm{perovskite}}-E_{\\mathrm{molecule}})$ as strong as $-1.7\\mathrm{eV}$ . \n\nThis observation suggested that the neighboring H-bond between the xanthine molecule and the $\\mathrm{PbI}_{6}^{2-}$ octahedron can contribute to the defect passivation. A methyl group was added to the N on the imidazole ring of theophylline (resulting in caffeine) to eliminate the effect from H-bonding between the $\\mathrm{{N-H}}$ and I, leaving just the interaction with surface $\\mathrm{Pb}_{\\mathrm{I}}$ defects (Fig. 1B). The missing H-bond between $\\mathrm{\\DeltaN-H}$ and $\\mathrm{PbI}_{6}^{2-}$ octahedron resulted in a weakened interaction and a less favorable $E_{\\mathrm{int}}$ of $-1.3\\mathrm{\\eV}.$ . Compared with the theophyllinetreated device, a caffeine-treated perovskite PV device had a lower PCE of $22.32\\%$ along with a lower $V_{\\mathrm{OC}}$ of 1.178 V, $J_{\\mathrm{SC}}$ of $25.04\\mathrm{mAcm^{-2}}$ , and FF of $75.76\\%$ . \n\n![](images/634c770052e941e10642baaf761d52432fa22971cbc665c25f4f883d9d8e6a74.jpg) \nFig. 2. Investigation of the interactions between surface defects and the small molecules. FTIR spectra of (A) pure theophylline and theophylline- $\\left.\\mathsf{P b l}_{2}\\right.$ films, (B) pure caffeine and caffeine- $\\left.\\mathsf{P b l}_{2}\\right.$ films, and (C) pure theobromine and theobromine- $\\left.\\mathsf{P b l}_{2}\\right.$ films. (D) PL spectra of perovskite films without and with small-molecules treatment. (E) tDOS in perovskite solar cells with or without small-molecules treatment. (F) Nyquist plots of perovskite solar cells with or without small-molecules treatment measured in the dark and at corresponding open-circuit voltages. a.u., arbitrary units; C, junction capacitance; $R_{\\mathsf{r e c}}$ recombination resistance; $R_{s}$ , Series Resistance. \n\n![](images/0d7e698b85f6d3e9c18b0ca666b124f5f77165068f1f02ba952c5dfb6271598d.jpg) \nFig. 3. Characterization of perovskite films and interfaces with theophylline treatment. (A) XPS data for Pb 4f 7/2 and Pb 4f 5/2 core-level spectra in perovskite films with or without theophylline treatment. (B) UPS spectra of perovskite films with or without theophylline treatment. (C) AFM and KPFM images of perovskite films with (right) or without (left) theophylline treatment. (D) Time-resolved PL spectra of perovskite films before and after depositing Spiro-OMeTAD without and with theophylline treatment. (E) Cross-section SEM images and the corresponding EBIC images and line profile of the perovskite solar cells with (right) or without (left) theophylline treatment. \n\nWhen the $\\mathrm{{N-H}}$ group was located next to the $\\scriptstyle{\\mathrm{C}}=0$ group on the same six-membered ring, producing a shorter distance between the $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ and the $\\mathbf{N}{\\cdot}\\mathbf{H}$ , in theobromine, the spatially effective interaction between the N–H and I was disabled as $\\scriptstyle{\\mathrm{C}}=0$ was bound to antisite $\\mathrm{\\Pb}$ , resulting in an even weaker $E_{\\mathrm{int}}$ of $-1.1\\ \\mathrm{eV}$ (Fig. 1B). Although $\\scriptstyle{\\mathrm{C}}=0$ and $\\mathrm{\\DeltaN-H}$ are both present on the molecule, the lack of appropriate coordination of I to the molecule led to a spatially destructive molecular configuration. The theobromine-treated devices showed a decrease in PCE to $20.24\\%$ with a lower $V_{\\mathrm{OC}}$ of 1.163 V, $J_{\\mathrm{SC}}$ of $24.27\\mathrm{mAcm^{-2}}$ and FF of $71.58\\%$ compared with the reference device. This result emphasizes the importance of the constructive configuration of $\\mathrm{{N-H}}$ and $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ groups that enable the cooperative multisite interaction and synergistic passivation effect. \n\nWe studied the variation in the $\\scriptstyle\\mathrm{C=O}$ and the $\\mathrm{PbI_{2}}$ -terminated perovskite surface interaction with different molecular configurations using Fourier-transform infrared spectroscopy (FTIR). The $\\scriptstyle{\\mathrm{C}}=0$ in pure theophylline showed a typical stretching vibration mode at $1660~\\mathrm{{cm}^{-1}}$ that it shifted to $1630~\\mathrm{{cm}^{-1}}$ upon binding to $\\mathrm{PbI_{2}}$ (Fig. 2A). The downward shift of $30~\\mathrm{cm}^{-1}$ of the $\\scriptstyle{\\mathrm{C}}=0$ stretching vibration frequency resulted from the electron delocalization in $\\scriptstyle\\mathrm{C=O}$ when a Lewis base-acid adduct was formed, demonstrating a strong interaction between $\\mathrm{PbI_{2}}$ and $\\scriptstyle{\\mathrm{C=O}}$ in theophylline. The atomic distance between the O in $\\scriptstyle{\\mathrm{C}}=0$ and the $\\mathrm{\\Pb}$ in $\\mathrm{PbI_{2}}$ , on the basis of theoretical modeling, was as low as 2.28 Å. \n\nWhen the H atom was replaced by a methyl group on the N of imidazole to eliminate the effect of an H bond, the vibration frequency of $\\scriptstyle\\mathrm{C=O}$ in caffeine shifted only $\\mathrm{{10~cm^{-1}}}$ upon addition of $\\mathrm{PbI_{2}}.$ , indicating a weakened interaction between the $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ and $\\mathrm{PbI_{2}}$ (Fig. 2B). The atomic distance between the corresponding O and $\\mathrm{Pb}$ also increased to $2.32\\mathrm{\\AA}.$ In the case of theobromine, when the N–H was in a closer position to $\\scriptstyle\\mathrm{C=O}$ , the interaction between the molecule and $\\mathrm{PbI_{2}}$ became comparable to that in theophylline, as evidenced by the large shift of $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ stretching vibration frequency from 1655 to $1620\\mathrm{cm}^{-1}$ and the short distance between O and $\\mathrm{\\Pb}$ (Fig. 2C). However, this strong interaction was enabled by the free rotation of $\\mathrm{PbI_{2}}$ , which resulted in a different configuration than that in theophylline and caffeine. Hence, when the configuration of $\\mathrm{PbI_{2}}$ was fixed and had a $90^{\\circ}$ angle between Pb and I atom, like that on perovskite surface (the $\\mathrm{PbI}_{6}^{2-}$ octahedron), the N–H was in a position that led to an unfavorable interaction with I. This configuration would cause either weakened interaction between the molecule and the perovskite surface or distorted $\\mathrm{PbI}_{6}^{2-}$ octahedron, resulting in the ineffectiveness of defect passivation and perhaps causing even more defects through lattice distortion (fig. S3). \n\nThe surface passivation effects of the three molecules with different configuration were further studied by photoluminescence (PL). The PL intensity increased noticeably with the treatment by theophylline (Fig. 2D), implying the suppressed nonradiative chargerecombination sites from defects (15). With the caffeine treatment, enhanced PL intensity was also observed, but not as strong as that with the theophylline, suggesting a less effective passivation effect. For theobromine, however, a decrease in PL intensity was observed compared with the reference material, which can be attributed to the destructive molecular configuration of the passivation agents causing more charge recombination sites. \n\n![](images/d738ce68d0a31f753f15ff4843e62a942b7ddeb8d7fdcd71a047ec1a5b877bdb.jpg) \nFig. 4. Enhanced photovoltaic performance and long-term stability of perovskite solar cells with theophylline treatment. (A) $J\\cdot V$ curves of perovskite solar cells with or without theophylline treatment. (B) EQE curves of perovskite solar cells with or without theophylline treatment. (C) Stabilized maximum power output and the photocurrent density at maximum power point as a function of time for the best-performing \nperovskite solar cells with or without theophylline treatment, as shown in (A), recorded under simulated 1-sun AM1.5G illumination. (D) PCE distribution of perovskite solar cells with or without theophylline treatment. (E) Evolution of the PCEs measured from the encapsulated perovskite solar cells with or without theophylline treatment exposed to continuous light $(90\\pm10\\mathsf{m W}\\mathsf{c m}^{-2},$ ) under open-circuit condition. \n\nThe trap density of states (tDOS) of the asfabricated devices were also deduced from the angular frequency-dependent capacitance. As shown in Fig. 2E, the tDOS as a function of the defect energy demonstrated a reduction in trap states for theophylline- and caffeinetreated perovskite compared with the reference device. By contrast, theobromine treatment induced more trap states, consistent with the decrease in PCE. The change in tDOS with different surface treatments was also confirmed by theoretical modeling (fig. S4). In addition, electrochemical impedance spectroscopy (EIS) characterization was performed to demonstrate the carrier transport processes under illumination at the interface. The middle frequency zone of the EIS semicircle should be dominated by junction capacitance and recombination resistance related to the interfaces between transport materials and perovskite. According to Fig. 2F, the device with theophylline surface treatment has the smallest impedance, signifying a substantially suppressed charge recombination at the interface, which originated from the reduced surfacedefect states. A larger impedance was observed in caffeine-treated device, and an even larger impedance was measured in theobrominetreated device. \n\nFurther characterizations were performed to better understand the perovskite interface with theophylline. High-resolution XPS patterns of the Pb 4f for the theophylline-treated film showed two main peaks located at 138.48 and $143.38\\:\\mathrm{eV}$ , corresponding to the Pb 4f 7/2 and Pb 4f 5/2, respectively (Fig. 3A), whereas the reference film showed two main peaks at 138.27 and 143.13 eV. The peaks from Pb 4f shifted to higher binding energies in the film with theophylline surface treatment, indicating the interaction between the theophylline and the Pb on perovskite surface. We used ultraviolet photoelectron spectroscopy (UPS) to measure the surface band structure with and without the theophylline surface treatment. The work function was determined to be $-4.77$ and $-4.96\\mathrm{eV}$ with the valance band maximum of $-5.66$ and $-5.73\\mathrm{eV}$ for reference and theophylline, respectively (Fig. 3B). This difference indicated a less $n$ -type surface after theophylline treatment, which could improve the hole extraction in devices. \n\nAtomic force microscopy (AFM) combined with Kelvin probe force microscopy (KPFM) was further applied to probe the effect of theophylline on the surface morphology and surface potential. The theophylline-treated surface exhibited a higher electronic chemical potential than that of reference film, while keeping the surface morphology unchanged (Fig. 3C). The transient PL of the perovskite films with hole-transporting layer (HTL) was compared in Fig. 3D to delineate the carrier dynamics of the devices. The perovskite film with theophylline treatment showed a slightly longer carrier lifetime than the reference film, whereas a faster decay profile was observed when adding the HTL on top of the perovskite film. This result demonstrated a better hole extraction with theophylline treatment (20), most likely arising from lesser recombination sites at the interface and the slightly shallower work function of the perovskite film with theophylline. \n\nThe improved carrier dynamics originating from the effective surface passivation by theophylline was further characterized by cross-sectional electron-beam–induced current (EBIC) measurement. In EBIC measurement, the electron-beam–excited carriers were collected on the basis of the collection probability CP $(x,\\mathrm{L_{d}})$ , where $x$ is the distance between junction and incident beam position, and $L_{\\mathrm{d}}$ is the diffusion length of the carriers (fig. S5). The device with theophylline treatment exhibited higher EBIC current compared with the reference device (Fig. 3E). The average intensity extracted from these EBIC maps demonstrated a general increase in the EBIC signal after treatment with theophylline (fig. S6), indicating an enhanced carrier collection efficiency (25). Specifically, in Fig. 3E, a representative EBIC line profile of the reference device showed a current decay from the HTLperovskite to the $\\mathrm{{snO}_{2}}$ -perovskite interface. The decay indicates that carrier collection was limited by the hole-diffusion length as the beam position moved away from the HTL-perovskite interface. By contrast, the device with theophylline treatment displays minimal decay in the perovskite layer in the EBIC line profile. This difference suggests that a longer diffusion length of holes was present in theophyllinetreated sample and balanced electron and that hole charge transport and collection was achieved, which is likely the result of fewer surface recombination sites (Fig. 3E). \n\nFurther assessment of the performance of the PV devices based on the theophylline surface passivation was performed. The devices showed a negligible hysteresis $(4.1\\%)$ (Fig. 4A) because of the balanced charge collection originating from the effective surface passivation, whereas the reference device showed a large hysteresis (up to $7.6\\%$ ) (table S3). External quantum efficiency (EQE) spectra of the devices were compared in Fig. 4B. An integrated $J_{\\mathrm{SC}}$ of $24.42\\mathrm{mAcm^{-2}}$ from the target device matched well with the value measured from the $J_{\\cdot}V$ scan $\\textlangle<5\\%$ discrepancy), whereas the control device showed an integrated $J_{\\mathrm{SC}}$ of $23.56\\mathrm{mAcm^{-2}}$ . A stabilized PCE of $22.64\\%$ was achieved with the target device when biased at $1.00{\\mathrm{V}}$ , whereas that of the control device was $20.36\\%$ when biased at $0.98{\\mathrm{~V~}}$ (Fig. 4C). The histogram of PV efficiencies for 40 devices is shown in Fig. 4D (the detailed parameters are shown in table S2), which confirms good reproducibility of the performance improvement with theophylline $(11.1\\%$ improvement in an average PCE from $20.36\\pm$ $0.53\\%$ to $22.61\\pm0.58\\%$ with the incorporation of the theophylline). \n\nThe changes in PCE of the encapsulated devices at a relative humidity of 30 to $40\\%$ and temperature of $40^{\\circ}\\mathrm{C}$ were tracked over time to test the long-term operational stability (Fig. 4E). The reference device (initial PCE $19.34\\%$ ) degraded by more than $80\\%$ in 500 hours, whereas the target device maintained ${>}90\\%$ of its initial efficiency $(21.32\\%)$ ) during this time. Also, as shown in fig. S7, the shelf stability of the device based on theophylline treatment was noticeably enhanced, maintaining $>95\\%$ of its original PCE $(22.78\\%)$ when stored under ambient conditions with 20 to $30\\%$ humidity at $25^{\\circ}\\mathrm{C}$ for 60 days. By contrast, the reference device lost $>35\\%$ of its initial efficiency $(20.67\\%)$ . The strong interaction between the theophylline and the surface defects likely suppressed deleterious ion migration (26–28). \n\n# REFERENCES AND NOTES \n\n1. J. Tong et al., Science 364, 475–479 (2019). \n2. H. Tan et al., Science 355, 722–726 (2017). \n3. X. Zheng et al., Nat. Energy 2, 17102 (2017). \n4. J. J. Yoo et al., Energy Environ. Sci. 12, 2192–2199 (2019). \n5. Q. Jiang et al., Nat. Photonics 13, 460–466 (2019). \n6. N. Li et al., Nat. Energy 4, 408–415 (2019). \n7. J. S. Manser, J. A. Christians, P. V. Kamat, Chem. Rev. 116, 12956–13008 (2016). \n8. H. Zhang et al., ACS Appl. Mater. Interfaces 10, 42436–42443 (2018). \n9. J. W. Lee, H. S. Kim, N. G. Park, Acc. Chem. Res. 49, 311–319 (2016). \n10. Y. Zong et al., Chem 4, 1404–1415 (2018). \n11. D. Bi et al., Nat. Energy 1, 16142 (2016). \n12. B. Chen, P. N. Rudd, S. Yang, Y. Yuan, J. Huang, Chem. Soc. Rev. 48, 3842–3867 (2019). \n13. T. Wu et al., Adv. Energy Mater. 9, 1803766 (2019). \n14. T. Niu et al., Adv. Mater. 30, e1706576 (2018). \n15. R. Wang et al., Joule 3, 1464–1477 (2019). \n16. W. Xu et al., Nat. Photonics 13, 418–424 (2019). \n17. H. Zhang, M. K. Nazeeruddin, W. C. H. Choy, Adv. Mater. 31, e1805702 (2019). \n\n18. W. J. Yin, T. Shi, Y. Yan, Appl. Phys. Lett. 104, 063903 (2014). \n19. W. S. Yang et al., Science 356, 1376–1379 (2017). \n20. N. J. Jeon et al., Nat. Energy 3, 682–689 (2018). \n21. E. H. Jung et al., Nature 567, 511–515 (2019). \n22. M. A. Green, A. Ho-Baillie, H. J. Snaith, Nat. Photonics 8, \n506–514 (2014). \n23. Z. Xiao, Z. Song, Y. Yan, Adv. Mater. 31, e1803792 (2019). \n24. N. Liu, C. Yam, Phys. Chem. Chem. Phys. 20, 6800–6804 \n(2018). \n25. E. Edri et al., Nat. Commun. 5, 3461 (2014). \n26. R. Wang et al., Adv. Funct. Mater. 29, 1808843 (2019). \n27. J. A. Christians et al., Nat. Energy 3, 68–74 (2018). \n28. Y. Hou et al., Science 358, 1192–1197 (2017). \n\n# ACKNOWLEDGEMENTS \n\nFunding: Y.Y. acknowledges the Office of Naval Research (ONR) (N00014-17-1-2,484) for their financial support. Part of this material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technologies Office Award Number DE- EE0008751. Z.-K.W. acknowledges the Natural Science Foundation of China (no. 91733301). This project was also supported by the Collaborative Innovation Center of Suzhou Nano Science and Technology. Y.L. and D.F. are grateful for the financial support of a California Energy Commission Advance Breakthrough award (EPC-16-050). This work was performed in part at the San Diego Nanotechnology Infrastructure (SDNI) of UCSD supported by the National Science Foundation (grant ECCS-1542148). Part of the computations were performed in the SIMULAB of Marmara University, Physics Department and in the UHEM cluster of Turkey. K.N.H. and S.N. are grateful to the National Science Foundation (CHE‐1764328) for financial support of this research. Computer time was provided by the UCLA Institute for Digital Research and Education (IDRE). Author contributions: R.W., J.X., and Y.Y. conceived the idea for the study. R.W. and J.X. fabricated the solar cell devices and designed the experiments. K.-L.W. performed the film and device characterizations under the supervision of Z.-K.W. Y.L. and D.F. performed the EBIC measurement. G.X. carried out the tDOS measurement. S.N., I.Y., and K.N.H. performed the DFT calculation. T.H. carried out the TPC and TPV measurement. Y.Z., J.L.Y., J.Z., M.W., and S.T. assisted with the device fabrication and characterizations. R.W., J.X., and Y.Y. wrote the manuscript. All authors discussed the results and commented on the manuscript. Y.Y. supervised the project. Competing interests: None declared. Data and materials availability: All (other) data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/366/6472/1509/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S13 \nTables S1 to S3 \nReferences (29–41) \n1 August 2019; accepted 8 November 2019 \n10.1126/science.aay9698 \n\n# Science \n\n# Constructive molecular configurations for surface-defect passivation of perovskite photovoltaics \n\nRui Wang, Jingjing Xue, Kai-Li Wang, Zhao-Kui Wang, Yanqi Luo, David Fenning, Guangwei Xu, Selbi Nuryyeva, Tianyi Huang, Yepin Zhao, Jonathan Lee Yang, Jiahui Zhu, Minhuan Wang, Shaun Tan, Ilhan Yavuz, Kendall N. Houk and Yang Yang \n\nScience 366 (6472), 1509-1513. DOI: 10.1126/science.aay9698 \n\n# Optimizing surface passivation \n\nUnproductive charge recombination at surface defects can limit the efficiency of hybrid perovskite solar cells, but these defects can be passivated by the binding of small molecules. Wang et al. studied three such small molecules− theophylline, caffeine, and theobromine−−that bear both carbonyl and amino groups. For theophylline, hydrogen bonding of the amino hydrogen to surface iodide optimized the carbonyl interaction with a lead antisite defect and improved the efficiency of a perovskite cell from 21 to $22.6\\%$ . \n\nScience, this issue p. 1509 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1021_jacs.9b00574", + "DOI": "10.1021/jacs.9b00574", + "DOI Link": "http://dx.doi.org/10.1021/jacs.9b00574", + "Relative Dir Path": "mds/10.1021_jacs.9b00574", + "Article Title": "Element Replacement Approach by Reaction with Lewis Acidic Molten Salts to Synthesize nullolaminated MAX Phases and MXenes", + "Authors": "Li, M; Lu, J; Luo, K; Li, YB; Chang, KK; Chen, K; Zhou, J; Rosen, J; Hultman, L; Eklund, P; Persson, POÅ; Du, SY; Chai, ZF; Huang, ZR; Huang, Q", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "nullolaminated materials are important because of their exceptional properties and wide range of applications. Here, we demonstrate a general approach to synthesizing a series of Zn-based MAX phases and Cl-terminated MXenes originating from the replacement reaction between the MAX phase and the late transition-metal halides. The approach is a top-down route that enables the late transitional element atom (Zn in the present case) to occupy the A site in the pre-existing MAX phase structure. Using this replacement reaction between the Zn element from molten ZnCl2 and the Al element in MAX phase precursors (Ti3AlC2, Ti2AlC, Ti2AlN, and V2AlC), novel MAX phases Ti3ZnC2, Ti2ZnC, Ti2ZnN, and V2ZnC were synthesized. When employing excess ZnCl2, Cl-terminated MXenes (such as Ti3C2Cl2 and Ti2CCl2) were derived by a subsequent exfoliation of Ti3ZnC2 and Ti2ZnC due to the strong Lewis acidity of molten ZnCl2. These results indicate that A-site element replacement in traditional MAX phases by late transition-metal halides opens the door to explore MAX phases that are not thermodynamically stable at high temperature and would be difficult to synthesize through the commonly employed powder metallurgy approach. In addition, this is the first time that exclusively Cl-terminated MXenes were obtained, and the etching effect of Lewis acid in molten salts provides a green and viable route to preparing MXenes through an HF-free chemical approach.", + "Times Cited, WoS Core": 1024, + "Times Cited, All Databases": 1083, + "Publication Year": 2019, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000462260400032", + "Markdown": "# Element Replacement Approach by Reaction with Lewis Acidic Molten Salts to Synthesize Nanolaminated MAX Phases and MXenes \n\nMian Li,† Jun Lu,‡ Kan Luo, $\\dagger\\textcircled{\\circ}$ Youbing Li,† Keke Chang,† Ke Chen,† Jie Zhou,‡ Johanna Rosen,‡ Lars Hultman,‡ Per Eklund, $\\ddag\\textcircled{\\ d}$ Per O. Å. Persson, $\\ddag\\textcircled{\\pm}$ Shiyu Du, $\\dagger\\textcircled{\\circ}$ Zhifang Chai,† Zhengren Huang, and Qing Huang\\*,† \n\n†Engineering Laboratory of Advanced Energy Materials, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences, Ningbo, Zhejiang 315201, China ‡Department of Physics, Chemistry, and Biology (IFM), Linköping University, 58183 Linköping, Sweden \n\n\\*S Supporting Information \n\nABSTRACT: Nanolaminated materials are important because of their exceptional properties and wide range of applications. Here, we demonstrate a general approach to synthesizing a series of $Z\\mathbf{n}$ -based MAX phases and Clterminated MXenes originating from the replacement reaction between the MAX phase and the late transition-metal halides. The approach is a top-down route that enables the late transitional element atom $\\mathrm{{{Zn}}}$ in the present case) to occupy the A site in the pre-existing MAX phase structure. Using this replacement reaction between the $Z\\mathbf{n}$ element from molten $\\mathrm{ZnCl}_{2}$ and the Al element in MAX phase precursors $(\\mathrm{Ti}_{3}\\mathrm{AlC}_{2},$ ${\\mathrm{Ti}}_{2}{\\mathrm{AlC}},$ , $\\mathrm{Ti}_{2}\\mathrm{AlN}$ , and $\\mathrm{V}_{2}\\mathrm{AlC},$ ), novel MAX phases ${\\mathrm{Ti}}_{3}{\\mathrm{ZnC}}_{2},$ $\\mathrm{Ti}_{2}\\mathrm{ZnC},$ $\\mathrm{Ti}_{2}\\mathrm{ZnN}$ , and $\\mathrm{V}_{2}Z_{\\mathrm{nC}}$ were synthesized. When \n\n![](images/5bd0f41267525ae26efc84a103cbea2c3cd7d56151657dc99488c1c2a1062fc8.jpg) \n\nemploying excess $\\mathrm{ZnCl}_{2},$ Cl-terminated MXenes (such as ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ and ${\\mathrm{Ti}}_{2}{\\mathrm{CCl}}_{2}{\\mathrm{,}}$ ) were derived by a subsequent exfoliation of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ and $\\mathrm{Ti}_{2}\\mathrm{ZnC}$ due to the strong Lewis acidity of molten $\\mathrm{ZnCl}_{2}$ . These results indicate that A-site element replacement in traditional MAX phases by late transition-metal halides opens the door to explore MAX phases that are not thermodynamically stable at high temperature and would be difficult to synthesize through the commonly employed powder metallurgy approach. In addition, this is the first time that exclusively Cl-terminated MXenes were obtained, and the etching effect of Lewis acid in molten salts provides a green and viable route to preparing MXenes through an HF-free chemical approach. \n\n# INTRODUCTION \n\nThe family of nanolaminates called MAX phases and their twodimensional (2D) derivative MXenes are attracting significant attention owing to their unparalleled properties.1−7 The MAX phases have the formula $\\mathbf{M}_{n+1}\\mathbf{AX}_{n}$ $\\left(n=1-3\\right)$ , where $\\mathbf{M}$ is an early transition metal, A is an element traditionally from groups 13−16, and $\\mathrm{\\DeltaX}$ is carbon or nitrogen. The unit cell of MAX phases is composed of $\\mathbf{M}_{6}\\mathbf{X}$ octahedral (e.g., $\\mathrm{Ti}_{6}C\\dot{}\\quad$ ) interleaved with layers of A elements (e.g., Al). When etching the A-site atoms by HF or other acids, the retained $\\mathbf{M}_{n+1}\\mathbf{X}_{n}$ sheets form 2D sheets, called MXenes. Theses 2D derivatives show great promise for applications such as battery electrodes, supercapacitors, electromagnetic absorbing and shielding coatings, catalysts, and carbon capture.8−15 \n\nSo far, about 80 ternary MAX phases have been experimentally synthesized, with more continuously being studied, often guided by theory.16,17 However, MAX phases with the A-site elements of late transition metal (e.g., Fe, ${\\bf N i},$ $Z\\mathrm{n}_{,}$ , and Pt), which are expected to exhibit diverse functional properties (e.g., magnetism and catalysis), are difficult to synthesize. For these late transition metals, their M-A intermetallics are usually more stable than the corresponding MAX phases at high synthesis temperatures, which means that the target MAX phases can hardly be achieved by a thermodynamic equilibrium process such as hot pressing (HP) and spark plasma sintering (SPS). \n\nIn 2017, Fashandi et al. synthesized MAX phases with noblemetal elements in the A site, obtained through a replacement reaction.18,19 The replacement reaction was achieved by the replacement of Si by Au in the A layer of $\\mathrm{Ti}_{3}\\mathrm{SiC}_{2}$ at high annealing temperature with a thermodynamic driving force for the separation of Au and Si at moderate temperature, as determined from the $_\\mathrm{Au-Si}$ binary phase diagram. The formation of $\\mathrm{Ti}_{3}\\mathrm{AuC}_{2}$ is driven by an A-layer diffusion process. Its formation is preferred over competing phases (e.g., $\\mathrm{\\Au{-}T i}$ alloys), and the MAX phase can be obtained at a moderate temperature. Similarly, Yang et al. also synthesized $\\mathrm{Ti}_{3}\\mathrm{SnC}_{2}$ by a replacement reaction between the Al atom in $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{SnO}_{2}^{\\mathrm{~\\20~}}$ although $\\mathrm{Ti}_{3}\\mathrm{SnC}_{2}$ can also be synthesized by a hot isostatic pressing (HIP) route.21 Their work implies the feasibility of synthesizing novel MAX phases through replacement reactions. \n\nIt is worth noting that the synthesis of MAX phases by the A-site element exchange approach is similar to the preparation of MXenes by an A-site element etching process. Both are topdown routes that make modification of the A atom layer of preexisting structure of the MAX phase, which involve the extraction of A-site atoms and the intercalation of new species (e.g., metallic atoms or functional terminals) at a particular lattice position. On the basis of this idea, we introduce here a general approach to synthesizing a series of novel nanolaminated MAX phases and MXenes based on the element exchange approach in the A-layer of the traditional MAX phase. The late transition-metal halides (e.g., $\\mathrm{ZnCl}_{2}$ in this study) are so-called Lewis acids in their molten state.22−25 These molten salts can produce strong electron-accepting ligands, which can thermodynamically react with the A element in the MAX phases. Simultaneously, certain types of atoms or ions can diffuse into the two-dimensional atomic plane and bond with the unsaturated $\\mathbf{M}_{n+1}\\mathbf{X}_{n}$ sheet to form corresponding MAX phases or MXenes. The flexible selection of salt constituents can provide sufficient room to control the reaction temperature and the type of intercalated ions. In the present work, a variety of novel MAX phases $(\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2},$ $\\mathrm{Ti}_{2}\\mathrm{ZnC},$ $\\mathrm{Ti}_{2}\\mathrm{ZnN}.$ , and $\\mathrm{V}_{2}Z_{\\mathrm{nC}})$ and MXenes $\\left(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}\\right)$ and $\\mathrm{Ti}_{2}\\mathrm{CCl}_{2},$ ) were synthesized by elemental replacement in the A atomic plane of traditional MAX phases in $\\mathrm{ZnCl}_{2}$ molten salts. The results indicate a general and controllable approach to synthesizing novel nanolaminated MAX phases and the derivation of halide-group-terminated MXenes from its respective parent MAX phase. \n\n# EXPERIMENTAL AND COMPUTATIONAL DETAILS \n\nPreparation of MAX Phases and MXenes. All of the obtained new MAX phases $(\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2},$ $\\mathrm{Ti}_{2}\\mathrm{ZnC}.$ , $\\mathrm{Ti}_{2}\\mathrm{ZnN}.$ , and $\\mathrm{V}_{2}Z{\\mathrm{nC}},$ denoted in brief as $Z\\mathrm{n}$ -MAX) and MXenes $\\mathrm{\\Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ and ${\\mathrm{Ti}}_{2}{\\mathrm{CCl}}_{2},$ denoted in brief as Cl-MXenes) were prepared by a reaction between the traditional MAX phase precursors $(\\mathrm{Ti}_{3}\\mathrm{AlC}_{2},$ ${\\mathrm{Ti}}_{2}{\\mathrm{AlC}},$ $\\mathrm{Ti}_{2}\\mathrm{AlN}$ , and ${\\mathrm{V}}_{2}{\\mathrm{AlC}},$ denoted as Al-MAX) and $\\mathrm{ZnCl}_{2}$ . For synthesizing $Z\\mathrm{n}$ -MAX, a mixture powder composed of the $\\mathrm{\\Al{-}M A X/Z n C l_{2}}~=~\\mathrm{\\bar{1}}{:}1.5$ (molar ratio) was used as the starting material. For synthesizing the ClMXenes, a mixture powder composed of Al-MAX/ $\\mathrm{\\mathrm{~ZnCl}}_{2}=1{:}6$ (molar ratio) was used as the starting material. \n\nThe starting material was mixed thoroughly using a mortar under the protection of nitrogen in a glovebox. Then the as-obtained mixture powder was taken out of the glovebox and placed in an alumina crucible. The alumina crucible was loaded into a tube furnace and heat treated at $550~^{\\circ}\\mathrm{C}$ for $5\\mathrm{~h~}$ under the protection of Ar gas. After the reaction, the product was washed with deionized water to remove the residual $\\mathrm{ZnCl}_{2},$ and the final product was dried at $40~^{\\circ}\\mathrm{C}$ . Finally, the target reaction product was obtained. The weight change during various steps of the process was provided in the Supporting Information (Tables S1 and S2 and Figure S1). \n\nIn addition, the starting materials of $\\mathrm{Ti_{3}A l C_{2}/Z n C l_{2}}=1{:}1$ to 1:6 were heat treated at $550~^{\\circ}\\mathrm{{C}}$ for $s\\mathrm{h}$ to investigate the influence of the $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}/\\mathrm{ZnCl}_{2}$ ratio on the composition of the product. The starting materials of $\\mathrm{Ti_{3}A l C_{2}/Z n C l_{2}}=1{:}6$ were heat-treated at $550~^{\\circ}\\mathrm{C}$ for different times ( $0.5\\mathrm{{h}}$ to $\\mathfrak{s h}$ ) to investigate the phase evolution of the reaction product. \n\nPreparation of MAX Phase Precursors. The ${\\mathrm{Ti}}_{3}{\\mathrm{AlC}}_{2},$ ${\\mathrm{Ti}}_{2}{\\mathrm{AlC}},$ $\\mathrm{Ti}_{2}\\mathrm{AlN},$ and $\\mathrm{V}_{2}\\mathrm{AlC}$ MAX phase precursors were powders prepared by a molten-salt method as reported previously.14,26,27 Metal carbide/ nitride powders (TiC, TiN, and VC), M-site metal powders (Ti and \n\nV), and A-site metal powders (Al) were used as the source for synthesizing the target MAX phases. $\\mathrm{\\DeltaNaCl}$ and KCl with the molar ratio of 1:1 was used as the source for the molten salt bath. All of these metal carbides/nitrides were ${\\sim}10~\\mu\\mathrm{m}$ in particle size and were purchased from Pantian Nano Materials Co. Ltd. (Shanghai, China). Ti, V, and Al powders were 300 mesh in particle size and were purchased from Yunfu Nanotech Co. Ltd. (Shanghai, China). Analytical grade NaCl and KCl were purchased from Aladdin Industrial Co. Ltd. (Shanghai, China). \n\nThe starting materials, with the composition shown in Table 1, were mixed in a mortar and placed in an alumina crucible. Under the protection of argon, the alumina crucible was packed in a tube furnace and heat-treated to $1100~^{\\circ}\\mathrm{C}$ at a rate of $4~{}^{\\circ}\\mathrm{C/min}$ and held $3\\mathrm{~h~}$ to accomplish the reaction. After reaction, the tube furnace was cooled to room temperature at a rate of $4~{}^{\\circ}\\mathrm{C/min}$ . Then the product was washed with deionized water to remove the $\\mathrm{\\DeltaNaCl}$ and $\\operatorname{KCl},$ and the residual product was dried at $60~^{\\circ}\\mathrm{C}.$ . As a result, the target MAX phase precursors were obtained. \n\nTable 1. Composition of Starting Materials for Synthesizing the Al-MAX Phases \n\n\n
MAX phasecomposition of starting materials
TiAICTiC/Ti/Al/NaCl/KCl = 2:1:1.1:4:4
TiAlCTiC/Ti/Al/NaCl/KCl = 1:1:1.1:4:4
TiAINTiN/Ti/Al/NaCl/KCl = 1:1:1.1:4:4
VAlCVC/V/Al/NaCl/KCl= 1:1:1.1:4:4
\n\nCharacterization. Scanning electron microscopy (SEM) was performed in a thermal field emission scanning electron microscope (Thermo Scientific, Verios G4 UC) equipped with an energydispersive spectroscopy (EDS) system. Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) were performed in the Linköping monochromated, highbrightness, double-corrected FEI Titan3 $60{\\-}300$ operated at $300\\mathrm{\\kV},$ equipped with a SuperX EDS system. X-ray diffraction (XRD) analysis of the composite powders was performed using a Bruker D8 ADVANCE X-ray diffractometer with Cu $\\mathrm{K}\\alpha$ radiation at a scan rate of $2^{\\circ}/\\mathrm{min}$ . X-ray photoelectron spectra (XPS) were recorded in an XPS system (Axis Ultra DLD, Kratos, U.K) with a monochromatic Al X-ray source. The binding energy (BE) scale was assigned by adjusting the C 1s peak at $284.8\\ \\mathrm{eV}$ . \n\nComputational Methods. First-principles density-functional theory (DFT) calculations were carried out using the CASTEP module.28,29 A plane wave cutoff of $500~\\mathrm{eV}$ and the ultrasoft pseudopotentials in reciprocal space with the exchange and correlation effects represented by the generalized gradient approximation (GGA) of the Perdew−Breke−Ernzerhof (PBE) functional were employed in the structure calculations.30−33 The atomic positions were optimized to converge toward a total energy change smaller than $5\\times\\dot{1}0^{-6}~\\mathrm{eV/atom},$ with the maximum force over each atom below $0.001\\ \\mathrm{{\\eV}/\\mathring{A},}$ pressure smaller than $0.001~\\mathrm{\\GPa}_{.}$ and maximum atomic displacement not exceeding $5\\times10^{-4}\\mathrm{~\\AA~}$ . Phonon calculations were also performed by the finite displacement approach implemented in CASTEP to evaluate the dynamically stability.34,35 The cleavage energies $E$ of different M and $Z\\mathbf{n}$ atomic layers in ${\\mathrm{Ti}}_{3}{\\mathrm{ZnC}}_{2},$ $\\mathrm{Ti}_{2}\\mathrm{ZnC},$ $\\mathrm{\\bar{Ti}}_{2}\\mathrm{ZnN},$ , and $\\mathrm{V}_{2}Z_{\\mathrm{nC}}$ were calculated using the equation $E=\\big(E_{\\mathrm{broken}}~-E_{\\mathrm{bulk}}\\big)/2A,^{36}$ where $E_{\\mathrm{bulk}}$ and $E_{\\mathrm{broken}}$ are the total energies of bulk MAX and the cleaving structures with a $10\\mathrm{~\\AA~}$ vacuum separation in the corresponding M and $Z\\mathrm{n}$ atomic layers and A is the cross-sectional surface area of the MAX phase materials. \n\nThe CALPHAD approach was applied to calculate the phase diagrams of the $_{\\mathrm{Ti-Al-C}}$ and $\\mathrm{Ti{-}Z n{-}C}$ systems. The Ti−Al−C system has been well assessed by Witusiewicz et al.,37 and the thermodynamic data set was adopted in this work. Because of the lack of experimental data on the ternary $_{\\mathrm{Ti-Zn-C}}$ compounds, firstprinciples calculations were conducted to support the CALPHAD work.38 The formation enthalpies of the $\\mathrm{Ti}_{2}\\mathrm{ZnC}$ and $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ ternary compounds were computed to be −414.63 and $-230.16\\mathrm{\\kJ/mol},$ respectively. Their Gibbs free energy functions were then determined with the Neumann−Kopp rule and added to the CALPHAD-type data set of the $_{\\mathrm{Ti-Zn-C}}$ system, which included the thermodynamic parameters of the binary $\\mathrm{Ti-Zn}$ and $Z\\mathrm{n-C}$ systems.39 With the established thermodynamic data set, the isothermal sections of the Ti−Al−C and $\\mathrm{Ti{-}Z n{-}C}$ systems at 1300 and $550~^{\\circ}\\mathrm{C}$ were computed. All calculations were performed with the Thermo-Calc software. \n\n![](images/2e87e99f1a65480dc1cf43ddf822faffcc5d477987f4c9057e094d0d9ae40bdd.jpg) \nFigure 1. Characterization of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ . (a) XRD patterns of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ . (b) SEM image of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . (c) SEM image of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ . (d, e) High-resolution (HR)-STEM image of ${\\mathrm{Ti}}_{3}{\\mathrm{ZnC}}_{2},$ showing the atomic positions from different orientations. (f) HR-STEM and the corresponding EDS map of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ . \n\n![](images/86a287383685b17a1c9db2542e648227228f88808ee12293b876d95faa65c48f.jpg) \nFigure 2. Characterization of $\\mathrm{Ti}_{2}\\mathrm{ZnC},$ , $\\mathrm{Ti}_{2}\\mathrm{ZnN}_{\\cdot}$ , and $\\mathrm{V}_{2}Z_{\\mathrm{nC}}$ . $\\left(\\mathsf{a}-\\mathsf{c}\\right)$ XRD patterns showing the three MAX phases with their respective precursors, where the arrows indicate the difference. (d−f) HR-STEM images of $\\mathrm{Ti}_{2}\\mathrm{ZnC},$ $\\mathrm{Ti}_{2}\\mathrm{ZnN}$ , and $\\mathrm{V}_{2}Z\\mathrm{nC},$ showing the atomic positions in different orientations. \n\n# RESULTS AND DISCUSSION \n\nZn-MAX Phases. $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ was prepared by using the starting materials of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{ZnCl}_{2}$ with a mole ratio of 1:1.5. Figure 1a shows the XRD patterns of initial phase $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and final product $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ . Compared to ${\\mathrm{Ti}}_{3}{\\mathrm{AlC}}_{2},$ the XRD peaks of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ (e.g., (103), (104), (105), and (000l) peaks) are shifted toward lower angles, indicating a larger lattice constant caused by the replacement of Al atoms by $Z\\mathrm{n}$ atoms. Note that the relative intensity of (0004), (0006) peaks increased while that of (0002) peaks decreased. This is caused by the change in structure factor by the replacement of the A atoms. According to a Rietveld refinement of the XRD pattern (Figure S2), the determined $^a$ and $\\boldsymbol{\\mathscr{c}}$ lattice parameter of $\\mathrm{Ti}_{3}\\mathrm{\\bar{ZnC}}_{2}$ are 3.0937 and $18.7206\\mathring{\\mathrm{A}},$ which are larger than those of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ $a=3.080\\mathrm{~\\AA},$ $c=18.41\\hat{\\mathrm{S}}\\ \\mathring{\\mathrm{A}}$ ). \n\n![](images/cd20315410368092ceeb2789580436b3a4beb58a2a834bc887129dad3e8bf6eb.jpg) \nFigure 3. Characterization of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ . (a) XRD patterns from the as-reacted product and HCl-treated product. (b) SEM image showing ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ in the as-reacted sample. (c) HR-STEM image showing the atomic positions of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ . (d) Ti $\\mathsf{2p}$ XPS analysis of the as-reacted product. (e) Cl 2p XPS analysis of the as-reacted product. (f) Band structure of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ . \n\nFigure 1b,c shows SEM images of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ powders. The $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ precursor exhibits the typical layered structure of MAX phases. In contrast, the layered structure of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ becomes less distinct, which is possibly attributed to the dissolution of the edges of the powders in the molten salt. EDS analysis (Figure S3) indicates that the elemental composition of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ is $\\mathrm{Ti}/\\mathrm{Zn}/\\mathrm{C}=50.2{:}16.1{:}26.9$ (atomic ratio), and a small amount of Al (2.4 atom $\\%$ ) and O (3.4 atom $\\%$ ). This observation indicates that a nearly complete replacement of Al by $Z\\mathrm{n}$ was achieved. \n\nAtomically resolved STEM in combination with latticeresolved EDS was employed to demonstrate the elemental organization of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ . Figure 1d,e shows the atomic projections with the electron beam along [112̅0] and [11̅00], respectively. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ sublayers exhibit the characteristic zigzag pattern of MAX phases when observed along [112̅0]. Atomically thin layers of $Z\\mathrm{n},$ , which are brighter because of mass-contrast imaging, separate the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ sheets. Figure 1f shows an STEM image with the lattice-resolved elemental map. Note that the individual $Z\\mathrm{n}$ atoms in these images cannot readily be distinguished because they form a continuous line. This observation may be explained by in-plane vibrations of the $Z\\mathrm{n}$ atoms, presumably caused by weaker bonding to the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ layers than in the $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ case. \n\nFigure 2 shows the phase identification of products derived from $\\mathbf{M}_{2}\\mathbf{A}\\mathbf{X}$ precursors. ${\\mathrm{Ti}}_{2}{\\mathrm{AlC}}$ , $\\mathrm{T}_{2}\\mathrm{AlN}_{\\cdot}$ , and $\\mathrm{V}_{2}\\mathrm{AlC}$ were studied here.) The XRD patterns in Figure 2a exhibit a similar variation to that of the $\\mathbf{M}_{3}\\mathbf{AX}_{2}$ system, with (103), (106), and (110) peaks shifted toward lower angles and the relative intensity of the (000l) peaks changed. The STEM images (Figure $^{2\\mathrm{b,c}},$ ) and the EDS analysis (Figure S4) further confirmed the formation of the corresponding $\\mathbf{Z}\\mathbf{n}{\\cdot}\\mathbf{M}_{2}\\mathbf{A}\\mathbf{X}$ $\\left(\\mathrm{T}_{2}\\mathrm{ZnC},\\mathrm{Ti}_{2}\\mathrm{ZnN},\\right.$ , and $\\mathrm{V}_{2}\\mathrm{ZnC)}$ after the reactions. \n\nCl-MXenes. A mixture of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ MXene sheets and $Z\\mathrm{n}$ spheres was obtained by using the starting materials of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{ZnCl}_{2}$ with a mole ratio of 1:6. The SEM image (Figure 3a) and TEM images (Figure S5) of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ show exfoliation along the basal planes. The corresponding EDS analysis (Figure S6) indicates that the elemental composition of MXene is $\\mathrm{Ti}/\\mathrm{C}/\\mathrm{Cl}=43.2{:}21.5{:}25.3$ in atomic ratio, with small amounts of Zn (0.7 atom $\\%$ ), Al (2.9 atom $\\%$ ), and O(6.3 atom $\\%$ ). The presence of oxygen is reasonable because of prevailing O-containing compounds such as $\\mathrm{Al(OH)}_{3},$ which is the hydrolysis product of $\\mathrm{AlCl}_{3}$ . Note that our theoretical calculation results indicate that the Cl terminations can strongly bond to the MXene surfaces but are not competitive with O-containing terminals.40 Thus, a small part of the Cl terminations might be replaced by O-containing terminals during processes such as water washing, which could also contribute to the oxygen element detected on the surface. In addition, large $Z\\mathrm{n}$ spheres can also be observed in the product, which can be easily distinguished from the MXenes (Figure S7). \n\nFigure 3b shows the XRD patterns of the as-reacted and HCl-rinsed products. Besides diffraction peaks characteristic of Zn metal, the XRD patterns of the as-reacted product are similar to those of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene produced by the commonly used HF etching method. Most of the non-basalplane peaks of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (e.g., the intense (104) peak at ${\\sim}39^{\\circ}$ ) weakened significantly or disappeared. The (0002) peaks downshift to a lower angle of $2\\theta=7.94{\\mathrm{~}}^{\\circ}\\mathrm{C},$ attributed to an increased c lattice parameter of $22.24\\mathrm{~\\normalfont~\\AA~}.$ This $\\boldsymbol{\\mathscr{c}}$ lattice parameter agrees with the theoretical value calculated by DFT $\\bar{(}22.34\\mathrm{~\\AA})$ and is larger than that of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ produced by HF etching (19.49 Å for $\\mathrm{Ti}_{3}C_{2}(\\mathrm{OH})_{2}$ and 21.541 Å for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{F}_{2},$ ).3 Note that unlike the typical broad (000l) peaks of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ produced by HF etching, the (000l) peaks of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ are sharp and intense, indicating an ordered crystal structure. The etching mechanism of the MAX phase in molten salts may be of great interest because the chemical process is considerably safer and cleaner compared to the HF etching method. Regarding the etching chemistry, the reduction of the $Z\\mathrm{n}$ cation in the molten salts is similar to the generation of $\\mathrm{H}_{2}$ in the HF solution to etch $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ .3 \n\nThe as-reacted product was treated with a 5 wt $\\%\\mathrm{HCl}$ solution at $25~^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{~h~}}$ and washed with deionized water to remove $Z\\mathrm{n}$ according to reaction 1. \n\n$$\n\\mathrm{Zn}+2\\mathrm{HCl}=\\mathrm{ZnCl}_{2}+\\mathrm{H}_{2}\\uparrow\n$$ \n\nAfter HCl treatment, the XRD peaks corresponding to $Z\\mathrm{n}$ disappeared, while the peaks corresponding to ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ remained unchanged. SEM and EDS analyses also confirmed that the morphology and composition of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ were not influenced by the HCl treatment (Figure S8), indicating that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ is stable in the HCl solution. \n\nA STEM/EDS study was further employed to investigate the as-synthesized MXenes. As shown in Figure 3c, Cl atoms terminate the surface of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . Note that the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ MXenes show good ordering along the basal planes, which is in agreement with the intense (000l) peaks in the XRD patterns. For a more detailed investigation on the Cl terminations, please see ref 40. \n\nA Ti 2p X-ray photoelectron spectrum of the as-reacted sample was shown in Figure 3d. The peak at 454.4 and 455.7 $\\mathrm{^\\bulletv}$ are assigned to the Ti−C (I) $(2\\mathsf{p}_{3/2})$ and $_{\\mathrm{Ti-C}}$ (II) $(2\\mathsf{p}_{3/2})$ bond.41,42 The peak at 458.1 eV, attributing to a high valence Ti compound, is assigned to the Ti−Cl (2p3/2) bond.43,44 Besides, the peaks at $460.3\\ \\mathrm{eV}$ , 461.8 and $464.1\\ \\mathrm{eV}$ are assigned to the $\\mathrm{Ti-C}$ (I) $(2\\mathsf{p}_{1/2})$ , Ti−C (II) $(2\\mathsf{p}_{1/2})$ , and Ti−Cl $(2\\bar{\\mathrm{p}}_{1/2})$ bonds, respectively. Figure 3e is the Cl 2p spectrum. The peaks at 198.6 and $200.1~\\mathrm{eV}$ agrees well with the position of $\\mathrm{Cl-Ti}$ $(2\\mathsf{p}_{1/2})$ and Cl−Ti $(2\\mathsf{p}_{3/2})$ bonds43,44 which confirmed the presence of $\\mathrm{Ti\\mathrm{-}C l}$ bonds. The Ti:Cl ratio determined by the XPS analysis is 2.94:2, which agrees well with the EDS and STEM results. Detailed information on the XPS analysis was provided in upporting information (Figure S9, Figure S10 and Table S4). \n\nThe electronic band structures and phonon spectra of singlelayer ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ calculated by DFT is shown in Figure 2f. The layer is metallic in nature with a finite density of states at the Fermi level. The phonon spectra show that all phonon frequencies are positive (Figure S11) (i.e., $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ MXene is dynamically stable). \n\nSimilar to the production of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2},$ $\\mathrm{Ti}_{2}\\mathrm{CCl}_{2}$ was also obtained by using $\\mathrm{Ti}_{2}\\mathrm{AlC}$ and $\\mathrm{ZnCl}_{2}$ with a mole ratio of 1:6 as the staring materials. Characterization is provided in the Supporting Information, Figure S12). The phonon spectra of ${\\mathrm{Ti}}_{2}{\\mathrm{CCl}}_{2}$ show that all phonon frequencies are positive (Supporting Information, Figure S13a). The calculated band structure indicates that $\\mathrm{Ti}_{2}\\mathrm{CCl}_{2}$ has a metallic nature, similar to that of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ (Figure S13b). \n\nIn contrast, for starting materials $\\mathrm{Ti}_{2}\\mathrm{AlN}{:}\\mathrm{ZnCl}_{2}=1{:}6$ and $\\mathrm{V}_{2}\\mathrm{AlC{:}Z n C l_{2}}~=~1{:}6,$ their final reaction products remained $\\mathrm{Ti}_{2}\\mathrm{ZnN}$ and $\\mathrm{V}_{2}Z_{\\mathrm{nC}},$ but not the corresponding Cl-MXenes (Figure S14). \n\nFormation Mechanism. Taking $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ as an example, the formation of the $Z\\mathrm{n}$ -MAX phase can be stated as the following simplified reactions: \n\n$$\n\\begin{array}{r l}&{\\mathrm{Ti_{3}A l C_{2}}+1.5\\mathrm{ZnCl_{2}}=\\mathrm{Ti_{3}Z n C_{2}}+0.5\\mathrm{Zn}+\\mathrm{AlCl_{3}}}\\\\ &{}\\\\ &{\\mathrm{Ti_{3}A l C_{2}}+1.5\\mathrm{ZnCl_{2}}=\\mathrm{Ti_{3}C_{2}}+1.5\\mathrm{Zn}+\\mathrm{AlCl_{3}}\\uparrow}\\\\ &{}\\\\ &{\\mathrm{Ti_{3}C_{2}}+\\mathrm{Zn}=\\mathrm{Ti_{3}Z n C_{2}}}\\end{array}\n$$ \n\nReaction 2 is the general reaction that can be divided into subreactions 3 and 4. It is well known that $\\mathrm{ZnCl}_{2}$ has a melting pointing of ${\\sim}280~^{\\circ}\\mathrm{C}$ and is ionized to ${\\mathrm{Zn}}^{2+}$ and the $\\mathrm{ZnCl}_{4}^{2-}$ tetrahedron in its molten state.23,24 The coordinately unsaturated $Z\\mathrm{n}^{2+}$ is a strong acceptor of $\\mathrm{Cl^{-}}$ and electrons, which act as the Lewis acids in the $\\mathrm{ZnCl}_{2}$ molten salt. In this acidic environment, the weakly bonded Al atoms in $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ can be easily converted to $\\mathsf{A l}^{3\\dot{+}}$ by a redox reaction (reaction 3). The as-produced $\\mathsf{A l}^{3+}$ would further bond with $\\mathrm{Cl}^{-}$ to form ${\\mathrm{AlCl}}_{3},$ , which has a boiling point of ${\\sim}180^{\\circ}\\mathrm{C}$ and is expected to rapidly evaporate at the reaction temperature $(550~^{\\circ}\\mathrm{C})$ . Meanwhile, the in situ reduced $Z\\mathrm{n}$ atoms intercalate into the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ layers and fill the A sites of the MAX phase previously occupied by Al atoms, resulting in the formation of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ . The evaporation of $\\mathrm{AlCl}_{3}$ provides the driving force for the outward diffusion of the Al atom, while the A-site vacancies in the MAX phase enable the $Z\\mathrm{n}$ atoms to intercalate into the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ layers. In fact, the Al−Zn system forms a eutectic alloy at ${\\sim}385^{\\ \\circ}\\mathrm{C},$ well below the reaction temperature. The formation of a liquid $\\mathtt{A l-Z n}$ eutectic in the two-dimensional A sublayer of the MAX phase, together with liquid-state $\\mathrm{ZnCl}_{2},$ also accelerates the in-plane diffusion of Al and $Z\\mathrm{n}$ atoms. Actually, the calculated $_{\\mathrm{Ti-Zn-C}}$ phase diagram indicates that $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ is not stable at $1300^{\\circ}\\mathrm{C}$ because of the existence of competitive phases (Figure S15a). This is the main reason that the ZnMAX phases are unavailable through traditional solid reaction methods. Otherwise, the main composition at high temperature should be the $\\mathrm{Ti}{-}\\mathrm{Zn}$ alloy and TiC phase. However, the calculated phase diagram at $550~^{\\circ}\\mathrm{C}$ suggests that $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ is thermodynamically competitive with the $\\mathrm{Ti}-\\mathrm{Zn}$ alloys and should be at equilibrium at this temperature (Figure S15b). In contrast, the well-known stable Al-MAX phase exists in the Ti−Al−C phase diagrams at both 1300 and $550~^{\\circ}\\mathrm{C}$ (Figure S15c,d). The A-site replacement approach takes advantage of the diffusion of elements of interest at low temperatures and avoids the reaction to form competitive M-A alloys at high temperature that are usually required to generate the MX sublayer of the MAX phase. \n\nAlthough the formation mechanism of $Z\\mathrm{n}$ -MAX phases is reasonably explained above, the formation process of ClMXenes remains an open question. It is clear that the molar ratio of $\\mathrm{Al{-}M A X/Z n C l_{2}}$ plays a key role in determining the final product. With the increasing $\\mathrm{ZnCl}_{2}$ ratio in the starting materials, the final product gradually transformed from $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ . The XRD patterns of the reaction products for the starting materials with different $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}/$ $\\mathrm{ZnCl}_{2}$ ratios (Figure S16) clearly illustrate this phase evolution. On the basis of these conditions, we propose that the formation of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ follows a two-step reaction: (1) the formation of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ in an initial stage and (2) the further etching of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ in excess $\\mathrm{ZnCl}_{2}$ melt to form $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ . \n\nTo confirm this hypothesis, the starting materials of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{ZnCl}_{2}$ with a molar ratio of 1:6 were heat treated at 550 $^{\\circ}\\mathrm{C}$ for different annealing times to show the phase evolution of the reaction product. As shown in Figure $\\mathsf{4a}_{\\mathrm{,}}$ , the reaction product shows a variation tendency from $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ to $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ and then to ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ with increasing reaction time. The product after $0.5\\mathrm{~h~}$ of annealing remained ${\\mathrm{Ti}_{3}}{\\mathrm{AlC}_{2}},$ while after $1.0\\mathrm{~h~}$ it had converted to $\\mathrm{Ti}_{3}\\mathrm{\\bar{Z}n C}_{2}$ . Note that for the $1.0\\mathrm{~h~}$ sample the (000l) peaks of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ are less obvious than in Figure 1a, indicating that the crystal ordering along the (000l) plane was reduced. This is because that part of the $Z\\mathrm{n}$ atoms had already been extracted from the A layer. When the reaction time was further increased to $1.5\\mathrm{h},$ the non-basal-plane peaks of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ were diminished and the (000l) of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ emerged. Note that intense peaks of $Z\\mathrm{n}$ were also observed in this sample, indicating that the formation of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ is accompanied by the generation of free $Z\\mathbf{n}$ . The $3.0\\mathrm{h}$ sample is the same as the result in Figure 3, and a mixture of highly crystallized ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ and $Z\\mathrm{n}$ was obtained. The phase evolution was further confirmed by the EDS mapping analysis of the $1.5\\mathrm{~h~}$ sample. As shown in Figure 4b, this sample has a core−shell structure in which the core region is dense and rich in $Z\\mathrm{n}$ and the edge region is delaminated along the in-plane direction and rich in Cl. This core−shell microstructure shows an intermediate state of the conversion from $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ . \n\n![](images/ec7f275686ea51156b2cd2433804f75985fb268ca2b37d5184e66a084da78ccd.jpg) \nFigure 4. Phase evolution. (a) XRD patterns of the product of the $\\mathrm{Ti_{3}A l C_{2}/Z n C l_{2}}=1{:}6$ system with different reaction times, showing the phase evolution from $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ $\\mathrm{\\toTi_{3}Z n C_{2}}$ to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ . (b) EDS mapping analysis of the $1.5\\mathrm{h}$ sample showing the $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}@\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ core−shell structure. \n\nThe above results confirmed that ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ was the exfoliation product of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ and not directly derived from $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . This process can be reasonably described by the following simplified equations: \n\n$$\n\\begin{array}{r l}&{\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}+\\mathrm{ZnCl}_{2}=\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}+2\\mathrm{Zn}}\\\\ &{\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}+\\mathrm{Zn}^{2+}=\\mathrm{Ti}_{3}\\mathrm{C}_{2}+\\mathrm{Zn}_{2}^{2+}}\\end{array}\n$$ \n\n$$\n\\begin{array}{l}{{\\mathrm{Ti}_{3}\\mathrm{C}_{2}+2\\mathrm{Cl}^{-}=\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}+2\\mathrm{e}^{-}}}\\\\ {{\\mathrm{Zn}_{2}^{\\ 2+}+2\\mathrm{e}^{-}=2\\mathrm{Zn}}}\\end{array}\n$$ \n\nReaction 5 is the general reaction that can be divided into subreactions $_{6-8}$ . Reaction 6 can be explained by the dissolution of $Z\\mathrm{n}$ in molten $\\mathrm{ZnCl}_{2}$ . Previous research has demonstrated that $Z\\mathbf{n}$ dissolved well in molten $\\mathrm{ZnCl}_{2},$ which is attributed to a redox reaction between $Z\\mathrm{n}$ and $Z\\mathrm{n}^{2+}$ .45,46 As mentioned above, the $Z\\mathrm{n}^{2+}$ cation is a strong electron acceptor that can react with $Z\\mathrm{n}$ to form lower-valence zinc cations $\\left(\\mathrm{Zn}^{+}\\right.$ or $\\scriptstyle\\mathrm{Zn}_{2}^{2+},$ ). Therefore, the weakly bonded $Z\\mathbf{n}$ atoms in $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ were easily extracted from the two-dimensional A-site plane and dissolved in the $\\mathrm{ZnCl}_{2}$ molten salt. Meanwhile, according to reaction 7, the $\\mathrm{Cl^{-}}$ anions spontaneously intercalated into the A-site plane and bonded with the specific site in between $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ sublayers to form a more stable phase (i.e., ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2})$ . The strong electronegativity of Cl results in the increasing valence of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ unit, which means that extra electrons were released. These were captured by $\\mathrm{Zn^{+}}$ or $\\mathrm{Zn}_{2}^{2+}$ ions and formed pure metal $Z\\mathrm{n}$ (reaction 8). Note that the valence state of Ti is also confirmed by the above XPS analysis (Figure 3d). In other words, the formation mechanism of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{Cl}}_{2}$ is comparable to the formation chemistry of HF etching on $\\mathrm{Ti}_{3}\\mathrm{\\AAic}_{2}{,}^{3}$ in which $Z\\mathrm{n}^{2+}$ and $\\mathrm{Cl^{-}}$ play roles similar to those for $\\mathbf{H}^{+}$ and $\\mathrm{F}^{-}$ , respectively. \n\nTable 2 shows the cleavage energies of the ${\\bf{M}}{\\cdot}{\\bf{Z}}{\\bf{n}}$ atomic layer in four $Z\\mathrm{n}$ -MAX phases. The $\\mathrm{\\partial_{M-Zn}}$ cleavage energies of $\\mathrm{Ti}_{2}\\mathrm{ZnN}$ and $\\mathrm{V}_{2}Z_{\\mathrm{nC}}$ are theoretically predicted to be higher than those of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ and $\\mathrm{Ti}_{2}\\mathrm{ZnC},$ indicating a stronger ${\\bf{M}}{\\cdot}{\\bf{Z}}{\\bf{n}}$ bond. The stronger bond indicates that a more severe etching condition than in the present work is required to remove the $Z\\mathrm{n}$ atoms from $\\ensuremath{\\mathrm{Ti}_{2}}\\ensuremath{\\mathrm{ZnN}}$ and $\\mathrm{V}_{2}Z_{\\mathrm{nC}}$ . The experimental results described above illustrated that under the same reaction condition no corresponding $\\mathbf{MXCl}_{2}$ MXenes can be obtained. This fact is also in agreement with the HF etching chemistry that MAX phases with higher M-A bonding energy, such as $\\mathrm{V}_{2}\\mathrm{AlC}$ and $\\mathrm{Nb}_{2}\\mathrm{AlC},$ require longer times and higher HF concentrations to etch out the Al atoms than does ${\\mathrm{Ti}}_{2}{\\mathrm{AlC}}.$ 5 This phase formation, together with the following calculation results, explains the reason that $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ and $\\mathrm{Ti}_{2}\\mathrm{ZnC}$ could convert to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ and ${\\mathrm{Ti}}_{2}{\\mathrm{CCl}}_{2}$ whereas $\\mathrm{V}_{2}Z_{\\mathrm{nC}}$ and $\\mathrm{Ti}_{2}\\mathrm{ZnN}$ were not converted to the corresponding Cl-MXenes. \n\n# SUMMARY AND OUTLOOK \n\nA series of novel MAX phases $\\mathrm{\\Ti}_{3}\\mathrm{ZnC}_{2},$ , $\\mathrm{Ti}_{2}\\mathrm{ZnC}$ , $\\mathrm{Ti}_{2}\\mathrm{ZnN}_{,}$ and $\\mathrm{V}_{2}\\mathrm{ZnC)}$ and Cl-terminated MXenes $\\mathrm{\\Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ and ${\\mathrm{Ti}}_{2}{\\mathrm{CCl}}_{2}^{*}$ ) were synthesized by a replacement reaction, where the A element in traditional MAX phase precursors is replaced with Zn from the $Z\\mathrm{n}^{2+}$ cation in molten $\\mathrm{ZnCl}_{2}$ . \n\nThe formation of the $Z\\mathbf{n}$ -MAX phases was achieved by a replacement reaction between $\\mathsf{Z n}^{2+}$ and Al and subsequently the occupancy of $Z\\mathrm{n}$ atoms in the A sites of the MAX phase. The formation of $\\mathbf{Zn-MAX}$ phases indicates that such an exchange mechanism between traditional Al-MAX phases and the late transition metal halides might be a general approach $^{a}\\mathrm{NA}$ : not available in the present work. \n\nTable 2. Calculated Cleavage Energy $E_{\\mathrm{\\ell}}(\\mathrm{J}/\\mathbf{m}^{2})$ of Different M and ${\\bf{Z}}{\\bf{n}}$ Atomic Layersa \n\n\n
TiZnC (Ti-Zn)TiZnC (Ti-Zn)VZnC (V-Zn)TiZnN (Ti-Zn)
E1.5521.5761.7741.754
derivative MXeneTiCClTiCClNANA
\n\nfor synthesizing some other unexplored MAX phases with functional A-site elements (such as magnetic element Fe). Late transition metal halides $\\left(\\mathbf{e.g.},\\mathrm{ZnCl_{2}}\\right)$ ), which have relatively low melting points and exhibit strong Lewis acidity in their molten state, seem to be ideal candidates for the replacement reaction. The acidic environment provided by the molten salts facilitates the extraction of the Al atoms from the A-atom plane in the MAX phase at a moderate temperature. The generation of the volatile Al halides in turn provides the driving force for the outward diffusion of the Al atom. Meanwhile, the liquid environment also facilitates the inward diffusion of replacement atoms, which finally promotes a thorough replacement reaction. \n\nThe formation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{Cl}_{2}$ and ${\\mathrm{Ti}}_{2}{\\mathrm{CCl}}_{2}$ MXenes was achieved by a further exfoliation of $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ and $\\mathrm{Ti}_{2}\\mathrm{ZnC}$ in the $\\mathrm{ZnCl}_{2}$ molten salt. $\\mathrm{Ti}_{2}\\mathrm{NCl}_{2}$ and $\\mathrm{{V}}_{2}\\mathrm{{CCl}_{2}}$ were not obtained because their $Z\\mathrm{n}$ -MAX phases have higher M-A bonding strengths than $\\mathrm{Ti}_{3}\\mathrm{ZnC}_{2}$ and $\\mathrm{Ti}_{2}\\mathrm{ZnC}$ . Significantly, this is also the first time that exclusively Cl-terminated MXenes were obtained through non-fluorine chemistry. The Cl-terminated MXenes are expected to be more stable than the F-terminated MXenes, which implicates promising applications such as energy storage.7,8 Actually, a few recent reports have indicated enhanced electrochemical behavior in Cl-functionalized MXenes.47,48 The moderate molten salt environment also facilitates viable and green chemistry for the fabrication of MXenes that paves the way for their scale up and even commercial application. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/jacs.9b00574. \n\nWeight change during the synthesis process; Rietveld refinement of the XRD pattern; additional SEM images and EDS data; additional TEM figures; detailed XPS results; DFT calculation results; additional XRD results; and phase diagrams of the Ti−Al−C and $\\scriptstyle\\mathrm{Ti-Zn-C}$ systems (DOCX) \n\n# AUTHOR INFORMATION \n\nCorresponding Author huangqing@nimte.ac.cn \n\n# ORCID \n\nMian Li: 0000-0002-3139-7456 \nKan Luo: 0000-0002-8639-6135 \nJohanna Rosen: 0000-0002-5173-6726 \nPer Eklund: 0000-0003-1785-0864 \nPer O. Å. Persson: 0000-0001-9140-6724 \nShiyu Du: 0000-0001-6707-3915 \nQing Huang: 0000-0001-7083-9416 \nNotes \nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis study was supported financially by the National Natural Science Foundation of China (grant nos. 21671195 and 91426304) and the China Postdoctoral Science Foundation (grant no. 2018M642498). The Knut and Alice Wallenberg Foundation is acknowledged for its support of the electron microscopy laboratory in Linköping through fellowship grants and a project grant (KAW 2015.0043). P.O.Å.P, J.R., and J.L. acknowledge the Swedish Foundation for Strategic Research (SSF) for project funding (EM16-0004) and Research Infrastructure Fellow RIF 14-0074. We also acknowledge support from the Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linköping University (faculty grant SFO-Mat-LiU No. 2009 00971). \n\n# REFERENCES \n\n(1) Barsoum, M. W. The $\\mathbf{M}_{\\mathrm{N+1}}\\mathbf{A}\\mathbf{X}_{\\mathrm{N}}$ Phases: A New Class of Solids. Prog. Solid State Chem. 2000, 28, 201−281. \n(2) Eklund, P.; Beckers, M.; Jansson, U.; Högberg, H.; Hultman, L. The $\\mathbf{M}_{\\mathrm{n+l}}\\mathbf{A}\\mathbf{X}_{\\mathrm{n}}$ phases: Materials science and thin-film processing. Thin Solid Films 2010, 518 (8), 1851−1878. \n(3) Naguib, M.; Kurtoglu, M.; Presser, V.; Lu, J.; Niu, J.; Heon, M.; Hultman, L.; Gogotsi, Y.; Baroum, M. W. Two-dimensional nanocrystals produced by exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 2011, 23 (37), 4248−4253. \n(4) Naguib, M.; et al. Two-dimensional transition metal carbides. ACS Nano 2012, 6 (2), 1322−1331. \n(5) Naguib, M.; Mochalin, V. N.; Barsoum, M. W.; Gogotsi, Y. 25th anniversary article: MXenes: A new family of two-dimensional materials. Adv. Mater. 2014, 26 (7), 992−1005. \n(6) Eklund, P.; Rosen, J.; Persson, P. O. A. Layered ternary $\\mathbf{M}_{\\mathrm{n+l}}\\mathbf{A}\\mathbf{X}_{\\mathrm{n}}$ phases and their 2D derivative MXene: an overview from a thin-film perspective. J. Phys. D: Appl. Phys. 2017, 50 (11), 113001. \n(7) Anasori, B.; Lukatskaya, M. R.; Gogotsi, Y. 2D metal carbides and nitrides (MXenes) for energy storage. Nat. Rev. Mater. 2017, 2 (2), 16098. \n(8) Ghidiu, M.; Lukatskaya, M. R.; Zhao, M. $\\mathrm{Q.;}$ Gogotsi, Y.; Barsoum, M. W. Conductive two-dimensional titanium carbide “clay” with high volumetric capacitance. Nature 2014, 516 (7529), 78−81. (9) Shahzad, F.; Alhabeb, M.; Hatter, C. B.; Anasori, B.; Hong, S. M.; Koo, C. M.; Gogotsi, Y. Electromagnetic interference shielding with 2D transition metal carbides (MXenes). Science 2016, 353 (6304), 1137−1140. \n(10) Han, M.; Yin, X.; Wu, H.; Hou, Z.; Song, C.; Li, X.; Zhang, L.; Cheng, L. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXenes with Modified Surface for High-Performance Electromagnetic Absorption and Shielding in the X-Band. ACS Appl. Mater. Interfaces 2016, 8 (32), 21011−21019. \n(11) Tang, $\\mathrm{Q.;}$ Zhou, $Z.;$ Shen, P. Are MXenes promising anode materials for Li ion batteries? Computational studies on electronic properties and Li storage capability of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{X}_{2}$ $\\mathrm{\\DeltaX=F_{\\cdot}}$ , OH) monolayer. J. Am. Chem. Soc. 2012, 134 (40), 16909−16916. (12) Ran, J.; Gao, G.; Li, F. T.; Ma, T. Y.; Du, A.; Qiao, S. Z. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene co-catalyst on metal sulfide photo-absorbers for enhanced visible-light photocatalytic hydrogen production. Nat. Commun. 2017, 8, 13907. \n(13) Persson, I.; Halim, J.; Lind, H.; Hansen, T. W.; Wagner, J. B.; Näslund, LÅ; Darakchieva, V.; Palisaitis, J.; Rosen, J.; Persson, POÅ. 2D Transition Metal Carbides (MXenes) for Carbon Capture. Adv. Mater. 2019, 31, 1805472. \n(14) Li, M.; Han, M.; Zhou, J.; Deng, $\\mathrm{Q.;}$ Zhou, X.; Xue, J.; Du, S.; Yin, X.; Huang, $\\mathsf{Q}.$ Novel Scale-Like Structures of Graphite/TiC/ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ Hybrids for Electromagnetic Absorption. Adv. Electron Mater. 2018, 4 (5), 1700617. \n(15) Wang, B.; Zhou, A.; Liu, F.; Cao, J.; Wang, L.; Hu, $\\mathsf{Q}.$ Carbon dioxide adsorption of two-dimensional carbide MXenes. J. Adv. Ceram. 2018, 7 (3), 237−245. \n(16) Roknuzzaman, M.; Hadi, M. A.; Abden, M. J.; Nasir, M. T.; Islam, A. K. M. A.; Ali, M. S.; Ostrikov, K.; Naqib, S. H. Physical properties of predicted $\\mathrm{Ti}_{2}\\mathrm{CdN}$ versus existing $\\mathrm{Ti}_{2}\\mathrm{CdC}$ MAX phase: An ab initio study. Comput. Mater. Sci. 2016, 113, 148−153. \n(17) Lin, Z.; Zhuo, M.; Zhou, Y.; Li, M.; Wang, J. Microstructures and theoretical bulk modulus of layered ternary tantalum aluminum carbides. J. Am. Ceram. Soc. 2006, 89 (12), 3765−3769. \n(18) Fashandi, H.; Dahlqvist, M.; Lu, J.; Palisaitis, J.; Simak, S. I.; Abrikosov, I. A.; Rosen, J.; Hultman, L.; Andersson, M.; Spetz, A. L.; Eklund, P. Synthesis of ${\\mathrm{Ti}_{3}}{\\mathrm{AuC}_{2}},$ $\\mathrm{Ti}_{3}\\mathrm{Au}_{2}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{Ir}{\\bf C}_{2}$ by noble metal substitution reaction in $\\mathrm{Ti}_{3}\\mathrm{SiC}_{2}$ for high-temperature-stable Ohmic contacts to SiC. Nat. Mater. 2017, 16 (8), 814−818. \n(19) Fashandi, H.; Lai, C. C.; Dahlqvist, M.; Lu, J.; Rosen, J.; Hultman, L.; Greczynski, G.; Andersson, M.; Spetz, A. L.; Eklund, P. $\\mathrm{Ti}_{2}\\mathrm{Au}_{2}\\mathrm{C}$ and $\\mathrm{Ti}_{3}\\mathrm{Au}_{2}\\mathrm{C}_{2}$ formed by solid state reaction of gold with $\\mathrm{Ti}_{2}\\mathrm{AlC}$ and $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Chem. Commun. 2017, 53 (69), 9554−9557. (20) Wang, S.; Cheng, J.; Zhu, S.; Ma, J.; Qiao, Z.; Yang, J.; Liu, W. A novel route to prepare a $\\mathrm{Ti}_{3}\\mathrm{SnC}_{2}/\\mathrm{Al}_{2}\\mathrm{O}_{3}$ composite. Scr. Mater. 2017, 131, 80−83. \n(21) Dubois, S.; Cabioc’H, T.; Chartier, P.; Gauthier, V.; Jaouen, M. A new ternary nanolaminate carbide: $\\mathrm{Ti}_{3}\\mathrm{SnC}_{2}$ . J. Am. Ceram. Soc. 2007, 90 (8), 2642−2644. \n(22) Zhang, H.; Dasbiswas, ${\\mathrm{K}}.{\\mathrm{}}$ Ludwig, N. B.; Han, G.; Lee, B.; Vaikuntanathan, S.; Talapin, D. V. Stable colloids in molten inorganic salts. Nature 2017, 542 (7641), 328−331. \n(23) Biggin, S.; Enderby, J. E. The structure of molten zinc chloride. J. Phys. C: Solid State Phys. 1981, 14 (22), 3129−3136. \n(24) Li, H.; Lu, K.; Wu, Z.; Dong, J. EXAFS studies of molten $\\mathrm{{ZnCl}}_{2},$ RbCl and $\\mathrm{Rb}_{2}\\mathrm{ZnCl}_{4}$ . J. Phys.: Condens. Matter 1994, 6 (20), 3629−3640. \n(25) Sun, J.; Wang, L.; Zhang, S.; Li, Z.; Zhang, X.; Dai, W.; Mori, R. $\\mathrm{ZnCl}_{2}$ /phosphonium halide: An efficient Lewis acid/base catalyst for the synthesis of cyclic carbonate. J. Mol. Catal. A: Chem. 2006, 256 (1−2), 295−300. \n(26) Li, M.; Wang, K.; Wang, J.; Long, D.; Liang, Y.; He, L.; Huang, F.; Du, S.; Huang, $\\mathsf{Q}.$ Preparation of $\\mathrm{TiC/Ti_{2}A l C}$ coating on carbon fiber and investigation of the oxidation resistance properties. J. Am. Ceram. Soc. 2018, 101, 5269−5280. \n(27) Wang, B.; Zhou, A.; Hu, $\\mathrm{Q.;}$ Wang, L. Synthesis and oxidation resistance of $\\mathrm{V}_{2}\\mathrm{AlC}$ powders by molten salt method. Int. J. Appl. Ceram. Technol. 2017, 14 (5), 873−879. \n(28) Clark, S. J.; Segall, M. D.; Pickard, C. J.; Hasnip, P. J.; Probert, M. I. J.; Refson, K.; Payne, M. C. First principles methods using CASTEP. Z. Kristallogr. - Cryst. Mater. 2005, 220, 567−570. \n(29) Segall, M. D.; et al. First-principles simulation: ideas, illustrations and the CASTEP code. J. Phys.: Condens. Matter 2002, 14, 2717. \n(30) Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 1996, 77 (18), 3865− 3868. \n(31) Perdew, J. P.; Jackson, K. A.; Pederson, M. R.; Singh, D. J.; Fiolhais, C. Atoms, molecules, solids, and surfaces: Applications of the GGA for exchange and correlation. Phys. Rev. B: Condens. Matter Mater. Phys. 1992, 46 (11), 6671. \n(32) Kohn, W.; Sham, L. J. Self-Consistent Equations Including Exchange and Correlation Effects. Phys. Rev. 1965, 140, A1133. (33) Vanderbilt, D. Soft self-consistent pseudopotentials in a generalized eigenvalue formalism. Phys. Rev. B: Condens. Matter Mater. Phys. 1990, 41 (11), 7892−7895. \n(34) Frank, W.; Elsässer, C.; Fähnle, M. Ab initio force-constant method for phonon dispersions in alkali metals. Phys. Rev. Lett. 1995, 74 (10), 1791−1794. \n(35) Parlinski, K.; Li, Z. $\\mathrm{Q.;}$ Kawazoe, Y. First-principles determination of the soft mode in cubic $\\mathrm{ZrO}_{2}$ . Phys. Rev. Lett. 1997, 78 (21), 4063−4066. \n(36) Fang, C. M.; Ahuja, R.; Eriksson, O.; Li, S.; Jansson, U.; Wilhelmsson, O.; Hultman, L. General trend of the mechanical properties of the ternary carbides $\\mathbf{M}_{3}\\mathbf{SiC}_{2}$ ( $\\mathbf{\\dot{M}}=$ transition metal). Phys. Rev. B: Condens. Matter Mater. Phys. 2006, 74 (5), No. 054106. (37) Witusiewicz, V. T.; Hallstedt, B.; Bondar, A. A.; Hecht, U.; Sleptsov, S. V.; Velikanova, T. Y. Thermodynamic description of the Al-C-Ti system. J. Alloys Compd. 2015, 623, 480−496. \n(38) Chang, K.; Du, Y.; Sun, W.; Xu, H.; Zhou, L. C. Thermodynamic assessment of the V-Zn system supported by key experiments and first-principles calculations. CALPHAD: Comput. Coupling Phase Diagrams Thermochem. 2010, 34 (1), 75−80. \n(39) Hämäläinen, M.; Isomäki, I. Thermodynamic evaluation of the C-Co-Zn system. J. Alloys Compd. 2005, 392, 220−224. (40) Lu, J.; Persson, I.; Lind, H.; Li, M.; Luo, K.; Li, Y.; Chen, K.; Zhou, J.; Du, S.; Chai, Z.; Huang, Z.; Hultman, L.; Rosen, J.; Eklund, P.; Huang, $\\mathrm{Q.;}$ Persson, P. O. $\\mathrm{\\AA.Ti_{n+1}C_{n}}$ MXene with fully saturated and thermally stable Cl terminations. arXiv:1901.05212, 2019. (41) Halim, J.; Cook, K. M.; Naguib, M.; Eklund, P.; Gogotsi, Y.; Rosen, J.; Barsoum, M. W. X-ray photoelectron spectroscopy of select multi-layered transition metal carbides (MXenes). Appl. Surf. Sci. 2016, 362, 406−417. \n(42) Schier, V.; Halbritter, J.; Karlsruhe, K. ARXPS-analysis of sputtered TiC, SiC and $\\mathrm{Ti}_{0.5}\\mathrm{Si}_{0.5}\\mathrm{C}$ layers. Fresenius' J. Anal. Chem. 1993, 346, 227−232. \n(43) Magni, E.; Somorjai, G. A. Preparation of a model Ziegler-Natta catalyst: Electron irradiation induced titanium chloride deposition on magnesium chloride thin films grown on gold. Surf. Sci. 1996, 345 (1−2), 1−16. \n(44) Mousty-Desbuquoit, C.; Riga, J.; Verbist, J. J. Solid state effects in the electronic structure of $\\mathrm{TiCl}_{4}$ studied by XPS. J. Chem. Phys. 1983, 79 (1), 26−32. \n(45) Kerridge, B. D. H.; Tariq, S. A. The Solution of Zinc in Fused Zinc Chloride. J. Chem. Soc. A 1967, 1122, 1961−1964. \n(46) Buyers, A. G. A study of the rate of isotopic exchange for $\\mathrm{Zn}^{65}$ in molten Zinc-Zinc Chloride systems at $433-681^{\\circ}\\mathrm{C}.$ . J. Phys. Chem. 1961, 65 (12), 2253−2257. \n(47) Sun, W.; Shah, S. A.; Chen, Y.; Tan, Z.; Gao, H.; Habib, T.; Radovic, M.; Green, M. J. Electrochemical etching of $\\mathrm{Ti}_{2}\\mathrm{AlC}$ to $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\mathrm{x}}$ (MXene) in low-concentration hydrochloric acid solution. J. Mater. Chem. A 2017, 5 (41), 21663−21668. \n(48) Kajiyama, S.; Szabova, L.; Iinuma, H.; Sugahara, A.; Gotoh, K.; Sodeyama, K.; Tateyama, Y.; Okubo, M.; Yamada, A. Enhanced LiIon Accessibility in MXene Titanium Carbide by Steric Chloride Termination. Adv. Energy Mater. 2017, 7 (9), 1601873. \n\n# NOTE ADDED AFTER ASAP PUBLICATION \n\nThis article published March 7, 2019 with errors in Table 1. \nThe corrected table published March 8, 2019. " + }, + { + "id": "10.1126_science.aav8680", + "DOI": "10.1126/science.aav8680", + "DOI Link": "http://dx.doi.org/10.1126/science.aav8680", + "Relative Dir Path": "mds/10.1126_science.aav8680", + "Article Title": "Thermodynamically stabilized β-CsPbI3-based perovskite solar cells with efficiencies >18%", + "Authors": "Wang, Y; Dar, MI; Ono, LK; Zhang, TY; Kan, M; Li, YW; Zhang, LJ; Wang, XT; Yang, YG; Gao, XY; Qi, YB; Grätzel, M; Zhao, YX", + "Source Title": "SCIENCE", + "Abstract": "Although beta-CsPbI3 has a bandgap favorable for application in tandem solar cells, depositing and stabilizing beta-CsPbI3 experimentally has remained a challenge. We obtained highly crystalline beta-CsPbI3 films with an extended spectral response and enhanced phase stability. Synchrotron-based x-ray scattering revealed the presence of highly oriented beta-CsPbI3 grains, and sensitive elemental analyses-including inductively coupled plasma mass spectrometry and time-of-flight secondary ion mass spectrometry-confirmed their all-inorganic composition. We further mitigated the effects of cracks and pinholes in the perovskite layer by surface treating with choline iodide, which increased the charge-carrier lifetime and improved the energy-level alignment between the beta-CsPbI3 absorber layer and carrier-selective contacts. The perovskite solar cells made from the treated material have highly reproducible and stable efficiencies reaching 18.4% under 45 +/- 5 degrees C ambient conditions.", + "Times Cited, WoS Core": 1035, + "Times Cited, All Databases": 1070, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000483195200040", + "Markdown": "# SOLAR CELLS \n\n# Thermodynamically stabilized b-CsPbI –based perovskite solar cells with efficiencies ${\\bf>18\\%}$ \n\nYong Wang1, M. Ibrahim $\\mathbf{Dar^{2*}}$ , Luis K. Ono3, Taiyang Zhang1, Miao Kan1, Yawen $\\mathbf{Li^{*}}$ Lijun Zhang4, Xingtao Wang1, Yingguo Yang5, Xingyu Gao5, Yabing $\\mathbf{\\Qi^{3*}}$ , Michael Grätzel2\\*, Yixin Zhao1,6\\* \n\nAlthough $\\mathsf{\\beta-C s P b l}_{3}$ has a bandgap favorable for application in tandem solar cells, depositing and stabilizing $\\mathsf{\\beta-C s P b l}_{3}$ experimentally has remained a challenge. We obtained highly crystalline $\\mathsf{\\beta-C s P b l}_{3}$ films with an extended spectral response and enhanced phase stability. Synchrotron-based $\\boldsymbol{\\mathsf{x}}$ -ray scattering revealed the presence of highly oriented $\\beta\\mathrm{-}\\mathsf{C s P b l}_{3}$ grains, and sensitive elemental analyses—including inductively coupled plasma mass spectrometry and time-of-flight secondary ion mass spectrometry—confirmed their all-inorganic composition. We further mitigated the effects of cracks and pinholes in the perovskite layer by surface treating with choline iodide, which increased the charge-carrier lifetime and improved the energy-level alignment between the $\\mathsf{\\beta-C s P b l}_{3}$ absorber layer and carrier-selective contacts. The perovskite solar cells made from the treated material have highly reproducible and stable efficiencies reaching $18.4\\%$ under $45\\pm5^{\\circ}{\\mathsf{C}}$ ambient conditions. \n\nT fhice esntactie-sof(-tPhCeE-asr) peopowretre-cdofnovrerisnatoirognaneifc- perovskite solar cells (PSCs), typically $\\mathrm{\\sim}15\\%,$ , are substantially lower than those of the hybrid organic-inorganic metal halide PSCs (as high as $24.2\\%$ , primarily because all-inorganic perovskites have larger bandgaps and less favorable photophysical properties (1–3). Cesium lead iodide $\\mathrm{(CsPbI_{3})}$ has the most promising bandgap for applications as two-level tandem solar cells in combination with silicon $(4,5)$ , but the small size of ${\\mathrm{Cs}}^{+}$ gives rise to the unideal tolerance factor that makes it difficult to stabilize the $\\mathrm{CsPbI_{3}}$ perovskite phase under ambient conditions (6–9). Theoretical calculations predict that the tetragonal $\\mathrm{^{3}}$ -phase) polymorph of $\\mathrm{CsPbI_{3}}$ can be crystallized at lower temperatures and would have a more stable perovskite structure than the cubic $\\upalpha$ -phase (10–13), but experimentally it has been challenging to deposit and stabilize $\\upbeta$ -CsPbI3 for high-efficiency PSCs (14). \n\nWe have grown highly stable $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ perovskite films with extended ultraviolet-visible (UV-vis) absorbance and fabricated PSCs with $15.1\\%$ PCE. Furthermore, we developed a crackfilling interface engineering method using choline iodine (CHI), which not only passivated the surface trap states of perovskite but also led to better matching of the energy levels at the interfaces between the $\\mathrm{\\upbeta{\\cdot}C s P b I_{3}}$ perovskite and the $\\mathrm{TiO}_{2}$ electron-transport layer (ETL), as well as with the spiro-OMeTAD {2,2′,7,7′-tetrakis[N,Nbis $\\dot{\\boldsymbol{p}}$ -methoxyphenyl)amino]-9,9′-spirobifluorene} hole-transport layer (HTL). With this approach, the efficiency of $\\upbeta$ -CsPbI3–based PSCs improved to $18.4\\%$ with high stability and reproducibility. \n\nTo mitigate the challenge of obtaining the $\\mathrm{CsPbI_{3}}$ perovskite phase through a conventional solvent engineering method from $\\mathrm{PbI_{2}}$ and CsI precursors (fig. S1), we spin-coated a precursor solution containing a stoichiometric mixture of $\\mathbf{PbI_{2}}{\\cdot}x\\mathbf{DMAI}$ $\\mathbf{\\hat{\\mathcal{x}}}=1.1$ to 1.2; DMAI, dimethylammonium iodide) and CsI onto a compact $\\mathrm{TiO}_{2}$ layer (figs. S2 to S5). After annealing at $210^{\\circ}\\mathrm{C}$ for $5~\\mathrm{min}$ , the $\\mathrm{CsPbI_{3}}$ films showed an absorbance edge ${\\sim}736~\\mathrm{nm}$ (Fig. 1A) and a bandgap of $1.68\\ \\mathrm{eV}$ as determined from a Tauc plot (fig. S2), substantially redshifted relative to the ${\\sim}1.73\\ \\mathrm{eV}$ value previously reported for $\\mathrm{CsPbI_{3}}$ films $\\left(4\\right)$ . \n\nTo rule out the incorporation of any organic A-site cations that could have caused this redshift, we used thermogravimetric analysis and nuclear magnetic resonance (NMR) spectroscopy (figs. S3 and S4). Both techniques establish that an optimized annealing process at ${\\sim}210^{\\circ}\\mathrm{C}$ for $5~\\mathrm{min}$ was sufficient to remove all organic species. This conclusion was further supported by absorption and x-ray diffraction (XRD) data recorded for the samples annealed at ${\\sim}210^{\\circ}\\mathrm{C}$ for different periods of time (fig. S5). \n\nWe also evaluated the composition of the perovskite films by using inductively coupled plasma mass spectrometry (ICP-MS) and time-of-flight secondary ion mass spectrometry (TOF-SIMs) (table S1 and fig. S6). These methods confirmed that the perovskite films are exclusively inorganic. In contrast, ICP-MS and TOF-SIMs revealed a deficiency of ${\\mathrm{Cs}}^{+}$ and the presence of organic A-site cations (dimethylammonium) in perovskite films that were annealed at lower temperatures $\\mathrm{100^{\\circ}}$ to $\\mathrm{110^{\\circ}C}$ ) (15). \n\nThe desired redshift is associated with the specific phase of $\\mathrm{CsPbI_{3}}$ (13). To determine the crystal structure of the perovskite films, we used x-ray scattering (XRD) techniques, including synchrotron-based grazing incidence wide-angle x-ray scattering (GIWAXS). We indexed the XRD patterns to $\\mathrm{\\beta\\mathrm{-}C s P b I_{3}}$ (Fig. 1B and fig. S7), a phase of $\\mathrm{CsPbI_{3}}$ previously observed only above $230^{\\circ}\\mathrm{C}$ Although the XRD pattern measured at room temperature will not be identical to the standard XRD pattern obtained at higher temperature owing to the lattice thermal expansion, the basic features of the patterns should be very similar, and the in situ temperature-dependent GIWAXS pattern of our $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ shows only small variation between $30^{\\circ}$ and $250^{\\circ}\\mathrm{C}$ (figs. S8 and S9). Relatively intense (110) and (220) reflections further indicate a preferred (110) orientation of the $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ grains. Powder samples obtained from scratching the $\\mathrm{CsPbI_{3}}$ films revealed peak splitting at $28^{\\circ}$ to $29^{\\circ}$ for 2q (Fig. 1B), as expected for the tetragonal ${\\mathsf{\\beta-C s P b I}}_{3}$ phase. The pattern was markedly different from those of $\\mathbf{\\alpha}_{\\mathrm{~d~}}.$ - and $\\upgamma\\mathrm{-CsPbI_{3}}$ systems (fig. S10). Notably, most of the previously reported XRD patterns that have been incorrectly indexed to the $\\mathsf{\\Gamma}_{\\mathsf{{U}}\\mathrm{{-C}}\\mathsf{{s P b I}}_{3}}$ phase actually correspond to $\\upgamma{\\mathrm{-CsPbI}}_{3}$ , in accordance with the large bandgap of ${\\sim}1.73\\ \\mathrm{eV}$ of the latter system. \n\nThe GIWAXS data (Fig. 1C) not only established the formation of $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ but also revealed peak splitting of the tetragonal crystallites in the (220) class of reflections. Radially integrated intensity plots (fig. S11) along the ring at $\\mathbf{q}=10\\mathrm{~nm}^{-1}$ [scattering vector $\\mathbf{q}=4\\pi\\mathrm{sin}(\\theta)/\\lambda$ $(\\lambda,$ wavelength)] at azimuthal angles of $90^{\\circ}$ further indicate a strong preferred (110) orientation of the ${\\upbeta}–\\mathrm{CsPbI_{3}}$ grains. First-principles modeling that used theoretically optimized structures (fig. S12) rationalized the lower bandgap of tetragonal $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ relative to orthorhombic $\\upgamma\\mathrm{-CsPbI_{3}}$ in terms of the degree of distortion away from the ideal cubic structure. \n\nScanning electron microscopy (SEM) revealed that the 350- to $400\\mathrm{-nm}$ -thick $\\mathsf{\\beta{-}C s P b I_{3}}$ perovskite films are composed of submicrometer-sized grains (Fig. 1D), comparable to the film thickness, which enables efficient charge extraction (16). Previous studies on $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ reported that smaller grain size can improve perovskite phase stability and also suggested poor stability of the $\\mathrm{\\upbeta\\mathrm{-CsPbI_{3}}}$ phase at low temperature, so we further evaluated the thermal stability of highly crystalline ${\\upbeta}–\\mathrm{CsPbI_{3}}$ (7, 14). The ${\\upbeta}–\\mathrm{CsPbI_{3}}$ films, without any additional treatment, retained their color and phase even after annealing at $70^{\\circ}\\mathrm{C}$ for $>200$ hours in the nitrogen glovebox (fig. S13). Compared with $\\mathrm{\\mathbf{MAPbI_{3}}},$ the $\\mathrm{\\beta-CsPbI_{3}}$ films also exhibited better phase stability (fig. S14). However, they turned into the undesired yellow phase when exposed to $85\\pm5\\%$ relative humidity (RH) at $30^{\\circ}\\mathrm{C}$ after several minutes (fig. S15). \n\n![](images/c13c1d63a45a51e1843ae510506cc239e0e0c5e4f9d3c7e67ce3b3be3b4c353e.jpg) \nFig. 1. Spectroscopic, structural, and morphological characterization of $\\mathfrak{\\textbf{\\textsf{\\textbf{\\beta}}}}$ -CsPbI3 thin films. (A) UV-vis spectrum. (B) XRD patterns acquired from a $\\mathsf{C s P b l}_{3}$ thin film and powders scratched from the films. Brown lines indicate the standard $\\mathsf{\\beta-C s P b l}_{3}$ XRD pattern calculated for Cu Ka1 radiation for the tetragonal perovskite structure determined by Marronnier et al. at $518\\mathsf{K}$ (13). a.u., arbitrary units. (C) GIWAXS data from $\\mathsf{\\beta-C s P b l}_{3}$ films. (D) Top-surface SEM image of $\\mathsf{\\beta-C s P b l3}$ . The inset presents the cross-sectional morphology of the $\\mathsf{\\beta-C s P b l}_{3}$ perovskite thin film. Scale bars, $1\\upmu\\mathrm{m}$ . \n\nWe fabricated planar PSCs with the configuration of $\\mathrm{FTO/c–TiO_{2}/}$ perovskite/spiro-OMeTAD/ $\\operatorname{Ag};$ where FTO is fluorine-doped tin oxide and $\\mathrm{{c{-TiO_{2}}}}$ is compact $\\mathrm{TiO_{2}}$ . Under standard 1.5G illumination, the best ${\\upbeta}{\\mathrm{-CsPbI_{3}}}$ PSC showed a PCE of $15.1\\%$ with a short-circuit photocurrent density $(J_{\\mathrm{sc}})=20.03\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ , an open-circuit photovoltage $(V_{\\mathrm{oc}})\\:=\\:1.05\\:\\mathrm{V}$ , and a fill factor $(F F)=0.72$ (fig. S16). This state-of-the-art efficiency for an all-inorganic perovskite is still substantially lower than the PCEs reported for the PSCs fabricated from organic-inorganic hybrid perovskites with bandgaps near that of $\\upbeta$ -CsPbI3. The large hysteresis presents an additional caveat. The low efficiency of $\\mathsf{\\beta-C s P b I_{3}}$ PSCs is mainly related to the modest $V_{\\mathrm{{oc}}}$ and $F F$ (fig. S16). Previous studies have suggested that the reduced $V_{\\mathrm{oc}}$ and $F F$ could be associated with the poor band alignment and nonradiative carrier recombination at the surface defects (17–19). \n\nTo further enhance the PCE of $\\mathrm{\\upbeta\\mathrm{-}C s P b I_{3}}$ PSCs, we used the cracks present on the perovskite films to passivate the grains and simultaneously improve the alignment between perovskite and ETL layer. We selected CHI, which has been previously used to passivate hybrid perovskite films (20), and we then spin-coated CHI from isopropanol (IPA) solution $\\mathrm{{\\cdot}\\mathrm{{1}\\mathrm{{mg}\\mathrm{{ml}^{-1}\\mathrm{{\\cdot}}}}}}$ ) onto ${\\mathsf{\\beta-C s P b I_{3}}}$ thin films (hereafter, $1\\mathrm{mg}\\mathrm{ml}^{-1}$ CHI-treated $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ is referred to as CHI- $\\mathrm{CsPbI_{3}}$ ) (Fig. 2A). The SEM images (fig. S17) and carbon distribution profiles across the perovskite layer (Fig. 2, B and \n\nC, and fig. S18) indicate that the CHI penetrates into the bulk of the $\\mathrm{CsPbI_{3}}$ thin films, possibly through the pinholes and cracks. This CHI treatment improved the energy-level alignment of the conduction band minimum between $\\mathrm{\\upbeta\\mathrm{-}C s P b I_{3}}$ and $\\mathrm{TiO_{2}}$ by 120 meV (Fig. 2, D to F, and fig. S19). Furthermore, the CHI treatment led to improved energy-level alignment at both the $\\beta{\\mathrm{-CsPbI_{3}/E T L}}$ interface and the $\\beta{\\mathrm{-CsPbI_{3}/H T L}}$ interface. \n\nThe CHI treatment had a negligible effect on the absorption features, as the absorbance edge of CHI- ${\\mathrm{.csPbI}}_{3}$ films is still ${\\sim}736\\ \\mathrm{nm}\\ (\\mathrm{\\sim}1.68\\ \\mathrm{eV})$ (Fig. 3A). Likewise, the XRD patterns of pristine and CHI- $\\mathrm{\\cdotcsPbI_{3}}$ perovskite films (Figs. 1B and 3B) were almost identical. The comparison of Fig. 3C and fig. S16 shows that the CHI homogeneously distributes on the surface of film and the pinhole locations are filled with CHI. The NMR-based quantitative analysis revealed that the CHI is only ${\\boldsymbol{\\sim}}1$ weight $\\%$ of the CHI- $\\mathrm{\\cdotCsPbI_{3}}$ film (fig. S20). The XRD patterns, UV-vis absorption spectra, and surface morphology of the ${\\upbeta}–\\mathrm{CsPbI_{3}}$ perovskite thin films treated with the different concentrations of CHI solution are presented in fig. S21. \n\nThe high-resolution cross-sectional SEM images (fig. S22A) revealed continuous monolithictype grains extending vertically across the entire $\\mathrm{CsPbI_{3}}$ film thickness but also some pinholes in the bulk of the films. The subsequent CHI spincoating treatment only filled these pinholes and cracks and did not lead to substantial disruptions in the structure, morphology, and absorption properties of the $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ films (fig. S22B). To exclude the effect of the IPA solvent, the $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ films treated only with IPA were further characterized by SEM (fig. S23), which showed a morphology similar to that of the $\\mathrm{CsPbI_{3}}$ films. \n\nWe also used time-resolved photoluminescence (TRPL) spectroscopy to investigate the impact of CHI treatment on the excitonic quality of perovskite films. The charge carriers are relatively long-lasting in the case of CHI- $\\mathrm{\\cdot{CsPbI}_{3}}$ films (Fig. 3D), which is likely the result of a reduction in nonradiative recombination by trap passivation, which improved the overall charge-carrier dynamics. We calculated Urbach energies (fig. S24) (21, 22) of $15.9\\mathrm{meV}$ for $\\mathrm{CsPbI_{3}}$ and $\\mathrm{14.4\\meV}$ for $\\mathrm{CHI-CsPbI_{3}}$ . The Urbach energy for the CHI$\\mathrm{CsPbI_{3}}$ should correspond to a lower density of trap states, consistent with the TRPL result. \n\nX-ray photoelectron spectroscopy (XPS) measurements were conducted to further explore the effect of CHI treatment on the chemical composition of perovskite films. All core-level peaks were assigned to Cs, Pb, I, C, N, and O (Fig. 3E and fig. S25). The absence of a $\\mathrm{{Ti}2p}$ peak confirmed the uniformity of coverage of the perovskite film on top of the $\\mathrm{TiO}_{2}$ substrate. No binding energy shifts or additional peaks were observed for Cs 3d, Pb 4f, or I 3d, establishing that the CHI treatment improves the interfacial properties without changing the chemical nature of the all-inorganic $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ perovskite photoactive layer (fig. S25). A small O 1s peak was also observed for the pristine $\\mathrm{\\beta-CsPbI_{3}}$ sample (Fig. 3E), possibly a result of a small amount of oxygen adsorbed on the sample surface and/or diffused into the sample during preparation in dry- ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ conditions (23). Furthermore, energydispersive x-ray spectroscopy (EDX) elemental mapping (Fig. 3F and fig. S26) shows a uniform distribution of N and O on the surface of $\\mathrm{CHI-CsPbI_{3}}$ . More importantly, the $\\mathrm{CHI-CsPbI_{3}}$ region (VBM, valence band minimum) of the as-prepared CsPbI3, CHI-CsPbI3 perovskite films, $\\mathsf{T i O}_{2}$ (ETL), and the highest occupied molecular orbital of the spiro-OMeTAD (HTL) with respect to the Fermi energy (w.r.t. $\\mathsf{E}_{\\mathsf{F}.}$ ).VBM onsets for perovskites were determined from semi-log plots (fig. S19). (E and F) Corresponding energy diagram of (E) the $\\mathsf{C s P b l}_{3}$ film and (F) the CHI-CsPbI3 film together with the $\\mathsf{T i O}_{2}$ ETL and spiro-OMeTAD HTL that constitute the solar cell architecture. \n\n![](images/cdc447cb911c6cb9737cd2b2598a56f91f2b47545990d1b0726821ad58c8ebfa.jpg) \nFig. 2. Effect of crack-filling interface engineering treatment on the energy-level alignment. (A) Schematic illustration of crack-filling interface engineering. (B and C) Comparison of cross-sectional carbon element analysis for the (B) $\\mathsf{\\beta-C s P b l}_{3}$ and (C) CHI-CsPbI3 films measured by TOF-SIMS. (D) Ultraviolet photoelectron spectroscopy (UPS) spectra (using the He-I line with photon energy of $21.22\\ \\mathrm{eV},$ ) corresponding to the secondary electron onset region (WF, work function) and valence band \n\n![](images/17246a8d7a93c81997932e6bd6ea88de6a232dbb2b217fd7fa3cff249ffd01f8.jpg) \nFig. 3. Effects of CHI treatment on the spectroscopy and structure of Abs., absorbance. (D) TRPL decay curves of $\\mathsf{C s P b l}_{3}$ and CHI-CsPbI3 $\\mathbf{\\beta}_{\\mathbf{\\beta}}$ -CsPbI3 perovskite thin films. (A) UV-vis spectra, (B) XRD patterns, thin films. norm., normalized. (E) XPS $(A l-K=1486.6\\:\\mathrm{eV}$ ) N 1s and O and (C) top-surface SEM image of CHI-CsPbI3 perovskite thin films. 1s core-level spectra for the ${\\mathsf{C H I-C s P b l}}_{3}$ sample. (F) EDX top-view Diamond symbols represent the FTO substrate. The inset in (C) shows element mapping of N and O distribution on the surface of CHI-CsPbI3 the cross-section morphology of the CHI-CsPbI3 perovskite thin films. perovskite thin films. Scale bars, $1\\upmu\\mathrm{m}$ . \n\nphotovoltage decay (TPV) measurements. Similar TPC responses (fig. S34) suggest that the CHI treatment had minimal influence on the charge transport or charge collection efficiency, in agreement with $J_{\\mathrm{sc}}$ and EQE results. In contrast, the TPV revealed that CHI treatment increased charge-carrier lifetime (Fig. 4D), indicating a decrease in the undesired charge-carrier recombination (24, 25). \n\nWe fabricated large-area PSCs based on CHI$\\mathrm{{Cs}\\mathrm{{Pb}\\mathrm{{I}_{3}}}}$ thin films. The best CHI- $\\mathrm{{CsPbI}_{3}}$ devices, fabricated on $2.5\\ \\mathrm{cm}$ –by–2.5 cm substrates with an effective cell area of $\\mathrm{1cm^{2}}$ (Fig. 4E), display a PCE of $16.1\\%$ with $J_{\\mathrm{sc}}$ of $19.62\\mathrm{\\mA\\cm^{-2}}$ , $V_{\\mathrm{{oc}}}$ of 1.11 $\\mathrm{v,}$ and $F F$ of 0.74 under reverse scan conditions. The PV metrics (fig. S35 and table S2) show an average efficiency as high as $15.2\\%$ . These large-area devices also show small hysteresis (Fig. 4E) and high EQE and stabilized PCE (figs. S36 and S37). Furthermore, the CHI$\\mathrm{CsPbI_{3}}$ –based PSCs stored in a $\\mathrm{N}_{2}$ glovebox retain $92\\%$ of their initial PCE after 500 hours of continuous illumination at the maximum power point (MPP) (Fig. 4F). The CHI- $\\mathrm{\\cdotCsPbI_{3}}$ –based PSCs stored in a dark, dry box $\\mathrm{^{\\prime}R H}<10\\%$ ) with oxygen exhibit no PV performance decay (fig. S38A). The encapsulated device shows excellent ambient stability (fig. S38B) and retains $95\\%$ of its initial PCE in air after 240 hours of continuous illumination at the MPP (fig. S38, C and D). \n\n![](images/c8c92b988f8223830b40f3db87472fcf0fb725d7d64ce18c772af10d43ead4ed.jpg) \nFig. 4. Photovoltaic and device characterization. (A) $J-V$ characteristics of PSCs based on $\\mathsf{C s P b l}_{3}$ and $\\mathsf{C H l-C s P b l}_{3}$ with $0.1\\mathrm{-cm}^{2}$ effective cell area under simulated AM 1.5G solar illumination of $100\\mathrm{\\mw}\\mathrm{cm}^{-2}$ in reverse scan. (B) Corresponding PV metrics $\\scriptstyle(0.1-\\mathsf{c m}^{2}$ effective cell area; 32 devices). All $J-V$ curves were measured at ${\\sim}45\\pm5^{\\circ}\\mathrm{C}$ under full-sun illumination. (C) EQE spectrum together with the integrated $J_{\\mathsf{s c}}$ for the $\\mathsf{C s P b l}_{3^{-}}$ and CHI-CsPbI3–based PSCs. (D) TPV of $\\mathsf{C s P b l}_{3^{-}}$ and ${\\mathsf{C H l-C s P b l}}_{3}$ –based PSCs. (E) $J-V$ characteristics of PSCs based on CHI- $\\mathsf{C s P b l}_{3}$ with $1\\cdot\\mathsf{c m}^{2}$ effective cell area under simulated AM 1.5G solar illumination of $100\\mathrm{\\mw\\cm^{-2}}$ in forward and reverse scans. $J_{\\mathsf{s c}}$ , short-circuit photocurrent density; $V_{\\mathrm{oc}}$ , open-circuit voltage; $F F.$ , fill factor; h, PCE. (F) Photostability of the unencapsulated CHI-CsPbI3 PSC devices under continuous white light LED (light-emitting diode) illumination $(100\\mathrm{\\mw\\cm^{-2}},$ ) at their MPP in a ${\\sf N}_{2}$ glovebox. \n\nperovskite thin films exhibited greater resistance toward humidity and also showed good thermal stability (figs. S27 and S28). \n\nWe compared the $J_{-}V$ characteristics of the best-performing PSCs based on $\\mathrm{CHI-CsPbI_{3}}$ and ${\\mathsf{\\beta-C s P b I_{3}}}$ perovskite films (Fig. 4A). Although the $J_{\\mathrm{sc}}$ remained unaffected, the CHI- $\\mathrm{{CsPbI}_{3^{-}}}$ based PSC showed better $V_{\\mathrm{oc}}$ (1.11 versus $1.05\\mathrm{V},$ and $F F$ (0.82 versus 0.72), improving the overall PCE from 15.1 to $18.4\\%$ (Fig. 4, B and C). We also obtained a certified PCE of $18.3\\%$ for CHI$\\mathrm{CsPbI_{3}}$ –based PSC (fig. S29). Additionally, we compared the PV parameters of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}.$ - and CHI- $\\mathrm{CsPbI_{3}}$ –based PSCs (Fig. 4B). For the latter, the $V_{\\mathrm{oc}}$ and $F F$ are substantially enhanced. We attributed this improvement to better energylevel alignment and desired charge-carrier dynamics. All $J{-}V$ curves were measured at ${\\sim}45\\pm$ $5^{\\circ}\\mathrm{C}$ under full-sun illumination $(100\\mathrm{{mW}c m^{-2}},$ . \n\nFigure S30 shows that the efficiency drops marginally at ${\\sim}60^{\\circ}\\mathrm{C}.$ Furthermore, the CHI- $\\mathrm{{\\cdot{CsPbI}_{3^{-}}}}$ based PSCs exhibit a smaller hysteresis, resulting in a stabilized output power of $17.8\\%$ (figs. S31 and S32). The external quantum efficiency (EQE) of CHI- $\\mathrm{\\cdotCsPbI_{3}}$ –based PSCs (Fig. 4C) is ${>}90\\%$ for wavelengths between 500 and $600\\mathrm{nm}$ . The integrated $J_{\\mathrm{sc}}$ of $19.85\\mathrm{mAcm^{-2}}$ calculated from the EQE is comparable to the value estimated for the pure $\\mathrm{CsPbI_{3}}$ device $(19.71\\mathrm{{mA}\\mathrm{{cm}^{-2})}}$ ), in agreement with the $J_{-}V$ characteristics. Furthermore, the photovoltaic (PV) performance of $\\mathrm{CsPbI_{3}}$ treated with 0.5 or $2~\\mathrm{mg~ml^{-1}}$ CHI also exhibited ${\\sim}17\\%$ PCE, which was much higher than that of pure $\\mathsf{\\beta{\\mathrm{-}C s P b I_{3}}}$ –based devices (fig. S33). \n\nWe further investigated the charge-transport properties of CHI-treated PSCs by using transient photocurrent decay (TPC) and transient \n\n# REFERENCE AND NOTES \n\n1. A. Swarnkar et al., Science 354, 92–95 (2016). \n2. P. Wang et al., Nat. Commun. 9, 2225 (2018). \n3. B. Zhao et al., J. Am. Chem. Soc. 140, 11716–11725 (2018). \n4. G. E. Eperon et al., J. Mater. Chem. A 3, 19688–19695 (2015). \n5. E. M. Sanehira et al., Sci. Adv. 3, eaao4204 (2017). \n6. S. Dastidar et al., Nano Lett. 16, 3563–3570 (2016). \n7. T. Zhang et al., Sci. Adv. 3, e1700841 (2017). \n8. B. Li et al., Nat. Commun. 9, 1076 (2018). \n9. A. K. Jena, A. Kulkarni, Y. Sanehira, M. Ikegami, T. Miyasaka, Chem. Mater. 30, 6668–6674 (2018). \n10. R. J. Sutton et al., ACS Energy Lett. 3, 1787–1794 (2018). \n11. C. C. Stoumpos, M. G. Kanatzidis, Acc. Chem. Res. 48, 2791–2802 (2015). \n12. C. C. Stoumpos, C. D. Malliakas, M. G. Kanatzidis, Inorg. Chem. 52, 9019–9038 (2013). \n13. A. Marronnier et al., ACS Nano 12, 3477–3486 (2018). \n14. Y. Fu et al., Chem. Mater. 29, 8385–8394 (2017). \n15. W. Ke, I. Spanopoulos, C. C. Stoumpos, M. G. Kanatzidis, Nat. Commun. 9, 4785 (2018). \n16. N. J. Jeon et al., Nat. Energy 3, 682–689 (2018). \n17. N. Arora et al., ACS Energy Lett. 1, 107–112 (2016). \n18. H. Chen et al., Adv. Energy Mater. 7, 1700012 (2017). \n19. Y. Shao, Y. Yuan, J. Huang, Nat. Energy 1, 15001 (2016). \n20. X. Zheng et al., Nat. Energy 2, 17102 (2017). \n21. P. Löper et al., J. Phys. Chem. Lett. 6, 66–71 (2015). \n22. W. Zhang et al., Nat. Commun. 6, 10030 (2015). \n23. L. K. Ono et al., J. Phys. Chem. Lett. 5, 1374–1379 (2014). \n24. H. Tan et al., Science 355, 722–726 (2017). \n25. T. Leijtens et al., Energy Environ. Sci. 9, 3472–3481 (2016). \n\n# ACKNOWLEDGMENTS \n\nWe thank the Instrumental Analysis Center (School of Environmental Science and Engineering and Shanghai Jiao Tong University) for assistance with material characterization tests. We also thank the National Institute of Metrology (China) for authentication tests. Funding: The work performed at Shanghai Jiao Tong University was supported by the NSFC (grants \n\n21777096 and 51861145101), a Huoyingdong grant (151046), a Shanghai Shuguang grant (17SG11), and the China Postdoctoral Science Foundation (2017M621466). The work performed at the Okinawa Institute of Science and Technology Graduate University was supported by funding from the Energy Materials and Surface Sciences Unit of the Okinawa Institute of Science and Technology Graduate University, the OIST R&D Cluster Research Program, the OIST Proof of Concept (POC) Program, and a JSPS KAKENHI grant (JP18K05266). The work performed at Jilin University was supported by the National Natural Science Foundation of China (grants 61722403 and 11674121). M.I.D acknowledges financial support from the Swiss National Science Foundation under the project number P300P2_174471. Y.Y. and X.G. acknowledge the support of the National Key Research and Development Program of China (2017YFA0403400). Calculations were performed at the High Performance Computing Center of Jilin University. Authors contributions: Y.Z., Y.Q., and M.G. designed and directed the study. Y.W. and T.Z. conceived and performed the device fabrication work. Y.L. and L.Z. performed the first-principles calculations and analyzed the results. Y.W., M.I.D., L.K.O., T.Z., M.K., X.W., Y.Y., X.G., Y.L., L.Z., Y.Q., M.G., and Y.Z. participated in characterization and data analysis. All authors contributed to the discussions. Y.W., Y.Z., M.I.D., Y.Q., and M.G. wrote the manuscript with input from all authors. All authors reviewed the paper. Competing interests: None declared. Data and materials availability: The data that support the findings of this study are available from the corresponding author upon request. All other data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/365/6453/591/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S38 \nTables S1 and S2 \nReferences (26–35) \n29 October 2018; resubmitted 16 May 2019 \nAccepted 9 July 2019 \n10.1126/science.aav8680 \n\n# Science \n\n# Thermodynamically stabilized $\\upbeta$ -CsPbI3−based perovskite solar cells with efficiencies $>18\\%$ \n\nYong Wang, M. Ibrahim Dar, Luis K. Ono, Taiyang Zhang, Miao Kan, Yawen Li, Lijun Zhang, Xingtao Wang, Yingguo Yang, Xingyu Gao, Yabing Qi, Michael Grätzel and Yixin Zhao \n\nScience 365 (6453), 591-595. DOI: 10.1126/science.aav8680 \n\n# Orthorhombic phases for perovskite solar cells \n\nThe power conversion efficiencies (PCEs) of all-inorganic perovskites are lower than those of materials with organic cations. This is in part because these materials have larger bandgaps. The cubic crystal phases of these materials also exhibit poor stability. Wang et $a I.$ synthesized the orthorhombic $\\upbeta$ -phase of $\\mathsf{C s P b l}_{3}$ from $\\mathsf{\\Pi}_{\\mathsf{-}}\\mathsf{I P b}\\mathsf{I}_{3}$ and CsI. The material exhibited higher stability and a more favorable bandgap, which allowed for PCEs of $15\\%$ . Passivation of the surface trap state with choline iodide boosted PCEs to $18\\%$ . \n\nScience, this issue p. 591 \n\nARTICLE TOOLS \n\nhttp://science.sciencemag.org/content/365/6453/591 \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41467-018-08169-8", + "DOI": "10.1038/s41467-018-08169-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-08169-8", + "Relative Dir Path": "mds/10.1038_s41467-018-08169-8", + "Article Title": "Control of MXenes' electronic properties through termination and intercalation", + "Authors": "Hart, JL; Hantanasirisakul, K; Lang, AC; Anasori, B; Pinto, D; Pivak, Y; van Omme, JT; May, SJ; Gogotsi, Y; Taheri, ML", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "MXenes are an emerging family of highly-conductive 2D materials which have demonstrated state-of-the-art performance in electromagnetic interference shielding, chemical sensing, and energy storage. To further improve performance, there is a need to increase MXenes' electronic conductivity. Tailoring the MXene surface chemistry could achieve this goal, as density functional theory predicts that surface terminations strongly influence MXenes' Fermi level density of states and thereby MXenes' electronic conductivity. Here, we directly correlate MXene surface de-functionalization with increased electronic conductivity through in situ vacuum annealing, electrical biasing, and spectroscopic analysis within the transmission electron microscope. Furthermore, we show that intercalation can induce transitions between metallic and semiconductor-like transport (transitions from a positive to negative temperature-dependence of resistance) through inter-flake effects. These findings lay the groundwork for intercalation-and termination-engineered MXenes, which promise improved electronic conductivity and could lead to the realization of semiconducting, magnetic, and topologically insulating MXenes.", + "Times Cited, WoS Core": 950, + "Times Cited, All Databases": 997, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000457291300010", + "Markdown": "# Control of MXenes’ electronic properties through termination and intercalation \n\nJames L. Hart 1, Kanit Hantanasirisakul 1,2, Andrew C. Lang1, Babak Anasori1,2, David Pinto1,2, Yevheniy Pivak3, J. Tijn van Omme $\\textcircled{1}$ 3, Steven J. May1, Yury Gogotsi1,2 & Mitra L. Taheri1 \n\nMXenes are an emerging family of highly-conductive 2D materials which have demonstrated state-of-the-art performance in electromagnetic interference shielding, chemical sensing, and energy storage. To further improve performance, there is a need to increase MXenes’ electronic conductivity. Tailoring the MXene surface chemistry could achieve this goal, as density functional theory predicts that surface terminations strongly influence MXenes' Fermi level density of states and thereby MXenes’ electronic conductivity. Here, we directly correlate MXene surface de-functionalization with increased electronic conductivity through in situ vacuum annealing, electrical biasing, and spectroscopic analysis within the transmission electron microscope. Furthermore, we show that intercalation can induce transitions between metallic and semiconductor-like transport (transitions from a positive to negative temperature-dependence of resistance) through inter-flake effects. These findings lay the groundwork for intercalation- and termination-engineered MXenes, which promise improved electronic conductivity and could lead to the realization of semiconducting, magnetic, and topologically insulating MXenes. \n\nD i2scDotvrearnesditiinon201m1e,taMl Xcaernbeisdaers,e anirtaripdiedsl,y agnrodwcianrgbfoanmitirliydeosf with the general formula $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x}$ ${\\mathit{\\Omega}}^{\\prime}n=1,2$ , or 3; $\\mathbf{M}=$ transition metal, e.g., Ti, V, Nb, Mo; ${\\mathrm{X}}={\\mathrm{C}}$ and/or N; $\\mathrm{T}=$ surface termination, e.g., $-\\mathrm{OH}$ , $-\\mathrm{F},\\ \\mathrm{=}\\mathrm{O})^{1-5}$ . MXenes are formed by selective etching parent ternary carbide MAX compounds to remove the A-group element, e.g., $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (layered $\\mathbf{MAX})\\rightarrow$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (2D MXene)6,7. For both device applications and fundamental studies, MXene samples are generally thin films comprised of many MXene flakes, though some studies have focused on single-layer MXene8,9. In contrast to most other 2D materials, MXenes offer an attractive combination of high electronic conductivity, hydrophilicity, and chemical stability1–5,10–13. With these properties, MXenes show exceptional promise in areas including electromagnetic interference shielding14,15, wireless communication16, chemical sensing17–20, energy storage21–23, optoelectronics24–27, triboelectrics28–30, catalysis31–33, and conformal/wearable electronics34. Performance in these applications is directly related to electronic conductivity, and as such, there is motivation to further increase the MXene metallic conductivity. In parallel, there is excitement surrounding the potential realization of semiconducting MXenes, which are predicted to be excellent materials for spintronics and thermoelectrics35–37. \n\nTo meet these demands on MXenes’ electronic properties, researchers have mostly focused on the development of new $\\mathbf{M}_{n+1}\\mathbf{X}_{n}$ chemistries. So far, over 30 MXenes have been synthesized, but the first discovered MXene— $.\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ —remains the most conductive13. Recently, certain Mo- and V-based MXenes have garnered interest due to their so-called semiconductor-like behavior38–40, i.e., a negative temperature-dependence of resistance $(\\mathrm{d}R/\\mathrm{d}T)$ . However, the cause of negative $\\mathrm{d}R/\\mathrm{d}T$ in these MXenes remains unclear, and their underlying electronic structure is debated38,41. A potentially more useful approach to control MXenes’ conductivity is to manipulate their surface chemistry. Surface terminations, which are introduced during MXene synthesis6, have been predicted to control metal-to-insulator transitions37,38 and to affect functional properties such as magnetism1,42, Li-ion capacity43, catalytic performance31,44, band alignment45, mechanical properties46, and predictions of superconductivity47. While promising, these predicted effects lack direct experimental confirmation48,49. An additional mechanism which can affect MXene conductivity is intercalation. Intercalants are not thought to alter the intra-flake (intrinsic) MXene properties, but for multi-layer samples, intercalation can increase device resistance by over an order of magnitude27,40,41,50–52. This effect is generally attributed to intercalants increasing the interflake spacing and thereby the inter-flake resistance. \n\nFor any multi-layer MXene sample, intercalation, termination, and $\\mathbf{M}_{n+1}\\mathbf{X}_{n}$ chemistry all contribute to the measured electronic conductivity, and this convolution of effects greatly complicates experimental interpretation. As a result, our understanding and ability to control MXenes’ electronic properties are lacking. To address this challenge, we perform in situ vacuum annealing (up to $775^{\\circ}\\mathrm{C},$ ) and electrical biasing of MXenes within the transmission electron microscope (TEM). We observe de-intercalation and surface de-functionalization with in situ electron energy loss spectroscopy (EELS) and ex situ thermogravimetric analysis with mass spectroscopy (TGA-MS). Importantly, we utilize low-dose direct detection (DD) EELS53 to avoid electron beam-induced specimen damage54 (Supplementary Figure 1). With this approach, we correlate the desorption of –OH, $\\mathrm{-F,}$ and $\\scriptstyle=0$ termination species with increased MXene conductivity. Additionally, we report transitions from ensemble semiconductor-like (negative ${\\bar{\\mathrm{d}}}R/{\\mathrm{d}}T)$ to metallic behavior in $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ and $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}$ after the de-intercalation of water and organic molecules. This work furthers our fundamental understanding of conduction through MXene films and opens the door to intercalation- and termination-engineered MXenes. \n\n# Results \n\nSample synthesis and experimental approach. We investigated three MXenes with diverse macroscopic electronic transport behavior: $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x},$ and $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}$ (Table 1). $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (its structure is shown schematically in the Fig. 1a top inset) is the most studied MXene and is known to be metallic and highly conductive7. Density functional theory (DFT) studies have consistently predicted that surface functionalization reduces the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ density of states (DOS) at the Fermi level $(E_{\\mathrm{F}})$ , suggesting a decrease in the charge carrier density and thereby a decrease in the conductivity43,55,56. Understanding of the next two MXenes— ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ and $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ —is limited. The structure of $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ is similar to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ but with a mixture of C and $\\mathrm{\\DeltaN}$ on the X-sites (Fig. 1b top inset). DFT predicts ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ to be metallic for all terminations55,57,58, but to date, this MXene has only shown semiconductor-like transport (unpublished results). $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}$ is an ordered, double transition metal MXene analogous to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ but with the outer Ti layers replaced by Mo layers59 (Fig. 1c top inset). Terminations have been predicted to induce metallic, semiconducting38, and topologically insulating60 states in this MXene. Experimentally, $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ shows semiconductor-like behavior in its as-prepared state38, but it is unclear if this behavior is due to intrinsic $(\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x}$ stoichiometry) or extrinsic (intercalation, inter-flake hopping) effects. \n\nWe produced the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ samples through etching of their 3D parent MAX phases, i.e., $\\mathrm{\\bar{Ti}}_{3}\\mathrm{AlC}_{2}$ and ${\\mathrm{Ti}}_{3}{\\mathrm{AlCN}},$ in a mixture of LiF and HCl. This process results in –OH, $\\mathrm{-F,}$ and $\\scriptstyle=0$ terminations and $\\bar{\\mathrm{H}}_{2}\\mathrm{O}$ and ${\\mathrm{Li^{+}}}$ intercalation6,23. $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ was instead produced through etching of $\\mathbf{Mo}_{2}\\mathrm{TiAlC}_{2}$ in HF and delaminating via tetrabutylammonium hydroxide (TBAOH) intercalation59. This method reduces the concentration of $\\mathrm{-F}$ termination and results in tetrabutylammonium $\\mathrm{(TBA^{+})}$ and $\\mathrm{H}_{2}\\mathrm{O}$ intercalation40,61. $\\mathrm{TBA^{+}}$ is a large organic ion which can significantly increase the interflake spacing and electrical resistanc $\\mathrm{e}^{6,40,52}$ . To directly compare $\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{T}\\mathrm{\\bar{B}A}^{+}$ intercalation, we additionally studied $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ prepared with HF etching and TBAOH delamination. For clarity, this sample is referred to as $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA^{+}})$ . \n\n
Table 1 Summary of in situ heating and biasing results
MXene chemistryTerminationIntercalationdR/dTResistance (Ω2)
TiC2Tx(OH)0.4F0.400.5→F0.200.5HO, Li+ → Li+M→M41→10
TiCNTx(OH)0.9F0.5O0.7 → F0.200.7HO, Li+ → Li+S→M159 → 27
TiCNT(TBA+)(OH)0.6F0.101.2 → 01.2H2O, TBA+ → nones→S3330→290
M02TiC2Tx(OH)0.5F0.0101.5 → 00.8HO, TBA+ → noneS→M2500→387
Il respieli
determined fromexsituTGA-MS,andthereductionin-Fand =Oterminatingspecies wasmeasuredwith in situ EELS
\n\n![](images/77c97311d62b31c8386b56ce84e7426fd4c175c46381413986bd41d1a1a1c0dd.jpg) \nFig. 1 Evolution of MXene electronic properties with in situ vacuum annealing. Resistance versus temperature measurements are shown for $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ (a), ${\\mathsf{T i}}_{3}{\\mathsf{C N T}}_{x}$ (b), and $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ (c). The measurements were conducted during various vacuum annealing steps performed in the TEM. Each vacuum annealing step is represented with a different color and symbol. For each annealing step, both the heating and cooling curves are shown. In all cases, the resistance decreased during annealing, hence, the cooling curve is always beneath the heating curve. The atomic structures of the various MXenes are shown as insets. The initial state schematics (top schematics) show $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ and ${\\mathsf{T i}}_{3}{\\mathsf{C N T}}_{x}$ with intercalated water molecules on their surfaces, and $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ is shown with water and $\\mathsf{T B A^{+}}$ molecules. With annealing, the MXene sample resistance is affected by the loss of adsorbed species, intercalants, and terminating species. Some of these processes are shown schematically. The resistance data in this figure are also shown in Supplementary Figures 13-15, where the resistance is plotted as a function of annealing time \n\nAfter synthesis, MXene films were spray-casted24 onto MEMS (microelectromechanical systems)-based nanochips62 designed for heating and biasing within the TEM column (Supplementary Figure 2). The MXene films were at least several flakes thick (Supplementary Figures 1 and 2), and the electrode spacing $(\\sim20$ $\\upmu\\mathrm{m})$ was considerably larger than the MXene flake diameters 1 ${\\sim}100\\mathrm{nm}$ up to $2{-}3\\ \\upmu\\mathrm{m})$ ). As such, sample resistance measurements were dependent upon both intra- and inter-flake contributions. The cross-sectional sample areas were not welldefined, so we report the relative change in sample resistance and not the absolute resistivity. TEM imaging and electron diffraction confirmed the MXene structure both before and after in situ annealing at ${\\geq}700^{\\circ}\\mathrm{C}$ (Supplementary Figure 2). \n\nThe temperature-dependent resistance of each sample was initially measured in ambient atmosphere from room temperature (RT) up to $75^{\\circ}\\mathrm{C}$ in order to understand the as-prepared sample properties. In agreement with previous results, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ displayed metallic behavior while $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ and $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ displayed semiconductor-like (negative $\\mathrm{d}R/\\mathrm{d}T)$ behavior27,38 (Table 1 and Fig. 1). After measurement of the as-prepared MXene electronic properties, the samples were inserted into the TEM and vacuum annealed at temperatures up to $775^{\\circ}\\mathrm{C}$ . \n\nBefore providing a detailed analysis of our in situ heating and biasing experiments, we first summarize our two main findings. First, we observed transitions from semiconductor-like to metallic behavior in ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ and $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ after the annealing-induced loss of intercalated species. These transitions reveal the intra-flake metallicity of $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ and $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ and demonstrate that intercalants can cause negative $\\mathrm{d}R/\\mathrm{d}T$ in multi-layer MXenes. Second, high temperature annealing and the partial loss of surface terminations (Fig. 1, bottom insets) increased the conductivity of all three MXenes. This finding is in agreement with past predictions that non-terminated MXenes exhibit metallic behavior with high carrier concentrations43,55,56,59. In the following, we describe the in situ heating and biasing data in greater detail; results are organized based on the different mechanisms which influence MXene electronic properties. \n\nAdsorbed species. Prior to thermal annealing, insertion of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ into the TEM vacuum $(\\sim\\mathrm{{i}}0^{-5}\\mathrm{{Pa})}$ caused an immediate reduction in resistance (Fig. 1a, b and Supplementary Figure 3). For both of these samples, the resistance decreased roughly $20\\%$ after $150s$ of insertion into the TEM. This change in resistance is attributed to the loss of adsorbed atmospheric species, e.g., $\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{O}_{2}$ . These species are known to cause doping in 2D materials such as graphene63, and similar effects have previously been reported in $\\breve{\\mathrm{Ti}_{3}}\\dot{\\mathrm{C}_{2}}\\mathrm{T}_{x}{}^{8,25}$ . We note that both of these samples were only intercalated with $\\mathrm{H}_{2}\\mathrm{O}$ and ${\\mathrm{Li^{+}}}$ . For $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ intercalated with $\\mathrm{TBA^{+}}$ , the sample resistance did not significantly change upon exposure to the TEM vacuum (Fig. 1c and Supplementary Figure 3). This observation suggests an increased effect of the large $\\mathrm{TBA^{+}}$ molecule relative to $\\mathrm{\\bar{H}}_{2}\\mathrm{O}$ , specifically, that $\\mathrm{TBA^{+}}$ intercalation limits the film resistance and masks the effect of atmospheric species desorption on the electronic resistance. The effect of adsorbed species on the resistance of $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA^{+}})$ could not be determined, since the sample resistance prior to in situ vacuum annealing was too high to be accurately measured. \n\nIntercalation. For all studied MXenes, de-intercalation significantly increased electronic conductivity. We first consider the role of $_{\\mathrm{H}_{2}\\mathrm{O}}$ , which began to de-intercalate at lower temperatures than $\\mathrm{TBA^{+}}$ . For all samples, mass spectroscopy (MS) showed a large peak in the $_{\\mathrm{H}_{2}\\mathrm{O}}$ (mass to charge ratio $(m/e)=18^{\\circ}$ ) ion current centered at ${\\sim}150^{\\circ}\\mathrm{C},$ indicating $\\mathrm{H}_{2}\\mathrm{O}$ de-intercalation. This behavior is shown for $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ in Fig. 2a, and full TGA-MS results for all samples are presented in Supplementary Figure 4. In situ EELS data is consistent with the de-intercalation of $\\mathrm{H}_{2}\\mathrm{O}$ during low temperature annealing. Figure 2b shows the O $K$ -edge of $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ after various in situ annealing steps; three distinct peaks are observed. For $\\scriptstyle=0$ or $-\\mathrm{OH}$ bonded with surface Ti, these three peaks are expected, with peak 1 arising due to hybridization between the termination moiety and the Ti $3d$ orbitals64. Conversely, the O $K\\mathrm{\\Omega}$ -edge of water does not contain peak $1^{65}$ . With annealing, peaks 2 and 3 decrease with respect to peak 1, signifying the loss of intercalated $_\\mathrm{H}_{2}\\mathrm{O}$ . The loss of $\\scriptstyle=0$ or –OH terminations cannot explain the observed changes in fine structure, as surface de-functionalization would produce a more uniform decrease in the O $K$ -edge intensity. \n\n![](images/a696f6e43914cf1143fa416f2487b3c237206b5117c20ae00102918a88c52dc3.jpg) \nFig. 2 Influence of intercalated species on the MXene resistance and ${\\mathrm{d}}R/{\\mathrm{d}}T.$ a TGA-MS of ${\\mathsf{T i}}_{3}{\\mathsf{C N T}}_{x}$ showing the loss of $H_{2}O$ intercalants and $-\\mathsf{O}\\mathsf{H}$ termination species. b In situ EELS of the normalized O $K$ -edge of ${\\sf T i}_{3}{\\sf C N T}_{x}$ indicating the loss of $H_{2}O$ intercalants with annealing. c $\\therefore E X$ situ XRD of the ${\\sf T i}_{3}{\\sf C N T}_{x}$ (002) peak for an as-prepared thick sample, i.e., vacuum filtered and free-standing, as well as thick samples annealed at $150^{\\circ}\\mathsf C$ (in vacuum) and $400^{\\circ}\\mathsf C$ (in $\\mathsf{A r})$ ). The peak shift to higher $2\\theta$ values represents a decrease in the inter-layer spacing. The dashed vertical line represents the approximate position of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ (002) peak after annealing at $150^{\\circ}\\mathsf C$ , taken from ref. 6. d Temperature-dependent PPMS resistance measurements of a thick asprepared (intercalated) ${\\sf T i}_{3}{\\sf C N T}_{x}$ sample and the de-intercalated sample annealed to $700^{\\circ}\\mathsf C$ within the TEM. $R_{\\mathsf{R T}}$ is the room temperature resistance. e TGA-MS of $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ showing the loss of $H_{2}O$ intercalants and the decomposition of $\\mathsf{T B A^{+}}$ intercalants. f Temperature-dependent PPMS resistance measurements of a thick as-prepared (intercalated) $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ sample and the de-intercalated sample annealed to $775^{\\circ}\\mathsf C$ within the TEM. The asprepared data is taken from ref. 38. $\\pmb{\\mathsf{g}}$ Schematic of intercalants’ influence on conduction through multi-flake $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{T}_{x}$ \n\nBy annealing samples at $200^{\\circ}\\mathrm{C},$ we isolate the influence of $\\mathrm{H}_{2}\\mathrm{O}$ de-intercalation on the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ electronic properties from any effects of surface de-functionalization. To prove this point, we consider the de-functionalization of $-\\mathrm{OH}$ , the least stable termination species and thus the first to desorb12,66. The MS –OH $(m/e=17)$ ) ion current in Fig. 2a shows two peaks for ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ . The first peak perfectly mirrors the $_{\\mathrm{H}_{2}\\mathrm{O}}$ ion current and is thus attributed to de-protonated $_{\\mathrm{H}_{2}\\mathrm{O}}$ (Supplementary Figure 4); the second peak at ${\\sim}375^{\\circ}\\mathrm{C}$ is attributed to $-\\mathrm{OH}$ termination loss. Our conclusion that –OH terminations are stable at ${<}200^{\\circ}\\mathrm{C}$ is supported by nuclear magnetic resonance spectroscopy and neutron scattering studies performed previously on $\\mathrm{\\dot{T}i_{3}C_{2}T}_{x}{}^{67,68}$ , assuming that the termination interaction with surface Ti atoms is similar in both carbide and carbonitride MXenes. Moreover, it was shown that hydroxyl groups do not desorb from titania powder until 350–500 °C69. \n\nFor $200^{\\circ}\\mathrm{C}$ annealed $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x},\\mathrm{H}_{2}\\mathrm{O}$ de-intercalation caused an $18\\%$ reduction in sample resistance, in qualitative agreement with past results (Fig. 1a)50,70. Subtle increases in the dR/dT of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ with 125 and $200^{\\circ}\\mathrm{C}$ annealing suggest the decrease of an insulating inter-flake resistive term, as opposed to a change in the intra-flake metallic conductivity (Supplementary Note 1, Supplementary Figure 5, and Supplementary Table 1). These changes in $\\mathrm{d}R/\\mathrm{d}T$ with low temperature annealing are in agreement with a decrease in resistance driven by $_{\\mathrm{H}_{2}\\mathrm{O}}$ de-intercalation. \n\nIn comparison to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ displayed an anomalously large response to $_{\\mathrm{H}_{2}\\mathrm{O}}$ de-intercalation. After annealing at $200^{\\circ}\\mathrm{C},$ there was a $36\\%$ decrease in resistance and a transition from negative to positive dR/dT (Fig. 1b). Ex situ XRD shows a contraction of the $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ $c$ -lattice parameter (signifying a decrease in the inter-layer spacing) after $150^{\\circ}\\mathrm{C}$ annealing (Fig. 2c). This measurement further confirms the partial deintercalation of water and supports the argument that deintercalation improves conductivity through a reduced inter-flake resistance. \n\nThe measurement of metallic conductivity in $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ confirms numerous theoretical predictions of its metallic nature55,57,58. To better understand the electronic properties of the de-intercalated ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x},$ we studied the sample’s lowtemperature conduction ex situ. To do so, the sample was further annealed to $700^{\\circ}\\mathrm{C}$ (ensuring maximum de-intercalation), removed from the TEM, and then inserted into the physical property measurement system (PPMS). Figure 2d shows the normalized resistance of as-prepared (intercalated) and $700^{\\circ}\\mathrm{C}$ annealed (de-intercalated) $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ . The intercalated sample shows semiconductor-like behavior across the entire temperature range of the PPMS measurement (from RT to $-263^{\\circ}\\mathrm{C})$ , while the de-intercalated sample displays metallic behavior down to roughly $-150^{\\circ}\\mathrm{C}$ . At this temperature, the de-intercalated ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ sample shows a transition to negative $\\mathrm{{d}}R/\\mathrm{{d}}T_{\\mathrm{{i}}}$ , which is similar to the reported behavior of multi-layer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ samples27,38. It is an open question whether this low temperature transition is due to intra-flake or inter-flake effects. Both the asprepared and annealed samples displayed negative magnetoresistance (MR) at $-263^{\\circ}\\mathrm{C}$ $(\\bar{10}\\mathrm{K})$ (Supplementary Figure 6). We note that annealing $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ above $300^{\\circ}\\mathrm{C}$ causes partial surface de-functionalization, which we discuss in the next section. However, high temperature annealing and surface defunctionalization did not significantly affect $\\mathrm{d}R/\\mathrm{d}T$ (Fig. 1b and Supplementary Table 1), so we ascribe the changes in normalized resistance shown Fig. 2d to de-intercalation. \n\n![](images/fd525ec4d8d36e15ce57e74e7fab1409a948229b213c44aa06be4034f4d8e45f.jpg) \nFig. 3 Correlation of MXene surface termination and conductivity. a In situ EELS of the $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ F $K$ -edge showing the loss of $-\\mathsf{F}$ with annealing. b TGA-MS of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ showing de-intercalation of $H_{2}O$ completing by ${\\sim}400^{\\circ}\\mathsf{C}$ and the onset of $-\\mathsf{F}$ de-functionalization at ${\\sim}400^{\\circ}\\mathsf{C}$ . c In situ EELS of the ${\\mathsf{T i}}_{3}{\\mathsf{C}}_{2}{\\mathsf{T}}_{x}\\circ K\\cdot$ - edge with annealing. The relative decrease in peaks 2 and 3 relative to peak 1 indicates the loss of intercalated $H_{2}O$ and the retention of $\\scriptstyle=0$ . d Comparison of the post-anneal RT resistance of $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ (black circles) and $-F$ concentration (green triangles) given in units of $x$ based on the chemical formula $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{O}_{0.5}\\mathsf{F}_{x}$ . e, f show the time-resolved resistance and F $K$ -edge intensity, respectively, of ${\\mathsf{T i}}_{3}{\\mathsf{C N T}}_{x}$ during in situ annealing. The solid (dashed) arrows represent heating (cooling). For the time axis, $t=0s$ corresponds to the beginning of annealing at RT. The stars mark $500^{\\circ}{\\mathsf C}$ , the maximum temperature of prior annealing. The green line in f is a Gaussian smooth of the EELS data (black circles). The dark orange line in f is the calculated RT resistance, determined using the measured value of ${\\mathrm{d}}R/{\\mathrm{d}}T$ upon heating. Because ${\\mathrm{d}}R/{\\mathrm{d}}T$ changes with annealing, this calculation is only valid up to ${\\sim}700^{\\circ}\\mathsf C$ . To highlight the correlation between the $-\\mathsf{F}$ concentration and the calculated RT resistance, both quantities were normalized by their initial value. $\\pmb{\\mathscr{g}}$ In situ EELS spectra of the $\\mathsf{O}{\\mathsf{\\Sigma}}K.$ -edge of ${M o}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}$ . h Comparison of the post-anneal RT resistance (black circles) with the concentration of $_{=0}$ (red squares), given in units of $x$ based on the chemical formula $\\mathsf{M o}_{2}\\mathsf{T i C}_{2}\\mathsf{O}_{x}$ . For a, c, and $\\scriptstyle{\\pmb{\\mathsf{g}}},$ EELS spectra were acquired at RT after annealing, and the edge intensities were normalized to the Ti L-edge intensity. In d and h, the change in elemental concentration was determined with in situ EELS. The temperature offset between elemental concentration data and resistance measurements in d and h are due to thermal gradients within the nanochip (Supplementary Figure 10). The range of these thermal gradients are represented by the horizontal error bars in the RT resistance data \n\nWhile $_{\\mathrm{H}_{2}\\mathrm{O}}$ intercalation was known to increase MXene resistance values, the findings shown in Figs. 1a, b and $2\\mathrm{a-d}$ demonstrate that $_\\mathrm{H}_{2}\\mathrm{O}$ intercalation can additionally act to decrease the value of $\\mathrm{d}R/\\mathrm{d}T$ . Moreover, given a sufficient concentration of intercalants in ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}^{-}$ the inter-flake resistance can mask the MXene’s intra-flake metallic conductivity. We stress that the resulting negative $d R/{\\mathrm{d}}T$ of intercalated ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ is not due to a bandgap opening, rather it is the consequence of the temperature-dependence of the inter-flake electron hopping process. \n\nIt is noteworthy that $_{\\mathrm{H}_{2}\\mathrm{O}}$ intercalated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ displayed metallic conduction while $_{\\mathrm{H}_{2}\\mathrm{O}}$ intercalated ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ displayed semiconductor-like conduction, despite both MXenes being intrinsically metallic. To understand this difference, we show the position of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (002) peak after annealing at $150^{\\circ}\\mathrm{C}$ (vertical dashed line in Fig. 2c). The $\\mathbf{\\Psi}_{c}$ -lattice spacing of $150^{\\circ}\\mathrm{C}\\mathrm{-}$ annealed $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ $(23.0\\textup{\\AA})$ is significantly larger than that of $150^{\\circ}\\mathrm{C}$ -annealed $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}\\left(20.6\\mathring{\\mathrm{A}}\\right)$ . The lattice spacing of $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ only contracts to ${\\sim}20\\mathrm{\\AA}$ after annealing at $400^{\\circ}\\mathrm{C}$ . This data suggests an increased lattice response of ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ to intercalated ${\\mathrm{H}}_{2}{\\mathrm{O}}_{3}$ , which in turn increases the inter-flake resistance and drives the transition to negative $\\mathrm{d}R/\\mathrm{d}T.$ \n\nMeasurements of $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x},$ having both $_\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{TBA^{+}}$ intercalants, showed an increased effect of $\\mathrm{TBA^{+}}$ relative to $\\mathrm{H}_{2}\\mathrm{O}$ . Annealing $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ at $200^{\\circ}\\mathrm{C}$ led to the de-intercalation of $_\\mathrm{H}_{2}\\mathrm{O}$ and a $24\\%$ reduction in resistance, but there was no change in the sign of $\\mathrm{d}R/\\mathrm{d}T$ (Figs. 1c and 2e). Subsequent annealing up to $500^{\\circ}\\mathrm{C}$ led to a $69\\%$ decrease in resistance and a transition from negative to positive $\\mathbf{d}R/\\mathbf{d}T$ (Fig. 1c). This transition to metallic behavior is due to the decomposition and loss of $\\mathrm{TBA^{+}}$ , as seen in the MS signal of ${\\mathrm{C}}_{2}{\\mathrm{H}}_{6}$ ${\\mathrm{\\Delta}m}/e=30$ ) (Fig. 2e). The measured temperature of $\\mathrm{TBA^{+}}$ de-intercalation/decomposition was $\\sim350^{\\circ}\\mathrm{C},$ which is similar to the decomposition temperature of $\\mathrm{TBA^{+}}$ intercalated in graphite71. Previous work has shown that annealing $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ at $530^{\\circ}\\mathrm{C}$ reduces the $\\boldsymbol{\\mathscr{c}}$ -lattice parameter from 37.7 to $24.5\\mathrm{~\\AA~}^{52}$ , which supports our claim that the decomposition of $\\mathrm{TBA^{+}}$ causes a decrease in the inter-flake resistance and consequently a transition to metallic behavior. \n\nTo further study the effect of $\\mathrm{TBA^{+}}$ decomposition, the lowtemperature resistance of $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ was measured. We annealed the sample up to $775^{\\circ}\\mathrm{C}$ in an attempt to eliminate residual $\\mathrm{TBA^{+}}$ , and then we removed the sample from the TEM and inserted it into the PPMS. The normalized resistance of the as-prepared (intercalated) and the annealed (de-intercalated) $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}$ are shown in Fig. 2f. The de-intercalated $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ sample shows metallic behavior down to the lowest measured temperature of $-263^{\\circ}\\mathrm{C}$ (10 K), and both the as-prepared and deintercalated samples show positive MR (Supplementary Figure 6). These results demonstrate the intrinsically metallic nature of $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x},$ in agreement with the previously reported metallic conductivity in this MXene after annealing at ${\\sim}53\\bar{0}^{\\circ}\\mathrm{C}^{52}$ . We note that annealing $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ at $775^{\\circ}\\mathrm{C}$ leads to the partial loss of termination groups; however, annealing at these high temperatures did not significantly alter the value of $\\mathrm{d}R/\\mathrm{d}T$ (Fig. 1c and Supplementary Table 1). Thus, the difference in normalized resistance shown in Fig. 2f is attributed to de-intercalation. \n\nThe observation of intercalation-induced negative $\\mathrm{d}R/\\mathrm{d}T$ in two different MXenes with two different intercalant species provides strong evidence that this is a general phenomenon. For sufficient levels of intercalation, the thermally activated inter-flake hopping process becomes the rate-limiting step for conduction through multi-layer samples. This extrinsic effect causes MXenes to display negative $\\mathrm{d}R/\\mathrm{d}T$ regardless of their intrinsic electronic properties, as shown schematically in Fig. $2\\mathrm{g}$ . \n\nNext, we consider ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ intercalated with $\\mathrm{TBA^{+}}$ . With annealing, $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA^{+}})$ showed a larger total reduction in resistance than $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ intercalated with only $_\\mathrm{H}_{2}\\mathrm{O}$ and ${\\mathrm{Li^{+}}}$ (Table 1 and Supplementary Figure 7), consistent with the increased effect of $\\mathrm{TBA^{+}}$ intercalants. However, even after annealing at $750^{\\circ}\\mathrm{C}.$ $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA}^{+})$ continued to display negative $\\mathrm{{\\dot{d}}}R/\\mathrm{d}T,$ albeit with a reduced temperature-dependency (Supplementary Table 1). Given the previous demonstration of metallic intra-flake conduction in $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x},$ we speculate that incomplete removal of $\\mathrm{TBA^{+}}$ is responsible for the persistence of the semiconductor-like behavior. After annealing, the temperature-dependent resistance closely followed $R\\propto T\\times$ exp $(W/\\bar{k}T)$ , which may be related to the inter-flake hopping mechanism (Supplementary Figure 7). It is presently unclear why annealing led to metallic conduction in $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}(\\mathrm{TBA}^{+})$ but not in $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA}^{+})$ . This difference could be due to the surface Mo atoms of $\\mathbf{Mo}_{2}\\mathbf{TiC}_{2}\\mathbf{T}_{x}$ affecting the release of $\\mathrm{TBA^{+}}$ and/or the inter-flake hopping process. \n\nTermination. After de-intercalation, vacuum annealing at higher temperatures led to surface de-functionalization and improved electronic conductivity. Initially, each sample had –OH, $\\mathrm{-F_{:}}$ , and $\\scriptstyle=0$ terminations in varying concentrations (Table 1). Based on DFT calculations, –OH should be the first species to desorb12,66, and for certain samples, TGA-MS data indicated the loss of $-\\mathrm{OH}$ $(m/e=17)$ at ${\\sim}375^{\\circ}\\mathrm{C}$ (Fig. 2a). However, for the majority of TGA-MS measurements, the release of de-protonated $_\\mathrm{H}_{2}\\mathrm{O}$ completely masked the signal of –OH loss (Supplementary Figure 4). De-functionalization of $-\\mathrm{OH}$ was also difficult to detect with in situ EELS (Fig. 2b), which could be due to the electron beam transforming –OH groups into more stable $\\scriptstyle=0$ terminations prior to EELS acquisition72. Conversely, the partial loss of $\\mathrm{-F}$ and $\\scriptstyle=0$ species were clearly identified. As such, we focus on the effects of $-\\mathrm{F}$ and $\\scriptstyle=0$ desorption; however, we stress that the release of these species indicates prior loss of less stable –OH groups12,66. \n\nAnnealing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ from 300 to $775^{\\circ}\\mathrm{C}$ led to a significant loss of $\\mathrm{-F}$ termination species and an associated increase in sample conductivity. In situ EELS measurements show a decrease in the F $K\\cdot$ -edge intensity after annealing at 500, 700, and $775^{\\circ}\\mathrm{C}$ (Fig. 3a), demonstrating the partial de-functionalization of $-\\mathrm{F}$ . Consistent with the EELS measurements, ex situ TGA-MS shows the release of $\\mathrm{-F}$ termination $\\dot{}m/e=19\\$ beginning around $400^{\\circ}\\mathrm{C}$ (Fig. 3b). The broad peak in the $m/e=19$ ion channel at ${\\sim}150^{\\circ}\\mathrm{C}$ closely mirrors the $\\mathrm{\\tilde{H}}_{2}\\mathrm{O}$ channel, indicating that this peak arises from a mechanism related to $_{\\mathrm{H}_{2}\\mathrm{O}}$ de-intercalation, e.g., release of protonated $_\\mathrm{H}_{2}\\mathrm{O}$ . Despite the large loss of –F, there was no evidence of $\\scriptstyle=0$ release, as demonstrated by the constant value of peak 1 of the O $K$ -edge EELS spectra (Fig. 3c). \n\nThe observed loss of $\\mathrm{-F}$ beginning at ${\\sim}400^{\\circ}\\mathrm{C}$ and the retention of $\\scriptstyle=0$ terminations is consistent with ref. 73, where Persson et al. report in situ annealing of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ with scanning TEM (STEM) and XPS analysis. However, our results differ from the recent in situ STEM annealing of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ reported by Sang et al.54. In their study, $\\scriptstyle=0$ terminations were lost and large voids were formed after $500^{\\circ}\\mathrm{C}$ annealing and electron irradiation. We attribute these contradictory results to beam induced effects. Sang et al. utilized a focused STEM probe $(\\sim10^{9}~\\mathrm{e}^{-}~s^{-1}\\mathring{\\mathrm{A}}^{-2})$ while we used a spread TEM beam $(\\sim10\\mathrm{\\bar{e}}^{-}s^{-1}\\mathrm{\\mathring{A}}^{-2})$ . Moreover, our use of low-dose DD $\\mathrm{EELS}^{53}$ allows short acquisition times, further decreasing the potential for beam-induced sample degradation (Supplementary Figure 1). \n\nIn Fig. 3d, we show the correlation between changes in the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}-\\mathrm{F}$ concentration and the RT resistance as a function of annealing temperature. The decrease in sample resistance produced during the $500^{\\circ}\\mathrm{C}$ annealing step likely has a significant contribution from the loss of $-\\mathrm{OH}$ groups. Additionally, there may be a small contribution from the final stages of $_\\mathrm{H}_{2}\\mathrm{O}$ deintercalation. However, after the $500^{\\circ}\\mathrm{C}$ annealing step, ex situ TGA-MS (Fig. 3b) and in situ EELS (Fig. 3c) show no evidence of further $_{\\mathrm{H}_{2}\\mathrm{O}}$ loss. Additionally, XRD studies have shown that there is no change in the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ c-lattice spacing for annealing beyond $500^{\\circ}\\mathrm{C}^{7\\tilde{4}}$ . With no evidence of intercalation loss, no change in the inter-flake spacing, and no observation of a conducting secondary phase (Supplementary Figure $2)^{75}$ , we conclude that the improvement in $\\mathrm{\\bar{Ti}}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ conductivity during annealing steps at 700 and $775^{\\circ}\\mathrm{C}$ is entirely due to the loss of $\\mathrm{-F}$ terminations. \n\nSimilar to $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ in situ annealing of $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ at 500 and $700^{\\circ}\\mathrm{C}$ led to a reduction in $\\mathrm{-F}$ species and improved conductivity (Fig. 1b and Supplementary Figure 8). In addition to the $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ sample discussed previously in the text and shown in Figs. 1 and 2, another $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ sample was measured with time-resolved in situ EELS. The time-resolved measurements of ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ show the simultaneous release of $-\\mathrm{F}$ termination species alongside an increase in electronic conductivity (Fig. 3e, f and Supplementary Figure 9). This data further demonstrates that the loss of termination species influences the MXene electronic properties. \n\nFor $\\mathrm{Mo}_{2}\\mathrm{Ti}\\bar{\\mathrm{C}}_{2}\\mathrm{T}_{x},$ surface de-functionalization occurred at lower temperatures than $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ or ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x},$ indicating a weaker interaction between termination species and surface Mo atoms compared to Ti atoms. In situ EELS shows the complete loss of $-\\mathrm{F}$ from $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ after annealing at $500^{\\circ}\\mathrm{C}$ (Supplementary Figure 8), and annealing at 700 and $775^{\\circ}\\mathrm{C}$ produced a large reduction in the $\\scriptstyle=0$ concentration (Fig. 3g). As $\\scriptstyle=0$ terminations were partially removed from the surface, the $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ resistance decreased a total of $32\\%$ (Fig. 3h). These findings suggest that the release of $\\scriptstyle=0$ from $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{O}_{x}$ increases the MXene intra-flake conductivity38,59. However, we cannot rule out the possibility that inter-flake effects contribute to the measured changes in resistance for annealing steps at 700 and $775^{\\circ}\\mathrm{C}$ . As opposed to $\\mathrm{H}_{2}\\mathrm{O}$ intercalants which cleanly de-intercalate, the $\\mathrm{TBA^{+}}$ intercalants decompose (Fig. 2e and Supplementary Figure 4). Even though the decomposition of $\\mathrm{TBA^{+}}$ leads to the onset of metallic behavior in $\\mathbf{Mo}_{2}\\mathbf{TiC}_{2}\\mathbf{T}_{x}$ (Fig. 1c), it is possible that some residue remains even after annealing at ${>}500{^\\circ}\\mathrm{C}$ . This is likely the case for $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA}^{+})$ , since this MXene does not show metallic behavior even after annealing at $750^{\\circ}\\mathrm{C}$ . \n\nTo the best of our knowledge, these results constitute the first direct experimental correlation of MXene surface chemistry and electronic conductivity. Previous DFT studies have predicted that termination of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ with –OH, $\\mathrm{-F}$ and/or $\\scriptstyle=0$ significantly alters the electronic states near $E_{\\mathrm{F}}{}^{7,43,55,56,66}$ . For non-terminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{CN}$ , DFT predicts a local maximum in the DOS at $E_{\\mathrm{F}},$ but with complete surface functionalization, the $\\mathrm{DOS}(E_{\\mathrm{F}})$ is greatly reduced. Consequently, surface functionalization may alter the electronic resistance through a decrease the carrier concentration, $n$ . To test the validity of this proposed mechanism, we analyzed the concurrent changes in the $\\mathrm{\\bar{Ti}}_{3}\\mathrm{\\bar{C}}_{2}\\mathrm{T}_{x}$ and ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ resistance and $\\mathrm{d}R/\\mathrm{d}T$ with in situ annealing. We assume that the metallic intra-flake conductivity of these MXenes can be described by the Drude equation, and that over the temperature range of our in situ TEM experiments, electron-phonon scattering is approximately linear in temperature $(\\mathrm{Fig.\\1}\\bar{)}^{76,77}$ . With these assumptions, the Drude equation predicts that an increase in $n$ with annealing will produce a proportional decrease in the resistance and $\\mathrm{{d}}R/\\mathrm{{d}}T,$ i.e., $\\bar{\\Delta}R{\\propto}\\Delta d R/\\bar{d}T{\\propto}(n_{1}/n_{2}{-}1)$ , where $n_{1}$ and $n_{2}$ are the carrier concentrations before and after annealing, respectively (Supplementary Note 1). To visualize this behavior, we define $\\eta$ as the ratio of the proportional change in the RT dR/dT to the proportional change in the RT resistance for a given annealing step. A value of $\\eta=1$ is predicted for a change in resistance driven solely by a change in the intra-flake carrier concentration. For annealing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ at high temperatures, $\\eta\\sim1$ supporting the claim that surface de-functionalization increases the MXene conductivity through an increase in $n$ (Fig. 4). \n\nIn contrast to the $\\eta\\sim1$ behavior for high temperature annealing, $\\eta$ is negative for annealing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ at low temperatures $(\\eta<0$ reflects a decrease in resistance and an increase in $\\mathrm{d}R/\\mathrm{d}T)$ . As we describe in Supplementary Note 1, a negative value of $\\eta$ is inconsistent with a change to the intra-flake metallic conductivity driven by, e.g., a change in $n$ , effective electron mass, or defect density. However, a negative value of $\\eta$ can be explained by a decrease in the insulating inter-flake resistance, assuming that the inter-flake and intra-flake resistances act in series. Thus, the observed transition from negative to positive $\\eta$ is indicative of a transition from control over the interflake resistance (due to low temperature annealing and deintercalation) to control over the intra-flake resistance (due to high temperature annealing and surface de-functionalization). For $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{X}$ and $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA^{+}})$ , $\\eta<0$ for all annealing temperatures, suggesting that residue from the $\\mathrm{TBA^{+}}$ decomposition continues to affect the MXene inter-flake resistance even after annealing at ${>}500^{\\circ}\\mathrm{C}$ (Supplementary Figure 5). \n\n# Discussion \n\nIn this study, we vacuum annealed multi-layer MXene samples within the TEM and measured 4, $6,\\ >10$ , and 6 times increases in the conductivity of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{{\\boldsymbol{x}}},$ ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x},$ ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ $\\mathrm{(TBA^{+})}$ , and $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ respectively. With annealing, we studied de-intercalation and surface de-functionalization with both in situ and ex situ spectroscopic techniques. By correlating this chemical analysis with in situ resistance and $\\mathrm{d}R/\\mathrm{d}T$ measurements, we were able to delineate the effects of intercalation and surface termination on MXene electronic properties. \n\n![](images/a7fd9c724ff4a84c956e0eee6dc5d2126789912849bfa4559657669b0b7ad329.jpg) \nFig. 4 Analysis of concurrent resistance and ${\\mathrm{d}}R/{\\mathrm{d}}T$ changes with annealing. For a given annealing step, $\\eta$ is the ratio of the proportional change in the RT dR/dT to the proportional change in the RT resistance (Supplementary Note 1). A positive value of $\\eta$ (indicating a decrease in both the ${\\mathrm{d}}R/{\\mathrm{d}}T$ and the resistance) is consistent with a change in the intra-flake resistance, and a negative value of $\\eta$ (indicating an increase in ${\\mathrm{d}}R/{\\mathrm{d}}T$ and a decrease in resistance) is consistent with a change to the inter-flake resistance. For a change in resistance solely due to a change in the intra-flake carrier concentration, the Drude formula predicts that $\\eta=1$ . The colored lines are a guide to the eye. Error bars represent the measurement standard error accounting for the linear fit to the dR/dT data and assuming a base uncertainty of $1.2\\%$ in the resistance measurements. For the inset equation, $n_{1}$ and $n_{2}$ refer to the intra-flake carrier concentrations before and after an annealing step, respectively. See Supplementary Figure 5 for ${\\mathrm{d}}R/{\\mathrm{d}}T$ and $\\eta$ analysis for all studied MXenes \n\nConsidering the role of intercalants first, we found that both $_\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{TB}\\dot{\\mathrm{A}}^{+}$ intercalants increase sample resistance and can induce negative dR/dT. Vacuum annealing caused de-intercalation, significant decreases in sample resistance, and the onset of metallic conduction (except for $\\bar{\\mathrm{Ti}}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA^{+}}))$ . The effects of $\\mathrm{TBA^{+}}$ intercalation on electronic properties were far greater than that of $\\mathrm{H}_{2}\\mathrm{O};$ and even after annealing at ${>}750^{\\circ}\\mathrm{C},$ lingering effects of $\\mathrm{TBA^{+}}$ intercalation persisted. These findings are relevant for the optimization of MXene devices where large metallic conductivity is required and the increased inter-flake spacing associated with intercalation does not affect performance, e.g., wireless communication and wearable electronics. The ability to control $\\mathbf{d}R/\\mathbf{d}T$ through intercalation could find use in multifunctional sensors or in the development of MXene films with arbitrary $\\mathrm{d}R/\\mathrm{d}T$ values. Additionally, we note the striking similarities between the intercalated ${\\mathrm{Ti}}_{3}{\\mathrm{CNT}}_{x}$ and $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}$ samples measured here with previous reports of semiconductor-like transport in Mo- and V-based MXenes38–40. Confirmation of intrinsic semiconducting MXene behavior will require temperature-dependent resistance measurements of single-flake MXene devices, which is beyond the scope of this study. \n\nRegarding the effects of termination, vacuum annealing was shown to cause partial surface termination removal and increases in the MXene electronic conductivity. Oxygen terminations were more stable than $\\mathrm{-F}$ terminations, and $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x}$ experienced a greater degree of surface de-functionalization than the Ti-based MXenes. These findings provide an avenue to further improve performance in MXene applications such as electromagnetic interference shielding and optoelectronics. For other applications, e.g., triboelectrics and catalysis, improved conductivity is desired, but the functionalized MXene surfaces offer chemical benefits. Hence, further analysis is needed to understand how partial defunctionalization affects performance in these areas. From a broader perspective, our findings provide a first step towards realizing non-functionalized MXenes and termination-engineered MXenes, which are predicted to exhibit magnetism56, fully spinpolarized transport42, semiconducting behavior36,38, and nontrivial topological order60,78. \n\n# Methods \n\nSyntheses of MXenes. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ MXene was synthesized by selective etching of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX phase (Materials Research Center, Ukraine) in a mixture of LiF and $\\mathrm{HCl}^{6}$ . Specifically, $0.5{\\mathrm{g}}$ of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ powder was allowed to react with a premixed etchant $\\left(0.8\\mathrm{g}\\right.$ of LiF and $10\\mathrm{mL}$ of $9\\mathrm{M}\\mathrm{HCl}_{\\cdot}^{\\cdot}$ for $24\\mathrm{h}$ at room temperature. Then the acid mixture was washed with $150\\mathrm{mL}$ of deionized water for 3–5 cycles until the $\\mathrm{\\tt{pH}}$ of the supernatant reached the value of 5. After that, the mixture was handshaken for $10\\mathrm{min}$ followed by centrifugation at $3500\\mathrm{rpm}$ for $10\\mathrm{min}$ to remove unreacted MAX particles and reaction by-products. The dark supernatant was centrifuged at $3500\\mathrm{rpm}$ for another $^{\\textrm{1h}}$ to yield delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ solution. \n\n$\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ MXene was synthesized from $\\mathrm{Ti_{3}A l C N\\ M A X^{11}}$ phase by two different routes. For the first route, the synthesis protocol is similar to the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ protocol mentioned earlier except that the reaction mixture was stirred at $500\\mathrm{rpm}$ at $40^{\\circ}\\mathrm{C}$ for $^{18\\mathrm{h}}$ . For the second route, etching is performed in HF acid and delamination is achieved with molecular intercalation. Initially, $2\\mathrm{g}\\mathrm{Ti}_{3}\\mathrm{AlCN}$ was etched in $20~\\mathrm{mL}$ of ${\\sim}30\\%$ HF acid for $24\\mathrm{h}$ at room temperature. The reaction mixture was washed with $150\\mathrm{mL}$ of deionized water for 3–5 cycles until the $\\mathrm{\\DeltapH}$ of the supernatant reached the value of 5. The resulting mixture was filtered through a filter paper (3501 Coated PP, Celgard, USA) to collect multilayer $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ powder. To delaminate the $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ powder, $_{1\\mathrm{g}}$ of dry powder was stirred in a mixture of ${\\mathfrak{g}}_{\\mathrm{mL}}$ of water and $1\\mathrm{mL}$ of tetrabutylammonium hydroxide (TBAOH) solution (48 ${\\bf w t\\%}$ , Sigma Aldrich) for $24\\mathrm{h}$ . The mixture was hand-shaken for $10\\mathrm{min}$ and washed with 3–5 cycles of deionized water. After neutral $\\mathrm{\\pH}$ was reached, the mixture was centrifuged at $3500\\mathrm{rpm}$ for $10\\mathrm{min}$ to remove unreacted MAX particles and reaction by-products. The brownish supernatant was centrifuged at $3500\\mathrm{rpm}$ for another hour to yield delaminated $\\operatorname{Ti}_{3}\\mathrm{CNT}_{x}$ solution. \n\n$\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ was synthesized from $\\mathbf{Mo}_{2}\\mathrm{TiAlC}_{2}$ MAX phase59. To produce the MAX phase, Mo, Ti, Al, and graphite powders (Alfa Aesar, Ward Hill, MA) were mixed in a ratio 2:1:1.1:2 and ball milled for $18\\mathrm{h}$ in a plastic jar with zirconia balls. The powder mixture was transferred in an alumina crucible and held at $1600^{\\circ}\\mathrm{C}$ for $^{4\\mathrm{h}}$ $\\bar{5}^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ , Ar). The resulting MAX block was drilled and sieved (400 mesh, particle size $<38\\upmu\\mathrm{m}$ ). Specifically, $2\\mathrm{g}$ of $\\mathbf{Mo}_{2}\\mathrm{TiAlC}_{2}$ powder was added to $40~\\mathrm{mL}$ of $48-51\\%$ aqueous HF solution and stirred at $50^{\\circ}\\mathrm{C}$ for $^{48\\mathrm{h}}$ . The mixture was washed and collected the same way as the HF-prepared $\\mathrm{Ti}_{3}\\mathrm{CNT}_{\\mathrm{x}}$ MXene. To delaminate $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ powder, $_{\\textrm{1g}}$ of the powder was stirred in $10~\\mathrm{mL}$ of $48\\%$ TBAOH aqueous solution for $^{12\\mathrm{h}}$ . The mixture was washed with 3 cycles of deionized water ( $3500\\mathrm{rpm}$ for $15\\mathrm{min}$ , each cycle). After a $\\mathrm{\\pH}$ of 7–8 was reached, the supernatant was decanted the same way as the $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA^{+}})$ . The sediment was dispersed in $30~\\mathrm{mL}$ of deionized water and sonicated for $30\\mathrm{min}$ in a water-ice sonication bath under argon bubbling. The final solution was centrifugate at 3500 rpm for $30\\mathrm{min}$ . Finally, the supernatant is collected. \n\nWe note that the exact changes in conductivity, intercalation, and surface termination reported here are likely related to MXene film thickness, flake size, and general flake quality, which are all a function of the synthesis process. As such, the measurement of different MXene films—produced with differing synthesis procedures—will likely produce a differing degree of conductivity changes with annealing. \n\nElectron microscopy and spectroscopy. A JEOL 2100F microscope with a Schottky electron emitter was used for these experiments. The microscope is equipped with the high-resolution pole piece with a ${\\mathrm{C}}_{\\mathrm{s}}$ of $1\\mathrm{mm}$ . EELS measurements were performed in TEM (diffraction) mode in order to sample a large area of the MXene film and to reduce irradiation-induced sample degradation. The EELS collection angle was set to 11 mrad. A direct detection (DD) EELS system was used as recently reported in ref. 53. The energy dispersion was set to $0.125\\mathrm{eV}$ per channel, and the zero-loss peak (approximate energy resolution) was measured to be ${\\sim}1.0\\mathrm{eV}$ . For EELS analysis, Gatan DigitalMicrograph was used. \n\nIn situ heating and biasing. The DENSsolutions Lighting $\\mathrm{D}9+$ heating and biasing sample holder was used for in situ TEM/EELS experiments with the 8 contact (A1-type) heating and biasing nanochips62. MXenes were deposited onto the nanochips through spray casting24 (Supplementary Figure 2). A mask was used to confine the MXene deposition to an area centered on the biasing electrodes (Supplementary Figure 2). Resistance measurements were performed with a 4- probe geometry using a Keithley 2400 SMU. Due to the high conductivity of MXene and the large sample cross-sectional area (relative to in situ TEM standards), application of voltages above $0.1\\mathrm{V}$ led to high current densities. The resulting Joule heating strongly affected heating measurements and damaged the heating and biasing chips. As such, the resistance measurements were obtained with applied voltages of $\\le5\\mathrm{mV}$ . \n\nThe maximum annealing temperatures were 775, 700, 750, and $775^{\\circ}\\mathrm{C}.$ for ${\\mathrm{Ti}_{3}}{\\mathrm{C}_{2}}{\\mathrm{T}_{{X}}},$ $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x},$ $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA}^{-})$ , and $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x},$ respectively. The $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ samples were not heated to $775^{\\circ}\\mathrm{C}$ since previous experiments showed a larger extent of $\\mathrm{TiO}_{2}$ formation at $775^{\\circ}\\mathrm{C}$ . Heating and cooling rates were $1{}^{\\circ}\\mathrm{C}\\ s^{-\\bar{1}}$ . For annealing steps performed at 75, 125, and $200^{\\circ}\\mathrm{C},$ the maximum temperature was held for $10~\\mathsf{s}.$ , and for annealing steps performed at 300, 500, 700, and $775^{\\circ}\\mathrm{C}.$ , the maximum temperature was held for $5\\mathrm{{min}}$ . We note that the average temperature within the samples deviated from the input temperature due to temperature gradients within the films (Supplementary Figure 10). \n\nA different heating procedure was used for the $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}(\\mathrm{TBA^{+}})$ sample. Initially, free $\\mathrm{TBA^{+}}$ molecules prevented good electrical contact, and the sample was annealed in situ at $200^{\\circ}\\mathrm{C}$ to achieve adequate contact between the MXene film and Pt electrodes. Then the sample was heated to $750^{\\circ}\\mathrm{C}$ and held at this temperature for $^{\\textrm{1h}}$ . This modified procedure was aimed at ensuring maximum deintercalation/decomposition of the $\\mathrm{TBA^{+}}$ molecules without significant $\\mathrm{TiO}_{2}$ formation. \n\nWe note that for each $\\mathbf{M}_{n+1}\\mathbf{X}_{n}$ chemistry, two samples were tested with in situ TEM heating and biasing, and each sample showed qualitatively similar behavior (Supplementary Table 2). \n\nThermogravimetric-mass spectrometry analysis. Simultaneous thermogravimetric-mass spectrometry analysis was performed on a Discovery SDT 650 model connected to Discovery mass spectrometer (TA Instruments, DE). Vacuum-filtered films of MXenes were cut to small pieces and packed in a ${90\\upmu\\mathrm{L}}$ alumina pan. Before heating, the analysis chamber was flushed with He gas at $100\\mathrm{mL}\\mathrm{min}^{-1}$ for $^{\\textrm{1h}}$ to reduce residual air. The samples were heated to $1500^{\\circ}\\mathrm{C}$ at a constant heating rate of $10^{\\circ}\\mathrm{C}\\ \\mathrm{min}^{-1}$ in He atmosphere $(100\\mathrm{mL}\\mathrm{min}^{-1}$ ). \n\nLow temperature electronic transport. Electronic transport properties of MXenes after heat treatments were measured in a Quantum Design EverCool II Physical Property Measurement System (PPMS). After the in situ annealing experiments, the heating and biasing nanochip was removed from the TEM and wired to the PPMS sample puck using conductive $\\mathrm{Ag}$ paint (Supplementary Figure 11). Temperature-dependent resistance was recorded from $25^{\\circ}\\mathrm{C}$ $(300~\\mathrm{K})$ down to $-263^{\\circ}\\mathrm{C}$ (10 K) in a low pressure helium environment ( ${\\sim}20$ Torr). Magnetoresistance data was recorded at $10\\mathrm{K}$ by sweeping the magnetic fieldperpendicular to the chip from $-70\\ \\mathrm{kOe}$ to $70\\mathrm{kOe}$ . We note that for both the $\\mathrm{Ti}_{3}\\mathrm{CNT}_{x}$ and $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}\\mathbf{T}_{x}$ samples, the room temperature resistance and $\\mathbf{d}R/\\mathbf{d}T$ values (but not the sign of $\\mathrm{d}R/\\mathrm{d}T)$ differed between the final measurement within the TEM and subsequent measurements within the PPMS. This difference is likely due to the differing experimental set-up and/or sample degradation during exposure to atmosphere after removal from the TEM. \n\nX-ray photoelectron spectroscopy. X-ray photoelectron spectroscopy analysis was performed in a spectrometer (Physical Electronics, VersaProbe 5000, Chanhassen, MN) using a $100~{\\upmu\\mathrm{m}}$ monochromatic Al Kα X-ray beam. Photoelectrons were collected by a takeoff angle of $45^{\\circ}$ between the sample surface and the hemispherical electron energy analyzer. Charge neutralization was applied using a dual beam charge neutralizer irradiating low-energy electrons and ion beam. Vacuum-filtered films were mounted on double-sided tape and were electrically grounded using a copper wire. Prior to data acquisition, an Ar beam operating at $2\\mathrm{kV}$ and $2\\upmu\\mathrm{A}$ was used to sputter the sample surface for 2 min. Quantification and deconvolution of the core-level spectra was performed using a software package (CasaXPS Version 2.3.16 RP 1.6). Background contributions to the measured intensities were subtracted using a Shirley function prior to quantification and deconvolution. \n\nX-ray diffraction. The X-ray diffraction data were acquired from vacuum-filtered films of the same solution used for the in situ TEM study. The data were acquired by a diffractometer (Rigaku Smart Lab, USA) with Cu Kα radiation at a step size of $0.03^{\\circ}$ with 0.6 s dwelling time. \n\n# Data availability \n\nThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. \n\nReceived: 29 June 2018 Accepted: 10 December 2018 \nPublished online: 31 January 2019 \n\n# References \n\n1. Khazaei, M., Ranjbar, A., Arai, M., Sasaki, T. & Yunoki, S. Electronic properties and applications of MXenes: a theoretical review. J. Mater. Chem. C 5, 2488–2503 (2017). \n2. Anasori, B., Lukatskaya, M. R. & Gogotsi, Y. 2D metal carbides and nitrides (MXenes) for energy storage. Nat. Rev. Mater. 2, 16098 (2017). \n3. Wang, H. et al. Clay-inspired MXene-based electrochemical devices and photo-electrocatalyst: state-of-the-art progresses and challenges. Adv. Mater. 1704561, 1–28 (2017). \n4. Naguib, M., Mochalin, V. N., Barsoum, M. W. & Gogotsi, Y. 25th anniversary article: MXenes: a new family of two-dimensional materials. Adv. Mater. 26, 992–1005 (2014). \n5. Chaudhari, N. K. et al. MXene: an emerging two-dimensional material for future energy conversion and storage applications. J. Mater. Chem. A 5, 24564–24579 (2017). \n6. Alhabeb, M. et al. Guidelines for synthesis and processing of two-dimensional titanium carbide $\\mathrm{\\Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene). Chem. Mater. 29, 7633–7644 (2017). \n7. Naguib, M. et al. Two-dimensional nanocrystals produced by exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 23, 4248–4253 (2011). \n8. Lipatov, A. et al. Effect of synthesis on quality, electronic properties and environmental stability of individual monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene flakes. Adv. Electron. Mater. 2, 1600255 (2016). \n9. Miranda, A. et al. Electronic properties of freestanding $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene monolayers. Appl. Phys. Lett. 108, 33102 (2016). \n10. Zhang, C. J. et al. Transparent, flexible, and conductive 2D titanium carbide (MXene) films with high volumetric capacitance. Adv. Mater. 29, 1–9 (2017). \n11. Naguib, M. et al. Two-dimensional transition metal carbides. ACS Nano 6, 1322–1331 (2012). \n12. Ashton, M., Mathew, K., Hennig, R. G. & Sinnott, S. B. Predicted surface composition and thermodynamic stability of MXenes in solution. J. Phys. Chem. C. 120, 3550–3556 (2016). \n13. Zhang, C. J. et al. Oxidation stability of colloidal two-dimensional titanium carbides (MXenes). Chem. Mater. 29, 4848–4856 (2017). \n14. Shahzad, F. et al. Electromagnetic interference shielding with 2D transition metal carbides (MXenes). Science 353, 1137–1141 (2016). \n15. Liu, J. et al. Hydrophobic, flexible, and lightweight mxene foams for highperformance electromagnetic-interference shielding. Adv. Mater. 29, 1–6 (2017). \n16. Sarycheva, A. et al. 2D titanium carbide (MXene) for wireless communication. Sci. Adv. 4, eaau0920 (2018). \n17. Yu, X. et al. Monolayer $\\mathrm{Ti}_{2}\\mathrm{CO}_{2}$ : a promising candidate for $\\mathrm{NH}_{3}$ sensor or capturer with high sensitivity and selectivity. ACS Appl. Mater. Interfaces 7, 13707–13713 (2015). \n18. Kim, S. J. et al. Metallic $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ MXene gas sensors with ultrahigh signal-tonoise ratio. ACS Nano 12, 986–993 (2018). \n19. Xu, B. et al. Ultrathin MXene-micropattern-based field-effect transistor for probing neural activity. Adv. Mater. 28, 3333–3339 (2016). \n20. Lee, E. et al. Room temperature gas-sensing of two-dimensional titanium carbide (MXene). ACS Appl. Mater. Interfaces 7, 37184–37190 (2017). \n21. Luo, J. et al. $\\mathrm{Sn^{4+}}$ ion decorated highly conductive $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene: promising lithium-ion anodes with enhanced volumetric capacity and cyclic performance. ACS Nano 10, 2491–2499 (2016). \n22. Lukatskaya, M. R. et al. Ultra-high-rate pseudocapacitive energy storage in two-dimensional transition metal carbides. Nat. Energy 2, 17105 (2017). \n23. Ghidiu, M., Lukatskaya, M. R., Zhao, M., Gogotsi, Y. & Barsoum, M. W. Conductive two-dimensional titanium carbide ‘clay’ with high volumetric capacitance. Nature 516, 78–90 (2014). \n24. Hantanasirisakul, K. et al. Fabrication of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ MXene transparent thin films with tunable optoelectronic properties. Adv. Electron. Mater. 2, 1600050 (2016). \n25. Dillon, A. D. et al. Highly conductive optical quality solution-processed films of 2D titanium carbide. Adv. Funct. Mater. 26, 4162–4168 (2016). \n26. Ying, G., Dillon, A. D., Fafarman, A. T. & Barsoum, M. W. Transparent, conductive solution processed spincast 2D $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\boldsymbol{x}}$ (MXene) films. Mater. Res. Lett. 5, 391–398 (2017). \n27. Halim, J. et al. Transparent conductive two-dimensional titanium carbide epitaxial thin films. Chem. Mater. 26, 2374–2381 (2014). \n28. Dong, Y. et al. Metallic MXenes: a new family of materials for flexible triboelectric nanogenerators. Nano Energy 44, 103–110 (2018). \n29. Jiang, Q. et al. MXene electrochemical microsupercapacitor integrated with triboelectric nanogenerator as a wearable self-charging power unit. Nano Energy 45, 266–272 (2018). \n30. Lian, W. et al. Two-dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ coating as an emerging protective solid-lubricant for tribology. Ceram. Int. 44, 20154–20162 (2018). \n31. Gao, G., O’Mullane, A. P. & Du, A. 2D MXenes: a new family of promising catalysts for the hydrogen evolution reaction. ACS Catal. 7, 494–500 (2017). \n32. Ran, J. et al. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene co-catalyst on metal sulfide photo-absorbers for enhanced visible-light photocatalytic hydrogen production. Nat. Commun. 8, 13907 (2017). \n33. Pan, H. Ultra-high electrochemical catalytic activity of MXenes. Sci. Rep. 6, 32531 (2016). \n34. An, H. et al. Surface-agnostic highly stretchable and bendable conductive MXene multilayers. Sci. Adv. 4, eaaq0118 (2018). \n35. Khazaei, M., Arai, M., Sasaki, T., Estili, M. & Sakka, Y. Two-dimensional molybdenum carbides: potential thermoelectric materials of the MXene family. Phys. Chem. Chem. Phys. 16, 7841–7849 (2014). \n36. Zha, X. H. et al. The thermal and electrical properties of the promising semiconductor MXene ${\\mathrm{Hf}}_{2}{\\mathrm{CO}}_{2}$ . Sci. Rep. 6, 27971 (2016). \n37. Dong, L., Kumar, H., Anasori, B., Gogotsi, Y. & Shenoy, V. B. Rational design of two-dimensional metallic and semiconducting spintronic materials based on ordered double-transition-metal MXenes. J. Phys. Chem. Lett. 8, 422–428 (2017). \n38. Anasori, B. et al. Control of electronic properties of 2D carbides (MXenes) by manipulating their transition metal layers. Nanoscale Horiz. 1, 227–234 (2016). \n39. Urbankowski, P. et al. 2D molybdenum and vanadium nitrides synthesized by ammoniation of 2D transition metal carbides (MXenes). Nanoscale 9, \n17722–17730 (2017). \n40. Halim, J. et al. Synthesis and characterization of 2D molybdenum carbide (MXene). Adv. Funct. Mater. 26, 3118–3127 (2016). \n41. Halim, J. et al. Variable range hopping and thermally activated transport in molybdenum-based MXenes. Phys. Rev. B 98, 104202 (2018). \n42. Gao, G. et al. Monolayer MXenes: promising half-metals and spin gapless semiconductors. Nanoscale 8, 8986–8994 (2016). \n43. Tang, Q., Zhou, Z. & Shen, P. Are MXenes promising anode materials for Li ion batteries? Computational studies on electronic properties and Li storage capability of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{X}_{2}$ ( $\\mathrm{X=F}$ , OH) monolayer. J. Am. Chem. Soc. \n134, 16909–16916 (2012). \n44. Handoko, A. D. et al. Tuning the basal plane functionalization of twodimensional metal carbides (MXenes) to control hydrogen evolution activity. ACS Appl. Energy Mater. 1, 173–180 (2017). \n45. Lee, Y., Hwang, Y. & Chung, Y. C. Achieving type i, ii, and iii heterojunctions using functionalized MXene. ACS Appl. Mater. Interfaces 7, 7163–7169 (2015). \n46. Bai, Y. et al. Dependence of elastic and optical properties on surface terminated groups in two-dimensional MXene monolayers: a first-principles study. RSC Adv. 6, 35731–35739 (2016). \n47. Lei, J., Kutana, A. & Yakobson, B. I. Predicting stable phase monolayer $\\mathrm{Mo}_{2}\\mathrm{C}$ (MXene), a superconductor with chemically-tunable critical temperature. J. Mater. Chem. C 5, 3438–3444 (2017). \n48. Römer, F. M. et al. Controlling the conductivity of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXenes by inductively coupled oxygen and hydrogen plasma treatment and humidity. RSC Adv. 7, 13097–13103 (2017). \n49. Lai, S. et al. Surface group modification and carrier transport property of layered transition metal carbides $\\mathrm{\\mathop{Ti}}_{2}\\mathrm{CT}_{\\mathrm{\\scriptsize{x}}},$ T: -OH, -F and -O). Nanoscale 7, \n19390–19396 (2015). \n50. Muckley, E. S. et al. Multimodality of structural, electrical, and gravimetric responses of intercalated MXenes to water. ACS Nano 11, 11118–11126 (2017). \n51. Ghidiu, M. et al. Alkylammonium cation intercalation into $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (MXene): effects on properties and ion-exchange capacity estimation. Chem. Mater. 29, \n1099–1106 (2017). \n52. Kim, H., Anasori, B., Gogotsi, Y. & Alshareef, H. N. Thermoelectric properties of two-dimensional molybdenum-based MXenes. Chem. Mater. 29, \n6472–6479 (2017). \n53. Hart, J. L. et al. Direct detection electron energy- loss spectroscopy: a method to push the limits of resolution and sensitivity. Sci. Rep. 7, 8243 (2017). \n54. Sang, X. et al. In situ atomistic insight into the growth mechanisms of single layer 2D transition metal carbides. Nat. Commun. 9, 2266 (2018). \n55. Enyashin, A. N. & Ivanovskii, A. L. Two-dimensional titanium carbonitrides and their hydroxylated derivatives: Structural, electronic properties and stability of MXenes $\\mathrm{Ti}_{3}\\mathrm{C}_{2-\\mathrm{x}}\\mathrm{N}_{\\mathrm{x}}(\\mathrm{OH})_{2}$ from DFTB calculations. J. Solid State Chem. 207, 42–48 (2013). \n56. Xie, Y. & Kent, P. R. C. Hybrid density functional study of structural and electronic properties of functionalized $\\mathrm{Ti}_{n+1}\\mathrm X_{n}$ $_{\\mathrm{(X=C,N}}$ ) monolayers. Phys. Rev. B 87, 235441 (2013). \n57. Zhang, W. et al. The role of terminations and coordination atoms on the pseudocapacitance of titanium carbonitride monolayers. Phys. Chem. Chem. Phys. 18, 4376–4384 (2016). \n58. Jhon, Y. I. et al. Metallic MXene saturable absorber for femtosecond modelocked lasers. Adv. Mater. 29, 1702496 (2017). \n59. Anasori, B. et al. Two-Dimensional, ordered, double transition metal carbides (MXenes). ACS Nano 9, 9507–9516 (2015). \n60. Khazaei, M., Ranjbar, A., Arai, M. & Yunoki, S. Topological insulators in ordered double transition metals $\\mathbf{M}_{\\ 2}^{\\prime}\\mathbf{M}\\mathbf{C}_{2}$ ( $\\mathrm{\\tilde{M}=M o}$ , W; $\\mathrm{\\Delta}\\mathrm{M}{=}\\mathrm{Ti}$ , Zr, Hf) MXenes. Phys. Rev. B 94, 125152 (2016). \n61. Naguib, M., Unocic, R. R., Armstrong, B. L. & Nanda, J. Large-scale delamination of multi-layers transition metal carbides and carbonitrides ‘MXenes’. Dalt. Trans. 44, 9353–9358 (2015). \n62. Pérez Garza, H. H. et al. in European Microscopy Congress (Wiley‐VCH Verlag GmbH & Co. KGaATO, Lyon France) 237–238 (2016). \n63. Liu, H., Liu, Y. & Zhu, D. Chemical doping of graphene. J. Mater. Chem. 21, \n3335–3345 (2011). \n64. Magne, D., Mauchamp, V., Celerier, S., Chartier, P. & Cabioc’h, T. Siteprojected electronic structure of two-dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene: the role of the surface functionalization groups. Phys. Chem. Chem. Phys. 18, 30946 (2016). \n65. Näslund, L. A. et al. X-ray absorption spectroscopy measurements of liquid water. J. Phys. Chem. B 109, 13835–13839 (2005). \n66. Hu, T. et al. Chemical origin of termination-functionalized MXenes: $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{2}$ as a case study. J. Chem. Phys. 121, 19254–19261 (2017). \n67. Wang, H. W., Naguib, M., Page, K., Wesolowski, D. J. & Gogotsi, Y. Resolving the structure of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXenes through multilevel structural modeling of the atomic pair distribution function. Chem. Mater. 28, 349–359 (2016). \n68. Hope, M. A. et al. NMR reveals the surface functionalisation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . Phys. Chem. Chem. Phys. 18, 5099–5102 (2016). \n69. Mueller, R., Kammler, H. K., Wegner, K. & Pratsinis, S. E. OH surface density of $\\mathrm{SiO}_{2}$ and $\\mathrm{TiO}_{2}$ by thermogravimetric analysis. Langmuir 19, 160–165 (2003). \n70. Ghidiu, M. et al. Ion-exchange and cation solvation reactions in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene. Chem. Mater. 28, 3507–3514 (2016). \n71. Sirisaksoontorn, W., Adenuga, A. A., Remcho, V. T. & Lerner, M. M. Preparation and characterization of a tetrabutylammonium graphite intercalation compound. J. Am. Chem. Soc. 133, 12436–12438 (2011). \n72. Xie, Y. et al. Role of surface structure on Li-ion energy storage capacity of twodimensional transition-metal carbides. J. Am. Chem. Soc. 136, 6385–6394 (2014). \n73. Persson, I. et al. On the organization and thermal behavior of functional groups on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene surfaces in vacuum. 2D Mater. 5, 15002 (2018). \n74. Wang, K. et al. Fabrication and thermal stability of two-dimensional carbide $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ nanosheets. Ceram. Int. 42, 8419–8424 (2016). \n75. Ghassemi, H. et al. In situ environmental transmission electron microscopy study of oxidation of two-dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and formation of carbonsupported $\\mathrm{TiO}_{2}$ . J. Mater. Chem. C. 2, 14339–14343 (2014). \n76. Kasap, S. O. Principles of Electronic Materials and Devices (McGrow-Hill, New York, 2006). \n77. Kittel, C. Introduction to Solid State Physics (John Wiley & Sons, New York, 2005). \n78. Weng, H. et al. Large-gap two-dimensional topological insulator in oxygen functionalized MXene. Phys. Rev. B 92, 75436 (2015). \n\n# Acknowledgements \n\nJ.L.H., A.C.L., and M.L.T. acknowledge funding from the National Science Foundation Major Research Instrumentation award #DMR-1429661, supporting electron microscopy, including EELS, and high-temperature transport measurements. K.H., Y.G., B.A., D.P., and S.M. acknowledge funding from the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, grant #DE-SC0018618, supporting MXene synthesis, low-temperature transport, photoemission, and thermogravimetric analysis. J. L.H., A.C.L., and M.L.T. thank Ben Miller, Stephen Mick, and Paolo Longo of Gatan Inc. for helpful discussions regarding EELS acquisition and in situ heating and biasing \n\nmeasurements. Tyler Mathis, Simge Uzun, and Mohamed Alhabeb are acknowledged for providing MXene solutions. Drexel University Core Facilities is acknowledged for providing access to XPS, XRD, and TEM instruments. Acquisition of the PPMS was supported by the U.S. Army Research Office under grant No. W911NF-11-1-0283. \n\n# Author contributions \n\nM.L.T. and Y.G. conceived of the experimental plan. J.L.H. performed the in situ TEM and EELS experiments with assistance from A.C.L., K.H., and Y.P. K.H. synthesized and deposited MXenes samples, performed TGA-MS, PPMS, and XPS measurements. B.A. and D.P. prepared $\\mathbf{Mo}_{2}\\mathrm{TiAlC}_{2}$ and $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ respectively. Y.P. and J.T.v.O. performed nanochip temperature simulations. J.L.H. prepared the manuscript. All authors reviewed and contributed to the final manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-08169-8. \n\nCompeting interests: Y.P. and J.T.v.O. are employees of DENSsolutions, which developed and is marketing the Lightning $\\mathrm{D9+}$ sample holder used here. The remaining authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks the anonymous reviewers for their contributions to the peer review of this work. Peer reviewer reports are available. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1038_s41467-019-13092-7", + "DOI": "10.1038/s41467-019-13092-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-13092-7", + "Relative Dir Path": "mds/10.1038_s41467-019-13092-7", + "Article Title": "Non-noble metal-nitride based electrocatalysts for high-performance alkaline seawater electrolysis", + "Authors": "Yu, L; Zhu, Q; Song, SW; McElhenny, B; Wang, DZ; Wu, CZ; Qin, ZJ; Bao, JM; Yu, Y; Chen, S; Ren, ZF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Seawater is one of the most abundant natural resources on our planet. Electrolysis of seawater is not only a promising approach to produce clean hydrogen energy, but also of great significance to seawater desalination. The implementation of seawater electrolysis requires robust and efficient electrocatalysts that can sustain seawater splitting without chloride corrosion, especially for the anode. Here we report a three-dimensional core-shell metal-nitride catalyst consisting of NiFeN nulloparticles uniformly decorated on NiMoN nullorods supported on Ni foam, which serves as an eminently active and durable oxygen evolution reaction catalyst for alkaline seawater electrolysis. Combined with an efficient hydrogen evolution reaction catalyst of NiMoN nullorods, we have achieved the industrially required current densities of 500 and 1000 mA cm(-2) at record low voltages of 1.608 and 1.709 V, respectively, for overall alkaline seawater splitting at 60 degrees C. This discovery significantly advances the development of seawater electrolysis for large-scale hydrogen production.", + "Times Cited, WoS Core": 985, + "Times Cited, All Databases": 1017, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000495393000001", + "Markdown": "# Non-noble metal-nitride based electrocatalysts for high-performance alkaline seawater electrolysis \n\nLuo $\\mathsf{Y u}^{1,2}$ , Qing Zhu2,3, Shaowei Song2,3, Brian McElhenny2, Dezhi Wang2, Chunzheng Wu4, Zhaojun Qin4, Jiming ${\\mathsf{B a o}}^{4}$ , Ying Yu 1\\*, Shuo Chen2\\* & Zhifeng Ren2\\* \n\nSeawater is one of the most abundant natural resources on our planet. Electrolysis of seawater is not only a promising approach to produce clean hydrogen energy, but also of great significance to seawater desalination. The implementation of seawater electrolysis requires robust and efficient electrocatalysts that can sustain seawater splitting without chloride corrosion, especially for the anode. Here we report a three-dimensional core-shell metalnitride catalyst consisting of NiFeN nanoparticles uniformly decorated on NiMoN nanorods supported on Ni foam, which serves as an eminently active and durable oxygen evolution reaction catalyst for alkaline seawater electrolysis. Combined with an efficient hydrogen evolution reaction catalyst of NiMoN nanorods, we have achieved the industrially required current densities of 500 and $1000\\mathsf{m A c m}^{-2}$ at record low voltages of 1.608 and 1.709 V, respectively, for overall alkaline seawater splitting at $60^{\\circ}\\mathsf C$ . This discovery significantly advances the development of seawater electrolysis for large-scale hydrogen production. \n\nH $\\left(\\operatorname{H}_{2}\\right)$ giys psloauyricneg oanw ingcrteoas hmepnoertragny dreonles tays an ideal ener its hig $(142\\mathrm{MJ}\\mathrm{kg}^{-1}),$ $\\mathrm{use}^{1-5}$ into $\\mathrm{H}_{2}$ and oxygen $\\left(\\mathrm{O}_{2}\\right)$ by electricity produced from waste heat or from renewable but intermittent wind or solar energy is one of the most efficient and sustainable routes for high-purity $\\mathrm{H}_{2}$ production6–11. Over the past decade, many low-cost water electrolyzers with electrolytes consisting of high-purity freshwater have been developed, and some achieve performance even better than that of the benchmark platinum $\\left(\\mathrm{Pt}\\right)$ and iridium dioxide $\\left(\\mathrm{Ir}\\mathrm{O}_{2}\\right)$ catalysts12–15. However, large-scale freshwater electrolysis would put a heavy strain on vital water resources. Seawater is one of the most abundant natural resources on our planet and accounts for $96.5\\%$ of the world’s total water resources16. Direct electrolysis of seawater rather than freshwater is highly significant, especially for the arid zones, since this technology not only stores clean energy, but also produces fresh drinking water from seawater. Nevertheless, the implementation of seawater splitting remains highly challenging, especially for the anodic reaction. \n\nThe major challenge in seawater splitting is the chlorine evolution reaction (CER), which occurs on the anode due to the existence of chloride anions $({\\sim}0.5\\mathrm{M})$ in seawater, and competes with the oxygen evolution reaction (OER)17,18. For the CER in alkaline media, chlorine would further react with $\\mathrm{OH^{-}}$ for hypochlorite formation with an onset potential of about $490\\mathrm{mV}$ higher than that of OER, and thus highly active OER catalysts are demanded to deliver large current densities (500 and $100\\dot{0}\\mathrm{mAcm}^{-2},$ ) at overpotentials well below $490\\mathrm{mV}$ to avoid hypochlorite formation18,19. Another bottleneck hindering the progress of seawater splitting is the formation of insoluble precipitates, such as magnesium hydroxide, on the electrode surface, which may poison the OER and hydrogen evolution reaction (HER) catalysts19. To alleviate this issue, catalysts possessing large surface areas with numerous active sites are more favorable. In addition, the aggressive chloride anions in seawater also corrode the electrodes, further restricting the development of seawater splitting18. Because of these intractable obstacles, only a few studies on electrocatalysts for seawater splitting have been reported, with limited progress made thus far. Recently, Kuang et al. reported an impressive anode catalyst composed of a nickel-iron hydroxide layer coated on a nickel sulfide layer for active and stable alkaline seawater electrolysis, in which a current density of $400\\mathrm{mA}\\mathrm{cm}^{-2}$ was achieved at $1.7\\dot{2}\\mathrm{V}$ for two-electrode electrolysis in $6\\mathrm{M}\\mathrm{KOH}+1.5\\mathrm{M}\\mathrm{NaCl}$ electrolyte at $80{}^{\\circ}\\mathrm{C}^{18}$ . Other non-precious electrocatalysts, including transition metal hexacyanometallate, cobalt selenide, cobalt borate, and cobalt phosphate, have been well studied for OER in NaCl-containing electrolytes17,20,21, but the overpotentials needed to deliver large current densities (500 and $1000\\mathrm{\\mAcm}^{-2}.$ ) are much higher than $490\\mathrm{mV}$ , not to mention the activity for overall seawater splitting. Therefore, it is highly desirable to develop other robust and inexpensive electrocatalysts to expedite the sluggish seawater splitting process, especially for OER at large current densities, so as to boost research on large-scale seawater electrolysis. \n\nTransition metal-nitride (TMN) is highly corrosion-resistant, electrically conductive, and mechanically strong, which makes it a very promising candidate for electrolytic seawater splitting22. Recent studies on $\\mathrm{Ni}_{3}\\mathrm{N}/\\mathrm{Ni}.$ , NiMoN, and Ni-Fe-Mo trimetallic nitride catalysts have established TMN-based materials to be efficient non-noble metal electrocatalysts for freshwater splitting in alkaline media $(1\\mathrm{M}\\mathrm{\\KOH})^{23-25}$ . Considering the need for catalysts with large surface areas and high-density active sites for seawater splitting, here we report the design and synthesis of a three-dimensional (3D) core-shell TMN-based OER electrocatalyst, in which NiFeN nanoparticles are uniformly decorated on NiMoN nanorods supported on porous Ni foam $(\\mathrm{NiMoN}@\\mathrm{NiFeN})$ for exceptional alkaline seawater electrolysis. The 3D core-shell catalyst yields large current densities of 500 and $1000\\mathrm{mAcm}^{-2}$ at overpotentials of 369 and $398\\mathrm{mV}$ , respectively, for OER in 1 $.\\mathrm{~M~KOH{+}}$ natural seawater at $25^{\\circ}\\mathrm{C}$ . In-depth studies show that in situ evolved amorphous layers of NiFe oxide and NiFe oxy(hydroxide) on the anode surface are the real active sites that are not only responsible for the excellent OER performance, but also contribute to the superior chlorine corrosion-resistance. Additionally, the integrated 3D core-shell TMN nanostructures with multiple levels of porosity offer numerous active sites, efficient charge transfer, and rapid gaseous product releasing, which also account for the promoted OER performance. An outstanding two-electrode seawater electrolyzer has subsequently been fabricated by pairing this OER catalyst with another efficient HER catalyst of NiMoN, where the current densities of 500 and $1000\\mathrm{mAcm}^{-2}$ are achieved at record low voltages of 1.608 and $1.709\\mathrm{V}$ , respectively, for overall alkaline seawater splitting at $60^{\\circ}\\mathrm{C}.$ along with superior stability. Impressively, our electrolyzer can be driven by an AA battery or a commercial thermoelectric (TE) module, demonstrating great potential and flexibility in utilizing a broad range of power sources. Overall, this work greatly boosts the science and technology of seawater electrolysis. \n\n# Results \n\nElectrocatalyst preparation and characterization. Figure 1a presents a schematic illustration of the synthesis procedures for the 3D core-shell NiMoN $@$ NiFeN catalyst, where commercial Ni foam (Supplementary Fig. 1) is used as the conductive support due to its high surface area, good electrical conductivity, and low cost26. We first used a hydrothermal method to synthesize $\\mathrm{NiMoO_{4}}$ nanorod arrays on Ni foam, which was then soaked in a NiFe precursor ink and air-dried, followed by a one-step thermal nitridation. The stable construction and the hydrophilic nature of the $\\mathrm{NiMoO_{4}}$ nanorod arrays (Supplementary Fig. 2) facilitate the uniform coverage of the nanorods by the NiFe precursor ink. The pure NiMoN catalyst was prepared by nitridation of $\\mathrm{NiMoO_{4}}$ without soaking in the precursor ink, and scanning electron microscopy (SEM) images show that numerous nanorods with smooth surfaces were uniformly and vertically grown on the surface of the Ni foam (Fig. 1b and its inset, and Supplementary Fig. 3). After soaking in the precursor ink and thermal nitridation, the NiMoN@NiFeN shows a well-preserved nanorod morphology with rough and dense surfaces (Fig. 1c and its inset). The high-magnification SEM image in Fig. 1d clearly shows that the surfaces of the nanorods were uniformly decorated with many nanoparticles, forming a unique 3D core-shell nanostructure that offers an extremely large surface area with a huge quantity of active sites, even with the formation of insoluble precipitates during seawater electrolysis. For comparison, pure NiFeN nanoparticles (Supplementary Fig. 4) were also synthesized on the Ni foam by soaking bare Ni foam in the NiFe precursor ink, followed by thermal nitridation. We also studied the morphology variation of NiMoN $@$ NiFeN with different loading amounts of NiFeN nanoparticles by controlling the concentration of NiFe precursor ink (Supplementary Fig. 5). It was determined that the optimized concentration is $0.\\dot{2}5\\dot{\\mathrm{g}}\\mathrm{ml}^{-1}$ , so this concentration was used for further analyses unless otherwise indicated. \n\nTransmission electron microscopy (TEM) images of $\\mathrm{NiMoN}@$ - NiFeN in Fig. 1e, f further detail the desired core-shell morphology of the nanoparticle-decorated nanorods, showing that the thickness of the NiFeN shell is about $100\\mathrm{nm}$ . Figure $\\mathrm{1g}$ displays a high-resolution TEM (HRTEM) image taken from the tip of the NiMoN $@$ NiFeN nanorod presented in Fig. 1f, showing that the NiFeN nanoparticles are highly mesoporous and interconnected with one another to form a 3D porous network, which is beneficial for seawater diffusion and gaseous product release27,28. The HRTEM image in the Fig. 1g inset reveals distinctive lattice fringes with interplanar spacings of $0.186\\mathrm{nm}$ which is assigned to the (002) plane of NiFeN. The selected area electron diffraction (SAED) pattern (Fig. 1h) recorded from the NiMoN $@$ NiFeN core-shell nanorod exhibits apparent diffraction rings of NiMoN and NiFeN, confirming the existence of NiMoN and NiFeN phases. The energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) line scan result (Fig. 1i) and EDS mapping analysis (Fig. 1j) further verify the quintessential core-shell nanostructure, clearly displaying that Mo and Fe are distributed in the central nanorod and edge nanoparticles, respectively, while Ni and $\\mathrm{~N~}$ are homogeneously distributed throughout the entire core-shell nanorod. \n\n![](images/fc95eda477da398687d51a79b56a586b8624e3d1fca5ece4dd62b58fecc42ebc.jpg) \nFig. 1 Synthesis and microscopic characterization of the as-prepared NiMoN@NiFeN catalyst. a Schematic illustration of the synthesis procedures for the self-supported 3D core-shell NiMoN $@$ NiFeN catalyst. b–d SEM images of $(\\bullet)$ NiMoN and (c, d) NiMoN@NiFeN at different magnifications. e, f TEM images of NiMoN@NiFeN core-shell nanorods at different magnifications. g HRTEM image, h SAED pattern, i EDS line scan, and j dark field scanning transmission electron microscopy (DF-STEM) image and corresponding elemental mapping of the NiMoN@NiFeN catalyst. Scale bars: b, $\\mathtt{\\pmb{c}}30\\upmu\\mathrm{m};$ insets of (b, c) $3\\upmu\\mathrm{m}.$ ; d, e $500\\mathsf{n m}$ ; f $200\\mathsf{n m}$ ; $\\textbf{g}20\\mathsf{n m}$ ; inset of (g) 1 nm; h 2 1/nm; i 250 nm; j 1 µm \n\nWe then conducted X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) measurements to study the chemical compositions and surface element states of the catalysts. Typical XRD patterns (Fig. 2a) reveal the successful formation of NiMoN and NiFeN compositions after corresponding thermal nitridation. Figure 2b shows the XPS survey spectra, demonstrating the presence of Ni, Mo, and $\\mathrm{~N~}$ in the NiMoN nanorods; $\\mathrm{Ni},$ Fe, and N in the NiFeN nanoparticles; and Ni, Mo, Fe, and N in the core-shell NiMoN $@$ NiFeN nanorods. For the high-resolution XPS of $\\mathsf{N i}\\ 2\\mathsf{p}$ of the three catalysts (Fig. 2c), the two peaks at 853.4 and $870.8\\:\\mathrm{eV}$ are attributed to the Ni $2\\mathrm{p}_{3/2}$ and Ni $2\\mathrm{p}_{1/2}$ of Ni species in Ni-N, respectively, while the peaks located at 856.3 and $873.9\\mathrm{eV}$ are assigned to the Ni $2\\mathrm{p}_{3/2}$ and Ni $2\\mathrm{p}_{1/2}$ of the oxidized Ni species (Ni–O), respectively29. The two additional peaks at 862.0 and $880.1\\mathrm{eV}$ are the relevant satellite peaks (Sat.). \n\n![](images/c410630b7605e80484879587bf5fd38942485217d7c263a10ba5ec09bbcd150f.jpg) \nFig. 2 Structural characterization of as-prepared catalysts. a XRD, and b XPS survey, and c–f high-resolution $\\mathsf{X P S}$ of $\\mathbf{\\eta}(\\bullet)$ Ni 2p, (d) Fe $2{\\mathsf{p}},$ (e) Mo 3d, and (f) N 1 s of the NiMoN, NiFeN, and NiMoN $@$ NiFeN catalysts \n\nThe Fe 2p XPS of NiFeN and NiMoN $@$ NiFeN in Fig. 2d show two peaks of Fe $2\\mathrm{p}_{3/2}$ and Fe $2\\mathrm{p}_{1/2}$ at 711.0 and $723.6\\mathrm{eV}$ , respectively, as well as a tiny peak at 720.5 corresponding to the satellite peak30. In Fig. 2e, the Mo 3d XPS of NiMoN and NiMoN $@$ NiFeN show two valence states of $\\mathrm{Mo}^{3+}$ and ${\\mathrm{Mo}}^{6+}$ . For NiMoN, the peak located at $229.6\\mathrm{eV}$ (Mo $3\\mathrm{d}_{5/2}$ ) is ascribed to $\\mathrm{Mo}^{3+}$ in the metal-nitride, which is recognized to be active for $\\mathrm{HER}^{22}$ . The peaks at 232.7 (Mo $3\\mathrm{d}_{3/2}$ ) and $235.3\\mathrm{eV}$ are attributed to ${\\mathrm{Mo}}^{6+}$ due to the surface oxidation of $\\mathrm{NiMoN}^{31}$ . However, the two main peaks of Mo $3\\mathrm{d}_{5/2}$ $(\\mathrm{Mo}^{3+})$ and Mo $3\\mathrm{d}_{3/2}$ $(\\mathrm{Mo}^{6+})$ show an apparent negative shift in binding energy for the NiMoN $@$ - NiFeN, indicating the strong electronic interactions between NiMoN and NiFeN. For the N 1 s XPS (Fig. 2f), the main peak is located at $397.4\\mathrm{eV}$ , which is ascribed to the N species in metalnitrides, and another peak at $399.6\\mathrm{eV}$ originates from the incomplete reaction of $\\mathrm{\\Delta}\\bar{\\mathrm{N}}\\mathrm{H}_{3}{}^{23,32}$ . Additionally, the Mo $3{\\mathrm{p}}_{3/2}$ peak also appears for the NiMoN and NiMoN $@$ NiFeN, and a negative shift in binding energy still exists for the NiMoN $@$ NiFeN, which is in good agreement with the results in Fig. 2e. \n\nOxygen and hydrogen evolution catalysis. We first evaluated the OER activity of the as-prepared catalysts in 1 M KOH electrolyte in freshwater at room temperature $(25^{\\circ}\\mathrm{C})$ . The benchmark $\\mathrm{IrO}_{2}$ catalyst on Ni foam was also included for comparison. All of the measured potentials vs. $\\mathrm{Hg/HgO}$ were converted to the reversible hydrogen electrode (RHE) according to the reference electrode calibration (Supplementary Fig. 6, $\\bar{E_{\\mathrm{RHE}}}=E_{\\mathrm{Hg/HgO}}+\\ 0.925,$ ). All data were measured after cyclic voltammetry (CV) activation and reported with iR compensation $(85\\%)$ . The current density was normalized by the geometrical surface area unless otherwise mentioned. As the CV forward scan results in Fig. 3a show, our 3D core-shell NiMoN $@$ NiFeN catalyst exhibits significantly improved OER activity, requiring overpotentials as low as 277 and $33{\\bar{7}}\\mathrm{mV}$ to achieve current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively, which are considerably smaller than that of NiFeN (348 and $417\\mathrm{mV},$ , NiMoN (350 and $458\\mathrm{mV}.$ ), and the benchmark $\\mathrm{IrO}_{2}$ electrodes (430 and $542\\mathrm{mV}.$ ). This performance is also superior to that of most non-precious OER catalysts in $1\\mathrm{M}\\mathrm{KOH}$ (Supplementary Table 1), including the recently reported $Z_{\\mathrm{{nCo}}}$ oxyhydroxide33, Se-doped $\\mathrm{FeOOH^{34}}$ , NiCoFe-MOF (metalorganic frameworks)35, and FeNiP/NCH (nitrogen-doped carbon hollow framework)36. The polarization curves of the CV backward scan, the CV without and with iR compensation are presented for comparison in Supplementary Figs. 7, 8, and 9a, respectively. We also investigated the redox behaviors of the different metal-nitride catalysts by analyzing their CV curves in the range of about 1.125 ${\\sim}1.525\\mathrm{V}$ vs. RHE, and the results are displayed in Supplementary Fig. 9b–d. In addition, the OER activity of other NiMoN $@$ NiFeN catalysts with different loading amounts of NiFeN was also studied (Supplementary Fig. 10), and the one prepared with a precursor ink concentration of $0.25\\mathrm{g}\\mathrm{ml}^{-1}$ exhibits the highest OER activity. Tafel plots in Fig. 3b show that the NiMoN@NiFeN catalyst has a relatively smaller Tafel slope of $58.6\\mathrm{mV}\\mathrm{dec}^{-1}$ in comparison with that of the NiFeN $(68.9\\mathrm{m}\\mathrm{\\bar{V}}\\mathrm{dec^{-1}}),$ , NiMoN $(82.1\\mathrm{mV}\\mathrm{dec}^{-1}),$ , and $\\mathrm{IrO}_{2}$ electrodes $(86.7\\mathrm{mV~dec^{-1}}),$ ), verifying its rapid OER catalytic kinetics. We further calculated TOF to assess the intrinsic OER activity of the NiMoN $@$ NiFeN catalyst, which presents a TOF value of $0.09s^{-1}$ at an overpotential of $300\\mathrm{mV}$ . This value is not the best among the OER catalysts listed in Supplementary Table 1, but still larger than that of the very good OER catalysts of (Ni,Fe) $\\mathrm{OOH}^{12}$ , $\\mathrm{Fe_{x}C o}_{1-x}\\mathrm{OOH}^{37}$ , and NiFe-OH/NiFeP38. Impressively, our 3D core-shell NiMoN $\\mathbf{\\widehat{\\varphi}}(\\varpi)$ NiFeN catalyst shows very good durability as well for OER in 1 M KOH electrolyte. As revealed in Fig. 3c, the current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ at constant overpotentials show negligible decrease over $^{48\\mathrm{h}}$ OER catalysis, and the CV polarization curves (inset of Fig. 3c) after the stability test remain almost the same as prior to the test. It should be noted that for the stability test at $\\bar{500}\\mathrm{mA}\\mathrm{cm}^{-2}$ , the current density slightly decreases from 499.5 to $480.9\\mathrm{mAcm}^{-2}$ with a degradation rate of $0.775\\mathrm{mAcm^{-2}h^{-1}}$ , which is mainly attributed to the strong adsorption of bubbles blocking the active sites. Moreover, \n\n![](images/2f9c1828b3d70fc5a5bebaf171364b5b3cdc343dfad920b0b36e98102650c042.jpg) \nFig. 3 Oxygen and hydrogen evolution catalysis. a OER polarization curves in 1 M KOH, and b corresponding Tafel plots of different catalysts. c OER chronoamperometry curves of NiMoN@NiFeN at overpotentials of 277 and $337\\mathsf{m V}$ in 1 M KOH. Inset: CV curves of NiMoN $@$ NiFeN before and after the stability test. d HER polarization curves tested in $1M\\mathsf{K O H}.$ , and e corresponding Tafel plots of different catalysts. f HER chronoamperometry curves of NiMoN at overpotentials of 56 and $127\\mathsf{m V}$ in 1 M KOH. Inset: LSV curves of NiMoN before and after the stability test. $\\pmb{\\mathsf{g}}\\mathsf{O}\\mathsf{E}\\mathsf{R}$ and HER polarization curves of NiMoN $@$ NiFeN and NiMoN, respectively, in different electrolytes. h Comparison of the overpotentials required to achieve current densities of 100, 500, and $1000\\mathsf{m A c m}^{-2}$ for NiMoN $@$ NiFeN (OER) and NiMoN (HER) in different electrolytes \n\nSEM images after OER stability tests (Supplementary Fig. 11) demonstrate the high integrity of the 3D core-shell nanostructures of the NiMoN $@$ NiFeN catalyst. Thus, the long-term robustness mostly originates from its integral 3D core-shell nanostructure with different levels of porosity, which benefits rapid gaseous product release, and the strong adhesion between the TMN catalysts and the Ni foam substrate. To investigate the origins of promoted OER activity in the NiMoN@NiFeN catalyst, we calculated the electrochemical active surface area (ECSA) for the different catalysts by double-layer capacitance $\\mathrm{(C_{dl})}$ from their CV curves (Supplementary Fig. 12)39. Clearly, the $C_{\\mathrm{dl}}$ values of the NiMoN and NiMoN $@$ NiFeN catalysts are as large as 188.3 and $238.7\\mathrm{mFcm}^{-2}$ (Supplementary Fig. 13), respectively, which are nearly 2.9 and 3.6 times that of the pure NiFeN nanoparticles $(65.4\\mathrm{~mF~cm}^{-2}$ ), respectively, demonstrating the highly improved ECSA and the increased number of active sites achieved by decorating NiFeN nanoparticles on the NiMoN nanorods to form a 3D core-shell nanoarchitecture, which benefits seawater adsorption and offers rich active sites for catalytic reactions40,41. We further normalized current density by the ECSA, and the NiMoN $@$ NiFeN catalyst still shows better OER activity than that of NiFeN (Supplementary Fig. 14), indicating that factors other than the ECSA also contribute to the enhanced OER activity. For the NiMoN@NiFeN core-shell catalyst, the highly conductive core of NiMoN nanorods and the robust contact between the NiFeN nanoparticles and NiMoN nanorods facilitate the charge transfer between the catalyst and electrolyte, as manifested by the results from electrochemical impedance spectroscopy (EIS, Supplementary Fig. 15), which show that the charge-transfer resistance $(R_{\\mathrm{ct}})$ of this 3D core-shell electrode is only $1.0\\Omega.$ significantly smaller than $9.6\\Omega$ for NiFeN. Additionally, the NiMoN catalyst also has a small $R_{\\mathrm{{ct}}}$ of $1.7\\Omega$ confirming its good electronic conductivity and fast charge transfer. Hence, the rational design of 3D core-shell TMN catalysts offers a large surface area and efficient charge transfer, both of which contribute to the improved OER activity. To seek a good HER catalyst to combine with our NiMoN@NiFeN catalyst for overall seawater splitting, we tested the HER performance of different catalysts, including the benchmark $\\mathrm{Pt/C}$ on Ni foam, in 1 M KOH in freshwater. Strikingly, both the NiMoN@NiFeN and NiMoN catalysts exhibit exceptional HER activity (Fig. 3d) that is even better than that of the benchmark $\\mathrm{Pt/C}$ catalyst, especially the NiMoN catalyst, which requires very low overpotentials of 56 and $127\\mathrm{mV}$ for current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively. The overpotentials required to achieve the same current densities by our NiMoN $@$ NiFeN catalyst (84 and $180\\mathrm{mV}.$ ) are slightly higher, but superior to those needed for the $\\mathrm{Pt/C}$ (96 and $252\\mathrm{mV},$ ) and NiFeN (205 and $299\\mathrm{mV},$ ) catalysts. NiMoN has been demonstrated to be an efficient HER catalyst in alkaline media because of its excellent electronic conductivity and low adsorption free energy of $\\mathrm{H}^{\\ast24,42,43}$ . Fig. 3e reveals that the NiMoN catalyst also exhibits a much smaller Tafel slope of $45.6\\mathrm{mV}$ dec−1 in comparison to the other catalysts measured. Moreover, the NiMoN catalyst shows good stability at current densities of 100 and $500\\mathrm{mA}\\mathrm{\\dot{c}m}^{-2}$ over $\\bar{4}8\\mathrm{h}$ HER testing (Fig. 3f). Therefore, our NiMoN $@$ NiFeN and NiMoN catalysts are highly active and robust for OER and HER, respectively, during freshwater electrolysis in alkaline media. \n\nWe then studied the OER and HER activity in an alkaline simulated seawater electrolyte $(1\\mathrm{M}\\mathrm{KOH}+\\dot{0.5}\\mathrm{M}\\mathrm{NaCl})$ ). As shown in Fig. ${3\\mathrm{g}},$ the 3D core-shell NiMoN@NiFeN catalyst still exhibits outstanding catalytic activity for OER, requiring overpotentials of 286 and $347\\mathrm{mV}$ to achieve current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively. This performance is very close to that in the 1 M KOH electrolyte (Fig. 3g), suggesting selective OER in the alkaline adjusted salty water. We also collected natural seawater from Galveston Bay near Houston, Texas, USA (Supplementary Fig. 16) and prepared an alkaline natural seawater electrolyte $(1\\mathrm{~M~KOH+Seawater})$ , in which the OER activity of the NiMoN $@$ NiFeN catalyst shows only slight decay compared with that in the other two electrolytes (Fig. 3g). The slight decrease in activity may be due to some insoluble precipitates [e.g., $\\mathrm{Mg(OH)}_{2}$ and $\\mathrm{Ca}(\\mathrm{OH})_{2}]$ covering the surface of the electrode, and thus burying some surface active sites (Supplementary Figs. 17 and 18). Even so, the NiMoN $@$ NiFeN catalyst still delivers current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ at small overpotentials of 307 and $369\\mathrm{mV}$ , respectively, in the alkaline natural seawater electrolyte (Fig. 3h). In addition, at an even larger current density of $\\mathrm{\\i}000\\mathrm{mAcm}^{-2}$ , the demanded overpotential is only $398\\mathrm{mV}$ , which is well below the $490\\mathrm{mV}$ overpotential required to trigger chloride oxidation to hypochlorite. Moreover, this overpotential is also much lower than that of any of the other reported non-precious OER catalysts in alkaline adjusted salty water (Supplementary Table 2). The HER catalyst of NiMoN also exhibits excellent activity in both the alkaline simulated and natural seawater electrolytes (Fig. 3g). To deliver current densities of 100, 500, and $1000\\mathrm{\\dot{m}A c m\\bar{-}}^{2}$ in the alkaline natural seawater, the required overpotentials are as low as 82, 160, and $218\\mathrm{mV}$ , respectively (Fig. 3h). Consequently, our NiMoN $@$ NiFeN and NiMoN catalysts are not only efficient for freshwater electrolysis, but also highly active for alkaline seawater splitting. \n\nOverall seawater splitting. Considering the outstanding catalytic performance of both the NiMoN@NiFeN and NiMoN catalysts, we further investigated the overall seawater splitting performance by integrating the two catalysts into a two-electrode alkaline electrolyzer (without a diaphragm or membrane), in which NiMoN@NiFeN is used as the anode for OER and NiMoN as the cathode for HER (Fig. 4a). Remarkably, this electrolyzer shows excellent overall seawater splitting activity in both the alkaline simulated and natural seawater electrolytes. As displayed in Fig. 4b, at room temperature $(25^{\\circ}\\mathrm{C})$ , the cell voltages needed to produce a current density of $100\\mathrm{mA}\\mathrm{cm}^{-2}$ are as low as 1.564 and $1.581\\mathrm{V}$ in $1\\mathrm{M}\\ \\mathrm{KOH}+0.5\\mathrm{M}\\ \\mathrm{NaCl}$ and $1\\mathrm{M}\\mathrm{\\KOH+Sea}.$ 一 water electrolytes, respectively. In particular, our electrolyzer can generate extremely large current densities of 500 and $1000\\mathrm{\\dot{m}A c m}^{-2}$ at 1.735 and $1.841\\mathrm{V}$ , respectively, in $1\\mathrm{M}\\mathrm{KOH+}$ $0.5\\mathrm{M}\\mathrm{NaCl}$ electrolyte, which is slightly better than the recently reported anion exchange membrane (AEM) based electrolyzer in an alkaline simulated seawater electrolyte44. Even in the alkaline natural seawater, the cell voltages for the corresponding current densities are only 1.774 and $\\mathrm{\\bar{1.901\\mathrm{V}}}$ . Such performance even outperforms that of most non-noble metal catalysts for alkaline freshwater splitting, as well as that of the benchmark of $\\mathrm{Pt/C}$ and $\\mathrm{IrO}_{2}$ catalysts in $1\\mathrm{M}\\mathrm{KOH}^{15}$ . To boost the industrial applications of this electrolyzer, the cell voltages are further decreased to 1.454, 1.608, and $1.709\\mathrm{V}$ for current densities of 100, 500, and $1000\\mathrm{mAcm}^{-2}$ , respectively, in 1 $\\mathrm{\\Delta}\\mathrm{M}\\mathrm{\\KOH}+\\mathrm{\\Delta}\\mathrm{S}$ eawater electrolyte by heating the electrolyte to $60^{\\circ}\\mathrm{C},$ which can be easily achieved by employing a solar thermal hot water system. These values represent the current record-high performance indices for overall alkaline seawater splitting. The overall seawater splitting performance without iR compensation was also tested in 1 M $\\mathrm{\\bar{\\KOH}+}$ Seawater at $25^{\\circ}\\mathrm{C}$ for comparison (Supplementary Fig. 19), and was found to be worse than that with iR compensation. We attempted to split pure natural seawater as well, but the performance is unsatisfactory due to the low ionic conductivity and strong corrosiveness of the natural seawater (Supplementary Fig. 20). We then evaluated the Faradaic efficiency of the electrolyzer in 1 M $\\mathrm{KOH}+0.5\\mathrm{M}$ NaCl at room temperature by collecting the evolved gaseous products over the cathode and anode (Supplementary Fig. 21). As shown in Fig. $\\begin{array}{r l}{{4}\\boldsymbol{c}.}&{{}}\\end{array}$ , only $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ gases with a molar ratio close to 2:1 are detected, and the Faradaic efficiency is determined to be around $97.8\\%$ during seawater electrolysis, demonstrating the high selectivity of OER on the anode. \n\nThe operating durability is also a very important metric to assess the performance of an electrolyzer. As shown in Fig. 4d, this electrolyzer can retain outstanding overall seawater splitting performance with no noticeable degradation over $\\boldsymbol{100}\\mathrm{h}$ operation at a constant current density of $10\\mathrm{0}\\mathrm{mA}\\mathrm{cm}^{-2}$ in both the alkaline simulated and natural seawater electrolytes. More importantly, the voltage needed to achieve a very large current density of $500\\mathrm{mA}\\mathrm{c}\\mathrm{\\bar{m}}^{-2}$ also shows very little increase $(<10\\%)$ after $\\dot{100}\\mathrm{h}$ water electrolysis in either of the two electrolytes (Fig. 4d), verifying the superior durability of this electrolyzer. The anode of the NiMoN $@$ NiFeN catalyst further demonstrates good structural integrity after long-term seawater electrolysis (Supplementary Fig. 22). In addition, the electrolyzer exhibits very good activity and stability (over $600\\mathrm{h}$ electrolysis) for overall seawater splitting in a very harsh condition of 6 M $\\mathrm{1\\KOH+\\leq}$ eawater (Supplementary Fig. 23), demonstrating its great potential for large-scale applications. Given its excellent catalytic performance, this electrolyzer can be easily actuated by a $1.5\\mathrm{V}$ AA battery (Supplementary Fig. 24). Moreover, we also demonstrated the harvesting of waste heat, the major energy loss in various activities and device operations, by our seawater electrolyzer powered with a commercial TE device that directly coverts heat into electricity (Fig. 4e)45. As shown in Fig. 4f, when the temperature gradient between the hot and cold sides of the TE module is 40, 50, and $60^{\\circ}\\mathrm{C},$ the corresponding output voltage can expeditiously drive the electrolyzer for stable delivery of current density of 30, 100, and $200\\mathrm{mAcm}^{-2}$ , respectively. Even when the temperature gradient through the TE module is decreased to $40^{\\circ}\\mathrm{C},$ the electrolyzer can still supply a current density of ${\\sim}30\\mathrm{mAcm}^{-2}$ with good recyclability, suggesting that we can efficiently use the waste heat to produce $\\mathrm{H}_{2}$ fuel by the electrolysis of seawater. \n\nActive sites for oxygen evolution catalysis. To gain a deeper insight into the real catalytic active sites for the extraordinary OER activity of the NiMoN $@$ NiFeN catalyst, we further studied its nanostructure, surface composition, and chemical state during and after OER tests. The TEM image in Fig. 5a shows that the 3D core-shell nanostructure of NiMoN $@$ NiFeN is intact after OER tests, which is consistent with the SEM results (Supplementary \n\n![](images/25116f0370f49f2a3ab10473804b13fc7c09d0633d7b9d58178c10c77bdf3bd1.jpg) \nFig. 4 Overall seawater splitting performance. a Schematic illustration of an overall seawater splitting electrolyzer with NiMoN and NiMoN $@$ NiFeN as the cathode and anode, respectively. b Polarization curves after iR compensation of NiMoN and NiMoN@NiFeN coupled catalysts in a two-electrode electrolyzer tested in alkaline simulated ( $1\\mathsf{M}\\mathsf{K O H}+0.5\\mathsf{M}\\mathsf{N a C l},$ , resistance: ${\\sim}1.1\\Omega^{\\cdot}$ ) and natural seawater ( $\\mathrm{?}1\\mathsf{M}\\mathsf{K O H+}\\mathrm{:}$ Seawater, resistance: ${\\sim}1.2\\Omega,$ electrolytes under different temperatures. c Comparison between the amount of collected and theoretical gaseous products $(H_{2}$ and $|\\boldsymbol{\\mathrm{O}}_{2}\\rangle$ ) by the twoelectrode electrolyzer at a constant current density of $100\\mathsf{m A c m}^{-2}$ in 1 $\\mathsf{M K O H}+0.5\\mathsf{M N a C l}$ at $25^{\\circ}\\mathsf{C}$ . d Durability tests of the electrolyzer at constant current densities of 100 and $500\\mathsf{m A c m}^{-2}$ in different electrolytes at $25^{\\circ}\\mathsf{C}$ . e Schematic illustration of the principle for power generation between the hot and cold sides of a TE device. f Real-time dynamics of current densities for the electrolyzer in 1 $\\mathsf{M K O H+O.F M N a}$ Cl at $25^{\\circ}\\mathsf{C}$ driven by a TE device when the temperature gradient $(\\Delta T)$ between its hot and cold sides is 40, 50, 60, and $40^{\\circ}\\mathsf{C}$ \n\nFig. 11). The TEM image in Fig. 5b reveals that many nanoparticles are closely attached on the nanorod, and there seems to be some very thin layers on the nanoparticle surface. The HRTEM image in Fig. 5c confirms the existence of thin amorphous layers and $\\mathrm{Ni(OH)}_{2}$ . We suspect that the thin layers are in situ generated amorphous NiFe oxides and NiFe oxy(hydroxides), which have been verified by elemental mapping and XPS analyses following OER testing. Figure 5d displays the DF-STEM and corresponding elemental mapping images, which show the absence of N and the increased O content on the NiMoN $@$ NiFeN surface after OER due to the intense oxidation process. The highresolution XPS of N 1s (Supplementary Fig. 25) also corroborates this point (the surface $\\mathrm{\\DeltaN}$ content in the NiMoN $@$ NiFeN catalyst was reduced from $10.3\\%$ in the fresh sample to $0.36\\%$ after OER). For the high-resolution XPS of $\\mathrm{Ni}~2\\mathrm{p}$ (Fig. 5e), the two peaks attributed to Ni-N species at 853.4 and $870.8\\mathrm{eV}$ also disappear after OER because of surface oxidation. A new peak at $868.9\\mathrm{eV}$ , which is assigned to $\\mathrm{Ni(OH)}_{2}$ , shows up,. Besides, the two peaks at 856.3 (Ni-O) and $862.0\\mathrm{eV}$ (Sat.) positively shift toward higher binding energy, which is also observed in the XPS of Fe $2\\mathrm{p}$ (Fig. 5f), indicating the oxidation of $\\mathrm{Ni}^{2+}$ and $\\mathrm{Fe}^{2+}$ to the higher valence states of $\\mathrm{Ni}^{3+}$ and $\\mathrm{Fe}^{3+}$ (Supplementary Fig. 26), respectively, resulting from the formation of NiFe oxides/oxy (hydroxides)46–48. The O 1s XPS (Supplementary Fig. 27) also proves the increased valence states of $\\bar{\\mathrm{Ni}}^{2+}$ and $\\mathrm{Fe}^{2+}$ after OER, as well as showing the appearance of Fe-OH from the NiFe oxy (hydroxides), which can be seen from the negative shift of the main peaks at 531.9 and $530.1\\mathrm{eV}$ and the appearance of a new peak at $532.3\\mathrm{eV}^{49}$ . To confirm the formation of NiFe oxides/oxy (hydroxides), we further performed in situ Raman measurements (Supplementary Fig. 28) to elucidate the real-time evolution of the NiMoN@NiFeN catalyst during the OER process. As the results in Fig. 5g show, the spectrum for the as-prepared NiMoN $@$ NiFeN exhibits a sharp and broad peak at around $80.3\\mathrm{cm}^{-1}$ , which is probably due to the metal- $.\\mathrm{\\DeltaN}$ stretching modes. The transformation into NiOOH starts at $1.4\\mathrm{V}$ according to a new Raman band located at $480.1\\mathrm{cm}^{-1}$ 12. When the potential reaches to 1.6 and $1.7\\mathrm{V}$ , two additional Raman bands are generated. The one located at $324.7\\mathrm{cm}^{-1}$ is assigned to the Fe-O vibrations in $\\mathrm{Fe}_{2}\\mathrm{O}_{3}{}^{50}$ , and the other at $693.1\\mathrm{cm}^{-1}$ belongs to the Fe-O vibrations in amorphous $\\mathrm{FeOOH^{51}}$ . Therefore, by combining these results with the XPS results, we conclude that thin amorphous layers of NiFe oxide and NiFe oxy(hydroxide) are evolved from the NiFeN nanoparticles at the surface during OER electrocatalysis, and that these serve as the real active sites participating in the OER process. The formation of a metal nitride-metal oxide/oxy(hydroxide) core-shell structure may also facilitate electron transfer from the NiFeN core to the oxidized species (Supplementary Fig. 29). This observation is consistent with the results of other reported OER catalysts, including metal selenides and phosphides14,46. However, the structure of the in situ formed NiFe oxides/oxy(hydroxides) is different from that of the (Ni,Fe)OOH thin-film catalyst reported by Zhou et al.12, which undergoes a rapid self-reconstruction due to the partial dissolution of FeOOH in KOH solution, forming amorphous NiOOH nanoarrays mixed with a small amount of FeOOH nanoparticles after OER. Notably, such in situ generated amorphous NiFe oxide and NiFe oxy(hydroxide) layers also play a positive role in improving the resistance to corrosion by chloride anions in seawater (Supplementary Fig. 30), which contributes to the superior stability during seawater electrolysis. \n\n![](images/4660cf94945ba2007dd00dc469f0b6671478bd95039f4932afa0d98d5571f0f7.jpg) \nFig. 5 Material characterization to study the OER active sites. a, b TEM images of NiMoN $@$ NiFeN core-shell nanorods at different magnifications after OER tests. c HRTEM image, and d DF-STEM image and corresponding elemental mapping of the NiMoN $@$ NiFeN catalyst after OER tests. Scale bars: a $500\\mathsf{n m}$ ; b $50\\mathsf{n m}$ ; $\\bullet5\\mathsf{n m}$ ; ${\\mathsf{\\mathbf{d}}}1\\upmu\\mathrm{\\mathrm{m}}$ . High-resolution XPS of (e), Ni 2p and $(\\pmb{\\upuparrow})_{i}$ , Fe 2p of NiMoN $@$ NiFeN after OER tests in comparison with those before OER tests. g In situ Raman spectra of the NiMoN@NiFeN catalyst at various potentials for the OER process \n\n# Discussion \n\nIn summary, we have developed a 3D core-shell OER catalyst of NiMoN@NiFeN for active and stable alkaline seawater splitting. The interior NiMoN nanorods are highly conductive and afford a large surface area, which ensure efficient charge transfer and numerous active sites. The outer NiFeN nanoparticles in situ evolve thin amorphous layers of NiFe oxide and NiFe oxy(hydroxide) during OER catalysis, which are not only responsible for the selective OER activity, but also beneficial for the corrosion resistance to chloride anions in seawater. At the same time, the 3D coreshell nanostructures with multiple levels of porosity are favorable for seawater diffusion and $\\mathrm{H}_{2}/\\mathrm{O}_{2}$ gases releasing. Thus, this OER catalyst requires very low overpotentials of 369 and $398\\mathrm{mV}$ to deliver large current densities of 500 and $1000\\mathrm{mAcm}^{-2}$ , respectively, in alkaline natural seawater at $25^{\\circ}\\mathrm{C}.$ Additionally, by pairing it with another efficient HER catalyst of NiMoN, we assembled an outstanding water electrolyzer for overall seawater splitting, which outputs current densities of 500 and $1000\\mathrm{mAcm}^{-2}$ at record low voltages of 1.608 and $1.709{\\mathrm{V}}$ , respectively, in alkaline natural seawater at $60^{\\circ}\\mathrm{C}.$ . The electrolyzer also shows excellent durability at current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ during up to $\\boldsymbol{100}\\mathrm{h}$ alkaline seawater electrolysis. This discovery represents a significant step in the development of a robust and active catalyst to utilize the world’s abundant seawater feedstock for large-scale hydrogen production by renewable energy sources. \n\n# Methods \n\nChemicals. Ethanol $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ , Decon Labs, Inc.), ammonium heptmolybdate $[\\mathrm{(NH_{4})_{6}M o_{7}O_{24}{\\cdot}4H_{2}O},$ $98\\%$ , Sigma-Aldrich], nickel(II) nitrate hexahydrate (Ni $(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ , $98\\%$ , Sigma-Aldrich), iron (III) nitrate hexahydrate (Fe $(\\mathrm{NO}_{3})_{3}{\\cdot}9\\mathrm{H}_{2}\\mathrm{O}$ , $98\\%$ , Sigma-Aldrich), N, N Dimethylformamide [DMF, $(\\mathrm{CH}_{3})_{2}\\mathrm{NC}$ $(\\mathrm{O})\\mathrm{H}$ anhydrous, $99.8\\%$ , Sigma-Aldrich], platinum powder (Pt, nominally $20\\%$ on carbon black, Alfa Aesar), iridium oxide powder (IrO2, $99\\%$ , Alfa Aesar), Nafion (117 solution, $5\\%$ wt, Sigma-Aldrich), sodium chloride (NaCl, Fisher Chemical), potassium hydroxide (KOH, $50\\%$ w/v, Alfa Aesar), and Ni foam (thickness: $1.6\\mathrm{mm}$ , porosity: ${\\sim}95\\%$ ) were used as received. Deionized (DI) water (resistivity: $18.3\\ \\mathrm{M}\\Omega\\cdot\\mathrm{cm},$ was used for the preparation of all aqueous solutions. \n\nSynthesis of $N i N a O_{4}$ nanorods on Ni foam. $\\mathrm{NiMoO_{4}}$ nanorods were synthesized on nickel foam through a hydrothermal method52. A piece of commercial Ni foam $(2\\times5\\mathrm{cm}^{2})$ was cleaned by ultrasonication with ethanol and DI water for several minutes, and the substrate was then transferred into a polyphenyl (PPL)-lined stainless-steel autoclave $(100\\mathrm{ml})$ containing a homogenous solution of Ni $(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ $(0.04\\mathrm{M})$ and $(\\mathrm{NH_{4}})_{6}\\mathrm{Mo}_{7}\\mathrm{O}_{24}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ $(0.01{\\mathrm{M}})$ in $50\\mathrm{ml}\\mathrm{H}_{2}\\mathrm{O}$ . Afterward, the autoclave was sealed and maintained at $150^{\\circ}\\mathrm{C}$ for $^{6\\mathrm{h}}$ . The sample was then taken out and washed with DI water and ethanol several times before being fully dried at $60~^{\\circ}\\mathrm{C}$ overnight under vacuum. \n\nSynthesis of NiMoN@NiFeN core-shell nanorods. The metal nitrides were synthesized by one-step nitridation of the $\\mathrm{NiMoO_{4}}$ nanorods in a tube furnace. For the synthesis of NiMoN nanorods, a piece of $\\mathrm{NiMoO_{4}/N i}$ foam $(\\sim1\\mathrm{cm}^{2})$ was placed at the middle of a tube furnace and thermal nitridation was conducted at $500^{\\circ}\\mathrm{C}$ under a flow of 120 standard cubic centimeters (sccm) $\\mathrm{NH}_{3}$ and 30 sccm Ar for $^{\\textrm{1h}}$ . The furnace was then automatically turned off and naturally cooled down to room temperature under Ar atmosphere. For the synthesis of NiMoN $@$ NiFeN core-shell nanorods, a piece of $\\mathrm{NiMoO_{4}/N i}$ foam $(\\sim1\\mathrm{{cm}}^{2})$ was first soaked in a NiFe precursor ink, which was prepared by dissolving $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ and Fe $(\\mathrm{NO}_{3})_{3}{\\cdot}9\\mathrm{H}_{2}\\mathrm{O}$ with a mole ratio of 1:1 in DMF, and the $\\mathrm{NiMoO_{4}/N i}$ foam coated with the NiFe precursor ink was then dried at ambient condition. The dried sample was subjected to thermal nitridation under the same conditions as for NiMoN. To study the effect of the NiFeN loading amount on the morphology of the core-shell nanorods, we prepared four different NiMoN $@$ NiFeN core-shell nanorods with different loading amounts of NiFeN by controlling the concentration of Ni and Fe precursors. Specifically, 0.1, 0.25, 0.5, and $0.75\\mathrm{g}\\mathrm{\\bar{ml}}^{-1}$ concentrations of precursor ink were used. For comparison, pure NiFeN nanoparticles were also prepared on the Ni foam by replacing the $\\mathrm{NiMoO_{4}/N i}$ foam with Ni foam. The concentration of precursor ink in this case was $0.25\\mathrm{g}\\mathrm{ml}^{-1}$ , and all other synthesis conditions were the same as for NiMoN $@$ NiFeN. \n\nPreparation of $\\mathbf{lrO}_{2}$ and Pt/C catalysts on Ni foam. To prepare the $\\mathrm{IrO}_{2}$ electrode for comparison53, $40\\mathrm{mg}$ of $\\mathrm{IrO}_{2}$ and $60\\upmu\\mathrm{L}$ of Nafion were dispersed in ${\\ }540\\upmu\\mathrm{L}$ of ethanol and $400\\upmu\\mathrm{L}$ of DI water, and the mixture was ultrasonicated for $30\\mathrm{min}$ . The dispersion was then coated onto a Ni foam substrate, which was dried in air overnight. $\\mathrm{Pt/C}$ electrodes were obtained by the same method. \n\nMaterials characterization. The morphology and nanostructure of the samples were determined by scanning electron microscopy (SEM, LEO 1525) and transmission electron microscopy (TEM, JEOL 2010F) coupled with energy dispersive X-ray (EDX) spectroscopy. The phase composition of the samples was characterized by X-ray diffraction (PANalytical X’pert PRO diffractometer with a $\\mathrm{{Cu}\\ K a}$ radiation source) and XPS (PHI Quantera XPS) using a PHI Quantera SXM scanning X-ray microprobe. \n\nElectrochemical tests. The electrochemical performance was tested on an electrochemical station (Gamry, Reference 600). The two half reactions of OER and HER were each carried out at room temperature $({\\sim}25^{\\circ}\\mathrm{C})$ in a standard threeelectrode system with our prepared sample as the working electrode, a graphite rod as the counter electrode, and a standard $\\mathrm{Hg/HgO}$ electrode as the reference electrode. Four different electrolytes, including 1 M KOH, 1 $\\mathrm{M\\KOH{+}0.5M\\ N a C l}$ $1\\mathrm{M}\\mathrm{KOH+}$ Seawater, and natural seawater, were used, and the pH was around 14 except for the natural seawater (pH\\~7.2). The electrode size is around $1{\\mathrm{cm}}^{-2}$ , and the effective parts in the electrolyte are $0.3\\sim0.45\\mathrm{cm}^{-2}$ for different samples. Both the anodes $(\\mathrm{NiMoN}@\\mathrm{NiFeN})$ and cathodes (NiMoN) were cycled ${\\sim}100$ times by CV until a stable polarization curve was developed prior to measuring each polarization curve. OER polarization curve measurements were performed by CV at a scan rate of $2\\mathrm{mVs^{-1}}$ and stability tests were carried out under constant overpotentials. HER polarization curve measurements were performed by linear sweep voltammetry (LSV) at a scan rate of $5\\mathrm{mVs^{-1}}$ and stability tests were carried out under constant overpotentials. Electrochemical impedance spectra (EIS) were measured at an overpotential of $270\\mathrm{mV}$ from $0.1\\mathrm{Hz}$ to $100\\mathrm{KHz}$ with an amplitude of $10\\mathrm{mV}$ . For the two-electrode seawater electrolysis, the as-prepared NiMoN $\\varrho$ NiFeN and NiMoN catalysts (after CV activation) were used as the anode and cathode, respectively. The polarization curves were measured in different electrolytes at different temperatures (25 and $60^{\\circ}\\mathrm{C})$ , and stability tests were carried out under constant current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ at room temperature. \n\nTurnover frequency (TOF) calculation. The TOF value is calculated from the Eq. (1)54,55: \n\n$$\n\\mathrm{TOF}=\\frac{j*A*\\eta}{4*F*n}\n$$ \n\nwhere $j$ is the current density at a given overpotential, $A$ is the surface area of the electrode, $\\eta$ is the OER Faradaic efficiency, $F$ is the Faraday constant, and $n$ is the total number of active sites on the electrode. To calculate TOF, the most significant challenge is to identify the number of active sites. Since the real active sites for the NiMoN $@$ NiFeN catalyst are in situ formed NiFe oxide and NiFe oxy(hydroxide), we calculated the number of active sites by integrating the Ni redox peaks from the CV curve according to the following Eq. $(2)^{55}$ : \n\n$$\nn={\\frac{Q*N_{A}}{F*R_{\\mathrm{{Ni}/\\mathrm{{Fe}}}}}}\n$$ \n\nwhere $Q$ is the integration of Ni redox features from the CV curve (Supplementary Fig. 9d), $N_{A}$ is Avogadro’s constant, $F$ is the Faraday constant, and $R_{\\mathrm{Ni/Fe}}$ is the molar ratio of $\\mathrm{Ni}/\\mathrm{Fe}_{;}$ , assuming that $\\mathrm{Ni}^{2+}/\\mathrm{Ni}^{3+}$ is a one-electron process. For the NiMoN $@$ NiFeN catalyst at overpotential of $300\\mathrm{mV}$ , $j=206\\mathrm{mA}\\mathrm{\\bar{c}m}^{-2}$ , and thus TOF was calculated to be $0.09{\\mathrm{~}}{\\mathrm{s}}^{-1}$ at overpotential of $300\\mathrm{mV}$ . \n\nGas chromatography measurement. Overall seawater splitting for gas chromatography (GC, GOW-MAC 350 TCD) tests were performed in a gas-tight electrochemical cell with $1\\mathrm{M}\\mathrm{KOH}+0.5\\mathrm{M}\\mathrm{NaCl}$ as the electrolyte at room temperature $(25^{\\circ}\\mathrm{C})$ . Chronopotentiometry was applied with a constant current density of $100\\mathrm{mA}\\mathrm{cm}^{-2}$ to maintain oxygen and hydrogen generation. For each measurement over an interval of $10\\mathrm{min}$ , $0.3\\upmu\\mathrm{L}$ gas sample was carefully extracted from the sealed cell and injected into the GC instrument using a glass syringe (Hamilton Gastight 1002). \n\nOverall seawater splitting driven by a TE module. We purchased a commercial TE module from Amazon and used it as a power generator to drive our twoelectrode electrolyzer according to our previous work12. During the test, the hot side of the TE module was covered by a large flat copper plate, which was in direct contact with a heater on top. The hot-side temperature was maintained relatively constant by tuning the DC power supply to the heater, while the cold-side temperature was controlled by placing it in direct contact with a cooling system, where the water inside was adjusted to remain at a constant temperature. Thus, the TE module generated a relatively stable open circuit voltage between the hot and cold sides. A nano-voltmeter and an ammeter were embedded into the circuit for realtime monitoring of the voltage and current, respectively, between the two electrodes of the water-splitting cell. \n\n# Data availability \n\nThe source data underlying Figs. 1i, 2a–f, 3c, f and h, 4c and f, $5\\mathrm{e-g},$ and Supplementary Figs. 2a, 6, 12, 20, 21a, 23a, 25, 26, and 27 are provided as a Source Data file. The other data that support the findings of this work are available from the corresponding authors upon reasonable request. \n\n# Code availability \n\nAll plots and data analysis were performed with OriginPro 8.5 software, and will be made available by the corresponding authors upon reasonable request. \n\nReceived: 18 June 2019; Accepted: 18 October 2019; Published online: 08 November 2019 \n\n# References \n\n1. Tiwari, J. N. et al. Multicomponent electrocatalyst with ultralow Pt loading and high hydrogen evolution activity. Nat. Energy 3, 773 (2018). \n2. Turner, J. A. Sustainable hydrogen production. Science 305, 972–974 (2004). \n3. Cabán-Acevedo, M. et al. Efficient hydrogen evolution catalysis using ternary pyrite-type cobalt phosphosulphide. Nat. Mater. 14, 1245 (2015). \n4. Luo, J. et al. Water photolysis at $12.3\\%$ efficiency via perovskite photovoltaics and earth-abundant catalysts. Science 345, 1593–1596 (2014). \n5. Pu, Z. et al. A universal synthesis strategy for P-rich noble metal diphosphide based electrocatalyst for hydrogen evolution reactions. Energy Environ. Sci. 12, 952–957 (2019). \n6. Roger, I., Shipman, M. A. & Symes, M. D. Earth-abundant catalysts for electrochemical and photoelectrochemical water splitting. Nat. Rev. Chem. 1, 0003 (2017). \n7. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: Insights into materials design. Science 355, eaad4998 (2017). \n8. Ledezma-Yanez, I. et al. Interfacial water reorganization as a pH-dependent descriptor of the hydrogen evolution rate on platinum electrodes. Nat. Energy 2, 17031 (2017). \n9. Ding, Q., Song, B., Xu, P. & Jin, S. Efficient electrocatalytic and photoelectrochemical hydrogen generation using $\\ensuremath{\\mathbf{MoS}}_{2}$ and related compounds. Chem 1, 699–726 (2016). \n10. Landman, A. et al. Photoelectrochemical water splitting in separate oxygen and hydrogen cells. Nat. Mater. 16, 646 (2017). \n11. Fabbri, E. et al. Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting. Nat. Mater. 16, 925 (2017). \n12. Zhou, H. et al. Water splitting by electrolysis at high current densities under 1.6 volts. Energy Environ. Sci. 11, 2858–2864 (2018). \n13. Hui, L. et al. Overall water splitting by graphdiyne-exfoliated andsandwiched layered double-hydroxide nanosheet arrays. Nat. Commun. 9, 5309 (2018). \n14. Yu, F. et al. High-performance bifunctional porous non-noble metal phosphide catalyst for overall water splitting. Nat. Commun. 9, 2551 (2018). \n15. Yu, L. et al. Cu nanowires shelled with NiFe layered double hydroxide nanosheets as bifunctional electrocatalysts for overall water splitting. Energy Environ. Sci. 10, 1820–1827 (2017). \n16. Dresp, S., Dionigi, F., Klingenhof, M. & Strasser, P. Direct electrolytic splitting of seawater: Opportunities and challenges. ACS Energy Lett. 4, 933–942 (2019). \n17. Hsu, S. H. et al. An earth‐abundant catalyst‐based seawater photoelectrolysis system with $17.9\\%$ solar‐to‐hydrogen efficiency. Adv. Mater. 30, 1707261 (2018). \n18. Kuang, Y. et al. Solar-driven, highly sustained splitting of seawater into hydrogen and oxygen fuels. Proc. Natl Acad. Sci. USA 116, 6624–6629 (2019). \n19. Dionigi, F., Reier, T., Pawolek, Z., Gliech, M. & Strasser, P. Design criteria, operating conditions, and nickel-iron hydroxide catalyst materials for selective seawater electrolysis. ChemSusChem 9, 962–972 (2016). \n20. Zhao, Y. et al. Charge state manipulation of cobalt selenide catalyst for overall seawater electrolysis. Adv. Energy Mater. 8, 1801926 (2018). \n21. Esswein, A. J., Surendranath, Y., Reece, S. Y. & Nocera, D. G. Highly active cobalt phosphate and borate based oxygen evolving catalysts operating in neutral and natural waters. Energy Environ. Sci. 4, 499–504 (2011). \n22. Zhang, Y. et al. 3D porous hierarchical nickel-molybdenum nitrides synthesized by RF plasma as highly active and stable hydrogen‐evolution‐ reaction electrocatalysts. Adv. Energy Mater. 6, 1600221 (2016). \n23. Song, F. et al. Interfacing nickel nitride and nickel boosts both electrocatalytic hydrogen evolution and oxidation reactions. Nat. Commun. 9, 4531 (2018). \n24. Wang, Y. et al. Self-supported NiMo-based nanowire arrays as bifunctional electrocatalysts for full water splitting. J. Mater. Chem. A 6, 8479–8487 (2018). \n25. Zhu, C. et al. Fe‐Ni‐Mo nitride porous nanotubes for full water splitting and Zn‐air batteries. Adv. Energy Mater. 8, 1802327 (2018). \n26. Feng, L.-L. et al. High-index faceted $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanosheet arrays as highly active and ultrastable electrocatalysts for water splitting. J. Am. Chem. Soc. 137, 14023–14026 (2015). \n27. Xiao, M. et al. Hollow nanostructures for photocatalysis: Advantages and challenges. Adv. Mater. 31, 1801369 (2018). \n28. Yu, L. et al. Ternary $\\mathrm{Ni}_{2(1-\\mathrm{x})}\\mathrm{Mo}_{2\\mathrm{x}}\\mathrm{P}$ nanowire arrays toward efficient and stable hydrogen evolution electrocatalysis under large-current-density. Nano Energy 53, 492–500 (2018). \n29. Qiu, B. et al. Fabrication of nickel-cobalt bimetal phosphide nanocages for enhanced oxygen evolution catalysis. Adv. Funct. Mater. 28, 1706008 (2018). \n30. Wang, T. et al. NiFe (oxy) hydroxides derived from NiFe disulfides as an efficient oxygen evolution catalyst for rechargeable Zn-air batteries: the effect of surface S residues. Adv. Mater. 30, 1800757 (2018). \n31. Wu, A. et al. Integrating the active OER and HER components as the heterostructures for the efficient overall water splitting. Nano Energy 44, 353–363 (2018). \n32. Yan, H. et al. Anion‐modulated HER and OER activities of 3D Ni-V‐based interstitial compound heterojunctions for high‐efficiency and stable overall water splitting. Adv. Mater. 31, 1901174 (2019). \n33. Huang, Z.-F. et al. Chemical and structural origin of lattice oxygen oxidation in Co-Zn oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). \n34. Niu, S. et al. Se-doping activates FeOOH for cost-effective and efficient electrochemical water oxidation. J. Am. Chem. Soc. 141, 7005–7013 (2019). \n35. Qian, Q., Li, Y., Liu, Y., Yu, L. & Zhang, G. Ambient fast synthesis and active sites deciphering of hierarchical foam‐like trimetal-organic framework nanostructures as a platform for highly efficient oxygen evolution electrocatalysis. Adv. Mater. 31, 1901139 (2019). \n36. Wei, Y.-S. et al. A single-crystal open-capsule metal-organic framework. J. Am. Chem. Soc. 141, 7906–7916 (2019). \n37. Ye, S. H., Shi, Z. X., Feng, J. X., Tong, Y. X. & Li, G. R. Activating CoOOH porous nanosheet arrays by partial iron substitution for efficient oxygen evolution reaction. Angew. Chem. Int. Ed. 57, 2672–2676 (2018). \n38. Liang, H. et al. Amorphous NiFe-OH/NiFeP electrocatalyst fabricated at low temperature for water oxidation applications. ACS Energy Lett. 2, 1035–1042 (2017). \n39. Gao, S. et al. Partially oxidized atomic cobalt layers for carbon dioxide electroreduction to liquid fuel. Nature 529, 68 (2016). \n40. Zhang, J., Zhao, Z., Xia, Z. & Dai, L. A metal-free bifunctional electrocatalyst for oxygen reduction and oxygen evolution reactions. Nat. Nanotech. 10, 444 (2015). \n41. Yu, F. et al. Recent developments in earth-abundant and non-noble electrocatalysts for water electrolysis. Mater. Today Phys. 7, 121–138 (2018). \n42. Chang, B. et al. Bimetallic NiMoN nanowires with a preferential reactive facet: An ultraefficient bifunctional electrocatalyst for overall water splitting. ChemSusChem 11, 3198–3207 (2018). \n43. Jia, J. et al. Nickel molybdenum nitride nanorods grown on Ni foam as efficient and stable bifunctional electrocatalysts for overall water splitting. ACS Appl. Mater. Interfaces 10, 30400–30408 (2018). \n44. Dresp, S. et al. Direct electrolytic splitting of seawater: activity, selectivity, degradation, and recovery studied from the molecular catalyst structure to the electrolyzer cell level. Adv. Energy Mater. 8, 1800338 (2018). \n45. He, J. & Tritt, T. M. Advances in thermoelectric materials research: looking back and moving forward. Science 357, eaak9997 (2017). \n46. Xu, X., Song, F. & Hu, X. A nickel iron diselenide-derived efficient oxygenevolution catalyst. Nat. Commun. 7, 12324 (2016). \n47. He, Q. et al. Highly defective Fe-based oxyhydroxides from electrochemical reconstruction for efficient oxygen evolution catalysis. ACS Energy Lett. 3, 861–868 (2018). \n48. Hu, C. et al. Synergism of geometric construction and electronic regulation: \n3D Se‐(NiCo) $\\mathrm{S_{x}/(O H)_{x}}$ nanosheets for highly efficient overall water splitting. Adv. Mater. 30, 1705538 (2018). \n49. Zhou, H. et al. Highly active catalyst derived from a 3D foam of $\\mathrm{Fe}(\\mathrm{PO}_{3})_{2}/$ ${\\mathrm{Ni}}_{2}{\\mathrm{P}}$ for extremely efficient water oxidation. Proc. Natl Acad. Sci. USA 114, \n5607–5611 (2017). \n50. Song, F. et al. An unconventional iron nickel catalyst for the oxygen evolution reaction. ACS Cent. Sci. 5, 558–568 (2019). \n51. Chemelewski, W. D., Lee, H.-C., Lin, J.-F., Bard, A. J. & Mullins, C. B. Amorphous FeOOH oxygen evolution reaction catalyst for photoelectrochemical water splitting. J. Am. Chem. Soc. 136, 2843–2850 (2014). \n52. Zhang, J. et al. Efficient hydrogen production on $\\mathrm{MoNi_{4}}$ electrocatalysts with fast water dissociation kinetics. Nat. Commun. 8, 15437 (2017). \n53. Yu, F. et al. Three-dimensional nanoporous iron nitride film as an efficient electrocatalyst for water oxidation. ACS Catal. 7, 2052–2057 (2017). \n54. Song, F. & Hu, X. Exfoliation of layered double hydroxides for enhanced oxygen evolution catalysis. Nat. Commun. 5, 4477 (2014). \n55. Zhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n\n# Acknowledgements \n\nThe work performed in China is financially supported by the National Natural Science Foundation of China (Nos. 21573085 and 51872108), the Wuhan Planning Project of Science and Technology (No. 2018010401011294), and self-determined research funds of CCNU from the college’s basic research and operation through the Chinese Ministry of Education (No. CCNU18TS034). J.B. acknowledges the support from the Robert A. Welch Foundation (E-1728). Z.R. acknowledges the Research Award from the Alexander von Humboldt Foundation and Prof. Kornelius Nielsch at IFW Dresden Germany. \n\n# Author contributions \n\nZ.F.R. and Y.Y. led the project. L.Y. designed and performed most of the experiments and analyzed most of the data including material synthesis, characterization, and electrochemical tests. Q.Z. carried out the thermoelectric measurements. S.W.S. performed the XPS characterization. B.M. and D.Z.W. took the TEM images. Z.J.Q. and J.M.B. performed the in situ Raman tests. C.Z.W. and J.M.B. performed the GC tests. L.Y., S.C., Y. Y., and Z.F.R. wrote the paper. All of the authors have discussed the results and revised the paper together. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 019-13092-7. \n\nCorrespondence and requests for materials should be addressed to Y.Y., S.C. or Z.R \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contributions to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41467-019-10351-5", + "DOI": "10.1038/s41467-019-10351-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-10351-5", + "Relative Dir Path": "mds/10.1038_s41467-019-10351-5", + "Article Title": "Over 16% efficiency organic photovoltaic cells enabled by a chlorinated acceptor with increased open-circuit voltages", + "Authors": "Cui, Y; Yao, HF; Zhang, JQ; Zhang, T; Wang, YM; Hong, L; Xian, KH; Xu, BW; Zhang, SQ; Peng, J; Wei, ZX; Gao, F; Hou, JH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Broadening the optical absorption of organic photovoltaic (OPV) materials by enhancing the intramolecular push-pull effect is a general and effective method to improve the power conversion efficiencies of OPV cells. However, in terms of the electron acceptors, the most common molecular design strategy of halogenation usually results in down-shifted molecular energy levels, thereby leading to decreased open-circuit voltages in the devices. Herein, we report a chlorinated non-fullerene acceptor, which exhibits an extended optical absorption and meanwhile displays a higher voltage than its fluorinated counterpart in the devices. This unexpected phenomenon can be ascribed to the reduced non-radiative energy loss (0.206 eV). Due to the simultaneously improved short-circuit current density and open-circuit voltage, a high efficiency of 16.5% is achieved. This study demonstrates that finely tuning the OPV materials to reduce the bandgap-voltage offset has great potential for boosting the efficiency.", + "Times Cited, WoS Core": 906, + "Times Cited, All Databases": 911, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000470656800023", + "Markdown": "# Over 16% efficiency organic photovoltaic cells enabled by a chlorinated acceptor with increased open-circuit voltages \n\nYong Cui1,2, Huifeng Yao $\\textcircled{1}$ 1, Jianqi Zhang $\\textcircled{1}$ 3, Tao Zhang1, Yuming Wang4, Ling Hong1,2, Kaihu Xian1,2, Bowei $\\mathsf{X}\\mathsf{u}^{1},$ , Shaoqing Zhang1,5, Jing Peng6, Zhixiang Wei3, Feng Gao 4 & Jianhui Hou $\\textcircled{1}$ 1,2 \n\nBroadening the optical absorption of organic photovoltaic (OPV) materials by enhancing the intramolecular push-pull effect is a general and effective method to improve the power conversion efficiencies of OPV cells. However, in terms of the electron acceptors, the most common molecular design strategy of halogenation usually results in down-shifted molecular energy levels, thereby leading to decreased open-circuit voltages in the devices. Herein, we report a chlorinated non-fullerene acceptor, which exhibits an extended optical absorption and meanwhile displays a higher voltage than its fluorinated counterpart in the devices. This unexpected phenomenon can be ascribed to the reduced non-radiative energy loss (0.206 eV). Due to the simultaneously improved short-circuit current density and open-circuit voltage, a high efficiency of $16.5\\%$ is achieved. This study demonstrates that finely tuning the OPV materials to reduce the bandgap-voltage offset has great potential for boosting the efficiency. \n\nA s a promising solar energy-harvesting technology, organic photovoltaic (OPV) cells have advantages like light-weight, flexibility, transparency, and potential low costs1–3. In the last three decades, great efforts have been devoted to material design, device engineering, morphology optimization, and mechanism study, contributing to the increase in the power conversion efficiencies (PCEs) from solar energy to electricity $4{-}20$ . At present, although PCEs exceeding $15\\%$ have been achieved in single-junction OPV cells21,22, further improvement is still needed to compete with other photovoltaic technologies, such as silicon solar cells and perovskite solar cells. \n\nDesigning low bandgap materials to have a good match with the solar spectrum is a general method for improving the short-circuit current density $(J_{\\mathrm{SC}})$ and thereby the PCEs of OPV cells23–28. In the last few years, the development of low bandgap non-fullerene small molecular acceptors with acceptor–donor–acceptor structures has achieved great success29–33. Halogenation of electronaccepting units can enhance the intramolecular charge transfer (ICT) effects and reduce the bandgaps of non-fullerene small molecular acceptors, which has been demonstrated to be one of the most effective molecular design strategies34–36. To date, most of the top-performing acceptors, such as $\\Pi^{\\breve{-}4\\breve{\\Gamma}^{36}}$ , IEICO- $\\cdot4\\mathrm{F}^{37}$ , and BT-CIC13, contain fluorine or chlorine atoms. \n\nAs chlorination is easier in the synthesis and plays a more pronounced role in enhancing the ICT effect than fluorination does, it is more attractive for designing highly efficient OPV materials38–41. However, one of the biggest problems of chlorinated acceptors is that they usually exhibit downshifted lowest unoccupied molecular orbit (LUMO) levels, leading to reduced open-circuit voltages $(V_{\\mathrm{OC}}s)$ in the resulting OPV cells. For example, a $100\\mathrm{meV}$ downshift of the LUMO level and $40\\mathrm{nm}$ red-shift of the absorption spectrum were observed when the fluorine atoms in IT-4F were replaced by the chlorine atoms of $\\mathrm{IT-4Cl^{40}}$ . The IT-4Cl-based OPV cell yielded an increased $J_{\\mathrm{SC}}$ with significant sacrifice of $V_{\\mathrm{OC}}$ . As a result, the overall PCE is even decreased compared with that of the IT-4F-based device. These results pose a large challenge for broadening the optical absorption of chlorinated acceptors while maintaining high $V_{\\mathrm{OC}}s$ in the OPV cells. \n\nIn this work, we report a chlorinated low bandgap acceptor BTP-4Cl by replacing the halogen atoms of the fluorinated nonfullerene acceptor Y6 (herein named BTP-4F). The chlorinated acceptor BTP-4Cl shows a redshift of ca. $20\\mathrm{nm}$ in optical absorption and a ca. $100\\mathrm{meV}$ downshift of the LUMO level, which are easily understood by established molecular design theories13,40. In the OPV cells fabricated using the same polymer donor PBDB-TF, however, the BTP-4Cl-based device yields an even higher $V_{\\mathrm{OC}}$ of $0.867\\mathrm{V}$ compared with that of the BTP-4Fbased device $(0.834\\mathrm{V})$ . Detailed studies on blend films indicate that the BTP-4Cl-containing film has a higher electroluminescence quantum efficiency $(\\mathrm{EQE_{EL}})$ $(3.47\\times\\mathrm{\\bar{1}}0^{-4})$ than its BTP-4F counterpart $(1.40\\times10^{-4})$ , which indicates that there is a reduced non-radiative energy loss $(E_{\\mathrm{loss,nr}})$ of ${\\sim}24~\\mathrm{meV}$ that contributes to the improved $V_{\\mathrm{OC}}$ Benefiting from the simultaneously broader photo-response range and improved $V_{\\mathrm{OC}},$ we record high efficiencies of $16.5\\%$ and $15.3\\%$ with active areas of 0.09 and ${\\overline{{1}}}\\thinspace\\mathrm{cm}^{2}$ , respectively, which are among the top values for single-junction OPV cells. \n\n# Results \n\nMaterials design and theoretical calculations. In our previous work, we have demonstrated that chlorination has great potential for constructing OPV materials with superior performances compared to fluorination40. Very recently, Zou et al. reported a fluorinated non-fullerene small molecular acceptor Y6 and obtained an outstanding photovoltaic performance21, which motivates us to explore the applications of its chlorinated derivative in OPV cells. Figure 1a shows the molecular structures of the fluorine-containing and chlorine-containing non-fullerene acceptors and the used polymer donor PBDB-TF. As shown in Supplementary Fig. 1, the synthesis of BTP-4Cl is similar to BTP4F in the reported literature, where the chlorine-containing terminal group was used instead of the fluorine-containing unit21. BTP-4Cl can be dissolved in solvents like chloroform (CF) and chlorobenzene. The detailed synthesis procedure and characterization can be found in the experimental part in the Supplementary Methods. \n\nTo study the influence of the exchange of halogen atoms on the geometries and electrical properties, we performed molecular simulations using density functional theory with the B3LYP $(6-31G^{**})$ basis set, where the long alkyl side chains were simplified to methyl or ethyl groups to construct the molecular models. As displayed in Supplementary Fig. 2, the optimized molecular geometries and wavefunction distributions of the frontier orbitals including the highest occupied molecular orbits (HOMOs) and LUMOs show little difference between the two acceptors. It should be noted that from the fluorinated BTP-4F to chlorinated BTP-4Cl, the molecular energy levels of the HOMO $(-5.60$ to $-5.65\\mathrm{eV})$ and LUMO $(-3.55$ to $-3.63\\mathrm{eV})$ are downshifted. As the replacement of halogen atoms has a more pronounced impact on the LUMO level ( $\\mathrm{\\Delta\\Omega\\mathrm{meV}}$ , compared with $50\\mathrm{meV}$ for the HOMO level), the BTP-Cl displays a bandgap that is narrowed by $30\\mathrm{meV}$ compared to that of BTP-4F. These results are predictable according to the established molecular design theories, and lower $V_{\\mathrm{OC}}s$ are expected when applying the BTP-4Cl in OPV cells. \n\nUnlike the acceptors with centrosymmetric features (e.g. in the case of $\\mathrm{ITIC^{42}}.$ ), interestingly, the BTP-4X (X represents F or Cl) molecules possess axisymmetric structures. For ITIC and analogs, although they have strong ICT effects, the overall molecular dipole moments are extremely small37. As presented in Fig. 1b, in comparison, the molecular dipole moments are 0.8653 and 0.6882 Debye for BTP-4F and BTP-4Cl, respectively. Since the chlorine–carbon bond has a larger dipole moment than that of the fluorine–carbon bond, the dipole direction in BTP-4Cl is turned to the opposite of that in BTP-4F. Although it is hard to relate the dipole properties to the photovoltaic performance of OPV materials, there are studies that suggest large dipoles moments are beneficial for charge separation in donor:acceptor blends43 and are helpful for achieving fill factors (FFs) in the devices44. \n\nWe conducted calculations of the excited states of BTP-4X. Supplementary Figure 3 shows the charge density distributions of the lowest excited states, from which the Coulomb attractive energies between the electrons and holes are calculated to be 2.24 and $\\bar{2}.21\\mathrm{eV}$ for BTP-4F and BTP-4Cl, respectively. The reduced attractive energy in BTP-4Cl can be ascribed to the more delocalization of the charge density and may be beneficial for charge transfer in the donor:acceptor combinations with lowenergy offsets. Figure 1c shows the calculated absorption spectra of BTP-4X, where the main peak of BTP-4Cl is redshifted by $8\\mathrm{nm}$ from that of PTP-4F. The molar absorption coefficients of BTP-4X are almost the same $(1.05\\times10^{5}$ and $1.03\\times10^{5}\\mathrm{M}^{-1}\\mathrm{cm}^{-1}$ for BTP-4Cl and BTP-4F, respectively). \n\nOptical, electrochemical, and crystalline properties. We measured the ultraviolet–visible (UV–Vis) absorption spectra of BTP4X in diluted solutions and as thin films. As shown in Fig. 1d and Supplementary Fig. 4a, the main absorption peak was located at $732{\\mathrm{nm}}$ for BTP-4F, while that of BTP-4Cl redshifts by $14\\mathrm{nm}$ \n\n![](images/d90d2681b178dc2d458d8ca594c140cc0bb02919907c47cad53f0e15382dc3ac.jpg) \nFig. 1 Molecular structure, optical, and electrochemical properties. a Chemical structure of the BTP-4X acceptors and the polymer donor PBDB-TF. b Molecular dipoles in the optimized molecular models for the BTP-4X acceptors. c Calculated UV–Vis absorption spectra of the BTP-4X. d Normalized UV–vis absorption spectra of the donor and acceptors as thin films. e Schematic energy level alignment of the materials measured by the SWV method. f 2D GIWAXS patterns of the neat BTP-4X films. $\\pmb{\\mathscr{g}}$ Extracted 1D profiles along the IP and OOP directions \n\n$746\\mathrm{nm})$ . From solutions to films, significant redshifts of 84 and $93\\mathrm{nm}$ are observed for BTP-4F and BTP-4Cl, respectively, and the main absorption bands locate in the range of $600{-}900\\mathrm{nm}$ . The larger redshift in BTP-4Cl may be related to the stronger intermolecular $\\pi{-}\\pi$ packing caused by the larger atomic size of chlorine and larger length of the chlorine–carbon bond. The absorption coefficients are $9.90\\times10^{4}$ and $1.09\\times10^{5}\\mathrm{cm}^{-1}$ (Supplementary Fig. 4b) for the BTP-4F and BTP-4Cl films, respectively. The broader optical absorption range and higher absorption coefficient of BTP-4Cl are beneficial for the more effective utilization of the solar photon. \n\nWe measured the electrochemical energy levels of the BTP-4X films via the square-wave voltammetry (SWV) method, and the detailed current–voltage curves are plotted in Supplementary Fig. 5. BTP-4Cl shows downshifted HOMO (by $30\\mathrm{meV}.$ ) and LUMO (by $100\\mathrm{meV},$ ) levels compared to those of BTP-4F, resulting in an electrochemical bandgap that is narrowed by $70\\mathrm{meV}$ (Fig. 1e). We also performed ultraviolet photoelectron spectroscopy (UPS) measurements to compare with the SWV results. As provided in Supplementary Fig. 6, BTP-4Cl has a higher ionization potential (IP) of $5.55\\mathrm{eV}$ compared to BTP-4F $(5.48\\mathrm{eV})$ , which is consistent with the theoretical calculations. \n\nThe molecular packing properties of the acceptors were investigated by grazing-incidence wide-angle X-ray scattering (GIWAXS). From the two-dimensional (2D) patterns shown in \n\nFig. 1f, clear $\\pi{-}\\pi$ stacking (010) diffraction signals are observed in the out-of-plane (OOP) direction for both films, suggesting they have a preferential face-on orientations with respect to the substrate. In contrast, the peak in the BTP-4Cl film is more pronounced than that in the BTP-4F for similar film thicknesses, which may indicate a more orderly molecular packing structure. From the onedimensional (1D) profiles extracted along the OOP direction from the 2D patterns (Fig. 1g), the $\\pi{-}\\pi$ stacking distances are calculated to be around $3.60\\mathrm{\\AA}$ for the BTP-4X films. These crystalline results are consistent with our previous reports40. \n\nFrom fluorination to chlorination, the changes in the optical and electrochemical properties are highly consistent with the theoretical calculations and can be easily understood by the established molecular design theories for OPV materials. When applying the BTP-4Cl in solar cell devices, it is difficult to predict whether it will exhibit better PCEs than BTP-4F. However, higher $V_{\\mathrm{OC}}s$ are not expected because of the downshifted LUMO level. \n\nPhotovoltaic performance and charge dynamics. To study the photovoltaic performance of BTP-4X, we fabricated OPV cells with an inverted configuration of indium tin oxide $(\\mathrm{ITO})/\\mathrm{ZnO}$ nanoparticles/PBDB-TF:BTP- $\\mathrm{4X/MoO}_{3}/\\mathrm{Al}.$ where PBDB-TF was selected as the electron donor material. First, we measured the photoluminescence (PL) spectra of the neat and blend films to investigate the photo-induced charge transfer in the donor: acceptor blend films. As displayed in Supplementary Fig. 7, the fluorescence of PBDB-TF or BTP-4X can be thoroughly quenched by the presence of the other in the corresponding blend films, suggesting that there is efficient charge transfer between the PBDB-TF and BTP-4X. \n\n![](images/9f86205915bda591a50723d03bf673f0de77d4c574e4c825f9fbc2d47479be7e.jpg) \nFig. 2 Device performance. a $J-V$ curves of the PBDB-TF:IT-4X-based devices. b Statistical diagram of PCEs for 100 PBDB-T:BTP-4Cl-based cells. c $J{-}V$ curves of the devices measured by the NIM, China. d EQE curves of the PBDB-TF:BTP-4X blend cells. e Photo-CELIV curves of the devices for carrier mobility calculations. f Carrier lifetimes under varied light intensities obtained from TPV measurements \n\n
Table 1 Detailed photovoltaic parameters of the OPV cells
DevicesVoc (V)Jsc (mA cm-2)FFPCE (%)Area (cm²)
PBDB-TF:BTP-4F0.834 (0.833 ± 0.002)24.9 (24.8 ± 0.2)0.753 (0.741± 0.011)15.6 (15.3 ± 0.2)0.09
PBDB-TF:BTP-4CI0.867 (0.866 ±0.002)25.4 (25.2 ± 0.2)0.750 (0.737± 0.017)16.5 (16.1± 0.2)0.09
PBDB-TF:BTP-4CI0.859 (0.857± 0.002)25.0 (24.9 ± 0.3)0.713 (0.694± 0.024)15.3 (14.8 ± 0.3)1.00
\n\nThe average parameters were calculated from more than 30 independent cells \n\nTo obtain the best device performance, we carefully optimized the fabrication conditions, including the donor:acceptor ratio, additive, and thermal annealing temperature (Supplementary Table 1). Figure 2a shows the current density–voltage $\\left(J-V\\right)$ curves, and the detailed parameters are collected in Table 1. The PBDB-TF:BTP-4F-based device yields a good PCE of $15.6\\%$ , with a $V_{\\mathrm{OC}}$ of $0.834\\mathrm{V}$ , a $J_{\\mathrm{SC}}$ of $24.9\\mathrm{m}\\mathrm{\\dot{A}}\\mathrm{cm}^{-2}$ , and a FF of 0.753, which is close to value in the reported literature21. For the device based on BTP-4Cl as the acceptor, the $V_{\\mathrm{OC}}$ unexpectedly increase to $0.867\\mathrm{V}$ , which is $33\\mathrm{mV}$ higher than that of the BTP-4F-based device. The $J_{\\mathrm{SC}}$ and FF are $2{\\bar{5}}.4\\operatorname{mA}\\operatorname{cm}^{-2}$ and 0.750, respectively. Overall, an outstanding PCE of $16.5\\%$ is recorded for the PBDBTF:BTP-4Cl-based device, which represents the top result for single-junction OPV cells and is much higher than the results obtained by non-halogenated45 and fluorinated acceptors21. Figure 2b displays the statistical diagram of the efficiencies of 100 devices, and the average value reaches $16.1\\%$ . To carefully evaluate the high PCE, we sent the best device to the National Institute of Metrology, China (NIM) for certification and got a PCE of $15.83\\%$ (Fig. 2c and Supplementary Fig. 8). We fabricated the PBDB-TF:BTP-4Cl devices with varied active layer thicknesses from 70 to ${300}\\mathrm{nm}$ . As shown in Supplementary Fig. 9 and \n\nSupplementary Table 2, we can find that the devices can deliver above $14\\%$ PCEs from 100 to $250\\mathrm{nm}$ . \n\nThe photovoltaic performance discussed above is based on cells with a small active area of $9\\mathrm{mm}^{2}$ . As large-area fabrication of the OPV cells is of great significance for practical applications, we also fabricated PBDB-TF:BTP-4Cl devices with a $\\textstyle1\\cos^{2}$ area. As presented in the $J{-}V$ curve (the inset in Fig. 2a shows the real device) and summarized in Table 1, the device yields an impressive PCE of $15.3\\%$ . The result was also certified by NIM using a 0.807 $\\mathrm{cm}^{2}$ mask, and a PCE of $15.08\\%$ is recorded (Fig. 2c and Supplementary Fig. 8). We noted that the best results for the devices with similar areas were only around $12\\mathrm{-}13\\%$ in earlier published reports12,22. \n\nFigure 2d displays the external quantum efficiency (EQE) curves of the best cells. Both devices exhibit EQEs of over $75\\%$ in the range of $500{-}800\\mathrm{nm}$ , and the maximum EQE values are close to $85\\%$ . By comparison, the BTP-4Cl-containing device has a broader photo-response range by approximately $15\\mathrm{nm}$ than the device based on BTP-4F as the acceptor, which should be ascribed to the redshift of the optical absorption of BTP-4Cl. The integrated $J_{\\mathrm{SC}}s$ from the EQE spectra are calculated to be 24.7 and $25.3\\mathrm{mA}\\mathrm{cm}^{-2}$ , which are very close to the values obtained from $J{-}V$ measurements. \n\nWe measured the light intensity dependence of the $J{-}V$ characteristics to understand the recombination kinetics of the devices. As shown in Supplementary Fig. 10, by fitting the curves, we can find that both devices possess weak bimolecular and trapassisted recombination, which may be related to the efficient charge transport in the devices (Supplementary Table $3)^{46}$ . We measured the mobilities of the faster carrier components via photo-induced charger-carrier extraction in linearly increasing voltage (photoCELIV) measurements47. From the curves shown in Fig. 2e, the mobilities are calculated to be $7.45\\times10^{-5}$ and $1.82\\times10^{-{\\overline{{4}}}}\\mathrm{cm}^{2}$ $\\mathrm{V}^{-1}{\\mathsf{S}}^{-1}$ for the BTP-4F-containing and BTP-4Cl-containing cells, respectively. We subsequently conducted transient photovoltage (TPV) measurements to investigate the charge carrier lifetimes $(\\tau)$ . As shown in Fig. 2f, the results suggest that the PBDB-TF:BTP-4Clbased device exhibits a slightly longer $\\tau$ $(2.4\\upmu s)$ than the PBDB-TF: BTP-4F-based device $(1.5\\upmu s)$ , which may help to obtain the high $J_{\\mathrm{SC}}$ and FF of the device at such a low-energy $\\log s^{48,49}$ . \n\n![](images/596b74636b3dc6956da0b079f49f9bb671b570c9f608cac5d9661832817a9966.jpg) \nFig. 3 Morphology characterizations of the PBDB-TF:BTP-4X blend films. a AFM height images. b AFM phase images. c 2D GIWAXS patterns. d 1D plots extracted from the 2D patterns along the OOP and IP directions \n\n
Table 2 Detailed Voc losses of the PBDB-TF:BTP-4X-based OPV cells
Eg (eV)E(eV)qv (ev)E (eV)E (eV)E (eV)
Devices PBDB-TF:BTP-4F1.4070.5731.1430.2640.0740.230
PBDB-TF:BTP-4CI1.4000.5331.1370.2630.0650.206
\n\nBlend morphology characterization. We carried out morphology characterizations of the blend films via atomic force microscopy (AFM), transmission electron microscopy (TEM), and GIWAXS. As shown in the height images in Fig. 3a, both films have smooth surfaces. The mean-square surface roughness $(R_{\\mathrm{q}})$ of the PBDB-TF: BTP-4Cl film is $1.68\\mathrm{nm}$ , which is slightly higher than that of the PBDB-TF:BTP-4F film $(1.33\\mathrm{nm})$ . The AFM phase images (Fig. 3b) and TEM patterns (Supplementary Fig. 11) suggest that both films form nanoscale phase-separated morphologies with appropriate domain sizes in the surface and bulk. Figure 3c shows the 2d patterns from the GIWAXS measurements. The acceptors maintained their previous orientations from the blended films after blending the polymer donor PBDB-TF. Calculated from the 1D profiles, the (010) coherence lengths are around $2.0\\mathrm{nm}$ for the blend films (Fig. 3d and Supplementary Table 4). \n\nNon-radiative energy loss. To investigate the reasons behind the unusual increase of the $V_{\\mathrm{OC}},$ we studied the detailed energy losses in both devices (Table 2). According to the reported method6,50, the total energy loss $(\\Delta E)$ can be divided into three parts: (1) $\\Delta E_{1}$ , radiative recombination loss above the bandgap; (2) $\\Delta E_{2}$ , radiative recombination loss below the bandgap; and (3) $\\Delta E_{3}$ , nonradiative energy loss, also called $\\boldsymbol{E_{\\mathrm{loss,nr}}}$ . First, we estimated the optical bandgaps $(E_{\\mathrm{g}})$ by the intersections between the absorption and emission of the low bandgap BTP- $4\\mathrm{X}^{50}$ . Extracted from the plots shown in Supplementary Fig. 12, the $E_{\\mathrm{g}}\\varsigma$ are calculated to be 1.407 and $1.400\\mathrm{eV}$ . \n\nBased on the Shockley–Queisser (SQ) theory51, both devices exhibit similar values of $\\Delta E_{1}$ of about $0.263\\mathrm{eV}$ . Therefore, the SQ limit output voltages $\\left(V_{\\mathrm{OC}}^{\\mathrm{SQ}}s\\right)$ are estimated to be 1.143 and $1.137\\mathrm{V}$ for the devices based on BTP-4F and BTP-4Cl, respectively. We then measured the highly sensitive EQE spectra of the devices to evaluate the $\\Delta E_{2}$ . As shown in Fig. 4a, the blend films of PBDB-TF: BTP-4X have very similar sensitive-EQE spectra to the neat acceptors (Supplementary Fig. 13). In addition, the measured electroluminescence (EL) spectra of the blend films are also quite similar to the corresponding neat acceptors without additional emission peaks from the charge-transfer states. This phenomenon is commonly observed in highly efficient donor:acceptor systems with low-energy offsets and is beneficial for reducing $\\Delta E_{2}$ . When compared with the PBDB-TF:BTP-4F device, the band edge of PBDB-TF:BTP-4Cl is more abrupt, leading to a slightly reduced $\\Delta E_{2}$ of $0.065\\mathrm{eV}$ $\\mathrm{(0.074eV}$ for BTP-4F-containing device). \n\nBy measuring the $\\mathrm{EQE_{EL}}$ of the devices, the third part of energy loss, $\\Delta E_{3}$ , can be evaluated using the following equation: $\\Delta E_{3}=-k T\\ln{(\\mathrm{EQE_{EL}})^{52}}$ . As shown in Fig. 4b, both devices display high $\\mathrm{EQE_{EL}}$ values with magnitudes of $10^{-4}$ , which are very high values among the highly efficient OPV systems50,53. The PBDB-TF:BTP-4Cl-based device shows a higher $\\mathrm{EQE_{EL}}$ of \n\n![](images/d4ffec1c8154d596fa2ca6dbd4da7da1843f5d97e7ec5ce4eb6e42701a650e66.jpg) \nFig. 4 Energy loss. a Highly sensitive EQE curves of both devices. b EL quantum efficiencies of the solar cells at various injected current densities. c Radiative and non-radiative energy losses in the OPV cells \n\n$3.47\\times10^{-4}$ than the PBDB-TF:BTP-4F-based device $(1.40\\times10^{-4})$ and the calculated $\\Delta E_{3}$ is $0.206\\mathrm{eV}$ for the device based on PBDBTF:BTP-4Cl, which is lower than that in the PBDB-TF:BTP-4Fbased cell by $24\\mathrm{meV}$ (Fig. $\\mathrm{4c})$ ). Compared with PBDB-TF:BTP-4F blend, the lower $\\Delta E_{3}$ in PBDB-TF:BTP-4Cl blend may be associated with its lower reorganization energy instead of the higher $\\mathrm{EQE_{EL}}$ of the BTP-4Cl (Supplementary Fig. $14)^{54,55}$ . The reduced non-radiative energy loss should be the major contribution to the $V_{\\mathrm{OC}}$ increase in the PBDB-TF:BTP-4Cl-based device. The higher $\\mathrm{EQE_{EL}}$ of BTP-4Cl-containing combinations is also observed in other systems when blending different polymer donors (Supplementary Fig. 15 and Supplementary Table 5). \n\n# Discussion \n\nTo summarize, we report a chlorinated non-fullerene acceptor BTP-4Cl and achieve record PCEs of $16.5\\%$ and $15.3\\%$ for OPV cells with 0.09 and $\\textstyle{1\\cos^{2}}$ active areas, respectively. The chlorination method broads the optical absorption and helps to obtain a high $J_{\\mathrm{SC}}$ of $25.4\\mathrm{mA}\\mathrm{cm}^{-2}$ . Although the BTP-4Cl shows a downshifted LUMO level compared to its fluorinated analog BTP-4F, an unexpected higher $V_{\\mathrm{OC}}$ of $0.867\\mathrm{V}$ is obtained at a bandgap of $1.400\\mathrm{eV}$ , and the corresponding energy loss is only $0.533\\mathrm{eV}$ . The $\\mathrm{EQE_{EL}}$ measurements indicate that the BTP-4Clbased device displays a high $\\mathrm{EQE_{EL}}$ of $3.47\\times10^{-4}$ . Therefore, the calculated non-radiative energy loss is as low as $0.206\\mathrm{eV}$ , contributing to the increase in $V_{\\mathrm{OC}}.$ Our work presents an example where an extended optical absorption and improved output voltage can be achieved simultaneously by the molecular design of chlorination. These results imply that the non-radiative energy loss in OPV cells can be modified by chemical modification of the photoactive materials, which provides opportunities to design of highly efficient OPV materials with low bandgap–voltage offsets. \n\n# Methods \n\nMaterials. The polymer donor PBDB-TF and the acceptor BTP-4F (Y6) were synthesized via referencing the reported literatures21,56,57. The synthesis of BTP-4Cl was synthesized by replacing the fluorinated electron-accepting unit with its chlorinated analog reported in our previous work40. The detailed synthetic procedures and characterizations of the chemical structures can be found in Supplementary Information. \n\nFabrication and measurement of OPV cell. PBDB-TF:BTP-4X-based OPV cells were fabricated on precleaned ITO glass substrates. $\\mathrm{znO}$ nanoparticles were spincoated on the ITO with a thickness of $20\\mathrm{nm}$ and baked at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . The PBDB-TF:BTP-4F (1:1.2) blends were fully dissolved in CF at a total weight concentration of $19.8\\mathrm{mg}\\mathrm{mL}^{-1}$ . Before the spin-coating, $0.5\\%$ volume 1- chloronaphthalene (CN) was used as the solvent additive. As the spin-coated PBDBTF:BTP-4Cl film from CF solution was grainy, we changed the processing solvent to chlorobenzene/CN. The optimized donor:acceptor ratio is 1:1 for PBDB-TF:BTP-4Cl. PBDB-TF:BTP-4Cl was dissolved at a total weight concentration of $20\\mathrm{mg}\\mathrm{mL}^{-1}$ at $80^{\\circ}\\mathrm{C}$ . The active layer thicknesses were controlled at $100\\pm10\\mathrm{nm}$ . The blend films were treated with the thermal annealing at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . Finally, $\\mathrm{MoO}_{3}/\\mathrm{Al}$ ( $\\mathrm{10/100~nm},$ ) was evaporated onto the active layer under high vacuum. The $J{-}V$ tests were carried out using the solar simulator (SS-F5-3A, Enlitech) in glove box. The radiative intensity (AM $1.5\\mathrm{G}$ spectrum, $100\\mathrm{mW}\\mathrm{cm}^{-2}.$ ) was calibrated by the standard silicon solar cell (SRC-2020), which was calibrated by the National Institute of Metrology (NIM), China. $J{-}V$ curves were measured in the forward direction from $-0.5$ to $1.5\\mathrm{V}$ , with a scan step of $50\\mathrm{mV}$ and a dwell time of $5\\mathrm{ms}$ . The active area was defined by a metal mask with an aperture. Area of the aperture is 0.09 and $\\textstyle1\\cos^{2}$ in our laboratory. Area of the aperture is 0.0905 and $0.80{\\bar{7}}\\mathrm{cm}^{2}$ in NIM. EQE spectra were measured using the integrated system (QE-R, Enlitech). \n\nTheoretical simulation. We optimized the molecular geometries of BTP-4X by Gaussian $\\boldsymbol{09^{58}}$ . The hole–electron attractive energy was conducted by a wavefunction software Multiwfn59. \n\nUV–vis absorption, PL, and molecular energy level measurements. Absorption spectra of the materials were measured on a Hitachi UH5300 spectrophotometer. PL spectra were obtained on a FLS1000 PL spectrometer. The SWV measurements were conducted on a CHI650D electrochemical workstation, where the tetrabutylammonium hexafluorophosphate acetonitrile solution was used as the electrolyte and the scan rate was $10\\bar{0}\\mathrm{mVs^{-1}}$ . \n\nHighly sensitive EQE and $\\pmb{\\E Q E_{E L}}$ measurements. Highly sensitive EQE was measured using a integrated system (PECT-600, Enlitech), where the photocurrent was amplified and modulated by a lock-in instrument. $\\mathrm{EQE_{EL}}$ measurements were performed by applying external voltage/current sources through the devices (ELCT-3010, Enlitech). All of the devices were prepared for $\\mathrm{EQE_{EL}}$ measurements according to the optimal device fabrication conditions. $\\mathrm{EQE_{EL}}$ measurements were carried out from 0 to 2 V). \n\nCharge carrier mobility and TPV measurements. Photo-CELIV mobilities and TPV data were obtained by the all-in-one characterization platform, Paios (Fluxim AG, Switzerland). The space charge-limited current method was used to estimate the hole and electron mobilities, where single-carrier devices with structures of ITO/PEDOT:PSS/active layer/Au or ITO/ZnO/active layer/PFN-Br devices were fabricated, respectively. \n\nAFM, TEM, and GIWAXS characterizations. AFM height and phase images were recorded on a Nanoscope V AFM microscope (Bruker), where the tapping mode was used. TEM patterns were acquired on a JEOL 2200FS instrument (bright-field mode, accelerating voltage, $200\\mathrm{kV},$ ). GIWAXS measurements were performed on a XEUSS SAXS/WAXS system (XENOCS, France) at the National Center for Nanoscience and Technology (NCNST, Beijing). \n\n# Data availability \n\nThe relevant data are available from the authors upon reasonable request. \n\nReceived: 9 March 2019 Accepted: 29 April 2019 \nPublished online: 07 June 2019 \n\n# References \n\n1. Li, G., Zhu, R. & Yang, Y. Polymer solar cells. Nat. Photonics 6, 153–161 (2012). \n2. Inganäs, O. Organic photovoltaics over three decades. Adv. Mater. 0, 1800388 (2018). \n3. Wadsworth, A. et al. Critical review of the molecular design progress in nonfullerene electron acceptors towards commercially viable organic solar cells. Chem. Soc. Rev. 48, 1596–1625 (2018). \n4. Ye, L. et al. Quantitative relations between interaction parameter, miscibility and function in organic solar cells. Nat. Mater. 17, 253–260 (2018). \n5. Bin, H. et al. $11.4\\%$ Efficiency non-fullerene polymer solar cells with trialkylsilyl substituted 2D-conjugated polymer as donor. Nat. Commun. 7, 13651 (2016). \n6. Liu, J. et al. Fast charge separation in a non-fullerene organic solar cell with a small driving force. Nat. Energy 1, 16089 (2016). \n7. Deng, D. et al. Fluorination-enabled optimal morphology leads to over $11\\%$ efficiency for inverted small-molecule organic solar cells. Nat. Commun. 7, 13740 (2016). \n8. Li, M. et al. Solution-processed organic tandem solar cells with power conversion efficiencies ${>}12\\%$ . Nat. Photonics 11, 85–90 (2016). \n9. Ran, N. A. et al. Impact of interfacial molecular orientation on radiative recombination and charge generation efficiency. Nat. Commun. 8, 79 (2017). \n10. Baran, D. et al. Reducing the efficiency-stability-cost gap of organic photovoltaics with highly efficient and stable small molecule acceptor ternary solar cells. Nat. Mater. 16, 363–369 (2016). \n11. Meng, L. et al. Organic and solution-processed tandem solar cells with $17.3\\%$ efficiency. Science 361, 1094–1098 (2018). \n12. Fan, B. et al. Fine-tuning of the chemical structure of photoactive materials for highly efficient organic photovoltaics. Nat. Energy 3, 1051–1058 (2018). \n13. Che, X., Li, Y., Qu, Y. & Forrest, S. R. High fabrication yield organic tandem photovoltaics combining vacuum- and solution-processed subcells with $15\\%$ efficiency. Nat. Energy 3, 422–427 (2018). \n14. Yao, H. et al. Critical role of molecular electrostatic potential on charge generation in organic solar cells. Chin. J. Chem. 36, 491–494 (2018). \n15. Menke, S. M., Ran, N. A., Bazan, G. C. & Friend, R. H. Understanding energy loss in organic solar cells: toward a new efficiency regime. Joule 2, 25–35 (2018). \n16. Zhou, Z. et al. High-efficiency small-molecule ternary solar cells with a hierarchical morphology enabled by synergizing fullerene and non-fullerene acceptors. Nat. Energy 3, 952–959 (2018). \n17. Liu, F., Gu, Y., Jung, J. W., Jo, W. H. & Russell, T. P. On the morphology of polymer-based photovoltaics. J. Polym. Sci. Part B 50, 1018–1044 (2012). \n18. Gao, K. et al. Over $12\\%$ efficiency nonfullerene all-small-molecule organic solar cells with sequentially evolved multilength scale morphologies. Adv. Mater. 0, 1807842 (2019). \n19. Kong, J. et al. Long-term stable polymer solar cells with significantly reduced burn-in loss. Nat. Commun. 5, 5688 (2014). \n20. Kang, H. et al. Determining the role of polymer molecular weight for highperformance all-polymer solar cells: its effect on polymer aggregation and phase separation. J. Am. Chem. Soc. 137, 2359–2365 (2015). \n21. Yuan, J. et al. Single-junction organic solar cell with over $15\\%$ efficiency using fused-ring acceptor with electron-deficient core. Joule 3, 1140–1151 (2019). \n22. Cui, Y. et al. Achieving over $15\\%$ efficiency in organic photovoltaic cells via copolymer design. Adv. Mater. 0, 1808356 (2019). \n23. Duan, C., Huang, F. & Cao, Y. Recent development of push-pull conjugated polymers for bulk-heterojunction photovoltaics: rational design and fine tailoring of molecular structures. J. Mater. Chem. 22, 10416–10434 (2012). \n24. Graetzel, M., Janssen, R. A., Mitzi, D. B. & Sargent, E. H. Materials interface engineering for solution-processed photovoltaics. Nature 488, 304–312 (2012). \n25. Polman, A., Knight, M., Garnett, E. C., Ehrler, B. & Sinke, W. C. Photovoltaic materials: present efficiencies and future challenges. Science 352, aad4424 (2016). \n26. Cheng, Y. J., Yang, S. H. & Hsu, C. S. Synthesis of conjugated polymers for organic solar cell applications. Chem. Rev. 109, 5868–5923 (2009). \n27. Henson, Z. B., Mullen, K. & Bazan, G. C. Design strategies for organic semiconductors beyond the molecular formula. Nat. Chem. 4, 699–704 (2012). \n28. Li, Y. F. Molecular design of photovoltaic materials for polymer solar cells: toward suitable electronic energy levels and broad absorption. Acc. Chem. Res. 45, 723–733 (2012). \n29. Zhang, G. et al. Nonfullerene acceptor molecules for bulk heterojunction organic solar cells. Chem. Rev. 118, 3447–3507 (2018). \n30. Cheng, P., Li, G., Zhan, X. & Yang, Y. Next-generation organic photovoltaics based on non-fullerene acceptors. Nat. Photonics 12, 131–142 (2018). \n31. Hou, J., Inganäs, O., Friend, R. H. & Gao, F. Organic solar cells based on nonfullerene acceptors. Nat. Mater. 17, 119 (2018). \n32. Zhang, J., Tan, H. S., Guo, X., Facchetti, A. & Yan, H. Material insights and challenges for non-fullerene organic solar cells based on small molecular acceptors. Nat. Energy 3, 720–731 (2018). \n33. Li, S. et al. An unfused-core-based nonfullerene acceptor enables highefficiency organic solar cells with excellent morphological stability at high temperatures. Adv. Mater. 30, 1705208 (2018). \n34. Bin, K. et al. A chlorinated low-bandgap small-molecule acceptor for organic solar cells with $14.1\\%$ efficiency and low energy loss. Sci. China Chem. 61, 1307–1313 (2018). \n35. Li, Y. et al. High efficiency near-infrared and semitransparent non-fullerene acceptor organic photovoltaic cells. J. Am. Chem. Soc. 139, 17114–17119 (2017). \n36. Zhao, W. et al. Molecular optimization enables over $13\\%$ efficiency in organic solar cells. J. Am. Chem. Soc. 139, 7148–7151 (2017). \n37. Yao, H. et al. Design, synthesis, and photovoltaic characterization of a small molecular acceptor with an ultra-narrow band gap. Angew. Chem. Int. Ed. 56, 3045–3049 (2017). \n38. Chen, H. et al. A chlorinated $\\pi$ -conjugated polymer donor for efficient organic solar cells. Joule 2, 1623–1634 (2018). \n39. Zhang, Q., Kelly, M. A., Bauer, N. & You, W. The curious case of fluorination of conjugated polymers for solar cells. Acc. Chem. Res. 50, 2401–2409 (2017). \n40. Zhang, H. et al. Over $14\\%$ efficiency in organic solar cells enabled by chlorinated nonfullerene small-molecule acceptors. Adv. Mater. 30, e1800613 (2018). \n41. Kang, S.-H. et al. Chlorinated 2,1,3-benzothiadiazole-based polymers for organic field-effect transistors. Macromolecules 50, 4649–4657 (2017). \n42. Lin, Y. et al. An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174 (2015). \n43. Carsten, B. et al. Examining the effect of the dipole moment on charge separation in donor–acceptor polymers for organic photovoltaic applications. J. Am. Chem. Soc. 133, 20468–20475 (2011). \n44. Gao, W. et al. Asymmetrical ladder-type donor-induced polar small molecule acceptor to promote fill factors approaching $77\\%$ for high-performance nonfullerene polymer solar cells. Adv. Mater. 30, e1800052 (2018). \n45. Yuan, J. et al. Fused benzothiadiazole: a building block for $\\mathbf{n}$ -type organic acceptor to achieve high-performance organic solar cells. Adv. Mater. 31, 1807577 (2019). \n46. Gupta, V. et al. Barium: an efficient cathode layer for bulk-heterojunction solar cells. Sci. Rep. 3, 1965 (2013). \n47. Holliday, S. et al. High-efficiency and air-stable P3HT-based polymer solar cells with a new non-fullerene acceptor. Nat. Commun. 7, 11585 (2016). \n48. Zhou, H. et al. Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). \n49. Dong, Q. et al. Electron-hole diffusion lengths $>175\\mathrm{mm}$ in solution-grown $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ single crystals. Science 347, 967–970 (2015). \n50. Yuan, J. et al. Enabling low voltage losses and high photocurrent in fullerenefree organic photovoltaics. Nat. Commun. 10, 570 (2019). \n51. Shockley, W. & Queisser, H. J. Detailed balance limit of efficiency of p–n junction solar cells. J. Appl. Phys. 32, 510–519 (1961). \n52. Nikolis, V. C. et al. Reducing voltage losses in cascade organic solar cells while maintaining high external quantum efficiencies. Adv. Energy Mater. 7, 1700855 (2017). \n53. Qian, D. et al. Design rules for minimizing voltage losses in high-efficiency organic solar cells. Nat. Mater. 17, 703–709 (2018). \n54. Vandewal, K., Benduhn, J. & Nikolis, V. C. How to determine optical gaps and voltage losses in organic photovoltaic materials. Sustain. Energy Fuels 2, 538–544 (2018). \n55. Azzouzi, M. et al. Nonradiative energy losses in bulk-heterojunction organic photovoltaics. Phys. Rev. X 8, 031055 (2018). \n56. Cheng, Y.-J. et al. Synthesis, photophysical and photovoltaic properties of conjugated polymers containing fused donor–acceptor dithienopyrrolobenzothiadiazole and dithienopyrroloquinoxaline arenes. Macromolecules 45, 2690–2698 (2012). \n57. Feng, L. et al. Thieno[3,2-b]pyrrolo-fused pentacyclic benzotriazole-based acceptor for efficient organic photovoltaics. ACS Appl. Mater. Interfaces 9, 31985–31992 (2017). \n58. Gaussian 09 (Gaussian, Inc., Wallingford, CT, USA, 2009). \n59. Lu, T. & Chen, F. Multiwfn: a multifunctional wavefunction analyzer. J. Comput. Chem. 33, 580–592 (2012). \n\n# Acknowledgements \n\nJ.H. would like to acknowledge the financial support from the National Natural Science Foundation of China (51673201, 21835006, and 91633301), the Chinese Academy of Science (XDB12030200 and KJZDEW-J01). H.Y. gratefully acknowledges the support from the National Natural Science Foundation of China (21805287) and the Youth Innovation Promotion Association CAS (No. 2018043). F.G. acknowledges the financial support from the Swedish Energy Agency Energimyndigheten (grant no. 2016-010174) and the Swedish Research Council VR (2018-06048). Z.W. acknowledges the financial support from the National Natural Science Foundation of China (51961135103). \n\n# Author contribution \n\nH.Y. and J.H. conceived the idea. H.Y. synthesized the acceptor BTP-4Cl, conducted the theoretical calculations, and carried out the absorption and energy level measurements. Y.C. performed the fabrication/test of the devices. T.Z. conducted the Photo-CELIV and TPV characterizations. L.H. carried out the highly sensitive-EQE and EL measurements. Y.W. and F.G. analyzed the highly sensitive-EQE and EL data. S.Z. and J.P. provided the acceptor Y6 and the intermediate. K.X. and B.X. provided AFM and TEM images. J.Z. and Z.W. conducted the GIWAXS measurements. H.Y., Y.C., and J.H. prepared the manuscript. All authors commented on the manuscript. J.H. supervised the project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-10351-5. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks Changduk Yang and other anonymous reviewer(s) for their contribution to the peer review of this work. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1002_advs.201900246", + "DOI": "10.1002/advs.201900246", + "DOI Link": "http://dx.doi.org/10.1002/advs.201900246", + "Relative Dir Path": "mds/10.1002_advs.201900246", + "Article Title": "Defect-Rich Heterogeneous MoS2/NiS2 nullosheets Electrocatalysts for Efficient Overall Water Splitting", + "Authors": "Lin, JH; Wang, PC; Wang, HH; Li, C; Si, XQ; Qi, JL; Cao, J; Zhong, ZX; Fei, WD; Feng, JC", + "Source Title": "ADVANCED SCIENCE", + "Abstract": "Designing and constructing bifunctional electrocatalysts is vital for water splitting. Particularly, the rational interface engineering can effectively modify the active sites and promote the electronic transfer, leading to the improved splitting efficiency. Herein, free-standing and defect-rich heterogeneous MoS2/NiS2 nullosheets for overall water splitting are designed. The abundant heterogeneous interfaces in MoS2/NiS2 can not only provide rich electroactive sites but also facilitate the electron transfer, which further cooperate synergistically toward electrocatalytic reactions. Consequently, the optimal MoS2/NiS2 nullosheets show the enhanced electrocatalytic performances as bifunctional electrocatalysts for overall water splitting. This study may open up a new route for rationally constructing heterogeneous interfaces to maximize their electrochemical performances, which may help to accelerate the development of nonprecious electrocatalysts for overall water splitting.", + "Times Cited, WoS Core": 946, + "Times Cited, All Databases": 984, + "Publication Year": 2019, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000477711600019", + "Markdown": "# Defect-Rich Heterogeneous ${\\mathsf{M o S}}_{2}/{\\mathsf{N i S}}_{2}$ Nanosheets Electrocatalysts for Efficient Overall Water Splitting \n\nJinghuang Lin, Pengcheng Wang, Haohan Wang, Chun Li, Xiaoqing Si, Junlei Qi,\\* Jian Cao, Zhengxiang Zhong, Weidong Fei, and Jicai Feng \n\nDesigning and constructing bifunctional electrocatalysts is vital for water splitting. Particularly, the rational interface engineering can effectively modify the active sites and promote the electronic transfer, leading to the improved splitting efficiency. Herein, free-standing and defect-rich heterogeneous ${\\mathsf{M o S}}_{2}/{\\mathsf{N i S}}_{2}$ nanosheets for overall water splitting are designed. The abundant heterogeneous interfaces in $M o S_{2}/N i S_{2}$ can not only provide rich electroactive sites but also facilitate the electron transfer, which further cooperate synergistically toward electrocatalytic reactions. Consequently, the optimal $M o S_{2}/\\mathsf{N i S}_{2}$ nanosheets show the enhanced electrocatalytic performances as bifunctional electrocatalysts for overall water splitting. This study may open up a new route for rationally constructing heterogeneous interfaces to maximize their electrochemical performances, which may help to accelerate the development of nonprecious electrocatalysts for overall water splitting. \n\nThe electrolysis of water offers a promising solution to produce clean and renewable hydrogen fuel supply.[1] Electrocatalytic water splitting involving two half reactions, hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), requires highly efficient electrocatalysts such as Pt for HER and $\\mathrm{RuO}_{2}$ or $\\mathrm{IrO}_{2}$ for OER to lower the activation barrier and boost the reaction process.[2,3] However, the high cost and scarcity of these noble electrocatalysts seriously limited their wide application.[4] In view of the above situation, tremendous effort has been devoted to develop nonprecious yet efficient catalysts for OER and HER simultaneously.[5,6] \n\nAmong these potential candidates, transition metal sulfides (TMSs), such as $\\mathsf{M o S}_{2}$ , $\\mathrm{CoS}_{2}$ , and $\\mathrm{Ni}\\mathsf{S}_{2}$ , have drawn extensive attention, due to their considerable electrocatalytic performances.[7,8] aHnodwienvesru,fftichie nltimstiatebdiliteyleocftrotahcetsieveTsMitSes seriously restricted the improved electrocatalytic activity.[9,10] Element doping would be an effective method to improve the catalytic activities, such as doping Ni atoms in $\\mathsf{M o S}_{2}$ .[1,7] Considering that \nsurfaces or interfaces play the key role in electrochemical \nreactions, the morphology, surface defects or interfaces, and \nelectrical structures are the key factors on the electrocatalytic \nperformances of efficient catalysts.[11–15] As for tuning the \nmorphology, constructing 2D TMS nanosheets could generate \nabundant electroactive sites because of inherent large spe \ncific surface and rich active edges.[16,17] In particular, in situ \ngrowing nanosheet nanostructures on conductive substrates, \nsuch as Ni foam, carbon cloth, and stainless steel, could supply \nthe efficient pathways for charge transport and provide open \nchannels for rapid release of gas bubbles during OER or HER \nprocess.[18–20] Further, interface modification could be another \neffective approach to engineering the physical or chemical \nproperties of electrocatalysts.[21,22] The interface engineering \ncould be beneficial to enrich the active sites and promote the \nelectronic transfer, and thus boost the sluggish water splitting \nefficiency.[23,24] Additionally, owing to the different chemical \nreactivity, there are abundant interior defects in bimetal sulfide \nhybrids.[25,26] Undoubtedly, the defects in bimetal sulfide \nhybrids have a significant impact on electrical behavior, and \nthus modify the electrocatalytic performances.[25,26] Conse \nquently, it is highly desirable to design and construct defected \nheterogeneous nanosheets with abundant electroactive sites \ndirectly on conductive substrates for overall water splitting. Herein, we successfully construct defect-rich heterogeneous \n\n$\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ nanosheets directly on carbon cloth and investigate the influence of interface configuration on the electrocatalytic performances. The defect-rich interfaces with disordered structure are confirmed by the high-resolution transmission electron microscopy (HRTEM), and X-ray photoelectron spectroscopy (XPS) further evidences the strengthened interfacial effects between ${\\mathrm{MoS}}_{2}$ and $\\mathrm{NiS}_{2}$ . Consequently, the optimal $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ nanosheets present low overpotentials of 62 and $278~\\mathrm{mV}$ at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ for HER and OER, respectively. Further, for overall water splitting, the optimal $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets exhibit a voltage of $1.59\\mathrm{V}$ at $10\\mathrm{mAcm}^{-2}$ as well as good stability. \n\n![](images/08f141b5f05731bd2f7edf2e24785ddf3a1cc24fc8fed718feeafa2afff89bd0.jpg) \nFigure 1.  Schematic illustration for the formation of defect-rich heterogeneous ${\\sf M o S}_{2}/{\\sf N i S}_{2}$ nanosheets. \n\nThe fabrication of defect-rich heterogeneous $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets involves two steps, as schematically shown in Figure  1. First, Ni-Mo precursors were synthesized on carbon cloth by the hydrothermal process. Second, $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ nanosheets were synthesized by annealing the Ni-Mo precursors with sublimed sulfur in Ar atmosphere at $400~^{\\circ}\\mathrm{C}$ for $^{1\\mathrm{{h}}}$ . And different $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ nanosheets are prepared by finely controlling the amount of sublimed sulfur (50, 100, 200, and $400\\mathrm{mg}$ ), which is briefly named as $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}–1,$ 2, 3, and 4. For comparison, pure $\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets also are prepared by the similar process and more detailed information could be found in Supporting Information. And pure $\\mathrm{NiMoO}_{4}$ nanosheets are also synthesized by annealing Ni-Mo precursors in air. \n\nThe crystal phases of obtained samples are investigated by X-ray diffraction (XRD) analysis, as shown in Figure 2a. Evidently, all diffraction peaks except for the peak of carbon cloth could be well indexed to $\\mathrm{NiS}_{2}$ (Joint Committee on Powder Diffraction Standards (JCPDS) Card No. 11-0099)[6] and $\\ensuremath{\\mathrm{MoS}}_{2}$ (JCPDS Card No. 37-1492),[12] suggesting the presence of metal sulfides. The morphologies of obtained samples are characterized by scanning electron microscopy (SEM), as shown in Figure  2b. A porous, discontinuous, and loose surface could be found in $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ , while a continuous and compact surface could be observed for $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}–1$ (Figure S3a, Supporting Information). And with excessive sulfur source, the $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}–4$ nanosheets have been seriously etched and more porous nanosheets could be formed (Figure S3d, Supporting Information). From the SEM images in Figure 2b and Figure S3 in the Supporting Information, it can be found that various morphologies and structures of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ nanosheets could be prepared by finely controlling the amount of sublimed sulfur. Again, the TEM images in Figure  2c confirm that $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ nanosheets possess the amounts of nanoholes, which could provide more electroactive sites for catalytic reactions. The Brunauer–Emmett–Teller specific surface area of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ nanosheets was calculated as $56.6\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}$ , again suggesting the rich active sites for electrochemical reactions. In the HRTEM images (Figure $2\\mathrm{d-g)}$ , the lattice fringe of $0.62\\ \\mathrm{nm}$ belong to the (002) lattice plane of $\\mathsf{M o S}_{2}$ , while the lattice distances of $0.28\\mathrm{nm}$ are indexed to (200) plane of $\\mathrm{NiS}_{2}$ . More importantly, clear hetero­interfaces derived from the mismatch of $\\mathrm{MoS}_{2}$ and $\\mathrm{NiS}_{2}$ in Figure 2e,g could result in rich defects and disordered structure. Such heterointerfaces in obtained sulfides are beneficial for promoting HER performances, and it will be discussed in the following sections. Further, the energy dispersive X-ray spectroscopy mapping results (Figure 2h) show the homogeneously distribution of Ni, Mo, and S elements in $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ nanosheets. \n\n![](images/18d3c441ece5d80638c199df59ceceed56bcd076306cd591b5e887c93aeb18a1.jpg) \nFigure 2.  a) XRD patterns of obtained samples. b) SEM images of MoS2/NiS2-3 nanosheets. c–g) TEM and HRTEM images of MoS2/NiS2-3 nanosheets. h) The corresponding element mappings in $\\mathsf{M o S}_{2}/\\mathsf{N i S}_{2}.3$ nanosheets. \n\n![](images/f816742c4124fc8a02b19dbe35d98c4450be5f157d2ebc80f76cfefd6c5a0874.jpg) \nFigure 3.  a) Raman spectrum of $\\mathsf{M o S}_{2}/\\mathsf{N i S}_{2}.3$ nanosheets. High-resolution XPS profiles of b) Ni 2p of $\\mathsf{M o S}_{2}/\\mathsf{N i S}_{2}.3$ and ${\\mathsf{N i S}}_{2}$ c) Mo 3d, and d) $\\mathsf{S2p}$ in $\\mathsf{M o S}_{2}/\\mathsf{N i S}_{2}{\\cdot}3$ nanosheets. \n\nSince electrochemical reactions mainly occur on the surfaces or at the interfaces of electrocatalysts,[11–13] it is vital to investigate the surface states of obtained samples by Raman and XPS measurements. As shown in Figure  3a, the peaks at about 294, 375, and $404~\\mathrm{cm}^{-1}$ belong to $\\mathrm{E}_{1\\mathrm{g},}\\ \\mathrm{E}^{1}{}_{2\\mathrm{g}},$ and $\\mathbf{A}_{1\\mathrm{g}}$ modes of $2\\mathrm{H}{\\cdot}\\mathrm{MoS}_{2}$ , and the peak $345~\\mathrm{cm}^{-1}$ is from the modes of the Ni-S.[8,27–29] More importantly, the obvious three peaks in $800{-}1000\\ \\mathrm{cm}^{-1}$ could be ascribed to the molecular structure of $\\mathrm{Mo}_{3}\\mathrm{S}_{13}$ that existing the edge sites of $\\mathrm{MoS}_{2}$ , and further suggest rich under-coordinated Mo-S edge sites in $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ nanosheets.[8,28,29] As for $\\mathrm{Ni}~2\\mathrm{p}$ in Figure 3b, two obvious peaks at 872.9 and $855.4\\mathrm{eV}$ are attributed to the Ni $2\\mathrm{p}_{1/2}$ and Ni $2\\mathrm{p}_{3/2}$ as well two broad satellite peaks, demonstrating the presence of $\\mathrm{Ni}^{2+}$ [30] Compared to pure $\\mathrm{Ni}\\mathsf{S}_{2}$ , two peaks of Ni $2\\mathrm{p}_{1/2}$ and Ni $2\\mathrm{p}_{3/2}$ in $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ are slightly shifted to higher binding energies (about $0.5~\\mathrm{eV}$ ). It suggests the strong electronic interactions between $\\mathrm{Ni}\\mathsf{S}_{2}$ and ${\\mathrm{MoS}}_{2}$ domains through established heterogeneous interfaces.[31,32] As for Mo 3d in Figure  3c, the peaks at about 232.4 and $229.1\\mathrm{eV}$ are corresponded to Mo $3\\mathrm{d}_{3/2}$ and Mo $3\\mathrm{d}_{5/2}$ , suggesting the presence ${\\mathrm{Mo}}^{4+}$ .[8] And the nearby peak at about $226.2\\:\\mathrm{eV}$ from S 2s suggests the formation of Ni-S and Mo-S bindings.[8,33] For $\\mathrm{~s~}2\\mathrm{p}$ spectra in obtained samples (Figure  3d), it can be deconvoluted into three peaks corresponding to the $\\mathrm{~S~}2\\mathrm{p}_{3/2},\\mathrm{~S~}2\\mathrm{p}_{1/2}$ for Mo-S bond and $\\mathrm{~S~}2\\mathrm{p}_{1/2}$ for Ni-S bond, at as well as a peak from the oxidized species formed on the surface of metal sulfides.[3] The S $2\\mathrm{p}_{3/2}$ peak is attributed to the typical metal-S bond, while the S $2\\mathrm{p}_{1/2}$ corresponds to the sulfur with low coordination that is generally related to sulfur defects.[34,35] It suggests the presence of terminal unsaturated S atoms on Mo-S and Ni-S sites, which may be beneficial for HER performances.[35,36] Based on SEM, TEM, Raman, and XPS analysis, as-synthesized $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets are proved to possess porous nanostructure and defected interface for rich active sites and are expected to achieve excellent electrocatalytic performances. \n\n![](images/5daef2814bc4a320933a2d97c980a358a19c7b3dd856ea0e9cb3ec126f18d6a4.jpg) \nFigure 4.  a) Polarization curves and b) the corresponding Tafel plots of obtained sample for HER. c) Chronopotentiometric curve of HER for ${\\mathsf{M o S}}_{2}/$ ${\\mathsf{N i S}}_{2}$ -3 nanosheets. d) Polarization curves and e) the corresponding Tafel plots of obtained sample for OER. f) Chronopotentiometric curve of OER for $\\mathsf{M o S}_{2}/\\mathsf{N i S}_{2}.3$ nanosheets. \n\nThe electrocatalytic HER and OER activities of heterogeneous $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets were measured in a three-electrode configuration using $1\\mathrm{~M~}$ potassium hydroxide (KOH) as electrolyte. For comparison, the performance of the commercial $\\mathrm{Pt/C}$ , $\\mathrm{RuO}_{2}$ and $\\mathrm{Ni}\\mathsf{S}_{2}$ were also measured. Figure 4a presents the polarization curves of the samples with iR correction. As for $\\ensuremath{\\mathrm{MoS}}_{2}/$ $\\mathrm{NiS}_{2^{-3}}$ nanosheets, the current density rapidly increases with the increased potential, demonstrating the remarkable HER performances. The $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2^{-3}}$ nanosheets delivered an overpotential of 62, 108, and $131\\mathrm{mV}$ at the current densities of 10, 50, and $100\\mathrm{\\mA\\cm^{-2}}$ , superior to those of other counterparts, and comparable with $\\mathrm{Pt/C}$ . As further compared with the current noble-metal-free catalysts (Table S1, Supporting Information), our $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ nanosheets show the competitive electrocatalytic performances. When compared the HER performances of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ and pure $\\mathrm{Ni}\\mathsf{S}_{2}$ , the obvious improvement suggests the synergy and mutual interaction between $\\mathbf{MoS}_{2}$ and $\\mathrm{Ni}\\mathsf{S}_{2}$ . In addition, we also prepared different samples by simply changing the annealing temperature, and the sublimed sulfur was fixed at $200~\\mathrm{{mg}}$ . As shown in Figures S6–S8 in the Supporting Information, $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ obtained at $400~^{\\circ}\\mathrm{C}$ possesses the richest sulfur defects and shows the best HER and OER performances. These results demonstrate to some extent, sulfur defects could provide rich active sites and accelerate electron/ mass transfer, resulting in improved catalytic performances. \n\nTo investigate the HER kinetic mechanism, the Tafel plots calculated from the polarization curves are shown in Figure 4b. The Tafel slop of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ nanosheets $(50.1\\ \\mathrm{mV\\dec^{-1}})$ is smaller than pure $\\mathrm{Ni}\\mathsf{S}_{2}$ and other $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ samples, while it is close to that of $\\mathrm{Pt/C}$ $(31.7~\\mathrm{mV~dec^{-1}})$ . According to previous researches,[37,38] HER in KOH solution involves in three principal steps: i) Volmer reaction (Tafel slope of about $120\\mathrm{~mV~dec^{-1})}$ , ii) Heyrovsky reaction (Tafel slope of about $40\\mathrm{mV}\\mathrm{dec^{-1}}$ ), and iii) Tafel reaction (Tafel slope of about $30\\ \\mathrm{mV\\dec^{-1})}$ . Such a Tafel slope of the $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheet $(50.1\\mathrm{mV}\\mathrm{dec}^{-1})$ suggests the HER reaction follows the Volmer– Heyrovsky mechanism $(\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{H}_{\\mathrm{ads}}+\\mathrm{e}^{-}\\rightarrow\\mathrm{H}_{2}+\\mathrm{OH}^{-})$ , where $\\mathrm{H}_{\\mathrm{ads}}$ presents the $\\mathrm{~H~}$ atom on an active site. Compared with pure $\\mathrm{Ni}\\mathsf{S}_{2}$ $(172.2\\mathrm{mV}\\mathrm{dec}^{-1}.$ ), the obviously decreased Tafel slope of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ also confirms the enhanced Volmer step in HER kinetics.[8,30] From the XPS result in Figure  3b, it could be inferred that the electron density around Ni is reduced in $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ , which could provide sufficient empty d orbitals to improve the binding ability with H atoms.[31,39] Therefore, the improved H binding would facilitate the Volmer step, leading to the obviously decreased Tafel slope and enhanced HER performances of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ . Figure S9a shows the chronopotentiometric curve for $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ electrode at various current densities from 10 to $190\\mathrm{\\mA\\cm^{-2}}$ . The potential shows no obvious changes in every step, indicating the good conductivity, excellent mass transport, and mechanical properties of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ electrode in HER tests. In the long-time stability test (Figure  4c), the $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ electrode maintains a stable HER activity at different current densities ranging from 10 to $50\\mathrm{\\mA\\cm^{-2}}$ . In addition, SEM and XRD results in Figure S10 in the Supporting Information demonstrate that the nanosheet structure and crystallinity of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ are well retained after the HER stability measurement. Consequently, the good HER performances could be attributed to the strengthened interfacial effects between $\\mathrm{MoS}_{2}$ and $\\mathrm{NiS}_{2}$ with multilevel interfaces. Further, the rich electroactive sites by structure fine tuning also make great contribution to the good HER performances. \n\nSince OER is another key role for overall water splitting, the OER performances of these samples are further characterized. As shown in Figure 4d, the polarization curve of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ shows the remarkably improved OER activity with low overpotentials of 278, 352, and $393~\\mathrm{mV}$ at 10, 50, and $100\\mathrm{\\mA\\cm^{-2}}$ . Further, the OER performances of $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2^{-3}}$ are competitive among the current noble-metal-free catalysts (Table S2, Supporting Information). As shown in Figure  4e, the Tafel slope for $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ is $91.7~\\mathrm{mV~dec^{-1}}$ , which is lower than that of pure $\\mathrm{Ni}\\mathsf{S}_{2}$ $(154.2~\\mathrm{mV~dec^{-1}})$ ) and is close to that of $\\mathrm{RuO}_{2}$ $(65.5\\ \\mathrm{mV\\dec^{-1}})$ ). It indicates that the $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ proceeds a faster OER kinetic.[40] The chronopotentiometric curve of $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ electrode in Figure S9b in the Supporting Information shows no obvious changes in every step, suggesting the good conductivity, excellent mass transport, and mechanical properties in OER tests. Further, we also compared the electrochemical sensitive area by measuring the double-layer capacitance $(C_{\\mathrm{dl}})$ of these samples in Figure $\\mathsf{S9c}$ in the Supporting Information. The $C_{\\mathrm{dl}}$ of $6.32~\\mathrm{mF~cm}^{-2}$ on $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ is much higher than that of pure $\\mathrm{NiS}_{2}$ $(2.70\\mathrm{~mF~cm^{-2}})$ ). Consequently, the higher $C_{\\mathrm{dl}}$ value demonstrates the more efficient mass and charge transport capability on $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ for OER.[41] Further, the Nyquist plots (Figure S9d, Supporting Information) show that the $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ possesses the lowest transfer resistance, revealing the fastest electron transfer kinetics.[40,41] To investigate the stability for OER, a long-time chronopotentiometry measurement was carried out at 10 and $50\\mathrm{mA}\\mathrm{cm}^{-2}$ . As shown in Figure  4f, no obvious degradation could be found, suggesting the good stability. \n\nIn order to get insight the reaction mechanism for OER, the $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ after long-term OER tests was characterized by SEM, XRD, Raman, and XPS (Figure S12, Supporting Information). $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ after long-term OER tests maintained the nanosheet morphology with a rougher and thicker surface, as shown in Figure S12a in the Supporting Information. XRD pattern in Figure S12b in the Supporting Information shows that the new phase of $\\mathrm{Ni}(\\mathrm{OH})_{2}{\\cdot}0.75\\mathrm{H}_{2}\\mathrm{O}$ is formed after OER. It suggests that the Mo content in $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}{\\cdot}3$ is greatly reduced after long-term OER tests. The Raman result in Figure S12c in the Supporting Information also shows the 471 and $558~\\mathrm{cm}^{-1}$ peaks from the presence of NiOOH.[42] As for Ni 2p in Figure S12d in the Supporting Information, the energy separation of $17.6\\ \\mathrm{eV}$ demonstrate the presence of $\\mathrm{Ni}^{3+}$ .[43,44] \n\nIn other word, it suggests that the surface $\\mathrm{Ni}^{2+}$ was oxidized after continuous electrochemical tests. As in Figure S12e in the Supporting Information, the intensity of $\\mathrm{~S~}2\\mathrm{p}$ has been greatly reduced after OER stability tests, suggesting the loss of S element. And the intensity of Mo 3d (Figure S12f, Supporting Information) also suggests that Mo content is reduced after long-term OER tests. With respect to O 1s (Figure $\\mathrm{s12g}$ , Supporting Information), the peaks at 530.4 and $532.3\\ \\mathrm{eV}$ correspond to the lattice oxygen and surface hydroxyls.[45] It suggests that nickel oxides/hydroxides are formed during OER process. According to previous researches,[45–49] metal sulfides could be formed corresponding oxides/hydroxides during OER process and the formed oxides/hydroxides are known as the electrocatalytically active phases. \n\nTo illustrate the effect of the interface between $\\mathrm{MoS}_{2}$ and $\\mathrm{NiS}_{2}$ , we also we synthesized pure ${\\mathrm{MoS}}_{2}$ nanosheets on carbon cloth (see Figures S13 and S14, Supporting Information). Then, we scratched the $\\mathrm{MoS}_{2}$ and $\\mathrm{Ni}\\mathsf{S}_{2}$ powders from the carbon cloth, then mechanically mixed $\\mathrm{MoS}_{2}$ and $\\mathrm{Ni}\\mathsf{S}_{2}$ with the atomic ratio of $\\mathrm{Mo}{:}\\mathrm{Ni}=1{:}1$ (denoted as $\\mathrm{MoS}_{2}{\\cdot}\\mathrm{Ni}\\mathrm{S}_{2}$ ). The mechanically mixed ${\\mathrm{MoS}}_{2}{\\cdot}{\\mathrm{Ni}}{\\mathrm{S}}_{2}$ powders were also prepared on carbon cloth for tests. As shown in Figure S15 in the Supporting Information, it can be found that $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ shows much better HER and OER performances than that of mechanically mixed $\\mathrm{MoS}_{2}.$ $\\mathrm{NiS}_{2}$ sample. And according to previous researches,[50,51] interface engineering could be beneficial to accelerate the HER and OER kinetics by modifying the chemisorption. Owing to the strong electronic interactions and synergistic effects, the formed interfaces between two active materials could reconstruct more active centers for catalytic reactions.[50,52,53] Consequently, these results further demonstrate the effect of the interface, which could enrich the active sites and promote the electronic transfer, and thus boost the sluggish water splitting efficiency. \n\nFinally, the optimum $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ was further used as bifunctional electrocatalyst for overall water splitting. As shown in Figure  5a, the device affords a current density of $10\\mathrm{\\mA\\cm^{-2}}$ with a cell voltage of $1.59\\mathrm{V}.$ As shown in Figure 5b, the measured voltage is slightly larger than calculated voltage in different current densities, which may be due to the difference in the testing system. As shown in Figure 5c, the low cell voltage $(1.59\\mathrm{~V~}$ at $10\\mathrm{\\mA\\cm^{-2}},$ ) for $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ is competitive with recently reported bifunctional electrocatalysts, such as NiS$\\mathrm{NiS}_{2}$ $(1.58~\\mathrm{V}$ at $10\\ \\mathrm{mA\\cm^{-2}}$ ,[54] $\\mathrm{Ni}_{0.33}\\mathrm{Co}_{0.67}\\mathrm{S}_{2}\\|\\mathrm{Ni}\\mathrm{Co}_{2}\\mathrm{O}_{4}$ $\\ensuremath{\\left(1.69\\mathrm{~V~}\\right.}$ at $10\\mathrm{\\mA\\cm^{-2}}$ ),[55] NiS- ${\\mathrm{Ni}_{2}P_{2}S_{6}}$ ( $1.64\\mathrm{~V~}$ at $10\\mathrm{\\mA\\cm^{-2}}$ ,[56] $\\mathrm{MoS}_{2}/\\mathrm{NiS}$ $(1.64~\\mathrm{~V~}$ at $10\\mathrm{\\mA\\cm^{-2}})$ ,[52] $\\mathrm{MoS}_{2}/\\mathrm{NiS}$ (1.61  V at $10\\mathrm{\\mA\\cm^{-2}})$ ),[57 $\\mathrm{|\\NiS/Ni_{2}P}$ $(1.67\\mathrm{V}$ at $10\\ \\mathrm{mA\\cm^{-2}})$ ),[58] $\\mathrm{NiS}/\\mathrm{NiS}_{2}$ $(1.62~\\mathrm{V}$ at $10\\mathrm{\\mA\\cm^{-2}}$ ),[59] Ni-Co-P ( $1.62\\mathrm{~V~}$ at $10\\ \\mathrm{mA\\cm^{-2}}$ ,[60] $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{MoS}_{2}$ $(1.59\\mathrm{~V~}$ at $10\\mathrm{\\mA\\cm^{-2}})$ ),[61] and $\\mathrm{MoS}_{2}–\\mathrm{CoOOH}$ $[1.60\\mathrm{V}$ at $10\\mathrm{mAcm^{-2}}$ .[62] To investigate the faradaic efficiency, the amounts of $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ produced during water splitting were measured in Figure S16 in the Supporting Information. After comparing the measured and calculated gas amounts, the faradaic efficiency for $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ is closed to $100\\%$ . Further, Figure  5d shows that $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}\\|\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}$ exhibits unnoticeable deterioration at 10 and $50\\mathrm{\\mA\\cm^{-2}}$ , suggesting good stability during overall water splitting. \n\nOverall, the improved OER and HER performances of as-synthesized $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ nanosheets is attributed to following aspects: 1) nanosheet arrays directly on carbon cloth could make sure the efficient pathways for charge transport and open channels for rapid release of gas bubbles. 2) The nanoholes by finely controlling the amount of sublimed sulfur could provide rich electroactive sites for catalytic reactions. 3) The strengthened interfacial effects between $\\mathrm{MoS}_{2}$ and $\\mathrm{NiS}_{2}$ could effectively modify the electronic interactions, contributing the electrocatalytic activities. 4) The abundant heterogeneous interfaces in $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ could not only provide rich electroactive sites but also facilitate the electron transfer. Consequently, optimal $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets show the enhanced electrocatalytic performances for HER, OER, and overall water splitting. \n\n![](images/5d8277b3e0a6e95b686df28cb2fa02d9f30864df406a74c77650abaa19d09929.jpg) \nFigure 5.  a) Polarization curves of optimal ${\\mathsf{M o S}}_{2}/{\\mathsf{N i S}}_{2}$ nanosheets and $\\mathsf{R u O}_{2}//\\mathsf{P t}/\\mathsf{C}$ for overall water splitting. b) The comparison of calculated and measured water splitting potential. c) The comparison of overall water splitting performances between optimal ${\\sf M o S}_{2}/{\\sf N i S}_{2}$ nanosheets and other eletrocatalysts in reported literature. d) Chronopotentiometric curve of water electrolysis for optimal ${\\mathsf{M o S}}_{2}/{\\mathsf{N i S}}_{2}$ nanosheets. \n\nIn summary, free-standing and defect-rich heterogeneous $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets are successfully designed and fabricated, which serves as bifunctional electrocatalysts for overall water splitting. The derived $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}_{2}$ interface with rich defects and disordered structure could modify the electronic interactions and facilitate the electron, which could be beneficial for electrocatalytic reactions. Further, the binder-free nanosheet arrays with rich nanoholes could also boost the HER and OER performances by providing rich electroactive sites and favoring the gas release from nanosheets. Consequently, working as both cathode and anode electrodes, the optimal $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathsf{S}_{2}$ nanosheets exhibit a voltage of $1.59{\\mathrm{~V~}}$ at the current density of $10\\mathrm{mAcm}^{-2}$ , as well as good stability. Therefore, rational construct and comprehension of heterogeneous interfaces offer a promising alternative to nonprecious electrocatalysts for overall water splitting. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nJ.L. and P.W. contributed equally to this work. The support from the National Natural Science Foundation of China (Grant Nos. 51575135, 51622503, U1537206, and 51621091) is highly appreciated. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\ndefects, free-standing, heterointerfaces, metal sulfides, overall water splitting \n\nReceived: January 30, 2019 \nRevised: April 22, 2019 \nPublished online: May 20, 2019 \n\n[1]\t Y. Huang, Y. Sun, X. Zheng, T. Aoki, B. Pattengale, J. Huang, X. He, W. Bian, S. Younan, N. Williams, J. Hu, J. Ge, N. Pu, X. Yan, X. Pan, L. Zhang, Y. Wei, J. Gu, Nat. Commun. 2019, 10, 982. [2]\t Y.  Luo, L.  Tang, U.  Khan, Q.  Yu, H.  Cheng, X.  Zou, B.  Liu, Nat. Commun. 2019, 10, 269. [3]\t F.  Li, D.  Zhang, R.  Xu, W.  Fu, X.  Lv, ACS Appl. Energy Mater. 2018, 1, 3929. \n[4]\t H.  Zhang, X.  Li, A.  Hähnel, V.  Naumann, C.  Lin, S.  Azimi, S. L.  Schweizer, A. W.  Maijenburg, R. B.  Wehrspohn, Adv. Funct. Mater. 2018, 28, 1706847. \n[5]\t K.  Xu, Y.  Sun, Y.  Sun, Y.  Zhang, G.  Jia, Q.  Zhang, L.  Gu, S.  Li, Y.  Li, H. J. Fan, ACS Energy Lett. 2018, 3, 2750. [6]\t Y. Zhang, F. Lu, L. Pan, Y. Xu, Y. Yang, Y. Bando, D. Golberg, J. Yao, X. Wang, J. Mater. Chem. A 2018, 6, 11978. [7]\t H.  Zhang, L.  Yu, T.  Chen, W.  Zhou, X. W.  Lou, Adv. Funct. Mater. 2018, 28, 1807086. \n[8]\t J.  Staszak-Jirkovský, C. D.  Malliakas, P. P.  Lopes, N.  Danilovic, S. S.  Kota, K.  Chang, B.  Genorio, D.  Strmcnik, V. R.  Stamenkovic, M. G. Kanatzidis, N. M. Markovic, Nat. Mater. 2016, 15, 197. \n[9]\t Y. Liu, C. Xiao, P. Huang, M. Cheng, Y. Xie, Chem 2018, 4, 1263. \n[10]\t X. Y. Yu, X. W. Lou, Adv. Energy Mater. 2018, 8, 1701592. \n[11]\t Y. P.  Zhu, T. Y.  Ma, M.  Jaroniec, S. Z.  Qiao, Angew. Chem., Int. Ed. 2017, 56, 1324. \n[12]\t S.  Liu, Y.  Yin, M.  Wu, K. S.  Hui, K. N.  Hui, C.  Ouyang, S. C.  Jun, Small 2019, 15, 1803984. \n[13]\t S. Ye, Z. Shi, J. Feng, Y. Tong, G. Li, Angew. Chem., Int. Ed. 2018, 57, 2672. \n[14]\t J. Feng, J. Wu, Y. Tong, G. Li, J. Am. Chem. Soc. 2018, 140, 5118. \n[15]\t K. N.  Dinh, X.  Sun, Z.  Dai, Y.  Zheng, P.  Zheng, J.  Yang, J.  Xu, Z. Wang, Q. Yan, Nano Energy 2018, 54, 82. \n[16]\t G.  Zhang, Y.  Feng, W.  Lu, D.  He, C.  Wang, Y.  Li, X.  Wang, F.  Cao, ACS Catal. 2018, 8, 5431. \n[17]\t M. S.  Islam, M.  Kim, X.  Jin, S. M.  Oh, N.  Lee, H.  Kim, S.  Hwang, ACS Energy Lett. 2018, 3, 952. \n[18]\t B.  Liu, Y.  Wang, H.  Peng, R.  Yang, Z.  Jiang, X.  Zhou, C.  Lee, H. Zhao, W. Zhang, Adv. Mater. 2018, 30, 1803144. \n[19]\t D.  Wang, Q.  Li, C.  Han, Z.  Xing, X.  Yang, ACS Cent. Sci. 2018, 4, 112. \n[20]\t S.  Deng, Y.  Zhong, Y.  Zeng, Y.  Wang, X.  Wang, X.  Lu, X.  Xia, J.  Tu, Adv. Sci. 2018, 5, 1700772. \n[21]\t H.  Ding, Q.  Jiao, H.  Lv, K.  Xu, Q.  Xing, M.  Chen, W.  Chu, X.  Wu, Y. Guo, J. Mater. Chem. A 2018, 6, 17488. \n[22]\t Y.  Li, J.  Yin, L.  An, M.  Lu, K.  Sun, Y.  Zhao, D.  Gao, F.  Cheng, P.  Xi, Small 2018, 14, 1801070. \n[23]\t C. Guo, Y. Zheng, J. Ran, F. Xie, M. Jaroniec, S. Qiao, Angew. Chem., Int. Ed. 2017, 56, 8539. \n[24]\t Z. Zhang, X. Ma, J. Tang, J. Mater. Chem. A 2018, 6, 12361. \n[25]\t J.  Zhang, W.  Xiao, P.  Xi, S.  Xi, Y.  Du, D.  Gao, J.  Ding, ACS Energy Lett. 2017, 2, 1022. \n[26]\t C. Zhang, Y. Shi, Y. Yu, Y. Du, B. Zhang, ACS Catal. 2018, 8, 8077. \n[27]\t M. A. R.  Anjum, H. Y.  Jeong, M. H.  Lee, H. S.  Shin, J. S.  Lee, Adv. Mater. 2018, 30, 1707105. \n[28]\t J.  Kibsgaard, T. F.  Jaramillo, F.  Besenbacher, Nat. Chem. 2014, 6, 248. \n[29]\t D.  Kong, Y.  Wang, Y. V.  Lim, S.  Huang, J.  Zhang, B.  Liu, T.  Chen, H. Y. Yang, Nano Energy 2018, 49, 460. \n[30]\t G. F. Chen, T. Y. Ma, Z. Q. Liu, N. Li, Y. Z. Su, K. Davey, S. Z. Qiao, Adv. Funct. Mater. 2016, 26, 3314. \n[31]\t Y.  Yang, K.  Zhang, H.  Lin, X.  Li, H. C.  Chan, L.  Yang, Q.  Gao, ACS Catal. 2017, 7, 2357. \n[32]\t L. An, J. Feng, Y. Zhang, R. Wang, H. Liu, G. Wang, F. Cheng, P. Xi, Adv. Funct. Mater. 2019, 29, 1805298. \n[33]\t X.  Wang, J.  Wang, X.  Sun, S.  Wei, L.  Cui, W.  Yang, J.  Liu, Nano Res. 2018, 11, 988. \n[34]\t M. R.  Gao, J. X.  Liang, Y. R.  Zheng, Y. F.  Xu, J.  Jiang, Q.  Gao, J.  Li, S. H. Yu, Nat. Commun. 2015, 6, 5982. \n[35]\t Y. Li, K. Yin, L. Wang, X. Lu, Y. Zhang, Y. Liu, D. Yan, Y. Song, S. Luo, Appl. Catal., B 2018, 239, 537. \n[36]\t J.  Zhang, C.  Zhang, Z.  Wang, J.  Zhu, Z.  Wen, X.  Zhao, X.  Zhang, J. Xu, Z. Lu, Small 2018, 14, 1703098. \n[37]\t Y.  Zhu, G.  Chen, Y.  Zhong, W.  Zhou, Z.  Shao, Adv. Sci. 2018, 5, 1700603. \n[38]\t Y.  Zheng, Y.  Jiao, Y.  Zhu, L. H.  Li, Y.  Han, Y.  Chen, A.  Du, M. Jaroniec, S. Z. Qiao, Nat. Commun. 2014, 5, 3783. \n[39]\t J. Greeley, T. F. Jaramillo, J. Bonde, I. B. Chorkendorff, J. K. Norskov, Nat. Mater. 2006, 5, 909. \n[40]\t S.  Dutta, A.  Indra, Y.  Feng, H.  Han, T.  Song, Appl. Catal., B 2019, 241, 521. \n[41]\t Q.  Xu, H.  Jiang, H.  Zhang, Y.  Hu, C.  Li, Appl. Catal., B 2019, 242, 60. \n[42]\t Y.  Li, H.  Zhang, M.  Jiang, Y.  Kuang, X.  Sun, X.  Duan, Nano Res. 2016, 9, 2251. \n[43]\t L.  Hou, Y.  Shi, C.  Wu, Y.  Zhang, Y.  Ma, X.  Sun, J.  Sun, X.  Zhang, C. Yuan, Adv. Funct. Mater. 2018, 28, 1705921. \n[44]\t J.  Lin, H.  Wang, Y.  Yan, X.  Zheng, H.  Jia, J.  Qi, J.  Cao, J.  Tu, W.  Fei, J. Feng, J. Mater. Chem. A 2018, 6, 19151. \n[45]\t M.  Lee, H.  Oh, M. K.  Cho, J.  Ahn, Y. J.  Hwang, B. K.  Min, Appl. Catal., B 2018, 233, 130. \n[46]\t O.  Mabayoje, A.  Shoola, B. R.  Wygant, C. B.  Mullins, ACS Energy Lett. 2016, 1, 195. \n[47]\t R.  Eadha, Y. R.  Kumar, M.  Sakar, K. R.  Vinod, S.  Balakumar, Appl. Catal., B 2018, 225, 386. \n[48]\t B.  Ni, T.  He, J.  Wang, S.  Zhang, C.  Ouyang, Y.  Long, J.  Zhuang, X. Wang, Chem. Sci. 2018, 9, 2762. \n[49]\t F.  Hu, S.  Zhu, S.  Chen, Y.  Li, L.  Ma, T.  Wu, Y.  Zhang, C.  Wang, C.  Liu, X.  Yang, L.  Song, X.  Yang, Y.  Xiong, Adv. Mater. 2017, 29, 1606570. \n[50]\t J. Zhang, Q. Zhang, X. Feng, Adv. Mater. 2019, 1808167. \n[51]\t Z. W. Seh, J. Kibsgaard, C. F. Dickens, I. Chorkendorff, J. K. Nørskov, T. F. Jaramillo, Science 2017, 355, eaad4998. \n[52]\t Q. Qin, L. Chen, T. Wei, X. Liu, Small 2018, 1803639. \n[53]\t R.  Subbaraman, D.  Tripkovic, K.-C.  Chang, D.  Strmcnik, A. P.  Paulikas, P.  Hirunsit, M.  Chan, J.  Greeley, V.  Stamenkovic, N. M. Markovic, Nat. Mater. 2012, 11, 550. \n[54]\t P. Luo, H. Zhang, L. Liu, Y. Zhang, J. Deng, C. Xu, N. Hu, Y. Wang, ACS Appl. Mater. Interfaces 2017, 9, 2500. \n[55]\t Z. Peng, D. Jia, A. M. Al-Enizi, A. A. Elzatahry, G. Zheng, Adv. Energy Mater. 2015, 5, 1402031. \n[56]\t X. Zhang, S. Zhang, J. Li, E. Wang, J. Mater. Chem. A 2017, 5, 22131. \n[57]\t Z.  Zhai, C.  Li, L.  Zhang, H.  Wu, L.  Zhang, N.  Tang, W.  Wang, J. Gong, J. Mater. Chem. A 2018, 6, 9833. \n[58]\t X.  Xiao, D.  Huang, Y.  Fu, M.  Wen, X.  Jiang, X.  Lv, M.  Li, L.  Gao, S. Liu, M. Wang, C. Zhao, Y. Shen, ACS Appl. Mater. Interfaces 2018, 10, 4689. \n[59]\t Q.  Li, D.  Wang, C.  Han, X.  Ma, Q.  Lu, Z.  Xing, X.  Yang, J. Mater. Chem. A 2018, 6, 8233. \n[60]\t E. Hu, Y. Feng, J. Nai, D. Zhao, Y. Hu, X. W. Lou, Energy Environ. Sci. 2018, 11, 872. \n[61]\t J.  Liu, J.  Wang, B.  Zhang, Y.  Ruan, H.  Wan, X.  Ji, K.  Xu, D.  Zha, L. Miao, J. Jiang, J. Mater. Chem. A 2018, 6, 2067. \n[62]\t B. Shang, P. Ma, J. Fan, L. Jiao, Z. Liu, Z. Zhang, N. Chen, Z. Cheng, X. Cui, W. Zheng, Nanoscale 2018, 10, 12330. " + }, + { + "id": "10.1021_acs.chemmater.9b01294", + "DOI": "10.1021/acs.chemmater.9b01294", + "DOI Link": "http://dx.doi.org/10.1021/acs.chemmater.9b01294", + "Relative Dir Path": "mds/10.1021_acs.chemmater.9b01294", + "Article Title": "Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals", + "Authors": "Chen, C; Ye, WK; Zuo, YX; Zheng, C; Ong, SP", + "Source Title": "CHEMISTRY OF MATERIALS", + "Abstract": "Graph networks are a new machine learning (ML) paradigm that supports both relational reasoning and combinatorial generalization. Here, we develop universal MatErials Graph Network (MEGNet) models for accurate property prediction in both molecules and crystals. We demonstrate that the MEGNet models outperform prior ML models such as the SchNet in 11 out of 13 properties of the QM9 molecule data set. Similarly, we show that MEGNet models trained on similar to 60 000 crystals in the Materials Project substantially outperform prior ML models in the prediction of the formation energies, band gaps, and elastic moduli of crystals, achieving better than density functional theory accuracy over a much larger data set. We present two new strategies to address data limitations common in materials science and chemistry. First, we demonstrate a physically intuitive approach to unify four separate molecular MEGNet models for the internal energy at 0 K and room temperature, enthalpy, and Gibbs free energy into a single free energy MEGNet model by incorporating the temperature, pressure, and entropy as global state inputs. Second, we show that the learned element embeddings in MEGNet models encode periodic chemical trends and can be transfer-learned from a property model trained on a larger data set (formation energies) to improve property models with smaller amounts of data (band gaps and elastic moduli).", + "Times Cited, WoS Core": 796, + "Times Cited, All Databases": 903, + "Publication Year": 2019, + "Research Areas": "Chemistry; Materials Science", + "UT (Unique WOS ID)": "WOS:000468242300054", + "Markdown": "# Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals \n\nChi Chen, Weike Ye, Yunxing Zuo, Chen Zheng, and Shyue Ping Ong\\* \n\nDepartment of NanoEngineering, University of California San Diego, 9500 Gilman Dr, Mail Code 0448, La Jolla, California 92093-0448, United States \n\n$\\otimes$ Supporting Information \n\nABSTRACT: Graph networks are a new machine learning (ML) paradigm that supports both relational reasoning and combinatorial generalization. Here, we develop universal MatErials Graph Network (MEGNet) models for accurate property prediction in both molecules and crystals. We demonstrate that the MEGNet models outperform prior ML models such as the SchNet in 11 out of 13 properties of the QM9 molecule data set. Similarly, we show that MEGNet models trained on ${\\sim}60~000$ crystals in the Materials Project substantially outperform prior ML models in the prediction of the formation energies, band gaps, and elastic moduli of crystals, achieving better than density functional theory accuracy over a much larger data set. We present two new strategies to address data limitations common in materials science and chemistry. First, we demonstrate a physically intuitive approach to unify four separate molecular MEGNet models for the internal energy at $0\\mathrm{~K~}$ and room temperature, enthalpy, and Gibbs free energy into a single free energy MEGNet model by incorporating the temperature, pressure, and entropy as global state inputs. Second, we show that the learned element embeddings in MEGNet models encode periodic chemical trends and can be transfer-learned from a property model trained on a larger data set (formation energies) to improve property models with smaller amounts of data (band gaps and elastic moduli). \n\n![](images/9010cd819a0e506d11633eaeba82aa74df0d41917f51ad56d01414233dae067e.jpg) \n\n# INTRODUCTION \n\nMachine learning $(\\mathbf{ML})^{1,2}$ has emerged as a powerful new tool in materials science,3−14 driven in part by the advent of large materials data sets from high-throughput electronic structure calculations15−18 and/or combinatorial experiments.19,20 Among its many applications, the development of fast, surrogate ML models for property prediction has arguably received the most interest for its potential in accelerating materials design21,22 as well as accessing larger length/time scales at near-quantum accuracy.11,23−28 \n\nThe key input to any ML model is a description of the material, which must satisfy the necessary rotational, translational, and permutational invariances as well as uniqueness. For molecules, graph-based representations29 are a natural choice. This graph representation concept has been successfully applied to predict molecular properties.30,31 Recently, Faber et al.32 have benchmarked different features in combination with models extensively on the QM9 data set.33 They showed that the graph-based deep learning models34,35 generally outperform classical ML models with various features. Furthermore, graph-based models are generally less sensitive to the choice of atomic descriptors, unlike traditional feature engineering-based ML models. For example, Schütt et al.10,36 achieved state-of-the-art performance on molecules using only the atomic number and atom coordinates in a graph-based neural network model. Gilmer et al.37 later proposed the message passing neural network (MPNN) framework that includes the existing graph models with differences only in their update functions. \n\nUnlike molecules, descriptions of crystals must account for lattice periodicity and additional space group symmetries. In the crystal graph convolutional neural networks (CGCNNs) proposed by Xie and Grossman,9 each crystal is represented by a crystal graph, and invariance with respect to permutation of atomic indices and unit cell choice are achieved through convolution and pooling layers. They demonstrated excellent prediction performance on a broad array of properties, including formation energy, band gap, Fermi energy, and elastic properties. \n\nDespite these successes, current ML models still suffer from several limitations. First, it is evident that most ML models have been developed on either molecular or crystal data sets. A few notable exceptions are the recently reported SchNet36 and an update of the MPNN,38 which have been tested on both molecules and crystals, respectively, although in both cases performance evaluation on crystals is limited to formation energies only. Second, current models lack a description of global state (e.g., temperature), which are necessary for predicting state-dependent properties such as the free energy. Last but not least, data availability remains a critical bottleneck for training high-performing models for some properties. For example, while there are ${\\sim}69$ 000 computed formation energies in the Materials Project,15 there are only $\\mathord{\\sim}6000$ computed elastic constants. \n\n![](images/fd37bc702c211cd5ac804ab73a3df072db57a3abef7ad957380c4e91d297836d.jpg) \nFigure 1. Overview of a MEGNet module. The initial graph is represented by the set of atomic attributes $V=\\{\\mathbf{v}_{i}\\}_{i=1:N}^{\\mathrm{v}},$ bond attributes $E=\\left\\{\\left(\\mathbf{e}_{k},r_{k},\\right.\\right.$ $s_{k})\\bar{\\}_{k=1:N}^{\\mathrm{e}},$ and global state attributes u. In the first update step, the bond attributes are updated. Information flows from atoms that form the bond, the state attributes, and the previous bond attribute to the new bond attributes. Similarly, the second and third steps update the atomic and global state attributes, respectively, by information flow among all three attributes. The final result is a new graph representation. \n\nIn this work, we aim to address all these limitations. We propose graph networks39 with global state attributes as a general, composable framework for quantitative structure− state−property relationship prediction in materials, that is, both molecules and crystals. Graph networks can be shown to be a generalization/superset of previous graph-based models such as the CGCNN and MPNN; however, because graph networks are not constrained to be neural network-based, they are different from the aforementioned models. We demonstrate that our MatErials Graph Network (MEGNet) models outperform prior ML models in the prediction of multiple properties on the ∼131 000 molecules in the QM9 data set33 and ${\\sim}69~000$ crystals in the Materials Project.15 We also present a new physically intuitive strategy to unify multiple free energy MEGNet models into a single MEGNet model by incorporating state variables such as temperature, pressure, and entropy as global state inputs, which provides for multifold increase in the training data size with minimal increase in the number of model parameters. Finally, we demonstrate how interpretable chemical trends can be extracted from elemental embeddings trained on a large data set, and these elemental embeddings can be used in transfer learning to improve the performance of models with smaller data quantities. \n\n# METHODS \n\nMEGNet Formalism. Graph networks were recently proposed by Battaglia et al.39 as a general, modular framework for ML that supports both relational reasoning and combinatorial generalization. Indeed, graph networks can be viewed as a superset of the previous graph-based neural networks, though the use of neural networks as function approximators is not a prerequisite. Here, we will outline the implementation of MEGNet models for molecules and crystals, with appropriate modifications for the two different material classes explicitly described. Throughout this work, the term “materials” will be used generically to encompass molecules to crystals, while the more precise terms “molecules” and “crystals” will be used to refer to collections of atoms without and with lattice periodicity, respectively. \n\nLet $V,E,$ and u denote the atomic (node/vertex), bond (edge), and global state attributes, respectively. For molecules, bond information (e.g., bond existence, bond order, and so on) is typically provided as part of the input definition. For crystals, a bond is loosely defined between atoms with distance less than certain cutoff. Following the notation of Battaglia et al.,39 $V$ is a set of $\\mathbf{v}_{i},$ which is an atomic attribute vector for atom i in a system of $N^{\\mathrm{v}}$ atoms. $E=\\left\\{\\left(\\mathbf{e}_{k},\\ r_{k},\\right.\\right.$ $s_{k})\\}_{k=1:N}^{\\mathrm{e}}$ are the bonds, where $\\mathbf{e}_{k}$ is the bond attribute vector for bond $k,r_{k}$ and $s_{k}$ are the atom indices forming bond $k,$ and $N^{\\mathrm{e}}$ is the total number of bonds. Finally, $\\mathbf{u}$ is a global state vector storing the molecule/crystal level or state attributes (e.g., the temperature of the system). \n\nA graph network module (Figure 1) contains a series of update operations that map an input graph $G=\\left(E,V,\\mathbf{u}\\right)$ to an output graph $\\bar{G^{\\prime}}=\\left(E^{\\prime},\\ V^{\\prime},\\ \\mathbf{u}^{\\prime}\\right)$ . First, the attributes of each bond $(\\mathbf{e}_{k},\\bar{r}_{k},s_{k})$ are updated using attributes from itself, its connecting atoms (with indices $r_{k}$ and $s_{k},$ , and the global state vector ${\\bf u},$ as follows \n\n$$\n\\mathbf{e}_{k}^{\\prime}=\\phi_{\\mathrm{e}}(\\mathbf{v}_{s_{k}}\\oplus\\mathbf{v}_{r_{k}}\\oplus\\mathbf{e}_{k}\\oplus\\mathbf{u})\n$$ \n\nwhere $\\phi_{\\mathrm{e}}$ is the bond update function and $\\oplus$ is the concatenation operator. Next, the attributes of each atom $\\mathbf{v}_{i}$ are updated using attributes from itself, the bonds connecting to it, and the global state vector $\\mathbf{u}$ , as follows \n\n$$\n\\overline{{\\mathbf{v}}}_{i}^{\\mathrm{e}}=\\frac{1}{N_{i}^{\\mathrm{e}}}\\sum_{k=1}^{N_{i}^{\\mathrm{e}}}\\left\\{\\mathbf{e}_{k}^{\\prime}\\right\\}_{r_{k}=i}\n$$ \n\n$$\n\\mathbf{v}_{i}^{\\prime}=\\phi_{\\mathrm{v}}(\\overline{{\\mathbf{v}}}_{i}^{\\mathrm{e}}\\oplus\\mathbf{v}_{i}\\oplus\\mathbf{u})\n$$ \n\nwhere $N_{i}^{\\mathrm{e}}$ is the number of bonds connected to atom i and $\\phi_{\\mathrm{v}}$ is the atom update function. The aggregation step (eq 2) acts as a local pooling operation that takes the average of bonds that connect to the atom i. \n\nThe first two update steps contain localized convolution operations that rely on the atom-bond connectivity. One can imagine that if more graph network modules are stacked, atoms and bonds will be able to “see” longer distances, and hence, longer-range interactions can be incorporated even if the initial distance cutoff is small to reduce the computational task. \n\nFinally, the global state attributes u are updated using information from itself and all atoms and bonds, as follows \n\n$$\n\\begin{array}{l}{{\\displaystyle{{\\overline{{\\mathbf{u}}}}^{\\mathrm{e}}}=\\frac{1}{N^{\\mathrm{e}}}\\sum_{k=1}^{N^{\\mathrm{e}}}\\left\\{\\mathbf{e}_{k}^{\\prime}\\right\\}}}\\\\ {{\\displaystyle{\\overline{{\\mathbf{u}}}^{\\mathrm{v}}}=\\frac{1}{N^{\\mathrm{v}}}\\sum_{i=1}^{N^{\\mathrm{v}}}\\left\\{\\mathbf{v}_{i}^{\\prime}\\right\\}}}\\end{array}\n$$ \n\n$$\n\\mathbf{u}^{\\prime}=\\phi_{\\mathrm{u}}(\\bar{\\mathbf{u}}^{\\mathrm{e}}\\oplus\\bar{\\mathbf{u}}^{\\mathrm{v}}\\oplus\\mathbf{u})\n$$ \n\nwhere $\\phi_{\\mathrm{u}}$ is the global state update function. In addition to providing a portal to input state attributes (e.g., temperature), $\\mathbf{u}$ also acts as the global information placeholder for information exchange on larger scales. \n\nThe choice of the update functions $\\phi_{\\mathrm{e}},\\ \\phi_{\\mathrm{v}},$ and $\\phi_{\\mathrm{u}}$ largely determines the model performance in real tasks. In this work, we choose the $\\phi\\mathbf{s}$ to be multilayer perceptrons with two hidden layers (eq 7), given their ability to be universal approximators for nonlinear functions.40 \n\n$$\n\\boldsymbol{\\Phi}(\\mathbf{x})=\\mathbf{W}_{3}(\\zeta(\\mathbf{W}_{2}(\\zeta(\\mathbf{W}_{1}\\mathbf{x}+\\mathbf{b}_{1}))+\\mathbf{b}_{2}))+\\mathbf{b}_{3}\n$$ \n\nwhere $\\zeta$ is the modified softplus function10 acting as a nonlinear activator, Ws are the kernel weights, and bs are the biases. Note that the weights for atom, bond, and state updates are different. Each fully connected layer will be referred to as a “dense” layer using keras terminology. \n\nTo increase model flexibility, two dense layers are added before each MEGNet module to preprocess the input. This approach has been found to increase model accuracy. We define the combination of the two dense layers with a MEGNet module as a MEGNet block, as shown in Figure 2. The block also contains residual netlike42 skip connections to enable deeper model training and reduce over-fitting. Multiple MEGNet blocks can be stacked to make more expressive models. In the final step, a readout operation reduces the output graph to a scalar or vector. In this work, the order-invariant set2set model43 that embeds a set of vectors into one vector is applied on both atomic and bond attribute sets. After the readout, the atomic, bond, and state vectors are concatenated and passed through multilayer perceptrons to generate the final output. The overall model architecture is shown in Figure 2. If the atom features are only the integer atomic numbers, an embedding layer is added after the atom inputs $V.$ . \n\n![](images/541bcfc25d724d1167e12d124fa10021954dee2401f80f53d51e719365edae91.jpg) \nFigure 2. Architecture for the MEGNet model. Each model is formed by stacking MEGNet blocks. The embedding layer is used when the atom attributes are only atomic numbers. In the readout stage, a set2set neural network is used to reduce sets of atomic and bond vectors into a single vector. The numbers in brackets are the number of hidden neural units for each layer. Each MEGNet block contains a MEGNet layer as well as two dense layers. The “add” arrows are skip connections to enable deep model training. \n\nAtomic, Bond, and State Attributes. Table 1 summarizes the full set of atomic, bond, and state attributes used as inputs to the MEGNet models. The molecule attributes are similar to the ones used in the benchmarking work by Faber et al.32 For crystals, only the atomic number and spatial distance are used as atomic and bond attributes, respectively. \n\nTable 1. Atomic, Bond, and State Attributes Used in the Graph Network Models \n\n\n
systemlevelattributes name description
moleculeatomatom typeH, C, O, N, F (one-hot)
chirality ring sizesR or S (one-hot or null) for each ring size (3-8), the number
of rings that include this atom. If the atom is not in a ring, this field
hybridizationis null sp,sp², sp3 (one-hot or null)
donoracceptorwhether the atom is an electron acceptor (binary) whether the atom donates electrons
(binary) whether the atom belongs to an
bondaromatic bond typearomatic ring (binary) single, double, triple, or aromatic
(one-hot or null) whether the atoms in the bond are in
same ring graph distancethe same ring (binary) shortest graph distance between atoms (1-7). This is a topological
distance. For example, a value of 1 means that the two atoms are nearest neighbors, whereas a value of 2 means they are second nearest neighbors, etc. distance r valued on Gaussian basis
statedistanceexp(-(r - ro)²/o²), where ro takes values at 20 locations linearly placed between O and 4, and the width o = 0.5
average atomic weight bonds permolecular weight divided by the number of atoms (float) average number of bonds per atom
systemattributesatom(float)
crystallevel atom Znamedescription the atomic number of element (1-94)
bond spatialexpanded distance with Gaussian basis exp(-(r - ro)2/o2) centered at 100 points
distance 0 = 0.5linearly placed between O and 5 and
statetwo zerosplaceholder for global information exchange
\n\nData Collections. The molecule data set used in this work is the QM9 data set33 processed by Faber et al.32 It contains the B3LYP/6- $31\\mathrm{G}(2\\mathrm{df,p})$ -level density functional theory (DFT) calculation results on $130~462$ small organic molecules containing up to 9 heavy atoms. \n\nThe crystal data set comprises the DFT-computed energies and band gaps of $69640$ crystals from the Materials Project15 obtained via the Python Materials Genomics (pymatgen)44 interface to the Materials Application Programming Interface (API)45 on June 1, 2018. We will designate this as the MP-crystals-2018.6.1 data set to facilitate future benchmarking and comparisons as data in the Materials Project is constantly being updated. The crystal graphs were constructed using a radius cutoff of $\\mathbf{\\hat{4}}\\ \\hat{\\mathbf{A}}.$ Using this cutoff, 69 239 crystals do not form isolated atoms and are used in the models. All crystals were used for the formation energy model and the metal against the nonmetal classifier, while a subset of 45 901 crystals with a finite band gap was used for the band gap regression. A subset of 5830 structures have elasticity data that do not have calculation warnings and will be used for elasticity models. \n\nModel Construction and Training. A customized Python version of MEGNet was developed using the keras $\\mathrm{API}^{41}$ with the tensorflow backend.46 Because molecules and crystals do not have the same number of atoms, we assemble batches of molecules/crystals \n\nTable 2. Comparison of MAEs of 13 Properties in the QM9 Data Set for Different Modelsa,b \n\n\n
MEGNet-full° MEGNet-simpled
propertyunits(this work)(this work) SchNet36enn-s2s37 benchmark32 target
EHOMOeV0.038±0.0010.0430.0410.0430.055℃0.043
ELUMOeV0.031±0.0000.0440.0340.0370.064e0.043
eV0.061±0.0010.0660.0630.0690.087e0.043
ZPVEmeV1.40±0.061.431.71.51.9g1.2
μD0.040 ± 0.0010.0500.0330.0300.101℃0.1
αbohr30.083±0.0010.0810.2350.0920.1610.1
(R²)bohr²0.265 ± 0.0010.3020.0730.1801.2
U。eV0.009±0.0000.0120.0140.0190.025g0.043
UeV0.010±0.0000.0130.0190.0190.043
HeV0.010±0.0000.0120.0140.0170.043
GeV0.010±0.0000.0120.0140.0190.043
C,cal (mol K)-10.030±0.0010.0290.0330.0400.044%0.05
cm-11.10±0.081.181.92.71h10
\n\naThe “benchmark” column refers to the best model in the work by Faber et al.,32 and the “target” column refers to the widely accepted thresholds for “chemical accuracy”.32 The standard deviations in the MAEs for the MEGNet-full models over three randomized training:validation:test splits are also provided. $^{b}\\epsilon_{\\mathrm{HOMO}}$ : highest occupied molecular orbital; $\\epsilon_{\\mathrm{LUMO}}$ : lowest unoccupied molecular orbital; $\\Delta\\epsilon$ : energy gap; ZPVE: zero-point vibrational energy; $\\mu$ : dipole moment; $\\alpha$ : isotropic polarizability; $\\big$ : electronic spatial extent; $U_{0}$ : internal energy at $0\\mathrm{K};$ U: internal energy at 298 $\\operatorname{K};H$ : enthalpy at $298\\ \\mathrm{K}$ ; G: Gibbs free energy at 298 K; $C_{\\nu}$ : heat capacity at $298\\ \\mathrm{K};$ ; $\\omega_{1}$ : highest vibrational frequency. cFull MEGNet models using all listed features in Table 1. The optimized models for ZPVE, $\\big,\\mu,$ and $\\omega_{1}$ contain five, five, three, and one MEGNet blocks, respectively, while the optimized models for all other properties use two MEGNet blocks. dSimple MEGNet models using only the atomic number as the atomic feature, expanded distance as bond features, and no dummy state features. All models contain three MEGNet blocks. eGraph convolution with a molecular graph feature.34 fGated-graph neural network with a molecular graph feature.35 gKernel-ridge regression with histograms of distances, angles, and dihedrals. hRandom forest model with bonds, angles, ML feature. \n\ninto a single graph with multiple targets to enable batch training. The Adam optimizer47 was used with an initial learning rate of 0.001, which is reduced to 0.0001 during later epochs for tighter convergence. \n\nEach data set is divided into three partstraining, validation, and test. For the molecule models, $90\\%$ of the data set was used for training and the remaining were divided equally between validation and test. For the crystal formation energy models, $60~000$ crystals were used for training and the remaining were divided equally between validation and test for direct comparison to the work of Schütt et al.36 For the band gap classification models and elastic moduli models, an 80:10:10 split was applied. All models were trained on the training set, and the configuration and hyperparameters with the lowest validation error were selected. Finally, the test error is calculated. During training, the validation error is monitored and the training is stopped when the validation error does not improve for 500 consecutive epochs. The models were trained on Nvidia GTX 1080Ti GPUs. On average, it takes $80~\\mathrm{s}$ and $110\\mathrm{~s~}$ per epoch for each molecular and crystal model, respectively. Most models reach convergence within 1000 epochs. However, models for $U_{0},U,H,G,$ and $\\langle\\check{R}^{2}\\rangle$ require 2000−4000 epochs. The embedding dimension is set to 16. The elemental embeddings trained on the formation energy using one MEGNet block were transferred to the band gap regression model and kept fixed. We use the same architecture featuring three MEGNet blocks in the models for crystals. \n\nData and Model Availability. To ensure reproducibility of the results, the MP-crystals-2018.6.1 data set used in this work has been made available as a JavaScript Object Notation file at https://figshare. com/articles/Graphs_of_materials_project/7451351. The graph network modules and overall models have also been released as opensource code in a Github repository at https://github.com/ materialsvirtuallab/megnet. \n\n# RESULTS \n\nPerformance on QM9 Molecules. Table 2 shows the comparison of the mean absolute errors (MAEs) of 13 properties for the different models, and the convergence plots with the number of training data are shown in Figure S1. It can be seen that the MEGNet models using the full set of attributes (“full” column in Table 2) outperform the state-of-art SchNet36 and MPNN enn-s2s models37 in all but two of the propertiesthe norm of dipole moment $\\mu$ and the electronic spatial extent $R^{2}$ . Out of 13 properties, only the errors on zeropoint vibrational energy (ZPVE) $\\left(1.40\\mathrm{\\meV}\\right)$ and band gap $\\bar{(}\\Delta\\epsilon)$ $\\left(0.060~\\mathrm{eV}\\right)$ exceed the thresholds for chemical accuracy. The errors of various properties follow Gaussian distributions, as shown in Figure S2. \n\nWe note that the atomic and bond attributes in Table 1 encode redundant information. For example, the bond type can usually be inferred from the bonding atoms and the spatial distance. We therefore developed “simple” MEGNet models that utilize only the atomic number and spatial distance as the atomic and bond attributes, respectively. These are the same attributes used in the crystal MEGNet models. From Table 2, we may observe that these simple MEGNet models achieve largely similar performance as the full models, with only slightly higher MAEs that are within chemical accuracy and still outperforming prior state-of-the-art models in 8 of the 13 target properties. It should be noted, however, that the convergence of the “simple” models is slower than the “full” models for certain properties (e.g., $\\mu_{\\mathrm{-}}$ ZVPE). This may be due to the models having to learn more complex relationships between the inputs and the target properties. \n\nUnified Molecule Free Energy Model. To achieve the results presented in Table 2, one MEGNet model was developed for each target, similar to previous works.36,37 However, this approach is extremely inefficient when multiple targets are related by a physical relationship and should share similar features. For instance, the internal energy at 0 K $\\left(U_{0}\\right)$ and room temperature $(U)$ , enthalpy $\\left(H=U+{\\dot{P}}V\\right)$ , and Gibbs free energy $\\ ^{\\prime}G=U+P V-T S)$ are all energy quantities that are related to each other by temperature $(\\bar{T})$ , pressure $(P)$ , volume $(V)$ , and entropy (S). To illustrate this concept, we have developed a combined free energy model for $U_{0},U,H,$ and $G$ for the QM9 data set by incorporating the temperature, pressure (binary), and entropy (binary) as additional global state attributes in $\\mathbf{u},$ , that is, $(0,0,0)$ , (298, 0, 0), (298, 1, 0), and (298, 1, 1) for $U_{0},U,H,$ and $G_{;}$ , respectively. Using the same architecture, this combined free energy model achieves an overall MAE of $0.010\\ \\mathrm{~eV}$ for the four targets, which is comparable to the results obtained using the separate MEGNet models for each target. \n\nIn principle, the combined free energy model should be able to predict free energies at any temperature given sufficient training data. Indeed, the predicted $U$ at 100 and $200\\mathrm{~K~}$ matches well with our DFT calculations (see Figure S3), even though these data points were not included in the training data. However, the predicted $H$ and $G$ at the same temperatures show large deviations from the DFT results. We hypothesize that this is due to the fact that only one temperature data for these quantities exist in the training data and that the addition of $H$ and $G$ data at multiple temperatures into the training data would improve the performance of the unified free energy MEGNet model. \n\nPerformance on Materials Project Crystals. Table 3 shows the comparison of the performance of the MEGNet models against the SchNet36 and CGCNN models.9 The convergence of formation energy model is shown in Figure S4. We may observe that the MEGNet models outperform both the SchNet and CGCNN models in the MAEs of the formation energies $E_{\\mathrm{f}}$ band gap $E_{\\mathrm{g}},$ bulk modulus $K_{\\mathrm{VRH}},$ and shear modulus $G_{\\mathrm{VRH}}.$ . It should be noted that these results especially the prediction of $E_{\\mathrm{g}}$ and the metal/nonmetal classifiersare achieved over much diverse data sets than previous works, and the prediction error in $E_{\\mathrm{f}},E_{\\mathrm{g}},K_{\\mathrm{VRH}},$ and GVRH is well within the DFT errors in these quantities.48−52 The MEGNet models, similar to the SchNet models, utilize only one atomic attribute (atomic number) and one bond attribute (spatial distance), while nine attributes were used in the CGCNN model. We also found that transferring the elemental embeddings from the $E_{\\mathrm{f}}$ model, which was trained on the largest data set, significantly accelerates the training and improves the performance of the $E_{\\mathrm{g}},$ $K_{\\mathrm{VRH}},$ and $G_{\\mathrm{VRH}}$ models. For example, an independently trained model (without transfer learning) for $E_{\\mathrm{g}}$ has a higher MAE of $0.38\\ \\mathrm{eV}$ . \n\nTable 3. Comparison of the MAEs in the Formation Energy $E_{\\mathrm{f}}$ Band Gap $E_{\\mathrm{g}},$ Bulk Modulus $K_{\\mathrm{VRH}},$ Shear Modulus ${\\cal G}_{\\mathrm{VRH}},$ and Metal/Nonmetal Classification between MEGNet Models and Prior Works on the Materials Project Data Seta \n\n\n
unitsMEGNet SchNet36CGCNN9
elements898987
EfeV atom-10.028 ± 0.000 (60 000)0.035 (60 000)0.039 (28 046)
eV0.33 ± 0.01 (36 720)0.388 (16 485)
KVRHlog1o (GPa)0.050 ± 0.002 (4664)0.054 (2041)
GVRHlog1o (GPa)0.079 ± 0.003 (4664)0.087 (2041)
metal classifier78.9% ± 1.2% (55391)80% (28 046)
nonmetal classifier90.6% ± 0.7% (55 391)95% (28 046)
\n\naThe number of structures in the training data is in parentheses. The standard deviations in the MAEs for the MEGNet models over three randomized training:validation:test splits are also provided. \n\nWe note that the data set used in the development of the CGCNN model is significantly smaller than that of MEGNet or SchNet, despite all three models having obtained their data from the Materials Project. The reason is that crystals with warning tags or without band structures were excluded from the CGCNN model training. Using this exclusion strategy and a similar training data size, the MEGNet models for formation energy and band gap have MAEs of $0.032\\ \\mathrm{eV}$ atom−1 and 0.35 eV, respectively. The accuracies for metal and nonmetal classifiers are increased to 82.7 and $93.1\\%$ , respectively. \n\nThere are also nongraph-based crystal ML models such as the JARVIS-ML model53 and the AFLOW-ML model.54 The MAEs of the JARVIS-ML models53 for formation energy, band gap, bulk moduli, and shear moduli are $0.12~\\mathrm{eV~atom}^{-1}$ , 0.32 eV, $10.5\\ \\mathrm{GPa},$ , and $9.5\\ \\mathrm{GPa}$ , respectively, while the MAEs of AFLOW-ML models54 for band gap, bulk moduli, and shear moduli are 0.35 eV, $8.68\\ \\mathrm{GPa}_{,}$ , and $10.62~\\mathrm{GPa}_{.}$ , respectively. However, these ML models are developed with very different data sets (e.g., the JARVIS-DFT database contains formation energies, elastic constants, and band gaps for bulk and 2D materials computed using different functionals) and are therefore not directly comparable to the MEGNet, SchNet, or CGCNN models, which are all trained using Materials Project data. \n\nFigure 3a,b provides a detailed analysis of the MEGNet model performance on $E_{\\mathrm{f}}$ The parity plot (Figure 3a) shows that the training and test data are similarly well-distributed, and consistent model performance is achieved across the entire range of $E_{\\mathrm{f}}$ We have performed a sensitivity analysis of our MEGNet $E_{\\mathrm{f}}$ model to various hyperparameters. Increasing the radius cutoff to $6\\textup{\\AA}$ slightly increases the MAE to $0.03\\ \\mathrm{eV}$ atom−1. Using one or five MEGNet blocks instead of three results in MAEs of 0.033 and $0.027~\\mathrm{eV~atom}^{-1}$ , respectively. Hence, we can conclude that our chosen radius cutoff of 4 Å and model architecture comprising three MEGNet blocks are reasonably well-optimized. Figure 3b plots the average test MAEs for each element against the number of training structure containing that element. In general, the greater the number of training structures, the lower the MAE for structures containing that element. Figure 3c shows the receiver operating characteristic (ROC) curve for the metal/ nonmetal classifier. The overall test accuracy is $86.9\\%$ , and the area under curve for the receiver operation conditions is 0.926. \n\n![](images/158413294f023af0d634dc8d97928a27522d0f05025b939f18a47f2fa71bbcb0.jpg) \nFigure 3. Performance of MEGNet models on the Materials Project data set. (a) Parity plots for the formation energy of the training and test data sets. (b) Plot of average MAE for each element against the number of training structures containing that element. (c) ROC curve for test data for the MEGNet classifier trained to distinguish metals against nonmetals. \n\n# DISCUSSION \n\nIt is our belief that the separation of materials into molecules and crystals is largely arbitrary, and a true test of any structured representation is its ability to achieve equally good performance in property prediction in both domains. We have demonstrated that graph networks, which provide a natural framework for representing the attributes of atoms and the bonds between them, are universal building blocks for highly accurate prediction models. Our MEGNet models, built on graph network concepts, show significantly improved accuracies over prior models in most properties for both molecules and crystals. \n\nA key advance in this work is the demonstration of the incorporation of global state variables to build unified models for related properties. A proof of concept is shown in our unified molecule free energy MEGNet model, which can successfully predict the internal energy at multiple temperatures, enthalpy, and Gibbs free energy with temperature, entropy, and pressure as global state variables. This stands in sharp contrast to the prevailing approach in the materials ML community of building single-purpose models for each quantity, even if they are related to each other by wellknown thermodynamic relationships. The unification of related models has significant advantages in that one can achieve multifold increases in training data with minimal increase in model complexity, which is particularly important given the relatively small data sets available in materials science. \n\nInterpretability. For chemistry and materials science applications, a particularly desirable feature for any representation is interpretability and reproduction of known chemistry intuition.55 To this end, we have extracted the elemental embeddings from the MEGNet model for crystal formation energy. As shown in Figure 4, the correlations between the elemental embeddings correctly recover the trends in the periodic table of the elements. For example, the alkaline, alkali, chalcogen, halogen, lanthanoid, transition metals, posttransition metals, metalloid, and actinoid show highest similarities within their groups. It is important to note that the extracted trends reproduce well-known “exceptions” in the periodic arrangement of atoms as well. For example, the fact that Eu and Yb do not follow the lanthanoids but are closer to alkaline earth elements (Figure S6) is in good agreement with chemical intuition and matches well with the structure graphs proposed by Pettifor.56 Furthermore, these trends are obtained from the diverse Materials Project dataset encompassing most known crystal prototypes and 89 elements, rather than being limited to specific crystal systems.57,58 \n\nSuch embeddings obtained from formation energy models are particularly useful for the development of models to predict stable new compounds or as features for other ML models. Hautier et al.59 previously developed an ionic substitution prediction algorithm using data mining, which has been used successfully in the discovery of several new materials.60,61 The ion similarity metric therein is purely based on the presence of ions in a given structural prototype, a slightly coarse-grained description. Here, the MEGNet models implicitly incorporate the local environment of the site and should in principle better describe the elemental properties and bonding relationships. We note that with more MEGNet blocks, the contrast of the embeddings between atoms is weaker, as shown in Figure S5. The two-dimensional t-SNE plots62 confirm these conclusions, as shown in Figure S6. This is because with more blocks, the environment seen by the atom spans a larger spatial region, and the impact of geometry becomes stronger, which obscures the chemical embeddings. \n\n![](images/bfe6afefeb19eb5d6e03f0e6b54dc9a13f1cadff9406cd3b38c2d4117a297cd5.jpg) \nFigure 4. Pearson correlations between elemental embedding vectors. Elements are arranged in order of increasing Mendeleev number56 for easier visualization of trends. \n\nComposability. A further advantage of the graph networkbased approach is its modular and composable nature. In our MEGNet architecture, a single block captures the interactions between each atom and its immediate local environment (defined via specified bonds in the molecule models and a radius cutoff in the crystal models). Stacking multiple blocks allows for information flow and hence capturing of interactions, across larger spatial distances. \n\nWe can see this effect in the MEGNet models for the QM9 data set, where different numbers of blocks are required to obtain good accuracy for different properties. For most properties, two blocks are sufficient to achieve MAEs within chemical accuracy. However, more blocks are necessary for the ZPVE (five), electronic spatial extent (five), and dipole moment (three), which suggests that it is important to capture longer-ranged interactions for these properties. In essence, the choice of number of MEGNet blocks for a particular property model boils down to a consideration of the range of interactions necessary for accurate prediction, or simply increasingly the number of blocks until convergence in accuracy is observed. \n\nData Limitations and Transfer Learning. The critical bottleneck in building graph networks models, like all other ML models, is data availability. For instance, we believe that the inability of the unified free energy MEGNet model to accurately predict $H$ and $G$ at 100 and $200~\\mathrm{K}$ is largely due to the lack of training data at those temperatures. Similarly, a general inverse relationship can be seen between the number of training structures and the average MAE in formation energies of the crystals in Figure 3b. \n\nBesides adding more data (which is constrained by computational cost as well as chemistry considerations), another avenue for improvement is to use ensemble models. We tested this hypothesis by training two independent three block MEGNet models and used the average as the ensemble prediction for the formation energies of the Materials Project data set. The MAE reduces from $\\bar{0}.028\\ \\mathrm{eV\\atom^{-1}}$ for a single MEGNet model to 0.024 eV atom−1 for the ensemble MEGNet model. \n\nYet, another approach to address data limitations is transfer learning,63,64 and we have demonstrated an instructive example of how this can be applied in the case of the crystal MEGNet models. Data quantity and quality is a practical problem for many materials properties. Using the Materials Project as an example, the formation energy data set comprises ${\\sim}69\\ 000$ crystals, that is, almost all computed crystals in the database. However, only about half of these have nonzero band gaps. Less than $10\\%$ crystals in Materials Project have computed elastic constants because of the high computational effort in obtaining these properties. By transferring the elemental embeddings, which encode the learned chemical trends from the much larger formation energy data set, we were able to efficiently train the band gap and elastic moduli MEGNet models and achieve significantly better performance than prior ML models. We believe this to be a particularly effective approach that can be extended to other materials properties with limited data availability. \n\n# CONCLUSIONS \n\nTo conclude, we have developed MEGNet models that are universally high performing across a broad variety of target properties for both molecules and crystals. Graphs are a natural choice of representation for atoms and the bonds between them, and the sequential update scheme of graph networks provides a natural approach for information flow among atoms, bonds, and global state. Furthermore, we demonstrate two advancesincorporation of global state inputs and transfer learning of elemental embeddingsin this work that extend these models further to state-dependent and data-limited properties. These generalizations address several crucial limitations in the application of ML in chemistry and materials science and provide a robust foundation for the development of general property models for accelerating materials discovery. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.chemmater.9b01294. \n\nConvergence of MEGNet models for the QM9 data set; MEGNet error distributions on the QM9 dataset; QM9 energy predictions at different temperatures; convergence of the MEGNet model for Materials Project formation energy; elemental embeddings for one and five MEGNet block models; and t-SNE visualization of elemental embeddings for one, three, and five MEGNet block models (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author \n$^{*}\\mathrm{E}$ -mail: ongsp@eng.ucsd.edu. \nORCID \nChi Chen: 0000-0001-8008-7043 \nShyue Ping Ong: 0000-0001-5726-2587 \nNotes \nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work is supported by the Samsung Advanced Institute of Technology (SAIT)’s Global Research Outreach (GRO) Program. The authors also acknowledge data and software resources provided by the Materials Project, funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under contract no. DE-AC02-05-CH11231: Materials Project program KC23MP, and computational resources provided by Triton Shared Computing Cluster (TSCC) at the University of California, San Diego, the National Energy Research Scientific Computing Centre (NERSC), and the Extreme Science and Engineering Discovery Environment (XSEDE) supported by National Science Foundation under grant no. ACI-1053575. \n\n# REFERENCES \n\n(1) Michalski, R. S.; Carbonell, J. G.; Mitchell, T. M. Machine Learning: An Artificial Intelligence Approach; Springer Science & Business Media, 2013. \n(2) LeCun, Y.; Bengio, Y.; Hinton, G. Deep learning. Nature 2015, 521, 436. \n(3) Mueller, T.; Kusne, A. G.; Ramprasad, R. Machine Learning in Materials Science. Recent Progress and Emerging Applications; John Wiley & Sons, Inc., 2016; Vol. 29, pp 186−273. \n(4) Ramprasad, R.; Batra, $\\mathrm{R.},$ Pilania, G.; Mannodi-Kanakkithodi, A.; Kim, C. Machine learning in materials informatics: recent applications and prospects. npj Comput. Mater. 2017, 3, 54. \n(5) Pilania, G.; Wang, C.; Jiang, X.; Rajasekaran, S.; Ramprasad, R. Accelerating materials property predictions using machine learning. Sci. Rep. 2013, 3, 2810. \n(6) Ward, L.; Agrawal, A.; Choudhary, A.; Wolverton, C. A generalpurpose machine learning framework for predicting properties of inorganic materials. npj Comput. Mater. 2016, 2, 16028. \n(7) Rupp, M.; Tkatchenko, A.; Müller, K.-R.; Von Lilienfeld, O. A. Fast and accurate modeling of molecular atomization energies with machine learning. Phys. Rev. Lett. 2012, 108, 058301. \n(8) Hautier, G.; Fischer, C. C.; Jain, A.; Mueller, T.; Ceder, G. Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory. Chem. Mater. 2010, 22, 3762−3767. \n(9) Xie, T.; Grossman, J. C. Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties. Phys. Rev. Lett. 2018, 120, 145301. \n(10) Schütt, K. T.; Arbabzadah, F.; Chmiela, S.; Müller, K. R.; Tkatchenko, A. Quantum-chemical insights from deep tensor neural networks. Nat. Commun. 2017, 8, 13890. \n(11) Bartók, A. P.; Payne, M. C.; Kondor, ${\\mathrm{R}}.{\\mathrm{}}{\\mathrm{}}$ Csányi, G. Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons. Phys. Rev. Lett. 2010, 104, 136403. \n\n(12) Butler, K. T.; Davies, D. W.; Cartwright, H.; Isayev, O.; Walsh, A. Machine learning for molecular and materials science. Nature 2018, 559, 547. (13) Ye, W.; Chen, C.; Wang, Z.; Chu, I.-H.; Ong, S. P. Deep neural networks for accurate predictions of crystal stability. Nat. Commun. 2018, 9, 3800. (14) Bartók, A. P.; De, S.; Poelking, C.; Bernstein, N.; Kermode, J. R.; Csányi, G.; Ceriotti, M. Machine learning unifies the modeling of materials and molecules. Sci. Adv. 2017, 3, e1701816. (15) Jain, A.; Ong, S. P.; Hautier, G.; Chen, W.; Richards, W. D.; Dacek, S.; Cholia, S.; Gunter, D.; Skinner, D.; Ceder, G.; Persson, K. A. Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater. 2013, 1, 011002. (16) Saal, J. E.; Kirklin, S.; Aykol, M.; Meredig, B.; Wolverton, C. Materials design and discovery with high-throughput density functional theory: the open quantum materials database (OQMD). JOM 2013, 65, 1501−1509. (17) Curtarolo, S.; Setyawan, W.; Hart, G. L. W.; Jahnatek, M.; Chepulskii, R. V.; Taylor, R. H.; Wang, S.; Xue, J.; Yang, K.; Levy, O.; Mehl, M. J.; Stokes, H. T.; Demchenko, D. O.; Morgan, D. AFLOW: an automatic framework for high-throughput materials discovery. Comput. Mater. Sci. 2012, 58, 218−226. (18) NOMAD. 2011, http://nomad-repository.eu (Online; accessed Nov 28, 2018). (19) Chan, E. M. Combinatorial approaches for developing upconverting nanomaterials: high-throughput screening, modeling, and applications. Chem. Soc. Rev. 2015, 44, 1653−1679. (20) Xiang, C.; Suram, S. K.; Haber, J. A.; Guevarra, D. W.; Soedarmadji, E.; Jin, J.; Gregoire, J. M. High-throughput bubble screening method for combinatorial discovery of electrocatalysts for water splitting. ACS Comb. Sci. 2014, 16, 47−52. (21) Mansouri Tehrani, A.; Oliynyk, A. O.; Parry, M.; Rizvi, Z.; Couper, S.; Lin, F.; Miyagi, L.; Sparks, T. D.; Brgoch, J. Machine learning directed search for ultraincompressible, superhard materials. J. Am. Chem. Soc. 2018, 140, 9844−9853. (22) Oliynyk, A. O.; Mar, A. Discovery of intermetallic compounds from traditional to machine-learning approaches. Acc. Chem. Res. 2017, 51, 59−68. (23) Behler, J.; Parrinello, M. Generalized neural-network representation of high-dimensional potential-energy surfaces. Phys. Rev. Lett. 2007, 98, 146401. (24) Deringer, V. L.; Pickard, C. J.; Csányi, G. Data-driven learning of total and local energies in elemental boron. Phys. Rev. Lett. 2018, 120, 156001. (25) Thompson, A. P.; Swiler, L. P.; Trott, C. R.; Foiles, S. M.; Tucker, G. J. Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials. J. Comput. Phys. 2015, 285, 316−330. (26) Wood, M. A.; Thompson, A. P. Quantum-accurate Molecular Dynamics Potential for Tungsten. 2017, arXiv:1702.07042. arXiv.org e-Print archive, https://arxiv.org/abs/1702.07042 (accessed June 1, 2018). (27) Artrith, N.; Urban, A.; Ceder, G. Efficient and accurate machine-learning interpolation of atomic energies in compositions with many species. Phys. Rev. B 2017, 96, 014112. (28) Chen, C.; Deng, Z.; Tran, R.; Tang, H.; Chu, I.-H.; Ong, S. P. Accurate force field for molybdenum by machine learning large materials data. Phys. Rev. Mater. 2017, 1, 043603. (29) Bonchev, D. Chemical Graph Theory: Introduction and Fundamentals; CRC Press, 1991; Vol. 1. (30) Duvenaud, D. K.; Maclaurin, D.; Iparraguirre, J.; Bombarell, R.; Hirzel, T.; Aspuru-Guzik, A.; Adams, R. P. Convolutional networks on graphs for learning molecular fingerprints. Adv. Neural Info. Proces. Syst. 2015, 2224−2232. (31) Coley, C. W.; Barzilay, R.; Green, W. H.; Jaakkola, T. S.; Jensen, K. F. Convolutional embedding of attributed molecular graphs for physical property prediction. J. Chem. Info. Model. 2017, 57, 1757−1772. \n\n(32) Faber, F. A.; Hutchison, L.; Huang, B.; Gilmer, J.; Schoenholz, S. S.; Dahl, G. E.; Vinyals, O.; Kearnes, S.; Riley, P. F.; von Lilienfeld, O. A. Prediction errors of molecular machine learning models lower than hybrid DFT error. J. Chem. Theory Comput. 2017, 13, 5255− 5264. \n(33) Ramakrishnan, R.; Dral, P. O.; Rupp, M.; Von Lilienfeld, O. A. Quantum chemistry structures and properties of 134 kilo molecules. Sci. Data 2014, 1, 140022. \n(34) Kearnes, S.; McCloskey, K.; Berndl, M.; Pande, V.; Riley, P. Molecular graph convolutions: moving beyond fingerprints. J. Comp. Aid. Mol. Design 2016, 30, 595−608. \n(35) Li, Y.; Tarlow, D.; Brockschmidt, M.; Zemel, R. Gated Graph Sequence Neural Networks. 2015, arXiv:1511.05493. arXiv.org ePrint archive. https://arxiv.org/abs/1511.05493 (accessed June 1, 2018). \n(36) Schütt, K. T.; Sauceda, H. E.; Kindermans, P.-J.; Tkatchenko, A.; Müller, K.-R. SchNet - A deep learning architecture for molecules and materials. J. Chem. Phys. 2018, 148, 241722. \n(37) Gilmer, J.; Schoenholz, S. S.; Riley, P. F.; Vinyals, O.; Dahl, G. E. Neural Message Passing for Quantum Chemistry. 2017, arXiv:1704.01212. arXiv.org e-Print archive, https://arxiv.org/abs/ 1704.01212 (accessed July 23, 2018). \n(38) Jørgensen, P. B.; Jacobsen, K. W.; Schmidt, M. N. Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials. 2018, arXiv:1806.03146. arXiv.org e-Print archive, https://arxiv.org/abs/1806.03146 (accessed Dec 20, 2018). (39) Battaglia, P. W.; et al. Relational Inductive Biases, Deep Learning, and Graph Networks. 2018, arXiv:1806.01261. arXiv.org ePrint archive, https://arxiv.org/abs/1806.01261 (accessed May 30, 2018). \n(40) Hornik, K.; Stinchcombe, M.; White, H. Multilayer feedforward networks are universal approximators. Neural Networks 1989, 2, 359− 366. \n(41) Chollet, F. Keras. https://keras.io, 2015 (accessed April 05, 2018). \n(42) He, K.; Zhang, X.; Ren, S.; Sun, J. Deep residual learning for image recognition. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2016; pp 770−778. \n(43) Vinyals, O.; Bengio, S.; Kudlur, M. Order Matters: Sequence to Sequence for Sets. 2015, arXiv:1511.06391. arXiv.org e-Print archive, https://arxiv.org/abs/1511.06391 (accessed May 30, 2018). \n(44) Ong, S. P.; Richards, W. D.; Jain, A.; Hautier, G.; Kocher, M.; Cholia, S.; Gunter, D.; Chevrier, V. L.; Persson, K. A.; Ceder, G. Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis. Comput. Mater. Sci. 2013, 68, 314−319. \n(45) Ong, S. P.; Cholia, S.; Jain, A.; Brafman, M.; Gunter, D.; Ceder, G.; Persson, K. A. The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles. Comput. Mater. Sci. 2015, 97, 209−215. \n(46) Abadi, M.; et al. Tensorflow: a system for large-scale machine learning. OSDI, 2016; pp 265−283. \n(47) Kingma, D. P.; Ba, J. Adam: A Method for Stochastic Optimization. 2014, arXiv:1412.6980. arXiv.org e-Print archive. https://arxiv.org/abs/1412.6980 (accessed May 1, 2018). \n(48) Kirklin, S.; Saal, J. E.; Meredig, B.; Thompson, A.; Doak, J. W.; Aykol, M.; Rühl, S.; Wolverton, C. The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies. npj Comput. Mater. 2015, 1, 15010. \n(49) Lany, S. Semiconductor thermochemistry in density functional calculations. Phys. Rev. B: Condens. Matter Mater. Phys. 2008, 78, 245207. \n(50) Jain, A.; Hautier, G.; Moore, C. J.; Ping Ong, S.; Fischer, C. C.; Mueller, T.; Persson, K. A.; Ceder, G. A high-throughput infrastructure for density functional theory calculations. Comput. Mater. Sci. 2011, 50, 2295−2310. \n\n(51) Crowley, J. M.; Tahir-Kheli, J.; Goddard, W. A., III Resolution of the band gap prediction problem for materials design. J. Phys. Chem. Lett. 2016, 7, 1198−1203. (52) De Jong, M.; Chen, W.; Angsten, T.; Jain, A.; Notestine, R.; Gamst, A.; Sluiter, M.; Krishna Ande, C.; Van Der Zwaag, S.; Plata, J. J.; Toher, C.; Curtarolo, S.; Ceder, G.; Persson, K. A.; Asta, M. Charting the complete elastic properties of inorganic crystalline compounds. Sci. Data 2015, 2, 150009. (53) Choudhary, K.; DeCost, B.; Tavazza, F. Machine learning with force-field-inspired descriptors for materials: Fast screening and mapping energy landscape. Phys. Rev. Mater. 2018, 2, 083801. (54) Isayev, O.; Oses, C.; Toher, C.; Gossett, E.; Curtarolo, S.; Tropsha, A. Universal fragment descriptors for predicting properties of inorganic crystals. Nat. Commun. 2017, 8, 15679. (55) Zhou, $\\mathrm{Q.;}$ Tang, P.; Liu, S.; Pan, J.; Yan, $\\mathrm{Q.;}$ Zhang, S.-C. Learning atoms for materials discovery. Proc. Natl. Acad. Sci. 2018, 115, E6411−E6417. (56) Pettifor, D. G. Structure maps for. Pseudobinary and ternary phases. Mater. Sci. Technol. 1988, 4, 675−691. (57) Xie, T.; Grossman, J. C. Hierarchical visualization of materials space with graph convolutional neural networks. J. Chem. Phys. 2018, 149, 174111. (58) Willatt, M. J.; Musil, F.; Ceriotti, M. Feature optimization for atomistic machine learning yields a data-driven construction of the periodic table of the elements. Phys. Chem. Chem. Phys. 2018, 20, 29661−29668. (59) Hautier, G.; Fischer, C.; Ehrlacher, V.; Jain, A.; Ceder, G. Data mined ionic substitutions for the discovery of new compounds. Inorg. Chem. 2011, 50, 656−663. (60) Hautier, G.; Jain, A.; Chen, H.; Moore, C.; Ong, S. P.; Ceder, G. Novel mixed polyanions lithium-ion battery cathode materials predicted by high-throughput ab initio computations. J. Mater. Chem. 2011, 21, 17147−17153. (61) Wang, Z.; Ha, J.; Kim, Y. H.; Im, W. B.; McKittrick, J.; Ong, S. P. Mining Unexplored Chemistries for Phosphors for High-ColorQuality White-Light-Emitting Diodes. Joule 2018, 2, 914−926. (62) van der Maaten, L.; Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 2008, 9, 2579−2605. (63) S Smith, J.; Nebgen, B. T.; Zubatyuk, R.; Lubbers, N.; Devereux, C.; Barros, K.; Tretiak, S.; Isayev, O.; Roitberg, A. Outsmarting Quantum Chemistry through Transfer Learning. 2018, chemrxiv.6744440. chemrxiv.org e-Print archive. https://doi.org/10. 26434/chemrxiv.6744440.v1 (accessed Dec 20, 2018). (64) Altae-Tran, H.; Ramsundar, B.; Pappu, A. S.; Pande, V. Low data drug discovery with one-shot learning. ACS Cent. Sci. 2017, 3, 283−293. " + }, + { + "id": "10.1126_science.aav9750", + "DOI": "10.1126/science.aav9750", + "DOI Link": "http://dx.doi.org/10.1126/science.aav9750", + "Relative Dir Path": "mds/10.1126_science.aav9750", + "Article Title": "BIOMEDICINE Multivascular networks and functional intravascular topologies within biocompatible hydrogels", + "Authors": "Grigoryan, B; Paulsen, SJ; Corbett, DC; Sazer, DW; Fortin, CL; Zaita, AJ; Greenfield, PT; Calafat, NJ; Gounley, JP; Ta, AH; Johansson, F; Randles, A; Rosenkrantz, JE; Louis-Rosenberg, JD; Galie, PA; Stevens, KR; Miller, JS", + "Source Title": "SCIENCE", + "Abstract": "Solid organs transport fluids through distinct vascular networks that are biophysically and biochemically entangled, creating complex three-dimensional (3D) transport regimes that have remained difficult to produce and study. We establish intravascular andmultivascular design freedoms with photopolymerizable hydrogels by using food dye additives as biocompatible yet potent photoabsorbers for projection stereolithography. We demonstrate monolithic transparent hydrogels, produced in minutes, comprising efficient intravascular 3D fluid mixers and functional bicuspid valves. We further elaborate entangled vascular networks from space-filling mathematical topologies and explore the oxygenation and flow of human red blood cells during tidal ventilation and distension of a proximate airway. In addition, we deploy structured biodegradable hydrogel carriers in a rodent model of chronic liver injury to highlight the potential translational utility of this materials innovation.", + "Times Cited, WoS Core": 996, + "Times Cited, All Databases": 1128, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000466809600028", + "Markdown": "BIOMEDICINE \n\n# Multivascular networks and functional intravascular topologies within biocompatible hydrogels \n\nBagrat Grigoryan1\\*, Samantha J. Paulsen1\\*, Daniel C. Corbett2,3\\*, Daniel W. Sazer1, Chelsea L. Fortin3,4, Alexander J. Zaita1, Paul T. Greenfield1, Nicholas J. Calafat1, John P. Gounley5†, Anderson H. $\\bf{T a}^{\\bf{1}}$ , Fredrik Johansson2,3, Amanda Randles5, Jessica E. Rosenkrantz6, Jesse D. Louis-Rosenberg6, Peter A. Galie7, Kelly R. Stevens $^{2,3,4}\\dag$ , Jordan S. Miller1‡ \n\nSolid organs transport fluids through distinct vascular networks that are biophysically and biochemically entangled, creating complex three-dimensional (3D) transport regimes that have remained difficult to produce and study.We establish intravascular and multivascular design freedoms with photopolymerizable hydrogels by using food dye additives as biocompatible yet potent photoabsorbers for projection stereolithography. We demonstrate monolithic transparent hydrogels, produced in minutes, comprising efficient intravascular 3D fluid mixers and functional bicuspid valves. We further elaborate entangled vascular networks from space-filling mathematical topologies and explore the oxygenation and flow of human red blood cells during tidal ventilation and distension of a proximate airway. In addition, we deploy structured biodegradable hydrogel carriers in a rodent model of chronic liver injury to highlight the potential translational utility of this materials innovation. \n\nhe morphologies of the circulatory and pulmonary systems are physically and evolutionarily entangled (1). In air-breathing vertebrates, these bounded and conserved vessel topologies interact to enable the \noxygen-dependent respiration of the entire or \nganism (2–4). To build and interrogate soft hy \ndrogels containing such prescribed biomimetic \nand multivascular architectures, we sought to \nuse stereolithography (fig. S1) (5), commonly em \nployed to efficiently convert photoactive liquid \nresins into structured plastic parts through lo \ncalized photopolymerization $(6,7)$ . Compared with \nextrusion 3D printing, which deposits voxels in \na serial fashion (8–12), photocrosslinking can \nbe highly parallelized via image projection to \nsimultaneously and independently address mil \nlions of voxels per time step. In stereolithography, \nxy resolution is determined by the light path, whereas \n$z$ resolution is dictated by light-attenuating ad \nditives that absorb excess light and confine the \n\npolymerization to the desired layer thickness, thereby improving pattern fidelity. In the absence of suitable photoabsorber additives, 3D photopatterning of soft hydrogels has been limited in the types of patterns that can be generated (13–16) or has required complex, expensive, and low-throughput microscopy to enhance $z$ resolution via the multiphoton effect (17–19). However, common light-blocking chemicals used for photoresist patterning or plastic part fabrication, such as Sudan I, are not suitable for biomanufacturing owing to their known genotoxic and carcinogenic characteristics (20). Therefore, we hypothesized that the identification of nontoxic light blockers for projection stereolithography could provide a major advance to the architectural richness available for the design and generation of widely used biocompatible hydrogels. \n\nHere, we establish that synthetic and natural food dyes, widely used in the food industry, can be applied as potent biocompatible photoabsorbers to enable the stereolithographic production of hydrogels containing intricate and functional vascular architectures. We identified candidate photoabsorbers among food additives whose absorbance spectra encompass visible light wavelengths that can be used for biocompatible photopolymerization. We initially sought to generate monolithic hydrogels, composed primarily of water and poly(ethylene glycol) diacrylate [PEGDA, 6 kDa, 20 weight $\\%(\\mathrm{wt\\%})],$ , with a 1-mm cylindrical channel oriented perpendicular to the light-projection axis. The fabrication of even this trivial design cannot be easily realized because of the dilute nature of such aqueous formulations, in which the low mass fraction of crosslinkable groups and the requisite longer polymerization times result in inadvertent polymerization and solidification within the narrow void spaces that were designed to be hollow perfusable vasculature (figs. S2 to S4). \n\nWe determined that aqueous pre-hydrogel solutions containing tartrazine (yellow food coloring FD&C Yellow 5, E102), curcumin (from turmeric), or anthocyanin (from blueberries) can each yield hydrogels with a patent vessel (figs. S2 to S5). In addition to these organic molecules, inorganic gold nanoparticles $\\mathrm{\\Gamma}[50\\mathrm{\\nm}]$ ), widely regarded for their biocompatibility and lightattenuating properties (21), also function as an effective photoabsorbing additive to generate perfusable hydrogels (fig. S4). \n\nTo understand how these photoabsorbers affect the gelation kinetics of photopolymerizable hydrogels, we performed photorheological characterization with short-duration light exposures, which indicate that these additives cause a dose-dependent delay in the induction of photocrosslinking (figs. S2D and S4E). Saturating light exposures that extend beyond the reaction termination point demonstrate that suitable additives did not ultimately interfere with the reaction because hydrogels eventually reached an equivalent storage modulus independent of the additive concentration (figs. S2D and S4E). We selected tartrazine as a photoabsorber for further studies. In addition to its low toxicity in humans and broad utility in the food industry (22), we observed that this hydrophilic dye is easily washed out of generated hydrogels $70\\%$ elutes within 3 hours for small gels), resulting in nearly transparent constructs suitable for imaging (fig. S2E). Some tartrazine may also be degraded during polymerization, as tartrazine is known to be sensitive to free radicals (23). Submerging gels in water or saline solution to remove soluble tartrazine also flushes the vascular topology and removes unreacted pre-hydrogel solution. In contrast to tartrazine, curcumin is lipophilic and does not wash out in aqueous solutions; anthocyanin has a peak absorbance far from our intended $405\\mathrm{-nm}$ light source, requiring high concentrations for suitable potency; and gold nanoparticles are physically entrapped and make transmission or fluorescence microscopy impractical (fig. S4E). \n\nWe assessed whether this materials insight could similarly impart new architectural freedoms to more-advanced photoactive materials. Photoabsorber additives are necessary and sufficient to enable vessel construction in thiol-ene stepgrowth photopolymerization (24) of hydrogels and in a continuous liquid interface production (6) workflow for the generation of hydrogels (fig. S5). We observed strong lamination between adjacent fabricated layers and a rapid response of the patterned hydrogel to mechanical deformations (fig. S6). This facile generation of soft hydrogels with patent cylindrical vessels oriented orthogonal to the light-projection axis suggests an extensive design flexibility toward the generation of complex vascular topologies, and the optical clarity of resultant hydrogels implies imaging methodologies suitable for characterization and validation of fluid flows. \n\nNext, we investigated the ability to form hydrogels containing functional intravascular topologies. We first explored chaotic mixers: intravascular topologies that homogenize fluids as a result of interactions between fluid flow streams and the vessel geometry (25, 26). Whereas macroscale static mixers have found broad utility in industrial processes (27) because of their unparalleled efficiency, translation of intravascular static mixers into microfluidic systems has been difficult to implement, owing to their complex 3D topology. To this end, we generated monolithic hydrogels with an integrated static mixer composed of 3D twisted-fin elements $\\operatorname{150}\\upmu\\mathrm{m}$ thick) of alternating chirality inside a $\\scriptstyle1-\\mathrm{mm}$ cylindrical channel. We applied laminar fluid streams to the static mixer at a low Reynolds number (0.002) and observed rapid mixing per unit length (Fig. 1A) and as a function of fin number (fig. S7). The elasticity and compliance of PEG-based hydrogels (fig. S6) enabled the facile generation of a 3D functional bicuspid venous valve (Fig. 1B). We observed that the valve leaflets are dynamic, respond rapidly to pulsatile anterograde and retrograde flows, and promote the formation of stable mirror image vortices in the valve sinuses (Fig. 1B and movie S1) according to established mappings of native tissue (28, 29). \n\nSolid organs contain distinct fluid networks that are physically and chemically entangled, providing the rich extracellular milieu that is a hallmark of multicellular life. The ability to fabricate such multivascular topologies within biocompatible and aqueous environments could enable a step change in the fields of biomaterials and tissue engineering. A first objective is the development of an efficient framework to design entangled networks that can provide suitable blueprints for their fabrication within hydrogels. Separate vascular networks must not make a direct fluid connection or they would topologically reduce to a single connected network. We find that mathematical space-filling and fractal topology algorithms provide an efficient parametric language to design complex vascular blueprints and a mathematical means to design a second vascular architecture that does not intersect the first (Fig. 2). We demonstrate a selection of hydrogels (20 wt $\\%$ , 6-kDa PEGDA) containing entangled vascular networks based on 3D mathematical algorithms (Fig. 2, A to D): a helix surrounding an axial vessel, $1^{\\circ}$ and $2^{\\circ}$ Hilbert curves, a bicontinuous cubic lattice (based on a Schwarz P surface), and a torus entangled with a torus knot. Perfusion with colored dyes and micro-computed tomography $(\\upmu\\mathrm{{CT})}$ analysis demonstrate pattern fidelity, vascular patency, and fluidic independence between the two networks (Fig. 2, A to D, and movie S2). \n\n![](images/d850ef7319badbbbfe7e425bb425e805a54908ddd5d8819b6de8021636be93c0.jpg) \n \nFig. 1. Monolithic hydrogels with functional intravascular topologies. (A) Monolithic hydrogels with a perfusable channel containing integrated fin elements of alternating chirality. These static elements rapidly promote fluid dividing and mixing (as shown by fluorescence imaging), consistent with a computational model of flow \n(scale bars, 1 mm). (B) Hydrogels with a functional 3D bicuspid valve integrated into the vessel wall under anterograde and retrograde flows (scale bars, $500~{\\upmu\\mathrm{m}}$ ). Particle image velocimetry demonstrates stable mirror image vortices in the sinus region behind open valve leaflets. \n\nWe sought to evaluate the efficiency of intervascular interstitial transport by measuring the delivery of oxygen from a source vessel to perfused human red blood cells (RBCs) flowing in an adjacent 3D topology. We tessellated the entangled helical topology shown in Fig. 2A along a serpentine path while maintaining the intervessel distance at $300~{\\upmu\\mathrm{m}}$ (Fig. 2E). Perfusion of deoxygenated RBCs [oxygen partial pressure $\\left(P\\mathrm{O_{2}}\\right)\\leq40~\\mathrm{mmHg}$ ; oxygen saturation $(S0_{2})\\leq$ $45\\%]$ into the helical channel during ventilation of the serpentine channel with humidified gaseous oxygen $(\\mathrm{7~kPa})$ caused a noticeable color change of RBCs from dark red at the inlet to bright red at the outlet (Fig. 2, E and F). Collection of perfused RBCs showed significantly higher $S\\mathrm{o}_{2}$ and $P_{\\mathrm{O_{2}}}$ relative to deoxygenated RBCs loaded at the inlet and negative control gels ventilated with humidified nitrogen gas (Fig. 2G and fig. S8). \n\nAlthough this serpentine-helix design demonstrates the feasibility of intervascular oxygen transport between 3D entangled networks, we sought to introduce additional structural features of native distal lung into a bioinspired model of alveolar morphology and oxygen transport. In particular, the realization of 3D hydrogels that contain branching networks and that can support mechanical distension during cyclic ventilation of a pooled airway could enable investigations of the performance of lung morphologies derived from native structure (30) and could provide a complete workflow for the development and examination of new functional topologies. Over the past several decades, alveolar morphology has been approximated mathematically as 3D spacefilling tessellations of polyhedra (31–34). However, the translation of these ideas into useful blueprints has remained nontrivial because of the need for efficient space-filling tessellations and an ensheathing vasculature that closely tracks the curvature of the 3D airway topography. Our solution is to calculate a 3D topological offset of the airway (moving each face in its local normal rate $N=3$ , data are mean $\\pm$ SD, $^{*}P<9\\times10^{-4}$ by Student’s t test).The dashed line indicates $S_{0_{2}}$ of deoxygenated RBCs perfused at the inlet. (F) Elaboration of a lung-mimetic design through generative growth of the airway, offset growth of opposing inlet and outlet vascular networks, and population of branch tips with a distal lung subunit. (G) The distal lung subunit is composed of a concave and convex airway ensheathed in vasculature by 3D offset and anisotropicVoronoi tessellation. (H) Photograph of a printed hydrogel containing the distal lung subunit during RBC perfusion while the air sac was ventilated with ${{\\mathrm O}_{2}}$ (scale bar, 1 mm). (I) Threshold view of the area enclosed by the dashed box in (H) demonstrates bidirectional RBC flow during ventilation. (J) Distal lung subunit can stably withstand ventilation for more than 10,000 cycles $(24\\mathsf{k P a}$ , $0.5{\\mathsf{H z}}^{\\cdot}$ ) and demonstrates RBC sensitivity to ventilation gas $(\\mathsf{N}_{2}\\mathsf{o r}\\mathsf{O}_{2})$ ). \n\n![](images/888d0558dfab9f50ab47d0f7de47dc3fb46f0d66d48065dc08d61ea7ee834104.jpg) \nFig. 2. Entangled vascular networks. (A to D) Adaptations of mathematical space-filling curves to entangled vessel topologies within hydrogels (20 wt $\\%$ PEGDA, $6\\mathsf{k D a},$ : (A) axial vessel and helix, (B) interpenetrating Hilbert curves, (C) bicontinuous cubic lattice, and (D) torus and (3,10) torus knot (scale bars, $3\\mathsf{m m}$ ). (E) Tessellation of the axial vessel and its encompassing helix along a serpentine pathway. The photograph is a top-down view of a fabricated hydrogel with oxygen and RBC delivery to \nrespective vessels. During perfusion, RBCs change color from dark red (at the RBC inlet) to bright red (at the RBC outlet) (scale bar, $3\\mathsf{m m}$ ). $_{\\sf B o x e d}$ regions are magnified in (F) (scale bar, $1\\mathsf{m m};$ ). (G) Perfused RBCs were collected at the outlet and quantified for $S_{0_{2}}$ and $P_{{{0}_{2}}}$ . Oxygen flow increased $S\\phantom{\\frac{1}{2}}$ and $P_{{{0}_{2}}}$ of perfused RBCs compared with deoxygenated RBCs perfused at the inlet (dashed line) and a nitrogen flow negative control $(N\\geq3$ replicates, data are mean $\\pm$ SD, ${\\ast}P<2\\times10^{-7}$ by Student’s t test). \n\n![](images/8e8f9099c658bef7b0f9265b586481be35b72d1aa68f79df4187b3986bf5aada.jpg) \nFig. 3. Tidal ventilation and oxygenation in hydrogels with vascularized alveolar model topologies. (A) (Top) Architectural design of an alveolar model topology based on a Weaire-Phelan 3D tessellation and topologic offset to derive an ensheathing vasculature. (Bottom) Cutaway view illustrates the model alveoli (alv.) with a shared airway atrium. Convex (blue) and concave (green) regions of the airway are highlighted. (B) Photograph of a printed hydrogel during RBC perfusion while the air sac was ventilated with ${{\\sf O}_{2}}$ (scale bar, 1 mm). (C) Upon airway inflation with oxygen, concave regions of the airway (dashed black circles) squeeze adjacent blood vessels and cause RBC clearance (scale bar, $500\\upmu\\mathrm{m}\\dot{}$ ). (D) A computational model of airway inflation demonstrates increased displacement at concave regions (dashed yellow circles). (E) Oxygen saturation of RBCs increased with decreasing RBC flow \n\n![](images/8056f4e7b8d4b6190e93fb6a2dd8f584bb76055dab5ba5dd2ba09f53e4f077ed.jpg) \nFig. 4. Engraftment of functional hepatic hydrogel carriers. (A to C) Albumin promoter activity was enhanced in hydrogel carriers containing hepatic aggregates after implantation in nude mice. Data from all time points for each condition are shown in (B) $[N=4$ , $^{*}P<0.05$ by two-way analysis of variance (ANOVA) followed by Tukey’s post-hoc test]. Cumulative bioluminescence for each condition is shown in (C) $\\langle N=4$ , $^{\\ast}P<0.05$ by one-way ANOVA followed by Tukey’s post-hoc test). Error bars indicate SEM. GelMA, gelatin methacrylate. (D) Gross images of hydrogels upon resection (scale bars, $5\\mathsf{m m}$ ). (E) (Left) Prevascularized hepatic hydrogel carriers are created by seeding endothelial cells (HUVECs) in the vascular network after printing. \n\n(Right) Confocal microscopy observations show that hydrogel anchors physically entrap fibrin gel containing the hepatocyte aggregates (Hep) (scale bar, $1\\mathsf{m m}$ ). (F) Hepatocytes in prevascularized hepatic hydrogel carriers exhibit albumin promoter activity after implantation in mice with chronic liver injury. Graft sections stained with H&E show positioning of hepatic aggregates (black arrows) relative to printed (case, anchor) and nonprinted (fibrin) components of the carrier system (scale bar, $50\\upmu\\mathrm{m}\\dot{}$ ). (G) Hydrogel carriers are infiltrated with host blood (gross, H&E). Carriers contain aggregates that express the marker cytokeratin-18 (Ck-18) and are in close proximity to Ter-119–positive RBCs (scale bars, $40\\upmu\\mathrm{m};$ ). \n\ndirection) and have the new surface serve as the template on which a vascular skeleton is built. With this approach, we developed a bioinspired alveolar model with an ensheathing vasculature from 3D tessellations of the Weaire-Phelan foam topology (35) (Fig. 3 and fig. S9). Although the fundamental units of the Weaire-Phelan foam are convex polyhedra (fig. S9), 3D tessellations can produce a surface containing both convex and concave regions reminiscent of native alveolar air sacs (30) with a shared airway atrium supporting alveolar buds (Fig. 3A). We extended the manifold air surface in the normal direction, removed faces, and ensheathed edges in a smoothed polygonal mesh to form a highly branched vascular network (containing 185 vessel segments and 113 fluidic branch points) that encloses the airway and tracks its curvature (fig. S9B). \n\nWe printed hydrogels $20\\mathrm{wt\\%}$ , 6-kDa PEGDA) patterned with the alveolar model topology at a voxel resolution of ${\\boldsymbol{5}}\\mathrm{pl}$ and a print time of 1 hour (Fig. 3B). Cyclic ventilation of the pooled airway with humidified oxygen gas (10 kPa, $0.5\\mathrm{Hz}$ ) led to noticeable distension and an apparent change in the curvature of concave airway regions (fig. S9C). Perfusion of deoxygenated RBCs at the blood vessel inlet (10 to $100~{\\upmu\\mathrm{m/min}}$ ) during cyclic ventilation led to observable compression and RBC clearance from vessels adjacent to concave airway regions (Fig. 3, B and C). By observing dilute RBC streams at the early stages of perfusion, we also discerned that the cyclic compression of RBC vessels—actuated by the concave airway regions upon each inflation cycle—acts as switching valves to redirect fluid streams to neighboring vessel segments (movie S3). We implemented a simplified 2D computational model of airway inflation (fig. S9D), which predicts anisotropic distension of the airway and compression of adjacent blood vessels, corresponding to local curvature (fig. S9E). In addition, analysis from a 3D computational model supports anisotropic distension of the concave regions of the airway during inflation (Fig. 3D). Despite the volume of the alveolar model hydrogel $(0.8\\mathrm{ml})^{\\cdot}$ ) being $<25\\%$ of that of the serpentine-helix model $(3.5~\\mathrm{ml})$ ), we measured similar oxygenation efficiencies for the two designs (Fig. 3E). Our data suggest that branching topology, hydrogel distension, and redirection of fluid streams during ventilation may boost intravascular mixing and allow faster volumetric uptake of oxygen by the well-mixed RBCs. Vascular constriction during breathing has been previously described as an important fluid control mechanism in the mammalian lung (36), and here we provide a means to actualize these ideas in completely defined and biocompatible materials and within aqueous environments. \n\nTo extend this work toward a coherent approximation of scalable lung-mimetic design, we must consolidate the location of the vascular inlet, vascular outlet, and air duct, such that distal lung subunits can be populated on the tips of multiscale branching architecture. Therefore, within a given computational bounding volume, we first derive a branching airway (Fig. 3F). Next, the centerlines of inlet and outlet blood vessel networks are grown $180^{\\circ}$ opposite each other across and topologically offset from the airway, and the blood vessels traverse down to the tips of all daughter branches. The final step is to populate the tips of each distal lung with an alveolar unit cell (Fig. 3G and movie S4) whose ensheathing vasculature (containing 354 vessel segments and 233 fluidic branch points) itself is an anisotropic Voronoi surface tessellation along a topological offset of its local airway (fig. S9, F and G). We found that hydrogels (20 wt $\\%$ , 6-kDa PEGDA) could withstand more than 10,000 ventilation cycles (at $24\\mathrm{\\kPa}$ and a frequency of $0.5\\mathrm{Hz}\\rangle$ over 6 hours during RBC perfusion and while switching the inflow gas between humidified oxygen and humidified nitrogen (Fig. 3, H to J). Color-filtered views of the early stages of RBC perfusion (Fig. 3I) indicate that ventilation promotes RBC mixing and bidirectional flows within selected vessel segments near the midpoint of the distal lung subunit (movie S4). \n\nWe use our custom stereolithography apparatus for tissue engineering (SLATE) to demonstrate production of tissue constructs containing mammalian cells (figs. S1, S10, and S11 and movie S5). Lung-mimetic architectures can also be populated with human lung fibroblasts in the bulk of the interstitial space and human epithelial-like cells in the airway (fig. S12), which could facilitate the development of a hydrogel analog of a labon-a-chip lung design (37). Finally, we subjected primary human mesenchymal stem cells (hMSCs) to SLATE fabrication (with mixtures of PEGDA and gelatin methacrylate) and show that the cells within cylindrical fabricated hydrogels remain viable and can undergo osteogenic differentiation (fig. S13D). In related multiweek perfusion tissue culture of hMSCs with osteogenic differentiation media, osteogenic marker–positive hMSCs were visible throughout the gel (fig. S14). These studies indicate that SLATE fabrication supports rapid biomanufacturing, can maintain the viability of mammalian cell lines, supports the normal function and differentiation of primary human stem cells, and provides an experimentally tractable means to explore stem cell differentiation as a function of soluble factor delivery via vascular perfusion. \n\nWe next sought to establish the utility of this process for fabricating structurally complex and functional tissues for therapeutic transplantation. In particular, the liver is the largest solid organ in the human body, carrying out hundreds of essential tasks in a manner thought to be dependent on its structural topology. We created complex structural features in hydrogel within the expanded design space imparted by SLATE to assemble multimaterial liver tissues. Bioprinted single-cell tissues and bioprinted hydrogel carriers containing hepatocyte aggregates were fabricated (Fig. 4, A to C). The albumin promoter activity of tissue carriers loaded with aggregates was enhanced by more than a factor of 60 compared with that of implanted tissues containing single cells (Fig. 4, B and C). Furthermore, upon gross examination of tissues after resection, hydrogel carrier tissues appeared to have more integration with host tissue and blood (Fig. 4D). Despite the improved utility of hepatic aggregates over single cells, aggregate size puts substantial architectural limitations on 3D printing because aggregates are larger in size than our lowest voxel resolution $(50\\ \\upmu\\mathrm{m})$ ). To accommodate these design constraints, we built a more advanced carrier that can deliver hepatic aggregates within natural fibrin gel, has a vascular compartment that can be seeded with endothelial cells, and incorporates structural hydrogel anchors to physically, rather than chemically, retain the fibrin gel and facilitate remodeling between the graft and host tissue (Fig. 4E and fig. S15). Microchannel networks were seeded with human umbilical vein endothelial cells (HUVECs) because our previous studies demonstrated that inclusion of endothelial cords improved tissue engraftment (38). We then evaluated whether optimized bioengineered liver tissues would survive transplantation in a rodent model of chronic liver injury. After 14 days of engraftment in mice with chronic liver injury, hepatic hydrogel carriers exhibited albumin promoter activity indicative of surviving functional hepatocytes (Fig. 4F). Immunohistological characterization revealed the presence of hepatic aggregates adhered to printed hydrogel components that stained positively for the marker cytokeratin-18 (Fig. 4, F and G). Further characterization through gross examination and highermagnification images of slides stained with hematoxylin and eosin (H&E) indicated the presence of host blood in explanted tissues. Immunostaining using a monoclonal antibody against Ter-119 confirmed the erythroid identity of cells in microvessels adjacent to hepatic microaggregates in explanted tissues (Fig. 4G, right). This work provides an approach to address long-standing design limitations in tissue engineering that have hindered progress of preclinical studies. \n\nWe have identified readily available food dyes that can serve as potent photoabsorbers for biocompatible and cytocompatible production of hydrogels containing functional vascular topologies for studies of fluid mixers, valves, intervascular transport, nutrient delivery, and host engraftment. With our stereolithographic process, there is potential for simultaneous and orthogonal control over tissue architecture and biomaterials for the design of regenerative tissues. \n\n# REFERENCES AND NOTES \n\n1. R. Monahan-Earley, A. M. Dvorak, W. C. Aird, \nJ. Thromb. Haemost. 11 (suppl. 1), 46–66 (2013). \n2. G. R. Scott, J. Exp. Biol. 214, 2455–2462 (2011). \n3. E. R. Schachner, J. R. Hutchinson, C. Farmer, PeerJ 1, e60 (2013). \n4. C. G. Farmer, Physiology 30, 260–272 (2015). \n5. Supplementary figures, as well as materials and methods, are \navailable as supplementary materials. \n6. J. R. Tumbleston et al., Science 347, 1349–1352 (2015). \n7. B. E. Kelly et al., Science 363, 1075–1079 (2019). \n8. J. S. Miller et al., Nat. Mater. 11, 768–774 (2012). \n9. T. J. Hinton et al., Sci. Adv. 1, e1500758 (2015). \n10. T. Bhattacharjee et al., Sci. Adv. 1, e1500655 (2015). \n11. D. B. Kolesky, K. A. Homan, M. A. Skylar-Scott, J. A. Lewis, \nProc. Natl. Acad. Sci. U.S.A. 113, 3179–3184 (2016). \n12. H.-W. Kang et al., Nat. Biotechnol. 34, 312–319 (2016). \n\n13. V. Liu Tsang et al., FASEB J. 21, 790–801 (2007). \n14. H. Lin et al., Biomaterials 34, 331–339 (2013). \n15. J. A. S. Neiman et al., Biotechnol. Bioeng. 112, 777–787 (2015). \n16. X. Ma et al., Proc. Natl. Acad. Sci. U.S.A. 113, 2206–2211 (2016). \n17. M. S. Hahn, J. S. Miller, J. L. West, Adv. Mater. 18, 2679–2684 (2006). \n18. C. A. DeForest, K. S. Anseth, Nat. Chem. 3, 925–931 (2011). \n19. K. A. Heintz et al., Adv. Healthc. Mater. 5, 2153–2160 (2016). \n20. T. M. Fonovich, Drug Chem. Toxicol. 36, 343–352 (2013). \n21. S. Kumar, J. Aaron, K. Sokolov, Nat. Protoc. 3, 314–320 (2008). \n22. L. J. Stevens, J. R. Burgess, M. A. Stochelski, T. Kuczek, Clin. Pediatr. 54, 309–321 (2015). \n23. M. Li et al., J. Agric. Food Chem. 62, 12052–12060 (2014). \n24. C. A. DeForest, B. D. Polizzotti, K. S. Anseth, Nat. Mater. 8, 659–664 (2009). \n25. A. D. Stroock et al., Science 295, 647–651 (2002). \n26. D. Therriault, S. R. White, J. A. Lewis, Nat. Mater. 2, 265–271 (2003). \n27. A. Ghanem, T. Lemenand, D. Della Valle, H. Peerhossaini, Chem. Eng. Res. Des. 92, 205–228 (2014). \n28. F. Lurie, R. L. Kistner, B. Eklof, D. Kessler, J. Vasc. Surg. 38, 955–961 (2003). \n29. E. Bazigou, T. Mäkinen, Cell. Mol. Life Sci. 70, 1055–1066 (2013). \n30. C. C. W. Hsia, D. M. Hyde, E. R. Weibel, Compr. Physiol. 6, 827–895 (2016). \n31. J. Mead, T. Takishima, D. Leith, J. Appl. Physiol. 28, 596–608 (1970). \n32. A. Linhartová, W. Caldwell, A. E. Anderson, Anat. Rec. 214, 266–272 (1986). \n33. Y. C. Fung, J. Appl. Physiol. 64, 2132–2141 (1988). \n34. P. Hofemeier, J. Sznitman, J. Biomech. Eng. 136, 061007 (2014). \n35. D. Weaire, R. Phelan, Philos. Mag. Lett. 69, 107–110 (1994). \n36. J. B. West, C. T. Dollery, A. Naimark, J. Appl. Physiol. 19, 713–724 (1964). \n37. D. Huh et al., Science 328, 1662–1668 (2010). \n38. K. R. Stevens et al., Sci. Transl. Med. 9, eaah5505 (2017). \n39. J. S. Miller, Dataset for: Multivascular networks and functional intravascular topologies within biocompatible hydrogels, Version 1.0, Zenodo (2019); https://doi.org/10.5281/zenodo. 2614071 \n40. A. P. Randles, V. Kale, J. Hammond, W. Gropp, E. Kaxiras, in Proceedings of the 2013 IEEE 27th International Symposium on Parallel and Distributed Processing (IEEE, 2013), pp. 1063–1074. \n41. L. Andrus et al., Hepatology 54, 1901–1912 (2011). \n\n# ACKNOWLEDGMENTS \n\nWe thank the large number of open-source and related projects that facilitated this work, including Arduino.cc, RepRap.org, UltiMachine.com, Ultimaker.com, Blender.org, Python.org, ImageMagick.org, Git, NIH ImageJ, Fiji.sc, and the NIH 3D Print Exchange. We thank G. Calderon, P. Deme, S. Chen, A. Porter, H. Jackson, S. Panchavati, G. Quilap (Prime Camera), and F. Castaldi (Ikan) for technical assistance; T. J. Vadakkan and C.-W. Hsu from the Optical Imaging and Vital Microscopy Core at Baylor College of Medicine for assistance with $\\upmu\\mathrm{CT}$ ; A. J. Budi Utama, W. Hauser, and M. Guerra for assistance with the IVIS imaging system; and M. Dickinson, M. Wettergreen, J. Tabor, and S. Cutting for helpful discussions. Funding: This work was supported in part by the Robert J. Kleberg, Jr. and Helen C. Kleberg Foundation (J.S.M.), the U.S. National Science Foundation (NSF) (P.A.G., 1728239), an NSF Graduate Research Fellowship (B.G., 1450681), the U.S. National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) via F31 NRSA Fellowship (S.J.P., HL134295), the NIH Director’s New Innovator Award (K.R.S., NHLBI, DP2HL137188), the John H. Tietze Foundation (K.R.S.), NIH National Institute of Biomedical Imaging and Bioengineering (NIBIB) Cardiovascular Training Grant (D.C.C., T32EB001650); NIH National Institute of General Medical Sciences (NIGMS) Molecular Medicine Training Grant (C.L.F., T32GM095421); Office of the Director of the National Institutes of Health Early Independence Award (A.R., DP5OD019876), and a training fellowship from the Gulf Coast Consortia on the NSF \n\nIGERT: Neuroengineering from Cells to Systems (D.W.S., 1250104). The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies. Author contributions: B.G. and J.S.M. conceived and initiated the project. All authors contributed to experimental design, planning, and execution; data analysis; and manuscript writing. B.G., S.J.P., D.W.S., J.E.R., J.D.L-R., and J.S.M. developed designs and algorithms. A.R., P.G., K.R.S., and J.S.M. supervised the project. Competing interests: J.S.M. and B.G. are cofounders of and hold an equity stake in the startup company Volumetric, Inc. J.E.R. and J.D.L-R. are cofounders and hold an equity stake in Nervous System, Inc., a design studio that works at the intersection of science, art, and technology. B.G., A.H.T., and J.S.M. are listed as co-inventors on pending U.S. patent application 15/709,392. D.C.C., K.R.S., B.G., and J.S.M. are listed as co-inventors on pending U.S. patent application 62/746,106. The remaining coauthors declare no competing interests. Data and materials availability: Data, SLATE design files, and hydrogel STL design files are available in Zenodo (39). HARVEY (40) is a closed-source code that is available under a research license from Duke University. Research licenses can be applied for at the Duke University Office of License and Ventures. Plasmids pTRIP.Alb.IVSb.IRES.tagRFP-DEST and pTRIP.Alb.Fluc.ires.TagRFP. NLS-IPS (41) were provided by C. Rice, The Rockefeller University, under a uniform biological material transfer agreement with The Rockefeller University. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/364/6439/458/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S15 \nTable S1 \nReferences (42–68) \nMovies S1 to S5 \n6 November 2018; accepted 9 April 2019 \n10.1126/science.aav9750 \n\n# Science \n\n# Multivascular networks and functional intravascular topologies within biocompatible hydrogels \n\nBagrat Grigoryan, Samantha J. Paulsen, Daniel C. Corbett, Daniel W. Sazer, Chelsea L. Fortin, Alexander J. Zaita, Paul T. Greenfield, Nicholas J. Calafat, John P. Gounley, Anderson H. Ta, Fredrik Johansson, Amanda Randles, Jessica E. Rosenkrantz, Jesse D. Louis-Rosenberg, Peter A. Galie, Kelly R. Stevens and Jordan S. Miller \n\nScience 364 (6439), 458-464. DOI: 10.1126/science.aav9750 \n\n# Routes to independent vessel networks \n\nIn air-breathing vertebrates, the circulatory and pulmonary systems contain separate networks of channels that intertwine but do not intersect with each other. Recreating such structures within cell-compatible materials has been a major challenge; even a single vasculature system can be a burden to create. Grigoryan et al. show that natural and synthetic food dyes can be used as photoabsorbers that enable stereolithographic production of hydrogels containing intricate and functional vascular architectures. Using this approach, they demonstrate functional vascular topologies for studies of fluid mixers, valves, intervascular transport, nutrient delivery, and host engraftment. \n\nScience, this issue p. 458 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.aau5701", + "DOI": "10.1126/science.aau5701", + "DOI Link": "http://dx.doi.org/10.1126/science.aau5701", + "Relative Dir Path": "mds/10.1126_science.aau5701", + "Article Title": "A Eu3+-Eu2+ ion redox shuttle imparts operational durability to Pb-I perovskite solar cells", + "Authors": "Wang, LG; Zhou, HP; Hu, JN; Huang, BL; Sun, MZ; Dong, BW; Zheng, GHJ; Huang, Y; Chen, YH; Li, L; Xu, ZQ; Li, NX; Liu, Z; Chen, Q; Sun, LD; Yan, CH", + "Source Title": "SCIENCE", + "Abstract": "The components with soft nature in the metal halide perovskite absorber usually generate lead (Pb)degrees and iodine (I)degrees defects during device fabrication and operation. These defects serve as not only recombination centers to deteriorate device efficiency but also degradation initiators to hamper device lifetimes. We show that the europium ion pair Eu3+-Eu2+ acts as the redox shuttle that selectively oxidized Pb degrees and reduced I degrees defects simultaneously in a cyclical transition. The resultant device achieves a power conversion efficiency (PCE) of 21.52% (certified 20.52%) with substantially improved long-term durability. The devices retained 92% and 89% of the peak PCE under 1-sun continuous illumination or heating at 850 degrees C for 1500 hours and 91% of the original stable PCE after maximum power point tracking for 500 hours, respectively.", + "Times Cited, WoS Core": 864, + "Times Cited, All Databases": 910, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000456140700033", + "Markdown": "# SOLAR CELLS \n\n# A Eu3+-Eu2+ ion redox shuttle imparts operational durability to Pb-I perovskite solar cells \n\nLigang $\\mathbf{Wang^{1}}$ , Huanping $\\mathbf{Z}\\mathbf{h}\\mathbf{ou}^{\\mathbf{1}*}$ , Junnan $\\mathbf{H}\\mathbf{u}^{\\mathbf{1}}$ , Bolong $\\mathbf{Huang^{2}}$ , Mingzi $\\mathbf{sun^{2}}$ , Bowei $\\mathbf{Dong^{\\mathbf{1}}}$ , Guanghaojie Zheng1, Yuan Huang1, Yihua Chen1, Liang $\\mathbf{Li}^{\\mathbf{\\lambda}}$ , Ziqi $\\mathbf{X}\\mathbf{u}^{\\mathbf{1}}$ , Nengxu $\\mathbf{Li}^{\\mathbf{I}}$ , Zheng ${{\\bf{L i u}}^{\\bf{1}}}$ , Qi $\\mathbf{chen^{3}}$ , Ling-Dong $\\mathbf{Sum^{1*}}$ , Chun-Hua $\\mathbf{Yan^{1*}}$ \n\nThe components with soft nature in the metal halide perovskite absorber usually generate lead $({\\mathsf{P}}{\\mathsf{b}})^{\\circ}$ and iodine $(1)^{0}$ defects during device fabrication and operation. These defects serve as not only recombination centers to deteriorate device efficiency but also degradation initiators to hamper device lifetimes. We show that the europium ion pair $\\mathsf{E}\\mathsf{u}^{\\bar{3}+}\\cdot\\mathsf{E}\\mathsf{u}^{2+}$ acts as the “redox shuttle” that selectively oxidized $\\mathsf{P}\\mathsf{b}^{\\mathsf{o}}$ and reduced $1^{\\circ}$ defects simultaneously in a cyclical transition. The resultant device achieves a power conversion efficiency (PCE) of $21.52\\%$ (certified $20.52\\%$ ) with substantially improved long-term durability. The devices retained $92\\%$ and $89\\%$ of the peak PCE under 1-sun continuous illumination or heating at $85^{\\circ}\\mathsf{C}$ for 1500 hours and $91\\%$ of the original stable PCE after maximum power point tracking for 500 hours, respectively. \n\nD feivcicencliyfe(tPiCmEe anred tphoewkerycfoanctvoers oden erfmining the final cost of the electricity that solar cells generate. The certified PCE of perovskite solar cells (PSCs) has rapidly reached $23.7\\%$ over the past few years (1–9), which is on par with that of polycrystalline silicon and $\\mathrm{Cu(In,Ga)Se_{2}}$ solar cells, but poor device stability (10–12) under operating conditions prevents the perovskite photovoltaics from occupying even a tiny market share $(\\mathit{I3},\\mathit{I4})$ . Generally, commercial solar cells come with a warranty of a 20- to 25-year lifetime with a less than $10\\%$ drop of PCE, which corresponds to an average degradation rate of ${\\sim}0.5\\%$ per year (15). Compared with those inorganic photovoltaic materials—e.g., silicon (IV group) and CIGS (I-III-VI group) (16)—the elements or components are mostly large and more polarized in organic-inorganic halide perovskite materials, such as ${\\mathrm{I}}^{-}$ , methylammonium $(\\mathrm{MA}^{+})$ , and $\\mathrm{Pb^{2+}}$ . They construct a soft crystal lattice prone to deform $(I7)$ and vulnerable to various aging stresses such as oxygen, moisture (18, 19), and ultraviolet (UV) exposure (20, 21). By encapsulation (22–24), interface modification (13, 25–29), and UV filtration, the device lifetime can be prolonged by the temporary exclusion of these external environmental factors. \n\nHowever, some aging stresses cannot be avoided during device operation, including light illumination, electric field, and thermal stress, upon which both ${\\boldsymbol{\\mathrm{I}}}^{-}$ and $\\mathrm{Pb^{2+}}$ in perovskites become chemically reactive to initiate the decomposition even if they are well encapsulated (30). Because of the soft nature of ${\\boldsymbol{\\mathrm{I}}}^{-}$ , $\\mathrm{Pb^{2+}}$ ions, and Pb-I bonding, intrinsic degradation would occur in perovskite materials upon various excitation stresses, which finally induce PCE deterioration. On one hand, ${\\mathrm{I}}^{-}$ is easily oxidized to ${\\boldsymbol{\\mathrm{I}}}^{0}$ , which not only serve as carrier recombination centers but also initiate chemical chain reactions to accelerate the degradation in perovskite layers (31). On the other hand, $\\mathrm{Pb}^{2+}$ is prone to be reduced to metallic $\\mathrm{Pb}^{0}$ upon heating or illumination, which has been observed in Pb halide perovskite films (32, 33). \n\n$\\mathrm{{\\Pb}^{0}}$ is a primary deep defect state that severely degrades the performance of perovskite optoelectronic devices (34, 35), as well as their longterm durability (36). Furthermore, most soft inorganic semiconductors are suffering similar instability, such as PbS (37), $\\mathrm{PbI_{2}}$ (38, 39), and AgBr (40), among others. Several attempts have been reported to eliminate either $\\mathrm{Pb}^{0}$ or ${\\boldsymbol{\\mathrm{I}}}^{0}$ defects, like optimizing film processing (41) and additive engineering (42–44). To date, these additives are mostly sacrificial agents specific for one kind of defects, which diminish soon after they take effects. Long-term operational durability requires the simultaneous elimination of both $\\mathrm{Pb}^{0}$ and ${\\boldsymbol{\\mathrm{I}}}^{0}$ defects in perovskite materials in a sustainable manner. \n\nWe demonstrated constant elimination of $\\mathrm{Pb}^{0}$ and ${\\mathrm{~\\boldmath~I~}}^{0}$ simultaneously in PSCs over their life span, which leads to exceptional stability improvement and high PCE through incorporation of the ion pair of $\\mathrm{Eu}^{3+}(\\mathrm{f}^{6})\\leftrightarrow\\mathrm{Eu}^{2+}(\\mathrm{f}^{7})$ as the redox shuttle. In this cyclic redox transition, $\\mathrm{Pb}^{0}$ defects could be oxidized by $\\mathrm{Eu^{3+}}$ , while ${\\boldsymbol{\\mathrm{I}}}^{0}$ defects could be reduced by ${\\mathrm{Eu}}^{2+}$ at same time. The $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ pair is not consumed during device operation, probably because of its nonvolatility and the suitable redox potential in this cyclic transition. Thus, the champion PCE of the corresponding device was promoted to $21.52\\%$ (certified, $20.52\\%$ ) with negligible current density-voltage $\\left(J{-}V\\right)$ hysteresis. Devices with the $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ ion pair exhibited excellent shelf lifetime and thermal and light stability, which suggests that this approach may provide a universal solution to the inevitable degradation issue during device operation. \n\nThe reaction between $\\mathrm{{Pb}}^{0}$ and ${\\boldsymbol{\\mathrm{I}}}^{0}$ is thermodynamically favored and has a standard molar Gibbs formation energy for $\\mathrm{PbI_{2}(s)}$ of $-173.6\\mathrm{kJ/mol}$ $(45)$ , which provides the driving force for eliminating both defects. However, simply mixing metallic $\\mathrm{\\Pb}$ and $\\mathrm{I}_{2}$ powder only led to limited formation of $\\mathrm{PbI_{2}}$ , which suggests the presence of kinetic barriers at room temperature. To enable elimination of $\\mathrm{Pb}^{0}$ and ${\\mathrm{~\\boldmath~I~}}^{0}$ defects in PSCs simultaneously across device life span, we propose the “redox shuttle” to oxidize $\\mathrm{Pb}^{0}$ and reduce ${\\boldsymbol{\\mathrm{I}}}^{0}$ independently, wherein they can be regenerated during the complete circle. It requires selectively oxidizing $\\mathrm{Pb}^{0}$ and reducing ${\\boldsymbol{\\mathrm{I}}}^{0}$ defects without introducing additional deep-level defects. After finely screening many possible redox shuttle additives, the rare earth ion pair of $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ was identified as the best candidate, mostly owing to their appropriate redox potentials. $\\mathrm{Eu^{3+}}$ could easily be reduced to $\\mathrm{Eu^{2+}}$ with the stable half-full $\\mathbf{f}^{7}$ electron configuration to form the naturally associated ion pair. The redox shuttle can transfer electrons from $\\mathrm{Pb}^{0}$ to ${\\boldsymbol{\\mathrm{I}}}^{0}$ defects in a cyclical manner, wherein the $\\mathrm{Eu^{3+}}$ oxidizes $\\mathrm{Pb}^{0}$ to $\\mathrm{Pb^{2+}}$ and the formed $\\mathrm{Eu^{2+}}$ simultaneously reduces ${\\boldsymbol{\\mathrm{I}}}^{0}$ to ${\\boldsymbol{\\mathrm{I}}}^{-}$ (Fig. 1F). Thus, each ion in this pair is mutually replenished during defects elimination. \n\nThe proposed redox shuttle eliminates corresponding defects on the basis of the following two chemical reactions: \n\n$$\n2\\mathrm{Eu}^{3+}+\\mathrm{Pb}^{0}\\rightarrow2\\mathrm{Eu}^{2+}+\\mathrm{Pb}^{2+}\n$$ \n\n$$\n\\mathrm{Eu^{2+}+I^{0}\\rightarrow E u^{3+}+I^{-}}\n$$ \n\nWe first explored the feasibility of the $\\mathrm{Eu^{3+}{-}E u^{2+}}$ ion pair to promote electron transfer from $\\mathrm{Pb}^{0}$ to ${\\boldsymbol{\\mathrm{I}}}^{0}$ in solution (Fig. 1A) by dispersing $\\mathrm{I}_{2}$ $\\mathrm{25~mg)}$ powder and metallic $\\mathrm{Pb}$ powder (25 mg) in $2\\mathrm{ml}$ of N,N-dimethylformamide (DMF) and isopropanol (IPA) that had a volume ratio of 1:10 as a reference solution. The $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ ion pair was incorporated by further adding europium acetylacetonate $\\mathrm{[Eu(acac)_{3}]}$ (11 mg) into the $2\\mathrm{-ml}$ solution. Under continuous stirring at $100^{\\circ}\\mathrm{C}$ , the sample solution gradually turned from black to colorless with a large amount of yellow precipitates after $60~\\mathrm{{min}}$ , whereas the reference solution remained dark brown with little evidence of yellow precipitates. \n\nUV-visible (UV-vis) spectra of the reference solution exhibited an absorption peak at ${\\sim}370\\mathrm{nm}$ (Fig. 1B), which we attributed to the presence of an ${\\mathrm{~\\boldmath~I~}}^{0}$ species (36) that was absent in the sample solution, which had an absorption peak at ${\\sim}290\\mathrm{nm}$ that we attributed to a $\\mathrm{PbI_{x}}$ species. Both the ${\\mathrm{~\\boldmath~I~}}^{0}$ and $\\mathrm{Pb}^{0}$ species were effectively converted to ${\\boldsymbol{\\mathrm{I}}}^{-}$ and $\\mathrm{Pb^{2+}}$ upon $\\mathrm{Eu^{3+}}$ addition. An x-ray diffraction (XRD) measurement on the precipitates revealed both $\\mathrm{PbI_{2}}$ $(12.7^{\\circ},$ 25.9°, $39.5^{\\mathrm{o}}\\AA,$ ) and metallic $\\operatorname{Pb}\\ (31.3^{\\circ},36.2^{\\circ},52.2^{\\circ})$ species in both cases (Fig. 1C). In the sample, the characteristic peak intensity ratio of $\\mathrm{PbI_{2}}$ to metallic $\\mathrm{\\Pb}$ was larger than that of the reference. This result further confirmed that $\\mathrm{Eu}^{3+}$ could accelerate the conversion of $\\mathrm{Pb}^{0}$ and ${\\mathrm{~\\boldmath~I~}}^{0}$ to $\\mathrm{Pb^{2+}}$ and ${\\boldsymbol{\\mathrm{I}}}^{-}$ , respectively. \n\nWhen we added $\\mathrm{Eu(acac)_{3}}$ to the $\\mathrm{CH_{3}N H_{3}I}$ solution of water/chloroform, we observed no ${\\boldsymbol{\\mathrm{I}}}^{0}$ species absorption peak in the corresponding UV-vis spectrum (Fig. 1D), showing that $\\mathrm{Eu^{3+}}$ selectively oxidizes $\\mathrm{{Pb}}^{0}$ rather than ${\\mathrm{I}}^{-}$ . The stronger oxidizing agent of $\\mathrm{Fe^{3+}}$ oxidized ${\\boldsymbol{\\mathrm{I}}}^{-}$ species, and the absorption peak of ${\\mathrm{~\\boldmath~I~}}^{0}$ was present. We verified that $\\mathrm{Eu^{3+}}$ was reduced to paramagnetic $\\mathrm{Eu}^{2+}$ in $\\mathrm{{CH_{3}N H_{3}P b I_{3}}}$ $\\mathrm{(MAPbI_{3})}$ perovskite films with $1\\%$ $\\mathrm{(Eu/Pb}$ , molar ratio) $\\mathrm{Eu}^{3+}$ incorporated, which showed a strong signal in electron paramagnetic resonance (EPR) measurements (Fig. 1E) that was absent in $\\mathrm{Eu_{2}O_{3}}$ and in the reference $\\mathbf{MAPbI_{3}}$ film. \n\nWe compared the effect of $\\mathrm{Eu^{3+}}$ by studying other ions, including redox-inert ${\\mathrm{Y}}^{3+}$ and strong oxidizing $\\mathrm{Fe^{3+}}$ , by preparing film samples incorporated with $1\\%$ metal ions $(\\mathrm{M}/\\mathrm{Pb}$ , molar ratio) and performed high-resolution x-ray photoelectron spectroscopy (XPS) analysis to elucidate the potential effects on both $\\mathrm{{\\Pb}}^{0}$ and ${\\boldsymbol{\\mathrm{I}}}^{0}$ defects. As shown in Fig. 2A, the binding energy (BE) at 142.8 and 137.9 eV were assigned to $4\\mathrm{f}_{5/2},$ $4\\mathrm{f}_{7/2}$ of divalent $\\mathrm{Pb^{2+}}$ , respectively, and the two shoulder peaks at 141.3 and $\\mathrm{136.4~eV}$ around lower BE were associated with metallic $\\mathrm{Pb}^{0}$ . We calculated the intensity ratio of $\\mathrm{Pb}^{0}/(\\mathrm{Pb}^{0}+\\mathrm{Pb}^{2+})$ for three metal-incorporated samples and the reference to observe a notable tendency (Fig. 2, A and D, and table S1). The $\\mathrm{Pb}^{0}$ intensity ratio in reference reached $5.4\\%$ , which is comparable to that of ${\\mathrm{Y}}^{3+}$ -incorporated film. This ratio in the perovskite film with oxidative $\\mathrm{Eu^{3+}}$ and $\\mathrm{Fe^{3+}}$ additives was reduced to nearly $1.0\\%$ , indicating that metallic $\\mathrm{Pb}^{0}$ was successfully oxidized. \n\nWith respect to ${\\mathrm{~\\boldmath~I~}}^{0}$ species, it is difficult to obtain $\\boldsymbol{\\mathrm{I}}^{0}/(\\boldsymbol{\\mathrm{I}}^{0}+\\boldsymbol{\\mathrm{I}}^{-})$ ratio by peak fitting accurately the absorption spectra of bottom layer in which MAI mixed with $\\mathsf{E u}^{3+}$ or $\\mathsf{F e}^{3+}$ dissolved in water/chloroform. (E) EPR spectra of $\\mathsf{M A P b l}_{3}$ film with or without $\\mathsf{E u}^{3+}$ incorporation and $\\mathsf{E u}_{2}\\mathsf{O}_{3}$ sample, for which the value of proportionality factor $\\cdot g$ -factor) is 2.0023. (F) Proposed mechanism diagram of cyclically elimination of ${\\mathsf{P b}}^{0}$ and $1^{\\circ}$ defects and regeneration of $\\mathsf{E U}^{3+}\\cdot\\mathsf{E U}^{2+}$ metal ion pair. a.u., arbitrary units; Ref, reference. \n\n![](images/81daaf9813e13f737c83cbb28c12a6107d631a98fa168c57028ab1fc5d634e36.jpg) \nFig. 1. $\\mathsf{E u}^{3+}\\cdot\\mathsf{E u}^{2+}$ ion pair promotes the conversion of $\\mathsf{P}\\mathsf{b}^{\\mathsf{o}}$ and $1^{\\circ}$ to $\\mathsf{P b}^{2+}$ and $\\ulcorner$ in solution and perovskite film. (A) $|^{0}$ and ${\\mathsf{P b}}^{0}$ powder dispersed in mixed DMF/IPA solvent (volume ratio 1:10) with or without $\\mathsf{E u}^{3+}$ [Eu(acac)3], and the solutions were stirred at $100^{\\circ}\\mathrm{C}$ . (B) The UV-vis absorption spectra of the upper solution and (C) XRD patterns of the bottom precipitation from the sample and reference solutions (after $60~\\mathrm{{min}}^{\\cdot}$ ) shown in (A). (D) The representative solution and \n\nbecause ${\\mathrm{I}}^{0}$ species are volatile during the annealing process of perovskite film preparation. Thus, we examined the ratio of $\\mathrm{I/Pb}$ and BE shift to monitor the iodine evolution indirectly. As shown in Fig. 2, B and E, and table S1, we observed the similar $\\mathrm{I/Pb}$ ratio in the reference and the ${\\mathrm{Y}}^{3+}$ - incorporated sample but a much lower ratio in the $\\mathrm{Fe^{3+}}$ sample. Incorporation of $\\mathrm{Fe^{3+}}$ likely generated ${\\boldsymbol{\\mathrm{I}}}^{0}$ species that were released. A higher I/Pb ratio was observed in the ${\\mathrm{Eu}}^{3+}$ sample compared with the reference, possibly indicating less volatile ${\\mathrm{~\\boldmath~I~}}^{0}$ species produced in the corresponding film. Furthermore, the BE of I $\\mathrm{3d_{3/2}}$ further confirmed the argument, wherein it shifted toward a higher value of $0.3~\\mathrm{eV}$ in $\\mathrm{Fe^{3+}}$ sample but lower $0.2\\:\\mathrm{eV}$ in $\\mathrm{Eu^{3+}}$ sample as compared with the reference. Given the lower BE of I–, it clearly showed that $\\mathrm{I}^{-}$ was well preserved in the ${\\mathrm{Eu}}^{3+}$ sample. In addition, $\\mathrm{Eu^{2+}}$ was $36\\%$ of the total Eu content, which further confirmed the $\\mathrm{Eu}^{3+}\\mathrm{-Eu}^{2+}$ ion pair working as a redox shuttle (Fig. 2C). \n\nAccording to the charge conservation rule, the amount of ${\\boldsymbol{\\mathrm{I}}}^{0}$ should be twice that of $\\mathrm{Pb}^{0}$ involved in the entire redox reaction. Iodine species (HI and ${\\mathrm{I}}_{2}^{\\cdot}$ ) are all volatile, which follows the 1:2 molar ratio (33). We checked the total change in the amount of iodine $\\left(\\Delta\\mathrm{I}\\right)$ and lead $(\\Delta\\mathrm{Pb}^{0})$ in the film upon the addition of $\\mathrm{Eu(acac)_{3}}$ , wherein $\\Delta\\mathrm{I}/{\\Delta\\mathrm{Pb}}^{0}$ was calculated to be 3.5 (see table S1 and supplementary text). The change in the amount of iodine $\\left(\\Delta\\mathrm{I}\\right)$ was about three times that of lead $(\\Delta\\mathrm{Pb}^{0})$ during the degradation process, indicating that the amount of ${\\mathrm{~\\boldmath~I~}}^{0}$ species preserved was twice that of $\\mathrm{Pb}^{0}$ species consumed upon redox shuttle addition. In the context of a redox reaction, the standard electrode potential $(\\mathrm{E}^{\\uptheta})$ is often used as a reference point to rationally predict the occurrence of the reaction. According to the $\\operatorname{E}^{6}$ of each half reaction involved (which may deviate in solid materials) (table S2), $\\mathrm{Fe^{3+}}$ is too oxidative and oxidizes $\\mathrm{Pb}^{0}$ and ${\\boldsymbol{\\mathrm{I}}}^{-}$ simultaneously. On the contrary, ${\\mathrm{Eu}}^{3+}$ exhibited the suitable $\\boldsymbol{\\mathrm{E}}^{\\ominus}$ to selectively oxidize $\\mathrm{Pb}^{0}$ without ${\\boldsymbol{\\mathrm{I}}}^{-}$ oxidation, while the reduction product of $\\mathrm{Eu}^{2+}$ reduced ${\\boldsymbol{\\mathrm{I}}}^{0}$ to ${\\boldsymbol{\\mathrm{I}}}^{-}$ at same time. Thus, the constant elimination of $\\mathrm{Pb}^{0}$ and ${\\mathrm{~\\boldmath~I~}}^{0}$ defects still preserved the $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ ion pair. \n\nWe examined the effectiveness of $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ redox shuttle in the film. Metallic $\\mathrm{Pb}^{0}$ is the major accumulated defect in aged perovskite films because of its nonvolatility (33). The content of $\\mathrm{Pb}^{0}$ is a measure of the extent of decomposition in the perovskite film. When the sample was subjected to 1 sun illumination or $85^{\\circ}\\mathrm{C}$ aging condition for more than 1000 hours, the $\\mathrm{{Pb}^{0}/(\\mathrm{{Pb}^{0}+}}$ $\\mathrm{Pb}^{2+})$ ratio in films with redox shuttle were $2.5\\%$ or $2.7\\%$ , compared with $7.4\\%$ or $11.3\\%$ in the reference film, respectively, as shown in fig. S1 and table S3. The redox shuttle can preserve the $\\mathrm{I/Pb}$ ratio in the aged film. Meanwhile, the corresponding $\\mathrm{I/Pb}$ ratio in $\\mathrm{Eu^{3+}}$ -incorporated film was 2.68 or 2.57 as compared with that of reference 2.30 or 2.13, indicating the perovskite film was well preserved. \n\nWe also examined the crystallographic and optoelectronic properties perovskite films with the redox shuttle. According to XRD results, the phase structure was retained in the perovskite films with improved crystallinity upon $\\mathrm{Eu}^{3+}$ addition (figs. S2 to S4). No residual acetylacetonate anion was detected by XPS and Fourier transform infrared spectroscopy measurement (figs. S5 and S6). The $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ ions were concentrated near the film surface, wherein the detected $\\mathrm{Eu/Pb}$ ratio was much higher than the precursor ratio (table S1). When the $\\mathrm{Eu(acac)_{3}}$ was introduced from 0.15 to $4.8\\%$ , we observed neither extra diffraction peaks nor an obvious shift of diffraction peaks in the XRD patterns (figs. S2 to S4), which indicates that $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ ions may not necessarily accommodate in the crystal lattice. \n\nGiven the similar radius of $\\mathrm{Eu}^{2+}[117\\mathrm{pm}(46)]$ and $\\mathrm{Pb^{2+}}$ $({\\bf{119}}{\\bf{\\ p m}})$ ), however, we cannot confidently rule out the possibility that ${\\mathrm{Eu}}^{2+}$ replaces $\\mathrm{Pb^{2+}}$ at B site, wherein direct evidence is expected. In addition, europium-iodine–based organic-inorganic perovskite (47) and lanthanide ions doped $\\mathrm{CsPbX_{3}}$ perovskite nanocrystals were found in previous reports (48). The morphology and grain size of the perovskite film with the tiny amount redox shuttle remained similar to the reference (Fig. 3A and fig. S7). Also, we did not observe obvious orientation variation by synchrotron grazing-incidence wide-angle x-ray scattering (GIWAXS) analysis (Fig. 3B and fig. S8). \n\n![](images/3aeeb2678106ded29506bfa970d4b77319dbb88eeb049add42871fc2f9ae897e.jpg) \nFig. 2. High-resolution XPS spectra of Pb 4f, I 3d, and the Eu 3d of perovskite films with the incorporation of $1\\%$ M/Pb different acetylacetonate metal salts [M(acac)3, $\\boldsymbol{\\mathsf{M}}=\\boldsymbol{\\mathsf{E}}\\boldsymbol{\\mathsf{u}}^{3+}$ , $\\gamma^{3+}$ , $\\mathsf{F e}^{3+}]$ . (A) Pb 4f spectra, the insertions are the enlarged spectra of ${\\mathsf{P b}}^{0}$ 4f. (B) I 3d spectra. (C) Eu 3d spectra. (D) Fitted results of the $\\mathsf{P b}^{0}/(\\mathsf{P b}^{0}{+}\\mathsf{P b}^{2+})$ ratio. (E) Fitted results of I/Pb ratio. \n\nIn addition, the optical bandgap of the perovskite film upon $\\mathrm{Eu^{3+}}$ addition was calculated to be 1.55 eV, similar to that of the reference (fig. S9). The photoluminescence (PL) intensity (fig. S10) and carrier lifetime (Fig. 3C) increased in the perovskite film with the incorporation of ${\\mathrm{Eu}}^{3+}$ , indicating the decrease of nonradiative recombination centers from defects elimination. The improvement of the morphology and grain size could also lead to the increased PL lifetime, so the defects reduction should be further confirmed by other methods. We used the space charge–limited current (SCLC) measurement to quantify the defect density $N_{\\mathrm{defects}}$ of $5.1\\times10^{15}$ and $1.5\\times10^{16}\\ \\mathrm{cm^{-3}}$ for $\\mathrm{Eu^{3+}}$ -incorporated samples and the reference, respectively (Fig. 3D). \n\nWe studied the influence of the $\\mathrm{Eu}^{3+}\\ –\\mathrm{Eu}^{2+}$ ion pair on the formation energies of redox reaction, lattice stability, and energy band structure by density functional theory (DFT) calculations. To construct the model, a small fraction of metal ions $\\mathrm{(Eu^{3+})}$ was intercalated into two adjacent lattices (Fig. 3E), given the observation that Eu was concentrated at surfaces and grain boundaries. The formation energies for defects elimination (Eqs. 1 and 2) were calculated (Fig. 3F). For both reference and $\\mathrm{Eu^{3+}}$ -incorporated systems, the half reactions related to $\\mathrm{Pb}^{0}$ elimination required a substantially high potential energy as the main barrier, whereas the ${\\mathrm{~\\boldmath~I~}}^{0}$ elimination half reactions were comparably favorable. However, after introducing Eu species at the interface, the barrier in $\\mathrm{{Pb}}^{0}$ elimination half reactions was greatly decreased, but the barrier for ${\\mathrm{~\\boldmath~I~}}^{0}$ elimination half reactions decreased only slightly. With the assistance of Eu species at the interface, the overall redox potential energy has been much lowered, representing an energetical stabilization trend for the charge-transfer reaction (Fig. 3F). \n\nWe also compared the thermodynamic properties for reference and Eu-incorporated systems. Figure 3G shows that the $\\mathrm{\\mathbf{MAPbI_{3}}}$ with Eu incorporation has a steeper slope in change of free energy $\\Delta G$ than in that of reference, meaning that Eu-incorporated $\\mathbf{MAPbI_{3}}$ shows a more energetically favorable physicochemical trend than pure $\\mathbf{MAPbI_{3}}$ does. Additionally, it reveals Eu incorporation in $\\mathbf{MAPbI_{3}}$ materials did not bring in obvious electronic disorders as extra traps (fig. S11). \n\nWe incorporated the perovskite absorber equipped with the redox shuttle in two device configurations. One is based on $\\mathrm{ITO/TiO_{2}/}$ perovskite/spiro-OMeTAD/Au, wherein spiroOMeTAD refers to $^{2,2^{\\prime},7,7^{\\prime}}$ -tetrakis- $\\cdot N\\mathcal{N}$ -di- $p$ - methoxyphenylamine)-9,9′-spirobifluorene, with $\\mathrm{MAPbI_{3}(C l)}$ . The other is based on ITO $\\mathrm{\\SnO_{2}/}$ perovskite/spiro-OMeTAD (modified)/Au for higher PCE and stability, with $(\\mathrm{FA},\\mathrm{MA},\\mathrm{Cs})\\mathrm{Pb}(\\mathrm{I},\\mathrm{Br}){}_{3}(\\mathrm{Cl}),$ , in which FA is formamidinium. Both perovskites were deposited by means of a traditional two-step method, during which $\\mathrm{Eu(acac)_{3}}$ or other additives were added in $\\mathrm{PbI_{2}/D M F}$ precursor solution. The two devices showed similar trends (Fig. 4A and fig. S12). The $\\mathrm{Eu^{3+}}$ -incorporated devices exhibited the best PCE, whereas the $\\mathrm{Fe^{3+}}$ -incorporated devices suffered from the markedly decreased PCE. The average PCE increased from 18.5 to $20.7\\%$ in the mixed perovskite upon ${\\mathrm{Eu}}^{3+}$ addition (Fig. 4A), which is attributed to the effective defects elimination. We attributed the decreased PCE in $\\mathrm{Fe^{3+}}$ -incorporated devices to the additional ${\\mathrm{I}}^{0}$ defects introduced by oxidation. \n\n![](images/901600e84099b98de45f3db9cc2cfce0b58713335706927c857685485450affe.jpg) \nFig. 3. Influence of morphology, orientation, electronic structure, carrier behaviors of $\\mathsf{E u}^{3+}$ -incorporated perovskite film, and results of DFT calculations. The characterization of reference and $0.15\\%$ ${\\mathsf{E u}}^{3+}$ -incorporated perovskite film: (A) scanning electron microscopy images; (B) GIWAXS data; (C) time-resolved photoluminescence spectra; (D) $J-V$ characteristics of devices (ITO/perovskite/Au), used for estimating the SCLC defects concentration $(N_{\\mathrm{defects}}=2\\varepsilon\\varepsilon_{0}V_{\\sf T F L}/{\\mathrm e L}^{2}$ , e and $\\scriptstyle\\varepsilon_{0}$ are the \ndielectric constants of perovskite and vacuum permittivity, $L$ is the thickness of the perovskite film, and e is the elementary charge). (E) The interface ultrathin Eu clustering-layer-incorporated structural model. (F) Left: half-reaction potential barriers; right: overall redox charge-transfer reaction barrier for Eu incorporated at the interface. (G) The summary of $\\Delta G$ between $\\mathsf{M A P b l}_{3}$ and $\\mathsf{M A P b l}_{3}$ incorporated with Eu at the interface. \n\nOne of the optimized devices achieved the PCE of $21.52\\%$ (reverse $21.89\\%$ , forward $21.15\\%$ ) (Fig. 4B) with negligible hysteresis (certified reverse $20.73\\%$ , forward $20.30\\%$ , average $20.52\\%$ , certificate attached in fig. S13). The measured stable output at maximum point (0.97 V) was $20.9\\%$ . Integrating the overlap of the incident-photon-to-currentefficiency spectrum of ${\\mathrm{Eu}}^{3+}$ -incorporated PSCs under the AM 1.5-G solar photon flux generated the current density of $23.2\\mathrm{\\mA{\\cdot}c m^{-2}}$ (fig. S14). The stabilized $J{-}V$ performance of PSCs was evaluated as follows (49): parameters are measured under a 13-point IV sweep configuration wherein the bias voltage (current for open circuit voltage $V_{\\mathrm{OC}}$ determination) is held constant until the measured current (voltage for $V_{\\mathrm{OC}})$ was determined to be unchanging at the $0.05\\%$ level. The original, stabilized, and poststabilized efficiency of ${\\mathrm{Eu}}^{3+}$ -incorporated PSCs tested by third-party certification institution were similar, which indicates the stable characteristics of the devices (fig. S15). \n\nThe shelf lifetime of the corresponding devices was investigated, wherein the PCE evolution was descripted for solar cells stored in an inert environment (Fig. 4C). With the $\\mathrm{Eu^{3+}\\mathrm{-Eu^{2+}}}$ redox shuttle incorporated, the devices maintained $90\\%$ of the original PCE even after 8000 hours storage because of improved long-term $V_{\\mathrm{OC}},$ short-circuit current density $(\\mathrm{J}_{\\mathrm{SC}})$ and fill factor (FF) stability (fig. S16). Although the stability of ${\\mathrm{Y}}^{3+}$ -incorporated PSCs was comparable to the reference, $\\mathrm{Fe^{3+}}$ -incorporated PSC showed severely deteriorated stability, which lost the photoelectric conversion capability completely after merely 2000 hours of storage. \n\nTo estimate the stability of ${\\mathrm{Eu}}^{3+}$ -incorporated PSCs under operational conditions, half solar cells were subjected to either continuous 1 sun illumination or $85^{\\circ}\\mathrm{C}$ aging condition, respectively (Fig. 4D), in which the top charge-transfer materials and electrode were deposited after aging test. Improved long-term $V_{\\mathrm{OC}}$ and FF stability (fig. S17) allowed the devices, after 1000 hours, to retain $93\\%$ of the original PCE continuous 1 sun illumination or $91\\%$ after heating at $85^{\\circ}\\mathrm{C}.$ Several previous studies showed that smallmolecule spiro-OMeTAD would crystallize under thermal stress and create pathways that allow for an interaction of the perovskite and the metal electrode $(50,5I)$ . By modifying the holetransport materials (spiro-OMeTAD) with conductive polymer poly(triarylamine), the full devices incorporated with the $\\mathrm{Eu^{3+}-E u^{2+}}$ ion pair maintained $92\\%$ and $89\\%$ of the original PCE because of obvious long-term $V_{\\mathrm{OC}}$ and FF stability improvement (fig. S18) under the same light or thermal stress for 1500 hours, respectively (Fig. 4E). Furthermore, the $\\mathrm{Eu^{3+}}$ -incorporated full devices could maintain $91\\%$ of the original stable PCE tracked at maximum power point (MPP) for 500 hours (Fig. 4F). \n\n![](images/15395d8d4ed97e2ee73bbbaa7fbb33627a1c38b025bb6e9632166d11ab0fa583.jpg) \nFig. 4. Long-term stability and original performance evolution of PSCs. (A) Original performance evolution based on $(F A,M A,C s)P b(1,B r)_{3}(C|)$ perovskite with the incorporation of $0.15\\%$ different ${\\sf M}({\\sf a c a c})_{3}$ $\\langle\\mathsf{M}=\\mathsf{E}\\mathsf{U}^{3+}$ , $\\mathsf{Y}^{3+}$ , $\\mathsf{F e}^{3+\\cdot}$ ). (B) The J-V curve, stable output (measured at 0.97 V), and parameters of $0.15\\%$ Eu3+-incorporated champion devices. (C) Long-term stability of PSCs based on $\\mathsf{M A P b l}_{3}(\\mathsf C|)$ perovskite absorber with the incorporation of $0.15\\%$ different $[\\mathsf{M}(\\mathsf{a c a c})_{3}$ $(\\mathsf{M}=\\mathsf{E u}^{3+},\\mathsf{Y}^{3+},\\mathsf{F e}^{3+})$ , stored in \n\ninert condition. The PCE evolution of $\\mathsf{E U}^{3+}\\cdot\\mathsf{E U}^{2+}$ -incorporated and reference devices under 1 sun illumination or $85^{\\circ}\\mathrm{C}$ aging condition: (D) half PSCs (original PCE: $0.15\\%$ $\\mathsf{E u}^{3+}$ incorporated PSCs, $19.21\\pm0.54\\%$ ; reference PSCs, $18.05\\pm0.38\\%$ ) and (E) full PSCs (original PCE: $0.15\\%$ $\\mathsf{E u}^{3+}$ incorporated PSCs, $19.17\\pm0.42\\%$ ; reference PSCs, $17.82\\pm0.30\\%$ ). Scanning speed is $20\\mathrm{mV/s}$ . (F) The MPP tracking of $0.15\\%$ $\\mathsf{E u}^{3+}$ -incorporated device, measured at 0.97 V and 1-sun illumination. \n\n# REFERENCES AND NOTES \n\n1. A. Kojima, K. Teshima, Y. Shirai, T. Miyasaka, J. Am. Chem. Soc. 131, 6050–6051 (2009). \n2. M. M. Lee, J. Teuscher, T. Miyasaka, T. N. Murakami, H. J. Snaith, Science 338, 643–647 (2012). \n3. H. Zhou et al., Science 345, 542–546 (2014). \n4. J.-H. Im, I.-H. Jang, N. Pellet, M. Grätzel, N.-G. Park, Nat. Nanotechnol. 9, 927–932 (2014). \n5. M. Yang et al., Adv. Mater. 27, 6363–6370 (2015). \n6. O. Malinkiewicz et al., Nat. Photonics 8, 128–132 (2014). \n7. W. S. Yang et al., Science 348, 1234–1237 (2015). \n8. W. S. Yang et al., Science 356, 1376–1379 (2017). \n9. National Renewable Energy Laboratory (NREL) Efficiency chart (2018); www.nrel.gov/pv/assets/pdfs/pv-efficiency-chart. 20181214.pdf. \n10. N. H. Tiep, Z. Ku, H. J. Fan, Adv. Energy Mater. 6, 1501420 (2016). \n11. Y. Rong, L. Liu, A. Mei, X. Li, H. Han, Adv. Energy Mater. 5, 1501066 (2015). \n12. T. A. Berhe et al., Energy Environ. Sci. 9, 323–356 (2016). \n13. G. Grancini et al., Nat. Commun. 8, 15684 (2017). \n14. J. P. Correa-Baena et al., Science 358, 739–744 (2017). \n15. D. C. Jordan, S. R. Kurtz, Prog. Photovolt. Res. Appl. 21, 12–29 (2013). \n16. Q. Cao et al., Adv. Energy Mater. 1, 845–853 (2011). \n17. F. De Angelis et al., ACS Energy Lett. 2, 857–861 (2017). \n18. J. M. Frost et al., Nano Lett. 14, 2584–2590 (2014). \n19. Z. Yu, L. Sun, Adv. Energy Mater. 5, 1500213 (2015). \n20. W. Li, J. Li, G. Niu, L. Wang, J. Mater. Chem. A 4, 11688–11695 (2016). \n21. W. Li et al., Energy Environ. Sci. 9, 490–498 (2016). \n22. M. Saliba et al., Science 354, 206–209 (2016). \n23. M. Hösel, R. R. Søndergaard, M. Jørgensen, F. C. Krebs, Adv. Eng. Mater. 15, 1068–1075 (2013). \n24. Y. Han et al., J. Mater. Chem. A 3, 8139–8147 (2015). \n25. Y. Li et al., J. Am. Chem. Soc. 137, 15540–15547 (2015). \n26. H. Azimi et al., Adv. Energy Mater. 5, 1401692 (2015). \n27. J. Cao et al., Nanoscale 7, 9443–9447 (2015). \n28. X. Li et al., Nat. Chem. 7, 703–711 (2015). \n29. W. Peng et al., Angew. Chem. Int. Ed. 55, 10686–10690 (2016). \n30. R. K. Gunasekaran et al., ChemPhysChem 19, 1507–1513 (2018). \n31. S. Wang, Y. Jiang, E. J. Juarez-Perez, L. K. Ono, Y. Qi, Nat. Energy 2, 16195 (2016). \n32. S. R. Raga et al., Chem. Mater. 27, 1597–1603 (2015). \n33. Y. Li et al., J. Phys. Chem. C 121, 3904–3910 (2017). \n34. B. Philippe et al., J. Phys. Chem. C 121, 26655–26666 (2017). \n35. H. Cho et al., Science 350, 1222–1225 (2015). \n36. V. Adinolfi et al., Adv. Mater. 28, 3406–3410 (2016). \n37. G. W. Hwang et al., Adv. Mater. 27, 4481–4486 (2015). \n38. A. Friedenberg, Y. Shapira, Surf. Sci. 115, 606–622 (1982). \n39. X. Tang et al., J. Mater. Chem. A 4, 15896–15903 (2016). \n40. R. Purbia, S. Paria, Dalton Trans. 46, 890–898 (2017). \n41. H. Xie et al., J. Phys. Chem. C 120, 215–220 (2016). \n42. C. Qin, T. Matsushima, T. Fujihara, C. Adachi, Adv. Mater. 29, 1603808 (2017). \n43. W. Zhang et al., Nat. Commun. 6, 10030 (2015). \n44. Z. Liu et al., Adv. Mater. 29, 1606774 (2017). \n45. D. R. Lide, CRC Handbook of Chemistry and Physics, vol. 5 (CRC Press, ed. 84, 2003). \n46. P. Jakubcová, F. M. Schappacher, R. Pöttgen, D. Johrendt, Z. Anorg. Allg. Chem. 635, 759–763 (2009). \n47. D. B. Mitzi, K. Liang, Chem. Mater. 9, 2990–2995 (1997). \n48. G. Pan et al., Nano Lett. 17, 8005–8011 (2017). \n49. ASTM E948-16, Standard Test Method for Electrical Performance of Photovoltaic Cells Using Reference Cells Unde Simulated Sunlight. ASTM International (2016). \n50. T. Malinauskas et al., ACS Appl. Mater. Interfaces 7, 11107–11116 (2015). \n51. K. Domanski et al., ACS Nano 10, 6306–6314 (2016). \n\n# ACKNOWLEDGMENTS \n\nThe manuscript was improved by the insightful reviews of anonymous reviewers. We thank Y. Yang (University of California, Los Angeles), Y. Li (Beijing Institute of Technology), H. Xie (Central South University), Q. Bao (East China Normal University), and \n\nJ. Xiao (Beijing Institute of Technology) for insightful data analysis and valuable discussion. We also thank the third certification institutions National Institute of Metrology (China) and Newport Technology and Application Center PV Lab (USA) for authentication tests; beamline BL14B1 (Shanghai Synchrotron Radiation Facility, SSRF) for providing beam time and help during the experiments; and Enli technology Co., Ltd. for help with PV efficiency and EQE measurement. Funding: This work was supported by National Natural Science Foundation of China (nos. 91733301, 51672008, 51722201, 21425101, 21331001, and 21621061), MOST of China (2014CB643800), National Key Research and Development Program of China (grant nos. 2017YFA0206701 and 2017YFA0205101), Beijing Natural Science Foundation (4182026), National Key Research and Development Program of China (grant no. 2016YFB0700700), National Natural Science Foundation of China (51673025), Beijing Municipal Science and Technology Project (no. Z181100005118002), and Young Talent Thousand Program. Author contributions: L.W. and H.Z. conceived the idea and designed the project. H.Z., C.-H.Y., and L.-D.S. directed and supervised the research. L.W. fabricated and characterized devices. Y.H., Y.C., L.L., Z.X., and N.L. also contributed to device fabrication. L.W. performed the SEM, PL, UPS, UV-vis, XPS, and XRD measurements. GIWAXS was performed and analyzed by G.Z., supported by BL14B1 beamline of SSRF. B.D. and Z.L. performed EPR. M.S. and B.H. carried out DFT calculation. L.W. drafted the manuscript; Q.C. and H.Z. revised and finalized the manuscript. Competing interests: The authors have no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nwww.sciencemag.org/content/363/6424/265/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S18 \nTables S1 to S3 \nReferences (52–57) \n24 June 2018; resubmitted 25 September 2018 \nAccepted 28 November 2018 \n10.1126/science.aau5701 \n\n# Science \n\n# A $\\mathsf{E u}^{3+\\_E\\mathsf{u}^{2+}}$ ion redox shuttle imparts operational durability to Pb-I perovskite solar cells \n\nLigang Wang, Huanping Zhou, Junnan Hu, Bolong Huang, Mingzi Sun, Bowei Dong, Guanghaojie Zheng, Yuan Huang, Yihua Chen, Liang Li, Ziqi Xu, Nengxu Li, Zheng Liu, Qi Chen, Ling-Dong Sun and Chun-Hua Yan \n\nScience 363 (6424), 265-270. DOI: 10.1126/science.aau5701 \n\n# A redox road to recovery \n\nDevice longevity is a key issue for organic-inorganic perovskite solar cells. Encapsulation can limit degradation arising from reactions with oxygen and water, but light, electric-field, and thermal stresses can lead to metastable elemental lead and halide atom defects. Wang et al. show that for the lead-iodine system, the introduction of the rare earth europium ion pair $\\mathsf{E u}^{3+\\_\\mathsf{E u}^{2+}}$ can shuttle electrons and recover lead and iodine ions $\\mathsf{P b^{Z+}}$ and $\\mid^{-}$ ). Devices incorporating this redox shuttle maintained more than $90\\%$ of their initial power conversion efficiencies under various aging conditions. \n\nScience, this issue p. 265 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41586-019-1357-2", + "DOI": "10.1038/s41586-019-1357-2", + "DOI Link": "http://dx.doi.org/10.1038/s41586-019-1357-2", + "Relative Dir Path": "mds/10.1038_s41586-019-1357-2", + "Article Title": "Planar perovskite solar cells with long-term stability using ionic liquid additives", + "Authors": "Bai, S; Da, PM; Li, C; Wang, ZP; Yuan, ZC; Fu, F; Kawecki, M; Liu, XJ; Sakai, N; Wang, JTW; Huettner, S; Buecheler, S; Fahlman, M; Gao, F; Snaith, HJ", + "Source Title": "NATURE", + "Abstract": "Solar cells based on metal halide perovskites are one of the most promising photovoltaic technologies(1-4). Over the past few years, the long-term operational stability of such devices has been greatly improved by tuning the composition of the perovskites(5-9), optimizing the interfaces within the device structures(10-13), and using new encapsulation techniques(14,15). However, further improvements are required in order to deliver a longer-lasting technology. Ion migration in the perovskite active layer-especially under illumination and heat-is arguably the most difficult aspect to mitigate(16-18). Here we incorporate ionic liquids into the perovskite film and thence into positive-intrinsic-negative photovoltaic devices, increasing the device efficiency and markedly improving the long-term device stability. Specifically, we observe a degradation in performance of only around five per cent for the most stable encapsulated device under continuous simulated full-spectrum sunlight for more than 1,800 hours at 70 to 75 degrees Celsius, and estimate that the time required for the device to drop to eighty per cent of its peak performance is about 5,200 hours. Our demonstration of long-term operational, stable solar cells under intense conditions is a key step towards a reliable perovskite photovoltaic technology.", + "Times Cited, WoS Core": 825, + "Times Cited, All Databases": 847, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000474843400036", + "Markdown": "# Planar perovskite solar cells with long-term stability using ionic liquid additives \n\nSai Bai1,2\\*, Peimei $\\mathrm{Da^{1}}$ , Cheng $\\mathrm{Li}^{3,8}$ , Zhiping Wang1, Zhongcheng Yuan2, Fan $\\mathrm{Fu^{4}}$ , Maciej Kawecki5,6, Xianjie $\\mathrm{Liu^{2}}$ , Nobuya Sakai1 Jacob Tse-Wei Wang7, Sven Huettner3, Stephan Buecheler4, Mats Fahlman2, Feng $\\mathrm{Gao^{1,2*}}$ & Henry J. Snaith1\\* \n\nSolar cells based on metal halide perovskites are one of the most promising photovoltaic technologies1–4. Over the past few years, the long-term operational stability of such devices has been greatly improved by tuning the composition of the perovskites5–9, optimizing the interfaces within the device structures10–13, and using new encapsulation techniques14,15. However, further improvements are required in order to deliver a longer-lasting technology. Ion migration in the perovskite active layer—especially under illumination and heat—is arguably the most difficult aspect to mitigate16–18. Here we incorporate ionic liquids into the perovskite film and thence into positive–intrinsic–negative photovoltaic devices, increasing the device efficiency and markedly improving the long-term device stability. Specifically, we observe a degradation in performance of only around five per cent for the most stable encapsulated device under continuous simulated fullspectrum sunlight for more than 1,800 hours at 70 to 75 degrees Celsius, and estimate that the time required for the device to drop to eighty per cent of its peak performance is about 5,200 hours. Our demonstration of long-term operational, stable solar cells under intense conditions is a key step towards a reliable perovskite photovoltaic technology. \n\nIonic liquids have previously been incorporated into negative–intrinsic– positive perovskite solar cells (in which the perovskite light-absorbing layer is deposited directly on top of the $n$ -type (electron-dominated) charge-extraction layer, rather than on the $\\boldsymbol{p}$ -type (hole-dominated) charge-extraction layer as in a positive–intrinsic–negative cell), resulting in improved device performance19,20. The mechanism driving the improvement has been ascribed to the formation of halide complexes20, or to an advantageous energy-level alignment at the $n$ -type interface between the charge-extraction layer and the perovskite19. Here we incorporate an ionic-liquid-containing triple-cation perovskite absorber of $(\\mathrm{FA_{0.83}M A_{0.17}})_{0.95}\\mathrm{Cs_{0.05}P b(I_{0.9}B r_{0.1})_{3}}$ (ref. 5)—where FA is formamidinium and MA is methylammonium—into positive–intrinsic–negative planar solar cells, using nickel oxide (NiO) and [6,6]-phenyl- $C_{61}^{^{-}}$ -butyric acid methyl ester (PCBM) as, respectively, the $\\boldsymbol{p}$ -type and $n$ -type charge-extraction layers (Fig. 1a). \n\nWe add 1-butyl-3-methylimidazolium tetrafluoroborate $\\mathrm{(BMMBF_{4};}$ Fig. 1b) to the perovskite precursor, and observe enhanced efficiencies in complete photovoltaic cells comprising $0.15{-}0.9\\mathrm{mol\\%}$ of $\\mathrm{BMIMBF_{4}}$ with respect to the lead atoms (Extended Data Fig. 1a–e). We notice an improved performance due to initial light soaking during the current– voltage $(J-V)$ measurements, which we elaborate upon in Extended Data Fig. 1e, f. We measure the steady-state power output (SPO) of the top one or top two best performing devices of each substrate for 50–100 seconds at a fixed voltage near the maximum power point (MPP) obtained from the peak $J{-}V$ curves. For our ‘champion’ device, comprising $0.3\\mathrm{mol}\\%$ $\\mathrm{BMMBF_{4}},$ , we measure an open-circuit voltage $(V_{\\mathrm{OC}})$ of $1.08\\mathrm{V},$ a short-circuit current $(J_{\\mathrm{SC}})$ of $23.8\\mathrm{\\mA}\\mathrm{cm}^{-2}$ and a high fill factor of 0.81, yielding a power conversion efficiency (PCE) of $19.8\\%$ (Fig. 1c and Extended Data Table 1; measurement is made under a light intensity of $105\\mathrm{mW}\\mathrm{cm}^{-2}.$ . The champion control device exhibits a PCE of $18.5\\%$ , owing to a lower $V_{\\mathrm{OC}}$ of $1.02\\mathrm{V}$ and fill factor of 0.79. \n\nWe provide histograms of the PCEs for controls and for devices with $0.3\\mathrm{mol\\%}$ $\\mathrm{BMIMBF_{4}}$ in Fig. 1d. We verify that $J_{\\mathrm{SC}}$ values derived from the $J{-}V$ curves are well matched with the external quantum efficiency (EQE) results, integrated over the solar spectrum (Fig. 1e). We note that, with careful optimization, we can obtain devices with little $J{-}V$ hysteresis (Extended Data Fig. 1h), but there is nevertheless some hysteresis; however, we measure SPOs of $18.7\\%$ and $20.0\\%$ for the champion control device and the device with optimal $\\mathrm{BMIMBF_{4}}$ , respectively (Fig. 1f). We observe increased hysteresis in $\\mathrm{BMIMBF_{4}}$ -containing devices with increasingly higher concentrations of $\\mathrm{BMMBF_{4}}$ in the perovskite film. A pronounced hysteresis and an abnormal ‘overshoot’ close to the MPP in the $J{-}V$ curve appear when $1.2\\mathrm{mol}\\%$ $\\mathrm{BMMBF_{4}}$ is incorporated into the perovskite active layer (Extended Data Fig. 1i). \n\nIn order to understand why adding a low concentration of $\\mathrm{BMIMBF_{4}}$ improves the device performance, we carry out a range of film characterizations. With the addition of $\\mathrm{BMMBF_{4}},$ the $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) peak positions remain unaltered, consistent with neither $\\mathrm{[BMM]^{+}}$ nor $\\mathrm{[BF_{4}]^{-}}$ incorporating into and perturbing the perovskite crystal lattice (Extended Data Fig. 2a). However, a slightly increased intensity of the main diffraction peaks occurs, suggesting enhanced texturing or crystallinity, in good agreement with the slightly enlarged grains seen in scanning electron microscopy (SEM) images (Extended Data Fig. 2b). We find a negligible change in the film absorption, but an increased photoluminescence intensity and extended photoluminescence lifetime for the $\\mathrm{BMIMBF_{4}}$ -containing perovskite film (Extended Data Fig. 2c, d), consistent with reduced defects in the film. \n\nWe carry out ultraviolet photoelectron spectroscopy (UPS) and X-ray photoelectron spectroscopy (XPS) to investigate the surface electronic properties of the perovskite films. From the UPS spectra, we observe a $320\\mathrm{meV}$ decrease in the work function of the perovskite film—from $5.13\\mathrm{eV}$ to $4.81\\mathrm{eV}.$ —with respect to vacuum after addition of $\\mathrm{BMMBF_{4}}$ (Extended Data Fig. 2e). There is no change in the relative Fermi level position with respect to the valance-band offset, indicating that the energy levels of the perovskite absorber, when processed with $\\mathrm{BMMBF_{4}},$ move closer to vacuum. The change in the energy-level structure could result from a shift in the relative energy alignment of the buried heterojunction between the perovskite and the NiO holeextraction layer, or from a shift in energy-level alignment at the topmost perovskite surface, which in a complete device would subsequently contact the PCBM electron-extraction layer. In light of the increased $V_{\\mathrm{OC}}$ and fill factor in the cells, this resulting energetic shift is most likely leading to an improved energetic alignment, with smaller voltage losses at one or both of the heterojunctions, and improved charge extraction21. \n\nFrom XPS spectra of the $\\mathrm{BMIMBF_{4}}$ -containing perovskite film (Fig. 2a), we detect the nitrogen of BMIM at $402.3\\mathrm{eV}$ but no fluorine from $\\mathrm{BF}_{4}$ at $686.2\\mathrm{eV}$ on the top surface. We note that the signal strength for the fluorine 1s orbital is usually stronger than that of the nitrogen 1s orbital; thus our results suggest that there is a predominant presence of BMIM at the top surface. This is also consistent with the energetic shifts being due to the organic cation modifying the surface dipole of the perovskite film. \n\n![](images/5e0928b4eb4e7c05ca589a3832205a67f6c3c9b28535bdf6f7ca863691eb5d2e.jpg) \nFig. 1 | Device architecture and characterization. a, Architecture of our planar heterojunction positive–intrinsic–negative perovskite solar cell. b, Chemical structure of the ionic liquid $\\mathrm{BMIMBF_{4}}$ . $\\mathbf{c-f},$ Characteristics of control devices (navy circles) and devices comprising an optimal amount of $\\mathrm{BMMBF_{4}}$ ( $0.3\\mathrm{mol}\\%$ ; red squares). c, Current density–voltage $\\left(J-V\\right)$ curves of the best performing device for each condition measured from forward bias (FB) to short-circuit (SC) scan and back again under simulated AM1.5 sunlight. The light intensities used to measure the control device and the $\\mathrm{BMIMBF_{4}}$ -containing device were $102\\mathrm{mW}\\mathrm{cm}^{-2}$ and $105\\mathrm{mW}\\mathrm{cm}^{-2}$ , respectively. d, Histograms showing the device \nefficiencies (power conversion efficiency, PCE) of 50 cells per type, fitted with Gaussian distributions (solid lines). e, External quantum efficiency (EQE) spectra (data points) and integrated photocurrent (solid lines), integrated over the AM1.5 $(100\\mathrm{mW}\\mathrm{cm}^{-2}$ ) solar spectrum. The integrated $J_{\\mathrm{SC}}$ values over the entire EQE spectra were $22.3\\mathrm{mA}\\mathrm{cm}^{-2}$ and $22.8\\mathrm{mA}\\mathrm{cm}^{-2}$ for the control and the $\\mathrm{BMIMBF_{4}}$ -containing device, respectively. f, Current density and steady-state power output (SPO), measured for $100\\mathrm{{s}}$ at a fixed voltage near the maximum power point (MPP) identified in the $J{-}V$ curves. Dashed ovals with arrows pointing left and right represent measured SPO and current-density values, respectively. \n\nWe perform time-of-flight secondary-ion mass spectrometry (ToF-SIMS) to probe the chemical composition throughout the film, and we present the signals from both negative and positive secondary ions. In the $\\mathrm{BMMBF_{4}}$ -containing perovskite film, the $\\mathrm{BF}_{4}$ is located mainly at the buried interface (Fig. 2b), while the BMIM exists throughout the bulk film, as well as accumulating at the buried interface (Fig. 2c). This suggests that there is an accumulation of ion pairs of BMIM and $\\mathrm{BF}_{4}$ at the perovskite/NiO interface. We note that if we substitute the NiO with an organic hole-conductor, poly $[N,N^{\\prime}$ -bis(4-butylphenyl)- $\\cdot N,N^{\\prime}$ -bis(phenyl)benzidine] (poly-TPD), we measure decreased efficiencies with obvious hysteresis and the emergence of an overshoot in the $J{-}V$ curve from devices with $0.3\\mathrm{mol\\%}$ $\\mathrm{B\\bar{MIMB}F_{4}}$ (Extended Data Fig. 3). This indicates that the mechanism driving the enhanced device performance in our NiO-based cells is related to the improved interaction between perovskite and NiO at the interface22, facilitated by processing with $\\mathrm{BMIMBF_{4}}$ . \n\nWe characterize the photoluminescence of perovskite thin films between two in-plane electrodes, with a constant electrical bias applied between the electrodes, to determine whether there are any field- or ion-induced changes in the $\\mathrm{BMIMBF_{4}}$ -containing perovskite films17,23. In a series of photoluminescence images of the films as a function of time (Fig. 2d), we observe clear luminescence quenching from the positive towards the negative electrode for the control film. We interpret this to indicate that the photoluminescence is suppressed by ion migration, whereby some regions of the film accumulate a high density of defects, and/or the stoichiometry of the perovskite layer deviates considerably at different positions across the channel between the electrodes24. In stark contrast, for the BMIMBF4-containing perovskite film, the photoluminescence is close to unchanging throughout the entire measurement time. Unpredictably, our observations indicate that ion migration in the perovskite films is greatly suppressed by introducing $\\mathrm{BMIMBF_{4}}$ . \n\nWe then investigate the stability of perovskite films under simulated full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ in ambient air. For the control film, we observe an obvious colour change from black to yellow-grey after 72 hours of light soaking; this results from a fractional decomposition to $\\mathrm{Pb}\\ensuremath{\\mathrm{I}_{2}}.$ as we infer from XRD measurements (Fig. 3a). We expect this to happen because, in the presence of light and oxygen, superoxide is generated, which decomposes $\\mathbf{MAPbI}_{3}$ rapidly to $\\mathrm{\\bar{PbI}}_{2}$ (refs 25,26). \n\n![](images/e6c9ae4040420897b4672dd38b3c057677431cb15c41b2cd5b52e00c6dc9ba11.jpg) \nFig. 2 | Compositional distribution of BMIMBF4 in the perovskite active layer and its impact on ion migration. a, Nitrogen 1s (N 1s) and fluorine 1s (F 1s) XPS spectra of neat $\\mathrm{BMIMBF_{4}}$ , control film and $\\mathrm{BMIMBF_{4}}$ -containing film. b, c, ToF-SIMS depth profiles of the $\\mathrm{BMIMBF_{4}}$ -containing perovskite film on an NiO/fluoride-doped tin oxide (FTO)-coated glass substrate, measured in negative (b) and positive (c) \npolarity. d, Photoluminescence images of control film and $\\mathrm{BMIMBF_{4}}$ - containing film under a constant applied bias (10 V). The bright areas represent photoluminescence emission from the perovskite films. The $\\mathrm{BMIMBF_{4}}$ concentration in the $\\mathrm{BMIMBF_{4}}$ -containing perovskite films is $0.3\\mathrm{mol\\%}$ with respect to the lead atoms. \n\nBy contrast, we observe no discolouration and negligible $\\mathrm{PbI}_{2}$ in the post-aged $\\mathrm{BMIMBF_{4}}$ -containing perovskite films. \n\nIn order to understand which component of the ionic liquid— $\\mathrm{[BMM]^{+}}$ or $\\mathrm{[BF_{4}]^{-}}$ —is important for improving the device efficiency and the film stability, we assess the impact of a range of different ionic additives. We first characterize devices with added $\\mathrm{FABF_{4}}.$ obtaining efficiencies comparable to that of the control (Extended Data Fig. 4a), with no improvement in the film stability (Fig. 3b and Extended Data Fig. 4b). By replacing the $\\mathrm{[BF_{4}]^{-}}$ with halide (X) anions—for example, $\\mathrm{I}^{-}$ , $\\mathrm{Br}^{\\dot{-}}$ or $\\mathrm{Cl^{-}}$ —and retaining the $\\mathrm{[BMIM]^{+}}$ cation, we replicate the improved stability of the perovskite films (Fig. 3b and Extended Data Fig. 4b), but find a substantial decrease in the device efficiencies (Extended Data Fig. 4a). Thus both $\\mathrm{[BMIM]^{+}}$ and $\\mathrm{[BF_{4}]^{-}}$ are required to improve the film’s stability while simultaneously enhancing the device efficiency. \n\nIn order to elucidate the differences between adding $\\mathrm{BMIMBF_{4}}$ versus BMIMX, we investigate the interaction between $\\mathrm{PbI}_{2}$ and these BMIM-based ionic liquids. From photographs of the films, we observe that the $\\mathrm{PbI_{2}/B M I M B F_{4}}$ film retains the yellow colouration of $\\mathrm{Pb}\\ensuremath{\\mathrm{I}_{2}}.$ while all of the $\\mathrm{PbI_{2}/B M I M X}$ samples are optically transparent (Fig. 3c), suggesting the formation of lead halide/imidazolium halide complexes. We find further evidence for the formation of $\\mathrm{Pb}{\\mathrm{I}}_{2}I$ BMIMX complexes in the corresponding film absorption and XRD results (Fig. 3d, e). Furthermore, all of the BMIM-based ionic liquids investigated greatly suppress the emergence of crystalline $\\mathrm{PbI}_{2}$ . \n\nTo further probe the differences between the ionic liquids comprising halide ions and those comprising $\\mathrm{[BF_{4}]^{-}}$ ions, we investigate the compositional distribution of halide throughout a BMIMCl-containing perovskite film. According to our ToF-SIMS results, $\\mathrm{Cl^{-}}$ ions distribute throughout the thickness of the film (Fig. 3f), unlike $\\mathrm{[BF_{4}]^{-}}$ ions (Fig. 2b), indicating that if $\\mathrm{Pb}{\\mathrm{I}}_{2}/$ BMIMX complexes do exist within BMIMX-containing perovskite films, they are likely to be found throughout the bulk film. \n\nFor completeness, we investigate whether $\\mathrm{BMIMBF_{4}}$ needs to be incorporated within the perovskite film, or if it can be pre-processed onto the substrate before perovskite deposition. For cells fabricated through the latter approach—which we term ‘with $\\mathrm{BMIMBF_{4}}$ at the perovskite/NiO interface’—we observe improvement in device efficiency compared with control cells, with a higher $V_{\\mathrm{OC}}$ and fill factor (Extended Data Fig. 4c and Extended Data Table1). This result is consistent with the idea that the enhanced efficiency of cells based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite films is related to an improvement in interfacial properties when $\\mathrm{BMIMBF_{4}}$ accumulates at the perovskite/ NiO interface. However, film stability does not noticeably improve in such devices (Extended Data Fig. 4d). Therefore, we conclude that the improved stability of devices based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite films stems mainly from the presence of BMIM, with the $\\mathrm{BF_{4}}$ ensuring that the introduced ionic liquid does not negatively affect the film properties and device performance of the ensuing solar cells. We assume that, in the as-crystallized films, the large $\\mathrm{[BMM]^{+}}$ ions are excluded from the perovskite crystals and hence accumulate at the surface and grain boundaries of the perovskite film. We postulate that the $\\mathrm{[BMM]^{+}}$ cations will bind to surface sites that would have otherwise been susceptible to degradation via oxygen or moisture adsorption and subsequent reactions under light and heat27, and hence suppress the degradation of the perovskite active layer. However, as is the case for films processed with BMIMX, we speculate that the readily formed large-band-gap complexes of $\\mathrm{PbI_{2}/B M I M X}$ disrupt the perovskite lattice or introduce surface strain, and hence introduce electronic defects into the active layer, inhibiting the photovoltaic performance of the resulting devices. \n\n![](images/ffa18dce04f226f8b9e9c038f8824c320412d572125d0444f36aeb4b8abdb5e0.jpg) \nFig. 3 | Film stability and the interaction between $\\mathbf{P}\\mathbf{b}\\mathbf{I}_{2}$ and BMIMcontaining ionic liquids. a, XRD patterns of pristine and aged samples of control film and film containing $\\mathrm{BMIMBF_{4}}$ $0.3\\mathrm{mol\\%}$ ) on NiO/FTOcoated glass substrates. The stars represent the decomposition product of $\\mathrm{PbI}_{2}$ in the films. The insets show images of the aged samples (around $2.8\\:\\mathrm{cm}\\times2.8\\:\\mathrm{cm},$ ) after $72\\mathrm{{h}}$ of light-soaking at $60{-}65^{\\circ}\\mathrm{C}$ . b, Evolution of the ratio between $\\mathrm{PbI}_{2}$ and perovskite (100) peak intensity in XRD patterns of control film and films with different ionic additives during light ageing \nat $70–75^{\\circ}\\mathrm{C}$ . $\\mathbf{c-e}$ , Characterization of thin films deposited from neat $\\mathrm{PbI}_{2}$ solution or from solutions containing $\\mathrm{PbI}_{2}$ and different BMIM-containing ionic liquids (molar ratio $1/1$ ) on NiO/FTO substrates: c, photographs; d, ultraviolet-visible (UV-Vis) absorption spectra; and e, XRD patterns. The size of the substrate is around $2.8\\:\\mathrm{cm}\\times2.8\\:\\mathrm{cm}$ . The $\\mathrm{PbI_{2}/B M I M B F_{4}}$ film retains the colour of $\\mathrm{PbI}_{2}$ and exhibit a polycrystalline $\\mathrm{Pb}\\mathrm{I}_{2}$ feature. f, ToF-SIMS depth profiles, measured in negative polarity, of perovskite film containing BMIMCl $(0.3\\mathrm{mol\\%})$ ) on an NiO/FTO substrate. \n\nHaving demonstrated the improved stability of $\\mathrm{BMMBF_{4}}$ -containing perovskite films, we proceed to investigate the stability of complete photovoltaic cells under combined heat and light stressing. We first test the stability performance of non-encapsulated devices under full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ (Fig. 4a). Rather like the freshly made devices, we notice light-soaking improvements during $J{-}V$ measurements of the aged devices (Extended Data Fig. 5a), and present the final PCEs based on peak $J{-}V$ values for non-encapsulated cells as a function of ageing time in Fig. 4a. We observe no degradation for both types of device (with or without $\\mathrm{BMMBF_{4}}$ ) during the first 20 hours. By contrast with our previous best reported stability6 and that found in other studies of negative–intrinsic–positive perovskite solar cells5, we do not here observe an early-time light-induced degradation, or ‘burn-in’. This is already a key step forward, and we assign this primarily to our use of a positive–intrinsic–negative device structure comprising NiO as a hole conductor and a $\\mathrm{Cr}/\\mathrm{Cr}_{2}\\mathrm{O}_{3}$ interlayer22,28. For the control device, the PCE quickly decreases to around zero after roughly another 80 hours of ageing. By contrast, the $\\mathrm{BMIMBF_{4}}$ -containing device retains about $86\\%$ of its initial performance after 100 hours of ageing in air. \n\nThe control device discolours in the regions beyond the electrode-protected area, whereas the $\\mathrm{BMIMBF_{4}}$ -containing device shows no visible discolouration (Fig. 4a, insets), consistent with the idea that the enhanced device stability originates from the improved stability of the $\\mathrm{BMIMBF_{4}}$ -containing perovskite active layer. \n\nWe encapsulate a series of cells and probe their long-term stability. We measure improvements in device performance and, in some cases, an obvious decrease in hysteresis in the J–V curves after device encapsulation (Extended Data Fig. 5b, c). In Extended Data Fig. 5d, we compare the stability of devices comprising $\\mathrm{BMIMBF_{4}}$ within the perovskite film with those comprising $\\mathrm{BMIMBF_{4}}$ at the perovskite/ NiO interface, under full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ . We observe no obvious degradation of the encapsulated devices under this ageing condition. For the devices based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite film, we measure an increase in both the $J{-}V.$ -derived efficiency and the SPO, together with a ‘healing’ of the J–V hysteresis after 150 hours of ageing (Extended Data Fig. 5e, f). \n\nWe then allow the chamber temperature to rise to between $70^{\\circ}\\mathrm{C}$ and $75^{\\circ}\\mathrm{C},$ and again evaluate the device stability. We show the evolution of device parameters in Fig. 4b, c and Extended Data Fig. 6a–c. We measure very little degradation in J– $V.$ -determined efficiency for cells based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite film, and a faster degradation of control devices. The cells with $\\mathrm{BMIMBF_{4}}$ at the perovskite/ NiO interface also degrade at a similar rate to the control cells under this higher-temperature ageing. Therefore, it appears essential that the $\\mathrm{BMMBF_{4}}$ is within the perovskite absorber in order to enhance the stability. However, we observe increased hysteresis and, in some instances, the emergence of overshoot in the $J{-}V$ curves for devices based on BMIM $\\mathrm{[BF_{4}}$ -containing perovskite films during higher-temperature light \n\n![](images/1b8d65b25ad37047f50c4defd574d8e0ae177e009541cd120be30f092c454894.jpg) \n\nFig. 4 | Device stability under combined full-spectrum sunlight and heat stressing. a, Evolution of power conversion efficiencies (PCEs) of a non-encapsulated control device and a device with $\\mathrm{BMIMBF_{4}}$ in the perovskite film, during ageing under full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ in air with relative humidity (RH) ranging from $40\\%$ to $50\\%$ . The insets show pictures of the perovskite cells after $100\\mathrm{h}$ of ageing (the size of the substrate is around $2.8\\:\\mathrm{cm}\\times2.8\\:\\mathrm{cm}$ ). b, c, Stability performance of the encapsulated solar cells under full-spectrum sunlight at $70–75^{\\circ}\\mathrm{C}$ . PCE (b) and SPO (c), including standard errors, were calculated from ten devices (and from the best performing eight devices for the SPO) with $\\mathrm{BMIMBF_{4}}$ in the perovskite film, and from seven devices (and from the best performing four devices for the SPO) for the other two sets of devices. The top and bottom stars in the PCE and SPO stability curves for devices with $\\mathrm{BMIMBF_{4}}$ in the perovskite film represent the maximum and minimum values, respectively. d, Long-term stability performance of the most stable device with $\\mathrm{BMIMBF_{4}}$ in the perovskite film, under full-spectrum sunlight and heat stressing at $70–75^{\\circ}\\mathrm{C}$ . The device parameters were collected from the peak FB-to-SC J– $V$ curves for this device. The concentration of the $\\mathrm{BMIMBF_{4}}$ in the perovskite film is $0.3\\mathrm{mol}\\%$ with respect to the lead atoms. \n\nstressing (Extended Data Fig. 6d). For such devices, the SPO values also degrade more quickly than the $J{-}V.$ -determined efficiency, and we observe a roughly $20\\%$ decrease in the initial performance after 1,072 hours of ageing (Fig. 4c). By comparison, for the control cells and that with $\\mathrm{BMMBF_{4}}$ at the perovskite/NiO interface, we observe a roughly $35\\mathrm{-}40\\%$ drop in the SPO over the same ageing period. \n\nIn Fig. 4d we show the longer-term stability results for the moststable cell with $\\mathrm{BMIMBF_{4}}$ in the perovskite film, aged under fullspectrum sunlight at the elevated temperature $(70-75^{\\circ}\\mathrm{C})$ . We observe a slow increase in the $J{-}V.$ -derived efficiency at the beginning of ageing. However, we also measure a small early-time burn-in of the SPO during the first 100 hours or so, coincident with enhanced $J{-}V$ hysteresis under the high-temperature ageing, and proceed to measure a relatively slow drop in the SPO during the extended ageing test. We present the $J{-}V$ and the measured SPO curves at different ageing times in Extended Data Fig. 7a–f, clearly showing the evolution of device performance—including the increased hysteresis in the $J{-}V$ curves— during long-term ageing. Remarkably, the most-stable device based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite film exhibits only around $5\\%$ degradation in the $J{-}V.$ -derived efficiency and around $15\\%$ degradation in the SPO over the entire 1,885-hour ageing test. \n\nBy fitting the degradation data of the most-stable device based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite film (as in Extended Data Fig. 8), we estimate a time to $80\\%$ of the peak PCE $(T_{80})$ of roughly 5,200 hours, and the $T_{80}$ of the post-burn-in SPO to be about 4,100 hours. The $T_{80}$ values of our $J{-}V.$ -determined PCE and SPO are respectively 1.3 and 2.4 times as great as our previous best reported values for negative– intrinsic–positive solar cells28, which were aged at a lower temperature of $50\\mathrm{-}60^{\\circ}\\mathrm{C}$ and exhibited a severe early-time burn-in, with over $20\\%$ of the initial efficiency lost within the first few hundred hours. We would expect that an additional degradation-acceleration factor due to a temperature increase is in the region of fourfold (twofold per $10^{\\circ}\\mathrm{C}$ increase in temperature)29. We therefore estimate that the cells we present here are in the region of five to ten times more stable than our previous most stable devices. \n\nTo put our results into a broader context, we tabulate the long-term stability performance of perovskite solar cells from the literature in Extended Data Table 2, specifying the device structures, the ageing conditions, the degradation factors and the estimated $T_{80}$ values. By comparison with the cells with the longest $T_{80}$ values measured under combined light and heat stressing10, our cells are stressed under ultraviolet-light-containing full-spectrum sunlight at temperatures about $10–15^{\\circ}\\mathrm{C}$ higher, yet deliver a comparable $T_{80}$ lifetime, indicating that our cells are likely to be at least twice as stable. We note that all of the results in Extended Data Table 2 were measured under slightly different conditions (light source, atmosphere, electric bias, temperature, and so on). Ultimately, standardized measurement conditions with which to fairly compare experimental results in different laboratories would greatly benefit the community30. \n\nTo demonstrate the applicability of our strategy for improving operational stability to different perovskite absorber materials, we undertake a similar ageing test with the ‘unstable’ perovskite $\\mathrm{MAPbI}_{3}$ in the same positive–intrinsic–negative device structure (Extended Data Fig. 9a–h). For cells based on $\\mathrm{BMIMBF_{4}}$ -containing $\\operatorname{MAPbI}_{3}$ , ageing at about $60{-}65^{\\circ}\\mathrm{C}$ , we observe a similar improvement in device performance during the first 100 hours, while the performance of control cells decreases slightly. We then set the temperature of the ageing box to about $70–75^{\\circ}\\mathrm{C}$ for a short period, and observe a fast decrease in both the device efficiency and the SPO for all devices. We then drop the temperature back to $60{-}65^{\\circ}\\mathrm{C}$ and proceed with the ageing. The control devices exhibit a faster degradation after the higher-temperature ageing, and their performance quickly decreases to about $60\\%$ of the original values after about 400 hours. By contrast, devices with $\\mathrm{BMIMBF_{4}}$ in the $\\mathrm{MAPbI}_{3}$ perovskite slowly recover to their initial efficiency before the high-temperature ageing, and show less than $10\\%$ degradation in both the $J{-}V$ -derived efficiency and the SPO after about 400 hours of ageing under full-spectrum light and heat stressing (Extended Data Fig. 9). \n\nIn summary, we have presented a simple, broadly applicable method that greatly enhances the long-term operational stability of perovskite solar cells. Our approach represents another milestone towards stable perovskite-based photovoltaic technology, and is likely to be applicable to other optoelectronic applications that use metal halide perovskites. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, statements of data availability and associated accession codes are available at https://doi.org/10.1038/s41586-019-1357-2. \n\nReceived: 7 February 2018; Accepted: 20 May 2019; \nPublished online 10 July 2019. \n1. Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n2. Burschka, J. et al. Sequential deposition as a route to high-performance perovskite-sensitized solar cells. Nature 499, 316–319 (2013). \n3. Jeon, N. J. et al. Compositional engineering of perovskite materials for high-performance solar cells. Nature 517, 476–480 (2015). \n4. Liu, M., Johnston, M. B. & Snaith, H. J. Efficient planar heterojunction perovskite solar cells by vapour deposition. Nature 501, 395–398 (2013). \n5. Saliba, M. et al. Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency. Energy Environ. Sci. 9, 1989–1997 (2016). \n6. Wang, Z. et al. Efficient ambient-air-stable solar cells with 2D–3D heterostructured butylammonium-caesium-formamidinium lead halide perovskites. Nat. Energy 2, 17135 (2017). \n7. McMeekin, D. P. et al. A mixed-cation lead mixed-halide perovskite absorber for tandem solar cells. Science 351, 151–155 (2016). \n8. Saliba, M. et al. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). \n9. Tsai, H. et al. High-efficiency two-dimensional Ruddlesden–Popper perovskite solar cells. Nature 536, 312–316 (2016). \n10.\t Arora, N. et al. Perovskite solar cells with CuSCN hole extraction layers yield stabilized efficiencies greater than $20\\%$ . Science 358, 768–771 (2017). \n11.\t Chen, W. et al. Efficient and stable large-area perovskite solar cells with inorganic charge extraction layers. Science 350, 944–948 (2015). \n12.\t Hou, Y. et al. A generic interface to reduce the efficiency-stability-cost gap of perovskite solar cells. Science 358, 1192–1197 (2017). \n13.\t Christians, J. A. et al. Tailored interfaces of unencapsulated perovskite solar cells for ${>}1,000$ hour operational stability. Nat. Energy 3, 68–74 (2018). \n14.\t Bella, F. et al. Improving efficiency and stability of perovskite solar cells with photocurable fluoropolymers. Science 354, 203–206 (2016). \n15.\t Cheacharoen, R. et al. Design and understanding of encapsulated perovskite solar cells to withstand temperature cycling. Energy Environ. Sci. 11, 144–150 (2018). \n16.\t Divitini, G. et al. In situ observation of heat-induced degradation of perovskite solar cells. Nat. Energy 1, 15012 (2016). \n17.\t Leijtens, T. et al. Mapping electric field-induced switchable poling and structural degradation in hybrid lead halide perovskite thin films. Adv. Energy Mater. 5, 1500962 (2015). \n18.\t Domanski, K. et al. Migration of cations induces reversible performance losses over day/night cycling in perovskite solar cells. Energy Environ. Sci. 10, 604–613 (2017). \n19.\t Yang, D. et al. Surface optimization to eliminate hysteresis for record efficiency planar perovskite solar cells. Energy Environ. Sci. 9, 3071–3078 (2016). \n20.\t Zhang, Y. et al. A strategy to produce high efficiency, high stability perovskite solar cells using functionalized ionic liquid-dopants. Adv. Mater. 29, 1702157 (2017). \n21.\t Luo, D. et al. Enhanced photovoltage for inverted planar heterojunction perovskite solar cells. Science 360, 1442–1446 (2018). \n22.\t Nie, W. et al. Critical role of interface and crystallinity on the performance and photostability of perovskite solar cell on nickel oxide. Adv. Mater. 30, 1703879 (2018). \n23.\t Li, C. et al. Real-time observation of iodide ion migration in methylammonium lead halide perovskites. Small 13, 1701711 (2017). \n24.\t Li, C., Guerrero, A., Huettner, S. & Bisquert, J. Unravelling the role of vacancies in lead halide perovskite through electrical switching of photoluminescence. Nat. Commun. 9, 5113 (2018). \n25.\t Bryant, D. et al. Light and oxygen induced degradation limits the operational stability of methylammonium lead triiodide perovskite solar cells. Energy Environ. Sci. 9, 1655–1660 (2016); correction 9, 1850 (2016). \n26.\t Aristidou, N. et al. Fast oxygen diffusion and iodide defects mediate oxygeninduced degradation of perovskite solar cells. Nat. Commun. 8, 15218 (2017). \n27.\t Sun, Q. et al. Role of microstructure in oxygen induced photodegradation of methylammonium lead triiodide perovskite films. Adv. Energy Mater. 7, 1700977 (2017). \n28.\t Kaltenbrunner, M. et al. Flexible high power-per-weight perovskite solar cells with chromium oxide–metal contacts for improved stability in air. Nat. Mater. 14, 1032–1039 (2015). \n29.\t Ross, J. R. G. Crystalline-silicon reliability lessons for thin-film modules. In Proc. 18th IEEE Photovoltaic Specialists Conference 1114–1020 (1985). \n30.\t Snaith, H. J. & Hacke, P. Enabling reliability assessments of pre-commercial perovskite photovoltaics with lessons learned from industrial standards. Nat. Energy 3, 459–465 (2018). \n\nAcknowledgements This work was funded in part by the UK Engineering and Physical Sciences Research Council (EPSRC; grants EP/M015254/2 and EP/M024881/1); the European Research Council (ERC) Starting Grant (717026); the Swedish Research Council Vetenskapsrådet (grant 330-2014- 6433); the European Commission Marie Skłodowska-Curie action (grant INCA 600398); the Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linköping University (faculty grant SFOMat-LiU 2009-00971); and the European Union’s Horizon 2020 research and innovation program under grant agreement 763977 of the PerTPV project. S. Bai is a VINNMER Fellow and Marie Curie Fellow. P.D. and Z.Y. acknowledge support from the China Scholarship Council (CSC). C.L. and S.H acknowledge financial support from the Bavarian State Ministry of Science, Research, and the Arts for the Collaborative Research Network ‘Solar Technologies go Hybrid’ and the German Research Foundation (DFG). M.K. acknowledges support from the Swiss National Science Foundation (grant cr23i2-162828). We thank H. Long, Z. Yan, C. Bao, N. Noel, B. Wenger, J. Ball and O. Inganäs for experimental assistance and discussions. \n\nReviewer information Nature thanks Aditya Mohite, Shougen Yin and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\nAuthor contributions S. Bai, F.G. and H.J.S. conceived the idea of the project, designed the experiments, analysed the data and wrote the manuscript. S. Bai performed the fabrication, optimization and characterization of the films and solar cells. P.D. contributed to characterization of the films and stability tests of the devices. C.L. and S.H. characterized the ion-migration process. S. Bai, Z.W. and Z.Y. performed the XRD and SEM characterizations. M.K., F.F. and S. Buecheler conducted the ToF-SIMS measurements and analysed the data. X.L. and M.F. carried out the UPS and XPS measurements and analysed the data. S. Bai, Z.W. and N.S. performed the optical measurements. J.T-W.W. contributed to optimization of the positive–intrinsic–negative device architecture. All authors commented on the final version of the manuscript. F.G. and H.J.S. supervised the project. \n\nCompeting interests H.J.S. is a co-founder, Chief Scientific Officer and a Director of Oxford PV Ltd. Oxford University has filed a patent related to the subject matter of this manuscript. \n\n# Additional information \n\nExtended data is available for this paper at https://doi.org/10.1038/s41586- 019-1357-2. \nSupplementary information is available for this paper at https://doi.org/ 10.1038/s41586-019-1357-2. \nReprints and permissions information is available at http://www.nature.com/ reprints. \nCorrespondence and requests for materials should be addressed to S. Bai or F.G. or H.J.S. \nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 \n\n# Methods \n\nMaterials. Detailed information on all chemicals used here is listed in Supplementary Table 1. \n\nSubstrate preparation. Fluoride-doped tin oxide (FTO)-coated glass substrates (Pilkington TEC 7, sheet resistance 7–8 ohms per square) were etched with zinc powder and $2\\mathrm{M}$ hydrochloric acid (HCl) to produce desired patterns. The substrates were cleaned with a $2\\mathrm{vol}\\%$ solution of Hellmanex cuvette-cleaning detergent, then washed with deionized water and ethanol, and dried with dry nitrogen. The substrates were treated with UV-ozone for $10\\mathrm{min}$ before use. Substrates coated with poly $\\mathrm{\\Phi}_{\\cdot}\\mathrm{N},N^{\\prime}$ -bis(4-butylphenyl)- $\\cdot N,N^{\\prime}$ -bisphenylbenzidine] (poly-TPD) were fabricated as described31. The nickel oxide (NiO) precursor (0.1 M) was prepared by dissolving nickel acetylacetonate $(\\mathrm{Ni}(\\mathsf{a c a c})_{2})$ in anhydrous ethanol, and HCl ( $1\\%$ $\\nu/\\nu)$ was used as the stabilizer. The precursor solution was stirred overnight at room temperature, filtered $:0.45\\upmu\\mathrm{m}$ , polytetrafluoroethylene (PTFE)), and spin-coated on cleaned FTO substrates at $^{4,000}$ r.p.m. for $40\\:s.$ . The films were dried at $180^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ and then sintered at $400^{\\circ}\\mathrm{C}$ in air for $45\\mathrm{{min}}$ to obtain a compact NiO layer. For the $\\mathrm{BMIMBF_{4}}$ -treated substrates, a $3\\mathrm{mg}\\mathrm{ml}^{-1}$ $\\mathrm{BMMBF_{4}}$ solution in ethanol was spin-coated onto the NiO substrates at $6,000{\\mathrm{~r.p.m}}$ ., followed by annealing at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ in a glove box. The relative humidity during spin-coating and thermal annealing of NiO films ranged from $40\\%$ to $50\\%$ in our clean room. Preparation of perovskite precursor solutions. All chemicals used for the perovskite precursor solutions are listed in Supplementary Table 1. We prepared the $(\\mathrm{FA_{0.83}M A_{0.17}})_{0.95}\\mathrm{Cs_{0.05}P b(I_{0.9}B r_{0.1})_{3}}$ triple-cation perovskite precursor solution (1.3 M) by dissolving formamidinium iodide (FAI, $176.6\\mathrm{mg})$ and methylammonium iodide (MAI, $33.1\\mathrm{mg}$ ), CsI $(16.9\\mathrm{mg})$ , $\\mathrm{PbI}_{2}$ ( $\\mathrm{509.4mg)}$ and $\\mathrm{Pb}\\mathrm{Br}_{2}(71.6\\mathrm{mg})$ 1 in $1\\mathrm{ml}$ of a mixed anhydrous solvent of $N,N.$ -dimethylformamide (DMF), dimethyl sulfoxide (DMSO) and $N$ -methyl-2-pyrrolidinone (NMP). The ratio of the solvents was fixed at $4/0.9/0.1\\$ (DMF/DMSO/NMP) by volume. In parallel, we prepared ionic liquids containing perovskite precursor solution by dissolving the same components in mixed solvent containing different ionic liquids $(1.2\\mathrm{mol}\\%)\\$ ). The perovskite precursor solutions were stirred overnight in the glove box and filtered ( $:0.45\\upmu\\mathrm{m}$ , PTFE) before spin-coating. The ionic-liquid-containing precursor solutions of desired concentrations were prepared by mixing the precursor without and with ionic liquid $\\cdot1.2\\mathrm{mol}\\%$ ) at different ratios. The precursor solutions for $\\mathbf{MAPbI}_{3}$ perovskite $(1.4\\mathrm{M})$ were prepared by dissolving $\\mathrm{PbI}_{2}$ and MAI with a molar ratio of $1/1$ in anhydrous DMF/DMSO $(4/1$ , volume ratio) without and with $\\mathrm{8MMBF_{4}}$ $0.3\\mathrm{mol}\\%$ ). The perovskite precursor solutions were stirred overnight in the glove box and filtered ( $0.45\\upmu\\mathrm{m}$ , PTFE) before use. \n\nDevice fabrication. Triple-cation perovskite films were deposited in the glove box using a solvent-quenching method32 with anisole as the antisolvent. In detail, $100\\upmu\\mathrm{l}$ perovskite precursor solution was dropped on the NiO-coated FTO substrates $(2.8\\times2.8\\mathrm{cm})$ and spin-coated at $1,300\\ \\mathrm{r.p.m}$ . for 5 s (5-s ramp) and $5{,}000{\\mathrm{r.p.m}}$ . for 30 s (5-s ramp). We quickly dropped $250\\upmu\\mathrm{l}$ anhydrous anisole onto the substrates 5 s before the end of the program. The samples were immediately put on a preheated hot plate and annealed at $100^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . For $\\mathbf{MAPbI}_{3}$ films, the precursor solution was spin-coated at 4,000 r.p.m. for $30~\\mathsf{s}$ in a dry box with a controlled humidity of about $20\\%$ (ref. 33). We dropped $250\\upmu\\mathrm{l}$ anhydrous anisole onto the substrates $10s$ before the end of the program. The films were annealed at $80^{\\circ}\\mathrm{C}$ for 5 min. PCBM solution with a concentration of $20\\mathrm{mg}\\mathrm{ml}^{-1}$ in chlorobenzene (CB)/1,2-dichlorobenzene (ODCB) $(3/1,\\nu/\\nu)$ was spin-coated on top of the perovskite films at a speed of $1,800\\mathrm{r.p.m}$ . for $30{\\mathrm{s}}.$ The samples were then annealed at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . After cooling to room temperature, we dynamically spincoated bathocuproine (BCP) solution $(0.5\\mathrm{mg}\\mathrm{ml}^{-1}$ in isopropanol) on top of the PCBM at a speed of $4{,}000\\ \\mathrm{r.p.m}$ . for $20s$ . We took the samples from the glove box and finished the devices by thermally evaporating chromium $(3.5\\mathrm{nm})$ ) and gold $(100\\mathrm{nm})$ ) electrodes under a vacuum of $6\\times10^{-6}$ torr. \n\nCharacterization of solar cells. We measured $J.$ –V curves in air with a Keithley 2400 source meter under AM1.5 sunlight generated using an ABET Class AAB sun 2000 simulator. The mismatch factor for the test cell, the light source and the National Renewable Energy Laboratories (NREL)-calibrated KG5 filtered silicon reference cell was estimated and applied in order to correctly estimate the equivalent AM1.5 irradiance level. Before measurement of each set of devices, the intensity of the solar simulator was automatically measured using a KG5 reference cell, and this recorded intensity (which typically varied from $99\\mathrm{mW}\\mathrm{cm}^{-2}$ to $105\\mathrm{mW}\\mathrm{cm}^{-2}$ ) was used to calculate the precise power conversion efficiency, where power conversion efficiency is: (electrical power out/solar light power $\\mathrm{in})\\times100\\%$ . All devices were masked with a $0.0919\\mathrm{cm}^{-2}$ metal aperture to define the active area and to eliminate edge effects. The $J{-}V$ curves were measured at a scan rate of $200\\mathrm{mVs^{-1}}$ (delay time of $100\\mathrm{{ms}}$ ) from $1.2\\mathrm{V}$ to $-0.2\\mathrm{V}$ and then back again (from $-0.2\\:\\mathrm{V}$ to $1.2\\mathrm{V}$ ). A stabilization time of 2 s at forward bias of $1.2\\mathrm{V}$ under illumination was done before scanning. We measured the cells multiple times until a peak performance was achieved. This typically took two to five $J{-}V$ scans, in a measurement time of around $1{-}2\\mathrm{min}$ . External quantum efficiency measurements were performed using custom-built Fourier transform photocurrent spectroscopy based on the Bruker Vertex 80v Fourier transform spectrometer. A Newport AAA sun simulator was used as the light source and the light intensity was calibrated with a Newport-calibrated reference silicon photodiode. \n\nFilm characterization. The morphologies of the perovskite films on NiO-coated FTO substrates were characterized using a SEM (Hitachi S-4300) at an accelerating voltage of $3{\\mathrm{-}}5{\\mathrm{kV.}}$ The diffraction patterns were measured from samples of perovskite films on NiO-coated FTO substrates using a Panalytical X’PERT Pro X-ray diffractometer. UV-Vis absorption spectra were measured using a Varian Carry 300 Bio (Agilent Technologies). Steady-state and time-resolved photoluminescence spectra were acquired using a fluorescence lifetime spectrometer (FLuo Time 300, PicoQuant). The samples were excited using a $507\\mathrm{-nm}$ laser (LDH-P-C-510, PicoQuant) with pulse duration of 117 ps, a fluence of about 30 nJ $c\\mathrm{m}^{-2}$ per pulse and a repetition rate of 1 MHz. The photoluminescence data were collected using a high-resolution monochromator and hybrid photomultiplier detector assembly (PMA Hybrid 40, PicoQuant). The samples were prepared on thin insulating amorphous $\\mathrm{TiO}_{2}$ -coated glass substrates to avoid any impacts of morphology and structure change in the perovskite films on the photoluminescence measurements34. UPS and XPS measurements were carried out using a Scienta ESCA 200 spectrometer in ultrahigh vacuum with a base pressure of $\\bar{1}\\times10^{-10}$ mbar. The measurement chamber was equipped with a monochromatic aluminium $(\\operatorname{K}\\alpha)$ X-ray source providing photons with energies of $1,486.6\\mathrm{eV}$ for XPS, and a standard helium-discharge lamp with He Ι photons of $21.22\\mathrm{eV}$ for UPS. The XPS experimental condition was set so that the full width at half maximum of the clean gold $4f_{7/2}$ line (at a binding energy of $84.00\\mathrm{eV}.$ ) was $0.65\\mathrm{eV.}$ The total energy-resolution UPS measurement is about $80\\mathrm{meV}$ as extracted from the width of the Fermi level (at the binding energy of $0.00\\mathrm{eV}$ ) of clean gold foil. All spectra were measured at a photoelectron takeoff angle of $0^{\\circ}$ (normal emission). The work function of film was extracted from the edge of the secondary electron cutoff of the UPS spectra by applying a bias of $-3\\mathrm{V}$ to the sample. \n\nToF-SIMS measurements. Compositional depth profiling of perovskite films was carried out using a ToF-SIMS 5 system from IONTOF, operated in the spectral mode and using a $25\\mathrm{-keV\\Bi_{3}+}$ primary ion beam with an ion current of $0.7\\mathrm{pA}$ . A mass-resolving power of about $8,000\\mathrm{~m~}\\Delta\\mathrm{m}^{-1}$ was reached. For depth profiling, a $500\\mathrm{-eV}\\mathrm{Cs}^{+}$ sputter beam with a current of $28\\mathrm{nA}$ was used to remove material layer by layer in interlaced mode, from a raster area of $300\\upmu\\mathrm{m}\\times300\\upmu\\mathrm{m}$ . Mass spectrometry was performed on an area of $100\\upmu\\mathrm{m}\\times100\\upmu\\mathrm{m}$ in the centre of the sputter crater. A low-energy electron-flood gun was used for charge compensation. In the positive polarity, the $[\\mathrm{SnO+Cs}]^{+}$ secondary ion is the SnO fragment ionized through interaction with the sputter ion ${{\\mathrm{Cs}}^{+}}$ , yielding the highest signalto-noise-ratio positive-secondary-ion signal characteristic of the FTO substrate. In-plane electronic device characterization. For photoluminescence imaging experiments under an electric field, perovskite films on glass samples were deposited with planar gold electrodes on top (channel width of about $150\\upmu\\mathrm{m}$ ). Characterization was performed as described23,24 using a home-built photoluminescence imaging microscope. Based on commercial microscopy (Microscope Axio Imager.A2m), samples were illuminated by a LED illuminator using an excitation filter and dicroic mirror (HC 440 SP, AHF Analysentechnik AG), allowing excitation at $440~\\mathrm{nm}$ . The excitation power could be controlled and was set to roughly $34\\mathrm{mW}\\mathrm{cm}^{-2}$ in the focus plane using an infinity-corrected objective $(\\times10/0.25\\mathrm{HD}$ , Zeiss). The photoluminescence light was filtered (HC-BS 484, AHF Analysentechnik AG) to suppress residual excited light and directed to the microscope with the same objective lens. The photoluminescence signal was imaged with a charge-coupled-device (CCD) camera (Pco. Pixelfly, PCO AG) with an exposure time of $200\\mathrm{{ms}}$ . The perovskite films were placed in the focal plane of the objective lens. The photoluminescence changing process was recorded with a constant $10\\mathrm{V}$ voltage being applied between the gold electrodes (Keithley 236 Source Measure Unit). \n\nCharacterization of film and device stability. The complete perovskite solar cells were simply encapsulated with a cover glass (LT-Cover, Lumtec) and UV adhesive (LT-U001, Lumtec) in a nitrogen-filled glove box. All of the non-encapsulated perovskite films on NiO/FTO substrates, the encapsulated devices and the nonencapsulated devices were aged in an Atlas SUNTEST $\\mathrm{XLS+}$ (1,700 W air-cooled xenon lamp) light-soaking chamber under simulated full-spectrum AM1.5 sunlight with $76\\mathrm{\\mW\\cm^{-2}}$ irradiance. All devices were aged under open-circuit conditions, and were taken out from the chamber and tested at different time intervals under a separate solar simulator (AM1.5, 99 to $105\\mathrm{mW}\\mathrm{cm}^{-2}$ ) for $J{-}V$ characterization. No additional ultraviolet filter was used during the whole ageing process. During the ageing test, the temperature of the light ageing chamber was initially set between $60^{\\circ}\\mathrm{C}$ and $65^{\\circ}\\mathrm{C},$ , and proceeded to between $70^{\\circ}\\mathrm{C}$ and $75^{\\circ}\\mathrm{C}$ as measured on a black temperature standard inserted into the ageing box positioned at the same level and the same orientation as the solar cells. When measuring the cells during ageing, we removed them from the ageing chamber and allow them to cool to room temperature, which typically took a few minutes. The relative humidity in the laboratory was within $40\\%$ to $60\\%$ during the entire ageing test. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n31.\t Wang, J. T.-W. et al. Efficient perovskite solar cells by metal ion doping. Energy Environ. Sci. 9, 2892–2901 (2016). \n32.\t Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n33.\t Bai, S. et al. Reproducible planar heterojunction solar cells based on one-step solution-processed methylammonium lead halide perovskites. Chem. Mater. 29, 462–473 (2017). \n34.\t Wang, Z. et al. Efficient and air-stable mixed-cation lead mixed-halide perovskite solar cells with n-doped organic electron extraction layers. Adv. Mater. 29, 1604186 (2017). \n35.\t Mei, A. et al. A hole-conductor-free, fully printable mesoscopic perovskite solar cell with high stability. Science 345, 295–298 (2014). \n36.\t Shin, S. S. et al. Colloidally prepared La-doped $B a S_{n}O_{3}$ electrodes for efficient, photostable perovskite solar cells. Science 356, 167–171 (2017). \n37.\t Tan, H. et al. Efficient and stable solution-processed planar perovskite solar cells via contact passivation. Science 355, 722–726 (2017). \n38.\t Bush, K. A. et al. $23.6\\%$ -efficient monolithic perovskite/silicon tandem solar cells with improved stability. Nat. Energy 2, 17009 (2017). \n\n![](images/77db47ef35dcd2f8bd95a0f6cf19c8f219ef2b54bb334b4f3a03e4f356ede9e6.jpg) \nExtended Data Fig. 1 | Impact of $\\mathbf{BMMBF_{4}}$ concentration on device performance. a–e, Statistics of device parameters for solar cells on NiO/ FTO substrates fabricated from perovskite precursors with a $\\mathrm{BMIMBF_{4}}$ concentration ranging from $0\\mathrm{mol\\%}$ to $1.2\\mathrm{mol}\\%$ (with respect to lead atoms). The PCE (a), $J_{\\mathrm{SC}}$ (c), $V_{\\mathrm{OC}}$ (d) and fill factor (FF; e) were determined from the FB-to-SC J– $\\cdot V$ scan curves of 20 cells for each condition. The SPO (b) was measured for $50~\\mathrm{s}$ at a fixed voltage near the MPP from the $J{-}V$ curves. The top and bottom stars show the maximum and minimum values, respectively; the open squares show mean values; \nand the boxes show the region containing $25\\mathrm{-}75\\%$ of the data, obtained from 20 cells for each condition. f, g, Light soaking during $J{-}V$ curve measurements of the control (f) and the device with $0.3\\mathrm{mol\\%}$ $\\mathrm{BMIMBF_{4}}$ $\\mathbf{\\delta}(\\mathbf{g})$ . h, $J{-}V$ curves of an optimized solar cell with $0.3\\mathrm{mol\\%}$ $\\mathrm{3MIMBF_{4}}$ measured from FB to SC and back again, with a scan rate of $200\\mathrm{mVs^{-1}}$ . The inset shows the SPO curve for the device. i, Hysteresis in the $J{-}V$ curves of devices with increasingly higher concentrations of $\\mathrm{BMIMBF_{4}}$ in the perovskite layer. \n\n![](images/64e26fbcf318855f93befcdafe1c68e9974c07b64626fabb709419182bced473.jpg) \nExtended Data Fig. 2 | Characterization of perovskite film. d, Time-resolved photoluminescence decay curves. e, Photoemission cuta–e, Characteristics of the control film and the film containing $\\mathrm{BMIMBF_{4}}$ off energy and valence-band region of the UPS spectra. $\\mathrm{E}_{\\mathrm{f}}$ Fermi level; $(0.3\\mathrm{mol\\%}$ ). a, XRD patterns. b, Top-view SEM images. c, UV-Vis VBM, valence-band maximum; WF, work function. absorption and steady-state photoluminescence (PL) spectra. \n\n![](images/229d04be4fe17aeae2b0e82bb8e38c12b849692aa15f3c2af422b4f46a9165b6.jpg) \nExtended Data Fig. 3 | Perovskite solar cells on poly-TPD holeconductor. a, PCE statistics for perovskite solar cells on poly-TPD-coated FTO substrates fabricated from precursors without and with $0.3\\mathrm{mol}\\%$ $\\mathrm{BMIMBF_{4}}$ . The PCEs were determined from FB-to-SC J–V scan curves of 13 cells for each condition. The bottom and top stars represent the \n\n![](images/68b80745808f83fd9c76d8b3af8117ce26c5f76244740c7595743c110c384f96.jpg) \nminimum and maximum values, respectively; the open squares represent mean values; and the boxes show the regions containing $25\\mathrm{-}75\\%$ of the data. b, $J{-}V$ curves for a device fabricated on poly-TPD/FTO with $0.3\\mathrm{mol}\\%$ $\\mathrm{BMIMBF_{4}}$ in the perovskite film, measured from FB to SC and back again with a scan rate of $200\\mathrm{mVs^{-1}}$ . \n\n![](images/11ed18ebb02febb224785a57c6acc05d7140c1a0b2e743b6c80c8758acdf82d8.jpg) \nExtended Data Fig. 4 | Device performance and film stability with different ionic additives. a, PCE statistics for perovskite solar cells on NiO/FTO substrates fabricated from precursors without and with different ionic additives $(0.3\\mathrm{mol\\%}$ ). b, Photographs of the non-encapsulated control and of devices with different ionic additives after ageing for $^{100\\mathrm{h}}$ under full-spectrum sunlight at $70–75^{\\circ}\\mathrm{C}$ . c, PCE statistics for perovskite solar cells fabricated on bare NiO and $\\mathrm{BMIMBF_{4}}$ -modified NiO. The PCEs \nwere determined from FB-to-SC J–V scan curves of 15 or more cells from at least two different batches for each condition. The bottom and top stars represent the minimum and maximum values, respectively; the open squares represent mean values; and the boxes show the regions containing $25\\mathrm{-}75\\%$ of the data. d, XRD patterns of the fresh and aged perovskite films (under full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ in ambient air) without ionic liquids on bare NiO and on $\\mathrm{BMIMBF_{4}}$ -modified NiO substrates. \n\n![](images/2d6140b218d820b52aca30610f47433b1cb4007aa0ea0ac8f69226fb7da4733d.jpg) \nExtended Data Fig. 5 | Device stability performance under combined full-spectrum light and heat stressing. a, Light soaking during $J{-}V$ measurements of a non-encapsulated device with $0.3\\mathrm{mol\\%}$ $\\mathrm{BMMBF_{4}}$ in the perovskite layer after $77\\mathrm{{h}}$ ageing at $60{-}65^{\\circ}\\mathrm{C}$ in air. RH, relative humidity. b, PCE statistics for devices before and after encapsulation. The PCEs were determined from FB-to-SC J–V scan curves of ten cells for each condition. The bottom and top stars represent the minimum and maximum values, respectively; the open squares represent mean values; \nand the boxes show the regions containing $25\\mathrm{-}75\\%$ of the data. c, J–V curves for one device based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite film before and after encapsulation. d, Stability performance of solar cells with and without $\\mathrm{BMIMBF_{4}}$ in the perovskite film under full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ . e, f, $J{-}V$ and SPO curves for one high-performance device based on $\\mathrm{BMIMBF_{4}}$ -containing perovskite film before (e) and after (f) ageing under full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ . \n\n![](images/7cc6286c4194ed98e64a5394b63ff42fe07a0b9a573f9aaad4bf03057b31ba21.jpg) \nExtended Data Fig. 6 | Long-term stability performance of perovskite solar cells under combined full-spectrum light and elevated temperature. a–c, Evolution of device parameters for encapsulated perovskite solar cells during stability testing under full-spectrum sunlight stressing at $70–75^{\\circ}\\mathrm{C}$ : a, $J_{\\mathrm{SC}};\\mathbf{b}$ , FF; and $\\mathbf{c}$ $V_{\\mathrm{OC}}$ . The average device parameters and standard errors (error bars) were calculated from ten cells \nfor devices with $\\mathrm{BMIMBF_{4}}$ in the perovskite film (top eight cells for the SPO), and seven cells for the other two sets of devices (top four cells for the SPO), determined from the FB-to-SC J–V scan curves. d, $J{-}V$ and SPO curves for one device with $\\mathrm{BMIMBF_{4}}$ in the perovskite film after $105\\mathrm{h}$ of ageing under full-spectrum sunlight at $70–75^{\\circ}\\mathrm{C}$ . \n\n![](images/7871409a64b5d995e3eae3969cbefd107c3d5e5f6eeba6f0a89476abe03fc8e9.jpg) \nExtended Data Fig. 7 | Performance of the most-stable cell based on during a long-term stability test under full-spectrum sunlight at $70–75^{\\circ}\\mathrm{C}$ , $\\mathbf{BMMBF_{4}}$ -containing perovskite film. a, b,Device performance before after ageing for: c, $360\\mathrm{h}$ ; d, $792\\mathrm{h}$ ; e, $^{1,122\\mathrm{h}}$ ; and f, $^{1,885\\mathrm{h}}$ . (a) and after (b) encapsulation. c–f, Evolution of $J{-}V$ and SPO curves \n\n![](images/cf621f9123b8bbe9a21ae0df9d7a0d55669b622ea18eeb6dbed756b912efe740.jpg) \nExtended Data Fig. 8 | Methods for estimating $\\pmb{T}_{80}$ values. a, For devices with an early ‘burn-in’ effect, we fit the stability performance data after the burn-in section to a straight line, and extrapolated the curve back to time zero to obtain the $T=0$ efficiency. We then determined the lifetime to $80\\%$ of the $T=0$ efficiency, that is, the $T_{80}$ (ref. 34). b, For devices \n\n![](images/cece41eb75137972fb5cf08be7b0c0ab77a31f10311f59e775881024bc9dc4f2.jpg) \n\nwith a positive ‘light-soaking’ effect, we fit the stability data from the peak performance after the light-soaking section to a straight line. We calculated the lifetime to $80\\%$ of the peak efficiency and added the ‘lightsoaking’ time to obtain the total $T_{80}$ lifetime. \n\n![](images/6fe8b9d07a8dcd60fff20877f5f50aaa04f6bc73af00021821b1d8038b6feacb.jpg) \nExtended Data Fig. 9 | Operational stability of $\\mathbf{MAPbI}_{3}$ solar cells under combined light and heat stressing. a–d, Evolution of device parameters during long-term stability testing under full-spectrum sunlight at $60{-}65^{\\circ}\\mathrm{C}$ : a, PCE and SPO; $\\mathbf{b}$ , $J_{\\mathrm{SC}};$ c, $V_{\\mathrm{OC}};$ and d, FF. The average device parameters and standard errors (error bars) were determined from peak FB-to-SC J–V scan curves for two and three different cells for devices with (two cells) and without (three cells) $\\mathrm{BMIMBF_{4}}$ in the $\\mathbf{MAPbI}_{3}$ perovskite \nfilm. During the region marked in blue (100–115 h), the chamber temperature was increased to $70–75^{\\circ}\\mathrm{C}$ to evaluate the device degradation behaviour under elevated temperatures. $\\mathbf{e}{\\mathrm{-}}\\mathbf{h}$ $J{-}V$ and SPO curves for the $\\operatorname{MAPbI}_{3}$ device containing $0.3\\mathrm{mol\\%}$ $\\mathrm{BMIMBF_{4}}$ in the perovskite layer during ageing for different times: e, before ageing; f, after ageing for $115\\mathrm{h}$ ; $\\mathbf{g},$ after ageing for $210\\mathrm{h}$ ; h, after ageing for $405\\mathrm{h}$ . \n\nExtended Data Table 1 | Summarized parameters of our perovskite solar cells \n\n\n
DevicesLight intensity* (mW cm-2)Measured Jsc (mA cm²)Measured Voc (V)Measured FFPCE (%)SPO (%)
Control devices
Average102±122.5±0.61.01±0.020.77±0.0217.3±0.617.6±0.6
Champion10223.21.020.7918.518.7
Devices with BMiMBF4 at the perovskite/NiO interface
Average103±222.7±0.81.03±0.020.79±0.0217.9±0.817.9±0.8
Champion10523.61.060.8119.319.5
Devices with BMIMBF4 in the perovskite film
Averaget104±123.1±0.61.07±0.020.81±0.0219.3±0.719.6±0.2
Champion10523.81.080.8119.820.0
\n\n\\*The light intensity of the solar simulator varied from 99 mW cm−2 to $105\\mathsf{m w c m}^{-2}$ during our measurements of the different batches of cells. †The average device parameters of JSC, $V_{\\mathsf{O C}},$ FF and PCE (with standard deviations) were calculated on the basis of 50 devices from 5 or more different batches of each condition before ageing. The average SPOs (with standard deviation) were obtained from the 20 highest-performance cells for each condition. \n\n
omparisonofourdevicewithpublishedperovskitesolarcells
Device StructureLight sourceAgeing conditionDegradation factorInitial PCE (%)Estimated Tao (hrs)Reference
Mesoporous structure
FTO/c-TiO/Li-doped meso-TiO2White LEDNitrogen, MPP,Light (without UV),~ 17~ 1,7008
+ perovskite/PTAA/Au500 h85°℃(Burn-in)
FTO/c-TiO2/Li-doped meso TiO2White LEDNitrogen, MPP,Light (without UV),~ 20~ 5,70010
+ perovskite/CuSCN/r-GO/Au1,000 h,60℃
FTO/meso-TiO2/meso-ZrO2/Ambient air,Light (-), air~ 1135
perovskite/carbon
Planar n-i-p structure
FTO/BaSnO3:La/perovskite/Metal-halideAmbient air, sealed,Light (with UV)~ 1436
NiO/FTO FTO/SnO/PCBM/perovskite/lamp Xenon lampopen-circuit, 1,000 h Ambient air, sealed,
Spiro-OMeTAD/Auopen-circuit, 2,400 hLight (with UV) 50-60 °C~ 17~ 3,9006
ITO/TiO2-Cl/perovskite/Xenon lamp*Nitrogen,MPP,500 hLight (without UV)~ 20(Burn-in) ~ 1,60037
Spiro-OMeTAD/Au
ITO/C60-SAM/SnO×/PCBM/White LEDNitrogen,Light (without UV)~ 20~ 1,60012
perovskite/polymer/Ta-WOx/Auopen-circuit, 1,000 h(Light-soaking)
Ambient air, MPP,Light (with UV), air,~ 250013
FTO/SnO/perovskite/EH44/Sulphur1,000h~ 30℃~ 12(Light-soaking)
MoO/AIplasma lampNitrogen, MPP,Light (with UV),~1613
1,500 h~ 30°℃
Planar p-i-n structure:
FTO/LiMgNiO/perovskite/PCBMXenon lamp*Ambient air, sealed,Light (without UV),~ 16~ 220011
/Nb-TiO/AgMPP,1,000 h45-50 °℃
ITO/NiO/perovskite/PCBM/SulphurAmbient airt, MPP,Light (with UV),~ 13~ 2,00038
SnO2/ZTO/ITO/LiF/Agplasma lamp1,000 h~ 35 ℃(Light-soaking)
ITO/PEDOT:PSS/2DXenon lampAmbient air, sealed,Light (with UV)9
perovskite/PCBM/AIopen-circuit, 2,250 h
FTO/NiO/perovskite/Ambient air, sealed,Light (with UV),(PCE, Light-soaking)
PCBM/BCP/Cr(Cr2O3)/AuXenon lampopen-circuit,1,885 h70-75 °C~ 18~ 4,100This work
(SPO,Burn-in)
\n\nData on the long-term operational stability of published perovskite solar cells are from refs 6,8–13,35–38. $^{\\ast}\\mathsf{A}420\\mathsf{-n m}$ cut-off UV filter was used during this stability test. †The sputtered indium tin oxide (ITO) electrode acts as a protective layer in the solar cell. " + }, + { + "id": "10.1038_s41586-019-1481-z", + "DOI": "10.1038/s41586-019-1481-z", + "DOI Link": "http://dx.doi.org/10.1038/s41586-019-1481-z", + "Relative Dir Path": "mds/10.1038_s41586-019-1481-z", + "Article Title": "Quantifying inactive lithium in lithium metal batteries", + "Authors": "Fang, CC; Li, JX; Zhang, MH; Zhang, YH; Yang, F; Lee, JZ; Lee, MH; Alvarado, J; Schroeder, MA; Yang, YYC; Lu, BY; Williams, N; Ceja, M; Yang, L; Cai, M; Gu, J; Xu, K; Wang, XF; Meng, YS", + "Source Title": "NATURE", + "Abstract": "Lithium metal anodes offer high theoretical capacities (3,860 milliampere-hours per gram)(1), but rechargeable batteries built with such anodes suffer from dendrite growth and low Coulombic efficiency (the ratio of charge output to charge input), preventing their commercial adoption(2,3). The formation of inactive ('dead') lithium- which consists of both (electro)chemically formed Li+ compounds in the solid electrolyte interphase and electrically isolated unreacted metallic Li-0 (refs(4,5))-causes capacity loss and safety hazards. Quantitatively distinguishing between Li+ in components of the solid electrolyte interphase and unreacted metallic Li-0 has not been possible, owing to the lack of effective diagnostic tools. Optical microscopy(6), in situ environmental transmission electron microscopy(7,8), X-ray microtomography(9) and magnetic resonullce imaging(10) provide a morphological perspective with little chemical information. Nuclear magnetic resonullce(11), X-ray photoelectron spectroscopy(12) and cryogenic transmission electron microscopy(13,14) can distinguish between Li+ in the solid electrolyte interphase and metallic Li-0, but their detection ranges are limited to surfaces or local regions. Here we establish the analytical method of titration gas chromatography to quantify the contribution of unreacted metallic Li-0 to the total amount of inactive lithium. We identify the unreacted metallic Li-0, not the (electro)chemically formed Li+ in the solid electrolyte interphase, as the dominullt source of inactive lithium and capacity loss. By coupling the unreacted metallic Li-0 content to observations of its local microstructure and nullostructure by cryogenic electron microscopy (both scanning and transmission), we also establish the formation mechanism of inactive lithium in different types of electrolytes and determine the underlying cause of low Coulombic efficiency in plating and stripping (the charge and discharge processes, respectively, in a full cell) of lithium metal anodes. We propose strategies for making lithium plating and stripping more efficient so that lithium metal anodes can be used for next-generation high-energy batteries.", + "Times Cited, WoS Core": 817, + "Times Cited, All Databases": 903, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000482219600042", + "Markdown": "# Quantifying inactive lithium in lithium metal batteries \n\nChengcheng Fang1,6, Jinxing $\\mathrm{Li}^{2,6}$ , Minghao Zhang2, Yihui Zhang1, Fan $\\mathrm{Yang^{3}}$ , Jungwoo Z. Lee2, Min-Han Lee1, Judith Alvarado1,4, Marshall A. Schroeder4, Yangyuchen Yang1, Bingyu $\\mathrm{Lu^{2}}$ , Nicholas Williams3, Miguel $\\mathrm{Ceja^{2}}$ , Li Yang5, Mei $\\mathrm{Cai}^{5}$ , Jing $\\mathrm{Gu}^{3}$ , Kang $\\mathrm{{Xu^{4}}}$ Xuefeng Wang2 & Ying Shirley Meng1,2\\* \n\nLithium metal anodes offer high theoretical capacities (3,860 milliampere-hours per gram)1, but rechargeable batteries built with such anodes suffer from dendrite growth and low Coulombic efficiency (the ratio of charge output to charge input), preventing their commercial adoption2,3. The formation of inactive (‘dead’) lithium— which consists of both (electro)chemically formed ${{\\bf{L i}}^{+}}$ compounds in the solid electrolyte interphase and electrically isolated unreacted metallic ${\\bf{L i}}^{0}$ (refs 4,5)—causes capacity loss and safety hazards. Quantitatively distinguishing between ${{\\bf{L i}}^{+}}$ in components of the solid electrolyte interphase and unreacted metallic ${\\bf L i^{0}}$ has not been possible, owing to the lack of effective diagnostic tools. Optical microscopy6, in situ environmental transmission electron microscopy7,8, $\\mathbf{X}$ -ray microtomography9 and magnetic resonance imaging1 provide a morphological perspective with little chemical information. Nuclear magnetic resonance11, $\\mathbf{X}$ -ray photoelectron spectroscopy12 and cryogenic transmission electron microscopy13,14 can distinguish between ${{\\bf{L i}}^{+}}$ in the solid electrolyte interphase and metallic ${\\bf\\cal L i}^{0}$ , but their detection ranges are limited to surfaces or local regions. Here we establish the analytical method of titration gas chromatography to quantify the contribution of unreacted metallic ${\\bf{L i}}^{0}$ to the total amount of inactive lithium. We identify the unreacted metallic ${\\bf L i^{0}}$ , not the (electro) chemically formed ${{\\bf{L i}}^{+}}$ in the solid electrolyte interphase, as the dominant source of inactive lithium and capacity loss. By coupling the unreacted metallic ${\\bf L i}^{0}$ content to observations of its local microstructure and nanostructure by cryogenic electron microscopy (both scanning and transmission), we also establish the formation mechanism of inactive lithium in different types of electrolytes and determine the underlying cause of low Coulombic efficiency in plating and stripping (the charge and discharge processes, respectively, in a full cell) of lithium metal anodes. We propose strategies for making lithium plating and stripping more efficient so that lithium metal anodes can be used for next-generation highenergy batteries. \n\nInactive lithium consists of diverse ${\\mathrm{Li}}^{+}$ compounds within the solid electrolyte interphase (SEI), such as LiF, $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ , $\\mathrm{Li}_{2}\\mathrm{O};$ , $\\mathrm{ROCO}_{2}\\mathrm{Li}$ (refs 15,16), and of unreacted metallic ${\\mathrm{Li}}^{0}$ which is isolated by the SEI from the electronic conductive pathway. It is generally assumed that low Coulombic efficiency mostly arises from continuous repair of SEI fractures, which consumes both the electrolyte and active Li metal17, although some researchers have suggested that unreacted metallic $\\mathrm{Li}^{0}$ may increase the tortuosity at the electrode/electrolyte interface and decrease the Coulombic efficiency in this way18,19. These assumptions and hypotheses are mostly based on observation, and the contribution to capacity loss from SEI formation has not been successfully quantified. Consequently, efforts to make Li metal a valid anode material may be misdirected. Differentiating and quantifying the $\\mathrm{Li^{+}}$ and $\\mathrm{Li}^{0}$ remaining on the electrode after stripping is key to understanding the mechanisms leading to capacity decay. \n\nIn our work, the pivotal difference exploited between the SEI $\\mathrm{Li^{+}}$ compounds and metallic ${\\mathrm{Li}^{0}}$ is their chemical reactivity: only the metallic ${\\mathrm{Li}}^{0}$ reacts with protic solvents (such as $\\mathrm{H}_{2}\\mathrm{O}\\dot{}$ ) and generates hydrogen gas $\\left(\\operatorname{H}_{2}\\right)$ . The solubility and reactivity of known SEI species with $\\mathrm{H}_{2}\\mathrm{O}$ are listed in Extended Data Table 1. The possible presence of LiH (refs 20–22) in inactive Li might affect the quantification of metallic $\\mathrm{Li}^{0}$ because LiH also reacts with water and produces $\\mathrm{H}_{2}$ , so it was important to exclude this possibility in our results (see Methods for details). We combine $\\mathrm{H}_{2}\\mathrm{O}$ titration (the step in which all metallic ${\\mathrm{Li}}^{0}$ is reacted) and gas chromatography (the subsequent step to quantify the $\\mathrm{H}_{2}$ generated in the reaction) into a single analytical tool, hereafter referred to as titration gas chromatography (TGC; schematic process in Extended Data Fig. 1), which is able to quantify the content of metallic ${\\mathrm{Li}}^{0}$ based on the reaction \n\n$$\n2\\mathrm{Li}+2\\mathrm{H}_{2}\\mathrm{O}\\longrightarrow2\\mathrm{LiOH}+\\mathrm{H}_{2}\\uparrow\n$$ \n\nWhen this is coupled with an advanced barrier ionization $\\mathrm{H}_{2}$ detector, the measurement of metallic $\\mathrm{Li}^{0}$ in the designed system is accurate to $10^{-7}\\mathrm{g}$ . The complete TGC methodologies are illustrated in Methods. \n\nWe then applied TGC to correlate the origin of inactive Li with the Coulombic efficiency in $\\mathrm{Li}||\\mathrm{Cu}$ half-cells. As the Coulombic efficiency of Li metal varies greatly with electrolyte properties and current density, we compared two representative electrolytes, a high-concentration electrolyte (HCE; 4 M lithium bis(fluoro sulfonyl)imide (LiFSI) and $2\\mathrm{M}$ lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) in 1,2-dimethoxyethane (DME))23 and a commercial carbonate electrolyte (CCE; $1\\mathrm{MLiPF}_{6}$ in ethylene carbonate/ethyl methyl carbonate (EC/EMC)), at three stripping rates $(0.5\\operatorname{mA}\\mathrm{cm}^{-2}$ , $2.5\\mathrm{m}\\dot{\\mathrm{A}}\\mathrm{cm}^{-2}$ and $5.0\\mathrm{mA}\\mathrm{cm}^{-2}$ ; all plating at $0.5\\mathrm{\\mA}\\mathrm{cm}^{-2}$ for 2 hours) . In addition, we examined six other electrolytes with a variety of salts, solvents and additives that frequently appear in the literature: 2 M LiFSI in dimethyl carbonate (DMC), $0.5{\\mathrm{~M~}}$ LiTFSI in DME/1,3-dioxolane (DOL), 1 M LiTFSI– DME/DOL, 1 M LiTFSI–DME/DOL plus $2\\%$ $\\mathrm{LiNO}_{3}$ , CCE plus ${{\\mathrm{Cs}}^{+}}$ , and CCE plus fluoroethylene carbonate (FEC). Figure 1a shows that their first-cycle average Coulombic efficiencies have a broad range of values, from $17.2\\%$ to $97.1\\%$ . Representative voltage profiles are shown in Extended Data Fig. 2a, b. The total amount of inactive Li is equal to the capacity loss between the plating and stripping processes, displaying a linear relationship with Coulombic efficiency (Fig. 1d). The content of metallic $\\mathrm{Li}^{0}$ was directly measured by the TGC method. Once the amount of unreacted metallic ${\\mathrm{Li}^{0}}$ has been determined, the SEI $\\mathrm{Li^{+}}$ amount can be calculated, as the total amount of inactive Li $\\left({\\mathrm{known}}\\right)=$ unreacted metallic $\\mathrm{Li}^{0}$ (measured) $+\\operatorname{SEI}\\operatorname{Li}^{+}$ . \n\nThe average capacity utilization under all conditions was quantified by the TGC, as summarized in Fig. 1b. The reversible capacity increases with increasing Coulombic efficiency. Interestingly, the unreacted metallic $\\mathrm{Li}^{0}$ amount increases significantly with the decrease of Coulombic efficiency, whereas the SEI ${\\mathrm{Li}^{+}}$ amount remains at a constantly low level under all testing conditions. Further analysing the data, we found to our surprise that the amount of unreacted metallic $\\mathrm{Li}^{0}$ exhibits a linear relationship with loss of Coulombic efficiency (Fig. 1e), and this relationship is almost independent of the testing conditions. This implies that the Coulombic efficiency loss is governed by the formation of unreacted metallic $\\mathrm{Li}^{0}$ . Meanwhile, the SEI ${\\mathrm{Li}}^{+}$ amount (Fig. 1f), as deduced from the total inactive Li and unreacted metallic $\\mathrm{Li}^{0}$ , remains low and relatively constant under various testing conditions. The ratio of SEI ${\\mathrm{Li}^{+}}$ and unreacted metallic $\\mathrm{Li}^{0}(\\mathrm{Li}^{+}/\\mathrm{Li}^{0})$ (Fig. 1c) reveals that the unreacted metallic $\\mathrm{Li}^{0}$ dominates the content of inactive L $\\mathrm{(Li^{+}/L i^{0}<1)}$ as well as the capacity loss when Coulombic efficiency is under about $95\\%$ in the first cycle. Once the Coulombic efficiency is higher than about $95\\%$ , the amount of SEI ${\\mathrm{Li}}^{+}$ starts to dominate. The ratios of unreacted metallic ${\\mathrm{Li}^{0}}$ to total inactive Li, and of SEI ${\\mathrm{Li}^{+}}$ to total inactive Li, are further shown in Extended Data Fig. 2c, d. \n\n![](images/51a26f823d628f99c95357579ddd88985a59a98be7c017bd7108ac166a1380c6.jpg) \nFig. 1 | Quantitative differentiation of inactive Li by the TGC method. the standard deviation of the average values of Coulombic efficiency. a, Average first-cycle Coulombic efficiency of $\\mathrm{Li}||\\mathrm{Cu}$ cells under different b, Analysis of capacity usage (SEI $\\bar{\\mathrm{Li^{+}}}$ , unreacted metallic ${\\mathrm{Li}}^{0}$ and reversible testing conditions. Eight electrolytes (HCE, CCE, 2 M LiFSI–DMC, $0.5{\\mathrm{~M~}}$ Li) under different testing conditions by the TGC method. c, The ratio of LiTFSI–DME/DOL, 1 M LiTFSI–DME/DOL, 1 M LiTFSI–DME/DOL $+$ SEI ${\\mathrm{Li}^{+}}$ to unreacted metallic ${\\mathrm{Li}}^{0}$ based on TGC quantification results. The $2\\%\\mathrm{LiNO}_{3}$ , $\\mathrm{CCE}+\\mathrm{Cs}^{+}$ and $\\mathrm{CCE}+\\mathrm{FEC})$ and three stripping rates ( $\\mathrm{\\cdot}0.5\\mathrm{mA}$ blue line indicates exponential fitting. d, Total capacity loss as a function $c\\mathrm{m}^{-2}$ , $2.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ and $5.0\\mathrm{mA}\\mathrm{cm}^{-2}$ to $1\\mathrm{V},$ are used. In all electrolytes, of Coulombic efficiency. (For unit conversion between milliampere-hours Li was plated at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for 2 hours $\\mathrm{`1~mAh~cm^{-2}}.$ ). HCE and CCE and milligrams of Li, see Extended Data Fig. 2f.) e, Amount of unreacted were selected for the three stripping rates study. Li formed in the rest metallic $\\bar{\\mathrm{Li}^{0}}$ measured by the TGC method as a function of Coulombic electrolytes were stripped at $0.{\\overset{-}{5}}\\operatorname*{mA}\\operatorname{cm}^{-2}$ to $1\\mathrm{V}.$ At each condition, three efficiency. f, Calculated SEI ${\\mathrm{Li}^{+}}$ amount as a function of Coulombic to five cells were tested to obtain better statistics. The error bar represents efficiency. \n\nIncreasing Li deposition capacity is reported to improve the firstcycle Coulombic efficiency24. To extend this method under different electrochemical conditions, we performed TGC tests on the CCE with Li plating capacities increased to $2\\mathrm{mAh}\\mathrm{cm}^{-2}$ , $3\\mathrm{mAh}\\mathrm{cm}^{-2}$ and $5\\mathrm{mAh}\\mathrm{cm}^{-2}$ . The TGC results (Extended Data Fig. 3a, b) show that the SEI $\\mathrm{Li^{+}}$ amount increases with the extended deposition capacity; the improvement in Coulombic efficiency with increased Li deposition capacity is due to the reduction in the amount of unreacted metallic $\\mathrm{Li}^{\\hat{0}}$ . At $\\dot{3}\\mathrm{mAh}\\mathrm{cm}^{-2}$ , the Coulombic efficiency reaches $95.21\\%$ , while the ratio of SEI ${\\mathrm{Li}}^{+}$ to unreacted metallic ${\\mathrm{Li}^{0}}$ is measured to be 1.43, consistent with the above results. \n\nBesides the first cycle, we also investigated the ratio of SEI $\\mathrm{Li^{+}}$ to unreacted metallic $\\mathrm{Li}^{\\mathrm{\\dot{0}}}$ after multiple cycles (two, five and ten) until the Coulombic efficiency is stabilized around $90\\%$ in CCE. As shown in Extended Data Fig. 3c, d, the $\\mathrm{Li^{+}/L i^{0}}$ ratio after one, two, five and ten cycles remains 0.27, 0.30, 0.27 and 0.34, respectively, indicating that the main capacity loss is from the unreacted metallic $\\mathrm{Li}^{0}$ . The TGC results also reveal that the unreacted metallic ${\\mathrm{Li}^{0}}$ amount accumulates during extended cycles, indicating continuous consumption of active Li in Li metal batteries. These experiments, with varying electrolytes, additives, deposition capacities and cycles, all validate the TGC method as a reliable tool in studying the inactive Li. \n\nFurther examining the SEI components in HCE and CCE by X-ray photoelectron spectroscopy (XPS), we found that stripping rates have negligible impact on the relative contributions from SEI components (see Extended Data Fig. 4a, b). The TGC quantification analysis and XPS results establish that the contribution from the SEI ${\\mathrm{Li}}^{+}$ to the global content of inactive Li is not as large as commonly believed from previous studies25–27. \n\nTo elucidate the formation mechanism of inactive Li, we use cryogenic focused ion beam–scanning electron microscopy (cryo-FIB–SEM) to explore the microstructures of inactive Li. HCE and CCE samples under different stripping rates are chosen for the morphological study. Cryogenic protection is critical here, because the highly reactive Li metal is not only sensitive to the electron beam but is also apt to react with the incident Ga ion beam to form a $\\operatorname{Li}_{x}\\operatorname{Ga}_{y}$ alloy at room temperature28. Completely different morphologies are generated by variations in stripping rates, even though all samples start from the same chunky Li deposits after plating at $\\bar{0}.5\\operatorname{mA}{\\mathrm{cm}^{-2}}$ (Extended Data Fig. 5a–c). As the stripping rate increases, the morphology of inactive Li in HCE evolves from uniform sheets to local clusters (Fig. 2a–c) with a thickness increased from $500\\mathrm{nm}$ to $2\\upmu\\mathrm{m}$ (Fig. 2d–f). For the CCE, the individual whisker-like Li deposits (Extended Data Fig. 5d–f) become thinner after stripping (Fig. $2\\mathrm{g-i})$ , but the whole inactive Li layer becomes thicker in cross-section with the increased stripping rates (Fig. 2j–l), corresponding to the increased loss of Coulombic efficiency at high rates. It is worth noting that these residues exhibit poor connection to the current collector, indicating the loss of electronic conductive pathways. \n\n![](images/0530e89acc4694bdb27071901333bcbfc7326328d31838749fc6ac1290d0f80a.jpg) \nig. 2 | Microstructures of inactive Li generated in HCE and CCE sections obtained by cryo-FIB. Each column represents a different maged by cryo-FIB–SEM. a–f, Results for HCE. $\\mathbf{g}\\mathbf{-}\\mathbf{l}$ , Results for CCE. stripping rate: 0.5 mA $\\dot{\\mathrm{cm}}^{-2}$ (a, d, g, j); 2.5 $\\mathrm{m}\\mathrm{A}\\mathrm{\\dot{c}m}^{-2}\\left(\\mathbf{b},\\mathbf{e},\\mathbf{h},\\mathbf{k}\\right)$ ; or a–c, $\\mathbf{g-i},$ Top view of the inactive Li at $52^{\\circ}$ tilted stage. d–f, j–l, Cross- $5.0\\mathrm{\\mA}\\mathrm{cm}^{-2}$ (c, f, i, l). \n\nWe further used cryogenic transmission electron microscopy (cryoTEM) to investigate the nanostructure of the inactive Li in HCE and CCE after stripping at $0.5\\operatorname{mA}{\\mathrm{cm}^{-2}}$ . Sheet-like inactive Li appears in the HCE sample (Fig. 3a), whereas inactive Li in the CCE retains a whisker-like morphology (Fig. 3e). Based on the (110) lattice plane distance of body-centered cubic Li, the region that contains crystalline metallic $\\mathrm{Li}^{\\dot{0}}$ is highlighted in green in the high-resolution TEM (HRTEM) images for both electrolytes (Fig. 3b, f). Compared with the inactive Li obtained from CCE, a much smaller area of metallic $\\mathrm{Li}^{0}$ component is observed in HCE. This indicates that most of the deposited metallic ${\\mathrm{Li}}^{0}$ in HCE has been successfully stripped, corresponding to the high Coulombic efficiency. Whisker-like unreacted metallic $\\mathrm{Li}^{\\smash{\\breve{0}}}$ up to about $80\\mathrm{nm}$ in length remains in the CCE sample and is well isolated by the surrounding SEI. The SEI components were determined by matching the lattice spacing in HRTEM images with their fast Fourier transform (FFT) patterns (Fig. 3c, g). The SEI components from more than 50 different sample positions have been analysed and are provided in Extended Data Fig. 5g, h for better statistics. Consistent with the XPS results (Extended Data Fig. 4), $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ and $\\mathrm{Li}_{2}\\mathrm{O}$ constitute the majority of the SEI, which also contains LiF as well as other amorphous organic species for both electrolytes. The above observations from cryo-TEM are summarized in the schematic plot (Fig. 3d, h), which shows the form of inactive Li with two different morphologies at the nanoscale. \n\nCorrelating the inactive metallic ${\\mathrm{Li}^{0}}$ content with the micro- and nanostructures of inactive Li formed under different conditions, we propose mechanisms for the formation of inactive Li and for the stripping of Li metal. Two processes are involved in the stripping. The first of these is ${\\mathrm{Li}}^{+}$ dissolution: under the electric field, metallic ${\\mathrm{Li}}^{0}$ is oxidized to $\\mathrm{Li^{+}}$ , which diffuses through the SEI layers and dissolves into the electrolyte. The second is SEI collapse: when the Li is removed, the SEI simultaneously shrinks and collapses towards the current collector. During these two dynamic processes, we emphasize an ignored but crucial aspect, the structural connection, which is defined as the capability of the active Li to maintain an electronic conductive network. The cryo-FIB–SEM and cryo-TEM images show that inactive $\\mathrm{Li}^{0}$ was either disconnected from the current collector or encapsulated by the insulating SEI, leading to the loss of structural connection. Obviously, for a Li deposit with whisker morphology and large tortuosity (Fig. 4a, taking the Li deposits formed in CCE as an example), the undesired microstructure can easily produce both ways of losing structural connection, leaving more unreacted metallic $\\mathrm{Li}^{\\dot{0}}$ during the stripping process. In contrast, dense Li with chunky morphology and low tortuosity (Fig. 4b, from HCE) has bulk integrity to maintain its structural connection and intimate contact with the current collector, resulting in a reduced presence of unreacted metallic $\\mathrm{Li}^{0}$ and high Coulombic efficiency. This is further evidenced by an advanced electrolyte with columnar microstructure and minimum tortuosity, which can deliver a first-cycle Coulombic efficiency as high as $96.2\\%$ (Extended Data Fig. 6a, b). \n\n![](images/5511ad2f6b4e24838c4581f481b81f3cd846ac67e47ebe874bb5412b2fc95af9.jpg) \nFig. 3 | Nanostructures of inactive Li generated in HCE and CCE imaged by cryo-TEM. a–c, Results for HCE. $\\mathbf{e}{\\mathbf{-}}\\mathbf{g}$ , Results for CCE. a, e, Inactive Li morphology at low magnifications for both electrolytes. b, f, HRTEM shows that a different amount of metallic $\\mathrm{Li}^{0}$ is wrapped by SEI in the two types of electrolyte. The highlighted metallic $\\mathrm{Li}^{0}$ region in green is identified through an inverse FFT process by applying mask filter on the \n\n![](images/3d4fed0b7b8c5c8cfdf234630074bf6ebd0ea9da702ef755963d1080e73a405f.jpg) \norigin FFT patterns. c, g, FFT patterns of corresponding HRTEM indicate the SEI component, which contains crystalline $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ , $\\mathrm{Li}_{2}\\mathrm O$ and LiF. ${\\bf d},{\\bf h}$ , Schematic of inactive Li nanostructure in HCE (d) and CCE (h). A small area of metallic $\\mathrm{Li}^{0}$ is embedded in a sheet-like SEI layer for HCE, whereas a large bulk of metallic $\\mathrm{Li}^{0}$ is isolated in a whisker-like SEI layer in CCE. \nsmall amounts of metallic $\\mathrm{Li}^{0}$ are stuck in tortuous SEI edges. c, An ideal Li deposit should have a columnar microstructure with a large granular size, minimum tortuosity and homogeneous distribution of SEI components, facilitating a complete dissolution of metallic $\\mathrm{Li}^{0}$ . d, A general correlation of morphology of Li deposits, Coulombic efficiency and the ratio of SEI ${\\mathrm{Li}^{+}}$ to unreacted metallic $\\mathrm{Li}^{0}$ . \n\nFig. 4 | Schematic of inactive Li formation mechanism in different electrolytes, based on TGC quantification, cryo-FIB–SEM and cryo-TEM observation. a, Li deposits with whisker morphology and high tortuosity are more likely to lose electronic connection and maintain poor structural connection, leaving large amounts of unreacted metallic $\\mathrm{Li}^{\\hat{0}}$ trapped in SEI. b, Li deposits with large granular size and less tortuosity tend to maintain a good structural electronic connection, in which only \n\nBased on the above observations and discussion, we propose the following strategies to improve Coulombic efficiency. An ideal architecture of deposited Li would promote structural connection and mitigate inactive Li formation, especially the formation of unreacted metallic $\\mathrm{Li}^{0}$ . The ideal architecture includes the following. (1) The Li deposits should retain a columnar microstructure with a large granular size and minimum tortuosity, to minimize the unreacted metallic ${\\mathrm{Li}}^{0}$ residue (Fig. 4c, d). (2) The SEI should be both chemically and spatially homogeneous so that uniform ${\\mathrm{Li}}^{+}$ dissolution occurs. It should be mechanically elastic enough to accommodate the volume change. The SEI could be refilled during extended cycles, as schematized in Extended Data Fig. 6g. Using advanced electrolytes and artificial SEI may help to meet these requirements, while three-dimensional (3D) hosts that maintain electronic pathway and low tortuosity can contribute to constructing a durable structural connection and guiding the Li plating and stripping. To test this hypothesis, we compared 2D Cu foil and 3D Cu foam as the current collectors (Extended Data Fig. 6c, d). The initial Coulombic efficiency of 2D Cu foil and 3D Cu foam is $82\\%$ and $90\\%$ , respectively (Extended Data Fig. 6e). The increased Coulombic efficiency in the latter is attributed to the reduced amount of unreacted metallic ${\\dot{\\mathrm{Li}}}^{0}$ (Extended Data Fig. 6f), despite the fact that the amount of SEI ${\\mathrm{Li}^{+}}$ increases from $21.5\\%$ to $62.7\\%$ owing to the higher surface area of 3D Cu foam. Therefore, although the 3D current collector helps in maintaining a good electronic conductive network, it is necessary to control its surface properties to minimize SEI formation. The structural connection can be further enforced by applying external pressure. Slight stacking pressure can improve cycling performance29,30. In our proposed model, we believe that pressure promotes structural collapse towards the current collector, thus leading to better structural connection which mitigates the generation of unreacted metallic $\\mathrm{Li}^{0}$ . We found the critical pressure in maintaining good structural connection to be as low as about 5 psi, which should not damage any SEI (Extended Data Fig. 6h). A fast stripping rate could accelerate the ${\\mathrm{Li}}^{+}$ dissolution but may destroy the structural connection, because Li at the tip of column or whiskers could fail to keep pace with the rapid dynamic. Overall, the tools established here can be universally extended to examine various battery chemistries under different conditions, with the aim of developing a better battery that is energy-dense and safe. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-019-1481-z. \n\nReceived: 21 January 2019; Accepted: 12 June 2019; \nPublished online 21 August 2019. \n1.\t Tarascon, J. M. & Armand, M. Issues and challenges facing rechargeable lithium batteries. Nature 414, 359–367 (2001). \n2.\t Lin, D., Liu, Y. & Cui, Y. Reviving the lithium metal anode for high-energy batteries. Nat. Nanotechnol. 12, 194–206 (2017). \n3.\t Xu, W. et al. Lithium metal anodes for rechargeable batteries. Energy Environ. Sci. 7, 513–537 (2014). \n4. Yoshimatsu, I., Hirai, T. & Yamaki, J. Lithium electrode morphology during cycling in lithium cells. J. Electrochem. Soc. 135, 2422–2427 (1979). \n5.\t Lu, D. et al. Failure mechanism for fast-charged lithium metal batteries with liquid electrolytes. Adv. Energy Mater. 5, 1400993 (2015). \n6.\t Wood, K. N., Noked, M. & Dasgupta, N. P. Lithium metal anodes: toward an improved understanding of coupled morphological, electrochemical, and mechanical behavior. ACS Energy Lett. 2, 664–672 (2017). \n7.\t Bai, P., Li, J., Brushett, F. R. & Bazant, M. Z. Transition of lithium growth mechanisms in liquid electrolytes. Energy Environ. Sci. 9, 3221–3229 (2016). \n8.\t Mehdi, B. L. et al. Observation and quantification of nanoscale processes in lithium batteries by operando electrochemical (S)TEM. Nano Lett. 15, 2168–2173 (2015). \n9.\t Harry, K. J., Hallinan, D. T., Parkinson, D. Y., Macdowell, A. A. & Balsara, N. P. Detection of subsurface structures underneath dendrites formed on cycled lithium metal electrodes. Nat. Mater. 13, 69–73 (2013). \n10.\t Chandrashekar, S. et al. 7Li MRI of Li batteries reveals location of microstructural lithium. Nat. Mater. 11, 311–315 (2012). \n11.\t Bhattacharyya, R. et al. In situ NMR observation of the formation of metallic lithium microstructures in lithium batteries. Nat. Mater. 9, 504–510 (2010). \n12.\t Xu, C. et al. Interface layer formation in solid polymer electrolyte lithium batteries: an XPS study. J. Mater. Chem. A 2, 7256–7264 (2014). \n13.\t Li, Y. et al. Atomic structure of sensitive battery materials and interfaces revealed by cryo-electron microscopy. Science 358, 506–510 (2017). \n14.\t Wang, X. et al. New insights on the structure of electrochemically deposited lithium metal and its solid electrolyte interphases via cryogenic TEM. Nano Lett. 17, 7606–7612 (2017). \n15.\t Cheng, X. B. et al. A review of solid electrolyte interphases on lithium metal anode. Adv. Sci. 3, 1–20 (2015). \n16.\t Zheng, J., Lochala, J. A., Kwok, A., Deng, Z. D. & Xiao, J. Research progress towards understanding the unique interfaces between concentrated electrolytes and electrodes for energy storage applications. Adv. Sci. 4, 1700032 (2017). \n17.\t Li, S. et al. Developing high-performance lithium metal anode in liquid electrolytes: challenges and progress. Adv. Mater. 30, 1706375 (2018). \n18.\t Steiger, J., Kramer, D. & Mönig, R. Microscopic observations of the formation, growth and shrinkage of lithium moss during electrodeposition and dissolution. Electrochim. Acta 136, 529–536 (2014). \n19.\t Chen, K.-H. et al. Dead lithium: mass transport effects on voltage, capacity, and failure of lithium metal anodes. J. Mater. Chem. A 5, 11671–11681 (2017). \n20.\t Zachman, M. J., Tu, Z., Choudhury, S., Archer, L. A. & Kourkoutis, L. F. Cryo-STEM mapping of solid–liquid interfaces and dendrites in lithium-metal batteries. Nature 560, 345–349 (2018). \n21.\t Aurbach, D. & Weissman, I. On the possibility of LiH formation on Li surfaces in wet electrolyte solutions. Electrochem. Commun. 1, 324–331 (1999). \n22.\t Hu, Y. Y. et al. Origin of additional capacities in metal oxide lithium-ion battery electrodes. Nat. Mater. 12, 1130–1136 (2013). \n23.\t Alvarado, J. et al. Bisalt ether electrolytes: a pathway towards lithium metal batteries with Ni-rich cathodes. Energy Environ. Sci. 12, 780–794 (2019). \n24.\t Adams, B. D., Zheng, J., Ren, X., Xu, W. & Zhang, J. G. Accurate determination of Coulombic efficiency for lithium metal anodes and lithium metal batteries. Adv. Energy Mater. 8, 1702097 (2017). \n25.\t Lu, J., Wu, T. & Amine, K. State-of-the-art characterization techniques for advanced lithium-ion batteries. Nat. Energy 2, 17011 (2017). \n26.\t Lee, H. et al. Suppressing lithium dendrite growth by metallic coating on a separator. Adv. Funct. Mater. 27, 1704391 (2017). \n27.\t Zheng, J. et al. Highly stable operation of lithium metal batteries enabled by the formation of a transient high-concentration electrolyte layer. Adv. Energy Mater. 6, 1–10 (2016). \n28.\t Saint, J., Morcrette, M., Larcher, D. & Tarascon, J. M. Exploring the Li-Ga room temperature phase diagram and the electrochemical performances of the LixGay alloys vs. Li. Solid State Ion. 176, 189–197 (2005). \n29.\t Yin, X. et al. Insights into morphological evolution and cycling behaviour of lithium metal anode under mechanical pressure. Nano Energy 50, 659–664 (2018). \n30.\t Lee, H. et al. Electrode edge effects and the failure mechanism of lithium-metal batteries. ChemSusChem 11, 3821–3828 (2018). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\nElectrochemical testing. Coulombic efficiency was measured in Li||Cu coin cells: Li metal ( $\\mathrm{~\\chi~mm~}$ thick, 0.5 inch in diameter), two pieces of separators (Celgard) and $\\mathrm{cu}$ foil (0.5 inch in diameter) were sandwiched in CR2032 coin cells with a spacer and a spring, and crimped inside an Ar-filled glovebox. A $50\\upmu\\mathrm{l}$ amount of the electrolyte was added in each cell. HCE consists of $^{4\\mathrm{M}}$ LiFSI (battery grade; Oakwook Products, Inc.) $+2\\mathbf{M}$ LiTFSI (battery grade; Solvay) in DME (anhydrous, $>99.5\\%$ ; BASF). CCE consists of $1\\mathrm{MLiPF}_{6}$ (battery grade, BASF) in EC/EMC (battery grade, BASF) (3:7 by weight) with $2\\mathrm{wt\\%}$ of vinylene carbonate (battery grade, BASF). $\\mathrm{CCE}+\\mathrm{Cs}^{+}$ contains $50\\mathrm{mM}$ of ${\\mathrm{CsPF}}_{6}$ (Synquest Laboratory). $\\mathrm{CCE}+\\mathrm{FEC}$ contains $10\\mathrm{wt\\%}$ of FEC (anhydrous, $599\\%$ , Sigma-Aldrich). DOL (anhydrous, ${>}99.5\\%$ ) and $\\mathrm{LiNO}_{3}$ were purchased from Sigma-Aldrich. Cells for TGC are plating at $0.5\\operatorname{mA}{\\mathrm{cm}^{-2}}$ for $1\\mathrm{\\mAh}\\mathrm{cm}^{-2}$ and stripping at various rates $(0.5\\mathrm{mA}\\mathrm{cm}^{-2}$ , $\\bar{2}.5\\operatorname{mA}{\\mathrm{cm}^{-2}}$ and $5\\operatorname{mA}\\mathrm{cm}^{-2}$ ) to ${}^{1\\mathrm{V},}$ unless otherwise specified. \n\nTitration gas chromatography. Extended Data Fig. 1 demonstrates the typical processes of the TGC method for the inactive Li quantification, including the following six main steps. (1) After plating and stripping, the Li||Cu coin cell was disassembled in an Ar-filled glovebox. (2) While still in the glovebox, both the Cu foil and separator on the Cu foil side were harvested without washing and sealed in a container with an inside pressure of 1 atm by a rubber septum which is stable against water. (3) After transferring the sample container out of the glovebox, we injected $0.5\\mathrm{ml}$ of $_\\mathrm{H_{2}O}$ into the container to react with the inactive Li completely. (4) A gas-tight syringe was used to transfer $30\\upmu\\mathrm{l}$ of the resultant gas from the container into the gas chromatography (GC) system. (5) The amount of $\\mathrm{\\ddot{H}}_{2}$ was measured by the GC. (6) The content of the metallic $\\mathrm{Li}^{0}$ was determined by converting the corresponding $\\mathrm{H}_{2}$ amount according to a pre-established standard calibration curve (Extended Data Fig. 7b). All the processes minimize the potential damage and contamination during sample transfer, to obtain reliable results. \n\nIn the GC column, the stationary phase has a different affinity with different species, so that gas species can be differentiated by retention time. Extended Data Fig. 8a shows the GC chromatograms of background gases from a well-sealed empty container in the Ar-filled glovebox. The peaks at 1.45 min, 2.42 min and $3.21\\mathrm{min}$ represent Ar, $\\Nu_{2}$ and $\\mathrm{CH}_{4},$ , respectively. When an $\\mathrm{H}_{2}\\mathrm{O}$ titration process is applied to a small piece of pure Li metal, $\\mathrm{H}_{2}$ will be generated. The $\\mathrm{H}_{2}$ characteristic peak appears at $1.05\\mathrm{min}$ , as shown in Extended Data Fig. 8b. \n\nSource of $\\cdot_{N_{2}}$ in the gas chromatograms. Note that ${\\bf N}_{2}$ detected from the GC comes from the gas sampling process, instead of existing in the reaction container. As schematized in the TGC process in Extended Data Fig. 1, the inactive Li samples were loaded and sealed into the reaction container in an Ar-filled and $\\Nu_{2}$ -free glovebox. After the samples were taken out of the glovebox, $0.5{\\mathrm{ml}}$ of pure $\\mathrm{H}_{2}\\mathrm{O}$ was injected into the container and reacted with the inactive Li sample. This is an air-free process. A gas-tight syringe was then used to take the gas sample for GC injection and measurement. There is a small amount of air left in the needle space of the gas-tight syringe. Moreover, in the GC injection process, when the needle breaks the septum, a tiny amount of air might be introduced into the GC column. Even though the air peak is inevitable for the injection gas sampling method, the inactive Li samples have indeed all been reacted in advance and were never exposed to $\\Nu_{2}$ . \n\nWe carried out the following tests to demonstrate that the $\\Nu_{2}$ comes from the air during sampling and that the presence of air has negligible impact on the inactive Li $\\left(\\mathrm{H}_{2}\\right)$ quantification. First, we measured the gas in the blank container without any inactive Li, which has been well sealed in the Ar-filled glovebox. If the $\\Nu_{2}$ comes from the reaction container, the intensity of the $\\Nu_{2}$ peaks will vary proportionally to the injected gas amount into the GC. We took different amounts of gas sample from the blank container and performed GC measurement. As shown in Extended Data Fig. 8c, the $\\mathrm{N}_{2}$ peak intensities remain almost identical for injection amounts varying from 5 to $30\\upmu\\mathrm{l}$ . The same result was obtained when $\\mathrm{H}_{2}\\mathrm{O}$ titration was performed on inactive Li. The measured $\\mathrm{H}_{2}$ content increase as a function of injected gas amount while the $\\Nu_{2}$ content remains almost constant (Extended Data Fig. 8d). Noting that the reaction container is sealed in the Ar-filled glovebox, the Ar peak is saturated even if only ${5\\upmu\\mathrm{l}}$ of sample gas is injected and remains unchanged in all measurements. The invariability of $\\mathrm{N}_{2}$ peaks is not because of saturation in the previous measurements, since the intensity of the $\\Nu_{2}$ peak increases significantly after purposely injecting $10\\upmu\\mathrm{l}$ of air (Extended Data Fig. 8e). Therefore, we have confirmed that the $\\Nu_{2}$ comes from the injection sampling process and it will not have any chemical reaction with the inactive Li samples. Moreover, the $\\mathrm{H}_{2}$ quantification is not influenced by the injection sampling process. \n\nPossible existence of LiH. Besides the SEI species listed in Extended Data Table 1, there have been mixed reports regarding the existence of LiH in Li metal electrodes20–22. There are two possible scenarios in which LiH may exist in the Li metal electrodes: (1) LiH may exist within the SEI as an electrochemical reduction product at excessively negative potentials21,22; (2) LiH may largely exist in the bulk electrode as mossy dendrites20. To examine the possible influence from LiH in SEI, we repeatedly polarized the current collectors above $0\\mathrm{V},$ so that only SEI forms without metallic ${\\mathrm{Li}^{0}}$ deposition31. For the electrolytes investigated in this work, after such cyclic polarizations between $0\\mathrm{V}$ and $1\\mathrm{V}$ for ten cycles, the TGC detected no $\\mathrm{H}_{2}$ from all SEI–water reactions (Extended Data Fig. 9a-h), indicating that LiH does not exist in the SEIs. To examine the possible influence from LiH in bulk inactive Li, we changed the titration solution from $\\mathrm{H}_{2}\\mathrm{O}$ to $\\mathrm{D}_{2}\\mathrm{O},$ which can distinguish LiH and metallic ${\\mathrm{Li}}^{0}$ by producing HD and $\\mathrm{D}_{2}$ , respectively, based on the following reactions: (1) $\\mathrm{LiH}+\\mathrm{D}_{2}\\mathrm{O}=\\mathrm{LiOD}+\\mathrm{HD}\\uparrow$ ; (2) $2\\mathrm{Li}+2\\mathrm{D}_{2}\\mathrm{O}=2\\mathrm{LiOD}$ $+\\mathrm{D}_{2}\\uparrow$ . Differentiating HD and $\\mathrm{D}_{2}$ was then achieved based on partial pressure analysis by residual gas analyser $(\\mathrm{RGA})^{32}$ . From the RGA results (Extended Data Fig. 9i–n), we confirmed that LiH does not exist in the bulk inactive Li generated by the electrolyte systems of low Coulombic efficiency. The exclusion of LiH from either SEI or bulk inactive Li confirms that the conclusions drawn from the TGC analysis should be reliable and free of interference from possible LiH species. \n\nCalibration. The $\\mathrm{H}_{2}$ concentration was calibrated and measured using a Shimadzu GC-2010 Plus Tracera equipped with a barrier ionization discharge (BID) detector. Helium $(99.9999\\%$ ) was used as the carrier gas. Split temperature was kept at $200^{\\circ}\\mathrm{C}$ with a split ratio of 2.5 (split vent flow: $2\\mathrm{0.58\\ml\\min^{-1}}$ , column gas flow: $8.22\\mathrm{ml}\\mathrm{min}^{-1}$ , purge flow: $0.5\\mathrm{{\\dot{ml}}\\mathrm{{min}^{-1}}}$ ). Column temperature (RT-Msieve 5A, $0.53\\mathrm{mm}\\dot{}$ was kept at $40^{\\circ}\\mathrm{C}$ . A BID detector was kept at $235^{\\circ}\\mathrm{C},$ and BID detector gas flow rate was $50\\mathrm{ml}\\mathrm{min}^{-1}$ . All calibration and sample gases were immediately collected via a $50\\upmu\\mathrm{l}$ Gastight Hamilton syringe before injection. For calibration of $\\mathrm{H}_{2}$ concentration, 1,500 p.p.m. of $\\mathrm{H}_{2}$ gas was produced by reacting highpurity sodium with DI water in a septum sealed glass vial. We collected ${5\\upmu\\mathrm{l}}$ $10\\upmu\\mathrm{l},$ $15\\upmu\\mathrm{l}$ $20\\upmu\\updownarrow,25\\upmu\\mathrm{l}$ and $30\\upmu\\mathrm{l}$ of the $\\mathrm{H}_{2}$ gas produced, corresponding to 250 p.p.m., 500 p.p.m., 750 p.p.m., 1,000 p.p.m., 1,250 p.p.m. and $1,500{\\mathrm{p.p.m}}.$ , respectively, and injected them into the GC. The calibration curve was plotted and fitted with $\\mathrm{H}_{2}$ concentration versus $\\mathrm{H}_{2}$ peak area as measured by the GC. The as-established $\\mathrm{H}_{2}$ calibration curve $\\mathrm{(H}_{2,\\mathrm{ppm}}$ versus detected $\\mathrm{H}_{2}$ area) and equation are shown in Extended Data Fig. 7a. To acquire the exact number of $\\mathrm{H}_{2}$ molecules within the container, the $\\mathrm{H}_{2}$ concentration calibration curve was converted to a calibration curve in terms of the mole number of $\\mathrm{H}_{2}$ as a function of detected area based on the following two conditions: (1) $1\\ {\\mathrm{p.p.m.}}=4.08\\times10^{-8}\\ {\\mathrm{mmol}}\\ {\\mathrm{ml^{-1}}}$ (1 atm, 298 K); (2) container volume $(30\\pm0.5\\mathrm{ml})$ ). \n\nThe mole number of $\\mathrm{H}_{2}$ calibration curve established a direct relationship between $\\mathrm{H}_{2}$ area reported by the GC software and the number of $\\mathrm{\\ddot{H}}_{2}$ molecules in the fixed TGC set-up, making the following inactive Li measurement independent of slight pressure change. Based on the chemical reaction $2\\mathrm{Li}+2\\mathrm{H}_{2}\\mathrm{O}\\longrightarrow2\\mathrm{LiOH}+$ $\\mathrm{H}_{2}\\uparrow$ , the standard calibration curve and the equation for Li metal mass $(m_{\\mathrm{Li}})$ as a function of the detected $\\mathrm{H}_{2}$ area are obtained and shown in Extended Data Fig. 7b. Validation of the GC measurement. (1) The $\\mathrm{H}_{2}$ concentration in p.p.m. as a function of GC detected $\\mathrm{H}_{2}$ area (Extended Data Fig. 7a) was verified by using the certified GASCO $\\mathrm{H}_{2}$ calibration test gas. (2) We then used commercial Li metal of known mass to verify the relationship established for $m_{\\mathrm{Li}}$ versus detected $\\mathrm{H}_{2}$ area (Extended Data Fig. 7b). We carefully weighed nine pieces of commercial Li metal with mass ranging from $0.54\\mathrm{mg}$ to $1.53\\mathrm{mg}$ in the Ar-filled glovebox with a fivedigit balance $(\\bar{1}0^{-5}\\mathbf{g})$ and then performed the TGC measurement. The detected $\\mathrm{H}_{2}$ area as a function of the Li metal mass from the nine pieces of Li metal is shown in Extended Data Fig. 7c. The result shows that the mass of Li metal is linearly related $(R^{2}=99.8\\%)$ ) to the detected $\\mathrm{H}_{2}$ area, indicating the validity of the TGC system for quantifying metallic $\\mathrm{Li}^{0}$ . In reverse, we calculated the Li metal mass from the detected $\\mathrm{H}_{2}$ area using the relationship of $m_{\\mathrm{Li}}$ versus detected $\\mathrm{H}_{2}$ area. The TGC-measured and balance-measured Li metal masses are compared in Extended Data Fig. 7d. The exact values of TGC-measured and balance-measured Li metal masses are listed in Extended Data Fig. 7e. The negligible differences between the TGC quantification and balance measurement indicate the validity and accuracy of the TGC method. The significant digit of the balance is $0.01\\mathrm{img}(10^{-5}\\mathrm{g})$ , as marked in red in Extended Data Fig. 7e, whereas that of the TGC is $0.0001\\mathrm{mg}$ $(0.1\\upmu\\mathbf{g},10^{-7}\\mathbf{g})$ , which has been demonstrated in the limit of detection/limit of quantification (LOD/LOQ) analysis. Thus, the minimal difference between the two quantification methods is mainly ascribed to the inaccuracy of the balance, which has a precision two orders of magnitude smaller than the TGC. \n\nLOD/LOQ analysis. The concentration of hydrogen in the air is $0.000053\\%$ . To get the LOD/LOQ values, $30\\upmu\\mathrm{l}$ of the air sample was injected into GC by the same gas-tight syringe as used for the hydrogen measurement and repeated for a total of 10 times. The results are listed in Extended Data Fig. 7f. Based on the definition of LOD/LOQ, the calculated LOD/LOQ from the table is $16.44\\mathrm{p.p.m}$ and 49.81 p.p.m., respectively, corresponding to $0.28\\upmu\\mathrm{g}$ and $0.84\\upmu\\mathrm{g}$ of metallic ${\\mathrm{Li}}^{0}$ in the designed TGC system. \n\nInactive Li sample measurement. After stripping under various conditions, $\\mathrm{Li}||\\mathrm{Cu}$ cells were disassembled inside an Ar-filled glovebox $(\\mathrm{H}_{2}\\mathrm{O}<0.5\\:\\mathrm{p.p.m.}$ ). The Cu foil and separator near the Cu foil side with inactive Li residue on top were placed into a $30\\mathrm{ml}$ container without washing. The container was sealed by a rubber septum and further capped by a stainless-steel/copper ring for safety and to minimize the deformation of the rubber septum when gas was generated later. The internal pressure of the sealed container was adjusted to 1 atm by connecting the container and glovebox environment (0 mbar) with an open-ended syringe needle. After transferring the sealed container out of the glovebox, $0.5\\mathrm{ml}$ of water was injected into the container, allowing complete reaction of inactive Li residue with water. An excess amount of $_\\mathrm{H}_{2}\\mathrm{O}$ was added to react with all the inactive metallic $\\mathrm{Li}^{0}$ , leading to complete conversion to the $\\mathrm{H}_{2}$ products. The Cu foil became shiny and the separator normally became clean when reactions finished, indicating a complete reaction of the inactive Li with $\\mathrm{H}_{2}\\mathrm{O}$ The as-generated gases were then well dispersed and mixed by shaking the container to prevent $\\mathrm{H}_{2}$ accumulation on top of the container. Then a gas-tight syringe was used to quickly take $30\\upmu\\mathrm{l}$ of the well-mixed gas and to inject it into the GC for $\\mathrm{H}_{2}$ measurement. The GC-measured $\\mathrm{H}_{2}$ areas as a function of cell Coulombic efficiency are shown in Extended Data Fig. 2e. The conversion between mAh and mg of Li is shown in Extended Data Fig. 2f. \n\nSafety considerations. Li is electrochemically inactive, but chemically hyperactive due to the high surface areas which may lead to serious potential safety hazards33. Inactive Li quantification using the TGC method should be done carefully, taking the following aspects into consideration: \n\n(1) The proper amount of inactive Li for TGC measurement. The minimum amount of inactive metallic Li that has been measured is as low as $1\\upmu\\mathrm{g}$ $({\\sim}0.004\\ \\mathrm{mAh})$ ). The maximum amount measured in the present work is ${\\sim}1.6\\mathrm{mg}.$ corresponding to ${\\sim}6\\mathrm{mAh}$ . It is generally preferred to reduce the amount of inactive Li sample, as the GC with an advanced $\\mathrm{H}_{2}$ detector can be very sensitive (1 p.p.m.). The greater the amount of $\\mathrm{H}_{2}$ generated, the more dangerous it could be. \n\n(2) The reaction container must be completely sealed inside the Ar-filled glovebox before it is taken out, to avoid $\\mathrm{O}_{2}$ and moisture entering the container. Moisture in air influences the measurement accuracy, and $\\mathrm{O}_{2}$ may lead to an explosion when a large amount of water reacts with inactive Li. \n\n(3) Stainless steel/copper rings should be used to minimize the deformation of the rubber septum when $\\mathrm{H}_{2}$ is generated inside the reaction container after water titration, and to prevent potential explosion due to the increased internal pressure. \n\n(4) Waste gas in the container after TGC measurement should be disposed of in a fume hood to avoid regional $\\mathrm{H}_{2}$ accumulation which can lead to an explosion (explosive limits of $\\mathrm{H}_{2}$ in air range from about $18\\%$ to $60\\%$ ; the flammable limits are $4\\mathrm{-}75\\%$ ). \n\nCryogenic focused ion beam scanning electron microscopy. The inactive Li samples on Cu foil were disassembled and washed with anhydrous DME (for HCE) or DMC (for CCE) in the Ar-filled glovebox. The samples were mounted on the SEM sample holder in the glovebox, then transferred to a FEI Helios NanoLab Dualbeam. Platinum was deposited for surface protection from the ion beam: $100\\mathrm{nm}$ of Pt was deposited using the electron beam at $5\\mathrm{kV},0.8\\mathrm{nA}$ ; ${300}\\mathrm{nm}$ of Pt was deposited using the ion beam at $30\\mathrm{kV},0.1\\mathrm{nA}$ . The stage was cooled with liquid nitrogen to $-180^{\\circ}\\mathrm{C}$ or below. Sample cross-sections were exposed using a 1 nA ion beam current and 100 ns dwell time, and cleaned twice at $0.5\\mathrm{nA}$ and $0.1\\mathrm{nA}$ , respectively. SEM images were taken with an Everhart-Thornley Detector (ETD) at $5\\mathrm{kV.}$ \n\nCryogenic transmission electron microscopy. The cryo-TEM sample for HCE was directly deposited and stripped on a lacey carbon grid in the Li||Cu half-cell. The sample for CCE was prepared by peeling the inactive Li from Cu foil cycled in the half-cell, and then depositing it onto the same type of TEM grid. Both half-cells were plated at $0.5\\mathrm{mAcm}^{-2}$ for 2 hours and then stripped to 1 V at the same rate. Both TEM samples were slightly rinsed with DME/DMC in the Ar-filled glovebox to remove trace Li salt. Once dry, the samples were sealed in airtight bags and plunged directly into a bath of liquid nitrogen. The airtight bags were then cut and the TEM grids were immediately immersed in liquid nitrogen. Then the grids were mounted onto a TEM cryo-holder (Gatan) via a cryo-transfer station. In short, the whole TEM sample preparation and transfer process prevents any contact of Li metal with the air at room temperature. TEM characterizations were carried out on JEOL JEM-ARM300CF at $300\\mathrm{kV}$ and JEM-2100F at $200\\mathrm{kV}.$ HRTEM images were taken at a magnification of $\\times500{,}000$ with a Gatan OneView Camera (full $4,000\\times4,000$ pixel resolution) when the temperature of samples reached about $100\\mathrm{K}.$ . The FFT pattern and inverse FFT image after mask filtering were analysed with DigitalMicrograph software. \n\n$\\mathbf{X}$ -ray photoelectron spectroscopy. After a plating/stripping process, cells were disassembled in an Ar-filled glovebox with $\\mathrm{H}_{2}\\mathrm{O}<0.5$ p.p.m. Cu foils with inactive Li residue were gently and thoroughly rinsed by DME (for HCE) and DMC (for CCE) to remove residual surface Li salts. The rinsed electrodes were sealed in an airtight stainless-steel container and transferred into the glovebox connected to the XPS chamber. XPS was performed with a Kratos AXIS Supra, with the Al anode source operated at $15\\mathrm{kV.}$ The chamber pressure was $<10^{-8}$ torr during all measurements. All XPS measurements were collected with a spot size $300\\upmu\\mathrm{m}$ by $700\\upmu\\mathrm{m}$ with a charger neutralizer during acquisition. Survey scans were collected with a $1.0\\mathrm{eV}$ step size, followed by high-resolution scans collected with a step size of $0.05\\mathrm{eV.}$ Fittings of the XPS spectra were performed with CasaXPS software (version 2.3.15, Casa Software Ltd) to estimate the atomic compositions and chemical species. All species (Li 1s, F 1s, O 1s and C 1s) were fitted using a Shirley type background. High-resolution spectra were calibrated using the $\\mathrm{~C~}1s$ peak at $284.6\\mathrm{eV}.$ The peak positions and areas were optimized by a Levenberg– Marquardt least-squares algorithm using $70\\%$ Gaussian and $30\\%$ Lorentzian line shapes. Quantification was based on relative sensitivity factors. The curve fit for the core peaks was obtained using a minimum number of components to fit the experimental curves. \n\nResidual gas analyser. To exclude the potential influence on TGC $\\left(\\mathrm{H}_{2}\\right)$ quantification from LiH, which may exist in the bulk electrode as mossy dendrite, we designed an alternative approach to distinguish between LiH and metallic ${\\mathrm{Li}}^{0}$ by changing the titration solution from $\\mathrm{H}_{2}\\mathrm{O}$ to $\\mathrm{D}_{2}\\mathrm{O}$ , which reacts with LiH and Li to produce HD and $\\mathrm{D}_{2}\\mathrm{:}$ , respectively, followed by differentiating between HD and $\\mathrm{D}_{2}$ based on partial pressure analysis by RGA. The base pressure in the vacuum chamber is $\\mathrm{{\\sim}8\\times10^{-8}}$ torr. The gas mixtures were introduced into the chamber using an MKS pressure/flow control valve controlled by a computer. The partial pressures of gases in the system were measured using an SRS RGA with a detection limit down to $10^{-11}$ torr. The turbo pump and backing pump used in this vacuum system were specially designed for handling highly corrosive gases. This setup provides a wide-range partial pressure control $(\\bar{10}^{-11}$ torr to $10^{-4}$ torr) and allow the identification of the different gas molecules including hydrogen isotopes present in the system under high vacuum conditions. Before measuring each sample, the whole system was pumped down to high vacuum $10^{-8}$ torr) to minimize the possibility of contamination. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author on reasonable request. \n\n31.\t Wood, S. M. et al. Predicting calendar aging in lithium metal secondary batteries: the impacts of solid electrolyte interphase composition and stability. Adv. Energy Mater. 8, 1–6 (2018). \n32.\t Drenik, A. et al. Evaluation of the plasma hydrogen isotope content by residual gas analysis at JET and AUG. Phys. Scr. T170, 014021 (2017). \n33.\t Xu, K. Nonaqueous liquid electrolytes for lithium-based rechargeable batteries. Chem. Rev. 104, 4303–4418 (2004). \n\nAcknowledgements This work was supported by the Office of Vehicle Technologies of the US Department of Energy through the Advanced Battery Materials Research (BMR) Program (Battery500 Consortium) under contract DE-EE0007764. Cryo-FIB was performed at the San Diego Nanotechnology Infrastructure, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the US National Science Foundation (NSF) (grant ECCS-1542148). We acknowledge the UC Irvine Materials Research Institute for the use of the cryo-electron microscopy and XPS facilities, funded in part by the NSF Major Research Instrumentation Program under grant CHE-1338173. The partial pressure measurements and analysis were done using a unique RGA based high vacuum gas evolution system developed under the guidance of I. K. Schuller’s laboratory at UC San Diego. The development of this system were supported by the US Department of Energy, Office of Science, Basic Energy Science (BES) under grant DE FG02 87ER-45332. C.F. thanks D. M. Davies for his suggestions on the manuscript and Shuang Bai for her assistance with the TEM experiment. J.L. thanks W. Wu for helping on figure design. \n\nAuthor contributions C.F., J.L., X.W. and Y.S.M. conceived the ideas. C.F. designed and implemented the TGC system. C.F. designed and performed the TGC, cryoFIB–SEM, XPS experiments and data analysis. M.Z. collected the cryo-TEM data. C.F., M.Z. and B.L. interpreted TEM data. Y.Z., C.F. and M.C. prepared samples for characterizations. J.Z.L. and Y.Y. helped to set up cryo-FIB instrumentation. F.Y., N.W. and J.G. helped with GC set up and calibration. C.F. and M.-H.L. performed the RGA experiment. J.A., M.A.S. and K.X. formulated and provided the HCE electrolyte. L.Y. and M.C. formulated and provided the GM electrolyte. J.L. and C.F. wrote the manuscript. All authors discussed the results and commented on the manuscript. All authors have approved the final manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nCorrespondence and requests for materials should be addressed to Y.S.M. Reprints and permissions information is available at http://www.nature.com/ reprints. \n\n![](images/a91c75ad4e45890a3835f37c0b4a0cdfdc1f76677615e5c346affb62264040dd.jpg) \nExtended Data Fig. 1 | Schematic working principle of the TGC method. By combining $[\\mathrm{H}_{2}\\mathrm{O}$ titration on an inactive Li sample and $\\mathrm{H}_{2}$ quantificatio y GC, the amount of metallic $\\mathrm{Li}^{0}$ is calculated based on the chemical reaction $2\\mathrm{Li}+2\\mathrm{H}_{2}\\mathrm{O}\\rightarrow2\\mathrm{LiOH}+\\mathrm{H}_{2}\\uparrow$ . \n\n![](images/9760d009ab04910c0a8d4bad1025171d052d1b571a653b12bf3e8b525619677b.jpg) \nExtended Data Fig. 2 | Supplementary materials for TGC analysis. a, b, Representative voltage profiles of $\\mathrm{Li}||\\mathrm{Cu}$ cells in (a) HCE and CCE, plating at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for $\\bar{1}\\mathrm{mAh}\\mathrm{cm}^{-2}$ , stripping to $1\\mathrm{V}$ at $0.5\\mathrm{mA}\\mathrm{cm}^{-2}$ , $\\bar{2}.5\\operatorname{mA}{\\mathrm{cm}^{-2}}$ and $5.0\\mathrm{mA}\\mathrm{cm}^{-2}$ (voltage profiles below $0\\mathrm{V}$ represents the plating process, while those above $0\\mathrm{V}$ represents the stripping process); (b) $2\\mathrm{M}$ LiFSI–DMC, $0.5{\\mathrm{~M~}}$ LiTFSI–DME/DOL, $1\\mathrm{M}$ LiTFSI–DME/DOL, 1 M LiTFSI–DME/DOL $+2\\%$ $\\mathrm{LiNO}_{3}$ , $\\mathrm{CCE}+\\mathrm{Cs}^{+}$ and CCE $^+$ FEC, plating at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ , stripping to $1\\mathrm{V}$ at $0.5\\mathrm{mA}\\mathrm{cm}^{-2}$ . \n\nc, The isolated metallic ${\\mathrm{Li}}^{0}$ percentage in total capacity loss $\\mathrm{(Li^{0}/L i^{0}}$ $+\\mathrm{Li^{+}})$ . d, SEI ${\\mathrm{Li}}^{+}$ percentage in total capacity loss $(\\mathrm{Li^{+}/L i^{0}+L i^{+}})$ . e, Measured $\\mathrm{H}_{2}$ area as a function of Coulombic efficiency under a variety of testing conditions. Every data point is an average of three separate GC measurements. The error bars represent the standard deviation, indicating the accuracy and reproducibility of the GC measurement. f, Unit conversion between milliampere-hours and milligrams of Li. \n\n![](images/b37599b60980348e0d2f7845db916e7c2bc368e240876151c20f7350efc96551.jpg) \nExtended Data Fig. 3 | TGC analysis of inactive Li formed under extended electrochemical conditions. a, The voltage profiles of CCE with different deposition capacities at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for 1 mAh $c\\mathrm{m}^{-2}$ , $2\\mathrm{mAh}\\mathrm{cm}^{-2}$ , $3\\mathrm{\\mAh\\cm}^{-2}$ and 5 mAh $c\\mathrm{m}^{-2}$ . b, The corresponding TGC analysis of inactive Li with associated capacity loss and Coulombic \nefficiency under different deposition capacities. c, The cycling performance of CCE in $\\mathrm{Li}||\\mathrm{Cu}$ half-cells at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for $\\bar{1\\mathrm{mAh}}\\mathrm{cm}^{-2}$ . d, TGC analysis showing $\\mathrm{Li}^{0}$ and ${\\mathrm{Li}^{+}}$ contents with associated capacity loss after one, two, five and ten cycles, respectively. \n\nb \n\n![](images/a43bdd522cef185a1dc0e28dc57921e1313f55448e693bece6d368514a4eb88d.jpg) \nExtended Data Fig. 4 | XPS analysis of inactive Li SEI components formed in HCE and CCE for various stripping rates. a, Inactive Li formed in HCE. b, Inactive Li formed in CCE. The stripping rates show negligible impact on SEI components and contents in both electrolytes. \n\n![](images/c2eedf77e57b81273f4cebadb630374ab8db590445e20c117efcdd444aee7af0.jpg) \nExtended Data Fig. 5 | Supplementary materials for cryo-FIB-SEM and cryo-TEM analysis. a–c, Top view, cryo-FIB cross-section and schematic of deposited Li in HCE, respectively. The Li deposited in HCE forms large particles with several micrometres in size, with reduced porosity. d–f Top view, cryo-FIB cross-section and schematic of deposited Li in \nCCE, respectively. The Li shows a whisker-like morphology with high porosity. All deposited at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for $0.5\\mathrm{mAh}\\mathrm{\\overline{{c}}m}^{-2}$ . g, Statistics of inactive Li SEI components formed in HCE, as detected at 50 different sample positions by cryo-TEM. h, Statistics of inactive Li SEI components formed in CCE, as detected at 50 different sample positions by cryo-TEM. \n\n![](images/367ac969dd6e3afb958771e4d50288060c554ee4daa003c1c9a3e73989d68050.jpg) \n\nExtended Data Fig. 6 | Strategies that may mitigate inactive Li formation. a, Cross-sectional morphology of Li deposits generated in an advanced electrolyte developed by General Motors (GM), showing a columnar structure. b, The GM electrolyte delivers a first-cycle Coulombic efficiency of $96.2\\%$ , plating at $0.5\\mathrm{mAc}\\dot{\\mathrm{m}}^{-2}$ for $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ , stripping at $0.5\\mathrm{mA}\\mathrm{cm}^{-2}$ to 1 V. c–f, 3D current collector. c, SEM image of Li deposits on Cu foil. d, SEM image of Li deposits on Cu foam. Both were deposited at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for $1\\mathrm{\\dot{m}A h}\\mathrm{cm}^{-\\bar{2}}$ in CCE. e, Representative first-cycle voltage profiles of Cu foil and Cu foam, plating at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ for $1\\dot{\\operatorname*{mAh}}{\\operatorname{cm}^{-2}}$ , stripping at $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ to $1\\mathrm{V}$ in CCE. f, TGC quantification of inactive Li for $\\mathtt{C u}$ foil and Cu foam samples. g, Schematic of an ideal artificial SEI design. The polymer-based artificial SEI should \n\nbe chemically stable against Li metal and mechanically elastic enough to accommodate the volume and shape change. Meanwhile, the edges of the artificial SEI should be fixed to the Li metal or the current collector, preventing the electrolyte from diffusing and making contact with fresh Li metal. The flexible polymer SEI thus can accommodate expansion and shrinkage during repeated Li plating and stripping. In this way, no Li will be consumed to form SEI during extended cycles, and we can realize anode-free Li metal batteries. h, Influence of pressure on Li plating/ stripping. The results are from the HCE, at $0.{\\overset{-}{5}}\\operatorname*{mA}\\ c\\operatorname*{m}^{-2}$ for $\\mathrm{1}\\mathrm{mA}\\mathrm{\\bar{h}}\\mathrm{cm}^{-2}$ , using a load cell. At each condition, two load cells were measured. The error bars indicate the standard deviation. \n\n![](images/6d2566fdc057d4906e8db87e850fcca36bbd605d67b9946cef4142818502eee5.jpg) \n\nef \n\n
Li, mg12345678910
TGC0.00050.58200.68250.89700.93040.94721.19431.45501.47811.5098
BalanceBlank0.540.660.860.900.911.181.451.511.53
\n\nSignificant digits of the measurement methods are marked in red \n\n
Blank Sample12345678910
H2 concentration in ppm47.2058.2754.3941.0746.5451.0251.0354.6545.4953.98
\n\nExtended Data Fig. 7 | TGC calibration and LOD/LOQ analysis. a, $\\mathrm{H}_{2}$ concentration in ppm calibration curve as a function of detected $\\mathrm{H}_{2}$ area and verification with certified GSCO $\\mathrm{H}_{2}$ calibration gas. b, Converted metallic $\\mathrm{Li}^{0}$ mass calibration curve as a function of detected $\\mathrm{H}_{2}$ area. c, Nine pieces of Li metal with known mass were tested using the TGC set-up. The strongly linear relationship with detected $\\mathrm{H}_{2}$ area indicates the feasibility of this method. d, Comparison between the balance-measured mass and TGC-quantified mass of the commercial Li metal pieces. e, Numerical comparison between the balance-measured mass and TGC-quantified mass of the commercial Li metal pieces. As the accuracy of the balance is two orders of magnitude lower than the TGC $(10^{-5}\\mathrm{g}$ versus $10^{-7}{\\bf g}$ , the differentials should mainly come from the balance. f, $\\mathrm{H}_{2}$ concentration in the blank samples measured for LOD/LOQ analysis. A total of 10 measurements were taken for the LOD/LOQ calculation. \n\n![](images/879d1087068c69f96af6702cbd1535ccf4492ad58a70d472cdbaad40a2b46be2.jpg) \nExtended Data Fig. 8 | GC chromatogram and ${\\bf N}_{2}$ interference analysis. a, GC chromatogram of the background gas from glovebox. $\\mathbf{b}$ , GC chromatogram of gases with $\\mathrm{H}_{2}$ after $\\mathrm{H}_{2}\\mathrm{O}$ titration on metallic $\\mathrm{Li}^{0}$ . c, Glovebox background gas measurements with various sampling amounts. The $\\mathrm{N}_{2}$ amounts remain at the same level with various injection amounts, indicating the $\\Nu_{2}$ does not exist in the reaction container. d, Container gas measurements with various sampling amounts after \nthe $\\mathrm{H}_{2}\\mathrm{O}$ titration. The $\\Nu_{2}$ amounts still remain identical with different injection amounts, whereas the $\\mathrm{H}_{2}$ amounts increase in proportion to the increment of injection amounts, indicating that the $\\mathrm{N}_{2}$ does not originally exist in the reaction container but comes from the gas sampling process, and thus will not have any chemical reactions with the inactive Li samples; the $\\mathrm{H}_{2}$ quantification is not influenced by the injection sampling process. e, GC chromatogram of $10\\upmu\\mathrm{l}$ of air. \n\n![](images/2351e0959651098c4fada74791292c4e929cc2aa68bac21ff5f4ff85d3f5e270.jpg) \nExtended Data Fig. 9 | Analysis of possible LiH presence in inactive Li. a-h, Possible influence from LiH in SEI. $\\mathbf{a-g}$ , The voltage profiles of SEI formation between $0\\mathrm{V}$ and $1\\mathrm{V}$ at $0.1\\mathrm{mA}$ for ten cycles in $2\\mathrm{M}$ LiFSI–DMC (a), $0.5{\\mathrm{M}}{}$ LiTFSI–DME/DOL ${\\bf(b)}$ , 1 M LiTFSI–DME/DOL (c), CCE (d), HCE (e), $\\mathrm{CCE}+\\mathrm{Cs}^{+}$ (f) and $\\mathbf{CCE}+\\mathbf{FEC}\\left(\\mathbf{g}\\right)$ . After the SEI formation, we performed TGC measurements on the current collectors with SEI. h, TGC results of the seven types of electrolytes. No $\\mathrm{H}_{2}$ can be detected from any of them, indicating no LiH presence in the SEI of the systems studied. i–n, Possible influence from LiH in bulk inactive Li. To \ndifferentiate the two species, we substitute the titration solution with $\\mathrm{D}_{2}\\mathrm{O}$ instead of $\\mathrm{H}_{2}\\mathrm{O}$ The $\\mathrm{D}_{2}\\mathrm{O}$ reacts with LiH and metallic ${\\mathrm{Li}}^{0}$ to produce HD and $\\mathrm{D}_{2}$ , respectively. RGA can effectively distinguish between HD (relative molecular mass 3) and $\\mathrm{D}_{2}$ (relative molecular mass 4) by partial pressure analysis. i, The $\\mathrm{D}_{2}$ standard from the reaction between commercial pure Li metal and $\\mathrm{D}_{2}\\mathrm{O}$ . j, The HD standard from the reaction between commercial LiH powder and $\\mathrm{D}_{2}\\mathrm{O}$ k–n, Analysis of gaseous products from reactions between $\\mathrm{D}_{2}\\mathrm{O}$ and inactive Li forming in 2 M LiFSI–DMC (k), 0.5 M LiTFSI–DME/DOL (l), $1\\mathrm{M}$ LiTFSI–DME/DOL $\\mathbf{\\tau}(\\mathbf{m})$ and CCE (n). \n\nExtended Data Table 1 | The solubility or reactivity of known SEI species with $H_{2}O$ \n\n\n
SEl componentSolubility in 100 mL H2O
LiF0.134 g (0.67 mg in 0.5 mL HzO)
LiOH12.8 g
LiC2048g
LiCO31.29 g
Li2OLi2O + H2O = 2LiOH
CH3LiCHLi + HO = LiOH + CH4 ↑
ROLiROLi + H2O = LiOH + ROH
(CH2OCO2Li)2(CH2OCO2Li)2 + HO = LiCO3 + (CHOH)2 + CO2 ↑
LiOCO2R2LiOCO2R + HO = LiCO3 + 2ROH + CO2↑
" + }, + { + "id": "10.1016_j.chempr.2018.10.007", + "DOI": "10.1016/j.chempr.2018.10.007", + "DOI Link": "http://dx.doi.org/10.1016/j.chempr.2018.10.007", + "Relative Dir Path": "mds/10.1016_j.chempr.2018.10.007", + "Article Title": "Nitrogen Fixation by Ru Single-Atom Electrocatalytic Reduction", + "Authors": "Tao, HC; Choi, C; Ding, LX; Jiang, Z; Hang, ZS; Jia, MW; Fan, Q; Gao, YN; Wang, HH; Robertson, AW; Hong, S; Jung, YS; Liu, SZ; Sun, ZY", + "Source Title": "CHEM", + "Abstract": "Nitrogen fixation under ambient conditions remains a significant challenge. Here, we report nitrogen fixation by Ru single-atom electrocatalytic reduction at room temperature and pressure. In contrast to Ru nulloparticles, single Ru sites supported on N-doped porous carbon greatly promoted electroreduction of aqueous N-2 selectively to NH3, affording an NH3 formation rate of 3.665 mg(NH3) h(-1) mg(Ru)(-1) at -0.21 V versus the reversible hydrogen electrode. Importantly, the addition of ZrO2 was found to significantly suppress the competitive hydrogen evolution reaction. An NH3 faradic efficiency of about 21% was achieved at a low overpotential (0.17 V), surpassing many other reported catalysts. Experiments combined with density functional theory calculations showed that the Ru sites with oxygen vacancies were major active centers that permitted stabilization of *NNH, destabilization of *H, and enhanced N-2 adsorption. We envision that optimization of ZrO2 loading could further facilitate electroreduction of N-2 at both high NH3 synthesis rate and faradic efficiency.", + "Times Cited, WoS Core": 804, + "Times Cited, All Databases": 845, + "Publication Year": 2019, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000455452800017", + "Markdown": "# Article Nitrogen Fixation by Ru Single-Atom Electrocatalytic Reduction \n\nHengcong Tao, Changhyeok Choi, Liang-Xin Ding, ..., Yousung Jung, Shizhen Liu, Zhenyu Sun \n\nhhwang@scut.edu.cn (H.W.) ysjn@kaist.ac.kr (Y.J.) sunzy@mail.buct.edu.cn (Z.S.) \n\n![](images/6f8d523d26ab68f54bd354ecc7f4bdd92d5e77a79b456091156aa4cbd6d39665.jpg) \n\n# HIGHLIGHTS \n\nSingle Ru atoms exhibit outstanding catalytic ${\\sf N}_{2}$ electroreduction performance \n\nAddition of $Z\\mathsf{r O}_{2}$ could suppress the competitive hydrogen evolution reaction \n\nRu sites with oxygen vacancies are likely major active centers \n\nWe demonstrate single Ru sites coordinated in nitrogen-doped porous carbon for highly active and stable aqueous electroreduction of ${\\sf N}_{2}$ to $N H_{3}$ . \n\n# Article Nitrogen Fixation by Ru Single-Atom Electrocatalytic Reduction \n\nHengcong Tao,1 Changhyeok Choi,2 Liang-Xin Ding,3 Zheng Jiang,4 Zishan Han,1 Mingwen Jia,1 Qun Fan,1 Yunnan Gao,1 Haihui Wang,3,\\* Alex W. Robertson,5 Song Hong,1 Yousung Jung,2,6,\\* Shizhen Liu,1 and Zhenyu Sun1,7,\\* \n\n# SUMMARY \n\nNitrogen fixation under ambient conditions remains a significant challenge. Here, we report nitrogen fixation by Ru single-atom electrocatalytic reduction at room temperature and pressure. In contrast to Ru nanoparticles, single Ru sites supported on N-doped porous carbon greatly promoted electroreduction of aqueous ${\\ensuremath{\\mathsf{N}}}_{2}$ selectively to $M H_{3},$ affording an $N H_{3}$ formation rate of 3.665 $\\mathsf{m g}_{\\mathsf{N H}_{3}}\\mathsf{h}^{-1}\\mathsf{m g}_{\\mathsf{R u}}^{-1}$ at $-0.21\\mathrm{~V~}$ versus the reversible hydrogen electrode. Importantly, the addition of $Z r O_{2}$ was found to significantly suppress the competitive hydrogen evolution reaction. An $N H_{3}$ faradic efficiency of about $21\\%$ was achieved at a low overpotential $_{(0.17\\vee)}$ , surpassing many other reported catalysts. Experiments combined with density functional theory calculations showed that the Ru sites with oxygen vacancies were major active centers that permitted stabilization of \\*NNH, destabilization of ${\\star}_{\\mathsf{H}},$ and enhanced $\\ensuremath{\\mathsf{N}}_{2}$ adsorption. We envision that optimization of $Z r O_{2}$ loading could further facilitate electroreduction of $\\mathsf{N}_{2}$ at both high $N H_{3}$ synthesis rate and faradic efficiency. \n\n# INTRODUCTION \n\nThe reduction of ${\\sf N}_{2}$ to $N H_{3}$ at room temperature and atmospheric pressure has been the subject of intense research. However, the ${\\sf N}_{2}$ molecule is stable and inert with a strong triple bond and low polarizability.1,2 The Haber-Bosch process that was developed 100 years ago is still employed in industry for $N H_{3}$ synthesis at high temperatures $(>300^{\\circ}\\mathsf{C})$ and pressures $(>10\\mathsf{M P a})$ .3 This energy- and capital-intensive process uses ${\\sf H}_{2}$ that is mainly produced from the steam reformation of natural gas, which substantially increases greenhouse gas emissions.3 In addition, the $N H_{3}$ yield is rather low with a conversion of less than $15\\%$ . Finding efficient ways to adsorb and activate ${\\sf N}_{2}$ remains a big challenge. \n\nElectrochemical reduction of ${\\sf N}_{2}$ to $N H_{3}$ is an attractive route and can be powered by energy from solar or wind sources, enabling a sustainable energy economy.4 There are two major issues associated with electrochemical ${\\sf N}_{2}$ reduction: (1) large overpotential and (2) low faradic efficiency (FE) toward $N H_{3}$ due to the occurrence of the competing hydrogen evolution reaction (HER), especially in aqueous solutions.5,6 So far, only a limited number of electrocatalysts $(\\mathsf{A u},^{7-9}\\mathsf{P t}/\\mathsf{C},^{10}\\mathsf{R u},^{11}\\mathsf{M o},^{6}$ $\\mathsf{A g/A u},\\mathsf{\\Omega}^{12}\\mathsf{B i_{4}V_{2}O_{11}/C e O_{2},\\Omega}^{13}$ Rh,14 and ${\\mathsf{F e/C N T}}^{15}$ ) have been reported for the reduction of ${\\sf N}_{2}$ to $N H_{3}$ . Most of these catalysts, however, suffer from slow reaction kinetics, low ${\\sf N}_{2}$ adsorption, and reduction activity. The highest $N H_{3}$ FE reported hitherto in an ambient aqueous ${\\sf N}_{2}$ electroreduction reaction (NRR) is about $10.1\\%$ at $-0.48\\mathrm{~V~}$ versus $\\mathsf{A g/A g C l}$ for amorphous Au supported on $\\mathsf{C e O}_{x}/$ reduced graphene oxide.7 Ru is considered a second-generation $N H_{3}$ catalyst with a ${\\sf N}_{2}$ \n\n# The Bigger Picture \n\nElectrochemical reduction of ${\\sf N}_{2}$ to $N H_{3}$ using renewable electricity is a simple and green $N H_{3}$ production method. Most reported catalytic systems, however, suffer from slow reaction kinetics, low ${\\sf N}_{2}$ adsorption, and reduction activity. Designing selective and energy-efficient electrocatalysts is highly desirable to enable both high faradic efficiency and $N H_{3}$ yield rate. Isolating Ru single atoms in Ndoped porous carbon significantly promotes ${\\sf N}_{2}$ -to-NH3 conversion, reaching an $N H_{3}$ formation rate of more than 3.6 mgNH3h\u00011mgR\u0001u1 . The addition of $Z r O_{2}$ can effectively suppress the hydrogen evolution reaction, affording a large $N H_{3}$ faradic efficiency of up to $21\\%$ at a low overpotential (0.17 V). This work opens up opportunities for development of single-atom catalysts to facilitate efficient $N H_{3}$ synthesis. \n\nreduction potential calculated to be lower than Fe.4,11,16 However, to date only one work has demonstrated $N H_{3}$ production on Ru cathodes, where an $N H_{3}$ formation rate and FE in the best case were limited to $1.3\\times10^{-3}\\mathsf{m g}_{\\mathsf{N H}_{3}}\\mathsf{h}^{-1}\\mathsf{c m}^{-2}$ (at $-1.02\\lor$ versus $\\mathsf{A g}/\\mathsf{A g C l};$ and $0.92\\%$ (at $-0.96{\\mathrm{~V~}}$ versus $\\mathsf{A g}/\\mathsf{A g C l}\\backslash$ at $90^{\\circ}\\mathsf{C}$ , respectively.11 Despite these advances, high FE is usually obtained at the expense of a low $N H_{3}$ production rate. Therefore, designing selective and energy-efficient electrocatalysts is highly desirable to enable both high FE and $N H_{3}$ synthesis rate at low overpotentials. \n\nIsolated metal atoms that are dispersed on supports17 have attracted tremendous interest because of the homogeneity of the catalytically active sites, the low-coordination environment of metal atoms, and maximum metal utilization efficiency. These important features endow single-atom catalysts with high catalytic activity, stability, and selectivity for a range of electrochemical processes.18–20 Nevertheless, single-atom electrocatalysis in $N H_{3}$ synthesis has yet to be reported. Here, we show that single Ru sites encapsulated in N-doped porous carbon via a coordination-assisted strategy enable highly efficient electrochemical ${\\sf N}_{2}$ fixation. Control of coordinated ligands permits ready tuning of Ru sizes and catalytic properties of $\\mathsf{R}\\mathsf{u}$ in NRR. This catalyst provided a very high $N H_{3}$ yield rate of $3.665\\:\\mathrm{\\mg_{NH_{3}}h^{-1}}\\mathsf{m g}_{\\mathsf{R u}}^{-1}$ at $-0.21\\mathrm{~\\vee~}$ versus reversible hydrogen electrode (RHE), which is over two times higher than that of the best reported catalyst $\\left({\\sf A u}/{\\sf T i O}_{2}\\right)$ .9 Equally interestingly, addition of $Z r O_{2}$ was found to effectively inhibit the competitive HER. A remarkably large $N H_{3}$ FE of approximately $21\\%$ was attained even at a low applied potential of $-0.11\\vee,$ outperforming other metal-based catalysts. All potentials reported in this work are with respect to the RHE scale unless specified otherwise. \n\n# RESULTS AND DISCUSSION \n\nUiO-66 $({\\cal Z}r_{6}{\\cal O}_{4}({\\cal O}\\mathsf{H})_{4}(\\mathsf{B}\\mathsf{D}{\\mathsf{C}})_{6}.$ ; BDC, 1,4-benzenedicarboxylate) confined with Ru ions was first synthesized simply by a hydrothermal method, which was subsequently annealed to yield ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ . Inductively coupled plasma-atomic emission spectrometry (ICP-AES) verified the existence of Ru in the resultant samples. The X-ray diffraction (XRD) patterns of these samples are given in Figure S1. Characteristic reflection peaks of $Z r O_{2}$ were observed in the resulting ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ . The average $Z r O_{2}$ sizes were estimated to be about $9\\mathsf{n m}$ from the (111) reflection utilizing Scherrer’s equation. No diffraction peaks of Ru were identified, probably due to its amorphous structure and/or too low loading content (0.1 wt $\\%$ determined by ICP-AES). This also ruled out the presence of large Ru particles or aggregates. \n\nThe formation of Ru was also confirmed by the presence of a Ru 3d X-ray photoelectron spectroscopy (XPS) signal, which was obscured by the C 1s signal at $284.8\\mathsf{e V}$ (Figure 1A). The deconvoluted spectrum presents two doublets, denoting a main valence state of ${\\mathsf{R}}{\\mathsf{u}}^{3+}$ together with ${\\mathsf{R}}{\\mathsf{u}}^{0}$ . The peaks at 284.8, 285.9, and $288.5\\ \\mathrm{eV}$ correspond to $C{\\mathrm{-}}C$ bonds in aromatic networks, C–O bonds in phenols or ethers, and $C=0$ groups in ketones and quinones, respectively. The Zr 3d core-level spectrum (Figure 1B) shows a Zr $3{\\mathrm{d}}_{5/2}$ peak at $182.1~\\mathrm{eV},$ which is lower than the value of $Z r O_{2}$ ( $182.8~\\mathrm{eV})$ reported in the literature.21 This may suggest the generation of O vacancies on the surface of $Z r O_{2}$ as a result of annealing in ${\\sf N}_{2}$ . Pyridinic N and pyrrolic N were observed to be predominant N species in the ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ (Figure S2). These two N moieties facilitated the yield and stabilization of Ru atoms by coordination with the metal.17 N doping also introduced defect sites in the carbon lattice, thus affecting catalytic properties, which is discussed later on in the NRR section. \n\n![](images/a8ef49d378042364aa54be92f64696874bd43fb8bff9a708241c2e99d8d43191.jpg) \nFigure 1. Surface Characterization by XPS (A) C 1s and Ru 3d XPS spectra of ${\\mathsf{R u@N C}}$ . (B) Zr 3d XPS spectrum of ${\\sf R u@Z r O_{2}/N C}$ . \n\nScanning electron microscopy (SEM) (Figures 2A and S3) and aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADFSTEM) images (Figures 2B and 2D) showed octahedron morphology of the ${\\sf R u@Z r O_{2}/N C}.$ , similar to the shape of $V_{1}0-66\\mathsf{-N H}_{2}$ . In situ energy-dispersive X-ray spectroscopy (EDS) together with elemental mapping (Figure 2C) and HAADFSTEM observations confirmed the distribution of single Ru sites on the carbon support. Brighter spots in the HAADF-STEM images indicate single Ru atoms because of the atomic number contrast nature of the technique and the higher atomic number of Ru than of carbon (Figures 2E–2G). For clarity, some Ru atoms are annotated with red circles (Figure 2F). The sizes of about $88\\%$ of Ru objects fell in the range of $0.1\\mathrm{-}0.2~\\mathsf{n m}$ (inset in Figure 2F), corresponding to single atoms. The formation of such atomically dispersed Ru is most likely due to the stabilization of ${\\mathsf{R u C l}}_{3}$ precursor by the uncoordinated $-N H_{2}$ groups and further inhibition of Ru assembling during pyrolysis. By contrast, Ru clusters were obtained originating from aggregation of Ru atoms at high temperature in the absence of $-N H_{2}$ groups (Figure S4). This suggests the importance of $-N H_{2}$ groups in the yield of Ru single sites during the annealing process. In addition, some Ru atoms dispersed on $Z r O_{2}$ were also visualized by virtue of the higher atomic number of Ru than Zr and O (Figure 2H). \n\nThe ${\\sf N}_{2}$ reduction activities of all catalysts were tested with a carbon paper working electrode in a gas-tight H-type cell separated by a Nafion 117 membrane. Figure S7A shows the linear sweep voltammetries of ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ in $0.1~\\mathsf{M}$ aqueous HCl solution saturated with Ar or ${\\sf N}_{2}$ . The NRR took place at potentials $>-0.01$ V with an overpotential of less than 0.07 V (given the equilibrium thermodynamic potential for ${\\sf N}_{2}$ reduction to $N H_{3}$ is $0.06~\\mathsf{V}$ versus normal hydrogen electrode under our experimental conditions $[298\\ \\mathsf{K}$ and 1 atm]) under ${\\sf N}_{2}$ saturation when ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ was used as the cathodic catalyst. Such low-onset overpotential is similar to that of Au subnanoclusters on $\\bar{\\mathsf{T i O}}_{2}$ but significantly lower than the value attained on N-doped porous carbon catalyst (\u00010.499 V).22 Under reaction conditions, only $N H_{3}$ was detected by the indophenol blue method. No by-product $N_{2}H_{4}$ was detectable by the Watt and Chrisp method, suggesting good selectivity of ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ for NRR. \n\nTo confirm the origin of the $N H_{3}$ produced, we performed several control experiments. As shown in Figure 3A, very little or no $N H_{3}$ was detected by the indophenol blue method in Ar-saturated electrolyte, with a carbon paper electrode without ${\\sf R u@Z r O_{2}/N C},$ , or at an open circuit as a control. This suggests that the $N H_{3}$ was generated from electroreduction of dissolved ${\\sf N}_{2}$ by ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ catalyst. We further conducted isotopic labeling measurements using $^{15}{\\mathsf N}_{2}$ -enriched gas $98\\%$ \n\n# Chem \n\n![](images/4931ab08d6b1cadf3d4af90688f0c2f617d3bf8fc1f9feba292b3e592fdb7a61.jpg) \nFigure 2. Morphology and Structure Characterization of Ru@ZrO2/NC \n\n(A) SEM image. \n(B) Low-magnification HAADF-STEM image along with EDS maps of C, N, Ru, Zr, and O. \n(C) EDX spectrum of the region shown in image (B). \n(D and E) Low-magnification (D) and high-magnification (E) HAADF-STEM images. \n(F) Enlarged HAADF-STEM image of the region encased by the dotted square in (E). The inset shows the size-distribution histogram of Ru objects. \n(G) The image was subjected to a bandpass filter to remove the variations in intensity due to the differing carbon support thicknesses, allowing for clearer distinguishing of the Ru single atoms. \n(H) HAADF-STEM image after tuning color contrast. \n\n$^{15}\\mathsf{N}\\equiv{}^{15}\\mathsf{N}\\rangle$ ) as the feeding gas to examine the actual N source of the $N H_{3}$ produced in our experimental conditions. The corresponding reaction solution was analyzed by $^1\\mathsf{H}$ NMR, and the result is shown in Figure S8. It can be clearly seen that the $^1\\mathsf{H}$ NMR spectrum of the product has a pair of sharp peaks in the region near $6.92\\mathrm{-}7.07~\\mathsf{p p m}$ , which correspond well to the calibration curve of $^{15}\\mathsf{N H}_{4}\\mathsf{C l}$ with a distinguishable chemical shift. In contrast, there is only a very weak triple signal of $^{14}{\\mathsf{N}}{\\mathsf{H}}_{4}^{+}$ in the spectrum. Considering the purity of isotopic gas, here the absolute dominant $^{15}{\\mathsf{N H}}_{4}^{+}$ doublets confirm that the $\\mathsf{N}$ in $N H_{3}$ originates from the gaseous ${\\sf N}_{2}$ supplied. \n\nInterestingly, as shown in Figure 3B, the ${\\sf R u}/{\\sf N C}$ catalyst displayed an $N H_{3}$ yield rate of up to $3.665\\mathsf{m g}_{\\mathsf{N H}_{3}}\\mathsf{h}^{-1}\\mathsf{m g}_{\\mathsf{R u}}^{-1}$ at $-0.21\\vee.$ , over two times higher than that of the best catalyst $(\\mathsf{A u}/\\mathsf{T i O}_{2}$ ; $N H_{3}$ yield rate, $\\approx1.39\\:\\mathrm{mg}_{\\mathsf{N H}_{3}}\\mathsf{h}^{-1}\\mathsf{m g}_{\\mathsf{A u}}^{-1})$ reported so far,9 whereas the loading of Ru on electrode was ten times lower than that of Au used. The $N H_{3}$ FE of ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ at 0.21 V was about $15\\%$ , significantly surpassing those of $\\mathsf{A u/T i O}_{2}$ $(\\approx8.1\\%),^{9}\\mathsf{A u@C e O_{x}/r G O_{\\theta}(\\approx10.1\\%)_{\\theta}},^{7}$ and Au nanorods $(\\approx4.0\\%)$ .8 The $N H_{3}$ FE was nearly zero for both commercial $5\\%$ Ru/C and $N a B H_{4}$ reduced Ru on few-laye graphene (FLG). This could be due to the larger sizes of formed Ru (over $3\\mathsf{n m}$ in either case), thus leading to predominant occurrence of HER; when the sizes of Ru are reduced to an atomic level, the HER could be suppressed, and $N H_{3}$ formation could be promoted. Indeed, the $N H_{3}$ yield rates of both ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ and ${\\mathsf{R u@N C}}$ catalysts were substantially higher than those of $\\mathsf{R u@Z r O_{2}/C}$ and ${\\mathsf{R u@C}},$ in which no amino groups were used during synthesis (Figure 3B), highlighting the (B) The FE and yield rate of $N H_{3}$ over $5\\%$ ${\\mathsf{R u@C}}.$ , ${\\sf R u@F L G}$ $(N a B H_{4})$ ), $R\\cup\\bigoplus_{\\cdot}Z_{\\Gamma}\\bigcirc_{2}/\\mathsf{N C}$ , ${\\mathsf{R u@N C}}$ (removal of $Z\\mathsf{r}{\\mathsf{O}}_{2})$ , ${\\sf R u@Z r O_{2}/C}$ (in the absence of $-N H_{2}$ groups), and ${\\mathsf{R u@C}}$ (in the absence of $-N H_{2}$ groups and removal of $Z\\mathsf{r}{\\mathsf{O}}_{2})$ . The results of Au catalysts7–9 reported earlier are also provided for comparison. The $N H_{3}$ yield rates were normalized by dividing corresponding noble metal mass. \n\n![](images/b54507b5e7393f1c6a3067debf1bbb86d0a2f6c5d7fbe1300b1b306436620db5.jpg) \nFigure 3. Electrochemical Nitrogen Reduction Activities (A) UV-visible absorption spectra of the electrolytes after electrolysis at $-0.21\\mathrm{~V~}$ for $2\\mathsf{h r}$ with Ar-saturated electrolyte (Ar gas), without $\\mathsf{R u@Z r O_{2}}/$ NC catalyst (carbon paper), or at an open circuit (open circuit). \n\n(C–E) The FEs (C), yield rates (D), and partial current densities (E) of $N H_{3}$ over ${\\mathsf{R u@N C}}$ , ${\\mathsf{R u@C}}$ , ${\\sf R u@Z r O_{2}/N C},$ , and $\\mathsf{R u@Z r O_{2}/C}$ at various applied potentials. The catalytic results of NC were also added in (C) and (E). \n(F) The long-term durability test at $-0.21\\mathrm{~V~}$ over $R\\cup\\bigoplus_{\\cdot}Z_{\\Gamma}\\bigcirc_{2}/\\mathsf{N C}$ at ${\\sim}10^{\\circ}\\mathsf C$ . \nDuring the $N H_{3}$ yield rate calculation in (B), (D), and (F), contributions of $Z r O_{2}/N C$ and $Z r O_{2}/C$ in ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ and ${\\sf R u@Z r O_{2}/C},$ , respectively, and NC in ${\\mathsf{R u@N C}}$ were subtracted. \n\nimportance of the small size of Ru in NRR. The lack of further work using Ru in NRR is likely due to the difficulty in obtaining a high yield of single Ru sites. \n\nWe explored the effect of $Z r O_{2}$ in the Ru catalysts on NRR. The $N H_{3}$ FEs, average $N H_{3}$ yield rates, and partial $N H_{3}$ current densities of ${\\mathsf{R u@N C}}$ , ${\\mathsf{R u@C}}$ , ${\\sf R u@Z r O_{2}/N C},$ and $\\mathsf{R u@Z r O_{2}/C}$ at potentials between $-0.01$ and $-0.31\\mathrm{~V~}$ are plotted in Figures 3C, 3D, and 3E, respectively. At potentials that are more negative than $-0.31\\ \\vee,$ , the $N H_{3}$ FEs decreased to near zero as a result of serious HER.23 NC alone was not active for NRR (Figures 3C, 3E, and S7B). $Z r O_{2}/C$ and $Z r O_{2}/N C$ exhibited low \n\n# Chem \n\n![](images/670ef2117fbb292d9658cfb6f34259e489f9dcea6ad07019df807b301279a141.jpg) \nFigure 4. Morphology and Structure Characterization of the Ru@ZrO /NC after Six Cycle Tests of NRR (A) Low-magnification HAADF-STEM image. (B–F) EDS maps of C (B), N (C), Ru (D), Zr (E), and $\\bigcirc$ (F) of the region shown in (A). (G) HAADF-STEM image showing the presence of single Ru sites annotated with yellow dotted circles. \n\n$N H_{3}$ FEs $<5\\%$ , whereas the addition of $Z r O_{2}$ remarkably improved the $N H_{3}$ FEs of Ru catalysts at all applied potentials without significantly affecting the $N H_{3}$ yield rate according to the total mass of electrode materials (Figure S7B). The $N H_{3}$ FEs of ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ and $\\mathsf{R u@Z r O_{2}/C}$ both increased concomitantly with the potential in the range of $-0.31$ to $-0.11\\mathrm{~V~}$ and reached a maximum as high as ${\\sim}21\\%$ at $-0.11\\mathrm{~V~}$ with an overpotential of $0.17\\mathrm{\\DeltaV}$ for ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ . As far as we are aware, this is the highest $N H_{3}$ FE reported so far for aqueous NRR at ambient conditions. This contrasts with the maximum $N H_{3}$ FEs of less than $9\\%$ on ${\\sf R u}/{\\sf N C}$ and ${\\sf R u/C}$ in the absence of $Z r O_{2}$ at $-0.21\\vee$ . Likewise, the $N H_{3}$ partial current densities of $\\mathsf{R u@Z r O_{2}/}$ NC and $\\mathsf{R u@Z r O_{2}/C}$ , the former of which outperformed the latter, were higher than those of corresponding catalysts without $Z r O_{2}$ at various potentials (Figure 3E). The mass activities of the catalysts at the applied potentials followed a similar trend with their $N H_{3}$ partial current densities (Figure S7C), further confirming the significant role of $Z r O_{2}$ in probably suppressing HER during NRR. We believe that optimization of $Z r O_{2}$ loading would further facilitate the electroreduction of ${\\sf N}_{2}$ to produce $N H_{3}$ with both high yield and large efficiency. \n\nThe long-term performances of ${\\sf R u@Z r O_{2}/N C}$ were evaluated at a constant potential of $-0.21\\vee$ . The trend of current density curves against time displayed a very stable behavior over 60 hr (Figure S7D). We conducted XPS measurements on the electrode after the electrolysis. No evidence of Ag was identified on the electrode after the experiment. This ruled out the possibility that Ag leached out of the reference electrode and got deposited on the working electrode during this chronoamperometry experiment, thereby affecting electrochemical performance. Both $N H_{3}$ yield rate and FE exhibited almost no degradations after six consecutive ${\\sf N}_{2}$ reduction cycles (Figure S7E) or even $60~\\mathsf{h r}$ of continuous experimentation (Figure 3F), indicating the excellent stability of ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ for NRR. Experiments were also performed at $-0.21\\vee$ with ${\\sf N}_{2}$ flow rates in a range of $20{-}100\\mathsf{c m}^{3}\\mathsf{m i n}^{-1}$ . No significant effect was observed in either FE or yield rate of $N H_{3},$ suggesting that diffusion was unlikely a key step.11 HAADF-STEM images of the ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ after the recycling \n\n# Chem \n\ntests showed preservation of isolated single Ru sites without apparent aggregation or agglomeration (Figure 4), suggesting that they are beneficial for long-term durability of the catalyst. \n\nTo elucidate the cause of the enhanced catalytic activity and selectivity of $\\mathsf{R u@Z r O_{2}/}$ NC, we calculated the reaction free energies for NRR and HER by using density functional theory (DFT) calculations. On the basis of the experimental observation of a Ru single atom embedded at $Z r O_{2}$ and N-doped carbon (Figure 2), we considered single Ru sites supported on both $Z r O_{2}$ and N-doped carbon. For a Ru single atom at $Z\\mathsf{r O}_{2}.$ , three cases were modeled: a Ru single atom at stoichiometric $Z r O_{2}$ $(\\mathsf{R u@{Z r_{32}O_{64}}})$ , $Z\\boldsymbol{\\mathrm r}$ vacancy $(\\mathsf{R u@Z r_{31}O_{64}})$ , and at $\\bigcirc$ -vacancy sites in reduced $Z r O_{2}$ $(\\mathsf{R u@{Z r_{32}O_{63}}})$ (Figures 5A and S9).24,25 We found that the stoichiometric $\\mathsf{R u@Z r_{32}O_{64}}$ and $\\mathsf{R u@Z r_{31}O_{64}}$ with $Z r$ vacancy showed too high of a reaction free energy $(>1\\mathsf{e V})$ for the first electroreduction step to form $\\star_{\\mathsf{N N H}}$ , but $\\mathsf{R u@Z r_{32}O_{63}}$ with $\\bigcirc$ vacancy showed a superior NRR catalytic activity. \n\nThe Ru single atoms in $Z r O_{2}$ were observed in this study as well as a previous study via AC-HAADF-STEM;26 however, the chemical environment (such as coordination number and coordinated atoms) of Ru atoms in $Z r O_{2}$ remains unclear. A previous theoretical study on a similar system also indicated that the $\\bigcirc$ vacancy in the $Z r O_{2}$ surface plays an important role in stabilizing the Ru single atom;24,25 the $\\bigcirc$ vacancy can bind the Ru single atom strongly and reduce the mobility of the anchored Ru single atom significantly, supporting the presence of $\\mathsf{R u@Z r_{32}O_{63}}$ . Thus, we expect that Ru single atoms tend to be anchored at the surface $\\bigcirc$ vacancy. On the basis of the calculated free energy and stability of different singleatom configurations considered, we focused here on the results for $\\mathsf{R u@Z r_{32}O_{63}}$ with $\\bigcirc$ vacancy. \n\nFor Ru single atom at N-doped carbon, we considered ${\\mathsf{R u@N}}_{x}{\\mathsf{C}}_{y}$ moieties $(0\\leq x\\leq4$ and $0\\leq y\\leq4;$ ) embedded in graphene, where $x$ and y represent the number of anchoring nitrogen and carbon atoms, respectively, to the Ru single atom (Figure S10). ${\\mathsf{R u@N C}}_{2}$ was found to show the lowest free energy for NRR among the considered ${\\mathsf{R u@N}}_{x}{\\mathsf{C}}_{y},$ and hence we mainly discuss the results for ${\\mathsf{R u@N C}}_{2}$ . We note that the configuration of ${\\mathsf{R u@N C}}_{2}$ is also well matched with the experimental characterizations of ${\\sf R u}/{\\sf N C}$ in a previous study, which revealed that the Ru atom in ${\\sf R u}/{\\sf N C}$ has a coordination number of three by extended X-ray absorption fine structure analyses.17 The optimized geometries for all reaction intermediates for NRR and HER are shown in Figures S11 and S12. All of these computational results for ${\\mathsf{R u@Z r O}}_{2}$ and ${\\mathsf{R u@N C}}$ are then compared with NRR and HER activities of the bulk $Z r O_{2}$ and Ru (0001) surfaces, as well as ${\\sf R u@C_{\\times}}$ without N doping. These comparisons are summarized in Figure 5A and Table S2. \n\nBoth Ru single-atom catalysts (SACs), $\\mathsf{R u@Z r_{32}O_{63}}$ and $\\mathsf{R u/N C}_{2}$ , showed improvements in catalytic activity compared with that of Ru (0001) (Figure 5A) in terms of free-energy change at the potential-determining step (PDS) for NRR: $\\mathsf{R u@Z r_{32}O_{63}}$ $(0.55~\\mathrm{eV})$ and $\\mathsf{R u/N C}_{2}$ $(0.42\\ \\mathsf{e V})$ versus Ru (0001) $(0.61~\\mathrm{eV})$ . In particular, both Ru SACs, $\\mathsf{R u@Z r_{32}O_{63}}$ and ${\\sf R u}/{\\sf N C}_{2},$ reduced the free energy for $^{\\star}\\mathsf{N N H}$ formation $({}^{\\star}\\mathsf{N}_{2}+(\\mathsf{H}^{+}+\\mathsf{e}^{-})\\rightarrow{}^{\\star}\\mathsf{N}\\mathsf{N}\\mathsf{H})$ compared with that of Ru (0001) by 0.65 and $0.26\\ \\mathrm{eV}$ , respectively (Figures 5C, 5D, and S13), which is usually the most energy-consuming step in electrochemical NRR on most metal surfaces, hindering the initiation of the NRR process.4,27 The ${\\sf N}_{2}$ adsorption was also favorable on both Ru SACs $(\\Delta G[^{\\star}\\mathsf{N}_{2}]$ was $-0.60$ and $-0.10\\ \\mathrm{eV}$ for $\\textcircled{\\sc2}Z r_{32}\\bigcirc_{63}$ and ${\\sf R u}/{\\sf N C}_{2}.$ , respectively) to initiate the activation process on both Ru SACs. \n\n![](images/c4600fe21b38b98c2bdb769ded51640c1af4b38afebeb9f0b457dd8263f40067.jpg) \nFigure 5. Calculation Models and Free-Energy Diagrams for NRR \n\n(A) $\\Delta G_{\\mathsf{P D S}}$ for NRR on various reaction sites. \n(B) Calculation models for $\\mathsf{R u@Z r_{32}O_{63}}$ and $\\mathsf{R u}/\\mathsf{N C}_{2}$ . \n(C) Free-energy diagram for NRR on $\\mathsf{R u@Z r_{32}O_{63}}$ . \n(D) Free-energy diagram for NRR on ${\\mathsf{R u@N C}}_{2}$ . \nThe horizontal dashed line in (A) represents the $\\Delta G_{\\mathsf{P D S}}$ of Ru (0001) $(0.61\\ \\mathrm{eV})$ . Stoichiometric $Z r O_{2}$ and $Z r O_{2}$ with $\\bigcirc$ vacancy are modeled with $Z r_{32}\\bigcirc_{64}$ and $Z r_{32}{\\bigcirc}_{63},$ respectively. The asterisk (\\*) represents a surface site for adsorption. Black and red lines indicate the free-energy change for NRR and hydrogen adsorption, respectively. The free-energy change at the PDS is denoted in the figure. After the first desorption of $N H_{3},$ it is omitted for clarity. \n\nOn the other hand, support materials themselves $(\\mathsf{Z r O}_{2}$ or $Z r O_{2}$ with $\\bigcirc$ vacancy) do not activate ${\\sf N}_{2}$ sufficiently. The free-energy change for ${\\sf N}_{2}$ adsorption on the bare $Z r O_{2}$ surface $(Z r_{32}{\\bigcirc}_{64})$ was unfavorable $(+0.21~\\mathrm{eV})$ , and that for $\\star\\mathsf{N N H}$ formation was prohibitively high $(2.15~\\mathrm{eV})$ (Figure 5A). Similarly, the $Z r O_{2}$ with $\\bigcirc$ vacancy $(Z r_{32}{\\cal O}_{63})$ , suggested by XPS analyses, itself was also inactive for NRR $(\\Delta G_{\\mathsf{P D S}}=$ $1.61~\\mathrm{{\\eV}})$ . When used as a support material for single Ru atoms, however, $Z r_{32}\\mathrm{O}_{63}$ enhanced the catalytic activity of Ru compared with that of Ru (0001) as described above, and thus we can conclude that $\\bigcirc$ -vacancy sites in $Z r O_{2}$ promote the catalytic activity of Ru single atoms in the $N H_{3}$ production but do not themselves act as a catalyst. We also compared ${\\mathsf{R u@N C}}_{2}$ with ${\\sf R u@C_{3}}$ and $\\mathsf{R u@C_{4}}$ (Figures 5A and S14 and Table S2), which do not involve nitrogen, to investigate the role of N for improved catalytic activity. The $\\Delta G_{\\mathsf{P D S}}$ of ${\\mathsf{R u@N C}}_{2}$ $(0.42~\\mathrm{eV})$ was significantly lower than that of ${\\sf R u@C_{3}}$ $(1.28~\\mathrm{eV})$ and ${\\sf R u@C_{4}}$ $\\dag1.13\\mathrm{~eV}\\dag$ . Thus, the unsaturated $-N H_{2}$ groups not only inhibit aggregation of a Ru single atom during pyrolysis17 but also considerably increase the catalytic activity of Ru. \n\nWith negative potentials, H adsorption $(\\mathsf{H}^{+}+\\mathsf{e}^{-}\\to{}^{\\star}\\mathsf{H})$ will be thermodynamically more favored than the ${\\sf N}_{2}$ adsorption, and most metal surfaces will be covered by $^{\\star}\\mathsf{H}$ .5 Under these usual experimental conditions, the adsorbed $\\star_{\\mathsf{H}}$ not only undergoes unwanted HER processes, but, perhaps more importantly, also blocks the active sites used to initiate NRR, significantly decreasing the FE of NRR. Therefore, suppressing this initial $^{\\star}\\mathsf{H}$ adsorption has been considered important to improve FE and selectivity of NRR.28 Thus, we focused here also on the H adsorption free energetics rather than HER overpotentials. We indeed found that H adsorption was suppressed on both $\\mathsf{R u}$ SACs with smaller DG $(^{\\star}\\mathsf{H})$ : $\\mathsf{R u@Z r_{32}O_{63}}$ (\u00010.20 eV) and $\\mathsf{R u@N C}_{2}(-0.42\\:\\mathrm{eV})$ versus Ru (0001) $(-0.47\\mathrm{eV})$ (Figures 5C, 5D, and S13). Especially for ${\\sf R u@Z r_{32}O_{63}},$ the H adsorption was suppressed most significantly, consistent with the aforementioned selectivity experiments. Comparing $\\Delta G(^{\\star}\\mathsf{N}_{2})$ and $\\Delta G(^{\\star}\\mathsf{H})$ might give an approximate idea of the adsorption selectivity. The $\\Delta_{\\Delta G}\\left(\\mathbf{\\hat{\\sigma}}\\mathbf{\\times}\\mathbf{\\mapsto}\\mathbf{\\vec{\\sigma}}\\mathbf{N}_{2}\\right)=\\Delta G\\left(\\mathbf{\\hat{\\sigma}}\\mathbf{\\times}\\mathbf{\\vec{N}}_{2}\\right)$ $-\\Delta G(^{\\star}\\mathsf{H})$ for $\\mathsf{R u@Z r_{32}O_{63}(-0.40\\mathsf{e V})}$ was much smaller than those for $\\mathsf{R u}/\\mathsf{N C}_{2}\\left(+0.32\\right.$ eV) and Ru (0001) $(+0.11\\ \\mathrm{eV})$ , suggesting that ${\\sf N}_{2}$ adsorption would be less hindered by the H adsorption for $\\mathsf{R u@Z r_{32}O_{63}}$ at low overpotential regions. \n\nIn Figure 3D, the $N H_{3}$ yield rate is most promising for samples that contain both Ru and N-doped carbon sites, namely, for ${\\mathsf{R u@N C}}$ and ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ . In our DFT calculations, ${\\mathsf{R u@N C}}_{2}$ showed the most improved catalytic activity, indicating that ${\\mathsf{R u@N C}}_{2}$ sites are likely the origin of the enhanced $N H_{3}$ yield rate of ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ and ${\\mathsf{R u@N C}}$ . On the other hand, Figure 3C shows that FE depends critically on the presence or absence of $Z\\r\\mathrm{r}O_{2}$ , suggesting that the NRR/HER selectivity for ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ is enhanced by $R\\cup\\ @Z\\mathsf{r}\\mathsf{O}_{2}$ or $Z r O_{2}$ itself. Our DFT calculations indeed suggest that $\\star_{\\mathsf{N}_{2}}/\\star_{\\mathsf{H}}$ selectivity is significantly improved at the $\\mathsf{R u@Z r_{32}O_{63}}$ sites and thus plays an important role in the higher FE of ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ than of ${\\mathsf{R u@N C}}$ . Therefore, in a sense, ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ seems to show a bifunctional capability in which ${\\mathsf{R u@N C}}$ is mainly responsible for improved NRR and $R\\cup\\ @Z\\mathsf{r}\\bigcirc_{2}$ helps to suppress HER. \n\n# Conclusion \n\nIn summary, we have demonstrated that single Ru sites supported on N-doped porous C are highly active for ambient electroreduction of aqueous ${\\sf N}_{2}$ to $N H_{3}$ . Such catalyst afforded a high and stable $N H_{3}$ production rate of 3.665 $\\mathsf{m g}_{\\mathsf{N H}_{3}}\\mathsf{h}^{-1}\\mathsf{m g}_{\\mathsf{R u}}^{-1}$ at $-0.21\\mathrm{~V~}$ . A remarkably large $N H_{3}$ FE of up to $21\\%$ was obtained with the addition of $Z r O_{2}$ at an overpotential as low as $0.17\\ \\vee.$ . This outstanding activity correlates with the small size of Ru and the promotion effect of $Z r O_{2}$ (to suppress HER). DFT calculations suggested that the ${\\sf N}_{2}$ reduction reaction mainly occurred at Ru sites with $\\bigcirc$ vacancies, and their high catalytic performances can be attributed to the stabilization of \\*NNH (low overpotential), dramatic destabilization of $^{\\star}\\mathsf{H}$ (high NRR/HER selectivity), and enhanced ${\\sf N}_{2}$ adsorption (to initiate the NRR process). We believe that the development of SACs opens a potentially alternative avenue for efficient $N H_{3}$ synthesis, which deserves further research in ${\\sf N}_{2}$ fixation. \n\n# EXPERIMENTAL PROCEDURES \n\nUiO-66 $(Z\\r_{6}{\\bigcirc}_{4}({\\mathsf{O H}})_{4}({\\mathsf{B D C}})_{6}$ ; BDC, 1,4-benzenedicarboxylate) confined with Ru ions was first synthesized by hydrothermal treatment of a precursor solution containing glacial acetic acid, $\\mathsf{Z r C l_{4}}.$ , ${\\mathsf{H}}_{2}{\\mathsf{B D C}}$ , and ${\\mathsf{R u C l}}_{3}$ in dimethylformamide, followed by washing and annealing to yield ${\\mathsf{R u@Z r O}}_{2}/{\\mathsf{N C}}$ . \n\nXPS experiments were carried out with a Thermo Scientific ESCALAB 250Xi instrument. The instrument was equipped with an electron flood and scanning ion gun. All spectra were calibrated to the C 1s binding energy at $284.8~\\mathrm{eV}$ . XRD was performed with a D/MAX\u0001RC diffractometer operated at $30\\mathsf{k V}$ and $100~\\mathrm{{mA}}$ with $\\mathsf{C u K}\\alpha$ radiation. SEM was carried out with a field emission microscope (FEI Quanta 600 FEG) operated at $20\\upboldsymbol{\\upkappa}\\upnu$ . HAADF-STEM was conducted with a JEOL ARM200 microscope with a $200~\\mathsf{k V}$ accelerating voltage. STEM samples were prepared by depositing a droplet of suspension onto a Cu grid coated with a lacey carbon film. \n\nThe electrochemical measurements were tested in an H-shaped electrochemical cell system with a Nafion 117 membrane to separate the working and counter electrode \n\n# Chem \n\ncompartments. A Toray carbon fiber paper measuring $1\\times1$ cm was used as the working electrode. Pt wire and $\\mathsf{A g}/\\mathsf{A g C l}$ electrodes were used as the counter electrode and reference electrode, respectively. The potentials were controlled by an electrochemical working station (CHI 760E; Shanghai CH Instruments, China). All potentials in this study were converted to the RHE reference scale. \n\nThe isotope labeling test was carried out in $^{15}{\\mathsf N}_{2}$ saturated diluted hydrochloric acid electrolyte. \n\nAll other experimental and setup details, as well as DFT calculations, are provided in the Supplemental Experimental Procedures. \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information includes Supplemental Experimental Procedures, 14 figures, and 2 tables and can be found with this article online at https://doi.org/10. 1016/j.chempr.2018.10.007. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the State Key Laboratory of Organic–Inorganic Composites (oic-201503005), the Fundamental Research Funds for the Central Universities (buctrc201525), the Beijing National Laboratory for Molecular Sciences (BNLMS20160133), the Key Laboratory of Materials for High-Power Laser (Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences), and the State Key Laboratory of Separation Membranes and Membrane Processes (Tianjin Polytechnic University, M2-201704). Y.J. acknowledges support through the National Research Foundation of Korea from the Korean Government (2016M3D1A1021147 and 2017R1A2B3010176). A.W.R. acknowledges Engineering and Physical Sciences Research Council EP/K040375/1, the South of England Analytical Electron Microscope. \n\n# AUTHOR CONTRIBUTIONS \n\nConceptualization, Z.S.; Methodology, Z.S., H.T., C.C., and Y.J.; Investigation, H.T., C.C., L.-X.D., Z.H., M.J., Q.F., S.H., and A.W.R.; Writing – Original Draft, H.T. and Z.S.; Writing – Review & Editing, Z.S., Y.J., and H.W.; Funding Acquisition, Z.S. and Y.J.; Resources, Z.J., Y.G., and S.L.; Supervision, Z.S. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: April 11, 2018 \nRevised: May 20, 2018 \nAccepted: October 14, 2018 \nPublished: November 8, 2018 \n\n# REFERENCES AND NOTES \n\n1. Honkala, K., Hellman, A., Remediakis, I.N., Logadottir, A., Carlsson, A., Dahl, S., Christensen, C.H., and Norskov, J.K. (2005). Ammonia synthesis from first-principles calculations. Science 307, 555–558. 2. Li, H., Shang, J., Ai, Z.H., and Zhang, L.Z. (2015). Efficient visible light nitrogen fixation with BiOBr nanosheets of oxygen vacancies on the exposed {001} facets. J. Am. Chem. Soc. 137, 6393–6399. \n\n3. Pool, J.A., Lobkovsky, E., and Chirik, P.J. (2004). Hydrogenation and cleavage of dinitrogen to ammonia with a zirconium complex. Nature 427, 527–530. \n4. Montoya, J.H., Tsai, C., Vojvodic, A., and Norskov, J.K. (2015). The challenge of electrochemical ammonia synthesis: a new perspective on the role of nitrogen scaling relations. ChemSusChem 8, 2180– 2186. \n5. Singh, A.R., Rohr, B.A., Schwalbe, J.A., Cargnello, M., Chan, K., Jaramillo, T.F. Chorkendorff, I., and Norskov, J.K. (2017). Electrochemical ammonia synthesis—the selectivity challenge. ACS Catal. 7, 706–709. \n6. Yang, D.S., Chen, T., and Wang, Z.J. (2017). Electrochemical reduction of aqueous nitrogen $(\\mathsf{N}_{2})$ at a low overpotential on (110)- oriented Mo nanofilm. J. Mater. Chem. A 5, 18967–18971. \n7. Li, S.J., Bao, D., Shi, M.M., Wulan, B.R., Yan, J.M., and Jiang, Q. (2017). Amorphizing of Au nanoparticles by $\\mathsf{C e O}_{\\times}$ –RGO hybrid support towards highly efficient electrocatalyst for ${\\sf N}_{2}$ reduction under ambient conditions. Adv. Mater. 29, https://doi.org/10.1002/adma. 201700001. \n8. Bao, D., Meng, F.L., Zhong, H.X., Shi, M.M., Zhang, Y., Yan, J.M., Jiang, Q., and Zhang, X.B. (2017). Electrochemical reduction of ${\\sf N}_{2}$ under ambient conditions for artificial ${\\sf N}_{2}$ fixation and renewable energy storage using $N_{2}/N H_{3}$ cycle. Adv. Mater. 29, https://doi.org/10.1002/adma. 201604799. \n9. Shi, M.M., Bao, D., Wulan, B.R., Li, Y.H., Zhang, Y.F., Yan, J.M., and Jiang, Q. (2017). Au subnanoclusters on $\\bar{\\mathsf{T i O}}_{2}$ toward highly efficient and selective electrocatalyst for ${\\sf N}_{2}$ conversion to $N H_{3}$ at ambient conditions. Adv. Mater. 29, https://doi.org/10.1002/adma.201606550. \n10. Murakami, T., Nohira, T., Goto, T., Ogata, Y.H., and Ito, Y. (2005). Electrolytic ammonia synthesis from water and nitrogen gas in molten salt under atmospheric pressure. Electrochim. Acta 50, 5423–5426. \n11. Kordali, $\\mathsf{V}_{\\cdot,\\prime}$ Kyriacou, G., and Lambrou, C. (2000). Electrochemical synthesis of ammonia at atmospheric pressure and low temperature in a solid polymer electrolyte cell. Chem. Commun. 17, 1673–1674. \n12. Hiang, K.L., Lee, Y.H., Liu, C., Phang, I.Y., Han, X.M., Tsung, C.K., and Ling, X.Y. (2018). Favoring the unfavored: selective electrochemical nitrogen fixation using a reticular chemistry approach. Sci. Adv. 4, eaar3208. \n13. Lv, C.D., Chen, G., Yu, D., Sun, J.X., Zhou, Y.S., and Yu, G.H. (2018). An amorphous noblemetal-free electrocatalyst enables $N_{2}$ fixation under ambient conditions. Angew. Chem. Int. Ed. 57, 6073–6076. \n14. Liu, H.M., Han, S.H., Zhao, Y., Zhu, Y.Y., Tian, X.L., Zeng, J.H., Jiang, J.X., Xia, B.Y., and Chen, Y. (2018). Surfactant-free atomically ultrathin rhodium nanosheet nanoassemblies for efficient nitrogen electroreduction. J. Mater. Chem. A 6, 3211–3217. \n15. Chen, S.M., Perathoner, S., Ampelli, C. Mebrahtu, C., Su, D.S., and Centi, G. (2017). Electrocatalytic synthesis of ammonia at room temperature and atmospheric pressure from water and nitrogen on a carbon-nanotubebased electrocatalyst. Angew. Chem. Int. Ed. 56, 2699–2703. \n16. Back, S., and Jung, Y.S. (2016). On the mechanism of electrochemical ammonia synthesis on the Ru catalyst. Phys. Chem. Chem. Phys. 18, 9161–9166. \n17. Wang, X., Chen, W.X., Zhang, L., Yao, T., Liu, W., Lin, Y., Ju, H.X., Dong, J.C., Zheng, L.R., Yan, W.S., et al. (2017). Uncoordinated amine groups of metal-organic frameworks to anchor single Ru sites as chemoselective catalysts toward the hydrogenation of quinoline. J. Am. Chem. Soc. 139, 9419–9422. \n18. Zhu, C.Z., Shi, Q.R., Du, D., and Lin, Y.H. (2017). Single-atom electrocatalysts. Angew. Chem. Int. Ed. 56, 13944–13960. \n19. Fan, L.L., Liu, P.F., Yan, X.C., Gu, L., Yang, Z.Z., Yang, H.G., Qiu, S.L., and Yao, X.D. (2016). Atomically isolated nickel species anchored on graphitized carbon for efficient hydrogen evolution electrocatalysis. Nat. Commun. 7, 10667. \n20. Zhang, L.Z., Jia, Y., Gao, G.P., Yan, X.C., Chen, N., Chen, J., Soo, M.T., Wood, B., Yang, D.J., Du, A.J., and Yao, X.D. (2017). Graphene defects trap atomic Ni species for hydrogen and oxygen evolution reactions. Chem 4, 194–195. \n21. Sun, Z.Y., Zhang, X.R., Na, N., Liu, Z.M., Han, B.X., and An, G.M. (2006). Synthesis of ZrO2- carbon nanotube composites and their application as chemiluminescent sensor material for ethanol. J. Phys. Chem. B 110, 13410–13414. \n22. Liu, Y.M., Quan, X., Fan, X.F., Chen, S., Yu, H.T., Zhao, H.M., Zhang, Y.B., and Zhao, J.J. (2018). Facile ammonia synthesis from electrocatalytic ${\\sf N}_{2}$ reduction under ambient conditions on N-doped porous carbon. ACS Catal. 8, 1186– 1191. \n23. Cherevko, S., Geiger, S., Kasian, O., Kulyk, N., Grote, J.P., Savan, A., Shrestha, B.R., Merzlikin, S., Breitbach, B., Ludwig, A., and Mayrhofer, K.J.J. (2016). Oxygen and hydrogen evolution reactions on Ru, $\\mathsf{R u O}_{2},$ Ir, and $\\mathsf{I r O}_{2}$ thin film electrodes in acidic and alkaline electrolytes: a comparative study on activity and stability. Catal. Today 262, 170–180. \n24. Chen, H.Y.T., Tosoni, S., and Pacchioni, G. (2015). Adsorption of ruthenium atoms and clusters on anatase $\\bar{\\mathsf{T i O}}_{2}$ and tetragonal $Z r O_{2}$ (101) surfaces: a comparative DFT study. J. Phys. Chem. C 119, 10856–10868. \n25. Chen, H.Y.T., Tosoni, S., and Pacchioni, G. (2015). Hydrogen adsorption, dissociation, and spillover on Ru-10 clusters supported on anatase $\\bar{\\mathsf{T i O}}_{2}$ and tetragonal $Z r O_{2}$ (101) surfaces. ACS Catal. 5, 5486–5495. \n26. Cao, W.X., Luo, W.H., Ge, H.G., Su, Y., Wang, A.Q., and Zhang, T. (2017). UiO-66 derived ${\\sf R u}/Z r{\\sf O}_{2}@{\\sf C}$ as a highly stable catalyst for hydrogenation of levulinic acid to g-valerolactone. Green Chem. 19, 2201–2211. \n27. Skulason, E., Bligaard, T., Gudmundsdottir, S., Studt, F., Rossmeisl, J., Abild-Pedersen, F., Vegge, T., Jonsson, H., and Norskov, J.K. (2012). A theoretical evaluation of possible transition metal electro-catalysts for ${\\sf N}_{2}$ reduction. Phys. Chem. Chem. Phys. 14, 1235– 1245. \n28. Zhang, L.N., Sharada, S.M., Singh, A.R., Rohr, B.A., Su, Y.N., Qiao, L.J., and Nørskov, J.K. (2018). A theoretical study of the effect of a non-aqueous proton donor on electrochemical ammonia synthesis. Phys. Chem. Chem. Phys. 20, 4982–4989. " + }, + { + "id": "10.1038_s41467-019-09351-2", + "DOI": "10.1038/s41467-019-09351-2", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-09351-2", + "Relative Dir Path": "mds/10.1038_s41467-019-09351-2", + "Article Title": "Plant-inspired adhesive and tough hydrogel based on Ag-Lignin nulloparticles-triggered dynamic redox catechol chemistry", + "Authors": "Gan, DL; Xing, WS; Jiang, LL; Fang, J; Zhao, CC; Ren, FZ; Fang, LM; Wang, KF; Lu, X", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Adhesive hydrogels have gained popularity in biomedical applications, however, traditional adhesive hydrogels often exhibit short-term adhesiveness, poor mechanical properties and lack of antibacterial ability. Here, a plant-inspired adhesive hydrogel has been developed based on Ag-Lignin nulloparticles (NPs)triggered dynamic redox catechol chemistry. Ag-Lignin NPs construct the dynamic catechol redox system, which creates long-lasting reductive-oxidative environment inner hydrogel networks. This redox system, generating catechol groups continuously, endows the hydrogel with long-term and repeatable adhesiveness. Furthermore, Ag-Lignin NPs generate free radicals and trigger self-gelation of the hydrogel under ambient environment. This hydrogel presents high toughness for the existence of covalent and non-covalent interaction in the hydrogel networks. The hydrogel also possesses good cell affinity and high antibacterial activity due to the catechol groups and bactericidal ability of Ag-Lignin NPs. This study proposes a strategy to design tough and adhesive hydrogels based on dynamic plant catechol chemistry.", + "Times Cited, WoS Core": 835, + "Times Cited, All Databases": 867, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000462985600005", + "Markdown": "# Plant-inspired adhesive and tough hydrogel based on Ag-Lignin nanoparticles-triggered dynamic redox catechol chemistry \n\nDonglin Gan1, Wensi Xing1, Lili Jiang2, Ju Fang3, Cancan Zhao3, Fuzeng Ren3, Liming Fang4, Kefeng Wang5 & Xiong Lu 1 \n\nAdhesive hydrogels have gained popularity in biomedical applications, however, traditional adhesive hydrogels often exhibit short-term adhesiveness, poor mechanical properties and lack of antibacterial ability. Here, a plant-inspired adhesive hydrogel has been developed based on Ag-Lignin nanoparticles (NPs)triggered dynamic redox catechol chemistry. AgLignin NPs construct the dynamic catechol redox system, which creates long-lasting reductive-oxidative environment inner hydrogel networks. This redox system, generating catechol groups continuously, endows the hydrogel with long-term and repeatable adhesiveness. Furthermore, Ag-Lignin NPs generate free radicals and trigger self-gelation of the hydrogel under ambient environment. This hydrogel presents high toughness for the existence of covalent and non-covalent interaction in the hydrogel networks. The hydrogel also possesses good cell affinity and high antibacterial activity due to the catechol groups and bactericidal ability of Ag-Lignin NPs. This study proposes a strategy to design tough and adhesive hydrogels based on dynamic plant catechol chemistry. \n\nHryedpraoigr os hsaovfet dtirsaswuen, itntcelnutidoing skiidne1a, 2,mactaerrtilalsgef3o, atnhde hydrogels have limited their application in biomedical engineering. Various approaches have been used to prepare hydrogels with excellent mechanical properties, such as nanocomposite hydrogels5, topological hydrogels6, and double-network hydrogels7. However, many tough hydrogels possess poor cell or tissue adhesion, which preclude the integration of the hydrogel with human tissues. Recently, adhesive hydrogels have been designed based on different mechanism. For example, an adhesive hydrogel consisting of an adhesive surface and an energy dissipative matrix has been prepared8. Another adhesive hydrogel tackified by a nucleobase exhibits good adhesive properties because the nucleobase forms adhesive interactions with various materials9. Sundew-inspired adhesive hydrogels have been developed because the hydrogel has a well-patterned scaffold structure similar to the structure of sundew mucilage10. \n\nRecently, catechol chemistry has shed light on a method for preparing a hydrogel with good adhesiveness and super toughness11. Mussel-inspired adhesive hydrogels with polydopamine (PDA) are typical examples of catechol-chemistry-based adhesive hydrogels12–14. In these hydrogels, the catechol functional groups of PDA form covalent bonds/noncovalent bonds with different materials, and therefore these hydrogels exhibit good adhesion to various surfaces15. Nevertheless, pure PDA-functionalized hydrogels generally have poor mechanical properties16–18 and these adhesive hydrogels are not reusable19. This is because some of the catechol groups in the adhesive hydrogel are converted to quinone groups through oxidation. The catechol groups can form physical or chemical bonds with different surfaces and the quinone groups promote cohesion in the hydrogel. However, overoxidation of catechol groups cause loss of adhesiveness of the hydrogel20–22. Actually, mussel retains its long-term adhesion because a reductive protein is continuously secreted in mussel footprints to maintain a dynamic balance between the quinone and catechol groups, which allows the retention of long-term adhesion23. The adhesion properties of mussels inspired us to consider that controlling the oxidation degree of catechol groups is vital to maintaining the adhesive features of PDA-containing hydrogels. In our recent study, we controlled the oxidation process of the catechol groups and maintained the quantity of catechol groups in the hydrogel to obtain tough hydrogels with excellent repeatable and durable adhesiveness24, 25. \n\nMany plants have inherent adhesiveness because extracellular matrix of plants contain adhesive molecules, although plantbased adhesives are brittle and vulnerable26, 27. Lignin is the second-most abundant biopolymer originating from plants and has been widely used in biomedical engineering owing to its biocompatibility and environmental friendliness28–30. Lignin possesses multiple functional groups such as reductive phenolic hydroxyls and methoxy groups, which can serve as reducing and stabilizing agents31. Lignin has been used as a phenolic resin adhesive because of the reactive functional groups32, 33. It should be noted that the lignin-based adhesiveness in most previous reports are short-term and non-repeatable34, 35. The phenolic hydroxyls or methoxy groups on the lignin can be converted to redox-active quinone/hydroquinone, and consequently to semiquinone radicals by a comproportionation reaction36. The phenol or methoxy groups in lignin can reduce silver ions $(\\mathrm{Ag^{+}})$ to metallic silver nanoparticles $(\\mathrm{Ag\\NPs})^{37}$ , and these functional groups were oxidized to the corresponding quinone/hydroquinone in this process. Furthermore, the Ag NPs can form photogenerated electrons because of surface plasmon resonance38, 39. In the presence of the photogenerated electron, the quinone/hydroquinone groups in lignin were converted into catechol groups40, 41. The previous studies inspired us to propose a long-lasting adhesive hydrogel based on plant catechol chemistry. \n\nInspired by plants, a catechol-chemistry-based hydrogel with long-term adhesiveness, high toughness, and antibacterial ability is developed. The hydrogel is gelled from an aqueous precursor solution containing Ag-Lignin NPs, pectin, and acrylic acid (AA) under an ambient environment. Pectin and polyacrylic acid (PAA) forms an interpenetrating network with multi-crosslinking of covalent bonds and noncovalent bonds, which endows the hydrogel with excellent mechanical properties. The hydrogel displays long-term and repeatable adhesiveness because the AgLignin NPs continuously generate the catechol groups in the inner hydrogel network. The hydrogel is spontaneously polymerized under room temperature conditions because Ag-Lignin NPs interact with ammonium persulfate (APS) to produce a large amount of free radicals and initiate the polymerization of the hydrogel. Consequently, ultraviolet (UV) or thermal treatment, which is harmful to cells/tissues, is avoided. Because of the convenient direct gelation, this plant catechol-chemistry-based adhesive and tough hydrogel is suitable for surgical operation or other biomedical applications. \n\n# Results \n\nDesign rationale of the hydrogel. The Ag-Lignin NPs-PAApectin hydrogel was prepared in two steps, as shown in Fig. 1. First, Ag-Lignin NPs core-shell nanostructures were synthesized through a redox reaction between lignin and the $[\\mathrm{A}\\dot{\\bf g}(\\mathrm{NH}_{3})_{2}]^{+}$ complex (Supplementary Figure 1). During this process, the methoxyl and catechol groups of lignin are oxidized into quinone groups, as proved by cyclic voltammetry (CV) experiments, Fourier-transform infrared spectroscopy, and X-ray photoelectron spectroscopy (XPS) analysis (Supplementary Figure 5, 6, 7 and 8, Supplementary Table 4, and Supplementary Notes 7–9). Second, AA monomers and pectin were mixed with the AgLignin NPs suspension to form the Ag-Lignin NPs-PAA/pectin nanocomposite hydrogel owing to the Ag-Lignin NPs-triggered free-radical polymerization under an ambient environment (Fig. 1a). The Ag-Lignin NPs have the ability to realize the quinone-catechol reversible reaction, which endows the hydrogel with adhesiveness (Fig. 1b). \n\nIn this hydrogel, both the lignin and pectin originated from plants. Pectin is a heteropolysaccharide, and is the main component in the primary cell walls of plants. Pectin contains -OH and -COOH groups, which act as active sites for hydrogen bonds or ionic bonds. These pectin functional groups provide selective and strong bonding with certain substances42. Moreover, pectin improved the biocompatibility and also interpenetrated into the PAA network to make the hydrogel tougher and more flexible (Fig. 1c). Lignin formed Ag-Lignin NPs to create a redox environment inside the hydrogel network, which was the key factor for the preparation of such a multifunctional hydrogel. First, Ag-Lignin NPs can construct the dynamic catechol redox system inner hydrogel network, which mimics the long-lasting reductive/oxidative environment in mussel footprint and continuously generates catechol groups, and therefore endows the hydrogel with repeatable and long-lasting adhesion ability. As shown in Fig. 1b, the quinone-catechol reversible reaction of AgLignin NPs maintains a dynamic balance inside the aqueous hydrogel network with the assistance of free electrons from surface plasmon resonance of ${\\mathrm{Ag}}{\\mathrm{NPs}}$ (Supplementary Notes 10 and Supplementary Figure 9) and the $\\bar{\\mathrm{H^{+}}}$ from ionization of PAA, which continuously replenishes the catechol and quinone groups in the hydrogel. Second, $\\mathrm{Ag}$ -Lignin NPs generate free radicals that trigger self-gelation of the hydrogel. Therefore, the hydrogel was able to cure under an ambient environment. As shown in Supplementary Figure 1, under an alkaline environment, the functional groups, such as ${\\mathrm{-OCH}}_{3}$ or -OH on lignin, are oxidized by silver ions to quinone/semiquinone free radicals. After the addition of APS, large amounts of free radicals are continuously generated to initiate steady free-radical polymerization (Fig. 1a). Therefore, UV irradiation or thermal initiation with toxic auxiliary agents, such as tetramethylethylenediamine, was avoided during hydrogel gelation. Finally, the functional groups of Ag-Lignin NPs form noncovalent interaction with the PAA and pectin, and therefore the NPs work as nano-reinforcement to improve the mechanical properties of the hydrogel (Fig. 1c). \n\n![](images/a5e96c5d410bbcda7ffbef6ff1a98fea2cedc904ea98990a002a9428382510a4.jpg) \nFig. 1 Design strategy for the plant-inspired catechol-chemistry-based self-adhesive, tough, and antibacterial NPs-P-PAA hydrogel. a Generation of radicals by the redox reaction between $\\mathsf{A g}$ -Lignin NPs and ammonium persulfate (APS), triggering the gelation of the hydrogel under an ambient environment. b Quinone-catechol reversible reaction maintains dynamic balance. c Scheme of molecular structure of plant-inspired adhesive and tough hydrogel. d Electron spin-resonance spectroscopy (ESR) spectra for quinone radical detection. e Transmission electron microscope (TEM) micrograph shows the core-shell structure of $\\mathsf{A g}$ -Lignin ${\\mathsf{N P s}},$ the inset is $\\mathsf{A g}$ element mapping. f High-resolution transmission electron microscopy (HRTEM) micrograph shows the structure of $\\mathsf{A g}$ -Lignin ${\\mathsf{N P s}},$ ; the inset is high-resolution lattice. g Scanning electron microscope (SEM) micrograph shows the microfibril structures in the hydrogel; the inset presents typical microfibrils. NPs, nanoparticles; P, pectin; PAA, polyacrylic acid \n\nTo further investigate the mechanism of the free radical generated by Ag-Lignin NPs, electron spin-resonance spectroscopy (ESR) was used to characterize free radicals in various solutions (Fig. 1d, Supplementary Figure 1, 2 and Supplementary Table 2). The ESR spectrum of the Ag-Lignin NPs with APS contained a signal with a $g$ value of 2.0034, which was attributed to quinone/semiquinone radicals36. The ESR spectrum of the pure lignin/APS solution exhibited the same peak with a lower intensity, which indicated that the quantity of the quinone/ semiquinone radicals was much smaller (Supplementary Table 3). These results demonstrated that pure lignin or APS solution can generate free radicals, but the quantity of free radicals in the solution is not enough to trigger free-radical polymerization. Thus, only the Ag-Lignin NPs-APS solution can generate enough radicals to trigger the self-polymerization of the hydrogel under an ambient environment, whereas lignin or APS alone did not (Supplementary Figure 10). Furthermore, Ag-Lignin NPs-APS solution can initiate the polymerization of other free-radical monomers, such as AA, acrylamide, and poly(ethylene glycol) diacrylate (Supplementary Figure 11). \n\nScanning electron microscope (SEM) and transmission electron microscope (TEM) micrographs revealed that the Ag-Lignin NPs formed clusters with core-shell structures (Fig. 1e, f and Supplementary Figure 3). The DLS analysis showed that the average size of the Ag-Lignin NPs was $125{\\sim}145\\mathrm{nm}$ (Supplementary Figure 4). After incorporation in the hydrogel, the AgLignin NPs were well dispersed in the network (Fig. 1g). The distribution of the Ag-Lignin NPs in the hydrogel was also revealed by element mapping of Ag, and the results indicated that Ag was distributed uniformly inside the hydrogel (Supplementary Figure 17). With the presence of catechol groups of Ag-Lignin NPs, the freeze-dried hydrogel exhibited an interwoven microfibril structure. The microfibrils were a distinctive feature that only present in the NPs-P-PAA hydrogel, but not in pure PAA and P-PAA hydrogels (Supplementary Figure 16a, b). The microfibrils were formed by the interactions between polymer chains and NPs because catechol groups of $\\mathrm{Ag}$ -Lignin NPs can form intermolecular interactions with the polymer chains and generate nanostructured morphologies43. \n\nDynamic reductive/oxidative reaction in the NPs-P-PAA hydrogel. The redox environment inner the NPs-P-PAA hydrogel was investigated by XPS analysis and CV experiments (Supplementary Notes 13, 14). XPS analysis was used to investigate changes in the content of catechol group during the redox reaction. The XPS results indicated that lignin had high contents of C-O and C-OH groups at $285.9\\mathrm{eV}$ and a low content of ${\\mathrm{C}}={\\mathrm{O}}$ at $288.6\\mathrm{eV}$ . For the Ag-Lignin NPs, the C 1s spectrum showed that the contents of C-O and C-OH groups sharply decreased and the content of ${\\mathrm{C}}={\\mathrm{O}}$ groups greatly increased (Supplementary Figure 8). These changes were evidence of oxidation and the associated reaction between lignin and $\\mathrm{[Ag(NH}_{3})_{2}]^{+}$ . In the NPs-PPAA hydrogel, both C-O(C-OH) and $\\mathbf{C}=\\mathbf{O}$ appeared, which indicated that C-O or C-OH (catechol) groups were present in the NPs-P-PAA hydrogel (Supplementary Figure 12 and Supplementary Table 6). CV experiments were conducted to investigate the redox reaction in the NPs-P-PAA hydrogel system. The curves of CV scanning presented a prominent redox peak at $0.10{\\sim}0.20\\mathrm{V}$ (Supplementary Figure 13a), which corresponded to catechol oxidation and quinone reduction that occurred at the same potential44, 45. These redox peaks still existed even with excessive persulfate (Supplementary Table 7 and Supplementary Figure 13b–e), which indicated that the stable redox reaction of Ag-Lignin NPs happened even in excessive persulfate solution. In short, both the results of XPS analysis and CV experiments prove that redox exchange occurs in the hydrogel. Furthermore, the antioxidative abilities of the hydrogels were tested by measuring their capacities to scavenge ${\\mathfrak{a}},$ $\\mathtt{a}$ -diphenyl- $\\cdot\\beta$ -picrylhydrazyl (DPPH) free radicals, and the results indicate that both the NPs and NPs-P-PAA hydrogels have high reduction abilities (Supplementary Figure 14, Supplementary Table 8, and Supplementary Notes 15). \n\nMechanical properties. The NPs-P-PAA hydrogel was resilient, stretchable, and tough. As shown in Fig. 2a, the hydrogel was stretched to 26 times its initial length. The load–unload tensile stress–strain curves proved it as well (Fig. 2b). It also withstood a high compression to complete deformation and did not break; after the compressive load was removed, the hydrogel recovered automatically and rapidly to its initial shape (Fig. 2c). The load–unload compression stress–strain curves indicated that the NPs-P-PAA hydrogel have good recoverability (Fig. 2d and Supplementary Figure 19). Figure 2e shows the typical tensile stress–strain curves of the hydrogels under tensile tests. The maximum tensile strain increased with the content of NPs and reached a maximum value of $2660\\%$ at the $0.03\\ \\mathrm{NPs}$ , much higher than that of the P-PAA hydrogel $(860\\%)$ , and in sharp contrast to that of the PAA hydrogel $(380\\%)$ . The strength and ductility product of various hydrogels was also measured and the 0.03 NPs-P-PAA hydrogel exhibited the highest value $(300\\mathrm{MPa\\%})$ ) shown in Fig. 2f. The fracture energy showed a similar trend, as demonstrated by the single edge notched tests (Fig. 2g). A maximum fracture energy of $\\bar{5}500\\bar{\\mathrm{J}}\\mathrm{m}^{-2}$ was achieved at $0.03\\mathrm{\\NPs},$ which was much larger than that of human skin $(\\sim2000\\ \\mathrm{J}\\ \\mathrm{m}^{-2})$ . The high toughness and good resilience of the hydrogel was attributed to two factors. First, pectin interpenetrated the PAA networks and strengthened the hydrogel. Second, the $\\mathrm{Ag\\mathrm{-}}$ Lignin NPs, PAA, and pectin had noncovalent interactions between each other, which dissipated energy under large deformation and improved the mechanical properties of the hydrogel. Third, the AgLignin NPs have many hydrophilic functional groups, and therefore can be well dispersed in the hydrogel. Thus, the mechanical properties of the hydrogel were improved because of the nanoreinforcement effects of the NPs. As a control, pure lignin was incorporated in the L-P-PAA hydrogel, and the tensile strength of the L-P-PAA hydrogel was lower than those of the PAA, P-PAA, and $0.03~\\mathrm{NPs}$ -P-PAA hydrogels. This is because lignin has many hydrophobic methoxy groups and therefore cannot be uniformly distributed in the hydrogel, demonstrating that bare lignin cannot improve the mechanical properties of the hydrogel (Supplementary Figure 18). \n\nAdhesiveness. Similar to an adhesive plant, this hydrogel had long-term and repeatable adhesiveness to a variety of substrates. The hydrogels can adhere to both hydrophilic and hydrophobic surfaces, such as polypropylene, Teflon (PTFE), rubber, glass, nut shell, and steel (Fig. 3a). The adhesive hydrogels also had high adhesiveness to biological tissue, including heart, lung, kidney, spleen, liver, bone, and muscle, which is crucial for biomedical applications (Fig. 3a). The hydrogel exhibited excellent adhesive performance on the skin surface of the author’s body and was peeled off without any residue and anaphylactic reaction (Fig. 3b). The adhesion strength of the hydrogel on representative surfaces was quantified by a tensile adhesion test (Fig. 3c and Supplementary Figure 20); the adhesion strength to glass, titanium (Ti), PTFE, and porcine skin was 38, 50, 65, and $27.5\\mathrm{kPa}$ , respectively. The hydrogel maintained good adhesion even after 30 repeated peeling/adhering cycles (Fig. 3d). To prove that the hydrogels had long-lasting adhesiveness, tensile adhesion testing was performed on NPs-P-PAA hydrogels with different storage times (7, 14, and 28 days). The hydrogel maintained good adhesion to porcine skin after 28 days (Supplementary Figure 21). \n\n![](images/3a170802c1b4e7cb2a8c94e00ef30f213969c816ec8ff3e629e3df786ef4da5e.jpg) \nFig. 2 Mechanical properties of the hydrogels. a The 0.03 NPs-P-PAA hydrogel was elongated to 26 times its initial length and recovered in 2 min. b Tensile loading–unloading curves of 0.03 NPs-P-PAA hydrogel. c The 0.03 NPs-P-PAA hydrogel was compressed and recovered in 2 min. d Compressive loading–unloading curves of 0.03 NPs-P-PAA hydrogel. e Typical tensile stress–strain curves of the hydrogel. f Strength and ductility product of various hydrogels. g Fracture energy of the hydrogels. (Error bar means the standard deviation, \\*indicates statistically difference at $p<0.05,$ $p$ value was generated by one‐way analysis of variance (ANOVA), followed by Tukey's multiple‐comparison post hoc test, $n=4.$ ) ${\\mathsf{N P s}},$ , nanoparticles; P, pectin; PAA, polyacrylic acid \n\nThus, the adhesiveness of the hydrogel was attributed to the synergistic effect of the carboxyl groups of PAA and catechol groups of Ag-Lignin NPs (Supplementary Notes 16 and Supplementary Figure 15). First, the carboxyl groups of PAA can interact with various surfaces through electrostatic interactions. Second, Ag-Lignin NPs generate catechol and quinone groups during the redox reaction, which endows the hydrogel with adhesiveness. Quinone groups form physical crosslinking with the pectin and PAA, which can dramatically enhance the cohesion of the hydrogel. Catechol groups possess strong adhesion to various substrates, which interact with different substrates through covalent and noncovalent bonding (Fig. 3e). Covalent bonding was formed at some specific substrates containing amine or thiol groups through Schiff base or Michael addition reactions; noncovalent bonding, such as hydrogen bonding, $\\pi{-}\\pi$ stacking, and metal coordination or chelating, could also exist between hydrogels and solid surfaces43. Two types of hydrogels were tested to investigate the synergistic effects of the carboxyl groups of PAA and catechol groups of the Ag-Lignin NPs on the adhesiveness of the hydrogel. A hydrogel without carboxyl groups was prepared from polyacrylamide, pectin, and Ag-Lignin NPs (NPs-P-PAM gel), and a hydrogel with low content of carboxyl groups were prepared from poly(acrylic acidco-acrylamide), pectin, and Ag-Lignin NPs (NPs-P-P(AA-coAM) gel) (Supplementary Notes 21 and Supplementary Table 9). As shown in Supplementary Figure 22, the adhesion strengths of NPs-P-PAM and NPs-P-P(AA-co-AM) hydrogels to porcine skin were $12\\mathrm{kPa}$ and $15\\mathrm{kPa}$ , respectively, which were lower than that of the NP-P-PAA hydrogel $(25~\\mathrm{kPa})$ . These results proved that both carboxyl groups of PAA and catechol groups of Ag-Lignin NPs contributed to the good adhesiveness of the hydrogel. \n\n![](images/cbcca0868cdcabaf7305ee56810a4725db90ef49d61f0e3930290315d536f99f.jpg) \nFig. 3 Adhesive properties of the NPs-P-PAA hydrogel. a The hydrogel was adhered to various material surfaces and tissues. b The hydrogel was repeatedly adhered on the skin of the author. After peeling off, no residue or irritation on skin was found. c The adhesive strength of various hydrogels to porcine skin. d The repeated adhesion of 0.03 NPs-P-PAA hydrogels to porcine skin after 30 cycles of adhering–stripping. e The adhesion mechanism of the ${\\mathsf{N P s}}$ -P-PAA hydrogel. The blue oval indicated the hydrogen bonding or hydrophobic interaction between the hydrogel and different surfaces. (Error bar means the standard deviation, \\* indicates statistically difference at $p<0.05$ , $p$ value was generated by one‐way analysis of variance (ANOVA), followed by Tukey's multiple‐comparison post hoc test, $n=4.$ ) ${\\mathsf{N P s}},$ nanoparticles; P, pectin; PAA, polyacrylic acid \n\nAntibacterial activity. The NP-P-PAA hydrogels displayed strong antibacterial activities owing to the broad-spectrum antimicrobial activity of $\\mathrm{Ag}$ in the Ag-Lignin $\\mathrm{NPs^{46,\\^{-}47}}$ . Figure 4a shows a photograph of bacterial suspensions cultured with hydrogels. The suspensions of the blank group, PAA, and P-PAA were turbid during the $24\\mathrm{-h}$ culture, whereas that of the NPs-PPAA hydrogel was clear. The bactericidal ratio of the hydrogel for Escherichia coli and Staphylococcus epidermidis were $97\\%$ and $98\\%$ , respectively (Fig. 4b). These results indicated the hydrogel effectively and significantly inhibited both $G-$ and $G+$ bacteria. \n\nThe antibacterial activities of the hydrogel were further confirmed in vivo in a rabbit model. The purified NPs-P-PAA hydrogels were implanted in the subcutaneous pockets on the back of rabbits and then an $E.$ . coli suspension $\\mathrm{i}\\mathrm{mL}.$ , $\\mathsf{\\bar{10}}^{5}$ cells $\\mathrm{mL^{-1}}$ ) was injected in the pockets (Fig. 4c). After 7 days, the surgical sites were harvested to examine the infections and inflammatory reactions (Fig. 4d). The site treated with P-PAA was filled with purulence, whereas the site treated with NPs-P-PAA was clear. The tissue surrounding the implants was removed and stained with hematoxylin and eosin (H&E) to assess the anti-infection ability of the hydrogel (Fig. 4e). Histological staining revealed that the PPAA group had a large number of multinucleated giant cells and edema tissue in the surrounding tissue, and the subcutaneous tissue was destroyed, indicating that the E. coli caused severe inflammation reactions. In sharp contrast, the tissue surrounding the NPs-PPAA hydrogel was in good condition and there were almost no multinucleated giant cells or edema tissue around the hydrogel. These results demonstrated that the NPs-P-PAA hydrogel had good antibacterial ability in vivo and can be safely applied for healing wounds and repairing bone or cartilage. \n\n![](images/6aa63e17ceff52df7568baa14e5858040444d492f04af3d145cf643c90124493.jpg) \nFig. 4 The antibacterial activity of the hydrogel. a Photos of S. epidermidis and E. coli. solution co-cultured with the hydrogels after 1 day. b The bactericidal ratio of the hydrogels to S. epidermidis and E. coli. (Error bar means the standard deviation, \\* indicates statistically difference at $p<0.05,$ , $p$ value was generated by one‐way analysis of variance (ANOVA), followed by Tukey's multiple‐comparison post hoc test, $n=3{\\mathrm{:}}$ . c Scheme of the in vivo antibacterial experiments. d Photographs of harvested hydrogels after they were implanted in the skin pockets for 7 days of post surgery. e Hematoxylin–eosin (H&E)- stained sections of connective tissues surrounding the hydrogel \n\nCell affinity and wound healing. The NPs-P-PAA hydrogel exhibited cell affinity and favored the adhesion and proliferation of cells (Fig. 5a, b). Fibroblasts, the cell types typically responsible for wound repair, were cultured on the PAA, P-PAA, and NPs-PPAA hydrogels. Before cell culture or the implantation experiment, the hydrogel was purified by repeated purification in a phosphate-buffered saline solution and $75\\%$ alcohol to remove excessive APS and other residues. Confocal laser scanning microscopy images showed that all the hydrogels supported cell adhesion and spreading (Fig. 5a). Compared with the PAA hydrogel, the P-PAA hydrogel showed better cell adhesiveness. The 0.03 NPs-P-PAA hydrogel showed the best cell adhesiveness. An MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide) assay was used to further evaluate the cell proliferation on the hydrogel (Fig. 5b). The proliferation of fibroblasts on the P-PAA and NPs-P-PAA hydrogels was faster than that on the PAA hydrogel because the pectin and $\\mathrm{Ag}$ -Lignin NPs had improved biocompatibility and cell affinity. Note that the silver release of the current hydrogel was lower than that in an earlier study48 (Supplementary Figure 23 and Supplementary Notes 22), which is because both the lignin and the hydrogel system play important roles in retarding the release of ${\\dot{\\mathrm{Ag}}}^{+}$ . The functional groups of lignin can bind Ag+ to slow Ag release49, 50. In addition, the functional groups of PAA51, 52 and pectin53, such as carboxyl and hydroxyl, coordinate with $\\mathrm{Ag^{+}}$ . Thus, the concentrations of released $\\mathrm{Ag^{+}}$ are low and such a low dose of $\\mathrm{Ag^{+}}$ is non-toxic to cells. \n\nThe NPs-P-PAA hydrogel was further used to repair fullthickness skin defects in vivo (Fig. 5c–f). The NPs-P-PAA hydrogel showed better healing than the blank and P-PAA. After epidermal growth factor (EGF) was loaded, the hydrogels showed the best healing performance. After implantation of the hydrogel for 14 days, the wound was well healed and the defect areas were nearly closed in all the groups treated with a hydrogel, whereas large scars were observed only in the groups treated without hydrogel (Fig. 5d). The skin healing ratio, which was defined as the ratio of wound healing area to the initial defect area, was used to quantitatively evaluate the wound healing rate of different hydrogel-treated defect areas (Fig. 5e). The NPs-P-PAA hydrogel had a healing ratio of $90\\%$ , which was higher than that of the blank group $(59\\%)$ and the P-PAA hydrogel $(78\\%)$ . The EGFloaded hydrogel had the highest healing ratio of $92\\%$ . \n\nThe quality of the regenerated skin tissue in the defects was further investigated by H&E staining. As shown in Fig. 5f, all the samples were covered with an intact and complete layer of epidermis. The samples treated with a blank and P-PAA had a large area of unmatured tissue, whereas the sample treated with NPs-P-PAA hydrogel had a small proportion of new tissue. The quality of the newly regenerated tissue was further examined by obtaining magnified micrographs. Many granulation tissue still existed in the regenerated area of the samples treated with the blank and P-PAA hydrogel, whereas collagen fibers appeared in the sample treated with NPs-P-PAA hydrogels. The sample treated with EGF-loaded hydrogel had ordered collagen fibers and hair follicles, which showed that this regenerated tissue was almost mature. In short, this NPs-P-PAA hydrogel was able to repair wound healing and increase skin tissue regeneration, and it had better tissue regeneration ability than the other hydrogels. \n\n![](images/c64a46264c69271970ab1190391b0107af167171dc30476088a20f2d03805d94.jpg) \nFig. 5 The biocompatible NPs-P-PAA hydrogel used to repair a full-thickness skin defect. a Confocal laser scanning microscopy (CLSM) micrographs of fibroblasts on various hydrogels. b MTT assay of the proliferation of fibroblasts. (Error bar means the standard deviation, \\* indicates statistical difference at $p<0.05.$ , p value was generated by one‐way analysis of variance (ANOVA), followed by Tukey's multiple‐comparison post hoc test, $n=4$ ). c Scheme of the hydrogel implanted into the skin defect of a rat. d Percent wound closure at different periods of post wounding. e Representative of the gross appearance of defects treated with various hydrogels. f Hematoxylin–eosin (H&E) staining of the wound section after 14 days of treatment. NPs, nanoparticles; P, pectin; PAA, polyacrylic acids \n\n# Discussion \n\nIn summary, we prepared a plant catechol-chemistry-based hydrogel with high adhesiveness, toughness, and cell affinity. Ag-Lignin NPs were developed to generate radicals and maintain the quinone-catechol redox balance in the inner hydrogel network. Compared with the commonly used adhesives, this hydrogel had the following advantages. First, the gelation of the hydrogel was triggered by radically enriched Ag-Lignin NPs without the need for UV and thermal treatment. Therefore, the hydrogel was biocompatible and not harmful to skin tissue. Second, the hydrogels displayed durable adhesiveness and maintained their adhesiveness for a long time. Third, the plantinspired Ag-Lignin NPs hydrogel exhibited good cell affinity and tissue adhesiveness. Finally, the hydrogel has the ability of antiinfection, which is particularly suitable for skin wound repair. In short, this easy-to-prepare and environmentally friendly plantinspired hydrogel illustrates a strategy for the development of adhesiveness hydrogels with multifunctionality based on dynamic redox catechol chemistry. \n\n# Methods \n\nMaterials. Alkali lignin $\\mathrm{'Wn}=1000{\\sim}10,000\\rangle$ was purchased from Qunlin paper Group Co., China, pectin (P, galacturonic acid content $\\geq74\\%$ ) and AA $(99.0\\%)$ were supplied by Macklin, APS $(98.0\\%)$ and poly (ethylene glycol) dimethacrylate (PEGDA, average $\\mathrm{Mn}=750$ , $99.8\\%$ ) were purchased from Sigma-Aldrich (USA). $\\mathrm{AgNO}_{3}$ $(99.8\\%)$ , ammonia solution $\\mathrm{(NH}_{3}{\\cdot}\\mathrm{H}_{2}\\mathrm{O}$ , $25.0{\\sim}28.0\\%$ ), and sodium hydroxide $\\mathrm{(NaOH,99.0\\%}$ ) was purchased from KESHI Chemical Works in Chengdu. Deionized water was used in the experiment. All solvents and chemicals were purchased from commercial sources and used as received, unless otherwise noted. \n\nPreparation of Ag-Lignin NPs. The Ag-Lignin core-shell NPs were prepared according to the procedure described in previous report50. First, an aqueous solution of lignin at a concentration of $50\\mathrm{{\\bar{mg}m L^{-1}}}$ was prepared by dissolving the weighted amount of lignin powder in $\\mathrm{NaOH}$ solution $(\\mathrm{pH}=10^{\\cdot}$ ) with the aid of ultrasonic agitation (solution A). Second, an aqueous solution of $\\mathrm{AgNO}_{3}$ at an $\\mathrm{Ag^{+}}$ ion concentration of 3.33, 10, and $16.67\\mathrm{mg}\\mathrm{m}\\mathrm{\\bar{L}}^{-1}$ was prepared and $5\\mathrm{mol}\\mathrm{L}^{-1}$ of aqueous ammonia solution was added to the silver-ammonia complex (solutions B). Finally, solution A was added slowly dropwise to solution B and reacted at room temperature for $^{\\textrm{1h}}$ to obtain Ag-Lignin core-shell NPs ( $\\mathrm{\\Ag}$ -Lignin NPs) solution. The concentration of various Ag-Lignin NPs was listed in Supplementary Notes 1 and Supplementary Table 1. CV was used to analyze the reaction between lignin and $\\mathrm{[Ag(NH}_{3})_{2}]^{+}$ solution (Supplementary Notes 7). \n\nPreparation of hydrogel. AA, pectin, Ag-Lignin NPs solution, APS, PEGDA, and ceionized water were poured into the beaker and stirred to prepare a homogeneous solution. Thereafter, the solution was injected into a reaction mold. Finally, the samples were placed in $\\Nu_{2}$ atmosphere for $20\\mathrm{min}$ at room temperature to obtain NPs-P-PAA hydrogels. The formulations of hydrogels were denoted as $x$ NPs-PPAA, where $x$ was masses of $\\mathrm{AgNO}_{3}$ . The details of preparation and composition of various hydrogels were listed in Supplementary Notes 11, 12 and Supplementary Table 5. \n\nCharacterization. The electron spin-resonance spectroscopy analysis results were performed on an ESR Spectrometer (JES-FA200 ESR Spectrometer, Japan) at 9.873 GHz. The morphology structures were examined using a scanning electron microscope (SEM; JSM 6390, JEOL, Japan). TEM images of NPs in aqueous dispersion were obtained by using a Tecnai-F30, FEI, USA. The mechanical property measurements and adhesiveness properties of the hydrogels were conducted according to our previous studies25, 54 using a universal testing machine (5567, Instron, America) with a $100\\mathrm{N}$ load cell. Details are described in Supplementary Notes 2–6 and 17–20. \n\nAntibacterial activity in vitro. To investigate the antibacterial activity of the hydrogel, S. epidermidis (ATCC6538, Gram-positive organism) and E. coli (ATCC8739, Gram-negative organism) were used for the tests according to our previous study54. The antibacterial activity of five groups of samples $(30\\upmu\\up g$ $\\mathrm{\\bar{sample}}^{-1}.$ ), including PAA, P-PAA, and NPs-P-PAA with different concentrations of NPs, were tested by evaluating the inhibition of the bacterium S. epidermidis and $E.$ coli. Details are described in Supplementary Notes 23. \n\nAntibacterial activity in vivo. The antibacterial activities of the hydrogel were further confirmed in vivo in a rabbit model, refer to our previous study54. The PPAA and $\\mathrm{NPs}$ -P-PAA hydrogels were implanted subcutaneously on the back of New Zealand rabbit (Dashuo, Chengdu, China), following which $1\\mathrm{mL}$ of $E$ . coli ( $:10^{5}$ cells $\\mathrm{mL}^{-1}$ ) was injected to the hydrogel site. The P-PAA hydrogels were treated as a positive control. In the days following the surgical operation, the animal activity and appearance of the wound was examined each day. The surgical sites were harvested to examine infections and inflammatory reactions (Supplementary Notes 24). \n\nCell biocompatibility in vitro. NIH-3T3 fibroblast (SCSP-515, Stem Cell Bank, Chinese Academy of Sciences, Shanghai, China) cells in a growth phase were treated with trypsin and harvested. According to previous methods54, the cells were seeded on the hydrogels with a density of $5\\times10^{\\overline{{4}}}$ cells) in the wells of the tissue culture plates and left undisturbed in an incubator for $^{3\\mathrm{h}}$ to allow for cell attachment. Then, an additional $1\\mathrm{mL}$ of the Dulbecco’s modified eagle medium (HyClone, USA) supplemented with $10\\%$ fetal bovine serum (HyClone, USA) was added into each well. The cells were allowed to adhere and grow for 3 and 5 days. \n\nThe morphologies of the cells on the hydrogel surfaces were observed using a laser scanning confocal microscope (Leica, Germany). The biocompatibility of the hydrogel and the cell proliferation was assessed by the MTT assay. Details were described in Supplementary Notes 25. \n\nWound healing in vivo. Full skin wounds were created on the dorsal area of rats and treated with the P-PAA hydrogel, NPs-P-PAA hydrogels, and the EGF-loaded NPs-P-PAA hydrogels. The wounds treated without hydrogels were used as a control. The surgical procedure was performed according to a previous study55. Briefly, four full-thickness circular wounds $\\mathrm{8}\\mathrm{mm}$ in diameter) were created on the upper back of each Sprague Dawley $(180{\\sim}220\\mathrm{g}$ , Dashuo, Chengdu, China) rat using a disposable $8\\mathrm{-mm}$ skin biopsy punch. The P-PAA, NPs-P-PAA, and EGFloaded hydrogels $30\\upmu\\mathrm{g}$ sample−1, Shanghai Primegene Bio-Tech Co., Ltd.) were implanted on other wound sites of the rats. A wound without a hydrogel was used as a control. Five parallel specimens of each type of hydrogel were tested. All animal procedures were performed according to protocols approved by the institutional animal ethics committee of the Southwest Jiaotong University and laboratory animal administration rules of China. Details were described in Supplementary Notes 26. \n\n# Data availability \n\nThe authors declare that all relevant data of this study are available from the corresponding authors. \n\nReceived: 13 October 2018 Accepted: 4 March 2019 \nPublished online: 02 April 2019 \n\n# References \n\n1. Sun, X. et al. Electrospun photocrosslinkable hydrogel fibrous scaffolds for rapid in vivo vascularized skin flap regeneration. Adv. Funct. Mater. 27, 1604617 (2016). \n2. Zhao, X. et al. Photocrosslinkable gelatin hydrogel for epidermal tissue engineering. Adv. Healthc. Mater. 5, 108–118 (2016). \n3. Balakrishnan, B., Joshi, N., Jayakrishnan, A. & Banerjee, R. Self-crosslinked oxidized alginate/gelatin hydrogel as injectable, adhesive biomimetic scaffolds for cartilage regeneration. Acta Biomater. 10, 3650–3663 (2014). \n4. Wang, L., Wu, Y., Guo, B. & Ma, P. X. Nanofiber yarn/hydrogel core-shell scaffolds mimicking native skeletal muscle tissue for guiding 3D myoblast alignment, elongation, and differentiation. ACS Nano 9, 9167 (2015). \n5. Gaharwar, A. K., Peppas, N. A. & Ali, K. Nanocomposite hydrogels for biomedical applications. Biotechnol. Bioeng. 111, 441–453 (2014). \n6. Yang, J., Bai, R. & Suo Z. Topological adhesion of wet materials. Adv Mater. 30, e1800671 (2018). \n7. Zhao, Y. et al. Proteoglycans and glycosaminoglycans improve toughness of biocompatible double network hydrogels. Adv. Mater. 26, 436–442 (2014). \n8. Li, J. et al. Tough adhesives for diverse wet surfaces. Science 357, 378 (2017). \n9. Liu, X., Zhang, Q. & Gao, G. Bioinspired adhesive hydrogels tackified by nucleobases. Adv. Funct. Mater. 27, 1703132 (2017). \n10. Sun, L. et al. Sundew-inspired adhesive hydrogels combined with adiposederived stem cells for wound healing. ACS Appl. Mater. Inter. 8, 2423 (2016). \n11. Han, L. et al. A mussel-inspired conductive, self-adhesive, and self-healable tough hydrogel as cell stimulators and implantable bioelectronics. Small 13, 1601916 (2017). \n12. Kaur, S., Weerasekare, G. M. & Stewart, R. J. Multiphase adhesive coacervates inspired by the sandcastle worm. ACS Appl. Mater. Inter. 3, 941–944 (2011). \n13. Zhao, Q. et al. Underwater contact adhesion and microarchitecture in polyelectrolyte complexes actuated by solvent exchange. Nat. Mater. 15, 407–412 (2016). \n14. Lee, H., Dellatore, S. M., Miller, W. M. & Messersmith, P. B. Mussel-inspired surface chemistry for multifunctional coatings. Science 318, 426–430 (2007). \n15. Liu, Y., Ai, K. & Lu, L. Polydopamine and its derivative materials: synthesis and promising applications in energy, environmental, and biomedical fields. Chem. Rev. 114, 5057–5115 (2014). \n16. Shin, J. et al. Tissue adhesive catechol-modified hyaluronic acid hydrogel for effective, minimally invasive cell therapy. Adv. Funct. Mater. 25, 3814–3824 (2015). \n17. Fullenkamp, D. E. et al. Mussel-inspired silver-releasing antibacterial hydrogels. Biomaterials 33, 3783–3791 (2012). \n18. GhavamiNejad, A., Park, C. H. & Kim, C. S. In situ synthesis of antimicrobial silver nanoparticles within antifouling zwitterionic hydrogels by catecholic redox chemistry for wound healing application. Biomacromolecules 17, 1213–1223 (2016). \n19. Kim, B. J. et al. Mussel-mimetic protein-based adhesive hydrogel. Biomacromolecules 15, 1579 (2014). \n20. Kord Forooshani, P. & Lee, B. P. Recent approaches in designing bioadhesive materials inspired by mussel adhesive protein. J. Polym. Sci. Part A 55, 9–33 (2017). \n21. Waite, J. H. Mussel adhesion-Cessential footwork. J. Exp. Bot. 220, 517–530 (2017). \n22. Lee, B. P., Messersmith, P. B., Israelachvili, J. N. & Waite, J. H. Musselinspired adhesives and coatings. Annu Rev. Mater. Res 41, 99–132 (2011). \n23. Hofman, A. H. et al. Bioinspired underwater adhesives by using the supramolecular toolbox. Adv. Mater. 30, 1704640 (2018). \n24. Han, L. et al. Mussel-inspired adhesive and tough hydrogel based on nanoclay confined dopamine polymerization. ACS Nano 11, 256–2574 (2017). \n25. Han, L. et al. Transparent, adhesive, and conductive hydrogel for soft bioelectronics based on light-transmitting polydopamine-doped polypyrrole nanofibrils. Chem. Mater. 30, 5561–5572 (2018). \n26. Yang, Z., Qiu, H., Li, X., Gao, P. & Huang, N. Plant-inspired gallolamine catalytic surface chemistry for engineering an efficient nitric oxide generating coating. Acta Biomater. 76, 89–98 (2018). \n27. Hong, S. et al. Pyrogallol 2-aminoethane: a plant flavonoid-inspired molecule for material-independent surface chemistry. Adv. Mater. Inter 1, 1400113 (2014). \n28. Thakur, V. K., Thakur, M. K., Raghavan, P. & Kessler, M. R. Progress in green polymer composites from lignin for multifunctional applications: a review. ACS Sustain Chem. 2, 1072–1092 (2014). \n29. Thakur, V. K. & Thakur, M. K. Recent advances in green hydrogels from lignin: a review. Int. J. Biol. Macromol. 72, 834–847 (2015). \n30. Kai, D. et al. Towards lignin-based functional materials in a sustainable world. Green. Chem. 18, 1175–1200 (2016). \n31. Richter, A. P. et al. An environmentally benign antimicrobial nanoparticle based on a silver-infused lignin core. Nat. Nanotechnol. 10, 817–823 (2015). \n32. Young, R., Fujita, M. & River, B. H. New approaches to wood bonding A baseactivated lignin adhesive system. Wood Sci. Technol. 19, 363–381 (1985). \n33. Ji, X. & MJIJoA, Guo Adhesives. Preparation and properties of a chitosanlignin wood adhesive. Int J. Adhes. Adhes. 82, 8–13 (2018). \n34. Yang, W. et al. Preparation and properties of adhesives based on phenolic resin containing lignin micro and nanoparticles: a comparative study. Mater. Des. 161, 55–63 (2019). \n35. Luo, J. et al. An eco-friendly wood adhesive from soy protein and lignin: performance properties. RSC Adv. 5, 100849–100855 (2015). \n36. Bährle, C., Nick, T. U., Bennati, M., Jeschke, G. & Vogel, F. High-field electron paramagnetic resonance and density functional theory study of stable organic radicals in lignin: influence of the extraction process, botanical origin, and protonation reactions on the radical g tensor. J. Phys. Chem. A 119, 6475–6482 (2015). \n37. Milczarek, G., Rebis, T. & Fabianska, J. One-step synthesis of lignosulfonatestabilized silver nanoparticles. Colloids Surf. B 105, 335–341 (2013). \n38. Ke, J., Niu, C., Zhang, J. & Zeng, G. Significantly enhanced visible light photocatalytic activity and surface plasmon resonance mechanism of $\\mathrm{\\Ag/}$ AgCl/ZnWO 4 composite. J. Mol. Catal. A 395, 276–282 (2014). \n39. Yang, H. et al. Quantitative detection of photothermal and photoelectrocatalytic effects induced by SPR from Au@Pt nanoparticles. Angew. Chem. Int. Ed. 54, 11462–11466 (2015). \n40. Huang, J. et al. Simultaneouly enhanced durability and performance by employing dopamine copolymerized PEDOT with high work function and water-proofness for inverted perovskite solar cells. J. Mater. Chem. C 6, 2311–2318 (2018). \n41. Huang, J. et al. Improving the efficiency and stability of inverted perovskite solar cells with dopamine-copolymerized PEDOT: PSS as hole extraction layer. J. Mater. Chem. A 5, 13817–13822 (2017). \n42. Servais, A. B. et al. Functional mechanics of a pectin-based pleural sealant after lung injury. Tissue Eng. Part A 24, 695–702 (2018). \n43. Han, L. et al. Tough, self-healable and tissue-adhesive hydrogel with tunable multifunctionality. NPG Asia Mater. 9, e372 (2017). \n44. Milczarek, G. Lignosulfonate-modified electrodes: electrochemical properties and electrocatalysis of NADH oxidation. Langmuir 25, 10345–10353 (2009). \n45. Movil-Cabrera, O., Rodriguez-Silva, A., Arroyo-Torres, C. & Staser, J. A. Electrochemical conversion of lignin to useful chemicals. Biomass Bioenergy 88, 89–96 (2016). \n46. You, C. et al. The progress of silver nanoparticles in the antibacterial mechanism, clinical application and cytotoxicity. Mol. Biol. Rep. 39, 9193–9201 (2012). \n47. Xiu, Z.-m, Zhang, Q.-b, Puppala, H. L., Colvin, V. L. & Alvarez, P. J. J. N. Negligible particle-specific antibacterial activity of silver nanoparticles. Nano Lett. 12, 4271–4275 (2012). \n48. Xie, C.-M. et al. Silver nanoparticles and growth factors incorporated hydroxyapatite coatings on metallic implant surfaces for enhancement of osteoinductivity and antibacterial properties. ACS Appl. Mater. Inter. 6, 8580–8589 (2014). \n49. Richter, A. P. et al. An environmentally benign antimicrobial nanoparticle based on a silver-infused lignin core. Nat. Nanotechnol. 10, 817 (2015). \n50. Milczarek, G., Rebis, T., Fabianska, J. & Biointerfaces, S. B. One-step synthesis of lignosulfonate-stabilized silver nanoparticles. Colloids Surf. B 105, 335–341 (2013). \n51. Zheng, Y. & Wang, A. Ag nanoparticle-entrapped hydrogel as promising material for catalytic reduction of organic dyes. J. Mater. Chem. 22, 16552–16559 (2012). \n52. Lu, Y. et al. In situ formation of Ag nanoparticles in spherical polyacrylic acid brushes by UV irradiation. J. Phys. Chem. C 111, 7676–7681 (2007). \n53. Eswaramma, S., Reddy, N. S. & Rao, K. K. J. Ijobm Phosphate crosslinked pectin based dual responsive hydrogel networks and nanocomposites: development, swelling dynamics and drug release characteristics. Int. J. Biol. Macromol. 103, 1162–1172 (2017). \n54. Gan, D. et al. Mussel-inspired contact-active antibacterial hydrogel with high cell affinity, toughness, and recoverability. Adv. Funct. Mater. 29, 1805964 (2018). \n55. Han, L. et al. Mussel-inspired adhesive and tough hydrogel based on nanoclay confined dopamine polymerization. ACS Nano 11, 2561–2574 (2017). \n\n# Acknowledgements \n\nThis work was financially supported by the National key research and development program of China (2016YFB0700800), NSFC (81671824), and Fundamental Research Funds for the Central Universities (2682016CX075, 2682018QY02). The authors wish to acknowledge the assistance on materials characterization received from Analytical and Testing Center of the Southwest Jiaotong University. \n\n# Author contributions \n\nD.G. and X.L. designed the experiments, analyzed the data, and prepared the manuscript. W.X. conducted the experiments, analyzed the data, and participated in the writing of the manuscript. L.J. contributed to the CV analysis. F.R. and J.F., and C.Z. performed the TEM tests. L.F., F.R., and K.W. contributed to the preparation and discussion of the manuscript. All authors commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-09351-2. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks Jiaxi Cui, Amin Ghavaminejad and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1063_1.5132354", + "DOI": "10.1063/1.5132354", + "DOI Link": "http://dx.doi.org/10.1063/1.5132354", + "Relative Dir Path": "mds/10.1063_1.5132354", + "Article Title": "Implicit self-consistent electrolyte model in plane-wave density-functional theory", + "Authors": "Mathew, K; Kolluru, VSC; Mula, S; Steinmann, SN; Hennig, RG", + "Source Title": "JOURNAL OF CHEMICAL PHYSICS", + "Abstract": "The ab initio computational treatment of electrochemical systems requires an appropriate treatment of the solid/liquid interfaces. A fully quantum mechanical treatment of the interface is computationally demanding due to the large number of degrees of freedom involved. In this work, we develop a computationally efficient model where the electrode part of the interface is described at the density-functional theory (DFT) level, and the electrolyte part is represented through an implicit solvation model based on the Poisson-Boltzmann equation. We describe the implementation of the linearized Poisson-Boltzmann equation into the Vienna Ab initio Simulation Package, a widely used DFT code, followed by validation and benchmarking of the method. To demonstrate the utility of the implicit electrolyte model, we apply it to study the surface energy of Cu crystal facets in an aqueous electrolyte as a function of applied electric potential. We show that the applied potential enables the control of the shape of nullocrystals from an octahedral to a truncated octahedral morphology with increasing potential. Published under license by AIP Publishing.", + "Times Cited, WoS Core": 829, + "Times Cited, All Databases": 865, + "Publication Year": 2019, + "Research Areas": "Chemistry; Physics", + "UT (Unique WOS ID)": "WOS:000513157600004", + "Markdown": "# \n\n# Implicit self-consistent electrolyte model in plane-wave density-functional theory EP \n\nCite as: J. Chem. Phys. 151, 234101 (2019); https://doi.org/10.1063/1.5132354 \nSubmitted: 16 October 2019 . Accepted: 23 October 2019 . Published Online: 16 December 2019 \n\nKiran Mathew , V. S. Chaitanya Kolluru , Srinidhi Mula , Stephan N. Steinmann , and Richard G. Hennig \n\n# COLLECTIONS \n\n![](images/49e3816843b7436e1e530928b104383ab2b94d045e7f674fde0a422bd8dbcdb4.jpg) \n\nThis paper was selected as an Editor’s Pick \n\n$\\circledcirc$ 2019 Author(s). \n\n# Implicit self-consistent electrolyte model in plane-wave density-functional theory EP \n\nCite as: J. Chem. Phys. 151, 234101 (2019); doi: 10.1063/1.513235 Submitted: 16 October 2019 $\\cdot\\cdot$ Accepted: 23 October 2019 • Published Online: 16 December 2019 \n\n# Kiran Mathew,1,2,a) V. S. Chaitanya Kolluru,2,3,a) $\\textcircled{1}$ Srinidhi Mula,2,3 Stephan N. Steinmann,4 and Richard G. Hennig2,3,b) \n\n# AFFILIATIONS \n\n1 Department of Materials Science and Engineering, Cornell University, Ithaca, New York 14853, USA \n2Department of Materials Science and Engineering, University of Florida, Gainesville, Florida 32611, USA \n3Quantum Theory Project, University of Florida, Gainesville, Florida 32611, USA \n4University Lyon, Ecole Normale Supérieure de Lyon, CNRS, Université Lyon 1, Laboratoire de Chimie UMR 5182, 46 allée d’Italie, \nF-69364 Lyon, France \n\na)Contributions: K. Mathew and V. S. C. Kolluru contributed equally to this work. b)Electronic mail: rhennig@ufl.edu \n\n# ABSTRACT \n\nThe ab initio computational treatment of electrochemical systems requires an appropriate treatment of the solid/liquid interfaces. A fully quantum mechanical treatment of the interface is computationally demanding due to the large number of degrees of freedom involved. In this work, we develop a computationally efficient model where the electrode part of the interface is described at the density-functional theory (DFT) level, and the electrolyte part is represented through an implicit solvation model based on the Poisson-Boltzmann equation. We describe the implementation of the linearized Poisson-Boltzmann equation into the Vienna $A b$ initio Simulation Package, a widely used DFT code, followed by validation and benchmarking of the method. To demonstrate the utility of the implicit electrolyte model, we apply it to study the surface energy of Cu crystal facets in an aqueous electrolyte as a function of applied electric potential. We show that the applied potential enables the control of the shape of nanocrystals from an octahedral to a truncated octahedral morphology with increasing potential. \n\nPublished under license by AIP Publishing. https://doi.org/10.1063/1.5132354., \n\n# I. INTRODUCTION \n\nInterfaces between dissimilar systems are ubiquitous in nature and frequently encountered and employed in scientific and engineering applications. Of particular interest are solid/liquid interfaces that form the crux of many technologically essential systems such as electrochemical interfaces,1– corrosion, lubrication, and nanoparticle synthesis.4–6 A comprehensive understanding of the behavior and properties of such systems requires a detailed microscopic description of the solid/liquid interfaces. \n\nGiven the heterogeneous nature and the complexities of solid/liquid interfaces,7 experimental studies often need to be supplemented by theoretical undertakings. A complete theoretical investigation of such an interface based on an explicit description of the electrolyte and solute involves solving systems of nonlinear equations with a large number of degrees of freedom, which quickly becomes prohibitively expensive even when state-of-the-art computational resources are employed.8 This calls for the development of efficient and accurate implicit computational frameworks for the study of solid/liquid interfaces.8–14 \n\nWe have previously developed a self-consistent implicit solvation model15,16 that describes the dielectric screening of a solute embedded in an implicit solvent, where the solute is described by density-functional theory (DFT). We implemented this solvation model into the widely used DFT code VASP.17 This software package, VASPsol, is freely available under the open-source Apache License, Version 2.0 and has been used by us and others to study the effect of the presence of solvent on a number of materials and processes, such as the catalysis of ketone hydrogenation,18 ionization of sodium superoxide in sodium batteries,19 the chemistry at electrochemical interfaces,20,21 hydrogen adsorption on platinum surfaces,22 the surface stability and phase diagram of solvated mica,23 etc.24,25 \n\n![](images/2ffe661396bea0a780d4934624c1cccc5963486a581586b718ec5e6583ac280d.jpg) \nFIG. 1. Spatial decomposition of the solid/electrolyte system into the solute, interface, and electrolyte regions for an fcc Pt(111) surface embedded in an electrolyte with a relative permittivity of $\\epsilon_{r}=78.4$ and monovalent cations and anions with a concentration of 1M. The solute is described by density-functional theory, and the electrolyte is described by an implicit solvation model. The interface region is formed self-consistently as a functional of the electronic density of the solute. All properties are shown as a percentage of their maximum absolute value. The inset shows the relatively invisible peak in the Hartree potential at the interface. \n\nIn this work, we describe the extension of our solvation model VASPsol15,16 to include the effects of mobile ions in the electrolyte through the solution of the linearized Poisson-Boltzmann equation and then apply the method to electrochemical systems to demonstrate the power of this approach. Figure 1 illustrates how the solid/electrolyte system is divided into spatial regions that are described by the explicit DFT and the implicit solvent. This solvation model allows for the description of charged systems and the study of the electrochemical interfacial systems under applied external voltage. Section II outlines the formalism and presents the derivation of the energy expression. Section III describes the details of the implementation, and Sec. IV validates the method against previous computational studies of electrochemical systems. Finally, in Sec. V, we apply the approach to study how an applied electric potential can control the equilibrium shape of $\\mathrm{c}_{\\mathrm{u}}$ nanocrystals. \n\n# II. THEORETICAL FRAMEWORK \n\nOur solvation model couples an implicit description of the electrolyte to an explicit quantum-mechanical description of the solute. The implicit solvation model incorporates the dielectric screening due to the permittivity of the solvent and the electrostatic shielding due to the mobile ions in the electrolyte. The solute is described explicitly using DFT. \n\nTo obtain the energy of the combined solute/electrolyte system, we spatially divide the material system into three regions: (i) the solute that we describe explicitly using DFT, (ii) the electrolyte that we describe using the linearized Poisson-Boltzmann equation, and (iii) the interface region that electrostatically couples the DFT and Poisson-Boltzmann equation. Figure 1 illustrates the regions for a Pt(111) surface embedded in a 1M aqueous electrolyte. The interface between the electrolyte and the solute system is formed self-consistently through the electronic density, and the interaction between the electrolyte and the solute is described by the electrostatic potential as explained in Sec. II A. \n\n# A. Total energy \n\nWe define the interface region between the solute and the electrolyte using the electronic charge density of the solute, $n(\\vec{r})$ . The electrolyte occupies the volume of the simulation cell where the solute’s electronic charge density is essentially zero. In the interface region where the electronic charge density increases rapidly from zero toward the change from their values inside of the solute, the properties of the implicit solvation model, e.g., the permittivity, $\\epsilon$ , and the Debye screening length, $\\lambda_{\\mathrm{D}}$ , change from their bulk values of the electrolyte to the vacuum values in the explicit solute region. The scaling of the electrolyte properties is given by a shape function,10,15,26–28 \n\n$$\n\\zeta\\left(n(\\vec{r})\\right)=\\frac{1}{2}\\mathrm{erfc}\\Bigg\\{\\frac{\\log(n/n_{c})}{\\sigma\\sqrt{2}}\\Bigg\\}.\n$$ \n\nFollowing our previous work15 and the work by Arias et al.,10,26–28 the total free energy, $A$ , of the system consisting of the solute and electrolyte is expressed as \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\cal A}\\big[n(\\vec{r}),\\phi(\\vec{r})\\big]={\\cal A}_{\\mathrm{TXC}}\\big[n(\\vec{r})\\big]+\\int\\phi(\\vec{r})\\rho_{s}(\\vec{r})d^{3}r-\\int\\epsilon(\\vec{r})\\frac{|\\nabla\\phi|^{2}}{8\\pi}d^{3}r}}\\\\ {{\\displaystyle~+\\int\\frac12\\phi(\\vec{r})\\rho_{\\mathrm{ion}}(\\vec{r})d^{3}r+{\\cal A}_{\\mathrm{cav}}+{\\cal A}_{\\mathrm{ion}},~(2)}}\\end{array}\n$$ \n\nwhere $A_{\\mathrm{TXC}}$ is the kinetic and exchange-correlation contribution from DFT, $\\phi$ is the net electrostatic potential of the system, and $\\rho_{s}$ and $\\rho_{\\mathrm{ion}}$ are the total charge density of the solute and the ion charge density of the electrolyte, respectively. \n\nThe total solute charge density, $\\rho_{s}$ , is the sum of the solute electronic and nuclear charge densities, $n(\\vec{r})$ and $N(\\vec{r})$ , respectively, \n\n$$\n\\rho_{\\mathrm{s}}\\big(\\vec{r}\\big)=n\\big(\\vec{r}\\big)+N\\big(\\vec{r}\\big).\n$$ \n\nThe ion charge density of the electrolyte, $\\rho_{\\mathrm{ion}}$ , is given by \n\n$$\n\\rho_{\\mathrm{ion}}(\\vec{r})=\\sum_{i}q z_{i}c_{i}(\\vec{r}),\n$$ \n\nwhere $c_{i}$ is the concentration of ionic species i, $z_{i}$ denotes the formal charge, and $q$ is the elementary charge. The concentration of ionic species, $c_{i}$ , is given by a Boltzmann factor of the electrostatic energy that is modulated in the interface region by the shape function, $\\zeta(n(\\vec{r}))$ , \n\n$$\n{c_{i}}\\left(\\vec{r}\\right)=\\zeta[n(\\vec{r})]{c_{i}^{0}}\\exp\\left(\\frac{-z_{i}q\\phi(\\vec{r})}{k_{\\mathrm{B}}T}\\right),\n$$ \n\nwhere $c_{i}^{0}$ is the bulk concentration of ionic species $i,\\ k_{\\mathrm{B}}$ is the Boltzmann constant, and $T$ is the temperature. \n\nThe relative permittivity of the electrolyte, $\\epsilon(\\vec{r})$ , is assumed to be a local functional of the electronic charge densit(y o)f the solute and modulated by the shape function,10,15,26–28 \n\n$$\n\\epsilon\\big(n(\\vec{r})\\big)=1+\\big(\\epsilon_{\\mathrm{b}}-1\\big)\\zeta\\big(n(\\vec{r})\\big),\n$$ \n\nwhere $\\epsilon_{\\mathrm{b}}$ is the bulk relative permittivity of the solvent. \n\nThe cavitation energy, $A_{\\mathrm{{cav}}}$ , describes the energy required to form the solute cavity inside the electrolyte and is given by \n\n$$\nA_{\\mathrm{cav}}=\\tau\\int|\\nabla\\zeta(n(\\vec{r}))|d^{3}r,\n$$ \n\nwhere the effective surface tension parameter $\\tau$ describes the cavitation, the dispersion, and the repulsion interaction between the solute and the solvent that are not captured by the electrostatic terms.13 \n\nIn comparison with our previous solvation model,15 the main changes to the free energy expression are the inclusion of the electrostatic interaction of the ion charge density in the electrolyte with the system’s electrostatic potential, $\\phi$ , and the nonelectrostatic contribution to the free energy from the mobile ions in the electrolyte, $A_{\\mathrm{ion}}$ . In our work, we assume this nonelectrostatic contribution from the ions to consist of just the entropy term, \n\n$$\nA_{\\mathrm{ion}}=k_{B}T S_{\\mathrm{ion}},\n$$ \n\nwhere $S_{\\mathrm{ion}}$ is the entropy of mixing of the ions in the electrolyte, which for small electrostatic potentials can be approximated to first order as29 \n\n$$\n\\begin{array}{r l r}&{}&{S_{\\mathrm{{ion}}}=\\int\\sum_{i}c_{i}\\ln\\left({\\frac{c_{i}}{c_{i}^{0}}}\\right)d^{3}r}\\\\ &{}&{~\\approx-\\int\\sum_{i}c_{i}{\\frac{z_{i}q\\phi}{k_{B}T}}d^{3}r.}\\end{array}\n$$ \n\n# B. Minimization \n\nTo obtain the stationary point of the free energy, $A$ , given by Eq. (2), we set the first order variations of the free energy with respect to the system potential, $\\phi$ , and the electronic charge density, $n(r)$ , to zero.10,15,26–28 Taking the variation of $A[n({\\vec{r}}),\\phi({\\vec{r}})]$ with respect to the electronic charge density, $n(\\vec{r})$ , yield[s t(he)typ(ic)a]l Kohn-Sham Hamiltonian30 with the following a(⃗d)ditional term in the local part of the potential: \n\n$$\nV_{\\mathrm{solv}}=\\frac{\\delta\\epsilon(n)}{\\delta n}\\frac{|\\nabla\\phi|^{2}}{8\\pi}+\\phi\\frac{\\delta\\rho_{\\mathrm{ion}}}{\\delta n}+\\tau\\frac{\\delta|\\nabla\\zeta|}{\\delta n}+k_{B}T\\frac{\\delta S_{\\mathrm{ion}}}{\\delta n}.\n$$ \n\nTaking the variation of $A\\big[n\\big(\\vec{r}\\big),\\phi\\big(\\vec{r}\\big)\\big]$ with respect to $\\phi(\\vec{r})$ yields the generalized Poisson-Boltzmann equation, \n\n$$\n\\vec{\\nabla}\\cdot\\epsilon\\vec{\\nabla}\\phi=-\\rho_{s}-\\rho_{\\mathrm{ion}},\n$$ \n\nwhere $\\epsilon(n(r))$ is the relative permittivity of the solvent as a local functional of the electronic charge density. \n\nWe further simplify the system by considering the case of electrolytes with only two types of ions present, whose charges are equal \n\nand opposite, i.e., $c_{1}^{0}=c_{2}^{0}=c^{0}$ and $z_{1}=-z_{2}=z$ . Then, the ion charge density of the electrolyte becomes29 \n\n$$\n\\begin{array}{r l}&{\\rho_{\\mathrm{ion}}=\\zeta\\big[n(\\vec{r})\\big]q z c^{0}\\bigg[\\exp\\bigg(\\displaystyle\\frac{-z q\\phi}{k_{B}T}\\bigg)-\\exp\\bigg(\\displaystyle\\frac{z q\\phi}{k_{B}T}\\bigg)\\bigg]}\\\\ &{\\quad\\quad\\quad=-2\\zeta\\big[n(\\vec{r})\\big]q z c^{0}\\sinh\\bigg(\\displaystyle\\frac{z q\\phi}{k_{B}T}\\bigg),}\\end{array}\n$$ \n\nand the Poisson-Boltzmann equation becomes \n\n$$\n\\vec{\\nabla}\\cdot\\epsilon\\vec{\\nabla}\\phi=-\\rho_{s}+2\\zeta\\bigl[n\\bigl(\\vec{r}\\bigr)\\bigr]q z c^{0}\\sinh\\biggl(\\frac{z q\\phi}{k_{B}T}\\biggr).\n$$ \n\nFor small arguments $\\begin{array}{r}{x\\ =\\ \\frac{z q\\phi}{k_{B}T}\\ll1}\\end{array}$ , $\\sinh(x)\\to x$ and we obtain the linearized Poisson-Boltzman equation \n\n$$\n\\vec{\\nabla}\\cdot\\epsilon\\vec{\\nabla}\\phi-\\kappa^{2}\\phi=-\\rho_{s}\n$$ \n\nwith \n\n$$\n\\kappa^{2}=\\zeta\\big[n\\big(\\vec{r}\\big)\\big]\\left(\\frac{2c^{0}z^{2}q^{2}}{k_{B}T}\\right)=\\zeta\\big[n\\big(\\vec{r}\\big)\\big]\\frac{1}{\\lambda_{\\mathrm{D}}^{2}},\n$$ \n\nwhere $\\lambda_{\\mathrm{D}}$ is the Debye length that characterizes the dimension of the electrochemical double layer. \n\nThe linearized Poisson-Boltzmann equation given by Eqs. (14) and (15) and the additional local potential, $V_{\\mathrm{solv}};$ , of Eq. (10) define our implicit electrolyte model. This model has four key approximations: (i) The ionic entropy term of Eq. (9) treats the ionic solution as an ideal system and assumes that any interactions between the ions are small compared to $k_{B}T.$ (ii) The cations and anions of the electrolyte have equal and opposite charges, simplifying the PoissonBoltzmann equation. (iii) The electrostatic potential in the electrolyte region is small such that $z q\\Phi\\ll k_{B}T,$ , which leads to the linear approximation of the Poisson-Boltzmann Eq. (14). To be quantitative, arguments to the sinh function in Eq. (13) of less than 0.25 lead to errors below $1\\%$ . Hence, in the region where the shape function is unity (and thus $\\vec{\\nabla}\\cdot\\epsilon\\approx0)$ , charge excesses of up to $0.5~c^{0}$ are still faithfully reprod∇u⋅ced.≈(iv) The ions are treated as point charges. The finite size of the ions in solution would limit their maximum concentration at the interface. These four approximations could be overcome and will be considered in future extensions of the VASPsol model. \n\n# III. IMPLEMENTATION \n\nWe implement the implicit electrolyte model described above into the widely used DFT software Vienna $A b$ initio Software Package (VASP).17 VASP is a parallel plane-wave DFT code that supports both ultrasoft pseudopotentials31,32 and the projector-augmented wave (PAW)33 formulation of pseudopotentials. Our software module, VASPsol, is freely distributed as an open-source package and hosted on GitHub at https://github.com/henniggroup/VASPsol.16 \n\nThe main modifications in the code are the evaluation of the additional contributions to the total energy and the local potential, given by Eqs. (2) and (10), respectively. Corrections to the local potential require the solution of the linearized Poisson-Boltzmann equation given by Eq. (13) in each self-consistent iteration. Our implementation solves the equation in reciprocal space and makes efficient use of fast Fourier transformations (FFTs).15 This enables our implementation to be compatible with the Message Passing Interface (MPI) and to take advantage of the memory layout of VASP. We use a preconditioned conjugate gradient algorithm to solve the linearized Poisson-Boltzmann equation with the preconditioner $\\left(\\boldsymbol{G}^{2}+\\kappa^{2}\\right)^{-1}$ , where $G$ is the magnitude of the reciprocal lattice vector and $\\kappa^{2}$ is the inverse of the square of the Debye length, $\\lambda_{D}$ . \n\nThe solution of the linearized Poisson-Boltzmann Eq. (13) provides a natural reference electrostatic potential by setting the potential to zero in the bulk of the electrolyte. However, planewave DFT codes, such as VASP, implicitly set the average electrostatic potential in the simulation cell to zero, not the potential in the electrolyte region. For simplicity, we do not modify the VASP reference potential but provide the shift in reference potential that needs to be added to the Kohn Sham eigenvalues and the Fermi level. Furthermore, the shift of the electrostatic potential to align the potential in the electrolyte region to zero, or to any other value, modifies the energy of the system. This energy change is given by $\\Delta E_{\\mathrm{ref}}=n_{\\mathrm{electrode}}$ $\\Delta U_{\\mathrm{ref}},$ where $n_{\\mathrm{electrode}}$ is the net charge of the electrode slab and $\\Delta U_{\\mathrm{ref}}$ is the change in reference potential, i.e., the shift to align the potential in the electrolyte region to zero. \n\nTo validate the change in reference potential, Fig. 2 shows the grand-canonical electronic energy, $F(U)$ , as a function of the applied potential, $U_{:}$ , of the $\\mathrm{Pt}$ (111) electrode slab. The grandcanonical electronic energy, $F,$ , is the Legendre transformation of the free energy, A, of the system, $F(U)=A(n)\\:-\\:n_{\\mathrm{electrode}}U,$ , and is always lowered when charge is added or re−moved from the neutral slab. The grand canonical energy, $F,$ exhibits the expected quadratic behavior34 and the maximum at the neutral slab when the energy change $\\Delta E_{\\mathrm{ref}}$ due to the change in reference potentials is included. \n\n![](images/cea3695f17b6cece89751a9bfde2d44c31f8fcbf9f01e9f031d8388e9955b089.jpg) \nFIG. 2. The grand-canonical electronic energy, $F(U)$ , of a charged Pt(111) slab relative to the neutral slab as a function of the electrode potential $U$ . The grand canonical energy displays the maximum correctly at the neutral slab when the reference electrostatic potential is chosen such that the potential is zero in the bulk of the electrolyte and the necessary correction due to the reference potential $\\Delta E_{\\mathrm{ref}}=n_{\\mathrm{electrode}}$ $\\Delta U_{\\mathsf{r e f}}$ is included in the energy. \n\n# IV. VALIDATION \n\nWe further validate the model by comparison with existing experimental and computational data. First, we compute the potential of zero charge (PZC) of various metallic slabs and compare them against the experimental values. Second, we calculate the surface charge density of a $\\mathrm{Pt}(111)$ slab as a function of the applied external potential and compare the resulting value of the double-layer capacitance with previous computations and experiments. \n\nThe DFT calculations for these two benchmarks and the following application are performed with VASP and the VASPsol module using the PAW formalism describing the electron-ion interactions and the PBE approximation for the exchangecorrelation functional.17,33,36 The Brillouin-zone integration employs an automatic mesh with $50k$ -points per inverse Ångstrom with only one $k$ -point in the direction perpendicular to the slab. \n\nWe consider an electrolyte that consists of an aqueous solution of monovalent anions and cations of 1M concentration. At room temperature, this electrolyte has a relative permittivity of $\\epsilon_{\\mathrm{b}}=78.4$ and a Debye length of $\\lambda_{\\mathrm{D}}=3.04\\mathrm{~\\AA~}$ . The parameters for the shape function, $\\dot{\\zeta}(n(\\vec{r})\\big)$ , are taken from Refs. 15 and 28 to be $n_{\\mathrm{c}}=0.{\\dot{0}}025{\\dot{\\mathrm{A}}}^{-1}$ and $\\sigma=0.6$ .) \n\nTo properly resolve the interfacial region between the solute and the implicit electrolyte region and to obtain accurate values for the cavitation energy requires a high plane-wave basis set cutoff energy of $1000~\\mathrm{eV}$ . However, in our validation calculations and applications, we observe that the contribution of the cavitation energy to the solvation energies is negligibly small. We, therefore, set the effective surface tension parameter $\\tau=0$ for all following calculations. This also removes the requirement for such a high cutoff energy, and we find that a cutoff energy of $600~\\mathrm{eV}$ results in converged surface energies and PZC. \n\nTo change the applied potential, we adjust the electron count and then determine the corresponding potential from the shift in electrostatic potential, as reflected in the shift in the Fermi level. This takes advantage of the fact that the electrostatic potential goes to zero in the electrolyte region for the solution of the PoissonBoltzmann equation, providing a reference for the electrostatic potential. \n\nFigure 3 compares the PZC for Cu, Ag, and Au surface facets calculated with the implicit electrolyte model as implemented in VASPsol with experimental data. The electrode PZC is defined as the electrostatic potential of a neutral metal electrode and is given by the Fermi energy measured relative to the reference potential. A natural choice of reference for the implicit electrolyte model is the electrostatic potential in the bulk of the electrolyte, which is zero in any solution of the Poisson-Boltzmann equation. In experiments, the reference is frequently chosen as the standard-hydrogen electrode (SHE). The dashed line in Fig. 3 presents the fit of $U^{\\mathrm{{pred}}}=U^{\\mathrm{{exp}}}+\\Delta U_{\\mathrm{{SHE}}}^{\\mathrm{{pred}}}$ to obtain the shift, $\\Delta U_{\\mathrm{SHE}}^{\\mathrm{pred}}$ , between the experimenta=l and the computed PZC, i.e., the potential of the SHE for our electrolyte model. The resulting USprHeEd 4.6 V compares well with the previously reported computed value of $4.7\\mathrm{V}$ for a similar solvation model.28 \n\nFigure 4 shows the calculated surface charge density, $\\sigma_{:}$ , of a $\\mathrm{Pt}(111)$ surface as a function of applied electrostatic potential, $U$ . We find that the PZC for the $\\mathrm{Pt}(111)$ electrode is $0.85\\mathrm{V}$ , in good agreement with previous computational studies.26,28 However, this value is at the high end of the experimentally reported results.35,37 This discrepancy is likely due to adsorption on $\\mathrm{Pt}(111)$ . The work by Sekong and Groß shows that $\\mathrm{Pt}(111)$ is covered by hydrogen at potentials below $0.5\\mathrm{V}$ , followed by the so-called double layer region between 0.5 and $0.75\\mathrm{V}$ with no adsorbates present and OH adsorption at more positive potentials.25 The presence of adsorbates in the experiments alters the PZC and precludes a direct comparison with our calculations. \n\n![](images/05827fcbf482bde9d2a5b0d7b12283c113235c555e3b17f67778710806460623.jpg) \nFIG. 3. Comparison between the computed and the experimental potential of zero charge (PZC) with respect to the standard hydrogen electrode (SHE). The dashed line is a fit of $U^{\\mathrm{{pred}}}=U^{\\mathrm{{exp}}}+\\Delta U_{\\mathrm{{SHE}}}^{\\mathrm{{pred}}}$ to determine the theoretical potential of the SHE, $\\Delta U_{\\mathrm{SHE}}^{\\mathrm{pred}}$ . The e=xperimental values are taken from Ref. 35. \n\nThe linear slope of $\\sigma(U)$ is the double-layer capacitance. Fitting a quadratic polynomial to the data and evaluating the slope at the PZC yields a double-layer capacitance for the $\\mathrm{Pt}(111)$ surface at 1M concentration of $14\\mu\\mathrm{F}/\\mathrm{cm}^{2}$ . This agrees perfectly with the previously reported computed result28 and is close to the experimental value of 20 μF/cm2.37 \n\nOur implementation of the electrolyte model neglects the finite volume of the ions in the electrolyte. Hence, at larger applied potentials, the model may predict unphysically large ion concentrations to screen the surface charge. To understand how this approximation limits the applied potential, we perform calculations on a $\\mathrm{Cu}(111)$ slab in an electrolyte with 2M concentration for a range of applied potentials from $^{-3}$ to $+3{\\mathrm{~V~}}$ . \n\n![](images/e464cbe4a62736bb6d8d25c11de460b2a9bfa069cae862497bae688f17f8a9ba.jpg) \nFIG. 4. Surface charge density of the $\\mathsf{P t}(111)$ surface as a function of applied electrostatic potential computed with the implicit electrolyte module, VASPsol. The slope of the curve determines the capacitance of the dielectric double layer. \n\nFigure 5 shows the extrema of the net ion concentration in the double-layer region as a function of the applied potential (written by VASPsol into the file RHOION). The negative and positive concentrations correspond to excess cations and anions near the surface, respectively. For a large range of potentials from $^{-2}$ to $+3{\\mathrm{~V~}}$ , the net ion concentration depends nearly linear on the applied potential. At negative potentials below $-2\\mathrm{V}$ , we observe that electrons leak from the slab into the electrolyte−region, rendering the results of the electrolyte model unphysical. Hence, care should be taken when utilizing the model at large negative potentials. \n\nThe inset of Fig. 5 illustrates the average net ion concentration along the direction perpendicular to the $\\mathrm{Cu}(111)$ surface for an applied potential of $-1\\mathrm{~V~}$ . The ion concentration decays exponentially away from the−solid-liquid interface and approaches zero in the bulk electrolyte. We selected an electrolyte region of $30\\textup{\\AA}$ to illustrate the need to converge the results with respect to the size of the electrolyte domain. Here, the size is not quite sufficient to reach a negligible ion concentration. While this does not affect the considered extrema of the ion concentration, care must be taken to ensure convergence of the results with the size of the electrolyte region. As general guidance, an electrolyte region $>10\\lambda$ should suffice.38 \n\nAt a large applied potential of $+3{\\mathrm{~V~}}$ , we find a net ion concentration of $0.2\\mathrm{M}$ , which is $10\\%$ of the electrolyte concentration, far from the $50\\%$ excess that would introduce a $1\\%$ error, as discussed following Eq. (14). Here, the concentrations of anions and cations are 2.1 and 1.9M, respectively, and the error introduced by the linear approximation to the sinh function is less than $0.1\\%$ . Thus, even for a considerable potential of $+3\\mathrm{V}$ , the linear electrolyte model does not result in unphysically large ion concentrations. \n\nFinally, we validate the accuracy of the implemented analytic force evaluation. As an example, we have chosen the adsorption of a Na atom on the $\\mathrm{Au}(111)$ surface. The surface charge was set to \n\n![](images/4dd9048de2f1709ff1b36fc1d046bbcf6bdb51cdb4bf268b928b5181bc187208.jpg) \nFIG. 5. The extrema of the ion concentrations over the potential range of $^{-3}$ to $^{+3}$ V relative to the PZC in an electrolyte with an ion concentration of 2M. T−he negative and positive concentrations correspond to an excess of cations and anions, respectively, in the double layer. The solid blue line is a linear fit between 1 and $+2V,$ , indicating the large linear potential range. The inset shows the xy averaged ion concentration profile along the z-direction at a potential of $-1\\ V;$ the central region corresponds to the solute slab with zero ion concentration−. \n\n![](images/afc82573e344b120ad26f8e3d0d5a8a295b262ae6da5b11099c7ce8ba0b2447f.jpg) \nFIG. 6. Analytical gradient and relative energy as a function of the distance of a Na ion from the Au(111) surface, at a potential of about $-1.9\\vee$ vs the potential of the SHE. The plane-wave cutoff of $400{\\mathsf{e V}}$ leads to nume−rical noise, which disappears at $600{\\mathsf{e V}}.$ \n\n$0.4~e^{-}$ for the symmetric $\\mathtt{p}(2\\times2)$ surface, corresponding to an electrochemical potential of abou×t $-1.9{\\mathrm{V}}$ vs the SHE, while the neutral ${\\mathrm{Na}}@{\\mathrm{Au}}(111)$ surface corresponds to a potential of $-2.6\\mathrm{V}.$ . Figure 6 shows that the agreement between the analytical gradient and the minimum for the energy is excellent, provided a sufficiently high cutoff energy of $600~\\mathrm{eV}$ is used. \n\n# V. CRYSTAL SHAPE CONTROL BY APPLIED POTENTIAL \n\nThe implicit electrolyte model, VASPsol, enables the study of electrode surfaces in realistic environments and under various conditions, such as of an electrode immersed in an electrolyte with an applied external potential. To illustrate the utility of the solvation model, we determine how an applied potential changes the equilibrium shape of a Cu crystal in a 1M electrolyte. The crystal shape is controlled by the surface energies. We show that the surface energies are sensitive to the applied potential and that each facet follows different trends, leading to opportunities for the practical control of the shape of nanocrystals. \n\nUsing the MPInterfaces framework,40 we construct slabs of minimum $10\\mathrm{~\\AA~}$ thickness for the (111), (100), (110), (210), (221), (311), and (331) facets of Cu. The different facets for Cu are chosen based on the crystal facets included in the MaterialsProject database.39 We calculate the surface energy of each slab in vacuum and electrolyte by relaxing the top and bottom layers and keeping the middle layers of atoms fixed to their bulk positions. We employ a vacuum spacing of $30\\mathrm{~\\AA~}$ to ensure that the electrostatic interactions between periodic images of the slabs are negligibly small. From the surface energies, we determine the resulting shape using the Wulff construction as implemented in the pymatgen framework. \n\nFigure 7 compares the crystal shape of Cu in vacuum obtained in our calculations with that in MaterialsProject. The MaterialsProject calculations used a cutoff energy of $400\\ \\mathrm{eV}$ and a vacuum spacing of $10\\mathrm{~\\AA~}$ , both of which are lower than the cutoff energy of $600~\\mathrm{eV}$ and the vacuum spacing of $30\\mathrm{~\\AA~}$ used in this work. We find that our predicted surface energies agree with those in MaterialsProject within $2\\%$ for all the facets. However, we note that even such small deviations in surface energies matter for the details of the crystal shape, where the high index (310) and (221) facets do not show up in our calculation of the equilibrium crystal shape of Cu. These small but observable deviations demonstrate that the crystal shape is sensitive to small variations in the surface energies. \n\nFor the calculation of the Cu surface energies in the 1M electrolyte, we vary the number of electrons in the slabs and determine the change in the corresponding applied electrostatic potential, as described in Sec. III. We calculate the surface energies for each of the above facets in vacuum over a range of applied potentials of approximately $\\pm1\\ \\mathrm{eV}$ around the corresponding PZC. We then perform a spline i±nterpolation to obtain the surface energies as a function of the applied potential. This transformation enables the comparison of the surface energies for a given applied potential and is made possible by the absolute reference potential provided by the solvation model. From the results, we obtain the equilibrium crystal shape as a function of applied potentials by the Wulff construction. \n\nFor copper, the (111) facets exhibit the lowest surface energy over the whole potential range. Figure 8 shows how the ratios of the surface energies of the copper (hkl) facets relative to the (111) facet vary as a function of applied potential. As expected, the surface energies of all facets systematically increase with potential; however, their ratios relative to the (111) facet decrease. Due to this, the crystal shape changes as a function of applied potential. \n\n![](images/0db94b98f77f92f5cd5d8087c5b42e0d268f987c5a08a30acbae15e533930fcd.jpg) \nFIG. 7. Comparison of the predicted shape of a Cu crystal in vacuum (a) for this work obtained by the Wulff construction using the surface energies of the (100), (110), (111), (210), (221), (311), and (331) facets compared with (b) the MaterialsProject database.39 \n\n![](images/3b11cf9ab574ad948891376c269662eab8214066db4c0f0d6826d06b280b8bb2.jpg) \nFIG. 8. The surface energies, $\\gamma_{h k I}$ , of the various facets of Cu with respect to surface energies, $\\gamma_{111}$ , of the (111) facet as a function of applied potential. The dashed horizontal line indicates the ratio of the (100) and (111) surface energies, $\\gamma_{100}/\\gamma_{111}$ equals $\\sqrt{3}$ , which corresponds to a change in shape from an octahedron to a truncated octahedron. \n\nFigure 9 illustrates the change in crystal shape with increasing applied potential. At negative potentials, the (111) facets dominate and lead to an octahedral shape. With increasing potential, the ratio of the (100) to (111) surface energies decreases sufficiently to lead to a change in shape to a truncated octahedron. The transition occurs around a potential of $-0.56\\mathrm{~V~}$ for Cu. With a further increase in potential, the area of t−he (100) facets increases. Even though the ratios of the surface energies of other facets are also lowered, the change is not sufficient for other facets to show up in the equilibrium crystal shape. \n\nThe prediction for the changes in the equilibrium shape of the Cu crystal as a function of applied electric potential demonstrates the utility of the VASPsol solvation model for computational electrochemistry simulations using density-functional theory. It furthermore provides the opportunity to design nanocrystals of specific shape through the application of an electrostatic potential during growth at a positive applied potential. \n\n![](images/3824ab6526bbd6259e1b8eda2bb88bec8f7634bbd44c54be51a03babdd87edb8.jpg) \nFIG. 9. Variation of the equilibrium crystal shape of Cu with applied electrode potential. The equilibrium shape transitions from an octahedron at negative potentials to a truncated octahedron upon increasing applied potentials. \n\n# VI. CONCLUSIONS \n\nSolid/liquid interfaces between electrodes and electrolytes in electrochemical cells present a complex system that benefits from insights provided by computational studies to supplement and explain experimental observations. We developed and implemented a self-consistent computational framework that provides an efficient implicit description of electrode/electrolyte interfaces within density-functional theory through the solution of the linearized Poisson-Boltzmann equation. The electrolyte model is implemented in the widely used DFT code VASP, and the implementation is made available as a free and open-source module, VASPsol, hosted on GitHub at https://github.com/henniggroup/VASPsol. We showed that this model enables ab initio electrochemistry studies at the DFT level. We validated the model by comparing the calculated electrode potentials of zero charge for various metal electrodes with experimental values and the calculated double-layer capacitance of Pt(111) in a 1M solution to previous calculations and experiments. We tested the validity of the linear approximation at large applied potentials and the accuracy of the analytic expressions for the forces. To illustrate the usefulness of the model and the implementation, we apply the model to determine the equilibrium shape of the Cu crystal as a function of applied electrostatic potential. We predict a change in shape from an octahedron to a truncated octahedron with increasing potential. These calculations illustrate the utility of the implicit VASPsol model for computational electrochemistry simulations. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the National Science Foundation under Award Nos. DMR-1542776, OAC-1740251, and CHE-1665305. This research used computational resources of the Texas Advanced Computing Center under Contract No. TGDMR050028N and of the University of Florida Research Computing Center. Part of this research was performed while the authors were visiting the Institute for Pure and Applied Mathematics (IPAM), which is supported by the National Science Foundation under Grant No. DMS-1440415. S.N.S. thanks the SYSPROD project and AXELERA Pôle de Compétitivité for support (PSMN Data Center). \n\n# REFERENCES \n\n1D. Wang, H. L. Xin, Y. Yu, H. Wang, E. Rus, D. A. Muller, and H. D. Abruña, J. Am. Chem. Soc. 132, 17664 (2010). \n2D.-H. Ha, M. A. Islam, and R. D. Robinson, Nano Lett. 12, 5122 (2012). \n3G. Liu, E. Luais, and J. J. Gooding, Langmuir 27, 4176 (2011). \n4J. J. Choi, C. R. Bealing, K. Bian, K. J. Hughes, W. Zhang, D.-M. Smilgies, R. G. \nHennig, J. R. Engstrom, and T. Hanrath, J. Am. Chem. Soc. 133, 3131 (2011). \n5D. F. Moyano and V. M. Rotello, Langmuir 27, 10376 (2011). \n6T.-F. Liu, Y.-P. Chen, A. A. Yakovenko, and H.-C. Zhou, J. Am. Chem. Soc. 134, 17358 (2012). \n7V. A. Agubra and J. W. Fergus, J. Power Sources 268, 153 (2014). \n$^{8}{\\mathrm{S}}.$ . Ismail-Beigi and T. A. Arias, Comput. Phys. Commun. 128, 1 (2000). \n9J. A. White, E. Schwegler, G. Galli, and F. Gygi, J. Chem. Phys. 113, 4668 (2000). \n$^{10}\\mathrm{S}.$ . A. Petrosyan, A. A. Rigos, and T. A. Arias, J. Phys. Chem. B 109, 15436 (2005). \n11C. J. Cramer and D. G. Truhlar, Acc. Chem. Res. 41, 760 (2008). \n12J. Lischner and T. A. Arias, J. Chem. Phys. B 114, 1946 (2010). \n$^{13}\\mathrm{O}$ . Andreussi, I. Dabo, and N. Marzari, J. Chem. Phys. 136, 064102 (2012). 14S. Ringe, H. Oberhofer, C. Hille, S. Matera, and K. Reuter, J. Chem. Theory Comput. 12, 4052 (2016). \n${}^{15}\\mathrm{K}.$ Mathew, R. Sundararaman, K. Letchworth-Weaver, T. A. Arias, and R. G. Hennig, J. Chem. Phys. 140, 084106 (2014). \n${}^{16}\\mathrm{K}.$ Mathew and R. G. Hennig, “VASPsol - solvation model for the plane wave DFT code VASP,” https://github.com/henniggroup/VASPsol, 2015. \n$^{17}\\mathrm{G}$ . Kresse and J. Furthmüller, Comput. Mater. Sci. 6, 15 (1996). \n$^{18}\\mathrm{C}$ . Michel, J. Zaffran, A. M. Ruppert, J. Matras-Michalska, M. Jedrzejczyk, J. Grams, and P. Sautet, Chem. Commun. 50, 12450 (2014). \n${}^{19}\\mathrm{J}$ . Kim, H. Park, B. Lee, W. M. Seong, H.-D. Lim, Y. Bae, H. Kim, W. K. Kim, K. H. Ryu, and K. Kang, Nat. Commun. 7, 10670 (2016). \n${}^{20}\\mathrm{N}$ . Kumar, K. Leung, and D. J. Siegel, J. Electrochem. Soc. 161, E3059 (2014). 21S. N. Steinmann, C. Michel, R. Schwiedernoch, and P. Sautet, Phys. Chem. Chem. Phys. 17, 13949 (2015). \n$^{22}\\mathrm{S}.$ . Sakong, M. Naderian, K. Mathew, R. G. Hennig, and A. Groß, J. Chem. Phys. 142, 234107 (2015). \n23A. K. Vatti, M. Todorova, and J. Neugebauer, Langmuir 32, 1027 (2016). 24J. D. Goodpaster, A. T. Bell, and M. Head-Gordon, J. Phys. Chem. Let. 7, 1471 (2016). \n$^{25}\\mathrm{S}.$ . Sakong and A. Groß, ACS Catal. 6, 5575 (2016). \n${}^{26}\\mathrm{K}.$ Letchworth-Weaver and T. A. Arias, Phys. Rev. B 86, 075140 (2012). 27R. Sundararaman, D. Gunceler, K. Letchworth-Weaver, and T. A. Arias, JDFTx, http://jdftx.sourceforge.net, 2012. \n${}^{28}\\mathrm{D}$ . Gunceler, K. Letchworth-Weaver, R. Sundararaman, K. A. Schwarz, and T. A. Arias, Modell. Simul. Mater. Sci. Eng. 21, 074005 (2013). \n${}^{29}\\mathrm{K}.$ . A. Sharp and B. Honig, J. Phys. Chem. 94, 7684 (1990). \n30W. Kohn and L. J. Sham, Phys. Rev. 140, A1133 (1965). \n31D. Vanderbilt, Phys. Rev. B 41, 7892 (1990). \n32G. Kresse and D. Joubert, Phys. Rev. B 59, 1758 (1999). \n33P. E. Blöchl, Phys. Rev. B 50, 17953 (1994). \n34E. Santos and W. Schmickler, Chem. Phys. Lett. 400, 26 (2004). \n$^{35}\\mathrm{S}$ . Trasatti and E. Lust, in Modern Aspects of Electrochemistry, edited by R. E. White, J. O. Bockris, and B. E. Conway (Springer US, Boston, MA, 1999), pp. 1–215. \n36J. P. Perdew, K. Burke, and M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996). 37T. Pajkossy and D. Kolb, Electrochim. Acta 46, 3063 (2001). \n38S. N. Steinmann and P. Sautet, J. Phys. Chem. $\\mathrm{~C~}$ 120, 5619 (2016). \n$^{39}\\mathrm{R}.$ . Tran, Z. Xu, B. Radhakrishnan, D. Winston, W. Sun, K. A. Persson, and S. P. Ong, Sci. Data 3, 160080 (2016). \n$^{40}\\mathrm{K}.$ . Mathew, A. K. Singh, J. J. Gabriel, K. Choudhary, S. B. Sinnott, A. V. Davydov, F. Tavazza, and R. G. Hennig, Comput. Mater. Sci. 122, 183 (2016). " + }, + { + "id": "10.1038_s41467-019-09398-1", + "DOI": "10.1038/s41467-019-09398-1", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-09398-1", + "Relative Dir Path": "mds/10.1038_s41467-019-09398-1", + "Article Title": "Additive-free MXene inks and direct printing of micro-supercapacitors", + "Authors": "Zhang, CF; McKeon, L; Kremer, MP; Park, SH; Ronull, O; Seral-Ascaso, A; Barwich, S; Coileáin, CO; McEvoy, N; Nerl, HC; Anasori, B; Coleman, JN; Gogotsi, Y; Nicolosi, V", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Direct printing of functional inks is critical for applications in diverse areas including electrochemical energy storage, smart electronics and healthcare. However, the available printable ink formulations are far from ideal. Either surfactants/additives are typically involved or the ink concentration is low, which add complexity to the manufacturing and compromises the printing resolution. Here, we demonstrate two types of two-dimensional titanium carbide (Ti3C2Tx) MXene inks, aqueous and organic in the absence of any additive or binary-solvent systems, for extrusion printing and inkjet printing, respectively. We show examples of all-MXene-printed structures, such as micro-supercapacitors, conductive tracks and ohmic resistors on untreated plastic and paper substrates, with high printing resolution and spatial uniformity. The volumetric capacitance and energy density of the all-MXene-printed micro-supercapacitors are orders of magnitude greater than existing inkjet/extrusion-printed active materials. The versatile direct-ink-printing technique highlights the promise of additive-free MXene inks for scalable fabrication of easy-to-integrate components of printable electronics.", + "Times Cited, WoS Core": 802, + "Times Cited, All Databases": 841, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000464976500001", + "Markdown": "# Additive-free MXene inks and direct printing of micro-supercapacitors \n\nChuanfang (John) Zhang 1,2, Lorcan McKeon1,3, Matthias P. Kremer 1,2,4, Sang-Hoon Park1,2, Oskar Ronan1,2, Andrés Seral‐Ascaso1,2, Sebastian Barwich1,3, Cormac Ó Coileáin1,2, Niall McEvoy1,2, Hannah C. Nerl $\\textcircled{1}$ 1,3, Babak Anasori5, Jonathan N. Coleman 1,3, Yury Gogotsi 5 & Valeria Nicolosi1,2,4 \n\nDirect printing of functional inks is critical for applications in diverse areas including electrochemical energy storage, smart electronics and healthcare. However, the available printable ink formulations are far from ideal. Either surfactants/additives are typically involved or the ink concentration is low, which add complexity to the manufacturing and compromises the printing resolution. Here, we demonstrate two types of two-dimensional titanium carbide $(\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x})$ MXene inks, aqueous and organic in the absence of any additive or binary-solvent systems, for extrusion printing and inkjet printing, respectively. We show examples of allMXene-printed structures, such as micro-supercapacitors, conductive tracks and ohmic resistors on untreated plastic and paper substrates, with high printing resolution and spatial uniformity. The volumetric capacitance and energy density of the all-MXene-printed microsupercapacitors are orders of magnitude greater than existing inkjet/extrusion-printed active materials. The versatile direct-ink-printing technique highlights the promise of additive-free MXene inks for scalable fabrication of easy-to-integrate components of printable electronics. \n\nThnmeinrioeafctetuhnritinzbegsodohemanseigrnrgeya-etslxtyiobrsltaeig,mepuodlraetvaeibdcetsh1e–l3ed. srHiogonwiceosfvearnd,dvaminactneurd-, facturing of micro-supercapacitors (MSCs), in particular those that can achieve high energy density with a long lifetime or energy harvesting at a high rate, remains a significant challenge4. While elaborate patterning techniques, such as lithography, spray-masking and laser-scribing can partially resolve the problems5–7, the sophisticated processing and inefficient material utilization in these protocols limit the large-scale production of MSCs. In other words, incorporating nanomaterials with excellent charge-storage capability into low-cost manufacturing routes is in high demand. \n\nDirect ink writing of functional materials offers a promising strategy for scalable production of smart electronics with a high degree of pattern and geometry flexibility8–12. Compared with conventional manufacturing protocols, direct ink writing techniques, such as inkjet printing and extrusion printing, allow digital and additive patterning, customization, reduction in material waste, scalable and rapid production, and so on13,14. An important advance for direct ink writing is the incorporation of functional inks with suitable fluidic properties, in particular surface tension and viscosity9,12,13. Substantial progress has been made in the ink writing of various electronic/photonic devices10,12,15,16 based on graphene13–15,17,18, molybdenum disulfide12, black phosphorous16, etc19,20. However, so far only limited success has been reported in achieving both fineresolution printing and high-charge-storage MSC performance8. In addition, in most printable inks, additives (such as surfactants or secondary solvents) are typically used to tune the concentration/rheological properties of the ink, as well as to improve the conductivity of the printed lines. The additional surfactant removal and thermal annealing steps complicate the device manufacturing process. In other words, the formulation of additive-free inks is of significance for a scalable, low-cost, yet efficient printing process. \n\nMXenes are a family of two-dimensional (2D) carbides and nitrides of transition metals (M), where $X$ stands for carbon or nitrogen21. The most extensively studied MXene, titanium carbide $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x},$ where $\\mathrm{T}_{x}$ represents the terminated functional groups) possesses a high electronic conductivity up to ${\\sim}10{,}0005$ $\\mathsf{\\bar{c}m}^{-\\bar{1}}$ and a $\\mathrm{TiO}_{2}$ -like surface22, resulting in ultrahigh volumetric capacitance $(\\sim1500\\mathrm{F}\\mathrm{cm}^{-3})$ in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ hydrogel films and high areal capacitance $(\\sim61\\mathrm{mF}\\mathrm{cm}^{-2},$ ) in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ $\\mathsf{\\breve{M}S C s}^{23-25}$ . While plenty of printed graphene MSCs have been reported with good areal capacitances, but fairly low volumetric capacitances15,18,26, to date, there are just a few reports on inkjet printing of MXenes for sensors and electromagnetic interference shielding27,28. The only reported MXene printing was achieved on a thermal HP printer25, which limits the deposition of the MXene ink on a blank paper with a single pass, and is thus incompatible with most of micro- or nanofabrication procedures, which typically require multiple passes and/or deposits on curved surfaces. For scaling up production and industrial applications of flexible MXene-based devices, a controllable and scalable piezoelectric printing approach, which is compatible with the commercial manufacturing lines, is needed. To date, all-printed MXene MSCs with fine resolution using direct ink printing techniques have yet to be developed. \n\nThe main challenges of realizing precise MXene printing lies either in the MXene ink formulation or the solvent evaporation kinetics, or both. Typically, inkjet printing requires a high ink viscosity within a narrow range $\\left(1{-}20\\mathrm{mPa}{\\cdot}s\\right)$ and a suitable surface tension to ensure a stable jetting of singledroplets9,14,16,29,30. In addition, surface tension has to be matched with the surface energy and texture of the substrate to allow good wetting16. To overcome the “coffee ring” issue9,14, inks are usually mixed with surfactants or polymer stabilizers (e.g., ethyl cellulose)13,15,31, and/or exchanged with low-boiling-point solvents (e.g., terpineol11,14,15 or ethanol14) to rapidly solidify the materials. Electronics printed in this way contain residual surfactants/polymers, which need to be removed either through high-temperature annealing11,15, chemical treatment9,14 or intense pulsed light treatments13. These processes are not compatible with most substrates and are especially impractical for MXenes, which may oxidize upon heating in open air32,33. In addition, MXene nanosheets typically suffer from a quick precipitation in low-boiling-point solvents, limiting the formation of concentrated MXene ink for efficient additive manufacturing. \n\nHere, we report formulation and direct printing of additivefree, concentrated MXene inks, with high printing efficiency and spatial uniformity. Two types of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene inks, aqueous and organic, in the absence of any additives, were designed for extrusion printing and inkjet printing, respectively. The allMXene printed MSCs have exhibited excellent areal capacitance and volumetric capacitance. In addition, the protocols of MXene ink formulations as well as printing are general, i.e., ohmic resistors can be inkjet-printed, suggesting the great potential of this printing platform for scalable manufacturing of nextgeneration electronics and devices. \n\n# Results \n\nSolvent selection criteria. To minimize the amount of defects on the MXene nanosheets, a less aggressive etching method, socalled minimally intensive layer delamination (MILD), is employed in this research (Supplementary Fig. 1)34. The asobtained multi-layered $\\left(\\mathrm{m}-\\right)$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ \"cake\", which swells after multiple washes (Supplementary Fig. 2), was subjected to vigorous manual shaking in water or bath sonication in organic solvent for delamination. Unlike other 2D materials, which typically require the addition of surfactants or polymer stabilizers12,13, the negative electrostatic charge on the hydrophilic $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ nanosheets leads to stable aqueous inks containing clean and predominantly single-layered flakes (Supplementary Figs. 3, 4). On the other hand, by selecting suitable organic solvents with a high polarity and a high dispersion interaction strength (dispersion Hansen solubility parameter)3,35, stable, concentrated MXene organic inks can be formed. It is worth mentioning that solvents, such as methanol, with a low boiling point typically possess a low polarity index, and so poorly disperse MXene nanosheets and thus limit the dispersion stability. While a binarysolvent system with a low boiling point and low-medium polarity index would allow faster evaporation, the MXene ink concentration and, as a result, the printing resolution and efficiency, could be compromised compared with pure organic solvents with a high boiling point/polarity index. These two types of viscous inks are used for direct ink writing, namely, organic inks for inkjet printing and aqueous inks for extrusion printing, such as MSCs (Fig. 1). \n\nFormulation of inkjet-printable MXene organic inks. We start by describing the formulation of inkjet-printable MXene organic inks. Four organic solvents, N-Methyl-2-pyrrolidone (NMP), dimethyl sulfoxide (DMSO), dimethylformamide (DMF) and ethanol that disperse MXene forming stable colloidal solutions35 were used to delaminate the nanosheets and give MXene inks (Fig. 2a, Supplementary Figs. 5, 6), as detailed in Methods. Transmission electron microscopy (TEM) images and electron diffraction (ED) of the MXene nanosheets from the ink are shown in Fig. 2b and inset as well as Supplementary Fig. 6b–f. The MXene inks were found to be composed of monolayers to few-layered nanosheets. From the TEM histogram, the flakes in various organic inks possess a mean lateral dimension in the range of ${\\sim}1{-}2.1\\upmu\\mathrm{m}$ (Supplementary Fig. 7). The atomic force microscopy (AFM) analysis further confirms that the suspended nanosheets are predominantly single-layered (Fig. 2c, d), agreeing with previous reports24. \n\n![](images/b7e5f7036c36101c64e3777f7b1e990a5ef3ebd5aee1208f6e3f93ccd5dcd87b.jpg) \nFig. 1 Schematic illustration of direct MXene ink printing. The $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ organic inks, i.e., $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ -ethanol (molecules shown in the bottom panel) are used for inkjet printing of various patterns, such as MSCs, MXene letters, ohmic resistors, etc. The $\\mathsf{T i}_{3}\\mathsf{C}_{2}\\mathsf{T}_{x}$ aqueous inks (with water molecules shown in the top panel) are designed for extrusion printing of MSCs and other patterns on flexible substrates. As for the MSCs, a gel electrolyte made of ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ -PVA, was coated onto the as-printed patterns and dried naturally, forming all-MXene printed, solid-state MSCs \n\n![](images/789c437dd4650f25b913d219b31a56c962ff050322dc55d62d705c4d52d7e533.jpg) \nFig. 2 Characterization of MXene organic inks. a Photos of various MXene organic inks. b TEM image of MXene nanosheets from NMP ink. Inset shows the selected area electron diffraction (SAED) pattern. Scale bar $=200\\mathsf{n m}$ and $=21/\\mathsf{n m}$ in the inset. c AFM image and d the corresponding height profiles along the lines in $\\mathbf{\\eta}(\\bullet)$ . e Viscosity plotted as a function of shear rates for different MXene organic inks. The data were fitted according to the Ostwald-de Waele power law: $\\eta=k\\gamma^{n-1}$ , where $k$ and $\\mathfrak{n}$ are the consistency and shear-thinning index, respectively46. f Scheme of fine resolution of inkjet printing of MXene organic inks. The curved green lines represent MXene nanosheets while the arrows indicate the inward (blue) and outward (red) flows of the droplet. Three critical steps, namely, stable jetting, good substrate wetting and droplet drying, control the spatial uniformity of the resultant printed patterns/lines. SEM image of the inkjet-printed MSC using, g the NMP ink (inset shows the whole device) and h the ethanol ink. Scale bar in ${\\bf\\Pi}({\\bf g})$ and $({\\bf h})=$ $200\\upmu\\mathrm{m}$ and $=1$ cm in the inset of $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ . The distances between the two arrows in $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ and ${\\bf\\Pi}({\\bf h})$ are $50\\upmu\\mathrm{m}$ and $130\\upmu\\mathrm{m}.$ , respectively. i width variation of inkjetprinted MXene lines printed using NMP (top) and ethanol (bottom) inks \n\nBy sealing all the organic inks in Ar-filled hermetic bottles and storing them in a refrigerator32, no changes in ink stability (that is, re-aggregation) have been observed over the course of 12 months except in the case of the DMSO ink (Supplementary Fig. 6g–j), which precipitated after 6 months. This necessitates future studies to reveal the possible reasons, as the colloidal stability of the ink is crucial for printing. For instance, measuring the extinction and absorption spectra of DMSO ink over time could provide the decay rate and other insights, however, this is beyond the scope of this work. Nevertheless, the shelf-life of all these inks are over a timeframe that is viable for inkjet printing16. \n\n![](images/6c552fac785aad506d15fed98bf8056e1266aabc3e0b6d9598522172302f2acf.jpg) \nFig. 3 Inkjet printing of MXene organic inks. a Optical images of inkjet-printed “MXene” word (top), “Direct MXene Ink Printing” word (middle) and MSCs (bottom) supported on $\\mathsf{A l O}_{\\mathsf{x}}$ -coated PET. A total of 20 MSCs with different combinations and 80 letters were printed as a demonstration, indicating a high reproducibility of the inkjet printing. Scale bar $=1{\\mathsf{c m}}$ . b Multiple peeling tests of an inkjet-printed MSC (inset) using scotch tape. No material is stuck to the tape after ten peels, indicating a strong adhesion between the printed lines and the ${\\mathsf{A l O}}_{\\times}$ -coated PET substrate. c AFM image of the inkjet-printed line, showing a homogenous surface consisting of interconnected nanosheets. Scale bar $=10\\upmu\\mathrm{m}$ . d The height profiles of inkjet-printed lines with different number of paths, $$ . e The line thickness plotted as a function of $$ . The lines in (d) and (e) were printed using NMP ink with a concentration of 12.5 $\\mathsf{m g}\\mathsf{m}\\mathsf{L}^{-1}$ . f The sheet resistance, $R_{\\mathsf{s}\\prime}$ plotted as a function of $$ . Inset shows the optical images of various printed lines (2 cm in length) with different $$ . g The electronic conductivity changes as a function of bending degree (top) and number of bending cycles (bottom). One cycle is defined as bending the printed line to $150^{\\circ}$ then releasing to $0^{\\circ}$ (flat). h I–V curves of lines with different $$ . i Resistance of the printed lines with different $$ plotted as a function of length (left). An excellent linearity is observed in all the as-printed lines. The right panel shows resistance of lines with $=1$ using NMP ink, indicating a line resistivity of $620\\up k\\Omega\\upmu\\mathrm{m}^{-1}$ and $26M\\Omega\\upmu\\mathrm{m}^{-1}$ achieved in the inks diluted by 20 times $(\\sim0.63\\:\\mathrm{mg}\\:\\mathrm{mL}^{-1}$ , bottom right) and 100 times (\\~0.13 $\\mathsf{m g}\\mathsf{m}\\mathsf{L}^{-1}.$ , top right), respectively \n\nTo reach a fine-resolution printing, MXene inks should be designed for stable jetting (that is, no secondary droplet formation after each electrical impulse)16. The inverse Ohnesorge number $Z$ is commonly used as a figure of merit to predict if an ink will form stable drops: $Z=\\sqrt{\\gamma\\rho D}/\\eta^{9}$ , where $Z$ depends on surface tension $(\\gamma)$ , density $(\\rho)$ , viscosity $(\\eta)$ and nozzle diameter $(D)$ . The viscosity–shear rate plots indicate non-Newtonian characteristics and shear-thinning (pseudoplastic) behaviour in the organic inks (Fig. 2e and Supplementary Fig. 8)36. Based on the inks' rheological properties (Supplementary Table 1), the $Z{\\sim}2.6$ for ethanol ink is slightly higher than those of DMSO $(Z{\\sim}2.5)$ and NMP $(Z{\\sim}2.2)$ inks. The $Z$ values of all-MXene organic inks are well within the optimal $Z$ value range for stable jetting (1 < Z < 14)12,16. \n\nAfter jetting, proper substrate wetting and ink drying are crucial for uniform material deposition. Previous best practices suggested that the ink $\\gamma$ should be $7{-}10\\ \\mathrm{mN}\\ \\mathrm{m}^{-1}$ lower than the substrate surface energy16. While $\\gamma$ of ethanol $(\\small{\\sim}22.1\\mathrm{mN}\\mathrm{m}^{-1}),$ ) well matches that of common substrates like glass $({\\sim}36\\mathrm{mN}\\mathrm{m}^{-1})$ ) and polyethylene terephthalate (PET, ${\\sim}48\\ \\mathrm{mN}\\ \\mathrm{m}^{-1})$ 16, the MXene-ethanol ink concentration is fairly low $(0.7\\mathrm{mg}\\mathrm{mL}^{-1},\\$ . DMF, NMP and DMSO on the other hand, possess high γ $(\\sim37.1\\$ , 40.8 and $43.5\\mathrm{mNm^{-1}}$ , respectively), with MXene concentrations up to $12.5\\mathrm{mg}\\mathrm{mL}^{-1}$ , but require additional treatment such as solvent transfer to match the substrate16. Here we choose an $\\mathrm{{AlO}_{\\mathrm{x}}}$ -coated PET substrate $(\\sim66\\mathrm{mN}\\mathrm{m}^{-1})^{37}$ to solve the substrate wetting issue for all organic inks, as shown in Fig. 2f. \n\nThe representative inkjet-printed lines using NMP and ethanol (Fig. 2g, h) inks showcase a high printing resolution without undesirable coffee ring effects; the nanosheets can be clearly seen on the smooth surface, forming a conductive film (Supplementary Fig. 9). By inkjet printing the NMP ink, a line (width, gap, spatial uniformity) of $(\\sim80\\upmu\\mathrm{m}$ , $\\sim50\\upmu\\mathrm{m}$ , ${\\sim}3.3\\%$ ) was achieved, in contrast to $(\\sim580\\upmu\\mathrm{m}$ , ${\\sim}130\\upmu\\mathrm{m},6.4\\%$ in the ethanol-based inks (Fig. 2i and Supplementary Fig. 10). On the other hand, depositing NMP ink onto Kapton and glass substrates led to non-uniform lines (Supplementary Fig. 11), highlighting the importance of substrate selection in achieving high-resolution printing of MXene inks. \n\nAll-MXene inkjet-printed patterns. Figure 3a shows examples of inkjet-printed patterns, such as “MXene” word, printed using NMP-based MXene ink on an $\\mathrm{{AlO}_{\\mathrm{x}}}$ -coated PET substrate under ambient conditions. In particular, all-MXene MSCs can be produced in series and/or parallel (Fig. 3a). These MSCs are strongly adhered to the substrate, as confirmed by the clean scotch tape observed after peeling the MSC ten times (Fig. 3b, Supplementary Movie 1). These MSCs showcase an interconnected nanosheet network in the film, according to the atomic force microscopy (AFM, Fig. 3c). By adjusting the printing pass, both the thickness (obtained from AFM height profile, Fig. 3d) and sheet resistance $(R_{s})$ can be effectively tuned. The line thickness and roughness increase linearly with the number of paths $($ , Fig. 3e and Supplementary Fig. 12). For instance, a line thickness of $100\\pm$ $21.5\\mathrm{nm}$ and $530\\pm120\\mathrm{nm}$ is achieved when $=10$ and 100, respectively. The $R_{s}$ of the printed lines (2-cm-long) quickly decreases from $445\\Omega/\\mathrm{sq}$ $\\mathop{'}=1\\mathop{}$ ) to $35\\Omega/\\mathrm{sq}$ $(=50),$ , as shown in Fig. 3f and the inset. In addition, the inkjet-printed lines become darker with increasing ${<}N>$ , indicative of uniform printing28. No oxide was observed on the as-printed lines while the film surface became rougher in the lines that were exposed to the ambient lab environment for 6 months (Supplementary Fig. 13). This is in good agreement with $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) results (Supplementary Fig. 14a), as the deconvoluted Ti 2p core-level spectrum of the printed line produced using NMP ink $(=2)$ is similar to that of fresh MXene38, indicating that the pristine nanosheets are preserved after evaporation of the solvent. Although the $\\scriptstyle{\\mathrm{C=O}}$ contribution is negligible in the deconvoluted C 1s core-level spectrum (Supplementary Fig. 14b), the N1s core-level spectrum can be deconvoluted into three peaks, which can be attributed to the trapped and adsorbed NMP molecules in the inkjet-printed MXene lines39–41. This result suggests that some NMP molecules residue within the MXene nanosheets after the completion of printing. \n\nThe representative printed line $\\stackrel{\\prime}{\\ 、}N{>}=5\\stackrel{\\cdot}{}$ ) shows an electronic conductivity up to $2770\\mathrm{{Scm}^{-1}}$ initially and maintains $510\\mathrm{{Scm}^{-1}}$ after 6 months in ambient air, most probably due to the trapped water among the MXene layers. Moreover, printed MXene patterns are not damaged by substrate deformation, i.e., the conductivity of the as-printed lines can be fully recovered to the initial value upon releasing the bending force (Fig. ${3\\mathrm{g}},$ top); after 1000 bending cycles, the conductivity decreases to $\\mathrm{\\bar{10935}}\\mathrm{cm}^{-1}$ (Fig. 3g, bottom), probably due to the mismatch of the nanosheets (Supplementary Fig. 15). \n\nIn printed electronics, printing homogeneous lines is of great importance14. Here the reliability and reproducibility of inkjet printing technology allows us to print smooth, even and straight MXene lines on plastic substrates, and enables us to study their electrical properties. Figure 3h shows the current–voltage profiles of various lines with ${<}N{>}$ ranging from 1 to 25, demonstrating ohmic characteristics. The resistance of these MXene lines is ${<}N{>}$ and length dependent, showing an excellent linearity with negligible contact resistance (Fig. 3i, left). The line resistivity was determined to be 0.27, 0.21 and $0.12\\Omega\\upmu\\mathrm{m}^{-1}$ for $=1$ , 2 and 10, respectively. Through diluting the initial ink concentration by a factor of 20 $({\\sim}0.63\\ \\mathrm{\\bar{mg}m L^{-1}},$ and 100 $(\\sim0.13\\mathrm{mg}\\mathrm{mL}^{-1},$ , the line resistivity sharply increases to $620\\mathrm{k}\\Omega\\upmu\\mathrm{m}^{-1}$ and $26\\mathrm{M}\\Omega$ $\\upmu\\mathrm{m}^{-1}$ , respectively at $=1$ (Fig. 3i, right). This indicates that by adjusting ink concentration, line length and thickness, our direct MXene ink writing technique may offer a simple route to print resistors/conductive wires, with resistance values ranging from a few $\\Omega$ to several $\\mathbf{M}\\Omega$ , on flexible substrates, which are essential components of printed analogue circuits14. \n\nExtrusion printing of all-MXene patterns. We further demonstrate the extrusion printing using MXene aqueous ink due to its suitable fluidic properties36, including a viscous nature (Fig. 4a), a high MXene ink concentration $({\\sim}3\\bar{6}\\mathrm{mg}\\mathrm{mL^{-1}}.$ ) and an apparent viscosity of ${\\sim}0.71$ Pa·s (Supplementary Fig. 16). No sedimentation is observed over the course of 12 months in the aqueous ink (sealed in Ar-filled bottles and placed in a refrigerator). Figure 4b shows various fine-printed patterns. For instance, printing 2 paths gives MSCs with line gap ${\\sim}120\\upmu\\mathrm{m}$ (Fig. 4c), width ${\\sim}438\\upmu\\mathrm{m}$ and spatial uniformity within ${\\sim}5.6\\%$ (Fig. 4d). The as-printed lines consist of interconnected nanosheets, forming a continuous metallic network (Fig. 4e). Well-resolved characteristic Raman peaks of MXene are detected when probing the line along different directions (Fig. 4f and insets), showing no signs of oxidation during extrusion printing. \n\n![](images/1419d3bb94115cea4d0b09ce23ca95051c4c1186d2b52853fb8e18ae11c8200d.jpg) \nFig. 4 Extrusion printing of MXene viscous aqueous inks. a Photo of MXene aqueous ink, showing its viscous nature. b Optical images of all-MXene printed patterns, including MSCs with various configurations, on paper. The yield is high using the extrusion printing method, producing $>70$ MSCs $\\angle N>\\angle1)$ on paper based on 1 mL of the MXene ink. c Low-magnification SEM image of printed MXene MSC. Scale bar $=200\\upmu\\mathrm{m}$ . d High-magnification SEM image of MXene MSC of the framed area in $\\mathbf{\\eta}(\\bullet)$ , showing stacked, interconnected MXene nanosheets forming a continuous film. Scale bar $=500\\mathsf{n m}$ . e The width distribution and the resultant width spatial uniformity of the extrusion-printed MXene MSCs. f Raman spectrum of the extrusion-printed lines along line A, inset shows the sum intensity of peak C along line B. The MXene characteristic peaks are well retained, indicating no oxidation occurred during the extrusion printing. $\\pmb{\\mathrm{\\pmb{g}}}\\mathsf{S E}\\mathsf{M}$ images of printed MSCs with $=1$ (top) and $=5$ (middle). Cross-sectional SEM image of MSC with $=5$ is shown on the bottom, demonstrating a well-stacked, continuous nanostructure. Scale bar ${\\cdot=}100\\upmu\\mathrm{m}$ (top and middle) and $=1\\upmu\\mathrm{m}$ (bottom). h The sheet resistance, $R_{{\\mathsf{s}}\\prime}$ plotted as a function of $$ , showing an exponential decay. i Extrusion-printed tandem devices (two MSCs in serial and two in parallel) on a paper substrate (left panel), showing a great flexibility (right panel). j Comparison of the conductivity of the as-printed lines plotted as a function of ink concentration, showing the advantage of our work in printing highly concentrated inks for highly conductive networks. The data in $(\\mathbf{j})$ come from ref. 13 and references within \n\nWhile the thickness of the lines printed on paper cannot be precisely measured due to the rough substrate surface, we found, generally, that a higher ${<}N{>}$ corresponds to a thicker continuous film (Fig. $^{4\\mathrm{g}}$ and Supplementary Fig. 17), forming a wellpercolated nanosheet network that provides a much lower sheet resistance. Indeed, increasing ${<}N{>}$ from 1 to 5 leads to an exponentially-decayed $R_{s}$ from 2000 to $10\\Omega\\mathrm{sq}^{-1}$ of the extrusion-printed lines (Fig. 4h). The metallic conductivity of the compacted printed lines eliminates the need for additional current collectors and conductive agents, while strong adhesion of stacked MXene sheets due to hydrogen bonds between the layers eliminates the need for a polymeric binder, enabling the scalable production of all-MXene-printed MSCs. For instance, highresolution, flexible MXene-based tandem MSCs can be extrusionprinted and connected in series and parallel, to meet the energy or power requirements (Fig. 4i). In addition to porous paper, the viscous MXene aqueous ink can be extrusion-printed on solid Al foil without any pre-treatment (Supplementary Fig. 18), showing a homogenous surface and a spatial uniformity to within $3.6\\%$ (Supplementary Fig. 19). \n\nTo achieve efficient printing, the ideal ink formulation should possess both, high concentration (C) and high electronic conductivity $(\\sigma)$ . Thus, a figure of merit, $\\mathrm{FoM}=\\bar{\\sigma}C$ $\\mathrm{\\Delta}\\cdot\\mathrm{cm}^{-1}$ · $\\mathrm{mg}\\mathrm{mL}^{-1},$ ), is commonly used to describe the electronic network properties of a printable $\\mathrm{ink}^{13}$ . A higher FoM value is preferable, as it requires less printed paths to obtain similar electrode conductivity. A combination of MXene bulk behaviour and ultrahigh nanosheet concentration results in a record-high FoM $(66,996\\mathrm{S}\\mathrm{cm}^{-1}\\cdot\\mathrm{mg}\\mathrm{mL}^{-1})$ in this work (Fig. 4j), much higher than those of other printable inks such as graphene ( $\\mathrm{\\mathop{FoM}=}$ $6000\\mathrm{Scm^{-1}\\cdot m g m L^{-1}}\\mathrm{\\hat{)}^{1}}$ 3. The ultrahigh FoM in the MXene inks enables both high-resolution printing and excellent chargestorage performance in the printed MSCs, as discussed below. \n\nCharge-storage performance of printed MSCs. To demonstrate the possible use of the direct MXene ink printing technique for producing miniature energy-storage devices, the charge-storage performance of both inkjet- and extrusion-printed all-MXene MSCs was evaluated using a sulfuric acid $\\mathrm{(H}_{2}\\mathrm{SO}_{4})$ -poly(vinyl alcohol, PVA) gel electrolyte23. The normalized cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) curves in Fig. 5a, b as well as the rate response (Supplementary Fig. 20) indicate pseudo-capacitive and high rate behaviour of a typical extrusion-printed MSC (line gap ${\\sim}89\\upmu\\mathrm{m}$ , $\\angle N>=3,$ . By optimizing the ${<}N{>}$ as well as the printed line gap, the electrochemical performance of extrusion-printed MSCs can be changed (Supplementary Fig. 21). In general, increasing the ${<}N{>}$ results in an enhancement of areal capacitance while minimizing the line gap leads to a substantially reduced time constant, indicative of simple ion diffusion paths (Fig. 5c and Supplementary Fig. 22). For instance, the $\\mathrm{C}/\\mathrm{A}$ improves from 3.5 to $43\\mathrm{mF}\\mathrm{cm}^{-2}$ upon depositing the MXene ink from $=1$ to 5 (Fig. 5c). Electrochemical impedance spectroscopy (EIS, Fig. 5d) indicates that pseudo-capacitive behaviour is gradually improved upon cycling, agreeing with the CV and GCD results. It is worth noting that the voltage of all-MXene MSCs is limited to $0.5\\mathrm{V}$ due to some parasitic reactions at low rates, highlighting the necessity of printing asymmetric MSCs to enlarge the voltage window. \n\nSimilarly, all inkjet-printed MSCs, with a variety of line ${<}N>$ and solvents, demonstrate pseudo-capacitive responses and rate capability up to $1\\mathrm{V}\\thinspace s^{-1}$ (Supplementary Figs. 23–25). In particular, the MSC printed using NMP ink exhibits the highest capacitance, reaching 1.3 and $12\\thinspace\\dot{\\mathrm{mF}}\\thinspace\\mathrm{cm}^{-2}$ when $=2$ and 25, respectively (Fig. 5c and Supplementary Fig. 25). Importantly, our inkjet- and extrusion-printed all-MXene MSCs have outperformed most other printed $\\mathrm{MSCs}^{10,15}$ in terms of areal capacitance (C/A) and volumetric capacitance (C/V), which are two practical metrics for evaluating the charge-storage performance (Fig. 5e)42. For instance, printed graphene MSCs typically display a volumetric capacitance below $100{\\overset{\\cdot}{\\mathrm{F}}}\\subset\\mathbf{m}^{-34,5,10,1\\dot{5}}$ , much lower than our inkjet-printed MXene MSC using the NMP ink $(562\\mathrm{F}\\mathrm{cm}^{-3}$ , $\\dot{=}25$ , Fig. 5f). The calculated energy density of the extrusion-printed MXene MSC $\\mathop{'}{<}N\\mathop{>}=5\\mathop{ $ reaches as high as $0.32\\upmu\\mathrm{W}\\mathrm{h}\\dot{\\mathrm{cm}}^{-2}$ at a power density of $11.4\\upmu\\mathrm{W}\\mathrm{cm}^{-2}$ , and $0.11\\upmu\\mathrm{W}$ h $c\\mathrm{m}^{-2}$ is still maintained at a high power density of $158\\upmu\\mathrm{W}\\mathrm{cm}^{-2}$ (Fig. 5g). The achieved energy density is an order of magnitude higher than that of MSCs based on printed graphene43, sprayed graphene/MXene44, etc. We note that by optimization, such as minimizing the line gap, increasing the ${<}N>$ , and/or introducing more pseudo-capacitive sites on the MXene nanosheets, the MSC performance could be further enhanced. There are also dozens of other than $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXenes to choose from ref. 21. \n\nBoth as-printed MSCs showcase excellent mechanical flexibility (Fig. 5h, i) and electrochemical cycling performance (Fig. 5j), with capacitance retention of ${\\sim}97\\%$ and ${\\sim}100\\%$ in the extrusion and inkjet-printed MSCs, respectively. The excellent mechanical properties of MXene films can be attributed to the high mechanical strength of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ flakes45 and strong adhesion between the flakes. These high-performance, all-printed MXene MSCs can be arbitrarily connected in series or parallel, forming tandem devices which exhibit capacitive responses, to satisfy specific energy/power demands (Fig. 5k and Supplementary Figs. 26, 27). \n\n# Discussion \n\nWe demonstrate additive-free MXene inks and direct printing of high-performance, all-MXene micro-supercapacitors with a high resolution. The printed flexible MSCs demonstrate excellent electrochemical performance, including volumetric capacitance up to $562\\mathrm{F}\\mathrm{cm}^{-\\hat{3}}$ and energy density as high as $0.32\\upmu\\mathrm{Wh}\\mathrm{cm}^{-2}$ , surpassing all other printed MSCs, to the best of our knowlege. The direct MXene ink printing technique is of fundamental importance to fields beyond energy storage and harvesting, including electronics, circuits, packaging and sensors, where cheaper and easy-to-integrate components are needed. Of equal importance is that the MXene ink formulation can be achieved by means of a scalable, facile and low-cost route. The additive- and binary-solvent-free, low-temperature printing technique suggests new possibilities for applications in smart electronics, sensors, electromagnetic shielding, antennas and other applications. \n\n# Methods \n\nPreparation of $\\pmb{\\Tilde{\\Pi}}_{3}\\pmb{\\C}_{2}\\pmb{\\Tilde{\\Pi}}_{x}$ aqueous inks. Thirty-five millilitres of DI-water was added to the above mentioned m $\\mathrm{\\Omega}_{1-\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}}$ “cake”, followed by vigorous shaking by hand/vortex machine for $20\\mathrm{min}$ . This process delaminates the $\\mathrm{m-Ti_{3}C_{2}T_{\\it x}}$ into single- or few-layered nanosheets well dispersed in water. Then, the mixture was centrifuged at $3500\\mathrm{rpm}$ for $30\\mathrm{min}$ . The top $80\\%$ supernatant was collected, and further centrifuged at $5000\\mathrm{rpm}$ for $^{\\textrm{\\scriptsize1h}}$ . After decanting the supernatant, which contains relatively small nanosheets and/or impurities, $10\\mathrm{mL}$ of DI-water was \n\n![](images/bf5d6947121dcddcb2e8f920e8438d9c271ef84e1b9686a860fd3b4625cf67a8.jpg) \nFig. 5 Electrochemical response of inkjet- and extrusion-printed MXene MSCs. a Normalized cyclic voltammograms (CV) profiles and $\\bullet$ galvanostatic charge–discharge (GCD) curves of a typical extrusion-printed MSC (line gap ${\\sim}89\\upmu\\mathrm{m}$ , $=3$ ). c Electrochemical impedance spectroscopy of extrusionprinted MSC before and after the CV tests at various scan rates. d Areal capacitance of inkjet- and extrusion-printed MSCs with different $$ . An areal capacitance of 1.3 and $12\\mathsf{m F}\\mathsf{c m}^{-2}$ is achieved with inkjet printing of $=2$ and 25, respectively. e Areal capacitance (C/A) and f volumetric capacitance (C/V) comparison of this work to other reported MSC systems, showing much higher $\\mathsf{C}/\\mathsf{V}$ of our printed MXene MSCs than other reports. g Ragone plot comparison of this work (extrusion-printed MSC with $=5$ ) to other MSC systems. Detailed references and specific values in (e)– $\\mathbf{\\nabla}\\cdot(\\mathbf{g})$ can be found in the Supplementary Information (Supplementary Table 2–4). h CVs of extrusion-printed MSC supported on a paper substrate (inset) under different bending degrees. i Electronic conductivity of the extrusion-printed lines plotted as a function of bending degree (top) and bending cycles (bottom). j Longterm cycling of inkjet- and extrusion-printed MSCs with current densities of 14 and $200\\upmu\\upepsilon\\mathrm{m}^{-2}$ , respectively. Insets are the typical GCD curves, showing capacitive behaviour during cycling, indicating that the excellent electrochemical performance is not due to parasitic reactions. k Typical CV curves of the as-printed tandem devices, such as printing four MSCs in series and in parallel, and two in series and in parallel. The as-formed tandem devices exhibit capacitive responses, showing the great flexibility of this approach to satisfy different energy/power demands \n\nadded to the sediment for redispersion by vigorous shaking, resulting in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ aqueous inks. \n\nPreparation of $\\pmb{\\Tilde{\\Pi}}_{3}\\pmb{\\C}_{2}\\pmb{\\Tilde{\\Pi}}_{x}$ organic inks. In this work, various organic inks were prepared using a solvent-transfer strategy. Typically, the as-prepared $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ aqueous dispersion was centrifuged at $10,000\\mathrm{rpm}$ for $^{\\textrm{1h}}$ . After decanting the supernatant, $20~\\mathrm{mL}$ of NMP was added to $_{0.1\\mathrm{g}}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and the dispersion was sonicated for $30\\mathrm{min}$ . A low speed $(1500\\mathrm{rpm},30\\mathrm{min})$ centrifugation was then employed to separate the well-dispersed flakes from the aggregated platelets. The supernatant was further centrifuged at $5000\\mathrm{rpm}$ for $30\\mathrm{min}$ . After decanting the supernatant, the sediment was re-dispersed in NMP. The ink concentration can be easily controlled by varying the volume of added NMP. DMSO, DMF and ethanolbased inks were prepared following a similar procedure. \n\nInkjet printing of micro-supercapacitors and resistors. The $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ organic inks, without any additives, were inkjet-printed using a Dimatix DMP2800 Material printer on a variety of substrates, such as $\\mathrm{AlO}_{\\mathrm{x}}$ -coated PET (NB-TP \n\n3GU100, Mitsubishi Paper Mills Ltd.), glass, Kapton, etc. The printer was fitted with a cartridge (DMC 11610), producing $10\\mathrm{pL}$ droplets with spacing defined by rotating the print head to a pre-defined angle. The nozzle array consists of 16 identical nozzles $21\\upmu\\mathrm{m}$ in diameter spaced $254\\upmu\\mathrm{m}$ apart. The substrate was placed onto the vacuum plate of the printer. During printing, the substrate was heated up to $60^{\\circ}\\mathrm{C}$ while $70^{\\circ}\\mathrm{C}$ was maintained at the ink ejection point in the print head. Patterns, resistors and micro-supercapacitors were printed at a droplet spacing of $25\\upmu\\mathrm{m}$ on the coated PET substrate and $100\\upmu\\mathrm{m}$ on the glass substrate. Microsupercapacitor devices with a range of film thicknesses were produced by changing the print pass of the print head. Resistors were printed with different paths (ranging from 1 to $25\\mathrm{Ps}$ ) using the pristine ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}{\\mathrm{-NMP}}$ ink as well as NMP inks diluted by 20 and 100 times. Resistance was measured as a function of the channel length of the resistor. \n\nExtrusion printing of micro-supercapacitors. The $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ aqueous inks, without any surfactants, were extrusion-printed on paper substrates using a 3D printer (Voxel8 Inc., USA). The temperature of the substrate was set to $60^{\\circ}\\mathrm{C}$ while the print head was held at room temperature. The ink was loaded inside the print head and squeezed through the $200\\upmu\\mathrm{m}$ -wide nozzle and deposited onto the substrate and then quickly solidified. Printing paths were designed by CAD drawings (SolidWorks 2016, Dassault Systèmes) and converted into G-code by a Voxel8’s proprietary tool path generator to command the x-y-z motion of the printer head. Various patterns and micro-supercapacitors were printed with different print pass, line spacing, width, length, etc. \n\nMaterials characterization. The rheological properties of MXene aqueous inks as well as organic inks, were studied on the Anton Paar MCR 301 rheometer. Morphologies and microstructure of the as-printed lines and devices were studied by scanning electron microscopy and Raman spectroscopy. The surface chemistry of MXene was studied using XPS and the composition analysed by energydispersive X-ray spectroscopy (EDX). The electrical conductivity and flexibility of the as-printed lines were evaluated using a two-point probe technique. A detailed description of characterization can be found in Supplementary Methods. \n\nElectrochemical characterization. Both inkjet- and extrusion-printed MSCs were coated with a layer of gel-like polymer electrolyte made of $3\\mathrm{M}$ sulfuric acid $\\mathrm{(H}_{2}\\mathrm{SO}_{4})$ -Poly(vinyl alcohol, PVA) gel electrolyte, followed by natural drying. The electrochemical performance of the as-printed MXene MSCs was evaluated on a potentiostat (VMP3, BioLogic) in a voltage window of $0.5\\mathrm{V}$ . CV, GCD, long-term cycling, as well as flexibility of the device were assessed. A detailed description of characterization can be found in Supplementary Methods. \n\n# Data availability \n\nThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. We also provide a source data file to include all the source data except the images. \n\n# Received: 23 November 2018 Accepted: 8 March 2019 Published online: 17 April 2019 \n\n# References \n\n1. Beidaghi, M. & Gogotsi, Y. Capacitive energy storage in micro-scale devices: recent advances in design and fabrication of micro-supercapacitors. Energy Environ. Sci. 7, 867–884 (2014). \n2. Tang, H. et al. In situ formed protective barrier enabled by sulfur $@$ titanium carbide (MXene) ink for achieving high-capacity, long lifetime Li-S. Batter. Adv. Sci. 4, 1800502 (2018). \n3. Zhang, C. (John) & Nicolosi, V. Graphene and MXene-based transparent conductive electrodes and supercapacitors. Energy Storage Mater. 16, 102–125 (2019).. \n4. Pech, D. et al. Ultrahigh-power micrometre-sized supercapacitors based on onion-like carbon. Nat. Nanotechnol. 5, 651–654 (2010). \n5. El-Kady, M. F. & Kaner, R. B. Scalable fabrication of high-power graphene micro-supercapacitors for flexible and on-chip energy storage. Nat. Commun. 4, 1475 (2013). \n6. Zhang, C. (John) et al. Liquid exfoliation of interlayer spacing-tunable 2D vanadium oxide nanosheets: High capacity and rate handling Li-ion battery cathodes. Nano Energy 39, 151–161 (2017).. \n7. El-Kady, M. F., Strong, V., Dubin, S. & Kaner, R. B. Laser scribing of highperformance and flexible graphene-based electrochemical capacitors. Science 335, 1326–1330 (2012). \n8. Liu, Y. et al. Development of graphene oxide/polyaniline inks for high performance flexible microsupercapacitors via extrusion printing. Adv. Funct. Mater. 28, 1706592 (2018). \n9. Hu, G. et al. Functional inks and printing of two-dimensional materials. Chem. Soc. Rev. 47, 3265–3300 (2018). \n10. Li, J. et al. Scalable fabrication and integration of graphene microsupercapacitors through full inkjet printing. ACS Nano 11, 8249–8256 (2017). \n11. Song, D. et al. High-resolution transfer printing of graphene lines for fully printed, flexible electronics. ACS Nano 11, 7431–7439 (2017). \n12. McManus, D. et al. Water-based and biocompatible 2D crystal inks for allinkjet-printed heterostructures. Nat. Nanotechnol. 12, 343–350 (2017). \n13. Secor, E. B., Ahn, B. Y., Gao, T. Z., Lewis, J. A. & Hersam, M. C. Rapid and versatile photonic annealing of graphene inks for flexible printed electronics. Adv. Mater. 27, 6683 (2015). \n14. Li, J. et al. Efficient inkjet printing of graphene. Adv. Mater. 25, 3985 (2013). \n15. Li, L. et al. High-performance solid-state supercapacitors and microsupercapacitors derived from printable graphene inks. Adv. Energy Mater. 6, 1600909 (2016). \n16. Hu, G. et al. Black phosphorus ink formulation for inkjet printing of optoelectronics and photonics. Nat. Commun. 8, 278 (2017). \n17. Liu, Z. et al. Ultraflexible in-plane micro-supercapacitors by direct printing of solution-processable electrochemically exfoliated graphene. Adv. Mater. 28, 2217 (2016). \n18. Hyun, W. J. et al. Scalable, self-aligned printing of flexible graphene microsupercapacitors. Adv. Energy Mater. 7, 1700285 (2017). \n19. Zhou, K.-G., Mao, N.-N., Wang, H.-X., Peng, Y. & Zhang, H.-L. A mixedsolvent strategy for efficient exfoliation of inorganic graphene analogues. Angew. Chem. Int. Ed. 50, 10839–10842 (2011). \n20. Kang, J. et al. Solution-based processing of optoelectronically active indium selenide. Adv. Mater. 30, 1802990 (2018). \n21. Anasori, B., Lukatskaya, M. R. & Gogotsi, Y. 2D metal carbides and nitrides (MXenes) for energy storage. Nat. Rev. Mater. 2, 16098 (2017). \n22. Zhang, C. J. et al. Transparent, flexible, and conductive 2D titanium carbide (MXene) films with high volumetric capacitance. Adv. Mater. 29, 1702678 (2017). \n23. Lukatskaya, M. R. et al. Ultra-high-rate pseudocapacitive energy storage in two-dimensional transition metal carbides. Nat. Energy 2, 17105 (2017). \n24. Zhang, C. J. et al. Stamping of flexible, coplanar micro-supercapacitors using MXene inks. Adv. Funct. Mater. 28, 1705506 (2018). \n25. Quain, E. et al. Direct writing of additive-free MXene-in-water ink for electronics and energy storage. Adv. Mater. Technol. 4, 1800256 (2019). \n26. Sun, G. et al. Layer-by-layer printing of laminated graphene-based interdigitated microelectrodes for flexible planar micro-supercapacitors. Electrochem. Commun. 51, 33–36 (2015). \n27. Zheng, J. et al. An inkjet printed $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ -GO electrode for the electrochemical sensing of hydrogen peroxide. J. Electrochem. Soc. 165, B227–B231 (2018). \n28. Vural, M. et al. Inkjet printing of self-assembled 2D titanium carbide and protein electrodes for stimuli-responsive electromagnetic shielding. Adv. Funct. Mater. 28, 1801972 (2018). \n29. Aleeva, Y. & Pignataro, B. Recent advances in upscalable wet methods and ink formulations for printed electronics. J. Mater. Chem. C. 2, 6436–6453 (2014). \n30. Secor, E. B., Prabhumirashi, P. L., Puntambekar, K., Geier, M. L. & Hersam, M. C. Inkjet printing of high conductivity, flexible graphene patterns. J. Phys. Chem. Lett. 4, 1347–1351 (2013). \n31. Zhang, L. et al. Inkjet printing high-resolution, large-area graphene patterns by coffee-ring lithography. Adv. Mater. 24, 436–440 (2012). \n32. Zhang, C. J. et al. Oxidation stability of colloidal two-dimensional titanium carbides (MXenes). Chem. Mater. 29, 4848–4856 (2017). \n33. Lipatov, A. et al. Effect of synthesis on quality, electronic properties and environmental stability of individual monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene flakes. Adv. Electron. Mater. 2, 1600255 (2016). \n34. Alhabeb, M. et al. Guidelines for synthesis and processing of two-dimensional titanium carbide $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene). Chem. Mater. 29, 7633–7644 (2017). \n35. Maleski, K., Mochalin, V. N. & Gogotsi, Y. Dispersions of two-dimensional titanium carbide MXene in organic solvents. Chem. Mater. 29, 1632–1640 (2017). \n36. Akuzum, B. et al. Rheological characteristics of 2D titanium carbide (MXene) dispersions: a guide for processing MXenes. ACS Nano 12, 2685–2694 (2018). \n37. Struller, C. F., Kelly, P. J. & Copeland, N. J. Aluminum oxide barrier coatings on polymer films for food packaging applications. Surf. Coat. Technol. 241, 130–137 (2014). \n38. Halim, J. et al. X-ray photoelectron spectroscopy of select multi-layered transition metal carbides (MXenes). Appl. Surf. Sci. 362, 406–417 (2016). \n39. Charlier, J., Cousty, J., Xie, Z. X., Poulennec, C. V.-L. & Bureau, C. Adsorption of substituted pyrrolidone molecules on Au(111): an STM and XPS study. Surf. Interface Anal. 30, 283–287 (2000). \n40. Peng, H. et al. Effect of transition metals on the structure and performance of the doped carbon catalysts derived from polyaniline and melamine for ORR application. ACS Catal. 4, 3797–3805 (2014). \n41. Sun, H. et al. Binder-free graphene as an advanced anode for lithium batteries. J. Mater. Chem. A 4, 6886–6895 (2016). \n42. Gogotsi, Y. & Simon, P. True performance metrics in electrochemical energy storage. Science 334, 917–918 (2011). \n43. Sollami Delekta, S., Smith, A. D., Li, J. & Östling, M. Inkjet printed highly transparent and flexible graphene micro-supercapacitors. Nanoscale 9, 6998–7005 (2017). \n44. Li, H. et al. Flexible all-solid-state supercapacitors with high volumetric capacitances boosted by solution processable MXene and electrochemically exfoliated graphene. Adv. Energy Mater. 7, 1601847 (2017). \n45. Lipatov, A. et al. Elastic properties of 2D $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathbf{x}}$ MXene monolayers and bilayers. Sci. Adv. 4, eaat0491 (2018). \n46. Zhang, C. et al. Highly porous carbon spheres for electrochemical capacitors and capacitive flowable suspension electrodes. Carbon N. Y. 77, 155–164 (2014). \n\n# Acknowledgements \n\nWe thank the SFI-funded AMBER Research Centre (SFI/12/RC/2278) and the Advanced Microscopy Laboratory for the provision of their facilities. V.N. thanks the European Research Council (StG 2DNanocaps and CoG 3D2D print) and Science Foundation Ireland (PIYRA) for funding. V.N. and M.P.K are supported by the Science Foundation Ireland (SFI) under grant number 16/RC/3872 and is co-funded under the European Regional Development Fund and by I-Form industry partners. We also acknowledge Prof. Matthias E. Möbius and Conor Patrick Cullen (Trinity College Dublin, Ireland) for the useful discussions on rheological tests and XPS. Y.G. and B.A. were supported by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, grant #DE-SC0018618. \n\n# Author contributions \n\nC.F.Z., Y.G. and V.N. conceived the project. C.F.Z. synthesized materials and prepared the MXene ink, S.B. performed the rheology tests, L.M. performed the inkjet printing, M. P.K. conducted the extrusion printing, M.P.K. and B.A. created the 3D schemes and graphics, A.S., O.R. and H.C.N. performed the electron microscopy analysis, S.H.P. measured the conductivity. N.M. performed Raman analysis, C.C. conducted AFM studies, C.F.Z. performed electrochemical characterizations, C.F.Z., J.N.C., Y.G. and V.N. analysed electrochemical data. C.F.Z. wrote the manuscript with contributions from all co-authors, all authors discussed the results and commented on the manuscript. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-09398-1. \n\nCompeting interests: The authors declare no competing interests. \n\nJournal peer review information: Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1016_j.joule.2019.09.010", + "DOI": "10.1016/j.joule.2019.09.010", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2019.09.010", + "Relative Dir Path": "mds/10.1016_j.joule.2019.09.010", + "Article Title": "Alkyl Chain Tuning of Small Molecule Acceptors for Efficient Organic Solar Cells", + "Authors": "Jiang, K; Wei, QY; Lai, JYL; Peng, ZX; Kim, H; Yuan, J; Ye, L; Ade, H; Zou, YP; Yan, H", + "Source Title": "JOULE", + "Abstract": "The field of organic solar cells has seen rapid developments after the report of a high-efficiency (15.7%) small molecule acceptor (SMA) named Y6. In this paper, we design and synthesize a family of SMAs with an aromatic backbone identical to that of Y6 but with different alkyl chains to investigate the influence of alkyl chains on the properties and performance of the SMAs. First, we show that it is beneficial to use branched alkyl chains on the nitrogen atoms of the pyrrole motif of the Y6. In addition, the branching position of the alkyl chains also has a major influence on material and device properties. The SMA with 3rd-position branched alkyl chains (named N3) exhibits optimal solubility and electronic and morphological properties, thus yielding the best performance. Further device optimization using a ternary strategy allows us to achieve a high efficiency of 16.74% (and a certified efficiency of 16.42%).", + "Times Cited, WoS Core": 815, + "Times Cited, All Databases": 838, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000503428000012", + "Markdown": "# Article Alkyl Chain Tuning of Small Molecule Acceptors for Efficient Organic Solar Cells \n\nKui Jiang, Qingya Wei, Joshua Yuk Lin Lai, ..., Harald Ade, Yingping Zou, He Yan \n\nyingpingzou@csu.edu.cn (Y.Z.) hyan@ust.hk (H.Y.) \n\n# HIGHLIGHTS \n\nA new non-fullerene acceptor, named N3, achieving better performance than Y6 \n\n![](images/3bd897b4bfa0a8a9862ed7bd396bbcbbe34df8340c73431889bc63c01f2057d5.jpg) \n\n$3^{\\mathrm{rd}}$ -position branched alkyl chain yielding optimal properties \n\nA certified power conversion efficiency of $16.42\\%$ was achieved \n\nTernary strategy achieving a high power conversion efficiency of $16.74\\%$ \n\nA new non-fullerene acceptor, named N3, was developed by using a $3^{\\mathrm{rd}}$ -position branched alkyl chain on the pyrrole motif of the molecule, which yielded better performance than the state-of-the-art acceptor Y6. Ternary devices were fabricated, achieving a power conversion efficiency of $16.74\\%$ in the lab and a certified efficiency of $16.42\\%$ by Newport. \n\n# Article Alkyl Chain Tuning of Small Molecule Acceptors for Efficient Organic Solar Cells \n\nKui Jiang,1,2,5 Qingya Wei,1,5 Joshua Yuk Lin Lai,2,5 Zhengxing Peng,3 Ha Kyung Kim,2 Jun Yuan,1 Long Ye,3 Harald Ade,3 Yingping Zou,1,\\* and He Yan2,4,6,\\* \n\n# SUMMARY \n\nThe field of organic solar cells has seen rapid developments after the report of a high-efficiency $(15.7\\%)$ small molecule acceptor (SMA) named Y6. In this paper, we design and synthesize a family of SMAs with an aromatic backbone identical to that of Y6 but with different alkyl chains to investigate the influence of alkyl chains on the properties and performance of the SMAs. First, we show that it is beneficial to use branched alkyl chains on the nitrogen atoms of the pyrrole motif of the Y6. In addition, the branching position of the alkyl chains also has a major influence on material and device properties. The SMA with $3^{\\mathsf{r d}}$ -position branched alkyl chains (named N3) exhibits optimal solubility and electronic and morphological properties, thus yielding the best performance. Further device optimization using a ternary strategy allows us to achieve a high efficiency of $16.74\\%$ (and a certified efficiency of $16.42\\%$ . \n\n# INTRODUCTION \n\nOrganic solar cells (OSCs) are considered one of the most promising/emerging solar technologies because of their mechanical flexibility, light weight, and the possibility of mass production by roll-to-roll print process.1–8 Traditional OSCs utilize fullerene derivatives as electron accepting materials, which exhibit many drawbacks such as poor absorption, instability, limited tunability of energy levels, and large voltage losses.3,9–12 In recent years, there has been a rapid development of non-fullerene OSCs with many attractive features including great absorption properties, tunable energetics, etc. Importantly, many examples of non-fullerene OSCs can achieve a relatively small voltage loss while maintaining a relatively high fill factor and external quantum efficiency (EQE),13–25 thus out-performing traditional fullerene OSCs. Recently, a high-performing SMA, Y6, was reported26 to have an exceptional device performance when combined with a known polymer donor, Poly[(2,6-(4,8-bis(5- (2-ethylhexyl-3-fluoro)thiophen-2-yl)-benzo][1,2-b:4,5 - b’]dithiophene))-alt-(5,5-(1’,30- di-2-thienyl- $.5^{\\prime},7^{\\prime}$ -bis(2-ethylhexyl)benzo[1’,2’-c:4’,50 -c’]dithiophene-4,8-dione), named PM6. It is worth mentioning that the voltage loss of PM6:Y6-based OSC devices is only 0.53 V while maintaining a high fill factor and EQE, thus achieving a high PCE of $15.7\\%$ . \n\nDespite the breakthrough, questions remain as to why the Y6 molecule performs exceptionally well and what the structural features of Y6 that contribute to its high performance are. Comparing Y6 with previously reported ladder-type SMAs such as indacenodithieno[3,2-b]thiophene 2-(3-oxo-2,3-dihydroinden-1-ylidene)malononitrile (ITIC), one of the important differences between them is alkyl chains. In ITICtype SMAs, the alkyl chains are usually p-hexylphenyl or linear alkyl chains attached \n\n# Context & Scale \n\nNon-fullerene organic solar cells (OSCs) have attracted considerable attention due to their advantages of light weight, mechanical flexibility, and low-cost production via printing processes. In the past 2 years, the OSC field has been developing rapidly thanks to the emergence of non-fullerene small molecular acceptors (SMAs), the molecular design of which is a crucial subject of research. Herein, we design and synthesize a series of SMAs that have an aromatic backbonoe identical to that of the state-of-the-art SMA (named Y6) but with different alkyl chains (linear or $3^{\\mathrm{rd}}.$ - or $4^{\\mathrm{th}}$ -position branched alkyl chains) on the nitrogen atoms of the pyrrole motif of Y6. It was found that the SMA with $3^{\\mathrm{rd}}$ -position branched alkyl chains exhibited the best performance with a power conversion efficiency of $16.74\\%$ and a certified efficiency of $16.42\\%$ . \n\non the two $\\mathsf{s p}^{3}$ hybridized carbon atoms bridging the adjacent aromatic rings. These two $\\mathsf{s p}^{3}$ carbon atoms are typically located on opposite sides of the molecular backbone in a C2 symmetric manner. As a result, the four alkyl chains on ITIC-type molecules are pointing to different directions in the space. For Y6, however, there are two types of alkyl chains on the molecular structure. One is the $2^{\\mathsf{n d}}$ -position branched alkyl chain, 2-ethylhexyl (2EH), attached on the two $\\mathsf{s p}^{2}$ hybridized nitrogen atoms in the pyrrole motif of the molecule. The other type is two straight alkyl chains, n-undecyl, attached on the $\\upbeta$ position of the thiophene unit on the outer side of the core. One interesting feature of the alkyl chain orientation in Y6 is that the two 2EH branched alkyl chains that are located on the pyrrole motif of the molecule are partially pointing toward each other. Such arrangement and orientation of the alkyl chains on Y6 are certainly different from those on conventional ITIC-type SMAs. \n\nIt is also well known in the organic solar cell community that the size, branching position, orientation, and position of alkyl chains can have a significant influence on the solubility, aggregation, optical, and electronic properties of the small molecules, thus affecting the photovoltaic performance of OSCs.12,27–32 For example, for donor polymers, the use of $1^{\\mathsf{s t}}.$ -, $2^{\\mathsf{n d}}.$ -, and $3^{\\mathsf{r d}}$ -position branched alkyl chains can completely change the aggregation behaviors of the polymers in solution and cause the important phenomenon of temperature-dependent aggregation,6 which is an important approach to control the morphology of the OSC blends. In the broad field of organic semiconductor, it is also found that the length and the branching position of the alkyl chain can affect the crystal structure and molecular packing in the solid state, so that changes the small molecule’s electronic property.33–36 Since the orientation of alkyl chains in Y6 is quite different from the previously reported high-performance ladder-type SMAs, this inspired us to investigate the effect of different branched alkyl chains on Y6 properties. \n\nIn this paper, we study the effect of alkyl chains on the electronic and photonic properties of Y6, and the performance of related OPV devices. First, we ‘‘swap’’ the position of the n-undecyl and 2EH alkyl chains on the Y6 molecule. The resulting molecule has two C11 $\\mathfrak{n}$ -undecyl straight alkyl chains on the two nitrogen atoms on the pyrrole motif of the molecule. The comparison of Y6 and N-C11 should reveal the effect of having branched alkyl chains on the pyrrole motif of the molecule. Our results show that N-C11 exhibits much reduced solubility and yields excessively larger domains in the bulk heterojunction (BHJ) blend and thus significantly reduced OPV performance compared to that obtained by Y6. This indicates that it is important to keep the branched alkyl chains on the two nitrogen atoms on the pyrrole motif of the Y6 molecule. Next, while keeping branched alkyl chains on the pyrrole motif, we optimized the branching position of the branched alkyl chains. Two new SMAs were synthesized with $3^{\\mathsf{r d}}.$ - and $4^{\\mathrm{th}}$ -position branched alkyl chains, named N3 and N4. Our investigation shows that shifting out the branching position of the alkyl chains will increase the solubility of the molecule significantly from $40\\ m g/\\mathsf{m L}$ for $\\mathsf{Y}6$ to $64m g/m L$ for N3 and $120\\ m g/\\mathsf{m L}$ for N4. It appears that the molecule with a $4^{\\mathrm{th}}$ -position branched alkyl chain, N4, exhibits excessive solubility, which also introduces undesirable large domains, lower domain purity, and edge-on orientation with respect to the substrate. The molecule with a $3^{\\mathsf{r d}}$ -position branched alkyl chain, N3, appears to exhibit optimum property in terms of domain size, crystallinity, and more dominant face-on orientation of the $\\pi-\\pi$ stacking. As a result, the best performance was obtained with N3, achieving a PCE of $16.0\\%$ in binary devices. Further device optimization using ternary strategy, by incorporating a small amount of $\\mathsf{P C}_{71}\\mathsf{B M}$ acceptor, allowed us to achieve a highly efficient organic solar cell with $16.74\\%$ efficiency. One of \n\n# Joule \n\n![](images/b2192c1b600381e0b0e4ddd548ff550299925c8c1a4f2e49c086f8998460b3bd.jpg) \nFigure 1. Molecular Structures of Y6, N-C11, N3, and N4 \n\nour best devices was certified by Newport and yielded $16.42\\%$ under the new stress-test certification protocol. \n\n# RESULTS AND DISCUSSION \n\nIn order to understand the influence of alkyl chains on the properties of Y6, an analog molecule (named N-C11) was synthesized by swapping the positions of the n-undecyl and 2-ethylhexyl alkyl chains on Y6. This N-C11 molecule can be synthesized following the reported synthetic procedures similar to those of Y6. One intermediate of the N-C11 molecule, 2-ethylhexyl thienothiophene, can be synthesized by Kumada coupling using commercially available 2-ethylhexyl magnesium bromide and 3-bromothieonothiophene. \n\nThe structures of Y6 and N-C11 are shown in Figure 1. The optical and electronic properties of these molecules are characterized. Both SMAs have similar UV-vis absorption spectra in solution (Figure S1), which is expected, because changing the position of the alkyl chains does not change the conjugated aromatic backbone of the molecules. Importantly, the solubility of N-C11 is dramatically reduced compared to that of Y6. While the solubility of Y6 is $40\\ m g/\\mathsf{m L}$ in chloroform at room temperature, the solubility of N-C11 is reduced to $22m g/m L$ . The poor solubility of N-C11 also causes significant difficulty in its purification process by silica gel column chromatography. It is well known that when purifying an organic semiconductor with a large coplanar structure and poor solubility, the molecule tends to ‘‘drag’’ on the silica gel column and form an excessively extended band, which makes it difficult to separate the product and impurity bands with a clear separation. Due to the poor solubility of N-C11, it drags into an excessively long band that spans over the entire column during the purification process, which is also an indication of its poor solubility. Therefore, the purification of N-C11 took multiple rounds of column chromatography and recrystallization until the pure form was obtained. As the alkyl chains on N-C11 and Y6 have identical sizes, the only difference is that the positions of the branched and straight alkyl chains are swapped. (Note that we also attempted to synthesize the molecule with C11 alkyl chains on both the pyrrole and thienothiophene units. However, the resulting molecule has extremely poor solubility, and it was challenging to purify and obtain pure solids). Our results show that the position of the branched alkyl chain on the pyrrole motif of the molecule plays a very important role to achieve the solubility property of the molecule. The difference in solubility may be due to the difference in steric hinderance between the alkyl chain on the pyrrole motif. The 2EH alkyl chains on the pyrrole motif in Y6 provide larger intramolecular steric hindrance in the molecule, leading to a slightly twisted molecule backbone,26 thus increasing its solubility. The low solubility of N-C11 could result in excessive aggregation during the film formation process, forming undesirable large domains in blend films. \n\nTable 1. Photovoltaic Characteristics of Solar Cells Based on PM6:SMAs, under the Illumination of AM 1.5G, 100 Mw/cm2 \n\n\n
Active LayerVoc (V)Jsc (mA cm-2)FF (%)PCE (%) (average)a
PM6:Y60.84724.02 (23.99)b74.715.20 (15.04 ± 0.15)
PM6:N-C110.85221.47 (21.18)70.612.91 (12.47 ± 0.31)
PM6:N30.83725.81 (25.64)73.915.98 (15.79 ± 0.18)
PM6:N40.81925.01 (24.61)69.914.31 (13.63 ± 0.33)
PM6:N3:PC71BM0.85025.71 (25.99)76.616.74 (16.52 ± 0.20)
PM6:N3:PC7,BM0.86226.2072.716.42℃
\n\naAverage PCEs in brackets are based on 25 devices. bValues in brackets are calculated from EQE. cCertified by Newport (asymptotic scans on encapsulated devices). \n\nTo investigate the impact of alkyl chain on the device performance, OSC devices were fabricated using a donor polymer PM6 with a device structure of ITO/PEDOT:PSS/PM6:SMA/PNDIT- $.F3N^{37}/A1$ . For the PM6:Y6 devices, the open-circuit voltage $(V_{o c})$ is $0.847\\ \\vee.$ the short-circuit current density $(J_{s c})$ is $24.02\\ m\\mathsf{A}\\ c m^{-2}$ , and the fill factor (FF) is $74.7\\%$ , thus giving a PCE of $15.20\\%$ which is consistent with the reported performance. However, the PM6:N-C11 devices exhibit a $V_{o c}$ of $0.852\\mathrm{V}$ and a lower $J_{s c}$ of $21.47\\mathsf{m A c m}^{-2}$ and $F F$ of $70.6\\%$ , hence leading to a lower PCE of $12.47\\%$ (Table 1 and Figure 2). \n\nIn order to understand the performance difference between these two systems, both the hole and electron mobility were determined by using a Space-Charge Limited Current (SCLC) model with a device architecture of $17\\bigcirc/\\mathsf{M o O}_{3}/\\mathsf{P M}6{:}\\mathsf{S M A}/\\mathsf{M o O}_{3}/$ Al for hole-only devices and ITO/ZnO/PM6:SMA/PNDIT-F3N/Al for electron-only devices. For PM6:Y6, the hole mobility and the electron mobility are $4.3\\times10^{-4}$ $\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ and $3.4\\times10^{-4}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ , respectively. However, for PM6:N-C11, the hole mobility and the electron mobility are $3.1\\times10^{-4}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ and $1.1\\times$ $10^{-4}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ , respectively, in the blend film (Table S1 and Figure S3) . The lower and less-balanced charge mobility of PM6:N-C11 could partially contribute to inferior device performance of PM6:N-C11 devices. \n\nTo investigate the difference in their blend film morphology, state-of-the-art X-ray characterization methods such as grazing-incidence wide-angle X-ray scattering (GIWAXS) \n\n# Joule \n\n![](images/9ab72ac49483c949fcc1860f81c20e68e2ee25e2197d63b30bd79e32ad129a12.jpg) \nFigure 2. Photovoltaic Characteristics of the PM6:SMA OPVs with Conventional Architectures (A) J-V curve. (B) EQE spectra of PM6:acceptor(s). \n\nand resonant soft X-ray scattering $({\\mathsf{R S o}}\\mathsf{X S})^{38-40}$ were conducted on both films. From GIWAXS results of neat films, both SMAs have a (010) scattering peak at around $1.77mathring\\mathsf{A}^{-1}$ . This corresponds to an identical $\\pi-\\pi$ stacking distance of $3.54\\mathring{\\mathsf{A}}$ (Figure 3 and Table 2). However, PM6:Y6 has a higher normalized peak intensity than PM6:N-C11, suggesting that Y6 in the blend film has a larger volume fraction of highly packed molecules than N-C11, which is often beneficial to charge transport.41 Also, RSoXS using X-ray with a photon energy of $283.8\\mathsf{e V}$ was performed to determine the relative purity and average size of domains in the blend films. The relative root-mean-square composition variation (monotonically related to the domain purity) can be obtained by taking the square root of the integrated scattering intensity (ISI) over the q range detected. Since PM6:Y6 blend has the highest ISI, all the blend ISIs were normalized to the PM6:Y6 for easy relative comparison. For PM6:N-C11 blend, the relative composition variation is 0.83 (Table 3), which means that there is more intermixing in the mixed domain, generating more trap states in the blend. The lower domain purity and more imbalanced charge mobility (described in the previous page) should both partially contribute to the lower FF of PM6:N-C11-based devices. At acceptor concentrations above the percolation threshold, the relation between purity and $F F$ has been explicitly and quantitatively shown in model systems.10 Also, we measure the $J_{s c}$ under different light intensity and plot the $J_{s c}$ against the light intensity (Figure S2). The relationship between $J_{s c}$ and light intensity $(P)$ can be described as $J s c=k P^{S}$ .42 If all the free charges can be collected at the electrodes prior to recombination, the value of S is unity. If there is some extent of bimolecular recombination before charge collection, the value of S will be smaller than unity. The experimental S values of PM6:Y6 and PM6:N-C11 are 0.975 and 0.935, respectively, which indicates that PM6:NC11 suffers from more bimolecular recombination. Overall, lower crystallinity and impure domains can explain the lower and imbalanced charge mobility, which are the reasons for the lower $F F$ of PM6:N-C11 devices. \n\nWe further estimated the long period by fitting the ${\\sf R S o X S}$ profiles with a single lognormal peak (Figure S7). In the PM6:Y6 blend film, the scattering peak locates at $0.15\\ \\mathsf{n m}^{-1}$ , which corresponds to a long period of $41.9\\:\\mathrm{nm}$ (Figure 4 and Table 3). With the assumption of a two-phase morphology, the average domain size, which is approximately half of the long period, of PM6:Y6 is $21{\\mathsf{n m}}$ , which is close to the optimal domain size of $20\\mathsf{n m}$ generally accepted by the OSC research community. Using the same characterization method, it was found that PM6:N-C11 has a scattering peak at $0.056\\ \\mathsf{n m}^{-1}$ , which corresponds to an average domain size of $56~\\mathsf{n m}$ . The AFM images of PM6:N-C11 also show larger grains in the PM6:N-C11 blend film (Figure S5). This evidence supports the hypothesis that the poor solubility of N-C11 results in formation of large domains in the blend film during the spincoating process. The larger domain may cause issues on charge separation and partially contribute to the lower EQE and $J_{s c}$ of the PM6:N-C11 devices. \n\n![](images/e3c23e644eab666f66b8b7263976aa8c6f002e45bc2270ee70f82fd8d9d9e74b.jpg) \nFigure 3. Molecular Packing Behaviors of PM6:SMA Blend Films (A–D) 2D GIWAXS patterns of (A) PM6:Y6, (B) PM6:N-C11, (C) PM6:N3, and (D) PM6:N4. (E) 1D profiles of PM6:SMAs blend films. Dashed lines represent the in-plane profiles, and solid lines show the out-of-plane direction. \n\nAll these results indicate that the use of branched alkyl chains on the pyrrole motif is important to the optimal solubility and morphology properties of the SMAs. In previous studies, the branching position of the alkyl chain is shown to be important in the morphology and performance of organic, electronic, and photoelectronic devices including OSCs and organic transistor devices.33,34 Therefore, to further improve the performance of the SMA, we optimized the branching position of the alkyl chain on the SMA. A $3^{\\mathsf{r d}}$ -position branched alkyl chain (3-ethylheptyl, 3EH) and $4^{\\mathrm{th}}$ -position branched alkyl chain (4-ethyloctyl, 4EO) were used to replace the $2^{\\mathsf{n d}}$ -position branched alkyl chain (2-ethylhexyl) on the pyrrole motif. The molecule with a $1^{\\mathsf{s t}}$ -position branched alkyl chain was unable to be obtained due to synthetic difficulty. \n\nThese two molecules are named N3 and N4 and are shown in Figure 1. These two molecules can be synthesized following the reported synthetic route of Y6 by using commercially available alkyl bromides. Similarly, the optical and electronic properties of N3 and N4 in solution are consistent with those of Y6 and N-C11. Interestingly when the alkyl chain is changed from 2-ethylhexyl to 3-ethylheptyl and 4-ethyloctyl, the solubility of the molecules is significantly increased. The solubilities of Y6, N3, \n\n# Joule \n\nTable 2. GIWAXS Characteristics of Different PM6:SMA Blend Films \n\n\n
Blend(010) Peaka Position (A-1)(010) Stacking Distance (A)FWHM of (010) Peak (A-1)Coherence Length of (010) Stacking (A)Normalized (010) Peak Intensity
PM6:Y61.7743.540.26224.00.96
PM6:N- C111.7753.540.25324.80.48
PM6:N31.773.550.22827.51
PM6:N41.783.530.14543.31N.A.
\n\na(010) peak intensity in the out-of-plane direction was calculated for PM6:Y6, PM6:N-C11, and PM6:N3. For the PM6:N4 blend, the diffraction is in the in-plane direction; therefore, direct comparison of peak intensity is not accurate. \n\nand N4 in chloroform are $40\\:\\mathrm{mg/mL}$ , $64~\\mathrm{mg/mL}$ , and $120~\\mathrm{mg/mL}$ , respectively. The trend of increased solubility from Y6 to N3 to N4 is interesting. One of the possible reasons is that the side chains on N3 and N4 are one and two carbons longer than that on the pyrrole unit of Y6, which could increase the solubility of the molecule. While other effects (steric hindrance of the two adjacent branched alkyl chains) could be possible, it would require in-depth theoretical modulation (such as molecular dynamics simulation) to fully understand the structure-property relationship (Figure S4). Organic solar cell devices were made using the same device architecture as PM6:Y6 and PM6:N-C11. The device performance is summarized in Table 1. It is obvious that the N4-based device exhibits the worst performance, with a decreased $F F$ of $69.9\\%$ , which leads to an average performance of $13.63\\%$ . On the other hand, the binary N3 device exhibits the best performance among the three SMAs. The $V_{o c}$ and FF are similar to those of Y6, but the $J_{s c}$ significantly increases from $24.02\\ m\\mathsf{A}\\ c m^{-2}$ to $25.81~\\mathsf{m A}~\\mathsf{c m}^{-2}$ , and thus a higher overall efficiency of $15.79\\%$ was achieved. \n\nTo understand the differences in performance for these SMAs with different alkyl chain branching positions, GIWAXS and ${\\sf R S o X S}$ experiments were also performed. Here we first intend to understand the origin of the significantly lower performance of the N4-based devices. The RSoXS profiles and the parameters extracted are shown in Figure 4 and Table 3, respectively. The long period of PM6:N4 blend $(122\\ \\mathsf{n m})$ is significantly larger than those of the other two blends $(41.9\\ \\mathsf{n m}$ for PM6:Y6, $43.9\\:\\mathrm{nm}$ for PM6:N3); hence, the domain size of the PM6:N4-based blend can be as large as $56~\\mathsf{n m}$ . This domain size is larger than the commonly accepted optimal domain size for OSCs, which is about $20~\\mathsf{n m}$ .43–45 Also, by obtaining the square root of normalized ISI value, the relative average purity of all domains of PM6:N4 is the lowest within these three systems. This could partially contribute to the lower FF of PM6:N4 devices. Moreover, the GIWAXS data show that the PM6:N4-based blend shows predominantly edge-on preferred orientation, while \n\nTable 3. RSoXS Characteristics of Different PM6:SMA Blend Films \n\n\n
Blend Peak Position (nm-1)Long Period (nm)Average Domain Size (nm)Normalized ISIRoot-Mean- Square Composition Variationa
PM6:Y60.1541.921.01
PM6:N- C110.056112.756.40.690.83
PM6:N30.14343.922.00.9240.96
PM6:N40.056112.156.10.8020.90
\n\naMonotonically related to the average phase purity. \n\n![](images/f24a7b6b5a8b0c6c9e4b9ff3bf323a20e8fbde51a0d02ec5134776fad38e292c.jpg) \nFigure 4. Lorentz Corrected RSoXS Profiles of PM6:SMA Blend Films Acquired at 283.8 eV Exhibiting Log-Normal Composition Distributions \n\nY6 and N3 show more face-on orientation. The ratio of face-on and edge-on orientation is the smallest for the PM6:N4-based blend compared to other ones covered in this study. The relatively higher fraction of edge-on orientation observed in the blend film contributes to the inferior charge transport of the PM6:N4 device.30,46,47 In terms of charge mobility, PM6:N4 also suffers from imbalanced charge mobility. Both hole and electron mobility of PM6:N3 and PM6:N4 were determined with the same method for PM6:N-C11. It was found that the hole and electron mobility of PM6:N4 are $3.2\\times10^{-4}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ and $1.4\\times10^{-4}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ , respectively, which is more imbalanced than those of PM6:N3 (Table S1 and Figure S3). All the morphology data help to explain the lower and imbalanced charge mobility of the PM6:N4 blend and the lower $F F$ of PM6:N4 devices. \n\nHaving explained why the PM6:N4 devices show a relatively lower performance, we proceeded to understand the morphology-performance relations in the higher-performance N3 system. For the N3-based device, as its performance is slightly better than that of Y6, we again turn to morphology data to explain the differences between them. First, ${\\sf R S o X S}$ data show that both N3- and Y6-based devices have a domain size of ${\\sim}20~\\mathsf{n m}$ , which is suitable for OPV device operation. Next, the coherence length of (010) stacking peaks in the out-of-plane direction of the PM6:N3-based blend is $27.5\\mathring{\\mathsf{A}},$ which is slightly larger than that of PM6:Y6 $(24\\mathring{\\mathsf{A}})$ . We also found that the (010) peak intensity of PM6:N3 is higher. These results indicate that the PM6:N3 blend is less amorphous and more ordered than the PM6:Y6-based blend. Finally, by analyzing the ratio of face-on and edge-on orientation, although both blends showed preferred face-on orientation, the ratio was higher for the PM6:N3-based blend (3.42) than for the PM6:Y6-based blend (2.98) (Figure S6 and Table S2). Besides this morphology data, we also measured the hole and electron mobility of both blends. The PM6:N3-based blend shows higher values (Table S1). The ratio of $\\upmu_{\\mathrm{h}}/\\upmu_{\\mathrm{e}}$ of the PM6:N3 blend is the closest to 1 among all systems, which is beneficial for the overall charge collection and thus the FF, consistent with device performance. \n\nOverall, our results show that the $3^{\\mathsf{r d}}$ -position branched pyrrolic alkyl chain in conjunction with a linear thienyl alkyl chain is the optimum choice for this family of SMAs. A long alkyl chain (e.g., 4-ethyloctyl) results in excessively large and impure domains. Also, the N4 molecule loses the preferred face-on orientation in the blend film. A similar observation has been reported for polymer systems with different alkyl chains. Polymers with excessive solubility (for example, PffBT4T-2DT) tend to form \n\n# Joule \n\n![](images/251f9cb36284453a759ba57e1957aba12101b41b66d3546129dd12290d889629.jpg) \nFigure 5. Device Structure and Photovoltaic Characteristics of Ternary Devices (A) Device architecture and Chemical structures of PM6 and $\\mathsf{P C}_{71}\\mathsf{B M}$ . (B) J-V curve of the ternary device under the illumination of an AM 1.5G solar simulator, $100\\mathsf{m}\\mathsf{W}\\mathsf{c m}^{-2}$ . (C) EQE spectra of the ternary device. \n\nlarger and impure domains.6 We further optimize the OSC devices using the ternary strategy, which has been demonstrated to be an effective way to integrate the advantages of different donors or acceptors. By loading a third component with matching absorption properties or more favorable energy levels into binary blends, the OSC devices can improve $J_{s c},V_{o c},$ and/or $F F,$ and thus device efficiency. Although the OSCs based on PM6:N3 blends can already achieve high efficiencies, the addition of a small amount of phenyl- $\\cdot\\mathsf{C}_{71}$ -butyric acid methyl ester derivatives $(P C_{71}\\mathsf{B M})$ can have significant benefits on $V_{o c},$ $F F,$ and $J_{s c}$ . First, as $\\mathsf{P C}_{71}\\mathsf{B M}$ has a slightly higher-lying LUMO level than N3, the addition of $P C_{71}\\mathsf{B M}$ helps to improve the $V_{o c}$ of the device slightly (from 0.837 to $0.850\\vee$ . Second, $\\mathsf{P C}_{71}\\mathsf{B M}$ -based ternary devices can also achieve higher $F F s$ , which is a phenomenon that has been observed in many examples of ternary OSCs previously. This effect was presumably due to, among other reasons, enhanced electron transport upon adding $\\mathsf{P C}_{71}\\mathsf{B M}$ and the improved percolation with the addition of $\\mathsf{P C}_{71}\\mathsf{B M}$ into the PM6:N3 blend.48 To obtain optimal device performance, we vary the ratio of N3 and $\\mathsf{P C}_{71}\\mathsf{B M}$ in the ternary blends while keeping the overall PM6:acceptor weight ratio at 1:1.2 and the active layer thickness at about $105\\ \\mathsf{n m}$ . By incorporating about $20\\%$ of $P C_{71}\\mathsf{B M}$ acceptor and optimizing the ratio of the acceptors $(N3{:}\\mathsf{P C}_{71}\\mathsf{B M})$ , we achieved efficient $\\mathsf{P M}\\mathsf{\\&N}3:\\mathsf{P C}_{71}\\mathsf{B M}$ (1:0.96:0.24) ternary devices with efficiencies up to $16.74\\%$ (Figures 5B and 5C). As shown in Table 1, the three parameters, i.e., the $V_{o c}$ of $0.850~\\mathsf{V}$ , $J_{s c}$ of $25.71~\\mathsf{m A}~\\mathsf{c m}^{-2}$ , and $F F$ of $76.6\\%$ , were simultaneously enhanced in the ternary cell compared to those in the PM6:N3-based binary cell. One of our best devices was sent to Newport for certification and yielded $16.42\\%$ (Figure S9) under the new stressed certification protocol for solar cells that is enforced by National Renewable Energy Laboratory (NREL): the tested cell must undergo a period of extended light stress around maximum power output point (MPP) with negligible degradation in photocurrent (delta photocurrent less than $0.1\\%$ within 60 s). This result was included in the latest best solar cell efficiency table reported by Green et al. (Figure S8).49 \n\n# Conclusion \n\nTo conclude, we synthesized a series of Y6 analog SMAs with linear, $3^{\\mathsf{r d}}$ -position and $4^{\\mathrm{th}}$ -position branched alkyl chains on the nitrogen atoms on the pyrrole motif of the molecule and studied the influence of alkyl chains on the electronic and morphological properties of the materials and devices. First, by comparing Y6 and N-C11, which have the C11 linear alkyl chain on the pyrrole motif, it is clear that the N-C11 molecule exhibits much worse solubility and excessively large domains, which hurts the power conversion efficiency of the devices. This first comparison shows that it is important to keep the branched alkyl chains on the nitrogen atoms of the molecule. With this finding, we further optimize the branching position of the branched alkyl chain on the pyrrole motif. By comparing the three molecules with different branching positions, we show that the SMA with a $3^{\\mathsf{r d}}$ -position branched alkyl chain gives the optimum morphology and electronic property, thus achieving the best efficiency of $16.0\\%$ . Lastly, by utilizing the ternary strategy (i.e., incorporating a small amount of $\\mathsf{P C}_{71}\\mathsf{B M}$ acceptor), we achieved a highly efficient organic solar cell with a PCE of $16.74\\%$ . One of our best devices has been sent to Newport for certification with the new stress protocol with asymptotic scans, achieving a certified efficiency of $16.42\\%$ , which is one of the highest certified values for single-junction OSCs to date. \n\n# EXPERIMENTAL PROCEDURES \n\n# Materials \n\nAll chemicals, unless otherwise specified, were purchased from commercial resources and used as received. Tetrahydrofuran (THF) and toluene were distilled from sodium and benzophenone under nitrogen before use. The non-fullerene acceptor materials (e.g., N3) are available from eFlexPV (WeChat ID: Y6SALE). Donor polymer PM6 (Mn: $24.2\\ \\mathsf{k D a}$ ; Mw: $88.0~\\mathsf{k D a}$ ; PDI: 3.361) was purchased from Solarmer Material Inc. (www.solarmer.com). \n\n# Optical Characterization \n\nFilm UV-vis absorption spectra were acquired on a PerkinElmer Lambda 20 UV/VIS Spectrophotometer. All film samples were spin-cast on ITO/PEDOT:PSS substrates. \n\n# Atomic Force Microscopy \n\nAtomic force microscopy was performed by using a Scanning Probe Microscope Dimension 3100 in tapping mode. All film samples were spin-cast on ITO/PEDOT:PSS substrates. \n\n# Device Fabrication and Characterization \n\nSolar cells were fabricated in a conventional device configuration of ITO/PEDOT:PSS/active layers/PNDIT-F3N/Ag (Figure 5A). The ITO substrates were first scrubbed by detergent and then sonicated with deionized water, acetone and isopropanol subsequently, and dried overnight in an oven. The glass substrates were treated by UV-Ozone for 30 min before use. PEDOT:PSS (Heraeus Clevios P VP AI 4083) was spin-cast onto the ITO substrates at 5,000 rpm for 30 s and then dried at $\\boldsymbol{150^{\\circ}C}$ for 15 min in air. The PM6:acceptors blends (1:1.2 weight ratio) were dissolved in chloroform (the total concentration of blend solutions was $17.6~\\mathrm{mg}~\\mathrm{mL}^{-1}$ for all blends), with the addition of $0.05\\%$ CN as additive, and stirred overnight on a hotplate at $55^{\\circ}\\mathsf{C}$ in a nitrogen-filled glove box. The blend solutions were spincast at 3,000 rpm for 35 s on the top of a PEDOT:PSS layer followed by a thermal annealing step at $90^{\\circ}\\mathsf{C}$ for 5 min. PM6:N $3{:}\\mathsf{P C}_{71}\\mathsf{B M}$ -based ternary devices were fabricated using the same conditions of the binary devices. A thin PNDIT-F3N layer was coated on the active layer, followed by the deposition of Ag $(220\\mathsf{n m})$ (evaporated under $5\\times10^{-5}$ Pa through a shadow mask). The optimal active layer thickness measured by a Bruker Dektak XT stylus profilometer was about $110\\mathrm{nm}$ . The current densityvoltage $(J-V)$ curves of all encapsulated devices were measured using a Keithley 2400 Source Meter in air under AM 1.5G $100\\mathsf{m}\\mathsf{W}\\mathsf{c m}^{-2},$ ) using a Newport solar simulator. The light intensity was calibrated using a standard Si diode (with KG5 filter, purchased from PV Measurement to bring spectral mismatch to unity). An optical microscope (Olympus BX51) was used to define the device area $(5.9~\\mathsf{m m}^{2})$ ). EQEs were \n\n# Joule \n\nmeasured using an Enlitech QE-S EQE system equipped with a standard Si diode. \nMonochromatic light was generated from a Newport 300 W lamp source. \n\n# Hole Mobility and Electron Mobility Measurements \n\nThe hole-only or electron-only diodes were measured using the space charge limited current (SCLC) method, employing the following device architectures: $1\\mathsf{T O}/\\mathsf{M o O}_{3}/$ blend fil $\\mathsf{\\Omega}_{\\mathsf{N M o O}_{3}/\\mathsf{A l}}$ for holes and ITO/ZnO/blend film/PNDIT-F3N/Al for electrons. The mobilities were obtained by taking current-voltage curves and fitting the results to a space charge limited form, where the SCLC is described by \n\n$$\nJ=\\frac{9\\varepsilon_{0}\\varepsilon_{r}\\mu V^{2}}{8L^{3}},\n$$ \n\nwhere $\\varepsilon_{O}$ is the permittivity of free space, $\\varepsilon_{r}$ is the relative permittivity of the material (assumed to be 3), $\\upmu$ is the hole mobility, and $\\boldsymbol{L}$ is the thickness of the film. From the plots of $J^{1/2}$ versus $V,$ electron mobilities can be deduced. \n\n# GIWAXS Characterization \n\nGIWAXS measurements were performed at beamline 7.3.3 at the Advanced Light Source. Samples were prepared on Si substrates using blend solutions and conditions identical to those used in OPV fabrication. The $\\boldsymbol{10}\\boldsymbol{\\mathrm{keV}}\\times$ -ray beam was incident at a grazing angle of $0.11^{\\circ}-0.15^{\\circ}$ , which maximized the scattering intensity from the samples. The scattered X-rays were detected using a Dectris Pilatus 2M photon counting detector. In-plane and out-of-plane sector averages were calculated using the Nika software package. The uncertainty for the peak fitting of the GIWAXS data is $0.3\\mathsf{A}$ . The coherence length was calculated using the Scherrer equation: $\\mathsf{C L}=2\\pi\\mathsf{K}/\\Delta\\mathsf{q},$ where $\\Delta\\mathsf{q}$ is the full width at half-maximum of the peak and K is a shape factor (0.94 was used here). \n\nThe azimuthal angle was defined to be $\\omega$ , which is the angle with respect to the $\\mathsf{q}_{z}$ axis. The face-on/edge-on ratio can be calculated from the following equation. \n\n$$\nf a c e-o n/e d g}-o n\\ r a t i o=\\frac{\\int_{\\pi/4}^{\\pi/2}I(X)d X}{\\int_{0}^{\\pi/4}I(X)d X}.\n$$ \n\n# R-SoXS Characterization \n\n$R-S_{0}\\times S$ transmission measurements were performed at beamline 11.0.1.2 at the Advanced Light Source. Samples for $R{-}S_{0}X S$ measurement were prepared on a PSS modified Si substrate under the same conditions as those used for device fabrication and then transferred by floating in water to a $1.5\\times1.5\\mathsf{m m}$ , $100\\mathsf{n m}$ thick Si3N4 membrane supported by a $5\\times5~\\mathrm{mm}$ , $200\\upmu\\mathrm{m}$ thick Si frame (Norcada Inc.). 2D scattering patterns were collected on an in-vacuum charge-coupled device (CCD) camera (Princeton Instrument PI-MTE). The sample detector distance was calibrated from diffraction peaks of a triblock copolymer poly (isoprene-b-styrene-b-2-vinyl pyridine), which has a known spacing of $391\\mathring{\\mathsf{A}}.$ The beam size at the sample is approximately $100\\times200~{\\upmu\\mathrm{m}}$ . The composition variation (or relative domain purity) over the length scales probed can be extracted by integrating scattering profiles to yield the total scattering intensity. The median domain spacing is calculated from $2\\pi/{\\mathsf{q}},$ , where q here corresponds to half the total scattering intensity. The purer the average domains are, the higher the total scattering intensity. Owing to a lack of absolute flux normalization, the absolute composition cannot be obtained only by $R{-}S_{0}X S$ . \n\n# Solubility Measurement \n\nTo $150\\mathrm{mg}$ of SMA, $1~\\mathsf{m L}$ of chloroform $0.6\\%$ ethanol as stabilizer) was added. The solution was stirred for 30 min at room temperature. The solution was filtered with a \n\n$0.2~{\\upmu\\mathrm{m}}$ PTFE membrane. To $0.5~\\mathrm{mL}$ of the filtrate, methanol was added in portions until all solids precipitated out. The precipitate was filtered out with a $0.2~{\\upmu\\mathrm{m}}$ PTFE membrane and dried under vacuum. The weight of the precipitate was weighed by weight-by-difference. The solubility of the SMA can be calculated by the following equation. \n\n$$\ns o l u b i l i t y~(m g/~m L)=~\\frac{w e i g h t~o f~t h e~p r e c i p i t a t e~(m g)}{0.5~m L}.\n$$ \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information can be found online at https://doi.org/10.1016/j.joule. \n2019.09.010. \n\n# ACKNOWLEGMENTS \n\nY.Z. acknowledges National Natural Science Foundation of China (21875286), the National Key Research & Development Projects of China (2017YFA0206600), and Science Fund for Distinguished Young Scholars of Hunan Province (2017JJ1029). K.J. and H.Y. acknowledge the Shen Zhen Technology and Innovation Commission (project numbers JCYJ20170413173814007, JCYJ20170818113905024), the Hong Kong Research Grants Council (Research Impact Fund R6021-18, project numbers 16305915, 16322416, 606012, and 16303917), and Hong Kong Innovation and Technology Commission for the support through projects ITC-CNERC14SC01 and ITS/471/18. Z.P., L.Y., and H.A. were supported by the U.S. Office of Naval Research (ONR), under award no. N000141712204. X-ray data were acquired at the Advanced Light Source (beamlines 5.3.2.2, 7.3.3, and 11.0.1.2), which is a user facility of the U.S. Department of Energy Office of Science (no. DE-AC02-05CH11231). C. Wang, C. Zhu, E. Schaible, and M. Marcus are appreciated for beamline maintenance and support. \n\n# AUTHOR CONTRIBUTIONS \n\nK.J., Y.Z., and H.Y. conceived the idea and designed the experiment; K.J. performed the device fabrication and data analysis; K.J. prepared the devices for certification and samples for X-ray characterization; Q.W., J.Y.L.L., H.K.K., and J.Y. synthesized N3; J.Y.L.L. and H.K.K. synthesized Y6, N-C11, and N4; Z.P. performed the GIWAXS and RSoXS experiment and data analysis supervised by L.Y. and H.A.; K.J., J.Y.L.L., Y.Z., and H.Y. wrote the original draft; all authors discussed the results and commented on the manuscript; Y.Z. and H.Y. directed the project. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: June 24, 2019 \nRevised: September 2, 2019 \nAccepted: September 19, 2019 \nPublished: October 7, 2019 \n\n# REFERENCES \n\n1. Yu, G., Gao, J., Hummelen, J.C., Wudl, F., and Heeger, A.J. (1995). Polymer Photovoltaic Cells: Enhanced Efficiencies via a Network of Internal Donor-Acceptor Heterojunctions. Science 270, 1789–1791. \n2. Li, G., Shrotriya, V., Huang, J., Yao, Y., Moriarty, T., Emery, K., and Yang, Y. (2005). High \n\nefficiency solution processable polymer photovoltaic cells by selforganization of polymer blends. Nat. Mater. 4, 864–868. 3. You, J., Dou, L., Yoshimura, K., Kato, T., Ohya, K., Moriarty, T., Emery, K., Chen, C.-C., Gao, J., Li, G., and Yang, Y. (2013). A polymer tandem solar cell with $10.6\\%$ power conversion efficiency. Nat. Commun. 4, 1446. \n\n4. Hou, J., Ingana¨ s, O., Friend, R.H., and Gao, F. (2018). Organic solar cells based on non-fullerene acceptors. Nat. Mater. ${17},$ 119–128. \n\n# Joule \n\n5. Yan, C., Barlow, S., Wang, Z., Yan, H., Jen, A.K.Y., Marder, S.R., and Zhan, X. (2018). Nonfullerene acceptors for organic solar cells. Nat. Rev. Mater. 3, 18003. \n6. Liu, Y., Zhao, J., Li, Z., Mu, C., Ma, W., Hu, H., Jiang, K., Lin, H., Ade, H., and Yan, H. (2014). Aggregation and morphology control enables multiple cases of high-efficiency polymer solar cells. Nat. Commun. 5, 5293. \n7. Zhao, J., Li, Y., Yang, G., Jiang, K., Lin, H., Ade, H., Ma, W., and Yan, H. (2016). Efficient organic solar cells processed from hydrocarbon solvents. Nat. Energy 1, 15027. \n8. Li, Y. (2012). Molecular design of photovoltaic materials for polymer solar cells: toward suitable electronic energy levels and broad absorption. Acc. Chem. Res. 45, 723–733. \n9. Li, N., Perea, J.D., Kassar, T., Richter, M., Heumueller, T., Matt, G.J., Hou, Y., Gu¨ ldal, N.S., Chen, H., Chen, S., et al. (2017). Abnormal strong burn-in degradation of highly efficient polymer solar cells caused by spinodal donoracceptor demixing. Nat. Commun. 8, 14541. \n10. Ye, L., Hu, H., Ghasemi, M., Wang, T., Collins, B.A., Kim, J.-H., Jiang, K., Carpenter, J.H., Li, H., Li, Z., et al. (2018). Quantitative relations between interaction parameter, miscibility and function in organic solar cells. Nat. Mater. 17, 253–260. \n11. Liu, J., Chen, S., Qian, D., Gautam, B., Yang, G., Zhao, J., Bergqvist, J., Zhang, F., Ma, W., Ade, H., et al. (2016). Fast charge separation in a non-fullerene organic solar cell with a small driving force. Nat. Energy 1, 16089. \n12. Dyer-Smith, C., Howard, I.A., Cabanetos, C., El Labban, A., Beaujuge, P.M., and Laquai, F. (2015). Interplay Between Side Chain Pattern, Polymer Aggregation, and Charge Carrier Dynamics in PBDTTPD:PCBM BulkHeterojunction Solar Cells. Adv. Energy Mater. 5, 1401778. \n13. Qian, D., Zheng, Z., Yao, H., Tress, W., Hopper, T.R., Chen, S., Li, S., Liu, J., Chen, S., Zhang, J., et al. (2018). Design rules for minimizing voltage losses in high-efficiency organic solar cells. Nat. Mater. 17, 703–709. \n14. Meng, L., Zhang, Y., Wan, X., Li, C., Zhang, X., Wang, Y., Ke, X., Xiao, Z., Ding, L., Xia, R., et al. (2018). Organic and solution-processed tandem solar cells with $17.3\\%$ efficiency. Science 361, 1094–1098. \n15. Zhao, W., Qian, D., Zhang, S., Li, S., Ingana¨ s, O., Gao, F., and Hou, J. (2016). Fullerene-Free Polymer Solar Cells with over $11\\%$ Efficiency and Excellent Thermal Stability. Adv. Mater. 28, 4734–4739. \n16. Chen, S., Liu, Y., Zhang, L., Chow, P.C.Y., Wang, Z., Zhang, G., Ma, W., and Yan, H. (2017). A Wide-Bandgap Donor Polymer for Highly Efficient Non-fullerene Organic Solar Cells with a Small Voltage Loss. J. Am. Chem. Soc. 139, 6298–6301. \n17. Xiao, Z., Jia, X., and Ding, L. (2017). Ternary organic solar cells offer $14\\%$ power conversion efficiency. Sci. Bull. (Beijing) 62, 1562. \n18. Yuan, J., Huang, T., Cheng, P., Zou, Y., Zhang, H., Yang, J.L., Chang, S.-Y., Zhang, Z., Huang, W., Wang, R., et al. (2019). Enabling low voltage losses and high photocurrent in fullerene-free organic photovoltaics. Nat. Commun. 10, 570. \n19. Zhang, J., Li, Y., Huang, J., Hu, H., Zhang, G., Ma, T., Chow, P.C.Y., Ade, H., Pan, D., and Yan, H. (2017). Ring-Fusion of Perylene Diimide Acceptor Enabling Efficient Nonfullerene Organic Solar Cells with a Small Voltage Loss. J. Am. Chem. Soc. 139, 16092–16095. \n20. Holliday, S., Ashraf, R.S., Wadsworth, A., Baran, D., Yousaf, S.A., Nielsen, C.B., Tan, C.-H., Dimitrov, S.D., Shang, Z., Gasparini, N., et al. (2016). High-efficiency and air-stable P3HTbased polymer solar cells with a new no fullerene acceptor. Nat. Commun. 7, 11585. \n21. Baran, D., Ashraf, R.S., Hanifi, D.A., Abdelsamie, M., Gasparini, N., Ro¨ hr, J.A., Holliday, S., Wadsworth, A., Lockett, S., Neophytou, M., et al. (2017). Reducing the efficiency-stability-cost gap of organic photovoltaics with highly efficient and stable small molecule acceptor ternary solar cells. Nat. Mater. 16, 363–369. \n22. Baran, D., Kirchartz, T., Wheeler, S., Dimitrov, S., Abdelsamie, M., Gorman, J., Ashraf, R.S., Holliday, S., Wadsworth, A., Gasparini, N., et al. (2016). Reduced voltage losses yield $10\\%$ efficient fullerene free organic solar cells with >1 V open circuit voltages. Energy Environ. Sci. 9, 3783–3793. \n23. Cui, Y., Yao, H., Zhang, J., Zhang, T., Wang, Y., Hong, L., Xian, K., Xu, B., Zhang, S., Peng, J., et al. (2019). Over $16\\%$ efficiency organic photovoltaic cells enabled by a chlorinated acceptor with increased open-circuit voltages. Nat. Commun. 10, 2515. \n24. Zhang, G., Zhao, J., Chow, P.C.Y., Jiang, K., Zhang, J., Zhu, Z., Zhang, J., Huang, F., and Yan, H. (2018). Nonfullerene Acceptor Molecules for Bulk Heterojunction Organic Solar Cells. Chem. Rev. 118, 3447–3507. \n25. Zhang, J., Tan, H.S., Guo, X., Facchetti, A., and Yan, H. (2018). Material insights and challenges for non-fullerene organic solar cells based on small molecular acceptors. Nat. Energy 3, 720–731. \n26. Yuan, J., Zhang, Y., Zhou, L., Zhang, G., Yip, H.-L., Lau, T.-K., Lu, X., Zhu, C., Peng, H., Johnson, P.A., et al. (2019). Single-Junction Organic Solar Cell with over $15\\%$ Efficiency Using Fused-Ring Acceptor with ElectronDeficient Core. Joule 3, 1140–1151. \n27. Chen, S., Zhang, L., Ma, C., Meng, D., Zhang, J., Zhang, G., Li, Z., Chow, P.C.Y., Ma, W., Wang, Z., et al. (2018). Alkyl Chain Regiochemistry of Benzotriazole-Based Donor Polymers Influencing Morphology and Performances of Non-Fullerene Organic Solar Cells. Adv. Energy Mater. 8, 1702427. \n28. Hu, H., Jiang, $\\mathsf{K}_{\\cdot,\\prime}$ Yang, G., Liu, J., Li, Z., Lin, H., Liu, Y., Zhao, J., Zhang, J., Huang, F., et al. (2015). Terthiophene-based D-A polymer with an asymmetric arrangement of alkyl chains that enables efficient polymer solar cells. J. Am. Chem. Soc. 137, 14149–14157. \n29. Hu, H., Chow, P.C.Y., Zhang, G., Ma, T., Liu, J., Yang, G., and Yan, H. (2017). Design of Donor Polymers with Strong TemperatureDependent Aggregation Property for Efficient Organic Photovoltaics. Acc. Chem. Res. 50, 2519–2528. \n30. Osaka, I., Saito, M., Koganezawa, T., and Takimiya, K. (2014). Thiophene-thiazolothiazole copolymers: significant impact of side chain composition on backbone orientation and solar cell performances. Adv. Mater. 26, 331–338. \n31. Lee, K.C., Song, S., Lee, J., Kim, D.S., Kim, J.Y., and Yang, C. (2015). A roundabout approach to control morphological orientation and solarcell performance by modulating side-chain branching position in benzodithiophenebased polymers. ChemPhysChem 16, 1305– 1314. \n32. Li, Z., Jiang, K., Yang, G., Lai, J.Y.L., Ma, T., Zhao, J., Ma, W., and Yan, H. (2016). Donor polymer design enables efficient non-fullerene organic solar cells. Nat. Commun. 7, 13094. \n33. Lei, T., Dou, J.-H., and Pei, J. (2012). Influence of alkyl chain branching positions on the hole mobilities of polymer thin-film transistors. Adv. Mater. 24, 6457–6461. \n34. Yao, Z.-F., Wang, J.-Y., and Pei, J. (2018). Control of $\\pi-\\pi$ Stacking via Crystal Engineering in Organic Conjugated Small Molecule Crystals. Cryst. Growth Des. 18, 7–15. \n35. Haddon, R.C., Chi, X., Itkis, M.E., Anthony, J.E., Eaton, D.L., Siegrist, T., Mattheus, C.C., and Palstra, T.T.M. (2002). Band Electronic Structure of One- and Two-Dimensional Pentacene Molecular Crystals. J. Phys. Chem. B 106, 8288– 8292. \n36. Anthony, J.E., Eaton, D.L., and Parkin, S.R. (2002). A road map to stable, soluble, easily crystallized pentacene derivatives. Org. Lett. 4, 15–18. \n37. Chen, Z., Hu, Z., Wu, Z., Liu, X., Jin, Y., Xiao, M., Huang, F., and Cao, Y. (2017). Counteriontunable n-type conjugated polyelectrolytes for the interface engineering of efficient polymer solar cells. J. Mater. Chem. A Mater. Energy Sustain. 5, 19447–19455. \n38. Hexemer, A., Bras, W., Glossinger, J., Schaible, E., Gann, E., Kirian, R., MacDowell, A., Church M., Rude, B., and Padmore, H. (2010). A SAXS/ WAXS/GISAXS beamline with multilayer monochromator. Journal of Physics: Conference Series 247, 012007. \n39. Collins, B.A., Li, Z., Tumbleston, J.R., Gann, E., McNeill, C.R., and Ade, H. (2013). Absolute Measurement of Domain Composition and Nanoscale Size Distribution Explains Performance in PTB7:PC71BM Solar Cells. Adv. Energy Mater. 3, 65–74. \n40. Ma, W., Tumbleston, J.R., Wang, M., Gann, E., Huang, F., and Ade, H. (2013). Domain Purity, Miscibility, and Molecular Orientation at Donor/Acceptor Interfaces in High Performance Organic Solar Cells: Paths to Further Improvement. Adv. Energy Mater. 3, 864–872. \n41. Li, W., Albrecht, S., Yang, L., Roland, S., Tumbleston, J.R., McAfee, T., Yan, L., Kelly, M.A., Ade, H., Neher, D., and You, W. (2014). Mobility-controlled performance of thick solar cells based on fluorinated copolymers. J. Am. Chem. Soc. 136, 15566–15576. \n42. Jiang, K., Zhang, G., Yang, G., Zhang, J., Li, Z., Ma, T., Hu, H., Ma, W., Ade, H., and Yan, H. (2018). Multiple Cases of Efficient Nonfullerene Ternary Organic Solar Cells Enabled by an Effective Morphology Control Method. Adv. \nEnergy Mater. 8, 1701370. \n43. Hoppe, H., Niggemann, M., Winder, C. Kraut, J., Hiesgen, R., Hinsch, A., Meissner, D., and Sariciftci, N.S. (2004). Nanoscale Morphology of Conjugated Polymer/ Fullerene-Based Bulk- Heterojunction Solar Cells. Adv. Funct. Mater. 14, 1005– \n1011. \n44. Shaw, P.E., Ruseckas, A., and Samuel, I.D.W. (2008). Exciton diffusion measurements in poly(3-hexylthiophene). Adv. Mater. 20, 3516– \n3520. \n45. Dou, L., You, J., Hong, Z., Xu, Z., Li, G., Street, R.A., and Yang, Y. (2013). 25th anniversary article: a decade of organic/polymeric photovoltaic research. Adv. Mater. 25, 6642– 6671. \n46. Vohra, V., Kawashima, K., Kakara, T. Koganezawa, T., Osaka, I., Takimiya, K., and Murata, H. (2015). Efficient inverted polymer solar cells employing favourable molecular orientation. Nat. Photonics 9, 403. \n47. Guo, X., Zhou, N., Lou, S.J., Smith, J., Tice, D.B., Hennek, J.W., Ortiz, R.P., Navarrete, J.T.L., Li, S., Strzalka, J., et al. (2013). Polymer solar cells \n\nwith enhanced fill factors. Nat. Photonics 7, 825. \n\n48. Zhu, Y., Gadisa, A., Peng, Z., Ghasemi, M., Ye, L., Xu, Z., Zhao, S., and Ade, H. (2019). Rational Strategy to Stabilize an Unstable HighEfficiency Binary Nonfullerene Organic Solar Cells with a Third Component. Adv. Energy Mater. 9, 1900376. \n49. Green, M.A., Dunlop, E.D., Levi, D.H., HohlEbinger, J., Yoshita, M., and Ho-Baillie, A.W.Y. (2019). Solar cell efficiency tables (version 54). Prog. Photovolt. Res. Appl. 27, 565–575. " + }, + { + "id": "10.1038_s41586-019-1783-1", + "DOI": "10.1038/s41586-019-1783-1", + "DOI Link": "http://dx.doi.org/10.1038/s41586-019-1783-1", + "Relative Dir Path": "mds/10.1038_s41586-019-1783-1", + "Article Title": "Additive manufacturing of ultrafine-grained high-strength titanium alloys", + "Authors": "Zhang, DY; Qiu, D; Gibson, MA; Zheng, YF; Fraser, HL; StJohn, DH; Easton, MA", + "Source Title": "NATURE", + "Abstract": "Additive manufacturing, often known as three-dimensional (3D) printing, is a process in which a part is built layer-by-layer and is a promising approach for creating components close to their final (net) shape. This process is challenging the dominullce of conventional manufacturing processes for products with high complexity and low material waste(1). Titanium alloys made by additive manufacturing have been used in applications in various industries. However, the intrinsic high cooling rates and high thermal gradient of the fusion-based metal additive manufacturing process often leads to a very fine microstructure and a tendency towards almost exclusively columnar grains, particularly in titanium-based alloys(1). (Columnar grains in additively manufactured titanium components can result in anisotropic mechanical properties and are therefore undesirable(2).) Attemptsto optimize the processing parameters of additive manufacturing have shown that it is difficult to alter the conditions to promote equiaxed growth of titaniumgrains(3). In contrast with other common engineering alloys such as aluminium, there is no commercial grain refiner for titanium that is able to effectively refine the microstructure. To address this challenge, here we report on the development of titanium-copper alloys that have a high constitutional supercooling capacity as a result of partitioning of the alloying element during solidification, which can override the negative effect of a high thermal gradient in the laser-melted region during additive manufacturing. Without any special process control or additional treatment, our as-printed titanium-copper alloy specimens have a fully equiaxed fine-grained microstructure. They also display promising mechanical properties, such as high yield strength and uniform elongation, compared to conventional alloys under similar processing conditions, owing to the formation of an ultrafine eutectoid microstructure that appears as a result of exploiting the high cooling rates and multiple thermal cycles of the manufacturing process. We anticipate that this approach will be applicable to other eutectoid-forming alloy systems, and that it will have applications in the aerospace and biomedical industries.", + "Times Cited, WoS Core": 745, + "Times Cited, All Databases": 798, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000501599200046", + "Markdown": "# Article \n\n# Additive manufacturing of ultrafine-grained high-strength titanium alloys \n\nhttps://doi.org/10.1038/s41586-019-1783-1 \n\nReceived: 4 March 2019 \n\nAccepted: 8 October 2019 \n\nPublished online: 4 December 2019 \n\nDuyao Zhang1,6, Dong Qiu1,6, Mark A. Gibson1,3, Yufeng Zheng2,5, Hamish L. Fraser2\\*, David H. StJohn4 & Mark A. Easton1\\* \n\nAdditive manufacturing, often known as three-dimensional (3D) printing, is a process in which a part is built layer-by-layer and is a promising approach for creating components close to their final (net) shape. This process is challenging the dominance of conventional manufacturing processes for products with high complexity and low material waste1. Titanium alloys made by additive manufacturing have been used in applications in various industries. However, the intrinsic high cooling rates and high thermal gradient of the fusion-based metal additive manufacturing process often leads to a very fine microstructure and a tendency towards almost exclusively columnar grains, particularly in titanium-based alloys1. (Columnar grains in additively manufactured titanium components can result in anisotropic mechanical properties and are therefore undesirable2.) Attempts to optimize the processing parameters of additive manufacturing have shown that it is difficult to alter the conditions to promote equiaxed growth of titanium grains3. In contrast with other common engineering alloys such as aluminium, there is no commercial grain refiner for titanium that is able to effectively refine the microstructure. To address this challenge, here we report on the development of titanium–copper alloys that have a high constitutional supercooling capacity as a result of partitioning of the alloying element during solidification, which can override the negative effect of a high thermal gradient in the laser-melted region during additive manufacturing. Without any special process control or additional treatment, our as-printed titanium–copper alloy specimens have a fully equiaxed fine-grained microstructure. They also display promising mechanical properties, such as high yield strength and uniform elongation, compared to conventional alloys under similar processing conditions, owing to the formation of an ultrafine eutectoid microstructure that appears as a result of exploiting the high cooling rates and multiple thermal cycles of the manufacturing process. We anticipate that this approach will be applicable to other eutectoid-forming alloy systems, and that it will have applications in the aerospace and biomedical industries. \n\nAccording to Interdependence Theory4, the key factors controlling grain size include: (1) $\\Delta T_{\\mathfrak{n}},$ , the critical undercooling for nucleation; (2) $\\Delta T_{\\mathrm{cs}},$ the amount of constitutional supercooling in front of the growing solid that provides the nucleation undercooling; and $(3)x_{\\mathrm{sd}},$ the average spacing between the potent nucleation particles. A small $\\Delta T_{\\mathfrak{n}}$ , large $\\Delta T_{\\mathrm{cs}}$ and small $x_{\\mathrm{sd}}$ favours grain refinement. The rate of development of a constitutional supercooling zone is controlled by the growth restriction factor $Q$ . Larger values of $Q$ promote more nucleation. However, in additively manufactured metals, the dimensions of the laser-melted region, coupled with a high thermal gradient, considerably suppress the extent of the constitutional supercooling zone making it challenging to achieve a fine grain size in additively manufactured titanium alloys. Multiple research groups have explored the possibilities of adding solute elements such as beryllium, silicon or boron to stop epitaxial growth5. However, these solute elements only decrease the width of columnar grains of the additively manufactured titanium or only achieve a partial columnarto-equiaxed transition. It hence remains an open question whether fully equiaxed grain structures in additively manufactured titanium alloys are practically achievable through conventional grain-refining paradigms. \n\nIt should be noted that in previous grain-refining studies, the normalized $Q$ value— $\\cdot m(k-1)$ , where $m$ is the slope of the liquidus line and $k$ is the solute partition coefficient—has frequently been used \n\n# Article \n\n![](images/c5dac6d38ef269c370c37e54567afbdfc8c8e4cfd5448652bc4e52958aa97746.jpg) \nFig. 1 | Additive manufacturing of Ti–6Al–4V and Ti–8.5Cu alloys. a, Optical micrograph of an as-printed Ti–6Al–4V alloy showing coarse columnar grains. b, By contrast, optical microstructures of an as-printed Ti–8.5Cu alloy show fine, fully equiaxed grains along the building direction under the same manufacturing conditions. The yellow arrows in b indicate successive layer boundaries approximately every $200\\upmu\\mathrm{m}$ and the average prior- $\\cdot\\ B$ grain size is $9.6\\upmu\\mathrm{m}$ , measured by the linear intercept technique. Inset, an enlarged portion of a local region with ultrafine grains. c, Schematic diagram of the grain growth mechanism of Ti–8.5Cu and Ti–6Al–4V alloys. $T_{\\mathrm{A}}$ is the profile of the temperature of the melt and $T_{\\mathrm{{E}}}$ is the profile of the equilibrium liquidus temperature. The values of $\\Delta T_{\\mathrm{CS}}(=T_{\\mathrm{E}}-T_{\\mathrm{A}})$ and $\\Delta T_{\\mathfrak{n}}$ are represented qualitatively \n\nby the length bars. The red dot is the centre of the previous grain, which has grown to the size of the circle. The grey shapes represent the grain morphology for the two alloys. d, Summary of the area percentage of equiaxed grains versus grain size for the as-printed titanium alloys5,8–15. Ti–Si alloys (blue triangles) are, from top to bottom, Ti–0.04Si, Ti–0.19Si and Ti–0.75Si. The other titanium alloys (dark red diamonds) are, from left to right, Ti–6Al–2Zr–2Sn–3Mo–1Cr– 2Nb, Ti–6.5Al–3.5Mo–1.5Zr–0.3Si and Ti–3Al–10V–2Fe. Most as-printed titanium alloys have either fully columnar or mixed columnar and equiaxed prior- $\\cdot\\ B$ grains and the grain sizes are in the range of $100\\upmu\\mathrm{m}$ to 1 mm. This work shows that fully equiaxed prior- $\\cdot\\ B$ grains can be achieved throughout the asprinted samples. Error bars represent one standard deviation. \n\nto guide the choice of solute elements. However, the solubility of a given solute element in the $\\upbeta$ -phase titanium, which defines the practical maximum solute concentration, $c_{0-\\mathrm{{max}}},$ , has been neglected. By simply exploring binary titanium alloy phase diagrams, we note copper to be a promising solute, with a $c_{0-\\operatorname*{max}}$ as high as $17\\mathrm{wt\\%}$ and a reasonably high $m(k-1)$ value of $6.5{\\sf K}$ . This leads to an overall very high maximum $Q$ value, $Q_{\\mathrm{max}}=c_{\\mathrm{0-max}}m(k-1)=110.5\\mathsf{K}$ , which far surpasses that of silicon or boron6. \n\nIn addition to its potential for refining $\\upbeta$ -phase titanium grains, copper is also a typical eutectoid-forming element in titanium binary alloy systems where $\\beta\\to\\upalpha+\\sf T i_{2}C u$ at $792^{\\circ}\\mathrm{C}$ . Because copper diffuses rapidly in titanium, this eutectoid reaction cannot easily be prevented from occurring even after water quenching7. Such characteristics are beneficial to the high cooling rates during additive manufacturing and are likely to produce a very fine eutectoid microstructure, improving both the strength and ductility of as-printed specimens. Therefore, in the present study, we aim to develop additively manufactured titanium–copper alloys (Extended Data Fig. 1) to form fully equiaxed $\\upbeta$ -phase titanium grains and an ultrafine eutectoid microstructure in a one-step process. \n\n![](images/a41124570ca7d508da935d112149af33dff01a155facad83c51d19a27802d742.jpg) \nFig. 2 | Scanning electron microscopy (SEM) characterization of Ti–8.5Cu alloy. a, b, Backscattered electron (BSE) images of the as-printed Ti–8.5Cu alloy from Fig. 1b showing the microstructure evolution at the first layer (indicated by the red spots) during the additive manufacturing process, with constant processing parameters. The martensite phase forms when only a single layer was deposited (a); fine eutectoid lamellae surrounded by hyper-eutectoid \n${\\sf T i}_{2}{\\sf C u}$ particles form when multiple layers were deposited (b). c, A schematic continuous cooling transformation diagram illustrates different solid–solid phase transformation pathways for laser deposition of the first layer and the successive layers. Heat accumulates during the deposition of successive layers, thus the cooling rate is reduced and the $\\beta\\to\\upalpha+\\uptau i_{2}\\mathbf{C}\\mathbf{u}$ reaction is complete before the martensite transformation temperature $(M_{s})$ is reached. \n\n![](images/98efecad35a304f390a02cd8d21b0eec6e61c9114f45d752fa674b3c916a1501.jpg) \nFig. 3 | Transmission electron microscopy characterization of as-printed Ti–8.5Cu alloy. a, Bright-field image showing the ultrafine eutectoid lamellar structure and a small portion of hyper-eutectoid ${\\sf T i}_{2}{\\sf C u}$ particles close to the prior- $\\cdot\\ B$ grain boundaries. b–d, X-ray energy dispersive spectroscopy (XEDS) mapping on a section of the eutectoid lamellar structure: high-angle annular dark-field scanning transmission electron microscopy image (b), titanium elemental map (c) and copper elemental map (d). XEDS point analyses show that the copper contents in the lamellar structure are $2.8\\mathrm{wt\\%}$ in $\\upalpha$ -phase titanium and 39.1 wt% in ${\\sf T i}_{2}{\\sf C u}$ . Under equilibrium conditions, the maximum solubility of copper in α-phase titanium is $2.0\\mathrm{wt\\%}$ and in ${\\sf T i}_{2}{\\sf C u}$ it is $39.9\\mathrm{wt\\%^{21}}$ . \n\nThe optical micrographs of the as-printed (see Methods) Ti–8.5Cu specimen (herein, we use weight per cent unless otherwise specified) show fully equiaxed prior- $\\mathbf{\\beta}\\mathbf{\\cdot}\\mathbf{\\{\\vec{\\mathbf{\\tau}}\\beta\\mathbf{\\cdot}\\mathbf{\\vec{\\mathbf{\\tau}}\\beta\\mathbf{\\cdot}\\mathbf{\\vec{\\mathbf{\\tau}}\\beta\\mathbf{\\cdot}\\mathbf{\\vec{\\mathbf\\$ grains ( primary Ti grains that form during solidification, as shown in Fig. 1b) without any noticeable cracks and with a small volume fraction of enclosed porosity (see Extended Data Fig. 2). The as-printed specimen also has excellent chemical homogeneity along the building direction (see Extended Data Fig. 3). The prior- $\\mathbf{\\beta}$ grains have a bimodal distribution with an average grain size of $9.6\\upmu\\mathrm{m}$ . In comparison, the microstructure of as-printed Ti–6Al–4V alloy is dominated by coarse columnar grains (Fig. 1a) under the same laser processing conditions. It can be seen that the addition of copper has not only fully converted the columnar grains to equiaxed grains but also refined the prior- $\\cdot\\boldsymbol{\\mathsf{\\{\\{\\beta\\$ grains by two orders of magnitude. The commonly observed epitaxial growth is also completely eliminated, indicated by the size of the equiaxed grains, which is much smaller than the layer thickness of about $200\\upmu\\mathrm{m}$ (yellow arrows in Fig. 1b). It is also worth noting that compared with other additively manufactured titanium alloys reported thus far5,8–15, our current work has produced the smallest equiaxed prior- $\\mathbf{\\beta}$ titanium alloy grains made by additive manufacturing, as shown in Fig. 1d. The grain-refining efficiency of the as-printed titanium–copper alloys stems from the high capacity of the copper solute to establish a sufficiently large constitutional supercooling zone in front of the solid–liquid interface, which is formed when the solute copper segregates around the first $\\upbeta$ -phase titanium dendritic grain (Fig. 1c); the $Q$ value of the Ti–8.5Cu alloy is $62\\mathsf{K}.$ . By contrast, in Ti–6Al–4V, the Al and V solutes provide negligible constitutional supercooling (that is, $Q=8\\mathsf{K}$ ), which is far less than the nucleation undercooling $\\Delta T_{\\mathfrak{n}}$ during solidification. As a result, wide columnar grains with an average width of $120{\\upmu\\mathrm{m}}$ grow in the Ti–6Al–4V alloy, but fine equiaxed grains of average dimension $9.6\\upmu\\mathrm{m}$ grow in the Ti–8.5Cu alloy. The constitutional supercooling, $\\Delta T_{\\mathrm{cs}}$ is proportional to the $Q$ value16 through the dimensionless supersaturation parameter, $\\varOmega$ : \n\n$$\n\\varDelta T_{\\mathrm{CS}}=Q\\varOmega\n$$ \n\nThis means that the constitutional supercooling zone is eight times greater in magnitude during additive manufacturing of Ti–8.5Cu compared to Ti–6Al–4V, subjected to the same laser processing conditions. Sufficient constitutional supercooling can efficiently offset the negative impact of a high thermal gradient and ensures that waves of heterogenous nucleation events can be triggered in the constitutional supercooling zone and a complete columnar-toequiaxed transition can be achieved. By Interdependence Theory, the grain size is also dependent on $Q$ . More copper solute delivers higher constitutional supercooling faster, and therefore the size of the equiaxed prior- $\\mathbf{\\beta}$ grain is reduced with increasing copper content (see Extended Data Fig. 4). \n\nIt is worth mentioning that the Scheil–Gulliver solidification path and freezing range are often used to predict the likelihood of cracking during solidification17. A large freezing range usually leads to less liquid being available for interdendritic feeding during the last stage of solidification. In this study, Scheil curves show a large freezing range of more than $500\\mathsf{K}$ (Extended Data Fig. 5, dashed line) based on the titanium–copper equilibrium phase diagram. However, no cracks in the as-printed titanium–copper specimens were observed. This can be at least partially explained by equation (1). As the required constitutional supercooling critical temperature for the columnarto-equiaxed transition is usually between $10^{-1}\\mathsf{K}$ to 10 K, the resultant supersaturation $\\varOmega$ is much less than 1. This means that heterogeneous nucleation events occur very early during solidification. The formation of fine equiaxed dendrites can effectively decrease the hot-tearing susceptibility, as validated in previous studies of cast alloys18. \n\nUpon completion of liquid-to- $\\cdot\\boldsymbol{\\mathsf{\\{\\{\\xi\\cdot\\beta}}}}$ -phase solidification, the $\\upbeta$ -phase of titanium (a body-centred cubic structure) can decompose into different product phases in the subsequent solid–solid phase transformations subject to the cooling rate19. A high cooling rate can restrict the diffusion of atoms, which suppresses eutectoid coupled growth, resulting in martensite ( $\\mathbf{\\dot{\\mathbf{\\upalpha}}}\\mathbf{\\Psi}^{\\prime}$ -phase titanium, hexagonal close-packed structure) formation20. Martensite in titanium alloys can lead to higher strength but lower ductility8. As expected, acicular plates of martensite (Fig. 2a) were observed as a result of the high cooling rate in the single track of the additively manufactured Ti–8.5Cu alloy; however, successive layer-by-layer fabrication leads to multiple thermal cycles above and below the eutectoid reaction temperature $(792^{\\circ}\\mathsf{C})$ in the previously deposited layer and thus the cooling rate of the $\\upbeta$ -phase decomposition decreases as the number of layers increases, owing to insufficient heat dissipation (see Fig. 2c). This characteristic thermal history can efficiently reverse the martensitic transformation and results in ultrafine eutectoid lamellae (Fig. 2b and Extended Data Fig. 6). Similar phenomena have been observed in other compositions as well (see Extended Data Fig. 7). Moreover, the average interlamellar spacing in the as-printed Ti–8.5Cu alloy is $46\\mathsf{n m}\\pm7\\mathsf{n m}$ (Fig. 2b), which is much finer than conventionally manufactured water-quenched (about $150\\mathsf{n m}\\cdot$ ) and furnace-cooled (about $1\\upmu\\mathrm{m}\\dot{}$ ) samples7. This is because the interlamellar spacing is controlled by the diffusion length of the copper atoms; the diffusion length is considerably restricted by fast cooling. \n\nTitanium alloys, in general, have a very low thermal conductivity21, $\\leq16\\mathsf{W}\\mathsf{m}^{-1}\\mathsf{K}^{-1}.$ , which may lead to interlamellar spacing coarsening from the surface to the core, owing to the variation in cooling rate during a conventional normalizing heat treatment for large, bulky \n\n# Article \n\n![](images/3cec8e9aa5f8aabec5c1066c3e2681e6161c0df75001adddd84436636c684e65.jpg) \nFig. 4 | Mechanical properties of as-printed Ti–Cu alloys. a, Representative engineering stress–strain curves of the as-printed materials in this study; error bars represent one standard deviation. b, Yield strength $0.2\\%$ offset) versus tensile elongation to failure for Ti–Cu alloys manufactured by different methods24–26; the properties of these alloys are comparable with those of the \nASTM standard1 for a Ti–6Al–4V alloy. c, Ductile fracture surface of Ti–3.5Cu showing small dimples. d, Fracture surface of Ti–6.5Cu showing a mixture of regions of small dimples with regions of cleavage facets. e, Brittle fracture surface of Ti–8.5Cu showing only cleavage facets. \n\ntitanium–copper components. By contrast, the laser metal deposition process enables relatively constant cooling rates across the alloy, leading to a more uniform microstructure regardless of the size of the specimen. Only a slight increase in interlamellar spacing from the bottom $(41\\mathsf{n m}\\pm5\\mathsf{n m})$ to the top $(54\\mathrm{nm}\\pm9\\mathrm{nm})$ of the specimen was observed (errors represent one standard deviation). This is a result of the probably decreased cooling rate along the building direction. It is also worth mentioning that the copper concentration in the eutectoid lamellae (Fig. 3b–d) deviates from the equilibrium composition. The $\\upalpha$ -phase titanium contains $2.8\\mathrm{wt\\%}$ copper and it is supersaturated, because the maximum solid solubility of copper in $\\upalpha$ -phase titanium is $2.0\\mathrm{wt\\%}$ at equilibrium. This indicates that a more substantial precipitation hardening effect could be achieved to further increase the tensile strength through optimized post heat treatment. \n\nTensile tests with subsized ASTM standard specimens were performed on the as-printed alloys and the associated $0.2\\%$ offset yield strength $(\\sigma_{\\mathrm{y}})$ , ultimate tensile strength, and uniform elongation (ε) are summarized in Table 1. Comparing the Ti–6.5Cu and Ti–3.5Cu alloys, the eutectoid lamellae in Ti–6.5Cu increases the strength substantially but decreases the ductility (see Fig. 4a). Comparing the Ti–8.5Cu and Ti–6.5Cu alloys, Ti–8.5Cu has higher strength because of the higher volume fraction of eutectoid lamellae, but lower ductility owing to the hyper-eutectoid ${\\sf T i}_{2}{\\sf C}{\\sf u}$ particles22 (see Extended Data Table 1). The size of equiaxed prior- $\\upbeta$ grains (Fig. 1b and Extended Data Fig. 4) and microstructural lengthscales (Fig. 2b and Extended Data Fig. 7a, b) will probably also have an impact on the mechanical properties23. The fracture surfaces (Fig. 4c–e) show changes from dimples to a typical intragranular fracture morphology, which is consistent with the change in the ductility of the alloys. Compared with conventional casting and postheat-treatment methods (Fig. 4b), the mechanical properties of the as-printed titanium–copper alloys with ultrafine equiaxed prior- $\\cdot\\boldsymbol{\\upbeta}$ grains and eutectoid lamellar structure display a superior combination of offset yield strength and ductility. The properties are also comparable to that of cast and wrought Ti–6Al–4V alloy1, as well as laser-metal-deposited Ti–6Al–4V alloy24. Furthermore, copper is a relatively low-cost alloying element and titanium–copper alloys can be additively manufactured with mixed elementary powders instead of with pre-alloyed powders. Titanium–copper alloys also have excellent antibacterial properties, good biocompatibility and corrosion resistance22,25–27. It is also anticipated that further improvements in a range of properties can be achieved through process manipulation using additive manufacturing. \n\nTable 1 | Mechanical properties of as-printed Ti–Cu alloys \n\n\n
Samplesg(MPa)UTS (MPa)ε(%)
Ti-3.5Cu747±7867±814.9 ± 1.9
Ti-6.5Cu964± 311073 ± 275.5± 0.4
Ti-8.5Cu1023±291180 ±212.1±0.6
\n\nWe have demonstrated a pathway to additively manufacturing titanium–copper alloys with both fine equiaxed prior- $\\upbeta$ grains and an ultrafine eutectoid lamellar structure. Our experimental results show that the solidification and subsequent eutectoid decomposition can be synergistically engineered to tailor mechanical properties to suit specific applications. This approach to grain refinement, using alloys with high $Q$ values, has been demonstrated across many alloying systems28 and solidification processes and has been demonstrated here as a design methodology for additively manufactured titanium alloys. The methodology is also likely to be applicable to other eutectoid systems such as for pearlitic steels, in which the mechanical properties of these conventional alloys could be enhanced by additive manufacturing for high-performance engineering applications. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-019-1783-1. \n\n1. Zhang, D. et al. Metal alloys for fusion-based additive manufacturing. Adv. Eng. Mater. 20, 1700952 (2018). \n2. Carroll, B. E., Palmer, T. A. & Beese, A. M. Anisotropic tensile behavior of Ti–6Al–4V components fabricated with directed energy deposition additive manufacturing. Acta Mater. 87, 309–320 (2015). \n3. Herzog, D., Seyda, V., Wycisk, E. & Emmelmann, C. Additive manufacturing of metals. Acta Mater. 117, 371–392 (2016). \n4. StJohn, D. H., Qian, M., Easton, M. A. & Cao, P. The Interdependence Theory: the relationship between grain formation and nucleant selection. Acta Mater. 59, 4907–4921 (2011). \n5. StJohn, D. H. et al. The challenges associated with the formation of equiaxed grains during additive manufacturing of titanium alloys. Key Eng. Mater. 770, 155–164 (2018). \n6. Bermingham, M. J., McDonald, S. D., StJohn, D. H. & Dargusch, M. S. Beryllium as a grain refiner in titanium alloys. J. Alloys Compd. 481, L20–L23 (2009). \n7. Cardoso, F. F. et al. Hexagonal martensite decomposition and phase precipitation in Ti–Cu alloys. Mater. Des. 32, 4608–4613 (2011). \n8. Xu, W., Lui, E. W., Pateras, A., Qian, M. & Brandt, M. In situ tailoring microstructure in additively manufactured Ti–6Al–4V for superior mechanical performance. Acta Mater. 125, 390–400 (2017). \n9. Mitzner, S., Liu, S., Domack, M. S. & Hafley, R. A. Grain refinement of freeform fabricated Ti6Al4V alloy using beam/arc modulation. In 23rd Solid Freeform Fabrication Symp. 536–555 (2012); https://sffsymposium.engr.utexas.edu/Manuscripts/2012/2012-42- Mitzner.pdf. \n10.\t Wang, F., Williams, S. & Rush, M. Morphology investigation on direct current pulsed gas tungsten arc welded additive layer manufactured Ti6Al4V alloy. Int. J. Adv. Manuf. Technol. 57, 597–603 (2011). \n11.\t Mereddy, S. et al. Trace carbon addition to refine microstructure and enhance properties of additive-manufactured Ti–6Al–4V. JOM 70, 1670–1676 (2018). \n12.\t Wang, J. et al. Grain morphology evolution and texture characterization of wire and arc additive manufactured Ti–6Al–4V. J. Alloys Compd. 768, 97–113 (2018). \n13.\t Li, Z., Li, J., Zhu, Y., Tian, X. & Wang, H. Variant selection in laser melting deposited α + β titanium alloy. J. Alloys Compd. 661, 126–135 (2016). \n14.\t Zhu, Y.-Y., Tang, H.-B., Li, Z., Xu, C. & He, B. Solidification behavior and grain morphology of laser additive manufacturing titanium alloys. J. Alloys Compd. 777, 712–716 (2019). \n15.\t Zhu, Y., Liu, D., Tian, X., Tang, H. & Wang, H. Characterization of microstructure and mechanical properties of laser melting deposited Ti–6.5Al–3.5Mo–1.5Zr–0.3Si titanium alloy. Mater. Des. 56, 445–453 (2014). \n16.\t Kurz, W. & Fisher, D. J. Fundamentals of Solidification 3rd edn (Trans Tech Publications, \n1989). \n17. Fulcher, B. A., Leigh, D. K. & Watt, T. J. Comparison of AlSi10Mg and Al 6061 processed through DMLS. In Proc. Solid Freeform Fabrication (SFF) Symp. 46, 404–419 (2014). \n18. Easton, M., Wang, H., Grandfield, J., StJohn, D. & Sweet, E. An analysis of the effect of grain refinement on the hot tearing of aluminium alloys. Mater. Forum 28, 224–229 (2004). \n19. Souza, S. A., Afonso, C. R. M., Ferrandini, P. L., Coelho, A. A. & Caram, R. Effect of cooling rate on Ti–Cu eutectoid alloy microstructure. Mater. Sci. Eng. C 29, 1023–1028 (2009). \n20.\t Williams, J. C., Taggart, R. & Polonis, D. H. The morphology and substructure of Ti–Cu martensite. Metall. Trans. 1, 2265–2270 (1970). \n21. Brandes, E. A. & Brook, G. B. Smithells Metals Reference Book 7th edn (ButterworthHeinemann, 1992). \n22. Zhang, E., Wang, X., Chen, M. & Hou, B. Effect of the existing form of Cu element on the mechanical properties, bio-corrosion and antibacterial properties of Ti–Cu alloys for biomedical application. Mater. Sci. Eng. C 69, 1210–1221 (2016). \n23.\t Ren, Y. M. et al. Microstructure and deformation behavior of Ti–6Al–4V alloy by highpower laser solid forming. Acta Mater. 132, 82–95 (2017). \n24.\t Kok, Y. et al. Anisotropy and heterogeneity of microstructure and mechanical properties in metal additive manufacturing: a critical review. Mater. Des. 139, 565–586 (2018). \n25.\t Hayama, A. O. F. et al. Effects of composition and heat treatment on the mechanical behavior of Ti–Cu alloys. Mater. Des. 55, 1006–1013 (2014). \n26.\t Kikuchi, M. et al. Mechanical properties and microstructures of cast Ti–Cu alloys. Dent. Mater. 19, 174–181 (2003). \n27.\t Liu, R. et al. Antibacterial effect of copper-bearing titanium alloy (Ti–Cu) against Streptococcus mutans and Porphyromonas gingivalis. Sci. Rep. 6, 29985 (2016). \n28.\t Easton, M. A., Qian, M., Prasad, A. & StJohn, D. H. Recent advances in grain refinement of light metals and alloys. Curr. Opin. Solid State Mater. Sci. 20, 13–24 (2016). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Article Methods \n\n# Laser metal deposition \n\nPure $(99.9\\%)$ ) titanium and $(99.5\\%)$ copper spherical powders (TLS Technik and Thermo Fisher, respectively) with diameters between ${50\\upmu\\mathrm{m}}$ and $100\\upmu\\mathrm{m}$ (see Extended Data Fig. 8) were blended in a Turbula shaker mixer for an hour to achieve the designed compositions. Laser metal deposition was performed on a Trumpf TruLaser cell 7020. Before manufacturing bulk samples, we used single-layer deposition to optimize the processing parameters on the basis of visual observations of the weld bead. The optimized laser metal deposition parameters for the studied alloys are: laser power, $800\\mathsf{w}$ ; scanning speed, $800\\mathsf{m m m i n^{-1}}$ ; laser spot size, $1.5\\mathsf{m m}$ ; powder flow rate, 2.0 rpm $(1.7\\mathrm{g}\\mathsf{m i n}^{-1})$ ; hatch distance, $1.05\\mathsf{m m}$ ; shielding gas (argon) flow, $161\\mathrm{{min}^{-1}}$ . The processing parameters were kept the same for all Ti–xCu alloys. Three cubes of $10\\times10\\times10\\mathrm{mm}^{3}$ were built on a commercially pure titanium plate with different compositions $(3.5\\mathrm{wt\\%}$ , 6.5 wt% and $8.5\\mathrm{wt\\%}$ copper). The laser scanning route for laser metal deposition was a raster pattern with an increment of $90^{\\circ}$ between each layer and the delay time between two subsequent layers was $20{\\mathsf{s}}.$ For comparison, a Ti–6Al–4V specimen was additively manufactured using the same parameters. \n\nFor the tensile samples, three cuboids $(120\\times25\\times25\\mathrm{{mm}^{3}}.$ ) were horizontally built and then machined into five tensile samples. The loading direction of tensile samples is perpendicular to the laser metal deposition building direction. \n\n# Chemical compositions \n\nThe chemical composition of the as-printed samples was determined by inductively coupled plasma-atomic emission spectroscopy, as summarized in Extended Data Table 1. A small amount of copper evaporation is expected, as its boiling point is $2{,}560^{\\circ}\\mathrm{C}$ , much lower than that of titanium $(3,285^{\\circ}\\mathsf{C})^{21}$ . \n\n# $\\mathbf{x}$ -ray micro computed tomography \n\nThe as-printed samples were scanned using X-ray micro computed tomography (GE Phoenix V tome) with a nominal resolution of ${5\\upmu\\mathrm{m}}$ . Defect analysis including 3D image reconstruction, relative density, dimension and percentage of the defects was performed with Volume Graphics software. The as-printed specimens are all fully dense $(>99.4\\%)$ without any lack of fusion defects. The porosity found in the as-printed specimens may come from the existing porosity in the powders (see Extended Data Fig. 8) as well as the manufacturing process. \n\n# X-ray diffraction \n\nPhase identification was determined by X-ray diffraction (XRD) using a Bruker AXS D4 Endeavour diffractometer over a $2\\theta$ range between $15^{\\circ}$ and $90^{\\circ}$ at a scanning rate of $0.06^{\\circ}\\mathsf{s}^{-1}$ . \n\n# Microscopy \n\nAs-printed cube samples were cut along the central section parallel to the build direction. All the samples as well as raw powders were prepared by mounting, grinding and polishing. The samples for optical microscopy were etched by Kroll’s reagent to reveal the grain boundaries. Light optical microscopy with a polarized lens was used for examination of the microstructure. SEM in BSE mode was carried out using a FEI Verios 460L. Fracture tomography was analysed using SEM in secondary electron mode. \n\nThe average grain size was measured from five optical micrographs of each alloy using the linear intercept technique. Volume fraction of lamellae phase was calculated from three BSE microstructure images $(5,000\\times$ magnification) by using the colour threshold. \n\nFor transmission electron microscopy (TEM) sample preparation, SEM with a focused ion beam (FEI Scios) was used to prepare sitespecific TEM foils. Then, scanning transmission electron microscopy and XEDS mapping was performed in an image-corrected Titan3 G2 60-300 (S)TEM equipped with FEI’s ChemiSTEM technology. \n\n# Solidification simulation \n\nEquilibrium and Scheil–Gulliver solidification models were simulated using Pandat software with PanTitanium database (version 2018). The $Q$ values for Ti–6Al–4V and Ti–8.5Cu were determined from Scheil cooling curves29. \n\n# Tensile testing \n\nAs-printed samples were machined into rectangular tension test specimens with gauge length of $25\\mathsf{m m}$ and thickness of $4\\mathsf{m m}$ (subsize specimen of ASTM standard E8/E8 M-08). The tensile test loading direction is perpendicular to the laser metal deposition building direction. Quasi-static uniaxial testing was carried out at room temperature with an initial strain rate of $1.0\\times10^{-3}{\\mathsf{s}}^{-1}$ on a universal testing facility (MTS810, $100\\mathsf{k N})$ ) equipped with a non-contact laser extensometer. Five tensile specimens were tested for each composition (see Extended Data Fig. 9). The results were then compared with ASTM standards for standard-size specimens. \n\n# Data availability \n\nThe datasets generated or analysed during the current study are available from the corresponding author on reasonable request. \n\n29.\t Schmid-Fetzer, R. & Kozlov, A. Thermodynamic aspects of grain growth restriction in multicomponent alloy solidification. Acta Mater. 59, 6133–6144 (2011). 30.\t Okamoto, H. Phase Diagrams For Binary Alloys 2nd edn (ASM International, 2010). \n\nAcknowledgements We acknowledge the Australian Research Council (ARC) for financial support (grant number DP160100560). D.Q. would like to thank the RMIT Vice-Chancellor’s Senior Research Fellowship Fund for support. We thank M. Brandt and A. Jones for their support during laser metal deposition manufacturing, K. Yang for her support in etching additively manufactured titanium samples and E. Lui for his support in tensile testing. We acknowledge the facilities, and the scientific and technical assistance, of the RMIT Microscopy and Microanalysis Facility (RMMF). We also acknowledge the Center for Electron Microscopy and Analysis (CEMAS) at the Ohio State University for providing access to research facilities. \n\nAuthor contributions M.A.E., M.A.G., D.H.StJ. and H.L.F. conceived the idea. D.Q. and D.Z. designed the experiments. D.Z. and D.Q. helped with processing parameter development and sample manufacturing, and performed the microstructure characterization. Y.Z. and D.Z. conducted the transmission electron microscopy and analysed the results. D.Z. performed mechanical testing, simulations and X-ray computed tomography. M.A.E. supervised the project. D.Z. and D.Q. drafted the manuscript. All authors discussed the results and edited the manuscript at all stages. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nCorrespondence and requests for materials should be addressed to H.L.F. or M.A.E. Peer review information Nature thanks Amy Clarke, David Dye and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/813c2e507e4b444aeb8e60d3733b9db1df5546f436628ce1000ebbd0fd5ecacc.jpg) \n\nExtended Data Fig. 1 | Ti–Cu phase diagram. Portion of the Ti–Cu phase diagram indicating the compositions selected for laser metal deposition. We selected 3.5, 6.5 and $8.5\\mathrm{wt\\%}$ copper to explore the behaviour of hypoeutectoid, eutectoid and hyper-eutectoid compositions under additive manufacturing. This figure is adapted from ref. 30, with the permission of ASM International. \n\n# Article \n\n![](images/ad9322e6293eeb49068f580e3269837d8a732a8686b8a1932125b68bcef68e88.jpg) \nExtended Data Fig. 2 | 3D visualization of the porosity of the manufactured specimens in the xyz coordinate system. a, Ti–3.5Cu. b, Ti–6.5Cu. c, Ti–8.5Cu. d, Calculated relative density of the as-printed specimens. Error bars represent one standard deviation. \n\n![](images/85393d1077f234a7b8ffc540c9db64a64a03dc0d81d51a479e58faebff36e039.jpg) \nExtended Data Fig. 3 | XEDS results of the copper content along the building direction for Ti–8.5Cu alloy. The base point is $0\\mathrm{mm}$ and the chemical composition is homogeneous. Error bars represent one standard deviation. \n\n# Article \n\n![](images/842c7d0f4cb5ce28e7185b25f14b7660bbf1a30ffe6711c70e63c216f9e30675.jpg) \n\nExtended Data Fig. 4 | Polarized optical microstructures. a, b, The equiaxed grains of as-printed Ti–3.5Cu (a) and Ti–6.5Cu (b). The average grain size is $69.8\\upmu\\mathrm{m}$ for Ti–3.5Cu and $16.3\\upmu\\mathrm{m}$ for Ti–6.5Cu. \n\n![](images/83aa5ef6b7145dc9b255f5de422c555779d8ec0b2f8a0ade82d701d2e0c5b24f.jpg) \nExtended Data Fig. 5 | Solidification curves. The data are shown for different copper compositions under equilibrium and Scheil conditions. The Scheil curve show a substantially enlarged temperature interval between liquidus and solidus temperatures compared with the equilibrium condition. \n\n# Article \n\n![](images/a25b5af042b67921badc1b80663c8300fdfd4a1b7e610c13e14e64fde1103c6b.jpg) \n\nExtended Data Fig. 6 | XRD spectra. Experimental XRD spectra collected from the as-printed Ti–8.5Cu alloy indicates that only two phases are present in the specimen: $\\mathfrak{a}$ -phase titanium and ${\\sf T i}_{2}{\\sf C u}$ \n\n![](images/0f882202f3a27ae39b8aecdca88f5c5595302876241f3b3adb7b74c49ad55ceb.jpg) \n\nExtended Data Fig. 7 | BSE images. a–d, BSE images of as-printed specimens showing the fine α phases when multiple layers were deposited, for Ti–3.5Cu (a) and Ti–6.5Cu (b); and the martensite phase when only a single layer was \n\ndeposited for Ti–3.5Cu (c) and Ti– $.6.5\\mathsf{C u}$ (d). Images were taken at the first layer of build specimens, indicated by the red spots. \n\n# Article \n\n![](images/3095f6d4b81eb89af3ea370beb557a7e0644e6d82e5647fdca9a4e28fd711f68.jpg) \n250μm \n\n250μm \n\nExtended Data Fig. 8 | SEM images of the cross-section of raw powders. a, b, SEM images of the titanium powder (a) and copper powder (b) crosssections. The powders are spherical in shape with a diameter between ${50\\upmu\\mathrm{m}}$ \n\nand $100\\upmu\\mathrm{m}$ , and porosity can be observed within some powder particles. The yellow arrows indicate examples where powder particles fell out of the resin during the polishing process. \n\n![](images/b395addcfeaf73f619c3f6e56cdc8e08c133a3d9731015aceb9cbf4be5661300.jpg) \nExtended Data Fig. 9 | Engineering stress–strain curves. The data for the additively manufactured materials tested in this study indicate good repeatability. \n\n# Article \n\nExtended Data Table 1 | Measured chemical compositions (wt%) and volume fraction of eutectoid lamellae in the as-printed alloys \n\n\n
Alloy (nominal composition)CuN0TiEutectoid lamellae (%)
Ti-3.5Cu3.200.010.22Bal.
Ti-6.5Cu6.330.020.23Bal.53±7
Ti-8.5Cu8.360.020.21Bal.92±4
\n\nErrors represent one standard deviation. " + }, + { + "id": "10.1039_c9ee02268f", + "DOI": "10.1039/c9ee02268f", + "DOI Link": "http://dx.doi.org/10.1039/c9ee02268f", + "Relative Dir Path": "mds/10.1039_c9ee02268f", + "Article Title": "Conformal monolayer contacts with lossless interfaces for perovskite single junction and monolithic tandem solar cells", + "Authors": "Al-Ashouri, A; Magomedov, A; Ross, M; Jost, M; Talaikis, M; Chistiakova, G; Bertram, T; Márquez, JA; Köhnen, E; Kasparavicius, E; Levcenco, S; Gil-Escrig, L; Hages, CJ; Schlatmann, R; Rech, B; Malinauskas, T; Unold, T; Kaufmann, CA; Korte, L; Niaura, G; Getautis, V; Albrecht, S", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "The rapid rise of perovskite solar cells (PSCs) is increasingly limited by the available charge-selective contacts. This work introduces two new hole-selective contacts for p-i-n PSCs that outperform all typical p-contacts in versatility, scalability and PSC power-conversion efficiency (PCE). The molecules are based on carbazole bodies with phosphonic acid anchoring groups and can form self-assembled monolayers (SAMs) on various oxides. Besides minimal material consumption and parasitic absorption, the self-assembly process enables conformal coverage of arbitrarily formed oxide surfaces with simple process control. The SAMs are designed to create an energetically aligned interface to the perovskite absorber without non-radiative losses. For three different perovskite compositions, one of which is prepared by co-evaporation, we show dopant-, additive- and interlayer-free PSCs with stabilized PCEs of up to 21.1%. Further, the conformal coverage allows to realize a monolithic CIGSe/perovskite tandem solar cell with as-deposited, rough CIGSe surface and certified efficiency of 23.26% on an active area of 1 cm(2). The simplicity and diverse substrate compatibility of the SAMs might help to further progress perovskite photovoltaics towards a low-cost, widely adopted solar technology.", + "Times Cited, WoS Core": 765, + "Times Cited, All Databases": 793, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000494816300007", + "Markdown": "# Conformal monolayer contacts with lossless interfaces for perovskite single junction and monolithic tandem solar cells† \n\nAmran Al-Ashouri, $\\textcircled{1}$ \\*a Artiom Magomedov, $\\textcircled{1}$ \\*b Marcel Roß,a Marko Josˇt, $\\textcircled{1}$ Martynas Talaikis, $\\textcircled{10}\\textcircled{<}$ Ganna Chistiakova,d Tobias Bertram, $\\textcircled{1}$ e Jose´ A. Ma´rquez, $\\textcircled{1}$ Eike Ko¨hnen, $\\textcircled{1}$ a Ernestas Kasparavicˇius,b Sergiu Levcenco, $\\mathbb{\\oplus^{f}}$ Lido´n Gil-Escrig,a Charles J. Hages,f Rutger Schlatmann, $\\oplus^{\\mathrm{e}}$ Bernd Rech,dg Tadas Malinauskas,b Thomas Unold, $\\textcircled{1}$ f Christian A. Kaufmann, $\\oplus^{\\mathrm{e}}$ Lars Korte, $\\textcircled{10}\\textcircled{<}$ Gediminas Niaura,c Vytautas Getautis $\\textcircled{1}$ b and Steve Albrecht\\*ag \n\nThe rapid rise of perovskite solar cells (PSCs) is increasingly limited by the available charge-selective contacts. This work introduces two new hole-selective contacts for $p{-}i{-}n$ PSCs that outperform all typical p-contacts in versatility, scalability and PSC power-conversion efficiency (PCE). The molecules are based on carbazole bodies with phosphonic acid anchoring groups and can form self-assembled monolayers (SAMs) on various oxides. Besides minimal material consumption and parasitic absorption, the self-assembly process enables conformal coverage of arbitrarily formed oxide surfaces with simple process control. The SAMs are designed to create an energetically aligned interface to the perovskite absorber without non-radiative losses. For three different perovskite compositions, one of which is prepared by co-evaporation, we show dopant-, additive- and interlayer-free PSCs with stabilized PCEs of up to $21.1\\%$ Further, the conformal coverage allows to realize a monolithic CIGSe/perovskite tandem solar cell with as-deposited, rough CIGSe surface and certified efficiency of $23.26\\%$ on an active area of $\\textstyle{1\\ \\cos^{2}}$ . The simplicity and diverse substrate compatibility of the SAMs might help to further progress perovskite photovoltaics towards a low-cost, widely adopted solar technology. \n\nrsc.li/ees \n\n# Broader context \n\nPerovskite-based photovoltaics promises three main benefits: low cost, high efficiency and large versatility. However, combining all three factors into one solar cell design is still a difficult endeavor. In particular, one of the main bottlenecks towards large-scale production is the available choice of hole-selective contacts. The best standards in both polarities, n–i–p (Spiro-OMeTAD) and p–i–n (PTAA), are highly unsuitable for commercial production due to their very high prices and limited processing versatility. Thus, with this work, we present a new generation of self-assembled monolayers (SAMs) as hole-selective contacts that are intrinsically scalable, simple to process, dopant-free and cheap. In addition, they enable highly efficient $\\operatorname{p-i-n}$ perovskite solar cells and a record-efficiency monolithic perovskite/CIGSe tandem device. While self-assembly offers the crucial advantage of conformally covering rough surfaces within a self-limiting process, one of the herein used SAMs creates an energetically well-aligned interface to the perovskite absorber with minimal non-radiative recombination. Our model system further provides insights into the influence of molecular design on surface passivation and open-circuit voltage, beneficially adding to future prospects of rationally engineering perfect charge-selective contacts. \n\n# Introduction \n\nMetal-halide perovskites triggered intensive research activities throughout the last 5 years with over 3000 published papers on perovskite solar cells (PSCs) only in 2018.1 Typical metal-halide perovskite absorbers are composed of a mixture of different cations (methylammonium MA, formamidinium FA, Cs, Rb etc.) and anions $(\\mathrm{I}^{-},~\\mathrm{Br}^{-},~\\mathrm{Cl}^{-})$ . These compositions have attracted attention due to their outstanding optoelectronic properties including a steep absorption onset together with strong solar absorption2 and high defect tolerance.3,4 Furthermore, the low non-radiative recombination rates enabled voltage deficits that are only $\\sim65~\\mathrm{mV}$ below the radiative limit,5 which is striking for a material processed at low temperatures of around $100~^{\\circ}\\mathrm{C}$ . The perovskite layers can be fabricated through a variety of techniques, including vacuum deposition by co-evaporation6 and versatile solution processing methods like spin coating or printing.7 The relatively high band gap of $1.6\\mathrm{-}1.7\\ \\mathrm{eV}$ , together with the ability of band gap tuning by compositional engineering,8 also renders these materials suitable for integration into tandem solar cell architectures to overcome the efficiency limit of single solar cells.9 In efficient tandem devices, the PSC is used as the top cell absorber with either crystalline silicon,10,11 $\\mathrm{Cu}(\\mathrm{In},\\mathrm{Ga})\\mathrm{Se}_{2}$ (CIGSe)12,13 or a Sn-based perovskite forming the lower band gap bottom cell.14 \n\nAlthough highest reported power conversion efficiencies (PCEs) of over $23\\%$ are demonstrated for PSCs with the ‘‘regular’’ n–i–p device architecture,15 the $\\mathsf{p}{\\mathsf{-i-n}}$ (so called ‘‘inverted’’) architecture is gaining increasing popularity due to its ease of processing and superior suitability for perovskitebased tandem solar cells.16–19 Moreover, p–i–n PSCs carry the promise of low-temperature fabrication, high stability20 without the use of dopants that cause degradation,21–23 low current– voltage hysteresis24 and compatibility to flexible substrates.25,26 However, compared to their n–i–p single junction counterparts, p–i–n PSCs still lack behind in maximum power-conversion efficiency. This is predominantly due to a higher loss in potential, i.e., energetic difference between open-circuit potential $(e V_{\\mathrm{OC}},$ with elementary charge e) and band gap. This loss was identified to be dominated by the interfaces to charge-selective contacts.27 Thus, recent efforts were dedicated to reduce these losses through surface passivation, mostly by processing nanometer-thick interfacial layers between absorber and charge-selective contacts.28–34 Recently, changes of the perovskite precursor (e.g., addition of $\\mathrm{Sr}^{35}$ or an organic molecule with passivating functional groups,36 or a substitution5 of $\\mathrm{PbI}_{2}^{\\cdot}$ ) led to open-circuit voltages of well over $1.20{\\mathrm{~V~}}$ with comparable loss-in-potential values as obtained in best n–i–p PSCs. However, the mentioned strategies often require finely tuned processing that might be complicated to implement on a large scale. Additionally, for most high- $\\cdot V_{\\mathrm{OC}}$ approaches, acceptable stability of the PSCs has yet to be shown. \n\nIn the scope of future high-throughput commercialization, it is crucial to keep the simplicity and robustness that $\\mathsf{p}{\\mathrm{-i}}{\\mathrm{-n}}$ PSCs exhibit even at high PCEs $>20\\%$ . Additionally, it is desirable to minimize parasitic absorption and to use low-cost materials that are suitable for a variety of substrates with arbitrary surfaces and large areas, in order to expand the fields of PSC applications. These ambitions could be realized by using selfassembled monolayers (SAMs) as charge-selective contacts: the required material quantities are minimal; the substrate compatibility is manifold and process control is simple, with the molecules autonomously forming a functional layer in a self-limiting process by design. Functionalization of surfaces with SAMs already has a rich history in surface chemistry.37–39 With the rise of miniaturized electronics, e.g., SAM-based fieldeffect transistors were built.40,41 After first occurrences in PSCs as electrode modifications,42,43 the first hole-selective SAMs were introduced in 2018.44,45 These molecules covalently bind to the transparent conductive oxide (TCO), e.g., indium tin oxide (ITO), on which the perovskite absorber crystallizes. Due to their hole-selectivity, the SAMs can replace the classical hole-transporting layer. To date, however, the SAMs in PSCs did not enable high PCEs of over $20\\%$ that would surpass those reached with the typically used polymeric hole contact material PTAA (poly[bis(4-phenyl)(2,4,6-trime-thylphenyl)amine]). Here, we reach this important objective by using a new generation of SAMs in which the molecules are based on carbazole bodies with phosphonic acid anchoring groups. \n\nWe show that the SAMs act as simple hole-selective contacts that can be prepared by classical dip-coating or spin-coating within wide processing windows. By replacing PTAA with a SAM, we demonstrate a maximum PCE of over $21\\%$ , which is comparable to current record-efficiencies in the $\\mathsf{p}{\\mathrm{-i}}{\\mathrm{-n}}$ architecture.27,34,36 Notably, this PCE is achieved without any perovskite post-treatments, additives, dopants or interlayers that are usually used for high PCEs after delicate fine-tuning. Ultraviolet photoelectron spectroscopy reveals that both new SAMs show a stronger hole-selectivity than PTAA, and photoluminescence (PL) studies show that the SAM/perovskite interface does not introduce non-radiative losses. This enables a $V_{\\mathrm{OC}}$ of up to $1.19{\\mathrm{~V~}}$ and a PL decay time of $\\sim2~{\\upmu\\mathrm{s}}$ . The investigated SAMs work efficiently for three different perovskite compositions, including a $19.6\\%$ -efficient PSC which is fabricated by co-evaporation, assuring that hole-extraction by SAMs is a universal approach. We further demonstrate that self-assembly leads to conformal coverage of rough surfaces like as-deposited CIGSe. By integrating a SAM into a tandem architecture, we realize a $23.26\\%$ -efficient monolithic CIGSe/perovskite tandem solar cell (certified) with an active area of $1.03~\\mathrm{cm}^{2}$ , embodying a low-cost, facile way of realizing all-thin-film tandem solar cells, which has proven to be a hard endeavor in the past.46,47 \n\n# Results \n\nA schematic representation of the used p–i–n device structure is displayed in Fig. 1a. The glass/ITO serves as a substrate for covalent bonding of the molecules to the ITO, forming a SAM. Afterwards, the perovskite is deposited on top of the SAM. As the electron-selective contact, $\\mathbf{C}_{60}$ is thermally evaporated on top of the perovskite absorber. The device is completed by thermal evaporation of a bathocuproine $\\mathbf{(BCP)/Cu}$ electrode. \n\n![](images/a3f0d459a6646b83c7d8a4128a25ae2b14611214e70fcbb0b3fd43bdb0f5c446.jpg) \nFig. 1 Solar cell device architecture and molecule structures investigated in this work. (a) Schematic of the investigated device structure. The zoom-in visualizes how the SAM molecules attach to the ITO surface and therefore enable the hole selective contact to the perovskite above. (b) Molar extinction coefficient of solutions in tetrahydrofuran containing the different hole-selective contact materials at a concentration of 0.1 mmol $\\lfloor^{-1}$ (c) Chemical structure of the SAM molecules V1036,44 MeO-2PACz (d) and 2PACz (e). (f) Chemical structure of the typically used polymer PTAA. \n\nMore details on sample fabrication and methods are provided in the supporting information. Fig. 1c–e displays the molecular structures of the molecules that form the SAMs. Fig. 1f shows the molecule structure of PTAA, which is currently used in the highest performing p–i–n PSCs in literature.27,34,36 PSCs with V1036 ((2-{3,6- bis[bis(4-methoxyphenyl)amino]-9H-carbazol-9-yl}ethyl)phosphonic acid) were already investigated in our previous work.44 MeO-2PACz ([2-(3,6-dimethoxy-9H-carbazol-9-yl)ethyl]phosphonic acid) and 2PACz ([2-(9H-carbazol-9-yl)ethyl]phosphonic acid) are new molecules based on a carbazole moiety. \n\nCarbazole derivatives have been studied, e.g., for their electron-localizing and thus hole-selective properties,48 starting from first applications in electro-photographic devices. Since then, a huge variety of carbazole-based conductive polymers and molecular glasses has been synthesized and characterized.49 Currently, the carbazole fragment is widely adapted in the synthesis of new materials used in organic light-emitting diodes,50 and, more recently, in PSCs.51 Organic phosphonic acids (PA) are known to form strong and stable bonds on, e.g., ITO surfaces,52–54 enable reliable work function modifications and can principally form bonds to any oxide surface.55–57 In particular, it was calculated for the case of $\\mathrm{TiO}_{2}$ that PA has the strongest binding energy among all studied anchoring groups.58 Strong bonds like these enable exceptional stability of the formed monolayers.59 In the frame of perovskite photovoltaics, it has been shown that organic PAs on ITO are stable under continuous solar cell operation for at least $1000\\mathrm{~h~}$ .60 Fig. 1b presents the absorption spectra of all used molecules in a tetrahydrofuran solution. The new SAMs 2PACz and \n\nMeO-2PACz show reduced absorption in the visible wavelength regime as compared to PTAA or V1036. The synthesis of these carbazole derivatives was conducted following a simplified version of the previously published synthesis procedure used for V1036 (see Fig. S1 in the $\\mathrm{ESI\\dag}$ ).44 In comparison to V1036, the reaction scheme is one step shorter, no metal-based catalysis was required, and inexpensive, commercially available starting materials were used. \n\nThe classic method to coat oxide surfaces with a SAM is to immerse the substrates for several hours into a solution containing the material, optionally under heating of the solution to accelerate binding to the surface. Some molecules, such as the ones used in this work, can also form a dense monolayer simply by spin-coating the solution with a suitable concentration, as was previously described by Nie et al.61 The process is intrinsically self-limiting, since the PA groups only attach to sites on the surface where there is still blank oxide. Following previous studies, we assume that the self-assembly is ordered and stabilized by $\\pi{-}\\pi$ interactions between adjacent carbazole fragments, in contrast to an ordering that is dominated by van der Waals forces in long-chain aliphatic monolayers.62–64 We investigated solar cells with SAMs formed both by classical dip-coating and spin-coating and did not observe significant differences in solar cell performance between both methods (Fig. S2 in the $\\mathrm{ESI\\dag}$ ). This indicates SAMs of similar surface coverage in both cases. Dip-coating is more suitable for largearea application and conformal coating of textured or rough substrates, while spin-coating is useful for high-throughput optimization in laboratory workflows. \n\nThe SAM films obtained from both methods show similar properties in reflection–absorption infrared spectra (RAIRS) measured on ITO substrates as presented in Fig. 2. RAIRS is a molecule-specific, surface-sensitive technique, which allows for probing the structure and bonding of adsorbed molecules on metallic substrates with sub-monolayer sensitivity.65 Here we use the reflection signal $(R)$ , normalized to the signal of a bare ITO substrate $\\left(R_{0}\\right)$ , to detect the absorption bands of the molecular vibrational modes of the SAM components. By comparing to density functional theory (DFT) calculations (see Fig. S4 and S5, $\\mathrm{ESI\\dag})$ and previous reports,66–70 we assign the individual absorption bands to the specific molecular bonds. In general, the observed bands fit to the ones expected from the molecular structure of the SAM molecules. For instance, in the V1036 spectrum in Fig. 2a, the strong band near $1511~\\mathrm{{cm}}^{-1}$ can be assigned to $\\scriptstyle\\mathbf{C}=\\mathbf{C}$ in-plane stretching vibrations of aromatic rings of the carbazole structure with some contribution from $\\scriptstyle\\mathbf{C}=\\mathbf{C}$ in-plane stretching vibrations of $p$ -methoxy-phenyl groups.66–68,70 The second strongest band of V1036 near $1246~\\mathrm{cm}^{-1}$ can be associated with $\\mathbf{C}{\\mathrm{-}}\\mathbf{N}$ stretching vibrations.67,68 Both MeO-2PACz and 2PACz exhibit two bands located near $1490{-}1494~\\mathrm{cm}^{-1}$ and $1466{-}1483\\mathrm{cm}^{-1}$ which are associated with carbazole ring stretching vibrations. Characteristically, 2PACz exhibits two carbazole ring stretching modes at 1242 and $1347~\\mathrm{cm}^{-1}$ and MeO-2PACz a frequency mode at $1582~\\mathrm{cm}^{-1}$ that is associated with the asymmetric stretching vibration of rings with adjacent methoxy groups.69 \n\n![](images/2237de29557263f0b598d1c250f26759ecdbc573273be5be5923e51f054ddffd.jpg) \nFig. 2 Infrared and X-ray spectroscopic characterizations of SAM-coated ITO substrates. (a–c) FTIR spectrum of the $\\mathsf{S A M}$ molecule bulk material and reflection–absorption infrared spectra (RAIRS) of monolayers on Si/ITO substrates. (a) Spectra of V1036, MeO-2PACz and 2PACz from spin-coating on Si/ITO substrates, after washing with ethanol and chlorobenzene. (b) Comparison between V1036 bulk material vs. SAM formation from spin-coating and dip-coating. Inset: Detail spectrum in which the monolayer fingerprint (P–O to metal bond) is visible as a broad peak at $1010~\\mathsf{c m}^{-1}$ . (c) Effect of the washing step on the RAIRS spectra on spin-coated $S A M s$ . MeO-2PACz and 2PACz already show the monolayer fingerprint without washing. (d) X-ray photoelectron spectroscopy (XPS) spectra of the C1s region, in which the solid line shows the fit to the data and the dotted lines show the components thereof. The additional methoxy group that defines MeO-2PACz in comparison to 2PACz is visible as an additional peak near 286 eV that is assigned to carbon species in $C{\\mathrm{-}}{\\mathsf{O}}{\\mathrm{-}}{\\mathsf{C}}$ bonds. \n\nImportantly, the RAIR spectra show a signature of monolayer formation by detection of the bound PA functional group, which is the covalent link between hole-transporting fragment and metal oxide. In our previous work, we concluded the absence of multilayers by comparing absorption measurements to optical simulations.44 This conclusion is further supported by the shown RAIRS analysis. Fig. 2b presents the RAIR spectra for molecules of V1036, comparing monolayers on ITO that are derived from spin- and dip-coating, versus the bulk Fouriertransform infrared (FTIR) spectrum obtained from the powder pressed into a KBr tablet. While the main spectral features are the same for all three materials, the monolayers, in contrast to the bulk material, exhibit a broad feature in the RAIR spectrum at $1010~\\mathrm{cm}^{-1}$ (see inset in Fig. 2b). Both monolayers formed from spin- and dip-coating of V1036 show this band, while the bulk material of V1036 only shows a small shoulder and a slightly shifted spectrum compared to the monolayer spectrum. In conjunction with previous reports,71–74 we can assign the peak at $1010~\\mathrm{{cm}^{-1}}$ to $\\scriptstyle\\mathbf{P-O}$ species bound to ITO. The appearance of this peak, together with the disappearance of the P–OH peak that is prominent in the bulk material at $\\sim950~\\mathrm{cm}^{-1}$ (see Fig. S4 and S5, ESI†), provides evidence for deprotonation of the phosphonic anchoring group and monolayer formation. \n\nAfter spin-coating the SAM solution and heating the substrates at $100^{\\circ}\\mathrm{C}$ for $10~\\mathrm{{min}}$ , the substrates are typically washed with the solvent that dissolves the molecules (here ethanol) to remove any molecules that did not bind to the oxide surface. The effect of this is visible in Fig. 2c. Here, the RAIR spectra are shown for ITO samples on which the different SAM solutions were spin-coated, with and without washing the substrates afterwards. For V1036 (upmost curve), the intensity drops by a factor of $\\mathord{\\sim}7$ after the washing procedure, and the characteristic $\\scriptstyle\\mathbf{P-O}$ absorption shoulder, i.e., the monolayer fingerprint, appears at $1010~\\mathrm{cm}^{-1}$ . However, with MeO-2PACz and 2PACz, we notice that the washing step only slightly decreases the intensity of the absorption bands and the monolayer fingerprint is already present without washing. Thus, we conclude that simply spin-coating MeO-2PACz and 2PACz solution with a concentration of roughly 0.5–1 mmol $1^{-1}$ and subsequent heating of the substrate is sufficient for obtaining a monolayer of the material. Indeed, a wide window of concentrations (at least between $0.5\\mathrm{\\mmol\\}1^{-1}$ and 3 mmol $1^{-1}$ , see Fig. S3, ESI†) of the solutions is found for which no extra rinsing step is required to obtain equivalently performing PSCs. This large processing window further adds to the simplicity of the here presented process strategy and highlights the robustness of monolayer formation with the new SAMs. \n\nAs another surface-sensitive technique, we utilized X-ray photoelectron spectroscopy (XPS) to detect the atomic species on the SAM-coated substrates. Fig. 2d shows the X-ray photoelectron spectra in the C1s binding energy region of the investigated SAMs on glass/ITO substrates. While the bare ITO substrate shows almost no signal in this region (see Fig. S14, $\\mathrm{ESI\\dag}$ ), the SAM-coated substrates show characteristic signals that can be fitted with 4–5 peaks with a mixed Lorentzian/ Gaussian lineshape and a linear background. The strongest peak can be assigned to aromatic carbon (C–C, C–H) with relative peak areas of 0.57, 0.38 and 0.42 compared to the area of the sum of all peaks for 2PACz, MeO-2PACz and V1036 respectively, each indicating the ratio of the atomic specie to the sum of atoms in the molecule structure. The second strongest peak arises from carbon atoms bonded to nitrogen (C–N), with relative peak areas of around 0.3, 0.27 and 0.28 for 2PACz, MeO-2PACz and V1036, respectively. For MeO-2PACz and V1036, an additional peak is present compared to 2PACz (0.21 relative peak area for MeO-2PACz and 0.16 for V1036), at an energy corresponding to ether functional groups.75 In this case, it can be assigned to C atoms in $\\scriptstyle\\mathbf{C-O-C}$ bonds, since methoxy groups are present only for MeO-2PACz and V1036. This is in conjunction with an additional analysis of the Oxygen specie in Fig. S12 of the ESI. $\\dagger$ Regarding the peak between the respective C–O–C and $\\mathbf{C}{\\mathrm{-}}\\mathbf{P}$ assignments, we hypothesize that it might stem from the C atoms bonded to three other C atoms in the carbazole fragment (4a and 4b positions). Overall, the trend of relative peak areas compared between the different SAMs is in line with the counts of atoms in the molecule structures depicted in Fig. 1c–e. \n\n# Perovskite solar cell performance \n\nFor comparing the performance and device-relevant characteristics of SAM-based solar cells, we chose to focus our analysis on the so called ‘‘triple cation’’ perovskite absorber76 $\\begin{array}{r}{\\mathbf{C}s_{5}(\\mathbf{M}\\mathbf{A}_{17}.}\\end{array}$ $\\mathbf{FA}_{83}\\big)_{95}\\mathbf{Pb}\\big(\\mathbf{I}_{83}\\mathbf{B}\\mathbf{r}_{17}\\big)_{3}$ (CsMAFA), which is widely used due to its high reproducibility. The various hole-selective contacts (HSCs) are compared using the device design as shown in Fig. 1a. Since the polymeric hole transport material PTAA is currently being used in the highest-performing p–i–n PSCs,27,34,36 we compare the SAM-based cells to PTAA-based PSCs and analyze the perovskite film and device properties. To keep the devices as simple as possible, the SAM and PTAA cells do not contain any interfacial compatibilizers, additives or doping. As such, our PTAA control cells are comparable to state-of-the art ones as found in literature.27,77 \n\nFig. 3a shows $J{-}V$ characteristics under simulated AM 1.5G illumination of best PSCs obtained on the respective HSCs in forward $\\scriptstyle\\mathbf{J}_{\\mathrm{SC}}$ to $V_{\\mathrm{OC}})$ and reverse scan $\\mathrm{~\\textit~{~V~}~o c~t o~}J_{\\mathrm{SC}})$ direction, with continuous maximum power point (MPP) tracks in the inset. Their photovoltaic parameters are summarized in Table 1. A statistical comparison of the PCEs is plotted in Fig. 3c with 41–53 solar cells per HSC (other device metrics in Fig. S7 in the $\\mathrm{ESI\\dag}$ ). From the $J{-}V$ curves, we obtain that hysteresis is overall negligible with MPP-tracked efficiencies close to the respective $J{-}V$ scan values and the fill factor (FF) is overall comparable at around $80\\%$ between all PSCs. Fig. 3b displays the external quantum efficiencies (EQEs) of the best devices as well as the integrated product of EQE and AM 1.5G spectrum. The $J_{\\mathrm{SC}}$ values from EQE integration have a negligible difference to the $J_{\\mathrm{SC}}$ values obtained from the $J{-}V$ scans $(\\sim1\\%)$ . The most striking difference between the HSCs is visible in the opencircuit voltage $\\left(V_{\\mathrm{OC}}\\right)$ , with a difference of $63~\\mathrm{mV}$ between PTAA and 2PACz. For the most efficient 2PACz solar cell, a $V_{\\mathrm{OC}}$ of $\\sim1.19\\mathrm{~V~}$ is measured, which is among the highest for this perovskite composition and device architecture, and the highest for CsMAFA cells without interlayers, dopants or additives. Overall, the PCE trend resembles the increase in $V_{\\mathrm{OC}}$ and both MeO-2PACz and 2PACz solar cells surpass the efficiency of PTAA cells, with 2PACz yielding the highest efficiency of $20.9\\%$ in $J{-}V$ scan and $20.8\\%$ in the maximum power point (MPP) track. One of the 2PACz cells was masked, encapsulated and sent to Fraunhofer ISE for certification (see Fig. S23–S25 (ESI†) and red star in Fig. 3c). The certified MPP performance of $20.44\\%$ is close to our in-house measurement of $20.7\\%$ of that specific cell, validating our analysis. Interestingly, all SAM-based cells show a lower leakage current compared to a champion PTAA cell with a $\\sim10~\\mathrm{{nm}}$ thick PTAA polymer film (see Fig. 3d). This finding demonstrates that the formed SAMs are dense enough (with regard to number of molecules per surface area) to provide efficient rectification, even though this is just one molecular layer covering the ITO surface. \n\n![](images/6c972b87d71d679452cdcfbc1ea60f1ca5d9bae88654ac7ff4bdfe4aa3606c41.jpg) \nFig. 3 Device-related analysis of SAM-based solar cells in comparison to state-of-the-art PTAA solar cells with triple cation perovskite absorber. (a) $\\jmath_{-}\\chi$ curves under simulated AM 1.5G illumination at a scan rate of $250~\\mathsf{m V}\\thinspace\\mathsf{s}^{-1}$ in forward $(\\boldsymbol{J}_{\\mathsf{S C}}$ to $V_{\\mathrm{OC}},$ dashed) and reverse scan $(V_{\\mathsf{O C}}$ to ${\\cal J}_{\\mathsf{S C}},$ solid) with respective MPP tracks in the inset. (b) External quantum efficiency (EQE) spectra of best solar cells and corresponding integration of the product of EQE and $\\mathsf{A M}1.5\\mathsf{G}$ spectrum (right axis). (c) $\\mathsf{B o x}$ plot of power conversion efficiency (PCE) values for 41 V1036, 53 PTAA, 47 MeO-2PACz and 46 2PACz solar cells. (d) Typical $\\jmath_{-}\\chi$ curves measured under dark conditions of the respective hole-selective contacts. \n\nTable 1 Photovoltaic parameters from $\\jmath_{-}\\chi$ scans under illumination in reverse scan direction together with the efficiency of MPP tracking of best CsMAFA perovskite solar cells based on the different investigated holeselective contacts \n\n\n
HSCJsc (mA cm)Jsc_EQE (mA cm) 2)(V) VocFF (%)PCE (J-V) (%)PCE (MPP) (%)
V103621.221.11.04179.317.516.9
PTAA21.521.71.12579.319.218.9
MeO-2PACz22.222.51.14480.520.420.2
2PACz21.921.91.18880.220.920.8
\n\n# Energetic alignment \n\nAs shown above, both 2PACz and MeO-2PACz enable higher $V_{\\mathrm{OC}}$ values in solar cells compared to PTAA. Changes in $V_{\\mathrm{OC}}$ can have a variety of origins, most importantly changes of the bulk properties and of the non-radiative recombination velocities at one or both interfaces. The latter can be caused by either a higher selectivity due to more favorable energetic alignment and/or less defect states at one or both interfaces to the respective charge-selective contacts. Changes in the bulk properties (e.g., density of trap states) could be caused by altered crystallization of the perovskite film. Since the perovskite film crystallizes on top of various HSCs here, the morphology of the perovskite is analyzed with scanning electron microscopy (SEM) images and X-ray diffraction (XRD) patterns (Fig. S9 and $\\mathbf{S10},\\mathbf{ESI\\dagger}.$ ). No obvious differences in the grain morphology and X-ray diffractograms are observed. Moreover, we estimate the so-called Urbach energy, which is given by the slope of the exponential increase of the absorption edge,2,78 to be around $16~\\pm~2~\\mathrm{meV}$ measured on PSCs based on all four HSCs (obtained from EQE, see Fig. S11, ESI†). The Urbach energy is a measure of electronic disorder in the absorber material, and has been associated with the crystalline quality of lead halide perovskite thin films.79,80 Thus, since we observe neither significant differences in the Urbach energy, XRD, nor coarse grain morphology between the perovskites grown on the investigated HSCs, we conclude that the HSCs do not significantly alter the bulk film properties of the herein used CsMAFA perovskite. \n\nTo assess the energetic properties of the studied HSCs in relation to the perovskite absorber, we performed ultra-violet photoelectron spectroscopy (UPS) on ITO/HSC and on CsMAFA samples. We can thus compare the positions of the HSC’s \n\nHOMO (highest occupied molecular orbital) to the perovskite’s valence band maximum (VBM). Furthermore, adding the band gaps of the materials estimated from the absorption edge (Fig. 1b), we can also calculate the positions of the HSC’s LUMO (lowest unoccupied molecular orbital) and compare it to the perovskite’s conduction band minimum, CBM. The spectra are shown in Fig. S18 and S19 $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ and a summary of the results is schematically displayed in Fig. 4a, referenced to the vacuum level. The valence band or HOMO onset values are given in the lowermost row and the work function (i.e., difference between vacuum and Fermi level) values in the upmost row. \n\nAll SAMs show a p-type character in the energetic diagram. Comparing the valence band onset of the perovskite absorber to the HOMO levels of the HSC layers, it is apparent that MeO-2PACz and 2PACz are energetically more hole-selective than PTAA, due to the higher energetic barrier for electrons, while still allowing for an efficient extraction of holes (no barrier). 2PACz shows the closest alignment to the valence band maximum (VBM) of the perovskite, whereas V1036 shows the strongest offset. In this respect, MeO-2PACz is similar to PTAA, while the presence of methoxy groups in MeO-2PACz suggests a passivating function, as reported in earlier works.81,82 Changes in ITO work function with PA-based SAMs have been thoroughly analyzed in literature.71,83,84 In our case, the binding type between the studied SAMs is the same, thus differences between the work functions can be assigned to differences of the molecular dipole moments of the hole-selective fragments.85,86 The shift in work function between bare ITO (4.6 eV, see Fig. S18a, $\\mathrm{ESI\\dag}_{\\cdot}$ ) and the SAM-modified surface is higher for 2PACz as compared to MeO-2PACz, being 5.0 and $4.6~\\mathrm{eV}$ , respectively. This is in line with the larger molecular dipole moment of 2PACz of $^{+2}$ D compared to $+0.2$ D for MeO-2PACz (calculated by DFT following a previously published procedure,56 more details in the $\\mathrm{ESI\\dag}$ ). V1036 has a negative calculated dipole moment of $-2.4\\mathrm{~D~}$ , reducing the ITO work function to $4.4\\ \\mathrm{eV}.$ Judging from this energetic picture, the observed trend in $V_{\\mathrm{OC}}$ could potentially be explained with how close the HOMO of the HSCs is aligned to the perovskite’s VBM.87 V1036 devices show the smallest $V_{\\mathrm{OC}}$ and V1036 the largest offset in $E_{\\mathrm{VBM}}\\left(0.9\\:\\mathrm{eV}\\right)$ , whereas 2PACz yields the highest $V_{\\mathrm{OC}}$ and shows almost no offset to the perovskite’s VBM. \n\n![](images/b691fe2b562eeb81b03e2b3e2c605e26f4c549ab0f723fbbe21ea01d9568a897.jpg) \nFig. 4 Energetic alignment and Photoluminescence analysis on CsMAFA perovskite. (a) Schematic representation of the band edge positions of the investigated HSCs based on values from UPS measurements, referenced to the vacuum level. The lowermost numbers indicate the difference between Fermi level $(E_{\\mathsf{F}})$ of the ITO substrate and ${\\mathsf{H O M O}}$ level or valence band maximum $(E_{\\lor\\mathsf{B}M})$ (in eV, global error of $\\mathord{\\sim}0.1\\mathrm{eV})$ . The energetic distance between conduction band minimum $(E_{\\mathsf{C B}M})$ or LUMO and $E_{\\check{\\mathsf{V B M}}}$ was estimated from the onset of optical absorption. The grey, dashed lines are guides to the eye that mark the CBM and VBM levels of the perovskite absorber. (b) Summary of absPL and TrPL measurements. Left axis: average $V_{\\mathrm{OC}}$ values of solar cells (stars) based on the different HSCs, together with the average quasi Fermi level splitting values (QFLSs, blue spheres) obtained from perovskite films grown on the respective HSCs. The blue filling indicates the span between maximum and minimum QFLS values obtained from several samples (3 V1036, 5 PTAA, 8 MeO-2PACz and 9 2PACz samples). The $V_{\\mathrm{OC}}$ error bars show the standard deviation from values of 38 V1036 cells, 56 PTAA cells, 42 MeO2PACz cells and 40 2PACz cells. Right axis: the light-green bars represent the highest obtained PL decay time; the decay time of the perovskite on quartz glass is indicated as a dashed line. (c) Photoluminescence transients of perovskite films deposited on the respective HSCs. The dotted lines are extrapolated fits to the mono-exponential tail of the transients, from which the PL decay time values are obtained. \n\n# Photoluminescence studies \n\nThe energetic alignment discussed above already provides a first hint to why PSCs based on the new SAMs outperform those on PTAA. However, it remains unclear how the bands align to each other at the buried interface between the HSC and perovskite itself. Recent reports also point to an insensitivity of the energetic difference in $E_{\\mathrm{VBM}}$ between perovskite and HSC for moderate misalignment.88 Thus, we further investigate the differences with photoluminescence (PL) studies, using timeresolved PL (trPL) to study the behavior of the charge carriers on short time scales and absolute PL (absPL) to estimate the ‘‘implied $V_{\\mathrm{OC}}{}^{\\prime\\prime}$ or quasi Fermi level splitting (QFLS)89 of the bare absorber computed by the high-energy tail fit method27,90,91 for a temperature of $300~\\mathrm{K}$ . The PL measurements were conducted on glass/ITO/HSC/CsMAFA samples without the $\\mathbf{C}_{60}$ overlayer. The QFLS was also determined from the full 2PACz solar cell that is shown in Fig. 3a, with negligible difference to the $e V_{\\mathrm{OC}}$ value obtained from a $J{-}V$ scan (see Fig. S20, ESI†). \n\nFig. 4b shows a summary of the QFLS values from absPL (blue spheres) on the left axis, together with average values of measured $V_{\\mathrm{OC}}$ (stars) of the full devices. The right axis presents PL decay times from TrPL (bars), calculated from Fig. 4c, in comparison to the PL decay time for a perovskite film on quartz glass (dashed line), which is known as a highly passivated surface.27,92 The rising trend in average QFLS from V1036 over PTAA to MeO-2PACz and 2PACz fits to the trend in $V_{\\mathrm{OC}}$ . Compared to V1036 and PTAA, the spread of QFLS values is smaller with MeO-2PACz and 2PACz. The TrPL transients are plotted in Fig. 4b and were recorded at an excitation fluence that is relevant for device operation at 1 sun illumination (fluence $\\sim15{-}30~\\mathrm{nJ~cm}^{-2}$ , see PL section in ESI†). The PL measured on the perovskite film on glass decays monoexponentially. The deviation from mono-molecular decay in the measurements with HSCs could be attributed to charge transfer effects.93 MeO-2PACz allows for PL decay times of over $650\\mathrm{ns}$ , which approaches the decay time of the same perovskite on quartz glass of $\\sim860$ ns, a comparable value to the ones previously reported for the same perovskite in record-efficiency PSCs.27 Interestingly, the decay time on 2PACz with a value of $2~\\upmu\\mathrm{s}$ even surpasses the one on quartz glass by a factor of over 2. Since the 2PACz PL transient shows signs of slow charge transfer, the significantly longer decay time cannot be attributed to a mere reduction of majority carriers at the interface. We thus conclude that the interface defect density must be negligibly low, highlighting that bare Carbazole is chemically compatible to the perovskite, forming a well-passivated surface. A direct comparison to MeO-2PACz with regard to interface defect density is not possible from the TrPL data alone, since an energetic offset can independently affect interfacial recombination.94 However, the faster decay at early times suggests faster hole extraction. With the only difference between MeO-2PACz and 2PACz being the termination with a methoxy group, it is interesting to observe such an intrinsically different behavior in the charge carrier dynamics. \n\nComparing the values obtained on PTAA and on 2PACz, the decay times differ by an order of magnitude, and both the QFLS and $V_{\\mathrm{OC}}$ values are around $60~\\mathrm{mV}$ higher with 2PACz. This fits to the thermodynamically expected increase of $60\\ \\mathrm{\\mV}$ when increasing the photoluminescence yield by a factor of 10, with $k T\\mathrm{ln}\\left(10\\right)\\approx60\\mathrm{~meV}$ , where $k$ is the Boltzmann constant and $T$ the temperature (300 K).95 We emphasize that the FF values of the full solar cells are comparable among all HSCs, suggesting similarly efficient charge extraction. Thus, we conclude that the trend in PL decay time is set by the non-radiative recombination velocity at the interface. Assuming that interface recombination is dominating, the recombination velocities can be estimated to range from $193\\ \\mathrm{cm\\s^{-1}}$ (V1036) to a lowest value of $12\\ \\mathrm{cm}\\ \\mathrm{s}^{-1}$ for 2PACz (upper estimate, see Section 8 for details, $\\mathrm{ESI\\dag}$ ). The clear correlation between QFLS, PL decay time and $V_{\\mathrm{OC}}$ provides a strong indication that the differences in $V_{\\mathrm{OC}}$ of the solar cells are originating from differences in the compatibility of the HSC interface to the perovskite. This is either governed by the interface defect density, energetic alignment as addressed above, or a combination of both. It remains open whether the molecular dipole moments play a role other than the mentioned work function modifications. The energetic difference between QFLS and $e V_{\\mathrm{OC}}$ with all HSCs is induced by non-radiative recombination at the perovskite/ $\\mathrm{\\primeC}_{60}$ interface (see also Fig. S20, ESI†). Previously it was identified that the perovskite $/{\\bf C}_{60}$ interface limits the $V_{\\mathrm{OC}}$ to a fixed value in the used PSC architecture, independent of the perovskite bulk quality.27 Indeed, our PTAA devices achieve max. $\\mathrm{\\sim}1.13\\mathrm{V}.$ even though the perovskite on PTAA can reach a QFLS of up to $1.18\\ \\mathrm{~eV}$ . It is thus interesting that by increasing the holeselectivity and decreasing the interface recombination velocity, the $1.13{\\mathrm{~V~}}$ limitation can be overcome although the perovskite morphology stays the same. It is furthermore worth noting that a recent study that compared a wide variety of typically used charge-selective layers identified that every single layer introduces non-radiative losses compared to the bare perovskite bulk, lowering the PL decay time and QFLS.94 In sharp contrast, the herein introduced 2PACz HSC is an important demonstration that the opposite is possible as well, rendering a ‘‘lossless’’ hole-selective interface. With SAM contacts, further enhancement of the $V_{\\mathrm{OC}}$ to a level of the QFLS of the bare perovskite film or above is expected upon mitigating the losses introduced at the $\\mathbf{C}_{60}$ interface. \n\nTo conclude our analysis, we identified several aspects as to why the herein introduced molecules lead to high-performance PSCs, besides the already discussed dense film-forming properties. Consequently, a clear guidance could be drawn from our findings to develop other lossless contact materials in the near future: on the one hand, the structure of these small molecules leads to a small density of interfacial trap states as seen by the comparison of quartz glass to 2PACz-covered ITO and by the comparison of PTAA to MeO2PACz. On the other hand, as shown by simulations of a similar device stack in a recent work,94 our own energetic alignment data and other experimental studies,96–100 energetic alignment for majority carrier extraction influences interfacial recombination losses and is a crucial factor for achieving high $V_{\\mathrm{OC}}$ values. The strong correlation in our SAM model system (layers with similar carbazole chemistry and similar thickness, but different HOMO levels) indicates that by using carbazole derivatives and tuning the work function by dipole moment engineering, ideal hole-selective layers could be rationally designed for specific perovskite absorbers. Further investigations on the exact hole extraction mechanisms at a SAM interface might include simulations of the electric field in atomic scales,84 tunneling of charge carriers and atomistic simulations on the interaction between dipole moment and perovskite interface. \n\n# Stability assessment \n\nIn addition to the increased efficiencies of both MeO-2PACz and 2PACz-based solar cells compared to PTAA, we also observe an increased stability. Fig. 5a shows the time evolution of PCE under continuous MPP tracking for the investigated HSCs at simulated 1 sun $\\mathbf{AM}\\ 1.5\\mathbf{G}$ illumination without active sample cooling. The samples reach temperatures of at least $40~^{\\circ}\\mathbf{C}$ under operation. Only small differences are visible between cells with the investigated HSCs, while a slight advantage is evident for the MeO-2PACz and 2PACz-based devices after $^{11\\mathrm{~h~}}$ of operation ( $\\textless3\\%$ PCE loss with 2PACz with a stable value after an initial drop, $\\sim3\\%$ loss with MeO-2PACz, $\\sim6\\%$ loss with PTAA and almost $12\\%$ loss with V1036). A stronger difference is visible when increasing the stress on the solar cells, which is done here by light soaking at open-circuit condition under 1 sun illumination, a condition at which a high average density of charge-carriers is present in the device that can induce a quick degradation of the PSC.101 The most notable differences occur in the time evolution of $V_{\\mathrm{OC}}$ , as displayed in Fig. 5b. PTAA-based solar cells show a substantial drop $\\mathrm{\\Delta}60\\ \\mathrm{mV}$ amplitude) after two hours, while the $V_{\\mathrm{OC}}s$ of all SAM-based cells remain virtually stable after an initial drop caused by increasing temperature. Interestingly, light soaking steadily improves the $V_{\\mathrm{OC}}$ of V1036-based samples. The difference in stability between PTAA and SAMs under illumination cannot simply be explained with the differences in non-radiative recombination rates at the interface, since judging by QFLS and PL decay time, V1036 should then show the weakest $V_{\\mathrm{OC}}$ stability. We attribute the quick degradation of PTAA-based cells to be a material-specific characteristic of the CsMAFA/PTAA contact that occurs under conditions with a high number of excess charge carriers and direct illumination of the PTAA, as also observed in a recent work.102 A previous study identified that a large number of excess charge carriers, as under illumination at open-circuit, leads to a lowered energetic threshold of ionic movement.101 We hypothesize that the diffusion of iodine to the PTAA interface leads to structural damage of the PTAA, as recently argued by Sekimoto et al.103 In contrast, a SAM, being a chemically robust electrode modification with virtually no volume, is neither susceptible to structural damages nor to an accumulation of ions. \n\n![](images/ae1e9d93a2814c8fc96611a6c58b8d2ec36f2bfc33f4913187df0aec1d70d6aa.jpg) \nFig. 5 Stability assessments of PSCs based on the investigated HSCs in ${\\sf N}_{2}$ atmosphere. (a) MPP tracking under continuous, simulated 1 sun AM 1.5G illumination of uncooled devices (reaching a temperature of $\\sim40~^{\\circ}C$ in operation). (b) Time evolution of $V_{\\mathrm{OC}}$ values of solar cells kept at open-circuit conditions under light-soaking at full sun illumination at $\\sim40^{\\circ}\\mathsf C$ cell temperature (no active cooling). The values were extracted from $\\begin{array}{r}{J-V-}\\end{array}$ scans every $6{-}8\\mathsf{m i n}$ . The error bars show the standard deviation of these values across the individual cells (4 V1036, 6 PTAA, 3 MeO-2PACz and 10 2PACz cells). \n\n![](images/69b6a3d78a4da894ce9dc18224b2db5a4bf0218093a3ab33a62857b73bcfde99.jpg) \nFig. 6 Display of the versatility of $\\mathsf{S A M}$ contacts and tandem solar cell integration. (a) $\\jmath_{-}\\chi$ curves under illumination of solar cells based on a solution processed ‘‘double cation’’ perovskite absorber $(F A_{95}{\\mathsf{M A}}_{5}{\\mathsf{P b}}(\\mathsf{I}_{95}{\\mathsf{B r}}_{5})_{3},$ , orange line) and co-evaporated perovskite absorber $(M A P b|_{3},$ green line). Inset: Continuous MPP tracks of these cells. (b) $\\jmath_{-}\\chi$ curve of a monolithic CIGSe/perovskite tandem solar cell (active area of $1.034~\\mathsf{c m}^{2})$ , with MeO2PACz2PACz as HSC conformally covering the rough CIGSe bottom cell. The orange circle indicates the MPP at $23.26\\%$ PCE (see certified MPP track by Fraunhofer ISE in Fig. S27, ESI†). Inset: SEM image of the cross-section of a representative tandem device. The recombination contact consists of aluminum-doped zinc oxide, sputtered onto the CIGSe surface and covered by MeO-2PACz. \n\n# Versatility of a SAM contact and tandem solar cell integration \n\nIn order to show versatility of the new HSC molecules, we demonstrate in Fig. 6 that the SAMs also yield highly efficient perovskite solar cells with perovskite compositions other than CsMAFA. In addition to the ‘‘triple cation’’ composition utilized for the analysis above, we investigate here a ‘‘double cation’’ $\\mathbf{MA}_{5}\\mathbf{FA}_{95}\\mathbf{Pb}\\big(\\mathbf{I}_{95}\\mathbf{Br}_{5}\\big)_{3}$ (MAFA)8 absorber with a lower band gap of ca. 1.55 eV and a ‘‘single cation’’ $\\left(\\mathbf{MAPbI}_{3}\\right)$ absorber layer that is fabricated by direct co-evaporation with an optical band gap of $c a.\\ 1.60\\ \\mathrm{\\eV}$ (see Fig. S26 for the absorption onset, $\\mathrm{ESI\\dag}\\$ ). Table 2 shows the corresponding performance metrics. We noticed that on MeO-2PACz, the MAFA and $\\mathbf{MAPbI}_{3}$ perovskites tend to crystallize more reproducibly than on 2PACz, thus we chose MeO-2PACz for the purpose of demonstrating that a SAM enables a broad spectrum of applications. \n\nPerovskite processing by co-evaporation is highly attractive due to large-area compatibility and absence of potentially harmful solvents for fabrication. Utilizing MeO-2PACz as the HSC also works well with the co-evaporated $\\mathbf{MAPbI}_{3}$ perovskite absorber. The herein shown stabilized PCE of $19.6\\%$ with over $1.14\\mathrm{~V~}V_{\\mathrm{OC}}$ is approaching the PCE of the best co-evaporated PSC to date and represents the highest reported value for $\\mathsf{p}{\\mathrm{-i}}{\\mathrm{-n}}$ type devices utilizing co-evaporation for the perovskite absorber.104,105 \n\nRecently, highest PSC performances were reported for the MAFA double cation composition.15,106 Compared to the CsMAFA solar cells shown before, the MAFA cell has an advantage in higher current density due to the lower bandgap of the composition, but still enables a relatively high $V_{\\mathrm{OC}}$ . Without detailed optimization, the MAFA absorber enables a stabilized PCE of $21.1\\%$ when utilizing MeO-2PACz as the HSC. As seen in Table 2, for all three solar cells the $J_{\\mathrm{SC}}$ values measured in the $J{-}V$ curve closely fit to the values obtained by integrating the product of EQE measurement and AM 1.5G spectrum (Fig. S26a, ESI†). 2PACz enables an over $21\\%$ -efficient MAFA PSC as well, as shown in Fig. S27 $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ . \n\nFurthermore, we show in Fig. 6b that a SAM is also a suitable HSC for manufacturing PSCs on rough surfaces, which is essential for e.g., CIGSe/perovskite tandem solar cells. Allthin-film tandem solar cells pose an attractive strategy for cheap, versatile and flexible high-efficiency solar cells and are a promising route for the introduction of halide perovskites into industrial production. CIGSe enables thin-film solar cells with a suitable bandgap for the use in perovskite-based tandem solar cells. However, the rough surface of the CIGSe makes it difficult to process the thin HSCs that currently enable efficient perovskite top cells. Recently, we demonstrated that the use of a $\\mathrm{NiO_{x}}$ layer processed by atomic layer deposition (ALD) in combination with PTAA represents a CIGSe/perovskitecompatible hole-transport layer that prevents shunting caused by the CIGSe roughness, enabling a $21.6\\%$ -efficient tandem cell.47 Here we now show that a SAM removes the need of an ALD step, since the self-assembly process works reliably even on rough surfaces, by dipping the CIGSe bottom cell into a MeO-2PACz solution. The perovskite layer was fabricated by solution-processing and the top contact layers by either evaporation or ALD/sputtering (see $\\mathrm{ESI\\dag}$ for details). The so prepared tandem solar cell, shown in Fig. 6b, shows a stabilized efficiency of $23.26\\%$ on an area of $1.03~\\mathrm{cm}^{2}$ (certified by Fraunhofer ISE, see Fig. ${\\bf S}30{\\mathrm{-}}{\\bf S}32,{\\mathrm{~ESI}}{\\dagger}.$ , while the bottom cell alone has a PCE of $15\\mathrm{-}16\\%$ (see Fig. S28, $\\mathbf{ESI\\dagger}$ ). The EQEs of both sub-cells measured in the tandem are shown in Fig. S29 $\\left(\\mathrm{ESI\\dag}\\right)$ . Following the $V_{\\mathrm{OC}}$ trend shown earlier, our SAM-based tandem shows an improved $V_{\\mathrm{OC}}$ as compared to our previously published one ( $\\mathrm{\\sim90~mV}$ increase from 1.59 to 1.68 V). However, the SAM-based tandem cell shows a lower FF ( $72\\%$ vs. $76\\%$ with the $\\mathrm{NiO}_{2}/\\mathrm{PTAA}$ double layer), which here is mainly limited by the shunt resistance. Since the tandem current is limited here by the bottom cell, further optimization could be dedicated to developing a more robust stack design that prevents micro-shunts caused by processing and measuring (here we use the same design as in our previous work47). Nonetheless, the here presented tandem cell surpasses the previous record46 $\\left(22.4\\%\\right)$ in PCE and area ( $\\mathrm{\\dot{\\}p}.04\\ \\mathrm{cm}^{2}$ vs. $1.03~\\mathrm{cm}^{2}$ here). The simplicity of the tandem stack and the use of as-deposited CIGSe additionally suggests that our approach could be easily adopted in higher throughput fabrication. \n\nTable 2 Photovoltaic parameters from $\\jmath_{-}\\boldsymbol{V}$ scans under illumination in reverse scan direction as well as continuous MPP tracking. Presented are single cells with double cation MAFA and co-evaporated $M A P b|_{3}$ perovskite and a CIGSe/perovskite (triple cation) tandem solar cell. All cells are based on MeO-2PACz as the HSC \n\n\n
PerovskiteDevice typeJsc (mA cm-2)Jsc_EQE (mA cm-2)Voc (V)FF (%)PCE (J-V) (%)PCE (MPP) (%)
Co-evaporated MAPbI3Single22.622.51.14576.819.819.6
Double cation MAFASingle23.523.41.12080.621.221.1
Triple cation CsMAFAMonolithic19.1720.2/19.1a1.6871.923.1623.26 ± 0.75
Tandem(certified)(in-house)(certified)(certified)(certified)(certified)
\n\na First value corresponds to the perovskite top cell and second value to the CIGSe bottom cell. \n\nIn summary, the compatibility of the SAM to three different perovskite compositions, two different processing techniques (solution and vacuum process), two different oxides (ITO in the single junctions and Al-doped zinc oxide in the tandem) and two different substrate morphologies (rough and flat) strongly suggests that SAM hole-selective contacts represent a universal approach for perovskite-based photovoltaics. \n\n# Conclusion \n\nTwo new simple molecules that form self-assembling monolayers (SAMs), MeO-2PACz and 2PACz, were synthesized and integrated into inverted perovskite solar cells, enabling holeselective contacts with minimized non-radiative losses. The new SAMs can be deposited on transparent conductive oxides via spin-coating or by dipping the substrate into the solution, both yielding layers of comparable properties, combining high reproducibility and ease of fabrication. Both new SAMs outperform the polymer PTAA, the material that enabled the highestperforming $\\mathsf{p}{\\mathsf{-i-n}}$ PSCs to date, in efficiency, stability and versatility. With a standard triple-cation absorber, a maximum power conversion efficiency of $20.9\\%$ , certified efficiency of $20.44\\%$ and a $V_{\\mathrm{OC}}$ of up to $1.19{\\mathrm{V}}$ were demonstrated. MeO-2PACz further enabled a $21.1\\%$ -efficient solar cell with a double-cation absorber, and a stabilized efficiency of $19.6\\%$ with a co-evaporated singlecation absorber. Photoelectron spectroscopy and photoluminescence (PL) investigations revealed a well-suited energetic alignment and strongly reduced non-radiative recombination at the interface between absorber and contact, leading to a PL decay time of $2~{\\upmu\\mathrm{s}}$ for a perovskite on 2PACz. As deduced from a comparison between the PL transients of perovskite grown on 2PACz versus on quartz glass, the interface defect density at the $2\\mathbf{P}\\mathbf{ACz}/$ perovskite interface is minimal. From the trend between surface recombination velocity, $V_{\\mathrm{OC}}$ and offset between the SAM HOMO level and perovskite valence band edge, our model system provides experimental evidence for the energetic alignment and interface defect density being similarly important for mitigating non-radiative recombination losses. The results highlight that carbazole derivatives can combine all necessary features for lossless interfaces and are thus a compelling material class for future chemical engineering of high-performance hole-selective contacts. In a light-soaking stress test at open circuit conditions, SAM-based PSCs showed a higher stability compared to PTAA-based cells. Finally, by integrating a SAM contact into a monolithic CIGSe/perovskite tandem solar cell, the ability of conformally creating a hole-selective layer on a rough surface was demonstrated. This led to a stabilized, certified PCE of $23.26\\%$ with facile device design on an active area of $1.03~\\mathrm{cm}^{2}$ , surpassing the values achieved with a complex bilayer47 or mechanical polishing.46 Importantly, the herein demonstrated solar cells are fabricated without additional passivation layers, additives or dopants. Together with the minimal material consumption, manifold substrate compatibility and simplicity during fabrication, the SAM contacts might present a realistic way to further progress perovskite photovoltaics into a low-cost, wide-spread technology. \n\n# Author contributions \n\nA. A. A., A. M., M. J. and S. A. coordinated the project and designed the experiments. A. M., Er. K. and T. M. designed, synthesized and characterized the SAM molecules. A. A. A. optimized the SAM formation procedures, carried out sample fabrication and solar cell characterization, coordinated data analysis and prepared the manuscript figures. M. T. recorded the RAIRS and FTIR spectra, and calculated the theoretical spectra; M. T., G. N., A. M. and A. A. A. analyzed the data. G. C. measured the UPS and XPS data; A. A. A., A. M. and G. C. analyzed the data. A. A. A. recorded the absolute PL data in a setup designed by J. A. M. and T. U., and, together with S. L., recorded the trPL data in a setup designed by C. J. H., S. L. and T. U. The PL data was analyzed by A. A. A., J. A. M, S. L. and T. U. Fabrication of the co-evaporated solar cell was carried out by M. R.; M. R. and L. G. E. optimized the co-evaporation process. A. A. A. and M. J. processed the CIGSe/perovskite tandem solar cell, with optimization of the top contact by Ei. K. The CIGSe bottom cell was fabricated by T. B. and C. K. All authors contributed to manuscript writing and scientific discussions. B. R., T. U., L. K., G. N., R. S., V. G. and S. A. supervised the project. \n\n# Conflicts of interest \n\nThere are no competing interests to declare. \n\n# Acknowledgements \n\nThe authors thank M. Gabernig, C. Ferber, T. Lußky, H. Heinz, C. Klimm and M. Muske at Institute for Silicon Photovoltaics (HZB), T. H¨anel, B. Bunn, K. Mayer-Stillrich, M. Kirsch, S. Stutzke and J. Lauche at PVcomB (HZB) for technical assistance. For XPS and UPS measurements, the Energy Materials In-Situ Laboratory (EMIL), R. Wilks and J. Frisch are acknowledged. Funding was provided by German Federal Ministry for Education and Research (BMBF) (grant no. 03SF0540) within the project ‘‘Materialforschung fu¨r die Energiewende’’, (BMWi) project ‘‘EFFCIS’’ (grant no. 0324076B). A. M. and T. M. acknowledge funding by the Research Council of Lithuania under grant agreement no. S-MIP-19-5/SV3-1079 of the SAM project. G. N. gratefully acknowledges the Center of Spectroscopic Characterization of Materials and Electronic/Molecular Processes (SPECTROVERSUM Infrastructure) for use of their FTIR spectrometer. T. B. acknowledges funding from the BMWi project Speedcigs (grant no. 0324095D). The authors acknowledge the HyPerCells graduate school for support and the funding by the Helmholtz Foundation for the HySPRINT Innovation lab which was supported by the Helmholtz Energy Materials Foundry (HEMF). The research leading to these results has partly received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 763977 of the PerTPV project. \n\n# References \n\n1 Web of Science search for ‘perovskite’ AND ‘solar’ AND ‘cells’ in the title. \n2 S. de Wolf, J. Holovsky, S.-J. Moon, P. Lo¨per, B. Niesen, M. Ledinsky, F. Haug, J. Yum and C. Ballif, J. Phys. Chem. C, 2014, 5, 1035–1139. \n3 W. J. Yin, T. Shi and Y. Yan, Appl. Phys. Lett., 2014, 104(6), 063903. \n4 K. X. Steirer, P. Schulz, G. Teeter, V. Stevanovic, M. Yang, K. Zhu and J. J. Berry, ACS Energy Lett., 2016, 1, 360–366. \n5 Z. Liu, L. Kru¨ckemeier, B. Krogmeier, B. Klingebiel, J. A. M´arquez, S. Levcenko, S. O¨z, S. Mathur, U. Rau, T. Unold and T. Kirchartz, ACS Energy Lett., 2019, 4, 110–117. \n6 M. Liu, M. B. Johnston and H. J. Snaith, Nature, 2013, 501, 395–398. \n7 Z. Wei, H. Chen, K. Yan and S. Yang, Angew. Chem., Int. Ed., 2014, 53, 13239–13243. \n8 N. J. Jeon, J. H. Noh, W. S. Yang, Y. C. Kim, S. Ryu, J. Seo and S. Il Seok, Nature, 2015, 517, 476–480. \n9 A. De Vos, J. Phys. D: Appl. Phys., 1980, 13, 839–846. \n10 S. Albrecht, M. Saliba, J. P. Correa Baena, F. Lang, L. Kegelmann, M. Mews, L. Steier, A. Abate, J. Rappich, L. Korte, R. Schlatmann, M. K. Nazeeruddin, A. Hagfeldt, M. Gra¨tzel and B. Rech, Energy Environ. Sci., 2016, 9, 81–88. \n11 J. P. Mailoa, C. D. Bailie, E. C. Johlin, E. T. Hoke, A. J. Akey, W. H. Nguyen, M. D. McGehee and T. Buonassisi, Appl. Phys. Lett., 2015, 106(12), 121105. \n12 T. Todorov, T. Gershon, O. Gunawan, Y. S. Lee, C. Sturdevant, L. Y. Chang and S. Guha, Adv. Energy Mater., 2015, 5, 1–6. \n13 J. Luo, X. Wang, S. Li, J. Liu, Y. Guo, G. Niu, L. Yao, Y. Fu, L. Gao, Q. Dong, C. Zhao, M. Leng, F. Ma, W. Liang, L. Wang, S. Jin, J. Han, L. Zhang, J. Etheridge, J. Wang, Y. Yan, E. H. Sargent and J. Tang, Nature, 2018, 563, 541–545. \n14 G. E. Eperon, T. Leijtens, K. A. Bush, R. Prasanna, T. Green, J. T. W. Wang, D. P. McMeekin, G. Volonakis, R. L. Milot, R. May, A. Palmstrom, D. J. Slotcavage, R. A. Belisle, J. B. Patel, E. S. Parrott, R. J. Sutton, W. Ma, F. Moghadam, B. Conings, A. Babayigit, H. G. Boyen, S. Bent, F. Giustino, L. M. Herz, M. B. Johnston, M. D. McGehee and H. J. Snaith, Science, 2016, 354, 861–865. \n15 Q. Jiang, Y. Zhao, X. Zhang, X. Yang, Y. Chen, Z. Chu, Q. Ye, X. Li, Z. Yin and J. You, Nat. Photonics, 2019, 13(7), 460–466. \n16 K. J¨ager, L. Korte, B. Rech and S. Albrecht, Opt. Express, 2017, 25, A473. \n17 K. Bush, A. F. Palmstrom, Z. J. Yu, M. Boccard, R. Cheacharoen, J. P. Mailoa, D. P. McMeekin, R. L. Z. Hoye, C. D. Bailie, T. Leijtens, I. M. Peters, M. C. Minichetti, N. Rolston, R. Prasanna, S. Sofia, D. Harwood, W. Ma, F. Moghadam, H. J. Snaith, T. Buonassisi, Z. C. Holman, S. F. Bent and M. D. McGehee, Nat. Energy, 2017, 2, 1–7. \n18 E. Ko¨hnen, M. Josˇt, A. B. Morales-Vilches, P. Tockhorn, A. Al-Ashouri, B. Macco, L. Kegelmann, L. Korte, B. Rech, R. Schlatmann, B. Stannowski and S. Albrecht, Sustainable Energy Fuels, 2019, 3, 1995–2005. \n19 J. Y. Jeng, Y. F. Chiang, M. H. Lee, S. R. Peng, T. F. Guo, P. Chen and T. C. Wen, Adv. Mater., 2013, 25, 3727–3732. \n20 M. Saliba, M. Stolterfoht, C. M. Wolff, D. Neher and A. Abate, Joule, 2018, 2, 1019–1024. \n21 A. Magomedov, E. Kasparaviˇcius, K. Rakstys, S. Paek, N. Gasilova, K. Geneviˇcius, G. Juˇska, T. Malinauskas, M. K. Nazeeruddin and V. Getautis, J. Mater. Chem. C, 2018, 6, 8874–8878. \n22 F. Lamberti, T. Gatti, E. Cescon, R. Sorrentino, A. Rizzo, E. Menna, G. Meneghesso, M. Meneghetti, A. Petrozza and L. Franco, Chem, 2019, 1–12. \n23 E. Kasparavicius, A. Magomedov, T. Malinauskas and V. Getautis, Chem. – Eur. J., 2018, 24, 9910–9918. \n24 J. H. Heo, H. J. Han, D. Kim, T. K. Ahn and S. H. Im, Energy Environ. Sci., 2015, 8, 1602–1608. \n25 P. Docampo, J. M. Ball, M. Darwich, G. E. Eperon and H. J. Snaith, Nat. Commun., 2013, 4, 1–6. \n26 M. Kaltenbrunner, G. Adam, E. D. Głowacki, M. Drack, R. Schwo¨diauer, L. Leonat, D. H. Apaydin, H. Groiss, M. C. Scharber, M. S. White, N. S. Sariciftci and S. Bauer, Nat. Mater., 2015, 14, 1032–1039. \n27 M. Stolterfoht, C. M. Wolff, J. A. Ma´rquez, S. Zhang, C. J. Hages, D. Rothhardt, S. Albrecht, P. L. Burn, P. Meredith, T. Unold and D. Neher, Nat. Energy, 2018, 3, 847–854. \n28 J. Seo, S. Park, Y. Chan Kim, N. J. Jeon, J. H. Noh, S. C. Yoon and S. Il Seok, Energy Environ. Sci., 2014, 7, 2642–2646. \n29 C. M. Wolff, F. Zu, A. Paulke, L. P. Toro, N. Koch and D. Neher, Adv. Mater., 2017, 29, 1–8. \n30 Q. Wang, Q. Dong, T. Li, A. Gruverman and J. Huang, Adv. Mater., 2016, 28, 6734–6739. \n31 X. Liu, Y. Zhang, L. Shi, Z. Liu, J. Huang, J. S. Yun, Y. Zeng, A. Pu, K. Sun, Z. Hameiri, J. A. Stride, J. Seidel, M. A. Green and X. Hao, Adv. Energy Mater., 2018, 1800138. \n32 J. Lee, H. Kang, G. Kim, H. Back, J. Kim, S. Hong, B. Park, E. Lee and K. Lee, Adv. Mater., 2017, 29, 1–8. \n33 X. Zheng, B. Chen, J. Dai, Y. Fang, Y. Bai, Y. Lin, H. Wei, X. C. Zeng and J. Huang, Nat. Energy, 2017, 2, 17102. \n34 D. Luo, W. Yang, Z. Wang, A. Sadhanala, Q. Hu, R. Su, R. Shivanna, G. F. Trindade, J. F. Watts, Z. Xu, T. Liu, K. Chen, F. Ye, P. Wu, L. Zhao, J. Wu, Y. Tu, Y. Zhang, X. Yang, W. Zhang, R. H. Friend, Q. Gong, H. J. Snaith and R. Zhu, Science, 2018, 360(6396), 1442–1446. \n35 P. Caprioglio, F. Zu, C. M. Wolff, J. A. Ma´rquez Prieto, M. Stolterfoht, P. Becker, N. Koch, T. Unold, B. Rech, S. Albrecht and D. Neher, Sustainable Energy Fuels, 2019, 3, 550–563. \n36 S. Yang, J. Dai, Z. Yu, Y. Shao, Y. Zhou, X. Xiao, X. C. Zeng and J. Huang, J. Am. Chem. Soc., 2019, 141(14), 5781–5787. \n37 M. Halik and A. Hirsch, Adv. Mater., 2011, 23, 2689–2695. \n38 A. Vilan, D. Aswal and D. Cahen, Chem. Rev., 2017, 117, 4248–4286. \n39 W. C. Bigelow, D. L. Pickett and W. A. Zisman, J. Colloid Sci., 1946, 1, 513–538. \n40 W. B. Russel, Sci. Technol., 2001, 413, 8257–8263. \n41 B. Gothe, T. De Roo, J. Will, T. Unruh, S. Mecking and M. Halik, Nanoscale, 2017, 9, 18584–18589. \n42 L. Liu, A. Mei, T. Liu, P. Jiang, Y. Sheng, L. Zhang and H. Han, J. Am. Chem. Soc., 2015, 137, 1790–1793. \n43 Z. Gu, L. Zuo, T. T. Larsen-Olsen, T. Ye, G. Wu, F. C. Krebs and H. Chen, J. Mater. Chem. A, 2015, 3, 24254–24260. \n44 A. Magomedov, A. Al-Ashouri, E. Kasparaviˇcius, S. Strazdaite, G. Niaura, M. Joˇst, T. Malinauskas, S. Albrecht and V. Getautis, Adv. Energy Mater., 2018, 8, 1801892. \n45 E. Yalcin, M. Can, C. Rodriguez-Seco, E. Aktas, R. Pudi, W. Cambarau, S. Demic and E. Palomares, Energy Environ. Sci., 2019, 12, 230–237. \n46 Q. Han, Y.-T. Hsieh, L. Meng, J.-L. Wu, P. Sun, E.-P. Yao, S.-Y. Chang, S.-H. Bae, T. Kato, V. Bermudez and Y. Yang, Science, 2018, 361, 904–908. \n47 M. Joˇst, T. Bertram, D. Koushik, J. A. Marquez, M. A. Verheijen, M. D. Heinemann, E. Ko¨hnen, A. Al-Ashouri, S. Braunger, F. Lang, B. Rech, T. Unold, M. Creatore, I. Lauermann, C. A. Kaufmann, R. Schlatmann and S. Albrecht, ACS Energy Lett., 2019, 4, 583–590. \n48 H. Hoegl, J. Phys. Chem., 1965, 69, 755–766. \n49 J. V. Grazulevicius, P. Strohriegl, J. Pielichowski and K. Pielichowski, Prog. Polym. Sci., 2003, 28, 1297–1353. \n50 B. Wex and B. R. Kaafarani, J. Mater. Chem. C, 2017, 5, 8622–8653. \n51 M. S. Kang, S. Do Sung, I. T. Choi, H. Kim, M. Hong, J. Kim, W. I. Lee and H. K. Kim, ACS Appl. Mater. Interfaces, 2015, 7, 22213–22217. \n52 T. J. Gardner, C. D. Frisbie and M. S. Wrighton, J. Am. Chem. Soc., 1995, 117, 6927–6933. \n53 E. L. Hanson, J. Guo, N. Koch, J. Schwartz and S. L. Bernasek, J. Am. Chem. Soc., 2005, 127, 10058–10062. \n54 S. A. Paniagua, E. L. Li and S. R. Marder, Phys. Chem. Chem. Phys., 2014, 16, 2874–2881. \n55 N. Metoki, L. Liu, E. Beilis, N. Eliaz and D. Mandler, Langmuir, 2014, 30, 6791–6799. \n56 I. Lange, S. Reiter, M. Pa¨tzel, A. Zykov, A. Nefedov, J. Hildebrandt, S. Hecht, S. Kowarik, C. Wo¨ll, G. Heimel and D. Neher, Adv. Funct. Mater., 2014, 24, 7014–7024. \n57 R. Quin˜ones, A. Raman and E. S. Gawalt, Thin Solid Films, 2008, 516, 8774–8781. \n58 F. Ambrosio, N. Martsinovich and A. Troisi, J. Phys. Chem. Lett., 2012, 3, 1531–1535. \n59 S. A. Paniagua, A. J. Giordano, O. L. Smith, S. Barlow, H. Li, N. R. Armstrong, J. E. Pemberton, J. L. Bre´das, D. Ginger and S. R. Marder, Chem. Rev., 2016, 116, 7117–7158. \n60 Y. Hou, X. Du, S. Scheiner, D. P. McMeekin, Z. Wang, N. Li, M. S. Killian, H. Chen, M. Richter, I. Levchuk, N. Schrenker, E. Spiecker, T. Stubhan, N. A. Luechinger, A. Hirsch, P. Schmuki, H. P. Steinru¨ck, R. H. Fink, M. Halik, H. J. Snaith and C. J. Brabec, Science, 2017, 358, 1192–1197. \n61 H. Y. Nie, M. J. Walzak and N. S. McIntyre, J. Phys. Chem. B, 2006, 110, 21101–21108. \n62 S. Casalini, C. A. Bortolotti, F. Leonardi and F. Biscarini, Chem. Soc. Rev., 2017, 46, 40–71. \n63 P. Xue, P. Wang, P. Chen, B. Yao, P. Gong, J. Sun, Z. Zhang and R. Lu, Chem. Sci., 2017, 8, 6060–6065. \n64 R. F. Dou, X. C. Ma, L. Xi, H. L. Yip, K. Y. Wong, W. M. Lau, J. F. Jia, Q. K. Xue, W. S. Yang, H. Ma and A. K. Y. Jen, Langmuir, 2006, 22, 3049–3056. \n65 F. M. Hoffmann, Surf. Sci. Rep., 1983, 3, 107–192. \n66 O. I. Negru and M. Grigoras, J. Polym. Res., 2015, 22, 1–11. \n67 A. Botta, S. Pragliola, V. Venditto, A. Rubino, S. Aprano, A. De Girolamo Del Mauro, M. Grazia Maglione and C. Minarini, Polym. Compos., 2015, 36, 1110–1117. \n68 O. Abbas, G. Compe\\`re, Y. Larondelle, D. Pompeu, H. Rogez and V. Baeten, Vib. Spectrosc., 2017, 92, 111–118. \n69 I. Matulaitiene, Z. Kuodis, A. Matijosˇka, O. Eicher-Lorka and G. Niaura, J. Phys. Chem. C, 2015, 119, 26481–26492. \n70 S. Schneider, M. F¨user, M. Bolte and A. Terfort, Electrochim. Acta, 2017, 246, 853–863. \n71 S. A. Paniagua, P. J. Hotchkiss, S. C. Jones, S. R. Marder, A. Mudalige, F. S. Marrikar, J. E. Pemberton and N. R. Armstrong, J. Phys. Chem. C, 2008, 112, 7809–7817. \n72 M. Bomers, A. Mezy, L. Cerutti, F. Barho, F. GonzalezPosada Flores, E. Tournie´ and T. Taliercio, Appl. Surf. Sci., 2018, 451, 241–249. \n73 R. Quin˜ones, S. Garretson, G. Behnke, J. W. Fagan, K. T. Mueller, S. Agarwal and R. K. Gupta, Thin Solid Films, 2017, 642, 195–206. \n74 W. Zhang, W. Ju, X. Wu, Y. Wang, Q. Wang, H. Zhou, S. Wang and C. Hu, Appl. Surf. Sci., 2016, 367, 542–551. \n75 J. F. Moulder, W. F. Stickle, P. E. Sobol and K. D. Bomben, Handbook of X-ray Photoelectron Spectroscopy, 1992. \n76 M. Saliba, T. Matsui, J.-Y. Seo, K. Domanski, J.-P. CorreaBaena, M. K. Nazeeruddin, S. M. Zakeeruddin, W. Tress, A. Abate, A. Hagfeldt and M. Gra¨tzel, Energy Environ. Sci., 2016, 9, 1989–1997. \n77 X. Zheng, B. Chen, J. Dai, Y. Fang, Y. Bai, Y. Lin, H. Wei, X. C. C. Zeng and J. Huang, Nat. Energy, 2017, 2, 17102. \n78 F. Urbach, Phys. Rev., 1953, 92, 1324. \n79 J. Kim, S. H. Lee, J. H. Lee and K. H. Hong, J. Phys. Chem. Lett., 2014, 5, 1312–1317. \n80 A. Sadhanala, F. Deschler, T. H. Thomas, S. E. Dutton, K. C. Goedel, F. C. Hanusch, M. L. Lai, U. Steiner, T. Bein, P. Docampo, D. Cahen and R. H. Friend, J. Phys. Chem. Lett., 2014, 5, 2501–2505. \n81 C. Huang, W. Fu, C. Z. Li, Z. Zhang, W. Qiu, M. Shi, P. Heremans, A. K. Y. Jen and H. Chen, J. Am. Chem. Soc., 2016, 138, 2528–2531. \n82 S. J. Park, S. Jeon, I. K. Lee, J. Zhang, H. Jeong, J. Y. Park, J. Bang, T. K. Ahn, H. W. Shin, B. G. Kim and H. J. Park, J. Mater. Chem. A, 2017, 5, 13220–13227. \n83 P. J. Hotchkiss, H. Li, P. B. Paramonov, S. A. Paniagua, S. C. Jones, N. R. Armstrong, J. L. Br´edas and S. R. Marder, Adv. Mater., 2009, 21, 4496–4501. \n84 M. Timpel, H. Li, M. V. Nardi, B. Wegner, J. Frisch, P. J. Hotchkiss, S. R. Marder, S. Barlow, J. L. Bre´das and N. Koch, Adv. Funct. Mater., 2018, 28, 1–12. \n85 H. Li, P. Paramonov and J. L. Bredas, J. Mater. Chem., 2010, 20, 2630–2637. \n86 J. Rittich, S. Jung, J. Siekmann and M. Wuttig, Phys. Status Solidi B, 2018, 255, 27–29. \n87 S. Ryu, J. H. Noh, N. J. Jeon, Y. Chan Kim, W. S. Yang, J. Seo and S. Il Seok, Energy Environ. Sci., 2014, 7, 2614–2618. \n88 R. A. Belisle, P. Jain, R. Prasanna, T. Leijtens and M. D. McGehee, ACS Energy Lett., 2016, 1, 556–560. \n89 K. Schick, E. Daub, S. Finkbeiner and P. W¨urfel, Appl. Phys. A: Solids Surf., 1992, 54, 109–114. \n90 A. Delamarre, L. Lombez and J. F. Guillemoles, Appl. Phys. Lett., 2012, 100(13), 131108. 91 T. Unold and L. Gu¨tay, Advanced Characterization Techniques for Thin Film Solar Cells, John Wiley & Sons, Ltd, 2011, pp. 151–175. 92 D. W. Dequilettes, S. Koch, S. Burke, R. K. Paranji, A. J. Shropshire, M. E. Ziffer and D. S. Ginger, ACS Energy Lett., 2016, 1, 438–444. \n93 B. Krogmeier, F. Staub, D. Grabowski, U. Rau and T. Kirchartz, Sustainable Energy Fuels, 2018, 2, 1027–1034. \n94 M. Stolterfoht, P. Caprioglio, C. M. Wolff, J. A. Ma´rquez, J. Nordmann, S. Zhang, D. Rothhardt, U. Ho¨rmann, Y. Amir, A. Redinger, L. Kegelmann, F. Zu, S. Albrecht, N. Koch, T. Kirchartz, M. Saliba, T. Unold and D. Neher, Energy Environ. Sci., 2019, 12(9), 2778–2788. \n95 R. T. Ross, J. Chem. Phys., 1967, 46, 4590–4593. \n96 P. Schulz, L. L. Whittaker-Brooks, B. A. Macleod, D. C. Olson, Y. L. Loo and A. Kahn, Adv. Mater. Interfaces, 2015, 2(7), 1400532. \n97 J. P. Correa Baena, L. Steier, W. Tress, M. Saliba, S. Neutzner, T. Matsui, F. Giordano, T. J. Jacobsson, A. R. Srimath Kandada, S. M. Zakeeruddin, A. Petrozza, A. Abate, M. K. Nazeeruddin, M. Gra¨tzel and A. Hagfeldt, Energy Environ. Sci., 2015, 8, 2928–2934. 98 P. Caprioglio, M. Stolterfoht, C. M. Wolff, T. Unold, B. Rech, S. Albrecht and D. Neher, Adv. Energy Mater., 2019, 1901631. \n99 P. Schulz, D. Cahen and A. Kahn, Chem. Rev., 2019, 119, 3349–3417. \n100 P. Schulz, E. Edri, S. Kirmayer, G. Hodes, D. Cahen and A. Kahn, Energy Environ. Sci., 2014, 7, 1377–1381. \n101 Y. Yan, P. N. Rudd, J. Zhao, Z. Yu, Y. Fang, Y. Lin, Y. Yuan, Y. Deng, J. Huang, B. Chen and C. Bao, Nat. Commun., 2018, 9, 1–9. \n102 B. Chen, J. Song, X. Dai, Y. Liu, P. N. Rudd, X. Hong and J. Huang, Adv. Mater., 2019, 1902413. \n103 T. Sekimoto, T. Matsui, T. Nishihara, R. Uchida, T. Sekiguchi and T. Negami, ACS Appl. Energy Mater., 2019, 2, 5039–5049. \n104 J. Avila, L. Gil-Escrig, P. P. Boix, M. Sessolo, S. Albrecht and H. J. Bolink, Sustainable Energy Fuels, 2018, 2, 2429–2434. \n105 C. Momblona, L. Gil-Escrig, E. Bandiello, E. M. Hutter, M. Sessolo, K. Lederer, J. Blochwitz-Nimoth and H. J. Bolink, Energy Environ. Sci., 2016, 9, 3456–3463. \n106 N. J. Jeon, H. Na, E. H. Jung, T. Y. Yang, Y. G. Lee, G. Kim, H. W. Shin, S. Il Seok, J. Lee and J. Seo, Nat. Energy, 2018, 3, 682–689. " + }, + { + "id": "10.1126_sciadv.aaw5484", + "DOI": "10.1126/sciadv.aaw5484", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.aaw5484", + "Relative Dir Path": "mds/10.1126_sciadv.aaw5484", + "Article Title": "Architecting highly hydratable polymer networks to tune the water state for solar water purification", + "Authors": "Zhou, XY; Zhao, F; Guo, YH; Rosenberger, B; Yu, GH", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Water purification by solar distillation is a promising technology to produce fresh water. However, solar vapor generation, is energy intensive, leading to a low water yield under natural sunlight. Therefore, developing new materials that can reduce the energy requirement of water vaporization and speed up solar water purification is highly desirable. Here, we introduce a highly hydratable light-absorbing hydrogel (h-LAH) consisting of polyvinyl alcohol and chitosan as the hydratable skeleton and polypyrrole as the light absorber, which can use less energy (<50% of bulk water) for water evaporation. We demonstrate that enhancing the hydrability of the h-LAH could change the water state and partially activate the water, hence facilitating water evaporation. The h-LAH raises the solar vapor generation to a record rate of similar to 3.6 kg m(-2) hour(-1) under 1 sun. The h-LAH-based solar still also exhibits long-termdurability and antifouling functionality toward complex ionic contaminullts.", + "Times Cited, WoS Core": 772, + "Times Cited, All Databases": 805, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000473798500083", + "Markdown": "# A P P L I E D S C I E N C E S A N D E N G I N E E R I N G \n\nXingyi Zhou1\\*, Fei Zhao1\\*, Youhong Guo1, Brian Rosenberger2, Guihua Yu1† \n\nWater purification by solar distillation is a promising technology to produce fresh water. However, solar vapor generation, is energy intensive, leading to a low water yield under natural sunlight. Therefore, developing new materials that can reduce the energy requirement of water vaporization and speed up solar water purification is highly desirable. Here, we introduce a highly hydratable light-absorbing hydrogel (h-LAH) consisting of polyvinyl alcohol and chitosan as the hydratable skeleton and polypyrrole as the light absorber, which can use less energy $(<50\\%$ of bulk water) for water evaporation. We demonstrate that enhancing the hydrability of the h-LAH could change the water state and partially activate the water, hence facilitating water evaporation. The h-LAH raises the solar vapor generation to a record rate of ${\\sim}3.6\\mathrm{kg}\\mathrm{m}^{-2}$ hour−1 under 1 sun. The h-LAH-based solar still also exhibits long-term durability and antifouling functionality toward complex ionic contaminants. \n\n# Architecting highly hydratable polymer networks to tune the water state for solar water purification \n\nCopyright $\\circledcirc$ 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\n# INTRODUCTION \n\nRapid, energy-efficient water purification methods are urgently required to address growing water scarcity $(1,2)$ . Solar distillation is a promising technique that uses renewable energy to power the removal of contaminants in water, delivering fresh water to alleviate the freshwater shortage (3, 4). However, solar vapor generation (SVG), the essential process of solar distillation to separate water and contaminants, is energy intensive. Developing materials with an adaptive structure that can efficiently convert solar irradiation to heat and boost water vaporization creates a foundation for solar water purification independent of solar concentrators, opening up opportunities for cost-effective freshwater production. In particular, capillary structures, including porous structure (5–7), directional channel array (8–10), and two-dimensional network $(l l)$ as the means to regulate water distribution, have recently been explored using broadband light absorbers such as plasmonic nanoparticles (8, 12–14), carbon materials $(5,6,15,16)$ , and semiconductor-based absorbers (17, 18). However, these designs exhibit a limited range of SVG rate (vapor yield, $\\leq1.6\\mathrm{kg}\\mathrm{m}^{-2}\\mathrm{hour}^{-1})$ under natural sunlight (solar flux, $\\leq1\\mathrm{~kW~m}^{-2}.$ ). Whereas this drawback is caused by the intrinsic energy demand of water vaporization, the hydrated solutes in water have a substantial impact on the phase change behaviors of water by varying the water state (19, 20). \n\nOwing to their tunable physicochemical properties, hydrogel materials consisting of highly hydratable polymer networks and swollen water molecules are conducive to applications in flexible electronics (21, 22), biomedical technology (23, 24), and environmental sensing (25, 26). The hydration of this polymer network opens up possibilities to achieve an intriguing water state distinct from that of bulk water (19, 27, 28). Here, we introduce a light-absorbing hydrogel with highly hydratable polymer networks (termed hydratable light-absorbing hydrogel or h-LAH), made by infiltrating polypyrrole (PPy) absorbers into a matrix consisting of polyvinyl alcohol (PVA) and chitosan. We provide fundamental insights into the links between the involved polymer-water interaction and the resultant variation of water phase change behavior and demonstrate that h-LAH could significantly reduce the energy demand of SVG. Because of the hydration effect, the polymer chains in hydrogels could capture nearby water molecules through strong interaction, such as hydrogen bonding, to form bound water (Fig. 1, deep blue area). In contrast, the water molecules that are separated from the polymer chains [termed as free water (FW)] exhibit identical properties with those in bulk water (Fig. 1, light blue area). There is an intermediate region (Fig. 1, yellow area) between bound water and FW, where the water molecules present relatively delicate interplay with polymer chains and adjacent water molecules. The intermediate water (IW) has been demonstrated as activated water that could be vaporized by less energy compared with bulk water (19, 20, 29, 30). On the basis of this design, the rate of 1-sun SVG could be increased up to $3.6\\mathrm{kg}\\mathrm{m}^{-2}\\mathrm{hour}^{-1}$ at an energy efficiency of ${\\sim}92\\%$ . The h-LAH–improved SVG enables highly efficient, scalable, and costeffective solar water purification of various soluble ionic contaminates with antifouling functionality, as well as long-term durability. \n\n# RESULT Preparation and characterization of h-LAH \n\nThe in situ cogelation method is used to construct the polymer network that consists of PVA and chitosan. The PPy was used as an additive endowing the h-LAH with a light-absorbing functionality (see section S1 for details). The as-prepared h-LAHs were black and flexible (Fig. 2A). The configuration of h-LAHs, such as the size and shape, depends on the mold used for gelation, indicating desirable scalability. Scanning electron microscopy (SEM) imaging reveals the cross-section morphology of the freeze-dried h-LAH (Fig. 2B). Pores with a diameter of several microns are uniformly distributed in the h-LAH, which is a typical structural feature, indicating homogeneous gelation throughout the resultant hydrogel. To analyze the chemical composition, we show the Fourier transform infrared (FTIR) spectra of pure PVA, PPy, chitosan, and the $\\mathbf{h}$ -LAH in Fig. 2C. In the spectrum of PVA (black curve), the peak at $1087~\\mathrm{{cm}^{-1}}$ represents the C—O stretching, which is a characteristic peak of PVA (31). The spectrum of PPy (red curve) shows the absorption signal at $1451\\mathrm{cm}^{-1}$ , corresponding to the $\\scriptstyle{\\mathrm{C}}={\\mathrm{C}}$ stretching in the pyrrole rings (32). The blue curve represents the spectrum of chitosan in which the characteristic peaks are located at 1626 and $1374\\mathrm{cm}^{-1}$ , corresponding to the amide peak of chitosan (31). All the characteristic peaks of PVA, PPy, and chitosan can be found in the spectrum of the h-LAH (purple curve), confirming the existence of PPy in the PVA and chitosan hybrid polymer network. \n\n![](images/c916879b12a61ab89e7a952865c58a6ec297444ddeffc0e561c238f76c00e5f0.jpg) \nFig. 1. Schematic illustration of SVG based on the h-LAH. The h-LAH is made by infiltrating PPy absorbers into a matrix consisting of PVA and chitosan. As PVA can play the role of surfactant, the PPy chains are dispersed uniformly in the cross-linked PVA and chitosan polymer network. Upon exposure to the solar irradiation, h-LAH can generate water vapor using solar energy. The floating h-LAH consists of the hydratable polymer network based on cross-linked PVA and chitosan, which is interpenetrated by the light-absorbing PPy. The containing water has three different water types—bound water, IW, and FW. Wherein, the IW can be effectively evaporated with significantly reduced energy demand. \n\n![](images/5e9448ba3e13200ae022e8668c1c417922906239b4556a9b738d8f8315f51301.jpg) \nFig. 2. Chemical and structural characterization of the h-LAH. (A) Photograph of as-prepared h-LAH sample. (B) SEM image of the micron-sized pores in the freezedried h-LAH. (C) FTIR spectra of PVA (black curve), PPy (red curve), chitosan (blue curve), and the h-LAH (purple curve). a.u., arbitrary units. (D) Dynamic mechanical analysis showing storage modulus $(G^{\\prime})$ and loss modulus $(G^{\\prime\\prime})$ of PVA/PPy hydrogel and the h-LAH. Photo credit: Xingyi Zhou, The University of Texas at Austin. \n\nAs viscoelastic materials, hydrogels show energy storage and energy dissipation characteristics. The corresponding storage modulus $\\left(G^{\\prime}\\right)$ and loss modulus $\\left(G^{\\prime\\prime}\\right)$ can be measured to reveal the structural difference of hydrogels (33). To confirm the cogelation of PVA and chitosan, we prepared a PVA/PPy hydrogel as the blank sample (i.e., control sample without chitosan). The higher $G^{\\prime}$ values compared with $G^{\\prime\\prime}$ values confirm the cross-linked polymeric skeleton of these hydrogels (Fig. 2D). The higher $G^{\\prime}$ value of the h-LAH compared with PVA/PPy indicates stronger mechanical strength due to the introduction of chitosan, while the higher $G^{\\prime\\prime}$ value reveals the steric hindrance of chitosan polymer chains (33). In addition, the comparison of $G^{\\prime}$ and $G^{\\prime\\prime}$ values between PVA/chitosan hydrogel and the h-LAH confirms that PPy is interpenetrated in the polymer network composed of PVA and chitosan (fig. S1). These above results demonstrate that the PPy is interpenetrated in the PVA/chitosan hybrid polymer network. \n\n# Tunable water state in the h-LAH \n\nAccording to the difference of intermolecular hydrogen bonding, including water/polymer bonding, weakened water/water bonding, and normal water/water bonding (Fig. 3A), the water in the hydrated polymer network has been classified into three types: FW (Fig. 3A, light blue color), IW (Fig. 3A, yellow color), and bound water (Fig. 3A, dark blue color), respectively. We analyze the Raman spectra in the region of O—H stretching to show the hydrogen bonding distinction of water molecules in the h-LAH (see details in section S2.3.1), revealing the water state in the h-LAH (Fig. 3B). The peaks at 3233 and $3401~\\mathrm{{\\bar{cm}}^{-1}}$ correspond to FW (Fig. 3B) with four hydrogen bonds (two protons and two lone electron pairs are involved in hydrogen bonding with adjacent water molecules), while the peaks at 3514 and $3630\\mathrm{cm}^{-\\mathrm{Y}}$ are associated with weakly hydrogen-bonded IW (Fig. 3B) (19). Hence, the stronger IW peaks compared with FW peaks indicate a higher proportion of IW in the h-LAH. \n\nGiven that the water in each state shows characteristic phase change behaviors (34), such as freezing and melting, the involved energy transfer could be monitored to further confirm that the h-LAHs induced the differentiation of water state. To quantitatively describe the water content (i.e., hydration level) of h-LAHs, we first define a water fraction $(W_{\\mathrm{H_{2}O}})$ as \n\n$$\nW_{\\mathrm{H_{2}O}}=W/W_{s}\n$$ \n\nwhere the $W$ and $W_{s}$ are the weight of water in the h-LAH and the saturated water content of a fully swollen h-LAH, respectively. We use the differential scanning calorimetry (DSC) to reveal the phase change of water (Fig. 3C). The h-LAH with a low $W_{\\mathrm{H_{2}O}}$ of $1\\%$ (i.e., almost dried sample) presents a straight line without signals of endothermic process (black curve). It has been demonstrated that bound water, which strongly interacts with hydrophilic polymer chains, is nonfreezable water, while the IW and FW are freezable (34). Therefore, the water molecules are captured by the polymer network of the h-LAH, forming bound water, when the $W_{\\mathrm{H_{2}O}}$ is $1\\%$ . In contrast, there are two peaks located at $0^{\\circ}$ and ${\\sim}5^{\\circ}\\mathrm{C}$ corresponding to the melting of IW and FW, respectively, that could be observed in the fully hydrated h-LAH (i.e., $W_{\\mathrm{H_{2}O}}$ is $100\\%$ ; green curve). In addition, the measured melting point of FW is shifted to a higher temperature with the increase in $W_{\\mathrm{H_{2}O}}$ (red, blue, and green curves), which could be attributed to the postponed heating of samples induced by endothermic melting. In contrast, the steep signal of IW (purple curve) is independent of the water content of the h-LAH, indicating that the generation of IW relies on the hydratable polymer network. It should be mentioned that the melting points of IW and FW are close because of the almost similar melting enthalpy of ices with different crystal structures (35). \n\nTo obtain a tailored water state that is capable of providing highproportioned IW, we constructed polymer networks consisting of PVA and chitosan with a different proportion. Wherein, the h-LAH samples with various PVA/chitosan weight ratios from 1:0 (i.e., no chitosan additive), 1:0.05, 1:0.1, and 1:0.175 to 1:0.25 are noted as h-LAH1 to h-LAH5, respectively. Because of the similar carbon/oxygen ratio (i.e., molar ratio of hydrophobic and hydrophilic groups) of PVA and chitosan (Fig. 4A), the obtained polymer networks in h-LAHs show a similar ability to capture water molecules to form bound water (see details in fig. S2, A and B). The amount of IW highly depends on the hydrability of polymer networks, which presents the ability of polymer networks to swell water and can be indicated by the saturated water content of h-LAHs. The saturated water content $(Q_{s})$ of $\\mathrm{\\Deltah}$ -LAHs is represented by \n\n$$\nQ_{s}=W/W_{\\mathrm{d}}\n$$ \n\nwhere $W$ and $W_{\\mathrm{d}}$ are the weights of the water in the fully swollen sample and the corresponding dried aerogel sample, respectively. The $Q_{s}$ of h-LAHs rises with the proportion of chitosan (Fig. 4B), indicating an increased hydrability. This phenomenon could be attributed to the presence of highly hydratable $\\ensuremath{-}\\ensuremath{\\mathrm{N}}\\ensuremath{\\mathrm{H}_{2}}$ groups on chitosan chains (36). \n\nTo systematically assess the influence of the hydrability of polymer networks on the water state, we calculated the ratio of IW and FW in fully swollen h-LAHs. According to the DSC data (fig. S2, C and D), the ratios of IW to FW in h-LAH1 to h-LAH5 are 0.758, 0.933, 1.124, 1.284, and 1.339, respectively, indicating that h-LAH with a higher hydrability favors the formation of IW (Fig. 4C). These results are consistent with the estimation derived by Raman spectra (fig. S3, A to D). To evaluate the benefits of IW to the SVG, we carefully measured the equivalent water vaporization enthalpy through a comparison of $\\mathbf{h}$ -LAH1 to $\\mathbf{h}$ -LAH5 and bulk water regarding the spontaneous evaporation (see details in fig. S3E). The equivalent water vaporization enthalpy $(E_{\\mathrm{equ}})$ of water in the h-LAHs can be estimated by assuming that the water vaporization is powered by identical energy input $(U_{\\mathrm{in}})$ , which has \n\n![](images/61c7810ed2f1e25bf438b31668221cd76f1d12f0d2567f777cc10a9597eec582.jpg) \nFig. 3. Water state in the h-LAH. (A) Schematic of the water in the hydratable polymer network of the h-LAH, showing water/polymer bonding, weakened water/ water bonding, and normal water/water bonding. (B) Raman spectra showing the fitting peaks representing IW and FW in the h-LAH. (C) Differential scanning calorimetry (DSC) curves of the h-LAH with different water fraction (i.e., swollen level, $100\\%$ refers to the fully swollen state). \n\n![](images/4aa39a4d62b6db8f146a801a3dc364f1514e5ca3a839ec2d7485f5e5ebd47d6d.jpg) \nFig. 4. Tunable water state and water vaporization enthalpy of the h-LAHs. (A) Schematic illustration of PVA and chitosan structure. (B) The saturated water content of h-LAH samples, where the h-LAHs with PVA/chitosan weight ratios of 1:0 (i.e., no chitosan additive), 1:0.05, 1:0.1, 1:0.175, and 1:0.25 are noted as h-LAH1 to h-LAH5, respectively. (C) The ratio of IW to FW in h-LAHs. (D) The equivalent water vaporization enthalpy of bulk water and water in h-LAH1 to h-LAH5. \n\n$$\nE_{\\mathrm{equ}}=E_{0}m_{0}/m_{\\mathrm{g}}\n$$ \n\nwhere $E_{0}$ and $m_{0}$ are the vaporization enthalpy and mass change of bulk water, respectively, and $m_{\\mathrm{g}}$ is the mass change of these $\\mathrm{\\Deltah}$ -LAHs. As shown in Fig. 4D, the obtained equivalent water vaporization enthalpy gradually decreases from $\\mathrm{\\Deltah}$ -LAH1 to $\\mathrm{\\Deltah}$ -LAH5, suggesting that the IW can reduce the overall energy demand of water evaporation (also see fig. S3F). To systematically investigate this effect, we involved hydrogels that consist of less hydratable polymer networks (see details in fig. S3, G to I). \n\n# DISCUSSION \n\n# Solar water purification based on the h-LAH \n\nThe SVG performance of h-LAHs upon pure water is represented by the mass change of water under 1-sun solar irradiation over time (Fig. 5A). Note that all the h-LAHs are of optimized light absorption (fig. S4A) and thermal management (Fig. 4, B to F) and the experimental data involved were calibrated with dark evaporation data. It is clear that the SVG rate based on the $\\mathrm{\\Deltah}$ -LAH is faster than that of pure water. On the basis of the optimized hydrophilic polymer/water ratio (fig. S5, A and B), PPy absorber concentration (fig. S5, C and D), and cross-linking density (fig. S5, E and F), the h-LAH4 exhibited a high vapor generation rate of ${\\sim}3.6\\mathrm{kg}\\mathrm{m}^{-2}$ hour−1 with an energy efficiency of ${\\sim}92\\%$ among all samples (fig. S5, G and H). The evaporation rate and energy efficiency gradually increased from h-LAH1 to h-LAH4 due to decreasing equivalent vaporization enthalpy. Despite the low water vaporization enthalpy, the h-LAH5 exhibits high water content, hindering the effective energy utilization and restricting the SVG rate (see detailed discussion in section S2.4.2), which shows the significance of balancing factors regarding water content and state in design of hydratable polymer networks for SVG. \n\nWe used a real seawater sample (from the Gulf of Mexico) to show the solar distillation based on the h-LAH and evaluated the quality of collected water using inductively coupled plasma mass spectroscopy (ICP-MS). As shown in Fig. 5B, the concentrations of four primary ions $(\\mathrm{Na}^{+},\\mathrm{Mg}^{2+}$ , $\\operatorname{K}^{+}$ , and ${\\mathrm{Ca}}^{2+}$ ) in seawater are significantly reduced by ${\\sim}2$ to 3 orders after purification and were below the values obtained through membrane- and distillation-based seawater desalination techniques (13). To prove the durability of the h-LAH as an evaporator, we tested the SVG rate under continuous 1-sun irradiation over 96 hours (Fig. 5C). The stable evaporation rate shows that the h-LAH presents a promising performance for practical long-term solar desalination with antifouling functionality (fig. S6A). In addition, the salinities of three brine samples (NaCl solution) with representative salinities of the Baltic \n\n![](images/48e5db162f888dd4af6df40d7dc4f4ccc875427ccb577fafdf33f79f0fb66752.jpg) \nFig. 5. Solar water purification based on the h-LAH. (A) The mass loss of pure water for different h-LAH samples under 1 sun compared with the bare pure water as blank control experiment. (B) The primary ions in a seawater sample before and after desalination. (C) The duration test of the h-LAH4 based on continuous solar desalination for 96 hours. Insets: The mass loss of water with the h-LAH4 as a solar evaporator at the 1st hour and 96th hour. (D to G) Evaluation of corrosion resistance (D) in acid or alkali solutions. (E and F) Comparison of the pH of the solution before and after purification. (G) Purification of heavy metal polluted water. Inset: The concentration of heavy metal ions in the solution before and after purification. (H) Ion residual in purified water compared with several competitive purification techniques designed for a specific ion. \n\nSea [lowest salinity, 0.8 weight $\\%$ (wt $\\%$ )], World Sea (average salinity, $3.5\\mathrm{wt}\\%$ ) and Dead Sea (highest salinity, 10 wt $\\%$ ) were all significantly decreased (about four orders of magnitude) after desalination, which are about two orders below drinking water standards defined by the World Health Organization (1 per mil; fig. S6, B to E) (13). These results demonstrate effective solar desalination based on the h-LAH. \n\nFigure 5D shows the steady evaporation rate of the $\\mathrm{\\Deltah}$ -LAH under strong acid (1 M $\\mathrm{H}_{2}\\mathrm{SO}_{4},$ ) and alkali $\\mathrm{{(1\\M\\NaOH)}}$ ) solutions, and the $\\mathsf{p H}$ value of the purified water is close to 7 (Fig. 5, E and F). Moreover, we also conducted the solar purification of water containing mixed heavy metal ions with four representative ions, including $\\mathrm{Ni}^{2+}$ , ${\\mathrm{Cu}}^{2+}$ , \n\n$Z\\mathrm{n}^{2+}$ , and $\\mathrm{Pt}^{2+}$ , which are the most common heavy metal ions with relatively high concentrations in industrial waste water, based on the h-LAH. As shown in Fig. 5G, the h-LAH exhibits a stable evaporation rate, and the concentrations of heavy metal ions dropped below $1~\\mathrm{mg}\\mathrm{liter}^{-1}$ after purification (Fig. 5G, inset), which are comparable with those of competitive purification techniques designed for the specific ion (Fig. 5H) (37–39). Along with the unique advantages of h-LAH–based solar water purification compared with other methods in terms of core requirements of practical application, the h-LAH presents a remarkable potential for the practical purification of industrial sewage containing multiple ionic contaminants (fig. S7). \n\n# CONCLUSION \n\nIn conclusion, we demonstrated the regulation of water state in hydrogels via architecting the hydratable polymer network, as a new effective means beyond the previous structural designs to endow materials with stronger ability to accelerate solar water evaporation. The hydrophilic functional groups, such as hydroxyl and amino groups, on the polymer network present strong interaction with water molecules. Hence, the hydrability of the polymer network determines the proportion of IW, thus influencing the overall energy demand of vapor generation. The morphology of the polymer network (i.e., pore size), which depends on the cross-linking density, significantly influences the water diffusion within the hydrogel, since those pores serve as water pathways when the water diffuses to the evaporating surface. Note that the “pores” here are not the microscopic scale pores but the molecular level meshes in the polymer network. It is expected that these fundamental design principles regarding molecular engineering will spur the development of nextgeneration photothermal materials capable of managing the phase transition of water and associated energy conversions. \n\nWe also demonstrated highly efficient solar water purification enabled by the light-absorbing hydrogels with hydratable polymer networks (h-LAH) under 1-sun irradiation. The h-LAH showed an ultrafast water evaporation rate up to ${\\sim}3.6\\mathrm{kg}\\mathrm{m}^{-2}\\mathrm{hour}^{-1}$ and effective water purification removal of over $99.9\\%$ of ionic contaminants. The promising performance of h-LAH shows great potential as an antifouling, long-term stable, and cost-effective vapor generator for solar water purification, and the introduction of IW-facilitated SVG provides a new approach for addressing growing challenges at the energy-water nexus. \n\n# MATERIALS AND METHODS \n\n# Chemicals and materials \n\nChemicals including PVA with an average molecular weight of 15,000, hydrochloric acid $(37\\%)$ , pyrrole, glutaraldehyde $50\\%$ aqueous solution), poly(ethylene glycol) diacrylate [number-average molecular weight $(M_{\\mathrm{n}}),{\\sim}700]$ , chitosan with low molecular weight, $^{2,2^{\\prime}}$ -azobis(2- methylpropionitrile), and ammonium persulfate were purchased from Sigma-Aldrich. All the materials were used without further purification. \n\n# Preparation of h-LAHs \n\nIn a typical synthesis, PPy $(100\\upmu\\mathrm{l},$ 10 wt $\\%$ ) solution and glutaraldehyde $[12.5\\upmu]_{:}$ , 50 wt $\\%$ in deionized (DI) water] were added to $\\mathrm{1ml}$ of PVA/ chitosan precursor solution. The gelation was carried out for 24 hours. The obtained gel was immersed into DI water overnight to obtain the pure hydrogel. The purified hydrogel was frozen by liquid nitrogen and then thawed in DI water at a temperature of $30^{\\circ}\\mathrm{C}$ . The freezing-thawing process was repeated 10 times. Last, the obtained hydrogel sample was fully swollen for testing. \n\n# SVG experiments \n\nThe water evaporation performance experiments were conducted using a solar simulator (M-LS Rev B, Abet Tech), outputting a simulated solar flux of 1 sun. The solar flux was measured using a thermopile $(818\\mathrm{SL},$ Newport) connected to a power meter (1916-R, Newport). h-LAHs with a thickness of ca. $0.5\\mathrm{cm}$ were floated on pure water (or unpurified for purification tests) in a beaker with a solar flux of 1 sun. The mass of the water loss was measured by a lab balance with a $0.1\\mathrm{-}\\upmu\\mathrm{g}$ resolution and calibrated to weights heavier than the total weight of the setup. All evaporation rates were measured after a stabilization under 1 sun for $30~\\mathrm{min}$ . \n\n# Characterizations \n\nThe SEM images were implemented by SEM (S5500, Hitachi) to observe the morphology and microstructure of the samples. The h-LAHs were freeze-dried for 24 hours before observation. The FTIR spectra were conducted by the FTIR spectrometer (Infinity Gold FTIR, Thermo Mattson) equipped with a liquid nitrogen cooled narrow-band mercury cadmium telluride detector using an attenuated total reflection cell equipped with a Ge crystal. The mechanical properties of h-LAHs were performed by rheological experiments (AR2000EX, TA Instruments) using a parallel plate on a Peltier plate in the frequency sweep mode. Absorption spectra and reflectance were conducted using a UV-VisNIR spectrometer (Cary 5000) with an integrating sphere unit and automation of reflectance measurement unit, and the measurements were corrected by baseline/blank correction with dark correction. The Raman spectra were measured via spectrometer (WITec alpha300). The excitation radiation for the Raman emission was produced using a Yttrium aluminium garnet laser that had a single-mode operation at $532\\mathrm{nm}$ . The evaporation and melting behavior of h-LAHs were observed by a differential scanning calorimeter (METTLER TOLEDO DSC 3). The temperature and melting enthalpy were calibrated by indium. The concentration of ions was tracked by ICP-MS (Agilent $7500\\mathrm{ce})$ with dilutions in $2\\%\\mathrm{HNO}_{3}$ to make the loaded ion concentration lower than 10 parts per million. \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/5/6/eaaw5484/DC1 \nSection S1. Supplementary methods \nSection S1.1. Fabrication procedure \nSection S1.1.1. Preparation of PPy absorbers \nSection S1.1.2. Preparation of PVA and chitosan solution \nSection S1.1.3. Preparation of PVA/chitosan hydrogel \nSection S1.1.4. Preparation of PEG/PPy hydrogel (l-LAH1, less hydratable \nlight-absorbing hydrogel) \nSection S1.1.5. Preparation of PEG/PVA/PPy hydrogel (l-LAH2) \nSection S1.2. Melting behavior of h-LAHs by DSC measurement \nSection S2. Supplementary figures \nSection S2.1. Investigation of PPy penetrated in the PVA and chitosan polymer network Section S2.2. Investigation of water state in h-LAHs \nSection S2.2.1. DSC measurement of bound water content in h-LAHs \nSection S2.2.2. Investigation of water state in fully swollen h-LAHs \nSection S2.3. Polymer network enabled activation of water \nSection S2.3.1. Study of water-polymer interaction in h-LAHs \nSection S2.3.2. Observation of vapor generation under dark conditions \nSection S2.3.3. DSC measurement of evaporation enthalpy \nSection S2.3.4. Investigation of water state and SVG rate of less hydratable polymer networks Section S2.4. Investigation of photothermal behaviors of h-LAHs \nSection S2.4.1. Evaluation of light absorption of h-LAHs \nSection S2.4.2. Investigation of photothermal behavior of h-LAHs \nSection S2.5. Variables influencing the SVG of h-LAHs \nSection S2.5.1. Ratio of hydrophilic polymers (PVA and chitosan)/water \nSection S2.5.2. Ratio of PPy/hydrophilic polymer \nSection S2.5.3. Cross-linker density of h-LAHs \nSection S2.5.4. Evaluation of 1-sun vapor generation performance of h-LAHs \nSection S2.6. Performance evaluation of h-LAHs in salt solutions \nSection S2.6.1. Evaluation of the antifouling functionality of the h-LAH \nSection S2.6.2. Evaluation of purified simulating seawater based on the h-LAH \nSection S2.7. Comparison of techniques for purification of heavy metal ions \nFig. S1. Dynamic mechanical analysis of storage modulus (G′) and loss modulus $(G^{\\prime\\prime})$ of PVA/ chitosan hydrogel and the h-LAH4. \nFig. S2. DSC analysis of different samples. \nFig. S3. Investigation of water-polymer interaction in h-LAHs. \nFig. S4. Photothermal behaviors of h-LAHs. \nFig. S5. Factors influencing the SVG of h-LAHs. \nFig. S6. Performance evaluation of h-LAHs in salt solutions. Fig. S7. Qualitative comparison of different techniques in terms of core requirements of practical purification of heavy metal ions. \nTable S1. Bound water content of h-LAHs from the DSC measurement. \nTable S2. The fraction of free, intermediate, and bound water in h-LAHs. \nTable S3. Comparison of evaporation enthalpy from DSC measurement and dark experiment. References (40–46) \n\n# REFERENCES AND NOTES \n\n1. M. Elimelech, W. A. Phillip, The future of seawater desalination: Energy, technology, and the environment. Science 333, 712–717 (2011). \n2. C. J. Vörösmarty, P. Green, J. Salisbury, R. B. Lammers, Global water resources: Vulnerability from climate change and population growth. Science 289, 284–288 (2000). \n3. M. A. Shannon, P. W. Bohn, M. Elimelech, J. G. Georgiadis, B. J. Mariñas, A. M. Mayes, Science and technology for water purification in the coming decades. Nature 452, 301–310 (2008). \n4. H. M. Qiblawey, F. Banat, Solar thermal desalination technologies. Desalination 220, 633–644 (2008). \n5. H. Ren, M. Tang, B. Guan, K. Wang, J. Yang, F. Wang, M. Wang, J. Shan, Z. Chen, D. Wei, H. Peng, Z. Liu, Hierarchical graphene foam for efficient omnidirectional solar–thermal energy conversion. Adv. Mater. 29, 1702590 (2017). \n6. Y. Ito, Y. Tanabe, J. Han, T. Fujita, K. Tanigaki, M. Chen, Multifunctional porous graphene for high-efficiency steam generation by heat Localization. Adv. Mater. 27, 4302–4307 (2015). \n7. H. Ghasemi, G. Ni, A. M. Marconnet, J. Loomis, S. Yerci, N. Miljkovic, G. Chen, Solar steam generation by heat localization. Nat. Commun. 5, 4449 (2014). \n8. K. Bae, G. Kang, S. K. Cho, W. Park, K. Kim, W. J. Padilla, Flexible thin-film black gold membranes with ultrabroadband plasmonic nanofocusing for efficient solar vapour generation. Nat. Commun. 6, 10103 (2015). \n9. N. Xu, X. Hu, W. Xu, X. Li, L. Zhou, S. Zhu, J. Zhu, Mushrooms as efficient solar steamgeneration devices. Adv. Mater. 29, 1606762 (2017). \n10. M. Zhu, Y. Li, G. Chen, F. Jiang, Z. Yang, X. Luo, Y. Wang, S. D. Lacey, J. Dai, C. Wang, C. Jia, J. Wan, Y. Yao, A. Gong, B. Yang, Z. Yu, S. Das, L. Hu, Tree-inspired design for high-efficiency water extraction. Adv. Mater. 29, 1704107 (2017). \n11. X. Li, W. Xu, M. Tang, L. Zhou, B. Zhu, S. Zhu, J. Zhu, Graphene oxide-based efficient and scalable solar desalination under one sun with a confined 2D water path. Proc. Natl. Acad. Sci. U.S.A. 113, 13953–13958 (2016). \n12. O. Neumann, C. Feronti, A. D. Neumann, A. Dong, K. Schell, B. Lu, E. Kim, M. Quinn, S. Thompson, N. Grady, P. Nordlander, M. Oden, N. J. Halas, Compact solar autoclave based on steam generation using broadband light-harvesting nanoparticles. Proc. Natl. Acad. Sci. U.S.A. 110, 11677–11681 (2013). \n13. L. Zhou, Y. Tan, J. Wang, W. Xu, Y. Yuan, W. Cai, S. Zhu, J. Zhu, 3D self-assembly of aluminium nanoparticles for plasmon-enhanced solar desalination. Nat. Photonics 10, 393–398 (2016). \n14. M. S. Zielinski, J.-W. Choi, T. La Grange, M. Modestino, S. M. H. Hashemi, Y. Pu, S. Birkhold, J. A. Hubbell, D. Psaltis, Hollow mesoporous plasmonic nanoshells for enhanced solar vapor generation. Nano Lett. 16, 2159–2167 (2016). \n15. P. Yang, K. Liu, Q. Chen, J. Li, J. Duan, G. Xue, Z. Xu, W. Xie, J. Zhou, Solar-driven simultaneous steam production and electricity generation from salinity. Energy Environ. Sci. 10, 1923–1927 (2017). \n16. X. Yang, Y. Yang, L. Fu, M. Zou, Z. Li, A. Cao, Q. Yuan, An ultrathin flexible 2D membrane based on single-walled nanotube– ${\\cdot}M\\circ{\\mathsf{S}}_{2}$ hybrid film for high-performance solar steam generation. Adv. Funct. Mater. 28, 1704505 (2018). \n17. L. Zhang, B. Tang, J. Wu, R. Li, P. Wang, Hydrophobic light-to-heat conversion membranes with self-healing ability for interfacial solar heating. Adv. Mater. 27, 4889–4894 (2015). \n18. J. Wang, Y. Li, L. Deng, N. Wei, Y. Weng, S. Dong, D. Qi, J. Qiu, X. Chen, T. Wu, High-performance photothermal conversion of narrow-bandgap $\\bar{\\mathsf{I i}}_{2}\\mathsf{O}_{3}$ Nanoparticles. Adv. Mater. 29, 1603730 (2017). \n19. Y. Sekine, T. Ikeda-Fukazawa, Structural changes of water in a hydrogel during dehydration. J. Chem. Phys. 130, 034501 (2009). \n20. K. Kudo, J. Ishida, G. Syuu, Y. Sekine, T. Ikeda-Fukazawa, Structural changes of water in poly(vinyl alcohol) hydrogel during dehydration. J. Chem. Phys. 140, 044909 (2014). \n21. Y. Xu, Z. Lin, X. Huang, Y. Liu, Y. Huang, X. Duan, Flexible solid-state supercapacitors based on three-dimensional graphene hydrogel films. ACS Nano 7, 4042–4049 (2013). \n22. L. Pan, A. Chortos, G. Yu, Y. Wang, S. Isaacson, R. Allen, Y. Shi, R. Dauskardt, Z. Bao, An ultra-sensitive resistive pressure sensor based on hollow-sphere microstructure induced elasticity in conducting polymer film. Nat. Commun. 5, 3002 (2014). \n23. A. S. Hoffman, Hydrogels for biomedical applications. Adv. Drug Deliv. Rev. 64, 18–23 (2012). \n24. Y. S. Zhang, A. Khademhosseini, Advances in engineering hydrogels. Science 356, eaaf3627 (2017). \n25. Y. Qiu, K. Park, Environment-sensitive hydrogels for drug delivery. Adv. Drug Deliv. Rev. 53, 321–339 (2017). \n26. T. Miyata, N. Asami, T. Uragami, A reversibly antigen-responsive hydrogel. Nature 399, 766–769 (1999). \n27. H. Hatakeyama, T. Hatakeyama, Interaction between water and hydrophilic polymers. Thermochim. Acta 308, 3–22 (1998). \n28. B. Potkonjak, J. Jovanović, B. Stanković, S. Ostojić, B. Adnadjević, Comparative analyses on isothermal kinetics of water evaporation and hydrogel dehydration by a novel nucleation kinetics model. Chem. Eng. Res. Des. 100, 323–330 (2015). \n29. F. Zhao, X. Zhou, Y. Shi, X. Qian, M. Alexander, X. Zhao, S. Mendez, R. Yang, L. Qu, G. Yu, Highly efficient solar vapour generation via hierarchically nanostructured gels. Nat. Nanotechnol. 13, 489–495 (2018). \n30. X. Zhou, F. Zhao, Y. Guo, Y. Zhang, G. Yu, A hydrogel-based antifouling solar evaporator for highly efficient water desalination. Energy Environ. Sci. 11, 1985–1992 (2018). \n31. L. L. S. Dias, H. S. Mansur, C. L. Donnici, M. M. Pereira, Synthesis and characterization of chitosan-polyvinyl alcohol-bioactive glass hybrid membranes. Biomatter 1, 114–119 (2011). \n32. Y. Shi, C. Ma, L. Peng, G. Yu, Conductive “smart” hybrid hydrogels with PNIPAM and nanostructured conductive polymers. Adv. Funct. Mater. 25, 1219–1225 (2015). \n33. E. Parparita, C. N. Cheaburu, C. Vasile, Morphological, thermal and rheological characterization of polyvinyl alcohol/chitosan blends. Cellul. Chem. Technol. 46, 571–581 (2012). \n34. T. Nakaoki, H. Yamashita, Bound states of water in poly(vinyl alcohol) hydrogel prepared by repeated freezing and melting method. J. Mol. Struct. 875, 282–287 (2008). \n35. Y. Hirata, Y. Miura, T. Nakagawa, Oxygen permeability and the state of water in Nafion membranes with alkali metal and amino sugar counterions. J. Membr. Sci. 163, 357–366 (1999). \n36. A. Bernkop-Schnürch, C. Paikl, C. Valenta, Novel bioadhesive chitosan-EDTA conjugate protects leucine enkephalin from degradation by aminopeptidase N. Pharm. Res. 14, 917–922 (1997). \n37. A. E. Burakov, E. V. Galunin, I. V. Burakova, A. E. Kucherova, S. Agarwal, A. G. Tkachev, V. K. Gupta, Adsorption of heavy metals on conventional and nanostructured materials for wastewater treatment purposes: A review. Ecotoxicol. Environ. Saf. 148, 702–712 (2018). \n38. F. Fu, Q. Wang, Removal of heavy metal ions from wastewaters: A review. J. Environ. Manage. 92, 407–418 (2011). \n39. S. Babel, T. A. Kurniawan, Low-cost adsorbents for heavy metals uptake from contaminated water: A review. J. Hazard. Mater. 97, 219–243 (2003). \n40. M. Okumura, L. I. Yeh, J. D. Myers, Y. T. Lee, Infrared spectra of the solvated hydronium ion: Vibrational predissociation spectroscopy of mass-selected ${\\mathsf{H}}_{3}{\\mathsf{O}}^{+}$ . cntdot $({\\mathsf{H}}_{2}{\\mathsf{O}})_{\\mathsf{n}}$ . cntdot $(H_{2})_{\\mathsf{m}}$ . J. Phys. Chem. 94, 3416–3427 (1990). \n41. J.-C. Jiang, Y.-S. Wang, H.-C. Chang, S. H. Lin, Y. T. Lee, G. Niedner-Schattteburg, H.-C. Chang, Infrared spectra of ${\\mathsf{H}}^{+}({\\mathsf{H}}_{2}{\\mathsf{O}})_{5-8}$ clusters: Evidence for symmetric proton hydration. J. Am. Chem. Soc. 122, 1398–1410 (2000). \n42. M. Miyazaki, A. Fujii, T. Ebata, N. Mikami, Infrared spectroscopic evidence for protonated water clusters forming nanoscale cages. Science 304, 1134–1137 (2004). \n43. M. V. Kirov, G. S. Fanourgakis, S. S. Xantheas, Identifying the most stable networks in polyhedral water clusters. Chem. Phys. Lett. 461, 180–188 (2008). \n44. W. B. Monosmith, G. E. Walrafen, Temperature dependence of the Raman OH-stretching overtone from liquid water. J. Chem. Phys. 81, 669–674 (1984). \n45. N. von Solms, K. Y. Koo, Y. C. Chiew, Mixing rules for binary Lennard–Jones chains: Theory and Monte Carlo simulation. Fluid Phase Equilib. 180, 71–85 (2001). \n46. F. Edition, Guidelines for drinking-water quality. WHO Chron. 38, 104–108 (2011). \n\n# Acknowledgments \n\nFunding: G.Y. acknowledges the financial support from the Lockheed Martin Corp., Sloan Research Fellowship, and Camille-Dreyfus Teacher-Scholar Award. Author contributions: G.Y. supervised the project. X.Z., F.Z., and G.Y. conceived the idea and cowrote the manuscript. X.Z. and F.Z. performed the materials fabrication, characterization, and carried out the data analysis. Y.G. assisted in the experimental work and data analysis. B.R. provided technical advice and helped edit the manuscript. All authors discussed the results and commented on the manuscript. Competing interests: X.Z., F.Z., and G.Y. are inventors on a provisional U.S. patent application related to this work (no. 15/941,080, filed 30 March 2018). The other authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 4 January 2019 \nAccepted 17 May 2019 \nPublished 28 June 2019 \n10.1126/sciadv.aaw5484 \n\nCitation: X. Zhou, F. Zhao, Y. Guo, B. Rosenberger, G. Yu, Architecting highly hydratable polymer networks to tune the water state for solar water purification. Sci. Adv. 5, eaaw5484 (2019). \n\n# ScienceAdvances \n\n# Architecting highly hydratable polymer networks to tune the water state for solar water purification \n\nXingyi Zhou, Fei Zhao, Youhong Guo, Brian Rosenberger and Guihua Yu \n\nSci Adv 5 (6), eaaw5484. DOI: 10.1126/sciadv.aaw5484 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 46 articles, 6 of which you can access for free http://advances.sciencemag.org/content/5/6/eaaw5484#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41929-019-0325-4", + "DOI": "10.1038/s41929-019-0325-4", + "DOI Link": "http://dx.doi.org/10.1038/s41929-019-0325-4", + "Relative Dir Path": "mds/10.1038_s41929-019-0325-4", + "Article Title": "Iron-facilitated dynamic active-site generation on spinel CoAl2O4 with self-termination of surface reconstruction for water oxidation", + "Authors": "Wu, TZ; Sun, SN; Song, JJ; Xi, SB; Du, YH; Chen, B; Sasangka, WA; Liao, HB; Gan, CL; Scherer, GG; Zeng, L; Wang, HJ; Li, H; Grimaud, A; Xu, ZJ", + "Source Title": "NATURE CATALYSIS", + "Abstract": "The development of efficient and low-cost electrocatalysts for the oxygen evolution reaction (OER) is critical for improving the efficiency of water electrolysis. Here, we report a strategy using Fe substitution to enable the inactive spinel CoAl2O4 to become highly active and superior to the benchmark IrO2. The Fe substitution is revealed to facilitate surface reconstruction into active Co oxyhydroxides under OER conditions. It also activates deprotonation on the reconstructed oxyhydroxide to induce negatively charged oxygen as an active site, thus significantly enhancing the OER activity of CoAl2O4. Furthermore, it promotes the pre-oxidation of Co and introduces great structural flexibility due to the uplift of the oxygen 2p levels. This results in the accumulation of surface oxygen vacancies along with lattice oxygen oxidation that terminates as Al3+ leaches, preventing further reconstruction. We showcase a promising way to achieve tunable electrochemical reconstruction by optimizing the electronic structure for low-cost and robust spinel oxide OER catalysts.", + "Times Cited, WoS Core": 797, + "Times Cited, All Databases": 817, + "Publication Year": 2019, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000486144700008", + "Markdown": "# Iron-facilitated dynamic active-site generation on spinel ${\\mathsf{C o A l}}_{2}{\\mathsf{O}}_{4}$ with self-termination of surface reconstruction for water oxidation \n\nTianze $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{1,2,13}$ , Shengnan Sun1,2,13, Jiajia Song1,13, Shibo $x_{i}=$ , Yonghua Du $\\textcircled{10}3$ , Bo Chen1, Wardhana Aji Sasangka4, Hanbin Liao1,5, Chee Lip Gan1,4, Günther G. Scherer6,7, Lin Zeng $\\textcircled{1}:$ 8, Haijiang Wang8, Hui $L i^{9}$ , Alexis Grimaud $\\mathbb{P}^{10,11\\star}$ and Zhichuan J. Xu   1,2,12\\* \n\nThe development of efficient and low-cost electrocatalysts for the oxygen evolution reaction (OER) is critical for improving the efficiency of water electrolysis. Here, we report a strategy using Fe substitution to enable the inactive spinel $\\mathbf{CoAl}_{2}\\mathbf{O}_{4}$ to become highly active and superior to the benchmark ${\\mathbf{IrO}}_{2}.$ The Fe substitution is revealed to facilitate surface reconstruction into active Co oxyhydroxides under OER conditions. It also activates deprotonation on the reconstructed oxyhydroxide to induce negatively charged oxygen as an active site, thus significantly enhancing the OER activity of ${\\tt c o A l}_{2}{\\tt O}_{4}$ . Furthermore, it promotes the pre-oxidation of Co and introduces great structural flexibility due to the uplift of the oxygen $2p$ levels. This results in the accumulation of surface oxygen vacancies along with lattice oxygen oxidation that terminates as $\\pmb{\\big\\wedge}\\pmb{\\big|}^{3+}$ leaches, preventing further reconstruction. We showcase a promising way to achieve tunable electrochemical reconstruction by optimizing the electronic structure for low-cost and robust spinel oxide OER catalysts. \n\nydrogen has long been proposed as an energy carrier for a sustainable and clean energy infrastructure. However, such an infrastructure has not yet been realized, even though many years have passed since it was first discussed. Reasons for this include the low efficiency and high material cost of water electrolysis—a method used to sustainably produce hydrogen fuel from water using the electrical energy generated by sustainable resources such as solar panels1. The low energy efficiency of water electrolysis is mainly caused by sluggish reaction kinetics at the anode2, where water is oxidized and the oxygen evolution reaction (OER) occurs. The benchmark anode electrocatalysts are noble metal-based oxides such as $\\mathrm{IrO}_{2}$ and $\\mathrm{RuO}_{2}$ (refs. 3,4); however, the use of these oxides aggravates the cost problems for water electrolysis. In recent years, great efforts have been made to explore firstrow $3d$ transition metal oxides as low-cost alternatives for $\\mathrm{OER}^{1,5}$ . One important advantage is that the active sites are oxyhydroxides generated under operando conditions6–10. In particular, many Co-based oxides have been reported to undergo surface self-reconstruction of Co sites to $\\operatorname{Co}\\(\\operatorname{III})$ oxyhydroxides with the di- $\\upmu$ -oxo bridged Co–Co sites11,12, offering higher activity6,9. However, how to properly facilitate this surface reconstruction has remained elusive. Furthermore, surface reconstruction should be controlled to avoid compromising all the bulk of the oxide catalyst, which serves as the template for creating the highly active surface. Thus, \n\nit is highly desirable to develop strategies for activating and terminating the surface reconstruction. \n\nHere, we report an approach to promoting surface reconstruction on inactive but low-cost $\\mathrm{CoAl}_{2}\\mathrm{O}_{4}$ (see Supplementary Note 1 for more details) and boosting its OER performance by substituting Al with a small amount of Fe. The partially substituted $\\mathrm{CoFe}_{0.25}\\mathrm{Al}_{1.75}\\mathrm{O}_{4}$ outperforms some perovskites and $\\mathrm{IrO}_{2}$ . We demonstrate here that a low level of Fe substitution is able to facilitate the surface reconstruction of $\\mathrm{CoAl_{2}O_{4}}$ by activating the pre-oxidation of Co and optimizing the O $2p$ level of oxide for greater structural flexibility. More importantly, a distinctive reconstruction behaviour with selftermination has been revealed on $\\mathrm{CoFe}_{0.25}\\mathrm{Al}_{1.75}\\mathrm{O}_{4}.$ which enables a stable surface chemistry. In addition, we suggest that, on the reconstructed surface, the Fe substitution facilitates a two-step deprotonation process, which leads to the formation of active oxygen sites at a low overpotential and thus greatly promotes the OER. Finally, the electrolysis application of $\\mathrm{CoFe}_{0.25}\\mathrm{Al}_{1.75}\\mathrm{O}_{4}$ as an OER catalyst is demonstrated in a membrane electrode assembly (MEA) configuration. \n\n# Results \n\nCrystal structure characterization. The $\\mathrm{CoFe}_{x}\\mathrm{Al}_{2-x}\\mathrm{O}_{4}$ $(x{\\approx}0–2.0)$ oxides were synthesized using a sol–gel method. The crystal structures of the $\\mathrm{CoFe}_{x}\\mathrm{Al}_{2-x}\\mathrm{O}_{4}$ oxides were characterized by powder X-ray diffraction (XRD). As displayed in Fig. 1a, the diffraction peaks of the as-prepared $\\mathrm{CoAl}_{2}\\mathrm{O}_{4}$ and ${\\mathrm{CoFe}}_{2}{\\mathrm{O}}_{4}$ match with that of the standard cubic spinel $(F d-3m)$ oxides. $\\mathrm{CoFe}_{x}\\mathrm{Al}_{2-x}\\mathrm{O}_{4}$ oxides with different Fe substitution amounts remain in the cubic spinel structure. Furthermore, the diffraction peak exhibits a shift to a lower angle with increasing Fe substitution amount in the range of $0.25\\mathbf{Co}>\\mathbf{Cu}>$ $\\mathbf{M}\\mathbf{n}>\\mathbf{N}\\mathbf{i}$ .12–14 Recently, Fe–N–C catalysts have demonstrated significantly improved activity approaching that of $\\mathbf{\\rho}_{\\mathrm{Pt/C}}$ in challenging acidic media.3,5,11,15–18 Unfortunately, Fe-based catalysts suffer from poor stability, challenged by insufficient understanding of their degradation mechanisms during fuel cell operation.19–22 The possible degradation may be attributed to (1) leaching of the nonprecious metal sites from catalysts,19,21,23,24 (2) the attack by $\\mathbf{H}_{2}\\mathbf{O}_{2}$ (and/or free radicals),20 and (3) protonation of the active site or adjacent $\\mathbf{N}$ dopants followed by anion adsorption.25 Recently, Dodelet et al., proposed a new mechanism concerning micropore flooding as an explanation for the rapid initial performance loss.22 In addition, a deactivation mechanism has been verified by Jaouen et al., providing new insights that durable Fe–N–C catalysts can be retained in PEMFCs if rational strategies to minimize the amount of $\\mathbf{H}_{2}\\mathbf{O}_{2}$ or reactive oxygen species produced during the ORR are developed.26 Thus, the possible Fenton’s reactions between Fe and ${\\bf H}_{2}{\\bf O}_{2}$ , which generate hydroxyl and hydroperoxyl radical species, are likely one of reasons causing the degradation of current Fe–N–C catalysts along with the degradation of organic ionomers within the electrodes and the membranes in PEMFCs.26,27 Thus, it is essential to develop Fe-free catalysts to completely address the Fenton reaction issue and to acquire the understanding of the degradation mechanisms. Alternatively, Co-based catalysts would have far less deleterious effects in this regard and appear to be the ideal candidate for Pt-free and Fe-free catalysts.12,13,28–30 When compared to the Fe–N–C catalysts,15 current $\\scriptstyle\\mathbf{Co-N-C}$ ones have far less activity and higher yield of $\\mathbf{H}_{2}\\mathbf{O}_{2}$ during the ORR in acids,28,29,31–39 which still requires significant effort to improve their performance. \n\nMetal–organic frameworks (MOF), especially zeolitic-imidazole frameworks (ZIFs), have been used as precursors to synthesize atomically dispersed Co–N–C catalysts, due to their unique capability to form a large number of $\\mathbf{CoN}_{x}$ active sites and yield porous structures through a thermal activation.37,40 The resultant catalysts have exhibited well-dispersed atomic $\\mathbf{CoN}_{x}$ active sites, which correlated with good catalytic activity. However, there is still a significant activity gap between the Co–N–C and $\\mathrm{\\Pt/C}$ catalysts, such as at least $60~\\mathrm{mV}$ of half-wave potential in acidic aqueous electrolytes.37 Simply increasing Co metal content in the precursors is found to be ineffective, because it gives rise to severe aggregation of Co metal during high-temperature treatments.41 Thus, new strategies to effectively control the synthesis of $\\mathrm{CoN}_{x}$ active sites with high density are extremely desirable, but very challenging. Here, we develop an innovative surfactant-assisted MOF approach to preparing core–shell structured $\\scriptstyle\\mathbf{Co-N-C}$ catalysts, which was inspired by the strong interactions between surfactants and nanocrystal particles in solution phases.42–44 Due to the confinement role of surfactants covering onto the ZIF-8 nanocrystals, core–shell structured and atomically dispersed $\\mathbf{Co-N-C\\textcircled{\\2}}$ surfactant catalysts with significantly increased active site density were obtained versus other synthetic routes. Among the surfactants studied, F127 block copolymer (PEO100-PPO65-PEO100) was explored to identify as the optimal surfactant. Advanced electron microscopy and X-ray absorption fine structure (XAFS) measurements show that the $\\mathrm{CoN_{4}}$ are atomically dispersed and are more abundant in the catalysts synthesized using surfactant F127 versus those synthesized without surfactant or other surfactants. The Co–N–C@F127 catalyst exhibits exceptionally enhanced ORR activity with a halfwave potential $\\left(E_{1/2}\\right)$ of $0.84\\mathrm{V}$ (vs. RHE) in acidic electrolyte. To the best of our knowledge, this ORR activity exceeds those values of any previously-known PGM-free and Fe-free catalysts (see Table S1, $\\mathrm{ESI\\dag}^{\\prime}\\mathrm{,}$ and is comparable to that of the state-of-the-art Fe–N–C catalysts.15 Density functional theory (DFT) calculations were used to elucidate the chemical nature of the active sites capable of catalyzing the ORR via four electrons $(4\\mathrm{e}^{-})$ pathway. Fuel cell tests further confirm that the Co–N–C@F127 catalyst can perform as an efficient cathode in PEMFCs. Thus, exploration of alternative high-performance $\\scriptstyle\\mathbf{Co-N-C}$ catalysts would provide more insightful understanding on degradation mechanisms and open a new avenue to design advanced PGM-free catalysts for vital applications in PEMFCs. \n\n# Results and discussion \n\n# Catalyst synthesis and morphology \n\nThe synthesis procedures for the core–shell structured atomically dispersed $\\scriptstyle\\mathbf{Co-N-C}$ catalysts are illustrated in Fig. 1a. The experimental details are given in the ESI. $\\dagger$ It was initially driven by the organometallic reaction of $\\mathrm{Zn}^{2+}/\\mathrm{Co}^{2+}$ ions and 2-methylimidazole ligands to form Co doped ZIF-8 nanocrystals, then surfactants were added as the capping agents to regulate the crystallization. The surface of Co-ZIF-8 polyhedrons has abundant $\\scriptstyle{\\mathrm{Zn}}^{2+}$ and ${\\mathrm{Co}}^{2+}$ sites, which can be easily coordinated with the hydrophilic groups of the surfactants. This coordination effect can slow down the crystal growth rate and control the crystal size and morphology of Co-ZIF-8 crystals.45,46 During the subsequent pyrolysis, it can be speculated that the surfactant layers are the first one to carbonize, forming a carbon shell, coating on the Co-ZIF-8 polyhedrons.47 With increasing temperatures, the Co-ZIF-8 polyhedrons begin to carbonize. The strong cohesive interface interaction leads to a significant confinement effect, thus avoiding the collapse of the internal microporous carbon structures derived from Co-ZIF-8 polyhedrons while also mitigating the agglomeration of neighboring Co single atomic sites.48 As a result, the Co–N–C@surfactant catalyst has an abundantly-microporous structure and high density of $\\mathbf{CoN_{4}}$ atomic sites. Four types of surfactants (e.g., anionic surfactant SDS, cationic surfactant CTAB, non-ionic triblock copolymer F127, and non-ionic surfactant PVP) were examined in terms of their effectiveness to tune catalyst morphologies and properties. The molecular formula of these surfactants are shown in Fig. S1 $\\left(\\mathrm{ESI\\dag}\\right)$ . Typically, surfactant-free Co-ZIF-8 particles had a non-uniform rhombododecahedral shape with an average size of $850\\mathrm{nm}$ , yet there were some particles with smaller sizes of approximately $100\\ \\mathrm{nm}$ (Fig. S2, ESI†). Due to the capping ability of different surfactants, the particle sizes of the CoZIF-8@suffactant particles proportionally decreased from 850 to $100~\\mathrm{{nm}}$ when molecular weights of the surfactants increase (Fig. 1b). In addition, all the Co-ZIF-8@surfactant nanocrystals presented uniform particle sizes. This is a result that the surfactants formed the micelles which evenly dispersed zinc and cobalt ions in the methanol solution.49 Although the use of PVP resulted in the smallest size of catalysts (down to $100\\ \\mathrm{nm}$ , particle fusing was observed. As for the Co-ZIF- ${8}\\textcircled{\\mathrm{a}}\\mathrm{F}127$ catalyst, nanoparticles showed isolated dispersion with an average diameter of $250\\mathrm{nm}$ (Fig. S3, ESI†). High-resolution transmission electron microscopy (HR-TEM) and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) images were employed to further reveal the detailed structures and morphologies. Fig. 2 compares the surfactant-free Co-ZIF-8 and the Co-ZIF-8@F127 nanocrystal precursors and their corresponding catalysts after thermal activations. Compared to the rhombododecahedral shape of the Co-ZIF-8 precursor (Fig. 2A and Fig. S4, ESI†), a core–shell structure is observed in the Co-ZIF-8@F127 precursor (Fig. 2B and Fig. S5, $\\mathrm{ESI\\dag}\\$ ), which consisted of a Co-ZIF-8 nanocrystal core and a surfactant F127 polymer shell. STEM-EDS elemental mapping results in Fig. 2 indicate that C, N, and Co are uniformly dispersed into the precursors regardless of the addition of the F127 surfactant. Fig. S6 $\\left(\\mathrm{ESI}\\dag\\right)$ shows X-ray diffraction (XRD) patterns of the Co-ZIF-8 and Co-ZIF-8@F127 precursors. Their diffraction patterns are identical, indicating that the addition of surfactants and the doping of Co ions did not influence the crystalline structure of the ZIF-8. \n\n![](images/189ee44f0ef462effb3c7ffff42da33e01969c248f325815bf9a26c1041ec57e.jpg) \nFig. 1 (a) Proposed in situ confinement pyrolysis strategy to synthesize core–shell-structured Co–N–C@surfactants catalysts with increased active site density (The yellow, grey and blue balls represent Co, Zn and N atoms, respectively.). (b) Expected particle sizes and (c) SEM images to show the changes in the size and morphology of the catalysts with varying surfactants including SDS, CTAB, F127 and PVP. \n\nAfter a thermal treatment at $900^{\\circ}\\mathrm{C}$ , the size and shape of the various $\\scriptstyle\\mathbf{Co-N-C}$ catalysts were similar to their corresponding Co-ZIF-8 crystal precursors (Fig. S7, $\\mathrm{ESI\\dag}$ ). The hydrocarbon networks in all Co-ZIF-8 crystals were completely carbonized as evidenced in the XRD patterns showing dominant peaks at $25^{\\circ}$ and $44^{\\circ}$ for the (002) and (101) planes of carbon, respectively (Fig. S8, $\\mathrm{ESI\\dag}$ ). Based on HR-TEM and HAADF-STEM images (Fig. 2C and D), the carbon networks in both $\\scriptstyle\\mathbf{Co-N-C}$ and Co–N–C@F127 catalysts were highly disordered due to the doping of the heteroatoms $\\mathbf{N}_{}$ which led to the turbostratic stacking of graphite planes.50 Notably, the Co–N–C@F127 exhibited a typical core–shell structure, in which the core was derived from the Co-doped ZIF-8 nanocrystal and the carbon shell was from the surfactant F127 layers (Fig. 2D).51 The partially graphitized carbon shells could be clearly observed at the edge of the polyhedron, attributable to the graphitization of F127. Compared to the carbon structures in the shells, the carbon cores derived from the ZIF-8 precursors seems more amorphous and porous. Raman spectra in Fig. S9 and Table S2 $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ indicate that, regardless of the type of surfactants, all the catalysts exhibited similar carbon structures with dominant D and G bands at 1350 and $1585~\\mathrm{{cm}^{-1}}$ , associated with the disordered carbons and $\\displaystyle\\boldsymbol{\\mathsf{s p}}^{2}$ hybridized graphitic carbons, respectively.52 Among the samples studied, Co–N–C@F127 demonstrates a relatively high $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ value of 1.52, suggesting the largest amounts of defects. This finding is in good agreement with the X-ray photoelectron spectroscopy (XPS) results, discussed in detail later, which show this catalyst containing the highest content of N and Co dopants.50 \n\n![](images/892fabf546d65c6f355aa1149fbe958a5678e3d868404b7c2c29899b34565743.jpg) \nFig. 2 HRTEM, HAADF-STEM and STEM-EDS elemental mappings for (A) surfactant-free Co-ZIF-8 precursor, (B) Co-ZIF-8@F127 precursor, (C) surfactant-free Co–N–C catalyst and (D) Co–N–C@F127 catalyst. \n\nThe porosity of Co–N–C@surfactant nanocrystals prepared with different surfactants was quantified by $\\ensuremath{\\mathbf{N}}_{2}$ adsorption– desorption measurements (Fig. S10 and S11, $\\mathrm{ESI\\dag}$ ). The surfactant-free Co–N–C catalyst revealed a type IV sorption isotherm. The increased adsorption volume at a low relative pressure indicates the existence of micropores, while the distinct hysteresis loop in the range of $P/P_{0}0.4–0.8$ is indicative of a mesoporous feature.16 In contrast, the isotherms of $\\mathbf{Co-N-C\\textcircled{a}F127}$ porous carbon revealed a type I sorption isotherm, an indication of the existence of only micropores in the absence of mesopores. The BET specific surface area and the total pore volume of the ${\\bf C o-N-C\\otimes F127}$ catalyst are $825~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ and $0.54~\\mathrm{\\cm}^{3}~\\mathrm{g}^{-1}$ , respectively (Table S3, $\\mathrm{ESI\\dag}\\$ , which are much higher than those of the surfactant-free $\\scriptstyle\\mathbf{Co-N-C}$ catalyst $\\ensuremath{324}\\ensuremath{\\mathrm{~m~}^{2}\\mathrm{~g}^{-1}}$ and $0.235\\ \\mathrm{cm}^{3}\\ \\mathrm{g}^{-1})$ . The comparison implies that direct carbonization of the Co-ZIF-8 without protection from F127 most likely led to the significant obstruction and the collapse of micropores within ZIF-8. It has been postulated that ORR active sites in M–N–C catalysts are likely located inside or around the micropores of carbon phases.53 Therefore, the richness of micropores in the $\\mathbf{Co-N-C\\textcircled{a}F127}$ catalyst is beneficial for accommodating a high density of active sites. \n\n# High-density atomically dispersed $\\mathbf{CoN_{4}}$ sites \n\nThe N-coordinated Co sites, whose local coordination environments are similar to those of the $\\mathbf{CoN_{4}}$ in Co-porphyrin structures, have been predicted as the possible ORR active sites in Co-based catalysts.54 To further determine the local chemical bonding of Co atoms in the Co–N–C@F127 catalyst, the catalyst was analyzed using Co K-edge X-ray absorption spectroscopy encompassing both the near-edge and extended energy regions, \n\n![](images/6137a49e8d2439bfda5b9d61aa852a3ec7e1240ea9975543054ddd8b76d478be.jpg) \nFig. 3 (a) Co K edge XANES spectra. (b) The magnitude (solid black) and imaginary part (dashed black) of the Fourier transform of the $k^{2}$ -weighted EXAFS. (c) Fit of the magnitude of the Fourier transform of the $k^{2}$ -weighted EXAFS (data-black and fit-red) for the Co–N–C@F127 catalyst. Aberration-corrected HAADF-STEM images with accompanying EELS point spectra of (d) $C O-N-C$ and (e and f) Co–N–C@F127 catalyst. \n\nXANES and EXAFS, respectively. The results are presented in Fig. 3a–c. The increased XANES white line intensity of $\\mathbf{Co-N-C\\textcircled{a}F127}$ compared to the reference cobalt foil is consistent with the sample containing oxidized Co and the similar pre-edge energy of the catalyst and the $\\mathrm{Co}(\\mathrm{NO}_{3})_{2}$ reference (Table S4, ESI†) indicates the Co is in the $^{2+}$ oxidation state. The pre-edge feature in the Co K-edge XANES spectrum $\\cdot\\sim7708\\ –7711\\ \\mathrm{eV})$ arises from the a 1s to 3d transition and in general the intensity of this peak in the K-edge spectra of 3d metals is related to the extent of 3d–4p mixing, which increases with decreasing centrosymmetry of the metal coordination environment.55 The pre-edge peak intensity for the catalyst compared to that of the octahedral $\\mathrm{Co}(\\mathrm{NO}_{3})_{2}$ reference suggests that the coordination of Co in the catalyst is less centrosymmetric than the octahedral complex (Fig. 3a). The magnitude and imaginary part of the Fourier transform of the $k^{2}$ -weighted EXAFS of $\\mathbf{Co-N-C\\textcircled{a}F1}27$ are shown in Fig. 3b. A peak arising from light scattering $\\left(\\mathbf{C}/\\mathbf{N}/\\mathbf{O}\\right)$ nearestneighbors is observed at $1.6\\mathring{\\mathbf{A}}$ (phase uncorrected distance) and was fit using a single $\\mathbf{Co-N}$ scattering path.11,56 The fitted coordination number of $3.6\\pm\\:0.6$ is in agreement with the XANES with Co having a tetrahedral geometry. The Co–N bond length derived from the EXAFS fit was $1.94~\\pm~0.02$ Å. No evidence of Co–Co scattering is observed in the EXAFS of the Co–N–C/F127 catalyst, which is consistent with an atomically dispersed species. Moreover, HAADF-STEM imaging coupled with electron energy loss spectroscopy (EELS) were performed. As depicted in Fig. 3d–f, well-dispersed isolated Co atomic sites are clearly observed in both the $\\scriptstyle\\mathbf{Co-N-C}$ and the $\\mathbf{Co-N-C\\textcircled{a}F127}$ catalysts, located at both the edge sites and in the carbon matrix. EELS point spectra taken by focusing the electron beam on the bright dot in the HAADF-STEM image (green circle) in \n\nFig. 3e and f indicates that Co atoms and N co-exist in the form of $\\mathbf{CoN}_{x}$ . This atomic level spectroscopic analysis agrees with the results from XANES and EXAFS, verifying that well-dispersed atomic Co sites are coordinated with N. Although it is challenging to obtain accurate sample composition via the EELS overall composition analysis, there is a clear tendency of more Co (perhaps $3\\times$ as much), as well as more N $(2\\times)$ and slightly more O in the Co–N–C@F127 catalysts as compared to those in the surfactant-free Co–N–C catalyst (Tables ${\\bf S5-S8,E S I\\dagger}$ ). This suggests significantly increased density of $\\mathrm{CoN_{4}}$ active sites due to the confined role of using the F127 surfactant. \n\nElemental analysis and XPS measurements were conducted to probe the content and chemical composition of C, N, and Co in the surface layers (less than $10\\ \\mathrm{nm}$ ) of these Co–N–C catalysts. With the addition of the surfactant F127, the content of Co is slightly increased from $0.9\\ \\mathrm{at\\%}$ for the surfactant-free Co–N–C to $1.0\\ \\mathrm{at\\%}$ for the $\\mathbf{Co-N-C\\textcircled{a}F127}$ (Table S7, ESI†). For other surfactants derived Co–N–C catalysts, they showed similar Co content. Since Co atoms under the porous carbon shells could not be accurately detected by using XPS, the Co content of the catalysts was further analyzed by X-ray fluorescence (XRF) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) (Table S8, $\\mathrm{ESI\\dag}^{\\prime}$ ). These results also indicated that the Co content in the ${\\bf C o-N-C\\otimes F127}$ catalyst is the highest than any other catalysts, suggesting the beneficial role of F127 in maintaining more atomic Co sites within the carbon framework during pyrolysis. The samples obtained from different surfactants exhibits similar C 1s XPS spectra (Fig. 4a and Table S9, ESI†). The Co $2{\\tt p}_{3/2}$ $(780.5~\\mathrm{eV})$ and Co $2\\mathsf{p}_{1/2}$ (795.6 eV) peaks, as shown in Fig. 4b and Fig. S10 $\\bigl(\\mathrm{ESI\\dag}\\bigr)$ , are typical features of ${\\bf C o}^{2+}$ species,57,58 consistent with the XANES results. The $\\mathbf{N}$ 1s XPS for all the samples (Fig. 4c and Fig. S11, ESI†) reveal three main components including pyridinic-N $\\left(398.4\\mathrm{~\\eV}\\right)$ , graphitic-N (401.1 eV), and oxidized graphitic-N (403–405 eV). The $\\mathbf{Co-N-C\\textcircled{a}F1}27$ catalyst displays a significantly increased N content of $9.1\\ \\mathrm{at\\%}$ with respect to the $6.1\\ \\mathrm{at\\%}$ N for the surfactant-free $\\scriptstyle\\mathbf{Co-N-C}$ catalyst and others. It should be noted that the N content reaches to the highest level compared to all of other such-synthesized M–N–C catalysts through high temperature approaches.7,8,59 Such a high N content is attributed to the possible confinement pyrolysis effect of F127 to retain N during high-temperature pyrolysis, which is beneficial for the formation and retention of high-density $\\mathbf{CoN_{4}}$ active sites. An additional peak at $399.2{\\mathrm{~eV}}$ is likely assigned to N atoms bonding to atomic Co sites in the form of $\\mathbf{CoN_{4}}$ .60 Among all the catalysts studied, the ${\\bf C o-N-C\\otimes F127}$ catalyst presents the highest intensity of this peak, implying the largest fraction of $\\mathbf{CoN_{4}}$ sites. \n\n![](images/60afa7b578cb2e5c20c0f21f3d83f122a3749bfccfcb234d52026656b97310df.jpg) \nFig. 4 XPS analysis of (a) C 1s, (b) N 1s and (c) Co 2p to elucidate the effect of surfactants for different catalysts including Co–N–C; Co–N–C@SDS, Co–N–C@CTAB; Co–N–C@F127 and Co–N–C@PVP catalysts. \n\n# Density functional theory (DFT) calculations \n\nTo theoretically evaluate the ORR activity and selectivity on the identified $\\mathbf{CoN_{4}}$ sites in the $\\scriptstyle\\mathbf{Co-N-C}$ catalysts, we performed first principles DFT calculations to study the adsorption energy, free energy evolution, and O–O bond breaking activation energy on possible $\\mathbf{CoN}_{x}\\mathbf{C}_{y}$ active sites during the ORR. Based on the XANES analysis results (i.e., coordination number of N around Co is 3.6), we focused our present computational study on $\\mathbf{CoN_{4}}$ (a $\\bf{C o-N_{4}}$ moiety embedded in intact graphitic layer) and $\\mathbf{CoN}_{2+2}$ (a $\\mathrm{Co-N_{4}}$ moiety bridging over two adjacent armchair graphitic edge) sites, as depicted in Fig. 5a. From their optimized structures, the Co–N bond length is predicted to be $1.85\\mathrm{~\\AA~}$ in the $\\mathrm{CoN_{4}}$ site and $1.88\\mathrm{~\\AA~}$ in the $\\mathbf{CoN}_{2+2}$ site. Our theoretical prediction of the $\\mathrm{Co-N}$ bond length is close to the value of $1.94\\mathring{\\mathrm{A}}$ based on the aforementioned EXAFS analysis. It should be noted that these two types of the metal- ${\\bf\\cdot N_{4}}$ coordination geometries have been proposed as ORR active sites in Fe–N–C catalysts in a prior study.61 The four-electron $(4\\mathrm{e}^{-})$ ORR on the $\\scriptstyle\\mathbf{Co-N-C}$ catalysts starts with the adsorption of reactant $\\mathbf{O}_{2}$ and ends with the release of product $\\mathbf{H}_{2}\\mathbf{O}.$ . Consistent with this process, we have determined the adsorption configurations (Fig. S12, $\\mathrm{ESI\\dag}$ and adsorption energy (Table S12, $\\mathrm{ESI\\dag}$ ) of $\\mathbf{O}_{2}$ OOH, O, OH, and $\\mathbf{H}_{2}\\mathbf{O}$ on the $\\mathrm{CoN_{4}}$ and $\\mathbf{CoN}_{2+2}$ sites. DFT results show that both $\\mathrm{CoN_{4}}$ and $\\mathbf{CoN}_{2+2}$ can bind $\\mathbf{O}_{2}$ appropriately to initiate the ORR as well as bind $\\mathbf{H}_{2}\\mathbf{O}$ weakly to complete ORR. Moreover, we examined the thermodynamic free energy change for a $4\\mathrm{e}^{-}$ ORR pathway, in which $\\mathbf{O}_{2}$ molecule will be first adsorbed on the top of the central Co, then $\\mathbf{O}_{2}$ will be protonated to form OOH, the OOH will dissociate into $^{\\mathrm{~\\small~O~}}$ and OH, and finally both $^{\\mathrm{~o~}}$ and OH will be pronated to form product $\\mathbf{H}_{2}\\mathbf{O}$ . Here, we employed the computational hydrogen electrode method developed by Norskov et al.62 and computed the free energies of every elementary steps as a function of electrode potential $U$ with reference to reversible hydrogen electrode (RHE). Fig. 5b shows that the free energy change for these elementary ORR reactions on the $\\mathbf{CoN}_{2+2}$ site become negative (i.e., exergonic reaction) when the electrode potential $U$ is lower than a limiting potential of $0.73{\\mathrm{~V}}.$ Thus, the $\\mathbf{CoN}_{2+2}$ site is predicted to be thermodynamically capable of catalyzing the $4\\mathrm{e}^{-}$ ORR. In contrast, we predicted a free energy barrier of $0.39~\\mathrm{eV}$ for ${}^{*}\\mathrm{OOH}$ to dissociate to ${}^{*}\\mathbf{O}$ and ${}^{*}\\mathrm{OH}$ on the $\\mathrm{CoN_{4}}$ site. This result suggests that it is thermodynamically difficult for the $4\\mathrm{e}^{-}$ ORR to occur on this $\\mathrm{CoN_{4}}$ site. \n\nIn order to elaborate the ORR pathway on $\\mathbf{CoN_{4}}$ and $\\mathbf{CoN}_{2+2}$ sites, the climbing image nudged elastic band (CI-NEB) calculation was carried out63 to locate the transition state and predict the activation energies for the OOH dissociation reaction. This is the crucial step that breaks the $_{0-0}$ bond in the $4\\mathrm{e}^{-}$ ORR pathway, on both the $\\mathrm{CoN_{4}}$ and $\\mathbf{CoN}_{2+2}$ sites. Fig. 5c shows the atomic details of this reaction on the $\\mathbf{CoN}_{2+2}$ site. In the initial state, the OOH is adsorbed on the central Co atom; in the final state, both the dissociated O and OH are co-adsorbed on the central Co atom. Our DFT calculations indicate that the OOH dissociation reaction must overcome an activation energy of $0.69\\ \\mathrm{eV}$ on the $\\mathbf{CoN}_{2+2}$ site and $1.11\\ \\mathrm{eV}$ on the $\\mathbf{CoN_{4}}$ site (Fig. 5b). In comparison, our previous DFT study predicted the activation energy for the same OOH dissociation reaction to be $0.56\\mathrm{eV}$ on $\\mathrm{FeN}_{4}$ site, which is able to catalyze the $4\\mathrm{e}^{-}$ ORR.64,65 Consequently, it can be inferred from these computational results that $\\mathbf{CoN}_{2+2}$ can catalyze the $4\\mathrm{e}^{-}$ ORR, similar to $\\mathrm{FeN_{4}}$ whereas $\\mathbf{CoN_{4}}$ cannot catalyze the $4\\mathrm{e}^{-}$ ORR owing to the insurmountable activation energy for $_{0-0}$ bond breaking on this site. \n\n![](images/074248d053a53dcccc3a9c9d15335ce60b22da188c124cd8af85165de783d90a.jpg) \nFig. 5 (a) Atomistic structure of $C O N_{2+2}$ and $C O N_{4}$ active sites of the $C O-N-C$ catalysts. (b) Calculated free energy evolution diagram for $4\\mathsf{e}^{-}$ ORR pathway on the $C O N_{2+2}$ site under a limiting electrode potential of $U=0.73\\:\\forall$ and on $C O N_{4}$ site under a limiting electrode potential of $U=0.67~\\forall.$ (c) Atomistic structure of the initial state (left), transition state (middle), and final state (right) for OOH dissociation reaction on the $C O N_{2+2}$ site. In this figure, the gray, blue, yellow, red and white balls represent C, N, Co, O, and H atoms, respectively. \n\n# Catalyst activity and stability \n\nThe oxygen reduction activity and four-electron selectivity $\\left(\\mathrm{H}_{2}\\mathbf{O}_{2}\\right.$ yield) of various catalysts were evaluated in $\\mathbf{O}_{2}$ -saturated $0.5\\:\\mathrm{M}\\:\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution. Without Co doping, the $\\mathbf{N}{\\mathbf{-C}}$ catalyst showed poor activity with a low onset potential $(E_{\\mathrm{onset}},$ defined as potential at which the current density reaches $0.1\\mathrm{\\mA\\cm^{-2}}$ ) of $_{0.81\\mathrm{v}}$ and a half-wave potential $\\left(E_{1/2}\\right.$ , defined as the potential at which the current reaches half the limiting current density) of $0.59\\mathrm{V}$ vs. RHE (Fig. 6a and Fig. S13, $\\mathrm{ESI\\dag}$ ). Co doping boosted the ORR performance, most likely associated with the formation of $\\mathrm{CoN_{4}}$ sites which are more intrinsically active than the metal-free N activated C sites based on our theoretical predictions. The ORR activity was found to be dependent on the type of surfactants used. The highest ORR activity was measured for the Co–N–C@F127 catalyst, with a size of $250\\ \\mathrm{nm}$ , exhibiting an $E_{\\mathrm{onset}}$ of $_{0.93\\mathrm{~V~}}$ and an $E_{1/2}$ of $0.84\\mathrm{V}$ vs. RHE. It should be noted that the correlation of doped Co content and the corresponding ORR activity follows a so-called ‘‘volcano plot’’ (Fig. S14, ESI†). Lower doping yields insufficient density of active sites, while higher doping leads to Co agglomeration and unfavorable carbon structures (i.e., less defect and porosity). This suggests that maximum atomic Co sites coordinated with N generate largest density of active sites corresponding to the best activity. This remarkable activity for the Co–N–C catalyst in acid is comparable to that of the state-ofthe-art Fe–N–C ( $\\cdot E_{\\mathrm{onset}}$ at $0.95\\mathrm{~V~}$ and $E_{1/2}$ at 0.85 V).15 This ORR activity in challenging acidic media is superior to that of previously known PGM-free and Fe-free catalysts (Table S1, ESI†), representing a new record. In addition, only negligible $\\mathbf{H}_{2}\\mathbf{O}_{2}$ was generated during the ORR on the ${\\bf C o-N-C\\otimes F127}$ catalyst (Fig. 6b), indicating a dominant $4\\mathrm{e}^{-}$ reduction pathway. Combined with the DFT simulation results, it suggests that our synthesis method for $\\scriptstyle\\mathbf{Co-N-C}$ catalysts increases the amount of $\\mathbf{CoN}_{2+2}$ sites, which are on the edge of carbon layers and highly active for the $4\\mathrm{e}^{-}$ ORR. The ${\\bf C o-N-C\\otimes F127}$ also demonstrates excellent stability during both potential cycling $(0.6\\mathrm{-}1.0\\mathrm{~V};$ $50\\mathrm{~mV~s~}^{-1})$ and holding at constant potentials (0.7 and $0.85\\mathrm{~V~}$ for 100 hours) in $\\mathbf{O}_{2}$ -saturated $0.5{\\ensuremath{\\mathrm{~M~}}}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ . There is a loss of only $40~\\mathrm{mV}$ in $E_{1/2}$ after 30 000 potential cycles from 0.6 to $1.0\\mathrm{V}$ (Fig. 6c). The corresponding CV profiles are compared in Fig. S15 $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ during the potential cycling, indicating initial carbon oxidation during the first 10 000 cycles in good agreement to the major loss occurred in the first 10 000 cycles with a loss of $30~\\mathrm{mV}$ . This thus implies that the rapid degradation of unstable active sites is associated with the carbon oxidation at surfaces. The remaining active sites are more stable against degradation. Furthermore, constant potential tests were conducted for up to 100 hours at relatively high potentials of 0.7 and $0.85\\mathrm{~V~}$ (Fig. 6d–f), respectively. Retention of initial activity up to $94.5\\%$ and $65\\%$ was determined at both potentials, respectively. At $0.85\\mathrm{~V~}$ , the significant loss occurred at the initial 20 hours, which is good agreement with the potential cycling tests. To further elucidate the possible degradation likely due to carbon corrosion, the samples after the 30 000 potential cycles and the 100 hour $0.85\\mathrm{~V~}$ potential holds tests were analyzed by STEM imaging (Fig. 6g–j, Fig. S16 and S17, $\\mathrm{ESI\\dag}$ ). The catalyst particles became rough at the surface after two long-term stability tests, which is probably associated with the initial activity loss. Overall, the carbon particle morphologies and structures were maintained and were similar to that observed in the pre-test catalyst samples. The observed structural stability may be attributed to the protective role of graphitized carbon layers,66,67 which prevents the continuous corrosion and oxidization from the external acidic environment of the electrolyte. \n\n![](images/532431404c70aac49a383af357b443b88e19f6a64d60321093e27f074faf4309.jpg) \nFig. 6 (a) ORR polarization plots and (b) calculated $H_{2}O_{2}$ yield for different Co-ZIF-8@surfactants derived catalysts in $0.5~M$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at $25^{\\circ}\\mathsf{C}$ and at 900 rpm. (c) Potential cycling $(0.6\\mathrm{-}1.0\\ V)$ stability test of best Co–N–C@F127 catalysts in $\\mathrm{O}_{2}$ -saturated $0.5M\\mathsf{H}_{2}\\mathsf{S}\\mathsf{O}_{4}$ (the Pt/C catalyst was tested in $0.1{\\ensuremath{\\mathsf{M}}}$ ${\\mathsf{H C l O}}_{4})$ (d) $100\\ h$ chronoamperometry tests at (e) $0.7\\mathrm{~V~}$ and (f) $0.85~\\mathsf{V},$ respectively. Bright field and high resolution TEM images of Co–N–C@F127 catalysts (g and h) after $100\\mathrm{~h~}$ chronoamperometry test at $0.85\\mathrm{\\vee}$ and (i and j) after 30 000 cycling $(0.6\\mathrm{-}1.0\\ V)$ stability test. \n\n![](images/0be79c3b86186ab1779e5bc17ac4e6eae2eaa9f8d7b9025c3d9fa2da0291d3ba.jpg) \nFig. 7 Fuel cell performance before and after durability tests of best Co–N–C@F127 catalyst and Fe–N–C catalyst. (a and b) ${\\sf H}_{2}\\mathrm{-}{\\sf O}_{2}$ and (c and d) ${\\sf H}_{2}$ -ai fuel cell polarization plots at different relative humidity (RH). Cell temperature: $80\\ {}^{\\circ}{\\mathsf{C}};$ flow rate ${\\sf H}_{2}/\\sf O_{2}$ or air: 200/200 sccm, RH: $100\\%$ or $60\\%$ , 1 ba ${\\sf H}_{2}/\\sf{O}_{2}$ or air partial pressure. $4\\ m g\\ c m^{-2}$ , ${1/C}=0.6,$ Nafion 212. \n\nTo examine the effectiveness of the Co–N–C@F127 catalyst as a practical PGM-free cathode in PEMFCs, the catalyst was incorporated into membrane-electrode assemblies (MEAs) with a total catalyst loading of $4.0~\\mathrm{mg~cm}^{-2}$ . When ${\\bf H}_{2}/{\\bf O}_{2}$ at 1.0 bar pressure was used (Fig. 7a, b and Fig. S18, $\\mathrm{ESI\\dag}\\$ ), the cell exhibited an open-circuit voltage of $_{0.92\\mathrm{~V~}}$ and generated current densities of $30\\mathrm{\\mA\\cm}^{-2}$ at $_{0.8\\mathrm{~V~}}$ and $2.2\\mathrm{~A~cm}^{-2}$ at $0.4{\\mathrm{V}}.$ . It should be noted that, when a relative humidity (RH) of $100\\%$ was applied, the performance at high voltages $\\mathrm{(>0.7~V)}$ was still inferior to that of the Fe–N–C catalysts. However, at moderate voltages (0.5–0.7 V) typical of PEMFC operation, the ${\\bf C o-N-C\\otimes F127}$ was able to generate comparable performance showing a high power density of 0.87 W $\\mathrm{cm}^{-2}$ . At a low RH $(60\\%)$ , the ${\\bf C o-N-C\\otimes F127}$ cathode exhibited slightly higher performance than a $\\mathbf{\\partial}_{\\mathbf{Fe-N-C}}$ catalyst, suggesting that water flooding is a serious issue of the $\\mathbf{Co-N-C\\textcircled{a}F1}27$ cathode due to the catalyst’s micropore feature. Fuel cell performance was then evaluated by using more practical $\\mathbf{H}_{2}/{\\mathrm{air}}$ at 1.0 bar. The polarization curves recorded at $100\\%$ RH indicates a significant mass transport loss associated with serious water flooding issue (Fig. 7c and Fig. S19, ESI†). However, at a relatively low RH of $60\\%$ , the $\\mathbf{Co-N-C\\textcircled{a}127}$ exhibited enhanced performance at all voltages studied (Fig. 7d). SEM images of a MEA cathode present very dense and aggregated morphologies (Fig. S20, $\\mathrm{ESI\\dag}\\$ ), which is not favorable for mass transport. This suggests that further optimization of electrode structures is highly demanded to improve ionomer dispersion, facilitate mass transport, and mitigate the water flooding in the fuel cell electrodes. The durability of the Co–N–C@F127 catalyst in the MEA was further evaluated for 100 hours at a cell voltage of $0.7\\mathrm{~V~}$ using $\\mathbf{H}_{2}$ and air at 1.0 bar and two different RHs (Fig. S21, $\\mathbf{ESI\\dagger}_{\\mathbf{\\lambda}}$ ). Significant initial performance loss was observed, which is in good agreement with initial activity loss in RDE tests. Compared to other PGM-free and Fe-free cathodes in fuel cells,37,68,69 the performance durability at such a relatively high voltage $(i.e.,\\ 0.7\\ \\mathrm{V})$ was commendable. The performance loss is likely due to the possible surface oxidation of carbon along with degradation of three-phase interface within cathodes. Currently, performance durability especially at high voltages is still a grand challenge for PGM-free cathodes, which need increasing effort to address this issue. \n\n# Conclusion \n\nIn summary, we developed an effective surfactant-assisted confinement pyrolysis strategy to enable controlled synthesis of atomically dispersed $\\mathrm{CoN_{4}}$ sites with increased density, therefore leading to significantly enhanced catalytic activity for the ORR in challenging acids for PEMFCs. Distinct from prior studies, Co-doped ZIF nanocrystal precursors were coated with a surfactant layer, which would be carbonized to graphitized carbon shells via a heat treatment. This carbon shell can effectively retain dominant micropores and high content of N in the carbon matrix, thus preventing the agglomeration of single atomic Co sites. Furthermore, we applied extensive physical characterization on the thus-synthesized catalysts to verify the atomic dispersion of $\\mathrm{CoN_{4}}$ sites with increased density than the catalysts synthesized using conventional surfactant-free approach. Among four types of studied surfactants, the $\\mathbf{Co-N-C\\textcircled{\\sc2}F1}27$ catalyst exhibited excellent ORR activity with the most positive $E_{1/2}$ of $0.84\\mathrm{~V~}$ (vs. RHE) along with a dominant $4\\mathrm{e}^{-}$ ORR pathway in acidic media $\\mathrm{\\bf{\\tilde{H}}}_{2}\\mathbf{O}_{2}$ yield ${<}2\\%)$ . This superior ORR activity is the highest ever reported for PGM- and Fe-free catalysts. First principles DFT calculations further predicted that the $\\mathbf{CoN}_{2+2}$ sites on the edge of carbon layers are able to catalyze the $4\\mathrm{e}^{-}$ ORR showing comparable activity to $\\mathrm{FeN_{4}}$ sites, whereas the conventional $\\mathrm{CoN_{4}}$ sites embedded inside compact carbon layers could mainly catalyze the $2\\mathrm{e}^{-}$ ORR. Unlike other Co catalysts, this new atomically dispersed $\\scriptstyle\\mathbf{Co-N-C}$ catalyst derived from the surfactant-coated ZIF precursors is believed to contain substantial $\\mathbf{CoN}_{2+2}$ sites and hence demonstrated highly active and selective for the desirable $4\\mathrm{e}^{-}$ ORR in acids. Importantly, fuel cell tests further confirm the effectiveness of the $\\mathbf{Co-N-C\\textcircled{a}F1}27$ cathode catalyst in PEMFCs with a power density of 0.87 W $\\mathrm{cm}^{-2}$ comparable to that of a Fe–N–C catalyst-based cathode, especially at relatively low RH. Similar to Fe–N–C catalysts, initial performance degradation was observed with the $\\scriptstyle\\mathbf{Co-N-C}$ catalyst in both RDE and fuel cell tests, which is likely due to carbon oxidation. One of our future focuses will be on the improvement of catalyst stability through engineering carbon structures in catalysts. The surfactant-assisted confinement strategy provides a new approach to synthesizing single metal site catalyst with significantly increased density of active sites for widespread electrochemical energy conversion applications. \n\n# Conflicts of interest \n\nThere are no conflicts to declare. \n\n# Acknowledgements \n\nG. Wu thanks the financial support from the National Science Foundation (CBET-1604392, 1804326). G. Wu, G. F. Wang, and S. Litster acknowledge the support from U.S. DOE-EERE Fuel Cell Technologies Office (DE-EE0008076). Electron microscopy research was conducted at the Center for Functional Nanomaterials at Brookhaven National Laboratory (S. Hwang and D. Su, under contract No. DE-SC0012704) and the Center for Nanophase Materials Sciences of Oak Ridge National Laboratory (D. A. Cullen and K. L. More), which both are DOE Office of Science User Facilities. This research used resources of the Advanced Photon Source (APS), a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract DE-AC02-06CH11357. \n\n# References \n\nPalacin, Energy Environ. Sci., 2011, 4, 1238–1254. 2 F. Jaouen, E. Proietti, M. Lef\\`evre, R. Chenitz, J.-P. Dodelet, G. Wu, H. T. Chung, C. M. Johnston and P. Zelenay, Energy Environ. Sci., 2011, 4, 114–130. 3 H. T. Chung, D. A. Cullen, D. Higgins, B. T. Sneed, E. F. Holby, K. L. More and P. Zelenay, Science, 2017, 357, 479–484. 4 G. Wu, K. L. More, C. M. Johnston and P. Zelenay, Science, 2011, 332, 443–447. 5 S. T. Thompson, A. R. Wilson, P. Zelenay, D. J. Myers, K. L. More, K. C. Neyerlin and D. Papageorgopoulos, Solid State Ionics, 2018, 319, 68–76. 6 G. Wu, Front. Energy, 2017, 11, 286–298. 7 G. Wu and P. Zelenay, Acc. Chem. Res., 2013, 46, 1878–1889. 8 G. Wu, A. Santandreu, W. Kellogg, S. Gupta, O. Ogoke, H. Zhang, H.-L. Wang and L. Dai, Nano Energy, 2016, 29, 83–110. 9 J. Shui, M. Wang, F. Du and L. Dai, Sci. Adv., 2015, 1, e1400129. \n10 W. Gu, L. Hu, J. Li and E. Wang, Electroanalysis, 2018, 30, 1217–1228. \n11 A. Zitolo, V. Goellner, V. Armel, M.-T. Sougrati, T. Mineva, L. Stievano, E. Fonda and F. Jaouen, Nat. Mater., 2015, 14, 937. \n12 H. Peng, F. Liu, X. Liu, S. Liao, C. You, X. Tian, H. Nan, F. Luo, H. Song and Z. Fu, ACS Catal., 2014, 4, 3797–3805. \n13 J. Masa, A. Zhao, W. Xia, M. Muhler and W. Schuhmann, Electrochim. Acta, 2014, 128, 271–278. \n14 G. Wu, M. Nelson, S. Ma, H. Meng, G. Cui and P. K. Shen, Carbon, 2011, 49, 3972–3982. \n15 H. Zhang, S. Hwang, M. Wang, Z. Feng, S. Karakalos, L. Luo, Z. Qiao, X. Xie, C. Wang, D. Su, Y. Shao and G. Wu, J. Am. Chem. Soc., 2017, 139, 14143–14149. \n16 S. Gupta, S. Zhao, O. Ogoke, Y. Lin, H. Xu and G. Wu, ChemSusChem, 2017, 10, 774–785. \n17 Z. Qiao, H. Zhang, S. Karakalos, S. Hwang, J. Xue, M. Chen, D. Su and G. Wu, Appl. Catal., B, 2017, 219, 629–639. \n18 X. Wang, H. Zhang, H. Lin, S. Gupta, C. Wang, Z. Tao, H. Fu, T. Wang, J. Zheng, G. Wu and X. Li, Nano Energy, 2016, 25, 110–119. \n19 D. Banham, S. Ye, K. Pei, J.-I. Ozaki, T. Kishimoto and Y. Imashiro, J. Power Sources, 2015, 285, 334–348. \n20 V. Goellner, V. Armel, A. Zitolo, E. Fonda and F. Jaouen, J. Electrochem. Soc., 2015, 162, H403–H414. \n21 J. A. Varnell, C. Edmund, C. E. Schulz, T. T. Fister, R. T. Haasch, J. Timoshenko, A. I. Frenkel and A. A. Gewirth, Nat. Commun., 2016, 7, 12582. \n22 G. Zhang, R. Chenitz, M. Lef\\`evre, S. Sun and J.-P. Dodelet, Nano Energy, 2016, 29, 111–125. \n23 C. H. Choi, C. Baldizzone, G. Polymeros, E. Pizzutilo, O. Kasian, A. K. Schuppert, N. Ranjbar Sahraie, M.-T. Sougrati, K. J. J. Mayrhofer and F. Jaouen, ACS Catal., 2016, 6, 3136–3146. \n24 C. H. Choi, C. Baldizzone, J.-P. Grote, A. K. Schuppert, F. Jaouen and K. J. J. Mayrhofer, Angew. Chem., Int. Ed., 2015, 54, 12753–12757. \n25 J. Herranz, F. Jaouen, M. Lefevre, U. I. Kramm, E. Proietti, J.-P. Dodelet, P. Bogdanoff, S. Fiechter, I. Abs-Wurmbach and P. Bertrand, J. Phys. Chem. C, 2011, 115, 16087–16097. \n26 C. H. Choi, H.-K. Lim, M. W. Chung, G. Chon, N. Ranjbar Sahraie, A. Altin, M.-T. Sougrati, L. Stievano, H. S. Oh, E. S. Park, F. Luo, P. Strasser, G. Drazˇi´c, K. J. J. Mayrhofer, H. Kim and F. Jaouen, Energy Environ. Sci., 2018, DOI: 10.1039/C8EE01855C. \n27 S.-F. Kang and H.-M. Chang, Water Sci. Technol., 1997, 36, 215–222. \n28 T. Sun, Q. Wu, R. Che, Y. Bu, Y. Jiang, Y. Li, L. Yang, X. Wang and Z. Hu, ACS Catal., 2015, 5, 1857–1862. \n29 R. Zhou, M. Jaroniec and S. Z. Qiao, ChemCatChem, 2015, 7, 3808–3817. \n30 S. Ma, G. A. Goenaga, A. V. Call and D. J. Liu, Chem. – Eur. J., 2011, 17, 2063–2067. \n31 L. Chong, G. A. Goenaga, K. Williams, H. M. Barkholtz, L. R. Grabstanowicz, J. A. Brooksbank, A. B. Papandrew, R. Elzein, R. Schlaf and T. A. Zawodzinski Jr, ChemElectroChem, 2016, 3, 1541–1545. \n32 Y. Han, Y.-G. Wang, W. Chen, R. Xu, L. Zheng, J. Zhang, J. Luo, R.-A. Shen, Y. Zhu and W.-C. Cheong, J. Am. Chem. Soc., 2017, 139, 17269–17272. \n33 A. Kong, Y. Kong, X. Zhu, Z. Han and Y. Shan, Carbon, 2014, 78, 49–59. \n34 H.-W. Liang, W. Wei, Z.-S. Wu, X. Feng and K. Mu¨llen, J. Am. Chem. Soc., 2013, 135, 16002–16005. \n35 L. Osmieri, A. H. Monteverde Videla, P. Oc´on and S. Specchia, J. Phys. Chem. C, 2017, 121, 17796–17817. \n36 S.-T. Chang, H.-C. Huang, H.-C. Wang, H.-C. Hsu, J.-F. Lee and C.-H. Wang, Int. J. Hydrogen Energy, 2014, 39, 934–941. \n37 X. X. Wang, D. A. Cullen, Y. T. Pan, S. Hwang, M. Wang, Z. Feng, J. Wang, M. H. Engelhard, H. Zhang and Y. He, Adv. Mater., 2018, 30, 1706758. \n38 B. You, N. Jiang, M. Sheng, W. S. Drisdell, J. Yano and Y. Sun, ACS Catal., 2015, 5, 7068–7076. \n39 Q. Cheng, S. Han, K. Mao, C. Chen, L. Yang, Z. Zou, M. Gu, Z. Hu and H. Yang, Nano Energy, 2018, 52, 485–493. \n40 X. X. Wang, S. Hwang, Y.-T. Pan, K. Chen, Y. He, S. Karakalos, H. Zhang, J. S. Spendelow, D. Su and G. Wu, Nano Lett., 2018, 18, 4163–4171. \n41 B. Y. Xia, Y. Yan, N. Li, H. B. Wu, X. W. D. Lou and X. Wang, Nat. Energy, 2016, 1, 15006. \n42 J. Gao, K. Ye, L. Yang, W.-W. Xiong, L. Ye, Y. Wang and Q. Zhang, Inorg. Chem., 2013, 53, 691–693. \n43 I. S. Amiinu, X. Liu, Z. Pu, W. Li, Q. Li, J. Zhang, H. Tang, H. Zhang and S. Mu, Adv. Funct. Mater., 2018, 28, 1704638. \n44 T. Xing, Y. Lou, Q. Bao and J. Chen, CrystEngComm, 2014, 16, 8994–9000. \n45 Y. Pan, D. Heryadi, F. Zhou, L. Zhao, G. Lestari, H. Su and Z. Lai, CrystEngComm, 2011, 13, 6937–6940. \n46 J. Zhao, Y. Wang, W. Dong, Y. Wu, D. Li, B. Liu and Q. Zhang, Chem. Commun., 2015, 51, 9479–9482. \n47 G. Yang, F. Li, L. Wang, K. H. Row, H. Liu, L. Bai, W. Cao and T. Zhu, Chromatographia, 2008, 68, 27–31. \n48 Q. Lai, Y. Zhao, Y. Liang, J. He and J. Chen, Adv. Funct. Mater., 2016, 26, 8334–8344. \n49 M. S. Bakshi, Cryst. Growth Des., 2015, 16, 1104–1133. \n50 Y. Chang, F. Hong, C. He, Q. Zhang and J. Liu, Adv. Mater., 2013, 25, 4794–4799. \n51 M. Jiang, X. Cao, D. Zhu, Y. Duan and J. Zhang, Electrochim. Acta, 2016, 196, 699–707. \n52 A. Sadezky, H. Muckenhuber, H. Grothe, R. Niessner and U. P¨oschl, Carbon, 2005, 43, 1731–1742. \n53 E. Proietti, F. Jaouen, M. Lef\\`evre, N. Larouche, J. Tian, J. Herranz and J.-P. Dodelet, Nat. Commun., 2011, 2, 416. \n54 S. Liu, C. Deng, L. Yao, H. Zhong and H. Zhang, J. Power Sources, 2014, 269, 225–235. \n55 T. E. Westre, P. Kennepohl, J. G. DeWitt, B. Hedman, K. O. Hodgson and E. I. Solomon, J. Am. Chem. Soc., 1997, 119, 6297–6314. \n56 W. Liu, L. Zhang, W. Yan, X. Liu, X. Yang, S. Miao, W. Wang, A. Wang and T. Zhang, Chem. Sci., 2016, 7, 5758–5764. \n57 D. Xu, P. Lu, P. Dai, H. Wang and S. Ji, J. Phys. Chem. C, 2012, 116, 3405–3413. \n58 H. Jing, X. Song, S. Ren, Y. Shi, Y. An, Y. Yang, M. Feng, S. Ma and C. Hao, Electrochim. Acta, 2016, 213, 252–259. \n59 H. Zhang, H. Osgood, X. Xie, Y. Shao and G. Wu, Nano Energy, 2017, 31, 331–350. \n60 Y. Shao, S. Zhang, M. H. Engelhard, G. Li, G. Shao, Y. Wang, J. Liu, I. A. Aksay and Y. Lin, J. Mater. Chem., 2010, 20, 7491–7496. \n61 K. X. Liu, G. Wu and G. F. Wang, J. Phys. Chem. C, 2017, 121, 11319–11324. \n62 J. K. Norskov, J. Rossmeisl, A. Logadottir, L. Lindqvist, J. R. Kitchin, T. Bligaard and H. Jonsson, J. Phys. Chem. B, 2004, 108, 17886–17892. \n63 G. Henkelman, B. P. Uberuaga and H. Jonsson, J. Chem. Phys., 2000, 113, 9901–9904. \n64 K. X. Liu, S. Kattel, V. Mao and G. F. Wang, J. Phys. Chem. C, 2016, 120, 1586–1596. \n65 S. Kattel and G. F. Wang, J. Phys. Chem. Lett., 2014, 5, 452–456. \n66 S. Gupta, S. Zhao, X. X. Wang, S. Hwang, S. Karakalos, S. V. Devaguptapu, S. Mukherjee, D. Su, H. Xu and G. Wu, ACS Catal., 2017, 7, 8386–8393. \n67 S. Gupta, L. Qiao, S. Zhao, H. Xu, Y. Lin, S. V. Devaguptapu, X. Wang, M. T. Swihart and G. Wu, Adv. Energy Mater., 2016, 6, 1601198. \n68 G. Wu, K. Artyushkova, M. Ferrandon, A. J. Kropf, D. Myers and P. Zelenay, ECS Trans., 2009, 25, 1299–1311. \n69 M. Ferrandon, X. Wang, A. J. Kropf, D. J. Myers, G. Wu, C. M. Johnston and P. Zelenay, Electrochim. Acta, 2013, 110, 282–291. " + }, + { + "id": "10.1002_adfm.201806220", + "DOI": "10.1002/adfm.201806220", + "DOI Link": "http://dx.doi.org/10.1002/adfm.201806220", + "Relative Dir Path": "mds/10.1002_adfm.201806220", + "Article Title": "Highly Stretchable, Elastic, and Ionic Conductive Hydrogel for Artificial Soft Electronics", + "Authors": "Zhou, Y; Wan, CJ; Yang, YS; Yang, H; Wang, SC; Dai, ZD; Ji, KJ; Jiang, H; Chen, XD; Long, Y", + "Source Title": "ADVANCED FUNCTIONAL MATERIALS", + "Abstract": "High conductivity, large mechanical strength, and elongation are important parameters for soft electronic applications. However, it is difficult to find a material with balanced electronic and mechanical performance. Here, a simple method is developed to introduce ion-rich pores into strong hydrogel matrix and fabricate a novel ionic conductive hydrogel with a high level of electronic and mechanical properties. The proposed ionic conductive hydrogel is achieved by physically cross-linking the tough biocompatible polyvinyl alcohol (PVA) gel as the matrix and embedding hydroxypropyl cellulose (HPC) biopolymer fibers inside matrix followed by salt solution soaking. The wrinkle and dense structure induced by salting in PVA matrix provides large stress (1.3 MPa) and strain (975%). The well-distributed porous structure as well as ion migration-facilitated ion-rich environment generated by embedded HPC fibers dramatically enhances ionic conductivity (up to 3.4 S m(-1), at f = 1 MHz). The conductive hybrid hydrogel can work as an artificial nerve in a 3D printed robotic hand, allowing passing of stable and tunable electrical signals and full recovery under robotic hand finger movements. This natural rubber-like ionic conductive hydrogel has a promising application in artificial flexible electronics.", + "Times Cited, WoS Core": 771, + "Times Cited, All Databases": 801, + "Publication Year": 2019, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000454703900029", + "Markdown": "# Highly Stretchable, Elastic, and Ionic Conductive Hydrogel for Artificial Soft Electronics \n\nYang Zhou, Changjin Wan, Yongsheng Yang, Hui Yang, Shancheng Wang, Zhendong Dai, Keju Ji, Hui Jiang, Xiaodong Chen,\\* and Yi Long\\* \n\nHigh conductivity, large mechanical strength, and elongation are important parameters for soft electronic applications. However, it is difficult to find a material with balanced electronic and mechanical performance. Here, a simple method is developed to introduce ion-rich pores into strong hydrogel matrix and fabricate a novel ionic conductive hydrogel with a high level of electronic and mechanical properties. The proposed ionic conductive hydrogel is achieved by physically cross-linking the tough biocompatible polyvinyl alcohol (PVA) gel as the matrix and embedding hydroxypropyl cellulose (HPC) biopolymer fibers inside matrix followed by salt solution soaking. The wrinkle and dense structure induced by salting in PVA matrix provides large stress (1.3 MPa) and strain $(975\\%)$ . The well-distributed porous structure as well as ion migration–facilitated ion-rich environment generated by embedded HPC fibers dramatically enhances ionic conductivity (up to $3.45m^{-1}$ , a $t f=1M H z)$ . The conductive hybrid hydrogel can work as an artificial nerve in a 3D printed robotic hand, allowing passing of stable and tunable electrical signals and full recovery under robotic hand finger movements. This natural rubber-like ionic conductive hydrogel has a promising application in artificial flexible electronics. \n\n# 1. Introduction \n\nStretchable and flexible electronics have received increasing attention due to their unique advantages and wide applications in the fields of biomedicine, soft robotics, energy harvesting, etc.[1] For the biological applications, the stretchable materials need to integrate superior performance of both high conductivity and good mechanical properties so that they can be suitable for the long-time biocompatible use with human bodies, such as skin, muscle, heart, or brain.[2] In addition to the demands of high conductivity and good stretchability, some important parameters should also be carefully considered for a specific application; for example, the conductors may need to operate at high frequencies, be biocompatible, and remain conductive while undergoing high expansions,[3] whereas the existing electronic conductors struggle to meet these demands. It is still a challenge to fabricate such systems with desirable multiple functions. \n\nHydrogel is a kind of 3D polymeric network that can swell in water.[4] The polymer networks of the hydrogel make it solid-like, while the aqueous phase of the hydrogel enables fast diffusion of the carriers, which indicates that the hydrogels have liquid-like transport properties. Due to these good attributes, many hydrogels are biocompatible and soft, making them perfect candidates for applications of biocompatible materials,[5] drug delivery,[6] energy saving,[7] medical dressings,[8] tissue engineering,[9] etc. However, the poor mechanical strength and strain of hydrogel seriously limit its potential applications.[10] Recently, toughening hydrogels were fabricated to increase the stretchability and toughness by adding nanoparticles[11] and double networking.[12,13] The mechanical properties of toughening hydrogels were improved. However, the improvements are too low to reach the level of natural rubbers.[14] It is necessary to increase the mechanical properties further as well as retain high conductivity so that we can make the hydrogels work with soft human tissues, such as muscle and skin.[15] \n\nWith increase of the cross-link density, the mechanical strength and elasticity of the hydrogels will increase,[16] but the resistance of the ion migration will also increase,[17] so it is hard to retain both high mechanical strength and high ionic conductivity at the same time. The ionic conductive gel is a possible solution since it can retain high conductivity via ion transport, while the high toughness can be provided by the large strain, but the mechanical strength and elasticity are relatively low.[18] For example, Odent et al. fabricated an ionic conductive gel with high conductivity of $2.9\\mathrm{~S~m}^{-1}$ and a large strain of $425\\%$ , but the tensile strength and elasticity were relatively low (0.007 MPa and $5\\ \\mathrm{kPa}$ , respectively).[19] However, for real commercial applications, high mechanical strength is required for conductive hydrogels in stretchable sensor and artificial tissue applications to bear enormous mechanical loads and avoid unexpected fractures.[13] At the same time, the mechanical properties of designed materials should mimic tissue without compromising its high conductivity because the mismatch between artificial materials and tissues may cause further scarring by immunological responses.[20] Thus, the balanced mechanical strength, elongation, and elasticity to human tissue with high conductivity are important for stretchable soft artificial materials, but hard to be achieved at the same time. \n\nIn this work, we demonstrate a novel method to fabricate a natural rubber-like ionic conductive hydrogel. Biocompatible hydroxypropyl cellulose (HPC)[21]–embedded physically crosslinked polyvinyl alcohol (PVA) hydrogel[22] was infiltrated into the sodium chloride $\\mathrm{(NaCl)}$ solution and formed an HPC/PVA ionic conductive hydrogel. The mechanical properties and ionic conductivities of this natural rubber-like HPC/PVA ionic conductive hydrogel were easily tuned to match different soft tissue requirements by varying the concentration of HPC fibers (from 0 to $3.75\\ \\mathrm{wt\\%}$ ) and soaking level of $\\mathrm{\\DeltaNaCl}$ solution (from 1 to $5\\mathrm{~M~}$ solution). This natural rubber-like HPC/PVA hydrogel is biocompatible, stretchable (fully recover under $100\\%$ strain), and combines tunable mechanical strength (from 0.6 to $4\\mathrm{MPa}$ tensile strength) and elasticity (from 15 to $900~\\mathrm{kPa}$ ), large strain (up to $975\\%$ , and high ionic conductivity (up to $3.4\\mathrm{~\\AA~}\\mathrm{m}^{-1}$ at $f{=}1~\\mathrm{MHz})}$ . In this hydrogel, the stiff and dense PVA hydrogel was selected to provide large mechanical strength after soaking in a salt solution. The embedded HPC fibers enhanced ionic conductivity while tuning the mechanical properties at the same time. We demonstrated the natural rubber-like HPC/PVA ionic conductive hydrogel as artificial ligament and nerve in a 3D printed robotic hand. When strain increased from 0 to $100\\%$ , the alternative current (AC) signal changes were negligible at high frequency, which means it can transfer steady AC signal under expansion and could act as a monitor for muscle movement. This ionic conductive hydrogel can also work together with a pressure sensor as artificial nerve to transfer touch signal (direct current signal) with different finger positions (different strains), which will generate different touch signals. \n\nattract both $\\mathrm{{Na^{+}}}$ and $\\mathrm{Cl^{-}}$ ions in solution. In order to synthesize rubber-like ionic conductive HPC/PVA hydrogel, physically cross-linked PVA hydrogels with embedded HPC fibers are first fabricated. The embedded HPC fibers inside PVA hydrogel matrix will decrease the cross-linking density of PVA hydrogel matrix and generate water-rich porous area. After soaking HPC/PVA hybrid hydrogels in NaCl solution, $\\mathrm{{Na^{+}}}$ and $\\mathrm{Cl^{-}}$ ions will diffuse into HPC/PVA hybrid hydrogels and water molecules will diffuse out from HPC/PVA hydrogels to reach balanced ionic concentration. At the same time, HPC fibers will attract more ions[24] to water-rich porous area. The HPC/PVA hybrid hydrogels will become conductive due to the absorption of $\\mathrm{Na^{+}}$ and $\\mathrm{Cl^{-}}$ ions. The mechanical properties of HPC/PVA ionic conductive hydrogel are supposed to be enhanced because of the salting out effect of $\\mathrm{{Na^{+}}}$ and $\\mathrm{Cl^{-}}$ ions. Both mechanical properties and ionic conductivity are expected to be tuned by changing the soaking level from 1 to $5\\mathrm{~M~}$ . \n\nFigure  1 shows the schematic illustration, microstructure, and microscope photos of pure PVA hydrogel, HPC/PVA hybrid hydrogel, and HPC/PVA ionic conductive hydrogel after soaking in NaCl solution. Pure PVA hydrogel exhibits a uniform structure (Figure 1a), and no porous structure or defects can be observed, as seen in Figure 1a(iii). Once HPC short-chain fibers were introduced into the PVA hydrogel system, the fibers in HPC/PVA hydrogel were well distributed and generated water-rich pores (Figure 1b(i)), which is due to dispersion of HPC short chains in between PVA polymer chains (Figure 1b(ii)) without interaction (Figure S1 in the Supporting Information shows Fourier transform infrared (FTIR) spectra of commercial PVA powders, HPC fibers, and dried HPC/PVA hydrogel; no new significant peaks were generated after HPC/PVA hydrogel was obtained). The pores were suggested to be filled with HPC solution, as HPC solution was kept in liquid state during the HPC/PVA gelation process (Figure S2, Supporting Information). As shown in Figure 1b(iii), the waterrich porous area can be observed inside the uniform PVA hydrogel matrix. With the increase in HPC content, number of pores also increase (Figure S3, Supporting Information). After soaking HPC/ PVA hydrogel in NaCl solution, the pores in HPC/PVA ionic conductive hydrogel became rich in $\\mathrm{{Na^{+}}}$ and $\\mathrm{Cl^{-}}$ ions, due to ion diffusion and the attraction of HPC chains to salt ions[24] (Figure 1c(i) and (ii)). The porous structure can be straightly observed through microscope (Figure 1c(iii)). The whole hydrogel shrunk (Figure S4, Supporting Information) due to the salting out effect; meanwhile, PVA polymer chains became densely packed with wrinkle structure generated (Figure S5, Supporting Information). Figure S3a and b in the Supporting Information shows the height distribution detected by optical surface profiler of HPC/PVA hydrogel before and after soaking in NaCl solution (5 m), respectively. Wrinkle structure looks like “mountain ridge” that can be observed in Figure S4b in the Supporting Information. \n\n# 2. Results and Discussion \n\n# 2.1. Synthetic Strategy and Mechanism Investigation \n\nConsidering the good mechanical strength and high waterretaining ability as well as good biocompatibility and flexibility in artificial soft tissue applications,[23] PVA hydrogel is carefully selected to fabricate the new ionic conductive hydrogel. HPC fiber is selected to be embedded into PVA hydrogel to enhance the ionic concentration after soaking in NaCl solution since it can \n\n# 2.2. Mechanical Properties of HPC/PVA Ionic Conductive Hydrogel \n\nThe $\\mathrm{HPC}/\\mathrm{PVA}_{x}$ composite hydrogels were obtained with different PVA amounts $_x$ refers to the weight percentage of PVA compared with a solution, i.e., $8\\%$ , $16\\%$ , and $24\\%$ ) and a fixed HPC weight percentage at $2.5~\\mathrm{wt\\%}$ . Soaked in NaCl solution $(3\\mathrm{~\\textmu~},\\ 24\\mathrm{~h})$ , the mechanical strength of composite hydrogels increases with increase in $x$ , while $\\mathrm{HPC}/\\mathrm{PV}\\mathrm{A}_{16\\%}$ ionic conductive hydrogel provides the highest strain and toughness (Figure 3a) as HPC amount is fixed at $2.5\\mathrm{\\wt\\%}$ (weight percentage of HPC compared with solution). Compared with pure $\\mathrm{PVA_{16\\%}}$ ionic conductive hydrogel of same PVA/ $_\\mathrm{H}_{2}\\mathrm{O}$ ratio and soaking level, $\\mathrm{HPC}/\\mathrm{PV}\\mathrm{A}_{16\\%}$ ionic conductive hydrogel exhibits more suitable tensile strength, elasticity, and toughness (Figure  2a). The extremely large Young’s modulus $(900~\\mathrm{kPa})$ of pure $\\mathrm{PVA_{16\\%}}$ ionic conductive hydrogel limited its usage in artificial tissue applications, due to the elasticity mismatch with human tissue (around $5{\\mathrm{-}}1000{\\mathrm{~kPa}}_{\\mathrm{.}}$ ).[15] According to Figure 2a, HPC plays a vital role in this ionic conductive hydrogel, which successfully increases the strain and decreases Young’s modulus in comparison to pure PVA hydrogel. \n\n![](images/ebd93f62e0065abfc691e226faa74c78a7c9e3a180b44db2c4f8d04cc3e5e7aa.jpg) \nFigure 1.  i) Schematic design, ii) microstructure, and iii) microscope image, respectively, of a) pure PVA $(76\\mathrm{wt\\%})$ hydrogel, where pure PVA hydrogel has uniform structure, b) HPC/PVA $(2.5/16~\\mathrm{wt\\%})$ hybrid hydrogel, where HPC fibers were dispersed inside PVA hydrogel matrix and water-rich pores were generated around HPC fibers inside PVA hydrogel matrix, and c) HPC/PVA $(2.5/16~\\mathrm{wt}\\%)$ ionic conductive hydrogel (soaked in 5 m NaCl solution), where ${\\mathsf{N a}}^{+}$ and ${\\mathsf{C l}}^{-}$ ions were attracted by HPC fibers through ion–dipole interaction and pores in HPC/PVA ionic conductive hydrogel were retained. The scale bar of microscope images is $100\\upmu\\mathrm{m}$ . \n\nHPC/ $\\mathrm{PVA_{16\\%}}$ hydrogel was selected to fabricate ionic conductive hydrogel (HPC/PVA hydrogel represents $\\mathrm{HPC}/\\mathrm{PV}\\mathrm{A}_{16\\%}$ hydrogel in this work). By adjusting the concentration of NaCl solution, mechanical properties of the ionic conductive hydrogels were facilely tuned (Figure S6, Supporting Information). Figure 2b and c shows that after the ionic conductive hydrogel was soaked in different concentrations of NaCl solution from 1 to $5\\mathrm{~\\textmu~}$ , the largest tensile strength reaches $1.3\\pm0.2\\mathrm{{\\MPa}}$ after soaking in $5\\mathrm{~M~}$ solution, which was 13 times higher than that of the original hydrogel without soaking $(0.1\\ \\mathrm{MPa})$ . At the same time, the largest strain reaches $8.6\\pm1.2$ after soaking in $2\\ensuremath{\\mathrm{~M~}}\\ensuremath{}\\ensuremath{\\mathrm{NaCl}}$ solution, which is three times higher than the original strain. HPC/PVA ionic conductive hydrogel exhibited a suitable elastic modulus from $95.8\\pm12.1$ to $586.7\\pm14.9\\mathrm{{kPa}}$ (Figure 2d). The toughness dramatically increased 42 times from $0.139\\pm0.1$ MJ $\\mathbf{m}^{-3}$ for $\\mathrm{HPC}/\\mathrm{PV}\\mathrm{A}_{16\\%}$ original hydrogel to $5.85\\pm0.8$ MJ $\\mathbf{m}^{-3}$ after soaking in $3\\mathrm{~\\textmu~}$ solution (Figure 2e) and this particular ionic conductive hydrogel was further demonstrated to withstand various deformations such as elongation, knotting, and compression, which exhibits both superior stiffness and high toughness (Figure $2\\mathrm{f-h})$ ). Notably, the ionic conductive hydrogel could recover to its original shape after removing pressure, indicating its outstanding shaperecovery performance (Figure 2h). Due to the high mechanical strength, this $2\\times5$ mm ionic conductive hydrogel could bear $2.5~\\mathrm{kg}$ weight as shown in Figure S7 in the Supporting Information without perceptible crack or fracture. \n\n![](images/903c837d5b6ba4dff47cc48f21cb264c5470dddec8e504930282adc08cf63e01.jpg) \nFigure 2.  a) Tensile curves of HPC/PVA hydrogel with different PVA $w t\\%$ and pure PVA hydrogel as reference at $3\\mathrm{~M~}$ soaking level. b) Tensile strength, c) strain, d) Young’s modulus, and e) toughness of $H P C/P V/A_{16\\%}$ ionic conductive hydrogel with different ionic concentrations from 1 to $5\\mathsf{\\Omega}_{\\mathsf{M}}$ f) Stretching, g) knotting, and h) compression of $H P C/P V/A_{76\\%}$ ionic conductive hydrogel. \n\nThe remarkable improvement of mechanical properties of HPC/PVA ionic conductive hydrogel before and after soaking was mainly provided by PVA matrix, which could be ascribed to three possible reasons. First, as depicted in Figure 1, the salting out effect decreases the volume of HPC/PVA hydrogel (Figure S4, Supporting Information), which directly increases the density of the PVA matrix. Second, the wrinkle morphology (Figure S5b, Supporting Information) due to the shrinkage enables the ionic conductive hydrogels to exhibit larger strain than the original HPC/PVA hydrogel under tensile stress to toughen the ionic conductive hydrogels. Figure S8 in the Supporting Information shows the scanning electron microscopy (SEM) image of freeze-dried HPC/PVA hydrogel after soaking in NaCl solution: a large area of wrinkle structure can be observed (NaCl crystals observable on the cutting surface after freeze drying). The increase of microcrystallites in HPC/PVA hydrogel after soaking is the third potential reason of toughness enhancement. Figure S9 in the Supporting Information shows the X-ray diffraction (XRD) spectra of HPC/PVA and HPC/PVA ionic conductive hydrogels soaked in different concentrations of NaCl solution and the peaks at $19^{\\circ}$ represent the microcrystallites of PVA hydrogel.[25] As the NaCl concentration increases, the intensity of microcrystallite peaks increases, which may enhance the toughness of HPC/PVA ionic conductive hydrogel. \n\n# 2.3. Electrical Properties of HPC/PVA Ionic Conductive Hydrogel \n\nThe conductivity of HPC/PVA ionic conductive hydrogel was enhanced by introducing a porous structure by embedding second HPC network compared with pure PVA ionic conductive hydrogel. As HPC content increases from 0 to $3.75\\ \\mathrm{wt\\%}$ ionic conductivity increases from 1.7 to $3.4~\\mathrm{S~m}^{-1}$ $\\mathrm{\\Delta}f{=}1~\\mathrm{\\DeltaMHz}$ NaCl solution soaking level is $5~\\mathrm{~M~}$ ) (Figure  3a). The morphology of the HPC/PVA ionic conductive is finely tuned by using different concentrations of HPC. Higher HPC concentration implies more pores in the PVA network, which can be confirmed from the optical microscope (Figure S2 in the Supporting Information shows that the pore distribution in ${\\mathrm{HPC}}/$ PVA hydrogel increases as HPC content increases from 0 to $3.75~\\mathrm{wt\\%}$ ). Therefore, HPC/PVA ionic conductive hydrogel with a higher concentration of HPC possesses more pores, which would absorb more ions and provide more space to facilitate ion migration.[26] These pores endow the hydrogel with high ionic conductivity while weakening the mechanical properties (Figure S10, Supporting Information) due to the introduction of pores (defects). As a compromised result, HPC/PVA ionic conductive hydrogel with $2.5~\\mathrm{wt\\%}$ HPC is selected in this work to analyze soaking level effect, considering the relatively high ionic conductivity up to $2.6\\mathrm{~S~m^{-1}}$ , as well as suitable mechanical properties $/1.3\\ \\mathrm{MPa}$ tensile strength, $520\\%$ strain, and $590\\mathrm{kPa}$ Young’s modulus). As shown in Figure 3b, HPC/ PVA ionic conductive hydrogels $(2.5~\\mathrm{wt\\%}$ HPC) are sensitive to strain with DC applied and the gauge factor increases as strain increases from 0 to $400\\%$ . At the same time, with increasing soaking level, the gauge factor of hydrogels decreases. \n\nNext, the conductive properties of the ionic conductive hydrogel under AC signal were investigated (Figure 3c). The conductivity increases with increased frequency at the same soaking level. At the same time, the conductivity also increases with the increased soaking level at a fixed frequency, due to the higher ionic concentration. Compared with pure PVA hydrogel, the electronic conductivity of HPC/PVA ionic hydrogel at same soaking level is nearly doubled (2.6 vs $1.3\\mathrm{~S~m}^{-1}$ at $f{=}1~\\mathrm{MHz})}$ ). As shown in the energy-dispersive X-ray spectroscopy (EDX) results of $\\mathrm{{Na^{+}}}$ and $\\mathrm{Cl^{-}}$ in both HPC/PVA (Figure S11a and b, Supporting Information) and pure PVA (Figure S11c and d, Supporting Information) ionic conductive hydrogels after freeze drying, ions were uniformly distributed in both hydrogels, and the content of both $\\mathrm{Na^{+}}$ and $\\mathrm{Cl^{-}}$ ions in HPC/PVA hydrogel was higher than that of pure PVA hydrogel. Such high conductivity of the hydrogel under the alternating electric field could enable the high efficiency of electric signal transmission in soft electronic devices in artificial tissue. \n\n![](images/5675c02ae037a240548b4d10f6ad468963bbee362468c144a5c9a7933dc65824.jpg) \nFigure 3.  a) Ionic conductivity of HPC/PVA ionic conductive hydrogel increases with increasing HPC content, b) gauge factor of HPC/PVA ionic conductive hydrogel increases with increase of strain from 0 to $400\\%$ or decrease of soaking level from 5 to 1 m, c) ionic conductivity of HPC/PVA ionic conductive hydrogel increases with increase of both AC frequency and soaking level, and d) relative change in hydrogel resistance of AC; the insert photos are HPC/PVA ionic conductive hydrogels at 0 and $100\\%$ strain. \n\nTo study the AC resistance characteristics under strain, a simple test circuit was used as shown in Figure S12 in the Supporting Information. One ionic conductive hydrogel film $(5.5~\\mathrm{cm}\\times1.2~\\mathrm{cm}\\times0.2~\\mathrm{cm})$ ) was connected with a resistor $(R_{1}=4.67\\mathrm{~k}\\Omega)$ in series. $1.0\\mathrm{~V~}$ sigmoidal signals $(V_{\\mathrm{I}})$ were applied on the hydrogel wire and the resistor, then the voltage response on the hydrogel $(V_{\\mathrm{O}})$ was measured as an output. By varying the strain applied on hydrogel from 0 to $100\\%$ , slight changes in voltage output could be observed with AC signals of both $1\\mathrm{kHz}$ (human muscle electronic signal frequency ranges from $10^{-1}$ to $10^{3}~\\mathrm{Hz})^{[27]}$ and $1~\\mathrm{MHz}$ , as shown in Figure S13a and b in the Supporting Information, respectively. The voltage changes could be considered as the changes in resistance when loading a strain on the hydrogel and the resistance of the hydrogel could be estimated by the following equation: \n\n$R_{\\mathrm{gel}}=R_{1}\\times U_{\\mathrm{O}}/(U_{\\mathrm{I}}-U_{\\mathrm{O}})$ . The relative change in resistance was plotted as a function of strain as shown in Figure 3d. A similar trend could be found with the two frequencies, in which low resistance change could be observed by increasing the strains. Low gauge factors of 0.947 and 0.984 were achieved for $1\\mathrm{MHz}$ and $1\\mathrm{kHz}$ signals, respectively (Figure S14, Supporting Information). The mechanical properties make the HPC/PVA ionic conductive hydrogels promising for artificial tissue applications. \n\nAccording to the test results of mechanical and electrical properties, both HPC concentration and NaCl soaking level will affect the mechanical and electrical properties of HPC/PVA ionic conductive hydrogels. As HPC concentration increased, both tensile strength and Young’s modulus of HPC/PVA ionic conductive hydrogels were reduced, while ionic conductivity was increased at a fixed soaking level. Once the NaCl solution soaking level increased, the mechanical strength, elasticity, and conductivity were increased. At the same time, water content reduced with increasing soaking level (Figure S15a, Supporting Information), which resulted in the reduction of conductivity rate (Figure S15b, Supporting Information). \n\n# 2.4. Demonstration of HPC/PVA Ionic Conductive Hydrogel as Artificial Tissue \n\nCompared with recently generated ionic conductive gels,[19,28] this new HPC/PVA ionic conductive hydrogel combined high ionic conductivity and balanced tensile strength and strain, as shown in Figure 4. HPC/PVA ionic conductive hydrogel with $5\\mathrm{~M~NaCl}$ soaking level gives the best electronic conductivity, and HPC/PVA ionic conductive hydrogel with $3\\mathrm{~M~NaCl}$ soaking level showed the best mechanical property. Such results indicate that our ionic conductive hydrogel possesses high potential for the tissue monitoring and replacement. Furthermore, to well match other soft functional components, Young’s modulus and toughness are other important parameters. Normally Young’s modulus and toughness of hydrogel-based artificial tissue range from 10 to $1750\\mathrm{kPa}$ and 0.1 to $12\\mathrm{~M~}$ J $\\mathrm{m}^{-3}$ ,[29] respectively. According to Figure S16 in the Supporting Information, both HPC/PVA ionic conductive hydrogels with 3 and $5\\mathrm{~M~}$ soaking levels have suitable Young’s modulus (250 and $650~\\mathrm{kPa}$ ) and large toughness (6.7 and 5.8  MJ $\\mathbf{m}^{-3}$ ) compared with other reported artificial tissue hydrogels. HPC/PVA ionic conductive hydrogel with $5\\mathrm{~M~NaCl}$ soaking level was selected to fabricate artificial tissues for the following demonstration due to its higher conductivity (Figure 4). \n\n![](images/31caa4ae3aac9758d21d91d0ff2e9be2a1f0e7ef9fda48529253d646428547eb.jpg) \nFigure 4.  Comparison of strain, stress, and conductivity of reported ionic conductive gels, including 1-ethyl-3-methylimidazolium dicyanamide/ poly(2-acrylamido-2-methyl-1-propanesulfonic acid) $([E M\\mid m][\\mathsf{D C A}]/$ PAMPS),[28a] ${\\mathsf{N a}}^{+}/$ acrylamide/[2-(Acryloyloxy)ethyl]trimethylammonium chloride $(\\mathsf{N a}^{+}/\\mathsf{A A}/\\mathsf{A E T A})$ ,[19] $\\mathsf{F e}^{3+}/\\mathsf{G}$ lycine (Gly) with abundant carboxylic groups incorporated into the PEG backbone/poly(acrylamide-coacrylic acid) $(\\mathsf{F e}^{3+}/$ PEG-Gly/PAMAA),[28c] 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl) amide/poly(styrene-b-ethylene oxideb-styrene) ([EMI][TFSA]/ABA),[28b] Li+/polyacrylamide-based gel $(\\mathsf{L i^{+}}/$ PAAm),[28d] and HPC/PVA ionic conductive hydrogel (3 and $5\\mathrm{~M~}$ ). \n\nThe HPC/PVA ionic conductive $5\\mathrm{~M~}$ hydrogel shows good selfrecovery at $100\\%$ strain (Figure 5a; Video S1, Supporting Information). As discussed above, the conductivity of this hydrogel is steady under strain from 0 to $100\\%$ . We further demonstrated this hydrogel as artificial ligament on a 3D printed robotic hand with steady $1\\ \\mathrm{kHz}$ AC at $10\\mathrm{~V~}$ with the circuitry (Figure S17, Supporting Information). This ionic conductive hydrogel with a length of $15\\mathrm{cm}$ was connected to the cathode of a light-emitting diode (LED), and copper wire was connected to the anode. Once the AC was applied, the light illuminated as shown in Figure 5b. With finger curving and the strain of hydrogel increasing up to $50\\%$ , negligible changes in the light brightness could be observed during finger movement (Video S2, Supporting Information). This artificial ligament is able to continuously transmit steady AC electronic signal without degradation of continuous finger movements, and such signal could be used to monitor the ligament condition regardless of mechanical deformations. The white dash line indicates the position of hydrogel wire that has been inserted inside the robotic finger. \n\nA robotic system was built (Figure S18, Supporting Information) to further demonstrate the robotic artificial nerve applications. This hydrogel and the pressure sensor were integrated and a LED was used as the indicator. The system was supplied with DC; if no pressure is applied to the pressure sensor, no current could be measured. Once the pressure sensor is pressed, a sharp and large current was detected at the beginning and then it decreased soon to a certain value (Figure 5c). Once the strain of the hydrogel was increased to $100\\%$ , the current responses show a similar trend to that of $0\\%$ strain, while obvious decreases in both the peak and steady state of currents could be observed, which is consistent with the discussion in Figure 3a. \n\n![](images/b787a036b2774ff5cace33db84bc21012070b476ee044e647d88160880c15692.jpg) \nFigure 5.  a) Self-recovery of HPC/PVA ionic conductive hydrogel, b) demonstration of hydrogel system on robotic hand with AC applied to transfer steady AC signal, c) response of hydrogel and pressure sensor integrated system when loading a 2 kPa pressure collected at different strains (0 and $50\\%)$ ), and d) demonstration of hydrogel/sensor system on robotic hand with DC applied. \n\nAs shown in Figure 5d, when no pressure is loaded on the pressure sensor, the whole system is open circuited. Therefore, the LED on the robot finger turns off (Figure 5d(ii)). Once the pressure sensor is touched with a human finger, which applies a certain level of pressure, the resistance of the sensor and the current through the artificial nerve are obviously reduced to trigger the LED (Figure 5d(iii)). This system can generate different touching signals with different finger positions (different hydrogel strains). \n\n# 3. Conclusion \n\nWe have fabricated a novel natural rubber-like ionic conductive hydrogel by infiltrating HPC fiber–embedded PVA hydrogel with NaCl solution. This hydrogel is biocompatible, stretchable (fully recover under $100\\%$ strain), and combines tunable mechanical strength (from 0.6 to $4\\mathrm{MPa}$ tensile strength), good elasticity (from 15 to $900~\\mathrm{kPa}$ ), large strain (up to $975\\%$ ), and high ionic conductivity (up to $3.4\\mathrm{~S~m}^{-1}$ at $f=1~\\mathrm{MHz}$ ). HPC fibers play a critical role in increasing the concentration of $\\mathrm{Na^{+}}$ and $\\mathrm{Cl^{-}}$ ions and provide large space for ion migration. To the best of our knowledge, the balanced mechanical strength, elongation, and elasticity of stretchable hydrogel with high conductivity are important for artificial tissue usage, but hard to be achieved at the same time. The ionic conductive hydrogel wire is successfully fabricated and embedded in a 3D printed robotic hand to be demonstrated as an artificial nerve, which enables passing of stable AC and tunable DC electrical signals as well as full recovery under robotic finger movement. Our design is versatile and adaptable to a variety of hydrogels and ionic liquids/solutions for soft and stretchable conductive gels. \n\n# 4. Experimental Section \n\nFabrication of HPC/PVA Ionic Conductive Conductor: Polyvinyl alcohol $(\\mathsf{M}\\mathsf{W}\\approx6\\mathsf{l}\\ 000$ , Sigma-Aldrich), hydroxypropyl cellulose $(\\mathsf{M}\\mathsf{M}\\approx\\mathsf{I}00\\ 000$ , $99\\%$ purification, Sigma-Aldrich), dimethyl sulfoxide (DMSO, analysis purification, Sigma-Aldrich), sodium chloride $(99\\%$ , Sigma-Aldrich), and deionized water $(78.2\\mathsf{M}\\Omega)$ were used without further purification. \n\nFirst, $0.9~\\mathsf{m L}$ of DMSO was added into $3m L$ of deionized water, followed by $0.1\\ \\mathsf{g}\\mathsf{H P C}$ , and the mixture was stirred for 10 min. Next, the mixture was heated up to $70^{\\circ}\\mathsf C$ using a water bath with further stirring until all HPC was fully dissolved. Then, $0.64\\ \\mathrm{g}$ PVA was added, and the mixture was heated up again to $90^{\\circ}\\mathsf{C}$ until all PVA powder was dissolved, and then heating and stirring were continued for $3h$ . Then the HPC/PVA solution was poured into a mold to cool down to room temperature for $\\rceil2\\mathrm{~h~}$ . At the same time, the cooling process eliminated the visible gas bubbles in solution due to stirring (Figure S19, Supporting Information). Then the HPC/PVA solution was frozen in fridge at $-20^{\\circ}\\mathsf C$ . It was taken out of the fridge after $12\\mathrm{~h~}$ of freezing and thawed for $3h$ . After three freeze–thaw cycles, a solid HPC/PVA hydrogel was obtained. By varying the PVA weight percentage, three kinds of ${\\mathsf{H P C}}/{\\mathsf{P V A}}_{x}$ hydrogels were produced (x refers to the weight percentage: $8\\%$ , $16\\%$ , and $24\\%$ ). Then ${\\mathsf{H P C}}/{\\mathsf{P V A}}_{x}$ hydrogel was soaked in NaCl solution (concentration from 1 to $5\\textmd{M}$ ) for $12\\ h$ (ion exchange reached equilibrium after soaking for \n\n$12\\mathrm{~h~}$ ; Table S1, Supporting Information) to generate ${\\mathsf{H P C}}/{\\mathsf{P V A}}_{x}$ ionic conductive hydrogel. Figure S20 in the Supporting Information shows the whole process to generate the PVA-based ionic conductive hydrogel. \n\nFabrication of Pressure Sensor: The pressure sensors were reported in our previous work.[30] Microstructured silver nanowire (AgNW)/ polydimethylsiloxane (PDMS) films were prepared by depositing an aqueous solution of AgNWs (Blue Nano) on silicon masters and allowing this to dry in air, and then casting a mixture of PDMS elastomer and cross-linker in 10:1 w/w ratio (Sylgard 184, Dow Corning) through spin coating $(7000~\\mathsf{r p m})$ . The elastomer mixture was degassed in a vacuum and cured at $90~^{\\circ}\\mathsf{C}$ for $\\textsf{l h}$ , then the films were sectioned by a scalpel and peeled off from the silicon master. The microstructured AgNW/PDMS film was then placed face-to-face with an interdigital gold electrode to form a resistive pressure sensor. \n\nMechanical Properties’ Characterization: The hydrogels were prepared in a rectangular shape $(3.2~\\mathsf{m m}\\times2.2~\\mathsf{m m}\\times25~\\mathsf{m m})$ for tensile testing. All measurements were taken with MTS C43 machine. A fixed rate of extension $(2\\ \\mathsf{m m}\\ \\mathsf{m i n^{-1}},$ ) was applied to all tensile testing. The nominal stress $(\\sigma)$ was calculated by dividing the applied force (F) by the crosssection area, and the nominal tensile strain $(\\varepsilon)$ was obtained by dividing stretched length $(\\Delta I)$ by the original length $(I_{0})$ . The elastic module was obtained from the stress–strain curve and the toughness was the total area under the stress–strain curve. The elastic modulus was calculated from the slope over $0{-}100\\%$ strain of the stress–strain curve. The toughness was calculated from the area of stress–strain curves. For recovery experiment, we prepared five groups of hydrogel samples: original, 10, 30, 60, and $300\\mathrm{~s~}$ . These samples were first extended to $100\\%$ strain and then placed for a different time for recovery. For loading–unloading tests, the dissipated energy was calculated by (1) \n\n$$\nU_{i}=\\int\\displaylimits_{\\mathrm{{loading}}}\\sigma\\mathrm{d}\\varepsilon-\\int\\displaylimits_{\\mathrm{{unloading}}}\\sigma\\mathrm{d}\\varepsilon\n$$ \n\nwhere $\\sigma$ and $\\varepsilon$ are tensile stress and strain during the cycles, respectively. \n\nElectrical Characterization: The AC signals were generated by function/ arbitrary waveform generator (Agilent 33220A) and were measured by an oscilloscope (Tektronix DPO5054B). The electrical measurements for control of robotic hands were characterized by Keithley 4200 semiconductor characterization system. \n\nOptical Characterization: JSM-5310 and FESEM-6340F were used to capture the SEM and EDX images of the samples, respectively. Before the experiment, samples were freeze-dried using liquid nitrogen before drying in a chamber for $72\\mathrm{{h}}$ . After that, the freeze-dried powder was examined using SEM. The FTIR data were collected by FTIR Perkin Elmer Spectrophotometer (Spectrum 400 FT-IR). The height distributions of HPC/PVA hydrogel were obtained by Zeiss Smartproof 5 optical surface profiler. All the microscope images were obtained through the Olympus BX51 microscope. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nY.Z. and C.W. contributed equally to this work. This research was supported by grants from the National Research Foundation, Prime Minister’s Office, Singapore under its Campus of Research Excellence and Technological Enterprise (CREATE) program, Ministry of Education (MOE) Tier One, RG124/16 and RG200/17. The characterization of SEM and XRD was performed at the Facility for Analysis Characterization Testing $\\&$ Simulation (FACTS) in Nanyang Technological University, Singapore. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\nbioelectronics, ionic conductive hydrogel, soft electronics, tissue engineering, tough hydrogel \n\nReceived: September 3, 2018 \nRevised: October 19, 2018 \nPublished online: November 14, 2018 \n\n[1]\t a) C.  Keplinger, J.-Y.  Sun, C. C.  Foo, P.  Rothemund, G. M. Whitesides, Z. Suo, Science 2013, 341, 984; b) M. L. Hammock, A.  Chortos, B. C. K.  Tee, J. B. H.  Tok, Z.  Bao, Adv. Mater. 2013, 25, 5997; c) M. Ramuz, B. C. K. Tee, J. B. H. Tok, Z. Bao, Adv. Mater. 2012, 24, 3223; d) D. Qi, Z. Liu, Y. Liu, Y. Jiang, W. R. Leow, M. Pal, S. Pan, H.  Yang, Y.  Wang, X.  Zhang, J.  Yu, B.  Li, Z.  Yu, W.  Wang, X.  Chen, Adv. Mater. 2017, 29, 1702800; e) G.  Chen, N.  Matsuhisa, Z.  Liu, D.  Qi, P.  Cai, Y.  Jiang, C.  Wan, Y.  Cui, W. R.  Leow, Z.  Liu, S.  Gong, K.-Q. Zhang, Y. Cheng, X. Chen, Adv. Mater. 2018, 30, 1800129. \n[2]\t a) D.-H.  Kim, N.  Lu, R.  Ma, Y.-S.  Kim, R.-H.  Kim, S.  Wang, J.  Wu, S. M.  Won, H.  Tao, A.  Islam, K. J.  Yu, T.-i.  Kim, R.  Chowdhury, M. Ying, L. Xu, M. Li, H.-J. Chung, H. Keum, M. McCormick, P. Liu, Y.-W.  Zhang, F. G.  Omenetto, Y.  Huang, T.  Coleman, J. A.  Rogers, Science 2011, 333, 838; b) T.  Sekitani, T.  Someya, Stretchable Electronics, Wiley-VCH, Weinheim 2012, 271. \n[3]\t a) R. Pelrine, R. Kornbluh, Q. Pei, J. Joseph, Science 2000, 287, 836; b) S. J.  Benight, C.  Wang, J. B. H.  Tok, Z.  Bao, Prog. Polym. Sci. 2013, 38, 1961. \n[4]\t a) B.  Hu, C.  Owh, P. L.  Chee, W. R.  Leow, X.  Liu, Y.-L.  Wu, P.  Guo, X. J.  Loh, X.  Chen, Chem. Soc. Rev. 2018; b) C.  Li, M. J.  Rowland, Y. Shao, T. Cao, C. Chen, H. Jia, X. Zhou, Z. Yang, O. A. Scherman, D. Liu, Adv. Mater. 2015, 27, 3298; c) A. V. Salvekar, W. M. Huang, R. Xiao, Y. S. Wong, S. S. Venkatraman, K. H. Tay, Z. X. Shen, Acc. Chem. Res. 2017, 50, 141; d) M. D. Konieczynska, M. W. Grinstaff, Acc. Chem. Res. 2017, 50, 151; e) F. Zhang, L. Xiong, Y. Ai, Z. Liang, Q. Liang, Adv. Sci. 2018, 5, 1800450. \n[5]\t a) C. Y. Tay, Y.-L. Wu, P. Cai, N. S. Tan, S. S. Venkatraman, X. Chen, L. P.  Tan, NPG Asia Mater. 2015, 7, e199; b) I.  Irwansyah, Y.-Q.  Li, W. Shi, D. Qi, W. R. Leow, M. B. Y. Tang, S. Li, X. Chen, Adv. Mater. 2015, 27, 648; c) Y.  Hu, W.  Guo, J. S.  Kahn, M. A.  Aleman-Garcia, I. Willner, Angew. Chem., Int. Ed. 2016, 55, 4210. \n[6]\t B. Jeong, Y. H. Bae, D. S. Lee, S. W. Kim, Nature 1997, 388, 860. \n[7]\t a) Y. Ke, C. Zhou, Y. Zhou, S. Wang, S. H. Chan, Y. Long, Adv. Funct. Mater. 2018, 28, 1800113; b) Y.  Zhou, M.  Layani, S.  Wang, P.  Hu, Y. Ke, S. Magdassi, Y. Long, Adv. Funct. Mater. 2018, 28, 1705365. \n[8]\t R. Langer, D. A. Tirrell, Nature 2004, 428, 487. \n[9]\t A. T. Neffe, B. F. Pierce, G. Tronci, N. Ma, E. Pittermann, T. Gebauer, O. Frank, M. Schossig, X. Xu, B. M. Willie, M. Forner, A. Ellinghaus, J. Lienau, G. N. Duda, A. Lendlein, Adv. Mater. 2015, 27, 1738. \n[10]\t P. Calvert, Adv. Mater. 2009, 21, 743. \n[11]\t a) P. Thoniyot, M. J. Tan, A. A. Karim, D. J. Young, X. J. Loh, Adv. Sci. 2015, 2, 1400010; b) K.  Haraguchi, T.  Takehisa, Adv. Mater. 2002, 14, 1120. \n[12]\t A.  Nakayama, A.  Kakugo, J. P.  Gong, Y.  Osada, M.  Takai, T.  Erata, S. Kawano, Adv. Funct. Mater. 2004, 14, 1124. \n[13]\t J. P. Gong, Y. Katsuyama, T. Kurokawa, Y. Osada, Adv. Mater. 2003, 15, 1155. \n[14]\t a) J.-Y.  Sun, X.  Zhao, W. R. K.  Illeperuma, O.  Chaudhuri, K. H. Oh, D. J. Mooney, J. J. Vlassak, Z. Suo, Nature 2012, 489, 133; b) X. P.  Morelle, W. R.  Illeperuma, K.  Tian, R.  Bai, Z.  Suo, J. J.  Vlassak, Adv. Mater.1801541; c) C. H.  Yang, B.  Chen, J.  Zhou, Y. M.  Chen, Z.  Suo, Adv. Mater. 2016, 28, 4480; d) M.  Wehner, R. L.  Truby, D. J.  Fitzgerald, B.  Mosadegh, G. M.  Whitesides, J. A. Lewis, R. J. Wood, Nature 2016, 536, 451. \n[15]\t a) M. J. d.  Silva, A. O.  Sanches, L. F.  Malmonge, J. A.  Malmonge, Mater. Res. 2014, 17, 59; b) J. R.  May, C.  Gentilini, D. E.  Clarke, Y. I. Odarchenko, D. V. Anokhin, D. A. Ivanov, K. Feldman, P. Smith, M. M.  Stevens, RSC Adv. 2014, 4, 2096; c) V. R.  Feig, H.  Tran, M. Lee, Z. Bao, Nat. Commun. 2018, 9, 2740. \n[16]\t B.  Depalle, Z.  Qin, S. J.  Shefelbine, M. J.  Buehler, J. Mech. Behav. Biomed. Mater. 2015, 52, 1. \n[17]\t W.-K.  Shin, J.  Cho, A. G.  Kannan, Y.-S.  Lee, D.-W.  Kim, Sci. Rep. 2016, 6, 26332. \n[18]\t a) S.  Yao, Y.  Zhu, Adv. Mater. 2015, 27, 1480; b) J.  Wang, C.  Yan, G. Cai, M. Cui, A. Lee-Sie Eh, P. See Lee, Adv. Mater. 2016, 28, 4490; c) T.  Sekitani, T.  Someya, Adv. Mater. 2010, 22, 2228; d) Y.  Cao, T. G.  Morrissey, E.  Acome, S. I.  Allec, B. M.  Wong, C.  Keplinger, C. Wang, Adv. Mater. 2017, 29, 1605099; e) S. Z. Bisri, S. Shimizu, M. Nakano, Y. Iwasa, Adv. Mater. 2017, 29, 1607054. \n[19]\t J. Odent, T. J. Wallin, W. Pan, K. Kruemplestaedter, R. F. Shepherd, E. P. Giannelis, Adv. Funct. Mater. 2017, 27, 1701807. \n[20]\t a) C.  Marin, E. Fernández, Front. Neuroeng. 2010, 3, 8; b) E.  Castagnola, A.  Ansaldo, E.  Maggiolini, T.  Ius, M.  Skrap, D. Ricci, L. Fadiga, Front. Neuroeng. 2014, 7. \n[21]\t T.  Ito, Y.  Yeo, C. B.  Highley, E.  Bellas, C. A.  Benitez, D. S.  Kohane, Biomaterials 2007, 28, 975. \n[22]\t C.  Wu, N.  Yosef, T.  Thalhamer, C.  Zhu, S.  Xiao, Y.  Kishi, A.  Regev, V. K. Kuchroo, Nature 2013, 496, 513. \n[23]\t W. E. Hennink, C. F. van Nostrum, Adv. Drug Delivery Rev. 2002, 54, 13. \n[24]\t K. Missoum, J. Bras, M. N. Belgacem, Biomacromolecules 2012, 13, 4118. \n[25]\t S.  Komiya, E.  Otsuka, Y.  Hirashima, A.  Suzuki, Prog. Nat. Sci.: Mater. Int. 2011, 21, 375. \n[26]\t Z.  Zhao, H.  Chen, H.  Zhang, L.  Ma, Z.  Wang, Biosens. Bioelectron. 2017, 91, 306. \n[27]\t A. van Boxtel, Psychophysiology 2001, 38, 22. \n[28]\t a) Y. Ding, J. Zhang, L. Chang, X. Zhang, H. Liu, L. Jiang, Adv. Mater. 2017, 29, 1704253; b) Y.  Gu, S.  Zhang, L.  Martinetti, K. H.  Lee, L. D. McIntosh, C. D. Frisbie, T. P. Lodge, J. Am. Chem. Soc. 2013, 135, 9652; c) S. Liu, O. Oderinde, I. Hussain, F. Yao, G. Fu, Polymer 2018, 144, 111; d) C.-C. Kim, H.-H. Lee, K. H. Oh, J.-Y. Sun, Science 2016, 353, 682. \n[29]\t a) T.  Li, S.  Xiang, P.  Ma, H.  Bai, W.  Dong, M.  Chen, J. Polym. Sci. B: Polym. Phys. 2015, 53, 1020; b) J.  Yang, C. R.  Han, J. F.  Duan, M. G.  Ma, X. M.  Zhang, F.  Xu, R.-C.  Sun, Cellulose 2013, 20, 227; c) K.  Shi, Z.  Liu, Y.-Y.  Wei, W.  Wang, X.-J.  Ju, R.  Xie, L.-Y.  Chu, ACS Appl. Mater. Interfaces 2015, 7, 27289; d) Y.  Sun, S.  Liu, G.  Du, G. Gao, J. Fu, Chem. Commun. 2015, 51, 8512; e) S. Sornkamnerd, M. K.  Okajima, T.  Kaneko, ACS Omega 2017, 2, 5304; f) G.-l.  Du, Y.  Cong, L.  Chen, J.  Chen, J.  Fu, Chin. J. Polym. Sci. 2017, 35, 1286; g) M.  Sabzi, N.  Samadi, F.  Abbasi, G. R.  Mahdavinia, M. Babaahmadi, Mater. Sci. Eng. C 2017, 74, 374; h) Y. Liu, M. Zhu, X. Liu, W. Zhang, B. Sun, Y. Chen, H.-J. P. Adler, Polymer 2006, 47, 1. \n[30]\t B. Zhu, H. Wang, Y. Liu, D. Qi, Z. Liu, H. Wang, J. Yu, M. Sherburne, Z. Wang, X. Chen, Adv. Mater. 2016, 28, 1559. " + }, + { + "id": "10.1016_j.joule.2018.10.015", + "DOI": "10.1016/j.joule.2018.10.015", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2018.10.015", + "Relative Dir Path": "mds/10.1016_j.joule.2018.10.015", + "Article Title": "Large-Scale and Highly Selective CO2 Electrocatalytic Reduction on Nickel Single-Atom Catalyst", + "Authors": "Zheng, TT; Jiang, K; Ta, N; Hu, YF; Zeng, J; Liu, JY; Wang, HT", + "Source Title": "JOULE", + "Abstract": "The scaling up of electrocatalytic CO2 reduction for practical applications is still hindered by a few challenges: low selectivity, small current density tomaintain a reasonable selectivity, and the cost of the catalytic materials. Here we report a facile synthesis of earth-abundant Ni single-atom catalysts on commercial carbon black, which were further employed in a gas-phase electrocatalytic reactor under ambient conditions. As a result, those single-atomic sites exhibit an extraordinary performance in reducing CO2 to CO, yielding a current density above 100 mA cm(-2), with nearly 100% selectivity for CO and around 1% toward the hydrogen evolution side reaction. By further scaling up the electrode into a 10 3 10-cm(2) modular cell, the overall current in one unit cell can easily ramp up to more than 8 A while maintaining an exclusive CO evolution with a generation rate of 3.34 L hr(-1) per unit cell.", + "Times Cited, WoS Core": 716, + "Times Cited, All Databases": 755, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000457552800023", + "Markdown": "# Article Large-Scale and Highly Selective CO2 Electrocatalytic Reduction on Nickel SingleAtom Catalyst \n\n![](images/7c642f3139caebac3755a612cd3fad844268327a2ee199fa133bd8adb33ec21f.jpg) \n\nTingting Zheng, Kun Jiang, Na Ta, Yongfeng Hu, Jie Zeng, Jingyue Liu, Haotian Wang \n\nhtwang@rice.edu \n\n# HIGHLIGHTS \n\nA facile and scalable synthesis of Ni single-atom catalysts on lowcost carbon blacks \n\nCurrent densities over $100~\\mathrm{{mA}}$ $\\mathsf{c m}^{-2}$ with nearly $100\\%$ selectivity for ${\\mathsf{C O}}_{2}$ -to-CO conversion \n\nA practical CO generation rate of $3.34\\ L\\mathsf{h r}^{-1}$ was achieved in a $10\\times$ $10-\\mathsf{c m}^{2}$ unit cell \n\nEarth-abundant Ni single atoms on commercial carbon black were synthesized in large quantities via an economic and scalable protocol, with record-high selectivity and activity toward CO production. Scaling up the electrodes into a $10\\times10\\mathrm{-}\\mathrm{cm}^{2}$ modular cell achieves a high overall current over 8 A while maintaining a nearly exclusive CO evolution. \n\n# Article Large-Scale and Highly Selective CO2 Electrocatalytic Reduction on Nickel Single-Atom Catalyst \n\nTingting Zheng,1,2 Kun Jiang,1 Na Ta,3 Yongfeng Hu,4 Jie Zeng,2 Jingyue Liu,3 and Haotian Wang1,5,6,\\* \n\n# SUMMARY \n\nThe scaling up of electrocatalytic ${\\mathsf{C O}}_{2}$ reduction for practical applications is still hindered by a few challenges: low selectivity, small current density to maintain a reasonable selectivity, and the cost of the catalytic materials. Here we report a facile synthesis of earth-abundant Ni single-atom catalysts on commercial carbon black, which were further employed in a gas-phase electrocatalytic reactor under ambient conditions. As a result, those single-atomic sites exhibit an extraordinary performance in reducing $\\mathsf{C O}_{2}$ to CO, yielding a current density above $100m\\mathbf{A}c m^{-2}$ , with nearly $100\\%$ selectivity for CO and around $1\\%$ toward the hydrogen evolution side reaction. By further scaling up the electrode into a $10\\times10^{-}{\\mathsf{c m}}^{2}$ modular cell, the overall current in one unit cell can easily ramp up to more than 8 A while maintaining an exclusive CO evolution with a generation rate of $3.34\\ L\\ h r^{-1}$ per unit cell. \n\n# INTRODUCTION \n\nThe intensive consumption of fossil fuels along with excessive emission of carbon dioxide $(\\mathsf{C O}_{2})$ acceleratingly exacerbate global environmental problems, which severely limit the potential of a sustainable progress of human civilization.1,2 Developing clean energy conversion technologies becomes extremely urgent to circumvent these challenges. Electrochemical ${\\mathsf{C O}}_{2}$ reduction reaction $(\\mathsf{C O}_{2}\\mathsf{R R})$ under ambient conditions, coupled with renewable electricity sources, represents a promising approach to curb ${\\mathsf{C O}}_{2}$ emissions while generating value-added fuels and chemicals.3–13 In a variety of $C O_{2}R R$ pathways such as ${\\mathsf C}_{1}$ (CO, formate, methane, etc.),14–21 ${\\mathsf C}_{2}$ (ethylene, ethanol, etc.),22–28 or ${\\mathsf C}_{3}$ (n-propanol, etc.),29,30 the reduction of ${\\mathsf{C O}}_{2}$ to CO is currently one of the most promising practices due to its relatively high selectivity and large current density, as well as the facile separation of gas product from liquid water. More importantly, CO as a fundamental chemical feedstock such as the component of syngas, holds a large market compatibility and a wide range of applications in bulk chemicals manufacturing, medicine, and so on. Despite recent breakthroughs on exploiting various selective catalysts for reduction of ${\\mathsf{C O}}_{2}$ to CO, the ultimate practical viability of this technology, however, is contingent upon the scaling up of $C O_{2}R R$ process, which is still in its infancy with challenges in catalyst cost, product selectivity, scalable activity, as well as long-term stability. \n\nOn the way of scaling up $C O_{2}R R$ for practical ${\\mathsf{C O}}_{2}$ electrolysis, mass production of high-performance catalysts with cost efficiency is the cornerstone and first step. However, there are only a few known catalysts to date, including Au and Ag noble metals,31–34 developed to deliver a significant selectivity toward CO evolution. As a cost-effective substitute and for the continuous efforts in our group,35,36 \n\n# Context & Scale \n\nElectrochemical reduction of ${\\mathsf{C O}}_{2}$ to fuels and chemicals carries extraordinary significance for industry and is highly competitive with water electrolysis and downstream gas-phase ${\\mathsf{C O}}_{2}$ reduction for addressing energy problems. Single-atom materials endowed with maximum atom efficiency, tunable coordination environments, and electronic structures have emerged as highly active catalysts for converting ${\\mathsf{C O}}_{2}$ to CO. However, practical application of single-atom catalysts still seems to be too far away due to their complicated and high-cost materials synthesis, as well as low performance metrics. In this work, Ni single atoms on a low-cost carbon nanoparticle support are developed via a simple and scalable method, with record-high selectivity and activity toward CO production. Moreover, scaling up the electrodes into a modular cell achieves a high overall current while maintaining an exclusive CO evolution. \n\nearth-abundant single-atom catalysts (SACs) provide an intriguing paradigm for ${\\mathsf{C O}}_{2}$ -to-CO conversion, with projected high atomic efficiency, superior activity, and selectivity.37–41 The Ni single atoms coordinated in graphene vacancies, with/ without neighboring N coordination, have been demonstrated to be highly selective to CO.42–45 Nevertheless, the commonly pursued strategies for preparing SACs,46 e.g., core-shell strategy, confined pyrolysis strategy, and polymer encapsulation strategy are not as straightforward to scale up, and sometimes lack general applicability: most of the carbon precursors, including graphene oxides,36,45 carbon nanotubes,47 and metal organic frameworks (MOFs),43 are either not economically viable for large-scale production, or involve relatively complicated preparation steps; in addition, some of the carbon matrix with nanosheet structures suffer from gas diffusion limit when piled up layer by layer on the electrode, greatly hindering the reduction current density for practical implementation. In this sense, developing a facile process for massive production of SACs becomes an important stepping-stone for practical ${\\mathsf{C O}}_{2}$ electrolysis. \n\nAnother critical challenge that goes beyond the nature of the electrocatalysts revolves around the low current density needed to maintain a high CO selectivity. In a traditional H-cell device where the catalysts were immerged in liquid water, the maximal CO evolution current was limited by the following two factors: (1) the solubility of ${\\mathsf{C O}}_{2}$ in water is relatively low, and beyond some point the $C O_{2}R R$ current density will be dominated not by the reaction kinetics but by the mass diffusion limitation, and (2) due to the concentrated water molecules around the catalyst surface, once the overpotential is gradually increased for larger current density, the hydrogen evolution side reaction (HER) can take off and eventually dominate the reaction as observed in previous studies.43,44,48 Fuel cell technology emerges as a platform for maximizing the throughput of $C O_{2}R R$ as reflected in the current and selectivity boost, via preventing the catalyst from direct contact with liquid water, as well as facilitating ${\\mathsf{C O}}_{2}$ gas diffusion.36,49–54 In addition, the compact design of cell and membrane electrode assembly (MEA) can further boost a practical ${\\mathsf{C O}}_{2}$ electrolyzer system with scalable stacks and gas flow system.55 \n\nHerein, we report the synthesis of high-performance Ni SACs with commercial carbon black particles as the support via a simple and scalable method. The Ni single-atomic sites exhibit excellent performance for $C O_{2}R R$ in a traditional H-cell, with a CO faradic efficiency $(\\mathsf{F E_{C O}})$ of ${\\sim}99\\%$ at $-0.681\\mathrm{~V~}$ in 0.5 M $K{\\mathsf{H C O}}_{3}$ aqueous electrolyte. More importantly, large current densities above $100\\ m\\mathsf{A}\\ \\mathsf{c m}^{-2}$ with nearly $100\\%$ CO generation, which are ${\\sim}10$ -fold higher than the current densities in H-cell, were demonstrated on an anion MEA. An ultra-high ${\\mathsf{C O}}/{\\mathsf{H}}_{2}$ ratio of 114, which we define as the ‘‘relative selectivity’’ when the CO selectivity is close to $100\\%$ and ${\\sf H}_{2}$ below $1\\%$ by gas chromatography (GC), was achieved while maintaining a significant current of $74\\mathsf{m A c m}^{-2}$ . In addition, after $20\\mathsf{h r}$ continuous operation with an average current density of $\\sim85\\mathsf{m A c m}^{-2}.$ , the CO formation FE was still maintained around $100\\%$ , while ${\\sf H}_{2}$ below $1\\%$ . When the Ni SACs were further integrated into a $10\\times10\\mathrm{-}\\mathrm{cm}^{2}$ modular cell, the CO evolution current in one unit cell can be scaled up to as high as 8.3 A with an $F E_{C O}$ of $98.4\\%$ , representing a large CO generation rate of $3.34\\ L\\mathsf{h r}^{-1}$ per unit cell. \n\n# RESULTS AND DISCUSSION \n\n# Materials Synthesis and Characterizations \n\nInstead of starting with well-defined graphene matrix or precursors such as polymers or MOFs,35,36,43,56 we used commercially available carbon blacks with activated \n\n# Joule \n\n![](images/466f29057243a66068b26ceba636121cb48e43221e8be959082cccfdeca437f1.jpg) \nFigure 1. Schematic of Synthetical Procedure of Ni-NCB A facile ion adsorption process by mixing Ni salts with activated carbon black dispersed in aqueous solution is carried out and followed with further pyrolysis, enabling gram-scale SACs produced in a one-batch synthesis. \n\nsurface to trap Ni single atoms and thus form a similar coordination environment and active sites for ${\\mathsf{C O}}_{2}$ -to CO-conversion. Compared with that of graphene nanosheets where the layer-by-layer stacking could block the gas diffusion pathways,36 the nanoparticulate morphology of the carbon black support further facilitates the ${\\mathsf{C O}}_{2}$ diffusions across the gas diffusion layer to ensure a high local concentration of reactants. An illustration of the synthetic process for the catalyst is shown in Figure 1. In a typical preparation (see Experimental Procedures), 1 g of activated carbon blacks was well dispersed in water, followed with drop-by-drop addition of ${\\mathsf{N i}}^{2+}$ solution under vigorous stirring. Due to the presence of defects and oxygen-containing functional groups on the surface as well as the high surface areas, the activated carbon black possesses a high adsorption capacity to metal cations in aqueous solution. To ensure a full, but not excess, adsorption of ${\\mathsf{N i}}^{2+}$ on the carbon black, the solution was stirred overnight and then centrifuged to collect the products denoted as ${\\mathsf{N i}}^{2+}$ -adsorbed carbon black $(\\mathsf{N i}^{2+}\\mathrm{-CB})$ . Subsequently, the ${\\mathsf{N i}}^{2+}$ -CB was mixed with certain amount of urea as the N source and annealed at elevated temperatures $(800^{\\circ}\\mathsf{C})$ in Ar for $1\\ h\\ r,$ with gram scale catalysts (denoted as Ni-NCB) produced. \n\nThe high-resolution transmission electron microscopy (HRTEM) image of Ni-NCB in Figure 2A shows the onion-like, defective graphene layers in CB particles, which can serve well as the coordination matrix for Ni single atoms. The corresponding aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) image reveals the individually and uniformly dispersed Ni atoms as bright spots on the CB nanoparticle (Figure 2B). The individual Ni atoms were well separated from each other and were relatively stable under electron beam irradiation, suggesting strong anchoring (Figure 2C). In supplementation, a large area TEM image confirms that no Ni nanoparticles or clusters were formed on the CBs (Figure S1). Elemental mapping by energy-dispersive X-ray spectroscopy \n\n![](images/5f5f6101134c296a7fbb20fb2ff2ea7bfc56dfb469955f03053de520d09d4062.jpg) \nFigure 2. Structure Characterization of Ni-NCB \n\n(A) Aberration-corrected bright-field STEM image. Scale bar represents $2{\\mathsf{n m}}$ . \n(B) Aberration-corrected HAADF-STEM image. Scale bar represents $2{\\mathsf{n m}}$ . \n(C) Zoom-in HAADF-STEM image shows the isolated Ni single atoms confined in carbon matrix as represented by these high-contrast dots. Scale bar represents $0.5\\mathsf{n m}$ . \n(D) Ni $2\\mathsf{p}$ region XPS spectra. \n(E) Ni K-edge XANES spectra. \n(F) Ni K-edge Fourier transformed EXAFS spectra in R space. \nSee also Figures S1–S4. \n\n(EDS) demonstrates that Ni and N species are homogeneously distributed throughout the carbon framework (Figure S2). The mass loading of Ni was determined to be ${\\sim}0.27$ wt $\\%$ by inductively coupled plasma atomic emission spectrometry (Experimental Procedures). X-ray photoelectron spectroscopy (XPS) characterization of Ni-NCB was performed to further elucidate the profile of elemental composition and related chemical states (Figure S3). The Ni $2\\mathsf{p}$ spectrum of Ni-NCB shows a positive Ni $2\\mathsf{p}_{3/2}$ binding energy $(854.9\\ \\mathrm{eV})$ relative to Ni metal $(852.6~\\mathrm{eV}).$ , indicating the positive oxidation states of Ni single atoms (Figure 2D). The XPS N 1s spectrum deconvoluted into pyridinic $(\\sim398.3\\:\\mathrm{eV})$ , Ni-N $(\\sim399.5~\\mathrm{eV})$ , pyrrolic $(\\sim400.5~\\mathrm{eV})$ , quaternary $(\\sim401.3\\ \\mathrm{eV})$ , and oxidized $(\\sim403.0$ eV)-like N species (Figure S4).45,57 The atomic concentrations of Ni and N in Ni-NCB determined by XPS is $0.28\\mathsf{a t\\%}$ and $1.81\\mathrm{at}\\%$ , respectively. Synchrotron-based X-ray absorption near-edge spectroscopy (XANES) and extended X-ray fine structure (EXAFS) were used to determine the electronic and local coordination of the single-atomic sites in Ni-NCB (Experimental Procedures). The Ni K-edge XANES profiles in Figure 2E indicate that Ni species in Ni-NCB were in a higher oxidation state than Ni foil and lower than NiO, according to the near-edge position, which is consistent with the XPS results. As shown in the EXAFS results in R space (Figure 2F), Ni-NCB exhibits prominent peaks at 1.4 and $1.9\\mathring{\\mathsf{A}}$ arising from the first shell \n\n# Joule \n\nNi-N or Ni-C coordination.58 No other typical peaks for Ni-Ni contribution at longer distances (2.2 A˚ ) were observed. Thus, Ni atoms were atomically dispersed throughout the N-doped carbon blacks. Although different Ni-N and Ni-C structures have been proposed in literatures,35,36,59 the explicit coordination environment of Ni is still not clear and awaits further exploring. \n\n# Electrocatalytic $C O_{2}R R$ Performance \n\nThe ${\\mathsf{C O}}_{2}$ electrocatalytic reduction activity and selectivity of Ni-NCB were first evaluated in a standard three-electrode H-cell configuration with ${\\mathsf{C O}}_{2}$ -saturated $0.5\\mathsf{M}$ $K{\\mathsf{H C O}}_{3}$ as the electrolyte. In control, an N-doped carbon black (denoted as N-CB) and a Ni-doped carbon black (denoted as Ni-CB) were also prepared for comparison (Figures S5 and S6). As revealed by linear sweep voltammetry in Figure S7, Ni-NCB shows a much higher current density in ${\\mathsf{C O}}_{2}$ -saturated electrolyte than that of $\\mathsf{N}_{2},$ indicating the participation of ${\\mathsf{C O}}_{2}$ gas in the reaction. Steady-state chronoamperometry of ${\\mathsf{C O}}_{2}$ electrolysis was recorded under different potentials between $-0.3$ and \u00011 V versus reversible hydrogen electrode (vsRHE). The FE of gas products were analyzed by online GC (Figures 3A and S8; Supplemental Information).35,60 In ${\\mathsf{C O}}_{2}$ -saturated $0.5\\mathsf{M K H C O}_{3}$ Ni-NCB exhibits current densities significantly higher than those of Ni-CB and N-CB (Figure S8). ${\\sf H}_{2}$ and CO are the major gas products in all these three samples. For Ni-NCB, CO signals were detectable at $-0.41\\vee$ vs RHE, suggesting that the onset overpotential of ${\\mathsf{C O}}_{2}$ to CO is at least lower than $290\\mathsf{m V}$ . It is noted that the overall FE under this potential is far less than $100\\%$ , which is possibly due to the instrumental detection limit. As the potential becomes more negative, the FE of CO increases, while that of ${\\sf H}_{2}$ decreases correspondingly. A high plateau of CO FEs over $95\\%$ was retained under a broad potential range from $-0.6$ to $-0.84\\mathrm{\\DeltaV}$ vs RHE, with a maximum CO selectivity of above $99\\%$ at $-0.68\\mathrm{\\DeltaV}$ vs RHE while the competitive HER suppressed to $2\\%$ . No other liquid products were detected by $^1\\mathsf{H}$ nuclear magnetic resonance (NMR) (Figure S9). In sharp contrast, NCB exhibits a faint activity for CO generation, indicating that Ni single atoms play a critical role in activating ${\\mathsf{C O}}_{2}$ to produce CO (Figure S8). In addition, Ni-CB only shows a maximum $F E_{C O}$ of $29\\%$ , which is presumably attributed to the poor dispersion of Ni atoms on the CBs in the absence of nitrogen, as demonstrated in our previous study.35,36 The partial current shown in Figure 3B demonstrates that the activity of the Ni-NCB is better than, or comparable with, most of the noblemetal-based catalysts reported to date.32,33,61 Moreover, Ni-NCB exhibits a high intrinsic ${\\mathsf{C O}}_{2}$ reduction activity, reaching a specific CO current of ${111\\mathsf{A}\\mathsf{g}^{-1}}$ . Besides, a ${\\mathsf{C O}}_{2}$ -to-CO Tafel slope of $101~\\mathrm{{mV/}}$ decade on Ni-NCB (Figure S10) suggests that the first electron transfer process generating surface adsorbed $\\star_{\\mathsf{C O O H}}$ species is possibly the rate-determining step for CO evolution.45 To further testify the intrinsic activity of Ni-NCB for ${\\mathsf{C O}}_{2}$ reduction, the CO production turnover frequency (TOF) per Ni single-atomic site is calculated based on the total mass loaded on the electrode, as a minimum value of estimation, as well as the electrochemical double layer capacity (EDLC), as the effective surface area normalization (Figure S11). As shown in Figure 3C, the TOF of Ni-NCB normalized by the mass and electrochemical active surface area (ECSA) for CO production was calculated to be 3.67 and $9.66~{\\mathsf{s}}^{-1}$ , respectively, at an overpotential of $0.56~\\mathsf{V},$ which is better than, or comparable with, those of metal porphyrins or noble metal catalysts in aqueous solutions.7,8,31,62 Furthermore, to elucidate the influence of Ni content, N doping, as well as annealing temperature, a series of control samples were prepared and tested for ${\\mathsf{C O}}_{2}$ reduction (Figures S12–S18). It shows that both the partial current density and CO FE of Ni-NCB annealed under $N H_{3}$ atmosphere are slightly lower than those with urea as N precursor. This could be due to the different vapor pressures of the N dopants, or different radicals from $N_{2}H_{4}$ and $N H_{3}$ under high temperature. It also reveals that \n\n![](images/f2d517544928fb0f00a97b7f3bd0dc515f42bf58dfad3dab1e5c048daa45adcc.jpg) \n\n(A–C) FEs of ${\\sf H}_{2}$ and CO (A), the corresponding steady-state current densities (B), and TOF (C) of Ni-NCB in an H-cell test. The catalyst mass loading is $0.2~\\mathsf{m g}~\\mathsf{c m}^{-2}$ . The error bars represent three independent samples. \n(D) The $C O_{2}R R$ stability test of Ni-NCB on CFP $(1.25~\\mathsf{m g}~\\mathsf{c m}^{-2})$ in an H-cell under $0.55\\vee$ overpotential. \n(E–G) The steady-state current densities (E) and the corresponding FEs of ${\\sf H}_{2}$ and CO (F), and the ${\\mathsf{C O}}/{\\mathsf{H}}_{2}$ ratio (G) of Ni-NCB $(1.25\\mathsf{m g c m}^{-2})$ in an anion membrane electrode assembly. \n(H) Long-term electrolysis under a full-cell voltage of $2.46\\mathrm{\\:V}$ (without iR compensation) for more than $20\\mathsf{h r}$ continuous operation. \nSee also Figures S5–S24 and Table S1. \n\n# Joule \n\nincreasing the Ni loading leads to the generation of Ni clusters, which impairs the overall performance for $C O_{2}R R$ (Figure S14). Besides, appropriate temperature and amount of N doping are required to gain the optimal performance of NiNCB. More importantly, the ${\\mathsf{C O}}_{2}$ -to-CO reduction performance of Ni-NCB is extremely stable, retaining $99\\%$ of the initial current for CO formation $\\mathord{\\leftrightharpoons}23\\mathrm{\\mA}$ $\\mathsf{c m}^{-2})$ after $24~\\mathsf{h r}$ of continuous operation, with $F E_{C O}$ remaining above $95\\%$ . Postcatalysis HAADF-STEM imaging and EXAFS (Figure S19) show that those Ni species still maintain the feature of well-dispersed single atoms, reiterating the excellent chemical stability of the Ni atomic sites in Ni-NCB. \n\nThe scaling up of CO generation rate in a traditional H-cell is limited by the following two factors: (1) a larger overpotential is usually required to deliver a higher kinetic current, which, however, can promote strong HER competition due to the contact between catalyst and liquid water, and (2) the reduced ${\\mathsf{C O}}_{2}$ gas reactant in an H-cell configuration is that dissolved in liquid water, therefore the reaction rate beyond a certain point is limited by ${\\mathsf{C O}}_{2}$ mass diffusion. To circumvent this issue and inspired by fuel cell reaction mechanisms, an anion MEA was adopted in a gas-phase electrochemical reactor to greatly boost the current density while maintaining high CO selectivity (Experimental Procedures).36 On the cathode side, humidified ${\\mathsf{C O}}_{2}$ gas was supplied. This high concentration of ${\\mathsf{C O}}_{2}$ and low concentration of $H_{2}O$ vapor can block the direct contact between catalyst and liquid water and prevent limiting of reactant diffusion. On the anode side, $0.1~\\mathsf{M}$ $K{\\mathsf{H C O}}_{3}$ solution was circulated whereby the water oxidation is taking place (Figure S20). As shown in Figure 3E, the ${\\mathsf{C O}}_{2}$ conversion increases rapidly above $2.1~\\lor$ cell voltage and reaches a significantly high current density of $130~\\mathsf{m A}$ $\\mathsf{c m}^{-2}$ at only $2.7\\:\\forall$ without iR compensations. Notably, the catalyst maintains nearly $100\\%$ FE for CO formation across a broad range of current densities from 30 to $130\\mathsf{m A}\\mathsf{c m}^{-2}$ , while the FE of ${\\sf H}_{2}$ was suppressed to a minimum of $0.9\\%$ (Figures 3F and S21). It is important to mention here that, due to the experimental errors introduced by GC detection, the measured CO selectivity could sometimes be slightly higher than $100\\%$ , especially when ${\\sf H}_{2}$ was suppressed to below $1\\%$ . In this case, we propose to define the ${\\mathsf{C O}}/{\\mathsf{H}}_{2}$ ratio, which we denote as relative selectivity, as an additional criterion to more accurately evaluate the high selectivity toward CO evolution. As shown in Figure 3G, with the gradual increase of cell voltage, the ${\\mathsf{C O}}/{\\mathsf{H}}_{2}$ ratio increases accordingly and reaches a maximum value of 113.8, with a high $C O_{2}R R$ current density of $74\\ m\\mathsf{A}\\mathsf{c m}^{-2}$ . This is to our knowledge the highest ratio of ${\\mathsf{C O}}/{\\mathsf{H}}_{2}$ under a significant current density compared with the most active catalysts reported to date (Table S1). An impressive stability of the catalyst in this gas-phase electrochemical reactor is also presented in Figure 3H, with an average current density of $85~\\mathsf{m A}~{\\mathsf{c m}}^{-2}$ over $20~\\mathsf{h r}$ continuous electrolysis, while maintaining CO formation FEs $\\sim100\\%$ and ${\\sf H}_{2}$ below $1\\%$ . The slight degradation of the current density was probably attributed to several factors including the deactivation of catalysts, the corrosion of the gas diffusion layer, as well as membrane degradation (Figures S22–S24). Overall, this high performance of the Ni-NCB catalyst in the gas-phase electrochemical reactor opens up great opportunities in scaling up highly selective ${\\mathsf{C O}}_{2}$ reduction. \n\nMotivated by the superior activity of Ni-NCB and its facile synthesis process, it is expected that, by increasing the catalyst loading, extending the size of the gas diffusion layer, as well as alternatively stacking anodes and cathodes, the NiNCB integrated gas-phase electrochemical reactor can be further scaled up to produce large CO generation currents for potential practical applications. Here we customized one unit cell with a $10\\times10\\mathrm{-}\\mathrm{cm}^{2}$ anion MEA as a preliminary demonstration to justify this application possibility in the future (Figures 4A–4C). Considering the high ${\\mathsf{C O}}_{2}$ flow rate needed to ensure sufficient reactants, gas collecting bags were used to collect the gas products which were later analyzed by GC under different cell voltages (Experimental Procedures). As shown in Figures 4D–4F, a record-high $C O_{2}R R$ current of 8.3 A was achieved with a high CO selectivity approximating to $99\\%$ and ${\\sf H}_{2}$ about $1\\%$ . Delivering an average current of ${\\sim}8$ A for stability test, our device maintained a stable CO selectivity of more than $90\\%$ for over 6 hr continuous electrolysis with a total volume of $20.4\\ \\mathsf{L}\\mathsf{C O}$ generated (Figure 4G). This represents a CO generation rate of $3.42\\ L\\ \\mathsf{h r}^{-1}$ or $0.14\\mathrm{~mol}$ $\\mathsf{h r}^{-1}$ and a conversion rate of $11.33\\%$ . \n\n![](images/cd36d8eaea27b13b798a24ffa6b6f2aa93787396725cad28ca88f60a1f7c16c4.jpg) \nFigure 4. Electrocatalytic $C O_{2}R R$ Performance of Ni-NCB in a $10\\times10^{-}\\mathsf{c m}^{2}$ Anion Membrane Electrode Assembly Gas-Phase Electrochemical Reactor (A) Photographs of assembled reactor, membrane electrode assembly, and individual cell components. (B and $\\mathsf{C})$ The steady-state current densities (B) and the corresponding FEs of ${\\sf H}_{2}$ and CO $\\left(\\mathsf{C}\\right)$ of Ni-NCB $1.25\\ m g\\ c m^{-2})$ . (D) Long-term electrolysis under a full-cell voltage of $2.8{\\ V}$ and a current of ${\\sim}8\\mathsf{A}$ . The CO selectivity maintained above $90\\%$ over the course of 6 hr continuous operation. (E) The accumulated CO production during 6 hr continuous electrolysis. \n\n# Joule \n\nIt is anticipated that this work can be further pushed forward toward commercialized ${\\mathsf{C O}}_{2}$ electrolysis by optimizing several technological aspects according to industry standards. First, stability is one of the major concerns, which suffers from the corrosion of both anode and cathode, as well as membrane and electrode decay, which require tremendous efforts to overcome. In addition, ${\\mathsf{C O}}_{2}$ feed recycling can be set up by separating ${\\mathsf{C O}}_{2}$ from gas products to achieve a sustained ${\\mathsf{C O}}_{2}$ supply. The cost of the anode should also be taken into consideration, which can be greatly reduced by replacing $\\mathsf{I r O}_{2}$ with efficient transition metal-based materials. Meanwhile, one circumstance should be paid attention to, where the metal leaching happens from the anode to be deposited onto the cathode, which will hamper the $C O_{2}R R$ by encouraging competitive HER. \n\nIn conclusion, a highly efficient transition metal-based SAC was synthesized via an economic and scalable protocol, and applied in ${\\mathsf{C O}}_{2}$ electrolysis for large-scale production of CO. The results demonstrate that it is promising to replace noble metal catalysts, such as Au or Ag, with earth-abundant materials with remarkable CO evolution performance approaching practical expectations, which opens an avenue for future renewable energy infrastructures and achieves a significant progress in closing the anthropogenic carbon cycle for global sustainability. \n\n# EXPERIMENTAL PROCEDURES \n\n# Synthesis \n\nThe carbon blacks were activated by dispersing $_{2\\texttt{g}}$ carbon blacks in $100~\\mathrm{{mL}}$ of $9M$ nitric acid solution followed with refluxing at $90^{\\circ}\\mathsf{C}$ for $3h r$ . The Ni-NCB catalyst was prepared via a facile ion adsorption process followed with further pyrolysis. Typically, a $3-m g/m L$ nickel nitrate stock solution was first prepared by dissolving ${\\mathsf{N i}}({\\mathsf{N O}}_{3})_{2}{\\cdot}6{\\mathsf{H}}_{2}{\\mathsf{O}}$ (Puriss, Sigma-Aldrich) into Millipore water (18.2 $\\mathsf{M W}{\\cdot}\\mathsf{c m})$ ). A carbon black suspension was prepared by mixing $\\boldsymbol{1}_{\\mathfrak{g}}$ activated carbon blacks (Vulcan XC-72, purchased from Fuel Cell Store and activated in acid bath) with $400~\\mathrm{{mL}}$ of Millipore water, and tip sonicated (Branson Digital Sonifier) for $30~\\mathrm{min}$ until a homogeneous dispersion was achieved. Then $40~\\mathsf{m L}$ of ${\\mathsf{N i}}^{2+}$ solution was dropwise added into carbon black solution under vigorous stirring overnight and then centrifuged to collect the products $(\\mathsf{N i}^{2+}{\\mathrm{-}}\\mathsf{C B})$ . The as-prepared ${\\mathsf{N i}}^{2+}$ -CB powder was mixed with urea with a mass ratio of 1:10, and then heated up in a tube furnace to $800^{\\circ}\\mathsf{C}$ under a gas flow of 80 standard cubic centimeters per minute (sccm) Ar (UHP, Airgas) and maintained for $1\\ \\mathsf{h r}.$ , obtaining the final products. NCB and Ni-CB were prepared in a similar way but with the absence of Ni precursor and urea, respectively. $V i-N C B-N H_{3}$ was prepared by annealing the as-prepared ${\\mathsf{N i}}^{2+}$ -CB powder at $800^{\\circ}\\mathsf{C}$ under a gas flow of 80 sccm $N H_{3}$ . Ni-NCB-1:5 and Ni-NCB-1:20 were prepared in the same way as Ni-NCB, except by varying the mass ratio of ${\\mathsf{N i}}^{2+}$ -CB powder and urea to 1:5 and 1:20. Ni-NCB600 and Ni-NCB-1000 were prepared by just varying the annealing temperature to $600^{\\circ}\\mathsf{C}$ and $1,000^{\\circ}\\mathsf{C}$ . Ni excess was prepared with a modified strategy reported before.36 \n\n# Electrochemical Measurements \n\nThe electrochemical measurements were run at $25^{\\circ}\\mathsf{C}$ in a customized gastight H-type glass cell separated by Nafion 117 membrane (Fuel Cell Store). A BioLogic ${\\mathsf{V M P}}_{3}$ work station was employed to record the electrochemical response. The set-up of the three-electrode test system can be found in our earlier reports.35,36 Typically, $5\\mathrm{\\mg}$ of as-prepared catalyst was mixed with $1m L$ of ethanol and $100~\\upmu\\upiota$ of Nafion 117 solution $(5\\%$ , Sigma-Aldrich), and sonicated for 20 min to get a homogeneous catalyst ink. Ink $(80\\upmu\\mathsf{L})$ was pipetted onto a $2\\cdot\\mathsf{c m}^{2}$ glassy carbon surface $(0.2\\ m g/\\mathsf{c m}^{2}$ mass loading). For the stability test, $500~\\upmu\\up L$ of the ink was air-brushed onto a carbon fiber paper gas diffusion layer toward a mass loading of $1.25~\\mathsf{m g}/\\mathsf{c m}^{2}$ , and then vacuum dried prior to use. All potentials measured against a saturated calomel electrode were converted to the RHE scale in this work using E $:(\\boldsymbol{\\mathsf{v s}}\\mathsf{R H E})=\\mathsf{E}$ (v $\\mathsf{s}\\mathsf{S C E})+0.244\\mathsf{V}+0.0591^{\\star}\\mathsf{p}\\mathsf{H}$ , where ${\\mathsf{p H}}$ values of electrolytes were determined by an Orion 320 PerpHecT LogR Meter (Thermo Scientific). Solution resistance $(\\mathsf{R}_{\\mathsf{u}})$ was determined by potentiostatic electrochemical impedance spectroscopy at frequencies ranging from $0.1\\mathsf{H z}$ to $200~\\mathsf{k H z}$ , and manually compensated as E (iR corrected versus RHE) $\\mathbf{\\Psi}=\\mathsf{E}$ (vs RHE) $\\mathsf{R}_{\\mathsf{u}}^{}\\star\\mathsf{I}$ (amps of average current). \n\nFor the anion MEA test (or scale-up fuel cell test), $1.25~\\mathsf{m g}/\\mathsf{c m}^{2}$ Ni-NG and $\\mathsf{I r O}_{2}$ was air-brushed onto two $2\\times2\\mathrm{-cm}^{2}$ (or $10\\times10\\mathrm{-}\\mathrm{cm}^{2})$ Sigracet 35 BC gas diffusion layer electrodes as a $C O_{2}R R$ cathode and an oxygen evolution reaction anode, respectively. A PSMIM anion-exchange membrane (Dioxide Materials) was sandwiched by the two gas diffusion layer electrodes to separate the chambers. On the cathode side, a titanium gas flow channel supplied 50 sccm (or 500 sccm) humidified ${\\mathsf{C O}}_{2}$ while the anode was circulated with 0.1 M $K{\\mathsf{H C O}}_{3}$ electrolyte at $2{\\mathrm{~mL~}}{\\mathrm{min}}^{-1}$ (or $10\\ m L\\ m i\\ n^{-1};$ flow rate. The cell voltages in Figures 3E–3H were recorded without iR correction. The $10\\times10\\mathrm{-}\\mathrm{cm}^{2}$ MEA response was recorded by a Sorensen DCS 33-33 power supply and is shown in Figure 4 without iR correction. \n\n# $C O_{2}R R$ Products Analysis \n\nDuring electrolysis, ${\\mathsf{C O}}_{2}$ gas $(99.995\\%$ , Airgas) was delivered into the cathodic compartment containing ${\\mathsf{C O}}_{2}$ -saturated electrolyte at a rate of 50.0 sccm (monitored by an Alicat Scientific mass flow controller) and vented into a Shimadzu GC-2014 GC equipped with a combination of molecular sieve 5A, Hayesep Q, Hayesep ${\\intercal,}$ and Hayesep N columns.35,60 A thermal conductivity detector was mainly used to quantify ${\\sf H}_{2}$ concentration, and a flame ionization detector with a methanizer was used to quantitative analysis CO content and/or any other alkane species. The detectors are calibrated by three different concentrations $(\\mathsf{H}_{2}$ : 100, 1,042, and 49,830 ppm; CO: 100, 496.7, and $9,754~\\mathsf{p p m})$ of standard gases. The gas products were sampled after a continuous electrolysis of ${\\sim}15$ min under each potential. The partial current density for a given gas product was calculated as below: \n\n$$\nj_{i}=x_{i}\\times v\\times\\frac{n_{i}F P_{0}}{R T}\\times\\left(\\mathrm{electrode\\area}\\right)^{-1}\n$$ \n\nwhere $x_{i}$ is the volume fraction of certain product determined by online GC referenced to calibration curves from three standard gas samples, $v$ is the flow rate, $n_{i}$ is the number of electrons involved, $p_{0}=101.3\\mathsf{k P a}$ , F is the Faraday constant, and R is the gas constant. The corresponding FE at each potential is calculated by \n\n$$\nF E=\\frac{j_{i}}{j_{t o t a l}}\\times100\\%\n$$ \n\nFor a $10\\times10–\\mathsf{c m}^{2}\\mathsf{I}$ MEA, the FEs of ${\\sf H}_{2}$ and CO were tested ex situ and calculated based on the concentration normalization. \n\n1D $^1\\mathsf{H}$ NMR spectra were collected on an Agilent DD2 600 MHz spectrometer to test if any liquid products present during the ${\\mathsf{C O}}_{2}$ reduction (Figure S9). Typically, $600\\upmu\\up L$ of electrolyte after electrolysis was mixed with ${100\\upmu\\up L}$ of $D_{2}O$ (Sigma-Aldrich, 99.9 at $\\%$ D) and $0.05~\\upmu\\up L$ DMSO(Sigma-Aldrich, $99.9\\%$ ) as internal standard. \n\n# Joule \n\n# Evaluation of TOF \n\nCalculation of TOF by mass loading normalization: catalyst loading on glass carbon electrode is $0.2~\\mathsf{m g}~\\mathsf{c m}^{-2}$ . The content of Ni in Ni-NCB is 0.27 wt $\\%$ . The moles of active sites per $\\mathsf{c m}^{2}$ : \n\n$$\nN={\\frac{0.2\\times10^{-3}\\times0.27\\times10^{-2}}{58}}=9.31\\times10^{-9}~{\\mathrm{mole}}~{\\mathrm{cm}}^{-2}\n$$ \n\n$$\n\\mathsf{T O F}\\bigl(\\mathsf{s}^{-1}\\bigr)=\\frac{J\\times F E_{C O}\\times0.965}{2\\times96485.3\\times9.31\\times10^{-9}}\n$$ \n\nCalculation of TOF by ECSA normalization: according to the reported EDLC value of graphene ${\\sim}21~\\upmu\\mathsf{F/c m}^{2(36)}$ , the electrochemical surface area of graphene layers in NiNCB was calculated to be $390.5~{\\mathsf{c m}}^{2}$ , given the $8.2~\\mathrm{mF}/\\mathrm{cm}^{2}$ EDLC value of Ni-NCB. The moles of carbon atoms on the electrochemical surface can be calculated to be $390.5\\times10^{-4}/2,600\\times12=1.25\\times10^{-6}\\mathsf{m o l}$ , where $2,600\\mathsf{m}^{2}\\mathsf{g}^{-1}$ is the theoretical specific surface area of graphene. Taken together the Ni atomic content in Ni-NG was determined to be $0.28\\%$ by XPS (Figure S1), and the number of Ni sites in the surface was $\\mathsf{N}=3.5\\times10^{-9}\\mathrm{mol}$ . Accordingly, $\\mathsf{T O F}(\\mathsf{s}^{-1})=\\frac{J\\times F E_{C O}\\times0.965}{2\\times96485.3\\times3.5\\times10^{-9}}.$ \n\n# Instrumentation \n\nThe STEM characterization in Figure 1A was carried out using a JEOL ARM200F aberration-corrected scanning transmission electron microscope at $200~\\mathsf{k V}$ with an image resolution of ${\\sim}0.08~\\mathsf{n m}$ . All other TEM images were obtained by using a JEOL 2100 transmission electron microscope operated under $200\\mathsf{k V}$ . EDS analysis was performed at $300\\mathsf{k V}$ using Super-X EDS system in a Probe-corrected FEI Titan Themis 300 S/TEM. Drift correction was applied during acquisition. XPS was obtained with a Thermo Scientific K-Alpha ESCA spectrometer, using a monochromatic Al $\\mathsf{K}\\mathsf{\\alpha}$ radiation $(1,486.6\\ \\mathrm{eV})$ and a low energy flood gun as neutralizer. The binding energy of the C 1s peak at $284.6\\mathsf{e V}$ was used as reference. Thermo Avantage V5 program was employed for surface componential content analysis as well as peaks fitting for selected elemental scans. XAS spectra on Ni K-edge was acquired using the SXRMB beamline of Canadian Light Source. The SXRMB beamline used an Si(111) double-crystal monochromator to cover an energy range of $2{\\-}-10\\ k\\in\\mathsf{V}$ with a resolving power of 10,000. The XAS measurement was performed in fluorescence mode using a four-element Si(Li) drift detector in a vacuum chamber. The powder sample was spread onto double-sided, conducting carbon tape. Ni foil was used to calibrate the beamline energy. \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information includes 24 figures and 1 table and can be found with this article online at https://doi.org/10.1016/j.joule.2018.10.015. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Rowland Fellows Program at Rowland Institute, Harvard University. The Center for Nanoscale Systems (CNS) is part of Harvard University. This research used resources of the Canadian Light Source, which is supported by NSERC, the National Research Council Canada, the Canadian Institutes of Health Research, the Province of Saskatchewan, Western Economic Diversification Canada, and the University of Saskatchewan. J.L. and N.T. were supported by the National Science Foundation under CHE-1465057, and gratefully acknowledge the use of facilities within the John M. Cowley Center for High Resolution Electron Microscopy at Arizona State University. T.Z. and N.T. acknowledge funding from the China \n\n# \n\nScholarship Council (CSC) (201706340152 and 201704910441, respectively). J.Z. acknowledges support from MOST of China (2014CB932700) and NSFC (21573206). This work was performed in part at the CNS, a member of the National Nanotechnology Infrastructure Network (NNIN), which is supported by the National Science Foundation under NSF award no. ECS-0335765. H.W. acknowledges support from Rice University. \n\n# AUTHOR CONTRIBUTIONS \n\nH.W. designed the studies. T.Z. conducted the synthesis and catalytic tests of catalysts. K.J. performed the characterization of catalysts. N.T. and J.L. conducted HRTEM characterization. Y.H. performed XAFS measurements. J.Z. provided suggestions on the work. T.Z. and H.W. wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\n# DECLARATION OF INTERESTS \n\nH.W. has submitted a patent application (US 62/486,148, 2017) regarding the transition single-atom catalyzed carbon dioxide conversion technology. \n\nReceived: August 24, 2018 \nRevised: October 2, 2018 \nAccepted: October 16, 2018 \nPublished: November 8, 2018 \n\n# REFERENCES \n\n1. Chu, S., Cui, $\\mathsf{Y}_{\\cdot,\\prime}$ and Liu, N. (2017). The path towards sustainable energy. Nat. Mater. 16, 16–22. \n2. Obama, B. (2017). The irreversible momentum of clean energy. Science 355, 126–129. \n3. Rosen, B.A., Salehi-Khojin, A., Thorson, M.R., Zhu, W., Whipple, D.T., Kenis, P.J., and Masel, R.I. (2011). Ionic liquid-mediated selective conversion of CO2 to CO at low overpotentials. Science 334, 643–644. \n4. Zheng, T., Jiang, K., and Wang, H. (2018). Recent advances in electrochemical ${\\mathsf{C O}}_{2}$ -toCO conversion on heterogeneous catalysts. Adv. Mater. e1802066, https://doi.org/10. 1002/adma.201802066. \n5. Zhu, D.D., Liu, J.L., and Qiao, S.Z. (2016). Recent advances in inorganic heterogeneous electrocatalysts for reduction of carbon dioxide. Adv. Mater. 28, 3423–3452. \n6. Liu, M., Pang, Y., Zhang, B., De Luna, P. Voznyy, O., Xu, J., Zheng, X., Dinh, C.T., Fan, F., Cao, C., et al. (2016). Enhanced electrocatalytic $C{\\mathsf{O}}_{2}$ reduction via field-induced reagent concentration. Nature 537, 382–386. \n7. Lin, S., Diercks, C.S., Zhang, Y.B., Kornienko, N., Nichols, E.M., Zhao, Y., Paris, A.R., Kim, D. Yang, P., Yaghi, O.M., and Chang, C.J. (2015). Covalent organic frameworks comprising cobalt porphyrins for catalytic ${\\mathsf{C O}}_{2}$ reduction in water. Science 349, 1208–1213. \n8. Zhang, X., Wu, Z., Zhang, X., Li, L., Li, Y., Xu, H., Li, X., Yu, X., Zhang, Z., Liang, Y., and Wang, H. (2017). Highly selective and active $C{\\mathsf{O}}_{2}$ reduction electrocatalysts based on cobalt phthalocyanine/carbon nanotube hybrid structures. Nat. Commun. 8, 14675. \n9. Kas, R., Hummadi, K.K., Kortlever, R., de Wit, P., Milbrat, A., Luiten-Olieman, M.W., Benes, N.E., Koper, M.T., and Mul, G. (2016). Threedimensional porous hollow fibre copper electrodes for efficient and high-rate electrochemical carbon dioxide reduction. Nat. Commun. 7, 10748. \n10. Ross, M.B., Dinh, C.T., Li, Y., Kim, D., De Luna, P., Sargent, E.H., and Yang, P. (2017). Tunable Cu enrichment enables designer syngas electrosynthesis from CO2. J. Am. Chem. Soc. 139, 9359–9363. \n11. Sharma, P.P., Wu, J., Yadav, R.M., Liu, M., Wright, C.J., Tiwary, C.S., Yakobson, B.I., Lou, J., Ajayan, P.M., and Zhou, X.D. (2015). Nitrogen-doped carbon nanotube arrays for high-efficiency electrochemical reduction of $C\\mathsf{O}_{2}$ : on the understanding of defects, defect density, and selectivity. Angew. Chem. Int. Ed. 54, 13701–13705. \n12. Huang, H., Jia, H., Liu, Z., Gao, P., Zhao, J., Luo, Z., Yang, J., and Zeng, J. (2017). Understanding of strain effects in the electrochemical reduction of CO2: using Pd nanostructures as an ideal platform. Angew. Chem. Int. Ed. 129, 3648–3652. \n13. Zhang, L., Zhao, Z.J., and Gong, J. (2017). Nanostructured materials for heterogeneous electrocatalytic $C{\\mathsf{O}}_{2}$ reduction and their related reaction mechanisms. Angew. Chem. Int. Ed. 56, 11326–11353. \n14. Kuhl, K.P., Hatsukade, T., Cave, E.R., Abram, D.N., Kibsgaard, J., and Jaramillo, T.F. (2014). Electrocatalytic conversion of carbon dioxide to methane and methanol on transition metal surfaces. J. Am. Chem. Soc. 136, 14107–14113. \n15. Mariano, R.G., McKelvey, K., White, H.S., and Kanan, M.W. (2017). Selective increase in $C{\\mathsf{O}}_{2}$ \n\nelectroreduction activity at grain-boundary surface terminations. Science 358, 1187–1192. \n16. Wang, H., Jia, J., Song, P., Wang, Q., Li, D., Min, S., Qian, $\\mathsf{C}_{\\cdot,\\prime}$ Wang, L., Li, Y.F., Ma, C., et al. (2017). Efficient electrocatalytic reduction of $C\\mathsf{O}_{2}$ by nitrogen-doped nanoporous carbon/ carbon nanotube membranes - a step towards the electrochemical ${\\mathsf{C O}}_{2}$ refinery. Angew. Chem. Int. Ed. 129, 7955–7960. \n17. Weng, Z., Wu, Y., Wang, M., Jiang, J., Yang, K. Huo, S., Wang, X.F., Ma, Q., Brudvig, G.W., Batista, V.S., et al. (2018). Active sites of copper-complex catalytic materials for electrochemical carbon dioxide reduction. Nat. Commun. 9, 415. \n18. Ju, W., Bagger, A., Hao, G.P., Varela, A.S., Sinev, I., Bon, V., Roldan Cuenya, B., Kaskel, S., Rossmeisl, J., Strasser, P., et al. (2017). Understanding activity and selectivity of metalnitrogen-doped carbon catalysts for electrochemical reduction of CO2. Nat.Commun. 8, 944. \n19. Dai, L., Qin, $\\scriptstyle\\bigcirc_{\\cdot,\\prime}$ Wang, P., Zhao, X., Hu, C., Liu, P., Qin, R., Chen, M., Ou, D., Xu, C., et al. (2017). Ultrastable atomic copper nanosheets for selective electrochemical reduction of carbon dioxide. Sci. Adv. 3, e1701069. \n20. Niu, K., Xu, Y., Wang, H., Ye, R., Xin, H.L., Lin, F., Tian, C., Lum, Y., Bustillo, K.C., Doeff, M.M., et al. (2017). A spongy nickel-organic $C{\\mathsf{O}}_{2}$ reduction photocatalyst for nearly $100\\%$ selective CO production. Sci. Adv. 3, e1700921. \n21. Dunwell, M., Lu, $\\scriptstyle\\bigcirc_{\\cdot,}$ Heyes, J.M., Rosen, J. Chen, J.G., Yan, Y., Jiao, F., and Xu, B. (2017). The central role of bicarbonate in the electrochemical reduction of carbon dioxide on gold. J. Am. Chem. Soc. 139, 3774–3783. \n22. Liu, Y., Zhang, Y., Cheng, K., Quan, X., Fan, X., Su, Y., Chen, S., Zhao, H., Zhang, Y., Yu, H., and Hoffmann, M.R. (2017). Selective electrochemical reduction of carbon dioxide to ethanol on a boron- and nitrogen-Co-doped nanodiamond. Angew. Chem. Int. Ed. 56, 15607–15611. \n23. Loiudice, A., Lobaccaro, P., Kamali, E.A., Thao, T., Huang, B.H., Ager, J.W., and Buonsanti, R. (2016). Tailoring copper nanocrystals towards C2 products in electrochemical $\\mathrm{\\bar{C}O}_{2}$ reduction. Angew. Chem. Int. Ed. 55, 5789–5792. \n24. Ma, M., Djanashvili, $\\mathsf{K}_{\\cdot,\\cdot}$ and Smith, W.A. (2016). Controllable hydrocarbon formation from the electrochemical reduction of $\\mathsf{C O}_{2}$ over Cu nanowire arrays. Angew. Chem. Int. Ed. 55, 6680–6684. \n25. Dinh, C.-T., Burdyny, T., Kibria, M.G., Seifitokaldani, A., Gabardo, C.M., Garcı´a de Arquer, F.P., Kiani, A., Edwards, J.P., De Luna, P., Bushuyev, O.S., et al. (2018). CO2 electroreduction to ethylene via hydroxidemediated copper catalysis at an abrupt interface. Science 360, 783–787. \n26. Jiang, K., Sandberg, R.B., Akey, A.J., Liu, X., Bell, D.C., Nørskov, J.K., Chan, $\\mathsf{K}_{\\cdot,\\prime}$ and Wang, H. (2018). Metal ion cycling of Cu foil for selective C-C coupling in electrochemical CO2 reduction. Nat. Catal. 1, 111–120. \n27. Weng, $Z.,$ Jiang, J., Wu, Y., Wu, Z., Guo, X., Materna, K.L., Liu, W., Batista, V.S., Brudvig, G.W., and Wang, H. (2016). Electrochemical $C{\\mathsf{O}}_{2}$ reduction to hydrocarbons on a heterogeneous molecular Cu catalyst in aqueous solution. J. Am. Chem. Soc. 138, 8076–8079. \n28. Ma, S., Sadakiyo, M., Heima, M., Luo, R., Haasch, R.T., Gold, J.I., Yamauchi, M., and Kenis, P.J. (2016). Electroreduction of carbon dioxide to hydrocarbons using bimetallic CuPd catalysts with different mixing patterns. J. Am. Chem. Soc. 139, 47–50. \n29. Lee, S., Kim, D., and Lee, J. (2015). Electrocatalytic production of C3-C4 compounds by conversion of ${\\mathsf{C O}}_{2}$ on a chloride-induced bi-phasic $\\mathsf{C u}_{2}\\mathsf{O}.$ Cu catalyst. Angew. Chem. Int. Ed. 127, 14914–14918. \n30. Wu, J., Ma, S., Sun, J., Gold, J.I., Tiwary, C., Kim, B., Zhu, L., Chopra, N., Odeh, I.N., Vajtai, R., et al. (2016). A metal-free electrocatalyst for carbon dioxide reduction to multi-carbon hydrocarbons and oxygenates. Nat. Commun. 7, 13869. \n31. Lu, Q., Rosen, J., Zhou, Y., Hutchings, G.S., Kimmel, Y.C., Chen, J.G., and Jiao, F. (2014). A selective and efficient electrocatalyst for carbon dioxide reduction. Nat. Commun. 5, 3242. \n32. Yoon, Y., Hall, A.S., and Surendranath, Y. (2016). Tuning of silver catalyst mesostructure promotes selective carbon dioxide conversion into fuels. Angew. Chem. Int. Ed. 128, 15508– 15512. \n33. Zhu, W., Michalsky, ${\\sf R}_{\\cdot,\\prime}$ Metin O¨ , Lv H., Guo, S., Wright, C.J., Sun, X., Peterson, A.A., and Sun, S. (2013). Monodisperse Au nanoparticles for selective electrocatalytic reduction of $C{\\mathsf{O}}_{2}$ to CO. J. Am. Chem. Soc. 135, 16833–16836. \n34. Feng, X., Jiang, $\\mathsf{K}_{\\cdot,\\prime}$ Fan, S., and Kanan, M.W. (2015). Grain-boundary-dependent ${\\mathsf{C O}}_{2}$ \n\n# Joule \n\nelectroreduction activity. J. Am. Chem. Soc. 137, 4606–4609. \n35. Jiang, K., Siahrostami, S., Akey, A.J., Li, Y., Lu, Z., Lattimer, J., Hu, Y., Stokes, C., Gangishetty, M., Chen, $\\mathsf{G}_{\\cdot,\\prime}$ et al. (2017). Transition-metal single atoms in a graphene shell as active centers for highly efficient artificial photosynthesis. Chem 3, 950–960. \n36. Jiang, K., Siahrostami, S., Zheng, T., Hu, Y., Hwang, S., Stavitski, E., Peng, Y., Dynes, J., and Gangisetty, M. (2018). Isolated Ni single atoms in graphene nanosheets for high-performance CO2 reduction. Energy Environ. Sci. 11, 893–903. \n37. Wei, H., Huang, K., Wang, D., Zhang, R., Ge, B., Ma, J., Wen, B., Zhang, S., Li, Q., Lei, M., et al. (2017). Iced photochemical reduction to synthesize atomically dispersed metals by suppressing nanocrystal growth. Nat. Commun. 8, 1490. \n38. Fei, H., Dong, J., Feng, Y., Allen, C.S., Wan, C., Volosskiy, B., Li, M., Zhao, Z., Wang, Y., Sun, H., et al. (2018). General synthesis and definitive structural identification of MN4C4 single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72. \n39. Qiao, B., Wang, A., Yang, X., Allard, L.F., Jiang, Z., Cui, Y., Liu, J., Li, J., and Zhang, T. (2011). Single-atom catalysis of CO oxidation using Pt1/FeOx. Nat. Chem. 3, 634–641. \n40. Wei, H., Liu, X., Wang, A., Zhang, L., Qiao, B., Yang, X., Huang, Y., Miao, S., Liu, J., Zhang, T., et al. (2014). FeOx-supported platinum singleatom and pseudo-single-atom catalysts for chemoselective hydrogenation of functionalized nitroarenes. Nat. Commun. 5, 6634. \n41. Li, H., Wang, L., Dai, Y., Pu, Z., Lao, Z., Chen, Y., Wang, M., Zheng, X., Zhu, J., Zhang, W., et al. (2018). Synergetic interaction between neighbouring platinum monomers in CO2 hydrogenation. Nat. Nanotechnol. 13, 411–417. \n42. Varela, A.S., Ranjbar, S.N., Steinberg, J., Ju, W., Oh, H.S., and Strasser, P. (2015). Metal-doped nitrogenated carbon as an efficient catalyst for direct $C{\\mathsf{O}}_{2}$ electroreduction to CO and hydrocarbons. Angew. Chem. Int. Ed. 54, 10758–10762. \n43. Zhao, C., Dai, X., Yao, T., Chen, W., Wang, X., Wang, J., Yang, J., Wei, S., Wu, Y., and Li, Y. (2017). Ionic exchange of metal-organic frameworks to access single nickel sites for efficient electroreduction of CO2. J. Am. Chem. Soc. 139, 8078–8081. \n44. Li, X., Bi, W., Chen, M., Sun, Y., Ju, H., Yan, W., Zhu, J., Wu, X., Chu, W., Wu, C., and Xie, Y. (2017). Exclusive Ni-N4 sites realize near-unity CO selectivity for electrochemical CO2 reduction. J. Am. Chem. Soc. 139, 14889– 14892. \n45. Yang, H.B., Hung, S.-F., Liu, S., Yuan, K., Miao, S., Zhang, L., Huang, X., Wang, H.-Y., Cai, W., Chen, R., et al. (2018). Atomically dispersed Ni (i) as the active site for electrochemical CO2 reduction. Nat. Energy 3, 140. \n46. Chen, $\\mathsf{Y}_{\\cdot,\\prime}$ Ji, S., Chen, C., Peng, Q., Wang, D., and Li, Y. (2018). Single-atom catalysts: synthetic strategies and electrochemical applications. Joule 2, 1242–1264. \n47. Cheng, Y., Zhao, S., Johannessen, B., Veder, J.P., Saunders, M., Rowles, M.R., Cheng, M., Liu, C., Chisholm, M.F., De Marco, R., et al. (2018). Atomically dispersed transition metals on carbon nanotubes with ultrahigh loading for selective electrochemical carbon dioxide reduction. Adv. Mater. 30, e1706287. \n48. Voiry, D., Shin, H.S., Loh, K.P., and Chhowalla, M. (2018). Low-dimensional catalysts for hydrogen evolution and $C{\\mathsf{O}}_{2}$ reduction. Nat. Rev. Chem. 1, 0105. \n49. Lim, R.J., Xie, M., Sk, M.A., Lee, J.-M., Fisher, A., Wang, X., and Lim, K.H. (2014). A review on the electrochemical reduction of ${\\mathsf{C O}}_{2}$ in fuel cells, metal electrodes and molecular catalysts. Catal. Today 233, 169–180. \n50. Prakash, G.S., Viva, F.A., and Olah, G.A. (2013). Electrochemical reduction of ${\\mathsf{C O}}_{2}$ over SnNafion\u0002 coated electrode for a fuel-cell-like device. J. Power Sources 223, 68–73. \n51. Kutz, R.B., Chen, Q., Yang, H., Sajjad, S.D., Liu, $Z.,$ and Masel, I.R. (2017). Sustainion imidazolium-functionalized polymers for carbon dioxide electrolysis. Energy Technol. 5, 929–936. \n52. Delacourt, C., Ridgway, P.L., Kerr, J.B., and Newman, J. (2008). Design of an electrochemical cell making syngas $(C O+H_{2})$ from $C{\\mathsf{O}}_{2}$ and $H_{2}O$ reduction at room temperature. J. Electrochem. Soc. 155, B42–B49. \n53. Weekes, D.M., Salvatore, D.A., Reyes, A., Huang, A., and Berlinguette, C.P. (2018). Electrolytic CO2 reduction in a flow cell. Acc. Chem. Res. 51, 910–918. \n54. Jhong, H.R., Brushett, F.R., and Kenis, P.J. (2013). The effects of catalyst layer deposition methodology on electrode performance. Adv. Energy Mater. 3, 589–599. \n55. Burke, K.A., and Jiao, F. (2016). Game changing development program-next generation life support project: oxygen recovery from carbon dioxide using ion exchange membrane electrolysis technology. Technical report. https://ntrs.nasa.gov/search.jsp? R=20160014804. \n56. Pan, $\\mathsf{Y}_{\\cdot,\\prime}$ Lin, R., Chen, Y., Liu, S., Zhu, W., Cao, X., Chen, W., Wu, K., Cheong, W.C., Wang, Y., et al. (2018). Design of single-atom Co-N5 catalytic site: a robust electrocatalyst for ${\\mathsf{C O}}_{2}$ reduction with nearly $100\\%$ CO selectivity and remarkable stability. J. Am. Chem. Soc. 140, 4218–4221. \n57. Kabir, S., Artyushkova, K., Serov, A., Kieferb, B., and Atanassova, P. (2016). Binding energy shifts for nitrogen-containing graphene-based electrocatalysts-experiments and DFT calculations. Surf. Interface Anal. 48, 293–300. \n58. Ushiro, M., Uno, K., Fujikawa, T., Sato, Y., Tohji, $\\mathsf{K}_{\\cdot,\\prime}$ Watari, F., Chun, W.-J., Koike, Y., and Asakura, K. (2006). X-ray absorption fine structure (XAFS) analyses of Ni species trapped in graphene sheet of carbon nanofibers. Phys. Rev. B 73, 144103. \n59. Yan, C., Li, H., Ye, Y., Wu, H., Cai, F., Si, R., Xiao, J., Miao, S., Xie, S., Yang, F., et al. (2018). Coordinatively unsaturated nickel-nitrogen sites towards selective and high-rate $C{\\mathsf{O}}_{2}$ electroreduction. Energy Environ. Sci. 11, 1204–1210. \n\n60. Jiang, $\\mathsf{K}_{\\cdot,\\prime}$ Chen, G., and Wang, H. (2018). Synthesis and performance characterizations of transition metal single atom catalyst for electrochemical $C{\\mathsf{O}}_{2}$ reduction. J. Vis. Exp. 134, e57380. \n\n61. Liu, S., Tao, H., Zeng, L., Liu, Q., Xu, Z., Liu, $\\cdot,$ and Luo, J.L. (2017). Shape-dependent electrocatalytic reduction of ${\\mathsf{C O}}_{2}$ to CO on triangular silver nanoplates. J. Am. Chem. Soc. 139, 2160–2163. \n\n62. Kornienko, N., Zhao, Y., Kley, C.S., Zhu, C., Kim, D., Lin, S., Chang, C.J., Yaghi, O.M., and Yang, P. (2015). Metal-organic frameworks for electrocatalytic reduction of carbon dioxide. J. Am. Chem. Soc. 137, 14129–14135. " + }, + { + "id": "10.1038_s41586-019-1431-9", + "DOI": "10.1038/s41586-019-1431-9", + "DOI Link": "http://dx.doi.org/10.1038/s41586-019-1431-9", + "Relative Dir Path": "mds/10.1038_s41586-019-1431-9", + "Article Title": "Maximized electron interactions at the magic angle in twisted bilayer graphene", + "Authors": "Kerelsky, A; McGilly, LJ; Kennes, DM; Xian, LD; Yankowitz, M; Chen, SW; Watanabe, K; Taniguchi, T; Hone, J; Dean, C; Rubio, A; Pasupathy, AN", + "Source Title": "NATURE", + "Abstract": "The electronic properties of heterostructures of atomically thin van der Waals crystals can be modified substantially by moire superlattice potentials from an interlayer twist between crystals(1,2). Moire tuning of the band structure has led to the recent discovery of superconductivity(3,4) and correlated insulating phases5 in twisted bilayer graphene (TBG) near the 'magic angle' of twist of about 1.1 degrees, with a phase diagram reminiscent of high-transition-temperature superconductors. Here we directly map the atomic-scale structural and electronic properties of TBG near the magic angle using scanning tunnelling microscopy and spectroscopy. We observe two distinct van Hove singularities (VHSs) in the local density of states around the magic angle, with an energy separation of 57 millielectronvolts that drops to 40 millielectronvolts with high electron/hole doping. Unexpectedly, the VHS energy separation continues to decrease with decreasing twist angle, with a lowest value of 7 to 13 millielectronvolts at a magic angle of 0.79 degrees. More crucial to the correlated behaviour of this material, we find that at the magic angle, the ratio of the Coulomb interaction to the bandwidth of each individual VHS (U/t) is maximized, which is optimal for electronic Cooper pairing mechanisms. When doped near the half-moire-band filling, a correlation-induced gap splits the conduction VHS with a maximum size of 6.5 millielectronvolts at 1.15 degrees, dropping to 4 millielectronvolts at 0.79 degrees. We capture the doping-dependent and angle-dependent spectroscopy results using a Hartree-Fock model, which allows us to extract the on-site and nearest-neighbour Coulomb interactions. This analysis yields a U/t of order unity indicating that magic-angle TBG is moderately correlated. In addition, scanning tunnelling spectroscopy maps reveal an energy-and doping-dependent threefold rotational-symmetry breaking of the local density of states in TBG, with the strongest symmetry breaking near the Fermi level and further enhanced when doped to the correlated gap regime. This indicates the presence of a strong electronic nematic susceptibility or even nematic order in TBG in regions of the phase diagram where superconductivity is observed.", + "Times Cited, WoS Core": 730, + "Times Cited, All Databases": 800, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000478017900042", + "Markdown": "# Maximized electron interactions at the magic angle in twisted bilayer graphene \n\nAlexander Kerelsky1, Leo J. McGilly1, Dante M. Kennes2, Lede Xian3, Matthew Yankowitz1, Shaowen Chen1,4, K. Watanabe5, T. Taniguchi5, James Hone6, Cory Dean1, Angel Rubio3,7\\* & Abhay N. Pasupathy1\\* \n\nThe electronic properties of heterostructures of atomically thin van der Waals crystals can be modified substantially by moiré superlattice potentials from an interlayer twist between crystals1,2. Moiré tuning of the band structure has led to the recent discovery of superconductivity3,4 and correlated insulating phases5 in twisted bilayer graphene (TBG) near the ‘magic angle’ of twist of about 1.1 degrees, with a phase diagram reminiscent of high-transitiontemperature superconductors. Here we directly map the atomicscale structural and electronic properties of TBG near the magic angle using scanning tunnelling microscopy and spectroscopy. We observe two distinct van Hove singularities (VHSs) in the local density of states around the magic angle, with an energy separation of 57 millielectronvolts that drops to 40 millielectronvolts with high electron/hole doping. Unexpectedly, the VHS energy separation continues to decrease with decreasing twist angle, with a lowest value of 7 to 13 millielectronvolts at a magic angle of 0.79 degrees. More crucial to the correlated behaviour of this material, we find that at the magic angle, the ratio of the Coulomb interaction to the bandwidth of each individual VHS (U/t) is maximized, which is optimal for electronic Cooper pairing mechanisms. When doped near the half-moiré-band filling, a correlation-induced gap splits the conduction VHS with a maximum size of 6.5 millielectronvolts at 1.15 degrees, dropping to 4 millielectronvolts at 0.79 degrees. We capture the doping-dependent and angle-dependent spectroscopy results using a Hartree–Fock model, which allows us to extract the on-site and nearest-neighbour Coulomb interactions. This analysis yields a U/t of order unity indicating that magic-angle TBG is moderately correlated. In addition, scanning tunnelling spectroscopy maps reveal an energy- and doping-dependent threefold rotational-symmetry breaking of the local density of states in TBG, with the strongest symmetry breaking near the Fermi level and further enhanced when doped to the correlated gap regime. This indicates the presence of a strong electronic nematic susceptibility or even nematic order in TBG in regions of the phase diagram where superconductivity is observed. \n\nVan der Waals heterostructures of atomically thin layers with a rotational misalignment yield a structural moiré superlattice, often inducing new electronic properties2,6,7. TBG is a particularly interesting case in which the band structure has two VHSs with energy separation determined by the moiré period2 and interlayer hybridization8–11. A continuum model analysis1 of the band structure of TBG predicted that near $1.1^{\\circ}$ , which is a ‘magic angle’, the separation tends to zero, creating a two-dimensional region in momentum space where the states have almost no dispersion. The low-energy physics of the electrons would then be largely determined by the Coulomb interaction and lead to the possibility of emergent many-body ground states6. Indeed, recent transport measurements have shown the presence of both superconducting3,4 and insulating states5 under these conditions. The phase diagram is reminiscent of unconventional superconductors, but in a two-dimensional, gate-tunable material with simple chemistry. These developments establish TBG as a model system in which bandwidth and interactions can be tuned using simple experimental knobs (changing the electrostatic gate voltage with a power supply can sweep both carrier density and displacement field within one device, which modifies bandwidth and interactions), thus paving the way towards understanding unconventional superconductivity. \n\nDespite rapid progress, the precise experimental atomic and electronic structure of TBG at the magic angle is unknown. This has posed a challenge for theoretical modelling—in particular, theory has not established the origin of the correlated insulating phases12–16 or whether the superconducting pairing is mediated by electronic interactions. Therefore, direct measurements of the atomic and low-energy electronic structure are required. Here we present measurements of the local angle- and doping-dependent atomic-scale structure and the local density of states (LDOS) of near-magic-angle TBG on hexagonal boron nitride (hBN) using scanning tunnelling microscopy (STM) and scanning tunnelling spectroscopy (STS) at $5.7\\mathrm{K}$ . Although previous STM works have explored TBG, measurements were at angles far from the magic angle8,17, or on conducting substrates where electrostatic doping is not possible and the Coulomb interaction is screened9–11. Our samples are nominally similar to transport devices in which superconductivity has been measured, although our samples do not have a top hBN layer in order to access the bilayer graphene with the STM tip. An optical image and schematic of a typical sample are shown in Fig. 1a, b. Figure 1c shows the structure of a TBG moiré. Within a moiré unit cell, the two layer atomic stacking arrangement displays regions of AA, AB/BA (Bernal) and saddle-point stacking17,18. Figure 1d–f shows typical atomic-resolution topographic images of TBG at various small angles. The bright spots are the AA sites, while the dark regions are the AB/BA sites8,17. No TBG-hBN moiré pattern is present because we have intentionally made the TBG-hBN angle large to minimize the hBN interaction. Without strain and disorder, a single moiré wavelength exists which can be used to determine the twist angle. In our samples and previous spatial studies, a small amount of heterostrain is present (arising in the conventional fabrication method) yielding a different moiré period along the principal directions of the moiré lattice. We use a comprehensive model (Supplementary Information section S1) to extract the precise local twist angle and strain, finding uniaxial strain between $0.1\\%$ and $0.7\\%$ at these small twist angles. Variability in strain or twist probably causes variable transport results, even within different regions of a single device4. \n\nOne important structural consideration in TBG is the nature of the saddle-point region at the AB/BA interface. At large twist angles $(>4^{\\circ})$ , the superlattice structure evolves smoothly, whereas at small angles $(<0.5^{\\circ})$ , AB/BA regions are maximized, producing topological domain walls at the saddle-point regions17,18. The magic angle is in an intermediate regime. Domain-wall-like lines are to some degree visible in all three angles in Fig. 1d–f. Figure 1g shows normalized height profiles along the direction of the next-nearest neighbour AA (dotted line in Fig. 1g) for the three angles, allowing direct comparison of the extent of each stacking arrangement (see Supplementary Information section S2 for bias dependence). We find that atomic rearrangements towards domain-wall saddle-point regions are important at all of these small angles, including $1.10^{\\circ}$ , which will be relevant to future theoretical modelling (for instance, it is predicted that this reconstruction suppresses other magic angles19). \n\n![](images/347ad60d790ac6e93287ecd3e02bb13906553b13f5981ec3ba1a71c526567421.jpg) \nFig. 1 | Atomic insights on TBG structure near the magic angle. a, Optical images of one of the measured samples. Dashed lines highlight the layers of hBN and the two twisted monolayers of graphene. The top is mid-fabrication, immediately after stacking, and the bottom is the final structure contacted (using the microsoldering technique described in Methods) with bismuth indium tin (BiInSn) on polypropylene carbonate (PPC). b, Sample schematic. c, Schematics of a real-space moiré pattern \ninterchanging between AA, AB/BA and saddle-point (SP) stacking. d–f, Atomic-resolution STM topographies on $2.02^{\\circ}$ , $1.10^{\\circ}$ and $0.79^{\\circ}$ TBG samples. Topographies were taken at $1\\mathrm{V}$ and $50\\mathrm{pA}$ , at $0.5\\mathrm{V}$ and $30\\mathrm{pA}$ , and at $0.5\\mathrm{V}$ and $50\\mathrm{pA}$ , respectively. g, Normalized spatial height profiles from the AA site to the second-nearest AA site, as delineated in the inset, for the three twist angles shown in d–f. \n\nFigure 2a shows STS measurements of the LDOS on the AA stacked regions for a series of small twist angles $3.49^{\\circ}$ to $0.79^{\\circ^{\\cdot}}.$ ) at zero external doping. The LDOS profiles show a filled (valence) and an unfilled (conduction) VHS (black arrows). The VHSs shift in energy towards the Dirac point with decreasing twist angle, as previously shown8. Figure 2d shows the VHS separation angle dependence. At $1.10^{\\circ}$ , where superconductivity is observed, there are still two distinct peaks in the LDOS separated by about $57\\pm2{\\mathrm{~meV}}.$ At the smallest angle studied here, $0.79^{\\circ}$ , the VHSs nearly merge, with a separation of $13\\pm2{\\mathrm{meV}}.$ \n\nWe compare the experimental spectra to tight-binding calculations (see Methods). We note that we use an intralayer hopping fitted to the experimental Fermi velocity for monolayer graphene, unlike previous work10,20 that used density functional theory monolayer band structures (which underestimate the Fermi velocity by about $20\\%$ , a manybody correlation effect that can be corrected using many-body GW self-energy calculations21; see Supplementary Information section S3). Figure 2b shows the results for angles of $1.10^{\\circ}$ and larger, matching the experimental VHS separations well, as plotted in Fig. 2d. At $1.10^{\\circ}$ , the VHS separation calculated by our tight-binding model is about $41\\mathrm{meV},$ comparable with the 57-meV STS value, but much larger than for other tight-binding models of TBG near $1.10^{\\circ}$ (less than $5\\mathrm{meV})^{3,22}$ . The larger intralayer hopping in our tight-binding model implies that the Fermi velocity vanishes at a smaller angle than previously reported22. We have considered other experimental effects that can affect the measured VHS separation and do not believe that they contribute substantially (Supplementary Information section S4). \n\nFigure 2c shows higher-resolution STS LDOS profiles at $0.79^{\\circ}$ versus the magic angle. Although the peaks at $0.79^{\\circ}$ are closer together than at $1.15^{\\circ}$ , the individual VHS width is not smaller. Extraction of the valence half-width reveals $10\\pm1\\mathrm{meV}$ at $1.15^{\\circ}$ and $11\\pm1\\mathrm{meV}$ at $0.79^{\\circ}$ . Extraction of the conduction half-width reveals $13\\pm1\\mathrm{meV}$ at $1.15^{\\circ}$ and $13\\pm1$ meV at $0.79^{\\circ}$ (the conduction half-widths drop to $9.5\\pm1$ and $10\\pm1\\mathrm{meV}$ when doped near the Fermi level; Extended Data Fig. 1f). Figure 2e shows the angle-dependent half-widths of the valence and conduction VHS peaks at zero external doping. The average peak half-widths gradually decrease with decreasing angle (about $30\\mathrm{meV}$ per degree) at angles above $1.5^{\\circ}$ . The width then sharply drops to about $10\\mathrm{meV}$ at the magic angle. The importance of electron correlations is determined by the ratio of on-site Coulomb interaction, $U_{:}$ to bandwidth, $t,$ of an electron in a single VHS band (that is isolated from other bands). Following simple geometric principles, $U$ decreases proportionally to $1/\\lambda,$ where $\\lambda$ is the moiré wavelength. Our angle-dependent measurements of bandwidth $t$ therefore imply that the ratio $U/t$ is maximum at the magic angle, and superconductivity arises in a single isolated VHS band15,16 with maximized electron correlations. We also note that the conduction VHS is wider at all angles, indicating band structure electron–hole asymmetry consistent with recent calculations19. \n\n![](images/e6cf84f269ad67dc3f753dbf79485b0b17f05a4748077fb1282e76b351f39f6a.jpg) \nFig. 2 $|\\mathbf{LDOS}$ and bandwidth of TBG at the magic angle. a, STS LDOS Measurements are taken in a closed loop at the $100\\mathrm{-meV}$ and 50-pA at zero external doping on moiré AA sites of $3.48^{\\circ}$ , $2.02^{\\circ}$ , $1.59^{\\circ}$ , $1.10^{\\circ}$ and setpoints with a $0.5\\mathrm{-meV}$ and $1\\mathrm{-meV}$ oscillation. d, Experimental versus $0.79^{\\circ}$ , normalized to the maximum value for each curve and vertically tight-binding VHS separation as a function of twist angle. e, Experimental offset for clarity. Arrows show several prominent features consistent at conduction and valence VHS half-widths versus tight-binding half-widths all angles—the VHSs (black arrows), the first dips (purple arrows) and a as a function of twist angle. f, STS LDOS on AA versus AB sites in $1.10^{\\circ}$ second smaller peak (green arrows) previously observed. With decreasing TBG. Error bars in d and e are derived from the sum of squares of the twist angle, all features shift towards the Fermi level. b, Tight-binding lock-in oscillation used to identify features ( $\\mathrm{0.5\\:meV}$ for near-magic angle, calculations of the LDOS at the measured angles down to $1.10^{\\circ}$ . c, High- $1\\mathrm{meV}$ for $0.79^{\\circ}$ and $10\\mathrm{meV}$ for $1.5^{\\circ}$ and above). energy-resolution zoom-in of STS LDOS on $1.15^{\\circ}$ and $0.79^{\\circ}$ AA sites. \n\nWe now turn to the doping-dependent AA site LDOS. Figure 3a, b shows spectra as a function of back-gate voltage on two TBG samples at $1.10^{\\circ}$ and $1.15^{\\circ}$ , limited in gate voltage by gate leakage (see Methods). The positions, shapes and separation of the VHSs are a sensitive function of doping. In the $1.15^{\\circ}$ sweep (Fig. 3b) we were able to dope past electron half-filling of the moiré superlattice, $-0.5n_{\\mathrm{s}}$ ( $\\dot{\\boldsymbol{n}}_{s}$ is four carriers per moiré unit cell), which was not possible in the $1.10^{\\circ}$ sample. A finer set of doping-dependent spectra around electron half-filling is shown in Fig. 3c. As the conduction VHS peak is crossing the Fermi level, it splits and a gap emerges that is maximized at a doping of about $-1.5\\times\\dot{1}0^{12}\\mathrm{cm}^{-2}$ (magenta in Fig. 3d). The gap persists for a doping range of $2\\times10^{11}\\mathrm{cm}^{-2}$ with a peak-to-peak value of $6.5\\pm0.5\\mathrm{meV.}$ In transport, the largest gap is observed at half-filling of the moiré conduction band. Based on our moiré unit cell area, this corresponds to a doping of $-1.55\\times10^{12}{\\mathrm{cm}}^{-2}$ , within the error of the spectroscopy gap doping. The persistence of the gap for $2\\times10^{11}\\mathrm{cm}^{-2}$ is also consistent with the half-filling insulator doping range in transport. Thus, this gap is naturally associated with the correlated insulator state. The magnitude of the spectroscopy gap, however, is much bigger than the activation energy of the resistance in transport measurements, probably owing to disorder averaging, which always produces smaller activation gaps in transport than spectroscopy23. \n\nOne important question that we can address is whether the gap opens precisely at the VHS peak or simply at a moiré lattice commensurate filling. To quantitatively investigate this, we integrate the LDOS over a small range $(1.5\\mathrm{meV})$ on the electron-versus-hole side of the Fermi level at each doping. The integrated LDOS profiles are plotted in Fig. 3e. The dip in the profiles corresponds to the correlated gap, which is maximized when the two curves cross within the dip at $-1.5\\times10^{12}\\mathrm{cm}^{-2}$ (about $0.5n_{\\mathrm{s}}^{\\cdot},$ . The highest integrated LDOS where the curves cross, $-1.87\\times10^{12}{\\mathrm{cm}}^{-2}$ (about $0.6n_{s}^{\\cdot},$ , corresponds to the VHS peak precisely at the Fermi level. Figure 3d shows the spectra at these two dopings. The analysis reveals that the gap opens on the shoulder of the VHS rather than the peak. Such a gap is more consistent with a Mott insulator, which occurs at commensurate filling, rather than a density wave order, which more naturally occurs at a density of states peak. This also provides band structure explanations for the extreme anisotropies seen in transport24 on either side of half-filling, where the temperature-dependent resistance, effective mass and Hall coefficient are strongly asymmetric. Interestingly, we note that the doping difference between the maximized correlated gap and the VHS peak at the Fermi level is the same as the doping difference between the half-filling correlated insulator state and the highest-transition-temperature superconducting dome in transport. In transport, additional gaps emerge at quarter and three-quarter filling of the moiré bands4,5. We have not seen these, possibly owing to the measurement temperature. \n\nNext, we discuss the separation between the two VHSs, which is maximum at charge neutrality and reduced with electron/hole doping. This behaviour is reminiscent of the quasiparticle gap in twodimensional semiconductors with doping. We model this with a simple one-band model on a honeycomb lattice with nearest-neighbour hopping $t_{0}=16.3\\ \\mathrm{meV}.$ We include correlations via on-site and nearest-neighbour repulsive interactions $U$ and $V_{1}$ , respectively, and study the spectrum of the system in the Hartree–Fock approximation (Supplementary Information section S5). The results are shown in Fig. 3f. The nearest-neighbour interaction $V_{1}$ renormalizes the hopping via its Fock contribution, causing a doping-dependent VHS separation. $V_{1}=6.26\\mathrm{meV}$ best reproduces the experimental dependence of VHS separation, as shown in Fig. 3g, plotting theoretical separation as a function of chemical potential and experimental separation as a function of doping. Theory captures the relatively doping-independent separation near charge neutrality and the strong decrease with higher doping. In this simple model, the on-site interaction $U$ opens a gap at half-filling owing to Fermi surface nesting. Although this level of theory is inadequate to determine the true nature of the gap, we use it as a simple way to quantify the on-site U. $U=4.03\\mathrm{meV}$ approximately reproduces the STS gap, showing that magic-angle TBG is a moderately correlated material with $U/t$ of order unity. The peak shapes in Fig. 3a, b also display interesting doping dependence: when doped near the Fermi level, they sharpen, whereas when doped away from the Fermi level, they become highly asymmetric (quantified for the valence VHS in Extended Data Fig. 2). This is characteristic of spectroscopy on strongly correlated materials25–27 (see Supplementary Information section S6 for further discussion). \n\n![](images/9490bf6da9376f3c9b0fdfb1d3f84433e65fd2aa113ecbff92881638dcb0f130.jpg) \nFig. 3 | Doping dependence of magic-angle LDOS peaks. a, b, STS LDOS on a $1.10^{\\circ}$ AA site (a) and a $1.15^{\\circ}$ AA site (b) as a function of doping. Curves are offset for clarity. Doping is given in units of $\\mathrm{cm}^{-2}$ and fractional filling of the moiré superlattice with four electrons or holes $(n_{s})$ . In a, spectra were taken in a closed loop at $200\\mathrm{-meV}$ and 50-pA setpoints with an oscillation of $1\\mathrm{meV}$ for $1.10^{\\circ}$ . In b, spectra were taken in a closed loop at $100\\mathrm{-meV}$ and 50-pA setpoints with an oscillation of $0.5\\mathrm{meV}$ for $1.15^{\\circ}$ . c, Zoom-in to $\\mathbf{b}$ around half-filling of the moiré superlattice $(-0.5n_{s})$ , revealing a gap as the VHS crosses the Fermi level $E_{\\mathrm{{F}}}$ d, Zoom-in of the conduction VHS at $-1.5\\times10^{12}\\mathrm{cm}^{-2}\\left(-0.5n_{s}\\right)$ (magenta) and \n$-1.87\\times10^{12}\\mathrm{cm}^{-2}\\left(-0.6n_{s}\\right)$ (red), where the gap is most prominent and the VHS peak is at $E_{\\mathrm{F}}$ respectively. e, Integrated LDOS from $E_{\\mathrm{F}}$ to $\\delta=1.5\\mathrm{meV}$ below and above the Fermi level, showing the crossings where the gap is maximized and where the VHS peak is at the Fermi level, as highlighted in d. f, Hartree–Fock mean-field density of states, offset as a function of chemical potential shift from neutrality, $E_{\\mathrm{d}}$ g, Experimental VHS separation versus doping and mean-field VHS separation versus chemical potential $(E_{\\mathrm{d}}-\\mu)$ . The uncertainty is derived from the sum of squares of the lock-in oscillation used to identify features. \n\nA natural question is how the correlated gap evolves with angle. We present doping-dependent LDOS of the $0.79^{\\circ}$ TBG in Extended Data Fig. 1. Most of the observed phenomenology is the same as at the magic angle: changing VHS shapes, separation and a gap emerging around electron half-filling. Compared to the correlated gap at the magic angle, the half-filling gap at $0.79^{\\circ}$ is less pronounced and smaller, being $4\\pm1$ meV as opposed to $6.5\\pm1\\mathrm{meV}$ observed at $1.15^{\\circ}$ . This corroborates that correlation effects are reduced at $0.79^{\\circ}$ (see Supplementary Information section S7 for further discussion). \n\nNext we turn to the LDOS spatial dependence in magic-angle TBG. Figure 4a shows an STS map energy slice at the conduction VHS peak (zero external doping) of one moiré cell at $1.15^{\\circ}$ When undoped, LDOS maps at energies around the VHS peaks show the same contrast as the topographies. For comparison, the tight-binding probability density (see Methods) of a single wavefunction at this energy is plotted in Fig. 4b. We compare line profiles of the experimental and tight-binding LDOS in Fig. 4c. The tight-binding wavefunction systematically underestimates the saddle-point region intensity and is more confined around the AA site than in the experiment, something to consider in future calculations. \n\nFinally, we focus on the doping- and energy-dependent STS maps. In a perfect moiré lattice at the single particle level, the LDOS should have three-fold (C3) rotational symmetry. The small amount of strain present, however, introduces some symmetry breaking. We explore whether this symmetry breaking is uniform with energy and doping (which could be trivially due to the strain), or is enhanced at certain energies28,29 and dopings. To quantify the energy-dependent anisotropy, we use a technique shown in Fig. 4d (described in Methods). Energy-dependent anisotropies for three dopings below half-filling are plotted in Fig. 4e with AA site LDOS averages from the corresponding maps. The energy-dependent asymmetry is not uniform; however, despite large asymmetries at other energies, at around the conduction VHS the LDOS is symmetric at these dopings. This is visualized in the map slices at the conduction VHS peak and $\\pm5\\mathrm{meV}$ around it, shown in the top three rows of Fig. 4g. This is in stark contrast to Fig. 4f at half-filling in doping when the correlated gap emerges. In this situation, the anisotropy is highly enhanced at energies around the gap, visualized in the bottom row of Fig. 4g, showing the map slices at and around the correlated gap. The LDOS strongly breaks three-fold (C3) symmetry around the correlated gap, where the wavefunction was symmetric at lower dopings. Additionally, the symmetry breaking at all dopings is strongest in a narrow region of energy around the Fermi level, as evidenced by the anisotropy peaks in Fig. 4e, f, which shift with doping (full spatial slices are shown in Supplementary Information section S8). These findings indicate that the electronic structure is nematic, with the strongest nematicity near half-filling. Two possibilities exist to explain the observed nematicity: (1) it is possible that the electronic structure has a strong nematic susceptibility and strain breaks the three-fold (C3) symmetry allowing visualization of the nematic susceptibility, as recently observed in the iron pnictides in the high-temperature tetragonal phase28,30; and (2) it is possible that a true nematic order exists, independent of strain. In this scenario, we would expect domains of nematic order with different orientation, which we have not observed so far. Future measurements should focus on this, because our samples were not uniform over large enough areas to test for this (Supplementary Information section S9). Whether a translational symmetry breaking occurs simultaneously (that is, by Fermi surface nesting31; see Supplementary Information section S10) is also unclear. \n\n![](images/fcb5052800c858f3f31dab2f261c14bf10579cec303f0fd3f6680903f0c6eece.jpg) \nFig. 4 | Wavefunctions and symmetry breaking in magic-angle TBG under doping. a, STS LDOS spatial map at $50\\mathrm{meV}$ above the $E_{\\mathrm{F}}$ value of a moiré cell (centred at AA) in zero externally doped $1.15^{\\circ}$ TBG. b, Probability density distribution of a single K-point wavefunction $\\varPsi;$ calculated using tight binding. c, Spatial line cuts comparing the experimental/tight-binding LDOS in the nearest and second-nearest AA directions. d, Procedure for quantifying anisotropy, as outlined in the text. The top row shows the three rotations of an isolated AA site Wigner–Seitz cell and the bottom row shows the three combinations of the magnitude of the difference between the cells. e, Averaged STS map AA site LDOS profiles and their anisotropy as a function of energy for three dopings below half electron or hole filling $(\\pm0.5n_{s})$ . Dashed lines correspond to the Fermi level, the conduction VHS peak and $\\pm5\\mathrm{meV}$ around the \n\nOur spectroscopic measurements of magic-angle TBG provide insights into the nature of the superconducting and insulating states seen in transport. The VHS separation is larger than previously thought around $1.1^{\\circ}$ , implying that the physics of correlated states is to be understood in the context of doping through a single VHS. Regarding superconducting order, electronic pairing mechanisms such as spin fluctuations are expected to be important when the ratio of the on-site Coulomb interaction $U$ to the bandwidth $t$ is large. On the other hand, in phonon-mediated pairing scenarios, the superconducting transition temperature is improved by lowering the Coulomb pseudopotential (proportional to $U$ ) and increasing the density of states at the Fermi level. Our spectroscopic results show that $U/t$ is maximized near $1.1^{\\circ}$ . Superconductivity in TBG is thus observed where $J{=}U^{2}/t$ is maximized, conditions that maximize electronic rather than phonon-based pairing. The insulating gap that emerges at half-filling of magic-angle TBG is not conduction VHS peak for each doping in the first three rows of $\\mathbf{g}$ . f, Averaged STS map AA site LDOS at half electron filling $(-0.5n_{s})$ , around the correlated gap, and the associated enhanced anisotropy. Dashed lines correspond to the newly split peaks and the correlated gap ( $\\dot{.}-3\\mathrm{meV},$ Fermi level, $4\\mathrm{meV},$ , which are spatially plotted in the bottom row of g. g, STS spatial images corresponding to the dopings and dashed lines in e and f. The first three rows are at dopings below half-filling, as indicated, and at energies $5\\mathrm{meV}$ below the conduction VHS peak, at the conduction VHS peak and $5\\mathrm{meV}$ above the conduction VHS peak. The final row is at half electron filling, at energies $3\\mathrm{meV}$ below the correlated gap (lower split peak), in the correlated gap (Fermi level) and $4\\mathrm{meV}$ above the correlated gap (higher split peak), as shown by the dashed lines in f. \n\nat the peak of the VHS, and is therefore more consistent with a Mott insulator rather than a density wave picture. Our observation of energy- and doping-dependent symmetry breaking, maximized near the correlated gap at half-filling, is indicative of a strong nematic electronic susceptibility or order in magic-angle TBG. The interaction of such ordered states with superconductivity in TBG remains to be investigated. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586- 019-1431-9. \n\n# Received: 23 December 2018; Accepted: 14 June 2019; Published online 31 July 2019. \n\n1. Bistritzer, R. & MacDonald, A. H. Moiré bands in twisted double-layer graphene. Proc. Natl Acad. Sci. USA 108, 12233–12237 (2011). \n2. Lopes dos Santos, J. M. B., Peres, N. M. R. & Castro Neto, A. H. Graphene bilayer with a twist: electronic structure. Phys. Rev. Lett. 99, 256802 (2007). \n3. Cao, Y. et al. Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43–50 (2018). \n4. Yankowitz, M. et al. Tuning superconductivity in twisted bilayer graphene. Science 363, 1059–1064 (2019). \n5. Cao, Y. et al. Correlated insulator behaviour at half-filling in magic-angle graphene superlattices. Nature 556, 80–84 (2018). \n6. Wu, F., Lovorn, T., Tutuc, E. & MacDonald, A. H. Hubbard model physics in transition metal dichalcogenide moiré bands. Phys. Rev. Lett. 121, 026402 (2018). \n7.\t Xian, L., Kennes, D. M., Tancogne-Dejean, N., Altarelli, M. & Rubio, A. Multi-flat bands and strong correlations in twisted bilayer boron nitride. Preprint at https://arxiv.org/abs/1812.08097 (2018). \n8. Wong, D. et al. Local spectroscopy of moiré-induced electronic structure in gatetunable twisted bilayer graphene. Phys. Rev. B 92, 155409 (2015). \n9. Li, G. et al. Observation of Van Hove singularities in twisted graphene layers. Nat. Phys. 6, 109–113 (2010). \n10.\t Brihuega, I. et al. Unraveling the intrinsic and robust nature of van Hove singularities in twisted bilayer graphene by scanning tunneling microscopy and theoretical analysis. Phys. Rev. Lett. 109, 196802 (2012). \n11.\t Yin, L.-J., Qiao, J.-B., Zuo, W.-J., Li, W.-T. & He, L. Experimental evidence for non-Abelian gauge potentials in twisted graphene bilayers. Phys. Rev. B 92, 081406 (2015). \n12.\t Yuan, N. F. Q. & Fu, L. Model for the metal-insulator transition in graphene superlattices and beyond. Phys. Rev. B 98, 045103 (2018). \n13.\t Po, H. C., Zou, L. J., Vishwanath, A. & Senthil, T. Origin of Mott insulating behavior and superconductivity in twisted bilayer graphene. Phys. Rev. X 8, 031089 (2018). \n14.\t Padhi, B., Setty, C. & Phillips, P. W. Doped twisted bilayer graphene near magic angles: proximity to Wigner crystallization, not Mott insulation. Nano Lett. 18, 6175–6180 (2018). \n15.\t Isobe, H., Yuan, N. F. Q. & Fu, L. Unconventional superconductivity and density waves in twisted bilayer graphene. Preprint at https://arxiv.org/ abs/1805.06449 (2018). \n16.\t Kennes, D. M., Lischner, J. & Karrasch, C. Strong correlations and d+id superconductivity in twisted bilayer graphene. Preprint at https://arxiv.org/ abs/1805.06310 (2018). \n17.\t Huang, S. et al. Topologically protected helical states in minimally twisted bilayer graphene. Phys. Rev. Lett. 121, 037702 (2018). \n18.\t Yoo, H. et al. Atomic and electronic reconstruction at van der Waals interface in twisted bilayer graphene. Preprint at https://arxiv.org/abs/1804.03806 (2018). \n19.\t Carr, S., Fang, S., Zhu, Z. & Kaxiras, E. An exact continuum model for low-energy electronic states of twisted bilayer graphene. Preprint at https://arxiv.org/ abs/1901.03420 (2019). \n20.\t Trambly de Laissardière, G., Mayou, D. & Magaud, L. Localization of Dirac electrons in rotated graphene bilayers. Nano Lett. 10, 804–808 (2010). \n21.\t Grüneis, A. et al. Electron-electron correlation in graphite: a combined angle-resolved photoemission and first-principles study. Phys. Rev. Lett. 100, 037601 (2008). \n22.\t Trambly de Laissardière, G., Mayou, D. & Magaud, L. Numerical studies of confined states in rotated bilayers of graphene. Phys. Rev. B 86, 125413 (2012). \n23.\t Xia, F., Farmer, D. B., Lin, Y.-m. & Avouris, P. Graphene field-effect transistors with high on/off current ratio and large transport band gap at room temperature. Nano Lett. 10, 715–718 (2010). \n24.\t Cao, Y. et al. Strange metal in magic-angle graphene with near Planckian dissipation. Preprint at https://arxiv.org/abs/1901.03710 (2019). \n25.\t Koralek, J. D. et al. Laser based angle-resolved photoemission, the sudden approximation, and quasiparticle-like spectral peaks in BSCCO. Phys. Rev. Lett. 96, 017005 (2006). \n26.\t Mo, S. K. et al. Prominent quasiparticle peak in the photoemission spectrum of the metallic phase of $V_{2}0_{3}$ . Phys. Rev. Lett. 90, 186403 (2003). \n27.\t Valla, T. et al. Coherence–incoherence and dimensional crossover in layered strongly correlated metals. Nature 417, 627–630 (2002). \n28.\t Rosenthal, E. P. et al. Visualization of electron nematicity and unidirectional antiferroic fluctuations at high temperatures in NaFeAs. Nat. Phys. 10, 225–232 (2014). \n29.\t Li, S.-Y. et al. Evidence of electron-electron interactions around Van Hove singularities of a graphene Moiré superlattice. Preprint at https://arxiv.org/ abs/1702.03501 (2017). \n30.\t Andrade, E. F. et al. Visualizing the nonlinear coupling between strain and electronic nematicity in the iron pnictides by elasto-scanning tunneling spectroscopy. Preprint at https://arxiv.org/abs/1812.05287 (2018). \n31.\t Kim, Y. et al. Charge inversion and topological phase transition at a twist angle induced van Hove singularity of bilayer graphene. Nano Lett. 16, 5053–5059 (2016). \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 \n\n# Methods \n\nExperimental setup. Our fabrication of TBG samples followed the established ‘tearing’ method, using PPC as a polymer to sequentially pick up hBN, then half of a piece of graphene, followed by the second half but with a twist angle. This structure was flipped over and placed on an $\\mathrm{Si}/\\mathrm{SiO}_{2}$ chip. Direct contact was made to the TBG via microsoldering with Field’s metal32, keeping temperatures below $80^{\\circ}\\mathrm{C}$ during the entire process to minimize the chance of layers rotating back to AB/BA stacking, which occurs when the structures are annealed. \n\nUltrahigh-vacuum STM/STS measurements were carried out in a home-built 5.7-K ultrahigh-vacuum STM. All tips used in this study were prepared on Au (111) and calibrated to be atomically sharp and to detect the Au (111) Shockley surface state via STS. Tens of freshly prepared tips were used in this study to ensure the consistency and accuracy of the findings. \n\nGate doping estimation. Owing to the PPC in our gate structure, we estimate gate-dependent carrier concentration by fabricating a parallel plate capacitor and measuring the capacitance per unit area in the STM at $5.7\\mathrm{K}$ . All of our sample gating is limited to where gate leakage is below a nanoampere. \n\nAnisotropy quantification technique. As shown in Fig. 4d, we begin by cropping to a single Wigner–Seitz cell of the triangular lattice formed by the LDOS in TBG. We affine-transform this cell to a perfect hexagonal shape to remove any effect of strain. Any breaking of three-fold (C3) symmetry in the LDOS would imply that this cell is not symmetric under $120^{\\circ}$ and $240^{\\circ}$ degree rotations, as illustrated in Fig. 4d. We hence calculate the energy-dependent anisotropy: $\\begin{array}{r}{A(E)=\\frac{1}{3}\\Bigg(\\frac{\\mid I_{0^{\\circ}}(E)-I_{120^{\\circ}}(E)\\mid}{n_{\\mathrm{pixel}}}+\\frac{\\mid I_{0^{\\circ}}(E)-I_{240^{\\circ}}(E)\\mid}{n_{\\mathrm{pixel}}}+\\frac{\\mid I_{120^{\\circ}}(E)-I_{240^{\\circ}}(E)\\mid}{n_{\\mathrm{pixel}}}\\Bigg),}\\end{array}$ , where I120°( ) and $I_{240^{\\circ}}(E)$ refer to the spatial LDOS profiles of the $120^{\\circ}.$ - and $240^{\\circ}$ -rotated Wigner–Seitz cells respectively and $n_{\\mathrm{pixel}}$ is the number of pixels. \n\nTight-binding calculations. We model the twisted bilayer graphene system with the following tight-binding Hamiltonian20: \n\n$$\nH=\\sum_{i,j}t_{i j}|i j|\n$$ \n\nwhere $t_{i j}$ is the hopping parameter between $p z$ orbitals at the two lattice sites $r_{i}$ and $r_{j},$ with the following form: \n\n$$\nt_{i j}=(1-n^{2})\\gamma_{0}\\mathrm{exp}\\Bigg[\\lambda_{1}\\Bigg(1-\\frac{|r_{i}-r_{j}|}{a}\\Bigg)\\Bigg]+n^{2}\\gamma_{1}\\mathrm{exp}\\Bigg[\\lambda_{2}\\Bigg(1-\\frac{|r_{i}-r_{j}|}{c}\\Bigg)\\Bigg]\n$$ \n\nwhere $a=1.412\\mathrm{\\AA}$ is the in-plane C–C bond length, $c=3.36\\mathrm{\\AA}$ is the interlayer separation, $n$ is the direction cosine of $r_{i}-r_{j}$ along the out of plane axis (z axis), $\\gamma_{0}$ $(\\gamma_{_1})$ is the intralayer (interlayer) hopping parameter, and $\\lambda_{1}\\left(\\lambda_{2}\\right)$ is the intralayer (interlayer) decay constant. This tight-binding model has been shown to reproduce the low-energy structure of TBG calculated by local density functional theory calculations with the following values for the parameters: $\\gamma_{0}=-2.7\\mathrm{eV},\\gamma_{1}=0.48\\mathrm{eV},$ $\\lambda_{1}=3.15$ and $\\lambda_{2}=7.50$ . However, the Fermi velocity for monolayer graphene is usually $20\\%$ larger than what is calculated in density functional theory owing to correlation effects that are captured by GW calculations21. To incorporate those effects, we consider a larger intralayer hopping $\\gamma_{0}^{\\prime}=1.2\\gamma_{0}$ (ref. 21) (the experimental parameter) as previously done8,10 (see Supplementary Information section S3). \n\nFor the calculation of LDOS, we employ the Lanczos recursive method33 to calculate the LDOS in two twisted graphene sheets in real space with a system size larger than $200\\mathrm{nm}\\times200\\mathrm{nm}$ with an effective smearing of 1 meV. For the Hartree– Fock mean-field interactions model, see Supplementary Information section S5. \n\n# Data availability \n\nThe data presented in this work is available upon reasonable request to A.N.P. \n\n# Code availability \n\nCode for the analysis described in Methods section ‘Anisotropy quantification technique’ and other analyses presented in this paper are available upon reasonable request. \n\n32.\t Girit, Ç. Ö. & Zettl, A. Soldering to a single atomic layer. Appl. Phys. Lett. 91, 193512 (2007). \n33.\t Wang, Z. F., Liu, F. & Chou, M. Y. Fractal Landau-level spectra in twisted bilayer graphene. Nano Lett. 12, 3833–3838 (2012). \n\nAcknowledgements We thank A. Millis, J. Schmalian, L. Fu, R. Fernandes and S. Todadri for discussions. This work is supported by the Programmable Quantum Materials (Pro-QM) programme at Columbia University, an Energy Frontier Research Center established by the Department of Energy (grant DESC0019443). Equipment support is provided by the Office of Naval Research (grant N00014-17-1-2967) and Air Force Office of Scientific Research (grant FA9550-16-1-0601). Support for sample fabrication at Columbia University is provided by the NSF MRSEC programme through Columbia in the Center for Precision Assembly of Superstratic and Superatomic Solids (DMR-1420634). Theoretical work was supported by the European Research Council (ERC-2015- AdG694097). The Flatiron Institute is a division of the Simons Foundation. L.X. acknowledges the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement number 709382 (MODHET). A.N.P. and A.R. acknowledge support from the Max Planck—New York City Center for Non-Equilibrium Quantum Phenomena. D.M.K. acknowledges funding from the Deutsche Forschungsgemeinschaft through the Emmy Noether programme (KA 3360/2-1). C.D. acknowledges support by the Army Research Office under W911NF-17-1-0323 and The David and Lucile Packard foundation. \n\nAuthor contributions A.K. performed STM measurements. L.J.M., M.Y. and S.C. fabricated samples for STM measurements. A.K. and L.J.M. performed experimental data analysis. K.W. and T.T. provided hBN crystals. D.M.K. and L.X. performed theoretical calculations. J.H., C.D., A.R. and A.N.P. advised. A.K. wrote the manuscript with assistance from all authors. \n\nCompeting interests : The authors declare no competing interests. \n\nAdditional information \nSupplementary information is available for this paper at https://doi.org/ 10.1038/s41586-019-1431-9. \nCorrespondence and requests for materials should be addressed to A.R. or A.N.P. \nPeer review information Nature thanks Miguel M. Ugeda and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/ reprints. \n\n![](images/4dd555aa45d5ede1c2754f9cd37157a4f8745e4df7a2bfb00cd668bbf0bb84a5.jpg) \nExtended Data Fig. 1 $|\\mathbf{0.79^{\\circ}L D O S}$ doping dependence. a, STS LDOS as a function of doping at a $0.79^{\\circ}$ TBG AA site for a doping range of $-0.95n_{\\mathrm{s}}$ to $0.8n_{s}$ ( $\\dot{n}_{\\mathrm{s}}$ being full filling of the moiré band with four electrons or holes). Spectra were taken in a closed loop at $100\\mathrm{-meV}$ and 50-pA setpoints with a $0.5\\mathrm{-meV}$ oscillation. b, Experimental VHS separation versus doping (bottom axis) and theoretical mean-field VHS separation as a function of chemical potential $(E_{\\mathrm{d}}-\\mu)$ relative to charge neutrality (top axis) for the $0.79^{\\circ}$ doping-dependent LDOS. c, LDOS comparison of the \ncorrelated gap at half-filling $(-0.5n_{s})$ in $1.15^{\\circ}$ TBG and $0.79^{\\circ}$ TBG. d, Peak-to-peak gap size as a function of doping, offset to half-filling $(0.5n_{s})$ for $1.15^{\\circ}$ and $0.79^{\\circ}$ , where $x$ is additional carrier doping in carriers per square centimetre around half-filling. e, Comparison of $0.79^{\\circ}$ , $1.15^{\\circ}$ and $1.10^{\\circ}\\mathrm{LDOS}$ when doped near the Fermi level, which is $0\\mathrm{V}$ in the plot. The doping level of each curve is indicated in the legend. Error bars in b and d are estimated from the sum of squares of the lock-in oscillation $(0.5\\mathrm{meV}$ for $1.15^{\\circ}$ and $1\\mathrm{meV}$ for $0.79^{\\circ}$ ) used to determine feature positions. \n\n![](images/67840a80ae589777f6c8ea695e8a55642919d57a0c89dfe0eb3ac775e43653a4.jpg) \nExtended Data Fig. 2 | Asymmetry in valence VHS with doping. Halfwidths of the trailing edge and leading edge of the valence VHS as a function of doping in the $1.15^{\\circ}$ sample. Error bars are estimated from the sum of squares of the lock-in oscillation $\\mathrm{(0.5~meV)}$ ) used, which determines the peak half-width position. " + }, + { + "id": "10.1016_j.joule.2019.02.012", + "DOI": "10.1016/j.joule.2019.02.012", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2019.02.012", + "Relative Dir Path": "mds/10.1016_j.joule.2019.02.012", + "Article Title": "A Metal-Organic Framework Host for Highly Reversible Dendrite-free Zinc Metal Anodes", + "Authors": "Wang, Z; Huang, JH; Guo, ZW; Dong, XL; Liu, Y; Wang, YG; Xia, YY", + "Source Title": "JOULE", + "Abstract": "Zinc metal featuring low cost, high capacity, low potential, and environmental benignity is an exciting anode material for aqueous energy storage devices. Unfortunately, the dendrite growth, limited reversibility, and undesired hydrogen evolution hinder its application. Herein, we demonstrate that MOF ZIF-8 annealed at 500 degrees C (ZIF-8-500) can be used as a host material for high-efficiency (approximately 100%) and dendrite-free Zn plating and stripping because of its porous structure, trace amount of zinc in the framework, and high over-potential for hydrogen evolution. The Zn@ZIF-8-500 anode (i.e., ZIF-8-500 pre-plated with 10.0 mAh cm(-2) Zn) is coupled with an activated carbon cathode or an I-2 cathode to form a hybrid supercapacitor or a rechargeable battery, respectively. The supercapacitor delivers a high energy density of 140.8 Wh kg(-1) (normalized to the mass of active materials in electrodes) while retaining 72% capacity over 20,000 cycles, and the battery shows a long life of 1,600 cycles.", + "Times Cited, WoS Core": 753, + "Times Cited, All Databases": 780, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000467969300015", + "Markdown": "# Article A Metal-Organic Framework Host for Highly Reversible Dendrite-free Zinc Metal Anodes \n\n![](images/f27138015f83fbd0d29b1ee709afdf33ab2028a687b82d2b9c4bbf3d4f8b736e.jpg) \n\nZn-based MOF ZIF-8-500 (annealed at $500^{\\circ}\\mathrm{C})$ possesses the trace amount of $Z n^{0}$ in the host framework and the high over-potential for hydrogen evolution. The resulting ZIF-8-500 anode exhibits high efficiency (close to $100\\%$ and dendritefree Zn plating/stripping. \n\nZhuo Wang, Jianhang Huang, Zhaowei Guo, Xiaoli Dong, Yao Liu, Yonggang Wang, Yongyao Xia \nygwang@fudan.edu.cn \n\n# HIGHLIGHTS \n\nMOF is first employed as the host for high efficiency and dendritefree Zn anode \n\nThe results show a new and lowcost avenue for developing highly reversible zinc anode \n\nThe AC//Zn@ZIF-8-500 supercapacitor delivers $72\\%$ capacity retention after 20,000 cycles \n\nThe $\\ensuremath{\\vert_{2}//Z n@}$ ZIF-8-500 battery shows a long life of 1,600 cycles \n\n# Article A Metal-Organic Framework Host for Highly Reversible Dendrite-free Zinc Metal Anodes \n\nZhuo Wang,1 Jianhang Huang,1 Zhaowei Guo,1 Xiaoli Dong,1 Yao Liu,1 Yonggang Wang,1,2,\\* and Yongyao Xia1 \n\n# SUMMARY \n\nZinc metal featuring low cost, high capacity, low potential, and environmental benignity is an exciting anode material for aqueous energy storage devices. Unfortunately, the dendrite growth, limited reversibility, and undesired hydrogen evolution hinder its application. Herein, we demonstrate that MOF ZIF-8 annealed at $\\mathsf{500^{\\circ}C}$ (ZIF-8-500) can be used as a host material for high-efficiency (approximately $100\\%$ ) and dendrite-free Zn plating and stripping because of its porous structure, trace amount of zinc in the framework, and high over-potential for hydrogen evolution. The Zn@ZIF-8-500 anode (i.e., ZIF-8-500 pre-plated with $10.0\\ m A\\mathrm{h}\\ c m^{-2}\\ Z_{n})$ is coupled with an activated carbon cathode or an $\\mathsf{I}_{2}$ cathode to form a hybrid supercapacitor or a rechargeable battery, respectively. The supercapacitor delivers a high energy density of $140.8\\mathsf{W h}\\mathsf{k g}^{-1}$ (normalized to the mass of active materials in electrodes) while retaining $72\\%$ capacity over 20,000 cycles, and the battery shows a long life of 1,600 cycles. \n\n# INTRODUCTION \n\nThe ever-increasing demand for renewable energy evokes the enthusiasm to develop highly safe, highly stable, low cost, and environmentally friendly electrochemical energy storage systems (rechargeable batteries and supercapacitors).1–10 Aqueous zinc $(Z\\mathsf{n})$ -based batteries and supercapacitors have been considered as promising candidates for electrochemical energy storage because of the inherent advantages of the $Z n$ anode, involving natural abundance, low cost, nontoxicity, high safety, high capacity $(820m\\mathsf{A h\\thinspace g}^{-1})$ ), and low potential.11–13 Recently, several rechargeable $Z n$ -based batteries and supercapacitors using a mild aqueous electrolyte (pH is close to 7), such as $\\mathsf{M n O}_{2}//2\\mathsf{n},^{14-19}\\mathsf{V}_{2}\\mathsf{O}_{5}//2\\mathsf{n},^{20-22}$ hexacyanoferrate//Zn, $^{23-25}\\ |_{2}//Z n$ batteries,26–30 and activated carbon (AC)//Zn supercapacitors,31–34 demonstrated excellent performance, showing a very bright perspective. However, the practical application is still much hindered by the poor cycle life and limited utilization efficiency of the Zn anode. For all of these recent reports, an excess Zn anode must be employed to ensure the stable operation. \n\nIt is well known that the Zn anode shows a much improved plating and stripping reversibility in neutral electrolyte compared to that in alkaline electrolyte, which thus encouraged the research about Zn-based batteries and supercapacitors with the mild electrolyte.11,19,20,35–38 However, the stability of the Zn anode in the mild electrolyte is still much limited by several factors. First, the dendrite growth still exists during plating and stripping, leading to safety issues. Second, the undesired hydrogen evolution (i.e., $H_{2}O$ decomposition) at the anode not only limits the \n\n# Context & Scale \n\nAqueous Zn-based batteries and supercapacitors have been considered as promising candidates for electrochemical energy storage devices because of the inherent advantages of metallic Zn. Unfortunately, the stability of the Zn anode in the mild electrolyte is still much limited by the dendrite growth, undesired hydrogen evolution, and the formation of inert ‘‘dead’’ Zn. Here, we report the utilization of MOF ZIF-8 treated with an optimized temperature $(500^{\\circ}\\mathsf{C})$ as a host material for the development of highly stable and dendrite-free Zn metal anodes. The ZIF-8-500 anode exhibits unprecedented reversibility of Zn plating/stripping behavior, high Coulombic efficiency (close to $100\\%$ ), and dendrite-free Zn. The novel Zn@ZIF-8-500 anode coupled with an activated carbon cathode or an $\\mathsf{I}_{2}$ cathode works well. This work represents a new and low-cost avenue for developing a highly reversible zinc metal anode. \n\nplating and stripping efficiency but also increases the local concentration of $\\mathsf{O H}^{-}$ on the anode surface. Third, the formation of $Z n(O H)_{\\times}$ on the anode surface generally converts dendritic Zn to electrochemically inert ‘‘dead’’ Zn, which limits the efficient utilization of Zn. Recently, the strategy of electrolyte optimization was employed to alleviate the issue of the $Z n$ anode.34,35,38–40 For example, very recently, Wang’s group reported the best Zn plating and stripping efficiency (close to $100\\%$ ) in the ‘‘water in salt’’ solution (i.e., $1\\mathrm{~m~}Z\\mathrm{n}(\\mathrm{TFSI})_{2}+20\\mathrm{~m~}$ LiTFSI).38 However, such a high concentration of salts potentially discounts the low-cost nature of aqueous Zn batteries. Therefore, it is highly desired to develop a low-cost strategy to improve the reversibility and utilization efficiency of $Z n$ anodes. \n\nHerein, a simple and low-cost approach is proposed to accomplish the target mentioned above, which is different from previous reports. In our strategy, the conventional metal-organic framework (MOF) ZIF-8 with a sodalite topology, in which $Z n N_{4}$ tetrahedral units are bridged through imidazolate linkers to form a threedimensional structure with large cages interconnected via small six-memberedring apertures (Figure S1), was annealed at an optimized temperature $(500^{\\circ}\\mathsf{C})$ to form the host for Zn plating and stripping. After the heat treatment under inert atmosphere, the $Z n^{2+}$ in the framework of ZIF-8 was converted into trace amount of $Z n^{0}$ with a uniform distribution in the framework through the thermal reduction, and the inherent porous structure was well maintained without change. It was demonstrated that such host material can be used for highly stable, highly reversible, and dendrite-free Zn plating and stripping in the conventional aqueous electrolyte containing $Z n^{2+}$ , which is attributable to the trace amount of $Z n^{0}$ in the framework to provide uniform nuclei for $Z n$ plating and the high over-potential for hydrogen evolution to reduce the undesired $H_{2}O$ decomposition. The host material pre-plated with a very limited Zn $10.0\\mathsf{m A h c m}^{-2})$ was coupled with an AC cathode or an $\\mathsf{I}_{2}$ cathode to form an AC//Zn hybrid supercapacitor or an $\\ensuremath{\\vert_{2}//Z n}$ battery, showing a super long life of 20,000 cycles or 1,600 cycles. \n\n# RESULTS AND DISCUSSION \n\n# Materials Synthesis and Characterization \n\nThe ZIF-8 nanoparticles were synthesized at room temperature using a modified method.41 The typical rhombic dodecahedral morphology with an average crystal size of $200~\\mathsf{n m}$ and phase purity of the as-prepared ZIF-8 nanoparticles were confirmed by scanning electron microscope (SEM) (Figure S2) and X-ray powder diffraction (XRD) characterization (Figure S3), respectively. Then, the as-prepared ZIF-8 was calcined at various temperatures $400^{\\circ}\\mathsf C$ , $500^{\\circ}\\mathsf C$ , $600^{\\circ}\\mathsf C$ , and $800^{\\circ}\\mathsf{C})$ . For convenience, the resulting samples are nominated as ZIF-8-400, ZIF-8-500, ZIF-8- 600, and ZIF-8-800, respectively. The transmission electron microscope (TEM) images in Figure 1A show that all four samples obtained at different temperatures still maintain the morphology of the pristine ZIF-8. The XRD patterns of ZIF-8-400 and ZIF-8-500 match well with that of as-synthesized ZIF-8 (Figure S3), suggesting that the low-temperature heat treatment only leads to partial decomposition of ZIF-8. However, for ZIF-8-600 and ZIF-8-800, the reflection peaks ascribed to ZIF-8 have disappeared and an apparent peak at $2\\uptheta=24^{\\circ}$ corresponding to the (002) lattice plane of carbon is observed (Figure S3), implying that the ZIF-8 nanocrystals have completely decomposed and new nitrogen-doped porous carbon materials have been generated after the calcination at $\\geq600^{\\circ}\\mathsf C$ . The obtained results are further confirmed by Raman characterization (Figure S4), where the coexistence of D band (at around $1,328\\ c m^{-1}$ ) and G band (at around $1,580{\\mathsf{c m}}^{-1}$ ) can be detected in the Raman spectra of ZIF-8-600 and ZIF-8-800, corresponding to the disorder and ideal graphitic sp2 hybrid carbons. The nitrogen sorption investigations (Figure S5) indicate that both the pristine ZIF-8 and the ZIF-8 samples with heat treatment exhibit a type 1 isotherm behavior with a drastic gas uptake at very low relative pressures, showing the typical microporous characteristic. The Brunauer-Emmett-Teller (BET) surface area and total pore volume of pristine ZIF-8 are $1,879\\ m^{2}\\ {\\mathfrak{g}}^{-1}$ and $0.708~\\mathsf{c m}^{3}~\\mathsf{g}^{-1}$ , respectively, which is consistent with previous reports.41 The corresponding data for the samples with heat treatment are determined to be $1,922\\ m^{2}\\ {\\mathfrak{g}}^{-1}$ and $0.731~\\mathsf{c m}^{3}~\\mathsf{g}^{-1}$ (ZIF-8-400), $1.635\\ m^{2}\\ 9^{-1}$ and $0.768~\\mathsf{c m}^{3}~\\mathsf{g}^{-1}$ (ZIF-8-500), $750\\ m^{2}\\ {\\mathfrak{g}}^{-1}$ and $0.443~\\mathsf{c m}^{3}~\\mathsf{g}^{-1}$ (ZIF-8-600), and $666\\ m^{2}\\ \\mathfrak{g}^{-1}$ and $0.258~{\\mathsf{c m}}^{3}~{\\mathsf{g}}^{-1}$ (ZIF-8-800). The pore distribution of all of the samples centers at about $1\\:\\mathsf{n m}$ (Figure S6). The energy dispersive $\\mathsf{X}$ -ray spectroscopy (EDX) mapping (Figure 1B) suggests uniform distributions of the elements carbon, zinc, nitrogen, and oxygen in these samples. The high-resolution X-ray photoelectron spectroscopy (XPS) spectra of the Zn $2{\\mathsf{p}}_{3/2}$ region for these samples with heat treatment are given in Figure 1C. The spectrum of the ZIF-8-400 can be fitted to two components located at $1,022.2\\mathsf{e V}$ for $z_{n\\mathrm{O}}$ and 1, $023.2\\mathsf{e V}$ for $Z n(O H)_{2}$ . For the other three samples, the Zn $2{\\mathsf{p}}_{3/2}$ peak can be deconvoluted into three peaks: $Z n^{0}$ at 1,021.4–1,021.6 eV, ZnO at \n\n![](images/172e7e4b82260ef274e8cbbac00ec1886cefa753f4b4508164389e41cc10523f.jpg) \nFigure 1. Characterization of Samples (A) TEM images of the samples prepared at $400^{\\circ}\\mathsf C,$ , $500^{\\circ}\\mathsf{C}$ , $600^{\\circ}\\mathsf C,$ and $800^{\\circ}\\mathsf{C}$ . Scale bars, $100~\\mathsf{n m}$ . (B) Elemental mappings of the samples prepared at $400^{\\circ}\\mathsf C$ , $500^{\\circ}\\mathsf{C}$ , $600^{\\circ}\\mathsf C,$ and $800^{\\circ}\\mathsf{C}$ . Scale bars, $100~\\mathsf{n m}$ . (C) $Z n2\\mathsf{p}_{3/2}$ XPS spectra of the samples prepared at $400^{\\circ}\\mathsf C$ , $500^{\\circ}\\mathsf C,$ , $600^{\\circ}\\mathsf C,$ and $800^{\\circ}\\mathsf{C}$ . \n\n![](images/3e4e1f9703054e4c1a71f385be1d8499d8faac2431c4b398a059312b0458bd69.jpg) \nFigure 2. Electrochemical Performance of Zn Metal Anodes (A) The polarization of the plating and stripping for the different electrodes at $2.0\\mathsf{m A}\\mathsf{c m}^{-2}$ with a capacity of $1.0\\mathsf{m A h c m}^{-2}$ . (B) Coulombic efficiency of different electrodes at a current density of $2.0\\mathsf{m A}\\mathsf{c m}^{-2}$ with a capacity of $1.0\\mathsf{m A h c m}^{-2}$ . \n\n1,022.2–1,022.4 eV, and $Z n(O H)_{2}$ at 1,023.2–1,023.4 eV. The formation of $Z n^{0}$ arises from the thermal reduction. However, with increasing calcination temperature from $500^{\\circ}\\mathsf{C}$ to $800^{\\circ}\\mathsf{C},$ the intensity of the $Z n^{0}$ peak decreases, which is attributable to the evaporation of Zn0. \n\n# Zn Plating and Stripping Behavior \n\nThe plating and stripping performances of these samples (i.e., ZIF-8-400, 500, 600, and 800) in $2.0\\mathsf{M}\\mathsf{Z n S O}_{4}$ electrolyte were investigated by the typical coin-type cells (i.e., $Z n//Z1F-8–\\mathsf{X},\\mathsf{X}=400$ , 500, 600, and 800) with a fixed plating capacity of $1.0\\mathsf{m A h}$ $\\mathsf{c m}^{-2}$ at an applied current density of $2.0\\mathsf{m A c m}^{-2}$ . In this experiment, these samples were mixed with the conductivity additive (Ketjen black, KB) and binder (polytetrafluoroethylene, PTFE) to form the corresponding film electrodes (see Experimental Procedures). The galvanostatic plating and stripping curves (voltage versus capacity) at the selected cycles $(1^{\\mathsf{s t}},50^{\\mathsf{t h}},$ and $200^{\\mathrm{th}})$ ) and the Coulombic efficiency over 200 cycles of these electrodes are given in Figures 2A and 2B, respectively. As shown in Figure 2A, the plating and stripping reversibility of the ZIF-8-500 electrode is much higher than other electrodes. Furthermore, the ZIF-8-500 electrode shows a highly stable Coulombic efficiency of $98.6\\%$ over 200 cycles (Figure 2B), which is much superior to other electrodes. The lower reversibility of ZIF-8-400 compared to ZIF-8-500 should arise from the lack of $Z n^{0}$ distribution in the framework, which is confirmed by XPS analysis. For ZIF-8-600 and ZIF-8-800, the formation of N-doped carbon (confirmed by XRD and Raman characterization in Figures S3 and S4) might increase the undesired $H_{2}O$ decomposition because N-doped carbon generally exhibits catalytic activity of hydrogen evolution.42,43 To confirm this point, hydrogen evolution behavior of these electrodes was determined in 1.0 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ by line sweep voltammetry tests with a three-electrode system (Figure S7). As shown in Figure S7, the onset potentials for hydrogen evolution on ZIF-8-600 and ZIF-8-800 electrodes are obviously higher than on ZIF-8-500 or ZIF-8-400 electrodes, which confirms the above assumption. In view of the initial Zn deposition potential $(-0.99~\\mathsf{V}$ versus $\\mathsf{A g-A g C l}$ with saturated KCl; Figure S8), ZIF-8-600 and ZIF-8-800 \n\n![](images/d587f512070b739595b1f1fb837cfc7ae767725ab746e87765f853dec99116d9.jpg) \nFigure 3. Electrochemical Data of Half Cells \n\n(A) Coulombic efficiency of Zn deposition on ZIF-8-500 electrode at different current densities with a capacity of $1.0\\mathsf{m A h c m}^{-2}$ . \n(B) Coulombic efficiency of Zn deposition on ZIF-8-500 electrode at different capacities with a current density of $20.0\\mathsf{m A}\\mathsf{c m}^{-2}$ . \n(C) SEM images of Zn deposits at a current density of $1.0\\mathsf{m A}\\mathsf{c m}^{-2}$ for different capacities. Scale bars, $2~{\\upmu\\mathrm{m}}$ . \n(D) Schematic illustration of the $Z n$ plating. \n\nelectrodes might result in undesired hydrogen evolution reaction (HER) during the Zn plating and stripping cycle. These results suggest that ZIF-8-500 is an optimized sample for $Z n$ plating and stripping. \n\nThe Zn plating and stripping behavior of the ZIF-8-500 electrode was further tested with a fixed plating capacity of $1.0\\mathsf{m A h c m}^{-2}$ at different current densities from 1.0 to $30.0\\mathsf{m A c m}^{-2}$ (Figure 3A). As shown in Figure 3A, the ZIF-8-500 electrode exhibits very stable Coulombic efficiencies at various applied current densities over 200 plating and stripping cycles. At a high current density of $30.0~\\mathsf{m A}~\\mathsf{c m}^{-2}$ , the Coulombic efficiency gradually increases and reaches around $99.8\\%$ (98–200 cycles) (Figure 3A). The corresponding galvanostatic plating and stripping curves (voltage versus capacity) of Figure 3A are shown in Figure S9. Furthermore, different plating areal capacities (1.0, 2.0, 3.0, 5.0, and $10.0\\mathsf{m A h c m}^{-2}$ ) on the ZIF-8-500 electrode at a high current density of $20.0\\mathsf{m A c m}^{-2}$ were also determined (Figure 3B). Examination of Figure 3B shows that the Coulombic efficiencies maintain at about $98.4\\%$ , $99.3\\%$ , $99.5\\%$ , $98.8\\%$ , and $97.6\\%$ over the 200 cycles at the capacity of 1.0, 2.0, 3.0, 5.0, and $10.0\\ m A h\\ c m^{-2}$ , respectively. Furthermore, the polarization voltage keeps stable at various capacities (Figure S10). The effect of areal capacity on the morphologies of the zinc deposits is tested up to $10.0\\mathsf{m A h c m}^{-2}$ . A smooth surface with uniform morphology is consistently obtained even at high areal capacity (Figure 3C), indicating that the ZIF-8-500 electrode is promising for the development of a high-capacity zinc anode. Such excellent plating and stripping performance arises from the unique structure of the ZIF-8-500 electrode, which is illustrated by Figure 3D. As shown in Figure 3D, the initial Zn plating prefers to occur in and/or on ZIF-8-500 particles in the electrode (i.e., ZIF $-8-500+k B+1$ TFE) because the trace amount of $Z n^{0}$ in the framework of ZIF-8-500 provides nuclei for Zn plating. After the initial plating, the ZIF-8-500 particles filled with $Z n$ can serve as the substrate with uniform Zn-nuclei for further Zn plating, leading the dendrite-free deposition (Figure 3D). The dendrite-free phenomenon induced by uniform nucleation has been widely demonstrated by previous Li plating and stripping.44–46 The SEM images of the electrode at different plating capacities of 0, 0.333, 0.666, and $1.0\\ m A h\\ c m^{-2}$ clearly confirm this process (Figure S11). As shown in Figure S11, the particle size of ZIF-8-500 increases with the increase of plating capacities, whereas the particle size of KB keeps constant. Furthermore, the BET surface area and pore volume of ZIF-8-500 after plating is much lower than that of the pristine one, indicating that the pores of ZIF-8-500 are filled up with Zn (Figure S12). Herein, it should be noted that the significant loss of specific surface (or pore volume) does not arise from the $Z n$ -plating-induced mass increase (see the extended discussion about Figure S12 for details). In addition, the ex situ XRD analysis of the electrode shows that the structure of ZIF-8-500 is well maintained with different Zn plating capacities (Figure S13). \n\n# Electrochemical Profile of AC//Zn@ZIF-8-500 Hybrid Supercapacitor \n\nThe ZIF-8-500 electrode $(1.5~\\mathrm{mg}~\\mathrm{cm}^{-2})$ was deposited with a limited Zn of $10\\ m\\mathsf{A h}$ $\\mathsf{c m}^{-2}$ to form the Zn@ZIF-8-500 anode, which was then coupled with a commercial AC-based cathode (with a mass loading of $6.0\\mathsf{m g}\\mathsf{c m}^{-2}\\mathsf{\\Lambda}$ ) to construct a hybrid supercapacitor using 2.0 M $Z n S O_{4}$ as the electrolyte. BET surface area of the commercial AC is $1,990{\\mathsf{m}}^{2}{\\mathsf{g}}^{-1}$ (Figure S14). A commercial $Z n$ plate $(20\\ m\\mathsf{g\\ c m}^{-2})$ was also used as the anode to fabricate an AC//Zn hybrid supercapacitor for comparison. Figure 4A displays the discharge-charge profiles at different current densities of AC//Zn@ZIF8-500, in a potential range of $0.2\\mathrm{-}1.8\\mathrm{V}.$ , where the current densities and capacities were normalized to the mass of the AC electrode. The discharge capacities are 132, 114, 100, 81, 71, 58, 29, and ${15\\mathsf{m A h}\\mathsf{g}^{-1}}$ at current densities of 0.1, 0.2, 0.4, 1.0, 2.0, 4.0, 10.0, and ${16.0\\mathsf{A}\\mathsf{g}^{-1}}$ , respectively, showing a good rate performance. The discharge capacities of AC//Zn $@$ ZIF-8-500 are higher than those of AC//Zn constructed with bare Zn-plate anode at all current densities (Figure S15). A Ragone plot (power density versus energy density normalized to the total active material mass of cathode and anode) for AC//Zn@ZIF-8-500 in Figure 4B illustrates that the energy density is about 140.8 Wh $\\mathsf{k g}^{-1}$ at a power density of $70.0\\:\\mathsf{W}\\:\\mathsf{k g}^{-1}$ . Moreover, the energy density of AC//Zn $@$ ZIF-8-500 still remains high up to $46.6\\mathsf{W h}\\mathsf{k g}^{-1}$ even at power density of $2,850\\mathsf{W}\\mathsf{k g}^{-1}$ . The long-term cycling behavior was further investigated (Figure 4C). At a current density of $4.0\\mathsf{A}\\mathsf{g}^{-1}$ , the $\\mathsf{A C//Z n@Z l F-8-500}$ supercapacitor exhibits outstanding cyclic stability with $72\\%$ of capacitance retention and $100\\%$ of Coulombic efficiency over 20,000 cycles. However, in the case of Zn//AC, it fails to work after about 600 cycles with $80\\%$ capacity retention. The lower cycle capability of the Zn//AC supercapacitor arises from the formation of dendrite on the Zn-plate anode (Figure S16A). On the contrary, the SEM image of the Zn@ZIF-8-500 anode after 20,000 cycles reveals a dendrite-free and smooth surface morphology (Figure S16B). This result is also confirmed by the symmetric cell $(Z n//Z n$ and Zn@ZIF-8-500//Zn@ZIF-8-500) tests (Figure S17). The achieved high stability of 20,000 cycles is much superior to most of the previous reports about $Z n$ -based hybrid supercapacitors or batteries (Table S1).17–24,31–34 It also should be noted that such a long cycle is never realized with the limited Zn $(10\\ m A h\\ c m^{-2})$ anode. In all of the previous reports about the Zn-based supercapacitors or batteries,17–23,31–33 the excess Zn (i.e., Zn plates or foils) was employed to ensure the stable cycle. \n\n![](images/d03ecdb5ae989d262d106383742517b460964721b3e4f3acb29af9640f4e3035.jpg) \nFigure 4. Electrochemical Performances of the AC//Zn@ZIF-8-500 Hybrid Supercapacitor (A) Galvanostatic charge and discharge potential profiles of AC//Zn@ZIF-8-500 at different current densities. (B) Ragone plot of AC//Zn@ZIF-8-500 (power density and energy density were normalized to the total active material mass of cathode and anode). (C) Capacity retention and Coulombic efficiency at a current density of $4.0\\mathsf{A}\\mathsf{g}^{-1}$ . \n\n# Electrochemical Performance of I2//Zn@ZIF-8-500 Battery \n\nTo further verify the feasibility of $Z n@Z|\\mathsf{F}.8–500$ as an aqueous rechargeable battery anode, an $\\lvert_{2}//Z\\cap\\ @Z\\rvert\\lvert\\mathsf{F}\\cdot\\&\\cdot500$ battery was assembled with a deposited zinc $(10.0\\ m A h\\ c m^{-2},$ ) anode, $0.5\\mathsf{M}\\mathsf{L i}_{2}\\mathsf{S O}_{4}+0.5\\mathsf{M}\\mathsf{Z n}\\mathsf{S O}_{4}$ anolyte, ion-exchange membrane (GN-1135), and 1 M LiI $+0.5$ M $Z n S O_{4}+0.1\\textsf{M l}_{2}$ catholyte. Figure 5A displays the discharge-charge curves at varied current densities of $\\mathsf{I}_{2}//\\mathsf{Z n@Z l F-8-500}$ within $0.6\\mathrm{-}1.6\\mathrm{\\:V},$ , where the current densities and capacities were normalized to the mass of $\\mathsf{I}_{2}$ in the cathode. At a low current density of $0.2\\mathsf{A}\\mathsf{g}^{-1}$ , the $\\lvert_{2}//Z\\cap\\ @Z\\rvert\\lvert\\mathsf{F}\\cdot\\mathsf{8}\\ –\\mathsf{500}$ battery can exhibit a high initial capacity of $183\\mathrm{\\mAh\\}\\mathfrak{g}^{-1}$ . The capacity decreases upon high current densities, as capacities of 156, 135, 121, 110, and 99 mAh $\\mathfrak{g}^{-1}$ are achieved at 0.5, 1.0, 2.0, 4.0, and $6.0\\mathsf{A g}^{-1}$ , respectively. Even when the current density is increased 40 times $(8.0\\mathsf{A g}^{-1}\\bar{.}$ ), $\\lvert_{2}//Z\\cap\\ @Z\\rvert\\mathsf{F}-8{-}500$ still delivers a capacity of $80\\ m A\\ h\\ {\\ }\\ {\\mathfrak{g}}^{-1}$ , corresponding to the initial capacity retention of $44\\%$ , indicating an excellent rate capability. However, the $\\ensuremath{\\vert_{2}//Z n}$ cell with bare Zn-plate anode only gives $159m\\mathsf{A h\\thinspace g}^{-1}$ at $0.2\\mathsf{A}\\mathsf{g}^{-1}$ (Figure S18). Moreover, the rate capability of the $\\lvert_{2}//Z\\cap\\ @Z\\rvert\\lvert\\mathsf{F}\\cdot\\&\\cdot500$ battery is highly improved compared with the bare $Z n$ -plate counterparts, especially at high current densities (Figure S19). The $\\mathsf{I}_{2}//Z\\mathsf{n@Z}|\\mathsf{F}{-}8$ - 500 battery displays a high energy density of 197.9 Wh $\\mathsf{k g}^{-1}$ at 215.6 W $\\mathsf{k g}^{-1}$ (normalized to $\\mathsf{I}_{2}$ in cathode and anode) and still remains 52.7 Wh $\\mathsf{k g}^{-1}$ even at 9,169.7 W $\\mathsf{k g}^{-1}$ (Figure 5B). Figure 5C depicts the cycling performance and Coulombic efficiency of the $\\lvert_{2}//Z\\cap\\ @Z\\rvert\\lvert\\mathsf{F}\\cdot\\&\\cdot500$ cell at a high current density of $2.0\\mathsf{A}\\mathsf{g}^{-1}$ . As shown in Figure 5C, I2//Zn@ZIF-8-500 shows a capacity retention of $97\\%$ with $100\\%$ Coulombic efficiency after 1,600 charge and discharge cycles, suggesting a good cycling stability. In contrast, $\\mathsf{I}_{2}//\\mathsf{Z}\\mathsf{n}$ only delivers a capacity retention of $69\\%$ after 500 cycles. Although there is only limited Zn $\\cdot10.0\\ m\\mathsf{A\\ c m}^{-2})$ in the anode, the achieved cycle life (1,600 cycles) is still much higher than previous reports about $\\mathsf{I}_{2}//\\mathsf{Z}\\mathsf{n}$ batteries using excess Zn plate or foil as the anode (Table S2).26–30 The \n\n![](images/4c22c3876d78352111f2ebc64af3c70903bd4b52eb2b8bb4bf7839a769540691.jpg) \nFigure 5. Electrochemical Performances of the $\\ensuremath{\\vert_{2}//2n@}$ ZIF-8-500 Full Cell (A) Galvanostatic charge and discharge curves of $\\lvert_{2}//Z\\cap\\ @Z\\rvert\\lvert\\mathsf{F}.8.500$ at different current densities. (B) Ragone plot of $\\mathsf{I}_{2}//Z\\mathsf{n}@Z|\\mathsf{F}-8{-}500$ (power density and energy density were normalized to the total active material mass of cathode and anode). (C) Capacity retention and Coulombic efficiency at a current density of $2.0\\mathsf{A}\\mathsf{g}^{-1}$ . \n\n# Joule \n\nSEM image of the Zn@ZIF-8-500 anode after 1,600 cycles presents a dense, smooth, and dendrite-free surface morphology (Figure S20A), implying a small volume expansion of the electrode material during repeated Zn plating and stripping. In comparison, large amounts of dendrites and mossy Zn can be clearly observed on the surface of the bare Zn anode after 500 cycles (Figure S20B). \n\n# Conclusion \n\nIn summary, extensive efforts are being made to improve the performance of Zn-based batteries and supercapacitors with the mild aqueous electrolytes. However, the dendrite growth and limited reversibility of the zinc anode are still the ‘‘Achilles’ heel’’ for their practical application. In this work, we have demonstrated that the microporous Zn-based MOF (i.e., ZIF-8) treated with an optimized temperature $(500^{\\circ}\\mathsf{C})$ is an attractive host matrix for Zn plating and stripping, which shows a high Coulombic efficiency that is close to $100\\%$ and a dendrite-free characteristic. It was found that such excellent performance arises from the trace amount of $Z n^{0}$ in the framework of ZIF-8-500, which provides uniform nuclei for Zn plating. Moreover, the high over-potential for hydrogen evolution on ZIF-8-500 can alleviate the undesired water decomposition. When being applied as an anode, a hybrid supercapacitor with AC cathode shows high energy density, high power density, long cycle life, and dendrite-free behavior after 20,000 cycles. More importantly, the zinc-iodine rechargeable battery using the $Z n@Z|\\mathsf{F}-\\mathsf{8}-500$ as anode exhibits a long life of 1,600 cycles and an excellent rate capability, which is a dramatic improvement compared to the control cell with routine pure Zn metal anode. These results may open up a new and low-cost avenue for developing highly reversible Zn metal anodes for aqueous batteries. \n\n# EXPERIMENTAL PROCEDURES \n\n# Material Preparation \n\nThe synthesis of ZIF-8 was based on a modified previous report. Typically, zinc nitrate hexahydrate $(2.975\\ {\\mathfrak{g}}.$ , Aldrich) and 2-methylimidazole $(3.284~\\mathfrak{g}$ , Aldrich) were separately dissolved in methanol $100~\\mathrm{{mL},}$ Aldrich) and then mixed together under vigorous stirring for $5\\min$ . The solution was aged at room temperature for $12\\mathrm{~h~}$ . After that, white powders were collected by centrifugation, washed several times with methanol, and dried overnight at $80^{\\circ}C$ . The as-synthesized ZIF-8 nanocrystals were subsequently thermally treated at different high temperatures $(400^{\\circ}\\mathsf C,$ , $500^{\\circ}\\mathsf{C}$ , $600^{\\circ}\\mathsf C,$ and $800^{\\circ}\\mathsf{C},$ respectively) with a heating rate of $3^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ under flowing ${\\sf N}_{2}$ for $3h$ to form four kinds of powders. \n\n# Materials Characterization \n\nThe morphologies of the samples were characterized by SEM (JEOL JSM-6390). TEM and energy-dispersive spectrometer (EDS) mapping were taken on a Tecnai G2 F20 S-Twin. XRD measurements were collected on a powder diffractometer (Bruker D8 Advance, Germany) with a Cu $\\mathsf{K}\\mathsf{\\mathfrak{a}}$ radiation source $(\\lambda=0.15406\\ \\mathrm{nm})$ ). Raman spectroscopy was conducted using a Raman spectrometer (Renishaw 1000B) with a $633\\ \\mathsf{n m}$ laser excitation. The nitrogen sorption isotherms were collected at $-196^{\\circ}C$ on a Quantachrome Autosorb system. The samples were degassed overnight at $300^{\\circ}\\mathsf{C}$ before the test. The BET method was utilized to calculate the specific surface areas and the pore volumes, and the quenched solid density functional theory (QSDFT) method was applied to obtain pore size distribution. X-ray photoelectron spectroscopy (XPS) analysis was performed on a PerkinElmer PHI 5000C ESCA instrument with a twin anode Mg Ka $\\langle1253.6\\ \\mathrm{eV}\\rangle$ radiation. \n\n# Electrochemical Measurements \n\nCoin cells of CR2016 type were assembled to deposit zinc on four ZIF-8-X electrodes to evaluate the Coulombic efficiency. The coin cells were composed of ZIF-8-X electrodes (work electrode), glass fiber separators, bare Zn foil electrodes (counter or reference electrode), and the electrolyte (aqueous 2.0 M $Z n S O_{4}$ solution, $200~\\upmu\\up L)$ . The working electrode was prepared by compressing a mixture of the active materials (ZIF-8-X), conductive material (Ketjen black, KB), and binder (PTFE) at a weight ratio of 80:10:10 onto a nickel grid. The areal mass loading for the work electrode is $1.5\\mathsf{m g}\\mathsf{c m}^{-2}$ , while that for the counter electrode is $20\\mathsf{m g c m}^{-2}$ to exclude the effect of zinc anode fading. Galvanostatic deposition testing was conducted by plating metallic $Z n$ on ZIF-8-X with a fixed capacity of $1.0\\ m{\\mathsf{A}}{\\mathsf{h}}\\ c{\\mathsf{m}}^{-2}$ at current densities of $2.0\\mathsf{m A}\\mathsf{c m}^{-2}$ at room temperature. The stripping cutoff voltage was set at $0.5\\mathrm{V}$ (versus $Z n^{2+}/Z n\\rangle$ ) for each cycle. For the ZIF-8-500 electrode, further galvanostatic zinc plating experiments were conducted with a fixed capacity of $1.0\\mathsf{m A h c m}^{-2}$ at various current densities of 1.0, 2.0, 5.0, 10.0, and $30.0\\mathsf{m A}\\mathsf{c m}^{-2}$ . The fixed capacities were also set as 1.0, 2.0, 3.0, 5.0, and $10.0\\mathsf{m A h c m}^{-2}$ to probe the plating process at $20.0\\mathsf{m A c m}^{-2}$ . For symmetric cells, $5\\mathsf{m A h c m}^{-2}$ of Zn was first plated on ZIF8-500 at $1\\mathsf{m A}\\mathsf{c m}^{-2}$ , forming the Zn@ZIF-8-500 anode, two $Z n@Z|\\mathsf{F}.8–500$ anodes were reassembled into a symmetric cell in a $2.0\\mathsf{M}\\mathsf{Z n S O}_{4}$ aqueous electrolyte, and the cell was then charged and discharged with a cycling capacity of $1\\mathsf{m A}\\mathsf{h}\\mathsf{c m}^{-2}$ at $1.0\\mathsf{m A}\\mathsf{c m}^{-2}$ . The $Z n$ symmetric cell was also assembled with two $Z n$ disks and the same electrolyte. \n\nFor the AC//Zn@ZIF-8-500 hybrid supercapacitor, $Z n@Z|\\mathsf{F}.8–500$ anodes were obtained from the half cell, and the deposition amount of zinc was $10.0\\ m A h\\ c m^{-2}$ . The Zn@ZIF-8-500 anode was reassembled into a hybrid supercapacitor against an AC cathode. The AC cathode electrode was prepared by mixing 80 wt $\\%$ AC, 10 wt $\\%$ KB, and 10 wt $\\%$ PTFE in isopropanol, and the slurry mixture was then coated on a titanium mesh. The mass loading of AC in the cathode was $6.0\\ m\\ g\\ c m^{-2}$ . The electrolyte was the same with the half cells (aqueous $2.0~\\mathsf{M}$ $Z n S O_{4}$ solution, $200~\\upmu\\up L)$ . The electric conductivity of Zn@ZIF-8-500-based electrodes was measured using an automatic four-point probe meter Model 280 technique (see Table S3). \n\nFor $\\lvert_{2}//Z\\cap\\ @Z\\rvert\\lvert\\mathsf{F}\\cdot\\&\\cdot500$ full cell, a deposited Zn $(10.0\\ m A h\\ c m^{-2})$ was used as the anode. The current collector constructed with the KB-loaded titanium mesh was employed as the liquid cathode. The cathode electrode was prepared by mixing 80 wt $\\%$ KB and 20 wt $\\%$ PTFE using isopropanol. The mixtures were rolled into a film and pressed onto titanium mesh with a KB loading of $5.0~\\mathrm{mg}~\\mathrm{cm}^{-2}$ . An aqueous electrolyte containing 1 M LiI, $0.1~\\mathsf{M}~\\mathsf{I}_{2}$ and $0.5\\mathrm{~M~}\\ Z n{\\mathsf{S O}}_{4}$ was used as the liquid cathode. For full cell assembly, $0.1~\\mathsf{m L}$ of the aqueous cathode and the 0.5 M $\\mathsf{L i}_{2}\\mathsf{S O}_{4},$ 0.5 M $Z n S O_{4}$ solution-wetted anode was separated with Nepem GN-1135. Prior to cell assembly, the commercial Nepem GN-1135 film was alternately immersed in 1 M $\\mathsf{L i}_{2}\\mathsf{S O}_{4}$ solution and washed with deionized water until the pH value reached around 7. Linear sweep voltammetry (LSV) was carried out on a CH Instruments electrochemical workstation (CHI 660D). LSV measurements were conducted in 1.0 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ at a sweep rate of $5\\mathrm{\\mV\\}\\mathsf{s}^{-1}$ , where an AC film electrode $(1\\times2c m^{2})$ ) and an Ag-AgCl electrode (with saturated KCl) were used as the counter electrode and reference electrode, respectively. LSV of a $Z n$ plate $(1\\times1\\ c m^{2})$ was also measured in 2.0 M $Z n S O_{4}$ aqueous electrolyte under the same testing conditions. Galvanostatic charge-discharge tests were performed on a Hukuto Denko battery charge-discharge system (HJ series). \n\n# Joule \n\nThe power density $\\mathsf{P}(\\mathsf{W}\\mathsf{k g}^{-1})$ and energy density $\\mathsf{E}(\\mathsf{W h}\\mathsf{k g}^{-1})$ were obtained according to the following equations: \n\n$$\n\\mathsf{P}=\\frac{i\\times V\\times1000}{m},\n$$ \n\n$$\nE=\\frac{C\\times V\\times1000}{m},\n$$ \n\n(Equation 2) \n\nwhere $V$ is the average discharge voltage $(\\mathsf{V})$ , i and m are the discharge current (A) and the total mass (g) of active materials in both the anode and the cathode, respectively, and C is the discharge capacity (Ah). \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information can be found online at https://doi.org/10.1016/j.joule. \n2019.02.012. \n\n# ACKNOWLEDGMENTS \n\nThe authors gratefully acknowledge funding support from the National Natural Science Foundation of China (21622303 and 21333002) and the State Key Basic Research Program of China (2016YFA0203302). \n\n# AUTHOR CONTRIBUTIONS \n\nY.W. conceived the idea and designed the experiments. Y.W. and Y.X. directed the research. Z.W., Y.W., and J.H. conducted the material synthesis, characterization, and electrochemical measurements. Z.G., X.D., and Y.L. assisted with the electrochemical measurements and data analysis. Z.W. and Y.W. co-wrote the manuscript. All authors discussed and analyzed the results. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: October 23, 2018 \nRevised: January 28, 2019 \nAccepted: February 26, 2019 \nPublished: March 27, 2019 \n\n# REFERENCES \n\n1. Dunn, B., Kamath, H., and Tarascon, J.M. (2011). Electrical energy storage for the grid: a battery of choices. Science 334, 928–935. \n2. Suo, L., Borodin, O., Gao, T., Olguin, M., Ho, J., Fan, X., Luo, C., Wang, C., and Xu, K. (2015). ‘‘Water-in-salt’’ electrolyte enables highvoltage aqueous lithium-ion chemistries. Science 350, 938–943. \n3. Chen, W., Li, G., Pei, A., Li, Y., Liao, L., Wang, H., Wan, J., Liang, Z., Chen, G., Zhang, H., et al. (2018). A manganese–hydrogen battery with potential for grid-scale energy storage. Nat. Energy 3, 428–435. \n4. Zhao, Q., Huang, W., Luo, Z., Liu, L., Lu, Y., Li, $\\mathsf{Y}_{\\cdot,\\prime}$ Li, L., Hu, J., Ma, H., and Chen, J. (2018). High-capacity aqueous zinc batteries using sustainable quinone electrodes. Sci. Adv. 4, eaao1761. \n5. Lin, K., Go´ mez-Bombarelli, R., Beh, E.S. Tong, L., Chen, Q., Valle, A., Aspuru-Guzik, A., Aziz, M.J., and Gordon, R.G. (2016). A redox-flow battery with an alloxazinebased organic electrolyte. Nat. Energy 1, 16102. \n6. Xu, Y., Zhang, C., Zhou, M., Fu, Q., Zhao, C., Wu, M., and Lei, Y. (2018). Highly nitrogen doped carbon nanofibers with superior rate capability and cyclability for potassium ion batteries. Nat. Commun. 9, 1720. \n7. Guo, S., Li, Q., Liu, P., Chen, M., and Zhou, H. (2017). Environmentally stable interface of layered oxide cathodes for sodium-ion batteries. Nat. Commun. 8, 135. \n8. Orita, A., Verde, M.G., Sakai, M., and Meng, Y.S. (2016). A biomimetic redox flow battery based on flavin mononucleotide. Nat. Commun. 7, 13230. \n9. Wang, Y., Liu, J., Lee, B., Qiao, R., Yang, Z., Xu, S., Yu, X., Gu, L., Hu, Y.S., Yang, W., et al. (2015). Ti-substituted tunnel-type Na0.44MnO2 oxide as a negative electrode for aqueous sodiumion batteries. Nat. Commun. 6, 6401. \n10. Ouchi, T., Kim, H., Spatocco, B.L., and Sadoway, D.R. (2016). Calcium-based multi-element chemistry for grid-scale electrochemical energy storage. Nat. Commun. 7, 10999. \n11. Wan, F., Zhang, L., Dai, X., Wang, X., Niu, Z., and Chen, J. (2018). Aqueous rechargeable zinc/sodium vanadate batteries with enhanced performance from simultaneous insertion of dual carriers. Nat. Commun. 9, 1656. \n12. Parker, J.F., Chervin, C.N., Pala, I.R., Machler, M., Burz, M.F., Long, J.W., and Rolison, D.R. (2017). Rechargeable nickel-3D zinc batteries: an energy-dense, safer alternative to lithiumion. Science 356, 415–418. \n13. Guo, Z., Ma, Y., Dong, X., Huang, J., Wang, Y., and Xia, Y. (2018). An environmentally friendly and flexible aqueous zinc battery using an organic cathode. Angew. Chem. Int. Ed. 57, 11737–11741. \n14. $\\mathsf{X}\\mathsf{u},$ C., Li, B., Du, H., and Kang, F. (2012). Energetic zinc ion chemistry: the rechargeable zinc ion battery. Angew. Chem. Int. Ed. Engl. 51, 933–935. \n15. Alfaruqi, M.H., Gim, J., Kim, S., Song, J., Jo, J., Kim, S., Mathew, V., and Kim, J. (2015). Enhanced reversible divalent zinc storage in a structurally stable $\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}\\mathsf{\\alpha}$ nanorod electrode. J. Power Sources 288, 320–327. \n16. Sun, W., Wang, F., Hou, S., Yang, C., Fan, X., Ma, Z., Gao, T., Han, F., Hu, R., Zhu, M., et al. (2017). $Z{\\mathsf{n/M n O}}_{2}$ Battery chemistry with $\\mathsf{H}^{+}$ and $Z n^{2+}$ coinsertion. J. Am. Chem. Soc. 139, 9775–9778. \n17. Han, S.-D., Kim, S., Li, D., Petkov, V., Yoo, H.D. Phillips, P.J., Wang, H., Kim, J.J., More, K.L., Key, B., et al. (2017). Mechanism of Zn insertion into nanostructured d-MnO2: a nonaqueous rechargeable Zn metal battery. Chem. Mater. 29, 4874–4884. \n18. Zhang, N., Cheng, F., Liu, J., Wang, L., Long, X., Liu, X., Li, F., and Chen, J. (2017). Rechargeable aqueous zinc-manganese dioxide batteries with high energy and power densities. Nat. Commun. 8, 405. \n19. Pan, H., Shao, Y., Yan, P., Cheng, Y., Han, K.S., Nie, Z., Wang, C., Yang, J., Li, X., Bhattacharya, P., et al. (2016). Reversible aqueous zinc/ manganese oxide energy storage from conversion reactions. Nat. Energy 1, 16039. \n20. Kundu, D., Adams, B.D., Duffort, $\\mathsf{V}_{\\cdot,\\prime}$ Vajargah, S.H., and Nazar, L.F. (2016). A high-capacity and long-life aqueous rechargeable zinc battery using a metal oxide intercalation cathode. Nat. Energy 1, 16119. \n21. He, P., Quan, Y., Xu, X., Yan, M., Yang, W., An, $\\scriptstyle\\bigcirc_{\\cdot,}$ He, L., and Mai, L. (2017). High-performance aqueous zinc-ion battery based on layered $H_{2}V_{3}O_{8}$ nanowire cathode. Small 13, 1702551. \n22. Yan, M., He, P., Chen, $\\Upsilon_{\\cdot,\\cdot}$ Wang, S., Wei, Q. Zhao, K., $\\mathsf{X}\\mathsf{u},\\mathsf{X}.,$ An, Q., Shuang, Y., Shao, Y., et al. (2018). Water-lubricated intercalation in ${\\mathsf{V}}_{2}{\\mathsf{O}}_{5}{\\cdot}{\\mathsf{n H}}_{2}{\\mathsf{O}}$ for high-capacity and high-rate aqueous rechargeable zinc batteries. Adv. Mater. 30, 1703725. \n23. Tr ´ocoli, R., and La Mantia, F. (2015). An aqueous zinc-ion battery based on copper hexacyanoferrate. ChemSusChem 8, 481–485. \n24. Zhang, L., Chen, L., Zhou, X., and Liu, Z. (2015). Towards high-voltage aqueous metal-ion batteries beyond 1.5 V: the zinc/zinc \n\nhexacyanoferrate system. Adv. Energy Mater. \n\n5, 1400930. \n25. Canepa, P., Sai Gautam, G., Hannah, D.C., Malik, R., Liu, M., Gallagher, K.G., Persson, K.A., and Ceder, G. (2017). Odyssey of multivalent cathode materials: open questions and future challenges. Chem. Rev. 117, 4287–4341. \n26. Li, B., Nie, Z., Vijayakumar, M., Li, G., Liu, J., Sprenkle, V., and Wang, W. (2015). Ambipolar zinc-polyiodide electrolyte for a high-energy density aqueous redox flow battery. Nat. Commun. 6, 6303. \n27. Weng, G.-M., Li, Z., Cong, G., Zhou, Y., and Lu, Y.-C. (2017). Unlocking the capacity of iodide for high-energy-density zinc/polyiodide and lithium/polyiodide redox flow batteries. Energy Environ. Sci. 10, 735–741. \n28. Lee, J., Srimuk, P., Fleischmann, S., Ridder, A., Zeiger, M., and Presser, V. (2017). Nanoconfinement of redox reactions enables rapid zinc iodide energy storage with high efficiency. J. Mater. Chem. A 5, 12520–12527. \n29. Bai, C., Cai, F., Wang, L., Guo, S., Liu, X., and Yuan, Z. (2018). A sustainable aqueous Zn-I2 battery. Nano Res. 11, 3548–3554. \n30. Xie, C., Zhang, H., Xu, W., Wang, W., and Li, X. (2018). A long cycle life, self-healing zinc-iodine flow battery with high power density. Angew. Chem. Int. Ed. 57, 11171–11176. \n31. Dong, L., Ma, X., Li, Y., Zhao, L., Liu, W., Cheng, J., Xu, C., Li, B., Yang, Q.-H., and Kang, F. (2018). Extremely safe, high-rate and ultralonglife zinc-ion hybrid supercapacitors. Energy Storage Mater. 13, 96–102. \n32. Wang, H., Wang, M., and Tang, Y. (2018). A novel zinc-ion hybrid supercapacitor for longlife and low-cost energy storage applications. Energy Storage Mater. 13, 1–7. \n33. Han, J., Wang, $\\mathsf{K}_{\\cdot,\\prime}$ Liu, W., Li, C., Sun, X., Zhang, X., An, Y., Yi, S., and Ma, Y. (2018). Rational design of nano-architecture composite hydrogel electrode towards high performance Zn-ion hybrid cell. Nanoscale 10, 13083–13091. \n34. Liu, Z., Li, G., Cui, T., Borodin, A., Kuhl, C., and Endres, F. (2018). A battery-supercapacitor hybrid device composed of metallic zinc, a biodegradable ionic liquid electrolyte and graphite. J. Solid State Electrochem. 22, 91–101. \n35. Sun, K.E.K., Hoang, T.K.A., Doan, T.N.L., Yu, Y., and Chen, P. (2018). Highly sustainable zinc anodes for a rechargeable hybrid aqueous battery. Chemistry 24, 1667–1673. \n36. Liu, Z., Cui, T., Pulletikurthi, G., Lahiri, A., Carstens, $\\intercal_{\\cdot,\\prime}$ Olschewski, M., and Endres, F. (2016). Dendrite-free nanocrystalline zinc electrodeposition from an ionic liquid containing nickel triflate for rechargeable Zn-based batteries. Angew. Chem. Int. Ed. Engl. 55, 2889–2893. \n37. Song, M., Tan, H., Chao, D., and Fan, H.J. (2018). Recent advances in Zn-ion batteries. Adv. Funct. Mater. 28, 1802564. \n38. Wang, F., Borodin, O., Gao, T., Fan, X., Sun, W., Han, F., Faraone, A., Dura, J.A., Xu, $\\mathsf{K}_{\\cdot,\\prime}$ and Wang, C. (2018). Highly reversible zinc metal anode for aqueous batteries. Nat. Mater. 17, 543–549. \n39. Zhang, J., Zhao, J.W., Du, H.P., Zhang, Z.Y., Wang, S.C., and Cui, G.L. (2018). Amide-based molten electrolyte with hybrid active ions for rechargeable Zn batteries. Electrochim. Acta 280, 108–113. \n40. Zhao, J.W., Sonigara, K.K., Li, J.J., Zhang, J., Chen, B.B., Zhang, J.J., Soni, S.S., Zhou, X.H., Cui, G.L., and Chen, L.Q. (2017). A smart flexible zinc battery with cooling recovery ability. Angew. Chem. 129, 7979–7983. \n41. Saliba, D., Ammar, M., Rammal, M., Al-Ghoul, M., and Hmadeh, M. (2018). Crystal growth of ZIF-8, ZIF-67, and their mixed-metal derivatives. J. Am. Chem. Soc. 140, 1812–1823. \n42. Fei, H., Dong, J., Arellano-Jim ´enez, M.J., Ye, G., Dong Kim, N., Samuel, E.L., Peng, Z., Zhu, Z., Qin, F., Bao, J., et al. (2015). Atomic cobalt on nitrogen-doped graphene for hydrogen generation. Nat. Commun. 6, 8668. \n43. Han, N., Yang, K.R., Lu, Z., Li, Y., Xu, W., Gao, T., Cai, Z., Zhang, Y., Batista, V.S., Liu, W., et al. (2018). Nitrogen-doped tungsten carbide nanoarray as an efficient bifunctional electrocatalyst for water splitting in acid. Nat. Commun. ${\\boldsymbol{\\mathscr{G}}}_{\\prime}$ 924. \n44. Ye, H., Xin, S., Yin, Y.X., Li, J.Y., Guo, Y.G., and Wan, L.J. (2017). Stable Li plating/stripping electrochemistry realized by a hybrid Li reservoir in spherical carbon granules with 3D conducting skeletons. J. Am. Chem. Soc. 139, 5916–5922. \n45. Pei, A., Zheng, G., Shi, F., Li, Y., and Cui, Y. (2017). Nanoscale nucleation and growth of electrodeposited lithium metal. Nano. Lett. 17, 1132–1139. \n46. Zhang, R., Chen, X.R., Chen, X., Cheng, X.B., Zhang, $\\times.0.,$ Yan, C., and Zhang, Q. (2017). Lithiophilic sites in doped graphene guide uniform lithium nucleation for dendrite-free lithium metal anodes. Angew. Chem. Int. Ed. Engl. 56, 7764–7768. " + }, + { + "id": "10.1038_s41467-019-09290-y", + "DOI": "10.1038/s41467-019-09290-y", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-09290-y", + "Relative Dir Path": "mds/10.1038_s41467-019-09290-y", + "Article Title": "Cascade anchoring strategy for general mass production of high-loading single-atomic metal-nitrogen catalysts", + "Authors": "Zhao, L; Zhang, Y; Huang, LB; Liu, XZ; Zhang, QH; He, C; Wu, ZY; Zhang, LJ; Wu, JP; Yang, WL; Gu, L; Hu, JS; Wan, LJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Although single-atomically dispersed metal-N-x on carbon support (M-NC) has great potential in heterogeneous catalysis, the scalable synthesis of such single-atom catalysts (SACs) with high-loading metal-Nx is greatly challenging since the loading and single-atomic dispersion have to be balanced at high temperature for forming metal-Nx. Herein, we develop a general cascade anchoring strategy for the mass production of a series of M-NC SACs with a metal loading up to 12.1 wt%. Systematic investigation reveals that the chelation of metal ions, physical isolation of chelate complex upon high loading, and the binding with N-species at elevated temperature are essential to achieving high-loading M-NC SACs. As a demonstration, high-loading Fe-NC SAC shows superior electrocatalytic performance for O-2 reduction and Ni-NC SAC exhibits high electrocatalytic activity for CO2 reduction. The strategy paves a universal way to produce stable M-NC SAC with high-density metal-N-x sites for diverse high-performance applications.", + "Times Cited, WoS Core": 713, + "Times Cited, All Databases": 736, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000461757800001", + "Markdown": "# Cascade anchoring strategy for general mass production of high-loading single-atomic metal-nitrogen catalysts \n\nLu Zhao1,2, Yun Zhang1,3, Lin-Bo Huang1,2, Xiao-Zhi Liu2,4, Qing-Hua Zhang4, Chao He1,2, Ze-Yuan Wu1,2, Lin-Juan Zhang5, Jinpeng Wu $\\textcircled{1}$ 6, Wanli Yang $\\textcircled{1}$ 6, Lin Gu 4, Jin-Song ${\\mathsf{H u}}^{1,2}$ & Li-Jun Wan1,2 \n\nAlthough single-atomically dispersed metal- $\\cdot\\mathsf{N}_{\\times}$ on carbon support (M-NC) has great potential in heterogeneous catalysis, the scalable synthesis of such single-atom catalysts (SACs) with high-loading metal- $\\mathsf{N}_{\\mathsf{x}}$ is greatly challenging since the loading and single-atomic dispersion have to be balanced at high temperature for forming metal- $\\cdot\\mathsf{N}_{\\times}$ . Herein, we develop a general cascade anchoring strategy for the mass production of a series of M-NC SACs with a metal loading up to $12.1\\mathrm{wt\\%}$ . Systematic investigation reveals that the chelation of metal ions, physical isolation of chelate complex upon high loading, and the binding with N-species at elevated temperature are essential to achieving high-loading M-NC SACs. As a demonstration, high-loading Fe-NC SAC shows superior electrocatalytic performance for $\\mathsf{O}_{2}$ reduction and Ni-NC SAC exhibits high electrocatalytic activity for ${\\mathsf{C O}}_{2}$ reduction. The strategy paves a universal way to produce stable M-NC SAC with high-density metal- $\\cdot\\mathsf{N}_{\\times}$ sites for diverse high-performance applications. \n\nSisetnragorlgei-naeocoaumts yastniasdl shitno(cmSeoAigtCe)cnoehoamsubsineceaesnatlhlyes esmewerhitgisledofbarsibdaogtrehi htnehgtegap between them with unique features. Comparing with heterogeneous catalysts, SAC maximizes the atom utilization and has homogenous active sites with tunable electronic environments for highly catalytic activity or/and selectivity, while simultaneously holds improved stability and excellent recyclability in contrast to homogeneous catalysts $_{\\mathrm{i-10}}$ . In the past a couple of years, dozens of SACs have been therefore developed for thermocatalytic reaction (such as CO oxidation11,12, water–gas shift reaction12,13, and methane conversion14), photocatalytic reaction (photocatalytic $\\mathrm{H}_{2}$ evolution15 and $\\bar{\\mathrm{CO}}_{2}$ reduction16), electrocatalytic reaction $\\mathrm{\\tilde{(H}}_{2}$ evolution17–19, $\\mathrm{O}_{2}$ reduction20–24, $\\mathrm{CO}_{2}$ reduction25, and $\\Nu_{2}$ reduction26), as well as organic electrosynthesis27. Controllable preparation of SAC, however, still remains challenging in view of the strong tendency of migration and aggregation of active atoms during either the fabrication or the subsequent application processes. To this end, supporting monodispersed atoms on appropriate support represents the most feasible and effective way to achieve SAC. Until now, several strategies such as using confinement effect, coordination effect, or chemical bonding have been reported to synthesize isolated metal sites over supports by (1) limiting the loading amount of active component; (2) boosting the interactions between metal atom and support; or (3) employing defect or void on suppor $^{128-32}$ . \n\nAmong SACs, atomic metal– $\\cdot\\mathrm{N_{x}}$ $(\\mathrm{M}{-}\\mathrm{N}_{\\mathrm{x}})$ moieties anchored on carbon support (M–NC) have attracted particular interests especially in electrocatalysis, since nitrogen can not only effectively anchor and stabilize single-metal atom on carbon but also modulate the electronic structures of metal or carbon atom to optimize the adsorption/desorption of intermediates for enhancing catalytic performance $33-3^{2}7$ . Moreover, carbon supports are readily available for commercial use and highly electrically conductive for accelerating electron transfer during reactions. Such single-atomic M–NC SACs have demonstrated extraordinary promise in catalytic oxidation of benzene to phenol38, chemoselective hydrogenation of nitroarenes to produce azo compounds39, semihydrogenation of 1-hexyne40, etc. Huang and \n\nDuan et al.41 recently reported a two-step approach to the synthesis of well-defined atomic $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ $\\mathbf{\\dot{M}}=\\mathbf{Fe}$ , Co, Ni) moieties embedded in graphene with a metal loading of ${\\sim}0.05~\\mathrm{at\\%}$ as efficient electrocatalysts for oxygen evolution reaction. \n\nThe catalytic activity and turnover efficiency of a catalyst and thus the power/energy density of catalyst-based devices closely depend on the number of catalytic sites, besides its intrinsic activity. One of big challenges for SAC is the low concentration of single-atomic sites, since the loading and the aggregation of atoms have to be balanced. Especially at elevated temperature, metal atoms are getting easier to migrate and aggregate, causing more challenging to achieve M–NC SACs with high metal loading since the formation of $\\mathrm{{_{M-N}}}$ bonding usually needs high temperature (such as over $700^{\\circ}\\mathrm{C})^{42-45}$ . Although the progress has been made on the synthesis of M–NC SACs, few reports can achieve the metal loading over $4\\mathrm{wt\\%}$ . Another challenge is the mass production of M–NC SACs, which is essential to their practical applications. Most strategies for the synthesis of SAC need delicate control of the defects in supports and synthetic procedures to stabilize single atoms, whereas the mass production requires the commercially available low cost supports and scalable, manageable processing. It is therefore highly desirable to develop a method compatible with large-scale production for synthesizing M–NC SACs with high metal loadings. \n\nHerein, we report a general approach to synthesize a wide range of M–NC SACs ( $\\mathbf{\\dot{M}}=\\mathbf{M}\\mathbf{n}$ , Fe, Co, Ni, Cu, Mo, Pt, etc.) with metal loadings up to $12.1\\mathrm{wt\\%}$ via a cascade anchoring strategy. As shown in Fig. 1, the metal ions are first chelated by chelating agent such as glucose here, then anchored onto oxygen-speciesrich porous carbon support with high surface area (Step 1). The chelating agent can effectively sequester metal ions (primary protection) and bind to O-rich carbon support via the interaction with O-containing groups. The excessive chelating agent bound to support surface will physically isolate the metal complex (secondary protection). The complex bound carbon is then mixed with melamine as a nitrogen source for subsequent pyrolysis to achieve M–NC SACs. During pyrolysis, the chelated metal complex can further secure metal atoms via the decomposed residues up to certain temperature ( $.{\\sim}500^{\\circ}\\mathrm{C}$ Step 2) (tertiary protection), while carbon nitrogen species $\\left(\\mathrm{CN}_{\\mathrm{x}}\\right)$ (such as $\\bar{\\mathrm{{C}}}_{3}\\mathrm{{N}}_{4}$ etc.) decomposed from melamine at higher temperature $\\left(>\\sim600^{\\circ}\\mathrm{C}\\right)$ can subsequently bind with metal atoms to form $\\mathrm{{M-N_{x}}}$ moieties (Step 3), taking over the protection and preventing metal atoms from aggregation (quaternary protection). Systematical experiments reveal that such sequential protecting strategy allows for producing wide-ranging M–NC SACs with a high metal loading up to $12.1\\mathrm{wt\\%}$ , since the chelating interaction can take place between a wide range of metal ions and ligands46,47. Moreover, the carbon support can be low-cost commercial porous carbon; the chelating agents can be low-cost carbohydrates, such as glucose etc.; and the processing is very easy to scale up. In this regard, the present strategy is suitable for the low-cost mass production of M–NC SACs for diverse applications. As a demonstration, Fe–NC SAC shows a superior electrocatalytic activity for oxygen reduction reaction (ORR) in 0.1 M KOH with a half-wave potential of $0.90{\\mathrm{V}}$ (all potentials are versus to RHE) and a kinetic mass current of $100.{\\bar{7}}\\mathrm{Ag^{-1}}$ at $0.9\\mathrm{V}$ , $50\\mathrm{mV}$ and $65\\mathrm{Ag^{-1}}$ higher than that of state-of-the-art commercial $\\mathrm{Pt/C}$ catalyst, respectively. Ni–NC SAC exhibits an excellent electrocatalytic activity for $\\mathrm{CO}_{2}$ reduction to CO in terms of a good Faraday efficiency of $89\\%$ with a high current density of $30\\mathrm{mA}\\mathrm{cm}^{-2}$ at $-0.85\\dot{\\mathrm{V}}$ . \n\n![](images/9e1745fc75070b67f174dac375b311d618431333dfe12863176e27dd6c49d2cc.jpg) \nFig. 1 The cascade anchoring strategy for the synthesis of M–NC SACs. First, chelating agent (glucose) efficiently sequesters metal ions and binds to O-rich carbon support, while excessive glucoses physically isolate glucose–metal complexes on carbon substrate. Second, the chelated metal complexes further secure metal atoms via the decomposed residues up to certain temperature. Third, $\\mathsf{C N}_{\\times}$ species decomposed from melamine at higher temperature subsequently capture metal atoms to form M– $\\cdot\\mathsf{N}_{\\times}$ moieties and integrate into the pyrolyzed carbon layer \n\n# Results \n\nSynthesis and structural analysis of Fe–NC SAC. Since Fe–NC electrocatalysts are particularly interested for ORR to replace precious $\\mathrm{Pt}$ -based commercial catalysts in fuel cells etc. We first take Fe–NC SAC as an example to demonstrate our strategy and its application. Fe–NC SAC was prepared in two steps. First, porous carbon (PC) support was ultrasonically dispersed in the solution containing Fe source and glucose (chelating agent). Second, the dried powder was ground with melamine (nitrogen source), followed by pyrolysis at $800^{\\circ}\\mathrm{C}$ to achieve Fe–NC SAC. The scanning electron microscope (SEM) image (Fig. 2a) shows that PC substrate (prepared by pyrolysis of potassium citrate as presented in the section of Methods) has a three-dimensional honeycomb-like morphology with plenty of macropores in several micrometers, which benefits mass transfer during both synthesis and application processes. X-ray diffraction (XRD) pattern (cyan curve in Fig. 2b) shows two typical broad peaks at 24.3 and $44.3^{\\circ}$ for the PC substrate. The specific surface area and pore volume are measured to be $1713\\mathrm{m}^{2}\\mathrm{g}^{-1}$ and $0.75\\mathrm{cm}^{3}\\mathrm{g}^{-1}$ respectively (Supplementary Fig. 1). The pore size distribution analysis indicates most of nanopores centered at 1.3 and $2.0\\mathrm{nm}$ . X-ray photoelectron spectroscopy (XPS) spectrum reveals plenty of O-species $(10.05\\ \\mathrm{at\\%})$ on the surface of the PC substrate (Supplementary Fig. 2). X-ray energy dispersive spectroscopic (EDS)-mapping images show that the elemental $\\bar{\\mathrm{~O~}}$ uniformly distributes on whole-carbon sheets (Supplementary Fig. 3). These features make such carbon substrate perfect for anchoring glucose-chelated Fe complex. The chelation of $\\mathtt{a}$ -D-glucose and $\\bar{\\mathrm{Fe(III)}}$ ions to form $\\mathtt{a}$ -D-glucose–Fe(III) complex has been reported in the literatures47,48 and supported by our density functional theory (DFT) calculations (Supplementary Fig. 4). After mixing this PC substrate with glucose and Fe source, Fourier-transform infrared (FTIR) spectrum and EDS-mapping images indicate that glucose and glucose-chelated Fe complex cover on whole substrate in view of uniform FTIR signals of $^{\\mathrm{{-}}\\mathrm{{H}}}$ and distribution of elemental Fe and O (Supplementary Figs. 5 and 6). After pyrolysis at $800^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ , no additional XRD peaks are detected except for those from carbon (Fig. 2b), implying no formation of crystallized Fe. Transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) images (Fig. 2c, d) show that carbon sheet support is covered by flocculent sheet-like structures, which is a typical feature of pyrolyzed carbonaceous materials (glucose). Raman spectra (Supplementary Fig. 7) indicate that the $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratio for Fe–NC SAC is slightly higher than carbon substrate (1.3 vs. 1.2, PC substrate here went through the same pyrolysis for Raman recording), agreeing with the formation of the flocculent carbon layer in more disorder as observed in TEM image. No Fe-based particles, which are typically seen in pyrolyzed Fe–NC products, are found during TEM observation. \n\n![](images/365663ef5a8fcbf87b273f462285c87e1dd0c9d2c624b631da0a9dfd0bc7eac7.jpg) \nFig. 2 Structural characterizations of PC support and Fe–NC SAC. a SEM image of PC support. b XRD patterns of PC and Fe–NC SAC. c TEM, d, HRTEM, e, HAADF–STEM images of Fe–NC SAC. f HAADF–STEM image and EELS mapping images of Fe, N, and overlaid Fe and N on Fe–NC SAC. Scale bars, $1\\upmu\\mathrm{m}$ (a); $200\\mathsf{n m}$ (c); $20\\mathsf{n m}$ (d); 3 nm (e); $2{\\mathsf{n m}}$ (f) \n\nXRD and TEM results suggest that Fe may exist in a form of single atom. For clearly revealing the state of Fe, the high-angle annular dark-filed scanning TEM (HAADF–STEM) was used to acquire the evidence of Fe distribution at atomic resolution. As displayed in Fig. 2e and Supplementary Fig. 8, a number of bright spots in a single-atom size are clearly observed, which can be safely attributed to Fe atoms in this sample. The average size of spots is $1.04\\pm0.35\\mathring\\mathrm{A}$ on a basis of statistical analysis on over 400 bright spots (inset in Supplementary Fig. 8a), corroborating these Fe atoms are mainly in single-atomic state. EDS spectrum evidences the existence of elemental C, Fe, and N (Supplementary Fig. 9a). Electron energy loss spectroscopy (EELS) and EDSmapping images depict the homogenous and uniform distribution of Fe and $\\mathrm{\\DeltaN}$ in the Fe–NC SAC (Fig. 2f and Supplementary Figs. 9b–f and 10). \n\nAtomic structure analysis of Fe–NC SAC by XAFS and XPS. Element-selective X-ray absorption fine structure (XAFS) spectroscopy experiments were further conducted, including the extended X-ray absorption fine structure (EXAFS), which are powerful for determining the coordination environment and chemical state of absorbing centers with high sensitivity. As shown in Fig. 3a, X-ray absorption near-edge structure (XANES) spectrum and the first derivative XANES spectrum of Fe–NC SAC are very similar to those of the reference iron phthalocyanine (FePc) which has well-defined Fe–N4 coordinated sites49–51, while distinct from those of the metallic Fe foil. This means Fe state in Fe–NC SAC should be similar to that in FePc. Figure 3b shows the Fourier transform (FT) $k^{3}$ -weighted EXAFS spectra of Fe $\\mathbf{k}$ -edge. Comparing with the Fe foil, no apparent peaks (2.20 and $4.4\\overset{\\smile}{2}\\mathring{\\mathrm{A}}$ ) for Fe−Fe coordination are observed in Fe–NC SAC. As expected, FT EXAFS spectrum of Fe–NC SAC has a strong peak at $1.50\\mathrm{\\AA}$ . In reference to FePc, this peak can be well assigned to Fe–N distance where a nitrogen shell surrounds one Fe atom. Wavelet transform (WT) was also used to investigate the Fe K-edge EXAFS oscillations of Fe–NC SAC and the references. As shown in Fig. 3c, WT analysis of Fe–NC SAC shows only one intensity maximum at about $4.5\\mathring\\mathrm{A}^{-1}$ for Fe–NC SAC, which is very close to that in the reference FePc $({\\sim}4.5\\mathring\\mathrm{A}^{-1})$ , but distinct from the feature of Fe foil $(7.0\\mathring\\mathrm{A}^{-1})$ . Combining with above HAADF–STEM results that all Fe species are atomically dispersed without detectable aggregation, these analyses suggest that Fe in Fe–NC SAC exists in a similar state to the reference FePc. For giving further insights into the chemical configuration of Fe, FT EXAFS fittings in $R,q.$ and $k$ spaces were carried out to reveal the structural parameters and evaluate the fitting quality. As shown in Supplementary Figs. 11 and 12, all fittings are in good consistency with experimental data. The fitting results give an average coordination number of 4.3 for the first shell (Fe–N) and an average $\\mathrm{Fe-N}$ bond length of $1.99\\mathring{\\mathrm{A}}$ (see more details in Supplementary Table 1). \n\nThe chemical environments of $\\mathrm{\\DeltaN}$ in Fe–NC SAC and reference FePc were further investigated by near-edge XAFS (NEXAFS) and XPS technique. The N K-edge NEXAFS spectrum of Fe–NC SAC shows three distinct peaks at about 398.8, 399.8, and $401.8\\:\\mathrm{eV}$ (Fig. 3d). The peak at $398.8\\mathrm{eV}$ can be assigned to pyridinic state or the state similar to aza-bridge in FePc due to the same energy position. The peak at $399.8\\mathrm{eV}$ shares the identical position with the Fe–N bonding in FePc, corroborating the existence of $\\mathrm{Fe\\mathrm{-}N}$ bonding in Fe–NC $S A C^{52,53}$ . The wide peak at $401.8\\:\\mathrm{eV}$ could be assigned to pyrrolic or other nitrogen states according to the literatures54,55. For XPS spectra shown in Fig. 3e, the $\\mathrm{~N~}1s$ signal for Fe–NC SAC can be deconvoluted into several characteristic peaks. The XPS signals at 398.3, 399.5, 400.4, 400.9, and $401.7\\mathrm{eV}$ are assigned to pyridinic-N, Fe– $\\mathrm{\\cdotN_{x},}$ pyrrolic-N, graphitic-N, and oxidized-N, respectively $^{56-58}$ . The peak at $399.5\\mathrm{eV}$ indicates the presence of N in the chemical state similar to $\\mathrm{Fe-N_{x}}$ moiety in FePc.59,60 The high-resolution Fe $2p$ XPS spectrum (Supplementary Fig. 13) indicates that Fe exists in form of iron (II). No clear signal of metallic Fe is detected. These XPS data agree with the existence of $\\mathrm{Fe-N_{x}}$ coordination in Fe–NC SAC. Moreover, the NEXAFS spectra of O K-edge (Supplementary Fig. 14) for Fe–NC SAC shows no distinct features of O–Fe bonding which should appear in the region from 529 to $531\\mathrm{eV}^{61}$ , suggesting there is no significant O–Fe bonding in our Fe–NC SAC. All the above analyses support that Fe–N bonding is the dominated Fe state in Fe–NC SAC. The amount of Fe in Fe–NC SAC is further determined by thermogravimetric analysis (TGA) (Supplementary Fig. 15). The Fe loading of $8.9\\mathrm{wt\\%}$ is significantly higher than those in reported SACs (Supplementary Table 2), suggesting the present strategy is able to deliver single-atomic catalysts with a high metal loading. Importantly, it should be noted that this cascade-anchoring strategy can achieve the mass production of Fe–NC SAC due to facile and manageable processing. As a demonstration, about $_{8\\mathrm{~g~}}$ of Fe–NC SAC is easily obtained in a one-batch synthesis (Supplementary Fig. 16) in the laboratory. XRD pattern and TEM images indicate that the product shares the similar structure to the sample characterized above (Supplementary Fig. 17). \n\n![](images/c0504de085b8dd4a678989ffcd43b0adf4f1b659256768ea0f60abb0e0ac2ed1.jpg) \nFig. 3 Atomic structure analysis of Fe–NC SAC by XAFS and XPS. a Fe K-edge XANES spectra (inset: first-derivative curves), b Fourier transform of Fe K-edge EXAFS spectra, and c, Wavelet transform of the $k^{3}$ -weighted EXAFS data of Fe–NC SAC and reference samples (FePc and Fe foil). d N $K$ -edge NEXAFS spectra and e, deconvoluted N 1s XPS spectra of Fe–NC SAC and reference FePc \n\nInsight into the formation process of Fe–NC SAC. As mentioned above, the present cascade-anchoring strategy is able to prepare single-atomic $\\mathrm{Fe-NC}$ materials with a high Fe loading up to $8.9\\mathrm{wt\\%}$ . It is found that the successive protection tactics at each stage during the synthesis are essential to prevent the aggregation of Fe atoms at high loading condition. (1) Glucose chelating effect: The chelation of Fe ion with glucose is the first protection step to well isolate Fe ion in physical space. The control sample $(\\mathrm{Fe@C-N)}$ prepared in parallel, except for no addition of glucose, shows clearly iron/iron carbide nanoparticles on carbon sheets with some nanotubes formed via Fe-catalyzed growth during the decomposition of melamine, as evidenced by XRD pattern (Fig. 4a) and TEM images (Fig. 4b and Supplementary Fig. 18). The crystallized Fe species are even observed in the sample prepared at $500^{\\circ}\\mathrm{C}$ , without addition of glucose (XRD pattern in Supplementary Fig. 19 for control sample $\\mathrm{Fe}@\\mathrm{C}-\\mathrm{N}-500)$ . The role of chelation is corroborated by another two control experiments. If inorganic iron salt (iron (III) nitrate) is substituted with iron (III) acetylacetonate $(\\mathrm{Fe}(\\mathsf{a c a c})_{3})$ , where the strong interaction between Fe ion and acetylacetone excludes the chelation of glucose and Fe ion, plenty of iron carbide nanoparticles are formed instead of isolated Fe atoms as suggested by XRD (Fig. 4a) and TEM results (Fig. 4c and Supplementary Fig. 20). Moreover, if other chelating agent such as ethylenediamine tetraacetic acid (EDTA) is used to replace glucose, XRD, TEM, and EDS-mapping results suggest that the similar Fe–NC SAC material is obtained (Fig. 4a, d and Supplementary Figs. 21 and 22). In view of the low cost, availability and solubility in water for mass production, glucose was used as chelating agents in our experiments. (2) Physical isolation of complex: The physical isolation of Fe centers is also important. The excessive amount of glucose is found to be necessary for achieving single-atomic $\\mathrm{Fe-N_{x}}$ in the final product. The insufficient amount of glucose (such as 5:1 molar ratio of glucose: Fe) cannot keep Fe atoms away enough to prevent their aggregation during high-temperature pyrolysis so that some Fe-based nanoparticles are produced (Fe–NC–Low Glu, Supplementary Figs. 23 and 24). (3) Carbon substrate: O-rich substrate with a high surface area is critical for the synthesis of high-loading single-atomic $\\mathrm{Fe-N_{x}}$ . Commercial Ketjenblack (KB) with a comparable surface area of $1400\\mathrm{m}^{2}\\mathrm{g}^{-1}$ can be used to replace PC support (Supplementary Fig. 25). XRD pattern in Fig. 4a and TEM images in Fig. 4e and Supplementary Fig. 26 imply that the similar catalyst structure is obtained. It is noted that the acid pre-treatment of KB to create O-rich surface is necessary to achieve uniform distribution of glucose–Fe complex and physically isolate Fe centers on substrate. Without acid treatment, KB is not dispersed well in aqueous solution and Fe aggregates are obtained. In contrast, if graphene oxide (GO) with a low surface area of $90\\mathrm{m}^{2}\\mathrm{g}^{-1}$ is used (Supplementary Fig. 25), a number of Fe-based nanoparticles are produced as evidenced by XRD pattern (Fig. 4a) and TEM images (Fig. 4f and Supplementary Fig. 27). It is believed that such surface area is not sufficient to isolate glucose–Fe complex, leading to the aggregation of active Fe atoms during pyrolysis. (4) Cascade protection at different stages: As mentioned above, excessive glucose to chelate Fe ion and physically isolate them is required to achieve Fe–NC SAC; however, it is not sufficient. It is found that the glucose protection is only effective at a moderate temperature. The control sample prepared without addition of melamine shows no crystalline Fe species at the pyrolysis temperature up to $500^{\\circ}\\mathrm{C}$ $\\mathbf{\\tilde{F}e}@\\mathbf{C}\\mathbf{-Glu}\\mathbf{-}500_{\\r{\\r{G}}}^{\\r{\\prime}}$ (Supplementary Fig. 19), whereas increasing the pyrolysis temperature to $600^{\\circ}\\mathrm{C}$ crystallized ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ phase can be clearly detected in XRD pattern ${\\mathrm{Te@C-}}$ Glu-600) (Supplementary Fig. 19). Further increasing the temperature to $800^{\\circ}\\mathrm{C}$ metallic Fe-based phase shows up in XRD pattern (Fig. 4a) of the sample $\\left(\\mathrm{Fe@C-Glu}\\right)$ instead of ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ phase due to carbothermal reduction and a number of nanoparticles can be clearly identified in TEM images (Fig. $4\\mathrm{g}$ and Supplementary Fig. 28). Without melamine these nanoparticles can even migrate, leaving the holes in carbon substrate. It is known that melamine decomposes to N-containing species such as $\\mathrm{C}_{3}\\mathrm{N}_{4}$ etc. at over $400^{\\circ}\\mathrm{C}^{6\\hat{2}}$ . In the synthesis of Fe–NC SAC, when the Fe–glucose complexes start to decompose and release Fe atoms at elevated temperature, the surrounding abundant active $\\mathrm{CN}_{\\mathrm{x}}$ species decomposed from excessive amount of melamine will instantly capture these active Fe atoms by forming $\\mathrm{Fe\\mathrm{-}N}$ bonding as $\\mathrm{Fe-N_{x}}$ species since it is an energy-favorable process, similar to the case of the formation of $\\mathrm{Pd}\\mathrm{-}\\mathrm{N}^{63}$ . These $\\bar{\\mathrm{Fe-N_{x}}}$ species will be subsequently incorporated into the carbon network newly evolved from the graphitization of glucose and melamine during pyrolysis, preventing them from aggregation. The single-atomically dispersed $\\mathrm{Fe-N_{x}}$ sites have been evidenced by the above-mentioned analyses. \n\n![](images/ae32d41aa55b218168edc8052254c69ea09df463cab1c4a93b3f0a79f3f07fa2.jpg) \nFig. 4 Structural characterizations of control samples. a XRD patterns and b–g, TEM images of Fe@C–N (b), Fe(acac) $\\mid_{3}$ –NC (c), Fe–NC SAC–EDTA (d), Fe–NC SAC–KB (e), Fe–N–GO (f), and Fe@C-Glu $\\mathbf{\\sigma}(\\mathbf{g})$ . Scale bars: $200\\mathsf{n m}$ (b, d); $100\\mathsf{n m}$ (c, e, f); $500\\mathsf{n m}$ (g) \n\nElectrocatalytic performance evaluation of Fe–NC SAC. As a demonstration of the potential applications of M–NC SACs, the electrocatalytic activity of Fe–NC SAC for ORR was evaluated and compared with benchmark $\\mathrm{Pt/C}$ catalyst and control samples $(\\mathrm{Fe@C-N}$ , Fe@C-Glu, and C–N-Glu). As shown in Fig. 5a and Supplementary Table 3, the state-of-the-art commercial $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%})$ exhibits a good ORR activity in terms of an onset potential (defined by the potential at which the current density reaches $0.1\\mathrm{mA}\\mathrm{cm}\\dot{-}2)^{64,6\\hat{5}}$ of $0.96\\mathrm{V}$ and a half-wave potential of $0.85\\mathrm{V}$ . While the present Fe–NC SAC obviously shows a positively shifted onset potential (0.98 V) and a half-wave potential $(0.90\\mathrm{V})$ , which are 20 and $50\\mathrm{mV}$ more positive than those for $\\mathrm{Pt/C}$ catalyst and superior to most of non-precious metal ORR electrocatalysts (Supplementary Table 4). The mass activity of $_{\\mathrm{Fe-NC-SAC}}$ is calculated to be $9.0\\mathrm{Ag}^{-1}$ at $0.90{\\mathrm{V}}$ . What is more, the Fe–NC SAC shows a high kinetic mass current of $100.7\\mathrm{Ag^{-1}}$ at $0.90{\\mathrm{V}}$ , $65\\mathrm{Ag^{-1}}$ larger than $\\mathrm{Pt/C}$ $(35.7\\mathrm{Ag^{-1}})$ . In contrast, control sample $\\mathrm{Fe@C-N}$ (prepared without glucose), ${\\mathrm{Fe@C}}$ -Glu (prepared without melamine), and C–N–Glu (prepared without iron) demonstrate poor ORR electrocatalytic activities (Supplementary Fig. 29). The superior ORR electrocatalytic activity of Fe–NC SAC is further confirmed by the smallest Tafel slope (48 vs. $69\\mathrm{mV}$ dec−1 for $\\mathrm{Pt/C)}$ (Fig. 5b) and the lowest $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield (below $3.5\\%$ at the whole potential range) (Fig. 5c). These results indicate that ORR process on Fe–NC SAC follows a four-electron pathway with a high electrocatalytic efficiency for ORR. \n\n![](images/985591fcba401eacd6b1a9742df4661b7a26f7900c68c8f70bce27fb747dc87f.jpg) \nFig. 5 Evaluation of electrocatalytic performance of Fe–NC SAC for ORR. a Steady-state ORR polarization curves of Fe–NC SAC, $\\mathsf{P t/C}$ and control samples (Fe $@{\\mathsf{C}}-{\\mathsf{N}}$ and F $\\mathsf{e}(\\varpi mathsf{C}\\cdot\\mathsf{G}|\\mathsf{u})$ . b Corresponding Tafel plots. c Hydrogen peroxide yield. d Steady-state ORR polarization curves of Fe–NC SAC recorded in $\\mathsf{O}_{2}$ - saturated $0.1\\mathsf{M}\\mathsf{K}\\mathsf{O}\\mathsf{H}$ with or without poisoning by 0.01 M $S C N^{-}$ , and one collected after removing $S C N^{-}$ . e Steady-state ORR polarization curves of Fe–NC SAC with different Fe loading. f Steady-state ORR polarization curves of Fe–NC SAC and $\\mathsf{P t/C}$ before and after 5000 potential scanning cycles in $\\mathsf{O}_{2}$ - saturated 0.1 M KOH \n\nTo get insight into the active sites for ORR in Fe–NC SAC, additional control experiments were carried out. Although there is still debate about the most active sites for ORR in Fe–N–C catalysts due to complicate catalyst structures, $\\mathrm{Fe-N_{x}}$ site is generally considered to play an important role in catalyzing ORR. It has been reported that $\\mathsf{S C N^{-}}$ ion is able to strongly interact with Fe center, thus poisoning $\\mathrm{Fe-N_{x}}$ coordination site66. Since the coordination of Fe–SCN is stable in the acidic condition but not in the alkaline medium, we first test the ORR activity of Fe–NC SAC in $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{~M~}\\mathrm{HClO_{4}}$ containing $0.01\\mathrm{M}$ $\\mathrm{{\\calS}C N^{-}}$ . The result shows that the half-wave potential decrease distinctly by about $116\\mathrm{mV}$ comparing with the curve measured without addition of $0.01\\mathrm{M}\\mathrm{SCN}^{-}$ (Supplementary Fig. 30), which can be ascribed to the blocking of $\\mathrm{Fe-N_{x}}$ active sites by $\\mathrm{{SCN^{-}}}$ . Moreover, when rinsing this pre-poisoned electrode to $\\mathrm{\\pH}=7$ and re-testing it in $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{M}\\mathrm{\\KOH}$ , the half-wave potential negatively shifts by about $30\\mathrm{mV}$ compared with the values measured in $0.1\\mathrm{M}$ KOH without $\\mathsf{S C N^{-}}$ (Fig. 5d)67,68. It is noted that polarization curve can gradually recover to its original state during the measurements since the blocked $\\mathrm{Fe-N_{x}}$ coordination sites can be gradually released as the dissociation of $\\mathrm{Fe-SCN^{-}}$ in KOH (Fig. 5d). These results suggest that $\\mathrm{Fe-N_{x}}$ sites should be the most active sites in Fe–NC SAC in view that only two possible active sites exist, i.e. Fe– $\\mathrm{\\cdotN_{x}}$ sites and N-doped carbon. To further demonstrate the role of $\\mathrm{Fe-N_{x}}$ sites, we prepared another control sample Fe–NC SAC with a low Fe loading via reducing the amount of Fe source and keeping all other conditions same. The characterizations indicate that the similar catalyst to Fe–NC SAC was achieved except for the low Fe loading of $2.6\\mathrm{wt\\%}$ (vs. $8.9\\mathrm{wt\\%}$ for Fe–NC SAC) (Supplementary Fig. 31). The electrochemical measurements show that the ORR electrocatalytic activity is significantly attenuated in terms of 80 $\\mathrm{mV}$ negatively shifted half-wave potential and decreased limiting current density (Fig. 5e). This result corroborates that $\\mathrm{Fe-N_{x}}$ sites in Fe–NC SAC are the efficient active sites for delivering a high ORR activity and the loading of $\\mathrm{Fe-N_{x}}$ sites affects the activity. Furthermore, it is noted that Fe–NC SAC also shows a better ORR electrocatalytic activity than the reference sample $\\mathrm{FePc/C}$ which was prepared by loading FePc on carbon substrate with a similar Fe loading (see more details in Supplementary Fig. 32). This could be ascribed to the severe aggregation of FePc and the possible differences in the environments of $\\mathrm{Fe-N_{x}}$ centers for our Fe–NC SAC and reference ${\\mathrm{FePc/C}}$ . \n\nDurability is another important criterion for assessing electrocatalyst performance. The durability of Fe–NC SAC was evaluated using accelerated durability test (ADT) by cyclic voltammetry experiment from 0.6 to $1.0\\mathrm{V}$ at $50\\mathrm{mVs^{-1}}$ in $\\mathrm{O}_{2}$ - saturated 0.1 M KOH. As shown in Fig. 5f, polarization curves recorded after 5000 cycles for Fe–NC SAC display a negligible degradation for half-wave potential and limiting current density, indicating its superior durability in alkaline medium. TEM and EDS-mapping images reveal that no Fe aggregation is observed, and the atomic dispersion of $\\mathrm{Fe-N_{x}}$ sites retains in Fe–NC SAC after ADT (Supplementary Fig. 33). By contrast, the commercial $\\mathrm{Pt/C}$ catalyst shows a $20\\mathrm{mV}$ loss in half-wave potential and appreciable reduction of limiting current density after ADT. The significant activity degradation for $\\mathrm{Pt/C}$ catalyst should be attributed to the serious dissolution/agglomeration of $\\mathrm{Pt}$ nanoparticles during ADT, as shown in Supplementary Figs. 34 and $35^{69}$ . \n\nDemonstration for general synthesis of M–NC SACs. Inspired by the simplicity and general applicability of the present cascadeprotection strategy, we easily extend it to prepare a wide range of other M–NC SACs ( $\\mathbf{\\dot{M}}=\\mathbf{M}\\mathbf{n}$ , Co, Ni, Cu, Mo, Pt, etc.) with a high metal loading. As shown in Fig. 6a–f and Supplementary Fig. 36, the white spots in a size of single atom in HAADF–STEM images indicate that Mn, Co, Ni, Cu, Mo, and $\\mathrm{Pt}$ are singleatomically dispersed in the PC substrate. A couple of spots with different size could be ascribed to the metal atom imaged at different focusing planes or possible atom cluster. XRD patterns prove that no crystallized metal-based phases are detected (Supplementary Fig. 37). EDS spectra, corresponding mapping images and EELS-mapping images confirm the existence of element metal and nitrogen as well as their homogenous distribution (Supplementary Figs. 38–45). These results suggest that these M–NC SACs should share the similar structure to Fe–NC SAC. TGA analyses give the metal loading from 12.1 to $4.5\\mathrm{wt\\%}$ (Fig. $6\\mathrm{g}$ and Supplementary Fig. 46). The variation could be ascribed to the differences in the interaction of glucose and metal ions as well as the carbon loss in the presence of different metals. The exploration for the applications of these M–NC SACs are expected in view of the high density of single-atomically dispersed metal– $\\cdot\\mathrm{N_{x}}$ active centers. For example, Ni–NC SAC exhibits the potential for $\\mathrm{CO}_{2}$ reduction to CO and shows an $89\\%$ of Faraday efficiency at $-0.85\\mathrm{V}$ with a $30\\mathrm{mA}\\mathrm{cm}^{-2}$ of current density for CO (Supplementary Fig. 47 and Fig. 6h, i). This high current density outperforms most reported Ni-based singleatom catalysts, which should be attributed to the high-density Ni-based active sites with a Ni loading of $5.9\\mathrm{wt\\%}$ in Ni–NC SAC (Supplementary Tables 5 and 6). \n\n# Discussion \n\nIn summary, a cascade-protection strategy is developed to synthesize single-atomic metal– $\\cdot\\mathrm{N_{x}}$ sites on N-doped carbon with a high metal loading up to $12.1\\mathrm{wt\\%}$ . The single-atomic dispersion of metal atoms and the formation of metal– $\\mathbf{\\cdotN_{x}}$ sites are evidenced by the different analytic techniques, including HAADF–STEM, EELS, XANES, EXAFS, and NEXAFS etc. The formation process of single-atomic metal– $\\cdot\\mathrm{N_{x}}$ sites and the effectiveness of the cascade-protection strategy are systematically investigated by a series of control experiments. The results suggest that the chelation of glucose and Fe ion, physical isolation of glucose–Fe complex via excessive glucose, support with sufficient O-species and surface area to anchor and isolate glucose–Fe complex, and the binding with N-species at elevated pyrolysis temperature are required to achieve the high-loading single-atomic $\\bar{\\mathrm{Fe-N_{x}}}$ sites. As a demonstration, the electrocatalytic performance of Fe–NC SAC for ORR is evaluated. Benefiting from the high-loading $\\mathrm{Fe-N_{x}}$ active sites and their single-atomic dispersion for exposing each site, Fe–NC SAC exhibits a superior ORR electrocatalytic activity and durability with a half-wave potential of $0.90\\mathrm{V}$ and a kinetic mass current of $100.7\\mathrm{Ag^{-1}}$ at $0.90{\\mathrm{V}}$ , $50\\mathrm{mV}$ and $65\\mathrm{Ag^{-1}}$ higher than state-of-the-art $\\mathrm{Pt/C},$ respectively. The poisoning and loading-dependent experiments indicate that such ORR performance should be from $\\mathrm{Fe-N_{x}}$ sites. The mass production and scalability of the present strategy is demonstrated by synthesis over $_{8\\mathrm{g}}$ of such Fe–NC SAC with consistent ORR activity in a single-lab batch. The universal syntheses of other M–NC SACs 1 $\\mathbf{\\dot{M}}=\\mathbf{M}\\mathbf{n}$ , Co, Ni, Cu, Mo, Pt, etc.) demonstrate that such strategy can be easily adapted to apply different chelating agents, substrates, and metal sources for a wide range of metal–NC SACs. In view of high-loading metal– $\\cdot\\mathrm{N_{x}}$ coordination sites in singleatomic level, these materials are expected for diverse applications, including electrocatalysis and heterogeneous catalysis etc. \n\n![](images/77a594391f317a712b00727da6b8ec247e768fb7a4bf1f82a4f6b0da420c5da9.jpg) \nFig. 6 Atomic structure characterizations and loading analysis of M–NC SACs. a–f HAADF–STEM images for Mn–NC SAC (a), Co–NC SAC (b), Ni–NC SAC (c), Cu–NC SAC (d), Mo–NC SAC (e), and Pt–NC SAC (f). Scale bars, $3\\mathsf{n m}$ (a–f). g Metal loading in M–NC SACs. h Faradaic efficiency of CO, and i, $j_{\\mathtt{c o}}$ for Ni–NC SAC and control sample (NC) \n\n# Methods \n\nSynthesis of PC support. In total, 8 mmol of potassium citrate (Alfa Aesar Co., Ltd.) was pyrolyzed at $800^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ in a tube furnace and Ar atmosphere. The black solid product was washed with $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution $(0.5{\\bf M})$ (Alfa Aesar Co., Ltd.) and water $(18.2\\mathrm{M}\\Omega)$ to remove inorganic impurities. After drying at $60^{\\circ}\\mathrm{C},$ , the PC support was achieved. \n\nSynthesis of Fe–NC SAC. In total, $60\\mathrm{mg}$ of PC, $0.3\\mathrm{mmol}$ of iron (III) nitrate nonahydrate (Alfa Aesar Co., Ltd.), and 6.7 mmol of $\\mathtt{a}$ -D-glucose (Sinopharm \n\nChemical Reagent Co., Ltd.) were dispersed in $5\\mathrm{mL}$ of ultrapure water, and sonicated for $30\\mathrm{min}$ to get a homogenous black suspension. The slurries were harvested after washing with water and drying at $60^{\\circ}\\mathrm{C}.$ and then grounded together with melamine (Alfa Aesar Co., Ltd.) at a mass ratio of 1:5. The obtained powder was placed into a tube furnace and heated to $800^{\\circ}\\mathrm{C}$ under Ar flow $(100\\ \\mathrm{sccm}),$ . After $^{2\\mathrm{h}}$ of pyrolysis, the black Fe–NC SAC was obtained. M–NC SACs $\\mathbf{M}=\\mathbf{M}\\mathbf{n}$ , Co, Ni, Cu, Mo, and Pt) were prepared via the same procedures, except for using manganese nitrate hexahydrate (Alfa Aesar Co., Ltd.), cobalt nitrate hexahydrate (Alfa Aesar Co., Ltd.), nickel nitrate hexahydrate (Alfa Aesar Co., Ltd.), cupric nitrate hemipentahydrate (Alfa Aesar Co., Ltd.), ammonium molybdate tetrahydrate (Alfa Aesar Co., Ltd.), and (hydro)chloroplatinic acid (Alfa Aesar Co., Ltd.) as the metal precursor, respectively. \n\nSynthesis of control samples. (1) Fe–NC SAC–EDTA was synthesized in parallel by the same method as that for Fe–NC SAC, except for using the same mass amount of EDTA (Alfa Aesar Co., Ltd.) instead of glucose. $\\mathrm{Fe}(\\mathrm{acac})_{3}\\mathrm{-NC}$ was prepared in parallel by the same method as that for Fe–NC SAC, except for using the same molar amount of ${\\mathrm{Fe}}(\\mathsf{a c a c})_{3}$ (Alfa Aesar Co., Ltd.) instead of iron (III) nitrate nonahydrate. (2) Fe–NC SAC–KB and Fe–N–GO were prepared in parallel by the same method as that Fe–NC SAC except for using the same mass amount of commercial KB $(1400\\mathrm{m}^{2}\\mathrm{g}^{-1})$ (Ketjenblack EC-600JD, Akzo Nobel, Inc.) and GO $(90\\mathrm{m}^{2}\\mathrm{g}^{-1})$ (Nanjing XFNANO Materials Tech. Co.) instead of PC support, respectively. (3) Fe@C-Glu was obtained in parallel by the same synthesis route as that for Fe–NC SAC, except for no addition of melamine; the samples pyrolyzed at 500, 600, and $800^{\\circ}\\mathrm{C}$ are designated as Fe@C-Glu-500, Fe@C-Glu-600, and $\\mathrm{Fe@C\\mathrm{-}G l u},$ respectively. (4) $\\mathrm{Fe@C-N}$ was prepared in parallel by the same synthesis route as that for Fe–NC SAC, except for no addition of glucose; the samples pyrolyzed at 500 and $800^{\\circ}\\mathrm{C}$ are designated as $\\mathrm{Fe}@\\mathrm{C}-\\mathrm{N}-500$ and $\\mathrm{Fe@C-N}$ , respectively. (5) Fe–NC–Low Glu was prepared in parallel by the same method as that Fe–NC SAC except for using $1.5\\mathrm{mmol}$ glucose instead of $6.7\\mathrm{mmol}$ glucose. (6) C–N–Glu was prepared in parallel by the same synthesis route as that for Fe–NC SAC, except for no addition of iron source. (7) $\\mathrm{FePc}/\\mathrm{C}$ was prepared by dispersion $60\\mathrm{mg}$ of PC and $42\\mathrm{mg}$ of FePc (Alfa Aesar Co., Ltd.) in $5\\mathrm{mL}$ of dimethyl formamide (Alfa Aesar Co., Ltd.), followed by sonication for $30\\mathrm{min}$ to get a homogenous black suspension. The product was collected after washing and drying. (8) NC was synthesized in parallel by the same method as that Fe–NC SAC, except for no addition of iron source and glucose. \n\nA scale-up synthesis of Fe–NC SAC. The product was prepared in parallel by the same synthesis route as that for Fe–NC SAC, except for increasing the amount of carbon substrate, iron (III) nitrate nonahydrate, glucose, and ultrapure water to ${5}{\\mathrm{g}},$ 24.8 mmol, $0.56\\mathrm{M}$ and $420\\mathrm{mL}$ , respectively. \n\nCatalyst characterizations. XRD patterns were recorded on Regaku D/Max-2500 (Rigaku Co., Japan) diffractometer equipped with a Cu Kα1 radiation $\\mathrm{\\Delta}\\lambda=1.54056$ Å). The morphologies were characterized by SEM on S4800 (JEOL, Japan) and TEM on JEM-2100F (JEOL, Japan) equipped with an EDS detector. \n\nHAADF–STEM and EELS mapping observations were carried out on a JEOL ARM200F (JEOL, Japan) STEM operated at $200\\mathrm{kV}$ with cold-filled emission gun and double hexapole Cs correctors (CEOS GmbH, Germany). The attainable spatial resolution defined by the probe-forming objective lens is better than 80 picometers. Nitrogen adsorption–desorption isotherms were collected on a Quadrasorb SI-MP system (Quantachrome, USA) at $77\\mathrm{K}$ . The specific surface area was calculated by Brunauer Emmett Teller method. The pore size distribution and pore volume were calculated using DFT method. XPS spectra were recorded on an ESCALab220i-XL electron spectrometer (VG Scientific, UK) using an Al Kα radiation. Raman spectra were obtained on Lab-RAM HR Evolution (Horiba Scientific, Japan) with a laser excitation wavelength of $532\\mathrm{nm}$ . FTIR experiments were performed using Thermo Fisher Nicolet iN10 FTIR microscope (Thermo Nicolet Corp., USA). The metal loading was measured via TGA on a Netzsch DSC214 instrument (NETZSCH, Germany) from 40 to $800^{\\circ}\\mathrm{C}$ under air flow with a ramp of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ . XANES and EXAFS of the Fe K-edges were acquired on the XAFS station of the 14W1 beam line of the Shanghai Synchrotron Radiation Facility. The fluorescence mode was used to record the X-ray absorption spectra of Fe K-edges. Data were recorded by using a Si (111) double-crystal monochromator. The back-subtracted EXAFS function was converted into $k$ space and weighted by $k^{3}$ to compensate for the diminishing amplitude due to the decay of the photoelectron wave. The Fourier transforming of the $\\mathrm{k}^{3}$ -weighted (for Fe) EXAFS data was performed in the range of $\\mathrm{k}=3{-}1\\overset{\\smile}{2}\\mathring{\\mathrm{A}}^{-1}$ using a Hanning function window to get the radial distribution function. The NEXAFS spectra were collected at Beamline 8.0 of Advanced Light Source in Lawrence Berkeley National Lab via a total fluorescence yield mode with a probing depth of ${\\sim}100\\mathrm{nm}$ . The samples were thoroughly outgassed before measurements. \n\nElectrochemical measurements. ORR Tests. All ORR electrochemical measurements were recorded on a rotating ring-disk electrode rotator (RRDE-3A) (ALS, Japan) by a standard three-electrode cell system connected to an electrochemical workstation (Autolab PGSTAT 302N) (Metrohm, Netherlands) at room temperature. A rotating ring-disk electrode (RRDE) ( $\\mathrm{:4}\\mathrm{mm}$ in diameter) with catalytic material acted as the working electrode; and an $\\mathrm{\\Ag/AgCl}$ electrode (saturated KCl solution) and a graphite rod were employed for the reference and counter electrode, respectively. The working electrodes were prepared as follows: all non-precious homogeneous ink was formed by mixing $2\\mathrm{mg}$ of catalysts and ${800\\upmu\\mathrm{L}}$ of ethanol (Beijing Chemical Reagent Factory) in a glass vial and sonicated for 30 min. The $30\\upmu\\mathrm{L}$ of ink and $2\\upmu\\mathrm{L}\\ 0.5\\mathrm{wt\\%}$ of Nafion solution (Alfa Aesar Co., Ltd.) were dropped on polished RRDE to get catalysts loading of $600\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ and dried $10\\mathrm{min}$ in the air. For comparison, commercial Johnson–Matthey $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%})$ was also measured with loading of $25.5\\upmu\\mathrm{g}_{\\mathrm{Pt}}\\mathrm{cm}^{-2}$ . The accelerated durability tests of Fe–NC SAC and commercial $\\mathrm{Pt/C}$ were performed in the $\\mathrm{O}_{2}$ -saturated $0.1\\mathbf{M}$ KOH (Alfa Aesar Co., Ltd.) solution by cycling the catalysts between 0.6 and $1.0\\mathrm{V}$ at $50\\mathrm{mVs^{-1}}$ , referring to the protocol from USA Department of Energy. Poisoning experiment for Fe–NC SAC was first executed in $\\mathrm{O}_{2}$ -saturated 0.1 M $\\mathrm{\\bar{HClO}_{4}}$ (Alfa Aesar Co., Ltd.) with addition of 0.01 M NaSCN (Alfa Aesar Co., Ltd.). The remarkably depression of catalytic activity can be seen. After that, the working electrode with poisoned Fe–NC SAC was rinsed thoroughly and measured again in $0.1\\mathrm{{M}}$ KOH under $\\mathrm{O}_{2}$ atmosphere. All ORR measurements were collected at a scan rate of $10\\mathrm{mVs^{-1}}$ at a rotation speed of $1600~\\mathrm{rpm}$ . Before each ORR test, the electrolyte was purged with oxygen at least for $30\\mathrm{min}$ . All non-Pt catalysts were scanned in the $\\Nu_{2}$ -saturated electrolyte. The obtained background voltammograms were subtracted from that measured in the $\\mathrm{O}_{2}$ -saturated electrolyte before each ORR measurement. \n\nThe yield of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ on different catalysts was calculated by the following equation: \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}_{2}\\%=200*{\\frac{I_{\\mathrm{R}}/N}{I_{\\mathrm{R}}/N+I_{\\mathrm{D}}}}\n$$ \n\nwhere $I_{\\mathrm{R}}$ and $\\ensuremath{I_{\\mathrm{D}}}$ are the ring and disk currents, respectively, and $N$ is the ring collection efficiency. The $N$ value was measured to be $42.4\\%$ . \n\n$\\pmb{\\ c o_{2}}$ reduction tests. All electrochemical measurements for $\\mathrm{CO}_{2}$ reduction were carried out in a gas-tight cell with two-compartments separated with a Nafion membrane (Nafion $^{\\circledcirc}115$ , DuPont, Inc.). A same standard three-electrode cell system as that for ORR was used to collect electrochemical data. In a typical prepared process of the working electrode, $600\\upmu\\mathrm{L}$ of the mixing ink, which was obtained by dispersing $1\\mathrm{mg}$ catalyst in $30\\upmu\\mathrm{L}0.5\\up w\\upnu\\%$ of Nafion solution and $570\\upmu\\mathrm{L}$ of ethanol solution, was loaded on two sides of a carbon cloth (Alfa Aesar Co., Ltd.) with $1\\times1\\mathrm{cm}^{2}$ . During the $\\mathrm{CO}_{2}$ reduction experiments, all measurements were collected at a scan rate of $10\\mathrm{mVs^{-1}}$ in $\\Nu_{2}$ -saturated 0.5 M ${\\mathrm{KHCO}}_{3}$ (Alfa Aesar Co., Ltd.) or $\\mathrm{CO}_{2}$ -saturated $0.5\\mathrm{M}\\mathrm{KHCO}_{3}$ electrolyte. The gas phase composition was analyzed by gas chromatograph (Agilent 7890B, USA) every $^{\\textrm{1h}}$ . The separated gas products were measured by a thermal conductivity detector (for $\\mathrm{H}_{2}^{\\cdot\\cdot}$ and a flame ionization detector (for CO). \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 22 November 2018 Accepted: 1 March 2019 \nPublished online: 20 March 2019 \n\n# References \n\n1. Yang, X.-F. et al. Single-atom catalysts: A new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748 (2013). \n2. Zhu, C., Fu, S., Shi, Q., Du, D. & Lin, Y. Single-atom electrocatalysts. Angew. Chem., Int. Ed. 56, 13944–13960 (2017). \n3. Herzing, A. A., Kiely, C. J., Carley, A. F., Landon, P. & Hutchings, G. J. Identification of active gold nanoclusters on iron oxide supports for CO oxidation. Science 321, 1331–1335 (2008). \n4. Vajda, S. et al. Subnanometre platinum clusters as highly active and selective catalysts for the oxidative dehydrogenation of propane. Nat. Mater. 8, 213–216 (2009). \n5. Jones, J. et al. Thermally stable single-atom platinum-on-ceria catalysts via atom trapping. Science 353, 150–154 (2016). \n6. Li, H. et al. Synergetic interaction between neighbouring platinum monomers in $\\mathrm{CO}_{2}$ hydrogenation. Nat. Nanotechnol. 13, 411–417 (2018). \n7. Yang, F., Deng, D., Pan, X., Fu, Q. & Bao, X. Understanding nano effects in catalysis. Natl. Sci. Rev. 2, 183–201 (2015). \n8. Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}/F e O_{x}}$ Nat. Chem. 3, 634–641 (2011). \n9. Liu, P. et al. Photochemical route for synthesizing atomically dispersed palladium catalysts. Science 352, 797–800 (2016). \n10. Shan, J., Li, M., Allard, L. F., Lee, S. & Flytzani-Stephanopoulos, M. Mild oxidation of methane to methanol or acetic acid on supported isolated rhodium catalysts. Nature 551, 605–608 (2017). \n11. Peterson, E. J. et al. Low-temperature carbon monoxide oxidation catalysed by regenerable atomically dispersed palladium on alumina. Nat. Commun. 5, 4885 (2014). \n12. Ding, K. et al. Identification of active sites in CO oxidation and water-gas shift over supported Pt catalysts. Science 350, 189–192 (2015). \n13. Lin, J. et al. Remarkable performance of $\\mathrm{Ir_{1}/F e O_{x}}$ single-atom catalyst in water gas shift reaction. J. Am. Chem. Soc. 135, 15314–15317 (2013). \n14. Guo, X. et al. Direct, nonoxidative conversion of methane to ethylene, aromatics, and hydrogen. Science 344, 616–619 (2014). \n15. Li, X. et al. Single-atom Pt as co-catalyst for enhanced photocatalytic $\\mathrm{H}_{2}$ evolution. Adv. Mater. 28, 2427–2431 (2016). \n16. Gao, G., Jiao, Y., Waclawik, E. R. & Du, A. Single atom (Pd/Pt) supported on graphitic carbon nitride as an efficient photocatalyst for visible-light reduction of carbon dioxide. J. Am. Chem. Soc. 138, 6292–6297 (2016). \n17. Cheng, N. et al. Platinum single-atom and cluster catalysis of the hydrogen evolution reaction. Nat. Commun. 7, 13638 (2016). \n18. Bayatsarmadi, B., Zheng, Y., Vasileff, A. & Qiao, S.-Z. Recent advances in atomic metal doping of carbon-based nanomaterials for energy conversion. Small 13, 1700191 (2017). \n19. Wei, H. et al. Iced photochemical reduction to synthesize atomically dispersed metals by suppressing nanocrystal growth. Nat. Commun. 8, 1490 (2017). \n20. Chung, H. T. et al. Direct atomic-level insight into the active sites of a highperformance PGM-free ORR catalyst. Science 357, 479–484 (2017). \n21. Yin, P. et al. Single cobalt atoms with precise N-coordination as superior oxygen reduction reaction catalysts. Angew. Chem., Int. Ed. 55, 10800–10805 (2016). \n22. Han, A. et al. A polymer encapsulation strategy to synthesize porous nitrogendoped carbon-nanosphere-supported metal isolated-single-atomic-site catalysts. Adv. Mater. 30, 1706508 (2018). \n23. Liu, J. et al. High performance platinum single atom electrocatalyst for oxygen reduction reaction. Nat. Commun. 8, 15938 (2017). \n24. Wang, J. et al. In situ formation of molecular Ni-Fe active sites on heteroatomdoped graphene as a heterogeneous electrocatalyst toward oxygen evolution. Sci. Adv. 4, eaap7970 (2018). \n25. Ju, W. et al. Understanding activity and selectivity of metal-nitrogen-doped carbon catalysts for electrochemical reduction of $\\mathrm{CO}_{2}$ . Nat. Commun. 8, 944 (2017). \n26. Shi, M.-M. et al. Au sub-nanoclusters on $\\mathrm{TiO}_{2}$ toward highly efficient and selective electrocatalyst for $\\Nu_{2}$ conversion to $\\mathrm{NH}_{3}$ at ambient conditions. Adv. Mater. 29, 1606550 (2017). \n27. Shi, Y. et al. Single-atom catalysis in mesoporous photovoltaics: The principle of utility maximization. Adv. Mater. 26, 8147–8153 (2014). \n28. Judai, K., Abbet, S., Wörz, A. S., Heiz, U. & Henry, C. R. Low-temperature cluster catalysis. J. Am. Chem. Soc. 126, 2732–2737 (2004). \n29. Lee, S., Fan, C., Wu, T. & Anderson, S. L. CO oxidation on ${\\mathrm{Au}}_{\\mathrm{n}}/{\\mathrm{TiO}}_{2}$ catalysts produced by size-selected cluster deposition. J. Am. Chem. Soc. 126, 5682–5683 (2004). \n30. Lei, Y. et al. Increased silver activity for direct propylene epoxidation via subnanometer size effects. Science 328, 224–228 (2010). \n31. Liu, L. et al. Generation of subnanometric platinum with high stability during transformation of a 2D zeolite into 3D. Nat. Mater. 16, 132–138 (2017). \n32. Choi, C. H. et al. Tuning selectivity of electrochemical reactions by atomically dispersed platinum catalyst. Nat. Commun. 7, 10922 (2016). \n33. Fei, H. et al. Atomic cobalt on nitrogen-doped graphene for hydrogen generation. Nat. Commun. 6, 8668 (2015). \n34. Malko, D., Kucernak, A. & Lopes, T. In situ electrochemical quantification of active sites in Fe–N/C non-precious metal catalysts. Nat. Commun. 7, 13285 (2016). \n35. Li, Y. et al. An oxygen reduction electrocatalyst based on carbon nanotube–graphene complexes. Nat. Nanotechnol. 7, 394–400 (2012). \n36. Genovese, C. et al. Operando spectroscopy study of the carbon dioxide electro-reduction by iron species on nitrogen-doped carbon. Nat. Commun. 9, 935 (2018). \n37. Xu, H., Cheng, D., Cao, D. & Zeng, X. C. A universal principle for a rational design of single-atom electrocatalysts. Nat. Catal. 1, 339–348 (2018). \n38. Deng, D. et al. A single iron site confined in a graphene matrix for the catalytic oxidation of benzene at room temperature. Sci. Adv. 1, e1500462 (2015). \n39. Liu, W. et al. Single-atom dispersed Co-N-C catalyst: Structure identification and performance for hydrogenative coupling of nitroarenes. Chem. Sci. 7, 5758–5764 (2016). \n40. Chen, Z. et al. Stabilization of single metal atoms on graphitic carbon nitride. Adv. Funct. Mater. 27, 1605785 (2017). \n41. Fei, H. et al. General synthesis and definitive structural identification of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n42. Campbell, C. T., Parker, S. C. & Starr, D. E. The effect of size-dependent nanoparticle energetics on catalyst sintering. Science 298, 811–814 (2002). \n43. Simonsen, S. B. et al. Direct observations of oxygen-induced platinum nanoparticle ripening studied by in situ TEM. J. Am. Chem. Soc. 132, 7968–7975 (2010). \n44. Hansen, T. W., DeLaRiva, A. T., Challa, S. R. & Datye, A. K. Sintering of catalytic nanoparticles: Particle migration or ostwald ripening? Acc. Chem. Res. 46, 1720–1730 (2013). \n45. Risse, T., Shaikhutdinov, S., Nilius, N., Sterrer, M. & Freund, H.-J. Gold supported on thin oxide films: From single atoms to nanoparticles. Acc. Chem. Res. 41, 949–956 (2008). \n46. Geetha, K., Raghavan, M. S. S., Kulshreshtha, S. K., Sasikala, R. & Rao, C. P. Transition-metal saccharide chemistry: Synthesis, spectroscopy, electrochemistry and magnetic susceptibility studies of iron(III) complexes of mono- and disaccharides. Carbohydr. Res. 271, 163–175 (1995). \n47. Nagy, L. et al. Iron(III) complexes of sugar-type ligands. Inorg. Chim. Acta 124, 55–59 (1986). \n48. Nagy, L., Gajda, T., Kürti, J., Schrantz, K. & Burger, K. Spectroscopic studies of iron(III) complexes of D-saccharose and D-glucose in the solid state and in solution. J. Radioanal. Nucl. Chem. 209, 225–234 (1996). \n49. Jiang, R. et al. Edge-site engineering of atomically dispersed Fe– ${\\bf\\cdot N_{4}}$ by selective C–N bond cleavage for enhanced oxygen reduction reaction activities. J. Am. Chem. Soc. 140, 11594–11598 (2018). \n50. Cao, R. et al. Promotion of oxygen reduction by a bio-inspired tethered iron phthalocyanine carbon nanotube-based catalyst. Nat. Commun. 4, 2076 (2013). \n51. Cheon, J. Y. et al. Graphitic nanoshell/mesoporous carbon nanohybrids as highly efficient and stable bifunctional oxygen electrocatalysts for rechargeable aqueous Na–air batteries. Adv. Energy Mater. 6, 1501794 (2016). \n52. Zhou, J. et al. Fe–N bonding in a carbon nanotube–graphene complex for oxygen reduction: an XAS study. Phys. Chem. Chem. Phys. 16, 15787–15791 (2014). \n53. Cook, P. L., Liu, X., Yang, W. & Himpsel, F. J. X-ray absorption spectroscopy of biomimetic dye molecules for solar cells. J. Chem. Phys. 131, 194701 (2009). \n54. Yang, J. et al. In situ thermal atomization to convert supported nickel nanoparticles into surface-bound nickel single-atom catalysts. Angew. Chem., Int. Ed. 57, 14095–14100 (2018). \n55. Wang, X. et al. Uncoordinated amine groups of metal–organic frameworks to anchor single Ru sites as chemoselective catalysts toward the hydrogenation of quinoline. J. Am. Chem. Soc. 139, 9419–9422 (2017). \n56. Li, X. et al. Simultaneous nitrogen doping and reduction of graphene oxide. J. Am. Chem. Soc. 131, 15939–15944 (2009). \n57. Zou, X. et al. Cobalt-embedded nitrogen-rich carbon nanotubes efficiently catalyze hydrogen evolution reaction at all pH values. Angew. Chem., Int. Ed. 53, 4372–4376 (2014). \n58. Wang, H., Maiyalagan, T. & Wang, X. Review on recent progress in nitrogendoped graphene: Synthesis, characterization, and its potential applications. ACS Catal. 2, 781–794 (2012). \n59. Yang, J., Liu, D.-J., Kariuki, N. N. & Chen, L. X. Aligned carbon nanotubes with built-in $\\mathrm{FeN_{4}}$ active sites for electrocatalytic reduction of oxygen. Chem. Commun. 21, 329–331 (2008). \n60. Wu, G. et al. Synthesis–structure–performance correlation for polyaniline–Me–C non-precious metal cathode catalysts for oxygen reduction in fuel cells. J. Mater. Chem. 21, 11392–11405 (2011). \n61. Wu, Z. Y. et al. Characterization of iron oxides by $\\mathbf{x}$ -ray absorption at the oxygen K edgeusing a full multiple-scattering approach. Phys. Rev. B 55, 2570–2577 (1997). \n62. Yan, S. C., Li, Z. S. & Zou, Z. G. Photodegradation performance of $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ fabricated by directly heating melamine. Langmuir 25, 10397–10401 (2009). \n63. Wei, S. et al. Direct observation of noble metal nanoparticles transforming to thermally stable single atoms. Nat. Nanotechnol. 13, 856–861 (2018). \n64. Wu, G., More, K. L., Johnston, C. M. & Zelenay, P. High-performance electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt. Science 332, 443–447 (2011). \n65. Shui, J., Wang, M., Du, F. & Dai, L. N-doped carbon nanomaterials are durable catalysts for oxygen reduction reaction in acidic fuel cells. Sci. Adv. 1, e1400129 (2015). \n66. Wang, Q. et al. Phenylenediamine-based $\\mathrm{FeN}_{\\mathrm{x}}/\\mathrm{C}$ catalyst with high activity for oxygen reduction in acid medium and its active-site probing. J. Am. Chem. Soc. 136, 10882–10885 (2014). \n67. Jiang, W.-J. et al. Understanding the high activity of Fe–N–C electrocatalysts in oxygen reduction: $\\mathrm{Fe}/\\mathrm{Fe}_{3}\\mathrm{C}$ nanoparticles boost the activity of $\\mathrm{Fe-N_{x}}$ . J. Am. Chem. Soc. 138, 3570–3578 (2016). \n68. Chen, Y. et al. Isolated single iron atoms anchored on N-doped porous carbon as an efficient electrocatalyst for the oxygen reduction reaction. Angew. Chem., Int. Ed. 56, 6937–6941 (2017). \n69. Li, Q. et al. Metal–organic framework-derived bamboo-like nitrogen-doped graphene tubes as an active matrix for hybrid oxygen-reduction electrocatalysts. Small 11, 1443–1452 (2015). \n\n# Acknowledgements \n\nThis work was supported by the National Key Project on Basic Research (2015CB932302), National Natural Science Foundation of China (21773263 and 91645123) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB12020100). This research used resources of the Advanced Light Source, which is a DOE Office of Science User Facility under contract no. DE-AC02-05CH11231. Any opinions, findings, conclusions or recommendations expressed in this work are those of the author(s) and do not necessarily reflect the views of the National Natural Science Foundation of China, Strategic Priority Research Program of the Chinese Academy of Sciences. \n\n# Author contributions \n\nL.Z., Y. Z. and J.S.H. conceived the project. L.Z., L.B.H. and C.H. carried out the synthesis, most of the structural characterizations and electrochemical tests. X.Z.L., Q.H.Z. and L.G. performed the HAADF–STEM characterizations and EELS experiments. L.J.Z. analyzed the EXAFS and XANES data. Z.Y.W. carried out DFT calculations. J.W. and W.Y. performed NEXFAS experiments. L.J.W. discussed the results and commented on the paper. L.Z., Y. Z. and J.S.H. cowrote the paper. J.S.H. supervised the project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-09290-y. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1039_c9ee02020a", + "DOI": "10.1039/c9ee02020a", + "DOI Link": "http://dx.doi.org/10.1039/c9ee02020a", + "Relative Dir Path": "mds/10.1039_c9ee02020a", + "Article Title": "The impact of energy alignment and interfacial recombination on the internal and external open-circuit voltage of perovskite solar cells", + "Authors": "Stolterfoht, M; Caprioglio, P; Wolff, CM; Márquez, JA; Nordmann, J; Zhang, SS; Rothhardt, D; Hörmann, U; Amir, Y; Redinger, A; Kegelmann, L; Zu, FS; Albrecht, S; Koch, N; Kirchartz, T; Saliba, M; Unold, T; Neher, D", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "Charge transport layers (CTLs) are key components of diffusion controlled perovskite solar cells, however, they can induce additional non-radiative recombination pathways which limit the open circuit voltage (V-OC) of the cell. In order to realize the full thermodynamic potential of the perovskite absorber, both the electron and hole transport layer (ETL/HTL) need to be as selective as possible. By measuring the photoluminescence yield of perovskite/CTL heterojunctions, we quantify the non-radiative interfacial recombination currents in pin- and nip-type cells including high efficiency devices (21.4%). Our study comprises a wide range of commonly used CTLs, including various hole-transporting polymers, spiro-OMeTAD, metal oxides and fullerenes. We find that all studied CTLs limit the V-OC by inducing an additional non-radiative recombination current that is in most cases substantially larger than the loss in the neat perovskite and that the least-selective interface sets the upper limit for the V-OC of the device. Importantly, the V-OC equals the internal quasi-Fermi level splitting (QFLS) in the absorber layer only in high efficiency cells, while in poor performing devices, the V-OC is substantially lower than the QFLS. Using ultraviolet photoelectron spectroscopy and differential charging capacitance experiments we show that this is due to an energy level mis-alignment at the p-interface. The findings are corroborated by rigorous device simulations which outline important considerations to maximize the V-OC. This work highlights that the challenge to suppress non-radiative recombination losses in perovskite cells on their way to the radiative limit lies in proper energy level alignment and in suppression of defect recombination at the interfaces.", + "Times Cited, WoS Core": 704, + "Times Cited, All Databases": 726, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000486019600011", + "Markdown": "# Energy & Environmental Science \n\n![](images/225dbf5d9e0b11bd14085aae21ec28c8a11d2218d8579ab4ba25aea4dd26aee6.jpg) \n\nAccepted Manuscript \n\nThis article can be cited before page numbers have been issued, to do this please use: M. Stolterfoht, P. Caprioglio, C. M. Wolff, J. A. Márquez Prieto, J. Nordmann, S. Zhang, D. Rothhardt, U. Hörmann, Y. Amir, A. Redinger, L. Kegelmann, F. Zu, S. Albrecht, N. Koch, T. Kirchartz, M. Saliba, T. Unold and D. Neher, Energy Environ. Sci., 2019, DOI: 10.1039/C9EE02020A. \n\n![](images/ab4fe1141543a757e845f8befd7fa9e756ccbb133365a1af9b09673fd7d0b822.jpg) \n\nThis is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication. \n\nAccepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof reading. Using this free service, authors can make their results available to the community, in citable form, before we publish the edited article. We will replace this Accepted Manuscript with the edited and formatted Advance Article as soon as it is available. \n\nYou can find more information about Accepted Manuscripts in the Information for Authors. \n\nPlease note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. \n\n# The impact of energy alignment and interfacial recombination on the open-circuit voltage of perovskiteViseowlAartricle Online DOI: 10.1039/C9EE02020A cells \n\nMartin Stolterfoht1,\\*, Pietro Caprioglio1,3, Christian M. Wolff1, José A. Márquez2, Joleik Nordmann1, Shanshan Zhang1, Daniel Rothhardt1, Ulrich Hörmann1, Yohai Amir1, Alex Redinger2, Lukas Kegelmann3, Fengshuo $\\mathsf{Z u}^{4,5}$ , Steve Albrecht3, Norbert Koch4,5, Thomas Kirchartz6, Michael Saliba7, Thomas Unold2,\\*, Dieter Neher1,\\* \n\n1Institute of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 PotsdamGolm, Germany. \n\n2Department of Structure and Dynamics of Energy Materials, Helmholtz-Zentrum-Berlin, Hahn-Meitner-Platz 1, D-14109 Berlin, Germany \n\n3Young Investigator Group Perovskite Tandem Solar Cells, Helmholtz-Zentrum Berlin für Materialien und Energie GmbH, Kekuléstraße 5, 12489 Berlin, Germany \n\n4Helmholtz-Zentrum Berlin für Materialien und Energie GmbH, 12489 Berlin, Germany \n\n5Institut für Physik & IRIS Adlershof, Humboldt-Universitat zu Berlin, 12489 Berlin, Germany \n\n6Institut für Energie- und Klimaforschung, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany \n\n7Soft Matter Physics, Adolphe Merkle Institute, CH-1700 Fribourg, Switzerland \n\nE-mail: stolterf@uni-potsdam.de, unold@helmholtz-berlin.de, neher@uni-potsdam.de \n\n# Abstract \n\nCharge transport layers (CTLs) are key components of diffusion controlled perovskite solar cells, however, they can induce additional non-radiative recombination pathways which limit the open circuit voltage $(V_{0\\mathrm{C}})$ of the cell. In order to realize the full thermodynamic potential of the perovskite absorber, both the electron and hole transport layer (ETL/HTL) need to be as selective as possible. By measuring the photoluminescence of perovskite/CTL heterojunctions, we quantify the non-radiative interfacial recombination currents in pin- and niptype cells including high efficiency devices $(21.4\\%)$ . Our study comprises a wide range of commonly used CTLs, including various hole-transporting polymers, Spiro-OMeTAD, metal oxides and fullerenes. We find that all studied CTLs limit the $V_{0\\mathrm{C}}$ by inducing an additional non-radiative recombination current that is in most cases substantially larger than the loss in the neat perovskite and that the least-selective interface sets the upper limit for the $V_{\\mathrm{0C}}$ of the device. Importantly, the $V_{\\mathrm{0C}}$ equals the internal quasi-Fermi level splitting (QFLS) in the absorber layer only in high efficiency cells while in poor performing devices, the $V_{\\mathrm{0C}}$ is substantially lower than the QFLS. Using ultraviolet photoelectron spectroscopy and differential charging experiments we show that this is due to an energy level mis-alignment at the $p$ -interface. The findings are corroborated by rigorous device simulations which outline several important considerations to maximize the $V_{\\mathrm{0C}}$ . This work highlights that the challenge to suppress non-radiative recombination losses in perovskite cells on their way to the radiative limit lies in proper energy level alignment and in suppression of defect recombination at the interfaces. \n\n# Broader context \n\nAs perovskite solar cells continue to improve at a rapid pace, more fundamental insights into the remaining opencircuit voltage $(V_{\\mathrm{{oc}}})$ losses are required in order to unlock power conversion efficiencies (PCEs) of $\\sim30\\%$ . Several studies highlight that the perovskite absorber exhibits an opto-electronic quality that is comparable to GaAs in terms of external fluorescence, therefore potentially allowing PCEs close to the radiative limits. However, the high internal potential in the absorber layer can often not be directly translated into an equal potential at the metal electrodes. In this work, we reveal the reasons for the discrepancy by decoupling the main $V_{\\mathsf{O C}}$ losses in the bulk, perovskite/charge transport layer (CTL) interfaces and/or metal contacts for a broad range of different perovskite compositions and several, commonly used CTLs. Undoubtedly, by introducing additional non-radiative recombination centres at the interfaces, the CTLs have the most striking impact on the device VOC. MoreVioewveArt,icle Online DOI: 10.1039/C9EE02020A interface recombination is often exponentially increased in case of an energy level mismatch between the perovskite and the CTLs. We conclude that energy level matching is of primary importance to achieve the implied $V_{\\mathrm{{oc}}}$ of the perovskite/CTL stack, followed by suppression of defect recombination at the interfaces and in the absorber layer. \n\n# Introduction \n\nHuge endeavours are devoted to understanding and improving the performance of perovskite solar cells, which continue to develop at a rapid pace already outperforming other conventional thin-film technologies on small cells $(<\\mathsf{1c m}^{2})$ .1 It is well established that further improvements will require suppression of non-radiative recombination losses to reach the full thermodynamic potential in terms of open-circuit voltage $(V_{\\mathrm{{0C}}})$ and fill factor (FF).2 As such, a major focus of the entire field to push the technology forward is targeted at reducing defect recombination in the perovskite bulk with numerous works highlighting the importance of grain boundaries in determining the efficiency losses.3,4 In contrast, many other studies highlight the significance of traps at the perovskite surface which is likely chemically distinct from the bulk.4–6 In many cases, performance improvements were achieved by mixing additives into the precursor solution including multiple cations and/or halides.6–9 In many studies, a slower transient photoluminescence (TRPL) decay is shown as the figure of merit to prove the suppressed trap-assisted recombination in the bulk while implying its positive impact on the overall device efficiency.3,6,10 Significantly fewer publications have focused on the importance of non-radiative recombination of charges across the perovskite/CTL interface.11–13 Until recently it has been challenging to pinpoint the origin of these free energy losses in complete cells, although there have been some studies with valuable insight.11–15 Methods that have been employed to study interfacial recombination in perovskite stacks include impedance spectroscopy,11,16 transient photoluminescence (TRPL)13,17,18 or reflection spectroscopy (TRS),14 transient microwave conductivity (TRMC),15 transient photovoltage (TPV).19 Whilst these techniques exhibit in principle the required time resolution to unveil the kinetics of the interface and bulk recombination, the interpretation of these transient measurements can be very challenging. The reasons are related to the inherent fact that extraction and recombination can both reduce the emitting species in the bulk, thus causing the signal decay.2 Previously, a more direct approach to decouple the origin of these recombination losses at each individual interface has been introduced based on steady-state photoluminescence measurements.9,20–25 In particular, measurements of the emitted photoluminescence quantum yield (PLQY) on individual perovskite/transport layer junctions have been used to explain the $V_{\\mathrm{0C}}$ through QFLS losses in the perovskite bulk and at the individual interfaces.9,20,21 However, the relation between the internal QFLS and the external $V_{\\mathrm{0C}}$ remains poorly understood today, especially for different solar cells architectures with different perovskite absorbers and/or charge transport layers. For example, in a recent study, a very high external PLQY $(15\\%)$ has been reported on a nip-stack (i.e. an electron transport layer/perovskite/hole transport layer junction) upon grain boundary passivation using potassium iodide.9 Considering, the provided external quantum efficiency (EQE), this high PLQY translates in an internal QFLS of ${\\sim}1.26\\ \\mathsf{e V}$ which is very close to the radiative limit of the given perovskite absorber layer $(\\sim1.31\\ \\mathsf{e V})$ . Yet, the $V_{\\mathrm{{oc}}}$ of the optimized cells was considerably lower (1.17 V). This suggests that interfacial recombination (which impacts the QFLS of the nip-stack) is not causing the primary $V_{\\mathrm{0C}}$ limitation and suggests that losses of ${\\sim}100~\\mathrm{mv}$ are of different nature. This raises the important question whether the external $V_{\\mathrm{0C}}$ as measured on a complete solar cell truly represents the QFLS in the perovskite bulk and how this depends on the strength of interfacial defect recombination or the energy level alignment between the perovskite and the transport layers. Until today, the importance and impact of energy level alignment remains an important, yet heavily debated topic in perovskite solar cells. For example, several studies showed the benefit or a large impact of energy level alignment between the perovskite and the transport layers,13,26–28 which was however challenged in other works.29 \n\nIn this work, we studied the relation between the QFLS and the $V_{\\mathsf{O C}}$ by means of absolute PL measurements in “regular” (nip-type)7,30,31 and “inverted” (pin-type)32–34 perovskite solar cells for a broad range of CTLs including metal oxides, conjugated polymers,6,35 small molecules, and fullerenes. First, we aim to compare the selectivity of CTLs used for nip and pin configurations in triple cation perovskite cells; i.e. for instance $\\mathsf{T i O}_{2}$ or $\\mathsf{S n O}_{2}$ vs. PTAA underneath the perovskite or doped Spiro-OMeTAD vs. ${\\sf C}_{60}$ on top. We note that in this work we define the selectivity of a CTL as its ability to maintain the QFLS of the absorber layer while providing efficient maVjieowr iAtrtyicle Online \n\nDOI: 10.1039/C9EE carrier extraction. The results suggest that when attached to the perovskite, all studied CTL cause a reduction of the QFLS with respect to the QFLS of the neat perovskite on a fused silica substrate $\\left(1.23\\mathrm{eV}\\right)$ . The results were also generalized to different perovskite absorber layers. A comparison of the QFLS obtained on CTL/perovskite (or perovskite/CTL) bilayers and nip- or pin-stacks, suggests a simple superposition principle of non-radiative recombination currents at each individual interface. This implies that the inferior interface dominates the free energy loss in the complete cell. In efficient cells, where the QFLS matches the device $V_{\\mathrm{OC}},$ we can further estimate the parallel recombination currents in the bulk, interfaces and/or metal contacts under $V_{\\mathrm{{oc}}}$ conditions. However, in poor performing cells we find that the $V_{\\mathrm{0C}}$ is substantially lower than the corresponding QFLS of the pin-stack. Drift diffusion simulations highlight the impact of energy level offsets in causing the mismatch between the internal QFLS and the external $V_{\\mathrm{0C}}$ which we further confirmed using photoemission spectroscopy (UPS) and transient differential charging capacitance experiments. The results underline that the primary non-radiative recombination loss channel of today´s perovskite cells is interfacial recombination at (or across) the perovskite/CTL interface and that interfacial recombination is often exponentially increased in case of an energy level offset between the perovskite and the TLs. As such, our findings highlight the importance of tailoring the energetics and kinetics at the perovskite/CTL interfaces to harvest the full potential in perovskite solar cells. \n\n# Materials \n\nThe studied CTLs in this work belong to 3 material classes, conjugated polymers, small molecules and metal oxides. Regarding the conjugated polymers, we studied highly selective wide-band gap donors such as PolyTPD and PTAA.6,35 Poly({9,9-bis[30-({N,N-dimethyl}- $.N-$ -ethylammonium)-propyl]-2,7-fluorene}-alt-2,7-{9,9-di-noctylfluorene})dibromide (PFN) was added on top of both materials to improve the wettability. In order to draw correlations between the QFLS and the energetics of the HTL, we also investigated P3HT,36,37 as well as highly conductive composite PEDOT:PSS.12 As small molecule HTL, we tested Spiro-OMeTAD38,39 which requires doping by different ionic salts and other additives.39 For the case of small molecule ETLs, we tested the fullerene ${\\sf C}_{60}$ (with and without the interlayer LiF20) and the solution-processable fullerene derivative PCBM.34,40 Lastly, we studied the commonly used transparent metal oxides $\\mathsf{T i O}_{2}$ and $\\mathsf{S n O}_{2}$ . $\\mathsf{T i O}_{2}$ is widely considered as an ideal electron transporting layer due to its high selectivity and high charge carrier mobility,41 while $\\mathsf{S n O}_{2}$ is the preferred platform for planar efficient nip cells.11 These chemical structures of the materials are shown in Figure 1. As absorber layer we chose the so-called triple cation perovskite $(\\mathsf{C s P b l}_{3})_{0.05}[(\\mathsf{F A P b l}_{3})_{0.83}(\\mathsf{M A P b B r}_{3})_{0.17}]_{0.95}$ (see Supplementary Methods),8 while the results were extended to other perovskite systems as discussed below. \n\n# Comparison of CTLs for pin and nip type devices \n\nIn order to quantify the free energy losses at the CTL/perovskite interface, we measured the absolute photoluminescence (PL) yield of perovskite/transport layer heterojunctions. The absolute PL is a direct measure of the quasi-Fermi level splitting (QFLS or $\\mu$ ) in the absorber,24,42–45 and this approach has been recently applied to perovskite solar cells by various groups.20–23 The ratio of emitted $(\\phi_{\\mathrm{em}})$ and absorbed photon fluxes $(\\phi_{\\mathrm{abs}})$ defines the absolute external PL quantum yield (PLQY): \n\n$$\n\\mathrm{PLQY}={\\frac{\\phi_{\\mathrm{em}}}{\\phi_{\\mathrm{abs}}}}={\\frac{J_{\\mathrm{rad}}/e}{J_{\\mathrm{G}}/e}}={\\frac{J_{\\mathrm{rad}}}{J_{\\mathrm{R,tot}}}}={\\frac{J_{\\mathrm{rad}}}{J_{\\mathrm{rad}}+J_{\\mathrm{non}-\\mathrm{rad}}}}={\\frac{J_{\\mathrm{rad}}}{J_{\\mathrm{rad}}+J_{\\mathrm{B}}+J_{\\mathrm{p}-\\mathrm{i}}+J_{\\mathrm{i-n}}+\\ ...}}\n$$ \n\nIf all emission is from the direct recombination of free charges, and also every absorbed photon generates a free electron-hole pair, the PLQY equals the ratio of the radiative recombination current density $U_{\\mathrm{rad}})^{42}$ and the total free charge generation current density $\\left({J_{\\mathrm{G}}}\\right)$ . At $V_{\\mathrm{0C}},$ charge extraction is zero, meaning that $J_{\\mathrm{G}}$ is equal to the total recombination current $U_{\\mathrm{R,tot}})$ of radiative and non-radiative losses $(J_{\\mathrm{rad}}+J_{\\mathrm{non-rad}})$ . Furthermore, $J_{\\mathrm{non-rad}}$ is equal to the sum of all non-radiative recombination pathways in the bulk $\\left(J_{\\mathrm{B}}\\right)$ , at the HTL/perovskite $(J_{\\mathrm{p-i}})$ and perovskite/ETL $U_{\\mathrm{i-n}})$ interfaces, and potentially other losses (e.g. recombination in the transport layers, or at the CTL/metal interfaces). Using the expression for the radiative recombination current density according to Shockley-Queisser42 and Equation 1, we can write the QFLS as a function of the radiative efficiency \n\n𝐽rad \n\n$$\n{\\begin{array}{r l}&{=J_{\\mathrm{0,rad}}e^{\\mu/k T}\\to\\mu=k T\\ln\\left({\\frac{J_{\\mathrm{rad}}}{J_{\\mathrm{0,rad}}}}\\right)=k T\\ln\\left(\\operatorname{PLQY}{\\frac{J_{\\mathrm{G}}}{J_{\\mathrm{0,rad}}}}\\right)=k T\\ln\\left({\\frac{J_{\\mathrm{G}}}{J_{\\mathrm{0}}}}\\right)=k T}\\\\ &{\\ln\\left({\\frac{J_{\\mathrm{rad}}}{J_{\\mathrm{rad}}+J_{\\mathrm{B}}+J_{\\mathrm{p-i}}+J_{\\mathrm{i-n}}+\\ldots..J_{\\mathrm{0,rad}}}}\\right)}\\end{array}}\n$$ \n\nwhere $J_{\\mathrm{0,rad}}$ is the radiative thermal equilibrium recombination current density in the dark and $J_{0}=J_{0,\\mathrm{rad}}/\\mathrm{PLQY}$ the dark saturation current. We note, that the PLQY depends itself on external conditions such as the illumination intensity or the internal QFLS. This originates from the fact that the non-radiative recombination pathways depend differently on the actual number of charge pairs present in the device compared to radiative recombination.46 Thus, in order to predict the QFLS under 1 sun and open-circuit, the PLQY needs to be measured under the same illumination conditions. Equation 2 also shows that the QFLS depends logarithmically on the non-radiative recombination currents in the bulk, interface etc. In order to quantify the QFLS, the generated current density under illumination $\\left({J_{\\mathrm{G}}}\\right)$ and $J_{\\mathrm{0,rad}}$ need to be known, as well as the thermal energy (we measured a temperature of ${\\sim}26{\\cdot}28^{\\circ}C$ on the sample under 1 sun equivalent illumination using a digital standard infrared sensor). $J_{\\mathrm{G}}$ and $J_{\\mathrm{0,rad}}$ are obtained from the product of the external quantum efficiency (EQE) and the solar $(\\phi_{\\mathrm{sun}})$ and the 300 K - black body spectrum $(\\phi_{\\mathrm{BB}})$ , respectively.42,43,47,48 As such, we obtained a $J_{\\mathrm{0,rad}}$ of $\\sim6.5{\\times}10^{-21}\\mathsf{A}/\\mathsf{m}^{2}$ $(\\pm1\\mathrm{x}10^{-21}\\mathsf{A}/\\mathsf{m}^{2})$ independent of the bottom CTL (Supplementary Figure S1) as it is predominantly determined by the tail absorption of the triple cation perovskite absorber layer (with Urbach energies around $15\\ \\mathsf{m e V})$ . In all cases, the QFLS was measured by illuminating the films through the perovskite (or the transparent layer in case of pin or nip stacks) in order to avoid parasitic absorption of the studied CTL (and $\\phi_{\\mathrm{abs}}$ doesn’t equal $\\boldsymbol{J_{\\mathrm{G}}}/e$ anymore, see Supplementary Figure S2). The results of the PL measurements of the different transport layers are summarized in Table 1 and plotted in Figure 1b. All results were obtained as an average of multiple fabricated films (Supplementary Figure S3) with representative PL spectra shown in Supplementary Figure S4. Details of the measurements conditions are discussed in Supplementary Methods. \n\nTable 1. Optoelectronic quality of several tested perovskite-CTL layer junctions. \n\n\n
FilmAbsorptionPLQYJo, nr [Am-2]QFLS [eV]
ITO/Pero0.8392.0x10-53.5×10-161.060
PEDOT:PSS/Pero0.8547.5x10-59.9x10-171.092
P3HT/Pero0.8487.7x10-41.0x10-171.152
Pero/Spiro-OMeTAD0.9441.4x10-34.6x10-181.172
PTAA/PFN/Pero0.8525.1x10-31.3x10-181.204
PolyTPD/PFN/Pero0.8517.3x10-31.1x10-181.208
Pero0.8501.4x10-24.6x10-191.231
SnO2/Pero0.8545.9x10-31.5×10-181.201
TiO2/Pero0.8542.1x10-33.2x10-181.181
Pero/PCBM0.9345.7x10-41.3x10-171.145
Pero/C600.9273.8x10-41.8×10-171.137
Pero/LiF/C600.8921.3x10-34.9x10-181.170
\n\n![](images/6cc114da7bfe908eb5b4a2c60b391815155345c907b5801542d81f12fd942178.jpg) \nFigure 1. The optoelectronic quality of triple cation perovskite/CTL layer junctions. (a) Materials studied in this paper. (b) The calculated quasi-Fermi level splitting of the studied heterojunctions with different hole and electron transporting materials and of the neat absorber layer based on equation 2 using absolute photoluminescence measurements. The absorber was spin casted from the same solution for all transport layers. The non-radiative dark saturation current is plotted on the right and was obtained from $J_{\\mathrm{0,nr}}=J_{0}-J_{0,\\mathrm{rad}}$ which allows comparing the strength of non-radiative recombination of different junctions. \n\nFigure 1b shows that the triple cation perovskite on a fused silica substrate limits the QFLS to approximately 1.231 eV, which is ${\\sim}110$ meV below the radiative $V_{\\mathrm{0C}}$ limit (where the PLQY equals 1). We note that we cannot rule out that this value is limited by recombination at the fused silica/perovskite interface and that we observe a substantially lower QFLS $({\\sim}40\\mathsf{m e V})$ of the bare perovskite layer on a glass substrate (see Supplementary Figure S5). Moreover, significantly higher PLQY values above $20\\%$ were observed on methylammonium lead triiodide films where the top surface was passivated with tri-n-octylphosphine oxide (TOPO).49 These results highlight the high opto-electronic quality of the perovskite bulk comparable (or already better) than highly pure silicon or GaAs but also indicates substantial recombination losses at the perovskite top surface. For the HTL/perovskite junctions we also tested the influence of the underlying ITO layer, however this did not significantly influence the obtained QFLS within a small error except for samples with $\\mathsf{S n O}_{2}$ (see Supplementary Figure S3). Likewise, we tested the influence of the copper metal electrode on top of the ${\\sf C}_{60}$ in perovskite/ $\\mathsf{^{\\prime}C}_{60}$ heterojunctions and of pin stacks (Supplementary Figure S6). Overall, these tests suggest that there is an essentially lossless charge transfer between the metal electrodes and the HTL. Interestingly, Figure 1b shows that the polymers PTAA/PFN and PolyTPD/PFN performed best - even outperforming the omnipresent Spiro-OMeTAD. However, it is clear that the selectivity of a TL can be different underneath or on top of the perovskite. Therefore, we do not aim to quantify the opto-electronic quality of a CTL itself but rather assess the selectivity of the CTL in a particular configuration (i.e. either on top or underneath a particular perovskite layer). Among the studied ETLs, $\\mathsf{S n O}_{2}$ and $\\mathsf{T i O}_{2}$ outperform the organic ETLs ${\\sf C}_{60}$ and PCBM which are usually used in pin-type cells. Therefore, this data suggests that the $p$ -interface is the limiting interface for nip cells, and the $\\boldsymbol{n}$ -interface for pin cells consistent with earlier studies.21 Moreover, we observe that the capping CTLs PCBM and ${\\sf C}_{60}$ are worse than Spiro-OMeTAD. Considering that the inferior interface will dominate the final $V_{\\mathrm{0C}}$ (equation 1 and 2), this might be one reason for the superior performance of nip cells today. One approach to suppress non-radiative recombination at the perovskite/ $\\mathsf{\\Delta C}_{60}$ interface is to insert a thin LiF interlayer as demonstrated earlier20 and in Table 1. \n\nA frequently arising question is how much the perovskite morphology, which potentially varies depending on the underlying CTL, could influence the obtained QFLS and the interpretation of the results. Thus, we performed top scanning electron microscopy and AFM measurements (see Supplementary Figure S7). Interestingly, we find the largest grains on a PEDOT:PSS bottom CTL despite it being the worst among the studied transport layers. The largest grain size distribution is visible on perovskite films on $\\mathsf{T i O}_{2}$ while the perovskite morphology on all other substrates appears, at least qualitatively, similar where we observe relatively small grains $(<10-100\\ \\mathsf{n m})$ . In addition, AFM measurements reveal root mean square surface roughnesses varying from $12-27{\\mathsf{n m}}$ , where the perovskite on PolyTPD/PFN and PTAA/PFN appears to be roughest $(>20\\mathsf{n m})$ while the perovskite film on TVieOw2Airtsicle DOI: 10.1039/C9EE0 the smoothest. We also note the similar Urbach tail of the perovskite absorber layer when processed on different CTLs (Supplementary Figure S1) which is related to the density of subgap states. This further indicates a similar opto-electronic quality of the perovskite. Considering these results, it seems unlikely that the perovskite bulk morphology can explain the changes in the non-radiative recombination loss currents which increase by orders of magnitude depending on the underlying substrate (as shown in Figure 1b). It is also worth to note that these results do not allow distinguishing whether the critical recombination loss occurs across the perovskite/CTL interface, or at the perovskite surface next to the interface. In any case, the presence of the additional CTL triggers additional (non-radiative) interfacial recombination losses, which are dominating the non-radiative recombination losses. \n\n# Comparison of the QFLS and device $\\pmb{V_{0\\mathrm{c}}}$ and origin of free energy losses \n\nIn the following, we aim to compare the non-radiative recombination losses at the $p$ - and $\\boldsymbol{n}$ -interfaces with the QLFS of the pin stacks and the $V_{\\mathrm{0C}}$ of the complete cells with different HTLs and $(\\mathsf{L}|\\mathsf{F}/)\\mathsf{C}_{60}$ as ETL. Figure 2a shows that the device $V_{\\mathrm{0C}}$ (black line) generally increases with the average QFLS of the pin-stack (orange line) which was taken as an average as obtained on 3-4 samples for each configuration. Importantly, for optimized cells with PolyTPD or PTAA, the $V_{\\mathrm{0C}}$ (black line) matches the QFLS of the stack (orange line) within a small error. This is also nearly identical to the QFLS of the less selective perovskite $1C_{60}$ interface (blue line). This indicates that for these particular cells, the losses determining the $V_{\\mathrm{0C}}$ occur almost entirely at the inferior interface to the perovskite while the electrodes are not causing additional $V_{\\mathrm{0C}}$ losses. On the other hand, in case of the less selective PEDOT:PSS and P3HT bottom layers, the $V_{\\mathrm{0C}}$ was found to be substantially lower than the corresponding QFLS. This will be discussed further below. The current density vs. voltage $(J V)$ characteristics of the corresponding to cells are shown in Figure 2b which highlight the large differences in the measured $V_{0\\mathrm{C}^{\\mathsf{S}}}$ . Device statistics of individually measured stacks are shown in Supplementary Figure S9. We note that our devices with LiF $1C_{60}$ as ETL reach efficiencies of up to $21.4\\%$ with a $V_{\\mathrm{0C}}$ of ${\\sim}1.2\\lor$ (for a triple cation perovskite with a bandgap of ${\\sim}1.6$ eV), which is among the highest reported values for pin-type cells (Supplementary Figure S10).50–52 \n\nNext, we compared the PLQY with the external electroluminescence quantum efficiency $(E Q E_{\\mathrm{EL}})$ as shown in Figure 2c. Under conditions where the dark injection current equals the generation current, the $E Q E_{\\mathrm{EL}}$ of PTAA and PolyTPD cells ( $3{\\times}10^{-4}$ for both devices) approaches the PLQY of the stack within a factor of two $(5.9{\\times}10^{-4}$ for PTAA and $4.6{\\times}10^{-4}$ for PolyTPD). Improving the perovskite/ETL interface by inserting LiF increases both the QFLS of the pin stack and the $V_{\\mathrm{0C}}$ to 1.17 V corresponding to a PLQY of ${\\sim}1.3{\\times}10^{-3}$ and $E Q E_{\\mathrm{EL}}$ of ${\\sim}8.3{\\times}10^{-4}$ .20 However, for devices with PEDOT:PSS, the $E Q E_{\\mathrm{EL}}(\\sim1.4{\\times}10^{-8})$ is orders of magnitude lower than the PLQY of the stack $(\\sim$ $\\scriptstyle1\\times10^{-5})$ . We note that the measured $E Q E_{\\mathrm{EL}}$ matches roughly the expected $E Q E_{\\mathrm{EL}}$ value for a $V_{\\mathrm{0C}}$ of $0.9\\mathrm{\\:V}$ as obtained from the $J V$ scan $(3.8\\times10^{-8})$ . Therefore, we conclude that the inferior interface (PEDOT:PSS/perovskite) limits the QFLS of the stack, however, there is an additional loss which affects the $V_{\\mathrm{0C}}$ but not the QFLS. This will be addressed further below. Lastly, films with P3HT lie somewhat in between PEDOT:PSS and PTAA (PolyTPD) devices. Here, both interfaces (P3HT/perovskite and perovskite $/{\\mathsf C}_{60}]$ appear to be equally limiting the QFLS of the stack which also lies below the QFLS of the individual heterojunctions (bilayers). Similar to PEDOT:PSS devices, we observe a considerable mismatch between PLQY of the optical pin stack $(6.2\\times10^{-5})$ and the $E Q E_{\\mathrm{EL}}(\\sim9{\\times}10^{-7})$ . We note that the measure $E Q E_{\\mathrm{EL}}$ is again very close to the $E Q E_{\\mathrm{EL}}$ that is expected for a P3HT device with a $V_{\\mathrm{0C}}$ of ${\\sim}1.0$ V $(\\sim1.8{\\times}10^{-6})$ . \n\n![](images/7fa9302ed9826007b1f4a4a9e54b7a37609437036f2afb5f8a371e2d297c7c59.jpg) \nFigure 2. Open-circuit voltage, quasi-Fermi level splitting and electroluminescence of pin cells. (a) Average $V_{\\mathrm{0C}}$ of pin cells employing different conjugated polymers as HTLs and a $C_{60}{E T L},$ , compared to the average QFLS of the corresponding HTL/perovskite bilayers (red), and of the pin stacks (orange). The QFLS of the perovskite/C60 junction and of the neat perovskite on fused silica are shown in dashed blue and black lines, respectively. The dark saturation current $(J_{0,n r}=J_{0}-J_{0,r a d})$ as plotted on the right allows to compare the strength of non-radiative recombination of different junctions. (b) Corresponding current density vs. voltage characteristics of the pin cells with different HTLs, and (c) the external electroluminescence efficiency as a function of voltage. The dashed line shows conditions where the dark injection and light generation currents are equal for each device. \n\nAs for the nip-cells with $\\mathsf{S n O}_{2}$ and $\\mathsf{T i O}_{2}$ as the ETL, and SpiroOMeTAD as the HTL, we observe a similar trend as in our optimized pin-type cells with PTAA or PolyTPD, that is a close match between the average device $V_{\\mathrm{0C}}\\left(\\sim1.15\\right.$ V) and the average internal QFLS (1.161 eV and $\\mathtt{1.168\\ e V}$ for $\\mathsf{T i O}_{2}$ and $\\mathsf{S n O}_{2}$ based cells, respectively) under 1 sun conditions. All results obtained on nip-cells are shown in Supplementary Figure S11. Regarding the potential impact of the perovskite morphology when the samples are prepared on different hole (electron) transport layers, it is important to note that the losses in the neat material (dashed black in Figure 2a) cannot be larger than the cumulative losses observed in the CTL/perovskite bilayers (red). Moreover, the match between the QFLS of the glass/perovskite/CTL bilayers (blue) and the pin or nip stacks (Figure 2a and Supplementary Figure S11) means that the recombination at the top CTL interface can consistently explain the overall $V_{\\mathrm{{oc}}}$ regardless, if the perovskite is deposited on glass or on the CTL (PTAA:PFN, PolyTPD:PFN, ${\\mathsf{T i O}}_{2},$ $\\mathsf{S n O}_{2}\\vert$ . This highlightVsiewt hArteicle Online I: 10. 039/C9EE02020A importance of the top interface in determining the non-radiative recombination current in perovskite solar cells. \n\n# Quantification of parallel recombination currents at $\\mathtt{v_{o c}}$ \n\nThe absolute-PL approach allows to further estimate the parallel recombination currents at $V_{\\mathsf{O C}}$ . To this end, we successively quantify the non-radiative recombination currents in the neat material and the bottom and top interfaces from the PLQY of the corresponding perovskite/CTL films (Equation 1) and knowledge of $J_{\\mathrm{rad}}$ (Equation 2). Important to note is that the PLQY needs to be known at the $V_{\\mathrm{0C}}$ of the complete cell. Moreover, the individual recombination currents must add up to $J_{\\mathrm{G}}$ which allows to the check the consistency of the approach. This is possible in efficient cells where the QFLS in the absorber layer matches the device $e V_{O C}$ within a relatively small error $(\\approx20\\mathrm{\\meV})$ , but the procedure is prone to fail in cells where ${\\mathsf{Q F L S}}>e V_{O C}$ . Figure 3a shows the obtained recombination currents for efficient pin-type and nip-type cells. Figure 3b illustrates our optimized pin cells with $\\mathsf{L I F/C}_{60}$ as ETL at $V_{\\mathrm{{oc}}}$ by a bucket with holes which represent the recombination losses (see caption). We note again that the recombination current in the neat perovskite (green) is obtained from a film on fused silica and therefore the loss in the neat absorber layer might be slightly different when deposited on top of a CTL. However, as we detail throughout the manuscript, changes in the perovskite morphology when deposited on different CTL cannot explain the $\\mathsf{v}_{\\mathsf{o c}}$ of the final cells, and the fact that the recombination currents add up to $J_{\\mathrm{G}}$ suggests that this loss estimation provides a realistic description of the parallel recombination currents at $V_{\\mathrm{{OC}}}$ . \n\n![](images/7399b1a53aa7440a42541c2368b785e6f7fc0c25dcad75abd76a990355200676.jpg) \nFigure 3. (a) Bulk and Interfacial recombination currents at open-circuit as obtained on nip and pin type cells with nearly flat quasi-Fermi levels. In pin type cells, the non-radiative recombination current is dominated by the $C_{60}$ interface (blue) – even if optimized with LiF. In nip-type cells, the recombination at the upper perovskite/Spirointerface (red) dominates the recombination loss, although the recombination at the $p$ - and $\\boldsymbol{n}$ -interface are quite similar in case of cells based on $\\bar{T i O_{2}}$ . In all cases, the non-radiative recombination losses in the neat perovskite (green) are smaller than at the top interface. We note the radiative recombination current density is very small, e.g. $7.8\\mu A c m^{-2}$ in panel (a). (b) Illustrates a solar cell as bucket with holes where the water level represents the $c e I I s^{\\prime}V_{O C}$ .53 The water stream from the tap corresponds to the generation current density from the sun. The holes in the buck represent the recombination losses at $V_{O C}$ in the bulk, interfaces etc. Depending on the exact size of the holes, the water level will change so as the $V_{O C}$ of the device. \n\n# Understanding the QFLS across the pin (nip) junction \n\nThe experimental results in the previous sections show that $\\mathsf{Q F L S}{\\sim}V_{\\mathrm{0C}}$ in case of good performing transport layers (PTAA and PolyTPD). This indicates that interfacial recombination in these devices lowers the QFLS throughout the whole bulk equally. However, in case of PEDOT:PSS or P3HT, the device $V_{\\mathrm{0C}}$ is lower than the QFLS in the perovskite layer. In such cases, at least one QFL bends, presumably at the interfaces or contacts, causing a further reduction in the electrochemical potential of the photogenerated charges. This bending has a much larger effect on the final $V_{\\mathrm{0C}}$ than on the average QFLS in the perovskite bulk. In order to check whether this phenomenon depends on the charge carrier generation profile, we analysed all samples by illuminating the samples through the bottom glass or top using a 445 nm laser (Supplementary Figure S2) and through intensity and wavelength dependent $V_{\\mathrm{0C}}$ measurements (Supplementary Figure S12). However, we concludedV ietwhAartic DOI: 10.1039/C9EE neither the QFLS nor the $V_{\\mathrm{0C}}$ depend significantly on the charge generation profile, which we attribute to the rapid diffusion of charges through the perovskite. In order to understand the spatial distribution of the recombination losses and the QFLS, we simulated our perovskite solar cells using the well-established driftdiffusion simulator SCAPS.54 These simulations take into account previously measured interface recombination velocities and perovskite bulk lifetimes.20 The simulated electron/hole quasi-Fermi levels $\\cdot E_{\\mathrm{F,e}}$ and ${E}_{\\mathrm{F,h}})$ at opencircuit are shown along with the conduction and valence bands in Figure 4a for a PTAA/PFN/perovskite $1C_{60}$ device. Important simulation parameters listed in Supplementary Table S1. Qualitatively, these simulations confirm that $E_{\\mathrm{F,e}}$ and $E_{\\mathrm{F,h}}$ are spatially flat in the perovskite bulk and extend to the corresponding electrodes which explains that $e V_{\\mathrm{0C}}$ is nearly identical to the QFLS (of ${\\sim}1.13\\mathsf{e V}$ ) in these devices. Interestingly, to reproduce the comparatively high open-circuit voltages $(\\sim1.14\\lor)$ and FFs up to $80\\%$ of these devices, a considerable builtin voltage $(V_{\\mathrm{BI}})$ of at least $\\ensuremath{1.0\\mathrm{~V~}}$ had to be assumed considering realistic interface recombination velocities. Otherwise, a strong backfield would hinder charge extraction in forward bias but also accumulate minority carriers at the wrong contact (Supplementary Figure S13). We note that the role of the $V_{\\mathrm{BI}}$ across the absorber layer is currently an important topic in the community and further efforts need to be taken to properly consider the impact of ions on the field distribution.55 Moreover, we had to assume a small majority carrier band offset (Δ $E_{\\mathrm{maj}}<0.1\\mathrm{eV_{\\iti}}$ ) between the perovskite valance/conduction band and the HOMO/LUMO of the HTL/ETL, respectively in order to reproduce the measured device $V_{\\mathrm{{OC}}}$ . \n\nInterestingly, the implementation of a majority carrier band offset at the $p$ -interface causes a considerable bending of the hole quasi-Fermi level close to the interface which explains the $\\mathsf{\\Omega}\\mathsf{e}F\\mathsf{L S-}V_{\\mathrm{OC}}$ mismatch (Figure 4b). Considering that $E_{\\mathrm{F,e}}$ and $E_{\\mathrm{F,h}}$ need to extend throughout the CTLs to the metal contacts in order to produce an external $V_{\\mathrm{OC}},$ it is clear that any $\\Delta E_{\\mathrm{maj}}$ will cause an exponential increase of the hole population in the HTL. This implies an exponential increase in the recombination rate. Therefore, it is expected that a finite $\\Delta E_{\\mathrm{maj}}$ will lead to an equal loss in the device $V_{\\mathsf{O C}}$ . In order to generalize the conditions under which the $V_{\\mathrm{0C}}$ deviates from the QFLS, we extended our simulations by studying a wide range of parameters (Supplementary Table S1). We found that at least two requirements must be fulfilled in order to explain the $\\mathsf{\\Omega}\\mathsf{e r c l}{\\mathsf{S}}{\\mathsf{-}}V_{\\mathrm{OC}}$ mismatch: (a) a band offset for the majority carrier of at least ${\\sim}0.2\\ \\mathsf{e V}$ , and (b) a sufficiently high recombination velocity $(>1\\mathsf{c m}/\\mathsf{s})$ , otherwise $E_{\\mathrm{F,e}}$ and $E_{\\mathrm{F,h}}$ can remain flat despite the energy offset (Supplementary Figure S14). Indeed, these simulations show that the $V_{\\mathrm{{oc}}}$ loss scales linearly with the $\\Delta E_{\\mathrm{maj}}$ offset as long as the $p$ -interface is limiting. We also note that the minority carrier band offset $\\Delta E_{\\mathrm{min}}$ (i.e. the LUMO of the HTL and the perovskite conduction band) is not influencing the results if $\\Delta E_{\\mathrm{min}}$ is larger than only $0.1\\mathsf{e V}$ which is further discussed at Supplementary Figure S15. We also simulated a pin stack with a PEDOT:PSS bottom layer which we simplified by a metal with a work function of $5\\upepsilon\\upnu$ , a high surface recombination velocity for holes and an intermediate value for electrons (Supplementary Table S1). Also, for these settings we observed that $E_{\\mathrm{F,h}}$ bends at the interface, giving rise to the experimentally observed $\\mathsf{\\Omega}\\mathsf{e r c l}{\\mathsf{S}}{\\mathsf{-}}V_{0\\mathrm{C}}$ mismatch of roughly $150\\mathrm{\\meV}$ in the PEDOT cell. All results on PEDOT:PSS cells are summarized in Supplementary Figure S16. We acknowledge that these simulations only illustrate one possible scenario of the internal device energetics using a set of plausible parameters, and thus different energetic alignments or a morphological issue at the interface cannot be excluded. However, we can conclude that energy level alignment of all layers is a crucial requirement to maximize the $V_{\\mathrm{0C}}$ while the defect density at the interface is also a critical parameter in determining the non-radiative recombination losses. \n\n![](images/e69c8ead174b706150b67fee33847dcf08797a98eaaad090c1fc7f37b573186b.jpg) \nFigure 4. Simulation of the QFLS and $\\pmb{V_{0\\mathrm{c}}}$ of pin-type devices using SCAPS. (a) The simulated quasi-Fermi level splitting (QFLS) in junctions with aligned transport layers (PTAA/perovskite $\\ensuremath{\\langle C_{60}\\rangle}$ is identical to $e V_{\\mathrm{0C}}$ but not in case of energetically mis-aligned transport layers (b) where the hole QFL bends at the interface to the hole transport layer which causes a $\\boldsymbol{Q F L S–V_{O C}}$ mismatch. The perovskite is represented in brown showing unoccupied states in between the conduction band minimum $(E_{\\complement})$ and valence band maximum $(E_{\\mathrm{V}}),$ while the dashed lines show the electron and hole quasi-Fermi levels $\\begin{array}{r}{(E_{\\mathrm{F,e}}a n d E_{\\mathrm{F,h}}),}\\end{array}$ the resulting QFLS in the absorber and the open-circuit voltage $(V_{0\\mathrm{C}})$ at the contacts. The HTL (red) and ETL (blue) are represented by their unoccupied states in between the highest and lowest unoccupied molecular orbitals. \n\n# Energy Level Alignment at the HTL/perovskite interface \n\nThe findings in the previous sections suggest that the observed mismatch between the internal QFLS and the $V_{\\mathrm{0C}}$ in cells comprising PEDOT:PSS and P3HT is due to an energy offset at the $p$ -interface. To study the energy level alignment between the perovskite and the transport layer, we first performed photoelectron yield spectroscopy measurements (PYS) on the individual layers of the solar cells (Supplementary Figure S17). However, these measurements did not allow a reliable prediction of $\\Delta E_{\\mathrm{maj}}$ which is due to the assumption of a constant vacuum level across different layers of the stack. To measure the energetic offsets between the perovskite and the transport layers with respect to the fixed Fermi level $(E_{\\mathsf{F}})$ of the ITO substrate, we performed UPS measurements with background illumination. Recently, it has been shown that the perovskite surface can be considerably ndoped,56 which will directly impact the location of the valence band onset with respect to $\\boldsymbol{E}_{\\mathsf{F}}$ when measuring the top surface of the perovskite film with a He beam (21.1 eV). However, when UPS is performed with an additional background light, the band bending at the surface can be flattened which then allows to access the bulk energy levels. This enabled a direct comparison between the energy levels of the transport layers and the perovskite bulk. Indeed, as shown in Figure 5 below, by properly taking into account the surface photovoltage (SPV) effect, we found that the valance band of the perovskite is aligned with the HOMO of PTAA and PolyTPD HTLs, while P3HT and PEDOT:PSS exhibited states close to, or at the Fermi-edge. Thus, we conclude that PTAA and PolyTPD allow maintaining the high QFLS that is generated from the perovskite upon illumination which is in agreement with the drift diffusion simulations. In contrast, in case of P3HT, and even worse in case of PEDOT:PSS, carriers will lose part of their free energy once they are transferred from the perovskite to the HTL, thereby causing the additional $\\mathsf{V}_{\\mathsf{O C}}$ -loss as numerically predicted and experimentally observed. A further confirmation of this picture comes from the measurement of the charge carrier density in the bulk $(n_{\\mathrm{bulk}})$ at a given $V_{\\mathrm{0C}}$ using differential charging capacitance measurements. $^{57,58}\\left|{\\mathfrak{n}}\\right.$ the case of proper energy alignment, $n_{\\mathrm{bulk}}$ would be a sole function of the $\\mathsf{V}_{\\mathsf{O C}},$ independent of the choice of the TL material. The results in Supplementary Figure S18 show that this is not the case. Instead, for a given $V_{\\mathrm{OC}},{n}_{\\mathrm{bulk}}$ is substantially larger for the PEDOT:PSS cell than for the P3HT and the PTAA cell with proper energy alignment. This is a direct consequence of the energy offset and the resulting \n\n![](images/8b12660c3aeeba3906dbb54bfc4e3f5afab9402f2f38c7a018947f8ee26215cc.jpg) \nFigure 5. (a) Ultraviolet photoelectron (UPS) spectra of PTAA, PolyTPD, P3HT and PEDOT:PSS on ITO. The corresponding signal of the perovskite film is shown above. The perovskite surface is n-doped56 resulting in an apparent valence band onset of $1.35~e V.$ Application of a background light (with a 1 sun equivalent intensity) flattens the band bending at the surface which allows accessing the valence band offset in the perovskite bulk (0.8 eV away from the Fermi level).56 The spectra of PEDOT:PSS is scaled by a factor of 60 as compared to the other films. As discussed by Hwang et al.,59 a high-bandgap PSS layer is present on top of a solution processed film which weakens the photoelectron signal of states at the Fermi-edge of the underlying PEDOT:PSS bulk as shown in several publications.59,60 The deduced energy levels are plotted in (b). As predicted from the $\\boldsymbol{Q F L S–V_{\\mathrm{OC}}}$ match in these cells, in case of PTAA and PolyTPD hole transport layers, the HOMO of the HTL is aligned with respect to the perovskite valence band. However, considerable majority carrier band offsets exist in case of P3HT and PEDOT:PSS. This causes the observed QFLS- $V_{\\mathrm{{OC}}}$ mismatch as carriers relax to the band edges during their transport to the extracting electrode. \n\n# Recombination Losses in other Perovskite Systems \n\nIn order to generalize the findings, we also studied QFLS and $V_{\\mathrm{{OC}}}$ losses in other currently popular perovskite materials (Supplementary Figure S19). The results further confirm our main conclusions: (i) the perovskite bulk usually allows to reach higher $V_{0\\mathrm{C}^{\\mathsf{S}}}$ than ultimately achieved in the cell. This is confirmed in a low-gap triple cation perovskite $(\\sim1.54~\\mathrm{eV})$ which is currently used in the highest efficiency solar cells,1 a hybrid vacuum/solution processed $\\mathsf{M A P b l}_{3}$ $(\\sim1.6\\ \\mathsf{e V})$ which is relevant for application on textured surfaces in tandem solar cells,61,62 a high-gap mixed perovskite with a bandgap of $1.7~\\mathsf{e V}$ which is the ideal bandgap for monolithic Si/perovskite tandem solar cells, as well as two-dimensional perovskites based on $\\boldsymbol{n}$ -butylammonium63 - a popular system which demonstrates increased stability under thermal and environmental stress.64 However, in some cases the QFLS of the optical stack is close to the QFLS of the neat absorber layer, e.g. for a solution processed CsFAPbI3 (\\~ $1.47\\ \\mathrm{eV})$ and $\\mathsf{M A P b l}_{3}$ $(\\sim1.6\\ \\mathsf{e V})$ . (ii) In most cases, the QFLS-PL technique can well describe the $V_{\\mathrm{0C}}$ of the final cell which allows to assess the inferior interface by comparing the QFLS of HTL/perovskite or perovskite/ELT junctions. However, in a high-bandgap $(\\sim1.7\\ \\mathrm{eV})$ mixed perovskite system we observe again a considerable mismatch between the QFLS of the pin-stack and the $V_{\\mathrm{{OC}}}$ . This highlights the difficulties in increasing the perovskite bandgap while maintaining aligned energy levels and further demonstrates the relevance of our findings for other perovskite systems. \n\n# Conclusions \n\nUsing absolute PL measurements, we were able to decouple the origin of non-radiative recombination losses for cells in pin and nip configurations fabricated from different CTLs. For a triple cation perovskite system, we found that a range of the most common CTLs induce large non-radiative recombination currents which dwarf the nonradiative losses in the neat perovskite. We identified that the most selective bottom CTLs are the polymers PTAA and PolyTPD and $\\mathsf{S n O}_{2}$ which are outperforming the omnipresent $\\mathsf{T i O}_{2}$ although this can vary depending on the exact preparation conditions and the absorber material. For pin-cells the perovskite/ $\\mathsf{\\Delta C}_{60}$ interface was fouVinedw Atrotic 10.1039/C9EE be a major issue which induces more interfacial recombination than Spiro-OMeTAD which could be one reason for the lower performance of pin-type cells with the standard electron transporter ${\\sf C}_{60}$ . A comparison between the QFLS of perovskite/CTL bilayers, optical pin- or nip-type stacks and the $V_{\\mathrm{0C}}$ of the complete device shows that the relevant energy losses happen at the top interface in efficient triple cation cells based on PTAA and PolyTPD, $\\mathsf{S n O}_{2}$ and $\\mathsf{T i O}_{2}$ . In these systems, the electron/hole QFLs are expected to be spatially flat throughout the junction to the electrodes, meaning that the QFLS in the perovskite bulk determines the $V_{\\mathrm{0C}}$ of the cells. This allows further quantification of the parallel recombination currents in the bulk and interfaces and/or metal contacts which defines the $V_{\\mathrm{{OC}}}$ of the complete cells. However, in cells with energetically misaligned HTLs such as PEDOT or $\\mathsf{P3H T}$ , the $V_{\\mathrm{0C}}$ is lower than the QFLS in the absorber layer due to an internal bending of the holeQFL. The fundamental study was validated in high-efficiency perovskite cells in pin-configuration with PCEs up to $21.4\\%$ and through rigorous device simulations. The simulations substantiated the understanding obtained from the experimental results and highlighted the importance of a high built-in voltage and negligible majority carrier band offsets between the perovskite and the transport layers. The presence of an energy level offset at the $p$ - contact was confirmed with UPS and also differential charging capacitance measurements. In order to generalize the findings, additional perovskite systems were studied which showed that the absorber layer often allows a substantially higher $V_{\\mathrm{0C}}$ than achieved by the cell. However, a $\\mathsf{\\Omega}\\mathsf{e}F\\mathsf{L S}\\mathsf{-}V_{\\mathrm{oc}}$ mismatch in complete devices appears also in other systems than those featuring a triple cation absorber with PEDOT:PSS and P3HT HTLs. Therefore, this work allows to conclude that energetic offsets are often harming the device $\\mathsf{v}_{\\mathsf{o c}}$ beyond the limitation imposed by defect recombination in the absorber layer and the interfaces. This implies that proper energy level alignment is a primary consideration to harvest the full potential of the optical pin or nip stack. Only then suppression of interfacial defect recombination will allow us to reach the potential of the perovskite absorber, while suppression of defects in the perovskite bulk or at grain boundaries and photon management will be the final goal to improve this technology to its radiative limit. \n\n# References \n\n1 N. J. Jeon, H. Na, E. H. Jung, T.-Y. Yang, Y. G. Lee, G. Kim, H.-W. Shin, S. Il Seok, J. Lee and J. Seo, Nat. Energy, 2018, 3, 682–689. \n2 W. Tress, Adv. Energy Mater., 2017, 7, 1602358. \n3 D. Bi, C. Yi, J. Luo, J.-D. Décoppet, F. Zhang, S. M. Zakeeruddin, X. Li, A. Hagfeldt and M. Grätzel, Nat. Energy, 2016, 1, 16142. \n4 T. S. Sherkar, C. Momblona, L. Gil-Escrig, J. Ávila, M. Sessolo, H. J. Bolink and L. J. A. Koster, ACS Energy Lett., 2017, 2, 1214–1222. \n5 X. Zheng, B. Chen, J. Dai, Y. Fang, Y. Bai, Y. Lin, H. Wei, X. C. Zeng and J. Huang, Nat. Energy, 2017, 2, 17102. \n6 W. S. Yang, B. Park, E. H. Jung, N. J. Jeon, Y. C. Kim, D. U. Lee, S. S. Shin, J. Seo, E. K. Kim, J. H. Noh and S. Il Seok, Science, 2017, 356, 1376–1379. \n7 M. Saliba, T. Matsui, K. Domanski, J.-Y. Seo, A. Ummadisingu, S. M. Zakeeruddin, J.-P. J.-P. CorreaBaena, W. R. Tress, A. Abate, A. Hagfeldt, M. Grätzel and M. Gratzel, Science, 2016, 354, 206. \n8 M. Saliba, T. Matsui, J.-Y. Seo, K. Domanski, J.-P. Correa-Baena, M. K. Nazeeruddin, S. M. Zakeeruddin, W. Tress, A. Abate, A. Hagfeldt and M. Grätzel, Energy Environ. Sci., 2016, 9, 1989–1997. \n9 M. Abdi-Jalebi, Z. Andaji-Garmaroudi, S. Cacovich, C. Stavrakas, B. Philippe, J. M. Richter, M. Alsari, E. P. Booker, E. M. Hutter, A. J. Pearson, S. Lilliu, T. J. Savenije, H. Rensmo, G. Divitini, C. Ducati, R. H. Friend and S. D. Stranks, Nature, 2018, 555, 497–501. \n10 X. Li, D. Bi, C. Yi, J.-D. Décoppet, J. Luo, S. M. Zakeeruddin, A. Hagfeldt and M. Grätzel, Science, 2016, 8060, 1–10. \n11 J.-P. Correa-Baena, W. Tress, K. Domanski, E. H. Anaraki, S.-H. Turren-Cruz, B. Roose, P. P. Boix, M. Grätzel, M. Saliba, A. Abate and A. Hagfeldt, Energy Environ. Sci., 2017, 10, 1207–1212. K. Tvin DOI: 10.1039/C9EE and V. Dyakonov, ACS Energy Lett., 2017, 2, 424–430. \nC. M. Wolff, F. Zu, A. Paulke, L. P. Toro, N. Koch and D. Neher, Adv. Mater., 2017, 29, 1700159. Y. Yang, M. Yang, D. T. Moore, Y. Yan, E. M. Miller, K. Zhu and M. C. Beard, Nat. Energy, 2017, 2, 1–7. E. M. Hutter, J. J. Hofman, M. L. Petrus, M. Moes, R. D. Abellón, P. Docampo and T. J. Savenije, Adv. Energy Mater., 2017, 7, 1–8. \nE. Guillén, F. J. Ramos, J. A. Anta, S. Ahmad, E. Guille, F. J. Ramos, J. A. Anta and S. Ahmad, J. Phys. Chem. C, 2014, 118, 22913–22922. \nF. Staub, H. Hempel, J. C. Hebig, J. Mock, U. W. Paetzold, U. Rau, T. Unold and T. Kirchartz, Phys. Rev. Appl., 2016, 6, 1–13. \nB. Krogmeier, F. Staub, D. Grabowski, U. Rau and T. Kirchartz, Sustain. Energy Fuels, 2018, 2, 1027– 1034. \nD. Kiermasch, A. Baumann, M. Fischer, V. Dyakonov and K. Tvingstedt, Energy Environ. Sci., 2018, 11, 629–640. \nM. Stolterfoht, C. M. Wolff, J. A. Márquez, S. Zhang, C. J. Hages, D. Rothhardt, S. Albrecht, P. L. Burn, P. Meredith, T. Unold and D. Neher, Nat. Energy, 2018, 3, 847–854. \nV. Sarritzu, N. Sestu, D. Marongiu, X. Chang, S. Masi, A. Rizzo, S. Colella, F. Quochi, M. Saba, A. Mura and G. Bongiovanni, Sci. Rep., 2017, 7, 44629. \nI. L. Braly and H. W. Hillhouse, J. Phys. Chem. C, 2016, 120, 893–902. \nG. El-Hajje, C. Momblona, L. Gil-Escrig, J. Ávila, T. Guillemot, J.-F. Guillemoles, M. Sessolo, H. J. Bolink and L. Lombez, Energy Environ. Sci., 2016, 131, 6050–6051. \nG. H. Bauer, L. Gütay and R. Kniese, Thin Solid Films, 2005, 480–481, 259–263. \nA. Delamarre, L. Lombez and J. F. Guillemoles, Appl. Phys. Lett., 2012, 100. \nP. Schulz, E. Edri, S. Kirmayer, G. Hodes, D. Cahen and A. Kahn, Energy Environ. Sci., 2014, 7, 1377. L. E. Polander, P. Pahner, M. Schwarze, M. Saalfrank, C. Koerner and K. Leo, APL Mater., 2014, 2, 1–6. I. Gelmetti, N. F. Montcada, A. Pérez-Rodríguez, E. Barrena, C. Ocal, I. García-Benito, A. Molina-Ontoria, N. Martín, A. Vidal-Ferran and E. Palomares, Energy Environ. Sci., 2019, 12, 1309–1316. \nR. A. Belisle, P. Jain, R. Prasanna, T. Leijtens and M. D. McGehee, ACS Energy Lett., 2016, 1, 556–560. Y. Hou, X. Du, S. Scheiner, D. P. McMeekin, Z. Wang, N. Li, M. S. Killian, H. Chen, M. Richter, I. Levchuk, N. Schrenker, E. Spiecker, T. Stubhan, N. A. Luechinger, A. Hirsch, P. Schmuki, H.-P. Steinrück, R. H. Fink, M. Halik, H. J. Snaith and C. J. Brabec, Science, 2017, 358, 1192–1197. \nW. S. Yang, J. H. Noh, N. J. Jeon, Y. C. Kim, S. Ryu, J. Seo and S. Il Seok, Science, 2015, 348, 1234–1237. M. Stolterfoht, C. M. Wolff, Y. Amir, A. Paulke, L. Perdigón-Toro, P. Caprioglio and D. Neher, Energy Environ. Sci., 2017, 10, 1530–1539. \nX. Zheng, B. Chen, J. Dai, Y. Fang, Y. Bai, Y. Lin, H. Wei, X. C. C. Zeng and J. Huang, Nat. Energy, 2017, 2, 17102. \nQ. Wang, Q. Dong, T. Li, A. Gruverman and J. Huang, Adv. Mater., 2016, 28, 6734–6739. \nC. C. Chueh, C. Z. Li and A. K. Y. Jen, Energy Environ. Sci., 2015, 8, 1160–1189. \nH. Wei, Y. Fang, P. Mulligan, W. Chuirazzi, H.-H. Fang, C. Wang, B. R. Ecker, Y. Gao, M. A. Loi, L. Cao and J. Huang, Nat. Photonics, 2016, 10, 333–339. \nS. Zhang, M. Stolterfoht, A. Armin, Q. Lin, F. Zu, J. Sobus, H. Jin, N. Koch, P. Meredith, P. L. Burn and D. Neher, ACS Appl. Mater. Interfaces, 2018, 10, 21681–21687. \nL. Calió, S. Kazim, M. Grätzel and S. Ahmad, Angew. Chemie Int. Ed., 2016, 55, 14522–14545. \nA. Gheno, S. Vedraine, B. Ratier and J. Bouclé, Metals (Basel)., 2016, 6, 21. \nY. Shao, Y. Yuan and J. Huang, Nat. Energy, 2016, 1, 1–6. \nP. Tiwana, P. Docampo, M. B. Johnston, H. J. Snaith and L. M. Herz, ACS Nano, 2011, 5, 5158–5166. W. Shockley and H. J. Queisser, J. Appl. Phys., 1961, 32, 510–519. \nT. Kirchartz and U. Rau, Phys. Status Solidi Appl. Mater. Sci., 2008, 205, 2737–2751. \nU. Rau, D. Abou-Ras and T. Kirchartz, Advanced Characterization Techniques for Thin Film Solar Cells, Wiley, 2011. \nP. Wurfel, J. Phys. C Solid State Phys., 1982, 15, 3967–3985. \nK. Tvingstedt and C. Deibel, Adv. Energy Mater., 2016, 6, 1502230. \nW. Tress, N. Marinova, O. Inganäs, M. K. Nazeeruddin, S. M. Zakeeruddin and M. Grätzel, Adv. Energy Mater., 2015, 5, 1400812. \nK. Tvingstedt, O. Malinkiewicz, A. Baumann, C. Deibel, H. J. Snaith, V. Dyakonov and H. J. Bolink, Sci. Rep., 2014, 4, 6071. \nI. L. Braly, D. W. DeQuilettes, L. M. Pazos-Outón, S. Burke, M. E. Ziffer, D. S. Ginger and H. W. Hillhouse, Nat. Photonics, 2018, 12, 355–361. \nD. Luo, W. Yang, Z. Wang, A. Sadhanala, Q. Hu, R. Su, R. Shivanna, G. F. Trindade, J. F. Watts, Z. Xu, T. Liu, K. Chen, F. Ye, P. Wu, L. Zhao, J. Wu, Y. Tu, Y. Zhang, X. Yang, W. Zhang, R. H. Friend, Q. Gong, H. J. Snaith and R. Zhu, Science, 2018, 360, 1442–1446. \nZ. Liu, L. Krückemeier, B. Krogmeier, B. Klingebiel, J. A. Márquez, S. Levcenko, S. Öz, S. Mathur, U. Rau, T. Unold and T. Kirchartz, ACS Energy Lett., 2019, 4, 110–117. \nP. Caprioglio, F. Zu, C. M. Wolff, J. A. Márquez Prieto, M. Stolterfoht, P. Becker, N. Koch, T. Unold, B. Rech, S. Albrecht and D. Neher, Sustain. Energy Fuels, 2019, 3, 550–563. \nJ. Wang, W. Fu, S. Jariwala, I. Sinha, A. K. Y. Jen and D. S. Ginger, ACS Energy Lett., 2019, 4, 222–227. M. Burgelman, P. Nollet and S. Degrave, Thin Solid Films, 2000, 362, 527–532. \nP. Calado, A. M. Telford, D. Bryant, X. Li, J. Nelson, B. C. O’Regan and P. R. F. Barnes, Nat. Commun., 2016, 7, 1–10. \nF. Zu, C. M. Wolff, M. Ralaiarisoa, P. Amsalem, D. Neher and N. Koch, ACS Appl. Mater. Interfaces, 2019, acsami.9b05293. \nD. Kiermasch, L. Gil-Escrig, A. Baumann, H. J. Bolink, V. Dyakonov and K. Tvingstedt, J. Mater. Chem. A, 2019. \nS. G. M. Wheeler, PhD Thesis: Bulk and Surface Recombination Limitations to High Voltage Solution Processed Solar Cells, 2017, https://spiral.imperial.ac.uk/handle/10044/1/67751. \nJ. Hwang, F. Amy and A. Kahn, Org. Electron. physics, Mater. Appl., 2006, 7, 387–396. \nL. Kegelmann, P. Tockhorn, C. M. Wolff, J. A. Márquez, S. Caicedo-Dávila, L. Korte, T. Unold, W. Lövenich, D. Neher, B. Rech and S. Albrecht, ACS Appl. Mater. Interfaces, 2019, 11, 9172–9181. S. Pisoni, M. Stolterfoht, J. Loeckinger, T. Moser, P. Caprioglio, D. Neher, S. Buecheler and N. Ayodhya, in production Science and Technology of Advanced Materials 10.1080/14686996.2019.1633952. F. Sahli, J. Werner, B. A. Kamino, M. Bräuninger, R. Monnard, B. Paviet-Salomon, L. Barraud, L. Ding, J. J. Diaz Leon, D. Sacchetto, G. Cattaneo, M. Despeisse, M. Boccard, S. Nicolay, Q. Jeangros, B. Niesen and \n\nS. Zhang, S. M. Hosseini, R. Gunder, A. Petsiuk, P. Caprioglio, C. M. Wolff, S. Shoaee, P. Meredith, S. Schorr, T. Unold, P. L. Burn, D. Neher and M. Stolterfoht, Adv. Mater., 2019, 1901090. 64 H. Tsai, W. Nie, J. C. Blancon, C. C. Stoumpos, R. Asadpour, B. Harutyunyan, A. J. Neukirch, R. Verduzco, J. J. Crochet, S. Tretiak, L. Pedesseau, J. Even, M. A. Alam, G. Gupta, J. Lou, P. M. Ajayan, M. J. Bedzyk, M. G. Kanatzidis and A. D. Mohite, Nature, 2016, 536, 312–317. \n\nAcknowledgements. We thank Lukas Fiedler and Frank Jaiser for lab assistance. Florian Dornack and Andreas Pucher for providing measurement and laboratory equipment. Philipp Tockhorn for characterization of $\\mathsf{S n O}_{2}$ based cells. This work was in part funded by HyPerCells (a joint graduate school of the Potsdam University and the HZB) and by the German Research Foundation (DFG) within the collaborative research center 951 “Hybrid Inorganic/Organic Systems for Opto-Electronics (HIOS)”. \n\nAuthor contributions. M.S. planned the project, drafted the manuscript, fabricated cells and films, performed electrical measurements, developed the PL setup, measured absolute PL and performed simulations and analysed all data. P.C. developed the PL setup, measured absolute PL. and data analysis, measured SEM and contributed to film fabrication and to manuscript drafting. C.M.W. provided important conceptual ideas regarding the identification of the recombination losses, cell fabrication and electrical characterization. J.A.M. performed PL measurements and performed corresponding data analysis and interpretation. J.N. performed PL measurements on cells and films and contributed to electrical measurements. S.Z. performed PESA and UVVis measurements and analysis of this data. D.R. fabricated cells and films, and contributed to electrical measurements. U.H. provided important conceptual ideas regarding the development of the PL setup and corresponding data analysis. Y.A. performed TPC, TPV and differential charging measurements with C.M.W. and M.S. A.R. contributed to the analysis of PL data and development of the setup. L.K. fabricated $\\mathsf{S n O}_{2}$ based cells and films and performed corresponding electrical characterizations. F.Z. performed UPS measurements and interpreted corresponding data. S.A. developed $\\mathsf{S n O}_{2}$ based cells and films. N.K. performed UPS measurements and interpreted corresponding data. T.K. contributed to the analysis of recombination losses and analysed the simulation results. M.Sa. fabricated $\\mathsf{T i O}_{2}$ based cells and films and performed corresponding electrical characterizations. T.U. performed numerical simulations and analysed simulation results, contributed to the analysis of PL measurements and recombination losses. D.N. contributed to project planning, manuscript drafting and analysis of all electro-optical measurements. All co-authors contributed to proof reading of the manuscript. \n\nCompeting financial interests. The authors declare no competing financial interests. \n\nData availability. The data that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request. " + }, + { + "id": "10.1038_s41467-019-08507-4", + "DOI": "10.1038/s41467-019-08507-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-08507-4", + "Relative Dir Path": "mds/10.1038_s41467-019-08507-4", + "Article Title": "Strain engineering in perovskite solar cells and its impacts on carrier dynamics", + "Authors": "Zhu, C; Niu, XX; Fu, YH; Li, NX; Hu, C; Chen, YH; He, X; Na, GR; Liu, PF; Zai, HC; Ge, Y; Lu, Y; Ke, XX; Bai, Y; Yang, SH; Chen, PW; Li, YJ; Sui, ML; Zhang, LJ; Zhou, HP; Chen, Q", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "The mixed halide perovskites have emerged as outstanding light absorbers for efficient solar cells. Unfortunately, it reveals inhomogeneity in these polycrystalline films due to composition separation, which leads to local lattice mismatches and emergent residual strains consequently. Thus far, the understanding of these residual strains and their effects on photovoltaic device performance is absent. Herein we study the evolution of residual strain over the films by depth-dependent grazing incident X-ray diffraction measurements. We identify the gradient distribution of in-plane strain component perpendicular to the substrate. Moreover, we reveal its impacts on the carrier dynamics over corresponding solar cells, which is stemmed from the strain induced energy bands bending of the perovskite absorber as indicated by first-principles calculations. Eventually, we modulate the status of residual strains in a controllable manner, which leads to enhanced PCEs up to 20.7% (certified) in devices via rational strain engineering.", + "Times Cited, WoS Core": 763, + "Times Cited, All Databases": 799, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000458864600018", + "Markdown": "# Strain engineering in perovskite solar cells and its impacts on carrier dynamics \n\nCheng Zhu1, Xiuxiu Niu1, Yuhao $\\mathsf{F u}^{2}$ , Nengxu Li3, Chen ${\\mathsf{H u}}^{4}$ , Yihua Chen3, Xin ${\\mathsf{H e}}^{2}$ , Guangren ${\\mathsf N}\\mathsf{a}^{2}$ , Pengfei Liu1, Huachao Zai5, Yang ${\\mathsf{G e}}^{6}$ , Yue ${\\mathsf{L u}}^{6}$ , Xiaoxing ${\\mathsf{K e}}^{6}$ , Yang Bai1, Shihe Yang4,7, Pengwan Chen8, Yujing Li1, Manling Sui 6, Lijun Zhang $\\textcircled{1}$ 2, Huanping Zhou3 & Qi Chen 1 \n\nThe mixed halide perovskites have emerged as outstanding light absorbers for efficient solar cells. Unfortunately, it reveals inhomogeneity in these polycrystalline films due to composition separation, which leads to local lattice mismatches and emergent residual strains consequently. Thus far, the understanding of these residual strains and their effects on photovoltaic device performance is absent. Herein we study the evolution of residual strain over the films by depth-dependent grazing incident X-ray diffraction measurements. We identify the gradient distribution of in-plane strain component perpendicular to the substrate. Moreover, we reveal its impacts on the carrier dynamics over corresponding solar cells, which is stemmed from the strain induced energy bands bending of the perovskite absorber as indicated by first-principles calculations. Eventually, we modulate the status of residual strains in a controllable manner, which leads to enhanced PCEs up to $20.7\\%$ (certified) in devices via rational strain engineering. \n\nver the past decade, hybrid organic−inorganic halide perovskites have received enormous interest as low-cost and highly efficient light absorbers in photovoltaics1–6. The power conversion efficiency (PCE) of perovskite solar cells has shortly surpassed $22\\%$ in the lab scale7, and that of larger-area $(>1\\thinspace{\\mathrm{cm}}^{2})$ devices has exceeded $20\\%^{8-11}$ . The highest PCEs are mostly achieved by employing the mixed halide perovskites (e.g., $(\\mathrm{HC(NH_{2})_{2}P b I_{3}})_{0.85}(\\mathrm{CH_{3}N H_{3}P b B r_{3}})_{0.15}$ i.e., $(\\bar{\\mathrm{FAPbI}}_{3})_{0.85}$ $(\\mathrm{MAPbBr}_{3})_{0.15})$ . Through element substitution, it provides a largely unexplored compositional space to tailor the physiochemical properties of corresponding materials for efficient and stable devices $^{1,12-15}$ . However, the mixed hybrid perovskites potentially suffer from materials inhomogeneity partially due to composition separation16,17 and/or thermal stress. This may be originated from substantial chemical mismatch among each component, and the nonequilibrium growth conditions during film fabrication. On one hand, serious material inhomogeneity is regarded as phase separation, deviating from the originally desired materials properties to deteriorate the resultant device performance (both efficiency and operational stability)18,19. On the other hand, moderate material inhomogeneity correlates to local lattice mismatches and emergent residual strains in perovskite films. It deserves more attention, because such residual strains should result in lattice distortion of microscopic crystal structure, and further affect optoelectronic properties of the perovskite thin film20–25. \n\nRecently, the residual strains have been identified in the singlecomposition $\\mathbf{MAPbI}_{3}$ polycrystalline films, and were found to influence stability of perovskite films under illumination22. In an even wider spectrum of semiconductors, strain has been extensively investigated, and accordingly, strain engineering has been exploited to tailor the optoelectronic functionalities. For instance, the application of tensile strain was found to improve light emission in Germanium crystals and drive indirect-to-direct optical transition in bilayered two-dimensional $\\mathrm{WSe}_{2}{^{26-28}}$ . Strain compensation strategy has been demonstrated to improve efficiencies of GaAs-based quantum dot solar cells29,30. Strainengineered $\\ensuremath{\\mathrm{MoS}}_{2}$ monolayer was also proposed to have broadrange capture of solar energy26. For hybrid halide perovskites, especially mixed perovskites, in-depth understanding of their characteristics and effects on the material’s optoelectronic properties, is still absent. This precludes effective employment of strain engineering to further enhance the device performance. \n\nIn this report, we probe the residual strain distribution profiles in the mixed perovskite thin films and its effects on photovoltaic device efficiency. We investigate the evolution of in-plane residual strain over the film thickness in the typical mixed perovskite $({\\mathrm{FAPbI}}_{3})_{0.85}({\\mathrm{MAPbBr}}_{3})_{0.15}$ by using grazing incident X-ray diffraction (GIXRD) measurement. We identify a gradient distribution of in-plane strain component that correlates to the composition inhomogeneity perpendicular to the substrate. We further demonstrate a feasible method to modulate the tensile or compressive nature of residual strain and even its gradient over perovskite films in a controllable manner. With the aid of firstprinciples calculations, we find that the strain gradient induces energy bands bending and thus affects the carrier dynamics across the interfaces over the solar cell. By deliberately engineering the residual strains to enhance carrier extraction efficiency, we successfully fabricate strain-engineered perovskite solar cells to achieve enhanced PCEs up to $20.7\\%$ (certified). \n\n# Results \n\nProbing residual strain gradient of mixed perovskite films. In the direction parallel to substrates, the grain-to-grain inhomogeneity in polycrystalline films was already observed by adopting photoluminescence in a scanning electron microscopy (PL-SEM) and conductive-atomic force microscopy (C-AFM)31. However, it lacks depth profile along the film thickness regarding the lattice structure inhomogeneity. At the macroscopic level, the vertical homogeneity of thin films can be quantitatively evaluated by residual strain to reflect the lattice mismatch $^{20,22,32}$ . The macroscopic residual strain is an internal strain in polycrystalline materials that is balanced over a wide range of grains. We explored the residual strain distribution for mixed perovskite films vertically with the depth-dependent GIXRD measurement, wherein the classical $\\sin^{2}\\varphi$ measurement is combined with grazing incident X-ray diffraction to probe the in-plane residual strain. This method has been used in thin films of $\\mathrm{ZrO}_{2}$ and TiN, which provides reliable depth resolution to reveal lattice structure evolution33–35. As depicted in Fig. 1a, we fixed the $2\\theta$ and varied the instrument tilt angle $\\psi$ to obtain corresponding X-ray diffraction (XRD) patterns as shown in Fig. 1b. For detailed test information, please see the Supplementary method, Supplementary Fig. 1 and Supplementary Table 1. The mixed perovskite films on the $\\mathrm{SnO}_{2}/\\mathrm{ITO}_{I}$ glass substrates showed XRD peaks (2θ) at around $14.0^{\\circ},31.6^{\\circ}$ , and $40.5^{\\circ}$ , corresponding to (001), (012), and (022) crystallographic planes, respectively36. Among all three planes with intensive diffraction peaks, the (012) plane was chosen for further analysis due to its high diffraction angle and multiplicative factor, which provides the most reliable structure symmetry information. \n\nWe picked up three representative depths of 50, 200 and 500 nm to check the residual strain in the mixed perovskite films with the nominal formula of $(\\mathrm{FAPbI_{3}})_{0.85}(\\mathrm{MAPbBr}_{3})_{0.15}$ . At each fixed depth, diffraction data were fitted with Gaussian distribution function and it clearly observed a systematic shift in peak position to lower $2\\theta$ when the penetrated depth increased (Fig. 1b and Supplementary Fig. 2). Generally, $\\sin^{2}\\varphi$ and $2\\theta$ follow a linear relationship and the slope of the fitting line stands for the magnitude of the residual strain (see equation (1) in Supplementary method). As shown in Fig. 1b, all fitting lines exhibited negative value in the slopes, which means (012) crystal planes exhibit enlarged distance when turning to the out-of-plane direction at the same detected depth. It thus indicates the entire sample is subjected to tensile strain. It is in agreement with previous study wherein the residual tensile strain was observed in perovskite thin films upon the similar annealing process22. \n\nWith the increase of probe depth, the fitting lines show smaller slopes in absolute value, which implies the macroscopic residual tensile strain gradually decreases. Moreover, we found the most significant deviation in lattice constant at $50\\mathrm{nm}$ as compared to that of 200 and $500\\mathrm{nm}$ . Besides, the (001) and (022) crystal planes were also found to follow the similar trend (Supplementary Fig. 2). It indicates the residual strain inhomogeneity in the mixed perovskite thin film, wherein the top surface of the film bears the largest tensile strain. It is worth noting that residual strain correlates to the lattice distortion, which might affect the carrier dynamics at the relevant interfaces, as will be discussed later. Therefore, the residual tensile strain gradient was clearly identified, which gradually decreases from the top surface to the core in the mixed perovskite polycrystalline thin films. \n\nSo far, we have observed the gradient distribution of tensile strain in the perovskite thin film. And it will be interesting to understand the origin of the residual strain. The residual stain is often stemmed from the lattice mismatch due to lattice structure evolution. We thus conducted GIXRD measurements with variable grazing incident angle $\\omega$ (Supplementary Table 1) to reveal the lattice mismatch along the film thickness. These depthdependent XRD patterns were roughly similar and no new diffraction peaks appeared, indicating the film exhibited the same cubic phase structure at different depths. However, we observed a systematic shift of diffraction peaks along with the probing depths at 50, 200, and $500\\mathrm{nm}$ in the perovskite film. Take (001) planes for example, the corresponding diffraction peaks for 50, 200, and $500\\mathrm{nm}$ exhibited peak centers at $14.01^{\\circ}$ , $13.94^{\\circ}$ , and $13.90^{\\circ}$ respectively (Supplementary Fig. 3). Among different crystal planes of (001), (012) and (022), corresponding peak positions gradually shift towards the low diffraction angle with the increase of probing depths. According to the Bragg’s law, larger lattice constant was expected in the deeper zone of films. Thus, the crystal structure inhomogeneity along the film thickness is detected unambiguously. To provide the evidence regarding the structure inhomogeneity in the microscopic level, transmission electron microscopy (TEM) nano-beam electron diffraction measurement was further carried out to investigate crystal structure evolution along the depth direction of mixed perovskite films. We obtained the high-resolution TEM image with microarea diffraction patterns to inspect three typical regions with different depths (Fig. 1d–f). After careful calibration of all measured diffraction patterns (Supplementary Table 2), we found that the crystal plane distance increased with scanning depth. As shown in Fig. 1e–g, lattice parameters of (004) planes were measured to be 1.60, 1.64 and $1.67\\mathring{\\mathrm{A}}$ for three individual areas, respectively, which is consistent with the GIXRD results. Combining the microscopic analysis (TEM) and the long-range structure characterization (GIXRD), we clearly illustrate lattice structure evolution developed vertically in the mixed perovskite polycrystalline thin films, wherein the lattice constant decreases from the surface to the bottom. \n\n![](images/9ba27bd8187cf0253e2159a49172dd5fcdc78b29d0abb0b14ec6bbcfbd371878.jpg) \nFig. 1 Gradient lattice structure characterization. a Schematic illustration of the residual strain distribution measurement. The corresponding XRD patterns and lattice structure strain information can be obtained by fixing the test crystal plane and adjusting the instrument tilt angle $\\psi,$ where $\\ensuremath{\\mathbf{N}}_{0}$ is the sample normal direction and $\\pmb{\\mathsf{N}}_{\\mathsf{k}}$ is the diffraction vector. b GIXRD spectrum at different tilt angles at the depth of $50\\mathsf{n m}$ for the tensile-strained film. c Residual strain distribution in the depth of 50, 200, 500 nm for the tensile-strained film (measured (points) and Gauss fitted (line) diffraction strain data as a function of $\\sin^{2}\\varphi)$ . The error bar indicates standard deviation of the 2θ. d The cross-sectional TEM image of device. e, f, g The nano-beam electron diffraction patterns ([100] zone axis and TEM specimens is FIBed), corresponding with e-f- $\\cdot{\\_}$ point in $\\begin{array}{r}{\\big\\vert\\big\\vert_{\\pmb{d}_{\\prime}}}\\end{array}$ confirming the FAMA hybrid perovskite phase structure transform to nearly pure FA phase from the surface to the bottom of perovskite film according to the larger quadrangle. h PL depth profile of confocal fluorescence microscope, the inset represents TOF-SIMS depth profiles of the $(F A P b|_{3})_{0.85}(M A P b B r_{3})_{0.15}$ perovskite film with tensile strain. XRD X-ray diffraction, TEM transmission electron microscopy \n\nThe above-mentioned crystal structure inhomogeneity is likely to correlate to the composition evolution in mixed perovskite thin films. It is commonly accepted that $\\mathrm{FAPbI}_{3}$ exhibits the cubic phase with the lattice constant of $6.357\\mathring{\\mathrm{A}}^{36}$ . When MA and/or Br element are incorporated to form the mixed perovskites single crystals, they hold the cubic phase with decreased lattice parameters. We observed smaller lattice constant at the surface of the film, which may partially attribute to higher ratio of MA and/or Br components in the long-range ordered FA based perovskite lattices. To identify the distribution of MA and/or Br components, we resorted to time-of-flight secondary ion mass spectrometry (TOF-SIMS) depth profiles and TEM/EDX mapping for the $(\\mathrm{FAPbI_{3}})_{0.85}(\\mathrm{MAPbBr}_{3})_{0.15}$ perovskite film samples as shown in the inset of Fig. 1h, Supplementary Figs. 4 and 5. It shows a homogeneous distribution of $\\mathrm{CsBr^{2+}}$ , $\\mathrm{\\dot{C}s I^{\\tilde{2}+}}$ , $\\mathrm{FA^{+}}$ in the all samples, which indicates the even distribution of the halogen $\\mathrm{Br^{-}}$ . It is reasonable because the smallest halogen ion $\\mathrm{Br^{-}}$ can diffuse and be evenly distributed during the crystallization process. To be noted, the signal intensity of $\\mathrm{MA^{+}}$ fragment decreased substantially from the surface to the core region in all mixed perovskite thin films, consistent with the XRD and TEM results. Unambiguously it reveals the gradient evolution of composition and thus lattice structure across the depth direction due to the gradient distribution of organic cation $\\mathrm{M}\\mathrm{\\bar{A}^{+}}$ . The nonuniform composition distribution indicates the unique kinetics for film growth, which is possibly related to the coordination strength of different precursors37 and film processing conditions. It clearly implies the compositional distribution serve as one major factor that leads to the gradient residual strain. \n\nIt is revealed that hybrid perovskites with different lattice structures often exhibit different optoelectronic properties25,38 and it is expected to observe the gradient variation in terms of optoelectronic properties within the gradient phase structure of the film. Therefore, we examined the depth-dependent photoluminescence (PL) spectra within the film by using confocal fluorescence microscope. With the increasing depth of the beam probe, a systematic red shift of PL spectra was observed (Fig. 1h and Supplementary Fig. 6). Fitting with the Gaussian distribution function, we found the PL peak positions shifted from 781 to 788 nm, and their full width at half maximum (FWHM) decreased along the film thickness. Since the emission photon energy is determined by the bandgap of semiconductors, it indicates the perovskite film exhibits gradually decreased bandgap from the surface to the bottom vertically. To be noted, it follows the similar trend in gradient evolution of lattice structure and compositional distribution, wherein more $\\mathrm{MA^{+}}$ ions are incorporated in the perovskite crystals at the top surface of the film. In addition, narrower PL linewidth emission at the deeper region of perovskite film was observed, which may indicate weakened interaction between charge carriers and lattice vibrations (phonons) due to improved film homogeneity and lattice order39,40. \n\nModulating the residual strains. Based on the analysis above, we reveal that the observed residual strain gradient in perovskite films is closely related to lattice structure evolution due to detectable compositional inhomogeneity. However, it may not be the only contributor that governs the residual strain, given the largest tensile strain concentrated on the film surface. Interestingly, when examining the pure $\\operatorname{MAPbI}_{3}$ perovskite thin film, we still observed the existence of gradient residual strain (Supplementary Fig. 7). It is thus speculated that the thermal strain may take effects due to the temperature gradient during perovskite film fabrication. To illustrate, the perovskite film is roughly divided into two regions, e.g., the surface and the bottom (near the substrate). When heated on a hot plate, both regions experienced substantial temperature gradient (higher at the bottom). Consequently, the inorganic framework near the bottom expands more in volume upon annealing as compared to that at the surface, which facilitates the insertion of larger cation $(\\mathrm{FA^{+}})$ to form the perovskite crystalline structure. It possibly results in the inhomogeneous composition in the film, wherein $\\mathrm{MA^{+}}$ prefers to stay at the surface. Upon cooling, it is reasonable that the surface cools down much faster than that of the core, which leads to less volume shrinkage. As a result, the surface withstands tensile strain and the core is subjected to compressive strain accordingly. Additionally, since the thermal expansion coefficient of perovskites is much larger than that of the substrate, the entire film bears the tensile strain during film cooling process. Thereby, the core experiences not only compressive strain from the surface, but also tensile strain from the substrate, which leads to the gradient residual tensile strain in the perovskite thin film. \n\nTo verify the speculation, we attempted to modulate the gradient in-plane residual strain in the perovskite thin films by adjusting the annealing process. We first tried to anneal the film at $150^{\\circ}\\mathrm{C}$ high temperature for a long time, which is a conventional approach to eliminating residual strains in metal alloy materials. Unfortunately, it led to the significant occurrence of $\\mathrm{PbI}_{2}$ (Supplementary Fig. 7) in the resultant thin films due to the relative poor thermal stability of hybrid perovskites41. We then tried to change the temperature gradient when the films were annealed. Simply, we modified the heat treatment process by flipping over the thin film sample to provide an invert temperature gradient. Interestingly, tensile strain was significantly reduced in the samples upon this treatment as shown in Fig. 2a, b. With small strain gradient and the closer lattice distance in the perovskite film, the lattice structure was almost homogeneous. It thus suggests an effective way to significantly reduce the tensile strain inhomogeneity across the film thickness by tuning the temperature gradient during film processing. Furthermore, we tried to directly perform flipped annealing process to the intermediate state film after the spin-coating process ends, which is expected to apply compressive strain with vertical gradient over the film. In contrast to the previous samples, the as-prepared films show the fitting curves possessed slopes in positive values (Fig. 2c, d), which increased along with the probe depth. It clearly indicates films exhibit compressive strain, which is also distributed in a vertical gradient. Unfortunately, we observed a lot of pinholes in the resultant film possibly because the solvent cannot be spread smoothly during the annealing process (Supplementary Fig. 9). Therefore, we demonstrate the temperature gradient is also an important source to residual strain during the film growth, which further suggests a method to manipulate the evolution of lattice structure of polycrystalline thin films and the surface strain. \n\nTo investigate whether the upper contacting layer influences the surface strain, we prepared a tensile-strained film to test the surface residual strain as a reference point. Then for the same sample, $1\\mathrm{mL}$ chlorobenzene solution was dripped on the film surface during the spin-coating process and the film was tested. Furthermore, the same sample was coated with Spiro-OMeTAD layer and then tested again. We found the same slope of the fitting curves indicating the magnitude of the surface strain remained constant. (Supplementary Fig. 10) It clearly shows that the chlorobenzene dripped process and/or Spiro-OMeTAD contacting layer does not affect the surface strain significantly. \n\nThe residual strain and its gradient distribution reflects the structure inhomogeneity in the perovskite thin film along the vertical direction. It is known that the strain gradient is derived from the XRD peak offset, which actually reveals the variation of lattice parameters leading to the crystal structure mismatch across the thin film. In hybrid halide perovskites, the framework of corner-sharing $\\mathrm{PbI}_{6}^{\\cdot}$ octahedral contributes to the electronic configuration, especially at the band-edge42,43. It means variations in the inorganic framework would possibly result in the change in optoelectronic properties of the materials. The structure variations include enlargement/shrinkage, tilting, and other deformation of the octahedral network, which can be clearly illustrated by measuring the residual strain. Therefore, it is of great interest to bridge the gulf between the residual strain and the optoelectronic properties of the materials and relevant devices. Given the thin film surface exhibits the most significant strain, it is reasonable focus on the carrier dynamic behavior across the interface via strain modulation, and their effects on device performance. \n\n# Impacts of strain on carrier dynamics and device performance. \n\nTo investigate the impact of the gradient residual strain on the device performance, we first fabricated planar heterojunction solar cells by adopting the perovskite absorbers with/without residual strains. The device architecture follows the regular structure of $\\mathrm{ITO}/\\mathrm{SnO}_{2}/$ perovskite/Spiro-OMeTAD/Ag. We then compare the $J{-}V$ curves of the tensile-strained and the strain-free devices. To avoid possible misleading due to sample variation, we fabricated 40 cells under optimal conditions in each batch. Figure 3a shows the histograms of PCEs for each batch of samples with/without strain. The tensile-strained devices exhibited the PCE averaged around $18.7\\%$ with a wider distribution from $17.3\\%$ and $20.3\\%$ . In comparison, the strain-free devices achieved the averaged PCE of $19.8\\%$ , whose PCEs were distributed in a narrow range between $18.8\\%$ and $20.7\\%$ . The narrow distribution in PCEs of the strain-free devices stands for the good processing reproducibility. We also conducted the current–voltage $\\left(I-V\\right)$ measurement for devices under different annealing conditions to preserve different tensile strains in the absorbers, which provided the statistics of parameters in Supplementary Fig. 11 and Supplementary Table 4. It is found that the fill factor (FF) and the open-circuit voltage $(V_{\\mathrm{OC}})$ have significantly improved with the increase of the flipped annealing time, wherein the surface tensile strain is gradually released through prolonged annealing at $120^{\\circ}\\mathrm{C}$ . \n\nWe measured current-density voltage $\\left(J-V\\right)$ characteristics of one of the best devices under a simulated illumination of air mass (AM) 1.5 and $100\\mathrm{mW}\\mathrm{cm}^{-2}$ . This device generated a short-circuit current density $\\left(J_{\\mathrm{SC}}\\right)$ of $22.8\\mathrm{mAcm}^{-2}$ , a FF of $78.0\\%$ , an opencircuit voltage $\\scriptstyle\\left(V_{\\mathrm{OC}}\\right)$ of $1.17\\mathrm{V},$ , and a power conversion efficiency of $20.7\\%$ (Fig. 3b). The forward and reverse scanning current density–voltage $\\left(J-V\\right)$ curves showed negligible hysteresis in the corresponding device in Supplementary Fig. 11e, which was likely attributed to the improved carrier extraction at the interface44,45. By holding a bias near the maximum power output point (0.96 V), a stabilized photocurrent of $21.3\\mathrm{mA}\\mathrm{{cim}}^{-2}$ was obtained, corresponding to a stabilized efficiency of $20.5\\%$ (the inset of Fig. 3b). The device performance was certified by the independent third party (Supporting Information). The External quantum efficiency (EQE) spectra for the two types of devices were shown in Supplementary Fig. 11f. Compared to the tensile strain device, the strain-free device showed improved light harvesting efficiency along the entire absorption wavelength range of 350 to $800\\mathrm{nm}$ . The integrated photocurrent densities were calculated to be 20.81, $22.7\\mathrm{mA}\\mathrm{\\bar{c}}\\mathrm{m}^{-2}$ , respectively, which was in good agreement with the $J_{\\mathrm{SC}}$ derived from the $J{-}V$ measurement. Thus far, we observed the significant improvement in FF and $V_{\\mathrm{OC}}$ in strain-engineered devices. This is likely attributed to improved carrier extraction dynamics around the absorber interface, which is subjected to further analysis. \n\nFirstly, the carriers transport behavior at the interface was probed with transient photocurrent (TPC) and time-resolved photoluminescence (TRPL) measurement. The TPC measurement (Fig. 3c) was often used to monitor the carrier transport across the device. By fitting with the exponential function, the photocurrent decay time was significantly reduced from 12.96 to $1.0\\upmu s$ (Supplementary Table 5). A faster decay of photocurrent than the reference device suggested the improvement in carrier extraction when tensile strain gradient was almost eliminated at the surface. Further investigation with the TRPL measurement indicates improved hole extraction due to elimination of residual strain, as observed in the samples with the configuration of glass/ perovskite/Spiro-OMeTAD. As shown in Supplementary Fig. 12 and Supplementary Table 6, the average decay time $\\tau_{\\mathrm{avg}}$ related to PL quenching was dramatically decreased from 14.6 to $4.9\\mathrm{ns}$ in the strain-free sample, showing the higher quenching rate. It indicates that the strain-free sample exhibits better hole extraction at the interface between absorber and hole transport material (HTM), as compared to that of the tensile strain sample. This result is in accordance with the TPC measurement, showing that modulation of residual tensile strain can accelerate the carrier transfer process. \n\nSecondly, we investigated how the carrier recombination process of devices is affected by the residual strain. We conducted the combined measurements of light-intensity-dependent $V_{\\mathrm{OC}},$ electrochemical impedance spectroscopy (EIS) and transient photovoltage decay (TPV). The light-intensity-dependent $V_{\\mathrm{OC}}$ provides critical insights into the mechanism of recombination processes in solar cells46. The corresponding charge carrier recombination process is reflected by the ideality factor of $\\\"n\\\"$ as determined by the slope of the $V_{\\mathrm{OC}}$ versus incident light-intensity according to the equation $V_{\\mathrm{OC}}{=}E_{\\mathrm{g}}/q n k_{\\mathrm{B}}T/q{\\ln}J_{0}/J;$ where $q$ is the elementary charge, $k_{\\mathrm{B}}$ is the Boltzmann constant, and $T$ is the temperature. When the ideality factor $n$ approaches 2, ShockleyRead-Hall (SRH) type, trap-assisted recombination dominates. As shown in Fig. 3d, from the relationship between $V_{\\mathrm{OC}}\\sim\\ln(\\mathrm{I})$ , the ideality factor $n$ are 1.01, 1.55 for the devices with/without tensile strain, respectively. It indicates that trap-assisted SRH recombination is effectively suppressed by reducing the tensile strain that is mainly located at the absorber surface. The alleviated SRH recombination may be attributed to the reduced trap density in strain-free devices, wherein crystal structure homogeneity is achieved. \n\nThe carrier dynamics across the perovskite/HTM interface upon strain modulation is further examined by EIS. Corresponding Nyquist plots were obtained from solar cells with/without gradient residual strain in dark without applied bias (Fig. 3e). It shows two separate arcs, equivalent to the resistive and capacitive components of various interfaces47,48. Generally, the first arc in the intermediate-frequency region is associated with the recombination impedance due to the selective contacts or their interface with the perovskite active layer in the device. Here, we mainly focused on the mid-frequency region and found that the recombination impedance increased from 23.69 to $521.10\\mathrm{K}\\Omega$ when the tensile strain was relaxed. It is consistent with that of the light-intensity-dependent $V_{\\mathrm{OC}}$ measurement. We further measured the recombination resistance $(R_{\\mathrm{rec}})$ , wherein the device was subjected to applied bias ranging from 0.4 to $1.0\\mathrm{V}$ By fitting with the simple RC equivalent circuit, we exacted the recombination resistance under different bias as shown in Fig. 3f. It is clear that strain-free devices display a larger $R_{\\mathrm{rec}}$ than that of the tensile-strained one, which indicates that the interfacial charge recombination is suppressed in strain-free device. The reduced recombination loss was further confirmed by TPV measurement49, wherein the photovoltage decay time was significantly increased from 4.01 to $10.32\\upmu s$ (Supplementary Fig. 12 and \n\n![](images/1adb66dbde7c86e43050e2e73c30121738fd5edac6d2f3a78b9fff78f80ae5c5.jpg) \nFig. 2 Residual strain distribution measurement with the GIXRD method. a, c GIXRD spectrum at different tilt angles at the depth of $50\\mathsf{n m}$ for the strainfree film, compressive strained film. b, d Residual strain distribution in the depth of 50, 200, $500\\mathsf{n m}$ for the strain-free film, compressive strained film (measured (points) and Gauss fitted (line) diffraction strain data as a function of $\\sin^{2}\\varphi)$ . The error bar indicates standard deviation of the 2θ. e The schematic representation of the tensile strain state of the film in the top surface, showing the lattice structure with/without tensile strain on the film surface from the perspective of long-range order \n\nSupplementary Table 5) when tensile strain was released. It is also in agreement with higher $V_{\\mathrm{OC}}$ observed in the devices with strainfree absorbers. \n\n# Mechanisms of the effect of strain on photovoltaic properties. \n\nThe above results unambiguously indicate that the gradient distribution of residual strains directly affects the hole carrier dynamics across the perovskite/HTM interface and thus the device performance. To reveal the underlying mechanism, we performed first-principles calculations to simulate changes of electronic structure and optoelectronic properties of the perovskite films under strained condition. In particular, we chose the (001)-oriented $\\mathrm{FAPbI}_{3}$ perovskite film represented by six-layers Ruddlesden-Popper phase of $\\mathrm{FAPbI}_{3}$ and applied in-plane biaxial strains to it. Since (001) is one of predominate growth direction of perovskite crystals as indicated by the XRD measurements, and $\\mathrm{\\bar{F}A P b I}_{3}$ , $\\mathbf{MAPbBr}_{3}$ and their mixture have similar electronic structures50,51, we expect the above model can reasonably mimic the strained mixed perovskite $({\\mathrm{FAPbI}}_{3})_{0.85}({\\mathrm{MAPbBr}}_{3})_{0.15}$ films in experiment. We embedded the (001) $\\mathrm{FAPbI}_{3}$ film in the vacuum and applied biaxial strains of $1\\%$ , $0.5\\%$ (compressive) and $-0.5\\%$ , $-1\\%$ (tensile), respectively (Supplementary Fig. 13). We found that the perpendicular direction exhibit quite small opposite stain components as the rotation of organic FA/MA molecules contributes substantially to strain relaxation. The calculated band structures under tensile, zero, and compressive strains are shown in Fig. 4a, b. One sees that the band gaps of the films show increase with the strain changing from compression, zero-strain, to tension. This agrees with the observed tendency of bandgap change from the ultraviolet (UV)–visible (Vis) absorption and PL measurement (Fig. 4c). To be noted, the bandgap measured from UV–Vis absorption and PL spectra less than the theoretical value. It is because the theoretical value was calculated with the assumption that the entire lattice structure is subjected to strain state. In our experiment however, the largest strain only locates at the surface region rather than the entire film (Fig. 1c), wherein quite a large portion of films remain the original bandgap. The tendency can be explained by consideration of the band-edge features of $\\mathrm{Pb}$ halide perovskites $\\mathrm{APbX}_{3}$ , where the valence band (VB) edge is composed of the strong anti-bonding interaction between $\\operatorname{Pb}-s$ and $X{-}p$ orbitals, and the conduction band (CB) edge is predominantly from $\\mathrm{Pb}{-}p$ orbital with weak anti-bonding character51,52. With the perovskite film experiencing compressive, zero, to tensile biaxial strain, the in-plane lattice gradually expands, which weakens the $\\mathrm{Pb}{-}\\mathrm{X}$ bonds and thus in principle pulls down both the anti-bonding VB and CB energy levels. However, the VB with strong anti-bonding hybridization is substantially decreased, while the CB is less affected. As the result, the bandgap shows increase from compressive, zero, to tensile strain. This explanation is indeed supported by our calculations as shown in Fig. 4a. \n\n![](images/0d7ee51cc966e8984bce2dc2cb725f10705a954e4be79941608e4744642e9d8f.jpg) \nFig. 3 Device performance and carrier dynamic behavior analysis. a Histograms of the PCEs for the devices with different strain conditions. b $J-V$ curves of the tensile strain device and strain-free device. The inset is the stabilized current density measured at a bias voltage (0.94, $0.96\\vee,$ respectively). c TPC decay curves for PSCs with tensile strain and strain-free conditions. d The light-intensity dependence of $V_{\\mathsf{O C}}$ measurement related to tensile strain and strain-free device. e EIS curves for PSCs with different strain conditions and the inset is frequency response signal according to frequency parameter from 1 MHz to $100{\\mathsf{H z}}$ . f Variation of recombination resistance as a function of applied voltage. PCE power conversion efficiency, TPC transient photocurrent, EIS electrochemical impedance spectroscopy \n\nBased on the changed electronic structure in the strained perovskite, we attempt to illustrate how residual strains affect hole carrier dynamics in solar cells. Figure 4b (left panel) shows the evolution of band-edge energies under tensile strains. The CB decreases slightly with increasing strain magnitude, whereas the VB exhibits pronounced downshift. It reveals that strains evolve vertically in the perovskite film, wherein the largest tensile strain is observed at the perovskite/HTM interface. Therefore, the VB bends downward monotonously over the entire perovskite absorber layer, as depicted in the Fig. 4b (right panel). This VB downward bending has dual effects on the hole carrier dynamics. On one hand, it creates the ‘‘cliff-type’’ band alignment by repelling hole carrier energy level away from that of the HTM (Fig. 4b). This was reported to be unfavorable for hole extraction in $\\mathrm{\\bar{Cu}(I n,G a)S e}_{2}^{53}$ and perovskite solar cells54–58. On the other hand, the hole mobility is possibly affected along the direction of VB downward bending, wherein the hole carrier diffusion suffers from extra hindering force field due to unfavored energy level gradient. As indicated by the space-charge-limited current (SCLC) measurement (Fig. 4d) of the fabricated capacitor-like devices by sandwiching the perovskite films between ITO and Au, the mobilities of the samples with and without tensile strain were calculated to be $7.04\\times10^{-4}$ and $1.02\\times10^{-3}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{S}^{-1}$ , respectively. Indeed, the experimentally observed carrier mobility is improved when tensile strain is released. In short, by eliminating the tensile strain gradient in the perovskite film, the VB is flattened to cancel the ‘‘cliff-type’’ band alignment of perovskite absorber/HTM and hole mobility is enhanced simultaneously. It thus favors the charge transport and extraction of photogenerated holes, which suppresses the carrier recombination and leads to the significant improvement in FF and $V_{\\mathrm{OC}}$ in the corresponding device. \n\n![](images/a7b05d9bb27c2fd568a8deaa7ca0002e33020dd18d273fe1a938f7289708fd8e.jpg) \nFig. 4 Strain-induced electronic structure analysis. a Calculated band structures under biaxial tensile, zero, and compressive strains from first-principle density functional theory (DFT)-based approaches. The band structure alignment is made by using the vacuum energy level as reference. b The evolution of band-edge energies under gradually increasing tensile strains in perovskite films (left panel), and the schematic of the band alignment between tensile strain/strain-free film and hole transport layer in solar cell. c Ultraviolet (UV)–visible (Vis) absorption spectra and PL spectra under tensile strain, strainfree, and compressive strain conditions. d The $J-V$ characteristics of the hole-only space-charge-limited current (SCLC) device with/without residual tensile strain \n\nIn addition to the above two main effects, the tensile strain induced downward shift of valence bands may also result in the deeper defect levels of the perovskite films with the assumption of defect energy levels being not sensitive to strain. This is supported by the experimental observation that the hydrostatic pressure render the shallower defect energy levels of hybrid halide perovskites59,60. As demonstrated above we also observed the prolonged carrier lifetime in the strain-free samples (Supplementary Fig. 14). \n\n# Discussion \n\nIn conclusion, we revealed gradient evolution of residual strain in the vertical direction of the mixed halide perovskite film by depth-dependent grazing incident X-ray diffraction characterization. The residual strain distribution may be stemmed from composition inhomogeneity and/or gradient thermal stress during film processing. A simple technique was developed to modulate the strain nature (e.g., tensile and compressive) and its gradient over the perovskite film in a controllable manner. This allows us to identify substantial impact of the residual strain gradient on hole carrier dynamics across the perovskite solar cell. First-principle calculations reveal that the strain gradient induces valence bands bending of perovskite absorber and thus affects the interfacial hole dynamics. By reducing the strain gradient of the perovskite film through strain engineering, we achieved substantial improvement in hole carrier transport and extraction across the interface of perovskite absorber/HTM. Consequently, the optimized perovskite solar cell reaches the certified power conversion efficiency of $20.7\\%$ . By demonstrating the impact of residual strain on optoelectronic properties of halide perovskite film, this contribution sheds a light on further understanding the composition-structure-property relationship of halide perovskite system, which may be exploited to further advance the performance of halide perovskite based optoelectronic devices. \n\n# Methods \n\nMaterials. All the commercial materials were used as received without further purification, including ethanol (AR Beijing Chemical Works), Methylamine $(33\\mathrm{wt.\\%}$ in absolute ethanol), Formamidine acetate $99\\%$ , Aldrich), HBr $(48\\mathrm{wt.\\%}$ in water, Sigma-Aldrich), HI $(57\\mathrm{wt.\\%}$ in water, Sigma-Aldrich), $\\mathrm{PbI}_{2}$ ( $99.999\\%$ , SigmaAldrich), $\\mathrm{Pb}{\\mathrm{Br}}_{2}$ $99.999\\%$ , Aldrich), CsI ( $99.90\\%$ Aladdin Industrial Corporation) N, N-dimethylformamide (DMF, $99.99\\%$ , Sigma-Aldrich), Dimethyl sulfoxide (DMSO, $99.9\\%$ , Sigma-Aldrich), chlorobenzene (CB, $99.9\\%$ , Sigma-Aldrich), Spiro-OMeTAD (Lumtec), bis(trifluoromethane)sulfonimide lithium salt $(99.95\\%$ , Aldrich), 4-tertbutylpyridine $(99.9\\%$ , Sigma-Aldrich), acetonitrile $(99.9\\%$ , Sigma-Aldrich), and ITO substrates. The $\\mathrm{HC}(\\mathrm{NH}_{2})_{2}\\mathrm{I}$ and $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Br}$ were prepared according to procedure mentioned in previous work. \n\nPerovskite precursor solutions. The precursor solutions were prepared according to the work delivered by Saliba. \n\nFAMA perovskite solution: The mixed perovskite solution were prepared by mixing FAI $(1.38\\mathrm{M})$ , $\\mathrm{PbI}_{2}$ (1.49 M), MABr $(0.24\\mathrm{M})$ , $\\mathrm{Pb}\\mathrm{Br}_{2}$ (0.26 M) in anhydrous DMF: DMSO 4:1 (v:v) according to previous work with a slight amount of \n\nexcessive $\\mathrm{PbI}_{2}$ . To be convenient, we labeled the mixed perovskite solution with compositions mentioned above as FAMA57. \n\nCsI solutions: CsI solution was deposited by dissolving CsI in pure DMSO with the concentration of $1.5\\mathrm{M}$ . \n\n$(\\mathrm{FAMA})_{(100-x)}\\mathrm{Cs}_{x}$ perovskite solution: $(\\mathrm{FAMA})_{(100-x)}\\mathrm{Cs}_{x}$ perovskite solution was obtained by adding appropriate amount of CsI into $300\\upmu\\mathrm{L}$ FAMA perovskite solution with different cesium concentrations (volume ratio, $x=100\\%\\times V_{\\mathrm{CsI}}/$ $(V_{\\mathrm{CsI}}+300)\\mathrm{\\Omega}$ to achieve the desired cation composition $5\\%$ . \n\nOptimal flipped annealing method for polycrystalline perovskite film. The perovskite film washed by antisolvent was annealed about $20\\mathrm{min}$ at $120^{\\circ}\\mathrm{C}$ through the normal method in order to most of the solvent can escape smoothly, then it was flipped over and annealed $25\\mathrm{min}$ at $120^{\\circ}\\mathrm{C}$ so that the maximum tensile strain in the top surface can be gradually released at the highest temperature. In order to drop down the cooling rate at the same total annealing time, we first transferred the film to a hot stage at $80^{\\circ}\\mathrm{C}$ for $1\\mathrm{min}$ and then transferred to a hot stage at $40^{\\circ}\\mathrm{C}$ for $1\\mathrm{min}$ . All annealing processes are finished in in a nitrogen glove box. \n\nSample preparation and devices fabrication. The ITO substrate was sequentially washed with distilled water, acetone, ethanol, and isopropanol. After $30\\mathrm{min}$ of $\\mathrm{UV}{-}\\mathrm{O}_{3}$ treatments, the $\\mathrm{SnO}_{2}$ electron transport layers (ETLs) were spin-coated on ITO substrates from the $\\mathrm{SnO}_{2}$ colloidal solutions, and annealed on a hot plate at the displayed temperature of $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ in ambient air. For the mixed Acation $\\mathrm{FA}_{0.85}\\mathrm{MA}_{0.15}\\mathrm{Pb}(\\mathrm{I}_{0.85}\\mathrm{Br}_{0.15})_{3}$ and $\\mathrm{FA_{0.85}M A_{0.15}C s_{0.05}P b(I_{0.85}B r_{0.15})_{3}}$ metal halide perovskite layer, one-step method used toluene as antisolvent developed by Saliba was adopted. In detail, the perovskite solutions were spin-coated at $6000\\mathrm{rpm}$ for $30\\mathrm{{s}}$ . Two-hundred microliters of chlorobenzene was dropped on the spinning substrate during the spin-coating step at $10s$ before the end of the procedure. Then, the as-fabricated film were baked at $120^{\\mathrm{o}}\\mathrm{C}$ for $45\\mathrm{{min}}$ in a nitrogen filled glove box. After the perovskite annealing, $30\\upmu\\mathrm{L}$ Spiro-OMeTAD solution doped with LiTFSI and tBP was deposited at $3000\\mathrm{rpm}$ for $30{\\mathrm{~s.}}$ . The hole transport material (HTM) solution was prepared by dissolving $60\\mathrm{mg}$ spiro-OMeTAD, $30\\upmu\\mathrm{L}$ 4-tert-butylpyridine and $35\\upmu\\mathrm{L}$ Li-TFSI/acetonitrile $(260\\mathrm{mg}\\mathrm{\\bar{mL}^{-1}}.$ ) in $1\\mathrm{mL}$ chlorobenzene. Finally, $100{\\mathrm{nm~Ag}}$ was thermally evaporated as counter electrode under a pressure of $5\\times10^{-5}$ Pa on top of the hole transport layer to form the back contact. \n\nFabrication of space-charge limited current devices. The structure of the device was ITO/PEDOT:PSS/perovskite/Spiro-OMeTAD /Au. The ITO glass substrate was treated by ${\\mathrm{UV}}{\\mathrm{-}}{\\mathrm{O}}_{3}$ for $30\\mathrm{min}$ , the PEDOT:PSS was filtered and then spincoated on ITO substrates. $\\mathrm{FA_{0.85}M A_{0.15}P b I_{2.55}B r_{0.45}}$ perovskite film was deposited on the PEDOT:PSS/ITO substrate by spin-coating. After the perovskite annealing, Spiro-OMeTAD layer was deposited and $150\\mathrm{nm}$ Au was thermally evaporated as counter electrode. \n\nCharacterizations. The morphologies and sizes of nanocrystals were characterized by JEOL JEM-2100 transmission electron microscopy (TEM). Scanning electron microscope (SEM) images were measured using Hitachi S4800 fieldemission scanning electron microscopy. XRD patterns were recorded on a Rigaku smartlab X-ray Diffractometer. The cross-section of the device was prepared by focused ion beam (FIB) using a FEI Helios Dualbeam system. The sample was first covered by Pt protection layer deposited by electron beam and ion beam in dualbeam system, and was then milled to thin lamella following standard FIB sample preparation techniques. Due the beam-sensitivity of organic–inorganic hybrid halide perovskite structure, low beam voltage, and current was applied during final cleaning steps. The as-prepared thin lamella was studied by high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) using a FEI Titan G2 microscope equipped by an aberration corrector for probe forming lens, operated at $300\\mathrm{kV}$ . Depthdependent steady-state photoluminescence (PL) measurement was executed by confocal fluorescence microscope and time-resolved photoluminescence data was obtained by FLS980 (Edinburgh Instruments Ltd) with an excitation at 465 nm. The time-of-flight secondary ion mass spectrometry (TOF-SIMS) measurements (Model TOF-SIMS V, ION-TOF GmbH) were performed with the pulsed primary ions from a $\\mathrm{Cs}+$ (3 keV) liquid-metal ion gun and a $^{\\mathrm{Bi+}}$ pulsed primary ion beam for the analysis $(25\\mathrm{keV})$ . Current–voltage characteristics were recorded by using a Keithley 2400 source-measure unit. The typical current–voltage characteristics of the devices were measured using a Keithley 2400 source meter by reverse scanning from 1.2 to $-0.2\\mathrm{V}$ or forward scanning from $-0.2$ to $1.2\\mathrm{V}$ at a scanning speed of $50\\mathrm{mVs^{-1}}$ . The photocurrent was measured under AM1.5G illumination at $100\\mathrm{mW}\\mathrm{cm}^{-2}$ under a by 3A steadystate solar simulator (SS-F5-3A). Light-intensity was calibrated with a National Institute of Metrology (China) calibrated KG5-filtered Si reference cell. The effective area of each cell was $0.102\\mathrm{cm}^{2}$ defined by masks for all the photovoltaic devices discussed in this work. Space-charge limited current measurements were conducted on hole-only ITO/PEDOT:PSS/perovskite/Spiro-OMeTAD/Ag devices. A Keithly 2400 source meter was used to measure the relevant $J{-}V$ curves. The absorption spectra were measured by Hitachi UH4150 spectrophotometer. \n\nExternal quantum efficiencies (EQE) were performed on a solar cell quantum efficiency measurement system (QE-R) supported by Enli Technology Co., Ltd. A calibrated silicon diode with a known spectral response was used as a reference. The transient photovoltage/photocurrent (TPV/TPC) decay measurements were obtained on Molex 180081-4320 simulating one sun working condition, the carriers were excited by a $532\\mathrm{nm}$ pulse laser. The electrochemical impedance spectroscopy (EIS) was determined by the electrochemical workstation (Germany, Zahner Company), employing light emitting diodes driven by Export (Germany, Zahner Company). \n\nFirst-principles calculations. Calculations were performed within the framework of density functional theory (DFT) by using plane-wave pseudopotential methods as implemented in the Vienna Ab initio Simulation Package61,62. The electron−ion interactions were described by the projected augmented wave pseudopotentials63 with the 1s (H), 2s and $2p$ (C), 2s and $2p$ (N), 5s and $5p$ (I) and 5d, 6s and $6p$ (Pb) electrons treated explicitly as valence electrons. We used the generalized gradient approximation formulated by Perdew, Burke, and Ernzerhof64 as the exchange correlation functional. Kinetic Energy cutoff for the plane-wave basis set were set to $400\\mathrm{eV}$ . The k-point meshes with grid spacing of $\\dot{2}\\pi\\times0.03\\mathring{\\mathrm{A}}^{-1}$ were used for electronic Brillouin zone integration. We modeled the perovskite film by using the (001)-oriented six-layers Ruddlesden-Popper phase of $\\mathrm{FAPbI}_{3}$ embedded in a vacuum region of $30\\mathrm{\\AA}$ . The biaxial strains of $1\\%$ , $0.5\\%$ (compressive) and $-0.5\\%$ , $-1\\%$ (tensile) were applied to the film, respectively. The structures under the biaxial strain conditions were optimized by fixing the in-plane structure parameters of Pb–I perovskite framework through total energy minimization with the residual forces on the atoms converged to below $0.{\\overset{\\vartriangle}{0}}2\\ \\mathrm{eV}\\ \\mathring{\\mathrm{A}}^{-1}$ . To properly take into account the long-range van der Waal interactions that play a nonignorable role in the hybrid perovskites involving organic molecules, the vdW-optB86b functional65 was adopted. The alignment of the band structures upon different strains is made by using the vacuum energy as reference. \n\n# Data availability \n\nAll the relevant data are available from the corresponding authors upon reasonable request. \n\nReceived: 16 August 2018 Accepted: 6 January 2019 \nPublished online: 18 February 2019 \n\n# References \n\n1. Jeon, N. J. et al. Compositional engineering of perovskite materials for highperformance solar cells. Nature 517, 476–480 (2016). \n2. Jeon, N. J. et al. Solvent engineering for high-performance inorganicorganic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n3. Saliba, M. et al. Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency. Energy Environ. Sci. 9, 1989 (2016). \n4. Snaith, H. J. et al. Present status and future prospects of perovskite photovoltaics. Nat. Mater. 17, 372–376 (2018). \n5. Xiao, J. W. et al. The emergence of the mixed perovskites and their applications as solar cells. Adv. Energy Mater. 7, 1700491 (2017). \n6. Malinkiewicz, O. et al. Perovskite solar cells employing organic chargetransport layers. Nat. Photon. 8, 128 (2013). \n7. Yang, W. S. et al. Iodide management in formamidinium-lead-halide-based perovskite layers for efficient solar cells. Science 356, 1376–1379 (2017). \n8. Li, X. et al. A vacuum flash–assisted solution process for high-efficiency largearea perovskite solar cells. Science 353, 58–62 (2016). \n9. Wu, W. Q. et al. Molecular doping enabled scalable blading of efficient hole-transport-layer-free perovskite solar cells. Nat. Commun. 9, 1625 (2018). \n10. He, M. et al. Meniscus-assisted solution printing of large-grained perovskite films for high-efficiency solar cells. Nat. Commun. 8, 16045 (2017). \n11. Li, Z. et al. Scalable fabrication of perovskite solar cells. Nat. Rev. Mater. 3, 18017 (2018). \n12. Eperon, G. E. et al. Formamidinium lead trihalide: a broadly tunable perovskite for efficient planar heterojunction solar cells. Energy Environ. Sci. 7, 982–988 (2014). \n13. Jodlowski, A. D. et al. Large guanidinium cation mixed with methylammonium in lead iodide perovskites for $19\\%$ efficient solar cells. Nat. Energy 2, 972 (2017). \n14. Huang, Y. et al. The intrinsic properties of $\\mathrm{FA}_{(1-\\mathrm{x})}\\mathrm{MA}_{\\mathrm{x}}\\mathrm{Pb}\\mathrm{I}3$ perovskite single crystals. J. Mater. Chem. A 5, 8537–8544 (2017). \n15. Saparov, B. et al. Organic-inorganic perovskites: Structural versatility for functional materials design. Chem. Rev. 116, 4558 (2016). \n16. Gratia, P. et al. Intrinsic halide segregation at nanometer scale determines the high efficiency of mixed cation/mixed halide perovskite solar cells. J. Am. Chem. Soc. 138, 15821–15824 (2016). \n17. Philippe, B. et al. Chemical distribution of multiple cation $\\mathrm{Rb^{+}}$ , ${\\mathrm{Cs^{+}}}$ , $\\mathrm{MA^{+}}$ , and $\\mathrm{FA^{+}}$ ) perovskite materials by photoelectron spectroscopy. Chem. Mater. \n29, 3589–3596 (2017). \n18. Abdi-Jalebi, M. et al. Maximizing and stabilizing luminescence from halide perovskites with potassium passivation. Nature 555, 497 (2018). \n19. Brennan, M. C. et al. Light-induced anion phase segregation in mixed halide perovskites. ACS Energy Lett. 3, 204–213 (2018). \n20. Bush, K. A. et al. Controlling thin-film stress and wrinkling during perovskite film formation. ACS Energy Lett. 3, 1225–1232 (2018). \n21. Zheng, X. et al. Improved phase stability of formamidinium lead triiodide perovskite by strain relaxation. ACS Energy Lett. 1, 1014–1020 (2016). \n22. Zhao, J. et al. Strained hybrid perovskite thin films and their impact on the intrinsic stability of perovskite solar cells. Sci. Adv. 3, eaao5616 (2017). \n23. Prasanna, R. et al. Band gap tuning via lattice contraction and octahedral tilting in perovskite materials for photovoltaics. J. Am. Chem. Soc. 139, \n11117–11124 (2017). \n24. Murali, B. et al. Temperature-induced lattice relaxation of perovskite crystal enhances optoelectronic properties and solar cell performance. J. Phys. Chem. Lett. 8, 137–143 (2017). \n25. MD, P. et al. Crystallization kinetics and morphology control of formamidinium–cesium mixed-cation lead mixed-halide perovskite via tunability of the colloidal precursor solution. Adv. Mater. 29, 1607039 (2017). \n26. Feng, J. et al. Strain-engineered artificial atom as a broad-spectrum solar energy funnel. Nat. Photon. 6, 866–872 (2012). \n27. Kurdi, M. E. et al. Control of direct band gap emission of bulk germanium by mechanical tensile strain. Appl. Phys. Lett. 96, 1738 (2010). \n28. Ahn, G. H. et al. Strain-engineered growth of two-dimensional materials. Nat. Commun. 8, 608 (2017). \n29. Hubbard, S. M. et al. Effect of strain compensation on quantum dot enhanced GaAs solar cells. Appl. Phys. Lett. 92, 5014–5166 (2008). \n30. Oshima, R. et al. Strain-compensated InAs/GaNAs quantum dots for use in high-efficiency solar cells. Appl. Phys. Lett. 93, 083111 (2008). \n31. Leblebici, S. Y. et al. Facet-dependent photovoltaic efficiency variations in single grains of hybrid halide perovskite. Nat. Energy 1, 16093 (2016). \n32. Vailionis, A. et al. Misfit strain accommodation in epitaxial A B O 3 perovskites: Lattice rotations and lattice modulations. Phys. Rev. B 83, 064101 (2011). \n33. Benediktovitch, A. et al. Stress gradient analysis by noncomplanar X-ray diffraction and corresponding refraction correction. Adv. Mater. Res 996, \n162–168 (2014). \n34. Stefenelli, M. et al. X-ray analysis of residual stress gradients in TiN coatings by a Laplace space approach and cross-sectional nanodiffraction: a critical comparison. J. Appl. Crystallogr. 46, 1378–1385 (2013). \n35. Chen, Z. et al. Residual stress gradient analysis with GIXRD on ZrO2 thin films deposited by MOCVD. Surf. Coat. Technol. 206, 405–410 (2011). \n36. Zhumekenov, A. A. et al. Formamidinium lead halide perovskite crystals with unprecedented long carrier dynamics and diffusion length. Acs Energy Lett. 1, \n32–37 (2016). \n37. Ahn, N. et al. Highly reproducible perovskite solar cells with average efficiency of $18.3\\%$ and best efficiency of $19.7\\%$ fabricated via lewis base adduct of lead (II) iodide. J. Am. Chem. Soc. 137, 8696 (2015). \n38. Zhifang, S. et al. Symmetrization of the crystal lattice of $\\mathbf{MAPbI}_{3}$ boosts the performance and stability of metal–perovskite photodiodes. Adv. Mater. 29, \n1701656 (2017). \n39. Nah, S. et al. Spatially segregated free-carrier and exciton populations in individual lead halide perovskite grains. Nat. Photon. 11, 285–288 (2017). \n40. Wright, A. D. et al. Electron–phonon coupling in hybrid lead halide perovskites. Nat. Commun. 7, 11755 (2016). \n41. Leijtens, T. et al. Towards enabling stable lead halide perovskite solar cells; interplay between structural, environmental, and thermal stability. J. Mater. Chem. A 5, 11483–11500 (2017). \n42. Yin, W.-J. et al. Unusual defect physics in CH3NH3PbI3 perovskite solar cell absorber. Appl. Phys. Lett. 104, 063903 (2014). \n43. Xiao, Z. et al. Progress in theoretical study of metal halide perovskite solar cell materials. Adv. Energy Mater. 7, 1701136 (2017). \n44. Chen, H. et al. Molecular engineered hole-extraction materials to enable dopant-free, efficient p-i-n perovskite solar cells. Adv. Energy Mater. 7, \n1700012 (2017). \n45. Rajagopal, A. et al. Highly efficient perovskite–perovskite tandem solar cells reaching $80\\%$ of the theoretical limit in photovoltage. Adv. Mater. 29, 1702140 (2017). \n46. Sherkar, T. et al. Recombination in perovskite solar cells: Significance of grain boundaries,interface traps, and defect ions. Acs Energy Lett. 2, 1214–1222 (2017). \n47. Pankaj, Y. et al. The role of rubidium in multiple-cation-based high-efficiency perovskite solar cells. Adv. Mater. 29, 1701077 (2017). \n48. Li, H. et al. Carbon quantum dots/TiOx electron transport layer boosts efficiency of planar heterojunction perovskite solar cells to $19\\%$ . Nano Lett. 17, 2328 (2017). \n49. Zhou, H. et al. Photovoltaics. Interface engineering of highly efficient perovskite solar cells. Science 345, 542–546 (2014). \n50. Yang, D. et al. Functionality-directed screening of $\\mathrm{Pb}$ -free hybrid organicinorganic perovskites with desired intrinsic photovoltaic functionalities. Chem. Mater. 29, 524–538 (2017). \n51. Yin, W. J. et al. Halide perovskite materials for solar cells: a theoretical review. J. Mater. Chem. A 3, 8926–8942 (2015). \n52. Brandt, R. E. et al. Identifying defect-tolerant semiconductors with high minority-carrier lifetimes: beyond hybrid lead halide perovskites. MRS Commun. 5, 265–275 (2015). \n53. Giorgi, G. et al. Small photocarrier effective masses featuring ambipolar transport in methylammonium lead iodide perovskite: A density functional analysis. J. Phys. Chem. Lett. 4, 4213–4216 (2013). \n54. HS, N. et al. Investigating the role of 4-tert butylpyridine in perovskite solar cells. Adv. Energy Mater. 7, 1601079 (2017). \n55. Kobayashi, T. et al. $\\mathrm{Cu(In,Ga)Se}_{2}$ thin film solar cells with a combined ALD$Z\\mathrm{n}(\\mathrm{O},\\mathrm{S})$ buffer and MOCVD-ZnO:B window layers. Sol. Energy Mater. Sol. Cells 119, 129–133 (2013). \n56. Chen, Q. et al. Controllable self-induced passivation of hybrid lead iodide perovskites toward high performance solar cells. Nano Lett. 14, 4158 (2014). \n57. Jeng, J. Y. et al. CH3NH3PbI3 perovskite/fullerene planar-heterojunction hybrid solar cells. Adv. Mater. 25, 3727–3732 (2013). \n58. Hawash, Z. et al. Interfacial modification of perovskite solar cells using an ultrathin MAI layer leads to enhanced energy level alignment, efficiencies, and reproducibility. J. Phys. Chem. Lett. 8, 3947–3953 (2017). \n59. Kong, L. et al. Simultaneous band-gap narrowing and carrier-lifetime prolongation of organic-inorganic trihalide perovskites. Proc. Natl Acad. Sci. U.S.A 113, 8910–8915 (2016). \n60. Gang, L. et al. Pressure-induced bandgap optimization in lead-based perovskites with prolonged carrier lifetime and ambient retainability. Adv. Funct. Mater. 27, 1604208 (2017). \n61. Kresse, G. et al. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comp. Mater. Sci. 6, 15–50 (1996). \n62. Kresse, G. et al. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n63. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n64. Perdew, J. P. et al. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n65. Klimeš, J. et al. Van der Waals density functionals applied to solids. Phys. Rev. B 83, 195131 (2011). \n\n# Acknowledgements \n\nWe acknowledge funding support from National Key Research and Development Program of China Grant No. 2016YFB0700700, National Natural Science Foundation of China (51673025 and 51672008), and the Young Talent Thousand Program. L.Z. acknowledges the support of the NSFC (Grant 61722403 and 11674121), National Key Research and Development Program of China (Grant 2016YFB0201204), and Program for JLU Science and Technology Innovative Research Team. P.C. acknowledges the support of the Project of State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology under Grant ZDKT18-01. Calculations were performed in part at High Performance Computing Center of Jilin University. S.Y. and B.H. appreciate Shenzhen Peacock Plan (KQTD2016053015544057) and Nanshan Pilot Plan (LHTD20170001). We appreciate the insightful technical discussion and experimental support with Mr. Gang Tang and Mr. Yizhou Zhao. We would like to thank Enli Technology for providing the depth-dependent PL measurement and EQE measurement. \n\n# Author contributions \n\nQ.C. and C.Z. conceived the idea and designed the experiments. Both C.Z. and X.N. were involved in all the experimental parts. N.L, H.C.Z. and Y.C carried out the PL measurement, P.L. finished EIS measurements, G.Y. and Y.L. finished TEM measurements. X.K. and M.S. provided the insightful technical assistance for TEM analysis. Y.F., X.H. and G.N. performed the theoretical calculations, L.Z. and Y.F. analyzed the results. S.Y., Y.B. and C.H. performed the TOF-SIM measurement. P.C. provided theoretical support for firstprinciples calculations. All the authors were involved in the discussion for data analysis and commented on the manuscript, and Y.L., L.Z., H.Z., Q.C. and C.Z. co-wrote the paper. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-08507-4. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks Anna Osherov and the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1038_s41467-019-13436-3", + "DOI": "10.1038/s41467-019-13436-3", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-13436-3", + "Relative Dir Path": "mds/10.1038_s41467-019-13436-3", + "Article Title": "Zinc anode-compatible in-situ solid electrolyte interphase via cation solvation modulation", + "Authors": "Qiu, HY; Du, XF; Zhao, JW; Wang, YT; Ju, JW; Chen, Z; Hu, ZL; Yan, DP; Zhou, XH; Cui, GL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "The surface chemistry of solid electrolyte interphase is one of the critical factors that govern the cycling life of rechargeable batteries. However, this chemistry is less explored for zinc anodes, owing to their relatively high redox potential and limited choices in electrolyte. Here, we report the observation of a zinc fluoride-rich organic/inorganic hybrid solid electrolyte interphase on zinc anode, based on an acetamide-Zn(TFSI)(2) eutectic electrolyte. A combination of experimental and modeling investigations reveals that the presence of anioncomplexing zinc species with markedly lowered decomposition energies contributes to the in situ formation of an interphase. The as-protected anode enables reversible (similar to 100% Coulombic efficiency) and dendrite-free zinc plating/stripping even at high areal capacities (>2.5 mAh cm(-2)), endowed by the fast ion migration coupled with high mechanical strength of the protective interphase. With this interphasial design the assembled zinc batteries exhibit excellent cycling stability with negligible capacity loss at both low and high rates.", + "Times Cited, WoS Core": 697, + "Times Cited, All Databases": 716, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000498795200001", + "Markdown": "# Zinc anode-compatible in-situ solid electrolyte interphase via cation solvation modulation \n\nHuayu $\\mathsf{Q i u}^{1,2,4}$ , Xiaofan $\\mathsf{D u}^{1,4}$ , Jingwen Zhao1\\*, Yantao Wang1, Jiangwei Ju1, Zheng Chen1, Zhenglin Hu1, Dongpeng Yan $\\textcircled{1}$ 3, Xinhong Zhou2\\* & Guanglei Cui1\\* \n\nThe surface chemistry of solid electrolyte interphase is one of the critical factors that govern the cycling life of rechargeable batteries. However, this chemistry is less explored for zinc anodes, owing to their relatively high redox potential and limited choices in electrolyte. Here, we report the observation of a zinc fluoride-rich organic/inorganic hybrid solid electrolyte interphase on zinc anode, based on an acetamide- $.Z_{n}(\\mathsf{T F S}|)_{2}$ eutectic electrolyte. A combination of experimental and modeling investigations reveals that the presence of anioncomplexing zinc species with markedly lowered decomposition energies contributes to the in situ formation of an interphase. The as-protected anode enables reversible $\\mathord{\\sim}100\\%$ Coulombic efficiency) and dendrite-free zinc plating/stripping even at high areal capacities $(>2.5\\mathsf{m A h c m^{-2}},$ ), endowed by the fast ion migration coupled with high mechanical strength of the protective interphase. With this interphasial design the assembled zinc batteries exhibit excellent cycling stability with negligible capacity loss at both low and high rates. \n\nM(eulnMteiIrvBgasly)enstat-orierongheig $(\\mathrm{Mg}^{2+}$ $Z\\mathrm{n}^{2+}$ $\\mathrm{Ca}^{2+}$ e tshceetailcr.e atbatauitnotednrairneyst hly desirable for larg systems because of reservoir, environmental friendliness, intrinsic safety and comparable or even superior capacities to those of Li-ion counterparts1–5. Among the anode materials developed for MIBs, metallic $Z\\mathrm{n}$ offers a better insensitivity in oxygen and humid atmosphere6,7, which broadens the availability of electrolytes and lowers the handling and processing costs. Additional enthusiasm for the $Z\\mathrm{n}$ chemistry is stimulated by its high volumetric capacity $(5855\\mathrm{Ah\\L^{-1}},$ ), superior to Li $(206\\dot{1}\\mathrm{Ah}\\mathrm{L}^{-1}.$ ), Ca $(2072\\mathrm{Ah^{\\prime}L^{-1}},$ , and $\\mathbf{Mg}$ $\\begin{array}{r l}{~}&{{}\\bigcup_{\\mathbf{\\delta}}\\ (3833\\operatorname{Ah}^{-1})}\\end{array}$ counterparts8. Indeed, since the “rediscovery” of the rechargeable $Z\\mathrm{n}$ -ion batteries (ZIBs), new cathode materials and $Z\\mathrm{n}$ -storage mechanisms have enjoyed substantial achievements in the last few years8,9. However, there is a fly in the ointment: the suboptimal cycling efficiency resulting from uncontrolled dendrites and notorious side-reactions occurred at the $Z\\mathrm{n}$ -electrolyte interface (especially for aqueous electrolytes) restricts the development of real rechargeable ZIBs and their broad applicability6,10,11. \n\nActually, intensive previous investigations have been dedicated to handling these $Z\\mathrm{n}$ -related issues, such as introducing additives into electrolytes or electrodes, constructing nanoscale interface and designing hierarchical structures12–15, but still suffer from a low Coulombic efficiency (CE). Very recently, highly concentrated electrolytes were introduced to stabilize the Zn anode by regulating the solvation sheath of the divalent cation16–18, which is a feasible approach to reducing water-induced sidereactions and improving Zn plating/stripping CE. Unfortunately, the underlying mechanism on the inhibition of Zn dendrites has not been entirely understood yet. Even today, the Zn-electrolyte interface instability remains challenging, and a broadly applicable interfacial protection strategy is highly desired yet largely unexplored, especially compared with the rapid progress regarding the effective utilization for alkaline metal (Li or Na, etc.) anodes. \n\nWhen encountered with a similar dilemma of intrinsic limitations on anodes, Li-ion batteries (LIBs) offer a tactful response: in situ formation of a solid electrolyte interphase (SEI). Admittedly, this SEI is highly permeable for Li ions and prevents excess Li consumption by blocking solvents and electrons19,20. Importantly, via electrolyte modulation (e.g., introduction of F-rich species), additional unusual functionalities can also be achieved, in particular concerning the dendrite suppression and long-term cycling for Li-metal batteries at high CE or high rate20,21. However, such SEI response has always been associated with aprotic electrolytes. Given the much higher redox potential of $Z\\mathrm{n}\\dot{/}Z\\mathrm{n}^{2+}$ couple $(-0.76\\mathrm{V}$ vs. NHE) compared with that of $\\mathrm{Li/Li^{+}}$ $\\left(-3.04\\mathrm{V}\\right.$ vs. NHE), routine anions and organic solvents are difficult to decompose reductively before $Z\\mathrm{n}$ deposition. Despite the great appeal for aqueous Zn anodes, the competitive $\\mathrm{H}_{2}$ evolution reaction inevitably occurred during each recharging cycle makes this in situ protection mechanism infeasible22, while the local $\\mathrm{\\pH}$ change induces the formation of ionically insulating byproducts which has been also faced in other multivalent metal anodes23,24. Hence, another possibility for designing reliable $Z\\mathrm{n}$ -anode SEI is to look beyond the conventional water-based and organic-solvent electrolytes. \n\nWe explore the in situ formation of a $\\mathrm{ZnF}_{2}$ -rich, ionically permeable SEI layer to stabilize $Z\\mathrm{n}$ electrochemistry, by manipulating the electrolyte decomposition based on a eutectic liquid with peculiar complexing ionic speciation. Regulating the solvation structure (either locally or totally) has been verified and found to be an effective strategy for shifting the reductive potentials of electrolyte components20,21,25; however, due to the high charge density of $Z\\mathrm{n}^{2+}$ , $\\mathrm{{\\dot{Z}n}}$ salts do not readily dissociate in common solvents over a wide concentration range, resulting in limited control over the coordination properties. As a new class of versatile fluid materials, the deep eutectic solvents (DESs), generally created from eutectic mixtures of Lewis or Brønsted acids and bases that can associate with each other, have been found to be interesting on account of their excellent dissolution ability, even for the multivalent metal salts and oxides26,27. Remarkably, characterized by highly adjustable compositions and rich intermolecular forces, DESs are also expected to accommodate concentrated ionic species and have aided the development of alternative media for electrochemistry27,28. \n\nHere in this work, based on a new DES composed of acetamide (Ace) and $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ , a large portion of $\\bar{\\mathrm{TFSI^{-}}}$ is found to coordinate to $Z\\mathrm{n}^{2+}$ directly in the form of anion-containing $Z\\mathrm{n}$ complexes $\\mathrm{'}[\\mathrm{ZnTFSI}_{m}(\\mathrm{Ace})_{n}]^{(2-m)+}$ , $m=1{-}2$ , $n=1-3\\mathrm{\\cdot}$ ), which induces the preferential reductive decomposition of $\\mathrm{TFSI^{-}}$ prior to $Z\\mathrm{n}$ deposition. Correspondingly, a well-defined anion-derived SEI layer compositionally featured with a rich content of mechanically rigid $\\mathrm{ZnF}_{2}$ and $Z\\mathrm{n}^{2+}$ -permeable organic (S and N) components can be obtained during the initial cycling. This SEIcoated $Z\\mathrm{n}$ anode is stabilized to sustain long-term cycling $(>2000$ cycles; average $Z\\mathrm{n}$ plating/stripping CE of $99.7\\%$ ), and enables a highly uniform Zn deposition even at a high areal capacity of 5 mAh $\\mathrm{cm}^{-2}$ , without short-circuit or surface passivation. Moreover, the transformed interfacial chemistry has been further confirmed by the unprecedented reversibility of $Z\\mathrm{n}$ redox reactions upon implanting the SEI-coated $Z\\mathrm{n}$ anodes into cells with routine aqueous electrolytes. With this in situ anode protection, ZIBs paired with a $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cathode accomplish the cyclability of $92.8\\%$ capacity retention over 800 cycles $(99.9\\%$ CEs after activation), and are demonstrated to cycle up to 600 times along with a capacity fading of only $0.003\\dot{5}\\%\\mathrm{cycle}^{-1}$ under a practical cathode-anode coupling configuration $(\\mathrm{Zn};\\mathrm{V}_{2}\\mathrm{O}_{5}$ mass ratio of 1:1; areal capacity of $>0.{\\dot{7}}\\mathrm{mAh}\\mathrm{\\bar{c}m}^{-2},$ . As per our knowledge, it is the first successful attempt to in situ construct reliable SEI on $Z\\mathrm{n}$ anode, providing fresh insights for all multivalent chemistries confronted with the same requirements at anodes. \n\n# Results \n\nThe new $\\mathbf{Zn(TFSI)}_{2}/\\mathbf{Ace}$ eutectic solution and physicochemical properties. Recent progress on new electrolytes has demonstrated that better control over the metal coordination environment provides more possibilities for achieving unique properties beyond routine views, such as significantly extended electrochemical window, enhanced oxidative/reductive stability and unusual ion-transport behavior29. In fact, there have been reports on $\\mathrm{ZnCl}_{2}$ -based DESs, in which various complex anionic (e.g., $[\\mathrm{ZnCl}_{3}]^{-}$ , $[\\mathrm{ZnCl}_{4}]^{2-},$ and $[\\mathrm{Zn}_{3}\\mathrm{Cl}_{7}]^{-})$ and cationic (e.g., $\\mathrm{[}Z\\mathrm{nCl}$ $(\\mathrm{HBD})_{n}]^{+}$ ; HBD, hydrogen bond donor) $Z\\mathrm{n}^{2+}$ species can be detected30,31. The Cl-containing solutions, however, are corrosive to common battery components especially at high operation voltages, and are not readily available in forming a stable and ionically conducting interphase for $Z\\mathrm{n}$ anodes. As an alternative anion to form DESs, $\\mathrm{TFSI^{-}}$ is generally considered to be a decomposition source to promote the formation of uniform SEI and thus has aroused our concern12,32. Besides, the binding energy of $\\mathrm{TFSI^{-}}$ to metal ions appears to be relatively lower compared with those of other conventional anions such as $\\mathrm{BF_{4}}^{-}$ , $\\mathrm{PF}_{6}{}^{-}$ , allowing the TFSI-based salts to dissociate easily33,34. Based on the above considerations, the $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ -based eutectic solvent (ZES) with Ace as the HBD was selected as a promising $Z\\mathrm{n}$ electrolyte. \n\nAs shown in Supplementary Fig. 1, the ZESs are homogenous and transparent liquids at ambient-temperature when $Z\\mathrm{n}(\\mathrm{\\bar{T}F S I})_{2}$ and Ace were blended in a predetermined molar ratio range (1:9 −1:4). Correspondingly, they are denoted as ZES $_{1:x}$ solutions $(x=4,5,7,$ and 9). The lowest-eutectic temperature of ZES is found to be $-51.51^{\\circ}\\mathrm{C}$ at a molar ratio of 1:9, and rises to $-35.70^{\\circ}\\mathrm{C}$ with the molar ratio increased to 1:4 (Supplementary Fig. 2 and Supplementary Table 2). Furthermore, no phase change is observed in all ratios blow $100^{\\circ}\\mathrm{C},$ and weight losses are only about $4.3\\%$ (1:9) and $3.3\\%$ (1:4) after heating at $100^{\\circ}\\dot{\\mathrm{C}}$ (Supplementary Figs. 2, 3), reflecting the thermal adaptability of ZESs in the operating temperature region. This wide temperature range of liquid state is in contrast to the highly concentrated electrolytes that suffer from salt precipitation at low temperatures35; simultaneously, the cost issue of the salt-concentrated method can be alleviated29. \n\nSolution structure analysis of ZES. The formation mechanism of the ZES was explored by various spectrum analyses. The Raman bands at 3354 and $31\\dot{5}7\\mathrm{cm}^{-1}$ in solid Ace correspond to the asymmetric and symmetric NH stretching, respectively (Fig. 1a, left). Upon the introduction of $Z\\mathrm{n(TFSI)}_{2}\\mathrm{.}$ , the $3354\\mathrm{cm}^{-1}$ band moves to $3380\\mathrm{cm}^{-1}$ while the $3157\\mathrm{cm}^{-1}$ band disappears, suggesting the breaking of H-bonding between Ace molecules. The $\\mathrm{SO}_{3}$ and $\\mathrm{CF}_{3}$ groups of $\\mathrm{TFSI^{-}}$ are proved to be sensitive to the cation–anion and anion–solvent interactions36,37. Once eutectic liquid formed, there is a strong interaction between the $\\mathrm{NH}_{2}$ group on Ace and the $\\mathrm{SO}_{2}$ group on $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ , as implied by the overlap of the bands at $11\\bar{50}\\mathrm{cm}^{-1}$ and $1128\\mathrm{cm}^{-1}$ (Fig. 1a, right)38,39. From fourier transform infrared spectroscopy (FTIR) spectra of ZESs (the left panel of Fig. 1b), an evident change appears at the $\\scriptstyle{\\mathrm{C=O}}$ stretching region of Ace, where the $1665\\mathrm{{cm}^{\\circ}\\dot{\\bar{\\mathbf{\\theta}}}\\mathbf{1}}$ band redshifts slightly to $16\\bar{5}4\\mathrm{cm}^{-1}$ accompanied by obvious broadening in comparison to the pristine Ace. This is in line with the formation of metal-oxygen coordination between $Z\\mathrm{n}^{2+}$ and $\\scriptstyle{\\mathrm{C=O}}$ group (Fig. 1e)39–41. These intermolecular interactions between components jointly weaken the respective bonds of pristine components, resulting in eutectic solutions (for more details, see Supplementary Figs. 4, 5). \n\nFor the highly concentrated electrolytes proposed for LIBs, organic anions tend to coordinate to $\\mathrm{Li^{+}}$ and exist dominantly in associated states (i.e., contact ion pairs or ionic aggregates), which effectively tunes the molecular frontier orbit properties of the electrolyte solutions42. In theory, this strategy can also be anticipated in multivalent metal electrochemistries, but no one has yet achieved it partially due to shortage of reliable electrolyte systems at present. Inspirationally, the associated $Z\\mathrm{n}^{2+}{\\cdot}\\mathrm{TFSI}^{-}$ states have been found by reasonably introducing a neutral ligand (i.e., Ace) to create anion-containing $Z\\mathrm{n}^{2+}$ species in this work, which is verified in detail below Fig. 1b (right panel) compares the shift of the $\\upsilon_{s}$ (SNS) peak $(\\mathrm{TFSI}^{-})^{43,44}$ as the salt concentration increases, with crystalline $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ as the reference (bottom trace). Apparently, this vibration mode is rather susceptible to the change of the $\\mathrm{TFSI^{-}}$ environment42, slightly drifting from 742.7 $\\mathrm{cm}^{-\\widetilde{1}}$ at 1:9 to $741.9\\mathrm{cm}^{-1}$ at 1:4. Essentially, the latter is identical to that in crystal lattice $(741.6\\mathsf{c m}^{-1},$ ), indicative of a possible pronounced interionic attraction in $\\mathrm{ZESs^{43}}$ . Turning to the Raman vibration mode of $\\mathrm{TFSI^{-}}$ at the same region (Fig. 1c), a deconvolution analysis shows that the Raman band consists of three modes at 740, 744, and $748/747\\mathrm{cm}^{-1}$ , arising from free anions (FA)- $\\scriptstyle\\left(\\#Z\\ n^{2+}=0\\right)$ , loose ion pairs (LIP)- $\\scriptstyle(\\#Z\\ n^{2+}=1)$ ), and intimate ion pairs (IIP)- $(\\#\\mathrm{Zn}^{2+}=\\dot{1})$ ), respectively22,37,45. In all cases of the ZES system, albeit without obvious ionic aggregates (AGG; the anions are coordinated to two or more cations)37, the ubiquitous presence of cation–anion coordination can be identified. In 1:7 and 1:9 solutions, the majority of $\\mathrm{TFSI^{-}}$ anions exist as long-lived LIPs, suggesting the dominant monomeric $Z\\mathrm{n}$ species coordinated by $\\mathrm{\\bar{TFSI^{-}}}$ , while the ionic association becomes stronger with more IIPs formed at relatively higher salt contents (1:4 and 1:5 solutions) (Fig. 1d). Effects related to salt concentration are also imposed on drastic variation in viscosity and ion conductivity (Supplementary Fig. 13c). \n\nThe high-resolution mass spectra (HRMS) of ZESs testify the existence of LIPs and IIPs in all given ratios. Typically, distinct signals of various cationic $\\mathrm{TFSI^{-}}$ -containing complexes ( $[Z\\mathrm{nTFSI}$ $(\\mathrm{Ace})]^{+}$ at $m/z=403$ , $\\scriptstyle[Z\\mathrm{nTFSI}({\\mathrm{Ace}})_{2}]^{+}$ at $m/z=462$ , and $\\scriptstyle[\\mathrm{ZnTFSI}(\\mathrm{Ace})_{3}]^{+}$ at $m/z=521$ ) can be detected, but without evidence of free $Z\\mathrm{n}^{2+}$ ions (Supplementary Fig. 6). Moreover, the variation trend of these cationic peak intensities qualitatively indicates a more pronounced ionic association upon increasing the $Z\\mathrm{n}$ -salt content, in line with the above Raman results (Fig. 1c, d). It should be noted that the only anionic species of $\\mathrm{TFSI^{-}}$ found in HRMS suggests a low possibility of anionic $Z\\mathrm{n}$ complexes (monomeric) with more than two associated $\\mathrm{TFSI^{-}}$ anions (Supplementary Fig. 7). \n\nTheoretical simulations were performed to further identify the ion speciation of ZESs. In both cases of mixtures (1:7 and 1:4), molecular dynamics (MD) simulations predict a competition between the Ace and $\\mathrm{TFSI^{-}}$ for coordination to $Z\\mathrm{n}^{2+}$ cations (Supplementary Fig. 8). For the 1:7 ratio, one $\\mathrm{TFSI^{-}}$ anion (on average) could be observed in each $Z\\mathrm{n}^{2+}$ primary solvation sheath, typically in the form of the $[\\mathrm{ZnTFSI}(\\mathrm{Ace})_{2}]^{+}$ solvate (Supplementary Fig. 8a, b). However, in $1{:}4~\\mathrm{ZES}$ , where only four Ace molecules per $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ are involved in eutectic solution formation, a lower Ace population is available for $Z\\mathrm{n}^{2+}$ solvation and H-bonding with $\\bar{\\mathrm{TFSI^{-}}}$ anions simultaneously42; instead, more $\\mathrm{TFSI^{-}}$ anions enter the $Z\\mathrm{n}^{2+}$ solvation sheath (Supplementary Fig. 8c, d). The fraction of neutral $Z\\mathrm{n}$ complexes coordinated by two $\\mathrm{TFSI^{-}}$ anions is thus expected to increase, whereas no three $\\mathrm{TFSI^{-}}$ coordination case was found (Supplementary Fig. 8d). Apparently, ZES is a system featured with the existence of anion-associated $Z\\mathrm{n}$ solvates, and the ionic interplay strength can be tuned through simple regulation of the $Z\\mathrm{n}$ $(\\mathrm{TFSI})_{2}/{\\it A}$ Ace ratio. By virtue of structural flexibility, the $\\mathrm{TFSI^{-}}$ anion may be coordinated in varying ways to $Z n^{\\dot{2}+}$ cations37, incurring dynamic equilibria of cationic or neutral species with various configurations (Fig. 1g). \n\nGiven the fact that $\\mathrm{TFSI^{-}}$ is more likely to form bidentate coordination to a single cation than other common anions (i.e., $\\mathrm{PF_{4}}^{-}$ , $\\mathrm{ClO}_{4}{}^{-}$ , and $\\mathrm{BF_{4}}^{-}$ )46, the local atomic configurations of $Z\\mathrm{n}$ complexes were investigated theoretically. The density functional theory (DFT) geometry optimization of $[\\mathrm{ZnTFSI}(\\mathrm{Aice})_{n}]^{+}$ complexes verifies the preference of the $\\scriptstyle{\\mathrm{C=O}}$ group of Ace and both two O atoms of $\\mathrm{TFSI^{-}}$ for the coordination with the central $Z\\mathrm{n}^{2+}$ cation (Supplementary Figs. 9, 11). The $\\scriptstyle[\\mathrm{ZnTFSI}(\\mathrm{Ace})_{2}]^{+}$ structure with bidentate coordination by $\\mathrm{TFSI^{-}}$ possesses the most uniform molecular electrostatic potential energy surface distribution along with relatively low total binding energy (Fig. 1f and Supplementary Figs. 9, 11, 12), in reasonable agreement with the predominant signal of cationic species observed from HRMS. Note that the steric-hindrance effect caused by the bulky $\\mathrm{TFSI^{-}}$ also dictates the identity of solution species. This can be reflected by the absence of anionic $Z\\mathrm{n}$ solvates and lower tendency of bidentate coordination in $[\\mathrm{ZnTFSI}_{2}(\\mathrm{Ace})_{n}]$ complexes (Supplementary Fig. 10). \n\nElectrochemical and ion-transport properties of the ZES. On the optimization of electrolytes, the ZES with a molar ratio of 1:7 was found to possess a relatively high ionic conductivity (0.31 $\\mathrm{m}\\mathrm{S}\\mathrm{cm}^{-1}.$ ), a low viscosity $(0.789\\mathrm{Pa}{\\cdot}s)$ at $25^{\\circ}\\mathrm{C}.$ as well as an optimum $Z_{\\mathrm{{n}/Z n}}2+$ redox activity (Supplementary Fig. 13 and Supplementary Table 3). Taking the physical/chemical properties and cost factors into consideration, we chose the molar ratio of 1:7 as the main research object (for the selection of the control group see Supplementary Figs. 14, 15). Supplementary Fig. 16 displays the voltametric response of ZES as compared with an aqueous electrolyte of $1\\mathrm{M}\\bar{Z\\mathrm{n(TFSI)}_{2}}$ . It is evident that due to the water-splitting reaction, the potential window of $1\\mathrm{M}\\mathrm{Zn(TFSI)}_{2}$ is restricted to $1.9\\mathrm{V}$ (vs. ${\\mathrm{Zn/Zn}}^{2+}$ ). In contrast, the ZES provides an expanded anodic stability limit of $2.4\\mathrm{V}$ (vs. $Z_{\\mathrm{n/Zn}}2+{\\bar{~}}$ ), also outperforming those of DESs formed by other common Zn salts (e.g., $\\mathsf{\\bar{Z}n(C l O_{4})}_{2},$ $\\mathrm{Zn}(\\mathrm{CH}_{3}\\mathrm{COO})_{2}$ , and $\\mathrm{Zn(BF_{4})_{2}}.$ ) (Supplementary Fig. 17). The features regarding thermal and electrochemical stabilities allow ZES to be coupled with a wide range of highvoltage cathodes and to work at elevated temperatures, enabling elaborate optimizations of operating conditions in batteries. \n\n![](images/91c3373adba9208008d44c37644abf40cdfd56c8b1245c6dfdc521f254b01054.jpg) \nFig. 1 Structure analysis of ZESs and identity of the ionic species. a Raman, b FTIR, and c Fitted Raman spectra of ZESs with different $Z n(T F S|)_{2}/\\mathsf{A c e}$ molar ratios (1:9–1:4). Solid and dashed lines denote experimental spectra and fitting curves, respectively. d Solvate species distribution in ZESs (free anions (FA), loose ion pairs (LIP) and intimate ion pairs (IIP)), all obtained from the fitted Raman spectra. e Schematic diagram of the interplay among $Z n^{2+}$ , $T\\mathsf{F}\\mathsf{S}\\mathsf{I}^{-}$ , and Ace to form eutectic solutions. f Molecular electrostatic potential energy surface of $[Z\\mathsf{n T F S}|(\\mathsf{A c e})_{2}]^{+}$ $C_{2}{\\mathrm{-}}\\mathsf{O}{\\mathrm{-}}\\Pi$ , bidentate coordination of $T\\mathsf{F S l^{-}}$ ) based on density functional theory (DFT) simulation. Electron density from total self-consistent-field (SCF) density (isova $=0.001$ ). $\\pmb{\\mathrm{\\pmb{g}}}$ Illustration of representative environment of active Zn species within the ZES. \n\nIn addition, the ZES exhibits a much higher $Z\\mathrm{n}^{2+}$ transference number (0.572, Supplementary Fig. 18a) as compared with those of other available $Z\\mathrm{n}$ liquid electrolytes $(0.2\\mathrm{-}0.4)^{\\bar{4}7}$ . This effective migration of metal cations is most likely accounted for by the peculiar cationic Zn solvates with tethered anions48, and the resulting limited transport for negative charge carriers, which is analogous to the observations in highly concentrated electrolytes29,49. Furthermore, the high $\\bar{Z}\\mathrm{n}^{\\dot{2}+}$ transference number also implies that the ion-transport manner in ZESs differs from those observed in the conventional dilute electrolytes; the active $Z\\mathrm{n}^{2+}$ species might obey underlying hopping-type iontransport mechanisms $(\\bar{Z_{\\mathrm{n}}}^{2+}$ ions move from one anion to another through Lewis basic sites on $\\mathrm{TFSI^{-}}$ with the aid of Ace matrix)29,49. As shown in Supplementary Fig. 18b, the diffusion coefficient of the active $Z\\mathrm{n}$ species through ZES is $1.66\\times10^{-6}$ $\\mathsf{c m}^{2}\\mathsf{s}^{-1}$ , exceeding ionic liquid-based electrolytes reported50,51. These remarkable kinetic properties make for powering high-rate devices50,52,53. \n\nHigh ${\\bf Z n}/{\\bf Z n}^{2+}$ reversibility and uniform Zn deposits. The CE of $Z\\mathrm{n}$ plating/stripping, the most critical parameter responsible for the redox reversibility, was first investigated in $\\mathrm{Zn/Ti}$ cells with a galvanostatic capacity of $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ $(0.5\\mathrm{mA}\\mathrm{cm}^{-2},$ ) (Fig. 2a; Supplementary Fig. 19). Of note, the CE of the first 10 cycles in ZES rises gradually to above $98.0\\%$ ; instead, the inferior CE of $<70\\%$ was obtained in 1 M $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ (Supplementary Fig. 20a, b) under identical conditions, which could be ascribed to the severe parasitic reactions that simultaneously occurred during Zn deposition17, along with uncontrolled dendrites (Supplementary Fig. 20d)12,54. Interestingly, an overpotential of $0.185\\mathrm{V}$ is required for the 1st cycle in ZES while roughly $0.1\\mathrm{V}$ needed in the following cycles (Fig. 2a, green circle), which suggests the increase in surface area as well as the progressively improved stability induced by stepwise generation of the in situ formed interphase55,56. The relatively lower CE of ZES in initial cycles might originate from the consumption of active $Z\\mathrm{n}^{2+}$ for such interfacial activation. Additional support for our hypothesis comes from the post-mortem scanning electron microscopy (SEM) observation. It is apparent that a protective coating layer formed on the Ti surface deposited by flat and dense Zn (Supplementary Fig. 20c), essentially differing from the tanglesome deposits in $1\\mathrm{\\AA}\\mathrm{Zn(TFSI)}_{2}$ (Supplementary Fig. 20d). As another reliable method16,57, cyclic voltammetry (CV) was further applied to evaluate CE of ZES at an average deposition capacity ${\\sim}0.61$ mAh $\\mathrm{cm}^{-2}$ (Fig. 2b). Corresponding chronocoulometry curves (Fig. 2c) reveal that the plating/stripping is highly reversible; the CE approaches $100\\%$ after the initial 30 conditioning cycles (an average CE of $99.7\\%$ for 200 cycles; see Supplementary Fig. 21). From this aspect, compared with other reported $Z\\mathrm{n}$ electrolytes (see Supplementary Table 4)16,17,58, ZES provides a more promising route for the realization of secondary $Z\\mathrm{n}$ -metal cells to charge for hundreds of times, especially when the excess of $Z\\mathrm{n}$ anode is limited. \n\n![](images/a9d1099e5f6833597652275d4720f427f1738c5caadd66dedd76e6ea89e478b3.jpg) \nFig. 2 Zn plating/stripping behaviors in ZES. a Voltage profiles of galvanostatic Zn plating/stripping with the maximum oxidation potential of $0.5\\mathsf{V}$ (vs. $Z n/Z n^{2+};$ in ZES at a rate of $0.5\\mathsf{m A c m}^{-2}$ $(1.0\\mathsf{m A h c m}^{-2},$ . The working and counter electrodes are $\\bar{\\mathsf{T i}}$ and Zn, respectively. b Cyclic voltammetry (CV) curves of $Z n$ plating/stripping in ZES at a scan rate of $1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ with a potential range of $-0.5\\substack{-1.2\\vee}$ and an average deposition capacity of $\\sim0.61\\mathsf{m A h c m}^{-2}$ . The working and counter electrodes are Ti and $Z\\mathsf{n}.$ , respectively. c Chronocoulometry curves of $Z n$ plating/stripping in ZES based on CV. Voltage responses of $Z n/Z n$ symmetric cells d in ZES and 1 M $Z_{ Ḋ }\\mathsf{n}(\\mathsf{T F S l})_{2}$ electrolytes at $0.1\\mathsf{m A c m}^{-2}$ $(0.05\\mathsf{m A h c m^{-2}}$ for each half cycle) for 1000 cycles (insets: the optical images of the cycled Zn after 180 cycles in 1 M $Z\\mathsf{n}({\\mathsf{T F S l}})_{2}$ (left) and 2000 cycles in ZES (right)), and e in ZES electrolyte (inset: in 1 $M Z n({\\mathsf{T F S}}|)_{2}$ electrolyte) at $1\\mathsf{m A c m}^{-2}$ $\\mathsf{\\langle0.5m A h c m^{-2}}$ for each half cycle). \n\nThe superior performance of ZES for supporting the Zn anode was also demonstrated under galvanostatic conditions in a $Z_{\\mathrm{{n}/Z_{\\mathrm{{n}}}}}$ symmetric configuration. Despite of a slightly larger polarization, all cells using ZES exhibit more sustainable electrochemical cycling in contrast to those with $\\begin{array}{r}{\\mathrm{{1}}\\mathrm{{M}}\\mathrm{{Zn}}(\\mathrm{{TFSI}})_{2}}\\end{array}$ . As viewed from Fig. 2d, the overpotential experienced a gradual decrease (from 55 to $39\\mathrm{mV}$ ) upon cycling at $0.1\\mathrm{mA}\\mathrm{cm}^{-2}$ in ZES, conforming to the formation process of SEI. As the rate was raised to $0.{\\overset{\\sim}{5}}\\operatorname*{mA}\\operatorname{cm}^{-2}$ , the same cell with ZES continued to operate steadily for another $1000\\mathrm{h}$ (Supplementary Fig. 22a). Note that the surface morphology of cycled $Z\\mathrm{n}$ in ZES is visually uniform (Fig. 2d inset right and Supplementary Fig. 22c), while characteristic $Z\\mathrm{n}$ protrusions are shown in the case using $1\\mathrm{M}$ $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ (Fig. 2d inset left and Supplementary Fig. 22b). Even cycled at an elevated rate of $1\\mathrm{mA}\\mathrm{\\dot{c}}\\mathrm{\\dot{m}}^{-2}$ and a capacity of 0.5 mAh $c\\mathrm{m}^{-2}$ , the $Z_{\\mathrm{{n}/Z_{\\mathrm{{n}}}}}$ cell with ZES also maintains an impressive stability without voltage fluctuation, which lays the foundation for designing high-rate ZIBs. In sharp contrast, an erratic voltage response with the rapidly rising overpotential occurred after only 15 cycles in 1 $\\bar{\\Lambda}\\ \\mathrm{\\bar{Zn}(\\mathrm{\\bar{TFSI})}}_{2}$ (Fig. 2e inset). Given that side-reactions at the electrolyte–electrode interface are considered to be more competitive at relatively low rates12, further interrogation of the ZES electrolyte was carried out at $0.01{-}0.05\\operatorname*{mA}\\dot{\\operatorname{cm}}^{-2}$ (charge/discharge interval being extended to $10\\mathrm{{h}}$ , Supplementary Fig. 23). The $Z_{\\mathrm{{n}}/Z_{\\mathrm{{n}}}2+}$ redox reactions remain reversible and steady with a cycling life over $200\\mathrm{h}$ . \n\nThe $Z\\mathrm{n}$ -electrolyte interface stability has been detected by the sensitive electrochemical impedance spectroscopy (EIS). The charge-transfer resistance of symmetric $Z_{\\mathrm{{n}/Z_{\\mathrm{{n}}}}}$ cell using $1\\ensuremath{\\mathrm{M}}\\ensuremath{\\mathrm{Zn}}$ $(\\mathrm{TFSI})_{2}$ keeps increasing with cycling, reaching 356 ohm after 15 cycle (Supplementary Fig. 24). In the case of ZES, a much better interfacial compatibility can be obtained and the charge-transfer resistance maintains steady after 15th cycles. This significant difference is ascribed to, in part, the competing $\\mathrm{H}_{2}$ evolution reaction (Supplementary Fig. 25a) and the accumulation of undesirable passivating byproducts (such as $Z\\mathrm{n}(\\mathrm{OH})_{2},$ $x Z\\mathrm{nCO}_{3}{\\bullet}y Z\\mathrm{n(\\bar{O}H)}_{2}{\\bullet}z\\mathrm{H}_{2}\\mathrm{\\bar{O}}$ and $\\mathrm{ZnO}\\mathrm{\\:,\\:}$ ) on $Z\\mathrm{n}$ anode surface upon cycling in 1 $\\textrm{M Z n}(\\mathrm{TFSI})_{2}$ (Supplementary Fig. 25b). By contrast, the cycled Zn obtained from ZES presents well-defined $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) peaks, agreeing well with the $Z\\mathrm{n}$ reference (PDF#99-0110). The time evolution of interface resistance under open circuit conditions further verifies the chemical stability of the metallic $Z\\mathrm{n}$ in ZES (Supplementary Fig. 26). \n\nThe utilization of ZESs along with the possible in situ SEI layer can have a large impact on the Zn deposition. Upon deposition capacity of $0.{\\overset{\\cdot}{5}}\\operatorname*{mAh}\\operatorname{cm}^{-2}$ , loose structures with uncontrolled dendritic $Z\\mathrm{n}$ growth appeared in $1\\mathrm{M}\\ Z\\mathrm{n(TFSI)}_{2}$ (Fig. 3a, c), which surely accounts for the low CE (Supplementary Fig. 20a). This is not the case for our ZES electrolyte, as SEM images in Fig. 3d, e clearly show dendrite-free and smooth $Z\\mathrm{n}$ deposits, even at higher capacity of $2.5\\operatorname{mAh}\\operatorname{cm}^{-2}$ . Based on the crosssectional views (Fig. 3f, g), thickness of the deposited Zn layer is about $5.2\\upmu\\mathrm{m}$ , in line with the expected value $4.3\\upmu\\mathrm{m}$ for capacity of $2.5\\mathrm{mAh}\\mathrm{cm}^{-2}$ , which represents the dense Zn coating by electrodeposition in ZES. Notably, with increasing current densities (Fig. 3e, f), the $Z\\mathrm{n}$ deposits become more compact (theoretical/actual thickness: $1.7/2.3$ at $0.5\\operatorname{mA}{\\mathrm{cm}^{-2}}$ less than $4.3/$ 5.2 at $0.25\\mathrm{mAcm}^{-2}$ ) while the particle size decreases slightly, following the classical nucleation theory56. It is also visible that the $Z\\mathrm{n}$ anode after deposition is covered by a thin surface layer (Fig. 3d inset), also corresponding to the surface modification. Thus, it is reasonable to assume that this additional $Z\\mathrm{n}$ -electrolyte interphase dictates the reversible $Z_{\\mathrm{{n}/Z n}}2+$ redox with efficient $Z\\mathrm{n}^{2+}$ transport and deposition (Fig. 3b). \n\n![](images/cac6fa6f6f65ab0b54d51b43d5f63c015e67a4fd2c42a82ad24948700ddedc30.jpg) \nFig. 3 Effect of ZES and as-obtained SEI layer on Zn deposition. a $Z n$ dendrite growth along with $H_{2}$ evolution observed in 1 M $Z_{ Ḋ }\\mathsf{n}(\\mathsf{T F S l})_{2}$ and b SEI-regulated uniform Zn deposition in ZES. SEM images of Zn deposits using c 1 M $Z_{ Ḋ }\\mathsf{n}(\\mathsf{T F S l})_{2}$ and d ZES electrolytes at $1\\mathsf{m A c m}^{-2}$ $\\mathsf{(0.5m A h c m^{-2})}$ . e–g Cross-sectional SEM images of Zn deposits which were obtained in ZES electrolyte with $1\\mathsf{m A h c m}^{-2}$ $\\mathsf{(0.25m A c m^{-2})}$ ) (e) and $2.5\\mathsf{m A h c m}^{-2}$ $(0.5\\mathsf{m A c m}^{-2},$ (f) Zn on $Z n$ substrate, respectively. $\\pmb{\\mathsf{g A}}$ lower-magnification image of panel $(\\pmb{\\uparrow})$ showing a large area of uniform deposition. Scale bar: $50\\upmu\\mathrm{m}$ for $\\mathbf{\\eta}(\\bullet)$ , (d); $2\\upmu\\mathrm{m}$ for (e); $5\\upmu\\mathrm{m}$ for (f); $20\\upmu\\mathrm{m}$ for $\\mathbf{\\delta}(\\pmb{\\mathsf{g}})$ and inset in (d). \n\nFormation mechanism and chemical composition analysis of the SEI layer on ${\\bf{Z}}{\\bf{n}}$ anode. A uniform SEI can be rationally constructed by introducing selected elements and/or compounds (such as F-donating salts and solvents) that decompose beneficially on alkaline metal anodes59, but due to the higher redox potential of the $Z_{\\mathrm{{n}/Z n}}2+$ couple $(-0.76\\mathrm{V}$ vs. NHE) than that of free $\\mathrm{TFSI^{-}}$ $(-0.87\\mathrm{V}$ vs. $\\bar{Z}\\mathrm{n}/\\mathrm{Zn}^{2+})^{42}$ , the reductive $\\mathrm{TFSI^{-}}$ decomposition can hardly take place before $Z\\mathrm{n}$ deposition. In our case, by virtue of the intrinsic ion-association network in present eutectic liquid, a marked change of the $\\mathrm{TFSI^{-}}$ coordination environment has been confirmed (Fig. 1), making the anionderived SEI formation for metallic $Z\\mathrm{n}$ possible. DFT calculations demonstrate the altered reduction potential of $\\mathrm{TFSI^{-}}$ by its intimate interaction with $Z\\mathrm{n}^{2+}$ (Fig. 4a). The $\\mathrm{Zn}^{2+}{\\cdot}\\mathrm{TFSI}^{-}$ complexes become reductively unstable below $0.37\\mathrm{V}$ (vs. $\\mathrm{Zn}/\\mathrm{Zn}^{2+}.$ ), which is substantially higher than the reduction potential for the isolated $\\mathrm{TFSI^{-}}$ , corroborating the preferential decomposition of $\\mathrm{TFSI^{-}}$ over $Z\\mathrm{n}^{2+}$ reduction. \n\nIn support of the above mechanism, X-ray photoelectron spectroscopy (XPS) and Raman analyses were implemented to experimentally probe the existence of the in situ formed interphase. In the $\\mathrm{~F~}{}$ 1s spectra from XPS (Fig. 4b, the C 1s spectrum can be seen in Supplementary Figs. 27a, 28), except for the $\\mathrm{C-F}$ component arising from the residual $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ salt, we also observed the presence of $\\mathrm{ZnF}_{2}$ $(684.5\\mathrm{eV})$ on the cycled $Z\\mathrm{n}^{60}$ , in perfect accordance with the DFT calculation. For the $\\mathrm{~s~}2\\mathrm{p}$ spectrum shown in Fig. 4c and Supplementary Fig. $27\\mathrm{d}$ , a new peak associated with sulfide appears at $1{\\dot{6}}1.9{\\dot{\\mathrm{eV}}}^{45}$ , further verifying the decomposition of $\\mathrm{TFSI^{-}}$ . Encouragingly, from the Raman analysis, a strong characteristic peak assigned to $\\mathrm{ZnF}_{2}$ at $522\\mathrm{cm}^{-1}$ can be clearly detected61 (Fig. 4d). On the other hand, the $Z\\mathrm{n}$ anode cycled in 1 M $Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ displays two obvious \n\nRaman peaks at 437 and $563\\mathrm{cm}^{-1}$ , related to the formation of ZnO62. \n\nFTIR investigations provide additional insights into the chemical features of the Zn-compatible SEI. Compare with pure $Z\\mathrm{n}$ , the surface of the SEI-coated $Z\\mathrm{n}$ is enriched with organic functional groups (Supplementary Fig. 30). A blue shift in the $C^{-}$ F, $s{=}0$ and $\\mathrm{C^{-}N}$ functional groups can be found for the SEI layer (Supplementary Table 5) compared with the ZES electrolyte. Overall, the agreement between spectral characterization and theoretical calculation suggests that the unique anion-containing Zn species in ZES enable $\\mathrm{TFSI^{-}}$ to reductively decompose and participate in the SEI formation with major components involving $\\mathrm{ZnF}_{2}$ , S/N-rich organic compounds and/or their derivatives. Unlike the passivating layers on the surface of multivalent metals $(Z{\\mit\\mathrm{n}},\\mathrm{\\bar{M}}{\\mit\\mathrm{g}},$ and Ca, etc.)23,24, $Z\\mathrm{n}^{2+}$ is able to penetrate such anion-derived SEI layer, whose ionic conductivity is calculated to be $2.36\\times10^{-6}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1}$ (Supplementary Fig. 31), higher than that of the artificial interphase fabricated on $\\mathbf{Mg}$ anode $(1.19\\times10^{-6}\\mathrm{Scm^{-1}})^{23}$ . An additional evidence for the effective $Z\\mathrm{n}^{2+}$ diffusion through SEI can be provided by the low activation energy of $49.7\\mathrm{kJ\\bar{mol}^{-1}}$ obtained by temperaturedependent impedance measurements (Fig. 4e and Supplementary Fig. 32)25,63, which is comparable to that of $\\mathrm{Li^{+}}$ diffusion across the typical SEI formed in $\\mathrm{LiPF}_{6}/\\mathrm{EC/EMC}$ $(51\\mathrm{kJ}\\mathrm{mol}^{-1})^{2:}$ . Furthermore, several metal fluorides $(M_{x}\\mathrm{F}_{y},~M=\\mathrm{Li},$ Zn, Cu, and Al) have been well acknowledged as main rigid-frame materials for protecting metal anodes, since they can guide the metal nucleation and effectively inhibit the growth of dendrites64–66. Meanwhile, the S/N-rich organic compounds could provide sufficient ion channels for $Z n^{\\breve{2}+}$ transport, and their flexibility will accommodate volume changes caused by $Z\\mathrm{n}$ plating/stripping67,68. \n\nIn view of the element distribution of the SEI, two additional surface-sensitive techniques, time-of-flight secondary-ion mass spectrometry (TOF-SIMS) and XPS spectra at various sputtering depths were used. As shown in XPS spectra at various sputtering depths (0, 7, and $15\\mathrm{nm}$ ) on the SEI accumulated on $Z\\mathrm{n}$ (Fig. 4f), the signal of metallic $Z\\mathrm{n}$ at $1044.63\\mathrm{eV}$ can be observed with the depth increased to ca. $15\\mathrm{nm}$ (Fig. $4\\mathrm{g}$ and Supplementary Fig. 29), which defines the thickness of SEI layer. Moreover, as the etching depth increased, the intensity of $\\mathrm{ZnF}_{2}$ increases gradually while those of sulfides and nitrides decrease, indicating that $\\mathrm{ZnF}_{2}$ mainly exists in the inner SEI region and $\\mathsf{S}/\\mathrm{N}$ -rich organic compounds are mainly distributed in the outer SEI layer. Besides, TOF-SIMS results (Fig. 4f and Supplementary Fig. 33) combined with the energy-dispersive spectroscopy (EDS) analyses (Supplementary Fig. 34) further exhibit an even distribution of Zn, F, N, and S elements on the cycled $Z\\mathrm{n}$ surface, implying the uniformity of the SEI layer. \n\n![](images/a12419d90bfc073391287bba1cf4c382b5b24d90b000e6c76e58f371b10bbff9.jpg) \nFig. 4 Experimental and theoretical investigations on the existence and the composition of the Zn-compatible SEI layer. a Predicted reduction potentials by DFT calculations. XPS spectral regions for b F 1s and $\\textsf{\\textsf{c S}}2\\mathsf{p}$ of the surface of bare $Z n$ (top) and after cycled Zn (bottom), respectively. d Raman spectra of the cycled Zn anode in ZES and 1 M $Z_{\\mathsf{n}}({\\mathsf{T}}{\\mathsf{F}}{\\mathsf{S}}{\\mathsf{I}})_{2}$ . e Arrhenius behavior of the reciprocal resistances corresponding to interfacial components and the activation energy derived for the in situ formed SEI. f XPS spectral regions for $Z n2\\mathsf{p}$ , F 1s, N 1s, and $\\mathsf{S2p}$ at various argon $(\\mathsf{A r^{+}})$ sputtering depths on the SEI accumulated on $Z n$ substrate. g Three-dimensional view of Zn, N, F, and S elements distributions of SEI in the time-of-flight secondary-ion mass spectrometry (TOF-SIMS) sputtered volumes. The SEI-coated $Z n$ anode was obtained after 20 cycles of galvanostatic plating/stripping in ZES electrolyte $(Z n/Z n$ cells at $0.5\\mathsf{m A c m}^{-2}$ with a capacity of $1\\mathsf{m A h c m}^{-2}$ for each half cycle). \n\nThe validity of the SEI layer in various electrolyte systems. More direct evidence for modulated $Z\\mathrm{n}$ plating/stripping enabled by this SEI was obtained from in situ optical visualization observations of Zn deposition (in a home-made cell, Supplementary Fig. 35a). Not surprisingly, in $\\begin{array}{r}{{1}\\mathrm{~M~}\\mathrm{Zn}(\\mathrm{TFSI})_{2}}\\end{array}$ , rather uneven $Z\\mathrm{n}$ electrodeposits and copious air bubbles were observed as early as $5\\mathrm{min}$ after the inception of deposition (Fig. 5a and Supplementary Fig. 35b). For the cell using ZES, uniform and compact $Z\\mathrm{n}$ deposits can be achieved at capacity of $5\\mathrm{mAh}\\mathrm{cm}^{-2}$ $(10\\mathrm{\\:mA\\:cm^{-2}}, $ (Fig. 5b). We further investigated the availability of the SEI layer in the routine aqueous electrolyte. As is shown in Fig. 5c, the gas generation disappears when such SEI-coated $Z\\mathrm{n}$ anodes obtained in ZES were reassembled in $\\mathrm{~1~M~}\\:\\mathrm{Zn(TFSI)}_{2}$ . Particularly, these surface-modified $Z\\mathrm{n}$ anode exhibits extended cycling life and lower polarization at both low $(0.1\\mathrm{mA}\\mathrm{cm}^{-2}),$ and high $\\mathbf{\\bar{(}1\\ m A\\ c m^{-2}}.$ ) rates (Fig. 5d, e). Indeed, Zn surface after deposition remain visibly flat (Supplementary Fig. 35c), which emphasizes a strong correlation between SEI and dendrite-free Zn deposition. \n\n![](images/6df93d502ef810a5496a7bd56e71fe9769d4f1c9afddfcf11476654735981e4a.jpg) \nFig. 5 The validity of the SEI layer for Zn electrochemistry. a–c In situ investigations of the $Z n$ deposition by optical microscopy in $Z n/Z n$ cells. Images of the $Z n$ -electrolyte interface region in a 1 M $Z_{ Ḋ }\\mathsf{n}(\\mathsf{T}\\mathsf{F}\\mathsf{S}\\mathsf{I})_{2}$ and b ZES. c Images of SEI-coated $Z n$ -electrolyte interface region using 1 M $Z_{\\mathsf{n}}({\\mathsf{T}}{\\mathsf{F}}{\\mathsf{S}}{\\mathsf{I}})_{2}$ . The deposition current density is $10\\mathsf{m A}\\mathsf{c m}^{-2}$ with the areal capacity of $5\\mathsf{m A h c m}^{-2}$ . Galvanostatic cycling performance of symmetric $Z n/Z n$ cells tests using pure and SEI-coated Zn coupled with 1 M $1Z_{n}({\\mathsf{T F S}}|)_{2}$ at d low rate of $0.1\\mathsf{m A}\\mathsf{c m}^{-2}$ $\\langle0.05\\mathsf{m A h c m}^{-2}$ for each half cycle) and e high rate of $1\\mathsf{m A c m}^{-2}$ (0.5 $\\mathsf{m A h c m}^{-2}$ for each half cycle). The $Z n/V_{2}O_{5}$ cells in $1M Z n(T F S|)_{2}$ using f pure $Z n$ anode and $\\pmb{\\mathsf{g}}\\mathsf{S}\\mathsf{E}\\mathsf{I}$ -coated $Z n$ anode were first fully charged to $\\boldsymbol{1.8\\vee}$ at $20\\mathsf{m A g}^{-1}$ (based on active materials of cathode), respectively, and then the cells were rested at $100\\%$ stage of charge (SOC) for $48\\mathsf{h}$ , followed by full discharging. \n\nThe effect of the SEI on parasitic reactions was evaluated by monitoring the open circuit-voltage decay of fully charged $Z\\mathrm{n}/$ $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cells with $1\\mathrm{\\bar{M}}Z n(\\mathrm{TFSI})_{2}$ and then discharging after $^{48\\mathrm{h}}$ of storage. $97.8\\%$ of the original capacity was retained (Fig. 5f) in cell using SEI-protected $Z\\mathrm{n}$ anode, exceeding $68.78\\%$ using an untreated $Z\\mathrm{n}$ anode. Obviously, similar to the function of the anode SEI layer obtained in Li-metal anodes, this rigid-flexible coupling SEI formed on $Z\\mathrm{n}$ surface can eliminate direct contact between the active anode and electrolyte, thereby inhibiting the interface side-reactions (such as $\\mathrm{H}_{2}$ evolution and passivation) effectively during storage. More importantly, once the SEI forms, the coated Zn surface is functionalized by stable and favorable \n\n$Z\\mathrm{n}^{2+}$ transport with low-diffusion barrier, which can facilitate reversible Zn stripping/plating even applicable for implanted aqueous electrolytes. Note that ZES exhibits lower polarization and better stability for $Z_{\\mathrm{{n}/Z n}}2+$ reactions compared with DESs based on other $Z\\mathrm{n}$ salts (Supplementary Fig. 36), demonstrating the $\\mathrm{TFSI^{-}}$ -induced SEI formation mechanism and the uniqueness of the SEI composition. To the best of our knowledge, the in situ constructed effective SEI has not been reported in ZIBs. This strategy may also be helpful to the development of other MIBs electrolytes that are compatible with their corresponding metal anodes. \n\nHighly stable ZIBs coupled with cathodes ( $\\mathbf{V}_{2}\\mathbf{O}_{5}$ and $\\bf{M o}_{6}{S_{8}}.$ ) in the ZES electrolyte. Finally, we explored applications of the ZES electrolyte in ZIBs composed of $Z\\mathrm{n}$ anode and $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cathode (Fig. 6a). CV profiles of the cell after initial cycle activation are almost overlapped. For comparison, a co-intercalation of $Z\\mathrm{n}^{2+}$ and hydrated protons $(\\mathrm{H}_{3}\\mathrm{O}^{+})$ was observed in the cell that contains $1\\mathrm{M}\\mathrm{Zn(TFSI)}_{2}$ as electrolyte (Supplementary Fig. 37)69. From the CV measurement of the ${\\mathrm{Zn}}/{\\mathrm{V}}_{2}{\\mathrm{O}}_{5}$ cell at different scan rates, the diffusion-controlled reaction process can be certified in ZES (Supplementary Fig. 38). As expectedly, the cyclic stability of ${\\mathrm{Zn}}/{\\mathrm{V}}_{2}{\\mathrm{O}}_{5}$ cells using ZES outperforms their aqueous counterparts at each current density (Fig. 6b and Supplementary Figs. 39, 41). Unlike $1\\mathrm{M}\\mathrm{Zn(TFSI)}_{2}$ , ZES can be cycled without over-charging even at a relatively low rate $\\mathrm{\\left(10\\mA\\g^{-1}\\right)},$ ) (Supplementary Fig. 40). At a high rate of $200\\mathrm{mAg^{-1}}$ ${\\sim}34\\mathrm{min}$ rate), the $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cathode with ZES delivers an excellent stability with a high capacity retention of $91.3\\%$ with a high CE ${\\sim}99.34\\%$ for 100 cycles (Supplementary Fig. 41a). Besides, there is only a slight change of the cell overpotential throughout the cycling process (Supplementary Fig. 41b). Considering that the generation of a stabilized SEI extremely relies on the amount of charge passed through the cell54, we pre-activated the ${\\mathrm{Zn}}/{\\mathrm{V}}_{2}{\\mathrm{O}}_{5}$ cell at $\\mathrm{1Ag^{-1}}$ to accelerate the SEI growth on anode, and then tested its long-cycle stability at the rate of $600\\mathrm{mAg^{-1}}$ . Such a cell exhibits a highly reversible specific capacity of nearly $110\\mathrm{mAhg^{-1}}$ (based on the mass of ${\\bf V}_{2}{\\bf\\bar{O}}_{5})$ ); $92.8\\%$ of initial capacity could be retained over prolonged 800 cycles, along with a high average CE of $99.9\\%$ (Supplementary Fig. 42). In sharp contrast, the capacity of the cell with 1 $\\mathrm{~M~}\\mathrm{Zn(\\bar{T}F S I)}_{2}$ rapidly decayed to $61.9\\mathrm{{mAhg}^{-1}}$ (capacity retention $<50\\%$ ) after only 150 cycles, which is mainly ascribed to the formation of the insulating passivation layer on $Z\\mathrm{n}$ anode (Supplementary Fig. 25) that blocks the $Z\\mathrm{n}^{2+}$ interfacial transport, and the resulting increase in polarization10,23,26. The potential of ZES for power-type ZIBs is further evidenced by the attractive rate capability with elevating current density from 80 to $300\\mathrm{mAg^{-1}}$ (Fig. 6c, d). This should be contributed by high active $Z\\mathrm{n}^{2+}$ diffusion coefficient $(1.66\\times10^{-6}\\mathrm{cm}^{2}s^{-1}$ , Supplementary Fig. 18) and the pseudo-capacitance properties of $\\mathrm{V}_{2}\\mathrm{O}_{5}$ (Fig. 6c). Although cycling with a low areal capacity has been demonstrated to assist in maintaining a uniform morphology for metallic anodes70, material loadings must be rationally optimized to yield the truly competitive ZIBs for industrial scenarios16. Thus, we have attempted to estimate the utility of the ZES electrolyte on a more practical basis by a full cell with a highmass-loading $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cathode and a thin $Z\\mathrm{n}$ foil ( $20\\upmu\\mathrm{m}$ thickness, $\\sim11.7\\mathrm{mAh}\\mathrm{cm}^{-2}$ ). When the $\\mathrm{V}_{2}\\mathrm{O}_{5}$ loading is as high as $14.3\\mathrm{mg}$ $c\\mathrm{m}^{-2}$ , the $\\mathrm{Zn}//\\mathrm{ZES}//\\mathrm{V}_{2}\\mathrm{O}_{5}$ cell can be cycled still shows stable operation over 600 cycles at a high rate of $8.43\\mathrm{mA}\\mathrm{cm}^{-2}$ with a capacity fading of only $0.0035\\%$ cycle $^{-1}$ (the capacity retention of $97.89\\%$ ) (Fig. 6f). In contrast to most of the previously reported ZIBs, wherein much excessive $Z\\mathrm{n}$ needs to be used for prolonging the cycle life, the mass ratio between $Z\\mathrm{n}$ and $\\mathrm{V}_{2}\\mathrm{O}_{5}$ was set to 1:1 in this cell. Based on the total mass of cathode and anode, the capacity is calculated to be $25.5\\mathrm{mAh}\\mathrm{g}^{-1}$ , corresponding to an energy density of $25.8\\mathrm{Wh}\\mathrm{kg}^{-1}$ . In addition, further reducing the ${\\mathrm{Zn}}{:}\\mathrm{V}_{2}\\mathrm{O}_{5}$ mass ratio to 0.5:1 can provide an improved energy density of $40.9\\mathrm{Wh}\\mathrm{kg}^{-1}$ (Supplementary Fig. 43). In the case of development of the $\\bar{Z}\\mathrm{n}^{2+}$ -storage cathodes taking into account stability, capacity and operation voltage simultaneously, there is still vast scope for improvements in energy density of ZES-based $\\mathrm{ZIBs^{71}}$ . The ex situ XRD test (Fig. 6e and Supplementary Fig. 44) shows that a highly stable and completely reversible structure evolution occurred on the $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cathode during charge/discharge processes in ZES. A $\\mathrm{Zn/Mo_{6}S_{8}}$ cell was assembled to demonstrate the versatility of ZES for ZIB applications (Fig. 6g). Such a cell delivers a high discharge capacity of $128.6\\:\\mathrm{mAh\\bar{g}^{-1}}$ (based on the mass of $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ ) after three cycles, which is close to the theoretical value of $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ $(129\\mathrm{mAh}\\dot{\\mathrm{g}}^{-1})^{72}$ . Two pairs of typical redox peaks correspond well to the two-step $\\dot{Z}\\mathrm{n}^{2+}$ (de-)intercalation processes, analogous to cases of previously reported72. \n\n![](images/4cb3a2f4c62065412c558afeb7572f0c8d8087cde83150525b26592b25917413.jpg) \nFig. 6 Electrochemical properties of ZIBs. a Typical CV curves of the $Z n/\\mathsf{V}_{2}\\mathsf{O}_{5}$ cell using ZES at a scan rate of $0.5\\mathsf{m V s^{-1}}$ . b Charge/discharge cycling performance and CE of the $Z n/\\mathsf{V}_{2}\\mathsf{O}_{5}$ cells with ZES (after activation under $1\\mathsf{A}\\mathsf{g}^{-1})$ and 1 $M Z n({\\mathsf{T F S}}|)_{2}$ electrolytes at $600\\mathsf{m A g}^{-1}$ $(0.79\\mathsf{m A}\\mathsf{c m}^{-2};$ . c Charge/discharge curves at various current densities in ZES. d Rate performance of ZES and 1 M $Z_{ Ḋ }\\mathsf{n}(\\mathsf{T F S l})_{2}$ electrolytes. e XRD patterns of the $V_{2}O_{5}$ cathode at different voltage states of the first cycle in ZES $\\left\\langle10\\mathsf{m A}\\mathsf{g}^{-1}\\right\\rangle$ . f Long-term cycling performance of the $Z n//Z E S//V_{2}O_{5}$ cell with the $Z n;V_{2}O_{5}$ mass ratio of 1:1 at $8.43\\mathsf{m A c m}^{-2}$ (after activation under same rate; the capacity is calculated based on the total mass of cathode and anode). g Typical galvanostatic charge/discharge profiles and CV curves (inset) of the $Z n/M o_{6}S_{8}$ cell with ZES electrolyte. The current densities are calculated on the activated materials of cathode. \n\n# Discussion \n\nIn summary, we have demonstrated that the established in situ SEI protection is a feasible strategy toward rechargeable $Z\\mathrm{n}$ -metal anodes. Due to the direct coordination between cations and anions in a form of large-size cationic complexes endowed by the ZES, the reductive decomposition of $\\mathrm{TFSI^{-}}$ is induced before the Zn deposition during the initial cycling process, allowing a welldefined Zn-compatible SEI layer with a rich content of mechanically rigid $\\mathrm{ZnF}_{2}$ and $Z\\dot{\\mathrm{n}}^{2+}$ -permeable organic components. With this interface modulation, dendrite-free and intrinsically stable $Z\\mathrm{n}$ plating/stripping can be realized at the areal capacity of $>2.5\\mathrm{\\dot{m}A h}\\mathrm{\\dot{cm}}^{-2}$ or even under a common dilute aqueous electrolyte system. $\\mathrm{Zn}//\\mathrm{ZES}//\\mathrm{V}_{2}\\mathrm{O}_{5}$ cells present remarkable electrochemical reversibility (an average CE of ${\\sim}99.9\\%$ , superior to most aqueous $\\mathrm{ZiB}s^{9,73,74}$ ) and laudable capacity retention even under rigorous but practically desirable cathode-anode loading conditions. Given the extendibility of this strategy, we envision that this study will provide an unprecedented avenue for tackling the dilemmas raised by the intrinsic properties of multivalent metal anodes, which may lead to the potential fabrication of energy-storage devices. \n\n# Methods \n\nPreparation of electrolytes and cathodes. The ZES samples were formed by readily mixing the two components $(Z\\mathrm{n}(\\mathrm{TFSI})_{2}$ and Ace) with the required molar ratios (the $\\mathrm{Zn(TFSI)}_{2}/\\mathrm{Ace}$ molar ratio between 1:4 and 1:9) at room temperature (Supplementary Fig. 1). Homogenous and transparent liquids can be obtained directly after heating the mixtures at $80^{\\circ}\\mathrm{C}$ with gentle stirring $^{2\\mathrm{h}}$ . Subsequently, the electrolytes were stored in a dry atmosphere for further use. The micro-sized $\\mathrm{V}_{2}\\mathrm{O}_{5}$ material was purchased from Aldrich. The $\\mathrm{V}_{2}\\mathrm{O}_{5}$ electrodes used here comprise $70\\mathrm{wt\\%}$ ${\\mathrm{V}}_{2}{\\mathrm{O}}_{5},$ , $20\\mathrm{wt\\%}$ Super P carbon, and $10\\mathrm{wt\\%}$ polyvinylidene fluoride (PVDF; Sigma). $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ (Chevrel phase) was synthesized according to the previously reported method72. The $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ electrodes were prepared by the same procedure, but $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ $(80\\mathrm{wt\\%})$ , Super $\\mathrm{\\bfP}$ carbon $(10\\mathrm{wt\\%})$ , and PVDF $(10\\mathrm{wt\\%})$ , which were mixed and dispersed in N-methyl-2-pyrrolidone and cast on to the Ti current collector $.10\\upmu\\mathrm{m}$ in thickness). $\\mathrm{V}_{2}\\mathrm{O}_{5}$ and $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ cathodes were punched in the diameter of 1.2 cm $\\cdot1.1304\\mathrm{cm}^{2})$ for the full cell tests. The active mass loading for the $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cathode materials is $1.6\\pm1\\mathrm{mg}\\mathrm{cm}^{-2}$ for normal tests, while that for the $\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ cathode is $\\sim1.5\\mathrm{mg}\\mathrm{cm}^{-2}$ . The high active mass loading for the $\\mathrm{V}_{2}\\mathrm{O}_{5}$ cathode materials is $14.3\\mathrm{mg}\\mathrm{cm}^{-2}$ $4.1\\mathrm{mAh}\\mathrm{\\bar{c}m}^{-2}$ , $290\\mathrm{mAh}\\mathrm{g}^{-1}$ for the ${\\bf V}_{2}{\\bf O}_{5},$ ) and the thicknesses of $Z\\mathrm{n}$ foils are 20 and $10\\upmu\\mathrm{m}$ (14.28 and $7.14\\mathrm{mg}\\mathrm{cm}^{-2}$ , respectively) for the practical utility evaluation test. \n\nElectrochemical measurements. EIS was performed by an electrochemical working station (VMP-300) over the frequency range $\\dot{0.1}\\mathrm{-}7\\times10^{6}\\mathrm{Hz}$ with a perturbation amplitude of $5\\mathrm{mV}$ to better investigate the interfacial stability between \n\nZn metal and different electrolytes. Electrochemical cycling tests in $Z\\mathrm{n}/Z\\mathrm{n}$ symmetric cells, $\\mathrm{Ti}/\\mathrm{Zn}$ cells, ${\\mathrm{Zn}}/{\\mathrm{V}}_{2}{\\mathrm{O}}_{5}$ and $Z_{\\mathrm{n/Mo_{6}S_{8}}}$ cells were conducted in CR2032- type coin cells with LAND testing systems. All cells were assembled in an open environment and a glass fiber with a diameter of $16.5\\mathrm{mm}$ was used as the separator. \n\nCharacterization. SEM (Hitachi S-4800) was employed to detect the morphologies of Zn deposits on the $Z\\mathrm{n}$ -metal anodes or the Ti foils. FTIR measurements were carried out on a Perkin-Elmer spectrometer in the transmittance mode. XRD patterns were recorded in a Bruker-AXS Micro-diffractometer (D8 ADVANCE) with $\\mathrm{Cu-K_{\\mathrm{al}}}$ radiation $(\\lambda=1.5405\\mathrm{\\AA}$ ). Raman spectra were recorded at room temperature using a Thermo Scientific DXRXI system with excitation from an Ar laser at $532\\mathrm{nm}$ . A differential scanning calorimeter (TA, dsc250) was used to evaluate the thermal properties of the electrolytes. Samples are scanned from $-80\\mathrm{-}100^{\\circ}\\mathrm{C}$ at a rate of $5^{\\circ}\\mathrm{C}\\mathrm{-}\\mathrm{min}^{-1}$ under a nitrogen atmosphere. An in situ optical microscope from the Olympus Corporation was used to observe the depositional morphology of $Z\\mathrm{n}$ with different electrolytes in real time in order to study the interfacial stability. XPS was performed on a Thermo Scientific ESCA Lab 250Xi to characterize the surface components. TOF-SIMS (Germany, TOF-SIMS5) was employed to measure the components as a function of depth. \n\nCalculation methods. All quantum chemical calculations were performed by applying the DFT method with the B3LYP level and $6{-}31{+}\\mathrm{G}$ (d, p) basis set using Gaussian 09 program package. The structural optimization was determined by minimizing the energy without imposing molecular symmetry constraints. The binding energy of the anion-containing $\\dot{Z}\\mathrm{n}$ species were defined as the interaction between different molecule fragments, composed of the interaction between $Z\\mathrm{n}^{2+}$ , $\\mathrm{TFSI^{-}}$ and Ace. The binding energy $E$ was calculated according to Eq. (1), the expression as follows: \n\n$$\nE=E_{\\mathrm{total}}-n E(X)\n$$ \n\nwhere $E_{\\mathrm{total}}$ is the structure total energy, $E(X)$ is the energy of different molecule fragments $(X=\\mathrm{Zn}^{2+}$ , $\\mathrm{TFSI^{-}}$ , Ace), and $n$ is the number of corresponding molecule fragments according to the different structure configurations \n\nThe reduction potentials for the $\\mathrm{TFSI^{-}}$ anion with different paths in the solution containing $Z\\mathrm{n}^{2+}$ were calculated according to Eq. (2), in which the values of the reduction potentials were converted to the $Z_{\\mathrm{{n}/Z n^{2+}}}$ scale by subtraction of $3.66\\mathrm{V}$ as discussed extensively elsewhere42,75 \n\n$$\nE^{0}=-\\frac{\\Delta G_{298\\mathrm{K}}^{0}}{n F}-3.66\\mathrm{~V~}\n$$ \n\nwhere $\\Delta G_{298\\mathrm{K}}^{0}$ is the Gibbs energy of the reduction reaction of different paths, $n$ is the transferred electron number, $F$ is Faraday constant. \n\n# Data availability \n\nThe datasets generated during the current study are included in this published article (and its supplementary information files) are available from the corresponding author on reasonable request. \n\nReceived: 22 June 2019; Accepted: 10 November 2019; Published online: 26 November 2019 \n\n# References \n\n1. Zhang, N. et al. Rechargeable aqueous zinc-manganese dioxide batteries with high energy and power densities. Nat. Commun. 8, 405 (2017). \n2. Canepa, P. et al. Odyssey of multivalent cathode materials: open questions and future challenges. Chem. Rev. 117, 4287–4341 (2017). \n3. Ponrouch, A., Frontera, C., Barde, F. & Palacin, M. R. Towards a calciumbased rechargeable battery. Nat. Mater. 15, 169 (2016). \n4. Muldoon, J., Bucur, C. B. & Gregory, T. Quest for nonaqueous multivalent secondary batteries: magnesium and beyond. Chem. Rev. 114, 11683–11720 (2014). \n5. Aurbach, D. et al. Prototype systems for rechargeable magnesium batteries. Nature 407, 724–727 (2000). \n6. Caramia, V. & Bozzini, B. Material science aspects of zinc-air batteries: a review. Mater. Renew. Energy 3, 28 (2014). \n7. Wang, F. et al. How water accelerates bivalent ion diffusion at the electrolyte/ electrode interface. Angew. Chem. Int. Ed. 57, 11978–11981 (2018). \n8. Song, M., Tan, H., Chao, D. & Fan, H. J. Recent advances in Zn-ion batteries. Adv. Funct. Mater. 28, 1802564 (2018). \n9. Fang, G., Zhou, J., Pan, A. & Liang, S. Recent advances in aqueous zinc-ion batteries. Acs Energy Lett. 3, 2480–2501 (2018). \n10. Lu, W., Xie, C., Zhang, H. & Li, X. Inhibition of zinc dendrite growth in zincbased batteries. Chemsuschem 11, 3996–4006 (2018). \n11. Naveed, A., Yang, H., Yang, J., Nuli, Y. & Wang, J. Highly reversible and rechargeable safe Zn batteries based on a triethyl phosphate electrolyte. Angew. Chem. Int. Ed. 58, 2760–2764 (2019). \n12. Zhao, J. et al. “Water-in-deep eutectic solvent” electrolytes enable zinc metal anodes for rechargeable aqueous batteries. Nano Energy 57, 625–634 (2019). \n13. Kang, L. et al. Nanoporous $\\mathrm{CaCO}_{3}$ coatings enabled uniform Zn stripping/ plating for long-life zinc rechargeable aqueous batteries. Adv. Energy Mater. 8, 1801090 (2018). \n14. Parker, J. F. et al. Rechargeable nickel-3D zinc batteries: an energy-dense, safer alternative to lithium-ion. Science 356, 414–417 (2017). \n15. Gupta, T. et al. Improving the cycle life of a high-rate, high-potential aqueous dual ion battery using hyper-dendritic zinc and copper hexacyanoferrate. J. Power Sources 305, 22–29 (2016). \n16. Wang, F. et al. Highly reversible zinc metal anode for aqueous batteries. Nat. Mater. 17, 543 (2018). \n17. Chen, C. Y., Matsumoto, K., Kubota, K., Hagiwara, R. & Xu, Q. A roomtemperature molten hydrate electrolyte for rechargeable zinc-air batteries. Adv. Energy Mater. 9, 1900196 (2019). \n18. Wu, X. et al. Reverse dual-ion battery via a $\\mathrm{{ZnCl}}_{2}$ water-in-salt electrolyte. J. Am. Chem. Soc. 141, 6338–6344 (2019). \n19. Xu, W. et al. Lithium metal anodes for rechargeable batteries. Energy Environ. Sci. 7, 513–537 (2014). \n20. Zhang, X. Q. et al. Regulating anions in the solvation sheath of lithium ions for stable lithium metal batteries. Acs Energy Lett. 4, 411–416 (2019). \n21. Ren, X. D. et al. Guided lithium metal deposition and improved lithium coulombic efficiency through synergistic effects of $\\mathrm{LiAsF}_{6}$ and cyclic carbonate additives. Acs Energy Lett. 3, 14–19 (2018). \n22. Suo, L. et al. How solid-electrolyte interphase forms in aqueous electrolytes. $J.$ Am. Chem. Soc. 139, 18670–18680 (2017). \n23. Son, S. B. et al. An artificial interphase enables reversible magnesium chemistry in carbonate electrolytes. Nat. Chem. 10, 532–539 (2018). \n24. Wang, D. et al. Plating and stripping calcium in an organic electrolyte. Nat. Mater. 17, 16 (2017). \n25. Zhang, X. Q. et al. Highly stable lithium metal batteries enabled by regulating the solvation of lithium ions in nonaqueous electrolytes. Angew. Chem. Int. Ed. 57, 5301–5305 (2018). \n26. Mainar, A. R. et al. An overview of progress in electrolytes for secondary zincair batteries and other storage systems based on zinc. J. Energy Storage 15, 304–328 (2018). \n27. Smith, E. L., Abbott, A. P. & Ryder, K. S. Deep eutectic solvents (DESs) and their applications. Chem. Rev. 114, 11060–11082 (2014). \n28. Zhang, Q. H., Vigier, K. D., Royer, S. & Jerome, F. Deep eutectic solvents: syntheses, properties and applications. Chem. Soc. Rev. 41, 7108–7146 (2012). \n29. Yamada, Y., Wang, J., Ko, S., Watanabe, E. & Yamada, A. Advances and issues in developing salt-concentrated battery electrolytes. Nat. Energy 4, 269–280 (2019). \n30. Abbott, A. P., Barron, J. C., Ryder, K. S. & Wilson, D. Eutectic-based ionic liquids with metal-containing anions and cations. Chem. Eur. J. 13, 6495–6501 (2007). \n31. Abbott, A. P., Capper, G., Davies, D. L. & Rasheed, R. Ionic liquids based upon metal halide/substituted quaternary ammonium salt mixtures. Inorg. Chem. 43, 3447–3452 (2004). \n32. Zheng, B. et al. Stabilizing $\\mathrm{Li_{10}S n P_{2}S_{12}/L i}$ interface via an in situ formed solid electrolyte interphase layer. ACS Appl. Mater. Interfaces 10, 25473–25482 (2018). \n33. Borodin, O. & Smith, G. D. LiTFSI structure and transport in ethylene carbonate from molecular dynamics simulations. J. Phys. Chem. B 110, 4971–4977 (2006). \n34. Tsuzuki, S., Tokuda, H., Hayamizu, K. & Watanabe, M. Magnitude and directionality of interaction in ion pairs of ionic liquids: Relationship with ionic conductivity. J. Phys. Chem. B 109, 16474–16481 (2005). \n35. He, M., Fic, K., Frąckowiak, E., Novák, P. & Berg, E. J. Influence of aqueous electrolyte concentration on parasitic reactions in high-voltage electrochemical capacitors. Energy Storage Mater. 5, 111–115 (2016). \n36. Henderson, W. A. Glyme-lithium salt phase behavior. J. Phys. Chem. B 110, 13177–13183 (2006). \n37. Seo, D. M., Borodin, O., Han, S.-D., Boyle, P. D. & Henderson, W. A. Electrolyte solvation and ionic association II. Acetonitrile-lithium salt mixtures: highly dissociated salts. J. Electrochem. Soc. 159, A1489–A1500 (2012). \n38. Liang, H. Y. et al. New binary room-temperature molten salt electrolyte based on urea and LiTFSI. J. Phys. Chem. B 105, 9966–9969 (2001). \n39. Hu, Y. S., Wang, Z. X., Li, H., Huang, X. J. & Chen, L. Q. Spectroscopic studies on the cation-anion, cation-solvent and anion-solvent interactions in the LiCF ${}_{3}\\mathrm{SO}_{3}$ /acetamide complex system. Spectrochim. Acta A 61, 403–411 (2005). \n40. Yu, Z. X. et al. A series of LiI/acetamide phase transition electrolytes and their applications in dye-sensitized solar cells. Electrochim. Acta 55, 895–902 (2010). \n41. Narayanan, N. S. V., Ashokraj, B. V. & Sampath, S. Physicochemical, electrochemical, and spectroscopic characterization of zinc-based roomtemperature molten electrolytes and their application in rechargeable batteries. J. Electrochem. Soc. 156, A863–A872 (2009). \n42. Suo, L. et al. “Water-in-salt” electrolyte enables high-voltage aqueous lithiumion chemistries. Science 350, 938–943 (2015). \n43. Bakker, A., Gejji, S., Lindgren, J., Hermansson, K. & Probst, M. M. Contact ion pair formation and ether oxygen coordination in the polymer electrolytes M $[\\mathrm{N}(\\mathrm{CF}_{3}\\mathrm{SO}_{2})_{2}]_{2}\\mathrm{PEO}n$ for $\\mathbf{M}=\\mathbf{M}\\mathbf{g}{\\mathrm{.}}$ Ca, Sr and Ba. Polymer 36, 4371–4378 (1995). \n44. Bakker, A., Lindgren, J. & Hermansson, K. Polymer electrolytes based on triblock-copoly(oxyethylene/oxypropylene/oxyethylene) systems. Polymer 37, \n1871–1878 (1996). \n45. Yamada, Y. et al. Unusual stability of acetonitrile-based superconcentrated electrolytes for fast-charging lithium-ion batteries. J. Am. Chem. Soc. 136, \n5039–5046 (2014). \n46. Zhou, Q. et al. Phase behavior of ionic liquid-LiX mixtures: pyrrolidinium cations and $\\mathrm{TFSI^{-}}$ anions-linking structure to transport properties. Chem. Mater. 23, 4331–4337 (2011). \n47. Dye, J. L., Faber, M. P. & Karl, D. J. Transference numbers and conductances of multivalent salts in aqueous solution: zinc sulfate and zinc perchlorate. J. Am. Chem. Soc. 82, 314–318 (1960). \n48. Plancha, M. J. C. Characterisation and modelling of multivalent polymer electrolytes. Polym. Electrolytes 340–377 (2010). \n49. Ueno, K. et al. $\\mathrm{Li^{+}}$ solvation and ionic transport in lithium solvate ionic liquids diluted by molecular solvents. J. Phys. Chem. C. 120, 15792–15802 (2015). \n50. Simons, T. J., MacFarlane, D. R., Forsyth, M. & Howlett, P. C. Zn electrochemistry in 1-ethyl-3-methylimidazolium and N-butyl-Nmethylpyrrolidinium dicyanamides: promising new rechargeable Zn battery electrolytes. Chemelectrochem 1, 1688–1697 (2014). \n51. Xu, M., Ivey, D. G., Qu, W. & Xie, Z. Improved $Z\\mathrm{n/Zn(II)}$ redox kinetics, reversibility and cyclability in 1-ethyl-3-methylimmidazolium dicyanamide with water and dimethyl sulfoxide added. J. Power Sources 252, 327–332 (2014). \n52. Tarascon, J. M. & Armand, M. Issues and challenges facing rechargeable lithium batteries. Nature 414, 359–367 (2001). \n53. Suo, L., Hu, Y. S., Li, H., Armand, M. & Chen, L. A new class of solvent-in-salt electrolyte for high-energy rechargeable metallic lithium batteries. Nat. Commun. 4, 1481 (2013). \n54. Adams, B. D., Zheng, J., Ren, X., Xu, W. & Zhang, J. G. Accurate determination of coulombic efficiency for lithium metal anodes and lithium metal batteries. Adv. Energy Mater. 8, 1702097 (2018). \n55. Liu, Z. et al. Dendrite-free nanocrystalline zinc electrodeposition from an ionic liquid containing nickel triflate for rechargeable $Z\\mathrm{n}$ -based batteries. Angew. Chem. Int. Ed. 55, 2889–2893 (2016). \n56. Chen, S. et al. High-voltage lithium-metal batteries enabled by localized highconcentration electrolytes. Adv. Mater. 30, 1706102 (2018). \n57. Zhang, N. et al. Cation-deficient spinel $\\mathrm{ZnMn_{2}O_{4}}$ cathode in $\\mathrm{Zn}(\\mathrm{CF}_{3}\\mathrm{SO}_{3})_{2}$ electrolyte for rechargeable aqueous $Z\\mathrm{n}$ -ion battery. J. Am. Chem. Soc. 138, \n12894–12901 (2016). \n58. Zhang, C. et al. A $\\mathrm{ZnCl}_{2}$ water-in-salt electrolyte for a reversible Zn metal anode. Chem. Commun. 54, 14097–14099 (2018). \n59. Suo, L. et al. Fluorine-donating electrolytes enable highly reversible \n5-V-class Li metal batteries. Proc. Natl Acad. Sci. USA 115, 1156–1161 (2018). \n60. Gaarenstroom, S. W. & Winograd, N. Initial and final-state effects in esca spectra of cadmium and silver-oxides. J. Chem. Phys. 67, 3500–3506 (1977). \n61. Porto, S. P. S., Fleury, P. A. & Damen, T. C. Raman spectra of $\\mathrm{TiO}_{2}$ , $\\mathrm{MgF}_{2}$ $\\mathrm{ZnF}_{2}$ , $\\mathrm{FeF}_{2}$ and $\\mathrm{MnF}_{2}$ Phys. Rev. 154, 522 (1967). \n62. Damen, T. C., Porto, S. P. S. & Tell, B. Raman effect in zinc oxide. Phys. Rev. \n142, 570 (1966). \n63. Xu, K., Lam, Y., Zhang, S. S., Jow, T. R. & Curtis, T. B. Solvation sheath of $\\mathrm{Li^{+}}$ in nonaqueous electrolytes and its implication of graphite/electrolyte interface chemistry. J. Phys. Chem. C. 111, 7411–7421 (2007). \n64. Jia, W. et al. $\\mathrm{ZnF}_{2}$ coated three dimensional Li-Ni composite anode for improved performance. J. Materiomics 5, 176–184 (2019). \n65. Zhao, Q., Liu, X., Stalin, S., Khan, K. & Archer, L. A. Solid-state polymer electrolytes with in-built fast interfacial transport for secondary lithium batteries. Nat. Energy 4, 365 (2019). \n66. Yan, C. et al. An armored mixed conductor interphase on a dendrite-free lithium-metal anode. Adv. Mater. 30, 1804461 (2018). \n67. Yu, H. et al. Dendrite-free lithium deposition with self-aligned columnar structure in a carbonate–ether mixed electrolyte. Acs Energy Lett. 2, \n1296–1302 (2017). \n68. Yan, C. et al. Dual-layered film protected lithium metal anode to enable dendrite-free lithium deposition. Adv. Mater. 30, 1707629 (2018). \n69. Sun, W. et al. $\\mathrm{Zn/MnO}_{2}$ battery chemistry with $\\mathrm{H^{+}}$ and $Z\\mathrm{n}^{2+}$ coinsertion. J. Am. Chem. Soc. 139, 9775–9778 (2017). \n70. Louli, A. J. et al. Exploring the impact of mechanical pressure on the performance of anode-free lithium metal cells. J. Electrochem. Soc. 166, A1291–A1299 (2019). \n71. Chen, L. et al. Achieving high energy density through increasing the output voltage: a highly reversible $5.3\\mathrm{V}$ battery. Chem 5, 896–912 (2019). \n72. Chae, M. S., Heo, J. W., Lim, S.-C. & Hong, S.-T. Electrochemical zinc-ion intercalation properties and crystal structures of $\\mathrm{ZnMo}_{6}\\mathrm{S}_{8}$ and $\\mathrm{Zn}_{2}\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ chevrel phases in aqueous electrolytes. Inorg. Chem. 55, 3294–3301 (2016). \n73. Li, W., Wang, K., Cheng, S. & Jiang, K. A long-life aqueous $Z\\mathrm{n}$ -ion battery based on $\\mathrm{Na_{3}V_{2}(P O_{4})_{2}F_{3}}$ cathode. Energy Storage Mater. 15, 14–21 (2018). \n74. Zhang, L., Chen, L., Zhou, X. & Liu, Z. Towards high-voltage aqueous metalion batteries beyond $1.5\\mathrm{V}$ : the zinc/zinc hexacyanoferrate system. Adv. Energy Mater. 5, 1400930 (2015). \n75. Borodin, O., Behl, W. & Jow, T. R. Oxidative stability and initial decomposition reactions of carbonate, sulfone, and alkyl phosphate-based electrolytes. J. Phys. Chem. C. 117, 8661–8682 (2013). \n\n# Acknowledgements \n\nThe authors acknowledge the financial support from the National key R&D Program of China (Grant No. 2018YEB0104300), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA22010600), the National Natural Science Foundation for Distinguished Young Scholars of China (Grant No. 51625204), National Natural Science Foundation of China (Grant No. 21601195, U1706229), the Key research and development plan of Shangdong Province P. R. China (2018GGX104016), and the Youth Innovation Promotion Association of CAS (2019214, 2016193). \n\n# Author contributions \n\nH.Q. and X.D. contributed equally to the paper. G.C. and J.Z. proposed the concepts. H.Q. designed and carried out the experiments. X.D. and D.Y. performed the theoretical simulations. H.Q., Z.C., Z.H. and J.Z. analyzed the data. Y.W. and J.J. conducted the cross-sectional SEM studies. J.Z. supervised the research. H.Q. wrote the paper with the help from J.Z., G.C. and X.Z. All authors discussed the results and commented on paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 019-13436-3. \n\nCorrespondence and requests for materials should be addressed to J.Z., X.Z. or G.C. \n\nPeer review information Nature Communications thanks Masahiro Shimizu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1038_s41467-019-08460-2", + "DOI": "10.1038/s41467-019-08460-2", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-08460-2", + "Relative Dir Path": "mds/10.1038_s41467-019-08460-2", + "Article Title": "Enhanced strength-ductility synergy in ultrafine-grained eutectic high-entropy alloys by inheriting microstructural lamellae", + "Authors": "Shi, PJ; Ren, WL; Zheng, TX; Ren, ZM; Hou, XL; Peng, JC; Hu, PF; Gao, YF; Zhong, YB; Liaw, PK", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Realizing improved strength-ductility synergy in eutectic alloys acting as in situ composite materials remains a challenge in conventional eutectic systems, which is why eutectic high-entropy alloys (EHEAs), a newly-emerging multi-principal-element eutectic category, may offer wider in situ composite possibilities. Here, we use an AlCoCrFeNi2.1 EHEA to engineer an ultrafine-grained duplex microstructure that deliberately inherits its composite lamellar nature by tailored thermo-mechanical processing to achieve property combinations which are not accessible to previously-reported reinforcement methodologies. The as-prepared samples exhibit hierarchically-structural heterogeneity due to phase decomposition, and the improved mechanical response during deformation is attributed to both a two-hierarchical constraint effect and a self-generated microcrack-arresting mechanism. This work provides a pathway for strengthening eutectic alloys and widens the design toolbox for high-performance materials based upon EHEAs.", + "Times Cited, WoS Core": 703, + "Times Cited, All Databases": 737, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000457130800005", + "Markdown": "# Enhanced strength–ductility synergy in ultrafinegrained eutectic high-entropy alloys by inheriting microstructural lamellae \n\nPeijian Shi1, Weili Ren1, Tianxiang Zheng1, Zhongming Ren1, Xueling Hou2, Jianchao Peng2, Pengfei Hu2 \nYanfei Gao $\\textcircled{1}$ 3, Yunbo Zhong1 & Peter K. Liaw3 \n\nRealizing improved strength–ductility synergy in eutectic alloys acting as in situ composite materials remains a challenge in conventional eutectic systems, which is why eutectic highentropy alloys (EHEAs), a newly-emerging multi-principal-element eutectic category, may offer wider in situ composite possibilities. Here, we use an $\\mathsf{A l C o C r F e N i}_{2.1}$ EHEA to engineer an ultrafine-grained duplex microstructure that deliberately inherits its composite lamellar nature by tailored thermo-mechanical processing to achieve property combinations which are not accessible to previously-reported reinforcement methodologies. The as-prepared samples exhibit hierarchically-structural heterogeneity due to phase decomposition, and the improved mechanical response during deformation is attributed to both a two-hierarchical constraint effect and a self-generated microcrack-arresting mechanism. This work provides a pathway for strengthening eutectic alloys and widens the design toolbox for highperformance materials based upon EHEAs. \n\niven the energy-efficient improvement and large safety factors, the attainment of high strength and high ductility 一 in materials is arguably a vital requirement for most engineering applications. Unfortunately, these two properties are generally mutually exclusive, particularly in pure metals and alloys1–6. Eutectic alloys specifically exhibit good liquidity and castability, preventing common casting flaws, like internal shrinkage and compositional segregation, to downgrade mechanical properties6. They also possess a regularly arranged lamellar organization that can be viewed as a natural or in situ composite, which enables synergetic reinforcement to improve mechanical properties and sometimes bring unusual electrical, magnetic, and optical behaviors $7-11$ . Eutectic materials have therefore been investigated in diverse application fields, but traditionally, only certain eutectic systems have been of major commercial importance8–10. Recently, eutectic high-entropy alloys (EHEAs)11–13, first proposed by Lu et al. in $2014^{6}$ , were designed based on the above eutectic-alloy concept. Such alloys combine the advantages of both high-entropy alloys (HEAs)14,15 and conventional eutectic alloys, and usually show a fine dualphase lamellar microstructure with scarce casting defects6. Yet, owing to the absence of mature design theories at present, there are only a few EHEA systems which possess an attractive tensile behavior12,13, which could benefit from being further optimized. Moreover, the safety and advancement of modern technologies not only strongly relies on current mechanical properties of these eutectic alloys, but also calls for better ones7–10. \n\nTo date, many conventional routes to optimize eutectic alloys, such as processing to create line defects, usually result in reduced ductility6–8. Previous studies showed that engineering an ultrafinegrained duplex microstructure by severe cold-rolling and annealing could dramatically strengthen eutectic alloys although degrading ductility7. Recently, Wu et al. developed a heterogeneous structure of bimodal grains in Ti, which possesses $<30$ $\\mathrm{\\vol.\\%}$ soft, coarse-grained lamellae embedded in a hard, ultrafinegrained lamella matrix5,16. The resulting materials exhibited great ductility, as a high density of lamella interfaces could induce the building of large strain gradients across them during deformation. Meanwhile, the full deformation constraint imposed by the hard lamella matrix enables the soft lamellae to be almost as strong as the hard matrix, thus making materials with high strength16,17. So a remarkable strength–ductility enhancement is expected if we could inherit the heterogeneous lamellar nature via an appropriate thermo-mechanical treatment, instead of just tailoring a dualphase ultrafine-grained structure in eutectic alloys. \n\nInspired by the above idea, we architected a dual-phase heterogeneous lamella (DPHL) structure (Fig. 1) in a cold-rolled and annealed $\\mathrm{AlCoCrFeNi}_{2.1}$ $(\\mathrm{at\\%})$ EHEA (detailed processing procedure shown in Methods). Compared to the aforementioned heterogeneous lamella structure, our current structure features the strength heterogeneity with soft/hard phases instead of bimodal grains17, and simultaneously exhibits a higher lamella density arising from the full lamella nature of eutectic alloys. Furthermore, owning to phase decomposition, there are substantial hard intergranular B2 (ordered-body-centered-cubic) precipitates in the soft FCC (face-centered-cubic) lamella matrix, thereby imparting an additional rigid deformation constraint to FCC grains16,18. Unexpectedly, due to the introduction of the DPHL structure, the as-fabricated EHEAs can activate microcrack-arresting mechanisms (the extrinsically ductilizing effect) to further extend the strain-hardening ability (the intrinsically ductilizing effect) for great ductility at the late stage of deformation. In this study, we prepared three EHEAs with the DPHL structure, and denoted them as DPHL660, DPHL700, and DPHL740 as per their different annealing temperatures, to study their mechanical behavior and deformation mechanisms. \n\n# Results \n\nMicrostructure characterization. Similar to the as-cast EHEA (Fig. 1a), the tailored DPHL HEA showed a typical lamella morphology. Different lamella domains exhibited varied interlamella spacings $(1.5{-}5\\upmu\\mathrm{m})$ (Fig. 1b). These trends indicate the lamellar inheritance from the as-cast EHEA. There are also precipitated-out BCC (body-centered-cubic) phases of different sizes in the FCC lamellae (Fig. 1c). To better understand this microstructure, we conducted a detailed transmission electron microscopy (TEM) characterization coupled with energydispersive spectroscopy (EDS). Firstly, these lamellae consisted of recrystallized grains rather than simplex phase bands, and annealing twins were occasionally seen in FCC grains (Fig. 1d, g). Secondly, combining EDS maps and selected-area diffraction patterns (SADPs) suggested that the NiAl-rich lamellae (thickness of ${\\sim}1\\upmu\\mathrm{m}\\ '$ were B2 grains, and the enriched Fe and Cr lamellae corresponded to FCC grains (Fig. 1e and Supplementary Fig. 1). The average diameters of FCC and B2 grains are roughly comparable $(\\sim\\mathrm{{0.71\\upmum})}$ . Here, we did not detect the Cr-enriched BCC nano-precipitate within the B2 lamellae in our DPHL HEA (Supplementary Fig. 2), although it is well documented that in the as-cast EHEA, the $\\mathrm{Cr}$ -rich precipitates are densely dispersed inside the B2 lamellae6,12. Thirdly, as mentioned above, Fig. 1e, f also exhibited many BCC-phase precipitates in FCC lamellae. More specifically, they presented two types of NiAl-rich precipitates: the small and scarce P1 (intragranular B2 grains) of size $50\\mathrm{-}180~\\mathrm{nm}$ , and the large and primary P2 (intergranular B2 grains) with an average size of ${\\sim}350\\mathrm{nm}$ (Fig. 1f). Our results reveal a complex phase decomposition from the initial FCC lamellae19, which has now been detected in the EHEA category. This decomposition behavior has already been observed in some single-phase HEAs, such as the equiatomic CrMnFeCoNi $\\mathrm{HEA}^{19,20}$ , and originates from the limited entropic stabilization19. Before then, these alloys were widely accepted as a thermally stable single-phase solid solution, due to their ultrahigh mixing entropy19–21. Recently, Gwalani et al. linked the phase decomposition/precipitation incident with the competition between the thermodynamic driving force and activation barrier for the second-phase nucleation, synchronously coupled with the kinetics factor22. They suggested that the heavy cold-rolling provided high-energy interfaces, such as slip/twin bands and dislocations cell walls, which could act as heterogeneous nucleation sites for precipitates during annealing, consequently enabling a reduced heterogeneous nucleation barrier for the intergranular B2 and even σ phases22. Accordingly, as schematically illustrated in Fig. 1h, the developed DPHL structure shows a two-hierarchical heterogeneity2,16–18, which is composed of the submicron-grade FCC/B2 grains within the FCC lamellae and the micron-grade alternate FCC/B2 lamellae. Such structural characteristics were also seen in the other two DPHL HEAs (Supplementary Fig. 1). \n\nTensile properties. Figure 2a displays the mechanical behavior of three DPHL HEAs (detailed properties listed in Supplementary Table 1). To emphasize the markedly improved properties after engineering the DPHL structure, the curves of the ultrafinegrained EHEA7 and the as-cast EHEA are also shown. Deploying an ultrafine-grained duplex microstructure makes the EHEA twice stronger in yield strength than its as-cast sample, but comes at loss of ductility7. In contrast, our DPHL700 and DPHL740 with the inherited lamellar geometry exhibit a simultaneous strength–ductility enhancement, and even higher strengths over that of the ultrafine-grained EHEA. Recently, Bhattacharjee et al. processed a complex and hierarchical microstructure in the same AlCoCrFeN $\\mathrm{i}_{2.1}$ EHEAs by heavy cryo-rolling and annealing23, which shows a better strength–ductility balance (yield strength of \\~1.437 GPa and ductility of ${\\sim}14\\%$ than the ultrafine-grained EHEA7 and a comparable property combination to that of our DPHL660 (Fig. 2a). However, it is noted that the tensile data in ref. 23 is not consistent with its stress–strain curve, and the real data ought to be yield strength of ${\\sim}1.15\\mathrm{GPa}$ and ductility of ${\\sim}14\\%$ from the curve. This difference might be due to the abnormal tensile behavior after yielding (Fig. 2a). The dimensions of the tensile specimens in ref. 23 show that the sample is small, and the gage length, width, and thickness are $2\\mathrm{mm}$ , $1\\mathrm{mm}$ , and $300{\\upmu\\mathrm{m}}$ , respectively, while only one annealing condition, $800^{\\circ}\\mathrm{C}$ for $^\\mathrm{1h}$ , is applied. Thus, it is expected that uncertainty in the measurement of the properties could be larger due to possible drawbacks in small tensile specimens. In contrast, our slab cast by suction in the present research has a thickness $6\\mathrm{mm}$ , which is double than that of ref. 23. We use three annealing conditions of 660, 700, and $740^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ , and the dimensions of tensile specimens are $15\\mathrm{mm}$ in gage length, $3.2\\mathrm{mm}$ in width, and $600\\upmu\\mathrm{m}$ in thickness, which are typically consistent with the frequently reported dimensions in the literature16,18. All tensile tests were conducted, using a $12\\mathrm{-mm}$ extensometer to monitor the strain. All these features make the present tensile data more persuasive in comparison to ref. 23. That’s also why the above three data points in the banana curves are aligned at the same level of excellence, as revealed in our next discussion. Certainly, there are a few other routes (for instance, preparing nano-lamellar or near EHEAs) to strengthen the present EHEAs, but these strategies have not led to significant improvements in tensile properties12,23. To the best of our knowledge, the strength–ductility combination achieved in our work is not accessible to previously reported reinforcement methodologies. \n\n![](images/17d51d7109f623b6ac81f5d08cd56cd22e2e2a437825405848e4d4e941af0aea.jpg) \nFig. 1 Microstructures of the as-cast EHEA and the hierarchical DPHL700. a Electron-backscatter-diffraction (EBSD) phase image of the as-cast EHEA. b, c Scanning-electron-microscope (SEM) image, high-magnification SEM image, and EBSD-phase image of the DPHL HEA. RD, rolling direction; TD, transverse direction. d Scanning TEM (STEM) image exhibiting a more detailed $D P H L$ structure. e EDS maps of the identical region marked in d showing the distribution of Al, Ni, Co, Fe, and Cr. f Enlarged STEM image showing the distribution of P2 (the intergranular B2 phase, marked by blue arrows) and P1 (the intragranular B2 phase, marked by red arrow), and the corresponding SADPs and EDS composition profiles. g TEM image showing annealing twins. h Microstructural schematic sketch of the DPHL structure. AT, annealing twin. Scale bars, $20\\upmu\\mathrm{m}$ in a, b, $2\\upmu\\mathrm{m}$ in c, $1\\upmu\\mathrm{m}$ in d–f and $500\\mathsf{n m}$ in g \n\n![](images/23c29bc1829a66c2dacdfda2ac06619774ab11fb7079da4c30b059b3641e0632.jpg) \nFig. 2 Mechanical responses of the three DPHL HEAs at room temperature. a Tensile properties. UFG EHEA and CH EHEA refer to the ultrafine-grained EHEA7, and the complex and hierarchical EHEA23, respectively. The inset is the loading–unloading–reloading behavior of the DPHL700 and the as-cast EHEA (whole curves exhibited in Supplementary Fig. 3). b Strain-hardening response. As a representative, the multistage stress–strain relationships are marked as I–III in DPHL700. The inset shows the back-stress (BS) and effective-stress (ES) evolution with the plastic strain for the as-cast EHEA and DPHL700. Error bars in the inset indicate standard deviations for five tests \n\nFigure 2b gives the strain-hardening rate $\\left(\\Theta\\right)$ versus true strain curves. Interestingly, $\\Theta$ first drops quickly in region I, even to below zero in the curve of DPHL740, then is followed by an upturn to reach its maximum in region II, which is often observed in heterogeneous structures recently16,18,24. Wu et al. reported that such transient behavior is due to the lack of mobile dislocations16, which can not effectively accommodate the imposed constant strain rate at the onset of plastic deformation in region I. Upon yielding, dislocation multiplication and tangle is responsible for the rapid $\\Theta$ increase16 in region II. Due to a few regions with a high dislocation density before the tensile deformation in our DPHL660 (Supplementary Fig. 1a), the resulting strain-hardening curve shows an obviously weakened transient behavior in Fig. 2b. In addition, the as-built DPHL700 shows a striking ability of sustaining high $\\Theta$ over a wide strain region III, which is a prerequisite for attractive tensile ductility1–3. To better understand the origin of the observed high yield strength and strain hardening, we conducted loading–unloading–reloading (LUR) testing. The inset of Fig. 2a shows two LUR curves of the DPHL700 as a representative of DPHL-HEA samples and the ascast EHEA for comparison. Both of them exhibit a hysteresis loop, which reveals the existence of Bauschinger effect16. Here, as reported in ref. 16, we divided the flow stress into the back-stress associated with a long-range stress on mobile dislocations and the effective stress required locally for the dislocation movement. Additionally, we estimated the contributions of the above two kinds of stresses to the flow stress from the LUR curves24 (inset in Fig. 2b). Overall, these mechanical features indicate that we could optimize eutectic-alloy properties by inheriting its composite lamellar nature in the ultrafine-grained EHEAs. \n\n# Discussion \n\nAfter achieving the desirable properties in the AlCoCrFeNi2.1 EHEAs, it naturally follows to analyze the strengthening mechanisms lying behind the enhanced strength–ductility synergy. Here, only upon a clear comprehension of the deformation processes of the hierarchical DPHL HEAs can we reasonably account for the observed mechanical response. \n\nFirst, we systematically discuss the high yield strength (Fig. 2a). During tensile deformation, after the soft FCC and hard B2 phases co-deformed elastically, the soft FCC lamella matrix is more susceptible to starting plastic deformation (Fig. 3a, d). Nevertheless, the soft FCC matrix cannot plastically deform freely, owning to the constraint by the still elastic B2 lamellae. Considering the strain continuity, this implies the existence of plastic-strain gradients in the soft lamella matrix near lamella interfaces3,16. Accommodation of such strain gradients needs the storage of geometrically necessary dislocations (GNDs). Consequently, this process produces a long-range back-stress, making dislocations difficult to move in FCC grains until B2 grains start to yield deformation5. Here it should be mentioned that the coarse-grained FCC matrix is synchronously surrounded by the intergranular B2 phase in FCC lamellae (Fig. 3a and Supplementary Fig. 4). As per the analysis above, the same back-stress is also produced, yet in another $\\mathrm{size}^{18}$ . Ultimately, under such twohierarchical constraints, the FCC grains appear much stronger than when they are not constrained, producing so-called synergetic strengthening and significantly elevating the material yield strength17. Meanwhile, as shown in the inset of Fig. 2b, the backstress $({\\sim}950\\mathrm{MPa})$ of the closest to yield point is ${\\sim}3$ times higher than the effective stress in DPHL700, which quantitatively explains that the larger back-stress is primarily responsible for the observed high yield strength24. The high back-stress can therefore be regarded as a long-range internal stress connected with a local strain process, which enables the long-range interaction with mobile dislocations16–18. Correspondingly, the low effective stress is therefore the stress required locally for a dislocation to move, which is related to the short-range interaction in a similar way to friction stress and forest hardening16–18. \n\nSecond, we focus on the extra strain-hardening capacity prevailing in stage III (Fig. 2b). Beyond the yield point, both the soft and hard lamellae will deform plastically (Fig. 3a, d). But because the soft FCC grains deform easily, the FCC lamella matrix bear more plastic strains than hard B2 lamellae. Further strain gradients therefore appear17. However, the strain gradients in this case are built up not only in the soft but also hard lamellae near lamella boundaries. These strain gradients will become larger with ongoing deformation and thereby require more GNDs, leading to high back-stress hardening1,17. According to this theory, the same strain gradients and thus back-stress hardening will also appear in FCC lamellae due to the intergranular B2 phase5. Ultimately, they contribute to the observed high strain hardening together. This implies that an increased hard/brittle B2-phase content may still lead to the DPHL HEAs sustaining large or higher ductility12,25, in contrast to the as-cast EHEA. \n\nSimilarly, the excellent ductility for the above complex and hierarchical EHEA mainly stems from the strong back-stress hardening effect23. As reported by Bhattacharjee et al., a developed hierarchical microstructure is composed of two parts: the fine dual-phase lamellar region and the coarse dual-phase nonlamellar region23. Such a hierarchical architecture can provide substantial domain boundaries separating areas of diverse hardness, consequently being particularly favorable to benefiting from back-stress hardening and thus great ductility16,18,23. In the hierarchical structure, there are coarse non-lamellar regions featuring a mixture of soft FCC and hard B2 phases. Although these regions allow significant strain partitioning to induce back-stress strengthening, the soft FCC phase also allows the material to yield at low stress, owning to the absence of the lamellar constraint effect17. That is why a previous hierarchical structure23 shows a limited improvement in the yield strength compared to the corresponding ultrafine-grained EHEA7. Recently, Yang et al. reported work in a single-phase medium-entropy alloy26, where they purposely architectured a three-level heterogeneous grain structure with grain sizes spanning the nanometer-to-micrometer range via partial recrystallization annealing following conventional cold-rolling, achieving large uniform tensile strain $(\\sim22\\%)$ after yielding even at the gigapascal stress. They attributed these improved properties to high back-stress strengthening caused by structurally inhomogeneous deformation characteristics. On the one hand, the partially recrystallized starting structure with heterogeneous grain sizes supports the inhomogeneous plastic strain. On the other hand, the heterogeneous structure becomes even more heterogeneous during tensile straining as more twins, faults, and nano-grains with high-angle grain boundaries are generated dynamically owing to the low stacking fault energy, as well as the dislocations, leading to increased inhomogeneous plastic deformation. This implies a dynamically reinforced heterogeneous grain structure inducing strong back-stress hardening. In our work, the DPHL structure maintains its heterogeneous configuration during the entire plastic deformation which is only assisted by dislocations, without additional deformation mechanisms observed (Fig. 3c). Furthermore, compared to the above heterogeneous grain structure, our DPHL structure exhibits high hetero-interface density16,17 due to its composite lamellar nature, leading to an enhanced back-stress hardening potential16,17 regardless of additional mechanisms introduced during tensile deformation. \n\n![](images/c5f8a6182abdbd750b9e4b59d5154fa7f97b53c9ec3aec3aefa8ed9da3569f2c.jpg) \nFig. 3 Deformation micro-mechanisms in the hierarchical DPHL HEA with the increasing tensile strain. a STEM images showing the dislocationsubstructure evolution. The early stage of deformation $\\begin{array}{r}{\\langle\\varepsilon=4\\%\\rangle}\\end{array}$ ) leads to more obvious dislocations in soft FCC grains than hard P2 (the intergranular B2 grains) and B2 grains near phase interfaces. At medium strains $\\begin{array}{r}{\\langle\\varepsilon=13\\%}\\end{array}$ ), there exhibit significantly-increased dislocations in FCC grains and P2. The piling-up of GNDs is marked by dashed red lines in FCC grains. b, c STEM images of the microstructure stretched to fracture $\\begin{array}{r}{\\langle\\varepsilon=21\\%\\rangle}\\end{array}$ . The dual-phase lamellae and P2 (indicated by yellow dashed lines and red arrows, respectively) show apparent dislocations. b Microcrack propagation stays confined/ blunted by neighboring lamellae. c The dashed blue arrows point out different deformation directions, and even some FCC grains deform along two directions. d Schematic illustration of the dislocation evolution during deformation. Stage I: elastic deformation; Stage II: elastic-plastic deformation; Stage III: plastic deformation. ⊥, dislocation. Note that stage I in d is not the schematic illustration of $\\varepsilon=4\\%$ in a. Scale bars, $200\\mathsf{n m}$ in a, b and $1\\upmu\\mathrm{m}$ in c \n\nTo further verify that the observed mechanical response is led by the inherited lamellar geometry in the ultrafine-grained EHEAs, we analyze the microstructure of DPHL700 stretched to fracture. As shown in Fig. 3c, the originally equiaxed grains were subjected to a large amount of inhomogeneous plastic deformation, and the initially smooth lamella interfaces became ragged and convoluted. Unexpectedly, FCC grains deformed along different directions, not a single tensile direction (Fig. 3c and Supplementary Fig. 4). These phenomena hint that the twohierarchical constraint deformation effectively built up, and the dynamic hardening effect violently happened5 (Supplementary Fig. 4). Besides massive dislocations in FCC grains, there are also pronounced dislocations in both B2 lamellae and intergranular B2 grains (Fig. 3c), which shows that B2 grains can also plastically deform and sustain strain hardening in tension18. This provides direct evidence that forest dislocations have mediated dislocation hardening and contributed to the observed high strain-hardening capability16. In contrast, in the as-cast EHEA, many dislocations are generated/blocked in the soft FCC phase near phase boundaries, while no obvious dislocations are observed in the hard B2 phase12. This phenomenon is reflected by the fast-growing backstress and little-varied effective stress in this investigation27 (inset in Fig. 2b). Eventually, this process causes strain localization (Supplementary Fig. 5) rather than kinematic strain partitioning, degrading the EHEA’s properties5,27. We, therefore, conclude that the ultrafine-grained EHEAs with the inherited lamellar architecture promote the improved properties. A further corroboration to the importance of the inherited lamellar nature is given when we modify our specimen by increasing the annealing temperature $(900^{\\circ}\\mathrm{C})$ to induce a less ideal, partially degraded lamellar structure (Supplementary Fig. 1c, d), which leads to inferior tensile properties (Supplementary Fig. 6). Such an observation also lends support to the aforementioned assertions about deformation processes and strengthening mechanisms. \n\nFurthermore, we analyze the damage-evolution mechanisms of DPHL700 at the late stage of deformation. There are extensive uniformly distributed microcracks near the fractured end, instead of large (secondary) cracks usually seen in most cases (Fig. 4a). These microcracks exhibit varied and complex morphologies, and include circle-like, tortuous, and even submicron cracks. Here, the circle-like cracks appear to be the primary damage incident, with additional long and tortuous cracks (Fig. 4a, b). During deformation, such multiple microcracks can effectively weaken the high localized stress28. However, in our case, the formation of large cracks by the coalescence of small microcracks was found to be inhibited, even when some of the microcracks are separated by only a single lamella (Fig. 3b and Fig. 4b). To elucidate this phenomenon, further microstructure observations found that after the heavy-rolling deformation $(84-86\\%)$ , the resultant samples possess massive special lamellae $({\\sim}82{-}87\\ \\mathrm{vol.}\\%)$ with a directionally aligned arrangement along the rolling direction29 (Supplementary Fig. 7). It should be noted that the aligned arrangement here does not refer to the orientation behavior as in crystallography. With their special lamellar architecture, the DPHL materials are akin to artificially fabricated laminated composites30. The ductile components such as the FCC matrix, and even the hard B2 lamellae in the current samples, will therefore work well as very efficient crack arresters to delay crack propagation and coalescence during deformation:30 this is experimentally supported by the existence of restrained circle-like microcracks with blunted crack-tips (Fig. 4c, d). Eventually, these incidents delay the onset of global damage, enabling the further intrinsic kinematic hardening and inducing additional ductility (Fig. 4e). Such damage-evolution process does not take place in the as-cast EHEA even though they have a similar dual-phase lamellar structure, as these cracks with a simplex shape are primarily nucleated at the phase boundaries of the as-cast EHEA. Once initiated, they rapidly start to propagate and coalesce into long and large cracks along the lamellar interfaces due to the internal-stress accumulation and strain localization in FCC lamellae near phase boundaries28 (Supplementary Fig. 5). \n\n![](images/409d509238dbdd66310dfe02cf3ccec5aa332b4d59c96d741279959009e7dd64.jpg) \nFig. 4 Typical SEM images of damage-evolution mechanisms for the hierarchical DPHL HEA at the late stage of deformation. a Microcrack distribution near the fractured end. b Multiple microcracks mainly including circle-like, tortuous, and even submicron cracks (indicated by red, blue, and yellow arrows, respectively). c At strains of $17-20\\%$ , the circle-like microcracks with blunted crack-tips, whose propagation remains confined by adjacent ductile components. d High-magnification SEM image indicating that these circle-like cracks are initially nucleated predominantly in FCC lamellae and caused by the limited deformation ability of P2 (the intergranular B2 phase, marked by dashed red circles), which are revealed at the strain of ${\\sim}17\\%$ . e Fractography of the fracture surface with massive dimples, providing an indirect explanation for the enhanced ductility. Scale bars, $50\\upmu\\mathrm{m}$ in a, $10\\upmu\\mathrm{m}$ in b, $5\\upmu\\mathrm{m}$ in c, $1\\upmu\\mathrm{m}$ in d, and $5\\upmu\\mathrm{m}$ in e \n\n![](images/951c56354f778bdf1842b6f49201409b0343452e0d56d96c6e46966bffef9796.jpg) \nFig. 5 Tensile properties of the hierarchical DPHL HEAs in comparison with the traditional metallic materials and the previously-reported hardened HEAs. a, b A general summary of the fundamental tensile properties at ambient temperature. Note that the reported HEAs, including the as-cast EHEA12,13, ultrafine-grained (UFG) EHEA7, complex and hierarchical (CH) EHEA23, dual-phase HEAs33, metastable brittle ${\\mathsf{H E A s}}^{4}$ , precipitation-hardened ${\\mathsf{H E A s}}^{32}$ , and carbon-doped $H E A s^{31}$ , are the products of several of the most effective strengthening mechanisms among HEAs in general, but they only show the better tensile strength–ductility synergy, in comparison to traditional alloys. There, of course, are a few advanced HEAs not shown for comparison, due to their low yield strength (for example, $<400M{\\sf P a})^{35}$ and poor room-temperature properties \n\nFigure 5 shows a comparison of tensile properties of the hierarchical DPHL HEAs with various advanced steels, traditional alloys, and other reported HEAs with superior mechanical properties4,7,12,13,15,23,31–33. In Fig. 5a, both the current DPHL \n\nHEAs and previously reported HEAs are separated from the general trend for conventional metallic materials, suggesting a favorable tensile strength–ductility combination. However, in the yield strength-elongation map (Fig. 5b), only our DPHL HEAs stand out from the trend. This reveals a common phenomenon/ problem that it is currently possible (though difficult) to achieve great tensile strength–ductility balance in HEAs, but very challenging to simultaneously possess sufficiently high yield strength. Recently, Liang et al. prepared ultrastrong precipitationhardening high-entropy alloys (PH-HEAs)34. Different from the common PH-HEA design idea, they explored a non-equiatomic alloy as a prototype specimen, and then utilized spinodal decomposition to create a low-misfit coherent nanostructure. This enhanced the ability to achieve higher contents of nanoprecipitates, and also helped obtain a near-equiatomic, highentropy FCC matrix enabling ultrahigh yield strength $({\\sim}1570{\\mathrm{-}}1810\\mathrm{MPa})$ while retaining good ductility $({\\sim}9{-}10\\%)$ Therefore, we believe that further efforts will be devoted to this direction in the future26,34. In the present work, the yield strength on the order of $1.5\\mathrm{GPa}$ along with $\\sim16\\%$ elongation have rarely been achieved in existing HEAs (Fig. 5b). Hence our DPHL HEAs and some other ultrastrong $\\mathrm{HEAs}^{26,34}$ with ultrahigh yield strength and good ductility expand known performance boundaries and exhibit great potential to improve energy efficiency and system performance in numerous fields, such as aerospace, transportation, and civilian infrastructure. More importantly, it demonstrates that inheriting the composite lamellar nature from the as-cast EHEA can be an effective way to prepare highperformance HEAs. \n\nIn this work, we successfully achieve a superior strength–ductility combination in AlCoCrFeNi2.1 EHEAs by introducing two concurrent effects, the two-hierarchical constraint effect and the self-generated microcrack-arresting mechanisms. The underlying origin lying behind the observed mechanical response is the inherited lamellar geometry from the as-cast EHEA. It is known that grain refinement to the nano/ ultrafine-grained regime can render material stronger, but this process is usually accompanied by a dramatic loss of ductility1–5. However, with a composite lamellar architecture, the ultrafinegrained duplex microstructure in this study achieves an improved strength–ductility synergy. Phase decomposition is applied to optimize properties instead of just being a phase-instability phenomenon frequently observed in single-phase HEAs, which may encourage further research in this area. In addition, the $\\mathrm{AlCoCrFeNi_{2.1}}$ EHEA could be simply processed to achieve properties that are an improvement over traditional TRIP (transformation-induced plasticity) and TWIP (twinninginduced plasticity) steels (Fig. 5). We believe that the simplicity in the present processing procedure is extremely attractive for industrial applications. Meanwhile, we anticipate that the investigated EHEA based on the present strengthening strategy can be further modified to satisfy more demanding application requirements, such as high-temperature and/or corrosion environments6,11,12,15. In conclusion, our results provide a promising pathway to strengthen eutectic alloys and prepare highperformance HEAs. \n\n# Methods \n\nSample preparation. The ingots with a nominal composition of $\\mathrm{AlCoCrFeNi}_{2.1}$ $(\\mathrm{at\\%})$ was prepared by arc-melting a mixture of the constituent elements (purity better than $99.9\\mathrm{wt\\%}$ ) in a Ti-gettered high-purity argon atmosphere. The melting was repeated at least five times to achieve a good chemical homogeneity of the alloy. The molten alloy was suction-cast into a $30\\mathrm{mm\\(width)}\\times100\\mathrm{mm}$ $\\mathrm{(length)}\\times6\\mathrm{mm}$ (thickness) copper mold. Small pieces [dimensions: $50\\mathrm{mm}$ $\\mathrm{(length)}\\times25\\mathrm{mm}\\ \\mathrm{(width)}\\times4\\mathrm{mm}$ (thickness)] were extracted from the as-cast \n\nmaterial and subjected to multi-pass cold-rolling to $84\\mathrm{-}86\\%$ reduction in thickness (the final thickness of ${\\sim}600\\ \\upmu\\mathrm{m})$ using a laboratory-scale two-high rolling machine. The cold-rolled sheets were non-isothermally annealed to various temperatures. More specifically, four samples were, respectively, annealed from room temperature at 660, 700, 740, and $900^{\\circ}\\mathrm{C}$ with the constant heating rate of $10^{\\circ}\\mathrm{C}\\ \\mathrm{min}^{-1}$ , held at these four temperatures for $^{\\textrm{1h}}$ and then water quenched immediately. We denote them as DPHL660, DPHL700, DPHL740, and DPHL900, respectively, in this study. Note that by the extraction of small pieces from the as-cast material, we can obtain high-quality samples with no or few surface defects (such as oxide films), smooth surfaces, and uniform thickness, for the subsequent cold-rolling and annealing treatment, which is able to prevent other factors to influence and even deteriorate mechanical properties. Please see ref. 24, which shows the related equations and procedures for calculating the back-stress and effective stress from the loading–unloading–reloading (LUR) curve. \n\nMicrostructure characterization and tensile test. The EBSD and SEM observations were conducted by the CamScan Apollo 300 SEM equipped with a HKL–Technology EBSD system. The TEM analyses were operated on JEM–2100 F at $200\\mathrm{kV}$ . The samples for EBSD and TEM were prepared, using a mixture of the $90\\%$ ethanol and $10\\%$ perchloric acid $\\left(\\mathrm{vol.\\%}\\right)$ . All tensile specimens were dog-boneshaped, with a gauge length of $15\\mathrm{mm}$ , a width of $3.2\\mathrm{mm}$ , and a thickness of 600 $\\upmu\\mathrm{m}$ . In terms of the ultrafine-grained material, here, such tensile dimensions are typically consistent with that frequently reported in the literature16,18. Meanwhile, there are over 400 grains along the thickness direction in specimens (Fig. 1 and Supplementary Fig. 1a, b), which far exceeds the grain number $(\\sim100)$ required theoretically to ensure the representativeness and reproducibility of tensile data at a larger scale. Moreover, to obtain the reproducible tensile property, all tensile tests were repeated five times. The direction of tensile tests was parallel to the rolling direction. Tensile tests were carried out at room temperature using an MTS Criterion Model 44 with an initial strain rate of $2.5\\times10^{-\\mathrm{\\bar{4}}}\\mathrm{s}^{-1}$ . The condition for LUR tests was the same as that of the monotonic tensile test. Upon straining to a designated strain at the strain rate of $2.5\\times10^{-4}{{\\sf s}}^{-1}$ , the specimen was unloaded by the stress-control mode to $20\\mathrm{N}$ at the unloading rate of $\\bar{2}00\\mathrm{N}\\operatorname*{min}^{-1}$ , followed by reloading at a strain rate of $2.5\\times10^{-4}s^{-1}$ to the same applied stress before the next unloading. All tensile tests were conducted, using a $12\\mathrm{-mm}$ extensometer to monitor the strain. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\nReceived: 23 June 2018 Accepted: 20 December 2018 \nPublished online: 30 January 2019 \n\n# References \n\n1. Wang, Y. M., Chen, M. W., Zhou, F. H. & Ma, E. High tensile ductility in a nanostructured metal. Nature 419, 912–915 (2002). \n2. Wang, Y. M. et al. Additively manufactured hierarchical stainless steels with high strength and ductility. Nat. Mater. 17, 63–71 (2018). \n3. Lu, K. Making strong nanomaterials ductile with gradients. Science 345, \n1455–1456 (2014). \n4. Huang, H. L. et al. Phase-transformation ductilization of brittle high-entropy alloys via metastability engineering. Adv. Mater. 29, 1701678 (2017). \n5. Ma, E. & Zhu, T. Towards strength–ductility synergy through the design of heterogeneous nanostructures in metals. Mater. Today 20, 323–331 (2017). \n6. Lu, Y. P. et al. A promising new class of high-temperature alloys: eutectic high-entropy alloys. Sci. Rep. 4, 6200 (2014). \n7. Wani, I. S. et al. Ultrafine-grained AlCoCrFeNi2.1 eutectic high-entropy alloy. Mater. Res. Lett. 4, 174–179 (2016). \n8. Tan, Y. Z. et al. Microstructures, strengthening mechanisms and fracture behavior of Cu–Ag alloys processed by high-pressure torsion. Acta Mater. 60, \n269–281 (2012). \n9. Jana, S., Mishra, R. S., Baumann, J. B. & Grant, G. Effect of friction stir processing on fatigue behavior of an investment cast Al–7Si–0.6 Mg alloy. Acta Mater. 58, 989–1003 (2010). \n10. Wang, L., Shen, J., Shang, Z. & Fu, H. Z. Microstructure evolution and enhancement of fracture toughness of NiAl–Cr(Mo)–(Hf,Dy) alloy with a small addition of Fe during heat treatment. Scr. Mater. 89, 1–4 (2014). \n11. Guo, S., Ng, C. & Liu, C. T. Sunflower-like solidification microstructure in a near-eutectic high-entropy Alloy. Mater. Res. Lett. 1, 228–232 (2013). \n12. Lu, Y. P. et al. Directly cast bulk eutectic and near-eutectic high entropy alloys with balanced strength and ductility in a wide temperature range. Acta Mater. \n124, 143–150 (2017). \n13. Jin, X., Zhou, Y., Zhang, L., Du, X. Y. & Li, B. S. A novel $\\mathrm{Fe_{20}C o_{20}N i_{41}A l_{19}}$ eutectic high entropy alloy with excellent tensile properties. Mater. Lett. 216, 144–146 (2018). \n14. Yeh, J. W. et al. Nanostructured high-entropy alloys with multiple principal elements: novel alloy design concepts and outcomes. Adv. Eng. Mater. 6, 299–303 (2004). \n15. Ye, Y. F., Wang, Q., Lu, J., Liu, C. T. & Yang, Y. High-entropy alloy: challenges and prospects. Mater. Today 19, 349–362 (2016). \n16. Wu, X. L. et al. Heterogeneous lamella structure unites ultrafine-grain strength with coarse-grain ductility. Proc. Natl Acad. Sci. USA 112, 14501–14505 (2015). \n17. Wu, X. L. & Zhu, Y. T. Heterogeneous materials: a new class of materials with unprecedented mechanical properties. Mater. Res. Lett. 5, 527–532 (2017). \n18. Yang, M. X. et al. Strain hardening in Fe–16Mn–10Al–0.86C–5Ni high specific strength steel. Acta Mater. 109, 213–222 (2016). \n19. Schuh, B. et al. Mechanical properties, microstructure and thermal stability of a nanocrystalline CoCrFeMnNi high-entropy alloy after severe plastic deformation. Acta Mater. 96, 258–268 (2015). \n20. Otto, F. et al. Decomposition of the single-phase high-entropy alloy CrMnFeCoNi after prolonged anneals at intermediate temperatures. Acta Mater. 112, 40–52 (2016). \n21. He, F. et al. Phase separation of metastable CoCrFeNi high entropy alloy at intermediate temperatures. Scr. Mater. 126, 15–19 (2017). \n22. Gwalani, B. et al. Modifying transformation pathways in high entropy alloys or complex concentrated alloys via thermo-mechanical processing. Acta Mater. 153, 169–185 (2018). \n23. Bhattacharjee, T. et al. Simultaneous strength–ductility enhancement of a nano-lamellar AlCoCrFeNi2.1 eutectic high entropy alloy by cryo-rolling and annealing. Sci. Rep. 8, 3276 (2018). \n24. Yang, M. X., Pan, Y., Yuan, F. P., Zhu, Y. T. & Wu, X. L. Back stress strengthening and strain hardening in gradient structure. Mater. Res. Lett. 4, 145–151 (2016). \n25. Qi, L. & Chrzan, D. C. Tuning ideal tensile strengths and intrinsic ductility of bcc refractory alloys. Phys. Rev. Lett. 112, 115503 (2014). \n26. Yang, M. X. et al. Dynamically reinforced heterogeneous grain structure prolongs ductility in a medium-entropy alloy with gigapascal yield strength. Proc. Natl Acad. Sci. USA 115, 7224–7229 (2018). \n27. Li, Y., Li, W., Min, N., Liu, W. Q. & Jin, X. J. Effects of hot/cold deformation on the microstructures and mechanical properties of ultra-low carbon medium manganese quenching-partitioning-tempering steels. Acta Mater. 139, 96–108 (2017). \n28. Huang, L. J., Geng, L. & Peng, H. X. Microstructurally inhomogeneous composites: is a homogeneous reinforcement distribution optimal? Prog. Mater. Sci. 71, 93–168 (2015). \n29. Liu, Z. Y., Xiao, B. L., Wang, W. G. & Ma, Z. Y. Developing high-performance aluminum matrix composites with directionally aligned carbon nanotubes by combining friction stir processing and subsequent rolling. Carbon N. Y. 62, 35–42 (2013). \n30. Wu, H. et al. Deformation behavior of brittle/ductile multilayered composites under interface constraint effect. Int. J. Plast. 89, 96–109 (2017). \n31. Wang, Z. W., Baker, I., Guo, W. & Poplawsky, J. D. The effect of carbon on the microstructures, mechanical properties, and deformation mechanisms of thermo-mechanically treated $\\mathrm{Fe_{40.4}N i_{11.3}M n_{34.8}A l_{7.5}C r_{6}}$ high entropy alloys. Acta Mater. 126, 346–360 (2017). \n32. He, J. Y. et al. A precipitation-hardened high-entropy alloy with outstanding tensile properties. Acta Mater. 102, 187–196 (2016). \n33. Baker, I., Meng, F. L., Wu, M. & Brandenberg, A. Recrystalliztion of a novel two-phase FeNiMnAlCr high entropy alloy. J. Alloy Compd. 656, 458–464 (2016). \n34. Liang, Y. J. et al. High-content ductile coherent nanoprecipitates achieve ultrastrong high-entropy alloys. Nat. Commun. 9, 4063 (2018). \n35. Li, Z. M., Pradeep, K. G., Deng, Y., Raabe, D. & Tasan, C. C. Metastable highentropy dual-phase alloys overcome the strength–ductility trade-off. Nature 534, 227–230 (2016). \n\n# Acknowledgements \n\nThe present research was supported by the National Key Research and Development Program of China (2016YFB0300401), the National Natural Science Foundation of China (U1732276, U1860202), and the Science and Technology Commission of Shanghai Municipality (Key Project No. 15520711000). We thank C.J. Song and Z.H. Hu for their help with tensile tests, J.L. Zhang and H.W. Zhang for the cold-rolled sample preparation, and H. Wang and N. Min for the TEM characterization at Shanghai University. \n\n# Author contributions \n\nY.Z. and P.S. designed the study. P.S. carried out the main experiments. T.Z. and X.H. processed the alloy samples. P.K.L., W.R., Y.Z., Y.G. and P.S. analyzed the data and wrote the main draft of the paper. J.P. and P.H. conducted the TEM characterization. All authors discussed the results and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-08460-2. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41560-019-0474-3", + "DOI": "10.1038/s41560-019-0474-3", + "DOI Link": "http://dx.doi.org/10.1038/s41560-019-0474-3", + "Relative Dir Path": "mds/10.1038_s41560-019-0474-3", + "Article Title": "All-temperature batteries enabled by fluorinated electrolytes with non-polar solvents", + "Authors": "Fan, XL; Ji, X; Chen, L; Chen, J; Deng, T; Han, FD; Yue, J; Piao, N; Wang, RX; Zhou, XQ; Xiao, XZ; Chen, LX; Wang, CS", + "Source Title": "NATURE ENERGY", + "Abstract": "Carbonate electrolytes are commonly used in commercial non-aqueous Li-ion batteries. However, the high affinity between the solvents and the ions and high flammability of the carbonate electrolytes limits the battery operation temperature window to -20 to + 50 degrees C and the voltage window to 0.0 to 4.3 V. Here, we tame the affinity between solvents and Li ions by dissolving fluorinated electrolytes into highly fluorinated non-polar solvents. In addition to their non-flammable characteristic, our electrolytes enable high electrochemical stability in a wide voltage window of 0.0 to 5.6 V, and high ionic conductivities in a wide temperature range from -125 to + 70 degrees C. We show that between -95 and + 70 degrees C, the electrolytes enable LiNi0.8Co0.15Al0.05O2 cathodes to achieve high Coulombic efficiencies of >99.9%, and the aggressive Li anodes and the high-voltage (5.4 V) LiCoMnO4 to achieve Coulombic efficiencies of >99.4% and 99%, respectively. Even at -85 degrees C, the LiNi0.8Co0.15Al0.05O2 parallel to Li battery can still deliver similar to 50% of its room-temperature capacity.", + "Times Cited, WoS Core": 696, + "Times Cited, All Databases": 750, + "Publication Year": 2019, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000489768100019", + "Markdown": "# All-temperature batteries enabled by fluorinated electrolytes with non-polar solvents \n\nXiulin Fan1,2,4, Xiao Ji $\\textcircled{10}1,4$ , Long Chen1,4, Ji Chen1, Tao Deng1, Fudong Han1, Jie Yue1, Nan Piao1, Ruixing Wang3, Xiuquan Zhou   3, Xuezhang Xiao $\\oplus2$ , Lixin Chen2 and Chunsheng Wang   1,3\\* \n\nCarbonate electrolytes are commonly used in commercial non-aqueous Li-ion batteries. However, the high affinity between the solvents and the ions and high flammability of the carbonate electrolytes limits the battery operation temperature window to $-20$ to $+50\\textdegree$ and the voltage window to 0.0 to 4.3 V. Here, we tame the affinity between solvents and Li ions by dissolving fluorinated electrolytes into highly fluorinated non-polar solvents. In addition to their non-flammable characteristic, our electrolytes enable high electrochemical stability in a wide voltage window of 0.0 to ${\\mathsf{\\pmb{5.6}}}{\\mathsf{\\pmb{v}}},$ and high ionic conductivities in a wide temperature range from −125 to $+70\\textdegree$ . We show that between $-95$ and $+70^{\\circ}C_{1}$ , the electrolytes enable $\\mathbf{LiNi}_{0.8}\\mathsf{C o}_{0.15}\\mathsf{A l}_{0.05}\\mathsf{O}_{2}$ cathodes to achieve high Coulombic efficiencies of $>99.9\\%$ , and the aggressive Li anodes and the high-voltage (5.4 V) LiCoMnO4 to achieve Coulombic efficiencies of $>99.4\\%$ and $99\\%$ , respectively. Even at $-85^{\\circ}C$ , the L $\\mathbf{iNi}_{0.8}\\mathsf{C o}_{0.15}\\mathsf{A l}_{0.05}\\mathsf{O}_{2}||$ Li battery can still deliver ${\\sim}50\\%$ of its room-temperature capacity. \n\nn recent decades, the number of electric vehicles has expanded exponentially due to the significant reduction in cost of Li-ion batteries $(\\mathrm{LIB}s)^{1-8}$ . More than $60\\%$ of manufactured LIBs have been deployed in applications in transportation electrificaiton9–12. Hybrid and electrical vehicles urgently call for high-energy LIBs that are safe and capable of operating over a wide operational temperature range10,11. Commercial Li-ion batteries with ethylene carbonate (EC)-based electrolytes can only operate in the temperature range $-20$ to $+5^{\\circ}\\mathrm{C}$ . In addition, EC-based electrolytes are highly flammable, which could cause fires or even explosions under harsh operational and abuse conditions. Extensive efforts have been devoted to expand the operational ranges of Li-ion batteries. The most successful methods are: adding small amount of additives in the electrolytes13,14, externally heating and insulating the cells15 and self-heating the $\\mathsf{c e l l}^{12,16}$ . However, these strategies also reduce the energy and power density of the LIBs. The use of liquefied $\\mathrm{CO}_{2}$ and fluoromethane gas as an electrolyte enables the Li-ion battery to retain ${\\sim}60\\%$ of its room-temperature capacity at $-60^{\\circ}\\mathrm{C}$ (ref. 17), representing a breakthrough in low-temperature Li batteries. However, such a low-temperature performance was achieved by sacrificing safety at room temperatures, since the batteries have to be protected by sophisticated protective structures due to high pressures of tens of bars. The $-70^{\\circ}\\mathrm{C}$ LIB was developed by using the low melting point of ethyl acetate-based electrolytes, but the poor stability of the ethyl acetate severely limits the voltage of the battery, to only ${\\sim}2\\mathrm{V}$ (refs. 18,19). Broadly speaking, electrolytes that have good electrochemical performance at low temperatures normally deteriorate at high temperatures because the low melting temperature solvents normally also have high volatility, limiting their high-temperature behaviour. In addition, these low-temperature electrolytes are normally flammable. The narrow temperature windows of Li-ion battery electrolytes are attributed to the strong affinity between solvents and Li ions, which is required for high ionic conductivity. \n\nHerein, we tamed the affinity between solvents and Li ions by dissolving the fluorinated carbonate electrolytes (LiFSI-FEC/FEMC or LiBETI-FEC/DEC; LiFSI, lithium bis(fluorosulfonyl)imide; LiBETI, lithium bis(pentafluoroethanesulfonyl)imide; DEC, diethyl carbonate; FEC, fluoroethylene carbonate; FEMC, methyl (2,2,2-trifluoroethyl) carbonate) into non-polar stable solvents (tetrafluoro1-(2,2,2-trifluoroethoxy)ethane (D2) or methoxyperfluorobutane (M3)). The designed electrolyte exhibits a high ionic conductivity in a wide temperature range from $-125$ to $+70^{\\circ}\\mathrm{C},$ a high electrochemical stability in a wide potential window of $0.0{-}5.6\\mathrm{V}$ and a high non-flammable characteristic. Even at an ultralow temperature of $-85^{\\circ}\\mathrm{C}$ , the $\\mathrm{LiNi_{0.8}C o_{0.15}A l_{0.05}O_{2}}||$ Li battery can still deliver a capacity of $96\\mathrm{mAhg^{-1}}$ , which is more that $50\\%$ of the reversible capacity at room temperature. \n\n# Taming the electrolytes \n\nTo achieve high ionic conductivity, the solvents should have a high dielectric constant $(\\varepsilon)$ to sufficiently dissociate the Li ions from the anions. However, this requirement leads to several detrimental physical or chemical characteristics, and significantly restricts the electrochemical performance of the batteries.20 First, the high dielectric constant means strong affinity between the solvent molecules and the Li ions, and therefore the desolvation process on the electrode surface is suppressed, limiting the Li-ion intercalation kinetics18. Second, strong binding of the Li ions to the solvents reduces the Li-ion transference number to 0.2–0.4 (ref. 20). Third, the high dielectric constant of the solvents inevitably enhances the dipole–dipole force among these highly polar molecules, increasing the freezing temperature of the solvents and thus reducing the low-temperature performance of the electrolytes. All of these intrinsic features pose long-standing challenges in non-aqueous electrolytes, limiting the voltage window, the liquid temperature range and safety. \n\nAll-fluorinated, non-flammable electrolytes have high ionic conductivity and a wide electrochemical stability window21. However, Li-ion batteries using these all-fluorinated electrolytes cannot work at temperatures below $-30^{\\circ}\\mathrm{C}$ due to the high affinities between the \n\n![](images/6541a4e76e18bf4d26a08f3720e5b35ec2887ef51af958a7e968e7aff497dc0a.jpg) \n\nFig. 1 | Electrolyte design strategy and the properties. a, Our electrolyte uses a non-polar solvent (D2 or M3, denoted by the purple curves) to tame the fluorinated carbonate electrolytes. The transparent blue spheres indicate the Li-ion solvation structure. The purple, positive-charged spheres indicate the Li ions. The brown, negative-charged spheres are anions. The solvated solvents with brown crescent shapes around the Li ions are the fluorinated carbonate solvents. b, The affinities between the solvents and ions. The Li ions and fluorinated carbonate solvents have a strong interaction (indicated by the solid red arrow), while the other three species have weak interactions between each other (dashed arrows). c, The non-flammable and high electrochemical stability requirements for the non-polar solvent in the superelectrolyte. The non-polar solvents are non-flammable and can withstand an extremely high voltage of $5.6{\\sf V}.$ d, The expected electrochemical process at the electrode and electrolyte interface of the tamed electrolyte. In the bulk electrolyte, the Li ions will be solvated by fluorinated carbonate molecules and anions. At the surface region, the solvated Li ions will separate from the anions by means of the electric field. As the Li ions arrive at the surface of the electrode, the fluorinated carbonate molecules will finally be desolvated. \n\nfluorinated solvents and the Li ions. To achieve a wide operational temperature range, we reduced the affinities between the solvents and the Li ions by dissolving the all-fluorinated electrolytes into highly fluorinated non-polar solvents, forming a superelectrolyte, as shown in Fig. 1a. The solvation structures of the all-fluorinated electrolyte are maintained in the electrolyte, since the interaction between the non-polar solvents and the Li ions was much weaker than that of Li ions and fluorinated carbonates, as illustrated in Fig. 1b. The non-polar solvents break the strong interaction between the highly polar molecules, widening the liquid-phase range and increasing the transference number. Therefore, the superelectrolytes maintain the electrochemical properties of the all-fluorinated electrolyte, but have significantly enhanced physical properties. Moreover, the highly fluorinated non-polar solvent itself also has a high electrochemical and chemical stability (Fig. 1c), further enhancing the safety and electrochemical potential window. The change of solvation structure in the superelectrolytes is also expected to improve the electrochemical process, including mass transfer and charge transfer (Fig. 1d). \n\nTo demonstrate the design principle for the electrolytes, $4.2\\mathrm{M}$ LiFSI-FEC/FEMC and $2.33\\mathrm{M}$ LiBETI-FEC/DEC were used as two model fluorinated electrolytes, and D2 and M3 were selected as two non-polar solvents to formulate the superelectrolytes. Specifically, 1.28 M LiFSI-FEC/FEMC–D2 electrolyte was prepared by dissolving of $4.2\\mathrm{M}$ LiFSI-FEC/FEMC electrolyte into D2 solvent. The concentration of $1.28\\mathrm{M}$ refers to all FEC, FEMC and D2 solvents. Similarly, $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 electrolyte was also prepared by dissolving $2.33\\mathrm{M}$ LiBETI-FEC/DEC electrolyte into M3. Although no salts can be dissolved into pure D2 and M3, the $4.2\\mathrm{M}$ LiFSI-FEC/ FEMC and $2.33\\mathrm{M}$ LiBETI-FEC/DEC electrolytes can be completely dissolved in D2 and M3, forming clear $1.28\\mathrm{M}$ LiFSI-FEC/FEMC– D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 electrolytes, respectively. To distinguish from 1 M LiPF $\\dot{\\bar{\\cdot}}_{6}$ -EC/DMC (DMC, dimethyl carbonate) electrolyte, we use dash ‘–’ to express the process of electrolyte dissolution into D2 or M3 non-polar solvent in $1.28\\mathrm{M}$ LiFSI-FEC/ FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-DEC/FEC–M3 electrolytes. \n\nThe fluorinated polar carbonate solvents in the superelectrolyte can sufficiently solvate the Li ions, providing high conductivity of the electrolyte. Meanwhile, the highly fluorinated non-polar solvents of D2 and M3 have a much lower molecular interaction, breaking the interactions between the fluorinated carbonate electrolyte and ensuring a wide liquid-phase temperature range, low viscosity and low $\\mathrm{Li^{+}}$ desolvation energy. When $4.2\\mathrm{M}$ LiFSI-FEC/ FEMC and $2.33\\mathrm{M}$ LiBETI-FEC/DEC electrolytes were dissolved into a non-polar solvent (D2 or M3), the ion transport and other electrochemical properties mainly depended on the dissolved carbonate electrolyte ( ${\\bf\\dot{\\boldsymbol{4.2M}}}$ LiFSI-FEC/FEMC or $2.33\\mathrm{M}$ LiBETIFEC/DEC), while the physical and chemical properties (such as freezing point, boiling point, flammability and Li-ion solvation/ desolvation energy) essentially depended on the interactions between the dissolved electrolyte ${\\bf\\dot{\\theta}}_{\\ 4.2\\bf M}$ LiFSI-FEC/FEMC or $2.33\\mathrm{M}$ LiBETI-FEC/DEC) and the non-polar solvents (D2 or M3). Disassociating the electrochemical properties from these physical and chemical properties can simultaneously achieve high-voltage stability and wide temperature windows, low viscosity and high ionic conductivity. \n\nPhysical and electrochemical properties of the electrolytes Figure 2a shows the ionic conductivities of two superelectrolytes 1 $\\mathrm{1.28M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3), two representative liquid electrolytes ( $1\\mathrm{MLiPF}_{6}$ -EC/DMC commercial electrolytes and $4.2\\mathrm{M}$ LiFSI-FEC/FEMC high-concentration electrolytes) and two typical solid-state electrolytes $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ $(\\mathrm{LLZO})^{22}$ and $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ (LGPS)23. Since the ion transport of the three liquid electrolytes ( $\\mathrm{1.28M}$ LiFSI-FEC/FEMC–D2, $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 and $4.2\\mathrm{M}$ LiFSI-FEC/FEMC) is controlled by the mobility of the solvated molecules, the conductivity of these liquid electrolytes at different temperatures can be well described by the Vogel–Tammann–Fulcher empirical equation, as shown in Supplementary Fig. 1 (refs. 24,25). The conductivities of crystalized $1.0\\mathrm{\\dot{M}\\ L i P F_{\\mathrm{6}}\\mathrm{-EC/DMC}}$ below $-20^{\\mathrm{o}}\\mathrm{C},$ LLZO and LGPS electrolytes follow the Arrhenius law. The conductivity of 1 M LiPF6-EC/DMC electrolyte under $-20^{\\circ}\\mathrm{C}$ was fitted with the Arrhenius equation (Supplementary Fig. 1). Supplementary Table 1 lists the fitting parameters and calculated ionic conductivities of four liquid electrolytes. The crystallization of the 1 M LiPF6-EC/DMC electrolyte and the solidification of $4.2\\mathrm{M}$ LiFSI-FEC/FEMC due to a high glass transition temperature $T_{\\phantom{}_{0}}$ significantly reduced the conductivities of the 1 M LiPF6-EC/DMC electrolyte and $4.2\\mathrm{M}$ LiFSI-FEC/FEMC to less than $10^{-7}\\mathrm{mScm^{-1}}$ at $-80^{\\circ}\\mathrm{C}$ (Supplementary Table 1). \n\nThe introduction of D2 into $4.2\\mathrm{M}$ LiFSI-FEC/FEMC, and of M3 into $2.33\\mathrm{M}$ LiBETI-FEC/DEC, slightly reduces the ionic conductivities of these electrolytes at room temperature. However, D2 and M3 can effectively suppress solidification of both liquid electrolytes, thus significantly enhancing the ionic conductivity of electrolytes at low temperatures. The conductivities of $1.28\\mathrm{M}$ LiFSI-FEC/FEMC– D2 and $0.7\\ensuremath{\\mathrm{M}}$ LiBETI-FEC/DEC–M3 electrolytes at temperatures below $-20^{\\circ}\\mathrm{C}$ are 50 times higher than that of LLZO. In addition, the superelectrolytes have much lower interface resistance, higher fluidity and wider electrochemical windows than conventional carbonate electrolytes (Supplementary Fig. 3) and solid electrolytes (LLZO and $\\mathrm{LGPS})^{26,27}$ . In conventional electrolytes, Li cations are coordinated with solvent and form a large solvation shell, reducing the mobility of the solvated Li cations, with a low transference number of $0.2\\substack{-0.4}$ . In superelectrolytes, the Li cations are solvated with less solvent molecules and meanwhile the anions are seriously dragged by the Li cations, which results in an unexpectedly high Li-ion transference number of ${\\sim}0.7$ . At the extreme temperature of $-80^{\\circ}\\mathrm{C}$ , the conductivities of $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETIFEC/DEC–M3 electrolytes are still $>1\\times10^{-2}\\mathrm{mScm^{-1}}$ , which is ten times higher than that of LiPON at room temperature28,29, and sufficient to transport the ions between the anodes and the cathodes. \n\n![](images/15f2c2e460dcc161f950f0cc9c29699563df958d7e80a0732ae43a361ef3fe31.jpg) \nFig. 2 | Physical properties and simulated structure of the superelectrolytes. a, Conductivity of liquid and solid electrolytes. b, Temperature dependence of the magnetic moment of the four different electrolytes measured in a superconducting quantum interference magnetometer device in an applied field of $1{\\bmod{.}}$ . The freezing points of the electrolytes (as indicated by the arrows) can be determined by the transition point. The cooling rate is $1^{\\circ}{\\mathsf{C}}{\\mathsf{m i n}}^{-1}$ . c, cMD simulated electrolyte structure for $1.28{\\ensuremath{\\mathsf{M}}}$ LiFSI-FEC/FEMC–D2. 125 LiFSI, 234 FEC, 280 FEMC and 793 D2 molecules were dissolved into a periodic box $(65.1\\times65.1\\times65.1\\mathbb{A}^{3})$ . ${\\mathsf{L i}}^{+}$ ions and coordinated molecules (within $3\\mathbb{A}$ of ${\\mathsf{L i}}^{+}$ ions) are depicted by a ball-and-stick model, while the wireframes stand for the free solvents. Free D2, FEC and FEMC molecules are shown as cyan, blue and red wireframes, respectively, whereas hydrogens are excluded in the LiFSIFEC/FEMC–D2 electrolyte. d, The representative ${\\mathsf{L i}}^{+}$ solvation structure extracted from the cMD simulations. \n\nThe high ionic conductivities of $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 electrolytes at low temperatures are attributed to the extremely low melting point (Fig. 2b). The freezing points of these superelectrolytes were measured using a magnetic property measurement system $(\\mathrm{MPMS})^{30}$ from discontinuity of $\\mathrm{d}\\chi/\\mathrm{d}T$ , where $\\chi$ is the magnetic susceptibility and $T$ the temperature (Supplementary Notes), as shown in Fig. 2c. The 1 M $\\mathrm{LiPF}_{6}$ -EC/DMC electrolyte begins to freeze at about $-15^{\\circ}\\mathrm{C}$ , which is in good agreement with the differential scanning calorimetry (DSC) scan in Supplementary Fig. 4 and the freeze temperature reported in the literature20. The $4.2\\mathrm{M}$ LiFSI-FEC/FEMC electrolyte shows a phase transition at an even higher temperature $({\\sim}0^{\\circ}\\mathrm{C})$ due to the high freezing points of FEC $({\\sim}22^{\\circ}\\mathrm{C})$ and FEMC. The high freezing points of the two electrolytes (1 M $\\mathrm{LiPF}_{6}$ -EC/DMC and $4.2\\mathrm{M}$ LiFSI-FEC/FEMC) coincide with their sudden drop in conductivity below $-15^{\\circ}\\mathrm{C},$ as shown in Fig. 2a. Dissolving the $4.2\\mathrm{M}$ LiFSI-FEC/FEMC electrolytes into D2 and the $2.33\\mathrm{M}$ LiBETI-FEC/ \n\nDEC into M3 dramatically lowers the freezing points of these two electrolytes to approximately $-125^{\\circ}\\mathrm{C}$ and approximately $-132^{\\circ}\\mathrm{C},$ respectively. No deposits or phase separations emerge in these two electrolytes after being fully immersed in liquid at $-95^{\\circ}\\mathrm{C}$ for $3\\mathrm{h}$ (Supplementary Figure 5). \n\nThe $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/ DEC–M3 electrolytes also show low volatility at a high temperature, which is critical for the high-temperature performance of cells. As shown in Supplementary Fig. 6, the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 electrolytes show a volatility comparable to conventional the 1 M $\\mathrm{LiPF}_{6}$ -EC/DMC electrolyte. The remaining mass of the electrolytes is higher than $50\\%$ as the temperature ramps up to $100^{\\circ}\\mathrm{C}$ at $1.0{\\mathrm{atm}}$ , and the residual mass will be significantly increased in a sealed cell due to the increased pressures. In addition, the much higher fluorine content in $1.28\\mathrm{M}$ LiFSI-FEC/ FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 electrolytes than in the 1 M LiPF6-EC/DMC electrolyte significantly increases the LiF content in the solid electrolyte interphase (SEI) and cathode electrolyte interphase (CEI) (as discussed below), which will further increase the high-temperature stability of batteries due to the high thermal stability of the LiF-rich SEI/CEI and the lower solubility compared with organic-rich SEI. \n\nThe electrolytes $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 electrolytes have wide temperature ranges of over $160^{\\circ}\\mathrm{C}.$ , which is comparable to the temperature range for the LGPS solid electrolyte23. However, the narrow thermodynamic stability window of LGPS $(<0.5\\mathrm{V})$ limits its practical application in batteries27. Moreover, these liquid superelectrolytes have low interface resistance to the electrode and are capable of accommodating volume changes of the electrodes, which is not possible for LGPS solid electrolytes. \n\nThe structures of $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 (Fig. 2c,d and Supplementary Figs. 7–9) superelectrolytes were simulated by classical molecular dynamics (cMD). The $\\mathrm{Li^{+}}$ and coordinated molecules in the first shell are depicted with a ball-and-stick model, while the free molecules are in a wireframe format. The coordinated structures are uniformly dispersed in each electrolyte, as we expected. The D2 and M3 are free solvent molecules, and do not coordinate with either the Li ions or the anions (Supplementary Table 2). Raman spectra confirmed that LiFSI-FEC/FEMC and LiBETI-FEC/DEC solvation clusters are uniformly dispersed into the D2 or M3 non-polar solvents (Supplementary Fig. 10). In other words, when $4.2\\mathrm{M}$ LiFSI-FEC/ FEMC and $2.33\\mathrm{M}$ LiBETI-FEC/DEC electrolytes were dissolved into a non-polar solvent (D2 or M3), the electrochemical properties of the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/ DEC–M3 electrolytes were disassociated from the physical and chemical properties. In addition, the fluorinated polar carbonate solvents, highly fluorinated non-polar solvent and the LiFSI/LiBETI salts facilitate the formation of a LiF-rich SEI, and thereby enhance the high-temperature stability, maximizing the working electrochemical window. \n\nThe $\\mathrm{Li^{+}}$ solvation/desolvation energies of the conventional carbonate electrolyte and the disassociated electrolytes were calculated and are compared in Fig. 3a. The low ion-desolvation energy in the electrolytes is critical for the kinetics performance because the solvent molecules around $\\mathrm{Li^{+}}$ have to be completely stripped off before intercalation into the electrode materials. Especially at a low temperature, the sluggish desolvation process of $\\mathrm{Li^{+}}$ substantially limits lithiation/delithiation reaction kinetics18. For the EC/DMC (3:1 molar) electrolyte, the solvation energy calculated from quantum chemistry is about $-9.05\\mathrm{kcalmol^{-1}}$ , which is in good agreement with the literature31. As the solvent blend changes to FEC/FEMC and FEC/DEC at a ratio of 1:3, the solvation energy dramatically reduces to $-1.26$ and $-0.33\\mathrm{kcalmol^{-1}}$ , which is only about 1/7 and 1/27 of the traditional EC/DMC (3:1 molar) electrolytes, respectively. By introducing FEC/FEMC or FEC/DEC polar solvents into non-polar solvent D2 or M3, complexes involved with D2 and M3 molecules further reduce the solvation energy to a positive value due to the weak interaction between $\\mathrm{Li^{+}}$ and D2 or M3 solvent molecules. The increase in positive solvation energy value with increase in the number of D2 or M3 molecules suggests that the interaction is energetically unfavourable for the $\\mathrm{Li^{+}}$ ion and D2 or M3 pair. \n\nThe structure and composition of the electrolytes not only affect the desolvation and diffusivity of the Li ions, but also change the SEI on the electrodes. The interphase layers on the electrodes also affect the reaction kinetics and cycle stability of the batteries. The SEI composition on the Li metal in $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 is significantly different from that in the 1 M $\\mathrm{LiPF}_{6}$ -EC/DMC electrolyte. The SEI in the 1 M LiPF6-EC/DMC mainly consists of organic components, while the SEI film in the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC– D2 electrolyte is mainly composed of LiF-rich inorganic species (Supplementary Fig. 11). More specifically, the F:C atomic ratio in the SEI increases from 0.65 in the 1 M LiPF -EC/DMC, to 9.98 in the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte. The LiF-rich SEI has high mechanical strength and high interfacial energy with Li metal, which can effectively suppress the Li dendrite, thus enhancing the Coulombic efficiency (CE) of Li plating/stripping21,32. The LiF-rich SEI also has a much higher thermal stability than organic-rich SEI at a high temperatures, which significantly enhances the high-temperature $(60-70^{\\circ}\\mathrm{C})$ stability of the NCA $\\left(\\mathrm{LiNi_{0.8}C o_{0.15}A l_{0.05}\\mathrm{\\bar{O}_{2})}||}$ Li cell, as discussed below. The extremely low electronic conductivity of LiF significantly reduces the thickness of the LiF-rich SEI, as evidenced by the appearance of Li metal within in a short sputtering time of SEI, as shown in Fig. 3b. The Li metal signal appears after only $5\\mathrm{{min}}$ sputtering with $\\mathrm{Ar^{+}}$ on the SEI formed in the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte (Fig. 3b). However, the Li metal signal does not show up until after $20\\mathrm{min}$ sputtering of the SEI formed in the 1 M LiPF6-EC/DMC electrolyte (Fig. 3c). Therefore, a thin and conformal LiF-rich SEI was formed on Li in the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte, while a thick organic-rich SEI was formed on Li in the $\\mathrm{LiPF}_{6}$ -EC/DMC electrolyte, as schematically demonstrated in Fig. 3d,e. Formation of the LiF-rich SEI in the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte can be well explained by the cMD simulation of special solvation structures where most of the $\\mathrm{Li^{+}}$ cations $(>99\\%)$ are partially coordinated with more than two $\\mathrm{FSI^{-}}$ anions (Supplementary Table 2), enabling more $\\mathrm{FSI^{-}}$ to participate in the SEI-forming reaction (Supplementary Fig. 12). Similarly to the SEI layer, the CEI layer is also mainly composed of inorganic species (Supplementary Fig. 13). These LiF-rich interphases bring several other benefits:32,33 the Arrhenius behaviour of ionic conductivity for LiF-rich interphases enhances the ionic conductivity at low temperatures and the high thermal stability of the LiF-rich interphases improves the high-temperature electrochemical performance of both the anode and the cathode. \n\n# Low-temperature behaviour \n\nThe formation of the LiF-rich SEI on Li anodes in the $1.28\\mathrm{M}$ LiFSIFEC/FEMC–D2 electrolytes significantly increases the Li plating/ stripping CE to $99.4\\%$ (Supplementary Fig. 14), which is one of the highest CEs reported so far for Li plating/striping34. Figure $_{\\mathrm{4a-e}}$ shows the electrochemical performance of the $\\mathrm{\\DeltaNCA}||$ Li coin cells in different electrolytes at an area capacity of $\\sim1.2\\mathrm{mAhcm^{-2}}$ . The specific capacity and current density are calculated from the mass of the active cathode materials. At room temperature $(25^{\\circ}\\mathrm{C})$ , the discharge capacities of NCA $||$ Li cells in both $1\\mathrm{M}\\mathrm{LiPF}_{6}$ -EC/DMC and $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 are about $172\\mathrm{mAhg^{-1}}$ . However, when the temperature is reduced to $-42^{\\circ}\\mathrm{C},$ the $\\mathrm{NCA}||$ Li cells in $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte can still provide a high capacity of $160\\mathrm{mAhg^{-1}}$ , while the $\\mathrm{NCA}||$ Li cells in the $1\\mathrm{M}\\mathrm{LiPF}_{6}$ -EC/DMC electrolyte can only provide a capacity of $13.3\\mathrm{mAhg^{-1}}$ . The rapid decay in capacity of $\\mathrm{\\DeltaNCA}||$ Li cells at $-42^{\\circ}\\mathrm{C}$ in the $1\\mathrm{M}\\mathrm{LiPF}_{6}$ -EC/ DMC electrolyte (Fig. 4c) is because the electrolyte is completely solidified at $-30^{\\mathrm{{o}C}}$ . Even when the temperature is decreased to $-85^{\\circ}\\mathrm{C},$ the $\\mathrm{NCA}||$ Li cell using $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 can still deliver a capacity of $96\\mathrm{mAhg^{-1}}$ , while the $\\mathrm{NCA}||$ Li cell in $1\\mathrm{M}$ $\\mathrm{LiPF}_{6}$ -EC/DMC cannot provide any capacity below $-67^{\\circ}\\mathrm{C}.$ . This shows extreme battery performance at a temperature below the condensation point of $\\mathrm{CO}_{2}$ $(-78^{\\circ}\\mathrm{C})$ . Figure 4d demonstrates that a small NCA $\\Vert$ Li pouch cell can power an electric fan at $-95^{\\circ}\\mathrm{C}$ . \n\nThe $\\mathrm{NCA}||$ Li cells using $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte also show much longer cycling stability than those in 1 M $\\mathrm{LiPF}_{6}–\\mathrm{EC/DMC}$ at $-20^{\\circ}\\mathrm{C}$ at a $1/3{\\mathrm{C}}$ $\\mathrm{^{\\prime1C=170mAhg^{-1}}}$ ) rate. As demonstrated in Fig. 4e, $\\mathrm{NCA}||$ Li cells using the $1.28\\mathrm{M}$ LiFSI-FEC/ FEMC–D2 electrolyte can maintain a high capacity of $150\\mathrm{mAhg^{-1}}$ for 450 cycles, while NCA $\\Vert\\mathrm{Li}$ cells using the $1\\mathrm{M}\\mathrm{LiPF}_{6}$ EC/DMC electrolyte can only provide $35\\mathrm{mAhg^{-1}}$ for 100 cycles and then the capacity drops rapidly. The superelectrolytes also enable more aggressive Li-ion cathodes and $\\mathrm{{Na}}$ -ion cathodes to achieve high performance at a very low temperature. Supplementary Fig. 15 shows that a $\\mathrm{LiNi_{0.6}M n_{0.2}C o_{0.2}O_{2}}$ (NMC622) || Li cell using $0.7\\mathrm{M}$ \n\n![](images/eb92ad93fc45fde0f07a867d6d2103c5b339347456664e8758c981cf78dd8ef4.jpg) \nFig. 3 | Li-ion solvation/desolvation energy in different electrolytes and the interphase analysis. a, The calculated ${\\mathsf{L i}}^{+}$ solvation/desolvation energy with different structures of the LiPF $6$ -EC/DMC and superelectrolytes; DMCcc and DMCccb stand for the two DMC cis–cis conformers58. b,c, XPS Li 1s spectra of cycled lithium metal anode before sputtering and after different sputtering times using $1.28{\\ensuremath{\\mathsf{M}}}$ LiFSI-FEC/FEMC–D2 electrolyte (b) and 1 M LiPF6-EC/DMC electrolyte $\\mathbf{\\eta}(\\bullet)$ . d,e, Schematic illustration of SEI layers formed in different electrolytes: $1.28{\\ensuremath{\\mathsf{M}}}$ LiFSI-FEC/FEMC–D2 electrolyte (d) and 1 M LiPF $\\dot{\\mathbf{\\rho}}_{6}$ -EC/DMC electrolyte (e). \n\nLiBETI-FEC/DEC–M3 electrolytes can power 51 light-emitting diodes at $-80^{\\circ}\\mathrm{C}.$ . When the LiFSI salt was replaced by the NaFSI salt, the $\\mathrm{Na}_{3}\\mathrm{V}_{2}(\\mathrm{PO}_{4})_{2}\\mathrm{O}_{2}\\mathrm{F}\\left|\\right|\\mathrm{N};$ a cells using the $1.28\\mathrm{M}$ NaFSI-FEC/ FEMC–D2 electrolytes also showed significantly better low-temperature performance than cells using $1.0\\mathrm{M}$ ${\\mathrm{NaPF}}_{6}$ -EC/DMC (Supplementary Fig. 16). At $-58^{\\circ}\\mathrm{C},$ $\\mathrm{Na}_{3}\\mathrm{V}_{2}(\\mathrm{PO}_{4})_{2}\\mathrm{O}_{2}\\mathrm{F}\\left|\\right|\\mathrm{r}$ Na cells can still provide $70\\mathrm{mAhg^{-1}}$ , which is more than $50\\%$ of the capacity at $25^{\\circ}\\mathrm{C}$ . The extremely low alkaline ion solvation/desolvation energy (Fig. 3a), extended liquid temperature range (Fig. 2b) and the compact SEI/CEI (Fig. 3b) contribute to these highly reversible Li batteries at ultralow temperatures. \n\n# High-temperature behaviour \n\nNCA || Li cells using $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 and $0.7\\mathrm{M}$ LiBETI-FEC/DEC–M3 electrolytes also show a superior performance at high temperatures. As shown in Fig. $\\measuredangle4\\boldsymbol{\\mathrm{c}}$ and Supplementary Fig. 17, the capacity of the $\\mathrm{\\DeltaNCA}||$ $\\Vert\\mathrm{Li}$ cell at $70^{\\circ}\\mathrm{C}$ using $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 is similar to that using $1.0\\mathrm{M}$ $\\mathrm{LiPF}_{6}$ -EC/ DMC. During charge/discharge cycles, the $\\mathrm{NCA}||$ Li cell using the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte maintains a high capacity of $170\\mathrm{mAhg^{-1}}$ , while the capacity of the $\\mathrm{NCA}||$ $\\Vert\\mathrm{Li}$ cell using $1.0\\mathrm{M}\\mathrm{LiPF}_{6}$ -EC/DMC electrolyte rapidly decays to $50\\%$ capacity in less than five cycles, due to the instability of the SEI/CEI at high temperatures. At $60^{\\circ}\\mathrm{C},\\mathrm{NCA}||$ Li cells in $0.7\\mathrm{M}$ LiBETI-FEC/DEC– M3 electrolytes also show a significantly batter cycling stability than cells using 1 M LiPF6-EC/DMC electrolytes (Supplementary Fig. 17). \n\n# High-voltage cell behaviour \n\nIn addition, the superelectrolyte also possesses a wide electrochemical voltage window in a broadened operational temperature range. A high-voltage cathode (5.4 V) of $\\mathrm{LiCoMnO_{4}}$ is utilized to evaluate the high-voltage stability of the electrolytes over a wide temperature range. Figure $^{4\\mathrm{f},\\mathrm{g}}$ shows the cyclic voltammetry curves of $5.4\\mathrm{V}$ $\\mathrm{LiCoMnO_{4}|}$ | Li cells in $1.0\\mathrm{MLiPF}_{6}$ -EC/DMC and $1.28\\mathrm{M}$ LiFSI-FEC/ FEMC–D2 electrolytes at different temperatures. $\\mathrm{LiCoMnO_{4}||}]$ Li cells using 1 M $\\mathrm{LiPF}_{6}$ -EC/DMC experience significantly increased oxidation peaks, with extremely low CE at high voltages above $4.8\\mathrm{V}$ as the temperature increases from $25^{\\circ}\\mathrm{C}$ to $60^{\\circ}\\mathrm{C},$ while no redox peak is observed when the temperature drops to $-30^{\\circ}\\mathrm{C}$ (Fig. 4f). In contrast, a significantly highly reversible capacity is observed for $\\mathrm{LiCoMnO_{4}}$ using the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte even at $-60^{\\circ}\\mathrm{C}$ (Fig. 4g), although the overpotential of the spinel cathode is increased and the two-step lithiation/delithiation is merged into one step due to the reduced Li-ion diffusion kinetics35. The lithiation/delithiation behaviour of $\\mathrm{\\dot{\\Omega}_{\\mathrm{-}}i C o M n O_{4}||}$ Li cells at $+60^{\\circ}\\mathrm{C}$ is similar to that at $25^{\\circ}\\mathrm{C}$ , demonstrating the superior stability of the $1.28\\mathrm{M}$ LiFSI-FEC/FEMC–D2 electrolyte at high temperatures and high voltage. Besides, the superelectrolyte also enables graphite and 5 $\\mathrm{\\cdotV\\LiNi_{0.5}M n_{1.5}O_{4}}$ to achieve higher CEs and cycling stability than in 1 M LiPF6-EC/DMC electrolyte (Supplementary Figs. 18 and 19). \n\nSupplementary Fig. 21 shows the operation temperature limits of different rechargeable batteries, with the highest and lowest temperatures recorded on Earth for reference. No batteries can operate in such a harsh temperature range. Alkaline Ni-MH batteries still cannot operate below $-30^{\\circ}\\mathrm{C}$ due to being intrinsically prone to freezing of the aqueous electrolyte36. The operation temperature range of well-matured lead-acid batteries is only from $-40^{\\circ}\\mathrm{C}$ to $+65^{\\circ}\\mathrm{C}$ . Commercial LIBs can sustain a much narrower temperature range, between $-20^{\\circ}\\mathrm{C}$ and $+55^{\\circ}\\mathrm{C}$ with severe capacity decay at temperatures below $0^{\\circ}\\mathrm{C}$ (ref. 37). Considering the highest $(56.7^{\\circ}\\mathrm{C},$ Death Valley, California, USA, 1913) and lowest temperatures $\\left(-89.2^{\\circ}\\mathrm{C},\\right.$ Vostok Station, Antarctica, 1983) ever recorded on Earth, superelectrolyte Li batteries with an operational temperature range from $-95^{\\circ}\\mathrm{C}$ to $+70^{\\circ}\\mathrm{C}$ are highly reversible batteries that could operate at any place in our planet. \n\n![](images/fec6eb71d3ae70062dc296cca0a7e0df8b4033a0117703f0d07d5e3067ded7b3.jpg) \nFig. 4 | Electrochemical performance of NCA || Li cells using different electrolytes at different temperatures. a, Discharge profiles of NCA || Li cells using conventional 1 M $\\mathsf{L i P F}_{6}$ -EC/DMC electrolyte at different temperatures. b, Discharge profiles of NCA || Li cells using 1.28 M LiFSI-FEC/FEMC–D2 electrolyte at different temperatures. c, Discharge capacities of ${\\mathsf{N C A}}||$ Li cells using $1.28M$ LiFSI-FEC/FEMC–D2 and 1.0 M LiPF $\\dot{\\mathbf{\\rho}}_{6}$ -EC/DMC electrolytes at different temperatures. d, Optical images of an electric fan powered by the NCA || Li pouch cell using 1.28 M LiFSI-FEC/FEMC–D2 electrolyte at $-95^{\\circ}\\mathsf C$ . The video is in Supplementary Video 1, and the size of the pouch cell is shown in Supplementary Fig. 20. e, Cycling performance of NCA || Li using 1 M LiPF6-EC/DMC and $1.28{\\cal M}$ LiFSI-FEC/FEMC–D2 electrolytes at $-20^{\\circ}\\mathsf C$ with a charge/discharge current density of 1/3 C. f,g, Cyclic voltammetry curves of $\\mathsf{L i C o M n O}_{4}||$ Li at different temperatures using different electrolytes at a scanning rate of $0.05\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ using 1 M LiP $\\dot{\\mathbf{\\rho}}_{6}$ -EC/DMC electrolyte $(\\pmb{\\uparrow})$ and $1.28{\\ensuremath{\\mathsf{M}}}$ LiFSI-FEC/ FEMC–D2 electrolyte $\\mathbf{\\sigma}(\\mathbf{g})$ . \n\nAnother important requirement for electrolytes is non-flammability21,38–41. The superelectrolytes with physical and chemical properties disassociated from electrochemical properties can simultaneously achieve high electrochemical performance in a wide temperature and voltage window, and are non-flammable as well. Supplementary Fig. 22 compares the electrochemical properties of superelectrolytes with the most promising electrolytes, including aqueous electrolytes, sulfide-based solid-state LGPS and LPS electrolytes (Supplementary Figs. 23 and 24), traditional carbonate electrolytes and ether-based electrolytes. The superelectrolytes are non-flammable and have the widest electrochemical window from $0.0\\mathrm{V}$ Li metal anode to the ultrahigh-voltage cathode of $5.4\\mathrm{V}$ $\\mathrm{LiCoMnO_{4}}$ with the highest CEs, outperforming all other electrolytes, including solid-state electrolytes and water-in-salts aqueous electrolytes. The flammability tests of these electrolytes are shown in Supplementary Videos 2–6. The sulfide-based LGPS/LPS solid-state electrolytes are still flammable and will generate highly toxic gases such as $\\mathrm{SO}_{2}$ and $\\mathrm{H}_{2}S$ during burning or exposure to moisture. Therefore, sulfide solid-state electrolyte batteries still face safety concerns. \n\n# Conclusions \n\nBy dissolving fluorinated carbonate electrolytes into highly fluorinated non-polar solvents, we developed superelectrolytes where the electrochemical properties of the electrolytes are disassociated from their physical and chemical properties. At room temperature, the superelectrolytes enable the most promising electrodes to achieve a high cycling CE $(99.4\\%$ for Li metal, ${>}99.9\\%$ for graphite, ${>}99.9\\%$ for $\\mathrm{LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}},$ $99.9\\%$ for $5.0\\mathrm{V\\LiNi_{0.5}M n_{1.5}O_{4}}$ and $99\\%$ for $5.4\\mathrm{V}\\ \\mathrm{LiCoMnO_{4}},$ ). The $\\mathrm{NCA}||$ Li battery using superelectrolytes at $-85^{\\circ}\\mathrm{C}$ can deliver $56\\%$ of its room-temperature capacity and maintain high cycling stability at $60^{\\circ}\\mathrm{C}$ The highly fluorinated non-polar solvents associated with the fluorinated electrolyte make the electrolyte non-flammable, greatly improving the safety of the batteries. The present design therefore represents an encouraging path towards creating safe Li batteries with a sufficiently wide operational temperature range. \n\n# Methods \n\nMaterials. Li chips with a thickness of $250\\upmu\\mathrm{m}$ were purchased from MTI. Cathode NCA $\\mathrm{(LiNi_{0.8}C o_{0.15}A l_{0.05}O_{2})}$ and LNMO $\\left(\\mathrm{LiNi}_{0.5}\\mathrm{Mn}_{1.5}\\mathrm{O}_{4}\\right)$ powders were purchased from MTI. Graphite (TIMREX KS15) was obtained from Timcal. Ethylene carbonate, dimethyl carbonate (DMC), diethyl carbonate (DEC), fluoroethylene carbonate (FEC) and methoxyperfluorobutane $\\mathrm{(C_{4}F_{9}.}$ $\\mathrm{O-CH}_{3};$ , 1,1,1,2,2,3,3,4,4-nonafluoro-4-methoxybutane, M3) were purchased from Sigma-Aldrich. Methyl (2,2,2-trifluoroethyl) carbonate (FEMC), lithium bis(pentafluoroethanesulfonyl)imide (LiBETI, ${>}98\\%$ ) and 1,1,2,2-tetrafluoro-1- (2,2,2-trifluoroethoxy)ethane (D2) were obtained from Tokyo Chemical Industry. $\\mathrm{LiPF}_{6}\\left(99.999\\%\\right)$ was purchased from BASF USA. $\\mathrm{NaPF}_{6}$ $(>99\\%)$ was purchased from Sigma-Aldrich. Lithium bis(fluorosulfonyl)imide (LiFSI, ${>}99.99\\%$ ) was purchased from Chunbo. Sodium bis(fluorosulfonyl)imide (NaFSI, $99.7\\%$ ) was purchased from Solvionic. For a typical LiFSI-FEMC/FEC in D2 electrolyte, $\\mathrm{1ml}$ FEC and $2\\mathrm{ml}$ FEMC were mixed together, then $2.4\\mathrm{g}$ LiFSI was dissolved into the mixed solvents. After the LiFSI had completely dissolved, the LiFSI-FEMC/ FEC electrolyte was added into $7\\mathrm{ml}$ of D2 solvent under stirring, forming the LiFSI-FEMC/FEC in D2 electrolyte. For the LiBETI-DEC/FEC in M3 electrolyte, $2.7\\mathrm{g}$ LiBETI was dissolved into FEC:DEC:M3 $(0.5\\mathrm{ml};2.5\\mathrm{ml};7\\mathrm{ml})$ solvent. The ionic conductivities of the electrolytes at different temperatures were calculated by electrochemical impedance spectroscopy measurements with two platinum plate electrodes $(1\\mathsf{c m}^{2})$ symmetrically placed in the electrolyte solutions. \n\nThe $\\mathrm{LiCoMnO_{4}}$ was synthesized by a two-step method based on a previous report42. The solid-state electrolytes $\\mathrm{Li}_{10}\\mathrm{GeP}_{2}\\mathrm{S}_{12}$ (LGPS) and $\\mathrm{Li_{3}P S_{4}}$ (LPS) were synthesized following previously reported procedures23,43. \n\nCharacterizations. X-ray photoelectron spectroscopy (XPS) was conducted on a high sensitivity Kratos Axis $165\\mathrm{X}$ -ray photoelectron spectrometer with $\\mathbf{Mg}$ Kα radiation. All binding-energy values were referenced to the C 1s peak of carbon at $284.6\\mathrm{eV}.$ Before the XPS characterizations, the cycled electrodes were washed with the corresponding solvents to remove residual salts. The differential scanning calorimetry measurements were carried out in a DSC 404 F1 Pegasus (NETZSCH) differential scanning calorimeter using a scanning rate of $1^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ . Powder X-ray diffraction data were collected on a Bruker D8 X-ray diffractometer (Cu Kα radiation, wavelength $\\lambda{=}1.5418\\mathrm{\\AA}$ ). Freezing points of electrolytes were determined by respective first-order transitions of temperature-dependent magnetic susceptibility using a magnetic property measurement system (Quantum Design MPMS). The scanning rate was $1^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ . \n\nElectrochemical measurements. Electrolytes were prepared by adding the salt into various anhydrous solvents. All the solvents were dried by molecular sieve ${\\bf\\bar{4}}\\hat{\\bf A},$ Sigma-Aldrich) to make sure the water content was lower than $10\\mathrm{ppm}$ , which was tested using a Karl Fischer titrator (Metrohm 899 Coulometer). The charge–discharge performances of the Li batteries were examined using 2,032-type coin cells. The same coin-type cells were used to investigate the cycling stability of Li plating/stripping in different electrolytes. For the low-temperature discharge test, the battery was charged at room temperature with a current density of $1/3{\\dot{\\mathrm{C}}},$ and discharged at different temperatures with a current of 1/15 C. The CE of the Li plating and stripping was calculated from the ratio of the Li removed from the Cu substrate to that deposited in the same cycle. A three-electrode ‘T-cell’ was utilized to test the stability window of the different electrolytes with polished stainless steel as the working electrode and Li foils as the reference and counter electrodes using a Gamry 1000E electrochemical workstation (Gamry Instruments). The ${\\mathrm{Li^{+}}}$ transference number was calculated by testing the alternating-current (AC) impedance and direct-current (DC) impedance of the Li $\\Vert$ Li symmetric battery and by using the formula $t_{\\mathrm{Li}+}=R_{\\mathrm{cell}}/R_{\\mathrm{DC}}$ (ref. 44), where t is the transferance number and R the resistance. $R_{\\mathrm{cell}}$ was obtained by electrochemical impedance spectroscopy with a frequency of ${\\bf\\Pi}_{10\\mathrm{MHz}}$ to $0.1\\mathrm{Hz}$ and an AC signal amplitude of $5\\mathrm{mV}.$ $R_{\\mathrm{{DC}}}$ was obtained by performing a $10\\mathrm{mV}$ DC polarization for 10,800 s to obtain a steady current $(R_{\\mathrm{DC}}=V_{\\mathrm{DC}}/I_{\\mathrm{DC}},$ $V$ is voltage and $I$ is current). Both AC and DC impedence were performed using a CHI660E electrochemical workstation. The area capacity of the $\\mathrm{LiNi_{0.8}C o_{0.15}A l_{0.05}O_{2}}$ (NCA) in the pouch cell was about $2\\mathrm{mAhcm}^{-2}$ , and the total pouch cell capacity was $400\\mathrm{mAh}$ . All the cells were assembled in a glove box with a water/oxygen content lower than 1 ppm. The galvanostatic charge–discharge test was conducted on a battery test station (BT2000, Arbin Instruments). \n\nFlammability test. For the liquid electrolytes, the flammability was tested on the electrolyte-soaked glass fibre filter. For the solid-state sulfide electrolytes of LPS and LGPS, small pellets with a diameter of $1\\mathrm{cm}$ were prepared by cold pressing of about $200\\mathrm{mg}$ powder with a pressure of ${\\sim}800\\mathrm{MPa}$ . The flammability of the solidstate sulfide electrolytes was directly tested based on these pellets. \n\nComputational methods. To investigate the electrolytes of LiFSI-FEC/FEMC in D2 and LiBETI-FEC/DEC in M3 at an atomic scale, three types of calculations were performed. (1) cMD simulation to study the electrolyte structures using largescale atomic/molecular massively parallel simulator (LAMMPS, http://lammps. sandia.gov.)45. (2) Quantum chemistry calculations to predict solvation energy of possible solvation configurations in FEMC/FEC–D2 solvent using the Gaussian 09 package46. (3) Ab initio molecular dynamic (AIMD) simulation to show the structure and $\\mathrm{Li^{+}}$ motion of the electrolyte utilizing the Vienna ab initio simulation package $(\\mathrm{VASP})^{47-49}$ . Visualization of the structures was made using VESTA and VMD software50,51. \n\ncMD simulations. cMD simulations were conducted on the electrolytes using the LAMMPS simulation package. General amber force fields parameters52 and AM1- BCC charges52,53 were used and generated by the ANTECHAMBER program in AmberTools for the solvent molecules54. The force fields for Li, FSI and BETI were taken from previous publications55–57. For the LiFSI-FEMC/FEC in D2 electrolyte, 125 LiFSI, 234 FEC, 280 FEMC and 793 D2 molecules were dissolved into a periodic box, while for LiBETI-DEC/FEC in M3 electrolyte, 78 LiBETI, 70 FEC, 205 DEC and 364 M3 molecules were calculated. The systems were set up initially with simulation boxes 80 and $58\\mathrm{\\AA}$ in length, with the salt and solvent molecules distributed in the simulation boxes using Moltemplate (http://www.moltemplate. org/). First, NPT runs were performed at $330\\mathrm{K}$ for 5 ns and then $298\\mathrm{K}$ for 5 ns to ensure that the equilibrium salt dissociation had been reached. Then, the NVT runs were 10 ns long at $298\\mathrm{K}$ and the last 5 ns were used to obtain the structure of the electrolyte. The anions were not considered in the desolvation energy calculation because the anions in the interface will depart from the cations once the electric field is applied in the electrode and the electrolyte interface, as illustrated in Fig. 1, which is confirmed by the high transference number. The computation schemes have been widely used in previous related works58. \n\nQuantum chemistry calculations. All quality control calculations were performed using the Gaussian 09 software package. The Perdew–Burke–Ernzerhof functional was used as it was shown to accurately describe electron affinity and ionization potential. The double-zeta basis set $6{-}31{+}\\mathrm{G}(\\mathrm{d},\\mathsf{p})$ was used for structure optimization as well as the energy calculation. The SMD implicit solvation model was used to describe the solvation effect. Acetone ${\\varepsilon}=20.49,$ ) was used as the solvent for calculation of Li complexes. \n\nAIMD simulation. The electrolyte cell with a single LiFSI molecule was dissolved in a periodic box of 3 FEC, 3 FEMC and 9 D2 molecules. The system corresponds to 220 total atoms, with a density of $1.55\\mathrm{gcm}^{-3}$ . We performed the AIMD calculation using the VASP package. The ion–electron interaction was described with the projector augmented wave method, and the exchange-correlation energy was described by the functional of the Perdew–Burke–Ernzerhof form of the generalized gradient approximation59–61. The plane wave energy cut-off of $400\\mathrm{eV}$ was chosen and a minimal $\\Gamma$ -centred $1\\times1\\times1\\ k$ -point grid was used. All molecular dynamics simulations were performed in the NVT ensemble using a Nosé−Hoover thermostat. Each system was heated to $300\\mathrm{K}$ and equilibrated for 20 ps and then simulated for $30\\mathrm{ps}$ to gather statistics. AIMD simulations were performed on the electrolyte of LiFSI-FEMC/FEC in D2 to understand the mechanisms for superior performance. The electrolyte structure was simulated by assuming that $\\mathrm{Li^{+}}$ and FSI− ions are initially associated or initially dissociated (Supplementary Fig. 12). This showed that ${\\mathrm{Li^{+}}}$ tends to remain associated or to re-associate with $\\mathrm{FSI^{-}}$ and is coordinated with the FEMC and FEC. Even when $\\mathrm{Li^{+}}$ and FSI− are initially dissociated, the $\\mathrm{Li^{+}}$ and $\\mathrm{FSI^{-}}$ with a distance of ${\\sim}3.5\\mathrm{\\AA}$ follow similar trajectories to the associated $\\mathrm{Li^{+}}$ and FSI− after $10\\mathrm{ps}$ , changing to a correlated ion motion. These results are in good agreement with the cMD simulations and further confirmed the ${\\mathrm{Li^{+}}}$ coordinated with FSI− anions, FEC and FEMC molecules, while without coordination with D2 molecules. \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 28 April 2019; Accepted: 2 September 2019; Published online: 7 October 2019 \n\n# References \n\n1.\t Whittingham, M. S. Ultimate limits to intercalation reactions for lithium batteries. Chem. Rev. 114, 11414–11443 (1976). \n2.\t Cheng, X. B., Zhao, C. Z., Yao, Y. X., Liu, H. & Zhang, Q. Recent advances in energy chemistry between solid-state electrolyte and safe lithium metal anodes. Chem 5, 74–96 (2019). \n3.\t Assat, G. & Tarascon, J. M. Fundamental understanding and practical challenges of anionic redox activity in Li-ion batteries. Nat. Energy 3, 373–386 (2018). \n4.\t Armand, M. & Tarascon, J. M. Building better batteries. Nature 451, 652–657 (2008). \n5.\t Lin, D., Liu, Y. & Cui, Y. Reviving the lithium metal anode for high-energy batteries. Nat. Nanotechnol. 12, 194–206 (2017). \n6.\t Choi, J. W. & Aurbach, D. Promise and reality of post-lithium-ion batteries with high energy densities. Nat. Rev. Mater. 1, 16013 (2016). \n7.\t Sun, Y.-K. et al. Nanostructured high-energy cathode materials for advanced lithium batteries. Nat. Mater. 11, 942–947 (2012). \n8.\t Zhu, C., Usiskin, R. E., Yu, Y. & Maier, J. The nanoscale circuitry of battery electrodes. Science 358, eaao2808 (2017). \n9.\t Lee, J. et al. Reversible $\\mathrm{Mn^{2+}/M n^{4+}}$ double redox in lithium-excess cathode materials. Nature 556, 185–190 (2018). \n10.\tDunn, B., Kamath, H. & Tarascon, J.-M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n11.\tNoorden, R. V. The rechargeable revolution: a better battery. Nature 507, 26–28 (2014). \n12.\tYang, X.-G., Zhang, G., Ge, S. & Wang, C.-Y. Fast charging of lithium-ion batteries at all temperatures. Proc. Natl Acad. Sci. USA 115, 7266–7271 (2018). \n13.\tZhang, S. S., Xu, K. & Jow, T. R. A new approach toward improved low temperature performance of Li-ion battery. Electrochem. Commun. 4, 928–932 (2002). \n14.\tSmart, M. C., Whitacre, J. F., Ratnakumar, B. V. & Amine, K. Electrochemical performance and kinetics of $\\mathrm{Li}_{1+x}(\\mathrm{Co}_{1/3}\\mathrm{Ni}_{1/3}\\mathrm{Mn}_{1/3})_{1-x}\\mathrm{O}_{2}$ cathodes and graphite anodes in low-temperature electrolytes. J. Power Sources 168, 501–508 (2007). \n15.\tStuart, T. A. & Hande, A. HEV battery heating using AC currents. J. Power Sources 129, 368–378 (2004). \n16.\tWang, C.-Y. et al. Lithium-ion battery structure that self-heats at low temperatures. Nature 529, 515–518 (2016). \n17.\tRustomji, C. S. et al. Liquefied gas electrolytes for electrochemical energy storage devices. Science 356, aal4263 (2017). \n18.\tDong, X., Guo, Z., Guo, Z., Wang, Y. & Xia, Y. Organic batteries operated at $-70^{\\circ}\\mathrm{C}$ . Joule 2, 902–913 (2018). \n19.\tDong, X. et al. High energy rechargeable metallic lithium battery at $-70^{\\circ}\\mathrm{C}$ enabled by a co-solvent electrolyte. Angew. Chem. 131, 5679–5683 (2019). \n20.\tXu, K. Nonaqueous liquid electrolytes for lithium-based rechargeable batteries. Chem. Rev. 104, 4303–4418 (2004). \n21.\tFan, X. et al. Non-flammable electrolyte enables Li-metal batteries with aggressive cathode chemistries. Nat. Nanotechnol. 13, 715–722 (2018). \n22.\tRamakumar, S., Satyanarayana, L., Manorama, S. V. & Murugan, R. Structure and $\\mathrm{Li^{+}}$ dynamics of Sb-doped $\\mathrm{Li}_{7}\\mathrm{La}_{3}\\mathrm{Zr}_{2}\\mathrm{O}_{12}$ fast lithium ion conductors. Phys. Chem. Chem. Phys. 15, 11327–11338 (2013). \n23.\tKamaya, N. et al. A lithium superionic conductor. Nat. Mater. 10, 682–686 (2011). \n24.\tCroce, F., Focarete, M. L., Hassoun, J., Meschini, I. & Scrosati, B. A safe, high-rate and high-energy polymer lithium-ion battery based on gelled membranes prepared by electrospinning. Energy Environ. Sci. 4, 921–927 (2011). \n25.\tGu, G. Y. et al. 2-Methoxyethyl (methyl) carbonate-based electrolytes for Li-ion batteries. Electrochim. Acta 45, 3127–3139 (2000). \n26.\tMiara, L. J., Richards, W. D., Wang, Y. E. & Ceder, G. First-principles studies on cation dopants and electrolyte|cathode interphases for lithium garnets. Chem. Mater. 27, 4040–4047 (2015). \n27.\t Richards, W. D., Miara, L. J., Wang, Y., Kim, J. C. & Ceder, G. Interface stability in solid-state batteries. Chem. Mater. 28, 266–273 (2016). LiPON thin films. Solid State Ion. 177, 257–261 (2006). \n29.\tDudney, N. J. Addition of a thin-film inorganic solid electrolyte (Lipon) as a protective film in lithium batteries with a liquid electrolyte. J. Power Sources 89, 176–179 (2000). \n30.\tCini, R. & Torrini, M. Temperature dependence of the magnetic susceptibility of water. J. Chem. Phys. 49, 2826–2830 (1968). \n31.\tSkarmoutsos, I., Ponnuchamy, V., Vetere, V. & Mossa, S. $\\mathrm{Li^{+}}$ solvation in pure, binary, and ternary mixtures of organic carbonate electrolytes. J. Phys. Chem. C 119, 4502–4515 (2015). \n32.\tLu, Y., Tu, Z. & Archer, L. A. Stable lithium electrodeposition in liquid and nanoporous solid electrolytes. Nat. Mater. 13, 961–969 (2014). \n33.\tChoudhury, S. & Archer, L. A. Lithium fluoride additives for stable cycling of lithium batteries at high current densities. Adv. Electron. Mater. 2, 1500246 (2016). \n34.\tFan, X. et al. Highly fluorinated interphases enable high-voltage Li-metal batteries. Chem 4, 174–185 (2018). \n35.\tBi, K., Zhao, S. X., Huang, C. & Nan, C. W. Improving low-temperature performance of spinel $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ electrode and $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}/L i_{4}T i_{5}O_{12}}$ full-cell by coating solid-state electrolyte Li-Al-Ti-P-O. J. Power Sources 389, 240–248 (2018). \n36.\tFetcenko, M. A. et al. Recent advances in NiMH battery technology. J. Power Sources 165, 544–551 (2007). \n37.\t Evarts, E. C. Lithium batteries: to the limits of lithium. Nature 526, S93 (2015). \n38.\tXu, K., Zhang, S., Allen, J. L. & Jow, T. R. Nonflammable electrolytes for Li-ion batteries based on a fluorinated phosphate. J. Electrochem. Soc. 149, A1079–A1082 (2002). \n39.\tSuo, L. et al. “Water-in-salt” electrolyte enables high-voltage aqueous lithium-ion chemistries. Science 350, 938–943 (2015). \n40.\tWang, J. et al. Fire-extinguishing organic electrolytes for safe batteries. Nat. Energy 3, 22–29 (2018). \n41.\tHan, F. et al. Interphase engineering enabled all-ceramic lithium battery. Joule 2, 497–508 (2018). \n42.\tChen, L. et al. Achieving high energy density through increasing the output voltage: a highly reversible $5.3\\mathrm{V}$ battery. Chem 5, 896–912 (2019). \n43.\tHayashi, A., Hama, S., Morimoto, H., Tatsumisago, M. & Minami, T. Preparation of $\\mathrm{Li}_{2}\\mathrm{S}{\\mathrm{-P}_{2}\\mathrm{S}_{5}}$ amorphous solid electrolytes by mechanical milling. J. Am. Ceram. Soc. 84, 477–479 (2001). \n44.\tSuo, L., Hu, Y.-S., Li, H., Armand, M. & Chen, L. A new class of solvent-insalt electrolyte for high-energy rechargeable metallic lithium batteries. Nat. Commun. 4, 1481 (2013). \n45.\tPlimpton, S. Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117, 1–19 (1995). \n46.\tFrisch, M. J. et al. Gaussian 09, Rev E. 01. Wallingford CT: Gaussian, Inc. (2013). \n47.\tHohenberg, P. & Kohn, W. Inhomogeneous electron gas. Phys. Rev. 136, B864–B871 (1964). \n48.\tKresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251–14269 (1994). \n49.\tKohn, W. & Sham, L. J. Self-consistent equations including exchange and correlation effects. Phys. Rev. 140, A1133–A1138 (1965). \n50.\tMomma, K. & Izumi, F. VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J. Appl. Crystallogr. 44, 1272–1276 (2011). \n51.\tHumphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996). \n52.\tJakalian, A., Jack, D. B. & Bayly, C. I. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J. Comput. Chem. 23, 1623–1641 (2002). \n53.\t Jakalian, A., Bush, B. L., Jack, D. B. & Bayly, C. I. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method. J. Comput. Chem. 21, 132–146 (2000). \n54.\tWang, J., Wang, W., Kollman, P. A. & Case, D. A. Automatic atom type and bond type perception in molecular mechanical calculations. J. Mol. Graph. Model. 25, 247–260 (2006). \n55.\tChen, F. & Forsyth, M. Elucidation of transport mechanism and enhanced alkali ion transference numbers in mixed alkali metal–organic ionic molten salts. Phys. Chem. Chem. Phys. 18, 19336–19344 (2016). \n56.\tShimizu, K., Almantariotis, D., Gomes, M. F. C., Pádua, A. A. H. & Canongia Lopes, J. N. Molecular force field for ionic liquids V: hydroxyethylimidazolium, dimethoxy-2- methylimidazolium, and fluoroalkylimidazolium cations and bis(fluorosulfonyl)amide, perfluoroalkanesulfonylamide, and fluoroalkylfluorophosphate anions. J. Phys. Chem. B 114, 3592–3600 (2010). \n57.\tTsuzuki, S. et al. Molecular dynamics simulations of ionic liquids: cation and anion dependence of self-diffusion coefficients of ions. J. Phys. Chem. B 113, 10641–10649 (2009). \n58.\tBorodin, O. et al. Competitive lithium solvation of linear and cyclic carbonates from quantum chemistry. Phys. Chem. Chem. Phys. 18, 164–175 (2016). \n59.\tBlöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n60.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n61.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n\nR.W. conducted the calculations. X.F. and J.C. performed the XPS and Raman analysis. F.H. and J.Y. synthesized the solid-state electrolytes. X.Z. conducted the MPMS analysis. X.F. wrote the draft manuscript. X.F., X.J., Long Chen and C.W. revised the manuscript. C.W. conceived and supervised the project. All the authors contributed to the interpretation of the results. \n\n# Competing interest \n\nThe authors declare no competing interests. \n\n# Acknowledgements \n\nThis work was supported by the US Department of Energy (DOE) under award number DEEE0008202. The authors acknowledge the University of Maryland supercomputing resources (http://hpcc.umd.edu) made available for conducting the research reported in this paper. \n\n# Author contributions \n\nX.F., X.J. and Long Chen designed the experiments and analysed data. X.F., L.C., J.C., T.D., N.P., X.X. and Lixin Chen conducted the electrochemical experiments. X.J. and \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-019-0474-3. \n\nCorrespondence and requests for materials should be addressed to C.W. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 " + }, + { + "id": "10.1038_s41560-019-0409-z", + "DOI": "10.1038/s41560-019-0409-z", + "DOI Link": "http://dx.doi.org/10.1038/s41560-019-0409-z", + "Relative Dir Path": "mds/10.1038_s41560-019-0409-z", + "Article Title": "Trace doping of multiple elements enables stable battery cycling of LiCoO2 at 4.6V", + "Authors": "Zhang, JN; Li, QH; Ouyang, CY; Yu, XQ; Ge, MY; Huang, XJ; Hu, EY; Ma, C; Li, SF; Xiao, RJ; Yang, WL; Chu, Y; Liu, YJ; Yu, HG; Yang, XQ; Huang, XJ; Chen, LQ; Li, H", + "Source Title": "NATURE ENERGY", + "Abstract": "LiCoO2 is a dominullt cathode material for lithium-ion (Li-ion) batteries due to its high volumetric energy density, which could potentially be further improved by charging to high voltages. However, practical adoption of high-voltage charging is hindered by LiCoO2 's structural instability at the deeply delithiated state and the associated safety concerns. Here, we achieve stable cycling of LiCoO2 at 4.6V (versus Li/Li+) through trace Ti-Mg-Al co-doping. Using state-of-the-art synchrotron X-ray imaging and spectroscopic techniques, we report the incorporation of Mg and Al into the LiCoO2 lattice, which inhibits the undesired phase transition at voltages above 4.5 V. We also show that, even in trace amounts, Ti segregates significantly at grain boundaries and on the surface, modifying the microstructure of the particles while stabilizing the surface oxygen at high voltages. These dopants contribute through different mechanisms and synergistically promote the cycle stability of LiCoO2 at 4.6 V.", + "Times Cited, WoS Core": 688, + "Times Cited, All Databases": 732, + "Publication Year": 2019, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000474920100016", + "Markdown": "# Trace doping of multiple elements enables stable battery cycling of LiCoO2 at 4.6 V \n\nJie-Nan Zhang $\\textcircled{10}1,2,9$ , Qinghao Li1,3,9, Chuying Ouyang4, Xiqian Yu $\\textcircled{10}1,2\\star$ , Mingyuan ${\\tt G e}^{5}$ , Xiaojing Huang5, Enyuan Hu $\\textcircled{10}5$ , Chao Ma $\\textcircled{10}6$ , Shaofeng $\\mathsf{L}\\mathsf{I}^{\\prime}$ , Ruijuan Xiao1, Wanli Yang $\\textcircled{10}3$ , Yong Chu5, Yijin Liu $\\textcircled{10}7\\star$ , Huigen $\\forall u^{8}$ , Xiao-Qing Yang $\\textcircled{10}5$ , Xuejie Huang1, Liquan Chen1 and Hong Li   1,2\\* \n\n$\\mathbf{Licoo}_{2}$ is a dominant cathode material for lithium-ion (Li-ion) batteries due to its high volumetric energy density, which could potentially be further improved by charging to high voltages. However, practical adoption of high-voltage charging is hindered by $\\mathbf{LiCoO}_{2}^{\\prime}\\mathbf{S}$ structural instability at the deeply delithiated state and the associated safety concerns. Here, we achieve stable cycling of $\\mathbf{Licoo}_{2}$ at 4.6 V (versus $\\mathbf{\\mathbf{\\mathbf{Li}}}/\\mathbf{\\mathbf{\\mathbf{Li^{+}}}}$ ) through trace Ti–Mg–Al co-doping. Using state-of-the-art synchrotron X-ray imaging and spectroscopic techniques, we report the incorporation of Mg and Al into the $\\mathbf{LiCoO}_{2}$ lattice, which inhibits the undesired phase transition at voltages above $4.5V.$ We also show that, even in trace amounts, Ti segregates significantly at grain boundaries and on the surface, modifying the microstructure of the particles while stabilizing the surface oxygen at high voltages. These dopants contribute through different mechanisms and synergistically promote the cycle stability of $\\mathbf{Licoo}_{2}$ at 4.6 V. \n\nhe constantly increasing energy consumption of modern society has led to the demand for energy storage technology with higher energy densities1–3. Li-ion batteries (LIBs) are the most popular energy storage devices, which are widely deployed in portable electronics and, more recently, in electric vehicles. The energy density of LIBs is directly proportional to the working voltage and lithium storage capacity. Therefore, the development of cathode materials that are of larger reversible capacity and compatible with higher voltage charging has been a hot research topic4–7. Thanks to the tremendous research efforts devoted over the past few decades, we have witnessed the successful commercialization of quite a number of cathode materials (see the comparison of their theoretical energy densities in Supplementary Fig. 1). We note here that $\\mathrm{LiCoO}_{2},$ which was first recognized as a cathode material with good potential in the 1980s, still presents competitive or even superior energy density among all of the cathode materials that are commercially available. As a key player on today’s market of cathode materials, $\\mathrm{LiCoO}_{2}$ exhibits many essential advantages, including high theoretical capacity, $\\mathrm{Li^{+}},$ /electron conductivity, theoretical density and compressed electrode density8–10. While the theoretical capacity of $\\mathrm{LiCoO}_{2}$ is as high as $274\\mathrm{mAhg^{-1}}$ , its practical discharge capacity with an acceptable level of cycle reversibility is only about $173\\mathrm{mAhg^{-1}}$ $\\mathrm{(Li_{\\mathrm{1}-\\mathrm{{x}}}C o O_{2}}$ , $x={\\sim}0.63$ ; $4.45\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ ). Increasing the charging cut-off voltage to extract more $\\mathrm{Li^{+}}$ can further increase the capacity of $\\operatorname{LiCoO}_{2}$ (for example, $4.5\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ gives a $6.9\\%$ increase in capacity $(\\sim185\\mathrm{mAhg^{-1}})$ and $4.6\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ gives a $27.2\\%$ increase in capacity $({\\sim}220\\mathrm{mAhg^{-1}})$ ); however, such practice could lead to several detrimental problems, causing rapid decay of cycle efficiency and capacity. More specifically, when the voltage reaches $4.5\\mathrm{V},$ a harmful phase transformation from the O3 hexagonal phase to the hybridized O1–O3 hexagonal phase (denoted as the \n\nH1–3 phase, where O represents octahedral sites, 3 is the stacking sequence of oxygen layers ABCABC, and 1 represents ABAB) occurs and is accompanied by gliding of the lattice slabs and partial collapse of the O3 lattice structure11. Consequently, the internal strain builds up, leading to crack formation and particle pulverization11,12. Meanwhile, oxygen loss at high voltage further brings irreversible phase transition or even safety concerns. Besides these structural failure modes in the bulk, the surface instability is another critical issue that is amplified at the high state of charge. The high-valence $\\mathrm{\\Co/O}$ could trigger undesired interfacial side reactions, involving oxidization of the electrolyte. All of these factors add up to serious performance degradation of $\\mathrm{LiCoO}_{2}$ at high voltage, jeopardizing the practical application of the significantly increased capacity13–16. \n\nMany strategies have been considered to promote the cycle stability of $\\operatorname{LiCoO}_{2}$ at high voltage17–21. Among various approaches, foreign element doping is the most prevailing and has been demonstrated to be promising and effective for the improvement of electrochemical performances of $\\mathrm{LiCoO}_{2}{}^{22-25}$ . For example, a study compared the cycle performances of doped $\\operatorname{LiCoO}_{2}$ at a high charging voltage of $4.5\\mathrm{V}$ with various transition metal ions $\\mathrm{(LiTM_{0.05}C o_{0.95}O_{2}}\\mathrm{.}$ where $\\mathrm{TM}=\\mathrm{Mn}$ , Fe, Cu or $Z\\mathrm{n})^{26}$ , and found that Mn doping enhanced the reversible capacity the most, to ${\\sim}158\\mathrm{mAhg^{-1}}$ , compared with ${\\sim}138\\mathrm{mAhg^{-1}}$ for bare $\\operatorname{LiCoO}_{2}$ after 50 cycles in the voltage range of $3.5\\mathrm{-}4.5\\mathrm{V}.$ It has also been reported that concurrent doping of La and Al can greatly improve the Li diffusivity and structure stability of $\\mathrm{LiCoO}_{2}{}^{16}$ . With such a doping strategy, $\\mathrm{LiCoO}_{2}$ can achieve a high capacity of $190\\mathrm{mAhg^{-1}}$ over 50 cycles at a high cut-off voltage of $4.5\\mathrm{V}.$ Here, we point out that, while these previous works instinctively assume that the dopants are well incorporated into the parent lattice, theoretical calculations have predicted limited solubility of foreign atoms in $\\mathrm{LiCoO}_{2}$ in some cases27. Such inconsistencies necessitate in-depth investigations of the fundamental roles of various dopants in improving battery performances. Compared with the literature reports based on laboratory-scale experiments, it is worth noting that the doping concentration is generally two to three orders of magnitude lower for industrial production. Therefore, for $\\operatorname{LiCoO}_{2}$ with low-concentration doping at a level of industrial relevance, empirical accumulation is of vital significance and the corresponding fundamental research is urgently needed. Moreover, co-doping with multiple elements is commonly executed in practice. The desired synergistic effect among multiple dopants needs further exploration, but the characterizations of multiple doping elements at low concentrations are daunting and challenging. \n\nIn this work, we show that trace amounts of Ti–Mg–Al co-doping $(\\sim0.1\\mathrm{wt\\%}$ for each dopant) can greatly improve the cycle and rate performances of $\\mathrm{LiCoO}_{2}$ at a high charging cut-off voltage of $4.6\\mathrm{V}.$ The fundamental roles of each individual dopant in promoting the electrochemical performances are systematically studied by combining various characterization techniques, including synchrotron X-ray spectroscopy and X-ray imaging. We find that Al and $\\mathbf{Mg}$ atoms are successfully incorporated into the $\\operatorname{LiCoO}_{2}$ lattice and can effectively suppress the detrimental phase transition at high charging voltages (above $4.5\\mathrm{V}_{\\cdot}^{\\cdot}$ ). However, even at trace amounts, Ti segregates at the grain boundaries and on the particle surface, facilitating fast lithium diffusion and alleviating internal strain within the assembled $\\mathrm{LiCoO}_{2}$ particle. Moreover, the Ti-rich surface can stabilize the oxygen redox and inhibit the undesired electrode–electrolyte interfacial reactions. These experimental findings are further explained by first-principles calculations, showing that the extraordinary battery performance of Ti–Mg–Al co-doped $\\mathrm{LiCoO}_{2}$ can be attributed to both microstructure changes and electronic structure reconfiguration induced by co-doping with trace amounts of Ti, $\\mathbf{Mg}$ and Al. \n\n# Characterizations of bare LCO and TMA-LCO \n\nUndoped $\\mathrm{LiCoO}_{2}$ (bare LCO), Ti, $\\mathbf{Mg}$ or Al single-element-doped $\\mathrm{LiCoO}_{2},$ and Ti–Mg–Al co-doped $\\operatorname{LiCoO}_{2}$ (TMA-LCO) were prepared using a solid-state reaction method. The inductively coupled plasma emission spectroscopy results in Supplementary Table 1 indicate that the actual chemical compositions of these as-synthesized materials agree well with the intended compositions. Diverse characterizations of the synthesized materials were performed, and the results are summarized in Supplementary Tables 2–4 and Supplementary Figs. 2–4. It is evident that foreign-atom doping has a significant influence on various aspects of the physical properties of $\\mathrm{LiCoO}_{2}.$ , such as structural parameters, particle size, morphology and conductivity. The doping elements—especially Ti—can introduce lattice strain and slightly reduce the particle size of $\\mathrm{LiCoO}_{2}$ . Moreover, $\\mathbf{Mg}$ doping causes an increase in electronic conductivity, whereas Al doping has minimal impact on these physical parameters. \n\nHere, we focus on TMA-LCO, which shows the best electrochemical performances. The Rietveld refinements of X-ray diffraction patterns of bare LCO and TMA-LCO indicate a pure $\\scriptstyle{R-3m}$ layered structure with negligible differences in lattice parameters (Supplementary Fig. 2 and Supplementary Table 4). As shown in Fig. 1a,b, the primary particle size of TMA-LCO (that is, the diameter at which $50\\%$ of a sample’s mass comprises smaller particles (D50): ${\\sim}15\\upmu\\mathrm{m})$ ) is slightly smaller than that of bare LCO (D50: ${\\sim}16\\upmu\\mathrm{m})$ ). Further elemental mappings of the local region over a TMA-LCO particle show an overall homogeneous distribution of the foreign elements Ti, $\\mathbf{Mg}$ and Al (Fig. 1d), except for the Ti-rich edge region. In view of the resolution limit of elemental mapping, energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) and electron energy loss spectroscopy (EELS) measurements were carried out, revealing the slight differences in elemental concentration between the centre and edge areas of the TMA-LCO particle. As highlighted in Fig. 1e,f, both EDS and EELS results show that Ti has a higher elemental concentration at the surface than in the interior of the particle, but there is no evident difference for Mg and Al. To further confirm this phenomenon, elemental distribution near the particle edge in a finer area was analysed. The high-angle annular dark-field image and elemental mappings near the particle edge of the crosssectional transmission electron microscopy (TEM) sample are shown in Supplementary Fig. 5, which shows Ti aggregation at the particle surface. X-ray photoelectron spectroscopy (XPS) etching results further confirm the heterogeneity of the spatial distribution of Ti within the particles (Supplementary Fig. 6). \n\n# Electrochemical performances \n\nThe electrochemical performances of bare LCO and TMA-LCO were evaluated in both half cells and full cells, and the results are displayed in Fig. 2a–e and Supplementary Figs. 7 and 8 (initial charge–discharge curves and cycle versus rate performances, respectively). It is apparent that TMA-LCO presents improved cycle stability in half cells compared with bare LCO, in particular at the high-charging cut-off voltage of $4.6\\mathrm{V}.$ A high reversible discharge capacity of $174\\mathrm{mAhg^{-1}}$ , with capacity retention of $86\\%$ (compared with the second cycle), is achieved in TMA-LCO after 100 cycles at a current rate of $0.5\\mathrm{C}$ ( $\\scriptstyle1\\mathrm{C}=274\\mathrm{mA}\\mathrm{g}^{-1}$ ; note that all cells were cycled at $0.1\\mathrm{C}$ for the formation process at the first cycle). The Coulombic efficiency was also recorded during electrochemical cycling. The TMA-LCO cell shows slightly higher Coulombic efficiency $(93.7\\%)$ than the bare LCO cell $(90.2\\%)$ at $4.6\\mathrm{V}$ charging for the first cycle, quickly increases to $99\\%$ after three cycles and remains stable for the subsequent cycles (Supplementary Fig. 9). The charge–discharge profiles at selected cycle numbers are presented in Fig. $^{2\\mathrm{b},\\mathrm{c}}$ . It can be seen that bare LCO has significantly degraded voltage profiles after 50 cycles, indicating the more severe structural degradation in bare LCO than TMA-LCO. The cycle and rate performances of single-element-doped $\\mathrm{LiCoO}_{2}$ were also evaluated, and the results are shown in Supplementary Fig. 8. They all show better cycle and rate performances than bare LCO, but inferior performances to TMA-LCO. \n\nFor potential practical applications, full pouch cells $(\\sim2.8\\mathrm{Ah})$ with bare LCO or TMA-LCO cathodes and commercial graphite anodes were assembled and cycled at room temperature in the voltage range of $3.0{-}4.55\\mathrm{V}$ (equivalent to $4.6\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ ). As shown in Fig. 2d, the capacity of bare LCO fades quickly to $51.3\\mathrm{mAhg^{-1}}$ after 70 cycles. In contrast, the TMA-LCO cell shows much improved capacity retention with a capacity of $178.2\\mathrm{mAhg^{-1}}$ after 70 cycles, and a much more stable Coulombic efficiency than that of bare LCO (Supplementary Fig. 10). The discharge voltage remains almost unchanged at around $3.90\\mathrm{V}$ for TMA-LCO, while it gradually drops to $3.51\\mathrm{V}$ for bare LCO. The seriously degraded cycle performance of the bare LCO full cell can be attributed to the irreversible structural transformation and unwanted side reactions, which can be further proved by the obvious gas generation in the cycled pouch cell, as shown in the inset of Fig. 2e. Overall, TMALCO shows greatly improved electrochemical performances in both the half cell and the full cell at a high charging cut-off voltage of $4.6\\mathrm{V}$ (versus $\\mathrm{Li/Li^{+}}$ ) compared with bare LCO (a comparison of the performances with reports in the literature for high-voltage $\\mathrm{LiCoO}_{2}$ is provided in Supplementary Tables 5 and 6). \n\n# Structural evolution during first charge–discharge process \n\nAs the cycle stability of $\\mathrm{LiCoO}_{2}$ is strongly associated with its structural evolution, in  situ X-ray diffraction (XRD) experiments were performed to study the phase transition behaviour. Although pristine bare LCO and TMA-LCO share a similar crystal structure, distinct differences in structural evolution over the first charge–discharge process can be observed, as shown in Fig. 3a,b. The (003) and (107) diffraction peaks were selected for demonstration. A relatively small (003) peak shift is observed in TMA-LCO at a high voltage of \n\n![](images/d4ea43d9e5be80f1e7d34601d93fd3a1cfde21245df41626d839b322cc8474e4.jpg) \nFig. 1 | Morphology and elemental distribution in bare LCO and TMA-LCO. a,b, Scanning electron microscopy (SEM) images of bare LCO (a) and TMALCO (b). Scale bars: $20\\upmu\\mathrm{m}$ . c, Cross-sectional TEM image of TMA-LCO. Scale bar: $2\\upmu\\mathrm{m}$ . d, High-angle annular dark-field scanning TEM image and EDS elemental mappings of O, Co, Ti, $\\mathsf{M g}$ and Al (scale bar: $100\\mathsf{n m},$ ) in the selected region indicated by the yellow rectangle in c, showing an overall homogeneous distribution of the doping elements Ti, Mg and Al, except for the Ti-rich edge region (see the enlarged images and integrated intensity profiles in Supplementary Fig. 5). e,f, EDS (e) and EELS spectra $(\\pmb{\\uparrow})$ , collected separately from the edge (surface) and centre (interior) regions of TMA-LCO, as indicated by the white arrows in c. The green dashed rectangle highlights the signal of Ti, revealing the slightly increased concentration of Ti in the edge region compared with the centre region in the TMA-LCO particle. \n\n$4.6\\mathrm{V},$ in contrast with the dramatic (003) peak shift in bare LCO. This could be attributed to the suppressed O3 to H1–3 phase transition, which is accompanied by the oxygen stacking sequence change (Fig. 3d)28,29. Such mitigation of structural changes is also shown in the (107) peak shift, as highlighted by the vertical dotted lines in Fig. 3a,b. The (107) peak splitting at $4.1\\mathrm{V}$ occurs in both bare LCO and TMA-LCO, and can be attributed to an order–disorder transition30,31. Considering the superior battery performance of TMALCO, the conversion between the hexagonal and monoclinic phases at around $4.1\\mathrm{V}$ may not be the main cause of performance degradation. The phase transition behaviour also manifests itself in the charge–discharge voltage profiles and cyclic voltammetry curves of bare LCO and TMA-LCO, which are shown in Fig. 3c. The persistence of the anodic and cathodic peaks due to the order–disorder transition and the difference between bare LCO and TMA-LCO at a high voltage of $4.6\\mathrm{V}$ are consistent with the in situ XRD results. \n\n# 3D elemental distributions in the TMA-LCO particle \n\nConsidering the indication of a non-uniform dopant distribution from the EDS and EELS results, it is necessary to determine the actual spatial distribution of the key elements in the $\\mathrm{LiCoO}_{2}$ particles. X-ray fluorescence mapping, which is capable of detecting the spatial elemental distribution and concentration with high sensitivity, was utilized to probe the 3D elemental distribution within an arbitrarily selected TMA-LCO particle. Because $\\mathbf{Mg}$ was outside of the working energy window, only Al, Co and Ti signals were collected, and the 3D renderings of their distributions are displayed in Fig. 4a–c. Figure 4d–f shows the elemental distributions over a virtual $x{-}z$ slice through the centre of the particle. The absolute concentrations of these elements are very different, as indicated by the coloured scale bar in the corresponding insets. It is evident from Fig. 4a,d that Al is homogeneously distributed throughout the entire particle, with a minor degree of concentration variation. In contrast, the Ti distribution presented in Fig. $^{4\\mathrm{c},\\mathrm{f}}$ shows a large degree of segregation. The Ti-rich phase forms a complex interconnected network (as highlighted by the dashed lines in Fig. 4f), dividing the $\\mathrm{LiCoO}_{2}$ particle into several subdomains. For further evaluation of the subdomain separation effect, we first calculated the Ti-to-Co ratio, voxel by voxel, throughout the entire 3D volume. Areas with a Ti-to-Co ratio equal to or below the nominal value are segmented as active subdomains. As shown in Fig. 4g, 50 subdomains were identified and visualized. Note that different colours are used to distinguish adjacent subdomains for visualization. However, colours are reused for subdomains that are far apart, due to the large number of subdomains identified. Further quantification of these subdomains suggests that they have a wide distribution in volume and surface area, as indicated by Fig. $^\\mathrm{4h,i}$ . Compared with the entire particle as a whole, the subdomains with largely reduced size and significantly increased surface area ensure fast $\\mathrm{Li^{+}}$ diffusion in the microsized particles, which could be one major factor responsible for the improved rate performance of TMA-LCO. In addition, the subdomains separated by the Ti-rich phase can effectively reduce the lattice breathing induced by Li intercalation, and are more robust against lattice strain and particle fracture, thereby possibly enhancing the long-term cycle stability of TMA-LCO. To ensure the representativeness of the conclusion drawn from the single particle analysis, we conducted 2D elemental mapping over many TMALCO particles using a synchrotron-based microprobe. The correlation evaluation and principle component analysis of the Co and Ti maps further confirm the heterogeneity distribution of Ti from a statistical point of view (Supplementary Fig. 11). \n\n![](images/a4bc5a012964415834e1298471f1c112edd0216466a576aadd9f1906b269f03b.jpg) \nFig. 2 | Electrochemical characterization of bare LCO and TMA-LCO. a, Comparison of cycle performances of $\\mathsf{L i C o O}_{2}|$ Li half cells with bare LCO versus TMA-LCO. b,c, Charge–discharge curves of bare LCO (b) and TMA-LCO (c) half cells for the 1st, 5th, 10th, 50th and 100th cycles. The charge and discharge tests were conducted at 0.1 C for the first cycle and $_{0.5\\mathsf{C}}$ for the subsequent cycles. d, Cycle performances of $\\mathsf{L i C o O}_{2}\\vert$ |graphite full cells with bare LCO versus TMA-LCO. A constant current and constant voltage mode was used for the full-cell tests. For the charge process, the cells were charged at 0.33 C to $4.55\\mathsf{V}$ and then the voltage was held until the current dropped to 0.1 C. The discharge current was 0.33 C. e, Discharge voltage of the full cells and energy density of the cathode materials as a function of cycle number. Inset, pouch cells after the 70th cycle; obvious gas generation can be observed in the bare LCO|graphite pouch cell. \n\n# Surface reaction probed by soft X-ray spectroscopy \n\nSoft $\\mathrm{\\DeltaX}$ -ray spectroscopy (sXAS) measurements were performed to study the surface properties of bare LCO and TMA- $\\mathrm{.LCO^{32}}$ . Considering the strong correlation between oxygen involvement and battery failure at high voltage, the O K edge spectra are the research focus. Note that the strong hybridization between the transition metal $3d$ and O $2p$ states makes it challenging to separate the lattice oxygen signal from $\\mathrm{~O~K~}$ edge X-ray absorption spectroscopy $(\\mathrm{XAS})^{33}$ . As a result, resonant inelastic X-ray scattering (RIXS; probing depth: $\\sim150\\mathrm{nm},$ ), with extra resolution along the emission energy dimension, was selected as the tool of choice to clarify the role of oxygen34. \n\nO K edge RIXS maps for bare LCO and TMA-LCO charged to $4.6\\mathrm{V}$ are shown in Fig. 5a,b, respectively, and the corresponding RIXS maps for pristine materials are shown in Supplementary Fig. 12. On deep delithiation, the most obvious change for bare LCO is the appearance of a well-distinguished isolated feature at an incident energy of $531\\mathrm{eV}$ (Fig. 5a), indicating the oxidization of $\\mathrm{O}^{2-}$ to a higher-valence state35. This RIXS feature becomes much weaker in TMA-LCO, indicating less participation of oxygen redox in the outer shell of TMA-LCO particles (in view of the probing depth of $\\sim150\\mathrm{nm}$ ) compared with bare LCO, and the improved oxygen stability will also contribute to the enhanced safety behaviours at high voltage (Supplementary Figs. 13 and 14). Moreover, the RIXS spectra show the superior stability of TMA-LCO after 20 cycles compared with bare LCO, as shown in Fig. 5c. The elemental doping probably changes the intrinsic electronic structure, and consequently affects the redox reactions, particularly the oxygen redox chemistry. \n\nThe route of surface reactions with electrolyte may also be affected due to the different chemical reactivity of surface oxygen between bare LCO and TMA-LCO. Both XPS and sXAS results confirm the distinct cathode/electrolyte interphase (CEI) formed on bare LCO and TMA-LCO. As can be seen from the fitted O 1s XPS spectra in Fig. 5d, lattice oxygen (shaded area) shows a sharper peak that overwhelms signals from the CEI components in TMALCO compared with bare LCO, implying a relatively thinner and more stable CEI layer on TMA-LCO, as is schematically illustrated in Fig. 5e. Such an interpretation is also supported by quantitative analysis of XPS results, as shown in Supplementary Figs. 15 and 16 and Supplementary Table 7. Meanwhile, sXAS data collected in total electron yield (TEY) and total fluorescence yield (TFY) modes can provide further contrast between surface and bulk regions. Surfacesensitive TEY and bulk-sensitive TFY signals of TMA-LCO and bare LCO in different cycle states are displayed as solid and dotted lines, respectively, in Supplementary Fig. 17. Note that the TEY spectra do not simply reproduce the TFY spectra, which can be attributed to interfacial reactions between the electrode and electrolyte. The relatively low pre-edge shoulder in TEY indicates the decrease of high valence Co at the particle surface, particularly for TMA-LCO. This phenomenon implies that different types of CEI layer form on TMA-LCO and bare LCO, which is consistent with the O 1s XPS results. The stable interface layer between cathode materials and electrolyte can also suppress the Co dissolution process (Supplementary Figs. 18–20). Therefore, the thinner and more stable CEI layer is expected to contribute to the superior electrochemical performances of TMA-LCO. \n\n![](images/470dc253258b68e3b47f13054e491139f71611634eab978dfed54544687827ee.jpg) \nFig. 3 | Structural evolution during the initial charge–discharge process. a,b, In situ XRD evolution of bare LCO (a) and TMA-LCO (b) at the (003) and (107) diffraction peaks, with the corresponding charge–discharge curves aligned to the left. A suppressed O3 to H1–3 phase transition with a smaller (107) diffraction peak shift $(0.16^{\\circ})$ can be observed for TMA-LCO at the $4.6\\mathsf{V}$ charged state. c, Cyclic voltammetry results of bare LCO and TMA-LCO. d, Schematic of the atomic stacking of $\\mathsf{L i}_{x}\\mathsf{C o O}_{2}$ in the O3 and H1–3 phases. For pristine $\\mathsf{L i C o O}_{2},$ the stacking can be described as being in the O3 phase, with an oxygen layer stacking sequence of ABCABC. On charging to $4.6\\mathsf{V},$ this sequence changes into ABABCACABCBC and the O3 to H1–3 phase transition occurs. \n\n# Density functional theory and doping mechanisms \n\nAs Ti is rich on the surface of TMA-LCO, first principles calculations were conducted to gain a fundamental understanding of the Ti surface doping mechanism in $\\mathrm{LiCoO}_{2}$ . To verify the experimental observations on Ti distribution, the optimized $\\operatorname{LiCoO}_{2}$ (104) slab model was used (Fig. 6a). First, we considered replacing one Co atom from different layers of the slab with a Ti atom, and compared the total ground-state energies of Ti-doped $\\mathrm{LiCoO}_{2}$ at different atomic layers, as listed in Supplementary Table 8. The Ti atom prefers to stay at the surface layer, rather than in the inner layers, with a $0.7\\mathrm{eV}$ lower total energy. Then, we replaced two Co atoms at the surface layer with two Ti atoms, and considered the distribution of Ti atoms at the surface region. The different distances between the nearest Ti atoms on the (104) surface are shown in Supplementary Fig. 21, and the total energies are listed in Supplementary Table 9. The results indicate the preference of Ti occupancy at the surface region. The incorporation of Ti into the $\\operatorname{LiCoO}_{2}$ lattice alters the electronic structure as well. Figure $6\\ensuremath{\\mathrm{b}}$ compares the $2p$ states of the O atoms at the $\\operatorname{LiCoO}_{2}$ (104) surface. Unoccupied O $2p$ states can be observed for the surface O atoms for both Ti-doped and undoped $\\mathrm{LiCoO}_{2}$ in the delithiated $\\mathrm{Li}_{0.29}\\mathrm{CoO}_{2}$ state. However, the unoccupied states above the Fermi level are significantly suppressed after Ti doping, indicating suppressed charge deficiency in the surface layer. Figure 6c displays the relaxed structure of delithiated $\\mathrm{Li}_{0.29}\\mathrm{CoO}_{2}$ together with the charge density of the surface O atoms compared with lithiated $\\mathrm{LiCoO}_{2}$ . The charge density contour clearly shows a substantial charge deficiency for the O atoms in the surface layer. The O atoms near the Ti atoms lose less charge compared with those far from the Ti atoms. Figure 6d shows the optimized atomic structure of Ti-doped $\\mathrm{Li}_{0.29}\\mathrm{CoO}_{2};$ , where Ti atoms tend to stay in the surface layer. Charge analysis shows that the surface O atoms around Ti atoms hold more charge (are less oxidized), implying that Ti doping helps to resist the charge deficiency of the O atoms on delithiation. This agrees well with the aforementioned RIXS results. \n\n# Conclusions \n\nIn summary, by virtue of Ti–Mg–Al co-doping, the physical properties of $\\mathrm{LiCoO}_{2}$ , including the bulk crystal structure, electronic structure, particle shape and microstructure, are effectively modified. Each doping element plays a different role in modifying the material properties from different aspects. More specifically, $\\mathbf{M}\\mathbf{g}$ and Al atoms have been successfully doped into the $\\mathrm{LiCoO}_{2}$ lattice, altering the phase transition behaviour in the (de)lithiation process. $\\mathbf{Mg}$ doping can also increase the electronic conductivity of the material. In contrast, even trace amounts of Ti cannot be completely incorporated into the $\\operatorname{LiCoO}_{2}$ lattice. The segregation of Ti at the grain boundaries and on the surface, on the one hand, modifies the microstructure of the sample particle that is favourable for overall lithium diffusion and uniform internal strain distribution, and on the other hand, inhibits the oxygen activity and stabilizes the surface at high charging voltages. All of these effects synergistically add up to the remarkably improved electrochemical performances. \n\n![](images/2dc84d0275736018063f7a49262dfe4540d22a8972a81c8ba2e027d1ac009f51.jpg) \nFig. 4 | 3D X-ray tomography reconstruction and element distribution in TMA-LCO. a–c, 3D spatial distributions of Al (a), Co (b) and ${\\sf T i}({\\pmb\\bullet}),$ probed by fluorescence-yield scanning transmission X-ray microscopy. Scale bar: $1\\upmu\\mathrm{m}$ . d–f, Elemental distributions of Al (d), Co (e) and Ti (f) over the virtual $x{-}z$ slice through the centre of the particle. The green, blue and orange scale bars show counts. g, Identified and visualized subdomain formation. Note that different colours are used to distinguish between adjacent subdomains. h, Quantification of the volume and surface area of the subdomains and the entire particle as a whole (inset). The grey shadow is the linear trend extracted from the data for the subdomains. i, Volume distribution of all of the subdomains. Inset: volume fraction of each individual subdomain, highlighting the existence of a few large subdomains, which make up nearly $50\\%$ of the total volume, and a large number of small domains. \n\nIt can be inferred from this work that the rational design of electrode materials relies on comprehensive modifications from various aspects. Multiscale and multifaceted characterizations are the key to gaining insights into the roles of the modification elements, as well as the fundamental principles of the modification approaches. Moreover, as verified in this specific case, the low solubility of Ti and, thus, the segregation at the particle surface and grain boundaries, plays a vital role in electrochemical performance enhancement. The specific behaviour of Ti, which is beyond the conventional doping scenario, implies the necessity to revisit elements with a nonoptimum solubility as dopants for material design and optimization. This would have profound implications for the design of electrode materials, well beyond the present case of high-voltage $\\mathrm{LiCoO}_{2}$ cathodes for LIBs. Finally, it should be pointed out that, from the perspective of practical applications, the performances of $\\operatorname{LiCoO}_{2}$ at $4.6\\mathrm{V}$ are still far from satisfactory. The development of highenergy-density LIBs with high-voltage $\\operatorname{LiCoO}_{2}$ requires comprehensive consideration of the cathode, anode, electrolyte and other key components, which calls for more research efforts and engineering considerations. Nonetheless, this work unfolds the promising future of dragging $\\operatorname{LiCoO}_{2}$ to even higher voltage and approaching the theoretical capacity limit for practical applications. \n\n![](images/39a6a5a50baec99e545bf0b62dfc8e848a3f7676c9f443b7cbcc229c957f4482.jpg) \nFig. 5 | Revealing the surface chemistry with soft X-ray spectroscopy. a,b, O K edge RIXS maps collected on $4.6\\mathsf{V}$ charged bare LCO (a) and TMA-LCO (b). With a low X-ray irradiation energy of \\~529 eV, O 1s electrons are excited into unoccupied Co 3d–O $2p$ hybridization states, whereas irradiation with high-energy X-rays $(\\sim540\\mathsf{e V},$ ) excites O 1s electrons into Co $4s p\\mathrm{-}\\ensuremath{\\mathsf{O}}2p$ hybridization states. The horizontal dashed lines indicate the excitation energy at which the RIXS spectra in c were collected (around 531 eV). c, RIXS spectra collected on bare LCO (top) and TMA-LCO (bottom) in pristine, $4.6\\mathsf{V}$ charged states, and the $3.0\\vee$ discharged state after the 20th cycle with an $\\mathsf{X}$ -ray excitation energy of $531\\mathrm{eV.}$ The electrodes were prepared from cells cycled at a current rate of 0.1 C. d, O 1s XPS spectra of bare LCO (top) and TMA-LCO (bottom) electrodes after the 10th cycle at the $3.0\\vee$ discharged state. e, Schematic of the differences in CEI between bare LCO and TMA-LCO. \n\n# Methods \n\nMaterial synthesis. The $\\operatorname{LiCoO}_{2}$ materials were prepared by a solid-state reaction method using $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ $(99\\%)$ ), $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ $(99.7\\%)$ ), $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ $(99.9\\%)$ , MgO $(99\\%)$ and $\\mathrm{TiO}_{2}$ $(99.9\\%)$ as precursors. All of the raw materials are industrial materials of battery grade. An excess of $5\\mathrm{wt\\%}$ $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ was used to compensate for the lithium loss during high-temperature synthesis. The starting materials were ground in an Agate mortar and the mixed powders were sintered at $1,000^{\\circ}\\mathrm{C}$ for $\\mathrm{10h}$ in an Alumina crucible to form the intermediate products. Then, the intermediate products were ground again in an Agate mortar and sintered for a second time at $900^{\\circ}\\mathrm{C}$ for $10\\mathrm{{h}}$ to obtain the final products. \n\nXRD and SEM characterization. The XRD measurements were conducted using a Bruker D8 ADVANCE diffractometer with Cu Kα radiation $(\\lambda=1.5405\\mathrm{\\AA})$ ) in the scan range (2θ) of $10{-}80^{\\circ}$ . For the in situ XRD experiments, a specially designed Swagelok cell equipped with an X-ray-transparent aluminium window was used for the in situ measurements. The in situ XRD patterns were collected with an interval of $40\\mathrm{min}$ for each 2θ scan from $10{-}60^{\\circ}$ on charging and discharging at a current rate of $0.1\\mathrm{C}$ $\\mathrm{1C=274mAg^{-1}}$ ). The morphologies of the samples were investigated by SEM (Hitachi S-4800). \n\nXPS characterization. The XPS measurements were recorded with a spectrometer with Mg/Al $\\operatorname{K}\\upalpha$ radiation (ESCALAB 250 Xi; Thermo Fisher Scientific). All binding energies were calibrated using the C 1s peak of the Super P at $284.4\\mathrm{eV}$ as an internal standard. To prevent air exposure, all samples were transferred using a transfer box provided by Thermo Fisher Scientific. \n\nTEM characterization. The TEM/scanning TEM images, EDS and EELS measurements were performed using a JEOL ARM200F microscope operating at $200\\mathrm{kV},$ which was equipped with a probe-forming aberration corrector and Gatan image filter (GIF Quantum 965). \n\nHalf-cell assembly. The $\\mathrm{LiCoO_{2}/L i}$ half-cell tests were conducted using coin cells (CR2032), assembled in an argon-filled glove box. The working electrodes were prepared by coating the slurry mixture of active material $(80\\mathrm{wt\\%})$ , Super P $(10\\mathrm{wt\\%})$ and polyvinylidene fluoride $(10\\mathrm{wt\\%})$ on an aluminium current collector, followed by drying at $120^{\\circ}\\mathrm{C}$ in a vacuum for $\\mathrm{10h}$ . The loading of active material was controlled to between 3.0 and $4.0\\mathrm{mg}\\mathrm{cm}^{-2}$ . The electrolyte was a solution of $1\\mathrm{MLiPF}_{6}$ in ethylene and dimethyl carbonate (1:1 in volume). Lithium foil was used as the counter electrode, and $\\mathrm{Al}_{2}\\mathrm{O}_{3}$ -coated polyethylene film was used as the separator. \n\nFull-cell assembly. The $\\mathrm{LiCoO}_{2}/$ graphite full-cell tests were conducted using stacked pouch cells assembled in a dry room. The cathode electrodes were prepared by coating the mixture slurry of active material $(95\\mathrm{wt\\%})$ , carbon black $(3\\mathrm{wt\\%})$ and polyvinylidene fluoride $(2\\mathrm{wt\\%})$ on an aluminium current collector, followed by drying at $120^{\\circ}\\mathrm{C}$ in a vacuum for $\\mathrm{10h}$ . The areal capacity was controlled to between 3.5 and $3.8\\mathrm{mAh}\\mathrm{cm}^{-2}$ . The anode electrodes were composed of graphite $(94.5\\mathrm{wt\\%})$ ), carbon black $(2\\mathrm{wt\\%})$ , carboxy methyl cellulose sodium $(1.5\\mathrm{wt\\%})$ ) and styrene butadiene rubber $(2\\mathrm{wt\\%})$ , and fabricated following the same coating and drying procedures. The capacity ratio between negative electrode and positive electrode was controlled to between 1.05 and 1.08. The electrolyte and separator were the same as those used in the half cells. \n\n![](images/fc79e3c7c5f743c9dbe99d0ce11b67d2d9aba9a904be01de46278abcfd04200e.jpg) \nFig. 6 | Density functional theory calculations for Ti substitution that can modify the surface electronic structure. a, Optimized atomic structure of the (104) slab of $\\mathsf{L i C o O}_{2}$ . The grey, blue and red spheres represent Li, Co and O atoms, respectively. b, Projected density of states (PDOS) values of the surface $\\textsf{O}$ atom at the (104) surface of $\\mathsf{L i C o O}_{2},\\mathsf{L i}_{0.29}\\mathsf{C o O}_{2}$ and Ti-doped $\\mathsf{L i}_{0.29}\\mathsf{C o O}_{2}$ . $E_{\\scriptscriptstyle\\mathsf{F}}$ represents the Fermi level. c,d, Optimized atomic structures of the (104) slab of $\\mathsf{L i}_{0.29}\\mathsf{C o O}_{2}$ (c) and Ti-doped (104) slab of $\\mathsf{L i}_{0.29}\\mathsf{C o O}_{2}$ (d). The larger cyan sphere in d represents the Ti ion substituting the corresponding Co ion. The insets on the right-hand side for c and d are the top views of the corresponding surface structures (top) and surface charge density contours (bottom), respectively. The numbers on the charge density contours are the charge loss (in electrons) of the corresponding O atom on delithiation from $\\mathsf{L i C o O}_{2}$ to $\\mathsf{L i}_{0.29}\\mathsf{C o O}_{2},$ as obtained from Bader charge analysis. \n\nElectrochemical measurements. The charge and discharge tests were carried out using a Land CT2001A battery test system in a voltage range of $3.0{-}4.6\\mathrm{V}$ at various C rates at room temperature for the half cells. For the full-cell tests, a constant current and constant voltage mode was used. The cells were charged at $0.33\\mathrm{C}$ to $4.55\\mathrm{V}$ and then held until the current dropped to $0.1\\mathrm{C}$ . The discharge process was conducted at a constant current mode at $0.33\\mathrm{C}$ . The full cells were cycled at the first two cycles for the formation process. For the first cycle, the pouch cells were charged at $0.02\\mathrm{C}$ for $2\\mathrm{h}$ . After resting for $5\\mathrm{min}$ , the cells were charged at $0.2\\mathrm{C}$ to $4.55\\mathrm{\\AA}$ and then held at this voltage until the current dropped to $0.02\\mathrm{C}$ (constant voltage process). Then, the cells were discharged at $0.2\\mathrm{C}$ to 3 V and rested for $5\\mathrm{{min}}$ . For the second cycle, the cells were charged at $0.2\\mathrm{C}$ to $3.85\\mathrm{V}$ and rested at $45^{\\circ}\\mathrm{C}$ for $48\\mathrm{h}$ to complete the formation process. \n\nSynchrortron 2D and 3D fluorescence measurements and data analysis. Nanoand microfluorescence mapping were performed, respectively, at the Hard X-ray Nanoprobe Beamline of the National Synchrotron Light Source II at Brookhaven National Laboratory and Beamline 2-3 of the Stanford Synchrotron Radiation Lightsource at the SLAC National Accelerator Laboratory. The nanoprobe experiment was carried out at $9.6\\mathrm{keV}$ by focusing the coherent monochromatic X-rays down to a $50\\mathrm{-nm}$ spot size using a Fresnel X-ray zone plate. Tomography measurements were performed by collecting a total of 51 projections from $-75^{\\circ}$ to $75^{\\circ}$ , with $3^{\\circ}$ intervals. The tomographic reconstruction was carried out using an iterative algorithm known as the algebraic reconstruction technique. Further visualization and quantification of the imaging data were carried out using the commercial software package Avizo. The segmentation of subdomains in the imaged particle was based on the concentration ratio between Co and Ti. As discussed in the main text, the regions rich in Ti form interconnected networks (Fig. 4c,f) that divide the particle into 50 subdomains (Fig. 4g). The microprobe experiment was carried out using a Kirkpatrick–Baez mirror focused X-ray spot of ${\\sim}1\\upmu\\mathrm{m}$ to image a large field of view covering many particles, to ensure statistical representativeness (Supplementary Fig. 11). The correlation analysis of Ti and Co distribution was coupled with principle component analysis to separate the Ti-rich domains from the area of nominal composition. \n\nSynchrotron soft X-ray spectroscopy. Soft X-ray spectroscopy measurements were performed at Beamline 8.0.1 of the Advanced Light Source at the Lawrence Berkeley National Laboratory. The beamline is equipped with a spherical grating monochromator that supplies linearly polarized soft X-rays with a resolving power up to 6,000. The XAS spectra were collected in both TEY and TFY modes simultaneously. TEY is surface sensitive with a probing depth of ${\\sim}10\\mathrm{nm}$ , while TFY provides bulk information with a probing depth of $\\sim150\\mathrm{nm}$ . The energies of the O K edge XAS spectra were aligned based on O K edge of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ references. The spectra intensities were normalized to the beam flux measured by a gold mesh upstream. The RIXS experiments were carried out with the high-resolution RIXS system at Beamline 8.0.1 of the Advanced Light Source. The newly built-up system is equipped with a refocusing mirror, a spherical pre-mirror, a variable line-spacing grating and a high-resolution X-ray photon detector with entrance slitless design. The slitless operation improves the acceptance angle of the spectrograph and increases the throughput without compromising energy resolution. The incident excitation energy scale was calibrated according to XAS of the $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ reference sample, while the subsequent emission energy was calibrated using the elastically scattering line. The final datasets were presented on a 2D map, where the emission intensity was colour coded as a function of the incident excitation (ordinate) energy and emission energy (abscissa). \n\nFirst principles calculations. All density functional theory calculations were performed with the Vienna ab initio Simulation Package36. The spin-polarized generalized gradient approximation (GGA) with PBE function37 was used to treat the electron exchange–correlation interactions, and the projector-augmented wave approach38 was used to take into account the electron–ion interactions. Since GGA cannot correctly reproduce the localized electronic states of the transition metal oxide materials, the $\\mathrm{GGA}+U$ method was used39,40. The $U$ values for the Co $_{3d}$ and $\\operatorname{Ti}3d$ states were chosen to be 4.91 and $5.0\\mathrm{eV},$ respectively41,42. Furthermore, we included the Van der Waals interaction throughout the calculations. A planewave basis with a kinetic energy cut-off of $520\\mathrm{eV}$ was used. The Monkhorst–Pack scheme43, with a $2\\times3\\times1$ k-point mesh, was used for the integration in the irreducible Brillouin zone. The lattice parameters and ionic position were fully relaxed, and the final forces on all atoms were less than $0.01\\mathrm{\\bar{e}V}\\mathrm{\\AA}^{-1}$ . Density of states calculations were smeared using the Gaussian smearing method with a smearing width of $0.05\\mathrm{eV}.$ The $\\mathrm{LiCoO}_{2}$ (104) surface was simulated using the symmetric periodic slab model containing 42 Li atoms, $^{84}\\mathrm{O}$ atoms and $42\\mathrm{Co}$ atoms, with consecutive slabs separated by an $18\\mathrm{\\AA}$ vacuum layer. The delithiatedstate $\\mathrm{Li}_{0.29}\\mathrm{CoO}_{2}$ was modelled by extracting 30 out of 42 Li ions from the $\\mathrm{LiCoO}_{2}$ slab system. The Ti-doped $\\mathrm{LiCoO_{2}/L i_{0.29}C o O_{2}}$ slab system was modelled by substituting 1 out of 42 Co ions with a Ti ion. \n\n# Data availability \n\nThe data that support the plots within this paper and other finding of this study are available from the corresponding author upon reasonable request. \n\nReceived: 25 October 2018; Accepted: 9 May 2019; Published online: 17 June 2019 \n\n# References \n\n1.\t Whittingham, M. S. Ultimate limits to intercalation reactions for lithium batteries. Chem. Rev. 114, 11414–11443 (2014). \n2.\t Goodenough, J. B. Evolution of strategies for modern rechargeable batteries. Acc. Chem. Res. 46, 1053–1061 (2013). \n3.\t Nitta, N., Wu, F., Lee, J. T. & Yushin, G. Li-ion battery materials: present and future. Mater. Today 18, 252–264 (2015). \n4.\t Lin, F. et al. Metal segregation in hierarchically structured cathode materials for high-energy lithium batteries. Nat. Energy 1, 15004 (2016). \n5.\t Lin, F. et al. Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries. Nat. Commun. 5, 3529 (2014). \n6.\t Liu, C. F., Neale, Z. G. & Cao, G. Z. Understanding electrochemical potentials of cathode materials in rechargeable batteries. Mater. Today 19, 109–123 (2016). \n7.\t Wang, D. W. et al. Synthetic control of kinetic reaction pathway and cationic ordering in high-Ni layered oxide cathodes. Adv. Mater. 29, 1606715 (2017). \n8.\t Radin, M. D. et al. Narrowing the gap between theoretical and practical capacities in Li-ion layered oxide cathode materials. Adv. Energy Mater. 7, 1602888 (2017). \n9.\t Kalluri, S. et al. Surface engineering strategies of layered $\\mathrm{LiCoO}_{2}$ cathode material to realize high-energy and high-voltage Li-ion cells. Adv. Energy Mater. 7, 1601507 (2017). \n10.\tGu, R. et al. Improved electrochemical performances of $\\mathrm{LiCoO}_{2}$ at elevated voltage and temperature with an in situ formed spinel coating layer. ACS Appl. Mater. Interfaces 10, 31271–31279 (2018). \n11.\tYano, A., Shikano, M., Ueda, A., Sakaebe, H. & Ogumi, Z. $\\mathrm{LiCoO}_{2}$ degradation behavior in the high-voltage phase transition region and improved reversibility with surface coating. J. Electrochem. Soc. 164, A6116–A6122 (2017). \n12.\tXu, Y. H. et al. In situ visualization of state-of-charge heterogeneity within a $\\mathrm{LiCoO}_{2}$ particle that evolves upon cycling at different rates. ACS Energy Lett. 2, 1240–1245 (2017). \n13.\tMacNeil, D. D. & Dahn, J. R. The reactions of $\\mathrm{Li}_{0.5}\\mathrm{CoO}_{2}$ with nonaqueous solvents at elevated temperatures. J. Electrochem. Soc. 149, A912–A919 (2002). \n14.\tDoh, C.-H. et al. Thermal and electrochemical behaviour of $\\mathrm{C/Li}_{\\mathrm{{x}}}\\mathrm{CoO}_{2}$ cell during safety test. J. Power Sources 175, 881–885 (2008). \n15.\tWhittingham, M. S. Lithium batteries and cathode materials. Chem. Rev. 104, 4271–4301 (2004). \n16.\tLiu, Q. et al. Approaching the capacity limit of lithium cobalt oxide in lithium ion batteries via lanthanum and aluminium doping. Nat. Energy 3, 936–943 (2018). \n17.\tLu, Y.-C., Mansour, A. N., Yabuuchi, N. & Shao-Horn, Y. Probing the origin of enhanced stability of ${^{\\mathrm{\\tiny{s}}}\\mathrm{{AlPO}}}_{4}^{\\mathrm{\\tiny{>}}}$ nanoparticle coated $\\mathrm{LiCoO}_{2}$ during cycling to high voltages: combined XRD and XPS studies. Chem. Mater. 21, 4408–4424 (2009). \n18.\tKalluri, S. et al. Feasibility of cathode surface coating technology for high-energy lithium-ion and beyond-lithium-ion batteries. Adv. Mater. 29, 1605807 (2017). \n19.\tWu, N., Zhang, Y., Wei, Y., Liu, H. & Wu, H. Template-engaged synthesis of 1D hierarchical chainlike $\\mathrm{LiCoO}_{2}$ cathode materials with enhanced high-voltage lithium storage capabilities. ACS Appl. Mater. Interfaces 8, 25361–25368 (2016). \n20.\tWang, F. et al. Stabilizing high voltage $\\mathrm{LiCoO}_{2}$ cathode in aqueous electrolyte with interphase-forming additive. Energy Environ. Sci. 9, 3666–3673 (2016). \n21.\t Wang, J., Ji, Y. J., Appathurai, N., Zhou, J. G. & Yang, Y. Nanoscale chemical imaging of the additive effects on the interfaces of high-voltage $\\mathrm{LiCoO}_{2}$ composite electrodes. Chem. Commun. 53, 8581–8584 (2017). \n22.\t Wang, L. L., Chen, B. B., Ma, J., Cui, G. L. & Chen, L. Q. Reviving lithium cobalt oxide-based lithium secondary batteries—toward a higher energy density. Chem. Soc. Rev. 47, 6505–6602 (2018). \n23.\tKoyama, Y., Arai, H., Tanaka, I., Uchimoto, Y. & Ogumi, Z. First principles study of dopant solubility and defect chemistry in $\\mathrm{LiCoO}_{2}$ . J. Mater. Chem. A 2, 11235–11245 (2014). \n24.\tGopukumar, S., Jeong, Y. & Kim, K. B. Synthesis and electrochemical performance of tetravalent doped $\\mathrm{LiCoO}_{2}$ in lithium rechargeable cells. Solid State Ion. 159, 223–232 (2003). \n25.\tTukamoto, H. & West, A. R. Electronic conductivity of $\\mathrm{LiCoO}_{2}$ and its enhancement by magnesium doping. J. Electrochem. Soc. 144, 3164–3168 (1997). \n26.\tZou, M., Yoshio, M., Gopukumar, S. & Yamaki, J. Synthesis of high-voltage (4.5 V) cycling doped $\\mathrm{LiCoO}_{2}$ for use in lithium rechargeable cells. Chem. Mater. 15, 4699–4702 (2003). \n27.\tKim, S. et al. Self-assembly of core-shell structures driven by low doping limit of Ti in $\\mathrm{LiCoO}_{2};$ first-principles thermodynamic and experimental investigation. Phys. Chem. Chem. Phys. 19, 4104–4113 (2017). \n28.\tVan der Ven, A., Aydinol, M. K., Ceder, G., Kresse, G. & Hafner, J. First-principles investigation of phase stability in $\\mathrm{Li}_{x}\\mathrm{CoO}_{2}$ . Phys. Rev. B 58, 2975–2987 (1998). \n29.\t Amatucci, G. G., Tarascon, J. M. & Klein, L. C. $\\mathrm{CoO}_{2},$ the end member of the ${\\mathrm{Li}}_{x}{\\mathrm{CoO}}_{2}$ solid solution. J. Electrochem. Soc. 143, 1114–1123 (1996). \n30.\tReimers, J. N. & Dahn, J. R. Electrochemical and in situ X-ray diffraction studies of lithium intercalation in $\\mathrm{Li}_{x}\\mathrm{CoO}_{2}$ . J. Electrochem. Soc. 139, 2091–2097 (1992). \n31.\tYang, S.-H., Levasseur, S., Weill, F. & Delmas, C. Probing lithium and vacancy ordering in O3 layered ${\\mathrm{Li}}_{x}{\\mathrm{CoO}}_{2}$ $(\\mathbf{x}\\approx0.5)$ : an electron diffraction study. J. Electrochem. Soc. 150, A366–A373 (2003). \n32.\tYang, W. et al. Key electronic states in lithium battery materials probed by soft X-ray spectroscopy. J. Electron Spectros. 190, 64–74 (2013). \n33.\tYoon, W.-S. et al. Oxygen contribution on Li-ion intercalation–deintercalation in $\\mathrm{LiCoO}_{2}$ investigated by O K-edge and Co L-edge X-ray absorption spectroscopy. J. Phys. Chem. B 106, 2526–2532 (2002). \n34.\tKotani, A. & Shin, S. Resonant inelastic X-ray scattering spectra for electrons in solids. Rev. Mod. Phys. 73, 203–246 (2001). \n35.\tYang, W. & Devereaux, T. P. Anionic and cationic redox and interfaces in batteries: advances from soft X-ray absorption spectroscopy to resonant inelastic scattering. J. Power Sources 389, 188–197 (2018). \n36.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n37.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n38.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n39.\tAnisimov, V. I., Zaanen, J. & Andersen, O. K. Band theory and Mott insulators: Hubbard U instead of Stoner I. Phys. Rev. B 44, 943–954 (1991). \n40.\tVladimir, I. A., Aryasetiawan, F. & Lichtenstein, A. I. First-principles calculations of the electronic structure and spectra of strongly correlated systems: the $\\mathrm{LDA}+U$ method. J. Phys. Condens. Matter 9, 767–808 (1997). \n41.\tZhou, F., Cococcioni, M., Marianetti, C. A., Morgan, D. & Ceder, G. First-principles prediction of redox potentials in transition-metal compounds with $\\mathrm{\\LDA}+U.$ . Phys. Rev. B. 70, 235121 (2004). \n42.\tTanaka, S. et al. Atomic and electronic structures of $\\mathrm{Li_{4}T i_{5}O_{12}/L i_{7}T i_{5}O_{12}}$ (001) interfaces by first-principles calculations. J. Mater. Sci. 49, 4032–4037 (2014). \n43.\tMonkhorst, H. J. & Pack, J. D. Special points for Brillouin-zone integrations. Phys. Rev. B 13, 5188–5192 (1976). \n\n# Acknowledgements \n\nThis work was supported by funding from the National Key R&D Program of China (grant number 2016YFB0100100), National Natural Science Foundation of China (grant numbers 51822211, 11564016 and 11574281) and Foundation for Innovative Research Groups of the National Natural Science Foundation of China (grant number 51421002). The work done at BNL was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Vehicle Technology Office of the US Department of Energy through the BMR Program, including the Battery500 Consortium under contract DE-SC0012704. Use of the National Synchrotron Light Source II is supported by the US Department of Energy, an Office of Science user Facility operated by Brookhaven National Laboratory under contract number DE-SC0012704. The SLAC National Accelerator Laboratory is supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under contract number DE-AC02-76SF00515. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under contract number DE-AC02-76SF00515. Soft X-ray spectroscopic data were collected at beamline 8.0.1 of the Advanced Light Source, which is supported by the Director, Office of Science, Office of Basic Energy Sciences of the US Department of Energy under contract number DE-AC02-05CH11231. We gratefully acknowledge help from beamlines BL14W1 and BL08U at Shanghai Synchrotron Radiation Facility. \n\n# Author’s contributions \n\nX.Y. and H.L. conceived the idea; J.-N.Z. synthesized the materials and performed electrochemistry measurements and X-ray diffraction measurements; C.M. performed the TEM measurements and analysis; Y.L., M.G., Xiaojing.H., S.L. and Y.C. performed \n\nthe transmission X-ray microscopy measurement and data analysis; Q.L. and W.Y. \nperformed the soft X-ray spectroscopy experiment and data analysis; C.O. and R.X. \nperformed the density functional theory analysis; Q.L., X.Y., J.-N.Z., Y.L. and C.O. \nwrote the paper with critical inputs from all other authors. All authors edited and approved the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-019-0409-z. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nCorrespondence and requests for materials should be addressed to X.Y., Y.L. or H.L. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 " + }, + { + "id": "10.1016_j.joule.2019.05.006", + "DOI": "10.1016/j.joule.2019.05.006", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2019.05.006", + "Relative Dir Path": "mds/10.1016_j.joule.2019.05.006", + "Article Title": "Enabling High-Voltage Lithium-Metal Batteries under Practical Conditions", + "Authors": "Ren, XD; Zou, LF; Cao, X; Engelhard, MH; Liu, W; Burton, SD; Lee, H; Niu, CJ; Matthews, BE; Zhu, ZH; Wang, CM; Arey, BW; Xiao, J; Liu, J; Zhang, JG; Xu, W", + "Source Title": "JOULE", + "Abstract": "Rechargeable lithium (Li)-metal batteries (LMBs) offer a great opportunity for applications needing high-energy-density battery systems. However, rare progress has been demonstrated so far under practical conditions, including high voltage, high-loading cathode, thin Li anode, and lean electrolyte. Here, in opposition to common wisdom, we report an ether-based localized high-concentration electrolyte that can greatly enhance the stability of a Ni-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) cathode under 4.4 and 4.5 V with an effective protection interphase enriched in LiF. This effect, in combination with the superior Li stability in this electrolyte, enables dramatically improved cycling performances of Li parallel to NMC811 batteries under highly challenging conditions. The LMBs can retain over 80% capacity in 150 stable cycles with extremely limited amounts of the Li anode and electrolyte. The findings in this work point out a very promising strategy to develop practical high-energy LMBs.", + "Times Cited, WoS Core": 728, + "Times Cited, All Databases": 767, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000476463300010", + "Markdown": "# Article Enabling High-Voltage Lithium-Metal Batteries under Practical Conditions \n\n![](images/2e44068aa105ce20cbb8bbed82bf952600afebba06f3d9203afdb7e1f2a03919.jpg) \n\nXiaodi Ren, Lianfeng Zou, Xia Cao, ..., Jun Liu, Ji-Guang Zhang, Wu Xu \n\njiguang.zhang@pnnl.gov (J.-G.Z.) wu.xu@pnnl.gov (W.X.) \n\n# HIGHLIGHTS \n\nEther-based LHCE enables highvoltage (4.5 V) cycling of Li NMC811 cells \n\nEther-LHCE improves Coulombic efficiency and cycling stability of LMAs \n\nEther-LHCE greatly improves LMB performances under practical conditions \n\nInstability of electrolytes toward both highly reactive Li-metal anode and highvoltage cathodes has greatly impeded the development of Li-metal batteries. The authors designed an ether-based localized high-concentration electrolyte that can form stable interphases on both the Li anode and the Ni-rich NMC811 cathode to inhibit the undesired side reactions. This electrolyte enables a significantly enhanced battery performance under stringent practical conditions with a thin Limetal anode or Li-free anode, a high-loading cathode, and lean electrolyte. \n\n# Article Enabling High-Voltage Lithium-Metal Batteries under Practical Conditions \n\nXiaodi Ren,1 Lianfeng Zou,2 Xia Cao,1 Mark H. Engelhard,2 Wen Liu,2 Sarah D. Burton,2 Hongkyung Lee,1 Chaojiang Niu,1 Bethany E. Matthews,1 Zihua Zhu,2 Chongmin Wang,2 Bruce W. Arey,1 Jie Xiao,1 Jun Liu,1 Ji-Guang Zhang,1,\\* and Wu $\\mathsf{X}\\mathsf{u}^{1,3,\\star}$ \n\n# SUMMARY \n\nRechargeable lithium (Li)-metal batteries (LMBs) offer a great opportunity for applications needing high-energy-density battery systems. However, rare progress has been demonstrated so far under practical conditions, including high voltage, high-loading cathode, thin Li anode, and lean electrolyte. Here, in opposition to common wisdom, we report an ether-based localized highconcentration electrolyte that can greatly enhance the stability of a Ni-rich $\\mathsf{L i N i}_{0.8}\\mathsf{M n}_{0.1}\\mathsf{C o}_{0.1}\\mathsf{O}_{2}$ (NMC811) cathode under 4.4 and $4.5\\:\\mathsf{V}$ with an effective protection interphase enriched in LiF. This effect, in combination with the superior Li stability in this electrolyte, enables dramatically improved cycling performances of LijjNMC811 batteries under highly challenging conditions. The LMBs can retain over $80\\%$ capacity in 150 stable cycles with extremely limited amounts of the Li anode and electrolyte. The findings in this work point out a very promising strategy to develop practical high-energy LMBs. \n\n# INTRODUCTION \n\nLithium (Li)-metal batteries (LMBs) have attracted intensive research attentions in recent years as the next-generation high-energy-density battery systems. Compared to the conventional graphite anode whose theoretical specific capacity is only $372m\\mathsf{A h}$ $\\mathfrak{g}^{-1}$ , the Li anode possesses a value more than 10 times higher $(3,862m\\Delta{\\ h}\\ g^{-1})$ . In addition, the Li-metal anode (LMA) has an ultralow electrochemical redox potential $(-3.040\\vee$ versus the standard hydrogen electrode).1–4 One of the most promising approaches to maximize the energy density of LMBs is to couple the LMA with a highvoltage, high-capacity cathode. Recently, significant efforts have been made toward nickel (Ni)-rich $\\mathsf{L i N i_{x}M n_{y}C o_{1-x-y}O_{2}}$ (NMC) cathode materials (for example, NMC811) because of their high specific capacities and low costs with less Co contents.5,6 Nevertheless, the development of such high-voltage LMBs is confronted with tremendous challenges due to the high reactivity of electrolytes with both the Ni-rich NMC cathode and the LMA. As inherited from Li-ion battery systems, organic carbonate electrolytes have been almost exclusively used in high-voltage LMBs because of their oxidative stability $(\\sim4.5\\lor$ versus Li/Li+).7,8 However, increasing Ni content in the cathode can significantly accelerate side reactions with electrolytes because of the highly reactive ${\\mathsf{N i}}^{4+}$ species in the delithiated cathodes, which induce serious cathode capacity decays under high voltages (e.g., $4.4\\mathsf{V}$ and above).9,10 \n\nFurthermore, severe side reactions between Li-metal and carbonate electrolytes would result in low Li Coulombic efficiency (CE) and dendritic Li growth, which can greatly deteriorate the battery performance and impose potential safety hazards.11 Although numerous studies on salts, solvents, or additives were carried out to \n\n# Context & Scale \n\nHigh-energy-density Li-metal batteries are promising nextgeneration energy-storage systems. However, their development is greatly restricted because of the lack of functional electrolytes that can work efficiently on both the reactive Li anode and the aggressive cathodes under practical conditions, where high-voltage, high-loading cathode, thin Li anode and lean electrolyte are all indispensable. Here, we chose ether as the base solvent, which has intrinsic good cathodic but poor anodic stabilities and redesigned the electrolyte in a localized high-concentration electrolyte (LHCE) formulation to build the protective interphases onto both the anode and the cathode, simultaneously. Etherbased LHCE can effectively suppress side reactions, resulting in stable cycling of Li NMC811 cells under voltages up to $4.5\\:\\vee$ and under practical conditions. This electrolyte design provides critical insights for future electrolyte development for practical high-energy-density Limetal batteries. \n\nimprove Li CE in carbonate electrolytes, the goal of a stable Li anode is far from being realized.12–16 The challenges are even more formidable in the highly demanding conditions needed to realize the expected high energy densities of LMBs under practical conditions, where a high-voltage and high-loading cathode, a thin Li anode, and a very limited amount of electrolyte are required at the same time.3,17–19 As seen in Table S1 that summarizes the battery cycling performances of LMBs and ‘‘anode-free’’ LMBs using different electrolytes and under various conditions, the cell performances were significantly impacted even when either one of these restrictions is applied. Namely, when the cathode areal capacity loading is increased, the thickness of the Li anode is reduced, or the electrolyte amount (represented by the ratio of the electrolyte mass to the cell capacity, i.e., E/C) is reduced, the cycle life of the LMB is greatly shortened.20 Therefore, to the best of our knowledge, none of the electrolytes reported so far can work satisfactorily under such harsh conditions. Given the high reactivity issue of carbonate electrolytes with LMA, it would be highly desirable to use ether-based electrolytes, which are known for their good compatibility with Li metal.21,22 However, ethers have been almost excluded from being used in high-voltage batteries because of their anodic instability beyond $4.0\\:\\vee.$ .7,23 While ether-based electrolytes with high salt concentration have been found to have improved oxidation stabilities, apparent capacity decay of the $\\mathsf{L i C o O}_{2}$ cathode was still observed at $4.2\\:\\vee$ .24 Very recently, our group has developed a concentrated dual-salt in ether electrolyte that can form a protective cathode electrolyte interphase (CEI), thus realizing a greatly improved anodic stability of the ether-based electrolyte on the NMC333 cathode under $4.3\\:\\mathsf{V}$ .25 \n\nHowever, the high concentration electrolytes (HCEs) face several challenges in practical applications, such as high viscosity causing difficulties in injection of electrolyte into jelly cells, insufficient wetting of electrolyte to the separator and thick electrodes, poor low-temperature performances, and high cost issues due to the use of large amount of expensive salts, etc.26–28 Most of these issues can be mitigated by adding a cosolvent as a diluent into the HCEs, where the cosolvent is miscible with the major solvent(s) used in HCEs but does not dissociate the salt or coordinate with the salt cations, thus the merits of the HCEs in electrochemical properties can be retained. This new type of electrolyte has been named localized high concentration electrolytes (LHCEs) and reported by our group recently.29–32 Nevertheless, even LHCEs with optimized solvents and additives showed inferior performances under conditions toward practical (e.g., $50~{\\upmu\\mathrm{m}}$ thick Li, $3\\mathsf{m A h\\thinspace c m}^{-2}$ NMC333, and $5.2\\ \\mathfrak{g}$ $\\mathsf{A h}^{-1}$ electrolyte), which is still limited by the intrinsically high reactivity of solvent molecules (e.g., carbonates) toward Li metal.20 In this work, we report the studies of effects of an ether-based HCE and its LHCE counterpart on the LijjNMC811 cells under high voltages. The HCE composed of lithium bis(fluorosulfonyl)imide (LiFSI) and 1,2-dimethoxyethane (DME) at a molar ratio of 1:1.2 can largely improve the cycling stability of LijjNMC811 cells over the conventional carbonate electrolyte, 1 M lithium hexafluorophosphate $(\\mathsf{L i P F}_{6})$ in ethylene carbonate (EC)-ethyl methyl carbonate (EMC) (3:7 by wt.) with 2 wt $\\%$ vinylene carbonate (VC). More importantly, the LHCE, which is formed by adding 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (TTE) as the diluent into the HCE to yield LiFSI-1.2DME-3TTE (in molar ratio), can further greatly improve the stability of the Ni-rich NMC811 cathode under high potentials and also enable highly efficient LMB cycling under highly challenging conditions (e.g., $50\\upmu\\mathrm{m}$ Li, $4.2\\mathsf{m A h c m}^{-2}$ NMC811, and $3\\mathfrak{g}\\left(\\mathsf{A h}\\right)^{-1}$ electrolyte). The best cycling performances so far via the electrolyte design are demonstrated under such demanding conditions in LMBs. This study points out a very encouraging electrolyte design strategy and highlights the benefits of using ether-based electrolytes for future high-energy-density LMB applications. \n\n![](images/7d3e6ada7555c8cc296d051d6c13729d266a3278792aa97289d35e4dbc100908.jpg) \nFigure 1. Cycling Performances of LijjNMC811 Batteries in Different Electrolytes Conventional electrolyte $(1\\mathsf{M L i P F}_{6}$ in EC-EMC (3:7 by wt.) with 2 wt $\\%$ of VC); dilute electrolyte (LiFSI-9DME); HCE (LiFSI-1.2DME); and LHCE (LiFSI-1.2DME-3TTE) under the charge cutoff voltage of $4.4\\:\\forall$ (A) and $4.5\\:\\vee$ (B), respectively. The electrolyte amount in each coin cell is $75~\\upmu L$ . \n\n# RESULTS AND DISCUSSION \n\n# The Cathode-Electrolyte Interface \n\nTo evaluate the compatibility of the ether-based HCE (LiFSI-1.2DME) and LHCE (LiFSI-1.2DME-3TTE) with the NMC811 cathode, Li NMC811 cells with a mediumhigh cathode areal loading of $1.5\\mathsf{m A h c m}^{-2}$ , a thick $(450\\upmu\\mathrm{m})$ Li anode, and an excess electrolyte $(75\\upmu|)$ were first assembled and cycled under high voltages. As shown in Figure 1A where the LijjNMC811 cells were charged to $4.4\\mathsf{V}.$ the NMC811 cathode in the conventional $\\mathsf{L i P F}_{6}$ in carbonate electrolyte showed a continuous capacity fading, with only ${\\sim}68\\%$ of the initial capacity left after 250 cycles. Significantly enlarged cell overpotentials were also observed upon cycling (Figure S1A). The cell capacity in the dilute LiFSI-9DME electrolyte also decayed fast, and by only 94 cycles the capacity retention dropped to ${\\sim}87\\%$ and the cell polarization increased apparently (Figure S1B). This is because of the oxidation of the free DME ether molecules at voltages over $4.0\\vee$ .23 The cell cycling stability was much improved in the HCE, where the capacity retention was improved to about $76\\%$ after 250 cycles with reduced cell overpotentials (Figure S1C). The successful usage of the etherbased HCE can be attributed to the effect of the high salt/ether ratio, which decreases the population of free ether molecules as well as their highest occupied molecular orbital (HOMO) energy level through electron donation to ${\\mathsf{L i}}^{+}$ .24,25 The improved anodic stability of ether-based electrolytes can be verified using linear scanning voltammetry (LSV) on the SP-PVDF electrode (Super P carbon: ${\\mathsf{P V D F}}=$ 1:1, in weight ratio). With the high salt/ether ratio, the oxidation current was largely diminished until ${\\sim}4.5\\lor$ (Figure S2). In addition, the synergistic effect between the LiFSI salt and the DME solvent plays an important role in stabilizing the highly reactive NMC811 cathode, as reported in our recent work.33 A further enhanced cycling performance was achieved in the ether-based LHCE with ${\\sim}87\\%$ capacity retention \n\n# Joule \n\nafter 300 cycles $90\\%$ after 250 cycles) along with very limited cell overpotential changes (Figure S1D). \n\nX-ray diffraction (XRD) analysis shows no apparent bulk structural degradation in the cycled cathodes (Figure S3). This is consistent with previous reports that the electrolyte instability on highly active Ni-rich cathodes plays an important role in the capacity fading.9,10,34,35 Furthermore, parasitic electrolyte reactions under high voltages are closely related to CEI formation, surface reconstruction, oxygen loss etc., which could also contribute to the cathode decay.36 With excess Li in the anode, the cell CEs are indicating the electrolyte stability on the cathode. Interestingly, the variation in the cycling performance is following the same trend as the cell CEs in different electrolytes: $97.88\\%$ in the dilute ether electrolyte, $98.79\\%$ in the conventional carbonate electrolyte, $99.68\\%$ in the HCE, and $99.77\\%$ in the LHCE (Figure S4). Because of the poor anodic stability of the dilute LiFSI-9DME electrolyte at high voltages, it was not studied further in electrochemical cells. \n\nAs shown in Figure 1B, even at a cutoff voltage of $4.5\\mathsf{V}.$ , the LHCE could still lead to greatly improved cycling stability compared to the conventional electrolyte and the HCE, holding over $82\\%$ of the initial capacity after 250 cycles (only $\\sim53\\%$ for the conventional electrolyte). It should be noted that in the HCE, a faster capacity fading was observed along with a decreasing cell CE before the Li anode failure, as indicated by the recovery of the decay trend after Li anode replacement. The cell still has plenty of electrolyte left after $\\mathord{\\sim}120$ cycles (Figure S5). Therefore, it is likely that the accelerated side reactions of this HCE on the NMC811 cathode at $4.5\\:\\vee$ would generate more side products, which could seriously deteriorate the Li anode after crossover. Decreasing the charge cutoff voltage can improve the cycling stability but the cell capacity will be compromised, as shown in Figure S6 and recent reports.9 \n\nIn addition to the improved long-term cycling performance, the LHCE also brings other favorable physical properties. While the ionic conductivity was decreased from 4.18 to $2.44\\mathsf{m}\\mathsf{S}\\mathsf{c m}^{-1}$ after adding TTE because of a much lower ${\\mathsf{L i}}^{+}$ concentration (4.4 M versus $1.5\\mathsf{M}$ ), the electrolyte viscosity was dramatically decreased from 48 to $4.8\\mathsf{c P}$ (Table S2). Furthermore, the wettability of the LHCE is much better when compared to that of the HCE (Figure S7). Those improved electrolyte physical properties as well as the reduced cost are highly beneficial to practical applications, as indicated by the better battery capacities at high rates (e.g., 6C or ${\\sim}9\\ m\\mathsf{A c m}^{-2}$ current density) shown in Figure S8. \n\n$^{17}\\mathrm{O}$ -nuclear magnetic resonance (NMR) was used to study the electrolyte solvation structures in the dilute electrolyte, the HCE, and the LHCE. As shown in Figure 2A, when increasing the LiFSI/DME molar ratio from 1:9 to 1:1.2, the chemical shift of sulfonyl oxygen decreases from 171.6 to 163.7 ppm, which indicates the increased ion-dipole interactions between $\\mathsf{F S l^{-}}$ and ${\\mathsf{L i}}^{+}$ in the HCE. Meanwhile, the ethereal oxygen signal also moves to lower chemical shifts as the concentration increases, the same as reported before.37 This upfield shift is possibly related to the fact that $\\mathsf{F S l^{-}}$ anions are replacing DME molecules in the ${\\mathsf{L i}}^{+}$ solvation sheath as a high LiFSI/DME molar ratio (1:1.2) is reached, which induces a shield effect on ethereal oxygen atoms. The broadening of those signals is likely due to the complicated solvation structures, for example, contact ion pairs or cation-anion aggregates (scheme in Figure 2B).38 With the addition of TTE diluent, chemical shifts of the ethereal oxygen atoms further decrease, while the oxygen signals from both the sulfonyl and the TTE show negligible changes. This proves the TTE diluent will not interrupt the intimate interactions between $\\mathsf{F S l^{-}}$ and ${\\mathsf{L i}}^{+}$ in the HCE. Instead, more $\\mathsf{F S l^{-}}$ anions are entering the inner ${\\mathsf{L i}}^{+}$ solvation shell in the LHCE, which may be related to the differences in affinities between DME and $\\mathsf{F S l^{-}}$ anions with TTE molecules outside the solvation sheath (Figure 2C). This has further implications regarding the electrolyte reactivity, which will be discussed later. \n\n![](images/254540a0a1c82202bc2d162f1fe2253a485673bf829961eb5fbfb8727bc54f1d.jpg) \nFigure 2. Electrolyte Solvation Structures (A) $^{17}\\mathrm{O}$ -NMR spectra of different solvents and electrolytes. (B) The scheme of the solvation structure in the HCE (LiFSI-1.2DME). (C) The scheme of the solvation structure in the LHCE (LiFSI-1.2DME-3TTE). \n\nIn order to understand the suppressed side reactions and the boosted cycling stability of the LHCE over the HCE, the cycled cathodes were characterized by annular bright-field scanning transmission electron microscopy (ABF-STEM). As seen from Figures 3A–3C, an apparent CEI layer on the primary NMC811 particle was found after 50 cycles in the HCE with a thickness ranging from 3 to $5\\mathsf{n m}$ . This CEI shows a partially crystalline feature, where the crystalline domain is likely to be LiF with a d-spacing of ${\\sim}0.20~\\mathsf{n m}$ . In the LHCE, a similar crystalline phase was observed in the CEI layer but with a higher crystallinity and an overall thinner thickness. LiF is known to have a wide band gap $(13.6\\mathsf{e V})$ and a high oxidative stability (6.4 V versus ${\\mathsf{L i}}/{\\mathsf{L i}}^{+};$ ).39 Therefore, the LiF-enriched CEI layers could be highly valuable for inhibiting the side reactions between the active cathode surface and the ether electrolytes. Indeed, only limited ${\\mathsf{L i}}^{+}/{\\mathsf{N i}}^{2+}$ cation mixings were found underneath the CEIs after cycling from the high-angle annular dark-field (HAADF)-STEM images (Figure S9). \n\nX-ray photoelectron spectroscopy (XPS) analysis was carried out on the cycled cathodes to further investigate the interfacial chemistries between the NMC811 cathode and different electrolytes. Compared to the pristine NMC811, the surface of the cathode cycled in HCE shows greatly decreased signals from the conductive carbon (C-C and/or C-H, $284.8~\\mathrm{eV}$ , C 1s), the PVDF binder ${\\mathrm{CF}}_{2}{\\mathrm{-CH}}_{2},$ $286.9\\:\\mathrm{eV}.$ , C 1s; C-F, $290.6\\mathsf{e V}$ , C 1s or $687.7\\mathrm{eV}.$ , F 1s), and the M-O species $\\mathord{\\sim}529.5\\mathrm{eV}$ , O 1s) (Figure 3). Instead, the major species seems to be LiF (F 1s at $685.7\\:\\mathrm{eV})$ with each atomic ratio over $40\\%$ for Li and F through the depth profiling (Figure S10), which agrees with the Transmission electron microscopy (TEM) result. There are also apparent signals of S$\\mathsf{O}_{\\mathsf{x}}(170.1\\mathsf{e V},\\mathsf{S}2\\mathsf{p})$ and ${\\mathsf{N}}{\\mathsf{-}}{\\mathsf{O}}_{\\mathsf{x}}$ $\\mathsf{O}_{\\mathsf{x}}(400.7\\mathsf{e V},$ N 1s) species from salt anion decomposition (Figure S11). Interestingly, the atomic ratio of C on the NMC811 increases considerably after cycling in the LHCE, compared to that in the HCE (Figure S10C). In addition, more apparent signal of C-F species (Figure 3I) was observed. Such differences suggest the fluorinated ether diluent, TTE, participated in the CEI formation on the NMC811. According to the result from the time-of-flight secondary ion mass spectroscopy (ToF-SIMS) depth profiling on NMC811 cathodes after cycling in electrolytes with deuterium-labeled DME $(^{2}\\mathsf{H}$ -DME), the high $^2{\\mathsf{H}}/{}^{1}{\\mathsf{H}}$ atomic ratio in HCE with $^2\\mathsf{H}$ -DME proves the significant role of DME decomposition during the CEI formation process in the HCE ( $\\mathsf{\\Pi}^{1}\\mathsf{H}$ from PVDF binder) (Figure 3M). Nevertheless, the $^2{\\mathsf{H}}/{}^{1}{\\mathsf{H}}$ atomic ratio greatly decreased in the LHCE, which suggests the DME decomposition is inhibited. This may imply a major change in the CEI formation mechanism (Figure 3N), which can be explained as below. In the HCE, the formation of LiF-enriched CEI relies on the $\\mathsf{F S l^{-}}$ anion and the process is most likely induced by the intermediators from DME decomposition. The slight M-O signal (Figure 3K) \n\n![](images/4b4da87b08ec0fa78a05cdc09e0f5c5d7d2be8a585d85acd204992a2010a7cd9.jpg) \n(A–C) ABF-STEM images, (D–F) C 1s, (G–I) F 1s, and (J–L) O 1s XPS spectra of the pristine NMC811 (A, D, G, and J) as well as cathodes after 50 cycles at $4.4\\:\\forall$ in the HCE (B, E, H, and K) and the LHCE (C, F, I, and L). (M) ToF-SIMS depth profiling of cycled NMC811 cathodes in the HCE and the LHCE with or without $^2{\\mathsf{H}}$ isotope-labeled DME. (N) the proposed scheme of the CEI formation mechanism in the LHCE. \n\n![](images/32a46110e8c7817ddd114ce681fafa60b9c3d7f7c95ba98fa2a8b26becbab8fc.jpg) \nFigure 4. Li-Metal CE and Deposition Morphologies in Different Electrolytes \n(A) Stability of Li CEs with cycling measured in LijjCu cells with different electrolytes. (B–G) The SEM top-view (B, D, F) and cross-sectional view (C, E, G) images of deposited Li films (0.5 and $4\\mathsf{m A h c m}^{-2}$ ) in different electrolytes: conventional electrolyte (1 M LiPF6 in EC-EMC (3:7 by wt.) with 2 wt $\\%$ of VC) (B and C), HCE (LiFSI-1.2DME) (D and E), and LHCE (LiFSI-1.2DME-3TTE) (E and $\\mathsf{G}$ ). \n\nprobably indicated the dissolution of transition metal ions during the initial CEI formation process. In contrast, instead of being an ‘‘inert’’ diluent, the fluorinated ether in LHCE can have a significant contribution in the formation of the CEI, which in turn suppresses DME decomposition in the LHCE and reduces the amount of corrosive acidic side products. This effect is evidenced by the greatly improved cathode stability over long-term cycling. \n\n# The Li Anode-Electrolyte Interface \n\nBesides the electrolyte stability on the high-voltage cathode, the LMB cycling stability also depends heavily on the stability of the LMA. Otherwise, low Li CE or dendritic \n\n# Joule \n\nLi growth would easily lead to LMB failures. Therefore, the Li CEs in different electrolytes over cycling were measured in Li Cu cells $75~\\upmu L$ electrolyte in each cell). As shown in Figure 4A, the Li CE in the conventional carbonate electrolyte dropped to below $50\\%$ in just a few cycles, averaging ${\\sim}44\\%$ in the first 40 cycles. In addition, the voltage hysteresis kept increasing upon deposition-stripping cycles (Figure S12). This fully denotes the high reactivity of conventional carbonate electrolytes with Li metal and the influence of side products accumulation on the cell internal resistance. When HCE is used, however, a dramatically improved Li CE was observed, with an average $C E>99.1\\%$ over 220 cycles, along with stable voltage profiles during cycling. Unfortunately, Li CE fluctuations were more likely found toward longer cycling. Despite the side reactions between the HCE and the deposited Li metal being suppressed, the build-up of the porous surface layer on Cu could still raise increasing difficulties of uniform mass transport across, which induces non-uniform Li deposition-stripping processes. Importantly, such fluctuations can be largely mitigated over extended cycles (over 300 cycles) when the LHCE is used while the average Li CE can be further improved to $>99.3\\%$ . It indicates that compared to the HCE, the LHCE with lower viscosity and better wettability can not only induce more uniform Li deposition and stripping but also further minimize the side reactions between Li metal and the electrolyte. \n\nTo further verify the Li metal growth behavior in these electrolytes, Li metal films with a high capacity of $4\\mathsf{m A h}\\mathsf{c m}^{-2}$ were electrodeposited for post analysis. The optical images of the Li-metal films are shown in the insets of Figure 4. In the conventional carbonate electrolyte, a non-uniform film with gray color was obtained, which suggests extensive side reactions between the electrolyte and Li metal. On the contrary, quite uniform Li-metal films with similar color to the pristine Li metal were deposited in both the HCE and LHCE, which indicates the greatly improved Li-metal stability in these two electrolytes. Scanning electron microscopy (SEM) characterizations also confirm that in sharp contrast to the dendritic Li growth in the conventional electrolyte, large Li deposits were formed in the HCE and LHCE (Figures 4B, 4D and 4F). The cross-section image of the Li film in the LHCE shows a thickness of $32\\upmu\\mathrm{m}.$ , indicating an apparently denser and more uniform Li deposition than those in the conventional electrolyte $(45~{\\upmu\\up m})$ or the HCE $(40~\\upmu\\mathrm{m})$ ). This observation is in agreement with the variation of the Li CEs, considering that Li films with a higher surface area would induce more side reactions with the electrolyte thus a lower CE. \n\nFurthermore, the chemical compositions in the solid electrolyte interphase (SEI) layers on LMAs of LijjNMC cells were characterized by XPS after cycling in different electrolytes. As summarized in Figure S13, the Li SEI components in the conventional carbonate electrolyte are significantly different from those in the HCE and the LHCE because of the involvement of different anions in the conventional carbonate electrolytes from the ether-based HCE and LHCE. This is consistent with our previous studies on HCEs, where salt anions instead of solvent molecules would preferably react with Li metal and form the passivating SEI layers.30,40 As suggested by the high atomic ratios of C and F through ${\\mathsf{A}}{\\mathsf{r}}^{+}$ depth profiling (Figure 5A), the Li anode has serious side reactions with the carbonate solvent molecules and the $\\mathsf{L i P F}_{6}$ salt. The greatly decreased C content in the HCE implies that the SEI layer derived mainly from $\\mathsf{F S l^{-}}$ anions can effectively inhibit further side reactions with the solvent. From the HCE to the LHCE, the increase of the F atomic ratios was accompanied by the decrease of the C atomic ratios, resulting in an apparent rise of the F/C ratio (Figures 5B, 5C, and S14). This effect along with the nitride signal $\\mathrm{i}_{\\times}\\mathsf{N},396\\mathrm{eV},$ N 1s) may suggest the improved SEI passivating ability from more complete $\\mathsf{F S l^{-}}$ sacrificial decomposition (Figure S13). Therefore, besides reducing concentrations of reactive species on the Li anode surface, the F-ether diluent may further promote the reactions between $\\mathsf{F S l^{-}}$ and Li metal to suppress side reactions with the solvent molecules, which is consistent with recent calculations that the lowest unoccupied molecular orbital (LUMO) shifts more to the $\\mathsf{F S l^{-}}$ in the LHCE.30 This also agrees with the previous observation in the $^{17}\\mathrm{O}$ -NMR that there are more $\\mathsf{F S l^{-}}$ anions in the ${\\mathsf{L i}}^{+}$ solvation sheath in the LHCE than those in the HCE. As pointed out in recent studies,41,42 manipulating the components and structure of the solvation sheath is of significant importance for controlling the competitive reactions of the salt anions, solvent molecules, and other components at the interface, which in turn prominently influence the SEI composition and electrode stability. At the same time, obviously lower Mn $2\\mathsf{p}$ signal can be seen on the Li anode cycled in the LHCE compared to those in the conventional electrolyte and the HCE, again proving the LHCE can enable a better cathode stability (Figure S15). \n\n![](images/e95323991689f655aaa3acddde8a5a8036d095ef82847fd9192545fff11ef1ff.jpg) \nFigure 5. Characterizations of the Cycled Li Anodes in Different Electrolytes \n(A–C) XPS depth profiling of Li anodes after 50 cycles in Li NMC811 cells. (D–F) SEM images of Li anode after cycling in LijjNMC811 cells: 250 cycles in the conventional electrolyte $.1M L i P F_{6}$ in EC-EMC (3:7 by wt.) with 2 wt % of VC) (A and D), 250 cycles in the HCE (LiFSI-1.2DME) (B and E), and 300 cycles in the LHCE (LiFSI-1.2DME-3TTE) (C and F). \n\nIt should be pointed out that although the XPS, ToF-SIMS, and other characterization techniques can tell us the components and compositions of the SEI and CEI films, these results cannot completely explain the differences in the battery performances by using different electrolytes. It is also worth noting that the LHCE could also be helpful to inhibit the galvanic Li corrosion on a heterogeneous conductive surface (Cu foil or stainless-steel coin-cell parts on the anode part), an important Li-loss mechanism revealed recently.43,44 It is possible that the LHCE can induce a similar passivation layer enriched in F species as the SEI on Li metal onto the conductive surface (equipotential as Li), which is beneficial for suppressing the galvanic Li corrosion. In addition, the decreased populations of the active components (e.g., $\\mathsf{F S l^{-}}$ and DME) because of the TTE dilution could also suppress further Li corrosion via the galvanic mechanism. \n\n# Joule \n\nInterestingly, largely different Li anode morphologies were observed after longterm cycling of Li NMC cells in different electrolytes, especially for the LHCE (Figures 5D–5F). Compared to the uneven SEI layer accumulated in the conventional electrolyte, the HCE induced an SEI with a much better uniformity. Furthermore, the Li anode morphology underwent a major change in the LHCE, where a more uniform and integrated surface instead of accumulated small particles as in the HCE was observed. Such a Li anode morphology is highly desirable for LMAs, as it could be very beneficial for accommodating Li-metal volume changes during deposition and stripping as well as protecting against electrolyte attack. \n\n# Li-Metal Batteries under Practical Conditions \n\nThose highly important merits brought by the LHCE can be best signified when testing LMBs under highly challenging conditions required by practical applications. Currently, the majority of studies on LMBs uses either a thick Li anode, a low-loading cathode, or an excess amount of electrolyte. Very rarely has success been demonstrated under practical conditions, as a high-loading cathode would not only lead to a much larger Li volume change but also need a high charge-discharge current density at a specified C rate, which are well-known to induce fast Li anode and electrolyte depletion. In this work, we combine a thin Li anode (nominal thickness $50\\upmu\\mathrm{m})$ , a high-loading cathode $(4.2\\mathsf{m A h c m}^{-2})$ ), and an extremely limited amount of electrolyte (E/C ratio of $3\\mathfrak{g}\\left(\\mathsf{A h}\\right)^{-1}$ or ${\\sim}14\\upmu\\up L$ in each coin cell), in order to reliably evaluate the battery performance under conditions relevant to practical applications. Based on the masses of cell components (electrode materials, current collectors, separator, and electrolyte, excluding the coin-cell parts), the coin-cell type LMB had an estimated gravimetric energy density of 325 Wh $\\mathsf{k g}^{-1}$ (Table S3). It should be noted that when using these parameters to make real cells with light pouch bags and double-sided electrodes, the relative weight of the inactive materials will be largely reduced thus may give a specific energy higher than 325 Wh $\\mathsf{k g}^{-1}$ obtained from the coin cells. \n\nSuch testing conditions were found to be extremely demanding for the conventional carbonate electrolyte. As shown in Figure 6A, the cell using the conventional electrolyte could only run 6 cycles at C/3 (i.e., $1.4\\:\\mathrm{mA}\\:\\mathrm{cm}^{-2}.$ ) charge and discharge rates before a very quick battery failure due to severe side reactions between the electrolyte and Li anode. With the better Li stability in the HCE, the cell showed a greatly improved cycling stability, retaining $80\\%$ of initial capacity after 102 cycles (cell CE data shown in Figure S16). However, occasional battery capacity fluctuations were observed during cycling, which is probably related to the insufficient wetting of the electrolyte through the accumulated anode SEI layer as well as the non-uniform pressure on the Li anode (detailed cell voltage changes and analysis of abnormal behavior can be found in Figures S17–S20). The cell cycling stability could be significantly improved when the LHCE is used, where $80\\%$ capacity was maintained after 155 cycles. In addition, the LHCE greatly enhanced the cycling stability during cycling with suppressed side reactions, reduced electrolyte viscosity, and improved wettability. To the best of our knowledge, this is the first time that a long-stability, high-voltage (4.4 V) LMB with a pristine Li anode is demonstrated under such practical testing conditions. After cycling, there was still nearly half of the Li metal left $(4.77\\ m A\\ h\\ c m^{-2}$ , estimated Li consumption: $4.63\\ m A h\\ c m^{-2})$ in the anode but the electrolyte was almost fully consumed (Figure S21). The minimum amount of electrolyte to wet the pores inside the cathode and the separator is $\\sim5\\upmu\\up L$ (detailed calculation in notes for Table S3). Considering the surfaces and open space inside the coin-cell case, the ‘‘extra’’ electrolyte volume should be much less than $9\\upmu\\up L$ . In comparison, most LMB studies are using close to $100\\upmu\\up L$ or even more electrolyte in the similar coin cells. It is even more challenging for the LHCE case, as less than $30\\%$ of solvent molecules in the LHCE (1.2 DME versus 3 TTE) are able to transport ions during battery cycling. \n\n![](images/76ee8c3441b47939f2a5db3e4dce2a3ed0bca4f36484982def8e56690f9489dd.jpg) \nFigure 6. Electrochemical Behavior of Li NMC811 Batteries under Practical Conditions (A) Cycling performances of Li NMC811 cells in different electrolytes with a $50~{\\upmu\\mathrm{m}}$ Li anode, $4.2\\ m A\\ h\\ c m^{-2}$ NMC811 cathode, and lean electrolyte at $14\\upmu\\up L$ . (B) Cycling performances of Cu NMC811 cells in different electrolytes with a bare Cu as the anode, 4.2 mAh $\\mathsf{c m}^{-2}$ NMC811 cathode, and lean electrolyte at $14\\upmu\\up L$ . \n\nMore impressively, even in the ‘‘anode-free’’ cells with energy densities over 400 Wh $\\mathsf{k g}^{-1}$ and no Li metal in the anode before cycling (Table S3), the LHCE can still show a remarkable cycling performance. A record-high capacity retention of $77\\%$ was achieved in the LHCE after 70 cycles under highly demanding conditions (Figure 6B), while only 25 cycles with the same capacity retention were achieved in the HCE. As compared to the reported battery performances in the literature in Table S1, the results obtained in this work by using the ether-based LHCE exhibit the best battery performance up to date under practical conditions and prove that such an ether-based LHCE is highly promising for high-energy-density LMBs. \n\n# Conclusions \n\nWe have demonstrated that the ether-based LHCE exhibits a broad electrochemical stability window. It could significantly enhance the stabilities of both the NMC811 cathode at high voltages and the reactive LMA at a low voltage, thus enabling greatly improved cycling performances under highly demanding conditions required by practical applications. The addition of the fluorinated ether diluent not only endows favorable properties with respect to viscosity, wettability, and cost but also enables highly effective interphases on the cathode and anode to suppress undesirable side reactions. With the ether-based LHCE (LiFSI-1.2DME-3TTE), the LMBs with LijjNMC811 chemistry tested in coin-cell configuration under a highly \n\n# Joule \n\nstringent condition of high-voltage, high-loading cathode, thin Li anode, and lean electrolyte exhibit a high specific energy of 325 Wh $\\mathsf{k g}^{-1}$ when all cell components except for the coin-cell kits are counted. This battery has demonstrated a capacity retention of $80\\%$ in 155 cycles. Furthermore, when a pure Cu foil is used to replace the Li-on-Cu anode in the above cell, i.e., to make an ‘‘anode-free’’ cell, a specific energy of 412 Wh $\\mathsf{k g}^{-1}$ can be obtained. Both the LMB and ‘‘anode-free’’ cell using the ether-based LHCE exhibit greatly enhanced cycling performances of Li NMC811 batteries compared to the cells with the HCE (LiFSI-1.2DME). The crucial findings of this study highlight the importance of electrode-electrolyte chemistries and the criteria for designing an electrolyte to enable the employment of long-life high-energy-density LMBs. \n\n# EXPERIMENTAL PROCEDURES \n\n# Materials \n\nLi-metal chips (diameter: $1.55~\\mathrm{cm}$ ) of $450~{\\upmu\\mathrm{m}}$ thickness were purchased from MTI Corporation and $50\\upmu\\mathrm{m}$ thick Li-metal foil (on Cu foil) was ordered from China Energy Lithium. NMC811 cathode material (SNMC-03008) was obtained from Targray (Canada). The cathode laminates were prepared by slurry coating using N-methyl2-pyrrolidone (NMP) as the solvent at the Advanced Battery Facility, Pacific Northwest National Laboratory (PNNL). The slurry contained NMC811 material, conductive carbon (C-NERGY Super P C65, Timcal), and PVDF binder (Kureha L#1120) with a weight ratio of 96:2:2. The slurry containing only Super P and PVDF (1:1 wt) was also coated for LSV tests. Cathode disks of $^1/_{2}$ inch $(1.27\\mathrm{cm})$ ) diameter were punched out and further dried at $80^{\\circ}\\mathsf{C}$ under vacuum before use. The cathode loadings used in this study were either 1.5 or $4.2m\\mathsf{A h\\ c m}^{-2}$ . The cathode material was stored inside the glovebox and the slurry coating was conducted in a dry room with a dew point of $-60^{\\circ}\\mathsf C$ to minimize the influence of ambient moisture on the cathode material. Battery grade LiFSI was kindly provided by Nippon Shokubai (Japan) and further dried at $120^{\\circ}\\mathsf C$ under vacuum for $24\\mathsf{h}$ before use. Battery grade DME, EC, EMC, dimethyl carbonate (DMC), VC, and $\\mathsf{L i P F}_{6}$ were purchased from BASF and used as received. TTE, $99\\%$ was ordered from SynQuest Laboratories and dried with molecular sieves before use. $^2{\\mathsf{H}}$ isotope labeled DME $99\\%$ atom $\\%$ $^2\\mathsf{H})$ was ordered from Cambridge Isotope Laboratory and dried with molecular sieves before use. \n\n# Electrochemical Tests \n\nCR2032 coin-cell kits were purchased from MTI Corporation. Coin cells were assembled inside an Argon-fill glovebox (MBraun, with $H_{2}O<1$ ppm, $\\mathsf{O}_{2}<1\\mathsf{p p m})$ for the electrochemical tests. For LijjCu cells, a Li chip, a piece of polyethylene (PE) separator (Asahi Kasei), and a piece of Cu foil (2.11 cm diameter) were stacked together. For Li NMC cells, the Li chip, PE separator, and NMC cathode disk were assembled. For LijjSP-PVDF cells, the NMC disk was replaced by an SP-PVDF disk. To avoid the corrosion of the stainless-steel positive cases by the electrolytes, Al-clad cathode cases were used for high-voltage battery tests and an additional piece of Al foil (2.11 cm diameter) was placed underneath the cathode disk. $75~\\upmu L$ of electrolyte was added in each coin cell if not specified. For the high-loading cathode and lean electrolyte tests under extreme conditions, $14\\upmu\\up L$ of electrolyte was added in each coin cell to maximize the specific energy of the cell, which corresponded to an electrolyte/cathode capacity ratio of $3\\mathfrak{g}\\left(\\mathsf{A h}\\right)^{-1}$ . The diameter of the thin Li anode used was 1/2 inch (i.e., $1.27\\mathrm{cm})$ ), the same as the cathode. Galvanostatic cycling tests were conducted within a voltage window of 2.8–4.4 V or 2.8–4.5 V using Land battery testers (Wuhan Land, China) inside a temperature chamber (TestEquity) at $25^{\\circ}\\mathsf{C}$ . After two formation cycles at $\\mathsf{C}/10$ rates ( ${1}\\mathsf{C}=200\\mathsf{m A h}\\ \\mathsf{g}^{-1};$ , the LijjNMC cells were charged to $4.4\\mathsf{V}$ or $4.5\\mathsf{V}$ at C/3 and held at $4.4\\lor$ or $4.5\\mathsf{V}$ until the anodic current dropped below C/20 before discharged to $2.8\\vee$ at $C/3$ . A rest step of $20~\\mathrm{{min}}$ was added after each charge/discharge process under lean electrolyte conditions. For Li-CE measurements in LijjCu cells, a fixed amount of Li metal (areal capacity of $1.0\\mathsf{m A h c m}^{-2})$ was electrodeposited onto the bare Cu substrate at a current density of $0.5\\mathsf{m A c m}^{-2}$ , and then fully stripped until a cutoff voltage of 1 V in each cycle. The ratio between the stripped capacity and the deposited capacity is the Li CE of the specific cycle, indicating the amount of electrochemically active Li metal. \n\n# Characterizations \n\nThe liquid state $^{17}\\mathrm{O}$ -NMR spectra were collected on a 500 MHz Varian NMC Inova spectrometer at $60^{\\circ}\\mathsf{C}$ . For sample post analyses, the coin cells after cycling were disassembled inside the glovebox and rinsed several times by anhydrous DME $(^{2}\\mathsf{H}$ -DME for the isotope-labeled electrolyte) or DMC solvent to remove residual electrolytes before being dried under vacuum. For XPS studies, the samples were transferred in air-tight vessels and loaded into the test chamber without exposure to the ambient air. The spectra were collected on a Physical Electronic Quantera scanning $\\mathsf{X}$ -ray microprobe with a focused monochromatic Al $\\mathsf{K}\\alpha\\times$ -ray source. The sputter rate of Argon ion depth profiling $(2\\mathsf{k V},0.5\\mathsf{\\upmu A},$ and $45^{\\circ}$ incident angel) was calibrated for $\\mathsf{S i O}_{2}$ to be $6.1\\ \\mathrm{nm/min}$ . To minimize the interferences between different XPS signals (e.g., Ni $2\\mathsf{p}$ and F KLL Auger peaks, Mn 2p and Ni LNM Auger peaks, as well as $\\mathsf{C o2p}$ and Mn 2s peaks), Ni $3\\mathsf{p}$ signal was selected for quantification to represent the amount of transition metal ions. XRD patterns were obtained on a Rigaku MiniFlex II XRD instrument $\\operatorname{Cu}\\ K\\alpha$ radiation, $30~\\mathsf{k V}.$ , $15~\\mathsf{m A}.$ , and scan rate $0.3^{\\circ}$ per min). SEM characterizations were carried out on a FEI Helios DualBeam focused ion-beam (FIB) SEM at $5{-}15~{\\mathsf{k V}}.$ . TEM specimen preparation by FIB lift out was carried out on the Helios F ${\\mathsf{I B-S E M}}.2.2\\ {\\upmu\\mathrm{m}}$ thick Pt layer $200~\\mathsf{n m}$ e-beam deposition followed by $1~{\\upmu\\mathrm{m}}$ ion-beam deposition) was firstly deposited on the particles to be lifted out to avoid Ga-ion-beam damage. Afterward, the specimen was thinned to electron transparency using $30~\\mathsf{k V}$ Ga-ion beam. A final polishing using $2~{\\mathsf{k V}}$ Ga ion was performed to reduce the surface damage layer. After a $2~{\\mathsf{k V}}$ Ga ion polish, the surface damage layer was believed to be less than $4\\:\\mathsf{n m}$ . The FIB-prepared NMC samples were characterized using a JEOL JEM-ARM200CF microscope at $200~\\mathsf{k V}$ . This microscope is equipped with a probe spherical-aberration corrector for imaging at sub-a˚ ngstr ¨om resolution. The electron signals from 68 to 280 mrad were collected for HAADF-STEM imaging. Imaging parameters were tuned to minimize the influence on the samples. No apparent changes were observed before and after imaging. ToF-SIMS depth profiling experiments were carried out on the TOF.SIMS5 instrument (IONTOF GmbH, Mu¨ nster, Germany) with a $2000\\mathrm{~eV~Cs^{+}}$ ion beam. \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information can be found online at https://doi.org/10.1016/j.joule. \n2019.05.006. \n\n# ACKNOWLEDGMENTS \n\nThis work has been supported by the assistant secretary for Energy Efficiency and Renewable Energy, Vehicle Technologies Office of the US Department of Energy (DOE) through the Advanced Battery Materials Research (BMR) program (Battery500 Consortium) under the contract no. DE-AC02-05CH11231. The microscopic and spectroscopic characterizations were conducted in the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL), a national scientific user facility \n\n# Joule \n\nsponsored by DOE’s Office of Biological and Environmental Research and located at PNNL. PNNL is operated by Battelle for the DOE under contract DE-AC05- 76RLO1830. The salt LiFSI was provided by Dr. Kazuhiko Murata of Nippon Shokubai. \n\n# AUTHOR CONTRIBUTIONS \n\nW.X., X.R., and J.-G.Z. conceived the idea and designed the experiments. X.R. performed the electrochemical measurements, XRD, and SEM characterizations with help from X.C. L.Z. and C.W. carried out the TEM characterizations. W.L. and Z.Z. performed the ToF-SIMS measurements. M.H.E. and S.D.B. performed the XPS and NMR tests, respectively. B.D.M. and B.W.A. prepared the FIB samples. H.L. helped with the cell energy density calculations. H.L. and C.N. prepared the cathode laminates. X.R., W.X., and J.-G.Z. prepared the manuscript with input from all other co-authors. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. A number of the authors have filed a patent application related to this work. \n\nReceived: February 25, 2019 \nRevised: April 11, 2019 \nAccepted: May 4, 2019 \nPublished: June 5, 2019 \n\n# REFERENCES \n\n1. Cheng, X.B., Zhang, R., Zhao, C.Z., and Zhang, Q. (2017). Toward safe lithium metal anode in rechargeable batteries: a review. Chem. Rev. 117, 10403–10473. \n2. $\\mathsf{X}\\mathsf{u},$ W., Wang, J., Ding, F., Chen, X., Nasybulin, E., Zhang, Y., and Zhang, J.-G. (2014). Lithium metal anodes for rechargeable batteries. Energy Environ. Sci. 7, 513–537. \n3. Albertus, P., Babinec, S., Litzelman, S., and Newman, A. (2018). Status and challenges in enabling the lithium metal electrode for highenergy and low-cost rechargeable batteries. Nat. Energy 3, 16–21. \n4. Lin, D., Liu, $\\mathsf{Y}_{\\cdot,\\prime}$ and Cui, Y. (2017). Reviving the lithium metal anode for high-energy batteries. Nat. Nanotechnol. 12, 194–206. \n5. Myung, S.-T., Maglia, F., Park, K.-J., Yoon, C.S. Lamp, P., Kim, S.-J., and Sun, Y.-K. (2017). Nickel-rich layered cathode materials for automotive lithium-ion batteries: achievements and perspectives. ACS Energy Lett. 2, 196–223. \n6. Manthiram, A., Knight, J.C., Myung, S.T., Oh, S.M., and Sun, Y.K. (2016). Nickel-rich and lithium-rich layered oxide cathodes: progress and perspectives. Adv. Energy Mater. 6. \n7. Xu, K. (2004). Nonaqueous liquid electrolytes for lithium-based rechargeable batteries. Chem. Rev. 104, 4303–4417. \n8. Xu, K. (2014). Electrolytes and interphases in Liion batteries and beyond. Chem. Rev. 114, 11503–11618. \n9. Li, J., Downie, L.E., Ma, L., Qiu, W., and Dahn, J.R. (2015). Study of the failure mechanisms of LiNi0.8Mn0.1Co0.1O2 cathode material for lithium ion batteries. J. Electrochem. Soc. 162, A1401–A1408. \n10. Ryu, H.-H., Park, K.-J., Yoon, C.S., and Sun, Y.-K. (2018). Capacity fading of Ni-rich Li [NixCoyMn1–x–y]O2 (0. $)\\leq x\\leq0.95$ ) cathodes for high-energy-density lithium-ion batteries: bulk or surface degradation? Chem. Mater. 30, 1155–1163. \n11. Winter, M., Barnett, B., and Xu, K. (2018). Before Li ion batteries. Chem. Rev. 118, 11433–11456. \n12. Zheng, J.M., Engelhard, M.H., Mei, D.H., Jiao, S.H., Polzin, B.J., Zhang, J.G., and Xu, W. (2017). Electrolyte additive enabled fast charging and stable cycling lithium metal batteries. Nat. Energy 2, 17012. \n13. Zhang, X.Q., Chen, X., Cheng, X.B., Li, B.Q., Shen, X., Yan, C., Huang, J.Q., and Zhang, Q. (2018). Highly stable lithium metal batteries enabled by regulating the solvation of lithium ions in nonaqueous electrolytes. Angew. Chem. Int. Ed. Engl. 57, 5301–5305. \n14. Suo, L., Xue, W., Gobet, M., Greenbaum, S.G., Wang, C., Chen, Y., Yang, W., Li, Y., and Li, J. (2018). Fluorine-donating electrolytes enable highly reversible 5-V-class Li metal batteries. Proc. Natl. Acad. Sci. USA 115, 1156–1161. \n15. Fan, X., Chen, L., Borodin, O., Ji, X., Chen, J., Hou, S., Deng, T., Zheng, J., Yang, C., Liou, S.C., et al. (2018). Non-flammable electrolyte enables Li-metal batteries with aggressive cathode chemistries. Nat. Nanotechnol. 13, 715–722. \n16. Ren, X., Zhang, Y., Engelhard, M.H., Li, Q., Zhang, J.-G., and Xu, W. (2018). Guided lithium metal deposition and improved lithium coulombic efficiency through synergistic effects of LiAsF6 and cyclic carbonate additives. ACS Energy Lett. 3, 14–19. \n17. Nagpure, S.C., Tanim, T.R., Dufek, E.J., Viswanathan, V.V., Crawford, A.J., Wood, S.M., Xiao, J., Dickerson, C.C., and Liaw, B. (2018). Impacts of lean electrolyte on cycle life for rechargeable Li metal batteries. J. Power Sources 407, 53–62. \n18. Liu, B., Zhang, J.-G., and Xu, W. (2018). Advancing lithium metal batteries. Joule 2, 833–845. \n19. Liu, J., Bao, Z., Cui, Y., Dufek, E.J., Goodenough, J.B., Khalifah, P., Li, Q., Liaw, B.Y., Liu, P., Manthiram, A., et al. (2019). Pathways for practical high-energy longcycling lithium metal batteries. Nat. Energy 4, 180–186. \n20. Yu, L., Chen, S., Lee, H., Zhang, L., Engelhard, M.H., Li, Q., Jiao, S., Liu, J., Xu, W., and Zhang, J.-G. (2018). A localized high-concentration electrolyte with optimized solvents and lithium difluoro(oxalate)borate additive for stable lithium metal batteries. ACS Energy Lett. 3, 2059–2067. \n21. Koch, V.R., and Young, J.H. (1979). 2- methyltetrahydrofuran–lithium hexafluoroarsenate: a superior electrolyte for the secondary lithium electrode. Science 204, 499–501. \n22. Abraham, K.M., Goldman, J.L., and Natwig, D.L. (1982). Characterization of ether \n\nelectrolytes for rechargeable lithium cells \n\nJ. Electrochem. Soc. 129, 2404–2409. \n23. Campbell, S.A., Bowes, C., and Mcmillan, R.S. (1990). The electrochemical behaviour of tetrahydrofuran and propylene carbonate without added electrolyte. J Electroanal Chem. Interfacial Electrochem. 284, 195–204. \n24. Yoshida, $\\mathsf{K}_{\\cdot,\\prime}$ Nakamura, M., Kazue, Y. Tachikawa, N., Tsuzuki, S., Seki, S., Dokko, K. and Watanabe, M. (2011). Oxidative-stability enhancement and charge transport mechanism in glyme-lithium salt equimolar complexes. J. Am. Chem. Soc. 133, 13121– 13129. \n25. Jiao, S.H., Ren, X.D., Cao, R.G., Engelhard, M.H., Liu, Y.Z., Hu, D.H., Mei, D.H., Zheng, J.M., Zhao, W.G., Li, Q.Y., et al. (2018). Stable cycling of high-voltage lithium metal batteries in ether electrolytes. Nat. Energy 3, 739–746. \n26. Yamada, Y., and Yamada, A. (2015). Review— Superconcentrated electrolytes for lithium batteries. J. Electrochem. Soc. 162, A2406– A2423. \n27. Fan, X., Chen, L., Ji, X., Deng, T., Hou, S., Chen, J., Zheng, J., Wang, F., Jiang, J., Xu, K., et al. (2018). Highly fluorinated interphases enable high-voltage Li-metal batteries. Chem. 4, 174–185. \n28. Zhang, Y., Zhong, Y., Shi, Q., Liang, S., and Wang, H. (2018). Cycling and failing of lithium metal anodes in carbonate electrolyte. J. Phys. Chem. C 122, 21462–21467. \n29. Chen, S., Zheng, J., Mei, D., Han, K.S., Engelhard, M.H., Zhao, W., Xu, W., Liu, J., and Zhang, J.G. (2018). High-voltage lithium-metal batteries enabled by localized high-concentration electrolytes. Adv. Mater. 30, 1706102. \n30. Ren, X.D., Chen, S.R., Lee, H., Mei, D.H., Engelhard, M.H., Burton, S.D., Zhao, W.G., Zheng, J.M., Li, Q.Y., Ding, M.S., et al. (2018). Localized high-concentration sulfone electrolytes for high-efficiency lithium-metal batteries. Chem. 4, 1877–1892. \n31. Chen, H., Tu, H., Hu, C., Liu, Y., Dong, D., Sun, Y., Dai, Y., Wang, S., Qian, H., Lin, Z., et al. (2018). Cationic covalent organic framework nanosheets for fast Li-Ion conduction. J. Am. Chem. Soc. 140, 896–899. \n32. Zheng, J., Chen, S., Zhao, W., Song, J., Engelhard, M.H., and Zhang, J.-G. (2018). Extremely stable sodium metal batteries enabled by localized high-concentration electrolytes. ACS Energy Lett. 3, 315–321. \n33. Ren, X., Zou, L., Jiao, S., Mei, D., Engelhard, M.H., Li, Q., Lee, H., Niu, C., Adams, B.D., Wang, C., et al. (2019). High-concentration ether electrolytes for stable high-voltage lithium metal batteries. ACS Energy Lett. 4, 896–902. \n34. Li, J., Liu, H., Xia, J., Cameron, A.R., Nie, M., Botton, G.A., and Dahn, J.R. (2017). The impact of electrolyte additives and upper cut-off voltage on the formation of a rocksalt surface layer in LiNi0.8Mn0.1Co0.1O2 electrodes. J. Electrochem. Soc. 164, A655– A665. \n35. Zhao, W.G., Zheng, J.M., Zou, L.F., Jia, H.P., Liu, B., Wang, H., Engelhard, M.H., Wang, C.M., Xu, W., Yang, Y., et al. (2018). High voltage operation of Ni-Rich NMC cathodes enabled by stable electrode/electrolyte interphases. Adv. Energy Mater. 8. \n36. Tian, C., Lin, F., and Doeff, M.M. (2018). Electrochemical characteristics of layered transition metal oxide cathode materials for lithium ion batteries: surface, bulk behavior, and thermal properties. Acc. Chem. Res. 51, 89–96. \n37. Wan, C., Hu, M.Y., Borodin, O., Qian, J., Qin, Z., Zhang, J.-G., and Hu, J.Z. (2016). Natural abundance 17O, 6Li NMR and molecular modeling studies of the solvation structures of lithium bis(fluorosulfonyl)imide/1,2- dimethoxyethane liquid electrolytes. J. Power Sources 307, 231–243. \n38. Suo, L., Borodin, O., Gao, T., Olguin, M., Ho, J., Fan, $\\times.,$ Luo, C., Wang, C., and Xu, K. (2015). \"Water-in-salt\" electrolyte enables highvoltage aqueous lithium-ion chemistries. Science 350, 938–943. \n39. Richards, W.D., Miara, L.J., Wang, Y., Kim, J.C. and Ceder, G. (2016). Interface stability in solidstate batteries. Chem. Mater. 28, 266–273. \n40. Qian, J., Henderson, W.A., Xu, W., Bhattacharya, P., Engelhard, M., Borodin, O., and Zhang, J.G. (2015). High rate and stable cycling of lithium metal anode. Nat. Commun. 6, 6362. \n41. Suo, L., Oh, D., Lin, Y., Zhuo, Z., Borodin, O., Gao, T., Wang, F., Kushima, A., Wang, Z., Kim, H.C., et al. (2017). How solid-electrolyte interphase forms in aqueous electrolytes. J. Am. Chem. Soc. 139, 18670–18680. \n42. Zhang, X.-Q., Chen, X., Hou, L.-P., Li, B.-Q., Cheng, X.-B., Huang, J.-Q., and Zhang, Q. (2019). Regulating anions in the solvation sheath of lithium ions for stable lithium metal batteries. ACS Energy Lett. 4, 411–416. \n43. Harrison, K.L., Zavadil, K.R., Hahn, N.T., Meng, X., Elam, J.W., Leenheer, A., Zhang, J.G., and Jungjohann, K.L. (2017). Lithium self-discharge and its prevention: direct visualization through in situ electrochemical scanning transmission electron microscopy. ACS Nano 11, 11194– 11205. \n44. Lin, D., Liu, Y., Li, Y., Li, Y., Pei, A., Xie, J., Huang, W., and Cui, Y. (2019). Fast galvanic lithium corrosion involving a Kirkendall-type mechanism. Nat. Chem. 11, 382–389. " + }, + { + "id": "10.1103_PhysRevLett.122.206401", + "DOI": "10.1103/PhysRevLett.122.206401", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevLett.122.206401", + "Relative Dir Path": "mds/10.1103_PhysRevLett.122.206401", + "Article Title": "Topological Axion States in the Magnetic Insulator MnBi2Te4 with the Quantized Magnetoelectric Effect", + "Authors": "Zhang, DQ; Shi, MJ; Zhu, TS; Xing, DY; Zhang, HJ; Wang, J", + "Source Title": "PHYSICAL REVIEW LETTERS", + "Abstract": "Topological states of quantum matter have attracted great attention in condensed matter physics and materials science. The study of time-reversal-invariant topological states in quantum materials has made tremendous progress. However, the study of magnetic topological states falls much behind due to the complex magnetic structures. Here, we predict the tetradymite-type compound MnBi2Te4 and its related materials host topologically nontrivial magnetic states. The magnetic ground state of MnBi2Te4 is an antiferromagetic topological insulator state with a large topologically nontrivial energy gap (similar to 0.2 eV). It presents the axion state, which has gapped bulk and surface states, and the quantized topological magnetoelectric effect. The ferromagnetic phase of MnBi2Te4 might lead to a minimal ideal Weyl semimetal.", + "Times Cited, WoS Core": 672, + "Times Cited, All Databases": 743, + "Publication Year": 2019, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000469032700008", + "Markdown": "# Topological Axion States in the Magnetic Insulator $\\mathbf{MnBi}_{2}\\mathbf{Te}_{4}$ with the Quantized Magnetoelectric Effect \n\nDongqin Zhang,1 Minji Shi,1 Tongshuai Zhu,1 Dingyu Xing,1,2 Haijun Zhang,1,2,\\* and Jing Wang3,2,4,† \n1National Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093, China \n2Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China \n3State Key Laboratory of Surface Physics, Department of Physics, Fudan University, Shanghai 200433, China \n4Institute for Nanoelectronic Devices and Quantum Computing, Fudan University, Shanghai 200433, China \n\n(Received 18 September 2018; revised manuscript received 24 January 2019; published 20 May 2019) \n\nTopological states of quantum matter have attracted great attention in condensed matter physics and materials science. The study of time-reversal-invariant topological states in quantum materials has made tremendous progress. However, the study of magnetic topological states falls much behind due to the complex magnetic structures. Here, we predict the tetradymite-type compound $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ and its related materials host topologically nontrivial magnetic states. The magnetic ground state of $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ is an antiferromagetic topological insulator state with a large topologically nontrivial energy gap $(\\sim0.2\\ \\mathrm{eV})$ . It presents the axion state, which has gapped bulk and surface states, and the quantized topological magnetoelectric effect. The ferromagnetic phase of $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ might lead to a minimal ideal Weyl semimetal. \n\nDOI: 10.1103/PhysRevLett.122.206401 \n\nThe discovery of time-reversal-invariant (TRI) topological insulators (TIs) [1–4] brings the opportunity to realize a large family of exotic topological phenomena through magnetically gapping the topological surface states (SSs) [5–36]. Tremendous efforts have been made to introduce magnetism into TRI TIs. One successful example is the first realization of the quantum anomalous Hall (QAH) effect in Cr-doped $(\\mathrm{Bi},\\mathrm{Sb})_{2}\\mathrm{Te}_{3}$ TI thin films [28,37,38]. Aside from the dilute magnetic TIs, intrinsic magnetic materials are expected to provide a clean platform to study magnetic topological states with new interesting topological phenomena. Some magnetic topological states have been theoretically proposed [39], such as antiferromagnetic (AFM) TI [29], a dynamical axion field [40], magnetic Dirac semimetals [32,33,41,42], and Weyl semimetals [30,31,43]. Though a few magnetic Weyl semimetals were experimentally observed [44], the study of magnetic topological states falls much behind in experiments due to complex magnetic structure. Therefore, realistic intrinsic magnetic topological materials are highly desired. The class of $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ materials predicted in this Letter provide an ideal platform for emergent magnetic topological phenomena, such as AFM TI, topological axion state with quantized topological magnetoelectric effect (TME), minimal ideal Weyl semimetal, QAH effect, two-dimensional ferromagnetism, and so on. \n\nThe tetradymite-type compounds $X A_{2}B_{4}$ , also written as $X B A_{2}B_{3}$ with $X=\\mathbf{Ge}$ , Sn, $\\mathrm{Pb}$ or Mn, $A={\\mathrm{Sb}}$ or Bi, and $B={\\mathrm{Se}}$ or Te, crystallize in a rhombohedral crystal structure with the space group $D_{3d}^{5}$ (No. 166) with seven atoms in one unit cell. We take $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ as an example, which has been successfully synthesized in experiments [45]. \n\nIt has layered structures with a triangle lattice, shown in Fig. 1. The trigonal axis (threefold rotation symmetry $C_{3z}$ ) is defined as the $z$ axis, a binary axis (twofold rotation symmetry $C_{2x,}$ ) is defined as the $x$ axis and a bisectrix axis (in the reflection plane) is defined as the $y$ axis for the coordinate system. The material consists of seven-atom layers (e.g., Te1-Bi1-Te2-Mn-Te3-Bi2-Te4) arranged along the $z$ direction, known as a septuple layer (SL), which could be simply viewed as the intergrowth of (111) plane of rocksalt structure MnTe within the quintuple layer of TI $\\mathrm{Bi}_{2}\\mathrm{Te}_{3}$ [see Fig. 1(a) and (c)] [10]. The coupling between different SLs is the van der Waals type. The existence of inversion symmetry $\\mathcal{T}$ , with the Mn site as the inversion center, enables us to construct eigenstates with definite parity. \n\n![](images/4eb3a50270b386b5852536f0a2e5801f2e5b73bdef61e55be9fc947a062a0a09.jpg) \nFIG. 1. Crystal structure and magnetic structure. (a) The unit cell of AFM $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ consists of two SLs. The red arrows represent the spin moment of $\\mathbf{M}\\mathbf{n}$ atom. The green arrow denotes for the half translation operator $\\tau_{1/2}$ . (b) Schematic top view along the $z$ direction. The triangle lattice in one SL has three different positions, denoted as $A$ , $B$ , and $C$ . The dashed green line is used for the (011) plane. (c) The unit cell of FM $\\mathrm{MnBi_{2}T e_{4}}$ has one SL. (d) The schematic of the (011) plane, with the blue balls denoting Mn atoms. (e) The calculated total energy for different magnetic ordered states. \n\nFirst-principles calculations are employed to investigate the electronic structure of $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ , where the detailed methods can be found in the Supplemental Material [46]. We find that each Mn atom in $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ tends to have halffilled $d$ orbitals. We performed total energy calculations for different magnetic phases for the three-dimensional $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ , and the results are listed in Fig. 1(e), showing that the $A$ -type AFM phase with the out-of-plane easy axis, denoted as AFM1 [seen in Fig. 1(a)], is the magnetic ground state. It is ferromagnetic (FM) within the $x y$ plane in each SL, and AFM between neighbor SLs along the z direction, consisting with the previous report [49]. The total energy of the $A$ -type AFM phase AFM2 with the in plane easy axis is slightly higher than that of AFM1, and much lower than that of FM phase FM1 with the out of plane easy axis, which indicates that the magnetic anisotropy is weaker than the effective magnetic exchange interaction between Mn atoms in neighbor SLs. The FM phase FM2 with in plane easy axis has the highest energy. The Goodenough-Kanamori rule is the key to understand the AFM1 ground state. For the in plane Mn atomic layer, two nearest Mn atoms are connected through Te atom with the bond “Mn─Te─Mn,” whose bonding angle is close to 90 degree, so the superexchange interaction is expected to induce FM ordering. Contrarily, Mn atoms between neighbor atomic layers are coupled through the bond “Mn─Te─Bi─Te∶Te─Bi─Te─Mn,” considered as an effective bond “Mn─X─Mn” with a 180 degree bonding angle, where AFM ordering is induced. In the following discussion, we would focus on the AFM1 (the magnetic ground state) and FM1 (possibly realized through an external magnetic field) states. \n\nFirst, we investigate the AFM1 ground state. The band structures without and with spin-orbit coupling (SOC) are shown in Figs. 2(a) and 2(b), respectively. The timereversal symmetry $\\Theta$ is broken; however, a combined symmetry $S=\\Theta\\tau_{1/2}$ is preserved, where $\\tau_{1/2}$ is the half translation operator connecting nearest spin-up and -down Mn atomic layers, marked in Fig. 1(a). The operator $s$ is antiunitary with $S^{2}=-e^{-i{\\bf k}\\cdot\\tau_{1/2}}$ . $S^{2}=-1$ on the Brillouinzone (BZ) plane $\\mathbf{k}\\cdot\\boldsymbol{\\tau}_{1/2}=0$ . Therefore, similar to $\\Theta$ in TRI TI, $s$ could also lead to a $\\mathcal{Z}_{2}$ classification [29], where the topological invariant is well defined on the BZ plane with $\\mathbf{k}\\cdot\\boldsymbol{\\tau}_{1/2}=0$ . One can see an anticrossing feature around the $\\Gamma$ point from the band inversion, suggesting that $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ might be topologically nontrivial. Since $\\boldsymbol{\\mathcal{T}}$ is still preserved, the $\\mathcal{Z}_{2}$ invariant is simply determined by the parity of the wave functions at TRI momenta (TRIM) in the Brillouin zone [50]. Here we only need consider the four \n\n![](images/f726ac08054da266e26f203ab5252d02ab1a01d265d5c54e83c8edf8bc3d6e9e.jpg) \nFIG. 2. Electronic structure of AFM1 $\\mathrm{MnBi_{2}T e_{4}}$ . (a) and (b) The band structure of AFM1 state without (a) and with (b) SOC. (b) The bands are twofold degenerate due to conserved $\\boldsymbol{\\mathcal{T}}$ and $s$ . (c) Brillouin zone of $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ . The four inequivalent TRIM are $\\Gamma(0,0,0)$ , $L(\\pi,0,0)$ , $F(\\pi,\\pi,0)$ , and $Z(\\pi,\\pi,\\pi)$ . (d) Schematic diagram of the band inversion at $\\Gamma$ . The green dotted line represents the Fermi level. (e) The parity product at the TRIM with $\\bar{\\mathbf{G}}\\cdot\\boldsymbol{\\tau}_{1/2}=n\\pi$ . (f) The Wannier charge centers (WCC) is calculated in the plane with $\\Gamma$ and $3F$ , confirming $\\mathcal{Z}_{2}=1$ . \n\nTRIM $\\Gamma$ and three $F$ ) with $\\bar{\\mathbf{G}}\\cdot\\boldsymbol{\\tau}_{1/2}=n\\pi$ . As expected, by turning on SOC, the parity of one occupied band is changed at $\\Gamma$ point from band inversion between the $|P1_{z}^{+}\\rangle$ of Bi and the $|P2_{z}^{-}\\rangle$ of Te, schematically shown in Fig. 2(d), whereas the parity remains unchanged for all occupied bands at the other three momenta $F$ [see Fig. 2(e)], so $\\mathcal{Z}_{2}=1$ . We also employ the Willson loop method [51] to confirm the $\\mathcal{Z}_{2}$ invariant in Fig. 2(f), concluding that AFM $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ is an AFM TI. Especially, we notice that a large energy gap of about $0.2\\ \\mathrm{eV}$ is obtained in Fig. 2(b). \n\nThe existence of topological SSs is one of the most important properties of TIs. However, the TI state in AFM $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ protected by $s$ is topological in a weaker sense than the strong $\\mathrm{\\DeltaTI}$ protected by $\\Theta_{;}$ , which manifests in that the existence of gapless SS depends on the surface plane. As shown in Figs. 4(a) and 4(c), there is gapped SSs on the (111) surface accompanied by a triangular Fermi surface, for $s$ is broken. As shown in Fig. 4(b), only on the $s$ - preserving surfaces such as (011) surface, the gapless SSs are topologically protected which forms a single Diraccone-type dispersion at $\\Gamma$ . \n\nFor the FM1 state of $\\mathrm{MnBi_{2}T e_{4}}$ , the band structures without and with SOC effect are shown in Fig. 3. $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ is a FM insulator with the experimental lattice constant $(a_{0}$ , $\\boldsymbol{c}_{0}$ ), shown in Fig. 3(b). Interestingly, we find that the band structure is sensitive to the lattice constant. When the lattice constant is slightly extended, it first becomes a type-II Weyl semimetal with $(1.005a_{0}$ ; $1.005c_{0}\\mathrm{\\cdot}$ ) and then becomes a minimal ideal Weyl semimetal with $(1.01a_{0},1.01c_{0})$ , hosting two Weyl points at the Fermi level without other bulk bands mixing, shown in Figs. 3(c) and 3(d). The Willson loop calculations, shown in Figs. 3(e) and 3(f), suggest that the Chern number $C=1$ at $k_{z}=0$ plane, and $C=0$ at $k_{z}=\\pi$ plane, which is consist with the ideal Weyl semimetal in Fig. 3(d). Furthermore, the SSs of FM1 state on different typical surfaces are calculated. In Fig. 4(d), bulk states projected on the (111) surface have no energy gap, for the two Weyl points are exactly projected to the surface $\\bar{\\Gamma}$ point. In Fig. 4(e) and 4(f), one can clearly see the surface Fermi arcs connecting to the two ideal Weyl points are separated $(\\sim0.06\\ \\mathring\\mathrm{A}^{-1})$ . \n\n![](images/d2166ec7749642f4bbee22f18df5da7883738417725ef63e1894e2c21f3d0aa9.jpg) \nFIG. 3. Electronic structure of FM1 $\\mathrm{MnBi_{2}T e_{4}}$ . (a) Band structure for FM1 state without SOC. The dashed line indicates the Fermi level. The red (blue) lines are spin-up (-down) bands. (b)–(d) Band structures for FM1 state with SOC are calculated by the $\\mathrm{LDA}+\\mathrm{U}$ $\\mathrm{~\\mathit~{~U~}~}=3\\ \\mathrm{eV}$ ) functional with experimental lattice constants $(a_{0},\\ c_{0})$ in (b), extended lattice constants $(1.005a_{0}$ ; $1.005c_{0}\\rangle$ ) in (c) and $(1.01a_{0},1.01c_{0})$ in (d), respectively. The system has the transition from FM insulator to type-II Weyl semimetal, and finally to ideal Weyl semimetal. (e) and (f) The evolution of WCC along the $k_{x}$ direction in the $k_{z}=0$ plane (e) and in the $k_{z}=\\pi$ plane (f). The WCCs cross the reference horizontal line once in (e), indicating the Chern number $C=1$ in the $k_{z}=0$ plane. Oppositely, the WCCs don’t cross the reference line in (f), indicating the Chern number $C=0$ in the $k_{z}=\\pi$ plane. \n\nLow-energy effective model.—As the topological nature is determined by the physics near the $\\Gamma$ point, a simple effective Hamiltonian can be written down to characterize the low-energy long-wavelength properties of the system. We start from the four low-lying states $|P1_{z}^{+},\\uparrow(\\downarrow)\\rangle$ and $|P2_{z}^{-},\\uparrow(\\downarrow)\\rangle$ at the $\\Gamma$ point. Here the superscripts $^{66}+$ ,” “−” stand for the parity of the corresponding states. Without the SOC effect, around the Fermi energy, the bonding state $|P1_{z}^{+}\\rangle$ of two Bi layers stays above of the antibonding state $|P2_{z}^{-}\\rangle$ of two Te layers (Te1 and $\\mathrm{Te4}$ in SLs). As shown in Fig. 2(d), the SOC mixes spin and orbital angular momenta while preserving the total angular momentum, and $|P1_{z}^{+},\\uparrow(\\downarrow)\\rangle$ state is pushed down and the $|P2_{z}^{-},\\uparrow(\\downarrow)\\rangle$ state is pushed up, leading to the band inversion and parity exchange. In the nonmagnetic state, the symmetries of the system are $\\Theta,\\mathcal{T}$ , $C_{3z}$ and $C_{2x}$ . In the basis of $(|P1_{z}^{+},\\uparrow\\rangle$ , $|P2_{z}^{-},\\uparrow\\rangle$ , $|P1_{z}^{+},\\downarrow\\rangle$ , $|P2_{z}^{-},\\downarrow\\rangle\\rangle$ , the representation of symmetry operations is given by $\\Theta=1_{2\\times2}\\otimes i\\sigma^{y}{\\mathcal{K}}.$ , $\\mathcal{T}=\\tau^{z}\\otimes1_{2\\times2}$ , $C_{3z}=\\exp[1_{2\\times2}\\otimes i(\\pi/3)\\sigma^{z}]$ and $C_{2x}=$ $\\exp[\\tau^{z}\\otimes i(\\pi/2)\\sigma^{x}]$ , where $\\kappa$ is the complex conjugation operator, and $\\sigma^{x,y,z}$ and $\\tau^{x,y,z}$ denote the Pauli matrices in the spin and orbital space, respectively. By requiring these four symmetries and keeping only the terms up to quadratic order in $\\mathbf{k}$ , we obtain the following generic form of the effective Hamiltonian for nonmagnetic state \n\nFIG. 4. Surface states. (a) and (b) Energy and momentum dependence of the local density of states (LDOS) for AFM1 phase on the (111) and (011) surfaces, respectively. In (a), The SSs on (111) surface are fully gapped due to the $s$ symmetry broken. In (b), The gapless SSs can be seen at the $\\Gamma$ point with a linear dispersion in the bulk gap on the $s$ -preserving (011) surface. (c) Fermi surface on the (111) surface at the energy level $E_{0}$ in (a) presents the triangle shape, different from the hexagonal shape in TI ${\\bf B i}_{2}{\\bf S e}_{3}$ . (d) and (e), Energy and momentum dependence of the LDOS for FM1 phase on the (111) and (011) surfaces, respectively. In (e), the two Weyl points are seen along the $k_{z}$ direction. (f) There are two Fermi arc connecting the Weyl points W1 and W2, indicating the ideal Weyl semimetal feature. \n\n$$\n\\mathcal{H}_{\\mathrm{N}}(\\mathbf{k})=\\epsilon_{0}(\\mathbf{k})+\\left(\\begin{array}{c c c c}{M_{\\gamma}(\\mathbf{k})}&{A_{1}k_{z}}&{0}&{A_{2}k_{-}}\\\\ {A_{1}k_{z}}&{-M_{\\gamma}(\\mathbf{k})}&{A_{2}k_{-}}&{0}\\\\ {0}&{A_{2}k_{+}}&{M_{\\gamma}(\\mathbf{k})}&{-A_{1}k_{z}}\\\\ {A_{2}k_{+}}&{0}&{-A_{1}k_{z}}&{-M_{\\gamma}(\\mathbf{k})}\\end{array}\\right),\n$$ \n\nwhere $k_{\\pm}=k_{x}\\pm i k_{y}$ , $\\epsilon_{0}(\\mathbf k)=C+D_{1}k_{z}^{2}+D_{2}(k_{x}^{2}+k_{y}^{2}),$ , and $M_{\\gamma}(\\mathbf{k})=M_{0}^{\\gamma}+B_{1}^{\\gamma}k_{z}^{2}+B_{2}^{\\gamma}(k_{x}^{2}+k_{y}^{2})$ . \n\nThe FM1 state breaks $\\Theta$ and $C_{2x}$ but preserves the combined $C_{2x}\\Theta$ ; therefore the effective Hamiltonian for FM1 is obtained by adding perturbative term $\\delta\\mathcal{H}_{\\mathrm{FM1}}(\\mathbf{k})$ respecting the corresponding symmetries into $\\mathcal{H}_{\\mathrm{N}}(\\mathbf{k})$ , which is \n\n$$\n\\delta\\mathcal{H}_{\\mathrm{FM1}}({\\bf k})=\\left(\\begin{array}{c c c c}{M_{1}({\\bf k})}&{A_{3}k_{z}}&{0}&{A_{4}k_{-}}\\\\ {A_{3}k_{z}}&{M_{2}({\\bf k})}&{-A_{4}k_{-}}&{0}\\\\ {0}&{-A_{4}k_{+}}&{-M_{1}({\\bf k})}&{A_{3}k_{z}}\\\\ {A_{4}k_{+}}&{0}&{A_{3}k_{z}}&{-M_{2}({\\bf k})}\\end{array}\\right),\n$$ \n\nwhere $M_{1,2}(\\mathbf{k})=M_{\\alpha}(\\mathbf{k})\\pm M_{\\beta}(\\mathbf{k})$ , and $M_{j}({\\bf k})=$ $M_{0}^{j}+B_{1}^{j}k_{z}^{2}+B_{2}^{j}(k_{x}^{2}+k_{y}^{2})$ with $j=\\alpha$ , $\\beta$ . By fitting the energy spectrum of the effective Hamiltonian with that of the first-principles calculation, the parameters in the effective model can be determined, which can be found in the Supplemental Material [46]. The $M_{1,2}$ terms characterize the Zeeman coupling with the magnetized Mn orbitals, and in general $M_{1}\\neq M_{2}$ denotes the different effective $g$ factor of $|P1_{z}^{+},\\uparrow(\\downarrow)\\rangle$ and $|P2_{z}^{-},\\uparrow(\\downarrow)\\rangle$ . \n\nThe AFM1 state breaks $\\Theta$ but preserves ${\\boldsymbol{S}}=$ $1_{2\\times2}\\otimes i\\sigma^{y}\\mathcal{K}e^{i\\mathbf{k}\\cdot\\tau_{1/2}}$ , and the unit cell doubles compared to FM1 state. For simplicity, we obtain the low-energy fourband model similar to the above analysis. From band structure analysis, the four bands close the Fermi energy in the AFM1 state are the new bonding state $|P1_{z}^{\\prime+},\\uparrow(\\downarrow)\\rangle$ of four Bi layers and the antibonding state $|P2_{z}^{\\prime-},\\uparrow(\\downarrow)\\rangle$ of four Te layers (two Te1 and two Te4 in neighboring SLs). In the basis of $(|P1_{z}^{\\prime+},\\uparrow\\rangle$ , $|P2_{z}^{\\prime-},\\uparrow\\rangle$ , $|P1_{z}^{\\prime+},\\downarrow\\rangle$ , $|P2_{z}^{\\prime-},\\downarrow\\rangle)$ , by requiring the symmetries $\\mathcal{T}$ , $C_{3z}$ , and $s$ , we get the effective Hamiltonian for AFM1 which has the same expression as $\\mathcal{H}_{\\mathrm{N}}(\\mathbf{k})$ but with different parameters. The AFM1 model and fitting parameters are listed in the Supplemental Material [46]. \n\nAxion state and topological response.—The topological electromagnetic response from AFM TI is described by the topological $\\theta$ term, $\\begin{array}{r}{S_{\\theta}=(\\theta/2\\pi)(\\alpha/2\\pi)\\int d^{3}x d t{\\bf E}\\cdot{\\bf B}}\\end{array}$ . Here, $\\mathbf{E}$ and $\\mathbf{B}$ are the conventional electromagnetic fields inside the insulator, $\\alpha=e^{2}/\\hbar c$ is the fine-structure constant, $e$ is electron charge, and $\\theta$ is dimensionless pseudoscalar parameter and defined only modulo $2\\pi$ . Physically, $\\theta$ has an explicit microscopic expression of the momentum space Chern-Simons form [34,52]. $s$ constrains $\\theta$ to be quantized, namely $\\theta=-\\theta+2\\pi n$ for integer $n$ , thus $\\theta=\\pi$ for AFM TI. From the effective action with open boundary conditions, we know that $\\theta=\\pi$ implies a surface quantized Hall conductance of $\\sigma_{x y}=e^{2}/2h$ . This half quantized Hall effect on the surface is the physical origin behind the topological TME effect. For a finite TRI TI, $\\Theta$ forces TME to vanish, where the surface and bulk states contribution to TME precisely cancel each other [34,53,54]. As is suggested in Refs. [34,55], to obtain the quantized TME in TIs, one must fulfill the following stringent requirements. First, all surfaces are gapped by magnetic ordering. Second, the Fermi level is finely tuned into the magnetically induced surface gap to keep the bulk truly insulating. Third, the film of TI material should be thick enough to eliminate the finite-size effect. However, the previous proposals on TME in the FM-TI heterostructure have several drawbacks. First, the gapless SSs on side surfaces are hard to eliminate [55–57], which will destroy the TME. Second, the surface gap is tiny due to weak magnetic proximity effect. \n\nInterestingly, $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ provides a feasible platform for quantized TME, which has not been experimentally observed. One advantage is that the $s$ breaking surfaces are gapped by material’s own time-reversal breaking, thus allowing a nonvanishing TME. One can simply grow realistic materials without any $s$ -preserving surfaces or apply a small in plane magnetic field. Such axion state has fully gapped bulk and surfaces, and the same topological response as AFM TI with $\\theta=\\pi$ . The second advantage is that the surface gap induced by intrinsic magnetism is large of about $0.1\\mathrm{eV}.$ Furthermore, the finitesize effect is negligible when the film exceed 4 SLs [46]. Experimentally, such quantized TME can be observed by measuring the induction of a parallel polarization current when an ac magnetic field is applied [55], which is $\\mathcal{T}=(\\theta/\\pi)(e^{2}/2h)(\\partial{B_{x}}/\\partial{t})\\ell d$ . Here, $d$ and $\\ell$ are the thickness and width of the $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ sample. For an estimation, taking $B_{x}=B_{0}e^{-i\\omega t}$ , $B_{0}=10\\mathrm{~G~}$ , $\\omega/2\\pi=1$ GHz, $d=50\\ \\mathrm{nm}$ , $\\theta=\\pi$ , and $\\ell=400\\ \\mu\\mathrm{m}$ , we have $\\mathcal{I}=-i\\mathcal{I}_{0}e^{-i\\omega t}$ with $\\mathcal{I}_{0}=2.22~\\mathrm{nA}$ , in the range accessible by experiments. \n\nIt is worth mentioning that the Ne´el order in AFM1 state is essentially different from that in dynamical axion field proposed in Ref. [40]. In the latter case, the Ne´el order breaks $\\Theta$ and $\\boldsymbol{\\mathcal{T}}$ , but conserves $\\mathcal{T}\\Theta$ . The magnetic fluctuation of the Ne´el order leads to linear contribution to the fluctuation of axion field, and the static $\\theta$ deviates from $\\pi$ . While in the case of AFM1 $\\mathrm{MnBi_{2}T e_{4}}$ , the Ne´el order conserves both $\\boldsymbol{\\mathcal{T}}$ and $s$ , thus the static $\\theta=\\pi$ , and to the linear order, the magnetic fluctuation has no contribution to the dynamics of axion field [40,58]. \n\nMaterials.—Other tetradymite-type compounds $X{\\mathrm{Bi}_{2}T{\\mathrm{e}}_{4}}$ , $X\\mathrm{Bi}_{2}\\mathrm{Se}_{4}$ , and $X\\mathrm{Sb}_{2}\\mathrm{Te}_{4}$ $(X=\\mathbf{M}\\mathbf{n}$ or Eu), if with the same rhombohedral crystal structure, are also promising candidates to host magnetic topological states similar to $\\mathrm{MnBi_{2}T e_{4}}$ . For example, $\\mathrm{EuBi}_{2}\\mathrm{Te}_{4}$ is another AFM TI, and $\\mathrm{{MnSb}}_{2}\\mathrm{{Te}}_{4}$ is at the topological quantum critical point [46]. Actually, tetradymite-type compounds $X B A_{2}B_{3}$ belong to a large class of ternary chalcogenides materials $(X B)_{n}(A_{2}B_{3})_{m}$ with $X=(\\mathrm{Ge},\\mathrm{Sn},\\mathrm{or}\\mathrm{Pb})$ , $A=({\\mathrm{Sb~or~Bi}})$ , and $B=(\\mathrm{SeorTe})$ , most of which were found to be TIs [59]. Interestingly, $\\displaystyle(\\mathrm{GeTe})_{n}(\\mathrm{Sb}_{2}\\mathrm{Te}_{3})_{m}$ and $\\displaystyle(\\ensuremath{\\mathrm{GeTe}})_{n}\\bigl(\\ensuremath{\\mathbf{B}}\\ensuremath{\\mathrm{i}_{2}}\\ensuremath{\\mathrm{Te}}_{3}\\bigr)_{m}$ have been widely studied as phase change memory materials [60]. By tuning the layer index $m$ and $n$ , we can play with the crystal structure, the topological property, and the magnetic property of the series of materials $(X B)_{n}(A_{2}B_{3})_{m}$ , which opens a broad way to study emergent phenomena of magnetic topological states. For example, the dynamic axion field may be obtained in these systems. \n\nFinally, the intrinsic magnetism and band inversion further lead to QAH effect in odd layer $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ thin film with $\\mathcal{T}\\Theta$ broken [46]. The intrinsic magnetic topological materials predicted here are simple and easy to control, which could host extremely rich topological quantum states in different spatial dimensions and are promising for investigating other exotic emergent particles such as Majorana fermions. \n\nWe thank Ke He for stimulating discussions. H. Z. is supported by the Natural Science Foundation of China (Grants No. 11674165 and 11834006) and the Fok YingTong Education Foundation of China (Grant No. 161006). J. W. is supported by the Natural Science Foundation of China through Grant No. 11774065, the National Key Research Program of China under Grant No. 2016YFA0300703, the Natural Science Foundation of Shanghai under Grant No. 17ZR1442500, the Open Research Fund Program of the State Key Laboratory of Low-Dimensional Quantum Physics through Contract No. KF201606, and by Fudan University Initiative Scientific Research Program. D. Z. and M. S. contributed equally to this work. \n\nNote added.—Recently, we learned of the experimental papers in the same material by Gong et al. [61] and Otrokov et al. [62]. \n\n\\*zhanghj@nju.edu.cn †wjingphys@fudan.edu.cn \n[1] M. Z. Hasan and C. L. Kane, Rev. Mod. Phys. 82, 3045 (2010). \n[2] X.-L. Qi and S.-C. Zhang, Rev. Mod. Phys. 83, 1057 (2011). \n[3] C.-K. Chiu, J. C. Y. Teo, A. P. Schnyder, and S. Ryu, Rev. Mod. Phys. 88, 035005 (2016). \n[4] N. P. Armitage, E. J. Mele, and A. Vishwanath, Rev. Mod. Phys. 90, 015001 (2018). \n[5] C. L. Kane and E. J. Mele, Phys. Rev. Lett. 95, 226801 (2005). \n[6] B. A. Bernevig, T. L. Hughes, and S.-C. Zhang, Science 314, 1757 (2006). \n[7] M. König, S. Wiedmann, C. Brüne, A. Roth, H. Buhmann, L. Molenkamp, X.-L. Qi, and S.-C. Zhang, Science 318, 766 (2007). \n[8] X. Qian, J. Liu, L. Fu, and J. Li, Science 346, 1344 (2014). \n[9] Y. Xia, D. Qian, D. Hsieh, L. Wray, A. Pal, H. Lin, A. Bansil, D. Grauer, Y. S. Hor, R. J. Cava, and M. Z. Hasan, Nat. Phys. 5, 398 (2009). \n[10] H. Zhang, C.-X. Liu, X.-L. Qi, X. Dai, Z. Fang, and S.-C. Zhang, Nat. Phys. 5, 438 (2009). \n[11] Y. L. Chen, J. G. Analytis, J. H. Chu, Z. K. Liu, S. K. Mo, X. L. Qi, H. J. Zhang, D. H. Lu, X. Dai, Z. Fang, S. C. Zhang, I. R. Fisher, Z. Hussain, and Z. X. Shen, Science 325, 178 (2009). \n[12] H. Weng, C. Fang, Z. Fang, B. A. Bernevig, and X. Dai, Phys. Rev. X 5, 011029 (2015). \n[13] S.-M. Huang, S.-Y. Xu, I. Belopolski, C.-C. Lee, G. Chang, B. Wang, N. Alidoust, G. Bian, M. Neupane, C. Zhang, S. Jia, A. Bansil, H. Lin, and M. Z. Hasan, Nat. Commun. 6, 7373 (2015). \n[14] A. A. Soluyanov, D. Gresch, Z. Wang, Q. Wu, M. Troyer, X. Dai, and B. A. Bernevig, Nature (London) 527, 495 (2015). \n[15] S.-Y. Xu et al., Science 349, 613 (2015). \n[16] B. Q. Lv, H. M. Weng, B. B. Fu, X. P. Wang, H. Miao, J. Ma, P. Richard, X. C. Huang, L. X. Zhao, G. F. Chen, Z. Fang, X. Dai, T. Qian, and H. Ding, Phys. Rev. X 5, 031013 (2015). \n[17] F.-F. Zhu, W.-J. Chen, Y. Xu, C.-L. Gao, D.-D. Guan, C.-H. Liu, D. Qian, S.-C. Zhang, and J.-F. Jia, Nat. Mater. 14, 1020 (2015). \n[18] L. Lu, J. D. Joannopoulos, and M. Soljačić, Nat. Photonics 8, 821 (2014). \n[19] J. Ruan, S.-K. Jian, H. Yao, H. Zhang, S.-C. Zhang, and D. Xing, Nat. Commun. 7, 11136 (2016). \n[20] B. Bradlyn, J. Cano, Z. Wang, M. G. Vergniory, C. Felser, R. J. Cava, and B. A. Bernevig, Science 353, aaf5037 (2016). \n[21] Z. Wang, A. Alexandradinata, R. J. Cava, and B. A. Bernevig, Nature (London) 532, 189 (2016). \n[22] B. Lv, Z.-L. Feng, Q.-N. Xu, X. Gao, J.-Z. Ma, L.-Y. Kong, P. Richard, Y.-B. Huang, V. Strocov, C. Fang et al., Nature (London) 546, 627 (2017). \n[23] H. Zhou, C. Peng, Y. Yoon, C. W. Hsu, K. A. Nelson, L. Fu, J. D. Joannopoulos, M. Soljačić, and B. Zhen, Science 359, 1009 (2018). \n[24] S. Wu, V. Fatemi, Q. D. Gibson, K. Watanabe, T. Taniguchi, R. J. Cava, and P. Jarillo-Herrero, Science 359, 76 (2018). \n[25] T. Zhang, Y. Jiang, Z. Song, H. Huang, Y. He, Z. Fang, H. Weng, and C. Fang, Nature (London) 566, 475 (2019). \n[26] F. Tang, H. C. Po, A. Vishwanath, and X. Wan, Nature (London) 566, 486 (2019). \n[27] M. G. Vergniory, L. Elcoro, C. Felser, B. A. Bernevig, and Z. Wang, Nature (London) 566, 480 (2019). \n[28] C.-Z. Chang et al., Science 340, 167 (2013). \n[29] R. S. K. Mong, A. M. Essin, and J. E. Moore, Phys. Rev. B 81, 245209 (2010). \n[30] X. Wan, A. M. Turner, A. Vishwanath, and S. Y. Savrasov, Phys. Rev. B 83, 205101 (2011). \n[31] G. Xu, H. Weng, Z. Wang, X. Dai, and Z. Fang, Phys. Rev. Lett. 107, 186806 (2011). \n[32] P. Tang, Q. Zhou, G. Xu, and S.-C. Zhang, Nat. Phys. 12, 1100 (2016). \n[33] G. Hua, S. Nie, Z. Song, R. Yu, G. Xu, and K. Yao, Phys. Rev. B 98, 201116(R) (2018). \n[34] X.-L. Qi, T. L. Hughes, and S.-C. Zhang, Phys. Rev. B 78, 195424 (2008). \n[35] L. Wu, M. Salehi, N. Koirala, J. Moon, S. Oh, and N. P. Armitage, Science 354, 1124 (2016). \n[36] J. Wang and S.-C. Zhang, Nat. Mater. 16, 1062 (2017). \n[37] R. Yu, W. Zhang, H.-J. Zhang, S.-C. Zhang, X. Dai, and Z. Fang, Science 329, 61 (2010). \n[38] J. Wang, B. Lian, and S.-C. Zhang, Phys. Scr. T164, 014003 (2015). \n[39] L. Šmejkal, Y. Mokrousov, B. Yan, and A. H. MacDonald, Nat. Phys. 14, 242 (2018). \n[40] R. Li, J. Wang, X. L. Qi, and S. C. Zhang, Nat. Phys. 6, 284 (2010). \n[41] L. Šmejkal, J. Železný, J. Sinova, and T. Jungwirth, Phys. Rev. Lett. 118, 106402 (2017). \n[42] J. Wang, arXiv:1701.00896. \n[43] H. Zhang, J. Wang, G. Xu, Y. Xu, and S.-C. Zhang, Phys. Rev. Lett. 112, 096804 (2014). \n[44] K. Kuroda, T. Tomita, M.-T. Suzuki, C. Bareille, A. Nugroho, P. Goswami, M. Ochi, M. Ikhlas, M. Nakayama, and S. Akebi et al., Nat. Mater. 16, 1090 (2017). \n[45] D. S. Lee, T.-H. Kim, C.-H. Park, C.-Y. Chung, Y. S. Lim, W.-S. Seo, and H.-H. Park, CrystEngComm 15, 5532 (2013). \n[46] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevLett.122.206401 for technical details on first-principles calculations and effective models with fitting parameters, which includes Refs. [47–48]. \n[47] G. Kresse and J. Hafner, Phys. Rev. B 47, 558 (1993). \n[48] G. Kresse and D. Joubert, Phys. Rev. B 59, 1758 (1999). \n[49] M. M. Otrokov, T. V. Menshchikova, M. G. Vergniory, I. P. Rusinov, A. Y. Vyazovskaya, Y. M. Koroteev, G. Bihlmayer, A. Ernst, P. M. Echenique, A. Arnau, and E. V. Chulkov, 2D Mater. 4, 025082 (2017). \n[50] L. Fu and C. L. Kane, Phys. Rev. B 76, 045302 (2007). \n[51] R. Yu, X. L. Qi, A. Bernevig, Z. Fang, and X. Dai, Phys. Rev. B 84, 075119 (2011). \n[52] A. M. Essin, J. E. Moore, and D. Vanderbilt, Phys. Rev. Lett. 102, 146805 (2009). \n[53] M. Mulligan and F. J. Burnell, Phys. Rev. B 88, 085104 (2013). \n[54] H.-G. Zirnstein and B. Rosenow, Phys. Rev. B 96, 201112(R) (2017). \n[55] J. Wang, B. Lian, X.-L. Qi, and S.-C. Zhang, Phys. Rev. B 92, 081107(R) (2015). \n[56] M. Mogi, M. Kawamura, R. Yoshimi, A. Tsukazaki, Y. Kozuka, N. Shirakawa, K. S. Takahashi, M. Kawasaki, and Y. Tokura, Nat. Mater. 16, 516 (2017). \n[57] D. Xiao, J. Jiang, J.-H. Shin, W. Wang, F. Wang, Y.-F. Zhao, C. Liu, W. Wu, M. H. W. Chan, N. Samarth, and C.-Z. Chang, Phys. Rev. Lett. 120, 056801 (2018). \n[58] K. Taguchi, T. Imaeda, T. Hajiri, T. Shiraishi, Y. Tanaka, N. Kitajima, and T. Naka, Phys. Rev. B 97, 214409 (2018). \n[59] H. Jin, J.-H. Song, A. J. Freeman, and M. G. Kanatzidis, Phys. Rev. B 83, 041202(R) (2011). \n[60] M. Wuttig and N. Yamada, Nat. Mater. 6, 824 (2007). \n[61] Y. Gong et al., arXiv:1809.07926. \n[62] M. M. Otrokov et al., arXiv:1809.07389. " + }, + { + "id": "10.1016_j.cemconres.2018.04.018", + "DOI": "10.1016/j.cemconres.2018.04.018", + "DOI Link": "http://dx.doi.org/10.1016/j.cemconres.2018.04.018", + "Relative Dir Path": "mds/10.1016_j.cemconres.2018.04.018", + "Article Title": "Cemdata 18: A chemical thermodynamic database for hydrated Portland cements and alkali-activated materials", + "Authors": "Lothenbach, B; Kulik, DA; Matschei, T; Balonis, M; Baquerizo, L; Dilnesa, B; Miron, GD; Myers, RJ", + "Source Title": "CEMENT AND CONCRETE RESEARCH", + "Abstract": "Thermodynamic modelling can reliably predict hydrated cement phase assemblages and chemical compositions, including their interactions with prevailing service environments, provided an accurate and complete thermodynamic database is used. Here, we summarise the Cemdata18 database, which has been developed specifically for hydrated Portland, calcium aluminate, calcium sulfoaluminate and blended cements, as well as for alkali activated materials. It is available in GEMS and PHREEQC computer program formats, and includes thermodynamic properties determined from various experimental data published in recent years. Cemdata18 contains thermodynamic data for common cement hydrates such as C-S-H, AFm and AFt phases, hydrogarnet, hydrotalcite, zeolites, and M-S-H that are valid over temperatures ranging from 0 to at least 100 degrees C. Solid solution models for AFm, AFt, C-S-H, and M-S-H are also included in the Cemdata18 database.", + "Times Cited, WoS Core": 750, + "Times Cited, All Databases": 780, + "Publication Year": 2019, + "Research Areas": "Construction & Building Technology; Materials Science", + "UT (Unique WOS ID)": "WOS:000452935100041", + "Markdown": "# Cemdata18: A chemical thermodynamic database for hydrated Portland cements and alkali-activated materials \n\nBarbara Lothenbacha,⁎, Dmitrii A. Kulikb, Thomas Matscheic, Magdalena Balonisd, Luis Baquerizoe, Belay Dilnesaf, George D. Mironb, Rupert J. Myersg,1 \n\na Empa, Laboratory for Concrete & Construction Chemistry, CH-8600 Dübendorf, Switzerland \nb Paul Scherrer Institut, Laboratory for Waste Management, 5232 Villigen PSI, Switzerland \nc HTW Dresden University of Applied Sciences, Department of Civil Engineering, 01069 Dresden, Germany \nd Department of Materials Science and Engineering, University of California Los Angeles, Los Angeles, CA, USA \ne Lafarge Centre de Recherche, 38291 Saint-Quentin Fallavier, France \nf BASF Schweiz AG, 5082 Kaisten, Switzerland \ng University of Sheffield, Department of Materials Science and Engineering, Sheffield S1 3JD, UK \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nKeywords: \nThermodynamic modelling \nCement \nDatabase \nSolubility \nC-S-H \n\nThermodynamic modelling can reliably predict hydrated cement phase assemblages and chemical compositions, including their interactions with prevailing service environments, provided an accurate and complete thermodynamic database is used. Here, we summarise the Cemdata18 database, which has been developed specifically for hydrated Portland, calcium aluminate, calcium sulfoaluminate and blended cements, as well as for alkaliactivated materials. It is available in GEMS and PHREEQC computer program formats, and includes thermodynamic properties determined from various experimental data published in recent years. Cemdata18 contains thermodynamic data for common cement hydrates such as C-S-H, AFm and AFt phases, hydrogarnet, hydrotalcite, zeolites, and M-S-H that are valid over temperatures ranging from 0 to at least $100^{\\circ}\\mathrm{C}$ . Solid solution models for AFm, AFt, C-S-H, and M-S-H are also included in the Cemdata18 database. \n\n# 1. Introduction \n\nNumerous studies have shown that chemical thermodynamic modelling, coupled with accurate and complete thermodynamic databases, can reliably predict hydrated cement phase assemblages and chemical compositions. One of the most interesting aspects of applying thermodynamics to hydrated cements has been the discovery that the chemical compositions of $\\mathrm{Al}_{2}\\mathrm{O}_{3^{-}}\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ mono (AFm) and $\\mathrm{Al}_{2}\\mathrm{O}_{3^{-}}\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ tri (AFt) phases are very sensitive to the presence of carbonate [1–3] and temperature [4–6], thus demonstrating that these factors may significantly modify hydrated cement phase assemblages. Experiments have shown that compositions of hydrate cement phase assemblages can alter rapidly, often within weeks or months, reflecting changing system compositions and temperatures. Thus, thermodynamic calculations and experiments support each other: on the one hand, calculations enable more complete interpretations of limited experimental datasets and help to identify key experiments to perform; and on the other hand, experiments provide the data that are needed to validate calculation results and model parameters. \n\nThe quality of thermodynamic modelling results depends directly on the accuracy and completeness of the input thermodynamic properties of substances and phases, which are usually supplied from a thermodynamic database. Relevant thermodynamic data for solid cementitious substances, such as the solubility products of ettringite or hydrogarnet, have been compiled in several specific “cement databases” such as (1) the Cemdata07 and Cemdata14 databases [1,7–12] (http://www.empa. ch/cemdata), which are available for GEMS [13,14], (2) the Thermoddem (http://thermoddem.brgm.fr/) database [15,16] available for the Geochemists Workbench® [17](https://www.gwb.com/) and PHREEQC [18] or (3) HATCHES database [19] available for PHREEQC [18]. Data in the first two databases are generally comparable, although some differences exist, as discussed in more detail in Damidot et al. [20]. Our experience applying Cemdata in thermodynamic modelling applications underlines the importance of a careful data selection and evaluation process, and of including sensitivity analyses into the analysis and discussion of results. \n\nAdditional experimental data, and thermodynamic properties derived from these data, have become available since the first compilation of Cemdata07 in 2007/2008 and subsequent compilation of Cemdata14 in 2013/2014 [1,7,21]. Cemdata18 provides a significant update to both Cemdata07 and Cemdata14. Cemdata18 is written into a format supporting the GEM-Selektor code [13,14] and is fully compatible with the freely available GEMS-Selektor version of the PSI-Nagra 12/07 TDB [22,23] (http://gems.web.psi.ch/). PSI/Nagra 12/07 TDB [22] contains the same entries for aqueous species/complexes relevant to cement systems as the PSI/Nagra 01/01 [24], with only slight changes: the thermodynamic properties of $\\mathrm{Si}_{4}\\mathrm{O}_{8}(\\mathrm{OH})_{4}{}^{4-}$ and $\\mathrm{\\AlSiO_{3}(O H)_{4}}^{3-}$ were added, while the complex AlSiO $\\left(\\mathrm{OH}\\right)_{6}{}^{-}$ was removed. The GEMS version of the PSI/Nagra 12/07 TDB includes further changes to the thermodynamic properties of Al bearing species/complexes and the addition of Helgeson-Kirkham-Flowers equation of state parameters to account for changes in temperature and pressure [25,26]. Cemdata18 includes a comprehensive selection of cement hydrates commonly encountered in Portland cement (PC) systems in the temperature range of 0 to $100^{\\circ}\\mathrm{C}_{:}$ , including calcium silicate hydrate (C-S-H), magnesium silicate hydrate (M-S-H), hydrogarnet, hydrotalcite-like phases, some zeolites, AFm and AFt phases, and various solid solutions used to describe the solubility of these phases. Solubility constants have generally been calculated based on critical reviews of all available experimental data and from additional experiments made either to obtain missing data or to verify existing data. Additional solubility data were measured and compiled using temperatures ranging from 0 to $100^{\\circ}\\mathrm{C}$ in many instances, as documented in [9,12,27,28]. Numerous solid solutions among AFm and AFt phases, siliceous hydrogarnets, hydrotalcite-like phases, C-S-H, and M-S-H have been observed and are included in Cemdata18. \n\nSeveral C-S-H solid solution models, as well as two models for hydroxide-hydrotalcite are available in Cemdata18. The CSHQ model from [11] and the OH-hydrotalcite end member with $\\mathbf{M}\\mathbf{g}/\\mathbf{A}\\mathbf{l}=2$ are well adapted for PC. Although the CSHQ model is able to describe the entire range of $\\mathrm{Ca}/\\mathrm{Si}$ ratios encountered, it is best used for high $\\mathsf{C a}/\\mathsf{S i C-}$ S-H, as it still lacks the ability to predict aluminium uptake, which is of less importance for Portland cements than for blended cements. For alkali activated binders, the calcium (alkali) aluminosilicate hydrate (C(N-)A-S-H) gel model, with lower calcium but higher aluminium and alkali content than in the C-S-H type phase which exists in hydrated PC, and a Mg-Al layered double hydroxide with variable $\\mathbf{Mg}/\\mathbf{Al}$ ratio, are available. \n\nThis paper summarises Cemdata18, which includes the most important additions to the Cemdata07 and Cemdata14 databases in recent years. It also discusses the relevance and implications of these additions, and compares Cemdata07 and Cemdata18, accounting for their main differences. Summaries of the thermodynamic data compiled in the Cemdata18 database are available in formats supported (readable) by the computer programs GEM-Selektor [13,14] and PHREEQC [18]. Both of these Cemdata18 variants can be freely downloaded from http://www.empa.ch/cemdata. \n\n# 2. Thermodynamic data for cements \n\nRecent experimental data has enabled the Cemdata07 and Cemdata14 databases to be extended and refined [1,7,21]. We report this more comprehensive and refined dataset here as Cemdata18, compiled in several tables. Cemdata18 has been developed to predict changes in chemistry that occur during the hydration of Portland, blended and alkali activated cements, and also their interactions with service environments during use. \n\nTable 1 reports the thermodynamic properties of minerals important for cementitious systems, while Table 2 reports their solubility products referring to the dominate species present at the high pH values of cementitious systems. The data for hydrotalcite-like phases and detailed discussions of the different models for C-S-H are given in Sections 2.6 and 2.7. Standard thermodynamic data for minerals such as calcite, brucite and aqueous and gaseous species already documented in the PSI-Nagra chemical thermodynamic database [22] are not repeated in these tables, but given only in summary tables in Appendices B and D. To enable users to model cementitious systems using the Cemdata18 dataset with the law of mass action (LMA) geochemical modelling package PHREEQC [18], a variant of the Cemdata18 dataset has been generated as documented in Appendix B. \n\n# 2.1. Solubility of $A l(O H)_{3}$ and its effect on calcium aluminate and calcium sulfoaluminate cements \n\nThe solubility of precipitated $\\mathrm{\\sfAl(OH)}_{3}$ decreases with time. Initially “amorphous” or poorly ordered $\\mathrm{\\bfAl(OH)}_{3}$ precipitates with a solubility product of approximately $0\\pm\\:0.2$ . With time, the degree of ordering increases, and microcrystalline $\\mathrm{\\bfAl(OH)}_{3}$ forms, while the solubility product decreases to $-0.7$ after 2 years. The solubility of hydrothermally prepared gibbsite is with $-1.1$ lower as illustrated in Fig. 1, however its formation is not expected within the timeframe of months to years generally considered for hydrating cements. At $60^{\\circ}\\mathrm{C}$ and above, it is expected that microcrystalline $\\mathsf{A l}(\\mathsf{O H})_{3}$ does not persist, but that gibbsite forms relatively fast (Fig. 1). The solubility of $\\mathrm{\\bfAl(OH)}_{3}$ determines whether ${\\mathrm{CAH}}_{10}$ (as in the presence of $\\mathsf{A l}(\\mathrm{OH})_{3}$ with log $\\mathrm{K}_{50}\\geq-0.6$ at $25^{\\circ}\\mathrm{C})$ is formed initially in calcium aluminate cements or whether it converts to ${\\mathrm{C}}_{3}{\\mathrm{AH}}_{6}$ and microcrystalline $\\mathsf{A l}(\\mathrm{OH})_{3}$ [12]. The decrease of the solubility of $\\mathsf{A l}(\\mathrm{OH})_{3}$ with time is also responsible for the initial occurrence of ${\\mathrm{CAH}}_{10}$ and ettringite instead of monosulfate plus microcrystalline $\\mathrm{\\sfAl(OH)}_{3}$ in some calcium sulfoaluminate cements, as discussed in more detail in [53]. \n\nWhich $\\mathrm{\\bfAl(OH)}_{3}$ modification (see Table 1) should be taken into account depends mainly on the timeframe and the temperature considered. While gibbsite should be allowed to form at temperatures above $60^{\\circ}\\mathrm{C}$ , its precipitation should be suppressed for calculations at ambient temperatures, where microcrystalline $\\mathrm{\\bfAl(OH)}_{3}$ will form instead. Within very short timeframes (minutes to hour), possibly only amorphous $\\mathrm{\\sfAl(OH)}_{3}$ should be allowed to precipitate. Similarly, also the formation of some other stable phases such as goethite (FeOOH), hematite $\\left(\\mathrm{Fe}_{2}\\mathrm{O}_{3}\\right)$ and quartz $(\\mathrm{{SiO}}_{2})$ should be suppressed in calculations of hydrated cements in favour of their more disperse counterparts: microcrystalline FeOOH (or microcrystalline or amorphous $\\mathrm{Fe(OH)}_{3}$ , depending on the timeframe considered), and amorphous $\\mathrm{SiO}_{2}$ . \n\n# 2.2. Thaumasite \n\nDamidot et al. [54] obtained solubility data to derive a solubility constant for thaumasite at $25^{\\circ}\\mathrm{C}$ , at which temperature thaumasite was considered to be stable. Invariant points were calculated for phase assemblages including thaumasite in the system CaO–A$\\mathrm{l_{2}O_{3}{-}S i O_{2}{-}C a S O_{4}{-}C a C O_{3}{-}H_{2}O}$ . Schmidt et al. [55] used the solubility data of Macphee and Barnett [56] to derive thermodynamic data for thaumasite over the temperature range 1 to $30^{\\circ}\\mathrm{C}$ to confirm experimental data showing formation of thaumasite in mortars at 8 and $20^{\\circ}\\mathrm{C}$ as shown in Fig. 2. Another set of solubility data at $8^{\\circ}\\mathrm{C}$ for natural thaumasite was reported by Bellmann [57] who also highlighted the potential pathways of formation of thaumasite at this temperature. Macphee and Barnett [56] obtained the solubility data of ettringitethaumasite solid solutions in the temperature range between $5^{\\circ}\\mathrm{C}$ and $30^{\\circ}\\mathrm{C}$ no apparent decomposition of thaumasite and related solid solutions occurred after 6 months storage at $30^{\\circ}\\mathrm{C}$ , which suggests the persistence of thaumasite at temperatures at least up to ${\\sim}30^{\\circ}\\mathrm{C}$ . A \n\nTable 1 Cemdata18 database: Standard thermodynamic properties at $25^{\\circ}\\mathrm{C}$ and 1 bar. Update of Cemdata07 [1,7,29]. The data are compatible with the GEMS version of the PSI/Nagra 12/07 TDB [22,23]. Standard properties of master species and properties of reactions of forming product species out of master species, commonly used in LMA programs such as PHREEQC, are compiled in the Appendix B. \n\n\n
△G°[KJ/mol] hpnedteAppehaix △H° [KJ/mol]S° [J/K/ao [J/K/a [J/mol/a2 [J K/mol]a3 [J/K0.5]V° [cm3/Ref
mol]mol]K²]mol]mol]
AFt-phases
(Al-)ettringitea,b,c-15,205.94-17,535190019390.789-707[1,7]
C6As3H30℃-14,728.1-16,950.21792.414522.156708[30]
C6As3H13-10,540.6-11,530.31960.4970.71.483-411[30]
C6As3Hg-9540.4-10,643.7646.6764.31.638361[30]
Tricarboaluminatea-14,565.64-16,792185820420.559-7.78106650[1,7]
Fe-ettringiteb-14,282.36-16,600193719220.8552.02-106717[1,21]
Thaumasite-7564.52-8700897.110310.263-3.40·106330[28]
Hydrogarnet
C3AHd-5008.2-5537.34222900.644-3.25-106150[9,12]
C3AS0.41H5.18**d-5192.9- 56993993100.566- 4.37-106146[9]
C3AS0.84H4.32*,e-5365.2-58473753310.484-5.55-106142[9]
C3FHg**F- 4122.8- 45188703301.237-4.74·106155[9]
Al-Fe siliceous hydrogarnet (solid
solution)
C3FS0.84H4.32ef- 4479.9-48238403710.478-7.03-106149[9]
C3A0.5F0.5S0.84H4.32e-4926.0-53356193670.471-8.10-106146[9]
C3FS1.34H3.32-4681.1-49948203950.383-8.39·106145[9]
AFm-phases
C4AH19
-8749.9-10,017.9112011631.047--1600369[12,31]
C4AH13°-7325.7-8262.4831.5208.33.13274[31]
C4AH11-6841.4-7656.6772.70.01193.561.34-10-7-257[31]
C2AH7.5- 4695.5-5277.54503230.728180[12]
CAH10- 4623.0-5288.26101511.113-3200193[12]
C4ACo.5H12-7335.97-82707136641.014-1.30·106- 800285[1,7]
C4AC0.5H10.5- 6970.3-7813.3668.30.00952.8361.07-10-7 9.9410-8-261[31]
C4AC0.5Hg-6597.4-7349.7622.50.00882.635-249[31]
C4AcH11-7337.46-82506576180.982-2.59·106262[1,7]
C4AcHg-6840.3-7618.6640.6192.42.042234[31]
C4AsH16-8726.8- 9930.5975.06361.606--351[31,32]
C4AsH14-8252.9-9321.8960.91028.5--332[31,32]
C4AsH128h-7778.4-8758.6791.61752.594310[31,32]
C4AsH10.5-7414.9- 8311.97211722.402--282[31,32]
C4AsH9-7047.6-7845.5703.61692.211275[31,32]
C2ASH8-5705.15-63605464380.749-1.13·106-800216[1,7]
C2ASH7-5464.0-6066.8487.60.00631.8877.1210-8215[31]
C2ASH5.5-5095.2-5603.4454.80.00571.6856.36-10-8213[31]
C4AS0.5CIH12-7533.4-8472i8205571.141-1.02-106751289[27,33]
C4ACl2H10k-6810.9-76047314980.895-2.041061503272[33,34]
C4A(NO3)2H10 C4A(NO2)2H10- 6778.1 -6606.8-7719.3 -7493.1821 799580 5651.02 0.99-2.77-106 -2.24-106872 703296 275[34,35] [34-36]
\n\nTable 1 (continued) \n\n\n
△G°[kJ/mol]△H°[kJ/mol]S° [J/K/ mol]ao [J/K/ mol]a [J/mol/ K]a2 [J K/mol]mol] a3 [J/K0.5]V° [cm3/ mol]Ref
M-S-H (solid solution)
M1.5S2H2.5, Mg/Si = 0.759-3218.43-3507.52270318\"---95[40]
M1.5SH2.5, Mg/Si = 1.59-2355.66- 2594.22216\"250--74[40]
Zeolites
Zeolite P(Ca)*-5057.8-5423779753---153[41]
Natrolite*-5325.7-5728360359---169[41]
Chabazite-7111.8-7774581617--251[41]
Zeolite (Aa)5847.5-_
-6447564589-_214[4]
Clinkers
C3S-2784.33-29311692090.036-4.25·10673[1,7,42]
C2S-2193.21-23081281520.037-3.03-10652[1,7,42]
CA-3382.35-35612052610.019-5.06-10689[1,7,42]
C12A7-18,451.44-19,414104512630.274-2.31-107518[42]
CA-2207.90-23271141510.042-3.33·10654W[42]
CA2-3795.31- 40041782770.023-7.45·10689*[42]
C4AF-4786.50-50803263740.073-130[1,7,42]
C (lime)-604.03-63539.748.80.0045-6.53·105-17[43]
Ks (K2SO4 arcanite)-1319.60-14381761200.100-1.78·106-66[44]
337780.036- 3.68-105__403
K(KaSO4 thenardie)322.40150[
N (NaO)-376.07-41575760.020-1.21-106-25[43]
\n\n${{a}_{O}},$ $a_{1},$ , $^{a_{2},}$ $a_{3}$ are the empirical coefficients of the heat capacity function: $C_{p}^{\\circ}=a_{O}+a_{I}T+a_{2}T\\ ^{-2}+a_{3}T\\ ^{-O.S};$ ; heat capacity functions for cement hydrates are typically valid up to $100^{\\circ}\\mathrm{C}$ only; $\\ '_{-}\\ '=0$ . Cement shorthand notation is used: $\\begin{array}{r}{{\\bf A}={\\bf A}\\mathrm{l}_{2}{\\bf O}_{3};}\\end{array}$ $\\mathbf{C}=\\mathbf{CaO}$ ; $\\mathrm{F}=\\mathrm{Fe}_{2}\\mathrm{O}_{3};$ $\\begin{array}{r}{\\mathrm{H}=\\mathrm{H}_{2}\\mathrm{O};}\\end{array}$ $\\mathbf{M}=\\mathbf{M}\\mathbf{g}0$ ; $\\begin{array}{r}{S=S\\mathrm{i}0_{2}}\\end{array}$ ; $\\mathbf{c}=\\mathbf{C}\\mathbf{O}_{2}$ ; $\\begin{array}{r}{s=s0_{3};}\\end{array}$ ⁎ Precipitates very slowly at $20^{\\circ}C,$ generally not included in calculations. \n\n⁎⁎ Tentative value. \n\na Non-ideal solid solutions; miscibility gap: $\\mathrm{X}_{\\mathrm{CO3,}\\mathrm{solid}}=0.45\\mathrm{-}0.90$ reproduced with the dimensionless Guggenheim interaction parameters $\\alpha_{O}=1.67$ and $\\alpha_{\\mathrm{1}}=0.946$ ; downscaled in this paper to $1\\mathsf{C O}_{2}.$ : $150_{3}$ replacement, instead of the $3{\\mathrm{CO}}_{2}.$ : $350_{3}$ used in [4,7]. \n\nb Non-ideal solid solution; miscibility gap: $\\mathrm{X_{Al,solid}}=0.25\\mathrm{-}0.65$ reproduced with the dimensionless Guggenheim interaction parameters $\\alpha_{O}=2.1$ and $\\alpha_{1}=-0.169$ [45]. \nc Ideal solid solutions c.f. [9,11,30,39]. \nd Ideal solid solutions c.f. [9,11,30,39]. \ne Ideal solid solutions c.f. [9,11,30,39]. \nf Ideal solid solutions c.f. [9,11,30,39]. \ng Non-ideal solid solutions; miscibility gap: $\\mathrm{X_{OH,solid}}=0.50–0.97$ reproduced with the dimensionless Guggenheim interaction parameters $\\alpha_{O}=0.188$ and $\\alpha_{1}=2.49$ [7] h Non-ideal solid solutions; miscibility gap: $\\mathrm{X_{Al,solid}}=0.45\\mathrm{-}0.95$ reproduced with the dimensionless Guggenheim interaction parameters $\\alpha_{O}=1.26$ and $\\alpha_{1}=1.57$ [10]. \ni Ideal solid solutions c.f. [9,11,30,39]. \nj Typing error in [27], recalculated from ${\\bf{G}}_{\\mathrm{{f}}}^{\\circ}$ and S from [27]. \nk Ideal solid solutions c.f. [9,11,30,39]. \nl Typing error in [37], recalculated from ${\\mathbf{G}_{\\mathrm{f}}^{\\circ}}$ and S from [37]. Volume calculated from XRD data [37]. \nm Recalculated from $\\Delta\\mathrm{G_{r}}^{\\circ}$ of $-20{,}500J/\\mathrm{mol}$ [38]. \nn Calculated from density data from [33,46]. \no Valid up to $60^{\\circ}\\mathrm{C}$ only, estimated to describe solubility of microcrystalline $\\mathrm{\\bfAl(OH)}_{3}$ aged for 19 months between 5 and $60^{\\circ}\\mathrm{C}$ [12]. \np Ideal solid solutions c.f. [9,11,30,39]. \nq Ideal solid solutions c.f. [9,11,30,39]. \nr Estimated from $\\mathbf{C}_{\\mathrm{p}}$ and S of talc, chrysotile and $\\mathrm{H}_{2}\\mathrm{O}$ using data from [43]. \ns Volume from [47]. \nt Calculated from XRD data: pdf 00-038-0237 [48]. \nu Calculated from XRD data; pdf 00-039-1380 [49]. \nv [50]. \nw [51]. \nx [52] \n\ncomplete solubility dataset representative for the stability range of thaumasite was missing, as [56] reported the solubility data for thaumasite-ettringite solid-solutions but not for pure thaumasite. Hence, due to a lack of experimental data, no thermodynamic data for thaumasite were included in the Cemdata07 database, but were added in a first update using the data derived in Schmidt et al. [55] based on the solubility data given by Macphee and Barnett [49]. In 2015, Matschei and Glasser [28] published a new dataset obtained on apparently purephase synthetic thaumasite. It was shown that pure thaumasite was thermally stable up to $68\\pm5^{\\circ}\\mathrm{C}$ . The obtained new data agreed well, within limits of error, with those obtained by Macphee and Barnett [56], but differs significantly from the data for natural thaumasite reported by Bellmann [57] at $8^{\\circ}\\mathrm{C}.$ Experiments done by [28,56] excluded atmospheric carbon dioxide, whereas the solubility determinations reported in [57] were made in the presence of air containing carbon dioxide. The contact with the air may lead to the decomposition of thaumasite, which would make the interpretation of the solubility data invalid. \n\nTable 2 Equilibrium solubility products of solids and formation constants for calcium-silica complexes at 1 bar, $25^{\\circ}\\mathrm{C}$ in Cemdata18 (as given in Table 1). \n\n\n
Minerallog KsoDissolution reactions used to calculate solubility products.
Solids
(Al-)ettringite-44.9CagAl(SO4)(OH)1226HO→6Ca²+ + 2Al(OH)4-+ 3SO42-+ 4OH- + 26H2O
tricarboaluminate-46.5CaAl(CO3)3(OH)1226HO→6Ca²+ +2Al(OH)4+3CO²-+4OH-+26HO
Fe-ettringite-44.0CagFe2(SO4)3(OH)1226H2O→6Ca2+ + 2Fe(OH)4 + 3SO42- + 4OH + 26HO
thaumasite-24.75Ca3(SiO3)(SO4)(CO3)-15HO→3Ca²+ + HSiO4 + SO4²-+CO32- + OH + 13HO
C3AH6-20.50
C3AS0.41H5.18*Ca3Al(OH)12 → 3Ca²+ + 2Al(OH)4+ 4OH-
-25.35CagAl(SiO4))0.41(OH)10.36→3Ca²++2Al(OH)4+0.41 SiO(OH)3+3.590H-1.23HO
C3AS0.84H4.32* C3FH6-26.70CaAl(SiO4)0.84(OH)8.64→3Ca²++ 2Al(OH)4+0.84 SiO(OH)3+3.16OH- 2.52HO
C3FS0.84H4.32-26.30**Ca3Fe(OH)12→3Ca²+ + 2Fe(OH)4+40H CaFe(SiO4)0.84 (OH)8.64 →3Ca²+ + 2Fe(OH)4 + 0.84 Si0(OH)3- + 3.160H-- 2.52HO
C3(F,A)S0.84H4.32-32.50 -30.20CagFeAl(SiO4)0.84 (OH)8.64→3Ca²+ + Al(OH)4+ Fe(OH)4+ 0.84 Si0(OH)3-+ 3.16OH-- 2.52H
C3FS1.34H3.32-34.20CaFe(SiO4)1.34 (OH)6.64 →3Ca²+ + 2Fe(OH)4- + 1.34 Si0(OH)3- + 2.66OH- - 4.02HO
C4AH19
-25.45Ca4Al(OH)1412HO→4Ca²+ + 2Al(OH)4-+ 6OH- + 12HO
C4AH1325.25 ***Ca4Al(OH)146HO→4Ca²++ 2Al(OH)4+ 6OH+ 6HO
C2AH7.5 CAH10-13.80CaAl(OH)1o2.5HO →2Ca²+ + 2Al(OH)4+ 2OH+ 2.5HO
C4AC0.5H12-7.60CaAl2(OH)6HO→Ca²+ + 2Al(OH)4 + 6HO Ca4Al(CO3)0.5(OH)137H2O→4Ca2+ + 2Al(OH)4+ 0.5CO32- + 50H + 7H2O
C4AcH1-29.13 -31.47CaAl(CO3)(OH)125HO→4Ca²+ + 2Al(OH)4+ CO32-+ 4OH- + 5H2O
C4AsH14
C4AsH12-29.26CaAl(SO4)(OH)126HO→4Ca²+ + 2Al(OH)4 + SO42-+ 4OH + 6HO
29.23 ***Ca4Al(SO4)(OH)126HO→4Ca2+ + 2Al(OH)4 +SO4²- + 40H + 6HO
C2ASH8-19.70CaAlSiO2(OH)10-3HO →2Ca²+ + 2Al(OH)4 + SiO(OH)3- + OH + 2HO
Friedel's salt Kuzel's salt-27,27CaAlCl(OH)124HO→4Ca²+ + 2Al(OH)4+ 2Cl+ 4OH+ 4HO
Nitrate-AFm-28,53Ca4AlCl(SO4)0.5(OH)126HO→4Ca²+ + 2Al(OH)4-+ Cl- + 0.5SO4²- + 4OH-+ 6HO
Nitrite-AFm-28.67CaAl(OH)12(NO3)24HO→4Ca²+ + 2 Al(OH)4+ 2 NO3-+ 4OH+ 4HO
C4FH13-26.24CaAl(OH)12(NO2)24HO→4Ca2+ + 2 Al(OH)4+ 2 NO-+ 4OH + 4HO
Fe-hemicarbonate-30.75**CaqFe(OH)146HO→4Ca²+ +2Fe(OH)4+ 60H+ 6HO
Fe-monocarbonate-30.83CaqFe(CO3)0.5(OH)133.5HO →4Ca²+ + 2Fe(OH)4+ 0.5CO²- + 50H + 3.5HO
Fe-monosulfate-34.59 -31.57CaqFe(CO3)(OH)126HO→4Ca²+ + 2Fe(OH)4-+CO32-+ 4OH-+ 6HO
Fe-Friedel's salt-28.62CaqFe(SO4)(OH)126HO→4Ca²+ + 2Fe(OH)4- + SO4²- + 4OH + 6HO
Cs (anhydrite)-4.357CaFezCl(OH)124HO→4Ca²+ + 2Fe(OH)4-+ 2Cl+ 4OH+ 4HO CaSO4→ Ca²+ + S042-
CsH (gypsum)-4.581CaSO42H2O→Ca²+ + SO4²-+ 2H2O
CsHo.5(hemihydrate)-3.59CaSO40.5HO→Ca²+ + SO4²-+ 0.5HO
syngenite-7.20K2Ca(SO4)2H0→2K+ + Ca2+ + 2SO42-+ HO
Al(OH)3(am)0.24Al(OH)3(am)→Al(OH)4- - OH
Al(OH)3(mic)-0.67Al(OH)3(mic)→Al(OH)4-- OH
Al(OH)3(gibbsite) *-1.12Al(OH)3(gibbsite)→Al(OH)4- - OH
Fe(OH)3(am)-2.6Fe(OH)3(am)→Fe(OH)4-- OH-
Fe(OH)3(mic)-4.6Fe(OH)3(mic)→Fe(OH)4-- OH-
FeOOH(mic)-5.6FeOOH(mic)→Fe(OH)4-- OH - H2O
FeOOH(goethite) *-8.6FeOOH(goethite)→Fe(OH)4- OH - HO
CH-5.2Ca(OH)2→Ca²+ + 2OH-
SiO2(am)-2.714SiO (am)→SiO20 SiOz(quartz)→SiO2°
SiOz(quartz)*-3.746 -33.29***MgAl(OH)8(CO3)0.52.5HO→3Mg2++ Al(OH)4 + 0.5CO32-.+ 4OH +2.5HO
1/2M6AcH13-33.64***MgFe(OH)s(CO3)0.52.5HO→3Mg2++Fe(OH)4+0.5CO32-.+4OH+2.5HO
1/2MFcH13-28.80(MgO)15(SiO)2(HO)25→1.5Mg2++2SiO+30H+HO
M1.5S2H2.5-23.57(MgO)1.5SiO2(H2O)2.5→1.5Mg2++SiO2°+ 3OH+ HO
M1.5SH2.5-20.3CaAlSiOg4.5HO→Ca²++ 2Al(OH)4+2SiO°+ 0.5HO
Zeolite P(Ca) *-30.2NaAlSiO1o2HO→2Na+ +2Al(OH)4+3SiO°- 2HO
Natrolite *CaAlSi4O126HO→Ca²+ +2Al(OH)4+4SiO2° + 2HO
Chabazite-25.8
Zeolite X(Na)-20.1NaAlSi2.5Og6.2HO→2Na+ + 2Al(OH)4+ 2.5SiO°+ 2.2HO
Zeolite Y(Na)-25.0NaAlSi4O128HO→2Na+ + 2Al(OH)4-+ 4SiO2°+ 4HO
Calcium silicate complexes
CaHSiO3+1.2*VCa²+ + HSiO3²- → CaHSiO3+
CaSiO3°4.6*V Ca²+ + SiO3²-→ CaSiO3°
\n\n⁎ Precipitates very slowly at $20^{\\circ}C,$ generally not included in calculations. ⁎⁎ Tentative value. ⁎⁎⁎ Recalculated in this paper from $\\Delta\\mathrm{G}_{\\mathrm{f}}^{\\circ}$ values. ⁎v The formation of less strong calcium silicate complexes have been recently suggested $(\\log\\mathrm{K}(\\mathrm{CaHSiO_{3}}^{+})=0.5$ and log $\\mathrm{:K(CaSiO_{3}}^{0})=2.9$ . Within Cemdata18, however, the listed values for calcium silicate complexes have to be used to maintain compatibility with the C-S-H models. \n\nThe heat capacities were estimated using a reference reaction with a solid having a known heat capacity and similar structure, as discussed in more detail in [28,55]. As shown by Helgeson et al. [43], this principle can be successfully applied to estimate the heat capacity of silicate minerals by formulating a reaction involving a structurally-related mineral of known heat capacity. \n\nFinally, it is possible to do an internal consistency check and recalculate solubilities under the chosen experimental conditions with the thermodynamic data of the Cemdata18 dataset. As illustrated in Fig. 3, the calculated solubility data for thaumasite show generally good agreement with the experimentally-derived dataset. Despite an underestimation of the calculated silicon concentrations at $1^{\\circ}\\mathrm{C}$ and $5^{\\circ}\\mathrm{C}$ , both datasets, experimental and calculated, generally agree, proving the internal consistency of the data. Especially in the temperature range from 1 to ${\\sim}40^{\\circ}\\mathrm{C}$ , where the solid phase assemblage consists mainly of thaumasite and traces of calcite, differences between experimental calcium and sulfate concentrations are within analytical errors. In the temperature range $1^{\\circ}\\mathrm{C}$ to ${\\sim}40^{\\circ}\\mathrm{C}$ , concentrations of calcium, sulfate and silicon increase with rising temperature, whereas calculated carbonate concentrations show a continuous decrease. At temperatures $>\\sim40^{\\circ}\\mathrm{C}$ , calcium and sulfate concentrations increase significantly, whereas silicon concentrations decrease due to the formation of C-S-H. Thaumasite is absent at temperatures above $70^{\\circ}\\mathrm{C}$ . \n\n![](images/85c5895a73b957b46594f2f97de6856f667a06af21b5ad0e0e054c48ee9c24aa.jpg) \nFig. 1. Logarithm of the solubility product of $\\mathrm{\\bfAl(OH)}_{3}$ (referring to $\\mathrm{\\sfAl(OH)_{4}}^{-}$ and $\\mathrm{OH}^{-}$ ) as a function of time and temperature calculated from the literature, adapted from [12]. Gibbsite solubility (dotted line) was calculated using data from the GEMS version of the PSI/Nagra $12/$ 07 TDB [22,23], whereas the solubility of microcrystalline $\\mathrm{\\bfAl(OH)}_{3}$ (black line) and amorphous $\\mathrm{\\bfAl(OH)}_{3}$ (black hyphen) was calculated based on the data given in Table 1. \n\n![](images/f6787e492bd51f5d85fdef37ebaaf4dd626397e7a984207b5d25bb373e382305.jpg) \nFig. 2. Calculated solubility products referring to ${\\mathsf{C a}}^{2+}$ , $\\mathrm{SiO(OH)_{3}}^{-}$ , ${\\mathrm{~}}S{\\mathrm{O}_{4}}^{2-}$ , $\\mathrm{CO_{3}}^{2-}$ , $\\mathrm{{OH^{-}}}$ and $\\mathrm{H}_{2}\\mathrm{O}$ of synthetic and natural thaumasite samples from solubility experiments. The curve shows the calculated best fit using a three-term temperature extrapolation. Reproduced from [28]. \n\n# 2.3. Chloride-, nitrate-, and nitrite-AFm phases \n\nBinding of chloride and the formation of chloride bearing cement hydrates has been widely studied due to its impact on the corrosion of steel in reinforced concrete. The first comprehensive solubility data for Friedel's salt $(\\mathrm{Ca}_{4}\\mathrm{Al}_{2}\\mathrm{Cl}_{2}(\\mathrm{OH})_{12}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O})$ and Kuzel's salt $(\\mathrm{Ca}_{4}\\mathrm{Al}_{2}\\mathrm{Cl}$ $(\\mathrm{SO}_{4})_{0.5}(\\mathrm{OH})_{12}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O})$ were provided in the late nineties. Birnin-Yauri [58] has described the dissolution of Friedel's salt as congruent and provided values of log ${\\mathrm{K}}_{{\\mathrm{{S}}}0}$ as $-27.1$ and $-24.8$ $(\\mathrm{K}_{50}=\\{\\mathrm{Ca}^{2+}\\}^{4}\\{\\mathrm{Al}}$ $\\mathrm{(OH)}_{4}\\mathrm{\\overline{{\\cdot}}\\nabla^{2}\\{C l^{-}\\}^{2}\\{O H^{-}\\}^{4}\\{H_{2}O\\}^{4})}$ . Hobbs [59] estimated log ${\\bf K}_{S0}$ as $-27.6\\ \\pm\\ 0.9$ and Bothe [60] has estimated via geochemical modelling that the solubility product of Friedel's salt should fall within the range $-28.8<\\log\\mathrm{~K}_{S0}<-27.6$ . Balonis et al. [27] provided solubility data for Friedel's salt as a function of time and temperature with an estimated value of solubility product for an ideal composition and at room temperature to be $-27.27$ [34,36]. Compilation of the available solubility data is shown by triangles on Fig. 4. \n\nThe estimated thermodynamic data [36] $(\\Delta_{f}G^{0}\\sim\\mathrm{~-~}6810.9\\mathrm{kJ/mol},$ $\\Delta_{f}H^{0}\\sim-7604\\mathrm{kJ/mol}$ , $S^{0}731\\mathrm{J/mol}\\mathrm{K})$ have similar values (except the entropy) to the dataset published by Blanc et al. [16] $(\\Delta_{f}G^{0}\\sim\\mathrm{~-~}6815.44\\mathrm{kJ/mol};$ $\\Delta_{f}H^{0}\\sim-7670.04\\mathrm{kJ/mol}$ , $s^{0}$ $527.70\\mathrm{J}/\\$ mol K), and agree reasonably well with the data obtained by Grishchenko et al. [61] $(\\Delta_{f}G^{0}$ estimated in a range between 6800 and $6860\\mathrm{kJ/mol}$ , $S^{0}\\sim680\\mathrm{J/mol/K},$ , though it should be kept in mind that Grishchenko‘s composition is reported to be slightly contaminated with carbonate ions. Attempts to synthesize Cl-AFt at temperatures above $0^{\\circ}\\mathrm{C}$ were unsuccessful [34], hence no thermodynamic data are available that can be used. \n\n![](images/3d41fadbd13e8d7f481b17d681fe1003e030d7def1f14d4629c9816af8b3b05e.jpg) \nFig. 3. Experimentally measured (markers) and re-calculated (lines) solubility data for thaumasite; (filled markers represent the experimental data for synthetic thaumasite, open markers – the data for natural thaumasite from [28]). Calculations are based on the new thermodynamic data for thaumasite complemented with the CSHQ data from Cemdata18 [1,7]. Predicted solid phases/phase assemblages are shown along the top. \n\n![](images/8f1029057a550c20510aae09594cc11350f7e98d2f6cfb5f50c21c3bfa656322.jpg) \nFig. 4. Solubility products of Friedel's salt, Kuzel's salt, $\\mathsf{N O}_{3}$ -AFm and ${\\tt N O}_{2^{-}}{\\tt A F m}$ (referring to reactions using $\\mathsf{C a}^{2+}$ , $\\mathbf{Cl}^{-}$ , ${80_{4}}^{2-}$ , ${\\mathrm{NO}_{3}}^{-}$ , ${\\ N O_{2}}^{-}$ , $\\mathrm{\\Omega_{oH}\\mathrm{{^{-}}}}$ and $\\mathrm{H}_{2}\\mathrm{O}$ as indicated in Table 2) as a function of temperature. Data for Friedel's salt from [27,58–60,62], data for other AFm are from Balonis and co-workers [27,34–36]. \n\nGlasser et al. [62] first measured the solubility of Kuzel's salt and noted that its dissolution is strongly incongruent, with ettringite precipitating as a secondary phase. From the solubility data given by Glasser et al. a log ${\\mathrm{K}}_{{\\mathrm{{S}}}0}$ of Kuzel's salt $-28.54$ $(\\mathrm{K}_{\\mathrm{{S}0}}=\\{\\mathrm{Ca}^{2+}\\}^{4}\\{\\mathrm{Al}}$ $\\mathrm{(OH)_{4}}^{-}\\}^{2}\\{\\mathrm{Cl}^{-}\\}\\{\\mathrm{SO_{4}}^{2-}\\}^{0.5}\\{\\mathrm{OH}^{-}\\}^{4}\\{\\mathrm{H}_{2}O\\}^{6})$ was estimated [27]. Balonis et al. [27] has also experimentally derived the solubility data and calculated solubility products for Kuzel's salt at different temperatures ranging from 5 to $85^{\\circ}\\mathrm{C}$ for the period between 1 and 12 months, with the solubility product at room temperature determined to be log $\\mathrm{K}_{50}=-28.53$ . Data for 12 months are shown by the filled circles in Fig. 4. \n\nIn recent years, the impact of soluble nitrate and nitrite corrosion inhibitors on the mineralogy of cement pastes has been studied [34,36,63], and it has been demonstrated that the AFm phase has the ability to accommodate ${\\mathrm{NO_{3}}}^{-}$ and ${\\mathrm{NO_{2}}}^{-}$ ions in the interlayer position. Solubility data along with thermodynamic parameters for the nitrate AFm $(\\mathsf{N O}_{3^{-}}\\mathsf{A F m})$ and nitrite AFm $(\\mathsf{N O}_{2^{-}}\\mathsf{A F m})$ published by Balonis et al. [34,35] are shown in Fig. 4. Similarly, as in the case of Cl-AFt, an attempted synthesis of $\\mathsf{N O}_{3}.$ - or $\\mathrm{NO}_{2}$ -AFt at room temperature was not successful [34]. \n\n# 2.4. Iron containing hydrates \n\nThe main source of iron in cements is $5\\mathrm{-}15\\%$ ferrite clinker in Portland cements and slag in blended cements. In synthetic systems containing only water, $\\mathbf{C}_{2}\\mathbf{F}.$ , calcium sulfate, calcium carbonate or silica, different Fe-containing phases like ettringite, monosulfate, monocarbonate, siliceous hydrogarnet can precipitate, as well as form solid solutions with their Al-containing analogues [8–10,21]. \n\n![](images/1f985552fbfccf99a21d05dd5d28c24dc1f373f8546b6e9b451013ed18a2b296.jpg) \nFig. 5. Solubility product $(\\mathrm{K}_{\\mathrm{{S}0}})$ of Fe-containing hydrogarnet and AFm-phases at different temperatures, referring to reactions using $\\mathsf{C a}^{2+}$ , $\\mathrm{Fe(OH)_{4}}^{-}$ , SiO $\\left(\\mathrm{OH}\\right)_{3}{}^{-}$ , ${\\ S O_{4}}^{2-}$ , $\\mathrm{CO_{3}}^{2-}$ , $\\mathbf{Cl}^{-}$ , $\\mathrm{\\Omega_{oH}\\mathrm{{^{-}}}}$ and $_{\\mathrm{H}_{2}\\mathrm{O}}$ as indicated in Table 2. Data from Dilnesa and co-workers [8–10,37]. \n\nThe stability of Fe-containing phases generally is only moderately affected by temperature, as shown in Fig. 5. At ambient temperature, Fe-ettringite $(\\mathrm{C}_{6}\\mathrm{F}s_{3}\\mathrm{H}_{32})$ , Fe-monosulfate $\\mathrm{(C_{4}F s H_{12})}$ , Fe-monocarbonate $\\boldsymbol{(\\mathrm{C_{4}F c H_{12})}}$ , Fe-Friedel's salt $(\\mathrm{C_{4}F C l_{2}H_{10}})$ , and Fe-siliceous hydrogarnet $(\\mathrm{C}_{3}\\mathrm{FS}_{0.95}\\mathrm{H}_{4.1}$ , $\\mathrm{C}_{3}\\mathrm{FS}_{1.52}\\mathrm{H}_{2.96})$ are stable, while Fe-katoite $\\mathrm{(C_{3}F H_{6})}$ and Fe-hemicarbonate $(\\mathbf{C_{4}F c_{0.5}H_{10}})$ are metastable [8–10,21,37]. Attempts to synthesize Fe-strätlingite $\\mathrm{(C_{2}F S H_{8})}$ failed, as only portlandite, C-S-H and iron hydroxide formed, indicating the instability of Fe-strätlingite at ambient conditions. $\\mathrm{C}_{4}\\mathrm{F}s\\mathrm{H}_{12},$ $\\mathrm{C}_{4}\\mathrm{FcH}_{12}$ , and $\\mathbf{C_{4}F C l_{2}H_{10}}$ are also stable at $50^{\\circ}$ but not at $80^{\\circ}\\mathrm{C}$ , while Fe-siliceous hydrogarnet is stable at up to $110^{\\circ}\\mathrm{C}$ . The limited stability field of the Fe-containing AFm and AFt hydrates is related to the very high stability of goethite (FeOOH) and hematite $\\left(\\mathrm{Fe}_{2}\\mathrm{O}_{3}\\right)$ , which form at $50^{\\circ}\\mathrm{C}$ within several months and at $80^{\\circ}\\mathrm{C}$ within days [9]. Although hematite and portlandite would be more stable than the Fe-katoite, AFt and AFm phases between 0 and $100^{\\circ}\\mathrm{C},$ , the formation of goethite and hematite at ambient temperatures is very slow, such that Fe-containing siliceous hydrogarnet, AFt and AFm phases can be synthesized instead. Fig. 3 shows the solubility products of Fe-containing phases calculated based on the measured composition of the liquid phase at 20, 50 and $80^{\\circ}\\mathrm{C};$ those data were used to derive the thermodynamic data for standard conditions $(25^{\\circ}\\mathrm{C},$ 1 atm) given in Table 1. The formation of solid solutions between Al and Fe-containing endmembers has been observed for ettringite, siliceous hydrogarnet, monosulfate, and Friedel's salt, while no solid solution formed between the rhombohedral Fe-monocarbonate with the triclinic Al-monocarbonate due to the structural differences [8–10,21,37]. \n\nWhile different Fe-containing hydrates could be synthesized, only Fe-siliceous hydrogarnet is expected to occur in hydrated cements. The solubility product of Fe-siliceous hydrogarnet (given in Table 1) is 5 to 7 log units lower than that of Al-siliceous hydrogarnet indicating a high stabilization of Fe-siliceous hydrogarnet, while the solubility products of the Fe-containing hydrates are comparable or only somewhat more stable than their Al-containing analogues. In fact, in hydrated PC, Fe (III) precipitates as iron hydroxide during the first hours and as siliceous hydrogarnet $(\\mathrm{C}_{3}(\\mathrm{A},\\mathrm{F})\\mathrm{S}_{0.84}\\mathrm{H}_{4.32})$ after 1 day and longer [64–66]. The data for the $\\mathrm{C}_{3}\\mathrm{FS}_{0.84}\\mathrm{H}_{4.32}$ and for the mixed Al- and Fe-containing $\\mathrm{C}_{3}\\mathrm{A}_{0.5}\\mathrm{F}_{0.5}\\mathrm{S}_{0.84}\\mathrm{H}_{4.32}$ determined by Dilnesa et al. [9] are included in Cemdata18, but not the data for the Al-based $\\mathrm{C}_{3}\\mathrm{AS}_{0.84}\\mathrm{H}_{4.32}$ due to its formation being kinetically hindered at ambient conditions [9]. \n\n# 2.5. Effect of relative humidity \n\nCement hydrates are known to show varying water content as functions of temperature and relative humidity (RH). Some of these hydrates are crystalline phases with layered structure such as the AFmphases or ettringite-type structures. The AFm and AFt phases have different hydration states (i.e. varying molar water content) depending on the exposure conditions, which can impact the volume stability, porosity and density of cement paste. The molar volume of some AFm phases can decrease by as much as $20\\%$ during drying [31], which may strongly influence the porosity and performance of some cementitious systems. \n\nIn gel-like phases such as C-S-H, water can be present within the intrinsic gel porosity, as well as in its interlayer. Unfortunately, until recently there was no thermodynamic model capable of assessing this varying water content. \n\nThe crystalline AFm phases have a layered structure and are known for their varying water content in the interlayer, which can be of two types. Firstly, the “space filling”, loosely integrated zeolitic water molecules, which are easily removed from the structure upon increase of temperature or at an initial small decrease of RH and have thermodynamic properties close to liquid water. Secondly, the “structural water” molecules, which are strongly bound to calcium cations of the \n\n![](images/00d33d3e13c06b86c0056482bf2b397eb90578d45bdcaa9cc90d2270545c5054.jpg) \nFig. 6. Volume changes of the AFm phases studied as function of RH at $25^{\\circ}\\mathrm{C}$ . $100\\%$ volume corresponds to the higher hydration state of each phase. \n\nEttringite, ${\\mathrm{C}}_{6}{\\mathrm{A}}s_{3}{\\mathrm{H}}_{32}$ , is also known to have varying water content. This hydrate is a common phase occurring during the hydration of PC. It is also the main hydration product in calcium sulfoaluminate cements and calcium aluminate cement blended with gypsum. Understanding the stability of ettringite during hydration and under different drying conditions is of great importance to assess the performance of systems containing large amounts of this phase. In general, ettringite contains 32 $_{\\mathrm{H}_{2}\\mathrm{O}}$ molecules per formula unit: 30 fixed in the columns and 2 $\\mathrm{H}_{2}\\mathrm{O}$ of zeolitic water loosely bound in the channels. Removal of the two inter-channel water molecules takes place with decreasing relative humidity (RH) without any significant change of the structure. Nevertheless, a series of structural changes are observed when the water content is below $30~\\mathrm{H}_{2}\\mathrm{O}$ , resulting in an amorphous phase commonly known as metaettringite. The thermodynamic properties of crystalline ettringite, having 32 and $30\\mathrm{H}_{2}\\mathrm{O}$ , and amorphous ettringite (or metaettringite) having $_{13\\mathrm{H}_{2}\\mathrm{O}}$ and $\\mathsf{9H}_{2}\\mathrm{O}$ were recently derived by Baquerizo et al. [30] and are listed in Table 1. Something interesting to notice is that decomposition and reformation of ettringite takes place reversibly but with a marked hysteresis, which makes the estimation of thermodynamic properties difficult. The values presented in Table 1 corresponds to those derived using the desorption equilibrium properties. Fig. 7 shows the stability of ettringite at $25^{\\circ}$ , presenting three different zones: \n\n![](images/d4ab07d35b2f0c319287a34572be49d020ccb7a8c3c43c34ca765001584f298b.jpg) \nFig. 7. Stability of ettringite as a function of relative humidity and temperature. \n\n- The zone of decomposition, which has to be reached in order to decompose ettringite into metaettringite. \n- The hysteresis loop, where crystalline ettringite will not undergo decomposition unless the zone of decomposition is reached and amorphous metaettringite will not reform unless the zone of reformation is reached. \n- The zone of reformation, which has to be reached in order to be convert metaettringite back to crystalline ettringite. \n\nmain layer and can only be removed at low water activities and/or high temperatures, typically accompanied by high enthalpies values. Recently, the thermodynamic properties of the different hydration states of the most important AFm phases were determined by Baquerizo et al. [31,32] and are listed in Table 1. A summary of the volume stability of AFm phases at $25^{\\circ}\\mathrm{C}$ is shown in Fig. 6. \n\n# 2.6. Mg-Al layered double hydroxide (hydrotalcite-like phase) \n\nMg-Al layered double hydroxide (LDH) type phases are structurally similar to hydrotalcite and typically occur as secondary reaction products in hydrated Portland cements [67] and in alkali-activated granulated blast furnace slag (GBFS) [68,69]. In hydrated or alkaliactivated cementitious materials free from carbonation, Mg-Al LDH phases normally exhibit poor long-range structural order and are thought to significantly occur along the solid solution series $\\begin{array}{r}{\\mathbf{M}\\mathbf{g}_{(1-x)}\\mathbf{A}\\mathbf{l}_{x}(\\mathrm{OH})_{(2+x)}(\\mathbf{H}_{2}\\mathbf{O})_{4},}\\end{array}$ where $0.2\\leq x\\leq0.33$ [70,71] due to the deficiency of $\\mathsf{C O}_{2}$ in the system. Mg-Al LDH formation is thus often difficult to observe by conventional X-ray diffraction, particularly at low $\\mathtt{M g O}$ content. \n\nFew solubility data for hydroxide containing hydrotalcite like Mg-Al LDH phases have been measured; the data at $25^{\\circ}\\mathrm{C}$ are summarised in Fig. 8A and B. The samples studied by Bennet et al. [72] were synthesized for 2 days at $80^{\\circ}\\mathrm{C}$ , dried, and then re-dispersed in water for 4 weeks at $25^{\\circ}\\mathrm{C}$ . This procedure resulted in a solubility product of ${10^{-47}}$ for $\\mathbf{M_{4}A H_{10}}$ . Further re-dispersion steps lowered the solubility product of $\\mathbf{M_{4}A H_{10}}$ to $10^{-56}$ . This lower solubility product of $10^{-56}$ for $\\mathbf{M_{4}A H_{10}}$ was selected for use in Cemdata07 [1,29] (see Figs. 8A and 9), and by Bennet et al. [72]. \n\n![](images/04670299348801dcb323e2d877c36c7a5018746876ec853230aed475a3f12d5e.jpg) \nFig. 8. Solubility of A) $\\mathbf{M_{4}A H_{10}}$ (from Cemdata $107+18)$ and B) of the MgAl-OH-LDH solid solution compared to the solubility of microcrystalline $\\mathsf{A l}(\\mathrm{OH})_{3}$ and brucit (dotted lines) and to the experimental data (Mg: circles, Al: triangles) determined by Bennet et al. [72] and Gao and Li [73]. \n\n![](images/cfc7767136954d39c028e0efb0180f755a0b5b9dfd76602c32dbf464324b7961.jpg) \nFig. 9. Measured and calculated solubility products of $\\mathbf{M_{4}A H_{10}}$ (reactions refer to $\\mathbf{\\dot{M}g}^{2+}$ , $\\mathrm{\\bfAl(OH)_{4}}^{-}$ , $\\mathrm{\\Omega_{oH}\\mathrm{{^{-}}}}$ and $\\mathrm{H}_{2}\\mathrm{O}$ as indicated in Table 3) at different temperatures. Adapted from Myers et al. [74]. \n\nBased on the solubility data of Gao and Li [73] for samples precipitated from oversaturated solutions (equilibration time 2 days), solubility data for hydrotalcite like Mg-Al LDH phases intercalated with $\\mathrm{\\ooH^{-}}$ (MgAl-OH-LDH) were recently recompiled and recalculated [74], as shown in Figs. 8B and 9. Solubility products for the end members of MgAl-OH-LDH solid solution model were defined using the available data [72,73] and guided using experimental observations in alkali activated slag cements with the high stability of MgAl-OH-LDH and absence of brucite in uncarbonated alkali-activated slag cements is widely documented and provides a reliable proxy for this task. An ideal (simple mixing) solid solution thermodynamic model (MA-OH-LDH_ss) was provisionally defined using these data for Mg/Al molar ratios between 2 and 4. The use of independent experimental observations to derive the solid solution model is important because solubility products derived from the available solubility data are scattered by up to ${\\sim}10\\log_{10}$ units at $25^{\\circ}\\mathrm{C},$ , possibly due to the varied equilibration times used (2 days [73] to 1 month [72]). We recommend using MgAl-OH-LDH_ss for alkali activated materials. \n\nUsage of the MgAl-OH-LDH_ss model (describing hydrotalcite-like phases with variable $\\mathrm{Mg/Al}$ ratio, and recommended for use in alkali activated material systems) does not lead to hydrotalcite formation under typical PC conditions due to the low aluminium concentrations in the pore solution [29] of PCs, for which brucite would be calculated to precipitate instead. As the formation of hydrotalcite like phases is reported in well hydrated PCs with dolomite [75], the use of a single phase, $\\mathbf{M_{4}A H_{10}}$ , with a lower solubility product (see Table 3, Fig. 9) derived from the long-term experiments in [72] only, is recommended for hydrated PC. The necessity to use presently two different datasets and the large differences in the available data indicates that the solubility data selected for $\\mathbf{M_{4}A H_{10}}$ and for MgAl-OH-LDH_ss are tentative and may require updating as more data become available. Therefore, we believe that additional solubility measurements for Mg-Al LDH phases are needed. \n\n# 2.7. C-S-H solid solution models \n\nThe C-S-H gel-like phase is the major hydrate in PC and blended PC pastes. C-S-H is also the main “sorbent” of alkali, alkali-earth, and hazardous cations $(\\mathsf{S r}^{2+}$ , ${\\mathrm{UO}}_{2}^{2+}$ , $Z\\mathrm{n}^{2+}$ , etc.) in hydrated cements used as waste matrices, including engineered barriers in nuclear waste repositories. \n\nC-S-H phases have a variable composition that depends on the prevailing $\\mathrm{Ca}/\\mathrm{Si}$ ratio in the system that can change by pozzolanic reaction, leaching caused by the ingress of water and/or chemical attack, such as carbonation. There are differences between properties of C-S-H samples prepared by (a) $\\mathsf{C}_{3}\\mathsf{S}$ or $\\mathsf{C}_{2}\\mathsf{S}$ hydration; (b) co-precipitation (double-decomposition) methods [76]. C-S-H has a ‘defect-tobermorite’ structure with a mean silicate chain length depending on the Ca/Si ratio, $\\mathsf{p H}$ and the presence of aluminium [77]. It has variable “non-gel” water content (i.e. structural water and water present in the interlayer [78,79]), also depending on the $\\mathrm{Ca}/\\mathrm{Si}$ ratio and the synthesis route, variable particle morphology, stacking, and “gel” water content, i.e. water present between C-S-H particles. Many C-S-H experimental solubility data sets available to date have been critically analyzed [80], including C-S-H type phases with variable aluminium and alkali contents [76,81–84]. \n\nC-S-H solubility can be reliably modelled using either solid solution models [11,80,85] or (to a limited extent) using a surface complexation approach [86,87]. Quantitative knowledge of C-S-H solubility is needed in essentially all studies of cement hydration and of waste-cement interactions, which explains why measuring and modelling the C-S-H solubility and water content is a major topic in cement chemistry [76]. \n\nTable 3 Standard thermodynamic properties at $25^{\\circ}\\mathrm{C}$ and 1 atm for hydrotalcite-like phases (provided in separate modules of Cemdata18 database). The data are consistent with the GEMS version of the PSI/Nagra 12/07 TDB [22,23] and the data detailed in Tables 1 and 4. \n\n\n
△G°[kJ/mol]H°[kJ/mol]S° [J/K/mol]ao [J/K/mol]a [J/mol/K²]a [J K/mol]a3 [J/K0.5/mol]V° [cm3/mol]Ref
MqAH10*- 6394.6-7196549-3644.213.75·106629220[1,29]
MgAl-OH-LDH (ideal ternary solid solution)**
MAH10-6358.5-7160.2548.9547.6--__219.1[74]
M6AH12-8022.9-9006.7675.2803.1--305.4[74]
MgAH14-9687.4-10,853.3801.5957.7--392.4[74]
Mineral
M4AH10*log Kso -56.02*Dissolution reactions used to calculate solubility products.→ 4Mg²++ 2Al(OH)4+ 60H+ 3HO
M4AH10**-49.7Mg4Al2(OH)143HO→ 4Mg2++ 2Al(OH)4+ 60H + 3H2O
M6AH12**-72.0Mg4Al2(OH)143H2O Mg6Al(OH)183H2O→ 6Mg2+ + 2Al(OH)4 + 100H + 3HO
MgAH14**-94.3MggAl(OH)22-3H2O→ 8Mg2+ + 2Al(OH)4 + 140H- + 3HO
\n\n${{a}_{O}},$ $a_{1}$ , $\\scriptstyle a_{2},$ , $a_{3}$ are the empirical coefficients of the heat capacity function: $C_{p}^{\\circ}=a_{O}+a_{1}T+a_{2}T^{-2}+a_{3}T^{-O.5}$ . $*$ Tentative value; recommended for PC based systems. $^{**}$ Tentative values; recommended for alkali activated materials. \n\nTable 4 Solid solution models of C-S-H (provided in separate modules of Cemdata18 database).a \n\n\n
Phase,△G°△H°aoa1a2Ref
End member[kJ/mol][kJ/mol][J/K/mol][J/K/mol][J/mol/K2][J K/mol][cm3/mol]
C-S-H (CSH-II solid solution),
Tob: C0.83SH1.3-1744.36-191680850.16059[1]
Jen: C1.67SH2.1-2480.81-27231402100.120-3.07-10678[1]
C-S-H-K-N (ECSH-1 solid solution)
TobCa-1: Co.83SH1.83-1863.62-2059.5114.6170.468[85]
SH: SH (SiO2HO)-1085.45-1188.6111.3119.834[85]
NaSH-1: No.5S0.2H0.45-433.57-480.441.237.910.5[88]
KSH-1: K0.5S0.2H0.45-443.35-490.048.440.612.4[88]
SrSH-1: SrSH2-2020.89-2231.6 (-2228b)141.9174.864[88]
C-S-H-K-N (ECSH-2 solid solution)(-2017.47b)
TobCa-2: Co.83SH1.83-2059.5
JenCa: CSo.6H1.1-1863.62-1741.6114.6170.468 36[85] [85]
NaSH-2: No.5S0.2H0.45-1569.05 -430.72-477.673.0 41.2114.510.5[88]
KSH-2: K0.5S0.2H0.45-440.49-487.248.437.9 40.612.4[88]
SrSH-2: SrSH2-2019.75-2230.5141.9174.864[88]
(-2016.33b)(-2227b)
C-S-H (CSHQ solid solution)
TobH Ca/Si=0.67: C2/3SH15-1668.56-1841.589.9141.655[11]
TobD Ca/Si =1.25:C5/6S2/3H1.83-1570.89-1742.4121.8166.948[11]
JenH Ca/Si =1.33: C1.33SH2.17-2273.99-2506.3142.5207.976[11]
JenD Ca/Si=2.25: C1.5S0.67H2.5-2169.56-2400.7173.4232.881[11]
NaSH: No.5S0.2H0.45-431.20478.041.237.910.5[88,89]
KSH: K0.5S0.2H0.45-440.80-489.648.440.612.4[88,89]
C-S-H (CSH3T solid solution)
TobH Ca/Si=0.67: CS3/2H5/2-2561.53-2832.97152.8231.285[11]
T5C Ca/Si=1.0: C5/4S5/4H5/2-2518.66-2782.03159.9234.179[11]
T2C Ca/Si=1.5: C3/2SH5/2-2467.08-2722.40167.0237.081[11]
C-(N-)A-S-H (CNASH solid solution)
TobH °: CS3/2H5/2-2560.00-2831.485.0
INFCA: CA5/32S38/32H53/32-2342.90-2551.3152.8 154.5231.2 180.959.3[90]
INFCN: CN5/16S3/2H19/16-2452.46-2642.0185.6183.771.1[90] [90]
INFCNA: CA5/32N11/32S38/32H42/32-2474.28-2666.7198.4179.769.3[90]
T5C °: C5/4S5/4H5/2-2516.90-2780.3159.9234.179.3[90]
5CA: C5/4A1/8SH13/8-2292.82-2491.3163.1177.157.3[90]
5CNA: C5/4N1/4A1/8SH11/8-2381.81-2568.7195.0176.264.5[90]
T2C °: C3/2SH5/2-2720.7167.0237.080.6[90]
-2465.40
\n\na0, a1, $\\mathbf{a}_{2},$ are the empirical coefficients of the heat capacity equation: $\\mathrm{C^{\\circ}_{p}}=\\mathrm{a}_{0}+\\mathrm{a}_{1}\\mathrm{T}+\\mathrm{a}_{2}\\mathrm{T}^{-2}$ ; no value $=0$ . a Only CSH-II solid solution included in Cemdata $?07.03$ database. b For the ACW conditions. c Thermodynamic properties were slightly modified relative to the T2C, T5C, and TobH end members of the downscaled CSH3T thermodynamic model [1 \n\nIn Table 4, five alternative C-S-H solid solution models are represented, in part for backward compatibility with previous versions of Cemdata (Cemdata07 and Cemdata14); they are provided in the Cemdata18 database. Here we provide a brief overview of those models with some recommendations for their use. \n\n# 2.7.1. CSH-II model \n\nThis simple ideal C-S-H solid solution model [85] has been used for many years, and was included (with a modified stability to better describe the changes in the calcium concentrations with pH and less water to correspond to the composition of C-S-H present in cements) into Cemdata07 database [1,29]. The original model [85] consisted of two binary ideal solutions CSH-I and CSH-II. CSH-I used end-members of amorphous silica (SH; $\\mathrm{~siO}_{2})$ ) and a tobermorite-like C-S-H gel phase (Tob-I; $(\\mathrm{Ca(OH)_{2})_{2}(S i O_{2})_{2}.._{4}.2H_{2}O})$ . CSH-II used end-members of tobermorite-like (Tob-II; $\\mathrm{(Ca(OH)_{2})_{0.8333}S i O_{2:0.8333}\\cdot H_{2}O)}$ and jennite-like (Jen; $\\mathrm{(Ca(OH)_{2})_{1.6666}S i O_{2}{\\cdot}H_{2}O)}$ C-S-H gel phases. The CSH-II phase coexists with CH (portlandite) at $\\mathrm{Ca}/\\mathrm{Si}$ ratios above 1.5 to 1.7. The CSH-I solid solution has been shown to be unrealistic ([80] and references therein) and amorphous $\\mathrm{{siO}}_{2}$ co-exists with C-S-H gel of Ca/Si ratios $=0.4–0.8$ . The water content in this C-S-H II is lower than in the other models discussed below, but corresponds well to the water present in the interlayer of C-S-H as measured by $^1\\mathrm{H}$ NMR [78,79]. In Cemdata18, we provide the CSH-II solid solution model only, covering the range of $\\mathrm{Ca}/\\mathrm{Si}$ ratios from 0.83 to 1.67, for backward compatibility with the Cemdata07 database and as an alternative to the newer models. \n\n# 2.7.2. ECSH-1 and ECSH-2 models \n\nECSH-1 and ECSH-2 models extend both CSH-I and CSH-II models with Na-, K- and Sr- containing end members. Aimed at pragmatic description of uptake of minor cations, these provisional ideal solid solution models [88] were constructed with help of the statistical dualthermodynamic method [91] based on GEM-Selektor calculations. With this method, one can retrieve both the unknown stoichiometry and the standard molar Gibbs energy $\\Delta_{\\mathrm{f}}\\mathrm{G}^{\\circ}{}_{298}$ of ideal solid solution end members from the experimental bulk compositions of the aqueous solution and co-existing solid solution. In total, 13 possible end member stoichiometries with the general formula $\\operatorname{\\mathbb{I}}(\\operatorname{Ca}(\\operatorname{OH})_{2})_{n C a}(\\operatorname{Sr}$ $(\\mathrm{OH})_{2})_{n S r}(\\mathrm{KOH})_{n K}(\\mathrm{NaOH})_{n N a}\\mathrm{SiO}_{2}\\mathrm{H}_{2}\\mathrm{O}]_{n S i}$ were considered for these models. To develop these models, the nCa, nSr, … coefficients were adjusted in order to minimize the standard deviations of estimated $G_{298}^{0}$ values for model end members in trial GEM calculations for a number of experimental data points. These trial GEM calculations employed: (1) the Nagra-PSI database [24]; (2) many experimental data points at different $\\mathrm{Ca}/\\mathrm{Si},\\mathrm{Sr}/\\mathrm{Si},\\mathrm{Na}/\\mathrm{Si},\\mathrm{K}/\\mathrm{Si}$ ratios; and (3) varying stoichiometry coefficients of solid solution end members within the ranges of $0.1\\mathrm{~<~}n_{S i}\\mathrm{~<~}2$ , $0~<~n_{C a}<1.6$ , $0{\\sim}1.3$ than other C-S-H thermodynamic models, e.g. [11,80]. CNASH_ss closely represents the full set of solubility data for the C-(N)A-S-H gel phase down to $\\mathrm{Ca}/\\mathrm{Si}=0.67$ . Therefore, we recommend using CNASH_ss for alkali activated systems rather than hydrated PC systems, where we recommend the use of CSHQ or C-S-H-II. \n\nAdditional solubility data for C-(N-)A-S-H gel not used to validate CNASH_ss were recently published, including for C-(N-)A-S-H gels at synthesis temperatures of $7^{\\circ}\\mathrm{C}$ $50^{\\circ}\\mathrm{C}$ and $80^{\\circ}\\mathrm{C}$ [103,104] and using K rather than Na [84,105]. Future refinement to the CNASH_ss thermodynamic model should include these data and formally extend the model to different temperatures and alkali type. \n\n# 2.7.6. General remarks \n\nDuring the last 20 years, ideal solid solution models of C-S-H have evolved starting from simple ideal solid solutions using full endmember mixing up to recent truly multi-site mixing models consistent with both solubility data and structural/spectroscopic data. Because end members in multi-site solid solutions are constructed of moieties substituting each other on different sublattices, such models have the best potential for: (1) extension by adding moieties for other elements of interest (e.g. K, Na, Al, U, Sr) in their respective sites; (2) generating all possible end members; and (3) parameterizing end members based on available solubility, element uptake, and spectroscopic data (e.g. using the GEMSFITS code [106]) and are the subjects of ongoing research. \n\nFor the calcium silicate hydrate complexes, $\\mathrm{CaH_{3}S i O_{4}}^{+}$ $\\mathrm{(CaHSiO_{3}^{+}}$ $+2\\mathrm{H}_{2}\\mathrm{O})$ and ${\\mathrm{CaH}}_{2}{\\mathrm{SiO}}_{4}^{0}$ $(\\mathrm{CaSiO_{3}}^{0}+2\\mathrm{H}_{2}\\mathrm{O})$ , the reported complex formation data show a significant scatter. In particular, complex formation constants for ${\\mathrm{CaH}}_{2}{\\mathrm{SiO}}_{4}^{0}$ vary by more than one log unit. While the PSI/ Nagra TDB [22,23] reports a complex formation constant of $10^{4.6}$ for the reaction $\\mathsf{C a}^{2+}+\\mathsf{S i O_{3}}^{2-}\\to\\mathsf{C a S i O_{3}}^{0}$ (see Table 2), which has a large effect on the silicon concentrations in presence of C-S-H at $\\mathrm{{Ca}/\\mathrm{{Si}}>1}$ [80], no such constant is defined in the PHREEQC database [18]. Walker et al. [80] recommended to use a constant of $10^{4.0}$ , making the complex less important, while recently an even lower complex formation constant of $10^{2.9}$ has been derived based on titration experiments [107]. This large scatter of data results in very diverging assessment of the importance of the ${\\mathsf{C a S i O}}_{3}^{0}$ complex at $\\mathrm{{Ca}/\\mathrm{{Si}}>1}$ and has a significant impact on the C-S-H solubility as this complex accounts for about $90\\%$ of aqueous dissolved silicon in equilibrium with both CS-H and portlandite. Dedicated investigations not only of calcium silicate hydrate complexes but also of other possible complexes between aluminium, calcium and silicate at high pH values are urgently needed. \n\n![](images/4d9e9d9be253c76082f00604525daa2ed7e329cb6c1f05a0e181f78c2422aea0.jpg) \nFig. 11. Evolution of the solubility product $(\\mathrm{K}_{\\mathbf{S}0})$ of magnesium silicate hydrates at room temperature as a function of the total $\\mathbf{Mg}/\\mathbf{Si}$ ; referring to reactions using $\\mathbf{M}\\mathbf{g}^{2+}$ , $\\mathrm{SiO}_{2}$ and $\\mathrm{H}_{2}\\mathrm{O}$ as indicated in Table 2. Adapted from [118]. \n\n# 2.8. Magnesium silicate hydrates \n\nThe formation of magnesium silicates hydrate (M-S-H) has been observed at the interfacial zone of cement paste with clays [67,108,109] and/or as secondary products from the degradation of cement pastes by groundwater or seawater [110–112]. The combination of leaching and carbonation of the cement paste decreases $\\mathsf{p H}$ at the surface of the cement, decalcifies C-S-H and leads the formation of a Mg-enriched phase, M-S-H. M-S-H phases are poorly ordered but have a layered structure with tetrahedral silica arranged in sheets similar to clay minerals, have variable $\\mathrm{Mg/Si}$ from $\\approx0.8$ to $\\mathbf{Mg/Si}\\approx1.2$ and are stable at pH values between 7.5 and 11.5 [40,113–115]. Given the difference in structure and pH domains, most studies [114–117] observed the precipitation of distinct C-S-H and M-S-H phases and not of a mixed magnesium calcium silicate hydrate phase. Solubility measurements [40,113,118] indicated an only slightly higher solubility of the poorly ordered M-S-H in comparison to crystalline magnesium-silicates such as talc, antigorite or chrysotile as shown in Fig. 11. The ideal solid solution model for M-S-H published by Nied et al. [40] has been selected for the present version of the database. As several groups [113,114,118] are currently working on thermodynamic data for M-SH, we expect that more sophisticated models will be published in the coming years. \n\n# 2.9. Zeolites \n\nInteractions of highly alkaline solutions in hydrated PC systems with service environments will likely result in the partial dissolution of aluminosilicate minerals from adjacent rocks and the formation of secondary zeolite minerals [119] in the context of deep underground nuclear waste repositories. Zeolite formation also occurs in alkali activated cement systems. These zeolites are often related to the poorly crystalline N-A-S-H (sodium-aluminium-silicate-hydrate) and K-A-S-H (potassium-aluminium-silicate-hydrate) gels that form in these systems [74,103]; the type of gel formed depends on the presence of $\\mathrm{{Na}^{+}}$ or $\\mathrm{K}^{+}$ , cation concentrations, the relative degree of saturation of the liquid phase with respect to silica, pH and temperature [120]. Several papers in recent years estimated solubility data for different zeolites, based mainly on heat capacity and enthalpy measurements [47,74,121]. This may lead to considerable bias in the estimated solubility data in the range of several log units due to uncertainties associated with the measurements of enthalpy data. The determination of solubility data for zeolites has been hindered by variability in cation composition (Ca, Na, K), Al/Si ratios, $_{\\mathrm{H}_{2}\\mathrm{O}}$ contents and atomic structure, and also their slow reaction kinetics. \n\n![](images/abcf00cb3603d95d027346482caec1f8454015d7b7078ee5426c23d8d8ad46f2.jpg) \nFig. 12. Experimentally observed phase assemblage in a PC without additional limestone (PC) and with $4\\mathrm{wt\\%}$ of limestone (PC4); reproduced from [123]. \n\nIn 2017, two independent studies [41,103] reported very similar solubility products for zeolite Y and $\\mathbf{\\boldsymbol{X}}$ (or for N-A-S-H gel with Al/ $\\mathrm{si}=0.5$ and $\\mathsf{A l/S i}=0.8\\AA$ ) based on experimental data. The data for zeolite X(Na), zeolite Y(Na) and chabazite [41] make it possible to predict zeolite formation in sodium activated cements; data for potassium-based zeolites are still missing in the Cemdata18 database. Also data for natrolite and zeolite P(Ca) have been included [41]. In experiments with high pH values their formation was kinetically hindered (although natrolite and zeolite P(Ca) were more stable than zeolite X (Na), zeolite Y(Na) and chabazite). Thus we recommend that natrolite and zeolite P(Ca) should be considered in modelling the interface between cement and adjacent rocks. However, their formation may be supressed in models for alkali activated systems, where zeolite X(Na), zeolite Y(Na) and chabazite or their amorphous or nanocrystalline precursors are formed [122]. \n\n# 3. Comparison Cemdata07 with Cemdata18 \n\nThe updates since the first cemdata version, cemdata07 (published in 2008), are significant. In particular, the distribution of iron and aluminium, the volume and Ca/Si in C-S-H as well as the alkali concentrations in the pore solution in PC can significantly affect thermodynamic modelling results. To illustrate these differences, the effect of limestone on the same PC was calculated with Cemdata07 and Cemdata18 and compared below. The effect of relative humidity on calculated hydrates is used below as a second example. These comparisons concentrate on PC, as compiled specific data for alkali activated materials are only now available (in this paper). \n\n![](images/cbbc385c13d29d04393ccca3d1208c2992702c1eafd67c5206f8cbdadd362757.jpg) \nFig. 13. Comparison of calculated solid phase assemblage using A) Cemdata07 and B) Cemdata18 assuming complete hydration of PC using the composition reporte in [123]. \n\n![](images/a632e705cd00c928da1327ecb81ccc14a1c859a4c3b1cc18ae78c1d8cb6f8924.jpg) \nFig. 14. Effect of the amount of limestone on the phase assemblage and the distribution of aluminium and iron in hydrated PC calculated using Cemdata07 (A, C) and Cemdata18 (B, D). \n\n# 3.1. Effect of limestone on solid and liquid phase composition \n\nThe influence of limestone on cement hydration has been widely studied and was the subject of several publications by the authors [2,20,123]. Experimental investigations showed that the presence of calcium carbonate prevents the destabilisation of ettringite to monosulfate at long hydrations times and stabilises monocarbonate together with ettringite (see e.g. [123–125] and Fig. 12). \n\n![](images/140ca5dd3a56aa5ca70a9c6665222d7d4bcfecaad9128ee88e19c31001af84b3.jpg) \nFig. 15. Effect of the amount of limestone on the phase assemblage and the distribution of aluminium and iron in hydrated PC calculated using A) Cemdata07 and B) Cemdata18. \n\nAlso thermodynamic modelling [2,20,123] (mainly using the Cemdata2007 database) showed that the presence of small amounts of limestone significantly impacted the mineralogy of hydrated cements. In the absence of any limestone no ettringite but only monosulfate as well as of a small amount of katoite $(\\mathsf{C}_{3}(\\mathsf{A},\\mathsf{F})\\mathsf{H}_{6})$ was predicted as shown in Fig. 13A. The presence of a small amount of limestone was calculated to stabilise hemicarbonate and at higher dosages monocarbonate plus ettringite, resulting in an increase of the total volume. The higher volume in the presence of a small amount of limestone due to the stabilization of ettringite has been found to have a positive effect on the mechanical properties of PC and blended cements [20,124]. \n\nThe stability of siliceous hydrogarnet was a matter of debate during the development of Cemdata07 and in most calculations with Cemdata07 the formation of siliceous hydrogarnet $\\mathrm{C_{3}A S_{0.8}H_{4.4}}$ had been suppressed assuming kinetic hindrance. Based on the data compiled in Cemdata07, which originated from measurements from [7,72,126], ettringite and siliceous hydrogarnet were calculated to be significantly more stable than monosulfate, hemi- or monocarboaluminate thus theoretically preventing their presence. Since monosulfate, hemi- and monocarboaluminate are experimentally observed in hydrated PC, it was assumed that this was due to a kinetic hindrance in the formation of siliceous hydrogarnet and that possibly a later conversion of hemi- and monocarboaluminate to siliceous hydrogarnet could occur. \n\nThe new data for $(\\mathrm{C}_{3}\\mathrm{A}_{0.5}\\mathrm{F}_{0.5}\\mathrm{S}_{0.84}\\mathrm{H}_{4.32})$ by Dilnesa et al. [9], included in Cemdata18, suggest that mixed Al- and Fe-containing siliceous hydrogarnet can coexist with monosulfate, hemi- and monocarboaluminate at ambient conditions, which is in better agreement with the observed experimental data presented in Fig. 12 and elsewhere [123–125]. Fig. 13B displays the predicted phase assemblage of a hydrated PC with limestone using Cemdata18 as given in Tables 1-4; employing CSHQ and $\\mathbf{M_{4}A H_{10}}$ . The formation of hemi- and monocarboaluminate accompanied by a stabilization of ettringite instead of monosulfoaluminate was correctly predicted by both datasets. As shown in Fig. 13 the biggest difference between the two datasets is the prediction of a katoite-type siliceous hydrogarnet phase $(\\mathrm{C}_{3}\\mathrm{A}_{0.5}\\mathrm{F}_{0.5}\\mathrm{S}_{0.84}\\mathrm{H}_{4.32})$ , modelled as solid solution with a varying alumina and iron by using Cemdata18, together with hemi- and monocarboaluminate and ettringite throughout the modelled composition range independently of the $\\mathsf{C a C O}_{3}$ content. \n\n![](images/94b7ff041449921449d583203b6fb13c0b26e813c23b2146b7d1fe7c130e786d.jpg) \nFig. 16. Calculated specific volume changes of a hydrated model mixture consisting of $\\mathrm{C}_{3}\\mathrm{A}$ , portlandite and with fixed sulfate ratio $(\\mathsf{S O}_{3}/\\mathsf{A l}_{2}\\mathsf{O}_{3}=1$ , molar bulk ratio) in dependence of changing calcite content at $25^{\\circ}\\mathrm{C}$ ; calculated using Cemdata18. \n\n![](images/12ded4d6a34518545e151f8a54ad23bd906544a6bcb18204607e4dedbadc360b.jpg) \nFig. 17. Calculated specific volume changes of a hydrated model mixture consisting of $\\mathrm{C}_{3}\\mathrm{A}$ , portlandite and with fixed sulfate ratio $(\\mathsf{S O}_{3}/\\mathsf{A l}_{2}\\mathsf{O}_{3}=1$ , molar bulk ratio) in dependence of changing calcite content at $25^{\\circ}\\mathrm{C}.$ ., as shown in Fig. 16 for the Systems A, B and C; calculated using Cemdata18. \n\nThe consideration of the siliceous hydrogarnet solid solution in Cemdata18 led to a quite significant redistribution of alumina and iron within the phase assemblage. Whereas with Cemdata07 around $70\\%$ of the available alumina was bound in AFm phases (see Fig. 14A) the predictions based on Cemdata18 suggest that only about $25\\%$ of alumina is bound in AFm phases and ${\\sim}30\\%$ in the hydrogarnet phase (Fig. 14B). For iron, the difference is even more drastic. The predictions with Cemdata18 suggest that close to $100\\%$ of the iron is bound by the siliceous hydrogarnet solid solution (Fig. 14D) which is also in agreement with experimental observations [64–66], where predominantly the formation of mixed aluminium and iron containing hydrogarnet phases in close proximity to the original ferrite phases was observed in hydrated cements. \n\nThe binding of alkalis in C-S-H lowers the alkali and hydroxide concentrations [81,84,88] in the pore solution of hydrated PC and thus the pH values from above 14 to ${\\sim}13$ to 13.5 [1,29,123,127]. The disregard of alkali binding by C-S-H would result in very high predicted pH values of 14 and above, which does not agree with measurements of the pore solution composition [5,29]. As in 2007 no thermodynamic models to describe the uptake of alkali in C-S-H were available, distribution coefficients $(\\mathrm{K_{d}}$ values) were used together with Cemdata07 in most calculations of hydrated cements as described in details e.g. in [1,29,123]. The use of distribution coefficient allowed predicting the alkali concentrations in PC relatively well as shown in Fig. 15A, but the approach was not adequate to predict alkali uptake in low Ca/Si C-S-H present in blended cements. $\\mathrm{K_{d}}$ values do not account for competitive sorption on specific sites as would be expected for the C-S-H gel, and also tend to be experiment-specific and so cannot generally be applied to other systems under different conditions. In the Cemdata18, the uptake of alkalis by C-S-H is modelled by introducing additional Na- and Kendmembers $\\mathrm{([(NaOH)_{2.5}S i O_{2}H_{2}O]_{0.2}}$ and $[(\\mathrm{KOH})_{2.5}\\mathrm{SiO}_{2}\\mathrm{H}_{2}\\mathrm{O}]_{0.2})$ in the CSHQ model, as described above (Section 2.7). The introduction of these provisional data simplify the modelling, as no additional $\\mathrm{K_{d}}$ values have to be introduced in the models, and allows the calculation of alkali uptake over the whole range of $\\mathrm{Ca}/\\mathrm{Si}$ ratios, although the agreement between measured and calculated alkali concentrations is only satisfactorily, as shown in Fig. 15B. Due to the lack of appropriate models for sodium and potassium uptake in C-S-H valid over the complete range of $\\mathrm{Ca}/\\mathrm{Si}$ , the modelling of alkali and hydroxide concentrations in the pore solution remains a challenge. \n\nThe trends in the concentrations of calcium, sulfate, silicon and aluminium are generally correctly reproduced by both models (see e.g. \n\n[1,29,123,127], Fig. 15) although there are differences between measured and calculated values, in particular for Ca and Al for Cemdata07 and for sulfate and silicon for Cemdata18. \n\n# 3.2. Effect of relative humidity on hydrated cements \n\nUsing the thermodynamic properties of phases with different water contents described in Section 2.5 and Table 1 it was possible to predict the drying behaviour of hydrated systems. \n\nDrying of the $\\mathrm{CaO-Al_{2}O_{3}–S O_{3}–C O_{2}–H_{2}O}$ was simulated because it is directly relevant to PC and limestone blended cements. The initial model mixture contained $\\mathrm{C}_{3}\\mathrm{A},$ portlandite (CH), calcium sulfate $(S O_{3}/\\$ $\\mathsf{A l}_{2}\\mathsf{O}_{3}=1\\mathsf{M}$ bulk ratio), and varying amounts of calcite at $25^{\\circ}\\mathrm{C}$ . The amount of solids was kept constant at $_{100g}$ and reacted with $90\\mathrm{g}$ water. A diagram of the specific volume changes of the hydrated mixture with respect to calcite content is shown in Fig. 16. \n\nDue to their differing AFm-AFt mineralogy hydrate phase assemblages A, B and C in Fig. 16, with $0\\%$ , $7\\%$ and $13.2\\%$ of calcite respectively, were selected as initial hydrated systems for the drying modelling. Drying was simulated by continuously removing water from the assemblages until a RH of zero was reached. The investigated systems were: \n\n- System A: monosulfoaluminate (Ms14) and portlandite (CH) \n- System B: ettringite (Ett32), hemicarboaluminate (Hc12) and portlandite (CH) \n- System C: ettringite (Ett32), monocarboaluminate (Mc11) and portlandite (CH) \n\nFig. 17a, b and c present the evolution of specific solid volume as a function of RH. We can see that dehydration happens stepwise at critical RH stability limits of the phase assemblages, representing invariant points where the RH is fixed due to phase rule restrictions. At this critical RH two hydration states of the same cement hydrate coexist and buffer the humidity in a similar manner as conventional drying agents. Another important finding is that the addition of calcite and the formation of carboaluminates and ettringite will enhance the dimensional stability of hydrated cement paste and makes it less sensitive to humidity fluctuations, which appears to be relevant for limestone blended cements. Due to the presence of monocarboaluminate and ettringite system C is the most stable phase assemblage, which only decomposes at very low humidities (below $2\\%$ RH) whereas monosulfoaluminate quickly loses part of its interlayer water at $<99\\%$ RH. \n\nSomething important to keep in mind is that, although experimentally we observe the changes shown in Fig. 17, several of these dehydration processes are metastable with respect to other phase assemblages. This has to be considered when predicting the drying behaviour of cementitious systems. \n\n# 4. Conclusions \n\nThe Cemdata18 database summarised in this paper can reliably calculate the type, composition, amount and volume of hydrates formed and the pH and composition of the pore solution during hydration and degradation of cementitious systems. The Cemdata18 database, as compiled in Table 1 to Table 4, includes carefully selected thermodynamic data published in the literature based on critical reviews supplemented with new experimental data. Data for solids commonly encountered in cement systems in the temperature range $0{-}100^{\\circ}\\mathrm{C}$ , including C-S-H, M-S-H, hydrogarnet, hydrotalcite-like phases, some zeolite, AFm and AFt phases and their respective solid solutions has been compiled. The Cemdata18 database is an update of the Cemdata07 and Cemdata14 databases, and is compatible with the GEMS version of the PSI/Nagra 12/07 TDB [22,23]. Cemdata18 TDB is freely downloadable (http://www.empa.ch/cemdata) in formats supporting the computer programs GEM-Selektor [13,14] and PHREEQC [18]. Further details are available in Appendices A and B. \n\nThe most important additions to the Cemdata18 TDB include: \n\n# • C-S-H: \n\n- CSHQ model for Portland and blended cements, the uptake of alkalis by C-S-H is modelled by additional Na- and K-containing end members - CSH3T model that corresponds to pure defect-tobermorite structure with ordering at Ca/Si ratio close to 1.0, and forms the basis for CNASH-ss model - C-(N-)A-S-H model for alkali activated materials (CNASH-ss), which calculates the uptake of aluminium and sodium in low Ca/Si C-S-H \n• iron-containing hydrates, in particular for the mixed Fe-Al-hydrogarnet solid solution, $\\mathrm{C_{3}F S_{0.84}H_{4.32}–C_{3}A_{0.5}F_{0.5}S_{0.84}H_{4.32}}$ , which takes up iron and a part of the aluminium in hydrated cements \n• AFm and AFt-phases with different water contents to describe the effect of water activity and drying on hydrates \n• amorphous, microcrystalline $\\mathrm{AH}_{3}$ and gibbsite to study the effect of $\\mathrm{AH}_{3}$ solubility on the hydrates in calcium aluminate and calcium sulfoaluminate cements \n• chloride, nitrate and nitrate-containing AFm phases \n• thaumasite and the uptake of carbonates in $S O_{4}$ -ettringite. \n• description of the variation in $\\mathrm{Mg/Al}$ in layered double hydroxides (hydrotalcite-like phases) observed in alkali activated materials \n• data for M-S-H and some Na- and Ca-based zeolites, which can form at the interaction zone of cement with clays, rocks or seawater and in alkali activated materials. \n\nThese additions improve the reliability of thermodynamic modelling of cement systems, in particular for alkali activated materials and for processes at cement/environment interfaces, where hydrates such as thaumasite, Friedel's salt, M-S-H, and zeolites may form. \n\nThe consideration of siliceous hydrogarnet solid solution in Cemdata18 leads to a quite significant redistribution of alumina and iron within the phase assemblage in PC; the predictions based on Cemdata18 suggest that alumina is bound not only in AFt, AFm phases and hydrotalcite but also in siliceous hydrogarnet phase while all hydrated iron is present in siliceous hydrogarnet. \n\nSeveral C-S-H solubility models as well two models for hydroxidehydrotalcite are available (Table 4, Appendices A and B). The CSHQ and the OH-hydrotalcite with $\\mathbf{M}\\mathbf{g}/\\mathbf{A}\\mathbf{l}=2$ are well adapted for PC systems. Although CSHQ is able to describe the entire range of $\\mathrm{Ca}/\\mathrm{Si}$ ratios encountered, it is best used for high Ca/Si C-S-H as it lacks the ability to predict aluminium uptake, however, this is less important in PC where the aluminium content is relatively low. For alkali activated binders, the CNASH model has been developed for C-S-H type calcium (alkali) aluminosilicate hydrate gels with lower calcium but higher aluminium and alkali content. An Mg-Al layered double hydroxide model with variable $\\mathrm{Mg/Al}$ ratio is also available for use in alkali activated cement systems. \n\nDespite significant additions to the Cemdata18 TDB, several important gaps still exist in the database. In particular, reliable thermodynamic data for alkali, aluminium and water uptake in C-S-H applicable to high and low Ca/Si C-S-H and M-S-H, data for hydrotalcite-like phases of variable composition and for different interlayer ions, data for further zeolites derived from experimental solubility measurements, data for aqueous complexes which possibly form at high pH values as well as data for the reaction products of alkali silica reaction are needed. However, these data gaps should be viewed as possible future improvements rather than barriers to use thermodynamic modelling: Cemdata18 database has already been successfully applied to model hydrated PC, calcium aluminate, calcium sulfoaluminate and blended cements, and also alkali activated materials. Cemdata18, therefore, enables improved characterisation and understanding of the chemistry and related in-service performance properties of a wide range of cement systems, including the most common types. \n\n# Acknowledgements \n\nThe partial financial support from the NANOCEM consortium (www.nanocem.org), the Swiss National Foundation (SNF grants No. 117605, 132559, 130419 and 200021_169014), from Nagra, Wettingen, Switzerland, and from the BMBF ThermAc3 Verbundprojekt (Germany) are gratefully acknowledged. The authors thank also Tres Thoenen, Ravi Patel and Andres Idiart for their support on the PHREEQC version. \n\n# Appendix A. Cemdata18 dataset in GEMS format \n\nCemdata18 database in GEM-Selektor v.3 format can be freely downloaded (http://www.empa.ch/cemdata) and is fully compatible with the GEMS version of the PSI/Nagra 12/07 TDB [22,23] (http://gems.web.psi.ch). As several alternative C-S-H models, as well as two models for hydroxide-hydrotalcite are available, the user needs to select the appropriate models during the generation of new projects, as illustrated in Fig. A.1. The CSHQ and the OH-hydrotalcite with $\\mathbf{M}\\mathbf{g}/\\mathbf{A}\\mathbf{l}=2$ are well adapted for Portland cement systems (select cemdata, pc, ht. and cshq as indicated at the left hand side of Fig. A.1). \n\nFor alkali activated binders, the CNASH model has been developed for C-S-H type calcium (alkali) aluminosilicate hydrate gels with lower calcium but higher aluminium and alkali content. An Mg-Al layered double hydroxide model with variable $\\mathrm{Mg/Al}$ ratio is also available for use in alkali activated cement systems. For alkali activated binders, the selection of cemdata and aam and deselection of pc, including ht and csh is recommended as illustrated at the right hand side of Fig. A.1. \n\n
Built-in DatabaseVersionBuilt-in Database Version
support template supcrtsupport template
申psi-nagrasupcrt
cemdata 3rdpartypsi-nagra
3rdparty
白cemdata 18.01
pcpc 18.01
ht.ht
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cshq18.01 cshq
口 cshkn
cshkn 18.01
csh3t
18.01
口 csh2o 18.01
csh2o 口 aam白 aam 18.01
csh+ht
csh+ht 18.01
SSss
ss-fe318.01
18.01
ss-fe3
\n\n![](images/af20e5cbd6942f36c3c1bc70018318bedb4fdadef510a6a6057f7a3fd4f25c33.jpg) \n\n# Appendix B. Cemdata18 dataset in PHREEQC format \n\nTo enable users to model cementitious systems using the Cemdata18 dataset with the popular PHREEQC geochemical speciation code [18], a PHREEQC “.dat” format database of the Cemdata18 dataset (CEMDATA18.dat) is provided for download from http://www.empa.ch/cemdata. This LMA (Law of Mass Action) type dataset has been generated using the reaction generator module of the ThermoMatch code (Miron et al. in preparation) and exported into the PHREEQC format “.dat” file using the ThermoMatch database export module. The reaction generator algorithm is based on the matrix “row reduce” method described by Smith and Missen [128]. In this process, all aqueous and solid species from the Cemdata18 GEM-Selektor database were considered. The supplementary data for aqueous, gaseous and solid species corresponding to the list of elements covered by Cemdata18 were selected from the GEMS version of the PSI/Nagra TDB [22,23]. The latter and the Cemdata18 GEM database are mutually consistent, and should be used together in GEMS codes for modelling cementitious systems. \n\nTo generate PHREEQC-style reactions for product species, firstly the following master species were selected based on their generic predominance: $\\mathrm{Ca}^{+2}$ , $\\mathbf{M}\\mathbf{g}^{+2}$ , $S\\mathrm{r}^{+2}$ , $\\mathrm{{Na}^{+}}$ , $\\mathrm{K^{+}}$ , $\\mathrm{H^{+}}$ , $\\mathrm{CO_{3}}^{-2}$ , ${S O_{4}}^{-2}$ , $\\mathbf{Cl}^{-}$ , ${\\mathrm{NO}}_{3}{}^{-}$ , $\\mathsf{A l O}_{2}^{-}$ , $\\mathrm{FeO}_{2}{}^{-}$ , $\\mathrm{SiO}_{2}^{\\ 0}$ , $\\mathrm{H}_{2}\\mathrm{O}^{0}$ , and $\\mathtt{e}^{-}$ (electron). Using selected master species, the reactions were automatically generated for the remaining (product) species, and their properties at $25^{\\circ}\\mathrm{C}$ and 1 bar were calculated. Formation reactions were generated for aqueous product species, and dissolution reactions - for gaseous and solid product species. The LMA dataset of reactions was then exported into a PHREEQC “dat” file (CEMDATA18.dat) using the ThermoMatch database export module. Parameters for the $\\log\\mathrm{K^{o}}=\\mathrm{f(T)}$ analytical expressions were calculated for the 3-term extrapolation method that assumes the $\\Delta_{\\mathrm{{r}}}C p^{\\mathrm{{o}}}$ to be not zero and independent of temperature. These reported parameters are used by PHREEQC for calculating the $\\mathrm{log}_{10}K^{\\mathrm{o}}$ as a function of temperature. Such temperature extrapolations of $\\mathrm{log}_{10}K^{\\mathrm{o}}$ should be valid at least up to $100^{\\circ}\\mathrm{C}$ . \n\nTable B.1 contains the generated formation reactions for the aqueous product species, together with the values for reaction standard effects at $25^{\\circ}\\mathrm{C}$ and 1 bar. Table B.2 contains the generated dissolution reactions for gaseous and solid product species, together with the reaction standard effects at $25^{\\circ}\\mathrm{C}$ and 1 bar. Table B.2 contains, in addition to the Cemdata18 database as detailed in Table 1 to Table 4, also the thermodynamic data of all solids composed of Al, C, Ca, Cl, Fe, H, K, Mg, N, Na, S, Si or Sr compiled in the GEMS version of the PSI/Nagra 12/07 TDB [22,23], needed to allow the generation of a compatible dataset in PHREEQC. Figs. B.1, B.2, and B.3 show comparisons of cement-related modelling problems between GEM-Selektor (using GEM-type Cemdata18) and PHREEQC (using LMA-type Cemdata18 CEMDATA18.dat). For the PHREEQC calculations, PHREEQC for Windows version 2.18.00 (uses PHREEQC-2 source version 2.18.3-5570) was used. In all three cases, the considered solid solutions were modelled in PHREEQC using the simple ideal mixing model. \n\n(continued on next page) \nProduct aqueous species reactions from master species, together with their reaction properties at 25 °C and 1 bar. \n\n\n
Product SubstanceReactionl0g10K298AG298 [J/mol] ,H298 [J/mol]S298 [J/K/mol]△.CP298 [J/K/mol]AV298 [J/bar]
Al(S04)+S|6|O4-2 + AlO2- + 4H + = Al(SO4)+ + 2H20@26.8- 152,857-159,164-21.2261.80.8
Al(S04)2-2S|6|O4-2 + AlO2- + 4H + = Al(SO4)2-+ 2H2O@28.8-164,272-165,197-3.1463.63.2
Al+3AlO2-+ 4H + = Al+3 + 2H2O@22.9-130,595-176,821-155.071.1-1.9
AlHSi03+2AlO2-+ 3H+ + SiO2 = AlHSiO3+2 + H2O20.5- 116,839- 106,76433.8-1363.3
AlO+AlO2-+ 2H+ = AlO+ + H2O@12.3-70,124-73,951-12.8-0.70.9
Al02H@AlO2-+ H+ = AlO2H@6.4-36,798-21,55451.1-160.20.4
AlOH+2AlO2-+ 3H+ = Al(OH)+ 2 + H2O@17.9-102,299-127,582-84.8180.4
AlSi05-3AlO2-+ H2O@ + SiO2@ = AlSi05-3 + 2H+-22.6129,05971,975-191.50.00.6
Ca(C03)@C03-2 + Ca+2 = CaC03@3.2-18,40516,462116.9196.4-7.8
Ca(HCO3)+CO3-2 + Ca+2 + H+ = Ca(HCO3)+11.4-65,269-13,562173.4554.00.9
Ca(HSi03)+Ca+2 + H2O@ + SiO2@ = Ca(HSiO3)+ + H+-8.649,14330,328-63.148.93.8
Ca(S04)@Ca+2 + S|6|04-2 = CaSO4@2.3-13,128433658.6192.4-2.2
CaOH+Ca+2 + H2O@ = Ca(OH)+ + H+-12.872,95077,30114.6-38.41.0
CaSi03@Ca+2+ H20@ + SiO2@ = CaSi03@ + 2H+-18.5105,82748,743-191.50.00.6
CH4@CO3-2 + 8e- + 10H+ = C|-4|H4@ + 3H20@38.2- 217,923- 270,138-175.1677.3-1.6
Cl04-Cl- + 4H2O@ = Cl|7|O4- + 8e- + 8H+-187.71,071,5001,181,308368.3-87.69.8
CO2@C03-2 + 2H + = C02@ + H20@16.7-95,216-24,408237.5607.8-4.6
Fe(C03)@CO3-2 + e-+ 4H+ + Fe|3|O2- = FeCO3@ + 2H20@39.0-222,615-216,14421.7537.55.7
Fe(HCO3)+CO3-2 + e-+ 5H+ + Fe|3|O2- = FeHCO3+ + 2H2O@46.9- 267,988-246,73571.3892.02.5
Fe(HSO4)+S|6|O4-2 + e- + 5H+ + Fe|3|O2-= FeHSO4+ + 2H2O@37.7-215,125- 208,70421.5975.65.0
Fe(HSO4)+2S|6|O4-2 + 5H+ + Fe|3|O2- = Fe|3|HSO4+2 + 2H2O@26.1- 148,798- 200,163-172.31078.54.2
Fe(S04)@S|6|O4-2 + e- + 4H+ + Fe|3|O2- = Fe(SO4)@ + 2H2O@36.9-210,456-212,106-5.5535.72.5
Fe(S04)+S|6|04-2 + 4H+ + Fe|3|O2-= Fe|3|(SO4)+ + 2H20@25.6-146,355-160,671- 48.0505.82.4
Fe(S04)2-2S|6|O4-2 + 4H+ + Fe|3|O2- = Fe|3|(SO4)2-+ 2H2O@27.0-154,003-162,930-29.9707.52.0
Fe+2e- + 4H+ + Fe|3|O2-= Fe+2 + 2H2O@34.6-197,613- 220,183-75.7338.84.0
Fe+34H+ + Fe|3|O2-= Fe|3|+3 + 2H2O@21.6-123,295-177,529-181.9308.91.3
FeHSiO3+2FeO2-+ 3H+ + SiO2 = Fe|3|HSiO3+2 + H2O@21.5-122,665-148,472-86.5101.9-0.2
FeCl+Cl-+e-+ 4H+ + Fe|3|O2- = FeCl+ + 2H2O@34.8-198,413- 218,887- 68.7580.23.5
FeCl+2Cl- + 4H+ + Fe|3|O2- = Fe|3|Cl+2 + 2H2O@23.1-131,742-173,502-140.1523.01.9
FeCl2+2Cl- + 4H+ + Fe|3|O2-= Fe|3|Cl2+ + 2H2O@23.7-135,453- 179,471-147.6931.3-0.5
FeCl3@3Cl- + 4H+ + Fe|3|O2-= Fe|3|Cl3@ + 2H2O@22.7-129,649- 190,999-205.81121.31.1
FeO+2H+ + Fe|3|O2-= Fe|3|O+ + H2O@15.9- 90,930-97,152-20.9109.32.0
Fe02H@H+ + Fe|3|02- = Fe|3|02H@9.0-51,601- 37,13048.5-77.2-2.4
FeOH+e- + 3H+ + Fe|3|O2- = FeOH+ + H2O@25.1-143,387-167,718-81.6358.90.7 0.1
FeOH+23H+ + Fe|3|O2-= Fe|3|(OH)+2 + H2O@19.4-110,794-134,855-80.7276.6-0.8
Fe2(OH)2+4 Fe3(OH)4+52FeO2- + 6H + = Fe|3|2(OH)2+4 + 2H2O@40.3 58.5- 229,747 -333,918- 298,572 472,753- 230.8 465.6617.9 926.87.5 7.6
\n\nTable B.1 (continued) \n\n\n
Product SubstanceReactionl0g10K298AG298 [J/mol] H298 [J/mol]S298 [J/K/mol]△CP298 [J/K/mol]V298 [J/bar]
H2@2e-+ 2H+ = H|0|2@-3.117,729-4018-72.9138.02.5
H2S@S|6|O4-2 + 8e- + 10H+ = H2S|-2|@ + 4H2O@40.7-232,203- 272,852-136.3631.49.4
HCN@CO3-2 + NO3-+ 10e- + 13H+ = HC|-1|N|0|@ + 6H20@117.4- 669,854-729,336-199.5664.18.6
HC03-CO3-2 + H+ = HCO3-10.3-58,959- 14,699148.4254.53.0
HS-S|6|O4-2 + 8e- + 9H+ = HS|-2|- + 4H2O@33.7-192,305- 250,044-193.7358.38.0
HSi03-H20@ + SiO2@ = HSi03-+ H+-9.855,99229,057-90.3- 207.0-3.0
HS03-S|6|O4-2 + 2e- + 3H+ = HS|4|O3- + H20@3.8-21,822-388560.2307.23.8
HSO4-S|6|04-2 + H+ = HS|6|04-2.0-11,34620,464106.7288.82.2
K(SO4)-S|6|04-2 + K+ = KSO4-0.9-4851307026.6212.60.6
KOH@H2O@ + K+ = KOH@ + H+-14.582,53863,874-62.6- 168.8-1.2
Mg(C03)@C03-2 + Mg+2 = Mg(C03)@3.0-17,009912487.7194.51.1
Mg(HCO3)+CO3-2 + Mg + 2 + H+ = Mg(HCO3)+11.4-65,056-12,725175.5565.43.7
Mg(HSi03)+Mg+2 + H2O@ + SiO2@ = Mg(HSiO3)+ + H+-8.347,42925,758-72.760.5-2.3
MgOH+Mg+2 + H2O@ = Mg(OH)+ + H+-11.465,30061,792-11.875.50.6
MgSi03@Mg+2 + H2O + SiO2 = MgSiO3@ + 2H+-17.499,54885,125-48.4-363.01.0
Mgs04@S|6|04-2 + Mg + 2 = Mg(SO4)@2.4-13,529685568.4197.41.1
N2@2N03-+ 10e-+ 12H + = N|0|2@ + 6H2O@207.3-1.183,095-1.311,876- 431.9675.78.4
Na(CO3)-CO3-2 + Na+ = NaCO3-1.3-7251-22,969-52.7199.90.7
Na(HCO3)@CO3-2 + Na+ + H+ = NaHCO3@10.1- 57,533-13,909146.3451.54.0
Na(S04)-S|6|O4-2 + Na + = Na(SO4)-0.7-3996331424.5197.90.7
NaOH@Na+ + H2O@ = NaOH@ + H+-14.280,94056,026-83.6-126.9-1.3
NH3@ NO3-+ 8e-+ 9H + = N|-3|H3@ + 3H20@109.9- 627,314-732,284-352.1254.45.0
NH4+NO3- + 8e- + 10H + = N|-3|H4+ + 3H2O@119.1- 680,039-784,011-348.7244.64.4
02@2H20@ = O|0|2@ + 4e-+ 4H+-86.0490,812559,525230.5141.1-0.6
OH-H20@ = OH-+ H+-14.079,91355,872-80.6-211.7-2.3
S-2S|6|O4-2 + 8e- + 8H + = S|-2|-2 + 4H2O@14.7- 83,851- 250,044-557.4358.35.9
S203-22S|6|04-2 + 8e- + 10H + = S|2|203-2 + 5H2O@38.0- 216,987-259,866-143.8555.29.2
SCN-CO3-2 + NO3- + S|6|O4-2 + 16e- + 20H + = S|0|C|0|N|-1|- + 10H2O@156.9-895,711- 990,513-318.01105.518.1
Si4010-42H20@ + 4Si02@ = Si4010-4 + 4H+207,202207,2020.00.0-10.0
Si03-2H2O@ + Si02@ = Si03-2 + 2H+-36.3132,08475,000-191.50.0
S03-2S|6|04-2 + 2e-+ 2H+ = S|4|03-2 + H2O@- 23.119,390-13,070-108.931.6-3.4
Sr(C03)@-3.4-16,01318,891117.1196.60.1 0.9
Sr(HC03)+CO3-2 + Sr+2 = Sr(C03)@ CO3-2 + Sr+2 + H+ = SrHCO3+2.8-65,721-12,816177.4541.0
Sr(S04)@S|6|04-2 + Sr+2 = Sr(SO4)@11.5 2.3-13,072907174.3197.13.8
SrOH+Sr+2 + H2O@ = Sr(OH)+ + H+-13.375,86082,61922.7-65.51.0
SrSi03@Sr+2 + H2O@ + SiO2@ = SrSiO3@ + 2H+-18.8107,136107,1840.20.10.7 0.0
\n\n|| - is used for specifying a different valence for the element.@ - is used to represent a neutral aqueous species. \n\nTable B.2Product solid and gaseous species reactions from master species, together with their reaction properties at 25 °C and 1 bar. \n1 \n\n\n
298 [5/on] [J/10n] [J/R] [J/R] 298 m
mol]mol][J/ bar]
5CA(CaO)1.25(Si02)1(Al203)0.125(H20)1.625 + 2.25H+ = 0.25Al02- + 1.25Ca+2 + 2.75H20@ + Si02@ 15.9-90709-92987 -7.623.7-1.2
5CNA(CaO)1.25(Si02)1(Al203)0.125(Na20)0.25(H20)1.375 + 2.75H+ = 0.25AlO2- + 1.25Ca+2 + 0.5Na+ + 23.2-132663-135750-10.443.6-2.0
AlOHam2.75H20@ + Si02@ Al(OH)3 = AlO2- + H+ + H2O@-13.87853669482 -30.4-66.8-0.4
AlOHmicAl(OH)3 = Al02- + H+ + H2O@-14.78373053830 -100.3-66.8-0.4
Amor-SlSi02 = Si02@-2.71549215492 0.00.0-1.3
AnhCaSO4 = Ca+2 + S|6|04-2-4.424872-18165 -144.3-396.7-5.1
ArgCaCO3 = CO3-2 + Ca+2-8.347583 -11060-196.7-401.5-5.9
BrcMg(OH)2 + 2H+ = Mg+2 + 2H20@ 16.8-96124 -114419-61.451.8-1.1
C12A7(CaO)12(Al203)7 + 10H+ = 14Al02-+ 12Ca+2 + 5H2O@167.2-954361-1489798 -1795.9-1765.7-51.6
C2ACIH5Ca2AlCl(OH)6(H2O)2 + 2H+ = AlO2- + 2Ca+2 + Cl- + 6H2O@14.4-82445 -92106-32.4-195.7-3.8
C2AH65Ca2Al(OH)7(H2O)3 + 3H+ = Al02-+ 2Ca+2 + 8H2O@29.4-167699-167567 0.4-79.0-2.0
C2AH7.5Ca2Al2(OH)10(H2O)2.5 + 2H+ = 2AlO2-+ 2Ca+2 + 8.5H2O@14.2-81085-89743 -29.0-55.2-4.4
C2S(CaO)2Si02 + 4H+ = 2Ca+2 + 2H20@ + Si02@38.5-219567-237276 -59.44.7
C3A(CaO)3Al203 + 4H+ = 2Al02-+ 3Ca+2 + 2H2O@-403436-491527 -295.5-249.5-3.6
C3AFS0.84H4.3270.7-215980 -297.8-286.9-8.9
Fe|3|02-(AlFe|3|03)[Ca303(Si02)0.84(H2O)4.32] + 4H+ = AlO2- + 3Ca+2 + 6.32H2O@ + 0.84Si02@ +22.3-127203-6.3
C3AH6Ca3Al206(H20)6 + 4H+ = 2Al02- + 3Ca+2 + 8H20@35.5-202666-230152 -92.2-33.6-4.2
C3AS0.41H5.18Ca3Al206(Si02)0.41(H20)5.18 + 4H+ = 2Al02- + 3Ca+2 + 7.18H2O@ + 0.41Si02@28.9-165175-197973 -110.0-61.6-4.6
C3AS0.84H4.32Ca3Al206(Si02)0.84(H2O)4.32 + 4H+ = 2Al02- + 3Ca+2 + 6.32H20@ + 0.84Si02@25.8-147182-185475 -128.4-90.9-5.1
C3FH6Ca3Fe 13| 206(H20)6 + 4H+ = 3Ca+2 + 8H20@ + 2Fe|3|O2-29.7-169558-286244 -391.4-426.6-6.5
C3FS0.84H4.32(Fe|3|Fe|3|O3)[Ca303(Si02)0.84(H2O)4.32] + 4H+ = 3Ca+2 + 6.32H2O@ + 0.84Si02@ + 2Fe|3|02-20.0-114074-246486 -444.1-482.9-7.5
C3FS1.34H3.32Ca3Fe|3|206(Si02)1.34(H20)3.32 + 4H+ = 3Ca+2 + 5.32H2O@ + 1.34Si02@ + 2Fe|3|02-16.2-92409-233544 -473.4-516.4-8.5
C3S(CaO)3SiO2 + 6H+ = 3Ca+2 + 3H2O@ + SiO2@73.3-418180-444107 -87.06.2-5.8
C4AClH10Ca4Al2Cl2(OH)12(H2O)4 + 4H+ = 2Al02- + 4Ca+2 + 2Cl- + 12H20@28.9-164890-184212 -64.8-391.5-7.6
C4AF(CaO)4(Al203)(Fe|3|203) + 4H+ = 2Al02-+ 4Ca+2 + 2H2O@ + 2Fe|3|02-50.5-288060-402597 -384.2-937.0
C4AH11Ca4Al2(OH)14(H20)4 + 6H+ = 2Al02- + 4Ca+2 + 14H20@60.5-345302-369182 -80.1-228.6-14.8
C4AH13Ca4Al2(OH)14(H20)6 + 6H+ = 2Al02- + 4Ca+2 + 16H20@58.8-335407-335144 0.9-158.0-5.9
58.6 -334271-294932 5357.3-4.0
C4AH1H12Ca4A12((4ACI054132.0-2.6
C4FH13Ca4Fe|3|2(OH)14(H2O)6 + 6H+ = 4Ca+2 + 16H20@ + 2Fe|3|02-53.3-304002 -199193351.5-343.7
CACaOAl203 = 2Al02- + Ca+2-0.3 1756-67154-231.1-254.7-7.0
CA2CaO(Al203)2 + H20@ = 4Al02-+ Ca+2 + 2H+-30.1171600 44867-425.1-502.0-5.3 -8.8
CAH10CaOAl203(H20)10 = 2Al02-+ Ca+2 + 10H20@-7.643348 35098-27.7-43.2-1.3
Cal CaCO3 = CO3-2 + Ca+2-8.548404 -10975-199.2-402.1-6.1
CH4C|-4|H4 + 3H2O@ = CO3-2 + 10H+ + 8e--41.0234277 25714276.7-435.8
ClsSrSO4 = S|6|O4-2 + Sr+2-6.637855 -854-129.8-415.5Cement and Concrete Research xx -5.1
\n\n(continued on next page) \nTable B.2 (continued) \n\n\n
Product SubstanceReaction298 l0810°[J/mol] ArG 298AH 298 [J/mol]Ar$ 298 [J/K/ArCP 298 [J/K/ 298 Ar
mol]mol][/ bar]
CO2CO2 + H2O@ = CO3-2 + 2H+-18.11035604079-333.7-401.8
CSH3T-T2C(CaO)0.75(Si02)0.5(H20)1.25)2 + 3H+ = 1.5Ca+2 + 4H20@ + SiO2@25.3-144257-12357469.462.5-2.0
CSH3T-T5C((CaO)1(Si02)1(H20)2)1.25 + 2.5H+ = 1.25Ca+2 + 3.75H20@ + 1.25Si02@18.1-103538-7867683.465.4-1.4
CSH3T-TobH(CaO)1(Si02)1.5(H20)2.5 + 2H+ = Ca+2 + 3.5H20@ + 1.5Si02@12.5-71524-4246397.568.4-1.6
CSHQ-JenD(CaO)1.5(Si02)0.6667(H20)2.5 + 3H+ = 1.5Ca+2 + 4H20@ + 0.6667Si02@28.7-164004-14935749.151.9-2.6
CSHQ-JenH(CaO)1.3333(Si02)1(H20)2.1667 + 2.6666H+ = 1.3333Ca+2 + 3.5H20@ + SiO2@22.2-126609-10625868.359.1-2.1
CSHQ-TobD(CaO)1.25(Si02)1(H20)2.75)0.6667 + 1.66675H+ = 0.833375Ca+2 + 2.6668H20@ + 0.6667SiO2@13.7-77952-6448845.237.9-0.4
CSHQ-TobH(CaO)0.6667(Si02)1(H2O)1.5 + 1.3334H+ = 0.6667Ca+2 + 2.1667H20@ + SiO2@8.3-47306-2784265.345.5-1.2
Dis-DolCaMg(C03)2 = 2CO3-2 + Ca+2 + Mg+2-16.594412-43108-461.2-789.0-11.7
ECSH1-KSH(KOH)2.5Si02H2O)0.2 + 0.5H+ = 0.7H2O@ + 0.2Si02@ + 0.5K+5.5-31394-1370359.325.20.8
ECSH1-NaSH(NaOH)2.5Si02H20)0.2 + 0.5H+ = 0.5Na+ + 0.7H2O@ + 0.2Si02@5.4-30883-1739845.242.80.5
ECSH1-SH(SiO2H20)1 = H20@ + Si02@-2.614839148390.00.00.0
ECSH1-SrSH(Sr(OH)2)1Si02H2O)1 + 2H+ = Sr+2 + 3H20@ + Si02@15.4-87911-6474477.754.2-1.1
ECSH1-TobCa(Ca(OH)2)0.8333Si02H20)1 + 1.6666H+ = 0.8333Ca+2 + 2.6666H2O@ + SiO2@11.0-62909-4319466.149.3-1.9
ECSH2-JenCa((Ca(OH)2)1.6667Si02H20)0.6 + 2.00004H+ = 1.00002Ca+2 + 2.60004H2O@ + 0.6Si02@17.6-100489-7749577.177.20.2
ECSH2-KSH(KOH)2.5Si02H2O)0.2 + 0.5H+ = 0.7H20@ + 0.2Si02@ + 0.5K+6.0-34250-1655959.325.20.8
ECSH2-NaSH((NaOH)2.5SiO2H2O)0.2 + 0.5H+ = 0.5Na+ + 0.7H2O@ + 0.2SiO2@5.9-33732-2024745.242.80.5
ECSH2-SrSH(Sr(OH)2)1SiO2H2O)1 + 2H+ = Sr+2 + 3H20@ + Si02@16.2-92473-6930677.754.2-1.1
ECSH2-TobCa(Ca(OH)2)0.8333Si02H20)1 + 1.6666H+ = 0.8333Ca+2 + 2.6666H20@ + Si02@11.0-62909-4319466.149.3-1.9
ettringite(H20)2)Ca6Al2(SO4)3(OH)12(H20)24 + 4H+ = 2AlO2- + 6Ca+2 + 3S|6|O4-2 + 34H20@11.2-63708-23594134.5-694.0-14.6
ettringite03_ss(SO4)Ca2Al0.6666667(0H)4(H20)8.6666667 + 1.333332H+ = 0.666667Al02- + 2Ca+2 + S|6|04-2 + 3.7-21231-786044.8-231.3-4.9
ettringite0511. 3333333H20@ Ca3Al(S04)1.5(OH)6(H2O)13 + 2H+ = AlO2- + 3Ca+2 + 1.5S|6|O4-2 + 17H2O@5.6-31852-1179567.3-347.0-7.3
ettringite13Ca6Al2(S04)3(OH)12(H2O)7 + 4H+ = 2Al02- + 6Ca+2 + 3S|6|O4-2 + 15H20@39.0-222527-596572-1254.6-1364.4-19.3
Ettringite13_desCa6Al2(S04)3(OH)12(H2O)7 + 4H+ = 2AlO2- + 6Ca+2 + 3S|6|O4-2 + 15H2O@39.0-222527-596572-1254.6-1364.4-19.3
ettringite30Ca6Al2(SO4)3(OH)12(H2O)24 + 4H+ = 2AlO2- + 6Ca+2 + 3S|6|O4-2 + 32H2O@11.8-67136-36633102.3-764.6-18.3
ettringite9Ca6Al2(S04)3(OH)12(H2O)3 + 4H+ = 2AlO2- + 6Ca+2 + 3S|6|O4-2 + 11H2O@48.0-273943-339631-220.3-1505.6-21.5
Ettringite9_desCa6Al2(S04)3(OH)12(H2O)3 + 4H+ = 2AlO2- + 6Ca+2 + 3S|6|O4-2 + 11H2O@48.0-273943-339631-220.3-1505.6-21.5
FeFe|0| + 2H2O@ = 4H+ + 3e- + Fe|3|O2--18.610610912794773.2-367.4-4.3
Fe-ettringiteCa6Fe|3|2(SO4)3(OH)12(H2O)26 + 4H+ = 6Ca+2 + 3S|6|O4-2 + 34H20@ + 2Fe|3|02-12.1-688434803247.0-1091.4-17.4
Fe-ettringite05Ca3Fe|3|(S04)1.5(OH)6(H2O)13 + 2H+ =3Ca+2 + 1.5S|6|O4-2 + 17H2O@ + Fe|3|02-6.0-344202403123.5-545.7-8.7
Fe-hemicarbonateCa303Fe|3|203(CaCO3)0.5(Ca02H2)0.5(H20)9.5 + 5H+ = 0.5C03-2 + 4Ca+2 + 12.5H20@ +39.2-223627-390054-558.2-637.4-12.3
Femonocarbonate2Fe|3|02-21.4-252941-438.3
Fe-monosulph05Ca4O4Fe|3|203C02(H2O)12 + 4H+ = CO3-2 + 4Ca+2 + 14H20@ + 2Fe|3|O2-12.2-122258 -69792-154688-284.7-778.2-11.8
Fe-monosulphateCa2Fe|3|S0.5O5(H2O)6 + 2H+ = 2Ca+2 + 0.5S|6|O4-2 + 7H2O@ + Fe|3|02-24.5-139576-309368-569.5-386.3 -772.7-6.4
FeOOHmicCa4Fe|3|2S010(H2O)12 + 4H+ = 4Ca+2 + S|6|O4-2 + 14H2O@ + 2Fe|3|02--19.611187565468-155.7-309.3-12.8
GbsFe|3|OOH = H+ + Fe|3|O2- Al(OH)3 = Al02- + H+ + H20@-15.18632377269-30.4-66.8-3.4 -0.4
\n\n(continued on next page) \nTable B.2 (continued) \n\n\n
Product Substance Reactionl0g10° 298AG 298 [J/mol] AH 298 [J/mol]Ar$ 298 [J/K/ACP 298 Ar [J/K/298
mol]mol][J/ bar]
GpCaSO4(H20)2 = Ca+2 + S|6|O4-2 + 2H20@-4.626147-1167-91.6-332.5-4.4
GrC|O|+ 3H2O@ = CO3-2 + 6H+ + 4e--32.2183569182332-4.1-466.4-6.6
GtFe|3|O(OH)= H+ + Fe|3|O2--22.6128995124419-15.4-309.2-2.0
H2H|0|2 = 2H+ + 2e-0.0000.00.0
H20H20 = H20@1.5-8500-43481-117.335.3
H2SH2S|-2| + 4H2O@ = S|6|O4-2 + 10H+ + 8e--41.723774225445856.1-486.4
HemFe|3|2O3 + H2O@ = 2H+ + 2Fe|3|O2--42.1240195219672-68.8-650.0-4.7
hemicarbonat10.5(CaO)3Al203(CaC03)0.5(CaO2H2)0.5(H2O)10 + 5H+ = 2AlO2- + 0.5CO3-2 + 4Ca+2 + 13H20@42.6-243220-264276-70.6-232.4-8.4
hemicarbonate(CaO)3Al203(CaCO3)0.5(CaO2H2)0.5(H2O)11.5 + 5H+ = 2Al02-+ 0.5CO3-2 + 4Ca+2 + 14.5H2O@40.9-233337-236348-10.1-179.5-8.0
hemicarbonate9(CaO)3Al203(CaCO3)0.5(CaO2H2)0.5(H2O)8.5 + 5H+ = 2AlO2- + 0.5CO3-2 + 4Ca+2 + 11.5H20@45.6-260338-299005-129.7-285.4-9.9
hemihydrateCaSO4(H2O)0.5 = Ca+2 + S|6|O4-2 + 0.5H2O@-3.620413-20432-137.0-383.4-5.8
hydrotalciteMg4Al207(H20)10 + 6H+ = 2Al02-+ 4Mg+2 + 13H2O@28.0-159755-235072-252.6146.4-5.4
INFCA(CaO)1(Si02)1.1875(Al203)0.15625(H20)1.65625 + 1.6875H+ = 0.3125Al02-+ Ca+2 + 2.5H2O@ +9.0-51116-500803.514.1-1.1
INFCN1.1875Si02@ (CaO)1(SiO2)1.5(Na20)0.3125(H20)1.1875 + 2.625H+ = Ca+2 + 0.625Na+ + 2.5H2O@ + 1.5Si02@ 18.8-107089-9777031.364.3-2.1
INFCNA(CaO)1.25(SiO2)1(Al203)0.125(Na20)0.25(H2O)1.375 + 2.75H+ = 0.25AlO2- + 1.25Ca+2 + 0.5Na+ + 23.2-132663-135750-10.443.6-2.0
Jennite2.75H20@ + Si02@ (SiO2)1(CaO)1.666667(H20)2.1 + 3.333334H+ = 1.666667Ca+2 + 3.766667H20@ + SiO2@29.3-167347-14630670.6-2.5
K20K2O + 2H+ = H2O@ + 2K+84.1-480020-426988177.966.0 8.0-0.4
K2S04K2SO4 = S|6|O4-2 + 2K+-1.8102142372545.3-379.3-3.5
Kln Al2Si205(OH)4 = 2Al02-+ 2H+ + H2O@ + 2SiO2@-38.3218758185703-110.9-173.4-3.0
*KSiOH(KOH)2.5Si02H20)0.2 + 0.5H+ = 0.7H2O@ + 0.2Si02@ + 0.5K+5.8-32604-1346365.320.70.8
LimCaO + 2H+ = Ca+2 + H2O@32.6-186017-193861-26.31.6-1.7
M4A-OH-LDHMg4Al2(OH)14(H20)3 + 6H+ = 2AlO2-+ 4Mg+2 + 13H20@34.3-195826-271137-252.6147.4-5.3
M6A-OH-LDHMg6Al2(OH)18(H2O)3 + 10H+ = 2AlO2- + 6Mg+2 + 17H20@68.0-388083-499991-375.3250.0-11.1
M8A-OH-LDHMg8Al2(OH)22(H2O)3 + 14H+ = 2Al02- + 8Mg+2 + 21H20@101.7-580340-728838-498.1353.5-17.0
MagFeFe|3|2O4 + 2H2O@ = 4H+ + e- + 3Fe|3|O2--67.8387007361013-87.2-992.8-7.9
MelanteriteFeSO4(H2O)7 = S|6|O4-2 + 4H+ + e- + 5H2O@ + Fe|3|O2--36.821022223077468.9-109.8-4.3
Mg2AlC0.50HMg2Al(OH)6(CO3)0.5(H2O)2 + 2H+ = AlO2- + 0.5CO3-2 + 2Mg+2 + 6H20@5.9-33755-100890-225.2-182.5-4.0
Mg2FeC0.50HMg2Fel3|(OH)6(CO3)0.5(H2O)2 + 2H+ = 0.5CO3-2 + 2Mg+2 + 6H2O@ + Fe|3|O2-5.8-33224-81424-161.7-377.1-5.6
Mg3AlC0.50HMg3Al(OH)8(CO3)0.5(H2O)2.5 + 4H+ = AlO2- + 0.5CO3-2 + 3Mg+2 + 8.5H2O@22.7-129680-215112-286.5-130.7-2.1
Mg3FeC0.50HMg3Fe|3|(OH)8(C03)0.5(H2O)2.5 + 4H+ = 0.5CO3-2 + 3Mg+2 + 8.5H2O@ + Fe|3|02-22.4-127660-194156-223.0-325.3-3.4
MgsMgCO3 = CO3-2 + Mg+2-8.347310-28349-253.8-386.8-5.6
monocarbonateCa4Al2CO9(H2O)11 + 4H+ = 2AlO2- + CO3-2 + 4Ca+2 + 13H2O@24.5-140067-165182-84.2-412.8-8.8
monocarbonate05Ca2AlC0.5O4.5(H2O)5.5 + 2H+ = AlO2-+ 0.5CO3-2 + 2Ca+2 + 6.5H2O@12.3-70033-82591-42.1-206.4-4.4
monocarbonate9Ca4Al2CO9(H2O)9 + 4H+ = 2Al02-+ CO3-2 + 4Ca+2 + 11H2O@28.5-162891-224860-207.8-483.4-9.6
mononitrateCa4Al2(OH)12N|5|206(H2O)4 + 4H+ = 2AlO2- + 4Ca+2 + 2NO3- + 12H20@27.3-156023-14838925.6-356.1-7.7
mononitriteCa4Al2(OH)12N|3|204(H2O)4 = 2AlO2-+ 4Ca+2 + 2N03- + 4e- + 10H2O@-25.7146749197173169.1-420.1-9.2
\n\n@ - is used to represent a neutral aqueous species.Standard molar volumes for ideal gases are not listed because they are all equal to 2479 J/bar at 1 bar, 298.15 K. \n \n1 \n\n\n
290[J/O1][J/1o1]mol] mol] [5) bar]
monosulphate10.5Ca4Al2SO10(H20)10.5 + 4H+ = 2Al02- + 4Ca+2 + S|6|04-2 + 12.5H20@28.1-160590-194728-114.5-434.2-9.8
monosulphate12Ca4Al2S010(H20)12 + 4H+ = 2Al02- + 4Ca+2 + S|6|O4-2 + 14H2O@26.8-152912-176816 -80.2-381.2 -7.1
monosulphate1205 Ca2AlS0.505(H2O)6 + 2H+ = AlO2- + 2Ca+2 + 0.5S|6|04-2 + 7H20@13.4-76454-88406-40.1-190.6 -6.0
monosulphate14Ca4Al2S010(H20)14 + 4H+ = 2Al02- + 4Ca+2 + S|6|04-2 + 16H2O@26.8-152768-185449-109.6-310.6 -8.4
monosulphate16Ca4Al2SO10(H2O)16 + 4H+ = 2AlO2-+ 4Ca+2 + S|6|O4-2 + 18H2O@26.9-153259-148473 16.1-246.2 -6.7
monosulphate9Ca4Al2S010(H20)9 + 4H+ = 2Al02- + 4Ca+2 + S|6|O4-2 + 11H2O@30.2-172114-232353-202.0-487.1 -11.8
N2N|0|2 + 6H2O@ = 2NO3-+ 12H+ + 10e--210.512012891301508336.1-470.7
Na20 Na2O + 2H+ = 2Na+ + H2O@67.4-384943-351639111.782.7 -0.9
Na2S04Na2SO4 = S|6|O4-2 + 2Na+-0.31703-2457-14.0-254.9 -4.3
*NaSiOH((NaOH)2.5Si02H2O)0.2 + 0.5H+ = 0.5Na+ + 0.7H2O@ + 0.2SiO2@5.7-32021-19201 43.734.7 0.5
020|0|2 + 4H+ + 4e- = 2H20@83.1-474371-571762-326.763.7
Ord-DolCaMg(C03)2 = 2C03-2 + Ca+2 + Mg+2-17.197552-36538-449.7-789.0 -11.7
PortlanditeCa(OH)2 + 2H+ = Ca+2 + 2H2O@22.8-130145-130156 0.032.3 -1.5
PyFeS|0|S|-2| + 10H2O@ = 2S|6|O4-2 + 20H+ + 15e- + Fe|3|O2--120.5687822780233309.9-1366.5 -17.8
QtzSi02 = Si02@-3.72138621386 0.00.0-0.7
SdFeCO3 + 2H2O@ = CO3-2 + 4H+ + e- + Fe|3|02--45.5259775204566-185.2-742.7 -7.1
StrSrCO3 = CO3-2 + Sr+2-9.352918-324-178.6-413.3 -6.3
straetlingiteCa2Al2SiO7(H20)8 + 2H+ = 2Al02- + 2Ca+2 + 9H2O@ + Si02@4.1-23479-38065-48.9-39.9 -5.5
straetlingite5.5Ca2Al2SiO7(H2O)5.5 + 2H+ = 2AlO2- + 2Ca+2 + 6.5H2O@ + SiO2@7.1-40503-79963-132.3-128.1 -9.7
straetlingite7Ca2Al2SiO7(H2O)7 + 2H+ = 2Al02-+ 2Ca+2 + 8H2O@ + SiO2@4.8-27477-45434-60.2-75.2 -7.3
SulfurS|0| + 4H20@ = S|6|O4-2 + 8H+ + 6e--35.8204198233827 99.4-503.8 -7.5
syngeniteK2Ca(S04)2H20 = Ca+2 + 2S|6|O4-2 + H20@ + 2K+-7.24107819412-72.7-743.9 -8.4
T2C-CNASHss(CaO)1.5(Si02)1(H2O)2.5 + 3H+ = 1.5Ca+2 + 4H20@ + SiO2@25.6-145938-125275 69.362.5 -2.0
T5C-CNASHss(CaO)1.25(Si02)1.25(H20)2.5 + 2.5H+ = 1.25Ca+2 + 3.75H2O@ + 1.25SiO2@18.4-105297-80438 83.465.4 -1.5
thaumasite(CaSiO3)(CaSO4)(CaCO3)(H2O)15 + 2H+ = CO3-2 + 3Ca+2 + S|6/O4-2 + 16H2O@ + Si02@-0.9523623833 62.4-468.7 -7.3
TobH-CNASHss(CaO)1(Si02)1.5(H20)2.5 + 2H+ = Ca+2 + 3.5H20@ + 1.5Si02@12.8-73056-44000 97.568.3 -1.6
Tob-I-152677-105616157.8119.1 -4.5
Tob-II (SiO2)2.4(CaO)2(H2O)3.2 + 4H+ = 2Ca+2 + 5.2H2O@ + 2.4SiO2@26.7-63617-44009 65.849.6 -1.9
tricarboalu03(SiO2)1(CaO)0.833333(H20)1.333333 + 1.666666H+ = 0.833333Ca+2 + 2.166666H20@ + SiO2@ (CO3)Ca2Al0.6666667(OH)4(H20)8.6666667 + 1.3333332H+ = 0.6666667Al02- + CO3-2 + 2Ca+2 +11.1 3.2-18115-21090-10.0-236.8 -4.9
Tro113333H2020@$|604212H9e-Fe|32-73.6471331171.4-873.9-11.3 Cement
\n\n![](images/21bdc668829c05dc1b1f5a094da942432f8bd97b4121fd2cbab5540a880b414a.jpg) \n\n![](images/4e1bfa6d8fe2db4aa8df036ff318c1e4ddeaac56bd8a6f9383b25768cb6538b9.jpg) \nFig. B.2. Effect of the amount of limestone on the phase assemblage and the distribution of aluminium and iron in hydrated Portland cement calculated usin Cemdata18 GEM format (dashed lines) and Cemdata18 PHREEQC format (dotted lines), in both cases using ideal solid solutions. \n\n![](images/d2c3eda08fac9be76c8214a55e6b73b66ed7d1ae34eb601b0d70f8c383883952.jpg) \n\n![](images/c70690adc190ad3310c6bd4442f2b97116d15d9bd943649581c18dee1bd9b569.jpg) \n\n# Appendix C. Thermodynamic equations and assumptions \n\nThe solubility products compiled in Cemdata18 have generally been derived from solutions composition measured at different temperatures, as documented in detail in [1,7–10,12,27,28,30,31,34–37,39–41]. The activity of a species i, $a_{i},$ has been calculated with GEMS from the measured concentrations considering the formation of aqueous complexes. By definition $a_{i}=\\gamma_{i}{}^{*}m_{i},$ where $\\upgamma_{i}$ is the activity coefficient and $m_{i}$ the concentration in $\\mathrm{mol}/\\mathrm{kg}\\mathrm{H}_{2}\\mathrm{O}$ . Activity coefficients of aqueous species $\\upgamma_{i}$ were computed using the built-in extended Debye-Hückel equation with the common ionsize parameter $a_{i}$ of $3.{\\dot{6}}7{\\mathring{\\mathrm{A}}}$ for KOH and $\\mathbf{\\dot{\\tau}}_{3.31\\mathrm{\\AA}}$ for NaOH solutions and the common third parameter $b_{y}$ according to the Eq. (C.1): \n\n$$\n\\log\\gamma_{i}=\\frac{-A_{y}z_{i}^{2}\\sqrt{I}}{1+B_{y}a_{i}\\sqrt{I}}+b_{y}I\n$$ \n\nhere $z_{i}$ denotes the charge of species $i,I$ is the effective molal ionic strength, $b_{y}$ is a semi-empirical parameter ${\\it\\simeq}0.123{\\it$ for KOH and ${\\sim}0.098$ for NaOH electrolyte at $25^{\\circ}\\mathrm{C})$ , and $A_{y}$ and $B_{y}$ are $P,T$ -dependent coefficients. For uncharged species, Eq. (C.1) reduces to $\\mathrm{log}\\upgamma_{i}=b_{y}I.$ This extended Debye-Hückel activity correction is applicable up to approx. $1m$ ionic strength [130]. \n\nFrom the solubility products $K$ of solids calculated at different temperatures $T$ , the Gibbs free energy of reaction, $\\Delta_{r}G^{\\circ}$ , the Gibbs free energy of formation, $\\Delta f G^{\\circ}$ , and the absolute entropy, $\\boldsymbol{S}^{\\circ}$ , at $T_{0}=298.15\\mathrm{K}$ were obtained according to Eqs. (C.2) and (C.3): \n\n$$\n\\Delta_{r}G^{\\circ^{\\circ}}=\\sum_{i}\\nu_{i}\\Delta_{f}G^{\\circ}=-R T\\ln K\n$$ \n\n$$\n\\Delta_{a}G_{T}^{o}=\\Delta_{f}G_{T_{0}}^{o}-S_{T_{0}}^{o}(T-T_{0})+\\int_{T_{0}}^{T}C_{p}^{\\mathrm{0}}d T-\\int_{T_{0}}^{T}\\frac{C_{p}^{o}}{T}d T\n$$ \n\nUsing $C_{p}^{\\circ}=a_{O}+a_{I}T+a_{2}T^{-2}+a_{3}T^{O.5}$ [131], where $\\mathbf{a}_{0-3}$ are the empirical parameters defined for each mineral, the two integral terms of Eq. (C.3) can be solved to give Eq. (C.4): \n\n$$\na G_{T}^{o}=\\Delta_{f}G_{I_{0}}^{o}~-~S_{T_{0}}^{o}(T~-~T_{0})~-~a_{0}\\bigg(T\\ln\\frac{T}{T_{0}}~-~T+T_{0}\\bigg)-~0.5a_{1}(T-T_{0})^{2}-~a_{2}\\frac{(T-T_{0})^{2}}{2T\\cdot T_{0}^{2}}~-~a_{3}\\frac{2(\\sqrt{T}~-~\\sqrt{T_{0}})^{2}}{\\sqrt{T_{0}}}\n$$ \n\nwhere $\\nu_{i}$ are the stoichiometric reaction coefficients, $R=8.31451\\mathrm{J/mol/K},$ $T$ is the temperature in $\\mathbb{K},$ and $\\boldsymbol{C^{\\circ}}_{p}$ is the heat capacity at constant pressure. The apparent Gibbs free energy of formation, $\\Delta_{a}{G^{\\circ}}_{T},$ refers to standard Gibbs energies of elements at 298.15 K. A more detailed description of the derivation of the dependence of the Gibbs free energy on temperature is available in [131,132]. \n\nDependence of the solubility product on temperature, consistent to Eq. (C.4) can be expressed as: \n\n$$\n\\log K_{T}=A_{0}+A_{1}T+{\\frac{A_{2}}{T}}+A_{3}\\ln T+{\\frac{A_{4}}{T^{2}}}+A_{5}T^{2}+A_{6}{\\sqrt{T}}\n$$ \n\n[131], where $A_{O},\\ldots A_{6}$ are empirical coefficients. If the entropy $(S^{\\circ})$ , the enthalpy $(\\Delta_{\\mathrm{f}}H^{\\circ})$ , and the coefficients $(a_{O},\\ a_{1},\\ ...)$ of the heat capacity equation $(C_{p}^{\\circ}=a_{O}+a_{1}T+a_{2}T^{-2}+a_{3}T^{O.5}+a_{4}T^{2})$ of the species are available, the coefficients $A_{O},\\ldots A_{6}$ can be calculated directly (see [131]). These calculations involving Eqs. (C.4) and (C.5) are all implemented in the GEM-Selektor. \n\nThe heat capacity function, $\\mathbf{C}_{\\mathrm{p}}=\\mathbf{f}(\\mathrm{T})$ is usually obtained from calorimetry experiments. In many cases, the heat capacity has to be estimated by using a reference reaction with a solid having a known heat capacity and similar structure, as described in publications [1,7–10,12,27,28,30,31,34–37,39–41]. Helgeson et al. [43] applied this principle successfully to estimate heat capacities of silicate minerals by formulating reactions involving structurallyrelated minerals with known heat capacity functions. This method has limitations due to the differing thermodynamic properties of “water” varieties, bound loosely as a hydration water, or structurally as OH-groups. To minimize errors associated with the varying strengths of bonding for “water”, reference reactions had been formulated to involve no “free” water as a substituent in reactions, wherever appropriate. \n\nThe value of $\\Delta_{r}{{C_{p}}^{0}}$ has little influence on the calculated $\\log\\mathrm{K}$ value in the temperature range $0{-}100^{\\circ}\\mathrm{C}$ and is thus often assumed to be constant in a narrow temperature range: $\\Delta_{\\mathrm{r}}\\mathrm{Cp}_{\\mathrm{T}}^{0}=\\Delta_{\\mathrm{r}}\\mathrm{Cp}_{\\mathrm{T0}}^{0}=\\Delta\\mathbf{a}_{\\mathrm{o}}$ . This simplifies Eq. (C.5) to the so called 3-term approximation of the temperature dependence, see Eq. (C.6), which can be used to compute the standard thermodynamic properties of each solid [132] to obtain a temperature-dependent “log $\\mathbf{K}^{\\mathfrak{n}}$ function using Eqs. (C.6)-(C.12) (implemented in GEMS). \n\n$$\n\\log K_{T}=A_{0}+A_{2}T^{-1}+A_{3}\\ln T\n$$ \n\nand \n\n$$\n\\begin{array}{l}{{A_{0}=\\displaystyle\\frac{0.4343}{R}\\left[\\Delta_{r}S_{0_{0}}^{0}-\\Delta_{r}C{D}_{T_{0}}^{0}\\left(1+\\ln{T_{0}}\\right)\\right]}}\\\\ {{\\ }}\\\\ {{A_{2}=\\displaystyle\\frac{0.4343}{R}\\langle\\Delta_{r}{M_{0}^{a}}-\\Delta_{r}C{D}_{T_{0}}^{0}\\left(1\\right)}}\\\\ {{\\ }}\\\\ {{A_{3}=\\displaystyle\\frac{0.4343}{R}.\\Delta_{r}C{D}_{r_{0}}^{0}}}\\\\ {{\\ }}\\\\ {{\\Delta_{r}S_{\\tau}^{0}=\\Delta_{r}S_{0_{0}}^{0}+\\Delta_{r}C{D}_{r_{0}}^{0}\\ln{\\frac{T}{T_{0}}}}}\\\\ {{\\ }}\\\\ {{\\Delta_{r}I_{0}^{0}=\\Delta_{r}I_{0}^{0}+\\Delta_{c}C{D}_{r_{0}}^{0}\\left(T-T_{0}\\right)}}\\\\ {{\\ }}\\\\ {{\\Delta_{\\theta}G_{\\tau}^{0}=\\Delta_{r}R_{0}^{\\tau}+T\\Delta_{\\theta}S_{\\tau}^{0}}}\\end{array}\n$$ \n\nWithin the relatively narrow temperature range of 0 to $100^{\\circ}\\mathrm{C}$ , where the Cemdata18 database is valid, this simplification has a negligible influence on the resulting solubility products, also for non-isoelectric reactions as exemplified for ettringite in [20]. \n\nStandard (partial molal) thermodynamic properties and equation of state parameters of aqueous species at 25 °C, 1 bar used in GEM calculations, as detailed in the GEMS version of the PSI/Nagra 12/07 TDB [22,23]. Numbers referring to the charge of aqueous species are written after the plus or minus signs to avoid any ambiguity; “@” is used to represent a neutral aqueous species. \n \n\n\n
Species△G°△H°Cp°a10*az10-2*a*a410-4*C1*C210-4*0010-5*
(kJ/mol)(kJ/mol)(J/ mol·K)(J/mol·K)(J/bar)(cal/mol/ bar)(cal/mol)(cal-K/mol/ bar)(cal·K/ mol)(cal/mol/ K)(cal·K/ mol)(cal/mol)
Al(SO4)+ Al(SO4)²--1250.43 - 2006.30-1422.67 -2338.40-172.38 -135.50- 204.01 - 268.37-6.02 31.111.3869 6.8275-4.3920 8.89257.4693 2.2479-2.5974 -3.1466- 11.6742 -12.0220-12.9914 -16.14471.1729 2.1199
Al+3- 483.71-530.63-325.10-128.70-45.24-3.3802-17.007114.5185-2.075810.7000-8.06002.7530
Al0+-660.42-713.64-112.97-125.110.312.1705-2.48116.7241-2.6763-2.5983-9.14550.9570
AlO—-827.48-925.57-30.21-49.049.473.72213.9954-1.5879-2.944115.2391-5.45851.7418
AlO2H@-864.28-947.1320.92- 209.2113.013.53380.84855.4132-2.8140- 23.4129-13.2195-0.0300
AlOH+2- 692.60-767.27-184.9355.97-2.732.0469-2.78136.8376-2.663929.7923-0.34571.7247
Ca(CO3)@-1099.18-1201.9210.46-123.86-15.65-0.3907-8.73259.1753-2.4179-11.5309-9.0641-0.0380
Ca(HCO3)+-1146.04-1231.9466.94233.7013.333.70601.26705.2520-2.831041.72208.33600.3080
Ca(HSiO3)+-1574.24-1686.48-8.33137.80-6.741.0647-5.17877.7785-2.564930.80483.66190.5831
Ca(SO4)@-1310.38-1448.4320.92- 104.604.702.4079-1.89926.4895-2.7004-8.4942-8.1271-0.0010
Ca+2-552.79-543.07-56.48-30.92-18.44-0.1947-7.25205.2966-2.47929.0000-2.52201.2366
CaOH+-717.02-751.6528.036.055.762.7243-1.13036.1958-2.732211.1286-2.74930.4496
CH4@-34.35-87.8187.82277.2637.406.76178.72792.3212-3.139742.094110.4707-0.3179
Cl--131.29-167.1156.74-122.4917.344.03204.80105.5630- 2.8470-4.4000-5.71401.4560
Cl04-8.54-129.33182.00-24.0043.908.141115.5654-7.8077-3.422416.4500-6.57000.9699
CO2@-386.02-413.84117.57243.0832.816.24667.47112.8136-3.087940.03258.8004-0.0200
CO-2-527.98-675.31-50.00-289.33-6.062.8524-3.98446.4142-2.6143-3.3206-17.19173.3914
e-0065.3414.4200000000
Fe(CO3)@-644.49-763.51-58.45-123.03-17.23-0.6069-9.26049.3828-2.3961-11.4137-9.0233-0.0380
Fe(HCO3)+-689.86-794.10-8.87231.418.183.1064-0.19345.8191-2.771043.91758.21950.5831
Fe(HSO4)+-853.48-990.4510.21338.2318.814.53303.28974.4500-2.914958.230513.42170.5121
Fe(HSO4)+2-787.15-981.91-248.95426.712.322.8251-0.88046.0891-2.742683.831517.69941.9551
Fe(SO4)@-848.81-993.86-16.86-101.601.671.9794-2.94546.9007-2.6572-8.4131-7.9804-0.0380
Fe(SO4)+-784.71-942.42-124.68-145.93-2.641.7837-3.42327.0885-2.6374-5.1341-10.16000.9986
Fe(SO4)2-1536.81-1854.38-87.78-210.3730.496.67568.52152.3937-3.1312-5.4923-13.31731.9457
Fe+2-91.50-92.24-105.86-32.44-22.64-0.7867-9.69699.5479-2.378014.7860-4.64371.4382
Fe+3-17.19-49.58-277.40-76.71-37.79-2.4256-13.696111.1141-2.212719.0459-6.82332.5812
FeCl+-223.59- 258.05-42.0986.490.852.1468-2.53676.7401-2.674124.69121.16170.7003
FeCl+2-156.92-212.67-178.8214.83- 22.86-0.7164-9.52779.4878-2.385123.8149-2.34821.7013
FeCl2+-291.92 -417.51-385.75 -564.39-129.66 -131.06300.72 368.2210.27 35.943.5610 6.66860.9165 8.50385.3828 2.4024-2.8168 -3.130457.6940 57.395911.5846 14.89301.0276 -0.0380
\n\n \nThe thermodynamic data for aqueous and gaseous species compatible with Cemdata18 are summarised in Tables D.1 and D.2. \n\n(continued on next page) \nTable D.1 (continued) \n\n\n
Species△G°△H°Cp°V0a10*a210-2*ag*a410-4*C1*C10-4*Wo10-5*
(kJ/mol)(kJ/mol)(J/ mol·K)(J/mol·K)(J/bar)(cal/mol/ bar)(cal/mol)(cal-K/mol/ bar)(cal·K/ mol)(cal/mol/ K)(cal·K/ mol)(cal/mol)
- 222.00- 255.09-46.44- 200.94-3.7118-16.8408-2.0827
FeO+ FeO2-368.26-443.8244.35-234.93-42.02 0.452.3837-1.960212.3595 6.5182-2.6979-15.3982 -13.3207-12.8325 -14.50280.7191 1.4662
FeO2H@- 419.86- 480.9592.88-312.147.212.7401-1.09056.1776-2.7338- 37.8300-18.2305-0.0300
FeOH+-274.46-325.65-41.8463.06-16.71-0.2561-8.40299.0457-2.431521.40930.02090.7003
FeOH+2-241.87-292.79-106.27-33.69-25.34-1.1562-10.60099.9077-2.340714.6102-4.70481.4382
H+000000000000
H@17.73-4.0257.74166.8525.265.14274.77583.8729-2.976427.62515.0930-0.2090
H2O@-237.18-285.8869.9275.3618.070000000
Hs@-27.93-39.03125.52179.1734.956.50976.77245.9646-3.059032.30004.7300-0.1000
HCN@114.37103.75131.30000000000
HCO3\"-586.94- 690.0198.45-34.8524.217.56211.15051.2346-2.826612.9395-4.75791.2733
HS-11.97-16.2268.20-93.9320.215.01194.97993.4765-2.98493.4200-6.27001.4410
HSiO3--1014.60-1144.6820.92-87.204.532.9735-0.51815.9467-2.75758.1489-7.31231.5511
HSO3--529.10-627.70139.75-5.3832.966.70148.58162.3771-3.133815.6949-3.31981.1233
HSO4-755.81-889.23125.5222.6834.846.97889.25902.1108-3.161820.0961-1.95501.1748
K(SO4)--1031.77-1158.77146.44- 45.1327.465.94086.72743.0989-3.05719.9089-5.25491.0996
K+-282.46-252.14101.048.399.013.5590-1.47305.4350-2.71207.4000-1.79100.1927
KOH@-437.11-474.15108.37-85.0214.963.79381.48395.1619-2.8402-6.1240-7.2104-0.0500
Mg(CO3)@-998.98-1132.12-100.42-116.50-16.78-0.5450-9.11309.3320-2.4020-10.4990-8.7060-0.0380
Mg(HCO3)+-1047.02-1153.97-12.55254.429.343.27100.20605.6690-2.788047.28409.34000.5990
Mg(HSi03)+-1477.15-1613.91-99.50158.65-10.850.6289-6.24288.1967-2.520936.78824.67020.9177
Mg+2- 453.99-465.93 -690.02-138.07-21.66-22.01-0.8217 2.3105-8.5990 -2.13658.3900-2.390020.8000-5.89201.5372
MgOH+ MgS04@-625.87 -1211.97-1368.77-79.91 -50.88129.231.641.9985-2.89876.5827-2.690632.00083.23940.8449
N2@18.19-10.3795.81- 90.31 234.161.816.20467.36856.8823 2.8539-2.6591 -3.0836-6.8307 35.7911-7.4304-0.0380
Na(CO3)--797.11-938.56- 44.3133.412.3862-1.95216.5103-2.698215.33958.3726-0.3468
Na(HCO3)@-847.39-929.50-51.28-0.426.17307.2943-5.56861.7870
-1010.34-1146.66154.72200.3332.324.79453.92842.8760-3.080533.87906.7193-0.0380
Na(SO4)--261.88-240.28101.75-30.0918.641.8390-2.28504.1990-2.941413.4899-4.52561.2606
Na+-418.12- 470.1458.4138.12-1.21-2.32873.2560-2.726018.1800-2.98100.3306
NaOH@44.77-13.403.512.23386.6683-2.68264.0146-3.6863-0.0300
NH@-26.67-81.53107.82 111.1776.89 67.1124.45 18.085.0911 3.87632.7970 2.34488.6248 8.5605-2.8946 -2.875920.3000 17.4500-1.1700 -0.0210-0.0500 0.1502
NH4+ NO3--79.40 -110.91-133.26 - 206.89
\n\n+++°°°°0; 3Fe4H OFe (OH)4HG35.96,H59.834,S80.07,C03234 5rrrrp \n\n\n
Species△G°△H°Cp°V0a10*a10-2*a3*a410-4*C1*C10-4*W10-5
(kJ/mol)(kJ/mol)(J/ mol-K)(J/mol·K)(J/bar)(cal/mol/ bar)(cal/mol)(cal·K/mol/ bar)(cal·K/ mol)(cal/mol/ K)(cal·K/ mol)(cal/mol
S03-2-487.89-636.89-29.29- 280.99
S04-2-744.46- 909.7018.83- 266.09-4.12 12.922.4632 8.3014-1.7691 -1.98466.4494-2.7058-2.7967-16.78433.3210
Sr(CO3)@-1107.83-1207.2935.56-134.32-15.23-0.3332-8.5922-6.2122 9.1201-2.69701.6400 -12.9961-17.99803.1463
Sr(HCO3)+-1157.54-1239.0095.94210.0714.083.77021.42745.1820-2.4237 -2.838037.4746-9.5733-0.0380 0.2058
Sr(S04)@-1321.37-1451.5061.59-110.605.022.4382-1.82516.4604-2.7035-9.67317.1883
Sr+2-563.84-550.87-31.51-41.56-17.760.7071-10.15087.0027-2.359410.7452-8.4183-0.0380
SrOH+-725.16-754.1461.09-31.667.102.8620-0.79226.0586-2.74624.7576-5.08181.1363
aoa1a2-4.58260.3306
Temperature correction using Cp(T) integration 833.41 Si02@**(Cp° = ao+ aT+aT-2)
Temperature correction using logK(T)887.86*41.3444.471.61 46.94 Ao0.034 A1A2-1.13E+06
SiO3-2**-938.51-1098.74-80.20119.83 0-10.00060-3917.5(logK= Ao+ AT +AT-1)
Si4O10-4***-3600.81-3915.99305.20328.58 000-10,822.8
CaSiO3@**-1517.56-1668.06-136.6888.900 001371.49
MgSi03@-1425.03-1554.54-75.17-264.7905.700
AlSiO5-3 ***-1769.01-2027.33-110.4170.78-3.4100158.02
AIHSiO3+2 *V-1540.55-1634.31-24.99- 215.896014.58280-2141.57
FeHSiO3+2 *V-1087.15-1194.26-70.77-163.9109.700
Fe2(OH)2+4 v-491.9-614.44- 281.97-2.7106.945860-2950.45
Fe3(OH)4+5 *V-964.33-1232.44- 472.4371.3004.18240-3125.33
SrSiO3@***-1527.29-1617.4379.9278.391.64001302.92
s-2120.42-16.22-295.55-93.930-1900
\n\n1 加 1 1 S fromSiO2+>====+>+====+>====+>==°°°°+°°°°+°°°°+°°°SiOAlOAlSiOGG3.025,S0,C0; Si O4H4SiO2H OGH207.2,S0,C0; SiOMgMgSiOG32.54,H0,S109.126,C0; SiOSrSrSiOGH29.944,S32253rrrrp4104202rrrrp32230rrrrp32230rrr. ⁎vFromtheGEMSversionofthePSI/Nagra+>====+>===++°°°°++°°°°AlHSiOAlHSiOG42.24,H41,S279.19,C0; FeHSiOFeHSiOG55.37,H0,S185.7,C333 2rrrrp333 2rrrrp. S−2120.42−16.22−295.55−93.930−1900⁎Parameters of the HKF-equation of state; given in original calorimetric units (see [25,26,133]) as used in GEM.⁎⁎CalculatedinMatscheietal.[7]assumingΔrS° = ΔrC°p = 0usingS°and>==+>+====+>====°°+°°°°+°°°°SiOSiO (quartz)GH21.386; SiO2HSiOH OG132.08,H75,S191.46,C0; SiOCaCaSiOGH26.257,S0,C0pp202rr32202rrrr32230rrrr.⁎⁎⁎CalculatedinthispaperassumingΔrS° = ΔrC°p = 0usingS°andC°p \n=+>+===+++°°°°0; 2FeH OFe (OH)2HG16.84,H56.486,S132.98,C32222 4rrrrp \n\nTable D.2 Standard (partial molal) thermodynamic properties and heat capacity coefficients $(C p^{0}=a_{0}+a_{1}T+a_{2}T^{-2})$ of gaseous species at $25^{\\circ}\\mathrm{C}$ , 1 bar used in GEM calculations, as used in the GEMS version of the PSI/Nagra 12/07 TDB [22,23]. Standard molar volumes for ideal gases are not listed because they are all equal to 2479 J/bar at 1 bar, 298.15 K. \n\n\n
Species△G°△H°Cp°aoa1a2
(kJ/mol)(kJ/mol)(J/mol K)(J/mol K)(J/mol/K)(J/mol/K2)(J·K/mol)
CH4-50.66-74.81186.2635.7523.640.0479-192,464
CO2-394.39-393.51213.7437.1544.220.0088-861,904
H200130.6828.8227.280.003350,208
H2O-228.68-242.40187.2540.0752.99-0.04355472
H2S-33.75-20.63205.7934.2032.680.0124-192,464
N200191.6129.1328.580.0038-50,208
0200205.1429.3229.960.0042-167,360
\n\n# References \n\n[1] B. Lothenbach, T. Matschei, G. Möschner, F.P. Glasser, Thermodynamic modelling of the effect of temperature on the hydration and porosity of Portland cement, Cem. Concr. Res. 38 (2008) 1–18. [2] T. Matschei, B. Lothenbach, F.P. Glasser, The role of calcium carbonate in cement hydration, Cem. Concr. Res. 37 (2007) 551–558. \n[3] M. Moesgaard, D. Herfort, M. Steenberg, L.F. Kirkegard, Y. Yue, Physical performance of blended cements containing calcium aluminosilicate glass powder and limestone, Cem. Concr. Res. 41 (2011) 359–364. \n[4] T. Matschei, F.P. Glasser, Temperature dependence, 0 to $40^{\\circ}\\mathrm{C},$ of the mineralogy of Portland cement paste in the presence of calcium carbonate, Cem. Concr. Res. 40 (2010) 763–777. [5] B. Lothenbach, F. Winnefeld, C. Alder, E. Wieland, P. Lunk, Effect of temperature on the pore solution, microstructure and hydration products of Portland cement pastes, Cem. Concr. Res. 37 (2007) 483–491. \n[6] F. Deschner, B. Lothenbach, F. Winnefeld, J. Neubauer, Effect of temperature on the hydration Portland cement blended with siliceous fly ash, Cem. Concr. Res. 52 (2013) 169–181. \n[7] T. Matschei, B. Lothenbach, F.P. Glasser, Thermodynamic properties of Portland cement hydrates in the system CaO-Al2O3-SiO2-CaSO4-CaCO3-H2O, Cem. Concr. Res. 37 (2007) 1379–1410. \n[8] B.Z. Dilnesa, B. Lothenbach, G. Le Saout, G. Renaudin, A. Mesbah, Y. Filinchuk, A. Wichser, E. Wieland, Iron in carbonate containing AFm phases, Cem. Concr. Res. 41 (2011) 311–323. \n[9] B.Z. Dilnesa, B. Lothenbach, G. Renaudin, A. Wichser, D. Kulik, Synthesis and characterization of hydrogarnet $\\mathrm{Ca_{3}(A l_{x}F e_{1-x})_{2}(S i O_{4})_{y}(O H)_{4(3-y):}}$ Cem. Concr. Res. 59 (2014) 96–111. \n[10] B.Z. Dilnesa, B. Lothenbach, G. Renaudin, A. Wichser, E. Wieland, Stability of monosulfate in the presence of iron, J. Am. Ceram. Soc. 95 (2012) 3305–3316. \n[11] D.A. Kulik, Improving the structural consistency of C-S-H solid solution thermodynamic models, Cem. Concr. Res. 41 (2011) 477–495. \n[12] B. Lothenbach, L. Pelletier-Chaignat, F. Winnefeld, Stability in the system $\\mathrm{CaO-Al_{2}O_{3}-H_{2}O}$ , Cem. Concr. Res. 42 (2012) 1621–1634. \n[13] D. Kulik, T. Wagner, S. Dmytrieva, G. Kosakowski, F. Hingerl, K. Chudnenko, U. Berner, GEM-Selektor geochemical modeling package: revised algorithm and GEMS3K numerical kernel for coupled simulation codes, Comput. Geosci. 17 (2013) 1–24. \n[14] T. Wagner, D.A. Kulik, F.F. Hingerl, S.V. Dmytrieva, GEM-Selektor geochemical modeling package: TSolMod library and data interface for multicomponent phase models, Can. Mineral. 50 (2012) 1173–1195. \n[15] P. Blanc, X. Bourbon, A. Lassin, E. Gaucher, Chemical model for cement-based materials: Temperature dependence of thermodynamic functions for nanocrystalline and crystalline C-S-H phases, Cem. Concr. Res. 40 (2010) 851–866. \n[16] P. Blanc, X. Bourbon, A. Lassin, E. Gaucher, Chemical model for cement-based materials: thermodynamic data assessment for phases other than CSH, Cem. Concr. Res. 40 (2010) 1360–1374. \n[17] C.M. Bethke, Geochemical and Biogeochemical Reaction Modeling, 2nd Ed., Cambridge University Press, New York, NY, USA, 2008. \n[18] D.J. Parkhurst, C.A.J. Appelo, Description of Input and Examples for PHREEQC Version 3 - A Computer Program for Speciation, Batch-reaction, One-dimensional Transport, and Inverse Geochemical Calculations, 6 USGS, Denver, CO, USA, 2013. \n[19] J.E. Cross, F.T. Ewart, HATCHES - a thermodynamic database and management system, Radiochim. Acta 52/53 (1991) 421–422. \n[20] D. Damidot, B. Lothenbach, D. Herfort, F.P. Glasser, Thermodynamics and cement science, Cem. Concr. Res. 41 (2011) 679–695. \n[21] G. Möschner, B. Lothenbach, J. Rose, A. Ulrich, R. Figi, R. Kretzschmar, Solubility of Fe-ettringite $(\\mathrm{Ca}_{6}[\\mathrm{Fe(OH)}_{6}]_{2}(\\mathrm{SO}_{4})_{3}{\\cdots}26\\mathrm{H}_{2}\\mathrm{O})_{2}$ Geochim. Cosmochim. Acta 72 (2008) 1–18. \n[22] T. Thoenen, W. Hummel, U. Berner, E. Curti, The PSI/Nagra Chemical Thermodynamic Data Base 12/07, PSI Report 14-04, Villigen PSI, Switzerland, 2014. \n[23] T. Thoenen, D.A. Kulik, Nagra/PSI Chemical Thermodynamic Data Base 01/01 for the GEM-Selektor (V.2- PSI) Geochemical Modeling Code: Release 28-02-03. Internal Report TM-44-03-04, available from http://gems.web.psi.ch/TDB/doc/ pdf/TM-44-03-04-web.pdf, (2003) (checked 2018-04-19). \n[24] W. Hummel, U. Berner, E. Curti, F.J. Pearson, T. Thoenen, Nagra/PSI Chemical Thermodynamic Data Base 01/01, Universal Publishers/uPUBLISH.com, USA, Also Published as Nagra Technical Report NTB 02-16, Wettingen, Switzerland, 2002. \n[25] E. Shock, D. Sassani, M. Willis, D. Sverjensky, Inorganic species in geologic fluids: Correlations among standard molal thermodynamic properties of aqueous ions and hydroxide complexes, Geochim. Cosmochim. Acta 61 (1997) 907–950. \n[26] D. Sverjensky, E. Shock, H. Helgeson, Prediction of the thermodynamic properties of aqueous metal complexes to 1000 C and 5 kb, Geochim. Cosmochim. Acta 61 (1997) 1359–1412. \n[27] M. Balonis, B. Lothenbach, G. Le Saout, F.P. Glasser, Impact of chloride on the mineralogy of hydrated Portland cement systems, Cem. Concr. Res. 40 (2010) 1009–1022. \n[28] T. Matschei, F.P. Glasser, The thermal stability of thaumasite, Mater. Struct. 48 (2015) 2277–2289. \n[29] B. Lothenbach, F. Winnefeld, Thermodynamic modelling of the hydration of Portland cement, Cem. Concr. Res. 36 (2006) 209–226. \n[30] L.G. Baquerizo, T. Matschei, K.L. Scrivener, Impact of water activity on the stability of ettringite, Cem. Concr. Res. 76 (2016) 31–44. \n[31] L.G. Baquerizo, T. Matschei, K.L. Scrivener, Hydration states of AFm cement phases, Cem. Concr. Res. 73 (2015) 143–157. \n[32] L.G. Baquerizo, T. Matschei, K.L. Scrivener, M. Saeidpour, A. Thorell, L. Wadsö, Methods to determine hydration states of minerals and cement hydrates, Cem. Concr. Res. 65 (2014) 85–95. \n[33] M. Balonis, F.P. Glasser, The density of cement phases, Cem. Concr. Res. 39 (2009) 733–739. \n[34] M. Balonis, The Influence of Inorganic Chemical Accelerators and Corrosion Inhibitors on the Mineralogy of Hydrated Portland Cement Systems, Thesis University of Aberdeen, Aberdeen, UK, 2010. \n[35] M. Balonis, M. Medala, F.P. Glasser, Influence of calcium nitrate and nitrite on the constitution of AFm and AFt cement hydrates, Adv. Cem. Res. 23 (2011) 129–143. \n[36] M. Balonis, F.P. Glasser, Calcium nitrite corrosion inhibitor in portland cement: influence of nitrite on chloride binding and mineralogy, J. Am. Ceram. Soc. 94 (2011) 2230–2241. \n[37] B.Z. Dilnesa, Fe-containing Hydrates and Their Fate During Cement Hydration: Thermodynamic Data and Experimental Study, Thesis EPFL, Lausanne, 2012. \n[38] D. Garvin, V.B. Parker, H.J. White, CODATA Thermodynamic Tables. Selections for Some Compounds of Calcium and Related Mixtures: A Prototype Set of Tables, Springer Verlag, Berlin, 1987. \n[39] K.B. Rozov, U. Berner, D.A. Kulik, L.W. Diamond, Solubility and thermodynamic properties of carbonate-bearing hydrotalcite-pyroaurite solid solutions with a 3:1 Mg/(Al $^+$ Fe) mole ratio, Clay Clay Miner. 59 (2011) 215–232. \n[40] D. Nied, K. Enemark-Rasmussen, E. L'Hôpital, J. Skibsted, B. Lothenbach, Properties of magnesium silicate hydrates (M-S-H), Cem. Concr. Res. 79 (2016) 323–332. \n[41] B. Lothenbach, E. Bernard, U. Mäder, Zeolite formation in the presence of cement hydrates and albite, Phys. Chem. Earth 99 (2017) 77–94. \n[42] V.J. Babushkin, G.M. Matveyev, O.P. Mchedlov-Petrossyan, Thermodynamics of Silicates, Springer-Verlag, Berlin, H, 1985. \n[43] H.C. Helgeson, J.M. Delany, H.W. Nesbitt, D.K. Bird, Summary and critique of the thermodynamic properties of rock-forming minerals, Am. J. Sci. 278-A (1978) 1–229. \n[44] R.A. Robie, B.S. Hemingway, Thermodynamic properties of minerals and related substances at 298.15 K and 1 bar (105 Pascals) pressures and at higher temperatures, U.S. Geol. Surv. Bull. 2131 (1995) 1–461. \n[45] G. Möschner, B. Lothenbach, A. Ulrich, R. Figi, R. Kretschmar, Solid solution between Al-ettringite and Fe-ettringite $(\\mathrm{Ca}_{6}[\\mathrm{Al}_{1-\\mathrm{x}}\\mathrm{Fe}_{\\mathrm{x}}(\\mathrm{OH})_{6}]_{2}(\\mathrm{SO}_{4})_{3}{\\cdot}26\\mathrm{H}_{2}\\mathrm{O})$ , Cem. Concr. Res. 39 (2009) 482–489. \n[46] E. Corazza, C. Sabelli, The crystal structure of syngenite, $\\mathrm{K}_{2}\\mathrm{Ca}(\\mathrm{SO}_{4})_{2}{\\cdot}\\mathrm{H}_{2}\\mathrm{O}$ , Z Kristallog 124 (1967) 398–408. \n[47] P. Blanc, P. Vieillard, H. Gailhanou, S. Gaboreau, N. Marty, F. Claret, B. Made, E. Giffaut, ThermoChimie database developments in the framework of cement/ clay interactions, Appl. Geochem. 55 (2015) 95–107. \n[48] R.M. Milton, Molecular sieve adsorbents, US Patent No (1959) 2,882,244. \n[49] G. Gottardi, E. Galli, Natural Zeolites, Mineral and Rocks, 18 (1985). \n[50] H. Boysen, M. Lerch, A. Stys, A. Senyshyn, Structure and oxygen mobility in mayenite $\\mathrm{(Ca_{12}A l_{14}O_{33})}$ : a high-temperature neutron powder diffraction study, Acta Crystallogr. B63 (2007) 675–682. \n[51] W. Hörkner, H. Müller-Buschbaum, Zur Kristallstruktur von $\\mathrm{CaAl}_{2}\\mathrm{O}_{4},$ J. Inorg. Nucl. Chem. 38 (1976) 983–984. \n[52] D.W. Goodwin, A.J. Lindop, The crystal structure of $\\mathrm{CaO}{\\cdot}2\\mathrm{Al}_{2}\\mathrm{O}_{3},$ Acta Crystallogr B 26 (1970) 1230–1235. \n[53] F. Winnefeld, B. Lothenbach, Phase equilibria in the system $\\mathrm{Ca}_{4}\\mathrm{Al}_{6}\\mathrm{O}_{12}\\mathrm{SO}_{4}-$ $\\mathrm{Ca_{2}S i O_{4}-C a S O_{4}-H_{2}O}$ referring to the hydration of calcium sulfoaluminate cements, RILEM Tech. Lett. 1 (2016) 10–16. \n[54] D. Damidot, S.J. Barnett, F.P. Glasser, D.E. Macphee, Investigation of the CaO$\\mathrm{Al_{2}O_{3}{-}S i O_{2}{-}C a S O_{4}{-}C a C O_{3}{-}H_{2}O}$ system at $25^{\\circ}\\mathrm{C}$ by thermodynamic calculation, Adv. Cem. Res. 16 (2004) 69–76. \n[55] T. Schmidt, B. Lothenbach, M. Romer, K.L. Scrivener, D. Rentsch, R. Figi, A thermodynamic and experimental study of the conditions of thaumasite formation, Cem. Concr. Res. 38 (2008) 337–349. \n[56] D.E. Macphee, S.J. Barnett, Solution properties of solids in the ettringite-thaumasite solid solution series, Cem. Concr. Res. 34 (2004) 1591–1598. \n[57] F. Bellmann, On the formation of thaumasite $\\mathrm{CaSiO_{3}{\\cdot}C a S O_{4}{\\cdot}C a C O_{3}{\\cdot}15H_{2}O}$ : part I, Adv. Cem. Res. 16 (2004) 55–60. \n[58] U.A. Birnin-Yauri, F.P. Glasser, Friedel's salt, $\\mathrm{Ca_{2}A l(O H)_{6}(C l,O H){\\cdot}2H_{2}O};$ its solid solutions and their role in chloride binding, Cem. Concr. Res. 28 (1998) 1713–1723. \n[59] M.Y. Hobbs, Solubilities and Ion Exchange Properties of Solid Solutions Between OH, Cl and $\\mathrm{CO}_{3}$ End Members of the Monocalcium Aluminate Hydrates, Thesis University of Waterloo, Ontario, Canada, 2001. \n[60] J.V. Bothe Jr, P.W. Brown, PhreeqC modeling of Friedel's salt equilibria at $23\\pm1^{\\circ}\\mathrm{C},$ Cem. Concr. Res. 34 (2004) 1057–1063. \n[61] R.O. Grishchenko, A.L. Emelina, P.Y. Makarov, Thermodynamic properties and thermal behavior of Friedel's salt, Thermochim. Acta 570 (2013) 74–79. \n[62] F.P. Glasser, A. Kindness, S.A. Stronach, Stability and solubility relationships in AFm phases. Part I. Chloride, sulfate and hydroxide, Cem. Concr. Res. 29 (1999) 861–866. \n[63] G. Falzone, M. Balonis, G. Sant, X-AFm stabilization as a mechanism of bypassing conversion phenomena in calcium aluminate cements, Cem. Concr. Res. 72 (2015) 54–68. \n[64] B.Z. Dilnesa, E. Wieland, B. Lothenbach, R. Dähn, K. Scrivener, Fe-containing phases in hydrated cements, Cem. Concr. Res. 58 (2014) 45–55. \n[65] M. Vespa, E. Wieland, R. Dähn, B. Lothenbach, Identification of the thermodynamically stable Fe-containing phase in aged cement pastes, J. Am. Ceram. Soc. 98 (2015) 2286–2294. \n[66] H.F.W. Taylor, D.E. Newbury, An electron microporbe study of a mature cement aste, Cem. Concr. Res. 14 (1984) 565–573. \n[67] U. Mäder, A. Jenni, C. Lerouge, S. Gaboreau, S. Miyoshi, Y. Kimura, V. Cloet, M. Fukaya, F. Claret, T. Otake, M. Shibata, B. Lothenbach, 5-year chemico-physical evolution of concrete–claystone interfaces, Mont Terri rock laboratory (Switzerland), Swiss J. Geosci. 110 (2017) 307–327. \n[68] S.A. Bernal, R. San Nicols, R.J. Myers, R. Mejia de Gutierrez, F. Puertas, J.S.J. Van Deventer, J.L. Provis, MgO content of slag controls phase evolution and structural changes induced by accelerated carbonation in alkali-activated binders, Cem. Concr. Res. 57 (2014) 33–43. \n[69] I.G. Richardson, A.R. Brough, G.W. Groves, C.M. Dobson, The characterization of hardened alkali-activated blast-furnace slag pastes and the nature of the calcium silicate hydrate (C-S-H) phase, Cem. Concr. Res. 24 (1994) 813–829. \n[70] H. Taylor, Crystal structures of some double hydroxide minerals, Mineral. Mag. 39 (1973) 377–389. \n[71] I. Richardson, Clarification of possible ordered distributions of trivalent cations in layered double hydroxides and an explanation for the observed variation in the lower solid-solution limit, Acta Crystallogr. B 69 (2013) 629–633. \n[72] D.G. Bennett, D. Read, M. Atkins, F.P. Glasser, A thermodynamic model for blended cements. II: cement hydrate phases; thermodynamic values and modelling studies, J. Nucl. Mater. 190 (1992) 315–325. \n[73] W. Gao, Z. Li, Solubility and K SP of $\\mathrm{Mg_{4}A l_{2}(O H)_{14}{:}3H_{2}O}$ at the various ionic strengths, Hydrometallurgy 117–118 (2012) 36–46. \n[74] R.J. Myers, B. Lothenbach, S. Bernal, J.L. Provis, Thermodynamic modelling of alkali-activated slag-based cements, Appl. Geochem. 61 (2015) 233–247. \n[75] M. Zajac, S.K. Bremseth, M. Whitehead, M. Ben Haha, Effect of CaMg $\\mathrm{(CO}_{3})_{2}$ on hydrate assemblages and mechanical properties of hydrated cement pastes at $40^{\\circ}\\mathrm{C}$ and $60^{\\circ}\\mathrm{C},$ Cem. Concr. Res. 65 (2014) 21–29. \n[76] B. Lothenbach, A. Nonat, Calcium silicate hydrates: solid and liquid phase composition, Cem. Concr. Res. 78 (2015) 57–70. \n[77] I. Richardson, Tobermorite/jennite-and tobermorite/calcium hydroxide-based models for the structure of CSH: applicability to hardened pastes of tricalcium silicate, $\\upbeta$ -dicalcium silicate, Portland cement, and blends of Portland cement with blast-furnace slag, metakaolin, or silica fume, Cem. Concr. Res. 34 (2004) 1733–1777. \n[78] A. Muller, K. Scrivener, A. Gajewicz, P. McDonald, Use of bench-top NMR to measure the density, composition and desorption isotherm of C–S–H in cement paste, Microporous Mesoporous Mater. 178 (2013) 99–103. \n[79] A. Muller, K. Scrivener, J. Skibsted, A. Gajewicz, P. McDonald, Influence of silica fume on the microstructure of cement pastes: new insights from $^1\\mathrm{H}$ NMR relaxometry, Cem. Concr. Res. 74 (2015) 116–125. \n[80] C.S. Walker, S. Sutou, C. Oda, M. Mihara, A. Honda, Calcium silicate hydrate (C-SH) gel solubility data and a discrete solid phase model at $25^{\\circ}\\mathrm{C}$ based on two binary non-ideal solid solutions, Cem. Concr. Res. 79 (2016) 1–30. \n[81] S.-Y. Hong, F.P. Glasser, Alkali binding in cement pastes: part I. The C-S-H phase, Cem. Concr. Res. 29 (1999) 1893–1903. \n[82] E. L'Hôpital, B. Lothenbach, D. Kulik, K. Scrivener, Influence of calcium to silica ratio on aluminium uptake in calcium silicate hydrate, Cem. Concr. Res. 85 (2016) 111–121. \n[83] E. L'Hôpital, B. Lothenbach, G. Le Saout, D.A. Kulik, K. Scrivener, Incorporation of aluminium in calcium-silicate hydrate, Cem. Concr. Res. 75 (2015) 91–103. \n[84] E. L'Hôpital, B. Lothenbach, K. Scrivener, D.A. Kulik, Alkali uptake in calcium alumina silicate hydrate (C-A-S-H), Cem. Concr. Res. 85 (2016) 122–136. \n[85] D.A. Kulik, M. Kersten, Aqueous solubility diagrams for cementitious waste stabilization systems: II, end-member stoichiometries of ideal calcium silicates hydrate solid solutions, J. Am. Ceram. Soc. 84 (2001) 3017–3026. \n[86] J. Haas, A. Nonat, From C–S–H to C–A–S–H: experimental study and thermodynamic modelling, Cem. Concr. Res. 68 (2015) 124–138. \n[87] S.V. Churakov, C. Labbez, Thermodynamics and molecular mechanism of Al incorporation in calcium silicate hydrates, J. Phys. Chem. C 121 (2017) 4412–4419. \n[88] D. Kulik, J. Tits, E. Wieland, Aqueous-solid solution model of strontium uptake in C-S-H phases, Geochim. Cosmochim. Acta 71 (2007) A530. \n[89] B. Lothenbach, G. Le Saout, M. Ben Haha, R. Figi, E. Wieland, Hydration of a lowalkali CEM III/B- ${\\cdot\\mathrm{SiO}_{2}}$ cement (LAC), Cem. Concr. Res. 42 (2012) 410–423. \n[90] R. Myers, S.A. Bernal, J.L. Provis, A thermodynamic model for C-(N-)A-S-H gel: CNASH_ss. Derivation and validation, Cem. Concr. Res. 66 (2014) 27–47. \n[91] D. Kulik, Dual-thermodynamic estimation of stoichiometry and stability of solid solution end members in aqueous-solid solution systems, Chem. Geol. 225 (2006) 189–212. \n[92] J. Tits, E. Wieland, C.J. Müller, C. Landesman, M.H. Bradbury, Strontium binding by calcium silicate hydrates, J. Colloid Interface Sci. 300 (2006) 78–87. \n[93] D.D. Wagman, E.H. Evans, V.B. Parker, R.H. Schumm, I. Halow, S.M. Bailey, K.L. Churney, L. N.R., The NBS tables of chemical thermodynamic properties. Selected values for inorganic and C1 and C2 organic substances in SI units, J. Phys. Chem. Ref. Data 11 (Suppl. 2) (1982) 1–392. \n[94] I.G. Richardson, The calcium silicate hydrates, Cem. Concr. Res. 38 (2008) 137–158. \n[95] J.J. Chen, J.J. Thomas, H.F.W. Taylor, H.M. Jennings, Solubility and structure of calcium silicate hydrate, Cem. Concr. Res. 34 (2004) 1499–1519. \n[96] K. Garbev, M. Bornefeld, G. Beuchle, P. Stemmermann, Cell dimensions and composition of nanocrystalline calcium silicate hydrate solid solutions. part 2: XRay and thermogravimetry study, J. Am. Ceram. Soc. 91 (2008) 3015–3023. \n[97] X. Gaona, D.A. Kulik, N. Macé, E. Wieland, Aqueous–solid solution thermodynamic model of U(VI) uptake in C–S–H phases, Appl. Geochem. 27 (2012) 81–95. \n[98] A.J. Allen, J.J. Thomas, H.M. Jennings, Composition and density of nanoscale calcium–silicate–hydrate in cement, Nat. Mater. 6 (2007) 311–316. \n[99] J.J. Thomas, A.J. Allen, H.M. Jennings, Density and water content of nanoscale solid C–S–H formed in alkali-activated slag (AAS) paste and implications for chemical shrinkage, Cem. Concr. Res. 42 (2012) 377–383. \n[100] J.L. Provis, S.A. Bernal, Geopolymers and related alkali-activated materials, Annu. Rev. Mater. Res. 44 (2014) 299–327. \n[101] R.J. Myers, S.A. Bernal, J.L. Provis, Phase diagrams for alkali-activated slag binders, Cem. Concr. Res. 95 (2017) 30–38. \n[102] C.S. Walker, D. Savage, M. Tyrer, K.V. Ragnarsdottir, Non-ideal solid solution aqueous solution modeling of synthetic calcium silicate hydrate, Cem. Concr. Res. 37 (2007) 502–511. \n[103] L. Gomez-Zamorano, M. Balonis, B. Erdemli, N. Neithalath, G. Sant, C–(N)–S–H and N–A–S–H gels: Compositions and solubility data at $25^{\\circ}\\mathrm{C}$ and $50^{\\circ}\\mathrm{C},$ J. Am. Ceram. Soc. 100 (2017) 2700–2711. \n[104] R.J. Myers, E. L'Hôpital, J.L. Provis, B. Lothenbach, Effect of temperature and aluminium on calcium (alumino)silicate hydrate chemistry under equilibrium conditions, Cem. Concr. Res. 68 (2015) 83–93. \n[105] R.J. Myers, E. L'Hôpital, J.L. Provis, B. Lothenbach, Composition-solubility-structure relationships in calcium (alkali) aluminosilicate hydrate (C-(N,K-)A-S-H), Dalton Trans. 44 (2015) 13530–13544. \n[106] G.D. Miron, D.A. Kulik, S.V. Dmytrieva, T. Wagner, GEMSFITS: code package for optimization of geochemical model parameters and inverse modeling, Appl. Geochem. 55 (2015) 28–45. \n[107] L. Nicoleau, E. Schreiner, Determination of $\\mathrm{Ca^{2+}}$ complexation constants by monomeric silicate species at $25^{\\circ}\\mathrm{C}$ with a $\\mathsf{C a}^{2+}$ ion selective electrode, Cem. Concr. Res. 98 (2017) 36–43. \n[108] A. Jenni, U. Mäder, C. Lerouge, S. Gaboreau, B. Schwyn, In situ interaction between different concretes and Opalinus clay, Phys. Chem. Earth, 70–71 (2014) 71–83. \n[109] A. Dauzères, G. Achiedo, D. Nied, E. Bernard, S. Alahrache, B. Lothenbach, Magnesium perturbation in low-pH concretes placed in clayey environment—solid acterizat and modeling, Cem. Con \n[110] D. Bonen, M.D. Cohen, Magnesium sulfate attack on portland cement paste—II. Chemical and mineralogical analyses, Cem. Concr. Res. 22 (1992) 707–718. \n[111] M. Santhanam, M.D. Cohen, J. Olek, Mechanism of sulfate attack: a fresh look: part 1: summary of experimental results, Cem. Concr. Res. 32 (2002) 915–921. \n[112] U.H. Jakobsen, K. De Weerdt, M.R. Geiker, Elemental zonation in marine concrete, Cem. Concr. Res. 85 (2016) 12–27. \n[113] C. Roosz, S. Grangeon, P. Blanc, V. Montouillout, B. Lothenbach, P. Henocq, E. Giffaut, P. Vieillard, S. Gaboreau, Crystal structure of magnesium silicate hydrates (M S H): the relation with 2:1 Mg–Si phyllosilicates, Cem. Concr. Res. 73 (2015) 228–237. \n[114] E. Bernard, B. Lothenbach, F. Le Goff, I. Pochard, A. Dauzères, Effect of magnesium on calcium silicate hydrates (C-S-H), Cem. Concr. Res. 97 (2017) 61–72. \n[115] D.R.M. Brew, F.P. Glasser, Synthesis and characterisation of magnesium silicate hydrate gels, Cem. Concr. Res. 35 (2005) 85–98. \n[116] B. Lothenbach, D. Nied, E. L'Hôpital, G. Achiedo, A. Dauzères, Magnesium and calcium silicate hydrates, Cem. Concr. Res. 77 (2015) 60–68. \n[117] W.-S. Chiang, G. Ferraro, E. Fratini, F. Ridi, Y.-Q. Yeh, U. Jeng, S.-H. Chen, P. Baglioni, Multiscale structure of calcium-and magnesium-silicate-hydrate gels, J. Mater. Chem. A 2 (2014) 12991–12998. \n[118] E. Bernard, B. Lothenbach, D. Rentsch, I. Pochard, A. Dauzères, Formation of magnesium silicate hydrates (M-S-H), Phys. Chem. Earth 99 (2017) 142–157. \n[119] J.A.T. Smellie, Maqarin Natural Analogue Study: Phase III, SKB, SKB Technical Report 98-04, Stockholm, Sweden, 1998. \n[120] S.J. Chipera, J.A. Apps, Geochemical stability of natural zeolites, Rev. Mineral. Geochem. 45 (2001) 117–161. \n[121] R. Arthur, H. Sasamoto, C. Walker, M. Yui, Polymer model of zeolite thermochemical stability, Clays Clay Miner. 59 (2011) 626–639. \n[122] J.L. Provis, G.C. Lukey, J.S. van Deventer, Do geopolymers actually contain nanocrystalline zeolites? A reexamination of existing results, Chem. Mater. 17 (2005) 3075–3085. \n[123] B. Lothenbach, G. Le Saout, E. Gallucci, K. Scrivener, Influence of limestone on the hydration of Portland cements, Cem. Concr. Res. 38 (2008) 848–860. \n[124] K. De Weerdt, M. Ben Haha, G. Le Saout, K.O. Kjellsen, H. Justnes, B. Lothenbach, Hydration mechanisms of ternary Portland cements containing limestone powder and fly ash, Cem. Concr. Res. 41 (2011) 279–291. \n[125] F. Deschner, F. Winnefeld, B. Lothenbach, S. Seufert, P. Schwesig, S. Dittrich, F. Goetz-Neunhoeffer, J. Neubauer, Hydration of a Portland cement with high replacement by siliceous fly ash, Cem. Concr. Res. 42 (2012) 1389–1400. \n[126] T.G. Jappy, F.P. Glasser, Synthesis and stability of silica-substituted hydrogarnet $\\mathrm{Ca_{3}A l_{2}S i_{3-x}O_{12-4x}(O H)_{4x},}$ Adv. Cem. Res. 4 (1991) 1–8. \n[127] A. Vollpracht, B. Lothenbach, R. Snellings, J. Haufe, The pore solution of blended cements: a review, Mater. Struct. 49 (2016) 3341–3367. \n[128] W.R. Smith, R.W. Missen, Chemical Reaction Equilibrium Analysis: Theory and Algorithms, Wiley-Interscience, New York 1982. Reprinted With Corrections, Krieger, Malabar, ${\\mathrm{FL}},$ (1991). \n[129] T. Matschei, F.P. Glasser, New approaches to quantification of cement hydration, in: J. Stark (Ed.), 16 Internationale Baustofftagung (ibausil), Weimar, Germany, 2006, pp. 390–400. \n[130] B.J. Merkel, B. Planer-Friederich, Groundwater Geochemistry. A Practical Guide to Modeling of Natural and Contaminated Aquatic Systems, Springer Berlin, 2008. \n[131] G.M. Anderson, D.A. Crerar, Thermodynamics in Geochemistry: The Equilibrium Model, Oxford University Press, Oxford, 1993. \n[132] D. Kulik, Minimising uncertainty induced by temperature extrapolations of thermodynamic data: a pragmatic view on the integration of thermodynamic databases into geochemical computer codes, The Use of Thermodynamic Databases in Performance Assessment, OECD, Barcelona, 2002, pp. 125–137. \n[133] J.W. Johnson, E.H. Oelkers, H.C. Helgeson, SUPCRT92: a software package for calculating the standard molal thermodynamic properties of minerals, gases, aqueous species, and reactions from 1 to 5000 bar and 0 to $1000^{\\circ}\\mathrm{C}$ Comput. Geosci. 18 (1992) 899–947. " + }, + { + "id": "10.1038_s41586-019-1052-3", + "DOI": "10.1038/s41586-019-1052-3", + "DOI Link": "http://dx.doi.org/10.1038/s41586-019-1052-3", + "Relative Dir Path": "mds/10.1038_s41586-019-1052-3", + "Article Title": "Van der Waals contacts between three-dimensional metals and two-dimensional semiconductors", + "Authors": "Wang, Y; Kim, JC; Wu, RJ; Martinez, J; Song, XJ; Yang, J; Zhao, F; Mkhoyan, KA; Jeong, HY; Chhowalla, M", + "Source Title": "NATURE", + "Abstract": "As the dimensions of the semiconducting channels in fieldeffect transistors decrease, the contact resistance of the metalsemiconductor interface at the source and drain electrodes increases, dominating the performance of devices(1-3). Two-dimensional (2D) transition-metal dichalcogenides such as molybdenum disulfide (MoS2) have been demonstrated to be excellent semiconductors for ultrathin field-effect transistors(4,5). However, unusually high contact resistance has been observed across the interface between the metal and the 2D transition-metal dichalcogenide(3,5-9). Recent studies have shown that van der Waals contacts formed by transferred graphene(10,11) and metals(12) on few-layered transitionmetal dichalcogenides produce good contact properties. However, van der Waals contacts between a three-dimensional metal and a monolayer 2D transition-metal dichalcogenide have yet to be demonstrated. Here we report the realization of ultraclean van der Waals contacts between 10-nullometre-thick indium metal capped with 100-nullometre-thick gold electrodes and monolayer MoS2. Using scanning transmission electron microscopy imaging, we show that the indium and gold layers form a solid solution after annealing at 200 degrees Celsius and that the interface between the gold-capped indium and the MoS2 is atomically sharp with no detectable chemical interaction between the metal and the 2D transition-metal dichalcogenide, suggesting van-der-Waals-type bonding between the gold-capped indium and monolayer MoS2. The contact resistance of the indium/gold electrodes is 3,000 +/- 300 ohm micrometres for monolayer MoS2 and 800 +/- 200 ohm micrometres for few-layered MoS2. These values are among the lowest observed for three-dimensional metal electrodes evaporated onto MoS2, enabling high-performance field-effect transistors with a mobility of 167 +/- 20 square centimetres per volt per second. We also demonstrate a low contact resistance of 220 +/- 50 ohm micrometres on ultrathin niobium disulfide (NbS2) and near-ideal band offsets, indicative of defect-free interfaces, in tungsten disulfide (WS2) and tungsten diselenide (WSe2) contacted with indium alloy. Our work provides a simple method of making ultraclean van der Waals contacts using standard laboratory technology on monolayer 2D semiconductors.", + "Times Cited, WoS Core": 653, + "Times Cited, All Databases": 712, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000463384900041", + "Markdown": "# Van der Waals contacts between three-dimensional metals and two-dimensional semiconductors \n\nYan Wang1,2, Jong Chan $\\mathrm{Kim}^{3}$ , Ryan J. $\\mathrm{Wu^{4}}$ , Jenny Martinez5, Xiuju Song2,6, Jieun Yang1,2, Fang Zhao7, Andre Mkhoyan4, Hu Young Jeong3 & Manish Chhowalla1,2,6\\* \n\nAs the dimensions of the semiconducting channels in fieldeffect transistors decrease, the contact resistance of the metal– semiconductor interface at the source and drain electrodes increases, dominating the performance of devices1–3. Two-dimensional (2D) transition-metal dichalcogenides such as molybdenum disulfide $(\\mathbf{MoS}_{2})$ ) have been demonstrated to be excellent semiconductors for ultrathin field-effect transistors4,5. However, unusually high contact resistance has been observed across the interface between the metal and the 2D transition-metal dichalcogenide3,5–9. Recent studies have shown that van der Waals contacts formed by transferred graphene10,11 and metals12 on few-layered transitionmetal dichalcogenides produce good contact properties. However, van der Waals contacts between a three-dimensional metal and a monolayer 2D transition-metal dichalcogenide have yet to be demonstrated. Here we report the realization of ultraclean van der Waals contacts between 10-nanometre-thick indium metal capped with 100-nanometre-thick gold electrodes and monolayer $\\mathbf{MoS}_{2}$ . Using scanning transmission electron microscopy imaging, we show that the indium and gold layers form a solid solution after annealing at 200 degrees Celsius and that the interface between the gold-capped indium and the $\\mathbf{MoS}_{2}$ is atomically sharp with no detectable chemical interaction between the metal and the 2D transition-metal dichalcogenide, suggesting van-der-Waals-type bonding between the gold-capped indium and monolayer $\\mathbf{MoS}_{2}$ . The contact resistance of the indium/gold electrodes is $\\mathbf{3,000\\pm3000hm}$ micrometres for monolayer $\\mathbf{MoS}_{2}$ and ${\\bf800\\pm200}$ ohm micrometres for few-layered $\\mathbf{MoS}_{2}$ . These values are among the lowest observed for three-dimensional metal electrodes evaporated onto $\\mathbf{MoS}_{2},$ enabling high-performance field-effect transistors with a mobility of ${\\bf167\\pm20}$ square centimetres per volt per second. We also demonstrate a low contact resistance of ${\\bf220\\pm50}$ ohm micrometres on ultrathin niobium disulfide $(\\mathbf{Nb}\\mathbf{S}_{2})$ and near-ideal band offsets, indicative of defect-free interfaces, in tungsten disulfide $(\\mathbf{W}\\mathbf{S}_{2})$ and tungsten diselenide $\\mathbf{(WSe}_{2})$ contacted with indium alloy. Our work provides a simple method of making ultraclean van der Waals contacts using standard laboratory technology on monolayer 2D semiconductors. \n\nField-effect transistors (FETs) using 2D semiconductors as the channel material offer excellent gate electrostatics, which allows mitigation of short channel effects—making them interesting for sub- $.10\\mathrm{-nm}$ node devices13. However, in short-channel devices, the transport through the semiconductor is nearly ballistic and almost all of the power is dissipated at the contacts1. Thus, optimizing the contacts between 2D semiconductors and metal electrodes is an important technological challenge. Several strategies, such as phase engineering to create lateral metal–semiconductor–metal heterojunctions14, formation of clean interfaces via van der Waals contacts using graphene10,11, mechanical transfer of metal films12 and using hexagonal boron nitride (h-BN) as the tunnel barrier15, have been reported to improve the electrical properties of contacts on 2D materials. The main challenge in making contacts on atomically thin materials exposed to the atmosphere is the presence of adsorbed water or hydrocarbon layers on their surface. The thickness of these layers is comparable to that of 2D semiconductors so that when metal electrodes are deposited, the adsorbed contaminants are incorporated at the interface between the metal and the 2D semiconductor. This leads to the creation of interface states that can pin the Fermi level and increase the contact resistance16. It is possible to minimize the impact of adsorbed layers by depositing metal electrodes under ultrahigh vacuum17,18, which reduces the contact resistance. In addition, the transfer of thin metal films12 or few-layered mechanically exfoliated $\\mathrm{h}{-}\\mathrm{BN}^{15}$ on top of 2D semiconductors can squeeze out adsorbed layers. However, even when the adsorbed layer is removed, the direct deposition of metal can lead to substantial damage via kinetic energy transfer or chemical reaction between the metal atoms and the 2D semiconductor. Studies have shown that creation of van der Waals contacts via metal transfer12, graphene10,11 or $\\mathrm{h}{-}\\mathrm{BN}^{15}$ on 2D semiconductors can create clean interfaces without damaging the underlying 2D semiconductor. However, all of these strategies for improving contact properties have been reported for multi-layer 2D semiconductors; clean interfaces with low contact resistance have yet to be reported for single layers. \n\nWe have characterized the ultraclean van der Waals interface formed between monolayer 2D $\\mathbf{MoS}_{2}$ and indium/gold $\\mathrm{{(In/Au)}}$ electrodes deposited using a standard laboratory electron-beam evaporator under normal vacuum ( $\\cdot<10^{-6}$ Torr) using annular dark field (ADF) scanning transmission electron microscopy (STEM) and $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS). The electrodes consist of $10\\mathrm{-nm}$ -thick In capped with $100\\mathrm{-nm}$ -thick Au to prevent reaction of In with the environment. The schematic of the FET device tested in this work is shown in Fig. 1a (see Methods for details of electrode deposition and device fabrication). To image and study the interface between In/Au and $\\mathbf{MoS}_{2}$ , we conducted cross-sectional ADF STEM. It is well known that monolayer and few-layered transition-metal dichalcogenides are damaged during metal deposition12,16 and that only dry transfer of electrodes provide clean and intact interfaces12. By contrast, our analysis reveals that the $\\mathrm{In}/\\mathrm{Au}{-}\\mathrm{Mo}\\mathsf{S}_{2}$ interfaces for monolayer (see Fig. 1b, a broader view image is provided in Extended Data Fig. 1a) and few-layered (see Extended Data Fig. 1b, d) $\\ensuremath{\\mathrm{MoS}}_{2}$ are atomically sharp with no detectable evidence of reaction between the layers of $\\mathrm{In/Au}$ and $\\mathbf{MoS}_{2}$ . The ADF and bright-field STEM images in Fig. 1b clearly show the monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ and $\\mathrm{In/Au}$ alloy contact on top with atomic resolution. An ADF intensity profile across the interface for $\\mathrm{In/Au}$ on monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ revealed that the spacing between the sulfur atoms and In/Au atoms is $2.4\\mathring{\\mathrm{A}}\\pm0.3\\mathring{\\mathrm{A}}$ (Extended Data Fig. 1c)—indicating that the In gently deposits on the 2D semiconductor without causing any damage. Our chemical analysis reveals that only vacuum in the form of a van der Waals gap is observed at the interface and that no evidence for oxidation or indium sulfide formation is observed. XPS was performed \n\n![](images/4bb8ff4f9eaef2d603509f3ff0b4496f21de4538459eed897eb6bc91b07c3571.jpg) \nFig. 1 | Atomic resolution imaging and chemical analyses of $\\mathbf{In}/\\mathbf{Au}.$ - $\\mathbf{MoS}_{2}$ interface. a, Device structure of the bottom-gate FET used in this study. The electrodes consist of $10\\mathrm{-nm}$ -thick In capped with $100\\mathrm{-nm}$ -thick Au. The ellipse under the contact indicates the interface region that was analysed using high-resolution STEM. b, Atomic-resolution images of $\\mathrm{In}/$ Au on monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ . (ii), Low-pass filtered ADF STEM image showing Mo, S and $\\mathrm{In/Au}$ atoms as indicated by the enlarged image (i). (iii), \n\nCorresponding bright-field STEM image of the monolayer. Scale bars, $5\\mathrm{\\AA}$ to characterize the chemistry at the interface between the uppermost sulfur layer and the In/Au alloy. The binding energy values for the Mo $3d$ and $s2p$ doublets were found to be $229.3\\mathrm{eV}$ (Mo $3d_{5/2,}\\cdot$ ) and $162.1\\mathrm{eV}$ $(\\S2p_{3/2})$ —typical of pristine $\\ensuremath{\\mathrm{MoS}}_{2}$ (ref. 19). Nonstoichiometric $\\mathrm{Mo}_{x}\\mathrm{S}_{y}$ peaks were not observed, as indicated in Fig. 1c. Additional information about the chemical state of the interface is provided by the In $3d$ spectra and In MNN Auger measurements in Extended Data Fig. 1e, f. We corroborated this using electron energy loss spectroscopy (Fig. 1d). The electron energy loss spectroscopy was measured using a focused electron beam probe with spatial resolution of $0.8\\mathring\\mathrm{\\mathrm{A}}$ so that the spectra from highly localized regions at the interface could be obtained. It can be seen that the sulfur $\\mathrm{L}_{2,3}$ -edge exhibits an experimentally negligible difference between the topmost $\\ensuremath{\\mathrm{MoS}}_{2}$ layer in contact with the $\\mathrm{In/Au}$ and the fifth layer of $\\ensuremath{\\mathrm{MoS}}_{2}$ —suggesting that the deposition of In and \n\nAu does not introduce any chemical reactions, distortions or strain at the metal/semiconductor interface or within the 2D $\\ensuremath{\\mathrm{MoS}}_{2}$ . \n\nTo investigate whether the excellent structural features of van der Waals contacts with In/Au can be translated into better device performance, we measured the contact resistance using the transmission line method (TLM) and also the FET properties. The TLM results shown in Fig. 2a for In/Au electrodes on chemical vapour deposition (CVD)- grown monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ (see Extended Data Fig. 1g, h) reveal a contact resistance of $3.3\\pm0.3\\mathrm{k}\\Omega\\upmu\\mathrm{m}$ (at $n=5.0\\times10^{12}\\mathrm{{cm}^{-2})}$ and values of $800\\pm200\\Omega\\upmu\\mathrm{m}$ (at $n=3.1\\times10^{12}\\mathrm{cm}^{-2}$ , Extended Data Fig. 2a) were measured for few-layered mechanically exfoliated $\\mathbf{MoS}_{2}$ . The higher contact resistance in monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ compared to the few-layered material can be attributed to substrate-carrier scattering17. Despite this, the contact resistances of In/Au electrodes on monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ (Fig. 2b, c) \n\n![](images/cb4918b67e53850d40d9d860d244f81454a9a629a7d66ea9bc4fce5f7785c2b2.jpg) \nc, XPS of the $\\mathrm{In}/\\mathrm{Au}{-}\\mathrm{MoS}_{2}$ interface showing pristine Mo and S peaks. The XPS also shows that the deposition of $\\mathrm{In/Au}$ does not modify the $\\ensuremath{\\mathrm{MoS}}_{2}$ . d, Electron energy loss spectroscopy of the S $\\mathrm{L}_{2,3}$ -edge, showing that the sulfur atoms of the top layer are completely unaffected by the deposition of metal on top. The sulfur peaks of the topmost and the fifth layer are the same within the precision of the measurement, as indicated by the difference spectra (Diff.) shown in the bottom panel. a.u., arbitrary units. \nFig. 2 | Contact resistance and device properties of $\\mathbf{In}/\\mathbf{Au}$ electrodes comparison18. c, Comparison of contact resistance from the literature and on monolayer $\\mathbf{MoS}_{2}$ . a, Contact resistance $R_{\\mathrm{C}}$ extracted using TLM. our results for different types of electrode materials6,7,11,18,21–23. d, Typical The error bars result from the averaging of least five measurements; this transfer characteristics of a field-effect transistor with monolayer $\\mathbf{MoS}_{2}$ is the same for all the TLM results mentioned in this work. b, Contact as the channel and $\\mathrm{In/Au}$ alloy as the source and drain electrodes. The resistance versus carrier concentration $n$ for $\\mathrm{In/Au}$ electrodes at room length and width of the device are $2\\upmu\\mathrm{m}$ and $6\\upmu\\mathrm{m}$ A mobility of about temperature (filled points) and at $80\\mathrm{K}$ (open points). Au electrodes $17\\mathrm{0}\\mathrm{^cm}^{2}\\mathrm{V}^{-1}\\mathrm{}s^{-1}$ can be achieved with $\\mathrm{In/Au}$ electrodes. e, Linear output deposited under ultrahigh vacuum (UHV, $10^{-9}$ Torr) are provided for characteristics indicating the absence of a contact barrier. \n\n![](images/969cad6204b5733424bc452cf4645fd25f6a8625b657747811ea97766a142f14.jpg) \nFig. 3 | Contact properties of $\\mathbf{In/Au}$ electrodes on 2D $\\mathbf{Nb}\\mathbf{S}_{2}$ and $\\mathbf{WS}_{2}$ . with $\\mathrm{WS}_{2}$ as the channel material and $\\mathrm{In/Au}$ contacts; the length and width a, TLM contact resistance of $\\mathrm{In/Au}$ electrodes on CVD-grown $\\mathrm{Nb}{\\mathsf S}_{2}$ . of the device are $1\\upmu\\mathrm{m}$ and $1.2\\upmu\\mathrm{m}$ at drain voltage $V_{\\mathrm{ds}}=0.5\\:\\mathrm{V}$ The transfer b, TLM contact resistance of In/Au electrodes on mechanical exfoliated curve of Ti-contacted $\\mathrm{WS}_{2}$ device is included for comparison; length and $\\mathrm{WS}_{2}$ . c, Contact resistance versus carrier concentration from different width of the devices are $0.5\\upmu\\mathrm{m}$ and $2\\upmu\\mathrm{m}$ . In/Au devices show substantially studies reported in the literature6,8,24–26. It can be seen that the $\\mathrm{In/Au}$ better mobility (approximately $85\\thinspace\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\thinspace s^{-1})$ than do devices with Ti electrodes exhibit the lowest values. d, Transfer characteristics of FETs electrodes (approximately $1\\dot{\\mathrm{cm}}^{2}\\mathrm{V}^{-1}{\\mathrm{\\Omegas}}^{-1};$ . \n\nand few-layered $\\ensuremath{\\mathrm{MoS}}_{2}$ (Extended Data Fig. 2b, c) are among the lowest reported in the literature (Extended Data Table 1) so far at all the carrier concentrations that we measured and at low temperature. For comparison, pure Au electrodes deposited under ultrahigh vacuum have slightly higher contact resistance than $\\mathrm{In/Au}$ devices (Fig. 2b, c) and the contact resistance of graphene side contacts on h-BN-encapsulated few-layered $\\mathbf{MoS}_{2}$ at $100~\\mathrm{K}$ has been measured to be $1,200\\Omega\\ensuremath{\\upmu\\mathrm{m}}$ (at $n{=}6.85\\times10^{12}\\mathrm{cm}^{-2})^{1}\\mathrm{\\Omega}$ 5. \n\n![](images/c1d0dc7de6ef1e38900b8171fe58341ff01838bfc0dd2b230dec6c26e9637560.jpg) \nFig. 4 | In alloy contacts on ultrathin $\\mathbf{WSe}_{2}$ . a, Atomic-resolution ADF The length and width of the $\\mathrm{In/Au}$ -contacted device are $1\\upmu\\mathrm{m}$ and $2\\upmu\\mathrm{m}$ STEM image and corresponding schematic of the $\\mathrm{In}/\\mathrm{Au}{-}\\mathrm{WSe}_{2}$ interface, and of the $\\mathrm{In/Pd}$ device are $0.5\\upmu\\mathrm{m}$ and $1\\upmu\\mathrm{m}$ . The inset provides the energy showing a clear van der Waals gap corresponding to spacing between band levels of ${\\mathrm{WSe}}_{2}$ and the metal where $E_{\\mathrm{C}}$ and $E_{\\mathrm{V}}$ refer to the conduction the Se and In/Au metal atoms. (ii), Intensity profile of (i) showing that and valence band energies, respectively, of the 2D semiconductor. c, Linear the distance between the bottom metal and top selenium is $2.9\\mathring\\mathrm{A}$ . output characteristics of the device. d, e, Comparison of contact resistance b, Ambipolar transfer characteristics showing n-type-dominant behaviour and drain current with values reported in the literature $\\:\\{9,27-33\\$ . with In/Au contacts and hole-dominant behaviour with $\\mathrm{In/Pd}$ contacts. \n\nTypical transfer and output curves for In/Au-contacted monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ as the channel in FETs are shown in Fig. 2d, e. The devices were fabricated on off-the-shelf thermal $\\mathrm{SiO}_{2}$ ( $300\\mathrm{nm},$ ) on Si substrates and were not encapsulated. Despite this, the transfer characteristics such as those shown in Fig. 2d exhibited sharp turn on and high currents with mobility values reaching $167\\pm20\\mathrm{\\bar{c}m^{2}V^{-1}}\\mathrm{s^{-1}}$ . Measurements of mobility with temperature reveals that the phonon-limited mobility scales as $\\dot{\\mu}\\propto T^{-1}$ at low temperatures and as $\\mu\\propto T^{-1.6}$ at high temperatures because of acoustic phonon scattering20 (Extended Data Fig. 2f). The FETs also exhibit linear output characteristics both at room temperature and at low temperatures (Extended Data Fig. 2d, e), suggesting the absence of a Schottky barrier. The highest current density we obtained for multi-layered $\\ensuremath{\\mathbf{MoS}}_{2}$ FETs was $\\mathsf{\\bar{196\\upmu A}\\upmu m^{-1}}$ (see Extended Data Table  1 for comparison with literature). Measurements as a function of temperature reveal the Schottky barrier height to be around $110\\mathrm{meV}$ (Extended Data Fig. 2g, h), which is consistent with the work function of the metal and the conduction-band energy level of $\\mathbf{MoS}_{2}$ . \n\nIn addition to $\\ensuremath{\\mathbf{MoS}}_{2}$ , we have also deposited $\\mathrm{In/Au}$ on other 2D transition-metal dichalcogenides such as $\\mathrm{Nb}{\\mathsf S}_{2}$ , $\\mathrm{WS}_{2}$ and $\\mathrm{WSe}_{2}$ . It can be seen from Fig. 3a that we obtain a contact resistance of $220\\Omega\\upmu\\mathrm{m}$ for $\\mathrm{Nb}{\\mathsf{S}}_{2}$ grown by CVD, which is among the lowest values reported for any metal contact on a 2D transition-metal dichalcogenide. The TLM plot in Fig. 3b shows that the contact resistance for $\\mathrm{WS}_{2}$ is $2.4\\pm0.5\\mathrm{k\\Omega\\upmu\\mathrm{m}}.$ , which is also among the lowest reported in the literature, as indicated by the summary of results shown in Fig. 3c. The low contact resistance in $\\mathrm{WS}_{2}$ translates into better FET performance, as indicated by the transfer characteristics shown in Fig. 3d where substantially higher mobility $(83\\pm10\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1})$ can be observed for In/Au contacts in comparison with titanium electrodes $(1.2\\pm1\\mathrm{cm}^{2}\\mathrm{V}^{-1}s^{-1})$ . Output curves of $\\mathrm{WS}_{2}$ devices are given in Extended Data Fig. 3. \n\nWe have also confirmed the formation of an ultraclean interface on ${\\mathrm{WSe}}_{2}$ . The cross-sectional ADF STEM image of In/Au electrodes on two layers of $\\mathrm{WSe}_{2}$ shown in Fig. 4a reveals a clean van der Waals interface with spacing of $2.94\\mathring{\\mathrm{A}}$ between the metal and Se, as indicated in the schematic. In/Au alloy electrodes on $\\mathrm{WSe}_{2}$ yield ambipolar FET characteristics with the electron current being higher than the hole current, as shown in Fig. 4b. The output results for both p-type and n-type devices are provided in Fig. 4c. The resistance for electron injection is $16\\mathrm{k}\\Omega\\upmu\\mathrm{m}$ and for holes it is $225\\mathrm{k}\\Omega\\upmu\\mathrm{m}$ . These large values are consistent with the large energy offsets between the Fermi level of In $\\ensuremath{(4.10\\mathrm{eV})}$ , the conduction $(3.50\\mathrm{eV})$ and valence $(4.83\\mathrm{eV})$ bands of ${\\mathrm{WSe}}_{2}$ (see inset of Fig. 4b). Our measurements reveal that the energy barrier for hole injection is $0.73\\mathrm{eV}$ and the energy barrier for electrons is $0.60\\mathrm{eV}.$ Therefore, we expect the hole current to be less than the electron current with In/Au electrodes, which is consistent with our measurements. The energy barriers for carrier injection into $\\mathrm{WSe}_{2}$ match ideally with the band offsets and the FET properties. This also suggests that the In alloy contacts form clean interfaces with $\\mathrm{WSe}_{2}$ without the creation of defects or local reactions. A comparison of contact resistance and drain current values (shown in Fig. 4d, e) reveals that the $\\mathrm{In/Au}$ contacts yield the lowest contact resistance and that both the electron and hole currents are higher than values in the literature. \n\nFinally, the soft nature of In allows it to form stable alloys readily with other metals (Extended Data Figs. 4 and 5). This property can be used to adjust the work function of electrodes to facilitate electron or hole injection while maintaining the ultraclean interface. To demonstrate this, we deposited $3\\mathrm{nm}$ of In and $100\\mathrm{nm}$ of the high-workfunction metal Pd on top. The Kelvin force microscopy results shown in Extended Data Fig. 6 show that the work function of the alloy is slightly increased, as indicated in the inset of Fig. 4b. The typical transfer curves of FET devices with $\\mathrm{In/Pd}$ alloy electrodes given in Fig. 4b exhibit higher hole current and lower electron current owing to the increased work function. The measurements indicate that the energy barrier for hole injection is $0.63\\mathrm{eV}$ and the energy barrier for electrons is $0.7\\mathrm{eV}.$ The free adjusted barrier height indicates a clean interface between the $\\mathrm{WSe}_{2}$ and the In alloy without Fermi-level pinning. \n\nIn summary, our results demonstrate ultraclean van der Waals contacts on a variety of truly 2D semiconductors. The resulting devices from such clean contacts exhibit excellent performance. Our results should lead to the realization of ultrathin electronics based on 2D semiconductors. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, statements of data availability and associated accession codes are available at https://doi.org/10.1038/s41586-019-1052-3. \n\nReceived: 24 September 2018; Accepted: 22 January 2019; \nPublished online xx xx xxxx. \n1. Chhowalla, M., Jena, D. & Zhang, H. Two-dimensional semiconductors for transistors. Nat. Rev. Mater. 1, 16052 (2016). \n2.\t Jena, D., Banerjee, K. & Xing, G. H. 2D crystal semiconductors: intimate contacts. Nat. Mater. 13, 1076–1078 (2014). \n3. Allain, A., Kang, J., Banerjee, K. & Kis, A. Electrical contacts to two-dimensional semiconductors. Nat. Mater. 14, 1195–1205 (2015). \n4. Radisavljevic, B., Radenovic, A., Brivio, J., Giacometti, V. & Kis, A. Single-layer ${\\mathsf{M o S}}_{2}$ transistors. Nat. Nanotechnol. 6, 147–150 (2011). \n5. Das, S., Chen, H.-Y., Penumatcha, A. V. & Appenzeller, J. High performance multilayer ${\\mathsf{M o S}}_{2}$ transistors with scandium contacts. Nano Lett. 13, 100–105 (2013). \n6. Guimarães, M. H. D. et al. Atomically thin ohmic edge contacts between two-dimensional materials. ACS Nano 10, 6392–6399 (2016). \n7. Yu, L. et al. Graphene ${'}\\mathsf{M o S}_{2}$ hybrid technology for large-scale two-dimensional electronics. Nano Lett. 14, 3055–3063 (2014). \n8. Park, W. et al. Complementary unipolar ${\\mathsf{W S}}_{2}$ field-effect transistors using Fermi-level depinning layers. Adv. Electron. Mater. 2, 1500278 (2016). \n9. Yamamoto, M., Nakaharai, S., Ueno, K. & Tsukagoshi, K. Self-limiting oxides on ${\\mathsf{W S e}}_{2}$ as controlled surface acceptors and low-resistance hole contacts. Nano Lett. 16, 2720–2727 (2016). \n10.\t Liu, Y. et al. Toward barrier free contact to molybdenum disulfide using graphene electrodes. Nano Lett. 15, 3030–3034 (2015). \n11.\t Chee, S.-S. et al. Lowering the Schottky barrier height by graphene/Ag electrodes for high-mobility ${\\mathsf{M o S}}_{2}$ field-effect transistors. Adv. Mater. 31, 1804422 (2019). \n12.\t Liu, Y. et al. Approaching the Schottky–Mott limit in van der Waals metal– semiconductor junctions. Nature 557, 696–700 (2018). \n13.\t Desai, S. B. et al. ${\\mathsf{M o S}}_{2}$ transistors with 1-nanometer gate lengths. Science 354, 99–102 (2016). \n14.\t Kappera, R. et al. Phase-engineered low-resistance contacts for ultrathin ${\\mathsf{M o S}}_{2}$ transistors. Nat. Mater. 13, 1128–1134 (2014). \n15.\t Cui, X. et al. Low-temperature ohmic contact to monolayer ${\\mathsf{M o S}}_{2}$ by van der Waals bonded Co/h-BN electrodes. Nano Lett. 17, 4781–4786 (2017). \n16.\t Kim, C. et al. Fermi level pinning at electrical metal contacts of monolayer molybdenum dichalcogenides. ACS Nano 11, 1588–1596 (2017). \n17.\t English, C. D. et al. Improved contacts to ${\\mathsf{M o S}}_{2}$ transistors by ultra-high vacuum metal deposition. Nano Lett. 16, 3824–3830 (2016). \n18.\t Smithe, K. K. H. et al. Intrinsic electrical transport and performance projections of synthetic monolayer ${\\mathsf{M o S}}_{2}$ devices. 2D Mater. 4, 011009 (2016). \n19.\t Kondekar, N. P. et al. In situ XPS investigation of transformations at crystallographically oriented ${\\mathsf{M o S}}_{2}$ interfaces. ACS Appl. Mater. Interfaces 9, 32394–32404 (2017). \n20.\t Yu, Z. et al. Analyzing the carrier mobility in transition-metal dichalcogenide ${\\mathsf{M o S}}_{2}$ field-effect transistors. Adv. Funct. Mater. 27, 1604093 (2017). \n21.\t Gao, J. et al. Transition-metal substitution doping in synthetic atomically thin semiconductors. Adv. Mater. 28, 9735–9743 (2016). \n22.\t Liu, H. et al. Statistical study of deep submicron dual-gated field-effect transistors on monolayer chemical vapor deposition molybdenum disulfide films. Nano Lett. 13, 2640–2646 (2013). \n23.\t Smithe, K. K. H. et al. Low variability in synthetic monolayer ${\\mathsf{M o S}}_{2}$ devices. ACS Nano 11, 8456–8463 (2017). \n24.\t Iqbal, M. W. et al. Tailoring the electrical and photo-electrical properties of a ${\\mathsf{W S}}_{2}$ field effect transistor by selective n-type chemical doping. RSC Adv. 6, 24675–24682 (2016). \n25.\t Khalil, H. M. W. et al. Highly stable and tunable chemical doping of multilayer ${\\sf W S}_{2}$ field effect transistor: reduction in contact resistance. ACS Appl. Mater. Interfaces 7, 23589–23596 (2015). \n26.\t Kim, Y. J. et al. Contact resistance reduction of ${\\mathsf{W S}}_{2}$ FETs using high-pressure hydrogen annealing. IEEE J. Electron Devices Soc. 6, 164–168 (2018). \n27.\t Tosun, M. et al. Air-stable n-doping of ${\\mathsf{W S e}}_{2}$ by anion vacancy formation with mild plasma treatment. ACS Nano 10, 6853–6860 (2016). \n28.\t Movva, H. C. P. et al. High-mobility holes in dual-gated ${\\mathsf{W S e}}_{2}$ field-effect transistors. ACS Nano 9, 10402–10410 (2015). \n29.\t Wang, J. I.-J. et al. Electronic transport of encapsulated graphene and ${\\mathsf{W S e}}_{2}$ devices fabricated by pick-up of prepatterned hBN. Nano Lett. 15, 1898–1903 (2015). \n30.\t Das, S. & Appenzeller, J. ${\\mathsf{W S e}}_{2}$ field effect transistors with enhanced ambipolar characteristics. Appl. Phys. Lett. 103, 103501 (2013). \n31.\t Fang, H. et al. Degenerate n-doping of few-layer transition metal dichalcogenides by potassium. Nano Lett. 13, 1991–1995 (2013). \n32.\t Chuang, H.-J. et al. High mobility ${\\mathsf{W S e}}_{2}{\\mathsf{p}}.$ - and n-type field-effect transistors contacted by highly doped graphene for low-resistance contacts. Nano Lett. 14, 3594–3601 (2014). \n33.\t Zhou, C. et al. Carrier type control of ${\\mathsf{W S e}}_{2}$ field-effect transistors by thickness modulation and $M_{0}{\\mathsf{O}}_{3}$ layer doping. Adv. Funct. Mater. 26, 4223–4230 (2016). \n\nAcknowledgements M.C., Y.W. and J.Y. acknowledge support from the US National Science Foundation (Civil, Mechanical and Manufacturing Innovation 1727531, Electrical Communications and Cyber Systems 1608389) and Air Force Office of Scientific Research Award FA9550-16-1-0289. M.C. and X.S. acknowledge support from the Shenzhen Peacock Plan (grant number KQTD2016053112042971). J.M. acknowledges support from the Rutgers RiSE summer internship programme. H.Y.J. acknowledges support from the Creative Materials Discovery Program through the National Research Foundation of Korea (NRF-2016M3D1A1900035). R.J.W. and A.M. acknowledge partial support from US NSF MRSEC Award DMR-1420013 for Characterization Facility at the University of Minnesota. \n\nAuthor contributions M.C. conceived the idea, supervised the project and wrote the paper. Y.W. prepared and measured all devices. J.C.K. and H.Y.J. performed sample fabrication using focused ion beam and STEM on monolayer ${\\mathsf{M o S}}_{2}$ , $N b{\\mathsf S}_{2}$ and ${\\mathsf{W S e}}_{2}$ . R.J.W. and A.M. performed STEM on few-layered ${\\mathsf{M o S}}_{2}$ . J.M. assisted in making contacts and measured work functions. X.S. synthesized 2D materials by CVD. J.Y. performed XPS and analysed data. F.Z. assisted in device fabrication and In deposition. All authors read the paper and agreed on its content. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nExtended data is available for this paper at https://doi.org/10.1038/s41586- 019-1052-3. \nSupplementary information is available for this paper at https://doi.org/ 10.1038/s41586-019-1052-3. \nReprints and permissions information is available at http://www.nature.com/ reprints. \nCorrespondence and requests for materials should be addressed to M.C. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2019 \n\n# Methods \n\nSample preparation and device fabrication. Monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ was grown by CVD using $\\mathbf{MoO}_{3}$ and sulfur powder as precursors. $100~\\mathrm{{mg}}$ of $\\mathbf{MoO}_{3}$ and $400\\mathrm{mg}$ of sulfur were placed in two small tubes in the upstream of the tube furnace. A small drop of perylene-3,4,9,10-tetracarboxylic acid tetrapotassium salt (PTAS) was dropped on $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrates as a seed to trigger growth of monolayer $\\ensuremath{\\mathbf{MoS}}_{2}$ . The substrates were placed face-up on top of an alumina boat in the centre of the furnace. Air was evacuated by flowing argon (Ar, ultrahigh purity, Air Gas) for $15\\mathrm{min}$ at 200 standard cubic centimeters per minute (sccm). The tube was heated at $200^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ to remove moisture from the precursors. Then the temperature was increased to $870^{\\circ}\\mathrm{C}$ under a $90\\mathrm{\\sccm}$ Ar flow and the $\\mathbf{MoO}_{3}$ and S source were heated to $250^{\\circ}\\mathrm{C}$ and ${170^{\\circ}\\mathrm{C}},$ respectively. After $20\\mathrm{min}$ , the furnace was cooled down to room temperature and the samples were removed from the furnace. \n\nFew-layered transition-metal dichalcogenides were prepared by mechanically exfoliating flakes from the bulk crystals $(\\mathrm{MoS}_{2}$ , $\\mathrm{WS}_{2}$ and ${\\mathrm{WSe}}_{2}$ , purchased from HQ Graphene) via the Scotch tape method. Thermally grown ${300}\\mathrm{-nm}$ -thick $\\mathrm{SiO}_{2}$ substrates on heavily doped Si were used as the gate insulator and electrode, respectively. Monolayer or multilayer flakes were identified with optical microscopy and atomic force microscopy. Then electron-beam lithography was used to pattern the electrodes. Before metal electrode deposition, the evaporation system was pumped to a base pressure of $<10^{-6}$ Torr. Then, $10\\mathrm{-nm}$ -thick In was deposited with a low rate of $0.\\overset{\\cdot}{2}\\overset{\\cdot}{\\mathrm{A}}s^{-1}$ and $100\\mathrm{-nm}$ -thick Au was deposited subsequently. The device was rinsed with isopropanol after immersing in acetone for lift-off. Once the fabrication process was completed, all devices were annealed at $200^{\\circ}\\mathrm{C}$ in $\\mathrm{H}_{2}/\\mathrm{Ar}$ gas for one hour before measurements. \n\nMeasurements. Transport characteristics were measured by applying voltage with the Keithley 4200 semiconductor parameter analyser system. The low-temperature measurements were performed in a vacuum probe station with liquid nitrogen and a temperature controller. XPS was performed using the Thermo Scientific K-Alpha system. Atomic force microscopy and scanning Kelvin probe microscopy were performed using the Park NX-Hivac system. Photoluminescence data were collected using a 532-nm laser excitation focused through a $\\times100$ objective lens. The spectra were taken at an incident laser power of $50\\upmu\\mathrm{W},$ which was sufficiently low to avoid any damage to the sample. \n\nSchottky barrier extraction. The Schottky barrier height of the contact was extracted by measuring the activation energy in the thermionic emission region. In a Schottky-barrier FET, the reverse-biased contact consumes most of the voltage drop and dominates the transistor behaviour. The current density of thermal emission through a metal–semiconductor contact is: \n\n$$\nJ=A^{*}T^{\\alpha}\\exp\\left[-{\\frac{q\\varPhi_{\\mathrm{B}}}{k_{\\mathrm{B}}T}}\\right]\\left[1-\\exp\\left(-{\\frac{q V}{k_{\\mathrm{B}}T}}\\right)\\right]\n$$ \n\nwhere $^{A*}$ is the Richardson constant, $V$ is the applied voltage, $T$ is the temperature, $\\alpha$ is an exponent equal to 2 for bulk semiconductors and to $3/2$ for 2D semiconductors, and $k_{\\mathrm{B}}$ is Boltzmann’s constant. Using this equation, the slope of the Richardson plot, $\\ln(I/T^{3/2})\\approx1/T$ , yields $\\varPhi_{\\mathrm{B}}$ as a function of gate voltage. The gate voltage at which the Schottky barrier height tends to curve away from the linear dependence is where the flat band condition occurs because after the gate voltage reaches this condition, carriers are transferred through tunnelling as well. To extract Schottky barrier height, we identify the voltage at which $\\varPhi_{\\mathrm{B}}$ stops linearly depending on $V_{\\mathrm{g}}$ . As shown in Extended Data Fig. 2f, the Schottky barrier of $\\mathrm{In}/\\mathrm{MoS}_{2}$ is $110{\\mathrm{meV}}.$ \n\nSTEM specimen preparation and acquisition parameters. Cross-sectional STEM lamellas of the FET samples were prepared using a FEI Helios NanoLab G4 focused ion beam. The cross-sectional STEM images of a monolayer $\\ensuremath{\\mathbf{MoS}}_{2}$ were taken at $200\\mathrm{keV}$ using a FEI Titan $^3\\mathrm{G}260{-}300$ with a double-sided spherical aberration corrector. The probe convergence semi-angle was set to be approximately 25 mrad. ADF STEM images were acquired over the range $50{-}200\\mathrm{mrad}$ . All electron energy loss spectroscopy measurements were collected in dual mode to enable simultaneous collection of zero-loss and core-loss spectra to compensate for energy drift during specimen acquisition. It is worth noting that the energy drift was tested by continuous collection of zero-loss spectra for $5\\mathrm{min}$ to ensure a reasonable energy drift $(<0.3\\mathrm{eV})$ before beginning any data acquisition. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n34.\t Young, P. A. Lattice parameter measurements on molybdenum disulphide. J. Phys. Appl. Phys. 1, 936 (1968). \n35.\t Sanz, C., Guillén, C. & Herrero, J. Annealing of indium sulfide thin films prepared at low temperature by modulated flux deposition. Semicond. Sci. Technol. 28, 015004 (2013). \n36.\t Kaushik, N. et al. Schottky barrier heights for Au and Pd contacts to ${\\mathsf{M o S}}_{2}$ . Appl. Phys. Lett. 105, 113505 (2014). \n37.\t Du, Y. et al. ${\\mathsf{M o S}}_{2}$ field-effect transistors with graphene/metal heterocontacts. IEEE Electron Device Lett. 35, 599–601 (2014). \n38.\t Xie, L. et al. Graphene-contacted ultrashort channel monolayer ${\\mathsf{M o S}}_{2}$ transistors. Adv. Mater. 29, 1702522 (2017). \n39.\t Cui, X. et al. Multi-terminal transport measurements of ${\\mathsf{M o S}}_{2}$ using a van der Waals heterostructure device platform. Nat. Nanotechnol. 10, 534–540 (2015). \n40.\t Kaushik, N. et al. Interfacial n-doping using an ultrathin $\\mathsf{T i O}_{2}$ layer for contact resistance reduction in ${\\mathsf{M o S}}_{2}$ . ACS Appl. Mater. Interfaces 8, 256–263 (2016). \n41.\t Wang, J. et al. High mobility ${\\mathsf{M o S}}_{2}$ transistor with low Schottky barrier contact by using atomic thick h-BN as a tunneling layer. Adv. Mater. 28, 8302–8308 (2016). \n42.\t Yin, X. et al. Tunable inverted gap in monolayer quasi-metallic ${\\mathsf{M o S}}_{2}$ induced by strong charge-lattice coupling. Nat. Commun. 8, 486 (2017). \n43.\t Kim, H.-J. et al. Enhanced electrical and optical properties of single-layered ${\\mathsf{M o S}}_{2}$ by incorporation of aluminum. Nano Res. 11, 731–740 (2018). \n44.\t Park, W. et al. Contact resistance reduction using Fermi level de-pinning layer for ${\\mathsf{M o S}}_{2}$ FETs. In IEEE International Electron Devices Meeting 5.1.1–5.1.4, https://ieeexplore.ieee.org/abstract/document/7046986 (IEEE, 2014). \n45.\t Cho, K. et al. Contact-engineered electrical properties of ${\\mathsf{M o S}}_{2}$ field-effect transistors via selectively deposited thiol-molecules. Adv. Mater. 30, 1705540 (2018). \n46.\t Yang, L. et al. Chloride molecular doping technique on 2D materials: ${\\mathsf{W S}}_{2}$ and ${\\mathsf{M o S}}_{2}$ . Nano Lett. 14, 6275–6280 (2014). \n47.\t Kang, J., Liu, W. & Banerjee, K. High-performance ${\\mathsf{M o S}}_{2}$ transistors with low-resistance molybdenum contacts. Appl. Phys. Lett. 104, 093106 (2014). \n48.\t Cheng, Z. et al. Immunity to scaling in ${\\mathsf{M o S}}_{2}$ transistors using edge contacts. Preprint at https://arxiv.org/abs/1807.08296 (2018). \n\n![](images/181caf52b584c4d50aa1bf3d97c5ddc8c3689cd8338c4ff3ed614347fff73a17.jpg) \nExtended Data Figure 1 | Atomic resolution imaging and chemical analyses of the $\\mathbf{In}/\\mathbf{Au}{-}\\mathbf{Mo}\\mathbb{S}_{2}$ interface. a, Broader view STEM images of three-dimensional metal on 2D semiconductor. Cross-sectional STEM image of interface between $\\mathrm{In/Au}$ and monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ . Scale bar, $5\\mathrm{nm}$ . b, Cross-sectional STEM image of interface between $\\mathrm{In/Au}$ and multilayered $\\mathbf{MoS}_{2}$ . Scale bar, $2\\mathrm{nm}$ . c, Bright-field STEM of $\\mathrm{In/Au}$ contact to monolayer $\\mathbf{MoS}_{2}$ . The intensity profile shows that the distance between the $\\mathrm{In/Au}$ atoms of the electrode metal to sulfur atoms in the first layer is $2.4\\mathring\\mathrm{A}$ . d, ADF-STEM and intensity profile of In/Au contact to multilayer $\\mathbf{MoS}_{2}$ . The intensity profile shows that the $\\ensuremath{\\mathrm{MoS}}_{2}$ interlayer distance is $6.2\\mathring\\mathrm{A}.$ , which is consistent with the literature34. The distance between the \nsulfur atoms in adjacent layers is $2.7\\mathring\\mathrm{A}$ and the distance between the $\\mathrm{In}/$ Au atoms and sulfur atoms in the first layer is also $2.7\\mathring\\mathrm{A}$ for multi-layered samples, indicating a van der Waals contact at the interface. e, XPS image of the $\\mathrm{In}/\\mathrm{Au}{-}\\mathrm{MoS}_{2}$ interface showing In metal $3d_{5/2}$ $(443.8\\mathrm{eV})$ and $3d_{3/2}$ $(451.4\\mathrm{eV})$ peaks along with In metal loss features. f, X-ray-induced Auger spectrum showing a pristine In metal peak at $402.9\\mathrm{eV.}$ $\\mathrm{In}_{2}\\mathrm{O}_{3}$ has a clear peak at $400.2\\mathrm{eV},$ which is absent in our samples. There is no sign of $\\mathrm{In}_{2}\\mathrm{S}_{3}$ $(407.3\\mathrm{eV})$ and In MNN Auger spectra indicate no chemical reaction at the interface35. g, Atomic force microscopy image of CVD-grown monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ . h, Photoluminescence of CVD-grown $\\ensuremath{\\mathrm{MoS}}_{2}$ , with the A exciton peak at $1.84\\mathrm{eV}$ and the B exciton peak at $1.97\\mathrm{eV}$ clearly visible. \n\n![](images/cc4e1c2df317d8e899ac30d7ed6373d1328a43489ea068148e1d6c2f3b1e05c2.jpg) \nExtended Data Figure 2 | Contact resistance and device properties of characteristics at low temperature, with the linearity of the output $\\mathbf{In/Au}$ electrodes on few-layered $\\mathbf{MoS}_{2}$ . a, TLM results of $\\mathrm{In/Au}$ contacts characteristics indicating the absence of a contact barrier. f, Mobility on few-layered $\\mathbf{MoS}_{2}$ . b, Contact resistance $R_{\\mathrm{C}}$ versus carrier concentration versus temperature reveals phonon-limited mobility at low temperature for $\\mathrm{In/Au}$ electrodes. Sc, Ti and Au electrodes deposited under ultrahigh and acoustic phonon scattering at high temperature. g, Transfer vacuum (UHV, $10^{-9}$ Torr) are provided for comparison5,17. c, Comparison characteristics with temperature showing the metal–insulator transition. of contact resistance from the literature and our results for different types h, Schottky barrier $(\\phi_{\\mathrm{B}})$ extraction indicating ideal In contacts with $\\mathbf{MoS}_{2}$ . of electrode materials $^{17,36-41}$ . d, Typical output curve at room temperature The inset shows the energy band diagram of $\\ensuremath{\\mathrm{MoS}}_{2}$ and In. shows that the highest current density is $1\\bar{96}\\upmu\\mathrm{A}\\upmu\\mathrm{m}^{-1}$ . e, Output \n\n![](images/161bac95a0d49dbdeed7954ac6ab6d719cb143a195d5e47bedef422cfd4cc497.jpg) \nExtended Data Figure 3 | Output characteristics of $\\mathbf{WS}_{2}$ . a, In contacts. b, Ti contacts. \n\n![](images/0b02318c397f70e57dbeda799ef74a9e38d985fa5818b716ade4c1d7bd5642d3.jpg) \nExtended Data Figure 4 | Energy-dispersive X-ray spectroscopy mapping of the contact. a, Low-magnification cross-sectional high-angle annular dark-field (HAADF) STEM image of the $\\mathbf{MoS}_{2}$ with $\\mathrm{In/Au}$ contact. $\\mathbf{b-e}$ , Elemental mapping showing the distribution of In, Au, S and O. In and Au overlap over the entire metal layer, suggesting the formation of an alloy. S is observed underneath the In and Au. O is obtained primarily \n\nfrom $\\mathrm{SiO}_{2}$ of the substrate. f, Fast Fourier transform (FFT) pattern from metal electrode showing alloying between In and Au. Scale bar, $5\\mathrm{\\AA}$ . The diffraction pattern is of a face-centred cubic alloy. Pure In has bodycentred cubic crystal structure. a:C, amorphous carbon; dep., deposition; Z.A., zone axis. \n\n![](images/aada1508df5bcdc9ef73dc633418ef48d6a01732a296fe85466d47b8a734c41d.jpg) \nExtended Data Figure 5 | Typical transfer characteristics of the device measured immediately after fabrication and after 70 days. \n\n$$\n\\mathsf{W}\\mathsf{F}=5.09\\mathsf{e V}\n$$ \n\n$$\n{\\sf W F}=4.05\\mathrm{eV}\n$$ \n\n![](images/a02e741a0690b88a00eec8b2f99259e278e45c3a80dac292bfcbd36ff2e42a10.jpg) \nExtended Data Figure 6 | Topographical and scanning Kelvin probe microscopy images. a, d, Topographical and surface potential results of the Au sample; the work function (WF) extracted is $5.09\\mathrm{eV},$ similar to the theoretical value. b, e, Topographical and surface potential results of the \n\n$$\n{\\mathsf{W F}}=4.23\\ {\\mathsf{e V}}\n$$ \n\nIn/Au sample; the work function extracted is very close to that of the In work function, $4.05\\mathrm{eV.}$ c, f, Topographical and surface potential results of the $\\mathrm{In/Pd}$ sample; the work function extracted is $4.23\\mathrm{eV},$ higher than that of $\\mathrm{In/Au}$ . \n\nExtended Data Table 1 | Literature survey of device performance \n\n\n
MethodChannel length (μm)EOTGate voltage (V)Drain voltage (V)(μA/μm) IONRc(kΩ·μm)ref
Monolayer MoS
In/Au clean contact300 nm SiO2401183This
Graphene5285 nm SiO2800.10.8NA10
Graphene edge contact730 nm HfO230.0250.1596
Graphene/Ag4300 nm SiO801511511
Co/h-BN0.2BN+285 nm SiO2800.010.1615
Au UHV1.290 nm SiO235112518
Cr contact1285nm SiO240144016
Re doping10.5300 nm SiO2800.10.0526.2521
Double gate0.1B:2 5 mm SiO240121022
Ag/Au430 nm SiO2251171223
1T'/Au10285nm SiO25011.8NA42
AlO passivation1.5300 nm SiO210010.5NA43
Multilayer MoS
In/Au clean contact0.5300 nm SiO24031960.8This
Sc515 nm AlO83160NA5
Graphene contact5285 nm SiO2600.11NA10
Transferred Ag0.16BN+90 nm SiO2403660NA12
Phase engineering1.2300 nm SiO2305850.2414
Au UHV0.590 nm SiO225175217
Grapaet, h-BN285 nm SiO2800.050.22.539
h-BN tunneling0.3255 nm SiO240130441
Fermi level de-pinning1.590 nm SiO2203245.444
Molecules doping2300 nm SiO4035025.245
Cl doping0.590 nm SiO2501.2200(2 × 10.5 cm²2)46
K doping0.5B:28.5 nm SiO0,4052.515NA31
Mo72 nm AlO33031402 (4 ×1013 om47
Edge contact2.2300 nm SiO2300.480.820548
\n\nContact resistances are extracted at a carrier concentration of around $3\\times10^{12}\\mathsf{c m}^{-2}$ for multilayer ${\\mathsf{M o S}}_{2}$ and $5\\times10^{12}\\mathsf{c m}^{-2}$ for monolayer ${\\mathsf{M o S}}_{2}$ except where indicated otherwise. EOT, equivalent oxide thickness. $I_{0N}$ is the drain current when the device is in the ‘ON’ state. 1T’ represents distorted octahedral structure. Missing values are represented by NA (not available). Data are from refs 5,6,10–12,14–18,21–23,31,39,41–48. " + }, + { + "id": "10.1038_s41467-019-08881-z", + "DOI": "10.1038/s41467-019-08881-z", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-08881-z", + "Relative Dir Path": "mds/10.1038_s41467-019-08881-z", + "Article Title": "A silicon-on-insulator slab for topological valley transport", + "Authors": "He, XT; Liang, ET; Yuan, JJ; Qiu, HY; Chen, XD; Zhao, FL; Dong, JW", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Backscattering suppression in silicon-on-insulator (SOI) is one of the central issues to reduce energy loss and signal distortion, enabling for capability improvement of modern information processing systems. Valley physics provides an intriguing way for robust information transfer and unidirectional coupling in topological nullophotonics. Here we realize topological transport in a SOI valley photonic crystal slab. Localized Berry curvature near zone corners guarantees the existence of valley-dependent edge states below light cone, maintaining in-plane robustness and light confinement simultaneously. Topologically robust transport at telecommunication is observed along two sharp-bend interfaces in subwavelength scale, showing flat-top high transmission of similar to 10% bandwidth. Topological photonic routing is achieved in a bearded-stack interface, due to unidirectional excitation of valley-chirality-locked edge state from the phase vortex of a nulloscale microdisk. These findings show the prototype of robustly integrated devices, and open a new door towards the observation of non-trivial states even in non-Hermitian systems.", + "Times Cited, WoS Core": 652, + "Times Cited, All Databases": 702, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000459097100007", + "Markdown": "# A silicon-on-insulator slab for topological valley transport \n\nXin-Tao He1, En-Tao Liang1, Jia-Jun Yuan1, Hao-Yang Qiu1, Xiao-Dong Chen1, Fu-Li Zhao1 & Jian-Wen Dong 1 \n\nBackscattering suppression in silicon-on-insulator (SOI) is one of the central issues to reduce energy loss and signal distortion, enabling for capability improvement of modern information processing systems. Valley physics provides an intriguing way for robust information transfer and unidirectional coupling in topological nanophotonics. Here we realize topological transport in a SOI valley photonic crystal slab. Localized Berry curvature near zone corners guarantees the existence of valley-dependent edge states below light cone, maintaining inplane robustness and light confinement simultaneously. Topologically robust transport at telecommunication is observed along two sharp-bend interfaces in subwavelength scale, showing flat-top high transmission of ${\\sim}10\\%$ bandwidth. Topological photonic routing is achieved in a bearded-stack interface, due to unidirectional excitation of valley-chiralitylocked edge state from the phase vortex of a nanoscale microdisk. These findings show the prototype of robustly integrated devices, and open a new door towards the observation of non-trivial states even in non-Hermitian systems. \n\nSiplilcatofno-romn-tion fualsatteon (nSdOeI)n prrgoevidaetsa ra CsfeMrObSo-tchombeptawtiebelne replace their electronic components1. Miniaturization of SOI devices can achieve highly integrated photonic structures comprised of numerous optical components in a single chip, but increase inevitable backscattering that leads to energy loss and signal distortion. Consequently, optical backscattering suppression is of fundamental interest and great importance for compact SOI integration. The discovery of topological photonics offers an intriguing way for robust information transport of $\\mathrm{light}^{2,3}$ , particularly for their capacities in backscattering–immune propagation and unidirectional coupling. Such robustness is derived from the nontrivial bulk topology, enabling reflection-free transport between two topologically distinct domains2–17, such as by using a magneto-optical effect, 3D chiral structures, and bianisotropic metamaterials. As a target to integrated topological nanophotonics, some all-dielectric strategies have been proposed recently. An array of coupling resonator optical waveguides was designed to implement topological SOI structures at super-wavelength period18, and has been exploited to the topological-protected lasing effect19,20. Later, a subwavelength-scale strategy attracted much attention to reduce the size of topological devices, e.g., applying $C_{6\\nu}$ crystalline symmetries to realize all-dielectric topological structures above a light cone21–23, which have been achieved under in-plane unidirectional propagation over sufficient distances24 and observed topological states through outof-plane scattering25. These developments of topological nanophotonics open avenues to develop on-chip optical devices with built-in protection, such as robust delay lines, on-chip isolation, slow-light optical buffers, and topological lasers. \n\nValley pseudospin provides an additional degree of freedom (DOF) to encode and process binary information in graphene and two-dimensional transition metal dichalcogenide (TMDC) monolayers26–29. Analogous to valleytronics, exploration of valley physics in classical waves (e.g., photonics30–37 and phononics38–41) renders powerful routes to address the topological nontrivial phase by emerging an alternative valley DOF. To retrieve the topological valley phase, a general method is to break spatial-inversion symmetry for accessing the opposite Berry curvature profiles near Brillouin zone corners, i.e., the K and $\\mathbf{K^{\\prime}}$ valley. Advanced in nanofabrication techniques, precise manufacture of the inversionsymmetry-broken nanophotonic structures is easy to implement nowadays42. Consequently, valley photonic crystal (VPC) is a reliable candidate for SOI topological photonic structures, in particular for a subwavelength strategy that still remains much of a challenge in topological nanophotonics. Furthermore, the topological valley phase below a light cone ensures high–efficient light confinement in the plane of a chip, such that the photonic valley DOF naturally makes a balance between in-plane robustness and out-of-plane radiation. This is a crucial condition to design topological photonic structures for chips. Realization of topological valley transport in the SOI platform is desirable for integrated topological nanophotonics. \n\nIn this work, we experimentally demonstrate a valley topological nanophotonic structure at telecommunication wavelength. Our design is based on a standard SOI platform that allows integration with other optoelectronic devices on a single chip. Valley-dependent topological edge states can operate below light cone, benefiting to the balance between in-plane robust transport and out-of-plane radiation. Broadband robust transport is observed in sharp-turning interfaces constructed by two topologically distinct valley photonic crystals, with a footprint of $9\\times$ ${\\bar{9}}.2\\upmu{\\dot{\\mathrm{m}}}^{2}$ . In addition, we achieve topological photonic routing with high directionality, by exploiting unidirectional excitation of valley–chirality-locked edge state with a subwavelength microdisk. \n\n# Results \n\nSilicon-on-insulator valley photonic crystals. In this work, our nanophotonic structures are prepared on SOI wafers with $220\\mathrm{-nm}$ -thickness silicon layers. As depicted in Fig. 1a, the valley photonic structure comprises two honeycomb photonic crystals (VPC1 and VPC2). The VPC layer is asymmetrically placed between the $\\mathrm{SiO}_{2}$ substrate and top air region along the $z$ axis (see the inset of Fig. 1a). Instead of a freestanding membrane, the use of a $z$ -asymmetric SOI slab can improve the compatibility with other types of building blocks (e.g., microdisk later in this work). Figure 1b gives the details of VPC. The unit cell of VPC1 (red) contains two nonequivalent air holes, i.e., the smaller one $d_{1}=$ $81\\mathrm{nm}$ and the bigger one $d_{2}=181\\ \\mathrm{nm}$ . On the other hand, the diameter of two air holes is altered to form another type of VPC (blue), i.e., VPC2 with $d_{1}=181\\ \\mathrm{nm}$ and $d_{2}=81\\ \\mathrm{nm}$ . Here, VPC2 is the inversion-symmetry partner of VPC1. Thus, VPC1 and VPC2 have the same band structure, as shown in Fig. 1c. The details about the VPC design can be seen in Supplementary Note 1. Because the two air holes have different diameters that break the inversion symmetry, a bandgap $(1360\\mathrm{nm}\\sim1492\\mathrm{nm})$ ) emerges for TE-like polarizations. \n\nDue to the bulk-edge correspondence, we will first study the bulk states of the first TE-like band (labeled as $\\\"\\mathrm{TE1}\\\"\\$ in Fig. 1c), before discussing the topology of a TE-like gap. The electromagnetic fields in the $z$ -central plane (labeled as $\\boldsymbol{\\mathfrak{c}}_{z=0},$ in the inset of Fig. 1a) can mainly reflect the optical properties of the VPC slab, so that we will focus on the field patterns at $z=0$ plane in the following discussion. Take the eigenstates at the K valley as examples. The simulated $H_{z}$ phase profile at $z=0$ plane is plotted in Fig. 1d. We can see that the phase profile of VPC1/VPC2 increases anticlockwise/clockwise by $2\\pi$ phase around the center of a unit cell. Such optical vortex is related to valley pseudospin in an electronic system, and thus can be termed as a photonic valley DOF. In TMDCs, the valley-polarized excitons can be selectively generated through control of the chirality of $\\mathrm{light^{43,44}}$ . Similarly, the photonic valley is also locked to the chirality of excited light, i.e., left-circularly polarized (LCP) light couples to the $\\mathrm{K^{\\prime}}$ -valley mode, while right-circularly polarized (RCP) light couples to the K-valley mode32. To demonstrate this valley–chirality locking property remaining in the SOI slab, we give the distribution of the polarization ellipse of the in-plane electric field in Fig. 1e. Here, the polarization ellipse is generally defined as ellipticity angles45 $\\chi=\\arcsin[2|E_{x}||E_{y}|\\sin\\delta/(|E_{x}|^{2}+|E_{y}|^{2})]/2.$ where $\\delta=\\delta_{y}-\\delta_{x}$ is the phase difference between $E_{y}$ and $E_{x}$ For VPC1, the RCP response $(\\chi=\\pi/4)$ exists in the singularity point of the phase vortex at the K valley (red center in Fig. 1e), and vice versa for VPC2 (blue center in Fig. 1e). Figure 1f shows the temporal evolution of the RCP and LCP responses, respectively. Such valley–chirality locking gives the possibility to manipulate photonic valley modes. For example, when we place a circularpolarized dipole source in the singular point of the phase vortex, the photonic valley Hall effect can be observed (see Supplementary Note 2). \n\nThe above observation of the optical vortex and the photonic valley Hall effect can be related to a topologically nontrivial phase. Next, we numerically calculate the Berry curvature distribution and the corresponding topological invariant to insightfully confirm the topological valley phase in our proposed VPC slab46. See the section Methods for more details on numerical simulation. Figure 2a shows the Berry curvature of the TE1 band for VPC1, calculated with the parallel gauge transformation47. The Berry curvature of VPC is mainly distributed near two valleys, i.e., a singular sink at the K valley while peaking at $\\mathbf{K^{\\prime}}$ (red line in the inset of Fig. 2a). On the contrary, VPC2 reverses the Berry curvature distribution of the two valleys (blue line in the inset of Fig. 2a). In general, the global integration of Berry curvature over the whole Brillouin zone, the so-called Chern number, is zero under the protection of time-reversal symmetry. Instead, the valley-dependent integration of Berry curvature gives rise to a nonzero value, i.e., the valley-dependent index $C_{\\mathrm{K}}\\left(C_{\\mathrm{K^{\\prime}}}\\right)\\neq$ 0. Thus, we can use the valley Chern index $C_{V}{=}C_{\\mathrm{K}^{-}}C_{\\mathrm{K^{\\prime}}}$ to characterize the topology of the whole VPC system, providing a new route to retrieve a topologically nontrivial phase. \n\n![](images/8f5e0b471e5fe3f9800079a13af9502daae2602c21bf1accbbf29bef64427d71.jpg) \nFig. 1 Band structures and nontrivial topology in silicon-on-insulator (SOI) valley photonic crystals (VPCs). a Oblique-view scanning-electron-microscope image of the fabricated VPC, which is patterned on standard 220-nm-thickness silicon wafer. The VPC is arranged in a honeycomb lattice with a periodicity of $a=385\\mathsf{n m}$ . The inset indicates that the VPC slab is asymmetrically placed between the $\\mathsf{S i O}_{2}$ substrate and the top air region along the z axis. b Details of the unit cells consisting of two inequivalent air holes, i.e., the smaller one with a diameter $d_{1}$ $\\mathbf{\\nabla}_{|}\\left(d_{2}\\right)=81$ nm and the larger one with a diameter $d_{2}\\left(d_{1}\\right)=$ $181\\mathsf{n m}$ for VPC1 (VPC2). c Bulk band both for VPC1 and VPC2. The colormap indicates the linear polarization of a photonic band. There is a 132-nmbandwidth gap (yellow region) between the first and second TE-like bands (purple) due to the $y$ -axis inversion symmetry broken. Gray region: light cone of silica. d Simulated phase vortex of $H_{z}$ field profile and e ellipticity angle of $(E_{x},E_{y})$ field at the K valley of the TE1 band for VPC1 and $\\mathsf{V P C2}$ The $H_{z}$ phase vortex mainly rotates along the unit cell center, of which the singularity point corresponds to right- or left-handed circular polarization (RCP or LCP). All of the field patterns shown below focus on the $z$ -central plane (labeled as $z=0$ in the inset of Fig. 1a). f Temporal evolution of RCP and LCP at the singularity point, respectively. In this work, the refractive index of silicon and silica are $n_{\\mathrm{Si}}=3.47$ and $\\begin{array}{r}{n_{\\mathtt{S i l i c a}}=1.45,}\\end{array}$ respectively \n\nWe should note that the VPCs open a large TE-like gap $(\\sim10\\%)$ to guarantee broad bandwidth operation. Thus, the Berry curvature for both valleys will overlap with each other. As a consequence, the valley Chern index is not a well-defined integer, i.e., $0<\\lvert C_{V}\\rvert<1$ . The edge dispersion will not gaplessly cross from the lower band to the upper band. Regardless of this side effect, the difference in the sign of valley Chern index will ensure the protection of the topological valley phase, as long as the bulk state at the K valley is orthogonal to the $\\mathrm{K^{\\prime}}$ valley. Therefore, such novel design still enables broadband robust transport along the $\\Gamma\\mathrm{K}/\\Gamma\\mathrm{K^{\\prime}}$ direction against certain perturbations (such as sharpbend corners or $10\\%$ random bias of hole diameter), as the intervalley scattering is suppressed due to the vanishing field overlapping between two valley states. \n\nAs an intuitive example, we construct an interface by using two VPCs with the opposite valley Chern index. As schematically shown in Fig. 2b, the bearded interface is stacked with the bigger holes. The upper domain (VPC1 in Fig. 1) has valley Chern index $C_{V}<0$ , while the valley Chern index of the lower domain (VPC2 in Fig. 1) exhibits the opposite sign $\\left(C_{V}>0\\right)$ . The valleydependent edge states (green lines in Fig. 2c) for the beardedstack interface, include one with negative velocity at the K valley and the other with positive velocity at the $\\mathbf{K^{\\prime}}$ valley. The simulated patterns shown in Fig. 2e confirm that the propagating light at $\\bar{\\lambda}=1430\\mathrm{nm}$ will smoothly detour by $120^{\\mathrm{o}}$ bending $60^{\\mathrm{o}}$ sharp corner). Such propagation is valid for other wavelengths inside the bandgap, leading to optical broadband operation. Note that a little bit modulation of the signal in Fig. 2e is mainly caused by the out-of-plane radiation loss in the open-slab system. Note also that the TE/TM coupling in such $z$ -asymmetric slab is too weak (see Supplementary Note 3) to affect valley-dependent interface transport, i.e., the robust transport in $120^{\\mathrm{o}}$ bending and unidirectional coupling. In the next section, we will experimentally characterize this broadband robust transport phenomenon. \n\n![](images/3af704174a052bb97ee717e51d76f0b9bb5dae9efb25f1fe76b6dd503bf15063.jpg) \nFig. 2 Valley-dependent topological edge states in silicon-on-insulator (SOI). a Distribution of TE1 Berry curvature for VPC1, which is localized near the corners of the first Brillouin zone. The valley-dependent Berry curvature has opposite sign to each valley. The inset plots the Berry curvature along $k_{y}=0$ direction, indicating that the Berry curvature of VPC2 (blue) has inversed distribution to that of VPC1 (red). b Schematic of the valley-dependent topological interface constructed by two types of valley photonic crystal (VPC) slabs. The VPC1 (red) and VPC2 (blue) attribute to different topological phases, characterized by the sign of their valley Chern index $C_{V}.$ c Dispersion of the valley-dependent edge states (green lines) for the bearded-stack interface. Purple region: projection TE-like band. Translucent gray region: light cone of silicon dioxide substrate. d Top-view scanning-electron-microscope images of the fabricated samples, including flat, Z-shape, and $\\Omega$ -shape topological interfaces. e Simulation of electromagnetic energy intensities for the three distinct shape interfaces at $z=0$ plane $(\\lambda=1430\\mathsf{n m})$ . The Z- (Ω-) shape interface with two (four) $120^{\\circ}$ bends shows that light can smoothly propagate around the corners. f Measured and $\\pmb{\\mathscr{s}}$ simulated transmission spectra for the flat (blue), Z-shape (green), and $\\Omega$ -shape (red) interfaces, respectively. The yellow regions correspond to the TE-like gap of SOI VPC. All of the spectra in the bandgap maintain the flat-top high transmittance, even for a sharp-bending geometry (green and red). This intriguing property indicates broadband robust transport in the frequency interval from 1360 to $1492{\\mathsf{n m}}$ \n\nTopological robust transport. To experimentally demonstrate topological robust transport of the valley-dependent edge states, we employ an advanced nanofabrication technique to manufacture the flat-, Z-, and $\\Omega$ -shape VPC interfaces. The scanningelectron-microscope (SEM) images of fabricated samples are shown in Fig. 2d. The devices were prepared on a SOI wafer, with a nominal $220\\mathrm{-nm}$ silicon layer and $2.0\\mathrm{-}\\upmu\\mathrm{m}$ buried oxide layer. After the definition of a $370\\mathrm{-nm}$ -thickness positive resist through electron-beam lithography, inductively coupled plasma etching step is applied to pattern the top silicon layer, such that the VPC structure and its coupling waveguide was formed. Then the resist was removed by using an ultrasonic treatment process. See Methods for more details of the nanofabrication process. These processes are able to precisely achieve our designed structures even in close proximity (separation of about $40\\mathrm{nm}$ in the topological interface). \n\n![](images/6947b7911191ab50cddedd0e9922d4bb6724f839708492194bcebba13920b02c.jpg) \nFig. 3 Unidirectional coupling of valley-dependent edge states by using a circularly polarized chiral source. a Illustration of unidirectional coupling along the valley photonic crystal (VPC) interface, based on the selective excitation of the phase vortex. The vortex fields around the bearded holes at the upper domain will interact with those of the lower domain, and thus a chiral-flow edge state occurs. b Simulation of unidirectional coupling in a bearded-stack interface by controlling the chirality of a circularly polarized source at $\\lambda=1430\\mathsf{n m}$ . To simplify, a right-circularly polarized (RCP) or left-circularly polarized (LCP) dipole source is considered to generate a clockwise/anticlockwise phase vortex. c–e Analysis of unidirectional coupling efficiency determined by an averaged parameter $\\left\\langle\\kappa_{0}\\right\\rangle_{g a p}$ . Here, $\\left\\langle\\kappa_{0}\\right\\rangle_{g a p}$ is related to the frequency-domain integration of directionality $\\kappa_{0}$ in the whole bandgap. c Key geometry parameters for global directionality, including relative location $\\left\\langle D_{x}\\right\\vert$ and $D_{y})$ and diameter $(d_{e})$ of bearded edge holes. The separation $(\\delta_{\\mathsf{S i}})$ of the silicon region between the two bearded holes is variable as $\\delta_{\\mathrm{Si}}=\\sqrt{D_{x}^{2}+D_{y}^{2}}-d_{e}$ . d Simulated phase map of $\\left\\langle\\kappa_{0}\\right\\rangle_{g a p}$ varied with relative locations $D_{x}$ and $D_{y}$ . The maximum value emerges at the point of $D_{x}=192.5\\mathsf{n m}$ and $D_{y}=111\\mathsf{n m}$ , which is in correspondence with the valley-dependent topological interface. e Global directionality $\\left\\langle\\kappa_{0}\\right\\rangle_{g a p}$ as a function of separation $\\delta_{\\mathsf{S i}}$ when tuning the diameters $d_{e}$ . Here, the relative position is fixed with the maximum point of Fig. 3d \n\nNext, we will characterize the broadband robust transport of the VPC edge states at the $Z/\\Omega$ -shape interface. The experimental setup is shown in Supplementary Figure 5. The TE-polarized continuous waves at the telecommunication wavelength were coupled to the $1.7–up\\upmu\\mathrm{m}$ -width input waveguide by using a polarization-maintaining lensed fiber, and then launched into the VPC sample from the left end of the topological interface. After passing through the VPC devices, the propagating wave was coupled to the output waveguide at the right end and then collected by another lensed fiber. The corresponding transmission spectra were detected by using an optical powermeter, with tuning the operation wavelength of excited waves. Note that all the transmission spectra are normalized to the $1.7–up\\upmu\\mathrm{m}$ -width silicon strip waveguide located in the same writing field near the VPC samples. See Methods for more details of optical characterizations. Figure 2f shows the measured transmission spectra in the wavelength range of $1320\\mathrm{-}1570\\mathrm{nm}$ for flat-, Z-, and $\\Omega$ -shape topological interfaces. In the bandgap region (yellow), the spectra are kept on the flat-top high-transmittance platform, even for a sharp-bending geometry (green and red lines). This intriguing property indicates the broadband robust transport in the frequency interval from 1360 to $1492\\mathrm{nm}$ , due to the suppression of intervalley scattering. Although there is some noise in Fig. 2f due to Fabry–Perot resonance between the entrance and exit facets of the strip waveguide and dark current noise of the detector, these experimental spectra are in good agreement with simulations (Fig. 2g). Note that the SOI platform with a compact footprint of $9\\times{\\dot{9}}.2\\dot{\\upmu}\\mathrm{m}^{2}$ enables to integrate many photonic components on a single chip. In other words, the proposed SOI VPC with a subwavelength periodicity (about $\\lambda/4$ ) can develop a high-performance topological photonic device with a compact feature size of less than $10\\upmu\\mathrm{m}$ . \n\n![](images/49410910072a3fd15866ad5ce73ce0a774af250eac2383ccb8bc992222431541.jpg) \nFig. 4 Experimental realization of topological photonic routing. a Schematic view of a topological photonic routing sample, including the valley photonic crystal (VPC) interface and the microdisk. The incident light from WVG1/WVG2 will excite an anticlockwise/clockwise phase vortex in the microdisk and then couple to the upper/lower interface in support of the different valley–chirality-locked modes. The light will finally couple back to free space by a nonuniform grating coupler (G1 and G2). b Scanning-electron-microscope image of the sample near a microdisk. The width of the input waveguide is $W_{w v g}=373\\mathsf{n m}.$ , and the air gap in the waveguide is $w_{g a p}=355\\mathsf{n m}$ . The diameter of microdisk $d_{m}=630\\mathsf{n m}$ , with its distance to the center of the waveguide $h=586\\mathsf{n m}$ . c Control sample with the same configuration to $\\mathbf{b},$ except for replacing the VPC interfaces by two-strip silicon waveguides. $\\mathbf{d-g},$ Measurement of photonic routing profiles at $\\lambda=1400\\mathsf{n m}$ , imaged by an optical far-field microscopy $20\\times$ objective). For topological routing $({\\pmb{\\mathsf{d}}},{\\pmb{\\mathsf{e}}})$ , the incident light from the WVG1 port was routed to the upper interface, while another case from the WVG2 port was reversed. For normal routing $(\\pmb{\\mathscr{f}},\\pmb{\\mathsf{g}})$ , the light energy splits almost equally into two ports. h–i, Measured directionality spectra for topological ${\\bf\\Pi}({\\bf h})$ and normal (i) photonic routing devices. The spectra show the directional coupling efficiency, $\\kappa_{e x p}=(I_{G7}-I_{G2})/(I_{G1}+I_{G2})_{i}$ , as a function of the operation wavelength. Here, $I_{\\mathsf{G}1}$ and $I_{\\mathsf{G}2}$ are the extracted intensities collected from G1 and G2. For both WVG1 (red) and WVG2 (blue) incident case, the directional coupling efficiency of the topological routing device is beyond the value of 0.5 within a broadband region, some of which is close to unity. i For comparison, the normal routing device has low directionality within the considered wavelength range \n\nUnidirectional coupling. Unidirectional coupling is another important property of topological photonic structures to manipulate the flow of light. We should emphasize that the realization of robust transport does not definitely correspond to unidirectional coupling. For example, it is inaccessible to achieve high-efficiency unidirectional coupling from a single circularly polarized source to zigzag-stack valley-dependent interfaces, due to protection of the inversion symmetry with regard to the $y$ -axis center of the interface. In such $y$ -odd/even-like edge states, the circular-polarized point of the polarization ellipse is predominant at the low-intensity positions. For high-efficiency unidirectional coupling, breaking the inversion symmetry of the interface is required to engineer the generation of vortex fields in the edge states. Therefore, we chose bearded-stack VPC interface (Fig. 2b) with the inversion symmetry broken. In this case, the vortex fields around bearded holes at the upper domain will interact with the lower domain, and thus generate chiral-flow edge states (see Supplementary Note 3). As depicted in Fig. 3a, such chirality ensures the rightward (leftward) excitation by using the RCP (LCP) source. Simulated results in Fig. 3b confirm that the proposed valley-dependent topological interface can realize unidirectionality through control of the source chirality. In fact, similar results have been studied in a photonic crystal W1-like waveguide, by shifting one side of the waveguide by half a lattice constant48,49. \n\nWe should emphasize that the introduction of a topological nontrivial phase can guarantee high directionality under chiral source excitation in relatively broadband operation, while the case of the topologically trivial system commonly operates in a narrowband as it is sensitive to the source position with frequency variation. To quantitatively determine unidirectional coupling, we define the directionality for a given frequency as $\\kappa_{0}=(T_{L}-T_{R})/(T_{L}+T_{R})\\mathrm{.}$ , where $T_{L}$ and $T_{R}$ are the transmittances detected at the left and right end, respectively. Furthermore, we would like to analyze the global efficiency of unidirectional coupling inside the photonic bandgap, and thus define an averaged parameter related to the frequency-domain integration of $\\kappa_{0}$ in the whole bandgap, i.e., $\\begin{array}{r}{{\\langle\\kappa_{0}\\rangle}_{\\mathrm{gap}}=|\\int_{\\mathrm{gap}}\\kappa_{0}d\\omega|/\\Delta\\omega_{\\mathrm{gap}}}\\end{array}$ , where $\\Delta\\omega_{\\mathrm{gap}}$ is the bandwidth of a photonic bandgap. $\\left\\langle\\kappa_{0}\\right\\rangle_{\\mathrm{gap}}=1$ represents that the chiral source couples to pure left-/rightforward edge states for all frequencies in the bandgap. Here, we analyze the global directionality in the center on two dominant factors, i.e., relative positions ${\\bf\\nabla}[D_{x}$ and $D_{y}^{\\mathrm{~\\cdot~}}$ ) and diameter $(d_{e})$ of bearded edge holes (Fig. 3c). The separation $(\\delta_{S i})$ of the silicon region between the two bearded holes is variable as δSi ¼ qffiffiDffiffix2ffi ffiffiþffiffi ffiffiDffiffiy2ffi \u0003 de. A simulated phase map of Fig. 3d shows that the maximum $\\left\\langle\\kappa_{0}\\right\\rangle_{\\mathtt{g a p}}$ emerges at the point of $D_{x}=192.5\\mathrm{nm}$ and $D_{y}=111\\mathrm{{nm}}$ , which is in correspondence with the valleydependent topological interface. It is interesting that the proposed design based on valley topology can certainly find the point of high directionality, while the general method requires massive simulations, just like what we do in Fig. 3d. \n\nOn the other hand, considering a fixed relative position that Dx = 192.5 nm and Dy = 111 nm, the global directionality κ0igap as a function of separation $\\delta_{S i}$ is also retrieved in Fig. 3e, when tuning the diameters $d_{e}$ of bearded edge holes. We can see that $\\left\\langle\\kappa_{0}\\right\\rangle_{\\mathtt{g a p}}$ will stand on a high-directionality platform (above 0.9), when the separation is less than $50\\mathrm{nm}$ . Qualitatively, this is because such extreme separation will enhance the interaction of vortex fields between upper- and lower-domain bearded holes, and thus strengthen the valley–chirality coupling of the topological interfaces. \n\nTopological photonic routing. Experimental realization of unidirectional coupling of topological edge states shows many promising applications in light manipulation. Recently, it has been demonstrated in the microwave region as a valley filter36 and realized in a chip-scale system as a topological quantum optics interface24. For the on-chip strategy, the latter one use chiral quantum dots under a strong magnetic field at ultralow temperature24,50. In this work, we aim to develop an all-optical strategy, for unidirectional excitation of the valley–chirality locking edge states in the SOI platform. To do this, a subwavelength microdisk serving as a phase vortex generator51, is introduced into the topological interface. Figure 4a shows the schematic of a designed device, combining SOI VPC and a microdisk. The fabricated sample around a microdisk can be seen in Fig. 4b. There are two $373\\mathrm{-nm}$ -width strip silicon waveguides (labeled as $^{\\mathrm{e}}\\mathrm{WVG1}^{\\mathrm{p}}$ and $^{\\mathrm{e}}\\mathrm{WVG}2^{\\mathfrak{w}})$ at the left of the sample. When incident light couples to the WVG1/WVG2 input waveguide, it will generate an anticlockwise/clockwise phase vortex at the designed microdisk with a close-to-diffraction-limited scale ( ${\\cdot}630{\\cdot}\\mathrm{nm}$ diameter). Due to valley–chirality locking, the edge state near the $\\mathrm{K}/\\mathrm{K}^{\\prime}$ valley can be selectively routed to the upper/lower topological interface, through control of the chirality of the optical vortex inside a microdisk. This shows a prototype of the on-chip photonic routing device, with the advantage of an ultracompact (in sub-micrometer scale) coupling distance. \n\nFar-field microscopy is used to verify the photonic valley–chirality locking property and the topological routing effect. A $20\\times$ objective is used to predominantly collect the outof-plane radiation from two nonuniform grating couplers (labeled as $^{\\bar{\\kappa}}\\mathrm{G}1^{\\mathfrak{n}}$ and $^{\\mathfrak{a}}G2^{\\mathfrak{n}}$ in Fig. 4a) and then imaged by using an InGaAs CCD. For a given incidence waveguide, an asymmetric radiation is obvious between G1 and G2. For example, the microscope images are presented in Fig. 4d for the WVG1 incidence at $\\lambda\\overset{\\triangledown}{=}$ $1400\\mathrm{nm}$ . In this case, the propagating light was routed to the upper interface and radiated from the G1 port. The asymmetry of photonic routing is reversed when the incidence port is flipped to the other interface (Fig. 4e). For comparison, we also fabricated a control sample that replaced the SOI VPC by a two-strip silicon waveguide (Fig. 4c). The near-equal routing profiles demonstrate low directionality in Figs. 4f, g. Valley-dependent unidirectional routing is already visible to be distinguished from the control experiment. \n\nThe intensity of each grating coupler was collected from CCD, and the intensities $I_{G I}$ and $I_{G2}$ scattered from the upper (G1) and lower (G2) ports can be extracted with a high signal-to-noise ratio, after subtracting the noise that mainly arises from background radiation. The extracted intensities $I_{G I}$ and $I_{G2}$ reflect the amount of light transmission that is coupled to the upper- and lower-propagating valley-dependent edge states, respectively. To experimentally qualify directional coupling efficiency of routing devices, we define the experimental directionality as $\\kappa_{\\mathrm{exp}}\\bar{=}(I_{G1}-I_{G2})/(I_{G1}+I_{G2})$ . The full-band directionality can be measured by tuning the operation wavelength of the excited waves. Figure 4h shows the directionality spectra as a function of wavelength. In the bandgap, a strong and broadband directionality was observed. For anticlockwise-phase-vortex excitation, the incident light couples to valley-dependent edge states propagating along the upper interface (red line in Fig. $^{4\\mathrm{g})}$ . The directionality of the topological routing device is up to 0.5 within a broadband region. Note that the maximum $\\kappa_{\\mathrm{exp}}$ is up to ${\\sim}0.895$ , implying a 18:1 extinction ratio between G1 and G2. When the handedness of the excitation flips, so do the propagation directions of the valley-dependent edge states (blue line in Fig. 4h). For comparison, the low-directionality spectra for the control experiment were depicted in Fig. 4i. There are a few discrete wavelengths to reach $\\lvert\\kappa_{\\mathrm{exp}}\\rvert>0.5$ . A more experimental description is presented in Supplementary Note 5. \n\n# Discussion \n\nIn summary, we have successfully applied the valley DOF to topologically manipulate the flow of light in a silicon-on-insulator platform. Benefiting from the below-light-cone operation, the valley-dependent topological edge state can balance in-plane robust transport and out-of-plane radiation, which is important to the open system, such as a photonic crystal slab. Topological robust transport and topological photonic routing are experimentally demonstrated and confirmed at telecommunication wavelength. Our study paves the way to explore the photonic topology and valley in the SOI platform, which is a promising system in taking advantage of the topological properties into nanophotonic devices, particularly important for backscattering suppression and unidirectional coupling. Furthermore, our subwavelength strategy enables to design compact-size topological SOI devices that allow integration with other optoelectronic devices on a single chip. It shows a prototype of the on-chip photonic device, with promising applications for delay line, routing, and dense wavelength division multiplexing for information processing based on topological nanophotonics. Finally, the platform of the SOI topology opens a new door toward the observation of nontrivial states even in non-Hermitian photonic systems. \n\nWe are aware of a related work on experimental demonstration of valley-dependent edge states through air-bridge slab structures with sharp-turning profiles37. \n\n# Methods \n\nNumerical simulation. All of the simulation results in this work are retrieved from a 3D asymmetric slab instead of a 2D model52. The band structures and the corresponding eigenfield patterns were calculated by MIT Photonic Bands53 (MPB) based on the plane-wave expansion (PWE) method, while all of the optical transport calculations were implemented by MIT Electromagnetic Equation Propagation54 (MEEP) based on the finite-difference time-domain (FDTD) method. In all 3D simulations, the maximum scale of the discrete grid is smaller than $24\\mathrm{nm}$ . making the resolution large enough to ensure the convergence. For Berry curvature calculations, the original data of eigenfield $\\Psi(x,y,z)=\\bigl[\\sqrt{\\varepsilon_{z}(x,y,z)}u_{k}^{E z}(x,y,z)$ ; $\\sqrt{\\mu_{z}(x,y,z)}u_{k}^{H z}(x,y,z)]^{T}$ are obtained from MPB, by scanning the whole Brillouin zone with step $\\delta k=0.005(2\\pi/a)$ . Here, $u_{k}^{E z}$ and $u_{k}^{H z}$ are the periodic parts of $E_{z}$ and $H_{z},$ respectively. Then the Berry curvature can be calculated by $\\Omega=i\\bar{\\nabla}_{\\mathbf{k}}\\times\\langle\\Psi|\\dot{\\nabla}_{\\mathbf{k}}|\\Psi\\rangle$ . \n\nSample fabrication. The experimental samples were manufactured by employing a top–down nanofabrication process on a SOI wafer (with a nominal $220\\mathrm{-nm}$ device layer and a $2.0\\mathrm{-}\\upmu\\mathrm{m}$ buried oxide layer). First, a $370\\mathrm{-nm}$ -thickness positive resist (ZEP520A) was spun with a rotating speed of $3500\\mathrm{{min}^{-1}}$ on the wafer, and dried for $10\\mathrm{min}$ at $180^{\\circ}\\mathrm{C}$ . The VPC patterns were defined by electron-beam lithography (EBPG5000 ES, Vistec) in the resist, and developed by dimethylbenzene for $70\\mathrm{{s}}$ . Second, inductively coupled plasma (ICP) etching step was applied to etch the VPC structures and coupling waveguides on the top $220\\mathrm{-nm}$ -thickness silicon layer. Then the resist was removed by using an ultrasonic treatment process at room temperature. The final step was to cut up and polish the facets of samples, in order for high–efficient incident coupling. \n\nOptical characterization. The experimental results of the transmission spectra and far-field microscopy images were realized with three tunable continuous-wave lasers (Santec TSL-550/710) at telecom wavelength $(1260\\sim1640\\mathrm{nm})$ ). The incident light was first launched into a fiber polarization controller to select the TE wave, and then coupled to the input waveguide with the aid of a polarization-maintaining lensed fiber. After passing through VPC devices, the propagating waves coupled to the output waveguide at the right end of the topological interface. For robust transport measurement (Fig. 2), the output signals were collected by another lensed fiber and detected by an optical powermeter (Ophir Nova-II). For photonic routing measurement (Fig. 4), the propagating waves coupled out in the $z$ -direction thanks to the gratings at the end of the waveguide. The out-of-plane radiation was collected by a $20\\times$ microscope objective and then imaged by using an InGaAs CCD (Xenics Bobcat-640-GigE). More details on the experimental setup are provided in Supplementary Note 4. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 28 May 2018 Accepted: 6 February 2019 \nPublished online: 20 February 2019 \n\n# References \n\n1. Caulfield, H. J. & Dolev, S. Why future supercomputing requires optics. Nat. Photon 4, 261–263 (2010). \n2. Haldane, F. & Raghu, S. Possible realization of directional optical waveguides in photonic crystals with broken time-reversal symmetry. Phys. Rev. Lett. 100, \n013904 (2008). \n3. Wang, Z., Chong, Y., Joannopoulos, J. & Soljačić, M. Reflection-free one-way edge modes in a gyromagnetic photonic crystal. Phys. Rev. Lett. 100, 013905 (2008). \n4. Lu, L., Joannopoulos, J. D. & Soljacic, M. Topological photonics. Nat. Photon 8, 821–829 (2014). \n5. Khanikaev, A. B. & Shvets, G. Two-dimensional topological photonics. Nat. Photon 11, 763–773 (2017). \n6. Ozawa, T. et al. Topological photonics. Preprint at http://arxiv.org/abs/ 1802.04173 (2018). \n7. Wang, Z., Chong, Y., Joannopoulos, J. D. & Soljacic, M. Observation of unidirectional backscattering-immune topological electromagnetic states. Nature 461, 772–775 (2009). \n8. Poo, Y., Wu, R.-x, Lin, Z., Yang, Y. & Chan, C. T. Experimental realization of self-guiding unidirectional electromagnetic edge states. Phys. Rev. Lett. 106, 093903 (2011). \n9. Fang, K., Yu, Z. & Fan, S. Realizing effective magnetic field for photons by controlling the phase of dynamic modulation. Nat. Photon 6, 782–787 (2012). \n10. Bahari, B. et al. Nonreciprocal lasing in topological cavities of arbitrary geometries. Science 358, 636–640 (2017). \n11. Chen, W.-J. et al. Observation of backscattering-immune chiral electromagnetic modes without time reversal breaking. Phys. Rev. Lett. 107, 023901 (2011). \n12. Rechtsman, M. C. et al. Photonic Floquet topological insulators. Nature 496, 196–200 (2013). \n13. Lu, L. et al. Experimental observation of Weyl points. Science 349, 622–624 (2015). \n14. Khanikaev, A. B. et al. Photonic topological insulators. Nat. Mater. 12, 233–239 (2012). \n15. Chen, W.-J. et al. Experimental realization of photonic topological insulator in a uniaxial metacrystal waveguide. Nat. Commun. 5, 5782 (2014). \n16. Cheng, X. et al. Robust reconfigurable electromagnetic pathways within a photonic topological insulator. Nat. Mater. 15, 542–548 (2016). \n17. Ni, X. et al. Spin- and valley-polarized one-way Klein tunneling in photonic topological insulators. Sci. Adv. 4, eaap8802 (2018). \n18. Hafezi, M., Mittal, S., Fan, J., Migdall, A. & Taylor, J. M. Imaging topological edge states in silicon photonics. Nat. Photon 7, 1001–1005 (2013). \n19. Harari, G. et al. Topological insulator laser: theory. Science 359, eaar4003 (2018). \n20. Bandres, M. A. et al. Topological insulator laser: experiments. Science 359, eaar4005 (2018). \n21. Wu, L.-H. & Hu, X. Scheme for achieving a topological photonic crystal by using dielectric material. Phys. Rev. Lett. 114, 223901 (2015). \n22. He, C. et al. Acoustic topological insulator and robust one-way sound transport. Nat. Phys. 12, 1124–1129 (2016). \n23. Yang, Y. et al. Visualization of a unidirectional electromagnetic waveguide using topological photonic crystals made of dielectric materials. Phys. Rev. Lett. 120, 217401 (2018). \n24. Barik, S. et al. A topological quantum optics interface. Science 359, 666–668 (2018). \n25. Gorlach, M. A. et al. Far-field probing of leaky topological states in alldielectric metasurfaces. Nat. Commun. 9, 909 (2018). \n26. Xiao, D., Yao, W. & Niu, Q. Valley-contrasting physics in graphene: magnetic moment and topological transport. Phys. Rev. Lett. 99, 236809 (2007). \n27. Xiao, D., Liu, G.-B., Feng, W., Xu, X. & Yao, W. Coupled spin and valley physics in monolayers of $\\ensuremath{\\mathrm{MoS}}_{2}$ and other group-VI dichalcogenides. Phys. Rev. Lett. 108, 196802 (2012). \n28. Xu, X., Yao, W., Xiao, D. & Heinz, T. F. Spin and pseudospins in layered transition metal dichalcogenides. Nat. Phys. 10, 343–350 (2014). \n29. Mak, K. F. & Shan, J. Photonics and optoelectronics of 2D semiconductor transition metal dichalcogenides. Nat. Photon 10, 216–226 (2016). \n30. Ma, T. & Shvets, G. All-Si valley-Hall photonic topological insulator. New J. Phys. 18, 025012 (2016). \n31. Dong, J.-W., Chen, X.-D., Zhu, H., Wang, Y. & Zhang, X. Valley photonic crystals for control of spin and topology. Nat. Mater. 16, 298–302 (2017). \n32. Chen, X.-D., Zhao, F.-L., Chen, M. & Dong, J.-W. Valley-contrasting physics in all-dielectric photonic crystals: Orbital angular momentum and topological propagation. Phys. Rev. B 96, 020202 (2017). \n33. Gao, F. et al. Topologically protected refraction of robust kink states in valley photonic crystals. Nat. Phys. 14, 140–144 (2018). \n34. Wu, X. et al. Direct observation of valley-polarized topological edge states in designer surface plasmon crystals. Nat. Commun. 8, 1304 (2017). \n35. Noh, J., Huang, S., Chen, K. P. & Rechtsman, M. C. Observation of photonic topological valley hall edge states. Phys. Rev. Lett. 120, 063902 (2018). \n36. Kang, Y., Ni, X., Cheng, X., Khanikaev, A. B. & Genack, A. Z. Pseudospin–valley coupled edge states in a photonic topological insulator. Nat. Commun. 9, 3029 (2018). \n37. Shalaev, M. I., Walasik, W., Tsukernik, A., Xu, Y. & Litchinitser, N. M. Robust topologically protected transport in photonic crystals at telecommunication wavelengths. Nat. Nanotech 14, 31–34 (2019). \n38. Lu, J., Qiu, C., Ke, M. & Liu, Z. Valley vortex states in sonic crystals. Phys. Rev. Lett. 116, 093901 (2016). \n39. Lu, J. et al. Observation of topological valley transport of sound in sonic crystals. Nat. Phys. 13, 369–374 (2016). \n40. Pal, R. K. & Ruzzene, M. Edge waves in plates with resonators: an elastic analogue of the quantum valley Hall effect. New J. Phys. 19, 025001 (2017). \n41. Vila, J., Pal, R. K. & Ruzzene, M. Observation of topological valley modes in an elastic hexagonal lattice. Phys. Rev. B 96, 134307 (2017). \n42. Collins, M. J., Zhang, F., Bojko, R., Chrostowski, L. & Rechtsman, M. C. Integrated optical Dirac physics via inversion symmetry breaking. Phys. Rev. A. 94, 063827 (2016). \n43. Jones, A. M. et al. Optical generation of excitonic valley coherence in monolayer WSe2. Nat. Nanotech 8, 634–638 (2013). \n44. Ye, Z., Sun, D. & Heinz, T. F. Optical manipulation of valley pseudospin. Nat. Phys. 13, 26–29 (2016). \n45. Born, M. & Wolf, E. Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light, 7th edn (Cambridge University Press, Cambridge, 1999). \n46. Xiao, D., Chang, M.-C. & Niu, Q. Berry phase effects on electronic properties. Rev. Mod. Phys. 82, 1959–2007 (2010). \n47. Fukui, T., Hatsugai, Y. & Suzuki, H. Chern numbers in discretized brillouin zone: efficient method of computing (Spin) Hall conductances. J. Phys. Soc. Jpn. 74, 1674–1677 (2005). \n48. Mock, A., Lu, L. & O’Brien, J. Space group theory and Fourier space analysis of two-dimensional photonic crystal waveguides. Phys. Rev. B 81, 155115 (2010). \n49. Sollner, I. et al. Deterministic photon-emitter coupling in chiral photonic circuits. Nat. Nanotech 10, 775–778 (2015). \n50. Lodahl, P. et al. Chiral quantum optics. Nature 541, 473–480 (2017). \n51. Rodríguez-Fortuño, F. J., Barber-Sanz, I., Puerto, D., Griol, A. & Martínez, A. Resolving light handedness with an on-chip silicon microdisk. ACS Photon 1, 762–767 (2014). \n52. Joannopoulos, J. D., Johnson, S. G., Winn, J. N. & Meade, R. D. Photonic Crystals: Molding the Flow of Light, 2nd edn (Princeton University Press, New Jersey, 2008). \n53. Johnson, S. G. & Joannopoulos, J. D. Block-iterative frequency-domain methods for Maxwell’s equations in a planewave basis. Opt. Express 8, 173–190 (2001). \n54. Oskooi, A. et al. Meep: A flexible free-software package for electromagnetic simulations by the FDTD method. Comput. Phys. Commun. 181, 687–702 (2010). \n\n# Acknowledgements \n\nThis work is supported by the National Natural Science Foundation of China (No. 61775243, No. 11761161002, No. 11704422, and No. 11522437), Natural Science \n\nFoundation of Guangdong Province (No. 2018A030310089, No. 2018B030308005), Science and Technology Program of Guangzhou (No. 201804020029), and Project funded by the China Postdoctoral Science Foundation (No. 2018M633206). \n\n# Author contributions \n\nAll authors contributed extensively to this work. X.-T.H. and J.-W.D. conceived the idea. X.-T.H. performed the numerical simulations and designed the experiment. E.-T.L. and H.-Y.Q. fabricated the samples. J.-J.Y. performed the measurements. J.-J.Y., X.-T.H., F.-L.Z. and J.-W.D. did the experimental data analysis. X.-T.H., X.-D.C. and J.-W.D. wrote the paper. All the authors contributed to discussion of the results and paper preparation. J.-W.D. supervised the project. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-08881-z. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41467-018-07947-8", + "DOI": "10.1038/s41467-018-07947-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-07947-8", + "Relative Dir Path": "mds/10.1038_s41467-018-07947-8", + "Article Title": "Ultrasensitive detection of miRNA with an antimonene-based surface plasmon resonullce sensor", + "Authors": "Xue, TY; Liang, WY; Li, YW; Sun, YH; Xiang, YJ; Zhang, YP; Dai, ZG; Duo, YH; Wu, LM; Qi, K; Shiyanullju, BN; Zhang, LJ; Cui, XQ; Zhang, H; Bao, QL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "MicroRNA exhibits differential expression levels in cancer and can affect cellular transformation, carcinogenesis and metastasis. Although fluorescence techniques using dye molecule labels have been studied, label-free molecular-level quantification of miRNA is extremely challenging. We developed a surface plasmon resonullce sensor based on two-dimensional nullomaterial of antimonene for the specific label-free detection of clinically relevant biomarkers such as miRNA-21 and miRNA-155. First-principles energetic calculations reveal that antimonene has substantially stronger interaction with ssDNA than the graphene that has been previously used in DNA molecule sensing, due to thanking for more delocalized 5s/5p orbitals in antimonene. The detection limit can reach 10 aM, which is 2.3-10,000 times higher than those of existing miRNA sensors. The combination of not-attempted-before exotic sensing material and SPR architecture represents an approach to unlocking the ultrasensitive detection of miRNA and DNA and provides a promising avenue for the early diagnosis, staging, and monitoring of cancer.", + "Times Cited, WoS Core": 665, + "Times Cited, All Databases": 693, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000454756900005", + "Markdown": "# Ultrasensitive detection of miRNA with an antimonene-based surface plasmon resonance sensor \n\nTianyu Xue1, Weiyuan Liang1, Yawen Li2, Yuanhui Sun2, Yuanjiang Xiang1, Yupeng Zhang1, Zhigao Dai3,4, Yanhong Duo1, Leiming Wu1, Kun Qi1, Bannur Nanjunda Shivananju1, Lijun Zhang $\\textcircled{1}$ 2, Xiaoqiang Cui2, Han Zhang 1 & Qiaoliang Bao 3 \n\nMicroRNA exhibits differential expression levels in cancer and can affect cellular transformation, carcinogenesis and metastasis. Although fluorescence techniques using dye molecule labels have been studied, label-free molecular-level quantification of miRNA is extremely challenging. We developed a surface plasmon resonance sensor based on two-dimensional nanomaterial of antimonene for the specific label-free detection of clinically relevant biomarkers such as miRNA-21 and miRNA-155. First-principles energetic calculations reveal that antimonene has substantially stronger interaction with ssDNA than the graphene that has been previously used in DNA molecule sensing, due to thanking for more delocalized $5s/5p$ orbitals in antimonene. The detection limit can reach ${10\\mathsf{a M}},$ which is 2.3–10,000 times higher than those of existing miRNA sensors. The combination of not-attempted-before exotic sensing material and SPR architecture represents an approach to unlocking the ultrasensitive detection of miRNA and DNA and provides a promising avenue for the early diagnosis, staging, and monitoring of cancer. \n\nBimoomnairtkoerirnsghaovf dipsoetaesnetsi1a. Iin tphaer ipcrueladri, itohen,redisaganonsiesed ntdo which an early diagnosis is crucial or diagnosis is currently difficult2. MicroRNA (miRNA), which constitutes a class of short RNA, is emerging as ideal candidates as noninvasive biomarkers for applications in toxicology, diagnosis, and monitoring treatment responses or adverse events3,4. The aberrant expression of miRNA has been found in all types of tumours, including pancreatic cancer, lung cancer, prostate cancer, colorectal cancer, triple-negative breast cancer and osteosarcoma4. The detection of tumour-specific circulating miRNA at an ultrahigh sensitivity is of utmost significance for the early diagnosis and monitoring of cancer5. Unfortunately, miRNA detection remains challenging because miRNA are present at low levels and comprise ${\\sim}0.01\\%$ of the total RNA mass in a given sample. Therefore, the development of new approaches or sensing media for miRNA detection at the molecular level is urgently needed for clinical disease diagnosis. \n\nTraditionally, the use of miRNA detection techniques, such as quantitative real-time PCR $(\\mathrm{qRT-PCR})^{6}$ , northern blotting7 and microarray-based hybridization8, is limited in early diagnosis in clinical practice due to the difficulty in amplification, the high cost, complex operations and low sensitivity. Due to its many advantages, such as non-destructive label-free detection, high reproducibility and low cost, the surface plasmon resonance (SPR) technique has proven to be versatile in investigations of molecular interactions by assessing the refractive index change on a chip surface9–11. Nevertheless, using the traditional SPR technique to detect biomolecules at very low concentrations remains challenging due to the limited quantity of immobilized probe DNA and miRNA on the chip surface (normally a thin gold film)12–17. Therefore, there is an urgent need to identify advanced material with large adsorption energy and work function increment to improve the performance of the SPR biosensor. Recently, numerous emerging two-dimensional (2D) nanomaterials have been tested for DNA molecule sensing, including graphene18–20, transition-metal dichalcogenides $(\\mathrm{\\tilde{T}M D s})^{21,2\\tilde{2}};$ topological insulators23,24, black phosphorus25,26 and MXenes27. However, most nanomaterials are subject to certain limitations due to weak interactions with biomolecules or poor chemical stability. Identifying a new 2D material with a stronger molecular-level interaction with biomarkers is critical. \n\nAntimonene has been described as a 2D material that can be exfoliated from bulk antimony (Sb) and has quickly attracted the attention of the scientific community because its physicochemical properties are superior to those of typical 2D materials (e.g., graphene, $\\mathbf{MoS}_{2}$ , and black phosphorus)28,29. Similar to graphene materials, antimonene has an $s p^{\\widehat{2}}$ -bonded honeycomb lattice, but antimonene exhibits strong spin–orbit coupling, tremendous stability and hydrophilicity that is significantly better than that of graphene29,30. Antimonene nanosheets and quantum dots have already been used in nonlinear optics31, photothermal therapy (PTT)32, thermophotovoltaic (TPV) cells33, and field effect transistors (FET)34. Although the photoelectrical properties of antimonene nanomaterials have been studied, the interaction between DNA and antimonene and its application in optical sensing remain elusive. \n\nHere, we firstly explored via first-principles density functional theory (DFT) calculations the chemical interactions of singlestranded DNA (ssDNA) and double-stranded DNA (dsDNA) with antimonene, and find that antimonene has much better sensitivity than graphene previously used in DNA molecule sensing. Motivated by this theoretical finding, we developed a SPR sensor by using antimonene materials and performed trace attomolar-level quantification of miRNA molecules. This method reached an extremely low limit of detection (LOD), surpassing that of existing sensing methods. In addition, the sensor can distinguish miRNA that differ by one nucleobase mutation. Because of the extremely large adsorption energy between ssDNA and antimonene, we can envision an ultrasensitive RNA and DNA sensor device for early cancer diagnosis. This proposed methodology based on antimonene materials for nucleic acid detection holds intriguing potential for the development of multiplexed lab-on-chip platforms, which can be further applied for clinical purposes. \n\n# Results \n\nFirst-principles calculations. DFT-based energetic calculations including dispersive Van der Waals forces were performed to investigate the differential interactions of ssDNA and dsDNA with antimonene, as summarized in Fig. 1. The changes in work function after ssDNA/dsDNA absorption are shown in Table 1. The interactions with graphene were studied for direct comparison. The adsorption energies $(E_{\\mathrm{ad}})$ of the bases on antimonene are higher than those of the base-pairs on antimonene, indicating the stronger interaction between the nucleobases and antimonene. The work function $(\\Delta W)$ shows substantial increase after DNA absorption. These behaviors are consistent with those of current and previous calculations of graphene-based systems35. Distinctly and importantly, we found that by comparison with graphene, antimonene exhibits the much stronger interaction with ssDNA, as indicated by the higher adsorption energies (for the ssDNA absorption case, Fig. 1g) as well as the about 1.5 times larger work function increment (Table 1). This is further supported by the charge density difference map between antimonene/graphene with DNA absorption and noninteracting counterparts (Fig. 1h), where the stronger charge transfer and electronic orbital hybridization occurs in the antimonene case (upper panel). Further calculations of adsorption energies and work functions for the nucleobases on top of antimonene/graphene with varied adsorption orientations indicate that the bases adsorption orientations have negligible effect on the above results obtained (see Supplementary Fig. 1). The underlying mechanism might be related to the more delocalized $5s/5p$ orbitals or the buckling honeycomb lattice of antimonene. These results indicate that antimonene is more sensitive to ssDNA than graphene in terms of sensing ability. \n\nMethodology of an antimonene-based miRNA sensor. The strategy adopted for the highly sensitive detection of miRNA hybridization events on antimonene-modified SPR chips is depicted in Fig. 2. The SPR signal is sensitive to changes in the refractive index of the analyte. First, AuNRs are employed to connect with ssDNA to amplify the SPR signal. Then, AuNRssDNA complex is adsorbed onto the antimonene nanosheet due to the strong interaction between ssDNA and antimonene. Following the addition of complementary miRNA, the hybridized targets are easily desorbed from the antimonene interface since double-stranded DNA has a low affinity to antimonene. The amount of miRNA can be typically determined based on the negative shift of the SPR signal. The investigation of AuNRssDNA-modified antimonene interfaces is beneficial for detecting miRNA hybridization events. \n\nPreparation of the few-layer antimonene. Liquid-phase sonication is an effective method for preparing few-layer antimonene by breaking weak van der Waals forces. We obtained few-layer antimonene nanosheets using sonication liquid exfoliation as shown in Fig. 3a. The antimonene nanosheets consist of $\\beta$ -phase antimony based on the hexagonal coordinate system. The chemical composition and morphology of the prepared samples were systematically investigated. As shown in Fig. 3b, the Faraday–Tyndall effect, which is known as light scattering by particles in a fine suspension, was clearly observed, indicating the existence of antimonene nanosheets in the solution. Figure 3c shows a transmission electron microscope (TEM) image of the few-layer antimonene flake, in which very thin 2D nanosheets are resolved. The high-resolution TEM (HRTEM) image shows that the lattice is pure without any defects. The Fast Fourier Transform (FFT) image shows that the single-crystalline antimonene is a cubic system (Fig. 3d). The atomic force microscope (AFM) topography of typical antimonene nanosheets is shown in Fig. 3e. The overall lateral dimensions of the nanosheets are greater than $300\\mathrm{nm}$ , and the thinnest piece is ${\\sim}3\\mathrm{nm}$ thick. \n\n![](images/0ed5f0d11aa901938c02fd5bb745fa8501dc0b9295585e4f1a5b2d148c1575ec.jpg) \nFig. 1 Geometry and energies of adsorption systems. a Top and side views of the optimized structure of A nucleobases on antimonene. b Top and side views of the optimized structure of T nucleobases. c Top and side views of the optimized structure of G nucleobases. d Top and side views of the optimized structure of C nucleobases. e Top and side views of the optimized structure of $\\mathsf{A}{-}\\mathsf{T}$ base-pairs on antimonene. f Top and side views of the optimized structure of $G-C$ base-pairs on antimonene. g Adsorption energies of adsorbed nucleobases and base-pairs on antimonene and graphene. Blue bars respect to graphene $+\\mathsf{A}$ , black bars respect to antimonene $\\mathrm{\\Omega}\\cdot+\\mathsf{A},$ , red bars respect antimonene $+A-T$ . h Side views of the charge density difference of the nucleobases on antimonene and graphene \n\nThe crystal structure of antimonene was confirmed by XRD spectrum36 as depicted in Fig. 3f. The diffraction peaks of antimonene were identical to the spectrum of $\\beta$ -Sb precursor (JCPDS No. 35-0732). To further investigate the crystal structure and quality of the antimonene nanosheets, the Raman spectra of typical few-layer antimonene and bulk antimony were measured (Fig. 3g). Two characteristic Raman peaks, i.e., $\\operatorname{E}_{g}$ at $117\\mathrm{cm}^{-1}$ and $\\mathrm{A}_{I g}$ at $153\\mathrm{cm}^{-1}$ , were observed in the Raman spectra of the few-layer antimonene. The degenerate modes of $\\mathrm{E}_{g}$ symmetry, which correspond to the in-plane transversal and longitudinal vibrations of the sublayers in opposite directions, cause the experimentally observed Raman peak at $117\\mathrm{cm}^{-1}$ . The peak at $15\\bar{3}\\mathrm{cm}^{-1}$ is caused by the third mode opposite-in-phase out-ofplane vibrations of the sublayers of the $\\mathbf{A}_{I g}$ symmetry37. Compared to the bulk material, in the few-layer system, a strong contraction of the in-plane lattice constant occurred as the film thickness decreased. Thus, the bulk $\\mathbf{A}_{I g}$ mode blue shifted from $150\\mathrm{cm}^{-1}$ to $153\\mathrm{cm}^{-1}$ , and the film thickness decreased. The chemical compositions of the prepared antimonene were confirmed by X-ray photoelectron spectroscopy (XPS) as shown in Fig. 3h. The two characteristic peaks at $528\\mathrm{eV}$ and $537.5\\mathrm{eV}$ are attributed to the Sb $3d_{5/2}$ and Sb $3d_{3/2}.$ respectively, characteristics of nonvalent antimony37. \n\n
Table1Calculated verticaldistance (A)and workfunctionchange(△W)of antimonene and graphenewithnucleobases and base-pairs
ATGCA-TG-C
AntimoneneDistance (A)3.53.653.483.5
△W (eV)0.0930.120.130.0960.1040.071
GrapheneW (eV)0.0750.0830.0860.0450.0640.055
The calculated work functions of isolated antimonene and graphene are 4.389 and 4.2O8eV, respectively
\n\n![](images/4196a0c32614fe6110ae97e4fce70fc7de9e4e12f978fac8dd910d9060634dba.jpg) \nFig. 2 Fabrication of a miRNA sensor integrated with antimonene nanomaterials. Schematic illustration of the strategy employed to detect antimonenemiRNA hybridization events. I The antimonene nanosheets was assembled on the surface of Au film. II AuNR-ssDNAs were adsorbed on the antimonene nanosheets. III miRNA solution with different concentrations flowed through the surface of antimonene, and paired up to form a double-strand with complementary AuNR-ssDNA. IV The interaction between miRNA with AuNR-ssDNA results in release of the AuNR-ssDNA from the antimonene nanosheets. The reduction in the molecular of the AuNR-ssDNA on the SPR surface makes for a significant decrease of the SPR angle \n\nSensitivity simulation and LBL assembly of antimonene. To investigate the key point of antimonene for improving SPR sensor performance, a numerical simulation was performed to evaluate the effect of the antimonene thickness on the sensitivity of the SPR sensor. The sensitivity can be defined as $S=\\triangle\\theta/\\triangle\\dot{n},$ which is the ratio of the change in the resonance angle to the change in the refractive index of analyte38. The electric field distribution is shown in Supplementary Fig. 2, in which further enhancment rather than immediate drop in the electric field is observed while four layers antimonene is used. Figure 4a shows the variation in sensitivity with respect to the refractive index of the sensing medium and the number of antimonene layers in the proposed SPR biosensor. The simulation results suggest that antimonene materials can greatly improve the sensitivity of the SPR sensor. Figure 4b shows the variation in the sensitivity of the antimonene-based miRNA SPR sensor concerning the antimonene layer when the refractive index of the sensing medium is $1.37+\\triangle\\dot{n}$ . The sensitivity first increases to the maximum $\\cdot171^{\\circ}$ $\\mathrm{RIU^{-1}}.$ ) when the number of antimonene layer is 4 and then begins to decrease when $L>4$ . The highest sensitivity was obtained with four layers of antimonene (details shown in Supplementary Information). \n\nThe above simulations provide clear guidance for the assembly of antimonene nanosheets on SPR chip surfaces. Experimentally, we assembled the antimonene nanosheets on a gold chip surface using a layer-by-layer technique. Figure $\\mathtt{4c}$ shows the representative AFM topography of antimonene nanosheets assembled on an Au chip surface. Although the surface of Au film exhibits rough, the distribution of the nanosheets is relatively uniform, and the average thickness of the nanosheets is ${\\sim}5\\mathrm{nm}$ (see Supplementary Fig. 2e). The consecutive build-up of the layer-by-layer (LBL) antimonene film was monitored by AFM (Supplementary Fig. 2). The increase in the surface coverage and thickness as a function of the number of assembled layers indicates that a very uniform increase in the average layer thickness occurred during each dipping cycle. To further confirm the results of the antimonene assembly, contact angle experiments were carried out (Fig. 4d). After the antimonene nanosheets were assembled on the sensor chip, the contact angle was approximately $38^{\\circ}$ due to the high hydrophilicity of the antimonene material. The long-time chemical durability of antimonene nanosheets is outstanding (shown in Supplementary Fig. 3). Hence, we can control the assembly of antimonene films on SPR chip surfaces using layerby-layer assembly techniques. \n\nmiRNA sensing performance of antimonene. We measured the angle-resolved SPR spectra of the target miRNA-21 at very low concentration. The SPR responses upon the addition of complementary miRNA-21 are displayed in Fig. 5a. A prominent shift can be observed in the resonance angle, revealing the desorption of \n\n![](images/20a630c11fb0541679cb71f83afb602ade2454df7e6c35af3242588bcfdf027a.jpg) \nFig. 3 Fabrication and characterization of antimonene materials. a A schematic representation of the preparation process of two-dimensional antimonene. b Photograph of a dispersion of exfoliated antimonene showing the Faraday–Tyndall effect. c, d TEM (scale bar $=400{\\mathsf{n m}}.$ and FFT-masked HRTEM images (scale bar $=2{\\mathsf{n m}}$ ) of few-layer antimonene after exfoliation. e AFM topography showing few-layer antimonene on mica (scale bar $=400{\\mathsf{n m}}.$ . f XRD spectrum of antimonene (blue line). g Raman spectra of bulk antimony with $\\upbeta$ -phase (black line) and few-layer antimonene (blue line). The two peaks represent two different vibrational modes. h XPS spectra of Sb $3d$ \n\nAuNR-ssDNA. The hybridization of the target miRNA-21 results in an obvious left-shift in the SPR angles even at very low concentrations of $10^{-17}\\mathrm{M}$ . Using the same process but with unmodified-ssDNA, the shift in the SPR angle is barely detectable with the same concentrations (Fig. 5b). The calibration curve of the SPR angle shift versus the miRNA-21 concentration is shown in Fig. 5c. In the case of AuNR-ssDNA adsorption by antimonene, the detection limit of miRNA-21 was determined to be 10 aM according to the IUPAC guideline of a 3:1 signal to noise ratio. This detection limit is $10^{5}$ times lower than that using the non-modified ssDNA. Figure 5d shows the real-time desorption process of AuNRss DNA, which reaches a plateau after $5\\mathrm{{min}}$ (Fig. 5d). When one base mismatched miRNA was used, the SPR angle slightly shifted to the right relative to that of AuNR-ssDNA (Fig. 5e), indicating good selectivity. Thus, opposite signals are obtained for mismatched miRNA, indicating that mismatched miRNA also bound the antimonene surface instead of binding to the AuNR-ssDNA conjugates39,40. Importantly, we observed similar results in the detection of miRNA-155 and ssDNA (Supplementary Fig. 4, 5), suggesting that the antimonene nanomaterials are universal for the detection of miRNA and ssDNA. \n\nTo further demonstrate the sensitivity of our device, we compared the LOD of the antimonene 2D materials with that of previously reported miRNA biosensors41–47 as presented in Fig. 5f. Our antimonene-based miRNA SPR biosensor outperforms other miRNA biosensors based on conventional 2D nanomaterials41–47. In particular, the LOD of miRNA sensing can approach 10 aM ( $_{\\sim30}$ molecules for a ${5\\upmu\\mathrm{L}}$ sample), indicating the great potential of antimonene nanosheets in applications, such as single-molecule biological imaging, clinical therapy, and environmental monitoring48,49. \n\n# Discussion \n\nThe unprecedented high sensitivity of the SPR sensor not only relies on the strong interaction between antimonene and singlestranded DNA but also benefits from the enhanced coupling between the localized-SPR (LSPR) of the gold nanorods and propagating-SPR of the gold film. The preparation of AuNRs is characterized by TEM images (Fig. 6a). As shown in Fig. 6b, AuNRs modified with ssDNA show red-shifted plasmon bands at 513 and $747\\mathrm{nm}$ . The signal enhancement due to the electromagnetic field coupling between the plasmonic properties of the AuNRs and propagating plasmons was expected. As shown in Fig. 6c–e, the electromagnetic field intensity distributions of single AuNRs on gold films with a $5\\mathrm{nm}$ thick antimonene spacer were calculated by the finite-difference time-domain (FDTD) method50. The FDTD simulation parameters were consistent with the experimental conditions51. Compared with conventional SPR using gold film, a considerable electromagnetic enhancement was observed based on the evanescent field excitation and LSPR of the AuNRs with certain thickness of antimonene nanosheets. The simulation results of the local electric field distribution around antimonene nanosheets with different thicknesses were shown in Supplementary Fig. 6, which further verify the trend of sensitivity shown in Fig. 4b. The electric field at the optimal gap (antimonene layer) between the gold film and gold nanorod is increased by ${\\sim}300$ times at incident light wavelengths of $632.8\\mathrm{nm}$ , where $|E|=|E_{\\mathrm{local}}/E_{\\mathrm{in}}|$ , $E_{\\mathrm{local}}$ and $E_{\\mathrm{in}}$ are the local and incident electric fields, respectively. Thus, the sensor sensitivity is significantly improved by AuNRs. \n\n![](images/c311ba5bc2a7eba51422ed57501030f95b3fed12b3df96f85c663c252851299a.jpg) \nFig. 4 Simulation of antimonene SPR sensors and the antimonene assembly on the sensor chip. a, b The variation in the sensitivity of the proposed biochemical sensor when the refractive index of the sensing medium is $1.37+\\triangle n$ with respect to the different number of antimonene layers. To vividly illustrate the relationship of sensitivity with the number Sb layers, we assume that the number of Sb layers $(n=2.1+0.45i)$ can be continuously changed. c AFM images of antimonene on Au film (scale bar $=2\\upmu\\mathrm{m};$ . d Images of distilled water droplets on antimonene assembled on Au film \n\nIn this paper, we demonstrated the efficiency and ultrasensitivity of the antimonene-based SPR sensor in the quantitative detection of cancer-associated miRNA. Specifically, we applied the sensor to detect miRNA-21 and miRNA-155, which are promising biomarkers for cancer diagnosis. This antimonenebased biosensor has a LOD of $10\\ \\mathrm{aM}$ , representing the highest sensitivity described thus far in miRNA detection based on direct detection and quantification of miRNA levels. More importantly, the signal amplification of the AuNRs and the interaction between antimonene and ssDNA/dsDNA were computationally and experimentally investigated. Consequently, the proposed biosensor represents the first methodology reported using antimonene materials for clinically relevant nucleic acid detection and constitutes an extraordinary opportunity for the development of lab-on-chip platforms. Nevertheless, for clinical and practical applications of the antimonene-based SPR sensor to be successfully used in early cancer diagnosis and the realization of pointof-care systems, future investigations of the specificity and high throughput are critically needed. \n\n# Methods \n\nFirst-principles calculations. Calculations were performed using DFT-based planewave pseudopotential methods as implemented in the Vienna Ab initio Simulation Package52,53. We described the electron-ion interactions using the projected augmented wave pseudopotentials with $5s^{2}5p^{3}$ for Sb, $2s^{2}2p^{2}$ for C, $2s^{2}2\\dot{p}^{3}$ for N, 1s for $\\mathrm{~H~}$ , and $2s^{2}2p^{4}$ for O as valence electrons54. The generalized gradient approximation formulated by Perdew, Burke, and Ernzerhof was used as the exchange correlation functional55. To simulate DNAs absorbing antimonene, a separation of $20\\textup{\\AA}$ in the $z$ direction was adopted to avoid interactions between adjacent antimonenes (in $6\\times6$ or larger supercells). The nucleobase molecules were terminated with a methyl group to replace the sugar ring and generate an electronic environment as similar to a DNA chain as possible. The kinetic energy cut off for wave function expansion was set to $520\\mathrm{eV}$ , and the single Г point of the supercell was used for sampling the electronic Brillouin zone. Equilibrium structures of DNAs absorbing antimonene were obtained through total energy minimization with the energy convergence threshold of $1\\mathrm{meV}$ . \n\n![](images/f6063b1b7108a16a55e54ccdf2a3c87e754dc7234076e4175f8038859230e185.jpg) \nFig. 5 Sensing miRNA-21 using an antimonene SPR sensor. a SPR spectra with miRNA-21 concentrations ranging from $10^{-17}$ to $10^{-11}\\mathsf{M}$ using AuNRs amplification. The arrow denotes the shift in the SPR angle. b SPR spectra with miRNA-21 concentrations ranging from $10^{-17}$ to $10^{-11}\\boldsymbol{\\mathsf{M}}$ without AuNRs. c The relationship between the SPR angle and miRNA concentration. Each point corresponds to the SPR angle shift with the indicated miRNA concentration. All error bars is the standard error of SPR angle shift from five data points. d The real-time SPR response of ssDNA-AuNR desorption from the antimonene surface. e The SPR curve change of miRNA-21 contained one mismatched nucleobase (red line). f Comparison of the LOD of the antimonene miRNA SPR sensor with that of state-of-the-art sensors \n\nWe used the vdW-optB86b functional to properly take into account the long-range van der Waals interactions56. \n\nFDTD simulation. The near-field distribution of AuNRs on gold film under a $632.8\\mathrm{nm}$ incident laser was simulated by the FDTD method. To model the AuNRs on a gold film, the FDTD method was used with antisymmetric and symmetric boundary conditions at the $x{-}y$ axis and $z{-}y$ axis, respectively. The propagation of the plane waves was directed along $45^{\\circ}$ from the $x$ axis. For all simulations, the parameters of the AuNRs nanostructures were set according to the average sizes $\\mathrm{70~nm})$ measured from the experimental results. The mesh size was $1\\mathrm{nm}$ . The electromagnetic field distribution of the Au nanorod was calculated at incident light wavelengths of $632.8\\mathrm{nm}$ . The refractive index of Au used for the simulation was taken from the source program. \n\nSynthesis of antimonene nanosheets. The antimonene nanosheets were prepared by probe-sonication liquid-phase exfoliation in ethanol. Pulverized antimony (Sb) powder at an initial concentration of $30\\mathrm{mg}\\mathrm{mL}^{-1}$ was dispersed in a glass vial containing ethanol. Subsequently, the Sb powder solution was sonicated for $^{\\textrm{1h}}$ in an ice-bath at $450\\mathrm{W}$ and $22\\mathrm{kHz}$ with ultrasound probe $0.5\\:\\mathrm{s}$ pulses. Then, the resulting solution was centrifuged at $1509.3\\mathrm{\\times}g$ for $10\\mathrm{min}$ . Finally, the supernatant containing the antimonene nanosheets were carefully collected in a clean glass vial for future use. \n\nBioconjugation of AuNRs with ssDNA. The AuNRs were chemically modified with $5^{\\prime}$ -thiol-called oligonucleotides according to the procedure described by Mirkin et al.57. In total, $25\\upmu\\mathrm{L}$ of a $100\\mathrm{nM}$ HS-ssDNA solution were added to $200\\upmu\\mathrm{L}$ of the AuNRs solution $20{\\mathrm{nM}}$ in $0.1\\mathbf{M}$ PBS). After $16\\mathrm{h}$ the solution was mixed with $0.25\\mathrm{mL}$ of $10\\%$ NaCl. Then, AuNR-ssDNA was centrifuged twice at $3018.6\\times g$ for $20\\mathrm{{s}}$ to remove the excess HS-ssDNA, and the particles were redispersed in PBS buffer $\\mathrm{1MNaCl}$ , $100\\mathrm{mM}$ PBS, $\\mathrm{\\pH}=7$ ). The resultant colloidal solution was sonicated for 5 min and then stirred for $^{\\textrm{1h}}$ at room temperature. \n\n![](images/d30c148d3380041c4e415a98a125189dd0ca5f725d0f01fabfc311f20d8f4284.jpg) \nFig. 6 Signal amplification of AuNRs. a TEM image of gold nanorods (scale bar $=200{\\mathsf{n m}}$ ). b UV-Vis characterization spectra of ssDNA (black line), AuNRs (red line), and AuNR-ssDNA (blue line). c Schematic diagram of the SPR-AuNR configuration used for the FDTD simulation. d The FDTD calculated enhancement in the local electric field distribution $(\\log|E E_{\\mathrm{inc}}-^{1}|^{2})$ of AuNRs at $632.8\\mathsf{n m}$ with the incident wave-plane polarized along the $x$ -direction. A 5 nm antimonene is set between the gold film and AuNRs. e The side view of FDTD calculated enhancement in the local electric field distribution \n\nSensing test. The AuNR-ssDNA solution was injected over the antimonene SPR chip and washed with PBS buffer. Complementary and noncomplementary miRNA in PBS were injected, and the hybridization signal was recorded. The sequences of the oligonucleotides are shown in Supplementary Table 1. \n\nCharacterization. SPR measurements were performed with a commercially available Time-Resolved Surface Plasmon Resonance Spectrometer (DyneChem, China). TEM and HRTEM images were obtained under a JEM-3200FS microscope (JEOL, Japan). The Raman spectra were collected using an iHR 320 spectrometer (Horibai, Japan). The AFM images were taken under an L01F4C8 microscope (Bruker, Germany). The UV-visible spectroscopy was performed using Cary60 (Agilent, Malaysia). XRD was determined by a D8 Advance instrument (Bruker, Germany). The XPS data were collected using an ESCALAB 250Xi XPS spectrometer (Thermo Fisher, America). The contact angle experiments were performed with a Theta instrument (Biolin Scientific, Sweden). \n\nSupporting information. Details of the AFM images, SPR results for miRNA-155 and oligonucleotide sequences are provided. This material is available free of charge via the Internet at http://www.nature.com/naturecommunications \n\n# Data availability \n\nThe authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information files. \n\nReceived: 27 May 2018 Accepted: 4 December 2018 \nPublished online: 03 January 2019 \n\n# References \n\n1. Vargas, A. J. & Harris, C. C. Biomarker development in the precision medicine era: lung cancer as a case study. Nat. Rev. Cancer 16, 525 (2016). \n2. O’Connor, J. P. B. et al. Imaging biomarker roadmap for cancer studies. Nat. Rev. Clin. Oncol. 14, 169 (2016). \n3. Lewis, B. P., Burge, C. B. & Bartel, D. P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are MicroRNA targets. Cell 120, 15–20 (2005). \n4. Lu, J. et al. MicroRNA expression profiles classify human cancers. Nature 435, \n834 (2005). \n5. Lin, S. & Gregory, R. I. MicroRNA biogenesis pathways in cancer. Nat. Rev. Cancer 15, 321 (2015). \n6. Thomou, T. et al. Adipose-derived circulating miRNAs regulate gene expression in other tissues. Nature 542, 450 (2017). \n7. Lee, R. C. & Ambros, V. An extensive class of small RNAs in Caenorhabditis elegans. Science 294, 862–864 (2001). \n8. Li, Q. et al. Cellular microRNA networks regulate host dependency of hepatitis C virus infection. Nat. Commun. 8, 1789 (2017). \n9. Xu, S. et al. Real-time reliable determination of binding kinetics of DNA hybridization using a multi-channel graphene biosensor. Nat. Commun. 8, \n14902 (2017). \n10. Arlett, J. L., Myers, E. B. & Roukes, M. L. Comparative advantages of mechanical biosensors. Nat. Nanotechnol. 6, 203 (2011). \n11. Cao, S.-H., Xie, T.-T., Cai, W.-P., Liu, Q. & Li, Y.-Q. Electric field assisted surface plasmon-coupled directional emission: an active strategy on enhancing sensitivity for DNA sensing and efficient discrimination of single base mutation. J. Am. Chem. Soc. 133, 1787–1789 (2011). \n12. Li, J. et al. An enzyme-free surface plasmon resonance biosensor for real-time detecting microRNA based on allosteric effect of mismatched catalytic hairpin assembly. Biosens. Bioelectron. 77, 435–441 (2016). \n13. Li, Q. et al. High sensitivity surface plasmon resonance biosensor for detection of microRNA and small molecule based on graphene oxide-gold nanoparticles composites. Talanta 174, 521–526 (2017). \n14. Li, X. et al. A novel surface plasmon resonance biosensor for enzyme-free and highly sensitive detection of microRNA based on multi component nucleic acid enzyme (MNAzyme)-mediated catalyzed hairpin assembly. Biosens. Bioelectron. 80, 98–104 (2016). \n15. Liu, R. et al. Surface plasmon resonance biosensor for sensitive detection of microRNA and cancer cell using multiple signal amplification strategy. Biosens. Bioelectron. 87, 433–438 (2017). \n16. Na, H.-K. et al. Discrimination of single nucleotide mismatches using a scalable, flexible, and transparent three-dimensional nanostructure-based plasmonic miRNA sensor with high sensitivity. Biosens. Bioelectron. 113, \n39–45 (2018). \n17. Qian, S. et al. Boronic acid functionalized Au nanoparticles for selective microRNA signal amplification in fiber-optic surface plasmon resonance sensing system. ACS Sensors 3, 929–935 (2018). \n18. Rodrigo, D. et al. Mid-infrared plasmonic biosensing with graphene. Science \n349, 165–168 (2015). \n19. Prabowo, B. et al. Graphene-based portable SPR sensor for the detection of Mycobacterium tuberculosis DNA strain. Procedia Eng. 168, 541–545 (2016). \n20. P Shivananju, B. N. et al. The roadmap of graphene—based optical biochemical sensors. Adv. Funct. Mater. 27, 1603918 (2017). \n21. Manzeli, S., Ovchinnikov, D., Pasquier, D., Yazyev, O. V. & Kis, A. 2D transition metal dichalcogenides. Nat. Rev. Mater. 2, 17033 (2017). \n22. Tan, C. et al. High-yield exfoliation of ultrathin two-dimensional ternary chalcogenide nanosheets for highly sensitive and selective fluorescence DNA sensors. J. Am. Chem. Soc. 137, 10430–10436 (2015). \n23. Zhang, Y. et al. Crossover of the three-dimensional topological insulator Bi2Se3 to the two-dimensional limit. Nat. Phys. 6, 584 (2010). \n24. Chang, C. Z. et al. Experimental observation of the quantum anomalous hall effect in a magnetic topological insulator. Science 340, 167–170 (2013). \n25. Qiu, M. et al. Novel concept of the smart NIR-light–controlled drug release of black phosphorus nanostructure for cancer therapy. Proc. Natl Acad. Sci. USA \n115, 501–506 (2018). \n26. Wang, Y. W. et al. Ultraviolet saturable absorption and ultrafast carrier dynamics in ultrasmall black phosphorus quantum dots. Nanoscale 9, 4683–4690 (2017). \n27. Dai, C. et al. Two-dimensional tantalum carbide (MXenes) composite nanosheets for multiple imaging-guided photothermal tumor ablation. ACS Nano 11, 12696–12712 (2017). \n28. Gibaja, C. et al. Few-layer antimonene by liquid-phase exfoliation. Angew. Chem. Int. Ed. 55, 14345–14349 (2016). \n29. Pizzi, G. et al. Performance of arsenene and antimonene double-gate MOSFETs from first principles. Nat. Commun. 7, 12585 (2016). \n30. Pumera, M. & Sofer, Z. 2D monoelemental arsenene, antimonene, and bismuthene: beyond black phosphorus. Adv. Mater. 29, 1605299 (2017). \n31. Lu, L. et al. Broadband nonlinear optical response in few-layer antimonene and antimonene quantum dots: a promising optical Kerr media with enhanced stability. Adv. Opt. Mater. 5, 1700301 (2017). \n32. Tao, W. et al. Antimonene quantum dots: synthesis and application as nearinfrared photothermal agents for effective cancer therapy. Angew. Chem. Int. Ed. 56, 11896–11900 (2017). \n33. Xie, M. et al. Van der Waals bilayer antimonene: a promising thermophotovoltaic cell material with $31\\%$ energy conversion efficiency. Nano Energy 38, 561–568 (2017). \n34. Wang, Y. et al. Many-body effect, carrier mobility, and device performance of hexagonal arsenene and antimonene. Chem. Mater. 29, 2191–2201 (2017). \n35. Yin, Y., Cervenka, J. & Medhekar, N. V. Molecular dipole-driven electronic structure modifications of DNA/RNA nucleobases on graphene. J. Phys. Chem. Lett. 8, 3087–3094 (2017). \n36. Chen, K. et al. Growth kinetics and mechanisms of multinary copper-based metal sulfide nanocrystals. Nanoscale 9, 12470–12478 (2017). \n37. Ji, J. et al. Two-dimensional antimonene single crystals grown by van der Waals epitaxy. Nat. Commun. 7, 13352 (2016). \n38. Wu, L. et al. Sensitivity enhancement by using few-layer black phosphorusgraphene/TMDCs heterostructure in surface plasmon resonance biochemical sensor. Sens. Actuators B 249, 542–548 (2017). \n39. Dong, X., Shi, Y., Huang, W., Chen, P. & Li, L. J. Electrical detection of DNA hybridization with single-base specificity using transistors based on CVDgrown graphene sheets. Adv. Mater. 22, 1649–1653 (2010). \n40. He, S. et al. A graphene nanoprobe for rapid, sensitive, and multicolor fluorescent DNA analysis. Adv. Funct. Mater. 20, 453–459 (2010). \n41. Miao, X., Ning, X., Li, Z. & Cheng, Z. Sensitive detection of miRNA by using hybridization chain reaction coupled with positively charged gold nanoparticles. Sci. Rep. 6, 32358 (2016). \n42. Wang, Y., Zheng, D., Tan, Q., Wang, M. X. & Gu, L.-Q. Nanopore-based detection of circulating microRNAs in lung cancer patients. Nat. Nanotechnol. \n6, 668 (2011). \n43. Fan, Y. et al. Detection of microRNAs using target-guided formation of conducting polymer nanowires in Nanogaps. J. Am. Chem. Soc. 129, \n5437–5443 (2007). \n44. Wanunu, M. et al. Rapid electronic detection of probe-specific microRNAs using thin nanopore sensors. Nat. Nanotechnol. 5, 807 (2010). \n45. Dorvel, B. R. et al. Silicon nanowires with high-k hafnium oxide dielectrics for sensitive detection of small nucleic acid oligomers. ACS Nano 6, 6150–6164 (2012). \n46. Labib, M. et al. Three-mode electrochemical sensing of ultralow microRNA levels. J. Am. Chem. Soc. 135, 3027–3038 (2013). \n47. Huertas, C. S., Fariña, D. & Lechuga, L. M. Direct and label-free quantification of micro-RNA-181a at attomolar level in complex media using a nanophotonic biosensor. ACS Sens. 1, 748–756 (2016). \n48. Zhang, X., Liu, C., Sun, L., Duan, X. & Li, Z. Lab on a single microbead: an ultrasensitive detection strategy enabling microRNA analysis at the singlemolecule level. Chem. Sci. 6, 6213–6218 (2015). \n49. Neely, L. A. et al. A single-molecule method for the quantitation of microRNA gene expression. Nat. Methods 3, 41 (2005). \n50. Dai, Z. G. et al. Plasmon-driven reaction controlled by the number of graphene layers and localized surface plasmon distribution during optical excitation. Light Sci. Appl. 4, e342 (2015). \n51. Dai, Z. G. et al. In situ Raman scattering study on a controllable plasmondriven surface catalysis reaction on Ag nanoparticle arrays. Nanotechnology 23, 335701 (2012). \n52. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n53. Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comp. Mater. Sci. 6, 15–50 (1996). \n54. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n55. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n56. Klimeš, J., Bowler, D. R. & Michaelides, A. Van der Waals density functionals applied to solids. Phys. Rev. B 83, 195131 (2011). \n57. Mirkin, C. A., Letsinger, R. L., Mucic, R. C. & Storhoff, J. J. A DNA-based method for rationally assembling nanoparticles into macroscopic materials. Nature 382, 607 (1996). \n\n# Acknowledgements \n\nWe acknowledge support from the National Natural Science Foundation of China (51602305, 51571100, 61722403, 51601131 and 61875139), the Science and Technology Innovation Commission of Shenzhen (JCYJ20170818141429525, JCYJ20170818141407343, JCYJ20170818141519879), the China Postdoctoral Science Foundation (2018M633118, 2017M620383, 2018M633102, 2018M633127), the Shenzhen Nanshan District Pilotage Team Program (LHTD20170006) and ARC (IH150100006, FT150100450, and CE170100039). Q. Bao acknowledges support from the Australian Research Council (ARC) Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET). Calculations were performed in part at High Performance Computing Center of Jilin University. \n\n# Author contributions \n\nQ.B. and H.Z. conceived of the original concept. Q.B., H.Z., X.C. and L.Z. supervised the project. T.X. planned the project and performed most of the experiments. L.Z., Y.L. and Y.S. contributed to first-principles simulation. W.L., T.X. and K.Q. contributed to material preparations and characterizations. T.X., Y.X., and L.W contributed to the biosensing measurements. Z.D. and Y. Z. contributed to the FDTD measurements. T. X, B. S., Y. D., H. Z., X. C., L. Z. and Q. B. analyzed the data and co-wrote the paper. All authors discussed the results and commented on the manuscript. All authors have approved the final version of the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-07947-8. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1038_s41467-018-07951-y", + "DOI": "10.1038/s41467-018-07951-y", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-07951-y", + "Relative Dir Path": "mds/10.1038_s41467-018-07951-y", + "Article Title": "Highly stable and efficient all-inorganic lead-free perovskite solar cells with native-oxide passivation", + "Authors": "Chen, M; Ju, MG; Garces, HF; Carl, AD; Ono, LK; Hawash, Z; Zhang, Y; Shen, TY; Qi, YB; Grimm, RL; Pacifici, D; Zeng, XC; Zhou, YY; Padture, NP", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "There has been an urgent need to eliminate toxic lead from the prevailing halide perovskite solar cells (PSCs), but the current lead-free PSCs are still plagued with the critical issues of low efficiency and poor stability. This is primarily due to their inadequate photovoltaic properties and chemical stability. Herein we demonstrate the use of the lead-free, all-inorganic cesium tin-germanium triiodide (CsSn(0.5)Ge(0.5)l(3)) solid-solution perovskite as the light absorber in PSCs, delivering promising efficiency of up to 7.11%. More importantly, these PSCs show very high stability, with less than 10% decay in efficiency after 500 h of continuous operation in N-2 atmosphere under one-sun illumination. The key to this striking performance of these PSCs is the formation of a full-coverage, stable native-oxide layer, which fully encapsulates and passivates the perovskite surfaces. The native-oxide passivation approach reported here represents an alternate avenue for boosting the efficiency and stability of lead-free PSCs.", + "Times Cited, WoS Core": 629, + "Times Cited, All Databases": 690, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000454756600002", + "Markdown": "# Highly stable and efficient all-inorganic lead-free perovskite solar cells with native-oxide passivation \n\nMin Chen $\\textcircled{1}$ 1, Ming-Gang Ju $\\textcircled{1}$ 2, Hector F. Garces1, Alexander D. Carl3, Luis K. Ono4, Zafer Hawash $\\textcircled{1}$ 4, Yi Zhang1, Tianyi Shen1, Yabing Qi $\\textcircled{1}$ 4, Ronald L. Grimm3, Domenico Pacifici $\\textcircled{1}$ 1, Xiao Cheng Zeng $\\textcircled{1}$ 2, Yuanyuan Zhou1 & Nitin P. Padture $\\textcircled{1}$ 1 \n\nThere has been an urgent need to eliminate toxic lead from the prevailing halide perovskite solar cells (PSCs), but the current lead-free PSCs are still plagued with the critical issues of low efficiency and poor stability. This is primarily due to their inadequate photovoltaic properties and chemical stability. Herein we demonstrate the use of the lead-free, allinorganic cesium tin-germanium triiodide $(\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3})$ solid-solution perovskite as the light absorber in PSCs, delivering promising efficiency of up to $7.11\\%$ . More importantly, these PSCs show very high stability, with less than $10\\%$ decay in efficiency after $500\\mathsf{h}$ of continuous operation in ${\\sf N}_{2}$ atmosphere under one-sun illumination. The key to this striking performance of these PSCs is the formation of a full-coverage, stable native-oxide layer, which fully encapsulates and passivates the perovskite surfaces. The native-oxide passivation approach reported here represents an alternate avenue for boosting the efficiency and stability of lead-free PSCs. \n\nhe promise of high efficiency and low cost has been propelling perovskite solar cells (PSCs) research over the past decade or $\\mathbf{so}^{1-4}$ . While the record power conversion efficiency (PCE) of PSCs is now approaching $24\\%^{5}$ , rivaling that of silicon-based solar cells, the state-of-the-art PSCs employ leadbased organic–inorganic halide perovskite absorber materials. The toxicity of lead associated with the lifecycle of these PSCs is a serious concern, and it may prove to be a major hurdle in the path toward their commercialization $^{6-9}$ . Thus, significant effort is being devoted toward the development of low-cost, efficient leadfree PSCs. Several low-toxicity cations have been proposed for replacing $\\mathrm{Pb(II)}$ in halide perovskites, including $\\mathrm{\\hat{Ag}(I)^{10}}$ , Bi(III)11,12, ${\\mathrm{Sb}}({\\mathrm{III}})^{13}$ , $\\mathrm{Ti}(\\mathrm{IV})^{14,\\hat{1}5}$ , $G e(\\mathrm{II})^{16}$ , and $\\bar{\\mathrm{Sn}}(\\mathrm{II})^{17,18}$ Among these candidates, halide perovskites based on $\\mathrm{Sn(II)}$ have shown the highest PCE, and, thus, have attracted the most attention in the PSC field. Typical Sn-based halide perovskites that have been studied include $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{SnI}_{3}$ $\\begin{array}{r}{(\\mathrm{MASnI}_{3})}\\end{array}$ , $\\mathrm{HC(NH_{2})_{2}S n I_{3}}$ $\\left(\\mathrm{FASnI}_{3}\\right)$ , and $\\mathrm{CsSnI}_{3}$ . While PSCs based on $\\mathrm{MASnI}_{3}$ and $\\mathrm{FASnI}_{3}$ perovskites have been shown to deliver high PCE, up to $9\\%^{19}$ , these materials have intrinsically low stability20,21. This is primarily attributed to the presence of the organic cation, which is prone to facile volatilization. In this context, the all-inorganic lead-free $\\mathrm{CsSnI}_{3}$ perovskite becomes a more attractive candidate17,22. However, the facile oxidation of $\\mathrm{Sn(II)}$ to $\\operatorname{Sn}(\\operatorname{IV})$ , and attendant phase instability in the $\\mathrm{CsSnI}_{3}$ perovskite, results in the rapid degradation of its properties23. The most effective strategy that has been proposed for mitigating this issue is to incorporate $\\operatorname{Sn}(\\mathrm{II})$ -halide additive $(\\mathrm{SnF}_{2}^{24}$ , $\\mathrm{SnCl}_{2}{}^{2\\dot{5}}$ , and $\\mathrm{SnI}_{2}^{26}$ ), but the resulting PSCs show maximum PCE of only $4.81\\%$ , and no operational stability data on these PSCs has been reported. This calls for new stabilization approaches that can boost the stability and PCE of $\\mathrm{CsSnI}_{3}$ -based PSCs simultaneously. Herein, we report the surprising discovery that by simply alloying ${\\mathrm{Ge}}({\\mathrm{II}})$ in $\\mathrm{CsSnI}_{3}$ to form a $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ composition perovskite, its thin films can become highly stable and airtolerant. While the favorable Goldschmidt tolerance (0.94) and octahedral (0.4) factors in $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ contribute to the structural stability of this alloy (Supplementary Fig. 1), the extremely high oxidation activity of ${\\mathrm{Ge}}(\\mathrm{II})$ enables the rapid formation of an ultrathin $(<5\\mathrm{{nm})}$ uniform native-oxide surface passivating layer on the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite, imparting it with superior stability, even compared with the prototypical $\\operatorname{MAPbI}_{3}$ perovskite. We also demonstrate a facile one-step vaporprocessing method for the deposition of $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films, leading to PSCs with PCE up to $7.11\\%$ . We further show that these $\\bar{\\mathrm{Cs}}\\mathrm{Sn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ PSCs are highly stable upon continuous operation under 1-sun illumination for over $500\\mathrm{{h}}$ . The extraordinary stability of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite is explained using coupled experiments and theory. \n\n# Results \n\nSynthesis and processing of $\\mathbf{CsSn_{0.5}G e_{0.5}I_{3}}$ perovskites. Figure 1a is a photograph of $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite powder synthesized by solid-state reaction (at $450^{\\circ}\\mathrm{C})$ ) in an evacuated Pyrex glass tube. The indexed $\\mathrm{\\DeltaX}$ -ray diffraction pattern (XRD) in Supplementary Fig. 1a confirms that this powder is a single-phase perovskite, and it appears to crystallize in the space group of $R3m$ Its comparison with the XRD pattern of reference ${\\mathrm{CsGeI}}_{3}$ perovskite powder (space group $R3m$ ), synthesized using the same procedure, in Supplementary Fig. 1b shows peak shifts to lower $2\\theta$ angles. This indicates an expansion of the unit cell, as expected with the substitution of the smaller ${\\mathrm{Ge}}({\\mathrm{II}})$ by the larger $\\bar{\\mathrm{Sn}}(\\mathrm{II})$ Reference black phase B- $\\cdot\\gamma\\mathrm{-CsSnI}_{3}$ perovskite, which was also synthesized using the same procedure, crystallizes in the orthorhombic (space group Pnma) structure; Supplementary Fig. 1c shows its XRD pattern. (More detailed crystallographic analyses of $\\mathrm{CsSn}_{1-x}\\mathrm{Ge}_{x}\\mathrm{I}_{3}$ perovskite alloys will be studied in the future to resolve the symmetry transition with the increase of Ge content.) \n\nThe $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite powder was used to evaporate thin films onto various substrates, as shown schematically in Fig. 1b. Figure 1c is a photograph of such a film deposited on a $10\\times10{\\mathrm{-cm}}^{2}$ glass substrate showing dark reddish color. The XRD pattern in Fig. 1d confirms the single-phase nature of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin film (on a glass substrate). The inset within Fig. 1d shows scanning electron microscope (SEM) image of the top surface. SEM image of the cross section is presented in Supplementary Fig. 2a, where the typical film thickness is about $200\\mathrm{nm}$ , and the grain size is estimated at about $80\\mathrm{nm}$ . The films appear highly uniform, full-coverage, and ultrasmooth, where the root-mean-square roughness is found to be $2.1\\mathrm{nm}$ , as revealed in the atomic force microscope (AFM) image in Supplementary Fig. 2b. \n\nFigure 1e presents optical absorption and steady-state photoluminescence (PL) spectra of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin film. Good absorption is observed across the visible region, with an edge at about $840\\mathrm{nm}$ , although the estimated Urbach energy is relatively high $37\\mathrm{meV})$ , which could be related to the intrinsic Sn vacancies27,28. The PL emission peak is centered at about 830 nm, which is consistent with the absorption. The PL peak is relatively sharp $\\mathrm{(FWHM~}52\\mathrm{nm}$ ), a hallmark of a good lightabsorber material. The PL emission was also mapped over a $50\\times$ $50\\mathrm{-}\\upmu\\mathrm{m}^{2}$ area at various locations on the thin films (Supplementary Fig. 3), confirming the optical uniformity across the entire film. The Tauc plot of the thin films in Supplementary Fig. 4a indicates an optical bandgap of about $1.50\\mathrm{eV}$ , which is consistent with that predicted in our earlier computational studies29. This bandgap lies in-between the bandgaps of $\\mathrm{CsSnI}_{3}$ $(1.31\\mathrm{eV})$ and ${\\mathrm{CsGeI}}_{3}$ $(1.63\\mathrm{eV})$ perovskites, which is to be expected due to the upshift of the valence band maximum (VBM) with the substitution of $\\mathrm{Sn(II)}$ for ${\\mathrm{Ge}}({\\mathrm{II}})$ in ${\\mathrm{CsGeI}}_{3}$ . Supplementary Fig. 4b plots the real and the imaginary parts of the refractive index of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films as a function of the wavelength. \n\nNative-oxide surface passivation in $\\mathbf{CsSn_{0.5}G e_{0.5}I_{3}}$ perovskite. As soon as the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films are exposed to air, a stable native-oxide layer forms on the surface, within $30\\mathrm{{s}}$ . Figure 2a plots Ge 3d X-ray photoelectron spectroscopy (XPS) spectra at different incidence angles. At shallow angles, the presence of ${\\mathrm{Ge}}({\\mathrm{IV}})$ is detected (binding energy $33.0\\mathrm{eV},$ . Since the surface roughness is about $2.1\\mathrm{nm}$ and the native-oxide layer is expected to be less than $5\\mathrm{-nm}$ thick, the surface layer is sampled primarily at such shallow angles. With increasing incidence angle, the $G e(\\mathrm{II})$ peak (binding energy $31.0\\mathrm{eV})$ dominates, as the underlying $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin film is sampled primarily. These spectra are deconvoluted, and the estimated ${\\mathrm{Ge}}({\\mathrm{II}})$ content (relative to total Ge) is plotted in Fig. 2b. A sharp drop in the ${\\mathrm{Ge}}({\\mathrm{II}})$ content at incidence angles 30 to $45^{\\circ}$ indicates a distinct native-oxide layer comprising ${\\cal G e}(\\mathrm{IV})$ primarily. XPS maps (normal incidence angle) of Ge 3d $(33.0\\mathrm{eV})$ and $\\mathrm{~O~}$ 1s $(532.0\\mathrm{eV})$ in Fig. 2c, d, respectively, of the same surface region show a strong correlation30,31, confirming the formation of a Ge(IV)-rich native oxide. Supplementary Fig. 5a plots Sn 3d XPS spectra as a function of incidence angle. Since the binding energies for $\\mathrm{Sn(II)}$ $(486.0\\ \\mathrm{eV})$ and Sn(IV) $\\cdot486.6\\ \\mathrm{eV})$ are very close, it is difficult to discern the oxidation state of Sn. Nevertheless, the $S\\mathrm{n:Ge}$ atomic ratio is extracted from the data in Supplementary Fig. 5a and Fig. 2a, and it is plotted in Supplementary Fig. 5b as a function of incidence angle. It can be seen that there is a small amount $(<10\\%)$ of Sn present in the native oxide. In a related experiment, \n\n![](images/b1eb1502c3eae621eb56ef3f13dfcffd8fdd89107db4dd548d1a4eb08ac70cd8.jpg) \nFig. 1 Film synthesis and characterization. a Photograph of as-synthesized $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3}$ perovskite solid using the melt-crystallization method. b Schematic illustration of the single-source evaporation method for the deposition of ultrasmooth $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3}$ perovskite thin film. c Photograph of an as-synthesized large-area $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3}$ perovskite thin film on a glass substrate showing dark reddish color. d Indexed XRD pattern of the fresh CsSn0.5Ge0.5I3 perovskite thin film (inset: top-view SEM image of the microstructure). e Absorption and steady-state PL spectra of a fresh $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3}$ perovskite thin film \n\n![](images/1b20eb3d22a5ca3d121037285fa3709eb7f9ef87e2572f6c4dca5c6f6f97f7e8.jpg) \nFig. 2 XPS characterization. a Ge 3d XPS spectra, at different incidence angles, from $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3}$ perovskite thin film that has been exposed to air. b Corresponding plot of the fraction of Ge(II) vs. the incidence angle. c, d XPS maps of Ge 3d (33 eV) and O 1s $(532\\mathrm{eV})$ , respectively, from the same are of the thin film \n\n![](images/ca3bc4a77071eb80b12f64f862e70f4b647f1786c20a0c1b3f10b6f79be8c75d.jpg) \nFig. 3 Thin-film stability. XRD patterns of perovskite thin films before and after exposure for 24, 48, and $72\\mathrm{~h~}$ to light-soaking (1 sun) at approximately $45^{\\circ}C$ and $80\\%$ RH: a $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3},$ b $\\cos\\S_{n}\\vert_{3},$ c $\\mathsf{C s P b l}_{3},$ and d $M A P b|_{3}$ . e Plots of relative XRD peak intensities vs. time from a to d \n\nAr sputtering $(15~\\mathrm{{s})}$ was utilized in situ to remove the nativeoxide layer at the surface. The XPS results ( $15^{\\circ}$ incidence angle) after Ar sputtering (Supplementary Figs. 6a and 6b) show ${\\mathrm{Ge}}(\\mathrm{II})$ - rich and O-lean surface corresponding to the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite, which confirms that the thickness of the oxide layer is within $5\\mathrm{nm}$ . Taken together, the XPS results indicate that a uniform layer of Sn-containing ${\\mathrm{Ge}}({\\mathrm{IV}})$ -rich native oxide $(<5\\mathrm{{nm})}$ forms on the surface of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films. As with most native-oxide layers that are less than $5\\ \\mathrm{nm}$ in thickness, this native-oxide layer is expected to be amorphous. \n\nNative oxide passivated $\\mathbf{CsSn_{0.5}G e_{0.5}I_{3}}$ perovskite stability. The as-synthesized $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite powders when exposed to ambient atmosphere $25^{\\circ}\\mathrm{C}$ , $80\\%$ RH) for $24\\mathrm{h}$ remain black and maintain their phase purity (Supplementary Fig. 1d). Moreover, it appears that the $\\mathrm{CsSn}_{x}\\mathrm{Ge}_{1-x}\\mathrm{I}_{3}$ perovskite can become quite stable when the $x$ value is in the range of 0.25–0.75 (Supplementary Fig. 8). In contrast, reference pure $\\mathrm{CsSnI}_{3}$ and ${\\mathrm{CsGeI}}_{3}$ powders turn into yellow non-perovskite phases (Supplementary Fig. 1f and 1e). These results demonstrate clearly the superior air stability of the alloy $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite over its pure components. The $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films subjected to continuous 1-sun illumination in ambient atmosphere 1 ${\\sim}45^{\\circ}\\mathrm{C},$ $80\\%$ RH) for up to $^{72\\mathrm{h}}$ are also found to be highly stable. Figure 3a presents XRD patterns from $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films exposed for 0, 24, 48, and $^{72\\mathrm{h}}$ showing negligible change. The corresponding relative intensities of the main XRD peak are plotted in Fig. 3e. Comparative experiments on thin films of the popular halide perovskites $\\mathrm{\\Cs{SnI}}_{3}$ , $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{I}}_{3}$ , and $\\mathrm{MAPbI}_{3}$ ) show complete degradation after 24, 48, and $72\\mathrm{{h}}$ , respectively (Fig. 3b–d). Supplementary Fig. 9 presents conductive AFM (c-AFM) images of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin film samples exposed to ambient atmosphere for 0, 24, and $48\\mathrm{{h}}$ , where the microstructure and conductivity appear unchanged at the nanoscale. \n\nPhysical properties of $\\mathbf{CsSn_{0.5}G e_{0.5}I_{3}}$ perovskite thin films. The time-resolved PL (TRPL) spectroscopy data from $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films (on glass substrates) in Supplementary Fig. 10a reveal a promising lifetime of 10.92 ns, compared with only 510 ps for the reference $\\mathrm{CsSnI}_{3}$ thin film. Supplementary Fig. 10b shows TRPL results for $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films coated with either phenyl- $C_{61}$ -butyric acid methyl ester: ${\\mathrm{:C}}_{60}$ $(\\mathrm{PCBM:C_{60}})$ or spiro-OMeTAD as electron- or hole-quenching layers, respectively. Based on the PL decay dynamics, the photogenerated carrier diffusion coefficients are estimated at 0.85 $\\mathrm{cm}^{2}\\ s^{-1}$ and $0.39\\ \\mathrm{cm}^{2}\\ \\mathrm{s}^{-1}$ for electrons and holes14,32, respectively. These correspond to diffusion lengths of $963~\\mathrm{nm}$ and 653 nm for electrons and holes, respectively, which are sufficiently long for planar thin-film solar cells. \n\nThe carrier mobilities in the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films were determined by the space-charge-limited-current (SCLC) method using symmetric capacitor-like devices shown schematically in Supplementary Fig. 11a and 11b insets. For determining the electron mobility $(\\mu_{\\mathrm{e}})$ and the hole mobility $(\\mu_{\\mathrm{h}})$ in the dark, the $\\mathrm{Ga/PCBM:C_{60}/C s S n_{0.5}G e_{0.5}I_{3}/P C B M:C_{60}/G a}$ and the Au/spiro-OMeTAD/ $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3},$ /spiro-OMeTAD/Au device structures, respectively, were used, in conjunction with the following equation:33 \n\n$$\nJ_{\\mathrm{SCL}}={\\frac{9\\varepsilon\\varepsilon_{0}\\mu V^{2}}{8L^{3}}}\n$$ \n\nHere, $J_{\\mathrm{SCL}}$ is the measured current density, $L$ is the film thickness $(=1\\upmu\\mathrm{m})$ , $\\mu$ is the carrier mobility, ε is the dielectric constant $\\scriptstyle(=28)$ , and $\\scriptstyle{\\varepsilon_{\\mathrm{o}}}$ is the permittivity of free space. The $\\mu_{\\mathrm{e}}$ and $\\mu_{\\mathrm{h}}$ are estimated at $974\\ \\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ and $213\\mathrm{cm\\bar{^{2}}V^{-1}\\thinspace s^{-1}}$ , respectively, where the latter is consistent with the $\\mu_{\\mathrm{h}}$ value of $298\\thinspace\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\thinspace s^{-1}$ determined using the Hall-effect measurements. The electron- and hole-trap densities $(n_{\\mathrm{t}})$ were calculated using \n\n![](images/591ae45c113f9280885025a4fbfdfbfa5db0b8786d7f4a382ec3d10ac971e466.jpg) \nFig. 4 Device architecture and performance of $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3}$ thin-film PSCs. a Schematic illustration showing the planar PSC device structure used here. b Corresponding energy-level diagram. c $J-V$ responses of the “champion” PSC device. d PCE statistics. e Stabilized power output and f EQE spectrum of the “champion” PSC device \n\nthe following equation:34,35 \n\n$$\nn_{\\mathrm{t}}=\\frac{V_{\\mathrm{TFL}}2\\varepsilon\\varepsilon_{0}}{e L^{2}}\n$$ \n\nwhere $V_{\\mathrm{TFL}}$ is the trap-filled limit (TFL) voltage from the plots in Supplementary Fig. 11a and 11b; the electron- and hole-trap densities are estimated to be both as low as about $10^{16}~\\mathrm{cm}^{-3}$ . All of the above results indicate that the properties of $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films are highly suitable for thin-film planar solar cells. \n\nNative-oxide-passivated $\\mathbf{CsSn_{0.5}G e_{0.5}I_{3}}$ perovskite solar cells. The PV performance of $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films with the native-oxide layer is evaluated by incorporating them into PSC devices of the architecture shown in Fig. 4a. The $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin film (about $200\\mathrm{-nm}$ thickness) is sandwiched between PCBM electron-transport layer (ETL) and spiro-OMeTAD hole-transport layer (HTL), with the thin nativeoxide layer serving as a wide-bandgap interfacial layer between the $\\mathrm{Cs}\\mathrm{Sn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin film and the HTL. FTO and Au are used as the conducting electrodes. Figure 4b shows the energy-level diagrams for this device architecture. The VBM and the apparent bandgap of the amorphous native oxide were determined using the ultraviolet photoemission spectroscopy (UPS) results presented in Supplementary Fig. 12. The VBM of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ thin film is determined by performing UPS measurement after the removal of the native-oxide layer using Ar sputtering (Supplementary Fig. 13). Figure 4c plots the current density $(J)$ –voltage $(V)$ responses of the “champion” PSC in reverse and forward scans, showing negligible hysteresis. High overall PCE of $7.11\\%$ is achieved with open-circuit voltage $(V_{\\mathrm{OC}})$ \n\n![](images/a6a16dc47e4a55bed6b70ad84b4af3eb31c26dc2d4094a9e8b5eab074b15bcf4.jpg) \nFig. 5 Device stability of $\\mathsf{C s S n}_{0.5}\\mathsf{G e}_{0.5}|_{3}$ thin-film PSCs. a PCE evolution of a typical unencapsulated PSC in continuous operation under 1-sun illumination at $45^{\\circ}C$ in ${\\sf N}_{2}$ atmosphere. b Initial $J-V$ curves (reverse and forward scans) of the PSC and ones at the $500-11$ mark during continuous operation \n\nof $0.63\\mathrm{~V~}$ , short-circuit current density $(J_{\\mathrm{SC}})$ of $18.61\\mathrm{\\mA\\cm^{-2}}$ , and fill factor (FF) of 0.606. The $J_{\\mathrm{SC}}$ value is consistent with the integrated $J$ of $18.1\\mathrm{\\mA}\\ \\mathrm{cm}^{-2}$ from the external quantum efficiency (EQE) spectrum in Fig. 4f. The PCE output at the maximum power point $(0.45{\\mathrm{V}})$ shows $7.03\\%$ in Fig. 4e, which is very close to the extracted PCE from $J{-}V$ curves. The $V_{\\mathrm{OC}}$ reported here is much higher than that in other reported PSCs based on all-inorganic Sn-based halide perovskites26,36, and it appears to be stable (Supplementary Fig. 14). The evaluation of PV performance of about 40 PSC devices shows good reproducibility (Fig. 4d), with average PCE of $6.48\\%$ . More detailed performance statistics are included in Supplementary Fig. 15, and the device performance parameters are included in Supplementary Table 1. \n\nIn order to study the effect of the native-oxide layer on the PSC performance, control PSCs based on $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films, without the native oxide, were also fabricated. This was accomplished by performing all the processing steps inside a ${\\Nu}_{2}$ - filled glovebox $\\mathrm{\\mathrm{~\\cal~O~}}_{2}$ and $_\\mathrm{H}_{2}\\mathrm{O}$ levels below $0.1\\ \\mathrm{ppm},$ ). Note that the processing of the PSCs described earlier was performed outside of the glovebox. The control PSC shows much lower $V_{\\mathrm{OC}}$ of $0.48\\mathrm{V}$ (reverse scan) and PCE of $3.72\\%$ (Supplementary Fig. 16a). By comparison, a PSC with the native-oxide layer shows significantly higher $V_{\\mathrm{OC}}$ of $_{0.62\\mathrm{~\\textit~{~V~}~}}$ (reverse scan) and PCE of $6.52\\%$ (Supplementary Fig. 16b). Also, a control PSC based on $\\mathrm{CsSnI}_{3}$ perovskite was fabricated using the same evaporation method, showing low PCE of $1.7\\%$ (Supplementary Fig. 17). This clearly demonstrates the advantage of the mixed $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite composition, and the beneficial effect of the native oxide. The corresponding dark $J{-}V$ responses are also plotted in Supplementary Figs. 16a and 16b, showing lower current leakage when the native-oxide layer is present. \n\nLong-term device stability. A typical unencapsulated $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ thin-film PSC with $6.79\\%$ PCE (Fig. 5b) was chosen for stability testing where it was operated continuously under continuous 1-sun illumination in $\\Nu_{2}$ atmosphere $(45^{\\circ}\\mathrm{C})$ . The continuous monitoring of the PV performance shows that the PCE has degraded to only $6.23\\%$ $92\\%$ of the initial PCE) after $500\\mathrm{{h}}$ of continuous operation (Fig. 5a, b). Figure 5b also shows that there is no degradation in the $V_{\\mathrm{OC}}$ . This demonstrates clearly the excellent operational stability of PSCs based on $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films with the native-oxide layer. Regarding the stability in air, we have periodically measured the $J{-}V$ performance of a $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ -based PSC that was stored under 1-sun illumination. As shown in Supplementary Fig. 18, after $100\\mathrm{-h}$ storage, the PSC promisingly maintains $91\\%$ of the initial PCE. Overall, to the best of our knowledge, such stability is the highest of all lead-free perovskite PSCs reported so far. Note that, while it is practically challenging to perform a direct performance comparison between the $\\bar{\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}}$ -based and $\\mathrm{\\DeltaPb}$ -based PSCs with the same device configuration, the stability of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ -based PSCs is reasonably comparable to that of $\\mathrm{Pb}$ -based $\\mathrm{PSC}s^{5,37}$ . \n\n# Discussion \n\nWe have shown that thin-film PSCs based on all-inorganic, Pbfree perovskites of composition $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ show superior performance and exceptional stability. The air stability of $\\mathrm{\\bar{C}s S n}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite over its pure counterparts $\\mathrm{CsSnI}_{3}^{\\cdot}$ and ${\\mathrm{CsGeI}}_{3}$ is attributed to the formation of the passivating, stable native-oxide layer on $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite surfaces when exposed to air. As gleaned from the XPS results, the native oxide on $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films comprises ${\\mathrm{GeO}}_{2}$ doped with a small portion of $\\scriptstyle\\mathrm{Sn}$ . It may be that $\\scriptstyle\\mathrm{Sn}$ doping suppresses the formation of those volatile, unstable Ge suboxides during surface passivation in air38,39. It is likely that the Sn-doping also enhances the moisture stability of ${\\mathrm{GeO}}_{2}$ itself, making the passivation layer stable in air. Further studies will be performed to understanding the details of Sn-doping effects. Also, as shown in Supplementary Fig. 7, the entropy-of-mixing contributes to $0.03~\\mathrm{eV}$ $(1.2k_{\\mathrm{B}}T$ at room temperature, $k_{\\mathrm{B}}$ is the Boltzmann constant and $T$ is $300~\\mathrm{K}$ ) in reduced free energy in the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite, adding to its thermodynamic stability. \n\nIt is confirmed that the presence of the native-oxide layer on $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films is also important for the enhanced PV performance (Supplementary Fig. 16). This can be attributed to the suppression of recombination of photocarriers at the interface between the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite and the HTL where the native oxide resides. Also, the dark $J{-}V$ results in Supplementary Figure 16 indicate improved hole transport across that interface and enhanced shunt resistance, resulting in the enhanced PV performance. The remarkable operational stability of the PV performance is again attributed to the passivating nature of the $\\scriptstyle\\mathrm{Sn}$ -containing ${\\mathrm{GeO}}_{2}$ native-oxide layer that protects the thin-film surfaces and interfaces, and also the enhanced intrinsic or thermodynamic stability of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite. \n\nThe $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite composition studied here demonstrates the “proof-of-concept” of the efficacy of the nativeoxide approach in stabilizing materials and devices. Currently, we have relied on the native oxide that forms naturally upon exposure to air, which may not be optimum. Thus, an investigation where the native oxide is tailored via controlled heat treatments (temperature, time, and oxygen partial pressure) is likely to be a fruitful research direction. Tuning the electrical and chemical properties of native oxide, and also exploring other ETL, HTL, and electrode materials with energy levels better suited for the cesium tin-germanium triiodide alloy perovskites, may result in PSCs with further enhanced performance. Finally, the nativeoxide approach demonstrated for achieving enhanced PV performance and operational stability could be extended rationally to other halide-perovskite compositions. \n\n# Methods \n\nSynthesis of $\\cos\\sin_{0.5}\\mathsf{G e}_{0.5}\\mathsf{l}_{3}$ raw powders and films. All raw materials were purchased from Sigma Aldrich (USA) and used without further purification. $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite powder was synthesized by solid-state reaction between mixed solid powder precursors ${\\mathrm{CsI}}{:}{\\mathrm{SnI}}_{2}{:}{\\mathrm{GeI}}_{2}$ (2:1:1 molar ratio) carried out in evacuated Pyrex tubes. The tubes were evacuated to $10^{-3}$ Torr pressure for at least 6 h before sealing them using an oxy-methane torch under vacuum. The evacuated tubes with the powder mixture were then placed in a tube furnace and heated to $450^{\\circ}\\mathrm{C}$ and held for $^{72\\mathrm{h},}$ followed by slow cooling at a rate of $20^{\\circ}\\mathrm{C}\\mathrm{h}^{-1}$ to room temperature. The as-synthesized $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite powder was evaporated to deposit thin films of the same composition on various substrates using a thermal evaporator (Edwards/306A; UK). The deposition was carried out at $10^{-5}$ Torr under low current settings of 36 to $42~\\mathrm{mA}$ . \n\nMaterials characterization. XRD of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite powders and thin films (on glass substrate) was performed using a high-resolution diffractometer (D8 Advance, Bruker; Germany) with $\\mathrm{CuK}_{\\mathrm{a}}$ radiation. UV-vis spectra were obtained using a spectrophotometer (UV-2600, Shimadzu; Japan). The microstructures of the thin films were observed using a SEM (LEO 1530VP, Carl Zeiss; Germany). Hall-effect measurements were conducted on a device with fourGa electrode system (2400 SourceMeter, Keithley; USA). The majority carrier was determined to be holes based on the Hall-voltage sign. An XPS and UPS system (5600, PHI; USA) was used to acquire both angle-dependent XPS and UPS spectra. The analysis chamber base pressure was $<10^{-5}$ Torr prior to analysis. The instrument utilized a monochromated Al- $\\cdot\\operatorname{K}_{\\alpha}$ source for X-ray radiation at 1486.7 eV, and a UVS 40A2 (PREVAC, Poland) UV source and UV40A power supply provided by He $1_{\\mathrm{a}}$ for UPS at $21.22\\mathrm{eV}$ . Chamber pressure for UPS was maintained at less than $3\\times10^{-8}$ Torr. XPS data were collected at different incidence angles. In some cases, in situ Ar sputtering (15 s) was used to etch away the surface layer. XPS mapping was performed on another XPS system (AXIS ULTRA HAS, Kratos Analytical; UK). The determination for the ratio of valence states and atom ratios was performed by Casa XPS (2.3.19) and Origin. The measurement conditions were $150~\\mathrm{W}$ of applied power to the X-ray source under ultrahigh vacuum $\\cdot10^{-9}$ Torr). The images were collected using field of view $(200\\times\\bar{2}00\\upmu\\mathrm{m}^{2})$ with the high-resolution imaging Iris $(<3\\upmu\\mathrm{m})$ . The binding energies of the elements of interest for generating the maps were first defined by acquiring the XPS spectra. Acquisition time for each elemental mapping was $2\\mathrm{min}$ . The SCLC $I{-}V$ curves were measured using the 2400 SourceMeter (Keithley; USA). Thicker films $(1\\upmu\\mathrm m)$ are used here to eliminate current leakage. However, it should be noted that thicker films may amplify the mobility and lower the trap density. The refractive indices of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films were measured using an ellipsometer (M7000, J.A. Woollam; USA) at an incidence angle of $75^{\\circ}$ . The dielectric constant (ε) was accordingly calculated from electrical capacity test. The steady-state and timeresolved PL spectra were recorded using a spectrophotometer (Varian Cary Eclipse Fluorescence, Agilent; USA) operated at $395\\mathrm{-nm}$ excitation. The decay rate and lifetime were determined using the three-parameter decay function fitting method. \n\nDevice fabrication and testing. Patterned FTO-coated glass (Hartford Glass Co.; USA) substrates were cleaned successively with detergent solution, acetone, and isopropanol, and they were UV-ozone treated for $20\\mathrm{min}$ prior to the deposition of the other layers. A less than 20-nm PCBM layer using a $20\\mathrm{{mg}\\ m L^{-1}}$ solution of PCBM in 1,2-dichlorobenzene was spin-coated (3000 rpm, 60 s). $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films were then deposited using the method described above. The HTL solution was prepared by dissolving $91\\mathrm{mg}$ of spiro-OMeTAD (Merck, Germany) with additives in $1~\\mathrm{mL}$ of chlorobenzene. The additives were $21\\upmu\\mathrm{L}$ of Li-bis (trifluoromethanesulfonyl) imide from the stock solution ( $520~\\mathrm{mg}$ in $1\\mathrm{mL}$ of acetonitrile), $16\\upmu\\mathrm{L}$ of FK209 (tris(2-(1H-pyrazol-1-yl)-4-tert-butylpyridine)-cobalt (III) tris(bis(trifluoromethylsulfonyl) imide) ( $375\\mathrm{mg}$ in $1\\mathrm{mL}$ of acetonitrile), and $36\\upmu\\mathrm{L}$ of 4-tertbutylpyridine. The HTL solution was spin-coated $(4000\\mathrm{rpm},20\\mathrm{s})$ ), followed by the deposition of the 80-nm-thick Au electrode by thermal evaporation. Control PSCs were also fabricated, where all the deposition steps were conducted in a $\\Nu_{2}$ -filled glovebox $\\mathrm{\\mathrm{~\\textO}}_{2}$ and $\\mathrm{H}_{2}\\mathrm{O}$ levels ${<}0.1\\ \\mathrm{ppm})$ ) to prevent the formation of the native oxide on the surface of the $\\mathrm{CsSn}_{0.5}\\mathrm{Ge}_{0.5}\\mathrm{I}_{3}$ perovskite thin films. The $J{-}V$ characteristics of all the PSCs were measured using the 2400 SourceMeter under simulated 1-sun AM1.5G $100\\mathrm{\\mA}{\\cdot}\\mathrm{cm}^{-2}$ intensity (Sol3A Class AAA, Oriel, Newport; USA) in ambient atmosphere, using both reverse (from $V_{\\mathrm{OC}}$ to $J_{\\mathrm{SC}})$ ) and forward (from $J_{\\mathrm{SC}}$ to $V_{\\mathrm{OC}})$ scans with a step size of $0.015\\mathrm{V}$ and a delay time of $100~\\mathrm{{ms}}$ . The maximum-power output stability of PSCs was measured by monitoring the $J$ output at the maximum power-point bias (deduced from the reverse-scan $J{-}V$ curves) using the 2400 SourceMeter. A typical active area of 0.1 $\\mathrm{cm}^{2}$ was defined using a non-reflective mask for the $J{-}V$ measurements. The stable output PCE was calculated using the following relation: $\\scriptstyle\\mathrm{PCE}=J(\\mathrm{mA}\\mathrm{cm}^{-2})\\times V(\\mathrm{V})I$ 100 $\\mathrm{(mA~V~cm^{-2}}$ ). A shutter was used to control the 1-sun illumination on the PSC. The EQE spectra were obtained using a quantum efficiency measurement system (IQE 200B, Oriel; USA). For long-term device stability test, the PSCs were placed in a holder with a transparent-glass cover and a continuous flow of nitrogen gas. The current/PCE outputs of PSCs at the maximum-power point were monitored under continuous 1-sun-intensity (white-LED) illumination. \n\nDFT calculations. All first-principles computations were performed based on density-functional theory (DFT) methods as implemented in the Vienna ab initio simulation package (VASP 5.4). An energy cutoff of $520\\mathrm{eV}$ was employed, and the atomic positions were optimized using PBEsol functional until the maximum force on each atom was less than $0.02\\mathrm{eV}{\\cdot}\\mathring{\\mathrm{A}}^{-1}$ . The ion cores were described by using the projector-augmented wave (PAW) method. A $4\\times4\\times4~k$ -point grid was used for the mixed perovskites. The simulation cells of mixed perovskites with different stoichiometry containing eight units were constructed by replacing the corresponding $\\operatorname{Sn}(\\operatorname{II})$ or Ge(II). For each composition, the geometry and cell length were then fully relaxed. This justifies the estimation of the entropy-of-mixing contribution to the free energy by using the analytical formula for ideal alloys: $T\\Delta S=-k_{\\mathrm{B}}T[x\\mathrm{ln}x+(1-x)\\mathrm{ln}(1-x)]$ . The mixed energy contributions to the free energy can also be estimated based on the formula: $\\Delta E_{\\mathrm{mixed}}=E_{\\mathrm{CsSn}_{x}\\mathrm{Ge}_{(1-x)}\\mathrm{I}_{3}}-(x E_{\\mathrm{CsSnI}_{3}}+(1-x)E_{\\mathrm{CsGeI}_{3}})$ \n\n# Data availability \n\nThe authors declare that the data related to this study are available upon reasonable request. \n\nReceived: 14 August 2018 Accepted: 28 November 2018 \nPublished online: 03 January 2019 \n\n# References \n\n1. Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visiblelLight sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n2. Kim, H.-S. et al. Lead iodide perovskite sensitized all-solid-state submicron thin film mesoscopic solar cell with efficiency exceeding $9\\%$ . Sci. Rep. 2, 591 (2012). \n3. Lee, M. M., Teuscher, J., Miyasaka, T., Murakami, T. N. & Snaith, H. J. Efficient hybrid solar cells based on meso-superstructured organometal halide perovskites. Science 338, 643–647 (2012). \n4. Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897 (2014). \n5. Jeon, N. J. et al. A fluorene-terminated hole-transporting material for highly efficient and stable perovskite solar cells. Nat. Energy 3, 682–689 (2018). \n6. Green, M. A., Ho-Baillie, A. & Snaith, H. J. The emergence of perovskite solar cells. Nat. Photon. 8, 506 (2014). \n7. Grätzel, M. The light and shade of perovskite solar cells. Nat. Mater. 13, 838 (2014). \n8. Ju, M. G. et al. Toward eco-friendly and stable perovskite materials for photovoltaics. Joule 2, 1231–1241 (2018). \n9. Zong, Y. et al. Continuous grain-boundary functionalization for highefficiency perovskite solar cells with exceptional stability. Chem 4, 1404–1415 (2018). \n10. Du, K. Z., Meng, W., Wang, X., Yan, Y. & Mitzi, D. B. Bandgap engineering of lead-free double perovskite $\\mathrm{Cs}_{2}\\mathrm{AgBiBr}_{6}$ through trivalent metal alloying. Angew. Chem. Int. Ed. 56, 8158–8162 (2017). \n11. Zhang, Z. et al. High-quality $(\\mathrm{CH}_{3}\\mathrm{NH}_{3})_{3}\\mathrm{Bi}_{2}\\mathrm{I}_{9}$ film-based solar cells: pushing efficiency up to $1.64\\%$ . J. Phys. Chem. Lett. 8, 4300–4307 (2017). \n12. Wang M. et al. High-quality sequential-vapor-deposited $\\mathrm{Cs}_{2}\\mathrm{AgBiBr}_{6}$ thin films for lead-free perovskite solar cells. Solar RRL 2, 1800217 (2018). \n13. Zuo, C. & Ding, L. Lead-free perovskite materials $(\\mathrm{NH_{4}})_{3}\\mathrm{Sb_{2}I_{x}B r_{9-x}}$ . Angew. Chem. Int. Ed. 56, 6528–6532 (2017). \n14. Chen, M. et al. Cesium titanium(IV) bromide thin films based stable lead-free perovskite solar cells. Joule 2, 558–570 (2018). \n15. Ju, M. G. et al. Earth-abundant nontoxic titanium(IV)-based vacancy-ordered double perovskite halides with tunable 1.0 to $1.8\\:\\mathrm{eV}$ bandgaps for photovoltaic applications. ACS Energy Lett. 3, 297–304 (2018). \n16. Krishnamoorthy, T. et al. Lead-free germanium iodide perovskite materials for photovoltaic applications. J. Mater. Chem. A 3, 23829–23832 (2015). \n17. Wang, N. et al. Heterojunction-depleted lead-free perovskite solar cells with coarse-grained B-γ-CsSnI3thin films. Adv. Energy Mater. 6, 1601130 (2016). \n18. Hao, F., Stoumpos, C. C., Cao, D. H., Chang, R. P. H. & Kanatzidis, M. G. Lead-free solid-state organic–inorganic halide perovskite solar cells. Nat. Photon. 8, 489 (2014). \n19. Shao, S. et al. Highly reproducible Sn-based hybrid perovskite solar cells with $9\\%$ efficiency. Adv. Energy Mater. 8, 1702019 (2018). \n20. Dang, Y. et al. Formation of hybrid perovskite tin iodide single crystals by topseeded solution growth. Angew. Chem. Int. Ed. 55, 3447–3450 (2016). \n21. Zhou, Y. et al. Doping and alloying for improved perovskite solar cells. J. Mater. Chem. A 4, 17623–17635 (2016). \n22. Wu, B. et al. Long minority-carrier diffusion length and low surfacerecombination velocity in inorganic lead-free $\\mathrm{CsSnI}_{3}$ perovskite crystal for solar cells. Adv. Funct. Mater. 27, 1604818 (2017). \n23. Chung, I. et al. $\\mathrm{CsSnI}_{3}$ : Semiconductor or metal? High electrical conductivity and strong near-infrared photoluminescence from a single material. High hole mobility and phase-transitions. J. Am. Chem. Soc. 134, 8579–8587 (2012). \n24. Lee, S. J. et al. Fabrication of efficient formamidinium tin iodide perovskite solar cells through $\\mathrm{SnF}_{2}$ -pyrazine complex. J. Am. Chem. Soc. 138, 3974–3977 (2016). \n25. Marshall, K. P., Walker, M., Walton, R. I. & Hatton, R. A. Enhanced stability and efficiency in hole-transport-layer-free $\\mathrm{CsSnI}_{3}$ perovskite photovoltaics. Nat. Ener. 1, 16178 (2016). \n26. Song, T.-B., Yokoyama, T., Aramaki, S. & Kanatzidis, M. G. Performance enhancement of lead-free tin-based perovskite solar cells with reducing atmosphere-assisted dispersible additive. ACS Energy Lett. 2, 897–903 (2017). \n27. Zong, Y. et al. Homogenous alloys of formamidinium lead triiodide and cesium tin triiodide for efficient ideal-bandgap perovskite solar cells. Angew. Chem. Int. Ed. 56, 12658–12662 (2017). \n28. Sabba, D. et al. Impact of anionic $\\mathrm{Br^{-}}$ substitution on open circuit voltage in lead-free perovskite $(\\mathrm{CsSnI_{3-x}B r_{x}})$ solar cells. J. Phys. Chem. C. 119, 1763–1767 (2015). \n29. Ju, M. G., Dai, J., Ma, L. & Zeng, X. C. Lead-free mixed tin and germanium perovskites for photovoltaic application. J. Am. Chem. Soc. 139, 8038–8043 (2017). \n30. Ito, N. et al. Mixed Sn–Ge perovskite for enhanced perovskite solar cell performance in air. J. Phys. Chem. Lett. 9, 1682–1688 (2018). \n31. Nagane, S. et al. Lead-free perovskite semiconductors based on germanium–tin solid solutions: structural and optoelectronic properties. J. Phys. Chem. C. 122, 5940–5947 (2018). \n32. Chen, M. et al. Light-driven overall water-splitting enabled by a photoDember effect realized on 3D plasmonic structures. ACS Nano 10, 6693–6701 (2016). \n33. Mihailetchi, V. D., Wildeman, J. & Blom, P. W. M. Space-charge limited photocurrent. Phys. Rev. Lett. 94, 126602 (2005). \n34. Dong, Q. et al. Electron-hole diffusion lengths ${>}175~{\\upmu}\\mathrm{m}$ in solution-grown CH3NH3PbI3 single crystals. Science 347, 967–970 (2015). \n35. Shi, D. et al. Low trap-state density and long carrier diffusion in organolead trihalide perovskite single crystals. Science 347, 519–522 (2015). \n36. Song, T.-B. et al. Importance of reducing vapor atmosphere in the fabrication of tin-based perovskite solar cells. J. Am. Chem. Soc. 139, 836–842 (2017). \n37. Saliba, M. et al. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). \n38. Huang, Z. et al. Suppressing the formation of $\\mathrm{GeO_{x}}$ by doping Sn into Ge to modulate the Schottky barrier height of metal/n-Ge contact. Appl. Phys. Exp. \n9, 021301 (2016). \n39. Wu, Y. H. et al. Comparison of Ge surface passivation between $\\mathrm{SnGeO_{x}}$ films formed by oxidation of $\\mathrm{Sn/Ge}$ and $\\mathrm{SnGe_{x}/G e}$ structures. IEEE Electr. Device Lett. 32, 611–613 (2011). \n\n# Acknowledgements \n\nThe work at Brown University and University of Nebraska–Lincoln (UNL) was funded by the US National Science Foundation (OIA-1538893). Computations were performed at UNL Holland Computing Center. L.K.O., Z.H., and Y.B.Q. acknowledge the funding support from the Energy Materials and Surface Sciences Unit of the Okinawa Institute of Science and Technology Graduate University, the OIST Proof of Concept (POC) Program, the OIST R&D Cluster Research Program, and JSPS KAKENHI Grant Number JP18K05266. We thank Ms. Y. Zong for her experimental assistance. \n\n# Author contributions \n\nM.C., Y. Zhou, N.P.P., M.-G.J., and X.C. Zeng conceived the idea. Y. Zhou and N.P.P. supervised the project. Y. Zhou and M.C. designed the experiments. M.C. performed the film fabrication, most of materials characterization, and device fabrication/testing. H.F.G. helped with the thermal evaporation of perovskites. Y. Zhang assisted with the device fabrication. L.K.O., Z.H., and Y.B.Q. conducted the XPS mapping. A.D.C. and R.L.G. performed the regular XPS measurements. M.-G.J. and X.C. Zeng performed the theoretical calculations. T.S. and D.P. helped with the optical characterization. Y. Zhou, M.C., and N.P.P. co-wrote the paper, with comments from all the other authors. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-07951-y. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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" + }, + { + "id": "10.1073_pnas.1900556116", + "DOI": "10.1073/pnas.1900556116", + "DOI Link": "http://dx.doi.org/10.1073/pnas.1900556116", + "Relative Dir Path": "mds/10.1073_pnas.1900556116", + "Article Title": "Solar-driven, highly sustained splitting of seawater into hydrogen and oxygen fuels", + "Authors": "Kuang, Y; Kenney, MJ; Meng, YT; Hung, WH; Liu, YJ; Huang, JE; Prasanna, R; Li, PS; Li, YP; Wang, L; Lin, MC; McGehee, MD; Sun, XM; Dai, HJ", + "Source Title": "PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA", + "Abstract": "Electrolysis of water to generate hydrogen fuel is an attractive renewable energy storage technology. However, grid-scale freshwater electrolysis would put a heavy strain on vital water resources. Developing cheap electrocatalysts and electrodes that can sustain seawater splitting without chloride corrosion could address the water scarcity issue. Here we present a multilayer anode consisting of a nickel-iron hydroxide (NiFe) electrocatalyst layer uniformly coated on a nickel sulfide (NiSx) layer formed on porous Ni foam (NiFe/NiSx-Ni), affording superior catalytic activity and corrosion resistance in solar-driven alkaline seawater electrolysis operating at industrially required current densities (0.4 to 1 A/cm(2)) over 1,000 h. A continuous, highly oxygen evolution reaction-active NiFe electrocatalyst layer drawing anodic currents toward water oxidation and an in situ-generated polyatomic sulfate and carbonate-rich passivating layers formed in the anode are responsible for chloride repelling and superior corrosion resistance of the salty-water-splitting anode.", + "Times Cited, WoS Core": 652, + "Times Cited, All Databases": 686, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000463069900024", + "Markdown": "# Solar-driven, highly sustained splitting of seawater into hydrogen and oxygen fuels \n\nYun Kuanga,b,c,1, Michael J. Kenneya,1, Yongtao Menga,d,1, Wei-Hsuan Hunga,e, Yijin Liuf, Jianan Erick Huanga, Rohit Prasannag, Pengsong Lib,c, Yaping Lib,c, Lei Wangh,i, Meng-Chang Lind, Michael D. McGeheeg,j, Xiaoming Sunb,c,d,2, and Hongjie Daia,2 \n\naDepartment of Chemistry, Stanford University, Stanford, CA 94305; bState Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China; cBeijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; dCollege of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China; eDepartment of Materials Science and Engineering, Feng Chia University, Taichung 40724, Taiwan; fStanford Synchrotron Radiation Light Source, SLAC National Accelerator Laboratory, Menlo Park, CA 94025; gDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305; hCenter for Electron Microscopy, Institute for New Energy Materials, Tianjin University of Technology, Tianjin 300384, China; iTianjin Key Laboratory of Advanced Functional Porous Materials, School of Materials, Tianjin University of Technology, Tianjin 300384, China; and jDepartment of Chemical Engineering, University of Colorado Boulder, Boulder, CO 80309 \n\nContributed by Hongjie Dai, February 5, 2019 (sent for review January 14, 2019; reviewed by Xinliang Feng and Ali Javey) \n\nElectrolysis of water to generate hydrogen fuel is an attractive renewable energy storage technology. However, grid-scale freshwater electrolysis would put a heavy strain on vital water resources. Developing cheap electrocatalysts and electrodes that can sustain seawater splitting without chloride corrosion could address the water scarcity issue. Here we present a multilayer anode consisting of a nickel–iron hydroxide (NiFe) electrocatalyst layer uniformly coated on a nickel sulfide (NiSx) layer formed on porous Ni foam (NiFe/NiSx-Ni), affording superior catalytic activity and corrosion resistance in solar-driven alkaline seawater electrolysis operating at industrially required current densities (0.4 to $1\\mathsf{A}/\\mathsf{c m}^{2})$ over 1,000 h. A continuous, highly oxygen evolution reactionactive NiFe electrocatalyst layer drawing anodic currents toward water oxidation and an in situ-generated polyatomic sulfate and carbonate-rich passivating layers formed in the anode are responsible for chloride repelling and superior corrosion resistance of the salty-water-splitting anode. \n\nseawater splitting | hydrogen production | electrocatalysis | anticorrosion | solar driven \n\nSitsorain gatrtreancetiwvaebsleo eutnieorng ytobtyhderinvtienrgmuitptheinllcychperombilcealmrfeacetidobnys many alternative energy sources (1, 2). Due to its high gravimetric energy density $\\left(142\\ \\mathrm{MJ/kg}\\right)$ and pollution-free use, hydrogen is considered one of the most promising clean energy carriers (3–5). Electrolysis of water is a clean way to generate hydrogen at the cathode but is highly dependent on efficient and stable oxygen evolution reaction (OER) at the anode (6–10). However, if water splitting is used to store a substantial portion of the world’s energy, water distribution issues may arise if vast amounts of purified water are used for fuel formation. Seawater is the most abundant aqueous electrolyte feedstock on Earth but its implementation in the water-splitting process presents many challenges, especially for the anodic reaction. \n\nThe most serious challenges in seawater splitting are posed by the chloride anions $(\\sim0.5\\mathrm{~M~}$ in seawater). At acidic conditions, the OER equilibrium potential vs. the normal hydrogen electrode (NHE) is only higher than that of chlorine evolution by 130 $\\mathrm{mV}$ (11), but OER is a four-electron oxidation requiring a high overpotential while chlorine evolution is a facile two-electron oxidation with a kinetic advantage. While chlorine is a highvalue product, the amount of chlorine that would be generated to supply the world with hydrogen would quickly exceed demand (12). Unlike OER, the equilibrium potential of chorine evolution does not depend on pH. Selective OER over chlorine generation can thus be achieved in alkaline electrolytes to lower the onset of OER. However, hypochlorite formation could still compete with OER (Eqs. 1 and 2; both are pH-dependent) (11), with an onset potential ${\\sim}490~\\mathrm{mV}$ higher than that of OER, which demands highly active OER electrocatalysts capable of high-current $(\\sim1$ $\\mathrm{A}/\\mathrm{cm}^{2},$ ) operations for high-rate $\\mathbf{H}_{2}/\\mathbf{O}_{2}$ production at overpotentials well below hypochlorite formation: \n\n$$\n\\begin{array}{r l r}&{\\mathrm{Cl}^{-}(a q)+2\\mathrm{OH}^{-}(a q)\\rightarrow\\mathrm{OCl}^{-}(a q)+2\\mathrm{e}^{-}}&\\\\ &{\\quad\\quad\\quad\\mathrm{E}^{0}=1.72\\mathrm{V}-0.059*\\mathrm{pHvs.NHE}}&\\end{array}\n$$ \n\n$$\n\\begin{array}{r l r}{\\mathrm{4OH^{-}}(a q)\\rightarrow\\mathrm{O}_{2}(g)+2\\mathrm{H}_{2}\\mathrm{O}(l)+4\\mathrm{e}^{-}}&{{}}&{}\\\\ {\\mathrm{E^{0}=1.23\\mathrm{V}-0.059~*~p H v s.N H E}.}&{{}}&{}\\end{array}\n$$ \n\nEven with a highly active OER catalyst in alkaline electrolytes, the aggressive chloride anions in seawater can corrode many catalysts and substrates through metal chloride-hydroxide formation mechanisms (13): \n\n# Significance \n\nElectrolysis of water to generate hydrogen fuel could be vital to the future renewable energy landscape. Electrodes that can sustain seawater splitting without chloride corrosion could address the issue of freshwater scarcity on Earth. Herein, a hierarchical anode consisting of a nickel–iron hydroxide electrocatalyst layer uniformly coated on a sulfide layer formed on Ni substrate was developed, affording superior catalytic activity and corrosion resistance in seawater electrolysis. In situgenerated polyanion-rich passivating layers formed in the anode are responsible for chloride repelling and high corrosion resistance, leading to new directions for designing and fabricating highly sustained seawater-splitting electrodes and providing an opportunity to use the vast seawater on Earth as an energy carrier. \n\nAuthor contributions: Y.K., M.J.K., and H.D. designed research; Y.K., M.J.K., Y.M., W.-H.H., Y. Liu, J.E.H., R.P., P.L., Y. Li, L.W., and M.-C.L. performed research; Y.K., M.J.K., Y.M., W.-H.H., Y. Liu, J.E.H., R.P., P.L., Y. Li, L.W., M.-C.L., M.D.M., X.S., and H.D. analyzed data; and Y.K., M.J.K., and H.D. wrote the paper. \n\nAdsorption of $\\mathrm{Cl}^{-}$ by surface polarization : \n\n$$\n\\mathrm{M+Cl^{-}\\to M C l_{\\mathrm{ads}}+e^{-}}\n$$ \n\nDissolution by further coordination : \n\n$$\n\\mathbf{MCl}_{\\mathrm{ads}}+\\mathbf{Cl}^{-}\\rightarrow\\mathbf{MCl}_{\\mathrm{x}}^{-}\n$$ \n\nConversion from chloride to hydroxide \n\n$$\n\\mathrm{MCl_{x}}^{-}+\\mathrm{OH}^{-}\\to\\mathrm{M(OH)_{x}}+\\mathrm{Cl}^{-}.\n$$ \n\nTo avoid relying on costly desalination processes, development of electrodes that are corrosion-resistive for splitting seawater into $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ is crucial to the advancement of seawater electrolysis, an undertaking with limited success thus far. Mn-based oxides deposited on $\\mathrm{IrO}_{2}$ -Ti showed stability for OER in NaCl-containing electrolytes but were limited by Ir’s high cost (14–16). NiFe-layered double hydroxide (NiFe-LDH) (17), Co-borate, and Co-phosphate materials have all shown high OER activity in NaCl-containing electrolytes, but long-term stability at industrial current densities ${\\mathrm{\\sim}}1{\\mathrm{\\A/cm}}^{2}$ has not been achieved for seawater electrolysis (11, 18, 19). \n\nThis work developed a multilayer electrode that upon activation evolved into a polyanion sulfate/carbonate-passivated $\\mathrm{NiFe/}$ $\\mathrm{NiS_{x}{-N i}}$ foam anode with high activity and corrosion resistance for OER in chloride-containing alkaline electrolytes. The negatively charged polyanions incorporated into the anode were derived from anodization of the underlying nickel sulfide layer and carbonate ions in the alkaline solution, repelling $\\mathrm{Cl}^{-}$ anions in seawater and hence imparting corrosion resistance. When the anode is paired with an advanced $\\mathrm{Ni-NiO-Cr}_{2}\\mathrm{O}_{3}$ hydrogen evolution cathode in alkaline seawater, the electrolyzer can operate at low voltages and high currents and last for more than $^{1,000\\mathrm{h}}$ . \n\nThe $\\mathrm{NiFe/NiS_{x}{\\mathrm{-}}N}$ i foam anode (referred to as $\\mathrm{Ni}^{3}$ for brevity) was made by first converting the surface of Ni foam to $\\mathrm{NiS_{x}}$ by devising a solvothermal reaction of Ni foam with elemental sulfur in toluene (SI Appendix, Materials and Methods). After formation of the $\\mathrm{NiS_{x}}$ layer, an OER-active NiFe hydroxide $(20-$ 24) was electrodeposited via the reduction of nitrate from a solution of $\\mathrm{Ni}(\\mathsf{N O}_{3})_{2}$ and $\\mathrm{Fe}(\\mathsf{N O}_{3})_{3}$ $({\\mathrm{Ni}}{\\mathrm{:Fe}}=3{:}1$ ) (Fig. 1A) (20, 25). We propose that the matched crystalline phase and $d$ spacing could allow epitaxial growth of NiFe hydroxide laminates on $\\mathrm{NiS_{x}}$ surface, resulting in a uniform coating of vertically grown LDH on top of the $\\mathrm{NiS_{x}}$ layer (Fig. $1C$ and $S I$ Appendix, Fig. S1). Electron diffraction patterns revealed that the $\\mathrm{NiS_{x}}$ and NiFe layers were amorphous in nature (SI Appendix, Fig. S1). SEM (Fig. $1B$ and $C$ ) and cross-sectional elemental mapping revealed a $\\mathrm{\\sim}1\\cdot$ - to $2\\cdot\\upmu\\mathrm{m}$ -thick $\\mathrm{NiS_{x}}$ layer formed on $\\bf N i$ foam $S I$ Appendix, Fig. S2), with a ${\\sim}200$ -nm-thick NiFe layer on top of the $\\mathrm{NiS_{x}}$ layer (Fig. $1D$ and $E$ ). After anodic activation of the $\\mathbf{N}\\mathbf{i}^{3}$ anode in an alkaline simulated seawater electrolyte (1 M KOH plus $0.5\\:\\mathrm{M}\\:\\mathrm{NaCl}$ , a mimic of seawater adjusted to alkaline), OER performance was measured in a three-electrode configuration in a freshly prepared alkaline simulated seawater electrolyte (Fig. 2A). Cyclic voltammetry (CV) showed a $30~\\mathrm{mV}$ lower onset overpotential (taken to be the potential vs. RHE where the reverse scan reaches $0\\mathrm{\\mA}/\\mathrm{cm}^{2}$ ), an improvement over the original electrodeposited NiFe catalyst and NiFe-LDH (17, 20, 21). The large increase in the $\\mathrm{Ni}^{2+}\\stackrel{\\cdot}{\\rightarrow}\\mathrm{Ni}^{3+}$ oxidation peak $(\\sim1.44~\\mathrm{V}$ ; Fig. 2A) suggested increased electrochemically active nickel sites for OER through the activation process. A high current density of $400\\mathrm{mA}/\\mathrm{cm}^{2}$ at an overpotential of $\\upeta=510\\mathrm{mV}$ was reached (no iR compensation, $R=\\bar{0.7}\\pm0.05$ ohm; Fig. $2B$ ). After iR compensation, the actual overpotential applied on the ${\\bf N i}^{3}$ anode to achieve an OER current density of $400\\mathrm{\\mA}/\\mathrm{cm}^{2}$ was ${\\sim}0.3\\mathrm{~V~}$ , well below the $0.49\\mathrm{~V~}$ overpotential required to trigger chloride oxidation to hypochlorite. \n\n![](images/0c7265159e7ede6dde4c6485b125cec030a4eceeda0a40ca08efef5eb7e23de3.jpg) \nFig. 1. Fabrication and structure of the dual-layer NiFe/NiSx-Ni foam $(N i^{3})$ anode for seawater splitting. (A) Schematic drawing of the fabrication process, including a surface sulfuration step and an in situ electrodeposition of NiFe. (B–D) SEM images of untreated nickel foam, $\\mathsf{N i S}_{\\mathbf{x}}$ formed on nickel foam, and electrodeposited NiFe on the $\\mathsf{N i S}_{\\mathsf{x}}$ surface. (E) Elemental mapping of a cross-section of NiFe/NiSx on an Ni wire in the Ni foam, revealing Ni wire, $N i S_{x},$ and NiFe layers. \n\n![](images/d6c6be48dc3fbe9a540e423ad92c6f6e9d5995e6b475b88122b8ff55bd10ff61.jpg) \nFig. 2. Sustained, energy-efficient seawater splitting continuously over $1,000\\mathrm{~h~}$ . (A) CV scans of an ${\\mathsf{N i}}^{3}$ anode before and after activation in 1 M KOH at 400 $\\mathsf{m A}/\\mathsf{c m}^{2}$ for $12\\mathsf{h}$ and 1 $\\mathsf{M K O H}+0.5$ M NaCl for $12\\mathsf{h}$ at $400m\\mathsf{A}/\\mathsf{c m}^{2}$ ; the CV curves were taken in 1 M KOH, resistance $0.75\\pm0.05$ ohm. (B) CV scans of an $N_{1}^{\\cdot3}$ anode (activated in 1 M KOH at $400m\\mathsf{A}/\\mathsf{c m}^{2}$ for $12\\mathsf{h}$ followed by $1\\mathsf{M K O H}+0.5\\mathsf{M N}$ aCl at $100\\mathrm{mA}/\\mathrm{cm}^{2}$ for $12\\mathsf{h}$ ) before and after $1,000-\\hslash$ seawater splitting in an alkaline simulated seawater electrolyte (1 M KOH with 0.5 M NaCl in deionized water), $R=0.7\\pm0.05$ ohm. (C) Linear sweep voltammetry (LSV) scans of a seawater-splitting electrolyzer $(N i^{3}$ paired with an Ni-NiO- $.C r_{2}O_{3}$ cathode) taken in alkaline seawater electrolyte (1 M ${\\mathsf{K O H}}+$ real seawater) at room temperature $(23^{\\circ}\\mathsf C,$ resistance $0.95\\pm0.05$ ohm) and in near-saturated salt concentration $(1.5\\mathsf{M N a C l})$ ) under industrial electrolysis conditions $(6\\mathsf{M}\\mathsf{K}\\mathsf{O}\\mathsf{H}$ electrolyte at $80^{\\circ}\\mathsf C,$ resistance $0.55\\pm0.05$ ohm). The ${\\mathsf{N i}}^{3}$ anode was first activated under $400m\\mathsf{A}/\\mathsf{c m}^{2}$ in 1 M KOH for $12\\mathsf{h}$ followed by $1\\mathsf{M}\\mathsf{K O H}+0.5$ M NaCl at $100\\mathsf{m A}\\mathsf{I c m}^{2}$ for $12\\mathsf{h}$ . (D) Durability tests (1,000 h) recorded at a constant current of $400~\\mathsf{m A}/\\mathsf{c m}^{2}$ of the seawater-splitting electrolyzer under 1 M $\\mathsf{K O H+}$ real seawater at room temperature $(R=0.95\\pm0.05$ ohms), $1\\ \\mathsf{M K O H}+1.5\\ \\mathsf{M N a}$ Cl at room temperature $(R=0.8\\pm0.05$ ohms), and 6 M KOH electrolyte at $80^{\\circ}\\mathsf{C}$ $(R=0.55\\pm0.05$ ohms), respectively. Data were recorded after activation of ${\\mathsf{N i}}^{3}$ anode under $400~\\mathsf{m A}/\\mathsf{c m}^{2}$ in both 1 M KOH and 1 $\\mathsf{M K O H}+0.5$ M NaCl (or 1.5 M NaCl for the test in 1 M/6 M $\\mathsf{K O H}+1.5$ M NaCl) electrolytes for $12\\mathrm{~h~}$ . \n\nWe then paired the activated/passivated ${\\bf N i}^{3}$ anode with a highly active ${\\mathrm{Ni-NiO-Cr}}_{2}{\\mathrm{O}}_{3}$ hydrogen evolution reaction (HER) cathode (26) for two-electrode high-current electrolysis of alkaline seawater. Three-electrode linear scan voltammetry of the Ni-NiO$\\mathrm{Cr}_{2}\\mathrm{O}_{3}$ showed that ${\\sim}0.37\\mathrm{V}$ overpotential was required to drive an HER current density of $500\\mathrm{\\mA}/\\mathrm{cm}^{2}$ (SI Appendix, Fig. S3A, without iR compensation). After iR compensation, the overpotential applied on the catalyst to drive a current density of $\\mathbf{\\dot{500}}~\\mathbf{mA}/\\mathbf{cm}^{2}$ was as low as ${\\sim}160~\\mathrm{mV}$ , which was among the best nonprecious-metal-based HER catalysts reported so far. In addition, chloride did not degrade the activity and stability during the HER process (SI Appendix, Fig. S3B). The two-electrode electrolysis experiment was first carried out in $1\\ \\mathrm{M\\KOH}$ added to seawater from the San Francisco Bay at room temperature $(23^{\\circ}\\mathrm{C})$ . The electrolyzer operated at a current density of $400\\mathrm{\\mA}/\\mathrm{cm}^{2}$ under a voltage of $\\dot{2}.12\\dot{\\mathrm{~V~}}$ (Fig. 2C, without iR compensation; $R=$ $0.95\\pm0.05$ ohm) continuously for more than $1{,}000\\mathrm{h}$ without obvious decay (Fig. 2D), corroborated by three-electrode measurements before and after the $^{1,000-\\mathrm{h}}$ stability test (Fig. 2B). \n\nIn a real electrolysis application, salt may accumulate in the electrolyte if seawater is continuously fed to the system and water is converted to $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ . To this end, we investigated electrolytes with higher NaCl concentrations than in seawater, using deionized water with $\\mathrm{1~M~KOH+1~M~NaCl}$ or even $1.5\\:\\mathrm{M}\\:\\mathrm{Na}\\bar{\\mathrm{Cl}}$ (Fig. $2D$ and $S I$ Appendix, Fig. S4). Meanwhile we increased NaCl concentration during $\\mathbf{N}\\mathbf{i}^{3}$ anodic activation/passivation to match the conditions of the stability test (i.e., the second phase of anodization would use $1\\mathrm{\\:M\\:KOH+1\\:M}$ or $1.5\\mathrm{~M~Na\\bar{C}l}$ if the stability test was going to be carried out in this electrolyte). Due to the higher ionic strengths with $\\mathbf{NaCl}$ concentrations of $^\\mathrm{~1~M~}$ and \n\n$1.5~\\mathrm{M}$ , the cell resistance decreased and the voltages of the electrolyzers using the activated $\\mathbf{N}\\mathbf{i}^{3}$ anode afforded a current density of $\\dot{4}00\\mathrm{\\mA}/\\mathrm{cm}^{2}$ at lower cell voltages of $2.09\\mathrm{~V~}$ and $2.02\\mathrm{~V~}$ , respectively. The electrolysis was still stable for more than $^{1,000\\mathrm{~h~}}$ , with no obvious corrosion or voltage increase observed, suggesting impressively active and stable anode for electrolysis in high-salinity water. Further, the electrolyzer operated stably under conditions typically used in industry (high temperature and concentrated base) (27), needing only $1.72\\mathrm{V}$ to reach a current density of $400\\mathrm{mA}/\\mathrm{cm}^{2}$ in $6\\mathrm{{MKOH}+1.5\\mathrm{{MNaCl}}}$ at $80^{\\circ}\\mathrm{C}$ for ${\\tt>}1,000{\\tt h}$ (Fig. 2 $C$ and $D$ ). Mass spectrometry showed no anodic $\\mathrm{Cl}_{2}$ evolution and gas chromatography showed a relative Faradaic efficiency (R_FE, defined as the ratio of $\\mathrm{O}_{2}$ produced in $\\mathrm{\\KOH+NaCl}$ electrolyte over $\\mathbf{O}_{2}$ produced in KOH electrolyte) of $\\ensuremath{\\mathbf{O}}_{2}$ production of ${\\sim}100\\%$ (SI Appendix, Figs. S5 and S6), suggesting selective OER in alkalineadjusted salty water using the passivated ${\\bf N i}^{3}$ anode. \n\nWe performed control experiments and found that in a “harsh” electrolyte of 1 M KOH with a high concentration of $2\\mathrm{MNaCl}$ , an activated ${\\bf N i}^{3}$ anode paired with an $\\mathrm{Ni-NiO-Cr}_{2}\\mathrm{O}_{3}$ cathode lasted for ${\\sim}600\\mathrm{h}$ (SI Appendix, Fig. S7A) before breakdown under a constant current of $400\\mathrm{\\mA}/\\mathrm{cm}^{2}$ (during which R_FE was ${\\sim}99.9\\%$ for $\\mathrm{O}_{2}$ ; SI Appendix, Fig. S7C). Bare Ni foam and sulfurtreated Ni foam (to form $\\mathrm{NiS_{x}}$ ) without NiFe lasted for less than $20\\mathrm{min}$ (SI Appendix, Fig. S7A, Inset) with R_FE $<35\\%$ for $\\mathbf{O}_{2}$ (SI Appendix, Fig. S7C). NiFe hydroxide-coated $\\mathrm{Ni}$ foam without the $\\mathrm{NiS_{x}}$ interlayer was also inferior to ${\\mathrm{Ni}}^{3}$ and lasted $12\\mathrm{~h~}$ $(S I A p.$ pendix, Fig. S7A) with an R_FE for $\\mathrm{O}_{2}$ of $99\\%$ at $400\\mathrm{mA}/\\mathrm{cm}^{2}$ (SI Appendix, Fig. S7C). These results together with three-electrode constant voltage testing (SI Appendix, Fig. S7D) suggested that the combination of NiFe hydroxide on top of $\\mathrm{NiS_{x}/N i}$ to form a $\\mathrm{Ni}^{3}$ structure was key to superior chloride corrosion resistance. \n\nThe electrode structures (before and after seawater splitting in various electrolytes) were investigated by 3D X-ray microtomography $S I$ Appendix, Fig. S8). After $\\dot{\\mathrm{~1,000~h~}}$ of seawater electrolysis, the $\\mathbf{N}\\mathbf{i}^{3}$ anode showed a structural integrity (SI Appendix, Fig. S8B) similar to that before electrolysis (SI Appendix, Fig. S8A). Even under a harsh condition with four times the salt concentration of real seawater for $300\\mathrm{~h~}$ , the anode still maintained the Ni foam skeleton structure $S I$ Appendix, Fig. S8C). However, Ni foam without $\\mathrm{NiS_{x}}$ but with electrodeposited NiFe (the best control sample) showed severe corrosion after only an 8-h test in 1 $\\mathsf{M K O H}+2\\$ M \n\nNaCl (SI Appendix, Fig. S8D). Clearly, both the NiFe OER catalyst coating and the nickel sulfide layer underneath the catalyst are critical to long-term stability of the anode against chloride corrosion. \n\nGiven that the activated $\\mathbf{N}\\mathbf{i}^{3}$ anodes were quite stable in various electrolytes under the current density of $400\\mathrm{\\mA}/\\mathrm{cm}^{2}$ , we then tested the system at even higher current densities. Three-electrode testing of an activated $\\mathbf{N}\\mathbf{i}^{3}$ electrode in simulated alkaline seawater electrolyte showed a $750~\\mathrm{mV}$ overpotential (without iR compensation) for reaching a high OER current density of $1{,}500\\mathrm{mA}{\\cdot}\\mathrm{cm}^{-2}$ (Fig. 3A). After iR compensation, the actual overpotential applied on the $\\mathbf{N}\\mathbf{\\hat{i}}^{3}$ anode to achieve the OER current density of $1500\\mathrm{mA}/\\mathrm{cm}^{2}$ in simulated alkaline seawater was ${\\sim}0.38\\mathrm{~V~}$ (Fig. $3B$ ), still \n\n![](images/d4973a3ac8106b50a7072857cfaa9efdc7973cd2c0ab59de65b6bd8c7c83632a.jpg) \nFig. 3. Seawater electrolysis running at current density up to $1\\mathsf{A}/\\mathsf{c m}^{2}$ . (A) CV scans of a $0.25\\mathrm{-cm}^{2}\\mathsf{N i}^{3}$ anode before and after activation in 1 M KOH and 1 M $\\mathsf{K O H}+0.5$ M NaCl (both at $400m\\mathsf{A}/\\mathsf{c m}^{2})$ ; the CV curves were taken in simulated alkaline seawater $1\\mathsf{M}\\mathsf{K O H}+0.5$ M NaCl), resistance $1.2\\pm0.05$ ohm. (B) CV scans with and without iR compensation of the $0.25\\mathrm{-}\\mathsf{c m}^{2}\\mathsf{N i}^{3}$ anode shown in A. (C) Two electrode R_FEs of oxygen generation in seawater electrolyzer $(N i^{3}$ paired with Ni-NiO- $\\cdot\\mathsf{C r}_{2}\\mathsf{O}_{3})$ running at $400\\ m\\mathsf{A}/\\mathsf{c m}^{2}$ , $800\\mathrm{\\mA}/\\mathrm{cm}^{2}$ , and $1,000\\mathrm{mA}/\\mathrm{cm}^{2}$ in 1 $\\mathsf{M K O H}+0.5\\mathsf{M N}$ aCl electrolyte. $(D)$ Durability tests of the seawatersplitting electrolyzer $(0.5\\mathsf{c m}^{2}\\mathsf{N i}^{3}$ paired with Ni-NiO- $.(\\mathsf{r}_{2}\\mathsf{O}_{3})$ recorded in $1\\ \\mathsf{M}\\ \\mathsf{K O H}+0.5$ M NaCl electrolyte at room temperature under constant currents of $400\\ m\\mathsf{A}/\\mathsf{c m}^{2}$ $(R=1.5\\pm0.05$ ohms), $800\\ m\\mathsf{A}/\\mathsf{c m}^{2}$ $(R=1.6\\pm0.05$ ohms), and $1,000\\ m{\\mathsf{A}}/{\\mathsf{c m}}^{2}$ $(R=1.6\\pm0.05$ ohms), respectively. Data were recorded after activation of ${\\mathsf{N i}}^{3}$ anode under $400~\\mathsf{m A}/\\mathsf{c m}^{2}$ in both 1 M KOH and 1 $\\mathsf{M K O H}+0.5$ M NaCl electrolytes for 12 h. (E) Current density–potential curve (J–V) of the seawater electrolyzer and two perovskite tandem cells under dark and simulated AM 1.5-G $100\\mathrm{\\mw}{\\cdot}\\mathrm{cm}^{-2}$ illumination. The illuminated surface area of each perovskite cell was $0.12~\\mathsf{c m}^{2}$ $(0.24\\ c m^{2}$ total), and the catalyst electrode areas (geometric) were $1c m^{2}$ each. The ${\\mathsf{N i}}^{3}$ were first activated in 1 M KOH under $400~\\mathsf{m A}/\\mathsf{c m}^{2}$ for $12\\mathsf{h}$ then in $1\\ \\mathsf{M}\\mathsf{K O H}+0.5\\ \\mathsf{M}$ NaCl under $100\\mathrm{mA}/\\mathrm{cm}^{2}$ for $12\\mathsf{h}$ . After that the electrolyzer was held at $20\\mathsf{m A}/\\mathsf{c m}^{2}$ for $5\\mathfrak{h}$ before pairing with the solar cell. (F) Twenty-hour stability test of perovskite solar cell-driven seawater electrolysis and corresponding solar-to-hydrogen (STH) efficiency. (G) A photo showing a commercial silicon solar cell-driven electrolysis $(1-\\mathsf{c m}^{2}$ electrodes) of seawater running at $876~\\mathsf{m A}$ under a voltage of 2.75 V $(R=1.0\\pm0.05$ ohms). No iR compensation was applied to any experiment. \n\n$110\\mathrm{mV}$ lower than the $0.49{\\mathrm{V}}$ threshold for chloride oxidation. The ${\\bf R_{-}F E}$ tests running at 400, 800, and $1{,}000\\ \\mathrm{mA}/\\mathrm{cm}^{2}$ all showed nearly $100\\%$ for oxygen generation (Fig. 3C). Two-electrode electrolysis in $1\\ \\mathrm{M\\KOH}+0.5\\ \\mathrm{M\\NaCl}$ showed a cell voltage of $2.06\\mathrm{~V},2.27\\mathrm{~V~}$ , and $2.44\\mathrm{~V~}$ for a current density of 400, 800, and $1{,}000\\ \\mathrm{mA}/\\mathrm{cm}^{2}$ (Fig. $3D$ ), respectively, all without obvious performance decay for more than $\\mathrm{\\dot{5}00~h}$ at such high currents. \n\nDriving electrolysis with inexpensive solar cells is an attractive way to generate hydrogen using a carbon-free energy source. To this end, we paired an activated $\\mathrm{\\DeltaNi}^{3}$ anode with an $\\mathrm{Ni-NiO-Cr}_{2}\\mathrm{O}_{3}$ cathode in $\\bar{1^{\\mathbf{\\alpha}}}\\mathbf{M}\\mathbf{\\KOH}+0.5\\mathbf{\\beta}\\mathbf{M}\\bar{1}$ NaCl and the cell was allowed to operate for $^\\textrm{\\scriptsize5h}$ at $20\\mathrm{\\mA}/\\mathrm{cm}^{2}$ , after which the electrolyzer was connected in series with two $0.2\\mathrm{-cm}^{2}$ perovskite solar cells (28) $(0.12\\mathrm{-cm}^{2}$ masked area, single-cell maximum power point tracking data in SI Appendix, Fig. S9) connected in series as a side-by-side tandem cell. Under AM 1.5-G $100\\mathrm{\\mW/cm}^{2}$ simulated sunlight, the tandem cell (without electrolyzer) achieved an open circuit voltage of $2\\mathrm{v}$ , a short circuit current density of $9.7\\pm0.{\\dot{1}}\\mathrm{mA}/\\mathrm{cm}^{2}$ , and a maximum power conversion efficiency of $16\\%$ . The predicted operating current density of the solar cell–electrolyzer combination was defined by the intersection of the solar cell power curve with the electrolyzer load curve (Fig. 3E), giving a value of $9.7\\pm0.1\\mathrm{\\mA}/\\mathrm{cm}^{2}$ . The light-driven electrolysis rate corresponded to a solar-to-hydrogen (STH) efficiency of $11.9~\\pm$ $0.1\\%$ , comparable to similar systems that utilize purified water (29). The integrated solar-driven seawater-splitting system operated stably for $20\\mathrm{h}$ without obvious STH decay (Fig. $3F$ ). We then paired the seawater electrolyzer with a commercial Si solar cell (Renogy E.FLEX 5W, 5 V, 1 A) for a high-current test using real sunlight. The system operated at an impressively high current of ${\\sim}880\\mathrm{mA}$ under a photovoltage of $2.75\\mathrm{V}$ (Fig. $3G$ and Movie S1). \n\nActivation of $\\mathbf{N}\\mathbf{i}^{3}$ electrode in simulated alkaline seawater played a key role in formation of a chloride-repelling passivation layer. After 3 to $^{4\\mathrm{h}}$ of anodization in 1 M KOH plus $\\mathrm{0.5\\:M\\:NaCl}$ at $400\\mathrm{mA}/\\mathrm{cm}^{2}$ , an obvious voltage dip (drop and partial recovery) was observed (Fig. 4A), during which the R_FE of $\\mathrm{O}_{2}$ production was low $(\\sim96\\%$ ; Fig. $4B$ ), suggesting anodic etching/corrosion during OER in salty water. After the voltage dip and over $12\\mathrm{-h}$ continued activation, the voltage stabilized and the oxygen R_FE increased to a stable ${\\sim}100\\%$ , suggesting passivation of the anode with no further corrosion. In contrast, activation of NiFe/Ni foam (without a $\\mathrm{NiS_{x}}$ interlay) under the same condition $(400\\mathrm{mA}/\\mathrm{cm}^{2})$ ) in the $1\\ \\mathrm{M\\KOH}+0.5\\ \\mathrm{M\\NaCl}$ electrolyte showed continuous voltage increase with oxygen $\\mathrm{R\\_FE}<100\\%$ (SI Appendix, Fig. S10), suggesting continuous anodic corrosion by the chloride ions and the lack of passivation without the $\\mathrm{NiS_{x}}$ layer in the anode. \n\nSystematic investigations revealed that the activation/passivation treatment of $\\mathrm{\\tilde{Ni}}^{3}$ led to transient etching followed by passivation by polyanions through the layers of $\\mathrm{NiFe/NiS_{x}–N i}$ foam anode. Raman spectroscopy of the $\\mathrm{\\check{N}i}^{3}$ electrode after anodic activation revealed vibrational modes at $470~\\mathrm{cm}^{-1}$ and $540~\\mathrm{cm}^{-1}$ characteristic of NiFe LDHs (Fig. 4C) (30), with the peaks around $1{,}230\\mathrm{cm}^{-1}$ , $1{,}440\\mathrm{cm}^{-1}$ , and $1{,}590\\mathrm{cm}^{-1}$ assigned to $_{\\mathrm{{S-O}}}$ vibration (31). This result suggested etching of the $\\mathrm{\\tilde{Ni}}^{3}$ anode during the activation process was mainly oxidation of the sulfides, which was corroborated by the voltage dip in Fig. $^{4A}$ and reduced R_FE for OER (Fig. 4B). In the activation step, anodic etching of the $\\mathrm{NiS_{x}}$ layer led to the formation of sulfate ions that migrated to the NiFe catalyst layer (free sulfate ions were also observed in the electrolyte; see $S I$ Appendix, Fig. S11). Together with carbonate ions known to exist in KOH solution, the sulfate ions intercalated into the NiFe LDH resulted from anodization of the NiFe coating layer. Note that the NiFe-LDH was near amorphous in nature with a low degree of crystallinity (SI Appendix, Fig. $S1F$ ; the electron diffraction pattern did reveal ${\\sim}0.64$ -nm layer spacing). Indeed, TOF secondary ion mass spectrometry (TOF-SIMS) mapping on a ${\\mathrm{Ni}}^{3}$ electrode after activation unambiguously revealed the presence of both sulfate and carbonate species (Fig. $4D$ ), confirming the formation of a layer of NiFe-LDH intercalated with two types of polyanions (32, 33). \n\n![](images/29b2b100ee284fe3ed3971af6ee2d86cabd2f675ae683473947bcd8f4b464fb3.jpg) \nFig. 4. Cation selective layer generation during activation in salty electrolyte. (A) Three-electrode OER constant current activation of ${\\mathsf{N i}}^{3}$ in $1\\mathsf{M K O H}+0.5\\mathsf{M}$ 1 NaCl, resistance $1.4\\pm0.05$ ohm, electrode area $0.5\\mathsf{c m}^{2}$ . The decrease in voltage that occurred between 3 and $4h$ was due to the etching-passivation process. Note that ${\\mathsf{N i}}^{3}$ was first activated in 1 M KOH under $400~\\mathsf{m A}/\\mathsf{c m}^{2}$ for $12\\mathsf{h}$ before activation in 1 $\\mathsf{M K O H}+0.5\\mathsf{N}$ NaCl. (B) OER R_FE plots for $\\mathsf{O}_{2}$ production taken during A. Decrease in voltage at 3 to $4h$ corresponds to a small decrease in R_FE. Error bars were obtained by three parallel tests. (C) Raman spectra of ${\\mathsf{N i}}^{3}$ and $\\mathsf{N i S}_{\\mathsf{x}}/\\mathsf{N i}$ after $12-\\mathsf{h}$ activation in 1 M $\\mathsf{K O H}+0.5$ M NaCl, suggesting polyatomic anion intercalated LDH phase and formation of sulfate species at the $\\mathsf{L D H/N i S_{x}}$ interface. $(D)$ TOF-SIMS mapping of $\\mathsf{S O}_{\\mathsf{x}}{}^{2-\\slash1}$ - and CO32-/1- fragments from a ${\\mathsf{N i}}^{3}$ and ${N i S_{x}}/{N i}$ electrode surface after activation in $1\\textsf{M K O H}+0.5\\textsf{M}$ NaCl at $400~\\mathsf{m A}/\\mathsf{c m}^{2}$ . Negative TOF-SIMS counts were collected from $m/z=96/48/80/40$ $(50_{4}^{-}/50_{4}^{2-}/50_{3}^{-}/50_{3}^{2-})$ ) and 60/30 $({\\mathsf C}{\\mathsf O}_{3}{\\mathsf-}/{\\mathsf C}{\\mathsf O}_{3}{\\mathsf-}^{2-})$ after Ar plasma milling for 5 to $15\\mathrm{\\min}$ to clean the surface adsorbed electrolytes. (Scale bars: $10~\\upmu\\mathrm{m}$ .) \n\nFurther, we performed Raman spectroscopy to investigate the fate of the $\\mathrm{NiS_{x}}$ interlayer underneath the NiFe-based catalyst by activating an $\\mathrm{NiS_{x}}$ -coated $\\mathrm{Ni}$ foam electrode under the same anodic activation process used for $\\mathbf{N}\\mathbf{i}^{3}$ . We observed strong sulfate vibrational modes (34) at ${\\sim}930\\mathrm{cm}^{-1}$ after the activation step (Fig. 4C), corroborated by TOF-SIMS mapping. Raman spectroscopy also revealed LDH [i.e., $\\upalpha$ phase- $\\cdot\\mathrm{\\tilde{Ni}}(\\mathrm{OH})_{2}]$ signatures with TOF-SIMs revealing both sulfate and carbonate ions. These results suggested the formation of a layer of LDH highly enriched with sulfate intercalants formed over $\\mathrm{NiS_{x}}$ , with abundant sulfate anions outweighing carbonate anions compared with the relative abundance of anions in the NiFe catalyst layer after the same anodic activation. For the activated $\\mathrm{Ni}^{3}$ anode, we concluded that the sulfate and carbonate cointercalated NiFe hydroxide catalyst layer together with the underlying sulfate-rich anodized $\\mathrm{NiS_{x}}$ layer were responsible for the high OER activity and corrosion resistance to chloride anions in seawater. The NiFe hydroxide layer exhibited higher OER activity than the $\\mathrm{NiS_{x}}$ (SI Appendix, Fig. S12) and synergized corrosion resistance with the underlying sulfate-rich $\\mathrm{Ni-Fe-NiS_{x}}$ interface. Without the electrodeposited NiFe layer, $\\mathrm{NiS_{x}/N i}$ was much less stable for electrolysis in the same salty electrolytes tested (SI Appendix, Fig. S7A). This was based on the fact that multivalent anions on hydrous metal oxides surfaces are well known to enhance cation selectivity and afford repulsion and blocking of chloride anions (13, 35, 36). The polyatomic anion (sulfate and carbonate)- passivated $\\mathrm{\\DeltaNi}^{3}$ layers played a critical role in corrosion inhibition by repelling chloride anions and not allowing them to reach and corrode the underlying structure. In addition to electrode \n\n1. Dresselhaus MS, Thomas IL (2001) Alternative energy technologies. Nature 414: 332–337. \n2. Dunn B, Kamath H, Tarascon JM (2011) Electrical energy storage for the grid: A battery of choices. Science 334:928–935. \n3. Dunn S (2002) Hydrogen futures: Toward a sustainable energy system. Int J Hydrogen Energy 27:235–264. \n4. Turner JA (2004) Sustainable hydrogen production. Science 305:972–974. \n5. Lewis NS, Nocera DG (2006) Powering the planet: Chemical challenges in solar energy utilization. Proc Natl Acad Sci USA 103:15729–15735. \n6. Walter MG, et al. (2010) Solar water splitting cells. Chem Rev 110:6446–6473. \n7. McCrory CCL, Jung S, Peters JC, Jaramillo TF (2013) Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J Am Chem Soc 135:16977–16987. \n8. Gong M, Wang D-Y, Chen C-C, Hwang B-J, Dai H (2015) A mini review on nickel-based electrocatalysts for alkaline hydrogen evolution reaction. Nano Res 9:28–46. \n9. Zhang J, Chen G, Müllen K, Feng X (2018) Carbon-rich nanomaterials: Fascinating hydrogen and oxygen electrocatalysts. Adv Mater 30:e1800528. \n10. Yang X, et al. (2015) Enabling practical electrocatalyst-assisted photoelectronchemical water splitting with earth abundant materials. Nano Res 8:56–81. \n11. Dionigi F, Reier T, Pawolek Z, Gliech M, Strasser P (2016) Design criteria, operating conditions, and nickel-iron hydroxide catalyst materials for selective seawater electrolysis. ChemSusChem 9:962–972. \n12. van de Krol R, Grätzel M (2012) Photoelectrochemical Hydrogen Production (Springer, New York). \n13. Sharma SK (2011) Green Corrosion Chemistry and Engineering: Opportunities and Challenges (Wiley, New York). \n14. El-Moneim AA, Kumagai N, Hashimoto K (2009) Mn-Mo-W oxide anodes for oxygen evolution in seawater electrolysis for hydrogen production. Mater Trans 50:1969–1977. \n15. Jiang N, Meng H-m (2012) The durability of different elements doped manganese dioxide-coated anodes for oxygen evolution in seawater electrolysis. Surf Coat Tech 206:4362–4367. \n16. Fujimura K, et al. (1999) Anodically deposited manganese-molybdenum oxide anodes with high selectivity for evolving oxygen in electrolysis of seawater. J Appl Electrochem 29:769–775. \n17. Gong M, et al. (2013) An advanced Ni-Fe layered double hydroxide electrocatalyst for water oxidation. J Am Chem Soc 135:8452–8455. \n18. Surendranath Y, Dinca M, Nocera DG (2009) Electrolyte-dependent electrosynthesis and activity of cobalt-based water oxidation catalysts. J Am Chem Soc 131:2615–2620. \n\ndesign, we also purposely added sulfate and other polyatomic anions in alkaline seawater electrolytes for electrolysis and also observed stabilization effects for $\\dot{\\mathbf{Ni}}^{3}$ and other OER anodes. Hence, careful design of anodes and electrolytes can fully solve the chloride corrosion problem and allow direct splitting of seawater into renewable fuels without desalination. \n\nIn summary, we have developed an $\\mathrm{NiFe/NiS_{x}/N i}$ anode for active and stable seawater electrolysis. The uniform electrodeposited NiFe was a highly selective OER catalyst for alkaline seawater splitting, while the $\\mathrm{NiS_{x}}$ layer underneath afforded a conductive interlayer and a sulfur source to generate a cation-selective polyatomic anion-rich anode stable against chloride etching/corrosion. The seawater electrolyzer could achieve a current density of $400\\mathrm{mA}/\\mathrm{cm}^{2}$ under $2.1\\mathrm{\\V}$ in real seawater or salt-accumulated seawater at room temperature, while only $1.72{\\mathrm{~V~}}$ was needed in industrial electrolysis conditions at $80~^{\\circ}\\mathrm{C}.$ Critically, the electrolyzer also showed unmatched durability. No obvious activity loss was observed after up to $^{1,000\\mathrm{h}}$ of a stability test. Such a device provides an opportunity to use the vast seawater on Earth as an energy carrier. \n\n# Materials and Methods \n\nThe materials and methods used in this study are described in detail in $S I$ Appendix, Materials and Methods. Information includes synthesis procedures of $\\mathsf{N i S}_{\\mathsf{x}}/\\mathsf{N i}$ foam, NiFe/Ni, ${\\mathsf{N i}}^{3}$ , Ni-NiO- $\\phantom{+}C\\mathsf{r}_{2}\\mathsf{O}_{3}$ cathode, perovskite solar cell fabrication procedure, electrochemical tests details, gas chromatography measurement details, and materials characterization details. \n\nACKNOWLEDGMENTS. We thank Michael R. Angell for helping to collect spectra data and Andrew Kiss, Doug Van Campen, and Dave Day for support at beamlines 2-2 and 6-2c of the Stanford Synchrotron Radiation Lightsource. This work was partially supported by US Department of Energy (DOE) Grant DE-SC0016165 and Natural Science Foundation of China, National Key Research and Development Project 2016YFF0204402 (Y.K. and X.S.). Part of this work was performed at the Stanford Nano Shared Facilities, supported by National Science Foundation Grant ECCS-1542152. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the US DOE, Office of Science, Office of Basic Energy Sciences under Contract DE-AC02-76SF00515. \n\n19. Esswein AJ, Surendranath Y, Reece SY, Nocera DG (2011) Highly active cobalt phosphate and borate based oxygen evolving catalysts operating in neutral and natural waters. Energy Environ Sci 4:499–504. \n20. Corrigan DA (1989) Effect of coprecipitated metal ions on the electrochemistry of nickel hydroxide thin films cyclic voltammetry in 1M KOH. J Electrochem Soc 136:723–728. \n21. Corrigan DA (1987) The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes. J Electrochem Soc 134:377–384. \n22. Gong M, Dai H (2014) A mini review of NiFe-based materials as highly active oxygen evolution reaction electrocatalysts. Nano Res 8:23–39. \n23. Trotochaud L, Young SL, Ranney JK, Boettcher SW (2014) Nickel-iron oxyhydroxide oxygen-evolution electrocatalysts: The role of intentional and incidental iron incorporation. J Am Chem Soc 136:6744–6753. \n24. Xie $\\scriptstyle{\\mathsf{Q}},$ et al. (2018) Layered double hydroxides with atomic-scale defects for superior electrocatalysis. Nano Res 11:4524–4534. \n25. Lu X, Zhao C (2015) Electrodeposition of hierarchically structured three-dimensional nickeliron electrodes for efficient oxygen evolution at high current densities. Nat Commun 6:6616. \n26. Gong M, et al. (2015) Blending Cr2O3 into a NiO-Ni electrocatalyst for sustained water splitting. Angew Chem Int Ed Engl 54:11989–11993. \n27. Bodner M, Hofer A, Hacker V (2015) H2 generation from alkaline electrolyzer. Wiley Interdiscip Rev Energy Environ 4:365–381. \n28. Bush KA, et al. (2018) Compositional engineering for efficient wide band gap perovskites with improved stability to photoinduced phase segregation. ACS Energy Lett 3:428–435. \n29. Luo J, et al. (2014) Water photolysis at $12.3\\%$ efficiency via perovskite photovoltaics and Earth-abundant catalysts. Science 345:1593–1596. \n30. Louie MW, Bell AT (2013) An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen. J Am Chem Soc 135:12329–12337. \n31. Vorsina IA, Mikhailov YI (1996) Kinetics of thermal decomposition of ammonium persulfate. Russ Chem Bull 45:539–542. \n32. Weng LT, Bertrand P, Stone-Masui JH, Stone WEE (1994) ToF SIMS study of the desorption of emulsifiers from polystyrene latexes. Surf Interface Anal 21:387–394. \n33. Zhou D, et al. (2018) Effects of redox-active interlayer anions on the oxygen evolution reactivity of NiFe-layered double hydroxide nanosheets. Nano Res 11:1358–1368. \n34. Tomikawa K, Kanno H (1998) Raman study of sulfuric acid at low temperatures. J Phys Chem A 102:6082–6088. \n35. Sakashita M, Sato N (1979) Ion selectivity of precipitate films affecting passivation and corrosion of metals. Corrosion 35:351–355. \n36. Sakashita M, Sato N (1977) The effect of molybdate anion on the ion-selectivity of hydrous ferric oxide films in chloride solutions. Corros Sci 17:473–486. " + }, + { + "id": "10.1021_jacs.8b13091", + "DOI": "10.1021/jacs.8b13091", + "DOI Link": "http://dx.doi.org/10.1021/jacs.8b13091", + "Relative Dir Path": "mds/10.1021_jacs.8b13091", + "Article Title": "Tailoring Passivation Molecular Structures for Extremely Small Open-Circuit Voltage Loss in Perovskite Solar Cells", + "Authors": "Yang, S; Dai, J; Yu, ZH; Shao, YC; Zhou, Y; Xiao, X; Zeng, XC; Huang, JS", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Passivation of electronic defects at the surface and grain boundaries of perovskite materials has become one of the most important strategies to suppress charge recombination in both polycrystalline and single-crystalline perovskite solar cells. Although many passivation molecules have been reported, it remains very unclear regarding the passivation mechanisms of various functional groups. Here, we systematically engineer the structures of passivation molecular functional groups, including carboxyl, amine, isopropyl, phenethyl, and tert-butylphenethyl groups, and study their passivation capability to perovskites. It reveals the carboxyl and amine groups would heal charged defects via electrostatic interactions, and the neutral iodine related defects can be reduced by the aromatic structures. The judicious control of the interaction between perovskite and molecules can further realize grain boundary passivation, including those that are deep toward substrates. Understanding of the underlining mechanisms allows us to design a new passivation molecule, D-4-tert-butylphenylalanine, yielding high-performance p-i-structure solar cells with a stabilized efficiency of 21.4%. The open-circuit voltage (V-OC) of a device with an optical bandgap of 1.57 eV for the perovskite layer reaches 1.23 V, corresponding to a record small V-OC deficit of 0.34 V. Our findings provide a guidance for future design of new passivation molecules to realize multiple facets applications in perovskite electronics.", + "Times Cited, WoS Core": 644, + "Times Cited, All Databases": 674, + "Publication Year": 2019, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000464769000030", + "Markdown": "# Tailoring Passivation Molecular Structures for Extremely Small Open-Circuit Voltage Loss in Perovskite Solar Cells \n\nShuang Yang,†,‡ Jun Dai,§ Zhenhua Yu,† Yuchuan Shao,† Yu Zhou,† Xun Xiao,† Xiao Cheng Zeng,§ and Jinsong Huang\\*,†,‡ \n\n†Department of Applied Physical Sciences, University of North Carolina, Chapel Hill, North Carolina 27599, United States ‡Department of Mechanical and Materials Engineering and ${}^{\\S}\\mathrm{D}$ epartment of Chemistry, University of NebraskaLincoln, Lincoln, Nebraska 68588, United States \n\n\\*S Supporting Information \n\nABSTRACT: Passivation of electronic defects at the surface and grain boundaries of perovskite materials has become one of the most important strategies to suppress charge recombination in both polycrystalline and singlecrystalline perovskite solar cells. Although many passivation molecules have been reported, it remains very unclear regarding the passivation mechanisms of various functional groups. Here, we systematically engineer the structures of passivation molecular functional groups, including carboxyl, amine, isopropyl, phenethyl, and tert-butylphenethyl groups, and study their passivation capability to perovskites. It reveals the carboxyl and amine groups would heal charged defects via electrostatic interactions, and the neutral iodine related defects can be reduced by the aromatic structures. The judicious control of the interaction between perovskite and molecules can further realize grain boundary passivation, including those that are deep toward substrates. Understanding of the underlining mechanisms allows us to design a new passivation molecule, D-4-tert-butylphenylalanine, yielding high-performance p-i-structure solar cells with a stabilized efficiency of $21.4\\%$ . The open-circuit voltage $(V_{\\mathrm{OC}})$ of a device with an optical bandgap of $1.57\\mathrm{eV}$ for the perovskite layer reaches $1.23\\mathrm{V}_{\\mathrm{i}}$ corresponding to a record small $V_{\\mathrm{OC}}$ deficit of $0.34\\mathrm{V}$ . Our findings provide a guidance for future design of new passivation molecules to realize multiple facets applications in perovskite electronics. \n\n![](images/0d5e751282277e9eff7fbf834bab15a14104355bb71e58faa69cc0def0eccc9c.jpg) \n\n# INTRODUCTION \n\nHalide perovskite solar cells (PSCs) are one of the most promising next-generation photovoltaic technologies that can potentially drive down the cost of clean and renewable solar energy conversion. The achieved power conversion efficiencies (PCEs) are already over $24\\%$ for the solution-processed PSCs which are low-cost and can be scaled up. The polycrystalline perovskite films in the state-of-the-art PSCs have a large number of defects, including amorphous regions, surface defects, and grain boundaries, which are sensitive to material process.2−6 Though these materials are reported to have more benign defects compared to other semiconductors,7 the defects at film surface and grain boundaries still induce a high density of trap states which dramatically impair the efficiency and stability of PSCs.8 A faster photoluminescence decay at grain boundaries or unpassivated perovskite film surfaces is indicative of fast nonradiative charge recombination and the electronically defective nature of grain boundaries and film surfaces.9 \n\nLike all other inorganic PV materials, passivation of electronic surface trap states has been shown to be also necessary to reduce the charge recombination rate and enhance the efficiency of PSCs.10,11 However, this was not obvious to the society when these materials were initially treated as organic dyes. The passivation concept was first introduced by us in p-i-n structured PSCs with fullerene as the electron transport layer.12,13 S ince then, a number of passivation molecules have been reported to directly neutralize the surface charges or dangling bonds to annihilate the corresponding electronic traps. For example, the undercoordinated $\\mathrm{\\DeltaPb}$ ions can be passivated by bonding with Lewis base molecules which can donate electrons or share their electron pairs, such as $n$ -trioctylphosphine oxide.14 In addition, some electronic trap states can be reduced by Lewis acid molecules by acceptation of one electron from the Lewis based type defects on perovskite surface, such as phenyl-C61-butyric acid methyl ester (PCBM).12,13 The surface charged sites can also be neutralized by charged molecules or ions, such as positively charged phenethylammonium, negatively charged chloride ion, and choline chloride, which is a zwitterion.10,15,16 \n\nAlthough numerous approaches have been employed, the well passivation of surface electronic defects at grain boundaries still remains a great challenge because of the complexity and diversity of the surface defects that most of the electronic materials can only passivate one or two kinds of trap states. It is very unclear so far what functional groups are playing the passivation roles among passivation molecules with complicated chemical structures. Another critical issue is that most of the passivation methods are based on the surface coating or treatment of the top surface, which cannot effectively passivate the traps from inner grain boundaries toward the substrates within the perovskite films. \n\nIn this work, we systematically study the influence of molecular structure of passivation molecules on their passivation effect to hybrid perovskites. It is found that some small sized passivation molecules can spontaneously distribute at grain boundaries, which dramatically enhance the defect passivation at grain boundaries of hybrid perovskites. Through the analysis, we discovered a new type of amino acid passivation molecule, D-4-tert-butylphenylalanine (D4TBP), which combines all effective passivation groups and most efficiently passivate perovskite defects. As a proof of concept, we show that D4TBP passivated p-i-n solar cell (Figure 1a) has a record low $V_{\\mathrm{OC}}$ loss $(E_{\\mathrm{g}}/q\\stackrel{-}{-}V_{\\mathrm{OC}},E_{\\mathrm{g}}$ is the bandgap of perovskite) of only $0.34~\\mathrm{eV}$ . \n\n# RESULTS AND DISCUSSION \n\nThe ionic nature of hybrid perovskites determines that their defects are charged. The defects with negative or positive charges illustrated in Figure 1b have been experimentally and theoretically studied.17,18 These surface charged species typically provide extra energy levels within the forbidden gap which behave as charge traps. We first study whether one type of defect, positively charged or negatively charged, dominates on the perovskite surface and whether passivation of one of them is more effective in enhancing device efficiency. To neutralize these charged defects, phenylpropionic acid (PA) with a carboxyl group and phenethylamine (PEA) with an amine group were first used, which are expected to combine with positively and negatively charged defects, respectively (Figure 1c). Phenylalanine (PAA) with both carboxyl and amine groups was also chosen in this study and may passivate both negatively and positively charged defects. All passivation layers were formed by spin-coating of solution of the passivation molecules on the surfaces of perovskite films (see details in the Experimental Section). This avoids the complication induced by perovskite morphology changes in the case of mixing the additives in the perovskite solution, though mixing them directly is preferred in fabrication to reduce one step. It should be noted that passivation molecules may also penetrate into the polycrystalline films along the grain boundaries after spin-coating as observed in our previous results.12 \n\n![](images/e31bcb0268610dd3b42c988fb16db644130aa9fe4eee71fa983005de6c9bb289.jpg) \nFigure 1. (a) Device structure of planar heterojunction perovskite solar cells. (b) Schematic illustration of surface charged defects. (c) Chemical structure of passivation molecules with marked amino (blue) and carboxyl (red) groups. (d) PL and (e) TRPL spectra of perovskite films with different passivation layers. (f) $J{-}V$ curves and $\\mathsf{\\bar{(g)}}$ statistics of $V_{\\mathrm{OC}}$ distribution of perovskite solar cells with different passivation layers. \n\nTo assess the passivation effect of different molecules, we measured the steady-state photoluminescence (PL) and timeresolved photoluminescence (TRPL) decay of the films and current density−voltage $\\left(J-V\\right)$ characteristics of the devices with different passivation layers. Triple-cation perovskite with a chemical formula of $\\mathrm{Cs_{0.05}F A_{0.81}M A_{0.14}P b I_{2.55}B r_{0.45}}$ in precursors was employed in this study. An excitation light of $532~\\mathrm{nm}$ was used for the steady-state PL measurement to probe the surface properties, which has a penetration length of $80\\ \\mathrm{nm},$ , much less than the thickness of the perovskite films ( ${\\sim}500$ nm). As shown in Figure 1d, the PL intensity of PA and PEA films is about 2.3 and 2.9 times larger compared with that of the pristine one, indicating that the carboxyl and amine groups could passivate defects with specific charges. The PL decay of the perovskite films in Figure 1e shows biexponential decays with a fast and a slow component. The short lifetime $\\tau_{1}$ is a decay component related to the charge trapping process and the long lifetime $\\tau_{2}$ as a component of the detrapping process or carrier recombination process.19 The PL decay of pristine film without any passivation is dominated by the charge trapping process; i.e., over $90\\%$ of excess charge carriers are trapped immediately after generation. The $\\tau_{1}$ of perovskite films increases from 1.51 ns to 4.42 and 4.24 ns upon the passivation of PA and PEA, respectively (Table S1). In addition, the PL decay in the PA and PEA treated samples is dominated by the long decay process, implying charge trapping in PA and PEA films is suppressed. Amines and carboxylic acids have been widely used as the ligands in the synthesis of perovskite nanocrystals, which can adsorb onto different surface sites and generate high PL quantum yields over $80\\%$ .20,21 Previous literatures have also demonstrated the good passivation effect of PEA molecules in solar cells.14,23 In solution, amino or carboxyl groups readily ionize with positive and negative charges, respectively; we speculate that they may passivate different types of defects present on perovskite film surface, and thus combination of them would synergistically passivate more defects. To verify this, we used the PA and PEA mixture $\\left(\\mathrm{PA+PEA}\\right)$ as the passivation layer. As expected, the perovskite films treated by a PA−PEA mixture have shown a much larger PL intensity and longer PL lifetimes $'_{\\tau_{1}}=12.50$ ns, $\\tau_{2}=780.61$ ns), which confirms the synergetic passivation effect among these two passivation function groups on different defect sites on perovskites. We move a future step to use a single molecule, PAA, to replace the PA−PEA mixture in passivation because PAA has the combination of phenethyl, amine, and carboxyl functional groups. As expected, PAA passivated perovskite films also benefit from the passivation effect of both functional groups, as evidenced by the strong, blue-shifted PL signal compared with $\\mathrm{PA}{+}\\mathrm{PEA}$ sample and prolonged $\\tau_{1}$ and $\\tau_{2}$ of 9.80 and $737.33\\ensuremath{\\mathrm{~\\ns~}}$ , respectively, comparable to those of the sample treated by the PA−PEA mixture. \n\nThe passivation of defects should considerably impact the open circuit voltage $(V_{\\mathrm{OC}})$ of the devices due to their enhanced carrier concentration under light irradiation by uplifting the quasi-Fermi level splitting. To evaluate it, $\\mathtt{p-i-n}$ structure solar cells were fabricated with schematic structure of poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine](PTAA)/ perovskite/passivation layer/fullerene $\\left(\\mathrm{C}_{60}\\right)/2,9$ -dimethyl-4,7- diphenyl-1,10-phenanthroline (BCP)/copper $\\mathrm{{(Cu)}}$ , as shown in Figure 1a. The pristine champion device shows a shortcircuit current density $(J_{\\mathrm{SC}})$ of $22.40\\mathrm{\\mA\\cm^{-2}}$ , a $V_{\\mathrm{OC}}$ of 1.08 ${\\mathrm{v}},$ a fill factor (FF) of 0.788, and a higher PCE of $19.1\\%$ (Figure 1f). Solar cells based on PA and PEA layers exhibited improved average $V_{\\mathrm{OC}}$ of 1.10 and $1.11\\mathrm{V}$ and PCE of 19.0 and $19.2\\%$ , respectively, compared to that of the pristine device (Figure $_{1\\mathrm{g}}$ and Table S2). The reduction of surface defects will lead to higher density of photogenerated charges under given illumination and therefore provide larger quasi-Fermi level splitting and $V_{\\mathrm{OC}}$ values. Mixing PA and PEA gives a similar passivation effect with PAA, which is consistent with PL and TRPL studies and again showing the synergetic passivation of the functional groups. A high average $V_{\\mathrm{OC}}$ of $1.15\\mathrm{~V~}$ was achieved in the devices with mixed PA and PEA additives. When we used PAA with both carboxyl and amino groups as the passivation layer, the champion device delivered a $J_{\\mathrm{SC}}$ of $22.6\\dot{2}~\\mathrm{mA}~\\mathrm{cm}^{-2}$ , a $V_{\\mathrm{OC}}$ of $1.15\\mathrm{V}_{i}$ , a FF of 0.790, and a higher PCE of $20.6\\%$ (Figure 1f). The average $V_{\\mathrm{OC}}$ of PAA devices is $1.14\\mathrm{V},$ , which is consistent with the PL results. \n\nIn addition to the charged molecules, functional groups with neutral and nonpolar structures, such as fullerene or conjugated organics, also have passivation capability through the coordination interactions with perovskite surface.1 Previous X-ray photoelectron spectroscopy (XPS) studies have revealed the existence of neutral species, such as unsaturated ${\\mathrm{Pb}}^{0}$ which appeared on the surface of hybrid perovskite films, because of the oxidation of $\\mathrm{I}^{-}$ into $\\mathrm{I}_{2}$ .23−25 Moreover, the existence of residual iodine will introduce deep trap states by the formation of I interstitials or $\\mathrm{I{-}P b}$ antisites according to the previous theoretical study.26,27 Zhang et al. further validated the electronically acceptor nature of these iodine-related defects by surface photovoltage (SPV) measurements.28 We thus speculate that an electron-donating aromatic group may reduce the acceptor type trap states induced by dissociative iodine. A PAA molecule has six $\\pi$ electrons delocalized in the aromatic benzene ring which may act as Lewis base to form Lewis adducts with specific Lewis-type defects. Here, we compared three amino acid molecules, valine (VA), PAA with isopropyl, phenyl, and tert-butylphenethyl groups, respectively, whose chemical structures are shown in Figure 2a. By comparison of the passivation effect of VA and PAA treated films, the function of aromatic rings can be determined because the only difference of PAA and VA is the presence of an aromatic ring in PAA. \n\n![](images/0c4d8cd7ab0f71bde7d10429778c4ea748a20bdeacc35c640e5c1e67468a7360.jpg) \nFigure 2. (a) Chemical structure of passivation molecules with marked alkyl and phenyl groups. (b) Photograph of iodine dissolved in the hexane solution without and with $20\\%$ toluene $\\left(\\mathbf{v}{:}\\mathbf{v}\\right)$ . The concentration of iodine is $1~\\mathrm{mg/mL}$ . (c) UV−vis absorption spectra of iodine dissolved in different solvents. (d) PL and (e) TRPL spectra of perovskite films with different passivation layers. (f) $J{-}V$ curves and $(\\mathbf{g})$ statistics of $V_{\\mathrm{OC}}$ distribution of perovskite solar cells with different passivation layers. \n\nWe used $\\mathrm{I}_{2}$ −toluene to explore the possible interaction of $\\mathrm{I}_{2}$ and benzene rings. The iodine−hexane solution has a purple color, as shown in Figure 2b, which is the same color with solid iodine. When we added $20~\\mathrm{vol}~\\%$ toluene in the solution, the color of the iodine solution became dark red. As shown in Figure 2c, the absorption spectrum of this mixed solution shows the emergence of an absorption peak around $307~\\mathrm{nm}$ , which suggests the formation of benzene−iodine complexes as a result of the electron-donating property of the benzene ring.29 Thus, aromatic rings could reduce or capture the trace amount of $\\mathrm{I}_{2}$ existing as electronic defects in perovskites. This is supported by the steady-state and transient PL study. Although the PL intensity of VA is enhanced to ${\\sim}3.2$ times larger than pristine sample, it is still lower than the PAA sample ( ${\\widetilde{\\cdot}}{\\widetilde{4.4}}$ times), which implies the phenethyl group is also involved in surface passivation (Figure 2d). Moreover, the PL decay process in the PAA passivated films is much slower than in VA passivated films, as shown in Figure 2e, implying that aromatic structure reduced the charge capture rate by deep traps, most likely due to reduced density of excess-iodineinduced electronic trap states at the surface. \n\nOn the basis of the understanding of passivation mechanism, we design a new passivation molecule D4TBP. The chemical structure in Figure 2a shows that it contains all three passivation functional groups, i.e., 4-tert-butylphenyl, amine, and carboxyl ones. When D4TBP was used, the charge recombination lifetime of perovskite films is increased to $930.30~\\mathrm{ns}$ , and the charge-trapping process becomes negligible. There is one more tert-butyl group on the benzene ring in D4TBP compared with the PAA molecule, which may strengthen the electron-donating capability of the benzene ring and thus better passivate Lewis acid type surface defects, such as iodine and undercoordinated $\\mathrm{Pb}^{2+}$ . Figure 2f shows the $J{-}V$ characteristics without and with different passivation layers. The champion device with the D4TBP passivating layer exhibits excellent performance with a $J_{\\mathrm{SC}}$ of $22.51\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ , a $V_{\\mathrm{OC}}$ of $1.16~\\mathrm{V},$ , and a FF of 0.803, yielding a PCE of $21.0\\%$ , greatly outperforming the control cell. As exhibited in Figure ${2}\\mathrm{g},$ the average $V_{\\mathrm{OC}}$ of VA, PAA, and D4TBP is 1.11, 1.14, and $1.16\\mathrm{V},$ respectively, which again agree with the PL and TRPL results. \n\nThe aforementioned results have demonstrated the molecular engineering strategy to reduce the surface electronic defects. We then focus on another question: how to more effectively passivate the grain boundaries in polycrystalline perovskite films in addition to the top surfaces. If the passivation molecules are used as additive, they could be adsorbed onto the surfaces as well as the grain boundaries during the crystallization and growth process, which may enable a full coverage of grains. Here we added around $7.5\\mathrm{mM}$ of additives into perovskite solution and evaluated their passivation function. These additives do not cause the formation of impure phases, as shown in the X-ray diffraction (XRD) pattern in Figure S1. We do understand these additives or ligands would hinder grain growth and thus reduce the grain size, if they strongly bind to the crystal surface. Actually, when PA and PEA are added, the grain size of the resulting perovskite films reduces obviously from $312.0\\pm52.9\\ \\mathrm{nm}$ to be $138.7\\pm33.9$ and $99.3\\pm27.8~\\mathrm{nm},$ , respectively (Figure 3a and Figure S2). The grain sizes of VA, PAA, and D4TBP samples are $284.8~\\pm~57.4$ , $267.3~\\pm~49.0.$ , and $287.1~\\pm~46.2~\\mathrm{nm},$ respectively, as shown in Figure 3b. We speculate the amine group in amino acids may not participate into the perovskite crystal due to the steric effect of the large molecules.30 Nevertheless, amino acids should be excluded from perovskite crystals to grain boundary areas or interfaces, and passivation can be realized by reasonably tuning the adsorption and desorption behavior of passivation molecules without significantly reducing grain size. Here we performed PL measurement to identify the position of D4TBP molecules when incorporated as additive, and the setup of the experiment is shown in Figure 3c. The spontaneous radiative recombination via trap states typically resulted a red-shifted emission compared with that from the band-edge transition. Passivation of these trap states can blue-shift the PL peak. As shown in Figure 3d, the perovskite film with a D4TBP layer displayed a strong PL peak at $769\\ \\mathrm{nm}$ at the top side, whereas the PL emission at the glass side red-shifted to $775~\\mathrm{nm}$ with a much weaker signal. This suggests the surface defects are effectively passivated by the D4TBP layer on only the top side by the spin-coating method. However, the PL peak was independent of the incident light directions for the films passivated by the additive route, illustrating the top and bottom surfaces have similar optical properties. Therefore, it is believed that the D4TBP would be spontaneously excluded and distributed at the grain boundaries of perovskite when introduced as additives. \n\n![](images/93767c7d15816d5dee4cc9a95d63f09f9c97f5e558b2b1dc442b779fbc97dbd0.jpg) \nFigure 3. (a) Surface SEM images of perovskite films deposited with different passivation additives. The concentration of all additives is 7.5 mM. (b) Grain size distribution of the perovskite films. Insets show the adsorption of monodentate and bidentate ligands affected by the steric effects. (c) Schematic of the PL measurement of the grain boundary passivated perovskite films. An excitation light of $532~\\mathrm{nm}$ was used to probe the PL property and distribution of passivation molecules. (d) PL spectra of perovskite films with added D4TBP as addictive (AD) and top D4TBP passivation layer by spin-coating (SC) recorded under the excitation light from either air side (AS) or glass side (GS). \n\nWe have shown the excellent passivation effect of D4TBP molecules with a prolonged PL lifetime and very low $V_{\\mathrm{OC}}$ deficit in solar cells, which could combine the advantages of 4- tert-butylphenyl, amine, and carboxyl functional groups. We then optimized the fabrication of perovskite solar cells by using D4TBP as additive to passivate perovskite grains. The concentration of D4TBP in perovskite solution was varied from 2.5 to $10\\ \\mathrm{mM}.$ . Figure 4a shows the $J{-}V$ curves of solar cells with varied D4TBP concentration. The maximum PCE increased considerably from $19.7\\%$ to 20.6, 20.8, and $21.4\\%$ for the devices with 2.5, 5.0, and $7.5\\ \\mathrm{mM}$ D4TBP in perovskite solution, which may be due to more complete wrapping of perovskite grains by D4TBP molecules. The PCE subsequently decreased to $17.4\\%$ at $10\\ \\mathrm{mM}$ D4TBP in perovskite solution (Table S3). Likewise, the average $V_{\\mathrm{OC}}$ is 1.08, 1.13, 1.15, 1.20, and $1.19{\\mathrm{~V~}}$ for D4TBP concentrations of 0, 2.5, 5.0, 7.5, and $10.0\\ \\mathrm{mM},$ , respectively (Figure 4b). No obvious photocurrent hysteresis is identified in these devices (Figure 4c and Table S4). The histogram of the PCEs in Figure S3 shows an average efficiency of $20.55~\\pm~0.43\\%$ under simulated AM1.5G illumination. The $J_{\\mathrm{SC}}$ value obtained from external quantum efficiency (EQE) spectra in Figure S4 is calculated to be 22.1 mA $\\mathrm{cm}^{-2}$ , coinciding with the $J{-}V$ results. The absorption edge determined by the onset of EQE spectra is ${\\sim}1.57\\ \\mathrm{eV}$ (Figure S5). The champion device was held at maximum power point (MPP) to track the power output. As shown in Figure 4d, the photocurrent stabilized within seconds to be $20.7\\mathrm{mA}\\mathrm{cm}^{-2}$ with a PCE of $21.4\\%$ . The highest achieved $V_{\\mathrm{OC}}$ in these devices reaches $1.23\\mathrm{V}_{;}$ , with a PCE of $21.12\\%$ (Figure \n\n![](images/2003411ab43bf3e79c9c11db159357d292bb67270b16709e7cbe8c612dfed249.jpg) \nFigure 4. (a) $J{-}V$ characteristics and (b) $V_{\\mathrm{OC}}$ distribution of the perovskite solar cells with different concentrations of D4TBP in perovskite precursor solution. (c) $J{-}V$ curves of the champion perovskite solar cell with D4TBP passivation with forward and reverse scan. (d) Steady-state measurement of $J_{\\mathrm{SC}}$ and PCE of the champion D4TBP perovskite solar cells. (e) PL and (f) TRPL spectra of pristine and D4TBP perovskite films. $\\mathbf{\\eta}(\\mathbf{g})$ TPV curves and (h) trap density in the pristine and D4TBP perovskite devices. D4TBP is added as additive to passivate the perovskites film and devices. \n\nS6a). The $V_{\\mathrm{OC}}$ was confirmed by measuring the stabilized $V_{\\mathrm{OC}},$ as shown in Figure S6b. The $V_{\\mathrm{OC}}$ loss is thus only $0.34~\\mathrm{V},$ which is the lowest $V_{\\mathrm{OC}}$ loss reported, implying a very effective defect passivation of perovskite surface and grain boundaries. \n\nThe good passivation effect of D4TBP was also evidenced by the steady-state PL spectra that D4TBP sample possess ${\\sim}5.7$ times stronger PL emission with about $7\\ \\mathrm{nm}$ blue-shift compared with the pristine sample (Figure 4e). Furthermore, the PL lifetime of the D4TBP sample is further elongated so that the $\\tau_{1}$ and $\\tau_{2}$ improved to be 17.71 and 1280.71 ns, respectively, which is even longer than the spin-casted sample (Figure 4f). Devices were then irradiated under AM 1.5G simulated illumination and laser pulses $\\left(337\\ \\mathrm{nm},\\ 4\\ \\mathrm{ns}\\right)$ to measure the decay of transient photovoltage signals. As seen in Figure $^{4}\\mathrm{g},$ the charge-recombination lifetime was increased from $0.50~\\mu s$ in the pristine device to $1.71~\\mu s$ for D4TBPtreated device. As a well-established method in thin film photovoltaics, thermal admittance spectroscopy was operated to measure the trap density of states (tDOS) of the control and D4TBP devices. Figure 4h describes that the D4TBP device had the lower tDOS almost over the whole trap depth region. The density of shallower trap states $(0.3\\mathrm{-}0.5~\\mathrm{eV})$ of D4TBP device is about 1 order of magnitude lower than that of the control device. Our previous characterizations have disclosed that the shallow traps are mainly located at the grain boundaries.22 We therefore infer that the trap states are effectively reduced upon the D4TBP passivation. We have shown the addictive route can significantly reduce the density of trap states and enhance the PL intensities of perovskite films, with apparent better photovoltaic parameters compared with that based on spin-coating strategy. In fact, the spatial distribution of D4TBP molecules would be dependent on the chemical methods when incorporated. The D4TBP addictive is thought to be enriched at grain boundaries as evidenced by their independence of high PL intensities on both sides, whereas the film passivated by spin-coating only passivates the top side. The good molecular passivation effect of grain boundaries, other than only top surface, explains the extreme low $V_{\\mathrm{OC}}$ deficit of $0.34\\mathrm{~V~}$ of the passivated device. \n\n# CONCLUSION \n\nIn summary, we demonstrated a simple, generic strategy to p-in structure solar cells the electronic defects of the hybrid perovskite films. Multiple kinds of defects, such as the ionic or neutral ones, have been addressed based on the ionic and coordination interactions with certain molecular structures (Figure 5). We further enabled the grain boundary passivation by controlling the structure of small molecules. The defect passivation reduces the $V_{\\mathrm{OC}}$ deficit of the $\\mathrm{{\\ttp}-i-n}$ -structured device to $0.34\\mathrm{~V~}$ and boosts the efficiency to $21.4\\%$ . Our finding provides new guidelines for surface molecular modulation of hybrid perovskites. \n\n![](images/8683beee3da4dfddcb5904774b79bbfda8c599c2611f9462273ea3e30ba8c885.jpg) \nFigure 5. Schematic illustration of the origin of D4TBP passivation effect on different defect sites. \n\n# EXPERIMENTAL SECTION \n\nDevice Fabrication. Patterned ITO glass substrates were first cleaned by ultrasonication with soap, acetone, and isopropanol. The hole transport layer poly(bis(4-phenyl)(2,4,6-trimethylphenyl)amine) (PTAA) with a concentration of $2~\\mathrm{mg~mL^{-1}}$ dissolved in toluene was spin-coated at the speed of $4000~\\mathrm{rpm}$ for $35\\mathrm{~s~}$ and then annealed at $100~^{\\circ}\\mathrm{C}$ for $10~\\mathrm{min}$ . Before depositing perovskite films, the PTAA film was prewetted by spinning $80~\\mu\\mathrm{L}$ of DMF at $4000~\\mathrm{rpm}$ for $15\\mathrm{~s~}$ to improve the wetting property of the perovskite precursor solution. The perovskite precursor solution composed of mixed cations (lead (Pb), cesium $\\scriptstyle(\\mathbf{C}\\mathbf{s})$ , formamidinium (FA), and methylammonium (MA)) and halides (I and Br) was dissolved in mixed solvent $\\left(\\mathrm{DMF/DMSO}\\ =\\ 4{:}1\\right)$ with a chemical formula of $\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.81^{-}}$ $\\mathrm{MA}_{0.14}\\mathrm{PbI}_{2.55}\\mathrm{Br}_{0.45}.$ 13 Then $80\\mu\\mathrm{L}$ of precursor solution was spun onto PTAA at $2000~\\mathrm{rpm}$ for 2 s and $4000~\\mathrm{rpm}$ for $20\\ \\mathsf{s},$ and the film was quickly washed with $130~\\mu\\mathrm{L}$ of toluene at $18\\mathrm{~s~}$ during spin-coating. Subsequently, the sample was annealed at $65~^{\\circ}\\mathrm{C}$ for $10~\\mathrm{min}$ and 100 $^{\\circ}\\mathrm{C}$ for $10~\\mathrm{min}$ . For the surface passivation, the passivation molecules were dissolved in isopropanol with the concentration of $1\\mathrm{mg/mL}$ and was spun at $4000~\\mathrm{rpm}$ for $30~\\mathsf{s}.$ . The films were then annealed at 100 $^{\\circ}\\mathrm{C}$ for $10\\ \\mathrm{min}$ . For the grain boundary passivation, molecules were directly added into the perovskite precursor as additive with the concentration between 2.5 and $10~\\mathrm{mM}.$ . Hydroiodic acid (HI, 57 wt $\\%$ in water) was added by equal molar ratio with the passivation molecules in all samples. The devices were finished by thermally evaporating C60 $30\\ \\mathrm{nm},$ ), BCP $\\mathrm{~\\AA~}^{\\prime}8\\ \\mathrm{nm},$ ), and copper ( $\\cdot140\\ \\mathrm{nm}$ ) in sequential order. \n\nCharacterization. Crystallographic information for the assynthesized crystals was obtained by a Rigaku D/Max-B X-ray diffractometer with Bragg−Brentano parafocusing geometry, a diffracted beam monochromator, and a conventional cobalt target X-ray tube set to $40\\mathrm{kV}$ and $30~\\mathrm{mA}.$ . The morphology and structure of the samples were characterized by Quanta 200 FEG environmental scanning electron microscope. Optical absorption spectra were measured by means of an Evolution 201/220 UV/vis spectrophotometer. Time-resolved photoluminescence (TRPL) was performed on the perovskite films grown on varied substrates by a Horiba DeltaPro fluorescence lifetime system, which equipped with a DeltaDiode (DD-405) pulse laser diode with wavelength of 404 nm. The laser excitation energy in the measurement was $20\\textrm{\\textmu m}$ pulse−1. The PL spectrum was recorded by a iHR320 photoluminescence spectrometer at room temperature. The excitation source for PL measurement is a ${\\mathfrak{s}}32\\ \\mathrm{nm}$ green laser with an intensity of $10\\mathrm{mW}\\mathrm{cm}^{-2}$ from Laserglow Technologies. The sample for PL and TRPL measurements is perovskite layer on glass. The $J{-}V$ analysis of solar cells was performed using a solar light simulator (Oriel 67005, 150 W), and the power of the simulated light was calibrated to 100 $\\mathrm{m}\\mathrm{W\\cm}^{-2}$ with a silicon (Si) diode (Hamamatsu S1133) equipped with a Schott visible-color glass filter (KG5). All cells were measured using a Keithley 2400 source meter with scan rate of $0.1\\mathrm{~V~s~}^{-1}$ . The steady-state PCE was measured by monitoring current with the largest power output bias voltage and recording the value of the photocurrent. External quantum efficiency curves were characterized with a Newport QE measurement kit by focusing a monochromatic beam of light onto the devices. The tDOS of solar cells was derived from the frequency-dependent capacitance $(C{-}f)$ and voltagedependent capacitance $({\\bar{C}}{-}V)$ , which were obtained from the thermal admittance spectroscopy (TAS) measurement performed by a LCR meter (Agilent E4980A). The transient photovoltage was measured under 1 sun illumination. An attenuated UV laser pulse (SRS NL 100 nitrogen laser) was used as a small perturbation to the background illumination on the device. The laser-pulse-induced photovoltage variation and the $V_{\\mathrm{OC}}$ are produced by the background illumination. The wavelength of the ${\\bf N}_{2}$ laser was $337~\\mathrm{nm}$ , the repeating frequency was ${\\sim}10~\\mathrm{Hz},$ and the pulse width was $<3.5~\\mathrm{ns}$ . \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/jacs.8b13091. \n\nAdditional XRD patterns, SEM images, PCE distribution, EQE spectra, PL lifetimes and photovoltaic performances of the devices (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author \n$^{*}\\mathrm{E}$ -mail: jhuang@unc.edu. \nORCID \nShuang Yang: 0000-0002-8244-3002 \nXun Xiao: 0000-0002-9810-2448 \nXiao Cheng Zeng: 0000-0003-4672-8585 \nJinsong Huang: 0000-0002-0509-8778 \nNotes \nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work is financially supported by Air Force Office of Scientific Research (AFOSR) (Grant A9550-16-1-0299) and National Science Foundation under Award DMR-1420645. \n\n# REFERENCES \n\n(1) National Renewable Energy Laboratory, Best research-cell efficiencies chart; https://www.nrel.gov/pv/assets/pdfs/pvefficiencies-07-17-2018.pdf. (2) Zhou, H.; Chen, $\\mathrm{Q.;}$ Li, G.; Luo, S.; Song, T.; Duan, H.-S.; Hong, Z.; You, J.; Liu, Y.; Yang, Y. Interface engineering of highly efficient perovskite solar cells. Science 2014, 345, 542−546. (3) Shin, S. S.; Yeom, E. J.; Yang, W. S.; Hur, S.; Kim, M. G.; Im, J.; Seo, J.; Noh, J. H.; Seok, S. I. Colloidally prepared La-doped ${\\tt B a S n O}_{3}$ electrodes for efficient, photostable perovskite solar cells. Science 2017, 356, 167−171. (4) Saliba, M.; Matsui, T.; Domanski, K.; Seo, J.-Y.; Ummadisingu, A.; Zakeeruddin, S. M.; Correa-Baena, J.-P.; Tress, W. R.; Abate, A.; Hagfeldt, A.; Grätzel, M. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 2016, 354, 206−209. (5) Chen, W.; Wu, Y.; Yue, Y.; Liu, J.; Zhang, W.; Yang, X.; Chen, H.; Bi, E.; Ashraful, I.; Grätzel, M.; Han, L. Efficient and stable largearea perovskite solar cells with inorganic charge extraction layers. Science 2015, 350, 944−948. (6) Yang, S.; Wang, Y.; Liu, P.; Cheng, Y.-B.; Zhao, H. J.; Yang, H. G. Functionalization of perovskite thin films with moisture-tolerant molecules. Nat. Energy 2016, 1, 15016. (7) Yin, W.-J.; Shi, T.; Yan, Y. Unusual defect physics in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ perovskite solar cell absorber. Appl. Phys. Lett. 2014, 104, 063903. (8) Dong, $\\mathrm{Q.;}$ Fang, ${\\mathrm{Y}}.{\\mathrm{}}{\\mathrm{}}$ Shao, Y.; Mulligan, P.; Qiu, J.; Cao, L.; Huang, J. Electron-hole diffusion lengths $>175\\mu\\mathrm{m}$ in solution-grown $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ single crystals. Science 2015, 347, 967−970. (9) de Quilettes, D. W.; Vorpahl, S. M.; Stranks, S. D.; Nagaoka, H.; Eperon, G. E.; Ziffer, M. E.; Snaith, H. J.; Ginger, D. S. Impact of microstructure on local carrier lifetime in perovskite solar cells. Science 2015, 348, 683−686. (10) Zheng, X.; Chen, B.; Dai, J.; Fang, Y.; Bai, Y.; Lin, Y.; Wei, H.; Zeng, X. C.; Huang, J. Defect passivation in hybrid perovskite solar cells using quaternary ammonium halide anions and cations. Nat. Energy 2017, 2, 17102. (11) Chen, $\\mathrm{Q.;}$ Zhou, H.; Song, T.-B.; Luo, S.; Hong, Z.; Duan, H.- S.; Dou, L.; Liu, Y.; Yang, Y. Controllable self-induced passivation of hybrid lead iodide perovskites toward high performance solar cells. Nano Lett. 2014, 14, 4158−4163. (12) Shao, Y.; Xiao, Z.; Bi, C.; Yuan, Y.; Huang, J. Origin and elimination of photocurrent hysteresis by fullerene passivation in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3}$ planar heterojunction solar cells. Nat. Commun. 2014, $s,$ 5784. (13) Xu, J.; Buin, A.; Ip, A. H.; Li, W.; Voznyy, O.; Comin, R.; Yuan, M.; Jeon, S.; Ning, Z.; McDowell, J. J.; Kanjanaboos, P.; Sun, J.-P.; Lan, X.; Quan, L. N.; Kim, D. H.; Hill, I. G.; Maksymovych, P.; Sargent, E. H. Perovskite−fullerene hybrid materials suppress hysteresis in planar diodes. Nat. Commun. 2015, 6, 7081. (14) Braly, I. L.; deQuilettes, D. W.; Pazos-Outón, L. M.; Burke, S.; Ziffer, M. E.; Ginger, D. S.; Hillhouse, H. W. Hybrid perovskite films approaching the radiative limit with over $90\\%$ photoluminescence quantum efficiency. Nat. Photonics 2018, 12, 355−361. (15) Tan, H.; Jain, A.; Voznyy, O.; Lan, X.; de Arquer, F. P. G.; Fan, J. Z.; Quintero-Bermudez, R.; Yuan, M.; Zhang, B.; Zhao, Y.; Fan, F.; Li, P.; Quan, L. N.; Zhao, Y.; Lu, Z.-H.; Yang, Z.; Hoogland, S.; Sargent, E. H. Efficient and stable solution-processed planar perovskite solar cells via contact passivation. Science 2017, 355, 722−726. (16) Rajagopal, A.; Stoddard, R. J.; Jo, S. B.; Hillhouse, H. W.; Jen, A. K.-Y. Overcoming the photovoltage plateau in large bandgap perovskite photovoltaics. Nano Lett. 2018, 18, 3985−3993. \n\n(17) Walsh, A.; Scanlon, D. O.; Chen, S.; Gong, X.; Wei, S. H. Selfregulation mechanism for charged point defects in hybrid halide perovskites. Angew. Chem., Int. Ed. 2015, 54, 1791−1794. (18) Liu, Y.; Palotas, K.; Yuan, X.; Hou, T.; Lin, H.; Li, Y.; Lee, S.-T. Atomistic origins of surface defects in $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbBr}_{3}$ perovskite and their electronic structures. ACS Nano 2017, 11, 2060−2065. (19) Maiberg, M.; Hölscher, T.; Zahedi-Azad, S.; Scheer, R. Theoretical study of time-resolved luminescence in semiconductors. III. Trap states in the band gap. J. Appl. Phys. 2015, 118, 105701. (20) Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Krieg, F.; Caputo, R.; Hendon, C. H.; Yang, R. X.; Walsh, A.; Kovalenko, M. V. Nanocrystals of cesium lead halide perovskites ( $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3},$ , $\\mathrm{\\nabla{X}=\\mathrm{Cl}_{\\mathrm{\\Omega}}}$ Br, and I): novel optoelectronic materials showing bright emission with wide color gamut. Nano Lett. 2015, 15, 3692−3696. (21) De Roo, J. D.; Ibáñez, M.; Geiregat, P.; Nedelcu, G.; Walravens, W.; Maes, J.; Martins, J. C.; Van Driessche, I. V.; Kovalenko, M. V.; Hens, Z. Highly dynamic ligand binding and light absorption coefficient of cesium lead bromide perovskite nanocrystals. ACS Nano 2016, 10, 2071−2081. (22) Wang, F.; Geng, W.; Zhou, Y.; Fang, H.−H.; Tong, C.−J.; Loi, M. A.; Liu, L.−M.; Zhao, N. Phenylalkylamine passivation of organolead halide perovskites enabling high-efficiency and air-stable photovoltaic cells. Adv. Mater. 2016, 28, 9986−9992. (23) Lindblad, R.; Bi, D.; Park, B.-W.; Oscarsson, J.; Gorgoi, M.; Siegbahn, H.; Odelius, M.; Johansson, E. M. J.; Rensmo, H. Electronic structure of $\\mathrm{TiO_{2}/C H_{3}N H_{3}P b I_{3}}$ perovskite solar cell interfaces. J. Phys. Chem. Lett. 2014, 5, 648−653. (24) Bi, D.; Yi, C.; Luo, J.; Décoppet, J.-D.; Zhang, F.; Zakeeruddin, S. M.; Li, X.; Hagfeldt, A.; Grätzel, M. Polymer-templated nucleation and crystal growth of perovskite films for solar cells with efficiency greater than $21\\%$ . Nat. Energy 2016, 1, 16142. (25) Niu, G.; Li, We.; Meng, F.; Wang, L.; Dong, H.; Qiu, Y. Study on the stability of $\\mathrm{CH}_{3}\\mathrm{N}\\bar{\\mathrm{H}}_{3}\\mathrm{PbI}_{3}$ films and the effect of postmodification by aluminum oxide in all-solid-state hybrid solar cells. J. Mater. Chem. A 2014, 2, 705−710. (26) Buin, A.; Pietsch, P.; Xu, J.; Voznyy, O.; Ip, A. H.; Comin, R.; Sargent, E. H. Materials processing routes to trap-free halide perovskites. Nano Lett. 2014, 14, 6281−6286. (27) Wang, S.; Jiang, $\\mathrm{Y.j}$ Juarez-Perez, E. J.; Ono, L. K.; Qi, Y. Accelerated degradation of methylammonium lead iodide perovskites induced by exposure to iodine vapour. Nat. Energy 2017, 2, 16195. (28) Zhang, W.; Pathak, S.; Sakai, N.; Stergiopoulos, T.; Nayak, P. K.; Noel, N. K.; Haghighirad, A. A.; Burlakov, V. M.; deQuilettes, D. W.; Sadhanala, A.; Wang, W.; Li, L.; Ginger, D. S.; Friend, R. H.; Snaith, H. J. Enhanced optoelectronic quality of perovskite thin films with hypophosphorous acid for planar heterojunction solar cells. Nat. Commun. 2015, 6, 10030. (29) Liu, Z.-B.; Tian, J.-G.; Zang, W.-P.; Zhou, W.-Y.; Song, F.; Zhang, C.-P.; Zheng, J.-Y.; Xu, H. Flexible alteration of optical nonlinearities of iodine charge-transfer complexes in solutions. Opt. Lett. 2004, 29, 1099−1101. (30) Takeuchi, H.; Omogo, B.; Heyes, C. D. Are bidentate ligands really better than monodentate ligands for nanoparticles? Nano Lett. 2013, 13, 4746−4752. " + }, + { + "id": "10.7150_thno.29766", + "DOI": "10.7150/thno.29766", + "DOI Link": "http://dx.doi.org/10.7150/thno.29766", + "Relative Dir Path": "mds/10.7150_thno.29766", + "Article Title": "Engineering Bioactive Self-Healing Antibacterial Exosomes Hydrogel for Promoting Chronic Diabetic Wound Healing and Complete Skin Regeneration", + "Authors": "Wang, CG; Wang, M; Xu, TZ; Zhang, XX; Lin, C; Gao, WY; Xu, HZ; Lei, B; Mao, C", + "Source Title": "THERANOSTICS", + "Abstract": "Rationale: Chronic nonhealing diabetic wound therapy and complete skin regeneration remains a critical clinical challenge. The controlled release of bioactive factors from a multifunctional hydrogel was a promising strategy to repair chronic wounds. Methods: Herein, for the first time, we developed an injectable, self-healing and antibacterial polypeptide-based FHE hydrogel (F127/OHA-EPL) with stimuli-responsive adipose-derived mesenchymal stem cells exosomes (AMSCs-exo) release for synergistically enhancing chronic wound healing and complete skin regeneration. The materials characterization, antibacterial activity, stimulated cellular behavior and in vivo full-thickness diabetic wound healing ability of the hydrogels were performed and analyzed. Results: The FHE hydrogel possessed multifunctional properties including fast self-healing process, shear-thinning injectable ability, efficient antibacterial activity, and long term pH-responsive bioactive exosomes release behavior. In vitro, the FHE@exosomes (FHE@exo) hydrogel significantly promoted the proliferation, migration and tube formation ability of human umbilical vein endothelial cells (HUVECs). In vivo, the FHE@exo hydrogel significantly enhanced the healing efficiency of diabetic full-thickness cutaneous wounds, characterized with enhanced wound closure rates, fast angiogenesis, re-epithelization and collagen deposition within the wound site. Moreover, the FHE@exo hydrogel displayed better healing outcomes than those of exosomes or FHE hydrogel alone, suggesting that the sustained release of exosomes and FHE hydrogel can synergistically facilitate diabetic wound healing. Skin appendages and less scar tissue also appeared in FHE@exo hydrogel treated wounds, indicating its potent ability to achieve complete skin regeneration. Conclusion: This work offers a new approach for repairing chronic wounds completely through a multifunctional hydrogel with controlled exosomes release.", + "Times Cited, WoS Core": 648, + "Times Cited, All Databases": 679, + "Publication Year": 2019, + "Research Areas": "Research & Experimental Medicine", + "UT (Unique WOS ID)": "WOS:000452508600006", + "Markdown": "Research Paper \n\n# Engineering Bioactive Self-Healing Antibacterial Exosomes Hydrogel for Promoting Chronic Diabetic Wound Healing and Complete Skin Regeneration \n\nChenggui Wang1\\*, Min Wang2\\*, Tianzhen $\\mathsf{X}\\mathbf{u}^{1}.$ , Xingxing Zhang3, Cai Lin3, Weiyang Gao1, Huazi $\\mathsf{X}\\mathsf{u}^{1}.$ , Bo Lei2,4,5, Cong Mao1 \n\n1. Key Laboratory of Orthopedics of Zhejiang Province, Department of Orthopedics, the Second Affiliated Hospital and Yuying Children’s Hospital of \nWenzhou Medical University, Wenzhou 325027, China \n2. Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an 710000, China \n3. Center of Diabetic Foot, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China \n4. Frontier Institute of Science and Technology, Xi’an Jiaotong University, Xi’an 710054, China \n5. Instrument Analysis Center, Xi'an Jiaotong University, Xi’an 710054, China \n\n\\*These authors contributed equally to this work. \n\n Corresponding authors: maocong@wmu.edu.cn (Cong Mao) and rayboo@xjtu.edu.cn (Bo Lei). \n\n$\\circledcirc$ Ivyspring International Publisher. This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions. \n\nReceived: 2018.09.06; Accepted: 2018.11.19; Published: 2019.01.01 \n\n# Abstract \n\nRationale: Chronic nonhealing diabetic wound therapy and complete skin regeneration remains a critical clinical challenge. The controlled release of bioactive factors from a multifunctional hydrogel was a promising strategy to repair chronic wounds. \n\nMethods: Herein, for the first time, we developed an injectable, self-healing and antibacterial polypeptide-based FHE hydrogel (F127/OHA-EPL) with stimuli-responsive adipose-derived mesenchymal stem cells exosomes (AMSCs-exo) release for synergistically enhancing chronic wound healing and complete skin regeneration. The materials characterization, antibacterial activity, stimulated cellular behavior and in vivo full-thickness diabetic wound healing ability of the hydrogels were performed and analyzed. \n\nResults: The FHE hydrogel possessed multifunctional properties including fast self-healing process, shear-thinning injectable ability, efficient antibacterial activity, and long term pH-responsive bioactive exosomes release behavior. In vitro, the FHE@exosomes $(\\mathsf{F H E@e x o})$ hydrogel significantly promoted the proliferation, migration and tube formation ability of human umbilical vein endothelial cells (HUVECs). In vivo, the FHE@exo hydrogel significantly enhanced the healing efficiency of diabetic full-thickness cutaneous wounds, characterized with enhanced wound closure rates, fast angiogenesis, re-epithelization and collagen deposition within the wound site. Moreover, the FHE@exo hydrogel displayed better healing outcomes than those of exosomes or FHE hydrogel alone, suggesting that the sustained release of exosomes and FHE hydrogel can synergistically facilitate diabetic wound healing. Skin appendages and less scar tissue also appeared in FHE@exo hydrogel treated wounds, indicating its potent ability to achieve complete skin regeneration. \n\nConclusion: This work offers a new approach for repairing chronic wounds completely through a multifunctional hydrogel with controlled exosomes release. \n\nKey words: multifunctional hydrogel, bioactive exosomes, responsive sustained release, diabetic wound healing \n\n# Introduction \n\nDiabetic wounds have become a significant cause of diabetes related amputations, which lead to high medical cost and poor life quality of patients [1]. Normal wound healing is a complicated biological process involving three typical phases: inflammation, proliferation and remodeling, which involves many types of cells, cytokines and extracellular matrix (ECM) [2]. Mechanisms underlying poor healing of diabetic wounds are still unclear, yet the reasons for this dread complication of diabetes mainly involves hypoxia, impaired angiogenesis, damage from reactive oxygen species (ROS), and neuropathy, leading to long-time medical burden and compromised life quality of those patients [3]. Conventional clinical treatment of diabetic wounds includes surgical debridement and negative pressure therapy with wound dressings [1, 4]. However, these treatments often seem ineffective for many patients due to impaired cell function around the wound sites [5]. To solve these problems, therapies based on mesenchymal stem cells (MSCs) showed great potential for wound healing due to their ability to recruit cells and release growth factors and proteins, yet problems still arose because of immunological rejection, limited differentiation and proliferation ability, and chromosomal variation of stem cells [6, 7]. Recently, emerging studies showed that transplanted stem cell therapy may exert its function through a paracrine mechanism instead of direct differentiation, particularly by secreting extracellular vesicles [8, 9]. Exosomes are nanosized vesicles $(40-150\\ \\mathrm{nm})$ that are considered as primary secretory products from MSCs and can regulate cell-to-cell communication through transferring the contained mRNAs, miRNAs, and proteins to target cells and facilitate wound healing [6]. Moreover, they are immune-tolerant, have similar biological functions to those of the cells from which they are derived, and can be used as a possible alternative to MSCs therapy [10]. Angiogenesis is a critical factor determining the outcome of diabetic wound healing [2, 11]. Recent studies also showed that exosomes could improve wound healing by speeding up angiogenesis, which exhibited great promises for diabetic wound therapy application [12, 13]. For example, Guo et al. reported that exosomes derived from platelet-rich plasma can promote chronic cutaneous wound healing through YAP activation [14]. However, the common method of exosomes administration is injection, which can affect their function due to the rapid clearance rate [15]. On the other hand, diabetic wound repair and regeneration require a relatively long healing time. Herein, it is necessary to develop a novel biocompatible scaffold that can serve as a sustained release carrier for exosomes to maintain their bioactivity at the diabetic wound area and further accelerate wound healing. \n\nBiomedical hydrogels, structurally similar to the natural ECM, have been considered promising biomaterials to deliver drugs/cells for wound treatments [16, 17]. An ideal wound-healing hydrogel scaffold should have these features: appropriate mechanical properties, good water retention, anti-infection capacity, injectable capacity, and excellent cell biocompatibility [18]. Self-healing hydrogels exhibit rapid and autonomous self-recovery ability after damage caused by external forces, possibly maintaining their structural stability during the wound healing [19, 20]. Hydrogels with inherent antibacterial activity possess several advantages such as preventing infection, absorbing wound fluid and offering gaseous exchange [21]. Current antibacterial materials include inorganic metal ions or nanoparticles, reactive oxygen species (ROS)-producing molecules, antimicrobial peptides, etc., which also have their own disadvantages such as potential cytotoxicity, the limitations of utilization, low productivity and high production costs [22-25]. The injective and adhesive capacities of hydrogels could endow them with good operability and long term attachment on wound during healing [26-28]. In particular, the good cellular biocompatibility plays an important role for hydrogels, which could enhance cell proliferation and differentiation [29]. Hydrogel scaffolds contained amine groups have shown their potential for enhanced biocompatibility and integration with host tissue [30]. Poly-ε-L-lysine (EPL) is natural cationic polypeptide produced from Streptomyces albulus, which showed good biodegradability, inherent antibacterial activity and biocompatibility [31]. The US FDA has approved EPL for clinical uses or as a food-grade cationic antimicrobial [32]. Furthermore, the L-lysine residues in EPL enabled their facile surface modification to synthesize biomedical hydrogels. For example, EPL and poly(ethylene glycol) hydrogel with adhesive property has been fabricated for potential tissue regeneration applications [33]. On the other hand, exosome-based delivery by hydrogel probably will enhance the angiogenesis and tissue formation during wound healing. Recent studies also showed the use of hydrogels to deliver exosomes for restoring vascularization and promoting wound healing [34, 35]. Chitosan-based hydrogels loaded with exosomes have been developed for accelerating angiogenesis and wound healing [33]. However, hydrogels composed of natural polypeptides with multiple functions for exosome delivery and tissue regeneration were very rare in reports [36]. Therefore, it is very necessary and promising to fabricate an injectable self-healing and adhesive hydrogel with inherent antibacterial activity for delivering exosomes to promote chronic diabetic wound healing. \n\nIn this study, we developed an injectable self-healing polypeptide-based hydrogel that exhibited inherent antibacterial activity and pH-responsive long-term exosomes release (Scheme 1). The multifunctional hydrogel was composed of Pluronic F127 (F127), oxidative hyaluronic acid (OHA), and EPL (denoted as FHE hydrogel). The FHE hydrogel was formed through a reversible Schiff base reaction between OHA and EPL, and the thermal-responsive property of F127 (Scheme 1B). In this hydrogel, OHA provides the water-retaining ability and biocompatibility, EPL gives the intrinsic antibacterial activity and adhesive ability, F127 offers the thermal-responsive gelation, and Schiff base bonds (OHA and EPL) endow the self-healing performance. The adipose mesenchymal stem cells (AMSCs)-derived exosomes exhibit representative negative potential and could be loaded in the hydrogel through the electrostatic interaction between exosomes and EPL. The exosomes could be released under a weak acidic environment due to the broken of Schiff base bonds. Herein, for the first time, we reported that the self-healing multifunctional FHE hydrogel could be used to deliver bioactive exosomes for enhancing diabetic wound healing and skin regeneration. The effect of long-term exosomes released in the FHE hydrogel on angiogenesis and diabetic wound healing was studied. \n\n# Results and discussion \n\n# Physicochemical structure characterization of FHE hydrogel \n\nThe schematic representation of the FHE hydrogels is shown in Scheme 1. First, the aldehyde groups were introduced to HA through oxidation by sodium periodate (Scheme 1A). Oxidized HA was identified by $\\mathrm{{^{1}H N M R}},$ in which the new peaks at 4.9 ppm and $5.0\\ \\mathrm{ppm}$ corresponded to protons from the aldehyde group and adjacent hydroxyls (Figure S1). The actual oxidation degree of HA was quantified by measuring the number of aldehydes groups in the polymer using a hydroxylamine hydrochloride assay, and the results are shown in Table S1. Oxidized hyaluronic acid (OHA) can react with amino groups in EPL to form Schiff bases (Scheme 1B). When mixing the F127 and EPL solution with the OHA solution, the mixed solution forms the hydrogels $(\\mathrm{{100}\\upmu l})$ through a sol-to-gel transition in approximately $10\\mathrm{~s~}$ at $37^{\\circ}\\mathrm{C}$ (Schemes 1C-D). The chemical structure of the hydrogels was determined by FT-IR analysis (Figure 1A). The peak at $1660~\\mathrm{{cm^{-1}}}$ was assigned to the carbonyl $\\scriptstyle(-C=\\mathrm{O})$ from EPL and HA. The aldehyde group (-CHO) stretch in oxidized HA (OHA) was found at $1735\\mathrm{cm^{-1}}$ . The double peaks at $1467\\mathrm{cm^{-1}}$ and $1342\\mathrm{cm^{-1}}$ were attributed to the ether bond (-C-O-C-) from F127. The disappearance of the peak at $1735\\mathrm{cm^{-1}}$ in FHE hydrogel indicated the successful reaction between OHA and EPL. In addition, after freeze-drying, the FHE hydrogel showed a typical 3D porous morphology and the EPL content did not significantly affect the pore structure (Figure 1B). \n\n![](images/86ff8e75e543edbce22371049a136631bf3ba211da5cf7560985bce260e2fbf3.jpg) \nScheme 1. Synthesis of injectable FHE hydrogel with multifunctional properties. (A) Synthesis of oxidized hyaluronic acid (HA); (B) Schiff base reaction between oxidized HA and polypeptide (ε-poly-L-lysine, EPL); (C) Thermal-responsive sol-gel process of double network hydrogel composed of F127-EPL and oxidized HA; (D) Optical pictures showing the sol-gel transition of FHE hydrogel. \n\n# Multifunctional properties evaluation of FHE hydrogels \n\nThe rheological properties of FHE hydrogel under various conditions were tested to evaluate the mechanical behavior (Figures 1C-F). At $4^{\\circ}C,$ the storage modulus $(\\mathbf{G}^{\\prime})$ was significantly lower than the loss modulus $(\\mathrm{G}^{\\prime\\prime})$ in the F127 and FH groups, suggesting their low viscosity (Figure 1C). However, for FHE5 and FHE10 groups, the $\\mathbf{{\\cal{G}}^{\\prime}}$ was high compared with $\\mathbf{{G}^{\\prime\\prime}}$ , indicating the increased viscosity after adding OHA and EPL (Figure 1C). The significant low modulus at $4^{\\circ}\\mathrm{C}$ (approximately $10\\mathrm{Pa}$ suggested that various hydrogels should be in the sol state but not the gel state (Scheme 1). The $G^{\\prime}$ and $G^{\\prime\\prime}$ of all hydrogels were significantly increased with the temperature at 25 and $37^{\\circ}\\mathrm{C},$ and the $\\mathbf{G}^{\\prime}$ was significantly higher than the $G^{\\prime\\prime}$ in all groups, suggesting the hydrogel formation (Figure 1C). In addition, the rheological analysis and macroscopic test were used to evaluate the self-healing performance of the FHE hydrogels, using F127 and FH as controls (Figures 1D-G). When the step strain changed from $1\\%$ to $1000\\%$ , the $\\mathbf{{{G}^{\\prime}}}$ for various hydrogels was significantly decreased from ${\\sim}10\\mathrm{kPa}$ to several $\\mathrm{Pa}$ (Figure 1D). After two cycles of step strain, the $\\mathbf{{\\cal{G}}^{\\prime}}$ of the F127 and FH hydrogels showed a significant decrease, while those of the FHE-5 and FHE-10 hydrogels presented a negligible change (Figure 1E). The decrease in $G^{\\prime}$ was caused by the collapse of the hydrogel network due to the high dynamic strain $(1000\\%)$ . After releasing the strain to $1\\%$ , the FHE-5 and FHE-10 hydrogels returned to their initial $G^{\\prime}$ values quickly, suggesting the recovery of their hydrogel structure (Figures 1D-E and Figure S2A-D). We also tested the rheological properties of hydrogels before and after healing (Figure 1F). No significant difference can be found in $G^{\\prime}$ between the FHE-5 and FHE-10 hydrogels, indicating their fast recovery ability (Figure S2E). After adding new hydrogel to the defect in dydrogel, the FHE-5 hydrogel repaired the defect within $16\\mathrm{h}$ (Figure 1G), and no significant difference was observed in the rheological properties and structure between the initial and after healing hydrogel (Figure S2G and S2K). Additionally, the FHE-5 hydrogel could be extruded through a medical plastic catheter with an $0.8\\mathrm{mm}$ of inner diameter and $10\\mathrm{cm}$ of length without clogging and recover the gel state in a “rat” shape after injection, indicating its good injectability (Figure 1H). The injectability of FHE hydrogel was also characterized in its the shear thinning properties (Figure S2F). FHE-5 hydrogel also exhibited very good adhesive ability on skin, which may benefit the wound healing process (Figure 1I). The mechanism of the self-healing hydrogel probably was based on the dynamic Schiff based bond (Figure 1J and S2H-J) [37, 38]. Due to the presence of the antibacterial polypeptide (EPL), the FHE hydrogel demonstrated robust antibacterial activity (Figure S3). Compared with the F127 hydrogel, the FHE hydrogel efficiently killed the E. coli (Gram-negative bacterium) (Figures S3A-B) and S. aureus (Gram-positive bacterium) just after $^{2\\mathrm{~h~}}$ of incubation (Figures S3C-D). E. coli and S. aureus showed a significant increase after incubation with F127-HA (FH), indicating the excellent antibacterial ability of FHE hydrogels. After 13 days, the FHE-5 hydrogel exhibited a representative pH-responsive degradation in vitro; the weight residual was approximately $20\\%$ $\\mathrm{(pH~7.4)}$ and $1\\%$ $\\mathrm{(pH}5.5)$ , indicating that the FHE-5 hydrogel also has been mostly degraded in vivo (subcutaneous) (Figure S4). The multifunctional properties of FHE hydrogel including injectability, self-healing, antibacterial and adhesive activity enable their promising applications in wound healing. \n\n![](images/f116ba76c25dc618c92c079b98503b1e2b9fe6551ee765cef5e2d4bad28063c8.jpg) \nFigure 1. Physicochemical structure and multifunctional properties of FHE hydrogel. (A) FTIR showing the chemical structure; (B) SEM images exhibiting the porous morphology; (C) Rheological properties exhibiting the $\\boldsymbol{\\mathsf{G}^{\\prime}}$ and $\\pmb{G}\"$ of various hydrogels at 4, 25 and $37^{\\circ}\\mathrm{C};$ ; (D) $\\boldsymbol{\\mathsf{G}^{\\prime}}$ and $\\pmb{G}\"$ of various hydrogels when the step strain switched from $1\\%$ to $100\\%$ at $37^{\\circ}\\mathrm{C}$ ; (E) $\\boldsymbol{\\mathsf{G}}^{\\prime}$ recovery ratio of various hydrogel after two cycles of $100\\%$ step strain at $37^{\\circ}\\mathrm{C}$ (F) $\\boldsymbol{\\mathsf{G}^{\\prime}}$ of the initial hydrogel and the hydrogel after healing; (G) Pictures demonstrating the self-healing performance of FHE-5 hydrogels; (H) Photographs showing the injectable ability of FHE5 hydrogel through the catheter; (I) Images presenting the adhesive characteristic to the skin for FHE-5 hydrogel; (J) Schematic illustration of the self-healing process for FHE hydrogel. \n\n# Exosomes characterization, release profile and HUVECs biocompatibility evaluation in vitro \n\nThe obtained AMSCs were characterized by flow cytometry analysis for positive expression of CD90 and CD44, and negative expression of CD45 and \n\nCD34 (Figure 2). The AMSCs-derived exosomes were then harvested by differential centrifugation of the AMSCs conditioned media. TRPS analysis, TEM, and western blotting were performed to identify the purified exosomes. The TRPS measurement showed that the size of the AMSCs-derived exosomes was approximately $60{-}80~\\mathrm{\\nm}$ (Figure 2A), which was concordant with the previously reported exosomes size distributions [39]. TEM revealed that AMSCsderived exosomes exhibited a cup- or round-shaped morphology with a size below $100\\ \\mathrm{nm}$ (Figure 2B), which was consistent with the data from the TRPS analysis. Western blotting indicated that these exosomes were positive for the characteristic exosome surface marker proteins, including Alix, CD9, CD63 and CD81 (Figure 2C), which was also described by other studies [15, 40]. All these results indicated that the AMSCs-derived exosomes were successfully obtained in this study. \n\nThe exosomes release profile is shown in Figures 3 A and B. The bioactive exosomes were effectively encapsulated in the FHE hydrogel and exhibited a representative long term pH-responsive sustained release behavior. To investigate the angiogenic ability of AMSCs-derived exosomes, transwell coculture system was used. The function of free exosomes or FHE@exo hydrogels on HUVECs proliferation was tested by CCK-8 cell counting analysis. The results showed that HUVECs treated with FHE hydrogel showed equal proliferative capability to that of the control groups, but the sustained release of exosomes from FHE hydrogel can significantly enhance the proliferation of HUVECs over that of the free exosomes groups (Figure 3C). This result suggested that the FHE hydrogel possessed good biocompatibility and non-cytotoxicity towards HUVECs. Moreover, the sustained release of exosomes from the FHE hydrogel could remarkably enhance the proliferation of HUVECs than one-time treatment of exosomes, indicating that the FHE hydrogel can increase or at least maintain the bioactivity of released exosomes and can be an excellent carrier for the sustained release of exosomes. \n\nAngiogenesis is the biological process of new vessel formation involved in endothelial cell proliferation, migration, and tube formation, which can determine the outcomes of diabetic wound healing because newly formed vessels can transport oxygen and nutrition into wound sites [2, 41]. To evaluate the effect of FHE@exo hydrogel on migration and tube formation of HUVECs, exosomes or FHE@exo hydrogel pretreated HUVECs were seeded on the chamber of the transwell or Matrigel. The total migrated cells and tube numbers were counted to assess the angiogenic ability of HUVECs. As shown in \n\nFigures $3\\mathrm{~D~}$ and ${\\mathrm{E}},$ exosomes remarkably enhanced the motility of HUVECs compared to that of the control, and this effect on HUVECS was increased with the treatment of FHE@exo hydrogel. Furthermore, better tube formation performance was observed in FHE@exo hydrogel group, characterized with higher tube numbers and complete tubular structure when compared to the FHE hydrogel or exosome alone groups (Figures $3\\mathrm{~F~}$ and G). This observed phenomenon indicated the sustained release of exosomes could exert a potent effect on angiogenesis, which also confirmed the previous research that exosomes can accelerate angiogenesis and promote wound healing [13, 42, 43]. Herein, the above in vitro results showed that AMSCs-derived exosomes activate a cascade of angiogenic responses in HUVECs, including cell proliferation, migration and angiogenic activities, and the sustained release of exosomes from the FHE hydrogel further enhanced the angiogenic ability of HUVECs. \n\n# Diabetic wound healing examinations in vivo \n\nTo explore the healing efficiency of FHE@exo hydrogel on the cutaneous wound repair process, FHE@exo hydrogel, exosomes and FHE hydrogel were applied to the full-thickness diabetic wounds and saline were used as the blank control. Figure 4A exhibits the size change of the diabetic wounds from four groups on days 0, 3, 7, 14, and 21 postsurgery. Gross observation of wound closure in mice showed that all treated wounds achieved a remarkable decrease in wound size at 14 and 21 days, while the negative control exhibited a slow decrease of wound size during the experimental time. Among them, the FHE@exo hydrogel possessed the most efficient healing with complete closure and hair growth of diabetic wounds at day 21. Consistent with the gross observation, the quantitative wound closure rates showed that the FHE@exo hydrogel group exhibited faster healing rates than those of other groups during the whole healing process with $88.67{\\scriptstyle\\pm6.9\\%}$ closure rate on day 14, while other groups reached final healing rates of $76.3{\\pm}3.2\\%$ (exosomes), $64.3{\\pm}9.8\\%$ (FHE hydrogel) and $36.3{\\pm}10.4\\$ (control), respectively (Figure 4B). Moreover, with the loading of exosomes into the FHE hydrogel, the healing performance of the FHE@exo hydrogel was obviously promoted when compared with the pure exosomes, indicating that the FHE@exo hydrogel can promote the wound healing process through sustained release of exosomes. \n\n![](images/8925d89999324cbaf583a68d47c1311defa7b39ff3fc88025cf730a156707563.jpg) \nFigure 2. Characterization of AMSCs and AMSCs-exo. (A) Size distribution of AMSCs-exo; (B) TEM micrograph of AMSCs-exo, scale bar: $200~\\mathsf{n m}$ ; (C) Western blot analysis of AMSCs-exo markers of Alix, CD63, CD9 and CD81; (D) flow cytometry analysis of AMSCs markers of CD90, CD34, CD44 and $C D45$ ; $\\scriptstyle{\\mathsf{n}}=3$ independent experiments. \n\n![](images/8995139d798c22c482ca917b4348a13adf9fdcc6a4fce7d016c4ae7621902413.jpg) \nFigure 3. Exosomes release and HUVECs biocompatibility evaluation in vitro. (A) Scheme of pH- responsive exosomes release in FHE hydrogel; (B) pH-dependent release profile of loaded exosomes in FHE hydrogel; (C) CCK8 results of HUVECs treated by FHE or FHE@exo hydrogels; (D, E) Transwell migration assay results of HUVECs with different treatments. HUVECs were treated with PBS (control), FHE, exosomes and FHE@exo, and the cell migration of HUVECs was enhanced after exosomes or FHE@exo treatment (scale bar: $50\\upmu\\mathrm{m})$ ; (F, G) In vitro tube formation results of HUVECs with different treatments. The tube formation ability of HUVECs was improved after exosomes or FHE@exo treatment (scale bar: $200~{\\upmu\\mathrm{m}})$ . \n\nH&E staining was then used to assess the healing pathology of FHE@exo hydrogel treated wounds. As shown in Figure $4\\mathrm{C},$ unlike the control group, which exhibited with no formed neoepidermis, abundant granulation tissue formed with thinker and more layers in the wound gap of FHE@exo hydrogel, pure exo and FHE hydrogel groups at day 7. The calculated length of wound area also showed a significant difference between FHE@exo and other groups, with the shortest ones in FHE@exo hydrogel group, followed by pure exosomes, FHE hydrogel and control, respectively (Figures 4C, 3D). At day 14, the thickness of granulation tissue was much higher than that at day 7. Although a noticeable reduction in the wound length was also observed in all groups when compared to day 7, FHE@exo hydrogel treated wounds exhibited with the most abundant granulation tissue and shortest wound length (Figure 4E). Moreover, skin appendages were clearly observed at day 21 in the FHE@exo hydrogel group with a significantly higher number of dermal appendages (Figures 4C and F) in the scar tissue when compared with other groups, indicating that complete skin repair can be achieved by the FHE@exo hydrogel treatment. It should also be mentioned that despite the fact that pure exosomes can be useful for wound healing, the long-time release of exosomes from FHE@exo hydrogel can be more efficient on diabetic wound repair and regeneration from the H&E staining analysis. \n\n# Collagen deposition analysis in vivo \n\nProper collagen deposition and remodeling could improve the tissue tensile strength and result in better healing effect [44, 45]. Figure S5 exhibits the deposition of newly formed collagen in wounds treated by different methods. We can see wounds treated by FHE@exo hydrogel and exosome showed abundant and relatively well-organized collagen fibers at day 7, and the amount of collagen fibers increased with healing time, characterized by abundant well-arranged fibers appearing in the wound site. The FHE hydrogel group showed less collagen, and collagen deposition in control wounds can be hardly seen at day 7 and still had a lower level and loosely packed of collagen fibers when compared with others at day 21. Particularly, FHE@exo hydrogel treated wounds completely healed and skin appendages can be clearly seen at day 21, and this outcome was consistent with the H&E results (Figures 4C and F). Masson staining results suggested that FHE@exo hydrogel, the exosomes sustained release system, can improve collagen deposition in wound site, resulting in accelerated skin regeneration and better and even complete repair of full-thickness diabetic wounds. \n\nThe type Ⅰ and Ⅲ collagens are primary constituents in dermal ECM, which is very important in wound healing [46]. Hence, the collagen Ⅰ/Ⅲ levels in the wound tissues were evaluated by immunostaining. Figure 5 shows the deposition amount of collagen Ⅰ and Ⅲ exhibited similar changing trends to Masson staining. With the increase in healing time, the deposition of both types of collagens also increased in all wounds, while the FHE@exo hydrogel group showed significantly higher intensity (Figures \n\n5A-D) than that of other groups at 7 and 21 days posttreatment, followed by the exosomes, FHE hydrogel and control groups. It is known that scar tissue exhibited relatively lower Col III content than that of normal skin, and early abundant deposition of collagen Ⅲ would facilitate healing and result in scarless skin [47, 48]. Connecting the pathological results with formed skin appendages and well-organized collagen fibers, the abundant collagen formation during the healing period benefited the collagen matrix remodeling and stimulated complete healing, leading to better healing outcomes with more similar healed tissue to normal skin. \n\n![](images/ccfde802fd75d54e7117be42a83d5f61cb9caa20f107b7fbdb5343ec03ee8705.jpg) \nFigure 4. FHE@Exo hydrogel accelerated wound closure. (A) Representative images of healing process in wounds treated with FHE, exosomes, FHE@exo and control; (B) Wound closure rates of all four groups; (C) H&E staining images of full-thickness wounds on days 7, 14 and 21, arrows indicate newly formed dermal appendages, scale bar: $1000\\ \\upmu\\mathrm{m};$ (D) Quantification of the length of the wound site at day 7; (E) Quantification of the length of the wound area on day 14; (F) Quantification of the number of dermal appendages in the wound area on day 21. \n\n![](images/977d9e3e0af23d3c97d06d83130843339060a1ae9dac655a8a27e329fa8d3331.jpg) \nFigure 5. Histochemical analysis of collagen I and Ⅲ expression in wounds treated by FHE@exo hydrogel. (A, C) Immunohistochemistry staining images for collagen I and collagen Ⅲ at 7 and 21 days post-wounding, respectively; (B, D) Quantitative analysis of relative density of collagen I and collagen Ⅲ at 7 and 21 days after surgery, respectively; Scale bar: $50\\mu\\mathsf{m}$ . \n\n# Re-epithelialization and angiogenic ability assessment in vivo \n\nThe immunohistochemical staining of cytokeratin, which is a vital biomarker related to the differentiation and re-epithelialization of epidermal [49], was performed to assess the re-epithelialization level during healing. As shown in Figures S6A and B, the FHE@exo hydrogel group exhibited strongest staining of cytokeratin within neoepidermis at both day 7 and 14 in comparison to the other groups. FHE@exo hydrogel treated wounds also exhibited the thickest neoepidermis with differentiated structures and more well-organized layers (Figure S6A), while control wounds showed significantly lower staining of cytokeratin with less re-epithelialization as observed. Moreover, FHE hydrogel or pure exosomes alone also promoted re-epithelialization of the diabetic wounds, characterized with more positive stained cells with cytokeratin in the neoepidermis than those in the control group. This outcome also confirmed that the AMSCs-derived exosomes released into the wound sites promoted the epithelial cell differentiation [42], leading to stronger cytokeratin levels and faster re-epithelialization. The above data suggested that FHE@exo hydrogel, a sustained release system of exosomes, exerted a synergic effect of FHE hydrogel and exosomes, together leading to faster re-epithelization and wound healing. \n\nThe above results revealed that FHE@exo hydrogel can be very efficient for diabetic wound healing through facilitating granulation tissue formation and re-epithelialization during repair. These processes are closely connected to cell activities [44]. In this study, we also evaluate the cell proliferation activities by performing immunostaining of Ki67 at day 7 and 14 (Figure S6C) [50]. As shown in Figure S6C, positive staining of Ki67 was found in FHE@exo hydrogel and exo groups (Figure S6D), while the FHE hydrogel and control groups showed very small amount of positive staining of Ki67 at both time points. Although no difference can be found by visual inspection, the quantitative data of the positively stained Ki67 numbers revealed that a significantly higher level of Ki67 was expressed in FHE@exo hydrogel group (Figure S6D) than that of the exo group. Meanwhile, the Ki67 levels of all wounds moderately decreased at day 14 when compared with day 7. At that time, the healing stage had nearly progressed from proliferation to tissue remodeling, which explained the reduced cell proliferative activities and was also confirmed by the H&E staining with less granulation tissue. Moreover, reduced proliferative activities during the late repair stage may prohibit tissue hyperplasia and lead to relatively satisfactory outcomes [47]. These results confirmed that the FHE@exo hydrogel exosomes sustained release system enhances the cell proliferative activity of wounds sites, which promotes granulation tissue formation and further facilitates wound healing. \n\nBlood vessels have been considered critical for tissue regeneration due to their functions of providing nutrition and oxygen for cells around wounds [48, 51]. From the in vitro results we can see FHE@exo hydrogel has a potent angiogenic promoting effect towards HUVECs (Figure 3). Nevertheless, whether the in vitro angiogenic ability of FHE@exo hydrogel would affect the angiogenesis in diabetic wounds remained unclear. Therefore, the level of alpha-smooth muscle actin (α-SMA) was assessed to evaluate newly formed vessels within the regenerated tissue (Figure 6A). FHE@exo hydrogel treated diabetic wounds exhibited much higher expression of α-SMA than that of the other three groups, followed by pure exosomes treated wounds. The α-SMA staining in FHE and control group was very weak. Moreover, blood vessels in the FHE@exo hydrogel group appeared bigger size with lumen structure. The vessels numbers connected with smooth muscle cells was also counted according to the $\\upalpha$ -SMA staining results. Consistent with the visual observation, the vessel number of FHE@exo hydrogel group in the wound site was approximately 45, while other groups showed only about 20 vessels. These data supported the in vitro findings of enhanced tube formation in cells treated with FHE@exo hydrogel, indicating FHE@exo hydrogel successfully promoted angiogenesis and blood vessels formation in the diabetic wounds. \n\nFrom all of the above results we can see FHE@exo hydrogel, which possesses properties of self-healing, injectability, antibacterial activity, and long term pH-responsive exosomes release behavior, has a potent effect in promoting the healing process of diabetic wounds. The efficient antibacterial ability protected diabetic wounds from infection, and none of the treated diabetic wound was infected during the experimental period. Moreover, compared with other reported hydrogels [21, 52, 53], the FHE@exo hydrogel also showed excellent cytocompatibility, angiogenic ability and can significantly accelerate the diabetic wound repair and regeneration process. Specifically, once the FHE@exo hydrogel was applied onto the diabetic wounds, the exosomes with specific miRNA and proteins also began to release from the hydrogel with a sustained profile. With these released exosomes, the angiogenesis of wounds was initiated, characterized by more newly formed vessels appearing within the wounds. Meanwhile, the proliferative activity of the involved cells was also promoted. With the increased neovascularization and proliferation, the granulation tissue formation, re-epithelialization and matrix deposition processes were accelerated, leading to shorter healing time and faster healing rates compared to exosomes treated wounds. Particularly, much less scar tissue and more skin appendages appeared in the late healing stage of diabetic wounds treated with FHE@exo hydrogel, which is probably related to the sustained release of exosomes, as fewer skin appendages can also be found in wounds treated by pure exosomes. These results remind us that the sustained release of exosomes may facilitate complete diabetic wound healing with abundant skin appendages and scarless tissue. Further studies about the specific functional component of exosomes and its related molecular mechanism in diabetic wound healing should be investigated in the near future. \n\n![](images/3d7fcafaa0cee7cc9b452531ccf05c9eccbe68acfba0fc4047456dfcf9bb0280.jpg) \nFigure 6. Neovascularization evaluation of wounds treated by FHE@exo hydrogel. (A) Blood vessels stained with α-SMA (red) and DAPI (blue) in wound bed at days 7 postoperative. Scale bar: $20\\mu\\mathsf{m}$ , respectively; (B) Quantitative analysis of vessels pre field at 7 days after surgery corresponding to α-SMA staining. \n\n# Conclusions \n\nIn summary, a novel bioactive FHE@exo hydrogel was fabricated facilely for enhanced angiogenesis and diabetic wound healing. The FHE@exo hydrogel shows bioactive multifunctional properties including injectability, self-healing, antibacterial activity, stimuli-responsive exosomes release. The FHE@exo hydrogel significantly improved the proliferation, migration and angiogenesis of HUVECs. Further in vivo study confirmed that the neovascularization and cellular proliferation of the FHE@exo hydrogel treated wounds were promoted, leading to faster granulation tissue formation, re-epithelialization and collagen remodeling within wound sites; thus diabetic wound healing process was accelerated. Moreover, compared with the FHE hydrogel, exo and control groups, the appearance of abundant skin appendages and much less scar tissue in the FHE@exo hydrogel group makes FHE@exo hydrogel a highly promising therapeutic for chronic wounds and skin regeneration. \n\n# Supplementary Material \n\nSupplementary figures and tables. http://www.thno.org/v09p0065s1.pdf \n\n# Acknowledgement \n\nThis study was financed by National Natural Science Foundation of China (grant No. 51502237, 51802227, 51872224), Natural Science Foundation of Zhejiang Province (grant No. LGF18H150008), and Medical Health Science and Technology project of Zhejiang Province (grant No. 2019315934), Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi’an Jiaotong University (Grant No. 2018LHMKFKT004). \n\n# Competing Interests \n\nThe authors have declared that no competing interest exists. \n\n# References \n\n1. Martí-Carvajal AJ, Gluud C, Nicola S, Simancas-Racines D, Reveiz L, Oliva P, et al. Growth factors for treating diabetic foot ulcers. Cochrane Database Syst Rev. 2015; 10: CD008548. \n2. Martin P. Wound healing--aiming for perfect skin regeneration. Science. 1997; 276: 75-81. \n3. Guo S, DiPietro LA. Factors affecting wound healing. J Dent Res. 2010; 89: 219-29. \n4. Du Y, Yu M, Ge J, Ma PX, Chen X, Lei B. Development of a multifunctional platform based on strong, intrinsically photoluminescent and antimicrobial silica‐poly (citrates)‐based hybrid biodegradable elastomers for bone regeneration. Adv. Funct. Mater. 2015; 25:5016-29. \n5. Pop MA, Almquist BD. Biomaterials: A potential pathway to healing chronic wounds? Exp Dermatol. 2017; 26: 760-3. \n6. Yu M, Lei B, Gao C, Yan J, Ma PX. Optimizing surface-engineered ultra-small gold nanoparticles for highly efficient miRNA delivery to enhance osteogenic differentiation of bone mesenchymal stromal cells. Nano Res. 2017; 10: 49-63. \n7. Wang Y, Han ZB, Song YP, Chao HZ. Safety of mesenchymal stem cells for clinical application. Stem Cells Int. 2012; 2012: 652034. \n8. Song M, Heo J, Chun JY, Bae HS, Kang JW, Kang H, et al. The paracrine effects of mesenchymal stem cells stimulate the regeneration capacity of endogenous stem cells in the repair of a bladder-outlet-obstruction-induced overactive bladder. Stem Cells Dev. 2014; 23: 654-63. \n9. Liang X, Ding Y, Zhang Y, Tse HF, Lian Q. Paracrine mechanisms of mesenchymal stem cell-based therapy: current status and perspectives. Cell Transplant. 2014; 23: 1045-59. \n10. Ferguson SW, Nguyen J. Exosomes as therapeutics: The implications of molecular composition and exosomal heterogeneity. J Control Release. 2016; 228: 179-90. \n11. Zhao F, Lei B, Li X, Mo Y, Wang R, Chen D, et al. Promoting in vivo early angiogenesis with sub-micrometer strontium-contained bioactive microspheres through modulating macrophage phenotypes. Biomaterials. 2018; 178: 36-47. \n12. Zhang J, Guan J, Niu $x,$ Hu G, Guo S, Li $\\scriptstyle\\mathbf{Q},$ et al. Exosomes released from human induced pluripotent stem cells-derived MSCs facilitate cutaneous wound healing by promoting collagen synthesis and angiogenesis. J Transl Med. 2015; 13: 49. \n13. Zhang B, Wang M, Gong A, Zhang X, Wu X, Zhu Y, et al. HucMSC‐exosome mediated‐Wnt4 signaling is required for cutaneous wound healing. Stem Cells. 2015; 33: 2158-68. \n14. Guo SC, Tao SC, Yin WJ, Qi X, Yuan T, Zhang CQ. Exosomes derived from platelet-rich plasma promote the re-epithelization of chronic cutaneous wounds via activation of YAP in a diabetic rat model. Theranostics. 2017; 7: 81-96. \n15. Liu $x,$ Yang Y, Li Y, Niu $x,$ Zhao B, Wang Y, et al. Integration of stem cell-derived exosomes with in situ hydrogel glue as a promising tissue patch for articular cartilage regeneration. Nanoscale. 2017; 9: 4430-8. \n16. Xi Y, Ge J, Guo Y, Lei B, Ma PX. Biomimetic Elastomeric Polypeptide-Based Nanofibrous Matrix for Overcoming Multidrug-Resistant Bacteria and Enhancing Full-Thickness Wound Healing/Skin Regeneration. ACS Nano. 2018;12:10772-84. \n17. Sharifzadeh G, Hosseinkhani H. Biomolecule-responsive hydrogels in medicine. Adv Healthc Mater. 2017; 6: 1700801. \n18. Annabi N, Rana D, Shirzaei Sani E, Portillo-Lara R, Gifford JL, Fares MM, et al. Engineering a sprayable and elastic hydrogel adhesive with antimicrobial properties for wound healing. Biomaterials. 2017; 139: 229-43. \n19. Taylor DL, Marc IHP. Self‐healing hydrogels. Adv Mater. 2016; 28: 9060-93. \n20. Li Y, Wang X, Fu YN, Wei Y, Zhao L, Tao L. Self-adapting hydrogel to improve the therapeutic effect in wound-healing. ACS Appl Mater Interfaces. 2018; 10: 26046-55. \n21. Mao C, Xiang Y, Liu $x,$ Cui Z, Yang X, Yeung KWK, et al. Photo-inspired antibacterial activity and wound healing acceleration by hydrogel embedded with $\\mathrm{Ag/Ag@AgCl/ZnO}$ nanostructures. ACS Nano. 2017; 11: 9010-21. \n22. Xie X, Mao C, Liu X, Zhang Y, Cui Z, Yang X, et al. Synergistic bacteria killing through photodynamic and physical actions of Graphene Oxide/Ag/Collagen coating. ACS Appl Mater Interfaces. 2017; 9: 26417-28. \n23. Xie $x,$ Mao C, Liu $x,$ Tan L, Cui $Z,$ Yang X, et al. Tuning the bandgap of photo-sensitive Polydopamine/Ag3PO4/Graphene Oxide coating for rapid, noninvasive disinfection of implants. ACS Cent Sci. 2018; 4: 724-38. \n24. Tan L, Li J, Liu X, Cui $Z,$ Yang X, Zhu S, et al. Rapid biofilm eradication on bone implants near-infrared light. Adv Mater. 2018; 30: e1801808. \n25. Li J, Tan L, Liu X, Cui $Z,$ Yang $x,$ Yeung KWK, et al. Balancing bacteria-osteoblast competition through selective physical puncture and biofunctionalization of ZnO/Polydopamine/Arginine-Glycine-Aspartic Acid-Cysteine nanorods. ACS Nano. 2017; 11: 11250-63. \n26. Boateng J, Catanzano O. Advanced therapeutic dressings for effective wound healing--a review. J Pharm Sci. 2015; 104: 3653-80. \n27. Liao Jia Y, Wang B, Shi K, Qian Z. Injectable hybrid poly(ε-caprolactone)-b-poly(ethylene glycol)-b-poly(ε-caprolactone) porous microspheres/alginate hydrogel cross-linked by calcium gluconate crystals deposited in the pores of microspheres improved skin wound healing. ACS Biomater Sci Eng. 2018; 4: 1029-36. \n28. Zheng Y, Liang Y, Zhang D, Sun X, Liang L, Li J, et al. Gelatin-based hydrogels blended with gellan as an injectable wound dressing. ACS Omega. 2018; 3: 4766-75. \n29. Ge J, Liu K, Niu W, Chen M, Wang M, Xue Y, et al. Gold and gold-silver alloy nanoparticles enhance the myogenic differentiation of myoblasts through p38 MAPK signaling pathway and promote in vivo skeletal muscle regeneration. Biomaterials. 2018; 175: 19-29. \n30. Wang M, Guo Y, Yu M, Ma PX, Mao C, Lei B. Photoluminescent and biodegradable polycitrate-polyethylene glycol-polyethyleneimine polymers as highly biocompatible and efficient vectors for bioimaging-guided siRNA and miRNA delivery. Acta Biomater. 2017;54:69-80. \n31. Zhou $\\scriptstyle{\\mathrm{\\mathrm{~L,~}}}$ Xi Y, Chen M, Niu W, Wang M, Ma P X, et al. A highly antibacterial polymeric hybrid micelle with efficiently targeted anticancer siRNA delivery and anti-infection in vitro/in vivo. Nanoscale. 2018; 10: 17304-17. \n32. Zhou L, Xi Y, Yu M, Wang M, Guo Y, Li P, et al. Highly antibacterial polypeptide-based amphiphilic copolymers as multifunctional non-viral vectors for enhanced intracellular siRNA delivery and anti-infection. Acta Biomater. 2017; 58: 90-101. \n33. Zhou Y, Nie W, Zhao J, Yuan X. Rapidly in situ forming adhesive hydrogel based on a PEG-maleimide modified polypeptide through Michael addition. J Mater Sci Mater Med. 2013; 24: 2277-86. \n34. Zhang K, Zhao X, Chen X, Wei Y, Du W, Wang Y, et al. Enhanced therapeutic effects of mesenchymal stem cell-derived exosomes with an injectable hydrogel for hindlimb ischemia treatment. ACS Appl Mater Interfaces. 2018; 10: 30081-91. \n35. Shi $\\scriptstyle{\\mathrm{\\mathsf{Q}}},$ Qian $Z,$ Liu D, Sun J, Wang X, Liu H, et al. GMSC-derived exosomes Ccmbined with a chitosan/silk hydrogel sponge accelerates wound healing in a diabetic rat skin defect model. Front Physiol. 2017; 8: 904. \n36. Tan A, Rajadas J, Seifalian AM. Exosomes as nano-theranostic delivery platforms for gene therapy. Adv Drug Deliver Rev. 2013; 65: 357-67. \n37. Wei Z, Yang JH, Zhou J, Xu F, Zrinyi M, Dussault PH, et al. Self-healing gels based on constitutional dynamic chemistry and their potential applications. Chem Soc Rev. 2014; 43: 8114-31. \n38. Lei ZQ, Xie P, Rong MZ, Zhang MQ. Catalyst-free dynamic exchange of aromatic Schiff base bonds and its application to self-healing and remolding of crosslinked polymer. J Mater Chem A. 2015; 3: 19662-8. \n39. De Jong OG, Van Balkom BW, Schiffelers RM, Bouten CV, Verhaar MC. Extracellular vesicles: potential roles in regenerative medicine. Front Immunol. 2014; 5: 608. \n40. Crivelli B, Chlapanidas T, Perteghella S, Lucarelli E, Pascucci L, Brini AT, et al. Mesenchymal stem/stromal cell extracellular vesicles: From active principle to next generation drug delivery system. J Control Release. 2017; 262: 104-17. \n41. Du Y, Ge J, Li Y, Ma $\\mathrm{~P~}\\boldsymbol{\\mathrm{X}},$ Lei B. Biomimetic elastomeric, conductive and biodegradable polycitrate-based nanocomposites for guiding myogenic differentiation and skeletal muscle regeneration. Biomaterials. 2018; 157: 40-50. \n42. Liang $\\mathbf{\\boldsymbol{x}},$ Zhang L, Wang S, Han $\\scriptstyle{\\mathrm{Q}},$ Zhao RC. Exosomes secreted by mesenchymal stem cells promote endothelial cell angiogenesis by transferring miR-125a. J Cell Sci. 2016; 129: 2182-9. \n43. Li M, Ke $\\scriptstyle{\\mathrm{Q}},$ Tao S, Guo S, Rui B, Guo Y. Fabrication of hydroxyapatite/chitosan composite hydrogels loaded with exosomes derived from miR-126-3p overexpressed synovial mesenchymal stem cells for diabetic chronic wound healing. J Mater Chem B. 2016; 4: 6830-41. \n44. Epstein FH, Singer AJ, Clark RAF. Cutaneous wound healing. N Engl J Med. 1999; 341: 738-46. \n45. Wu J, Zhu J, He C, Xiao $Z,$ Ye J, Li ${\\mathrm{\\boldmath~Y,~}}$ et al. Comparative study of heparin-poloxamer hydrogel modified bFGF and aFGF for in vivo wound healing efficiency. ACS Appl Mater Interfaces. 2016; 8: 18710-21. \n46. Gao W, Jin W, Li X, Wan L, Wang C, Lin C,et al. A highly bioactive bone extracellular matrix-biomimetic nanofibrous system with rapid angiogenesis promotes diabetic wound healing. J. Mater. Chem. B 2017; 5:7285-7296. \n47. Liu $x,$ Ma $\\scriptstyle\\mathrm{\\mathrm{~L,~}}$ Liang J, Zhang B, Teng J, Gao C. RNAi functionalized collagen-chitosan/silicone membrane bilayer dermal equivalent for full-thickness skin regeneration with inhibited scarring. Biomaterials. 2013; 34: 2038-48. \n48. Wang C, Wang $\\scriptstyle{\\mathrm{Q}},$ Gao W, Zhang $Z,$ Lou Y, Jin H, et al. Highly efficient local delivery of endothelial progenitor cells significantly potentiates angiogenesis and full-thickness wound healing. Acta Biomater. 2018; 69: 156-69 \n49. Liu X, Ma $\\scriptstyle{\\mathrm{~L,~}}$ Liang J, Zhang B, Teng J, Gao C. RNAi functionalized collagen-chitosan/silicone membrane bilayer dermal equivalent for full-thickness skin regeneration with inhibited scarring. Biomaterials. 2013; 34: 2038-48. \n50. Xu H, Lv F, Zhang Y, Yi Z, Ke $\\scriptstyle\\mathrm{Q},$ Wu C, et al. Hierarchically micro-patterned nanofibrous scaffolds with a nanosized bio-glass surface for accelerating wound healing. Nanoscale. 2015; 7: 18446-52. \n51. Gurtner GC, Werner S, Barrandon Y, Longaker MT. Wound repair and regeneration. Nature. 2008; 453: 314-21. \n52. Kurokawa I, Mizutani H, Kusumoto K, Nishijima S, Tsujita‐Kyutoku M, Shikata N, et al. Cytokeratin, filaggrin, and p63 expression in reepithelialization during human cutaneous wound healing. Wound Repair Regen. 2006; 14: 38-45. \n53. Weihs AM, Fuchs C, Teuschl AH, Hartinger J, Slezak P, Mittermayr R, et al. Shock wave treatment enhances cell proliferation and improves wound healing by ATP release-coupled extracellular signal-regulated kinase (ERK) activation. J Biol Chem. 2014; 289: 27090-104. \n54. Nomi M, Atala A, De Coppi P, Soker S. Principals of neovascularization for tissue engineering. Mol Aspects Med. 2002; 23: 463-83. \n55. Mao C, Xiang Y, Liu X, Cui Z, Yang X, Li Z, et al. Repeatable photodynamic therapy with triggered signaling pathways of fibroblast cell proliferation and differentiation to promote bacteria-accompanied wound healing. ACS Nano. 2018; 12: 1747-59. \n56. Li M, Liu $\\mathbf{\\boldsymbol{x}},$ Tan L, Cui Z, Yang X, Li $Z,$ et al. Noninvasive rapid bacteria-killing and acceleration of wound healing through photothermal/photodynamic/copper ion synergistic action of a hybrid hydrogel. Biomater Sci. 2018; 6: 2110-21. " + }, + { + "id": "10.1063_1.5143061", + "DOI": "10.1063/1.5143061", + "DOI Link": "http://dx.doi.org/10.1063/1.5143061", + "Relative Dir Path": "mds/10.1063_1.5143061", + "Article Title": "WIEN2k: An APW+lo program for calculating the properties of solids", + "Authors": "Blaha, P; Schwarz, K; Tran, F; Laskowski, R; Madsen, GKH; Marks, LD", + "Source Title": "JOURNAL OF CHEMICAL PHYSICS", + "Abstract": "The WIEN2k program is based on the augmented plane wave plus local orbitals (APW+lo) method to solve the Kohn-Sham equations of density functional theory. The APW+lo method, which considers all electrons (core and valence) self-consistently in a full-potential treatment, is implemented very efficiently in WIEN2k, since various types of parallelization are available and many optimized numerical libraries can be used. Many properties can be calculated, ranging from the basic ones, such as the electronic band structure or the optimized atomic structure, to more specialized ones such as the nuclear magnetic resonullce shielding tensor or the electric polarization. After a brief presentation of the APW+lo method, we review the usage, capabilities, and features of WIEN2k (version 19) in detail. The various options, properties, and available approximations for the exchange-correlation functional, as well as the external libraries or programs that can be used with WIEN2k, are mentioned. References to relevant applications and some examples are also given. (C) 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).", + "Times Cited, WoS Core": 1611, + "Times Cited, All Databases": 1641, + "Publication Year": 2020, + "Research Areas": "Chemistry; Physics", + "UT (Unique WOS ID)": "WOS:000519820500008", + "Markdown": "# \n\n# WIEN2k: An APW+lo program for calculating the properties of solids \n\nCite as: J. Chem. Phys. 152, 074101 (2020); https://doi.org/10.1063/1.5143061 \nSubmitted: 19 December 2019 . Accepted: 24 January 2020 . Published Online: 19 February 2020 \n\nPeter Blaha , Karlheinz Schwarz , Fabien Tran , Robert Laskowski , Georg K. H. Madsen , and Laurence D. Marks \n\n# COLLECTIONS \n\nNote: This paper is part of the JCP Special Topic on Electronic Structure Software. \n\n![](images/be6cfaa386b2338644e190a346d3fc9c389c3b37dbedb89e21f711dfe44eb544.jpg) \n\nThis paper was selected as an Editor’s Pick \n\n![](images/47343a55c9f8eaa5a80abdcb0181b5a77b2c5f2d27aac5f496221880cd574488.jpg) \n\n# WIEN2k: An APW+lo program for calculating the properties of solids EP \n\nCite as: J. Chem. Phys. 152, 074101 (2020); doi: 10.1063/1.514306 Submitted: 19 December 2019 $\\cdot\\cdot$ Accepted: 24 January 2020 • Published Online: 19 February 2020 \n\n# Peter Blaha,1,a) Karlheinz Schwarz,1 Fabien Tran,1 Robert Laskowski,2 Georg K. H. Madsen,1 and Laurence D. Marks3 \n\n# AFFILIATIONS \n\n1 Institute of Materials Chemistry, Vienna University of Technology, Getreidemarkt 9/165-TC, A-1060 Vienna, Austria \n2Institute of High Performance Computing, A∗STAR, 1 Fusionopolis Way, #16-16, Connexis 138632, Singapore \n3Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, USA \n\nNote: This paper is part of the JCP Special Topic on Electronic Structure Software. a)Author to whom correspondence should be addressed: pblaha@theochem.tuwien.ac.at \n\n# ABSTRACT \n\nThe WIEN2k program is based on the augmented plane wave plus local orbitals $(\\mathrm{APW+lo}^{\\cdot}$ ) method to solve the Kohn–Sham equations of density functional theory. The APW+lo method, which considers all electrons (core and valence) self-consistently in a full-potential treatment, is implemented very efficiently in WIEN2k, since various types of parallelization are available and many optimized numerical libraries can be used. Many properties can be calculated, ranging from the basic ones, such as the electronic band structure or the optimized atomic structure, to more specialized ones such as the nuclear magnetic resonance shielding tensor or the electric polarization. After a brief presentation of the APW $+\\mathrm{lo}$ method, we review the usage, capabilities, and features of WIEN2k (version 19) in detail. The various options, properties, and available approximations for the exchange-correlation functional, as well as the external libraries or programs that can be used with WIEN2k, are mentioned. References to relevant applications and some examples are also given. \n\n© 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). https://doi.org/10.1063/1.5143061. \n\n# I. INTRODUCTION \n\nQuantum mechanical calculations play a central role in understanding the properties of materials and, increasingly, predicting the properties of new materials. While in the early days, the emphasis was mainly on understanding the energy, atom positions, and band structure, modern codes now calculate a large number of different properties ranging from piezoelectric response to nuclear magnetic resonance (NMR) shielding, examples of which will be given later. With the advent of increasingly sophisticated methods and the ever increasing speed of computers over the last decades, in some cases the accuracy of quantum mechanical calculations rivals or even surpasses the accuracy of experimental measurements. \n\nThere are many different methods of theoretically modeling the behavior of electrons and atoms in materials. While earlier approaches focused on dealing with the electrons via wave functions,1 many current methods use density functional theory (DFT),2 which has significant speed advantages. Following the method outlined by Kohn and Sham3 (KS), the interacting many-body system of electrons is mapped onto a non-interacting system of quasiparticles, characterized by KS orbitals with a specific KS energy. They have many of the properties of the true electron wave functions and of particular importance is that one can fill up these KS orbitals as a function of their KS energy yielding the true electron density. The KS approach needs an exchange-correlation (XC) functional and the corresponding XC potential. However, the exact functional is unknown and approximations are needed (see Sec. II B). \n\nA second split in terms of methods is how the atomic positions are considered, and there are two main methods: cluster calculations for a finite number of atoms, which focus on the local properties of some atomic arrangement, and those which are designed to exploit the periodic nature of most solids; the WIEN2k code is an example of the latter. We represent the solid by a unit cell, which is repeated in all three directions, corresponding to periodic boundary conditions. This assumes that the solid is perfect, ordered, and infinite; however, a real crystal differs from this ideal situation, since it is finite, may contain defects or impurities, and may deviate from its ideal stoichiometry. For these important aspects and how to handle them using supercells, see Chap. 8.2 of Ref. 4. \n\nThere are many computational methods for solving the KS equations, for instance, linear combination of atomic orbitals (LCAO), numerical basis sets, pseudopotential schemes, or space partitioning methods. A recent comparison of these methods showed that especially all-electron codes predict essentially identical results, demonstrating a high reproducibility, whereas some pseudopotential codes lead to large deviations. One of the most accurate codes is our WIEN2k code,6 which is the focus of this paper and is based on the augmented plane wave (APW) method. Detailed descriptions including many conceptual and mathematical details are given in Ref. 7. The term all-electron (see Chap. 8.4 of Ref. 4) means that all electrons from the core (starting from the 1s shell) to the valence states are included. \n\nTurning to some historical specifics of our approach (see also Ref. 8), Slater9 proposed the original APW method. Unfortunately, the original formulation leads to a nonlinear eigenvalue problem due to the energy-dependent radial basis functions, which is computationally expensive. An important improvement came from Andersen,10 who introduced a linearization of this energy dependency, and Koelling and Arbman11 made the linearized-APW (LAPW) method a practical computational scheme using the muffin-tin (MT) approximation (see Sec. II). This was taken a step further by Freeman and collaborators who made the LAPW method a full-potential all-electron total energy method.12,13 \n\nThis LAPW method formed the basis for the original WIEN code.14 However, the LAPW method had the drawback that only one principal quantum number per angular momentum $\\ell$ could be described and thus failed to give reliable results for all elements on the left of the periodic table because these atoms require a proper description of shallow core states (semi-core) and valence states at the same time (e.g., 1s and 2s in Li or $3s p$ and $^{4s p}$ in Ti). This problem was solved by Singh,15 who introduced local orbitals (LOs) for the description of semi-core states. He also noted that the LAPW method needed a larger plane-wave basis set than the APW method. To overcome this problem, he suggested the augmented plane wave plus local orbitals $(\\mathrm{APW+lo})$ ) method,16,17 where the linearization of the energy-dependent radial wave function was facilitated by an extra local orbital (lo, different from an LO, see Sec. II), which has a superior plane-wave convergence compared to LAPW. Last but not least, the linearization of the energy dependency can introduce some inaccuracy in high precision calculations. This problem was finally solved by introducing additional higher (second) derivative LOs (HDLOs).18,19 These latest developments form the basis of the present WIEN2k_19 code,6 while previous versions have been described in several reviews.7,8,20–23 The method of our choice could be named ( $_\\mathrm{L)APW+lo+LO+HDLO},$ but we use a shorter acronym $\\mathrm{\\APW+lo}$ . It is described in detail in Sec. II A. \n\n# II. THEORY \n\nIn the APW-based methods, the unit cell is decomposed into spheres centered at the nuclear sites and an interstitial region,7 as shown in Fig. 1. These atomic spheres with radii $R_{\\mathrm{MT}}$ must not overlap, but should be chosen for computational efficiency as large as possible with the additional constraint that $R_{\\mathrm{MT}}$ for $d$ -elements should be chosen to be about $10\\%{-}20\\%$ bigger than for $s p$ -elements, while $f$ -elements should get even larger spheres because for identical sphere sizes the number of plane-waves (PWs) to reach convergence is largest for the localized $4f$ (5f ) electrons, medium for $3d$ (4d, 5d)-electrons, and much smaller for $\\boldsymbol{s p}$ -states. An exception is the H atom, whose sphere with short $\\mathrm{C-H}$ or $_\\mathrm{O-H}$ bonds should be chosen approximately half the size of $R_{\\mathrm{MT}}({\\mathrm{C}})$ or $R_{\\mathrm{MT}}(\\mathrm{O})$ . In WIEN2k, these sphere radii can be set automatically in an optimal way using the setrmt utility. Note that non-optimal sphere sizes may lead to poor convergence (eventually only for one particular atom) and significantly longer computing time or suffer from truncated Fourier or spherical-harmonic expansions. In the worst case, they can even produce “ghost-states” (unphysical eigenvalues in the occupied spectrum) if the $R_{\\mathrm{MT}}$ of an $\\boldsymbol{s p}$ -element is much larger than that of the other atoms. \n\nThe electron density $\\rho$ and KS potential $\\nu^{\\mathrm{KS}}$ (defined in Sec. II B) are expanded as a Fourier series in the interstitial $(I)$ region (K denotes a reciprocal lattice vector in units of inverse bohr) and as lattice harmonics (symmetry adapted combinations of spherical harmonics $Z_{L M})^{24}$ times radial functions $\\rho_{L M}(r)\\ [\\nu_{L M}^{\\mathrm{KS}}(r)$ for the potential] inside the spheres $\\cdot S_{t}.$ , where $t$ is the atom index), \n\n$$\n\\begin{array}{r}{\\rho(\\mathbf{r})=\\left\\{\\begin{array}{l l}{\\displaystyle\\sum_{L,M}\\rho_{L M}\\big(r\\big)Z_{L M}\\big(\\hat{\\mathbf{r}}\\big),}&{\\mathbf{r}\\in S_{t}}\\\\ {\\displaystyle\\sum_{\\mathbf{K}}\\rho_{\\mathbf{K}}e^{i\\mathbf{K}\\cdot\\mathbf{r}},}&{\\mathbf{r}\\in I,}\\end{array}\\right.}\\end{array}\n$$ \n\n$$\n\\nu^{\\mathrm{KS}}(\\mathbf{r})=\\left\\{\\begin{array}{l l}{\\displaystyle\\sum_{L,M}\\nu_{L M}^{\\mathrm{KS}}(r)Z_{L M}(\\hat{\\mathbf{r}}),}&{\\mathbf{r}\\in S_{t}}\\\\ {\\displaystyle\\sum_{\\mathbf{K}}\\nu_{\\mathbf{K}}^{\\mathrm{KS}}e^{i\\mathbf{K}\\cdot\\mathbf{r}},}&{\\mathbf{r}\\in I.}\\end{array}\\right.\n$$ \n\nBy default, the Fourier expansion runs up to $\\mathbf{\\left|K\\right|}=12$ for large $R_{\\mathrm{MT}}$ (16 for $R_{\\mathrm{MT}}<1.2$ ; 20 for $R_{\\mathrm{MT}}<0.7$ bohr), while the angular momentum expansion truncates at $L=6$ . Note that the old “MT” approximation uses a constant value in the interstitial (i.e., only $\\mathbf{K}=0\\mathbf{\\dot{\\Omega}}$ ) and a spherically symmetric density/potential inside the spheres (i.e., only $L=0\\mathrm{\\dot{\\Omega}}$ ). \n\n![](images/946f69df82ef0f0dba84a867d0fbcdd8f3564d68505f34f9edec2468823bab4c.jpg) \nFIG. 1. Schematic unit cell with large transition metal (TM), medium O and small H spheres, and the interstitial region in between. \n\nThis space decomposition plays a crucial role in the definition of core and valence electrons, which are treated differently in APWtype methods. Core states are defined as having wave functions (densities) completely confined inside the atomic spheres. Thus, we do not use the standard definitions of core and valence, but, e.g., in $3d$ transition metals (TMs), the 3s and $3p$ states are also considered as valence, since a couple of percent of their charge leaks out of the atomic sphere. To distinguish them from the conventional definition, we call them semi-core states. Typically, these states are treated using LOs (see below) and their energies are less than 6 Ry below the Fermi energy, but in special situations (small spheres due to short nearest neighbor distances or high pressure), even lower lying states (such as Al- ${2p}$ ) have to be included. Relativistic effects are important for the core states, and thus, they are calculated by numerically solving the radial Dirac equation in the spherical symmetric part of the potential $\\nu^{\\mathrm{KS}}$ . Core states are constrained to be localized and not hybridized with states at the neighboring atoms, but we use a thawed core (no frozen core approximation), i.e., the core states are recalculated in each self-consistent field cycle.7 The semi-core and valence electrons are commonly treated scalar relativistically, i.e., including mass velocity and Darwin $s$ -shift corrections, but neglecting spin– orbit (SO) interactions.7,25 The SO effects can later on be included in a second variational step using the scalar-relativistic orbitals as a basis.7,26 Since $p_{1/2}$ radial wave functions differ considerably from scalar relativistic (or ${{p}_{3/2}}$ ) orbitals, one can also enrich the basis set with additional $p_{1/2}$ local orbitals, specifically, an LO (see below) with a $p_{1/2}$ radial wave function, which is added in the second-variational SO calculation.27 \n\n# A. The APW+lo method as implemented in WIEN2k \n\nThe basis functions for the valence electrons consist of APWs, which are plane waves in the interstitial region augmented with radial wave functions $u_{t\\ell}(r,E_{t\\ell})$ defined at a fixed energy $E_{t\\ell}$ , and lo.7,16,17 An APW is given by \n\n$$\n\\phi_{\\mathbf{k}+\\mathbf{K}}^{\\mathrm{APW}}\\left(\\mathbf{r}\\right)=\\left\\{\\begin{array}{l l}{\\sum_{\\ell,m}A_{t\\ell m}^{\\mathbf{k}+\\mathbf{K}}u_{t\\ell}\\big(r,E_{t\\ell}\\big)Y_{\\ell m}\\big(\\hat{\\mathbf{r}}\\big),}&{\\mathbf{r}\\in S_{t}}\\\\ {\\frac{1}{\\sqrt{\\Omega}}e^{i(\\mathbf{k}+\\mathbf{K})\\cdot\\mathbf{r}},}&{\\mathbf{r}\\in I,}\\end{array}\\right.\n$$ \n\nwhere $\\mathbf{k}$ is a point in the first Brillouin zone (BZ), $Y_{\\ell m}(\\hat{\\mathbf{r}})$ are spherical harmonics, and $\\boldsymbol{u}_{t\\ell}$ are solutions of the scalar-relativistic radial KS equation7 inside the sphere $S_{t}$ . Note that these radial functions $\\boldsymbol{u}_{t\\ell}$ are recalculated in each self-consistent-field (SCF) cycle, allowing for an expansion/contraction corresponding to the given charge state (ionicity) of the atom. These adaptive basis functions are part of the reason for the high accuracy of APW-based methods. The coefficients $A_{t\\ell m}^{\\mathbf{k+K}}$ are chosen such that the interstitial and sphere parts of the APW match at the sphere boundary. However, these APWs allow no variations of the radial functions for eigenvalues different than $E_{t\\ell}$ and thus would be a poor basis. To overcome this constraint, the energy dependency is handled by a lo, which is nonzero only inside a MT sphere, and given by \n\n$$\n\\phi_{t\\ell m}^{\\mathrm{lo}}(\\mathbf{r})=\\left\\{\\begin{array}{l l}{\\left[A_{t\\ell m}^{\\mathrm{lo}}u_{t\\ell}(r,E_{t\\ell})+B_{t\\ell m}^{\\mathrm{lo}}\\dot{u}_{t\\ell}(r,E_{t\\ell})\\right]Y_{\\ell m}(\\hat{\\mathbf{r}}),}&{\\mathbf{r}\\in S_{t}}\\\\ {0,}&{\\mathbf{r}\\in I,}\\end{array}\\right.\n$$ \n\nwhere $\\dot{u}_{t\\ell}$ is the first energy derivative of $\\boldsymbol{u}_{t\\ell}$ . The coefficients $A_{t\\ell m}^{\\mathrm{lo}}$ and $B_{t\\ell m}^{\\mathrm{lo}}$ are chosen such that $\\phi_{t\\ell m}^{\\mathrm{lo}}$ is zero at $R_{\\mathrm{MT}}$ and normalized. \n\nThe APW $+\\mathrm{lo}$ basis set has the advantage of a superior PW convergence as compared to the standard LAPW method,7,17 reducing the number of PWs by almost $50\\%$ , but it needs additional lo basis functions. Thus, in WIEN2k, the default is to restrict the $\\ell_{\\mathrm{max}}$ to the chemical $\\ell$ -values ${\\mathfrak{s p}}(d,f)$ , which are hard to converge, but use a standard LAPW basis set inside the spheres for the higher $\\ell$ values (by default up to $\\ell_{\\mathrm{max}}=10$ ), \n\n$$\n\\phi_{\\mathbf{k}+\\mathbf{K}}^{\\mathrm{LAPW}}(\\mathbf{r})=\\left\\{\\begin{array}{l l}{\\sum_{\\ell,m}\\left[A_{t\\ell m}^{\\mathbf{k}+\\mathbf{K}}u_{t\\ell}\\big(r,E_{t\\ell}\\big)+B_{t\\ell m}^{\\mathbf{k}+\\mathbf{K}}\\dot{u}_{t\\ell}\\big(r,E_{t\\ell}\\big)\\right]Y_{\\ell m}\\big(\\hat{\\mathbf{r}}\\big),}&{\\mathbf{r}\\in S_{t}}\\\\ {\\frac{1}{\\sqrt{\\Omega}}e^{i(\\mathbf{k}+\\mathbf{K})\\cdot\\mathbf{r}},}&{\\mathbf{r}\\in I,}\\end{array}\\right.\n$$ \n\nwhere the coefficients $A_{t\\ell m}^{\\mathbf{k+K}}$ and $B_{t\\ell m}^{\\mathbf{k}+\\mathbf{K}}$ are chosen such that $\\phi_{\\mathbf{k}+\\mathbf{K}}^{\\mathrm{LAPW}}$ and its first derivative are continuous at the sphere boundary. \n\nAs mentioned before, semi-core states (or also high-lying empty states) cannot be described accurately by $\\mathrm{\\APW+lo}$ . For these states, the basis set has to be improved, and this can be done by adding another type of local orbitals, the LOs, containing radial functions $\\boldsymbol{u}_{t\\ell}$ calculated at the appropriate (e.g., semi-core) energy $E_{t\\ell}^{\\mathrm{LO},i}$ , \n\n$$\n\\phi_{t\\ell m}^{\\mathrm{LO},i}(\\mathbf{r})=\\left\\{\\begin{array}{l l}{\\big[A_{t\\ell m}^{\\mathrm{LO},i}u_{t\\ell}\\big(r,E_{t\\ell}\\big)+C_{t\\ell m}^{\\mathrm{LO},i}u_{t\\ell}\\big(r,E_{t\\ell}^{\\mathrm{LO},i}\\big)\\big]Y_{\\ell m}\\big(\\hat{\\mathbf{r}}\\big),}&{\\mathbf{r}\\in S_{t}}\\\\ {0,}&{\\mathbf{r}\\in I.}\\end{array}\\right.\n$$ \n\nFor instance, for $\\mathrm{TiO}_{2}$ , one would use the Ti- ${3p}$ energy to calculate $u_{\\mathrm{Ti},1}(r,E_{\\mathrm{Ti},1}^{\\mathrm{LO},i})$ and then add some Ti- $^{4p}$ radial function $u_{\\mathrm{Ti,1}}(r,E_{\\mathrm{Ti,1}})$ , choo(sing the) coefficients $A_{t\\ell m}^{\\mathrm{LO},i}$ and $C_{t\\ell m}^{\\mathrm{LO},i}$ such that the LO is zero at the $R_{\\mathrm{MT}}$ and is normalized. By adding such LOs (representing Ti- $3p$ states), a consistent and accurate description of both the Ti- $3p$ semi-core and Ti- $^{4p}$ valence states is possible, retaining orthogonality, which is not assured when the multiple-window approach is used (see Ref. 7). Cases where this improvement is essential is the electric field gradient (EFG) calculation of rutile $\\mathrm{TiO}_{2}{}^{28}$ or lattice parameter calculations of compounds with such elements. Note how lo [Eq. (4)] and LO [Eq. (6)] differ in their respective second terms. \n\nA clever choice of energy parameters $E_{t\\ell}$ in Eqs. (3)–(6) is essential for accurate results, and WIEN2k has several automatic ways to make an optimal choice in most cases.6 $E_{t\\ell}$ of semi-core states (actually, of all states whose energy in the free atom is more than $0.5~\\mathrm{Ry}$ below the highest occupied atomic orbital, e.g., also C-2s or Ar-3s states) are determined by taking the average of the two energies $E_{\\mathrm{{bottom}}}$ and $E_{\\mathrm{top}}$ , where the corresponding $u_{t\\ell}(R_{\\mathrm{MT}})$ is zero or has zero slope. For localized $d$ or $f$ valence electrons, the same procedure is used, but $E_{\\mathrm{top}}$ is searched only 0.5 Ry above $E_{F}$ to ensure that the energy parameters are set below $E_{F}$ . The energy parameters of all other valence states are set to $0.2\\mathrm{Ry}$ below $E_{F}$ $[0.2\\mathrm{Ry}$ above $E_{F}$ if there is a high lying semi-core LO). Thus, all our energy parameters are dynamically updated during the SCF cycle and not fixed by input. \n\nImplicit in this approximation is a linearization of the energy dependency of the radial wave functions. Since the true $u_{t\\ell}(r,\\ E_{t\\ell}\\ =\\ \\varepsilon_{i})$ varies most for more localized states (e.g., $3d$ or $\\left|4f\\right|$ at larger distances from the nucleus, large spheres and a large valence bandwidth could cause a poor description of the variations of $u_{t\\ell}(r,\\varepsilon_{i})$ with energy, leading to a significant dependency of the results on $R_{\\mathrm{MT}}$ (where smaller $R_{\\mathrm{MT}}$ yield more correct results but with a larger computational effort). This can be solved by adding an LO, which involves the second energy derivative of $u_{t\\ell}$ , called an HDLO,18,19 \n\n$$\n\\phi_{t\\ell m}^{\\mathrm{HDLO}}(\\mathbf{r})=\\left\\{\\begin{array}{l l}{\\left[A_{t\\ell m}^{\\mathrm{HDLO}}u_{t\\ell}\\left(r,E_{t\\ell}\\right)+C_{t\\ell m}^{\\mathrm{HDLO}}\\ddot{u}_{t\\ell}\\left(r,E_{t\\ell}\\right)\\right]Y_{\\ell m}(\\hat{\\mathbf{r}}),}&{\\mathbf{r}\\in S_{t}}\\\\ {0,}&{\\mathbf{r}\\in I.}\\end{array}\\right.\n$$ \n\nFigure 2 illustrates the effect of adding HDLOs for the lattice parameter of fcc-La as a function of $R_{\\mathrm{MT}}$ . The lattice parameter becomes independent of $R_{\\mathrm{MT}}$ when both $d$ and $f$ -HDLOs are added to the basis set, while the standard $_{\\mathrm{APW+lo+LO}}$ basis (LOs for 5s, $5p$ states) produces an error of 0.04 bohr for the largest $R_{\\mathrm{MT}}$ . \n\nThe KS orbitals are expanded using the combined basis set described above ( $n$ is the band index), \n\n$$\n\\psi_{n\\mathbf{k}}=\\sum_{i}c_{n\\mathbf{k}}^{i}\\phi_{i},\n$$ \n\nand the coefficients $c_{n\\mathbf{k}}^{i}$ are determined by the Rayleigh–Ritz variational principle. The number of APW (or LAPW) basis functions Eq. $(3)$ [or Eq. (5)] is determined by the cutoff value $K_{\\mathrm{max}}$ for the reciprocal lattice vectors $\\mathbf{K}$ such that $\\left\\vert\\mathbf{k}+\\mathbf{K}\\right\\vert\\leq K_{\\operatorname*{max}}$ and depends on the smallest of the atomic radii $R_{\\mathrm{MT}}^{\\mathrm{min}}$ a∣nd the∣ t≤ype of atom. Typically, the necessary $R_{\\mathrm{MT}}^{\\mathrm{min}}K_{\\mathrm{max}}$ values range from 3 (for small H-spheres) to 7 for $\\boldsymbol{s p}$ -elements, 8 for TM- $\\cdot d$ elements, and 9 for $4f$ lanthanides. These values can be reduced by 0.5–1 for low quality screening calculations and increased by 0.5–2 for highest precision. It should be mentioned that the efficiency of the $\\mathrm{\\APW+lo}$ method depends crucially on the possible $R_{\\mathrm{MT}}$ values. For instance, the $_{\\mathrm{O-}2p}$ states converge well with $R_{\\mathrm{MT}}^{\\mathrm{O}}K_{\\mathrm{max}}=7$ . In $\\mathrm{MgO}$ , one can use $R_{\\mathrm{MT}}^{\\mathrm{O}}=2$ bohrs, leading to a very small PW cutoff energy of $170\\ \\mathrm{eV}$ . However, in $\\mathrm{Mg(OH)}_{2}$ , one has to use $R_{\\mathrm{MT}}^{\\mathrm{O}}=1.1$ bohrs due to the short $_\\mathrm{O-H}$ distances, leading to a PW cutoff of $550~\\mathrm{eV}$ , i.e., an order of magnitude larger effort. \n\n![](images/6c40490a95f2cc390536ac54b4f183c6d3f3b829255c78f069431875580e759c.jpg) \nFIG. 2. Lattice parameter (bohr) using PBE of fcc La as a function of $R_{\\mathrm{MT}}$ using the standard $A P W+10+10$ basis set, or with additional f -HDLO or $d{+}f$ -HDLO. \n\nThe specific setup of all these basis functions can, of course, be selected manually by experts, but one of the great strengths of WIEN2k is that the default input usually works quite well and is fairly robust. \n\n# B. Available DFT approximations \n\nIn DFT, the total energy of the system is given by \n\n$$\nE_{\\mathrm{tot}}=T_{s}+E_{\\mathrm{en}}+E_{\\mathrm{H}}+E_{\\mathrm{xc}}+E_{\\mathrm{nn}}.\n$$ \n\nThe terms on the right-hand side represent the noninteracting kinetic, electron–nucleus, Hartree, XC, and nucleus–nucleus energies, respectively. The variational principle leads to the KS [or generalized $\\mathrm{{KS^{29}\\left(g K S\\right)}}]$ equations (in this section, the orbital index $i$ is a shorthand notation for valence and core orbitals), \n\n$$\n\\biggl(-\\frac{1}{2}{\\boldsymbol{\\nabla}}^{2}+\\nu^{\\mathrm{KS}}(\\mathbf{r})\\biggr)\\psi_{i}(\\mathbf{r})=\\varepsilon_{i}\\psi_{i}(\\mathbf{r}),\n$$ \n\nwhere $\\nu^{\\mathrm{KS}}$ is the KS potential, \n\n$$\n\\nu^{\\mathrm{KS}}(\\mathbf{r})=\\nu_{\\mathrm{en}}(\\mathbf{r})+\\nu_{\\mathrm{H}}(\\mathbf{r})+\\nu_{\\mathrm{xc}}(\\mathbf{r}),\n$$ \n\nwhich is the sum of the electron–nucleus, Hartree, and XC potentials. Choosing an appropriate functional $E_{\\mathrm{xc}}$ in Eq. (9) [and potential $\\nu_{\\mathrm{xc}}$ in Eq. (11)] for the XC term is crucial in order to obtain reliable results for the problem at hand.30–32 Several hundred33,34 different functionals are available in the literature; some of them were proposed as general-purpose functionals, while others were devised for a specific property (e.g., bandgap) or types of systems (e.g., van der Waals). Numerous functionals have been implemented in the WIEN2k code, and below, we provide a brief overview of the different families of functionals. Note that for XC functionals that depend explicitly on the electron density $\\rho$ , e.g., the local density approximation (LDA) or the generalized gradient approximation (GGA), the XC potential $\\nu_{\\mathrm{xc}}$ is multiplicative, while for functionals that depend implicitly on $\\rho$ , e.g., meta-GGA (MGGA) or hybrids, the XC potential is non-multiplicative when implemented in the $\\mathrm{gKS}$ scheme. \n\n# 1. LDA, GGA, and MGGA \n\nThe LDA, GGA, and MGGA represent the first three rungs of Jacob’s ladder of XC functionals.35 These approximations are semilocal, since $E_{x c}$ is defined as \n\n$$\nE_{\\mathrm{xc}}=\\int\\varepsilon_{\\mathrm{xc}}({\\bf r})d^{3}r,\n$$ \n\nand the XC energy density $\\varepsilon_{\\mathrm{xc}}$ depends only locally on some properties of the system. In the LDA, $\\varepsilon_{\\mathrm{xc}}$ depends on the electron density $\\begin{array}{r}{\\rho=\\sum_{i=1}^{N}\\bigl|\\psi_{i}\\bigr|^{2}}\\end{array}$ , while in the GGA, $\\varepsilon_{\\mathrm{xc}}$ depends also on the first derivative $\\boldsymbol{\\nabla}\\rho$ . At the MGGA level, the functionals depend additionally on the L∇aplacian of the electron density $\\boldsymbol{\\nabla}^{2}\\rho$ and/or the kinetic-energy density $t=\\left(1/2\\right)\\sum_{i=1}^{N}\\boldsymbol{\\nabla}\\psi_{i}^{*}\\cdot\\boldsymbol{\\nabla}\\psi_{i}.$ . Semi∇local functionals are the most commonly used m∑et=h ods n the solid-state community for the calculation of properties depending on the total energy such as the geometry, cohesive energy, or the adsorption energy of a molecule on a surface. The main reason is that they are faster than all other types of approximations and therefore allow calculations of larger systems. \n\nThere is a huge literature on the performance of semilocal functionals, concerning the geometry and cohesive energy of solids. Extensive benchmark studies have been conducted by us36–39 and others (see, e.g., Refs. 40 and 41). The results of these works showed that among the GGA functionals, those with a small enhancement factor such as AM05,42 PBEsol,43 or a few others44–46 are the most accurate for the lattice constant and bulk modulus, while the standard $\\mathrm{PBE}^{47}$ is the best choice for the cohesive energy. At the MGGA level, the SCAN functional48 is becoming increasingly popular and has been shown to be simultaneously as good as the best GGAs for the geometry (e.g., PBEsol) and the cohesive energy (PBE).39,41 However, it should be mentioned that SCAN can be quite problematic for iterant magnetic systems49,50 or alkali metals.51 \n\nMany semilocal functionals have been implemented directly in the WIEN2k code, but basically all existing semilocal functionals can be used because WIEN2k is interfaced to the Libxc33,34 library of XC functionals. One current limitation is that the MGGA functionals are not yet implemented self-consistently (by default, the GGA PBE potential is used for generating the orbitals although the user can choose another potential). \n\n# 2. Hybrid functionals \n\nBeginning in the 21st century, hybrid functionals,52 which belong to the fourth rung of Jacob’s ladder, started to be extensively used for calculations of solids.53–55 The one that is currently the most popular is HSE06,56–58 which is a screened version of the other wellknown PBE0.59,60 In (screened) hybrid functionals, the exchange energy is a linear combination of a semilocal (SL) functional and the Hartree–Fock (HF) expression, \n\n$$\nE_{\\mathrm{xc}}^{\\mathrm{hybrid}}=E_{\\mathrm{xc}}^{\\mathrm{SL}}+\\alpha_{\\mathrm{x}}\\Big(E_{\\mathrm{x}}^{(\\mathrm{scr})\\mathrm{HF}}-E_{\\mathrm{x}}^{(\\mathrm{scr})\\mathrm{SL}}\\Big),\n$$ \n\nwhere \n\n$$\n\\begin{array}{l}{{\\displaystyle E_{\\mathrm{x}}^{(\\mathrm{scr})\\mathrm{HF}}=-\\frac{1}{2}\\sum_{i=1}^{N}\\sum_{j=1}^{N}\\delta_{\\sigma_{i}\\sigma_{j}}\\iint\\psi_{i}^{*}(\\mathbf{r})\\psi_{j}(\\mathbf{r})}}\\\\ {{\\displaystyle~\\times\\nu\\big(\\left|\\mathbf{r}-\\mathbf{r}^{\\prime}\\right|\\big)\\psi_{j}^{*}(\\mathbf{r}^{\\prime})\\psi_{i}(\\mathbf{r}^{\\prime})d^{3}r d^{3}r^{\\prime}}.}\\end{array}\n$$ \n\nIn Eq. (14), $\\nu$ is either the bare Coulomb potential $\\nu=1/\\big|\\mathbf{r}-\\mathbf{r}^{\\prime}\\big|$ for unscreened hybrids or a potential that is screened at=sh/o∣rt−or l∣ong range for screened hybrids. For solids, it is computationally advantageous to use a potential that is short range, for instance, the Yukawa potential $\\nu=\\left.e^{-\\lambda\\left|\\mathbf{r}-\\mathbf{r}^{\\prime}\\right|}/\\left|\\mathbf{r}-\\mathbf{r}^{\\prime}\\right|$ (Ref. 61) or $\\nu=\\mathrm{erfc}(\\mu|\\mathbf{r}-\\mathbf{r}^{\\prime}|)/\\big|\\mathbf{r}-\\mathbf{r}^{\\prime}\\big|$ (Ref. 56), where erfc is the complementary error function. Although hybrid functionals are also used for the total energy (geometry optimization, and cohesive energy), they are particularly interesting for properties derived from the electronic band structure such as the bandgap, for which they significantly improve upon standard GGA functionals such as PBE (see Refs. 62–65 for recent extensive benchmarking). \n\nIn WIEN2k, unscreened and screened hybrid functionals are implemented66 according to the scheme of Massidda et al.,67 which is based on the pseudo-charge method for calculating the Coulomb potential.12 The treatment of the Coulomb singularity is done by multiplying the Coulomb potential by a step function,68 which is very efficient compared to other methods.69 The screened hybrid functionals use the Yukawa potential, and in Ref. 66, it was shown that the results obtained with the PBE-based hybrid YS-PBE0 for the bandgap are almost identical to those obtained with HSE06 (which uses the erfc screened potential), provided that the screening parameter is chosen appropriately $~[\\lambda~=~(3/2)\\mu$ , see Ref. 70]. Because of the double integral and summations over orbitals in the HF exchange [Eq. (14)], the calculations are much more expensive (between 10 and 1000 times) than semilocal methods; however, there are a couple of ways to speed-up such calculations significantly. For instance, one can first use a rather crude $\\mathbf{k}$ -mesh and later on improve the k convergence in a few additional iterations continuing the previous calculations. Furthermore, a reduced $\\mathbf{k}$ -mesh for the internal loop in the HF potential is possible,71 and finally, often a one-shot procedure72,73 is sufficient, where the hybrid orbitals and eigenvalues are calculated perturbatively on top of a calculation with the semilocal functional on which the hybrid functional is based. \n\nCalculations using hybrid functionals in WIEN2k can be found in Refs. 74–77 for applications and in Refs. 39, 64, and 78–80 for various benchmark studies. \n\n# 3. On-site methods for strongly correlated electrons \n\nThe high computational cost of hybrid methods discussed in Sec. II B 2 limits the size of the systems that can be treated. Alternatively, one can use an on-site method, namely, $\\mathrm{DFT}+U,^{81}$ exact exchange for correlated electrons (EECE),82 or on-site hybrids,83 which can be viewed as approximate but cheap versions of the hybrid or HF methods. In these methods, a hybrid/HF treatment is applied only to the electrons of a particular angular momentum belonging to a selected atom. However, using such an on-site scheme only makes sense when the considered electrons are well localized around the atom, which is, in general, the case for strongly correlated electrons. The on-site methods are mostly applied to open $3d.$ -, 4f -, or $5f$ -shells in strongly correlated materials in order to improve the description of the electronic and magnetic properties. For such systems, the standard GGA methods provide results that are often even qualitatively inaccurate.84 \n\nDifferent versions of $\\mathrm{DFT}{+}U$ exist in the literature, and those available in WIEN2k are the following: (1) the original version,81 called Hubbard in mean field (HMF) in WIEN2k, (2) the fully localized limit version,85,86 called self-interaction correction (SIC), and (3) the around mean-field (AMF) version.86 The details of the implementation of $\\mathrm{DFT}+U$ in the LAPW method can be found in the work of Shick et al.,87 while a very good summary and discussion of the $\\mathrm{DFT}+U$ flavors is given in Ref. 88. Note that since the on-site term is applied only inside the sphere surrounding the atom of interest,87 the results may depend on the radius $R_{\\mathrm{MT}}$ of this sphere (see Refs. 89 and 90 for illustrations), which is a drawback of the on-site methods. Among our works reporting DFT $+U$ calculations, we mention Refs. 77 and 91–93. \n\nFor many technical aspects, the EECE and on-site hybrid methods are quite similar to $\\mathrm{DFT}{+}U$ ; however, there are two conceptual differences. The first one concerns the double-counting term. While in $\\mathrm{DFT}+U_{:}$ , the double-counting term is derived using concepts from the Hubbard model (see Ref. 88 for a summary of the various expressions), in EECE and on-site hybrids, it is given by the semilocal expression of $E_{\\mathrm{xc}}$ (e.g., PBE) evaluated with the density of the strongly correlated electrons.82 The second difference is the calculation of the Slater integrals in the Coulomb and Hartree– Fock terms. In $\\mathrm{DFT}+U_{:}$ , they are parameterized with screened intraatomic Coulomb $(U)$ and exchange $(J)$ interactions, which are usually chosen empirically. However, in EECE and on-site hybrids, the Slater integrals are calculated explicitly using the orbitals of the strongly correlated electrons.82 The results obtained with the on-site hybrid methods can be found in Refs. 83 and 94–98. \n\nThe results obtained with $\\mathrm{DFT}+U$ and on-site hybrids should be qualitatively similar in many (but not necessary all) cases.83,99–101 Actually, both methods contain empirical parameters: $U$ and $J$ (or only $U_{\\mathrm{eff}}=U-J)$ in $\\mathrm{DFT}+U$ and $\\alpha_{\\mathrm{x}}$ [Eq. (13)] in on-site hybrids. In both cases t−he results will depend crucially on the value of the parameters $(U,J)$ or $\\alpha_{\\mathrm{x}}$ . For applications, the EECE method82 is less interesting since it consists of $100\\%$ of unscreened Hartree– Fock exchange applied to correlated electrons, which usually is not accurate. \n\nTechnically, we mention that calculations with the on-site methods can only be done in a spin-polarized mode, i.e., with runsp_lapw. However, it is possible to apply on-site methods to non-magnetic systems by using the script runsp_c_lapw, which constrains the system to have no spin polarization. \n\n# 4. Methods for bandgaps \n\nIt is well known that the GGA functionals that are commonly used for total-energy calculations, such as PBE, provide bandgaps that are much smaller than experiment.57 Thus, one has to resort to other methods to get reliable results for the bandgap. Hybrid functionals and the GW method102,103 (see Sec. III I 4) provide much more accurate values; however, they are also significantly more expensive than semilocal methods and cannot be applied easily to very large systems. Therefore, fast semilocal methods have been proposed specifically intended for bandgap calculations, and those which are available in WIEN2k are discussed below. Note that a more detailed discussion of the DFT methods for bandgaps is provided in Ref. 104. \n\nThe Tran–Blaha modified Becke–Johnson (TB-mBJ) potential105 consists of a modified version of the BJ potential106 for exchange (which reproduces the exact KS potential of atoms very well106,107) and $\\mathrm{{LDA}^{\\hat{1}08}}$ for correlation. The exchange part, which is a MGGA since it depends on the kinetic-energy density $t$ , is \n\n$$\n\\nu_{\\mathrm{x}}^{\\mathrm{mBJ}}(\\mathbf{r})=c\\nu_{\\mathrm{x}}^{\\mathrm{BR}}(\\mathbf{r})+(3c-2)\\frac{1}{\\pi}\\sqrt{\\frac{5}{6}}\\sqrt{\\frac{t(\\mathbf{r})}{\\rho(\\mathbf{r})}},\n$$ \n\nwhere $\\nu_{\\mathrm{x}}^{\\mathrm{BR}}$ is the Becke–Roussel (BR) potential109 and \n\n$$\nc=\\alpha+\\beta g^{p}\n$$ \n\nwith \n\n$$\ng={\\frac{1}{V_{\\mathrm{cell}}}}\\int_{\\mathrm{cell}}{\\frac{\\left|\\nabla\\rho(\\mathbf{r}^{\\prime})\\right|}{\\rho(\\mathbf{r}^{\\prime})}}d^{3}r^{\\prime}\n$$ \n\nbeing the average of $|\\nabla\\rho|/\\rho$ in the unit cell. The parameters in Eq. (16) are $\\alpha=-0.012$ ∇, $\\beta=1.023~\\mathrm{bohrs}^{1/2}$ , and $\\boldsymbol{p}=1/2$ and were determined by mi−nimizing the mean absolute error of the bandgap for a set of solids.105 As shown in benchmark studies,64,65,80 the TB-mBJ potential is currently the most accurate semilocal method for bandgap prediction. Other parameterizations of Eq. (16) were proposed in Refs. 110 and 111 and are also available in WIEN2k. \n\nThe GLLB-SC potential112,113 is given by \n\n$$\n\\begin{array}{l}{{\\displaystyle\\nu_{\\mathrm{{xc}}}^{\\mathrm{GLLB-SC}}({\\bf r})=2e_{\\mathrm{x}}^{\\mathrm{PBEsol}}({\\bf r})+K_{\\mathrm{x}}^{\\mathrm{LDA}}}\\ ~}\\\\ {{\\displaystyle~\\times~\\sum_{n,{\\bf k}}\\sqrt{\\varepsilon_{\\mathrm{{H}}}-\\varepsilon_{n{\\bf k}}}\\frac{\\left|\\psi_{n{\\bf k}}({\\bf r})\\right|^{2}}{\\rho({\\bf r})}+\\nu_{\\mathrm{{c}}}^{\\mathrm{PBEsol}}({\\bf r})},}\\end{array}\n$$ \n\nwhere exPBEsol is the PBEsol exchange-energy density per electron, $\\nu_{c}^{\\mathrm{PBEsol}}=\\delta E_{c}^{\\mathrm{PBEsol}}/\\delta\\rho$ is the PBEsol correlation potential, and $K_{\\mathrm{x}}^{\\mathrm{LDA}}$ $=8\\sqrt{2}/\\left(3\\pi^{2}\\right)$ . Since the GLLB-SC potential depends on the orbital energies $\\varepsilon_{\\mathrm{H}}$ is the one at the valence band maximum), a non-zero derivative discontinuity114,115 can be calculated and added to the KS bandgap for comparison with the experimental value.113,116 Similar to TB-mBJ, the GLLB-SC potential is significantly more accurate than traditional GGA functionals, as shown in Refs. 80, 104, 113, and 117. On the other hand, we note that these potentials are not obtained as the functional derivative of an energy functional. \n\nAmong other DFT methods, which have been shown to provide bandgaps more accurately than PBE, are the GGAs EV93PW91,118,119 AK13,120,121 and HLE16,122 as well as the LDAtype functional Sloc.123 As mentioned in Sec. II B 1, the potential of MGGA energy functionals is not implemented in WIEN2k; however, it is still possible to calculate bandgaps non-self-consistently using the total energy (see Ref. 124 for details). Such MGGAs that are particularly interesting for bandgaps are HLE17125 and TASK.126 \n\nFigure 3 shows results for the bandgap of 76 solids, which we considered in our previous works.64,80 Compared to the standard PBE functional, the results are much improved when TB-mBJ, GLLB-SC, or HSE06 is used, since the mean absolute error (MAE) drops from $1.99\\mathrm{eV}$ with PBE to 0.47 eV, $0.64\\:\\mathrm{eV}$ , or $0.82\\mathrm{eV}$ , respectively, for the other methods. Among all methods considered in Refs. 64 and 80, TB-mBJ leads not only to the smallest MAE but also to a slope (b = 0.97) of the linear fit that is closest to 1 (the AK13120 functional also leads to a slope of 0.97). \n\nFinally, we also mention that the Slater127 and Krieger– Li–Iafrate128 potentials have been implemented in the WIEN2k code.129,130 However, these ab initio potentials, which are as expensive as the HF/hybrid methods, are not really intended for bandgap calculations, but may be interesting for more fundamental studies or as a better starting point for approximating the exact KS exchange potential. \n\n# 5. Methods for van der Waals systems \n\nThe semilocal and hybrid functionals are, in general, quite inaccurate for describing weak interactions.131,132 This is mainly due to the London dispersion forces that are not included properly in these approximations. Nevertheless, much better results can be obtained by adding to the semilocal/hybrid functional a correlation term $(E_{\\mathrm{c,disp}})$ accounting for the dispersion forces. There are essentially two types of dispersion corrections. The first one is of the atom-pairwise (at-pw) type, \n\n![](images/d74a5a0277820fb0646bc7580ceb135afca7b1b1c11c243ffb264e2d0e91ddfd.jpg) \nFIG. 3. Bandgaps of 76 solids calculated with the PBE, TB-mBJ, GLLB-SC, and HSE06 methods compared to experiment. The MAE compared to experiment, a linear fit $(y=a+b x.$ , dashed lines) of the data, and the corresponding root mean square deviation (RMSD) are also shown. The calculated results are from Refs. 64 and 80. \n\n$$\nE_{\\mathrm{c,disp}}^{\\mathrm{at\\mathrm{-}p w}}=-\\sum_{A\\rho_{\\mathrm{c}},}\\end{array}\\right.}\\end{array}\n$$ \n\nwhere $A=1{\\mathrm{~bohr}}^{3}$ and $\\rho_{\\mathrm{c}}$ is the density cutoff that determines how smooth the new density $\\rho_{\\mathrm{s}}$ should be. More details can be found in Ref. 139, where it is shown that converged benchmark results can easily be obtained at a relatively modest cost. \n\nIn our previous works,39,140 a plethora of DFT-D3 and NL-vdW functionals were assessed on solids. The test set consists of strongly bound solids and van der Waals solids such as rare gases or layered compounds. The results showed that among the at-pw methods, PBE-D3/D3(BJ)134,141 seems to be a pretty good choice, while among the nonlocal methods, rev-vdW-DF2142 is the most balanced and actually more or less the best among all tested functionals. \n\n# C. SCF convergence, total energies, forces, and structure optimization \n\nThe total energy $E_{\\mathrm{tot}}$ of a periodic solid (with frozen nuclear positions) is given by Eq. (9). The individual terms are of opposite sign and, in an all-electron method, very large. In order to cancel the Coulomb singularity, we follow the algorithm of Weinert et al.,143 where the kinetic and potential-energy terms are combined and a numerically stable method is obtained. \n\nThe force exerted on an atom $t$ residing at position $\\mathbf{R}^{t}$ , defined as \n\n$$\n\\mathbf{F}^{t}=-\\nabla_{\\mathbf{R}^{t}}E_{\\mathrm{tot}},\n$$ \n\nis calculated from the Hellman–Feynman theorem and includes Pulay corrections,144 thereby taking into account that parts of the basis set used in WIEN2k depend upon the position of atoms (see Refs. 17 and 145–147 for the derivation specific to APW-based methods). \n\nWIEN2k exploits the self-consistency of the KS equations, running through a sequence of calculations where the target is a density (and other parameters), which when passed through these SCF calculations yield the same density. This is equivalent to finding the solution to a set of simultaneous equations and is, in the most general case, referred to mathematically as a “fixed-point problem,” although it goes under the different name of “mixing” in the DFT literature. The general method used for just the electron density $\\rho$ and other density-like variables (for instance, the density matrix) is discussed in Ref. 148, while the extension to include atomic positions is described in Ref. 149. At any given iteration $n$ , the relevant variables can be written as a vector $(\\rho_{n},\\nu_{n}^{\\mathrm{orb}})$ , including the density $\\rho$ at the start of an iteration as a function the Cartesian coordinates r and an orbital potential $\\nu^{\\mathrm{orb}}$ (if used as in $\\mathrm{DFT}+U$ or on-site hybrids, see Sec. II B 3), as well as other relevant variables. After running through the SCF sequence, a new density [symbolized by the SCF mapping $\\mathrm{KS}(\\rho_{n},\\nu_{n}^{\\mathrm{orb}})]$ is produced. The fixed-point for just the density is when the two are equal, i.e., for all of the variables, the set of simultaneous equations \n\n$$\n{\\mathrm{KS}}(\\rho_{n},\\nu_{n}^{\\mathrm{orb}})-(\\rho_{n},\\nu_{n}^{\\mathrm{orb}})=D(\\rho_{n},\\nu_{n}^{\\mathrm{orb}})=0,\n$$ \n\nwhere $D(\\rho_{n},\\nu_{n}^{\\mathrm{orb}})$ is the density residual. Since the total energy with respect to he position of the atoms also has to be minimal, when these are allowed to vary, this can be expanded to include the forces $\\mathbf{F}_{n}\\big(\\rho_{n},\\mathbf{R}_{n}^{t},\\nu_{n}^{\\mathrm{orb}}\\big)\\ =\\ -\\nabla_{\\mathbf{R}_{n}^{t}}E\\big(\\rho_{n},\\mathbf{R}_{n}^{t},\\nu_{n}^{\\mathrm{orb}}\\big)$ , i.e., solve the larger problem \n\n$$\n\\begin{array}{r l}&{\\big(D\\big(\\rho_{n},\\nu_{n}^{\\mathrm{orb}}\\big),\\mathbf{F}_{n}\\big(\\rho_{n},\\mathbf{R}_{n}^{t},\\nu_{n}^{\\mathrm{orb}}\\big)\\big)=\\mathbf{G}\\big(\\rho_{n},\\mathbf{R}_{n}^{t},\\nu_{n}^{\\mathrm{orb}}\\big)=0.}\\end{array}\n$$ \n\nThis is equivalent to solving the SCF problem for an extended KS-equation, finding the variational minimum of both the atomic positions and densities. \n\nThe Hellman–Feynman forces due to the input density $\\rho_{n}$ are calculated within lapw0, while the Pulay corrections are calculated in lapw2 using the new density $\\mathrm{KS}(\\rho_{n},\\mathbf{R}_{n}^{t},\\nu_{n}^{\\mathrm{orb}})$ , so the forces above are, in general, not true derivative(s of the )ergy, rather pseudoforces that converge to them as the density converges. The general method is to expand to first order, i.e., write for the next value of the variables, \n\n$$\n\\left(\\rho_{n+1},\\mathbf{R}_{n+1}^{t},\\nu_{n+1}^{\\mathrm{orb}}\\right)=\\left(\\rho_{n},\\mathbf{R}_{n}^{t},\\nu_{n}^{\\mathrm{orb}}\\right)+\\mathbf{H}_{n}\\mathbf{G}\\left(\\rho_{n},\\mathbf{R}_{n}^{t},\\nu_{n}^{\\mathrm{orb}}\\right),\n$$ \n\nwhere $\\mathbf{H}_{n}$ is an approximation to the inverse Jacobian, which is constructed as a Simplex gradient, i.e., a multi-dimensional numerical derivative using some number of the prior steps. The approximate inverse Jacobian has two components: \n\n1. A predicted component where the density, positions, and other variables have changed in a way that maps onto the prior steps in the SCF iterations, so some information is already available. \n2. An unpredicted component where the changes in the variables are new, so no prior information is available. \n\nEquation (25) ignores higher-order terms in the expansion, which can break down far from the fixed point. In addition, because it is generated by a type of numerical differentiation, it can have limited accuracy if the step sizes are inappropriate. In addition, the unpredicted component can lead to instabilities. The approach taken is to control the algorithm greed for the unpredicted step and also use trust regions for both the predicted and unpredicted steps. The general idea of trust regions is that Eq. (25) is only reasonably accurate for changes of the variables, which are smaller than some value, which is called the trust radius, as illustrated in Fig. 4. Starting from some initial defaults, at each iteration, the algorithm will check to see if the step the mixer proposes to use is small enough; if it is too large, then the step is reduced. In the next iteration, if the step used led to an adequate improvement when bounded by the trust radius, then this radius is increased; if the step was not good, then the trust radius is decreased. In addition to changing the trust radii based upon improvement (or not), the most recent algorithm150 also looks at the last step to see how large it should have been for both the predicted and unpredicted parts. This approach is significantly more stable and often leads to much smaller steps than earlier versions of the mixer used. \n\n![](images/df24261b6374ae8c575e32e3ec2b80f952812282a70416302e434c60b93ace91.jpg) \nFIG. 4. Illustration of a trust-region approach. With contours shown dashed, from the initial point, the best route following the gradient of the contours is shown in red. However, only a linear step shown in blue is predicted by the multisecant expansion. The trust region (brown) limits the step along this direction so it makes adequate progress downhill and not too far, which is less efficient and can diverge. \n\nBy design, the algorithm requires minimal user input beyond an estimate for the initial step to take for the unpredicted step; the most recent version of the algorithm150 automatically controls all the internal parameters. No algorithm is perfect, and the convergence of the mixing depends significantly upon the nature of the physical problem being considered. The better the description of the underlying quantum mechanical problem, primarily the XC potential, the more rapidly it will converge. A very badly posed problem, in contrast, may converge only very slowly or not at all. \n\nTwo main algorithms are used within WIEN2k. The first is MSEC3, which is an updated version of a multisecant Broyden method148 with trust region controls. This is a conservative algorithm, which uses the least greedy approach at every iteration. It is recommended for problems that converge badly. The more pushy MSR1149 uses a more aggressive algorithm, which is significantly better for problems with soft modes that may converge only very slowly with MSEC3. \n\nOne unique feature of WIEN2k is that it can simultaneously converge both the density and atomic positions by solving the fixedpoint problem of Eq. (24) using a multisecant approach.149 This is often considerably faster than converging them independently as done in many other DFT codes and different from molecular dynamics approaches such as Car–Parrinello.151 The convergence rate depends upon the number and width of the eigenvalue clusters149 of the combined electron and atomic position Jacobian. This approach does not follow the Born–Oppenheimer surface, which is the energy surface when the density is converged, rather some other surface, which is a balance between having converged densities and pseudo-forces as illustrated in Fig. 5. As such it can be somewhat confusing to the user, particularly as the pseudoforces can vary in a strange fashion. This mode can be used with both the more conservative MSEC3 and the more aggressive MSR1 algorithm. \n\n![](images/9f4bfcf15a9725a5425f663373040c66b5275596a708fcc337f820e382613739.jpg) \nFIG. 5. The combined density and position algorithm does not follow the Born– Oppenheimer surface (indigo) where the density is converged or the surface where the pseudo-forces are zero (orange), instead it finds a fixed point of a combination (green contours) following the red path. \n\nFor the optimization of lattice parameters, WIEN2k offers a couple of workflows and utilities to generate structures with different lattice parameters, running the corresponding SCF calculations and analyzing the results. The optimized lattice parameters, however, are found only from the lowest total energy since there is no stress tensor in WIEN2k yet. This makes the optimization tedious for low symmetry cases and practically impossible for triclinic lattices. \n\n# D. User interface and utilities \n\nWIEN2k consists of a large set of individual programs (mostly written in Fortran 90), which are linked together via tcsh-shell scripts representing a particular workflow. With this modular structure, WIEN2k is, on the one hand, very flexible and one can run a dedicated program for a particular task. On the other hand, there is not just one program and the specific task will be determined by directives in the input file, but a user has to know which program performs this specific task. \n\nWIEN2k can be driven either from the command line or using a web-based graphical user interface (GUI), called $w2w e b$ , which can be accessed by any web browser. Most likely, an experienced user will use the command line and explore all advanced features of WIEN2k, but for the beginner, the web-based GUI provides a very good starting point and it also teaches the user the corresponding command line. \n\n# 1. Structure generation \n\nThe first task of every calculation is to define the structural data. As an example, the StructGen@w2web page is shown in Fig. 6 for the case of TiCoSb. The necessary basic input consists of the following: \n\nthe lattice type (P, B, F, and H for primitive, body centered, face centered, and hexagonal, respectively) or, if already known, one of the 230 space groups; for the Heusler compound TiCoSb, we can select F lattice or space group 216 $\\bar{(F43m)}$ ; \nthe lattice parameters $a,b,$ and $c$ (in bohr or $\\mathring\\mathrm{A}$ ) and the angles $\\alpha,\\beta,$ and $\\gamma$ (in degree); \nthe atoms and their positions; if the space group is given, only one of the equivalent atoms has to be specified. \n\nWhen the new structure is saved, the setrmt utility determines the nearest neighbor distances and automatically sets optimized atomic sphere sizes $R_{\\mathrm{MT}}$ for this structure. The choice of $R_{\\mathrm{MT}}$ has nothing to do with ionic radii but depends on the convergence properties of the atoms as discussed before (see the end of Sec. II A). It is important to note that if one wants to compare total energies for a series of calculations (e.g., for volume optimization), the $R_{\\mathrm{MT}}$ should be kept constant. \n\nAn alternative on the command line is the makestruct utility, which works analogous to StructGen@w2web. More complex structures can be converted from cif or xyz files using the cif2struct or xyz2struct utilities. The generated structures can be conveniently visualized using XCrysDen152 or VESTA.153 \n\nStarting from a basic (simple) structure, WIEN2k has powerful tools to generate supercells and manipulate them. supercell generates quickly $h\\times k\\times l$ supercells (with/without B- or F-centering so that the supercell size can be increased by factors of two) and can add vacuum for surface slab generation. The structeditor, a collection of GNU Octave scripts, is even more powerful, since it can create arbitrary supercells (e.g., ${\\sqrt{3}}\\times{\\sqrt{3}}\\times l)$ , rotate or merge structures, and delete or add atoms. \n\n![](images/fc4ff1246267e909d7bed5ae89d01024283b423c8a8a110429a7577cccef4218.jpg) \nFIG. 6. Screenshot of the StructGen@w2web page of the w2web GUI of WIEN2k for TiCoSb. \n\n# 2. Input generation \n\nAs mentioned above, WIEN2k consists of many individual programs and most of them have their own input file. Although this sounds very tedious at first, there are default inputs for all programs and several tools for changing the most important parameters on the fly. In w2web, the next step would be to check the symmetry of the newly generated structure and generate the input files for the SCF calculation (initialize@w2web). The user can provide a couple of parameters (only needed if one wants to change the defaults, see below) and run the following steps in batch mode or step by step: \n\nnn: Determines the distances between all atoms up to twice the nearest neighbor distance. In addition, it checks for overlapping spheres and will issue an error message if the spheres overlap. It also checks if identical elements have the same environment and eventually regroups them into equivalent sets. sgroup: Checks the structure and determines the spacegroup. It will group the atoms into sets of equivalent ones according to the Wyckoff positions of the corresponding space-group. In addition, it will check and determine the smallest possible (primitive) cell and create the corresponding structure file if necessary. For instance, if one enters the NaCl structure as a primitive cubic structure with four Na and four Cl atoms, it will automatically create a primitive FCC cell with only one Na and Cl atom. \nsymmetry: Finds the symmetry operations of the space group as well as the point group symmetry of each atom and the corresponding LM expansion for the density/potential [Eqs. (1) and (2)]. \nlstart: Solves numerically the radial Dirac equation for free atoms and creates atomic densities. Using the eigenvalues (or the localization within the atomic spheres) of all atomic states, it groups them into core and valence states. It selects automatically LOs for semi-core states and writes the starting energy parameters $E_{\\ell}$ to case.in1 (during the SCF cycle, they are searched and adapted automatically to ensure best possible settings in all cases). kgen: Generates a shifted or non-shifted equidistant $\\mathbf{k}$ -mesh with a user specified density in the irreducible part of the BZ. \ndstart: Superposes the atomic densities and creates the starting density for the SCF cycle. \n\nOn the command line, a corresponding script is called, which optionally allows us to specify various parameters (the most important ones are given below with their default values for reference): \n\nnit_lapw [-b -vxc PBE -ecut -6.0 -rkmax 7.0 -numk 1000] \n\nThe switches are described as follows: - $\\cdot b$ indicates batch mode (instead of step by step), -vxc selects the DFT functional, -ecut gives the core–valence separation energy (in Ry), -rkmax determines the plane wave cut-off parameter $R_{\\mathrm{MT}}^{\\mathrm{min}}K_{\\mathrm{max}}$ , and -numk determines the total number of $\\mathbf{k}$ -points in the full BZ. \n\nThe most critical parameter is $R_{\\mathrm{MT}}^{\\mathrm{min}}K_{\\mathrm{max}}$ , which determines not only the quality but also the required computing time. The type of atom with the smallest $R_{\\mathrm{MT}}$ determines this value because the $R_{\\mathrm{MT}}$ for other atoms are set such that when the smallest atom is converged with the number of PWs, all others are also converged with the number of PWs. If the smallest sphere is a H atom (for instance, in short $_\\mathrm{O-H}$ bonds), $R_{\\mathrm{MT}}^{\\mathrm{min}}K_{\\mathrm{max}}=3$ is sufficient, most $s p/d/f$ -elements converge with $R_{\\mathrm{MT}}^{\\mathrm{min}}K_{\\mathrm{max}}=7/8/9$ . For lower (higher) precision, one can decrease (increase) th=ese values by $10\\%{-}20\\%$ . \n\nOf similar importance is the selection of a $\\mathbf{k}$ -mesh. Generally speaking, small unit cells and metallic character require a large number of k-points (typical starting values for the SCF cycle would be a $10\\times10\\times10\\mathrm{mesh},$ ), while large cells (100 atoms) and insulators can be started with only one $\\mathbf{k}$ -point. In any case, after the first SCF cycle, the k-mesh should be increased and the results (e.g., the forces on the atoms) should be checked. Certain properties (DOS, optics, and NMR) may need an even denser mesh, which in WIEN2k can be easily done and is fairly cheap, since it is only used for the property of interest. \n\n# 3. SCF cycle \n\nThe SCF cycle consists in WIEN2k of a complex workflow using several different programs. The main steps are as follows: \n\nlapw0: Calculates the Coulomb and XC potential from the density. \nlapw1: Calculates the valence and semi-core eigenvalues and eigenvectors at all requested k-points \nlapw2: Calculates the valence electron density \nlcore: Calculates the core eigenvalues and the core density \nmixer: Adds up the core and valence densities and mixes the total density with densities from previous iterations. In addition, it may update the atomic positions according to the calculated forces (see Sec. II C) and also the density matrices or orbital potentials when $\\mathrm{DFT}+U$ or on-site hybrid methods are used. \n\nAdditional programs may be called depending on the requested options to include SO coupling or one of the specialized functionals discussed in Sec. II B (DFT-D3, NL-vdW, $\\mathrm{DFT}+U,$ on-site hybrid/EECE, or hybrid-DFT/HF). \n\nIn $w2w e b$ , the SCF cycle can be started by clicking on $S C F@w{2w e b}$ . In this interface, one can then specify several parameters such as convergence criteria, parallelization, simultaneous optimization of internal atomic positions, or adding SO coupling. \n\nThe most important parameters for the corresponding command line script are as follows: \n\nrun_lapw $\\left[-\\mathrm{ec}0.0001-\\mathrm{cc}0.0001\\right.$ -fc $1.0\\mathrm{-p}\\mathrm{-so-min}]$ \n\nThe SCF cycle will stop when the (optional) convergence criteria -ec (energy in Ry), - $\\cdot c c$ (charge in $\\mathrm{e}^{-}$ ), and $-f c$ (forces in mRy/bohr) are fulfilled three times in a row. SO coupling (only possible after a previous init_so_lapw step) is switched on using -so, -min relaxes the atomic positions simultaneously with the electron density (Sec. II C), and $-\\ensuremath{p}$ switches on parallelization (Sec. II E). \n\nThe basic summary of the SCF cycle is written into the case.scf file and all relevant quantities are labeled :LABEL: and can be searched/monitored using analyse@Utils@w2web or the Linux grep command. If the desired convergence has been reached, it is advisable to save all relevant input/output files using either save@Utils@w2web or the save_lapw utility. One can now either check results using more k-points (kgen@single_prog@Execution@ $w2w e b)$ or modify other inputs (input files@Files@w2web) such as $R_{\\mathrm{MT}}^{\\mathrm{min}}K_{\\mathrm{max}}$ or the XC functional and then continue with the SCF cycle. Later on, it is always possible to come back to a previously saved calculation using restore@Utils@w2web (restore_lapw). \n\n# 4. Tasks \n\nOnce these steps have been finished, one could, for instance, optimize the lattice parameters (optimize@w2web) or perform various other tasks (Tasks@w2web) such as Bandstructure@Tasks@ w2web, DOS@Tasks@w2web, ElectronDensities@Tasks@w2web, XSPEC@Tasks@w2web, TELNES@Tasks@w2web, or $O P T I C@$ Tasks@w2web (see Fig. 6). Each of these tasks consists of a guided workflow and let the user prepare the necessary inputs, executes various small programs, and visualizes the results. \n\n# E. Software requirements and parallelization \n\n# 1. Software \n\nWIEN2k runs on any Linux platform and also on Mac. It is written mainly in Fortran 90 (a few programs are written in C), and the workflows are managed by tcsh scripts. Most of the timecritical parts use libraries such as BLAS and LAPACK, and efficient libraries are therefore mandatory. There is direct installation support for the standard Linux tools GFortran $\\cdot+$ OpenBLAS (at least gcc 6.x) and Intel IFORT $^{\\cdot}+$ MKL. The latter still gives the best performance. w2web is a specialized web server written in perl and listens on a user-defined high port. Its access is, of course, password protected and can be limited to specific IP addresses. \n\nFor the optional installation of the MPI-parallel version (useful only on clusters with InfiniBand network or larger shared memory workstations with at least 16 cores), one needs obviously MPI (e.g., Open MPI or Intel MPI) and also ScaLAPACK (included in the MKL), FFTW,154 and, optional but highly recommended, ELPA.155,156 \n\nThe following Linux tools are necessary (not all of them are always installed by default): tcsh, Perl 5, Ghostscript, gnuplot, GNU Octave, and Python $2.7.\\mathrm{x}\\mathrm{+NumPy}$ . \n\nOptional, but highly recommended, programs for certain tasks include the following: \n\nXCrysDen152 and VESTA153 for structure and electron density visualization but also generation of band structure kmeshes or plotting Fermi-surfaces. \nLibxc33,34 for XC functionals not directly implemented in WIEN2k. \nDFT- ${\\bf\\cdot D3}^{135}$ for $\\mathrm{DFT}+\\mathrm{D}3$ calculations of van der Waals systems. \nWannier90157,158 for constructing Wannier functions using the wien2wannier utility. \nphonopy,159,160 Phonon,161,162 or PHON163,164 for phonon calculations. \nBoltzTraP2165 for transport calculations (see Sec. III I 1). \n● fold2bloch166 to fold supercell band structures back to the primitive BZ. $\\mathrm{\\dot{S}K E A F^{167}}$ to extract de Haas-van Alphen frequencies from WIEN2k. \nCritic2168,169 is an alternative program to the WIEN2k program aim to analyze 3D scalar fields such as the electron density by using the “atoms in molecules” (AIM) theory of Bader.170,171 \n\n# 2. Parallelization \n\nWIEN2k is a highly accurate all-electron code based on the APW method and thus certainly not as fast as some other (pseudopotential or minimal basis set) codes. However, it takes advantage of inversion symmetry and when present it will automatically use the “real” instead of the “complex” version of the code, thus saving half of the memory and running almost four times as fast. In addition, it is highly optimized and efficiently parallelized at three different levels, which can be optimally chosen depending on the size of the problem and the available hardware. \n\nExcept for OpenMP parallelization (see below), parallelization is activated by a $-\\boldsymbol{p}$ switch in our scripts and needs a .machines file as listed and described below: \n\n# .machines file for parallelization \n# OpenMP parallelization: \nomp_global:4 \nomp_lapw0:16 \n# k-point parallelization (speed:hostname): \n1:host1 \n1:host2 \n# MPI parallelization: \n1:host1:16 host2:16 . \nlapw0:host1:16 host2:16 . OpenMP parallelization: The main (time consuming) programs are all parallelized using OpenMP and can use the corresponding threaded BLAS, LAPACK, and FFTW libraries. It is activated by either setting the OMP_NUM_THREADS variable globally or using omp_prog:N directives in .machines. While many parts of the code scale very well with the number of parallel threads on a multi-core shared memory machine, unfortunately, the scaling of the matrix diagonalization is, at present, limited to 2–4 cores due to performance bottlenecks in the corresponding OpenBLAS or MKL libraries. k-point parallelization: This together with OpenMP is a very simple and highly efficient parallelization, which works even on a loosely coupled cluster of simple PCs with a slow network for small to medium sized cases (up to 100 atoms/cell) where the eigenvalue problem needs to be solved for several $\\mathbf{k}$ -points. It requires a common (NFS) filesystem on all machines and password-less ssh (private/public keys). $N$ lines speed:hostname in .machines will split the list of kpoints into $N$ junks, and $N$ jobs will be started in parallel on the corresponding hosts, followed by a summation step of the partial densities. Since WIEN2k can use temporary (local) storage for the eigenvectors, we are not limited in the number of $\\mathbf{k}$ -points and our personal record is a NMR chemical shift calculation for fcc Al with $10^{6}\\mathbf{k}$ -points. \n\nMPI-parallelization: \n\nWith a sufficiently powerful hardware (at least 16 cores or a cluster with InfiniBand network) and for medium to large sized problems (more than 50 atoms/cell), it is possible, and actually necessary, to parallelize further using MPI. Besides a tremendous speedup that can be achieved by parallelization over atoms and, in particular, over basis functions, this version will distribute the necessary memory on all requested computers, thus allowing calculations for unit cells with more than 1000 atoms.172–174 Such cells require basis sets of about ${10}^{5}$ APWs, and the resulting Hamiltonian, overlap, and eigenvector matrices may need about $500~\\mathrm{GB}$ of memory, which are distributed over the nodes in the standard ScaLAPACK block-cyclic distribution. For such large systems, the solution of the general eigenvalue problem can become the time-limiting $(\\breve{N}^{3})$ step (depending on the number, type, and $R_{\\mathrm{MT}}$ of the atoms, the setup of the complicated matrix elements can take a comparable fraction of the total time), but the ELPA library provides a highly efficient and scalable (1000 cores) diagonalization. In cases with fewer atoms in large cells (isolated molecules in a large box or surface slabs with sufficient vacuum), we can use an iterative diagonalization175 using the previous eigenvectors as start. Depending on the requested number of eigenvalues, this method may be up to 100 times faster than full diagonalization and still scales very well with the number of cores. The MPI version of the code is used when lines with speed:hostname:N (or lines with more than one hostname) in .machines are specified. Of course, coupling of $\\mathbf{k}-$ and MPI-parallelization (and/or OpenMP) is possible. \n\n# III. PROPERTIES AND FEATURES \n\n# A. Energy bands, density of states, electron densities \n\nOnce a self-consistent solution for a chosen atomic structure is done, one can focus on the electronic structure. The energy eigenvalues as a function of the k-vector obtained at the end of the KS calculation define the band structure. The $\\mathbf{k}$ -path along high symmetry lines in the irreducible BZ (see the Bilbao Crystallographic Server176) can be either obtained from WIEN2k default templates or generated graphically using XCrysDen.152 In WIEN2k, one can plot the energy bands by using the program spaghetti, indicating that its interpretation is difficult. However, there are some tools to help. A first tool is a symmetry analysis, which determines the irreducible representation (of the corresponding point group) for each KS eigenvalue. With this knowledge, one can connect the KS eigenstates to bands by using compatibility relations and satisfying the non-crossing rule. The chemical bonding information of state nk is contained in the corresponding wave function $\\psi_{n\\mathbf{k}}$ , which is complex and three dimensional. However, when computing the square of its modulus, one obtains an electron density, which is a real function and easy to visualize. Integrating this (normalized) electron density, one obtains a charge $q$ , which can be decomposed into contributions from the interstitial region $I$ and the atomic spheres $S_{t}$ (labeled by the atom number $t$ and the quantum number $\\ell$ according to the atomic-like basis set), \n\n$$\n1=\\sum_{t,\\ell}q_{t\\ell}+q_{I}.\n$$ \n\nThis allows us to compress the detailed information contained in the wave function of a single eigenstate state $\\psi_{n\\mathbf{k}}$ to a few numbers that can be stored and analyzed. In addition, WIEN2k decomposes the $q_{t\\ell}$ according to the symmetry of the corresponding point group. For example, the five $d$ -orbitals of a TM atom surrounded by ligands in octahedral symmetry are split into the $t_{2g}$ and $e_{g}$ manifold (crystal field splitting), while for lower symmetry, a splitting into five different $d$ -orbitals is obtained. A review paper8 (Sec. 6.2) illustrates these tools for TiC, a refractory metal (crystallizing in the sodium chloride structure) that is almost as hard as diamond but has metallic, covalent, and ionic bonding contributions. These data are very useful to analyze the electronic structure, and we illustrate this for the band structure of the Heusler compound TiCoSb (see Ref. 177). If one wants to know which atomic states (e.g., Co- $d$ , Ti- $d,$ , or $S{\\mathsf{b}}{-}P$ states) contribute most to a certain band, one can show the character of the bands, sometimes called “fat bands.” For each eigenvalue $\\varepsilon_{n\\mathbf{k}}$ , the size of the circle represents the weight of the chosen character (e.g., a particular $q_{t\\ell m}\\rangle$ . Figure 7 shows which band states originate mainly from Co- $d_{\\mathrm{{i}}}$ , Ti- $d$ , or $S{\\mathsf{b}}{-}P$ states, giving the band structure a chemical interpretation. \n\nFrom the KS eigenvalues calculated on a sufficiently fine k-grid in the irreducible BZ, one can obtain the density of states (DOS), usually by means of the (modified) tetrahedron method.178 By using the partial charges [Eq. (26)], one can decompose the total DOS into partial DOS (PDOS), which are useful for understanding chemical bonding and interpreting various spectroscopic data. Figure 8(a) shows how much each region (atomic spheres of Co, Ti, Sb, and the interstitial) contributes to the total DOS. We show the dominating valence contributions from the $C o{-}3d$ and Ti- $\\cdot3d$ electrons in Fig. 8(b) and those from $S\\mathrm{b}{-}5s/5p$ in Fig. 8(c). Unfortunately, the interstitial PDOS cannot be decomposed into atomic and $\\ell$ -like contributions uniquely. However, by analyzing the atomic orbitals in the free atom, we see (Table I) that only a fraction of the related electron density resides inside the corresponding atomic sphere, e.g., $81\\%$ for the $C o{-}3d$ but only $15\\%$ for the Co-4s orbital. Therefore, a significant part of the density lies outside the atomic sphere, leading to a non-negligible PDOS from the interstitial region [Fig. 8(a)]. A simple scheme to eliminate this interstitial part is to renormalize the partial DOS with a factor $q_{t\\ell}^{\\mathrm{ren}}$ (determined by a least squares fit) such that the sum of the renormalized PDOS contributions yields the total DOS, \n\n![](images/228fe188be47facfb81fa847594d3921f6ef8264f033452fcdfab4b6d2e7f0b5.jpg) \nFIG. 7. Band structure of TiCoSb with emphasis on Ti-d (blue), Co-d (red), and $S_{b-p}$ (black). The size of the circles in this fat band plot is proportional to the corresponding partial charge. \n\n![](images/871561c65e8cd16f5b6b4ab11b8ffe94653d62bf8243a1dbf71a7ecfcd2dfbb4.jpg) \nFIG. 8. Total, partial, and renormalized partial DOS of TiCoSb. (a) Total DOS decomposed into atoms and interstitial. (b) Ti- $\\cdot d$ and Co-d (renormalized) PDOS. (c) Sb-s, $p$ (renormalized) PDOS. (d) Ti-s, $p$ (renormalized) PDOS. (e) Co-s, $p$ (renormalized) PDOS. \n\nTABLE I. Fraction $q_{t\\ell}^{\\mathsf{f r e e}}$ of the charge density of atomic orbitals (atom t and momentum $\\ell)$ that resides inside the corresponding atomic sphere of the free atom and the renormalized charge $q_{t\\ell}^{\\mathsf{r e n}}$ in the solid. \n\n\n
qfreqre
Co-4s0.340.48
Co-4p0.45
Co-3d0.950.90
Ti-4s0.150.30
Ti-4p0.43
Ti-3d0.810.86
Sb-5s0.600.61
Sb-5p0.350.40
\n\n$$\n\\mathrm{DOS}=\\sum_{t,\\ell}\\mathrm{PDOS}_{t\\ell}+\\mathrm{PDOS}_{I}=\\sum_{t,\\ell}\\mathrm{PDOS}_{t\\ell}/q_{t\\ell}^{\\mathrm{ren}}.\n$$ \n\nThis sum runs only over the “chemical” $\\ell$ , which are the main contributions. In Table I, we see that the $q_{t\\ell}^{\\mathrm{ren}}$ are close to the free atom situation for more localized orbitals but differs significantly, for example, for Co-4s, which is more localized in the solid than in the free atom. For the importance of this effect, see Sec. III B. \n\nThe fundamental variable in DFT is the electron density $\\rho$ , which can be compared to experimental data. The total $\\rho$ , which is obtained by summing over all occupied states, can be decomposed into its contributions coming from the core, semi-core, and valence states. A variety of tools (such as XCrysDen152 or VESTA153) allows one to visualize the density $\\rho$ along a line, in a plane (2D), or in the unit cell (3D). One can easily compute the density corresponding to a selected energy window of electronic states in order to visualize their bonding character. By taking the difference between the crystalline density and a superposition of atomic densities (placed at the atomic position of the crystal), one obtains a difference density $\\Delta\\rho=\\rho_{\\mathrm{crystal}}-\\rho_{\\mathrm{atoms}}$ , which shows chemical bonding effects much more clearly than the total or valence density. Figure 9 provides an illustration of $\\Delta\\rho$ for TiCoSb within the (110) plane, where we can observe the strong asphericities in the electron density around the Ti and $\\scriptstyle\\mathrm{Co}$ atoms originating from different occupations of the five 3d orbitals, as well as the charge transfer (discussed below using Bader charges). \n\nWhen we want to compare the computed electron densities or the related $\\mathrm{\\DeltaX}$ -ray structure factors (computed using the lapw3 module) with experimental data, we must take into account the motion of the nuclei. In DFT calculations, we assume that the nuclei are at rest, whereas in an experiment, this motion must be considered, for example, by means of the Debye–Waller factors, which can also be calculated by phonon calculations. \n\n![](images/1123365d7e55a68629218a99bac59e5b0bb927bf956c69b3134f02a8ceca48e8.jpg) \nFIG. 9. Difference density $\\Delta\\rho=\\rho_{\\sf c r y s t a l}-\\rho_{\\sf a t o m s}$ $(e^{-}/\\mathsf{b o h r}^{3})$ ) of TiCoSb in the (110) plane. \n\nIt is a strength of theory to allow various decompositions (of the DOS or electron density, for instance), which are often useful for interpreting properties, but these may depend on the basis set used in a calculation, for example, when deriving atomic charges. In a LCAO scheme, one takes the weights of all atomic orbitals centered at a given atom to determine how much charge corresponds to that atom (Mulliken’s population analysis). In an APW scheme, the charge inside the related atomic sphere would give an atomic charge, but this value clearly depends on the chosen atomic radius and lacks the interstitial contribution. However, the renormalized partial charges ${Q}_{t}^{\\mathrm{ren}}$ obtained from an integral over the renormalized PDOS gives a meaningful measure of charge transfer, as shown in Table II. \n\nA basis-set independent alternative is the AIM procedure proposed by Bader,170,171 which is based on a topological analysis of the density. It uniquely defines volumes (called “atomic basins”) that contain exactly one nucleus by enforcing a zero-flux boundary: $\\nabla\\rho\\cdot{\\hat{n}}=0$ . Inside such an atomic basin, this scheme uniquely defines t∇he Ba=der charge for a given density independently of the basisset method that was used to calculate the electron density.170,171 An example of the application of the AIM method is given in Table II, which shows the charge inside the atomic basins of TiCoSb determined with the aim module of WIEN2k. $Q_{t,\\mathrm{crystal}}^{\\mathrm{Bader}}$ is the nuclear charge $Z_{t}$ minus the number of electrons (a positive value indicates a depletion of electrons) using the SCF density, and $Q_{t,\\mathrm{super}}^{\\mathrm{Bader}}$ is the same quantity but using a density from a superposition of the free neutral atoms. In this crystal structure, according to a Bader analysis, even the superposition of neutral densities leads to a significant charge transfer from Ti to $\\scriptstyle\\mathrm{Co}$ and Sb, which is enhanced for $\\scriptstyle\\mathrm{Co}$ and Ti but reduced for Sb during the SCF cycle. These Bader charges can be compared to the $\\boldsymbol{Q}_{t}^{\\mathrm{ren}}$ . As we can see, in both methods, there is a transfer of electrons from the Ti to the Co atom, but the specific amount and, in particular, the charge state of Sb differs significantly depending on the way it is calculated. An inspection of the difference density (Fig. 9) shows a negative $\\Delta\\rho$ around Sb and thus indicates a positive charge of the Sb atom in contrast to the Bader charges, which seems to pick up a lot of charges in the interstitial region leading to a negative Sb charge. In essence, one should be careful with quantitative charge state assignments. \n\nAn alternative to aim is the Critic2 package,168,169 which determines Bader charges using a pre-calculated 3D mesh of densities. It is very fast; however, the integration of total charges on such a crude mesh is inaccurate and one should restrict its usage for magnetic moments (integrating the spin densities) or valence charges densities (be careful with the 3D mesh). \n\nTABLE II. Bader charges $Q_{t,\\mathrm{crystal}}^{\\mathsf{B a d e r}}$ and $Q_{t,\\mathtt{s u p e r}}^{\\mathtt{B a d e r}}$ using the SCF and the free-atom superposed density, respectively, and renormalized atomic charges $Q_{t}^{\\mathsf{r e n}}$ of TiCoSb. \n\n\n
AtomQeadperQren
Co-0.89-0.18-1.25
Ti+1.28+0.82+0.85
Sb-0.39-0.64+0.40
\n\n# B. Photoelectron spectroscopy \n\n# 1. Valence-band photoelectron spectroscopy \n\nExperimental valence band photoelectron spectra (PES) are often just compared to the total DOS. Such a comparison, however, can at best reproduce certain peak positions, but usually not the experimental intensities. This is even more true with modern synchrotron-based hard X-ray PES (HAXPES), where the spectra differ considerably depending on the excitation energy. This is because the cross sections of different atomic orbitals change dramatically as a function of excitation energy and this effect should be taken into account. The pes module179 of WIEN2k uses the partial DOS $\\mathrm{(PDOS}_{t\\ell.}$ ) and multiplies it with the corresponding energydependent atomic orbital cross sections $\\sigma_{t\\ell}$ , taken from various tables,180,181 \n\n$$\nI=\\sum_{t,\\ell}{\\mathrm{PDOS}_{t\\ell}\\sigma_{t\\ell}}.\n$$ \n\nIn addition, pes can use the renormalized PDOS (see Sec. III A), so that the contributions from the less localized orbitals (whose wave functions are mainly in the interstitial region) are also properly taken into account. This module allows us to specify the X-ray energy and can handle unpolarized and linearly polarized light as well as linear dichroism in angular distribution (LDAD). It was successfully applied for various examples179 $\\mathrm{SiO}_{2}$ , $\\mathrm{Pb}{\\mathrm{O}}_{2}$ , $\\mathrm{CeVO_{4}}$ , $\\mathrm{In}_{2}\\mathrm{O}_{3}$ , and $\\mathrm{ZnO}_{\\cdot}^{\\cdot}$ ). \n\nHere, we compare in Fig. 10 the experimental HAXPES spec$\\mathrm{{trum}^{177}}$ of TiCoSb at $6\\ensuremath{\\mathrm{\\keV}}$ with the theoretical calculation. The theoretical spectrum reproduces the experimental intensities very well, but the bandwidth is too small so that the Sb-s peak has about $1~\\mathrm{eV}$ less binding energy. This is a well-known DFT problem and concerns all states at lower energy. The decomposition of the total spectrum allows us to analyze the contributions to the different peaks in the spectrum. The low energy feature is almost exclusively from Sb-s states, the double peak at $-5\\mathrm{\\eV}$ is from $S{\\mathsf{b}}{-}P$ states, and the double peak at $-2~\\mathrm{eV}$ is from Co- $\\cdot d$ states. However, Co-s also contributes significantly to the feature at $-6~\\mathrm{eV}$ , and $S{\\mathsf{b}}{-}P$ contributions are even larger than $C o{-}3d$ for the lowest binding energy peak at $-1.5\\mathrm{eV}$ . All Ti contributions are very small and thus not shown in Fig. 10. \n\n![](images/5998269f6b029754011da32e12e314ccad3f23d5912bd79453db34bd4d212a27.jpg) \nFIG. 10. Experimental177 and theoretical PES of TiCoSb at $6~\\mathsf{k e V}.$ . The theoretical spectrum is further decomposed into its main contributions Sb-s, $p$ and Co-s, p, d. \n\n# 2. Core-level photoelectron spectroscopy \n\nX-ray photoelectron spectroscopy (XPS) determines the binding energy (BE) of core states. These BEs are specific to certain atoms, but the possible small changes of BEs (core level shifts) provide important additional information about the chemical environment and, in particular, the oxidation state of that element. Since WIEN2k is an all-electron method, it has the self-consistent core eigenvalues available and one could calculate their BE as energy difference with respect to the Fermi level. However, according to Janak’s theorem,182 DFT eigenvalues represent the partial derivative of the total energy with respect to the orbital occupancy and are therefore not necessarily good approximations of experimental excitation energies. Such BEs are typically $10\\%{-}20\\%$ too small. In fact, even BE differences (core level shifts) from ground-state calculations might not be reliable because screening effects of the final state are not included. Much better approximations to experimental BEs can be obtained according to Slater’s transition state theory,183 where half of a core electron is removed.173,184,185 The corresponding SCF eigenvalue, which represents the slope of the total energy vs occupation at half occupation, is a much better approximation to the actual energy difference for $n$ and $n\\mathrm{~-~}1$ occupation, and typical BE errors are reduced to a few percent. For solids, such calculations should employ large supercells where only one of the atoms gets excited. This method also allows for some possible screening due to the valence electrons but suffers from the fact that, in solids, a neutral unit cell is required. The missing half electron can be compensated by adding a negative background charge, by increasing the number of valence electrons by one half, or by playing slightly with the nuclear charge186 according to a virtual crystal approximation. However, it is not always clear which of these methods should be preferred. Successful applications include, for instance, the N-1s shifts of h-BN covered Pt, Rh, and $\\mathrm{Ru}(111)$ surfaces (with a unit cell of the “nanomesh” containing more than 1000 atoms)173 or to ${\\mathrm{Pb}}{-}5d$ and Ta- $4f$ shifts in the misfit layer compound $(\\mathrm{Pb}\\mathsf{S})_{1.14}\\mathrm{TaS}_{2}$ .185 \n\nThe work function can also be obtained from surface slab calculations as the difference of the Fermi level and the Coulomb potential in the middle of the vacuum region. An example can be found for free and h-BN covered $\\mathrm{\\DeltaNi}$ and Rh(111) surfaces in Refs. 187 and 188. One has to carefully check the convergence of the work function with respect to the size of the vacuum region. \n\n# C. X-ray absorption/emission spectroscopy and electron energy loss spectroscopy \n\nExperimental techniques such as $\\mathrm{\\DeltaX}$ -ray emission (XES), nearedge X-ray absorption (XAS, NEXAFS, and XANES), and electron energy loss spectroscopy (EELS) represent an electronic transition between a core state and a corresponding valence/conduction band state, which leads to the measurement of emitted/absorbed X-rays or the energy loss of transmitted electrons. The intensity of such a spectrum is given by Fermi’s golden rule according to dipole transitions between an initial $(\\Psi_{I})$ and a final $(\\Psi_{F})$ state, \n\n$$\nI(E)\\propto\\langle\\Psi_{I}|\\varepsilon{\\bf r}|\\Psi_{F}\\rangle^{2}\\delta(\\varepsilon_{F}-\\varepsilon_{I}-E).\n$$ \n\nThe dipole selection rule is valid when the $\\mathrm{\\DeltaX}$ -ray energy is not too large and limits transitions between a core state on atom $X$ and angular momentum $\\ell$ into/from a conduction/valence band state with $\\Delta\\ell\\pm1$ on the same atom. In essence, the spectrum is calculated from± the corresponding partial DOS times the squared radial matrix element. In the case of polarized light and oriented samples, the orientation-dependent spectra can be obtained by substituting the $\\ell$ -like partial DOS by an appropriate $\\ell m$ -like DOS, e.g., for a K-spectrum of a tetragonal/hexagonal system by replacing the total $\\boldsymbol{p}$ -DOS by $p_{z}$ and $\\b{p_{x}}+\\b{p_{y}}$ -DOS.189 \n\nSuch a scheme leads to very good results for XES spectra, where the final state has a filled core-hole and the valence-hole is usually well screened. For XANES and EELS spectra, however, the final state190 determines the spectrum. The final state has a core hole and an excited electron in the conduction band, and they will interact with each other leading to strong excitonic effects. In order to describe this effect in a DFT-based band-structure code, one has to create a supercell (as large as possible, but depending on the specific system and the hardware resources) of about 32–256 atoms and remove a core electron from one of the atoms. This electron should be added either to the valence electrons (if there are proper states in the conduction band, e.g., in B–K edges of BN) or to the constant background charge (if the lowest conduction band states are of completely wrong character, e.g., for the $_{\\mathrm{O-K}}$ edge of a TM-oxide) to keep the system neutral. In the following SCF cycle, the valence states on the atom with the core hole will get a lower energy and localize, but the surrounding electrons are allowed to partially contribute to the screening. \n\nAs an example, the ${\\mathrm{Cs}}{\\mathrm{-}}{\\mathrm{L}}_{3}$ spectrum of $\\mathrm{CsK}_{2}\\mathrm{Sb}$ is shown in Fig. 11(a) and compared with state-of-the-art calculations191 using the Bethe–Salpeter equation (BSE) (for further details on BSE, see Sec. III I 3). Obviously, the spectrum calculated with the ground state electronic structure is very different from core hole supercell or BSE calculations, where the spectral weight is redistributed into the first (excitonic) peak. In particular, the $\\cos-5d$ states come down in energy and partially screen the core hole [Fig. 11(b)]. \n\n![](images/216f2fcf5cb603d409f8dc49d8ddcd659f88ce3f4afb11b40939c5684365ccca.jpg) \nFIG. 11. (a) $C s\\mathrm{-}L_{3}$ spectrum of $\\mathsf{C s K}_{2}\\mathsf{S b}$ calculated using the ground state or a core hole in 32 or 128 atom supercells. These calculations are compared with the BSE results from Ref. 191, which are aligned at the first main peak as it is not possible to calculate such spectra on an absolute energy scale. The spectra are broadened with a Gaussian of $0.5\\mathsf{e V}$ and a Lorentzian of $0.2\\mathsf{e V}.$ (b) Partial Cs-d DOS for a Cs atom with and without core hole. \n\nThe Cs-6s contributions (not shown) are 1–2 orders of magnitude smaller because both their dipole matrix elements and the 6s-PDOS are smaller than the corresponding $\\cos-5d$ quantities. On the other hand, the BSE and core hole supercell calculations agree quite well. Note that the BSE data have a larger broadening. In this example, the size of the supercell is easy to converge, but it should be noted that for details of the spectrum, a rather good $\\mathbf{k}$ -mesh $8\\times8\\times8$ for the 128 atom supercell) is necessary. \n\nWhile the core hole approach works generally quite well, it also has clear limitations or needs extensions: \n\n(i) For metals or small bandgap semiconductors, a full core hole is sometimes too much because the static screening in the supercell might not be enough. Better results can be obtained using a “partial” hole, 93 although adjusting the size of the hole until the resulting spectra match the experiment is not fully ab initio anymore. \n(ii) The used DFT approximation may not be accurate. This can concern the ground state, for instance, the $_{\\mathrm{O-K}}$ edge of NiO could be greatly improved using the TB-mBJ approxima$\\mathbf{tion}^{194}$ instead of PBE or $\\mathrm{PBE}+U.$ . Even more problematic are excited-state effects due to the additional $d$ electron in strongly correlated materials (for instance, $3d$ in TM oxides), where very poor $\\mathbf{L}_{2,3}$ edges are obtained in single particle approaches and sophisticated methods such as dynamical mean field theory (DMFT, see Sec. III I 5) or configuration interactions195 are needed. \n(iii) For early $(^{\\alpha}d^{0}\")$ TM compounds, the L2,3 edges are influenced strongly by interactions and interference effects between the $2p_{1/2}$ and $2p_{3/2}$ states, which are split only by a few eV. This can be accounted for using fully relativistic BSE calculations (see Sec. III I 3), where both the $2p_{1/2}$ and $2p_{3/2}$ states are taken into account simultaneously.196 \n(iv) The B-K edge of hexagonal BN has been investigated many times in the literature .189,197 While the first strong excitonic peak originating from antibonding $\\mathbf{B}{-}p_{z}$ $(\\pi^{*})$ states is well described by supercell calculations and in full agreement with BSE calculations,197 the experimental double peak at around $7\\mathrm{eV}$ above the $\\pi^{*}$ peak originating from $\\sigma^{*}$ $(\\mathrm{B}{-}p_{x,y})$ states shows up in the calculations only as a single peak. This can only be fixed by taking electron–phonon interactions into account. The approach is based on statistical averages over all vibrational eigenmodes of the system.197 Thus, one calculates first the vibrational modes of h-BN and then, using a supercell of e.g., 128 atoms, all atoms are displaced according to the vibrational eigenmodes with amplitudes determined by the Bose–Einstein occupations. Even at $T=0\\mathrm{K},$ the zero-point motion is enough to split the degenerate $p_{x}$ and $\\b{p_{y}}$ states, since, on average, each B will have one $N$ neighbor at a smaller (larger) distance than the two others. This leads to the desired splitting of the single $\\sigma^{*}$ peak into a double peak.19 \n\nEELS has fairly similar basic principles as XAS but differs slightly because of the finite momentum of the electrons.198 The telnes3 module of WIEN2k calculates the double differential scattering cross section on a grid of energy loss values and impulse transfer vectors. This double differential cross section is integrated over a certain momentum transfer $q$ to yield a differential cross section, which can be compared to the experiment. This formalism allows the calculation of relativistic EELS including transitions of arbitrary order (i.e., non-dipole transitions), and it can take into account the relative orientation between the sample and beam.199 Practical aspects on how to perform EELS calculations have been given by Hébert,200 and some examples can be found in Refs. 201–204. \n\n# D. Optics \n\nThe optics module of WIEN2k uses the independent-particle approximation (IPA) and calculates the direct transitions (conserving k) between occupied nk and unoccupied $n^{\\prime}\\mathbf{k}$ states, where for both states, KS eigenvalues are used.205 The joint density of states is modified by transition probabilities given by the square of the momentum matrix elements $M=\\langle n^{\\prime}\\mathbf{k}|A{\\cdot}p|n\\mathbf{k}\\rangle$ between these states, which determine the intensity of o⟨ptical spect⟩ra using dipole selection rules and clearly distinguish between optically allowed and forbidden transitions. From the resulting imaginary part $\\varepsilon_{2}$ of the dielectric function, its real part $\\varepsilon_{1}$ can be obtained by the Kramers– Kronig transformation and then additional optical functions such as conductivity, reflectivity, absorption, or the loss function can also be calculated. In a metallic solid, an additional Drude term accounts for the free-electron intraband contribution. For insulators and semiconductors, where the DFT gap is often too small when compared to the experiment, one can use a “scissor operator.” This sounds complicated but is nothing else than a rigid shift of the unoccupied DFT bands to adjust the (too small) DFT bandgap, either using the experimental gap or, more ab initio, using the gap calculated with TB-mBJ. Note that TB-mBJ usually gives very good bandgaps, but the bandwidth of both the valence and conduction bands are too small, and thus, the optical properties with TB-mBJ might not be very accurate, but still more accurate than standard GGA (see Sec. III B 2 in Ref. 104 for a brief summary of literature results with TB-mBJ). Alternatively, hybrid-DFT functionals66 can be used, which give quite good bandgaps for semiconductors, but one should be aware that the optical properties usually require a quite dense k-mesh, which makes hybrid calculations fairly expensive. \n\nAs an example we present in Fig. 12 the imaginary part of the dielectric function $\\varepsilon_{2}$ for $\\mathrm{CsK}_{2}\\mathrm{Sb}$ using various approximations. First, we note that very dense $\\mathbf{k}$ -meshes are necessary for converged results, which makes the application of more expensive many-body perturbation methods such as $G W$ even more difficult. As expected, PBE calculations yield the smallest bandgap of $1.06\\mathrm{eV}$ , while hybrid YS-PBE0 gives $1.68\\mathrm{~eV}$ and TB-mBJ $2.08\\mathrm{eV}$ . This can be compared to $G_{0}W_{0}$ results191 of $1.62\\ \\mathrm{eV}$ or early experimental estimates of $1.0\\mathrm{-}1.2\\mathrm{eV}$ , which, however, have been criticized. It should be noted that the GW result191 for $\\varepsilon_{2}$ probably suffers from an under converged k-mesh and even with their large smearing (note the large tail below $1.62\\ \\mathrm{eV}$ in the $G W$ results shown in Fig. 12), a distinct peak structure emerges, which is not present in the $\\mathbf{k}$ -converged results. \n\nExperimental results for optical conductivity, reflectivity, or absorption as well as the low energy valence electron energy loss spectrum (VEELS) can often be successfully interpreted in the IPA.203,204 However, sometimes (in particular, for wide gap insulators) the frequency-dependent dielectric function ε in the IPA may have little in common with the experimental situation. This is because excitations are two-particle processes and the missing electron–hole interaction (i.e., the excitonic effect already mentioned in Sec. III C) can significantly affect the calculated optical response of a material when they are strong. In order to overcome this problem, one needs to include the electron–hole correlation explicitly by solving the BSE (see Sec. III I 3). \n\n![](images/c565bc2299b7c2373ff81646b962c7e91410e8c6a387bbf66348bb545725d5be.jpg) \nFIG. 12. Imaginary part of the dielectric function $\\varepsilon_{2}$ for $\\mathsf{C s K}_{2}\\mathsf{S b}$ with various functionals. The PBE calculations are presented with a $6\\times6\\times6$ and $20\\times20\\times20$ k-mesh, and all other calculations have used the larger×mes×h. The GW r×esul s×are from Ref. 191. \n\n# E. Magnetism \n\nWhen magnetism occurs in a solid, it may come from localized electrons (e.g., from $f$ electrons of rare-earth atoms) or itinerant (delocalized) electrons (e.g., in Fe, Co, or Ni). In any case, magnetism comes mainly from exchange splitting causing a partial occupation of states, which differ between the spin-up $(N_{\\uparrow})$ and spin-down $(N_{\\downarrow})$ electrons. The corresponding magnetic moment $M$ is defined as the difference between these occupation numbers $(M=N_{\\uparrow}\\ -\\ N_{\\downarrow})$ . For such cases, one must perform spin-polarized calculations $(r u n s p\\textunderscore l a p w)$ and needs the spin density in addition to the total electron density. The default is collinear magnetic order as found in ferromagnets, for example, in Fe, Co, Ni, or antiferromagnets, for example, in Cr. In addition to collinear magnets mentioned here, one can also handle non-collinear magnetism (for example, systems with canted magnetic moments or spin spirals), as described in Sec. III I 2. \n\nFor spin-polarized calculations of a specific complex antiferromagnetic structure, in most cases, it is essential to specify proper (antiferromagnetic) atomic spin-moments as an input for the SCF cycle and the WIEN2k tool instgen allows us to set this easily. If one is interested in the orientation of the magnetic moments with respect to the crystal structure (easy or hard axis) or the magneto-crystalline anisotropy,206 the SO interaction must be included. For heavy elements or when orbital moments become important, one needs this full relativistic treatment by including the SO interaction. \n\nNowadays, one can study complicated systems, for example, ${\\tt B a F e}_{2}{\\tt O}_{5}$ , an oxygen-deficient perovskite-like structure, which shows a Verwey transition. At low temperature, this system has a charge-ordered state (with $\\mathrm{Fe}^{2+}$ and $\\mathrm{Fe}^{3+}$ at different Fe-sites), but above the Verwey transition temperature (at about $309\\mathrm{K}$ ), a valence mixed state with the formal oxidation state $\\mathrm{Fe}^{2.5+}$ appears. DFT calculations made it possible to interpret this complicated situation (for details see Ref. 207 and Sec. 7.4.1 of Ref. 208). Another complex system is $\\mathrm{Pr}\\mathrm{O}_{2}$ , which has a Jahn–Teller-distorted $\\mathrm{CaF}_{2}$ structure.209 It contains $\\operatorname{Pr}\\sp{-4f}$ electrons, which form a localized band (lower Hubbard band) for one $4f$ electron, but the others hybridize with the valence electrons forming a situation between $\\mathrm{Pr}^{\\dot{3}+}$ and $\\mathrm{Pr}^{4+}$ . This compound is an antiferromagnetic insulator that requires a relativistic treatment. $\\mathrm{PBE}+U$ calculations93 provide results that are consistent with all experimental data for the bandgap, magnetic moment, and structural distortion. \n\nIn the 1980s, a numerical problem occurred in connection with several studies of the $\\mathrm{Fe}_{65}\\mathrm{Ni}_{35}$ INVAR alloy, which has a vanishing thermal expansion around room temperature. This is one of the systems for which the magnetization shows a hysteresis when a magnetic field is applied. The hysteresis causes numerical difficulties, since for a certain magnetic field, there are three solutions (magnetic moments) with very similar total energies causing difficulties in the convergence of a conventional SCF procedure. In order to solve this problem, the fixed spin moment (FSM) method was proposed.210,211 It is a computational trick interchanging dependent and independent variables. Physically speaking, one applies a magnetic field and obtains a moment, but computationally one chooses the moment (as input) and calculates the field afterwards. In a conventional spin-polarized calculation, the Fermi energy must be the same for the spin-up and spin-down electrons. The magnetic moment $M$ is an output. In the FSM scheme, one does several constrained calculations, where the moment $M$ is an input, but allowing different Fermi energies for the two spin states. One can interpret the difference in the Fermi energies as a magnetic field. Although one needs to perform several calculations (instead of a single conventional one), they converge rather rapidly. The FSM method allows expanding the usual total-energy vs volume curve to an energy surface $E_{\\mathrm{tot}}(V,M)$ as a function of volume $V$ and moment $M$ , which also provides new insights. \n\n# F. Hyperfine fields and electric field gradients \n\nAll aspects of nucleus–electron interactions, which go beyond the electric point-charge model for a nucleus, define the hyperfine interactions. Nuclei with a nuclear quantum number $I\\geqslant1$ have an electric quadrupole moment $Q.$ . The nuclear quadrupole interaction (NQI) stems from the interaction of such a moment and the EFG, the second derivative of the Coulomb potential at the corresponding nuclear site. One can measure the EFG with Mössbauer spectroscopy, NMR, nuclear quadrupole resonance (NQR), or perturbed angular correlation (PAC). The NQI determines the product of Q and the EFG, a traceless tensor. The latter has a principal component and an asymmetry parameter $\\eta$ . The EFG is a ground-state property that can be determined experimentally (measuring NQI), provided the nuclear quadrupole moment is known. In early studies, the EFG was interpreted as a simple point charge model with additional corrections (Sternheimer factor212). However, later it was shown that the EFG can be calculated with DFT, as was illustrated213 for $\\mathrm{LiN}_{3}$ . The EFG is sensitive to the asymmetric charge distribution around a given nucleus and thus is a local probe, which often helps in clarifying the local atomic arrangement. The reader can find a short description of several EFG calculations for selected examples in Chap. 6.4 of Ref. 8, and here, we describe some important aspects and examples below. \n\nComputationally, it is important to treat both valence and semicore states very accurately because, due to the $1/r^{3}$ factor in the EFG expression, even small asphericities near the nucleus lead to important contributions. This was demonstrated for the first time for $\\mathrm{TiO}_{2}$ in the rutile structure, where the radial functions of the fully occupied Ti- $3p$ semi-core orbitals are slightly different for $p_{x},p_{y}$ , and $p_{z}$ states and thus contribute significantly to the EFG.28 \n\nThe mapping of the two $\\mathtt{C u}$ -EFGs in the high-temperature superconductor $\\mathrm{YBa}_{2}\\mathrm{Cu}_{3}\\mathrm{O}_{7}$ to the “plane” and “chain” Cu sites provides insight into which Cu atom is responsible for superconductivity, and the analysis of the EFG on all other sites helped us to interpret chemical bonding.214 It should be mentioned that the EFG at the (superconducting) Cu-plane site comes out quite inaccurate and ${\\mathrm{GGA}}+U$ calculations are necessary, leading to a redistribution of $0.07~\\mathrm{e}^{-}$ from a $3d_{x^{2}-y^{2}}$ orbital to a $3d_{z^{2}}$ orbital and an EFG in agreement with the experiment.92 \n\nNext, we briefly discuss the study on 16 fluoroaluminates from Ref. 215, for which experimental NMR data were compared to DFT results for the 27Al EFG. In all of these compounds, the aluminum atoms occur in $\\mathrm{AlF}_{6}^{3-}$ octahedra, which have a wide diversity of connectivity and distortions. One of these structures is shown in the inset of Fig. 13 for $\\mathrm{Ba}_{3}\\mathrm{Al}_{2}\\mathrm{F}_{12}$ . These fluoroaluminates illustrate how sensitive the EFG is to the exact position of neighboring atoms. A perfect octahedral symmetry would have a vanishing EFG, but small distortions cause an EFG. The calculations were first done using the less accurate powder diffraction data for the atomic positions [Fig. 13(a)], and the correlation between experiment and theory is not very good. Then, a DFT structure optimization was done leading to an almost perfect correlation between experimental and theoretical EFGs [Fig. 13(b)]. This structure optimization has an even more pronounced effect on the asymmetry parameter, as shown in Ref. 215. We should mention that there can also be a sensitivity to DFT functionals for EFG calculations as described in Refs. 66 and 80. \n\nLast but not least, we demonstrate how one can determine the nuclear quadrupole moment Q from a combination of theoretical EFG calculations and experimental measurements of the quadrupole splitting, which is proportional to the product of EFG and Q. From the slope of a linear regression for the EFG of several Fe compounds, we could deduce the nuclear quadrupole moment $Q$ of $^{57}\\mathrm{Fe}_{\\mathrm{:}}$ , the most important Mössbauer isotope. It was found to be about twice as large $Q=0.16\\mathrm{~b~}$ ) as the previous literature value $\\cdot Q=0.082{\\mathrm{~b}}^{\\cdot}$ ), suggesting to revise this nuclear property using electronic structure calculations.216 \n\nThe magnetic hyperfine field (HFF) at a nucleus originates from a Zeeman interaction between the magnetic moment $I$ of this nucleus and the magnetic field at this site produced by the spinpolarized electrons in a ferromagnet. The HFF has contributions from the Fermi-contact term (the spin density at the nucleus), an orbital, and a spin dipolar contribution. Here, we skip the details but mention that an all-electron treatment is crucial, especially for the Fermi-contact term, since one needs accurate values of the spindensity close to the nucleus, for which the basis set used in WIEN2k is extremely useful. We recalculate the densities of all electrons, including the core, in each cycle of the SCF scheme, in contrast to the frozen-core approximation. The resulting core polarization can often be the main contribution to the HFF. The high quality of such calculations was demonstrated for the double perovskite ${\\tt B a F e}_{2}{\\tt O}_{5}$ , for which the DFT calculations of EFG and HFF provided new insights (for details, see Ref. 207). \n\n![](images/664aa9d0e8e2e1e6176599691929c936fc21e251a5720e8a37e38792bcea9091.jpg) \nFIG. 13. The calculated EFG (principal component) vs the experimental $^{27}\\mathsf{A l}$ quadrupole frequency for 16 fluoroaluminates is shown for two cases based on (a) the experimental structure and (b) the DFT optimized structure. For further details, see Ref. 215. The inset shows as one example of the fluoroaluminates, the $\\mathsf{A l F}_{6}^{3-}$ octahedra in ${\\mathsf{B a}}_{3}{\\mathsf{A l}}_{2}{\\mathsf{F}}_{12}$ (Ba: blue, Al: red, and F: green). \n\n# G. NMR chemical and Knight shifts \n\nThe NMR shielding $\\overleftrightarrow{\\boldsymbol{\\sigma}}$ tensor is defined as a constant between an induced magnetic field $\\mathbf{B}_{\\mathrm{ind}}$ at the nucleus at site $\\mathbf{R}$ and the external uniform field $\\mathbf{B}_{\\mathrm{ext}}$ , \n\n$$\n{\\displaystyle{\\bf B}_{\\mathrm{ind}}({\\bf R})=-\\overleftrightarrow{\\boldsymbol{\\sigma}}({\\bf R}){\\bf B}_{\\mathrm{ext}}.}\n$$ \n\nIts value is usually in the range of ppm (part per million). Since the magnetic field cannot be controlled with such a precision, the tensor is measured only with respect to some reference, \n\n$$\n\\delta({\\bf R})=\\sigma_{\\mathrm{ref}}-\\sigma({\\bf R}),\n$$ \n\nand often only its isotropic part $\\sigma({\\bf R})=\\mathrm{tr}[\\overleftrightarrow{\\boldsymbol{\\sigma}}\\left({\\bf R}\\right)]$ is known. \n\nThe external magnetic field is a relatively weak perturbation compared to the typical energy scale of the electronic structure; therefore, its effect on the spin and orbit of an electron can be separated in the theoretical calculations. Here, we only outline the main features that are specific to the $\\mathrm{\\APW+lo}$ method and the WIEN2k code and are vital for achieving high accuracy of the computed NMR tensor. A more in-depth discussion can be found in the original publications. The formalism for computing the orbital part of the shielding (chemical shift) has been described in Refs. 217 and 218, and the spin part (Knight shift) of the response has been described in Ref. 219. The formalism has been applied for computing shielding in various insulating78,220,221 and metallic systems.222–224 \n\nAs will be explained below, this approach can reach the basis set limit for NMR calculations, and benchmark calculations for small molecular systems have proven that standard quantum chemistry methods can only reach this precision with very large uncontracted quintuple-zeta basis sets and only for light atoms.225 \n\n# 1. Orbital component \n\nThe orbital part of the shielding, i.e., the orbital component of the induced field $\\mathbf{B}_{\\mathrm{ind}}$ , is obtained directly from the Biot–Savart law (in atomic units, with $c$ as speed of light), \n\n$$\n\\mathbf{B}_{\\mathrm{ind}}(\\mathbf{R})={\\frac{1}{c}}\\int\\mathbf{j}(\\mathbf{r})\\times{\\frac{\\mathbf{r}-\\mathbf{R}}{\\left|\\mathbf{r}-\\mathbf{R}\\right|^{3}}}d^{3}r,\n$$ \n\nwhere $\\mathbf{j}(\\mathbf{r})$ is the induced orbital current, evaluated as expectation value of the current operator \n\n$$\n\\mathbf{J}(\\mathbf{r})=-{\\frac{\\mathbf{p}|\\mathbf{r}\\rangle\\langle\\mathbf{r}|+|\\mathbf{r}\\rangle\\langle\\mathbf{r}|\\mathbf{p}}{2}}-{\\frac{\\mathbf{B}_{\\mathrm{ext}}\\times\\mathbf{r}}{2c}}|\\mathbf{r}\\rangle\\langle\\mathbf{r}|.\n$$ \n\nWIEN2k separates the calculation of valence and core states. The core state contribution to the induced current is computed using the spherically symmetric core density only, \n\n$$\n\\mathbf{j}_{\\mathrm{core}}(\\mathbf{r})=-\\frac{1}{2c}\\rho_{\\mathrm{core}}(\\mathbf{r})\\mathbf{B}_{\\mathrm{ext}}\\times\\mathbf{r}.\n$$ \n\nThe method for computing the valence contribution to $\\mathbf{j}(\\mathbf{r})$ is based on a linear response approach226–228 originally developed by Mauri, Pfrommer, and Louie.226 The expression for the induced current involves only the first-order terms with respect to the external field Bext, \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\bf j}({\\bf r})=\\sum_{o}\\Bigl[\\langle\\psi_{o}^{(1)}|{\\bf J}^{(0)}({\\bf r})|\\psi_{o}^{(0)}\\rangle+\\langle\\psi_{o}^{(0)}|{\\bf J}^{(0)}({\\bf r})|\\psi_{o}^{(1)}\\rangle}}\\\\ {{\\displaystyle~+~\\langle\\psi_{o}^{(0)}|{\\bf J}^{(1)}({\\bf r})|\\psi_{o}^{(0)}\\rangle\\Bigr]},}\\end{array}\n$$ \n\nwhere ψo(0) is an unperturbed KS occupied orbital, J0(r) is the paramagnetic part of the current operator [the first term in Eq. (33)], and $J^{1}(\\mathbf{\\check{r}})$ is the diamagnetic component of the current operator [the second term in Eq. (33)]. $\\psi_{o}^{(1)}$ is the first-order perturbation of $\\psi_{o}^{(0)}$ , given by the standard formula involving a Green’s function, \n\n$$\n\\big|\\psi_{o}^{(1)}\\big\\rangle=\\sum_{e}\\big|\\psi_{e}^{(0)}\\big\\rangle\\frac{\\big\\langle\\psi_{e}^{(0)}\\big|H^{(1)}\\big|\\psi_{o}^{(0)}\\big\\rangle}{\\varepsilon_{o}-\\varepsilon_{e}}+\\sum_{\\mathrm{core}}\\big|\\psi_{\\mathrm{core}}^{(0)}\\big\\rangle\\frac{\\big\\langle\\psi_{\\mathrm{core}}^{(0)}\\big|H^{(1)}\\big|\\psi_{o}^{(0)}\\big\\rangle}{\\varepsilon_{o}-\\varepsilon_{\\mathrm{core}}},\n$$ \n\nand involves a sum over empty states (first term) as well as a sum over core states (second term) because the core states have been calculated before [Eq. (34)] and Eq. (36) is only correct if all states of a system are included. Note that core wave functions appear in Eq. (36) as if they were unoccupied states. $\\boldsymbol{H}^{(1)}$ is the perturbation due to the external magnetic field in symmetric gauge, \n\n$$\n\\boldsymbol{H}^{(1)}=\\frac{1}{2c}\\mathbf{r}\\times\\mathbf{p}\\cdot\\mathbf{B}_{\\mathrm{ext}}.\n$$ \n\nAs discussed in Sec. II A, the basis functions of the $\\mathrm{\\APW+lo}$ method are highly tuned to describe the occupied Bloch states everywhere in the unit cell (in particular, also close to the nucleus), but they are not a complete basis set. Therefore, depending on the perturbation of the Hamiltonian, they may not be well suited to expand the perturbations of wave functions. In fact, magnetic fields and NMR are such cases where the perturbed wave functions, in particular, near the nucleus, are very different, which means that the sum in Eq. (36) cannot be converged with the available set of orbitals. In order to remedy this issue, we had to enhance the original WIEN2k basis set. First, the standard set of local orbitals is extended significantly, both in the number of LOs per $\\ell$ (typically to $5{-}8\\ \\mathrm{LOs})$ and also in $\\ell$ (typically to $\\ell+1\\$ ), where $\\ell$ refers to the maximal “chemical” $\\ell$ of this atom.217 These extra local orbitals are referred to as NMRLOs, and the energy at which the radial functions of those NMR-LOs are computed is chosen such that each of the NMR-LO radial functions has zero value at the sphere boundary and the number of nodes inside the sphere of subsequent LOs increases by one corresponding to the next principal quantum number.217 However, these NMRLOs alone cannot completely improve the variational flexibility close to the nuclei. \n\nThe perturbation of the Hamiltonian due to the external magnetic field is proportional to a product of position and momentum operators. As a result, the perturbation of the radial wave function $\\boldsymbol{u}_{t\\ell}$ contains components proportional to $u_{t\\ell\\pm1}$ and their radial derivative $\\begin{array}{r}{r\\frac{\\partial}{\\partial r}u_{t\\ell\\pm1}}\\end{array}$ . A direct introduction of basi±s functions based on $r\\frac{\\partial}{\\partial r}u$ is not co±nvenient within the APW formalism because such functions are not eigenstates of the radial Schrödinger equation. Therefore, we have proposed to add the desired term directly to the Green’s function present in the formula for the first-order perturbation of the valence state wave function.218 It is referred to as the $\\mathit{\\Omega}^{\\alpha}\\frac{\\partial\\mathit{\\Omega}}{\\partial\\mathit{r}}u$ correction” (DUC). \n\nThe convergence test with respect to the number of NMR-LO and DUC corrections is presented in Fig. 14. The induced current and shielding calculated within our linear response formalism is compared to the exact value for an isolated Ar atom. The current and shielding for a spherically symmetric atom can be computed exactly using only its density and the same formula [Eq. (34)] as for the core states (diamagnetic current). \n\nBoth DUC and several additional NMR-LOs are needed to reproduce the shape of the exact diamagnetic current in a region within 0.5 bohr from the nucleus. It appears in Fig. 14(a) that any error in the representation of the current in this region results in substantial errors of the computed shielding values [Fig. 14(b)]. This method can therefore reach the basis set limit. \n\nThe all-electron nature and the modular concept of WIEN2k makes it very easy to perform NMR calculations with wave functions including SO interactions for heavy nuclei or using different \n\n![](images/845fd2dba3bf7fae1e317d28fcb313524ec91a1dfd7018343a5a6aeec6919179.jpg) \nFIG. 14. (a) Comparison of the induced current computed for an Ar atom (valence states 3s and $3p$ ) with and without DUC corrections and for 2 and 7 NMR-LOs. $j_{\\rho}$ is the (exact) diamagnetic current [see Eq. (34)]. (b) Convergence of NMR absolute shielding $\\sigma$ with respect to the number of NMR-LOs in the APW basis and with/without DUC corrections. The vertical blue line represents the exact value of the absolute shielding $\\sigma_{\\mathrm{Ar}}=1245.7$ ppm computed with $j_{\\rho}$ . \n\nDFT approximations, including $\\mathrm{DFT}+U$ (Sec. II B 3), but, in particular, also hybrid functionals (Sec. II B 2). Thus, we can compare the theoretical shielding with the experimental chemical shifts for several different compounds, and from the correlation and slope of the linear regression curve, the quality of a particular approximation to the XC effects can be evaluated. Ideally, the slope of this linear regression line should be $^{-1}$ , but typically for ionic compounds,78 the slope with PBE is too large $(-1.2)$ , while with the hybrid functional YS-PBE0,66 it is too small $\\left(-0.8\\right)$ . This is quite in contrast to organic molecules, where hybrid f−unctionals perform much better than the GGAs. Surprisingly, the BJ potential106 performs quite well for ionic oxides or halides and yields slopes close to $^{-1}$ . \n\nMost importantly, theory should not only reproduce measured experimental values but also provide insights. WIEN2k allows us to analyze and identify the contributions to the NMR shielding, and for instance, for the F-shielding in the alkali-fluoride series (Fig. 15), the following observations can be made:221 (i) Basically, all contributions to the F-shielding come from a region inside the F atomic sphere (the current in the rest of the unit cell contributes negligibly). (ii) The large (diamagnetic) shielding comes from the constant F-1s core contribution. (iii) The contributions from the $\\mathrm{F}{-}2s$ bands are still diamagnetic, but much smaller and again constant within the series. (iv) The diamagnetic metal- $\\cdot p$ semi-core contributions $(\\mathrm{Na}-2p$ to $\\mathsf{C s}{-}5p$ ) increase within the series. This can be explained by the fact that for heavier elements the metal $\\boldsymbol{p}$ -states increase in energy and come closer to the $\\mathrm{F}{-}2p$ band. This leads to an increased bonding (in the metal- $d$ band) and anti-bonding (in the $\\mathrm{F}{\\cdot}p$ band) metal- $\\cdot-\\mathrm{F}-P$ interaction giving slightly different (non-canceling) diamagnetic and paramagnetic contributions. (v) The trend of $\\sigma$ within the series comes mainly from the $\\mathrm{F}{-}2p$ valence band. The most important ingredient, which determines the size of the (mostly paramagnetic) $\\mathrm{F}{-}2p$ contribution, is the position of the unoccupied metal- $d$ band. The perturbation due to the magnetic field couples the occupied F- $\\cdot p$ states with $\\Delta\\ell\\pm1$ to unoccupied $d$ states, and due to the energy denominator in E±q. (36), the Cs- $d$ states give the largest contribution because they are the closest in energy to the valence bands. We can even artificially apply a (large) $U$ value to the empty $\\cos-5d$ states shifting them further up. In this way, we do not alter the occupied states but still can increase the F shielding in CsF to reproduce the LiF or NaF shifts. \n\n![](images/1a9de80f3255d7f90d1fd9f036a43e923693935a272b89b71ef4bec98fda7cf5.jpg) \nFIG. 15. $^{19}F$ NMR shielding $\\sigma$ (in ppm) in alkali fluorides (data taken from Ref. 221). Black lines: Total $\\sigma$ (full line) and contribution from within the F-sphere (dashed line). Further decomposition into core F-1s (green), F-2s band (blue), metal- $\\cdot p$ band (red), and $F-2p$ band (brown) is also shown. \n\nBy a similar analysis, we could explain why the $^{33}\\mathrm{S}$ magnetic shielding decreases with the metal nuclear charge $Z$ in the ionic alkali/alkali-earth sulfides but increases in TM sulfides.220 \n\n# 2. Spin component \n\nIn order to compute the induced spin density and spin part of the NMR shielding tensor, we use a direct approach,219 instead of applying the linear response formalism proposed, for instance, in Ref. 229. This is possible because the interaction of the spin with the external magnetic field does not break the periodicity. Therefore, we perform self-consistent spin polarized calculations with a finite external magnetic field $\\mathbf{B}_{\\mathrm{ext}}$ acting on the electron spin only. The interaction with $\\mathbf{B}_{\\mathrm{ext}}$ is cast into a spin-dependent potential leading to a spin splitting of eigenstates and a finite spin magnetization. The induced magnetic field at a given nucleus is computed using an expression for the magnetic hyperfine field,230 \n\n$$\n\\mathbf{B}_{\\mathrm{hf}}={\\frac{8\\pi}{3}}\\mu_{\\mathrm{B}}\\mathbf{m}_{\\mathrm{av}}+\\left\\langle\\Phi_{1}\\left\\vert{\\frac{S(r)}{r^{3}}}[3(\\mu\\cdot{\\hat{\\mathbf{r}}}){\\hat{\\mathbf{r}}}-\\mu]\\right\\vert\\Phi_{1}\\right\\rangle.\n$$ \n\nThe first term $\\left(\\mathbf{B}_{\\mathrm{c}}\\right)$ is the Fermi contact term, where $\\mathbf{m}_{\\mathrm{av}}$ is the average of the spin density in a region near the nucleus with a diameter equal to the Thomson radius. The second term $(\\mathbf{B}_{\\mathrm{sd}})$ captures the spin-dipolar contribution to the hyperfine field, where $\\Phi_{1}$ is the large component of the wave function, S is the reciprocal relativistic mass enhancement, and $\\mu$ is the magnetic moment operator of the electron. $\\mathbf{B}_{\\mathrm{sd}}$ comes almost entirely from within the atomic sphere, which simplifies its calculation. The spin contribution $(\\sigma_{s})$ , i.e., the Knight shift to the shielding, is therefore given by two terms, \n\n$$\n\\mathbf{B}_{\\mathrm{hf}}=-{\\overleftrightarrow{\\boldsymbol{\\sigma}_{s}}}\\mathbf{B}_{\\mathrm{ext}}=-\\Big({\\overleftrightarrow{\\boldsymbol{\\sigma}_{c}}}+\\overleftrightarrow{\\boldsymbol{\\sigma}_{s d}}\\Big)\\mathbf{B}_{\\mathrm{ext}}.\n$$ \n\nIn order to obtain a sizable response and evaluate the NMR shielding with a numerical precision at the level of $1\\ \\mathrm{ppm}$ , we apply in our calculations an external magnetic field of $100\\mathrm{T}$ , which induces a spin-splitting of approximately $1\\mathrm{mRy}$ . These small changes require an extremely fine $\\mathbf{k}$ -point sampling (for fcc Al, $10^{6}\\ \\mathbf{k}.$ -points are needed), and this must always be carefully checked. \n\nFurther details and results of our approach can be found in Refs. 219, 222, and 223, but, here, we summarize the main findings: (i) The previously accepted point of view, namely, that Knight shifts are proportional to the partial $s$ -DOS at the Fermi energy and the orbital contribution $\\sigma_{\\mathrm{orb}}$ is identical to that in the (ionic) reference compound, is only true for simple $\\boldsymbol{s p}$ metals. (ii) In TM $d$ -elements or metallic compounds, the orbital part $\\sigma_{\\mathrm{orb}}$ can be as important as the spin part $\\sigma_{s}$ . (iii) The $s$ -DOS at $E_{F}$ is always important, but an induced TM- $d$ magnetic moment (proportional to the partial $d$ -DOS at $E_{F}$ ) polarizes the core states in the opposite direction so that the valence and core polarizations can partly cancel. (iv) The dipolar contribution $\\sigma_{\\mathrm{sd}}$ is usually small, but, in anisotropic materials, a large dominance of one particular orbital at $E_{F}$ can eventually lead to a very large contribution. We have found this in $\\mathrm{BaGa}_{2}$ , where the $p_{z}{\\mathrm{-DOS}}$ has a large and sharp peak at $E_{F}$ leading to an aspherical magnetization density and a large dipolar contribution.222 \n\n# H. Wannier functions and Berry phases \n\nA single particle state of a periodic system is conventionally represented as a Bloch state $\\psi_{n\\bf{k}}({\\bf{r}})$ , which is labeled by a band index $n$ and a vector $\\mathbf{k}$ inside the first BZ. It satisfies Bloch’s theorem \n\n$$\n\\psi_{n\\mathbf{k}}(\\mathbf{r})=u_{n\\mathbf{k}}(\\mathbf{r})e^{i\\mathbf{k}\\cdot\\mathbf{r}},\n$$ \n\nwhere $u_{n\\mathbf{k}}(\\mathbf{r})=u_{n\\mathbf{k}}(\\mathbf{r+R})$ is a lattice periodic function and $\\mathbf{R}$ is a Bravais lattice vector. Alternatively, one can define Wannier functions (WFs) wnR(r) in unit cell R for a set of J bands as231,232 \n\n$$\nw_{n\\mathbf{R}}(\\mathbf{r})={\\frac{V}{(2\\pi)^{3}}}\\int_{\\mathrm{BZ}}e^{-i\\mathbf{k}\\cdot\\mathbf{R}}\\sum_{m=1}^{J}U_{m n}^{\\mathbf{k}}\\psi_{m\\mathbf{k}}(\\mathbf{r})d^{3}k,\n$$ \n\nwhere $V$ is the unit cell volume and $U^{\\mathbf{k}}$ are unitary transformation matrices that mix Bloch states at a given k. Because of the arbitrary phase of $\\psi_{n\\bf{k}}(\\bf{r})$ , the resulting WFs are usually not localized. Maximally localized WFs can be obtained by choosing the $U^{\\mathbf{k}}$ such that the spread $\\Omega$ is minimized, \n\n$$\n\\Omega=\\sum_{m=1}^{J}\\left[\\left\\langle w_{m\\mathbf{R}}\\middle|r^{2}\\middle|w_{m\\mathbf{R}}\\right\\rangle-\\left\\langle w_{m\\mathbf{R}}\\middle|r\\middle|w_{m\\mathbf{R}}\\right\\rangle^{2}\\right].\n$$ \n\nThis involves overlap integrals $M_{m n}^{\\mathbf{k},\\mathbf{b}}=\\langle u_{m\\mathbf{k}}|u_{n\\mathbf{k}+\\mathbf{b}}\\rangle$ between the periodic part of the wave functions on uniform grid in the BZ. \n\nThe maximally localized WFs are calculated by Wannier90,231 and the transformation matrices $U^{\\mathbf{k}}$ are provided by the wien2wannier232 module of WIEN2k. The resulting WF can be used for various tasks. They can be visualized and are useful for the interpretation of chemical bonding to generate tight-binding models or interpolations to very fine k-meshes for properties that require fine $\\mathbf{k}$ -meshes. Such properties can be transport, anomalous Hall conductivity, linear and non-linear optics, Berry curvatures and topology, or electron–phonon interactions. In particular, for the improved description of electronic correlations via the DMFT approximation,233,234 WFs provide a realistic starting point. \n\nIn connection with wien2wannier, there is also the $B e r r y P i^{235}$ module in WIEN2k, which calculates the polarization of solids using the Berry phase approach.236 BerryPi can calculate the change of polarization $\\Delta P$ in response to an external perturbation to study ferroelectricity, the Born effective charges, pyroelectric coefficients, or the piezoelectric tensor. In addition, one can define Wilson loops and calculate Chern numbers to study topological properties.237 \n\n# I. External programs \n\n# 1. Thermoelectric transport coefficients \n\nWIEN2k is interfaced with the BoltzTraP2 program165 for calculating transport coefficients within the relaxation time approximation. The calculation is based on evaluating the transport distribution function, \n\n$$\n\\sigma(\\varepsilon,T)=\\int\\sum_{n}\\mathbf{v}_{n\\mathbf{k}}\\otimes\\mathbf{v}_{n\\mathbf{k}}\\tau_{n\\mathbf{k}}\\delta{\\bigl(}\\varepsilon-\\varepsilon_{n\\mathbf{k}}{\\bigr)}{\\frac{d^{3}k}{8\\pi^{3}}},\n$$ \n\nusing a fine mesh in $\\mathbf{k}$ -space. To obtain the group velocities, $\\mathbf{v}_{n\\mathbf{k}}$ , and also quasi-particle energies on a fine mesh or effective masses, BoltzTrap2 relies on interpolating the eigenvalues, $\\varepsilon_{n\\mathbf{k}}$ , and possibly also the relaxation times, $\\tau_{n\\mathbf{k}}$ , using Fourier sums. \n\nThe interpolation is performed so that the calculated eigenvalue energies are reproduced exactly. Within KS theory, the multiplicative potential [Eq. (10)] means that it is often computationally very efficient to calculate a fine mesh of eigenvalues, which can then be interpolated further to evaluate Eq. (43). This argument no longer holds when hybrid functionals (Sec. II B 2), or the $G W$ method (Sec. III I 4), are used to obtain the band structure. Therefore, BoltzTraP2 can also include the $\\mathbf{k}$ -space derivatives in the interpolation scheme, as can be obtained from the momentum matrix elements introduced in Sec. III D. This allows a more efficient interpolation and the use of a coarser $\\mathbf{k}$ -mesh in the actual DFT calculation. \n\nOnce the transport distribution has been obtained, the temperature and chemical potential dependent transport coefficients \n\n$$\n\\mathcal{L}^{(\\alpha)}(\\mu;T)=q^{2}\\int\\sigma(\\varepsilon,T)(\\varepsilon-\\mu)^{\\alpha}\\Bigg(-\\frac{\\partial f^{(0)}(\\varepsilon;\\mu,T)}{\\partial\\varepsilon}\\Bigg)\\mathrm{d}\\varepsilon\n$$ \n\ncan be obtained by a simple numerical integration. Figure 16 shows the highest valence bands of TiCoSb calculated using the interpolation scheme of BoltzTraP2. Compared to Fig. 7, a very good agreement with the band structure obtained using DFT is found. \n\n![](images/dd960b9ff0aa9c005cc69eedec2d8aac2aba5f60eb4355490cd9adbd4c6d7948.jpg) \nFIG. 16. Highest valence bands of TiCoSb obtained with the BoltzTraP2 interpolation together with the calculated thermoelectric power factor at $300~\\mathsf{K}$ using a constant relaxation time of $\\tau=10^{-14}\\ s$ . The inset shows the constant energy surface at the energy marked by the dotted line. \n\nSince the Fourier interpolation is done bandwise (marked by color in Fig. 16), the band crossing along the $\\Gamma-X$ direction is not reproduced. However, the error is hardly visible−by eye and, in accordance with the intention of the original algorithm,238,239 no Fourier ripples are seen, which means that errors in the derivatives are isolated to the points where the crossing occurs. The calculated thermoelectric power factor using a constant relaxation time is also shown. The power factor peaks at a high value close to the band edge, where a steep transport distribution can be expected. The high power factor can be attributed to the complex constant energy surface shown in the inset, which is typical for half-Heusler compounds with favorable p-type thermoelectric performance.240 \n\nBoltzTraP2 is written mainly in PYTHON3 and can be used as PYTHON library. The interpolation is handled by a single PYTHON call, fitde3D. Once the Fourier coefficients have been obtained, the interpolation of the bands onto the direction needed for plotting the band structure (getBands), or the fine mesh needed for obtaining the transport distribution (getBTPbands), can be performed. The use of BoltzTraP2 as a library gives a reproducible and flexible work flow. The analysis associated with Fig. 16 can thus be performed with a single PYTHON script, which is included in the most recent distribution. \n\n# 2. Non-collinear magnetism \n\nWIEN2k can only compute the electronic structure of magnetic systems with a collinear spin arrangement. For performance benefits, WIEN2k assumes that the spin density matrix along some direction is diagonal for each eigenstate. When SO interactions are taken into account, this condition is sometimes not satisfied. In such cases, the off-diagonal terms of the spin density matrix are simply ignored during the SCF procedure and only the $z$ component of the spin density is properly converged. Generally, this is not a big issue for cases with collinear spin arrangement and is, in fact, common practice. However, such an approximation cannot be applied for systems with a non-collinear spin arrangement for which the full spin density matrix has to be considered. For that purpose, we have written a non-collinear spin version of WIEN2k, referred to as WIENNCM. \n\nOur implementation is based on a mixed spinor basis set approach.241,242 In the interstitial region, the basis functions are pure spinors given in a global $(g)$ spin coordinate frame, \n\n$$\n\\varphi_{\\bf K+k,\\sigma}=e^{i({\\bf K+k})\\cdot{\\bf r}}\\chi_{\\sigma}^{g},\n$$ \n\nwher $\\chi_{\\uparrow}^{g}={\\binom{1}{0}}$ $\\chi_{\\downarrow}^{g}={\\binom{0}{1}}$ Inside the atomic spheres, the basis functions are a combination of both up and down spinors, which are set in a local spin coordinate frame with a quantization axis pointing along the direction of the average magnetization of the given atomic sphere. This direction does not have to be the same for each sphere, and the basis functions are [for a LAPW basis set, where we drop the $(r,E)$ -dependency in the radial $u$ functions] \n\n$$\n\\varphi_{\\mathbf{K}+\\mathbf{k},\\sigma}^{\\mathrm{LAPW}}=\\sum_{\\ell,m,\\sigma^{t}}\\left(A_{t\\ell m}^{\\mathbf{K}+\\mathbf{k},\\sigma\\sigma^{t}}u_{t\\ell}^{\\sigma^{t}}+B_{t\\ell m}^{\\mathbf{K}+\\mathbf{k},\\sigma\\sigma^{t}}\\dot{u}_{t\\ell}^{\\sigma^{t}}\\right)Y_{\\ell m}\\chi_{\\sigma^{t}},\n$$ \n\nwhere $\\chi_{\\sigma^{t}}$ is a spinor given in a local coordinate frame. This choice of the spin coordinate frame allows us to use spin-polarized radial functions with the quantization axis along the direction of the average magnetization. The matching of the $\\varphi_{\\mathbf{K}+\\mathbf{k},\\sigma}^{\\mathrm{LAPW}}$ basis to the plane waves at $r=R_{\\mathrm{MT}}$ is done for up and down plane waves in a global spin coordinate frame, \n\n$$\ne^{i(\\mathbf{K}+\\mathbf{k})\\cdot\\mathbf{r}}\\chi_{\\sigma}^{g}=\\sum_{\\ell,m,\\sigma^{t}}\\left(A_{t\\ell m}^{\\mathbf{K}+\\mathbf{k},\\sigma\\sigma^{t}}u_{t\\ell}^{\\sigma^{t}}+B_{t\\ell m}^{\\mathbf{K}+\\mathbf{k},\\sigma\\sigma^{t}}\\dot{u}_{t\\ell}^{\\sigma^{t}}\\right)Y_{\\ell m}\\chi_{\\sigma^{t}}^{g}.\n$$ \n\nThus, the $A_{t\\ell m}$ and $B_{t\\ell m}$ depend on global $\\sigma$ and local $\\boldsymbol{\\sigma}^{t}$ spin indices. Multiplying both sides of Eq. (47) by $\\left(\\chi_{\\sigma^{t}}^{g}\\right)^{*}$ , integrating over the spin variable, and comparing to the standard collinear expression, $A_{t\\ell m}^{\\mathbf{K}+\\mathbf{k},\\sigma\\sigma^{t}}$ and $B_{t\\ell m}^{\\mathbf{K}+\\mathbf{k},\\sigma\\sigma^{t}}$ are given by \n\n$$\n\\begin{array}{r l}&{{\\cal A}_{t\\ell m}^{\\bf K+k,\\sigma\\sigma^{t}}=\\left(\\chi_{\\sigma^{t}}^{g}\\right)^{*}\\chi_{\\sigma}^{g}{\\cal A}_{t\\ell m}^{\\bf K+k,\\sigma^{t}},}\\\\ &{}\\\\ &{{\\cal B}_{t\\ell m}^{\\bf K+k,\\sigma\\sigma^{t}}=\\left(\\chi_{\\sigma^{t}}^{g}\\right)^{*}\\chi_{\\sigma}^{g}{\\cal B}_{t\\ell m}^{\\bf K+k,\\sigma^{t}},}\\end{array}\n$$ \n\nwhere AK+k,σ and BK+k,σt are the collinear matching coefficients calculated for “local” spins. We have extended the original formal$\\mathrm{ism}^{241,243}$ beyond the atomic moment approximation, and the code processes the spin density matrices without any approximations also inside the atomic spheres. Note that the adaptation of the above equations for LOs or the APW+lo basis set is trivial. \n\nA few more details of the implementation are the following: In WIENNCM, the default scalar relativistic Hamiltonian is extended with SO interactions and this doubles the size of the Hamiltonian. It is also possible to use the $\\mathrm{DFT}+U$ method for correlated systems. The setup and execution of WIENNCM is as in WIEN2k; however, the atomic structure has to be augmented with definitions of the magnetic structure, which requires to define the orientation of the average magnetic moment for each atom. This is to some extent automatized in such a way that the user only needs to provide the orientation for the “magnetic atoms” (e.g., only $\\mathrm{~U~}$ atoms in $\\mathrm{UO}_{2}^{\\cdot}$ ). The orientation for “non-magnetic” atoms (O in $\\mathrm{UO}_{2}$ ) is generated automatically. WIENNCM makes use of the spin symmetry, which simplifies the calculations. \n\nIf one wants to calculate spin spirals, one can either handle this by (big) supercells or, more efficiently, by using the generalized \n\nBloch theorem244 (neglecting SO interactions) so that these calculations can be done in the small crystallographic cell. \n\nExamples of application of our implementation can be found in Refs. 91 and 245. \n\n# 3. Electron–hole interactions \n\nThe state-of-the-art method to include electron–hole interactions is based on the solution of the equation of motion of the twoparticle Green’s function, known as the BSE.246–248 The WIENBSE code allows the calculation of the optical response taking into account excitonic effects. The BSE is solved in an approximate manner by representing them in the form of an effective eigenvalue problem with the so-called BSE Hamiltonian,249,250 \n\n$$\n\\sum_{\\nu^{\\prime},c^{\\prime},\\mathbf{k}^{\\prime}}H_{\\nu c\\mathbf{k},\\nu^{\\prime}c^{\\prime}\\mathbf{k}^{\\prime}}^{e}A_{\\nu^{\\prime}c^{\\prime}\\mathbf{k}^{\\prime}}^{\\lambda}=E^{\\lambda}A_{\\nu c\\mathbf{k}}^{\\lambda},\n$$ \n\nwhere the sum runs over occupied (they form the hole upon excitation) valence (v) and unoccupied (they become occupied upon excitation) conduction (c) bands and $\\mathbf{k}$ points (supplied by a DFT calculation performed with WIEN2k) and the electron–hole Hamiltonian consists of three terms, $H^{e}=H^{\\mathrm{diag}}+H^{\\mathrm{dir}}+H^{x}$ , which are given by $[\\mathbf{x}=(\\mathbf{r},\\sigma)]$ , \n\n$$\nH_{\\nu c\\mathbf k,\\nu^{\\prime}c^{\\prime}\\mathbf k^{\\prime}}^{\\mathrm{diag}}=\\big(\\varepsilon_{\\nu\\mathbf k}-\\varepsilon_{c\\mathbf k}+\\Delta\\big)\\delta_{\\nu\\nu^{\\prime}}\\delta_{c c^{\\prime}}\\delta_{\\mathbf k\\mathbf k^{\\prime}},\n$$ \n\n$$\nH_{\\nu c\\mathbf k,\\nu^{\\prime}c^{\\prime}\\mathbf k^{\\prime}}^{\\mathrm{dir}}=-\\int\\psi_{\\nu\\mathbf k}(\\mathbf x)\\psi_{c\\mathbf k}^{*}(\\mathbf x^{\\prime})W(\\mathbf r,\\mathbf r^{\\prime})\\psi_{\\nu^{\\prime}\\mathbf k^{\\prime}}^{*}(\\mathbf x)\\psi_{c^{\\prime}\\mathbf k^{\\prime}}(\\mathbf x^{\\prime})d^{3}x d^{3}x^{\\prime},\n$$ \n\n$$\nH_{\\nu\\mathrm{ck},\\nu^{\\prime}\\epsilon^{\\prime}{\\bf k}^{\\prime}}^{x}=\\int\\psi_{\\nu\\bf k}({\\bf x})\\psi_{\\mathrm{ck}}^{*}({\\bf x})\\bar{\\nu}({\\bf r},{\\bf r}^{\\prime})\\psi_{\\nu^{\\prime}{\\bf k}^{\\prime}}^{*}({\\bf x}^{\\prime})\\psi_{c^{\\prime}{\\bf k}^{\\prime}}({\\bf x}^{\\prime})d^{3}x d^{3}x^{\\prime}.\n$$ \n\nThe $\\boldsymbol{H}^{\\mathrm{diag}}$ term depends only on the eigenvalues and accounts for the response in the non-interacting limit. The exchange $H^{x}$ and the direct $H^{\\mathrm{dir}}$ Coulomb terms couple the electron–hole pairs.251 The direct term, in principle, depends on the dynamically screened Coulomb electron–hole interaction and on the excitation energy $(\\boldsymbol{E}^{\\lambda})$ , but here we apply the usual approximation and only account for non-local but static screening. The coupling coefficients $\\boldsymbol{A}_{\\nu c\\mathbf{k}}^{\\lambda}$ define the electron–hole correlation function and enter the expression for the imaginary part of the dielectric function, \n\n$$\n\\varepsilon_{2}{\\big(}\\omega{\\big)}={\\frac{8\\pi^{2}}{\\Omega}}\\sum_{\\lambda}\\left\\vert\\sum_{\\nu,c,\\mathbf{k}}A_{\\nu c\\mathbf{k}}^{\\lambda}{\\frac{\\langle\\nu\\mathbf{k}|-i\\nabla_{x}|c\\mathbf{k}\\rangle}{\\varepsilon_{\\nu\\mathbf{k}}-\\varepsilon_{c\\mathbf{k}}}}\\right\\vert^{2}\\delta{\\big(}E^{\\lambda}-\\omega{\\big)}.\n$$ \n\nThe BSE approach is very successful in dealing with excitons and the response in the optical regime. The excitonic effects are sometimes small (e.g., in small gap semiconductors), but still important, with binding energies of some tens of meV, sometimes large (in particular, in insulators) with binding energies of a couple of eV such that the resulting optical functions have hardly any resemblance with independent-particle results. The WIENBSE implementation has been used in several works for various semiconductors,252–255 but together with supercell calculations and GW- or TB-mBJ-based single particle states, it can also successfully describe F centers in wide bandgap alkali halides.76,256 It has also been extended to include a fully relativistic treatment of core states to study XANES at $\\mathbf{L}_{2,3}$ edges of 3d TM compounds.196 In particular, for formally $3d^{0}$ compounds such as $\\mathrm{TiO}_{2}$ , the correct $\\mathrm{L}_{2}/\\mathrm{L}_{3}$ branching ratio can be obtained due to interference effects of the $2p_{1/2}$ and $2p_{3/2}$ core states. Even fine differences in line shape between the rutile and anatase modifications are in agreement with the experiment demonstrating the power of this approach. \n\n# 4. GW approximation for quasi-particle calculations \n\nThe GW method102,103 is considered as the state-of-the-art method for a first-principles description of the electronic quasiparticle band structure in solids. The name of this many-body perturbation theory based method comes from the interacting Green’s function $G(\\boldsymbol{\\mathbf{r}},\\ \\boldsymbol{\\mathbf{r}}^{\\prime},\\ \\omega)$ , whose poles in the complex frequency plane determine the single-particle excitation energies and $W$ , the dynamically screened Coulomb potential, which is obtained using the polarizability in the random-phase approximation. The central quantity, namely, the self-energy $\\Sigma(\\boldsymbol{\\mathbf{r}},\\ \\boldsymbol{\\mathbf{\\bar{r}}}^{\\prime},\\ \\omega)$ from which the first-order correction to the KS eigenvalues can be calculated, is obtained from \n\n$$\n\\Sigma(\\mathbf{r},\\mathbf{r}^{\\prime},\\omega)=\\frac{i}{2\\pi}\\int G(\\mathbf{r},\\mathbf{r}^{\\prime},\\omega+\\omega^{\\prime})W(\\mathbf{r}^{\\prime},\\mathbf{r},\\omega^{\\prime})e^{i\\omega^{\\prime}\\eta}d\\omega^{\\prime},\n$$ \n\nwhere $\\eta$ is an infinitesimal positive number. \n\nThe GAP2 code257,258 is the second version of an all-electron GW implementation based on the WIEN2k code. As WIEN2k, this highly parallelized code can use an arbitrary number of HDLOs,259,260 which ensures that one can obtain fully converged $G W$ results even in difficult cases such as $\\mathrm{znO}$ . Since it is based on an all-electron method and can use orbitals from $\\mathrm{DFT}+U_{\\mathrm{:}}$ , a major advantage of this code is the possibility to explore $d.$ - and $f$ -electron systems in a meaningful way.260 We note that for materials that are traditionally categorized as strongly correlated (e.g., the oxides), the standard semilocal functionals usually fail (see Sec. II B 3). For such systems, using the $\\mathrm{DFT}+U$ (or hybrid) orbitals as input for one-shot, $G_{0}W_{0}$ performs much better.261,262 In addition, the code allows for partially self-consistent $G W_{0}$ calculations by updating $G$ with the modified eigenvalues. \n\nAnother important feature is the possibility for a first-principles determination of the Hubbard $U$ using the constrained random phase approximation263 and maximally localized WFs with an interface to Wannie $90^{231}$ by wien2wannier.232 \n\n# 5. Dynamical mean field theory \n\nMany systems have valence electrons in orbitals, which are quite extended in space and overlap strongly with their neighbors. This leads usually to strong bonding-antibonding effects, large bandwidth $W_{;}$ , and dominant contributions from the kinetic energy. If, in addition, the bare Coulomb interaction $U$ between two electrons on the same site is strongly screened (maybe due to metallic character), such systems are usually quite well described by standard DFT approximations. However, as already mentioned in Sec. II B 3, $3d$ or $4f$ electrons may be more localized so that they participate much less in bonding and have a more atomic-like character. In these cases, the bandwidth W (metal) and Coulomb interaction $U$ (Mott insulator) compete as does the crystal-field splitting (low-spin state) and Hund’s rule coupling $J$ (high-spin state). We talk about “correlated electrons” and standard semilocal DFT approximations may fail badly in certain cases. The $\\mathrm{DFT}+U$ and hybrid methods discussed in Secs. II B 3 and $\\mathrm{~I~I~B~}2$ , respectively, can be much more accurate depending on the investigated property. However, the state-of-the-art approach for these correlated electron systems is DMFT,233,234 which is based on the Hubbard model on a lattice, described by the following Hamiltonian: \n\n$$\nH=\\sum_{,\\sigma}~t_{i j}c_{i\\sigma}^{\\dag}c_{j\\sigma}+U\\sum_{i}n_{i\\uparrow}n_{i\\downarrow}.\n$$ \n\nThe first term (kinetic energy) describes the hopping $t_{i j}$ of an electron with spin $\\sigma$ from lattice site $j$ to lattice site $i_{:}$ , while the second term (potential energy) accounts for the strong Coulomb repulsion $U$ between two electrons at the same lattice site $i,$ which is responsible for the correlations in the system. Within DMFT, the complicated lattice problem is replaced by a single-site impurity model, which hybridizes with a self-consistently determined non-interacting bath. \n\nThe basic idea of $\\mathrm{DFT+DMFT}$ is to divide the electrons in the system into two groups: weakly correlated electrons (i.e., electrons in $s-$ and $\\boldsymbol{p}$ -orbitals) that are well described by an approximate DFT functional and strongly correlated electrons (i.e., $d-$ and $f$ -electrons) well described using DMFT. The model Hamiltonian for DFT $^+$ DMFT is then constructed for the correlated subset with a suitable basis usually defined by Wannier functions as discussed in Sec. III H. The full-orbital KS Hamiltonian $H^{\\mathrm{KS}}$ is then projected onto the correlated subspace of the partially filled orbitals and manybody terms $\\boldsymbol{H}^{U}$ as well as a double counting correction $H^{\\mathrm{DC}}$ are added. \n\nSeveral such DFT $+$ DMFT codes264–269 use WIEN2k as basis, and numerous applications have proven the power of the combined DFT $^+$ DMFT approach. The DMFT approach is often applied to explain optical, XAS, or ARPES spectra (see, e.g., Ref. 270 for $\\mathrm{V}_{2}\\mathrm{O}_{3}\\mathrm{,}$ ) and can also estimate the intensities of the spectral features due to lifetime broadening. Recently, free energies and forces have also been made available,269,271 which allows us to study structural (e.g., α-γ Ce), magnetic (e.g., bcc-fcc Fe), or metal–insulator (e.g., ${\\mathrm{NdNiO}}_{3}$ ) phase transitions with temperature.272 \n\n# 6. Phonons \n\nWIEN2k does not have its own program to calculate phonon spectra, but it is interfaced with at least three different external phonon programs: phonopy,159,160 Phonon,161,162 and PHON.163,164 They all employ the finite-displacement method162 and a harmonic approximation. First, the crystal structure must be very well relaxed so that residual forces on all atoms are very small. For this structure, the phonon codes suggest a systematic set of displacements (depending on symmetry) in a chosen supercell and WIEN2k calculates the forces for these displacements. These forces are then used by the phonon codes to calculate harmonic force constants and setup and diagonalize the dynamical matrices at the desired $\\mathbf{k}$ -points, which yields the phonon frequencies and their eigenmodes. For Γ-phonons (infrared or Raman spectroscopy), a supercell is not required; otherwise, the supercell should be large enough (typically more than 50 atoms/cell) such that the force constants between atoms separated by more than the supercell size become negligible. In ionic solids, the frequency splitting of the optical vibrational modes parallel and perpendicular to the electric field (the so-called LO-TO splitting) in the small wave-vector limit can be obtained when additionally the Born effective charges (see Sec. III H) are supplied to the phonon programs. An alternative approach for phonon calculations, namely, density functional perturbation theory,273 is not implemented. \n\nPhonon calculations can be used to investigate various properties of materials. Frequencies at Γ are analyzed according to their symmetry and can be compared to IR and Raman spectra (see, e.g., Ref. 274 for application on ${\\mathrm{PbFBr}}_{1-x}{\\mathrm{I}}_{x}.$ ). The full phonon band structure and the corresponding phonon-DOS can be calculated and integrated, yielding thermodynamic quantities such as the mean square thermal displacements, the specific heat, entropy, or free energy, which together with the quasi-harmonic approximation can be used to determine thermal expansion. Imaginary frequencies at certain $\\mathbf{k}$ -points indicate an instability of this phase (at $0\\mathrm{~K~},$ ) and occur, for instance, in all cubic perovskites.275 Freezing in one of the corresponding eigenmodes with a certain amplitude and subsequent structure relaxation yields a more stable phase in a particular space group of lower symmetry and can be used to detect and analyze second-order phase transitions in various materials.276–278 \n\n# 7. Band structure unfolding \n\nThe standard way to model defects, vacancies, alloys (disorder), or surfaces is by means of a supercell approach. While sufficiently large supercells can handle the energetics of these problems quite well, it is fairly difficult to describe the effect of the perturbation on the bulk electronic structure. A band structure from a supercell calculation usually looks like a bunch of spaghetti and is very difficult to interpret. It is therefore highly desirable to display the band structure in the original BZ of the bulk material and indicate the original Bloch character as much as possible. This unfolding can be done conveniently by the fold2Bloch utility.166,279 \n\nIn an $h\\times k\\times l$ supercell band structure, each k-point transforms into $h\\times k\\times l$ ×k-points of the bulk BZ. fold2Bloch calculates the corresp×ondi×ng spectral weights $w_{n}(\\mathbf{k})$ , which amounts to the Bloch character $\\mathbf{k}$ of the nth eigenvalue $\\scriptstyle{\\varepsilon_{n}}$ , subject to the normalization that $\\begin{array}{r}{\\sum_{\\mathbf{k}}w_{n}(\\mathbf{k})=1}\\end{array}$ , and displays $w_{n}(\\mathbf{k})$ in the unfolded band structure s∑o that one can distinguish between regular bulk and defect states. \n\n# 8. de Haas–van Alphen effect \n\nThe knowledge of the Fermi surface (FS) of a metallic compound is important to understand its electronic and transport properties. de Haas–van Alphen (dHvA) measurements of the quantum oscillatory magnetization contain detailed information about the FS and report frequencies that are proportional to extremal FS cross sections perpendicular to the magnetic field direction.280 However, it is not so easy to reconstruct from the measured data the actual multi-band FS. \n\nOn the other hand, FS calculations in WIEN2k are rather trivial and can be well presented using XCrysDen.152 For a quantitative comparison with experiment, it is highly desirable to calculate the corresponding dHvA frequencies as well as the corresponding effective masses. This can be done conveniently using the SKEAF (Supercell $\\mathbf{k}$ -space Extremal Area Finder) tool.167,280 An application can be found for the determination of transport properties in the HoBi281 compound. \n\n# IV. DISCUSSION AND SUMMARY \n\nIn this paper, we have reviewed the widely used WIEN2k code, which is based on the APW+lo method to solve the KS equations of DFT. Particular emphasis was placed on the various types of basis functions that are available. One of the strengths of the WIEN2k code is the possibility to use an arbitrary number of local orbitals, which allows an accurate calculation of all states, from the low-lying occupied semi-core to the high-lying unoccupied states. For the latter, the use of local orbitals is crucial in order to get converged results for a property that is calculated using perturbation theory such as the NMR chemical shift. \n\nVarious types of approximations for the treatment of XC effects are mentioned, and the large number of functionals that are available constitutes another strength of the WIEN2k code. They range from the semilocal approximations (all the existing ones can be used via the Libxc library) to the more sophisticated approximations such as $\\mathrm{DFT}+U_{:}$ , the hybrids, or functionals specifically developed for van der Waals interactions. In particular, the popular Tran–Blaha mBJ potential is implemented in WIEN2k, which is a cheap but accurate method to calculate bandgaps in solids. Since the WIEN2k code is a full-potential all-electron code, it is, in principle, able to provide the exact result within a chosen XC approximation. Thus, WIEN2k is ideally suited for the testing of XC functionals. \n\nThe structure of the WIEN2k code, as well as the workflow of programs in a SCF calculation, has been described. WIEN2k has also a user-friendly interface that is especially useful for beginners. In principle, an APW-based method needs many specific input parameters (various PW and LM cutoffs and case specific LM expansions and specific $E$ -parameters for each atom and angular momentum), but one of the great strengths of our implementation is that for all these parameters very good defaults are provided automatically to the user so that WIEN2k can also be mastered by non-experts. Of course, an all-electron code cannot be as fast as PW pseudopotential codes, where the extensive use of FFTs speeds up the calculations. Despite this, an APW-based method can be fairly efficient when large atomic spheres can be used because of the relatively fast PW convergence in such cases. It also has a fast and robust method to solve the SCF problem, including a simultaneous optimization of the atomic positions. WIEN2k is a very efficient implementation of the APW $+\\mathrm{lo}$ method from the computational point of view. The code is highly optimized and uses whenever possible efficient numerical libraries (BLAS, LAPACK, and ELPA). It has three different parallelization schemes, which allows us to run the code efficiently on a laptop as well as on a huge high performance computing cluster. \n\nWIEN2k can calculate a large number of different properties. Besides the basic quantities such as the optimized atomic structure, cohesive energy, electronic band structure, or magnetism, numerous more specialized properties are available and can be readily calculated. Among them, those whose corresponding programs or modules are part of the WIEN2k code are, for instance, the optical properties, electric polarization, electric-field gradients, NMR chemical and Knight shifts, or magnetic hyperfine fields. In particular, for the latter two quantities, an all-electron method is mandatory. We also described programs that are not part of the WIEN2k distribution but are compatible with it. This includes, for instance, WIENNCM (non-collinear magnetism), WIENBSE (electron–hole interactions), BoltzTraP2 (thermoelectric transport coefficients), GAP2 (GW), or the various programs that calculate phonons. \n\nThe main advantage of working with an all-electron code such as WIEN2k is the possibility to implement methods for calculating properties exactly. However, implementations within the $\\mathrm{\\APW+lo}$ method are not always straightforward, since the dual basis-set representation, atomic-like functions inside the atomic spheres, and plane waves between the atoms may lead to complicated equations. In addition, the discontinuity of the derivatives of the basis functions at the sphere boundary may require a careful treatment. DFT codes using a basis set consisting only of plane waves or only of localized basis functions (e.g., Gaussian) lead, in principle, to easier implementations. However, once a method has been implemented in the $\\mathrm{\\APW+lo}$ method, it can then be applied to any element of the periodic table, from hydrogen to the actinides, without any restriction, which is the great power of the APW $+\\mathrm{lo}$ method. \n\n# ACKNOWLEDGMENTS \n\nWe would like to thank the current and former colleagues of the WIEN2k group and external collaborators who have contributed to the development of the WIEN2k code (see our website282 or the WIEN2k user’s guide283). We also thank all the users keeping the WIEN2k mailing284 list alive. L.D.M. acknowledges support from the National Science Foundation, USA, under Grant No. DMR-1507101. P.B. acknowledges support from the Austrian Science Foundation (FWF) for Project W1243 (Solids4Fun). \n\n# REFERENCES \n\n1W. J. Hehre, L. Radom, P. von R. Schleyer, and J. Pople, Ab Initio Molecular Orbital Theory (Wiley-VCH, 1986). \n$\\scriptstyle2_{\\mathrm{P}}$ Hohenberg and W. Kohn, Phys. Rev. 136, B864 (1964). \n3W. Kohn and L. J. Sham, Phys. Rev. 140, A1133 (1965). \n$^4\\mathrm{K}.$ Schwarz and P. Blaha, “DFT calculations for real solids,” in Handbook of Solid State Chemistry, Theoretical Description Vol. 5, edited by R. Dronkowski, S. Kikkawa, and A. Stein (Wiley-VCH Verlag, Weinheim, Germany, 2017), Chap. 8, p. 227. \n${\\mathsf{s}}_{\\mathrm{K}}$ Lejaeghere, G. Bihlmayer, T. Björkman, P. Blaha, S. Blügel, V. Blum, D. Caliste, I. E. Castelli, S. J. Clark, A. Dal Corso, S. de Gironcoli, T. Deutsch, J. K. Dewhurst, I. Di Marco, C. Draxl, M. Dułak, O. Eriksson, J. A. Flores-Livas, K. F. Garrity, L. Genovese, P. Giannozzi, M. Giantomassi, S. Goedecker, X. Gonze, O. Grånäs, E. K. U. Gross, A. Gulans, F. Gygi, D. R. Hamann, P. J. Hasnip, N. A. W. Holzwarth, D. Ius¸an, D. B. Jochym, F. Jollet, D. Jones, G. Kresse, K. Koepernik, E. Küçükbenli, Y. O. Kvashnin, I. L. M. Locht, S. Lubeck, M. Marsman, N. Marzari, U. Nitzsche, L. Nordström, T. Ozaki, L. Paulatto, C. J. Pickard, W. Poelmans, M. I. J. Probert, K. Refson, M. Richter, G.-M. Rignanese, S. Saha, M. Scheffler, M. Schlipf, K. Schwarz, S. Sharma, F. Tavazza, P. Thunström, A. Tkatchenko, M. Torrent, D. Vanderbilt, M. J. van Setten, V. Van Speybroeck, J. M. Wills, J. R. Yates, G.-X. Zhang, and S. Cottenier, Science 351, aad3000 (2016). \n$^6\\mathrm{P}$ . Blaha, K. Schwarz, G. K. H. Madsen, D. Kvasnicka, J. Luitz, R. Laskowski, F. Tran, and L. D. Marks, WIEN2k: An Augmented Plane Wave Plus Local Orbitals Program for Calculating Crystal Properties (Vienna University of Technology, Austria, 2018). \n7D. J. Singh and L. Nordström, Planewaves, Pseudopotentials, and the LAPW Method, 2nd ed. (Springer, New York, 2006). 8K. Schwarz, P. Blaha, and S. B. Trickey, Mol. Phys. 108, 3147 (2010). \n9J. C. Slater, Phys. Rev. 51, 846 (1937). \n10O. K. Andersen, Phys. Rev. B 12, 3060 (1975). \n11D. D. Koelling and G. O. Arbman, J. Phys. F: Met. Phys. 5, 2041 (1975). \n12M. Weinert, J. Math. Phys. 22, 2433 (1981). \n13E. Wimmer, H. Krakauer, M. Weinert, and A. J. Freeman, Phys. Rev. B 24, 864 (1981). \n$^{14}\\mathrm{P}$ . Blaha, K. Schwarz, P. Sorantin, and S. B. Trickey, Comput. Phys. Commun. 59, 399 (1990). \n15D. Singh, Phys. Rev. B 43, 6388 (1991). \n16E. Sjöstedt, L. Nordström, and D. J. Singh, Solid State Commun. 114, 15 (2000). 17G. K. H. Madsen, P. Blaha, K. Schwarz, E. Sjöstedt, and L. Nordström, Phys. Rev. B 64, 195134 (2001). \n$^{18}\\mathrm{G}.$ Michalicek, M. Betzinger, C. Friedrich, and S. Blügel, Comput. Phys. Commun. 184, 2670 (2013). \n${}^{19}\\mathrm{F}.$ Karsai, F. Tran, and P. Blaha, Comput. Phys. Commun. 220, 230 (2017). ${}^{20}\\mathrm{K}.$ Schwarz, “Computation of materials properties at the atomic scale,” in Selected Topics in Application of Quantum Mechanics, edited by M. R. Pahlavani (InTechOpen, 2015), Chap. 10, p. 275. \n$^{21}\\mathrm{K}.$ Schwarz, P. Blaha, and G. K. H. Madsen, Comput. Phys. Commun. 147, 71 (2002). \n$^{22}\\mathrm{K}.$ Schwarz, J. Solid State Chem. 176, 319 (2003). \n${}^{23}\\mathrm{K}.$ Schwarz and P. Blaha, Comput. Mater. Sci. 28, 259 (2003). \n$^{24}\\mathrm{M}.$ . Kara and K. Kurki-Suonio, Acta Crystallogr., Sect. A 37, 201 (1981). 25D. D. Koelling and B. N. Harmon, J. Phys. C: Solid State Phys. 10, 3107 (1977). 26A. H. MacDonald, W. E. Pickett, and D. D. Koelling, J. Phys. C: Solid State Phys. 13, 2675 (1980). \n$^{27}]$ J. Kuneš, P. Novák, R. Schmid, P. Blaha, and K. Schwarz, Phys. Rev. B 64, 153102 (2001). \n$^{28}\\mathrm{P}.$ Blaha, D. J. Singh, P. I. Sorantin, and K. Schwarz, Phys. Rev. B 46, 1321 (1992). 29A. Seidl, A. Görling, P. Vogl, J. A. Majewski, and M. Levy, Phys. Rev. B 53, 3764 (1996). \n30A. J. Cohen, P. Mori-Sánchez, and W. Yang, Chem. Rev. 112, 289 (2012). $^{31}\\mathrm{K}.$ Burke, J. Chem. Phys. 136, 150901 (2012). \n32A. D. Becke, J. Chem. Phys. 140, 18A301 (2014). \n$^{33}\\mathrm{M}$ . A. L. Marques, M. J. T. Oliveira, and T. Burnus, Comput. Phys. Commun. 183, 2272 (2012). \n$^{34}\\mathrm{S}.$ . Lehtola, C. Steigemann, M. J. T. Oliveira, and M. A. L. Marques, SoftwareX 7, 1 (2018). \n35J. P. Perdew and K. Schmidt, AIP Conf. Proc. 577, 1 (2001). \n$^{36}\\mathrm{F}.$ . Tran, R. Laskowski, P. Blaha, and K. Schwarz, Phys. Rev. B 75, 115131 (2007). 37P. Haas, F. Tran, and P. Blaha, Phys. Rev. B 79, 085104 (2009); 79, 209902(E) (2009). \n38P. Haas, F. Tran, P. Blaha, L. S. Pedroza, A. J. R. da Silva, M. M. Odashima, and K. Capelle, Phys. Rev. B 81, 125136 (2010). \n${}^{39}\\mathrm{F}.$ Tran, J. Stelzl, and P. Blaha, J. Chem. Phys. 144, 204120 (2016). \n40A. E. Mattsson, R. Armiento, J. Paier, G. Kresse, J. M. Wills, and T. R. Mattsson, J. Chem. Phys. 128, 084714 (2008). \n41G.-X. Zhang, A. M. Reilly, A. Tkatchenko, and M. Scheffler, New J. Phys. 20, 063020 (2018). \n$^{42}\\mathrm{R}.$ . Armiento and A. E. Mattsson, Phys. Rev. B 72, 085108 (2005). \n43J. P. Perdew, A. Ruzsinszky, G. I. Csonka, O. A. Vydrov, G. E. Scuseria, L. A. Constantin, X. Zhou, and K. Burke, Phys. Rev. Lett. 100, 136406 (2008); 102, 039902(E) (2009). \n$^{44}\\mathrm{Z}$ . Wu and R. E. Cohen, Phys. Rev. B 73, 235116 (2006). \n45G. K. H. Madsen, Phys. Rev. B 75, 195108 (2007). \n46Y. Zhao and D. G. Truhlar, J. Chem. Phys. 128, 184109 (2008). \n47J. P. Perdew, K. Burke, and M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996); 78, 1396(E) (1997). \n48J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015). 49E. B. Isaacs and C. Wolverton, Phys. Rev. Mater. 2, 063801 (2018). \n50Y. Fu and D. J. Singh, Phys. Rev. Lett. 121, 207201 (2018). 51P. Kovács, F. Tran, P. Blaha, and G. K. H. Madsen, J. Chem. Phys. 150, 164119 (2019). \n52A. D. Becke, J. Chem. Phys. 98, 5648 (1993). \n53T. Bredow and A. R. Gerson, Phys. Rev. B 61, 5194 (2000). \n54J. K. Perry, J. Tahir-Kheli, and W. A. Goddard III, Phys. Rev. B 63, 144510 (2001). \n55J. Muscat, A. Wander, and N. M. Harrison, Chem. Phys. Lett. 342, 397 (2001). 56J. Heyd, G. E. Scuseria, and M. Ernzerhof, J. Chem. Phys. 118, 8207 (2003); 124, 219906 (2006). \n57J. Heyd, J. E. Peralta, G. E. Scuseria, and R. L. Martin, J. Chem. Phys. 123, 174101 (2005). \n58A. V. Krukau, O. A. Vydrov, A. F. Izmaylov, and G. E. Scuseria, J. Chem. Phys. 125, 224106 (2006). \n$^{59}\\mathrm{M}$ . Ernzerhof and G. E. Scuseria, J. Chem. Phys. 110, 5029 (1999). \n$^{60}\\mathrm{C}$ . Adamo and V. Barone, J. Chem. Phys. 110, 6158 (1999). \n61D. M. Bylander and L. Kleinman, Phys. Rev. B 41, 7868 (1990). \n$^{62}\\mathrm{J}$ . M. Crowley, J. Tahir-Kheli, and W. A. Goddard III, J. Phys. Chem. Lett. 7, 1198 (2016). \n63A. J. Garza and G. E. Scuseria, J. Phys. Chem. Lett. 7, 4165 (2016). \n64F. Tran and P. Blaha, J. Phys. Chem. A 121, 3318 (2017). \n$^{65}\\mathrm{P}$ . Borlido, T. Aull, A. W. Huran, F. Tran, M. A. L. Marques, and S. Botti, J. Chem. Theory Comput. 15, 5069 (2019). \n${}^{66}\\mathrm{F}.$ . Tran and P. Blaha, Phys. Rev. B 83, 235118 (2011). \n67S. Massidda, M. Posternak, and A. Baldereschi, Phys. Rev. B 48, 5058 (1993). 68J. Spencer and A. Alavi, Phys. Rev. B 77, 193110 (2008). \n${}^{69}\\mathrm{R}.$ . Sundararaman and T. A. Arias, Phys. Rev. B 87, 165122 (2013). \n70T. Shimazaki and Y. Asai, Chem. Phys. Lett. 466, 91 (2008). \n71J. Paier, M. Marsman, K. Hummer, G. Kresse, I. C. Gerber, and J. G. Ángyán, J. Chem. Phys. 124, 154709 (2006); 125, 249901 (2006). \n72A. Alkauskas and A. Pasquarello, Physica B 401-402, 670 (2007). \n73F. Tran, Phys. Lett. A 376, 879 (2012). \n74A. S. Botana, F. Tran, V. Pardo, D. Baldomir, and P. Blaha, Phys. Rev. B 85, 235118 (2012). \n$^{75}\\mathrm{F}.$ . Tran, D. Koller, and P. Blaha, Phys. Rev. B 86, 134406 (2012). \n76F. Karsai, P. Tiwald, R. Laskowski, F. Tran, D. Koller, S. Gräfe, J. Burgdörfer, L. Wirtz, and P. Blaha, Phys. Rev. B 89, 125429 (2014). \n77F. Tran, F. Karsai, and P. Blaha, Phys. Rev. B 89, 155106 (2014). \n$^{78}\\mathrm{R}.$ Laskowski, P. Blaha, and F. Tran, Phys. Rev. B 87, 195130 (2013). \n79D. Koller, P. Blaha, and F. Tran, J. Phys.: Condens. Matter 25, 435503 (2013). 80F. Tran, S. Ehsan, and P. Blaha, Phys. Rev. Mater. 2, 023802 (2018). \n81V. I. Anisimov, J. Zaanen, and O. K. Andersen, Phys. Rev. B 44, 943 (1991). 82P. Novák, J. Kuneš, L. Chaput, and W. E. Pickett, Phys. Status Solidi B 243, 563 (2006). \n$^{83}\\mathrm{F}.$ . Tran, P. Blaha, K. Schwarz, and P. Novák, Phys. Rev. B 74, 155108 (2006). $^{84}\\mathrm{K}.$ Terakura, T. Oguchi, A. R. Williams, and J. Kübler, Phys. Rev. B 30, 4734 (1984). \n85V. I. Anisimov, I. V. Solovyev, M. A. Korotin, M. T. Czyz˙yk, and G. A. Sawatzky, Phys. Rev. B 48, 16929 (1993). \n$^{86}\\mathrm{M}.$ . T. Czyz˙yk and G. A. Sawatzky, Phys. Rev. B 49, 14211 (1994). \n87A. B. Shick, A. I. Liechtenstein, and W. E. Pickett, Phys. Rev. B 60, 10763 (1999). 88E. R. Ylvisaker, W. E. Pickett, and K. Koepernik, Phys. Rev. B 79, 035103 (2009). ${}^{89}\\mathrm{K}.$ Nawa, T. Akiyama, T. Ito, K. Nakamura, T. Oguchi, and M. Weinert, Phys. Rev. B 97, 035117 (2018). \n$^{90}\\mathrm{Y}.$ .-C. Wang and H. Jiang, J. Chem. Phys. 150, 154116 (2019). \n$^{91}\\mathrm{R}.$ . Laskowski, G. K. H. Madsen, P. Blaha, and K. Schwarz, Phys. Rev. B 69, 140408(R) (2004). \n$^{\\mathfrak{s}_{2}}\\mathrm{P}$ . Blaha, K. Schwarz, and P. Novák, Int. J. Quantum Chem. 101, 550 (2005). 93F. Tran, J. Schweifer, P. Blaha, K. Schwarz, and P. Novák, Phys. Rev. B 77, 085123 (2008). \n$^{94}\\mathrm{L}$ . D. Marks, A. N. Chiaramonti, F. Tran, and P. Blaha, Surf. Sci. 603, 2179 (2009). \n${}^{95}\\mathrm{R}.$ Atta-Fynn and A. K. Ray, Europhys. Lett. 85, 27008 (2009). ${}^{96}\\mathrm{X}$ . Rocquefelte, M.-H. Whangbo, A. Villesuzanne, S. Jobic, F. Tran, K. Schwarz, and P. Blaha, J. Phys.: Condens. Matter 22, 045502 (2010). \n$^{97}\\mathrm{Y}$ . Lin, J. Wen, L. Hu, R. M. Kennedy, P. C. Stair, K. R. Poeppelmeier, and L. D. Marks, Phys. Rev. Lett. 111, 156101 (2013). \n$^{98}\\mathrm{Q}$ . C. Sherman, P. W. Voorhees, and L. D. Marks, Acta Mater. 181, 584 (2019). 99D. Torumba, P. Novák, and S. Cottenier, Phys. Rev. B 77, 155101 (2008). $^{100}\\mathrm{F}.$ Jollet, G. Jomard, B. Amadon, J. P. Crocombette, and D. Torumba, Phys. Rev. B 80, 235109 (2009). \n101C. A. Mizzi, P. Koirala, and L. D. Marks, Phys. Rev. Mater. 2, 025001 (2018). 102L. Hedin, Phys. Rev. 139, A796 (1965). \n103M. S. Hybertsen and S. G. Louie, Phys. Rev. B 34, 5390 (1986). \n104F. Tran, J. Doumont, L. Kalantari, A. W. Huran, M. A. L. Marques, and P. Blaha, J. Appl. Phys. 126, 110902 (2019). \n$^{105}\\mathrm{F}$ . Tran and P. Blaha, Phys. Rev. Lett. 102, 226401 (2009). \n106A. D. Becke and E. R. Johnson, J. Chem. Phys. 124, 221101 (2006). \n107F. Tran, P. Blaha, M. Betzinger, and S. Blügel, Phys. Rev. B 91, 165121 (2015). 108J. P. Perdew and Y. Wang, Phys. Rev. B 45, 13244 (1992); 98, 079904(E) (2018). 109A. D. Becke and M. R. Roussel, Phys. Rev. A 39, 3761 (1989). \n110D. Koller, F. Tran, and P. Blaha, Phys. Rev. B 85, 155109 (2012). \n111R. A. Jishi, O. B. Ta, and A. A. Sharif, J. Phys. Chem. C 118, 28344 (2014). $^{112}\\mathrm{O}$ . Gritsenko, R. van Leeuwen, E. van Lenthe, and E. J. Baerends, Phys. Rev. A 51, 1944 (1995). \n$^{113}\\mathrm{{M}}$ . Kuisma, J. Ojanen, J. Enkovaara, and T. T. Rantala, Phys. Rev. B 82, 115106 (2010). \n114J. P. Perdew, R. G. Parr, M. Levy, and J. L. Balduz, Jr., Phys. Rev. Lett. 49, 1691 (1982). \n$^{115}\\mathrm{L}.$ J. Sham and M. Schlüter, Phys. Rev. Lett. 51, 1888 (1983). \n116E. J. Baerends, Phys. Chem. Chem. Phys. 19, 15639 (2017). \n117I. E. Castelli, T. Olsen, S. Datta, D. D. Landis, S. Dahl, K. S. Thygesen, and K. W. Jacobsen, Energy Environ. Sci. 5, 5814 (2012). \n118E. Engel and S. H. Vosko, Phys. Rev. B 47, 13164 (1993). \n119J. P. Perdew, J. A. Chevary, S. H. Vosko, K. A. Jackson, M. R. Pederson, D. J. Singh, and C. Fiolhais, Phys. Rev. B 46, 6671 (1992); 48, 4978(E) (1993). $\\ensuremath{^120}{}_{\\mathrm{R}}$ . Armiento and S. Kümmel, Phys. Rev. Lett. 111, 036402 (2013). \n121V. Vlcˇek, G. Steinle-Neumann, L. Leppert, R. Armiento, and S. Kümmel, Phys. Rev. B 91, 035107 (2015). \n$^{122}\\mathrm{P}$ Verma and D. G. Truhlar, J. Phys. Chem. Lett. 8, 380 (2017). \n$^{123}\\mathrm{K}$ . Finzel and A. I. Baranov, Int. J. Quantum Chem. 117, 40 (2017). \n$^{124}\\mathrm{F}.$ Tran, J. Doumont, P. Blaha, M. A. L. Marques, S. Botti, and A. P. Bartók, J. Chem. Phys. 151, 161102 (2019). \n$\\boldsymbol{^{125}\\mathrm{{P}}}.$ Verma and D. G. Truhlar, J. Phys. Chem. C 121, 7144 (2017). \n$^{126}\\mathrm{T}$ . Aschebrock and S. Kümmel, Phys. Rev. Res. 1, 033082 (2019). \n${}^{127}\\mathrm{J}$ . C. Slater, Phys. Rev. 81, 385 (1951). \n128J. B. Krieger, Y. Li, and G. J. Iafrate, Phys. Rev. A 46, 5453 (1992). \n129F. Tran, P. Blaha, and K. Schwarz, J. Chem. Theory Comput. 11, 4717 (2015). 130F. Tran, P. Blaha, M. Betzinger, and S. Blügel, Phys. Rev. B 94, 165149 (2016). 131K. Berland, V. R. Cooper, K. Lee, E. Schröder, T. Thonhauser, P. Hyldgaard, and B. I. Lundqvist, Rep. Prog. Phys. 78, 066501 (2015). \n$^{132}\\mathrm{J}$ . Hermann, R. A. DiStasio, Jr., and A. Tkatchenko, Chem. Rev. 117, 4714 (2017). \n$^{133}\\mathrm{S}.$ Grimme, J. Comput. Chem. 27, 1787 (2006). \n$^{134}\\mathrm{S}.$ . Grimme, J. Antony, S. Ehrlich, and H. Krieg, J. Chem. Phys. 132, 154104 (2010). \n135See https://www.chemie.uni-bonn.de/pctc/mulliken-center/software/dft-d3/ dft-d3 for information about DFT-D3. \n$^{136}\\mathrm{J}$ . Moellmann and S. Grimme, J. Phys. Chem. C 118, 7615 (2014). \n$^{137}\\mathrm{{M}}$ . Dion, H. Rydberg, E. Schröder, D. C. Langreth, and B. I. Lundqvist, Phys. Rev. Lett. 92, 246401 (2004); 95, 109902(E) (2005). \n138G. Román-Pérez and J. M. Soler, Phys. Rev. Lett. 103, 096102 (2009). \n139F. Tran, J. Stelzl, D. Koller, T. Ruh, and P. Blaha, Phys. Rev. B 96, 054103 (2017). 140F. Tran, L. Kalantari, B. Traoré, X. Rocquefelte, and P. Blaha, Phys. Rev. Mater. 3, 063602 (2019). 141S. Grimme, S. Ehrlich, and L. Goerigk, J. Comput. Chem. 32, 1456 (2011). 142I. Hamada, Phys. Rev. B 89, 121103(R) (2014); 91, 119902(E) (2015). \n$^{143}\\mathrm{M}.$ . Weinert, E. Wimmer, and A. J. Freeman, Phys. Rev. B 26, 4571 (1982). 144P. Pulay, Mol. Phys. 17, 197 (1969). \n145R. Yu, D. Singh, and H. Krakauer, Phys. Rev. B 43, 6411 (1991). \n146B. Kohler, S. Wilke, M. Scheffler, R. Kouba, and C. Ambrosch-Draxl, Comput. Phys. Commun. 94, 31 (1996). \n147F. Tran, J. Kuneš, P. Novák, P. Blaha, L. D. Marks, and K. Schwarz, Comput. Phys. Commun. 179, 784 (2008). \n148L. D. Marks and D. R. Luke, Phys. Rev. B 78, 075114 (2008). \n149L. D. Marks, J. Chem. Theory Comput. 9, 2786 (2013). \n150L. D. Marks, “Hands-free DFT mixing” (unpublished). \n151R. Car and M. Parrinello, Phys. Rev. Lett. 55, 2471 (1985). \n152A. Kokalj, Comput. Mater. Sci. 28, 155 (2003). \n153K. Momma and F. Izumi, J. Appl. Crystallogr. 44, 1272 (2011). \n154See http://www.fftw.org for information about FFTW. \n155See https://elpa.mpcdf.mpg.de for information about ELPA. \n156A. Marek, V. Blum, R. Johanni, V. Havu, B. Lang, T. Auckenthaler, A. Heinecke, H.-J. Bungartz, and H. Lederer, J. Phys.: Condens. Matter 26, 213201 (2014). \n157See http://www.wannier.org for information about Wannier90. \n158G. Pizzi, V. Vitale, R. Arita, S. Blügel, F. Freimuth, G. Géranton, M. Gibertini, D. Gresch, C. Johnson, T. Koretsune, J. Ibañez-Azpiroz, H. Lee, J.-M. Lihm, D. Marchand, A. Marrazzo, Y. Mokrousov, J. I. Mustafa, Y. Nohara, Y. Nomura, L. Paulatto, S. Poncé, T. Ponweiser, J. Qiao, F. Thöle, S. S. Tsirkin, M. Wierzbowska, N. Marzari, D. Vanderbilt, I. Souza, A. A. Mostofi, and J. R. Yates, J. Phys.: Condens. Matter 32, 165902 (2020). \n159See https://atztogo.github.io/phonopy/ for information about phonopy. 160A. Togo and I. Tanaka, Scr. Mater. 108, 1 (2015). \n161See http://www.computingformaterials.com for information about Phonon. 162K. Parlinski, Z. Q. Li, and Y. Kawazoe, Phys. Rev. Lett. 78, 4063 (1997). 163D. Alfè, Comput. Phys. Commun. 180, 2622 (2009). \n164See http://www.homepages.ucl.ac.uk/∼ucfbdxa/phon/ for information about PHON. \n165G. K. H. Madsen, J. Carrete, and M. J. Verstraete, Comput. Phys. Commun. 231, 140 (2018). \n166See https://github.com/rubel75/fold2Bloch-Wien2k/ for information about fold2Bloch. \n167See http://www.wien2k.at/reg_user/unsupported/ for information about SKEAF. \n168A. Otero-de-la-Roza, M. A. Blanco, A. Martín Pendás, and V. Luaña, Comput. Phys. Commun. 180, 157 (2009). \n169A. Otero-de-la-Roza, E. R. Johnson, and V. Luaña, Comput. Phys. Commun. 185, 1007 (2014). \n170See https://www.chemistry.mcmaster.ca/bader/aim/ for the AIM theory of Bader. 171R. F. W. Bader, Atoms in Molecules: A Quantum Theory (Oxford University Press, New York, 1994). \n$^{172}\\mathrm{R}.$ Laskowski, P. Blaha, T. Gallauner, and K. Schwarz, Phys. Rev. Lett. 98, 106802 (2007). \n${}^{173}\\mathrm{R}.$ Laskowski and P. Blaha, Phys. Rev. B 81, 075418 (2010). \n174H. P. Koch, R. Laskowski, P. Blaha, and K. Schwarz, Phys. Rev. B 86, 155404 (2012). \n$^{175}\\mathrm{P}.$ Blaha, H. Hofstätter, O. Koch, R. Laskowski, and K. Schwarz, J. Comput. 176See http://www.cryst.ehu.es for the Bilbao Crystallographic Server. \n177S. Ouardi, G. H. Fecher, C. Felser, M. Schwall, S. S. Naghavi, A. Gloskovskii, B. Balke, J. Hamrle, K. Postava, J. Pištora, S. Ueda, and K. Kobayashi, Phys. Rev. B 86, 045116 (2012). \n178P. E. Blöchl, O. Jepsen, and O. K. Andersen, Phys. Rev. B 49, 16223 (1994). $^{179}\\mathrm{M}.$ . Bagheri and P. Blaha, J. Electron Spectrosc. Relat. Phenom. 230, 1 (2019). $^{180}\\mathrm{M}.$ . B. Trzhaskovskaya, V. I. Nefedov, and V. G. Yarzhemsky, At. Data Nucl. Data Tables 77, 97 (2001). 181M. B. Trzhaskovskaya, V. K. Nikulin, V. I. Nefedov, and V. G. Yarzhemsky, At. Data Nucl. Data Tables 92, 245 (2006). \n$^{182}]$ J. F. Janak, Phys. Rev. B 18, 7165 (1978). \n$^{183}]$ J. C. Slater, J. B. Mann, T. M. Wilson, and J. H. Wood, Phys. Rev. 184, 672 (1969). \n$^{184}\\mathrm{M}$ . V. Ganduglia-Pirovano, M. Scheffler, A. Baraldi, S. Lizzit, G. Comelli, G. Paolucci, and R. Rosei, Phys. Rev. B 63, 205415 (2001). \n$^{185}\\mathrm{E}$ Kabliman, P. Blaha, and K. Schwarz, Phys. Rev. B 82, 125308 (2010). 186P. S. Bagus, C. J. Nelin, X. Zhao, S. V. Levchenko, E. Davis, X. Weng, F. Späth, C. Papp, H. Kuhlenbeck, and H.-J. Freund, Phys. Rev. B 100, 115419 (2019). 187G. B. Grad, P. Blaha, K. Schwarz, W. Auwärter, and T. Greber, Phys. Rev. B 68, 085404 (2003). \n$^{188}\\mathrm{H}$ . Dil, J. Lobo-Checa, R. Laskowski, P. Blaha, S. Berner, J. Osterwalder, and T. Greber, Science 319, 1824 (2008). \n${}^{189}\\mathrm{R}.$ Laskowski, T. Gallauner, P. Blaha, and K. Schwarz, J. Phys.: Condens. Matter 21, 104210 (2009). \n$^{190}\\mathrm{U}$ . von Barth and G. Grossmann, Solid State Commun. 32, 645 (1979). 191C. Cocchi, S. Mistry, M. Schmeißer, J. Kühn, and T. Kamps, J. Phys.: Condens. Matter 31, 014002 (2019). \n$\\boldsymbol{^{192}}\\boldsymbol{\\mathrm{J}}$ . Luitz, M. Maier, C. Hébert, P. Schattschneider, P. Blaha, K. Schwarz, and B. Jouffrey, Eur. Phys. J. B 21, 363 (2001). \n193T. Mizoguchi, I. Tanaka, S. Yoshioka, M. Kunisu, T. Yamamoto, and W. Ching, Phys. Rev. B 70, 045103 (2004). \n194W. Hetaba, P. Blaha, F. Tran, and P. Schattschneider, Phys. Rev. B 85, 205108 (2012). \n$^{195}\\mathrm{H}$ . Ikeno, F. M. F. de Groot, E. Stavitski, and I. Tanaka, J. Phys.: Condens. Matter 21, 104208 (2009). \n196R. Laskowski and P. Blaha, Phys. Rev. B 82, 205104 (2010). \n$^{197}\\mathrm{F}.$ Karsai, M. Humer, E. Flage-Larsen, P. Blaha, and G. Kresse, Phys. Rev. B 98, 235205 (2018). \n$^{198}\\mathrm{{M}}$ . Nelhiebel, P.-H. Louf, P. Schattschneider, P. Blaha, K. Schwarz, and B. Jouffrey, Phys. Rev. B 59, 12807 (1999). \n$^{199}\\mathrm{P}$ Schattschneider, C. Hébert, H. Franco, and B. Jouffrey, Phys. Rev. B 72, 045142 (2005). \n$^{200}\\mathrm{C}.$ Hébert, Micron 38, 12 (2007). \n201C. Hébert-Souche, P.-H. Louf, M. Nelhiebel, J. Luitz, P. Schattschneider, K. Schwarz, and B. Jouffrey, Ultramicroscopy 83, 9 (2000). \n$^{202}\\mathrm{C}$ . Hébert, J. Luitz, and P. Schattschneider, Micron 34, 219 (2003). \n${}^{203}\\mathrm{K}.$ S. Virdi, Y. Kauffmann, C. Ziegler, P. Ganter, B. V. Lotsch, W. D. Kaplan, $204$ W. Khan, S. B. Betzler, O. Šipr, J. Ciston, P. Blaha, C. Scheu, and J. Minar, J. Phys. Chem. C 120, 23329 (2016). \n$^{205}\\mathrm{C}$ . Ambrosch-Draxl and J. O. Sofo, Comput. Phys. Commun. 175, 1 (2006). $^{206}\\mathrm{S}.$ . A. Khan, P. Blaha, H. Ebert, J. Minár, and O. Šipr, Phys. Rev. B 94, 144436 (2016). \n${}^{207}\\mathrm{C}$ . Spiel, P. Blaha, and K. Schwarz, Phys. Rev. B 79, 115123 (2009). \n$^{208}\\mathrm{K}$ . Schwarz and P. Blaha, “Electronic structure of solids and surfaces with WIEN2k,” in Practical Aspects of Computational Chemistry I: An Overview of the Last Two Decades and Current Trends, edited by J. Leszczyncski and M. K. Shukla (Springer Science+Business Media B.V., Berlin, Heidelberg, 2012), Vol. 7, p. 191. $^{209}\\mathrm{C}$ . H. Gardiner, A. T. Boothroyd, P. Pattison, M. J. McKelvy, G. J. McIntyre, and S. J. S. Lister, Phys. Rev. B 70, 024415 (2004). \n${}^{210}\\mathrm{A}.$ R. Williams, V. L. Moruzzi, J. Kübler, and K. Schwarz, Bull. Am. Phys. Soc. 29, 278 (1984). \n$^{211}\\mathrm{K}$ . Schwarz and P. Mohn, J. Phys. F: Met. Phys. 14, L129 (1984). \n212R. Sternheimer, Phys. Rev. 80, 102 (1950). \n213P. Blaha, K. Schwarz, and P. Herzig, Phys. Rev. Lett. 54, 1192 (1985). \n$^{214}\\mathrm{K}.$ Schwarz, C. Ambrosch-Draxl, and P. Blaha, Phys. Rev. B 42, 2051 (1990). $^{215}\\mathrm{{M}}$ . Body, C. Legein, J.-Y. Buzaré, G. Silly, P. Blaha, C. Martineau, and F. Calvayrac, J. Phys. Chem. A 111, 11873 (2007). \n$^{216}\\mathrm{P}$ Dufek, P. Blaha, and K. Schwarz, Phys. Rev. Lett. 75, 3545 (1995). \n$^{217}\\mathrm{R}.$ . Laskowski and P. Blaha, Phys. Rev. B 85, 035132 (2012). \n$^{218}\\mathrm{R}.$ Laskowski and P. Blaha, Phys. Rev. B 89, 014402 (2014). $^{219}\\mathrm{R}.$ Laskowski and P. Blaha, J. Phys. Chem. C 119, 19390 (2015). \n${}^{220}\\mathrm{R}.$ Laskowski and P. Blaha, J. Phys. Chem. C 119, 731 (2015). \n$^{221}\\mathrm{R}.$ Laskowski and P. Blaha, Phys. Rev. B 85, 245117 (2012). \n$^{222}\\mathrm{R}.$ Laskowski, K. H. Khoo, F. Haarmann, and P. Blaha, J. Phys. Chem. C 121, 753 (2017). \n$^{223}\\mathrm{K}.$ H. Khoo, R. Laskowski, and P. Blaha, J. Phys. Chem. C 121, 12398 (2017). $^{224}\\mathrm{L}$ . Kalantari, P. Blaha, K. H. Khoo, and R. Laskowski, J. Phys. Chem. C 121, 28454 (2017). \n$^{225}\\mathrm{G}$ . A. de Wijs, R. Laskowski, P. Blaha, R. W. A. Havenith, G. Kresse, and M. Marsman, J. Chem. Phys. 146, 064115 (2017). \n$^{226}\\mathrm{F}.$ Mauri, B. G. Pfrommer, and S. G. Louie, Phys. Rev. Lett. 77, 5300 (1996). 227C. J. Pickard and F. Mauri, Phys. Rev. B 63, 245101 (2001). \n228J. R. Yates, C. J. Pickard, and F. Mauri, Phys. Rev. B 76, 024401 (2007). 229M. d’Avezac, N. Marzari, and F. Mauri, Phys. Rev. B 76, 165122 (2007). $^{230}\\mathrm{S}.$ . Blügel, H. Akai, R. Zeller, and P. H. Dederichs, Phys. Rev. B 35, 3271 (1987). \n231A. A. Mostofi, J. R. Yates, Y.-S. Lee, I. Souza, D. Vanderbilt, and N. Marzari, Comput. Phys. Commun. 178, 685 (2008). \n232J. Kuneš, R. Arita, P. Wissgott, A. Toschi, H. Ikeda, and K. Held, Comput. Phys. Commun. 181, 1888 (2010). \n$^{233}\\mathrm{G}$ . Kotliar, S. Y. Savrasov, K. Haule, V. S. Oudovenko, O. Parcollet, and C. A. Marianetti, Rev. Mod. Phys. 78, 865 (2006). \n$^{234}\\mathrm{K}$ . Held, Adv. Phys. 56, 829 (2007). \n$^{235}\\mathrm{S}.$ J. Ahmed, J. Kivinen, B. Zaporzan, L. Curiel, S. Pichardo, and O. Rubel, Comput. Phys. Commun. 184, 647 (2013). \n$^{236}\\mathrm{R}.$ D. King-Smith and D. Vanderbilt, Phys. Rev. B 47, 1651(R) (1993). \n$^{237}\\mathrm{H}$ . Weng, C. Fang, Z. Fang, B. A. Bernevig, and X. Dai, Phys. Rev. X 5, 011029 (2015). \n238D. D. Koelling and J. H. Wood, J. Comput. Phys. 67, 253 (1986). \n239W. E. Pickett, H. Krakauer, and P. B. Allen, Phys. Rev. B 38, 2721 (1988). $^{240}\\mathrm{S}.$ . Bhattacharya and G. K. H. Madsen, J. Mater. Chem. C 4, 11261 (2016). 241H. Yamagami, Phys. Rev. B 61, 6246 (2000). \n242P. Kurz, F. Förster, L. Nordström, G. Bihlmayer, and S. Blügel, Phys. Rev. B 69, 024415 (2004). \n243P. Kurz, G. Bihlmayer, S. Blügel, K. Hirai, and T. Asada, Phys. Rev. B 63, 096401 (2001). \n$^{244}\\mathrm{L}$ . M. Sandratskii, Adv. Phys. 47, 91 (1998). \n$245$ J. Kuneš and R. Laskowski, Phys. Rev. B 70, 174415 (2004). \n$^{246}\\mathrm{S}$ . Albrecht, L. Reining, R. Del Sole, and G. Onida, Phys. Rev. Lett. 80, 4510 (1998). \n${^{247}\\mathrm{L}}$ . X. Benedict, E. L. Shirley, and R. B. Bohn, Phys. Rev. Lett. 80, 4514 (1998). \n$^{248}\\mathrm{M}$ . Rohlfing and S. G. Louie, Phys. Rev. Lett. 81, 2312 (1998). \n249G. Strinati, Phys. Rev. Lett. 49, 1519 (1982). \n${}^{250}\\mathrm{G}$ . Strinati, Phys. Rev. B 29, 5718 (1984). \n251M. Rohlfing and S. G. Louie, Phys. Rev. B 62, 4927 (2000). \n$^{252}\\mathrm{R}.$ Laskowski and N. E. Christensen, Phys. Rev. B 73, 045201 (2006). \n$^{253}\\mathrm{R}.$ Laskowski and N. E. Christensen, Phys. Rev. B 74, 075203 (2006). \n$^{254}\\mathrm{R}.$ Laskowski, N. E. Christensen, G. Santi, and C. Ambrosch-Draxl, Phys. Rev. B 72, 035204 (2005). \n${^{255}\\mathrm{T}}$ . Das, X. Rocquefelte, R. Laskowski, L. Lajaunie, S. Jobic, P. Blaha, and K. Schwarz, Chem. Mater. 29, 3380 (2017). \n$^{256}\\mathrm{P}.$ Tiwald, F. Karsai, R. Laskowski, S. Gräfe, P. Blaha, J. Burgdörfer, and L. Wirtz, Phys. Rev. B 92, 144107 (2015). \n257See http://www.chem.pku.edu.cn/jianghgroup/codes/gap2.html for information about GAP2. \n$^{258}\\mathrm{H}$ . Jiang, R. I. Gómez-Abal, X.-Z. Li, C. Meisenbichler, C. Ambrosch-Draxl, and M. Scheffler, Comput. Phys. Commun. 184, 348 (2013). \n${}^{259}\\mathrm{H}$ . Jiang and P. Blaha, Phys. Rev. B 93, 115203 (2016). \n$^{260}\\mathrm{H}$ . Jiang, Phys. Rev. B 97, 245132 (2018). \n${}^{261}\\mathrm{H}$ . Jiang, R. I. Gomez-Abal, P. Rinke, and M. Scheffler, Phys. Rev. Lett. 102, 126403 (2009). ${^{262}\\mathrm{H}}.$ . Jiang, R. I. Gomez-Abal, P. Rinke, and M. Scheffler, Phys. Rev. B 82, 045108 (2010). \n$^{263}\\mathrm{S}.$ K. Panda, H. Jiang, and S. Biermann, Phys. Rev. B 96, 045137 (2017). 264M. Wallerberger, A. Hausoel, P. Gunacker, A. Kowalski, N. Parragh, F. Goth, K. Held, and G. Sangiovanni, Comput. Phys. Commun. 235, 388 (2019). \n265See https://github.com/w2dynamics/w2dynamics for information about w2dynamics. \n$^{266}\\mathrm{\\dot{O}}$ . Parcollet, M. Ferrero, T. Ayral, H. Hafermann, I. Krivenko, L. Messio, and P. Seth, Comput. Phys. Commun. 196, 398 (2015). \n267See https://triqs.github.io/triqs/latest for information about TRIQS. \n268K. Haule, C.-H. Yee, and K. Kim, Phys. Rev. B 81, 195107 (2010). \n269See http://hauleweb.rutgers.edu/tutorials/index.html for DFT $^+$ embedded DMFT Functional. \n270P. Hansmann, A. Toschi, G. Sangiovanni, T. Saha-Dasgupta, S. Lupi, M. Marsi, and K. Held, Phys. Status Solidi B 250, 1251 (2013). \n${}^{271}\\mathrm{K}.$ Haule and G. L. Pascut, Phys. Rev. B 94, 195146 (2016). \n272K. Haule, J. Phys. Soc. Jpn. 87, 041005 (2018). \n273P. Giannozzi, S. de Gironcoli, P. Pavone, and S. Baroni, Phys. Rev. B 43, 7231 (1991). $^{274}\\mathrm{H}$ . Hagemann, A. Rief, F. Kubel, J. L. M. van Mechelen, F. Tran, and P. Blaha, J. Phys.: Condens. Matter 19, 036214 (2007). \n$^{275}\\mathrm{S}$ . Ehsan, A. Tröster, F. Tran, and P. Blaha, Phys. Rev. Mater. 2, 093610 (2018). \n$^{276}\\mathrm{P}.$ Blaha, D. J. Singh, and K. Schwarz, Phys. Rev. Lett. 93, 216403 (2004). 277J. M. Perez-Mato, M. Aroyo, A. García, P. Blaha, K. Schwarz, J. Schweifer, and K. Parlinski, Phys. Rev. B 70, 214111 (2004). \n278J. M. Perez-Mato, P. Blaha, K. Schwarz, M. Aroyo, D. Orobengoa, I. Etxebarria, and A. García, Phys. Rev. B 77, 184104 (2008). \n279O. Rubel, A. Bokhanchuk, S. J. Ahmed, and E. Assmann, Phys. Rev. B 90, 115202 (2014). \n$^{280}\\mathrm{P}.$ M. C. Rourke and S. R. Julian, Comput. Phys. Commun. 183, 324 (2012). 281H.-Y. Yang, J. Gaudet, A. A. Aczel, D. E. Graf, P. Blaha, B. D. Gaulin, and F. Tafti, Phys. Rev. B 98, 045136 (2018). \n282See http://www.wien2k.at/acknowledgment for acknowledgment to the WIEN2k contributors. \n283See http://www.wien2k.at/reg_user/textbooks/usersguide.pdf for the WIEN2k user’s guide. \n284See http://www.wien2k.at/reg_user/mailing_list for the WIEN2k mailing list. " + }, + { + "id": "10.1038_s41467-018-07903-6", + "DOI": "10.1038/s41467-018-07903-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-018-07903-6", + "Relative Dir Path": "mds/10.1038_s41467-018-07903-6", + "Article Title": "9.2%-efficient core-shell structured antimony selenide nullorod array solar cells", + "Authors": "Li, ZQ; Liang, XY; Li, G; Liu, HX; Zhang, HY; Guo, JX; Chen, JW; Shen, K; San, XY; Yu, W; Schropp, REI; Mai, YH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Antimony selenide (Sb2Se3) has a one-dimensional (1D) crystal structure comprising of covalently bonded (Sb4Se6)(n) ribbons stacking together through van der Waals force. This special structure results in anisotropic optical and electrical properties. Currently, the photovoltaic device performance is dominated by the grain orientation in the Sb2Se3 thin film absorbers. Effective approaches to enhance the carrier collection and overall power-conversion efficiency are urgently required. Here, we report the construction of Sb2Se3 solar cells with high-quality Sb2Se3 nullorod arrays absorber along the [001] direction, which is beneficial for sun-light absorption and charge carrier extraction. An efficiency of 9.2%, which is the highest value reported so far for this type of solar cells, is achieved by junction interface engineering. Our cell design provides an approach to further improve the efficiency of Sb2Se3-based solar cells.", + "Times Cited, WoS Core": 611, + "Times Cited, All Databases": 637, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000455354800022", + "Markdown": "# 9.2%-efficient core-shell structured antimony selenide nanorod array solar cells \n\nZhiqiang Li1, Xiaoyang Liang1, Gang Li1, Haixu Liu1, Huiyu Zhang1, Jianxin Guo1, Jingwei Chen1, Kai Shen2, Xingyuan San1, Wei $\\mathsf{Y u}^{1}$ , Ruud E.I. Schropp $\\textcircled{1}$ 2 & Yaohua Mai2 \n\nAntimony selenide $(\\mathsf{S b}_{2}\\mathsf{S e}_{3})$ has a one-dimensional (1D) crystal structure comprising of covalently bonded $({\\mathsf{S b}}_{4}{\\mathsf{S e}}_{6})_{n}$ ribbons stacking together through van der Waals force. This special structure results in anisotropic optical and electrical properties. Currently, the photovoltaic device performance is dominated by the grain orientation in the ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ thin film absorbers. Effective approaches to enhance the carrier collection and overall power-conversion efficiency are urgently required. Here, we report the construction of ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ solar cells with high-quality ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ nanorod arrays absorber along the [001] direction, which is beneficial for sun-light absorption and charge carrier extraction. An efficiency of $9.2\\%,$ , which is the highest value reported so far for this type of solar cells, is achieved by junction interface engineering. Our cell design provides an approach to further improve the efficiency of ${\\sf S b}_{2}{\\sf S e}_{3}$ -based solar cells. \n\nmong inorganic semiconductor thin film photovoltaics, cadmium telluride (CdTe) and copper indium gallium selenide $(\\mathrm{Cu}(\\mathrm{In},\\mathrm{Ga})\\mathrm{Se}_{2})$ solar cells have reached powerconversion efficiencies of over $22\\%^{1,2}$ . The high device performance is possible due to the enough photon absorption, high bulk lifetime, superior carrier collection efficiency, and excellent junction interface. The chalcogenide antimony selenide $(\\mathsf{S b}_{2}\\mathsf{S e}_{3})$ recently emerged as a promising alternative light-absorber material for high-efficiency photovoltaic devices due to its attractive properties, such as a single phase structure, proper optical bandgap $(1.1\\mathrm{-}1.3\\mathrm{eV})$ , high light absorption coefficient $(\\mathrm{i}0^{5}\\mathrm{cm}^{-1}$ at around $600\\mathrm{nm},$ ), low toxicity, and high element abundance3–8. The use of the chalcogenide ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ avoids the issue of low In and Ga availability. The application of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ in photovoltaic devices as light-absorber was explored by Nair et al. in 2000s, yielding a rather low conversion efficiency of $0.66\\%^{9,10}$ . Since the notable efficiency values of $3.21\\%$ and $2.26\\%$ obtained in 2014 by Choi et al. and Zhou et al., respectively, ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ -based solar cells have experienced rapid development3,11. A powerconversion efficiencies of $6.0\\%$ was reported for a zinc oxide $(\\mathrm{ZnO})/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ heterojunction and $6.5\\%$ for a cadmium sulfide (CdS) $\\langle\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ heterojunction with $\\mathrm{Pb}S$ quantum dot film as holetransporting layer, respectively12,13. Moreover, a $7.6\\%$ efficiency was reported this year, due to an improved crystallinity of $S{\\mathrm b}_{2}S{\\mathrm e}_{3}$ thin film absorbers14. However, for ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ to become a low cost, high abundancy compound to replace $\\mathrm{Cu(In,Ga)Se}_{2}$ , this value is still too much behind that of state-of-the-art $\\mathrm{Cu(In,Ga)Se}_{2}$ solar cells. We here present a concept based on growing ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays that can lead to fundamentally improved solar cells. This method thus far had led to cells with a certified efficiency of $9.2\\%$ . \n\nOne attractive feature of ${\\sf S b}_{2}{\\sf S e}_{3}$ is that it has a one-dimensional (1D) crystal structure and highly anisotropic properties. The ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ crystal consists of ribbon-like $\\left({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6}\\right)_{n}$ units linked through van der Waals forces in the [010] and [100] direction, while strong covalent Sb–Se bonds make the units holding together in the [001] direction3,15. This apparently directiondependent bonding nature will result in significant anisotropy. Theoretical calculation revealed that the surfaces parallel to the [001] direction, such as (110), (120) surfaces, have lower formation energies than the other surfaces and were terminated with surfaces free of dangling bonds15. Moreover, theoretical calculations and experimental results exhibited that carrier transport in the [001] direction is much easier than that in other directions15,16. Thus, the devices are expected to offer appealing photoresponse and device performance if the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorber consists of $({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6})_{n}$ ribbons stacked vertically on the substrate. However, up to date, only quality [221]-oriented absorbers have been fabricated, in which the $\\left({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6}\\right)_{n}$ ribbons were tilted and have a certain degree with the substrate. On the other hand, the optimal ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorber thickness for these devices were limited to the range of $0.3\\substack{-0.6\\upmu\\mathrm{m}}$ due to the electron diffusion length $\\left(L_{\\mathrm{e}}\\right)$ of only $0.3\\upmu\\mathrm{m}$ in the [221] direction16. Due to this effect, the higher electron diffusion length $L_{\\mathrm{e}}$ along the [001] direction, which approaches $1.7\\upmu\\mathrm{m}$ (five times that along the [221] direc$\\tan^{16^{\\cdot}}$ ), could thus far not be fully exploited. \n\nIn this work, we address this limitation and grew ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays and solar cells with [001]-orientation on Mocoated glass substrates using the close spaced sublimation (CSS) technique. A growth model is presented to investigate the mechanism covering the stages from atom absorption at the Mo surface to growth of the thin film structure towards the formation of aligned 1D ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays. We investigated the junction structure of the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ nanorod interface. We here reveal the migration of element antimony (Sb) into the whole CdS buffer layer if no specific precautions are taken. Subsequently, we introduce a very thin titanium oxide $\\left(\\mathrm{TiO}_{2}\\right)$ layer deposited by atomic layer deposition (ALD) technique at the $\\bar{\\mathrm{CdS}}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ junction interface. The interface engineering with $\\mathrm{TiO}_{2}$ leads to an independently verified record power-conversion efficiency of $9.2\\%$ for the $\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ solar cells $\\mathrm{(ZnO{:}A l/Z n O/C d S/T i O_{2}/S b_{2}S e_{3}}$ nanorod arrays $/\\mathrm{MoSe}_{2}/\\mathrm{Mo})$ with an absorber thickness over 1000 nm while maintaining a high fill factor of $70.3\\%$ . The values of external quantum efficiency (EQE) are higher than $85\\%$ in a wide spectral range from 550 to $900\\mathrm{nm}$ , approximating the values of well-developed $\\mathrm{CdS/Cu(In,Ga)Se_{2}}$ thin film solar cells. This work can facilitate the preparation and application of patterned 1D ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ -based nanostructures for applications in sensor arrays, piezoelectric antenna arrays, and other electronic and optoelectronic devices. \n\nResults \nCharacterization of $\\mathbf{S}\\mathbf{b}_{2}\\mathbf{S}\\mathbf{e}_{3}$ nanorod arrays. It is worth noting that, to our knowledge, the fabrication of high quality ribboned ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays on Mo-coated glass substrate by the CSS technique has not been previously reported. The surface and cross-sectional morphologies of the as-deposited ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays were characterized by scanning electron microscope (SEM) in Fig. 1a, b, respectively. A high density array of ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorods grown vertically on the substrate with diameters ranging from 100 to $300\\mathrm{nm}$ and lengths of about $1200\\mathrm{nm}$ was observed. The crystal structure and phase purity of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays were measured by X-ray diffraction (XRD) as depicted in Fig. 1c. The arrays exhibit the orthorhombic crystal geometry belonging to the space group of Pbnm (JCPDS 15-0861) with no detectable impurities of other phases. It is important to note that only strong $(h\\bar{k}I)$ and $(h k2)$ diffraction peaks are observed in the XRD pattern, suggesting that the ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorod arrays have a preferred orientation along the $\\scriptstyle{c}$ -axis direction. The intensity ratios of $I_{101}/$ $I_{221}$ and $I_{002}/I_{221}$ for the nanorod arrays reached 0.42 and 0.73, respectively. These ratios are much higher than those of thin films with the (221)-preferred orientation in previous reports12,17. Since the (221)-oriented grain consists of $({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6})_{n}$ ribbons grown vertically to the substrate with a tilt angle, the increased $I_{101}/I_{221}$ and $I_{002}/I_{221}$ values hint that the $S{\\mathrm b}_{2}S{\\mathrm e}_{3}$ nanorod arrays are grown with enhanced preference along the $c$ -axis [001] direction and at a higher tilt angle between $({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6})_{n}$ ribbons and the substrate, compared to the (221)-oriented thin films4,15. We further relied on high-resolution transmission electron microscopy (HRTEM) to reveal the crystal orientation of the individual ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorods. Samples were cross-sectioned by focused ion beam and a TEM image of the nanorod array is shown in Fig. 1d. The interplanar d-spacings of $0.389\\mathrm{nm}$ and $0.521\\mathrm{nm}$ correspond to the (001) and (210) planes of orthorhombic ${\\sf S b}_{2}{\\sf S e}_{3}$ , respectively, as shown in Fig. 1e, which is consistent with the 1D singlecrystalline ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanostructures synthesized by chemical synthesis methods18,19. The corresponding selected-area electron diffraction (SAED) pattern (Fig. 1f) exhibited the vertical relationship of the (001) and (210) planes, indicating the ½1\u000120\u0002 crystallographic axis of the Pbnm space group and the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod, suggesting that the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays in this work grow along the [001] direction. Analysis on additional ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorods further supported that the $S\\dot{\\mathsf{b}}_{2}S\\mathsf{e}_{3}$ nanorod arrays were grown along the [001] direction (Supplementary Figure 1). The SAED characterization provides a direct observation of the atomic arrangement of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod and echoes previous XRD and SEM results. \n\nGrowth model of $\\mathbf{S}\\mathbf{b}_{2}\\mathbf{S}\\mathbf{e}_{3}$ nanorod arrays on Mo substrate. As shown in Fig. 2, a series of plan-view and cross-sectional SEM images of $\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ grown with different durations on Mo substrate exhibit the morphological evolution of ${\\sf S b}_{2}{\\sf S e}_{3}$ . It was found that with increasing growth durations from 60 to $180s$ the morphologies of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ samples vary from a compact thin film structure to an aligned nanorod array structure. As seen from the corresponding cross-sectional images, the thickness of the ${\\sf S b}_{2}{\\sf S e}_{3}$ layer was 200, 600, 1000 and $2000\\ \\mathrm{nm}$ for the samples grown for 60, 120, 160 and $180s,$ , respectively. It indicates that both thickness and growth rate are increased as the deposition proceeds. The CSS-processed ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ is a smooth and compact film composed of grains with uniform grain size of about $100\\mathrm{nm}$ in the first $60\\mathrm{{s}}$ (Fig. 2a, e). When the growth time increases to $^{120s,}$ the grain size increases to $200{-}300\\mathrm{nm}$ and the sample still displays film structure morphology, though the surface becomes porous and some craters can be observed (Fig. 2b, f). For the sample grown for 160 s (Fig. 2c, g), it is observed that the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ consists of a compact bottom layer and a nanorod-array top layer vertical to the substrate. The vertical nanorod array appears to grow on top of the compact bottom layer. As the growth times increases further, to $180s,$ the thickness of the top nanorod-array layer increases while the compact bottom layer thickness shrinks (Fig. 2d, h). \n\n![](images/500bb420a68b235f9245cf800b3fb56bb0adc344f0619c356ff9277321fb4367.jpg) \nFig. 1 Microscopy and spectroscopy of ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ nanorod array. a–c Top-view (a), cross-sectional (b), SEM images and X-ray diffraction pattern (c) of the ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ nanorod arrays grown on Mo-coated glass substrate. d–f TEM image $({\\pmb d})$ , high resolution TEM (HRTEM) image (e), and the corresponding selected-area electron diffraction (SAED) pattern (f) of the ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ nanorod array \n\n![](images/d217b1c5822f2f940a56943bbe793e04c3b45faefa5d0ab3e42a64c6cf04901c.jpg) \nFig. 2 Morphology evolution of ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ : from thin film to nanorod array. a–d Top-view SEM images of ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ with different deposition times, a 60 s, b 120 s, c 160 s, and d 180 s. e–h The corresponding cross-sectional images of ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ with different deposition time, e 60 s, f 120 s, g 160 s, and h 180 s. The scale bar for a–h is $1\\upmu\\mathrm{m}$ \n\nBased on the above observation, we propose a model to understand the mechanism governing the transition in the growth process from ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ thin film to nanorod array. The growth process of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ can be divided into four stages: surface absorption, film growth, splitting, and nanorod array growth stage. For the first (surface absorption) stage, we have generated an atomistic model shown in Fig. 3a based on the following considerations: first, ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ possesses a 1D crystal structure and is comprised of $\\left({\\mathsf{S b}}_{4}{\\mathsf{S e}}_{6}\\right)_{n}$ ribbons. Considering the combination between the $\\left({\\mathsf{S b}}_{4}{\\mathsf{S e}}_{6}\\right)_{n}$ ribbon and the substrate surface, we calculated the atom displacement distributions by the Vienna ab initio Simulation Package $(\\mathrm{VASP})^{20}$ . The calculated results show that the Sb and Se atoms are dispersed from ${\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6}$ and scattered on the Mo surface and that the ribboned structure of ${\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6}$ collapses if the ${\\sf S b}_{4}{\\sf S e}_{6}$ unit runs parallel to the Mo (110) surface (Supplementary Figure 2 and Supplementary Figure 3a). On the contrary, when the ${\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6}$ unit is standing vertically on the Mo (110) plane, the simulated results display that the unit is stable with lower distortion (Supplementary Figure 3b). Second, despite the decomposition of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ during the thermal process, the absorption of $\\mathrm{\\sfSb}$ or Se atoms at the $\\mathrm{Sb}_{4}\\mathrm{Se}_{6}/\\mathrm{Mo}$ interface is also taken into account. The degree of lattice deformation for the $\\mathrm{Sb}_{4}\\mathrm{Se}_{6}/\\mathrm{Mo}$ , $\\mathrm{Sb}_{4}\\mathrm{Se}_{6}/\\mathrm{Sb}/\\mathrm{Mo}$ and $\\mathrm{Sb}_{4}\\mathrm{Se}_{6}/\\mathrm{Se}/\\mathrm{Mo}$ absorption models, respectively, is 0.755, 0.642 and 0.534. This indicates that on the Mo surface the absorption of one Se atom layer prior to $\\left({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6}\\right)_{n}$ ribbons is favored rather than the vertical growth of $\\left({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6}\\right)_{n}$ ribbons (Supplementary Figure 3c, 3d and Supplementary Table 1). \n\n![](images/5e395bf3e79e058e07616f19188ce04de979bdd5495f794cf4b6f8078596212a.jpg) \nFig. 3 Growth model of the ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ nanorod arrays on Mo substrate. a Atomistic model of $S\\mathsf{b}_{4}S\\mathsf{e}_{6}$ unit on the (110) plane of Mo. b–d Schematics of the ${\\sf S b}_{2}{\\sf S e}_{3}$ at different growth stages, b thin film growth, c split, and d nanorod array growth (top part exhibits obvious nanorod array morphology and bottom is compact layer) \n\nDuring film growth, splitting, and nanorod growth stages, the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ grains grow bigger as ${\\sf S b}_{2}{\\sf S e}_{3}$ vapor continuously evaporates from the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ source, and then the transition from thin film to nanorod growth occurs when the generated lateral stress beyond the tolerance of the van der Waals forces between the $({\\mathrm{Sb}}_{4}{\\mathrm{Se}}_{6})_{n}$ ribbons in the deposited ${\\sf S b}_{2}{\\sf S e}_{3}$ films. The nanorods get longer and more in number and the splitting goes deeper into the film as the growth time proceeds (Fig. 3d), which could be attributed to the higher growth rate in the ribbon direction due to the stronger covalent $56{-}S e$ bonds internally in the ribbon. \n\nDevice performance and characterization. To investigate the effect of different absorber morphologies on the performance of the ${\\sf S b}_{2}{\\sf S e}_{3}$ solar cells, the devices were finished by successively depositing the CdS buffer, high-resistance (HR) and lowresistance (LR) ZnO layer, and front Ag contact. The devices were divided into three groups according to the thicknesses and morphologies of the CSS-processed $\\mathrm{\\bar{S}b}_{2}\\mathrm{Se}_{3}$ absorbers. For description clarity, we denoted the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ thin film absorbers with thickness between 200 and $600\\mathrm{nm}$ as TF- ${\\sf S b}_{2}{\\sf S e}_{3}$ the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ thickness in the range of 650 to $1100\\mathrm{nm}$ , comprising a double layer (vertical nanorod-array top layer and compact-film bottom layer) as $\\mathrm{M}{\\cdot}\\mathrm{Sb}_{2}\\mathrm{Se}_{3},$ , and ${\\sf S b}_{2}{\\sf S e}_{3}$ absorbers thicker than $1100\\mathrm{nm}$ with nearly an entire nanorod-array structure as NA- ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ . \n\nFigure 4a displays representative current density-voltage $\\left(J\\cdot W\\right)$ curves of the solar cells employing the TF- ${\\sf S b}_{2}{\\sf S e}_{3}$ , $\\mathbf{M}{\\cdot}\\mathbf{S}\\mathbf{b}_{2}\\mathbf{S}\\mathbf{e}_{3}$ , and ${\\mathrm{NA}}{\\cdot}{\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorbers, respectively. Typical $J{-}V$ characterizations performed under standard test conditions (STC) yielded an optimal conversion efficiency of $4.78\\%$ for the $\\mathrm{M}{\\cdot}\\mathrm{S}\\mathrm{b}_{2}\\mathrm{S}\\mathrm{e}_{3}$ solar cell with an open circuit voltage $(V_{\\mathrm{OC}})$ of $0.370\\mathrm{V}$ , short circuit current density $(J_{\\mathrm{SC}})$ of $27.43\\mathrm{mA}\\mathrm{cm}^{-2}$ , and fill factor (FF) of $47.46\\%$ (see Table 1). The NA- ${\\displaystyle\\cdot\\ s b_{2}\\mathsf{S}e_{3}}$ samples show substantially reduced FF, which may be attributed to strong $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ interface recombination. \n\n![](images/63268de2335ec73c9af0ce6141ead4388c422ca7929fa2a1a9beb558cb043cec.jpg) \nFig. 4 Device performances of solar cells with different absorbers. a The representative $J{-}V$ curves of the solar cells with different ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ absorbers. b, c EQE spectra and the ratio of EQE(−0.5 V)/EQE(0 V) curves of the solar cells. d C-V profiling and DLCP profiling of the solar cells \n\n
Table 1 Photovoltaic performance parameters for the Sb2Se3 solar cells with different absorber structure (Fig. 4a)
AbsorberVoc (V)Jsc (mA cm-2) Fill factorEfficiency (%)
TF-SbSe30.368 24.8749.534.53
M-SbSe3 0.37027.3447.464.78
NA-SbSe3 0.38228.6040.184.39
\n\nThe presence of the nanorod structure in the absorbers increases the $J_{\\mathrm{SC}}$ of the solar cells, which is mainly due to the enhanced long wavelength response (Fig. 4b). The rough surface of the thicker nanorod absorber enhances the light harvesting and thus reduces the optical reflection (Supplementary Figure 4)21. At the same time, the [001] preferential orientation of the nanorods facilitates long-range carrier transport along the $(\\mathrm{Sb}_{4}\\mathrm{Se}_{6})_{n}$ ribbons and thus guarantees carrier extraction and high ${J_{\\mathrm{SC}}}^{16}$ . This is also supported by the EQE and biased EQE results. As shown in Fig. 4b, the EQE spectrum of the $\\mathrm{TF}{\\cdot}\\mathrm{S}{\\bf b}_{2}\\mathrm{S}e_{3}$ device reaches a maximum value of $80\\%$ at about $550\\mathrm{nm}$ , then declines both at shorter and longer wavelength due to the strong absorption of the CdS buffer and the insufficient generation and/or collection of carriers at the back side, respectively. This observation is consistent with previous reports of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ -based thin film solar cells22,23. For the $\\ensuremath{\\mathbf{M}}\\ensuremath{-}\\ensuremath{\\mathrm{S}}\\ensuremath{\\mathbf{b}}_{2}\\ensuremath{\\mathrm{S}}\\ensuremath{\\mathbf{e}}_{3}$ device, the maximum value of EQE reaches $88\\%$ at approximately $550\\mathrm{nm}$ , higher than that of the TF${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ device, partly due to its lower reflectance. The EQE spectra of the NA- ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ device demonstrates a relatively wide EQE plateau with values approaching $87\\%$ between 550 and ${900}\\mathrm{nm}$ , and a gradual decrease towards longer wavelengths. EQE spectra were also measured under bias-voltage conditions $(-0.5\\mathrm{V})$ , and the curves describing the ratio of EQE $(-0.5\\mathrm{V})$ over EQE (0 V) are shown in Fig. 4c. For the NA- ${\\mathrm{\\cdot}}S{\\mathrm{b}}_{2}S{\\mathrm{e}}_{3}$ device, the EQE ratio is approximately unity over the whole spectral range, while that of the TF- $S{\\mathrm{b}}_{2}S{\\mathrm{e}}_{3}$ and $\\mathrm{M}{\\cdot}\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ devices is strongly bias dependent, especially at long wavelength. This indicates that the photogenerated carriers in the latter devices are not collected completely and the collection requires an internal electric field. The high and wide plateau and its weak bias-voltage dependence of the EQE spectrum of NA- ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ device reveals that the carrier collection is highly efficient for the ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorod array structure along the [001] direction, explaining the higher JSC value of the NA- ${\\sf S b}_{2}{\\sf S e}_{3}$ device compared to that of the $\\ensuremath{\\mathbf{M}}\\ensuremath{-}\\ensuremath{\\mathrm{S}}\\ensuremath{\\mathbf{b}}_{2}\\ensuremath{\\mathrm{S}}\\ensuremath{\\mathbf{e}}_{3}$ device. \n\nWe then turned to the issue of the junction properties of the TF- ${\\mathrm{.}}{\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ , $\\ensuremath{\\mathbf{M}}\\ensuremath{-}\\ensuremath{\\mathrm{S}}\\ensuremath{\\mathbf{b}}_{2}\\ensuremath{\\mathrm{S}}\\ensuremath{\\mathbf{e}}_{3}$ and $\\mathrm{NA}{\\cdot}\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ solar cells. In order to understand their AC behavior, an equivalent circuit model was introduced. It consists of serial conductance, junction conductance and the capacitance element, which mainly includes the junction interface and trapping state induced capacitance. (Supplementary Figure 5). The junction capacitance is frequency independent while trapping capacitance is strongly frequencydependent24–26. In comparison with the TF- ${\\displaystyle\\cdot\\ s b_{2}\\mathsf{S}e_{3}}$ , the $\\mathrm{M}{\\cdot}\\mathrm{S}{\\bf b}_{2}\\mathrm{S}{\\bf e}_{3}$ and $\\mathrm{NA}{\\cdot}\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ device exhibit smaller and less frequency dependent capacitances, indicating that the growth of $\\bar{\\mathsf{S b}}_{2}\\mathsf{S e}_{3}$ nanorods reduces the defect density in the ${\\mathrm{Sb}}_{2}{\\bar{\\mathrm{Se}}}_{3}$ absorber or at its surface. \n\nWe further performed the capacitance–voltage (C-V) profiling and deep-level capacitance profiling (DLCP) measurements on these devices for characterizing the defects. In general, the $C^{}-V$ measurement is relation to free carriers, junction interface defects and bulk defects, while DLCP measurement is less sensitive to the junction interface defects27. As shown in Fig. 4d, the $N_{\\mathrm{DLCP}}$ values for these three devices are in the range of $4\\times10^{14}$ to $2\\times$ $10^{15}\\mathrm{cm}^{-3}$ , which are lower than the values obtained for reference samples of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ grown on $\\mathrm{{}}Z\\mathrm{{nO}}$ or $\\mathrm{TiO}_{2}$ layer as well as for ${\\mathrm{Sb}}_{2}{\\bar{\\mathrm{Se}}}_{3}$ deposited by thermal evaporation on Mo substrate $(4.6\\times$ $10^{15}$ to $\\mathrm{\\dot{1}}.1\\times10^{1\\dot{7}}\\mathrm{cm}^{-3})^{12,17,28}$ . This suggests that the CSSprocessed ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorbers on Mo substrate have a lower bulk defect density. On the other hand, $N_{\\mathrm{DLCP}}$ for TF- ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ device was a little higher than that for $\\mathrm{M}{\\cdot}\\mathrm{S}\\mathrm{b}_{2}\\mathrm{S}\\mathrm{e}_{3}$ and NA- ${\\sf S b}_{2}{\\sf S e}_{3}$ devices, indicating the reduced bulk defect densities due to the evolution of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ from thin films to nanorod array structure. However, the $N_{\\mathrm{CV}}$ values were much higher than the $N_{\\mathrm{DLCP}}$ values for these three devices, indicating serious interface defects present at the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ interface. The depletion width $(W_{\\mathrm{d}})$ is mainly located in the ${\\tt S b}_{2}{\\tt S e}_{3}$ region at the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ junction interface since the doping density of CdS is much higher than that of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorbers16,29,30. Hence, the interfacial defect density could be calculated to be $2.77\\times10^{12}\\ \\mathrm{cm}^{-2}$ , $2.85\\times10^{12}\\ \\mathrm{cm}^{-2}\\mathrm{\\dot{a}n c}$ $3.21\\times\\$ $10^{12}~\\mathrm{cm}^{-2}$ for $\\mathrm{TF}{\\cdot}\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ , $\\mathrm{M}{\\cdot}\\mathrm{S}{\\mathrm{b}}_{2}\\mathrm{S}{\\mathrm{e}}_{3}$ and ${\\mathrm{NA}}{\\cdot}{\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ devices, respectively. These values are higher than those of $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ , $\\mathrm{Zn{\\bar{O}}/S b}_{2}\\mathrm{Se}_{3}$ or $\\mathrm{TiO}_{2}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ in superstrate configurations, indicating that much more interface state activity can be expected for CBD-CdS buffer grown on ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorbers12. \n\n$\\mathbf{CdS}/\\mathbf{Sb}_{2}\\mathbf{Se}_{3}$ junction interface. To explore the coverage of CBDCdS layer coated on the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod surface and the interdiffusion of elements at the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ interface, we employed SEM, TEM, and high-angle annular dark-field scanning transmission electron microscope (HAADF-STEM) equipped with energy-dispersive spectroscopy (EDX) to characterize the interface of our CdS-coated ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod array samples. As shown in Fig. 5a, b, the CBD growth procedure yields a uniform, dense, and pin-hole free CdS film, and the CdS layer completely covers the $\\bar{\\mathrm{Sb}}_{2}\\mathrm{Se}_{3}$ nanorod array surface, yielding a $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ core-shell structure. The morphology of the CdS film reveals a fine-grain accumulated structure. The TEM image (Fig. 5c, d) displays that the thickness of the CdS coated at the top of the ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorods is about 50 to $60\\mathrm{nm}$ . More details on the CdS film growth on the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod arrays reveal that the CBD-CdS is not only present on top of the nanorods but also penetrates into the space between the nanorods and conformally coats the sidewalls of the nanorods and in the valleys on the bottom compact layer, making the cell at least partially a radial junction cell. The uniform and complete coverage of CdS layer suggests good adhesion and well defined junction formation between the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod array and the CdS buffer layer. \n\nA rectangular area in the Z-contrast HAADF cross-sectional image at the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ nanorod interface was chosen to analyze the Sb, Se, Cd, and S element distribution. As shown in Fig. 5e, element spatial mapping of Se, Cd, and S shows sharp edges, indicating negligible interfacial inter-diffusion of these three elements. On the contrary, the Sb element mapping exhibits an obvious two-zone behavior in the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ nanorod interface region, suggesting Sb-diffusion into the CBD-CdS layer. This phenomenon is quite different from the superstrate $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ heterojunction case, in which the Cd, S, Sb, and Se elements mix together to form a thin n-type inter-diffusion layer and a buried homojunction at the interface, dictating charge separation and device performance in superstrate $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ thin film solar cells. The presence of Sb in the whole CBD-processed CdS buffer layer can be attributed to the dissolution of ${\\sf S b}_{2}{\\sf S e}_{3}$ in the alkaline precursor solution (Supplementary Table 2). During the CBD process, some ammonia was added into the precursor solution to supply a suitable environment for the chemical reactions, and thus it also reacted with the precursor to form surface growth complexes31,32. For reference, the metal chalcogenide was dissolved in hydrazine or ammonia sulfide solution through the formation of highly soluble metal chalcogenide complexes at a molecular leve $3\\breve{3}-3\\dot{5}$ . A similar dissolution process is expected to occur in the reaction of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ with $\\mathrm{NH_{4}^{+}}$ during the deposition of the CdS layer in an ammonia solution. \n\n![](images/b15dcac8a3d482032d855e35b8fa30901693ddfb3d3e4174f786d1b38a1b10cb.jpg) \nFig. 5 Characterization of $\\mathsf{C d S}/\\mathsf{S b}_{2}\\mathsf{S e}_{3}$ junction interface. a, b Top-view (a) and cross-sectional (b) SEM images of CdS buffer deposited on ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ nanorod arrays. c–e TEM (c, d) and HAADF-STEM image and energy-dispersive spectroscopy elemental mapping (e) of the $\\mathsf{C d S}/\\mathsf{S}\\mathsf{b}_{2}\\mathsf{S}\\mathsf{e}_{3}$ junction interface. Elements detected: Sb L, Se $\\mathsf{L},$ Cd L, and S L \n\nSurface modification of $\\mathbf{S}\\mathbf{b}_{2}\\mathbf{S}\\mathbf{e}_{3}$ nanorod arrays by thin ALD$\\mathbf{TiO}_{2}$ . In order to address the issue of Sb diffusion and the concomitant high interface defect density, a very thin atomic layer deposited (ALD) $\\mathrm{TiO}_{2}$ layer was introduced between the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod array absorber and the CdS buffer to protect the ${\\sf S b}_{2}{\\sf S e}_{3}$ from directly contacting the $\\mathrm{NH_{4}^{+}}$ ions during the deposition of the CdS layer by CBD method. The EDX line scan analysis shows that the Sb content in the CdS layer was reduced for the CdS shell grown on ALD- $\\mathrm{\\cdotTiO}_{2}$ modificated ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod (Supplementary Figure 6). The decrease of Sb content in the CdS shell indicated that the thin ALD- $\\mathrm{\\cdotTiO}_{2}$ could efficiently reduce the dissolution of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ during the CBD process. Moreover, the corrosion rate of ${\\tt S b}_{2}{\\tt S e}_{3}$ layer in the ammonia solutions is slightly decreased after performing 20 cycles of $\\mathrm{TiO}_{2}$ (Supplementary Figure 7 and Supplementary Table 2). Figure 6b, c exhibit the topview and cross-sectional images of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ solar cells after applying all steps to a successfully completed fabrication. The device exhibits a stamp-like nanopatterned surface morphology and fewer holes and gaps are observed in the cross-sectional image, suggesting that the CBD-processed CdS and sputtered ${\\mathrm{Zn}}{\\mathrm{\\bar{O}}}/{\\mathrm{ZnO}}{\\mathrm{:}}{\\mathrm{\\bar{A}l}}$ completely covers the top of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorods as well as the lower parts within the space between nanorods. \n\nFigure 6d displays the $J{-}V$ curve of our best device in this work under simulated $\\mathrm{AM}1.5\\mathrm{G}$ solar illumination. This device was fabricated with 20 cycles of ALD $\\mathrm{TiO}_{2}$ on the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorber prior to the deposition of the CdS buffer. The cell exhibits a $V_{\\mathrm{OC}}$ of $0.40\\mathrm{V}$ , a $J_{\\mathrm{SC}}$ of $32.58\\mathrm{mA}\\mathrm{cm}^{-2}$ , a FF of $70.3\\%$ , resulting in an overall power-conversion efficiency of $9.2\\%$ , which has independently been verified by National Institute of Metrology of China (Supplementary Figure 8). A histogram of the device efficiencies obtained from 100 individually fabricated devices is shown in Fig. 6f. The average $V_{\\mathrm{OC}},J_{\\mathrm{SC}},$ FF, and conversion efficiency were $399\\pm33\\mathrm{mV}$ , $29.80\\pm3.36\\mathrm{mAcm}^{-2}$ , $64.46\\pm12.01\\%$ and $7.69\\pm$ $1.56\\%$ , respectively. Figure 6e depicts the corresponding EQE spectrum for the champion solar cell. It exhibits a broad plateau of over $85\\%$ between $550\\mathrm{nm}$ and ${900}\\mathrm{nm}$ and the integrated current density reaches a value as high as $31.48\\mathrm{mA}\\mathrm{cm}^{-\\tilde{2}}$ . The photoresponse in the plateau region is higher than that of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ solar cells in a superstrate configuration and is comparable with that of CdS/CIGS thin film solar cells prepared in our laboratory with an efficiency of $15\\%$ , as shown in Supplementary Figure 9. Nonetheless, there is large current loss at wavelengths below 550 nm due to strong parasitic absorption of the CdS buffer since the electron-hole pairs generated in the CdS layer are not collected. Therefore, it is desirable to replace the CdS with another wide band gap buffer material for further optimization. \n\nCompared with the device without ALD- $\\mathrm{TiO}_{2}$ (Fig. 4, Supplementary Figure 10), the enhancement in conversion efficiency mainly results from an increase in $\\mathrm{v_{oc}}$ and FF, which is tentatively attributed to the reduction of dissolution of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ during the CBD process and/or the reduction of shunt paths by the ALD- $\\mathrm{\\cdotTiO}_{2}$ of the surface defects on the ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorods (the dangling bonds at the tips of the $\\left({\\mathsf{S b}}_{4}{\\mathsf{S e}}_{6}\\right)_{n}$ nanoribbons). As shown in Supplementary Figure 11, Kelvin probe force microscope (KPFM) was employed to study the surface properties of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod array surfaces before and after the deposition of 20 cycles of $\\mathrm{TiO}_{2}$ . While the average roughness stays at the same value $\\left[100\\mathrm{nm}\\right]$ , the average surface potential difference decreases from 28.8 to $10.4\\mathrm{mV}$ after the deposition of the thin ALD- $\\mathrm{\\cdotTiO}_{2}$ . This suggests that a thin layer of ALD- $\\mathrm{\\cdotTiO}_{2}$ improves the surface band bending at the side walls and reduces the surface defects at the tips of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorods15,36. A surface potential difference of $280\\mathrm{mV}$ was observed between the ${\\mathrm{Sb}}_{2}{\\bar{\\mathrm{Se}}}_{3}$ layer before and after thin ALD- $\\mathrm{\\cdotTiO}_{2}$ modification. Taking into account of the valence band maximum (VBM) and band gap of ${\\sf S b}_{2}{\\sf S e}_{3}$ , we obtained the energy level diagram of the $\\mathrm{CdS}/(\\mathrm{TiO}_{2})$ ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ interface (Supplementary Figure 12). The conduction band minimum (CBM) of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ layer is shifted by about $0.13\\mathrm{eV}$ towards to the vacuum level after ALD- $\\mathrm{\\cdotTiO}_{2}$ modification. The downshifted of the CBM could decrease the conduction band offset at buffer/absorber interface, and lead to the increased fill factor. Furthermore, the possible shunt paths for the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}3$ junction with and without ALD- $\\cdot\\mathrm{TiO}_{2}$ were detected by conductive atomic force microscopy (C-AFM). For the sample without ALD- $\\mathrm{TiO}_{2}$ some white dots, representing the detected current, are observed (Supplementary Figure 13), indicating the poor coverage of CdS and the presence of shunt leakage due to local discontinuity or pinholes in the CdS buffers. On the contrary, with the insertion of thin ALD- $\\mathrm{TiO}_{2}$ between the CdS buffer and the ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorod array absorber, the white dotted area decreases or even vanishes, suggesting reduced shunt leakage. \n\n![](images/04e880c4df1c47a979694b4605577f5151d6488ab9fc17f24e381903879a4883.jpg) \nFig. 6 Solar cell structure and mechanistic investigation of ALD- $\\cdot\\mathsf{T i O}_{2}$ on ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorod arrays. a Schematic of the ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ nanorod arrays on Mo-coated glass and finished ${\\sf S b}_{2}{\\sf S e}_{3}/{\\sf C}{\\sf d}{\\sf S}$ core/shell nanorod array solar cells. b, c Cross-sectional (b) and top view $\\mathbf{\\eta}(\\bullet)$ SEM images of the completed $\\mathsf{C d S}/\\mathsf{S b}_{2}\\mathsf{S e}_{3}$ solar cells. d, e $J{-}V$ curve (d) and EQE spectrum (e) of the champion device ( $\\mathsf{a r e a}=0.2603\\mathsf{c m}^{2})$ . f Histogram of device efficiency over 100 individually fabricated solar cells. $\\pmb{\\mathsf{g}}\\ V_{\\mathsf{O C}}$ decay curves of the solar cells with and without ALD- $\\cdot\\mathsf{T i O}_{2}$ layer \n\nThe ALD- $\\mathrm{TiO}_{2}$ layer may also passivate the surface defects of the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ layer. This can be confirmed by the $\\mathrm{v_{oc}}$ decay measurement, which is related to the carrier recombination rate and the carrier lifetimes. Figure $6\\mathrm{g}$ displays the $\\mathrm{v_{oc}}$ decay curves of two representative ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ solar cells, with and without ALD$\\mathrm{TiO}_{2}$ thin layer. The cell with 20 cycles of ALD- $\\cdot\\mathrm{TiO}_{2}$ layer exhibits an obvious longer decay time than the cell without ALD$\\mathrm{TiO}_{2}$ . Furthermore, as the thin ALD- $\\mathrm{TiO}_{2}$ layer is compact and has excellent film conformity due to its layer-by-layer growth, it is expected to reduce or even prevent the chemical reaction of $\\mathrm{Sb}_{2}^{-}\\mathrm{Se}_{3}$ with the growth solution during the CBD deposition of the CdS buffer layer, leading to a more pure CdS buffer layer. The influence of doping of Sb in CdS buffer layers has not been exclusively demonstrated thus far and requires more investigation in the near future. We investigate the stability of the ${\\sf S b}_{2}{\\sf S e}_{3}$ nanorod array based solar cells. As shown in Fig. 7, the normalized efficiency of the $\\mathrm{CdS}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ solar cell with $\\mathrm{TiO}_{2}$ modification hold a slightly higher value $(\\sim97\\%$ of its initial value) than that of the device without $\\mathrm{TiO}_{2}$ modification $(\\sim94\\%$ of its initial value) after storage in air for more than $500\\mathrm{{h}}$ . \n\n![](images/208618eab4c34eb5ce52ee551bd1642a5bd606ded9030c51c42dd49660a4937b.jpg) \nFig. 7 Device stability. Stability of representative ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ solar cells without and with $\\mathsf{T i O}_{2}$ modification \n\n# Discussion \n\nIn summary, we have demonstrated the fabrication of high quality solar cells employing a 1D ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ nanorod array absorber with a height of more than $1000\\mathrm{nm}$ in the substrate configuration. TEM analysis indicated that the growth of nanorods is along the [001] direction. We propose a split growth model based on the morphology evolution from the thin film to a nanorod array. The solar cells exhibited excellent EQE spectra in the whole working wavelength range (higher than $85\\%$ between 550 and $900\\mathrm{nm}\\mathrm{.}$ ), indicating that there is long-range carrier transport along the [001] direction. Furthermore, we found that Sb diffuses into the CdS buffer due to the solubility of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ in the alkaline solution during the CBD process. A very thin $\\mathrm{TiO}_{2}$ layer deposited by ALD was introduced prior to the deposition of CdS buffer layer, leading to an improved $V_{\\mathrm{OC}},$ FF as well as conversion efficiency. This cell design and these results provide important progress towards the understanding and application of 1Dstructured ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ crystals. \n\n# Methods \n\nSolar cell fabrication. The bilayer Mo back contacts were prepared by a two-step magnetron sputtering process, which consisted of high working pressure $(2.0\\mathrm{Pa})$ and low working pressure $(0.3\\mathrm{Pa})$ process. The total thickness of Mo was about $1000\\mathrm{nm}$ . A Mo selenization process was carried out at $620^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ to form about $20\\mathrm{nm}$ thick $\\mathrm{MoSe}_{2}$ layer prior to the deposition of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}{}^{17}$ . The ${\\sf S b}_{2}{\\sf S e}_{3}$ absorber layers were grown on selenized Mo-coated glass by using a homemade CSS system. In CSS system, the thermocouple was inserted into the graphite plate to directly detect the temperatures of substrate and evaporation source, respectively. The temperatures of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ source and substrate holder were controlled by two sets of lamp heaters and thermocouples. The distance between the source and the sample holder was $11\\mathrm{mm}$ . We started the deposition when the pressure was below $1\\bar{0}^{-2}\\mathrm{Pa}$ . First, the source and sample holder were warmed up to $480^{\\circ}\\mathrm{C}$ and $270^{\\circ}\\mathrm{C}$ , respectively, in 200 seconds, and maintained at the high temperatures for hundreds of seconds to obtain the desired ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ absorber thickness. The thicknesses of the ${\\sf S b}_{2}{\\sf S e}_{3}$ layers in the range of $200{-}2000\\mathrm{nm}$ were controlled by adjusting the duration ranging from $60{-}180s$ at high temperature. The samples were taken out after cooling down to about $150^{\\circ}\\mathrm{C}$ in about $^{\\textrm{1h}}$ . After that, the ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ samples were coated with $60\\mathrm{nm}$ of CdS by chemical bath deposition at a bath temperature of $70^{\\circ}\\mathrm{C}$ Window layers of HR and LR $\\mathrm{{ZnO}}$ films were sputtered from pure $\\mathrm{znO}$ and $Z\\mathrm{nO:Al}$ targets $(\\mathrm{Al}_{2}\\mathrm{O}_{3}2\\mathrm{w}\\mathrm{t}\\%$ -doped). Top Ag grids of the solar cells were finally formed by thermal evaporation. The complete ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ solar cells have a structure of $\\mathrm{glass/Mo/MoSe_{2}/S b_{2}S e_{3}/H R-Z n O/L R-Z n O/A g}$ . $\\mathrm{TiO}_{2}$ was deposited at $150^{\\circ}\\mathrm{C}$ in a homemade ALD reactor system, which using titanium isopropoxide (TTIP) and $\\mathrm{H}_{2}\\mathrm{O}$ as Ti and O precursors, respectively. One deposition cycle involves a $_\\mathrm{H}_{2}\\mathrm{O}$ pulse of $0.5\\:s,$ a $\\Nu_{2}$ pulse of $60~\\mathsf{s}$ , a TTIP pulse of $0.5\\:\\mathrm{s}.$ and $60\\mathrm{{s}}$ of $\\Nu_{2}$ purging, and each deposition cycle was started with a $\\mathrm{H}_{2}\\mathrm{O}$ pulse and terminated with a TTIP pulse. About $2\\mathrm{nm}$ thickness of $\\mathrm{TiO}_{2}$ coating was deposited in 20 cycles. \n\nMaterial and device characterization. SEM observations were performed on a FEI Nova NANOSEM 450 field-emission microscope and the TEM measurements were carried out on a FEI Tecnai G2 transmission electron microscope. The optical properties were recorded using a Perkin-Elmer Lambda 950 spectrophotometer. The XRD data were collected with a Bruker D8 Advance diffractometer. The current density-voltage $\\left(J{-}V\\right)$ measurement was performed using an AM1.5 solar simulator equipped with a 300 W Xenon lamp (Model No. XES-100S1, SAN-EI, Japan). The EQE was measured by an Enlitech QER3011 system equipped with a $150\\mathrm{W}$ xenon light source. Capacitance-voltage (C-V) measurement was performed on Agilent B1500A Semiconductor device analyzer in the dark at room temperature. Carrier-lifetime measurements were performed using the DN-AE01 Dyenamo toolbox with a white light-emitting diode (Luxeon Star 1W) as the light source37,38. \n\nSimulation methods. All calculations of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ growing on the Mo (110) were calculated by the VASP. The DFT calculations employed the Perdew-BurkeErnzerhof (PBE) generalized gradient approximation (GGA) exchange-correlation functional and the projector-augmented wave (PAW) method. An energy cut-off of $500\\mathrm{eV}$ was applied for the plane wave expansion of the wave functions. $2\\times4\\times1$ Monkhorst-pack mesh for k-point sampling are required to relaxation all models of the ${\\sf S b}_{2}{\\sf S e}_{3}$ sheet growing on the Mo (110) with or without Se and Sb layers. \n\n# Data availability \n\nThe data supporting this study are available from the authors on request. \n\nReceived: 19 July 2018 Accepted: 5 December 2018 \nPublished online: 10 January 2019 \n\n# References \n\n1. Green, M. A. et al. Solar cell efficiency tables (version 51), Prog. Photovolt. Res. Appl. 26, 3–12 (2018). \n2. Solar Frontier. Solar Frontier achieves world record thin-film solar cell efficiency of $22.9\\%$ . Solar Frontier http://www.solar-frontier.com/eng/news/ \n2017/1220_press.html, Accessed June 2018 (2017). \n3. Zhou, Y. et al. Solution-processed antimony selenide heterojunction solar cells. Adv., Energy Mater. 4, 1079–1083. (2014). \n4. Liang, G. X. et al. Thermally induced structural evolution and performance of $\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ films and nanorods prepared by an easy sputtering method. Sol. Energy Mater. Sol. Cells 174, 263–270 (2018). \n5. Yuan, C., Zhang, L., Liu, W. & Zhu, C. Rapid thermal process to fabricate Sb2Se3 thin film for solar cell application. Sol. Energy 137, 256–260 (2016). \n6. Birkett, M. et al. Band gap temperature-dependence of close-space sublimation grown ${\\mathsf{S b}}_{2}{\\mathsf{S e}}_{3}$ by photo-reflectance. APL Mater. 6, 084901 (2018). \n7. Wang, X., Tang, R., Wu, C., Zhu, C. & Chen, T. Development of antimony sulfide–selenide ${\\mathrm{Sb}}_{2}(\\mathrm{S},\\mathrm{Se})_{3}$ -based solar cells. J. Energy Chem. 27, 713–721 (2018). \n8. Shen, K. et al. Mechanisms and modification of nonlinear shunt leakage in ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ thin film solar cells,. Sol. Energy Mater. Sol. Cells 186, 58–65 (2018). \n9. Sarah, M., Nair, M. T. S. & Nair, P. K. Antimony selenide absorber thin films in all-chemically deposited solar cells. J. Electrochem. Soc. 156, H327–H332 (2009). \n10. Bindu, K., Nair, M. T. S. & Nair, P. K. Chemically deposited Se thin films and their use as a planar source of selenium for the formation of metal selenide layers. J. Electrochem. Soc., 153, C526–C534 (2006). \n11. Choi, Y. C. et al. $\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ -sensitized inorganic–organic heterojunction solar cells fabricated using a single-source precursor. Angew. Chem. Int. Ed. 53, 1329–1333 (2014). \n12. Wang, L. et al. Stable $6\\%$ -efficient ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ solar cells with a ZnO buffer layer. Nat. Energy 2, 17046 (2017). \n13. Chen, C. et al. $6.5\\%$ certified efficiency ${\\sf S b}_{2}{\\sf S e}_{3}$ solar cells using PbS colloidal quantum dot film as hole-transporting layer. ACS Energy Lett. 2, 2125–2132 (2017). \n14. Wen, X. et al. Vapor transport deposition of antimony selenide thin film solar cells with $7.6\\%$ efficiency. Nat. Commun. 9, 2179 (2018). \n15. Zhou, Y. et al. Thin-film ${\\sf S b}_{2}{\\sf S e}_{3}$ photovoltaics with oriented one-dimensional ribbons and benign grain boundaries. Nat. Photon 9, 409–415 (2015). \n16. Chen, C. et al. Characterization of basic physical properties of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ and its relevance for photovoltaics, Front. Optoelectron 10, 18–30 (2017). \n17. Li, Z. et al. ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ thin film solar cells in substrate configuration and the back contact selenization. Sol. Energy Mater. Sol. Cells 161, 190–196 (2017). \n18. Zhai, T. et al. Single-crystalline ${\\sf S b}_{2}{\\sf S e}_{3}$ nanowires for high-performance field emitters and photodetectors. Adv. Mater. 22, 4530–4533 (2010). \n19. Xie, Q. et al. Polymer-controlled growth of ${\\sf S b}_{2}{\\sf S e}_{3}$ nanoribbons via a hydrothermal process. J. Cryst. Growth 252, 570–574 (2003). \n20. Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993). \n21. Zhu, J. et al. Optical absorption enhancement in amorphous silicon nanowire and nanocone arrays. Nano Lett. 9, 279–282 (2009). \n22. Liu, X. et al. Improving the performance of ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ thin film solar cells over $4\\%$ by controlled addition of oxygen during film deposition. Prog. Photovolt. Res. Appl. 23, 2892 (2015). \n23. Liu, X. et al. Enhanced ${\\mathrm{Sb}}_{2}{\\mathrm{Se}}_{3}$ solar cell performance through theory-guided defect control. Prog. Photovolt. Res. Appl. 25, 861–870 (2017). \n24. Proskuryakov, Y. Y. et al. Impedance spectroscopy of thin-film CdTe/ CdS solar cells under varied illumination. J. Appl. Phys. 106, 024504 (2009). \n25. Walter, T., Herberholz, R., Müller, C. & Schock, H. W. Determination of defect distributions from admittance measurements and application to ${\\mathrm{Cu}}({\\mathrm{In}},$ $\\mathrm{Ga})\\mathrm{Se}_{2}$ based heterojunctions. J. Appl. Phys. 80, 4411–4420 (1996). \n26. Kneisel, J., Siemer, K., Luck, I. & Braunig, D. Admittance spectroscopy of efficient $\\mathrm{CuInS}_{2}$ thin film solar cells. J. Appl. Phys. 88, 5474–5481 (2000). \n27. Duan, H. S. et al. The role of sulfur in solution-processed $\\mathrm{Cu}_{2}\\mathrm{ZnSn}(\\mathrm{S},\\mathrm{Se})_{4}$ and its effect on defect properties. Adv. Funct. Mater. 23, 1466–1471 (2013). \n28. Chao, C. et al. Accelerated optimization of $\\mathrm{TiO}_{2}/\\mathrm{Sb}_{2}\\mathrm{Se}_{3}$ thin film solar cells by high-throughput combinatorial approach. Adv. Energy Mater. 7, 1700866 (2017). \n29. Cwil, M., Igalson, M., Zabierowski, P. & Siebentritt, S. Charge and doping distributions by capacitance profiling in $\\mathrm{Cu(In,Ga)Se}_{2}$ solar cells. J. Appl. Phys. 103, 063701 (2008). \n30. Decock, K., Zabierowski, P. & Burgelman, M. Modeling metastabilities in chalcopyrite-based thin film solar cells. J. Appl. Phys. 111, 043703 (2012). \n31. Maticiuc, N., Katerski, A., Danilson, M., Krunks, M. & Hiie, J. XPS study of OH impurity in solution processed CdS thin films. Sol. Energy Mater. Sol. Cells 160, 211–216 (2017). \n32. Ortega Borges, R. & Lincot, D. Mechanism of chemical bath deposition of cadmium sulfide thin films in the ammonia-thiourea system: in situ kinetic study and modelization. J. Electrochem. Soc. 140, 3464–3473 (1993). \n33. Xia, Z. et al. Generalized water-processed metal chalcogenide complexes: synthesis and applications. Chem. Mater. 27, 8048–8057 (2015). \n34. Mitzi, D. B. Solution processing of chalcogenide semiconductors via dimensional reduction. Adv. Mater. 21, 3141–3158 (2009). \n35. Protesescu, L. et al. Atomistic description of thiostannate-capped CdSe nanocrystals: retention of four-coordinate $\\mathrm{SnS_{4}}$ motif and preservation of Cdrich stoichiometry. J. Am. Chem. Soc. 137, 1862–1874 (2015). \n36. Jiang, C.-S. et al. How grain boundaries in $\\mathrm{Cu(In,Ga)Se}_{2}$ thin films are charged: Revisit. Appl. Phys. Lett. 101, 033903 (2012). \n37. Freitag, M. et al. Dye-sensitized solar cells for efficient power generation under ambient lighting. Nat. Photon. 11, 372 (2017). \n\n38. Boschloo, G., Häggman, L. & Hagfeldt, A. Quantification of the effect of 4-tert-butylpyridine addition to $\\mathrm{I}^{-}/\\mathrm{I}^{3-}$ redox electrolytes in dye-sensitized nanostructured $\\mathrm{TiO}_{2}$ solar cells. J. Phys. Chem. B 110, 13144–13150 (2006). \n\n# Acknowledgements \n\nThis work was supported by the Advanced Talents Incubation Program of the Hebei University (801260201001), National Natural Science Foundation of China (NSFC No.61804040), Scientific Research Foundation for the Returned Overseas Chinese Scholars (CG2015003004), and Natural Science Foundation of Hebei Province (No. E2016201028). \n\n# Author contributions \n\nZ.L. and Y.M. conceived the idea and designed the experiments. Z.L., X.L. and G.L. performed most of the device fabrication and characterization. H.L., H.Z. and W.Y. conducted the $\\mathrm{TiO}_{2}$ deposition. K.S. and X.S. assisted in the TEM and EDX mapping characterization and data analysis. J.G. and J.C. carried out the theoretical simulation and analyzed the results. Z.L., R.E.I.S., and Y.M. analyzed the overall results and wrote the paper. Y.M. supervised the project and all authors discussed the experiments and commented on the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 018-07903-6. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1038_s41467-019-11718-4", + "DOI": "10.1038/s41467-019-11718-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-11718-4", + "Relative Dir Path": "mds/10.1038_s41467-019-11718-4", + "Article Title": "Tumor exosome-based nulloparticles are efficient drug carriers for chemotherapy", + "Authors": "Yong, TY; Zhang, XQ; Bie, NN; Zhang, HB; Zhang, XT; Li, FY; Hakeem, A; Hu, J; Gan, L; Santos, HA; Yang, XL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Developing biomimetic nulloparticles without loss of the integrity of proteins remains a major challenge in cancer chemotherapy. Here, we develop a biocompatible tumor-cell-exocytosed exosome-biomimetic porous silicon nulloparticles (PSiNPs) as drug carrier for targeted cancer chemotherapy. Exosome-sheathed doxorubicin-loaded PSiNPs (DOX@E-PSiNPs), generated by exocytosis of the endocytosed DOX-loaded PSiNPs from tumor cells, exhibit enhanced tumor accumulation, extravasation from blood vessels and penetration into deep tumor parenchyma following intravenous administration. In addition, DOX@E-PSiNPs, regardless of their origin, possess significant cellular uptake and cytotoxicity in both bulk cancer cells and cancer stem cells (CSCs). These properties endow DOX@E-PSiNPs with great in vivo enrichment in total tumor cells and side population cells with features of CSCs, resulting in anticancer activity and CSCs reduction in subcutaneous, orthotopic and metastatic tumor models. These results provide a proof-of-concept for the use of exosome-biomimetic nulloparticles exocytosed from tumor cells as a promising drug carrier for efficient cancer chemotherapy.", + "Times Cited, WoS Core": 609, + "Times Cited, All Databases": 636, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000482398900040", + "Markdown": "# Tumor exosome-based nanoparticles are efficient drug carriers for chemotherapy \n\nTuying Yong 1,2,6, Xiaoqiong Zhang1,6, Nana Bie1,6, Hongbo Zhang3,6, Xuting Zhang $\\textcircled{6}$ 1, Fuying Li1, Abdul Hakeem1, Jun $\\mathsf{H u}^{1}$ , Lu Gan $\\textcircled{1}$ 1,2, Hélder A. Santos $\\textcircled{1}$ 4,5 & Xiangliang Yang1,2 \n\nDeveloping biomimetic nanoparticles without loss of the integrity of proteins remains a major challenge in cancer chemotherapy. Here, we develop a biocompatible tumor-cell-exocytosed exosome-biomimetic porous silicon nanoparticles (PSiNPs) as drug carrier for targeted cancer chemotherapy. Exosome-sheathed doxorubicin-loaded PSiNPs (DOX@E-PSiNPs), generated by exocytosis of the endocytosed DOX-loaded PSiNPs from tumor cells, exhibit enhanced tumor accumulation, extravasation from blood vessels and penetration into deep tumor parenchyma following intravenous administration. In addition, DOX@E-PSiNPs, regardless of their origin, possess significant cellular uptake and cytotoxicity in both bulk cancer cells and cancer stem cells (CSCs). These properties endow DOX $@$ E-PSiNPs with great in vivo enrichment in total tumor cells and side population cells with features of CSCs, resulting in anticancer activity and CSCs reduction in subcutaneous, orthotopic and metastatic tumor models. These results provide a proof-of-concept for the use of exosomebiomimetic nanoparticles exocytosed from tumor cells as a promising drug carrier for efficient cancer chemotherapy. \n\nNseahnohoawpnanrctepidcroepsm-eirbsiamnsegadtbhildeirtruyagp nduedticrvetfrefiyn asicyoysnt n(mEcsPR(n)cNeeDrffDdeuSctes1), o.htaThvoe increase the capacity of targeting delivery of anticancer drugs to tumors, nanoparticles are usually functionalized with targeted antibodies, peptides or other biomolecules3,4. However, the presence of targeting ligands may sometimes have a negative influence on nanoparticle delivery owing to the enhanced immuneelimination5. Moreover, the targeting of these functionalized nanoparticles using targeting ligands is not possible and not precise for a wide range of cancers, because the receptors differ from versatile genetic or phenotypic heterogeneity of tumors6,7. \n\nBiomimetic nanoparticles that combine the unique functionalities of natural biomaterials, such as cells or cell membranes, and engineering versatility of synthetic nanoparticles have recently increased considerable attention as effective drug delivery platforms8,9. Nanoparticles can be coated by various cell membranes from red blood cells $(\\mathrm{RBCs})^{10,11}$ , cancer cells12,13, platelets14, or white blood cells $(\\mathrm{WBCs})^{15}$ , and have displayed good biocompatibility, prolonged circulation, as well as tumortargeting capacity. Exosomes are small extracellular vesicles secreted by mammalian cells16, and have lately been used as attractive nanocarriers owing to their stability in circulation, biocompatibility, low immunogenicity and low toxicity17–19. Furthermore, the exosomes display efficient cellular uptake and target-homing capabilities dependent on the proteins of their membrane17–19. Given that the surface protein composition of exosomes may be crucial to their function, preservation of exosome membrane integrity and stability is very important for their application in drug delivery20. Generally, exosomes-biomimetic nanoparticles are constructed by iterative physical extrusion or freeze/thaw cycles to fuse exosomes and nanoparticles21,22, which might affect the protein integrity on exosome membranes, thereby compromising the biofunctions of these biomimetic nanoparticles23,24. Therefore, it is highly desired to develop an efficient approach to construct exosome-biomimetic nanoparticles without interfering with the membrane integrity for cancer therapy. \n\nLuminescent porous silicon nanoparticles (PSiNPs) have been widely used as drug carriers owing to their excellent drug loading capacity, high biocompatibility and biodegradability15,25–30. Here, we develop a biocompatible tumor cell-exocytosed exosome-sheathed PSiNPs (E-PSiNPs) as a drug carrier for targeted cancer chemotherapy. When tumor cells are incubated with doxorubicin-loaded PSiNPs $(\\mathrm{DOX}@\\mathrm{PSiNPs},$ , they exocytose exosome-sheathed DOX-loaded PSiNPs (DOX@E-PSiNPs) (Fig. 1a). DOX $@$ E-PSiNPs, regardless of the exosome origin, possess strong cross-reactivity of cellular uptake and cytotoxicity against bulk cancer cells and cancer stem cells (CSCs), which are responsible for tumorgenesis, tumor progression, recurrence, metastasis and drug resistance31,32. Moreover, DOX@E-PSiNPs exhibit enhanced tumor accumulation, extravasation from blood vessels and deep penetration into tumor parenchyma. These features of $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs result in their greater in vivo enrichment in total tumor cells and side population cells with characteristics of $\\mathrm{CSCs}^{33,34}$ , thus generating remarkable anticancer and CSCs killing activity in subcutaneous, orthotopic and metastatic tumors (Fig. 1b). Our study provides a approach for cancer therapy by using exosome-biomimetic nanoparticles exocytosed from tumor cells as drug carriers to efficiently deliver anticancer drug. \n\n# Results \n\nAutophagy-involved in the exocytosis of PSiNPs. Luminescent PSiNPs were prepared by electrochemical etching of silicon wafers, lift-off of PSi film, ultrasonication, centrifugation and finally activation of luminescence by heating in an aqueous solution. The hydrodynamic diameter of PSiNPs was ca. $150\\mathrm{nm}$ measured by dynamic light scattering (DLS, Supplementary Fig. 1a). Scanning electron microscope (SEM) image showed a meso-porous nanostructure of the PSi film with the pore diameter of ca. $11\\mathrm{nm}$ (Supplementary Fig. 1b). The BET surface area, pore volume and average pore diameter of PSiNPs were $211.8\\mathrm{m}^{2}\\mathrm{{\\dot{g}}^{-1}}$ $0.2\\thinspace\\mathrm{cm}^{2}\\mathrm{g}^{-1}$ , and $13.5\\mathrm{nm}$ as measured by nitrogen adsorption analysis (Supplementary Fig. 1c), respectively. The intrinsic photoluminescence of PSiNPs under $488\\mathrm{nm}$ excitation appeared at wavelengths between 600 and ${800}\\mathrm{nm}$ (Supplementary Fig. 1d). \n\nHuman hepatocarcinoma Bel7402 cells were treated with PSiNPs for $6\\mathrm{{h}}$ , followed by washing thoroughly with PBS and then incubating in fresh nanoparticle-free medium for different time intervals. Inductively coupled plasma-optical emission spectroscopy (ICP-OES) analysis showed that PSiNPs were exocytosed from Bel7402 cells in a time-dependent manner, and ca. $96\\%$ of PSiNPs were expelled out after culture in fresh medium for $18\\mathrm{h}$ (Supplementary Fig. 2). Autophagy is a highly regulated process for intracellular homeostasis through clearance, degradation, or exocytosis of damaged cell components or foreign risks35. Thus, the exocytosis of PSiNPs may have high relevance to autophagy. To elucidate the role of autophagy in the exocytosis of PSiNPs, we first sought to determine whether PSiNPS-induced autophagy. Bel7402 cells were treated with PSiNPs for different time intervals and then the ratio of endogenous microtubuleassociated protein 1 light chain 3 (LC3)-II to LC3-I was assessed, since cytosolic LC3-I is conjugated to phosphatidylethanolamine to form membrane-associated LC3-II, which is recruited to autophagosomal membranes during autophagy, and therefore the conversion of LC3-I to LC3-II is considered to be an accurate indicator of autophagic activity36. PSiNPs treatment resulted in an increase of the ratio of LC3-II to LC3-I in a time-dependent manner (Fig. 2a), suggesting that PSiNPs treatment induces a cumulative increase in the formation of autophagosomes. Similar result was observed in murine hepatocarcinoma H22 cells (Supplementary Fig. 3), revealing that this phenomenal was not cell dependent. Bel7402 cells were also transfected with EGFPLC3 plasmid and then treated with PSiNPs for different time intervals. Consistently, treatment with PSiNPs led to significantly enhanced puncta formation of LC3-labeled vacuoles (Fig. 2b), confirming that PSiNPs-induced autophagosome formation. Moreover, we observed intracellular PSiNPs captured in the $\\mathrm{LC}3^{+}$ autophagosomes (Fig. 2b). To determine whether autophagy was involved in the exocytosis of PSiNPs, we exposed Bel7402 cells with PSiNPs in the presence or absence of autophagy inhibitor 3-methyladenine (3-MA), or autophagy inducers rapamycin and carbamazepine (CBZ). 3-MA significantly inhibited the exocytosis of PSiNPs, while both rapamycin and CBZ significantly enhanced the exocytosis of PSiNPs (Fig. 2c), indicating that autophagy mediates the exocytosis of PSiNPs. Furthermore, the exocytosis of PSiNPs from Atg7 (a crucial autophagy gene)-deficient $(\\mathrm{Atg}7^{-/-})$ mouse embryonic fibroblasts (MEFs) was significantly lower than that from wild type MEFs (Fig. 2d), confirming that PSiNPs-induced autophagy regulates their exocytosis after internalization. \n\nExosomes sheathed with PSiNPs (E-PSiNPs). After Bel7402 cells were incubated with PSiNPs, we collected the exocytosed PSiNPS (E-PSiNPs) by centrifugation. Field transmission electron microscope (FTEM) energy spectrum analysis showed that silicon was detected in E-PSiNPs (Supplementary Fig. 4), endorsing that E-PSiNPs were actually the exocytosed PSiNPs. DLS analysis showed that the size of E-PSiNPs and PSiNPs was $260\\pm15\\mathrm{{nm}}$ and $150\\pm11\\mathrm{{nm}}$ , and the corresponding PDI was $0.145\\pm0.032$ and $0.208\\pm0.028$ , respectively (Fig. 3a). The zeta-potential of E-PSiNPs and PSiNPs was $-11.0\\pm0.4\\mathrm{mV}$ and $-10.8\\pm0.2\\:\\mathrm{mV}$ . TEM images revealed that PSiNPs and E-PSiNPs displayed irregular morphology, and ca. $20\\mathrm{nm}$ thick membrane appeared on the surface of E-PSiNPs compared with PSiNPs (Fig. 3b). To further prove that PSiNPs were sheathed with membrane structure in E-PSiNPs, $^{3,3^{\\prime}}$ -dioctadecyloxacarbocyanine perchlorate (DiO), a commonly used cell membrane fluorescent probe, was used to stain E-PSiNPs. Colocalization of green DiO fluorescence with intrinsic red PSiNPs fluorescence was observed in E-PSiNPs, but not in PSiNPs by confocal microscopy (Fig. 3c), confirming the presence of the membrane sheathed on PSiNPs in E-PSiNPs. \n\n![](images/0fafdd96eea6baa7bb6a319ee86fe9b15f8027c96a972acbbecb2ebffe6cdd4c.jpg) \nFig. 1 Schematic illustration of E-PSiNPs as drug carriers for targeted cancer chemotherapy. a Schematic illustration of the preparation of DOX $@$ E-PSiNPs. ${\\mathsf{D O X@P S i N P s}}$ are endocytosed into cancer cells after incubation, then localized in multivesicular bodies (MVBs) and autophagosomes. After MVBs or amphisomes fuse with cell membrane, DOX $@$ E-PSiNPs are exocytosed into extracellular space. b Schematics showing how DOX $ @\\mathsf E$ -PSiNPs effeciently target tumor cells after intravenous injection into tumor-bearing mice. (I) DOX@E-PSiNPs effeciently accumulate in tumor tissues; (II) DOX@E-PSiNPs penetrate deeply into tumor parenchyma; and (III) DOX@E-PSiNPs are efficently internalized into bulk cancer cells and CSCs to produce strong anticancer efficacy \n\nExosomes, derived from fusion of intraluminal vesicles in MVBs with plasma membrane, serve as highly efficient export vehicles17–19. When internalized into Bel7402 cells, PSiNPs were found to be colocalized with FITC-CD63-labeled MVBs (Supplementary Fig. 5), suggesting that PSiNPs are associated with MVBs before exocytosis. To explore whether E-PSiNPs were sheathed with exosomes, FITC-conjugated CD63 (a common biomarker for exosomes) antibody was used to label E-PSiNPs exocytosed from Bel7402 cells. As shown by immunofluorescent staining, CD63 was detected in E-PSiNPs, but not in PSiNPs (Fig. 3d). Western blot experiments further showed that similar to the whole cell lysates and the purified exosomes obtained by differential ultracentrifugation37,38, exosome biomarkers TSG101 and CD63 were also detected in E-PSiNPs (Fig. 3e), confirming the presence of exosomes in E-PSiNPs. In contrast to exosome biomarkers, calnexin, a protein located in endoplasmic reticulum (ER)39, was only detected in whole cell lysates, but not in both \n\nE-PSiNPs and the purified exosomes (Fig. 3e), revealing the high purity of the exosomes sheathed on PSiNPs in E-PSiNPs. Similar results were also observed in E-PSiNPs exocytosed from H22 cells (Supplementary Fig. 6), suggesting that E-PSiNPs can be generated from different cell lines. Moreover, dimethyl amiloride (DMA), an inhibitor of exosome release by disrupting calcium signaling40, was found to significantly inhibit the yield of E-PSiNPs, while ionomycin, a promoter of exosome release by increasing intracellular calcium concentration41, significantly augmented the yield of E-PSiNPs (Fig. 3f). \n\nOverall, these results strongly confirm that the membrane that sheathed PSiNPs in E-PSiNPs is exosomes. The total protein amount of E-PSiNPs exocytosed from $10^{7}$ cancer cells was $60\\upmu\\mathrm{g},$ but only $1.8\\upmu\\mathrm{g}$ proteins were detected in the naturally secreted exosomes from equal numbers of cancer cells by differential ultracentrifugation, which was consistent with the other group’s report21. The fact that PSiNPs stimulated the production of exosomes by nearly 34 times shows that E-PSiNPs can be prepared with relatively high yield. \n\nE-PSiNPs as a drug carrier. E-PSiNPs as a drug carrier were investigated using DOX as a model drug. DOX was loaded into PSiNPs and then incubated with Bel7402 cells. Exosome-sheathed DOX-loaded PSiNPs (DOX $@$ E-PSiNPs) were also obtained by centrifugation in a similar fashion to E-PSiNPs. The colocalization of DOX, DiO-labeled membrane and PSiNPs by immunofluorescent staining showed the successful encapsulation of DOX into E-PSiNPs exocytosed from Bel7402 cells (Fig. 4a). DOX can also be encapsulated into E-PSiNPs exocytosed from H22 cells using the same processing method (Supplementary Fig. 7). The drug loading degree of DOX@E-PSiNPs was $300\\mathrm{{\\ng\\DOX\\\\upmug^{-1}}}$ protein (exosomes were quantified according to the protein content) and the drug loading efficiency was $0.8\\%$ determined by high performance liquid chromatography (HPLC). DOX loading did not significantly change the size of E-PSiNPs (Fig. 4b). Moreover, the size of $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs remained almost constant even after incubating in PBS with or without $10\\%$ fetal bovine serum (FBS) for 6 days (Fig. 4c). Furthermore, storage at $-80^{\\circ}\\mathrm{C}$ for 1 month or lyophilization followed by resuspension in PBS 1 week later did not affect the size (Supplementary Fig. 8a, d) and zeta-potential (Supplementary Fig. 8b, e) of $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs. Furthermore, relatively little degradation (Fig. 4d) and no significant morphology change (Supplementary Fig. 9) of $\\scriptstyle\\mathrm{DOX}@\\bar{\\mathrm{E}}{\\cdot}$ PSiNPs were detected after $^{72\\mathrm{h}}$ incubation in PBS. These results demonstrate that DOX $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{E}}$ -PSiNPs are relatively stable. $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ PSiNPs showed a sustained drug release profile as compared to DOX $@$ PSiNPs (Fig. 4e), which can avoid the side effects caused by DOX burst release during blood circulation. \n\n![](images/f6b039646cf02bcbed146e551a7f7bbae6a53ddd579a1684a90d6490909087e9.jpg) \nFig. 2 Role of autophagy in the exocytosis of PSiNPs. a LC3-I and LC3-II expression in Bel7402 cells treated with $200\\upmu\\upxi\\mathsf{m}\\mathsf{L}^{-1}$ PSiNPs for different time intervals by western blot. The number underneath each group in the immunoblotting indicates the relative ratio of LC3-II to LC3-I of the corresponding group. b Confocal fluorescence microscopic images of EGFP-LC3-transfected Bel7402 cells after treatment with $200\\upmu\\upxi\\mathsf{m}\\mathsf{L}^{-1}$ PSiNPs for different time intervals. Scale bar: $20\\upmu\\mathrm{m}$ . c Relative amount of the exocytosed PSiNPs in Bel7402 cells after treatment with $200\\upmu\\upxi\\mathsf{m}\\mathsf{L}^{-1}$ PSiNPs for $6\\mathfrak{h}$ , followed by washing with PBS and then incubating in fresh medium with or without $5{\\mathsf{m}}N$ of 3-MA, $200{\\mathsf{n}}M$ of rapamycin or $30\\upmu\\mathsf{M}$ of CBZ for another $16\\mathsf{h}$ by ICPOES. d Relative amount of the exocytosed PSiNPs in wild type and $\\mathsf{A t g7^{-/-}}$ MEF cells after treatment with $200\\upmu\\upxi\\mathsf{m}\\mathsf{L}^{-1}$ PSiNPs for $6\\mathfrak{h}$ , followed by washing with PBS and then incubating in fresh medium for 16 h by ICP-OES. Data were represented as mean $\\pm\\mathsf{S D}$ $\\therefore n=3)$ . $^{\\star}P<0.05$ , $^{\\star\\star}P<0.01$ (one-way ANOVA with Fisher’s LSD test for c and unpaired two-tailed Student’s t test for d). Source data are provided as a Source Data file \n\nEfficient cellular uptake and cytotoxicity. To explore the biological function of DOX $@$ E-PSiNPs, the interaction of $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ PSiNPs with CSCs with high drug resistance was first investigated. The H22 CSCs tumor spheroids were selected by the previously reported soft three-dimensional (3D) fibrin gel method42,43. Intracellular DOX fluorescence increased in a dosedependent manner in H22 CSCs treated with free DOX, DOX $@$ PSiNPs or $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs exocytosed from H22 cells (Fig. 5a). However, DOX@E-PSiNPs displayed the highest intracellular accumulation, which was ca. 2.1 and 1.7 times more than free DOX and $\\scriptstyle\\mathrm{DOX@PSiNPs},$ respectively (Fig. 5a). DOX $@$ E-PSiNPs after storage at $-80^{\\circ}\\mathrm{C}$ for 1 month or lyophilization followed by resuspension in PBS 1 week later still exhibited similarly strong cellular uptake by H22 CSCs (Supplementary Fig. 8c, f). Furthermore, the intracellular DOX retention in H22 CSCs was determined after treatment with free DOX, DOX $@$ PSiNPs or $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs exocytosed from H22 cells for $2\\mathrm{h}$ , followed by washing with PBS and then incubating in fresh medium for different time intervals. Treatment with ${\\mathrm{\\bar{D}O X}}({\\mathrm{\\textbar{\\alpha}E}}.$ PSiNPs resulted in the enhanced DOX retention in H22 CSCs compared with free DOX or DOX $@$ PSiNPs (Supplementary Fig. 10a). The enhanced DOX retention in DOX $@$ E-PSiNPstreated H22 CSCs might be due to the decreased expression of multidrug-resistant protein P-glycoprotein (P-gp) (Supplementary Fig. 10b), a plasma membrane transporter whose expression was associated with cell membrane microenvironment44. DOX $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{E}}$ -PSiNPs-induced decrease in P-gp expression might be due to the strong interaction with cell membrane (Supplementary Fig. 11a, b), reducing the cell membrane fluidity (Supplementary Fig. 11c). Correspondingly, fewer H22 tumor spheroids were formed when H22 cells were pretreated with DOX $@$ E-PSiNPs exocytosed from H22 cells for $^{4\\mathrm{h}}$ and then seeded in soft 3D fibrin gels ${\\sf90P a}$ , 400 cells per well) for 5 days as compared to those pretreated with free DOX or DOX@PSiNPs (Fig. 5b). Moreover, colony sizes were reduced significantly in $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ PSiNPs-pretreated group (Fig. 5c). On the other hand, when H22 CSCs selected by soft 3D fibrin gels were treated with free DOX, $\\mathrm{DOX@PSiNPs}$ or $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs exocytosed from H22 cells for $24\\mathrm{h}$ , $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs also exhibited the strongest inhibition in colony number and size of tumor spheroids (Supplementary Fig. 12a, b). These results strongly suggest that DOX $@$ E-PSiNPs display strong cellular uptake and intracellular retention with an excellent cytotoxicity against CSCs. \n\nTo evaluate whether DOX $@$ E-PSiNPs possess cross-reactive cellular uptake and cytotoxicity, murine melanoma B16-F10 CSCs were treated with free DOX, DOX $@$ PSiNPs or $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ PSiNPs exocytosed from H22 cells. Consistently, DOX@E \n\n![](images/0e1315c579a15b351743955e61928a05f13b2025633929f2821161295092d6cd.jpg) \nFig. 3 Evaluation of exosomes sheathed on PSiNPs in E-PSiNPs. a Hydrodynamic diameter of PSiNPs and E-PSiNPs by DLS analysis. b TEM images of PSiNPs and E-PSiNPs. Scale bar: $200\\mathsf{n m}$ . c Colocalization of DiO (green) and PSiNPs (red) in E-PSiNPs by confocal microscopy. Scale bar: $20\\upmu\\mathrm{m}$ . d Colocalization of CD63 (green) and PSiNPs (red) in E-PSiNPs by confocal microscopy. Scale bar: $20\\upmu\\mathrm{m}$ . e Immunoblotting analysis of exosome markers (TSG101 and CD63) and ER marker (calnexin) expressed in E-PSiNPs exocytosed from Bel7402 cells. f Yield of E-PSiNPs when Bel7402 cells were pretreated with $200\\upmu\\upxi\\mathsf{m}\\mathsf{L}^{-1}$ PSiNPs for $6\\mathfrak{h}$ and then incubated in fresh medium containing $15{\\mathsf n M}$ DMA or $10\\upmu\\upmu$ ionomycin for $16\\mathsf{h}$ by ICP-OES. Data were represented as mean $\\pm\\mathsf{S D}$ $\\therefore n=3;$ . $^{\\star\\star}P<0.01$ , $^{\\star\\star\\star}P<0.001$ (one-way ANOVA with Fisher’s LSD test). Source data are provided as a Source Data file \n\nPSiNPs showed the highest internalization into B16-F10 CSCs (Fig. 5d) and had the corresponding strongest cytotoxicity against B16-F10 CSCs compared with free DOX or DOX@PSiNPs (Fig. 5e, f and Supplementary Fig. 13a, b). Similarly, $\\mathrm{DOX}@\\mathrm{E}.$ PSiNPs exocytosed from B16-F10 cells exhibited the strongest cellular uptake and cytotoxicity against H22 CSCs (Supplementary Fig. 14). These results suggest that $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs have a strong cross-reactive cellular uptake and cytotoxicity against CSCs, irrespective of their origin. Furthermore, DOX $@$ E-PSiNPs also demonstrated the highest intracellular internalization and cross-reactive cytotoxicity against bulk cancer cells, such as H22, Bel7402 and B16-F10 cells compared with free DOX or DOX $@$ PSiNPs (Supplementary Fig. 15, 16). Intracellular trafficking analysis of DOX $@$ E-PSiNPs revealed that exosomes and DOX were internalized into cancer cells together and then colocalized with lysosomes, followed by DOX translocation to nuclei over time (Supplementary Fig. 17). Considering that more DOX was released from DOX $@$ E-PSiNPs under lysosomal acidic pH (Supplementary Fig. 18), DOX@E-PSiNPs released DOX in lysosomes to enter nuclei to exert the cytotoxicity. CD54 (ICAM1), a member of the immunoglobulin supergene family, was found to be involved in the cross-reactive cellular uptake of DOX $\\scriptstyle{\\mathcal{Q}}\\operatorname{E}$ -PSiNPs by cancer cells, as evidenced by the fact that DOX $@]$ E-PSiNPs exocytosed from B16-F10 and H22 cells expressed CD54 (Supplementary Fig. 19a), and pretreatment with CD54 antibody decreased the cellular uptake of $\\scriptstyle{\\mathrm{DOX}}\\ @\\mathrm{E}.$ PSiNPs exocytosed from H22 cells by H22 and B16-F10 cells (Supplementary Fig. 19b). Despite the strong cellular uptake by tumor cells, DOX $@$ E-PSiNPs exocytosed from H22 cells exhibited less internalization into human umbilical vein endothelial cells (HUVECs). In addition, less DOX $@$ E-PSiNPs exocytosed from HUVECs cells were internalized into H22 cells compared with DOX $@$ E-PSiNPs exocytosed from H22 cells (Supplementary Fig. 20), suggesting the tumor cell targeting capacity of tumor exosome-coated PSiNPs. \n\n![](images/e8535904af07a83fcf917b25d5fc919a8302755ae1322281be40cc20ba843f0d.jpg) \nFig. 4 Characterization of DOX $@$ E-PSiNPs. a Colocalization of DiO, ${\\mathsf{D O X}},$ and PSiNPs in DOX $@$ E-PSiNPs exocytosed from Bel7402 cells by confocal microscopy. Scale bar: $1\\upmu\\mathrm{m}$ . b Hydrodynamic diameter of E-PSiNPs and DOX $@$ E-PSiNPs by DLS. c Hydrodynamic diameter of E-PSiNPs incubating in PBS with or without $10\\%$ FBS for different time intervals. d Degradation behavior of PSiNPs, E-PSiNPs and DOX $\\ @\\mathsf{E}$ -PSiNPs in PBS at $37^{\\circ}\\mathsf C$ . e In vitro DOX release profiles of ${\\mathsf{D O X@P S i N P s}}$ and DOX $@^{\\ E}$ -PSiNPs in PBS at $\\mathsf{p H7}.4$ by dialysis bag. Data were presented as mean $\\pm\\mathsf{S D}$ ( $\\begin{array}{r}{{\\bf\\dot{n}}=3;}\\end{array}$ . $^{\\star\\star\\star}P<0.001$ (one-way ANOVA with Bonferroni’s multiple comparisons test for d and unpaired two-tailed Student’s t test for e). Source data are provided as a Source Data file \n\nEnhanced tumor accumulation and penetration. Besides efficient cellular uptake and accompanied strong cytotoxicity against bulk cancer cells and CSCs, an ideal anticancer drug delivery system following systemic administration should be characterized by enhanced tumor accumulation and penetration to reach bulk cancer cells and CSCs. Therefore, the in vivo biodistribution of $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs was investigated. Mice bearing H22 hepatocarcinoma tumors were intravenously injected with free DOX, $\\mathrm{DOX@PSiNPs}$ or DOX@E-PSiNPs at $0.{\\dot{5}}\\mathrm{mg}\\mathrm{kg}^{-1}$ DOX dosage, or high dosage of free DOX at $4\\mathrm{mg}\\mathrm{kg}^{-1}$ . At $24\\mathrm{h}$ after injection, the tumors and major normal organs (heart, liver, spleen, lung and kidney) were collected for DOX content measurement. Although DOX $@$ E-PSiNPs were accumulated in liver at relatively high level (Fig. 6a), especially Kupffer cells in liver (Supplementary Fig. 21), less DOX was accumulated in normal organs (heart, liver, lung and kidney) of DOX $\\mathrm{\\Pi}_{\\mathrm{\\tiny\\leftmoon\\mathrm{\\leftmoon\\mathrm{\\cdot}\\leftmoon\\mathrm{\\theta}}}}^{\\mathrm{\\theta}}$ -PSiNPs-treated mice than that of high dosage of DOX-treated mice (Fig. 6a). However, $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs exhibited strong tumor tropism and accumulation, ca. 2.5 and 2.3 times relative to free DOX and DOX@PSiNPs, respectively, comparable to high dosage of free DOX (Fig. 6a). Pretreatment with CD54 antibody decreased the tumor accumulation of DOX $@$ E-PSiNPs, suggesting that similar to the cross-reactive cellular uptake by cancer cells, CD54 was also involved in the enhanced tumor accumulation of DOX $@$ E-PSiNPs (Supplementary Fig. 22). The strong tumor-targeting ability of $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ 一 PSiNPs was further confirmed in B16-F10 lung metastatic model (Supplementary Fig. 23). \n\nFurthermore, we addressed the tumor penetration capacity of $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs. First, tumor spheroids as in vivo-mimetic tumors were treated with free DOX, DOX $@$ PSiNPs or $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ PSiNPs for $24\\mathrm{h}$ , and then the tumor spheroids were optically sectioned using confocal microscopy. The projection images of DOX fluorescence in tumor spheroids was reconstructed by using Amira software. DOX fluorescence intensity in both $X\\mathrm{-}$ and $Y.$ - axis shadows was distinctly stronger in DOX $@$ E-PSiNPs-treated group than that in free DOX- or DOX@PSiNPs-treated group at the same depth (Supplementary Fig. 24), suggesting the deep tumor penetration ability of DOX $\\mathrm{{\\dot{\\Omega}}}(\\varpi\\mathrm{E}$ -PSiNPs. Furthermore, the deep tumor penetration capability of DOX@E-PSiNPs was investigated in H22 tumor-bearing mice by intravenous injection of free DOX, DOX@PSiNPs or $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs. Confocal fluorescence microscopic images clearly showed that $\\scriptstyle{\\mathrm{DOX}}\\ @\\mathrm{E}.$ PSiNPs were distributed widely in whole tumor section at $24\\mathrm{h}$ after injection (Fig. 6b). In contrast, DOX $@$ PSiNPs and free DOX accumulated more around the blood vessels as indicated by stronger co-localization with FITC-CD31-labeled endothelial cells (Fig. 6b). The distance-dependent DOX fluorescence intensity also confirmed that only fluorescence signal of DOX delivered with DOX@E-PSiNPs was detectable at ca. $400\\upmu\\mathrm{m}$ far away from the blood vessels, while free DOX or DOX delivered with DOX $@$ PSiNPs was found at $<120\\upmu\\mathrm{m}$ away from the blood vessels (Fig. 6c). Overall, these results show that DOX $@$ E-PSiNPs are easy to extravasate from the blood vessels and penetrate into deep tumor parenchyma. The strong intercellular delivery capacity of $\\mathrm{DOX}@$ E-PSiNPs might be responsible for their enhanced tumor penetration26 (Supplementary Fig. 25), which is regulated by CD54 expressed on exosomes of DOX@E-PSiNPs (Supplementary Fig. 26). \n\n![](images/71156e7073e57ed7db428ba8976683d0868a227d370707c0d2a655eb5b2b1d27.jpg) \nFig. 5 Cellular uptake and cytotoxicity of DOX $@$ E-PSiNPs against CSCs. a, d Relative DOX mean fluorescence intensity (MFI) when H22 CSCs (a) and B16- F10 CSCs (d) selected in soft 3D fibrin gels were treated with free DOX, DOX $@$ PSiNPs or DOX $@$ E-PSiNPs exocytosed from H22 cells at different DOX concentrations for $2h$ by flow cytometry. Data were represented as mean $\\pm\\mathsf{S D}$ $\\therefore n=3;$ . b, e Relative colony number of tumor spheroids when H22 (b) and B16-F10 cells (e) were pretreated with free DOX, $\\mathsf{D O X@P S i N P s}$ or DOX $@$ E-PSiNPs exocytosed from H22 cells at different DOX concentrations for $4h$ and then seeded in soft 3D fibrin gels for 5 days. c, f Relative colony size of tumor spheroids when H22 (c) and B16-F10 cells (f) were pretreated with free DOX, DOX@PSiNPs or DOX@E-PSiNPs exocytosed from H22 cells at different DOX concentrations for $4h$ and then seeded in soft 3D fibrin gels for 5 days. Data were represented as mean $\\pm$ SD $_{\\cdot n=5)}$ . $^{\\star\\star}P<0.01$ , $^{\\star\\star\\star}P<0.001$ (two-way ANOVA with Bonferroni’s multiple comparisons test). Source data are provided as a Source Data file \n\nEnhanced in vivo enrichment in side population cells. Given that DOX $@$ E-PSiNPs demonstrate enhanced tumor accumulation and penetration, as well as efficient cellular uptake by bulk cancer cells and CSCs, their in vivo enrichment in total tumor cells and CSCs might be improved. Therefore, we determined the in vivo DOX accumulation in total tumor cells at $24\\mathrm{h}$ after GFPexpressing H22 tumor-bearing mice were intravenously injected with free DOX, DOX@PSiNPs or DOX@E-PSiNPs at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or high dosage of free DOX at $4\\mathrm{mg}\\mathrm{kg}^{-1}$ . The tumor tissues were digested into single cells and the intracellular DOX fluorescence in total GFP-positive tumor cells was measured by flow cytometry (Fig. 6d). DOX content in the total GFP-positive tumor cells of mice administrated with $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs was about 3.2 times of both free DOX- and $\\scriptstyle\\mathrm{DOX}@\\mathrm{P}$ - SiNPs-treated groups, respectively, even significantly higher than that of free DOX-treated group at high dosage. Subsequently, we isolated the side population cells from GFP-positive H22 tumors by flow cytometry and determined the intracellular DOX fluorescence (Fig. 6e). Similarly, higher DOX fluorescence intensity was detected in side population cells of $\\scriptstyle{\\mathrm{DOX}}\\ @\\mathrm{E}.$ PSiNPs-treated mice compared with that of free DOX-, DOX@PSiNPs- or high dosage of free DOX-treated group. Collectively, these results reveal that DOX@E-PSiNPs exhibit augmented in vivo enrichment in the total tumor cells and side population cells after intravenous injection, which further increases their in vivo anticancer and CSCs killing activity. \n\nExcellent anticancer and CSCs killing activity. The in vivo anticancer activity of $\\mathrm{DOX}@1$ E-PSiNPs was determined in ${\\mathrm{BALB}}/{\\mathrm{c}}$ mice bearing subcutaneous H22 tumors. Free DOX, $\\scriptstyle\\mathrm{DOX}@\\mathrm{P}$ - SiNPs, DOX@E-PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ were intravenously administrated into H22 tumor-bearing mice once every 3 days for 17 days. The tumors grew very fast, and free DOX and DOX $@$ PSiNPs at $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ dosage did not significantly inhibit the tumor growth compared with PBS and EPSiNPs (Fig. 7a, b and Supplementary Fig. 27). In contrast, DOX@E-PSiNPs at DOX dosage of $0.{\\dot{5}}\\mathrm{mg}\\mathrm{\\bar{k}g}^{-1}$ showed a significant anticancer activity, with 91 and $87\\%$ reduction in tumor volume and tumor weight compared to the PBS group, respectively, and even stronger than free DOX at high dosage (Fig. 7a, b and Supplementary Fig. 27). The excellent anticancer activity of DOX $@$ E-PSiNPs was further confirmed by increased \n\n![](images/d496d81f21ea445589ff9c310db300729d454c2e6775995b9d7d40e59416e0a5.jpg) \nFig. 6 Accumulation and penetration of DOX $@$ E-PSiNPs into tumor parenchyma. a DOX content in tumor tissues and major organs of H22 tumor-bearing mice at $24\\mathsf{h}$ after intravenous injection of DOX, DOX $@$ PSiNPs or DOX $@$ E-PSiNPs at DOX dosage of $0.5\\mathsf{m g}\\mathsf{k g}^{-1}$ , or high dosage of DOX at $4\\mathrm{mg}\\mathsf{k g}^{-1}$ b Colocalization of DOX and CD31-labeled tumor vessels in tumor sections of H22 tumor-bearing mice at $24\\mathsf{h}$ after intravenous injection of $\\mathsf{D O X},$ ${\\mathsf{D O X@P S i N P s}}$ or DOX $@$ E-PSiNPs at DOX dosage of $0.5\\mathsf{m g}\\mathsf{k g}^{-1}$ . Scale bar: $200\\upmu\\mathrm{m}$ . White lines represent the distance between DOX in blood vessels and DOX in tumor parenchyma. c DOX distribution profile from the blood vessels to tumor tissues on the specified white lines as indicated in b. d, e Relative DOX fluorescence intensity in GFP-positive tumor cells (d) and side population cells (e) of tumor tissues at $24\\mathsf{h}$ after GFP-expressing H22 tumor-bearing mice were intravenously injected with DOX, DOX@PSiNPs or ${\\mathsf{D}}{\\mathsf{O}}\\times\\underbrace{\\varpi}_{\\varepsilon}$ E-PSiNPs at $\\mathsf{D O X}$ dosage of $0.5\\mathsf{m g}\\mathsf{k g}^{-1}$ , or high dosage of DOX at $4\\mathrm{mg}\\mathsf{k g}^{-1}$ . Data were represented as mean $\\pm\\mathsf{S D}$ $\\therefore n=3)$ . $^{\\star}P<0.05$ , $^{\\star\\star}P<0.01$ , $^{\\star\\star\\star}P<0.001$ (two-way ANOVA with Bonferroni’s multiple comparisons test for a and oneway ANOVA with Bonferroni’s multiple comparisons test for d, e). Source data are provided as a Source Data file \n\nTUNEL-positive apoptotic tumor cells in excised tumor tissues (Supplementary Fig. 28). Moreover, prolonged survival time was observed in H22 tumor-bearing mice treated with $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ - PSiNPs (122 days), compared with PBS- (82 days), E-PSiNPs(85 days), free DOX- (84 days) or DOX $@$ PSiNPs-treated group (87 days) at $0.5\\mathrm{mg/kg}$ DOX dosage, or free DOX at $4\\mathrm{mg/kg}$ dosage (109 days) (Fig. 7c). Importantly, DOX@E-PSiNPs did not show systemic toxicity to H22 tumor-bearing mice, as evidenced by body weight (Supplementary Fig. 29), hematoxylin-eosin (H&E) staining of major organs (Supplementary Fig. 30) and serological analysis (Supplementary Fig. 31). However, free DOX at high dosage of $4{\\dot{\\mathrm{mg}}}\\mathrm{kg}^{-1}$ induced cardiotoxicity (Supplementary Fig. 30, 31). \n\nTo further assess whether DOX $@$ E-PSiNPs could efficiently kill CSCs, the tumor tissues after treatment were digested into single cells, and the number of CD133-positive cells (a CSC marker of liver cancer45) was measured. As a result, CD133-positive cells were significantly inhibited in DOX@E-PSiNPs-treated group, compared with free DOX-, DOX@PSiNPs-, or high dosage of free \n\nDOX-treated group (Fig. 7d). Consistently, the number of side population cells in tumor tissues of DOX@E-PSiNPs-treated GFP-expressing H22 tumor-bearing mice was the fewest compared with other groups (Fig. 7e). Furthermore, 800 single tumor cells were seeded in soft 3D fibrin gels $(90\\mathrm{Pa})$ for 5 days, which was developed to select $\\mathrm{CSCs^{42,\\tilde{43}}}$ . The fewest colony number and smallest colony size were formed in $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs-treated group (Fig. 7f, g). The excellent CSCs killing activity of DOX@E-PSiNPs was further confirmed by subcutaneously transplanting the same amounts of tumor cells from tumor tissues after treatment into BALB/c mice (Fig. 7h). $100\\%$ of mice (6/6 mice) generated tumors at 6 days after secondary transplantation of tumor cells of PBS-, E-PSiNPs-, free DOX- or $\\mathrm{DOX@PSiNPs}$ -treated group. However, $83\\%$ (5/6 mice) and $33\\%$ (2/6 mice) of mice generated tumors at 40 days after secondary transplantation of tumor cells of high dosage of DOX- and DOX $\\mathrm{\\Pi}_{\\mathrm{\\tiny\\leftmoon\\mathrm{\\leftmoon\\mathrm{\\cdot}\\leftmoon\\mathrm{\\theta}}}}^{\\mathrm{\\theta}}$ -PSiNPs-treated groups, respectively. Taken together, these results strongly reveal that DOX@E-PSiNPs have excellent anticancer and CSCs killing activity. To further improve the anticancer and CSCs killing efficacy, more $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs at DOX dosage of $0.8\\mathrm{mg}\\mathrm{kg}^{-1}$ , or the combination of $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ - PSiNPs at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ and all-trans-retinoic acid (ATRA), a powerful differentiating agent of CSCs, were intravenously injected into H22 tumor-bearing mice. As expected, increasing the used dosage of DOX@E-PSiNPs, or combination of $\\mathrm{DOX}@\\mathrm{I}$ E-PSiNPs and ATRA resulted in a significant tumor inhibition, with 3 or 2 tumor ablation in 6 mice, respectively (Supplementary Fig. $_{32\\mathrm{a-g})}$ ). Correspondingly, fewer side population cells in tumor tissues (Supplementary Fig. 32h), fewer colony number (Supplementary Fig. 32i) and smaller colony size (Supplementary Fig. 32j) after seeding the tumor cells in 3D fibrin gels were observed in these groups compared with only $\\mathrm{DOX}@\\mathrm{\\bar{E}}$ -PSiNPs treatment group at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , suggesting that CSCs might be responsible for the drug resistance. Meanwhile, combination treatment of $\\mathrm{DOX}@\\dot{}$ E-PSiNPs and ATRA, or increasing the used dosage of ${\\mathrm{DOX}}(\\varnothing\\operatorname{E}.$ -PSiNPs was found to be safe, as evidenced by routine blood test (Supplementary Fig. 33a–d), serological analysis (Supplementary Fig. 33e–j) and body weight (Supplementary Fig. 33k). \n\n![](images/08bb1a8379b50c59863c9aee98e179377a389e7ba3e6fce31fac18488ce53e65.jpg) \nFig. 7 Anticancer activity of DOX@E-PSiNPs in H22 tumor-bearing mice. a Tumor growth curves of H22 tumor-bearing mice after intravenous injection of PBS, E-PSiNPs, free DOX, DOX $@$ PSiNPs, DOX $@$ E-PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathsf{m g}\\mathsf{k g}^{-1}$ , or free DOX at high dosage of $4\\mathsf{m g}\\mathsf{k g}^{-1}$ . The arrows indicate the drug injection time. Data were represented as mean $\\pm\\mathsf{S D}$ $\\begin{array}{r}{\\dot{\\boldsymbol{\\mathbf{\\nabla}}}\\eta=14,}\\end{array}$ ). b Weight of tumor tissues at the end of tumor growth inhibition experiments. Data were represented as mean $\\pm\\mathsf{S D}$ $h=6)$ . c Kaplan–Meier survival plot of H22 tumor-bearing mice after intravenous administration of different formulations $(n=8)$ . d Number of CD133-postive cells in tumor tissues at the end of tumor growth inhibition experiments. e Number of side population cells in GFP-positive tumor cells of GFP-expressing H22 tumor-bearing mice at the end of tumor growth inhibition experiments as above. Data were represented as mean $\\pm\\mathsf{S D}$ $\\displaystyle{\\langle n=3\\rangle}$ ). f, g Relative colony number $(\\pmb{\\uparrow})$ and size $\\mathbf{\\sigma}(\\mathbf{g})$ of tumor spheroids when tumor cells digested from tumor tissues of H22 tumor-bearing mice at the end of tumor growth inhibition experiments were seeded in soft 3D fibrin gels for 5 days. Data were represented as mean $\\pm\\mathsf{S D}$ $\\hslash=5;$ . h Tumor formation ratio in BALB/c mice after subcutaneous injection of tumor cells ( ${10^{6}}$ cells per mouse) from tumor tissues of H22 tumor-bearing mice after treatment as above. $^{\\star}P<0.05$ , $^{\\star\\star}P<0.01$ , $^{\\star\\star\\star}P<0.001$ (one-way ANOVA with Bonferroni’s multiple comparisons test for a, $\\mathbf{b},$ and $\\mathsf{\\pmb{d}}\\mathrm{\\pmb{g}}$ and log-rank test for c). Source data are provided as a Source Data file \n\nTo further investigate the cross-reactive anticancer and CSCs killing efficacy of DOX@E-PSiNPs, mice bearing orthotopic \n\n4T1 breast tumors were intravenously administrated with free DOX, $\\mathrm{DOX@PSiNPs}$ , $\\mathrm{DOX}@\\dot{.}$ E-PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ once every 3 days for 15 days. DOX $@$ E-PSiNPs at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ exhibited a significant anticancer activity, with $68\\%$ and $65\\%$ reduction in tumor volume and tumor weight compared to the PBS group, respectively (Fig. 8a, b). Mice treated with ${\\mathrm{DOX}}(\\varnothing\\operatorname{E}.$ -PSiNPs had 11, 10, and 4 days longer survival time as compared to free DOX and $\\mathrm{DOX@PSiNPs}$ at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , and free DOX at $4\\mathrm{mg}\\mathrm{kg}^{-1}$ dosage (Fig. 8c). Furthermore, tumor cells digested from breast tumors after treatment were seeded in soft 3D fibrin gels $(90\\mathrm{Pa})$ . The fewest colony number and smallest colony size of the formed tumor spheroids were detected in $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs-treated group (Fig. 8d, e). These results demonstrate the excellent cross-reactive anticancer and CSCs killing efficacy of DOX@E-PSiNPs. DOX@E-PSiNPs did not cause toxicity to 4T1 tumor-bearing mice, as evidenced by routine blood test (Supplementary Fig. 34), serological analysis (Supplementary Fig. 35) and H&E staining of major organs (Supplementary Fig. 36), although free DOX at $4\\mathrm{mg}\\mathrm{kg}^{-1}$ dosage caused bone marrow and heart toxicity. \n\n![](images/4b8c79a757a93e8f3dab522969333503e19c828ee049d06cbf4befde0390697f.jpg) \nFig. 8 Anticancer activity of DOX $@$ E-PSiNPs in orthotopic 4T1 tumor-bearing mice. a Tumor growth curves of orthotopic 4T1 tumor-bearing mice after intravenous injection of PBS, E-PSiNPs, free DOX, DOX@PSiNPs, DOX@E-PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathsf{m g}\\mathsf{k g}^{-1}.$ or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ . The arrows indicate the drug injection time. Data were represented as mean $\\pm\\mathsf{S D}$ ( $\\cdot n=14)$ . b Weight of tumor tissues at the end of tumor growth inhibition experiments. Data were represented as mean $\\pm\\mathsf{S D}$ $_{(n=6)}$ . c Kaplan–Meier survival plot of 4T1 tumor-bearing mice after intravenous administration of different formulations $\\left\\langle n=8\\right\\rangle$ . d, e Relative colony number (d) and size (e) of tumor spheroids when tumor cells digested from tumor tissues of 4T1 tumor-bearing mice at the end of tumor growth inhibition experiments were seeded in soft 3D fibrin gels for 5 days. Data were represented as mean $\\pm\\mathsf{S D}$ $_{\\cdot n=6})$ . $^{\\star}P<0.05$ , $^{\\star\\star\\star}P<0.001$ (one-way ANOVA with Bonferroni’s multiple comparisons test for a, b, d, e and log-rank test for c). Source data are provided as a Source Data file \n\nFurthermore, the mice model bearing B16-F10 melanoma with high lung metastasis was developed to evaluate the cross-reactive anticancer and CSCs killing activity of DO $\\mathrm{\\Omega}\\left\\langle\\ @\\mathrm{E}\\right.$ -PSiNPs. At $^{48\\mathrm{h}}$ after injection of $5\\times10^{5}$ B16-F10 cells into C57BL/6 mice, the mice were intravenously administrated with free DOX, $\\scriptstyle\\mathrm{DOX}@\\mathrm{P}$ - SiNPs, $\\scriptstyle\\mathrm{DOX}@\\mathrm{F}$ -PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ once every 3 days for 13 days. Significantly fewer metastatic nodules were detected in the DOX@E-PSiNPs-treated group (Fig. 9a and Supplementary Fig. 37). The less lung metastasis in $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ -PSiNPs-treated mice was further confirmed by H&E staining on lungs (Fig. 9b). Mice treated with DOX@E-PSiNPs had 18, 17, and 4 days longer survival time as compared to free DOX and DOX@PSiNPs at DOX dosage of $0.5\\mathrm{mg}\\dot{\\mathrm{kg}}^{-1}$ , and free DOX at $4\\mathrm{mg}\\mathrm{kg}^{-1}$ dosage (Fig. 9c). Furthermore, the fewest colony number and smallest colony size of the formed tumor spheroids were detected in DOX $\\mathrm{\\Pi}_{\\mathrm{\\tiny{(\\it{a})E}}}$ -PSiNPs-treated group after seeding the tumor cells digested from lungs in the 3D fibrin gels (Fig. 9d, e). These results strongly demonstrate the excellent anticancer and CSCs killing efficacy of $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs, regardless of tumor models used and the origin of exosomes used in DOX $@]$ E-PSiNPs. The cross-reactive anticancer treatment of DOX@E-PSiNPs did not induce immunological reaction, as evidenced by the fact that treatment with DOX@E-PSiNPs exocytosed from H22 cells did not affect the content of IgM, TNF- $\\mathfrak{a}$ , IL- $1\\upbeta$ , and IL-6 in serum of C57BL/6 mice (Supplementary Fig. 38). \n\n# Discussion \n\nCSCs, a small population of cancer cells with self-renewal and high tumorigenesis, play an important role in tumor development, progression and metastasis31,32. Traditional chemotherapeutics kill bulk tumor cells, but can not efficiently eliminate CSCs due to their overexpression of ATP-binding cassette (ABC) transporters, antiapoptotic proteins and DNA repair enzymes, resulting in drug resistance and tumor recurrence after chemotherapy31,32. \n\n![](images/b669c5fba57c353799f3f896810946c48254349f207c3d836b4986b564bfc37b.jpg) \nFig. 9 Anticancer activity of DOX $@$ E-PSiNPs in B16-F10 lung metastasis mice. a Metastatic nodule numbers in lungs of B16-F10 tumor-bearing mice after intravenous injection of PBS, E-PSiNPs, free DOX, $\\mathsf{O C X@P S i N P s}$ , DOX@E-PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathsf{m g}\\mathsf{k g}^{-1}$ or free DOX at high dosage of $4\\log\\ k g^{-1}$ every three days for 13 days. Data were represented as mean $\\pm\\mathsf{S D}$ ${\\bf\\dot{\\boldsymbol{n}}}=6\\$ . b H&E staining of lungs of B16-F10 tumor-bearing mice at the end of tumor growth inhibition experiments. Scale bar: $1000\\upmu\\mathrm{m}$ c Kaplan–Meier survival plot of B16-F10 tumor-bearing mice after intravenous administration of different formulations ${\\bf\\dot{\\boldsymbol{n}}}={\\bf8})$ . d, e Relative colony number (d) and size (e) of tumor spheroids when tumor cells digested from lung tumor nodules at the end of tumor growth inhibition experiments were seeded in soft 3D fibrin gels for 5 days. Data were represented as mean $\\pm\\mathsf{S D}$ $\\mathbf{\\dot{\\eta}}_{n=}$ 5). $^{\\star\\star}P<0.01$ , $^{\\star\\star\\star}P<0.001$ (one-way ANOVA with Bonferroni’s multiple comparisons test for a, d, e and log-rank test for c). Source data are provided as a Source Data file \n\nTherefore, developing effective therapeutic strategies targeted to CSCs remains a big challenge for cancer therapy. \n\nNowadays, some NDDSs have been successfully applied to target CSCs to treat tumor. These approaches mainly include: (1) NDDSs were rationally designed to bypass the efflux pump via endocytosis, resulting in higher intracellular accumulation in $\\mathrm{CSCs^{4\\dot{6},47}}$ ; (2) NDDSs codelivered MDR modulators and anticancer drugs to CSCs to overcome drug resistance48; and (3) NDDSs were modified with CSCs targeting ligands, such as $\\mathrm{CD44^{49}}$ , $\\mathrm{CD1}33^{50}$ , and $\\mathrm{CD90^{51}}$ to increase specificity and cellular uptake. Although these NDDSs have shown potentials to overcome chemoresistance and enhance the accumulation of anticancer drug in CSCs, they cannot achieve full therapeutic efficacy. The main reasons lie in: (1) Ideal NDDSs targeting CSCs should be characterized by enhanced tumor accumulation, tumor penetration and cellular uptake by CSCs to highly enriched in CSCs following systemic administration52. However, the above approaches used to target CSCs are difficult to meet all demands at the same time, hindering the therapeutic efficacy; (2) There is no universal marker used for CSCs targeting in all cancers since the markers of CSCs differ from one type of tumor to another, and these markers are often expressed by other cell types, such as normal stem cells6,7. Thus, targeting NDDSs to CSCs using these markers is unreliable and risky; and (3) The constructed nanoparticles usually need complicated synthesis, and are usually toxic and may cause side effects as foreign components53. In the present study, we developed an exosome-sheathed PSiNPs to load DOX for efficient CSCs targeting and killing. DOX $@$ E-PSiNPs not only exhibited enhanced tumor accumulation and penetration, but also had strong cross-reactive cellular uptake and cytotoxicity against CSCs, as evidenced by the fact that DOX $@$ E-PSiNPs exocytosed from both H22 and B16-F10 cells are efficiently internalized into H22 and B16-F10 CSCs, resulting in the strongest cytotoxicity compared with free DOX and $\\mathrm{DOX@PSiNPs}$ . The strong cross-reactive cellular uptake of DOX $@$ E-PSiNPs can overcome the obstacles of requiring the specific markers for targeting CSCs in different tumors. Furthermore, $\\scriptstyle\\mathrm{DOX}@\\mathrm{E}.$ PSiNPs significantly decreased P-gp expression in CSCs, enhancing DOX retention in CSCs to overcome drug resistance. Therefore, DOX $@$ E-PSiNPs efficiently integrated all features to eradicate CSCs, generating remarkable anticancer and CSCs killing activity in H22 tumor-bearing ${\\mathrm{BALB}}/{\\mathrm{c}}$ mice, othotopic 4T1 tumor-bearing mice and B16-F10 tumor-bearing C57BL/6 mice. No significant toxicity of DOX $\\mathrm{\\Pi}_{\\cdot\\ @\\mathrm{E}}$ -PSiNPs was observed in tumor-bearing mice by serological and histopathological analysis. Moreover, $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs exocytosed from H22 cells, which were originated from liver cancer ascites of ${\\mathrm{BALB}}/{\\mathrm{c}}$ mice, did not induce immune response in C57BL/6 mice, suggesting that DOX $@$ E-PSiNPs are biocompatible and safe. \n\nUpon autophagy induction, cytoplasmic materials are sequestered in double-membrane vesicles termed autophagosomes, which can fuse with MVBs to form amphisomes or directly deliver to the lysosomes for degradation35. Thus, the induction of autophagy usually inhibits the release of exosomes54. However, when the cells can not degrade material in the lysosomes due to the lysosomal defect, lysosomal overload or transport interference, the contents of lysosomes, MVBs or amphisomes are exocytosed as exosomes when fusing with cell membrane53. Several nanoparticles, such as silver nanoparticles55, carbonbased nanoparticles56 or silicon-based nanoparticles57, were reported to induce autophagy. In this work, E-PSiNPs used as an anticancer drug carrier, were exocytosed from cancer cells in an autophagy-dependent manner. The possible reason is due to the unique structure of PSiNPs, which cannot be degraded under lysosomal acidic microenvironment58 (Supplementary Fig. 39), promoting cancer cells to release exosome-coated PSiNPs. The exocytosed E-PSiNPs might keep the protein integrity on exosome membranes, which can display fully the biological function of exosomes during drug delivery. \n\nIn summary, we have successfully developed biocompatible exosome-sheathed PSiNPs for targeted cancer chemotherapy. DOX@E-PSiNPs are exocytosed from tumor cells after incubation with DOX@PSiNPs. Following intravenous injection, $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs exhibit enhanced tumor accumulation, tumor penetration and cross-reactive cellular uptake by bulk cancer cells and CSCs, resulting in augmented in vivo DOX enrichment in total tumor cells and side population cells. DOX $@$ E-PSiNPs further demonstrate significant cross-reactive anticancer and CSCs killing activity in both subcutaneous transplantation tumor models, orthotopic tumor models and the advanced metastatic tumor models. Our study clearly demonstrates that exosome-biomimetic nanoparticles have potential as drug carriers to improve the anticancer efficacy. \n\n# Methods \n\nMaterials. Boron-doped p-type silicon wafers $(0.8-1.2\\mathrm{m}\\Omega\\mathrm{cm}$ resistivity, 〈100〉 orientation) were produced from Virginia Semiconductor, Inc. (Fredericksburg, VA, USA). Doxorubicin hydrochloride (DOX·HCl, with purity $>98.0\\%$ ) was obtained from Beijing HuaFeng United Technology CO., Ltd. (Beijing, China). RPMI 1640 medium, Dulbecco’s Modified Eagle’s Medium (DMEM), FBS, penicillin and streptomycin were provided by Gibco BRL/Life Technologies (Grand Island, NY, USA). Fibrinogen and thrombin were purchased from Searun Holdings Company (Freeport, ME, USA). Collagenase type I was purchased from Thermo Fisher Scientific (Waltham, MA, USA). Dispase II and TUNEL assay kit were purchased from F. Hoffmann-La Roche Ltd (Basel, Switzerland). Anti ICAM-1 antibody and anti P-gp antibody were purchased from ProteinTech (Wuhan, China). DIO, ionomycin, Hoechst 33342 and BCA protein quantification kit were purchased from Beyotime Biotechnology (Shanghai, China). Verapamil was provided by Selleck Chemicals (Houston, TX, USA). Cell counting kit (CCK-8) assay was obtained from Biosharp Company (Shanghai, China). DMA was purchased from Sigma-Aldrich (St Louis, MO, USA). All other reagents were of analytical grade and used without any further purification. \n\nCell lines and animals. Murine hepatocarcinoma cell line H22, mouse breast cancer cell line 4T1 and human hepatocarcinoma cell line Bel7402 were obtained from Type Culture Collection of Chinese Academy of Sciences (Shanghai, China). Murine melanoma cell line B16-F10 was kindly provided by Dr. Bo Huang (Huazhong University of Science and Technology, Wuhan, China). Wild type MEFs and $\\mathrm{Atg7^{-/-}}$ MEFs were kindly provided by Dr. Mingzhou Chen (Wuhan University, Wuhan, China). H22 cells were cultured in RPMI 1640 medium, and Bel7402 cells, wild type and $\\mathrm{Atg7^{-/-}}$ MEFs and B16-F10 cells were cultured in DMEM medium at $37^{\\circ}\\mathrm{C}$ in a $5\\%$ $\\mathrm{CO}_{2}$ humidified incubator. All media contained $10\\%$ FBS, $100\\ \\mathrm{U\\mL^{-1}}$ penicillin and $100\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ streptomycin. Six- to eightweek-old ${\\mathrm{BALB}}/{\\mathrm{c}}$ mice (male and female) and C57BL/6 mice (male) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). H22 tumor-bearing mice were constructed by subcutaneously injecting $10^{6}\\mathrm{H}22$ cells per mouse into the flanks of male BALB/c mice. Orthotopic 4T1 breast tumor mode was constructed by injecting $2\\times10^{5}$ 4T1 cells to the right mammary fat pad of female BALB/c mice. B16-F10 lung metastasis tumor model was constructed by intravenously injecting $5\\times10^{5}$ B16-F10 cells per mouse into C57BL/6 mice. All animal experiments comply with relevant ethical regulations for animal testing and research, and were approved by the Institutional Animal Care and Use Committee at Tongji Medical College, Huazhong University of Science and Technology (Wuhan, China). All cell lines were routinely tested for mycoplasma infection and were found to be negative by MycAway-Color one-step mycoplasma detection kit. \n\nCSC culture. CSCs were selected by soft 3D fibrin gels42,43. Fibrinogen was diluted to $2\\mathrm{mg}\\mathrm{mL}^{-1}$ with T7 buffer $\\mathrm{50~mM}$ Tris, pH 7.4, 150 mM NaCl) and then fibrinogen/cell mixtures were obtained by blending $2\\mathrm{mg}\\mathrm{mL}^{-1}$ fibrinogen with similar volume of cell solution $(2\\times10^{3}$ cells per mL), which produced gels of $90\\mathrm{Pa}$ in elastic stiffness. $250\\upmu\\mathrm{L}$ mixtures were loaded into each well of 24-well plate preadded with ${5}\\upmu\\mathrm{L}$ thrombin $(0.1\\mathrm{U}\\upmu\\mathrm{L}^{-1})$ . The cell culture plate was then incubated at $37^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . Finally, $1\\mathrm{mL}$ RPMI 1640 medium containing $10\\%$ FBS and antibiotics were added. On the fifth day, tumor spheroids were obtained and digested into single cells using $0.08\\%$ collagenase type I and $0.4\\%$ dispase II for $20\\mathrm{min}$ at $37^{\\circ}\\mathrm{C}$ . \n\nPreparation of PSiNPs and DOX@PSiNPs. PSiNPs were prepared by electrochemical etching method25–28. Briefly, boron-doped p-type silicon wafers were immersed into an aqueous solution of hydrofluoric acid (HF) and ethanol $(4{:}1,\\mathbf{v}/\\mathbf{v})$ in a Teflon etch cell, and then subjected to etch at a constant current density of $165\\mathrm{mAcm}^{-2}$ for $300\\mathrm{{s}}$ . The rufous porous silicon film on the substrate was removed in $3.3\\%$ aqueous HF solution in ethanol at a constant current of $4.5\\mathrm{mA}\\mathrm{cm}^{-2}$ for $90\\mathrm{s}_{\\mathrm{:}}$ , fragmented in ultrapure water by ultrasonication overnight, and then centrifuged at $_{10,000\\mathrm{g}}$ for $20\\mathrm{min}$ to collect PSiNPs. Finally, PSiNPs were heated at $60^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ to activate photoluminescence. \n\n$\\mathrm{DOX}@$ PSiNPs were prepared by adding PSiNPs in DOX solution at a weight ratio of 10:3 and then stirring for $^{12\\mathrm{h}}$ at room temperature. The mixtures were centrifuged at $_{10,000\\mathrm{g}}$ for $10\\mathrm{min}$ to collect DOX@PSiNPs, followed by gently washing with ultrapure water twice to eliminate free DOX. \n\nAutophagy induced by PSiNPs. H22 or Bel7402 cells were treated with $200\\upmu\\mathrm{g}\\mathrm{mL}$ $^{-1}$ PSiNPs for $^{6\\mathrm{h}}$ . After washing with PBS for three times, cells were lysed in RIPA lysis buffer and then subjected to western blot analysis. Briefly, $200\\upmu\\up g$ of lysates were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDSPAGE, $15\\%$ gel) and transferred onto nitrocellulose membranes. The membranes were blocked by $5\\%$ BSA for $^{2\\mathrm{h}}$ , and then incubated with anti-LC3 (Novus, NB100-2331SS) and anti- $\\cdot\\beta$ -actin antibody (Beyotime, AA128, diluted to 1:2,000) at $4^{\\circ}\\mathrm{C}$ overnight. After washing with Tris-buffered saline containing $0.1\\%$ Tween-20 (TBST), the membranes were incubated with horseradish peroxidase (HRP)- labeled secondary antibody (Beyotime, A0216, A0208, diluted to 1:10,000) at $37^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . The protein bands were detected using enhanced chemiluminescence (ECL) reagent and analyzed on ChemiDoc XRS Gel image system (Bio-Rad, Hercules, CA, USA). Uncropped gel images are provided in Source Data file. \n\nBel7402 cells were transfected with EGFP-LC3 plasmid by electroporation. After $24\\mathrm{h}$ transfection, the cells were treated with $200\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ PSiNPs for $\\mathsf{6h}.$ , washed with PBS for three times and then fixed with $4\\%$ paraformaldehyde. Green fluorescence of LC3 proteins were visualized by FV1000 confocal microscope (Olympus, Japan). \n\nPreparation and characterization of DOX $\\boldsymbol{\\mathbf{\\mathit{\\Pi}}}(\\mathbf{a}\\mathbf{E}$ -PSiNPs. To prepare E-PSiNPs or DOX $\\underline{{\\boldsymbol{\\mathcal{Q}}}}\\mathrm{F}$ -PSiNPs, $5\\times10^{7}$ H22, Bel7402, or B16-F10 cells were treated with PSiNPs (at silicon concentration of $200\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ ) or DOX@PSiNPs (at DOX concentration of $10\\upmu\\mathrm{g}\\mathrm{mL}^{-1},$ ) for $^{6\\mathrm{h}}$ in $10\\mathrm{cm}$ dishes. Subsequently, the media were discarded and replaced with fresh one without PSiNPs or $\\mathrm{DOX@PSiNPs}$ . After $16\\mathrm{h}$ incubation, the debris was discarded at ${5,000\\mathrm{g}}$ for $15\\mathrm{min}$ and then the supernatants were further centrifuged at $20{,}000\\ \\mathrm{g}$ for $30\\mathrm{min}$ to pellet out E-PSiNPs or $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs. Then, the obtained pellets were washed with PBS and resuspended in PBS for further experiments. DOX loading into E-PSiNPs was confirmed by labeling $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs with DiO and then observed by FV1000 confocal microscopy. The DiO fluorescence was detected at the excitation wavelength of $488\\mathrm{nm}$ and the emission range of $500{-}520~\\mathrm{nm}$ , DOX at the excitation wavelength of $559\\mathrm{nm}$ and the emission range of $570{-}600\\mathrm{nm}$ , and PSiNPs at the excitation wavelength of 488 and the emission range of $670{-}690\\mathrm{nm}$ . The hydrodynamic diameter of E-PSiNPs and $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs was determined by DLS (ZetaSizer ZS90, Malvern Instruments Ltd., Worcestershire, UK). The morphology of E-PSiNPs was observed by TEM (Tecnai G2-20, FEI Corp., Netherlands). DOX content loaded into $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs was determined by incubating in $1\\mathrm{M}\\mathrm{NaOH}$ for $30\\mathrm{min}$ to dissolve EPSiNPs, neutralizing with equal volume of 1 M HCl and then detecting DOX content by HPLC. \n\nExosome purification. Exosomes were purified using differential ultracentrifugation method37,38. First, FBS used for cell incubation was centrifuged at $_{100,000\\mathrm{g}}$ overnight to wipe out the existing exosomes. H22 or Bel7402 cells were incubated in exosome-free RPMI 1640 or DMEM medium for $^{48\\mathrm{h}}$ . Cell culture medium was collected and sequentially centrifuged at $1000\\mathrm{g}$ for $10\\mathrm{min}$ , $_{10,000\\mathrm{g}}$ for $30\\mathrm{min}$ and $_{100,000\\mathrm{g}}$ for $^{\\textrm{1h}}$ to pellet exosomes. Exosomes were washed with PBS and recovered by centrifugation at $_{100,000\\mathrm{g}}$ for $^{\\textrm{1h}}$ . \n\nConfirmation of exosomes sheathed on PSiNPs in E-PSiNPs. E-PSiNPs were stained with $10\\upmu\\mathrm{M}$ DiO for $30\\mathrm{min}$ , centrifuged at $20{,}000\\ \\mathrm{g}$ for $30\\mathrm{min}$ and then washed with PBS three times. The colocalization of DiO and PSiNPs was observed by FV1000 confocal microscopy. The fluorescence of DiO at $500{-}520\\mathrm{nm}$ and PSiNPs at $670{-}690\\mathrm{nm}$ was detected at the excitation of $488\\mathrm{nm}$ . \n\nE-PSiNPs was blocked by $5\\%$ BSA for $30\\mathrm{min}$ , and then incubated with FITCconjugated CD63 antibody (Biolegend, 353005, diluted to 1:200) for $30\\mathrm{min}$ at room temperature. The colocalization of CD63 and PSiNPs was observed by FV1000confocal microscopy. The fluorescence of FITC at $500{-}520~\\mathrm{nm}$ and PSiNPs at $670{-}690\\mathrm{nm}$ was detected at the excitation of $488\\mathrm{nm}$ . \n\nWhole cells, the purified exosomes and E-PSiNPs were lysed in RIPA lysis buffer and then subjected to western blot analysis. The primary antibodies used included anti-CD63 (Abcam, ab216130), anti-TSG101 (Santa Cruz, SC-7964) and anti-calnexin (Beyotime, AC018). All primary antibodies were diluted to 1:2000. Uncropped gel images are provided in Source Data file. \n\nE-PSiNPs yield. Bel7402 cells were incubated with $200\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ PSiNPs for $6\\mathrm{h}$ and washed with PBS three times. Then fresh medium containing $200{\\mathrm{nM}}$ \n\nrapamycin, $30\\upmu\\mathrm{M}$ CBZ, $5\\mathrm{mM}$ 3-MA, $15\\mathrm{nM}$ DMA or $10\\upmu\\mathrm{M}$ ionomycin were added. After 16 h incubation, the supernatants were collected, centrifuged at $5000\\mathrm{g}$ for $15\\mathrm{min}$ to remove debris, and then centrifuged at $20{,}000\\ \\mathrm{g}$ for $30\\mathrm{min}$ . The pellets were dissolved in $1\\mathrm{M}\\mathrm{NaOH}$ solution and silicon content was measured by Optima 4300 DV ICP-OES (PerkinElmer, Norwalk, CT, USA). \n\nIn vitro DOX release profile. DOX release profile from $\\mathrm{DOX}@]$ E-PSiNPs was determined by dialysis method. Briefly, DOX $@\\mathrm{I}$ -PSiNPs ( $300\\upmu\\mathrm{g}$ DOX content) were put into a dialysis bag (cutoff molecular weight was $3000\\mathrm{{Da}}$ ) and submerged fully into PBS ( $\\mathrm{30mL}$ ), then stirred with $250\\mathrm{rpm}$ at $37^{\\circ}\\mathrm{C}.$ . At the designated time intervals, $0.5\\mathrm{mL}$ of sample solution was taken out and replaced with equal amount of fresh PBS. DOX content in samples was measured by HPLC. \n\nInteraction between DOX@E-PSiNPs and CSCs by AFM. H22 CSCs were seeded on coverslips pretreated with poly-lysine in 6-well plates at a density of $3\\times10^{5}$ cells per well. H22 CSCs were then incubated with DOX, DOX $@$ PSiNPs or $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs at the DOX concentration of $2\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ at $37^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . After washing with PBS, CSCs were fixed with $0.25\\%$ $\\mathbf{\\tau}(\\mathbf{v}/\\mathbf{v})$ glutaraldehyde for $30\\mathrm{min}$ at room temperature. The coverslips were rinsed with deionized water to remove salt crystals and air dried before analysis. AFM images were obtained using a multimode 8 AFM (Bruker, Santa Barbara, CA, USA). Cell surface studies were performed in ScanAsys mode at scan frequencies below $1\\mathrm{Hz}$ . The roughness of CSCs membrane was analyzed by measurement of Image Rq. \n\nCell membrane fluidity. H22 CSCs membrane fluidity was measured using fluorescence polarization of 1,6-diphenyl-1,3,5-hexatriene $\\mathrm{(DPH)}^{59}$ . Briefly, H22 CSCs ( $10^{6}$ cell per mL) were incubated with DPH $(2\\upmu\\mathrm{M})$ at $37^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . The labeled CSCs were then incubated with DOX, DOX@PSiNPs or $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs at the DOX concentration of $2\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ for $^{2\\mathrm{h}}$ . Fluorescence anisotropy was measured using a polarization spectrofluorometer (FP-6500, Jasco, Tokyo, Japan) with an excitation wavelength of $365\\mathrm{nm}$ and an emission wavelength of $429\\mathrm{nm}$ . Anisotropy was calculated as: $r=(\\mathrm{I_{VV}-I_{V H}.G})/(\\mathrm{I_{VV}+I_{V H.}G})$ , where $G=\\mathrm{I}_{\\mathrm{HV}}/\\mathrm{I}_{\\mathrm{HH}}$ is used to correct the unequal transmission of the optics. \n\nInternalization into bulk cancer cells and CSCs. Bel7402 and H22 cells, and H22 and B16-F10 CSCs selected in soft 3D fibrin gels were seeded into six-well plates overnight at a density of $2\\times10^{5}$ cells per well. Subsequently, cells were incubated with free DOX, DOX $@$ PSiNPs or $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs at different DOX concentrations for $^{2\\mathrm{h}}$ , rinsed with PBS and then collected to analyze the intracellular DOX fluorescence in FL2 channel by flow cytometry (FC500, Beckman Coulter, Fullerton, CA, USA). \n\nCytotoxicity against bulk cancer cells and CSCs. For determination of $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs against bulk cancer cells, Bel7402, H22 and B16-F10 cells were seeded in 96-well plate at a density of $8\\times10^{3}$ cells per well overnight and then treated with free DOX, $\\mathrm{DOX@PSiNPs}$ or $\\scriptstyle\\mathrm{DOX}@\\mathrm{F}$ -PSiNPs at different DOX concentrations. After $24\\mathrm{h}$ treatment, cell survival rate was detected by CCK-8 assay. \n\nTo evaluate cytotoxicity of $\\mathrm{DOX}@1$ E-PSiNPs against CSCs, H22 and B16-F10 cells were pre-treated with DOX, $\\mathrm{DOX}@$ PSiNPs or DOX $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{E}}$ -PSiNPs at different DOX concentrations for $^{4\\mathrm{h}}$ . The cells were harvested, washed and counted. $4\\times10^{2}$ cells from different groups were then seeded in 3D fibrin gels. On the fifth day, the numbers of tumor spheroids in different groups were counted under Olympus IX 71 optical microscope (Tokyo, Japan). Tumor spheroids in each group were imaged and their sizes were calculated by Image J software. \n\nTo further determine cytotoxicity of DOX $\\boldsymbol{\\cdot}(\\omega\\mathrm{E}$ -PSiNPs against CSCs, H22 and B16-F10 CSCs were selected in 3D fibrin gels in 96-well plates. On day 5, the media were aspirated and fresh media containing DOX, DOX@PSiNPs or $\\mathrm{DOX}@\\mathrm{E}$ - PSiNPs at DOX concentration of $2\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ were added. After $24\\mathrm{h}$ incubation, tumor spheroids with integral rims in each group were counted under optical microscope. The images of tumor spheroids in each group were captured and their sizes were calculated by Image J software. \n\nIn vivo biodistribution. When tumor volume of H22 tumor-bearing mice reached ca. $250\\mathrm{mm}^{3}$ , or at 13 days after intravenous injection of B16-F10 cells into C57BL/ 6 mice, the mice were intravenously injected with free DOX, $\\mathrm{DOX@PSiNPs}$ or DOX $\\boldsymbol{\\mathcal{Q}}\\mathrm{E}$ -PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ . At $24\\mathrm{h}$ post-injection, the mice were sacrificed, and the major organs (heart, liver, spleen, lung and kidney) and tumors in H22 tumor-bearing mice and lung metastatic nodules in B16-F10 tumor-bearing mice were collected. Subsequently, tissues were lysed and DOX was extracted by incubating the lysates in $1\\mathrm{MNaOH}$ for $30\\mathrm{min}$ and neutralizing by the same volume of 1 M HCl. DOX contents in the lysates were tested by a FlexStation3 Multi-Mode Microplate Reader (Molecular Devices, Sunnyvale, CA, USA). \n\nIn vitro penetration in 3D tumor spheroids. H22 tumor spheroids were constructed using soft 3D fibrin gel method as described above. To observe penetration of $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs from outside of tumor spheroids to core area, tumor spheroids with diameter of ca. $150\\mathrm{-}200\\upmu\\mathrm{m}$ were treated with free DOX, DOX@PSiNPs or $\\scriptstyle{\\mathrm{DOX}}({\\mathcal{Q}})\\operatorname{E}$ -PSiNPs exocytosed from H22 cells at DOX concentration of $2\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ for $24\\mathrm{h}$ . The spheroids were washed with PBS twice, fixed with $4\\%$ paraformaldehyde for $30\\mathrm{min}$ , and then transferred to confocal dishes. DOX red fluorescence at $570-590\\mathrm{nm}$ was observed by confocal microscopy using Z-stack scanning mode at the intervals of $5\\upmu\\mathrm{m}$ at the excitation of $559\\mathrm{nm}$ . The 3D DOX fluorescence images in tumor spheroids were reconstructed by using Amira software. \n\nIn vivo tumor penetration. When tumor volume of H22 tumor-bearing mice reached ca. $250\\mathrm{mm}^{3}$ , the mice were intravenously injected with DOX, $\\operatorname{DOX}@\\operatorname{P}$ - SiNPs or DOX $@$ E-PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}$ $^{-1}$ . At $24\\mathrm{h}$ post-injection, tumor tissues were collected, washed with PBS, and then frozen-sectioned into pieces. The sections were incubated with FITC-CD31 antibody (Biolegend, 102405, diluted to 1:200) at $37^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ to label tumor vessels, and then rinsed with PBS. DOX red fluorescence at $570{-}600\\mathrm{nm}$ and FITC-CD31 green fluorescence at $500{-}520\\mathrm{nm}$ were observed by confocal microscopy at the excitation of $559\\mathrm{nm}$ or $488\\mathrm{nm}$ , respectively. DOX distribution from blood vessels to deep tumor tissues was measured by Image J Software. \n\nIntercellular delivery. H22 cells were seeded on coverslips, which were pretreated with $10\\upmu\\mathrm{g}\\ \\mathrm{mL}^{-1}$ poly-lysine overnight. Cells on the first coverslip were treated with $2\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ DOX, DOX $@$ PSiNPs or DOX $@$ E-PSiNPs for $6\\mathrm{h}$ . The treated cells were rinsed with PBS and then co-incubated with the new cells on the second coverslip for $16\\mathrm{h}$ in fresh medium. Finally, the cells on the second coverslip were co-incubated with the new cells on the third coverslip for another $16\\mathrm{h}$ in fresh medium. Cells were rinsed with PBS and the intercellular DOX fluorescence at $570\\mathrm{-}600\\mathrm{nm}$ were analyzed by confocal microscope at the excitation of $559\\mathrm{nm}$ and flow cytometry (FL2 channel). \n\nIn vivo DOX accumulation in total tumor cells and CSCs. When tumor volume of GFP-expressing H22 tumor-bearing mice reached ca. $250\\mathrm{mm}^{3}$ , the mice were intravenously injected with free DOX, $\\mathrm{DOX@PSiNPs}$ or $\\mathrm{DOX}@\\mathrm{E}$ -PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ . At $24\\mathrm{h}$ after injection, tumor tissues were collected, washed with PBS and then cut into small pieces, followed by digestion with $1\\mathrm{mg}\\mathrm{mL}^{-1}$ collagenase type I solution at $37^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . The single tumor cells were acquired by filtering the digested cells with 200-mesh nylon twice and then divided into two parts. One part was used to determine DOX content in total GFP-positive tumor cells by flow cytometry in FL2 channel. The other one was applied to determine DOX content in side population cells of GFP-positive tumor cells. The tumor cells were treated with $5\\upmu\\mathrm{g}\\mathrm{\\bar{mL}}^{-1}$ Hoechst 33342 for $90\\mathrm{min}$ in the presence or absence of $50\\upmu\\mathrm{m}$ verapamil at $37^{\\circ}\\mathrm{C}$ in the dark. Living cells were plotted on SSC-A and FSC-A graph. Hoechst 33342 fluorescence at $450\\mathrm{nm}$ or $660\\mathrm{nm}$ in living GFP-positive tumor cells was measured. The gating of side population cells was plotted as the absence of cell population in PBS-treated group comparted with verapamil-treated group. DOX fluorescence intensity in side population cells was detected by flow cytometry (FL2 channel). \n\nAnticancer activity in subcutaneous H22 tumor-bearing mice. When tumor volume of H22 tumor-bearing mice reached ca. $200\\mathrm{mm}^{3}$ , the mice were intravenously injected with PBS, E-PSiNPs, free DOX, DOX@PSiNPs, $\\mathrm{DOX}@\\$ E-PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ once every three days $\\overset{\\cdot}{n}=14$ per group). The tumor sizes were measured every day via vernier caliper and the body weights of mice were also recorded. On 17th day of treatment, mice were further divided into two groups. One group $(n=8)$ ) was used for survival experiment, while the other part $(n=6)$ was used to estimate anticancer efficacy. For anticancer efficacy analysis, mice were sacrificed, and tumors and major organs (heart, liver, spleen, lung and kidney) were obtained and washed with PBS. The cleaned tumors were weighed and fixed with $4\\%$ paraformaldehyde, then sectioned and stained using a TUNEL assay kit according to the manufacturer’s protocol. The major organs were also fixed with $4\\%$ paraformaldehyde, sectioned and examined by H&E staining. \n\nTo estimate CSCs killing activity of $\\mathrm{DOX}@\\mathrm{F}$ -PSiNPs in vivo, tumor tissues were digested into single cells after treatment as above using $1\\mathrm{mg}\\mathrm{mL}^{-1}$ collagenase type I solution. One part of cells were used to determine the number of CD133-positive cells by flow cytometry. The second part of cells were seeded in soft 3D fibrin gels (400 cells per well) and incubated for 5 days42,43. The numbers of tumor spheroids were counted under optical microscope. The images of tumor spheroids were captured and their sizes were calculated by Image J software. The third part of cells were subcutaneously transplanted into $_{\\mathrm{BALB/c}}$ mice ( $10^{6}$ cells per mouse) and the tumor formation ratio was evaluated. Furthermore, the anticancer treatment was performed in the GFP-expressing H22-tumor bearing mice as above. On 17th day of treatment, the mice were sacrificed and tumor tissues were digested into single cells. The cells were dyed with $5\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ Hoechst 33342 for $90\\mathrm{min}$ at $37^{\\circ}\\mathrm{C}$ in the presence or absence of $50\\upmu\\mathrm{M}$ verapamil in the dark, then washed and resuspended in PBS. The number of side population cells in GFP-positive tumor cells was measured by flow cytometry (450/45 BP filter for blue fluorescence and 660/20 BP filter for red fluorescence). \n\nAnticancer activity in orthotopic 4T1 breast cancer mode. 4T1 cells $(2\\times10^{5}$ cells) were suspended in $50\\upmu\\mathrm{L}$ PBS and then injected into the right forth breast fat pad. When the tumor volume reached $50{-}70\\mathrm{mm}^{3}$ , the mice were administrated with PBS, E-PSiNPs, free DOX, DOX $@$ PSiNPs or DOX@E-PSiNPs at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or high dosage of DOX at $4\\mathrm{mg}\\mathrm{kg}^{-1}$ once every three days for five times $\\overset{\\cdot}{n}=14$ per group). The tumor sizes were measured every day via vernier caliper. On 15th day of treatment, mice were further divided into two groups. One group $(n=8)$ was used for survival experiment, while the other part $(n=6)$ was used to estimate anticancer efficacy. \n\nTo investigate CSCs killing activity of DOX@E-PSiNPs in vivo, tumor tissues were collected and digested into single cells using $1\\mathrm{mg}\\mathrm{mL}^{-1}$ collagenase type I solution. The cells (400 tumor cells per well) were seeded in soft 3D fibrin gels. On day 5, the numbers of tumor spheroids were counted under optical microscope. The images of tumor spheroids were captured and their sizes were calculated by Image J software. \n\nAnticancer activity in B16-F10 lung metastasis cancer model. At $^{48\\mathrm{h}}$ after B16- F10 cells $\\langle5\\times10^{5}$ cells per mouse) were intravenously injected into C57BL/6 mice, the mice were intravenously administrated with PBS, E-PSiNPs, free DOX, DOX@PSiNPs, DOX $\\varrho\\mathrm{E}$ -PSiNPs exocytosed from H22 cells at DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ once every three days $\\overset{\\cdot}{n}=$ 14 per group). On 13th day of treatment, mice were divided into two parts. One part $\\mathrm{(n=8)}$ was used for long-term survival experiment and the other part $(n=6)$ was used for evaluation of anticancer effect. For evaluation of anticancer effect, the mice were sacrificed and the lungs were acquired. The numbers of tumor nodules on the surface of lungs were recorded. Lungs were then fixed with $4\\%$ paraformaldehyde, sectioned and examined by H&E staining. \n\nTo investigate CSCs killing activity of DOX@E-PSiNPs in vivo, tumor nodules were collected and digested into single cells using $1\\mathrm{mg}\\mathrm{mL}^{-1}$ collagenase type I solution. The cells (400 tumor cells per well) were seeded in soft 3D fibrin gels. On day 5, the numbers of tumor spheroids were counted under optical microscope. The images of tumor spheroids were captured and their sizes were calculated by Image J software. \n\nImmune response. C57BL/6 mice were intravenously injected with PBS, EPSiNPs, DOX, DOX@PSiNPs, DOX@E-PSiNPs exocytosed from H22 cells at the DOX dosage of $0.5\\mathrm{mg}\\mathrm{kg}^{-1}$ , or free DOX at high dosage of $4\\mathrm{mg}\\mathrm{kg}^{-1}$ . At different time intervals, the orbital blood was obtained, maintained for $30\\mathrm{min}$ and centrifuged at $_{10,000\\mathrm{g}}$ for $10\\mathrm{min}$ . The serum was collected and the contents of IgM, $\\mathrm{IL}{-}1\\upbeta$ , IL-6, and TNF- $\\mathtt{a}$ were analyzed by enzyme linked immunosorbent assay (ELISA). \n\nStatistical analysis. Experiments were performed with at least three replicates. All values were presented as mean values $\\pm\\thinspace\\mathrm{SD}$ . Statistical analyses were carried out using the GraphPad Prism software version 6.0. Comparison between two groups was performed using unpaired two-tailed Student’s t test. One-way ANOVA or two-way ANOVA was used for comparison of more than two groups. Statistical significance for survival curves was determined using a log-rank test. Values with $P$ $<\\dot{0}.05$ are considered significant. \n\nReporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nThe authors declare that the main data supporting the findings of this study are available within the article and its Supplementary Information. Extra data are available from the corresponding author upon reasonable request. The source data underlying Figs. 2–9 and Supplementary Figs. 1–39 are provided with the paper as a Source Data file. A reporting summary for this article is available as a Supplementary Information file. \n\nReceived: 9 February 2018 Accepted: 29 July 2019 \nPublished online: 23 August 2019 \n\n# References \n\n1. Peer, D. et al. Nanocarriers as an emerging platform for cancer therapy. Nat. Nanotech. 2, 751–760 (2007). \n2. Maeda, H., Nakamura, H. & Fang, J. The EPR effect for macromolecular drug delivery to solid tumors: improvement of tumor uptake, lowering of systemic toxicity, and distinct tumor imaging in vivo. Adv. Drug Deliv. Rev. 65, 71–79 (2013). \n3. Mitragotri, S., Burke, P. A. & Langer, R. Overcoming the challenges in administering biopharmaceuticals: formulation and delivery strategies. Nat. Rev. Drug Discov. 13, 655–672 (2014). \n4. Cheng, C. J. et al. A holistic approach to targeting disease with polymeric nanoparticles. Nat. Rev. Drug Discov. 14, 239–247 (2015). \n5. Salvati, A. et al. Transferrin-functionalized nanoparticles lose their targeting capabilities when a biomolecule corona adsorbs on the surface. Nat. Nanotechnol. 8, 137–143 (2013). \n6. Magee, J. A., Piskounova, E. & Morrison, S. J. Cancer stem cells: impact, heterogeneity, and uncertainty. Cancer Cell 21, 283–296 (2012). \n7. Zhao, Y., Alakhova, D. Y. & Kabanov, A. V. Can nanomedicines kill cancer stem cells? Adv. Drug Deliv. Rev. 65, 1763–1783 (2013). \n8. Tan, S. et al. Cell or cell membrane-based drug delivery systems. Theranostics 5, 863–881 (2015). \n9. Luk, B. T. & Zhang, L. Cell membrane-camouflaged nanoparticles for drug delivery. J. Control. Release 220, 600–607 (2015). \n10. Gao, W. et al. Surface functionalization of gold nanoparticles with red blood cell membranes. Adv. Mater. 25, 3549–3553 (2013). \n11. Piao, J. G. et al. Erythrocyte membrane is an alternative coating to polyethylene glycol for prolonging the circulation lifetime of gold nanocages for photothermal therapy. ACS Nano 8, 10414–10425 (2014). \n12. Chen, Z. et al. Cancer cell membrane-biomimetic nanoparticles for homologous-targeting dual-modal imaging and photothermal therapy. ACS Nano 10, 10049–10057 (2016). \n13. Sun., H. et al. Cancer-cell-biomimetic nanoparticles for targeted therapy of homotypic tumors. Adv. Mater. 28, 9581–9588 (2016). \n14. Wei., X. et al. Nanoparticles camouflaged in platelet membrane coating as an antibody decoy for the treatment of immune thrombocytopenia. Biomaterials 111, 116–123 (2016). \n15. Parodi, A. et al. Synthetic nanoparticles functionalized with biomimetic leukocyte membranes possess cell-like functions. Nat. Nanotechnol. 8, 61–68 (2013). \n16. Thery, C., Zitvogel, L. & Amigorena, S. Exosomes: composition, biogenesis and function. Nat. Rev. Immunol. 2, 569–579 (2002). \n17. Batrakova, E. V. & Kim, M. S. Using exosomes, naturally-equipped nanocarriers, for drug delivery. J. Control. Release 219, 396–405 (2015). \n18. van den Boorn, J. G. et al. Exosomes as nucleic acid nanocarriers. Adv. Drug Deliv. Rev. 65, 331–335 (2013). \n19. Vader, P. et al. Extracellular vesicles for drug delivery. Adv. Drug Deliv. Rev. 106, 148–156 (2016). \n20. Frydrychowicz, M. et al. Exosomes–structure, biogenesis and biological role in non-small-cell lung cancer. Scand. J. Immunol. 81, 2–10 (2015). \n21. Jang, S. C. et al. Bioinspired exosome-mimetic nanovesicles for targeted delivery of chemotherapeutics to malignant tumors. ACS Nano 7, 7698–7710 (2013). \n22. Sato, Y. T. et al. Engineering hybrid exosomes by membrane fusion with liposomes. Sci. Rep. 6, 21933 (2016). \n23. Fuhrmann, G. et al. Active loading into extracellular vesicles significantly improves the cellular uptake and photodynamic effect of porphyrins. J. Control. Release 205, 35–44 (2015). \n24. Haney, M. J. et al. Exosomes as drug delivery vehicles for Parkinson’s disease therapy. J. Control. Release 207, 18–30 (2015). \n25. Park, J. H. et al. Biodegradable luminescent porous silicon nanoparticles for in vivo applications. Nat. Mater. 8, 331–836 (2009). \n26. Yong, T. et al. Domino-like intercellular delivery of undecylenic acidconjugated porous silicon nanoparticles for deep tumor penetration. ACS Appl. Mater. Interfaces 8, 27611–27621 (2016). \n27. Fontana, F. et al. Multistaged nanovaccines based on porous silicon@acetalated dextran@cancer cell membrane for cancer immunotherapy. Adv. Mater. 29, 1603239 (2017). \n28. Xu, R. et al. An injectable nanoparticle generator enhances delivery of cancer therapeutics. Nat. Biotechnol. 34, 414–418 (2016). \n29. Wareing, N. et al. In vitro gene delivery with large porous silicon nanoparticles fabricated using cost-effective, metal-assisted chemical etching. Small 13, 1602739 (2017). \n30. Gu, L. et al. Multivalent porous silicon nanoparticles enhance the immune activation potency of agonistic CD40 antibody. Adv. Mater. 24, 3981–3987 (2012). \n31. Visvader, J. E. & Lindeman, G. J. Cancer stem cells in solid tumours: accumulating evidence and unresolved questions. Nat. Rev. Cancer 8, 755–768 (2008). \n32. Beck, B. & Blanpain, C. Unravelling cancer stem cell potential. Nat. Rev. Cancer 13, 727–738 (2013). \n33. Ho, M. M. et al. Side population in human lung cancer cell lines and tumors is enriched with stem-like cancer cells. Cancer Res. 67, 4827–4833 (2007). \n34. Nakanishi, T. et al. Side-population cells in luminal-type breast cancer have tumour-initiating cell properties, and are regulated by HER2 expression and signalling. Br. J. Cancer 102, 815–826 (2010). \n35. Levine, B., Mizushima, N. & Virgin, H. W. Autophagy in immunity and inflammation. Nature 469, 323–335 (2011). \n36. Kabeya, Y. et al. LC3, a mammalian homologue of yeast Apg8p, is localized in autophagosome membranes after processing. EMBO J. 19, 5720–5728 (2000). \n37. Rao, Q. et al. Tumor-derived exosomes elicit tumor suppression in murine hepatocellular carcinoma models and humans in vitro. Hepatology 64, \n456–472 (2016). \n38. Saari, H. et al. Microvesicle- and exosome-mediated drug delivery enhances the cytotoxicity of Paclitaxel in autologous prostate cancer cells. J. Control. Release 220, 727–737 (2015). \n39. Lobb, R. J. et al. Optimized exosome isolation protocol for cell culture supernatant and human plasma. J. Extracell. Vesicles 4, 27031 (2015). \n40. Miao, Y. et al. A TRP channel senses lysosome neutralization by pathogens to trigger their expulsion. Cell 161, 1306–1319 (2015). \n41. Hoffman, E. A. et al. Regulation of myocilin-associated exosome release from human trabecular meshwork cells. Invest. Ophthalmol. Vis. Sci. 50, 1313–1318 (2009). \n42. Liu, J. et al. Soft fibrin gels promote selection and growth of tumorigenic cells. Nat. Mater. 11, 734–741 (2012). \n43. Ma., J. et al. Reversing drug resistance of soft tumor-repopulating cells by tumor cell-derived chemotherapeutic microparticles. Cell Res. 26, 713–727 (2016). \n44. Peetla, C., Vijayaraghavalu, S. & Labhasetwar, V. Biophysics of cell membrane lipids in cancer drug resistance: implications for drug transport and drug delivery with nanoparticles. Adv. Drug Deliv. Rev. 65, 1686–1698 (2013). \n45. Clevers, H. The cancer stem cell: premises, promises and challenges. Nat. Med. \n17, 313–319 (2011). \n46. Wang., X. et al. Epirubicin-adsorbed nanodiamonds kill chemoresistant hepatic cancer stem cells. ACS Nano 8, 12151–12166 (2014). \n47. Rao, W. et al. Chitosan-decorated doxorubicin-encapsulated nanoparticle targets and eliminates tumor reinitiating cancer stem-like cells. ACS Nano 9, \n5725–5740 (2015). \n48. Liu, J. et al. A tailored DNA nanoplatform for synergistic RNAi/chemotherapy of multidrug-resistant tumors. Angew. Chem. Int. Ed. Engl. 57, 15486–15490 (2018). \n49. Shen, H. et al. Coating solid lipid nanoparticles with hyaluronic acid enhances antitumor activity against melanoma stem-like cells. Theranostics 5, 755–771 (2015). \n50. Ning, S. T. et al. Targeting colorectal cancer stem-like cells with anti-CD133 antibody-conjugated SN-38 nanoparticles. ACS Appl. Mater. Interfaces 8, \n17793–17804 (2016). \n51. Yang, Z. F. et al. Significance of $\\mathrm{CD90^{+}}$ cancer stem cells in human liver cancer. Cancer Cell 13, 153–166 (2008). \n52. Shen, S., Xia, J. X. & Wang, J. Nanomedicine-mediated cancer stem cell therapy. Biomaterials 74, 1–18 (2016). \n53. Fang, R. H. et al. Engineered nanoparticles mimicking cell membranes for toxin neutralization. Adv. Drug Deliv. Rev. 90, 69–80 (2015). \n54. Hessvik, N. P. & Llorente, A. Current knowledge on exosome biogenesis and release. Cell. Mol. Life Sci. 75, 193–208 (2018). \n55. Lin, J. et al. Inhibition of autophagy enhances the anticancer activity of silver nanoparticles. Autophagy 10, 2006–2020 (2014). \n56. Wu, L. et al. Tuning cell autophagy by diversifying carbon nanotube surface chemistry. ACS Nano 8, 2087–2099 (2014). \n57. Ha, S. W., Weitzmann, M. N. & Beck, G. R. Jr. Bioactive silica nanoparticles promote osteoblast differentiation through stimulation of autophagy and direct association with LC3 and p62. ACS Nano 8, 5898–5910 (2014). \n58. Jarvis, K. L., Barnes, T. J. & Prestidge, C. A. Surface chemistry of porous silicon and implications for drug encapsulation and delivery applications. Adv. Colloid Interface Sci. 175, 25–38 (2012). \n59. Xiao, L. et al. Role of cellular uptake in the reversal of multidrug resistance by PEG-b-PLA polymeric micelles. Biomaterials 32, 5148–5157 (2011). \n\n# Acknowledgements \n\nThis work was supported by National Basic Research Program of China (2018YFA0208900 and 2015CB931800), National Natural Science Foundation of China (81627901, 81672937, 81773653 and 81803018), Program for HUST Academic Frontier Youth Team (2018QYTD01), Program for Changjiang Scholars and Innovative Research Team in University (IRT13016), Academy of Finland (297580), Sigrid Jusélius Foundation (28001830K1 and 4704580), HiLIFE Research Funds and the European Research Council proof-of-concept grant (decision no. 825020). We thank the Research Core Facilities for Life Science (HUST), the Analytical and Testing Center of Huazhong University of Science and Technology and Wuhan institute of biotechnology for related analysis. \n\n# Author contributions \n\nL.G., H.A.S., and X.Y. designed the project. T.Y., Xiaoqiong Z., N.B., H.Z., Xuting Z., F.L., A.H., and J.H. performed the experiments. T.Y., Xiaoqiong Z., N.B., H.Z., L.G., H.A.S. and X.Y. analyzed and interpreted the data, and wrote the paper \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-11718-4. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nPeer review information: Nature Communications thanks Jeffery Coffer and other anonymous reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1088_0256-307X_36_7_076801", + "DOI": "10.1088/0256-307X/36/7/076801", + "DOI Link": "http://dx.doi.org/10.1088/0256-307X/36/7/076801", + "Relative Dir Path": "mds/10.1088_0256-307X_36_7_076801", + "Article Title": "Experimental Realization of an Intrinsic Magnetic Topological Insulator", + "Authors": "Gong, Y; Guo, JW; Li, JH; Zhu, KJ; Liao, MH; Liu, XZ; Zhang, QH; Gu, L; Tang, L; Feng, X; Zhang, D; Li, W; Song, CL; Wang, LL; Yu, P; Chen, X; Wang, YY; Yao, H; Duan, WH; Xu, Y; Zhang, SC; Ma, XC; Xue, QK; He, K", + "Source Title": "CHINESE PHYSICS LETTERS", + "Abstract": "An intrinsic magnetic topological insulator (TI) is a stoichiometric magnetic compound possessing both inherent magnetic order and topological electronic states. Such a material can provide a shortcut to various novel topological quantum effects but remained elusive experimentally for a long time. Here we report the experimental realization of thin films of an intrinsic magnetic TI, MnBi2Te4, by alternate growth of a Bi2Te3 quintuple layer and a MnTe bilayer with molecular beam epitaxy. The material shows the archetypical Dirac surface states in angle-resolved photoemission spectroscopy and is demonstrated to be an antiferromagnetic topological insulator with ferromagnetic surfaces by magnetic and transport measurements as well as first-principles calculations. The unique magnetic and topological electronic structures and their interplays enable the material to embody rich quantum phases such as quantum anomalous Hall insulators and axion insulators at higher temperature and in a well-controlled way.", + "Times Cited, WoS Core": 554, + "Times Cited, All Databases": 626, + "Publication Year": 2019, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000475395200016", + "Markdown": "EXPRESS LETTER \n\n# Experimental Realization of an Intrinsic Magnetic Topological Insulator \n\n# Recent citations \n\n- Intrinsic magnetic topological insulators in van der Waals layered MnBi2Te4-family materials \nJiaheng Li et al \n\nTo cite this article: Yan Gong et al 2019 Chinese Phys. Lett. 36 076801 \n\nView the article online for updates and enhancements. \n\n# Experimental Realization of an Intrinsic Magnetic Topological Insulator ∗ \n\nYan Gong(龚演)1, Jingwen Guo(郭景文)1, Jiaheng Li(李佳恒)1, Kejing Zhu(朱科静)1, \nMenghan Liao(廖孟涵)1, Xiaozhi Liu(刘效治)2, Qinghua Zhang(张庆华)2, Lin Gu(谷林)2, Lin Tang(唐林)1, Xiao Feng(冯硝)1, Ding Zhang(张定)1,3,4, Wei Li(李渭)1,4, Canli Song(宋灿立)1,4, Lili Wang(王立莉)1,4, \nPu Yu(于浦)1,4, Xi Chen(陈曦)1,4, Yayu Wang(王亚愚)1,3,4, Hong Yao(姚宏)4,5, Wenhui Duan(段文晖)1,3,4, Yong Xu(徐勇)1,4,6\\*\\*, Shou-Cheng Zhang(张首晟)7, Xucun Ma(马旭村)1,4, Qi-Kun Xue(薛其坤)1,3,4\\*\\*, Ke He(何珂)1,3,4\\*\\* $^1$ State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084 \n$^2$ Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 3Beijing Academy of Quantum Information Sciences, Beijing 100193 4Collaborative Innovation Center of Quantum Matter, Beijing 100084 5Institute for Advanced Study, Tsinghua University, Beijing 100084 $^6$ RIKEN Center for Emergent Matter Science (CEMS), Wako, Saitama 351-0198, Japan \n$^7$ Stanford Center for Topological Quantum Physics, Department of Physics, Stanford University, Stanford, California 94305-4045, USA \n\n# (Received 27 May 2019) \n\nAn intrinsic magnetic topological insulator (TI) is a stoichiometric magnetic compound possessing both inherent magnetic order and topological electronic states. Such a material can provide a shortcut to various novel topological quantum effects but remained elusive experimentally for a long time. Here we report the experimental realization of thin films of an intrinsic magnetic TI, $M n B i_{2}T e_{4}$ , by alternate growth of a $B i_{2}T e_{3}$ quintuple layer and a MnTe bilayer with molecular beam epitaxy. The material shows the archetypical Dirac surface states in angle-resolved photoemission spectroscopy and is demonstrated to be an antiferromagnetic topological insulator with ferromagnetic surfaces by magnetic and transport measurements as well as first-principles calculations. The unique magnetic and topological electronic structures and their interplays enable the material to embody rich quantum phases such as quantum anomalous Hall insulators and axion insulators at higher temperature and in a well-controlled way. \n\nPACS: 68.35.bg, 73.23.Ad, 71.20.Nr, 73.20.At \n\nDOI: 10.1088/0256-307X/36/7/076801 \n\nA topological insulator (TI) is non-magnetic, carrying gapless surface electronic states topologically protected by the time-reversal symmetry (TRS).[1,2] Many exotic quantum effects predicted in TIs, however, need the TRS to be broken by acquired magnetic order.[3] A remarkable example is the quantum anomalous Hall (QAH) effect, a zero-magneticfield quantum Hall effect that had been sought for over two decades until it was observed in a magnetic TI with ferromagnetic (FM) order induced by magnetic dopants. $\\left[3-7\\right]$ The experimental realization of the QAH effect paved the road for hunting many other novel quantum effects in TRS-broken TIs, for example, topological magnetoelectric (TME) effects and chiral Majorana modes.[3,8,9] However, magnetically doped TIs are notorious “dirty\" materials for experimental studies: the randomly distributed magnetic impurities induce strong inhomogeneity in the electronic structure and magnetic properties, and the sample quality is sensitive to the details of the molecular beam epitaxy (MBE) growth conditions.[10−12] Such a complicated system is often a nightmare for some delicate experiments such as those on chiral Majorana modes and topological quantum computation, and the strong inhomogeneity is believed to contribute to the extremely low temperature (usually $<$ <100 mK) required by the QAH effect.[13] An ideal magnetic TI is an intrinsic one, namely a stoichiometric compound with orderly arranged and exchange-coupled magnetic atoms, which features a magnetically ordered ground state, but becomes a TI when the TRS recovers above the magnetic ordering temperature. A thin film of such an intrinsic magnetic TI could be a congenital QAH insulator with homogeneous electronic and magnetic properties, and presumably higher QAH working temperature. Yet few experimental progresses were achieved in this direction in spite of several interesting theoretical proposals raised in past years.[14−16] \n\nSome stoichiometric ternary tetradymite compounds, which can be considered as variants of wellstudied Bi2Te3 family 3D TIs, have been found to be also 3D TIs.[17] A simplest system is $\\mathrm{XB_{2}T_{4}}$ where X is Pb, Sn or Ge, B is Bi or Sb, and T is Te or Se. Such a compound is a layered material with each septuple-layer (SL) composed of single atomic sheets stacking in the sequence T–B–T– X–T–B–T. If X is a magnetic element, there will be a chance that XB2T4 is an intrinsic magnetic TI. \n\nA few works have observed $\\mathrm{MnBi_{2}T e(S e)_{4}}$ in multicrystalline samples, or as the second phase or surface layer of $\\mathrm{Bi_{2}T e(S e)_{3}}$ , without figuring out their topological electronic properties. $\\big[\\begin{array}{r l}\\end{array}\\big]$ Interestingly, an SL of $\\mathrm{MnBi_{2}T e(S e)_{4}}$ on $\\mathrm{Bi_{2}T e(S e)_{3}}$ was reported to be able to open a large magnetic gap at the topological surface states of the latter.[20,21] \n\nIn this study, we find that high-quality $\\mathrm{MnBi_{2}T e_{4}}$ films can be fabricated in an SL-by-SL manner by alternate growth of 1 quintuple layer (QL) of $\\mathrm{Bi_{2}T e_{3}}$ and 1 bilayer (BL) of MnTe with MBE. Amazingly, MnBi2Te4 films with the thickness $d\\geq2$ SLs show Dirac-type surface states, a characteristic of a 3D TI. Low temperature magnetic and transport measurements as well as first-principles calculations demonstrate that MnBi2Te $^4$ is an intrinsic antiferromagnetic (AFM) TI, composed of ferromagnetic SLs with a perpendicular easy axis, which are coupled antiferromagnetically between neighboring SLs. Remarkably, a thin film of such an AFM TI thin film with FM surfaces is expected to be an intrinsic QAH insulator or axion insulator depending on the film thickness. \n\nTo prepare a $\\mathrm{MnBi_{2}T e_{4}}$ film, we first grow a 1-QL $\\mathrm{{Bi_{2}T e_{3}}}$ film on a Si(111) or $\\mathrm{SrTiO_{3}}$ (111) substrate (see the supplementary materials).[22] Mn and Te are then co-evaporated onto $\\mathrm{Bi_{2}T e_{3}}$ surface with the coverage corresponding to a MnTe BL with the sample kept at $200\\mathrm{{^\\circC}}$ . Post-annealing at the same temperature for $10\\mathrm{{min}}$ is carried out to improve the crystalline quality. This leads to the formation of an SL of $\\mathrm{MnBi_{2}T e_{4}}$ [see the schematic in Fig. 1(a)],[20] as experimentally proved and theoretically explained below. Then on the MnBi2Te $_4$ surface, we grow another QL of $\\mathrm{Bi_{2}T e_{3}}$ , which is followed by deposition of another BL of MnTe and post-annealing. By repeating this procedure, we can grow a $\\mathrm{MnBi_{2}T e_{4}}$ film SL by SL in a controlled way, in principle up to any desired thickness. \n\n![](images/bbe7102344dd558afbae45e665f9386da91e4ecc4c8e22cf500095b8f966bf68.jpg) \nFig. 1. MBE growth and structural characterizations of $\\mathrm{MnBi_{2}T e_{4}}$ films. (a) Schematic illustrations of the MBE growth process of 1 septuple layer (SL) $\\mathrm{MnBi_{2}T e_{4}}$ thin film. (b) XRD pattern of a $\\mathrm{MnBi_{2}T e_{4}}$ (MBT) film grown on Si(111). (c) Cross-sectional HAADF-STEM image of a 5-SL $\\mathrm{MnBi_{2}T e_{4}}$ film grown on a Si (111) substrate. (d) Zoom-in view of (c) with the structural model of $\\mathrm{MnBi_{2}T e_{4}}$ . (e) Intensity distribution of HAADF-STEM along Cut 1 in (c). (f) EELS spectra mapping along Cut 2 in (c). The pink curve shows the intensity distribution of the Mn $L_{2,3}$ -edge along Cut 2 in (c). \n\nThe $\\mathrm{MnBi_{2}T e_{4}}$ film shows sharp $1\\times1$ reflection high-energy electron diffraction streaks (Fig. S1) indicating its flat surface morphology and high crystalline quality. The x-ray diffraction (XRD) pattern [Fig. 1(c), taken from a 7-SL $\\mathrm{MnBi_{2}T e_{4}}$ film] exhibits a series of peaks (marked by blue arrows), most of which can neither be attributed to Bi2Te3 nor to MnTe. From the positions of these XRD peaks, we can estimate the spacing between the crystalline planes to be ${\\sim}1.36\\mathrm{nm}$ , very close to the inter-SL distance of bulk $\\mathrm{MnBi_{2}T e_{4}}$ $\\mathrm{1.356nm},$ predicted by our first-principles calculations. \n\nHigh resolution scanning transmission electron microscopy (STEM) was used to characterize the realspace crystalline structure of a $\\mathrm{MnBi_{2}T e_{4}}$ film (5 SLs). The high-angle annular dark field (HAADF) images [Figs. 1(a) and 1(b)] clearly show the characteristic SL structure of $\\mathrm{XB_{2}T_{4}}$ compounds, except for the region near the substrate where stack faults and dislocations are observed. Figure 1(e) displays the intensity profile along an atomic row across two SLs [Cut 1 in Fig. 1(c)]. One can see that the atomic contrast varies a lot at different positions in an SL. The contrast of an atom in an HAADF-STEM image is directly related to its atomic number. The intensity distribution along an SL is thus well consistent with the Te–Bi– Te–Mn–Te–Bi–Te sequence. The electron energy lose spectroscopy (EELS) [Fig. 1(f)] reveals the Mn $\\boldsymbol{L}_{2,3}$ edges at ${\\sim}645\\mathrm{eV}$ . The intensity distribution curve of EELS at $645\\mathrm{eV}$ [the pink line in Fig. 1(f)] taken along Cut 2 in Fig. 1(c) shows a peak at the middle atom of each SL, which also agrees with the $\\mathrm{MnBi_{2}T e_{4}}$ structure. \n\nThe in situ angle-resolved photoemission spectroscopy (ARPES) was used to map the electronic energy band structure of the MBE-grown MnBi2Te4 films. Figures 2(a)–2(d) show the ARPES bandmaps of the MnBi2Te4 films with the thickness $d\\ =\\ 1$ , 2, 5, 7 SLs, respectively, with the sample temperature at ${\\sim}25\\mathrm{K}$ (the lowest temperature that the sample stage can reach with liquid helium). The spectra were taken around the $\\varGamma$ point along the $M{-}I{-}$ $M$ direction of the Brillouin zone. The spectra of the $d\\ =\\ 1$ SL sample [Fig. 2(a)] shows a bandgap with Fermi level cutting the conduction band. The films with $d\\ \\geq\\ 2\\operatorname{SLs}$ all show similar band structures [Figs. 2(b)–2(d)]. One can always observe a pair of energy bands with nearly linear band dispersion crossing at the $\\varGamma$ point forming a Dirac cone. Figures 2(e) and 2(f) show the momentum distribution curves (MDCs) and the constant-energy contours of the 7-SL sample, respectively, which exhibit archetypal Dirac-type energy bands. It is worth noting that the Dirac-type bands are quite different from the topological surface states of $\\mathrm{Bi_{2}T e_{3}}$ .[23,24] The band dispersion observed here is rather isotropic, as shown by the nearly circular constant-energy contours, even at the energy far away from the Dirac point, which is distinct from the strongly warped $\\mathrm{Bi_{2}T e_{3}}$ topological surface states.[24,25] The Dirac point observed here is located right in the band gap, in contrast with the Bi2Te3 case where the Dirac point is below the valence band maximum. Moreover, the Fermi velocity near the Dirac point is $5.5{\\pm}0.5{\\times}10^{5}\\mathrm{m/s}$ , obviously larger than that of $\\mathrm{Bi_{2}T e_{3}}$ surface states $(3.87{-}4.05{\\times}10^{5}\\mathrm{m/s}$ in different directions).[24] Therefore the Dirac-type bands can only be attributed to $\\mathrm{MnBi_{2}T e_{4}}$ and are the topological surface states of a 3D TI as demonstrated below. \n\n![](images/83b924faf0cb1d88a42942950ed8e9cb77b2f0de0d6319dae15c8c58e243c0be.jpg) \nFig. 2. Energy band structures of $\\mathrm{MnBi_{2}T e_{4}}$ films measured by ARPES. (a)–(d) ARPES spectra of 1, 2, 5, 7- SL $\\mathrm{MnBi_{2}T e_{4}}$ films measured near the $\\boldsymbol{\\varGamma}$ point, along the $M{-}I{-}M$ direction. (e) Momentum distribution curves (MDCs) of the 7-SL film from $E_{\\mathrm{F}}$ to $-0.38\\mathrm{eV}$ . The red triangles indicate the peak positions. (f) Constant energy contours of the 7-SL film at different energies. All the ARPES data were taken at $25\\mathrm{K}$ . \n\nThe orderly and compactly arranged Mn atoms in MnBi2Te $^{\\mathrm{:4}}$ are expected to give rise to a long-range magnetic order at low temperature. Figure 3(a) displays the magnetization $M$ of a 7-SL $\\mathrm{MnBi_{2}T e_{4}}$ film versus magnetic field $H$ , measured with a superconducting quantum interference device (SQUID) at different temperatures $T$ . The linear diamagnetic background contributed by the substrate and capping layer has been subtracted (the raw data are shown in Fig. S2 in the supplementary materials). The unit of $M$ is the magnetic moment $\\mu_{\\mathrm{B}}$ per in-plane unit cell (2D U.C.), i.e. the average magnetic moment of each Mn atom multiplied by the number of SLs. $H$ is applied perpendicularly to the sample plane. With decreasing temperature, hysteresis appears in the $M{-}H$ curves and grows rapidly, exhibiting a typical FM behavior. The Curie temperature $T_{\\mathrm{C}}$ is $20\\mathrm{K}$ according to the temperature dependence of the remnant magnetization $\\lfloor M_{\\mathrm{r}}\\ =\\ M(0\\mathrm{T})\\rfloor$ shown in Fig. 3(b). The 𝑀– $H$ curve measured with in-plane magnetic field has much smaller hysteresis than the curve measured with perpendicular one [see the inset in Fig. 3(a), which was taken from another 7-SL MnBi2Te $^4$ sample]. Therefore the magnetic easy axis is along the $c$ direction [perpendicular to the (0001) plane]. Estimated from the saturation magnetization $M_{\\mathrm{s}}=8\\mu_{\\mathrm{s}}/2\\mathrm{D}$ U.C., the \n\nMn atomic magnetic moment is about $1.14\\mu_{\\mathrm{s}}$ , which is much smaller than $5\\mu_{\\mathrm{s}}$ expected for $\\mathrm{Mn^{2+}}$ ions. It suggests that $\\mathrm{Mn^{2+}}$ ions in the material may have a more complex magnetic structure than a simple uniform ferromagnetic configuration. \n\n![](images/91f9a4cb863cfc0449e6256c98728447143d9c077ebb29d0f0e2d4c64d678964.jpg) \nFig. 3. Magnetic and magneto-transport properties of $\\mathrm{MnBi_{2}T e_{4}}$ films. (a) Magnetization vs magnetic field $(M-$ $H^{'}$ ) of the 7-SL $\\mathrm{MnBi_{2}T e_{4}}$ film measured with SQUID at $3\\mathrm{K}$ (red), $15\\mathrm{K}$ (light green), $20\\mathrm{K}$ (green), and $30\\mathrm{K}$ (blue), respectively. $H$ is perpendicular to the sample plane. The inset shows the $M{-}H$ curves measured with $H$ perpendicular to (red) and in (blue) the sample plane (a different 7-SL $\\mathrm{MnBi_{2}T e_{4}}$ sample). (b) Temperature dependences of the remnant magnetization $(M_{\\mathrm{r}})$ and zero-magnetic-field Hall resistance $(R_{y x}^{0})$ of the 7-SL film, which give the Curie temperature $(T_{\\mathrm{C}})$ . (c) $M{-}H$ curves of the 6 SL $\\mathrm{MnBi_{2}T e_{4}}$ film measured with SQUID at $3\\mathrm{K}$ (red), $15\\mathrm{K}$ (light green), $20\\mathrm{K}$ (green), and $30\\mathrm{K}$ (blue). $H$ is perpendicular to the sample plane. (d) $R_{y x}–H$ curves measured at $1.6\\mathrm{K}$ at different gate voltages. (e) $M{-}H$ curves of 4, 5, 6, 7, 8, 9-SL $\\mathrm{MnBi_{2}T e_{4}}$ films measured at $3\\mathrm{K}$ and right above $T_{\\mathrm{C}}$ (upper panels) and the differences between the curves at the two temperatures (lower panels). (f) Thickness dependences of $M_{\\mathrm{r}}$ at $3\\mathrm{K}$ , $M_{\\mathrm{r}}$ difference at $3\\mathrm{K}$ and above $T_{\\mathrm{C}}$ (upper panel) and $H_{\\mathrm{c}}$ (lower panel). (g) $R_{y x}–H$ curve of the 7-SL MnBi2Te4 film measured at $1.6\\mathrm{K}$ with $H$ up to $9\\mathrm{T}$ . The blue arrows indicate the magnetic configurations at different $H$ . Each arrow represents the magnetization vector of an SL. In (e) and (f), $(1/2$ ) means that the displayed magnetization has been multiplied by $1/2$ for sake of comparison. \n\nFerromagnetism of the 7-SL $\\mathrm{MnBi_{2}T e_{4}}$ film is also demonstrated by Hall measurements. Figure 3(d) displays the Hall resistance $R_{y x}$ of the 7-SL film grown on a SrTiO (111) substrate vs $H$ , measured at $1.6\\mathrm{K}$ un$^3$ \nder different gate voltages $V_{\\mathrm{{g}}}$ . The SrTiO $^3$ substrate is used as the gate dielectric for its huge dielectric constant $(\\sim20000)$ at low temperature.[26] The curves exhibit hysteresis loops of the anomalous Hall effect (AHE) with a linear background contributed by the ordinary Hall effect (OHE). The slope of the OHE background reveals that the sample is electron-doped with the electron density $n_{e}\\sim1.1\\times10^{13}\\mathrm{cm^{-2}}$ , which \n\nbasically agrees with $n_{e}\\sim8\\times10^{12}\\mathrm{{cm}^{-2}}$ derived from the Fermi wavevector ( $k_{\\mathrm{F}}\\sim0.07\\textup{\\AA}^{-1}$ ) of the ARPESmeasured Dirac-type band. The hysteresis loops of the AHE confirm the ferromagnetism of the film with perpendicular magnetic anisotropy. The $T_{\\mathrm{C}}$ obtained from the $R_{y x}–T$ curve is similar to that given by the SQUID data [Fig. 2(b)]. The $H_{\\mathrm{c}}$ of the $R_{y x}–H$ hysteresis loops is however larger than that of the $M{-}H$ loops. Tuning the chemical potential of the film by applying different $V_{\\mathrm{g}}$ , we observe obvious change in the anomalous Hall resistance. The sensitivity of the AHE to the chemical potential suggests that the AHE is mainly contributed by the Berry curvature of the energy bands induced by intrinsic magnetism of the material instead of magnetic impurities or clusters.[27] \n\nNoticeably, the 6-SL MnBi Te $^{;4}$ film shows different magnetic properties from the 7-SL one. As shown in Fig. 3(c), the hysteresis ( $M_{\\mathrm{r}}$ and $H_{\\mathrm{c}}$ ) in the $M-$ $H$ curve of the 6-SL film is rather small even at $3\\mathrm{K}$ , and $M_{\\mathrm{s}}$ decreases slowly with increasing temperature. Clearly the film is not dominated by long-range FM order. The $M{-}H$ curves of the 4–9-SL $\\mathrm{MnBi_{2}T e_{4}}$ films are displayed in Fig. 3(e), which will be analyzed below based on our theoretical results. \n\n![](images/9348c07413db83e216dc710fa77d892e8b77e0e63852ece83e68427bf023ac41.jpg) \nFig. 4. First-principles calculation results of $\\mathrm{MnBi_{2}T e_{4}}$ . (a) Lattice structures of a MnTe bilayer adsorbed on a $\\mathrm{Bi_{2}T e_{3}}$ quintuple layer (left) and a $\\mathrm{MnBi_{2}T e_{4}}$ SL (right). Valence states of atoms were labelled by assuming $^{-2}$ for Te. Atom swapping between Mn and Bi results in stable valence states, thus stabilizing the whole structure. (b) Atomic structure of layered $\\mathrm{MnBi_{2}T e_{4}}$ , whose magnetic states are ferromagnetic within each SL and antiferromagnetic between adjacent SLs. Insets show Te-formed octahedrons together with center Mn. (c) Band structure of the 7-SL $\\mathrm{MnBi_{2}T e_{4}}$ film, which is an intrinsic QAH insulator (band gap ${\\sim}52\\mathrm{meV}$ ), as proved by the dependence of band gap on the strength of SOC (inset). (d) Schematic band structure of $\\mathrm{MnBi_{2}T e_{4}}$ (0001) surface states, showing a gapped Dirac cone with spin-momentum locking. The energy gap is opened by the surface exchange field $(m_{z})$ , which gets vanished when paramagnetic states are formed at high temperatures. \n\nNext we discuss the structure, magnetism and topological electronic properties of $\\mathrm{MnBi_{2}T e_{4}}$ with the above experimental observations and our firstprinciples calculation results. To understand the mechanism for the formation of $\\mathrm{MnBi_{2}T e_{4}}$ , we calculate the energies of a MnTe BL adsorbed on a $\\mathrm{Bi_{2}T e_{3}}$ QL [Fig. 4(a) left] and a MnBi2Te $^{;4}$ SL [Fig. 4(a) right]. The calculations show that the latter has 0.51 eV/unit lower total energy and is thus energetically more stable. The result is easy to understand in terms of valence states. By assuming $\\mathrm{Te^{2-}}$ , the former structure gives unstable valence states of $\\mathrm{Mn^{3+}}$ and $\\mathrm{Bi^{2+}}$ , which tend to change into more stable $\\mathrm{Mn^{2+}}$ and $\\mathrm{Bi^{3+}}$ by swapping their positions. The atom-swapping induced stabilization thus explains the spontaneous formation of $\\mathrm{MnBi_{2}T e_{4}}$ with a MnTe BL grown on $\\mathrm{Bi_{2}T e_{3}}$ . \n\nWe calculate the energies of different magnetic configurations of $\\mathrm{MnBi_{2}T e_{4}}$ (see Fig. S3 in the supplementary materials). It is found that the most stable magnetic structure is FM coupling in each SL and AFM coupling between adjacent SLs (i.e. Atype AFM), whose easy axis is out-of-plane [Fig. 4(b)]. In $\\mathrm{MnBi_{2}T e_{4}}$ , Mn atoms are located at the center of slightly distorted octahedrons that are formed by neighboring Te atoms. The FM intralayer coupling induced by Mn–Te–Mn superexchange interactions is significantly stronger than the AFM interlayer coupling built by weaker Mn–Te Te–Mn super-superexchange interactions. Similar A-type AFM states were predicted to exist in other magnetic $\\mathrm{XB_{2}T_{4}}$ compounds.[28] \n\nFigure 4(c) shows the calculated band structure of the 7-SL $\\mathrm{MnBi_{2}T e_{4}}$ film. We can observe the Dirac-like energy bands around $\\varGamma$ point, which basically agrees with the ARPES data, expect for a gap $\\mathrm{\\sim52meV)}$ at the Dirac point. All the films containing larger than 4 SLs show similar band features with nearly identical gap values at the Dirac point, implying that the gapped Dirac cone is an intrinsic surface feature of the material. Purposely tuning down the SOC strength in calculations, the gap at first decreases to zero and then increases [inset of Fig. 4(c)], which suggests a topological phase transition and thus the topologically non-trivial nature of the gap. Actually our calculations on the system reveal that bulk MnBi2Te4 is a 3D AFM TI with Dirac-like surface states that are gapped by the FM (0001) surfaces with out-of-plane magnetization.[28,29] \n\nAs illustrated in Fig. 4(d) and confirmed numerically, the gapped surface states can be described by an effective Hamiltonian $H(k)=(\\sigma_{x}k_{y}-\\sigma_{y}k_{x})+m_{z}\\sigma_{z}$ , where $\\sigma$ is the Pauli matrix with $\\sigma_{z}~=~\\pm1$ referring to spin-up and spin-down, $m_{z}$ is the surface exchange field.[2,3] For films thicker than 1 SL, hybridizations between top and bottom surfaces are negligible. Thus, their topological electronic properties are determined by the two isolated surfaces, which have the same (opposite) $m_{z}$ for odd (even) number of SLs and half-integer quantized Hall conductance of $e^{2}/2h$ or $-e^{2}/2h$ , depending on the sign of $m_{z}$ . Therefore, odd-SL MnBi Te $_4$ films are intrinsic QAH insulators with the Chern number $C=1$ , meanwhile even-SL films are the intrinsic axion insulators ( $C=0$ ) that behave like ordinary insulators in dc measurements but can show topological magnetoelectric effects in ac measurements.[3] However, when the TRS is recovered above $T_{\\mathrm{C}}$ , the exchange splitting of the bands gets vanished while the SOC-induced topological band inversion remains unaffected. MnBi2Te $^{\\cdot}4$ thus becomes a 3D TI showing gapless topological surface states, which are exactly the band structure observed in the ARPES measurements performed at $25\\mathrm{K}$ (above $T_{\\mathrm{C}}$ ). \n\nThe theoretically predicted magnetic configuration of MnBi2Te4 (Fig. 4(b)) is supported by our magnetic measurements. For an odd-SL AFM $\\mathrm{MnBi_{2}T e_{4}}$ film, whatever the exact thickness is, the net magnetic moment is only of 1 SL. It explains why the atomic magnetic moment of Mn estimated from the 7-SL MnBi2Te $^{;4}$ film $(1.14\\mu_{\\mathrm{s}}$ ) is much smaller than $5\\mu_{\\mathrm{B}}$ . The measured $M_{\\mathrm{s}}~=~8\\mu_{\\mathrm{B}}$ per 2D U.C. may have contributions from both the FM surfaces (supposed to be $5\\mu_{\\mathrm{B}}$ ) and the AFM bulk which can give magnetic signals via canting or disorder. With the AFM arrangement of neighboring FM SLs, $\\mathrm{MnBi_{2}T e_{4}}$ films are expected to show oscillation in its magnetic properties as the thickness changes between even and odd SLs. We indeed observed even-odd oscillation in their magnetic properties as shown in Figs. 3(e) and 3(f). The remnant magnetization $M_{\\mathrm{r}}$ , which characterizes long-range ferromagnetic order, is larger in odd-SL films than in even-SL ones. $\\boldsymbol{H_{\\mathrm{c}}}$ shows similar oscillation below 7 SLs, but increases monotonously in thicker films. This is because the Zeeman energy in magnetic field ( $E_{z}$ ) in an AFM film with FM surfaces is only contributed by the FM surfaces and thus invariant with film thickness, while the magnetocrystalline anisotropy energy $E_{\\mathrm{MCA}}$ , which is contributed by the whole film, increases with thickness and thus becomes more difficult to be overcome by $E_{z}$ . In addition, as shown in the 6-SL film [Fig. 3(c)] and other even-SL films, $M_{\\mathrm{s}}$ is less sensitive to temperature than in odd-SL films. For a comparison, the differences between the $M$ – $H$ curves measured at $3\\mathrm{K}$ and those measured above $T_{\\mathrm{C}}$ are displayed in the lower panels of Fig. 3(e), which shows a clear even-odd oscillation [Fig. 3(f)]. A rapid increase of $M_{\\mathrm{s}}$ with decreasing temperature below $T_{\\mathrm{C}}$ is typical for ferromagnetic order. The magnetic signal from AFM canting, on the other hand, decreases or keeps nearly constant with decreasing temperature. Thus the odd-SL films obviously have more FM features. \n\nThe large inter-SL distance ( $\\sim$ 1.36 nm) is expected to give a weak AFM coupling between neighboring SLs, which can be aligned into FM configuration in a magnetic field of several tesla.[30] We carried out a Hall measurement of a 7-SL MnBi $^2$ Te $^4$ film with $H$ up to 9 T. As shown in Fig. 3(g) (the linear background of the OHE has been subtracted from the $R_{y x}–H$ loop), besides a small hysteresis loop at low field contributed by the FM surfaces, $R_{y x}$ resumes growing above ${\\sim}2\\mathrm{T}$ and is saturated at a higher plateau above $\\mathrm{5T}$ . The phenomenon is a characteristic of a layered magnetic material and presumably results from an AFM-to-FM transition (see the schematic magnetic configuration shown by the blue arrows in Fig. 3(g)). The FM configuration may drive the system into a magnetic Weyl semimetal phase.[28,29] \n\nIn spite of the above evidences for an A-type AFM order of MnBi2Te4, there are still some observations that we have not yet fully understood. For example, the even-SL films show larger $M_{\\mathrm{s}}$ than odd-SL ones above $T_{\\mathrm{C}}$ , which is particularly clear in comparison of the 6 SLs [Fig. 3(c)] and 7 SLs [Fig. 3(a)] data at $30\\mathrm{K}$ . We also notice that overall $M_{\\mathrm{s}}$ shows a maximum around 6 SLs and 7 SLs at $3\\mathrm{K}$ , regardless of even or odd of SLs. Another confusion is that the magnetic properties revealed by Hall effect measurements are not fully consistent with those revealed by magnetization measurements: $R_{y x}–H$ loops always show larger $\\boldsymbol{H_{\\mathrm{c}}}$ than $M{-}H$ loops, and oscillatory behaviors are barely observed in the AHE data of the films of different thicknesses. These phenomena should result from the interplays between the complex magnetic structures and topological electronic properties of the unique layered magnetic material and require a comprehensive study combing various techniques to clarify. Moreover, we find that MnBi $^{-2}$ Te $^4$ films are relatively easy to decay under ambient conditions: $M_{\\mathrm{s}}$ of a sample decreases significantly after it is exposed in air for a couple of days. This may also complicate the magnetization and magneto-transport measurement results. Finding an effective way to protect the material is crucial for the experimental investigations on this system and for the explorations of the exotic topological quantum effects in it. \n\nThe authors thank Wanjun Jiang and Jing Wang for stimulating discussions. \n\n# References \n\n[1] Hasan M Z and Kane C L 2010 Rev. Mod. Phys. 82 3045 [2] Qi X L and Zhang S C 2011 Rev. Mod. Phys. 83 1057 \n[3] Qi X L, Hughes T L and Zhang S C 2008 Phys. Rev. B 78 195424 \n[4] Haldane F D M 1988 Phys. Rev. Lett. 61 2015 \n[5] Liu C X, Qi X L, Dai X, Fang Z and Zhang S C 2008 Phys. Rev. Lett. 101 146802 [6] Yu R et al 2010 Science 329 61 [7] Chang C Z et al 2013 Science 340 167 \n[8] Qi X L, Hughes T L and Zhang S C 2010 Phys. Rev. B 82 184516 \n[9] He Q L et al 2017 Science 357 294 \n[10] Lee I et al 2015 Proc. Natl. Acad. Sci. USA 112 1316 \n[11] Lachman E O et al 2015 Sci. Adv. 1 e1500740 \n[12] Grauer S et al 2015 Phys. Rev. B 92 201304 \n[13] Feng X et al 2016 Adv. Mater. 28 6386 \n[14] Liu Y et al 2018 Nature 555 638 \n[15] Tang P, Zhou Q, Xu G and Zhang S C 2016 Nat. Phys. 12 1100 \n[16] Xu G, Weng H, Wang Z, Dai X and Fang Z 2011 Phys. Rev. Lett. 107 186806 \n[17] Neupane M et al 2012 Phys. Rev. B 85 235406 \n[18] Lee D S et al 2013 CrystEngComm 15 5532 \n[19] Hagmann J A et al 2017 New J. Phys. 19 085002 \n[20] Hirahara T et al 2017 Nano Lett. 17 3493 \n[21] Otrokov M et al 2017 2D Mater. 4 025082 \n[22] Li Y Y et al 2010 Adv. Mater. 22 4002 \n[23] Zhang H et al 2009 Nat. Phys. 5 438 \n[24] Chen Y L et al 2009 Science 325 178 \n[25] Fu L 2009 Phys. Rev. Lett. 103 266801 \n[26] Chen J et al 2010 Phys. Rev. Lett. 105 176602 \n[27] Nagaosa N, Sinova J, Onoda S, MacDonald A H and Ong N P 2010 Rev. Mod. Phys. 82 1539 \n[28] Li J et al 2019 Sci. Adv. (to be published) (2018 arXiv:1808.08608 [cond-mat.mtrl-sci]) \n[29] Zhang D et al 2019 Phys. Rev. Lett. 122 206401 \n[30] Huang B et al 2017 Nature 546 270 " + }, + { + "id": "10.1038_s41467-019-09510-5", + "DOI": "10.1038/s41467-019-09510-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-09510-5", + "Relative Dir Path": "mds/10.1038_s41467-019-09510-5", + "Article Title": "Scalable synthesis of ant-nest-like bulk porous silicon for high-performance lithium-ion battery anodes", + "Authors": "An, WL; Gao, BA; Mei, SX; Xiang, B; Fu, JJ; Wang, L; Zhang, QB; Chu, PK; Huo, KF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Although silicon is a promising anode material for lithium-ion batteries, scalable synthesis of silicon anodes with good cyclability and low electrode swelling remains a significant challenge. Herein, we report a scalable top-down technique to produce ant-nest-like porous silicon from magnesium-silicon alloy. The ant-nest-like porous silicon comprising threedimensional interconnected silicon nulloligaments and bicontinuous nullopores can prevent pulverization and accommodate volume expansion during cycling resulting in negligible particle-level outward expansion. The carbon-coated porous silicon anode delivers a high capacity of 1,271 mAh g(-1) at 2,100 mA g(-1) with 90% capacity retention after 1,000 cycles and has a low electrode swelling of 17.8% at a high areal capacity of 5.1 mAh cm(-2). The full cell with the prelithiated silicon anode and Li(Ni1/3Co1/3Mn1/3)O-2 cathode boasts a high energy density of 502 Wh Kg(-1) and 84% capacity retention after 400 cycles. This work provides insights into the rational design of alloy anodes for high-energy batteries.", + "Times Cited, WoS Core": 631, + "Times Cited, All Databases": 655, + "Publication Year": 2019, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000462722200004", + "Markdown": "# Scalable synthesis of ant-nest-like bulk porous silicon for high-performance lithium-ion battery anodes \n\nWeili An 1,2, Biao Gao1,3, Shixiong Mei1, Ben Xiang1, Jijiang $\\mathsf{F u}^{1},$ , Lei Wang2, Qiaobao Zhang4, Paul K. Chu 3 & Kaifu Huo 2 \n\nAlthough silicon is a promising anode material for lithium-ion batteries, scalable synthesis of silicon anodes with good cyclability and low electrode swelling remains a significant challenge. Herein, we report a scalable top-down technique to produce ant-nest-like porous silicon from magnesium-silicon alloy. The ant-nest-like porous silicon comprising threedimensional interconnected silicon nanoligaments and bicontinuous nanopores can prevent pulverization and accommodate volume expansion during cycling resulting in negligible particle-level outward expansion. The carbon-coated porous silicon anode delivers a high capacity of $1,271\\ m A\\mathsf{h}\\ \\mathtt{g}^{-1}$ at $2,100\\mathsf{m A g}^{-1}$ with $90\\%$ capacity retention after 1,000 cycles and has a low electrode swelling of $17.8\\%$ at a high areal capacity of $5.1\\ m A\\ h\\ c m^{-2}$ . The full cell with the prelithiated silicon anode and $\\mathsf{L i}(\\mathsf{N i}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{M}\\mathsf{n}_{1/3})\\mathsf{O}_{2}$ cathode boasts a high energy density of 502 Wh $\\mathsf{K g}^{-1}$ and $84\\%$ capacity retention after 400 cycles. This work provides insights into the rational design of alloy anodes for high-energy batteries. \n\nFsavspetehcidiclefievcs proeopqwmueiern/etenolefirghpyio,umlao-binlogenee cacyttrceloren lcsi ed(,e aiBcnse)d awcinotdmh pelheiticgthirveicer costs1,2. Silicon (Si) has been identified as one of the promising anode materials for next-generation high-energy density LIBs because of its large theoretical specific capacity of $3579\\mathrm{m}\\mathrm{\\dot{A}h}\\mathrm{g}^{-1}$ $\\mathrm{(Li_{15}S i_{4})}^{3-5}$ . However, Si suffers from a large volume change $(>300\\%)$ during lithiation and delithiation causing mechanical pulverization of the particles, loss of inter-particles electrical contact, and continuous formation of the solid-electrolyte interface (SEI), consequently resulting in rapid capacity fading and deteriorated battery performance5–11. \n\nProgress has been made to address particle pulverization by decreasing the size to the critical nanosize10. Si nanostructures such as nanoparticles12, nanowires13, nanotubes9, as well as nano-Si/carbon hybrids6,14 have been developed as anode materials and enhanced cycle life compared to the bulk counterparts have been demonstrated. However, scalable synthesis of nanostructured Si with a large tap density, high initial Coulombic efficiency (ICE), and long cycle stability at a high mass loading remains a challenge5,10. Nanostructured Si has a large surface area, which increases the electrode/electrolyte interfacial area giving rise to low ICE and the small tap density causes a low volumetric energy density. To improve the tap density and ICE without structural pulverization during lithiation/delithiation, microscale or porous Si particles assembled from nanoscale building blocks have been proposed as anodes in $\\mathrm{LIBs^{11,15-20}}$ . For example, Cui et $\\mathrm{al}^{20}$ . prepared yolk-like nanoscale $\\mathrm{{si}/\\mathrm{{C}}}$ assembled microscale pomegranate-like particles, which had a tap density of $0.53\\mathrm{g}\\mathrm{cm}^{-3}$ and $97\\%$ capacity retention after 1000 cycles. Park et al16. prepared microscale porous Si by electroless metal deposition and chemical etching and the materials had a high capacity of $2050\\mathrm{mAhg^{-1}}$ at $400\\mathrm{\\overline{{mA}}g^{-1}}$ . However, fabrication of these microscale Si or $\\mathrm{Si/C}$ materials tends to be costly and is not yet scalable due to the complex synthesis. The tap density and electrochemical cyclability are still unsatisfactory from the commercial standpoint21. More importantly, large thickness swelling of the Si anodes presents the most critical challenge hampering practical implementation in high-energy full cells22 but this issue is often ignored in Si anode research. The large electrode swelling in thickness during lithiation in LIBs decreases the volumetric energy density and undermines cycling performance and unsafety23. To address these limitations, rational design of Si anode materials with a large tap density, minimal electrode thickness swelling, and large areal capacity $(>3.0\\mathrm{\\mAh\\cm}^{-2}$ for commercial $\\mathrm{LIB}s^{24}.$ ) together with a cost-effective and scalable preparation method are highly desirable but still very challenging. \n\nHerein, we report an ant-nest-like microscale porous Si (AMPSi) for high-performance anodes in LIBs. The AMPSi is produced via a low-cost and scalable top-down approach by thermal nitridation of the $\\mathrm{Mg-Si}$ alloy in nitrogen $(\\Nu_{2})$ followed by the removal of the $\\mathrm{Mg}_{3}\\mathrm{N}_{2}$ by-product in an acidic solution (schematically shown in Fig. 1a). The synchrotron radiation tomographic reconstruction images reveal that the AMPSi has 3D interconnected Si nanoligaments and bicontinuous nanoporous network resembling the natural ant nest (Fig. 1b). In situ transmission electron microscopy (TEM) reveals that the Si nanoligaments with widths of several $10\\mathrm{nm}$ can expand/shrink reversibly during lithiation/delithiation without pulverization and the volume expansion of the Si nanoligaments can be accommodated by the surrounding pores through reversible inward Li breathing, thereby resulting in negligible particle-level outward expansion as schematically shown in Fig. 1c. The AMPSi integrates the intrinsic merits of nanoscale and microscale Si with a high tap density of $0.84\\mathrm{g}\\mathrm{cm}^{-3}$ and small surface area. After coating a ${5{-}8\\mathrm{nm}}$ thick carbon layer to improve the conductivity, the anode composed of carbon-coated AMPSi $(\\mathrm{AMPSi@C})$ shows a high ICE of $80.3\\%$ , gravimetric capacities of 2134, and 1271 $\\mathrm{mAhg^{-1}}$ at 0.1 and $0.5\\mathrm{C}$ rates $(1\\bar{\\mathrm{C}}=4200\\mathrm{mAg^{-1}}^{\\cdot}$ ), and $90\\%$ capacity retention from the twentieth to thousandth cycles. The $\\mathrm{A}\\bar{\\mathrm{MPSi}}@{\\mathrm{C}}$ anode with an areal mass loading of $0.{\\dot{8}}\\mathrm{mg}\\mathrm{cm}^{-2}$ delivers a large volumetric capacity of $1712\\mathrm{m}\\mathrm{\\bar{A}h}\\mathrm{cm}^{-3}$ at $0.1\\mathrm{C}$ after 100 cycles, which is the highest reported from Si anodes so far. Furthermore, the bulk electrode of $\\mathrm{AMPSi@C}$ with an areal capacity of $5.1\\mathrm{mAh}\\mathrm{cm}^{-2}$ exhibits a small electrode swelling of $17.8\\%$ , which substantially outperforms most reported Si anodes11,15,25–27. The full cell comprising the prelithiated AMP$\\mathrm{Si@C}$ anode and commercial $\\mathrm{Li}(\\mathrm{Ni}_{1/3}\\mathrm{Co}_{1/3}\\mathrm{Mn}_{1/3})\\mathrm{O}_{2}$ cathode has a high-energy density of 502 Wh $\\mathrm{Kg^{-1}}$ and long-life cycle stability with $84\\%$ capacity retention for over 400 cycles. The economic and scalable top-down fabrication method, rational bulk nanoporous structure design, as well as superior electrochemical properties can be extended to other types of electrodes that tend to undergo large volume expansion in high-energy batteries. \n\n# Results \n\nSynthesis and characterization of AMPSi and AMPSi@C. As shown in Fig. 1a, fabrication of AMPSi commences with $\\mathrm{Mg}_{2}\\mathrm{Si}$ powders commercially available or synthesis from $\\mathbf{Mg}$ and metallurgical Si. Here the crystalline ${3{\\mathrm{-}}5\\upmu\\mathrm{m}\\ \\mathrm{Mg}_{2}\\mathrm{Si}}$ particles are prepared by alloying the bulk metallurgical Si and $\\mathbf{Mg}$ at $550^{\\circ}\\mathrm{C}$ and then the as-obtained $\\mathrm{Mg}_{2}\\mathrm{Si}$ particles are nitrided under $\\Nu_{2}$ at $750^{\\circ}\\mathrm{C}$ . During this process, $\\mathbf{Mg}$ in $\\mathrm{Mg}_{2}\\mathrm{Si}$ reacts with $\\Nu_{2}$ to produce $\\mathrm{Mg}_{3}\\mathrm{N}_{2}$ while Si is separated forming the $\\mathrm{Mg}_{3}\\mathrm{N}_{2}/\\mathrm{Si}$ composite $\\left(3\\mathrm{Mg}_{2}\\mathrm{Si}\\left(s\\right)+2N_{2}\\left(\\mathrm{g}\\right)\\right.\\rightarrow3\\mathrm{Si}\\left(s\\right)+2\\bar{\\mathrm{Mg}}_{3}N_{2}$ ðsÞ). The X-ray diffraction (XRD) patterns in Fig. 2a exhibit peaks from $\\mathrm{Mg}_{3}\\mathrm{N}_{2}$ (JCPDS No. 73–1070) and Si (JCPDS No. 27–1402), while the peaks associated with the $\\mathrm{Mg}_{2}\\mathrm{Si}$ phase (JCPDS No. 35–0773) disappear. Compared to pristine $\\mathrm{Mg}_{2}\\mathrm{Si}$ particles (Fig. 2b), the nitridated $\\mathrm{Mg}_{2}\\mathrm{Si}$ particles become coarse (Fig. 2c) and the highangle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) and TEM images reveal a loose connecting framework (Supplementary Fig. 1a, b). High-resolution TEM (HR-TEM) (Supplementary Fig. 1c) discloses that the single-crystal $\\mathrm{Mg}_{3}\\mathrm{N}_{2}$ and Si are closely connected forming the $\\mathrm{Mg}_{3}\\mathrm{N}_{2}/\\mathrm{Si}$ heterostructure. Energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) mapping (Supplementary Fig. 1d-g) shows uniform distributions of Si, $\\operatorname{Mg},$ and N. After removing $\\mathrm{Mg}_{3}\\mathrm{N}_{2}$ in diluted hydrochloric acid, the bulk porous Si particles (Fig. 2d) are obtained. The size of the synthesized AMPSi is measured by a laser particle size analyzer (Mastersizer 2000) and the average diameter $(D_{50})$ is $3\\pm0.2\\upmu\\mathrm{m}$ (Supplementary Fig. 2a). No $\\mathbf{M}\\mathbf{g}$ signal is detected from AMPSi by X-ray photoelectron spectroscopy (XPS) indicating complete removal of $\\mathbf{Mg}$ (Supplementary Fig. 3a, b). The Si 2p XPS spectra in Supplementary Fig. 3c, d show two peaks corresponding to $\\mathrm{Si}\\ 2\\mathrm{p}\\ \\mathrm{1}/2$ and $\\mathrm{Si}~2\\mathrm{p}~3/2$ of elemental Si $(\\mathrm{Si}^{0})$ at binding energies of 98.8 and $99.4\\mathrm{eV}$ , and the weak ones at 102.2 and $102.8\\mathrm{eV}$ are associated with $\\mathrm{SiO}_{x}$ formed by native oxidation after synthesis13–15. The oxygen content in AMPSi is about $6.7\\%$ (wt.). The magnified scanning electron microscopy (SEM) image in the inset of Fig. 2d shows that the porous Si particle consists of interconnected nanoligaments and 3D bicontinuous nanopores resembling the natural ant nest (Fig. 1b). The microstructure of AMPSi is further analyzed by TEM as shown in Supplementary Fig 2b, c. The Si ligaments with a size of $30{-}50~\\mathrm{nm}$ are interconnected and surrounded by the bicontinuous nanopores forming an ant-nest-like framework. The synchrotron radiation tomographic images (Fig. 2e) further confirm the 3D continuous nanopore structure and interconnected Si nanoligaments. This unique ant-nest-like material are fundamentally different from previously reported $\\mathrm{{si}/\\mathrm{{C}}}$ composite secondary particles11,15–20. HR-TEM and selected-area electron diffraction (SAED) reveal that AMPSi is composed of many crystalline grains of Si (Supplementary Fig. 4). The AMPSi has a high tap density of $0.84\\mathrm{g}\\mathrm{cm}^{-3}$ , which is larger than that of previously reported nanostructured Si and microscale Si6,11,14,15,20,25–27. \n\n![](images/76616c5019fad3530c5a7d3ab7e7598206d18337831ac6d30922425953f375cc.jpg) \nFig. 1 Design and schematic showing the synthesis method of AMPSi. a Schematic showing the preparation of AMPSi and $\\mathsf{A M P S i@C}$ b Photograph of an ant nest (scale bar $=20{\\mathsf{c m}}$ ). c Schematic illustrating the lithiation/delithiation process of the ant-nest-like microscale porous Si particles showing inward volume expansion and stable Si framework retention during cycling \n\n![](images/01a474caac2d9cec48abee28851c943d9493209256ab57c773d5998fac2eb568.jpg) \nFig. 2 Morphological and structural characterization. a XRD patterns of the products at different steps during preparation. SEM images of b pristine ${\\sf M g}_{2}{\\sf S i}$ particles, c nitrided ${M g}_{2}{\\sf S i}$ particles, and d AMPSi (scale bar for $\\ensuremath{\\mathbf{b}},\\ensuremath{\\mathbf{c}},$ and $\\mathsf{\\pmb{d}}=3\\upmu\\mathrm{m}$ and scale bar for the insets $=2\\upmu\\mathrm{m}\\upnu$ . e Synchrotron radiation tomographic 3D reconstruction images of the AMPSi (scale bar $=3\\upmu\\mathrm{m}\\dot{}$ \n\n![](images/a8de8852c80727a7b3135917bc33addaa9ff43e9c23570478c74b16f253a8431.jpg) \nFig. 3 Characterization of ${\\mathsf{A M P S i@C}}.$ . a SEM image of $\\mathsf{A M P S i@C}$ (scale bar $=2\\upmu\\mathrm{m})$ . b TEM image of $A M P\\mathsf{S i}@C$ (scale bar $=100{\\mathsf{n m}}.$ ). The inset (scale bar $=10\\mathsf{n m})$ is the HR-TEM image showing that the $5\\mathrm{-}8~\\mathsf{n m}$ thickness amorphous C shell is coated on the Si nanoligaments and the lattice distance of 0.31 nm corresponds to the $d$ -spacing of the (111) planes of crystalline Si (111). c EDS maps of the Si frameworks in AMPS $\\mathtt{\\Pi}_{\\mathtt{(a)}}\\mathtt{C}$ with red and green corresponding to Si and C, respectively (scale bar for $\\pmb{\\mathsf{c}}=200\\mathsf{n m}.$ ). d Raman scattering spectra of AMPSi and $A M P\\mathsf{S i@C}$ . e Comparison of the tap densities between our Si anodes and other Si-based anode materials (see Supplementary Table 1) \n\nSince the well-organized pores are continuous and most of the pores are larger than $50\\mathrm{nm}$ , mercury intrusion porosimetry is employed to examine the pores larger than $50\\mathrm{nm}$ and nitrogen adsorption-desorption isotherms are obtained to assess the mesopores. Brunauer-Emmett-Teller (BET) analysis reveals that the AMPSi has a small specific surface area of $12.6\\ensuremath{\\mathrm{m}}^{2}\\ensuremath{\\mathrm{g}}^{-1}$ due to the space-efficient packing of AMPSi (Supplementary Fig. 5a, b). The porosity of AMPSi is measured to be $64.3\\%$ that is close to the theoretical value of $68.6\\%$ assuming that the sample undergoes no macroscopic volume change during dealloying $\\mathbf{Mg}$ in $\\mathrm{Mg}_{2}\\mathrm{Si}^{\\mathrm{17}}$ . As schematically shown in Fig. 1c, the high porosity of AMPSi allows inward expansion of the 3D interconnected Si nanoligaments during cycling consequently, leading to high structural stability and negligible particle-level outward expansion. \n\nTo improve the electrical conductivity, a thin C layer is coated on AMPSi by dopamine self-polymerization followed by thermal carbonization, as schematically shown in Fig. 1a. Dopamine is a widely used carbon precursor for C coatings. It can selfpolymerize into polydopamine (PDA) coatings on the surface of Si with strong adhesion and so the thin and homogeneous carbon shell on Si can be achieved after thermal carbonization. The SEM and TEM images (Fig. 3a, b) disclose that the $\\mathrm{AMPSi@C}$ retains the 3D ant-nest-like porous structure of the pristine AMPSi and Supplementary Fig. 5b shows that the pore size decreases slightly after C coating. To confirm the uniform carbon coating, HR-TEM is performed on $\\mathrm{AMPSi@C}$ at different regions. The HR-TEM images at different regions (inset in Fig. 3b and Supplementary Fig. 6a, b) suggest that the C shell having a thickness of $\\mathsf{5}\\mathrm{-}8\\mathrm{nm}$ is amorphous and the lattice distance of 0.31 nm corresponds to the $d$ -spacing of the (111) planes of crystalline $\\mathrm{Si}^{25,28}$ . EDS mapping (Fig. 3c and Supplementary Fig. 6c) further confirms that C is uniformly coated on the surface of AMPSi. The Fourier transform infrared (FTIR) spectroscopy spectra of AMPSi and $\\mathrm{AMPSi@C}$ are depicted in Supplementary Fig. 7. The bands at 1060 and $1620\\mathrm{cm}^{-1}$ correspond to the characteristic vibrations of Si. Compared to AMPSi, the band of $\\mathrm{AMPSi@C}$ at $1060\\mathrm{cm}^{-1}$ is split into two peaks at 1240 and $1090\\mathrm{cm}^{-1}$ suggesting robust bonding between Si and coated carbon shell in $\\mathrm{\\bfA}\\mathrm{\\bar{M}P S i}@\\mathrm{\\bar{C}}^{18}$ . \n\n![](images/c021662720a2c23c3ec37710e3d2ed3d17b56a18cc8d5d2e8646c8d972078b0d.jpg) \nFig. 4 Electrochemical characterization of anodes in half-cell or full-cell configurations. a Long cycling test of AMPS $\\mathtt{\\Pi}_{\\mathtt{(a)C}}$ at $_{0.5\\mathsf{C}}$ after the activation process in the first three circles at 0.05 C ( $\\mathsf{C}=4.2\\mathsf{A g}^{-1})$ in the half-cell with areal mass loading of $0.8\\mathsf{m g}\\mathsf{c m}^{-2}$ . b Comparison of the CE between AMPSi and $\\mathsf{A M P S i@C}$ in the half-cell configuration with the inset being the corresponding voltage profiles. c Rate performance of AMPS $\\mathsf{i}@\\mathsf{C}$ and AMPSi at various current densities from 0.1 to 3 C. d Areal capacities vs. cycling number of the $A M P\\mathsf{S i@C}$ anodes with different mass loadings at a current density of $1.2\\mathsf{m A}$ $\\mathsf{c m}^{-2}$ (the initial three cycles are carried out at $0.1\\mathsf{m A}\\mathsf{c m}^{-2})$ . e Full-cell charge at $0.5\\mathsf{C}$ ( $1{\\mathsf{C}}=160{\\mathsf{m A}}{\\mathsf{g}}^{-1};$ with prelithiated $A M P\\mathsf{S i}@C$ anode and a Li $(\\mathsf{N i}_{1/3}\\mathsf{C o}_{1/3}\\mathsf{M n}_{1/3})\\mathsf{O}_{2}$ cathode. The inset showing the corresponding CE. f Rate performance of the full cell. All the specific capacity values in the half-cell are based on the total mass of AMPSi and C shell, unless otherwise stated \n\nThe Raman scattering spectrum (Fig. 3d) of AMPSi shows a sharp peak at $511\\mathrm{cm}^{-1}$ and two weak peaks at 299 and $925\\mathrm{cm}^{-1}$ , corresponding to the characteristic peaks of crystalline nanoscale $\\S\\mathrm{i}^{18,29,30}$ . The three peaks corresponding to Si are still clearly visible from AMPSi@C. However, the strong peak blue-shifts to $504\\mathrm{cm}^{-1}$ possibly due to confinement effect caused by the carbon coating and strong bonding between the coated carbon and $\\mathrm{Si^{4}}$ . The two peaks at 1347 and $1581\\mathrm{cm}^{-1}$ are attributed to the vibration modes of disordered graphite (D band) and $\\mathrm{E}_{2\\mathrm{g}}$ of crystalline graphite (G band) and the large $\\mathrm{I_{D}/I_{G}}$ ratio (1.14) reflects the low graphitic degree in the carbon coating consistent with XRD (Supplementary Fig. 8) and HR-TEM results. The thermogravimetric analysis shows that the C content in $\\mathrm{AMPSi@C}$ is $8.5\\mathrm{wt\\%}$ (Supplementary Fig. 9). The strong bonding between carbon and Si improves the cycle stability and stabilizes the SEI to enhance the CE during the charging/discharging cycles. \n\nThe tap density of $\\mathrm{AMPSi@C}$ is measured to be $0.80\\mathrm{g}\\mathrm{cm}^{-3}$ and is slightly less than that of pristine AMPSi of $0.84\\mathrm{g}\\mathrm{cm}^{-3}$ due to the presence of amorphous C coating. However, it is still bigger than those of commercial nano- $S\\mathrm{i},$ microscale ${\\mathrm{Si/C}}_{:}$ and porous Si/C (Fig. 3e and Supplementary Table $1)^{6,11,20,31-37}$ thus enabling a bigger volumetric energy density and thinner electrode thickness for the same mass loading in the practical cells. \n\nElectrochemical performance of AMPSi and AMPSi@C. The electrochemical performance of the AMPSi and $\\mathrm{AMPSi@C}$ electrodes is evaluated using half-cell and full-cell configurations, respectively. For comparison, nanoparticles assembled with 3D mesoporous Si (NS-MPSi) are also prepared by thermal distillation of $\\mathbf{Mg}$ in $\\mathrm{Mg}_{2}\\mathrm{Si}$ in vacuum38. The as-prepared NS-MPSi particles are composed of $20{-}40~\\mathrm{nm}$ primary particles with a specific surface area of $120\\mathrm{m}^{2}\\mathrm{g}^{-1}$ (Supplementary Fig. 10). The electrolyte is $1.0\\mathrm{M}\\mathrm{LiPF}_{6}$ in 1:1 v/v ethylene carbonate/diethyl carbonate with 6 vol $\\%$ vinylene carbonate (VC) as the additive. VC is widely used as an electrolyte additive as it can boost the formation of a smooth and stable SEI on Si-based anodes39. All the specific capacity values shown in this paper are based on the total mass of $\\mathrm{AMPSi@C},$ unless otherwise stated. \n\nThe delithiation capacities of AMPSi, AMPSi@C, and NS-MPSi versus cycle number are presented in Fig. 4a. After the three-cycle activation step at $\\mathrm{C}/20$ , the capacity of the AMPSi electrode is maintained at above $679\\mathrm{mA}\\dot{\\mathrm{h}}\\mathrm{g}^{-1}$ at $0.5\\mathrm{C}$ with good cycle stability for over 1000 cycles. Under similar conditions, the NSMPSi electrode shows rapid capacity decay from $2712\\mathrm{mAhg^{-1}}$ in the initial cycle to below $10\\bar{0}\\mathrm{mA}\\dot{\\mathrm{h}}\\mathrm{g}^{-1}$ after 650 cycles mainly due to the electrode cracking and structural destruction of NSMPSi during cycling (Supplementary Fig. 11). Compared to AMPSi, AMPSi@C shows a larger reversible capacity of 1271 $\\operatorname*{mAh}{\\mathrm{g}^{-1}}$ with $90\\%$ capacity retention from the twentieth to thousandth cycles (Fig. 4a). The large capacity decay during the first 20 cycles is attributed to the increased current density from 0.05 to $0.5\\mathrm{C}$ and continuous formation of SEI due to the slow penetration of the viscous organic electrolyte into the continuous porous structure in $\\mathrm{AMPSi@C}$ as a result of strong capillary effects, volume expansion of Si, and low crystalline carbon coating. Actually, capacity decay during the first several and even tens of cycles have been observed from Si and other anode materials $^{9,20,32,33}$ . The $\\mathrm{dQ}/\\mathrm{dV}$ curve of $\\mathrm{AMPSi@C}$ is presented in Supplementary Fig. 12 and the anodic and cathodic peaks overlap after 20 cycles suggesting high cycle reversibility. At a high rate up to $^{3\\mathrm{C},}$ AMPSi@C electrode still shows a large reversible capacity of $632\\mathrm{mAhg^{-1}}$ with $0.015\\%$ capacity decay per cycle for over 1000 cycles (Supplementary Fig. 13). Moreover, $72.5\\%$ capacity retention can be achieved after 500 cycles at a higher rate of $5.0\\mathrm{C}$ (Supplementary Fig. 14), which outperforms most previously reported microscale Si and amorphous-C-coated Si anodes (Supplementary Tables 1 and 2). The role of Fluoroethylene carbonate (FEC) and VC electrolyte additives is also investigated. Although the $\\mathrm{AMPSi@C}$ anodes display similar cycle stability for both electrolyte additives, $\\mathrm{AMPSi@C}$ has a slight larger average CE with VC additive (Supplementary Fig. 15). \n\nCyclic voltammetry (CV) is performed on $\\mathrm{AMPSi@C}$ in a potential range of $0.01\\mathrm{-}1.0\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ at a scanning rate of $\\mathbf{\\bar{0}.1\\ m V s^{-1}}$ as shown in Supplementary Fig. 16a. The broad cathodic peak at ${\\sim}0.16\\mathrm{V}$ is ascribed to the formation of $\\mathrm{Li}_{x}\\mathrm{Si}$ and the anodic peaks at 0.40 and $0.53\\mathrm{V}$ are characteristic of the Li desertion process from $\\mathrm{Li}_{x}\\mathrm{Si}$ to amorphous Si. The chemical states of the cycled electrode are determined by XPS. The fine XPS Si 2p results of the lithiated (0.01 V) and delithiated (0.40 and $0.53\\mathrm{V}.$ ) samples during the first cycle are depicted in Supplementary Fig. 17. The pristine $\\mathrm{AMPSi@C}$ shows two Si peaks at 98.8 and $99.4\\mathrm{eV}$ assigned to $\\mathrm{Si}~2\\mathrm{p}1/2$ and Si $2{\\mathrm{p}}3/2$ of elemental Si $(\\mathrm{Si}^{0})$ . After full lithiation to $0.01\\mathrm{V}$ , the two Si peaks shift to 97.3 and $97.9\\mathrm{eV}$ due to the alloying reaction to form the $\\mathrm{Li}_{x}\\mathrm{Si}$ phase. When the electrode is delithiated at $0.40\\mathrm{V}$ , the peaks of $\\mathrm{Si}^{0}$ reappear and those corresponding to $\\mathrm{Li}_{x}\\mathrm{Si}$ shift to high binding energy, suggesting partial Li-ion desertion from the $\\mathrm{Li}_{x}\\mathrm{Si}$ alloy. At a larger delithiation voltage of $0.53\\mathrm{V}$ , stronger peaks of $\\mathrm{Si}^{\\dot{0}}$ are observed in line with the Si binding energy in $\\mathrm{Li}_{x}\\mathrm{Si}$ shifting to higher energy, meaning that the decreased Li content in $\\mathrm{Li}_{x}\\mathrm{Si}$ stems from more Li-ion desertion from the $\\mathrm{Li}_{x}\\mathrm{Si}$ alloy. The ex situ XPS results agree well with the CV data confirming the alloying/ dealloying reactions of $\\mathrm{AMPSi@C}$ during lithiation/delithiation. The peak intensity in the CV curves of AMPSi and AMPSi@C (Supplementary Fig. 16a, b) increases initially with cycling possibly due to gradual activation of the electrodes20. After several cycles, these peaks overlap suggesting high reversibility and stability. The AMPSi@C electrode exhibits higher peak currents in comparison with the AMPSi electrode implying a largely enhanced capacity. Moreover, the anodic peaks of the $\\mathrm{AMPSi@C}$ electrode shift to higher voltage while the cathodic peaks shift to a lower voltage. The improved capacity and smaller voltage separation (Supplementary Fig. 16a, b) stem mainly from the higher Si electrochemical utilization ratio and enhanced electrical conductivity of $\\mathrm{AMPSi@C}$ , which is further confirmed by electrochemical impede spectroscopy as shown in Supplementary Fig. 18a. The Nyquist plots of the AMPSi and AMPSi@C and corresponding equivalent circuit are depicted in Supplementary Fig. 18. The two semicircles in the high-frequency region represent the resistance of the SEI film $(\\mathrm{R}_{s f})$ and charge transfer resistance $(\\mathrm{R}_{c t})$ and the straight lines in the low-frequency region correspond to diffusion of lithium ions $(\\boldsymbol{\\mathrm{Z}}_{w})$ . $\\mathrm{R}_{s f}$ of $\\mathrm{AMPSi@C}$ is smaller than that of AMPSi, indicating that the SEI at $\\mathrm{AMPSi@C}$ is thinner and more stable than that in AMPSi. Moreover, $\\mathrm{R}_{c t}$ of $\\mathrm{AMPSi@C}$ is less than that of AMPSi suggesting smaller resistance due to the high conductivity of the carbon coating. The voltage profiles of the AMPSi and $\\mathrm{AMPSi@C}$ electrodes during initial cycling are shown in the inset in Fig. 4b, which shows the typical lithiation plateau at around $0.1\\mathrm{V}$ corresponding to the alloying reaction of Si with Li to form $\\mathrm{Li}_{x}\\mathrm{Si}$ alloy. The initial lithiation capacity of both the AMPSi and $\\mathrm{AMPSi@C}$ electrodes reaches $284\\bar{3}\\ \\mathrm{mA}\\mathrm{\\dot{h}}\\ \\mathrm{g}^{-1}$ at $0.05\\mathrm{C}$ indicating that most of the Si in AMPSi and $\\mathrm{AMPSi@C}$ is active due to the high $\\mathrm{Li^{+}}$ accessibility of the bulk nanoporous structure. The ICE of AMPSi is $86.6\\%$ (Fig. 4b) and CE reaches $99.9\\%$ after 10 cycles, which are better than those of $\\mathrm{{si}/\\mathrm{{C}}}$ composites4,10,12. The ICE of $\\mathrm{AMPSi@C}$ is slightly reduced $(80.3\\%)$ possibly because of the formation of more SEI on the surface of the amorphous C shell as a result of the enlarged surface area of $\\mathrm{AMPSi@C}$ compared to AMPSi18. Figure $_{4c}$ presents the rate performance of the AMPSi and $\\mathrm{AMPSi@C}$ electrodes. Although both electrodes have similar capacities at 0.1 and $0.2\\mathrm{C},$ AMPSi $\\scriptstyle{\\mathcal{Q}}\\mathbf{C}$ has much higher capacities at higher rates. Even at a high rate of $3\\mathrm{C}$ , the $\\mathrm{AMPSi@C}$ electrode has a high capacity of $619\\mathrm{\\dot{mAh}g^{-1}}$ that is almost twice that of the AMPSi electrode. Moreover, when the current density is reverted to $0.1\\mathrm{C},$ a reversible capacity of $2134\\mathrm{mAhg^{-1}}$ is recovered readily implying high structural stability of the $\\mathrm{AMPSi@C}$ electrode. The tap density of the $\\mathrm{AMPSi@C}$ electrode is $0.80\\mathrm{mg}\\mathrm{cm}^{-3}$ and the volumetric capacity of the $\\mathrm{AMPSi@C}$ with an areal mass loading of $0.8\\mathrm{mg}\\dot{\\mathrm{cm}}^{-2}$ after 100 cycles is measured to be $1712\\mathrm{mAh}\\mathrm{cm}^{-3}$ (the lithiated stage) at $0.1\\mathrm{C}$ rate, which is the best value reported from Si-based electrodes so far (Supplementary Fig. 19a)21,40–44. \n\nThe areal capacities of the $\\mathrm{AMPSi@C}$ electrodes with different areal mass loadings from 0.8 to $2.9\\mathrm{mg}\\mathrm{cm}^{-2}$ are shown in Fig. 4d. The capacity of the $\\mathrm{AMPSi@C}$ anode increases linearly with areal mass loading (Supplementary Fig. 19b), indicating that the Si active materials are utilized effectively in spite of the large mass loading. At a high areal mass loading of $\\bar{2.9}\\mathrm{mg}\\mathrm{cm}^{-2}$ , the areal capacities of AMPS $@\\mathrm{C}$ reach $7.1\\mathrm{mA}\\bar{\\mathrm{h}}\\mathrm{cm}^{-2}$ at $\\bar{0}.1\\mathrm{mA}\\mathrm{cm}^{-2}$ and $3.{\\overset{\\circ}{9}}\\operatorname{mAh}\\operatorname{cm}^{-2}$ at $1.2\\mathrm{mA}\\mathrm{cm}^{-2}$ after 100 cycles. These values are higher than those of most of the reported Si anodes5,10,14,26,45–48. Generally, when the mass loading of Si is increased to achieve a larger areal capacity, cycle performance tends to worsen due to the increased serial resistance of the particle-electrolyte interface and electrode-level disintegration49. However, the $\\mathrm{AMPSi@C}$ electrode with a high mass loading still displays good stable cycle stability and excellent rate characteristics (Supplementary Fig. 19c, d) confirming that bulk nanoporous structure of $\\mathrm{AMPSi@C}$ electrode is favorable to $\\mathrm{Li^{+}}$ accessibility and electron transport. \n\nTo further evaluate the practicality of $\\mathrm{AMPSi@C}$ in LIBs, a full battery is assembled with the commercial $\\mathrm{Li}(\\mathrm{Ni}_{1/3}\\mathrm{Co}_{1/3}\\mathrm{Mn}_{1/3})\\mathrm{O}_{2}$ (NCM) cathode and prelithiated $\\mathrm{AMPSi@C}$ anode. The full-cell test is done with an anode limited capacity ratio of 1.1:1 considering safety and capacity matching of the full cell during cycling50. The prelithiation procedure is conducted in a half-cell by the first discharging process and the working electrode $({\\mathrm{\\AAMPSi@C}})$ is lithiated to $0.01\\mathrm{V}$ at a $0.05\\mathrm{C}$ rate by the galvanostatic discharging method (see details in Methods). The typical charging-discharging curves of the $\\mathrm{AMPSi@C//NCM}$ full cell with a cutoff voltage of $2.80{-}4.25\\mathrm{V}$ is shown in Supplementary Fig. 20a and Fig. 4e depicts the cycle stability. The AMPSi@C//NCM full cell delivers a high reversible capacity of $134\\mathrm{mAhg^{-1}}$ at $0.5\\mathrm{C}$ $\\mathrm{1C=160\\mAg^{-1}}$ based on cathode active material) with capacity retention of $84\\%$ for over 400 cycles. Moreover, the full battery exhibits a high rate capability of 118 mAh $\\mathbf{g}^{-1}$ at $1.0\\mathrm{C}$ (Fig. 4f). The corresponding CE is shown in the inset in Fig. 4e. The ICE of the AMPSi@C//NCM full cell is $94\\%$ and the later CE reaches $99.9\\%$ after 10 cycles (inset of Fig. 4e). The full cell has an average voltage of $3.75\\mathrm{V}$ and the discharge capacity is $134\\mathrm{mAhg^{-1}}$ at $0.5\\mathrm{C}_{:}$ , thus, the full cycle can deliver a high-energy density of $502\\mathrm{Wh}\\mathrm{kg}^{-1}$ outperforming previously reported Si-based full cells4,46 (Supplementary Table 1 and 2). For comparison, we also evaluate the cycling performance of full cells using $\\mathrm{AMPSi@C}$ anodes without prelithiation (Supplementary Fig. 20b). It shows a lower ICE of $83.1\\%$ , lower capacity, and poor cycle stability than the prelithiated $\\mathrm{AMPSi@C}$ anode, indicating that prelithiation is necessary to enhance the performance of the full cell. \n\n![](images/29c1f9c07dd5e84b3b2bfd7f2da83922d14378979087eeb0f31127f17fbc4723.jpg) \nFig. 5 Electrode swelling measurements of AMPSi $@{\\mathsf{C}}$ . Cross-sectional SEM images of the AMPSi $@{\\mathsf{C}}$ electrode films a before cycling, b after full lithiation, and c delithiation, respectively (scale bar for a, b, and $\\pmb{\\mathsf{c}}=20\\upmu\\mathrm{m}\\dot{}$ ). d–f Corresponding top-view SEM images (scale bar for $\\mathsf{d-f}{=}100\\upmu\\mathrm{m}$ and scale bar for insets $=20\\upmu\\mathrm{m};$ ). g–i TEM images of $\\mathsf{A M P S i@C}_{\\mathsf{\\Pi}}$ lithated AMPS $\\ @{\\mathsf C}$ and delithiated AMPS $\\mathtt{\\Pi}_{\\mathtt{(a)C}}$ (scale bar for g– $\\cdot\\mathsf{i}=1\\upmu\\mathsf{m}$ and scale bar for insets $=100\\mathsf{n m}$ ) \n\n![](images/6d7f2092830a2957a859256f71ab90a49b2e35a525bf4fa3ed8241bacfa4c8fb.jpg) \nFig. 6 In situ lithiation/delithiation behavior of ${\\mathsf{A M P S i@C}}.$ . a Schematic of in situ nanobattery configuration. b–g Time-resolved TEM images depicting the lithiation process of $A M P S i@C$ electrode (Supplementary Movie 1). After full lithiation, AMPS $\\ @{\\mathsf C}$ exhibits inward expansion and does not show cracks and pulverization. h–k In situ TEM images of AMPS $\\mathtt{\\Pi}_{\\mathtt{\\Pi}\\mathtt{\\backslash}\\mathtt{\\left(\\overline{{a}}\\right)}\\mathtt{C}}$ after different cycles (Supplementary Movie 2) showing a stable structure during repeated cycling. Scale bar for $\\mathbf{b}\\mathbf{-}\\mathbf{k}=200\\mathsf{n m}$ \n\nElectrode swelling and in situ lithiation of AMPSi@C. Electrode swelling is a show stopper for commercial implementation of Sibased LIBs but often ignored in Si anode research. Large electrode swelling of Si anodes undermines the long-term cycling stability and safety. The cross-sectional SEM images show that the pristine $\\mathrm{AMPSi@C}$ electrode film has an average thickness of $15.8\\upmu\\mathrm{m}$ (Fig. 5a) and after full lithiation, the electrode thickness increases to $17.4\\upmu\\mathrm{m}$ (Fig. 5b) with $10.1\\%$ thickness swelling. After full delithiation, the electrode thickness recovers to $16.2\\upmu\\mathrm{m}$ (Fig.5c), indicating negligible thickness change. The small swelling and negligible thickness fluctuation of the $\\mathrm{AMPSi@C}$ electrode ensure superior stability and safety in practice. The corresponding topview SEM images reveal that the $\\mathrm{AMPSi@C}$ electrode shows no observable mechanical damage such as cracking or fracture during cycling (Fig. 5d–f). More importantly, the microstructure of AMPSi $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ remains intact even after 1000 cycles, confirming the high structure stability and integrality during cycling as shown by the TEM images (Fig. 5g–i). Electrode thickness swelling of the Si anodes with different areal capacities of 3.5–7.1 $\\mathrm{m}\\bar{\\mathrm{Ah}}\\mathrm{cm}^{-2}$ is also assessed (Supplementary Fig. 21). The AMP$\\mathrm{Si@C}$ electrodes with thicknesses of 25.8, 34.7, and $45.1\\upmu\\mathrm{m}$ deliver areal capacities of 3.5, 5.1, and $7.1\\mathrm{mAh}\\mathrm{cm}^{-2}$ . After full lithiation, the electrode thicknesses increase to 29.4, 40.9, and $55.3\\upmu\\mathrm{m}$ , corresponding to $14.0\\%$ , $17.8\\%$ , and $22.6\\%$ electrode swelling, respectively, as shown in Supplementary Fig. 22. These values are much smaller than those of previously reported Si anodes11,15,25–27,47,48 (Supplementary Table 1). The large areal capacity and small electrode thickness swelling suggest promising applications of $\\mathrm{AMPSi@C}$ in high-energy LIBs. \n\nThe structural evolution of $\\mathrm{AMPSi@C}$ during lithiation is observed by in situ TEM using a nanobattery setup as schematically shown in Fig. 6a. AMPSi $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ is attached on a gold tip and then connected to $\\mathrm{Li}/\\mathrm{Li}_{2}\\mathrm{O}$ on a tungsten (W) tip. The asformed thin $\\mathrm{Li}_{2}\\mathrm{O}$ layer on Li serves as a solid electrolyte. The $\\mathrm{AMPSi@C}$ is lithiated when a negative bias $(-3\\mathrm{~V})$ is applied to the W end and the delithiation process of $\\mathrm{AMPSi@C}$ is realized when applying a positive bias. When the Li source comes in close contact, Li ions diffuse quickly from the contact point to the AMPSi $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ via wave propagation-like motion51. The structural changes of $\\mathrm{AMPSi@C}$ during lithiation is monitored by the timeresolved TEM images in Fig. $6\\mathsf{b-g}$ captured from in situ videos (Supplementary Movie 1). As lithiation proceeds, the Si framework maintains its intrinsic structure without any notable particle-level outward expansion (Supplementary Movie 1), which is confirmed by the similar projected area of $\\mathrm{AMPSi@C}$ during lithiation process. However, the magnified TEM images (Supplementary Fig. 23) of the pristine state, first lithiated state, and forth lithiated state of AMPSi@C demonstrate pore filling (shown in the red region) and at the same time, the particle size increases and shape changes (shown by the blue arrow). To further study the volume change of the electrode materials, snapshots are taken during lithiation by taking in situ TEM video (Supplementary Movie 2) of a representative Si particle in AMPSi $\\boldsymbol{\\mathcal{Q}}\\boldsymbol{\\mathrm{C}}$ at different lithiation time as shown in Supplementary Fig. 24. The size of the partial Si skeleton (shown in red region) is measured to be 105, 112, 117, and $125\\mathrm{nm}$ after lithiation for 3, 20, 40, and $60\\mathrm{s},$ respectively. Meanwhile, the pore (shown in yellow region) is filled accordingly. The robust structural stability of $\\mathrm{AMPSi@C}$ is further confirmed by in situ TEM during fast lithiation/delithiation cycling (Figs. 6h– $\\mathbf{\\nabla}\\cdot\\mathbf{k}$ and Supplementary Movie 2). As shown in Figs. 6h–k, even when a large constant bias of $-6/6\\mathrm{V}$ is applied, $\\mathrm{AMPSi@C}$ shows inward expansion of Si nano skeleton without any notable structural change during four lithiation/delithiation cycles (Supplementary Movie 2). In situ TEM is also performed on $\\mathrm{AMPSi@C}$ at a higher negative bias $(-9\\mathrm{V})$ . As shown in Supplementary Movie 3, the $\\mathrm{\\bar{AMPSi@C}}$ shows a sudden change leading to abrupt inward expansion of the Si nanoskeleton due to the fast lithiation rate. Nonetheless, the structure of $\\mathrm{AMPSi@C}$ is sufficiently robust without showing observable mechanical degradation. \n\nThe in situ TEM results indicate that $\\mathrm{AMPSi@C}$ remains stable without cracking and lithiation induced volume expansion of nanoligaments is largely accommodated by the surrounding pores. The inward volume expansion of AMPSi@C enables minimum particle-level outer expansion during lithiation/ delithiation cycling, giving rise to small swelling and excellent cycling performance. Moreover, the outer carbon coating enhances electron/ion transport and acts as a protective layer to stabilize SEI on the AMPSi@C electrode resulting in the excellent electrochemical properties. \n\n# Discussion \n\nA vapor dealloying reaction to produce AMPSi from the $\\mathrm{Mg-Si}$ alloy via a low-cost and scalable top-down approach is designed and described. At $750^{\\circ}\\mathrm{C},$ $\\mathbf{\\mathrm{{Mg}}}$ reacts with $\\Nu_{2}$ to form liquid $\\mathrm{Mg}_{3}\\mathrm{N}_{2}^{52}$ and solid Si is separated producing the $\\mathrm{Mg}_{3}\\mathrm{N}_{2}/\\mathrm{Si}$ heterostructure. The in situ generated liquid $\\mathrm{Mg}_{3}\\mathrm{N}_{2}$ acts as the selftemplate and filler in the $\\mathrm{Mg}_{3}\\mathrm{N}_{2}/\\mathrm{Si}$ hybrid. After removing $\\mathrm{Mg}_{3}\\mathrm{\\bar{N}}_{2}$ in an acidic solution, the bulk Si microparticles are produced, which consist of a bicontinuous porous network and crystalline Si nanoligaments resembling ant nests. The pore size and porosity of AMPSi can be adjusted by varying the $\\mathbf{Mg}$ concentration in the $\\mathrm{Mg-Si}$ alloy and nitridation temperature. Moreover, the $\\mathrm{MgCl}_{2}$ by-product can be converted into $\\mathbf{Mg}$ for recycling. This top-down method is simple and economical and can be scaled up for commercial production. In fact, we can produce $3{-}5\\upmu\\mathrm{m}$ AMPSi particles in $110\\mathrm{g}$ per batch in our laboratory using conventional tube furnaces (Supplementary Fig. 2d). \n\nThe superior electrochemical properties of AMPSi@C can be attributed to the ant-nest-like structure, which integrates the intrinsic merits of nanoscale and microscale Si. The 3D bicontinuous nanopores enable fast diffusion of the electrolyte and high ${\\mathrm{Li^{+}}}$ accessibility, whereas the interconnected nanoscale Si ligaments prevent pulverization and cracking. The bicontinuous nanoporous network allows inward volume expansion of Si nanoligaments without obvious particle size change. Our in situ TEM results reveal that the volume change of the Si ligaments is accommodated by the surrounding pores through reversible inward Li breathing without obvious particle size expansion. The as-obtained $\\mathrm{AMPSi@C}$ has a porosity of $64.3\\%$ . The maximum volume accommodation limitation $(\\Delta V)$ of $\\mathrm{AMPSi@C}$ is calculated to be $280\\%$ according to the equation: $\\Delta V=V_{\\mathrm{Porosity}}/V_{\\mathrm{Si}}+1$ without considering binders and conductive additives17,53. Here, $V_{\\mathrm{Porosity}}$ is the pore volume and $V_{\\mathrm{Si}}$ is the volume of solid Si. The large $\\Delta V$ of $280\\%$ gives rise to a lithiation capacity of ${\\sim}23\\bar{8}2\\ \\mathrm{mAh}\\ \\mathrm{g}^{-1}$ that is higher than that of $\\mathrm{AMPSi@C}$ 1 $2134\\mathrm{mAhg^{-1}}$ at $0.1\\mathrm{C})$ and therefore, in situ TEM demonstrates negligible particle-level outward expansion of AMPSi@C upon lithiation (Supplementary Movie 1–3). The bulk $\\mathrm{AMPSi@C}$ shows a large tap density and the carbon coating enhances electron/ion transport. Hence, $\\mathrm{AMPSi@C}$ exhibits enhanced capacity retention and cycling life in comparison with other Si-based anodes. Moreover, inward Li breathing in $\\mathrm{AMPSi@C}$ gives rise to minimal electrode swelling and large volumetric capacity at the lithiated state. The full cell composed of $\\mathrm{Li(Ni_{1/3}C o_{1/3}M n_{1/3})O_{2}//}$ $\\mathrm{AMPSi@C}$ has a high-energy density of $502\\mathrm{Wh}\\mathrm{kg}^{-1}$ and superior cycle stability with $84\\%$ capacity retention after 400 cycles. Owing to self-volume expansion effect of $\\mathrm{AMPSi@C}$ with negligible particle-level outer expansion, low thickness swelling is achieved in spite of a large areal mass loading and electrode thickness (Supplementary Fig. 21). \n\nIn summary, a simple, economical, and scalable nitrogen dealloying technique to fabricate ant-nest-like microscale porous Si from the Mg-Si alloy is reported for the first time. The asobtained $\\mathrm{AMPSi@C}$ has continuous pores and interconnected crystalline Si nanoligaments thereby overcoming technical hurdles which have hampered the use of bulk microscale Si in highperformance practical anodes in LIBs. The new design of AMP$\\mathrm{Si@C}$ simultaneously improves the tap density and electrochemical stability to achieve large volumetric capacity and longterm cycling stability for LIBs. In situ TEM reveals the selfvolume inward expansion mechanism of $\\mathrm{AMPSi@C}$ , which effectively mitigates electrochemically-induced mechanical degradation of the $\\mathrm{AMPSi@C}$ electrode during cycling and the bulk AMPSi anode shows less than $20\\%$ electrode thickness swelling even at a high areal capacity of $5.1\\mathrm{mAh}\\mathrm{cm}^{-2}$ . By virtue of these unique structural features, the $\\mathrm{AMPSi@C}$ electrode shows superior rate capability and long-term cycling stability in full cells with a high-energy density of 502 Wh $\\mathrm{\\dot{K}g^{-1}}$ . Our findings offer insights into the rational design of alloy-based materials that normally undergo large volume changes during operation and application for advanced electrochemical energy storage. \n\n# Methods \n\nSynthesis of Mg-Si alloy. The metallurgical Si purchased from Jinzhou Haixin Metal Materials Co., Ltd. was milled to $1-3\\upmu\\mathrm{m}$ with a sand mill (Shenzhen Sanxing Feirong Machine Co., Ltd) and then $2.8\\:\\mathrm{g}$ of the milled Si powers were mixed with $5\\mathrm{g}$ of $\\mathrm{i}\\mathrm{g}$ powders (200 mesh, Sinopharm Chemical Reagent Co., Ltd) to form $\\mathrm{Mg}_{2}\\mathrm{Si}$ in a stainless steel reactor heated to $550^{\\circ}\\mathrm{C}$ for $\\boldsymbol{4}\\mathrm{h}$ . \n\nSynthesis of AMPSi and NS-MPSi. The $\\mathrm{Mg}_{2}\\mathrm{Si}$ powders $(3-5\\upmu\\mathrm{m})$ were thermally nitrided in $\\Nu_{2}$ at $750^{\\circ}\\mathrm{C}$ . After thermal reaction, the powders were immersed into 1 M diluted hydrochloric acid to remove $\\mathrm{Mg}_{3}\\mathrm{N}_{2}$ and the AMPSi powers were collected by filtration. We also prepared nanoparticles assembled 3D mesoporous Si (NS-MPSi) by evaporating $\\mathbf{Mg}$ from $\\mathrm{Mg}_{2}\\mathrm{Si}$ at $900^{\\circ}\\mathrm{C}$ under vacuum for $^{6\\mathrm{h}}$ as the control sample. \n\nSynthesis of carbon coating AMPSi (AMPSi@C). $0.4\\:\\mathrm{g}$ of AMPSi and $0.48\\mathrm{g}$ of 2-amino-2-hydroxymethylpropane-1,3-diol (Sigma–Aldrich, $98\\%$ ) were dispersed in $400\\mathrm{ml}$ of deionized water and $0.6\\:\\mathrm{g}$ of dopamine hydrochloride (Aladdin, $98\\%$ ) were added under mechanical stirring. The polydopamine-coated AMPSi product was collected by filtration and then heated at $850^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ in $\\mathrm{Ar/H}_{2}$ . During this process, the polydopamine coating was carbonized into a thin N-doped carbon shell and the final product of AMPSi@C was obtained. \n\nMaterials characterization. The morphology and microstructure of the AMPSi and $\\mathrm{AMPSi@C}$ were characterized by field-emission scanning electron microscopy (FE-SEM, FEI Nano 450), transmission electron microscopy (TEM, FEI Titan $60{-}300~\\mathrm{Cs})$ , and high-resolution TEM (HR-TEM, Tecnai G20). The crystal structure, chemical compositions and chemical bonds of materials were characterized by X-ray diffraction (GAXRD, Philips X’Pert Pro), X-ray photoelectron spectroscopy (XPS, ESCALB MK-II, VG Instruments, UK), energy-dispersive Xray spectroscopy (EDS, Bruker, Super-X), Raman scattering (HB RamLab), and Fourier transform infrared spectroscopy (FTIR, VERTEX 70, Bruker). The surface areas were measured via Brunauer-Emmett-Teller (BET, Micrometrics, ASAP2010) method and the porosity was determined using the mercury porosimeter (Micromeritics, AutoPore V). The 3D structure of AMPSi was obtained by tomographic reconstruction strategy, which was carried out via the total variation based simultaneous algebraic reconstruction technique with synchrotron radiation (National Synchrotron Radiation Laboratory, Hefei, Anhui, China). Thermogravimetry (TG, STA449/6/GNETZSCH) was carried out from 30 to $1000^{\\circ}\\mathrm{C}$ at a rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ in air. The tap density was measured on a vibration density tester (Dandong Haoyu, HY-100B). \n\nIn situ TEM. The typical nanobattery setup consisted of the working electrode $(\\mathrm{AMPSi@C})$ , the counter electrode (Li metal), and the solid electrolyte of a naturally grown $\\mathrm{Li}_{2}\\mathrm O$ layer. A gold wire was used to capture the AMPSi@C particle by scratching the AMPSi@C sample, which was then transferred and loaded into the nanofactory TEM-scanning tunneling microscope (STM) specimen holder54. A tungsten tip was used to scratch Li metal and inserted into a holder in a glove box. Then, the holder was quickly transferred to the TEM instrument (JEOL-2100) and natural thin $\\mathrm{Li}_{2}\\mathrm O$ layer was formed on the surface of Li metal due to the native oxidation in air. The $\\mathrm{Li}_{2}\\mathrm O$ layer on the tungsten tip was controlled to contact $\\mathrm{AMPSi@C}$ to complete the nanobattery construction. The Li ions go through the $\\mathrm{Li}_{2}\\mathrm O$ layer to alloy with Si at the working electrode under applied voltages of $^{-3}$ , $^{-6,}$ and $-9\\mathrm{~V~}$ . \n\nElectrochemical tests and electrode swelling measurements. The electrodes were fabricated via the mixture of active materials, Super-P carbon black, and sodium alginate in water solution to form a slurry at a mass ratio of 8:1:1. The aqueous slurry was coated on a Cu foil by an automatic thick film coater (MTI, MSK-AFA-III) with mass loadings on the electrode of $0.8{-}2.9\\mathrm{mg}\\mathrm{cm}^{-2}$ . After vacuum drying, the electrode with a diameter of $12\\mathrm{mm}$ was prepared with a manual rolling machine. The coin cells (CR2016 type) were assembled in a glove box (Vigor SG1200/750TS-C) by using a Celgard 2400 film as separator, Li foil as a counter electrode, and $1\\mathrm{M}\\mathrm{LiPF}_{6}$ in a mixture of diethyl carbonate and ethylene carbonate (1:1) with $6\\mathrm{wt.\\%}$ VC or FEC additives as the electrolyte. The electrochemical measurements were carried out on the battery tester LANDCT2001A (Wuhan LAND electronics Co., Ltd., China). Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were conducted on a CHI750e electrochemical workstation (Shanghai CH Instrument Company, China). The full cells were assembled with prelithiated $\\mathrm{AMPSi@C}$ as the anode and commercial $\\mathrm{Li}(\\mathrm{Ni}_{1/3}\\mathrm{Co}_{1/3}\\mathrm{Mn}_{1/3})\\mathrm{O}_{2}$ (NCM) as the cathode. The ratio of negative electrode and positive electrode capacity was about 1.1:1. Galvanostatic charging/discharging was carried out to evaluate the electrochemical performance between $2.8\\dot{\\mathrm{V}}$ and $4.25\\mathrm{V}$ at $0.5\\mathrm{C}$ ( $1{\\mathrm{C}}=160{\\mathrm{mA}}{\\mathrm{g}}^{-1}$ based on the cathode active material). Electrochemical prelithiation of $\\mathrm{AMPSi@C}$ was conducted on the anode of a coin-like half-cell with $\\mathrm{AMPSi@C}$ as the working electrode and Li foil as the counter electrode. The prelithiation process was conducted via the first discharging process and the working electrode (AMP$\\operatorname{Si@C})$ was lithiated to $0.01\\mathrm{V}$ at a $0.05\\mathrm{C}$ rate by a galvanostatic discharging method and this potential was kept for $30\\mathrm{min}$ . After prelithiation, the half-cell of $\\mathrm{AMPSi@C//Li}$ was disassembled in a glove box and the prelithiated $\\mathrm{AMPSi@C}$ electrode was taken out quickly, which coupled with the $\\mathrm{Li}(\\mathrm{Ni}_{1/3}\\mathrm{Co}_{1/3}\\mathrm{Mn}_{1/3})\\mathrm{O}_{2}$ cathode to form a full cell. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\nReceived: 27 September 2018 Accepted: 15 March 2019 \nPublished online: 29 March 2019 \n\n# References \n\n1. Schmuch, R. et al. Performance and cost of materials for lithium-based rechargeable automotive batteries. Nat. Energy 3, 267–278 (2018). \n\n2. Armand, M. & Tarascon, J. M. Building better batteries. Nature 451, 652–657 (2008). \n3. Hatchard, T. D. et al. In situ XRD and electrochemical study of the reaction of lithium with amorphous silicon. J. Electrochem. Soc. 151, A838–A842 (2004). \n4. Hu, Y. S. et al. Superior storage performance of a $\\mathrm{Si@SiO_{x}/C}$ nanocomposite as anode material for lithium-ion batteries. Angew. Chem. Int. Ed. 47, 1645–1649 (2008). \n5. Li, Y. Z. et al. Growth of conformal graphene cages on micrometre-sized silicon particles as stable battery anodes. Nat. Energy 1, 15029 (2016). \n6. Xu, Q. et al. Watermelon-inspired Si/C microspheres with hierarchical buffer structures for densely compacted lithium-ion battery anodes. Adv. Energy Mater. 7, 1601481 (2016). \n7. Mcdowell, M. T. et al. In situ TEM of two-phase lithiation of amorphous silicon nanospheres. Nano. Lett. 13, 758–764 (2013). \n8. Mcdowell, M. T., Lee, S. W., Nix, W. D. & Cui, Y. 25th anniversary article: understanding the lithiation of silicon and other alloying anodes for lithiumion batteries. Adv. Mater. 25, 4966–4985 (2013). \n9. Wu, H. et al. Stable cycling of double-walled silicon nanotube battery anodes through solid-electrolyte interphase control. Nat. Nanotechnol. 7, 310–315 (2012). \n10. Liu, X. H. et al. Size-dependent fracture of silicon nanoparticles during lithiation. ACS Nano 6, 1522–1531 (2012). \n11. Yi, R. et al. Micro-sized Si-C composite with interconnected nanoscale building blocks as high-performance anodes for practical application in lithium-ion batteries. Adv. Energy Mater. 3, 295–300 (2013). \n12. Du, F. H. et al. Surface binding of polypyrrole on porous silicon hollow nanospheres for Li-ion battery anodes with high structure stability. Adv. Mater. 26, 6145–6150 (2014). \n13. Zhou, H. et al. Role of surface functionality in the electrochemical performance of silicon nanowire anodes for rechargeable lithium batteries. ACS Appl. Mater. Interfaces 6, 7607–7610 (2014). \n14. Zhang, Y. C. et al. Rice husk-derived hierarchical silicon/nitrogen-doped carbon/carbon nanotube spheres as low-cost and high-capacity anodes for lithium-ion batteries. Nano Energy 25, 120–127 (2016). \n15. Chae, S. J. et al. Micron-sized Fe-Cu-Si ternary composite anodes for high energy Li-ion batteries. Energy Environ. Sci. 9, 1251–1257 (2016). \n16. Bang, B. M. et al. High-performance macroporous bulk silicon anodes synthesized by template-free chemical etching. Adv. Energy Mater. 2, 878–883 (2012). \n17. Wada, T. et al. Bulk-nanoporous-silicon negative electrode with extremely high cyclability for lithium-ion batteries prepared using a top-down process. Nano. Lett. 14, 4505–4510 (2014). \n18. Wang, J. et al. Scalable synthesis of defect abundant Si nanorods for highperformance Li-ion battery anodes. ACS Nano 9, 6576–6586 (2015). \n19. Chae, S. J. et al. One-to-one comparison of graphite-blended negative electrodes using silicon nanolayer-embedded graphite versus commercial benchmarking materials for high-energy lithium-ion batteries. Adv. Energy Mater. 7, 1700071 (2017). \n20. Liu, N. et al. A pomegranate-inspired nanoscale design for large-volumechange lithium battery anodes. Nat. Nanotechnol. 9, 187–192 (2014). \n21. Magasinski, A. et al. High-performance lithium-ion anodes using a hierarchical bottom-up approach. Nat. Mater. 9, 353–358 (2010). \n22. Freunberger, S. A. True performance metrics in beyond-intercalation batteries. Nat. Energy 2, 17091 (2017). \n23. Xiao, X. et al. Regulated breathing effect of silicon negative electrode for dramatically enhanced performance of Li-ion battery. Adv. Funct. Mater. 25, 1426–1433 (2015). \n24. Chae, S. et al. Confronting issues of the practical implementation of Si anode in high-energy lithium-ion batteries. Joule 1, 47–60 (2017). \n25. Wang, B. et al. Self-template construction of mesoporous silicon submicrocube anode for advanced lithium ion batteries. Energy Storage Mater. 15, A8389–147 (2018). \n26. Li, X. L. et al. Mesoporous silicon sponge as an anti-pulverization structure for high-performance lithium-ion battery anodes. Nat. Commun. 5, 4105 (2014). \n27. Ngo, D. T. et al. Highly porous coral-like silicon particles synthesized by an ultra-simple thermal-reduction method. J. Mater. Chem. A 6, 2834–2846 (2018). \n28. Kim, N., Park, H., Yoon, N. & Lee, J. K. Zeolite-templated mesoporous silicon particles for advanced lithium-ion battery anodes. ACS Nano 12, 3853–3864 (2018). \n29. Luo, W. et al. Surface and interface engineering of silicon-based anode materials for lithium-ion batteries. Adv. Energy Mater. 7, 1701083 (2017). \n30. Fang, S. et al. Raspberry-like nanostructured silicon composite anode for high-performance lithium-ion batteries. ACS Appl. Mater. Inter 9, 18766–18773 (2017). \n31. Ryu, I., Choi, J. W., Cui, Y. & Nix, W. D. Size-dependent fracture of Si nanowire battery anodes. J. Mech. Phys. Solids 59, 1717–1730 (2011). \n32. Lee, J. I. et al. High-performance silicon-based multicomponent battery anodes produced via synergistic coupling of multifunctional coating layers. Energy Environ. Sci. 8, 2075–2084 (2015). \n33. Jia, H. P. et al. A novel approach to synthesize micrometer-sized porous silicon as a high performance anode for lithium-ion batteries. Nano Energy 50, 589–597 (2018). \n34. Yoon, T. et al. Mesoporous silicon hollow nanocubes derived from metalorganic framework template for advanced Li-ion battery anode. ACS Nano 11, 4808–4815 (2017). \n35. Gauthier, M. et al. A low-cost and high performance ball-milled Si-based negative electrode for high-energy Li-ion batteries. Energy Environ. Sci. 6, 2145–2155 (2013). \n36. Song, J. X. et al. Micro-sized silicon-carbon composites composed of carboncoated sub- $10\\ \\mathrm{nm\\Si}$ primary particles as high-performance anode materials for lithium-ion batteries. J. Mater. Chem. A 2, 1257–1262 (2013). \n37. Sohn, H. S. et al. Semimicro-size agglomerate structured silicon-carbon composite as an anode material for high performance lithium-ion batteries. J. Power Sources 334, 128–136 (2016). \n38. An, Y. et al. Green, scalable, and controllable fabrication of nanoporous silicon from commercial alloy precursors for high-energy lithium-ion batteries. ACS Nano 12, 4993–5002 (2018). \n39. Jin, Y. et al. Understanding fluoroethylene carbonate and vinylene carbonate based electrolytes for Si anodes in lithium ion batteries with NMR spectroscopy. J. Am. Chem. Soc. 140, 9854–9867 (2018). \n40. Jeong, S. et al. Etched graphite with internally grown Si nanowires from pores as an anode for high density Li-ion batteries. Nano. Lett. 13, 3403–3407 (2013). \n41. Choi, J. W. et al. Metal current collector-free freestanding silicon-carbon 1D nanocomposites for ultralight anodes in lithium ion batteries. J. Power Sources 195, 8311–8316 (2010). \n42. Wang, B. et al. High volumetric capacity silicon-based lithium battery anodes by nanoscale system engineering. Nano. Lett. 13, 5578–5584 (2013). \n43. Kovalenko, I. et al. A major constituent of brown algae for use in highcapacity Li-ion batteries. Science 334, 75–79 (2011). \n44. Yang, J. et al. Self-healing sei enables full-cell cycling of a silicon-majority anode with a coulombic efficiency exceeding $99.9\\%$ . Energy Environ. Sci. 10, 580–592 (2017). \n45. Lin, D. et al. High tap density secondary silicon particle anodes by scalable mechanical pressing for lithium-ion batteries. Energy Environ. Sci. 8, 2371–2376 (2015). \n46. Hassoun, J., Lee, K. S., Sun, Y. K. & Scrosati, B. An advanced lithium ion battery based on high performance electrode materials. J. Am. Chem. Soc. 133, 3139–3143 (2011). \n47. Xiao, Q. F. et al. Inward lithium-ion breathing of hierarchically porous silicon anodes. Nat. Commun. 6, 8844 (2015). \n48. Zhang, Q. et al. Harnessing the concurrent reaction dynamics in active Si and Ge to achieve high performance lithium-ion batteries. Energy Environ. Sci. 11, 669–681 (2018). \n49. Wang, L. et al. Highly stretchable conductive glue for high-performance silicon anodes in advanced lithium-ion batteries. Adv. Funct. Mater. 28, 1704858 (2018). \n50. Park, J. K. (ed.) Principles and applications of lithium secondary batteries (John Wiley & Sons, Weinheim 2012). \n51. Jung, C. H., Choi, J., Kim, W. S. & Hong, S. H. A nanopore-embedded graphitic carbon shell on silicon anode for high performance lithium ion batteries. J. Mater. Chem. A 6, 8013–8020 (2018). \n52. Uchida, H. et al. Synthesis of magnesium silicon nitride by the nitridation of powders in the magnesium-silicon system. J. Ceram. Soc. Jpn 105, 934–939 (1997). \n53. Obrovac, M. N., Christensen, L., Le, D. B. & Dahn, J. R. Alloy design for lithium-ion battery anodes. J. Electrochem. Soc. 154, A849–A855 (2007). \n54. Li, X. K. et al. In-situ electron microscopy observation of electrochemical sodium plating and stripping dynamics on carbon nanofiber current collectors. Nano Energy 42, 122–128 (2017). \n\n# Acknowledgements \n\nThis work was financially supported by National Natural Science Foundation of China (No. 51572100, 21875080, 51504171, 21703185, and 61434001), Major Project of Technology Innovation of Hubei Province (2018AAA011), HUST Key Interdisciplinary Team Project (2016JCTD101), Wuhan Yellow Crane Talents Program, and City University of Hong Kong Applied Research Grant (ARG) No. 9667122 and Hong Kong Research Grants Council (RGC) General Research Funds (GRF) No. CityU 11205617. The authors are grateful for the facility support provided by the Nanodevices and Characterization Centre of WNLO-HUST and Analytical and Testing Center of HUST. The authors thank Prof. Yong Guan (National Synchrotron Radiation Laboratory, Hefei, China) and Prof. Yonghui Song (University of Science and Technology of China) for Synchrotron radiation 3D tomographic reconstruction images of the AMPSi and also thank Prof. Qihui Wu (Jimei University) for XPS characterizations. \n\n# Author contributions \n\nK.H. designed the idea and protocol of this work. W.A. and B.G. prepared the materials, carried out the thermogravimetric analysis, XRD, BET and mercury porosimetry and cowrote the draft. W.A., B.G., J.F. and B.X. conducted the electrochemical tests. S.M. obtained the SEM images. L.W. carried out the TEM characterizations. B.G. and Q.Z. obtained and analyzed the in situ TEM. K.H., W.A., B.G. and P.K.C. discussed the results and co-wrote the manuscript. \n\n# Additional information \n\nSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467- 019-09510-5. \n\nCompeting interests: The authors declare no competing interests. \n\nReprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ \n\nJournal peer review information: Nature Communications thanks the anonymous reviewer (s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2019 " + }, + { + "id": "10.1039_c9ee01384a", + "DOI": "10.1039/c9ee01384a", + "DOI Link": "http://dx.doi.org/10.1039/c9ee01384a", + "Relative Dir Path": "mds/10.1039_c9ee01384a", + "Article Title": "Redefining the Robeson upper bounds for CO2/CH4 and CO2/N2 separations using a series of ultrapermeable benzotriptycene-based polymers of intrinsic microporosity", + "Authors": "Comesaña-Gándara, B; Chen, J; Bezzu, CG; Carta, M; Rose, I; Ferrari, MC; Esposito, E; Fuoco, A; Jansen, JC; McKeown, NB", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "Membranes composed of Polymers of Intrinsic Microporosity (PIMs) have the potential for energy efficient industrial gas separations. Here we report the synthesis and gas permeability data of a series of ultrapermeable PIMs, of two-dimensional chain conformation and based on benzotriptycene structural units, that demonstrate remarkable ideal selectivity for most gas pairs of importance. In particular, the CO2 ultrapermeability and high selectivity for CO2 over CH4, of key importance for the upgrading of natural gas and biogas, and for CO2 over N2, of importance for cost-effective carbon capture from power plants, exceed the performance of the current state-of-the-art polymers. All of the gas permeability data from this series of benzotriptycene-based PIMs are placed well above the current 2008 Robeson upper bounds for CO2/CH4 and CO2/N2. Indeed, the data for some of these polymers fall into a linear correlation on the benchmark Robeson plots [i.e. log(PCO2/PCH4) versus log PCO2 and log(PCO2/PN2) versus log PCO2], which are parallel to, but significantly above, that of the 2008 CO2/CH4 and CO2/N2 upper bounds, allowing their revision. The redefinition of these upper bounds sets new aspirational targets for polymer chemists to aim for and will result in more attractive parametric estimates of energy and cost efficiencies for carbon capture and natural/bio gas upgrading using state-of-the-art CO2 separation membranes.", + "Times Cited, WoS Core": 611, + "Times Cited, All Databases": 641, + "Publication Year": 2019, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000486019600007", + "Markdown": "# Redefining the Robeson upper bounds for ${\\mathsf{C O}}_{2}/$ $C H_{4}$ and $\\cos_{2}/N_{2}$ separations using a series of ultrapermeable benzotriptycene-based polymers of intrinsic microporosity† \n\nBibiana Comesan˜a-Ga´ndara, ‡a Jie Chen,‡a C. Grazia Bezzu, $\\textcircled{1}$ Mariolino Carta, $\\textcircled{10}^{\\flat}$ Ian Rose,a Maria-Chiara Ferrari,c Elisa Esposito, Alessio Fuoco, d Johannes C. Jansen $\\textcircled{1}$ \\*d and Neil B. McKeown $\\textcircled{1}$ a \n\nMembranes composed of Polymers of Intrinsic Microporosity (PIMs) have the potential for energy efficient industrial gas separations. Here we report the synthesis and gas permeability data of a series of ultrapermeable PIMs, of two-dimensional chain conformation and based on benzotriptycene structural units, that demonstrate remarkable ideal selectivity for most gas pairs of importance. In particular, the ${\\mathsf{C O}}_{2}$ ultrapermeability and high selectivity for ${\\mathsf{C O}}_{2}$ over $C H_{4},$ of key importance for the upgrading of natural gas and biogas, and for ${\\mathsf{C O}}_{2}$ over ${\\sf N}_{2},$ of importance for cost-effective carbon capture from power plants, exceed the performance of the current state-of-the-art polymers. All of the gas permeability data from this series of benzotriptycene-based PIMs are placed well above the current 2008 Robeson upper bounds for ${\\mathsf{C O}}_{2}/{\\mathsf{C H}}_{4}$ and $C O_{2}/N_{2}$ Indeed, the data for some of these polymers fall into a linear correlation on the benchmark Robeson plots [i.e. $\\mathsf{l o g}(P_{\\mathrm{CO}_{2}}/P_{\\mathrm{CH}_{4}})$ versus $\\mathsf{l o g}P_{\\mathsf{C O}_{2}}$ and $\\mathsf{l o g}(P_{\\mathrm{CO}_{2}}/P_{\\mathsf{N}_{2}})$ versus $\\mathsf{l o g}P_{\\mathsf{C O}_{2}}\\mathrm{l}.$ which are parallel to, but significantly above, that of the 2008 ${\\mathsf{C O}}_{2}/{\\mathsf{C H}}_{4}$ and ${C O_{2}}/{N_{2}}$ upper bounds, allowing their revision. The redefinition of these upper bounds sets new aspirational targets for polymer chemists to aim for and will result in more attractive parametric estimates of energy and cost efficiencies for carbon capture and natural/bio gas upgrading using state-of-the-art ${\\mathsf{C O}}_{2}$ separation membranes. \n\nrsc.li/ees \n\n# Broader context \n\nThe low-cost and energy-effective removal of carbon dioxide $\\left(\\mathbf{CO}_{2}\\right)$ from natural gas and biogas would help the supply of methane as the cleanest burning and lowest carbon-emitting hydrocarbon fuel. In addition, carbon capture and storage (CCS) from power plant emissions will be required to achieve the goals of the 2015 Paris Agreement, which aspires to maintain global warming to less than $1.5^{\\circ}\\mathrm{C}$ above that of the pre-industrial age by the end of the 21st Century. Indeed, the combined use of biofuels, such as biogas, and CCS technology is regarded as the key negative emissions technology required in order to reach the Agreement’s ambitious targets for reduced emissions. Despite the urgent need for CCS, the best technology platform for its delivery is still unclear due to the difficulties in the estimation of costs and the complex evaluation of the advantages and disadvantages associated with each technology. Highly permeable membranes that are selective for $\\mathbf{CO}_{2}$ over methane $\\mathrm{(CO_{2}/C H_{4})}$ and $\\mathbf{CO}_{2}$ over nitrogen $\\left(\\mathrm{CO}_{2}/\\mathrm{N}_{2}\\right)$ are of increasing interest for natural gas/biogas upgrading and carbon capture, respectively, due to the inherent efficiency of membrane separations. Here we report the synthesis of a series of ultrapermeable polymers that define the state-of-the-art in the trade-off between permeability and selectivity for all important gas separations and, in particular, for $\\mathrm{CO_{2}/C H_{4}}$ and $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ . The data from these polymers were used to redefine the benchmark Robeson upper bounds for these two gas separations at much higher values of selectivity. This enhancement will improve the credibility of polymer membranes for $\\mathbf{CO}_{2}$ separations when evaluated against competing processes. Hopefully, this will help to stimulate the fundamental polymer science and applied engineering required to develop membrane systems for these $\\mathbf{CO}_{2}$ separations of key importance to energy and the environment. \n\n# Introduction \n\nMembranes based on polymers as the selective layer are used for the energy efficient separation of gas mixtures including those of key relevance to energy and the environment.1–4 The development of new polymers with greater gas permeability and selectivity would further enhance the efficiency of membrane gas separations of current industrial interest,5 including hydrogen recovery during ammonia preparation ( $\\mathbf{\\tilde{H}}_{2}$ from $\\mathbf{N}_{2}\\mathbf{\\dot{\\Omega}}$ , oxygen or nitrogen enrichment of air $\\mathbf{\\bar{(O_{2}}}$ from $\\mathbf{N}_{2}$ )6 and natural gas or biogas upgrading (predominantly $\\mathbf{CO}_{2}$ from $\\mathrm{CH}_{4}^{\\cdot}$ ).7–10 Increasingly, polymer membranes are also being considered as a practical alternative to solvent absorption for large-scale capture of $\\mathbf{CO}_{2}$ from power plant flue gas (predominantly $\\mathbf{CO}_{2}$ from $\\mathbf{N}_{2}^{\\cdot\\dagger}$ ).7,9,11–14 For gas separations on such a massive scale, membranes with very high permeance (i.e. flux) are desirable to minimise energy costs for gas compression and to reduce the active surface area of the membrane, thereby, optimising the overall size and manufacture cost of the membrane system.5,15 However, polymer membrane materials suffer from the well-established trade-off between gas permeability $\\left(P_{\\mathrm{x}}\\right)$ and selectivity for one gas over another $\\left(P_{\\mathrm{{x}}}/P_{\\mathrm{{y}}}\\right)$ ,16,17 so that established ultrapermeable polymers, such as the polyacetylene poly(trimethylsilylpropyne) (PTMSP),18,19 and recently reported examples20 are insufficiently selective for use in gas separations. \n\nThe general trade-off between polymer permeability and selectivity was first quantified by Robeson in 1991 when he identified upper bounds in plots of $\\log(P_{\\mathrm{x}}/P_{\\mathrm{y}})$ , versus $\\log{P_{\\mathrm{x}}}$ for $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ , $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ , $\\mathrm{He}/\\mathrm{N}_{2}$ , $\\mathrm{{H}}_{2}/\\mathrm{{CH}_{4}}$ , $\\mathrm{He/CH_{4}}$ , $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ , and $\\mathrm{He/H}_{2}$ gas pairs based on the gas permeability of the best performing polymers at that time.21 Subsequently, for a newly prepared polymer (or a mixed matrix membrane)22,23 the position of its gas permeability data relative to the upper bounds on Robeson plots allows for its potential for gas separations to be estimated. Robeson updated all of the upper bounds in 2008 using initial data for two spirobisindane-based Polymers of Intrinsic Microporosity (PIM-1 and PIM-7; Table S1, ESI†),24 whose rigid and contorted macromolecular structures provided exceptionally high permeability with moderate selectivity.25 In addition, data for these two PIMs were also used to define an upper bound for the $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ gas pair, which is of key importance to post-combustion carbon capture but had been considered of no practical interest in 1991.24 Since 2008, many PIMs with enhanced rigidity have demonstrated gas permeability data that lie well above some of the 2008 upper bounds.26 These highly shape-persistent PIMs were obtained by replacing the relatively flexible spirobisindane structural unit with spirobifluorene27,28 units or highly rigid bridged bicyclic components such as ethanoanthracene,29–3 2 triptycene,33–36 methanopentacene37 and Tr¨ogers base.29,35 Indeed, in 2015 \n\nPinnau et al.38 proposed that the $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ , $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ and $\\mathrm{{H}}_{2}/\\mathrm{{CH}_{4}}$ upper bounds should be updated using permeability data from aged films of highly selective triptycene-based PIMs (e.g. PIM-Trip- $\\mathbf{\\cdotTB}^{35}$ and TPIM- ${\\boldsymbol{1}}^{33}$ ). However, revisions of the upper bound for $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ and $\\mathrm{CO_{2}/C H_{4}}$ were not proposed at that time due to the data for these polymers and other high-performing PIMs being close to the existing $2008\\thinspace{\\bf C O}_{2}/{\\bf N}_{2}$ and $\\mathrm{CO_{2}/C H_{4}}$ upper bounds (Table S1, $\\mathrm{ESI\\dag}$ ). \n\nRecently, we introduced a new PIM derived from a benzotriptycene monomer, PIM-TMN-Trip, which proved to be as ultrapermeable to gases as PTMSP due to enhanced intrinsic microporosity arising from its 2D chain structure.39 PIM-TMNTrip demonstrates higher selectivity than PTMSP due to its greater chain rigidity providing enhanced molecular sieving (i.e. diffusivity selectivity). Furthermore, it was found that the unsubstituted benzotriptycene-based PIM (PIM-BTrip) demonstrates even greater selectivity placing its data above the proposed 2015 $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ , $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ and $\\mathrm{{H}}_{2}/\\mathrm{{CH}}_{4}$ upper bounds and even above Robeson’s 2008 upperbounds for $\\mathbf{CO}_{2}/\\mathbf{N}_{2}$ and $\\mathbf{CO}_{2}/$ $\\mathrm{CH}_{4}$ .40,41 Here we report on the synthesis and properties of some new members of the benzotriptycene-based PIM series (Fig. 1), all of which demonstrate high permeability and selectivity. In particular, this polymer series demonstrates permeability data for $\\mathbf{CO}_{2}/\\mathbf{N}_{2}$ and $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ that suggest new positions of the Robeson upper bound for these important gas pairs that are of key interest for separations of relevance to energy and the environment. \n\n# Results and discussion \n\n# Polymer design and synthesis \n\nA further four benzotriptycene PIMs were synthesised along with new batches of PIM-TMN-Trip and PIM-BTrip to allow for direct comparison of their gas permeabilities. The novel polymers include PIM-HMI-Trip, for which the sterically crowded hexamethylindane (HMI)-solubilising group42 would be expected to be more rigid than the tetramethylnaphthalene (TMN) group of PIM-TMN-Trip. Previously for spirobifluorene-based PIMs,43 the introduction of adjacent methyl substituents had been shown to be beneficial to performance, therefore, a PIM based on dimethylbenzotriptycene was prepared (PIM-DM-BTrip). In addition, the potential benefit of introducing one or two trifluoromethyl (TFM) solubilising groups onto the benzotriptycene unit was evaluated by the synthesis of PIM-TFMBTrip and PIM-DTFM-BTrip, respectively. \n\n![](images/8ce17de06b6534cd053ce7554b93cd34ed70cf0ef607dc3d7a45f43000532c29.jpg) \nFig. 1 Structure and synthesis of the benzotriptycene PIMs. Reagents and conditions: i. ${\\sf B r}_{2},$ Fe, DCM, rt, $3h;$ ii. $n$ -BuLi, furan, THF, $-78^{\\circ}\\mathsf C,$ 1.5 h; iii. 9,10-Dimethyl2,3,6,7-tetramethoxyanthracene, $\\mathsf{D M F}$ , $250^{\\circ}\\mathsf{C},$ 7 bar, $2\\mathsf{h}.$ microwave irradiation, iv. TFA or $M e S O_{4}H,$ rt, $24\\mathsf{h}.$ ; v. $\\mathsf{B B r}_{3},$ DCM. (See ESI† for details). \n\nEach polymer was prepared from its tetrahydroxy benzotriptycene monomer (1a–f) using the well-established benzodioxinforming polymerisation reaction devised for PIM synthesis (Fig. 1).44 Monomers were prepared by adaptation of the classic benzotriptycene synthesis, involving the Diels–Alder reaction between 2,3,6,7-tetramethoxy-9,10-dimethylanthracene and the appropriate 1,4-dihydro-1,4-epoxynaphthalene39 – with the latter prepared from the Diels–Alder reaction between the appropriate benzyne intermediate and furan.45–47 \n\nPIM-TMN-Trip and PIM-HMI-Trip are both soluble in chloroform, facilitating analysis using Gel Permeation Chromatography (GPC) that confirmed that high molecular mass polymer was achieved for both polymers (Table 1). In contrast, PIM-DM-Btrip, PIM-TFM-BTrip and PIM-DTFM-BTrip proved soluble only in quinoline. The success of this high-boiling aromatic solvent for dissolving these otherwise intractable polymers prompted a re-investigation of the solubility of unsubstituted PIM-BTrip, which we had previously described as insoluble.39 Pleasingly, this polymer also proved soluble in quinoline. Although quinoline is not an appropriate solvent for GPC analysis, solutions of PIM-DM-BTrip, PIM-TFM-BTrip, PIM-DTFM-BTrip and PIMBTrip could be used to cast mechanically flexible and robust films, implying that a reasonably high molecular mass had been achieved during the synthesis. Synthetic and structural characterisation details, including solid state NMR (Fig. S1) are given in the ESI.† \n\n# Gas adsorption and gas transport properties. \n\nIn their powder form, all benzotriptycene-based PIMs adsorb a large amount of nitrogen $\\left(\\mathbf{N}_{2},\\ 77\\ \\mathbf{K}\\right)$ at low relative pressure. Analysis of the ${\\bf N}_{2}$ adsorption isotherms (Fig. S1, ESI†) gives apparent Brunauer–Emmett–Teller (BET) surface areas $\\mathrm{(SA_{BET})}$ within the range of $848{-}1034~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ (Table 1), which are amongst the highest obtained from solution processable polymers.29,39 The shapes of the ${\\bf N}_{2}$ isotherms are similar for all polymers except for PIM-TMN-Trip and PIM-DTFM-BTrip, for which there is larger uptake at higher pressures associated with a large hysteresis between the adsorption and desorption isotherms. This might be related to the TMN and $\\mathrm{CF}_{3}$ substituents protruding out of the 2D plane of the polymer chain and thus interfering with the electrostatic nitrile–nitrile interactions which are likely to dominate polymer cohesion. Adsorption of $\\mathbf{CO}_{2}$ at $273\\mathrm{~K~}$ (Fig. S2, $\\mathrm{ESI\\dag}$ ) shows similar uptakes for the benzotriptycene-PIMs $\\left(2.5{-}3.3\\mathrm{\\mmol\\g}^{-1}\\right)$ . The uptake for PIM-BTrip is slightly higher at lower pressures, which may be ascribed to a greater concentration of ultramicropores (diameter $<0.7\\mathrm{nm}$ in its pore size distribution (Fig. S3, $\\mathrm{ESI\\dag})$ ). \n\nSolvent cast films (Fig. S4, $\\mathrm{ESI\\dag}]$ of the benzotriptycenebased PIMs all demonstrate exceptionally high gas permeability (Table 2). However, the evaluation of gas permeability data for a new polymer requires careful consideration of its film history and thickness as these factors influence greatly the observed values.32 Generally, the highest reported values of gas permeability for high free volume polymers such as the PTMSP and PIMs were obtained from films freshly treated with methanol (or ethanol), which removes any residual casting solvent but also induces additional free volume.31,48 The values of gas permeability from freshly methanol treated thick films $(135-176~{\\upmu\\mathrm{m}})$ of the benzotriptycene PIMs are some of highest reported for a pure polymer film (e.g., $P_{\\mathrm{CO}_{2}}=21–53\\times10^{3}$ Barrer) and are comparable to those from ethanol treated ultrapermeable polyacetylenes (e.g., $\\scriptstyle P_{\\mathrm{CO}_{2}}=28-47\\times10^{3}$ Barrer).19,42 For each of the methanol treated films the order of decreasing gas permeability is $\\mathbf{CO}_{2}>\\mathbf{H}_{2}>\\mathbf{O}_{2}>\\mathbf{H}\\mathbf{e}>\\mathbf{CH}_{4}>\\mathbf{N}_{2}$ with the exception of those from the less permeable and more sizeselective PIM-BTrip for which He permeates faster than $\\mathbf{O}_{2}$ . The ideal selectivities of all of the methanol treated films are significantly higher than those obtained for the ultrapermeable polyacetylenes and fall in the range of those reported for methanol treated films of less permeable PIMs such as PIM-1 (e.g., $P_{\\mathrm{O_{2}}}/P_{\\mathrm{N_{2}}}=2.6\\substack{-3.6}$ ). \n\nAs noted for all PIMs and highly permeable polymers,31,32,49–51 the extremely high values of gas permeability measured initially from the freshly methanol treated films are not maintained on ageing.52 However, the reduction in permeability is accompanied by an increase in ideal selectivity for all gas pairs. In addition, on ageing, He permeability surpasses the value of $\\mathbf{O}_{2}$ for all the polymers, indicating enhanced size selectivity. Comparing data from approximately like-for-like samples (i.e. $\\sim120$ day aged and $110{-}180~{\\upmu\\mathrm{m}}$ thick films) the order \n\nTable 1 Yield, molecular mass and gas adsorption properties of the benzotriptycene-based PIMs \n\n\n
PolymerYield (%)SolubilityMn (g mol-1)Mw/Mnn² (cm² g-1)(m² g SABETVTotal (ml g-1)V (ml g-1)COz uptakee (mmol g-1)
PIM-TMN-Trip67CHCl352 300f3.87410340.870.383.3
PIM-HMI-Trip58CHCl361 300f2.45810330.710.383.0
PIM-BTrip78QuinolineLLg669110.630.333.2
PIM-DM-BTrip82Quinolineg729200.720.333.0
PIM-TFM-BTrip.79QuinolineL378480.660.312.5
PIM-DTFM-BTrip84QuinolineLLg659641.020.332.5
\n\na Inherent viscosity in quinoline at $25^{\\mathrm{~\\circ~}}\\mathrm{C}.$ . b BET surface area calculated from ${\\bf N}_{2}$ adsorption isotherm obtained at $77~\\mathrm{K}.$ c Total pore volume estimated from ${\\bf N}_{2}$ uptake at $P/P_{0}=0.98$ . d Micropore volume estimated from ${\\bf N}_{2}$ uptake at $P/P_{0}=0.05$ . $^e\\mathrm{~CO}_{2}$ adsorption at 1 bar and $273\\mathrm{~K~}$ f Relative to polystyrene standards. g Not measured due to insolubility in solvents compatible with GPC analysis. \n\nTable 2 Thickness $(\\mathsf{l},\\mathsf{\\upmu m})$ , ideal gas permeabilities $\\boldsymbol{\\mathrm{J}}\\boldsymbol{\\times},$ Barrer) and selectivities of freshly methanol treated and aged films measured at $25^{\\circ}C$ and 1 bar of feed pressure \n\n\n
PIM-αPNPoPcO2PCHsPHPHePO/PNPH/PNPcO/PNPco/PCH
BTrip160119043302150016901210045403.6410.218.112.7
(130)G,d160522257013200570844031104.9216.225.323.2
(253)c,d160401217010700411893034005.4122.326.726.0
(365)c,d16028015808020282716028105.6525.628.628.4
(490)G,d16019512406060203638026506.3432.631.029.9
(633)c,d1601279354350130510021807.3640.134.233.5
(718)eg1601128383770113482021507.5143.233.833.5
(±4)(±48)(±166)(±4)(±186)(±64)(±0.19)(±0.53)(±0.53)(±0.33)
BTripd6433918009200412943039605.3127.827.122.3
(120)6420011606040237718030205.7935.830.225.5
(253)d6419011435990225808034906.0142.531.526.6
(371)G,d641549975150163773036206.4750.233.431.6
TMN-Trip16635401040052 80072501880064902.945.3114.97.28
(120)166197066203330031301530056003.367.7716.910.6
(253)166147054402590020301410051903.719.5917.612.8
(358)166128950822364817511411852903.9411.018.413.5
(426)166110046202040014401410054204.2012.818.514.2
HMI-Tripd135256085404420048701660057003.346.4817.39.08
(1)135212073803900039901840065003.498.9518.69.94
(±330)(±989)(±3680)(±708)(±1765)(±762)(±0.14)(±2.16)(±1.7)(±1.44)
(120)135144051802690021501180042403.608.1918.712.5
(253)13597239301890012201070039604.0411.019.515.6
(358)13590737601740410831114142454.1512.319.216.1
(426)1358043580164009671100041504.4513.720.416.9
TFM-BTripc,d1761830621033700228013 60051503.397.4318.414.8
(123)℃176109042302210012501070041203.889.8220.317.7
(255)℃176875364018400953987040504.1511.321.019.3
(367)℃1767913450170008731010041704.3612.721.519.5
(496)176722326015600792976039204.5113.521.619.7
DTFM-BTrip1123000777042 60043401470058602.594.9014.29.82
(119)112180054102900021501130046903.016.2816.113.5
(366)112130044602290013901070045903.418.2317.516.4
(490)1128643490169008901040047704.0412.119.619.0
(636)112741317014800728102004730 40004.27 3.9013.8 11.320.0 21.820.3 14.0
DM-BTripd,f1141020 (±133)3950 (±374)22000 (±1071)1570 (±85)11400 (±482)
\n\na Number in parentheses is the ageing time in days after methanol treatment. b Thickness did not exhibit significant changes upon ageing. c Data defining the proposed $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ upper bound. d Data defining the proposed $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ upper bound. e Average and standard deviation (in parentheses) of four independent measurements of the same aged sample. f Average and standard deviation (in parentheses) of four independent samples. g Data not included on Robeson plots (Fig. 2). \n\nof decreasing permeability and increasing selectivity for the benzotriptycene PIMs is PIM-TMN-Trip $>$ PIM-DTFM-BTrip $>$ PIM-HMI-Trip $>$ PIM-TFM-Trip $>$ PIM-BTrip $\\approx$ PIM-DMBTrip. It can be deduced that the bulky TMN and HMI substituents both enhance permeability greatly, with the more rigid HMI substituent providing slightly higher selectivity over TMN. The relatively small $-\\mathbf{CF}_{3}$ substituents of PIM-TFM-BTrip and PIM-DTFM-BTrip also enhance permeability relative to unsubstituted PIM-BTrip. Interestingly, the $-\\mathbf{CF}_{3}$ substituents appear to slow ageing, with $54\\%$ of the value for $P_{\\mathrm{O}_{2}}$ of the methanol treated film of PIM-DTFM-BTrip retained after one year, and $56\\%$ for PIM-TFM-BTrip, as compared to only $30{-}36\\%$ for films without $-\\mathrm{CF}_{3}$ substituents. \n\nDepending on the gas, the standard deviation of the permeability is in the range $4\\mathrm{-}18\\%$ for the freshly MeOH treated PIM-HMI-Trip and PIM-DM-BTrip films, and $3\\mathrm{-}6\\%$ for the aged PIM-BTrip film. These are small compared to the effect of the ageing in this work, and almost negligible when represented on the double-logarithmic Robeson diagrams (Fig. S6, ESI†). \n\nA thinner film of PIM-BTrip $(64~{\\upmu\\mathrm{m}})$ demonstrates lower initial permeability after methanol treatment, consistent with the well-established trend that thinner films age more rapidly than thicker films.32,52,53 It is also more size selective than the thicker film of the same polymer with $\\mathbf{H}_{2}>\\mathbf{CO}_{2}>\\mathbf{He}>\\mathbf{O}_{2}>$ $\\mathrm{CH}_{4}>\\mathrm{N}_{2}$ the order of decreasing gas permeability. Due to the commonly encountered variability of gas permeability from differing film thicknesses and history, data for a new polymer are best compared to those of existing polymers by using Robeson plots (Fig. 2). As noted, the position of the data from a new polymer relative to the Robeson upper bounds provides a useful indicator of its potential performance as gas separation membranes. All data points for the benzotriptycene polymers lie far above the 2008 upper bounds for $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ (Fig. 2a), $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ (Fig. 2b), $\\mathrm{H}_{2}/\\mathrm{CH}_{4}$ , $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ (Fig. 2c) and $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ (Fig. 2d). Data for the $\\sim1$ year aged films for all of the polymers lie close to the proposed 2015 upper bound for $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ . In particular, aged PIM-BTrip demonstrates exceptional selectivity for a highly permeable polymer so that its data lie well above the proposed \n\n![](images/a4aa77832b737caa2b366f78103a6b52d613180ecea6294829bbd7df1a061c71.jpg) \nFig. 2 Robeson plots for the (a) $O_{2}/N_{2},$ (b) ${\\sf H}_{2}/{\\sf N}_{2},$ (c) ${C O_{2}}/{\\mathsf{N}_{2}}$ and (d) ${\\mathsf{C O}}_{2}/{\\mathsf{C H}}_{4}$ gas pairs showing the position of the gas permeability data for films of PIM-BTrip ( ), PIM-TMN-Trip $(\\boxed{\\begin{array}{r l}\\end{array}})$ , PIM-HMI-Trip $(\\equiv)$ , PIM-DM-BTrip $\\mathbf{\\Pi}(\\bullet)$ , PIM-TFM-BTrip $(\\bullet)$ and PIM-DTFM-BTrip $(\\diamond)$ . Previously reported data are also shown for non- $\\cdot\\mathsf{P l M}$ polymers (&) and PIMs $(\\triangle)$ . Upper bounds are represented by black lines (1991), blue lines (2008), and red lines for the previously proposed (2015) upper bounds for $O_{2}/N_{2}$ and $H_{2}/N_{2}$ . The proposed revised upper bounds for $C O_{2}/N_{2}$ and ${\\mathsf{C O}}_{2}/{\\mathsf{C H}}_{4}$ are shown as dotted red lines. \n\n2015 upper bounds for $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ (Fig. 2a), $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ (Fig. 2b), and $\\mathrm{H}_{2}/\\mathrm{CH}_{4}$ . A notable feature of the permeability data from aged samples of the benzotriptycene-PIMs on the $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ and $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ Robeson plots is the near linear correlation at a steeper slope than that of the upper bounds (Fig. S5, ESI†). This reflects the far larger reduction of permeabilities on ageing for gases composed of larger molecules such as ${\\bf N}_{2}$ and $\\mathrm{CH}_{4}$ as compared to those composed of the smaller $\\mathbf{O}_{2}$ and $\\mathbf{H}_{2}$ molecules. \n\nGas transport through a polymer is described by the solutiondiffusion model54 with $P_{\\mathrm{x}}=D_{\\mathrm{x}}\\times S_{\\mathrm{x}},$ where $D_{\\mathrm{x}}$ is the diffusivity coefficient (Table S2, $\\mathrm{ESI\\dag}$ ) and $S_{\\mathbf{x}}$ is the solubility coefficient for gas $\\mathbf{x}$ (Table S3, ESI†). Therefore, the ideal selectivity $\\left(P_{\\mathrm{x}}/P_{\\mathrm{y}}\\right)$ for a polymer comes from a combination of diffusivity selectivity $(D_{\\mathrm{{x}}}/D_{\\mathrm{{y}}})$ and solubility selectivity $(S_{\\mathrm{x}}/S_{\\mathrm{y}})$ . The remarkable positions of the data for the benzotriptycene-PIMs on the $\\mathbf H_{2}/\\mathbf N_{2}$ , and $\\mathbf O_{2}/\\mathbf N_{2}$ Robeson plots are due to very high diffusivity selectivity originating from the size-sieving behaviour of the polymers, which differentiates between gas molecules of differing effective diameters $(d_{\\mathrm{x}})$ .40 This is best illustrated by the correlation between ${d_{\\mathrm{x}}}^{2}$ and the diffusivity coefficient $(D_{\\mathrm{x}}),^{55}$ which is steepest for PIM-BTrip and less steep for benzotriptycene PIMs that possess a substituent, although the absolute value of the diffusion coefficient is larger (Fig. 3). Ageing decreases the diffusion coefficient for all polymers but steepens the correlation between ${d_{\\mathrm{x}}}^{2}$ and $D_{\\mathrm{{x}}},$ , especially for PIM-BTrip, which is evidence of its further enhanced size selectivity (Fig. S7, $\\mathrm{ESI\\dag}^{\\prime}$ ).40 The extraordinary performance of PIM-BTrip can be attributed to its ultramicroporosity, which facilitates the diffusivity of small gas molecules, together with very high chain rigidity,16,54 which hinders the activated transport of larger gas molecules by reducing thermal motions that allow gaps to form between voids. The extreme rigidity of PIM-BTrip accounts for the very high activation energy for the diffusion of larger gases such as ${\\bf N}_{2}$ and $\\mathrm{CH}_{4}$ .40 The gas transport properties of PIM-BTrip appears similar to those reported for the two triptycene-derived polymers, PIM-Trip- $\\mathbf{\\cdotTB}^{35}$ and TPIM-1,33 which were used to define the proposed 2015 upper bounds for $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ , $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ and $\\mathrm{H}_{2}/\\mathrm{CH}_{4}$ .38 It should be noted that the data from PIM-Trip-TB used to define the 2015 upper bounds were taken from a film that was aged for only 100 days after methanol treatment.35 Recent remeasurement of the gas permeability of this film after 1900 days gives data that are also well over the proposed 2015 upper bounds for $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ (i.e. $P_{\\mathrm{O}_{2}}=532$ Barrer; $P_{\\mathrm{O_{2}}}/P_{\\mathrm{N_{2}}}=8.2)$ and $\\mathbf{H}_{2}/\\mathbf{N}_{2}$ (i.e. $P_{\\mathrm{H}_{2}}=$ 4430 Barrer; $P_{\\mathrm{H}_{2}}/P_{\\mathrm{N}_{2}}=65\\$ ). Therefore, the design concepts used to obtain the extraordinary size selectivity demonstrated by PIM-BTrip and PIM-Trip-TB are likely to provide PIMs that will provoke future significant revisions of the $\\mathrm{O}_{2}/\\mathrm{N}_{2},\\ \\mathrm{H}_{2}/\\mathrm{N}_{2}$ and $\\mathrm{{H}}_{2}/\\mathrm{{CH}}_{4}$ Robeson upper bounds. \n\n# Redefining the $\\mathbf{CO}_{2}/\\mathbf{N}_{2}$ and $\\mathbf{CO_{2}}/\\mathbf{CH_{4}}$ upper bounds \n\nSeparations involving $\\mathbf{CO}_{2}$ are mechanistically more complex than those governed predominately by diffusivity selectivity (e.g. $\\mathbf{O}_{2}/\\mathbf{N}_{2}$ or $\\mathbf{H}_{2}/\\mathbf{N}_{2}^{\\cdot}$ ) because $S_{\\mathrm{CO}_{2}}$ dominates transport, especially for $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ due to the similar effective diameters of the two gas molecules. Typically for PIMs, values for $S_{\\mathrm{CO}_{2}}/S_{\\mathrm{N}_{2}}$ lie in the range 15–20 whereas those for $D_{\\mathrm{CO_{2}}}/D_{\\mathrm{N_{2}}}$ lie between $0.9–1.5$ and these values are similar for PIMs with both higher and lower $P_{\\mathrm{CO}_{2}}$ permeability. In general, solubility selectivity tends to remain fairly constant during ageing, in contrast to the increases observed for ideal selectivity values for transport dominated by diffusivity selectivity.52 Thus, plotting data for previously reported PIMs on the Robeson plot for $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ shows many data points slightly above the 2008 upper bound at higher permeability $\\left(P_{\\mathrm{CO_{2}}}>3000\\right.$ Barrer) but few at lower values of permeability. Indeed, very few highly permeable polymers possess a $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ selectivity $>30$ ,56–59 which is the lower limit of interest for a first-pass polymer membrane for post-combustion carbon capture (Table S1, ESI†).12 \n\n![](images/eecbeee31a0fb73323ef5ae7230ad05d46abca8e8ba8ca690cad426b615ea9eb.jpg) \nFig. 3 Plot of diffusivity coefficient $(D_{\\times})$ versus ${d_{\\mathrm{x}}}^{2}$ (where $d_{\\times}=$ effective diameter of gas molecule x: ${\\sf H e}=1.78$ ; ${\\sf H}_{2}=2.14$ ; $\\mathrm{O}_{2}=2.89$ ; $\\mathsf{C O}_{2}=3.02$ ; ${\\N}_{2}=3.04$ ; $\\mathsf{C H}_{4}=3.18\\mathrm{~\\AA})^{55}$ for freshly methanol treated films of PIM-BTrip $()$ , PIM-TMN-Trip $(\\bullet\\bullet)$ , PIM-HMI-Trip $(\\equiv)$ , PIM-DM-BTrip $(\\bullet)$ . Data for PIM-TFM-BTrip and PIM-DTFM-BTrip are not shown for clarity but are very similar to those for PIM-TMN-Trip and PIM-HMI-Trip, respectively. \n\nAlthough all of the data for the benzotriptycene PIMs are above the 2008 upper bound for $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ , the data from PIM-BTrip are particularly promising with both thick and thinner aged films providing $P_{\\mathrm{CO}_{2}}>4000$ Barrer and $P_{\\mathrm{CO_{2}}}/P_{\\mathrm{N_{2}}}>30$ . The impressive performance of PIM-BTrip appears to be due to an unusually high $D_{\\mathrm{CO_{2}}}/D_{\\mathrm{N_{2}}}$ of 2.0, whereas that of the substituted members of the series relies on greater $S_{\\mathrm{CO}_{2}}/S_{\\mathrm{N}_{2}}$ resulting from the greater number of $\\mathbf{CO}_{2}$ adsorption sites provided by the larger amount of intrinsic microporosity (Table S3, ESI†). The eleven data points on the Robeson plot from four different polymers that fall into a linear correlation parallel to that of the 2008 upper bound allows us to propose a substantially improved new upper bound for $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ (Fig. 2c and Tables 2 and 3). These data points are distributed over a large $P_{\\mathrm{CO}_{2}}$ range of 4400–52 000 Barrer. \n\nIn addition, the data for all of the benzotriptycene PIMs lie well above the 2008 upper bound for $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ at a higher selectivity than those of previously reported polymers. Indeed, only data for the highly rigid ‘‘intermolecularly-locked’’ derivative of PIM-1 (PIM-C1)60 and PIM-SBF- $2^{43}$ come close to those of the benzotriptycene PIMs (Table S1, ESI†). This exceptional performance appears due to a combination of both high diffusivity selectivity, with $D_{\\mathrm{CO_{2}}}/D_{\\mathrm{CH_{4}}}$ in the range 5.7–9.5 for aged films, and good solubility selectivity $\\left(S_{\\mathrm{CO_{2}}}/S_{\\mathrm{CH_{4}}}\\ >\\ 3\\right)$ . Ten data points from two different polymers allows us to propose a new upper bound for $\\mathrm{CO_{2}/C H_{4}}$ parallel to that of 2008 (Fig. 2d and Tables 2 and 3). The benzotriptycene PIMs that either define or provide data that are very close to this revised upper bound are either unsubstituted (PIM-BTrip) or possess only small substituents (i.e. PIM-DM-BTrip; PIM-TFM-BTrip and PIM-DTFM-BTrip). In contrast, those possessing larger cyclic solubilising groups (i.e. PIM-TMN-Trip and PIM-HMI-Trip) are slightly less selective. \n\nWhen defining his 2008 $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ upper bound, Robeson noted that data for a series of Thermally Rearranged (TR) \n\nTable 3 Fitting parameters for the 2008 and proposed ${\\mathsf{C O}}_{2}/{\\mathsf{N}}_{2}$ and ${\\mathsf{C O}}_{2}/$ $C H_{4}$ upper bounds using the formula $P_{\\times}={k}{\\alpha_{\\times y}}^{n}$ (where $P_{\\times}$ is permeability (Barrer) of the most permeable $\\mathsf{x}$ -gas, $k$ is the front factor (Barrer), $\\boldsymbol{\\alpha}_{\\mathrm{xy}}$ is the selectivity for x/y gas pair, and $n$ is the slope) \n\n\n
k (Barrer)n
Robeson 20o8 upper bounds24
CO2/CH45.369 × 106-2.636
CO2/N230.967×106-2.888
Proposed upper bounds
CO/CH422.584 × 10-2.401
CO/N755.58×106-3.409
\n\npolymers, reported by Park et al.,15,61 ‘‘with exceptional $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ separation capabilities’’,24 appeared to form an upper bound above that proposed for solution processable polymers. Such insoluble network polymers as the TR polymers often perform above the 2008 upper bounds defined for solution processable polymers due to their rigidity approaching that of carbon molecular sieves (i.e. polymers carbonised at high temperatures). Remarkably, the $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ upper bound defined by the solution processable benzotriptycene-based PIMs lies at the same position as that of Robeson’s tentatively proposed TR polymer upper bound with a selectivity 2.5 times higher than that for the 2008 upper bound. \n\n# Conclusions \n\nThe benzotriptycene-based PIMs provide exceptional gas permeability data for most important gas pairs and allow for the redefinition of the $\\mathrm{CO}_{2}/\\mathrm{CH}_{4}$ and $\\mathrm{CO}_{2}/\\mathrm{N}_{2}$ Robeson upper bounds. This is important in order to set aspirational targets for chemists in the design and synthesis of novel polymers. In addition, it will help parametric studies of energy and cost efficiency for carbon capture and natural/bio gas upgrading by providing enhanced but realistic state-of-the-art values for membrane permeability and selectivity. The resulting estimates of energy efficiencies and costs will be more attractive relative to both previous calculations for membrane systems and to competitive $\\mathbf{CO}_{2}$ separation processes. The resulting improved credibility of polymer membranes for these crucial separations will stimulate research activity in this technological area of prime importance to energy and the environment. \n\n# Conflicts of interest \n\nThere are no conflicts of interest to declare. \n\n# Acknowledgements \n\nThe research leading to these results has received funding from the EU FP7 Framework Program under grant agreement no. 608490, project $\\ensuremath{\\mathbf{M}}^{4}\\ensuremath{\\mathbf{CO}_{2}}$ and from the EPSRC (UK) grant numbers $\\mathrm{EP/M01486X}/1$ , EP/R000468/1 and EP/K008102/2. \n\n# References \n\n1 P. Bernardo, E. Drioli and G. Golemme, Ind. Eng. Chem. Res., 2009, 48, 4638–4663. \n2 Y. Yampolskii, Macromolecules, 2012, 45, 3298–3311. \n3 R. W. Baker and B. T. Low, Macromolecules, 2014, 47, 6999–7013. \n4 M. Galizia, W. S. Chi, Z. P. Smith, T. C. Merkel, R. W. Baker and B. D. Freeman, Macromolecules, 2017, 50, 7809–7843. \n5 P. M. Budd and N. B. McKeown, Polym. Chem., 2010, 1, 63–68. \n6 R. S. Murali, T. Sankarshana and S. Sridhar, Sep. Purif. Rev., 2013, 42, 130–186. 7 S. F. Wang, X. Q. Li, H. Wu, Z. Z. Tian, Q. P. Xin, G. W. He, D. D. Peng, S. L. Chen, Y. Yin, Z. Y. Jiang and M. D. Guiver, Energy Environ. Sci., 2016, 9, 1863–1890. \n8 J. K. Adewole and A. L. Ahmad, J. Polym. Res., 2017, 24, 17. \n9 N. Y. Du, H. B. Park, M. M. Dal-Cin and M. D. Guiver, Energy Environ. Sci., 2012, 5, 7306–7322. \n10 E. Esposito, L. Dellamuzia, U. Moretti, A. Fuoco, L. Giorno and J. C. Jansen, Energy Environ. Sci., 2019, 12, 281–289. \n11 M. C. Ferrari, D. Bocciardo and S. Brandani, Green Energy Environ., 2016, 1, 211–221. \n12 T. C. Merkel, H. Q. Lin, X. T. Wei and R. Baker, J. Membr. Sci., 2010, 359, 126–139. \n13 R. W. Baker, B. Freeman, J. Kniep, X. T. Wei and T. Merkel, Int. J. Greenhouse Gas Control, 2017, 66, 35–47. \n14 L. S. White, K. D. Amo, T. Wu and T. C. Merkel, J. Membr. Sci., 2017, 542, 217–225. \n15 S. Kim and Y. M. Lee, Prog. Polym. Sci., 2015, 43, 1–32. \n16 B. D. Freeman, Macromolecules, 1999, 32, 375–380. \n17 H. B. Park, J. Kamcev, L. M. Robeson, M. Elimelech and B. D. Freeman, Science, 2017, 356, eaab0530. \n18 T. Masuda, E. Isobe, T. Higashimura and K. Takada, J. Am. Chem. Soc., 1983, 105, 7473–7474. \n19 Y. Yampolskii, Polym. Rev., 2017, 57, 200–212. \n20 Y. He, F. M. Benedetti, S. Lin, C. Liu, Y. Zhao, H.-Z. Ye, T. Van Voorhis, M. G. De Angelis, T. M. Swager and Z. P. Smith, Adv. Mater., 2019, 31, 1807871. \n21 L. M. Robeson, J. Membr. Sci., 1991, 62, 165–186. \n22 S. Budhathoki, O. Ajayi, J. A. Steckel and C. E. Wilmer, Energy Environ. Sci., 2019, 12, 1255–1264. \n23 C. Y. Chuah, K. Goh, Y. Q. Yang, H. Q. Gong, W. Li, H. E. Karahan, M. D. Guiver, R. Wang and T. H. Bae, Chem. Rev., 2018, 118, 8655–8769. \n24 L. M. Robeson, J. Membr. Sci., 2008, 320, 390–400. \n25 P. M. Budd, K. J. Msayib, C. E. Tattershall, B. S. Ghanem, K. J. Reynolds, N. B. McKeown and D. Fritsch, J. Membr. Sci., 2005, 251, 263–269. \n26 M. D. Guiver and Y. M. Lee, Science, 2013, 339, 284–285. \n27 X. Ma, O. Salinas, E. Litwiller and I. Pinnau, Macromolecules, 2013, 46, 9618–9624. \n28 X. Ma, B. Ghanem, O. Salines, E. Litwiller and I. Pinnau, ACS Macro Lett., 2015, 4, 231–235. \n29 M. Carta, R. Malpass-Evans, M. Croad, Y. Rogan, J. C. Jansen, P. Bernardo, F. Bazzarelli and N. B. McKeown, Science, 2013, 339, 303–307. \n30 Y. Rogan, L. Starannikova, V. Ryzhikh, Y. Yampolskii, P. Bernardo, F. Bazzarelli, J. C. Jansen and N. B. McKeown, Polym. Chem., 2013, 4, 3813–3820. \n31 E. Tocci, L. De Lorenzo, P. Bernardo, G. Clarizia, F. Bazzarelli, N. B. McKeown, M. Carta, R. Malpass-Evans, K. Friess, K. Pilnacek, M. Lanc, Y. P. Yampolskii, L. Strarannikova, V. Shantarovich, M. Mauri and J. C. Jansen, Macromolecules, 2014, 47, 7900–7916. \n32 X. H. Ma and I. Pinnau, Macromolecules, 2018, 51, 1069–1076. \n33 B. S. Ghanem, R. Swaidan, X. H. Ma, E. Litwiller and I. Pinnau, Adv. Mater., 2014, 26, 6696–6700. \n34 B. S. Ghanem, R. Swaidan, E. Litwiller and I. Pinnau, Adv. Mater., 2014, 26, 3688–3692. \n35 M. Carta, M. Croad, R. Malpass-Evans, J. C. Jansen, P. Bernardo, G. Clarizia, K. Friess, M. Lanc and N. B. McKeown, Adv. Mater., 2014, 26, 3526–3531. \n36 I. Rose, M. Carta, R. Malpass-Evans, M.-C. Ferrari, P. Bernardo, G. Clarizia, J. C. Jansen and N. B. McKeown, ACS Macro Lett., 2015, 4, 912–915. \n37 R. Williams, L. A. Burt, E. Esposito, J. C. Jansen, E. Tocci, C. Rizzuto, M. Lanc, M. Carta and N. B. McKeown, J. Mater. Chem. A, 2018, 6, 5661–5667. \n38 R. Swaidan, B. Ghanem and I. Pinnau, ACS Macro Lett., 2015, 4, 947–951. \n39 I. Rose, C. G. Bezzu, M. Carta, B. Comesana-Gandara, E. Lasseuguette, M. C. Ferrari, P. Bernardo, G. Clarizia, A. Fuoco, J. C. Jansen, K. E. Hart, T. P. Liyana-Arachchi, C. M. Colina and N. B. McKeown, Nat. Mater., 2017, 16, 932–937. \n40 A. Fuoco, B. Comesana-Gandara, M. Longo, E. Esposito, M. Monteleone, I. Rose, C. G. Bezzu, M. Carta, N. B. McKeown and J. C. Jansen, ACS Appl. Mater. Interfaces, 2018, 10, 36475–36482. \n41 Y. Yin and M. D. Guiver, Nat. Mater., 2017, 16, 880–881. \n42 Y. Hu, M. Shiotsuki, F. Sanda, B. D. Freeman and T. Masuda, Macromolecules, 2008, 41, 8525–8532. \n43 C. G. Bezzu, M. Carta, M. C. Ferrari, J. C. Jansen, M. Monteleone, E. Esposito, A. Fuoco, K. Hart, T. P. LiyanaArachchi, C. M. Colina and N. B. McKeown, J. Mater. Chem. A, 2018, 6, 10507–10514. \n44 P. M. Budd, B. S. Ghanem, S. Makhseed, N. B. McKeown, K. J. Msayib and C. E. Tattershall, Chem. Commun., 2004, 230–231. \n45 H. Hart, C. Lai, G. C. Nwokogu and S. Shamouilian, Tetrahedron, 1987, 43, 5203–5224. \n46 F. Bailly, F. Cottet and M. Schlosser, Synthesis, 2005, 791–797, DOI: 10.1055/s-2005-861813. \n47 R. S. Luo, J. H. Liao, L. Xie, W. J. Tang and A. S. C. Chan, Chem. Commun., 2013, 49, 9959–9961. \n48 P. M. Budd, N. B. McKeown, B. S. Ghanem, K. J. Msayib, D. Fritsch, L. Starannikova, N. Belov, O. Sanfirova, Y. Yampolskii and V. Shantarovich, J. Membr. Sci., 2008, 325, 851–860. \n49 P. Bernardo, F. Bazzarelli, F. Tasselli, G. Clarizia, C. R. Mason, L. Maynard-Atem, P. M. Budd, M. Lanc, K. Pilnacek, O. Vopicka, K. Friess, D. Fritsch, Y. P. Yampolskii, V. Shantarovich and J. C. Jansen, Polymer, 2017, 113, 283–294. \n50 R. Swaidan, B. Ghanem, E. Litwiller and I. Pinnau, Macromolecules, 2015, 48, 6553–6561. \n51 L. Starannikova, V. Khodzhaeva and Y. Yampolskii, J. Membr. Sci., 2004, 244, 183–191. \n52 Z. X. Low, P. M. Budd, N. B. McKeown and D. A. Patterson, Chem. Rev., 2018, 118, 5871–5911. \n53 K. D. Dorkenoo and P. H. Pfromm, Macromolecules, 2000, 33, 3747–3751. \n54 L. M. Robeson, B. D. Freeman, D. R. Paul and B. W. Rowe, J. Membr. Sci., 2009, 341, 178–185. \n55 V. Teplyakov and P. Meares, Gas Sep. Purif., 1990, 4, 66–74. \n56 R. Swaidan, B. S. Ghanem, E. Litwiller and I. Pinnau, J. Membr. Sci., 2014, 457, 95–102. \n57 J. Wu, J. T. Liu and T. S. Chung, Adv. Sustainable Syst., 2018, 2, 1800044. \n58 N. Du, H. B. Park, G. P. Robertson, M. M. Dal-Cin, T. Visser, L. Scoles and M. D. Guiver, Nat. Mater., 2011, 10, 372–375. \n59 C. R. Mason, L. Maynard-Atem, N. M. Al-Harbi, P. M. Budd, P. Bernardo, F. Bazzarelli, G. Clarizia and J. C. Jansen, Macromolecules, 2011, 44, 6471–6479. \n60 J. Zhang, H. Kang, J. Martin, S. Zhang, S. Thomas, T. C. Merkel and J. Jin, Chem. Commun., 2016, 52, 6553–6556. \n61 H. B. Park, C. H. Jung, Y. M. Lee, A. J. Hill, S. J. Pas, S. T. Mudie, E. Van Wagner, B. D. Freeman and D. J. Cookson, Science, 2007, 318, 254–258. " + }, + { + "id": "10.1088_1361-648X_ab4007", + "DOI": "10.1088/1361-648X/ab4007", + "DOI Link": "http://dx.doi.org/10.1088/1361-648X/ab4007", + "Relative Dir Path": "mds/10.1088_1361-648X_ab4007", + "Article Title": "QuantumATK: an integrated platform of electronic and atomic-scale modelling tools", + "Authors": "Smidstrup, S; Markussen, T; Vancraeyveld, P; Wellendorff, J; Schneider, J; Gunst, T; Verstichel, B; Stradi, D; Khomyakov, PA; Vej-Hansen, UG; Lee, ME; Chill, ST; Rasmussen, F; Penazzi, G; Corsetti, F; Ojanperä, A; Jensen, K; Palsgaard, MLN; Martinez, U; Blom, A; Brandbyge, M; Stokbro, K", + "Source Title": "JOURNAL OF PHYSICS-CONDENSED MATTER", + "Abstract": "QuantumATK is an integrated set of atomic-scale modelling tools developed since 2003 by professional software engineers in collaboration with academic researchers. While different aspects and individual modules of the platform have been previously presented, the purpose of this paper is to give a general overview of the platform. The QuantumATK simulation engines enable electronic-structure calculations using density functional theory or tight-binding model Hamiltonians, and also offers bonded or reactive empirical force fields in many different parametrizations. Density functional theory is implemented using either a plane-wave basis or expansion of electronic states in a linear combination of atomic orbitals. The platform includes a long list of advanced modules, including Green?s-function methods for electron transport simulations and surface calculations, first-principles electron-phonon and electron-photon couplings, simulation of atomic-scale heat transport, ion dynamics, spintronics, optical properties of materials, static polarization, and more. Seamless integration of the different simulation engines into a common platform allows for easy combination of different simulation methods into complex workflows. Besides giving a general overview and presenting a number of implementation details not previously published, we also present four different application examples. These are calculations of the phonon-limited mobility of Cu, Ag and Au, electron transport in a gated 2D device, multi-model simulation of lithium ion drift through a battery cathode in an external electric field, and electronic-structure calculations of the composition-dependent band gap of SiGe alloys.", + "Times Cited, WoS Core": 1409, + "Times Cited, All Databases": 1439, + "Publication Year": 2020, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000499348200001", + "Markdown": "PAPER \n\n# QuantumATK: an integrated platform of electronic and atomic-scale modelling tools \n\nTo cite this article: Søren Smidstrup et al 2020 J. Phys.: Condens. Matter 32 015901 \n\nView the article online for updates and enhancements. \n\n# Recent citations \n\n![](images/ce30ad4319607b20f8886af0b4b8c62546836f885dd6bc5a7512ed9d247b9483.jpg) \n\nThis content was downloaded from IP address 132.174.255.215 on 14/11/2019 at 16:14 \n\n# QuantumATK: an integrated platform of electronic and atomic-scale modelling tools \n\nSøren Smidstrup1 , Troels Markussen1, Pieter Vancraeyveld1, Jess Wellendorff $^1\\textcircled{\\circ}$ , Julian Schneider1, Tue Gunst1,2, Brecht Verstichel1, Daniele Stradi1, Petr A Khomyakov1, Ulrik G Vej-Hansen $1\\textcircled{\\circ}$ , Maeng-Eun Lee1, Samuel T Chill1, Filip Rasmussen1, Gabriele Penazzi1, Fabiano Corsetti $^1\\textcircled{\\circ}$ , Ari Ojanperä1, Kristian Jensen1, Mattias L N Palsgaard1,2, Umberto Martinez $^1\\textcircled{\\circ}$ , Anders Blom $1_{\\textcircled{1}}$ , Mads Brandbyge2 and Kurt Stokbro1 \n\n1  Synopsys Denmark, Fruebjergvej 3, Postbox 4, DK-2100 Copenhagen, Denmark 2  DTU Physics, Center for Nanostructured Graphene (CNG), Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark \n\nE-mail: soren.smidstrup@synopsys.com \n\nReceived 6 May 2019, revised 9 August 2019 \nAccepted for publication 30 August 2019 \nPublished 10 October 2019 \n\n![](images/a18f6dbae5447d77598d293f6d35f1060d4eeefb301a14f34382348842c67650.jpg) \n\n# Abstract \n\nQuantumATK is an integrated set of atomic-scale modelling tools developed since 2003 by professional software engineers in collaboration with academic researchers. While different aspects and individual modules of the platform have been previously presented, the purpose of this paper is to give a general overview of the platform. The QuantumATK simulation engines enable electronic-structure calculations using density functional theory or tightbinding model Hamiltonians, and also offers bonded or reactive empirical force fields in many different parametrizations. Density functional theory is implemented using either a plane-wave basis or expansion of electronic states in a linear combination of atomic orbitals. The platform includes a long list of advanced modules, including Green’s-function methods for electron transport simulations and surface calculations, first-principles electron-phonon and electron-photon couplings, simulation of atomic-scale heat transport, ion dynamics, spintronics, optical properties of materials, static polarization, and more. Seamless integration of the different simulation engines into a common platform allows for easy combination of different simulation methods into complex workflows. Besides giving a general overview and presenting a number of implementation details not previously published, we also present four different application examples. These are calculations of the phonon-limited mobility of Cu, Ag and Au, electron transport in a gated 2D device, multi-model simulation of lithium ion drift through a battery cathode in an external electric field, and electronic-structure calculations of the composition-dependent band gap of SiGe alloys. \n\nKeywords: atomic-scale modelling, density functional theory, semi-empirical methods, tight-binding, force fields, first-principles simulations, non-equilibrium Green’s function (Some figures may appear in colour only in the online journal) \n\n# Contents \n\n# 1.  Introduction \n\n1.  Introduction\b 2.  Overview\b \n3.  Atomistic configurations\b \n4.  DFT simulation engines\b 4.1.  LCAO representation 4.2.  PW representation 4.3.  Pseudopotentials and LCAO basis sets 4.4.  Exchange-correlation methods 4.5.  Boundary conditions and Poisson solvers \n5.  Semi-empirical models\b \n6.  Empirical force fields\b 7.  Ion dynamics\b 7.1.  Local structural optimization 7.2.  Global structural optimization 7.3.  Reaction pathways and transition states 7.4.  Molecular dynamics 7.5.  Adaptive kinetic Monte Carlo \n8.  Phonons\b 8.1.  Calculating the dynamical matrix 8.2.  Wigner–Seitz method 8.3.  Phonon band structure and density of states 8.4.  Electron-phonon coupling 8.5.  Transport coefficients \n9.  Polarization and Berry phase\b \n10.  Magnetic anisotropy energy\b \n11.  Quantum transport\b 11.1.  NEGF method 11.2.  Retarded Green’s function 11.3.  Complex contour integration 11.4.  Bound states 11.5.  Spill-in terms 11.6.  Device total energy and forces 11.7.  Transmission coefficient and current 11.8.  Inelastic transmission and inelastic current\b 11.9.  Thermoelectric transport 11.10.  Photocurrent \n12.  QuantumATK parallelization 12.1.  Bulk DFT and semi-empirical simulations 12.2.  DFT-NEGF device simulations 12.3.  FF simulations \n13.  NanoLab simulation environment 13.1.  Python scripting 13.2.  NanoLab graphical user interface 13.3.  Documentation \n14.  QuantumATK applications\b 14.1.  \u0007Large-scale simulations of 2D field-effect transistors\b 14.2.  Phonon-limited mobility of metals 14.3.  \u0007Multi-model dynamics with an applied electric field 14.4.  Electronic structure of binary alloys\b \n15.  Summary\b \nAcknowledgments \nAppendix.  Computational details \n\nReferences \n\n2 Atomic-scale modelling is increasingly important for indus \n4 trial and academic research and development in a wide range \n5 of technology areas, including semiconductors [1, 2], batteries \n5 [3], catalysis [4], renewable energy [5], advanced materials \n5 [6], next-generation pharmaceuticals [7], and many others. \n6 Surveys indicate that the return on investment of atomic-scale \n6 modelling is typically around 5:1 [8]. With development of \n8 increasingly advanced simulation algorithms and more pow \n9 erful computers, we expect that the economic benefits of \n1 atomic-scale modelling will only increase. \n\nThe current main application of atomic-scale modelling is in early-stage research into new materials and technology designs, see [9, 10] for examples. The early research stage often has a very large design space, and experimental trial and error is a linear process that will explore only a small part of this space. Atomic-scale simulations make it possible to guide experimental investigations towards the most promising part of the technology design space. Such insights are typically achieved by simulating the underlying atomic-scale processes behind failed or successful experiments, to understand the physical or (bio-)chemical origins. Such insight can often rule out or focus research to certain designs or mat­erial systems [8]. Recently, materials screening has also shown great promise. In this approach, atomic-scale calculations are used to obtain important properties of a large pool of materials, and the most promising candidates are then selected for exper­imental verification and/or further theoretical refinement [6, 11, 12]. \n\nThe scientific field of atomic-scale modelling covers everything from near-exact quantum chemical calculations to approximate simulations using empirical force fields. Quantum chemical methods (based on wave-function theory) attempt to fully solve the many-body Schrödinger equation for all electrons in the system, and can provide remarkably accurate descriptions of molecules [13]. However, the computational cost is high: in practice, one is usually limited to calcul­ations involving far below 100 atoms in total. Such methods are cur­ rently not generally useful for industrial research into advanced materials and next-generation electronic devices. \n\nOn the contrary, force-field (FF) methods are empirical but computationally efficient: all inter-atomic interactions are described by analytic functions with pre-adjusted parameters. It is thereby possible in practice to simulate systems with millions of atoms. Unfortunately, this often also hampers the applicability of a force field for system types not included when fitting the FF parameters. \n\nAs an attractive intermediate methodology, density func \n27 tional theory (DFT) [14–17] provides an approximate but \n29 computationally tractable solution to the electronic many \nbody problem. This allows for good predictive power with \n30 respect to experiments with minimal use of empirical param­ \n32 eters at a reduced computational cost. Standard DFT simu \n33 lations may routinely be applied to systems containing more \n33 than one thousand atoms, and DFT is today the preferred \n33 framework for industrial applications of ab initio electronic \n33 structure theory. \n\nTable 1.  Simulation engines in the QuantumATK platform, with examples of other simulation platforms using the same underlying methodology. LCAO and PW means linear combination of atomic orbitals and plane wave, respectively. \n\n\n
EngineDescriptionFirst releaseRelated platforms
ATK-LCAOPseudopotential DFT using LCAO basis [19]2003SIESTA [20],OpenMX [21]
ATK-PlaneWavePseudopotential DFT using PW basis2016VASP [22], Quantum ESPRESSO [23]
ATK-SESemi-empirical TB methods [24]2010DFTB + [25], NEMO [26],OMEN [27]
ATK-ForceFieldAll types of empirical force fields [28]2014LAMMPS [29], GULP [30]
\n\nSemi-empirical (SE) electronic-structure methods based on tight-binding (TB) model Hamiltonians are more approximate, but have a long tradition in semiconductor research [18]. Whereas DFT ultimately aims to approximate the true many-body electronic Hamiltonian in an efficient but parameter-free fashion, a TB model relies on parameters that are adjusted to very accurately describe the properties of a number of reference systems. This leads to highly specialized electronic-structure models that typically reduce the computational expense by an order of magnitude compared to DFT methods. Such SE methods may be convenient for large-scale electronic-structure calculations, for example in simulations of electron transport in semiconductor devices. \n\nThe QuantumATK platform offers simulation engines covering the entire range of atomic-scale simulation methods relevant to the semiconductor industry and materials science in general. This includes force fields, SE methods, and several flavors of DFT. These are summarized in table  1, including examples of other platforms that offer similar methodology. \n\nTo give a bird’s-eye view of the computational cost of the different atomic-scale simulation methods mentioned above, we compare in figure  1 the computational speed of the methods when simulating increasingly larger structures of amorphous $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ . The measure of speed is here the number of molecular dynamics steps that are feasible within $24\\mathrm{h}$ when run in parallel on 16 computing cores. Although the parallel computing techniques used may differ between some of the methods, we find that figure 1 gives a good overview of the scaling between the different methods. \n\nIt is important to realize that the simulation methods listed in table  1 should ideally complement each other: for successful use of atomic-scale modelling, it is essential to have easy access to all the methods, in order to use them in combination. The vast majority of atomic-scale simulation tools are developed by academic groups, and most of them focus on a single method. Using the tool typically requires a large effort for compilation, installation, learning the input/output syntax, etc. The tool is often not fully compatible with any other tool, so learning an additional tool within a new modelling class requires yet another large effort. Even within one modelling class, for example DFT, a single simulation tool may not have all the required functionality for a given application, so several different tools within each modelling class may be needed to solve a given problem, and a significant effort must be invested to master each of them. As a commercially developed platform, QuantumATK aims to circumvent these issues. \n\nAcademic development of atomic-scale simulation platforms, often made available through open-source licenses, is essential for further technical progress of the field. However, the importance of commercial platforms in progressing the industrial uptake of the technology is often underestimated. Commercial software relies on payment from end users. This results in a strong focus on satisfying end-user requirements in terms of usability, functionality, efficiency, reliability, and support. The revenue enables the commercial software provider to establish a stable team of developers and thereby provide a software solution that will be maintained, extended, and supported for decades. \n\n![](images/8f206934e73d1384f2dd92834da8e6e5fcc7cf2529e7a498c1576cac951fabc5.jpg) \nFigure 1.  Comparison of the simulation methods available in QuantumATK, showing the total number of molecular dynamics steps performed in $24\\mathrm{{h}}$ ( $\\#$ MD steps) against system size ( $\\#$ atoms) for amorphous $\\mathrm{Al}_{2}\\mathrm{O}_{3}$ with constant density. Each step includes evaluation of the total energy and atomic forces. The simulations were run on a 16-core central processing unit (CPU) of the type Inte $\\mathsf{\\Omega}_{\\mathsf{X}}\\mathsf{e o n}^{\\circledast}\\mathsf{E}5\\mathsf{-}2670$ . The FF simulations (section 6) were performed using threading only, whereas full MPI parallelization was used for the TB (section 5) and DFT (section 4) simulations. For the latter, we have considered either semi-local exchange-correlation functionals using linear-combination-ofatomic-orbitals (DFT-LCAO) and plane-wave (DFT-PW) basis sets, or a hybrid exchange-correlation functional using a PW basis set (Hybrid DFT). Further details of the calculations are given in appendix. \n\nThe ambition of the QuantumATK platform is to provide a state-of-the-art and easy-to-use integrated toolbox with all important atomic-scale modelling methodologies for a growing number of application areas. The methods are made available through a modern graphical user interface (GUI) and a Python scripting-based frontend for expert users. Our current focus is semiconductor devices, polymers, glasses, catalysis, batteries, and materials science in general. In this context, semiconductor devices is a broad area, ranging from silicon-based electronic logics and memory elements [31, 32], to solar cells composed of novel materials [33] and nextgeneration electronic devices based on spintronic phenomona [34]. One key strength of a unified framework for a large selection of simulation engines and modelling tools is within multiphysics and multiscale problems. Such problems often arise in physical modelling of semiconductor devices, and the QuantumATK platform is widely used for coupling technology computer-aided design (TCAD) tools with atomic-scale detail, for instance to provide first-principles simulations of defect migration paths and subsequently the temperature-dependent diffusion constant for continuum-level simulation of semiconductor processes [2]. Furthermore, QuantumATK provides a highly flexible and efficient framework for coupling advanced electrostatic setups with state-of-the-art transport simulations including electron–phonon coupling and light-matter interaction. This has enabled predictions of gate-induced phonon scattering in graphene gate stacks [35], atomistic description of ferroelectricity driven by edge-absorbed polar molecules in gated graphene [36], and new 2D material science such as prediction of the room-temperature photocurrent in emerging layered Janus materials with a large dipole across the plane [37]. The flexibility of the QuantumATK framework supports the imagination of researchers, and at the same time enables solutions to both real-world and cutting-edge semiconductor device and material science problems. \n\n![](images/67fae50bcba7df7713f3ac431e953da8b0411c4f81ceaf7df0ea5eaabdcb8490.jpg) \nFigure 2.  Supported atomistic configurations in QuantumATK. (a) Molecule configuration of a pentane molecule. (b) Bulk configuration of a gold crystal. (c) Device configuration of a gold-silver interface. The structure consists of a left electrode (transparant yellow), central region (orange box), and a right electrode (transparent yellow). Both electrodes are semi-infinite in the left-right transport direction. The device is in this case periodic in the two directions perpendicular to the transport direction, but would be nonperiodic in one or both perpendicular directions in case of a nanosheet or nanotube device, respectively. (d) Surface configuration of a gold surface. The structure consists of a left electrode (transparant yellow) and a central region (orange box). We note that an electric field can be applied to the surface by choice of boundary condition on the right-hand face of the central region. \n\nThe purpose of this paper is to give a general overview of the QuantumATK platform with appropriate references to more thorough descriptions of several aspects of the platform. We also provide application examples that illustrate how the different simulation engines can complement each other. The paper is organized as follows: In section 2 we give a general overview of the QuantumATK platform, while section 3 introduces the types of system geometries handled by the platform. The next three sections  4–6 describe the DFT, SE, and FF simulation engines, respectively. We then introduce a number of simulation modules that work with the different engines. These modules include ion dynamics (section 7.1), phonon properties (section 8), polarization (section 9), magn­etic aniso­tropy energy (section 10), and quantum transport (section 11). We next describe the parallel computing strategies of the different engines, and present parallel scaling plots in section 12. We then in section 13 describe the scripting and GUI simulation environment in the QuantumATK platform. This is followed by four application examples in section 14, and the paper is summarized in section 15. \n\n# 2.  Overview \n\nThe core of QuantumATK is implemented in $^{C++}$ modules with Python bindings, such that all $^{C++}$ modules are accessible from ATK-Python, a customized version of Python built into the software. The combination of a $^{C++}$ backend and a Python-based frontend offers both high computational performance and a powerful but user-friendly scripting platform for setting up, running, and analyzing atomic-scale simulations. All simulation engines listed in table  1 are invoked using ATK-Python scripting. More details are given in section 13.1. QuantumATK also relies on a number of open-source packages, including high-performance numerical solvers. \n\nAll computationally demanding simulation modules may be run in parallel on many processors at once, using message passing between processes and/or shared-memory threading, and often in a multi-level approach. More details are given in section 12. \n\nThe full QuantumATK package is installed on Windows or Linux/Unix operating systems using a binary installer obtained from the Synopsys SolvNet website, https://solvnet. synopsys.com. All required external software libraries are precompiled and shipped with the installer. Licensing is handled using the Synopsys common licensing (SCL) system. \n\n# 3.  Atomistic configurations \n\nThe real-space physical system to be simulated is defined as an ATK-Python configuration object, including lattice vectors, element types and positions, etc. QuantumATK currently offers four main types of such configurations: molecule, bulk, device, and surface. Examples of these are given in figure 2. \n\nThe simplest configuration is the molecule configuration shown in figure 2(a). It is used for isolated (non-periodic) systems, and is defined by a list of elements and their positions in Cartesian coordinates. \n\nThe bulk configuration, shown in figure  2(b), defines an atomic-scale system that repeats itself in one or more directions, for example a fully periodic crystal (periodic in 3D), a 2D nanosheet (or a slab), or a 1D nanowire. The bulk system is defined by the Bravais lattice and the position of the atomic elements inside the primitive cell. \n\nThe two-probe device configuration is used for quantum transport simulations. As shown in figure 2(c), the device consists of a central region connected to two semi-infinite bulk electrodes. The central region, where scattering of electrons travelling from one electrode to the other may take place, can be periodic in zero (1D wire), one (2D sheet), or two (3D bulk) directions, but is bounded by the electrodes along the third dimension. The device configuration is used to simulate electron and/or phonon transport via the non-equilibrium Green’s function (NEGF) method [38]. \n\nFinally, for physically correct simulations of a surface, QuantumATK provides the one-probe surface configuration. This is basically a device configuration with only one electrode, as illustrated in figure  2(d). By construction, the surface configuration realistically describes the electronic structure of a semi-infinite crystal beyond the approximate slab model [19]. \n\nThe remainder of this paper is devoted to describing the computational methods available for calculating the properties of such configurations using QuantumATK. \n\n# 4.  DFT simulation engines \n\nDensity functional theory is implemented in the Kohn–Sham (KS) formulation [14–17] within the framework of the linear combination of atomic orbitals (LCAO) and plane-wave (PW) basis set approaches, combined with the pseudopotential method. The electronic system is seen as a non-interacting electron gas of density $n$ in the effective potential $V^{\\mathrm{eff}}[n]$ , \n\n$$\n\\begin{array}{r}{V^{\\mathrm{eff}}[n]=V^{\\mathrm{H}}[n]+V^{\\mathrm{xc}}[n]+V^{\\mathrm{ext}}[n],}\\end{array}\n$$ \n\nwhere $V^{\\mathrm{H}}$ is the Hartree potential describing the classical electrostatic interaction between the electrons, $V^{\\mathrm{xc}}$ is the exchange-correlation (XC) potential, which in practise needs to be approximated, and $V^{\\mathrm{ext}}$ is the sum of the electrostatic potential energy of the electrons in the external potential of ions and other electrostatic field sources. The total external potential is in QuantumATK given by \n\n$$\nV^{\\mathrm{ext}}=\\sum_{a}V_{a}^{\\mathrm{pseudo}}+V^{\\mathrm{gate}},\n$$ \n\nwhere $V_{a}^{\\mathrm{pseudo}}$ includes the local $(V_{a}^{\\mathrm{loc}})$ and nonlocal $(V_{a}^{\\mathrm{nl}})$ contrib­utions to the pseudopotential of the ath atom. The term $V^{\\mathrm{gate}}$ is a potential that may originate from other external sources of electrostatic fields, for example metallic gates. \n\nThe KS Hamiltonian consists of the single-electron kinetic energy and the effective potential, \n\n$$\n\\hat{H}^{\\mathrm{KS}}=-\\frac{\\hbar^{2}}{2m}\\nabla^{2}+V^{\\mathrm{eff}},\n$$ \n\nand the single-electron energies $(\\epsilon_{\\alpha})$ and wave functions $(\\psi_{\\alpha})$ are solutions to eigenvalue problem \n\n$$\n\\hat{H}^{\\mathrm{KS}}\\psi_{\\alpha}=\\epsilon_{\\alpha}\\psi_{\\alpha}.\n$$ \n\nThe electronic ground state is found by iteratively minimizing the KS total-energy density functional, $E[n]$ , with respect to the electron density, \n\n$$\n\\boldsymbol E[n]=\\boldsymbol T+\\boldsymbol E^{\\mathrm{H}}[n]+\\boldsymbol E^{\\mathrm{xc}}[n]+\\boldsymbol E^{\\mathrm{ext}}[n],\n$$ \n\nwhere $T$ is the kinetic energy. The forces (acting on the atoms) and stress tensor of the electronic system may then be computed as derivatives of the ground-state total energy with respect to the atomic coordinates and the strain tensor, respectively. \n\n# 4.1.  LCAO representation \n\nThe DFT-LCAO method uses a LCAO numerical representation of the KS equations, closely resembling the SIESTA formalism [20]. This allows for a localized matrix representation of the KS Hamiltonian in (3), and therefore an efficient implementation of KS-DFT for molecules, bulk materials, interface structures, and nanoscaled devices. \n\nIn the DFT-LCAO method, the single-electron KS eigenfunctions, $\\psi_{\\alpha}$ , are expanded in a set of finite-range atomic-like basis functions $\\phi_{i},$ \n\n$$\n\\psi_{\\alpha}(\\mathbf{r})=\\sum_{i}c_{\\alpha i}\\phi_{i}(\\mathbf{r}).\n$$ \n\nThe KS equation can then be represented as a matrix equation for determining the expansion coefficients $c_{\\alpha i}$ , \n\n$$\n\\sum_{j}H_{i j}^{\\mathrm{KS}}c_{\\alpha j}=\\varepsilon_{\\alpha}\\sum_{j}S_{i j}c_{\\alpha j},\n$$ \n\nwhere the Hamiltonian matrix $H_{i j}^{\\mathrm{KS}}=\\langle\\phi_{i}|\\hat{H}^{\\mathrm{KS}}|\\phi_{j}\\rangle$ and overlap matrix $S_{i j}=\\langle\\phi_{i}|\\phi_{j}\\rangle$ are given by integrals with respect to the electron coordinates. Two-center integrals are computed using 1D radial integration schemes employing a Fourier transform technique, while multiple-center integrals are computed on a real-space grid [20]. \n\nFor molecules and bulk systems, diagonalization of the Hamiltonian matrix yields the density matrix $D_{i j}$ , \n\n![](images/8cd273210efa84f2c18c8b98e77af03fbbee40dc9782cb083f775106b8831f96.jpg) \nFigure 3.  Time per 10 selfconsistent field (SCF) iterations for different sized gold melts at $900\\mathrm{K}$ . For each system, we use a single $\\mathbf{k}$ -point and the simulation runs on a 16-core CPU. The timings of the DFT-PW method are compared to those of the DFT-LCAO method using the Ultra (LCAO-U), High (LCAO-H), and Medium (LCAO-M) basis sets. \n\n$$\nD_{i j}=\\sum_{\\alpha}c_{\\alpha i}^{*}c_{\\alpha j}f\\left(\\frac{\\varepsilon_{\\alpha}-\\varepsilon_{\\mathrm{{F}}}}{k_{\\mathrm{{B}}}T}\\right),\n$$ \n\nwhere $f$ is the Fermi–Dirac distribution of electrons over energy states, $\\varepsilon_{\\mathrm{{F}}}$ the Fermi energy, $T$ the electron temperature, and $k_{\\mathrm{B}}$ the Boltzmann constant. For device and surface configurations, the density matrix is calculated using the NEGF method, as described in section 11. \n\nThe electron density is computed from the density matrix, \n\n$$\nn(\\mathbf{r})=\\sum_{i j}D_{i j}\\phi_{i}(\\mathbf{r})\\phi_{j}(\\mathbf{r}),\n$$ \n\nand is represented on a regular real-space grid, which is the same grid as used for the effective potential in (1). \n\n# 4.2.  PW representation \n\nA PW representation of the KS equations was recently implemented in QuantumATK. It is complimentary to the LCAO representation discussed above. The ATK-PlaneWave engine is intended mainly for simulating bulk configuratins with periodic boundary conditions. The KS eigenfunctions are expanded in terms of PW basis functions, \n\n$$\n\\psi_{\\alpha}(\\mathbf{r})=\\sum_{|\\mathbf{g}|
MediumHighUltraPW
Elemental solids: Delta tests
SG15 (meV)1.882.031.32
3.45 PseudoDojo (meV) 4.531.521.401.04
Rock salts: RMS of a and B
SG15 (%)0.240.230.16
PseudoDojo (%)0.180.150.09
Perovskites: RMS of a and B
SG15 (%)0.180.13
PseudoDojo (%)0.130.06
\n\nThe ATK-PlaneWave engine was implemented on the same infrastructure as used by the ATK-LCAO engine, though a number of routines were modified to reach state-of-the-art PW efficiency. For example, we have adopted iterative algorithms for solving the KS equations [39], and fast Fourier transform (FFT) techniques for applying the Hamiltonian operator and evaluating the electron density [40, 41]. \n\nIn figure 3 we compare the CPU times of DFT-PW vesrus DFT-LCAO calculations for different LCAO basis sets. The figure shows the CPU time for the different methods as function of the system size. The PW approach is computationally efficient for smaller systems, while the LCAO approach can be more than an order of magnitude faster for systems with more than 100 atoms. \n\n# 4.3.  Pseudopotentials and LCAO basis sets \n\nQuantumATK uses pseudopotentials (PPs) to avoid explicit DFT calculations of core electrons, and currently supports both scalar-relativistic and fully relativistic normconserving PPs [42]. Projector augmented-wave (PAW) potentials [43] is cur­rently available for the ATK-PlaneWave simulation engine only. \n\nThe QuantumATK platform is shipped with built-in databases of well-tested PPs, covering all elements up to $Z=83$ (Bi), excluding lanthanides. The current default PPs are those of the published SG15 [44] and PseudoDojo [45] sets. These are two modern normconserving PP types with multiple projectors for each angular momentum, to ensure high accuracy. Both sets contain scalar-relativistic and fully relativistic PPs for each element. The fully relativistic PPs are generated by solving the Dirac equation for the atom, which naturally includes spin–orbit coupling, and then mapping the solution onto the scalar-relativistic formalism [42, 46]. \n\nTable 3.  Fundamental band gaps (in units of eV) for a range of semiconductors and simple oxides, calculated using different XC methods, and compared to experimental values. The ATK-LCAO simulation engine was used for PBE, TB09, and PBE-1/2 calculations, while the ATK-PlaneWave engine was used for simulations using HSE06. PseudoDojo PPs were used, combined with Ultra basis sets for DFTLCAO, except for TB09 calculations, which were done using FHI-DZP. Default cutoff energies were used, and a $\\mathbf{k}$ -point grid density of $7\\mathring{\\mathrm{A}}$ . For bulk silicon, this corresponds to a $15\\times15\\times15{\\bf k}$ -point grid. Experimental band gaps are from [53] unless otherwise noted. The bottom row lists the RMS deviation between theory and experiments. \n\n\n
MaterialExperimentPBETB09PBE-1/2HSE06
C5.484.195.115.595.33
Si1.170.571.201.161.17
Ge0.740.001.110.810.55a
SiC2.421.362.312.662.27
BP2.401.241.791.632.01
BAs1.461.251.941.582.05
AIN6.134.166.975.835.54
AIP2.511.552.362.462.30
AlAs2.231.452.452.382.27
AlSb1.681.221.821.921.76
GaN3.501.894.103.272.87
GaP2.351.592.382.222.26
GaAs1.520.631.811.231.11
GaSb0.730.110.760.520.64
InN0.690.001.741.200.49
InP1.420.692.171.301.26
InAs0.410.001.080.510.23
InSb0.230.000.490.320.27
TiO23.0b1.913.113.003.37
SiO28.9c6.0711.318.167.83
ZrO25.5℃3.654.965.265.16
HfO25.7℃4.175.545.875.76
ZnO3.44d0.953.242.782.47
MgO7.224.798.516.756.49
RMS error1.340.710.330.43
\n\na Direct band gap $\\Gamma\\rightarrow\\Gamma$ ), different in size from the $0.72\\mathrm{eV}$ reported in [67], but similar to the $0.56\\mathrm{eV}$ reported in [53], both using theoretical lattice constants rather than experimental ones. b [68]. c [69]. d [70]. \n\nFor each PP, we have generated an optimized LCAO basis set, consisting of orbitals $\\phi_{\\mathrm{nlm}}$ , \n\n$$\n\\phi_{\\mathrm{nlm}}(\\mathbf{r})=\\chi_{n l}(r)Y_{l m}(\\hat{\\mathbf{r}}),\n$$ \n\nwhere $Y_{l m}$ are spherical harmonics, and $\\chi_{n l}$ are radial functions with compact support, being exactly zero outside a confinement radius. The basis orbitals are obtained by solving the radial Schrödinger equation for the atom in a confinement potential [20]. For the shape of the confinement potential, we follow [47]. \n\nTo construct high-accuracy LCAO basis sets for the SG15 and PseudoDojo PPs, we have adopted a large set of pseudoatomic orbitals that are similar to the ‘tight tier $2^{\\circ}$ basis sets used in the FHI-aims package [47]. These basis sets typically have 5 orbitals per PP valence electron, and a range of $\\Dot{5}\\Dot{\\mathrm{A}}$ for all orbitals, and include angular momenta up to $l=5$ . From this large set, we have constructed three different series of reduced DFT-LCAO basis sets implemented in QuantumATK: \n\n1.\t\u0007Ultra: generated by reducing the range of the original pseudo-atomic orbitals, requiring that the overlap of each contracted orbital with the corresponding original orbital can change by no more than $0.1\\%$ . Also denoted ‘LCAO-U’. 2.\t\u0007High: generated by reducing the number of basis orbitals in the Ultra basis set, requiring that the DFT-obtained total energy of suitably chosen test systems change by no more than 1 meV/atom. Also denoted ‘LCAO- $\\mathbf{\\nabla}\\cdot\\mathbf{H}^{\\prime}$ . 3.\t\u0007Medium: generated by further reduction of the number of orbitals in the High basis set, requiring that the subsequent change of the DFT-obtained total energies do not exceed 4 meV/atom. Also denoted ‘LCAO-M’. The number of pseudo-atomic orbitals in a Medium basis set is typically comparable to that of a double-zeta polarized (DZP) basis set. \n\nTable 4.  Silicon and germanium equilibrium lattice constants and fundamental band gaps, both calculated using the PPS-PBE XC method, and compared to experiments at $300\\mathrm{K}$ . The SG15- High combination of PPs and LCAO basis sets was used, and a $15\\times15\\times15{\\bf k}$ -point grid. The lattice constants were determined by minimizing the first-principles stress on the primitive unit cells, using a maximum stress criterion of 0.1 GPa $(0.6~\\mathrm{meV}\\mathring{\\mathbf{A}}^{-3},$ ). \n\n\n
MaterialPropertyPPS-PBEExperiment
SiliconLattice constant5.439 A5.431A
Band gap1.14 eV1.12eV
GermaniumLattice constant5.736A5.658 A
Band gap0.65eV0.67eV
\n\nTo validate the PPs and basis-sets, we have used the $\\Delta$ -test [48, 50] to check the accuracy of the equation  of state for elemental, rock-salt, and perovskite solids against all-electron reference calculations, as shown in table  2. For each bulk crystal, the equation of state was calculated at fixed internal ion coordinates, and the equilibrium lattice constant and bulk modulus were computed. In table  2, the $\\Delta$ -value is defined as the root-mean-square (RMS) energy difference between the equations  of state obtained with QuantumATK and the all-electron reference, averaged over all crystals in a purely elemental benchmark set. \n\nTable 2 suggests a general trend that the PseudoDojo PPs are slightly more accurate than the SG15 ones. Since the PseudoDojo PPs are in general also softer, requiring a lower real-space density mesh cutoff energy, these are the default PPs in QuantumATK. \n\nTable 2 also shows that the accuracy of the DFT-LCAO calculations done with High or Ultra basis sets is rather close to that of the PW calculations. The Medium basis sets give on average a larger deviation from the PW results. However, we also find that LCAO-M provides sufficient accuracy for many applications, and it is therefore the default ATK-LCAO basis set in QuantumATK. We note that in typical applications, using Medium instead of the High (Ultra) basis sets decreases the computational cost by a factor of 2–4 (10–20), as seen in figure 3. \n\nMore details on the construction and validation of the LCAO basis sets can be found in [19]. \n\n# 4.4.  Exchange-correlation methods \n\nThe XC functional in (5) is the only formal approximation in KS-DFT, since the exact functional is unknown [15–17]. QuantumATK supports a large range of approximate XC functionals, including the local density approximation (LDA), generalized gradient approximations (GGAs), and meta-GGA functionals, all supplied through the Libxc library [51]. The ATK-PlaneWave engine also allows for calculations using the HSE06 screened hybrid functional [52–54]. The ATK-LCAO and ATK-PlaneWave engines both support van der Waals dispersion methods using the two-body and three-body dispersion corrections by Grimme [55]. Both DFT engines support different spin variants for each XC functional: spin-unpolarized and spin-polarized (both collinear and noncollinear). Spin-polarized noncollinear calculations may include spin– orbit interaction through the use of fully relativistic PPs. \n\n4.4.1.  Semilocal functionals.  During the past 20 years, the semilocal (GGA) XC approximations have been widely used, owing to a good balance between accuracy and efficiency for DFT calculations. QuantumATK implements many of the popular GGAs, including the general-purpose PBE [56], the PBEsol (designed for solids) [57], and the revPBE/RPBE functionals (designed for chemistry applications) [58]. Recently, the meta-GGA SCAN functional [59] was also included in QuantumATK, often providing improved accuracy of DFT calculations as compared to PBE. \n\n4.4.2.  Hybrid functionals.  Hybrid XC approximations mix local and/or semilocal functionals with some amount of exact exchange in order to provide higher accuracy for electronicstructure calculations [52, 60]. However, the computational cost is usually much higher than for semilocal approx­ imations. New methodological developments based on the adaptively compressed exchange operator (ACE) method [61] allow reducing the computational burden of hybrid functionals. The ACE algorithm was recently implemented in Quant­ umATK for HSE06 calculations, which gives a systematically good description of the band gap of most semiconductors and insulators, see table 3. \n\n4.4.3.  Semiempirical methods.  Using hybrid functionals is computationally demanding for simulating large systems, often even prohibitive. QuantumATK offers a number of semiempirical XC methods that allow for computationally efficient simulations while giving rather accurate semiconductor band gaps. These include the DFT-1/2 method [62, 63], the TB09 XC potential [64], and the pseudopotential projectorshift approach of [19]. \n\nThe selfconsistent DFT-1/2 methods, including LDA1/2 and GGA-1/2, do contain empirical parameters. In QuantumATK, these parameters are chosen by fitting the calculated band gaps to measured ones for bulk crystals. Table  3 suggests that the DFT-1/2 method, as implemented in QuantumATK, allows for significantly improved band gaps at almost no extra computational cost. We note that a recent study has shown certain limitations of the DFT-1/2 method, in particular for anti-ferromagnetic transition metal oxides [65]. Furthermore, this method does not provide reliable force and stress calculations. It is also important to note that not all species in the system necessarily require the DFT-1/2 correction. In general, it is advisable to apply this correction to the anionic species only, keeping the cationic species as normal [62, 63]. \n\nThe Tran–Blaha meta-GGA XC functional (TB09) [64] introduces a parameter, $c$ , which can be calculated selfconsistently according to an empirical formula given in [64]. Table  3 includes band gaps computed using this approach. The $c$ -parameter may also be adjusted to obtain a particular band gap for a given material, and QuantumATK allows for setting different TB09 $\\boldsymbol{c}$ -parameters on different regions in the simulation cell. This may be useful for studying electronic effects at interfaces between dissimilar materials, for example in oxide-semiconductor junctions, where the appropriate (and material-dependent) $c$ -parameter may be significantly different in the oxide and in the semiconductor. \n\nQuantumATK also offers a pseudopotential projector-shift (PPS) method, that introduces empirical shifts of the nonlocal projectors in the PPs, in spirit of the empirical PPs proposed by Zunger and co-workers [66]. The PPS method is usually combined with ordinary PBE calculations [19]. The two main advantages of this PPS-PBE approach are that (1) for each semiconductor, the projector shifts can be fitted such that the DFT-predicted fundamental band gap and lattice parameters are both fairly accurate compared to measured ones, and (2) the PPS method does yield first-principles forces and stress, and therefore can be used for geometry optimization, unlike the DFT- $1/2$ and TB09 methods. Table  4 shows that the PPS-PBE predicted equilibrium lattice parameters are only slightly overestimated, and the PPS-PBE band gaps are fairly close to experiments. We note that the PPS-PBE parameters are currently available in QuantumATK for the elements silicon and germanium only. \n\n4.4.4. $D F T+U$ methods.  QuantumATK supports the mean-field Hubbard-U correction by Dudarev et  al [71] and Cococcioni et  al [72], denoted $\\mathrm{DFT+U}$ , $\\mathrm{LDA}+\\mathrm{U}$ , $\\mathrm{GGA}+\\mathrm{U}$ , or $\\mathrm{XC}+\\mathrm{U}$ . This method aims to include the strong on-site Coulomb interaction of localized electrons (often localized $d$ and $f$ electrons), which are not correctly described by LDA or GGA. A Hubbard-like term is added to the XC functional, \n\n$$\nE_{U}=\\frac{1}{2}\\sum_{l}U_{l}(n_{l}-n_{l}^{2}),\n$$ \n\nwhere $n_{l}$ is the projection onto an atomic shell $l$ , and $U_{l}$ is the Hubbard $\\mathrm{~U~}$ for that shell. The energy term $E_{U}$ is zero for a fully occupied or unoccupied shell, but positive for a fractionally occupied shell. This favors localization of electrons in the shell $l$ , typically increasing the band gap of semiconductors. \n\n# 4.5.  Boundary conditions and Poisson solvers \n\nAs already mentioned in section  4.1, the electron density, $n(\\mathbf{r})$ in (9), and the effective potential, $V^{\\mathrm{eff}}(\\mathbf{r})$ in (3), are in QuantumATK represented on a real-space regular grid. The corresponding Hartree potential $V^{\\mathrm{H}}({\\bf r})$ is then calculated by solving the Poisson equation  on this grid with appropriate boundary conditions (BCs) imposed on the six facets of the simulation cell, \n\n$$\n\\nabla^{2}V^{\\mathrm{H}}(\\mathbf{r})=-{\\frac{e^{2}}{4\\pi\\epsilon_{0}}}n(\\mathbf{r}),\n$$ \n\n![](images/9503d9ca903f8d1dfcea6f3f71067a65b3d0af67658b88bf9b7fb584c5120158.jpg) \nFigure 4.  QuantumATK supports many different BCs. (a) Multipole BCs for a charged molecule in all directions, (b) 3D periodic BCs for a bulk configuration, (c) mixed Dirichlet and Neumann BCs for a slab model, (d) Dirichlet and Neumann BCs are also the natural choice for a surface configuration, (e) Dirichlet BCs at the interfaces between the semi-infinite electrodes and the central region in a device configuration. Note that periodic BCs are imposed in the directions perpendicular to the $C\\mathrm{.}$ -axis in (b)–(e). \n\nwhere $e$ is the elementary charge, and $\\epsilon_{0}$ is the vacuum permittivity. \n\nIn QuantumATK, one may also specify metallic or di­electric continuum regions in combination with a microscopic, atomistic structure, as demonstrated for a 2D device in figure 14 in section 14.1. This affects the solution of the Poisson equation (14) in the following way. For a metallic region denoted $\\Omega$ , the electrostatic potential is fixed to a constant potential value $(V_{0})$ within this region, i.e. the Poisson equation  is solved with the constraint \n\nTable 5.  Classes of TB models currently supported by ATK-SE. The model types are either two-center Slater–Koster (SK) or based on environment-dependent parameters (Env). The model may be orthogonal $(H)$ or non-orthogonal $(H,S)$ . Short-ranged models include nearest-neighbour interactions only (range up to a few A˚), while the long-ranged Hückel models have a typical range of 5–10 $\\mathring\\mathbf{A}$ . As indicated in the right-hand column, not all models support calculation of total energies, forces, and stress, but are used mainly for simulating the electronic structure of materials. \n\n\n
ModelRef.TypeRangeE,F,0
Hickel[79]SK, (H,S)longno
Empirical TB[18]SK, (H)shortno
DFTB[78]SK, (H,S)mediumyes
Purdue[80]Env, (H)shortno
NRL[81]Env, (H,S)longyes
\n\n$$\nV^{\\mathrm{H}}(\\mathbf{r})=V_{0},\\mathbf{r}\\in\\Omega.\n$$ \n\nFor a dielectric region denoted $\\Upsilon$ , the right-hand side of the Poisson equation will be modified as follows: \n\n$$\n\\begin{array}{l l l}{{\\displaystyle\\nabla^{2}V^{\\mathrm{H}}({\\bf r})=-\\frac{e^{2}}{4\\pi\\epsilon_{0}}n({\\bf r}),{\\bf r}\\notin\\Upsilon,}}\\\\ {{\\displaystyle\\nabla^{2}V^{\\mathrm{H}}({\\bf r})=-\\frac{e^{2}}{4\\pi\\epsilon_{r}\\epsilon_{0}}n({\\bf r}),{\\bf r}\\in\\Upsilon,}}\\end{array}\n$$ \n\nwhere $\\epsilon_{r}$ is the relative dielectric constant, which can be specified as an external parameter in QuantumATK calculations. \n\n4.5.1.  Boundary conditions.  QuantumATK implements four basic types of BCs; multipole, periodic, Dirichlet and Neumann BCs. It is also possible to impose mixed BCs on the six facets of the simulation cell to simulate a large variety of physical systems at different levels of approximation. \n\nA multipole BC means that the Hartree potential at the boundary is determined by calculating the monopole, dipole and quadrupole moments of the charge distribution inside the simulation cell, and that these moments are used to extrapolate the value of the potential at the boundary. A Dirichlet BC means that the potential has been fixed to a certain potential $V_{0}(\\mathbf{r})$ at the boundary, such that, for a facet $S$ of the simulation cell, \n\n$$\nV^{\\mathrm{H}}(\\mathbf{r})=V_{0}(\\mathbf{r}),\\mathbf{r}\\in S.\n$$ \n\nA Neumann BC means that the normal derivative of the potential on a facet has been fixed to a given function $V_{0}^{\\prime}(\\mathbf{r})$ , \n\n$$\n\\frac{{\\partial{{V}^{\\mathrm{H}}}}({\\bf{r}})}{{\\partial{\\bf{n}}}}={\\bf{n}}\\cdot\\nabla{{V}^{\\mathrm{H}}}({\\bf{r}})=V_{0}^{\\prime}({\\bf{r}}),{\\bf{r}}\\in S,\n$$ \n\nwhere $\\mathbf{n}$ denotes the normal vector of the facet. Next, we briefly describe applications of the different BCs. \n\n•\t\u0007Multipole $B C s$ are used for molecule configurations, ensuring the correct asymptotic behavior of the Hartree potential, even for charged systems (ions or charged molecules), as shown in figure 4(a). \n\nTable 6.  Selected potential models included in ATK-ForceField. \n\n\n
Potential modelSpecial propertiesReferences
Stillinger-Weber (SW)Three-body[85]
Embedded atom model (EAM)Many-body[86]
Modified embedded atom model (MEAM)Many-body Directional bonding[87]
Tersoff/BrennerBond-order[88,89]
ReaxFFBond-order Dynamical charges[90]
COMB/COMB3Bond-order Dynamical charges Induced dipoles[91]
Core-shellDynamical charge fluctuations[92]
Tangney-Scandolo (TS)Induced dipoles[93]
Aspherical ion modelInduced dipoles and quadrupoles Dynamical ion distortion[94]
Biomolecular and valence force fieldsStatic bonds[95,96]
\n\n•\t\u0007Periodic $B C s$ is the natural choice along all directions for fully periodic bulk materials, as shown in figure 4(b). Periodic BCs are also often used to model heterostructures or interfaces, as well as surfaces using a slab model. •\t\u0007Dirichlet–Neumann BCs for a slab model. In slab calcul­ ations, it can be more advantageous to impose mixed BCs, such as Neumann (fixed potential gradient) and Dirichlet (fixed potential) on the left- and right-hand side of the slab, respectively, combined with periodic BCs in the in-plane-directions, as shown in figure  4(c). These mixed BCs provide a physically sound alternative to the often-used dipole correction for slab calculations [73]. •\t\u0007Dirichlet–Neumann BCs for a surface configuration. For accurate surface simulations, the surface configuration may be used, in combination with mixed BCs: Neumann in the right-hand-side vacuum region, Dirichlet at the left electrode, and periodic BCs in the in-plane directions, see figure 4(d). In this case, one can account, e.g. for the charge transfer from the near-surface region to the semiinfinite electrode, which acts as an electron reservoir [19]. •\t\u0007Dirichlet BCs for a device configuration. Two-probe device simulations are in QuantumATK done using Dirichlet BCs at the left and right boundaries to the electrodes. Periodic BCs may then be applied in the directions perpendicular to the electron transport direction, as shown in figure 4(e). For complex devices, one may need to apply a more mixed set of BCs, as discussed in the following. \n\n•\t\u0007General mixed BCs. QuantumATK also allows for combining Neumann, Dirichlet and periodic BCs. This can be used to, e.g. model a 2D device in a field-effect transistor setup, such as that in figure 14. \n\nTable 7.  ATK-ForceField timings as compared to LAMMPS [97]. Absolute timings for molecular dynamics (MD) simulations, in units of microseconds per atom per MD step, using one computing core for all potentials. Potential abbreviations are defined in table 6. In addition, LJ means Lennard–Jones. More details of the benchmark systems can be found in [28]. \n\n\n
LJTersoffSWEAMReaxFFCOMBTS
QuantumATK3.86.35.23.8180320360
LAMMPS1.97.85.22.4190240N/A
\n\nWe note that for systems with periodic or Neumann BCs in all directions, the Hartree potential can only be determined up to an additive constant. In this case, in order to obtain a uniquely defined solution, we require the average of the Hartree potential to be zero when solving the Poisson equation. \n\n4.5.2.  Poisson solvers.  To handle such different BCs, the QuantumATK simulation engines use Poisson solvers based on either FFT methods or real-space finite-difference (FD) methods. The FD methods are implemented using a multigrid solver [74], a parallel conjugate-gradient-based solver [75], and the MUMPS direct solver [76]. The real-space methods also allow for specifying spatial regions with specific di­electric constants or values of the electrostatic potential, as mentioned above. \n\nFor systems with 2D or 3D periodic BCs, and no dielectric regions or metallic gates, the Poisson equation  (14) is most efficiently solved using the FFT solvers. For a bulk configuration with 3D periodic directions, we use a 3D-FFT method, see figure 4(b). In the case of only 2 periodic directions, for example in slab models, surface configurations, and device configurations, we use a 2D-FFT method combined with a 1D finite-difference method, see figures 4(c)–(d) [77]. \n\n# 5.  Semi-empirical models \n\nAs a computationally fast alternative to DFT, the ATK-SE engine allows for semi-empirical TB-type simulations [24]. The TB models consist of a non-selfconsistent Hamiltonian that can be extended with a selfconsistent correction for charge fluctuations and spin polarization. These corrections closely follow the density functional tight-binding (DFTB) approach [78]. The main aspects of these TB models have been described in [24] and below we give only a brief description of the models. \n\nTable 5 summarizes the available models for the non-selfconsistent part of the SE Hamiltonian, $H_{i j}^{0}$ . Most of the models are non-orthogonal, that is, include a parametrization of the overlap matrix $S_{i j}$ . In most of the models, the Hamiltonian matrix elements depend only on two centers, parameterized in terms of Slater–Koster parameters. These models include Hückel models [79, 82], Slater–Koster orthogonal TB models [18, 83], and DFTB models [78]. The ATK-SE engine also supports models that take into account the position of atoms around the two centers. These currently include the environ­ment-dependent TB models from Purdue [80] and those from the U.S. Naval Research Laboratory [81]. \n\nIt is possible to add a selfconsistent correction to the nonselfconsistent TB models [24]. The selfconsistent correction use the change in the onsite Mulliken population of each orbital, relative to a reference system, to assign an orbitaldependent charge to each atom. The charge on the orbital is represented by a Gaussian orbital, and the width of the Gaussian, $\\sigma_{l}$ , can be related to an onsite repulsion, $U_{l},$ where $l$ is the angular momentum of the orbital. The relation is given by [24] \n\n$$\nU_{l}=\\frac{2e^{2}}{\\sqrt{\\pi}\\sigma_{l}}.\n$$ \n\nThis onsite repulsion can be calculated from the chargedependent onsite energies [78], \n\n$$\nU_{l}=\\frac{\\mathrm{d}\\varepsilon_{l}}{\\mathrm{d}n_{l}},\n$$ \n\nwhere $\\varepsilon_{l}$ is the orbital energy of the atom and $n_{l}$ the charge in orbital $l.$ QuantumATK comes with a database of $U_{l}$ calculated using DFT all-electron simulations of the atom. In practice, it is more reliable for each element to use a single averaged value [78], \n\n$$\nU=\\frac{1}{N}\\sum_{l}n_{l}U_{l},\n$$ \n\nwhere the average is determined by the number of valence electrons of each orbital, nl; $N=\\textstyle\\sum_{l}n_{l}$ . The ATK-SE default is to use such a single value. \n\nIn the ATK-SE selfconsistent loop, the Mulliken population is calculated for each orbital. Based on the change in charge relative to the reference system, a Gaussian charge is added at the orbital position. We note that in the default case, where an atom-averaged $U$ is used on each orbital, only changes in the atomic charge will have an affect. From the atom-centered charge we set up a real-space charge density from which the Hartree potential $V(\\mathbf{r})$ is calculated using the same methods as used for DFT, see section 4.5. It is added to the TB Hamiltonian through \n\n$$\nH_{i j}=H_{i j}^{0}+\\frac{1}{2}(V(\\mathbf{r}_{i})+V(\\mathbf{r}_{j}))S_{i j},\n$$ \n\nwhere $\\mathbf{r}_{i}$ is the position of orbital $i$ . \n\nThe ATK-SE engine also supports spin polarization through the term [84] \n\n$$\nH_{i j}^{\\sigma}=\\pm\\frac{1}{2}S_{i j}\\left(\\mathrm{d}E_{l_{i}}+\\mathrm{d}E_{l_{j}}\\right),\n$$ \n\n![](images/7f007cc206f0d1b737f5168e103c73f60f322a7db668021010a031deba4fe708.jpg) \nFigure 5.  Flowchart of a typical QuantumATK MD loop. \n\nwhere the sign depends on the spin. The spin splitting of shell $l,\\mathrm{d}E_{l_{i}}$ , is calculated from the spin-dependent Mulliken populations $m_{l\\uparrow},m_{l\\downarrow}$ of each shell at the local site $\\mu_{l}$ : \n\n$$\nd E_{l}=\\sum_{l^{\\prime}\\in\\mu_{l}}W_{l l^{\\prime}}\\left(m_{l^{\\prime}\\uparrow}-m_{l^{\\prime}\\downarrow}\\right).\n$$ \n\nThe shell-dependent spin-splitting strength $W_{l l^{\\prime}}$ is calculated from a spin-polarized atomic calculation [84], and ATK-SE provides a database with the parameters. \n\nThe main advantage of the SE models compared to DFT methods are their computational efficiency. For large systems, the main computational cost of both DFT and TB simulations is related to diagonalization of the Hamiltonian, the speed of which depends strongly on the number of orbitals on each site and their range. This makes TB Hamiltonians very attractive for large systems, provided the SE parametrization is appropriate for the particular simulation. Furthermore, orthogonal Hamiltonians have inherent performance advantages. The Empirical and Purdue environment-dependent models are the most popular TB models for electron transport calcul­ ations. We also note that for many two-probe device systems, it is mainly the band structure and quantum confinement that determine electrical characteristics such as current-voltage curves. TB model Hamiltonians can provide good results for such simple devices. Finally, DFTB models are popular for total-energy calculations, although we find in general that the accuracy should be cross-checked against DFT. \n\n# 6.  Empirical force fields \n\nATK-ForceField is a state-of-the-art FF simulation engine that is fully integrated into the Python framework. This has already been described in detail in [28], and we therefore only summarize some of the main features. \n\nTable 6 lists the empirical potential models supported by ATK-ForceField, which includes all major FF types. The simulation engine also allows for combining models, such that different FFs can be assigned to different sub-systems. The empirical potential for each sub-system, and the interactions between them, can be customized as desired, again using Python scripting. ATK-ForceField currently includes more than 300 predefined literature parameter sets, which can conveniently be invoked from the NanoLab GUI. Additionally, it is also possible to specify custom FF parameters via the Potential Editor tool in NanoLab or in a Python script, or even use builtin Python optimization modules to optimize the parameters against reference data. \n\nTable 7 compares the computational speed of ATKForceField molecular dynamics simulations to that of the popular LAMMPS package [97]. For most of the FF potential types, the two codes have similar performance. \n\n# 7.  Ion dynamics \n\nOne very powerful feature of QuantumATK is that ion dynamics is executed using common modules that are not specific to the chosen simulation engine. This means that modules for calculating energy, forces, and stress may be used with any of the supported engines, including DFT, SE methods, and classical FFs. Options for ion-dynamics simulations are defined using Python scripting, which allows for easy customization, extension, and combination of different simulation methods, without loss of performance. In section  14.3 we illustrate this by combining the DFT and FF engines in a single molecular dynamics simulation. Several methods related to ion dynamics in QuantumATK have been described in detail in [28], so here we only summarize the main features. \n\n![](images/fd214cb720845607e3c164822652d16925ee02eb18244914c45269894e8d2673.jpg) \nFigure 6.  Free energy map of a metadynamics simulation of surface vacancy diffusion on a $\\mathrm{Cu}(111)$ surface using QuantumATK. The collective variables CV1 and CV2 refer to the $x-$ and $y$ -position of a surface atom close to the vacancy. The atom positions of the surface layer of the lattice are depicted by the white circles. \n\n# 7.1.  Local structural optimization \n\nThe atomic positions in molecules and clusters are optimized by minimizing the forces, while for periodic crystals, the unitcell vectors can also be included in the optimization, possibly under an external pressure that may be anisotropic. The simultaneous optimization of positions and cell vectors is based on [98], where the changes to the system are described as a combined vector of atomic and strain coordinates. \n\nThe default method for optimization is the limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) quasiNewton-type minimization algorithm [99], but QuantumATK also implements the fast inertial relaxation engine (FIRE) method [100]. \n\n# 7.2.  Global structural optimization \n\nThe previous section considered methods for local geometry optimization, which locate the closest local minimum-energy configuration. However, often the goal is to find the globally most stable configuration, for example, the minimumenergy crystal structure. QuantumATK therefore implements a genetic algorithm for crystal structure prediction. It works by generating an initial set of random configurations and then evolving them using genetic operators, as described in [101]. An alternative approach is to perform simulated annealing using molecular dynamics [102]. \n\n# 7.3.  Reaction pathways and transition states \n\nThe minimum-energy path (MEP) for changes to the atomic positions from one stable configuration to another may be found using the nudged elastic band (NEB) method [103]. The QuantumATK platform implements state-of-the-art NEB [104], including the climbing-image method [105]. The initial set of images are obtained from linear interpolation between the NEB end points, or by using the image-dependent pair potential (IDPP) method [106]. The IDPP method aims to avoid unphysical starting guesses, and leads in general to an initial NEB path that is closer to the (unknown) MEP. This typically reduces the number of required NEB optimization steps by a factor of 2. \n\nIn some implementations, the projected NEB forces for each image are optimized independently. However, the L-BFGS algorithm is in that case known to behave poorly [107]. In QuantumATK, the NEB forces for each image are combined into a single vector, $\\mathbf{F}_{\\mathrm{NEB}}\\in\\mathbb{R}^{3m n}$ , where $m$ is the number of images and $n$ the number of atoms. This combined approach is more efficient when used with L-BFGS, and has been referred to as the global L-BFGS method [107]. \n\n# 7.4.  Molecular dynamics \n\nMolecular dynamics (MD) simulations provide insights into dynamic atomic-scale processes or sample microscopic ensembles. The essential functional blocks in a typical QuantumATK MD loop are depicted in figure  5. Different thermodynamic ensembles can be simulated. The basic NVE ensemble uses the well-known velocity-Verlet algorithm [108]. Additionally, thermostats or barostats can be applied to different parts of the system to simulate NVT or NPT ensembles, using for example the chained Nosé–Hoover thermostat [109], an impulsive version of the Langevin thermostat [110], or the barostat proposed by Martyna et al in [111] for isotropic and anisotropic pressure coupling. \n\nFigure 5 also shows that one may apply so-called pre-step hooks and post-step hooks during a QuantumATK MD simulation. These hook functions are scripted in ATK-Python, and may vastly increase flexibility with respect to specialized MD simulation techniques and custom on-the-fly analysis. This makes it easy to employ predefined or user-defined custom operations during the MD simulation. The pre-step hook is called before the force calculation, and may modify atomic positions, cell vectors, velocities, etc. This is often used to implement custom constraints on atoms or to apply a nontrivial strain to the simulation cell. The post-step hook is typically used to modify the forces and/or stress. It may, for example, be used to add external forces and stress contrib­ utions, such as a bias potential, to the regular interaction forces. \n\nQuantumATK is shipped with a number of predefined hook functions, implementing thermal transport via reverse non-equilibrium molecular dynamics (RNEMD) [112], metadynamics, and other methods. For metadynamics, QuantumATK integrates with the PLUMED package [113], so that all methods implemented in PLUMED are available in QuantumATK as well. Figure 6 illustrates the free-energy map of surface vacancy diffusion on $\\mathrm{Cu}(111)$ using the ATKForceField engine with an EAM potential [114]. \n\n# 7.5.  Adaptive kinetic Monte Carlo \n\nAdaptive kinetic Monte Carlo (AKMC) is an algorithm for modelling the long-timescale kinetics of solid-state mat­erials [115–117]. For a given configuration, AKMC involves 3 steps: (1) locate all kinetically relevant product states; (2) determine the saddle point between the reactant and product states; (3) select a reaction using kinetic Monte Carlo (KMC). \n\nStep 1 is in QuantumATK performed using high-temper­ ature MD. At regular intervals, the MD simulation is stopped and a geometry optimization is performed to check if the system has left the initial basin. This procedure is repeated until all relevant reactions are found within a user-specified confidence [117, 118]. \n\nIn step 2, the saddle-point geometry for each reaction is determined by performing a NEB optimization for each reaction, and the reaction rates $k$ are determined via harmonic transition-state theory (HTST) [119], \n\n$$\nk_{\\mathrm{HTST}}=\\frac{\\prod_{i}^{3N}\\nu_{i}^{\\mathrm{min}}}{\\prod_{i}^{3N-1}\\nu_{i}^{\\ddag}}\\exp\\left[-\\left(E^{\\ddag}-E^{\\mathrm{min}}\\right)/k_{\\mathrm{B}}T\\right],\n$$ \n\nwhere $N$ is the number of atoms, $\\nu_{i}^{\\mathrm{{min}}}$ and $\\nu_{i}^{\\ddag}$ are the positive (stable) normal-mode frequencies at the minimum and saddle points, $E^{\\mathrm{min}}$ and $E^{\\ddagger}$ the corresponding energies, $k_{\\mathrm{B}}$ is the Boltzmann constant, and $T$ the temperature. The ratio of the products of the vibrational frequencies in (25) is often called the attempt frequency or the prefactor, and can be computationally expensive to obtain. Instead of calculating the prefactor for each reaction mechanism, a user-given value may therefore be used. \n\nFinally, in step 3, a reaction is selected using KMC, the system evolves to the corresponding product configuration, and the entire procedure is repeated. More details of the QuantumATK implementation of AKMC may be found in [117]. \n\n# 8.  Phonons \n\nThe ground-state vibrational motion of atoms is of paramount interest in modern materials science. Within the harmonic approximation, which is valid for small thermal displacements of atoms around their equilibrium position, the vibrational frequencies of a configuration are eigenvalues of the dynamical matrix $D$ , \n\n$$\nD_{a,\\alpha;b,\\beta}=\\frac{1}{\\sqrt{m_{a}m_{b}}}\\frac{\\mathrm{d}F_{b,\\beta}}{\\mathrm{d}r_{a,\\alpha}},\n$$ \n\nwhere $m_{a}(m_{b})$ is the atomic mass of atom $a\\left(b\\right)$ and $d F_{b,\\beta}/\\mathrm{d}r_{a,\\alpha}$ is the force constant. Computing and diagonalizing $D$ yields the vibrational modes of the system (molecular or periodic), and is also used to obtain the phonon density of states for a periodic crystal. \n\n# 8.1.  Calculating the dynamical matrix \n\nQuantumATK calculates the dynamical matrix using a FD method, where each matrix element in (26) is computed by displacing atom $a$ along Cartesian direction $\\alpha$ , and then calculating the resulting forces on atom $b$ along directions $\\beta$ . This approach is sometimes referred to as the frozen-phonon or supercell method, and applies equally well to isolated (molecular) systems. The method lends itself to heavy computational parallelization over many computing cores, since all displacements may be calculated independently. Crystal symmetries are taken into account in that only symmetrically unique atoms in the unit cell are displaced, and the forces resulting from displacement of the equivalent atoms are obtained using the corresponding symmetry operations [120]. \n\n![](images/9ca8f9981516b2115473f1d2c413015978fa38948fd0a73cff390c561804ba61.jpg) \nFigure 7.  Phonon dispersions of the three FCC metals Au, $\\mathbf{A}\\mathbf{g}$ and $\\mathrm{Cu}$ , obtained from supercell calculations using the ATK-LCAO engine and the SG15-M LCAO basis set. Supercells were generated from $9\\times9\\times9$ repetitions of the primitive cells. \n\n# 8.2.  Wigner–Seitz method \n\nFor crystals with small unit cells, periodic repetition of the cell is usually needed to accurately account for long-range interactions in $D$ . For larger simulation cells, including cells with defects and amorphous structures, this is not always necessary, since the cell may already include the entire interaction range. In order to recover the correct phonon dispersion across periodic boundaries, the Wigner–Seitz method can be employed. Here, a Wigner–Seitz cell is centered around the displaced atom and the forces on each atom in the simulation cell is assigned to its periodic image that is located within the Wigner–Seitz cell [121]. \n\n# 8.3.  Phonon band structure and density of states \n\nThe phonon band structure (or phonon dispersion) consists of bands with index λ of vibrational frequencies ω = ωλq throughout the Brillouin zone (BZ) of phonon wave vectors q. The phonon density of states (phonon DOS) per unit cell, $g(\\omega)$ , is defined as \n\n$$\ng(\\omega)=\\frac{1}{N}\\sum_{\\mathbf{q}\\lambda}\\delta(\\omega-\\omega_{\\lambda\\mathbf{q}}),\n$$ \n\nwhere $N$ is the number of $\\mathbf{q}$ -points in the sum. In practice, the phonon DOS is calculated using the tetrahedron method [122]. Additionally, quantities such as vibrational free energy, entropy, and zero-point energy can easily be calculated from the vibrational modes and energies. \n\nFigure 7 gives an example of phonon simulations for different metals using the ATK-ForceField and ATK-LCAO engines. The ATK-LCAO supercell calculation yields accurate vibrational properties, as exemplified by the excellent agreement between the two methods. The dispersions follow the same trends, which is expected, since the three metals have the same FCC crystal symmetry. We note that the higher phonon frequencies in $\\mathrm{{Cu}}$ can be understood from the similar bond strength as in $\\operatorname{Ag}$ and Au, but significantly lower $\\mathrm{{Cu}}$ atomic mass. \n\n![](images/fd523521142cbfe953f5d5d3e6f327ca37720a87a994dd502ecb67059a8353e9.jpg) \nFigure 8.  (a) Illustrative $\\mathbf{k}-$ and $\\mathbf{q}$ -point selections in the Brillouin zone for the case of a two-dimensional semiconductor with two valleys $K$ and $K^{\\prime}$ ). In semiconductors, it is possible to make a clever selection of $\\mathbf{k}$ - and $\\mathbf{q}$ -points to minimize the computational load while including all relevant scattering processes. Typically, a sparse $\\mathbf{k}$ -point sampling is used for the mobility integral, while a denser $\\mathbf{q}$ -point sampling is needed to secure a correct scattering rate at each $\\mathbf{k}$ -point. (b) Fermi-surface of bulk Au. In metals, $\\mathbf{k}$ -points contributing to the neighborhood of the Fermi surface are not located in a small subset of the Brillouin zone. Therefore, $\\mathbf{k}-$ and $\\mathbf{q}$ -points are sampled in the full Brillouin zone, and $\\mathbf{q}$ -space is integrated using the tetrahedron method to minimize the sampling density. (c) Resistivity convergence with respect to the number of $\\mathbf{q}$ -points for bulk Au with either a direct or tetrahedron integration over the full Brillouin zone. Resistivities were calculated with $N_{k}\\times N_{k}\\times N_{k}\\mathbf{k}$ -points for a sequence of $N_{q}\\times N_{q}\\times N_{q}\\bullet$ q-points. \n\n# 8.4.  Electron-phonon coupling \n\nThe electron–phonon coupling (EPC) is an imporant quanti­ty in modern electronic-structure theory. It is, for example, used to calculate the transport coefficients in bulk crystals (see section  8.5) and inelastic scattering of electrons in two-probe devices (see section 11.8). \n\nTo obtain the EPC, we calculate the derivative of the Hamiltonian matrix with respect to the position of atom $a$ , $\\mathbf{r}_{a}$ , \n\n$$\n(\\delta\\hat{H}_{\\mathbf{r}_{a}})_{i j}=\\langle\\phi_{i}|\\frac{\\partial\\hat{H}}{\\partial\\mathbf{r}_{a}}|\\phi_{j}\\rangle,\n$$ \n\nwhere $\\partial\\hat{H}/\\partial\\mathbf{r}_{a}$ is calculated using finite differences, similar to the calculation of the dynamical matrix described above. A unit cell is repeated to form a supercell (for a device configuration, only the atoms in the central region are displaced). The terms that contribute to the Hamiltonian derivative is the local and non-local PP terms. The real-space Hamiltonian matrix is expanded in electron eigenstates, $n\\mathbf{k}$ , and Fourier transformed using the phonon polarization vectors, to finally obtain the electron–phonon couplings $g$ , \n\n$$\ng_{\\mathbf{k}\\mathbf{k}^{\\prime}\\mathbf{q}}^{\\lambda n n^{\\prime}}=\\langle n^{\\prime}\\mathbf{k}^{\\prime}|\\delta\\hat{H}_{\\lambda\\mathbf{q}}|n\\mathbf{k}\\rangle,\n$$ \n\nwhere $\\mathbf{q}$ is the phonon momentum and $\\lambda$ the phonon branch index. \n\nFurther details of how QuantumATK calculates the EPC are given in [123]. \n\n# 8.5. Transport coefficients \n\nThe electron/hole mobility in a semiconductor material is an important quantity in device engineering, and also determines the conductivity of metals. Electronic transport coefficients for bulk materials, including the conductivity, Hall conductivity, and thermoelectric response, may be calculated from the Boltzmann transport equation  (BTE) as linear-response coefficients related to the application of an electric field, magn­etic field, or temperature gradient. In QuantumATK, this is done by expanding the current density $\\mathbf{j}$ to lowest order in the electric field $\\mathcal{E}$ , magnetic field $B$ , and temperature gradient $\\boldsymbol{\\nabla}T$ , \n\nTable 8.  Born effective charges $(Z^{*})$ and piezoelectric tensor components ( $\\stackrel{\\cdot}{\\epsilon}_{33}$ and $\\epsilon_{14}$ ) for $\\mathrm{III-V}$ wurtzite nitrides and zincblende GaAs. Reference vales for the nitrides are from [127] and from [126] for GaAs. QuantumATK calculations were performed using the DFT-LCAO engine with the LDA XC functional and a DZP basis set. \n\n\n
Z*E33
ReferenceQuantumATKReferenceQuantumATK
AIN-2.70-2.671.461.65
GaN-2.72-2.750.730.86
InN-3.02-2.980.971.21
GaAs-1.98-2.07-0.26
\n\n$$\nj_{\\alpha}=\\sigma_{\\alpha\\beta}\\mathcal{E}_{\\beta}+\\sigma_{\\alpha\\beta\\gamma}\\mathcal{E}_{\\beta}B_{\\gamma}+\\nu_{\\alpha\\beta}\\nabla_{\\beta}T,\n$$ \n\nwhere the indices label Cartesian directions and σαβ, σαβγ and $\\nu_{\\alpha\\beta}$ are the electronic conductivity, Hall conductivity, and thermoelectric response, respectively. Following [124], the band-dependent thermoelectric transport coefficients and Hall coefficients are obtained as \n\n$$\n\\begin{array}{r l}&{\\sigma_{\\alpha\\beta}(n\\mathbf{k})=e^{2}\\tau_{n\\mathbf{k}}\\mathbf{v}_{\\alpha}(n\\mathbf{k})\\mathbf{v}_{\\beta}(n\\mathbf{k}),}\\\\ &{\\sigma_{\\alpha\\beta\\gamma}(n\\mathbf{k})=e^{3}\\tau_{n\\mathbf{k}}^{2}\\epsilon_{\\gamma u v}\\mathbf{v}_{\\alpha}(n\\mathbf{k})\\mathbf{v}_{v}(n\\mathbf{k})\\mathbf{M}_{\\beta u}^{-1}(n\\mathbf{k}),}\\\\ &{\\nu_{\\alpha\\beta}(n\\mathbf{k})=(\\varepsilon_{n\\mathbf{k}}-\\mu)e/T\\tau_{n\\mathbf{k}}\\mathbf{v}_{\\alpha}(n\\mathbf{k})\\mathbf{v}_{\\beta}(n\\mathbf{k}),}\\end{array}\n$$ \n\nwhere $\\mu$ is the chemical potential and $\\epsilon_{\\gamma u v}$ the Levi–Civita symbol. The band group velocities $\\mathbf{v}(n\\mathbf{k})$ and effective mass tensors $\\mathbf{M}(n\\mathbf{k})$ are obtained from perturbation theory. Importantly, we may in (31) include the full scattering rate $\\tau_{n\\mathbf{k}}$ , and thereby go beyond the constant scattering-rate approx­ imation used in [124]. As we will see in section 14.2, this may not only be important in order to obtain quantitatively correct results; it is also required to reproduce experimental trends in the conductivity of different materials. \n\nThe scattering rate is given by \n\n$$\n\\frac{1}{\\tau_{n\\mathbf{k}}}=\\sum_{n^{\\prime}\\lambda\\mathbf{q}}\\left[B_{\\mathbf{k}(\\mathbf{k}+\\mathbf{q})}^{n n^{\\prime}}P_{\\mathbf{k}(\\mathbf{k}+\\mathbf{q})\\mathbf{q}}^{\\lambda n n^{\\prime}}+B_{\\mathbf{k}(\\mathbf{k}-\\mathbf{q})}^{n n^{\\prime}}\\bar{P}_{\\mathbf{k}(\\mathbf{k}-\\mathbf{q})\\mathbf{q}}^{\\lambda n n^{\\prime}}\\right],\n$$ \n\nwhere $B$ is a temperature-dependent scattering weight, \n\n$$\nB_{\\mathbf{k}\\mathbf{k}^{\\prime}}^{n n^{\\prime}}=\\frac{1-f_{n^{\\prime}\\mathbf{k}^{\\prime}}}{1-f_{n\\mathbf{k}}}\\left[1-\\cos(\\theta_{\\mathbf{k}\\mathbf{k}^{\\prime}})\\right],\n$$ \n\nwhere $f$ is the Fermi function, and the scattering angle is defined by \n\n$$\n\\cos(\\theta_{\\mathbf{k}\\mathbf{k}^{\\prime}})=\\frac{\\mathbf{v}(n^{\\prime}\\mathbf{k}^{\\prime})\\cdot\\mathbf{v}(n\\mathbf{k})}{|\\mathbf{v}(n^{\\prime}\\mathbf{k}^{\\prime})||\\mathbf{v}(n\\mathbf{k})|}.\n$$ \n\nFurthermore, $P({\\bar{P}})$ are transition rates due to phonon absorption (emission). They are obtained from Fermi’s golden rule, \n\n$$\n\\begin{array}{l}{{\\displaystyle P_{{\\bf k}{\\bf k}^{\\prime}{\\bf q}}^{\\lambda n n^{\\prime}}=\\frac{2\\pi}{\\hbar}|g_{{\\bf k}{\\bf k}^{\\prime}{\\bf q}}^{\\lambda n n^{\\prime}}|^{2}n_{\\lambda{\\bf q}}\\delta\\left(\\varepsilon_{n^{\\prime}{\\bf k}^{\\prime}}-\\varepsilon_{n{\\bf k}}-\\hbar\\omega_{\\lambda{\\bf q}}\\right),}}\\\\ {{\\displaystyle\\bar{P}_{{\\bf k}{\\bf k}^{\\prime}{\\bf q}}^{\\lambda n n^{\\prime}}=\\frac{2\\pi}{\\hbar}|g_{{\\bf k}{\\bf k}^{\\prime}-{\\bf q}}^{\\lambda n n^{\\prime}}|^{2}\\left(n_{\\lambda-{\\bf q}}+1\\right)\\delta\\left(\\varepsilon_{n^{\\prime}{\\bf k}^{\\prime}}-\\varepsilon_{n{\\bf k}}+\\hbar\\omega_{\\lambda-{\\bf q}}\\right),}}\\end{array}\n$$ \n\nwhere $n_{\\lambda\\mathbf{q}}$ is the phonon occupation operator, and $g_{\\mathbf{k}\\mathbf{k}^{\\prime}\\mathbf{q}}^{\\lambda n n^{\\prime}}$ the EPC constant from (29). \n\nQuantumATK offers two different methods for performing the $\\mathbf{q}$ -integral in (32). In the first method, the delta functions in (35) are represented by Gaussians with a certain width, and we perform the discrete sum over q. In the second method, we realize that the integral closely resembles the numerical problem of obtaining a density of states, and use the tetrahedron method [122] for the integration. In particular for metals, we find the tetrahedron method to be most efficient. Figure 8(c) shows the convergence of the Au resistivity as the number of $\\mathbf{q}$ -points increases, using both Gaussian and tetrahedron integration. The tetrahedron calculation seems conv­ erged for $N_{q}=20$ , that is, a $20\\times20\\times20~\\mathbf{q}$ -point sampling. The result with a finite Gaussian broadening may converge fast if using a rather large broadening, but the resistivity then appears to converge to a wrong result. In general, we therefore recommend the tetrahedron integration method for calculation of metallic resistivity. \n\nTo further improve the computational performance when calculating transport coefficients, it is possible to use the energy-dependent isotropic-scattering-rate approximation, introduced in [125]. A two-step procedure is used for the $\\mathbf{k}$ -point sampling, which significantly reduces simulation time without affecting the resulting mobilities for many materials (those that have a fairly isotropic scattering rate in momentum space). In step one, an initial $\\mathbf{k}$ -space with a low sampling density and a well-converged $\\mathbf{q}$ -point sampling are used. The initial $\\mathbf{k}$ -point grid is automatically reduced further by including only $\\mathbf{k}$ -points where the band structure has energies in a specific range around the Fermi level. This limits the simulations to the relevant range of initial states (and relevant carrier densities), which significantly increases simulation speed and reduces memory usage. Typically, the variation of the scattering rates from the different directions in momentum space will be small. Fom the obtained data, we may therefore generate an isotropic scattering rate that only depends on energy, \n\n$$\n\\frac{1}{\\tau(E)}=\\frac{1}{n(E)}\\sum_{n\\mathbf{k}}\\frac{1}{\\tau_{n\\mathbf{k}}}\\delta(E_{n\\mathbf{k}}-E),\n$$ \n\nwhere we have integrated over bands $n$ and wave vectors $\\mathbf{k}$ , and $n(E)$ is the density of states. In the second step, we then perform a calculation on a fine $\\mathbf{k}$ -point grid, but using the energydependent isotropic scattering rate $\\tau(E)$ . Since the scattering rate often varies slowly on the Fermi surface (for metals), this is a good approximation. The second step therefore requires only an evaluation of band velocities and effective masses on the dense $\\mathbf{k}$ -point grid, while the scattering rate is reused. This two-step procedure, combined with either direct integration for semiconductors and semimetals, or tetrahedron integration for metals, makes QuantumATK an efficient platform for simulating phonon-limited mobilities of materials. \n\nTable 9.  MAE (in units of meV) for various Fe-based $\\mathrm{L}1_{0}$ phases. Atomic structures and reference results (SIESTA and VASP) are from [129]. The QuantumATK selfconsistent and non-selfconsistent calculations were performed with a $17\\times\\times17\\times14\\mathbf{k}$ -point grid, while the band energies were sampled on a $40\\times40\\times34\\mathbf{k}$ -point grid. PseudoDojo pseudopotentials were used for both LCAO and PW calculations. The High basis set was used for LCAO. \n\n\n
SIESTAVASPQuantumATKQuantumATK
StructureLCAOPWLCAOPW
FeCo0.450.550.660.66
FeCu0.420.450.450.45
FePd0.200.130.120.15
FePt2.932.782.432.57
FeAu0.360.620.220.56
\n\nIn addition, it is possible to input a predefined scattering rate as a function of energy. This is relevant for adding extra scattering mechanisms, for example impurity scattering, on top of the electron–phonon scattering, or in the case where a scattering-rate expression is known analytically. One special case of the last situation is the limit of a constant relaxation time, which is the basis of the popular Boltztrap code [124]. We note that such constant-relaxation-time calculations are easily performed within the more general QuantumATK framework outlined above. Moreover, since electron velocities are calculated from perturbation theory, accuracy is not lost due to band crossings, which is the case when velocities are obtained from FD methods, as is done in [124]. In some cases, the constant relaxation time approximation can give a good first estimate of thermoelectric parameters for a rough screening of materials, but for quantitative predictions, the more accurate models of the relaxation time outlined above must be used. \n\n# 9.  Polarization and Berry phase \n\nElectronic polarization in materials has significant interest, for example in ferroelectrics, where the electric polarization $\\mathbf{P}$ can be controlled by application of an external electric field, or in piezoelectrics, where charge accumulates in response to an applied mechanical stress or strain [126]. \n\nIt is common to divide the polarization into ionic and electronic parts, $\\mathbf{P}=\\mathbf{P}_{\\mathrm{i}}+\\mathbf{P}_{\\mathrm{e}}$ . The ionic part can be treated as a classical electrostatic sum of point charges, \n\n$$\n\\mathbf{P}_{\\mathrm{i}}={\\frac{|e|}{\\Omega}}\\sum_{a}Z_{a}^{\\mathrm{ion}}\\mathbf{r}_{a},\n$$ \n\nwhere $Z_{a}^{\\mathrm{ion}}$ and $\\mathbf{r}_{a}$ are the valence charge and position vector of atom $a$ , $\\Omega$ is the unit-cell volume, and the sum runs over all ions in the unit cell. \n\nThe electronic contribution to the polarization in direction $\\alpha$ is obtained as [126] \n\n$$\n\\mathbf{P}_{\\mathrm{e},\\alpha}=-\\frac{|e|}{\\Omega}\\frac{\\Phi_{\\alpha}}{2\\pi}\\mathbf{R}_{\\alpha},\n$$ \n\nwhere $\\ensuremath{\\mathbf{R}}_{\\alpha}$ is the lattice vector in direction $\\alpha$ , and the Berry phase $\\Phi_{\\alpha}$ is obtained as \n\n$$\n\\Phi_{\\alpha}=\\frac{1}{N_{\\bot}}\\sum_{\\mathbf{k}_{\\bot}}\\phi_{\\alpha}(\\mathbf{k}_{\\bot}),\n$$ \n\nwhere the sum runs over $N_{\\bot}\\textbf{k}_{\\bot}$ -points in the BZ plane perpend­icular to $\\mathbf{R}_{\\alpha}.$ , and \n\n$$\n\\phi_{\\alpha}(\\mathbf{k}_{\\perp})=2\\operatorname{Im}\\left[\\ln\\prod_{j=0}^{J-1}\\operatorname*{det}S(\\mathbf{k}_{j},\\mathbf{k}_{j+1})\\right],\n$$ \n\nwith the overlap integrals \n\n$$\n\\begin{array}{r}{S_{n m}(\\mathbf{k}_{j},\\mathbf{k}_{j+1})=\\langle\\mathbf{u}_{\\mathbf{k}_{j}n}\\big\\vert\\mathbf{u}_{(\\mathbf{k}_{j+1})m}\\rangle,}\\end{array}\n$$ \n\nand with the $J\\textbf{k}$ -points given by $\\mathbf{k}_{j}=\\mathbf{k}_{\\perp}+\\mathbf{k}_{\\parallel,j}$ lying on a line along the ${\\mathbf{R}}_{\\alpha}$ direction. \n\nThe polarization depends on the coordinate system chosen since it is related to the real-space charge position, and is determined by the Berry phase, which is only defined modulo $2\\pi$ . Consequently, the polarization is a periodic function and constitutes a polarization lattice itself. The polarization lattice in direction $\\alpha$ is written as \n\n$$\n\\mathbf{P}_{\\alpha}^{(n)}=\\mathbf{P}+n\\mathbf{P}_{\\mathcal{Q},\\alpha},\n$$ \n\nwhere $n$ is an integer labeling a polarization branch, and the polarization quantum in direction α is PQ,α = |eΩ| Rα. All measurable quantities are related to changes in the polarization, which is a uniquely defined variable, provided that the different polarization values are calculated for the same branch in the polarization lattice. \n\nQuantumATK supports calculation of the polarization itself, as well as the derived quantities piezoelectric tensor, \n\n$$\n\\epsilon_{i\\alpha}=\\frac{\\partial{\\mathbf{P}_{\\alpha}}}{\\partial\\epsilon_{i}},\n$$ \n\nwhere Voigt notation is used for the strain component, that is, $i\\in(x x,y y,z z,y z,x z,x y)$ , and the Born effective charge tensor \n\n$$\nZ_{a,\\alpha\\beta}^{*}=\\frac{\\partial\\mathbf{P}_{\\alpha}}{\\partial\\mathbf{r}_{a,\\beta}},\n$$ \n\nwhere the derivative is with respect to the position of atom $a$ in direction $\\beta$ . \n\nTable 8 shows calculated values of the Born effective charges (only the negative components for each structure) and elements of the piezoelectric tensor for III–V wurtzite nitrides and zincblende GaAs. The calculated Born effective charges and piezoelectric tensor components agree well with the reference calculations. \n\n![](images/b3f0c1f8889bc17fbc72785d3391dad73139587e1e1dc81dd3c24d998cf2f7e8.jpg) \nFigure 9.  MAE for a $\\mathrm{Fe/MgO}$ interface, calculated using the QuantumATK implementation of the FT method. The total MAE is $1.59\\mathrm{\\meV},$ in close agreement with previous results obtained with VASP $(1.56\\mathrm{meV})$ [130]. The black circles show the atomprojected MAE for all the atoms, while the colored squares show the projection onto the Fe $d.$ -orbitals, which contribute the most to the total MAE. Positive energies correspond to perpendicular ( ) magnetization, while negative energies correspond to in-plane ( ) magnetization. \n\n# 10.  Magnetic anisotropy energy \n\nThe magnetic anisotropy energy (MAE) is an important quanti­ty in spintronic magnetic devices. The MAE is defined as the energy difference between two spin orientations, often referred to as in-plane $(\\parallel)$ and out-of-plane $(\\perp)$ with respect to a crystal plane of atoms, a surface, or an interface between two materials: \n\n$$\n\\mathrm{MAE}=E_{\\parallel}-E_{\\perp}.\n$$ \n\nThe MAE can be split into two contributions: a classical dipole-dipole interaction resulting in the so-called shape anisotropy, and a quantum mechanical contribution often refered to as the magnetocrystalline anisotropy, which arises as a consequence of spin–orbit coupling (SOC). In this section we will focus on the magnetocrystalline anisotropy and refer to this as the MAE. \n\nThere are at least three different ways of calculating the MAE: (i) Selfconsistent total-energy calculations including SOC with the noncollinear spins constrained in the in-plane and out-of-plane directions, respectively, (ii) using the force theorem (FT) to perform non-selfconsistent calculations (including SOC) of the band-energy difference induced by rotating the noncollinear spin from the in-plane to the outof-plane direction, and (iii) second-order perturbation theory (2PT) using constant values for the SOC. While it has been demonstrated that methods (i) and (ii) give very similar results [128, 129], the 2PT method can lead to significantly different results [129]. In QuantumATK we have implemented an easyto-use workflow implementing the FT method (ii). Using the FT gives the advantage over method (i) that the calculated MAE can be decomposed into contributions from individual atoms or orbitals, which may give valuable physical and chemical insight. \n\nThe QuantumATK workflow for calculating the MAE using the FT method is the following: \n\n1.\t\u0007Perform a selfconsistent spin-polarized calculation. \n2.\t\u0007For each of the considered spin orientations \n\n(a)\t \u0007Perform a non-selfconsistent calculation, in a noncollinear spin representation including SOC, using the effective potential and electron density from the polarized calculation but rotated to the specified spin direction. \n(b)\t \u0007Calculate the band energies $\\epsilon_{n}$ and projection weights wn,p . \n\n3.\t\u0007Calculate the total MAE as \n\n$$\n\\mathrm{MAE}=\\sum_{n}f_{n}^{\\parallel}\\epsilon_{n}^{\\parallel}-\\sum_{n}f_{n}^{\\perp}\\epsilon_{n}^{\\perp},\n$$ \n\nwhere $f_{n}^{\\parallel}$ is the occupation factor for band $n$ (including both band and $\\mathbf{k}$ -point index) for the $\\parallel$ spin orientation and $\\epsilon_{n}^{\\parallel}$ is the corresponding band energy, and likewise for the $\\perp$ spin orientation. \n\nThe contribution to the total MAE for a particular projection $p$ (atom or orbital projection) is \n\n$$\n\\mathrm{MAE}_{p}=\\sum_{n}f_{n}^{\\parallel}\\epsilon_{n}^{\\parallel}w_{n,p}^{\\parallel}-\\sum_{n}f_{n}^{\\perp}\\epsilon_{n}^{\\perp}w_{n,p}^{\\perp},\n$$ \n\nwhere the projection weight is \n\n$$\nw_{n,p}=\\langle\\psi_{n}|(\\mathbf{SP}+\\mathbf{PS})/2|\\psi_{n}\\rangle,\n$$ \n\nwith $\\left|\\psi_{n}\\right\\rangle$ being the eigenstate, $\\mathbf{s}$ the overlap matrix, and $\\mathbf{P}$ the projection matrix. $\\mathbf{P}$ is a diagonal, singular matrix with ones in the indices corresponding to the orbitals we wish to project onto and zeros elsewhere. \n\nTable 9 shows the calculated MAE for a number of Fe-based $\\mathbf{L}1_{0}$ alloys. Atomic structures as well as reference values calculated with SIESTA and VASP using the FT method are from [129]. We first note that the calculated MAEs agree rather well among the four codes, the only exception being FeAu, where the LCAO representations give somewhat smaller values than obtained with PW expansions. In this case it seems that the LCAO basis set has insufficient accuracy, which could be related to the fact that the LCAO basis functions are generated for a scalar-relativistic PP derived from a fully relativistic pseudopotential. \n\nFigure 9 shows the atom- and orbital-projected MAE for a $\\mathrm{Fe/MgO}$ interface. The structure is similar to the one reported in [130]. We use periodic BCs in the transverse directions. The calculated interfacial anisotropy constant $K_{1}=\\mathbf{MAE}/(2A)$ , where $A$ is the cross-sectional area, is $K_{1}=1.41~\\mathrm{\\mJ}~\\mathrm{m}^{-2}$ , in close agreement with a previous reported value [130] of $K_{1}=1.40\\mathrm{\\mJ\\m}^{-2}$ . From the atomprojected MAE (black circles) it is clear that the interface Fe atoms favor perpendicular MAE (since $\\mathbf{MAE}>0$ ), while the atoms in the center of the Fe slab contribute with much smaller values. From the orbital projections it is evident that the MAE peak at the interface is caused primarily by a transition from negative to positive MAE contributaions from the Fe $d_{x y}$ and $d_{x^{2}-y^{2}}$ orbitals, which hybridize with the nearby oxygen atom. \n\n![](images/33e2425e0ce42d968a090aa98039c93fff60a8a1f5a23ecc6d1b2e760ea160fa.jpg) \nFigure 10.  Illustration of the NEGF quantum transport module in QuantumATK. The left and right electrode regions (orange background) have an equilibrium electron distribution with chemical potentials $\\mu_{\\mathrm{L}}$ and $\\mu_{\\mathrm{R}}$ , related through the applied sample bias, $\\mu_{\\mathrm{R}}-\\mu_{\\mathrm{L}}=e V_{\\mathrm{bias}}$ . At $T=0\\mathrm{K}$ , the electrons with energies in the bias window, $\\mu_{\\mathrm{L}}\\leqslant\\varepsilon\\leqslant\\mu_{\\mathrm{R}}$ , give rise to a steady-state electrical current from the right to left electrode. Note that the electron transport direction is from the left to right electrode. For higher temperatures, the electrons above (below) $\\mu_{\\mathrm{L}}\\left(\\mu_{\\mathrm{L}}\\right)$ will also contribute to the current because of the corresponding broadening of the Fermi–Dirac distribution at $T>0\\mathrm{K}$ . The system is modelled selfconsistently at the DFT or TB level using the NEGF method. It is possible to include the effect of gate potentials in the selfconsistent solution. Inelastic effects due to phonon or photon scattering can be included through perturbation theory. \n\n# 11.  Quantum transport \n\nThe signature feature of QuantumATK is simulation of device systems. While most DFT device simulation codes are constructed on top of an electronic structure code designed for simulating bulk systems, QuantumATK is designed from scratch to achieve the highest accuracy and performance for both bulk and device systems. \n\nFigure 10 shows a device (two-probe) geometry. It consists of a left electrode, a central region, and a right electrode. The three regions have the same BCs in the two lateral directions perpendicular to the left-right electron transport direction, as defined in figure 10. The left and right electrodes are assumed to have bulk properties, and the first step of the device simulation is to perform a bulk calculation of each electrode with periodic BCs in the transport direction. Using Bloch’s theorem, we describe the wave functions in terms of transverse $\\mathbf{k}$ -points, and to seamlessly connect the three regions, the same $\\mathbf{k}$ -point sampling is used in the transverse directions for all three regions. In the transport direction, the central-region wave functions are described by using scattering BCs, while the electrode wave functions are described by using periodic BCs. To have a seamless connection, it is important that the electrode wave functions very accurately reproduce the infinite-crystal limit in the transport direction. A very dense electrode $\\mathbf{k}$ -point grid is therefore needed in the transport direction. \n\nThe left and right electrodes are modelled in their ground states with chemical potentials $\\mu_{\\mathrm{L}}$ and $\\mu_{\\mathrm{R}}$ , respectively. This is only a correct model if the electrodes are not affected by the contact with the central region. The central-region electrostatic potential should therefore be sufficiently screened in the regions interfacing with the electrodes (denoted ‘electrode extensions’), such that the potential in each electrode extension virtually coincides with that in the electrode. Furthermore, the approximation is not valid if the finite-bias current density is high; in this case a non-equilibrium electron occupation is needed to accurately model the electrodes. A device with no electron scattering in the central region can therefore not be modelled reliably at finite bias. \n\nThe electronic structures of the isolated electrodes are defined with respect to an arbitrary energy reference. When used in a device simulation, they must be properly aligned to a common reference. This is achieved by applying a potential shift to the electronic structure of the right electrode, chosen to fulfill the condition \n\n$$\n\\mu_{\\mathrm{L}}-\\mu_{\\mathrm{R}}=-e V_{\\mathrm{bias}},\n$$ \n\nwhere $V_{\\mathrm{bias}}$ is the bias applied on the electrodes. It is clear that $\\mu_{\\mathrm{R}}=\\mu_{\\mathrm{L}}$ at zero bias. The electrode electrostatic potentials, including the right-electrode potential shift, sets up the BCs for the central-region electrostatic potential. Thus, the whole system is aligned to a common reference, and device built-in potentials, if any, are properly included. \n\nThe electrostatic potential enters the KS equation  from which the electron density in the central region is determined. We assume the system is in a steady state, that is, the centralregion electron density does not change with time. The density can then be described in terms of extended electronic states from the left and right electrodes, as well as bound states in the central region, \n\n$$\nn(\\mathbf{r})=n_{\\mathrm{L}}(\\mathbf{r})+n_{\\mathrm{R}}(\\mathbf{r})+n_{\\mathrm{B}}(\\mathbf{r}).\n$$ \n\nWe now focus on the contribution from the extended states of the left $(n_{\\mathrm{L}})$ and right $(n_{\\mathrm{R}})$ electrodes, and delay the discussion of bound states $(n_{\\mathrm{B}})$ for later. The former may be obtained by calculating the scattering states incoming from the left $(\\psi_{\\alpha}^{\\mathrm{L}})$ and right $(\\psi_{\\alpha}^{\\mathbf{R}})$ electrodes, which can be obtained by first calculating the Bloch states in the electrodes, and subsequently solving the KS equation  for the central region using those Bloch states as matching BCs. \n\nThe left and right electron densities can then be calculated by summing up the occupied scattering states, \n\n$$\nn_{\\mathrm{L}}(\\mathbf{r})=\\sum_{\\alpha}|\\psi_{\\alpha}^{\\mathrm{L}}(\\mathbf{r})|^{2}f\\left({\\frac{\\varepsilon_{\\alpha}-\\mu_{\\mathrm{L}}}{k_{\\mathrm{B}}T_{\\mathrm{L}}}}\\right),\n$$ \n\n$$\nn_{\\mathrm{R}}(\\mathbf{r})=\\sum_{\\alpha}|\\psi_{\\alpha}^{\\mathrm{R}}(\\mathbf{r})|^{2}f\\left(\\frac{\\varepsilon_{\\alpha}-\\mu_{\\mathrm{R}}}{k_{\\mathrm{B}}T_{\\mathrm{R}}}\\right),\n$$ \n\nwhere $f(x)=(1+\\mathbf{e}^{x})^{-1}$ is the Fermi–Dirac distribution. \n\n# 11.1.  NEGF method \n\nInstead of using the scattering states to calculate the nonequilibrium electron density, QuantumATK uses the NEGF method; the two approaches are formally equivalent and give identical results [38]. \n\nThe electron density is given in terms of the electron density matrix. We split the density matrix into left and right contributions, \n\n$$\nD=D^{\\mathrm{L}}+D^{\\mathrm{R}}.\n$$ \n\nThe left contribution is calculated using the NEGF method as [38] \n\n$$\nD^{\\mathrm{L}}=\\int{\\rho^{\\mathrm{L}}(\\varepsilon)f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{L}}}{k_{\\mathrm{B}}T_{\\mathrm{L}}}\\right)\\mathrm{d}\\varepsilon},\n$$ \n\nwhere \n\n$$\n\\rho^{\\mathrm{L}}(\\varepsilon)\\equiv\\frac{1}{2\\pi}G(\\varepsilon)\\Gamma^{\\mathrm{L}}(\\varepsilon)G^{\\dagger}(\\varepsilon)\n$$ \n\nis the spectral density matrix, expressed in terms of the retarded Green’s function $G$ and the broadening function $\\Gamma^{\\mathrm{L}}$ of the left electrode, \n\n$$\n\\Gamma^{\\mathrm{L}}=\\frac{1}{\\mathrm{i}}(\\Sigma^{\\mathrm{L}}-(\\Sigma^{\\mathrm{L}})^{\\dagger}),\n$$ \n\nwhich is given by the left electrode self-energy $\\Sigma^{\\mathrm{L}}$ . Note that while there is a non-equilibrium electron distribution in the central region, the electron distribution in the left electrode is described by a Fermi–Dirac distribution $f$ with an electron temperature $T_{\\mathrm{L}}$ . \n\nSimilar equations exist for the right density matrix contrib­ ution. The next section describes the calculation of $G$ and $\\Sigma$ in more detail. \n\nWe note that the implemented NEGF method supports spintronic device simulations, using a noncollinear electronic spin representation, and possibly including spin–orbit coupling. This enables, for example, studies of spin-transfer torque driven device physics [131]. \n\n# 11.2.  Retarded Green’s function \n\nThe NEGF key quantity to calculate is the retarded Green’s function matrix for the central region. It is calculated from the central-region Hamiltonian matrix $H$ and overlap matrix $S$ by adding the electrode self-energies, \n\n$$\n\\begin{array}{r}{G(\\varepsilon)=\\left[(\\varepsilon+\\mathrm{i}\\delta_{+})S-H-\\Sigma^{\\mathrm{L}}(\\varepsilon)-\\Sigma^{\\mathrm{R}}(\\varepsilon)\\right]^{-1},}\\end{array}\n$$ \n\nwhere $\\delta_{+}$ is an infinitesimal positive number. \n\nCalculation of $G$ at a specific energy $\\varepsilon$ requires inversion of the central-region Hamiltonian matrix. The latter is stored in a sparse format, and we only need the density matrix for the same sparsity pattern. This is done by block diagonal inversion [132], which is $\\mathcal{O}(N)$ in the number of blocks along the diagonal. \n\nThe self-energies describe the effect of the electrode states on the electronic structure in the central region, and are calculated from the electrode Hamiltonians. QuantumATK provides a number of different methods [133–136], where our preferred algorithm use the recursion method of cite134, which in our implementation exploits the sparsity pattern of the electrode. This can greatly speed up the NEGF calculation as compared to using dense matrices. \n\n# 11.3.  Complex contour integration \n\nThe integral in (54) requires a dense set of energy points due to the rapid variation of the spectral density along the real axis. We therefore follow [38] and divide the integral into an equilibrium part, which can be integrated on a complex contour, and a non-equilibrium part, which needs to be integrated along the real axis, but only for energies within the bias window. We have \n\n$$\nD=D_{\\mathrm{eq}}^{\\mathrm{L}}+\\Delta_{\\mathrm{neq}}^{\\mathrm{R}},\n$$ \n\nwhere \n\n$$\nD_{\\mathrm{eq}}^{\\mathrm{L}}=\\int\\mathrm{d}\\varepsilon(\\rho^{\\mathrm{L}}(\\varepsilon)+\\rho^{\\mathrm{R}}(\\varepsilon)+\\rho^{\\mathrm{B}}(\\varepsilon))f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{L}}}{k_{\\mathrm{B}}T_{\\mathrm{L}}}\\right),\n$$ \n\n$$\n\\Delta_{\\mathrm{neq}}^{\\mathrm{R}}=\\int\\mathrm{d}\\varepsilon\\rho^{\\mathrm{R}}(\\varepsilon)\\left[f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{R}}}{k_{\\mathrm{B}}T_{\\mathrm{R}}}\\right)-f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{L}}}{k_{\\mathrm{B}}T_{\\mathrm{L}}}\\right)\\right],\n$$ \n\nwhere $\\rho^{\\mathbf{B}}$ is the density of states of any bound states in the central region. Equivalently, we could write the density matrix as \n\n$$\nD=D_{\\mathrm{eq}}^{\\mathrm{R}}+\\Delta_{\\mathrm{neq}}^{\\mathrm{L}},\n$$ \n\nwhere $\\mathrm{~L~}$ and $\\mathtt{R}$ are exchanged in (59) and (60). \n\nDue to the finite accuracy of the integration along the real axis, (58) and (61) are numerically different. We therefore use a double contour [38], where (58) and (61) are weighted such that the main fraction of the integral is obtained from the equilibrium parts, $D_{\\mathrm{eq}}^{\\mathrm{L}}$ and $D_{\\mathrm{eq}}^{\\mathrm{R}}$ , which are usually much more accurate than the non-equilibrium parts, due to the use of high-precision contour integration. We have \n\n$$\n\\begin{array}{r}{D_{i j}=W_{i j}^{\\mathrm{L}}\\left[D_{\\mathrm{eq}}^{\\mathrm{L}}+\\Delta_{\\mathrm{neq}}^{\\mathrm{R}}\\right]_{i j}+W_{i j}^{\\mathrm{R}}\\left[D_{\\mathrm{eq}}^{\\mathrm{R}}+\\Delta_{\\mathrm{neq}}^{\\mathrm{L}}\\right]_{i j},}\\end{array}\n$$ \n\nwhere $W^{\\mathrm{L}}$ and $W^{\\mathrm{R}}$ are chosen according to [38], i.e. such that at each site, the equilibrium part of the density matrix gives the largest contribution and $\\bar{W}^{\\mathrm{L}}+W^{\\mathrm{R}}=1$ . \n\n# 11.4.  Bound states \n\nThe non-equlibrium integrals, $\\Delta_{\\mathrm{neq}}^{\\mathrm{L}}$ and $\\Delta_{\\mathrm{neq}}^{\\mathrm{R}}$ , do not include any density from bound states in the central region. However, the equilibrium part of the density matrix is calculated from a complex contour integral of the retarded Green’s function, and this calculation includes bound states with energies below the chemical potential of the contour. \n\nAssume $\\mu_{\\mathrm{L}}<\\mu_{\\mathrm{R}}$ , then a bound state with energy $\\varepsilon_{\\mathrm{B}}<\\mu_{\\mathrm{L}}$ will be included in both $D_{\\mathrm{eq}}^{\\mathrm{L}}$ and $D_{\\mathrm{eq}}^{\\mathrm{R}}$ , but a bound state in the bias window, $\\mu_{\\mathrm{L}}<\\varepsilon_{\\mathrm{B}}<\\mu_{\\mathrm{R}}$ , will only be included in $D_{\\mathrm{eq}}^{\\mathrm{R}}$ . Thus, from (62) we see that the state will be included with weight 1 if $\\varepsilon_{\\mathrm{B}}<\\mu_{\\mathrm{L}}$ and only with a fractional weight if $\\mu_{\\mathrm{L}}<\\varepsilon_{\\mathrm{B}}<\\mu_{\\mathrm{R}}$ . The weight will depend on the position of the bound state along the transport direction, that is, if the bound state is in a region that is well connected with the right electrode, the occupation will follow the right electrode and thus be close to 1. If it is in a region that is not well connected with the right electrode, the occupation will follow the left electrode, and thus for the current example the occupation be close to 0. \n\nThe true occupation of a bound state in the bias window will depend on the physical mechanism responsible for the occupation and de-occupation, for example electron–phonon scattering, defects, etc. However, the matrix element will typically be higher with the electrode that is well connected with the region around the bound state, so we believe that the use of a double contour gives a qualitatively correct description of the occupation of the bound states in the bias window. Furthermore, we find that if we do not use such weighting schemes, bound states in the bias window can cause instabilities in the selfconsistent finite-bias NEGF calculation. \n\n# 1 .5.  Spill-in terms \n\nGiven the density matrix $D$ , the electron density is obtained from the LCAO basis functions $\\phi$ : \n\n$$\nn(\\mathbf{r})=\\sum_{i j}D_{i j}\\phi_{i}(\\mathbf{r})\\phi_{j}(\\mathbf{r}).\n$$ \n\nThe Green’s function of the central region gives the density matrix of the central region, $D^{\\mathrm{CC}}$ . However, to calculate the density correctly close to the central-region boundaries towards the electrodes, the terms involving $D^{\\mathrm{{\\bar{L}L}}},D^{\\mathrm{{LC}}},D^{\\mathrm{{CR}}},$ , and $D^{\\mathrm{RR}}$ are also needed. These are denoted spill-in terms [137]. \n\nQuantumATK implements an accurate scheme for including all the spill-in terms, both for the electron density and for the Hamiltonian integrals [137]. This gives additional stability and well-behaved convergence in device simulations. \n\n# 11.6.  Device total energy and forces \n\nA two-probe device is an open system where charge can flow in and out of the central region through the left and right electrode reservoirs. Since the two reservoirs may have different chemical potentials, and the particle number from a reservoir is not conserved, it is necessary to use a grand canonical potential to describe the energetics of the system [138], \n\n$$\n\\Omega[n]=E_{\\mathrm{KS}}[n]-N_{\\mathrm{L}}\\mu_{\\mathrm{L}}-N_{\\mathrm{R}}\\mu_{\\mathrm{R}},\n$$ \n\nwhere $N_{\\mathrm{L/R}}$ is the number of electrons contributed to the central region from the left/right electrode, and $E_{\\mathrm{KS}}[n]$ is the KS total energy. \n\nDue to the screening approximation, the central region will be charge neutral, and therefore $N_{\\mathrm{L}}+N_{\\mathrm{R}}=N$ , where $N$ is the ionic charge in the central region. At zero bias $(\\mu_{\\mathrm{L}}=\\mu_{\\mathrm{R}})$ , the particle term is constant, so that $N\\mu_{\\mathrm{L}}=N\\mu_{\\mathrm{R}}$ , and is thus independent of atom displacements in the central region. However, at finite bias ${\\bf\\chi}_{\\mu_{\\mathrm{L}}}\\neq{\\mu_{\\mathrm{R}}})$ , the particle terms in $\\Omega$ will affect the forces. \n\nIf one neglects current-induced forces [139, 140], as done in QuantumATK simulations, the force acting on atom $a$ at position $\\mathbf{r}_{a}$ in the device central region is given by \n\n$$\n\\mathbf{F}_{a}=-\\frac{\\partial\\Omega[n]}{\\partial\\mathbf{r}_{a}}.\n$$ \n\nIt can be shown that the calculation of this force is identical to the calculation of the equilibrium (zero-bias) force, but in the non-equilibrium (finite-bias) case the density and energy density matrix must be calculated within the NEGF framework [38, 138, 141]. \n\n# 11.7. Transmission coefficient and current \n\nWhen the selfconsistent non-equilibrium density matrix has been obtained, it is possible to calculate various transport properties of the system. One of the most notable is the transmission spectrum from which the current and differential conductance are obtained. The transmission coefficient $T$ at electron energy $\\varepsilon$ is obtained from the retarded Green’s function [142], \n\n$$\nT(\\varepsilon)=\\mathrm{Tr}\\left[G(\\varepsilon)\\Gamma^{\\mathrm{L}}(\\varepsilon)G^{\\dagger}(\\varepsilon)\\Gamma^{\\mathrm{R}}(\\varepsilon)\\right],\n$$ \n\nand the electrical current is given by the Landauer formula, \n\n$$\nI=\\frac{2e}{h}\\int_{-\\infty}^{\\infty}\\mathrm{d}\\varepsilon T(\\varepsilon)\\left[f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{L}}}{k_{\\mathrm{B}}T_{\\mathrm{L}}}\\right)-f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{R}}}{k_{\\mathrm{B}}T_{\\mathrm{R}}}\\right)\\right].\n$$ \n\n# 11.8.  Inelastic transmission and inelastic current \n\nQuantumATK implements the lowest-order expansion (LOE) method [143] for calculating the inelastic current due to electron–phonon scattering, which is not included in (66) \n\nand (67). The LOE method is based on perturbation theory in the first Born approximation, and requires calculation of the dynamical matrix and the Hamiltonian derivative with respect to atomic positions in the central region, $\\nabla H(\\mathbf{r})$ . Calculation of these derivatives are described in section 8. \n\nFirst-principles calculation of $\\nabla H(\\mathbf{r})$ can be prohibitive for large device systems. However, if the atomic configuration of the central region can be generated by repeating the left electrode along the transport direction, then $\\nabla H(\\mathbf{r})$ can be obtained to a good approximation by using the $\\nabla H(\\mathbf{r})$ of the left electrode only [144]. \n\nFrom $\\nabla H(\\mathbf{r})$ of the central region we get the electron– phonon matrix elements in reciprocal space [123], \n\n$$\n\\begin{array}{l}{{\\displaystyle M_{\\lambda,{\\bf k},{\\bf q}}^{i j}=\\sum_{m n}\\mathrm{e}^{\\mathrm{i}{\\bf k}\\cdot({\\bf R}_{n}-{\\bf R}_{m})-\\mathrm{i}{\\bf q}\\cdot{\\bf R}_{m}}}\\ ~}\\\\ {{\\displaystyle~\\times~\\langle\\phi_{j}{\\bf R}_{m}|{\\bf v}_{\\lambda,{\\bf q}}\\cdot\\nabla H_{0}({\\bf r})|\\phi_{i}~{\\bf R}_{n}\\rangle},}\\end{array}\n$$ \n\nwhere the $(m n)$ -sum runs over repeated unit cells in the supercell calculation of the Hamiltonian derivatives [123], and the subscript 0 indicates that the derivatives are only calculated for atoms in the unit cell with index 0. Moreover, $\\left|\\phi_{i}\\mathbf{R}_{n}\\right\\rangle$ $(|\\phi_{j}\\mathbf{R}_{m}\\rangle)$ denotes the $i(j)^{:}$ ’th LCAO basis orbital in the unit cell displaced from the reference cell by the lattice vector ${\\bf R}_{n}$ $(\\mathbf{R}_{m})$ , while $\\mathbf{q}$ is the phonon momentum, and $\\mathbf{v}_{\\lambda,\\mathbf{q}}$ is the massscaled mode vector of phonon mode λ with frequency ωλ,q. \n\nFollowing [143], we obtain the inelastic transmission functions for a finite transfer of momentum. From these we calculate the total electrical current, including inelastic effects [144, 145]. The complete formulas for the QuantumATK implementation can be found in [144]. \n\n11.8.1.  Special thermal displacement method.  In [146] we showed that the average transmission from a thermal distribution of configurations accurately describes the inelastic electron transmission spectrum due to electron–phonon scattering at this temperature. In the special thermal displacement (STD) method, the average is replaced with a single representative configuration, which may drastically reduce the computational cost of inelastic transport simulations [147]. \n\nTo obtain the STD configuration, we first calculate the phonon eigenspectrum using the dynamical matrix of the central region. We consider only $\\mathbf{q}=\\mathbf{0}$ , since only relative displacements between atoms in the cell will be important, and to account for finite $\\mathbf{q}$ -vectors we will have to increase the cell size. The phonon modes are labeled by $\\lambda$ with frequency $\\omega_{\\lambda}$ , eigenmode vector $\\mathbf{e}_{\\lambda}$ , and characteristic length $l_{\\lambda}$ . \n\nThe STD vector of atomic displacements is given by [147] \n\n$$\n{\\bf u}_{\\mathrm{STD}}(T)=\\sum_{\\lambda}s_{\\lambda}(-1)^{\\lambda-1}\\sigma_{\\lambda}(T){\\bf e}_{\\lambda},\n$$ \n\nwhere $s_{\\lambda}$ denotes the sign of the first non-zero element in $\\mathbf{e}_{\\lambda}$ , enforcing the same choice of ‘gauge’ for the modes. The Gaussian width $\\sigma$ is related to the mean square displacement $\\begin{array}{r}{\\langle\\mathbf{u}_{\\lambda}^{2}\\rangle=l_{\\lambda}^{2}(2n_{B}(\\frac{\\hbar\\omega_{\\lambda}}{k_{B}T})+1)=\\sigma_{\\lambda}^{2}(T)}\\end{array}$ at temperature $T$ , where $n_{\\mathrm{B}}$ is the Bose–Einstein distribution. \n\nAn essential feature of the STD method is the use of opposite phases for phonons with similar frequencies; in this way phonon-phonon correlation functions average to zero and the transmission spectrum of the STD configuration becomes similar to a thermal average of single phonon excitations. \n\nThe final step in the STD method is to calculate the selfconsistent Hamiltonian of the system displaced by uSTD, and use that to calculate the transmission spectrum. Thus, the computational cost of the inelastic transmission calculation is for the STD method similar to that of an ordinary elastic transmission calculation. \n\nFormally, this method becomes accurate for systems where the central region is a large unit cell generated by the repetition of a basic unit cell. \n\n# 11.9. Thermoelectric transport \n\nThe thermoelectric figure  of merit, ZT, quantifies how efficiently a temperature difference (heat) can be converted into a voltage difference in a thermoelectric material, \n\n$$\n\\mathrm{ZT}=\\frac{G\\mathrm{e}^{\\cal S^{2}T}}{\\kappa},\n$$ \n\nwhere $G_{\\mathrm{e}}$ is the electronic conductance, $S$ the Seebeck coefficient, $T$ the temperature, and $\\kappa=\\kappa_{\\mathrm{e}}+\\kappa_{\\mathrm{ph}}$ the summed electron and phonon heat transport coefficients. Following [148], and given a set of electron and phonon transmission spectra for a device configuration, QuantumATK uses linear-response theory to compute the above-mentioned thermoelectric coefficients and the Peltier coefficient, $\\Pi$ , \n\n$$\nG_{\\mathrm{e}}=\\left.\\frac{\\mathrm{d}I}{\\mathrm{d}V_{\\mathrm{bias}}}\\right|_{\\mathrm{d}T=0},\n$$ \n\n$$\nS=-\\left.\\frac{\\mathrm{d}V_{\\mathrm{bias}}}{\\mathrm{d}T}\\right|_{I=0},\n$$ \n\n$$\n\\kappa_{\\mathrm{e}}=\\left.\\frac{\\mathrm{d}I_{Q}}{\\mathrm{d}T}\\right|_{I=0},\n$$ \n\n$$\n\\Pi=\\left.\\frac{I_{Q}}{I}\\right|_{\\mathrm{d}T=0}=S V_{\\mathrm{bias}},\n$$ \n\nwhere $I_{Q}=\\mathrm{d}Q/\\mathrm{d}T$ is the electronic contribution to the heat current. It is calculated in a similar way as the electronic cur­ rent [149], \n\n$$\n\\begin{array}{l}{{\\displaystyle I_{Q}=\\frac{2e}{h}\\int_{-\\infty}^{\\infty}\\mathrm{d}\\varepsilon T(\\varepsilon)\\left[\\varepsilon-\\mu\\right]}}\\\\ {{\\displaystyle\\qquad\\times\\left[f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{L}}}{k_{\\mathrm{B}}T_{\\mathrm{L}}}\\right)-f\\left(\\frac{\\varepsilon-\\mu_{\\mathrm{R}}}{k_{\\mathrm{B}}T_{\\mathrm{R}}}\\right)\\right],}}\\end{array}\n$$ \n\nwhere $\\mu=(\\mu_{\\mathrm{L}}+\\mu_{\\mathrm{R}})/2$ is the average chemical potential, and the difference to (67) is the inclusion of the factor $(\\varepsilon-\\mu)$ in the integral. \n\nNote that one may use DFT or a TB model for obtaining the electron transmission and a force field to calculate the \n\n![](images/923ceeaa98f350f4c56a2d09b5f06c7536e8914bb281763da5513580f95dcde1.jpg) \nFigure 11.  Scaling performance of QuantumATK DFT simulations for a 64-atom ${\\mathrm{Si}}_{0.5}{\\mathrm{Ge}}_{0.5}$ random-alloy supercell when executed in parallel (using MPI) on 1, 2, 4, and 8 computing nodes (16 cores per node). (a) Total wall-clock times for LCAO and PW selfconsistent total-energy calculations, and b) the corresponding peak memory requirements per core. Grey lines indicate ideal scaling of the wallclock time. PseudoDojo PPs with LCAO-High basis sets were used. Note that the Ge PP contains semicore states. The supercell has 32 irreducible $\\mathbf{k}$ -points, corresponding to two computing nodes for full MPI parallelization over $\\mathbf{k}$ -points. With 4 (8) full nodes, 2 (4) MPI processes are assigned to eack $\\mathbf{k}$ -point. \n\n![](images/c6b3970192e15f3eb14d05f59f19fbeb81546c0a8840c13ac249ba38ae49952f.jpg) \nFigure 12.  Scaling performance of equilibrium DFT-NEGF simulations for a $10\\mathrm{nm}$ long silicon $p{-}n$ junction with doping levels of $5\\cdot10^{20}\\ \\mathrm{cm}^{-3}$ . The junction cross section is $1.3\\hat{3}\\ \\mathrm{nm}^{2}$ , corresponding to $684\\mathrm{Si}$ atoms in the device central region. The NEGF calculations were done using a PseudoDojo PP with the LCAO-Low basis set, and 2 irreducible $\\mathbf{k}$ -points in the centralregion 2D Brillouin zone, resulting in 96 generalized contour points. The simulations were run on up to eight 24-core Intel Xeon nodes, using both MPI (purple) and hybrid parallelization schemes. Hybrid parallelization was done using 2 (orange), 4 (green), and 24 (blue) threads per MPI process, with processes distributed evenly over the nodes. Gray dashed line indicates ideal scaling of the wallclock time. \n\nphonon transmission, constituting a computaionally efficient workflow for investigating thermoelectric materials. \n\n# 11.10.Photocurrent \n\nQuantumATK allows for calculating photocurrent using firstorder perturbation theory within the first Born approximation [150–152]. In brief, the electron-light interaction is added to the Hamiltonian, \n\n$$\n{\\hat{H}}={\\hat{H}}_{0}+{\\frac{e}{m_{0}}}\\mathbf{A}_{\\omega}\\cdot{\\hat{\\mathbf{p}}},\n$$ \n\nwhere $\\hat{H}_{0}$ is the Hamiltonian without the electron-light interaction, $e$ the electron charge, $m_{0}$ the free-electron mass, $\\hat{\\mathbf{p}}$ \n\nthe momentum operator, and $\\mathbf{A}_{\\omega}$ the electromagnetic vector potential from a single-mode monocromatic light source with frequency $\\omega$ . \n\nThe first-order coupling matrix is \n\n$$\nM_{i j}=\\frac{e}{m_{0}}\\langle i|\\mathbf{A}_{\\omega}\\cdot\\hat{\\mathbf{p}}|j\\rangle,\n$$ \n\nwhere $\\left|j\\right\\rangle$ is an LCAO basis function. \n\nThe first Born electron-photon self-energies are \n\n$$\n\\begin{array}{r}{\\pmb{\\Sigma}_{\\mathtt{p h}}^{\\mathtt{>}}=[N\\mathbf{M}^{\\dagger}\\mathbf{G}_{0}^{\\mathtt{>}}(\\varepsilon^{+})\\mathbf{M}+(N+1)\\mathbf{M}\\mathbf{G}_{0}^{\\mathtt{>}}(\\varepsilon^{-})\\mathbf{M}^{\\dagger}],}\\\\ {\\pmb{\\Sigma}_{\\mathtt{p h}}^{\\mathtt{<}}=[N\\mathbf{M}\\mathbf{G}_{0}^{\\mathtt{<}}(\\varepsilon^{-})\\mathbf{M}^{\\dagger}+(N+1)\\mathbf{M}^{\\dagger}\\mathbf{G}_{0}^{\\mathtt{>}}(\\varepsilon^{-})\\mathbf{M}],}\\end{array}\n$$ \n\n![](images/436d20589fb19a7204e1d1418e246b94f8f645650e8c9d4fcccc2026cfd001a4.jpg) \nFigure 13.  Scaling performance of ATK-ForceField simulations for a $\\mathrm{SiO}_{2}$ supercell containing one million atoms, using a force field from [154]. The simulation used one MPI process per CPU core for parallelization, and was run on up to six 16-core Intel Xeon nodes. Gray dashed line indicates ideal scaling of the wall-clock time. \n\nwhere $\\varepsilon^{\\pm}=\\varepsilon\\pm\\hbar\\omega$ , and $N$ is the number of photons. The Green’s function including electron-photon interactions to first order is then \n\n$$\n\\mathbf{G}^{>/<}=\\mathbf{G}_{0}^{r}\\left(\\pmb{\\Sigma}_{L}^{>/<}+\\pmb{\\Sigma}_{R}^{>/<}+\\pmb{\\Sigma}_{p h}^{>/<}\\right)\\mathbf{G}_{0}^{a},\n$$ \n\nwhere ${\\bf G}_{0}^{r,>,<}$ denote the non-interacting Green’s functions, and $\\pmb{\\Sigma}_{\\mathrm{L,R}}^{>/<}$ are the lesser and greater self-energies due to coupling to the electrodes. The current in electrode $\\alpha$ (left or right) with spin $\\sigma$ is calculated as \n\n$$\nI_{\\alpha,\\sigma}=\\frac{e}{\\hbar}\\int\\frac{\\mathrm{d}\\varepsilon}{2\\pi}\\sum_{k}T_{\\alpha}(\\varepsilon,k,\\sigma),\n$$ \n\nwhere the effective transmission coefficients are given by [152] \n\n$$\nT_{\\alpha}(\\varepsilon,k,\\sigma)=\\mathrm{Tr}\\left\\{\\mathrm{i}\\Gamma_{\\alpha}(\\varepsilon,k)[1-f_{\\alpha}]G^{<}+f_{\\alpha}G^{>}\\right\\}_{\\sigma\\sigma}.\n$$ \n\nWe note that it is possible to include also the effect of phonons through the STD method, which is important for a good description of photocurrent in indirect-band-gap materials such as silicon [153]. \n\n# 12.  QuantumATK parallelization \n\nAtomic-scale simulations for small configurations (systems with only a few atoms) may often be executed in serial on a single CPU core, but most production simulations require execution in parallel on several cores (often many) to increase computational speed and/or to reduce the per-core memory footprint. The QuantumATK platform offers several parallelization techniques depending on the type of computational task. \n\n# 12.1.  Bulk DFT and semi-empirical simulations \n\nFor bulk DFT-LCAO calculations, the basic unit of computational work to distribute in parallel is a single $\\mathbf{k}$ -point. \n\nQuantumATK uses the message passing interface (MPI) proto­col to distribute such work units as individual computing processes on individual, or small groups of, CPU cores, and also allows for assigning multiple processes to each work unit. Moreover, each MPI process may be further distributed in a hybrid parallelization scheme by employing shared-memory threading of each process. \n\nFigure 11 shows an example of how the total wall-clock time and peak memory requirement for DFT-LCAO and DFT-PW calculations scale with the number of 16-core computing nodes used with MPI parallelization. We considered a 64 atom SiGe random-alloy supercell with $N_{\\mathrm{k}}=32\\mathrm{\\bfk}$ -points. In this case, 2 full nodes, $N_{\\mathrm{n}}=2$ , with 32 cores in total ${N_{\\mathrm{c}}}={N_{\\mathrm{n}}}\\times16=32)$ , yields full MPI parallelization over k-points. The PW calculations were done using a blocked generalized Davidson algorithm [39, 155] to iteratively diagonalize the Hamiltonian matrix, which in the QuantumATK implementation parallelizes the computational work over both $\\mathbf{k}$ -points and plane waves. The LCAO calculations use the LAPACK [156] (when $N_{\\mathrm{c}}/N_{\\mathrm{k}}\\leqslant1)$ or ELPA [157] (when $N_{\\mathrm{c}}/N_{\\mathrm{k}}>1)$ libraries to distribute Hamiltonian diagonalization over MPI processes. It is clear from figure  11 that the LCAO engine is both fast and requires less memory than the PW representation for the 64 atom supercell, although communication overhead causes the LCAO computational speed to start breaking off from ideal scaling when the number of processes (cores) exceeds the number of $\\mathbf{k}$ -points in the DFT calculation (when $N_{\\mathrm{c}}/N_{\\mathrm{k}}>1\\AA,$ . On the contrary, MPI parallelization over both $\\mathbf{k}$ -points and plane waves enables approximately ideal scaling of the PW wall-clock time up to at least 8 nodes (128 cores), corresponding to $4~\\mathrm{MPI}$ processes per $\\mathbf{k}$ -point. \n\n# 12.2.  DFT-NEGF device simulations \n\nAs discussed in section 11.3, the NEGF equilibrium density matrix at a single $\\mathbf{k}$ -point is obtained from integrating the spectral density matrix over $M_{\\varepsilon}$ energy points on a complex contour. This integral must be performed at all transverse $\\mathbf{k}$ -points in the 2D Brillouin zone of the device central region, yielding $N_{k}\\times M_{\\varepsilon}$ generalized contour points. Each of these constitute a unit of computational work in equilibrium NEGF calculations, equivalent to $\\mathbf{k}$ -point parallelization in DFT calcul­ations for periodic bulks. \n\nSince we typically have $M_{\\varepsilon}=48$ contour energies, an equilibrium NEGF simulation may easily require evaluation of hundreds of generalized contour points. MPI parallelization over contour points is therefore a highly efficient strategy. For devices with relatively large transverse cross sections, and therefore relatively few contour points (because of small $N_{k})$ , assignment of several processes to each contour point enables scaling of NEGF computational speed to numbers of computing cores well beyond the number of contour points. This can also be combined with more than one thread per process in a hybrid parallelization scheme, for a smaller speedup, but with a reduced per-core memory footprint. \n\nFigure 12 shows an example of how the total wall-clock time and peak memory usage for a DFT-NEGF calculation scale with the number of computing nodes used with both MPI and hybrid parallelization schemes. Calculations for this $10\\mathrm{nm}$ long silicon $p$ -n junction require evaluation of 96 generalized contour points, in this case corresponding to 4 nodes for full MPI distribution of computational work. As expected, we find that using only MPI parallelization requires most memory per core, but also results in the smallest wall-clock time for the NEGF calculation, although communication overhead causes a deviation from ideal scaling for more than 1 node, see figure 12(a). We also note that the per-core memory consumption is in this case almost constant in figure 12(b), except for a modest decrease for 8 nodes, where 2 processes (cores) are assigned to each contour point. It is furthermore clear from figure 12 that hybrid parallelization enables significant memory reduction, although at the cost of decreased computational speed. Taking simulation on 4 nodes as an example, hybrid parallelization with 4 threads per process (green lines) requires in this case $50\\%$ more wall-clock time as compared to the MPI-only simulation (purple lines), but at a $70\\%$ smaller memory footprint. \n\nAlthough NEGF computational efficiency and memory consumption depend significantly on the device length and transverse dimensions, the general trend is that MPI parallelization over contour points yields computational speedup, while threading of processes reduce the NEGF memory footprint at a comparatively smaller computational speedup. \n\n# 12.3.  FF simulations \n\nThe ATK-ForceField engine uses shared-memory threading for parallelization of relatively small systems, while additional parallelization by domain decomposition over MPI processes is available for large systems. As explained in detail in [28], the MPI distribution of ATK-ForceField workload is implemented via functionality from the Tremolo-X MD package [158], which is developed by the Fraunhofer Institute for Algorithms and Scientific Calculations (SCAI). \n\nIn figure  13, we show the wall-clock time per MD step for a simulation of $\\mathrm{SiO}_{2}$ with 1 million atoms, using a force field from Pedone et al [154] This illustrates how the use of domain decomposition over MPI processes results in a significant speedup when parallelizing over a large number of nodes and cores. \n\n# 13.  NanoLab simulation environment \n\n# 13.1.  Python scripting \n\nThe QuantumATK software is programmed in the $^{C++}$ and Python languages. Around $80\\%$ of the code lines are in Python, and only low-level numerically demanding parts are written in $^{C++}$ . The use of Python allows for using a large number of high-level physics and mathematics libraries, and this has greatly helped building the rich functionality of QuantumATK in a relatively short time. \n\nThe user input file is a Python script and the user has through the script access to the same functionality as a \n\nQuantumATK developer. This enables the user to transform input files into advanced simulation scripts, which do not only set up advanced workflows and analysis, but may also alter the functionality of the simulation engines, for example by adding new total-energy terms. QuantumATK supplies a public application programming interface (API) with currently more than 350 classes and functions. These all take a number of arguments with detailed checks of the input parameters to ensure correct usage. For example, if the input argument is a physical quantity, the physical units must be supplied. A wide range of units are supported, e.g.for energy, the user may select units of joule, calorie, electron volt, kilojoule per mole, kilocalories per mole, Hartree, or Rydberg. All physical units are automatically converted to the internal units used by QuantumATK. The user also has access to internal quantities such as the Hamiltonian, Green’s function, self-energies, etc through the API. \n\nThrough Python scripting it is possible to build advanced workflows that automate complex simulations and analysis. However, some simulations may require a large number of time consuming calculation tasks that are combined into a final result, and scripting such workflows can be impractical. For instance, if the computer crashes during a loop in the script, how to restart the script at the right step in a loop in the middle of the script? Or perhaps some additional tasks are needed after a custom simulation has finished; how to combine the already calculated data with the new data? \n\nTo simplify such simulations, QuantumATK has introduced a framework called a study object. The study object keeps track of complex simulations that rely on execution and combination of a number of basic tasks. It allows for running the basic tasks in parallel and will be able to resume if the calcul­ation is terminated before completion. A study object also allows for subsequently extending the number of tasks, and will only perform tasks that have not already completed. This framework is currently used for a number of complex simulations, for instance for coupling atomic-scale simulations with continuum-level TCAD tools. Examples include simulation of the formation energy and diffusion paths of charged point defects, scans over source-drain and gate bias for two-terminal devices, relaxation of devices, and calcul­ ation of the dynamical matrix and Hamiltonian derivatives by finite differences. \n\nTo store data we use the cross-platform HDF5 binary format [159], which allows for writing and reading data in parallel to/from a single file. This file can also hold many different objects, so the entire output from a QuantumATK simulation can be stored efficently in a single file. \n\n# 13.2.  NanoLab graphical user interface \n\nWhile scripting is very efficient for production runs, it requires knowledge of the scripting language, and it takes time to manually build up scripts for setting up the configuration, simulation, and analysis of interest. The NanoLab GUI eliminates this barrier to productivity by enabling the user to fully set up the Python input script in a professional \n\n![](images/087b48d3bc3e90fa55245a80928ed58daf4487ac09e167c3f9b9496598d0f272.jpg) \nFigure 14.  Structure of the $\\mathrm{M_{D}/M o T e_{2}/S n S_{2}/M_{S}}$ device. Mo, Te, Sn and S atoms are shown in cyan, orange, dark green and yellow, respectively. The atoms of the $\\mathbf{M}_{\\mathrm{D}}$ (Au, Al) and $\\mathbf{M}_{\\mathrm{S}}$ (Au) regions are shown in pink and yellow, respectively. The metallic gate regions (top and bottom gates) are shown as light grey rectangles. The dielectric regions are shown as dark purple ( $\\epsilon=6$ ) or light purple ${\\bf\\epsilon}(\\epsilon=25\\$ ) rectangles. The dashed green lines highlight the boundaries of the different device regions indicated in figures 16(a) and (b). Note that the region of $40.2\\mathrm{nm}$ is the 2D device central region without the left and right electrode extensions included, as defined in section 11. A vertical black solid line highlights the boundary between that region and the left (right) electrode extension. The semi-infinite, periodic left (right) electrode is visualized with the corresponding unit cell structure of $\\mathrm{MoTe}_{2}$ $(\\mathrm{{SnS}}_{2})$ , which is highlighted with a dark grey-shaded rectangle adjacent to the left (right) electrode extension region. The Dirichlet BC is imposed on the left (right) boundary plane between the left (right) electrode and its extension. The top (bottom) horizontal black solid line highlights the top (bottom) boundary of the device simulation box. Mixed BCs are imposed on the corresponding boundary planes: Dirichet BCs on the metal gate surfaces, and Neumann BCs on the boundary planes in the vacuum regions (white rectangles). A periodic BC is applied in the lateral direction, which is perpendicular to the transport direction and the $\\mathbf{MoTe}_{2}$ $\\mathrm{\\overline{{SnS}}}_{2}$ ) sheet. \n\nGUI environ­ment. NanoLab is itself programmed in Python, and each tool in NanoLab can interpret and generate Python scripts, thus, it is possible to seamlessly shift from using the GUI tools in NanoLab to manually editing the Python scripts. It is the ambition that all NanoLab functions are also available as Python commands, such that any GUI workflow can be documented and reproduced in a Python script. \n\nNanoLab is developed around a plugin concept, which makes it easy to extend it and add new functionality. Plugins can be downloaded and installed from an add-on server, and the majority of the plugins are available as source code, making it easy to modify or extend them with new userdefined functionality. \n\nNanoLab also provides GUI tools for communicating with online databases (‘Databases’), setting up the atomic-scale geometry of configurations (‘Builder’), writing the Python script (‘Scripter’), submitting the script to a remote or local computing unit (‘Job Manager’), and visualizing and analyzing the results (‘Viewer’). It is possible to connect thirdparty simulation cods with NanoLab by writing plugins that translate the input/output files into the internal NanoLab format. Such plugins are currently available for the VASP [22], Quantum ESPRESSO [23], ORCA [160], GPAW [161], and CASTEP [162] codes. \n\nThe plugin concept also allows for many specialized functions, for example specialized Builder tools like surface builders, interface builders [163], NEB setups [106], etc. The Job Manager has plugins that provide support for a wide range of job schedulers on remote computing clusters. Moreover, NanoLab has a large selection of graphical analysis tools, which can be used to visualize and analyze simulations with respect to a wide range of properties, all implemented as plugins. For instance, with the ‘MD analyser’ plugin, a MD trajectory can be analyzed with respect to angular and radial distribution functions, or different spatial and time correlation functions. Other examples are interactive band structure analysis with extraction of effective masses, and analysis of transmission in device simulations with on-the-fly inspection of transmission eigenstates at specified points in the transmission spectrum. NanoLab currently ships with more than 100 preinstalled plugins, and additional plugins are available through the add-on server. \n\n![](images/76c38b7b2e492220f6704d54718019f2427f0e039c8097f3a58568ef69ef440d.jpg) \nFigure 15.  (a) and (c) $I_{\\mathrm{DS}^{-}}V_{\\mathrm{GS}}$ transconductance curves calculated for the symmetrically gated $\\mathrm{Au/MoTe_{2}/S n S_{2}/A u}$ device at drainsource biases of $-0.2\\mathrm{V}$ (purple circles, solid line) and $-0.4\\mathrm{V}$ (purple circles, dashed line), and for the asymmetrically gated Al/ $\\mathrm{MoTe}_{2}/\\mathrm{SnS}_{2}/\\mathrm{Au}$ device at drain-source biases of $-0.2\\mathrm{V}$ (green squares circles, solid line) and $-0.4\\mathrm{V}$ (green circles, dashed line). \n\n# 13.3.  Documentation \n\nKeeping an updated documentation system for the large set of QuantumATK classes and functions pose a challenge. To synchronize the documentation with the source code, we have developed an automated documentation system where the information for the QuantumATK reference manual is extracted directly from the Python source code using the Sphinx documentation generator [164]. The reference manual is available from an online platform [165] together with tutorials, whitepapers, webinars, etc. Through a search engine it is thus easy to find all available information for a given problem. \n\n![](images/8892b455169cf84f5fb16d22960a83b3815bb74a1830e76a53872a06080c5289.jpg) \nFigure 16.  (a) Cut-planes of the Hartree difference potential, $\\Delta V^{\\mathrm{H}}$ , along the transport direction of the symmetrically contacted $\\mathrm{Au/MoTe}_{2}/$ $\\mathrm{SnS}_{2}/\\mathrm{Au}$ device. The potential is plotted in the range $-0.2\\ \\mathrm{eV}\\leqslant\\Delta V^{\\mathrm{H}}\\leqslant0.2\\ \\mathrm{eV}.$ , with equipotential lines shown at every $0.025\\mathrm{meV}.$ Regions of negative, zero, and positive potential are shown in blue, white, and red, respectively. The capital letters indicate the sections of the device corresponding to the drain (D) and source (S) electrodes, the overlap region (O), and the exposed region (E). (c) and (e) Projected local density of states along the transport direction for the SC device at $V_{\\mathrm{DS}}=-0.2\\:\\mathrm{V}$ and $V_{\\mathrm{GS}}=0.0~\\mathrm{V}$ (c) and at $V_{\\mathrm{GS}}=0.6\\:\\mathrm{V}$ (e). The red solid lines indicate the position of the left $(\\mu_{\\mathrm{D}})$ and right $(\\mu\\mathrm{{s})}$ chemical potentials. The green dashed lines mark the boundaries of the different device regions. (b),(d) and (f) Same as (a),(c) and (e), but for the asymmetrically contacted $\\mathrm{Al/MoTe_{2}/S n S_{2}/A u}$ device. \n\n# 14.  QuantumATK applications \n\n# 14.1.  Large-scale simulations of 2D field-effect transistors \n\nAs already described in section 11, the combination of DFTLCAO with the NEGF method makes it possible to use QuantumATK to simulate the electronic structure and electrical characteristics of devices at the atomistic level. Fieldeffect transistor (FET) device configurations [166, 167] are simulated by including dielectric regions and electrostatic gates, see section 4.5. \n\nHere, we show how this framework can be used to study the electrical characteristics of a tunnel FET (TFET) device, where the channel is formed by a heterojunction based on two-dimensional semiconductors [168, 169]. We demonstrate how the characteristics of the device can be tuned by using an asymmetric contact scheme. The latter is similar to that proposed for graphene-based photodetectors [170], where two different metals are used to contact the graphene channel. \n\nFigure 14 shows the 2D-TFET device considered here. The device comprises a semiconducting channel formed by a $\\mathrm{MoTe}_{2}/\\mathrm{SnS}_{2}$ heterojunction [171]. We consider two different contact schemes by including atomistic metallic contacts: In the symmetrically contacted (SC) $\\mathrm{M_{D}/M o T e_{2}/S n S_{2}/M_{S}}$ device, Au is used for both the source $(\\mathbf{M}_{\\mathrm{S}})$ and drain $\\mathbf{\\Gamma}(\\mathbf{M}_{\\mathrm{D}})$ metallic contacts, whereas in the asymmetrically contacted (ASC) device, we set $\\mathbf{M}_{\\mathrm{D}}=\\mathbf{A}\\mathbf{l}$ and $\\mathbf{M}_{\\mathrm{S}}=\\mathbf{A}\\mathbf{u}$ , in order to have a rather large work function difference $(\\Delta\\Phi)$ between $\\mathbf{M}_{\\mathrm{D}}$ and $\\mathbf{M}_{\\mathrm{S}}$ [172]. In both devices, the metallic contacts to $\\mathbf{MoTe}_{2}$ and $\\mathrm{SnS}_{2}$ are represented by $\\langle110\\rangle$ -oriented 4-layer slabs. \n\nThe device configurations were constructed from the optim­ized structures of the $\\mathrm{Au}(110)/\\mathrm{MoTe}_{2}$ and $\\mathrm{Au}(110)/\\mathrm{SnS}_{2}$ electrodes, and the interlayer distance in the overlap region was set to $3.1\\mathrm{~\\AA~}$ . Following [171], the devices were encapsulated in a high- $\\cdot\\kappa$ dielectric region $\\mathrm{(HfO}_{2}$ , $\\kappa=25.0\\AA$ ), and a thin low- $\\boldsymbol{\\kappa}$ dielectric region (h-BN, $\\kappa=6.0$ ) was placed above the ‘exposed’ $\\mathbf{MoTe}_{2}$ region that is not contacted or forms part of the overlap region, hereafter denoted $\\mathrm{E}(\\mathrm{MoTe}_{2})$ . Electrostatic top and bottom gates were defined outside the high- $\\boldsymbol{\\kappa}$ di­electric region, covering the overlap and half of the $\\mathrm{E}(\\mathrm{MoTe}_{2})$ and $\\mathrm{E}(\\mathrm{{SnS}}_{2})$ regions. The ASC device was constructed by replacing the Au atoms in the left electrode with Al atoms, with no further structural optimization3. Additional computational details are given in appendix. \n\n![](images/3a61587de0619bd164461ef5496ef91482d73a7169761622a1429e0eca0b1504.jpg) \nFigure 17.  Temperature-dependent phonon-limited resistivity of the three metals Au, $\\mathrm{Ag}$ and $\\mathrm{Cu}$ evaluated from first-principles simulations using the ATK-LCAO engine. \n\nTo study the impact of the contact asymmetry on the device characteristics, the reverse-bias $I_{\\mathrm{DS}^{-}}V_{\\mathrm{GS}}$ curves (the transconductance) were simulated for both devices and for two values of the drain-source voltage, $V_{\\mathrm{DS}}=-0.2\\mathrm{~V~}$ and $V_{\\mathrm{DS}}=-0.4~\\mathrm{V},$ by grounding the top gate and by sweeping the bottom gate. The same physical picture emerges for both values of $V_{\\mathrm{DS}}$ , and we discuss here only the results obtained for $V_{\\mathrm{DS}}=-0.4~\\mathrm{V}.$ The $I_{\\mathrm{DS}}-V_{\\mathrm{GS}}$ curves in figure  15 show that the drain-source current is higher in the SC device than in the ASC device across the entire range of gate-source volt­ ages. However, in the SC device, $I_{\\mathrm{DS}}$ increases only by a factor of ${\\sim}10$ , from $I_{\\mathrm{DS}}(V_{\\mathrm{GS}}=0.05~\\mathrm{V})=4.28\\times10^{-8}~\\mathrm{A}~\\mathrm{cm}^{-1}$ to $I_{\\mathrm{DS}}(V_{\\mathrm{GS}}=0.6~\\mathrm{V})=1.29\\times10^{-6}~\\mathrm{A}~\\mathrm{cm}^{-1}$ . Conversely, in the ASC device, $I_{\\mathrm{DS}}$ increases by about six orders of magnitude in the same $V_{\\mathrm{GS}}$ range, from $I_{\\mathrm{DS}}(V_{\\mathrm{GS}}=0.05~\\mathrm{V})=4.09\\times$ $10^{-15}\\ \\mathrm{A\\cm^{-1}}$ to $I_{\\mathrm{DS}}(V_{\\mathrm{GS}}=0.6~\\mathrm{V})=1.74\\times10^{-9}~\\mathrm{A}~\\mathrm{cm}^{-1}$ . \n\nUnderstanding these trends requires considering that the asymmetric contact scheme has a two-fold effect on the electronic structure of the device. On the one hand, the use of two metals with different work functions leads to an additional built-in electric field in the channel region, when the chemical potentials of the drain and source electrodes, $\\mu_{\\mathrm{D}}$ and $\\mu_{\\mathrm{{S}}}$ , are aligned on a common energy scale. On the other hand, the interaction between the metallic contact and $\\mathbf{MoTe}_{2}$ is expected to depend also on the chemical nature of the metal. \n\nThe presence of an additional built-in electric field, and its effect on the device electrostatics, are evident by comparing the Hartree difference potential $(\\Delta V^{\\mathrm{H}})$ in the two devices at $V_{\\mathrm{GS}}=0~\\mathrm{V}$ along the channel, as shown in figures 16(a) and (b). While in the SC device the potential changes smoothly along the channel region, a sudden increase in the potential is observed in the ASC device around the $\\mathrm{E}\\left(\\mathrm{MoTe}_{2}\\right)$ region. Here, the potential lines run parallel to the transport direction, indicating the presence of a left-pointing local electric field. The sign of this field is consistent with that generated by an asymmetric contact scheme with $\\Phi^{M_{\\mathrm{S}}}>\\Phi^{M_{\\mathrm{D}}}$ , that is, the same as that of the ASC device. \n\nTable 10.  First-principles phonon-limited resistivities at $300\\mathrm{K}$ (in units of $\\mathbf{n}\\Omega\\cdot\\mathbf{m}^{\\cdot}$ ), compared with experimental values from [173]. Au nanowire results from [146]. \n\n\n
DFTExperiment
Au, Bulk15.920.5
Au, NW (d ≈ 1 nm)56.0
Ag,Bulk4.914.7
Ag, NW (d ≈ 1 nm)28.7
Cu, Bulk14.215.4
Cu, NW (d ≈ 1 nm)98.3
\n\nThe projected local density of states (PLDOS) along the devices reveal that the different electrostatics also affect their electronic structure. For both contact schemes, the DOS within the bias window, $[\\mu_{\\mathrm{D}}-\\mu_{\\mathrm{S}}]\\pm k_{\\mathrm{B}}T=\\Delta\\mu\\pm k_{\\mathrm{B}}T$ , is strongly inhomogeneous along the channel, as the conduction bands (CBs) of $\\mathbf{MoTe}_{2}$ and $\\mathrm{SnS}_{2}$ are pinned to $\\mu_{\\mathrm{D}}$ and $\\mu_{\\mathrm{{S}}}$ , respectively (see figures 16(c) and (d)). This results in a vanishing DOS in the $\\mathrm{E}(\\mathrm{MoTe}_{2})$ region within the bias window. Here, the DOS is even smaller in the ASC device, due to (i) the weaker pinning of the CBs to $\\mu_{\\mathrm{D}}$ , and (ii) the effect of the local electric field, which bends and depletes even more the CBs, moving them further away from the bias window. In the SC device, the field is much weaker, and the CBs are bent only in the proximity of the overlap region. \n\nThe transconductance behavior can be understood from the combined analysis of $\\Delta V^{\\mathrm{H}}$ and of the PLDOS. The DOS within $\\Delta\\mu\\pm k_{\\mathrm{{B}}}T$ in the $\\mathrm{E}(\\mathrm{MoTe}_{2})$ region, described in terms of an effective barrier $\\phi_{\\mathrm{MoTe}_{2}}$ , ultimately determines the reverse-bias current in the channel. In the SC device, $\\phi_{\\mathrm{MoTe}_{2}}$ is lower for the case $V_{\\mathrm{GS}}=0\\:\\mathrm{V},$ and depends only weakly on $V_{\\mathrm{GS}},$ , as shown in figure 16(e). This results in a higher absolute value of $I_{\\mathrm{DS}}$ , and in a lower variation of $I_{\\mathrm{DS}}$ with $V_{\\mathrm{GS}}$ . Conversely, in the ASC device, $\\phi_{\\mathrm{MoTe_{2}}}$ is higher at comparable values of $V_{\\mathrm{GS}}$ , and varies appreciably when $V_{\\mathrm{GS}}$ is increased, see figure 16(f). This explains the lower values of the drainsource current, and its higher variation with the gate-source voltage. These trends are consistent with those of the transconductance curves shown in figure 15. \n\nIn summary, DFT-NEGF simulations for $\\mathbf{M}_{\\mathrm{D}}/\\mathbf{M}\\mathrm{oTe}_{2}/$ $\\mathrm{SnS}_{2}/\\mathrm{M}_{\\mathrm{S}}$ ultra-scaled 2D-TFET devices show that the transconductance can be engineered by an appropriate choice of the metallic electrodes, and highlight the importance of atomistic device simulations for optimization of the electrical characteristics of devices based on non-conventional semiconductors. \n\n# 14.2.  Phonon-limited mobility of metals \n\nThe continued downscaling of nanoelectronics makes the metal interconnects an increasingly critical part of transistor designs [174]. Present-day transistors use $\\mathrm{Cu}$ as an interconnect material, and a good understanding of the origin of resistance increase with downscaling of interconnects will be important for the design and performance of future nanoscale devices. \n\nWe here present first-principles calculations of the phononlimited resistivity of three FCC metals; Cu, Ag, and Au. We solve the Boltzmann transport equation for the mobility, using first-principles EPC constants, as described in section  8.5. Such DFT calculation of the resistivity of metals is computationally demanding, as one needs to integrate the EPC over both electron and phonon wave vectors $\\mathbf{k}-\\mathbf{\\lambda}$ and $\\mathbf{q}$ -space), and we know of only few studies of the EPC in metals that includes a full integration [146, 175, 176]. We here show that the tetrahedron integration method enables computationally efficient mobility calculations. The method may therefore be used for computational screening of materials, and first-principles simulations become accessible for identifying promising replacement materials for future interconnects. \n\nTo calculate the scattering rate related to EPC, the phonon modes and derivatives of the Hamiltonian with displacements are needed. The supercell method for calculation of phonons and EPC from first principles was described in section 8, and figure  7 showed the phonon band structures of Cu, Ag and Au, calculated using the ATK-LCAO simulation engine. For the integration of the scattering rate in (32) we use a sampling of $20\\times20\\times20\\textbf{q}$ -points and tetrahedron integration. In addition, we apply the two-step procedure, where a k-space isotropic but energy-dependent scattering rate is used to efficiently evaluate the resistivity. \n\nFigure 17 shows the DFT results for the temperaturedependent phonon-limited resistivity of bulk Cu, Ag, and Au (Debye temperatures of 347, 227 and $162\\mathrm{~K~}$ [177], respectively). The resistivity increases with temperature as the phonon occupation increases, and becomes linearly dependent on temperature above the Debye temperature. \n\nTable 10 presents the calculated room-temperature bulk resistivities, and compares them to experiments and to calculated values for metal nanowires (NWs) with diameters $d=1{\\mathrm{nm}}$ . In agreement with experiments, we find that Au has the largest resistivity, and that Ag is more conductive than Cu. In addition, the resistivity increases significantly when forming nanowires of the elements. Despite the fact that the phonon dispersions of bulk Au and $\\mathrm{Ag}$ are very similar, the resistivity is quite different. In the minimal free-electron model of metals, the conductivity is given by $\\begin{array}{r}{1/\\rho(T)=\\frac{1}{3}e^{2}v_{\\mathrm{F}}^{2}\\tau(T)n(\\varepsilon_{\\mathrm{F}})}\\end{array}$ . In the three FCC metals considered here, the Fermi velocity, $v_{\\mathrm{F}},$ , and the DOS, $n(\\varepsilon_{\\mathrm{F}}).$ , (and resulting carrier density) are almost identical, and the difference in the resistivity is traced back to the variation in the scattering rate. This shows how full firstprinciples Boltzmann transport simulations of the scattering rate is needed to capture the origin of the resistivities of different metals. While the resistivity of bulk $\\operatorname{Ag}$ is slightly underestimated by the simulations, we find good agreement with experiments for bulk Au and Cu, as well as the correct ranking of the individual metals. This illustrates the predictive power of the method. In general, we find that the resistivity of $d=1{\\mathrm{nm}}$ nanowires is increased by a factor of three for Au and even more for $\\mathrm{Ag}$ and $\\mathrm{{Cu}}$ , as compared to bulk, due to the increased EPC in nanowires. \n\n![](images/4020fc808db89432da9ee37d9e470f475e6cf5d30990cb37fbe843bd355fb716.jpg) \nFigure 18.  Average position of the ${\\mathrm{Li}^{+}}$ ions in $\\mathrm{LiFePO_{4}}$ along the $y$ Cartesian direction (along the [0 1 0] channel), as a function of time, calculated at temperatures $300\\mathrm{K}$ (a) and $1000\\mathrm{K}$ (b), and for electric field strengths from $D_{y}=0.0$ (purple lines) to $D_{y}=0.3$ (red lines) VA˚. The data obtained from multi-model and FF simulations are shown as solid and dashed lines, respectively. (c) and (d) Snapshots obtained from the simulations after $40\\mathrm{ps}$ of simulation for $\\bar{3}00\\mathrm{K}$ (c) and $1000\\mathrm{K}$ (d). The lithium and iron ions are shown in pink and orange, respectively, while the magenta tetrahedra represent the phosphate groups. The black arrow indicates the direction of the applied field. \n\n![](images/9543990520f970312510e3513242eada916469e41d64f9a6d57c7a7377cb5304.jpg) \nFigure 19.  Conduction band energies ( $\\cdot\\ E_{\\mathrm{X}}$ and $E_{\\mathrm{L}}$ ) of ${\\mathrm{Si}}_{1-x}{\\mathrm{Ge}}_{x}$ alloy as a function of Ge content, $x.$ , calculated using PPS-PBE and HSE06 functionals in combination with the LCAO basis set and the PW basis set, respectively. The $E_{\\mathrm{X}}$ and $E_{\\mathrm{L}}$ energies are defined with respect to the top of the valence band $(E_{\\mathrm{val}})$ at the $\\Gamma$ -point. Details on the definition of band energies at special $\\mathbf{k}$ -points for disordered alloys can be found elsewhere [186]. Reference experimental data (open markers) on the band-gap compositional dependence, $E_{\\mathrm{gap}}(x).$ , are given for low $(4.2\\mathrm{K})$ and room (296 K) temperatures [187] The dashed (solid) lines correspond to linear (quadratic) interpolation of the DFT-calculated band energies, $E_{\\mathrm{L}}$ $(E_{\\mathrm{X}})$ , given with filled markers; the interpolation formulas are given in table 11. \n\n# 14.3.  Multi-model dynamics with an applied electric field \n\nThe tight integration of different atomic-scale simulation engines within the same software framework allows for straight-forward combination of multiple atomistic models into one single simulation workflow. This enables elaborate computational workflows and extend the functionality of QuantumATK beyond that of methods based on a single atomistic model. We here show how such a multi-model approach can be used to implement a hybrid method that combines classical FF MD simulations with a DFT description of timedependent fluctuations of the atomic charges as the MD simulation progresses. \n\nTable 11.  First-principles interpolation formulas for the ${\\mathrm{Si}}_{1-x}{\\mathrm{Ge}}_{x}$ composition-dependent band gap and lattice constant. The variables $b_{\\mathrm{w}},\\bar{b}_{\\mathrm{w}}^{\\prime}.$ and $b_{\\mathrm{w}}^{\\prime\\prime}$ are bowing parameters. \n\n\n
Band gap interpolation formula (eV)
PPS-PBEEx =1.116-0.764x+bwx2 bw = 0.526 eV EL= 2.104-1.425x
HSE06Ex =1.204 -0.444x +bx2 b\"=0.228 eV EL=2.032-1.267x
Lattice constant interpolation formula (A)
PPS-PBEa(x)= 5.431+0.257x+bwx2 bw=0.034A
\n\nWe study here ${\\mathrm{LiFePO}}_{4}$ , a promising cathode material of the olivine family for Li-ion batteries [141, 178]. In this class of materials, the olivine scaffold provides natural diffusion channels for the ${\\mathrm{Li}^{+}}$ ions, which have been shown to diffuse via a hopping mechanism, preferentially through [0 1 0]-oriented channels [179, 180]. MD simulations aimed at understanding the diffusion process have focused mainly on its temperature $(T)$ dependence. In this case, relatively high temperatures, usually in the range $500{-}2000\\mathrm{K}$ , are required to reach a sufficiently high hopping probability within a reasonable MD simulation time, and allow for calculation of the associated diffusion constants. These simulations have demonstrated that the diffusion increases with T, as a natural consequence of the increased hopping probability favored by Brownian motion. \n\nHowever, in an electrochemical cell under operating conditions, the motion of the ${\\mathrm{Li}^{+}}$ ions may also have a non-negligible drift component, due to the displacement field resulting from the voltage difference applied between the anode and the cathode. This potentially rather important effect is rarely taken into account in atomistic simulations [181, 182]. \n\nAnother significant issue in the simulation of Li-ion batteries is related to the inclusion of electronic effects. In order to reach reasonably long simulation times, to describe atom diffusion at temperatures close to $300\\mathrm{~K~}$ , most low- $\\mathbf{\\nabla}\\cdot\\boldsymbol{T}_{} $ MD simulations are based on FFs, which by construction neglect any time-dependent fluctuations of the electronic density during the MD run. A number of models have tried to address this issue by either including approximate models to account for the charge fluctuation [183], or by running semi-classical dynamics on precalculated potential-energy surfaces based on DFT [184]. \n\nA QuantumATK multi-model approach can be used to address these issues by including first-principles charge fluctuations in the FF MD. The applied displacement field should add a force term $\\mathbf{F}_{a}^{\\prime}=Q_{a}\\mathbf{D}$ on the ath ion with formal charge $Q_{a}$ and $\\mathbf{D}$ being the field vector. However, in a FF, $Q_{a}$ is a timeindependent parameter, so the field-induced force will also be time-independent. In a multi-model approach, we instead use DFT simulations to determine the instantaneous charge $Q_{a}$ at regular intervals during the MD. Time-dependency in the field-induced force term is then included by use of a MD hook function (see section  7.4) by defining the time-dependent formal charge $Q_{a}^{\\prime}(t)$ as \n\n![](images/19e4bf9bea0fc500b8c8c2d3de2cbb49c18a2e82fe3591a94ec5eb246aa5445b.jpg) \nFigure 20.  Band structure of bulk Si (left panel) and Ge (right panel) obtained using the PPS-PBE (solid line) and HSE06 (dashed line) methods. The calculations used a $\\Gamma$ -centered $12\\times12\\times12{\\bf{k}}$ -point grid to sample the Brillouin zone of the 2 atom primitive cells. \n\n$$\n\\begin{array}{r}{Q_{a}^{\\prime}=\\mathrm{Q}_{a}^{\\mathrm{FF}}+\\Delta Q_{a}(t),}\\end{array}\n$$ \n\nwhere $\\Delta Q_{a}$ describes the time-dependent fluctuation. In principle, $\\Delta Q_{a}$ can be defined arbitrarily, provided that charge neutrality is maintained in the system. In the present case, we chose a simple definition, \n\n$$\n\\Delta Q_{a}(t)=\\mathrm{Q}_{a}^{\\mathrm{DFT}}(t)-\\mathrm{Q}_{a}^{\\mathrm{DFT,ref}},\n$$ \n\nwhere $Q_{a}^{\\mathrm{DFT}}(t)$ and $\\mathrm{Q}_{a}^{\\mathrm{DFT,ref}}$ are the time-dependent charge of the ith atom obtained from a DFT calculation for the MD configuration at time $t$ , and a time-independent charge obtained for a reference configuration at $T=0\\mathrm{K}$ , respectively. We note that, in the present case, the lack of consistency between the methods used to calculate $\\mathrm{Q}_{a}^{\\mathrm{FF}}$ and $\\Delta Q_{a}(t)$ does not constitute an issue, since the charge fluctuations during the dynamics are of the order $\\Delta Q_{a}\\sim0.1~e^{-}$ . \n\nWe have applied this multi-model approach to investigate the interplay between Brownian and drift components of the diffusion of ${\\mathrm{Li}^{+}}$ ions along the [0 1 0] channels in $\\mathrm{LiFePO_{4}}$ in the presence of an applied displacement field. The system was described by a $1\\times2\\times1~\\mathrm{LiFePO_{4}}~112$ atom supercell, that is, 2 times the conventional unit cell (16 formula units). For the classical part of the multi-model simulations, we used a FF potential by Pedone et al [154], which has been shown to describe qualitatively correctly the geometry and transport properties of olivine materials [185]. The ATK-LCAO engine was used for the DFT part. MD simulations were performed at temperatures $300~\\mathrm{K}$ and $1000\\mathrm{~K~}$ for a displacement field $\\mathbf{D}=[0,D_{y},0]$ , with $0.0\\mathrm{~V~}\\mathring{\\mathrm{A}}^{-1}\\leqslant D_{y}\\leqslant0.3\\mathrm{~V~}\\mathring{\\mathrm{A}}^{-1}.$ . For each temperature, a 5 ps equilibration run using a NPT ensemble was performed, starting from the structure optimized at $0\\mathrm{\\:K}$ , using a Maxwell–Boltzmann distribution of initial velocities, followed by a 45 ps production run using a NVT ensemble. The MD time step was 1.0 fs, and $\\Delta Q_{a}(t)$ was recalculated every $100~\\mathrm{{MD}}$ steps, see (84), with $Q_{a}^{\\mathrm{DFT}}(t)$ and $\\mathrm{Q}_{a}^{\\mathrm{DFT}}$ ,ref obtained from Mulliken population analysis. Further computational details are given in appendix. \n\nFigures 18(a) and (c) shows the average displacement $\\langle{y_{\\mathrm{Li^{+}}}}\\rangle$ of the ${\\mathrm{Li}^{+}}$ ions along the $y$ Cartesian direction, that is, along the [0 1 0] channels of the $\\mathrm{FePO_{4}}$ scaffold, calculated for temper­atures 300 and $1000\\mathrm{~K~}$ and for increasingly higher values of the applied field, using either FFs only or the $\\mathrm{FF+DFT}$ multi-model approach. In the absence of an applied field and at $300\\mathrm{~K~}$ , the average $\\mathrm{Li^{+}}$ -ion displacement remains constant at $\\langle y_{\\mathrm{Li^{+}}}\\rangle=4.67\\pm0.11\\stackrel{\\circ}{\\mathrm{A}}$ during the entire simulation, indicating the absence of hopping events. At $1000\\mathrm{K}$ , the situation is rather similar, as $\\left\\langle{y_{\\mathrm{Li}_{\\mathrm{\\Omega}}^{+}}}\\right\\rangle$ increases only slightly from an initial value of $7.12\\pm0.19\\check{\\mathrm{~A~}}$ (obtained from an average of the snapshots collected during the first picosecond of the FF-only MD) to a final value of $9.16\\pm0.{\\overset{\\cdot}{1}}3{\\overset{\\circ}{\\mathrm{A}}}$ (obtained from an average of the snapshots collected during the last picosecond). For the multi-model simulation, we observe instead a small decrease of $\\left\\langle y_{\\mathrm{Li^{+}}}\\right\\rangle$ over time. This indicates that, at both temperatures, ${\\mathrm{Li}^{+}}$ hopping due to Brownian motion is a rare event. \n\nApplying an increasingly stronger displacement field leads to a progressive increase in the ${\\mathrm{Li}^{+}}$ hopping probability. At $300~\\mathrm{K}$ , the average $\\mathrm{Li^{+}}$ -ion displacement increases steadily from the beginning of the MD run for $D_{y}\\geqslant0.20\\mathrm{~V~mathring{A}}^{-1}$ , indicating that, for these values of $D_{y}$ , ${\\mathrm{Li}^{+}}$ hopping is primarily due to field-induced drift. The ${\\mathrm{Li}}^{+}$ ions accelerate until they reach a constant velocity, as shown by the tendency of the $\\langle{y_{\\mathrm{Li^{+}}}}\\rangle$ versus time curves to continually decrease their slope, corresponding to a straight line on a linear plot. \n\nIn the absence of an applied field, increasing the temper­ ature should increase the probability of $\\mathrm{Li^{+}}$ ion diffusion due to increased Brownian motion [180, 185]. However, in the present case we find that the $\\mathrm{Li^{+}}$ ions move less at $1000\\mathrm{~K~}$ than at $300\\mathrm{K}$ . For comparable values of $D_{y}$ , the $\\left\\langle{y_{\\mathrm{Li^{+}}}}\\right\\rangle$ versus time curve has a smaller slope at $1000\\mathrm{K}$ than those calculated at $300~\\mathrm{K}$ . The reason is that collision events of the ${\\mathrm{Li}^{+}}$ ions with the $\\mathrm{LiFePO_{4}}$ lattice, where phonons are considerably more excited at higher temperatures than at room temperature, limits the effective velocity of the ${\\mathrm{Li}}^{+}$ ions. \n\nThis is evident by comparing the ${\\mathrm{LiFePO}}_{4}$ structures at the two temperatures. Figures 18(c) and (d) shows two snapshots extracted at the end of the MD runs at $D_{y}=0.3\\mathrm{V}\\mathring{\\mathrm{~A}}^{-1}$ and at temperatures 300 and $1000~\\mathrm{K}$ , respectively. At $300~\\mathrm{K}$ , the $\\mathrm{LiFePO_{4}}$ structure is relatively unperturbed. Consequently, the ${\\mathrm{Li}^{+}}$ ions are able to travel through the [0 1 0] channels with relatively few scattering events with the ${\\mathrm{LiFePO}}_{4}$ lattice. Conversely, at $1000\\mathrm{K}$ , the ${\\mathrm{LiFePO}}_{4}$ structure is significantlty perturbed, leading to a high probability of collisions between the $\\mathrm{Li^{+}}$ ions and the olivine lattice. \n\nIn summary, we have studied the diffusion of ${\\mathrm{Li}^{+}}$ in olivine $\\mathrm{LiFePO_{4}}$ , using a multi-model computational approach that combines a classical FF with DFT, the latter to include the effect of the field and of time-dependent charge fluctuations. Our analysis highlights the importance of considering the combined effect of both Brownian and drift contributions to the ${\\mathrm{Li}^{+}}$ hopping to describe the overall process, which strongly depends on not only the temperature itself, but also on the probability of collision events between the diffusing ions and the ${\\mathrm{FePO}}_{4}$ lattice. \n\n# 14.4.  Electronic structure of binary alloys \n\nUnderstanding the physical properties of semiconductor alloys, such as silicon-germanium binary compounds, is highly relevant, since such alloys are commonly used in microelectronics as a semiconductor material for, e.g. heterojunction bipolar transistors or as a strained semiconductor layer in CMOS transistors [188]. Moreover, device-level TCAD simulations, frequently used in industrial semiconductor research and development, usually require material-dependent input parameters such as band gap, effective masses, deformation potentials, and many others [189]. Atomic-scale simulations may be used to calculate such parameters from first principles if experimental values are not available, including composition dependence [186]. However, simulating randomly dis­ ordered alloys may be computationally challenging since the traditional approach to random-alloy (RA) simulations use stastical sampling of multiple large supercells with random atomic arrangements (configurational averaging) to take into account the effect of disorder on the physical properties of alloys. \n\nWe here adopt the special quasi-random structure (SQS) approach [190] for DFT modelling of SiGe random alloys, which significantly reduces the computational cost. Unlike in the RA approach, in the SQS method the configurational averaging of band energies is captured by a single supercell structure. We study 64 atom ${\\mathrm{Si}}_{1-x}{\\mathrm{Ge}}_{x}$ supercells in the full range of compositions, $0\\leqslant x\\leqslant1$ , by calculating composition-dependent lattice constants and band energies. The PPS-PBE method [19], discussed in section  4.4, was used with the ATK-LCAO simulation engine, and we compare the band energies to those obtained with the HSE06 hybrid functional using the ATK-PlaneWave engine. We also compare \n\nSQS band energies to those calculated using the traditional RA approach, obtained by averaging over 5 randomly generated RA configurations. In both the SQS and RA cases, the band energies were computed by averaging the energies of the conduction (valence) band states split by alloy disorder [186]. \n\nWe used a NanoLab SQS module to generate the SQS configurations. The module uses a genetic algorithm to optim­ize finite-size alloy configurations to reproduce selected correlation functions of the infinite alloy system. The genetic optim­ ization algorithm is very efficient, and systems with many hundred atoms are easily handled. In this case, the SQS structures were generated by fitting all pair, triplet, and quadruplet correlation functions with figure sizes up to 7.0, 5.0 and $4.0\\mathring\\mathrm{A}$ , respectively, such as to match those correlation functions for the truly random alloy, as detailed in [190, 191]. Generation of a single 64 atom SiGe SQS alloy takes about $4\\mathrm{{min}}$ on a modern 4-core processor. The alloy configurations were then relaxed using PPS-PBE followed by band structure analysis. HSE06-level band structures were calculated without further relaxation. More computational details are given in appendix. Figure 19 shows the $\\mathrm{Si}_{1-x}\\mathrm{Ge}_{x}$ composition dependent conduction band minima (CBM), referenced to the valence band maximum, for both the $X\\mathrm{-}$ and $L$ -valley in the SiGe BZ. We first note that SQS band energies are very similar to the those calculated using the more expensive RA approach. It is well known that the $\\mathrm{Si}_{1-x}\\mathrm{Ge}_{x}$ fundamental band gap changes character at $x\\sim0.85$ . The PPS-PBE and HSE06 predictions of the transition point are $x\\sim0.88$ and 0.82, respectively. As expected, the calculated $X$ -valley conduction-band energies exhibit bowing, i.e. nonlinear behavior of these quantities with respect to Ge content, $x.$ The best-fit interpolation formulas, shown as lines in figure 19, are listed in table 11, including the band-gap compositional bowing parameters. The PPS-PBE band gaps are in good agreement with room-temperature experiments (within ${\\sim}50\\mathrm{meV}$ for the entire range of Ge content), while the HSE06 band gaps are in better agreement with low-temperature experiments. Moreover, the HSE06-based approach appears to more accurately describe the band-gap bowing parameter, while PPS-PBE tends to overestimate it. Finally, the calculated SiGe lattice constant also exhibits compositional bowing, as indicated by the interpolation formula in table 11. The bowing parameter of $0.034\\overset{\\circ}{\\mathrm{A}}$ is overestimated by $\\sim26\\%$ as compared to experiments $(0.027\\mathring\\mathbf{A})$ ). \nTo benchmark the empirical PPS-PBE method against the \n\nparameter-free HSE06 approach, we also calculated the band structure of bulk Si and Ge using both methods, as shown in figure 20. The PPS-PBE conduction and valence bands around the Fermi energy are in good agreement with the HSE06 band structure. This is consistent with the fact that the PPS-PBE method was fitted to experimental data, and that the HSE06 hybrid functional accurately simulates the band structure of bulk semiconductors. \n\nIn summary, we find that the SQS approach is well suited to describe the compositional bowing of the band energies in $\\mathrm{Si}_{1-x}\\mathrm{Ge}_{x}$ random alloys, suggesting that SQS provides an accurate and efficient approach to random-alloy simulations. The HSE06 hybrid functional accurately describes the conduction-band energies of SiGe alloys and their compositional bowing, while the PPS-PBE method offers a computationally efficient alternative if only bands around the Fermi level are important. \n\n# 15.  Summary \n\nIn this paper we have presented the QuantumATK platform and details of its atomic-scale simulation engines, which are ATK-LCAO, ATK-PlaneWave, ATK-SE, and ATK-ForceField. We have compared the accuracy and performance of the different engines, and illustrated the application range of each. The platform includes a wide range of modules for application of the different simulation engines in solid-state and device physics, including electron transport, phonon scattering, photocurrent, phonon-limited mobility, optical properties, static polarizations, molecular dynamics, etc \n\nThe simulation engines are complimentary and through the seamless Python integration in the QuantumATK platform, it is easy to shift between different levels of theory or integrate different engines into complex computational workflows. This has been illustrated in several application examples, where we for example showed how ATK-LCAO and ATK-ForceField can be combined to study $\\mathrm{Li^{+}}$ -ion drift in a battery cathode material. We also presented applications of QuantumATK for simulating electron transport in 2D materials, phonon-limited resistivity of metals, and electronic-structure simulations of SiGe random alloys. \n\nWhile several of the simulation engines and methods have been described independently before [19, 24, 28, 106, 123, 132, 137, 147, 153, 163], we have here provided an overview of the entire platform, including implementation details not previously published. We expect that this paper can become a general reference for documenting the QuantumATK platform, and is a reference to its applications for atomic-scale modelling in semiconductor physics, catalysis, polymer mat­ erials, battery materials, and other fields. \n\n$0\\mathrm{K}$ to avoid extremely small bond distances. The MD simulations were then performed at $300\\mathrm{K}$ using a random Boltzmann distribution of initial velocities and a Langevin thermostat. The FF simulations used a Pedone potential [154], while the TB simulations used a Slater–Koster parametrization. For the DFT-LCAO and DFT-PW simulations, we used normconserving PseudoDojo pseudopotentials with a Medium basis set and a kinetic-energy cutoff energy of $1360\\mathrm{eV}$ $\\mathrm{50\\Ha)}$ , respectively. For TB, DFT-LCAO, and DFT-PW simulations, the Brillouin zone was sampled using a Monkhorst–Pack [192] (MP) $\\mathbf{k}$ -point density of $3{-}4\\mathring{\\mathrm{A}}$ . For systems with sizes between 240 and 960 atoms, 2 processes/k-point was used, whereas for the 1920 atom system, 16 processes/k-point was used. \n\nFor the DFT-NEGF device simulations presented in section  14.1, we used the PBE density functional with SG15- Medium (FHI-DZP) combinations of pseudopotentials and basis sets for $\\mathbf{MoTe}_{2}$ and $\\mathrm{SnS}_{2}$ (Au and Al). The real-space cutoff energy was 2721 eV $(100\\mathrm{Ha})$ , and $\\mathbf{MPk}$ -point grids of $12\\times1\\times100$ and $12\\times1$ were used to sample the BZ of the electrode and of the device, respectively. \n\nIn the study of multi-model dynamics presented in section 14.3, we used the ATK-LCAO engine with a DZP basis set and a real-space cutoff energy of $2180\\mathrm{eV}$ ( $\\mathrm{80\\Ha)}$ . Exchangecorrelation effects were described by the PBE functional, and the $\\mathrm{FePO_{4}B Z}$ was sampled using a $3\\times3\\times2\\mathrm{MP}\\mathbf{k}$ -point grid. \n\nFor the electronic-structure calculations for SiGe random alloys presented in section  14.4, we used a $3\\times3\\times3$ MP $\\mathbf{k}$ -point grid and an electron temperature of $0.025\\mathrm{eV}$ for the Fermi–Dirac occupation function. SG15 (FHI) pseudopotentials were used for the PSS-PBE (HSE06) simulations. The LCAO mesh density cutoff was 2721 eV ( $\\mathrm{100~Ha)}$ , and the PW kinetic-energy cutoff was $544\\mathrm{eV}$ $20\\ \\mathrm{Ha})$ . The LCAO simulations used Medium (High) bais sets for silicon (germanium). Relaxation of unit-cell volume and ion positions was done using the PPS-PBE method with total energy, forces and stress converged to $10^{-5}\\mathrm{eV},0.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ , and $0.05\\mathrm{GPa}$ , respectively. \n\n# Acknowledgments \n\nAuthors acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreements No. 713481 (SPICE), No. 766726 (COSMICS), and No. 723867 (EMMC-CSA), as well as funding from the Quantum Innovation Center (QUBIZ) and the Lundbeck Foundation (R95-A10510). CNG is sponsored by the Danish National Research Foundation (DNRF103). \n\n# Appendix.  Computational details \n\nIn the simulations presented in figure 1, we have considered noncrystalline $\\mathrm{a-Al}_{2}\\mathrm{O}_{3}$ structures with a constant density of $2.81\\mathrm{g}\\ \\mathrm{cm}^{-3}$ . The system sizes considered were formed by 5, 30, 60, 120, 240, 480, 960, 1920, 3840, 7680, 15360, and 30720 atoms, respectively, each system with the appropriate unit-cell volume. The amorphous phases were generated by randomizing the structure at $5000~\\mathrm{K}$ and then quenching to \n\n# ORCID iDs \n\nSøren Smidstrup $\\textcircled{6}$ https://orcid.org/0000-0002-1766-9662 \nJess Wellendorff $\\textcircled{1}$ https://orcid.org/0000-0001-5799-1683 \nUlrik G Vej-Hansen $\\circledcirc$ https://orcid.org/0000-0002-1114-9930 \nFabiano Corsetti $\\circledcirc$ https://orcid.org/0000-0002-2275-436X \nUmberto Martinez $\\textcircled{1}$ https://orcid.org/0000-0001-6842-4609 \nAnders Blom $\\textcircled{6}$ https://orcid.org/0000-0002-4251-5585 \n\n# References \n\n[1] Shankar S, Simka H and Haverty M 2008 J. Phys.: Condens. Matter 20 064232 \n[2] Zographos N, Zechner C, Martin-Bragado I, Lee K and Oh Y S 2017 Mater. Sci. Semicond. Process. 62 49 \n[3] Shi S, Gao J, Liu Y, Zhao Y, Wu Q, Ju W, Ouyang C and Xiao R 2015 Chin. Phys. B 25 018212 \n[4] Nørskov J K, Bligaard T, Hvolbæk B, Abild-Pedersen F, Chorkendorff I and Christensen C H 2008 Chem. Soc. Rev. 37 2163 \n[5] Islam M S 2010 Phil. Trans. R. Soc. A 368 3255 \n[6] Saal J E, Kirklin S, Aykol M, Meredig B and Wolverton C 2013 JOM 65 1501 \n[7] Trau M and Battersby B J 2001 Adv. Mater. 13 975 \n[8] Goldbeck G 2012 The economic impact of molecular modelling of chemicals and materials (https:// materialsmodelling.com/2012/07/10/) \n[9] Nakai Y, Honda K, Yanagi K, Kataura H, Kato T, Yamamoto T and Maniwa Y 2014 Appl. Phys. Express 7 025103 \n[10] Xiao Z, Ma C, Huang J, Liang L, Lu W, Hong K, Sumpter B G, Li A P and Bernholc J 2019 Adv. Theory Simul. 2 1800172 \n[11] Greeley J, Jaramillo T F, Bonde J, Chorkendorff I and Nørskov J K 2006 Nat. Mater. 5 909 \n[12] Armiento R, Kozinsky B, Fornari M and Ceder G 2011 Phys. Rev. B 84 014103 \n[13] Bartlett R J and Musiał M 2007 Rev. Mod. Phys. 79 291 \n[14] Hohenberg P and Kohn W 1964 Phy. Rev. 136 B864 \n[15] Kohn W and Sham L J 1965 Phys. Rev. 140 A1133 \n[16] Parr R G and Yang W 1994 Density-Functional Theory of Atoms and Molecules (Int. Series of Monographs on Chemistry) (Oxford: Oxford University Press) \n[17] Kohn W, Becke A D and Parr R G 1996 J. Phys. Chem. 100 12974 \n[18] Vogl P, Hjalmarson H P and Dow J D 1983 J. Phys. Chem. Solids 44 365 \n[19] Smidstrup S, Stradi D, Wellendorff J, Khomyakov P A, Vej-Hansen U G, Lee M E, Ghosh T, Jónsson E, Jónsson H and Stokbro K 2017 Phys. Rev. B 96 195309 \n[20] Soler J M, Artacho E, Gale J D, García A, Junquera J, Ordejón P and Sánchez-Portal D 2002 J. Phys.: Condens. Matter 14 2745 \n[21] Ozaki T 2003 Phys. Rev. B 67 155108 \n[22] Kresse G and Hafner J 1993 Phys. Rev. B 47 558 \n[23] Giannozzi P et al 2009 J. Phys.: Condens. Matter 21 395502 \n[24] Stokbro K, Petersen D E, Smidstrup S, Blom A, Ipsen M and Kaasbjerg K 2010 Phys. Rev. B 82 075420 \n[25] Aradi B, Hourahine B and Frauenheim T 2007 J. Phys. Chem. A 111 5678 \n[26] Klimeck G, Oyafuso F, Boykin T B, Bowen R C and von Allmen P 2002 Comput. Model. Eng. Sci. 3 601 \n[27] Klimeck G and Luisier M 2010 Comp. Sci. Eng. 12 28 \n[28] Schneider J, Hamaekers J, Chill S T, Smidstrup S, Bulin J, Thesen R, Blom A and Stokbro K 2017 Modelling Simul. Mater. Sci. Eng. 25 85007 \n[29] Sandia National Laboratories 2019 LAMMPS Molecular Dynamics Simulator (http://lammps.sandia.gov) \n[30] Gale J and Rohl A 2003 Mol. Simul. 29 291 \n[31] Thirunavukkarasu V et al 2017 Superlattices Microstruct. 111 649 \n[32] Dong Z, Cao X, Wu T and Guo J 2018 J. Appl. Phys. 123 094501 \n[33] Crovetto A, Palsgaard M L N, Gunst T, Markussen T, Stokbro K, Brandbyge M and Hansen O 2017 Appl. Phys. Lett. 110 083903 \n[34] Sankaran K, Swerts J, Couet S, Stokbro K and Pourtois G 2016 Phys. Rev. B 94 094424 \n[35] Gunst T, Kaasbjerg K and Brandbyge M 2017 Phys. Rev. Lett. 118 046601 \n[36] Caridad J M, Calogero G, Pedrinazzi P, Santos J E, Impellizzeri A, Gunst T, Booth T J, Sordan R, Bøggild P and Brandbyge M 2018 Nano Lett. 18 4675 \n[37] Palsgaard M, Gunst T, Markussen T, Thygesen K S and Brandbyge M 2018 Nano Lett. 18 7275 \n[38] Brandbyge M, Mozos J L, Ordejón P, Taylor J and Stokbro K 2002 Phys. Rev. B 65 165401 \n[39] Davidson E R 1975 J. Comput. Phys. 17 87 \n[40] Payne M C, Teter M P, Allan D C, Arias T A and Joannopoulos J D 1992 Rev. Mod. Phys. 64 1045 \n[41] Wende F, Marsman M and Steinke T 2016 CUG Proc. \n[42] Dal Corso A and Conte A M 2005 Phys. Rev. B 71 115106 \n[43] Blöchl P E 1994 Phys. Rev. B 50 17953 \n[44] Schlipf M and Gygi F 2015 Comput. Phys. Commun. 196 36 \n[45] Van Setten M, Giantomassi M, Bousquet E, Verstraete M J, Hamann D R, Gonze X and Rignanese G M 2018 Comput. Phys. Commun. 226 39 \n[46] Theurich G and Hill N A 2001 Phys. Rev. B 64 073106 \n[47] Blum V, Gehrke R, Hanke F, Havu P, Havu V, Ren X, Reuter K and Scheffler M 2009 Comput. Phys. Commun. 180 2175 \n[48] Lejaeghere K et al 2016 Science 351 aad3000 \n[49] Garrity K F, Bennett J W, Rabe K M and Vanderbilt D 2014 Comput. Mater. Sci. 81 446 \n[50] Center for Molecular Modeling, Ghent University 2019 Comparing Solid State DFT Codes, Basis Sets and Potentials (https://molmod.ugent.be/deltacodesdft) \n[51] Marques M A, Oliveira M J and Burnus T 2012 Comput. Phys. Commun. 183 2272 \n[52] Heyd J, Scuseria G E and Ernzerhof M 2003 J. Chem. Phys. 118 8207 \n[53] Heyd J, Peralta J E, Scuseria G E and Martin R L 2005 J. Chem. Phys. 123 174101 \n[54] Krukau A V, Vydrov O A, Izmaylov A F and Scuseria G E 2006 J. Chem. Phys. 125 224106 \n[55] Grimme S 2006 J. Comput. Chem. 27 1787 \n[56] Perdew J P, Burke K and Ernzerhof M 1996 Phys. Rev. Lett. 77 3865 \n[57] Perdew J P, Ruzsinszky A, Csonka G I, Vydrov O A, Scuseria G E, Constantin L A, Zhou X and Burke K 2008 Phys. Rev. Lett. 100 136406 \n[58] Hammer B, Hansen L B and Nørskov J K 1999 Phys. Rev. B 59 7413 \n[59] Sun J, Ruzsinszky A and Perdew J P 2015 Phys. Rev. Lett. 115 036402 \n[60] Paier J, Marsman M, Hummer K, Kresse G, Gerber I C and Ngyn J G 2006 J. Chem. Phys. 124 154709 \n[61] Lin L 2016 J. Chem. Theory Comput. 12 2242 \n[62] Ferreira L G, Marques M and Teles L K 2008 Phys. Rev. B 78 125116 \n[63] Ferreira L G, Marques M and Teles L K 2011 AIP Adv. 1 32119 \n[64] Tran F and Blaha P 2009 Phys. Rev. Lett. 102 226401 \n[65] Doumont J, Tran F and Blaha P 2019 Phys. Rev. B 99 115101 \n[66] Wang L W and Zunger A 1995 Phys. Rev. B 51 17398 \n[67] Schimka L, Harl J and Kresse G 2011 J. Chem. Phys. 134 024116 \n[68] Landmann M, Rauls E and Schmidt W G 2012 J. Phys.: Condens. Matter 24 195503 \n[69] Bersch E, Rangan S, Bartynski R A, Garfunkel E and Vescovo E 2008 Phys. Rev. B 78 085114 \n[70] Berger L I 2017 CRC Handbook of Chemistry and Physics 97th edn, ed J R Rumble (Boca Raton, FL: CRC Press) \n[71] Dudarev S L, Botton G A, Savrasov S Y, Humphreys C J and Sutton A P 1998 Phys. Rev. B 57 1505 \n[72] Cococcioni M and de Gironcoli S 2005 Phys. Rev. B 71 035105 \n[73] Neugebauer J and Scheffler M 1992 Phys. Rev. B 46 16067 \n[74] Holst M and Saied F 1993 J. Comput. Chem. 14 105 \n[75] Concus P, Golub G H and O’Leary D P 1976 Sparse Matrix Computations (Amsterdam: Elsevier) pp 309–32 \n[76] Amestoy P R, Guermouche A, L’Excellent J Y and Pralet S 2006 Parallel Comput. 32 136 \n[77] Ozaki T, Nishio K and Kino H 2010 Phys. Rev. B 81 035116 \n[78] Elstner M, Porezag D, Jungnickel G, Elsner J, Haugk M, Frauenheim T, Suhai S and Seifert G 1998 Phys. Rev. B 58 7260 \n[79] Ammeter J, Bürgi H, Thibeault J and Hoffmann R 1978 J. Am. Chem. Soc. 100 3686 \n[80] Boykin T B, Klimeck G, Bowen R C and Oyafuso F 2002 Phys. Rev. B 66 125207 [81] Bernstei Mehl M, Papaconstantopoulos D, Papanicolaou N, Bazant M Z and Kaxiras E 2000 Phys. Rev. B 62 4477 [82] Cerda J and Soria F 2000 Phys. Rev. B 61 7965 \n[83] Jancu J M, Scholz R, Beltram F and Bassani F 1998 Phys. Rev. B 57 6493 [84] Köhler C, Frauenheim T, Hourahine B, Seifert G and Sternberg M 2007 J. Phys. Chem. A 111 5622 \n[85] Stillinger F H and Weber T A 1985 Phys. Rev. B 31 5262 [86] Mishin Y, Mehl M, Papaconstantopoulos D, Voter A and Kress J 2001 Phys. Rev. B 63 224106 [87] Baskes M I 1997 Modelling Simul. Mater. Sci. Eng. 5 149 \n[88] Tersoff J 1988 Phys. Rev. B 37 6991 [89] Brenner D W, Shenderova O, Harrison J, Stuart S J, Ni B and Sinnott S B 2002 J. Phys.: Condens. Matter 14 783 [90] Chenoweth K, Van Duin A C and Goddard W A 2008 J. Phys. Chem. A 112 1040 [91] Yu J, Sinnott S B and Phillpot S R 2007 Phys. Rev. B 75 085311 [92] Mitchell P and Fincham D 1993 J. Phys.: Condens. Matter 5 1031 \n[93] Tangney P and Scandolo S 2002 J. Chem. Phys. 117 8898 [94] Rowley A J, Jemmer P, Wilson M and Madden P A 1998 J. Chem. Phys. 108 10209 [95] Mackerell A D 2004 J. Comput. Chem. 25 1584 [96] Keating P 1966 Phys. Rev. 145 637 \n[97] Plimpton S 1995 J. Comput. Phys. 117 1 \n[98] Sheppard D, Xiao P, Chemelewski W, Johnson D D and Henkelman G 2012 J. Chem. Phys. 136 74103 \n[99] Liu D C and Nocedal J 1989 Math. Program. 45 503 \n[100] Bitzek E, Koskinen P, Gähler F, Moseler M and Gumbsch P 2006 Phys. Rev. Lett. 97 170201 \n[101] Glass C W, Oganov A R and Hansen N 2006 Comput. Phys. Commun. 175 713 \n[102] Kirkpatrick S, Gelatt C D and Vecchi M P 1983 Science 220 671 \n[103] Jónsson H, Mills G and Jacobsen K W 1998 Classical and Quantum Dynamics in Condensed Phase Simulations (Singapore: World Scientific) pp 385–404 \n[104] Henkelman G and Jónsson H 2000 J. Chem. Phys. 113 9978 \n[105] Henkelman G, Uberuaga B P and Jónsson H 2000 J. Chem. Phys. 113 9901 \n[106] Smidstrup S, Pedersen A, Stokbro K and Jónsson H 2014 J. Chem. Phys. 140 214106 \n[107] Sheppard D, Terrell R and Henkelman G 2008 J. Chem. Phys. 128 134106 \n[108] Swope W C, Andersen H C, Berens P H and Wilson K R 1982 J. Chem. Phys. 76 637 \n[109] Martyna G J, Klein M L and Tuckerman M 1992 J. Chem. Phys. 97 2635 \n[110] Goga N, Rzepiela A J, de Vries A H, Marrink S J and Berendsen H J C 2012 J. Chem. Theory Comput. 8 3637 \n[111] Martyna G J, Tobias D J and Klein M L 1994 J. Chem. Phys. 101 4177 \n[112] Müller-Plathe F 1997 J. Chem. Phys. 106 6082 \n[113] Tribello G A, Bonomi M, Branduardi D, Camilloni C and Bussi G 2014 Comput. Phys. Commun. 185 604 \n[114] Kondati Natarajan S and Behler J 2017 J. Phys. Chem. C 121 4368 \n[115] Henkelman G and Jónsson H 2001 J. Chem. Phys. 115 9657 \n[116] Xu L and Henkelman G 2008 J. Chem. Phys. 129 114104 \n[117] Chill S T and Henkelman G 2014 J. Chem. Phys. 140 214110 \n[118] Aristoff D, Chill S and Simpson G 2016 Commun. Appl. Math. Comput. Sci. 11 171 \n[119] Vineyard G H 1957 J. Phys. Chem. Solids 3 121 \n[120] Alfè D 2009 Comput. Physi. Commun. 180 2622 \n[121] Parlinski K, Li Z Q and Kawazoe Y 1997 Phys. Rev. Lett. 78 4063 49 16223 \n[123] Gunst T, Markussen T, Stokbro K and Brandbyge M 2016 Phys. Rev. B 93 035414 \n[124] Madsen G K H and Singh D J 2006 Comput. Phys. Commun. 175 67 \n[125] Samsonidze G and Kozinsky B 2018 Adv. Energy Mater. 8 1870095 \n[126] King-Smith R D and Vanderbilt D 1993 Phys. Rev. B 47 1651 \n[127] Bernardini F, Fiorentini V and Vanderbilt D 1997 Phys. Rev. B 56 R10024 \n[128] Blonski P and Hafner J 2009 J. Phys.: Condens. Matter 21 426001 \n[129] Blanco-Rey M, Cerda J I and Arnau A 2018 (arXiv:1811.12100) \n[130] Masuda K, Kasai S, Miura Y and Hono K 2017 Phys. Rev. B 96 174401 \n[131] Nikolić B K, Dolui K, Petrović M D, Plecháč P, Markussen T and Stokbro K 2018 Handbook of Materials Modeling: Applications: Current and Emerging Materials ed W Andreoni and S Yip (Cham: Springer) pp 1–35 \n[132] Petersen D E, Sørensen H H B, Hansen P C, Skelboe S and Stokbro K 2008 J. Comput. Phys. 227 3174 \n[133] Sanvito S, Lambert C J, Jefferson J H and Bratkovsky A M 1999 Phys. Rev. B 59 11936 \n[134] Sancho M P L, Sancho J M L, Sancho J M L and Rubio J 1985 J. Phys. F: Met. Phys. 15 851 \n[135] Sørensen H H B, Hansen P C, Petersen D E, Skelboe S and Stokbro K 2008 Phys. Rev. B 77 155301 \n[136] Sørensen H H B, Hansen P C, Petersen D E, Skelboe S and Stokbro K 2009 Phys. Rev. B 79 205322 \n[137] Stradi D, Martinez U, Blom A, Brandbyge M and Stokbro K 2016 Phys. Rev. B 93 155302 \n[138] Todorov T, Hoekstra J and Sutton A 2000 Phil. Mag. B 80 421 \n[139] Lü J T, Brandbyge M, Hedegård P, Todorov T N and Dundas D 2012 Phys. Rev. B 85 245444 \n[140] Todorov T N, Dundas D, Lü J T, Brandbyge M and Hedegård P 2014 Eur. J. Phys. 35 065004 \n[141] Zhang W J 2011 J. Power Sources 196 2962 \n[142] Haug H and Jauho A P 2008 Quantum Kinetics in Transport and Optics of Semiconductors (Berlin: Springer) \n[143] Lü J T, Christensen R B, Foti G, Frederiksen T, Gunst T and Brandbyge M 2014 Phys. Rev. B 89 081405 \n[144] Gunst T, Brandbyge M, Palsgaard M, Markussen T and Stokbro K 2017 Int. Conf. on Simulation of Semiconductor Processes and Devices (IEEE) pp 13–6 \n[145] Vandenberghe W, Sorée B, Magnus W and Fischetti M V 2011 J. Appl. Phys. 109 124503 \n[146] Markussen T, Palsgaard M, Stradi D, Gunst T, Brandbyge M and Stokbro K 2017 Phys. Rev. B 95 245210 \n[147] Gunst T, Markussen T, Palsgaard M L N, Stokbro K and Brandbyge M 2017 Phys. Rev. B 96 161404 \n[148] Markussen T, Jauho A P and Brandbyge M 2009 Phys. Rev. Lett. 103 055502 \n[149] Sivan U and Imry Y 1986 Phys. Rev. B 33 551 \n[150] Henrickson L E 2002 J. Appl. Phys. 91 6273 \n[151] Chen J, Hu Y and Guo H 2012 Phys. Rev. B 85 155441 \n[152] Zhang L, Gong K, Chen J, Liu L, Zhu Y, Xiao D and Guo H 2014 Phys. Rev. B 90 195428 \n[153] Palsgaard M, Markussen T, Gunst T, Brandbyge M and Stokbro K 2018 Phys. Rev. Appl. 10 014026 \n[154] Pedone A, Malavasi G, Menziani M, Cormack A and Segre U 2006 J. Phys. Chem. B 110 11780 \n[155] Morgan R B and Scott D S 1986 SIAM J. Sci. Stat. Comput. 7 817 \n[156] Anderson E et al 1999 LAPACK Users’ Guide 3rd edn (Philadelphia, PA: SIAM) \n[157] Marek A, Blum V, Johanni R, Havu V, Lang B, Auckenthaler T, Heinecke A, Bungartz H J and Lederer H 2014 J. Phys.: Condens. Matter 26 213201 \n[158] Hamaekers J, Bollerhey G, Bulin J, Neuen C, Thesen R and Griebel M 2019 Tremolo-X (www.tremolo-x.com) \n[159] The HDF Group 2019 The HDF5 Library and File Format (www.hdfgroup.org/solutions/hdf5) \n[160] Neese F 2012 Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2 73 \n[161] Enkovaara J E et al 2010 J. Phys.: Condens. Matter 22 253202 \n[162] Clark S J, Segall M D, Pickard C J, Hasnip P J, Probert M I, Refson K and Payne M C 2005 Z. Kristallogr.-Cryst. Mater. 220 567 \n[163] Stradi D, Jelver L, Smidstrup S and Stokbro K 2017 J. Phys.: Condens. Matter 29 185901 \n[164] Brandl G 2019 Sphinx Python Documentation Generator (www.sphinx-doc.org) \n[165] Synopsys, Inc. 2019 QuantumATK Documentation (https:// docs.quantumatk.com) \n[166] Stradi D, Papior N R, Hansen O and Brandbyge M 2017 Nano Lett. 17 2660 \n[167] Zhong H et al 2016 Sci. Rep. 6 21786 \n[168] Fiori G, Bonaccorso F, Iannaccone G, Palacios T, Neumaier D, Seabaugh A, Banerjee S K and Colombo L 2014 Nat. Nanotechnol. 9 768 \n[169] IEEE 2018 The International Roadmap for Devices and Systems: 2017 (https://irds.ieee.org/images/files/ pdf/2017/2017IRDS_MM.pdf) \n[170] Mueller T, Xia F and Avouris P 2010 Nat. Photon. 4 297 \n[171] Szabó A, Koester S J and Luisier M 2015 IEEE Electron Device Lett. 36 514 \n[172] Singh-Miller N E and Marzari N 2009 Phys. Rev. B 80 235407 \n[173] Kasap S, Koughia C and Ruda H E 2017 Electrical Conduction in Metals and Semiconductors Springer \n\nHandbook of Electronic and Photonic Materials Springer Handbooks (Berlin, Springer) (https://doi. org/10.1007/978-3-319-48933-92) [174] Josell D, Brongersma S H and Tkei Z 2009 Annu. Rev. Mater. Res. 39 231 [175] Bauer R, Schmid A, Pavone P and Strauch D 1998 Phys. Rev. B 57 11276 [176] Gall D 2016 J. Appl. Phys. 119 085101 [177] Stewart G R 1983 Rev. Sci. Instrum. 54 1 [178] Islam M S and Fisher C A 2014 Chem. Soc. Rev. 43 185 [179] Boulfelfel S, Seifert G and Leoni S 2011 J. Mater. Chem. 21 16365 [180] Islam M S and Fisher C A 2015 J. Mater. Chem. A 3 20399 [181] English N J and Waldron C J 2015 Phys. Chem. Chem. Phys. 17 12407 [182] Rungger I, Chen X, Schwingenschlögl U and Sanvito S 2010 Phys. Rev. B 81 235407 [183] Kima S P, van Duin A and Shenoya V B 2011 J. Power Sources 196 8590 [184] Kahle L, Marcolongo A and Marzari N 2018 Phys. Rev. Mater. 2 065405 [185] Kutteh R and Avdeev M 2014 J. Phys. Chem. C 118 11203 [186] Khomyakov P A, Luisier M and Schenk A 2015 Appl. Phys. Lett. 107 062104 [187] Braunstein R, Moore A R and Herman F 1958 Phys. Rev. 109 695 [188] Taur Y et al 1997 Proc. IEEE 85 486 [189] Li S and Fu Y 2012 3D TCAD Simulation for Semiconductor Processes, Devices and Optoelectronics (New York: Springer) pp 41–80 [190] Zunger A, Wei S H, Ferreira L G and Bernard J E 1990 Phys. Rev. Lett. 65 353 [191] van de Walle A 2009 Calphad 33 266 (Tools for Computational Thermodynamics) [192] Monkhorst H J and Pack J D 1976 Phys. Rev. B 13 5188 " + }, + { + "id": "10.1088_1361-648X_ab51ff", + "DOI": "10.1088/1361-648X/ab51ff", + "DOI Link": "http://dx.doi.org/10.1088/1361-648X/ab51ff", + "Relative Dir Path": "mds/10.1088_1361-648X_ab51ff", + "Article Title": "Wannier90 as a community code: new features and applications", + "Authors": "Pizzi, G; Vitale, V; Arita, R; Blügel, S; Freimuth, F; Géranton, G; Gibertini, M; Gresch, D; Johnson, C; Koretsune, T; Ibañez-Azpiroz, J; Lee, H; Lihm, JM; Marchand, D; Marrazzo, A; Mokrousov, Y; Mustafa, JI; Nohara, Y; Nomura, Y; Paulatto, L; Poncé, S; Ponweiser, T; Qiao, JF; Thöle, F; Tsirkin, SS; Wierzbowska, M; Marzari, N; Vanderbilt, D; Souza, I; Mostofi, AA; Yates, JR", + "Source Title": "JOURNAL OF PHYSICS-CONDENSED MATTER", + "Abstract": "Wannier90 is an open-source computer program for calculating maximally-localised Wannier functions (MLWFs) from a set of Bloch states. It is interfaced to many widely used electronic-structure codes thanks to its independence from the basis sets representing these Bloch states. In the past few years the development of Wannier90 has transitioned to a community-driven model; this has resulted in a number of new developments that have been recently released in Wannier90 v3.0. In this article we describe these new functionalities, that include the implementation of new features for wannierisation and disentanglement (symmetry-adapted Wannier functions, selectively-localised Wannier functions, selected columns of the density matrix) and the ability to calculate new properties (shift currents and Berry-curvature dipole, and a new interface to many-body perturbation theory); performance improvements, including parallelisation of the core code; enhancements in functionality (support for spinor-valued Wannier functions, more accurate methods to interpolate quantities in the Brillouin zone); improved usability (improved plotting routines, integration with high-throughput automation frameworks), as well as the implementation of modern software engineering practices (unit testing, continuous integration, and automatic source-code documentation). These new features, capabilities, and code development model aim to further sustain and expand the community uptake and range of applicability, that nowadays spans complex and accurate dielectric, electronic, magnetic, optical, topological and transport properties of materials.", + "Times Cited, WoS Core": 1281, + "Times Cited, All Databases": 1341, + "Publication Year": 2020, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000520450700001", + "Markdown": "# ACCEPTED MANUSCRIPT $\\cdot$ OPEN ACCESS \n\n# Wannier90 as a community code: new features and applications \n\nTo cite this article before publication: Giovanni Pizzi et al 2019 J. Phys.: Condens. Matter in press https://doi.org/10.1088/1361-648X/ab51ff \n\n# Manuscript version: Accepted Manuscript \n\nAccepted Manuscript is “the version of the article accepted for publication including all changes made as a result of the peer review process, and which may also include the addition to the article by IOP Publishing of a header, an article ID, a cover sheet and/or an ‘Accepted Manuscript’ watermark, but excluding any other editing, typesetting or other changes made by IOP Publishing and/or its licensors” \n\nThis Accepted Manuscript is $\\circledcirc$ 2019 IOP Publishing Ltd. \n\nAs the Version of Record of this article is going to be / has been published on a gold open access basis under a CC BY 3.0 licence, this Accepted Manuscript is available for reuse under a CC BY 3.0 licence immediately. \n\nEveryone is permitted to use all or part of the original content in this article, provided that they adhere to all the terms of the licence https://creativecommons.org/licences/by/3.0 \n\nAlthough reasonable endeavours have been taken to obtain all necessary permissions from third parties to include their copyrighted content within this article, their full citation and copyright line may not be present in this Accepted Manuscript version. Before using any content from this article, please refer to the Version of Record on IOPscience once published for full citation and copyright details, as permissions may be required. All third party content is fully copyright protected and is not published on a gold open access basis under a CC BY licence, unless that is specifically stated in the figure caption in the Version of Record. \n\nView the article online for updates and enhancements. \n\n# Wannier90 as a community code: new features and applications \n\nGiovanni Pizzi,1, ∗ Valerio Vitale, ${}^{2,3}$ , ∗ Ryotaro Arita, $^{4,5}$ Stefan Bl¨ugel, $^6$ Frank Freimuth, $^6$ Guillaume G´eranton, $^6$ Marco Gibertini, $^{1,7}$ Dominik Gresch,8 Charles Johnson, $^{9}$ Takashi Koretsune, $^{10,11}$ Julen Iba˜nez-Azpiroz, $^{12}$ Hyungjun Lee, Jae-Mo Lihm,15 Daniel Marchand, $^{16}$ Antimo Marrazzo,1 Yuriy Mokrousov,6, 17 Jamal I. Mustafa, $^{18}$ Yoshiro Nohara, $^{19}$ Yusuke Nomura, $^4$ Lorenzo Paulatto,20 Samuel Ponc´e, $^{21}$ Thomas Ponweiser,22 Junfeng Qiao,23 Florian Th¨ole,24 Stepan S. Tsirkin, $^{12,25}$ Ma gorzata Wierzbowska, $^{26}$ Nicola Marzari,1, ∗ David Vanderbilt, $^{27}$ , ∗ Ivo Souza,12, 28, ∗ Arash A. Mostofi,3, ∗ and Jonathan R. Yates $^{21}$ , $*$ $^{1}$ Theory and Simulation of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), \nE´cole Polytechnique F´ed´erale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland $^2$ Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge CB3 0HE, UK $^3$ Departments of Materials and Physics, and the Thomas Young Centre for Theory and Simulation of Materials, Imperial College London, London SW7 2AZ, UK $^4$ RIKEN Center for Emergent Matter Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan $^{5}$ Department of Applied Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan $^6$ Peter Gru¨nberg Institut and Institute for Advanced Simulation, Forschungszentrum Ju¨lich and JARA, 52425 Ju¨lich, Germany Department of Quantum Matter Physics, University of Geneva, Geneva, Switzerland 8ETH Zurich, Zurich, Switzerland $^{9}$ Departments of Materials and Physics, Imperial College London, London SW7 2AZ, UK 10Department of Physics, Tohoku University, Sendai, Japan 11JST PRESTO, Kawaguchi, Saitama, Japan \nCentro de F´ısica de Materiales, Universidad del Paı´s Vasco, E-20018 San Sebasti´an, Spa \n$^{13}$ Institute of Physics, E´cole Polytechnique F´ed´erale de \nLausanne (EPFL), CH-1015 Lausanne, Switzerland \n$^{14}$ Korea Institute for Advanced Study, Hoegiro 85, Seoul 02455, Korea \n$^{15}$ Department of Physics and Center for Theoretical Physics, \nSeoul National University, Seoul 08826, Korea \n$^{16}$ Laboratory for Multiscale Mechanics Modeling (LAMMM), \nE´cole Polytechnique F´ed´erale de Lausanne (EPFL), Lausanne, Switzerland \n$^{17}$ Institute of Physics, Jonannes-Gutenberg University of Mainz, 55099 Mainz, Germany \n$^{18}$ Department of Physics, University of California \nat Berkeley, Berkeley, California 94720, USA \n$^{19}$ ASMS Co., Ltd., 1-7-11 Higashi-Gotanda, \nShinagawa-ku, Tokyo 141-0022, Japan \n$^{\\mathrm{20}}$ Institut de Min´eralogie, de Physique des Mat´eriaux et de Cosmochimie (IMPMC), \nSorbonne Universit´e, CNRS UMR 7590, Case 115, \n4 place Jussieu, 75252 Paris Cedex 05, France \n$^{21}$ Department of Materials, University of Oxford, \nParks Road, Oxford OX1 3PH, UK \n$^{22}$ Research Institute for Symbolic Computation (RISC), \nJohannes Kepler University, Altenberger Straße 69, 4040 Linz, Austria \n$^{23}$ Fert Beijing Institute, School of Microelectronics, \nBDBC, Beihang University, Beijing, China \n24Materials Theory, ETH Zu¨rich, Wolfgang-Pauli-Strasse 27, CH-8093 Z¨urich, Switzerland \n25Department of Physics, University of Zurich, \nWintherthurerstrasse 190, CH-8057 Zurich, Switzerland \n6Institute of High Pressure Physics, Polish Academy of Sciences, \nSoko owska street 29/37, 01-142 Warsaw, Poland \n27Department of Physics and Astronomy, Rutgers University, \nPiscataway, New Jersey 08854-8019, USA \n$^{28}$ Ikerbasque Foundation, E-48013 Bilbao, Spain \n(Dated: October 10, 2019) \n\n# Abstract \n\nWannier90 is an open-source computer program for calculating maximally-localised Wannier functions (MLWFs) from a set of Bloch states. It is interfaced to many widely used electronicstructure codes thanks to its independence from the basis sets representing these Bloch states. In the past few years the development of Wannier90 has transitioned to a community-driven model; this has resulted in a number of new developments that have been recently released in Wannier90 v3.0. In this article we describe these new functionalities, that include the implementation of new features for wannierisation and disentanglement (symmetry-adapted Wannier functions, selectively-localised Wannier functions, selected columns of the density matrix) and the ability to calculate new properties (shift currents and Berry-curvature dipole, and a new interface to many-body perturbation theory); performance improvements, including parallelisation of the core code; enhancements in functionality (support for spinor-valued Wannier functions, more accurate methods to interpolate quantities in the Brillouin zone); improved usability (improved plotting routines, integration with high-throughput automation frameworks), as well as the implementation of modern software engineering practices (unit testing, continuous integration, and automatic source-code documentation). These new features, capabilities, and code development model aim to further sustain and expand the community uptake and range of applicability, that nowadays spans complex and accurate dielectric, electronic, magnetic, optical, topological and transport properties of materials. \n\n# I. INTRODUCTION \n\nWannier90 is an open-source code for generating Wannier functions (WFs), in particular maximally-localised Wannier functions (MLWFs), and using them to compute advanced materials properties with high efficiency and accuracy. Wannier90 is a paradigmatic example of interoperable software, achieved by ensuring that all the quantities required as input are entirely independent of the underlying electronic-structure code from which they are obtained. Most of the major and widely used electronic-structure codes have an interface to Wannier90, including Quantum ESPRESSO $^{1}$ , ABINIT2, VASP3–5, Siesta $^6$ , Wien2k7, Fleur $^{8}$ , Octopus $^{\\mathrm{~9~}}$ and ELK $^{10}$ . As a consequence, once a property is implemented within Wannier90, it can be immediately available to users of all codes that interface to it. \n\nOver the last few years, Wannier90 has undergone a transition from a code developed by a small group of developers to a community code with a much wider developers’ base. This has been achieved in two principal ways: (i) hosting the source code and associated development efforts on a public GitHub repository11; and (ii) building a community of Wannier90 developers and facilitating personal interactions between individuals through community workshops, the most recent in 2016. In response, the code has grown significantly, gaining many novel features contributed by this community, as well as numerous fixes. \n\nIn this paper, we describe the most important novel contributions to the Wannier90 code, as embodied in its 3.0 release. The paper is structured as follows: In Sec. II we first summarise the background theory for the computation of MLWFs (additional details can be found in Ref. $\\mathrm{12}$ ), and introduce the notation that will be used throughout the paper. In Sec. III we describe the novel features of Wannier90 that are related to the core wannierisation and disentanglement algorithms; these include symmetry-adapted WFs, selective localisation of WFs, and parallelisation using the message-passing interface (MPI). In Sec. IV we describe new functionality enhancements, including the ability to handle spinor-valued WFs and calculations with non-collinear spin that use ultrasoft pseudopotentials (within Quantum ESPRESSO); improved interpolation of the $k$ -space Hamiltonian; a more flexible approach for handling and using initial projections; and the ability to plot WFs in Gaussian cube format on WF-centred grids with non-orthogonal translation vectors. In Sec. V we describe new functionalities associated with using MLWFs for computing advanced electronic-structure properties, including the calculation of shift currents, gyrotropic effects and spin Hall conductivities, as well as parallelisation improvements and the interpolation of bands originating from calculations performed with many-body perturbation theory (GW). In Sec. VI we describe the selected-columns-of-the-density-matrix (SCDM) method, which enables computation of WFs without the need for explicitly defining initial projections. In Sec. VII we describe new post-processing tools and codes, and the integration of Wannier90 with high-throughput automation and workflow management tools (specifically, the AiiDA materials’ informatics infrastructure $^{13}$ ). In Sec. VIII we describe the modern software engineering practices now adopted in Wannier90, that have made it possible to improve the development lifecycle and transform Wannier90 into a communitydriven code. Finally, our conclusions and outlook are presented in Sec. IX. \n\n# II. BACKGROUND \n\nWFs form a possible basis set for the electronic states of materials. As we are going to describe in the following, WFs are not unique and they can be optimised to obtain MLWFs. These, thanks to their localisation in real space, are particularly useful in a number of electronic-structure applications. For instance, they allow for efficient interpolation of operator matrix elements on dense grids in the Brillouin Zone (BZ), which is a key step to compute many materials properties. The interpolation is obtained starting from the value of these matrix elements and other properties of the wavefunctions (described below) computed on a coarser grid, usually with an accurate but slower ab initio code. MLWFs play in materials a role analogue to molecular orbitals in molecules and a typical shape of MLWFs (for instance, in the case of the valence bands of GaAs) can be seen in Fig. 1(a) and Fig. 1(e). \n\nFormally, MLWFs can be introduced as follows in the independent-particle approximation. The electronic structure of a periodic system is conventionally represented in terms of one-electron Bloch states $\\psi_{n\\mathbf{k}}(\\mathbf{r})$ , which are labelled by a band index $n$ and a crystal momentum k inside the first BZ, and which satisfy Bloch’s theorem: \n\n$$\n\\psi_{n\\mathbf{k}}(\\mathbf{r})=u_{n\\mathbf{k}}(\\mathbf{r})e^{i\\mathbf{k}\\cdot\\mathbf{r}},\n$$ \n\nwhere $u_{n\\mathbf{k}}(\\mathbf{r})=u_{n\\mathbf{k}}(\\mathbf{r+R})$ is a periodic function with the same periodicity of the singleparticle Hamiltonian, and $\\mathbf{R}$ is a Bravais lattice vector. (For the moment we ignore the spin degrees of freedom and work with spinless wave functions; spinor wave functions will be treated in Sec. IV A.) Such a formalism is also commonly applied, via the supercell approximation, to non-periodic systems, typically used to treat point, line and planar defects in crystals, surfaces, amorphous solids, liquids and molecules. \n\n# A. Isolated bands \n\nA group of bands is said to be isolated if it is separated by energy gaps from all the other lower and higher bands throughout the BZ (this isolated group of bands may still show arbitrary crossing degeneracies and hybridisations within itself). For such isolated set of $J$ bands, the electronic states can be equivalently represented by a set of $J$ WFs per cell, that are related to the Bloch states via two unitary transformations (one continuous, one discrete)14: \n\n$$\n|w_{n\\mathbf{R}}\\rangle=V\\int_{\\mathrm{BZ}}\\frac{\\mathrm{d}\\mathbf{k}}{(2\\pi)^{3}}e^{-i\\mathbf{k}\\cdot\\mathbf{R}}\\sum_{m=1}^{J}|\\psi_{m\\mathbf{k}}\\rangle U_{m n\\mathbf{k}},\n$$ \n\nwhere $w_{n\\mathbf{R}}(\\mathbf{r})=w_{n\\mathbf{0}}(\\mathbf{r}-\\mathbf{R})$ is a periodic (but not necessarily localised) WF labelled by the quantum number $\\mathbf{R}$ (the counterpart of the quasi-momentum $\\mathbf{k}$ in the Bloch representation), $V$ is the cell volume and $U_{\\mathbf{k}}$ are unitary matrices that mix Bloch states at a given $\\mathbf{k}$ and represent the gauge freedom that exists in the definition of the Bloch states and that is inherited by the WFs. \n\nMLWFs are obtained by choosing $U_{\\mathbf{k}}$ matrices that minimise the sum of the quadratic spreads of the WFs about their centres for a reference $\\mathbf{R}$ (say, $\\mathbf R=\\mathbf0$ ). This sum is given by the spread functional \n\n$$\n\\Omega=\\sum_{n=1}^{J}\\left[\\langle w_{n\\mathbf{0}}|\\mathbf{r}\\cdot\\mathbf{r}|w_{n\\mathbf{0}}\\rangle-|\\langle w_{n\\mathbf{0}}|\\mathbf{r}|w_{n\\mathbf{0}}\\rangle|^{2}\\right].\n$$ \n\nΩ may be decomposed into two positive-definite parts15, \n\n$$\n\\Omega=\\Omega_{\\mathrm{I}}+\\widetilde{\\Omega},\n$$ \n\n$$\n\\Omega_{\\mathrm{I}}=\\sum_{n}\\left[\\langle w_{n0}|\\mathbf{r}\\cdot\\mathbf{r}|w_{n0}\\rangle-\\sum_{m\\mathbf{R}}{|\\langle w_{m\\mathbf{R}}|\\mathbf{r}|w_{n0}\\rangle|^{2}}\\right]\n$$ \n\nis gauge invariant (i.e., invariant under the action of any unitary $U_{\\mathbf{k}}$ on the Bloch states), and \n\n$$\n\\widetilde{\\Omega}=\\sum_{n}\\sum_{m\\mathbf{R}\\neq n\\mathbf{0}}|\\langle w_{m\\mathbf{R}}|\\mathbf{r}|w_{n\\mathbf{0}}\\rangle|^{2}\n$$ \n\nis gauge dependent. Therefore, the “wannierisation” of an isolated manifold of bands, i.e., the transformation of Bloch states into MLWFs, amounts to minimising the gauge-dependent part $\\widetilde\\Omega$ of the spread functional. \n\nCrucially, the matrix elements of the position operator between WFs can be expressed in reciprocal space. Under the assumption that the BZ is sampled on a uniform Monkhorst– Pack mesh of $k$ -points composed of $N$ points $\\begin{array}{r}{\\big(V\\int_{\\mathrm{BZ}}\\frac{\\mathrm{d}\\mathbf{k}}{(2\\pi)^{3}}\\underset{\\mathcal{\\vec{N}}}{\\longrightarrow}\\frac{1}{N}\\sum_{\\mathbf{k}}\\big),}\\end{array}$ , the gauge-independent and gauge-dependent parts of the spread may be expressed, respectively, as15 \n\n$$\n\\Omega_{\\mathrm{I}}={\\frac{1}{N}}\\sum_{\\mathbf{k},\\mathbf{b}}w_{b}\\left[J-\\sum_{m n}\\left|{\\cal M}_{m n}^{(\\mathbf{k},\\mathbf{b})}\\right|^{2}\\right]\n$$ \n\nand \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\widetilde\\Omega}=\\frac{1}{N}\\sum_{{\\bf k},{\\bf b}}w_{b}\\sum_{m\\neq n}\\big\\vert M_{m n}^{({\\bf k},{\\bf b})}\\big\\vert^{2}}\\ ~}\\\\ {{\\displaystyle~+\\frac{1}{N}\\sum_{{\\bf k},{\\bf b}}w_{b}\\sum_{n}(-\\mathrm{Im}\\ln M_{n n}^{({\\bf k},{\\bf b})}-{\\bf b}\\cdot{\\bar{\\bf r}}_{n})^{2}},}\\end{array}\n$$ \n\nwhere $\\mathbf{b}$ are the vectors connecting a $k$ -point to its neighbours, $w_{b}$ are weights associated with the finite-difference representation of $\\nabla_{\\mathbf{k}}$ for a given geometry, the matrix of overlaps ${\\cal M}^{(\\mathbf{k},\\mathbf{b})}$ is defined by \n\n$$\nM_{m n}^{(\\mathbf{k},\\mathbf{b})}=\\left,\n$$ \n\nand the centres of the WFs are given by \n\n$$\n\\bar{\\bf r}_{n}\\equiv\\langle w_{n{\\bf0}}|{\\bf r}|w_{n{\\bf0}}\\rangle=-\\frac{1}{N}\\sum_{{\\bf k},{\\bf b}}w_{b}{\\bf b}\\mathrm{Im}\\ln M_{n n}^{({\\bf k},{\\bf b})}.\n$$ \n\nMinimisation of the spread functional is achieved by considering infinitesimal gauge transformations $U_{m n\\mathbf{k}}\\equiv\\delta_{m n}+\\mathrm{d}W_{m n\\mathbf{k}}$ , where dW is anti-Hermitian ( $\\mathrm{d}W^{\\dagger}=-\\mathrm{d}W$ ). The gradient of the spread functional with respect to such variations is given by \n\n$$\n\\mathcal{G}_{\\mathbf{k}}\\equiv\\frac{\\mathrm{d}\\Omega}{\\mathrm{d}W_{m n\\mathbf{k}}}=4\\sum_{\\mathbf{b}}w_{b}\\left(\\pmb{A}[R_{m n}^{(\\mathbf{k},\\mathbf{b})}]-\\pmb{S}[T_{m n}^{(\\mathbf{k},\\mathbf{b})}]\\right),\n$$ \n\nwhere $\\mathcal{A}$ and $\\boldsymbol{S}$ are the super-operators $\\boldsymbol{\\mathcal{A}}[B]=(B-B^{\\dagger})/2$ and ${\\cal S}[B]=(B+B^{\\dagger})/2i$ , \n\nrespectively, and \n\n$$\n\\begin{array}{l}{{\\displaystyle R_{m n}^{(\\mathbf{k},\\mathbf{b})}=M_{m n}^{(\\mathbf{k},\\mathbf{b})}M_{n n}^{(\\mathbf{k},\\mathbf{b})*},}}\\\\ {{\\displaystyle T_{m n}^{(\\mathbf{k},\\mathbf{b})}=\\frac{M_{m n}^{(\\mathbf{k},\\mathbf{b})}}{M_{n n}^{(\\mathbf{k},\\mathbf{b})}}q_{n}^{(\\mathbf{k},\\mathbf{b})},}}\\\\ {{\\displaystyle q_{n}^{(\\mathbf{k},\\mathbf{b})}=\\operatorname{Im}\\ln M_{n n}^{(\\mathbf{k},\\mathbf{b})}+\\mathbf{b}\\cdot\\bar{\\mathbf{r}}_{n}}.}\\end{array}\n$$ \n\nFor the full derivation of Eq. (11) we refer to Ref. 15. This gradient is then used to generate a search direction $\\mathcal{D}_{\\mathbf{k}}$ for an iterative steepest-descent or conjugate-gradient minimisation of the spread16: at each iteration the unitary matrices are updated according to \n\n$$\nU_{\\mathbf{k}}\\rightarrow U_{\\mathbf{k}}\\exp[\\alpha\\mathcal{D}_{\\mathbf{k}}],\n$$ \n\nwhere $\\alpha$ is a coefficient that can either be set to a fixed value or determined at each iteration via a simple polynomial line-search, and the matrix exponential is computed in the diagonal representation of $\\mathcal{D}_{\\mathbf{k}}$ and then transformed back in the original representation. Once the unitary matrices have been updated, the updated set of $M^{(\\mathbf{k},\\mathbf{b})}$ matrices is calculated according to \n\n$$\nM^{(\\mathbf{k},\\mathbf{b})}=U_{\\mathbf{k}}^{\\dagger}M^{(0)(\\mathbf{k},\\mathbf{b})}U_{\\mathbf{k+b}},\n$$ \n\nwhere \n\nis the set of initial $M^{(\\mathbf{k},\\mathbf{b})}$ matrices, computed once and for all, at the start of the calculation, from the original set of reference Bloch orbitals $|u_{n\\mathbf{k}}^{(0)}\\rangle$ \n\n# B. Entangled bands \n\nIt is often the case that the bands of interest are not separated from other bands in the Brillouin zone by energy gaps and are overlapping and hybridising with other bands that extend beyond the energy range of interest. In such cases, we refer to the bands as being entangled. \n\nThe difficulty in constructing MLWFs for entangled bands arises from the fact that, within a given energy window, the number of bands $\\mathcal{T}_{\\mathbf{k}}$ at each $k$ -point $\\mathbf{k}$ in the BZ is not a constant and is, in general, different from the target number $J$ of WFs: $\\mathcal{T}_{\\mathbf{k}}\\geq J$ . Even making the energy window $k$ -dependent would see discontinuous inclusion and exclusion of bands as the BZ is traversed. The treatment of entangled bands requires thus a more complex approach that is typically a two-step process. In the first step, a $J$ -dimensional manifold of Bloch states is selected at each $k$ -point, chosen to be as smooth as possible as a function of $\\mathbf{k}$ . In the second step, the gauge freedom associated with the selected manifold is used to obtain MLWFs, just as described in Sec. II A for the case of an isolated set of bands. \n\nFocusing on the first step, an orthonormal basis for the $J$ -dimensional subspace $S_{\\mathbf{k}}$ at each $\\mathbf{k}$ can be obtained by performing a semi-unitary transformation on the $\\mathcal{I}_{\\mathbf{k}}$ states at $\\mathbf{k}$ , where $V_{\\mathbf{k}}$ is a rectangular matrix of dimension $\\mathcal{I}_{\\mathbf{k}}\\times\\bar{\\mathcal{I}}$ that is semi-unitary in the sense that $V_{\\mathbf{k}}^{\\dagger}V_{\\mathbf{k}}=\\mathbf{1}$ . \n\nTo select the smoothest possible manifold, a measure of the intrinsic smoothness of the chosen subspace is needed. It turns out that such a measure is given precisely by what was the gauge-invariant part $\\Omega_{\\mathrm{I}}$ of the spread functional for isolated bands.17 Indeed, Eq. (7) can be expressed as \n\n$$\n\\mathbb{A}_{\\sf R}=\\frac{1}{N}\\sum_{\\mathbf{k},\\mathbf{b}}w_{b}\\mathrm{Tr}[P_{\\mathbf{k}}Q_{\\mathbf{k}+\\mathbf{b}}],\n$$ \n\nwhere $\\begin{array}{r}{P_{\\mathbf{k}}=\\sum_{n=1}^{J}\\left|\\widetilde{u}_{n\\mathbf{k}}\\right\\rangle\\left\\langle\\widetilde{u}_{n\\mathbf{k}}\\right|}\\end{array}$ is the projection operator onto $S_{\\mathbf{k}}$ , $Q_{\\mathbf{k}}=\\mathbf{1}-P_{\\mathbf{k}}$ is its Hilbertspace complement, eand “eTr” represents the trace over the entire Hilbert space. $\\operatorname{Tr}[P_{\\mathbf{k}}Q_{\\mathbf{k}+\\mathbf{b}}]$ measures the mismatch between the subspaces $S_{\\mathbf{k}}$ and $S_{\\mathbf{k}+\\mathbf{b}}$ , vanishing if they overlap identically. Hence $\\Omega_{\\mathrm{I}}$ measures the average mismatch of the local subspace $S_{\\mathbf{k}}$ across the BZ, so that an optimally-smooth subspace can be selected by minimising $\\Omega_{\\mathrm{I}}$ . Doing this with orthonormality constraints on the Bloch-like states is equivalent to solving self-consistently the set of coupled eigenvalue equations17 \n\n$$\n\\left[\\sum_{\\mathbf{b}}w_{b}P_{\\mathbf k+\\mathbf{b}}\\right]|\\widetilde u_{n\\mathbf k}\\rangle=\\lambda_{n\\mathbf k}|\\widetilde u_{n\\mathbf k}\\rangle.\n$$ \n\nThe solution can be achieved via an iterative procedure, whereby at the $i^{\\mathrm{th}}$ iteration the algorithm traverses the entire set of $k$ -points, selecting at each one the $J$ -dimensional subspace $S_{\\mathbf{k}}^{(i)}$ that has the smallest mismatch with the subspaces $S_{\\mathbf{k}+\\mathbf{b}}^{(i-1)}$ at the neighbouring \n\n$k$ -points obtained in the previous iteration. This amounts to solving \n\n$$\n\\left[\\sum_{\\mathbf{b}}w_{b}P_{\\mathbf{k+b}}^{(i-1)}\\right]|\\widetilde{u}_{n\\mathbf{k}}^{(i)}\\rangle=\\lambda_{n\\mathbf{k}}^{(i)}|\\widetilde{u}_{n\\mathbf{k}}^{(i)}\\rangle,\n$$ \n\nand selecting the $J$ eigenvectors with the largest eigenvalues17. Self-consistency is reached when $S_{\\mathbf{k}}^{(i)}=S_{\\mathbf{k}}^{(i-1)}$ (to within a user-defined threshold dis conv tol) at all the $k$ -points. To make the algorithm more robust, the projector appearing on the left-hand-side of Eq. (21) is replaced with $[P_{{\\bf k}+{\\bf b}}^{(i)}]_{\\mathrm{in}}$ , given by \n\n$$\n[P_{\\mathbf{k}+\\mathbf{b}}^{(i)}]_{\\mathrm{in}}=\\beta P_{\\mathbf{k}+\\mathbf{b}}^{(i-1)}+(1-\\beta)[P_{\\mathbf{k}+\\mathbf{b}}^{(i-1)}]_{\\mathrm{in}},\n$$ \n\nwhich is a linear mixture of the projector that was used as input for the previous iteration and the projector defined by the output of the previous iteration. The parameter $0<\\beta\\leq1$ determines the degree of mixing, and is typically set to $\\beta^{\\gamma}=0.5$ ; setting $\\beta=1$ reverts precisely to Eq. (21), while smaller and smaller values of $\\beta$ make convergence smoother (and thus more robust) but also slower. \n\nIn practice, Eq. (21) is solved by diagonalising the Hermitian operator appearing on the left-hand-side in the basis of the original $\\mathcal{I}_{\\mathbf{k}}$ Bloch states: \n\n$$\nZ_{m n\\mathbf{k}}^{(i)}=\\langle u_{m\\mathbf{k}}^{(0)}|\\sum_{\\mathbf{b}}w_{b}[P_{\\mathbf{k+b}}^{(i)}]_{\\mathrm{in}}|u_{n\\mathbf{k}}^{(0)}\\rangle.\n$$ \n\nOnce the optimal subspace has been selected, the wannierisation procedure described in Sec. II A is carried out to minimise the gauge-dependent part $\\widetilde\\Omega$ of the spread functional within that optimal subspace. \n\n# C. Initial projections \n\nIn principle, the overlap matrix elements $M_{m n}^{\\left(\\mathbf{k},\\mathbf{b}\\right)}$ are the only quantities required to compute and minimise the spread functional, and generate MLWFs for either isolated or entangled bands. In practice, this is generally true when dealing with an isolated set of bands, but in the case of entangled bands a good initial guess for the subspaces $S_{\\mathbf{k}}$ alleviates problems associated with falling into local minima of $\\Omega_{\\mathrm{I}}$ , and/or obtaining MLWFs that cannot be chosen to be real-valued (in the case of spinless WFs). Even in the case of an isolated set of bands, a good initial guess for the WFs, whilst not usually critical, often results in faster convergence of the spread to the global minimum. (It is important to note that both for isolated and for entangled bands multiple solutions to the wannierisation or disentanglement can exist, as discussed later.) \n\nA simple and effective procedure for selecting an initial gauge (in the case of isolated bands) or an initial subspace and initial gauge (in the case of entangled bands) is to project a set of $J$ trial orbitals $g_{n}(\\mathbf{r})$ localised in real space onto the space spanned by the set of original Bloch states at each $\\mathbf{k}$ : \n\n$$\n\\left|\\phi_{n\\mathbf{k}}\\right\\rangle=\\sum_{m=1}^{J{\\mathrm{or}}\\mathcal{T}_{\\mathbf{k}}}\\left|\\psi_{m\\mathbf{k}}\\right\\rangle\\left\\langle\\psi_{m\\mathbf{k}}\\mid g_{n}\\right\\rangle,\n$$ \n\nwhere the sum runs up to either $J$ or $\\mathcal{I}_{\\mathbf{k}}$ , depending on whether the bands are isolated or entangled, respectively, and the inner product $A_{m n\\bf{k}}=\\left<{\\psi_{m\\bf{k}}}\\left|{g_{n}}\\right>$ is over all the Born–von Karman supercell. (In practice, the fact that the gn are localised greatly simplifies this calculation.) The matrices $A_{\\mathbf{k}}$ are square $(J\\times J)$ ) or rectangular $\\left(\\mathcal{I}_{k}\\times J\\right)$ in the case of isolated or entangled bands, respectively. The resulting orbitals are then orthonormalised via a Lo¨wdin transformation18: \n\n$$\n\\begin{array}{l}{\\displaystyle|\\widetilde\\psi_{n\\mathbf{k}}\\rangle=\\sum_{m=1}^{J}|\\phi_{m\\mathbf{k}}\\rangle S_{m n\\mathbf{k}}^{-1/2}}\\\\ {=\\sum_{m=1}^{J\\mathrm{or}\\mathcal{I}_{\\mathbf{k}}}|\\psi_{m\\mathbf{k}}^{\\prime}\\rangle(A_{\\mathbf{k}}S_{\\mathbf{k}}^{-1/2})_{m n},}\\end{array}\n$$ \n\nwhere $S_{m n\\mathbf{k}}=\\langle\\phi_{m\\mathbf{k}}\\mid\\phi_{n\\mathbf{k}}\\rangle=(A_{\\mathbf{k}}^{\\dagger}A_{\\mathbf{k}})_{m n},$ and $A_{\\mathbf{k}}S_{\\mathbf{k}}^{-1/2}$ is a unitary or semi-unitary matrix. In the case of entangled bands, once an optimally-smooth subspace has been obtained as described in Sec. II B, the same trial orbitals $g_{n}(\\mathbf{r})$ can be used to initialise the wannierisation procedure of Sec. II A. In practice, the matrices $A_{\\mathbf{k}}$ are computed once and for all at the start of the calculation, together with the overlap matrices $M^{(\\mathbf{k},\\mathbf{b})}$ . These two operations need to be performed within the context of the electronic-structure code and basis set adopted; afterwards, all the operations of Wannier90 rely only on $A_{\\mathbf{k}}$ and ${\\cal M}^{(\\mathbf{k},\\mathbf{b})}$ and not on the specific representation of $\\bar{\\psi}_{m\\mathbf{k}}$ (e.g., plane waves, linearised augmented plane waves, localised basis sets, real-space grids, . . . ). \n\n# III. NEW FEATURES FOR WANNIERISATION AND DISENTANGLEMENT \n\nIn this section we provide an overview of the new features associated with the core wannierisation and disentanglement algorithms in Wannier90, namely the ability to generate \n\nWFs of specific symmetry; selectively localise a subset of the WFs and/or constrain their centres to specific sites; and perform wannierisation and disentanglement more efficiently through parallelisation. \n\n# A. Symmetry-adapted Wannier functions \n\nIn periodic systems, atoms are usually found at sites q whose site-symmetry group $G_{q}$ is a subgroup of the full point group $F^{'}$ of the crystal $^{19}$ (the symmetry operations in the group $G_{q}$ are those that leave q fixed). The set of points $\\left\\{\\mathbf{q}_{a}\\right\\}$ that are symmetry-equivalent sites to $\\mathbf{q}$ is called an $o r b i t^{20}$ . These are all the points in the unit cell that can be generated from $\\mathbf{q}$ by applying the symmetry operations in the full space group $G$ that do not leave q fixed. If ${\\bf q}_{a}$ is a high-symmetry site then its Wyckoff position has a single orbit20; for low-symmetry sites different orbits correspond to the same Wyckoff position. The number of points in the orbit(s) is the multiplicity $n_{q_{a}}$ of the Wyckoff position. MLWFs, however, are not bound to reside on such high-symmetry sites, and they do not necessarily possess the site symmetries of the crystal $^{17,21,22}$ . When using MLWFs as a local orbital basis set in methods such as first-principles tight binding, DFT+U and DFT plus dynamical-mean-field theory (DMFT), which deal with beyond-DFT correlations in a local subspace such as that spanned by $d$ orbitals (e.g., for systems containing transition metals atoms) or $f$ orbitals (e.g., for systems containing rare-earth or actinide series atoms), it is often desirable to ensure that the WFs basis possesses the local site symmetries. \n\nSakuma $^{21}$ has shown that such symmetry-adapted Wannier functions (SAWFs) can be constructed by introducing additional constraints on the unitary matrices $U_{\\mathbf{k}}$ of Eq. (2) during the minimisation of the spread. SAWFs, therefore, can be fully integrated within the original maximal-localisation procedure. The SAWF approach gives the user a certain degree of control over the symmetry and centres of the Wannier functions at the expense of some localisation since the final total spread of the resulting SAWFs can only be equal to, or most often larger than, that of the corresponding MLWFs with no constraints (note that in principle some SAWFs can have a smaller individual spread than any MLWFs). \n\nFor a given point ${\\bf q}_{a}$ in the home unit cell $\\mathbf{R}=\\mathbf{0}$ , the SAWFs centred at that point are denoted by \n\n$$\n\\{w_{i a}^{(\\varrho)}(\\mathbf{r})\\equiv w_{i}^{(\\varrho)}(\\mathbf{r}-\\mathbf{q}_{a}),\\quad i=1,\\ldots,n_{\\varrho}\\},\n$$ \n\nwhere $\\varrho$ is the character of the irreducible representation (irrep) of the corresponding sitesymmetry group $G_{a}$ with dimension $n_{\\varrho}$ . For instance, in a simple fcc crystal such as copper (Cu), the site-symmetry group associated with the Cu site is $O_{h}$ ; one of its irreps $^{20}$ is, e.g., 3-dimensional $\\operatorname{\\mathrm{~\\AE~}}^{\\prime}2g$ and, assuming the Cu atom is located at the origin $\\mathbf{r}=\\mathbf{0}$ of the unit cell, three associated SAWFs are denoted $w_{10}^{12g}(\\mathbf{r}),w_{20}^{12g}(\\mathbf{r})$ and $w_{30}^{22g}(\\mathbf{r})$ . \n\nTo find these SAWFs, one needs to specify appropriate unitary transformations $U_{m i a\\mathbf{k}}^{(\\varrho)}$ of the Bloch states, defined by \n\n$$\n\\begin{array}{r l r}{\\displaystyle}&{}&{\\displaystyle w_{i a}^{(\\varrho)}({\\bf r-R})=\\frac{1}{N}\\sum_{\\bf k}e^{-i{\\bf k\\cdot R}}\\sum_{m=1}^{J}\\psi_{m{\\bf k}}({\\bf r})U_{m i a{\\bf k}}^{(\\varrho)}}\\\\ &{}&{\\displaystyle=\\frac{1}{N}\\sum_{\\bf k}e^{-i{\\bf k\\cdot R}}\\psi_{i a{\\bf k}}^{(\\varrho)}({\\bf r}),}\\end{array}\n$$ \n\nwhere $\\{\\psi_{i a\\mathbf{k}}^{(\\varrho)}(\\mathbf{r})\\}$ are basis functions of the irrep $\\varrho$ and are formed from linear combinations of the $J$ eigenstates $\\{\\psi_{n\\mathbf{k}}(\\mathbf{r})\\}$ of the Hamiltonian $H$ . Since $H_{\\l}$ is invariant under the full spacegroup $G$ , the representation of a given symmetry operation $g=({\\mathcal{R}}|\\mathbf{t})\\in G$ (where $\\mathcal{R}$ and $\\mathbf{t}$ are the rotation and fractional-translation parts of the symmetry operation, respectively) in the basis $\\{\\psi_{n\\mathbf{k}}(\\mathbf{r})\\}$ must be a $J\\times J\\ {\\mathrm{unitary~matrix^{19}~}}\\widetilde{d}_{\\bf k}(g)$ , i.e., $\\widetilde{d}_{\\bf k}(g)$ represents how the $J$ Bloch states are transformed by the symmetry operation $g$ : \n\n$$\ng\\psi_{n\\mathbf{k}}(\\mathbf{r})=\\sum_{m=1}^{J}\\psi_{m\\mathcal{R}\\mathbf{k}}(\\mathbf{r})\\widetilde{d}_{m n\\mathbf{k}}(g),\\quad g\\in G,\n$$ \n\nwhere the matrix elements $\\bar{d_{\\bf k}}(y)_{\\mathrm{\\bf0\\mathrm{re}}}$ given by \n\n$$\n\\widetilde{d}_{m n\\mathbf{k}}(g)=\\int\\mathrm{d}\\mathbf{r}\\psi_{m\\mathcal{R}\\mathbf{k}}^{*}(\\mathbf{r})\\psi_{n\\mathbf{k}}\\left(g^{-1}\\mathbf{r}\\right).\n$$ \n\nOn the other hand, the Bloch functions $\\{\\psi_{i a\\mathbf{k}}^{(\\varrho)}(\\mathbf{r})\\}$ , defined in Eq. (28), transform under the action of $g\\in G$ as \n\n$$\ng\\psi_{i a\\mathbf{k}}^{(\\varrho)}(\\mathbf{r})=\\sum_{i^{\\prime}a^{\\prime}\\varrho^{\\prime}}\\psi_{i^{\\prime}a^{\\prime}\\mathcal{R}\\mathbf{k}}^{(\\varrho^{\\prime})}(\\mathbf{r})D_{i^{\\prime}a^{\\prime},i a\\mathbf{k}}^{(\\varrho^{\\prime},\\varrho)}(g),\n$$ \n\nwhere $D_{\\mathbf{k}}(g)$ is the matrix representation of the symmetry operation $g$ in the basis of $\\{\\psi_{i a\\bf{k}}^{(\\varrho)}({\\bf{r}})\\}$ ; the reader is referred to Refs. 19 and 21 for details. \n\nFrom Eqs. (28), (29) and (31) it can shown $^{21}$ that, for a symmetry operation $g_{\\mathbf{k}}$ that leaves a given $\\mathbf{k}$ unchanged, the following relationship holds: \n\n$$\nU_{{\\bf k}}D_{{\\bf k}}(g_{\\bf k})=\\widetilde{d}_{\\bf k}(g_{\\bf k})U_{\\bf k},~g_{\\bf k}\\in G_{\\bf k},\n$$ \n\nand, to obtain SAWFs, the initial unitary matrix $U_{\\mathbf{k}}$ ( $\\mathbf{k}\\in\\mathrm{IBZ}$ ) must satisfy this constraint. This can be achieved iteratively, starting with the initial projection onto localised orbitals as described in Sec. II C, and with knowledge of $\\widetilde{d}_{\\bf k}(g)$ [Eq. (29)] and $D_{\\mathbf{k}}(g)$ [Eq. (31)], as discussed in detail Ref. 21. The matrices $\\widetilde{d}_{\\bf k}(g)$ , which are independent of the underlying basis-set used to represent the Bloch states and are computed only once at the start of the calculation, can be calculated directly from the Bloch states via Eq. (30). The matrices $D_{\\mathbf{k}}(g)$ are calculated by specifying the centre ${\\bf q}_{a}$ and the desired symmetry of the Wannier functions (e.g., $s$ , $p$ , $d$ etc.) and, for each symmetry operation ga in the site-symmetry group $G_{a}$ , calculating the matrix representation of the rotational part. \n\nFor an isolated set of bands, the minimisation of $\\widetilde\\Omega$ with the constraints defined in Eq. (32) requires the gradient $\\mathcal{G}_{\\bf k}^{\\mathrm{sym}}$ of the total spread $\\Omega$ w th respect to a symmetry-adapted gauge variation, which is then used to generate a search $\\mathrm{direction}\\mathcal{P}_{\\mathbf{k}}^{\\mathrm{sym}}$ . The symmetry-adapted gradient is given by \n\n$$\n\\mathcal{G}_{\\mathbf{k}}^{\\mathrm{sym}}=\\frac{1}{n_{\\mathbf{k}}}\\sum_{g=(\\mathcal{R}|\\mathbf{t})\\in G}D_{\\mathbf{k}}(g)\\mathcal{G}_{\\mathcal{R}\\mathbf{k}}D_{\\mathbf{k}}^{\\dagger}(g),\n$$ \n\nwhere $\\mathcal{G}_{\\mathbf{k}}$ is the original gradient given in Eq. (11), and $n_{\\mathbf{k}}$ is the number of symmetry operations in $G$ that leave $\\mathbf{k}$ fixed. It is worth noting that there is no guarantee that Eq. (32) can be satisfied for any irrep, for example, when one is considering a target energy window with a limited number of Bloch states whose symmetry might not be compatible with the irrep. \n\nIn the case of entangled bands, a similar two-step approach is taken as in the case of MLWFs (Sec. II B): first ΩI is minimised by selecting an optimal subspace of Bloch states that are required to transform according to Eq. (31), followed by minimisation of $\\widetilde\\Omega$ with respect to gauge variations that respect the site symmetries within this subspace, as described for the case of isolated bands above, but with the difference that the constraint of Eq. (32) is modified to \n\n$$\nU_{{\\bf k}}D_{{\\bf k}}(g_{{\\bf k}})=D_{{\\bf k}}(g_{{\\bf k}})U_{{\\bf k}},\\quad g_{{\\bf k}}\\in G_{{\\bf k}},\n$$ \n\nsince the states of the optimal subspace transform according to Eq. (31), rather than Eq. (29). An implementation of the SAWF algorithm for both isolated and entangled bands can be found in pw2wannier90, the interface code between Quantum ESPRESSO and Wannier90. A typical calculation consists of the following steps: (a) Define the symmetry operations of the site-symmetry group. These are either calculated by pw2wannier90.x, if the site-symmetry group is equivalent to the full space group of the crystal, or they can be provided in the .sym file (eg, if the site-symmetry group contains fewer symmetry operations than the full space group); (b) Specify the site location and orbital symmetry of the SAWFs. These are defined in the projection block of the Wannier90 input file .win file. (c) Run a preprocessing Wannier90 calculation to write this info into an intermediate file (with extension .nnkp) which is then read by pw2wannier90.x; (d) Run pw2wannier90.x to calculate the $\\mathbf{D}$ matrix in Eq. (31). pw2wannier90.x computes also the ˜d matrix in Eq. (30) from the Kohn–Sham states of the DFT calculation; (e) These matrixes are then written to a .dmn file which is read by Wannier90 at the start of the optimisation. \n\n# B. Selectively-localised Wannier functions and constrained Wannier centres \n\nWang et al. have proposed an alternative method23 to the symmetry-adapted Wannier functions described in Section III A. Their method permits the selective localisation of a subset of the Wannier functions, which may optionally be constrained to have specified centres. Whilst this method does not enforce or guarantee symmetry constraints, it has been observed in the cases that have been studied $^{23}$ that Wannier functions whose centres are constrained to a specific site typically possess the corresponding site symmetries. \n\nFor an isolated set of $J$ bands, selective localisation of a subset of $J^{\\prime}\\ \\leq\\ J$ Wannier functions is accomplished by minimising the total spread $\\Omega$ with respect to only $J^{\\prime}\\times J^{\\prime}$ degrees of freedom in the unitary matrix $U_{\\mathbf{k}}$ . The spread functional to minimise is then given by \n\n$$\n\\Omega^{\\prime}=\\sum_{n=1}^{J^{\\prime}\\leq J}\\left[\\langle w_{n\\mathbf{0}}|r^{2}|w_{n\\mathbf{0}}\\rangle-|\\langle w_{n\\mathbf{0}}|\\mathbf{r}|w_{n\\mathbf{0}}\\rangle|^{2}\\right],\n$$ \n\nwhich reduces to the original spread functional $\\Omega$ of Eq. (3) for $J^{\\prime}=J$ . When $J^{\\prime}
(a)MLWF (b) s-like SAWF(c) opt. SLWF(d) opt. SLWF+C
(e) MLWF(f) p-like SAWF(g)unopt. SLWF(h) unopt.SLWF+C (g), (h)
(a), (b), (c), (d) Method r
MLWF[A] [A2] (-0.857,0.857,0.857) 1.78[A2] [A2] (0.857,-0.857,0.857) 1.78 7.12
SAWF(-1.413,1.413,1.413) 1.64(-1.413,1.413,1.413) 2.8310.14
SLWF(-0.89, 0.89, 0.89)1.42 (0.89,-0.89,0.92) 2.149.8
SLWF+C(-1.413,1.413,1.413) 1.63(1.23,-1.23,1.08) 2.727.87
\n\nFIG. 1: Top (figure): comparison of two Wannier functions representatives resulting from different minimisation schemes for gallium arsenide (larger pink spheres: Ga cation atoms, smaller yellow spheres: \n\nAs anions): (a), (e) MLWF; (b), (f) SAWF; (c), (g) SLWF; (d), (h) SLWF $+$ C. For MLWF, SLWF and \nSLWF $^+$ C, four $s$ -type orbitals centred at the midpoints of the four Ga–As bonds \n((1/8,1/8,1/8),(1/8,1/8,-3/8),(-3/8,1/8,1/8),(1/8,-3/8,1/8)) were used as initial guess. In the case of SLWF and \nSLWF+C, we optimise the first WF (and also constrain its centre to sit at (1/4,1/4, $^1/4$ ), i.e. on the As \natom, for SLWF+C), while all the other WFs are left unoptimised. For SAWF, one $s$ -type and three \n$p$ -type orbitals centred on the As atom are used as initial guess. Specifically, the first row shows one \nMLWF (a), one SAWF with s character centred on As (b), one WF obtained with the selective localisation \nscheme (c) and one WF obtained obtained with the selective localisation scheme with additional \nconstraints on its centre (d). The second row shows one of the other three WFs for all four methods. In \nparticular: (e) MLWF, (f) SAWF with $p$ character, (g) unoptimised SAWF and (f) unoptimised SAWF+C. \nFor all plots we choose an isosurface level of $\\pm\\ 0.5\\mathrm{\\AA}^{-3/2}$ (blue for $^+$ values and red for $-$ values) using the \nVesta visualisation program28. Bottom (table): Cartesian coordinates of the centres $\\bar{\\mathbf{r}}$ and minimised \nindividual spreads $\\left\\langle r^{2}\\right\\rangle-\\bar{r}^{2}$ for the two representative Wannier functions of each of the four different \nminimisation schemes and initial guesses described above. We also report the total spread $\\Omega$ of all four \nvalence WFs2f0or each method. \n\n![](images/3cb264d668c72cb0abc1e910350d43788ca8bae2a474ae81d14e54402de5fa87.jpg) \nFIG. 2: Illustration of the parallelisation scheme for a $3^{\\prime}\\mathrm{\\times3}$ mesh of $k$ -points (black dots) and one MPI process per $k$ -point. The calculation of the M (k,b), $Z_{\\mathbf{k}}$ , $\\Delta W_{\\mathbf{k}}$ and $U_{\\mathbf{k}}$ matrices are distributed over processes by $k$ -point. The $U_{\\mathbf{k}\\pm\\mathbf{b}}$ matrices for the neighbouring $k$ -points are sent from process to process (orange arrows) for the calculation of the ${\\cal M}^{(\\mathbf{k},\\mathbf{b})}$ and $Z_{\\mathbf{k}}$ matrices. \n\nIn such a way, the memory requirement per core (for the ${\\cal M}^{(\\mathbf{k},\\mathbf{b})}$ matrices) decreases by a factor of approximately $N_{\\mathrm{c}}$ . \n\nMinimisation of the spread. The minimisation of the spread functional is based on an iterative steepest-descent or conjugate-gradient algorithm. In each iteration, the unitary matrices $U_{\\mathbf{k}}$ are updated according to $U_{\\mathbf{k}}=U_{\\mathbf{k}}\\exp{(\\Delta W_{\\mathbf{k}})^{15}}$ , where $\\Delta W_{\\mathbf{k}}=\\alpha\\mathcal{D}_{\\mathbf{k}}$ , see Eq. (15). Updating the $U_{\\mathbf{k}}$ matrices according to this equation is by far the most time-consuming part in the iterative minimisation algorithm, as it requires a diagonalisation of the $\\Delta W_{\\mathbf{k}}$ matrices. A significant speed-up can be obtained, however, by distributing the diagonalisation of the different $\\Delta W_{\\mathbf{k}}$ matrices over several processes, and performing the calculations fully in parallel. The evaluation of $\\Delta W_{\\mathbf{k}}$ essentially requires the calculation of the overlap matrices M (k,b), as discussed above. \n\nDisentanglement. The disentanglement procedure is concerned with finding the optimal subspace $\\dot{S}_{\\bf k}$ . As the functional $\\Omega_{\\mathrm{I}}$ measures the global subspace dispersion across the Brillouin zone, at first sight it is not obvious that the task of minimising the spread $\\Omega_{\\mathrm{I}}$ can be parallelised with respect to the $k$ -points. In the iterative algorithm of Eq. (21), the systematic reduction of the spread functional at the $i^{\\mathrm{th}}$ iteration is achieved by minimising the spillage of the subspace $S_{\\mathbf{k}}^{(i)}$ over the neighbouring subspaces from the previous iteration $S_{\\mathbf{k}+\\mathbf{b}}^{(i-1)}$ . This problem reduces to the diagonalisation of $N$ independent matrices ( $N$ is the total number of $k$ -points of the mesh), where an efficient speed-up of the disentanglement procedure can be achieved by distributing the diagonalisation of the $Z_{\\mathbf{k}}^{(i)}$ matrices of Eq. (23) over several processes, which can be done fully in parallel. Since the construction of $Z_{\\mathbf{k}}^{(i)}$ only requires the knowledge of the $U_{\\mathbf{k}+\\mathbf{b}}^{(i-1)}$ matrices, these must be communicated between processes, as shown in Fig. 2. This results in a similar time spent in communication for the disentanglement part of the code as for the wannierisation part. \n\nPerformance. We have tested the performance of this parallelisation scheme for the calculation of the MLWFs in a FeP $\\mathrm{t}(5)$ /P $\\mathrm{t}$ (18) thin film. Computational details were given in Ref. 29. The benchmarks have been performed on the JURECA supercomputer of the Ju¨lich Supercomputing Center. We have extracted an optimal subspace of dimension $J=414$ from a set of 580 Bloch states per $k$ -point. The upper limit of the inner window was set to 5 eV above the Fermi energy, and 414 MLWFs were constructed by minimising the spread $\\Omega$ . The performance benchmark was based on the average wall-clock time for a single iteration of the minimisation procedure (several thousand iterations are usually needed for convergence). We first analyse the weak scaling of our implementation, i.e., how the computation time varies with the number of cores $N_{\\mathrm{c}}$ for a fixed number of $k$ -points per process. We show in Fig. 3(a) the time per iteration for the disentanglement and wannierisation parts of the minimisation, always using one $k$ -point per process. As we vary the number of $k$ -points $N$ from 4 to 144, the computation time increases only by a factor of 1.3 and 1.8 for disentanglement and wannierisation, respectively. We then demonstrate the strong scaling of our parallelisation scheme in Fig. 3(b), i.e., how the computation time varies with the number of cores $N_{\\mathrm{c}}$ for a fixed number $N=$ 64 of $k$ -points. When varying the number of cores from 4 to 64, we observe a decrease of the computation time per iteration by a factor of 12.6 and 9.5 for disentanglement and wannierisation, respectively. The deviation from ideal scaling is mostly explained by the time spent in inter-core communication of the $U_{\\mathbf{k}+\\mathbf{b}}$ matrices. \n\n# IV. ENHANCEMENTS IN FUNCTIONALITY \n\nIn this section we describe a number of enhancements to the functionality of the core Wannier90 code, namely: the ability to compute and visualise spinor-valued WFs, in \n\n![](images/83a7fdd83a2c8173fc12de9f4010b9eebb2840db6203bb85cf313d0132107e3f.jpg) \n\nFIG. 3: Plots of the time per single minimisation iteration as a function of the number of cores $N_{\\mathrm{c}}$ . (a) Weak scaling of the implementation, where the number of $k$ -points per process is fixed to one, i.e., $N_{\\mathrm{c}}=N$ . The time only increases by a factor 1.3 (1.8) for the disentanglement (wannierisation) parts of the code, when going from $N_{\\mathrm{c}}=4$ to $N_{\\mathrm{c}}=144$ . (b) Strong scaling of the algorithm for a fixed number of $k$ -points $N=64$ . The time per iteration with one single CPU (serial) is reported in the figure. \n\ncluding developments to the interface with the Quantum ESPRESSO package to cover also the case of non-collinear spin calculations performed with ultrasoft pseudopotentials (previously not implemented); an improvement to the method for interpolating the $k$ -space Hamiltonian; the ability to select a subset from a larger set of projections of localised trial orbitals onto the Bloch states for initialising the WFs; and new functionality for plotting WFs in Gaussian cube format on WF-centred grids with non-orthogonal translation vectors. \n\n# A. Spinor-valued Wannier functions with ultrasoft and projector-augmented-wave pseudopotentials \n\nThe calculation of the overlap matrix in Eq. (17) within the ultrasoft-pseudopotential formalism proceeds via the inclusion of so-called augmentation functions,30 \n\n$$\n\\begin{array}{r l}{\\lefteqn{M_{m n}^{(\\mathbf{k},\\mathbf{b})}=\\left}}\\\\ &{+\\sum_{I i j}Q_{i j}^{I}(\\mathbf{b})\\left<\\psi_{m\\mathbf{k}}^{\\mathrm{ps}}|B_{I i j}^{(\\mathbf{k},\\mathbf{b})}|\\psi_{n,\\mathbf{k}+\\mathbf{b}}^{\\mathrm{ps}}\\right>,}\\end{array}\n$$ \n\nwhere $|\\psi_{m\\mathbf{k}}^{\\mathrm{ps}}\\rangle$ is the pseudo-wavefunction, \n\n$$\nQ_{i j}^{I}({\\bf b})=\\int\\mathrm{d}{\\bf r}\\ Q_{i j}^{I}({\\bf r})e^{-i{\\bf b}\\cdot{\\bf r}}\n$$ \n\nis the Fourier transform of the augmentation charge, and $B_{I i j}^{(\\mathbf{k},\\mathbf{b})}=|\\beta_{I i}^{\\mathbf{k}}\\rangle\\langle\\beta_{I j}^{\\mathbf{k}+\\mathbf{b}}|$ , where |βIki⟩ denotes the $i^{\\mathrm{th}}$ projector of the pseudopotential on the $I^{\\mathrm{th}}$ atom in the unit cell. We refer to Appendix B of Ref. 30 for detailed expressions. \n\nWhen spin-orbit coupling is included, the Bloch functions become two-component spinors $(\\psi_{n\\mathbf{k}}^{\\uparrow}(\\mathbf{r}),\\psi_{n\\mathbf{k}}^{\\downarrow}(\\mathbf{r}))^{\\mathrm{T}}$ , where $\\psi_{n\\bf{k}}^{\\sigma}({\\bf{r}})$ is the spin-up (for $\\sigma=\\uparrow$ ) or spin-down $\\mathrm{for}\\delta\\varepsilon=\\downarrow$ ) component with respect to the chosen spin quantisation axis. Accordingly, $Q_{i j}^{I}(\\mathbf{b})$ becomes $Q_{i j}^{I\\sigma\\sigma^{\\prime}}({\\bf b})$ (see Eq. (18) in Ref. 31) and Eq. (40) becomes \n\n$$\n\\begin{array}{l}{{\\displaystyle M_{m n}^{\\mathrm{({\\bfk},b)}}=\\left\\langle u_{m\\mathbf{k}}\\middle\\vert u_{n,{\\bf k}+{\\bf b}}\\right\\rangle}\\ ~}\\\\ {{\\displaystyle~+\\sum_{I i j\\sigma\\sigma^{\\prime}}Q_{i j}^{I\\sigma\\sigma^{\\prime}}({\\bf b})\\left\\langle\\psi_{m\\mathbf{k}}^{\\mathrm{ps},\\sigma}\\middle\\vert B_{I i j}^{\\mathrm{({\\bfk},b)}}\\middle\\vert\\psi_{n,{\\bf k}+{\\bf b}}^{\\mathrm{ps},\\sigma^{\\prime}}\\right\\rangle}.}}\\end{array}\n$$ \n\nThe above expressions, together with the corresponding ones for the matrix elements of the spin operator, have been implemented in the pw2wannier90.x interface between Quantum ESPRESSO and Wannier90. \n\nThe plotting routines of Wannier90 have also been adapted to work with the complexvalued spinor WFs obtained from calculations with spin-orbit coupling. It then becomes necessary to decide how to represent graphically the information contained in the two spinor components. \n\nOne option is to only plot the norm $|\\psi_{n\\mathbf k}(\\mathbf{r})|=\\sqrt{|\\psi_{n\\mathbf k}^{\\uparrow}(\\mathbf r)|^{2}+|\\psi_{n\\mathbf k}^{\\downarrow}(\\mathbf r)|^{2}}$ of spinor WFs, which is reminiscent of the total charge density in the case of a 2 $\\times$ 2 density matrix in non-collinear DFT. Another possibility is to plot independently the up- and downspin components of the spinor WF. Since each of them is in general complex-valued, two options are provided in the code: (i) to plot only the magnitudes $|\\psi_{n\\bf{k}}^{\\uparrow}({\\bf{r}})|$ and $|\\psi_{n\\bf{k}}^{\\downarrow}({\\bf{r}})|$ of the two components; or (ii) to encode the phase information by outputting $|\\psi_{n\\mathbf{k}}^{\\uparrow}(\\mathbf{r})|\\mathrm{sgn}(\\mathrm{Re}\\{\\psi_{n\\mathbf{k}}^{\\uparrow}(\\mathbf{r})\\})$ and $|\\psi_{n\\mathbf{k}}^{\\downarrow}(\\mathbf{r})|\\mathrm{sgn}(\\mathrm{Re}\\{\\psi_{n\\mathbf{k}}^{\\downarrow}(\\mathbf{r})\\})$ , where sgn is the sign function. Which of these various options is adopted by the Wannier90 code is controlled by two input parameters, wannier plot spinor mode and wannier plot spinor phase. \n\nFinally we note that, for WFs constructed from ultrasoft pseudopotentials or within the projector-augmented-wave (PAW) method, only pseudo-wavefunctions represented on the soft FFT grid are considered in plotting WFs within the present scheme, that is, the WFs are not normalised. We emphasise that this affects only plotting of the WFs in real-space and not the calculation of the MLWFs (the overlap matrices being correctly computed by the interface codes). \n\n# B. Improved Wannier interpolation by minimal-distance replica selection \n\nThe interpolation of band structures (and many other quantities) based on Wannier functions is an extremely powerful tool $32\\substack{-34}$ . In many respects it resembles Fourier interpolation, which uses discrete Fourier transforms to reconstruct faithfully continuous signals from a discrete sampling, provided that the signal has a finite bandwidth and that the sampling rate is at least twice the bandwidth (the so-called Nyquist–Shannon condition). \n\nIn the context of Wannier interpolation, the “sampled signal” is the set of matrix elements \n\n$$\nH_{m n\\mathbf k_{j}}=\\langle\\chi_{m\\mathbf k_{j}}|H|\\chi_{n\\mathbf k_{j}}\\rangle\n$$ \n\nof a lattice-periodic operator such as the Hamiltonian, defined on the same uniform grid $\\{\\mathbf{k}_{j}\\}$ that was used to minimise the Wannier spread functional (see Sec. II A). The states $|\\chi_{n\\mathbf{k}_{j}}\\rangle$ are the Bloch sums of the WFs, related to ab initio Bloch eigenstates by $|\\chi_{n\\mathbf{k}_{j}}\\rangle=$ $\\begin{array}{r}{\\sum_{m}|\\psi_{m\\mathbf{k}_{j}}\\rangle U_{m n\\mathbf{k}_{j}}}\\end{array}$ . \n\nTo reconstruct the “continuous signal” $H_{n m\\bf{k}}$ at arbitrary $\\mathbf{k}$ , the matrix elements of Eq. (43) are first mapped onto real space using the discrete Fourier transform \n\n$$\n\\widetilde{H}_{m n\\mathbf{R}}=\\langle w_{m\\mathbf{0}}|H|w_{n\\mathbf{R}}\\rangle=\\frac{1}{N}\\sum_{j=1}^{N}e^{-i\\mathbf{k}_{j}\\cdot\\mathbf{R}}H_{m n\\mathbf{k}_{j}},\n$$ \n\nwhere $N=N_{1}{\\times}N_{2}{\\times}N_{3}$ is the grid size (which is also the number of $k$ -points in Wannier90). The matrices $H_{m n\\mathbf{k}_{j}}$ are then interpolated onto an arbitrary $\\mathbf{k}$ using an inverse discrete Fourier transform, \n\n$$\nH_{m n\\mathbf{k}}=\\sum_{\\mathbf{R^{\\prime}}}e^{i\\mathbf{k}\\cdot\\mathbf{R^{\\prime}}}\\widetilde{H}_{m n\\mathbf{R^{\\prime}}},\n$$ \n\nwhere the sum is over $N$ lattice vectors $\\mathbf{R^{\\prime}}$ , and the interpolated energy eigenvalues are obtained by diagonalising $H_{\\mathbf{k}}$ . In the limit of an infinitely dense grid of $k$ -points the procedure is exact and the sum in Eq. (45) becomes an infinite series. Owing to the real-space localisation of the Wannier functions, the matrix elements ${\\widetilde{H}}_{m n\\mathbf{R}}$ become vanishingly small when the distance between the Wannier centres exceeds a critical value $L$ (the “bandwidth” of the Wannier Hamiltonian), so that actually only a finite number of terms contributes significantly to the sum in Eq. (45). This means that, even with a finite $N_{1}\\times N_{2}\\times N_{3}$ grid, the interpolation is still accurate provided that – by analogy with the Nyquist–Shannon condition – the “sampling rate” $N_{i}$ along each cell vector $\\mathbf{a}_{i}$ is sufficiently large to ensure that $N_{i}|\\mathbf{a}_{i}|>2L$ . \n\nStill, the result of the interpolation crucially depends on the choice of the $N$ lattice vectors to be summed over in Eq. (45). Indeed, when using a finite grid, there is a considerable freedom in choosing the set $\\{{\\bf{R}}^{\\prime}\\}$ as ${\\widetilde{H}}_{m n\\mathbf{R}}$ is invariant under ${\\mathbf{R}}\\rightarrow{\\mathbf{R}}+{\\mathbf{T}}$ for any vector T of the Born–von Karman superlattice generated by $\\left\\{\\mathbf{A}_{i}=N_{i}\\mathbf{a}_{i}\\right\\}$ . The phase factor in Eq. (45) is also invariant when $\\mathbf{k}\\in\\{\\mathbf{k}_{j}\\}$ , but not for arbitrary $\\mathbf{k}$ . Hence we need to choose, among the infinite set of “replicas” ${\\bf R}^{\\prime}={\\bf R}+{\\bf T}$ of $\\mathbf{R}$ , which one to include in Eq. (45). We take the original vectors $\\mathbf{R}$ to lie within the Wigner–Seitz supercell centred at the origin. If some of them fall on its boundary then their total number exceeds $\\varLambda$ and weight factors must be introduced in Eq. (45). For each combination of m, n and R, the optimal choice of $\\mathbf{\\vec{x}}$ is the one that minimises the distance \n\nbetween the two Wannier centres. With this choice, the spurious effects arising from the artificial supercell periodicity are minimised. \n\nEarlier versions of Wannier90 implemented a simplified procedure whereby the vectors $\\mathbf{R^{\\prime}}$ in Eq. (45) were chosen to coincide with the unshifted vectors $\\mathbf{R}$ that are closer to the origin than to any other point $\\mathbf{T}$ on the superlattice, irrespective of the WF pair $(m,n)$ . As illustrated in Fig. 4, this procedure does not always lead to the shortest distance between the pair of WFs, especially when some of the $N_{i}$ are small and the Wannier centres are far from the origin of the cell. \n\nWannier90 now implements an improved algorithm that enforces the minimal-distance condition of Eq. (46), yielding a more accurate Fourier interpolation. The algorithm is the following: \n\n(a) For each term in Eq. (45) pick, among all the replicas ${\\bf R}^{\\prime}={\\bf R}+{\\bf T}$ of $\\mathbf{R}$ , the one that minimises the distance between Wannier centres (Eq. (46)). \n(b) If there are $\\mathcal{N}_{m n\\mathbf{R}}$ different vectors $\\mathbf{T}$ for which the distance of Eq. (46) is minimal, then include all of them in Eq. (45) with a weight factor $1/\\mathscr{N}_{m n\\mathbf{R}}$ . \n\nAn equivalent way to describe these steps is that (a) we choose $\\mathbf{T}$ such that ${\\bf r}_{n}+{\\bf R}+{\\bf T}$ falls inside the Wigner–Seitz supercell centred at $\\mathbf{r}_{m}$ (see Fig. 4), and that (b) if it falls on a face, edge or vertex of the Wigner–Seitz supercell, we keep all the equivalent replicas with an appropriate weight factor. In practice the condition in step (b) is enforced within a certain \n\n![](images/2b28354059a4b3a9b92d754935c051312bfe3a5bc37d94fc1d826da19c8b9d2e.jpg) \n\nFIG. 4: Owing to the periodicity of the Wannier functions over the Born-von Karman supercell (with size $2\\times2$ here), the matrix element $\\widetilde{H}_{m n}$ describes the interaction between the $m^{\\mathrm{th}}$ WF $w_{m\\mathbf{0}}$ (shown in orange) with ce tre $\\mathbf{r}_{m}$ inside the home unit cell $\\mathbf R=\\mathbf0$ (green shaded area) and the $n^{\\mathrm{th}}$ WF $w_{n\\mathbf{R}}$ (shown in blue) centred inside the unit cell $\\mathbf{R}$ , or any of its supercell-periodic replicas displaced by a superlattice vector $\\mathbf{\\vec{\\nabla}}^{r}\\mathbf{\\vec{r}}$ . When performing Wannier interpolation, we now impose a minimal-distance condition by choosing the replica $w_{n,\\mathbf{R}+\\mathbf{T}}$ of $w_{n\\mathbf{R}}$ whose centre lies within the Wigner–Seitz supercell centred at $\\mathbf{r}_{m}$ (thick orange line). \n\ntolerance, to account for the numerical imprecision in the values of the Wannier centres and in the definition of the unit cell vectors. Although step (b) is much less important than (a) for obtaining a good Fourier interpolation, it helps ensuring that the interpolated bands respect the symmetries of the system; if step (b) is skipped, small artificial band splittings may occur at high-symmetry points, lines, or planes in the BZ. \n\nThe procedure outlined above amounts to replacing Eq. (45) with \n\n$$\nH_{m n\\mathbf{k}}=\\sum_{\\mathbf{R}}\\frac{1}{\\mathcal{N}_{m n\\mathbf{R}}}\\sum_{j=1}^{\\mathcal{N}_{m n\\mathbf{R}}}e^{i\\mathbf{k}\\cdot(\\mathbf{R}+\\mathbf{T}_{m n\\mathbf{R}}^{(j)})}\\widetilde{H}_{m n\\mathbf{R}},\n$$ \n\nwhere {T(mj)nR} are the NmnR vectors T that minimise the distance of Eq. (46) for a given combination of $\\mathcal{W}$ , $n$ and $\\mathbf{R}$ ; $\\mathbf{R}$ lies within the Wigner–Seitz supercell centred on the origin. \n\nThe benefits of this modified interpolation scheme are most evident when considering a large unit cell sampled at the $\\Gamma$ point only. In this case $N=1$ so that Eq. (45) with $\\{{\\bf R}^{\\prime}\\}=\\{{\\bf R}\\}=\\{{\\bf0}\\}$ would reduce to $H_{m n\\mathbf{k}}=\\tilde{H}_{m n\\mathbf{0}}$ , yielding interpolated bands that do not disperse with $\\mathbf{k}$ . This is nonetheless an artefact of the choice $\\{{\\bf R}^{\\prime}\\}=\\{{\\bf0}\\}$ (of earlier versions of Wannier90) and not an intrinsic limitation of Wannier interpolation, as first \n\n![](images/f0cc3e39e1a67dd96b8a509c208d9ba668c46da79a2a108c5ffbc31a48bf8076.jpg) \n\nFIG. 5: Comparison between the bands obtained using the earlier interpolation procedure (blue lines), those obtained using the (current) modified approach of Eq. (47) (orange \nlines), and the ab initio bands (black crosses). (a) Linear chain of carbon atoms, with 12 atoms per unit cell (separated by a distance of 1.3 ˚A along the z direction) and $\\Gamma$ -point \nsampling. 36 Wannier functions have been computed starting from projections over $p_{x}$ and \n$p_{y}$ orbitals on carbon atoms and $s$ -orbitals midbond between them. A frozen window up to \nthe Fermi energy (set to zero in the plot) has been considered, while the disentanglement \nwindow included all states up to 14 eV above the Fermi level. (b) Bulk silicon, with the BZ sampled on an unconverged $3\\times3\\times3$ grid of $k$ -points. \n\ndemonstrated in Ref. 32 for one-dimensional systems. Indeed, equation (47), which in a sense extends Ref. 32 to any spatial dimension, becomes in this case \n\n$$\nH_{m n\\mathbf{k}}=\\frac{\\widetilde{H}_{m n\\mathbf{0}}}{\\mathcal{N}_{m n\\mathbf{0}}}\\sum_{j=1}^{\\mathcal{N}_{m n\\mathbf{0}}}e^{i\\mathbf{k}\\cdot\\mathbf{T}_{m n\\mathbf{0}}^{(j)}},\n$$ \n\nwhich can produce dispersive bands. This is illustrated in Fig. 5(a) for the case of a onedimensional chain of carbon atoms: the interpolated bands obtained from Eq. (45) with $\\{{\\bf R}^{\\prime}\\}=\\{{\\bf R}\\}=\\{{\\bf0}\\}$ (earlier version of Wannier90) are flat, while those obtained from Eq. (47) (new versions of Wannier90) are in much better agreement with the dispersive ab initio bands up to a few eV above the Fermi energy. \n\nClear improvements in the interpolated bands are also obtained for bulk solids, as shown in Fig. 5(b) for the case of silicon. The earlier implementation breaks the two-fold degeneracy along the X W line, with one of the two bands becoming flat. The new procedure recovers the correct degeneracies, and reproduces more closely the ab initio band structure (the remaining small deviations are due to the use of a coarse $k$ -point mesh that does not satisfy the Nyquist–Shannon condition, and would disappear for denser $k$ -grids together with the differences between the two interpolation procedures). \n\n# C. Selection of projections \n\nIn many cases, and particularly for entangled bands, it is necessary to have a good initial guess for the MLWFs in order to properly converge the spread to the global minimum. Determining a good initial guess often involves a trial and error approach, using different combinations of orbital types, orientations and positions. While for small systems performing many computations of the projection matrices is relatively cheap, for large systems there is a cost associated with storing and reading the wavefunctions to compute new projection matrices for each new attempt at a better initial guess. Previously, the number of projections that could be specified had to be equal to the number J of WFs to be constructed. The latest version of the code lifts this restriction, making it possible to define in the pre-processing step a larger number $J_{+}>J$ of projection functions to consider as initial guesses. In this way, the computationally expensive and potentially I/O-heavy construction of the projection matrices $A_{\\mathbf{k}}$ is performed only once for all possible projections that a user would like to consider. \n\nOnce the $A_{\\mathbf{k}}$ matrices (of dimension $J\\times J_{+}$ at each $\\mathbf{k}$ ) have been obtained, one proceeds with constructing the MLWFs by simply selecting, via a new input parameter (select projections) of the Wannier90 code, which $J$ columns to use among the $J_{+}$ that were computed by the interface code. Experimenting with different trial orbitals can thus be achieved by simply selecting a different set of projections within the Wannier90 input file, without the need to perform the pre-processing step again. \n\nSimilarly, another use case for this new option is the construction of WFs for the same material but for different groups of bands. Typically one would have to modify the Wannier90 input file and run the interface code multiple times, while now the interface code may compute $A_{\\mathbf{k}}$ for a superset of trial orbitals just once, and then different subsets may be chosen by simple modification of a single input parameter. As a demonstration, we have adapted example11 of the Wannier90 distribution (silicon band structure), that considers two band groups: (a) the valence bands only, described by four bond-centred $s$ orbitals, and (b) the four valence and the four lowest-lying conduction bands together, described by atom-centred $\\boldsymbol{s p}^{3}$ orbitals. In the example, projections onto all 12 trial orbitals are provided, and the different cases are covered by specifying in the Wannier90 input file which subset of projections is required. \n\n# D. Plotting cube files with non-orthogonal vectors \n\nIn Wannier90 v3.0 it is possible to plot the MLWFs in real-space in Gaussian cube format, including the case of non-orthogonal cell lattice vectors. Many modern visualisation programs such as Vesta $^{\\mathrm{28}}$ are capable of handling non-orthogonal cube files and the cube file format can be read by many computational chemistry programs. Wannier90’s representation of MLWFs in cube format can be significantly more compact than using the alternative xsf format. With the latter, MLWFs are calculated (albeit with a coarse sampling) on a supercell of the computational cell that can be potentially large (the extent of the supercell is controlled by an input parameter wannier plot supercell). Whereas, with the cube format, each Wannier function is represented on a grid that is centred on the Wannier function itself and has a user-defined extent, which is the smallest parallelepiped (whose sides are aligned with the cell vectors) that can enclose a sphere with a user-defined radius wannier plot radius. Because MLWFs are strongly localised in real space, relatively small cut-offs are all that is required, significantly smaller than the length-scale over which the MLWFs themselves are periodic. As a result, the cube format is particularly useful when a more memory-efficient representation is needed. The cube format can be activated by setting the input parameter wannier plot mode to cube, and the code can handle both isolated molecular systems (treated within the supercell approximation) as well as periodic crystals by setting wannier plot mode to either molecule or crystal, respectively. \n\n# V. NEW POST-PROCESSING FEATURES \n\nOnce the electronic bands of interest have been disentangled and wannierised to obtain well-localised WFs, the Wannier90 software package includes a number of modules and utilities that use these WFs to calculate various electronic-structure properties. Much of this functionality exists within postw90.x, an MPI-parallel code that forms an integral part of the Wannier90 package. In v2.x of Wannier90, postw90.x included functionality for computing densities of states and partial densities of states, energy bands and Berry curvature along specified lines and planes in $k$ -space, anomalous Hall conductivity, orbital magnetisation and optical conductivity, Boltzmann transport coefficients within the relaxation time approximation, and band energies and derivatives on a generic user-defined list of $k$ -points. Some further functionality exists in a set of utilities that are provided as part of the Wannier90 package, including a code (w90pov.F90) to plot WFs rendered using the Persistence of Vision Raytracer (POV-Ray) $^{35}$ code and to compute van der Waals interactions with WFs (w90vdw.F90). \n\nIn addition, there are a number of external packages for computing advanced properties based on WFs and which interface to Wannier90. These include codes to generate tight-binding models such as pythTB $^{36}$ and tbmodels37, quantum transport codes such as sisl $^{38}$ , gollum $^{39}$ , omen $^{40}$ and nanoTCAD-ViDES41, the EPW $^{42}$ code for calculating properties related to electron-phonon interactions and WannierTools $^{43}$ for the investigation of novel topological materials. \n\nBelow we describe some of the new post-processing features of Wannier90 that have been introduced in the latest version of the code, v3.0. \n\n# A. postw90.x: Shift Current \n\nThe photogalvanic effect (PGE) is a nonlinear optical response that consists in the generation of a direct current (DC) when light is absorbed. $^{44-46}$ It can be divided phenomenologically into linear (LPGE) and circular (CPGE) effects, which have different symmetry requirements within the acentric crystal classes. The CPGE requires elliptically-polarised light, and occurs in gyrotropic crystals (see next subsection). The LPGE occurs with linearly or unpolarised light as well; it is present in piezoelectric crystals and is given by \n\n$$\nJ_{a}(0)=2\\sigma_{a b c}(0;\\omega,-\\omega)E_{b}(\\omega)E_{c}(-\\omega),\n$$ \n\nwhere $\\mathbf{J}(0)$ is the induced DC photocurrent density, $\\mathbf{E}(\\omega)=\\mathbf{E}^{*}(-\\omega)$ is the amplitude of the optical electric field, and $\\sigma_{a b c}=\\sigma_{a c b}=\\sigma_{a b c}^{*}$ is a nonlinear photoconductivity tensor. \n\nThe shift current is the part of the LPGE photocurrent generated by interband light absorption.47 Intuitively, it arises from a coordinate shift accompanying the photoexcitation of electrons from one band to another. Like the intrinsic anomalous Hall effect48, the shift current involves off-diagonal velocity matrix elements between occupied and empty bands, depending not only on their magnitudes but also on their phases49–52. \n\nThe shift current along direction $a$ induced by light that is linearly polarised along $b$ is described by the following photoconductivity tensor:52,53 \n\n$$\n\\begin{array}{l}{{\\displaystyle\\sigma_{a b b}^{\\mathrm{shift}}(0;\\omega,-\\omega)=-\\frac{\\pi|e|^{3}}{\\hbar^{2}}\\int_{\\mathrm{BZ}}\\frac{\\mathrm{d}\\mathbf{k}}{(2\\pi)^{3}}\\sum_{n,m}f_{n m\\mathbf{k}}R_{n m\\mathbf{k}}^{a b}}}\\\\ {{\\displaystyle~\\times~\\left|r_{n m\\mathbf{k}}^{b}\\right|^{2}\\delta(\\omega_{m n\\mathbf{k}}-\\omega).}}\\end{array}\\overset{\\longleftrightarrow}{\\underbrace{(\\mathbf{e}_{\\mathbf{\\Gamma}}\\mathbf{e}_{\\mathbf{\\Gamma}})}}~,\n$$ \n\nHere, $f_{n m\\mathbf{k}}=f_{n\\mathbf{k}}-f_{m\\mathbf{k}}$ is the difference between occupation factors, $\\hbar\\omega_{m n\\bf{k}}=\\epsilon_{m\\bf{k}}-\\epsilon_{n\\bf{k}}$ is the difference between energy eigenvalues of the Bloch bands, rbnmk is the bth Cartesian component of the interband dipole matrix (the off-diagonal part of the Berry connection matrix $\\mathbf{A}_{n m\\mathbf{k}}=i\\langle u_{n\\mathbf{k}}|\\partial_{\\mathbf{k}}u_{m\\mathbf{k}}\\rangle,$ ), and \n\n$$\nR_{n m\\mathbf k}^{a b}=\\partial_{k_{a}}\\arg\\left(r_{n m\\mathbf k}^{b}\\right)-A_{n n\\mathbf k}^{a}+A_{m m\\mathbf k}^{a}\n$$ \n\nis the shift vector (not to be confused with the lattice vector $\\mathbf{R}$ , or with the matrix $R^{(\\mathbf{k},\\mathbf{b})}$ defined in Eq. (12)). The shift vector has units of length, and it describes the real-space shift of wavepackets under photoexcitation. \n\nThe numerical evaluation of Eq. (51) is tricky because the individual terms therein are gauge-dependent, and only their sum is unique. Different strategies were discussed in the early literature in the context of model calculations $^{51,54}$ and more recently for ab initio calculations. The ab initio implementation of Young and Rappe $^{55}$ employed a gauge-invariant $k$ -space discretisation of Eq. (51), inspired by the discretised Berry-phase formula for electric polarisation.56 \n\nThe implementation in Wannier90 is based instead on the formulation of Sipe and coworkers.52,57 In this formulation, the shift (interband) contribution to the LPGE tensor in Eq. (49) is expressed as \n\n$$\n\\begin{array}{l}{\\displaystyle{\\sigma_{a b c}^{\\mathrm{shift}}(0;\\omega,-\\omega)=\\frac{i\\pi|e|^{3}}{4\\hbar^{2}}\\int_{\\mathrm{BZ}}\\frac{\\mathrm{d}\\mathbf{k}}{(2\\pi)^{3}}\\sum_{n,m}f_{n m\\mathbf{k}}}}\\\\ {\\displaystyle{\\qquad\\times\\left(r_{m n\\mathbf{k}}^{b}r_{n m\\mathbf{k}}^{c;a}+r_{m n\\mathbf{k}}^{c}r_{n m\\mathbf{k}}^{b;a}\\right)}}\\\\ {\\displaystyle{\\qquad\\times\\left[\\delta(\\omega_{m n\\mathbf{k}}-\\omega)+\\delta(\\omega_{n m\\mathbf{k}}-\\omega)\\right],}}\\end{array}\n$$ \n\n$$\nr_{n m\\mathbf{k}}^{b;a}=\\partial_{k_{a}}r_{n m\\mathbf{k}}^{b}-i\\left(A_{n n\\mathbf{k}}^{a}-A_{m m\\mathbf{k}}^{a}\\right)r_{n m\\mathbf{k}}^{b}\n$$ \n\nis the generalised derivative of the interband dipole. When $b=c$ , Eq. (52) becomes equivalent to Eq. (50).52 \n\nThe generalised derivative $r_{n m\\mathbf{k}}^{b;a}$ is a well-behaved (covariant) quantity under gauge transformation but – as in the case of the shift vector – this is not the case for the individual terms in Eq. (53), leading to numerical instabilities. To circumvent this problem, Sipe and co-workers used $\\mathbf{k}\\cdot\\mathbf{p}$ perturbation theory to recast Eq. (53) as a summation over intermediate virtual states where the individual terms are gauge covariant.52,57 That strategy has been successfully employed to evaluate the shift-current spectrum from first principles.58,59 \n\nAs it is well known, similar “sum-over-states” expressions can be written for other quantities involving k derivatives, such as the inverse effective-mass tensor and the Berry curvature. When evaluating those expressions, a sufficient number of virtual states should be included to achieve convergence. Alternatively, one can work with a basis spanning a finite number of bands, such as a tight-binding or Wannier basis, and carefully reformulate $\\mathbf{k}\\cdot\\mathbf{p}$ perturbation theory within that incomplete basis to avoid truncation errors. This reformulation was carried out in Ref. 60 for the inverse effective-mass tensor, and in Ref. 33 for the Berry curvature; the formalism of Ref. 33 is at the core of the berry.F90 module of postw90, where Berry curvatures and related quantities are computed by Wannier interpolation. The same interpolation strategy was used in Refs. 61 and 62 to evaluate Eq. (52), and the approach of Ref. 62 is now implemented in the berry.F90 module. \n\n# B. postw90.x: Gyrotropic module \n\nIn the previous subsection we considered the shift current, an effect that occurs in piezoelectric crystals. Here we turn to a host of effects that occur in a different group of acentric crystals: those belonging to the gyrotropic crystal classes, which include the chiral, polar, and optically-active crystal classes.44 \n\nTo motivate the gyrotropic effects considered below, let us start from the more familiar magneto-optical effects. To review, the spontaneous magnetisation of ferromagnets endows their conductivity tensor $\\sigma_{a b}(\\omega)$ with an antisymmetric part. In the DC limit this antisymmetric conductivity describes the anomalous Hall effect (AHE), and at finite frequencies it describes magneto-optical effects such as Faraday rotation in transmission and magnetic circular dichroism in absorption. In paramagnets, those effects appear under applied magnetic \n\nfields. \n\nAs first pointed out in Refs. 63 and 64, an antisymmetric conductivity can be induced in certain nonmagnetic (semi)conductors by purely electrical means: by passing a current through the sample. Symmetry arguments indicate that this is allowed in the gyrotropic crystal classes, and the first experimental demonstration consisted in the measurement of a current-induced change in the rotatory power of $p$ -doped trigonal tellurium.65,66 When linearly polarised light of frequency $\\omega$ propagates along the trigonal ˆz axis in the presence of a current density $\\mathbf{j}=j_{z}\\hat{\\mathbf{z}}$ , the change in rotatory power is proportional to $\\widetilde{D}_{z z}(\\omega)j_{z}$ , where \n\n$$\n\\widetilde{D}_{a b}(\\omega)=\\int_{\\mathrm{BZ}}\\frac{\\mathrm{d}\\mathbf{k}}{(2\\pi)^{3}}\\sum_{n}f_{0}(\\epsilon_{n\\mathbf{k}})\\partial_{k_{a}}\\widetilde{\\Omega}_{n\\mathbf{k}}^{b}(\\omega).\n$$ \n\nIn this expression $f_{0}$ is the equilibrium occupation factor, and \n\n$$\n\\widetilde{\\Omega}_{n\\mathbf{k}}(\\omega)=-\\sum_{m}\\frac{\\omega_{m n\\mathbf{k}}^{2}}{\\omega_{m n\\mathbf{k}}^{2}-\\omega^{2}}\\mathrm{Im}[\\mathbf{A}_{n m\\mathbf{k}}\\times\\mathbf{A}_{m n\\mathbf{k}}],\n$$ \n\nwhere $\\mathbf{A}_{n m\\mathbf{k}}$ is the Berry connection matrix introduced in Sec. V A. At zero frequency, $\\widetilde{\\Omega}_{n\\mathbf{k}}(\\omega)$ reduces to the Berry curvature $\\Omega_{n\\mathbf k}=\\pmb{\\nabla}_{\\mathbf k}\\times\\mathbf k_{n n\\mathbf k}$ . \n\nThe DC or transport limit of this current-induced Faraday effect is the current-induced AHE, or nonlinear $A H E^{67-71}$ . Like the linear (spontaneous) AHE in ferromagnetic metals, the nonlinear (current-induced) AHE in gyrotropic conductors has an intrinsic contribution associated with the Berry curvature. It is given by $j_{a}\\propto\\tau\\varepsilon_{a d c}D_{b d}E_{b}E_{c}$ , where $\\mathbf{E}$ is the electric field, $\\tau$ is the relaxation time of the conduction electrons, $\\varepsilon_{a b c}$ is the alternating tensor, and $D_{a b}=\\widetilde{D}_{a b}(\\omega=0)$ is the “Berry-curvature dipole.”67 After performing an integration by parts in Eq. (54), the quantities $D_{a b}$ and $\\widetilde{D}_{a b}(\\omega)$ can be easily evaluated with the help of the berry.F90 module. \n\nAlong with nonlinear magneto-optical and anomalous Hall effects, the flow of electrical current in a gyrotropic conducting medium also generates a net magnetisation. This kinetic magnetoelectric effect was originally proposed for bulk chiral conductors,64,72 and later for two-dimensional (2D) inversion layers with an out-of-plane polar axis $^{73,74}$ , where it has been studied intensively75. The kinetic magnetoelectric effect in 2D – also known as the Edelstein effect – is a purely spin effect, whereas in bulk crystals an orbital contribution is also present.72 The orbital kinetic magnetoelectric effect is given by $M_{a}\\propto\\tau K_{b a}E_{b}$ , where the tensor $\\vec{K}_{a b}$ is obtained from $D_{a b}$ by replacing the Berry curvature with the intrinsic magnetic moment of the Bloch states, $^{76-78}$ a quantity that is also provided by the berry.F90 module.79 \n\nAnother phenomenon characteristic of gyrotropic crystals is the circular photogalvanic effect (CPGE) that was mentioned briefly in Sec. V A. This nonlinear optical effect consists in the generation of a photocurrent that reverses sign with the helicity of light44–46,64,80, and it occurs when light is absorbed via interband or intraband scattering processes. The intraband contribution to the CPGE can be expressed in terms of the Berry curvature dipole as $\\begin{array}{r}{j_{a}\\propto\\frac{\\omega\\tau^{2}D_{a b}}{1+\\omega^{2}\\tau^{2}}\\mathrm{Im}\\left[\\mathbf{E}(\\omega)\\times\\mathbf{E}^{*}(\\omega)\\right]_{b}}\\end{array}$ .67,81,82 \n\nThe above effects are being very actively investigated in connection with novel materials ranging from topological semimetals68,83,84 to monolayer and bilayer transition-metal dichalcogenides $69–71$ . The sensitivity of both the Berry curvature and the intrinsic orbital moment to the details of the electronic structure, together with the need to sample them on a dense mesh of $k$ -points, calls for the development of accurate and efficient ab initio methodologies, and the Wannier interpolation technique is ideally suited for this task. \n\nThe Wannier interpolation methodology for gyrotropic effects was presented in Ref. 78, where it was applied to $p$ -doped trigonal tellurium, and the resulting computer code has been incorporated in postw90 as the gyrotropic.F90 module. The reader is referred to Ref. 78 for more details such as the prefactors in the expressions above, as well as the formulas for natural optical activity, which has also been implemented in the same module. \n\n# C. postw90.x: Spin Hall conductivity \n\nThe spin Hall effect (SHE) is a phenomenon in which a spin current is generated by applying an electric field. The current is often transverse to the field (Hall-like), but this is not always the case.85 The SHE is characterised by the spin Hall conductivity (SHC) tensor $\\sigma_{a b}^{\\mathrm{spin},c}$ as follows: \n\n$$\nJ_{a}^{\\mathrm{spin},c}(\\omega)=\\sigma_{a b}^{\\mathrm{spin},c}(\\omega)E_{b}(\\omega),\n$$ \n\nwhere ${\\cal J}_{a}^{\\mathrm{spin},c}$ is the spin-current density along direction $a$ with its spin pointing along $c$ , and $E_{b}$ is the external electric field of frequency $\\omega$ applied along $b$ . In non-magnetic materials the equal number of up- and down-spin electrons forces the AHE to vanish, resulting in a pure spin current. \n\nLike the AHC, the SHC contains both intrinsic and extrinsic contributions. $^{86}$ The intrinsic contribution to the SHC can be calculated from the following Kubo formula,87 \n\n![](images/38fd8ded5dbec1381433317428efa194299fcb49f1c6a171056185aaae6fa564.jpg) \n\n$$\n\\begin{array}{l}{\\sigma_{a b}^{\\mathrm{spin},c}(\\omega)=-\\displaystyle\\frac{e^{2}}{\\hbar}\\frac{1}{V N}\\sum_{\\mathbf{k}}\\sum_{n}f_{n\\mathbf{k}}\\Omega_{n\\mathbf{k},a b}^{\\mathrm{spin},c}(\\omega),\\qquad}\\\\ {\\Omega_{n\\mathbf{k},a b}^{\\mathrm{spin},c}(\\omega)=\\hbar^{2}\\sum_{m\\neq n}\\frac{-2\\mathrm{Im}[\\langle\\psi_{n\\mathbf{k}}|\\frac{2}{\\hbar}j_{a}^{\\mathrm{spin},c}|\\psi_{m\\mathbf{k}}\\rangle\\langle\\psi_{m\\mathbf{k}}|v_{b}|\\psi_{n\\mathbf{k}}\\rangle]}{(\\epsilon_{n\\mathbf{k}}-\\epsilon_{m\\mathbf{k}})^{2}-(\\hbar\\omega+i\\eta)^{2}},\\qquad}\\end{array}\n$$ \n\nwhere $s_{c}$ , $v_{a}$ and $\\begin{array}{r}{j_{a}^{\\mathrm{spin,}c}=\\frac{1}{2}\\{s_{c},v_{a}\\}}\\end{array}$ are the spin, velocity and spin current operators, respectively; $V$ is the cell volume, and $N$ is the total number of $k$ -points used to sample the BZ. Equations (57) are very similar to the Kubo formula for the AHC, except for the replacement of a velocity matrix element by a spin-current matrix element. As mentioned in the previous two subsections, Wannier-interpolation techniques are very efficient at calculating such quantities. \n\nA Wannier-interpolation method scheme for evaluating the intrinsic SHC was developed in Ref. 87 (see also Ref. 88 for a related but independent work). The required quantities from the underlying ab initio calculation are the spin matrix elements S(m0)nk,a $S_{m n\\mathbf k,a}^{(0)}=\\langle\\psi_{m\\mathbf k}^{(0)}|s_{a}|\\psi_{n\\mathbf k}^{(0)}\\rangle$ , the Hamiltonian matrix elements $H_{m n\\mathbf{k}}^{(0)}=\\langle\\psi_{m\\mathbf{k}}^{(0)}|H|\\psi_{n\\mathbf{k}}^{(0)}\\rangle=\\epsilon_{m\\mathbf{k}}^{(0)}\\delta_{m n}$ , and the overlap matrix elements of Eq. (17). Since the calculation of all these quantities has been previously implemented in pw2wannier90.x (the interface code between pwscf and Wannier90), this advantageous interpolation scheme can be readily used while keeping to a minimum the interaction between the ab initio code and Wannier90. \n\nThe application of the method to fcc Pt is illustrated in Fig. 6. Panel (a) shows the calculated SHC as a function of the Fermi-level position, and panel (b) depicts the “spin Berry curvature” of Eq. (57b) that gives the contribution from each band state to the SHC. The aforementioned functionalities have been incorporated in the berry.F90, kpath.F90 and kslice.F90 modules of postw90.x. \n\n# D. postw90.x: Parallelisation improvements \n\nThe original implementation of the berry.F90 module in postw90.x (for computing Berry-phase properties such as orbital magnetisation and anomalous Hall conductivity $^{79}$ ), introduced in Wannier90 v2.0, was written with code readability in mind and had not been optimised for computational speed. In Wannier90 v3.0, all parts of the berry.F90 module have been parallelised while keeping the code readable; moreover, its scalability has been improved, accelerating its performance by several orders of magnitude.89 \n\n![](images/727a7b6b3d2529ded471b32bc7c0a9bd15bcd1f46e24d37d47c6f4b5b4a7da6b.jpg) \n\nFIG. 6: (a) Intrinsic spin Hall conductivity $\\sigma_{x y}^{\\mathrm{spin,}z}$ of fcc Pt, plotted as a function of the shift in Fermi energy relative to its self-consistent value. (b) Band structure of fcc $\\mathrm{Pt}$ , colour-coded by a dimensionless function $r(\\Omega_{n\\mathbf{k},x y}^{\\mathrm{spun},z})$ of the spin Berry curvature [Eq. (57b)]. The function $r(x)$ is equal to $x/10$ when $|x|<10,\\mathrm{andto}\\log_{10}(|x|)\\mathrm{sgn}(x)$ when $|x|\\geq10$ . \n\nTo illustrate the improvements in performance we present calculations on a 128-atom supercell of GaAs interstitially doped with Mn (we emphasise that here we are not interested in the results of the calculation but simply on its performance testing, and that the choice of the system does not affect the scaling results that we report). We use a lattice constant of the elementary cell of 5.65 ˚A. We use norm-conserving relativistic pseudopotentials with the PBE exchange-correlation functional. The energy cut-off for the plane waves is set to 40 Ry, and the Brillouin-zone sampling of the supercell is $3\\times3\\times3$ . We use a Gaussian metallic smearing with a broadening of 0.015 Ry. For the non-self-consistent step of the calculation, 600 bands are computed and used to construct 517 Wannier functions. The initial projections are chosen as a set of $s p^{3}$ orbitals centred on each Ga and As atom, and a set of $d$ orbitals on Mn. The calculations were performed on the Prometheus supercomputer of PL-GRID (in Poland). The code was compiled with the Intel ifort compiler (v15.0.2), using the OpenMPI libraries (v1.8.4) and BLAS/LAPACK routines from Intel MKL (v11.3.1). \n\nThe Berry-phase calculations can be performed in three distinct ways: (i) 3D quantities in $k$ -space (routine berry main), (ii) the same quantities resolved on 2D planes (routine kslice.F90), and (iii) 1D paths (routine kpath.F90) in the Brillouin zone. In the benchmarks, we will refer to these three cases as “Berry 3D”, “Berry 2D”, and “Berry 1D”, \n\nrespectively. \n\nThe first optimisation target was the function utility rotate in the module utility.F90, which calculates a matrix product of the form $B=R^{\\dagger}A R$ using Fortran’s built-in matmul function. The new routine utility rotate new uses instead BLAS and performs about 5.7 times better than the original one, giving a total speedup for berry main of about $55\\%$ . \n\nA second performance-critical section of code was identified in the routine get imfgh k list which took more than $50\\%$ of the total run-time of berry main. This routine computes three quantities: $F_{\\alpha\\beta}$ , $G_{\\alpha\\beta}$ and $H_{\\alpha\\beta}$ , which are defined in Eqs. (51), (66) and (56) of Ref. 79. By some algebraic transformations, it was possible to reduce 25 calls to matmul, carried out in the innermost runtime-critical loop, to only 5 calls. After replacement of matmul with the Basic Linear Algebra Subprogram (BLAS), the speed up of this routine exceeds a factor of 11, and the total time spent in berry main is 2.5 times shorter (including the speed-up from the first optimisation). \n\nIn the third step, a bottleneck was eliminated in the initialisation phase, where mpi bcast was waiting more than two minutes for the master rank to broadcast the parameters. The majority of this time was spent in loops computing matrix products of the form $S=(V_{1})^{\\dagger}S_{0}V_{2}$ . Again, we replaced this with two calls to the BLAS gemm routine. This resulted in a speed-up of a factor of 610 for the calculation of this matrix product in our test case, and the total initialisation time dropped to less than 15 seconds. In total, the berry main routine runs about 5 times faster than it did originally. \n\nFinally, the routines kslice.F90 and kpath.F90 were parallelised. The scalability results of berry main, kslice.F90 and kpath.F90 are presented in Fig. 7, and a comparison with the scalability of the previous version of berry main is also given. Absolute times for some of the calculations are reported in Table I. \n\n# E. GW bands interpolation \n\nWhile density-functional theory (DFT) is the method of choice for most applications in materials modelling, it is well known that DFT is not meant to provide spectral properties such as band structures, band gaps and optical spectra. Green’s function formulation of many-body perturbation theory (MBPT) $^{90}$ overcomes this limitation, and allows the excitation spectrum to be obtained from the knowledge of the Green’s function. Within \n\nMBPT the interacting electronic Green’s function $G(\\mathbf{r},\\mathbf{r}^{\\prime},\\omega)$ may be expressed in terms of the non-interacting Green’s function $G^{0}({\\bf r},{\\bf r}^{\\prime},\\omega)$ and the so-called self-energy $\\Sigma(\\mathbf{r},\\mathbf{r}^{\\prime},\\omega)$ , where several accurate approximations for $\\Sigma$ have been developed and implemented into first-principles codes91. While maximally-localised Wannier functions for self-consistent GW quasiparticles have been discussed in Ref. 92, here we focus on the protocol to perform bands interpolation at the one-shot ${\\mathrm{{G}}_{0}}{\\mathrm{{W}}_{0}}$ level. For solids, the ${\\mathrm{{G}}_{0}}{\\mathrm{{W}}_{0}}$ approximation has proven to be an excellent compromise between accuracy and computational cost and it has become the most popular MBPT technique in computational materials science $^{93}$ . In the standard one-shot $\\mathrm{{{G}_{0}}\\mathrm{{W}_{0}}}$ approach, $\\Sigma$ is written in terms of the Kohn–Sham (KS) Green’s function and the RPA dielectric matrix, both obtained from the knowledge of DFT-KS orbitals and eigenenergies. Quasi-particle (QP) energies are obtained from: \n\n$$\n\\epsilon_{n\\mathbf{k}}^{\\mathrm{QP}}=\\epsilon_{n\\mathbf{k}}+Z_{n\\mathbf{k}}\\langle\\psi_{n\\mathbf{k}}|\\Sigma(\\epsilon_{n\\mathbf{k}})-V_{\\mathrm{xc}}|\\psi_{n\\mathbf{k}}\\rangle,\n$$ \n\nwhere $\\psi_{n\\mathbf{k}}$ and $\\epsilon_{n\\mathbf{k}}$ are the KS orbitals and eigenenergies, $Z_{n\\mathbf{k}}$ is the so-called renormalisation factor and $V_{\\mathrm{xc}}$ is the DFT exchange-correlation potential. In addition, in the standard $\\mathrm{{{G}_{0}}\\mathrm{{W}_{0}}}$ \n\n
Mode k-grid Nc Time
version 3.0S
30×30×3024 6903
30×30×3048 3527
Berry 3D 30×30×30480 441
100×100×100480 13041
100×100×100 7680957
Berry 2D 100×10024 1389
Berry 1D 1000024 12639
version 2.0
30×30×30 Berry 3D24 56497
30×30×30 4840279
\n\nTABLE I: Wall-time for some of the runs performed with the Berry module, before (Wannier90 v2.0) and after (Wannier90 v3.0) the optimisations, for the test system described in the main text. $N_{\\mathrm{c}}$ indicates the number of cores used in the calculation. \n\n![](images/82c4a4d4f69ab4ff9ab99a88141adee95f177905bfeb3f5996637a3616a2096d.jpg) \n\nFIG. 7: (Top) Speedup of the new Wannier90 v3.0 with respect to v2.0, for a run of the berry module (mode “Berry 3D”) on the test system described in the text, demonstrating the improvements implemented in the new version of the code. (Bottom) Total CPU time (defined as total walltime times number of CPUs) for the three cases “Berry 3D”, “Berry 2D” and “Berry 1D” (whose meaning is described in the main text), normalised with respect to the same case run with $N_{\\mathrm{cpu}}/=24$ , for the Wannier90 v3.0 code. The “Berry 1D” and “Berry 2D” tests scan a 1D or 2D grid of points in the BZ, respectively; for these tests, the total number of grid points is 10000, therefore they can scale only up to a few hundreds of cores, above which the communication cost overweights the advantage coming from parallelisation. Instead, we emphasise that calculations with $N_{\\mathrm{cpu}}\\geq480$ for “Berry 3D” were run on a denser grid ( $100\\times100\\times100$ rather than $30\\times30\\times30$ ) and values have been rescaled using the time measured for both grids at $N_{\\mathrm{cpu}}=480$ to show the scalability of the code on thousands of CPUs. \n\napproximation the QP orbitals are approximated by the KS orbitals. At variance with DFT, QP corrections for a given $k$ -point require knowledge of the KS orbitals and eigenenergies at all points $(\\mathbf{k}+\\mathbf{q})$ in reciprocal space. In practice, codes such as Yambo $^{94}$ compute QP corrections on a regular grid and rely on interpolation schemes to obtain the full band structure along high-symmetry lines. Wannier90 supports the use of G0W $_0$ QP corrections through the general interface gw2wannier90.py distributed with Wannier90, while dedicated tools for Quantum ESPRESSO and Yambo allow for an efficient use of symmetries. Thanks to the software interface, QP corrections can be computed in the irreducible BZ (IBZ) and later unfolded to the full BZ to comply with Wannier90 requirements. In addition, the interface facilitates the use of a denser $k$ -point grid to converge the self-energy and of a coarser grid to obtain MLWFs, as long as the two grids are commensurate. This is particularly efficient in the case of two-dimensional materials, where the $k$ -point convergence of the self-energy is typically very slow while Wannier interpolation is already accurate with much coarser $k$ -point grids. Finally, the interface takes care of correcting and possibly reordering in energy both the KS eigenvalues and the corresponding input matrices (like $M_{m n}^{(\\mathbf{k},\\mathbf{b})}$ , $A_{m n\\bf{k}}$ ). After reading these eigenvalues and matrices, Wannier90 can proceed as usual and all functionalities are available (band-structure interpolation and beyond) at the level of ${\\mathrm{{G}}_{0}}{\\mathrm{{W}}_{0}}$ calculations. \n\n# VI. AUTOMATIC WANNIER FUNCTIONS: THE SCDM METHOD \n\nAn alternative method for generating localised Wannier functions, known as the selected columns of the density matrix (SCDM) algorithm, has been proposed by Damle, Lin and Ying $^{95,96}$ . At its core the scheme exploits the information stored in the real-space representation of the single-particle density matrix, a gauge-invariant quantity. Localisation of the resulting functions is a direct consequence of the well-known nearsightedness principle $^{97,98}$ of electronic structure in extended systems with a gapped Hamiltonian, i.e., insulators and semiconductors. In these cases, the density matrix is exponentially localised along the off-diagonal direction in its real-space representation $\\rho({\\bf r},{\\bf r^{\\prime}})$ and it is generally accepted that Wannier functions with an exponential decay also exist; numerical studies have confirmed this claim for a number of materials, and there exist formal proofs for multiband time-reversal-invariant insulators99–101. Since the SCDM method does not minimise a given gauge-dependent localisation measure via a minimisation procedure, it is free from any issue regarding the dependence on initial conditions, i.e., it does not require a good initial guess of localised orbitals. It also avoids other problems associated with a minimisation procedure, such as getting stuck in local minima. More generally, the localised Wannier functions provided by the SCDM method can be used as starting points for the MLWF minimisation procedure, by using them to generate the $A_{\\mathbf{k}}$ projection matrices needed by Wannier90. \n\nFor extended insulating systems, the density matrix is given by \n\n$$\n\\rho=\\sum_{\\mathbf{k}}P_{\\mathbf{k}}=\\sum_{n=1}^{J}\\sum_{\\mathbf{k}}\\left|\\psi_{n\\mathbf{k}}\\right\\rangle\\left\\langle\\psi_{n\\mathbf{k}}\\right|.\n$$ \n\nAs shown in Sec. II, the $P_{\\mathbf{k}}$ are the spectral projectors associated with the crystal Hamiltonian operator $H_{\\mathbf{k}}$ onto the valence space $S_{\\mathbf{k}}$ , hence their rank is $\\ensuremath{N_{\\mathrm{e}}}$ (number of valence electrons). Moreover, they are analytic functions of $\\mathbf{k}$ and also manifestly gauge invariant102,103. As mentioned above, the nearsightedness principle98 guarantees that the columns of the kernels $P_{\\mathbf{k}}(\\mathbf{r},\\mathbf{r}^{\\prime})=\\langle\\mathbf{r}|P_{\\mathbf{k}}|\\mathbf{r}^{\\prime}\\rangle$ are localised along the off-diagonal direction and therefore they may be used to construct a localised basis. If we consider a discretisation of the $J$ Bloch states at each $\\mathbf{k}$ on a real-space grid of $N_{\\mathrm{g}}$ points, we can arrange the wavefunctions into the columns of a unitary $N_{\\mathrm{g}}\\times J$ $k$ -dependent matrix Ψk \n\n$$\n\\Psi_{\\mathbf{k}}=\\left(\\begin{array}{c c c}{\\psi_{1\\mathbf{k}}(\\mathbf{r}_{1})}&{\\hdots}&{\\psi_{J\\mathbf{k}}(\\mathbf{r}_{1})}\\\\ {\\vdots}&{\\ddots}&{\\vdots}\\\\ {\\psi_{1\\mathbf{k}}(\\mathbf{r}_{N_{\\mathrm{g}}})}&{\\hdots}&{\\psi_{J\\mathbf{k}}(\\mathbf{r}_{N_{\\mathrm{g}}})}\\end{array}\\right),\n$$ \n\nsuch that $P_{\\mathbf{k},i j}=\\left(\\Psi_{\\mathbf{k}}\\Psi_{\\mathbf{k}}^{\\dagger}\\right){}_{i j}$ is $\\mathrm{a}\\ N_{\\mathrm{g}}\\times N_{\\mathrm{g}}$ matrix. In this representation, it is straightforward to see that the columns of $P_{\\mathbf{k}}(\\mathbf{r}_{i},\\mathbf{r}_{j})$ are projections of extremely localised functions (i.e., Dirac-delta functions localised on the grid points) onto the valence eigenspace. As a result, selecting any linearly-independent subset of $J$ of them will yield a localised basis for the span of $P(\\mathbf{r},\\mathbf{r}^{\\prime})$ . However, randomly selecting $J$ columns does not guarantee that a wellconditioned basis will be obtained. For instance, there could be too much overlap between the selected columns. Conceptually, the most well conditioned columns may be found via a QR factorisation with column pivoting (QRCP) applied to $P(\\mathbf{r},\\mathbf{r}^{\\prime})$ , in the form $P\\Pi=Q R$ , with $\\Pi$ being a matrix permuting the columns of $P$ , $Q$ a unitary matrix and $R$ an uppertriangular matrix (not to be confused with the lattice vector $\\mathbf{R}$ , or with the matrix $R^{(\\mathbf{k},\\mathbf{b})}$ defined in Eq. (12), or with the shift vector of Eq. (51)), and where $\\Pi$ is chosen so that $|R_{11}|\\geq|R_{22}|\\geq\\cdots\\geq|R_{n n}|$ . Then the $J$ columns forming a localised basis set are chosen to be the first $J$ of the matrix with permuted columns $P\\Pi$ . \n\nThe SCDM- $k^{96}$ method suggests that it is sufficient to apply the QRCP factorisation at k = 0 ( $\\Gamma$ point) only, and use the same selection of columns at all $k$ -points. However, this is still often impractical since $\\boldsymbol{P_{\\mathbf{\\tilde{I}}}}$ is prohibitively expensive to construct and store in memory. Therefore an alternative procedure is proposed, for which the columns can be computed via the QRCP of the (smaller) matrix $\\Psi_{\\mathbf{r}}^{\\dagger}$ instead: \n\n$$\n\\Psi_{\\bf{r}}^{\\dagger}\\Pi=Q^{\\prime}R^{\\prime},\n$$ \n\ni.e., the same $\\Pi$ matrix is obtained by computing a QRCP on $\\Psi^{\\dagger}$ only. Once the set of columns has been obtained, we need to impose the orthonormality constraint on the chosen columns without destroying their locality in real space. This can be achieved by a Lo¨wdin orthogonalisation, similarly to Eq. (26). In particular, the selection of columns of $\\Psi_{\\mathbf{T}}$ can be used to select the columns of all $\\Psi_{\\mathbf{k}}$ , which in turn define the $A_{m n\\bf{k}}$ matrices needed as input by Wannier90 to start the MLWF minimisation procedure, by defining $A_{m n\\mathbf{k}}=\\psi_{m\\mathbf{k}}^{*}(\\mathbf{r}_{\\Pi(n)})$ , where the $\\Pi(n)$ is the index of the $n^{\\mathrm{th}}$ column of $P\\vert$ after permutation with $\\Pi$ . In fact, we can write the $n^{\\mathrm{th}}$ column of $P$ after permutation, $\\widetilde{\\mathcal{P}_{\\mathbf{k}}}(\\mathbf{r},\\mathbf{r}_{\\Pi(n)})$ , as \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\cal P}_{{\\bf k}}({\\bf r},{\\bf r}_{\\Pi(n)})=\\sum_{m=1}^{J}\\psi_{m{\\bf k}}({\\bf r})\\psi_{m{\\bf k}}^{*}({\\bf r}_{\\Pi(n)})}\\ ~}\\\\ {{\\displaystyle~=\\phi_{\\Pi(n),{\\bf k}}\\equiv\\sum_{m=1}^{J}\\psi_{m{\\bf k}}({\\bf r})A_{m n{\\bf k}}}.}\\end{array}\n$$ \n\nThe unitary matrix $U_{\\mathbf{k}}$ sought for is then constructed via Lo¨wdin orthogonalisation \n\n$$\nU_{\\mathbf{k}}=A_{\\mathbf{k}}(A_{\\mathbf{k}}^{\\dagger}A_{\\mathbf{k}})^{-1/2}=A_{\\mathbf{k}}S_{\\mathbf{k}}^{-1/2}.\n$$ \n\nWe can also extend the SCDM- $k$ method to the case where the Bloch states are represented as two-component spinor wavefunctions $\\psi_{n\\mathbf{k}}(\\mathbf{r},\\alpha)$ , e.g., when including spin-orbit interaction in the Hamiltonian. Here, $\\alpha=\\uparrow,\\downarrow$ is the spinor index. In this case, we include the spin index as well as the position index to perform QRCP. First, we define the $2N_{g}\\times J$ matrix $\\Psi_{\\mathbf{k}}$ \n\n$$\n\\Psi_{\\mathbf{k}}=\\left(\\begin{array}{c c c}{\\psi_{1\\mathbf{k}}(\\mathbf{r}_{1},\\uparrow)}&{\\ldots}&{\\psi_{J\\mathbf{k}}(\\mathbf{r}_{1},\\uparrow)}\\\\ {\\psi_{1\\mathbf{k}}(\\mathbf{r}_{1},\\downarrow)}&{\\ldots}&{\\psi_{J\\mathbf{k}}(\\mathbf{r}_{1},\\downarrow)}\\\\ {\\vdots}&{\\ddots}&{\\vdots}\\\\ {\\psi_{1\\mathbf{k}}(\\mathbf{r}_{N_{g}},\\uparrow)}&{\\ldots}&{\\psi_{J\\mathbf{k}}(\\mathbf{r}_{N_{g}},\\uparrow)}\\\\ {\\psi_{1\\mathbf{k}}(\\mathbf{r}_{N_{g}},\\downarrow)}&{\\ldots}&{\\psi_{J\\mathbf{k}}(\\mathbf{r}_{N_{g}},\\downarrow)}\\end{array}\\right).\n$$ \n\nNext, as in the spinless case, the QRCP of $\\Psi_{\\mathbf{r}}^{\\dagger}$ is computed, and the first $J$ columns of the Π matrix are selected. Now, $\\Pi(n)$ , the index of the $n^{\\mathrm{th}}$ column of $P$ after permutation with $\\Pi$ , determines both the position index $\\mathbf{r}_{\\Pi(n)}$ and the spin index $\\alpha_{\\Pi(n)}$ . We define $\\dot{\\bf\\cal A}_{m n\\bf\\bf\\bf\\bf\\phi}=$ $\\psi_{m\\mathbf{k}}^{*}\\big(\\mathbf{r}_{\\Pi(n)},\\alpha_{\\Pi(n)}\\big)$ and perform Lo¨wdin orthogonalisation to obtain the unitary matrix $U_{\\mathbf{k}}$ . In the case of entangled bands, we need to introduce a so-called quasi-density matrix defined as \n\n$$\nP_{{\\bf k}}=\\sum_{n}\\left|\\psi_{n{\\bf k}}\\right\\rangle f(\\epsilon_{n{\\bf k}})\\left\\langle\\psi_{n{\\bf k}}\\right|,\n$$ \n\nwhere $f(\\epsilon_{n\\mathbf{k}})~\\in~[0,1]$ is a generalisation of the Fermi-Dirac probability for the occupied states. Also in this case we only use the information at $\\Gamma$ to generate the permutation matrix. Depending on what kind of entangled manifold one is interested in, $f(\\epsilon)$ can be modelled with various functional forms. In particular, the authors of Ref. 96 suggest the following three forms: \n\n1. Isolated manifold, e.g., the valence bands of an insulator or a semiconductor: $f(\\epsilon)$ is a step function, with the step inside the energy gap $\\Delta\\epsilon_{\\mathrm{g}}=\\epsilon_{\\mathrm{c}}-\\epsilon_{\\mathrm{v}}$ , where $\\epsilon_{\\mathrm{c(v)}}$ represents the minimum (maximum) of the conduction (valence) band: \n\n$$\nf(\\epsilon)=\\theta(\\epsilon_{\\mathrm{v}}+\\Delta\\epsilon_{\\mathrm{g}}/2-\\epsilon).\n$$ \n\nBoth $\\Delta\\epsilon_{\\mathrm{g}}$ and $\\epsilon_{\\mathrm{v}}$ are not free parameters, as they may be obtained directly from the ab initio calculation. \n\n2. Entangled manifold (case I), e.g., the valence bands and low-lying conduction bands in a semiconductor: $\\mathcal{f}(\\boldsymbol{\\epsilon})$ is a complementary error function: \n\n$$\nf(\\epsilon)=\\frac{1}{2}\\mathrm{erfc}\\left(\\frac{\\epsilon-\\mu}{\\sigma}\\right),\n$$ \n\nwhere $\\mu$ is used to shift the mid-value of the complementary error function, so that states with energy equal to $\\mu$ have a weight of $f(\\mu)=1/2$ . The parameter $\\sigma$ is used to gauge the “broadness” of the distribution function. \n\n3. Entangled manifold (case II), e.g., the $d$ bands in a transition metal: $f(\\epsilon)$ is a Gaussian function \n\n$$\nf(\\epsilon)=\\exp\\left(-\\frac{(\\epsilon-\\mu)^{2}}{\\sigma^{2}}\\right).\n$$ \n\nThe procedure then follows as in the previous case, by computing a QRCP factorisation on the quasi-density matrix. It is worth to note that in the case of an entangled manifold, the \n\nSCDM method requires the selection of two real numbers: $\\mu$ and $\\sigma$ , as well as the number of Wannier functions to disentangle $J$ . These parameters play a crucial role in the selection of the columns of the density matrix. While the selection of these parameters requires some care, as a rule of thumb (e.g., in entangled case I) $\\sigma$ is of the order 2 − 5 eV (which is the energy range of a typical bandwidth), while $\\mu$ can often be set around the Fermi energy (but the exact value depends on various factors, including the number $J$ of bands chosen and the specific properties of the bands of interest). It is worth to mention that since the SCDM- $k$ method is employed as an alternative way of specifying a set of initial projections and hence to compute the $A_{\\mathbf{k}}$ matrices in Eq. (26), the disentanglement procedure can be used in exactly the same way as described in Sec. II B. However, in the case of entangled bands the column selection is done on a quasi-density matrix, which implicitly defines a working subspace larger than the target subspace of dimension $J$ . We find that for wellknown systems SCDM- $k$ is typically already capable of selecting a smooth manifold and no further subspace selection is needed. \n\nThis method is now implemented as part of the pw2wannier90.x interface code to Quantum ESPRESSO. We have decided to implement the algorithm in the interface code(s) rather than in Wannier90 itself, because the SCDM method requires knowledge of the wavefunctions $\\psi_{n\\mathbf{k}}$ , which are only available in the ab initio code. \n\nIn Wannier90 only a single new input parameter auto projections is required. This disables the check on the number of projections specified in the input file (as we rely on SCDM to provide us with the initial guesses) and adds a new entry to the .nnkp file (which is read by pw2wannier90.x in order to compute the quantities required by Wannier90) that specifies the number of Wannier functions required. The remaining control parameters for the SCDM method are specified in the input file for the pw2wannier90.x code, including whether to use the SCDM method, the functional form of the $f(\\epsilon)$ function in Eq. (66) and, optionally, the values of $\\mu$ and $\\sigma$ in the definition of $f(\\epsilon)$ . \n\n# VII. AUTOMATION AND WORKFLOWS: AIIDA-WANNIER90 PLUGIN \n\nAiiDA $^{13}$ (Automated Interactive Infrastructure and Database for Computational Science) is an informatics infrastructure that helps researchers in managing, automating, storing and sharing their computations and results. AiiDA automatically tracks the entire provenance of every calculation to ensure full reproducibility, which is also stored in a tailored database for efficient querying of previous results. Moreover, it provides a workflow engine, allowing researchers to implement high-level workflows to automate sequences of tedious or complex calculation steps. AiiDA supports simulation codes via a plugin interface, and over 30 different plugins are available to date104. \n\nAmong these, the AiiDA-Wannier90 plugin provides support for the Wannier90 code. Users interact with the code (to submit calculations and retrieve the results) via the highlevel python interface provided by AiiDA rather than directly creating the Wannier90 input files. AiiDA will then handle automatically the various steps involved in submitting calculations to a cluster computer, retrieving and storing the results, and parsing them into a database. Furthermore, using the AiiDA workflow system users can chain pre-processing and post-processing calculations automatically (e.g., the preliminary electronic structure calculation with an ab initio code). These scientific workflows, moreover, can encode in a reproducible form the scientific knowledge of expert computational researchers in the field on how to run the simulations, choose the numerical parameters and recover from potential errors. In turn, their availability reduces the training time of new researchers, eliminates sources of error and enables large-scale high-throughput simulations. \n\nThe AiiDA-Wannier90 plugin expects that each calculation takes a few well-defined input parameters. Among the most important ones, a Wannier90 calculation run via AiiDA requires that the following input nodes are provided: an input crystal structure, a node of parameters with a dictionary of input flags for Wannier90, a node with the list of kpoints, a node representing the atomic projections, and a local input folder or remote input folder node containing the necessary input files (.amn, .mmn, .nnkp, .eig, .dmn) for the Wannier90 calculation as generated by an ab initio code. \n\nAll of these parameters, with the exception of projections, are generic to AiiDA to facilitate their reuse with different simulation codes. More detailed information on all inputs can be found in the AiiDA-Wannier90 package documentation105. \n\nAfter the Wannier90 execution is completed, the AiiDA-Wannier90 plugin provides parsers that are able to detect whether the convergence was successful and retrieve key parameters including the centres of the Wannier functions and their spread, as well as the different components of the spread ( $\\Omega_{\\mathrm{I}}$ , ΩD, ΩOD and $\\Omega$ ), and (if computed) the maximum imaginary/real ratio of the Wannier functions and the interpolated band structure. \n\nThe whole simulation is stored in the form of a graph, representing explicitly the provenance of the data generated including all inputs and outputs of the codes used in the workflow. An example of a provenance graph, automatically generated by AiiDA when running a Quantum ESPRESSO calculation followed by a Wannier90 calculation, is shown in Fig. 8. \n\nTo demonstrate the usefulness of this approach, we refer to Ref. 106 that reports the implementation and verification results of a fully-automated workflow (implemented within AiiDA, using the AiiDA-Wannier90 plugin described in this section) to compute Wannier functions of any material without any user input (besides its crystal structure). In addition, a virtual machine containing the codes (AiiDA with its plugins, Quantum ESPRESSO and Wannier90 including the SCDM implementation described in Sec. VI, and the automation workflows) is distributed. This virtual machine allows any researcher to reproduce the results of the paper and, even more, to perform simulations on new materials using the same protocol, without the need of installing and configuring all codes. \n\nWe emphasise that the availability of a platform to run Wannier90 in a fully-automated high-throughput way via the AiiDA-Wannier90 plugin has already proved to be beneficial for the Wannier90 code itself. Indeed, it has pushed the development of additional features or improvements now part of Wannier90 v3.0, including additional output files to facilitate output parsing and improvements in some of the algorithms and their default parameters to increase robustness. \n\n# VIII. MODERN SOFTWARE ENGINEERING PRACTICES \n\nIn this section, we describe a number of modern software engineering practices that are now part of the development cycle of the Wannier90 code. In particular, Wannier90 includes a number of tests that are run at every commit via a continuous integration approach, as well as nightly in a dedicated test farm. Version control is handled using git and the code is hosted on the GitHub platform $^{107}$ . We follow the fork and pull-request model, in which users can duplicate (fork) the project into their own private repository, make their own changes, and make a pull request (i.e., request that their changes be incorporated back into the main repository). When a pull request is made, a series of tests are automatically performed: the test suite is run both in serial and parallel using the Travis continuous in \n\n![](images/3b86a13be5543cc7107e47b49125e127b70511c4664c2f9eaf19eb1516dfae67.jpg) \n\nFIG. 8: The provenance graph automatically generated by AiiDA when running a \nWannier90 calculation for a diamond crystal using Quantum ESPRESSO as the DFT \ncode. Rectangles represent executions of calculations, ellipses represent data nodes, and diamonds are code executables. Graph edges connect calculations to their inputs and \noutputs. In particular, the following calculations are visible: Quantum ESPRESSO pw.x \nSCF (dark blue) and NSCF (green), Quantum ESPRESSO pw2wannier90.x (brown), and Wannier90 pre-processing (yellow) and minimisation run (purple). The initial \ndiamond structure (light blue) and the final interpolated band structure (dark grey) are also highlighted. \n\ntegration platform108, and code coverage is checked using codecov $^{\\cdot109}$ . If these tests are successful then the changes are reviewed by members of the Wannier90 developers group and, if the code meets the published coding guidelines, it can be merged into the development branch. \n\nIn addition, while interaction with end users happens via a mailing-list forum, discussion among developers is now tracked using GitHub issues. This facilitates the maintenance of independent conversation threads for each different code issue, new feature proposal or bug. \n\nThese can easily reference code lines as well as be referenced in code commit messages. Moreover, for every new bug report a new issue is opened, and pull requests that close the issue clearly refer to it. This approach facilitates tracking back the reasoning behind the changes in case a similar problem resurfaces. \n\nIn the remainder of this section we describe more in detail some of these modern software engineering practices. \n\n# A. Code documentation (FORD) \n\nThe initial release of Wannier90 came with extensive documentation in the form of a User Guide describing the methodology, input flags to the program and format of the input and output files. This document was aimed at the end users running the software. Documentation of the code itself was done via standard code comments. In order to foster not only a community of users but also of code contributors to Wannier90, we have now created an additional documentation of the internal structure of the code. This makes the code more approachable, particularly for new contributors. To create this code documentation in a fully automated fashion, we use the FORD (FORtran Documenter) $^{110}$ documentation generator. We have chosen this over other existing documentation solutions because of FORD’s specific support for Fortran. This tool parses the Fortran source, and generates a hyperlinked (HTML) index of source files, modules, procedures, types and programs defined in the code. Furthermore, it constructs graphs showing the dependencies between different modules and subroutines. Additional information can be provided in the form of special in-code comments (marked with double exclamation marks) describing in more detail variables, modules or subroutines. By tightly coupling the code to its documentation using in-code comments, the documentation maintenance efforts are greatly reduced, decreasing the risk of having outdated documentation. The compiled version of the documentation for the most recent code version is made available on the Wannier90 website $^{111}$ . \n\n# B. Testing infrastructure and continuous integration \n\nWith the recent opening to the community of the Wannier90 development, it has become crucial to create a non-regression test suite to ensure that new developments do not break existing functionalities of the code. Its availability facilitates the maintenance of the code and ensures its long-term stability. \n\nThe Wannier90 test suite relies on a modified version of James Spencer’s python testcode.py $^{112}$ . This provides the functionality to run tests and compare selected quantities parsed from the output files against benchmarked values. \n\nAt present, the Wannier90 test suite includes over 50 tests which are run both in serial and parallel and cover over $60\\%$ of the source code (with many modules exceeding $80\\%$ coverage). The code coverage is measured with the codecov software109. Developers are now required to add tests when adding new features to the code to ensure that their additions work as expected. This also ensures that future changes to the code will never break that functionality. Two different test approaches are implemented, serving different purposes. \n\nFirst, the Wannier90 repository is now linked with the Travis continuous integration platform $^{108}$ to prevent introducing errors and bugs into the main code branch. Upon any commit to the GitHub repository, the test suite is run both in serial and in parallel. Any test failure is reported back to the GitHub webpage. Additionally, for tests run against pull requests, any failed test results in the pull request being blocked and not permitted to merge. Contributors will first need to change their code to fix the problems highlighted in the tests; pull requests are able to be merged only after all tests pass successfully. \n\nSecond, nightly automatic tests are run on a Buildbot test-farm. The test-farm compiles and runs the code with a combination of compilers and libraries (current compilers include GFortran v6.4.0 and v7.3.0, Intel Fortran Compiler v17 and v18, and PGI compiler v18.05; current MPI libraries include Open MPI v1.10.7 and v3.1.3, Intel MPI v17 and MVAPICH v2.3b). This ensures that the code runs correctly on various high-performance computer (HPC) architectures. More information on the test-farm can be found on the Wannier90 GitHub wiki website113. \n\nIn addition to these tests, we have implemented git pre-commit hooks to help keep the same code style in all source files. The current pre-commit hooks run Patrick Seewald’s Fortran source code formatter fprettify $^{\\cdot114}$ to remove trailing whitespaces at the end of a line and to enforce a consistent indentation style. These precommit hooks, besides validating the code, can reformat it automatically. Developers may simply run the formatter code to convert the source to a valid format. If a developer installs the pre-commit hooks, these will be run automatically before every commit. Even if this is not the case, these tests are also run on Travis; therefore, a pull request that does not conform to the standard code style cannot be merged before the style is fixed. \n\n# C. Command-line interface and dry-run \n\nThe command-line interface of the code has been improved. Just running wannier90.x without parameters shows a short explanation of the available command line options. In addition, a -v flag has been added to print the version of the code, as well as a new -d dry-run mode, that just parses the input file to perform all needed checks of the inputs without running the actual calculation. The latter functionality is particularly useful to be used in input validators for Wannier90 or to precalculate quantities computed by the code at the beginning of the simulation (such as nearest-neighbour shells, $b$ -vectors or expected memory usage) and use this information to validate the run or optimise it (e.g., to decide the parallelisation strategy within automated AiiDA workflows). \n\n# D. Library mode \n\nWannier90 also comes with a library mode, where the core code functionality can be compiled into a library that can then be linked by external programs. This library mode is used as the default interaction protocol by some interface codes. The library mode provides only support for a subset of the full functionality, in particular at the moment it only supports serial execution. We have now added and improved support for the use of excluded bands also within the library mode. Moreover, beside supporting the generation of a staticallylinked library, we now also support the generation of dynamically-linked versions. Finally, we have added a minimal test code, run together with all other tests in the test suite, that serves both to verify that the library functionality works as expected, and as an example of the interface of the library mode. \n\n# IX. CONCLUSIONS AND OUTLOOK \n\nWannier90 v2.0 was released in October 2013 with a small update for v2.1 in January 2017. The results and developments of the past years, presented in this work, were released in Wannier90 v3.0 in February 2019. Thanks to the transition of Wannier90 to a community code, Wannier90 includes now a large number of new functionalities and improvements that make it very robust, efficient and rich with features. These include the implementation of new methods for the calculation of WFs and for the generation of the initial projections; parallelisation and optimisations; interfaces with new codes, methods and infrastructures; new user functionality; improved documentation; and various bug fixes. The effect of enlarging the community of developers is not only visible in the large number of contributions to the code, but also in the modern software engineering practices that we have put in place, that help improve the robustness and reliability of the code and facilitate its maintenance by the core Wannier90 developers group and its long-term sustainability. \n\nThe next major improvement that we are planning is the implementation of a more robust and general library mode. The features that we envision are: (1) the possibility to call the code from C or Fortran codes without the need to store files but by passing all variables from memory; (2) a more general library interface that is easily extensible in the future when new functionality is added; and (3) the possibility to run Wannier90 from a parallel MPI code, both by running each instance in parallel and by allowing massively-parallel codes to call, in parallel, various instances of Wannier90 on various structures or with different parameters. This improvement will demand a significant restructuring of most of the codebase and requires a good design of the new interface. Currently we are drafting the new library interface, by collecting feedback and use cases from the various contributors and users of the code, to ensure that the new library mode can be beneficial to all different possible use cases. \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge code contributions by Daniel Aberg (w90pov code), Lampros Andrinopoulos (w90vdw code), Pablo Aguado Puente (gyrotropic.F90 module), Raffaello Bianco ( $k$ -slice plotting), Marco Buongiorno Nardelli (dosqc v1.0 subroutines upon which some of transport.F90 is based), Stefano de Gironcoli (pw2wannier90.x interface to Quantum ESPRESSO), Pablo Garcia Fernandez (matrix elements of the position operator), Nicholas Hine (w90vdw code), Young-Su Lee (specialised $\\Gamma$ -point routines and transport), Antoine Levitt (preconditioning), Graham Lopez (extension of pw2wannier90.x to add terms needed for orbital magnetisation), Radu Miron (constrained centres), Nicolas Poilvert (transport routines), Michel Posternak (original plotting routines), Rei Sakuma (symmetry-adapted Wannier functions), Gabriele Sclauzero (disentanglement in spheres in $k$ -space), Matthew Shelley (transport routines), Christian Stieger (routine to print the U matrices), David Strubbe (various bug fixes and improvements), Timo Thonhauser (extension of pw2wannier90.x to add terms needed for orbital magnetisation), as well as the participants of the first Wannier90 developers meeting in San Sebasti´an (Spain) in 2016 for useful discussions (Daniel Fritsch, Victor Garcia Suarez, Pablo Garcia Fernandez, Jan-Philipp Hanke, Ji Hoon Ryoo, Ju¨rg Hutter, Javier Junquera, Liang Liang, Michael Obermeyer, Gianluca Prandini, Christian Stieger, Paolo Umari). The WDG acknowledges financial support from the NCCR MARVEL of the Swiss National Science Foundation, the European Union’s Centre of Excellence E-CAM (grant no. 676531), and the Thomas Young Centre for Theory and Simulation of Materials (grant no. TYC-101). \n\n1 P. Giannozzi, O. Andreussi, T. Brumme, O. Bunau, M. B. Nardelli, M. Calandra, R. Car, C. Cavazzoni, D. Ceresoli, M. Cococcioni, N. Colonna, I. Carnimeo, A. D. Corso, S. de Gironcoli, P. Delugas, R. A. DiStasio, A. Ferretti, A. Floris, G. Fratesi, G. Fugallo, R. Gebauer, U. Gerstmann, F. Giustino, T. Gorni, J. Jia, M. Kawamura, H.-Y. Ko, A. Kokalj, E. K¨u¸c¨ukbenli, M. Lazzeri, M. Marsili, N. Marzari, F. Mauri, N. L. Nguyen, H.-V. Nguyen, A. O. de-la Roza, L. Paulatto, S. Ponc´e, D. Rocca, R. Sabatini, B. Santra, M. Schlipf, A. P. Seitsonen, A. Smogunov, I. Timrov, T. Thonhauser, P. Umari, N. Vast, X. Wu and S. Baroni, Advanced capabilities for materials modelling with Quantum ESPRESSO, J. Phys. Cond. Matt. 29, 465901 (2017) 2 X. Gonze, B. Amadon, P.-M. Anglade, J.-M. Beuken, F. Bottin, P. Boulanger, F. Bruneval, D. Caliste, R. Caracas, M. Cˆot´e, T. Deutsch, L. Genovese, P. Ghosez, M. Giantomassi, S. Goedecker, D. Hamann, P. Hermet, F. Jollet, G. Jomard, S. Leroux, M. Mancini, S. Mazevet, M. Oliveira, G. Onida, Y. Pouillon, T. Rangel, G.-M. Rignanese, D. Sangalli, R. Shaltaf, M. Torrent, M. Verstraete, G. Zerah and J. Zwanziger, ABINIT: First-principles approach to material and nanosystem properties, Comp. Phys. Commun. 180, 2582 (2009). \n\n3 G. Kresse and J. Hafner, Ab initio molecular dynamics for liquid metals, Phys. Rev. B 47, \n558 (1993). \n4 G. Kresse and J. Furthm¨uller, Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set, Comp. Mat. Sci. 6, 15 (1996). \n5 G. Kresse and J. Furthm¨uller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set, Phys. Rev. B 54, 11169 (1996). \n6 J. M. Soler, E. Artacho, J. D. Gale, A. Garc´ıa, J. Junquera, P. Ordej´on and D. S´anchez-Portal, The SIESTA method for ab initio order-N materials simulation, J. Phys. Cond. Matt. 14, 2745 (2002). \n7 P. Blaha, K. Schwarz, G. Madsen, D. Kvasnicka and J. Luitz, WIEN2k: An Augmented Plane Wave plus Local Orbitals Program for Calculating Crystal Properties, TU Wien (2001), http://www.wien2k.at/reg_user/textbooks/usersguide.pdf. \n8 S. Bl¨ugel and G. Bihlmayer, Full-Potential Linearized Augmented Planewave Method, in Computational Nanoscience: Do It Yourself!, edited by J. Grotendorst, S. Bl¨ugel and D. Marx, vol. 31, pp. 85–129, John von Neumann Institute for Computing, Ju¨lich (2006). \n9 X. Andrade, D. Strubbe, U. De Giovannini, A. H. Larsen, M. J. T. Oliveira, J. Alberdi-Rodriguez, A. Varas, I. Theophilou, N. Helbig, M. J. Verstraete, L. Stella, F. Nogueira, A. Aspuru-Guzik, A. Castro, M. A. L. Marques and A. Rubio, Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems, Phys. Chem. Chem. Phys. 17, 31371 (2015). \n10 The Elk code, http://elk.sourceforge.net (2019). \n11 Wannier90 official GitHub repository, https://github.com/wannier-developers/ wannier90 (2019). \n12 N. Marzari, A. A. Mostofi, J. R. Yates, I. Souza and D. Vanderbilt, Maximally localized Wannier functions: Theory and applications, Rev. Mod. Phys. 84, 1419 (2012). \n13 G. Pizzi, A. Cepellotti, R. Sabatini, N. Marzari and B. Kozinsky, AiiDA: automated interactive infrastructure and database for computational science, Comp. Mat. Sci. 111, 218 (2016). \n14 G. H. Wannier, The structure of electronic excitation levels in insulating crystals, Phys. Rev. \n52, 191 (1937). \n\n15 N. Marzari and D. Vanderbilt, Maximally localized generalized Wannier functions for composite energy bands, Phys. Rev. B 56, 12847 (1997). \n\n16 A. A. Mostofi, J. R. Yates, Y.-S. Lee, I. Souza, D. Vanderbilt and N. Marzari, Wannier90: A tool for obtaining maximally-localised Wannier functions, Comp. Phys. Comm \n178, 685 (2008). \n17 I. Souza, N. Marzari and D. Vanderbilt, Maximally localized Wannier functions for entangled energy bands, Phys. Rev. B 65, 035109 (2001). \n18 P. L¨owdin, On the non-orthogonality problem connected with the use of atomic wave functions in the theory of molecules and crystals, J. Chem. Phys. 18, 365 (1950). \n19 R. Evarestov and V. Smirnov, Site Symmetry in Crystals: Theory and Applications, Springer Series in Solid-State Sciences, Springer Berlin Heidelberg (2012). \n20 T. Hahn, International Tables for Crystallography, Vol. A. Space-group Symmetry, Wiley (2006). \n21 R. Sakuma, Symmetry-adapted Wannier functions in the maximal localization procedure, Phys. Rev. B 87, 235109 (2013). \n22 K. S. Thygesen, L. B. Hansen and K. W. Jacobsen, Partly occupied Wannier functions: Construction and applications, Phys. Rev. B 72, 125119 (2005). \n23 R. Wang, E. A. Lazar, H. Park, A. J. Millis and C. A. Marianetti, Selectively localized Wannier functions, Phys. Rev. B 90, 165125 (2014). \n24 P. E. Bl¨ochl, Projector augmented-wave method, Phys. Rev. B 50, 17953 (1994). \n25 G. Kresse and D. Joubert, From ultrasoft pseudopotentials to the projector augmented-wave method, Phys. Rev. B 59, 1758 (1999). \n26 A. D. Corso, Pseudopotentials periodic table: From H to Pu, Comp. Mat. Sci. 95, 337 (2014). \n27 J. P. Perdew, K. Burke and M. Ernzerhof, Generalized gradient approximation made simple, Phys. Rev. Lett. 77, 3865 (1996). \n28 VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data, J. Appl. Crystallogr. 44, 1272 (2011). \n29 G. Ge´ranton, F. Freimuth, S. Bl¨ugel and Y. Mokrousov, Spin-orbit torques in L10 − FePt/Pt thin films driven by electrical and thermal currents, Phys. Rev. B 91, 014417 (2015). \n30 A. Ferretti, A. Calzolari, B. Bonferroni and R. Di Felice, Maximally localized Wannier functions constructed from projector-augmented waves or ultrasoft pseudopotentials, J. Phys. Cond. Matt. 19, 036215 (2007). 31 A. Dal Corso and A. M. Conte, Spin-orbit coupling with ultrasoft pseudopotentials: Ap plication to Au and Pt, Phys. Rev. B 71, 115106 (2005). \n32 Y.-S. Lee, M. B. Nardelli and N. Marzari, Band structure and quantum conductance of nanostructures from maximally localized Wannier functions: The case of functionalized carbon nanotubes, Phys. Rev. Lett. 95, 076804 (2005). \n33 X. Wang, J. R. Yates, I. Souza and D. Vanderbilt, Ab initio calcu ation of the anomalous Hall conductivity by Wannier interpolation, Phys. Rev. B 74, 195118 (2006). 34 J. R. Yates, X. Wang, D. Vanderbilt and I. Souza, Spectral and Fermi surface properties from Wannier interpolation, Phys. Rev. B 75, 195121 (2007). 35 Persistence of Vision Pty. Ltd., Persistence of Vision (TM) Raytracer, http://www. povray.org/ (2004). 36 S. Coh and D. Vanderbilt, Python tight binding (PythTB) code, http://www.physics. rutgers.edu/pythtb/index.html. 37 D. Gresch, Q. Wu, G. W. Winkler, R. H¨auselmann, M. Troyer and A. A. Soluyanov, Automated construction of symmetrized Wannier-like tight-binding models from ab initio calculations, Phys. Rev. Mat. 2, 103805 (2018). \n38 N. Papior, sisl: v0.9.5, https://doi.org/10.5281/zenodo.597181 (2018). 39 J. Ferrer, C. J. Lambert, V. M. Garc´ıa-Su´arez, D. Z. Manrique, D. Visontai, L. Oroszlany, R. Rodr´ıguez-Ferrad´as, I. Grace, S. W. D. Bailey, K. Gillemot, H. Sadeghi and L. Algharagholy, GOLLUM: a next-generation simulation tool for electron, thermal and spin transport, New J. Phys. 16, 093029 (2014). 40 M. Luisier, A. Schenk, W. Fichtner and G. Klimeck, Atomistic simulation of nanowires in the sp3d5s∗ tight-binding formalism: From boundary conditions to strain calculations, Phys. Rev. B 74, 205323 (2006). 41 NanoTCAD ViDES, http://vides.nanotcad.com (2019). 42 S. Ponce´, E. Margine, C. Verdi and F. Giustino, EPW: Electron–phonon coupling, transport and superconducting properties using maximally localized Wannier functions, Comp. Phys. Commun. 209, 116 (2016). \n43 Q. Wu, S. Zhang, H.-F. Song, M. Troyer and A. A. Soluyanov, WannierTools: An open-source software package for novel topological materials, Comp. Phys. Commun. 224, 405 (2018). \n44 V. I. Belinicher and B. I. Sturman, The photogalvanic effect in media lacking a center o symmetry, Sov. Phys. Usp. 23, 199 (1980). \n45 B. I. Sturman and V. M. Fridkin, The Photovoltaic and Photorefractive Effects in Noncentrosymmetric Materials, Gordon and Breach, Philadelphia (1992). \n46 E. L. Ivchenko and G. E. Pikus, Superlattices and Other Heterostructures, Springer, Berlin (1997). \n47 L. Z. Tan, F. Zheng, S. M. Young, F. Wang, S. Liu and A. M. Rappe, Shift current bulk photovoltaic effect in polar materials – hybrid and oxide perovskites and beyond, npj Comput. Mater. 2, 16026 (2016). \n48 N. Nagaosa, J. Sinova, S. Onoda, A. H. MacDonald and N. P. Ong, Anomalous Hall effect, Rev. Mod. Phys. 82, 1539 (2010). \n49 R. von Baltz and W. Kraut, Theory of the bulk photovoltaic effect in pure crystals, Phys. Rev. B 23, 5590 (1981). \n50 V. I. Belinicher, E. L. Ivchenko and B. I. Sturman, Kinetic theory of the displacement photovoltaic effect in piezoelectrics, Sov. Phys. JETP 56, 359 (1982). \n51 N. Kristoffel, R. von Baltz and D. Hornung, On the intrinsic bulk photovoltaic effect: Performing the sum over intermediate states, Z. Phys. B 47, 293 (1982). \n52 J. E. Sipe and A. I. Shkrebtii, Second-order optical response in semiconductors, Phys. Rev. B 61, 5337 (2000). \n53 B. M. Fregoso, T. Morimoto and J. E. Moore, Quantitative relationship between polarization differences and the zone-averaged shift photocurrent, Phys. Rev. B 96, 075421 (2017). \n54 H. Presting and R. Von Baltz, Bulk photovoltaic effect in a ferroelectric crystal: A model calculation, Phys. Status Solidi B 112, 559 (1982). \n55 S. M. Young and A. M. Rappe, First principles calculation of the shift current photovoltaic effect in ferroelectrics, Phys. Rev. Lett. 109, 116601 (2012). \n56 R. D. King-Smith and D. Vanderbilt, Theory of polarization of crystalline solids, Phys. Rev. B 47, 1651 (1993). \n57 C. Aversa and J. E. Sipe, Nonlinear optical susceptibilities of semiconductors: Results with a length-gauge analysis, Phys. Rev. B 52, 14636 (1995). \n58 F. Nastos and J. E. Sipe, Optical rectification and shift currents in GaAs and GaP response: Below and above the band gap, Phys. Rev. B 74, 035201 (2006). \n59 T. Rangel, B. M. Fregoso, B. S. Mendoza, T. Morimoto, J. E. Moore and J. B. Neaton, Large bulk photovoltaic effect and spontaneous polarization of single-layer monochalcogenides, Phys. Rev. Lett. 119, 067402 (2017). \n60 M. Graf and P. Vogl, Electromagnetic fields and dielectric response in empirical tightbinding theory, Phys. Rev. B 51, 4940 (1995). \n61 C. Wang, X. Liu, L. Kang, B.-L. Gu, Y. Xu and W. Duan, First-principles calculation of nonlinear optical responses by Wannier interpolation, Phys. Rev. B 96, 115147 (2017). \n62 J. Iba˜nez Azpiroz, S. S. Tsirkin and I. Souza, Ab initio calculation of the shift photocurrent by Wannier interpolation, Phys. Rev. B 97, 245143 (2018). \n63 N. B. Baranova, Y. V. Boddanov and B. Y. Zel’dovich, Electrical analog of the Faraday effect and other new optical effects in liquids, Optics Commun. 22, 243 (1977). \n64 E. L. Ivchenko and G. E. Pikus, New photogalvanic effect in gyrotropic crystals, JETP Lett. 27, 604 (1978). \n65 E. L. Vorob’ev, E. L. Ivchenko, G. E. Pikus, I. I. Farbshtein, V. A. Shalygin and A. V. Shturbin, Optical activity in tellurium induced by a current, JETP Lett. 29, 441 (1979). \n66 V. A. Shalygin, A. N. Sofronov, E. L. Vorob’ev and I. I. Farbshtein, Current-Induced Spin Polarization of Holes in Tellurium, Phys. Solid State 54, 2362 (2012). \n67 I. Sodemann and L. Fu, Quantum nonlinear Hall effect induced by Berry curvature dipole in time-reversal invariant materials, Phys. Rev. Lett. 115, 216806 (2015). \n68 Y. Zhang, Y. Sun and B. Yan, Berry curvature dipole in Weyl semimetal materials: An ab initio study, Phys. Rev. B 97, 041101 (2018). \n69 Y. Zhang, J. van den Brink, C. Felser and B. Yan, Electrically tuneable nonlinear anomalous Hall effect in two-dimensional transition-metal dichalcogenides WTe2 and MoTe2, 2D Mater. 5, 044001 (2018). \n70 J.-S. You, S. Fang, S.-Y. Xu, E. Kaxiras and T. Low, Berry curvature dipole current in the transition metal dichalcogenides family, Phys. Rev. B 98, 121109 (2018). \n71 Q. Ma, S.-Y. Xu, H. Shen, D. Macneill, V. Fatemi, T.-R. Chang, A. M. M. Valdivia, S. Wu, Z. Du, C.-H. Hsu, S. Fang, Q. D. Gibson, K. Watanabe, T. Taniguchi, R. J. Cava, E. Kaxiras, H.-Z. Lu, H. Lin, L. Fu, N. Gedik and P. Jarillo-Herrero, Observation of the nonlinear Hall effect under time-reversal-symmetric conditions, Nature 565, 337 (2019). \n72 L. S. Levitov, Y. V. Nazarov and G. M. Eliashberg, Magnetoelectric effects in conductors with mirror isomer symmetry, Sov. Phys. JETP 61, 133 (1985). \n73 V. M. Edelstein, Spin polarization of conduction electrons induced by electric current in two-dimensional asymmetric electron systems, Solid State Commun. 73, 233 (1990). \n74 A. G. Aronov and Y. Lyanda-Geller, Nuclear electric resonance and orientation of carrier spins by an electric field, JETP Lett. 50, 431 (1989). \n75 S. D. Ganichev, M. Trushin and J. Schliemann, Spin Polarization by Current, in Handbook of Spin Transport and Magnetism, edited by E. Y. Tsymbal and I. Zutic, p. 487, CRC Press, New York (2012). \n76 T. Yoda, T. Yokoyama and S. Murakami, Current-induced orbital and spin magnetizations in crystals with helical structure, Sci. Rep. 5, 12024 (2015). \n77 S. Zhong, J. E. Moore and I. Souza, Gyrotropic magnetic effect and the magnetic moment on the Fermi surface, Phys. Rev. Lett. 116, 077201 (2016). \n78 S. S. Tsirkin, P. A. Puente and I. Souza, Gyrotropic effects in trigonal tellurium studied from first principles, Phys. Rev. B 97, 035158 (2018). \n79 M. G. Lopez, D. Vanderbilt, T. Thonhauser and I. Souza, Wannier-based calculation of the orbital magnetization in crystals, Phys. Rev. B 85, 014435 (2012). \n80 V. M. Asnin, A. A. Bakun, A. M. Danishevskii, E. L. Ivchenko, G. E. Pikus and A. A. Rogachev, Observation o photo-emf that depends on the sign of the circular polarization of the light, JETP Lett. 28, 74 (1978). \n81 E. Deyo, L. E. Golub, E. L. Ivchenko and B. Spivak, Semiclassical theory of the photogalvanic effect in non-centrosymmetric systems, ArXiv e-prints arXiv:0904.1917 (2009). \n82 J. E. Moore and J. Orenstein, Confinement-induced Berry phase and helicity-dependent photocurrents, Phys. Rev. Lett. 105, 026805 (2010). \n83 F. de Juan, A. G. Grushin, T. Morimoto and J. E. Moore, Quantized circular photogalvanic effect in Weyl semimetals, Nature Commun. 8, 15995 (2017). \n84 F. Flicker, F. de Juan, B. Bradlyn, T. Morimoto, M. G. Vergniory and A. G. Grushin, Chiral optical response of multifold fermions, Phys. Rev. B 98, 155145 (2018). \n\n85 S. Wimmer, M. Seemann, K. Chadova, D. K¨odderitzsch and H. Ebert, Spin-orbitinduced longitudinal spin-polarized currents in nonmagnetic solids, Phys. Rev. B 92, 041101 (2015). \n\n86 J. Sinova, S. O. Valenzuela, J. Wunderlich, C. H. Back and T. Jungwirth, Spin Hall effects, Rev. Mod. Phys. 87, 1213 (2015). \n87 J. Qiao, J. Zhou, Z. Yuan and W. Zhao, Calculation of intrinsic spin Hall conductivity by Wannier interpolation, Phys. Rev. B 98, 214402 (2018). \n88 J. H. Ryoo, C.-H. Park and I. Souza, Computation of intrinsic spin Hall conductivities from first principles using maximally localized Wannier functions, Phys. Rev. B 99, 235113 (2019). \n89 T. Ponweiser and M. Wierzbowska, Optimizing the post-Wannier Berry-phase code for optical and anomalous Hall conductivities and orbital magnetization, available online at http: //www.prace-ri.eu/IMG/pdf/WP204.pdf . \n90 A. L. Fetter and J. D. Walecka, Quantum Theory of Many-Particle Systems, McGrawHill, Boston (1971). \n91 R. M. Martin, L. Reining and D. M. Ceperley, Interacting Electrons: Theory and Computational Approaches, Cambridge University Press (2016). \n92 D. R. Hamann and D. Vanderbilt, Maximally localized Wannier functions for GW quasiparticles, Phys. Rev. B 79, 045109 (2009). \n93 L. Reining, The GW approximation: content, successes and limitations, Wiley Interdiscip. Rev. Computat. Mol. Sci. 8, e1344 (2018). \n94 A. Marini, C. Hogan, M. Gr¨uning and D. Varsano, yambo: An ab initio tool for excited state calculations, Comp. Phys. Commun. 180, 1392 (2009). \n95 A. Damle, L. Lin and L. Ying, Compressed representation of Kohn–Sham orbitals via selected columns of the density matrix, J. Chem. Theory Comput. 11, 1463 (2015). \n96 A. Damle and L. Lin, Disentanglement via entanglement: A unified method for Wannier localization, Multiscale Model. Sim. 16, 1392 (2018). \n97 W. Kohn, Construction of Wannier functions and applications to energy bands, Phys. Rev. B 7, 4388 (1973). \n98 E. Prodan and W. Kohn, Nearsightedness of electronic matter, Proc. Natl. Acad. Sci. 102, 11635 (2005). \n99 C. Brouder, G. Panati, M. Calandra, C. Mourougane and N. Marzari, Exponential localization of Wannier functions in insulators, Phys. Rev. Lett. 98, 046402 (2007). \n100 L. He and D. Vanderbilt, Exponential decay properties of Wannier functions and related quantities, Phys. Rev. Lett. 86, 5341 (2001). \n101 D. Fiorenza, D. Monaco and G. Panati, Construction of real-valued localized composite Wannier functions for insulators, Ann. Henri Poincar´e 17, 63 (2016). \n102 G. Nenciu, Dynamics of band electrons in electric and magnetic fields: rigorous justification of the effective Hamiltonians, Rev. Mod. Phys. 63, 91 (1991). \n103 G. Panati and A. Pisante, Bloch bundles, Marzari-Vanderbilt functional and maximally localized Wannier functions, Comm. Math. Phys. 322, 835 (2013). \n104 AiiDA plugin registry, https://aiidateam.github.io/aiida-registry. \n105 Documentation of the AiiDA-Wannier90 plugin, https://aiida-wannier90.readthedocs. io. \n106 V. Vitale, G. Pizzi, A. Marrazzo, J. R. Yates, N. Marzari and A. A. Mostofi, Automated high-throughput Wannierisation, ArXiv e-prints arXiv:1909.00433 (2019). \n107 GitHub, https://www.github.com. \n108 Travis-CI, https://www.travis-ci.org. \n109 codecov.io, https://codecov.io. \n110 C. MacMackin, FORD, https://doi.org/10.5281/zenodo.1422473 (2018). \n111 Wannier90 developers documentation generated with FORD, http://www.wannier.org/ford/ (2019). \n112 J. Spencer, testcode, https://github.com/jsspencer/testcode. \n113 Wannier90 GitHub wiki page, https://github.com/wannier-developers/wannier90/wiki. \n114 fprettify autoformatter for moder Fortran code, https://github.com/pseewald/fprettify. " + }, + { + "id": "10.1038_s41467-020-18350-7", + "DOI": "10.1038/s41467-020-18350-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-18350-7", + "Relative Dir Path": "mds/10.1038_s41467-020-18350-7", + "Article Title": "Unique S-scheme heterojunctions in self-assembled TiO2/CsPbBr3 hybrids for CO2 photoreduction", + "Authors": "Xu, FY; Meng, K; Cheng, B; Wang, SY; Xu, JS; Yu, JG", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Exploring photocatalysts to promote CO2 photoreduction into solar fuels is of great significance. We develop TiO2/perovskite (CsPbBr3) S-scheme heterojunctions synthesized by a facile electrostatic-driven self-assembling approach. Density functional theory calculation combined with experimental studies proves the electron transfer from CsPbBr3 quantum dots (QDs) to TiO2, resulting in the construction of internal electric field (IEF) directing from CsPbBr3 to TiO2 upon hybridization. The IEF drives the photoexcited electrons in TiO2 to CsPbBr3 upon light irradiation as revealed by in-situ X-ray photoelectron spectroscopy analysis, suggesting the formation of an S-scheme heterojunction in the TiO2/CsPbBr3 nullohybrids which greatly promotes the separation of electron-hole pairs to foster efficient CO2 photoreduction. The hybrid nullofibers unveil a higher CO2-reduction rate (9.02 mu mol g(-1) h(-1)) comparing with pristine TiO2 nullofibers (4.68 mu mol g(-1) h(-1)). Isotope ((CO2)-C-13) tracer results confirm that the reduction products originate from CO2 source.", + "Times Cited, WoS Core": 1175, + "Times Cited, All Databases": 1211, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000604254000001", + "Markdown": "# Unique S-scheme heterojunctions in selfassembled TiO2/CsPbBr3 hybrids for CO2 photoreduction \n\nFeiyan Xu 1,2, Kai Meng $\\textcircled{1}$ 1, Bei Cheng $\\textcircled{1}$ 1, Shengyao Wang 3✉, Jingsan Xu 4✉ & Jiaguo Yu 1,2✉ \n\nExploring photocatalysts to promote ${\\mathsf{C O}}_{2}$ photoreduction into solar fuels is of great significance. We develop ${\\mathsf{T i O}}_{2}$ /perovskite $(\\mathsf{C s P b}\\mathsf{B r}_{3})$ S-scheme heterojunctions synthesized by a facile electrostatic-driven self-assembling approach. Density functional theory calculation combined with experimental studies proves the electron transfer from ${\\mathsf{C s P b B r}}_{3}$ quantum dots (QDs) to $\\mathsf{T i O}_{2},$ resulting in the construction of internal electric field (IEF) directing from ${\\mathsf{C s P b}}{\\mathsf{B}}{\\mathsf{r}}_{3}$ to $\\mathsf{T i O}_{2}$ upon hybridization. The IEF drives the photoexcited electrons in $\\mathsf{T i O}_{2}$ to ${\\mathsf{C s P b}}{\\mathsf{B}}{\\mathsf{r}}_{3}$ upon light irradiation as revealed by in-situ $\\mathsf{X}$ -ray photoelectron spectroscopy analysis, suggesting the formation of an S-scheme heterojunction in the $\\mathsf{T i O}_{2}/\\mathsf{C s P b B r}_{3}$ nanohybrids which greatly promotes the separation of electron-hole pairs to foster efficient ${\\mathsf{C O}}_{2}$ photoreduction. The hybrid nanofibers unveil a higher ${\\mathsf{C O}}_{2}$ -reduction rate $(9.02\\upmu\\mathrm{mol}\\ \\mathrm{g}^{-1}\\mathsf{h}^{-1})$ comparing with pristine $\\mathsf{T i O}_{2}$ nanofibers $(4.68~\\upmu\\mathrm{mol}~\\mathrm{g}^{-1}~\\mathsf{h}^{-1})$ . Isotope $^{\\prime13}{\\sf C O}_{2})$ tracer results confirm that the reduction products originate from ${\\mathsf{C O}}_{2}$ source. \n\nT he depletion of fossil fuels and continuous $\\mathrm{CO}_{2}$ emissions have caused emerging global energy and environmental crises1–5. The photoreduction of $\\mathrm{CO}_{2}$ into renewable fuels with solar energy is recognized as a potential solution to solve above issues6–10. As a chemically inert, nontoxic and earthabundant photocatalyst, $\\mathrm{TiO}_{2}$ is supposed to be proverbially utilized for $\\mathrm{CO}_{2}$ photoreduction11–13. However, like the majority of unitary photocatalysts, the photocatalytic efficiency of $\\mathrm{TiO}_{2}$ is still far away from the practical requirements largely due to its rapid electron–hole recombination14,15. Hybridizing $\\mathrm{TiO}_{2}$ with another semiconductor with a suitable band structure is a widely adopted strategy to tackle this issue owing to the efficient separation of photoinduced electron–hole pairs16–20. Therefore, it is of significance to explore or design a $\\mathrm{TiO}_{2}$ -based heterojunction to improve the photocatalytic $\\mathrm{CO}_{2}$ reduction performance. \n\n$\\mathrm{CsPbBr}_{3}$ , a typical material of halide perovskites, has attracted significant scientific interest in optoelectronic applications owing to its outstanding properties, including narrow photoemission, high photoluminescence quantum yield, tunable bandgap, and competing optoelectronic properties21–24. Inspired from the achievements in optoelectronic applications, $\\mathrm{CsPbBr}_{3}$ is a potential candidate for conducting efficient photocatalysis25,26. ${\\bar{\\mathrm{CsPbBr}}}_{3}$ quantum dots (QDs) have recently been hybridized with 2D graphene oxide27 and porous $\\mathrm{g-C_{3}N_{4}}^{28}$ for $\\mathrm{CO}_{2}$ photoreduction. Nevertheless, in these cases, the electrons in the conduction band of $\\mathrm{CsPbBr}_{3}$ transferred into graphene and $\\mathrm{g-C}_{3}\\mathrm{N}_{4}.$ . forming Schottky and type-II heterojunctions, respectively, sacrificing the reduction ability of the photoinduced electrons despite achieving better charge separation. Very recently, an Sscheme heterojunction composed of two n-type semiconductors has been proposed29,30. The transfer path of photogenerated charge carriers at interfaces is like an $^{\\mathrm{i}}\\mathrm{S}^{\\mathrm{p}}$ figure, enabling the heterojunctions to have the highest redox ability. The S-type charge transportation correlates with the band bending and internal electric field (IEF) at the junction. The n-type nature and remarkably different work functions of $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ suggest a high possibility of forming S-scheme $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ heterojunctions. Up to now, however, constructing perovskite $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ with $\\mathrm{TiO}_{2}$ , an emerging photoactive material and the most widespread photocatalyst, for efficient $\\mathrm{CO}_{2}$ photoreduction has not yet been reported. \n\nHerein, we report on a unique $\\mathrm{TiO_{2}/C s P b B r_{3}}$ S-scheme heterojunction built by electrostatic self-assembly of $\\mathrm{TiO}_{2}$ nanofibers and $\\mathrm{CsPbBr}_{3}$ QDs for boosted photocatalytic $\\mathrm{CO}_{2}$ reduction. $\\mathrm{TiO}_{2}$ nanofibers show no aggregation upon dispersion in solution and thereby retain their phototactically active sites exposed on the surface. Meanwhile, randomly stacked $\\mathrm{TiO}_{2}$ nanofibres readily form a loose network, facilitating the adsorption–desorption and transportation of reactants and products. More importantly, the $\\mathrm{TiO}_{2}$ nanofibres are composed of small nanocrystals, possessing interparticle voids and rough surface, which make $\\mathrm{TiO}_{2}$ nanofibres an ideal host to anchor $\\mathrm{CsPbBr}_{3}$ QDs. Experimental study and density functional theory (DFT) calculation verify the presence of IEF in the unique $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ heterojunction, which separate photoinduced charge carriers more efficiently. We argue the formation of the S-scheme charge transfer route at $\\mathrm{TiO}_{2}/$ $\\mathrm{CsPbBr}_{3}$ interfaces upon light irradiation. The obtained $\\mathrm{TiO}_{2}/$ $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ heterojunction shows a superior activity for reducing $\\mathrm{CO}_{2}$ into solar fuels under UV–visible-light irradiation. This work provides a point of view in $\\mathrm{TiO}_{2}$ -based photocatalyst for efficient $\\mathrm{CO}_{2}$ photoreduction driven by the S-scheme electron transfer route. \n\n# Results and discussion \n\nCharacterization of as-prepared $\\mathbf{CsPbBr}_{3}$ QDs. Transmission electron microscopy (TEM) images with different magnifications are shown in Fig. 1a, b. The $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs were of nanocubes with a size of $6{-}9\\mathrm{nm}$ (inset in Fig. 1a). High-resolution TEM (HRTEM) image (Fig. 1c) showed lattice spacings of $0.413\\mathrm{nm}$ , corresponding to the (110) facets of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ . As-prepared $\\mathrm{CsPbBr}_{3}$ QDs were of cubic phase (JCPDS No. 54-0752) as revealed by X-ray diffraction (XRD) pattern (Fig. 1d). The UV–vis absorption spectrum of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs revealed strong bands at 450 and $500\\mathrm{nm}$ (Fig. 1e). The corresponding photoluminescence (PL) spectrum unfolded a narrow emission at 520 nm, agreeing with previous reports21,31. Accordingly, the QDs solution showed a bright green fluorescence under $365\\mathrm{nm}$ UV light (inset of Fig. 1e). \n\n![](images/c6002292e8643c5d655977cfd56ab6682120cb46d986f1e70a0bb6ac3cadf1f0.jpg) \nFig. 1 Characterization of $\\cos P b B r_{3}$ QDs. a, b Transmission electron microscopy (TEM) image and corresponding size distribution (lower right inset of panel a), the geometrical structure (upper right inset of panel a), c high-resolution TEM (HRTEM) image, d X-ray diffraction (XRD) pattern, and e UV–vis absorption (black line) and PL emission (red line). Inset shows the photograph of $\\mathsf{C s P b B r}_{3}$ QDs colloidal solutions in hexane under UV light of $365\\mathsf{n m}$ . \n\nCharacterization of ${\\bf T i O}_{2}/{\\bf C s P b B r}_{3}$ heterojunction. The $\\mathrm{TiO}_{2}/$ $\\mathrm{CsPbBr}_{3}$ heterojunction was synthesized via electrostatic selfassembly of $\\mathrm{TiO}_{2}$ nanofibers and $\\mathrm{CsPbBr}_{3}$ QDs. Moreover, the minimization of the surface energy of the QDs should also be responsible for their adsorption to the $\\mathrm{TiO}_{2}$ nanofibers. The $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ hybrids were denoted as $\\mathrm{TC}x$ , where $\\mathrm{\\DeltaT}$ and C denote $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ QDs, respectively; $x$ represents the weight percentage of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ with respect to $\\mathrm{TiO}_{2}$ . The phase structures of $\\mathrm{TiO}_{2}.$ , TC2, and TC4 were determined via XRD analysis (Supplementary Fig. 1). $\\mathrm{TiO}_{2}$ nanofibers showed intensive reflections belonging to anatase (JCPDS No. 21-1272) and rutile (JCPDS No. 21-1276) phases. TC2 showed a similar XRD pattern with pristine $\\mathrm{TiO}_{2}$ , where the reflections of $\\mathrm{CsPbBr}_{3}$ QDs cannot be distinguished due to their low content. Apart from the characteristic reflections of $\\mathrm{TiO}_{2}.$ , TC4 showed additional reflections at $21.5^{\\circ}$ and $30.6^{\\circ};$ , which corresponded to the (110) and (200) planes of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs, confirming the formation of $\\mathrm{TiO}_{2}/$ $\\mathrm{CsPbBr}_{3}$ nanohybrids. The morphology and crystalline phase of pristine $\\mathrm{TiO}_{2}$ (Supplementary Fig. 2a) exhibited a porous nanofibrous shape with an average diameter of $200\\mathrm{nm}$ . The porous feature was further revealed by the $\\Nu_{2}$ sorption isotherms of $\\mathrm{TC}x$ (Supplementary Fig. 3). All the $\\mathrm{TC}x$ samples showed similar pore size distributions with a wide range of $10{-}20~\\mathrm{nm}$ , much larger than the size of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs $\\left(6{-}9\\mathrm{nm}\\right)$ . The resultant specific surface areas $(S_{\\mathrm{BET}})$ , pore volumes $(V_{\\mathrm{p}})$ , and average pore sizes $(d_{\\mathrm{p}})$ presented a volcano shape with increasing the loading of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs (Supplementary Table 1). At a low QDs loading ( $_{<2}$ $\\mathrm{wt.\\%}$ ), $\\mathrm{TC}x$ showed an increased $S_{\\mathrm{BET}}$ and reached the maximum value at TC2 because the low filling enables QDs to deposit onto the inner wall of $\\mathrm{TiO}_{2}$ mesopores. Such island-like QDs on the inner wall contribute additional specific surface area for the hybrid. When the QDs loading was further increased, QDs would aggregate in $\\mathrm{TiO}_{2}$ mesopores and the island-like distribution vanished, which thereby resulted in a decrease of $S_{\\mathrm{BET}}$ . The HRTEM image (Supplementary Fig. 2b) showed clear lattice spacings of 0.352 and $0.325\\mathrm{nm}$ , corresponding to anatase (101) and rutile (110) d-spacings, respectively. After the assembling process, the QDs were uniformly deposited on the $\\mathrm{TiO}_{2}$ nanofibers (Fig. 2a, b). The lattice spacings of anatase and rutile phase $\\mathrm{TiO}_{2}$ , as well as $\\mathrm{CsPbBr}_{3}$ QDs, appeared in the HRTEM image, as shown in Fig. 2c, confirming the formation of $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ nanohybrids. The energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDX) spectrum of TC2 (Fig. 2d) revealed the existence of Cs, $\\mathrm{Pb}$ , and Br apart from the dominant Ti and O elements. All the elemental mappings overlapped perfectly (Fig. 2e). Fourier-transform infrared (FTIR) spectra showed the presence of (Ti)–OH on $\\mathrm{TiO}_{2}$ and organic residues on QDs (Supplementary Fig. 4a, b)32. The (Ti)–OH signal weakened upon QDs deposition owing to the shielding effect of QDs. All the results confirmed the successful electrostatic assembly of $\\mathrm{TiO}_{2}$ nanofibers and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs. \n\nThe optical absorption of the samples was investigated by UV–vis diffuse reflectance spectrometer (DRS) (Supplementary Fig. 5a). The absorption edges of pristine $\\mathrm{TiO}_{2}$ nanofibers and $\\mathrm{CsPbBr}_{3}$ QDs were located at 400 and $550\\mathrm{nm}$ , corresponding to the bandgap energy of 3.10 and $2.24\\:\\mathrm{eV}$ , respectively (Supplementary Fig. 5b). In comparison with pristine $\\bar{\\mathrm{TiO}}_{2}$ , TCx showed two obvious absorption edges belonging to $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ QDs, and exhibited slightly enhanced UV and visible-light harvesting when increasing the amount of $\\mathrm{CsPbBr}_{3}$ QDs owing to the strong light-harvesting capability of perovskite QDs. Note that the calculated bandgap energy of $\\mathrm{TiO}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ in TC4 was different from their intrinsic bandgap, implying that there exist electrostatic attraction and interaction between $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ during the hybridization. \n\n$\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) was further performed to explore the chemical states of the resultant samples. The survey XPS spectrum (Supplementary Fig. 6a) showed the presence of Cs, $\\mathrm{Pb}.$ , and Br elements within TC2, as well as Ti and O. The exsitu Ti $2p$ XPS spectra of $\\mathrm{TiO}_{2}$ and TC2 (Fig. 3a) showed symmetrical Ti $2p$ doublets of $\\mathrm{Ti^{4+}}$ ions. The O 1s XPS spectra (Fig. 3b) revealed the presence of lattice oxygen $(529.3\\mathrm{eV})$ and –OH surface group $(531.2\\mathrm{eV})$ . Interestingly, TC2 showed a weaker XPS signal of $-\\mathrm{OH}$ than pristine $\\mathrm{TiO}_{2}$ , which was also attributed to an increase of QDs over $\\mathrm{TiO}_{2}$ nanofiber surface and was in agreement with the above FTIR results. The Br $3d$ -binding energies (BEs) of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs were 67.8 and $69.8\\mathrm{eV}$ , corresponding to Br $3d_{5/2}$ and Br $3d_{3/2}$ , respectively (Fig. 3c). Noticeably, the BEs of Ti $2p$ and O 1s in TC2 were shifted by 0.2 $\\mathrm{^\\circv}$ toward a lower BE in comparison with those of pristine $\\mathrm{TiO}_{2}$ , while the Cs $3d.$ Pb 4f (Supplementary Fig. 6c, d) and Br $3d$ BEs of TC2 became more positive as compared with those of QDs, indicating that the electrons transferred from $\\mathrm{CsPbBr}_{3}$ QDs to $\\mathrm{TiO}_{2}$ upon hybridization due to the difference of their work functions. Such electron transfer created an IEF at interfaces pointing from QDs to $\\mathrm{TiO}_{2}$ , facilitating the construction of Sscheme $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ heterojunction without any redox mediator, which would efficiently separate the charge carriers and thus promote the $\\mathrm{CO}_{2}$ photoreduction33–35. \n\nWork function $(\\phi)$ , as another important parameter to study the electron transfer within duplicate semiconductor heterostructures, can be estimated from the energy difference of vacuum and Fermi levels according to the electrostatic potential of a material. As shown in Fig. 3d–f, the work function of anatase $\\mathrm{TiO}_{2}$ (101), rutile $\\mathrm{TiO}_{2}$ (110), and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs (001) were 7.18, 7.08, and ${5.79\\mathrm{eV}}$ , respectively, indicating that both anatase and rutile $\\mathrm{TiO}_{2}$ have lower Fermi levels than $\\mathrm{CsPbBr}_{3}$ QDs. When they contacted with each other, electrons would flow from $\\mathrm{CsPbBr}_{3}$ to anatase and/or rutile $\\mathrm{TiO}_{2}$ to enable the phases at the same Fermi level and definitely created an IEF at $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ interfaces. These results were absolutely consistent with above exsitu XPS results and beneficial to the charge separation and $\\mathrm{CO}_{2}$ photoreduction activity. \n\n$\\mathbf{CO}_{2}$ photoreduction activity of ${\\bf T i O}_{2}/{\\bf C s P b B r}_{3}$ hybrids. The $\\mathrm{CO}_{2}$ photoreduction activity of resultant samples was measured in a closed gas-circulation system (Supplementary Fig. 7) with a Quartz and Pyrex glass hybrid reaction cell (Supplementary Fig. 8) and the photocatalytic reduction products consisted of a majority of CO and a small amount of $\\mathrm{H}_{2}$ . The original chromatograms for the reduction of $\\mathrm{CO}_{2}$ on sample TC2 are shown in Supplementary Fig. 9. Control experiments (Supplementary Fig. 10 and Table 2) showed that neither $\\mathrm{H}_{2}$ nor CO was detected in the dark or in the absence of $\\mathrm{CO}_{2}.$ , suggesting that the light irradiation and input $\\mathrm{CO}_{2}$ were indispensable for the photocatalytic reaction. As shown in Fig. 4a, b, pristine $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ QDs exhibited relatively lower production rates of $\\mathrm{H}_{2}$ (0.12 and $0.06\\upmu\\mathrm{mol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ , respectively) and CO (4.68 and 4.94 $\\upmu\\mathrm{mol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}$ , respectively), resulting from the rapid charge recombination. Note that the $\\mathrm{H}_{2}$ and CO productions were greatly enhanced with increased loading of QDs, and the generation of CO reached a maximum rate $(\\mathsf{\\bar{9}.02\\upmu m o l8^{-1}h^{-1}})$ with a relatively high selectivity $(95\\%)$ over TC2, due to the efficient charge separation of $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ heterostructure. Further increasing $\\mathrm{CsPbBr}_{3}$ QDs amount would be detrimental to the photocatalytic activity (e.g., TC3 and TC4), because the overloading of $\\mathrm{\\dot{C}s P b B r}_{3}$ could shield the light absorption of $\\mathrm{TiO}_{2}$ and decrease $S_{\\mathrm{BET}}$ of the nanohybrids. Interestingly, with the reaction time went on, the amount of $\\mathrm{O}_{2}$ decreased first and then increased, as shown in Fig. 4c. The initial $\\mathrm{O}_{2}$ in the system came from the input high-purity $\\mathrm{CO}_{2}$ . In the first two hours of photocatalytic $\\mathrm{CO}_{2}$ reduction, the fresh materials exhibit relatively strong reactivity of photoreduction. As a competitive reaction to $\\mathrm{CO}_{2}$ reduction, the consumption rate of $\\mathrm{O}_{2}$ $(\\mathrm{O}_{2}+\\mathrm{e}^{-}\\to\\cdot\\mathrm{O}_{2}{}^{-})$ was \n\n![](images/c95d05691fa4b9cc8e72ced9522105dc4c88dc88ca7a6427299a907edc007ef7.jpg) \nFig. 2 Morphology and structure of $\\pi_{1}0_{2}/\\subset_{5}\\mathsf{P b B r}_{3}$ heterojunction. a–c Transmission electron microscopy (TEM), STEM, and high-resolution TEM (HRTEM) images of TC2, d EDX spectrum of TC2, and e high-angle annular dark-field (HAADF) image and EDX elemental mappings of Ti, O, Cs, $\\mathsf{P b},$ and Br elements in TC2. \n\n![](images/063ed73ff9f285ab09be7d5e67a747c5b7ec66be5b5e27a528413b81d8fdb232.jpg) \nFig. 3 Electron transfer between $\\mathbf{TiO}_{2}$ and $\\cos P b B r_{3}$ quantum dots (QDs). In-situ and ex-situ X-ray photoelectron spectroscopy (XPS) spectra of a Ti $2p$ , b O 1s, and c Br $3d$ of $\\mathsf{T i O}_{2}$ , ${\\mathsf{C s P b B r}}_{3},$ and TC2. In-situ XPS spectra were collected under UV–vis light irradiation. The electrostatic potentials of d anatase $\\mathsf{T i O}_{2}$ (101), e rutile $\\mathsf{T i O}_{2}$ (110), and $\\textsf{\\pmb{f}}\\mathsf{C s P b}\\mathsf{B r}_{3}$ (001) facets. The blue, red, green, gray, and brown spheres stand for Ti, O, Cs, Pb, and Br atoms, respectively. Blue and red dashed lines indicate the Fermi and vacuum energy levels. \n\n![](images/12ac131d450fc66af148192c8c4d2fb2fbd309e79ac05a3cb54dea2ea80f2c34.jpg) \n\nFig. 4 $\\pmb{\\mathrm{co}}_{2}$ photoreduction performance and the photocatalytic mechanism of S-scheme heterojunction. Photocatalytic activities of ${\\mathsf{C O}}_{2}$ reduction over ${\\mathsf{T i O}}_{2},$ ${\\mathsf{T C}}x,$ and $\\mathsf{C s P b B r}_{3}$ quantum dots (QDs) during $4-h$ experiment performed under UV–vis light irradiation: time course of a $\\mathsf{H}_{2},$ b CO, and c $\\mathsf{O}_{2}$ production yields. The initial $\\mathsf{O}_{2}$ concentrations were normalized. d Mass spectra of $^{13}{\\mathsf{C O}}$ and total ion chromatography (inset) over TC2 in the photocatalytic reduction of ${}^{13}\\mathsf{C O}_{2}$ . Optimized structures of ${\\mathsf{C O}}_{2}$ molecule adsorbed on e anatase $\\mathsf{T i O}_{2}$ (101), f rutile $\\mathsf{T i O}_{2}$ (110), and $\\pmb{\\mathsf{g}}\\mathsf{C s P b}\\mathsf{B r}_{3}$ (001) facets. The blue, red, green, gray, and brown spheres stand for Ti, O, Cs, ${\\mathsf{P b}},$ and Br atoms, respectively. h The DOS of $\\mathsf{C s P b B r}_{3}$ . i Schematic illustration of $\\ T i O_{2}/$ $\\mathsf{C s P b B r}_{3}$ heterojunction: internal electric field (IEF)-induced charge transfer, separation, and the formation of S-scheme heterojunction under UV–visiblelight irradiation for ${\\mathsf{C O}}_{2}$ photoreduction. j Time-resolved photoluminescence (TRPL) spectra of $\\mathsf{T i O}_{2}$ (T) and TC2 at emission wavelengths of 450 and 520 nm, respectively. \n\nmuch higher than the production rate at the initial $^{2\\mathrm{h}}$ , while in the following $2\\mathrm{h}.$ , the production rate of $\\mathrm{O}_{2}$ was higher than the consumption rate, the total amount of oxygen and the ratio of oxygen:nitrogen have increased to a certain extent. \n\nThe recyclability and stability of TC2 for $\\mathrm{CO}_{2}$ photoreduction were investigated (Supplementary Fig. 11). After four times cycles, the decay of photocatalytic production yields of $\\mathrm{H}_{2}$ and CO were hardly perceptible. To evaluate the photostability of the nanohybrids, we have characterized the recycled photocatalyst using XRD, TEM, XPS, and FTIR. As shown in the XRD pattern (Supplementary Fig. 12a), the used photocatalyst showed no detectable phase change. The TEM image confirms that the QDs did not show obvious aggregation after cycled photocatalytic reactions, and the morphology was well maintained (Supplementary Fig. 12b). The chemical states of the used photocatalyst were also consistent with those of the fresh one, as examined by XPS (Supplementary Fig. 13). The FTIR spectra of TC2 before and after reaction were presented in Supplementary Fig. 14. The characteristic absorbance bands of the aliphatic species from QDs showed no obvious variation, implying that the capping agent of QDs was stable and was not decomposed during the photocatalytic $\\mathrm{CO}_{2}$ reduction. \n\nTo determine the origin of $\\mathrm{CO}_{2}$ photoreduction products, we performed an isotope-labeled carbon dioxide $\\left(^{13}\\bar{\\mathrm{CO}}_{2}\\right)$ photocatalytic reduction over TC2. Since the amount of products without photosensitizer and hole sacrificial agent was beyond the detection limit of mass spectrometry detector, we added tris $(2,2^{\\prime}$ - bipyridyl)ruthenium(II) chloride hexahydrate $([\\mathsf{R u}^{\\mathrm{II}}(\\mathsf{b p y})_{3}]$ $\\mathrm{Cl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{\\dot{O}})^{36}$ and 1,3-dimethyl-2-phenyl-2,3-dihydro-1H-benzo [d]imidazole $(\\mathrm{BIH})^{37}$ into the system to promote the photocatalytic activity, which behaved as the photosensitizer and hole sacrificial agent, respectively. In this case, the production yields of $\\mathrm{H}_{2}$ and CO were significantly enhanced (Supplementary Fig. 15 and Table 2) and readily detected by gas chromatography–mass spectrometer (GC-MS). As shown in Fig. 4d, the total ion chromatographic peak ${\\sim}3.44\\ \\mathrm{min}$ corresponded to CO, which produced three signals in the mass spectra. The main MS signal at $\\bar{m}/z=29$ belonged to $^{13}\\mathrm{CO}$ and the others $^{\\cdot_{13}}\\mathrm{C}$ at $m/z=13$ and O at $m/z=16$ ) corresponded to the fragments of $^{13}\\mathrm{CO}$ , confirming that the CO product exactly originated from the $\\mathrm{CO}_{2}$ photoreduction over $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}^{\\cdot38,39}$ . In addition, the total ion chromatographic peaks ${\\sim}2.36$ and $2.48\\mathrm{min}$ can be assigned to the $\\mathrm{O}_{2}$ and $\\Nu_{2}$ , respectively (Supplementary Fig. 16). The $\\mathrm{CO}_{2}$ adsorption of a photocatalyst is an essential step for $\\mathrm{CO}_{2}$ photoreduction40. Figure $4\\mathrm{e-g}$ compared the optimized models of one $\\mathrm{CO}_{2}$ molecule adsorbed on anatase $\\mathrm{TiO}_{2}$ (101), rutile $\\mathrm{TiO}_{2}$ (110), and $\\mathrm{CsPbBr}_{3}$ (001) surfaces. Clearly, the adsorption energy $(E_{\\mathrm{ads}})$ of $\\mathrm{CO}_{2}$ onto $\\mathrm{CsPbBr}_{3}$ $(-0.22\\mathrm{eV})$ was more negative than that onto anatase and rutile $\\mathrm{TiO}_{2}$ $_{-0.15}$ and $-0.10\\mathrm{eV})$ , which suggests that $\\mathrm{CO}_{2}$ molecules adsorbed on $\\mathrm{CsPbBr}_{3}$ is more stable than on $\\mathrm{TiO}_{2}$ . The results also indicate that $\\mathrm{CsPbBr}_{3}$ QDs were in favor of the adsorption of $\\mathrm{CO}_{2}$ molecules and the photocatalytic $\\mathrm{CO}_{2}$ reduction. \n\nTo further explore the photocatalytic mechanism, the band structures of $\\mathrm{Ti}\\bar{\\mathrm{O}}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs were investigated. The valence band (VB) potential was obtained by analyzing the VB XPS spectra. As shown in Supplementary Fig. 17a, b, the energy level of valence band maximum (VBM) of $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ is 2.39 and $1.03\\mathrm{eV}$ , respectively. Mott–Schottky (M–S) curves showed that $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ were of $\\mathfrak{n}$ -type semiconductors and had flat-band potentials of $0.01\\mathrm{eV}$ and $-\\bar{0}.51\\mathrm{eV}$ (vs. NHE), respectively (Supplementary Fig. 17c, d). Thus, the band structures of $\\mathrm{TiO}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs can be derived, and the positions of VBM and conduction band minimum (CBM) of $\\bar{\\mathrm{TiO}}_{2}$ and $\\mathrm{CsPbBr}_{3}$ are shown in Supplementary Fig. 17f. \n\nPhotocatalytic mechanism of S-scheme heterojunction. From the above analysis, the superior photoreduction activity was ascribed to the stronger $\\mathrm{CO}_{2}$ adsorption of $\\mathrm{CsPbBr}_{3}$ QDs and the formation of S-scheme heterojunction between $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ QDs. As revealed by the above ex-situ XPS and DFT analyses, $\\mathrm{TiO}_{2}$ has a lower Fermi level than $\\mathrm{CsPbBr}_{3}$ QDs before they contact. Upon hybridization, the electrons preferred to flow from $\\mathrm{CsPbBr}_{3}$ QDs to $\\mathrm{TiO}_{2}$ , which created an IEF at $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ interfaces pointing from $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ to $\\mathrm{TiO}_{2}$ and bent the energy bands of $\\mathrm{TiO}_{2}$ and $\\mathrm{CsPbBr}_{3}$ . Upon photoexcitation, the VB electrons of $\\mathrm{TiO}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ jumped to their CBs. Driven by the interfacial IEF and bent bands, the photogenerated electrons in $\\mathrm{TiO}_{2}$ CB spontaneously slid toward $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ and recombined with the holes in $\\mathrm{CsPbBr}_{3}$ VB. The electron-rich $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs then acted as active sites and donated electrons to activated $\\mathrm{CO}_{2}$ molecules for producing $\\mathrm{H}_{2}$ and CO. Noted that Pb was the active site for $\\mathrm{CO}_{2}$ photoreduction since the CB of $\\mathrm{CsPbBr}_{3}$ was mainly consisted of $\\mathrm{Pb}~6p$ orbitals as evidenced by the density of states (DOS) of $\\mathrm{CsPbBr}_{3}$ (Fig. 4h). Clearly, the transportation of photoinduced charge carriers follows a slide-like pathway, which implies the presence of S-scheme heterojunction between $\\mathrm{TiO}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs. This unique S-scheme charge transfer efficiently separated the photoinduced electron–hole pairs and meanwhile remained the high redox ability of electrons in $\\mathrm{CsPbBr}_{3}$ CB and holes in $\\mathrm{TiO}_{2}$ VB, respectively. The S-scheme heterostructure of $\\mathrm{TiO_{2}/C s P b B r_{3}}$ QDs along with the charge transfer and separation is illustrated in Fig. 4i. Such an S-scheme charge transfer route was strongly evidenced by the in-situ XPS spectra measured under light irradiation. As revealed in Fig. 3a–c and Supplementary Fig. 6c, d, the BEs of Ti $2p$ and O 1s for TC2 under light irradiation shifted positively by $0.3\\mathrm{eV}$ with reference to those in the corresponding ex-situ spectra. Conversely, the BEs of $\\mathrm{Cs}3d,\\mathrm{Pb}4f,$ and Br $3d$ of TC2 shifted negatively by $0.5\\mathrm{eV}$ . The BE shifts unequivocally proved that the photoexcited electrons in $\\mathrm{TiO}_{2}$ CB transferred to $\\mathrm{CsPbBr}_{3}$ QDs VB under light irradiation, following an S-scheme pathway, which supported the proposed photocatalytic mechanism. \n\nIt is worth mentioning that the $\\mathrm{TiO}_{2}$ we used consisted of both anatase and rutile phases, and the charge transfer between the two phases may take place as a result of forming homojunction. As evidenced by DFT results (Fig. 3d, e), the work function of anatase $\\mathrm{TiO}_{2}^{\\cdot}$ (101) was larger than that of rutile $\\mathrm{TiO}_{2}$ (110), indicating that electrons would flow from rutile to anatase and created an IEF at anatase/rutile $\\mathrm{TiO}_{2}$ interfaces. Driven by the interfacial IEF, the photogenerated electrons in anatase $\\mathrm{TiO}_{2}$ CB spontaneously slid toward rutile $\\mathrm{TiO}_{2}$ VB and recombined with the holes in the rutile $\\mathrm{TiO}_{2}$ VB. Such transportation of photoinduced charge carriers follows an S-like pathway (Sscheme homojunction) between anatase and rutile $\\mathrm{TiO}_{2}$ (Supplementary Fig. 18), which is consistent with our previous work41. When $\\mathrm{\\dot{C}s P b B r}_{3}$ QDs deposited on $\\mathrm{TiO}_{2}$ nanofibers, all possible schematic illustrations between anatase $\\mathrm{TiO}_{2}$ , rutile $\\mathrm{TiO}_{2}$ , and $\\mathrm{CsPbBr}_{3}$ QDs are shown in Supplementary Fig. 19. \n\nTo further prove the efficient charge separation of $\\mathrm{TiO}_{2}/$ $\\mathrm{CsPbBr}_{3}$ S-scheme heterojunction, photoluminescence (PL) emission spectra of the samples were collected (Supplementary Fig. 20). TC2 and TC4 showed a marginally lower PL intensity than $\\mathrm{TiO}_{2}$ , implying that the presence of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs efficiently retarded the electron–hole recombination in $\\mathrm{TiO}_{2}$ . To gain a deeper insight into the charge transfer dynamics, the timeresolved photoluminescence (TRPL) spectra of $\\mathrm{TiO}_{2}$ and TC2 were recorded at emission wavelengths $(E_{\\mathrm{W}})$ of $450\\mathrm{nm}$ and 520 nm (Fig. 4j), corresponding to the maximum fluorescence emissions of $\\mathrm{TiO}_{2}$ and QDs, respectively. The fitted decay curves disclose the lifetime $(\\tau)$ and percentage $(R e l.\\%)$ of charge carriers (Supplementary Table 3). The short lifetime $(\\tau_{1})$ corresponds to radiative recombination of the carriers (denoted as $\\tau_{1}$ -carriers), while the long lifetimes $\\cdot_{\\tau_{2}}$ and $\\tau_{3.}$ ) correspond to non-radiative recombination and energy-transfer process42. Note that the unrecombined $\\tau_{1}$ -carriers will participate in surface photocatalytic reaction. Thus, the decrease of $\\tau_{1}$ -carrier percentage implies radiative recombination inhibited. At $E_{\\mathrm{W}}=450\\mathrm{nm}$ , only $\\bar{\\mathrm{TiO}}_{2}$ showed a fluorescence emission signal. As shown in Supplementary Table 3, TC2 had a lower percentage ( $36.27\\%$ , $450\\mathrm{nm}$ ) of $\\tau_{1}$ - carriers than pristine $\\mathrm{TiO}_{2}$ $(37.98\\%$ , $450\\mathrm{nm}$ ), suggesting the radiative recombination over $\\mathrm{TiO}_{2}$ was inhibited upon QDs deposition due to the formation of S-scheme heterojunction43,44. Further, a similar decrease in $\\tau_{1}$ -carrier percentage was also observed at $E_{\\mathrm{W}}=520\\mathrm{nm}$ . Notably, TC2 showed longer lifetime than pristine $\\mathrm{TiO}_{2}$ due to the transfer of the electrons in $\\mathrm{TiO}_{2}$ CB to QDs VB. Therefore, it is not surprising that the TC2 composite sample exhibited enhanced photocatalytic $\\mathrm{CO}_{2}$ reduction performance. \n\nThe electrochemical impedance spectra (EIS) (Supplementary Fig. 21a) showed the samples with $\\mathrm{CsPbBr}_{3}$ QDs exhibited smaller semicircle compared to pure $\\mathrm{TiO}_{2}$ and revealed lower charge-transfer resistance. The polarization curves of $\\mathrm{TiO}_{2}$ and TC2 under light irradiation (Supplementary Fig. 21b) showed that the overpotential for TC2 was much lower than that of $\\mathrm{TiO}_{2}$ , indicating that $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ hybrids presented better reduction capability than that of $\\mathrm{TiO}_{2}$ . These results proved that $\\mathrm{CsPbBr}_{3}$ QDs, as an emerging semiconductor, could form S-scheme heterojunction with $\\mathrm{TiO}_{2}$ to promote the electron transfer and separate the electron–hole pairs for efficient $\\mathrm{CO}_{2}$ photoreduction. In summary, an S-scheme $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ heterojunction synthesizes through an electrostatic assembly method. The resulting $\\mathrm{TiO}_{2}/\\mathrm{CsPbBr}_{3}$ heterojunction reveals an enhanced activity toward $\\mathrm{CO}_{2}$ photoreduction under UV–visible-light irradiation due to the IEF-induced, more efficient charge separation between $\\mathrm{TiO}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ . DFT calculations reveal the work function of $\\mathrm{TiO}_{2}$ was greater than that of $\\mathrm{CsPbBr}_{3}$ , implying electrons transfer from $\\mathrm{CsPbBr}_{3}$ to $\\mathrm{TiO}_{2}$ upon hybridization and thus created an IEF at interfaces. The IEF drives photoinduced electrons in $\\mathrm{TiO}_{2}$ CB to immigrate to $\\mathrm{CsPbBr}_{3}$ VB as evidenced by in-situ XPS analysis, confirming an S-path of charge transfer. Isotope $\\left({}^{13}\\mathrm{CO}_{2}\\right)$ tracer results confirm that the reduction products originate from $\\mathrm{CO}_{2}$ source, instead of any contaminant carbon species. This work provides a point of view in the design of photocatalysts with distinct heterojunctions for efficient photocatalytic $\\mathrm{CO}_{2}$ reduction. \n\n# Methods \n\nSynthesis of electrospun $\\mathbf{TiO}_{2}$ nanofibers. All the chemicals were of analytic grade and purchased from Shanghai Chemical Company. Typically, tetrabutyl titanate (TBT, $2.0\\:\\mathrm{g})$ and poly(vinyl pyrrolidone) (PVP, $\\mathbf{0.75g},$ $\\mathrm{MW}=1,300,000$ ) were mixed with ethanol $(10.0\\:\\mathrm{g})$ and acetic acid $(2.0\\:\\mathrm{g})$ to form a transparent paleyellow solution after magnetic stirring for $^{5\\mathrm{h}}$ . Afterward, the solution was transferred into a $10\\mathrm{-mL}$ syringe in an electrospinning setup with a voltage of $20\\mathrm{kV}$ and a solution feeding rate of $2.5\\mathrm{mLh^{-1}}$ . The needle-to-collector distance was $10\\mathrm{cm}$ . The collected $\\mathrm{TiO}_{2}$ precursor was annealed at $550^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ with a heating rate of $2^{\\circ}\\mathrm{C}\\ \\mathrm{min}^{-1}$ in air. \n\nSynthesis of perovskite $\\cos P b B r_{3}$ QDs. Briefly, $130\\mathrm{mg}$ of $\\mathrm{Cs}_{2}\\mathrm{CO}_{3}$ ( $\\cdot0.4\\mathrm{mmol}\\rangle$ were mixed with octadecylene (ODE, $6\\mathrm{mL}$ ) and oleic acid (OA, $0.5\\mathrm{mL}$ ) under stirring in a three-neck flask $(25\\mathrm{mL}$ ). The mixture was dried at $120^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ under vacuum and heated to $150^{\\circ}\\mathrm{C}$ under $\\mathrm{N}_{2}$ gas to form Cs(oleate) solution, which was stored at room temperature and preheated to $140^{\\circ}\\mathrm{C}$ prior to use. Then $72\\mathrm{mg}$ of $\\mathrm{Pb}\\mathrm{Br}_{2}$ $\\mathrm{0.196\\mmol}_{,}$ was mixed with ODE $(5.0\\mathrm{mL}$ , oleylamine $(0.5\\mathrm{mL})$ , and OA $(0.5\\mathrm{mL})$ in another flask $(25\\mathrm{mL})$ ), and was dried under vacuum at $105^{\\circ}\\mathrm{C}$ for $0.5\\mathrm{h}$ . The mixture was heated to $170^{\\circ}\\mathrm{C},$ and Cs(oleate) $(0.45\\mathrm{mL})$ was rapidly injected under vigorously stirring for 5 s. The reaction was quenched by immersing the flask into an ice-water bath. The obtained product was mixed with $3\\mathrm{mL}$ of hexane and centrifuged at $1208\\times g$ for $2\\mathrm{min}$ to remove aggregates and large particles. The supernatant was precipitated with acetone and centrifuged at $3355\\times g$ for $5\\mathrm{min}$ . As-collected $\\mathrm{CsPbBr}_{3}$ QDs were re-dispersed in hexane for further use. \n\nPreparation of $\\mathsf{T i O}_{2}/\\mathsf{C s P b B r}_{3}$ heterostructures. Typically, $200\\mathrm{mg}$ of $\\mathrm{TiO}_{2}$ nanofibers were dispersed into $20~\\mathrm{mL}$ of hexane. A certain amount of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs solution was added into $\\mathrm{TiO}_{2}$ suspension under vigorous stirring for $^{2\\mathrm{h}}$ . $\\mathrm{TiO}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs were assembled by electrostatic self-assembly. The mixture was then vacuum-dried at $50^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ to form $\\mathrm{TiO_{2}/C s P b B r_{3}}$ heterostructures. The products are labeled as TCx, where $\\mathrm{\\DeltaT}$ and C denote $\\mathrm{TiO}_{2}$ and $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs, respectively; $x$ is the mass percentage of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ QDs. \n\nCharacterization. XRD was performed on a D/Max-RB X-ray diffractometer (Rigaku, Japan) with Cu Kα radiation. TEM images were observed on a Titan $_{\\mathrm{G2}}$ 60-300 electron microscope equipped with an EDX spectrometer. UV–visible DRS was collected on a Shimadzu UV-2600 UV–visible spectrophotometer (Japan). XPS was performed on a Thermo ESCALAB $250\\mathrm{Xi}$ instrument with Al $\\mathrm{K}_{\\mathrm{a}}$ X-ray radiation. In-situ XPS was conducted under the same condition, except that UV–visible-light irradiation was introduced. FTIR spectra were recorded with an attenuated total reflectance (ATR) mode on Nicolet iS 50 (Thermo Fisher, USA). The PL emission spectra were collected on a fluorescence spectrophotometer (F7000, Hitachi, Japan). TRPL spectra were recorded on a fluorescence lifetime spectrophotometer (FLS 1000, Edinburgh, UK) at an excitation wavelength of 325 nm. Electrochemical measurements were conducted on an electrochemical analyzer (CHI660C, CH Instruments, Shanghai). Pt wire, $\\mathrm{Ag/AgCl}$ (saturated KCl), and 0.5 M ${\\ N a}_{2}{\\ S}{\\ O}_{4}$ solution functioned as the counter electrode, reference electrode, and electrolyte, respectively. For the working electrode, $20\\mathrm{mg}$ of TCx was ground in $1.0\\mathrm{mL}$ of ethanol and $10\\upmu\\mathrm{L}$ of Nafion solution to make a slurry, which was coated onto F-doped $\\mathrm{SnO}_{2}$ -coated (FTO) glass with an exposed area of $\\textstyle1\\cos^{2}$ . The FTO electrode was then vacuum-dried at $60^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . \n\nPhotocatalytic $\\pmb{\\ c o_{2}}$ reduction. The photocatalytic $\\mathrm{CO}_{2}$ reduction was performed in a gas-closed system equipped with a gas-circulated pump. The apparatus of the system is shown in Supplementary Fig. 7. Typically, $10\\mathrm{mg}$ of photocatalysts, $30~\\mathrm{mL}$ of acetonitrile, and $100~\\upmu\\mathrm{L}$ of water were added in a Quartz and Pyrex glass hybrid reaction cell (Supplementary Fig. 8). The airtight system was completely evacuated by using a vacuum pump. Then ${\\sim}80\\mathrm{kPa}$ of high-purity $\\mathrm{CO}_{2}$ $(99.999\\%)$ ) gas was injected. After adsorption equilibrium, the photocatalytic cell was irradiated with a 300 W Xe arc lamp (PLS-SXE300D, Beijing Perfectlight, China), and the reaction system was kept at $10^{\\circ}\\mathrm{C}$ as controlled by cooling water. The $\\mathrm{CO}_{2}$ -reduction products were analyzed on a gas chromatograph (GC-2030, Shimadzu Corp., Japan) equipped with a barrier discharge ionization detector (BID) and a capillary column (Carboxen 1010 PLOT Capillary, $60\\mathrm{m}\\times0.53\\mathrm{mm}$ ). The column was maintained at $35^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ . It was then heated to $180^{\\circ}\\mathrm{C}$ at $20^{\\circ}\\mathrm{C}\\ \\operatorname*{min}^{-1}$ , and maintained for another 5 min. Helium was the carrier gas with pressure set to $70\\mathrm{\\kPa}$ . The temperatures of the injector and BID were set to be 150 and $280^{\\circ}\\mathrm{C},$ respectively. For comparison, $2\\mathrm{mM}$ of $\\mathrm{\\tris}(2,2^{\\prime}.$ -bipyridyl)ruthenium(II) chloride hexahydrate $([\\mathrm{Ru}^{\\mathrm{II}}(\\bar{\\mathrm{bpy}})_{3}]\\mathrm{Cl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O})$ and $10\\mathrm{mM}$ of 1,3-dimethyl-2-phenyl-2,3- dihydro-1H-benzo[d]imidazole (BIH) were added into the photocatalytic system (other parameters were unchanged), which behaved as the photosensitizer and hole sacrificial agent, respectively. A series of control experiments were also conducted, and the results are summarized in Supplementary Table 2. \n\nIsotope-labeling measurement. The isotope-labeling experiment was conducted by using $^{13}\\mathrm{CO}_{2}$ (isotope purity, $99\\%$ and chemical purity, $99.9\\%$ , Tokyo Gas Chemicals Co., Ltd.) as the carbon source. Typically, $10\\mathrm{mg}$ of photocatalysts, 2 mM of $[\\mathrm{Ru^{II}(b p y)_{3}}]\\mathrm{Cl_{2}}{\\cdot}6\\mathrm{H_{2}O}_{\\mathrm{:}}$ $10\\mathrm{mM}$ of BIH, $30~\\mathrm{mL}$ of acetonitrile and $100\\upmu\\mathrm{L}$ of water were loaded into the reaction cell. The protocol of $^{13}\\mathrm{CO}_{2}$ photoreduction was the same as that mentioned above. The gas products were analyzed by gas chromatography–mass spectrometry (JMS-K9, JEOL-GCQMS, Japan and $6890\\mathrm{N}$ Network GC system, Agilent Technologies, USA) equipped with the column for detecting the products of $^{13}\\mathrm{CO}$ (HP-MOLESIEVE, $30\\mathrm{m}\\times0.32\\mathrm{mm}\\times25\\mathrm{\\mum})$ . Helium was used as carrier gas. The column was maintained at $60^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ , and the flow of the carrier was $0.5\\mathrm{mlL^{-1}}$ . The temperatures of the injector, EI source, and the GCITF were set to be 200, 200, and $250^{\\circ}\\mathrm{C},$ , respectively. \n\n# Data availability \n\nAll data are available from the corresponding author on request. Source data are provided with this paper. Source data are also available in figshare with the identifier https://doi.org/10.6084/m9.figshare.12715484. \n\nReceived: 1 June 2019; Accepted: 5 August 2020; Published online: 14 September 2020 \n\n# References \n\n1. El-Khoulya, M. E., El-Mohsnawy, E. & Fukuzumi, S. Solar energy conversion: from natural to artificial photosynthesis. J. Photochem. Photobiol. C. 31, 36–83 (2017). \n2. Crake, A. Metal-organic frameworks based materials for photocatalytic $\\mathrm{CO}_{2}$ reduction. Mater. Sci. Technol. 33, 1737–1749 (2017). \n3. Collado, L. et al. Unravelling the effect of charge dynamics at the plasmonic metal/semiconductor interface for $\\mathrm{CO}_{2}$ photoreduction. Nat. Commun. 9, 4986 (2018). \n4. Xu, Q. et al. Direct Z-scheme photocatalysts: principles, synthesis, and applications. Mater. Today 21, 1042–1063 (2018). \n5. Yan, Z.-H. et al. Photo-generated dinuclear $\\{\\mathrm{Eu(II)}\\}_{2}$ active sites for selective $\\mathrm{CO}_{2}$ reduction in a photosensitizing metal-organic framework. Nat. Commun. 9, 3353 (2018). \n6. Li, X., Wen, J., Low, J., Fang, Y. & Yu, J. Design and fabrication of semiconductor photocatalyst for photocatalytic reduction of $\\mathrm{CO}_{2}$ to solar fuel. Sci. China Mater. 57, 70–100 (2014). \n7. Ran, J., Jaroniec, M. & Qiao, S.-Z. Cocatalysts in semiconductor-based photocatalytic $\\mathrm{CO}_{2}$ reduction: achievements, challenges, and opportunities. Adv. Mater. 30, 1704649 (2018). \n8. Nahar, S., Zain, M. F. M., Kadhum, A. A. H., Hasan, H. A. & Hasan, M. R. Advances in photocatalytic $\\mathrm{CO}_{2}$ reduction with water: a review. Materials 10, 629 (2017). \n9. Yu, W., Xu, D. & Peng, T. Enhanced photocatalytic activity of $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ for selective $\\mathrm{CO}_{2}$ reduction to $\\mathrm{CH}_{3}\\mathrm{OH}$ via facile coupling of $Z\\mathrm{nO}$ : a direct Zscheme mechanism. J. Mater. Chem. A 3, 19936–19947 (2015). \n10. Singh, A. K., Montoya, J. H., Gregoire, J. M. & Persson, K. A. Robust and synthesizable photocatalysts for $\\mathrm{CO}_{2}$ reduction: a data-driven materials discovery. Nat. Commun. 10, 443 (2019). \n11. Ola, O. & Maroto-Valer, M. M. Review of material design and reactor engineering on $\\mathrm{TiO}_{2}$ photocatalysis for $\\mathrm{CO}_{2}$ reduction. J. Photochem. Photobiol., C. 24, 16–42 (2015). \n12. Xu, F., Meng, K., Cheng, B., Yu, J. & Ho, W. Enhanced photocatalytic activity and selectivity for $\\mathrm{CO}_{2}$ reduction over a $\\mathrm{TiO}_{2}$ nanofibre mat using Ag and MgO as Bi-cocatalyst. ChemCatChem 10, 465–472 (2018). \n13. Wang, S. et al. Porous hypercrosslinked polymer- $\\mathrm{\\cdotTiO}_{2}$ -graphene composite photocatalysts for visible-light-driven $\\mathrm{CO}_{2}$ conversion. Nat. Commun. 10, 676 (2019). \n14. Abdullah, H., Khan, M. M. R., Ong, H. R. & Yaakob, Z. Modified $\\mathrm{TiO}_{2}$ photocatalyst for $\\mathrm{CO}_{2}$ photocatalytic reduction: an overview. J. $C O_{2}$ Util. 22, 15–32 (2017). \n15. Fang, W., Xing, M. & Zhang, J. Modifications on reduced titanium dioxide photocatalysts: a review. J. Photochem. Photobiol., C. 32, 21–39 (2017). \n16. Low, J., Cheng, B. & Yu, J. Surface modification and enhanced photocatalytic $\\mathrm{CO}_{2}$ reduction performance of $\\mathrm{TiO}_{2}$ : a review. Appl. Surf. Sci. 392, 658–686 (2017). \n17. Edelmannová, M. et al. Photocatalytic hydrogenation and reduction of $\\mathrm{CO}_{2}$ over $\\mathrm{CuO/TiO}_{2}$ photocatalysts. Appl. Surf. Sci. 454, 313–318 (2018). \n18. Shehzad, N., Tahir, M., Johari, K., Murugesan, T. & Hussaind, M. A critical review on $\\mathrm{TiO}_{2}$ based photocatalytic $\\mathrm{CO}_{2}$ reduction system: strategies to improve efficiency. J. $C O_{2}$ Util. 26, 98–122 (2018). \n19. Xu, F., Zhang, J., Zhu, B., $\\mathrm{Yu,}$ J. & Xu, J. $\\mathrm{CuInS}_{2}$ sensitized $\\mathrm{TiO}_{2}$ hybrid nanofibers for improved photocatalytic $\\mathrm{CO}_{2}$ reduction. Appl. Catal., B 230, 194–202 (2018). \n20. Yuan, L., Lu, K.-Q., Zhang, F., Fu, X. & Xu, Y.-J. Unveiling the interplay between light-driven $\\mathrm{CO}_{2}$ photocatalytic reduction and carbonaceous residues decomposition: a case study of ${\\mathrm{Bi}_{2}}\\mathrm{WO}_{6}$ -TiO2 binanosheets. Appl. Catal., B 237, 424–431 (2018). \n21. Hu, H. et al. Interfacial synthesis of highly stable CsPbX3/oxide Janus nanoparticles. J. Am. Chem. Soc. 140, 406–412 (2018). \n22. Li, M., Zhang, X., Matras-Postolek, K., Chen, H.-S. & Yang, P. An aniondriven $\\mathrm{Sn}^{2+}$ exchange reaction in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ nanocrystals towards tunable and high photoluminescence. J. Mater. Chem. C. 6, 5506–5513 (2018). \n23. Li, X., Wang, Y., Sun, H. & Zeng, H. Amino-mediated anchoring perovskite quantum dots for stable and low-threshold random lasing. Adv. Mater. 29, 1701185 (2017). \n24. Pan, A. et al. Nanorod suprastructures from a ternary graphene oxidepolymer- $\\mathrm{.csPb{X}}_{3}$ perovskite nanocrystal composite that display high environmental stability. Nano Lett. 17, 6759–6765 (2017). \n25. Protesescu, L. et al. Nanocrystals of cesium lead halide perovskites (CsPbX(3), ${\\mathrm{X}}={\\mathrm{Cl}},$ Br, and I): novel optoelectronic materials showing bright emission with wide color gamut. Nano Lett. 15, 3692–3696 (2015). \n26. Xu, Y.-F. et al. Enhanced solar-driven gaseous $\\mathrm{CO}_{2}$ conversion by $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ nanocrystal/Pd nanosheet Schottky-junction photocatalyst. ACS Appl. Energy Mater. 1, 5083–5089 (2018). \n27. Xu, Y.-F. et al. A $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ perovskite quantum dot/graphene oxide composite for photocatalytic $\\mathrm{CO}_{2}$ reduction. J. Am. Chem. Soc. 139, 5660–5663 (2017). \n28. Ou, M. et al. Amino-assisted anchoring of $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ perovskite quantum dots on porous $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ for enhanced photocatalytic $\\mathrm{CO}_{2}$ reduction. Angew. Chem. Int. Ed. 57, 13570–13574 (2018). \n29. Fu, J., Xu, Q., Low, J., Jiang, C. & Yu, J. Ultrathin 2D/2D $\\mathrm{WO}_{3}/\\mathrm{g}–\\mathrm{C}_{3}\\mathrm{N}_{4}$ stepscheme $\\mathrm{H}_{2}$ -production photocatalyst. Appl. Catal., B 243, 556–565 (2019). \n30. Xu, Q., Zhang, L., Cheng, B., Fan, J. & Yu, J. S-scheme heterojunction photocatalyst. Chem 6, 1543–1559 (2020). \n31. Pavliuk, M. V., Abdellah, M. & Sá, J. Hydrogen evolution with $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ perovskite nanocrystals under visible light in solution. Mater. Today Commun. 16, 90–96 (2018). \n32. Cai, Z. et al. Preparation and characterization of a bi-layered nano-filtration membrane from a chitosan hydrogel and bacterial cellulose nanofiber for dye removal. Cellulose 25, 5123–5137 (2018). \n33. Low, J., Dai, B., Tong, T., Jiang, C. & Yu, J. In situ irradiated X-ray photoelectron spectroscopy investigation on direct Z-scheme $\\mathrm{TiO}_{2}/\\mathrm{CdS}$ composite film photocatalyst. Adv. Mater. 30, 1802981 (2019). \n34. Xu, F., Zhang, L., Cheng, B. & Yu, J. Direct Z-scheme $\\mathrm{TiO}_{2}/\\mathrm{NiS}$ core–shell hybrid nanofibers with enhanced photocatalytic $\\mathrm{H}_{2}$ -production activity. ACS Sustain. Chem. Eng. 6, 12291–12298 (2018). \n35. Wang, S. et al. Direct Z-scheme ZnO/CdS hierarchical photocatalyst for enhanced photocatalytic $\\mathrm{H}_{2}$ -production activity. Appl. Catal., B 243, 19–26 (2019). \n36. Zhang, S. et al. An artificial photosynthesis system comprising a covalent triazine framework as an electron relay facilitator for photochemical carbon dioxide reduction. J. Mater. Chem. C. 8, 192–200 (2020). \n37. Hu, Y. et al. Tracking mechanistic pathway of photocatalytic $\\mathrm{CO}_{2}$ reaction at Ni sites using operando, time-resolved spectroscopy. J. Am. Chem. Soc. 142, 5618–5626 (2020). \n38. Wang, S. et al. Intermolecular cascaded pi-conjugation channels for electron delivery powering $\\mathrm{CO}_{2}$ photoreduction. Nat. Commun. 11, 1149 (2020). \n39. Yang, X. et al. Oxygen vacancies induced special $\\mathrm{CO}_{2}$ adsorption modes on ${\\mathrm{Bi}}_{2}{\\mathrm{MoO}}_{6}$ for highly selective conversion to $\\mathrm{CH}_{4}$ . Appl. Catal., B 259, 118088 (2019). \n40. Peng, C., Reid, G., Wang, H. & Hu, P. Perspective: photocatalytic reduction of $\\mathrm{CO}_{2}$ to solar fuels over semiconductors. J. Chem. Phys. 147, 030901 (2017). \n41. Xu, F., Xiao, W., Cheng, B. & $\\mathrm{Yu,}$ J. Direct Z-scheme anatase/rutile bi-phase nanocomposite $\\mathrm{TiO}_{2}$ nanofiber photocatalyst with enhanced photocatalytic $\\mathrm{H}_{2}$ -production activity. Int. J. Hydrog. Energ. 39, 15394–15402 (2014). \n42. Das, K., Sharma, S. N., Kumar, M. & De, S. K. Morphology dependent luminescence properties of Co doped $\\mathrm{TiO}_{2}$ nanostructures. J. Phys. Chem. C. 113, 14783–14792 (2009). \n43. Xia, P., Liu, M., Cheng, B., Yu, J. & Zhang, L. Dopamine modified $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ and its enhanced visible-light photocatalytic $\\mathrm{H}_{2}$ -production activity. ACS Sustain. Chem. Eng. 6, 8945–8953 (2018). \n44. Xia, P., Zhu, B., Yu, J., Cao, S. & Jaroniec, M. Ultra-thin nanosheet assemblies of graphitic carbon nitride for enhanced photocatalytic $\\mathrm{CO}_{2}$ reduction. J. Mater. Chem. A 5, 3230–3238 (2017). \n\n# Acknowledgements \n\nThis work was supported by NSFC (51932007, 21573170, U1705251, 51961135303, and 51902121), the National Key Research and Development Program of China (2018YFB1502001), National Postdoctoral Program for Innovative Talents (BX20190259), China Postdoctoral Science Foundation (2019M660189), and the Fundamental Research Funds for the Central Universities (WUT: 2019IVA111). J.X. is grateful to the financial support by the Australian Research Council. The project is also supported by the State Key Laboratory of Advanced Technology for Materials Synthesis and Processing (Wuhan University of Technology) (2018-KF-17). \n\n# Author contributions \n\nF.X., B.C., and J.Y. conceived and designed the experiments. F.X. and K.M. carried out the synthesis of the materials and the characterizations of the materials. F.X. and S.W. carried out the photocatalytic test. F.X., S.W., J.X., and J.Y. contributed to data analysis. J.Y. and J.X. supervised the project. F.X. wrote the paper. J.Y., S.W., and J.X. revised and reviewed the paper. All authors discussed the results and commented on the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-18350-7. \n\nCorrespondence and requests for materials should be addressed to S.W., J.X. or J.Y. \n\nPeer review information Nature Communications thanks Laura Schelhas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1126_science.aay5533", + "DOI": "10.1126/science.aay5533", + "DOI Link": "http://dx.doi.org/10.1126/science.aay5533", + "Relative Dir Path": "mds/10.1126_science.aay5533", + "Article Title": "Intrinsic quantized anomalous Hall effect in a moire heterostructure", + "Authors": "Serlin, M; Tschirhart, CL; Polshyn, H; Zhang, Y; Zhu, J; Watanabe, K; Taniguchi, T; Balents, L; Young, AF", + "Source Title": "SCIENCE", + "Abstract": "The quantum anomalous Hall (QAH) effect combines topology and magnetism to produce precisely quantized Hall resistance at zero magnetic field. We report the observation of a QAH effect in twisted bilayer graphene aligned to hexagonal boron nitride. The effect is driven by intrinsic strong interactions, which polarize the electrons into a single spin- and valley-resolved moire miniband with Chern number C = 1. In contrast to magnetically doped systems, the measured transport energy gap is larger than the Curie temperature for magnetic ordering, and quantization to within 0.1% of the von Klitzing constant persists to temperatures of several kelvin at zero magnetic field. Electrical currents as small as 1 nulloampere controllably switch the magnetic order between states of opposite polarization, forming an electrically rewritable magnetic memory.", + "Times Cited, WoS Core": 1084, + "Times Cited, All Databases": 1189, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000515235800041", + "Markdown": "# Intrinsic quantized anomalous Hall effect in a moiré heterostructure \n\nM. Serlin1, C. L. Tschirhart1, H. Polshyn1, Y. Zhang1, J. Zhu1, K. Watanabe2, T. Taniguchi2, L. Balents3, A. F. Young1\\* \n\n1Department of Physics, University of California, Santa Barbara, Santa Barbara, CA 93106, USA. 2National Institute for Materials Science, 1-1 Namik Tsukuba 305-0044, Japan. 3Kavli Institute for Theoretical Physics, University of California, Santa Barbara, Santa Barbara, CA 93106, USA. \n\n\\*Corresponding author. Email: andrea@physics.ucsb.edu \n\nThe quantum anomalous Hall (QAH) effect combines topology and magnetism to produce precisely quantized Hall resistance at zero magnetic field. We report the observation of a QAH effect in twisted bilayer graphene aligned to hexagonal boron nitride. The effect is driven by intrinsic strong interactions, which polarize the electrons into a single spin and valley resolved moiré miniband with Chern number $c=1$ . In contrast to magnetically doped systems, the measured transport energy gap is larger than the Curie temperature for magnetic ordering, and quantization to within $0.1\\%$ of the von Klitzing constant persists to temperatures of several Kelvin at zero magnetic field. Electrical currents as small as 1 nA controllably switch the magnetic order between states of opposite polarization, forming an electrically rewritable magnetic memory. \n\nTwo dimensional insulators can be classified by the topology of their filled energy bands. In the absence of time reversal symmetry, nontrivial band topology manifests experimentally as a quantized Hall conductivity $\\upsigma_{x y}=C\\frac{e^{2}}{h}$ where $C\\neq0$ is the total Chern number of the filled bands, $e$ is the electron charge, and $h$ is Plank’s constant. Motivated by fundamental questions about the nature of topological phase transitions $(I)$ as well as possible applications in resistance metrology (2) and topological quantum computing (3), significant effort has been devoted to engineering quantum anomalous Hall (QAH) effects showing topologically protected quantized resistance in the absence of an applied magnetic field. To date, QAH effects have been observed only in a narrow class of materials consisting of transition metal doped $(\\mathrm{{Bi},\\mathrm{{Sb})_{2}\\mathrm{{Te_{3}}}}}$ (4–10). In these materials, ordering of the dopant magnetic moments breaks time reversal symmetry, combining with the strongly spin-orbit coupled electronic structure to produce topologically nontrivial Chern bands $(I I)$ . However, the performance of these materials is limited by the inhomogeneous distribution of the magnetic dopants, which leads to microscopic structural, charge, and magnetic disorder (12–15). As a result, quantization occurs at temperatures that are approximately one order of magnitude smaller than the magnetic ordering temperature (4–6). \n\nMoiré graphene heterostructures provide the two essential ingredients—topological bands and strong correlations— necessary for engineering intrinsic quantum anomalous Hall effects. For both graphene on hexagonal boron nitride (hBN) and twisted multilayer graphene, moiré patterns generically produce bands with finite Chern number (16–19), with time reversal symmetry of the single particle band structure enforced by the cancellation of Chern numbers in opposite graphene valleys. In certain heterostructures, notably twisted bilayer graphene (tBLG) with interlayer twist angle $\\mathbf{\\uptheta}\\approx\\mathbf{\\up1.1^{\\circ}}$ and rhombohedral graphene aligned to hBN, the bandwidth of these Chern bands can be made exceptionally small $(I7,$ 20–22), favoring correlation driven states that break one or more spin, valley, or lattice symmetries. Experiments have indeed found correlation driven low temperature phases at integer band fillings when these bands are sufficiently flat (22– 26). Remarkably, states showing magnetic hysteresis indicative of time-reversal symmetry breaking have recently been reported in both tBLG (27) and ABC/hBN heterostructures (28) at commensurate filling. These systems show large anomalous Hall effects highly suggestive of an incipient Chern insulator at $B=0$ . \n\nHere we report the observation of a QAH effect showing robust zero magnetic field quantization in a flat band $(\\Theta\\approx$ $\\mathbf{1.1}5\\pm0.01^{\\circ}.$ ) tBLG sample aligned to hBN . The electronic structure of flat-band tBLG is described by two distinct bands per spin and valley projection isolated from higher energy dispersive bands by an energy gap. The total capacity of the flat bands is eight electrons per unit cell, spanning $-4<\\upnu<$ 4, where we define the band filling factor $\\upnu=n A_{\\mathrm{m}}$ with $n$ the electron density and $A_{\\mathrm{m}}\\approx130~\\mathrm{nm^{2}}$ the area of the moiré unit cell. Figure 1A shows the longitudinal and Hall resistances 1 $\\scriptstyle\\mathbf{\\mathcal{R}}_{x x}$ and $R_{x y,}$ measured at a magnetic field $B=150~\\mathrm{mT}$ (29) and temperature $T=1.6\\mathrm{~K~}$ as a function of charge density over the entire flat band. The sample is insulating at the overall charge neutral point and shows a weak resistance peak at $\\upnu=2$ . In addition, we observe $R_{x y}$ approaching $\\scriptstyle h/e^{2}$ in a narrow range of density near $\\upnu=3$ , concomitant with a deep minimum in $R_{x x}$ reminiscent of an integer quantum Hall state. \n\nFigure 1B shows the magnetic field dependence of both $R_{x x}$ and $R_{x y}$ at a density of $n=2.37\\times10^{12}~\\mathrm{cm^{-2}}$ measured at $T=1.6\\mathrm{~K~}$ . The Hall resistivity is hysteretic, with a coercive field of several tens of millitesla, and we observe a well quantized $R_{x y}~=~h/e^{2}$ along with $R_{x x}<1~\\mathrm{k}\\Omega$ persisting through $B=0$ indicative of a QAH state stabilized by spontaneously broken time reversal symmetry. The switching transitions are marked by discrete Barkhausen jumps in the resistance on the order of $\\scriptstyle h/e^{2}$ in both $R_{x x}$ and $R_{x y},$ typical of magnetic systems consisting of a small number of domains $(\\mathit{I5},\\mathit{30})$ . Figure 1C shows the detailed density evolution of the $R_{x y}$ hysteresis near $\\upnu=3$ . Both the coercive field and zero-field Hall resistance are maximal near $\\upnu=3$ , although hysteresis can be observed over a much broader range of ν between 2.84 and 3.68 (see fig. S13). Notably, quantized response is only observed for a particular choice of contacts at one end of the device (29). \n\nFigure 1D shows a schematic representation of the band structure at full filling $(\\upnu=4)$ and at $\\upnu=3$ . In the absence of interaction-driven order, the spin-degenerate bands in each valley have total Chern number $\\pm2$ . The observed QAH state occurs because the exchange energy is minimized when an excess valley- and spin-polarized Chern band (18, 19) is occupied, spontaneously breaking time-reversal symmetry. Magnetic order in two dimensions requires anisotropy. In graphene, the vanishingly small spin orbit coupling provides negligible anisotropy for the spin system. It is thus likely that the observed magnetism is orbital, with strong, easy-axis anisotropy arising from the two dimensional nature of the graphene bands (18, 19, 26, 27, 31). \n\nThe phenomenology of $\\upnu=3$ filling is nonuniversal across tBLG devices: some samples are metallic (23, 24), some $(26,$ 32) show a robust, thermally activated, trivial insulator whereas others show an anomalous Hall effect (27). This is consistent with theoretical expectations (31) that the phase diagram at integer ν is highly sensitive to details including the interlayer twist angle, both uniform and inhomogeneous strains (33), as well as alignment to an hBN encapsulant layer. The prior report of magnetic hysteresis at $\\upnu=3$ was indeed associated with close alignment of one of the two hBN layers (27). Theoretical analysis has shown $(I8,I9)$ that the resulting breaking of the $C_{2}$ rotation symmetry of tBLG strongly favors a QAH state at $\\upnu=3$ . \n\nThe device presented here is nominally aligned to one of the hBN layers (fig. S1), and additionally shows a number of signatures that suggest strong modifications of the band structure relative to unaligned devices. First, our device shows only a weakly resistive feature at $\\upnu=2$ , but a robust thermally activated insulator at charge neutrality. Remarkably, the activation gap for this $\\upnu=0$ insulator is larger than even the gaps for the states at $\\upnu=\\pm4$ , which are much smaller than typical (fig. S10) (29). Second, the quantum oscillations are highly anomalous, with hole-like quantum oscillations originating at $\\upnu=2$ , again in contrast to all prior reports (fig. S11) (23–26). Additional Landau fan features also appear consistent with hBN alignment of $0.6^{\\circ}$ (fig. S6); however, twist angle variations within the tBLG itself preclude unambiguous determination of the hBN-tBLG twist angle. Although no detailed theory for these observations is available, the extreme sensitivity of the detailed structure of the flat bands to model parameters, combined with observations that hBN substrates can produce energy gaps as large as $30\\mathrm{\\meV}$ in monolayer graphene (34), point to the role of the substrate in tipping the balance between competing many-body ground states at $\\upnu=3$ in favor of the QAH state. Taken together, these observations suggest that hBN aligned samples constitute a different class of tBLG devices with distinct phenomenology. \n\nFigure 2, A and B, shows the temperature dependence of major hysteresis loops in $R_{x x}$ and $R_{x y},$ , respectively. As $T$ increases, we observe both a departure from resistance quantization and a suppression of hysteresis, with the Hall effect showing linear behavior in field by $T=12\\mathrm{~K~}$ . In our measurements, we observe resistance offsets of ${\\sim}1\\mathrm{k}\\Omega$ from the ideal quantized value, which vanish when resistance is symmetrized or antisymmetrized with respect to magnetic field (or, for $B\\approx0$ , with respect to field training). For quantitative analysis of the $T$ -dependent data, we thus study field-training symmetrized resistances, denoted $\\overline{{R}}_{x y}$ and $\\overline{{R}}_{x x}$ . Figure 2C shows $\\overline{{R}}_{x y}\\left(0\\right)$ . Finite hysteresis is observed up to temperatures of $8\\mathrm{~K~}$ (Fig. 2C), consistent with the Curie temperature $T_{\\mathrm{C}}\\approx7.5\\ \\mathrm{K}$ determined from an Arrott plot (fig. S12). $\\overline{{R}}_{_{x y}}$ remains quantized up to $T\\approx3\\ \\mathrm{K},$ , with the average value of $\\big(1.0010\\pm0.0002\\big)\\times\\frac{h}{e^{2}}$ between 2 and $2.7\\mathrm{K}.$ . \n\nTo quantitatively assess the energy scales associated with the QAH state, we measure the activation energy at low temperature. Figure 2D shows both the measured $\\overline{{R}}_{x x}$ and the deviation from quantization of the Hall resistance, $\\delta\\overline{{R}}_{_{x y}}=h/e^{2}-\\overline{{R}}_{_{x y}}$ , on an Arrhenius plot. We assume that the Hall conductivity $\\upsigma_{x y}$ is approximately $T-$ -independent and the longitudinal conductivity ${\\upsigma_{x x}}\\sim e^{-\\triangle/(2T)}$ , where $\\Delta$ is the energy cost of creating and separating a particle-antiparticle excitation of the QAH state. Within this picture, inverting the conductivity tensor gives $\\delta R_{x y}\\sim e^{-\\Delta/(T)}$ and $R_{x x}\\sim e^{-\\Delta/(2T)}$ (29). We find the activation gaps extracted from fitting $\\delta\\overline{{R}}_{x y}$ and $\\overline{{R}}_{x x}$ to be $\\Delta=26\\pm4\\mathrm{K}$ and $\\Delta=31\\pm12\\mathrm{~K~}$ , respectively, with the large uncertainty in the latter arising from the absence of a single simply activated regime (29). The activation energy is thus several times larger than $T_{\\mathrm{c},}$ in contrast to magnetically doped topological insulator films where activation gaps are typically 10 to 50 times smaller than $T_{\\mathrm{C}}\\left(5,6,29\\right)$ . \n\nFerromagnetic domains in tBLG interact strongly with applied current (27). In our device, this allows deterministic electrical control over domain polarization using exceptionally small DC currents. Figure 3A shows $R_{x y}$ at $6.5\\mathrm{~K~}$ and $B=0$ , measured using a small AC excitation of ${\\sim}100~\\mathrm{pA}$ to which we add a variable DC current bias. We find that the applied DC currents drive switching analogous to that observed in an applied magnetic field, producing hysteretic switching between magnetization states. DC currents of a few nanoamps are sufficient to completely reverse the magnetization, which is then indefinitely stable (29). Figure 3B shows deterministic writing of a magnetic bit using current pulses, and its nonvolatile readout using the large resulting change in the anomalous Hall resistance. High fidelity writing is accomplished with $20\\mathrm{nA}$ current pulses while readout requires ${<}100\\ \\mathrm{pA}$ of applied AC current. \n\nAssuming a uniform current density in our micron-sized, two atom thick tBLG device results in an estimated current density $J<10^{3}\\mathrm{\\A{\\cdot}c m^{-2}}$ . Although current-induced switching at smaller DC current densities of $J\\approx10^{2}\\ \\mathrm{A{\\cdot}c m^{-2}}$ has been realized in MnSi, readout of the magnetization state in this material has so far only been demonstrated using neutron scattering (35). Compared with other systems that allow in situ electrical readout, such as GaMnAs $(J=3.4\\times10^{5}\\mathrm{A{\\cdot}c m^{-2}})$ 1 (36) and $\\mathrm{Cr-(BiSb)_{2}T e_{3}}$ heterostructures $(J=8.9\\times10^{4}\\mathrm{{A}{\\cdot}\\mathrm{{cm}^{-2})}}$ 1 (37), the applied current densities are at least one order of magnitude lower. More relevant to device applications, the absolute magnitude of the current required to switch the magnetization state of the system $({\\sim}10^{-9}~\\mathrm{A})$ in our device is, to our knowledge, considerably smaller than reported in any system. \n\nFigure 3C shows the Hall resistance at $T=7\\mathrm{{K}}$ , just below the onset of hysteresis, measured as a function of magnetic field and current. At zero magnetic field, opposite signs of DC current stabilize opposite magnetic polarizations. Furthermore, when a static field is present, DC currents can stabilize configurations disfavored by the applied field. Current breaks time reversal symmetry, but mirror symmetry across the plane perpendicular to the sample and parallel to the net current flow precludes an injected charge from favoring a particular out-of-plane polarization. We propose (29) a simple mechanism for the low-current switching that arises from the interplay of edge state physics and device asymmetry. In a QAH state, an applied current generates a chemical potential difference between the chiral one dimensional modes located on opposite sample edges. Owing to the opposite dispersion of a given edge state in opposite magnetic states (which have opposite $C_{\\iota}$ , the DC current $I$ changes the energy of the system by $\\delta E\\sim\\pm\\frac{8\\pi^{2}}{3}\\frac{\\hbar^{2}}{m e^{3}\\nu^{3}}L I^{3}$ for a $C=\\pm1$ state, where $m$ and $v$ are the edge state effective mass and velocity, $e$ is the elementary charge, and $L$ is the length of the edge state. When the edges have different lengths or velocities, the current favors one of the two domains, with the sign and magnitude of the effect dictated by the device asymmetry. For a current in the range of $I=10$ to $\\mathrm{100~nA}$ , comparable to the switching currents observed at low temperatures, using estimates of $m$ and $v$ based on bulk measurements (29) and assuming an edge length difference of ${\\approx}1~{\\upmu}\\mathrm{m}$ gives $\\delta E$ comparable to the magnetic dipole energy caused by a 1 mT field. \n\nWe note that although this effect should be generic to all QAH systems, it is likely to be dominant at low currents in tBLG because of the weak pinning of magnetic domains and small device dimensions. Crucially, it provides an engineering parameter for electrical control of domain structure that can be deterministically encoded in the device geometry. \n\n# REFERENCES AND NOTES \n\n1. F. D. M. Haldane, Model for a quantum Hall effect without Landau levels: Condensedmatter realization of the “parity anomaly”. Phys. Rev. Lett. 61, 2015–2018 (1988). doi:10.1103/PhysRevLett.61.2015 Medline \n2. M. Götz, K. M. Fijalkowski, E. Pesel, M. Hartl, S. Schreyeck, M. Winnerlein, S. Grauer, H. Scherer, K. Brunner, C. Gould, F. J. Ahlers, L. W. Molenkamp, Precision measurement of the quantized anomalous Hall resistance at zero magnetic field. Appl. Phys. Lett. 112, 072102 (2018). doi:10.1063/1.5009718 \n3. B. Lian, X.-Q. Sun, A. Vaezi, X.-L. Qi, S.-C. Zhang, Topological quantum computation based on chiral Majorana fermions. Proc. Natl. Acad. Sci. U.S.A. 115, 10938–10942 (2018). doi:10.1073/pnas.1810003115 Medline \n4. C.-Z. Chang, J. Zhang, X. Feng, J. Shen, Z. Zhang, M. Guo, K. Li, Y. Ou, P. Wei, L.-L. Wang, Z.-Q. Ji, Y. Feng, S. Ji, X. Chen, J. Jia, X. Dai, Z. Fang, S.-C. Zhang, K. He, Y. Wang, L. Lu, X.-C. Ma, Q.-K. Xue, Experimental observation of the quantum anomalous Hall effect in a magnetic topological insulator. Science 340, 167–170 (2013). doi:10.1126/science.1234414 Medline \n5. C.-Z. Chang, W. Zhao, D. Y. Kim, H. Zhang, B. A. Assaf, D. Heiman, S.-C. Zhang, C. Liu, M. H. W. Chan, J. S. Moodera, High-precision realization of robust quantum anomalous Hall state in a hard ferromagnetic topological insulator. Nat. Mater. 14, 473–477 (2015). doi:10.1038/nmat4204 Medline \n6. M. Mogi, R. Yoshimi, A. Tsukazaki, K. Yasuda, Y. Kozuka, K. S. Takahashi, M. Kawasaki, Y. Tokura, Magnetic modulation doping in topological insulators toward higher-temperature quantum anomalous Hall effect. Appl. Phys. Lett. 107, 182401 (2015). doi:10.1063/1.4935075 \n7. X. Kou, L. Pan, J. Wang, Y. Fan, E. S. Choi, W. L. Lee, T. Nie, K. Murata, Q. Shao, S. C. Zhang, K. L. Wang, Metal-to-insulator switching in quantum anomalous Hall states. Nat. Commun. 6, 8474 (2015). doi:10.1038/ncomms9474 Medline \n8. X. Kou, S.-T. Guo, Y. Fan, L. Pan, M. Lang, Y. Jiang, Q. Shao, T. Nie, K. Murata, J. Tang, Y. Wang, L. He, T.-K. Lee, W.-L. Lee, K. L. Wang, Scale-invariant quantum anomalous Hall effect in magnetic topological insulators beyond the twodimensional limit. Phys. Rev. Lett. 113, 137201 (2014). doi:10.1103/PhysRevLett.113.137201 Medline \n9. J. Wang, B. Lian, H. Zhang, Y. Xu, S.-C. Zhang, Quantum anomalous Hall effect with higher plateaus. Phys. Rev. Lett. 111, 136801 (2013). doi:10.1103/PhysRevLett.111.136801 Medline \n10. J. G. Checkelsky, R. Yoshimi, A. Tsukazaki, K. S. Takahashi, Y. Kozuka, J. Falson, M. Kawasaki, Y. Tokura, Trajectory of the anomalous Hall effect towards the \n\nquantized state in a ferromagnetic topological insulator. Nat. Phys. 10, 731–736 (2014). doi:10.1038/nphys3053 11. R. Yu, W. Zhang, H.-J. Zhang, S.-C. Zhang, X. Dai, Z. Fang, Quantized anomalous Hall effect in magnetic topological insulators. Science 329, 61–64 (2010). doi:10.1126/science.1187485 Medline 12. E. O. Lachman, A. F. Young, A. Richardella, J. Cuppens, H. R. Naren, Y. Anahory, A. Y. Meltzer, A. Kandala, S. Kempinger, Y. Myasoedov, M. E. Huber, N. Samarth, E. Zeldov, Visualization of superparamagnetic dynamics in magnetic topological insulators. Sci. Adv. 1, e1500740 (2015). doi:10.1126/sciadv.1500740 Medline 13. I. Lee, C. K. Kim, J. Lee, S. J. Billinge, R. Zhong, J. A. Schneeloch, T. Liu, T. Valla, J. M. Tranquada, G. Gu, J. C. Davis, Imaging Dirac-mass disorder from magnetic dopant atoms in the ferromagnetic topological insulator Crx(Bi0.1Sb0.9)2-xTe3. Proc. Natl. Acad. Sci. U.S.A. 112, 1316–1321 (2015). Medline 14. W. Wang, F. Yang, C. Gao, J. Jia, G. D. Gu, W. Wu, Visualizing ferromagnetic domains in magnetic topological insulators. APL Mater. 3, 083301 (2015). doi:10.1063/1.4921093 15. K. Yasuda, M. Mogi, R. Yoshimi, A. Tsukazaki, K. S. Takahashi, M. Kawasaki, F. Kagawa, Y. Tokura, Quantized chiral edge conduction on domain walls of a magnetic topological insulator. Science 358, 1311–1314 (2017). doi:10.1126/science.aan5991 Medline 16. J. C. W. Song, P. Samutpraphoot, L. S. Levitov, Topological Bloch bands in graphene superlattices. Proc. Natl. Acad. Sci. U.S.A. 112, 10879–10883 (2015). doi:10.1073/pnas.1424760112 Medline 17. Y.-H. Zhang, D. Mao, Y. Cao, P. Jarillo-Herrero, T. Senthil, Nearly flat Chern bands in moiré superlattices. Phys. Rev. B 99, 075127 (2019). doi:10.1103/PhysRevB.99.075127 18. N. Bultinck, S. Chatterjee, M. P. Zaletel, Anomalous Hall ferromagnetism in twisted bilayer graphene. arXiv:1901.08110 [cond-mat.str-el] (23 January 2019). 19. Y.-H. Zhang, D. Mao, T. Senthil, Twisted Bilayer Graphene Aligned with Hexagonal Boron Nitride: Anomalous Hall Effect and a Lattice Model. arXiv:1901.08209 [cond-mat.str-el] (24 January 2019). 20. R. Bistritzer, A. H. MacDonald, Moire bands in twisted double-layer graphene. Proc. Natl. Acad. Sci. U.S.A. 108, 12233–12237 (2011). doi:10.1073/pnas.1108174108 Medline 21. E. Suárez Morell, J. D. Correa, P. Vargas, M. Pacheco, Z. Barticevic, Flat bands in slightly twisted bilayer graphene: Tight-binding calculations. Phys. Rev. B. 82, 121407 (2010). doi:10.1103/PhysRevB.82.121407 22. G. Chen, L. Jiang, S. Wu, B. Lyu, H. Li, B. L. Chittari, K. Watanabe, T. Taniguchi, Z. Shi, J. Jung, Y. Zhang, F. Wang, Evidence of a gate-tunable Mott insulator in a trilayer graphene moire superlattice. Nat. Phys. 15, 237–241 (2019). doi:10.1038/s41567-018-0387-2 23. Y. Cao, V. Fatemi, A. Demir, S. Fang, S. L. Tomarken, J. Y. Luo, J. D. SanchezYamagishi, K. Watanabe, T. Taniguchi, E. Kaxiras, R. C. Ashoori, P. Jarillo-Herrero, Correlated insulator behaviour at half-filling in magic-angle graphene superlattices. Nature 556, 80–84 (2018). doi:10.1038/nature26154 Medline 24. Y. Cao, V. Fatemi, S. Fang, K. Watanabe, T. Taniguchi, E. Kaxiras, P. Jarillo-Herrero, Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43–50 (2018). doi:10.1038/nature26160 Medline 25. M. Yankowitz, S. Chen, H. Polshyn, Y. Zhang, K. Watanabe, T. Taniguchi, D. Graf, A. F. Young, C. R. Dean, Tuning superconductivity in twisted bilayer graphene. Science 363, 1059–1064 (2019). doi:10.1126/science.aav1910 Medline 26. X. Lu, P. Stepanov, W. Yang, M. Xie, M. A. Aamir, I. Das, C. Urgell, K. Watanabe, T. Taniguchi, G. Zhang, A. Bachtold, A. H. MacDonald, D. K. Efetov, Superconductors, orbital magnets and correlated states in magic-angle bilayer graphene. Nature 574, 653–657 (2019). doi:10.1038/s41586-019-1695-0 Medline 27. A. L. Sharpe, E. J. Fox, A. W. Barnard, J. Finney, K. Watanabe, T. Taniguchi, M. A. Kastner, D. Goldhaber-Gordon, Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene. Science 365, 605–608 (2019). doi:10.1126/science.aaw3780 Medline 28. G. Chen, A. L. Sharpe, E. J. Fox, Y.-H. Zhang, S. Wang, L. Jiang, B. Lyu, H. Li, K. Watanabe, T. Taniguchi, Z. Shi, T. Senthil, D. Goldhaber-Gordon, Y. Zhang, F. Wang. Tunable Correlated Chern Insulator and Ferromagnetism in Trilayer Graphene/Boron Nitride Moiré Superlattice. arXiv:1905.06535 [cond-mat.meshall] (16 May 2019). 29. See supplementary materials \n\n30. M. Liu, W. Wang, A. R. Richardella, A. Kandala, J. Li, A. Yazdani, N. Samarth, N. P. Ong, Large discrete jumps observed in the transition between Chern states in a ferromagnetic topological insulator. Sci. Adv. 2, e1600167 (2016). doi:10.1126/sciadv.1600167 Medline \n31. M. Xie, A. H. MacDonald, On the nature of the correlated insulator states in twisted bilayer graphene. arXiv:1812.04213 [cond-mat.str-el] (11 December 2018). \n32. M. Yankowitz, J. I.-J. Wang, A. G. Birdwell, Y.-A. Chen, K. Watanabe, T. Taniguchi, P. Jacquod, P. San-Jose, P. Jarillo-Herrero, B. J. LeRoy, Electric field control of soliton motion and stacking in trilayer graphene. Nat. Mater. 13, 786–789 (2014). doi:10.1038/nmat3965 Medline \n33. S. Liu, E. Khalaf, J. Y. Lee, A. Vishwanath, Nematic topological semimetal and insulator in magic angle bilayer graphene at charge neutrality. arXiv:1905.07409 [cond-mat.str-el] (17 May 2019). \n34. B. Hunt, J. D. Sanchez-Yamagishi, A. F. Young, M. Yankowitz, B. J. LeRoy, K. Watanabe, T. Taniguchi, P. Moon, M. Koshino, P. Jarillo-Herrero, R. C. Ashoori, Massive Dirac fermions and Hofstadter butterfly in a van der Waals heterostructure. Science 340, 1427–1430 (2013). doi:10.1126/science.1237240 Medline \n35. F. Jonietz, S. Mühlbauer, C. Pfleiderer, A. Neubauer, W. Münzer, A. Bauer, T. Adams, R. Georgii, P. Böni, R. A. Duine, K. Everschor, M. Garst, A. Rosch, Spin transfer torques in MnSi at ultralow current densities. Science 330, 1648–1651 (2010). doi:10.1126/science.1195709 Medline \n36. M. Jiang, H. Asahara, S. Sato, T. Kanaki, H. Yamasaki, S. Ohya, M. Tanaka, Efficient full spin-orbit torque switching in a single layer of a perpendicularly magnetized single-crystalline ferromagnet. Nat. Commun. 10, 2590 (2019). doi:10.1038/s41467-019-10553-x Medline \n37. Y. Fan, P. Upadhyaya, X. Kou, M. Lang, S. Takei, Z. Wang, J. Tang, L. He, L.-T. Chang, M. Montazeri, G. Yu, W. Jiang, T. Nie, R. N. Schwartz, Y. Tserkovnyak, K. L. Wang, Magnetization switching through giant spin-orbit torque in a magnetically doped topological insulator heterostructure. Nat. Mater. 13, 699–704 (2014). doi:10.1038/nmat3973 Medline \n38. M. Serlin, C. L. Tschirhart, H. Polshyn, Y. Zhang, J. Zhu, K. Watanabe, T. Taniguchi, L. Balents, A. F. Young, Intrinsic quantized anomalous Hall effect in a moiré heterostructure, Version 2, Dryad (2019); https://doi.org/10.5061/dryad.ffbg79cqks. \n39. K. Kim, M. Yankowitz, B. Fallahazad, S. Kang, H. C. P. Movva, S. Huang, S. Larentis, C. M. Corbet, T. Taniguchi, K. Watanabe, S. K. Banerjee, B. J. LeRoy, E. Tutuc, van der Waals heterostructures with high accuracy rotational alignment. Nano Lett. 16, 1989–1995 (2016). doi:10.1021/acs.nanolett.5b05263 Medline \n40. A. A. Zibrov, C. Kometter, H. Zhou, E. M. Spanton, T. Taniguchi, K. Watanabe, M. P. Zaletel, A. F. Young, Tunable interacting composite fermion phases in a halffilled bilayer-graphene Landau level. Nature 549, 360–364 (2017). doi:10.1038/nature23893 Medline \n41. L. Wang, I. Meric, P. Y. Huang, Q. Gao, Y. Gao, H. Tran, T. Taniguchi, K. Watanabe, L. M. Campos, D. A. Muller, J. Guo, P. Kim, J. Hone, K. L. Shepard, C. R. Dean, Onedimensional electrical contact to a two-dimensional material. Science 342, 614– 617 (2013). doi:10.1126/science.1244358 Medline \n42. H. H. Sample, W. J. Bruno, S. B. Sample, E. K. Sichel, Reverse-field reciprocity for conducting specimens in magnetic fields. J. Appl. Phys. 61, 1079–1084 (1987). doi:10.1063/1.338202 \n43. A. Uri, S. Grover, Y. Cao, J. A. Crosse, K. Bagani, D. Rodan-Legrain, Y. Myasoedov, K. Watanabe, T. Taniguchi, P. Moon, M. Koshino, P. Jarillo-Herrero, E. Zeldov, Mapping the twist angle and unconventional landau levels in magic angle graphene. arXiv:1908.04595 [cond-mat.mes-hall] (13 August 2019). \n44. E. M. Spanton, A. A. Zibrov, H. Zhou, T. Taniguchi, K. Watanabe, M. P. Zaletel, A. F. Young, Observation of fractional Chern insulators in a van der Waals heterostructure. Science 360, 62–66 (2018). doi:10.1126/science.aan8458 Medline \n45. F. Amet, J. R. Williams, K. Watanabe, T. Taniguchi, D. Goldhaber-Gordon, Insulating behavior at the neutrality point in single-layer graphene. Phys. Rev. Lett. 110, 216601 (2013). doi:10.1103/PhysRevLett.110.216601 Medline \n46. H. Polshyn, M. Yankowitz, S. Chen, Y. Zhang, K. Watanabe, T. Taniguchi, C. R. Dean, A. F. Young, Large linear-in-temperature resistivity in twisted bilayer graphene. Nat. Phys. 15, 1011–1016 (2019). doi:10.1038/s41567-019-0596-3 \n47. A. Arrott, Criterion for ferromagnetism from observations of magnetic isotherms. Phys. Rev. 108, 1394–1396 (1957). doi:10.1103/PhysRev.108.1394 \n48. D. Chiba, S. Fukami, K. Shimamura, N. Ishiwata, K. Kobayashi, T. Ono, Electrical control of the ferromagnetic phase transition in cobalt at room temperature. Nat. Mater. 10, 853–856 (2011). doi:10.1038/nmat3130 Medline \n\n# ACKNOWLEDGMENTS \n\nThe authors acknowledge discussions with A. Macdonald, Y. Saito, and M. Zaletel. Funding: Device fabrication was supported by the ARO under W911NF-17-1- 0323. Measurements were supported by the AFOSR under FA9550-16-1-0252. C.T. acknowledges support from the Hertz Foundation and from the NSF GRFP under Grant No. 1650114. L.B. was supported by the DOE Office of Sciences Basic Energy Sciences program under Award No. DE-FG02-08ER46524. A.F.Y. acknowledges the support of the David and Lucille Packard Foundation and the Alfred P. Sloan foundation. Author contributions: Y.Z. and H.P. fabricated the device. M.S., C.T., H.P., J.Z., and A.F.Y. performed the measurements and analyzed the data. T.T. and K.W. provided the hBN crystals. L.B. formulated the theoretical model for the current-induced switching. M.S., C.T., H.P., L.B., and A.F.Y. wrote the manuscript. Competing interests: The authors declare they have no competing interests. Data and materials availability: All data shown in the main text and supplementary material are available on the Dryad data repository (38). \n\nSUPPLEMENTARY MATERIALS \nscience.sciencemag.org/cgi/content/full/science.aay5533/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S17 \nReferences (39–48) \n\n29 June 2019; accepted 6 December 2019 \nPublished online 19 December 2019 \n10.1126/science.aay5533 \n\n![](images/3de70c66f603f306eefeb7a5153df9251694a97b95c045e0777ffccfd0001a5a.jpg) \nFig. 1. Quantized anomalous Hall effect in twisted bilayer graphene at $1.6\\mathsf{K}$ . (A) Longitudinal resistance $R_{x x}$ and Hall resistance $R_{x y}$ as a function of carrier density $n$ at $150~\\mathrm{mT}$ . $R_{x y}$ reaches $h/{\\tt e}^{2}$ and $R_{x x}$ approaches zero near $\\upnu=3$ . Data are corrected for mixing of $R_{x x}$ and $R_{x y}$ components by symmetrizing with respect to magnetic field at $B=\\pm150~\\mathrm{mT}$ (29). (B) Longitudinal resistance $R_{x x}$ and Hall resistance $R_{x y}$ measured at $n=2.37~\\times$ $10^{12}\\mathsf{c m}^{-2}$ as a function of $B$ . Data are corrected for mixing using contact symmetrization (29). Sweep directions are indicated by arrows. (C) Hall resistance $R_{x y}$ as a function of magnetic field $B$ and density $\\boldsymbol{\\mathsf{\\Pi}}_{n}$ . Hysteresis loop areas are shaded for clarity. The rear wall shows field-training symmetrized values of $R_{x y}$ at $B=0$ . $R_{x y}(0)$ becomes nonzero when ferromagnetism appears, and reaches a plateau of $h/{\\mathsf e}^{2}$ near a density of $n=2.37\\times$ $10^{12}\\mathsf{c m}^{-2}$ . (D) Schematic band structure at full filling of a moiré unit cell $(\\upnu=4)$ ) and $\\upnu=3$ . The net Chern number $C_{\\mathrm{net}}\\neq0$ at $\\upnu=3$ . \n\n![](images/763e672826775109bf13d53947e5321b8226d148c454d4b02be706234c0bc262.jpg) \n\nFig. 2. Temperature dependence of the quantum anomalous Hall effect. (A) $R_{x y}$ and (B) $R_{x x}$ as a function of $B$ measured at various temperatures for $n=2.37\\times10^{12}{\\mathsf{c m}}^{-2}$ . $R_{x x}$ and $R_{x y}$ mixing was corrected using contact symmetrization (29). (C) Temperature dependence of the field-training symmetrized resistance $\\overline{{R}}_{x y}$ at $B=0$ , as described in the main text. The Curie temperature was determined to be $T_{\\mathtt{C}}\\approx7.5(.5)\\ \\mathsf{K}$ using an Arrott plot analysis (see fig. S12). Inset: detailed lowtemperature dependence of the deviation of $\\overline{{R}}_{x y}$ from the quantized value at $B=0$ . Error bars are the standard error derived from 11 consecutive measurements. $\\overline{{R}}_{x y}$ saturates below ${\\approx}3\\mathrm{~K~}$ to a value of $(1.0010\\pm0.0002)\\times\\frac{h}{e^{2}}$ , determined by averaging the points between 2 and $2.7\\mathsf{K}.$ (D) Arrhenius plots of field training symmetrized resistances $\\overline{{R}}_{x x}$ and $\\delta\\overline{{R}}_{x y}=h/e^{2}-\\overline{{R}}_{x y}$ at $B\\ =\\ 0$ . Dotted lines denote representative activation fits. Systematic treatment of uncertainty arising from the absence of a single activated regime gives $\\Delta=31\\pm11\\mathsf{K}$ and $26\\pm41$ for $\\overline{{R}}_{_{x x}}$ and $\\delta\\overline{{R}}_{x y}$ , respectively (29). \n\n![](images/c4b9add06bf8ece49750547a212cb097d0cc1dff5655628ccb3f8263f0cfff16.jpg) \nFig. 3. Current controlled magnetic switching. (A) $R_{x y}$ as a function of applied DC current, showing hysteresis as a function of DC current analogous to the response to an applied magnetic field at $6.5{\\sf K}.$ . Insets: schematic illustrations of current controlled orbital magnetism. (B) Nonvolatile electrical writing and reading of a magnetic bit at $T=6.5~\\mathsf{K}$ and $B=0$ . A succession of 20 nA current pulses of alternating signs controllably reverses the magnetization, which is read out using the Hall resistance. The magnetization state of the bit is stable for at least $10^{3}\\mathsf{s}$ (29). (C) $R_{x y}$ as a function of both DC bias current and magnetic field at 7 K. Opposite directions of DC current preferentially stabilize opposite magnetization states of the bit. Measurements presented in (A to C) are neither field nor Onsager symmetrized, which why there is an offset in $R_{x y}$ . \n\n# Science \n\n# Intrinsic quantized anomalous Hall effect in a moiré heterostructure \n\nM. Serlin, C. L. Tschirhart, H. Polshyn, Y. Zhang, J. Zhu, K. Watanabe, T. Taniguchi, L. Balents and A. F. Young \n\npublished online December 19, 2019 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1002_adma.202003021", + "DOI": "10.1002/adma.202003021", + "DOI Link": "http://dx.doi.org/10.1002/adma.202003021", + "Relative Dir Path": "mds/10.1002_adma.202003021", + "Article Title": "An In-Depth Study of Zn Metal Surface Chemistry for Advanced Aqueous Zn-Ion Batteries", + "Authors": "Hao, JN; Li, B; Li, XL; Zeng, XH; Zhang, SL; Yang, FH; Liu, SL; Li, D; Wu, C; Guo, ZP", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "Although Zn metal has been regarded as the most promising anode for aqueous batteries, it persistently suffers from serious side reactions and dendrite growth in mild electrolyte. Spontaneous Zn corrosion and hydrogen evolution damage the shelf life and calendar life of Zn-based batteries, severely affecting their industrial applications. Herein, a robust and homogeneous ZnS interphase is built in situ on the Zn surface by a vapor-solid strategy to enhance Zn reversibility. The thickness of the ZnS film is controlled via the treatment temperature, and the performance of the protected Zn electrode is optimized. The dense ZnS artificial layer obtained at 350 degrees C not only suppresses Zn corrosion by forming a physical barrier on the Zn surface, but also inhibits dendrite growth via guiding the Zn plating/stripping underneath the artificial layer. Accordingly, a side reaction-free and dendrite-free Zn electrode is developed, the effectiveness of which is also convincing in a MnO2/ZnS@Zn full-cell with 87.6% capacity retention after 2500 cycles.", + "Times Cited, WoS Core": 901, + "Times Cited, All Databases": 920, + "Publication Year": 2020, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000546717000001", + "Markdown": "# An In-Depth Study of Zn Metal Surface Chemistry for Advanced Aqueous Zn-Ion Batteries \n\nJunnan Hao, Bo Li, Xiaolong Li, Xiaohui Zeng, Shilin Zhang, Fuhua Yang, Sailin Liu, Dan Li, Chao Wu, and Zaiping Guo\\* \n\nAlthough Zn metal has been regarded as the most promising anode for aqueous batteries, it persistently suffers from serious side reactions and dendrite growth in mild electrolyte. Spontaneous Zn corrosion and hydrogen evolution damage the shelf life and calendar life of Zn-based batteries, severely affecting their industrial applications. Herein, a robust and homogeneous ZnS interphase is built in situ on the Zn surface by a vapor–solid strategy to enhance Zn reversibility. The thickness of the ZnS film is controlled via the treatment temperature, and the performance of the protected Zn electrode is optimized. The dense ZnS artificial layer obtained at $350^{\\circ}mathsf{C}$ not only suppresses Zn corrosion by forming a physical barrier on the Zn surface, but also inhibits dendrite growth via guiding the Zn plating/stripping underneath the artificial layer. Accordingly, a side reaction-free and dendrite-free Zn electrode is developed, the effectiveness of which is also convincing in a $\\mathsf{M n O}_{2}/\\mathsf{Z n S}\\textcircled{\\circ}$ Zn full-cell with $87.6\\%$ capacity retention after 2500 cycles. \n\nRecently, Zn metal batteries have gained extensive attention due to the advantages of $Z\\mathrm{n}$ metal stemming from its high abundance, low toxicity, low reduction potential, high hydrogen evolution over-potential, and high theoretical capacity (gravimetric capacity of $820\\mathrm{\\mA}\\mathrm{~h~g^{-1}~}$ and volumetric capacity of $5855\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-3})$ .[1] Nevertheless, Zn metal anode in mild electrolyte still faces severe inherent problems of dendrite growth, \n\nZn corrosion, and hydrogen evolution, which significantly compromise the Coulombic efficiency (CE), cycling stability, and practical implementation of $Z\\mathrm{n}$ metal batteries.[2] \n\nAccording to our previous study,[3] fresh $Z\\mathrm{n}$ metal is highly unstable in mild electrolyte and generates a loose $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}\\cdot\\boldsymbol{x}\\mathrm{H}_{2}\\mathrm{O}$ layer that cannot block the electrolyte to stop side reactions, including the hydrogen evolution, which easily causes battery swelling. It is well known that there is a dense $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ passivation layer on the $Z\\mathrm{n}$ metal surface due to its oxidation by contact with oxygen and moisture in the air.[4] This layer is homogeneous and dense enough to effectively reduce the $Z\\mathrm{n}$ corrosion rate in the air.[5] Could this layer protect the fresh $Z\\mathrm{n}$ in mild electrolyte by termination of side reactions? Does the existence of this layer have an impact on the Zn stripping/plating behavior during $Z\\mathrm{n}$ battery operation? Up until now, little attention has been paid to in depth understand this dense passivation film in Zn metal batteries. \n\nTo date, most efforts have been spent on suppressing $Z\\mathrm{n}$ dendrite growth to enhance the CE of Zn metal, such as by designing eutectic Zn-alloys,[6] developing new/highly concentrated electrolytes,[1a,7] introducing different electrolyte additives,[8] and controlling the Zn deposition.[9] Although these strategies stabilize Zn metal to some extent, the battery performance is still far from satisfactory for industrial application due to the persistence of side reactions.[10] Because $Z\\mathrm{n}$ electrode continuously reacts with the electrolyte during transportation and during the shelf time after battery assembly but before customer use, the practical application of Zn batteries is severely limited. Building artificial solid-electrolyte interphase (SEI) layers should be a good alternative, which could not only inhibit Zn dendrite growth, but also stop the side reactions.[11] The inhomogeneous and uncompacted artificial layers built by ex situ techniques, however, are unlikely to effectively block electrolyte from the Zn metal surface, and thus the side reactions, including Zn corrosion and hydrogen evolution, would still occur when the uncovered $Z\\mathrm{n}$ contacted with the electrolyte. Even worse, such SEI layers feature poor adhesion and are easily detached from the $Z\\mathrm{n}$ surface due to the volume changes during cycling, so they cannot fully protect the fresh Zn metal underneath. Moreover, most artificial layers still suffer from low transference numbers $(t_{\\mathrm{Zn}^{2+}})$ , which may negate the benefits of the inhibition of dendrite growth. Because the divalent $Z\\mathrm{n}^{2+}$ ion (radius, $0.74\\mathrm{~\\AA~}$ ) has a much higher electric charge density compared to the monovalent $\\mathrm{Li^{+}}$ and $\\mathrm{{Na^{+}}}$ ions (radii, 0.76 and $1.02\\mathrm{~\\bar{A}~}$ , respectively),[12] a huge energy barrier is created for ${\\mathrm{Zn}}^{2+}$ transfer in these artificial layers. Therefore, in situ development of a dense and homogeneous artificial SEI with strong adhesion and a high $t_{\\mathrm{Zn}^{2+}}$ is still challenging for Zn metal anode. \n\nHere, the protective function of the oxidation layer on Zn metal is studied in-depth in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte, with the results indicating that this dense $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ oxidation layer is thermodynamically unstable in mild electrolyte and cannot act as an effective barrier against $Z\\mathrm{n}$ corrosion. Since it would be gradually transformed into a loose $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}{x}\\mathrm{H}_{2}\\mathrm{O}$ layer after soaking in $1\\mathrm{~M~}\\mathrm{ZnSO_{4}}$ electrolyte. To effectively suppress the $Z\\mathrm{n}$ dendrite growth and the side reactions, we have elaborately built a compact artificial $Z\\mathrm{nS}$ layer on the $Z\\mathrm{n}$ metal surface by an in situ vapor–solid strategy. Different temperatures have been conducted, suggesting that a homogeneous ZnS coating was realized at $350^{\\circ}\\mathrm{C}$ $(Z\\mathrm{nS}@Z\\mathrm{n}.350)$ . At the interphase of $Z\\mathrm{nS}$ and $Z\\mathrm{n}$ metal, S atoms have a bonding interaction with the $Z\\mathrm{n}$ atoms in the $Z\\mathrm{n}$ metal due to the occurrence of charge migration, as confirmed by the density functional theory (DFT) calculations. The unbalanced charge distribution not only enhances the ${\\mathrm{Zn}}^{2+}$ diffusion at the $Z{\\bmod{a}}Z{\\bmod{n}}$ interphase but also increases the adhesion of the $Z\\mathrm{nS}$ film to the $Z\\mathrm{n}$ surface. Importantly, the $Z\\mathrm{nS}$ layer is highly stable in aqueous electrolyte, contributing to enhancement of the $Z\\mathrm{n}$ reversibility by avoiding the side reactions. Thanks to its good mechanical strength and high ionic conductivity, the $Z\\mathrm{n}\\mathrm{S}$ coating film facilitates dendrite-free $Z\\mathrm{n}$ plating/stripping, as confirmed by in situ optical microscopy. With this strategy, high cycling stability $(>2500$ cycles) and high CE $(>99.8\\%)$ were realized in both symmetric cells and fullcells when coupled with $\\mathrm{MnO}_{2}$ cathode. \n\nA dense zinc hydroxycarbonate (i.e., $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ or $\\mathrm{Zn}_{4}\\mathrm{CO}_{3}(\\mathrm{OH})_{6}\\cdot\\mathrm{H}_{2}\\mathrm{O})$ passivation layer forms on the Zn metal surface once it is exposed to air, which can significantly retard the corrosion process by keeping out moisture and oxygen.[13] Can this passivation film protect the $Z\\mathrm{n}$ metal or influence the $Z\\mathrm{n}$ plating/stripping behavior in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte? These fundamental issues are still unclear. To address these problems, the stability of this oxidation layer was first studied in 1 m $\\mathrm{{ZnSO}_{4}}$ . A scanning electron microscope (SEM) image of bare Zn metal without polishing shows a flat surface with some holes (Figure  1a). After deep cleaning, the oxidation layer was removed, with many scratches remaining on the polished Zn metal (Figure S1, Supporting Information), which was confirmed by Fourier transform infrared (FTIR) spectroscopy (Figure S2, Supporting Information). Bare $Z\\mathrm{n}$ foil shows an absorption at ${\\approx}1500\\ \\mathrm{cm^{-1}}$ , corresponding to the $\\nu_{3}$ $(\\mathrm{CO}_{3})^{2-}$ antisymmetric stretching mode, which is convincing evidence of the presence of a $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ layer.[14] No obvious absorption can be observed after polishing, indicating that the $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ layer was thoroughly removed. Both the bare Zn metal and the polished $Z\\mathrm{n}$ were soaked in $1\\textbf{M}$ $\\mathrm{ZnSO_{4}}$ electrolyte. After one week, the surfaces of both the bare and polished $Z\\mathrm{n}$ metal incurred a severe corrosion reaction with significant color change (Figure S3, Supporting Information). The SEM image in Figure 1b shows by-products with the morphology of regular hexagonal flakes that cover the whole surface of the bare $Z\\mathrm{n}$ , which is similar to what is seen on the polished $Z\\mathrm{n}$ (Figure S4, Supporting Information), demonstrating that the $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ layer is highly active in the electrolyte. X-ray diffraction (XRD, Figure S5, Supporting Information) and FTIR measurements were conducted to identify the by-products of both samples. The results indicated that the by-product generated on both electrodes was $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}\\cdot\\boldsymbol{x}\\mathrm{H}_{2}\\mathrm{O}$ , as further confirmed by the energy dispersive spectroscopy (EDS) mapping of S and $Z\\mathrm{n}$ elements (Figure  1c–e). Accordingly, the $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ passivation layer cannot function as a protective layer in the electrolyte due to its high thermodynamic activity. The corrosion reaction of bare $Z\\mathrm{n}$ with a $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ passivation layer can be expressed as following: \n\n$$\n\\begin{array}{r l}&{\\mathrm{Zn}_{5}\\left(\\mathrm{CO}_{3}\\right)_{2}\\left(\\mathrm{OH}\\right)_{6}+\\mathrm{SO}_{4}^{2-}+4\\mathrm{H}^{+}+\\left(x-2\\right)\\mathrm{H}_{2}\\mathrm{O}\\rightarrow}\\\\ &{\\quad\\mathrm{Zn}_{4}\\mathrm{SO}_{4}\\left(\\mathrm{OH}\\right)_{6}\\cdot x\\mathrm{H}_{2}\\mathrm{O}+2\\mathrm{CO}_{2}+\\mathrm{Zn}^{2+}}\\end{array}\n$$ \n\n$$\n\\mathrm{Zn}\\leftrightarrow\\mathrm{Zn}^{2+}+2\\mathrm{e}^{-}\n$$ \n\n$$\n2\\mathrm{H}_{2}\\mathrm{O}+2\\mathrm{e}^{-}\\leftrightarrow2\\mathrm{OH}^{-}+\\mathrm{H}_{2}\n$$ \n\n$$\n4\\mathrm{Zn^{2+}}+6\\mathrm{OH^{-}}+\\mathrm{SO_{4}^{2-}}+x\\mathrm{H_{2}O}\\leftrightarrow\\mathrm{Zn_{4}S O_{4}}\\left(\\mathrm{OH}\\right)_{6}\\cdot x\\mathrm{H_{2}O}\n$$ \n\nThe electrochemical performance of symmetrical $Z\\mathrm{n}$ cells with/without polishing was tested to investigate the influence of the $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ layer on the $Z\\mathrm{n}$ electrodeposition behavior. Figure 1f compares the initial charge/discharge voltage profiles of both cells. Remarkably, the bare Zn cell displays a higher voltage hysteresis compared to the polished $Z\\mathrm{n}$ cell at the start of charge, indicating its higher energy barrier for Zn stripping/ plating due to the passivation layer.[15] As the charge proceeds, the voltage hysteresis of the bare Zn cell decreases, probably due to the dissolution of the passivation layer in $\\mathrm{ZnSO_{4}}$ electrolyte, but it increases in the polished Zn cell, indicating the enhanced impedance due to the by-product layer formation. Electrochemical impedance spectroscopy (EIS) measurements of Zn cells were conducted after different numbers of cycles (Figure S6, Supporting Information). Both bare and polished $Z\\mathrm{n}$ cells show two different charge transfer steps after one cycle and after 50 cycles, manifesting the additional by-product layer generated during the charge-discharge process. Digital images of the bare and polished Zn metal electrodes reveal that the two kinds of $Z\\mathrm{n}$ electrodes suffered from serious surface corrosion with an obvious color change during cycling (Figure S7, Supporting Information). SEM images show by-product formation and corrosion on the Zn surface regardless of the presence of a passivation layer (Figure S8, Supporting Information), as further confirmed by the XRD patterns. Before cycling, only the characteristic peaks of Zn metal located at $36.4^{\\circ}$ , $39.1^{\\circ}$ , and $43.3^{\\circ}$ can be found for the bare $Z\\mathrm{n}$ electrode (Figure 1g), which suggests that the $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ layer is hard to identify.[16] After one cycle, a small peak at $8.5^{\\circ}$ can be detected, corresponding to the (002) planes of $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ by-product, and the intensity increases with further cycling (50 cycles), indicating the aggravated side reactions during battery operation, which is similar to the XRD patterns of the polished Zn after different numbers of cycles (Figure S9, Supporting Information). Although removal of the $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ reduces the energy barrier for $Z\\mathrm{n}$ stripping/plating and prolongs the cycling lifespan from ${\\approx}100\\mathrm{~h~}$ to ${\\approx}250\\mathrm{h}$ at $2\\mathrm{\\mA\\cm^{-2}}$ (Figure S10, Supporting Information), the performance of the polished Zn cell is still far from satisfactory due to the notorious $Z\\mathrm{n}$ dendrite growth and side reactions. \n\n![](images/e9f19613c9b0d1e2bf02c78d700336ee623f0b46d32855718bf68087e459b003.jpg) \nFigure 1.  Characterization of the passivation layer on Zn metal. a) SEM image of bare $Z n$ foil without polishing. b) SEM image of bare $Z n$ foil after soaking in electrolyte for one week. $\\mathsf{c}{\\mathsf{-}}\\mathsf{e})$ Energy dispersive spectroscopy (EDS) mapping of the plates generated during the side reactions, showing the uniform distribution of S and $Z n$ elements. f) Initial charge/discharge voltage profiles of a bare $Z n$ symmetric cell and a polished $Z n$ symmetric cell, with an enlargement in the inset. g) X-ray diffraction (XRD) patterns of bare Zn electrode before cycling, and after 1 and 50 cycles. Green peaks indicate metallic $Z n$ and blue peaks indicate the by-product of $Z n_{4}S O_{4}(O H)_{6}{\\cdot}x H_{2}O$ . \n\nBuilding a dense and homogeneous SEI layer is an effective strategy to enhance the Zn reversibility.[17] Based on the phase diagram of sulfur (Figure S11, Supporting Information), we have elaborately grown an artificial $Z\\mathrm{nS}$ film on the Zn metal surface by an in situ vapor–solid reaction, as illustrated in Figure  2a. Specifically, sulfur can be vaporized at ${\\approx}200~^{\\circ}\\mathrm{C}$ under the pressure of $\\approx1\\times10^{-3}$ atm, and the sulfur vapor will react with $Z\\mathrm{n}$ metal by generating $Z\\mathrm{nS}$ at high temperatures. Accordingly, Zn foil was put in a specially designed tube with $100\\ \\mathrm{g}$ sulfur powder below it. Then, the tube was evacuated and sealed. At high temperature, the gaseous sulfur vapor spread to the Zn metal surface and reacted with $Z\\mathrm{n}$ metal to generate a dense and uniform $Z\\mathrm{n}S$ layer. As aforementioned, Zn electrode, whether with/without a $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ layer, is highly unstable, and suffers from side reactions and dendrite growth during battery operation (Figure 2b), which not only fades the CE and reversible capacity, but also shortens the cycling lifespan of $Z\\mathrm{n}$ batteries. In striking contrast, the $Z\\mathrm{nS}$ protective layer on the Zn surface not only effectively inhibits the corrosion reactions by blocking the electrolyte, but also suppresses the $Z\\mathrm{n}$ dendrite growth by guiding the $Z\\mathrm{n}^{2+}$ stripping/plating underneath, enhancing the reversibility of Zn metal (Figure 2b). \n\nTo study the influence of the treatment temperature on the $Z\\mathrm{n}S$ film, different operating temperatures of $300~^{\\circ}\\mathrm{C}$ , $350~^{\\circ}\\mathrm{C}$ and $400~^{\\circ}\\mathrm{C}$ were conducted. From the XRD patterns of $\\scriptstyle{\\mathrm{ZnS}}({\\overline{{a}}})$ Zn electrodes (Figure 3a), the sample obtained at $300^{\\circ}\\mathrm{C}$ $(Z\\ n S{@}$ $\\mathrm{{Zn}}{\\cdot}300)$ only shows the characteristic peaks of Zn metal, indicating no obvious formation of $Z\\mathrm{nS}$ film at this temperature, as further confirmed by EDS mapping (Figure S12, Supporting Information). No clear S element layer can be found on the Zn metal surface, suggesting that this is an improper operating temperature. When the temperature was increased to $350~^{\\circ}\\mathrm{C}_{\\mathrm{i}}$ , the XRD pattern displayed new peaks at $28.6^{\\circ}$ , $47.5^{\\circ}$ , and $56.3^{\\circ}$ , corresponding to the (111), (220), and (311) planes of $Z\\mathrm{nS}$ (PDF # 00-005-0566), respectively.[18] The intensity of these peaks increased when the temperature was increased to $400^{\\circ}\\mathrm{C}$ . Figure S13 (Supporting Information) presents digital images of $Z{\\bmod{a}}Z{\\bmod{n}}$ electrodes obtained at different temperatures, with the $\\mathrm{ZnS@\\mathbb{Z}n}{\\cdot}300$ foil showing almost no change in colors or luminosity. Remarkably, the surfaces of the $\\mathrm{ZnS@\\mathbb{Z}n}{\\cdot}350$ and $\\mathrm{ZnS@\\mathbb{Z}n}–400$ foils changed significantly due to the sulfur-vapor reaction. Unfortunately, the $\\mathrm{ZnS@2n}{\\cdot}400$ foil also suffered from serious distortion due to the deformation of the Zn metal at the high temperature, indicating that the high temperature of $400~^{\\circ}\\mathrm{C}$ is unsuitable, too. SEM images show that the $Z\\mathrm{n}$ surface was evenly covered by $Z\\mathrm{nS}$ at $350~^{\\circ}\\mathrm{C}$ (Figure  3b). The cross-sectional image (Figure  3c) reveals a homogeneous $Z\\mathrm{nS}$ coating layer with a thickness of ${\\approx}0.5~\\upmu\\mathrm{m}$ , as further confirmed by the high-resolution image (Figure S14, Supporting Information) and EDS mapping (Figure  3d). X-ray photoelectron spectroscopy (XPS) spectra of bare $Z\\mathrm{n}$ and $Z n S@Z n.350$ were collected (Figure  3e,f), and the bare $Z\\mathrm{n}$ electrode only shows the binding energies of $\\mathrm{Zn~}2\\mathrm{p}_{1/2}$ and $\\mathrm{Zn~}2\\mathrm{p}_{3/2}$ at 1045.1 and $1021.9\\ \\mathrm{~eV},$ respectively. Whereas the $2\\mathrm{nS}@\\mathrm{Z}\\mathrm{n}{-}350$ displays the S signals of S $2\\mathrm{p}_{3/2}$ and $\\mathtt{S2p}_{1/2}$ located at 161.9 and $163.2\\ \\mathrm{eV},$ respectively.[19] Importantly, a small binding energy shift in the Zn $2\\mathrm{p}_{3/2}$ region was mainly due to the formation of $Z\\mathrm{n-S}$ polar bonds at the interphase of $Z\\mathrm{nS}$ and $Z\\mathrm{n}$ metal, which enhances the adhesion of the $Z\\mathrm{n}S$ film to the $Z\\mathrm{n}$ metal. According to a previous report,[20] the Zn (002) facet is transformed into ZnS (002) at the interphase of $Z{\\bmod{a}}Z{\\bmod{n}}$ , as illustrated in Figure 3g. DFT calculations revealed that the bonding interaction occurs between the S atoms and $Z\\mathrm{n}$ atoms in the $Z\\mathrm{n}$ metal, which modifies the charge distribution (Figure  3h) and further leads to an unbalanced charge distribution at the interphase (Figure  3i). The unbalanced charge distribution not only accelerates the $Z\\mathrm{n}^{2+}$ diffusion at the $Z{\\bmod{a}}Z{\\bmod{n}}$ interphase, but also enhances the adhesion of the $Z\\mathrm{nS}$ layer to the $Z\\mathrm{n}$ metal.[21] Rolling and twisting experiments were also conducted to evaluate the adhesion between the $Z\\mathrm{ns}$ layer and the Zn metal. As depicted in Figure S15 (Supporting Information), the $Z n S@Z n.350$ foil keeps its surface integrity after twisting to various degrees, suggesting good adhesion between the ${\\mathrm{~}}Z{\\mathrm{ns}}$ layer and the Zn metal. \n\n![](images/e17fa1e6b3d1f8d744cc2bf96d38568fa5e1585b66b64e5aa1a6af7891fee262.jpg) \nFigure 2.  Schematic illustration of the artificial ZnS layer and Zn plating behavior with/without ZnS. a) Introducing the ZnS layer on the surface of Zn metal substrate by an in situ strategy. b) Zn plating on the bare Zn foil with a $Z\\mathsf{n}_{5}(\\mathsf{C O}_{3})_{2}(\\mathsf{O H})_{6}$ passivation layer, leading to side reactions and dendritic Zn deposition. After incorporating the artificial ZnS layer on the $Z n$ surface, uniform and compact $Z n$ plating behavior without side reactions can be obtained. \n\nIn order to study the stability of the $Z\\mathrm{ns}$ layer, $Z n S@Z n.350$ foil was soaked in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte for $10\\mathrm{~d~}$ . The digital images of the $Z n S@Z n.350$ foil show similar surfaces before and after soaking in electrolyte for $10\\mathrm{d}$ (Figure S16, Supporting Information), demonstrating that this layer is highly stable. The XRD pattern was collected after the soaking in electrolyte (Figure S17, Supporting Information), which is similar to that for $Z n S@Z n.350$ foil before soaking and without any peaks for the $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}{x}\\mathrm{H}_{2}\\mathrm{O}$ by-product, indicating that the side reactions between the Zn metal and the electrolyte were disrupted. The impact of the $Z\\mathrm{nS}$ layer on $Z\\mathrm{n}$ metal corrosion was investigated by linear polarization experiments in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte (Figure S18, Supporting Information). Compared to the bare $Z\\mathrm{n}$ , the corrosion potential of the $2\\mathrm{nS}@\\mathrm{Zn}{-350}$ increased from $-1.052$ to $-1.048\\mathrm{~V},$ suggesting that it has less tendency towards corrosion reactions.[22] Notably, this $Z\\mathrm{n}S$ layer also reduces the corrosion current by $368.5~{\\upmu\\mathrm{A}}~\\mathrm{cm}^{-2}$ . In addition to inhibiting the side reactions, the $\\mathrm{{zns}}$ layer also functions as a robust artificial SEI to suppress $Z\\mathrm{n}$ dendrite growth because it has poor electronic conductivity, but high ionic conductivity and high $t_{\\mathrm{Zn}^{2+}}$ . It is well known that cubic $Z\\mathrm{n}S$ has been widely used as a semiconductor due to its wide-bandgap properties.[23] The electrical resistivity $(\\rho)$ of the $Z\\mathrm{ns}$ protective film was also evaluated (Figure S19, Supporting Information). According to the following formula $\\rho=\\frac{R^{*}S}{L}=\\frac{U^{*}S}{I^{*}L}.$ , in which $R$ is the resistance, $I$ is the applied current, $L$ is the thickness of the $Z\\mathrm{n}S$ , $U$ is the corresponding voltage, and S is the contact area, $\\rho$ was estimated as $\\approx1.5\\times10^{5}\\Omega\\ \\mathrm{cm}$ $(\\sigma\\approx6.5\\times10^{-6}\\mathrm{~S~cm^{-1}})$ . The high resistance introduced by the insulating ZnS layer is critical for establishing the necessary potential gradient across the artificial film to drive ${\\mathrm{Zn}}^{2+}$ diffusion through the layer.[24] In addition, the $\\mathrm{{zns}}$ film features good ionic conductivity (evaluated as $\\approx1.3\\times10^{-5}\\mathrm{~S~cm^{-1}}$ , Figure S20, Supporting Information), which facilitates ${\\mathrm{Zn}}^{2+}$ diffusion through this protective film. Furthermore, the $t_{\\mathrm{Zn}^{2+}}$ was further calculated to quantitatively describe the $Z\\mathrm{n}^{2+}$ conducting ability of the $Z\\mathrm{nS}$ protective layer. In a bare $Z\\mathrm{n}$ symmetric cell, a rather low $t_{\\mathrm{Zn}^{2+}}$ of 0.33 was obtained (Figure S21a, Supporting Information), which is mainly due to the strong preferential solvation of $Z\\mathrm{n}^{2+}$ over the anions, leading to a bulky solvation shell around $Z\\mathrm{n}^{2+}$ . $\\mathrm{SO}_{4}^{2-}$ anions tend to migrate in the opposite direction from $Z\\mathrm{n}^{2+}$ and eventually accumulate at the electrode surface, resulting in a build-up of the concentration gradient. This concentration gradient not only limits the rate at which the battery may be charged or discharged, but also creates a concentration overpotential that limits the operating voltage of the battery, thus limiting the power and energy density of the battery.[25] Notably, $t_{\\mathrm{Zn}^{2+}}$ can be dramatically improved to ${\\approx}0.78$ after introducing the ZnS layer (Figure S21b, Supporting Information), suggesting that the anions were effectively retarded by this protective layer. \n\n![](images/61cd045a75aef88b147ceb07dc6541a1774a488e557c74be2c28d8977faa745a.jpg) \nFigure 3.  Characterization of Zn foil protected by a ZnS layer and the charge density distribution at the interface between the ZnS layer and the Zn metal. a) XRD patterns of $Z n S@Z n$ foils obtained at different temperatures. b) SEM image of $Z n S@Z n-350$ foil (top-view). c) Cross-sectional image of $Z n S@Z n-350$ foil, showing that the thickness of the $Z n S$ is ${\\approx}0.5\\upmu\\mathrm{m}$ . d) EDS mapping of Zn element (top) and S element (bottom). XPS characterizations of bare Zn and $Z n S@Z n-350$ foil: e) $Z n2mathsf{p}$ spectra, f ) $\\mathsf{S2p}$ spectra. g) Schematic representation of the $Z n S@Z n$ interphase of the $Z n S@Z n-350$ electrode. h) Electron density difference map at the $Z n S@Z n$ interphase. i) Slice of the electron density difference map to show the unbalanced charge distribution. \n\nTo confirm the suppression of Zn dendrite growth by the $Z\\mathrm{n}S$ artificial layer, transparent symmetric cells were assembled to in situ monitor the $Z\\mathrm{n}$ plating/stripping behavior using an optical microscope equipped with a digital camera. A high current density of $5\\mathrm{\\mA\\cm^{-2}}$ with $10\\mathrm{min}$ of intermittence was applied to repeatedly conduct plating/stripping measurements. Figure 4a presents images of a bare Zn electrode after different plating/stripping cycles. Before cycling, the bare $Z\\mathrm{n}$ electrode displays a smooth edge. After 50 cycles, protrusions start to grow along the edge of the bare $Z\\mathrm{n}$ electrode, which evidences uneven Zn plating. These protrusions gradually turns into $Z\\mathrm{n}$ dendrites on the Zn electrode with further cycling. In strong comparison, the $\\mathrm{ZnS@\\mathrm{Zn}}{\\mathrm{-}}350$ electrode exhibits smooth Zn plating and stripping in Figure 4b. There is still no sign of protrusions or $Z\\mathrm{n}$ dendrite generation, even after 250 cycles. \n\n![](images/0ebf8b3f7d91032c046773d85b1bb5771087550941e68549b03128b7ee8220c1.jpg) \nFigure 4.  Optical microscopy and SEM studies of Zn plating behavior: a) Images of the front surface of bare $Z n$ , and b) $Z n S@Z n-350$ electrode in a symmetric transparent cell after the specified numbers of plating/stripping cycles. Cross-sectional SEM images of Zn deposition: c) on bare $Z n$ metal at $\\mathsf{1}\\mathsf{m A}\\mathsf{c m}^{-2}$ for areal capacity of $\\mathsf{1}\\mathsf{m A}\\mathsf{h}\\mathsf{c m}^{-2}$ , d) $\\mathsf{1\\ m A\\ c m^{-2}}$ for $2\\mathsf{m A h c m}^{-2}$ , e) on $Z n S@Z n-350$ foil at $\\mathsf{1}\\mathsf{m}\\mathsf{A}\\mathsf{c m}^{-2}$ for $\\mathsf{I m A h c m{\\bar{}}}^{2}$ , f ) $\\mathsf{1\\ m A\\ c m^{-2}}$ for $2\\mathsf{m A h c m}^{-2}$ . g) CEs of $Z n$ plating/stripping in bare $C u-Z n$ and $Z n S@C u-Z n$ cells with capacity of 1 mA h $\\mathsf{c m}^{-2}$ . Voltage profiles of $\\boldsymbol{\\mathsf{h}}$ ) the bare $\\mathtt{C u{-}Z n}$ cell and i) the $Z n S@C u-Z n$ cell at the 1st, $50\\mathrm{th}$ , and 100th cycles. \n\nSEM was further conducted to observe the Zn electrodeposition with/without the $Z\\mathrm{n}S$ protective layer. Zn deposition was conducted under $1\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ with the deposition capacity of 1 and $2{\\mathrm{\\mA}}{\\mathrm{~h~}}{\\mathrm{cm}}^{-2}$ , respectively. Figure  4c shows a cross-sectional image of the bare $Z\\mathrm{n}$ metal after Zn plating $(1\\mathrm{mA}\\mathrm{hcm}^{-2})$ ). Remarkably, uneven deposition occurred on the $Z\\mathrm{n}$ surface with serious agglomeration, which easily triggers dendrite growth. After deposition of $2\\mathrm{\\mA}\\mathrm{h}\\mathrm{cm}^{-2}$ , the agglomeration was aggravated, raising a potential safety issue after further Zn plating (Figure  4d). In contrast, no obvious $Z\\mathrm{n}$ plates or protrusions were generated on the $2\\mathrm{nS}@\\mathrm{Zn}{-350}$ surface after $1\\mathrm{mA}$ h $\\mathrm{cm}^{-2}$ of plating (Figure 4e), indicating that the $Z\\mathrm{nS}$ protective layer helps to guide homogeneous $Z\\mathrm{n}$ deposition underneath the film. Moreover, the thickness of the deposited \n\nZn was ${\\approx}1.5\\ \\upmu\\mathrm{m}$ , similar to its theoretical value $(\\approx1.7\\upmu\\mathrm{m}$ under $1\\ \\mathrm{mA}$ h $\\mathrm{cm}^{-2}$ ). Even after $2\\ \\mathrm{mA}$ h $\\mathrm{cm}^{-2}$ of plating, uniform deposition under the $Z\\mathrm{ns}$ layer was still observed, as shown in Figure 4f, resulting in dendrite-free $Z\\mathrm{n}$ plating. \n\nThe CE is one of the most important parameters used to evaluate the reversibility of $Z\\mathrm{n}$ plating and stripping.[26] In a $\\mathrm{{Cu-Zn}}$ cell, the CEs were calculated from the ratio of $Z\\mathrm{n}$ removed from the $\\mathtt{C u}$ substrate to that deposited during the same cycle. The ZnS protective layer on Cu foil was obtained by the doctor blading method. First, the morphology of $Z\\mathrm{n}$ deposition on the bare $\\mathrm{{Cu}}$ and $Z{\\mathrm{nS}}@{\\mathrm{Cu}}$ was studied at current density of $2\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ with a capacity of $1\\mathrm{\\mA}\\mathrm{~h~}\\mathrm{cm}^{-2}$ . Clearly, the bare Cu substrate was covered by mossy Zn plates with obvious protrusions. In comparison, no obvious protrusions were generated on the $Z{\\mathrm{nS}}@{\\mathrm{Cu}}$ surface, further indicating that the ZnS protective layer guides the Zn deposition (Figure S22, Supporting Information). In the $\\mathrm{{Cu-Zn}}$ cell, the initial CE was only $\\approx77.6\\%$ and gradually increased to ${\\approx}97.6\\%$ after the first 20 cycles (Figure $\\ensuremath{4\\mathrm{g}}\\ensuremath{\\vert}$ ). Such a CE is still low, however, due to the poor reversibility of $Z\\mathrm{n}$ metal caused by the side reactions and dendrite formation. Notably, the CEs fluctuate greatly after ${\\approx}120$ cycles, which is mainly due to short-circuiting of the battery. The $Z n{\\mathrm{S}}\\textcircled{a}{\\mathrm{Cu-Zn}}$ cell, however, displayed a much higher initial CE of ${\\approx}88.5\\%$ compared to the $\\mathrm{{Cu-Zn}}$ cell, and it increased to $99.2\\%$ in the following 10 cycles. Even after 200 cycles, the CE remained stable, mainly benefiting from the suppression of side reactions and dendrite growth. The charge– discharge voltage profiles for different cycles of the $\\mathrm{{Cu-Zn}}$ cell are shown in Figure 4h. The initial voltage hysteresis is ${\\approx}141\\mathrm{mV}$ for the $\\mathrm{{Cu-Zn}}$ cell, much higher than that for the $Z n{\\mathrm{S}}@{\\mathrm{Cu-Zn}}$ cell $(\\approx105~\\mathrm{mV},$ Figure 4i), indicating a higher energy barrier for $Z\\mathrm{n}$ nucleation/dissolution in the phase transition between $Z\\mathrm{n}^{2+}$ ions and Zn metal.[27] \n\n![](images/e434c5642961347278e5dbb206493434d015846ada3f42dff4ed2fd2e0e95d6f.jpg) \nFigure 5.  Electrochemical characterization of the samples. a) Comparison of the cycling stability of bare $Z n$ symmetric cell and $Z n S@Z n.350$ symmetric cell at $2\\mathsf{m A}\\mathsf{c m}^{-2}$ with the capacity of $2\\mathsf{m A}\\mathsf{h}\\mathsf{c m}^{-2}$ . b) High-resolution voltage profiles for the first cycle. c) Rate performances of both cells at current densities from 0.2 to $10m A\\mathsf{c m}^{-1}$ . d) Cyclic voltammograms for the second cycle of $\\mathsf{M n O}_{2}/\\mathsf{Z n}$ batteries using bare Zn and $Z n S@Z n.350$ anodes. e) Long-term cycling stability of both batteries at $5C$ along with the corresponding CEs $(>99.8\\%)$ . \n\nThe stability of Zn metal anode with/without a $Z\\mathrm{n}S$ layer was evaluated by long-term galvanostatic cycling of the symmetrical cells (Figure 5a). After cycling for ${\\approx}100\\mathrm{h}$ at $2\\mathrm{\\mA}\\mathrm{cm}^{-2}$ , a sudden reduction of the polarization voltage appeared in the bare Zn cell, which might be ascribed to a dynamic dendrite-induced short circuit. In contrast, the $Z n S@Z n.350$ cell displayed prolonged cycling stability for more than $1100\\mathrm{~h~}$ . Figure  5b compares the first charge-discharge voltage profiles of both cells. The $Z n S@Z n.350$ cell delivers a polarization voltage of $\\approx98\\ \\mathrm{mV},$ much lower than that of the bare $Z\\mathrm{n}$ cell $(\\mathrm{\\approx}153~\\mathrm{mV})$ ), indicating its low energy barrier for Zn deposition. Even after 40 cycles, the bare $Z\\mathrm{n}$ cell still maintains a large polarization voltage (Figure S23, Supporting Information). One of the probable reasons for the high energy barrier is that the accumulation of detrimental by-products may block the conduction of ions.[28] The rate performance of $Z\\mathrm{n}$ cells was investigated at various current densities from 0.2 to $10\\ \\mathrm{mA\\cm^{-2}}$ , as shown in Figure 5c, in which the bare Zn cell always exhibits substantially higher voltage hysteresis than the $\\mathrm{ZnS@\\mathrm{Zn}}{\\mathrm{-}}350$ cell, suggesting low polarization and favorable stability in the $Z n S@Z n.350$ cell. After the rate tests, the morphology of the Zn and the $\\mathrm{ZnS@\\mathrm{Zn}}{\\mathrm{-}}350$ electrodes was studied by SEM. The bare $Z\\mathrm{n}$ electrode had an uneven surface with many agglomerated $Z\\mathrm{n}$ plates, as shown in Figure S24 (Supporting Information), which is mainly caused by the Zn corrosion and dendrite growth. The $2\\mathrm{nS}@\\mathrm{Zn}{-350}$ electrode displays a clean surface, however, resulting from its corrosionfree and dendrite-free stripping/plating behavior (Figure S25, Supporting Information). \n\nTo further prove the suitability for application of $2\\mathrm{nS}@\\mathrm{Zn}{-350}$ electrode, a $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ full-cell was assembled by choosing $\\mathrm{MnO}_{2}$ electrode as the cathode, since it is one of the most promising candidates for aqueous $Z\\mathrm{n}$ batteries.[29] Figure S26 (Supporting Information) presents representative SEM images of electrodeposited $\\mathrm{MnO}_{2}$ on carbon cloth. The surface of the carbon cloth is covered by $\\mathrm{MnO}_{2}$ clusters featuring a petal-like nanostructure. The full-cell was tested in electrolyte consisting of $1\\mathrm{~M~ZnSO_{4}+0.1\\mathrm{~M~MnSO_{4}}},$ in which $\\mathrm{MnSO}_{4}$ was used as an additive to inhibit the dissolution of $\\mathrm{Mn}^{2+}$ from the $\\mathrm{MnO}_{2}$ cathode.[30] Typical stepwise charge–discharge curves of the $\\mathrm{MnO_{2}/Z n S}@\\mathrm{Zn}{\\cdot}350$ battery were observed at 1 C (Figure S27, Supporting Information), suggesting the ${\\mathrm{Zn}}^{2+}$ and $\\mathrm{H^{+}}$ cointercalation mechanism.[31] The cyclic voltammetry (CV) curves of the $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ and $\\mathrm{MnO_{2}/Z n S}@\\mathrm{Zn}.350$ batteries are compared in Figure S28 (Supporting Information) and Figure  5d. Clearly, the $\\mathrm{MnO_{2}/Z n S}@\\mathrm{Zn}.350$ battery shows smaller voltage polarization $(\\approx20~\\mathrm{mV})$ than that of the $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ battery, indicating its good reversibility due to the $\\mathrm{{zns}}$ protection. The long-term cycling stability curves of both batteries at the high rate of $5\\mathrm{~C~}$ are plotted in Figure 5e. The cell with bare $Z\\mathrm{n}$ foil presents an initial capacity of ${\\approx}115.6\\ \\mathrm{mA}\\mathrm{h}\\ \\mathrm{g}^{-1}$ . The capacity dramatically drops after 1000 cycles, however, mainly because the separator was pierced by $Z\\mathrm{n}$ dendrites, leading to the short-circuiting of the battery. In contrast, the $\\mathrm{MnO_{2}/Z n S}\\ @\\mathrm{Zn}{\\cdot}350$ battery delivers a higher initial capacity $125.8\\mathrm{mAhg^{-1}})$ compared to the $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ battery. After 2500 cycles, a high capacity of $110.2~\\mathrm{mA}$ h $\\mathrm{g}^{-1}$ with a high CE of $99.3\\%$ was retained, corresponding to capacity retention of $87.6\\%$ , which is mainly due to the inhibition of $Z\\mathrm{n}$ corrosion and dendrite growth during the battery operation. \n\nThe protective function of $\\mathrm{Zn}_{5}(\\mathrm{CO}_{3})_{2}(\\mathrm{OH})_{6}$ passive film on Zn metal was explored in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte. Although this dense passivation layer could passivate $Z\\mathrm{n}$ metal in the air by blocking oxygen and moisture, it cannot protect $Z\\mathrm{n}$ metal in mild electrolyte. Accordingly, a homogeneous and dense $Z\\mathrm{nS}$ protective film was introduced in situ on the $Z\\mathrm{n}$ metal surface by a high-temperature vapor–solid strategy. This film was found to be highly stable in mild electrolyte, which contributes to improving the reversibility of $Z\\mathrm{n}$ metal by avoiding the electrolyte-induced side reactions. Moreover, this robust $Z\\mathrm{nS}$ film shows strong adhesion, good mechanical strength, and high ionic conductivity, which enables even $Z\\mathrm{n}$ plating/stripping, as confirmed by in situ optical microscopy. The $2\\mathrm{nS}@\\mathrm{Z}\\mathrm{n}{-}350$ symmetrical cell delivered a smaller voltage polarization and longer lifespan of $\\mathord{\\mathrm{>}}1100\\mathrm{h}$ at 2 mA h $\\mathrm{cm^{-1}}$ compared to the bare $Z\\mathrm{n}$ cells. Benefiting from the side-reaction-free and dendritefree $\\mathrm{ZnS@\\mathrm{Zn}}{\\mathrm{-}}350$ electrode, the $\\mathrm{MnO_{2}/Z n S}_{@}\\mathrm{Zn}{\\cdot}350$ full-cell displayed excellent cycling stability, with $87.6\\%$ capacity retention after 2500 cycles. Our fundamental findings offer a better understanding of $Z\\mathrm{n}$ metal surface chemistry and pave the way to developing practical $Z\\mathrm{n}$ metal batteries with mild electrolyte. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nFinancial support provided by the Australian Research Council (ARC) (FT150100109, DP170102406, and DE190100504) is gratefully acknowledged. The authors thank the Electron Microscopy Centre (EMC) at the University of Wollongong. The authors also thank Dr. Tania Silver for her critical reading of this manuscript. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\nDFT calculation, in situ strategies, side reactions, Zn anode protection, Zn ion batteries \n\nReceived: May 4, 2020 Revised: June 15, 2020 Published online: \n\n[1]\t a) F. Wang, O. Borodin, T. Gao, X. Fan, W. Sun, F. Han, A. Faraone, J. A.  Dura, K.  Xu, C.  Wang, Nat. Mater. 2018, 17, 543; b) J.  Fu, R. Liang, G. Liu, A. Yu, Z. Bai, L. Yang, Z. Chen, Adv. Mater. 2019, 31, 1805230; c) Y. Jin, L. Zou, L. Liu, M. H. Engelhard, R. L. Patel, Z. Nie, K. S. Han, Y. Shao, C. Wang, J. Zhu, Adv. Mater. 2019, 31, 1900567. \n[2]\t a) B. Tang, L. Shan, S. Liang, J. Zhou, Energy Environ. Sci. 2019, 12, 3288; b) M.  Song, Tan, D.  Chao, .  Fan, Adv. Funct. Mater. 2018, 28, 1802564; c) Q. Zhang, J . Luan, L. Fu, S. Wu, Y. Tang, X. Ji, H. Y. Wang, Angew. Chem., Int. Ed. 2019, 58, 15841; d) M. Yan, P. He, Y. Chen, S. Wang, Q. Wei, K. Zhao, X. Xu, Q. An, Y. Shuang, Y. Shao, Adv. Mater. 2018, 30, 1703725. \n[3]\t J. Hao, X. Li, S. Zhang, F. Yang, X. Zeng, S. Zhang, G. Bo, C. Wang, Z.  Guo, Adv. Funct. Mater. 2020, 2001263, https://doi.org/10.1002/ adfm.202001263. \n[4]\t P. K. Bowen, J. Drelich, J. Goldman, Adv. Mater. 2013, 25, 2577. \n[5]\t R. Ramanauskas, Appl. Surf. Sci. 1999, 153, 53. \n[6]\t S. B. Wang, Q. Ran, Yao, H. Shi, Z. Wen, M. Zhao, X. Y. Lang, Q. Jiang, Nat. 1634. \n[7]\t a) N.  Zha Zhao, K.  Lei, C.  Chen, X.  Liu, Chen 2016, 12894; b) L.  Zhang, . A.  Rodr Leonard, Q.  Guo, W.  Wan Mater. 2019, 29, 1902653; Tang, J. A.  Zapien, S. Chen, 908121. \n[8]\t a) S. 2015, 179, 475; b) J. Hao, Long, Zeng, Z. Yang, W. K. Pang, Z. Guo, Adv. Mate 903605 \n[9]\t a) J.  Zheng, Q.  Zhao, Tang, Yin, C. D.  Quilty, G. D.  Renderos, X.  Liu, Y.  Deng, Wang, Bock, Science 2019, 366, 645; b) Z.  Wang, J.  Huang, Z. Gu X. Dong, Y.  Liu, Y.  Wang, Y.  Xia, Joule 2019, 3, 1289; c) Q.  Yang, G.  Liang, Y.  Guo, Z.  Liu, B.  Yan, D.  Wang, Z.  Huang, X.  Li, J.  Fan, C.  Zhi, Adv. Mater. 2019, 31, 1903778. \n[10]\t Y. Zeng, X. Zhang, R. Qin, X. Liu, P. Fang, D. Zheng, Y. Tong, X. Lu, Adv. Mater. 2019, 31, 1903675. \n[11]\t a) Q.  Yang, Y.  Guo, B.  Yan, C.  Wang, Z.  Liu, Z.  Huang, Y.  Wang, Y.  Li, H.  Li, L.  Song, J.  Fan, C.  Zhi, Adv. Mater. 2020, 2001755; b) K.  Zhao, C.  Wang, Y.  Yu, M.  Yan, Q.  Wei, P.  He, Y.  Dong, Z. Zhang, X. Wang, L. Mai, Adv. Mater. Interfaces 2018, 5, 1800848; c) Z.  Wang, J.  Hu, L.  Han, Z.  Wang, H.  Wang, Q.  Zhao, J.  Liu, F. Pan, Nano Energy 2019, 56, 92. \n[12]\t J.  Huang, Z.  Guo, Y.  Ma, D.  Bin, Y.  Wang, Y.  Xia, Small Methods 2019, 3, 1800272. \n[13]\t N. S. Sangaj, V. Malshe, Prog. Org. Coat. 2004, 50, 28. \n[14]\t J.  Winiarski, W.  Tylus, K.  Winiarska, I.  Szczygieł, B.  Szczygieł, J. Spectroscopy 2018, 2018, 2079278. \n[15]\t R.  Xu, X. Q.  Zhang, X. B.  Cheng, H. J.  Peng, C. Z.  Zhao, C.  Yan, J. Q. Huang, Adv. Funct. Mater. 2018, 28, 1705838. \n[16]\t Z. Liu, T. Cui, G. Pulletikurthi, A. Lahiri, T. Carstens, M. Olschewski, F. Endres, Angew. Chem., Int. Ed. 2016, 55, 2889. \n[17]\t S. S.  Shinde, C. H.  Lee, A.  Sami, D. H.  Kim, S. U.  Lee, J. H.  Lee, ACS Nano 2017, 11, 347. \n[18]\t T. Zscheckel, W. Wisniewski, C. Rüssel, Adv. Funct. Mater. 2012, 22, 4969. \n[19]\t H.  Borchert, S.  Haubold, M.  Haase, H.  Weller, C.  McGinley, M. Riedler, T. Möller, Nano Lett. 2002, 2, 151. \n[20]\t Q. Li, C. Wang, Appl. Phys. Lett. 2003, 82, 1398. \n[21]\t a) J.  Hao, J.  Zhang, G.  Xia, Y.  Liu, Y.  Zheng, W.  Zhang, Y.  Tang, W. K.  Pang, Z.  Guo, ACS Nano 2018, 12, 10430; b) J.  Hao, F.  Yang, S.  Zhang, H.  He, G.  Xia, Y.  Liu, C.  Didier, T.  Liu, W. K.  Pang, V. K.  Peterson, Proc. Natl. Acad. Sci. USA 2020, 117, 2815. \n[22]\t a) E. McCafferty, J. Electrochem. Soc. 1977, 124, 1869; b) S. Hosseini, A.  Abbasi, L. O.  Uginet, N.  Haustraete, S.  Praserthdam, T. Yonezawa, S. Kheawhom, Sci. Rep. 2019, 9, 14958. \n[23]\t X.  Xu, S.  Li, J.  Chen, S.  Cai, Z.  Long, X.  Fang, Adv. Funct. Mater. 2018, 28, 1802029. \n[24]\t X.  Liang, Q.  Pang, I. R.  Kochetkov, M. S.  Sempere, H.  Huang, X. Sun, L. F. Nazar, Nat. Energy 2017, 2, 17119. \n[25]\t R.  Xu, Y.  Xiao, R.  Zhang, X. B.  Cheng, C. Z.  Zhao, X. Q.  Zhang, C. Yan, Q. Zhang, J. Q. Huang, Adv. Mater. 2019, 31, 1808392. \n[26]\t F.  Wang, E.  Hu, W.  Sun, T.  Gao, X.  Ji, X.  Fan, F.  Han, X. Q.  Yang, K. Xu, C. Wang, Energy Environ. Sci. 2018, 11, 3168. \n[27]\t Q.  Yang, F.  Mo, Z.  Liu, L.  Ma, X.  Li, D.  Fang, S.  Chen, S.  Zhang, C. Zhi, Adv. Mater. 2019, 31, 1901521. \n[28]\t Z. Zhao, J. Zhao, Z. Hu, J. Li, J. Li, Y. Zhang, C. Wang, G. Cui, Energy Environ. Sci. 2019, 12, 1938. \n[29]\t a) D.  Chao, W.  Zhou, C.  Ye, Q.  Zhang, Y.  Chen, L.  Gu, K.  Davey, S. Z. Qiao, Angew. Chem., Int. Ed. 2019, 58, 7823; b) X. Zeng, J. Hao, Z. Wang, J. Mao, Z. Guo, Energy Storage Mater. 2019, 20, 410. \n[30]\t Y. Zeng, X. Zhang, Y. Meng, M. Yu, J. Yi, Y. Wu, X. Lu, Y. Tong, Adv. Mater. 2017, 29, 1700274. \n[31]\t W.  Sun, F.  Wang, S.  Hou, C.  Yang, X.  Fan, Z.  Ma, T.  Gao, F.  Han, R. Hu, M. Zhu, J. Am. Chem. Soc. 2017, 139, 9775. " + }, + { + "id": "10.1063_1.5143190", + "DOI": "10.1063/1.5143190", + "DOI Link": "http://dx.doi.org/10.1063/1.5143190", + "Relative Dir Path": "mds/10.1063_1.5143190", + "Article Title": "DFTB plus , a software package for efficient approximate density functional theory based atomistic simulations", + "Authors": "Hourahine, B; Aradi, B; Blum, V; Bonafé, F; Buccheri, A; Camacho, C; Cevallos, C; Deshaye, MY; Dumitrica, T; Dominguez, A; Ehlert, S; Elstner, M; van der Heide, T; Hermann, J; Irle, S; Kranz, JJ; Köhler, C; Kowalczyk, T; Kubar, T; Lee, IS; Lutsker, V; Maurer, RJ; Min, SK; Mitchell, I; Negre, C; Niehaus, TA; Niklasson, AMN; Page, AJ; Pecchia, A; Penazzi, G; Persson, MP; Rezác, J; Sánchez, CG; Sternberg, M; Stöhr, M; Stuckenberg, F; Tkatchenko, A; Yu, VWZ; Frauenheim, T", + "Source Title": "JOURNAL OF CHEMICAL PHYSICS", + "Abstract": "DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green's functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives. (C) 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).", + "Times Cited, WoS Core": 780, + "Times Cited, All Databases": 806, + "Publication Year": 2020, + "Research Areas": "Chemistry; Physics", + "UT (Unique WOS ID)": "WOS:000521986100001", + "Markdown": "# \n\n# DFTB+, a software package for efficient approximate density functional theory based atomistic simulations \n\nCite as: J. Chem. Phys. 152, 124101 (2020); https://doi.org/10.1063/1.5143190 Submitted: 20 December 2019 . Accepted: 27 February 2020 . Published Online: 23 March 2020 B. Hourahine , B. Aradi , V. Blum , F. Bonafé , A. Buccheri , C. Camacho , C. Cevallos , M. Y. Deshaye, T. Dumitrică , A. Dominguez, S. Ehlert , M. Elstner, T. van der Heide, J. Hermann , S. Irle $\\oplus_{i}$ , J. J. Kranz, C. Köhler, T. Kowalczyk , T. Kubař , I. S. Lee, V. Lutsker, R. J. Maurer $\\oplus_{i}$ , S. K. Min $\\oplus_{\\cdot}$ I. Mitchell $\\oplus_{\\cdot}$ C. Negre, T. A. Niehaus $\\oplus_{\\cdot}$ A. M. N. Niklasson $\\oplus,$ A. J. Page , A. Pecchia $\\oplus,$ G. Penazzi , M. P. Persson , J. ${\\check{\\mathsf{R e z i c}}}^{\\oplus},$ C. G. Sánchez , M. Sternberg, M. Stöhr , F. Stuckenberg, A. Tkatchenko, V. W.-z. Yu, and T. Frauenheim \n\n# COLLECTIONS \n\nPaper published as part of the special topic on Electronic Structure Software Note: This article is part of the JCP Special Topic on Electronic Structure Softwar \n\n![](images/4b27b96ae92caa8618c66577692555a501be003003584103aae0bacc1c338105.jpg) \n\nThis paper was selected as Featured \n\n![](images/045c4fab7d3bd7a241e839342ded0e5b653bb8dff97ebb6db57598dbcb184803.jpg) \n\n# ARTICLES YOU MAY BE INTERESTED IN \n\nAdventures in DFT by a wavefunction theorist The Journal of Chemical Physics 151, 160901 (2019); https://doi.org/10.1063/1.5116338 \n\nGeneralized spin mapping for quantum-classical dynamics The Journal of Chemical Physics 152, 084110 (2020); https://doi.org/10.1063/1.5143412 \n\nA consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu The Journal of Chemical Physics 132, 154104 (2010); https://doi.org/10.1063/1.3382344 \n\n![](images/bb3263f3e5931e72d435127f205eaee238964f315d39c4df411b0c59a5abdbcc.jpg) \n\n# DFTB+, a software package for efficient approximate density functional theory based atomistic simulations \n\nCite as: J. Chem. Phys. 152, 124101 (2020); doi: 10.1063/1.514319 Submitted: 20 December 2019 $\\cdot$ Accepted: 27 February 2020 • Published Online: 23 March 2020 \n\nB. Hourahine,1 $\\textcircled{1}$ B. Aradi,2,a) $\\textcircled{1}$ V. Blum,3 $\\textcircled{1}$ F. Bonafé,4 $\\textcircled{1}$ A. Buccheri,5 $\\textcircled{1}$ C. Camacho,6 $\\textcircled{1}$ C. Cevallos,6 \nM. Y. Deshaye,7 T. Dumitric˘a,8 A. Dominguez,2,9 S. Ehlert,10 M. Elstner,11 T. van der Heide,2 J. Hermann,12 \nS. Irle,13 J. J. Kranz,11 C. Köhler,2 T. Kowalczyk,7 T. Kubarˇ, $11\\textcircled{\\scriptsize{\\parallel}}$ I. S. Lee,14 V. Lutsker,15 R. J. Maurer,16 \nS. K. Min,14 I. Mitchell,17 C. Negre,18 T. A. Niehaus,19 $\\textcircled{1}$ A. M. N. Niklasson,18 A. J. Page,20 A. Pecchia,21 $\\textcircled{1}$ \nG. Penazzi,2 M. P. Persson,22 J. Rˇ ezáˇc,23 C. G. Sánchez,24 M. Sternberg,25 M. Stöhr,26 \nF. Stuckenberg,2 A. Tkatchenko,26 V. W.-z. Yu,3 and T. Frauenheim2,9 \n\n# AFFILIATIONS \n\n1 SUPA, Department of Physics, The University of Strathclyde, Glasgow G4 0NG, United Kingdom \n2 Bremen Center for Computational Materials Science, University of Bremen, Bremen, Germany \n3 Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708, USA \n4 Max Planck Institute for the Structure and Dynamics of Matter, Hamburg, Germany \n5 School of Chemistry, University of Bristol, Cantock’s Close, Bristol BS8 1TS, United Kingdom \n6 School of Chemistry, University of Costa Rica, San José 11501-2060, Costa Rica \n7 Department of Chemistry and Advanced Materials Science and Engineering Center, Western Washington University, \nBellingham, Washington 98225, USA \n8 Department of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA \n9 Computational Science Research Center (CSRC) Beijing and Computational Science Applied Research (CSAR) \nInstitute Shenzhen, Shenzhen, China \n10University of Bonn, Bonn, Germany \n11 Institute of Physical Chemistry, Karlsruhe Institute of Technology, Karlsruhe, Germany \n12Freie Universität Berlin, Berlin, Germany \n13Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA \n14Department of Chemistry, Ulsan National Institute of Science and Technology, Ulsan, South Korea \n15Institut I – Theoretische Physik, University of Regensburg, Regensburg, Germany \n16Department of Chemistry, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, United Kingdom \n17Center for Multidimensional Carbon Materials, Institute for Basic Science (IBS), Ulsan 44919, South Korea \n18Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA \n19Université de Lyon, Université Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, F-69622 Villeurbanne, France \n20School of Environmental and Life Sciences, University of Newcastle, Callaghan, Australia \n21CNR-ISMN, Via Salaria km 29.300, 00015 Monterotondo Stazione, Rome, Italy \n22Dassault Systemes, Cambridge, United Kingdom \n23Institute of Organic Chemistry and Biochemistry AS CR, Prague, Czech Republic \n24Instituto Interdisciplinario de Ciencias Básicas, Universidad Nacional de Cuyo, CONICET, \nFacultad de Ciencias Exactas y Naturales, Mendoza, Argentina \n25Argonne National Laboratory, Lemont, Illinois 60439, USA \n26Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg \n\nNote: This article is part of the JCP Special Topic on Electronic Structure Software. a)Author to whom correspondence should be addressed: aradi@uni-bremen.de \n\n# ABSTRACT \n\n${\\mathrm{DFTB}}+$ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green’s functions, and many more. ${\\mathrm{DFTB}}+$ can be used as a userfriendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the ${\\mathrm{DFTB}}+$ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives. \n\n$\\circledcirc$ 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). https://doi.org/10.1063/1.5143190., \n\n# I. INTRODUCTION \n\nDensity Functional Theory $(\\mathrm{DFT})^{1,2}$ dominates the landscape of electronic structure methods, being the usual go-to technique to model large, chemically complex systems at good accuracy. For larger systems and time scales, force-field models instead dominate materials and chemical modeling. Between these is the domain of semi-empirical methods, derived from approximations to Hartree– Fock or DFT based methods. Within this space, density functional based tight binding (DFTB)3–5 effectively offers a reduced complexity DFT method, being derived from a simplification of Kohn–Sham DFT to a tight binding form.6 \n\nThis paper describes the ${\\mathrm{DFTB}}+$ code,7 an open source implementation, which aims at collecting the developments of this family of methods and making them generally available to the chemical, materials, and condensed matter communities. This article describes extensions to this code since its original release in $2007,^{8}$ there being a lack of a more recent overview of its features and underlying theory. \n\n# II. DFTB $^+$ FEATURES \n\n# A. The core DFTB-model \n\nThe basic DFTB-equations are presented below. They can be easily generalized for periodic cases $k$ -points) as well as for other boundary conditions, as implemented in ${\\mathrm{DFTB}}+$ . All equations throughout this paper are given in atomic units with Hartree as the energy unit. \n\n# 1. Expansion of the total energy \n\nThe DFTB models are derived from Kohn–Sham (KS) $\\mathrm{DFT}^{2}$ by expansion of the total energy functional. Starting from a properly chosen reference density $\\rho_{0}$ (e.g., superposition of neutral atomic densities), the ground state density is then represented by this reference, as perturbed by density fluctuations: $\\rho({\\bf r})=\\rho_{0}({\\bf r})+\\delta\\rho({\\bf r})$ . The total energy expression then expands the energy functional in a \n\nTaylor series up to third order, \n\n$$\n\\begin{array}{r}{\\begin{array}{r}{E^{\\mathrm{DFTB3}}\\big[\\rho_{0}+\\delta\\rho\\big]=E^{0}\\big[\\rho_{0}\\big]+E^{1}\\big[\\rho_{0},\\delta\\rho\\big]+E^{2}\\big[\\rho_{0},\\big(\\delta\\rho\\big)^{2}\\big]}\\\\ {+E^{3}\\big[\\rho_{0},\\big(\\delta\\rho\\big)^{3}\\big]~}\\end{array}}\\end{array}\n$$ \n\nwith \n\n$$\n\\begin{array}{l}{{\\displaystyle{E}^{l}[\\rho_{\\mathrm{o}}]=\\frac{1}{2}\\sum_{i=1}^{Z_{\\mathrm{o}}\\zeta_{\\mathrm{o}}}\\frac{1}{K_{i k}}-\\frac{1}{2}\\int\\int\\frac{\\rho_{\\mathrm{o}}(\\boldsymbol{\\mathbf{r}})\\rho_{\\mathrm{o}}(\\boldsymbol{\\mathbf{r}}^{\\prime})}{|\\boldsymbol{\\mathbf{r}}-\\boldsymbol{\\mathbf{r}}^{\\prime}|}\\mathrm{d}\\boldsymbol{\\mathbf{r}}\\mathrm{d}^{\\prime}}\\ ~}\\\\ {{\\displaystyle~\\qquad-\\int\\ V^{\\mathrm{x}}[\\rho_{\\mathrm{o}}]\\rho_{\\mathrm{o}}(\\boldsymbol{\\mathbf{r}})\\mathrm{d}\\boldsymbol{\\mathbf{r}}+E^{\\mathrm{x}}[\\rho_{\\mathrm{o}}]},}\\\\ {{\\displaystyle E^{l}[\\rho_{\\mathrm{o}},\\delta\\rho]=\\sum_{i}n\\langle|\\psi|\\hat{H}[\\rho_{\\mathrm{o}}]|\\psi\\rangle_{i}\\rangle,}}\\\\ {{\\displaystyle E^{\\frac{1}{2}}[\\rho_{\\mathrm{o}},(\\hat{\\rho}\\rho)^{2}]=\\frac{1}{2}\\iint\\left(\\frac{1}{|\\boldsymbol{\\mathbf{r}}-\\boldsymbol{\\mathbf{r}}^{\\prime}|}+\\frac{\\delta^{2}E^{\\mathrm{x}}[\\rho_{\\mathrm{o}}]}{\\delta\\rho(\\boldsymbol{\\mathbf{r}})\\delta(\\rho^{\\prime})}\\Big|_{\\rho_{\\mathrm{o}}}\\right)\\delta\\rho(\\boldsymbol{\\mathbf{r}})\\delta\\rho(\\boldsymbol{\\mathbf{r}}^{\\prime})\\mathrm{d}\\boldsymbol{\\mathbf{r}}\\mathrm{d}\\boldsymbol{\\mathbf{r}}^{\\prime},}}\\\\ {{\\displaystyle E^{\\frac{1}{2}}[\\rho_{\\mathrm{o}},(\\hat{\\rho}\\rho)^{2}]=\\frac{1}{6}\\iint\\frac{\\delta^{3}E^{\\mathrm{x}}[\\rho]}{\\delta\\rho(\\boldsymbol{\\mathbf{r}})\\delta\\rho(\\boldsymbol{\\mathbf{r}}^{\\prime})\\delta\\rho(\\boldsymbol{\\mathbf{r}}^{\\prime})}\\mathrm{d}\\boldsymbol{\\mathbf{r}}}\\\\ {{\\displaystyle~\\qquad\\times\\delta\\rho(\\boldsymbol{\\mathbf{r}})\\delta\\rho(\\boldsymbol{\\mathbf{r}}^{\\prime})\\mathrm{d}\\boldsymbol{\\mathbf{r}}\\boldsymbol{\\mathbf{\\rho}}(\\boldsymbol{\\mathbf{r}}^{\\prime})\\mathrm{d}\\boldsymbol{\\mathbf{r}}\\mathrm{d}^{\\prime}}.}\\end{array}\n$$ \n\nwith XC being the exchange correlation energy and potential. Several DFTB models have been implemented, starting from the first order non-self-consistent DFTB13,4 [originally called DFTB or non-SCC DFTB], the second order DFTB2 (originally called SCC-DFTB),5 and the more recent extension to third order, DFTB3.9–12 \n\n# 2. DFTB1 \n\nThe first order DFTB1 method is based on three major approximations: (i) it takes only $E^{0}[\\rho_{0}]$ and $E^{1}[\\rho_{0},\\delta\\rho]$ from Eq. (2) into account, (ii) it is based on a valence-only minimal basis set $(\\phi_{\\mu})$ within a linear combination of atomic orbitals (LCAO) ansatz, \n\n$$\n\\psi_{i}=\\sum_{\\mu}c_{\\mu i}\\phi_{\\mu},\n$$ \n\nfor the orbitals $\\psi_{i}$ , and (iii) it applies a two-center approximation to the hamiltonian operator $\\hat{H}[\\rho_{0}]$ . \n\na. Minimal atomic basis set. The atomic orbital basis set $\\phi_{\\mu}$ is explicitly computed from DFT by solving the atomic Kohn– Sham equations with an additional (usually harmonic) confining potential, \n\n$$\n\\biggl[-\\frac{1}{2}{\\boldsymbol{\\nabla}}^{2}+V^{\\mathrm{\\scriptsize~eff}}\\bigl[\\rho^{\\mathrm{\\scriptsize~atom}}\\bigr]+\\biggl(\\frac{r}{r_{0}}\\biggr)^{n}\\biggr]\\phi_{\\mu}=\\epsilon_{\\mu}\\phi_{\\mu}.\n$$ \n\nThis leads to slightly compressed atomic-like orbitals for describing the density in bonding situations. The actual values for $r_{0}$ are usually given in the publications describing the specific parameterization. The operator ${\\hat{H}}[\\rho^{0}]$ also depends on the superposition of atomic densities, $\\rho_{A}$ (or potentials, $V_{A}^{\\mathrm{eff}}.$ ) of neutral atoms, $\\{A\\}$ , in the geometry being modeled. This density is usually determined from the same atomic KS equations using a slightly different confinement radius, $r_{0}^{\\mathrm{d}}$ . \n\nb. DFTB matrix elements. The hamiltonian can be represented in an LCAO basis as \n\n$$\nH_{\\mu\\nu}^{0}=\\bigl\\langle\\phi_{\\mu}\\bigl|\\hat{H}\\bigl[\\rho_{0}\\bigr]\\bigr|\\phi_{\\nu}\\bigr\\rangle\\approx\\bigl\\langle\\phi_{\\mu}\\bigl|-\\frac{1}{2}\\nabla^{2}+V\\bigl[\\rho_{A}+\\rho_{B}\\bigr]\\bigr|\\phi_{\\nu}\\bigr\\rangle,\\quad\\mu\\in A,\\nu\\in B,\n$$ \n\nwhere the neglect of the three center terms and pseudo-potential contributions lead to a representation, which can be easily computed by evaluating the Kohn–Sham equations for dimers. These matrix elements are computed once as a function of inter-atomic distance for all element pairs. The Slater–Koster13 combination rules are applied for the actual orientation of these “dimers” within a molecule or solid. \n\nc. Total energy. ${\\cal E}^{0}[\\rho_{0}]$ depends only on the reference density, so is universal in the sense that it does not specifically depend on the chemical environment (which would determine any charge transfer (CT), $\\delta\\rho_{;}$ , occurring). It can, therefore, be determined for a “reference system” and then applied to other environments. This is the key to transferability of the parameters. In DFTB, ${\\boldsymbol E}^{0}[\\rho_{0}]$ is approximated as a sum of pair potentials called repulsive energy terms, \n\n$$\n{\\cal E}^{0}[\\rho_{0}]\\approx E_{\\mathrm{rep}}=\\frac{1}{2}\\sum_{A B}V_{A B}^{\\mathrm{rep}}\n$$ \n\n(see Ref. 14), which are either determined by comparison with DFT calculations4 or fitted to empirical data.15 Forces are calculated with the Hellmann–Feynman theorem and derivatives of the repulsive energy. \n\n# 3. DFTB2 and DFTB3 \n\nTo approximate the $E^{2}$ and $\\boldsymbol{E}^{3}$ terms in Eq. (2), the density fluctuations are written as a superposition of atomic contributions, taken to be exponentially decaying spherically symmetric charge densities \n\n$$\n\\delta\\rho(\\mathbf{r})=\\sum_{A}\\delta\\rho_{A}(\\mathbf{r}-\\mathbf{R}_{A})\\approx\\frac{1}{\\sqrt{4\\pi}}\\sum_{A}\\Biggl(\\frac{\\tau_{A}^{3}}{8\\pi}\\mathrm{e}^{-\\tau_{A}|\\mathbf{r}-\\mathbf{R}_{A}|}\\Biggr)\\Delta q_{A}.\n$$ \n\nBy neglecting the XC-contributions for the moment, the second order integral $E^{2}$ leads to an analytical function, $\\gamma_{A B}$ , with energy,5 \n\n$$\nE^{2}(\\tau_{A},\\tau_{B},R_{A B})=\\frac{1}{2}\\sum_{A B(\\neq A)}\\gamma_{A B}(\\tau_{A},\\tau_{B},R_{A B})\\Delta q_{A}\\Delta q_{B}.\n$$ \n\nThe energy depends on the Mulliken charges $\\{q_{A}\\}$ (where the atomic charge fluctuation, $\\Delta q_{A}=q_{A}-Z_{A}$ , is with respect to the neutral atom), which are, in turn, dependent on the molecular orbital coefficients, $c_{\\mu i}$ . Thus, the resulting equations have to be solved selfconsistently. At large distances, $\\gamma_{A B}$ approaches $1/R_{A B}$ , while at short distances, it represents electron–electron interactions within one atom. For the limit $R_{A B}\\rightarrow0$ , one finds $\\begin{array}{r}{\\tau_{A}=\\frac{16}{5}U_{A}}\\end{array}$ , i.e., the so-called Hubbard parameter $U_{A}$ →(twice the chem c=al hardness) is inversely proportional to the width of the atomic charge density $\\tau_{A}$ . This relation is intuitive in that more diffuse atoms (or anions) have a smaller chemical hardness. For DFTB, the chemical hardness is computed from DFT, not fitted. \n\nThe third order terms describe the change of the chemical hardness of an atom and are also computed from DFT. A function $\\Gamma_{A B}$ results as the derivative of the $\\gamma$ -function with respect to charge, and the DFTB3 total energy is then given by \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\cal E}^{\\mathrm{DFTB3}}=\\sum_{i}\\sum_{A B}\\sum_{\\mu\\in A}\\sum_{\\nu\\in B}n_{i}c_{\\mu i}c_{\\nu i}H_{\\mu\\nu}^{0}+\\frac12\\sum_{A B}\\Delta q_{A}\\Delta q_{B}\\gamma_{A B}^{h}}}\\\\ {{\\displaystyle~+~\\frac13\\sum_{A B}\\Delta q_{A}^{2}\\Delta q_{B}\\Gamma_{A B}+\\frac12\\sum_{A B}V_{A B}^{\\mathrm{rep}}.}}\\end{array}\n$$ \n\nThe third order terms become important when local densities deviate significantly from the reference, i.e., $\\Delta q_{A}$ is large. Apart from including the third order terms, DFTB3 also modifies $\\gamma_{A B}$ for the interactions between hydrogen and first row elements,9 where the deviation from the relation between the charge width and the chemical hardness, as formulated above, is most pronounced. \n\nThe resulting DFTB3 hamiltonian takes the form \n\n$$\nH_{\\mu\\nu}={H}_{\\mu\\nu}^{0}+{H}_{\\mu\\nu}^{2}[\\gamma^{h},\\Delta q]+{H}_{\\mu\\nu}^{3}[\\Gamma,\\Delta q],\\qquad\\mu\\in{\\cal A},\\nu\\in{\\cal B},\n$$ \n\n$$\nH_{\\mu\\nu}^{2}={\\frac{S_{\\mu\\nu}}{2}}\\sum_{C}\\Bigl(\\gamma_{B C}^{h}+\\gamma_{A C}^{h}\\Bigr)\\Delta q_{C},\n$$ \n\n$$\nH_{\\mu\\nu}^{3}=S_{\\mu\\nu}\\sum_{C}\\biggl(\\frac{\\Delta q_{A}\\Gamma_{A C}}{3}+\\frac{\\Delta q_{B}\\Gamma_{B C}}{3}+\\bigl(\\Gamma_{A C}+\\Gamma_{B C}\\bigr)\\frac{\\Delta q_{c}}{6}\\biggr)\\Delta q_{C},\n$$ \n\nwhere $S_{\\mu\\nu}$ is the overlap matrix between orbitals $\\phi_{\\mu}$ and $\\phi_{\\nu}$ , and $\\gamma^{h}$ is the modified DFTB2 interaction. \n\n# 4. Spin \n\nAnalogous to DFTB2, expanding the energy with respect to spin fluctuations16–18 leads to the spin-polarized expressions for DFTB. By introducing the magnetization density $m(\\mathbf{\\bar{r}})=\\rho^{\\uparrow}({\\bf r})-\\rho^{\\downarrow}({\\bf r})$ as difference of the densities of spin-up and spin-down elec−trons and its corresponding fluctuations $\\left[{\\delta m({\\bf r})}\\right]$ around the spin-unpolarized reference state $[|m({\\bf r})|=0]$ , a spin dependent term is added to the spin-independent $E^{2}$ of Eq. (2), \n\n$$\n\\begin{array}{c}{{\\displaystyle{\\cal E}^{2}\\big[\\rho_{0},big(\\delta\\rho)^{2},\\big(\\delta m\\big)^{2}\\big]={\\cal E}^{2}\\big[\\rho_{0},\\big(\\delta\\rho\\big)^{2}\\big]+\\frac{1}{2}\\int\\left.\\frac{\\delta^{2}{\\cal E}^{\\mathrm{xc}}[\\rho,m]}{\\delta m({\\bf r})^{2}}\\right\\vert_{\\rho_{0},m=0}}}\\\\ {{\\times\\left.\\delta m({\\bf r})^{2}\\mathrm{d}{\\bf r},\\qquad(1\\mathrm{~}}}\\end{array}\n$$ \n\nwhere a local or semi-local $E^{\\mathrm{xc}}$ has been assumed. \n\nIdentifying the spin density fluctuations with up- and downspin Mulliken charge differences, $\\Delta p_{A l},$ for angular momentum shell $l$ at atom $A$ , and approximating the second derivative of $E^{\\mathrm{xc}}[\\rho,m]$ as an atomic constant $W_{A l l^{\\prime}}$ (similar to the Hubbard $U_{A}$ ) lead to an on-site energy contribution \n\n$$\nE_{s p i n}^{2}=\\frac{1}{2}\\sum_{A}\\sum_{l\\in A}\\sum_{l^{\\prime}\\in A}W_{A l l^{\\prime}}\\Delta p_{A l}\\Delta p_{A l^{\\prime}}.\n$$ \n\nThis term in Eq. (14) is to be added to Eq. (8). It captures the spin-polarization contribution to the total energy and couples different atomic angular momentum shells via magnetic interaction. The $W_{A l l^{\\prime}}$ are usually an order of magnitude less than the $U_{A}$ and are multiplied with a (typically) small $\\Delta p_{A l};$ hence, inclusion of spinpolarization via Eq. (14) gives only a small energy contribution. If there is a net imbalance of up- and down-spin electrons in the system, the occupation of electronic states alone carries most of the effect of the unpaired electron(s) without including Eq. (14). The use of Mulliken charges leads to an additional hamiltonian contribution17 to the (now) shell resolved form of Eq. (10), \n\n$$\n\\begin{array}{c}{{H_{\\mu\\nu}^{s p i n\\pm}=\\pm\\displaystyle\\frac{S_{\\mu\\nu}}{2}\\Bigg(\\sum_{l^{\\prime\\prime}\\in A\\atop l\\not\\in l\\in A}W_{A l l^{\\prime\\prime}}\\Delta p_{A l^{\\prime\\prime}}+\\sum_{l^{\\prime\\prime}\\in B}W_{B l^{\\prime}l^{\\prime\\prime}}\\Delta p_{B l^{\\prime\\prime}}\\Bigg),}}\\\\ {{\\mu\\in l\\in A,\\nu\\in l^{\\prime}\\in B,}}\\end{array}\n$$ \n\nwhere the spin up (down) hamiltonian has this term added (subtracted). \n\nExpanding further to local (not global) up and down spin populations via Pauli spinors gives the non-collinear spin model.19 Equation (14) becomes \n\n$$\nE_{s p i n}^{2}=\\frac{1}{2}\\sum_{A}\\sum_{l\\in A}\\sum_{l^{\\prime}\\in A}W_{A l l^{\\prime}}\\Delta\\vec{p}_{A l}\\cdot\\Delta\\vec{p}_{A l^{\\prime}},\n$$ \n\nand the wave-function generalizes to two component spinors. The hamiltonian contributions take the form \n\n$$\n\\left(H_{\\mu\\nu}^{0}+H_{\\mu\\nu}^{2}+H_{\\mu\\nu}^{3}\\right)\\otimes{\\binom{1~0}{0~1}}+\\sum_{i=1}^{3}H_{\\mu\\nu}^{\\sigma_{i}}\\otimes\\sigma_{i},\n$$ \n\nwhere $\\sigma_{i}$ is the Pauli matrix for spin component $i(=x,\\ y,\\ z)$ and $H^{\\sigma_{i}}$ is constructed from the ith spin component of $\\Delta\\vec{p}$ . This spinblock two component hamiltonian then also enables spin–orbit cou$\\mathrm{pling}^{19,20}$ to be included in DFTB $^+$ . The spin-block hamiltonian addition is \n\n$$\nH_{\\mu\\nu}^{L\\cdot S}=\\frac{S_{\\mu\\nu}}{2}\\otimes\\left(\\xi_{A l}{\\left(L_{z}\\begin{array}{l}{L^{-}}\\\\ {L^{+}-L_{z}}\\end{array}\\right)}_{l}+\\xi_{B l^{\\prime}}{\\left(L_{z}\\begin{array}{l}{L^{-}}\\\\ {L^{+}}\\end{array}\\right)}_{l^{\\prime}}\\right),\n$$ \n\n$$\n\\mu\\in l\\in A,\\nu\\in l^{\\prime}\\in B,\n$$ \n\nwhere $\\xi_{A l}$ is the spin orbit coupling constant for shell $l$ of atom $A$ with $L^{\\pm}$ and $L_{z}$ being the angular momentum operators for atomic shells. \n\n# 5. Limitations of the core DFTB-model \n\nDFTB is an approximate method, and as such shows limitations, which can be traced back to the different approximations applied. However, the fitting of Eq. (6) can compensate for some of the inaccuracies. Since until now, only bonding contributions are addressed by the two-center nature of the repulsive potentials, bond-lengths, bond-stretch frequencies, and bond-energies can be targeted (properties such as bond angles or dihedral angles cannot be influenced by repulsive pair parameterization). This is the reason why DFTB performs better than a fixed minimal basis DFT method, which would be only of limited use in most of the applications. In some cases, DFTB can even perform better than double-zeta (DZ) DFT using generalized gradient approximation (GGA) functionals, as shown, e.g., in Ref. 12. This accuracy definitely can be traced back to the parameterization. \n\na. Integral approximations. There are some approximations in DFTB that cannot be compensated by parameterization, effecting, e.g., bond angles and dihedrals, which on average show an accuracy slightly less than DFT/DZ. Furthermore, the integral approximation leads to an imbalanced description of bonds with different bond order. For example, C–O single, double, and triple bonds have to be covered by a single repulsive potential, which shows only a limited transferability over the three bonding situations. This is the reason why both good atomization energies and vibrational frequencies cannot be covered with a single fit. Hence, in that work, two parameterizations were proposed, one for obtaining accurate energies and one for the vibrational frequencies. Similarly, description of different crystal phases with the same chemical composition but with very different coordination numbers can be challenging. Recent examples show,21,22 however, that it is possible to reach a reasonable accuracy if special care is taken during the parameterization process. \n\nb. Minimal basis set. The minimal basis set used has several clear limitations, which show up in the overall DFTB performance: First, for a good description of hydrogen in different bonding situations, relatively diffuse wave functions have to be chosen. For this atomic wave-function, however, the $\\mathrm{H}_{2}$ atomization energy is in error, which is dealt with by an ad hoc solution, again providing a special repulsive parameter set.12 Furthermore, nitrogen hybridization and proton affinities require at least the inclusion of $d$ -orbitals in the basis set: this again can be compensated by a special parameter set, which has to be applied under certain conditions.12 A similar problem occurs for highly coordinated phosphorus containing species.23 The minimal basis can also become problematic when describing the high lying (conduction band) states in solids. For example, silicon needs $d$ -orbitals in order to describe the conduction band minimum properly. The valence band, on the other hand, can be reasonably described with an $\\boldsymbol{s p}$ -only basis. \n\nc. Basis set confinement. As a result of the orbital confinement, Pauli repulsion forces are underestimated, which leads to DFTB non-bonding interactions being on average too short by $10\\%-15\\%$ . This has been investigated in detail for liquid water, where a different repulsive potential has been suggested.24 A related problem concerns molecular polarizabilities, which are underestimated using a minimal basis set. Approaches to correct for this shortcoming have been summarized recently in Ref. 25. The too-confined range of basis functions also impairs the calculation of electron-transfer couplings. Here, unconfined basis sets have to be used.26 Similarly, it can be challenging to find a good compromise for the basis confinement when describing 2D-layered materials. As the interlayer distances are significantly longer than the intra-layer ones, the binding between the layers often becomes weaker compared to DFT. \n\nd. DFT inherited weaknesses. DFTB is derived from DFT and uses standard DFT functionals, which also come with some wellknown limitations. There, several strategies applied within DFT are also viable for DFTB, as discussed below in more detail. \n\n# B. Density matrix functionals \n\nThe typical behavior of the SCC-DFTB ground state resembles local-density approximation (LDA) or GGA,27 i.e., a mean-field (MF) electronic structure method with associated self-interaction errors and, for some systems, qualitatively incorrect ground states. This is in contrast to non-SCC DFTB, which gives the correct linearity of total energy and step-wise chemical potentials28 for fractionally charged systems. However, non-SCC can also produce MF-DFT limits, such as in the case of dimer dissociation29,30 due to self-interaction errors in the underlying atomic DFT potentials. \n\n${\\mathrm{DFTB}}+$ now also supports long-range corrected hybrid functionals for exchange and correlation. With respect to conventional local/semi-local functionals, these are known to provide a better description of wave function localization and significantly reduce self-interaction.31 In the longer term, ${\\mathrm{DFTB}}+$ will continue to develop post-DFT based methods with the aim of making large $(\\gtrsim1000$ atom) correlated systems tractable via methods with correlated self-energies or wave-functions. \n\n# 1. Onsite corrections \n\nDFTB2 neglects on-site hamiltonian integrals of the type $(\\mu\\nu|\\mu\\nu)$ , where $\\phi_{\\mu}$ and $\\phi_{\\nu}$ are two different atomic orbitals of the same atom [both Eq. (5) and the use of Mulliken charges give onsite elements only for $\\delta_{\\mu\\nu}=1\\mathrm{\\ddot{\\Omega}}$ ]. A generalized dual population32 can be introduced as \n\n$$\nQ_{\\mu\\nu}^{A,l}=\\frac{1}{2}\\sum_{\\kappa}\\bigl(\\rho_{\\mu\\kappa}\\ensuremath{S_{\\kappa\\nu}}+\\ensuremath{S_{\\mu\\kappa}}\\rho_{\\kappa\\nu}\\bigr),\\qquadl\\in A;\\mu,\\nu\\in l,\n$$ \n\nwhere $Q_{\\mu\\nu}^{A,l}$ is a population matrix for shell $l$ of atom $A$ and the diagonal of each block represents the conventional Mulliken charges for orbitals in the lth shell. Based on this population, all fluctuations of the atomic parts of the density matrix from the reference can be included, not only the diagonal (charge) elements. These must then be treated self-consistently during the calculation. This generalization leads, for example, to an improved description of hydrogen bonds in neutral, protonated, and hydroxide water clusters as well as other water-containing complexes.33 \n\nThe onsite-corrected DFTB requires additional atomic parameters; these are not tunable but computed numerically using DFT (see Ref. 34 for details of their evaluation). The onsite parameter for some chemical elements can be found in the ${\\mathrm{DFTB}}+$ manual. The calculation requires convergence in the dual density populations. This is a somewhat heavier convergence criterion than just charge convergence, and thus, the computational time is moderately affected. \n\n# 2. $D F T B+U$ and mean-field correlation corrections \n\nFor correlated materials such as NiO, a popular correction choice in DFT is the $\\mathrm{LDA+U}$ family of methods,35 which add a contribution to the energy of the specified local orbitals obtained from the Hubbard model. The rotationally invariant36 form of $\\mathrm{LDA+U}$ can be written in terms of several choices of local projections of the density matrix.32 Likewise, the double-counting between the Hubbard-model and the density functional mean-field functional take several limiting cases.37 In ${\\mathrm{DFTB}}+$ , the fully localized limit of this functional was implemented early in the code’s history27 using the populations of Eq. (19). Originally applied for rare-earth systems,38 $\\mathrm{DFTB+U}$ gives excellent agreement with $\\mathrm{GGA+U}$ .39 A closely related correction, pseudo-SIC,40 where the local part of the self-interaction is removed, modifying only the occupied orbitals, is also available. These approximations lower the energies of occupied atomic orbitals within the specified atomic shells with the aim of removing self-interaction or more accurately representing selfenergy. However, as with its use in DFT, this approximation suffers from three main drawbacks. First, the form of the correction depends on the choice of double counting removal.41 The correlation is also mean-field in nature; hence, all equally filled orbitals within a shell receive the same correction, and therefore, cases not well described by a single determinant are not systematically improved. Finally, the choice of the $U$ (and $J_{.}$ ) values is not necessarily obvious, with a number of different empirical, linear response, and self-consistent choices possible. Specific to DFTB,42 the $U$ values may also require co-optimization with the repulsive parameters, in particular, for systems where the electronic structure is geometrically sensitive. \n\n# 3. Long-range corrected hybrid functionals \n\na. Single determinant formulation. To correct longer range errors, the electron–electron interactions can be split into short and long range components based on a single parameter $\\omega$ , \n\n$$\n\\frac{1}{r}=\\frac{\\exp\\bigl(-\\omega r\\bigr)}{r}+\\frac{\\bigl(1-\\exp\\bigl(-\\omega r\\bigr)\\bigr)}{r}.\n$$ \n\nThe short range contribution is treated in a local or semi-local density functional approximation, while the long range term gives rise to a Hartree–Fock-like exchange term in the hamiltonian.31 The necessary adaptions for the DFTB method (termed LC-DFTB) were introduced in Refs. 43 and 44. Note that quite generally for ${\\mathrm{DFTB}}+$ , the exchange-correlation functional is effectively chosen by loading the appropriate Slater–Koster files created for the desired level of theory. This also holds for LC-DFTB, where different values for the range-separation parameter, $\\omega$ , lead to different Slater–Koster files. The database at www.dftb.org currently hosts the ob2 set45 for the elements O, N, C, and H with $\\overline{{\\omega}}=0.3~a_{0}^{-1}$ . \n\nLC-DFTB calculations can also be performed for spin-polarized systems, enabling evaluation of triplet excited states and their corresponding relaxed geometries. It also paves the way for a rational determination and tuning31 of the range-separation parameter $\\omega$ , which amounts to total energy evaluations for neutral and singly ionized species. Note that the required atomic spin constants are functional specific. The spin parameters for the ob2 Slater–Koster set are available in the manual. \n\n$b$ . Spin restricted ensemble references. Instead of single determinants, the spin-restricted ensemble-referenced Kohn–Sham (REKS) method and its state-interaction state-averaged variant (SISA-REKS or $\\mathsf{S S R})^{46-51}$ based on ensemble density functional theory are now available in ${\\mathrm{DFTB}}+$ . SSR can describe electronic states with multi-reference character and can accurately calculate excitation energies between them (see Sec. II C 2). The SSR method is formulated in the context of the LC-DFTB method (LC-DFTB/SSR)52 since a long-range corrected functional is crucial to correctly describe the electronic structure particularly for the excited states (see Ref. 52 for details of the formalism). Spin-polarization parameters are also required to describe open-shell microstates. It was observed that LC-DFTB/SSR sometimes gives different stability of the open-shell singlet microstates from the conventional SSR results, depending on excitation characters. In such a case, a simple scaling of atomic spin constants is helpful to account for correct excitation energies (see Ref. 52 for the required scaling of spin constants). The LC-DFTB/SSR method can be extended in the future by using larger active spaces or with additional corrections such as the onsite or DFTB3 terms. \n\n# 4. Non-covalent interactions \n\nIn large systems, non-covalent interactions (van der Waals/vdW forces) between molecules and between individual parts of structures become of key importance. The computational performance of DFTB makes these systems accessible, but large errors are observed for these weaker interactions. Being derived from (semi-)local density-functional theory, DFTB naturally shares the shortcomings of these approximations. This includes the lack of long-range electron correlation that translates to underestimated or missing London dispersion. An accurate account of vdW forces is essential in order to reliably describe a wide range of systems in biology, chemistry, and materials science. DFTB has already been successfully combined with a range of different correction schemes53–58 to account for these weaker interactions, but here we outline some newer methods available in DFTB $^+$ . \n\na. H5 correction for hydrogen bonds. The H5 correction59 addresses the issue of hydrogen bonding at the level of the electronic structure. For DFTB2 and DFTB3, interaction energies of H-bonds are severely underestimated for two main reasons: most importantly, the monopole approximation does not allow on-atom polarization; even if this limitation is lifted, the use of minimal basis does not allow polarization of hydrogen. In the H5 correction, the gamma function (Sec. II A 3) is multiplied by an empirical term enhancing the interactions at hydrogen bonding distances between hydrogen atoms and electronegative elements (N, O, and S). The H5 correction is applied within the SCC cycle, thus including many-body effects (the source of the important cooperativity in H-bond networks). The H5 correction was developed for DFTB3 with the 3OB parameters and a specific version of the DFT- $\\mathrm{D}3^{60,61}$ dispersion correction. Note that this D3 correction also includes an additional term augmenting hydrogen–hydrogen repulsion at short range (necessary for an accurate description of aliphatic hydrocarbons62,63). \n\n$b$ . DFT-D4 dispersion correction. The D4 model64,65 is now available in ${\\mathrm{DFTB}}+$ as a dispersion correction. Like D3, pairwise $C_{6}^{A B}$ dispersion coefficients are obtained from a Casimir–Polder integration of effective atomic polarizabilities $\\alpha_{A/B}^{\\mathrm{eff}}(i u)$ , \n\n$$\nC_{6}^{A B}=\\frac{3}{\\pi}\\int_{0}^{\\infty}\\alpha_{A}^{\\mathrm{eff}}(i u)\\alpha_{B}^{\\mathrm{eff}}(i u)\\mathrm{d}u.\n$$ \n\nThe influence of the chemical environment is captured by using a range of reference surroundings, weighted by a coordination number. D4 improves on its predecessor by also including a charge scaling based on atomic partial charges determined as either Mulliken64 or classical electronegativity equilibration.65 Especially for metalcontaining systems, the introduced charge dependence improves thermochemical properties.66 Large improvements can also be observed for solid-state polarizabilities of inorganic salts.67 For a full discussion on the methodology behind D4, we refer the reader to Ref. 65, and the implementation details are presented in Ref. 67. The damping parameters for several Slater–Koster sets are provided in the supplementary material. \n\nTo investigate the performance of the DFTB-D4 parameterizations, we evaluate the association energies for the S30L benchmark set.68,69 DFTB-D4 is compared to DFTB3(3ob)-D3(BJ),54 GFN1-xTB,70 and GFN2-xTB;71 additionally, we include the dispersion corrected $\\mathrm{SCAN}^{72}$ functional in comparison to DFT. The deviation from the reference values is shown in Fig. 1. For the mio parameterization, complexes 4, 15, and 16 were excluded due to missing Slater–Koster parameters. The direct comparison of DFTB3(3ob)-D3(BJ) with a MAD of $7.1\\mathrm{kcal/mol}$ to the respective D4 corrected method with a MAD of $6.5\\mathrm{\\kcal/mol}$ shows a significant improvement over its predecessor. The DFTB2(mio)-D4 gives an improved description with a MAD of $4.5\\mathrm{kcal/mol}$ , which is better than GFN1-xTB with a MAD of $5.5\\mathrm{kcal/mol}$ . The best performance is reached with GFN2-xTB due to the anisotropic electrostatics and the density dependent D4 dispersion, giving a MAD of $3.6\\mathrm{kcal/mol}$ . \n\n![](images/fd9834939fafc7cd7a95abaedd3ca90441c42e58d13d9c60264532f8d315594d.jpg) \nFIG. 1. Performance of different dispersion corrected tight binding methods on the S30L benchmark set, and the values for SCAN-D4 are taken from Ref. 65. \n\nc. Tkatchenko–Scheffler (TS) dispersion. The Tkatchenko– Scheffler $\\mathrm{(TS)}^{73}$ correction includes vdW interactions as Londontype atom-pairwise $C_{6}/{R}^{6}$ -potentials with damping at short interatomic separations, where the electronic structure method already captures electron correlation. The suggested damping parameters for the mio and 3ob parameter sets are listed in the supplementary material. In the TS approach, all vdW parameters including the static atomic dipole polarizability, $\\alpha$ , and $C_{6}$ -dispersion coefficients depend on the local electronic structure and the chemical environment.73 High-accuracy in vacuo reference values (labeled by vac) are rescaled via \n\n$$\nx^{2}=\\left(\\frac{\\alpha_{A}^{\\mathrm{eff}}}{\\alpha_{A}^{\\mathrm{vac}}}\\right)^{2}=\\frac{C_{6,\\mathrm{eff}}^{A A}}{C_{6,\\mathrm{vac}}^{A A}}.\n$$ \n\nIn the case of DFT, $x$ is approximated based on the Hirshfeld atomic volumes.74 When combined with DFTB, a fast yet accurate alternative has been proposed,58 which does not require evaluating a real-space representation of the electron density. Instead, the ratio between atom-in-molecule and in vacuo net atomic electron populations [i.e., $\\operatorname{tr}(\\rho)_{A}/Z_{A}]$ is used to define $x$ . \n\nd. Many-body dispersion (MBD). Going beyond pairwise interactions, many-body dispersion $\\mathrm{(MBD)}^{75,76}$ accounts for manyatom interactions in a dipolar approximation up to infinite order in perturbation theory. This is achieved by describing the system as a set of coupled polarizable dipoles75 with rescaled in vacuo reference polarizabilities [as in Eq. (22)]. At short-ranges, this model switches, via a Fermi-like function with a range of $\\beta$ , to the local atomic environment as accounted for by solving a Dyson-like selfconsistent screening equation. $^{76}\\beta$ represents a measure for the range of dynamic correlation captured by the underlying electronic structure method, so it depends on the density functional or DFTB parameterization. The recommended $\\beta$ -values for the mio and 3ob parameter sets are listed in the supplementary material. \n\n# C. Excited states and property calculations \n\n# 1. Time dependent DFTB with Casida formalism \n\nElectronic excited states are accessible in DFTB $^+$ through time dependent DFTB methods (see Ref. 86 for a review and detailed discussion of this formalism). In a linear response treatment in the frequency domain, excitation energies are obtained by solving an eigenvalue problem known as Casida or RPA (random phase approximation) equations. Compared to first-principles time dependent DFT, the computational scaling can be reduced in DFTB from $N^{6}$ to $N^{3}$ . This is due to the Mulliken approximation for two-electron integrals,87 which uses transition charges $q_{A}^{p q\\sigma}$ , \n\n$$\nq_{A}^{p q\\sigma}=\\frac{1}{4}\\sum_{\\mu\\in A}\\sum_{\\nu}\\Bigl(c_{\\mu p}^{\\sigma}\\tilde{c}_{\\nu q}^{\\sigma}+c_{\\mu q}^{\\sigma}\\tilde{c}_{\\nu p}^{\\sigma}+c_{\\nu p}^{\\sigma}\\tilde{c}_{\\mu q}^{\\sigma}+c_{\\nu q}^{\\sigma}\\tilde{c}_{\\mu p}^{\\sigma}\\Bigr),\\tilde{\\mathbf{c}}_{p}=\\mathbf{c}_{p}\\cdot\\mathbf{S},\n$$ \n\nfor transitions from the Kohn–Sham orbital $p\\sigma$ to $q\\sigma$ . \n\nFor fixed geometry, ${\\mathrm{DFTB}}+$ provides a user defined number of low lying excitation energies, oscillator strengths, and orbital participations. In another mode of operation, the code computes excited state charges, eigenvectors of the Casida equation, and energy gradients for a specific state of interest, which can be combined with \n\n![](images/874b73f1cc463e99b5f89d98885309926d0824ec5faeba06cba9d0f45fac2715.jpg) \nFigure 2 and Ref. 58 demonstrate that DFTB and MBD represent a promising framework to accurately study long-range correlation forces and emergent behavior at larger length- and timescales. Recently, the DFT $\\ensuremath{\\mathrm{\\3+MBD}}$ approach has allowed the study of organic molecular crystals55 and solvated biomolecules, revealing the complex implications of many-body vdW forces for proteins and their interaction with aqueous environments.82 Further improvements of TS and MBD, including a better description of charge transfer effects83 and variational self-consistency,84 may also be incorporated into DFTB in the future. Both methods are formulated independently of the underlying electronic-structure methods. As a result, DFTB $^+$ outsources the evaluation of the MBD and TS interactions to Libmbd,85 an external open-source library. \nFIG. 2. Mean absolute errors (MAEs) and mean absolute relative errors (MAREs) in inter-molecular interaction energies of bare DFTB and with different van der Waals models in comparison to high-level reference data. S66 and $S66\\times8$ : small organic dimers and their dissociation curves,77,78 SMC13: set of 13 supra-molecular complexes.79–81 \n\nMD or geometry relaxation. For spin-unpolarized calculations, the response matrix is block diagonal for the singlet and triplet channels to speed up the computation. ${\\mathrm{DFTB}}+$ allows for the computation of the excited state properties of systems with general fractional occupation of the KS orbitals. This is useful, for example, for the simulations of metals and semi-metals at a finite temperature. For a detailed discussion on spin-polarization and fractional occupation within time dependent (TD) DFTB, see Ref. 34. The onsite correction, discussed in Sec. II B 1, is also possible for excited state calculations and was shown to lead to marked improvements.34 \n\nDue to their improved treatment of charge-transfer transitions, range-separated functionals are also relevant in the context of excited states. ${\\mathrm{DFTB}}+$ implements the time dependent long range corrected (TD-LC) DFTB method, as described in Ref. 88. Compared to the conventional TD-DFTB, the lower symmetry of the response matrix leads to a non-Hermitian eigenvalue problem, which we solve by the algorithm of Stratmann and co-workers.89 Somewhat surprisingly, it turns out that TD-LCDFTB calculations are, in practice, not significantly slower than TD-DFTB calculations (see Ref. 88 for a deeper discussion). Gradients can also be calculated with TD-LC-DFTB, making it possible to perform geometry optimizations and MD simulations in singlet excited states. \n\nNote that energetically high lying states and Rydberg excitations are clearly outside of the scope of TD(-LC)-DFTB since their description generally requires very diffuse basis sets. Apart from this class, the photochemically more relevant set of low energy valence excitations are predicted with similar accuracy to first principles TD-DFT, as several benchmarks indicate.34,90,91 As mentioned above, charge-transfer excitations can now be also treated using TD-LC-DFTB.88 \n\n# 2. SSR and excitations \n\nCurrently, the SSR method implemented in ${\\mathrm{DFTB}}+$ is formulated for active spaces including two electrons in two fractionally occupied orbitals [i.e., SSR(2,2)], which is suitable for a singlet ground state and the lowest singlet excited state as well as a doubly excited state.52 In addition, since the SSR method is based on an ensemble representation and includes the electronic correlation, it can give correct state-interactions among nearly degenerate electronic states. Thus, the SSR approach is useful to investigate conical intersections. The LC-DFTB/SSR method with scaled spin constants can accurately describe the ground and excited states including $\\pi/\\pi^{*}$ or $n/\\pi^{*}$ character, undergoing bond cleavage/bond formation reactions as well as the conical intersections where the conventional (TD)DFTB fails to obtain the electronic properties. Analytic energy gradients as well as non-adiabatic couplings are also available. \n\n# 3. Time-independent excited states from ΔDFTB \n\nThe linear response approach to excited-state properties in DFTB is efficient and powerful, but there exist circumstances where a more direct route to the excited states is desirable. For example, the excited-state properties obtained from linear response theory require an additional order of derivatives relative to the ground state. As noted in Sec. II C 1, linear-response TD-DFTB (like its parent method TD-DFT)92 should invoke range-separation to achieve a qualitatively correct picture of charge-transfer excitations and related long-range phenomena.88 \n\nAs an alternative to the time-dependent linear-response approach, it is possible to variationally optimize certain electronically excited states directly. The ΔDFTB method, modeled on the $\\Delta$ -self-consistent-field (ΔSCF) approach to excited states in DFT,93,94 involves solving the SCC-DFTB equations subject to an orbital occupation constraint that forces the adoption of a non-aufbau electronic configuration consistent with the target excited state. This method is implemented for the lowest-lying singlet excited state of closedshell molecules in ${\\mathrm{DFTB}}+$ .95 The converged, non-aufbau SCC-DFTB determinant is a spin-contaminated or “mixed” spin state, but the excitation energy can be approximately spin-purified through the Ziegler sum rule, which extracts the energy of a pure singlet from the energies of the mixed state and the triplet ground state. \n\nA significant advantage of the ΔDFTB approach is that excitedstate gradients and hessians are quite straightforward to compute, both mathematically and in terms of computational cost, relative to linear response approaches. Benchmarks of ΔDFTB excitedstate geometries and Stokes shifts95 demonstrate the suitability of the method for simulating excited-state energetics and dynamics of common organic chromophores along the $S_{1}$ potential energy surface. \n\n# 4. Real-time propagation of electrons and Ehrenfest dynamics \n\nIt is often desirable to study time dependent properties outside the linear response regime, e.g., under strong external fields. The numerical propagation of the electronic states enables the simulation of such phenomena, and its coupling to the nuclear dynamics in a semi-classical level can be included to the lowest order within the Ehrenfest method. Purely electronic (frozen-nuclei) dynamics as well as Ehrenfest dynamics are included in ${\\mathrm{DFTB}}+$ . We solve the equation of motion of the reduced density matrix $\\rho$ given by the Liouville-von Neumann equation \n\n$$\n\\dot{\\rho}=-\\mathrm{i}\\Bigl({\\cal S}^{-1}H[\\rho]\\rho-\\rho H[\\rho]{\\cal S}^{-1}\\Bigr)-\\Bigl({\\cal S}^{-1}D\\rho+\\rho D^{\\dagger}{\\cal S}^{-1}\\Bigr),\n$$ \n\nwith $D$ being the non-adiabatic coupling matrix $D_{\\mu\\nu}=\\dot{\\bf R}_{B}\\cdot\\nabla_{B}S_{\\mu\\nu}$ and $\\dot{\\bf R}_{B}$ being the velocity of atom $B$ . The on-site blocks can be calculated taking the $\\mathbf{R}_{B}\\rightarrow0$ limit, although neglecting those does not introduce significant ch→anges to the dynamics.96 \n\nUnitary evolution of $\\rho$ with no change in its eigenvalues would require $D^{\\dagger}=-D_{:}$ , which is normally not the case. Therefore, nuclear dynamics can induce electronic transitions leading to thermalization.97 Unitary evolution is recovered when all nuclear velocities are equal (frozen-nuclei dynamics) and the second term in Eq. (24) vanishes. \n\nThe force in the Ehrenfest-dynamics can be expressed as96,98 \n\n$$\n\\begin{array}{r l r}{\\lefteqn{\\mathbf{F}_{A}=-\\mathrm{Tr}\\Bigg\\{\\rho\\Bigg(\\bigtriangledown_{A}H^{0}+\\bigtriangledown_{A}S\\sum_{B}\\gamma_{A B}\\Delta q_{B}+\\bigtriangledown_{A}S S^{-1}H+H S^{-1}\\nabla_{A}S\\Bigg)\\Bigg\\}}}\\\\ &{}&{\\quad-\\mathrm{~i~}\\mathrm{Tr}\\big\\{\\rho\\nabla_{A}S S^{-1}D+\\mathrm{h.c.}\\big\\}+\\mathrm{i}\\ \\sum_{\\mu\\nu}\\big\\{\\rho_{\\nu\\mu}\\big\\langle\\nabla_{A}\\phi_{\\mu}\\big|\\nabla_{B}\\phi_{\\nu}\\big\\rangle\\cdot\\dot{\\mathbf{R}}_{B}+\\mathrm{h.c.}\\big\\}}\\\\ &{}&{\\quad-\\Delta q_{A}\\sum_{B}\\nabla_{A}\\gamma_{A B}\\Delta q_{B}-\\bigtriangledown_{A}E_{r e p}-\\Delta q_{A}\\mathbf{E}(t),\\quad\\quad\\quad(25)}\\end{array}\n$$ \n\nwhere $\\mathbf{E}(t)$ is the external electric field. In the present implementation, the velocity dependent terms have been neglected, and they would vanish for a complete basis96 and are necessary for momentum, but not for energy conservation.98 When the system is driven externally by an electric field, a dipole coupling term is added in the time-dependent hamiltonian in Eq. (24). \n\nSome applications that have been enabled by the speedup over time-dependent DFT are the simulation of the plasmon-driven breathing-mode excitation in silver nanoparticles of $1{-}2\\ \\mathrm{nm}$ in diameter99 and the simulation of transient absorption pump–probe spectra in molecules.100,101 \n\nWhenever a time propagation approach is used for the calculation of absorption spectra in the linear regime, this method is equivalent to calculations using the Casida formalism and shares its strengths and limitations. Specific pitfalls of the time dependent approach come into play whenever simulating the response to intense external fields. In these cases, the poor description of highly lying excited states due to the use of a minimal basis set would likely be inaccurate if these states are populated during the dynamics. \n\n# 5. pp-RPA \n\nAn approximate particle–particle RPA scheme, the so-called pp-DFTB,88 is now implemented in ${\\mathrm{DFTB}}+$ . Particle–particle RPA, based on the pairing matrix fluctuation formalism, has been shown to be an efficient approach for the accurate description of double and charge-transfer (CT) excitations involving the highest occupied molecular orbital (HOMO) (see Ref. 102 for details). In Ref. 88, we compare against TD-LC-DFTB for CT excitation energies of donor– acceptor complexes. TD-LC-DFTB has the advantage that transitions do not necessarily have to involve the HOMO of the system. Alternatively, pp-DFTB does not require parameter tuning and is efficient for the lowest lying excitations. \n\nAlthough one of the strengths of the original pp-RPA formulation lies on the accurate description of Rydberg excitations, our approximate formalism based on DFTB fails to describe these kinds of transitions, as explained in Sec. II C 1. \n\n# 6. Coupled perturbed responses \n\n${\\mathrm{DFTB}}+$ supports several types of response calculations for second-order derivatives. The general form of the response evaluation is via standard perturbation theory, \n\n$$\nP_{i j}=\\Big\\langle c_{i}\\Big|H_{i j}^{(1)}-\\epsilon_{j}S_{i j}^{(1)}\\Big|c_{j}\\Big\\rangle,\n$$ \n\n$$\n\\epsilon_{i}^{(1)}=P_{i j}\\delta_{i j},\n$$ \n\n$$\nU_{i j}=P_{i j}/{\\left(\\epsilon_{j}-\\epsilon_{i}\\right)},\n$$ \n\n$$\nc_{i}^{(1)}=\\sum_{j}U_{i j}c_{j}^{(0)},\n$$ \n\n$$\n\\rho^{(1)}=\\sum_{i}n_{i}^{(1)}\\Big\\vert{c^{(0)}}\\Big\\rangle\\Big\\langle{c^{(0)}}\\Big\\vert+\\sum_{i}n_{i}^{(0)}\\Big(\\Big\\vert{c^{(1)}}\\Big\\rangle\\Big\\langle{c^{(0)}}\\Big\\vert+\\mathrm{~c.c.~}\\Big),\n$$ \n\nwhere the sums for the states that $U$ mixes together may be over all states or only the virtual space (parallel gauge) depending on application. $U$ is anti-symmetric (anti-Hermitian) or has no symmetry depending on whether the derivative of the overlap matrix is non-zero. \n\nIn the case of systems with degenerate levels, a unitary transformation, $Z,$ , that diagonalizes the block of $P$ associated with that manifold can be applied to the states; note that this sub-block is always symmetric (Hermitian), leading to orthogonality between states in the perturbation operation, \n\n$$\n\\tilde{P}_{i j}=z_{i k}P_{k l}z_{l i}^{\\dagger},\n$$ \n\n$$\n\\tilde{c}_{i}=c_{j}z_{j i}.\n$$ \n\nFor fractionally occupied levels, the derivatives of the occupations for $\\mathbf{q}=0$ perturbations (where the change in the Fermi energy should be included) are then evaluated.103 \n\nTime dependent perturbations at an energy of hω can be written as \n\n$$\nU_{i j}^{\\pm}={P_{i j}}/{\\left({{\\epsilon_{j}}-{\\epsilon_{i}}\\pm\\hbar\\omega+i\\eta}\\right)},\n$$ \n\n$$\nc_{i}^{(1)\\pm}=\\sum_{j}U_{i j}^{\\pm}c_{j}^{(0)},\n$$ \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\rho^{(1)}=\\sum_{i}n_{i}^{(1)}\\Big\\vert c^{(0)}\\Big\\rangle\\Big\\langle c^{(0)}\\Big\\vert+\\sum_{i}n_{i}^{(1)}\\Big\\vert c^{(0)}\\Big\\rangle\\Big\\langle c^{(0)}\\Big\\vert}}}\\\\ {{\\displaystyle{+\\sum_{\\pm}\\sum_{i}n_{i}^{(0)}\\Big(\\Big\\vert c^{(1)\\pm}\\Big\\rangle\\Big\\langle c^{(0)}\\Big\\rangle+\\mathrm{c.c.}\\Big)}.}}\\end{array}\n$$ \n\nHere, the small constant $\\eta$ prevents divergence exactly at excitation poles. \n\nDerivatives with respect to external electric fields and potentials are included (giving polarizabilities and dipole excitation energies), with respect to atom positions (at $\\mathbf{q}=0$ , providing Born charges and electronic derivatives for the hessian) and with respect to $k$ in periodic systems (effective masses and also the Berry connection via $\\left\\langle u\\right|{\\partial u}/{\\partial\\mathbf{k}}\\right\\rangle$ ). In the longer term, perturbation with respect to magnetic fields, boundary conditions (elastic tensors), and alternative approaches (Sternheimer equations for $\\mathbf{q}\\neq0$ , and also lower computationally scaling density matrix perturbation theory) are planned. \n\n# D. Non-equilibrium Green’s function based electron transport \n\nElectron transport in the steady-state regime is described in ${\\mathrm{DFTB}}+$ within a non-equilibrium Green’s function (NEGF) method,104,105 as implemented in the code-independent libNEGF106 library. The density matrix is evaluated in terms of the electron– electron correlation matrix G<,105 \n\n$$\n\\rho=\\frac{1}{2\\pi\\mathrm{i}}\\int_{-\\infty}^{+\\infty}G^{<}(E)\\mathrm{d}E.\n$$ \n\nOpen boundary conditions are included in terms of electron baths with an arbitrary spectrum and chemical potential, allowing for a seamless description of charge injection from electrodes with an applied bias. The density matrix is then used to evaluate a real-space electron density distribution, which is coupled self-consistently with a Poisson solver. We perform a full band integration of Eq. (36), utilizing a complex contour integral to reduce the number of integration points.104 This allows for an implicit description of dielectric properties, which is crucial for an accurate modeling of ultra-scaled electron devices.107,108 After self-consistency is achieved, the total current flowing in the system is calculated with the Landauer/Caroli formula for the non-interacting case or with the Meir–Wingreen formula for the interacting case.105 A detailed description of the numerical algorithms and self-consistent coupling is presented in Ref. 109. Here, we summarize the main features that might differentiate ${\\mathrm{DFTB}}+$ from other nano-device simulation packages: (i) support for $N\\geqslant1$ electrodes (enabling structures from surfaces and semi-infinite wires to multiple terminal geometries), (ii) $O(L)$ memory and time scaling (where $L$ is the system length) via a block-iterative algorithm, (iii) a real space Poisson solver with support for gates and dielectric regions, and (iv) evaluation of local currents. Being a parameterized tight binding method, its usage is bounded by the availability of good parameters for the system under investigation. \n\nCarbon-based materials and molecular junctions have been a typical use-case since the first integration of DFTB and NEGF.110–112 In Fig. 3, we show a non-SCC calculation example of transmission in linear response for a multi-terminal device. The simulated system is a cross-junction between two (10,10) Carbon nanotubes (CNTs). One CNT is tilted by ${60}^{\\circ}$ with respect to the second, and the transmission is calculated by displacing one CNT along the axis of the other. The transmission follows, as expected, a periodic pattern in accordance with the lattice repeat of $0.25~\\mathrm{{nm}}$ along the axis of the CNT. \n\nCurrently, we are working on extending transport functionality in ${\\mathrm{DFTB}}+$ with electron–phonon coupling ,113–116 electron–photon coupling, spin polarized transport, and phonon transport.117–120 \n\nOverall, DFTB-NEGF shares many similarities with DFT based implementations, and it also inherits some shortcomings the less experienced users should be aware of. For example, the open boundary treatment demands that external and non-equilibrium potentials are screened at the boundaries.105 Therefore, the simulated system should be large enough compared to the screening length. This condition is easily achieved with bulk metallic electrodes, but it can be difficult with low dimensional systems that exhibit poor screening. \n\nWhen this condition is not fulfilled, unphysical discontinuities in the potential may be obtained. In addition, compared to band structure calculations, NEGF tends to converge with more difficulty.121 Aside from these common challenges, it is important that for DFTB-NEGF calculations, any set of parameters should be evaluated by verifying at the least band structure properties in the energy range of interest. DFTB parameters fitted to reproduce total energies and forces might be excellent in those applications but lack the necessary accuracy in the band structure. Depending on the degree of accuracy required, an ad hoc fitting for transport calculations could also be necessary, for example, in the case of silicon.122 \n\n# E. Extended Lagrangian Born–Oppenheimer dynamics \n\nThe Extended Lagrangian Born–Oppenheimer molecular dynamics (XLBOMD) framework allows123,124 molecular dynamics on the Born–Oppenheimer surface with only one hamiltonian diagonalization per time step without the need for self-consistency cycles. The basic idea is based on a backward error analysis, i.e., instead of calculating approximate forces through an expensive non-linear iterative optimization procedure for an underlying exact potential energy surface, XL-BOMD calculates exact forces for an approximate “shadow” potential energy surface, ${\\cal U}({\\bf R},n)$ . This is approximated from a constrained minimization of a linearized Kohn–Sham energy functional.124,125 The functional is linearized around an approximate ground state density, $n$ . This density is included as a dynamical field variable driven by an extended harmonic oscillator centered on an approximate ground state, $q[n]$ , which is given by the minimization of the linearized Kohn–Sham functional. The harmonic well is defined in terms of a metric tensor, $\\boldsymbol{T}=\\boldsymbol{K}^{T}\\boldsymbol{K},$ where the kernel $K$ is assumed to be the inverse Jacobian of the residual function, $q[n]-n$ .124 The equations of motion are given by \n\n![](images/66beac2baea0fede9e4b40c89637bc408e6db2e618574cb5eb809f8587984ca6.jpg) \nFIG. 3. Transmission across two (10,10) CNTs as a function of the displacement of the top CNT along the axis of the bottom CNT. The two curves represent the transmission resolved between electrode 1 of the bottom CNT, and, respectively, electrodes 2 and 3 of the top CNT (as labeled in the inset). \n\n$$\nM_{I}\\ddot{\\mathbf{R}}_{I}=-\\frac{\\partial U(\\mathbf{R},n)}{\\partial R_{I}}\\bigg|_{n}\\quad\\mathrm{and}\\quad\\ddot{n}=-\\omega^{2}K(q[n]-n).\n$$ \n\nHere, $M_{I}$ are the atomic masses, $\\mathbf{R}_{I}$ are the nuclear coordinates, $\\omega$ is the frequency of the harmonic oscillator, $q[n]$ are the net Mulliken charge vectors (from an optimized linearized energy expression), and $n$ is the extended dynamical variable that is set to the optimized ground state net Mulliken charge vector in the initial time step. The details of the DFTB $^+$ implementation are given in Ref. 126. \n\nWe currently approximate the kernel by a scaled identity matrix, \n\n$$\nK=-c I,c\\in[0,1].\n$$ \n\nFor many problems, this is a sufficiently accurate approximation. However, for the most challenging problems including simulations of reactive chemical systems or metals, the scaled delta function is not a sufficiently stable approximation. Improved approximations have been developed124 and will be implemented in the ${\\mathrm{DFTB}}+$ program in the near future. \n\n# F. Objective geometries \n\nObjective structures127 (OSs) describe geometries consisting of a set of identical cells, where the corresponding atoms in different cells can be mapped onto each other by orthogonal transformation(s). Both finite and infinite OSs are possible. Currently, we describe structures127–129 possessing $C_{n}$ rotational symmetry and a $C_{m}\\otimes T$ screw axis, where $\\boldsymbol{n}\\in\\mathbb{N}^{*}$ and $m\\in\\mathbb{R}^{+}$ , \n\n$$\n{\\bf X}_{i,\\zeta,\\xi}=\\left(C_{n}\\right)^{\\xi}\\left(C_{m}\\right)^{\\zeta}{\\bf X}_{i}+T^{\\zeta},\\quad i\\in N,\n$$ \n\nwith $N$ atoms in the reference objective cell $(\\{{\\bf X}_{i}\\})$ and $\\{\\zeta,\\xi\\}\\in\\mathbb{N},$ where $-\\infty<\\zeta<\\infty$ and $0<\\xi99\\%$ within five cycles), but also achieves ${>}6\\mathrm{~V~}$ oxidative stability. The limited-excess Li|NMC (lithium nickel manganese cobalt oxide) full cells retain $90\\%$ capacity after 420 cycles with an average CE of $99.98\\%$ . Industrial anode-free $\\mathrm{Cu}|\\mathrm{NMC}811$ $\\mathrm{(LiNi_{0.8}M n_{0.1}C\\bar{o}_{0.1}O_{2})}$ pouch cells achieve ${\\sim}325\\mathrm{Whkg^{-1}}$ single-cell energy density, while $\\mathrm{Cu}|\\mathrm{NMC}532$ $\\mathrm{(LiNi_{0.5}M n_{0.3}C o_{0.2}O_{2})}$ ones show a record-high $80\\%$ capacity retention after 100 cycles. Furthermore, the $^{1\\mathrm{~M~}}$ LiFSI/FDMB electrolyte is less flammable than commercial electrolytes and can be synthesized at large scale with low cost. Our electrolyte formulation satisfies the stringent requirements for a practical Li metal battery outlined above. \n\n![](images/c2bf470f071f94543550a1a3b43733cfdc1d1b79cb5d98d14c0857e2009552bb.jpg) \nFig. 1 | Design concepts and electrochemical stability of electrolytes studied in this work. a–c, Design scheme and molecular structures of three liquids studied in this work: DME (a), DMB (b) and FDMB (c). d, Oxidation stability of three electrolytes in Li|Al half cells detected by LSV. e,f, Cycling (e) and Aurbach34 measurement $(\\pmb{\\uparrow})$ of Li metal CE in Li|Cu half cells using different electrolytes. For clarity, only the first 50 cycles of long-term cycling are shown here. \n\n# Molecular design \n\nTo target a desired electrolyte solvent molecule, the ether backbone is chosen here due to its ability to solvate $\\mathrm{Li^{+}}$ ions and benefit Li metal anodes18,23,24; however, ethers usually show poor oxidation stability7,18,23–25, which seriously affects the battery performance when high-voltage cathodes are applied. Therefore, we propose two critical design concepts to ensure the oxidative stability as well as the Li cycling efficiency. First, the alkyl chain in the middle of a commonly used ether electrolyte structure, 1,2-dimethoxylethane (DME, Fig. 1a), is lengthened to obtain 1,4-dimethoxylbutane (DMB, Fig. 1b). The motivation is to take advantage of the robustness of a longer alkyl chain26,27 while still maintaining the ability to solvate Li salt and conduct $\\mathrm{Li^{+}}$ ions. Second, $-\\mathrm{F}$ groups are introduced to further enlarge the oxidation window and Li metal compatibility28,29. Nonetheless, it is known that only when the $-\\mathrm{F}$ groups are distant from $-\\mathrm{O}-$ groups can the solvation ability of the ether be maintained11,18–22. Hence only the central part of the DMB backbone is replaced with $-\\mathrm{CF}_{2}-$ (Fig. 1c, orange part) while the $-\\mathrm{O}-$ is still linked to $\\mathrm{CH}_{3^{-}}$ and $\\mathrm{-CH}_{2}\\mathrm{-}$ (Fig. 1c, light-blue part). As a result, the obtained FDMB molecule (Fig. 1c) is expected to be stable to both Li metal anodes and high-voltage cathodes. FDMB is an organic molecule that has never been reported; however, the ease of one-step synthesis and low costs of reagents endow FDMB with promise for large-scale commercialization (Supplementary Table 1 and Syntheses). \n\nAfter the syntheses, the physicochemical properties of DMB and FDMB are determined: both show high boiling points ( $\\mathrm{i}35^{\\circ}\\mathrm{C}$ for DMB and $150^{\\circ}\\mathrm{C}$ for FDMB; Supplementary Fig. 1). These solvents are further made into electrolytes with 1 M LiFSI salt, and they all (in the order of 1 M LiFSI/DME, 1 M LiFSI/DMB and $1\\mathrm{M}$ LiFSI/FDMB hereafter) show high ion conductivities (21.9, 3.8, $3.5\\mathrm{mScm^{-1}},$ , high $\\mathrm{Li^{+}}$ transference numbers (0.39, 0.45, 0.48), low viscosities (0.58, 2.7, $5.0\\mathrm{cp}$ ), reasonable densities (0.966, 0.951, $1.25\\mathrm{g}\\mathrm{ml}^{-1},$ and low Li metal stripping/deposition overpotentials $(\\sim10$ , ${\\sim}20$ , $\\mathrm{\\sim}40\\mathrm{mV},$ (Supplementary Figs. 1–5). In particular, the 1 M LiFSI/FDMB is less flammable compared with the conventional carbonate electrolyte (Supplementary Video). Density functional theory (DFT) calculations show lower highest occupied molecular orbital levels for LiFSI/DMB and LiFSI/FDMB electrolytes compared with the DME case, corresponding semiquantitatively to higher theoretical oxidation voltages30 $(5.48\\mathrm{V}$ for LiFSI/DME, $5.52\\mathrm{V}$ for LiFSI/DMB and $6.14\\mathrm{V}$ for LiFSI/FDMB; Supplementary Fig. 6). \n\nTo experimentally verify the above-mentioned design principles, both high-voltage tolerance and Li metal CE are evaluated. Linear sweep voltammetry (LSV) measurements on Li|Al cells are conducted to determine the oxidation voltage (Fig. 1d). Unlike the low oxidation voltage of 1 M LiFSI/DME $(\\sim3.9\\mathrm{V})^{23}$ , 1 M LiFSI/DMB and 1 M LiFSI/FDMB show considerable high-voltage tolerance by giving oxidation voltages at ${\\sim}5.2\\mathrm{V}$ and ${>}6\\mathrm{V},$ respectively. The potentiostatic polarization tests provide more accurate information on oxidation voltage, which is ${<}4\\mathrm{V}$ for $1\\mathrm{M}$ LiFSI/DME, ${\\sim}4.8\\mathrm{V}$ for $1\\mathrm{~M~}$ LiFSI/DMB and ${>}5\\mathrm{V}$ for $^\\mathrm{~1~M~}$ LiFSI/FDMB (Supplementary Fig. 7). Scanning electron microscopy (SEM) images prove that Al foil remains intact in $1\\mathrm{M}$ LiFSI/FDMB whereas it is corroded and cracked in DME or DMB electrolyte when holding at $5.5\\mathrm{V}$ for three days (Supplementary Fig. 8). \n\nThe CEs of Li metal anodes are measured to confirm the cycling efficiency (Fig. 1e,f). 1 M LiFSI/DME is unstable with long-term cycling in Li|Cu half cells; however, the Li metal CE vastly improves when using 1 M LiFSI/DMB. Albeit still low for the initial few tens of cycles, the CE of 1 M LiFSI/DMB stabilizes at ${\\sim}98.8\\%$ with cycling (Supplementary Fig. 9). By contrast, $1\\mathrm{~M~}$ LiFSI/FDMB repeatably offers high first-cycle CE $(\\sim97.6\\%)$ and a rapid ramp-up to ${>}99\\%$ within only five cycles (Fig. 1e and Supplementary Fig. 10), which is the fastest activation observed so far13–15,17,22,31–33. After this five-cycle activation, the CE maintains an average of $99.3\\%$ for over 300 cycles (Supplementary Fig. 9). Aurbach CE tests34, which better evaluate the efficiency of Li cycling on a Li metal substrate, further prove the benefit of the FDMB design by showing a substantially improved CE $(99.52\\%)$ compared with both DMB $(97.7\\%)$ ) and DME $(98.4\\%)$ (Fig. 1f and Supplementary Fig. 11). This CE is one of the highest among the state-of-the-art electrolytes11,15,21,22. The slightly higher overpotential shown in the FDMB cells (Fig. 1f and Supplementary Figs. 3 and 4) may be attributed to the moderate ion conductivity and high SEI resistance, as well as the densely packed Li morphology (that is low surface area)35 in 1 M LiFSI/FDMB. \n\nOn the basis of the structure of FDMB, we further lengthen the carbon chain to synthesize fluorinated 1,5-dimethoxylpentane (FDMP, Syntheses) as the electrolyte solvent. As expected, high CE $(\\sim99\\%)$ , fast activation $\\prime C E>99\\%$ within two cycles) and oxidation stability $({>}6.5{\\mathrm{V}})$ are achieved with LiFSI/FDMP electrolytes (Supplementary Fig. 12), proving that our design principle can be expanded to a whole new family of solvent molecules. \n\n# Performance of practical Li metal batteries \n\nThe extraordinary Li metal performance along with high-voltage stability makes 1 M LiFSI/FDMB promising for practical Li metal batteries. Two types of Li metal battery are examined here: Li metal full cells with limited-excess Li, and anode-free pouch cells36–39 (Fig. 2a). Both are considered as promising constructions for high-energy-density Li metal batteries. Figure $2\\ensuremath{\\mathrm{b}},\\ensuremath{\\mathrm{c}}$ demonstrates Li metal battery performance where thin Li foils (50- and $20\\mathrm{-}\\upmu\\mathrm{m}$ thickness, 10- and $4\\mathrm{-mAh-cm}^{-2}$ capacity, respectively) are used as the limited-excess Li source. As shown in Fig. 2b, the cell capacity markedly decreases within 20 cycles when 1 M LiFSI/DME or the conventional electrolyte, 1 M $\\mathrm{LiPF}_{6}$ in ethylene carbonate/ethyl methyl carbonate $(\\mathrm{EC/EMC}=3/7)$ plus $2\\mathrm{-}\\mathrm{wt}\\%$ vinylene carbonate (VC), is used. By contrast, 1 M LiFSI/DMB prolongs the cycle life to $\\sim50$ cycles. Its high-voltage stability enables a better performance than DME, but the Li metal stability is still poor, showing notable capacity drop after 50 cycles. This can be further confirmed by its fast failure in $\\mathrm{Cu|NMC}$ cells (Supplementary Fig. 13). In contrast, 1 M LiFSI/FDMB enables a $90\\%$ capacity retention even after 420 cycles with a high average CE of ${>}99.98\\%$ . Moreover, this 1 M LiFSI/FDMB battery also survives several unexpected temperature fluctuations (Fig. $^{2\\mathrm{b},\\mathrm{c})}$ . This tolerance proves the robustness of $1\\mathrm{M}$ LiFSI/FDMB. When the negative/positive capacity ratio is further reduced to ${\\sim}2.5$ and the electrolyte/cathode ratio is lowered to ${\\sim}6\\mathrm{g}\\mathrm{Ah}^{-1}$ , 1 M LiFSI/FDMB can still maintain stable battery cycling for ${>}210$ cycles (Fig. 2c). In addition to NMC532 batteries, 1 M LiFSI/FDMB maintains outstanding long-term cyclability and rate capability under other conditions such as NMC811 or LFP $\\mathrm{(LiFePO_{4})}$ ) cathodes, different cathode areal capacities, various limited-excess Li amounts and lean electrolyte (Supplementary Figs. 14–16). \n\nFurthermore, aggressive anode-free pouch cells using 1 M LiFSI/FDMB are tested to realize high specific energy. Industrial dry pouch cells were purchased and directly tested after adding the electrolyte. The critical parameters such as total capacity $(200-$ $250\\mathrm{mAh})$ , areal loading $(\\sim3\\mathrm{-}4\\mathrm{mAhcm^{-2}})$ ), active material content $(\\sim96\\%)$ , electrolyte amount $({\\sim}2\\mathrm{g}\\mathrm{Ah}^{-1})$ , pressure $(\\sim250\\mathrm{{kPa})}$ and temperature (ambient, uncontrolled $18{-}25^{\\circ}\\mathrm{C})$ are all at practical levels9,10 (Supplementary Table 2). Figure 2d shows the performance of the anode-free pouch cells. The $\\mathrm{Cu}|\\mathrm{NMC}532$ cell maintains its $80\\%$ capacity for 100 cycles, while the Cu|NMC622 $\\mathrm{(LiNi_{0.6}M n_{0.2}C o_{0.2}O_{2})}$ and $\\mathrm{\\dot{Cu}|N M811}$ cells achieve 80 cycles and 70 cycles, respectively. It is worth noting that all cells were cycled with $100\\%$ depth of discharge, and this performance is one of the highest among the state-of-the-art anode-free cells (Supplementary Table 3). Additionally, the $\\mathrm{Cu|NMC811}$ cells exhibit a high specific energy of ${\\sim}325\\mathrm{Whkg^{-1}}$ , determined from the total weight of the pouch. We believe that the specific energy can be further increased if single cells with higher total capacity (for example Ah-level cylinder or pouch cells) are investigated. To fulfil special battery applications, the fast-discharge capability of the $\\mathrm{Cu}|\\mathrm{NMC}622$ pouch cell is examined, and $80\\%$ capacity is retained after ${\\sim}60$ cycles (Fig. 2e). More anode-free coin or pouch cells are cycled under different conditions and they all show superior cycle life (Supplementary Figs. 13 and 17–19). For example, the home-made Cu|NMC811 pouch cell realizes $80\\%$ retention for over 90 cycles. The anode-free pouch cells maintain shiny and silver-coloured Li metal deposition even after 100 cycles, while generating little gas (Supplementary Fig. 20). \n\n![](images/16e8285ce3ef7ad1b04ec8a08aaa622a3e34739d64f6f5fa34bb0fd01b024da8.jpg) \nFig. 2 | Li metal full battery performance. a, Configurations of practical Li metal batteries. b,c, Li metal full battery performance $50\\ –\\upmu\\mathrm{m}$ Li in b and $20\\AA\\cdot\\upmu\\mathrm{m}$ Li in c) at room temperature. Before cycling at $C/3$ three precycles at $C/10$ were conducted. The average CE was calculated from the fifth to the final cycle. Temperature fluctuation (TF) 1, overcooled to $\\sim18^{\\circ}C;$ TF2 and TF3, cooling system failed for ${2\\mathsf{d}},$ resulting in temperature spike from room temperature to ${>}40^{\\circ}\\mathsf{C},$ , then back to room temperature. ${\\mathsf{N/P}},$ negative/positive capacity ratio; E/C, electrolyte/ cathode ratio. d, Cycling performance of anode-free pouch cells at 0.2-C charge and 0.3-C discharge. The specific energy was calculated on the basis of the real mass of the whole pouch cell. e, Fast-discharge performance of the anode-free Cu|NMC622 pouch cell at 0.2-C charge and 2-C discharge. \n\n![](images/0a02f341361e202942cd177ae3f7f76b228111406b383fd7320f98a2ad0728b3.jpg) \nFig. 3 | Li metal morphology and SEI. a–d, Li morphology in anode-free Cu|NMC532 (2.7 mAh cm−2) coin cells using 1 M LiFSI/DME after 10 cycles (a), 1 M LiFSI/DMB after 10 cycles (b) and 1 M LiFSI/FDMB after 70 cycles (c,d). e,f, Cryo-TEM showing the SEIs of 1 M LiFSI/DME (e) and 1 M LiFSI/FDMB (f). Insets in e and f: the fast Fourier transforms of the SEIs. g,h, F 1s XPS depth profiles of Li metal surface in 1 M LiFSI/DME $\\mathbf{\\sigma}(\\mathbf{g})$ and 1 M LiFSI/FDMB (h). a.u., arbitrary units. \n\n# Li metal morphology and SEI structure \n\nThe Li metal deposition morphology and SEI nanostructure are carefully studied. When the 1 M LiFSI/DME or 1 M LiFSI/DMB is applied in $\\mathrm{Cu}|\\mathrm{NMC}532$ anode-free cells after 10 cycles, the Li structure on $\\mathrm{Cu}$ is dendritic and porous (Fig. 3a,b and Supplementary Figs. 21–23). By contrast, with the $1\\mathrm{~M~}$ LiFSI/FDMB electrolyte, the $2.7\\mathrm{\\mAh\\cm^{-2}}$ Li deposited on Cu $(\\sim14\\upmu\\mathrm{m}$ thick theoretically while ${\\sim}20\\upmu\\mathrm{m}$ observed) shows densely packed, flat, large grains even after 70 cycles (Fig. 3c,d and Supplementary Figs. 22 and 23). The morphology is highly beneficial to reducing the surface area for SEI growth as well as suppressing dead Li formation, leading to an ideal cycling performance18,20,37. The Li metal morphology of Li|NMC532 cells provides similar results as well (Supplementary Figs. 22 and 24). \n\nFurthermore, cryo-TEM40 is utilized to characterize the compact $\\mathrm{SEI^{41}}$ structure. In 1 M LiFSI/DME, the SEI layer is relatively thick $(\\sim10\\mathrm{nm})$ and non-uniform; however, an ultrathin $(\\sim6\\mathrm{-nm})$ and amorphous SEI is observed on Li when 1 M LiFSI/FDMB is applied (Fig. 3e,f). Instead of containing wrinkles or non-uniform domains as does the SEI observed in 1 M LiFSI/DME or other conventional electrolytes41–43, the SEI in $1\\mathrm{~M~}$ LiFSI/FDMB exhibits extraordinary uniformity according to the fast Fourier transform (Fig. 3e,f insets). This is also one of the thinnest compact SEIs observed to date11,40–43. This feature can effectively reduce the Li consumption from SEI formation during each cycle, thus improving the $\\mathrm{\\bar{C}E^{44}}$ . Cryogenic energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy shows that the SEI is rich in $\\operatorname{F},\\operatorname{S}$ and O, consistent with a heavily anion-derived $\\mathrm{SEI^{11}}$ (Supplementary Fig. 25). The F 1s spectra of $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) conducted for the Li metal surface further support this argument (Fig. 3g,h). The peaks assigned to LiFSI $\\left(\\sim688\\mathrm{eV}\\right)$ in 1 M LiFSI/FDMB have similar intensities throughout the depth profiling, indicating uniform SEI, while those in $1\\mathrm{M}$ LiFSI/DME show large variation with sputtering. The XPS spectra of other elements and during Li|Li cell cycling are consistent with this conclusion (Supplementary Figs. 26 and 27). Albeit thin and uniform for the compact SEI, ion-insulating species such as LiFSI, $-S\\mathrm{O}_{x}$ and $\\mathrm{Li}_{2}\\mathrm S_{x},$ which correlate with the high SEI resistance, are detected by XPS on the Li surface in 1 M LiFSI/FDMB (Supplementary Figs. 26 and 27). However, the SEI resistance in 1 M LiFSI/FDMB gradually stabilizes with resting while that in DME or DMB continuously grows (Supplementary Fig. 4). These results indicate that the SEI formed in 1 M LiFSI/FDMB not only is more anion derived but also self-passivates and provides better protection for Li metal anodes over time. \n\n![](images/3adcffbe89fa6a2a1659a211d580f9cbb1054d3aa23052466a154190ec3636ff.jpg) \nFig. 4 | Unique solvation structure in 1 M LiFSI/FDMB. a, Optical image of three liquids and their 1 M LiFSI electrolytes. b, Single crystal of LiTf/FDMB showing Li–F interactions. For clarity, only one LiTf and one FDMB are shown. c–e, ESP comparison of DME (c), DMB (d) and FDMB (e). f–h, Solvation structure of 1 M LiFSI/DME (f), 1 M LiFSI/DMB $\\mathbf{\\sigma}(\\mathbf{g})$ and 1 M LiFSI/FDMB ${\\bf\\Pi}({\\bf h})$ given by MD simulations and the corresponding average ratio of solvation bindings from $\\mathsf{F S l^{-}}$ anions to those from solvents in the solvation sheath. i, $^{19}\\mathsf{F}$ -NMR of LiFSI/FDMB electrolytes. j, Ultraviolet–visible spectra of 1 M LiFSI/FDMB. k, Logic flow of the structure–property relationship of 1 M LiFSI/FDMB: the Li–F interaction and high anion/solvent ratio in the ${\\mathsf{L i}}^{+}$ solvation sheath result in the unconventional colour and stabilize both the Li metal and the high-voltage cathode, further enabling Li metal full batteries. Colour scheme in b,f–h: dark grey, Li; pink, F; red, ${\\sf O};$ light blue, C; navy, N; yellow, S. For clarity, H atoms are not shown in b,f–h. \n\n# Li–F interaction and solvation structure \n\nThe electrolyte chemistry is studied to provide a better understanding of the performance and SEI formation. Unlike typical transparent and colourless electrolytes, 1 M LiFSI/FDMB is brownish in colour (Fig. 4a and Supplementary Fig. 28). The NMR study rules out the possibility of impurity or decomposition (Supplementary Fig. 29). In addition, when Li salts with other anions are dissolved in FDMB, they all show similar colours; \n\nnevertheless, when Na or K salts or ionic liquids are dissolved, only colourless solutions are obtained (Supplementary Fig. 30). These tests indicate that there are some unique $\\mathrm{Li^{+}}$ –solvent interactions in 1 M LiFSI/FDMB. \n\nTo check the coordination structure, a single crystal of lithium triflate (LiTf) cocrystallized with FDMB was obtained (Fig. 4b, Single crystals and Crystallographic Data 1). LiTf is chosen because it is structurally similar to LiFSI yet much easier to crystallize. \n\nThe crystal structure demonstrates that the Li–FFDMB $(2.935\\mathring\\mathrm{A})$ distance is similar to that of $_{\\mathrm{Li-O_{FDMB}}}$ $(2.023\\mathring\\mathrm{A})$ , thereby indicating a weak yet existing interaction between $\\mathrm{Li^{+}}$ ions and $\\mathrm{~F~}$ atoms on $\\mathrm{FDMB^{45}}$ . This $\\mathrm{Li-F}$ interaction can be rationalized by the electrostatic potential (ESP) calculations, which strongly correlate with non-covalent interactions46 (Fig. 4c–e). The isopotential surfaces of DME and DMB show similar trends, where the negative parts only concentrate on O atoms. Nevertheless, the isopotential surface of FDMB is completely different: the negative charge is almost equally located at both $\\mathrm{\\DeltaO_{FDMB}}$ and $\\mathrm{F_{FDMB}}$ atoms and contributes to the coordination with positive $\\mathrm{Li^{+}}$ . \n\nMolecular dynamics (MD) simulations are conducted to further corroborate the coordination structures (Fig. 4f–h). The DME molecule coordinates with the $\\mathrm{Li^{+}}$ ion like a ‘clamp’ with both its $-\\mathrm{O}-$ groups (Fig. 4f and Supplementary Fig. 31). Such a coordination geometry is well known in both liquid47 or polymer48 electrolyte systems and single crystals49. For DMB, the majority of $\\mathrm{Li^{+}}$ –solvent coordination structures are ‘linear’, where only one $-\\mathrm{O}-$ group on DMB is bound with one $\\mathrm{Li^{+}}$ ion (Fig. $4\\mathrm{g}$ and Crystallographic Data 2); however, the clamp coordination can still be found as a minority (Supplementary Fig. 32). Different from either DME or DMB, a five-member ring structure is observed in LiFSI/FDMB where the $\\mathrm{Li^{+}}$ ion is bound simultaneously with $|\\mathrm{O}_{\\mathrm{FDMB}}|$ and $\\mathrm{F_{FDMB}}$ atoms (Fig. 4h and Supplementary Fig. 33). This coordination matches well with the above-mentioned single-crystal result, and can be further cross-validated by simulated radial distribution functions (Supplementary Fig. 34), Fourier-transform infrared spectra (Supplementary Fig. 35) and $^{19}\\mathrm{F}$ -NMR (Fig. 4i). With the LiFSI concentration increasing, the $^{19}\\mathrm{F}$ peak on FDMB shows an upfield shift, indicating Li–F interaction18. The measured ultraviolet–visible spectrum of 1 M LiFSI/FDMB matches well with the calculated one, where the broad absorption in the visible range causes the brownish colour (Fig. 4j and Supplementary Fig. 36). \n\nFinally, the difference in coordination leads to non-negligible differences in the $\\mathrm{Li^{+}}$ solvation sheath. The average ratio of solvation bindings from FSI− anions to those from solvent (coordination provided by $\\mathrm{FSI^{-}}$ anions and solvent surrounding one $\\mathrm{Li^{+}}$ ion) is 2.31:1 for DME and 2.29:1 for DMB, respectively (Fig. 4f,g). Nevertheless, the FSI−/solvent ratio in the $\\mathrm{Li^{+}}$ solvation sheath is vastly increased, to 3.29:1, in 1 M LiFSI/FDMB (Fig. 4h), which suggests that FDMB performs poorly in dissociating ion pairs despite its contribution from Li–F interaction. The uncoordinated ether band (that is free solvent) dominates in the Fourier-transform infrared spectra of $1\\mathrm{M}$ LiFSI/FDMB (Supplementary Fig. 35), proving the weak solvation ability of FDMB. This argument is also consistent with the 7Li-NMR, where the peak of $1\\mathrm{M}$ LiFSI/FDMB is shifted upfield, which is an indication of better anion shielding effect (Supplementary Fig. 37). With more anions participating in the $\\mathrm{Li^{+}}$ solvation, 1 M LiFSI/FDMB is expected to mitigate harmful parasitic reactions on Li metal ano des11,18–22,50. This is consistent with the ultrathin SEI observed by cryo-TEM and the evenly distributed SEI composition with XPS depth profiling. Meanwhile, $\\mathrm{FSI^{-}}$ anions are tightly bound in such a solvation environment, so Al corrosion caused by $\\mathrm{FSI^{-}}$ can be suppressed19,51 (Supplementary Fig. 8), thus showing higher oxidation stability for 1 M LiFSI/FDMB. In summary, the Li–F interaction and special solvation structure in the 1 M LiFSI/FDMB electrolyte not only result in the unconventional electrolyte colour but also greatly stabilize both Li metal and cathode, further leading to excellent performance in Li metal full batteries (Fig. 4k). \n\n# Conclusions \n\nIn this work, a low-concentration, additive-free electrolyte is developed using a rationally designed solvent molecule, FDMB, solely as the solvent, and LiFSI as the single salt. A unique Li–F interaction is observed in 1 M LiFSI/FDMB. This coordination further leads to higher anion content in the $\\mathrm{Li^{+}}$ solvation sheath, endowing the electrolyte simultaneously with Li metal compatibility and high-voltage stability. Therefore, 1 M LiFSI/FDMB promises a high CE $(99.52\\%)$ with fast activation $(>99\\%$ within five cycles) in Li|Cu half cells, and ${>}6\\mathrm{~V~}$ oxidative stability. A thin SEI layer $(\\sim6\\mathrm{nm})$ is observed by cryo-TEM while favourable densely packed Li morphology is shown by SEM in $\\mathrm{Cu}|\\mathrm{NMC}$ cells after long-term cycling. Furthermore, over 420 cycles for a limited-excess Li|NMC full cell are achieved with an average CE of $99.98\\%$ , during which even several temperature fluctuations are overcome. Industrial hundreds-of-mAh $\\mathrm{Cu}|\\mathrm{NMC}532$ pouch cells are found to maintain $80\\%$ capacity retention for 100 cycles, while the $\\mathrm{Cu|NMC811}$ ones exhibit a high single-cell specific energy of ${\\sim}325\\mathrm{Whkg^{-1}}$ . The molecular design concept in this work provides a new direction for electrolyte engineering. \n\n# Methods \n\nMaterials. 2,2,3,3-Tetrafluoro-1,4-butanediol was purchased from SynQuest. 1,4-Butanediol, methyl iodide, sodium hydride ( $60\\%$ in mineral oil) and other general reagents were purchased from Sigma-Aldrich or Fisher Scientific. All chemicals were used without further purification. LiFSI was purchased from Oakwood and Fluolyte; LiTFSI was provided by Solvay; LiTf, VC and fluoroethylene carbonate were purchased from Sigma-Aldrich. DME $(99.5\\%$ over molecular sieves) was purchased from Acros. The $1\\mathrm{MLiPF}_{6}$ in EC/EMC (LP57), $1\\mathrm{MLiPF}_{6}$ in EC/DMC (dimethyl carbonate) (LP30) and $1\\mathrm{MLiPF}_{6}$ in EC/ DEC (diethyl carbonate) (LP40) were purchased from Gotion. The commercial Li battery separator Celgard 2325 $25\\upmu\\mathrm{m}$ thick, polypropylene/polyethylene/ polypropylene) was purchased from Celgard and used in all coin cells. Thick Li foil $(\\sim750\\upmu\\mathrm{m}$ thick) and Cu current collector ( $25\\upmu\\mathrm{m}$ thick) were purchased from Alfa Aesar. Thin Li foils $(\\sim50\\upmu\\mathrm{m}$ and ${\\sim}20\\upmu\\mathrm{m}$ thick) were provided by Hydro-Québec. Commercial LFP and NMC532 cathode sheets were purchased from MTI, and NMC811 cathode sheets were purchased from Targray $({\\sim}2{\\cdot}\\mathrm{mAh-cm^{-2}}$ areal capacity for all sheets). Industrial dry Cu|NMC532, Cu|NMC622 and Cu|NMC811 pouch cells were purchased from Hunan Li-Fun Technology. Other battery materials, such as 2032-type coin-cell cases, springs and spacers, were all purchased from MTI. \n\nSyntheses. DMB (Supplementary Figs. 40–42): To a round-bottom flask were added dry tetrahydrofuran (THF) and 1,4-butanediol. The solution was cooled to $0^{\\circ}\\mathrm{C}$ and then 2.5 equivalents of sodium hydride were added slowly. Bubbling was observed upon sodium hydride addition. Then, 2.5 equivalents of methyl iodide were added dropwise to the stirring suspension followed by heating to reflux overnight. The mixture was then filtered off and the solvents were removed under vacuum. The crude sample was vacuum distilled to yield the final product as a colourless liquid. The product was then filtered off through a $0.45\\mathrm{-}\\upmu\\mathrm{m}$ polytetrafluoroethylene filter and moved to an argon glovebox for further use. Yield: $76\\%$ . 1H-NMR ${\\bf\\dot{400M H z}}$ , $\\mathrm{d}^{6}$ -DMSO, $\\delta/\\mathrm{{ppm}}$ ): 3.30–3.27 (m, 4 H), 3.20 (s, 6 H), 1.51–1.48 $\\left(\\mathrm{m},4\\mathrm{H}\\right)$ ). $^{13}\\mathrm{C}$ -NMR ( ${\\bf\\Phi}_{100}\\bf{M H z}$ , $\\mathrm{d}^{6}$ -DMSO, $\\delta/{\\mathrm{ppm}}^{\\cdot}$ ): 72.36, 58.37, 26.50. \n\nFDMB (Supplementary Figs. 43–46): The same procedure as for DMB synthesis was used, except that 1,4-butanediol was changed to 2,2,3,3-tetrafluoro1,4-butanediol. Yield: $85\\%$ . $\\mathrm{^{1}H}$ -NMR ${\\bf\\dot{\\Psi}}_{400}\\bf{M H z}$ , $\\mathrm{{\\bfd}}^{8}$ -THF, $\\delta/\\mathrm{{ppm}}$ ): 3.85–3.76 (m, 4 H), 3.42 (s, 6 H). $^{13}\\mathrm{C}$ -NMR ${\\bf\\chi}_{\\mathrm{100MHz}}$ , $\\mathrm{d^{8}}$ -THF, $\\delta/\\mathrm{{ppm}}$ ): 119.09–114.06, 69.54–69.02, 59.48. 19F-NMR (376 MHz, $\\mathrm{d^{8}}$ -THF, $\\delta/\\mathrm{{ppm}}$ ): –123.50 to –123.58 (m, 4 F). FDMP (Supplementary Figs. 47–50): The same procedure as for DMB synthesis was used, except that 1,4-butanediol was changed to 2,2,3,3,4,4-hexafluoro1,5-pentanediol. Yield: $89\\%$ . 1H-NMR ( ${400}\\mathrm{MHz}$ , $\\mathbf{d}^{\\mathrm{{s}}}$ -THF, $\\delta/\\mathrm{{ppm}}$ ): 3.92–3.84 (m, 4 H), 3.43 (s, 6 H). $^{13}\\mathrm{C}$ -NMR $\\mathrm{\\Delta}_{\\mathrm{100MHz}}$ , $\\mathrm{d^{8}}$ -THF, $\\delta/{\\mathrm{ppm}}^{\\cdot}$ : 119.02–108.86, 69.31–68.79, 59.56. $^{19}\\mathrm{F}$ -NMR (376 MHz, $\\mathrm{d}^{\\mathrm{{s}}}$ -THF, $\\delta/\\mathrm{{ppm}}$ : –121.44 to –121.52 (m, 4 F), –127.66 (s, 2 F). \n\nElectrolytes. All the electrolytes were made and stored in argon-filled glovebox (Vigor, oxygen $<0.01$ ppm, water ${<}0.01\\mathrm{ppm}$ ). LiFSI $(1,122\\mathrm{mg})$ or LiTFSI $(1,722\\mathrm{mg})$ 1 was dissolved and stirred in $6\\mathrm{ml}$ DME, DMB or FDMB to obtain 1 M LiFSI/DME, 1 M LiFSI/DMB, 1 M LiFSI/FDMB, 1 M LiTFSI/DME, 1 M LiTFSI/DMB or 1 M LiTFSI/FDMB, respectively. The LP57 with $2\\mathrm{-wt\\%}$ VC and LP30 were used as control electrolytes. \n\nTheoretical calculations. DFT: The molecular geometries for the ground states were optimized by DFT at the ${\\mathrm{B}}3{\\mathrm{LYP}}/{6}{-}311\\mathrm{G}+(\\mathrm{d},\\mathrm{p})$ level, and then the energy, orbital levels and ESPs of molecules were evaluated at the $\\mathrm{B}3\\mathrm{LYP}/6{-}311\\mathrm{G}+(\\mathrm{d},\\mathrm{p})$ level as well. All the DFT calculations were carried out with the Gaussian 09 package. \n\nMD simulations: Molecules and ions were described by the optimized potentials for a liquid simulations all-atom (OPLS-AA)52 force field. Partial charges on solvent (that is DME, DMB and FDMB) atoms were computed by fitting the molecular ESP at the atomic centres with the Møller–Plesset second-order perturbation method with the correlation-consistent polarized valence cc-pVTZ(-f) basis set53. The simulation boxes were cubic with a side length of about $6\\mathrm{nm}$ and contained 1 M LiFSI solvated in different solvents. During simulations, the temperature was controlled at $300\\mathrm{K}$ using a Nosé–Hoover thermostat with a relaxation time of $0.2\\mathrm{ps}$ and the pressure was controlled at 1 bar using a Parrinello–Rahman barostat with a relaxation time of $2.0\\mathrm{ps}$ . All MD simulations were conducted with the GROMACS 2018 program54 for $50\\mathrm{ns}$ , and the last 20 ns were used for analysis. $\\mathrm{Li^{+}}$ ion solvation structures were analysed with a self-written script based on the MDAnalysis Python module55. \n\nMaterial characterizations. ${}^{1}\\mathrm{H}.$ -, $^{13}{\\mathrm{C}}-$ and $^{19}\\mathrm{F}$ -NMR spectra were recorded on a Varian Mercury 400-MHz NMR spectrometer and $^\\mathrm{7Li}$ -NMR spectra were recorded on a UI 300-MHz NMR spectrometer at room temperature. Fourier-transform infrared spectra were measured using a Nicolet iS50 with a diamond attenuated total reflectance attachment. An FEI Titan 80–300 environmental (scanning) transmission electron microscope and a Gatan 626 holder were used for cryo-TEM experiments. Cryo-TEM sample preparations prevent air reaction and beam damage, as described previously40,42,43. Low-dose electron exposure procedures were employed using a Gatan OneView complementary metal–oxide–semiconductor camera, with $1,000\\mathrm{-e^{-}}\\mathrm{-}\\mathrm{\\AA}^{2}$ total dosage. The transmission electron microscope is equipped with an aberration corrector in the image-forming lens, which was tuned before imaging. An FEI Magellan 400 XHR scanning electron microscope was used for SEM and energy-dispersive X-ray spectroscopy characterizations. A Bruker D8 Venture X-ray diffractometer was used for single-crystal data collection. For XPS measurements, each Li foil (soaked in the electrolyte for 4 d or after Li|Li cell cycling) was washed with the corresponding solvent for 30 s to remove the remaining electrolyte. The samples were transferred and sealed into the XPS holder in the argon-filled glovebox. The XPS profiles were collected with a PHI VersaProbe 1 scanning XPS microprobe. Viscosity measurements were carried out using an Ares G2 rheometer (TA Instruments) with an advanced Peltier system at $25^{\\circ}\\mathrm{C}.$ . A Karl-Fisher titrator was used to determine the water content in electrolytes. Ultraviolet–visible spectra were collected using an Agilent Cary 6000i ultraviolet–visible–near-infrared instrument. \n\nElectrochemical measurements. All battery components used in this work were commercially available and all electrochemical tests were carried out in a Swagelok-cell, 2032-type coin-cell or pouch-cell configuration. All cells were fabricated in an argon-filled glovebox, and one layer of Celgard 2325 was used as a separator. Electrochemical impedance spectroscopy, $\\mathrm{Li^{+}}$ transference number (LTN), LSV and pouch-cell cycling were carried out on a Biologic VMP3 system. The cycling tests for coin cells were carried out on an Arbin system or Land instrument. The electrochemical impedance spectroscopy measurements were taken over a frequency range of 7 MHz to $100\\mathrm{mHz}$ . For the LTN measurements, $10\\mathrm{-mV}$ constant voltage bias was applied to Li|Li cells. The anodic constant-voltage tests were carried out over a voltage range of $-0.1$ to 2 V for three cycles in Li|Cu cells, while the cathodic LSV tests were over a voltage range of 2.5 to 7 V. For $_\\mathrm{Li|Cu}$ half-cell CE cycling tests, ten precycles between 0 and 1 V were initialized to clean the Cu electrode surface, and then cycling was done by depositing 1 (or $0.5)\\mathrm{mAhcm}^{-2}$ of Li onto the Cu electrode followed by stripping to 1 V. The average CE is calculated by dividing the total stripping capacity by the total deposition capacity after the formation cycle. For the Aurbach CE test34, a standard protocol was followed: (1) perform one initial formation cycle with Li deposition of $5\\mathrm{mAhcm}^{-2}$ on Cu under $0.5{\\mathrm{-}}\\operatorname*{mA-}{\\mathrm{cm}}^{-2}$ current density and stripping to 1 V; (2) deposit 5-mAh- $\\cdot\\mathrm{cm}^{-2}$ Li on Cu under $0.5\\mathrm{mAcm^{-2}}$ as a Li reservoir; (3) repeatedly strip/deposit Li of $1\\mathrm{mAhcm}^{-2}$ under $0.5\\mathrm{mAcm^{-2}}$ for 10 cycles; (4) strip all Li to 1 V. The Li|NMC and $\\mathrm{Cu}|\\mathrm{NMC}$ full cells were cycled with the following method (unless specially listed): after the first two activation cycles at $C/10$ charge/ discharge (or $0.1\\ –C$ charge 0.3-C discharge for anode-free pouch cells), the cells were cycled at different rates. Then a constant-current–constant-voltage protocol was used for cycling: cells were charged to top voltage and then held at that voltage until the current dropped below $C/20$ . The NMC532 coin cells were cycled between 2.7 and $4.2\\mathrm{V}$ or 3.0 and $4.2\\mathrm{V};$ ; the NMC532 pouch cells were cycled between 2.7 and $4.2\\mathrm{V}$ or 2.7 and $4.3\\mathrm{V};$ the NMC622 pouch cells were cycled between 2.7 and $4.4\\mathrm{V};$ the NMC811 coin cells were cycled between 2.8 and 4.4 V; the NMC811 pouch cells were cycled between 2.8 and $4.4\\mathrm{V}$ or 3.0 and 4.4 V. For anode-free pouch cells, the current was tuned to guarantee the cycling time. All cells were cycled under ambient conditions without temperature control. \n\nSingle crystals. LiTf/FDMB (Crystallographic Data 1 and Supplementary Fig. 51): Anhydrous LiTf was predried at $110^{\\circ}\\mathrm{C}$ in an argon-filled glovebox for 3 d. LiTf $(0.3\\mathrm{mg})$ was added to $200\\upmu\\mathrm{l}$ FDMB and the suspension was sonicated until a coloured solution formed. The solution was left undisturbed and open capped in the glovebox for over a week to obtain coloured flake-like crystals. A suitable crystal was selected and mounted on a Bruker D8 Venture diffractometer. The crystal was kept at $100\\mathrm{K}$ during data collection. Using Olex2 (ref. $^{56})$ , the structure was solved with the SIR2014 (ref. 57) structure solution program using Direct Methods and refined with the SHELXL58,59 refinement package using least-squares minimization. Crystallographic data of LiTf/FDMB have been submitted to the Cambridge Crystallographic Database (reference number CCDC 1935863). \n\nLiTf/DMB (Crystallographic Data 2 and Supplementary Fig. 52): The same crystal growth method as for LiTf/FDMB was used except that 0.1 mg LiTf was dissolved in $200\\upmu\\mathrm{l}$ DMB. The obtained crystals were colourless and needle-like. Crystallographic data of LiTf/DMB have been submitted to the Cambridge Crystallographic Database (reference number CCDC 1945342). Crystallographic data are available free of charge at http://www.ccdc.cam.ac.uk/data_request/cif. \n\n# Data availability \n\nAll relevant data are included in the paper and its Supplementary Information. \n\nCode availability \nThe Python script for analysing the $\\mathrm{Li^{+}}$ solvation structure is available at https:// github.com/xianshine/LiSolvationStructure.git. \n\nReceived: 12 December 2019; Accepted: 14 May 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Press release: The Nobel Prize in Chemistry 2019. The Nobel Prize https://www.nobelprize.org/prizes/chemistry/2019/press-release/ (2019). \n2.\t Battery revolution to evolution. Nat. Energy 4, 893 (2019). \n3.\t Janek, J. & Zeier, W. G. A solid future for battery development. Nat. Energy 1, \n16141 (2016). \n4.\t Lin, D., Liu, Y. & Cui, Y. Reviving the lithium metal anode for high-energy batteries. Nat. Nanotechnol. 12, 194–206 (2017). \n5.\t Albertus, P., Babinec, S., Litzelman, S. & Newman, A. Status and challenges in enabling the lithium metal electrode for high-energy and low-cost rechargeable batteries. Nat. Energy 3, 16–21 (2018). \n6.\t Choi, J. W. & Aurbach, D. Promise and reality of post-lithium-ion batteries with high energy densities. Nat. Rev. Mater. 1, 16013 (2016). \n7.\t Xu, K. Electrolytes and interphases in Li-ion batteries and beyond. Chem. Rev. 114, 11503–11618 (2014). \n8.\t Liu, B., Zhang, J. & Xu, W. Advancing lithium metal batteries. Joule 2, \n833–845 (2018). \n9.\t Liu, J. et al. Pathways for practical high-energy long-cycling lithium metal batteries. Nat. Energy 4, 180–186 (2019). \n10.\t Cao, Y., Li, M., Lu, J., Liu, J. & Amine, K. Bridging the academic and industrial metrics for next-generation practical batteries. Nat. Nanotechnol. \n14, 200–207 (2019). \n11.\tCao, X. et al. Monolithic solid–electrolyte interphases formed in fluorinated orthoformate-based electrolytes minimize Li depletion and pulverization. Nat. Energy 4, 796–805 (2019). \n12.\tLiu, Y. et al. Solubility-mediated sustained release enabling nitrate additive in carbonate electrolytes for stable lithium metal anode. Nat. Commun. 9, 3656 (2018). \n13.\tFan, X. et al. Non-flammable electrolyte enables Li-metal batteries with aggressive cathode chemistries. Nat. Nanotechnol. 13, 715–722 (2018). \n14.\tFan, X. et al. All-temperature batteries enabled by fluorinated electrolytes with non-polar solvents. Nat. Energy 4, 882–890 (2019). \n15.\tYang, Y. et al. High-efficiency lithium-metal anode enabled by liquefied gas electrolytes. Joule 3, 1986–2000 (2019). \n16.\tYamada, Y., Wang, J., Ko, S., Watanabe, E. & Yamada, A. Advances and issues in developing salt-concentrated battery electrolytes. Nat. Energy 4, \n269–280 (2019). \n17.\tFan, X. et al. Highly fluorinated interphases enable high-voltage Li-metal batteries. Chem 4, 174–185 (2018). \n18.\tRen, X. et al. Enabling high-voltage lithium-metal batteries under practical conditions. Joule 3, 1662–1676 (2019). \n19.\tRen, X. et al. Localized high-concentration sulfone electrolytes for high-efficiency lithium-metal batteries. Chem 4, 1877–1892 (2018). \n20.\tNiu, C. et al. High-energy lithium metal pouch cells with limited anode swelling and long stable cycles. Nat. Energy 4, 551–559 (2019). \n21.\tChen, S. et al. High-efficiency lithium metal batteries with fire-retardant electrolytes. Joule 2, 1548–1558 (2018). \n22.\tChen, S. et al. High-voltage lithium-metal batteries enabled by localized high-concentration electrolytes. Adv. Mater. 30, 1706102 (2018). \n23.\t Qian, J. et al. High rate and stable cycling of lithium metal anode. Nat. Commun. 6, 6362 (2015). \n24.\tAmanchukwu, C. V. et al. A new class of ionically conducting fluorinated ether electrolytes with high electrochemical stability. J. Am. Chem. Soc. 142, \n7393–7403 (2020). \n25.\tJiao, S. et al. Stable cycling of high-voltage lithium metal batteries in ether electrolytes. Nat. Energy 3, 739–746 (2018). \n26.\t Li, N., Leng, Y., Hickner, M. A. & Wang, C. Y. Highly stable, anion conductive, comb-shaped copolymers for alkaline fuel cells. J. Am. Chem. Soc. \n135, 10124–10133 (2013). \n27.\tZhang, X., Sheng, L., Higashihara, T. & Ueda, M. Polymer electrolyte membranes based on poly(m-phenylene)s with sulfonic acid via long alkyl side chains. Polym. Chem. 4, 1235–1242 (2013). \n28.\tLi, T., Zhang, X.-Q., Shi, P. & Zhang, Q. Fluorinated solid-electrolyte interphase in high-voltage lithium metal batteries. Joule 3, 2647–2661 (2019). \n29.\tAspern, N., Röschenthaler, G.-V., Winter, M. & Cekic‐Laskovic, I. Fluorine and lithium: ideal partners for high‐performance rechargeable battery electrolytes. Angew. Chem. Int. Ed. 58, 15978–16000 (2019). \n30.\tZhang, Z. et al. Fluorinated electrolytes for 5 V lithium-ion battery chemistry. Energy Environ. Sci. 6, 1806–1810 (2013). \n31.\tZeng, Z. et al. Non-flammable electrolytes with high salt-to-solvent ratios for Li-ion and Li-metal batteries. Nat. Energy 3, 674–681 (2018). \n32.\tSuo, L. et al. Fluorine-donating electrolytes enable highly reversible 5-V-class Li metal batteries. Proc. Natl Acad. Sci. USA 115, 1156–1161 (2018). \n33.\tXue, W. et al. FSI-inspired solvent and “full fluorosulfonyl” electrolyte for 4 V class lithium-metal batteries. Energy Environ. Sci. 13, 212–220 (2020). \n34.\tAdams, B. D., Zheng, J., Ren, X., Xu, W. & Zhang, J.-G. Accurate determination of Coulombic efficiency for lithium metal anodes and lithium metal batteries. Adv. Energy Mater. 8, 1702097 (2018). \n35.\tLiu, Y. et al. An artificial solid electrolyte interphase with high Li-ion conductivity, mechanical strength, and flexibility for stable lithium metal anodes. Adv. Mater. 29, 1605531 (2017). \n36.\tZhang, J. G. Anode-less. Nat. Energy 4, 637–638 (2019). \n37.\tWeber, R. et al. Long cycle life and dendrite-free lithium morphology in anode-free lithium pouch cells enabled by a dual-salt liquid electrolyte. Nat. Energy 4, 683–689 (2019). \n38.\tGenovese, M. et al. Hot formation for improved low temperature cycling of anode-free lithium metal batteries. J. Electrochem. Soc. 166, A3342–A3347 (2019). \n39.\tNanda, S., Gupta, A. & Manthiram, A. Anode‐free full cells: a pathway to high‐energy density lithium‐metal batteries. Adv. Energy Mater. 2000804 (2020). https://doi.org/10.1002/aenm.202000804 \n40.\tLi, Y. et al. Atomic structure of sensitive battery materials and interfaces revealed by cryo–electron microscopy. Science 358, 506–510 (2017). \n41.\tHuang, W., Wang, H., Boyle, D. T., Li, Y. & Cui, Y. Resolving nanoscopic and mesoscopic heterogeneity of fluorinated species in battery solid-electrolyte interphases by cryogenic electron microscopy. ACS Energy Lett. 5, 1128–1135 (2020). \n42.\tWang, J. et al. Improving cyclability of Li metal batteries at elevated temperatures and its origin revealed by cryo-electron microscopy. Nat. Energy \n4, 664–670 (2019). \n43.\tLi, Y. et al. Correlating structure and function of battery interphases at atomic resolution using cryoelectron microscopy. Joule 2, 2167–2177 (2018). \n44.\t Fang, C. et al. Quantifying inactive lithium in lithium metal batteries. Nature \n572, 511–515 (2019). \n45.\tYu, Z. et al. A dynamic, electrolyte-blocking, and single-ion-conductive network for stable lithium-metal anodes. Joule 3, 2761–2776 (2019). \n46.\tDou, J.-H. et al. Organic semiconducting alloys with tunable energy levels. J. Am. Chem. Soc. 141, 6561–6568 (2019). \n47.\tRen, X. et al. High-concentration ether electrolytes for stable high-voltage lithium metal batteries. ACS Energy Lett. 4, 896–902 (2019). \n48.\tMackanic, D. G. et al. Crosslinked poly(tetrahydrofuran) as a loosely coordinating polymer electrolyte. Adv. Energy Mater. 8, 1800703 (2018). \n49.\tHenderson, W. A., Brooks, N. R. & Smyrl, W. H. Polymeric $\\left[\\mathrm{Li}(\\mathrm{NO}_{3})\\right.$ (monoglyme) $]_{n}$ . Acta Crystallogr. E 58, $\\mathrm{m}500{\\mathrm{-}}\\mathrm{m}501$ (2002). \n50.\t Wang, Z. et al. An anion‐tuned solid electrolyte interphase with fast ion transfer kinetics for stable lithium anodes. Adv. Energy Mater. 10, 1903843 (2020). \n51.\t Zhang, C. et al. Chelate effects in glyme/lithium bis(trifluoromethanesulfonyl) amide solvate ionic liquids, part 2: Importance of solvate-structure stability for electrolytes of lithium batteries. J. Phys. Chem. C 118, 17362–17373 (2014). \n52.\tJorgensen, W. L., Maxwell, D. S. & Tirado-Rives, J. Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J. Am. Chem. Soc. 118, 11225–11236 (1996). \n53.\tSambasivarao, S. V. & Acevedo, O. Development of OPLS-AA force field parameters for 68 unique ionic liquids. J. Chem. Theory Comput. 5, 1038–1050 (2009). \n54.\tAbraham, M. J. et al. GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25 (2015). \n55.\tMichaud-Agrawal, N., Denning, E. J., Woolf, T. B. & Beckstein, O. MDAnalysis: a toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 32, 2319–2327 (2011). \n56.\t Dolomanov, O. V., Bourhis, L. J., Gildea, R. J., Howard, J. A. K. & Puschmann, H. OLEX2: a complete structure solution, refinement and analysis program. J. Appl. Crystallogr. 42, 339–341 (2009). \n57.\tBurla, M. C. et al. Crystal structure determination and refinement via SIR2014. J. Appl. Crystallogr. 48, 306–309 (2015). \n58.\tSheldrick, G. M. SHELXT—integrated space-group and crystal-structure determination. Acta Crystallogr. A 71, 3–8 (2015). \n59.\tSheldrick, G. M. Crystal structure refinement with SHELXL. Acta Crystallogr. C 71, 3–8 (2015). \n\n# Acknowledgements \n\nThis work is supported by the US Department of Energy, under the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies, Battery Materials Research (BMR) Program, and by the Battery 500 Consortium. Part of this work was performed at the Stanford Nano Shared Facilities, supported by the National Science Foundation under award ECCS-1542152. Z.Y. thanks X. Xu from Hunan Li-Fun Technology for fabricating pouch cells, Beijing Golden Feather New Energy Technology for providing LiFSI and Z. Yao for discussion on the DFT calculations. All authors thank K. Zaghib from Hydro-Québec for preparing and providing the thin Li metal foils. D.G.M. acknowledges support by the National Science Foundation Graduate Research Fellowship Program under grant no. (DGE‐114747). C.V.A. acknowledges the TomKat Center Postdoctoral Fellowship in Sustainable Energy for funding support. \n\n# Author contributions \n\nZ.Y., H.W., Y.C. and Z.B. conceived the idea. Z.Y. and H.W. designed the experiments. Y.C. and Z.B. directed the project. Z.Y. performed the syntheses, material characterizations, DFT calculations, electrochemical measurements and coin-cell tests. H.W. performed the XPS measurements, pouch-cell fabrication and tests, and coin-cell tests. X.K. and J.Q. conducted the MD simulations and rationales. William Huang performed the cryo-TEM and cryogenic energy-dispersive X-ray spectroscopy measurements. Y.T., William Huang and E.G.L. performed the SEM experiments. K.W. and X.W. helped with the single-crystal measurement and structure refinement. D.G.M. and C.V.A. collected the 7Li-NMR spectra. Wenxiao Huang helped with the pouch-cell fabrication and tests. S.C. measured the viscosities. Y.Z. collected the ultraviolet–visible spectra. S.T.H. measured the water contents. Y.M. helped with the syntheses. All authors discussed and analysed the data. Z.Y., H.W., Y.C. and Z.B. wrote and revised the manuscript. \n\n# Competing interests \n\nThis work has been filed as US Provisional Patent Application No. 62/928,638. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-020-0634-5. \n\nCorrespondence and requests for materials should be addressed to Y.C. or Z.B. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. $\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 " + }, + { + "id": "10.1002_adfm.202001263", + "DOI": "10.1002/adfm.202001263", + "DOI Link": "http://dx.doi.org/10.1002/adfm.202001263", + "Relative Dir Path": "mds/10.1002_adfm.202001263", + "Article Title": "Designing Dendrite-Free Zinc Anodes for Advanced Aqueous Zinc Batteries", + "Authors": "Hao, JN; Li, XL; Zhang, SL; Yang, FH; Zeng, XH; Zhang, S; Bo, GY; Wang, CS; Guo, ZP", + "Source Title": "ADVANCED FUNCTIONAL MATERIALS", + "Abstract": "Zn metal has been regarded as the most promising anode for aqueous batteries due to its high capacity, low cost, and environmental benignity. Zn anode still suffers, however, from low Coulombic efficiency due to the side reactions and dendrite growth in slightly acidic electrolytes. Here, the Zn plating/stripping mechanism is thoroughly investigated in 1 m ZnSO4 electrolyte, demonstrating that the poor performance of Zn metal in mild electrolyte should be ascribed to the formation of a porous by-product (Zn4SO4(OH)(6)center dot xH(2)O) layer and serious dendrite growth. To suppress the side reactions and dendrite growth, a highly viscoelastic polyvinyl butyral film, functioning as an artificial solid/electrolyte interphase (SEI), is homogeneously deposited on the Zn surface via a simple spin-coating strategy. This dense artificial SEI film not only effectively blocks water from the Zn surface but also guides the uniform stripping/plating of Zn ions underneath the film due to its good adhesion, hydrophilicity, ionic conductivity, and mechanical strength. Consequently, this side-reaction-free and dendrite-free Zn electrode exhibits high cycling stability and enhanced Coulombic efficiency, which also contributes to enhancement of the full-cell performance when it is coupled with MnO2 and LiFePO4 cathodes.", + "Times Cited, WoS Core": 756, + "Times Cited, All Databases": 791, + "Publication Year": 2020, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000537764400001", + "Markdown": "# Designing Dendrite-Free Zinc Anodes for Advanced Aqueous Zinc Batteries \n\nJunnan Hao, Xiaolong Li, Shilin Zhang, Fuhua Yang, Xiaohui Zeng, Shuai Zhang, Guyue Bo, Chunsheng Wang,\\* and Zaiping Guo\\* \n\nZn metal has been regarded as the most promising anode for aqueous batteries due to its high capacity, low cost, and environmental benignity. Zn anode still suffers, however, from low Coulombic efficiency due to the side reactions and dendrite growth in slightly acidic electrolytes. Here, the Zn plating/stripping mechanism is thoroughly investigated in ${\\mathsf{I}}{\\mathsf{M}}{\\mathsf{Z}}{\\mathsf{n}}{\\mathsf{S}}{\\mathsf{O}}_{4}$ electrolyte, demonstrating that the poor performance of Zn metal in mild electrolyte should be ascribed to the formation of a porous by-product $(\\mathsf{Z n}_{4}\\mathsf{S O}_{4}(\\mathsf{O H})_{6}{\\cdot}x\\mathsf{H}_{2}\\mathsf{O})$ layer and serious dendrite growth. To suppress the side reactions and dendrite growth, a highly viscoelastic polyvinyl butyral film, functioning as an artificial solid/electrolyte interphase (SEI), is homogeneously deposited on the Zn surface via a simple spin-coating strategy. This dense artificial SEI film not only effectively blocks water from the Zn surface but also guides the uniform stripping/plating of Zn ions underneath the film due to its good adhesion, hydrophilicity, ionic conductivity, and mechanical strength. Consequently, this side-reaction-free and dendrite-free Zn electrode exhibits high cycling stability and enhanced Coulombic efficiency, which also contributes to enhancement of the full-cell performance when it is coupled with $\\ensuremath{\\mathsf{M n O}}_{2}$ and LiFeP $\\infty_{4}$ cathodes. \n\n# 1. Introduction \n\nAqueous rechargeable batteries, as highly promising candidates for grid-scale energy storage, have recently received great attention due to their advantages of high safety, high ionic conductivity, low cost, and environmental benignity.[1] Among these aqueous batteries, Zn metal batteries have been intensively investigated, because the $Z\\mathrm{n}$ anode has the advantages of high theoretical capacity (gravimetric capacity of $820~\\mathrm{mA}$ h $\\boldsymbol{\\mathrm{g}}^{-1}$ and volumetric capacity of $5855~\\mathrm{mA}\\mathrm{~h~cm}^{-3}$ ), a low reduction potential $(-0.76~\\mathrm{V}$ vs Standard Hydrogen Electrode (SHE)), and high overpotential for hydrogen evolution in aqueous media.[2] \n\nAlthough aqueous Zn batteries, including the Zn–air battery and the $\\mathsf{Z n}{\\cdot}\\mathsf{M n}{\\mathsf{O}}_{2}$ battery, have achieved great progress in recent years,[3] state-of-the-art $Z\\mathrm{n}$ batteries with alkaline electrolyte still suffer from several critical challenges, such as Zn dissolution, shape change, passivation, dendrite growth, etc.[4] Zn electrode issues are mitigated to some extent in mild electrolyte, but it is well known that dendrite growth still exists in mild Zn systems.[5] Although the dendrite growth does not result in the same hazardous situations as in organic lithium-ion or sodium-ion batteries, such as fire or even explosion,[6] it causes unceasing water/electrolyte decomposition and further degrades the lifespan of the battery.[7] To enhance the reversibility of $Z\\mathrm{n}$ anode in neutral electrolyte, great efforts have recently been spent on the inhibition of Zn dendrite growth, including the introduction of different electrolyte additives,[8] designing porous Zn metal architectures,[9] guiding Zn backside plating,[10] employing high concentration electrolytes,[11] and building artificial inorganic layers.[7,12] Yet, the side reactions between Zn metal and mild electrolyte have often been neglected. These reactions between $Z\\mathrm{n}$ metal and electrolyte not only dramatically reduce the Coulombic efficiency (CE) of the $Z\\mathrm{n}$ battery, but also constantly  consume the Zn anode, which leads to a limited battery lifespan. Thus, achieving an in-depth understanding of the side reactions in slightly acidic electrolyte as well as their byproducts is highly desirable for further improving the CE and cycling stability of Zn batteries. \n\nIn this work, the stability has been studied of pure Zn metal electrode in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte. The results reveal that $Z\\mathrm{n}$ electrode is highly unstable in slightly acidic electrolyte because it generates a loose $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}{x}\\mathrm{H}_{2}\\mathrm{O}$ layer. Unfortunately, this loose layer cannot effectively block the electrolyte from coming into contact with the $Z\\mathrm{n}$ surface, so it cannot terminate the corrosion reactions by passivating the fresh Zn. In addition, $Z\\mathrm{n}$ plating in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte was studied in a transparent cell, demonstrating that $Z\\mathrm{n}$ dendrites with a palmleaf-like morphology grew on the surface of the $Z\\mathrm{n}$ anode. After ${\\approx}260$ and ${\\approx}750\\mathrm{h}$ of plating/stripping at $0.5\\mathrm{\\mA\\cm^{-1}}$ , the separators in the coin cells, with thicknesses of 0.24 and $0.96~\\mathrm{mm}$ , were pierced by $Z\\mathrm{n}$ dendrites, leading to battery failure. To effectively inhibit the side reactions and $Z\\mathrm{n}$ dendrite growth, a polymer film of poly(vinyl butyral) (PVB) as an artificial solid/ electrolyte interphase (SEI) layer was deposited on the surface of the $Z\\mathrm{n}$ anode via a facile spin-coating strategy. The PVB layer can effectively remove the $Z\\mathrm{n}$ solvated water during $Z\\mathrm{n}$ plating/ stripping, significantly suppressing the side reactions and enhancing the CE. Moreover, this polymer film also exhibits strong adhesion to the $Z\\mathrm{n}$ surface with excellent flexibility and encouraging hydrophilicity, rendering the electrolyte distribution on the $Z\\mathrm{n}$ surface highly homogeneous, which contributes to even $Z\\mathrm{n}$ plating/stripping underneath the artificial SEI layer, as confirmed by in situ optical microscopy. Consequently, the PVB protected Zn $({\\mathrm{PVB}}@{\\mathrm{Zn}})$ electrode delivered an extended plating/stripping cycling life of $2200\\mathrm{~h~}$ in symmetric cells at $0.5\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ . To further evaluate its practical implementation, an $\\mathrm{MnO}_{2}/\\mathrm{PVB}@\\mathrm{Zn}$ battery was assembled, and it showed excellent cycling stability with a capacity retention of ${\\approx}86.6\\%$ at $5\\mathrm{~C~}$ over 1500 cycles, much higher than that of the battery with bare $Z\\mathrm{n}$ electrode (where the capacity retention was only $31.8\\%$ . Additionally, this artificial layer protecting the $Z\\mathrm{n}$ anode also enhanced the CE and long-term cycling performance of a hybrid LiFe $\\mathsf{P O}_{4}$ (LFP)/PVB@Zn cell. \n\n# 2. Results and Discussion \n\n# 2.1. The Issues of Zn Anode in 1 m $\\mathsf{1Z n S O_{4}}$ Electrolyte \n\nTo explore the side reactions between $Z\\mathrm{n}$ metal and electrolyte, commercial $Z\\mathrm{n}$ foil was soaked in 1 m $\\mathrm{ZnSO_{4},}$ as illustrated in Figure 1a. After 7 days, the $Z\\mathrm{n}$ surface was seriously corroded, with the color changing from bright to gray (Figure 1b,c), indicating that Zn metal is highly unstable in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte. The morphology of bare $Z\\mathrm{n}$ before/after immersion in electrolyte was investigated by scanning electron microscopy (SEM). A rough and uneven surface was observed for the bare $Z\\mathrm{n}$ foil (Figure  1d), which is mainly generated during its manufacturing process. In comparison, the $Z\\mathrm{n}$ surface was damaged after soaking in electrolyte, and regular hexagonal flakes overgrew the whole surface (Figure  1e). Even worse, these flakes were piled up loosely on the fresh Zn surface with plenty of open space. Thus, this by-product layer could not effectively block the electrolyte and terminate the corrosion reaction, unlike the SEI layer generated on Li metal in organic electrolyte.[13] To determine the composition of the side products, X-ray powder diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) measurements were conducted. \n\n![](images/ef55f390352b28df1ba30a888500abcaa261b2d202a568454e3288aaf39df65b.jpg) \nFigure 1.  The stability of Zn metal in mild electrolyte. a) Zn foil soaked in 1 m $Z n S O_{4}$ electrolyte. b) Digital image of the bare Zn foil. c) Digital image of Zn foil after soaking in electrolyte for 7 days. SEM image of d) bare Zn foil and e) soaked $Z n$ foil. f ) XRD patterns of Zn foil before/after soaking in the electrolyte. g) FTIR spectra of $Z n$ foil before/after soaking in the electrolyte. h) The crystal structure of $Z n_{4}S O_{4}(O H)_{6}\\cdot3H_{2}O$ by-product. \n\nFigure  1f shows the XRD patterns of the $Z\\mathrm{n}$ foil before/after soaking in electrolyte. Several new peaks clearly located at 9.5, 19.1, and 28.9 emerged after the side reactions of the Zn foil with electrolyte, corresponding to the (002), (004), and (006) planes of $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ (PDF.#04-012-8190), respectively. Compared with the bare Zn foil, the corroded Zn foil also showed several new conspicuous absorption peaks in its FTIR spectrum (Figure 1g). The broad absorptions at ${\\approx}3230 $ and $\\approx1630~\\mathrm{cm^{-1}}$ are assigned to the stretching vibrations of $_\\mathrm{O-H}$ and the bending vibrations of $\\mathrm{H}_{2}\\mathrm{O}$ molecules, respectively.[14] The absorptions at $\\approx1160$ , 1100, 1000, and ${\\approx}600~\\mathrm{cm^{-1}}$ are attributed to the asymmetric and symmetric $s{\\mathrm{-}}0$ stretching vibrations of $\\mathrm{SO}_{4}{}^{2-}$ and the $_{\\mathrm{O-S-O}}$ bending vibrations of $\\mathrm{SO}_{4}{}^{2-}$ .[15] The ${\\approx}520~\\mathrm{cm^{-1}}$ and $\\approx417\\ {\\mathrm{cm}}^{-1}$ peaks reflect the stretching of the $z\\mathrm{n-O}$ bonds, combined with librational vibrations of $\\mathrm{H}_{2}\\mathrm{O}$ molecules.[16] All the absorptions on the FTIR spectrum are well matched with $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}{x}\\mathrm{H}_{2}\\mathrm{O}$ crystal,[17] which is also consistent  with the XRD results. Figure  1h illustrates the crystal structure of $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}\\cdot\\boldsymbol{x}\\mathrm{H}_{2}\\mathrm{O}$ with the space group $P\\overline{{1}}$ ( $a=8.367$ , $b=8.393$ , $c=18.569\\mathrm{~\\AA~}$ ; $\\alpha=90.29^{\\circ}$ , $\\beta=89.71^{\\circ}$ , $\\gamma=120.53^{\\circ})$ , in which the $Z\\mathrm{n}$ ions coordinate with oxygen ions, forming $\\mathrm{{ZnO}_{4}}$ tetrahedra and $Z_{ Ḋ }\\mathrm{nO}_{ Ḋ }\\mathrm{6} Ḍ Ḍ$ octahedra. The $Z\\mathrm{n}$ ion layered structure consists of the edge-sharing $Z_{\\mathrm{{nO}_{6}}}$ octahedra as well as the corner-sharing $\\mathrm{{ZnO}_{4}}$ tetrahedra with the $\\mathrm{H}_{2}\\mathrm{O}$ molecules between the layers. Overall, the side reactions of $Z\\mathrm{n}$ electrode with electrolyte can be expressed as follows \n\n$$\n\\begin{array}{r c l}{{}}&{{}}&{{\\mathrm{Zn}\\leftrightarrow\\mathrm{Zn}^{2+}+2e^{-}}}\\\\ {{}}&{{}}&{{}}\\\\ {{}}&{{}}&{{4\\mathrm{Zn}^{2+}+6\\mathrm{OH}^{-}+5\\mathrm{O}_{4}^{2-}+x\\mathrm{H}_{2}\\mathrm{O}\\leftrightarrow\\mathrm{Zn}_{4}\\mathrm{SO}_{4}\\left(\\mathrm{OH}\\right)_{6}\\cdot x\\mathrm{H}_{2}\\mathrm{O}}}\\\\ {{}}&{{}}&{{}}\\\\ {{}}&{{}}&{{2\\mathrm{H}_{2}\\mathrm{O}+2e^{-}\\leftrightarrow\\mathrm{H}_{2}\\uparrow+2\\mathrm{OH}^{-}}}\\end{array}\n$$ \n\nUnlike Li metal in organic electrolyte, $Z\\mathrm{n}$ metal in mild electrolyte cannot form a dense SEI film to protect the fresh $Z\\mathrm{n}$ , since the $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}{x}\\mathrm{H}_{2}\\mathrm{O}$ layer is loose and porous. Moreover, this by-product layer also increases the interphase impedance between the $Z\\mathrm{n}$ metal electrode and the electrolyte, seriously affecting the electronic/ionic diffusion at the interphase. The side reaction responsible for this and its loose by-product layer not only severely fades the CE of the Zn plating/stripping, but also shortens the cycle life of $Z\\mathrm{n}$ batteries. Therefore, studying how to suppress the side reactions is definitely promising for further enhancing the performance of the $Z\\mathrm{n}$ battery. \n\nZn plating on $Z\\mathrm{n}$ foil in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte was investigated using a transparent symmetrical cell at $10\\mathrm{\\mA\\cm^{-2}}$ (Figure S1, Supporting Information). After $0.5\\mathrm{~h~}$ of plating, the protrusions/dendrites grown on the $Z\\mathrm{n}$ surface were observed with an optical microscope equipped with a digital camera, as shown in Figure 2a. Zn dendrites, resembling Palma leaves in their morphology (Figure 2b), grow in the perpendicular direction to the Zn metal. To study the influence of Zn dendrites on the cycling stability of $Z\\mathrm{n}$ batteries, $Z\\mathrm{n}$ plating/stripping in symmetric bare $Z\\mathrm{n}$ coin-cells using separators with different thicknesses (0.24 and $0.96~\\mathrm{mm}$ , respectively, Figure S2, Supporting Information) was investigated at $0.5~\\mathrm{\\mA}~\\mathrm{cm}^{-2}$ (Figure S3, Supporting Information). After cycling for ${\\approx}260\\mathrm{~h~}$ , a sudden and profound polarization increase $(\\approx4.5~\\mathrm{~V~})$ was detected in the symmetric Zn cell with the $0.24~\\mathrm{mm}$ separator, indicating battery failure.[18] On the contrary, after $\\approx750\\mathrm{~h~}$ of stripping/ plating, an arresting polarization was observed in the cell with the separator that was $0.96~\\mathrm{mm}$ thick, suggesting that the thick separator could prolong the battery life. To further understand the effects of $Z\\mathrm{n}$ dendrites on the cycling stability, the $Z\\mathrm{n}$ foil electrodes and separators were stripped out of the cells after $100\\mathrm{{h}}$ , $200\\mathrm{~h~}$ , and $300\\mathrm{~h~}$ of cycling, as shown in Figure S4 (Supporting Information). Severe $Z\\mathrm{n}$ corrosion with the formation of a thick resistive layer of $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ had occurred on the $Z\\mathrm{n}$ foil electrodes after $100\\mathrm{{h}}$ of cycling, regardless of which separator was used. Zn corrosion also became worse with further cycling. Such serious corrosion and dendrite growth triggered battery failure by impaling the thin separator after $260\\mathrm{~h~}$ of cycling, as evidenced by the photographs of the separators after cycling (Figure S5, Supporting Information). The results confirm that Zn dendrite growth perpendicular to the $Z\\mathrm{n}$ foil surface is a huge potential hazard for battery failure, even in a mild electrolyte. Furthermore, the growth of $Z\\mathrm{n}$ dendrites promotes side reactions between the $Z\\mathrm{n}$ metal electrode and the electrolyte. This is because the fresh plated $Z\\mathrm{n}$ deposited in the form of dendrites has a higher surface area in contact with the electrolyte, contributing to reaction of the $Z\\mathrm{n}$ metal with the electrolyte. In turn, the side reactions also aggravate the inhomogeneity of the Zn electrode surface and the $Z\\mathrm{n}^{2+}$ concentration polarization in the electrolyte, which provides more nuclei for deposition and a stronger driving force to form the $Z\\mathrm{n}$ dendrites. Therefore, developing a new strategy to effectively suppress both side reactions and $Z\\mathrm{n}$ dendrite growth in such an electrolyte is a matter of top priority to enhance the electrochemical properties of Zn-based batteries. \n\n# 2.2. The Suppression of Side Reactions and Dendrite Growth by PVB Coating \n\nSimilar to Li-ion batteries, the side reactions and dendrite growth are self-enhancing in aqueous $Z\\mathrm{n}$ -ion batteries.[19] To develop a side-reaction-free and dendrite-free Zn electrode, building an dense artificial layer on the $Z\\mathrm{n}$ metal surface is quite promising.[12b] Theoretically, the ideal artificial layer should meet the following criteria. First, it should be waterinsoluble, which helps to block the aqueous electrolyte from encountering the Zn electrode surface. Second, it should feature a high ionic conductivity and a low electronic conductivity, promoting uniform $Z\\mathrm{n}^{2+}$ deposition underneath the artificial layer. Third, it should have strong and also flexible mechanical properties to accommodate the volumetric changes of $Z\\mathrm{n}$ electrode during cycling. Fourth, it should have good adhesion to the Zn metal surface, so that this layer would not be detached from the Zn surface during cycling. Based on the above conditions, the PVB polymer seems appropriate. PVB is the random ternary polymer poly(vinyl butyral, vinyl alcohol, and vinyl acetate), the structure of which is shown in Figure 2c. This PVB polymer is insoluble in an aqueous solution and has been intensively applied in laminated safety glass for automobile windshields and gel electrolytes due to its strong adhesion, superior flexibility, high ionic conductivity, good mechanical stability, and favorable hydrophilic property.[20] Due to these advantages, this PVB polymer was selected for the artificial SEI layer and deposited on the Zn metal surface using a facile spin-coating method, which not only retarded side reactions by blocking contact with the electrolyte, but also inhibited dendrite growth by promoting even $Z\\mathrm{n}$ -ion plating/stripping. \n\n![](images/48de5512a99e251cefbf8f07f310977c9ee9c178b044970859b4a82a32eeb8da.jpg) \nFigure 2.  Zn dendrite morphology and schematic illustration of Zn plating/stripping. a) Optical microscope image of Zn dendrites on a cross section of Zn foil. b) Photograph of a palm leaf, similar to the morphology of Zn dendrites. c) Schematic illustration of morphology evolution for both the bare $z_{n-Z_{n}}$ cell and the $\\mathsf{P V B}@\\mathsf{Z n}.\\mathsf{P V B}@\\mathsf{Z n}$ cell during repeated cycles of stripping/plating. d) Cycling stability of Zn plating/stripping in both bare $Z n$ and $P V B@Z n$ symmetric cells, with the inset showing the initial voltage profiles of both cells. \n\nThe effectiveness of the PVB layer for enhancing the stability of $\\operatorname{PVB}@Z\\mathrm{n}$ foil was evaluated in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte, as illustrated in Figure S6 (Supporting Information). After 7 days, the $\\operatorname{PVB}@Z\\mathrm{n}$ foil still maintains a bright surface without obvious corrosion, which is mainly because  the electrolyte is isolated by the protective PVB film. The electrochemical performance of $\\operatorname{PVB}@Z\\mathrm{n}$ electrode was investigated in the symmetrical $\\operatorname{PVB}@Z\\mathrm{n}$ cells by repeated plating/stripping measurements at $0.5\\mathrm{\\mA\\cm^{-2}}$ (Figure 2d). As was discussed above, the bare $Z\\mathrm{n-}$ Zn symmetrical cell with a thin separator failed after nearly $260\\mathrm{h}$ of cycling due to an internal short circuit. In strong contrast, the PVB $@Z\\mathrm{n}$ symmetrical cell with the same thin separator displayed much smaller polarization and maintained smaller polarization curves for more than $2200\\mathrm{~h~}$ of cycling without any internal short circuit, benefiting from the dendrite-free $Z\\mathrm{n}$ anode. That is to say, the PVB-coating effectively inhibits the Zn dendrites and prolongs the cycle life of the Zn symmetrical cell. In addition, the polarization curves of both cells after different cycling times are compared in the inset of Figure 2d and Figure S7 (Supporting Information). At the first plating/stripping, the $\\operatorname{PVB}@Z\\mathrm{n}$ cell shows polarization of $108.5~\\mathrm{mV},$ lower than that of the bare Zn $(\\approx200\\ \\mathrm{mV})$ (inset of Figure  2d). Importantly, the low polarization indicates a low energy barrier for metal nucleation, which promotes a relatively uniform metal plating process.[21] After 125 cycles, a sharp increase was found in the curves for the bare $Z\\mathrm{n}$ cell, essentially because the separator was pierced (Figure $7\\mathrm{a}$ , Supporting Information). In comparison, the PVB $@Z\\mathrm{n}$ cell still features the low polarization value of $84.5~\\mathrm{mV},$ which is also maintained in the following cycles, as evidenced by the value after 500 cycles $({\\approx}84.3~\\mathrm{mV})$ ) (Figure $76$ , Supporting Information). \n\nTo intuitively understand the protection of Zn foil provided by the PVB layer, Zn foil electrodes with/without PVB protection were stripped out of the symmetrical cells after different numbers of cycles. The symmetrical cells were cycled at a current density of $2\\mathrm{\\mA}\\mathrm{cm}^{-2}$ with 10 min of intermittence, as shown in Figure S8 (Supporting Information). After 50 cycles, the digital image of $\\operatorname{PVB}@Z\\mathrm{n}$ anode shows a bright and smooth surface (Figure  3a), although corrosion had occurred on the edge and surface of the bare Zn foil (Figure 3b). In the following cycles, the corrosion was aggravated, which had a serious impact on the CE and cycling stability of the $Z\\mathrm{n}$ -based battery. In contrast, only slight corrosion at the edge of the $\\operatorname{PVB}@Z\\mathrm{n}$ electrode was found, even after 800 cycles, which directly confirms that $Z\\mathrm{n}$ foil was protected by PVB film during the electrochemical tests. \n\n![](images/b92fbc86ec4a3899a9cfd834d45f32cd6d836fc51907f3173d0e21fc49d261c7.jpg) \nFigure 3.  The morphology of cycled $Z n$ anodes, optical microscopy study of $Z n$ plating/stripping chemistry, and Coulombic efficiencies of the Zn plating/stripping. a) Digital images of Zn electrodes that were stripped out of the cells after 50, 100, 200, 300, 400, and 800 cycles. b) Digital images of PVB $@2n$ electrodes stripped out after the same cycle numbers. In situ optical microscope images of the front surfaces of c) Zn electrodes and d) $P V B@Z n$ electrodes in symmetric transparent cells, along with the specified numbers of plating/stripping cycles. e) Coulombic efficiencies of the Zn plating/stripping on $\\mathsf{C u}$ foil with/without PVB at $4\\mathsf{m A}\\mathsf{c m}^{-2}$ . Voltage profiles of the f) bare $\\mathsf{C u}$ foil and g) PVB coated Cu foil. \n\nIn order to further evaluate the inhibition of $Z\\mathrm{n}$ dendrite growth by the PVB film, an optical microscope equipped with a digital camera (Figure S9, Supporting Information) was used for in situ monitoring of Zn plating/stripping on Zn foil in a transparent symmetrical cell. A high current density of $4\\mathrm{\\mA\\cm^{-2}}$ with 10 min of intermittence was applied to repeatedly conduct the plating/stripping measurements on the transparent cells. \n\nFigure  3c illustrates the nucleus formation as well as $Z\\mathrm{n}$ dendrite growth at different plating/stripping cycles in the bare Zn symmetric cell. Before cycling, the Zn surface was found to be uneven, which induces the generation of nuclei. After 50 cycles, nuclei or protrusions were observed at the edges and on the surface, which is evidence of inhomogeneous $Z\\mathrm{n}$ plating. Under further repeated plating/stripping, some nuclei evolve into Zn dendrites on the edge. Simultaneously, severe corrosion can be observed on the surface of the $Z\\mathrm{n}$ foil, which distorts the electrochemical performance of $Z\\mathrm{n}$ -based batteries. The PVB-film-protected $Z\\mathrm{n}$ foil was also tested under the same conditions. Before cycling, the surface of the $\\operatorname{PVB}@Z\\mathrm{n}$ foil was smooth. In the following plating/stripping process, the PVBprotected Zn electrode exhibited smooth $Z\\mathrm{n}$ deposition with no sign of dendrites or pulverization during cycling (Figure  3d). In addition to suppressing the $Z\\mathrm{n}$ dendrites, the impact of the PVB layer on the CE of the $Z\\mathrm{n}$ plating/stripping behavior was also evaluated at 1 and $4\\mathrm{\\mA\\cm^{-2}}$ , respectively. As illustrated in Figure S10 (Supporting Information), the $\\mathrm{PVB}@\\mathrm{Cu-Zn}$ cell delivers a higher initial CE $(83.5\\%)$ and smaller voltage hysteresis compared to the bare $\\mathrm{{Cu-Zn}}$ cell $(67.4\\%)$ at $1\\mathrm{mA}\\mathrm{cm}^{-2}$ with a capacity of $0.5\\ \\mathrm{mA}$ h $\\mathrm{cm}^{-2}$ . When the current was increased to $4\\mathrm{\\mA\\cm^{-2}}$ , fluctuating CEs with an average value of $93.8\\%$ were obtained for the bare Cu-Zn cell (Figure 3e). In contrast, the $\\mathrm{PVB}@\\mathrm{Cu-Zn}$ cell still presented stable CEs with the average value of $99.4\\%$ . The increased CE is mainly because the PVB film inhibits the side reactions as well as facilitating the formation of even nuclei and reversible $Z\\mathrm{n}$ plating/stripping, as  we mentioned above. Moreover, the initial voltage hysteresis in the $\\mathrm{PVB}@\\mathrm{Cu-Zn}$ cell is ${\\approx}133~\\mathrm{mV},$ which is much smaller than that in the bare $\\mathrm{{Cu-Zn}}$ cell $(\\approx170~\\mathrm{mV})$ (Figure $3\\mathrm{f},\\mathrm{g})$ ). \n\n# 2.3. Zn Dendrite Suppression Mechanism by PVB Coating \n\nFirst, the morphology of $\\operatorname{PVB}@Z\\mathrm{n}$ foil was studied by SEM. After spin-coating, the rough and uneven surface of $Z\\mathrm{n}$ foil was coated by a dense and uniform PVB film (Figure  4a), as evidenced by the cross-sectional images with energy dispersive spectroscopy (EDS) mappings of Zn, C, and O elements (Figure  4b). PVB powders have an amorphous structure, as evidenced by the broad peak in the XRD pattern of the PVB powder (Figure  4c). FTIR spectra of this artificial PVB SEI film exhibit several characteristic peaks. The peak located at ${\\approx}3309\\ \\mathrm{cm^{-1}}$ is attributed to the symmetrical stretching vibration of $_\\mathrm{O-H}$ , as labeled in Figure  4d.[22] The absorption at $\\approx1726~\\mathrm{cm^{-1}}$ and $1129~\\mathrm{cm}^{-1}$ is related to the stretching vibrations of $\\mathrm{C-H}$ and $\\scriptstyle{\\mathrm{C=O}}$ bonds, respectively.[23] Then, the surface characteristics of the PVB layer (Figure  4e) were also investigated by X-ray photoelectron spectroscopy (XPS). Figure 4f presents the C 1s and O 1s spectra, which could be decomposed into several Lorentzian peaks.[24] The curve fitting results for C 1s and O 1s clearly illustrate that this artificial PVB layer has abundant oxygen-containing functional groups, which not only enhance its adhesion to the $Z\\mathrm{n}$ metal, but also greatly boost its hydrophilicity in aqueous media.[25] The excellent adhesion between the PVB layer and the $Z\\mathrm{n}$ foil was confirmed by rolling and twisting experiments (Figure S11, Supporting Information). \n\nThe hydrophilicity of the PVB film with respect to the electrolytes was evaluated by measuring the dynamic contact angle of $Z\\mathrm{n}$ with/without the PVB coating at ambient temperature of $25~^{\\circ}\\mathrm{C}$ , as illustrated in Figure 5a,b. The initial contact angle of the bare $Z\\mathrm{n}$ was ${\\approx}88.7^{\\circ}$ , and it remained unchanged in the following $4~\\mathrm{min}$ . Even after $20~\\mathrm{min}$ , a large contact angle of $51.8^{\\circ}$ still remained, indicating the limited hydrophilicity of the $Z\\mathrm{n}$ metal surface in aqueous media. In striking contrast, the initial contact angle of $\\operatorname{PVB}@Z\\mathrm{n}$ foil was found to be $72.2^{\\circ}$ , smaller than that on the bare $Z\\mathrm{n}$ foil. In the ensuing $20~\\mathrm{min}$ , it was gradually reduced to $14.5^{\\circ}$ , suggesting that the artificial PVB film dramatically enhances the hydrophilicity due to its rich polar functional groups.[26] Thermodynamically, the enhanced hydrophilicity will reduce the interfacial free energy between the Zn substrate and the electrolyte,[25] contributing to the formation of homogeneous plating and nucleation, which plays a crucial role in the final $Z\\mathrm{n}$ plating pattern.[27] The stripping and plating of $Z\\mathrm{n}$ with/without the PVB coating was evaluated by linear polarization experiments in 1 m $\\mathrm{ZnSO_{4}}$ electrolyte, as shown in Figure S12 (Supporting Information). Compared to the bare $Z\\mathrm{n}$ electrode, the corrosion potential of the PVB coated Zn electrode increased from $-1.052$ to $-1.010\\mathrm{V}$ due to the PVB passivation layer coating. Then, SEM was employed to investigate the electrodeposition behavior of Zn-ions with/without the PVB layer (Figure 5c–e). Before plating, the cross-sectional view of the $\\operatorname{PVB}@Z\\mathrm{n}$ foil reveals that the bare $Z\\mathrm{n}$ surface was tightly coated by the PVB film, which had a thickness of ${\\approx}1\\upmu\\mathrm{m}$ (Figure  5c). After $0.5\\mathrm{\\mA}\\mathrm{~h~}\\mathrm{cm}^{-2}$ of plating (Figure S13, Supporting Information), the $Z\\mathrm{n}$ was evenly plated under the artificial protective layer, as shown in Figure 5d. \n\n![](images/ef6df9327d71b4aac8d2fa9d97767e592dce97c0efacea47d6f27197d37f10f4.jpg) \nFigure 4.  Characterization of bare $Z n$ and $P V B@Z n$ foils. a) SEM image of bare Zn foil. b) Cross-sectional SEM image of $P V B@Z n$ foil with EDS mappings of Zn, C, and O elements, respectively. c) XRD patterns of bare $Z n$ foil, $P V B@Z n$ foil, and PVB. d) FTIR spectrum of PVB film on the surface of Zn foil. e) Schematic illustration of $P V B@Z n$ foil. f) XPS analysis of PVB film, with the top panel showing the high-resolution C 1s spectrum, while the bottom panel contains the high-resolution O 1s spectrum. \n\n![](images/cd9e93e5ab169522fa4329f5f2723ffba1632738e4debc34eccf5b94e0d1cf23.jpg) \nFigure 5.  Hydrophilicity results and morphology of Zn foils before and after plating. a,b) In situ contact angle measurements of bare Zn and PVB@Zn foil, respectively. c–e) Cross-sectional SEM images of PVB $@2n$ foil, $P V B@Z n$ foil after $Z n$ plating, and bare Zn foil after Zn plating, respectively. \n\nThe protective PVB layer functions as an artificial SEI and serves to prevent water from reaching the $Z\\mathrm{n}$ surface, suppressing $Z\\mathrm{n}$ dendrites and enhancing the CE. PVB is an electronic insulator, as verified by an electrical conductivity measurement (Figure S14, Supporting Information). The electrical resistivity was estimated as $\\approx2.4\\times10^{5}\\ \\Omega\\ \\mathrm{cm}$ (the conductivity, $\\sigma={\\approx}4.17\\times10^{-6}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1}$ , see the Supporting Information for details). The high potential gradient in the PVB film due to the high electronic resistance of the insulating PVB film could drive $Z\\mathrm{n}^{2+}$ diffusion through the PVB film,[28] but prevented the reduction of solvated water and anions, thus increasing the transference number. Moreover, the PVB film features good ionic conductivity $({\\approx}6.67\\times10^{-5}\\ \\mathrm{S}\\ \\mathrm{cm}^{-1}$ , Figure S15, Supporting Information), as reported elsewhere,[20,29] which facilitates the $\\mathrm{Zn}^{2+}$ diffusion through this protective film. The transference number $(t_{\\mathrm{Zn}^{2+}})$ was further calculated to quantitatively describe the ${\\mathrm{Zn}}^{2+}$ conducting ability of the PVB layer. A rather low $t_{\\mathrm{Zn}^{2+}}$ of 0.34 was obtained in the pure $Z\\mathrm{n}$ symmetric cell (Figure S16a, Supporting Information), owing to the faster migration speed of the anions than solvated $Z\\mathrm n^{2+}$ , which is consistent with a previous report.[30] $t_{\\mathrm{Zn}^{2+}}$ can be dramatically improved to 0.68, however, after introducing the PVB layer (Figure S16b, Supporting Information), because the poly(vinyl alcohol) groups in PVB provide the active sites or solvating groups for ion transfer,[31] and the dense PVB can block solvated water and anions from diffusing through the PVB. To further confirm the enhanced $t_{\\mathrm{Zn}^{2+}}$ in the $\\operatorname{PVB}@Z\\mathrm{n}$ cells, we designed a special device to conduct in situ FTIR measurements at the electrolyte/Zn anode interface with/without the PVB film (Figure S17, Supporting Information). In the bare $Z\\mathrm{n}$ cell, the absorption intensity of $\\mathrm{SO}_{4}\\mathrm{}^{2-}$ at about $1100~\\mathrm{cm}^{-1}$ (due to the triply degenerate asymmetric stretching vibration) clearly decreased after $Z\\mathrm{n}^{2+}$ plating (Figure S18, Supporting Information), demonstrating that a great many anions had moved during this period, which led to the limited $t_{\\mathrm{Zn}^{2+}}$ . In strong contrast, the absorption intensity of $\\mathrm{SO}_{4}{}^{2-}$ almost retained a similar value when $Z\\mathrm{n}^{2+}$ plating was conducted in the $\\operatorname{PVB}@Z\\mathrm{n}$ cells, indicating that anion migration is much weaker at the electrolyte/ $z\\mathrm{n}$ interface (Figure S19, Supporting Information). The high $t_{\\mathrm{Zn}^{2+}}$ also contributes to eliminating the large $Z\\mathrm{n}^{2+}$ concentration gradient and facilitating uniform ion distribution, resulting in homogeneous Zn plating.[32] \n\nMoreover, the dense PVB film shows excellent mechanical strength. The Young’s modulus of the $\\operatorname{PVB}@Z\\mathrm{n}$ electrode was tested using the peak force tapping (PFT) mode of an atomic force microscope (AFM; Figure S20, Supporting Information). The value of the Young’s modulus of PVB film is ${\\approx}220{\\-}260\\ \\mathrm{\\MPa}$ , which helps to suppress the Zn dendrite growth. Hence, due to the limited electrical conductivity, good ionic conductivity, and excellent mechanical stability of the PVB film, the $Z\\mathrm{n}$ nuclei are generated on the $Z\\mathrm{n}$ surface instead of on the PVB film. In comparison, the Zn foil without the PVB protective film suffered from serious dendrite growth after electrodeposition (Figure 5e). These dendrites would be a potential hazard, leading to an internal short circuit of the battery. \n\n# 2.4. Electrochemical Performance of LFP/PVB $@$ Zn and $\\mathsf{M n O}_{2}/$ PVB@Zn Full Cells \n\nHybrid $\\mathrm{LFP/PVB}@Z\\mathrm{n}$ and $\\mathrm{MnO}_{2}/\\mathrm{PVB}@\\mathrm{Zn}$ batteries were assembled to further study the impact of the PVB protective film on $Z\\mathrm{n}$ on the performance of the full-cells. Galvanostatic charge–discharge of hybrid LFP/PVB $@Z\\mathrm{n}$ cells at $0.5\\mathrm{~C~}$ (where $1\\mathrm{C}$ is equal to $170\\mathrm{\\mA\\g^{-1}},$ ,[33] Figure  6a) shows a flat potential plateau, corresponding to the $\\mathrm{Li^{+}}$ ion extraction/insertion from/ into the LFP cathode,[34] which was also evidenced by ex situ XRD measurements (Figure S21, Supporting Information). Remarkably, an initial CE of $96.3\\%$ was obtained from the $\\mathrm{LFP}/\\protect$ $\\operatorname{PVB}@Z\\mathrm{n}$ battery (capacity o $\\mathrm{f{\\approx}153.5\\ m A\\ h\\ g^{-1})}$ , higher than that of the battery with bare $Z\\mathrm{n}$ electrode (an initial CE of $93.1\\%$ with a capacity of ${\\bf\\tilde{\\tau}}{\\approx}149.2\\ \\mathrm{mA}\\mathrm{h}\\ \\mathrm{g}^{-1})$ . Figure S22 (Supporting Information) shows the rate capability of $\\mathrm{LFP/Zn}$ batteries with/without the PVB protective film. Only the capacity of $32.1~\\mathrm{mA}$ h $\\mathbf{g}^{-1}$ , representing capacity retention of ${\\approx}21.5\\%$ (compared to $0.5{\\mathrm{~C}})$ , was retained in the $\\mathrm{LFP/Zn}$ battery when the current rate was increased to $20~\\mathrm{C}$ . In comparison, a high capacity of $76.9\\mathrm{\\mA}$ h $\\boldsymbol{\\mathrm{g}}^{-1}$ was still obtainable in the LFP/PVB $@Z\\mathrm{n}$ battery at the same current rate. After 500 cycles at $5\\mathrm{~C~}$ , the $\\mathrm{LFP}/\\protect$ $\\operatorname{PVB}@Z\\mathrm{n}$ battery still delivered a reversible discharge capacity of $108.4~\\mathrm{{mA}}$ h $\\boldsymbol{\\mathrm{g}}^{-1}$ and maintained a high capacity retention of $87.6\\%$ , with only $0.025\\%$ capacity fading per cycle (Figure  6b), which is much higher than that of the LFP/Zn battery with capacity retention of only $60\\%$ after 500 cycles. The morphology of $Z\\mathrm{n}$ anodes after 500 cycles was studied by SEM. The bare Zn electrode shows serious corrosion and dendrite growth (Figure S23, Supporting Information), which is likely to be the main reason for its poor CE and limited cycling stability.[35] The $\\operatorname{PVB}@Z\\mathrm{n}$ electrode is still even and smooth, however, and no serious corrosion or dendrites can be found (Figure S24, Supporting Information). Furthermore, the electrochemical performance of the LFP/PVB@Zn battery was also compared with other hybrid $Z\\mathrm{n}$ -based batteries, as illustrated in Figure S25 (Supporting Information). It shows that our LFP/PVB@Zn battery is superior to other hybrid $Z\\mathrm{n}$ -based batteries. To further demonstrate the versatility of our PVB SEI film on $Z\\mathrm{n}$ anode, $\\mathrm{MnO}_{2}/\\mathrm{PVB}@\\mathrm{Zn}$ batteries were assembled as well, as the $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ battery is one of the most commonly used systems in mild aqueous electrolyte.[36] The $\\mathrm{MnO}_{2}$ was in situ synthesized on a carbon cloth by a chronoamperometric electrodeposition process, and its nanoflower morphology was characterized by SEM (Figure S26, Supporting Information). $\\mathrm{MnO}_{2}/\\mathrm{PVB}@\\mathrm{Zn}$ batteries were tested in an electrolyte composed of $1\\mathrm{~M~ZnSO_{4}}$ and $0.1\\mathrm{~m~MnSO}_{4}.$ in which $\\mathrm{MnSO}_{4}$ serves as an electrolyte additive to suppress the $\\mathrm{Mn}^{2+}$ dissolution from the cathode material. The typical charge–discharge curves of $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ battery at $1\\mathrm{C}$ are presented in Figure 6c. Our PVB coated $Z\\mathrm{n}$ anode helps to enhance the CE and cycling stability of the $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ system, as shown in Figure 6d. After 1500 cycles, the capacity retention of the $\\mathrm{MnO}_{2}/\\mathrm{PVB}@\\mathrm{Zn}$ battery is ${\\approx}86.6\\%$ , much higher than that of the $\\mathrm{MnO}_{2}/\\mathrm{Zn}$ battery $(31.8\\%)$ . \n\n![](images/f2ecd509c38ddb96f59985bc707485e2a4a4627f1a17189af18524233b5ba38a.jpg) \nFigure 6.  Electrochemical performance of Zn-based full cells. a) The first cycle charge–discharge profiles of $\\mathsf{L F P/Z n}$ and $\\mathsf{L F P/P V B@Z n}$ batteries at the current rate of $0.5\\mathsf{C}.$ b) Long-term cycling stability of both batteries at 5 C with the corresponding CEs. c) Charge–discharge profiles of $\\mathsf{M n O}_{2}/\\mathsf{Z n}$ batteries in electrolyte composed of 1 m $Z n S O_{4}$ and 0.1 m $\\mathsf{M n S O}_{4}$ solution at the rate of 1 C. d) Long-term cycling stability of $\\mathsf{M n O}_{2}/\\mathsf{Z n}$ and $\\mathsf{M n O}_{2}/$ $P V B@Z n$ batteries at ${5}\\mathsf{C}$ with the corresponding CEs. \n\n# 3. Conclusion \n\nIn this work, the $Z\\mathrm{n}$ surface chemistry in slightly acidic electrolyte as well as the influence of $Z\\mathrm{n}$ dendrite growth on the electrochemical performance of $Z\\mathrm{n}$ -based batteries was comprehensively investigated. The results reveal that $Z\\mathrm{n}$ metal shows poor thermodynamic stability even in mild electrolyte. A by-product layer of $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ was generated at the interphase between the $Z\\mathrm{n}$ surface and the electrolyte, although it could not block the electrolyte due to its loose structure. In addition, Zn dendrites that formed on the bare $Z\\mathrm{n}$ electrode would pierce the thin separator $(0.24~\\mathrm{mm})$ and generate an internal short circuit after prolonged plating/ stripping. Although a thick separator $(0.96~\\mathrm{mm})$ extended the cycle life of the symmetric $Z\\mathrm{n}$ cell, it could not fundamentally address the issues caused by the $Z\\mathrm{n}$ dendrites. To effectively suppress the side reactions and $Z\\mathrm{n}$ dendrite growth, an even and dense PVB SEI film was deposited on the surface of the Zn metal using the spin-coating method. Benefiting from the abundant polar functional groups of the PVB chains, this insulating polymer shows good hydrophilicity and ionic conductivity, inhibiting the side reactions and $Z\\mathrm{n}$ dendrite growth. The side-reaction-free and dendrite-free $\\operatorname{PVB}@Z\\mathrm{n}$ anode facilitated repeated plating/stripping over $2200\\mathrm{~h~}$ in the symmetrical Zn cell, much longer than for the bare $Z\\mathrm{n}$ cells. Importantly, both the commonly used $\\mathrm{MnO}_{2}$ system and the hybrid LFP system displayed higher initial CE and longer lifespan when coupled with $\\operatorname{PVB}@Z\\mathrm{n}$ anode compared to the batteries with bare $Z\\mathrm{n}$ anode. Our findings can help to elucidate the side reactions between Zn metal electrode and mild electrolyte, as well as $Z\\mathrm{n}$ dendrite growth. We provide a simple and inexpensive strategy to manipulate the Zn electrodeposition behavior from dendritic to nondendritic, which paves the way to rejuvenated prospects for $Z\\mathrm{n}$ -based batteries in largescale applications. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nFinancial support provided by the Australian Research Council (ARC) (FT150100109, DP170102406, and DE190100504) is gratefully acknowledged. The authors thank the Electron Microscopy Centre (EMC) at the University of Wollongong. The authors also thank Gemeng Liang, Sailin Liu, Yifeng Cheng, Qining Fan, and Zhijie Wang for their help with FTIR and other measurements. The authors also thank Dr. Tania Silver for her critical reading of this manuscript. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Author Contributions \n\nJ.H. performed the experiments and wrote the manuscript. X.L. and S.Z. helped to conduct the SEM measurements. F.Y. and X.Z. analysed the electrochemical data. S.Z. performed the dynamic contact angle tests. G.B. conducted the AFM measurements. C.W. and Z.G. supervised the overall research. All the authors discussed the results and commented on the manuscript. \n\n# Keywords \n\naqueous Zn battery, artificial SEI layer, by-products, side reactions, Zn dendrites \n\nReceived: February 10, 2020 Revised: April 14, 2020 Published online: \n\nc) K. E.  Sun, T. K.  Hoang, T. N. L.  Doan, Y.  Yu, X.  Zhu, Y.  Tian, P.  Chen, ACS Appl. Mater. Interfaces 2017, 9, 9681; d) Q.  Zhang, J. Luan, L. Fu, S. Wu, Y. Tang, X. Ji, H. Wang, Angew. Chem., Int. Ed. 2019, 58, 15841. \n[9]\t M. Chamoun, B. J. Hertzberg, T. Gupta, D. Davies, S. Bhadra, B. Van Tassell, C. Erdonmez, D. A. Steingart, NPG Asia Mater.. 2015, 7, e178. \n[10]\t S.  Higashi, S. W.  Lee, J. S.  Lee, K.  Takechi, Y.  Cui, Nat. Commun. 2016, 7, 11801. \n[11]\t a) C.  Zhang, J.  Holoubek, X.  Wu, A.  Daniyar, L.  Zhu, C.  Chen, D. P.  Leonard, I. A.  Rodriguez-Perez, J. X.  Jiang, C.  Fang, X.  Ji, Chem. Commun. 2018, 54, 14097; b) F.  Wang, O.  Borodin, T.  Gao, X. Fan, W. Sun, F. Han, A. Faraone, J. A. Dura, K. Xu, C. Wang, Nat. Mater. 2018, 17, 543. \n[12]\t a) K.  Zhao, C.  Wang, Y.  Yu, M.  Yan, Q.  Wei, P.  He, Y.  Dong, Z. Zhang, X. Wang, L. Mai, Adv. Mater. Interfaces 2018, 5, 1800848; b) B. Tang, L. Shan, S. Liang, J. Zhou, Energy Environ. Sci. 2019, 12, 3288. \n[13]\t J.  Qian, B. D.  Adams, J.  Zheng, W.  Xu, W. A.  Henderson, J.  Wang, M. E. Bowden, S. Xu, J. Hu, J. G. Zhang, Adv. Funct. Mater. 2016, 26, 7094. \n[14]\t M.  Grechko, T.  Hasegawa, F.  D’Angelo, H.  Ito, D.  Turchinovich, Y. Nagata, M. Bonn, Nat. Commun. 2018, 9, 885. \n[15]\t X. Guo, H. S. Xiao, F. Wang, Y. H. Zhang, J. Phys. Chem. A 2010, 114, 6480. \n[16]\t M.  Faisal, A. A.  Ismail, A. A.  Ibrahim, H.  Bouzid, S. A.  Al-Sayari, Chem. Eng. J. 2013, 229, 225. \n[17]\t N. Chukanov, R. Rastsvetaeva, S. Aksenov, I. Pekov, D. Belakovskiy, G. Blass, G. Möhn, Geol. Ore Deposits 2013, 55, 663. \n[18]\t C. Lan, C. Lee, T. Chin, Electrochim. Acta 2007, 52, 5407. \n[19]\t a) N. W.  Li, Y. X.  Yin, C. P.  Yang, Y. G.  Guo, Adv. Mater. 2016, 28, 1853; b) H.  Li, D.  Chao, B.  Chen, X.  Chen, C.  Chuah, Y.  Tang, Y.  Jiao, M.  Jaroniec, S. Z.  Qiao, J. Am. Chem. Soc. 2020, 142, 2012; c) H. Gao, F. Yang, Y. Zheng, Q. Zhang, J. Hao, S. Zhang, H. Zheng, J. Chen, H. Liu, Z. Guo, ACS Appl. Mater. Interfaces 2019, 11, 5373. \n[20]\t Y. Bai, Y. Chen, Q. Wang, T. Wang, J. Mater. Chem. A 2014, 2, 9169. \n[21]\t J.  Xie, J.  Wang, H. R.  Lee, K.  Yan, Y.  Li, F.  Shi, W.  Huang, A.  Pei, G. Chen, R. Subbaraman, Sci. Adv. 2018, 4, eaat5168. \n[22]\t P.  Thomas, J. P.  Guerbois, G.  Russell, B.  Briscoe, J. Therm. Anal. Calorim. 2001, 64, 501. \n[23]\t L. J.  Chen, J. D.  Liao, S. J.  Lin, Y. J.  Chuang, Y. S.  Fu, Polymer 2009, 50, 3516. \n[24]\t B.  Erdem, R. A.  Hunsicker, G. W.  Simmons, E. D.  Sudol, V. L. Dimonie, M. S. El-Aasser, Langmuir 2001, 17, 2664. \n[25]\t D. Briggs, J. Adhes. 1982, 13, 287. \n[26]\t a) T. Meng, F. Yi, H. Cheng, J. Hao, D. Shu, S. Zhao, C. He, X. Song, F.  Zhang, ACS Appl. Mater. Interfaces 2017, 9, 42883; b) J.  Hao, T. Meng, D. Shu, X. Song, H. Cheng, B. Li, X. Zhou, F. Zhang, Z. Li, C. He, J. Colloid Interface Sci. 2019, 537, 57. \n[27]\t Z. Zhao, J. Zhao, Z. Hu, J. Li, J. Li, Y. Zhang, C. Wang, G. Cui, Energy Environ. Sci. 2019, 12, 1938. \n[28]\t X.  Liang, Q.  Pang, I. R.  Kochetkov, M. S.  Sempere, H.  Huang, X. Sun, L. F. Nazar, Nat. Energy 2017, 2, 17119. \n[29]\t a) F.  Lian, Y.  Wen, Y.  Ren, H.  Guan, J. Membr. Sci. 2014, 456, 42; b) K. F.  Chen, C. H.  Liu, H. K.  Huang, C. H.  Tsai, F. R.  Chen, Int. J. Electrochem. Sci. 2013, 8, 3524. \n[30]\t J. L. Dye, M. P. Faber, D. J. Karl, J. Am. Chem. Soc. 1960, 82, 314. \n[31]\t S.  Gopal, S.  Agnihotry, V.  Gupta, Sol. Energy Mater. Sol. Cells 1996, 44, 237. \n[32]\t R.  Xu, Y.  Xiao, R.  Zhang, X. B.  Cheng, C. Z.  Zhao, X. Q.  Zhang, C. Yan, Q. Zhang, J. Q. Huang, Adv. Mater. 2019, 31, 1808392. \n[33]\t a) G. Armstrong, A. R. Armstrong, P. G. Bruce, P. Reale, B. Scrosati, Adv. Mater. 2006, 18, 2597; b) J.  Hao, F.  Yang, S.  Zhang, H.  He, G. Xia, Y. Liu, C. Didier, T. Liu, W. K. Pang, V. K. Peterson, Proc. Natl. Acad. Sci. USA 2020, 117, 2815. \n[34]\t J.  Hao, J.  Long, B.  Li, X.  Li, S.  Zhang, F.  Yang, X.  Zeng, Z.  Yang, W. K. Pang, Z. Guo, Adv. Funct. Mater. 2019, 29, 1903605. \n[35]\t J. S.  Lee, S.  Tai Kim, R.  Cao, N. S.  Choi, M.  Liu, K. T.  Lee, J.  Cho, Adv. Energy Mater. 2011, 1, 34. \n[36]\t D.  Chao, W.  Zhou, C.  Ye, Q.  Zhang, Y.  Chen, L.  Gu, K.  Davey, S. Z. Qiao, Angew. Chem., Int. Ed. 2019, 58, 7823. " + }, + { + "id": "10.1038_s41467-020-16237-1", + "DOI": "10.1038/s41467-020-16237-1", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-16237-1", + "Relative Dir Path": "mds/10.1038_s41467-020-16237-1", + "Article Title": "In-situ structure and catalytic mechanism of NiFe and CoFe layered double hydroxides during oxygen evolution", + "Authors": "Dionigi, F; Zeng, ZH; Sinev, I; Merzdorf, T; Deshpande, S; Lopez, MB; Kunze, S; Zegkinoglou, I; Sarodnik, H; Fan, DX; Bergmann, A; Drnec, J; de Araujo, JF; Gliech, M; Teschner, D; Zhu, J; Li, WX; Greeley, J; Roldan Cuenya, B; Strasser, P", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "NiFe and CoFe (MFe) layered double hydroxides (LDHs) are among the most active electrocatalysts for the alkaline oxygen evolution reaction (OER). Herein, we combine electrochemical measurements, operando X-ray scattering and absorption spectroscopy, and density functional theory (DFT) calculations to elucidate the catalytically active phase, reaction center and the OER mechanism. We provide the first direct atomic-scale evidence that, under applied anodic potentials, MFe LDHs oxidize from as-prepared alpha -phases to activated gamma -phases. The OER-active gamma -phases are characterized by about 8% contraction of the lattice spacing and switching of the intercalated ions. DFT calculations reveal that the OER proceeds via a Mars van Krevelen mechanism. The flexible electronic structure of the surface Fe sites, and their synergy with nearest-neighbor M sites through formation of O-bridged Fe-M reaction centers, stabilize OER intermediates that are unfavorable on pure M-M centers and single Fe sites, fundamentally accounting for the high catalytic activity of MFe LDHs. NiFe and CoFe layered double hydroxides are among the most active electrocatalysts for the alkaline oxygen evolution reaction. Here, by combining operando experiments and rigorous DFT calculations, the authors unravel their active phase, the reaction center and the catalytic mechanism.", + "Times Cited, WoS Core": 757, + "Times Cited, All Databases": 776, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000537059500001", + "Markdown": "# In-situ structure and catalytic mechanism of NiFe and CoFe layered double hydroxides during oxygen evolution \n\nFabio Dionigi1,9✉, Zhenhua Zeng 2,9✉, Ilya Sinev3,4, Thomas Merzdorf1, Siddharth Deshpande2, Miguel Bernal Lopez3,4, Sebastian Kunze3,4, Ioannis Zegkinoglou $\\textcircled{1}$ 3,4, Hannes Sarodnik1, Dingxin Fan2, Arno Bergmann1,4, Jakub Drnec 5, Jorge Ferreira de Araujo1, Manuel Gliech1, Detre Teschner6,7, Jing $Z h u^{8}$ Wei-Xue Li $\\textcircled{1}$ 8, Jeffrey Greeley2, Beatriz Roldan Cuenya 4✉ & Peter Strasser 1✉ \n\nNiFe and CoFe (MFe) layered double hydroxides (LDHs) are among the most active electrocatalysts for the alkaline oxygen evolution reaction (OER). Herein, we combine electrochemical measurements, operando X-ray scattering and absorption spectroscopy, and density functional theory (DFT) calculations to elucidate the catalytically active phase, reaction center and the OER mechanism. We provide the first direct atomic-scale evidence that, under applied anodic potentials, MFe LDHs oxidize from as-prepared $\\upalpha$ -phases to activated $\\gamma$ - phases. The OER-active $\\boldsymbol{\\upgamma}$ -phases are characterized by about $8\\%$ contraction of the lattice spacing and switching of the intercalated ions. DFT calculations reveal that the OER proceeds via a Mars van Krevelen mechanism. The flexible electronic structure of the surface Fe sites, and their synergy with nearest-neighbor M sites through formation of O-bridged Fe-M reaction centers, stabilize OER intermediates that are unfavorable on pure M-M centers and single Fe sites, fundamentally accounting for the high catalytic activity of MFe LDHs. \n\nW ater splitting to generate $\\mathrm{O}_{2}$ and $\\mathrm{H}_{2}$ has been a major focus of (photo)electrochemical energy storage and conversion research, but fundamental and practical challenges remain. In this process, $\\mathrm{O}_{2}$ generation at the anode through the oxygen evolution reaction (OER), which is inherently slower by over four orders of magnitude compared with $\\mathrm{H}_{2}$ generation, accounts for the majority of energy losses1. NiFebased layered hydroxides are the most active OER catalysts in base and are the catalysts of choice for industrial water electrolysis2–10, whereas CoFe-based layered hydroxides have comparable performance7,8,10–12. Very recently, it has been found that NiFe and CoFe (MFe) layered (oxy)hydroxides are also the common active phases of other highly active OER catalysts, including perovskite oxides13,14, spinel oxides15, phosphides16, and potentially other Co- and Ni-based OER catalysts with Fe incorporated intentionally or accidentally, such as carbides17, nitrides18, sulfides19, and selenides20, which are prone to hydrolysis and oxidation under OER conditions13,15,16,21,22. Thus, studying the reactive structures of the MFe layered double hydroxides (LDHs) under in-situ conditions and the catalytic mechanism can provide a thorough understanding of the structure–property relationships of many related catalysts and potentially lead to the design of new catalysts with further improved performance. \n\nIn spite of previous reports on the ex-situ crystal structure of the as-synthesized precursors of MFe LDH catalysts23–28 and insitu local structure based on X-ray absorption spectroscopy (XAS) measurements3,4,12,29–32, little is known about the long-range crystal structures of the catalytically active phase under OER conditions. As a result, most proposals regarding the in-situ crystal structures of NiFe and CoFe LDHs under OER conditions are indirectly inferred from the crystal structures of the host Ni and Co oxyhydroxides, respectively. More specifically, for NiFe LDH, a $\\upgamma$ -NiOOH-type phase, in which water and cations are intercalated between layers28, has long been speculated4,5,24,25,33. However, no direct evidence has been observed to confirm this hypothesis, as previous in-situ structural studies could not provide the characteristic interlayer spacing that can be used to differentiate between the $\\upgamma$ -NiOOH-type phase and other common phases, such as the anhydrous $\\upbeta$ -NiOOH-type phase28. For CoFe LDH, in analogy to NiFe LDH, a transformation to a γ- NiOOH-type phase can be hypothesized under OER conditions. However, there is no analogous $\\gamma{\\mathrm{-CoOOH}}$ phase with species intercalated between layers; the other two known $\\upbeta$ -CoOOH and $\\mathrm{CoO}_{2}$ phases show no intercalation34. As a consequence, a Fedoped $\\upbeta$ -CoOOH has been proposed as the active phase of CoFe LDH under OER conditions11,12. \n\nDensity functional theory (DFT) calculations allow us to examine all of the above hypotheses and to extract atomic-scale details by screening suitable candidate phases and comparing their relative stability with that of known phases. Although significant efforts have been made, particularly on the modeling of the electronic structure effects and catalytic mechanism of Nibased catalysts for OER4,10–12,33,35–40, such a screening and comparison has not yet been rigorously carried out because of the structural complexity of the active phases. Indeed, even the atomic-scale structure of the $\\upgamma$ -NiOOH phase itself is still unclear4,33,38. The lack of these atomic-scale details has, in turn, made it highly challenging to choose appropriate models for DFT-based mechanistic studies4,38,41. Hence, a variety of structures have been employed in the modeling, including those that resemble as-synthesized precursor phases37, $\\mathrm{NiO}^{38}$ , twodimensional single layer (oxy)hydroxides35,39, $\\upbeta$ -MOOH analogs4,10–12,42, and $\\gamma{\\mathrm{-NiOOH}}$ analogs33,40,43–45 with or without Fe dopants. Although significant efforts have been made to explain the high activity of MFe LDHs, the diversity of studies suggests that large uncertainties exist concerning the relationship between the active site structure and the catalytic mechanism. This is because the predicted activity of the catalysts is highly sensitive to, and is an ensemble of, the geometrical structure46,47 and electronic structure (oxidation state)48,49 of the active site, as well as non-covalent interactions originating from bulk crystal structure50,51, the steady state of the surface configuration52,53, and the electronic structure methods used in the calculations54–56. These uncertainties, resulting from an incomplete consideration of this ensemble of factors, have hindered the mechanistic understanding of the high activity of NiFe and CoFe LDHs for the OER, which further hampers the prediction of new catalysts with improved performance. \n\nHerein, we combine electrochemical measurements with operando wide-angle X-ray scattering (WAXS) and XAS data, as well as ab initio molecular dynamic simulations and a synergistic DFT approach that was benchmarked specifically for the strongly correlated Fe, Co, and Ni oxides and (oxy)hydroxides55, to unravel and contrast the crystal structures and electrocatalytic OER mechanisms of the active phases of NiFe and CoFe LDH catalysts. We provide the first direct atomic-scale evidence that, under OER conditions, both NiFe and CoFe LDHs transform from the as-prepared $\\mathtt{a}$ -phase to a deprotonated $\\upgamma$ -phase. The oxidative phase transitions are characterized by ${\\sim}8\\%$ contractions in both the in-plane lattice constant and the interlayer distance, which are induced by the oxidation of Fe and M (Ni, Co), and by the anion-to-cation switching of intercalated ions, respectively. We then adopt the in-situ identified $\\upgamma$ -phases to study the OER mechanism through DFT-based calculations. The calculated surface phase diagrams indicate that surface O sites are saturated with H by forming bridge OH, and undercoordinated metal sites are saturated with atop OH under OER conditions. These structures, and the associated reaction free energies, suggest that the OER proceeds via a Mars van Krevelen mechanism, starting with the oxidation of bridge OH at the Fe-M reaction centers $\\mathrm{\\Delta}\\mathrm{M}=\\mathrm{Ni}$ or $\\mathrm{Co}^{\\cdot}$ ) to form O-bridged Fe-M moieties. The flexible electronic structure of the Fe site and its synergy with the nearestneighbor M sites through the formation of the O-bridged Fe-M reaction centers fundamentally accounts for the high OER activity of MFe oxyhydroxides due to the stabilization of OER intermediates that are unfavorable on pure M-M centers and single Fe sites. Our combined operando experimental and DFT computational approach thus provides a consistent atomic-scale explanation for the high OER activity of the MFe LDHs. \n\n# Results \n\nElectrochemical oxygen evolution and surface redox chemistry. We studied the redox chemistry of NiFe LDH and CoFe LDH (M: $\\mathrm{Fe}=\\sim3{:}1$ ) using cyclic and linear sweep voltammetry (CV and LSV) and compared their OER performance with that of their Fefree hydroxide analogs, including $\\mathsf{\\beta{-}N i}(\\mathrm{OH})_{2}$ and $\\mathsf{\\beta{-C o}(O H)}_{2}$ . LSV curves (Fig. 1a) indicated that OER overpotentials at $10\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ are $+348\\mathrm{mV}$ and $+404\\mathrm{mV}$ for NiFe LDH and CoFe LDH, respectively, which makes them among the most active electrocatalysts in alkaline conditions. NiFe and CoFe LDHs also exhibited substantially higher catalytic activity than the hydroxides containing only $\\mathrm{Ni}$ and $\\mathrm{Co}$ . For NiFe LDH, the overpotential is $225\\mathrm{mV}$ lower than that of NiOOH, whereas for CoFe LDH, the corresponding overpotential is $64\\mathrm{mV}$ lower than that of CoOOH. We note that, although it is not an intrinsic metric, the overpotential measured at $10\\mathrm{\\overline{{mA}}}\\mathrm{cm}^{-2}$ from LSV is a valid practical parameter to compare the activity trends of the catalysts57. This is confirmed by the good agreement with the trends of the intrinsic activity extracted with two distinct methods (see discussion in Supplementary Methods and Supplementary Figs. 1 and 2). Also, the trend of our measurement is consistent with what was reported for electrodeposited films of similar composition7. \n\n![](images/82ac07ee38c64f93073e613fd256ccb73f5a18a9e92a3d155daa56d0ab6faa29.jpg) \nFig. 1 Surface chemistry and OER of NiFe and CoFe LDHs. a Linear sweep voltammetry of NiFe LDH (black), CoFe LDH (red), $\\mathsf{\\{B-N i(O H)}}_{2}$ (blue), and $\\upbeta$ -Co $(\\mathsf{O H})_{2}$ (green) at a scan rate of $1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in purified 0.1 M KOH by RDE (1600 r.p.m.). Catalyst loading on GC electrodes: $0.1\\mathsf{m g c m}^{-2}$ . b Stable curves obtained in cyclic voltammetry of NiFe LDH (black) and CoFe LDH (red) in 0.1 M KOH in the grazing incident cell. Redox features are indicated with capital letters. c, d Differential electrochemical mass spectrometry (DEMS) of NiFe LDH $\\mathbf{\\eta}(\\bullet)$ and CoFe LDH (d) during a linear sweep voltammetry (LSV) in $0.1M$ KOH. The faradaic current normalized by the geometric area is shown in red, whereas the mass spectrum current related to mass $m/z=32$ is shown in blue. \n\nThe CV curves in Fig. 1b indicate that both NiFe LDH and CoFe LDH undergo redox transitions prior to (or slightly overlapping with) the onset of the OER, as confirmed by differential electrochemical mass spectrometry (DEMS) by comparing the Faraday current and the mass spectrum current related to mass $m/z=32$ (Fig. 1c, d). For NiFe LDH, the $\\mathrm{{Ni(II)}}$ oxidation peak at $+1.47\\ V_{\\mathrm{RHE}}$ $(\\mathrm{A^{\\prime}})$ overlaps with the OER onset and with the corresponding reduction wave peaks at $+1.35~V_{\\mathrm{RHE}}$ $\\left(\\mathrm{B^{\\prime}}\\right)$ . For CoFe LDH, the main oxidation peak at $+1.35~V_{\\mathrm{RHE}}$ (A) occurs clearly prior to any OER onset. More anodically, a second and small oxidation shoulder at around $+1.55\\ V_{\\mathrm{RHE}}$ (C) overlaps with the OER. The broad peaks B at $+1.1\\ V_{\\mathrm{RHE}}$ and D at $+1.4\\ V_{\\mathrm{RHE}}$ constitute the corresponding reduction waves on the cathodic scan, respectively. These redox features, in turn, provide strong evidence that the active phases for OER are not the as-synthesized phases (characterized in the Supplementary Methods and Supplementary Fig. 3). \n\nTracking structural transformations during activation. To follow the phase transition of the catalysts from their assynthesized precursor state into the catalytically active states, synchrotron-based operando WAXS analysis was employed. Insitu WAXS measurements were taken in $0.1\\mathrm{M}\\mathrm{\\KOH}$ , starting from the resting state $(+1~V_{\\mathrm{RHE}})$ of the catalysts, followed by stepping the applied potential up to $+1.7\\ {V}_{\\mathrm{RHE}}$ and then back down to the resting state or even lower potentials. The scattering pattern was measured at the end of each step (i.e., Supplementary Fig. 4). The potential window ranges from values closely prior to the anodic wave of $\\mathbf{M}(\\mathrm{II})$ oxidation, reaching into the OER region and then reverting to low values to ensure the reduction to M(II). We will initially focus on the evolution of the (003) diffraction peak of the LDHs (Fig. 2a, b), which provides the characteristic interlayer distance that is absent from XAS measurements and that is central to differentiating the phases with and without intercalation of water molecules and ions. For both MFe LDHs, the evolution of the (003) peak indicates a contraction of the interlayer distance in the anodic scan and a re-expansion in the cathodic scan. The detailed interlayer distances obtained by Rietveld refinement are shown in Fig. 2c, d (additional details in Supplementary Figs. 5–9). \n\nAt the resting state and the potential before $\\mathbf{M}(\\mathrm{II})$ oxidation, the measured interlayer distances are $7.8\\mathring\\mathrm{A}$ and $7.7\\mathring\\mathrm{A}$ for NiFe and CoFe LDHs, respectively, which are typical for LDHs with intercalated water molecules and carbonate anions between the layers23–28. As these interlayer distances resemble that of $\\mathsf{a}{-}\\mathsf{N i}$ $(\\mathrm{OH})_{2}$ $(\\sim8\\mathrm{\\AA},$ , as proposed in the Bode’s diagram28,58), we named this phase the $\\mathtt{a}$ -MFe LDH. As soon as the potential increased above the $\\mathbf{M}(\\mathrm{II})$ oxidation potential, the (003) reflections shifted to shorter interlayer distances and a shoulder (Supplementary Fig. 9) started to develop at the interlayer distance of $7.2\\mathring\\mathrm{A}$ and $7.\\mathrm{\\check{1}\\AA}$ for NiFe and CoFe LDHs, respectively. These interlayer distances are much larger than those of the anhydrous $\\scriptstyle\\beta-\\mathrm{NiOOH}$ $({\\sim}4.8\\mathrm{\\AA})^{59}$ and $\\upbeta$ -CoOOH $({\\sim}4.4\\mathring\\mathrm{A})^{60}$ phases but are close to that of the hydrous $\\gamma{\\mathrm{-NiOOH}}$ phase (i.e., $\\mathrm{\\sim}7\\mathrm{\\AA})^{28,59}$ . In analogy to $\\upgamma\\cdot$ - NiOOH and previous literature $^{4,24,61}$ , we refer to these new phases as $\\upgamma$ -MFe LDHs. \n\nDuring the cathodic scan, the interlayer distances started to reexpand as the reduction to $\\mathbf{M}(\\mathrm{II})$ occurred. However, the processes depended sensitively on the nature of M. For NiFe LDH, the shoulder at the interlayer distance of $7.2\\mathring\\mathrm{A}$ ( $\\cdot\\gamma$ -phase) disappeared at the resting state, and the peak restored to the original value of $7.8\\mathring\\mathrm{A}$ (α-phase), which indicates the reversibility of the $\\mathtt{a}$ -to- $\\cdot\\gamma$ transformation. Differently, for the CoFe LDH (Fig. 2b), the re-expansion to the original value $(7.7\\mathring\\mathrm{A})$ is very limited under the resting state $(1~\\mathrm{V}_{\\mathrm{RHE}})$ and is still incomplete at lower potentials $(0.5\\ \\bar{V_{\\mathrm{RHE}}})$ . The limited reversibility occurring in CoFe LDH has also been observed during electrochemical activation treatments (Supplementary Fig. 10) and verified by ex-situ soft X-ray XAS (sXAS) (Supplementary Figs. 11 and 12). In addition, Co-based hydroxides also have shown irreversible behavior in the literature32. \n\n![](images/8995c5fc516805b93d17681f97077f36980e9600ff537c9cd6c3b9aad2b0a02f.jpg) \nFig. 2 The evolution of the interlayer spacing and the intralayer metal–metal distances of NiFe and CoFe LDHs from WAXS measurement. a, b Waterfall plot of normalized and background-subtracted (003) peak obtained during in-situ WAXS in 0.1 M KOH and potential steps for NiFe LDH (a) and CoFe LDH (b). c, d Interlayer distances for NiFe LDH (c) and CoFe LDH (d) obtained by by Rietveld refinement. Full and open symbols are used for different phases. The error bars represent the SE provided by Topas. e, f In-situ WAXS patterns for $d$ -values close to the (110) peak of NiFe LDH (e) and CoFe LDH (f) under various conditions. For NiFe LDH, the WAXS patterns at the reported potentials have been obtained by the collapsed film technique. In e, the dashed arrows point to the feature associated to the $\\boldsymbol{\\upgamma}$ -phase. $\\pmb{\\mathrm{\\_{\\delta}}}$ h Lattice parameter a, corresponding to the intralayer metal–metal distance in NiFe LDH $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ and CoFe LDH $\\mathbf{\\eta}(\\mathbf{h})$ obtained by Rietveld refinement. Full and open symbols are used for different phases. Error bars represent SD provided by Topas for the refined parameters. \n\nAfter clarifying the catalytically active phases under OER condition via the (003) reflection, we now turn to the (110) reflection representing the in-plane lattice constants (Fig. 2e, f and Supplementary Fig. 13). As the (110) reflection is much weaker than the (003), and broadened under OER conditions, extracting exact lattice parameters is non-trivial. Nonetheless, our Rietveld refinement revealed an unambiguous trend toward shorter metal–metal distances, from ${\\sim}3.1\\mathrm{\\AA}$ to $\\breve{\\sim}2.85\\mathring{\\mathrm{A}}$ upon $\\mathtt{a}$ -to- $\\upgamma$ phase transitions for both NiFe and CoFe LDHs (Fig. 2g, h). This trend agrees well with the contraction of the local metal-O and metal–metal distances in previous in-situ EXAFS measurements3,4,12,29–32. Thus, there are contractions on both interlayer distances and in-plane bonds upon the $\\mathtt{a}$ -to- $\\cdot\\gamma$ phase transition. \n\nWe note that, similar to what has been observed in previous measurements with in-situ $\\mathrm{XAS}^{31,62}$ and Mössbauer spectroscopy on NiFe-based oxyhydroxides63, only a fraction of MFe LDHs in our operando WAXS measurements undergo phase transitions under OER potentials, although the fraction is higher for CoFe than NiFe LDH (Supplementary Fig. 9). The incomplete phase transition is likely because some nanoplates in the catalyst film are not electrochemically accessible, e.g., not in contact with the electrolyte or with the external electrical circuit (see Supplementary Information for detailed discussion and Supplementary Figs. 14 and 15). This incompleteness makes the quantitative interpretation of XAS data challenging, as the measured local structures and electronic structures are weighted averages of the two phases. Thus, the ensemble-averaged structural parameters and the electronic structure do not necessarily reflect the actual crystal structure parameters and the electronic structure of a specific phase, but strongly depend on the ratio of the $\\mathfrak{a}$ -to- $\\cdot\\gamma$ phase transition. This issue is known for unsupported NiFe (oxy)hydroxide nanocataylsts31, and confirmed by our operando XAS (see Supplementary Methods, Supplementary Figs. 16–25, and Supplementary Tables 1–4). Therefore, what sets the present operando WAXS measurements apart from other ensembleaveraging approaches is their ability to probe both intrinsic local and longer-range geometric effects of specific phases, providing essential information for the identification of the active phase under OER which cannot be achieved by the experimental techniques that solely provide average local structure information. This intrinsic structural information can serve as the reference for DFT calculations to study atomic-scale geometric structures and the intrinsic electronic structure of $\\upgamma$ -MFe LDHs, which can in turn be further employed to study the catalytic mechanism for OER. We note that, while the $\\upgamma$ phase is the focus of the study, a consistent measurement of the α phase is important for establishing a general picture regarding the completeness and the reversibility of the phase transition. \n\nGeometric and electronic structures from DFT calculations. Following the order in the above experimental section, we begin by discussing the as-prepared MFe phases $(\\mathrm{M}{:}\\mathrm{Fe}=3{:}1$ , $\\mathtt{a}$ -MFe LDHs). DFT calculations indicate that $\\mathtt{a}$ -MFe LDHs adopt the structure of hydrotalcite $(\\mathrm{Mg_{6}A l_{2}C O_{3}(O H)_{16}.4H_{2}O})$ , which is the archetypical LDH material with its characteristic three layer rhombohedral structure. Hydrotalcite formation is favorable from the component (oxy)hydroxides (FeOOH, $\\mathrm{\\mathrm{M}}(\\mathrm{OH})_{2}.$ ), water (in electrolyte), and $\\mathrm{CO}_{2}$ (in atmosphere) (Supplementary Figs. $26-$ 28 and Supplementary Table 5), which highlights the reliability of the present calculations. In these $\\mathrm{M_{6}F e_{2}(C O_{3}(O H)_{16}.4H_{2}O}$ structures, $\\mathrm{Fe}^{3+}$ ions are separated by $\\mathbf{M}^{2+}$ cations within the layer, and the $_\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{C}\\bar{\\mathrm{O}}_{3}{}^{2-}$ ions are intercalated between layers in a flat configuration, interconnected through hydrogen bonds. The intercalated species are further connected with the $\\mathrm{M}_{0.75}\\mathrm{Fe}_{0.25}(\\mathrm{OH})_{2}$ sheets by accepting hydrogen bonds from the OH terminations of the sheets (see Fig. 3). The calculated interlayer distances are $7.7\\mathring\\mathrm{A}$ for both NiFe and CoFe LDHs, which is fully consistent with the measured distances of $7.7\\mathring\\mathrm{A}-7.8\\mathring\\mathrm{A}$ . The calculated in-plane lattice constants are $3.10\\mathring{\\mathrm{A}}$ and $3.15\\mathrm{\\AA}$ for NiFe and CoFe LDHs, respectively, which also fully agree with the measured WAXS values (3.11 $\\mathring\\mathrm{A}$ and $3.13\\mathrm{\\AA}.$ respectively; Fig. 2). To identify the catalytically active phases of MFe LDHs under OER conditions, we first calculated a series of structures and configurations of $\\upgamma$ -NiOOH with seven possible nominal oxidation states of Ni, varying from $^{3+}$ to $^{4+}$ , and various amounts of water molecules and ions intercalated through abinitio molecular dynamics (AIMD) simulations (see Fig. 3a, b). We then used the most plausible $\\upgamma$ -NiOOH as the basis to study the possible configuration of $\\upgamma$ -MFe LDHs. Among the structures considered, a phase with 4 water molecules and $2\\mathrm{K}^{+}$ cations intercalated between $\\mathbf{M}_{6}\\mathbf{Fe}_{2}\\mathbf{O}_{16}$ layers is the most plausible phase under OER conditions. This conclusion is suggested by the favorable formation energies from its components ((hydroxy) oxides, water, and cations in the electrolyte, see Supplementary Table 5), and by the stability under OER conditions (see Fig. 3). The interlayer distances and the in-plane lattice constants are \n\n$7.18\\mathrm{\\AA}$ and $2.84\\mathring{\\mathrm{A}}$ , respectively, for both $\\upgamma$ -type NiFe and CoFe LDH phases. These values are in excellent agreement with the measured values during OER of the MFe $\\upgamma$ -phases: $7.1\\mathrm{-}7.2\\mathring\\mathrm{A}$ and ${\\sim}2.85\\mathrm{\\AA}$ , respectively. We note that the anhydrous phases with similar overall oxidation state $(\\mathrm{M}_{0.75}\\mathrm{Fe}_{0.25}\\mathrm{OOH}_{0.25}$ and $\\mathbf{M}_{0.75}\\mathrm{Fe}_{0.25}\\mathrm{O}_{2};$ see Supplementary Table 6) exhibit a similar in-plane lattice constant, yet the interlayer distance is ${\\sim}4.6\\mathring\\mathrm{A}$ . The similarity in the in-plane lattice constants of these two distinct phases strongly suggests that local metal–metal distance alone is insufficient to accurately identify the crystal phase present under OER condition. This fact underscores that for the present catalyst systems, the operando scattering analysis is the best technique for identifying the 3D structure of the catalytically active phases. \n\nAs described above, DFT calculations indicate that under OER conditions, MFe LDHs transform from the as-synthesized phase with the stoichiometry $\\mathrm{M}_{6}\\mathrm{Fe}_{2}\\mathrm{CO}_{3}(\\mathrm{OH})_{16}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ to the $\\upgamma$ -phase with the stoichiometry $\\mathrm{M}_{6}\\mathrm{Fe}_{2}\\mathrm{K}_{2}\\mathrm{O}_{16}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ . We note that, consistent with previous measurement with Raman spectroscopy64, there are no hydroxyl groups in $\\mathbf{M}_{0.75}\\mathrm{Fe}_{0.25}\\mathbf{O}_{2}$ layers in the $\\upgamma$ -phase. The deprotonation of the hydroxyls of the $\\mathtt{a}$ -phase, in turn, breaks the hydrogen bonds that exist between them and the carbonate anions and makes the intercalation of the latter highly unfavorable. Thus, $\\mathrm{CO}_{3}{}^{2-}$ ions are expelled and $\\mathrm{K^{+}}$ ions are intercalated from the electrolyte during the $a-\\gamma$ phase transition. $\\mathrm{K^{+}}$ ions connect $\\mathrm{M}_{0.75}\\mathrm{Fe}_{0.25}\\mathrm{O}_{2}$ sheets by forming O-K-O ionic bonds in the form of zigzag chains. The channels between the zigzag $\\mathrm{K^{+}}$ chains are filled with water molecules to fully saturate the remaining oxygen atoms in the $\\mathbf{M}_{0.75}\\mathrm{Fe}_{0.25}\\mathbf{O}_{2}$ layers through the formation of O-HOH-O hydrogen bonds (see Fig. 3). Based on the intrinsic magnetic moment39, M cations are in mixed $^{3+}$ and $^{4+}$ oxidation states (see Supplementary Figs. 29 and 30, and Supplementary Table 5), which is consistent with the average oxidation states in the range of 3.0–3.7 that have been reported in the literature based on XAS measurements $4,12,31,32,61,^{\\circ}65$ . It is worth noting that, for the cases of incomplete phase transition, the measured oxidation state is a weighted average of $2+,3+.$ , and $^{4+}$ . For $\\upgamma$ -NiFe LDH, consistent with a previous assignment based on operando Mössbauer spectroscopy studies25,63,66, Fe cations are in a $^{4+}$ oxidation state (see Supplementary Fig. 29 and Supplementary Table 5). We note that, in addition to $\\mathrm{Fe^{4+}}$ , higher Fe oxidation states have already been reported in the literatur $^{\\mathsf{267-69}}$ We will show in the reaction mechanism study below that the flexible oxidation state of the Fe site, and its synergy with M sites, are responsible for the high catalytic activity of MFe LDHs. Based on the energetics (see Fig. 3), the formation probability of the $\\upgamma\\cdot$ - phase that we screened, $\\mathrm{\\bar{K}}_{1/4}(\\mathrm{H}_{2}\\mathrm{O})_{1/2}\\mathrm{MO}_{2}.$ is over three orders of magnitude higher than the $\\gamma{\\mathrm{-NiOOH}}$ analog $\\mathrm{K}_{1/3}(\\mathrm{H}_{2}\\mathrm{O})_{2/3}\\mathrm{MO}_{2}$ used in previous studies70. As the activity is sensitive to noncovalent interactions induced by the bulk structure and the electronic structure, in addition to the geometric structure and electronic structure of the active site, the $\\upgamma$ -MFe phase is used in the study of the OER mechanism below. We note that, because of the characteristic stoichiometry of the layer and atomic-scale details of the intercalated species, the $\\upgamma$ phase cannot be obtained by simply introducing various amounts of water molecules and cations into the interlayer space of the $\\upbeta$ -MOOH analogs used in the literature. Further, as we demonstrate below, correct determination of the OER mechanism requires not only an accurate treatment of the bulk catalyst structure, but also a complete consideration of all key factors that have been missed in previous models, including the geometry, oxidation states, and adsorbate coverages on the catalyst surface. \n\nThe catalytic oxygen evolution reaction mechanism. Beginning with the elucidated bulk structures described above, we evaluated the steady state of the (01–10) surface of $\\upgamma$ -NiOOH, $\\upgamma$ -NiFe LDH, and $\\upgamma$ -CoFe LDH through surface phase diagrams, then calculated the reaction free energy diagram of oxygen redox $\\mathrm{(4OH^{-}+}$ $^{*}\\longleftrightarrow30\\mathrm{H}^{-}+\\mathrm{OH}^{*}+\\mathrm{e}^{-}\\longleftrightarrow2\\mathrm{OH}^{-}+{\\mathrm{O}}^{*}+\\mathrm{H}_{2}\\mathrm{O}+2\\mathrm{e}^{-}\\longrightarrow\\mathrm{OH}^{-}$ $+\\mathrm{OOH^{*}}+\\mathrm{H}_{2}\\mathrm{O}+3\\mathrm{e}^{-}{\\longrightarrow}\\mathrm{O}_{2}+2\\mathrm{H}_{2}\\mathrm{O}+4\\mathrm{e}^{-}+^{*})$ (see Fig. 4, Supplementary Figs. 31–41, and Supplementary Tables 7–11). We have focused on the reaction of the surface oxygen species and neglected the potential involvement of lattice oxygen, because recent isotope experiments suggest that the latter is not favorable for these specific systems2. We selected the (01–10) surface, because it belongs to the family of surfaces that are exposed at the edge of catalyst sheets, and thus widely used to study the catalytic activity of layered materials4,11,33,40,71. \n\n![](images/55f999b3693bf9d436fa02a7c865e3b095f2df9e99306a00000fa4cf510144bc.jpg) \nFig. 3 Screening process, structures, and stability (phase diagram) of NiFe LDH. a The relative energy of $\\boldsymbol{\\upgamma}$ -NiOOH $(\\mathsf{N i}_{8}{\\mathsf{O}}_{16}{\\mathsf{K}}_{2}{\\cdot}4{\\mathsf{H}}_{2}{\\mathsf{O}})$ at each picosecond of the AIMD simulation, which is used to screen the most stable configuration (at the 5th ps) of this specific stoichiometry. The inset is the energy evolution during the entire AIMD simulation. b Free energy of formation of a series of possible $\\boldsymbol{\\upgamma}$ -NiOOH structures with various amounts of water and ions intercalated between the NiOOH or $N i O_{2}$ layers. Each point is based on the most stable configuration of an AIMD simulation. For example, $N i0_{2^{-}}(2\\times4)$ $-2k-4H_{2}O$ is from the 5th ps simulation of $N i_{8}O_{16}K_{2}\\cdot4H_{2}O$ in A, which is then used to study the possible configuration of $\\boldsymbol{\\upgamma}$ -NiFe LDH. c Side, top, and bottom views of the $\\upalpha$ -NiFe $\\mathsf{L D H}$ ; d stability of $\\scriptstyle\\mathbf{\\alpha}\\mathbf{-}$ and $\\boldsymbol{\\upgamma}$ -NiFe LDH; e side, top, and bottom views of the $\\boldsymbol{\\upgamma}$ -NiFe LDH. The structural parameters of $\\alpha\\cdot$ and $\\boldsymbol{\\upgamma}$ -NiFe LDH are also given. \n\nThe calculated surface phase diagrams indicate that, under OER conditions, undercoordinated surface O sites are saturated with H by forming bridge OH species, and undercoordinated metal sites are saturated with atop OH when the surface is in equilibrium with the electrolyte and in steady state (see Fig. 4). Thus, we analyze the reaction free energy with a Mars van Krevelen-type mechanism, for which the reactions start from the deprotonation of the surface OH of the in-situ surface phase, instead of starting from OH adsorption, as has generally been assumed in many previous studies (to further motivate this choice, see the comparison with the reaction free energies of the conventional mechanism on two artificial surface models in the Supplementary Materials). For the Mars van Krevelen mechanism, we have found that the oxidation of two-metal coordinated bridge OH moieties is more favorable than that of one-metal coordinated atop OH due to the synergy of the two nearestneighbor metal sites in stabilizing the potential limiting OER reaction intermediates $\\mathrm{\\nabla{[}0^{*}}$ radials) by forming an O-bridged reaction center (see Fig. 4 and Supplementary Methods for details). Thus, we have focused our discussion below on the synergistic bridge OH oxidation pathway. \n\nThe highest reaction free energy barriers $(\\Delta G_{\\mathrm{a}})$ on $\\upgamma$ -NiOOH, $\\upgamma$ -CoFe, and $\\upgamma$ -NiFe oxyhydroxide surfaces are $1.90\\mathrm{eV}$ , $1.71\\mathrm{eV}$ , and $1.68\\mathrm{eV}$ (see Fig. 4c and Supplementary Figs. 31, 33, and 38), respectively, which implies overpotentials $(\\eta)$ of $0.67\\mathrm{V},\\ 0.48\\mathrm{V},$ . and $0.45\\mathrm{V}$ $(\\eta=(\\Delta G_{\\mathrm{a}}-1.23\\mathrm{eV})\\bar{/}\\mathrm{e})$ . The calculated overpotentials are semi-quantitatively consistent with the present measurements at $10\\mathrm{mA}\\mathrm{\\bar{c}}\\mathrm{m}^{-2}$ , $0.57\\dot{\\mathrm{V}}$ , $0.40\\mathrm{V}_{:}$ , and $0.35\\mathrm{V}$ , respectively, and with general trends in the literature. For $\\gamma{\\mathrm{-NiOOH}}$ and $\\upgamma$ -NiFe LDH, ${\\bar{\\mathrm{OH}}}^{*}$ deprotonation during the OER cycle has the highest free energy barrier, which forms the potential limiting step, followed by ${\\mathrm{OOH}}^{*}$ deprotonation. On the $\\gamma{\\mathrm{-NiOOH}}$ surface, bridge OH $(\\mathrm{Ni^{3+}{\\mathrm{-OH-}}\\bar{N}i^{4+}})$ deprotonation at $1.90{\\mathrm{V}}$ is accompanied by $\\mathrm{Ni}^{3+}$ oxidation to $\\mathrm{Ni^{4\\bar{+}}}$ , as characterized by the change of Ni magnetic moment from $1\\mu_{\\mathrm{{B}}}$ to $0\\mu_{\\mathrm{B}}$ . On the other hand, on the $\\upgamma$ -NiFe LDH surface, bridge OH $\\mathrm{(Fe^{4+}\\mathrm{-OH-Ni^{3+}})}$ ) deprotonation at $1.68\\mathrm{V}$ is accompanied by $\\mathrm{Fe^{4+}}$ oxidation (as characterized by the change of Fe magnetic moment, see Fig. 4), whereas the oxidation state of Ni is constant. Clearly, it is more feasible for Fe than Ni to be oxidized to a higher oxidation state, which stabilizes ${{\\mathrm{O}}^{*}}$ intermediates at the Fe-Ni reaction center compared with that at the Ni-Ni reaction center, and consequently lowers the free energy barrier of ${\\mathrm{OH}}^{*}$ oxidation to ${{\\mathrm{O}}^{*}}$ , the potential limiting step. Our calculations indicate that it is also the case for the other $\\upgamma$ -NiFe configurations with comparable energies that could coexist under the reaction conditions (see Supplementary Table 9). \n\n![](images/05b8fd82e2b787494b7bb14159ba1fe7de019a86fdd18000c90182949b74313d.jpg) \nFig. 4 OER mechanism on the $\\pmb{\\upgamma}$ -phase of MFe LDHs. a Structures of different surface phases and OER intermediates; adsorbates of surface phases are highlighted by blue circles on the sides views, and OER intermediates are differentiated by colors (yellow instead of white for hydrogen and rose instead of red for oxygen, respectively). A dashed rose circle indicates the formation of a surface O vacancy. The reaction centers are highlighted by large white circles. The magnetic moments of Ni and Fe during OER are also given on the top views. b Surface phase diagram of of $y-N i O O H$ , $\\gamma$ -NiFe LDH, and $\\boldsymbol{\\upgamma}$ -CoFe LDH. The representative surface phases are given in a. c Reaction free-energy diagrams for OER on $\\boldsymbol{\\upgamma}$ -NiOOH, $\\boldsymbol{\\upgamma}$ -NiFe LDH, and $\\boldsymbol{\\upgamma}$ -CoFe LDH; the potential limiting steps and the overpotentials are also given. d Volcano plot of the OER overpotential as a function of Gibbs free energies of the reaction intermediates. \n\nIt is worth noting that this stabilization effect is also valid and even stronger on single Fe sites as compared with single Ni sites $(0.73\\mathrm{eV}$ for the stabilization on single site vs. $0.22\\mathrm{\\bar{e}V}$ for the stabilization at the Fe-Ni center), as also observed in previous studies $(0.4\\mathrm{-}0.5\\mathrm{eV})^{33,43}$ . However, there is a fundamental difference between the synergistic stabilization through the FeNi reaction center and the stabilization through the single Fe site, with the former being over five orders of magnitude more active than the latter toward OER on NiFe LDH (see Supplementary Figs. 33 and 34). Similar synergy of two nearest-neighbor metal sites (reaction center) and flexibility of Fe site oxidation are also found on $\\upgamma$ -CoFe LDH, for which the stabilization effect is so significant that bridge OH $(\\mathrm{Fe^{4+}{-}O H{-}C o^{4+}})$ deprotonation and the accompanied $\\mathrm{Fe^{\\tilde{4}+}}$ oxidation is not the potential limiting step anymore. Instead, ${\\mathrm{OOH^{*}}}$ deprotonation to $\\mathrm{\\Gamma}_{\\mathrm{{O}_{2}(\\mathrm{{g})+}}}$ vacancy (with a $1.7\\mathrm{eV}$ free-energy barrier) becomes the potential limiting step. On pure Co sites of $\\upgamma$ -CoFe LDH, ${\\mathrm{OOH}}^{*}$ deprotonation is also the potential limiting step but with higher overpotential (at \n\n$1.83\\mathrm{V})$ because of the more unfavorable O vacancy formation. Therefore, in addition to the ${{\\mathrm{O}}^{*}}$ intermediate, the reaction center also can stabilize O vacancies in CoFe LDH through synergy and the flexible electronic structure of Fe. However, the stabilization effect on the O vacancy formation does not seem large enough to make $\\upgamma$ -CoFe LDH more active than $\\upgamma$ -NiFe LDH, whereas the stabilization of ${{\\mathrm{O}}^{*}}$ by the introduction of Fe is beneficial in both catalysts, resulting in a small difference in activity. As a consequence, the overpotentials on NiFe and CoFe LDH are only modestly $(0.14\\mathrm{-}0.22\\mathrm{V})$ higher than the optimal overpotential that is constrained by the scaling relationship (the scaling relationship of ${\\mathrm{OOH^{*}}}$ intermediate and ${\\mathrm{OH}}^{*}$ intermediate, which is $2.95\\mathrm{eV}$ in the present work, leads to an optimal overpotential of $0.25\\mathrm{V})^{72}$ . Such a constraint also implies that the OER overpotential of LDHs can be modestly improved by further stabilizing ${{\\cal O}^{*}}$ intermediates and surface O vacancies at the reaction centers simultaneously, perhaps with a more redoxflexible metal than Fe, or significantly improved by breaking the ${\\mathrm{OOH^{*}}}$ vs. $\\mathrm{OH^{*}}$ scaling relationship. \n\n# Discussion \n\nNiFe and CoFe LDHs are the archetypes of high-performing electrocatalysts for oxygen evolution in alkaline conditions. In the current work, we have identified the crystal structures of the active phase and the reaction mechanism by combining operando experiments, rigorous DFT calculations, and self-consistent mechanistic studies. We have found that, under applied anodic potentials, both NiFe and CoFe LDHs transform from the as-prepared $\\mathfrak{a}$ -phase to the active $\\upgamma$ -phase. In comparison with the as-prepared phase, with an interlayer distance of $\\mathrm{\\dot{7}.7\\AA}$ and an in-plane lattice constant of $3.1\\mathring\\mathrm{A}$ , the catalytically active phases are characterized by a compression of both lattice spacings to 7.1 $\\mathring\\mathrm{A}$ and $2.8\\mathring{\\mathrm{A}},$ respectively. These values were extracted from operando WAXS measurements and are also supported by DFT calculations. Although the latter is induced by the oxidation of both ${\\mathrm{Fe}}(\\mathrm{III})$ and $\\mathbf{M}(\\mathbf{\\bar{II}})$ , the former is related to the swapping of intercalated ions with $\\mathrm{K^{+}}$ , which is essential in identifying the crystal structure of the active phases and cannot be accessed experimentally with other local structure-based techniques. Thus, the combination of DFT and operando WAXS confirms a long speculated hypothesis regarding the crystal structure of NiFe LDH under OER conditions and disprove previous assumptions of the crystal structure of CoFe LDH, while, more importantly, providing key atomic-scale details of the in-situ phases for the study of the catalytic mechanism through DFT calculations. Our calculations demonstrate that OER proceeds with a Mars van Krevelen-type mechanism on these surfaces. The flexible electronic structure of the Fe sites and their synergy with the nearestneighbor $\\mathbf{M}$ sites $\\mathbf{\\langleM=Ni}$ or Co) through forming O-bridged Fe-M reaction centers stabilize OER intermediates that are unfavorable on M-M centers and pure Fe sites. This synergistic reaction center fundamentally accounts for the experimentally observed low overpotentials of MFe for OER. The present study suggests that doping oxides with additional redox-flexible metals to form active reaction centers through the synergy with nearestneighbor metal sites constitutes a general design principle for the synthesis of new OER catalysts design with improved catalytic performance. \n\n# Methods \n\nSynthesis. NiFe LDH $\\mathrm{'Ni}:\\mathrm{Fe}=3.55:1\\$ ) was synthesized by a previously reported solvothermal route in an autoclave73. CoFe LDH $\\begin{array}{r}{(\\mathrm{Co};\\mathrm{Fe}=3.33{:}1)}\\end{array}$ was synthesized by using co-precipitation followed by a solvothermal treatment in an autoclave. Ni $(\\mathrm{OH})_{2}$ was synthesized using a two-step synthesis consisting of a precipitation step and a subsequent hydrothermal treatment. $\\beta\\mathrm{-Co}(\\mathrm{OH})_{2}$ was synthesized by a similar process as that described by Ma et al.74 based on homogeneous precipitation. Further details are available in the Supplementary Information. \n\nRDE measurements and DEMS. RDE electrochemical experiments were performed in a three-compartment glass cell with a rotating disk electrode (RDE, $5\\mathrm{mm}$ in diameter of GC, Pine Instrument) and a potentiostat (Gamry) at room temperature. A $\\mathrm{\\Pt}$ -mesh and a Hydroflex reversible hydrogen electrode (RHE, Gaskatel) were used as counter electrode and reference electrode, respectively. The electrolytes were prepared with KOH pellets (semiconductor grade, $99.99\\%$ trace metals basis, Aldrich) and MilliQ water, and were further purified75,76. The catalyst was deposited on the GC by drop casting from an ink based on isopropanol/water solution with Nafion as a binder. The catalyst loading was $0.1\\mathrm{mg}\\mathrm{cm}^{-2}$ . The detailed protocol is provided in Supplementary Methods. \n\nDEMS measurements were performed using dual thin-layer electrochemical flow cell (see Supplementary Methods for details) with nitrogen-saturated electrolyte $0.1\\mathrm{{M}}$ KOH. \n\nIn-situ WAXS and Rietveld refinement. The electrodes used for in-situ WAXS were prepared similarly as for the RDE measurements. A home-made grazing incident cell (Supplementary Fig. 4) based on a thin-layer concept was used with a polyether ether ketone foil covering the top part of the cell as X-Ray window77. KOH (0.1 M) was used as electrolyte. In-situ WAXS experiments have been conducted at the ID31 beamline of the European Synchrotron Radiation Facility (Grenoble, France), using hard $\\mathrm{x}$ -rays with a monochromatized beam (60–77 KeV). The electrochemical protocol consisted in keeping the sample first at the potential of $1\\ V_{\\mathrm{RHE}}$ after electrolyte injection (wet condition), recording electrochemical impedance spectroscopy, conducting an activation procedure by CV, and potential steps of ${\\sim}10\\mathrm{min}$ for the regular measurements ( $40\\mathrm{min}$ for collapsed film technique explained in the in-situ WAXS section in the Supplementary Methods) from resting state, before the $\\mathbf{M}(\\mathrm{II})$ oxidation $\\mathbf{M}=\\mathbf{Ni}$ or $\\mathrm{Co}$ ), to OER potentials and back in the cathodic direction well below the reduction potential to M(II). The (003) and (110) peaks were fitted by Pseudo-Voigt functions in the preliminary analysis, after background subtraction. Rietveld refinement was performed on selected potentials. The hydrotalcite structure with space group $\\ensuremath{\\mathrm{R}}\\ensuremath{-}3\\ensuremath{\\mathrm{m}}$ was used as a model for both the \n\nLDH materials and for both the as-prepared and oxidized phases. For full details, see the Supplementary Information. \n\nOperando XAS. Operando XAS measurements were performed at the BL22 CLAESS beamline at ALBA light source (Barcelona, Spain) in fluorescence mode using a silicon drift diode detector. A home-made electrochemical cell was employed. A platinum mesh and leak-free $\\mathrm{\\Ag/AgCl}$ electrode were used as counter and reference electrode, respectively. The powder samples were deposited on graphite paper discs (Toray Carbon Paper TP-060, Quintech) by filtration from a slurry of the sample in ethanol containing Nafion $(0.1\\mathrm{v}/\\mathrm{v}\\ \\%)$ as a binding agent. The paper discs were mounted in the operando cell so that the unmodified side was facing out, whereas the side containing the catalyst layer was in contact with the electrolyte. The electrochemical conditions were identical to those described for insitu WAXS measurements. \n\nDFT calculation parameters. Self-consistent, periodic DFT calculations were performed with the projected augmented wave method, as implemented in the Vienna Ab-initio Simulation Package. To generate highly accurate electrochemical stability diagrams, we employ a recently developed approach55, which includes the use of a Hubbard U term, a van der Waals functional $\\mathrm{(optPBE)^{78}}$ , and the use of a water-based reference state for the calculations. $U.$ -values, which are applied to $d$ -orbitals of Fe, Co, and $\\mathrm{\\DeltaNi}$ are taken as 2.56, 3.50, and $5.20\\mathrm{eV}$ , respectively. For cell shape and volume relaxations of (hydroxy)oxide compounds, a cutoff energy of $500\\mathrm{eV}$ is used for the planewave expansion. For the calculations that do not involve cell optimization, a cutoff energy of $400\\mathrm{eV}$ is employed. Monkhorst–Pack k-point grids are used for Brillouin zone integration. A $(2\\times4\\times1)$ and a $(2\\times4\\times3)$ k-point grid are employed for $a-$ and $\\upgamma$ -phase of LDH with R3 and R1 symmetry, respectively. For the other bulk and surface calculations, equivalent or denser $\\mathbf{k}$ -point grids are utilized. An orthorhombic box $(14\\times15\\times16)\\mathring{\\mathrm{A}}^{3}$ and a single $\\mathbf{k}$ -point (0.25, 0.25, 0.25) for the Brillouin zone sampling are used for gas phase species. The equilibrium geometries are obtained when the maximum atomic forces are smaller than $0.01\\mathrm{eV}/\\bar{\\mathrm{A}}$ and when a total energy convergence of $10^{-5}\\mathrm{eV}$ is achieved for the electronic self-consistent field loop. AIMD simulations are performed at $400\\mathrm{K}$ and quenched down to $0\\mathrm{K}$ every 1 ps with a total simulation time of $10\\mathrm{ps}$ . To evaluate the solvation energy of OER intermediates (see Supplementary Table 11), vacuum between the slab and the images is filled with liquid water with a thickness that is equivalent to five water bilayers. Then AIMD simulations are performed with the same protocols and time scales as that described above. \n\n# Data availability. \n\nThe data supporting the findings of this study are available within this Article and its Supplementary Information files, or from the corresponding author upon reasonable request. The Supplementary Information contains descriptions of methods, discussions on physicochemical characterization of as-prepared MFe LDH, intermediate phases, size of coherently scattering domains, operando XAS, ex-situ sXAS, and DFT calculation. It also includes Supplementary Figs. 1–41 and Supplementary Tables 1–11. \n\nReceived: 30 March 2020; Accepted: 21 April 2020; Published online: 20 May 2020 \n\n# References \n\n1. McCrory, C. C. L. et al. Benchmarking hydrogen evolving reaction and oxygen evolving reaction electrocatalysts for solar water splitting devices. J. Am. Chem. Soc. 137, 4347–4357 (2015). \n2. Roy, C. et al. Impact of nanoparticle size and lattice oxygen on water oxidation on NiFeOxHy. Nat. Catal. 1, 820–829 (2018). \n3. Dresp, S. et al. Direct electrolytic splitting of seawater: activity, selectivity, degradation, and recovery studied from the molecular catalyst structure to the electrolyzer cell level. Adv. Energy Mater. 8, 1800338 (2018). \n4. Friebel, D. et al. Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting. J. Am. Chem. Soc. 137, 1305–1313 (2015). \n5. Trotochaud, L., Young, S. L., Ranney, J. K. & Boettcher, S. W. Nickel–iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation. J. Am. Chem. Soc. 136, 6744–6753 (2014). \n6. Gong, M. et al. An advanced Ni-Fe layered double hydroxide electrocatalyst for water oxidation. J. Am. Chem. Soc. 135, 8452–8455 (2013). \n7. Burke, M. S. et al. Revised oxygen evolution reaction activity trends for firstrow transition-metal (Oxy)hydroxides in alkaline media. J. Phys. Chem. Lett. 6, 3737–3742 (2015). \n8. Dionigi, F. & Strasser, P. NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes. Adv. Energy Mater. 6, 1600621 (2016). \n9. Hoang, T. T. H. & Gewirth, A. A. High activity oxygen evolution reaction catalysts from additive-controlled electrodeposited Ni and NiFe films. ACS Catal. 6, 1159–1164 (2016). \n10. Stevens, M. B. et al. Ternary Ni-Co-Fe oxyhydroxide oxygen evolution catalysts: Intrinsic activity trends, electrical conductivity, and electronic band structure. Nano Res. 12, 2288–2295 (2019). \n11. Zhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n12. Enman, L. J. et al. Operando X-ray absorption spectroscopy shows iron oxidation is concurrent with oxygen evolution in cobalt–iron (oxy)hydroxide electrocatalysts. Angew. Chem. Int. Ed. 57, 12840–12844 (2018). \n13. Risch, M. et al. Structural changes of cobalt-based perovskites upon water oxidation investigated by EXAFS. J. Phys. Chem. C. 117, 8628–8635 (2013). \n14. Fabbri, E. et al. Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting. Nat. Mater. 16, 925 (2017). \n15. Calvillo, L. et al. Insights into the durability of Co-Fe spinel oxygen evolution electrocatalysts via operando studies of the catalyst structure. J. Mater. Chem. A 6, 7034–7041 (2018). \n16. Zhang, B. W., Lui, Y. H., Zhou, L., Tang, X. H. & Hu, S. An alkaline electroactivated Fe-Ni phosphide nanoparticle-stack array for high-performance oxygen evolution under alkaline and neutral conditions. J. Mater. Chem. A 5, \n13329–13335 (2017). \n17. Kun, X. et al. Dual electrical‐behavior regulation on electrocatalysts realizing enhanced electrochemical water oxidation. Adv. Mater. 28, 3326–3332 (2016). \n18. Yongqi, Z. et al. Rapid synthesis of cobalt nitride nanowires: highly efficient and low‐cost catalysts for oxygen evolution. Angew. Chem. Int. Ed. 55, \n8670–8674 (2016). \n19. Yu, C. et al. An electrocatalyst with anti-oxidized capability for overall water splitting. Nano Res. 11, 3411–3418 (2018). \n20. Zhang, J.-Y. et al. Rational design of cobalt–iron selenides for highly efficient electrochemical water oxidation. ACS Appl. Mater. Interfaces 9, 33833–33840 (2017). \n21. Fabbri, E. et al. Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting. Nat. Mater. 16, 925–92 (2017). \n22. Zhuang, Z., Sheng, W. & Yan, Y. Synthesis of monodispere Au@Co3O4 coreshell nanocrystals and their enhanced catalytic activity for oxygen evolution reaction. Adv. Mater. 26, 3950–3955 (2014). \n23. Ma, R., Liang, J., Liu, X. & Sasaki, T. General insights into structural evolution of layered double hydroxide: underlying aspects in topochemical transformation from brucite to layered double hydroxide. J. Am. Chem. Soc. \n134, 19915–19921 (2012). \n24. Demourguesguerlou, L., Braconnier, J. J. & Delmas, C. Iron-substituted nickel oxyhydroxides and hydroxides obtained by Chimie-Douce. J. Solid State Chem. 104, 359–367 (1993). \n25. Demourguesguerlou, L., Fournes, L. & Delmas, C. On the iron oxidation-state in the iron-substituted gamma-nickel oxyhydroxides. J. Solid State Chem. 114, \n6–14 (1995). \n26. Batchellor, A. S., Kwon, G., Laskowski, F. A. L., Tiede, D. M. & Boettcher, S. W. Domain structures of Ni and NiFe (oxy)hydroxide oxygen-evolution catalysts from X-ray pair distribution function analysis. J. Phys. Chem. C. 121, \n25421–25429 (2017). \n27. Hunter, B. M., Hieringer, W., Winkler, J. R., Gray, H. B. & Muller, A. M. Effect of interlayer anions on [NiFe]-LDH nanosheet water oxidation activity. Energy Environ. Sci. 9, 1734–1743 (2016). \n28. Doyle, R. L., Godwin, I. J., Brandon, M. P. & Lyons, M. E. G. Redox and electrochemical water splitting catalytic properties of hydrated metal oxide modified electrodes. Phys. Chem. Chem. Phys. 15, 13737–13783 (2013). \n29. Görlin, M. et al. Oxygen evolution reaction dynamics, Faradaic charge efficiency, and the active metal redox states of Ni–Fe oxide water splitting electrocatalysts. J. Am. Chem. Soc. 138, 5603–5614 (2016). \n30. Bates, M. K., Jia, Q., Doan, H., Liang, W. & Mukerjee, S. Charge-transfer effects in Ni–Fe and Ni–Fe–Co mixed-metal oxides for the alkaline oxygen evolution reaction. ACS Catal. 6, 155–161 (2016). \n31. Gorlin, M. et al. Tracking catalyst redox states and reaction dynamics in Ni-Fe oxyhydroxide oxygen evolution reaction electrocatalysts: the role of catalyst support and electrolyte pH. J. Am. Chem. Soc. 139, 2070–2082 (2017). \n32. Smith, R. D. L. et al. Spectroscopic identification of active sites for the oxygen evolution reaction on iron-cobalt oxides. Nat. Commun. 8, 2022 (2017). \n33. Xiao, H., Shin, H. & Goddard, W. A. Synergy between Fe and Ni in the optimal performance of (Ni,Fe)OOH catalysts for the oxygen evolution reaction. Proc. Natl Acad. Sci. USA 115, 5872–5877 (2018). \n34. Bajdich, M., Garcia-Mota, M., Vojvodic, A., Norskov, J. K. & Bell, A. T. Theoretical investigation of the activity of cobalt oxides for the electrochemical oxidation of water. J. Am. Chem. Soc. 135, 13521–13530 (2013). \n35. Zaffran, J. & Toroker, M. C. Understanding the oxygen evolution reaction on a two-dimensional $\\mathrm{NiO}_{2}$ catalyst. ChemElectroChem 4, 2764–2770 (2017). \n36. Nagli, M. & Caspary Toroker, M. Communication: nickel hydroxide as an exceptional deviation from the quantum size effect. J. Chem. Phys. 149, 141103 (2018). \n37. Zhang, J. et al. Single-atom Au/NiFe layered double hydroxide electrocatalyst: probing the origin of activity for oxygen evolution reaction. J. Am. Chem. Soc. 140, 3876–3879 (2018). \n38. Diaz-Morales, O., Ledezma-Yanez, I., Koper, M. T. M. & Calle-Vallejo, F. Guidelines for the rational design of Ni-based double hydroxide electrocatalysts for the oxygen evolution reaction. Acs Catal. 5, 5380–5387 (2015). \n39. Goldsmith, Z. K. et al. Characterization of NiFe oxyhydroxide electrocatalysts by integrated electronic structure calculations and spectroelectrochemistry. Proc. Natl Acad. Sci. USA 114, 3050–3055 (2017). \n40. Li, Y. F. & Selloni, A. Mechanism and activity of water oxidation on selected surfaces of pure and Fe-doped NiOx. Acs Catal. 4, 1148–1153 (2014). \n41. Tripkovic, V., Hansen, H. A. & Vegge, T. From 3D to 2D Co and Ni oxyhydroxide catalysts: elucidation of the active site and influence of doping on the oxygen evolution activity. ACS Catal. 7, 8558–8571 (2017). \n42. Martirez, J. M. P. & Carter, E. A. Unraveling oxygen evolution on iron-doped beta-nickel oxyhydroxide: the key role of highly active molecular-like sites. J. Am. Chem. Soc. 141, 693–705 (2019). \n43. Shin, H., Xiao, H. & Goddard, W. A. In silico discovery of new dopants for Fedoped Ni oxyhydroxide (Ni1–xFexOOH) catalysts for oxygen evolution reaction. J. Am. Chem. Soc. 140, 6745–6748 (2018). \n44. Zaffran, J. et al. Influence of electrolyte cations on Ni(Fe)OOH catalyzed oxygen evolution reaction. Chem. Mater. 29, 4761–4767 (2017). \n45. Baker, J. G. et al. The role of aluminum in promoting Ni-Fe-OOH electrocatalysts for the oxygen evolution reaction. ACS Appl Energ. Mater. 2, 3488–3499 (2019). \n46. Liu, J.-X., Su, H.-Y., Sun, D.-P., Zhang, B.-Y. & Li, W.-X. Crystallographic dependence of CO activation on cobalt catalysts: HCP versus FCC. J. Am. Chem. Soc. 135, 16284–16287 (2013). \n47. Li, H., Li, Y., Koper, M. T. M. & Calle-Vallejo, F. Bond-making and breaking between carbon, nitrogen, and oxygen in electrocatalysis. J. Am. Chem. Soc. 136, 15694–15701 (2014). \n48. Hammer, B. & Nørskov, J. K. in Advances in Catalysis 45, 71–129 (Academic Press, Inc., 2000). \n49. Lee, Y.-L., Kleis, J., Rossmeisl, J., Shao-Horn, Y. & Morgan, D. Prediction of solid oxide fuel cell cathode activity with first-principles descriptors. Energy Environ. Sci. 4, 3966–3970 (2011). \n50. Strmcnik, D. et al. The role of non-covalent interactions in electrocatalytic fuel-cell reactions on platinum. Nat. Chem. 1, 466–472 (2009). \n51. Li, H., Xiao, J., Fu, Q. & Bao, X. Confined catalysis under two-dimensional materials. Proc. Natl Acad. Sci. USA 114, 5930–5934 (2017). \n52. Reuter, K., Frenkel, D. & Scheffler, M. The steady state of heterogeneous catalysis, studied by first-principles statistical mechanics. Phys. Rev. Lett. 93, 116105 (2004). \n53. Wang, S., Vorotnikov, V. & Vlachos, D. G. Coverage-induced conformational effects on activity and selectivity: hydrogenation and decarbonylation of furfural on Pd(111). ACS Catal. 5, 104–112 (2015). \n54. Hensley, A. J. R. et al. DFT-based method for more accurate adsorption energies: an adaptive sum of energies from RPBE and vdW density functionals. J. Phys. Chem. C. 121, 4937–4945 (2017). \n55. Zeng, Z. et al. Towards first principles-based prediction of highly accurate electrochemical Pourbaix diagrams. J. Phys. Chem. C. 119, 18177–18187 (2015). \n56. Zaffran, J. & Toroker, M. C. Benchmarking density functional theory based methods to model NiOOH material properties: Hubbard and van der Waals corrections vs hybrid functionals. J. Chem. Theory Comput. 12, 3807–3812 (2016). \n57. Wei, C. & Xu, Z. J. The comprehensive understanding of as an evaluation parameter for electrochemical water splitting. Small Methods 2, 1800168 (2018). \n58. Bode, H., Dehmelt, K. & Witte, J. Zur kenntnis der nickelhydroxidelektrode— I.Über das nickel (II)-hydroxidhydrat. Electrochim. Acta 11, 1079–1087 (1966). \n59. Oskar, G. & Josef, E. Die Struktur höherer Nickelhydroxyde. Z. f.ür. anorganische Chem. 261, 43–51 (1950). \n60. Delaplane, R. G., Ibers, J. A., Ferraro, J. R. & Rush, J. J. Diffraction and spectroscopic studies of the cobaltic acid system $\\mathrm{HCoC}_{2}–\\mathrm{DCoO}_{2}$ . J. Chem. Phys. 50, 1920–1927 (1969). \n61. Wang, D. et al. In situ X-ray absorption near-edge structure study of advanced $\\mathrm{NiFe(OH)x}$ electrocatalyst on carbon paper for water oxidation. J. Phys. Chem. C. 119, 19573–19583 (2015). \n62. Gonzalez-Flores, D. et al. Nickel-iron catalysts for electrochemical water oxidation - redox synergism investigated by in situ X-ray spectroscopy with millisecond time resolution. Sustain. Energ. Fuels 2, 1986–1994 (2018). \n63. Chen, J. Y. C. et al. Operando analysis of NiFe and Fe oxyhydroxide electrocatalysts for water oxidation: detection of $\\mathrm{Fe4+}$ by Mössbauer spectroscopy. J. Am. Chem. Soc. 137, 15090–15093 (2015). \n64. Louie, M. W. & Bell, A. T. An investigation of thin-film Ni–Fe oxide catalysts for the electrochemical evolution of oxygen. J. Am. Chem. Soc. 135, 12329–12337 (2013). \n65. Risch, M. et al. Water oxidation by amorphous cobalt-based oxides: in situ tracking of redox transitions and mode of catalysis. Energy Environ. Sci. 8, 661–674 (2015). \n66. Corrigan, D. A. The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes. J. Electrochem. Soc. 134, 377–384 (1987). \n67. Berry, J. F. et al. An octahedral coordination complex of iron(VI). Science 312, 1937–1941 (2006). \n68. Riedel, S. & Kaupp, M. The highest oxidation states of the transition metal elements. Coord. Chem. Rev. 253, 606–624 (2009). \n69. Hunter, B. M. et al. Trapping an iron(VI) water-splitting intermediate in nonaqueous media. Joule 2, 747–763 (2018). \n70. Van der Ven, A., Morgan, D., Meng, Y. S. & Ceder, G. Phase stability of nickel hydroxides and oxyhydroxides. J. Electrochem. Soc. 153, A210–A215 (2006). \n71. Wang, H. et al. Transition-metal doped edge sites in vertically aligned MoS2 catalysts for enhanced hydrogen evolution. Nano Res. 8, 566–575 (2015). \n72. Man, I. C. et al. Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem 3, 1159–1165 (2011). \n73. Dionigi, F., Reier, T., Pawolek, Z., Gliech, M. & Strasser, P. Design criteria, operating conditions, and nickel-iron hydroxide catalyst materials for selective seawater electrolysis. Chemsuschem 9, 962–972 (2016). \n74. Ma, R. et al. Topochemical synthesis of monometallic $(\\mathrm{Co}2+\\mathrm{-}\\mathrm{Co}3+)$ layered double hydroxide and its exfoliation into positively charged $\\mathrm{Co}(\\mathrm{OH})2$ nanosheets. Angew. Chem. Int. Ed. Engl. 47, 86–89 (2008). \n75. Trotochaud, L., Young, S. L., Ranney, J. K. & Boettcher, S. W. Nickel-iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation. J. Am. Chem. Soc. 136, 6744–6753 (2014). \n76. Burke, M. S., Kast, M. G., Trotochaud, L., Smith, A. M. & Boettcher, S. W. Cobalt-iron (oxy)hydroxide oxygen evolution electrocatalysts: the role of structure and composition on activity, stability, and mechanism. J. Am. Chem. Soc. 137, 3638–3648 (2015). \n77. Bergmann, A. et al. Reversible amorphization and the catalytically active state of crystalline Co3O4 during oxygen evolution. Nat Commun 6, 8625 (2015). \n78. Klimes, J., Bowler, D. R. & Michaelides, A. Van der Waals density functionals applied to solids. Phys. Rev. B 83, 195131 (2011). \n\n# Acknowledgements \n\nThe WAXS experiments were performed on beamline ID31 at the European Synchrotron Radiation Facility (ESRF), Grenoble, France. We thank ESRF and HZB Bessy II for allocation of synchrotron radiation beamtime, and E. Hornberger and H. Schmies for their help during beamtimes. We also thank Dr. M. Görlin for the scientific and helpful discussions on NiFe (oxy)hydroxides. ZELMI of Technical University Berlin is acknowledged for their support with TEM measurements. Help at the beamline from Lukas Pielsticker (RUB) is appreciated, as well as the technical support from Dr Carlo Marini and Dr Nitya Ramanan at CLAESS beamline of ALBA synchrotron during the operando XAS measurements. The operando XAS work has funded by the European Research Council under grant ERC-OPERANDOCAT (ERC-725915). S.K. acknowledges funding from the IMPRS SurMat. This work was partially supported by the German Research Foundation (DFG, Deutsche Forschungsgemeinschaf) in the frame of the collaborative research center/transregio TRR247 Heterogeneous Oxidation Catalysis in the liquid Phase, project no. 388390466 and through grant reference number STR 596/8-1, Bifunctional seawater electrolyzer, STR 596/12-1, catalyst-support interactions on the activity and stability of water splitting catalysts, and by the Federal Ministry for economic affairs and energy (Bundesministerium für Wirtschaft und Energie, BMWi) under grant number 03EIV041F, MethFuel/ MethQuest. Work at Purdue was supported through the Office of Science, Office of Basic Energy Sciences, Chemical, Biological, and Geosciences Division under DE-SC0010379 (J.G.). Work at University of Science and Technology of China was supported by the National Key R&D Program of China (2018YFA0208603) and the Frontier Science Key Project of the Chinese Academy of Sciences (QYZDJSSW-SLH054). F.D. and P.S. acknowledge partial funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany´s Excellence Strategy – EXC 2008/1 –390540038. \n\n# Author contributions \n\nF.D. conceived and performed the operando WAXS measurements at ESRF and the analysis of the operando WAXS data including Rietveld refinement. Z.Z. conceived DFT calculations. Z.Z. and D.F. performed DFT calculations of structure search. Z.Z., S.D. and J.Z. performed the DFT calculations of OER mechanism. I.S. performed the operando XAS experiments at ALBA, analyzed the corresponding data, and wrote part of the manuscript. T.M. and H.S. synthesized all the samples and performed the RDE electrochemical characterization. M.B.L., S.K. and I.Z. performed the operando XAS experiments at ALBA. T.M., A.B. and J.D. performed the operando WAXS measurements at ESRF. J.F.d.A. designed and performed the DEMS experiments. M.G. performed the TEM. D.T. designed and performed the sXAS measurements at BESSY II and wrote part of the manuscript. F.D., B.R.C., and P.S. designed the research and experiments and wrote parts of the manuscript. Z.Z., W.-X.L. and J.G. designed the research and DFT calculations, and wrote part of the manuscript. All authors discussed the results and assisted during manuscript preparation. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-16237-1. \n\nCorrespondence and requests for materials should be addressed to F.D., Z.Z., B.R.C. or P.S. \n\nPeer review information Nautre Communications thanks the anonymous reviewers for their contributions to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1038_s41467-020-15316-7", + "DOI": "10.1038/s41467-020-15316-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-15316-7", + "Relative Dir Path": "mds/10.1038_s41467-020-15316-7", + "Article Title": "3D printing of conducting polymers", + "Authors": "Yuk, H; Lu, BY; Lin, S; Qu, K; Xu, JK; Luo, JH; Zhao, XH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Conducting polymers are promising material candidates in diverse applications including energy storage, flexible electronics, and bioelectronics. However, the fabrication of conducting polymers has mostly relied on conventional approaches such as ink-jet printing, screen printing, and electron-beam lithography, whose limitations have hampered rapid innovations and broad applications of conducting polymers. Here we introduce a high-performance 3D printable conducting polymer ink based on poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) for 3D printing of conducting polymers. The resultant superior printability enables facile fabrication of conducting polymers into high resolution and high aspect ratio microstructures, which can be integrated with other materials such as insulating elastomers via multi-material 3D printing. The 3D-printed conducting polymers can also be converted into highly conductive and soft hydrogel microstructures. We further demonstrate fast and streamlined fabrications of various conducting polymer devices, such as a soft neural probe capable of in vivo single-unit recording.", + "Times Cited, WoS Core": 722, + "Times Cited, All Databases": 756, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000563559600005", + "Markdown": "# 3D printing of conducting polymers \n\nHyunwoo Yuk 1,6, Baoyang Lu $\\textcircled{1}$ 2,3,4,6, Shen Lin5, Kai ${\\mathsf{Q}}{\\mathsf{u}}^{3}.$ , Jingkun $\\mathsf{X u}^{2,3}$ , Jianhong Luo5 & Xuanhe Zhao 1,4✉ \n\nConducting polymers are promising material candidates in diverse applications including energy storage, flexible electronics, and bioelectronics. However, the fabrication of conducting polymers has mostly relied on conventional approaches such as ink-jet printing, screen printing, and electron-beam lithography, whose limitations have hampered rapid innovations and broad applications of conducting polymers. Here we introduce a highperformance 3D printable conducting polymer ink based on poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) for 3D printing of conducting polymers. The resultant superior printability enables facile fabrication of conducting polymers into high resolution and high aspect ratio microstructures, which can be integrated with other materials such as insulating elastomers via multi-material 3D printing. The 3D-printed conducting polymers can also be converted into highly conductive and soft hydrogel microstructures. We further demonstrate fast and streamlined fabrications of various conducting polymer devices, such as a soft neural probe capable of in vivo single-unit recording. \n\nonducting polymers, a class of polymers with intrinsic electrical conductivity, have been one of the most promising materials in applications as diverse as energy storage1, flexible electronics2, and bioelectronics3, owing to their unique polymeric nature as well as favorable electrical and mechanical properties, stability, and biocompatibility. Despite recent advances in conducting polymers and their applications, the fabrication of conducting polymer structures and devices have mostly relied on conventional manufacturing techniques such as ink-jet printing4–6, screen printing7, aerosol printing8–10, electrochemical patterning11–13, and lithography14–16 with limitations and challenges. For example, these existing manufacturing techniques for conducting polymers are limited to low-resolution (e.g., over $100\\upmu\\mathrm{m}\\dot{}$ ), two-dimensional (e.g., low aspect ratio) patterns, and/or complex and high cost procedures (e.g., multi-step processes in clean room involving alignments, masks, etchings, post-assemblies)4,5,7,14–16 (Supplementary Table 1), which have hampered rapid innovations and broad applications of conducting polymers. Unlike these conventional approaches, threedimensional (3D) printing offers capabilities to fabricate microscale structures in a programmable, facile, and flexible manner with a freedom of design in 3D space17,18 (Supplementary Table 1). For example, recent developments of 3D printable materials such as metals19,20, liquid metals21, hydrogels22,23, cellladen bioinks24–26, glass27, liquid crystal polymers28, and ferromagnetic elastomers29 have greatly expanded the accessible materials library for 3D printing. While intensive efforts have been devoted to 3D printing of conducting polymers, only simple structures such as isolated fibers have been achieved30–32 owing to insufficient 3D printability of existing conducting polymer inks. \n\nHere we invent a high-performance 3D printable ink based on one of the most widely utilized conducting polymers poly(3,4- ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) to take advantage of advanced 3D printing for the fabrication of conducting polymers. To achieve favorable rheological properties for 3D printing, we develop a paste-like conducting polymer ink based on cryogenic freezing of aqueous PEDOT:PSS solution followed by lyophilization and controlled re-dispersion in water and dimethyl sulfoxide (DMSO) mixture. The resultant conducting polymer ink exhibits superior 3D printability capable of high resolution (over $30\\upmu\\mathrm{m})$ ), high aspect ratio (over 20 layers), and highly reproducible fabrication of conducting polymers, which are also readily integratable with other 3D printable materials such as insulating elastomers by multi-material 3D printing. Dry-annealing of the 3D-printed conducting polymers provides highly conductive (electrical conductivity over $155\\mathrm{\\bar{S}c m^{-1}}.$ ) and flexible PEDOT:PSS 3D microstructures in the dry state. Moreover, the dry-annealed 3D-printed conducting polymers can be readily converted into a soft (Young’s modulus below $1.1\\mathrm{MPa},$ ) yet highly conductive (electrical conductivity up to $28\\thinspace\\mathrm{Scm^{-1}}$ ) PEDOT:PSS hydrogel via subsequent swelling in the wet environment. We further demonstrate a facile and streamlined fabrication of various functional conducting polymer devices by multi-material 3D printing, including a high-density flexible electronic circuit and a soft neural probe capable of in vivo single-unit recording. \n\n# Results \n\n3D printable conducting polymer ink. Conducting polymers are typically used in the form of liquid monomer or polymer solution whose fluidity prevents their direct use in 3D printing3,5,33. In order to endow rheological properties required for 3D printing to conducting polymers, we develop a simple process to convert a commercially available PEDOT:PSS aqueous solution to a highperformance 3D printable ink (Fig. 1 and Supplementary Fig. 1). The pristine PEDOT:PSS solution exhibits a dilute dispersion of PEDOT:PSS nanofibrils (Fig. 1a, d) with low viscosity (below $30\\mathrm{Pa}\\thinspace\\mathsf{s}$ . Inspired by 3D printability of concentrated cellulose nanofiber suspensions34,35, we hypothesize that a highly concentrated solution of the PEDOT:PSS nanofibrils can provide a 3D printable conducting polymer ink, due to the formation of entanglements among PEDOT:PSS nanofibrils (Fig. 1b). To test our hypothesis, we first isolate PEDOT:PSS nanofibrils by lyophilizing the pristine PEDOT:PSS solution. In order to avoid excessive formation of PEDOT-rich crystalline domains among PEDOT:PSS nanofibrils due to slow ice crystal formation during lyophilization at high temperature36, we perform lyophilization in a cryogenic condition (i.e., frozen in liquid nitrogen). The isolated PEDOT:PSS nanofibrils are then re-dispersed with a binary solvent mixture (w $\\operatorname{ater:DMSO}=85{:}15\\mathrm{v/v},$ to prepare concentrated suspensions. \n\nWith increasing concentration of the PEDOT:PSS nanofibrils, the suspensions gradually transit from liquids to thixotropic 3D printable inks (Fig. $\\mathrm{1g-j}$ ) due to the formation of reversible physical networks of the PEDOT:PSS nanofibrils via entanglements within the solvent (Fig. 1e). We perform small angle X-ray scattering (SAXS) and rheological characterizations to quantify microscopic and macroscopic evolutions of the conducting polymer ink with varying concentrations of the PEDOT:PSS nanofibrils, respectively (Fig. 1k–o). The SAXS characterizations show that the average distance between PEDOT-rich crystalline domains $L$ (d-spacing calculated by the Bragg expression $L=2\\pi/$ $q_{\\mathrm{max}})$ decreases with an increase in the concentration of the PEDOT:PSS nanofibrils ( $\\cdot16.1\\mathrm{nm}$ for $1\\mathrm{wt\\%}$ and $7.0\\mathrm{nm}$ for $10\\mathrm{wt\\%}$ ), indicating closer packing and higher degree of interactions between the adjacent PEDOT:PSS nanofibrils in more concentrated inks (Fig. 1k). \n\nRheological measurements of the conducting polymer inks clearly show the transition from low viscosity liquids (low concentration PEDOT:PSS nanofibrils) to physical gels (high concentration PEDOT:PSS nanofibrils) with characteristic shearthinning and shear-yielding properties for 3D printable inks18,19 (Fig. 1l–o and Supplementary Fig. 2). The low viscosity and low yield stress of the conducting polymer inks with low PEDOT:PSS nanofibril concentrations $(1-4~\\mathrm{wt\\%})$ cause lateral spreading of 3D-printed inks on the substrate (Fig. 1g, h, m, o). On the other hand, the conducting polymer inks with too high concentrations of PEDOT:PSS nanofibrils (above $8\\mathrm{wt\\%}$ ) start to clog printing nozzles due to the formation of large aggregates of PEDOT:PSS nanofibrils (Fig. 1j, m, o). Hence, we find that the intermediate range of PEDOT:PSS nanofibril concentrations $(5-7~\\mathrm{wt\\%})$ provides optimal rheological properties and 3D printability (Fig. 1i, m, o). The 3D printable conducting polymer ink can be stored under ambient conditions over a month without the significant change in rheological properties and printability (Supplementary Fig. 3). After 3D printing, we dry and anneal the 3D-printed conducting polymers to remove solvents (water and DMSO) and facilitate the formation of PEDOT-rich crystalline domains and subsequent percolation among PEDOT:PSS nanofibrils33 (Fig. 1c, f) (see Methods for details). The resultant dry pure PEDOT:PSS can also be readily converted into stable pure PEDOT:PSS hydrogels (equilibrium water contents $\\sim87\\%$ ) by swelling in a wet environment33. \n\n3D printing of conducting polymers. Superior printability of the conducting polymer ink allows various advanced 3D printing capabilities including printing of high resolution, high aspect ratio, and overhanging structures (Fig. 2). To demonstrate high resolution printing in microscale, we print meshes of the conducting polymer ink ( $7\\mathrm{wt\\%}$ PEDOT:PSS nanofibril) through 200-, 100-, 50-, and ${30}\\mathrm{-}\\upmu\\mathrm{m}$ diameter nozzles (Fig. 2a–d). Favorable rheological properties of the conducting polymer ink further enable the fabrication of multi-layered high aspect ratio microstructures ( $\\updownarrow00\\mathrm{-}\\upmu\\mathrm{m}$ nozzle, 20 layers) (Supplementary Movie 1) as well as overhanging features (Supplementary Movie 2) (Fig. 2e, h). The 3D-printed conducting polymer structures can readily be converted into dry and hydrogel forms without loss of the original microscale structures, owing to the constrained drying (while attached on the substrate) and swelling property of the pure PEDOT:PSS hydrogels33 (Fig. 2f, g and Supplementary Fig. 4). Furthermore, the 3D-printed conducting polymer hydrogels exhibit long-term stability in physiological wet environments without observable degradation of microscale features (e.g., high aspect ratio and overhanging structures) after storing in PBS for 6 months (Supplementary Fig. 5). \n\n![](images/fd295b79fa08dd770251dc68928a29309493d45a4cecb783dca0cac8ba4a96b6.jpg) \nFig. 1 Design of 3D printable conducting polymer ink. a, b, Pristine PEDOT:PSS solution (a) can be converted into a 3D printable conducting polymer ink (b) by lyophilization in cryogenic condition and re-dispersion with a solvent. c, 3D-printed conducting polymers can be converted into a pure PEDOT:PSS both in dry and hydrogel states by dry-annealing and subsequent swelling in wet environment, respectively. d CryoTEM image of a pristine PEDOT:PSS solution. e CryoTEM image of a 3D printable conducting polymer ink. f TEM image of a dry-annealed 3D-printed conducting polymer. g–j Images of redispersed suspensions with varying PEDOT:PSS nanofibril concentration. k SAXS characterization of conducting polymer inks with varying PEDOT:PSS nanofibril concentration. The d-spacing L is calculated by the Bragg expression $L=2\\pi/q_{\\mathrm{max}}$ . l Apparent viscosity as a function of shear rate for conducting polymer inks of varying PEDOT:PSS nanofibril concentration. m Apparent viscosity of conducting polymer inks as a function of PEDOT:PSS nanofibril concentration. n Shear storage modulus as a function of shear stress for conducting polymer inks of varying PEDOT:PSS nanofibril concentration. o Shear yield stress of conducting polymer inks as a function of PEDOT:PSS nanofibril concentration. For TEM images in (d–f), the experiments were repeated $\\zeta n=$ 5) based on independently prepared samples with reproducible results. Scale bars, $100\\mathsf{n m}$ . \n\n![](images/9f1ffe5a70821dd370a55bf0fdfdc6477e5a5a11b1ded906436d9c2e8428d519.jpg) \nFig. 2 3D printing of conducting polymers. a–d SEM images of 3D-printed conducting polymer meshes by $200\\mathrm{-}\\upmu\\mathrm{m}$ (a), $100\\mathrm{-}\\upmu\\mathrm{m}$ $(\\pmb{6})$ , $50\\mathrm{-}\\upmu\\mathrm{m}$ (c), and $30\\AA\\cdot\\upmu\\mathrm{m}$ (d) nozzles. e Sequential snapshots for 3D printing of a 20-layered meshed structure by the conducting polymer ink. f 3D-printed conducting polymer mesh after dry-annealing. $\\mathtt{\\pmb{g}}3\\mathsf{D}$ -printed conducting polymer mesh in hydrogel state. h Sequential snapshots for 3D printing of overhanging features over high aspect ratio structures by the conducting polymer ink. i 3D-printed conducting polymer structure with overhanging features in hydrogel state. Scale bars, $500\\upmu\\mathrm{m}$ (a); $200\\upmu\\mathrm{m}$ $({\\pmb{\\ b}}-{\\pmb{\\ d}})$ ; $1\\mathsf{m m}$ (a–d, inset panels); $2{\\mathsf{m m}}$ (e–i). \n\nThe 3D printable conducting polymer ink can be readily incorporated into multi-material 3D printing processes together with other 3D printable materials. For example, we fabricate a structure that mimics a high-density multi-electrode array (MEA) based on multi-material 3D printing of the conducting polymer ink and an insulating polydimethylsiloxane (PDMS) ink with a total printing time less than $30\\mathrm{min}$ (Supplementary Fig. 6a, b and Supplementary Movie 3). The 3D-printed MEA-like structure shows a complex microscale electrode pattern and a PDMS well that are comparable to a commercially available MEA fabricated by multi-step lithographic processes and post-assembly (Supplementary Fig. 6c). \n\nProperties of 3D-printed conducting polymers. The 3D-printed conducting polymers can achieve electrical conductivity as high as $155\\mathrm{Scm}^{-1}$ in the dry state and $28\\ensuremath{\\mathrm{S}}\\ensuremath{\\mathrm{cm}}^{-1}$ in the hydrogel state, comparable to the previously reported high-performance conducting polymers5,16,33 (Fig. 3a, Supplementary Fig. 7, and Supplementary Table 2). Notably, a smaller nozzle diameter yields a higher electrical conductivity for the printed conducting polymers, potentially due to shear-induced enhancements in the PEDOT:PSS nanofibril alignment22. Flexibility of the 3D-printed conducting polymers allows mechanical bending with maximum strain of $13\\%$ in the dry state $65\\upmu\\mathrm{m}$ radius of curvature with $17\\upmu\\mathrm{m}$ thickness) and $20\\%$ in the hydrogel state ( $200\\upmu\\mathrm{m}$ radius of curvature with $78\\upmu\\mathrm{m}$ thickness) without failure (Supplementary Fig. 8). To investigate the effect of mechanical bending on the electrical performance, we characterize the electrical conductivity of the 3D-printed conducting polymers ( $100\\mathrm{-}\\upmu\\mathrm{m}$ nozzle, 1 layer) on flexible polyimide substrates as a function of the bending radius as well as the bending cycle (Fig. 3b, c). The 3D-printed conducting polymers show small changes in the electrical conductivity (less than $5\\%$ ) across a wide range of tensile and compressive bending conditions (radius of curvature, $\\pm1{-}20\\mathrm{mm},$ ) in both the dry and hydrogel states (Fig. 3b). Furthermore, the 3D-printed conducting polymers can maintain a high electrical conductivity (over $100\\mathrm{{\\dot{S}}c m\\dot{^{-1}}}$ in dry state and over $\\mathrm{i}5\\mathrm{Scm}^{-1}$ in hydrogel state) after 10,000 cycles of repeated bending (Fig. 3c). \n\nTo further investigate the electrical properties, we perform the electrochemical impedance spectroscopy (EIS) of the 3D-printed conducting polymers $_{(100-\\upmu\\mathrm{m}}$ nozzle, 1 layer on Pt) (Fig. 3d). The EIS data are fitted to the equivalent circuit model shown in Fig. 3d, where $R_{\\mathrm{e}}$ represents the electronic resistance, $R_{\\mathrm{i}}$ represents the ionic resistance, $R_{c}$ represents the total ohmic resistance of the electrochemical cell assembly, and $\\mathrm{CPE_{\\mathrm{dl}}}$ and $\\mathrm{CPE_{g}}$ represent the constant phase elements (CPE) corresponding to the double-layer ionic capacitance and the geometric capacitance, respectively37,38. The semicircular Nyquist plot shape suggests the presence of comparable ionic and electronic conductivity in the 3D-printed conducting polymer hydrogels (Fig. 3d), which is confirmed by the extracted fitting parameters of the equivalent circuit model where the ionic and electronic resistances show comparable magnitudes $'{R_{\\mathrm{i}}}=105.5\\Omega$ and $R_{\\mathrm{e}}=$ $107.1\\Omega)$ . \n\nThe cyclic voltammetry (CV) demonstrates a high charge storage capability (CSC) of the 3D-printed conducting polymers ( $_{\\mathrm{100-\\upmum}}$ nozzle, 1 layer on Pt) compared to typical metallic electrode materials such as Pt with remarkable electrochemical stability (less than $2\\%$ reduction in CSC after 1000 cycles) (Fig. 3e). The CV of the 3D-printed conducting polymers further shows broad and stable anodic and cathodic peaks under varying potential scan rates39, suggesting non-diffusional redox processes and electrochemical stability of the 3D-printed conducting polymers (Supplementary Fig. 9). \n\n![](images/4ab8a581cee242431ff13d854892af4a603bdfe5baa15bd98235f8ce1e069017.jpg) \nFig. 3 Properties of 3D-printed conducting polymers. a Conductivity as a function of nozzle diameter for 3D-printed conducting polymers in dry and hydrogel states. b Conductivity as a function of bending radius for 3D-printed conducting polymers in dry $(17\\upmu\\mathrm{m}.$ thickness) and hydrogel $(78\\upmu\\mathrm{m},$ thickness) states. PI indicates polyimide. c Conductivity as a function of bending cycles for 3D-printed conducting polymers in dry $(17\\upmu\\mathrm{m}.$ , thickness) and hydrogel $(78\\upmu\\mathsf{m},$ thickness) states. d Nyquist plot obtained from the EIS characterization for a 3D-printed conducting polymer on $\\mathsf{P t}$ substrate $(78\\upmu\\mathrm{m},$ thickness) overlaid with the plot predicted from the corresponding equivalent circuit model38. In the equivalent circuit models, $R_{\\mathrm{e}}$ represents electronic resistance, $R_{\\mathrm{i}}$ represents ionic resistance, $R_{\\mathrm{c}}$ represents the total ohmic resistance of the cell assembly, $\\mathsf{C P E_{d\\mid}}$ represents the double-layer constant phase element (CPE), whereas $\\mathsf{C P E}_{\\mathrm{g}}$ represents the geometric CPE. CPE is used to account inhomogeneous or imperfect capacitance and are represented by the parameters $Q$ and $\\boldsymbol{n}$ where Q represents the peudocapacitance value and $n$ represents the deviation from ideal capacitive behavior. The true capacitance $\\boldsymbol{C}$ can be calculated from these parameters by using the relationship $C=Q\\mathfrak{o}_{\\mathfrak{m a x}}n{-}1$ , where $\\omega_{\\mathrm{{max}}}$ is the frequency at which the imaginary component reaches a maximum37. The fitted values for 3D-printed PEDOT:PSS are $R_{\\mathrm{e}}=107.1\\Omega,$ $R_{\\mathrm{i}}=105.5\\Omega$ $R_{\\mathrm{c}}=14.07\\Omega,$ $Q_{\\mathsf{d l}}=1.467\\times10^{-5}\\mathsf{F}\\mathsf{s}^{n-1}$ , $\\boldsymbol{n}_{\\mathrm{dl}}=0.924$ , $Q_{\\mathrm{g}}=4.446\\times$ $10^{-7}\\mathsf{F}\\mathsf{s}^{n-1}.$ , and $\\ensuremath{n_{\\mathrm{dl}}}=0.647$ . e CV characterization for a 3D-printed conducting polymer on Pt substrate. f Nanoindentation characterizations for 3Dprinted conducting polymers in dry and hydrogel states with the JKR model fits. Values in (a–c) represent the mean and the standard deviation $\\hslash=5$ per each testing conditions based on independently prepared samples and performed experiments). \n\nTo quantify mechanical properties of the 3D-printed conducting polymers, we conduct nanoindentation tests (Fig. 3f and Supplementary Fig. 10). The 3D-printed conducting polymers display relatively high Young’s modulus of $1.5\\pm0.31\\mathrm{GPa}$ in the dry state, similar to the previously reported values for dry PEDOT: $\\mathrm{PSS^{40}}$ (Fig. 3f). In contrast, the 3D-printed conducting polymers in the hydrogel state exhibit three orders of magnitude reduction in Young’s modulus to $1.1\\pm0.36\\mathrm{MPa}$ , comparable to those of soft elastomers such as PDMS (Young’s modulus, $\\mathrm{1-10\\:MPa}_{\\cdot}$ ) (Fig. 3f). The softness of 3D-printed conducting polymer hydrogels can offer favorable long-term biomechanical interactions with biological tissues, which may find a particular advantage in bioelectronic devices and implants3,41,42. \n\n3D printing of conducting polymer devices. Enabled by the superior 3D printability and properties, 3D printing of the conducting polymer ink can offer a promising route for facile and streamlined fabrication of high resolution and multi-material conducting polymer structures and devices (Fig. 4 and Supplementary Table 1). Highly reproducible 3D printing of conducting polymers in high resolution allows the rapid fabrication of over 100 circuit patterns with less than $100\\upmu\\mathrm{m}$ feature size on a flexible polyethylene terephthalate (PETE) substrate by a single continuous printing process with a total printing time less than $30\\mathrm{min}$ (Fig. 4a, Supplementary Fig. 11, and Supplementary Movie 4). The resultant 3D-printed conducting polymer electronic circuits exhibit high electrical conductivity to operate electrical components such as a light emitting diode (LED) \n\n(Fig. 4b and Supplementary Movie 4) and flexibility to withstand bending without mechanical failure (Fig. 4c). This programmable, high resolution, and high throughput fabrication of conducting polymer patterns by 3D printing can potentially serve as an alternative to ink-jet printing and screen printing with a higher degree of flexibility in the choice of designs based on applicational demands4,7. \n\nWe further demonstrate a facile fabrication of a soft neural probe for in vivo bioelectronic signal recording (Supplementary Fig. 12 and Supplementary Movie 5). The multi-material 3D printing capability in high resolution allows us to print both insulating encapsulation (PDMS ink) and electrodes (conducting polymer ink) of the neural probe by a facile continuous printing process (a total printing time less than $20\\mathrm{min}$ ) without the need of post-assemblies or complex multi-step procedures in conventional fabrication methods such as electron-beam lithography15,16 (Fig. 4d, Supplementary Fig. 12, and Supplementary Movie 5). The resultant probe consists of nine PEDOT:PSS electrode channels in the feature size of $30\\upmu\\mathrm{m}$ in diameter with the impedance in the range of $50{-}150\\mathrm{k}\\Omega$ at $1\\mathrm{kHz}$ , suitable for in vivo recording of neural activities43,44. After the connector assembly (Supplementary Fig. 13), the 3D-printed soft neural probe is implanted to the mouse dorsal hippocampus (dHPC, coordinate: $-1.8\\mathrm{mm}$ AP; $1.5\\mathrm{{mm}\\mathrm{{ML};-1.0\\mathrm{{mm}\\ D V}}}$ ) with the help of a plastic catheter (Fig. 4f, top). The 3D-printed soft neural probe can successfully record continuous neural activities in a freely moving mouse (Fig. 4f, bottom) from each channel including the local field potential (LFP; at $1\\mathrm{kHz}$ ) (Fig. 4g) and the action potential (AP; at $40\\mathrm{kHz}$ ) (Fig. 4h) over two weeks. Furthermore, the 3D-printed soft neural probe can record signals from distinctive single units, isolated from individual channel of the probe (Fig. 4i, j). \n\n![](images/5d798a00dd0c97c5528ce3db73af16b8f8b68f4aaa5b8c823b00437d3fe35119.jpg) \nFig. 4 3D printing of conducting polymer devices. a Sequential snapshots for 3D printing of high-density flexible electronic circuit patterns by the conducting polymer ink. b Lighting up of LED on the 3D-printed conducting polymer circuit. PETE indicates polyethylene terephthalate. c Bending of the 3Dprinted conducting polymer circuit without failure. d Image of the 3D-printed soft neural probe with $9$ -channels by the conducting polymer ink and the PDMS ink. e Image of the 3D-printed soft neural probe in magnified view. f Images of the implanted 3D-printed soft neural probe (top) and a freely moving mouse with the implanted probe (bottom). g, h Representative electrophysiological recordings in the mouse dHPC by the 3D-printed soft neural probe. Local field potential (LFP) traces (0.5 to $250\\mathsf{H z}$ ) under freely moving conditions $\\mathbf{\\sigma}(\\mathbf{g})$ . Continuous extracellular action potential (AP) traces (300 to $40\\left\\vert k\\right\\vert\\left\\vert\\boldsymbol{\\mathrm{\\Sigma}}\\right\\rangle$ recorded under freely moving conditions (h). i Principal component analysis of the recorded single-unit potentials from ${\\bf\\Pi}({\\bf h})$ . j Average two units spike waveforms recorded over time corresponding to clusters in (i). Scale bars, 5 mm (a–c); 1 mm (d, e); 2 mm (f). \n\n# Discussion \n\nIn summary, we present a high-performance 3D printable conducting polymer ink based on PEDOT:PSS capable of rapid and flexible fabrication of highly conductive microscale structures and devices both in the dry and hydrogel states. The conducting polymer ink exhibits superior 3D printability and ready integrability into advanced multi-material 3D printing processes with other 3D printable materials. Enabled by this capability, we further demonstrate 3D printing-based fabrication of the highdensity flexible electronic circuit and the soft neural probe in a facile, fast, and significantly streamlined manner. This work not only addresses the existing challenges in 3D printing of conducting polymers but also offers a promising fabrication strategy for flexible electronics, wearable devices, and bioelectronics based on conducting polymers. \n\n# Methods \n\nPreparation of 3D printable conducting polymer ink. A commercially available PEDOT:PSS aqueous solution (CleviosTM PH1000, Heraeus Electronic Materials) was stirred vigorously for $^{6\\mathrm{h}}$ at room temperature and filtered with a syringe filter $(0.45\\upmu\\mathrm{m})$ . The filtered pristine PEDOT:PSS solution was then cryogenically frozen by submerging in liquid nitrogen bath. The cryogenically frozen PEDOT:PSS solution was lyophilized for $^{72\\mathrm{h}}$ to isolate PEDOT:PSS nanofibrils. The isolated PEDOT:PSS nanofibrils with varying concentrations were re-dispersed with a deionized water-DMSO (Sigma-Aldrich) mixture (water:DM $\\mathrm{{3O}}=85{:}15\\mathrm{{v}}/\\mathrm{{v}},$ , followed by thorough mixing and homogenization by a mortar grinder (RM 200, Retcsh). The prepared conducting polymer ink was kept at $4^{\\circ}\\mathrm{C}$ before use. The detailed procedure for the 3D printable conducting polymer ink preparation is illustrated in Supplementary Fig. 1. \n\n3D printing procedure. 3D printing of the conducting polymer ink and the PDMS ink (SE 1700, Dow Corning) were conducted based on a custom-designed 3D printer based on a Cartesian gantry system (AGS1000, Aerotech)18 with various size of nozzles (200- and $100\\mathrm{-}\\upmu\\mathrm{m}$ nozzles from Nordson EFD; ${50}\\mathrm{-}\\upmu\\mathrm{m}$ nozzles from Fisnar; ${30}\\mathrm{-}\\upmu\\mathrm{m}$ nozzles from World Precision Instrument). Printing paths were generated by CAD drawings (SolidWorks, Dassault Systèmes) and converted into G-code by a commercial software package (CADFusion, Aerotech) and custom Python scripts to command the x-y-z motion of the printer head. The detailed printing paths are provided in Supplementary Figs. 6, 11, and 12. \n\nAfter printing, the 3D-printed conducting polymer was dried at $60^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ followed by multiple cycles of annealing at $130^{\\circ}\\mathrm{C}$ (3 cycles with $30\\mathrm{min}$ per each cycle) to yield pure PEDOT:PSS33. To achieve constrained drying of 3D-printed conducting polymers in thickness direction, the 3D-printed conducting polymers were placed on a glass substrate and dry-annealed. The dry-annealed 3D-printed conducting polymer was further equilibrated in PBS to be converted into a hydrogel state. \n\nElectron microscope imaging. Scanning electron microscope (SEM) images of the 3D-printed conducting polymers were taken by using a SEM facility (JSM-6010LA, JEOL) with $5\\mathrm{nm}$ gold sputtering to enhance image contrasts. Transmission electron microscope (TEM) images of the pristine PEDOT:PSS solution, conducting polymer ink, and dry-annealed 3D-printed conducting polymer were taken by using a TEM facility (2100 FEG, JEOL) at $200\\mathrm{kV}$ with a magnification of 10,000 to 60,000. For cryogenic TEM (CryoTEM) imaging, the samples were prepared by a cryo plunger (CP3, Gatan). All Images were recorded under low-dose conditions to avoid sample damage by electron beams. \n\nSmall angle X-ray scattering (SAXS) characterizations of the conducting polymer inks were conducted by using a SAXS facility (Pilatus $3\\mathrm{R}300\\mathrm{K},$ Bruker Nanostar SAXS) with a sample-detector distance of $1059.1\\mathrm{mm}$ and an exposure time of $300\\mathrm{s}.$ . The measured scattering intensity was corrected by subtracting the solvent background (water:D ${\\sf M S O}=85{\\cdot}15{\\mathrm{~v/v}}_{\\mathrm{~\\rightmoon~}}$ ). To analyze the average distance between PEDOT crystalline domains in the 3D printable conducting polymer inks, the d-spacing $L$ was calculated by the Bragg expression $L=2\\pi/q_{\\mathrm{max}}$ without further fitting of the SAXS data. \n\nRheological characterization. Rheological characterizations of the conducting polymer inks were conducted by using a rotational rheometer (AR-G2, TA Instrument) with $20\\mathrm{-mm}$ diameter steel parallel-plate geometry. Apparent viscosity was measured as a function shear rate by steady-state flow tests with a logarithmic sweep of shear rate $(0.01-100\\mathrm{s^{-1}},$ ). Shear storage modulus $(G^{\\prime})$ and loss modulus $\\left(G^{\\prime\\prime}\\right)$ were measured as a function of shear stress via oscillation tests with a logarithmic sweep of shear stress $\\left(1{-}1000\\mathrm{Pa}\\right)$ at $1\\mathrm{Hz}$ shear frequency and oscillatory strain of 0.02. Shear yield stress for each sample was identified as a shear stress at which shear and loss moduli were the same values. All rheological characterizations were conducted at $25^{\\circ}\\mathrm{C}$ with preliminary equilibration time of $1\\mathrm{min}$ . \n\nNanoindentation. Nanoindentation characterizations of 3D-printed conducting polymers were conducted by using an atomic force microscope (AFM) facility (MFP-3D, Asylum Research) with indentation depth of $50\\mathrm{nm}$ (for dry state) and $1\\upmu\\mathrm{m}$ (for hydrogel state). A spherical tip with $50\\mathrm{nm}$ radius (biosphereTM, Asylum Research) was used for the nanoindentation measurements. Young’s moduli of the samples were obtained by fitting force vs. indentation curve with a JKR model45 (Fig. 3f). \n\nElectrical conductivity measurement. Electrical conductivity of the 3D-printed conducting polymers was measured by using a standard four-point probe (Keithley 2700 digital multimeter, Keithley). To prepare conductivity measurement samples, one layer of the conducting polymer ink was printed into a rectangular shape ( $30\\mathrm{mm}$ in length and $5\\mathrm{mm}$ in width) with $100\\mathrm{-}\\upmu\\mathrm{m}$ nozzles on glass substrates ( $17\\upmu\\mathrm{m}$ and $78\\upmu\\mathrm{m}$ in thickness for dry-annealed and hydrogel samples, respectively). Copper wire electrodes (diameter, $0.5\\mathrm{mm}$ ) were attached onto the surface of dry-annealed 3D-printed conducting polymer by applying silver paste, while platinum wire electrodes (diameter, $0.5\\mathrm{mm}$ ) were employed for hydrogels to avoid the corrosion in wet environments (Supplementary Fig. 7). The electrical conductivity $\\sigma$ of the samples was calculated as \n\n$$\n\\upsigma=\\frac{I\\times L}{V\\times W\\times T},\n$$ \n\nwhere $I$ is the current flowing through the sample, $L$ is the distance between the two electrodes for voltage measurement, $V$ is the voltage across the electrodes, W is the width of the sample, and $T$ is the thickness of the sample. \n\nFor electrical conductivity measurements under cyclic bending, one layer of the conducting polymer ink was printed into a rectangular shape $30\\mathrm{mm}$ in length and $5\\mathrm{mm}$ in width) with $100\\mathrm{-}\\upmu\\mathrm{m}$ nozzles on polyimide substrates $17\\upmu\\mathrm{m}$ and $78\\upmu\\mathrm{m}$ in thickness for dry-annealed and hydrogel samples, respectively). Cyclic bending of the sample was performed by using a custom-made fixture with controllable bending radius of curvature. \n\nElectrochemical measurement. Cyclic voltammetry (CV) of the 3D-printed conducting polymer was performed by using a potentiostat/galvanostat (VersaSTAT 3, Princeton Applied Research) with a range of scan rates (50 to $500\\mathrm{mVs^{-1}}$ ). Pt wires (diameter, $1\\mathrm{mm}$ ) were employed as both working and counter electrodes, and an $\\mathrm{\\Ag/AgCl}$ electrode was used as the reference electrode. Prior to all measurements, the working and counter electrodes were cleaned successively with abrasive paper, deionized water, and ethyl alcohol. PBS was used as the supporting electrolyte. \n\nElectrochemical impedance spectroscopy (EIS) measurements of the 3D-printed conducting polymer were carried out by using a potentiostat/galvanostat (1287 A, Solartron Analytical) and a frequency response analyzer ( $1260\\mathrm{A}$ Solatron \n\nAnalytical) in an electrochemical cell installed with Pt sheet as both working and counter electrodes and $\\mathrm{Ag/AgCl}$ as a reference electrode. The frequency range between 0.1 and $100\\mathrm{kHz}$ was scanned in PBS with an applied bias of $0.01\\mathrm{V}$ vs. $\\mathrm{\\Ag/}$ AgCl. The EIS data for the 3D-printed conducting polymer were fitted by using an equivalent circuit model for further analysis (Fig. 3d). \n\nIn vivo electrophysiology by 3D-printed soft neural probe. Young adult mice (60-70 days old, Balb/C Male Jackson Laboratory Stock $\\#~000651$ ) were used in the electrophysiological experiments. Mice were maintained under a $^{12\\mathrm{h}}$ light/dark cycle at $22{-}25^{\\circ}\\mathrm{C},$ and given ad libitum access to tap water and standard chow. All procedures were approved by the Animal Advisory Committee at Zhejiang University and followed the US National Institutes of Health Guidelines for the Care and Use of Laboratory Animals. For all surgeries, mice were anesthetized with $1\\%$ pentobarbital (Sigma-Aldrich), and then fixed in a stereotaxic frame. A craniotomy was performed at $-1.80\\mathrm{mm}$ anterior to bregma and $1.5\\mathrm{mm}$ lateral to the midline. The incision was closed with tissue glue (VetBondTM, 3 M). Electrophysiological recording in the dHPC was carried out by using the 3D-printed soft neural probe coupling with Neuro Nano Strip Connectors (Omnetics). All data shown in Fig. $\\mathrm{4g-j}$ were collected from ${\\mathrm{BALB}}/{\\mathrm{c}}$ mice in the dHPC with a 64-channel multi-electrode recording system (Plexon). After the probe implantation, mice were allowed to recover for at least 3 days. Neuronal signals were referenced to two connected skull screws (above the prefrontal cortex and cerebellum). Spike sorting was carried out in Offline Sorter software (Plexon). In the principal component analysis, a rough separation of units from PNs and interneurons in the dHPC was mainly based on their differences in spike wave shapes and mean baseline firing rates. \n\nReporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Code availability \n\nThe custom codes used this study for 3D printing are available from the corresponding author upon reasonable request. \n\nReceived: 30 July 2019; Accepted: 21 February 2020; Published online: 30 March 2020 \n\n# References \n\n1. Shi, Y., Peng, L., Ding, Y., Zhao, Y. & Yu, G. Nanostructured conductive polymers for advanced energy storage. Chem. Soc. Rev. 44, 6684–6696 (2015). \n2. Someya, T., Bao, Z. & Malliaras, G. G. The rise of plastic bioelectronics. Nature 540, 379 (2016). \n3. Yuk, H., Lu, B. & Zhao, X. Hydrogel bioelectronics. Chem. Soc. Rev. 48, 1642–1667 (2019). \n4. Sirringhaus, H. et al. High-resolution inkjet printing of all-polymer transistor circuits. Science 290, 2123–2126 (2000). \n5. Wang, Y. et al. A highly stretchable, transparent, and conductive polymer. Sci. Adv. 3, e1602076 (2017). \n6. Bihar, E. et al. Inkjet‐printed PEDOT: PSS electrodes on paper for electrocardiography. Adv. Healthc. Mater. 6, 1601167 (2017). \n7. Zhu, C. et al. Stretchable temperature-sensing circuits with strain suppression based on carbon nanotube transistors. Nat. Electron. 1, 183 (2018). \n8. Hong, K., Kim, S. H., Mahajan, A. & Frisbie, C. D. Aerosol jet printed p-and n-type electrolyte-gated transistors with a variety of electrode materials: exploring practical routes to printed electronics. ACS Appl. Mater. Interfaces 6, 18704–18711 (2014). \n9. Hong, K. et al. Aerosol jet printed, Sub‐2 V complementary circuits constructed from P‐and N‐type electrolyte gated transistors. Adv. Mater. 26, 7032–7037 (2014). \n10. Thompson, B. & Yoon, H.-S. Aerosol-printed strain sensor using PEDOT: PSS. IEEE Sens. J. 13, 4256–4263 (2013). \n11. Sekine, S., Ido, Y., Miyake, T., Nagamine, K. & Nishizawa, M. Conducting polymer electrodes printed on hydrogel. J. Am. Chem. Soc. 132, 13174–13175 (2010). \n12. Ido, Y. et al. Conducting polymer microelectrodes anchored to hydrogel films. ACS Macro Lett. 1, 400–403 (2012). \n13. Feig, V. R. et al. An electrochemical gelation method for patterning conductive PEDOT: PSS hydrogels. Adv. Mater. 31, 1902869 (2019). \n14. Wang, S. et al. Skin electronics from scalable fabrication of an intrinsically stretchable transistor array. Nature 555, 83 (2018). \n15. Liu, Y. et al. Soft conductive micropillar electrode arrays for biologically relevant electrophysiological recording. Proc. Natl Acad. Sci. 115, 11718–11723 (2018). \n16. Liu, Y. et al. Soft and elastic hydrogel-based microelectronics for localized lowvoltage neuromodulation. Nat. Biomed. Eng. 3, 58 (2019). \n17. Truby, R. L. & Lewis, J. A. Printing soft matter in three dimensions. Nature 540, 371 (2016). \n18. Yuk, H. & Zhao, X. A new 3D printing strategy by harnessing deformation, instability, and fracture of viscoelastic inks. Adv. Mater. 30, 1704028 (2018). \n19. Ahn, B. Y. et al. Omnidirectional printing of flexible, stretchable, and spanning silver microelectrodes. Science 323, 1590–1593 (2009). \n20. Martin, J. H. et al. 3D printing of high-strength aluminium alloys. Nature 549, 365 (2017). \n21. Ladd, C., So, J. H., Muth, J. & Dickey, M. D. 3D printing of free standing liquid metal microstructures. Adv. Mater. 25, 5081–5085 (2013). \n22. Gladman, A. S., Matsumoto, E. A., Nuzzo, R. G., Mahadevan, L. & Lewis, J. A. Biomimetic 4D printing. Nat. Mater. 15, 413 (2016). \n23. Grigoryan, B. et al. Multivascular networks and functional intravascular topologies within biocompatible hydrogels. Science 364, 458–464 (2019). \n24. Kolesky, D. B. et al. 3D bioprinting of vascularized, heterogeneous cell‐laden tissue constructs. Adv. Mater. 26, 3124–3130 (2014). \n25. Kang, H.-W. et al. A 3D bioprinting system to produce human-scale tissue constructs with structural integrity. Nat. Biotechnol. 34, 312 (2016). \n26. Liu, X. et al. 3D printing of living responsive materials and devices. Adv. Mater. 30, 1704821 (2018). \n27. Kotz, F. et al. Three-dimensional printing of transparent fused silica glass. Nature 544, 337 (2017). \n28. Gantenbein, S. et al. Three-dimensional printing of hierarchical liquid-crystalpolymer structures. Nature 561, 226 (2018). \n29. Kim, Y., Yuk, H., Zhao, R., Chester, S. A. & Zhao, X. Printing ferromagnetic domains for untethered fast-transforming soft materials. Nature 558, 274 (2018). \n30. Kim, J. T. et al. Three‐dimensional writing of conducting polymer nanowire arrays by meniscus‐guided polymerization. Adv. Mater. 23, 1968–1970 (2011). \n31. Devaraj, H., Aw, K., Travas-Sejdic, J. & Sharma, R. 18th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS). 1097–1100 (IEEE, 2015). \n32. Heo, D. N. et al. Development of 3D printable conductive hydrogel with crystallized PEDOT: PSS for neural tissue engineering. Mater. Sci. Eng. C. 99, 582–590 (2019). \n33. Lu, B. et al. Pure PEDOT:PSS hydrogels. Nat. Commun. 10, 1043 (2019). \n34. Nazari, B., Kumar, V., Bousfield, D. W. & Toivakka, M. Rheology of cellulose nanofibers suspensions: boundary driven flow. J. Rheol. 60, 1151–1159 (2016). \n35. Mendoza, L., Batchelor, W., Tabor, R. F. & Garnier, G. Gelation mechanism of cellulose nanofibre gels: A colloids and interfacial perspective. J. Colloid Interface Sci. 509, 39–46 (2018). \n36. Guex, A. G. et al. Highly porous scaffolds of PEDOT: PSS for bone tissue engineering. Acta Biomater. 62, 91–101 (2017). \n37. Hsu, C. & Mansfeld, F. Concerning the conversion of the constant phase element parameter Y0 into a capacitance. Corrosion 57, 747–748 (2001). \n38. Feig, V. R., Tran, H., Lee, M. & Bao, Z. Mechanically tunable conductive interpenetrating network hydrogels that mimic the elastic moduli of biological tissue. Nat. Commun. 9, 2740 (2018). \n39. Heinze, J., Frontana-Uribe, B. A. & Ludwigs, S. Electrochemistry of conducting polymers—persistent models and new concepts. Chem. Rev. 110, 4724–4771 (2010). \n40. Lang, U., Naujoks, N. & Dual, J. Mechanical characterization of PEDOT: PSS thin films. Synth. Met. 159, 473–479 (2009). \n41. Park, S. I. et al. Soft, stretchable, fully implantable miniaturized optoelectronic systems for wireless optogenetics. Nat. Biotechnol. 33, 1280 (2015). \n42. Lacour, S. P., Courtine, G. & Guck, J. Materials and technologies for soft implantable neuroprostheses. Nat. Rev. Mater. 1, 16063 (2016). \n43. Kozai, T. D. Y. et al. Ultrasmall implantable composite microelectrodes with bioactive surfaces for chronic neural interfaces. Nat. Mater. 11, 1065 (2012). \n44. Park, S. et al. One-step optogenetics with multifunctional flexible polymer fibers. Nat. Neurosci. 20, 612 (2017). \n45. Johnson, K. L., Kendall, K. & Roberts, A. Surface energy and the contact of elastic solids. Proc. R. Soc. Lond. A. Math. Phys. Sci. 324, 301–313 (1971). \n\n# Acknowledgements \n\nThe authors thank Dr. Alan F. Schwartzman in MIT DMSE Nanomechanical Technology Laboratory for his help with AFM nanoindentation experiment and Dr. Dong Soo Yun in MIT Koch Institute Nanotechnology Materials Core for his help with TEM imaging. This work is supported by MIT. H.Y. acknowledges the financial support from Samsung Scholarship. B.L. acknowledges the financial support from National Natural Science Foundation of China (51763010 & 51963011), Technological Expertise and Academic Leaders Training Program of Jiangxi Province (20194BCJ22013), and Research Project of State Key Laboratory of Mechanical System and Vibration (MSV202013). \n\n# Author contributions \n\nH.Y. and B.L. conceived the idea. H.Y. and X.Z. developed the 3D printing platform. H.Y. and B.L. developed the materials and method and conducted experiments. K.Q. and J.X. conducted the electrical conductivity measurements. S.L. and J.L. designed and conducted the in vivo bioelectronic experiments. H.Y., B.L., and X.Z. analyzed the results and wrote the manuscript with inputs from all authors. \n\n# Competing interests \n\nH.Y., B.L., and X.Z. are inventors of a U.S. patent application that covers the 3D printing of conducting polymers. All other authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-15316-7. \n\nCorrespondence and requests for materials should be addressed to X.Z. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1126_science.aba0893", + "DOI": "10.1126/science.aba0893", + "DOI Link": "http://dx.doi.org/10.1126/science.aba0893", + "Relative Dir Path": "mds/10.1126_science.aba0893", + "Article Title": "Resolving spatial and energetic distributions of trap states in metal halide perovskite solar cells", + "Authors": "Ni, ZY; Bao, CX; Liu, Y; Jiang, Q; Wu, WQ; Chen, SS; Dai, XZ; Chen, B; Hartweg, B; Yu, ZS; Holman, Z; Huang, JS", + "Source Title": "SCIENCE", + "Abstract": "We report the profiling of spatial and energetic distributions of trap states in metal halide perovskite single-crystalline and polycrystalline solar cells. The trap densities in single crystals varied by five orders of magnitude, with a lowest value of 2 x 10(11) per cubic centimeter and most of the deep traps located at crystal surfaces. The charge trap densities of all depths of the interfaces of the polycrystalline films were one to two orders of magnitude greater than that of the film interior, and the trap density at the film interior was still two to three orders of magnitude greater than that in high-quality single crystals. Suprisingly, after surface passivation, most deep traps were detected near the interface of perovskites and hole transport layers, where a large density of nullocrystals were embedded, limiting the efficiency of solar cells.", + "Times Cited, WoS Core": 916, + "Times Cited, All Databases": 958, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000522167400047", + "Markdown": "# SOLAR CELLS \n\n# Resolving spatial and energetic distributions of trap states in metal halide perovskite solar cells \n\nZhenyi ${\\mathsf{N i}}^{\\mathsf{1}\\ast}$ , Chunxiong $\\mathsf{B a o}^{2\\ast}$ , Ye Liu1,2, Qi Jiang1, Wu-Qiang Wu1, Shangshang Chen1, Xuezeng Dai1, Bo Chen1, Barry Hartweg3, Zhengshan $\\boldsymbol{\\mathsf{Y}}\\boldsymbol{\\mathsf{u}}^{3}$ , Zachary Holman3, Jinsong Huang1,2† \n\nWe report the profiling of spatial and energetic distributions of trap states in metal halide perovskite single-crystalline and polycrystalline solar cells. The trap densities in single crystals varied by five orders of magnitude, with a lowest value of $2\\times10^{11}$ per cubic centimeter and most of the deep traps located at crystal surfaces. The charge trap densities of all depths of the interfaces of the polycrystalline films were one to two orders of magnitude greater than that of the film interior, and the trap density at the film interior was still two to three orders of magnitude greater than that in high-quality single crystals. Suprisingly, after surface passivation, most deep traps were detected near the interface of perovskites and hole transport layers, where a large density of nanocrystals were embedded, limiting the efficiency of solar cells. \n\nhe photovoltaic performance of metal halide perovskites (MHPs) is mainly attributed to their high optical absorption coefficient $(I)$ , high carrier mobility (2), long charge-diffusion length (3), and small Urbach energy (4). Defect tolerance in MHPs was initially proposed as one origin for their excellent carrier transport and particular recombination properties, in that most point defects have low formation energy in the bulk of perovskites and do not form deep charge traps $(5,6)$ . Later theoretical studies showed that the structural defects at the material surface and grain boundaries of perovskites can induce deep charge traps, which has guided the development of passivation techniques in perovskite solar cells (7–9), but this was only inferred indirectly. The nonradiative recombination process also leads to the energy loss of the perovskite solar cells, which is closely related to the defectinduced trap states in the perovskites (10, 11). Charge trap states play an important role in the degradation of perovskite solar cells and other devices (12, 13). Knowledge of the distributions of trap states in space and energy is one of the most fundamental ingredients for understanding the impact of the charge traps on charge transport and recombination in perovskite materials and devices. \n\nThermal admittance spectroscopy (TAS) and thermally stimulated current methods have been broadly applied to measure the energydependent trap density of states (tDOS) in perovskite solar cells (14–16). These methods can generally reach a trap depth of ${\\sim}0.55~\\mathrm{eV}$ from the conduction or valence band edge, which is normally deep enough for most low– band gap perovskites that make efficient solar cells. Techniques like surface photovoltage spectroscopy and sub–band gap photocurrent are capable of detecting deeper trap states that exist in wide–band gap perovskites (17–19). Sub–band gap photoluminescence, which was adopted to investigate the properties of luminescent trap states in perovskite (20), and cathodoluminescence were shown to image the nanoscale stoichiometric variations that are related to the traps at the film surface (21). However, these techniques are not readily applied to completed solar cell devices to measure the spatial distribution of trap states. Deep-level defect characterization methods such as deep-level transient spectroscopy are not readily applicable to perovskite devices, because the long biasing times are affected by ion migration in MHPs. Here, we demonstrate that the drive-level capacitance profiling (DLCP) method, an alternate capacitance-based technique, can provide wellcharacterized spatial distributions of carrier and trap densities in perovskites. We mapped the spatial and energetic distributions of trap states in perovskite single crystals and polycrystalline thin films. A straightforward comparison of the trap densities and distributions in perovskite single crystals and thin films in typical planar-structured solar cells was then conducted. \n\n# Drive-level capacitance profiling of perovskites \n\nThe DLCP method was developed to study the spatial distribution of defects in the band gap of amorphous and polycrystalline semiconductors, including amorphous silicon (Si) (22), $\\mathrm{CuIn}_{1-\\alpha}\\mathrm{Ga}_{\\alpha}\\mathrm{Se}_{2}\\left($ (23), and $\\mathrm{Cu_{2}Z n S n S e_{4}}\\left(24\\right)$ . With the junction capacitance measurements, DLCP can directly determine the carrier density that includes both free carrier density and trap density within the band gap of the semiconductors and their distributions in space and energy (Fig. 1A and supplementary materials). The trap density was estimated by subtracting the estimated free carrier density, which was measured at high alternating current (ac) frequencies when the measured carrier densities saturate with the further increase of the ac frequency, from the total carrier density measured at the low ac frequency. This technique allowed us to derive the energetic distribution $(E_{\\omega})$ of trap states by tuning the frequency of the ac bias (dV) or temperature $(T)$ and the position of trap states in real space by changing the direct current (dc) bias that was applied to the depletion region of the junction. As long as the spatial property of the semiconductor did not change dramatically, the differences in the profiling distance closely approximated the actual changes in the position where trap states responded to the capacitance, thus reflecting the change of the trap density in real space. In principle, DLCP can have a high resolution because the depletion edge can be continuously tuned by the applied dc bias. However, the profiling distance within the real devices was affected by the nonflat depletion interfaces caused by either the roughness or the heterogeneity of the materials, which could compromise the resolution of the profiling distance. \n\nTo validate the accuracy of the carrier density measured by DLCP, we first performed DLCP measurements on a Si solar cell, which was fabricated based on a p-type $(\\sim0.94$ ohm·cm with the dopant concentration of ${\\sim}1.6\\times10^{16}\\mathrm{cm}^{-3})$ 0 crystalline Si (p-Si) wafer with a heavily n-type diffusion layer Si $(\\mathrm{n^{+}})$ on top (details in the materials and methods section of the supplementary materials). The carrier density was calculated from the derived linear and nonlinear capacitive coefficients $C_{0}$ and $C_{1},$ respectively, by fitting the $C{-}\\delta V$ plots at different dc biases and ac frequencies (fig. S1). When the profiling distance is ${>}0.15~\\upmu\\mathrm{m}$ , which should reach the interior of the p-Si, the carrier densities measured at different ac frequencies (1 to $500~\\mathrm{kHz},$ ) were basically the same (Fig. 1B), indicating negligible contributions of the trap states to the junction capacitance. In this case, the measured carrier density should be the free carrier concentration of the p-Si wafer, which was read to be ${\\sim}1.8\\times10^{16}\\mathrm{{cm}^{-3}}$ from the DLCP measurement. This value was consistent with the dopant concentration of the p-Si wafer derived from the conductivity measurement, validating the accuracy of the carrier density measured by DLCP. \n\nBecause the profiling of carrier and trap densities by DLCP relied on the sweeping of a depletion region edge across a device from one electrode to the counter electrode, it was critical to understand the location of the junction(s) in typical planar-structured perovskite solar cells with the device structure of indium tin oxide (ITO)/poly[bis(4-phenyl)(2,4,6- trimethylphenyl)amine] (PTAA) $(15\\ \\mathrm{nm})$ )/ perovskite/fullerene $\\mathrm{(C_{60})}$ $\\mathrm{25~nm}$ )/bathocuproine (BCP)/copper (Cu). It was found that \n\n![](images/cad936e17ae290d3b0c98f811a6e9c0bf2156d7432a8aac2bb267ca0852a493d.jpg) \n\nFig. 1. DLCP technique. (A) Schematic of band bending of a $\\uprho$ -type semiconductor with deep trap states in an ${\\mathsf{n}}^{+}{\\mathsf{-p}}$ junction. $\\chi$ denotes the distance from the junction barrier where the traps may be able to dynamically change their charge states with the ac bias dV. $\\delta X$ denotes the differential change of $\\chi$ with respect to dV. $E_{\\omega}$ is the demarcation energy determined by $E_{\\omega}=k T|\\mathsf{n}(\\omega_{0}/\\omega)$ (where $k$ is the Boltzmann’s constant). EC, $\\bar{E_{\\vee}}$ , and $E_{\\mathsf{F}}$ indicate the conduction band edge, valence band edge, and Fermi level, respectively. (B) Dependence of the carrier density on the profiling distance of a Si solar cell at different ac frequencies measured by DLCP. The inset shows the schematic of the device structure. (C) Schematic of the synthesis of a bulk $\\mathsf{M A P b l}_{3}$ single crystal in an open-air solution. (D) Schematic of the synthesis of a double-layer $\\mathsf{M A P b l}_{3}$ thin single crystal using the space-confined growth method. (E) Dependence of the trap density on the profiling distance of a $\\mathsf{M A P b l}_{3}$ single crystal measured by DLCP. The inset shows the device structure. (F) Dependence of the trap density on the profiling distance of a double-layer $\\mathsf{M A P b l}_{3}$ thin single crystal. The inset shows the cross-sectional SEM image of the double-layer $\\mathsf{M A P b l}_{3}$ thin single crystal. The thicknesses of the top and bottom single crystals were 18 and $35\\upmu\\mathrm{m}$ , respectively. \n\nthese perovskite solar cells essentially had a ${\\mathrm{~\\mathfrak~{n}^{+}~}}$ -p junction formed between the $\\mathrm{C}_{60}$ and the perovskites (figs. S2 and S3). Another concern with DLCP measurements of MHPs is the role of ion migration. During the DLCP measurement, a positive dc bias was usually applied onto perovskite devices, which actually partially compensated for the built-in field in the devices. Thus, the field in the device was always less than the built-in field, which should, in principle, minimize ion migration. In addition, each DLCP scan takes only a few minutes, and we confirmed the negligible influence of the ion migration on the DLCP measurement of these hysteresis-free perovskite solar cells by performing consecutive forward and backward scans of the dc biases (fig. S4). \n\nWe synthesized bulk $\\mathrm{CH_{3}N H_{3}P b I_{3}(M A P b I_{3})}$ single crystals using the inverse solubility method (Fig. 1C). The DLCP measurements were performed on a $\\mathbf{MAPbI_{3}}$ single-crystal device with a structure of gold $\\mathrm{(Au)/MAPbI_{3}/}$ $\\mathrm{C_{60}/B C P/C u}$ , where both sides of the crystal were polished to remove the defective surface layers (fig. S5). A symmetric distribution of the trap density was observed (Fig. 1E), in a good agreement with the structural symmetry of the double-side polished $\\mathrm{\\mathbf{MAPbI}_{3}}$ single crystal. This result demonstrated the spatial profiling of trap densities in $\\mathrm{\\mathbf{MAPbI_{3}}}$ single crystals by DLCP. The trap density near the interface region was ${\\sim}10$ -fold greater than that inside the $\\mathbf{MAPbI_{3}}$ single crystal. This difference indicated that dangling bonds at the surface of the crystal form charge traps. \n\nTo determine whether the profile depth corresponded to the physical material depth, we made a device with double-layer $\\mathbf{MAPbI_{3}}$ thin single crystals so that we knew the location of the charge traps (Fig. 1D). We first synthesized a $35\\mathrm{-}\\upmu\\mathrm{m}$ -thick $\\mathbf{MAPbI_{3}}$ thin single crystal on a PTAA/ITO substrate using the space-confined growth method (25) and then interrupted the growth by exposing the top surface of the thin single crystal to air for 1 min before continuing the crystal growth. This step created a distinct boundary between the two layers [cross-sectional scanning electron microscope (SEM) image in the inset of Fig. 1F] that should be rich in charge traps. This defective interface was located $18\\upmu\\mathrm{m}$ below the surface of the top subcrystal (inset of Fig. 1F). The profiled trap density of this device (Fig. 1F) showed a peak in the trap density at the profiling distance of $18\\upmu\\mathrm{m}$ . \n\n# Trap distributions in $\\mathsf{M A P b l}_{3}$ thin single crystals \n\nWe studied the trap distribution in perovskite single-crystal solar cells. Perovskite solar cells made from a single-crystal perovskite could, in principle, have a power conversion efficiency (PCE) approaching the Shockley-Queisser limit (usually $33.7\\%$ for a single junction) because of the extremely low defect density and long carrier diffusion length (3, 26). However, the highest PCE of the first-reported $\\mathbf{MAPbI_{3}}$ single-crystal solar cell was only $17.9\\%$ (25). A more recent study reported $21.1\\%$ (27), which is still far lower than that of polycrystalline solar cells. Initial studies indicate that thin crystals formed by the space-confined growth method have a smaller carrier diffusion length (10 to $20\\upmu\\mathrm{m}\\dot{}$ ) than that of thick bulk crystals $(\\mathrm{{175}\\:\\upmu m})$ , which do not suffer from the impact of substrates. (25). However, the underlying mechanism limiting carrier diffusion in thin crystals was not clear. \n\nWe conducted DLCP measurements to understand the relationship of trap density and distribution with synthetic-crystal methods. Figure 2A shows the spatial distribution of carrier densities throughout a typical $\\mathbf{MAPbI_{3}}$ thin single crystal that was synthesized by the space-confined growth method in the device with a structure of ITO/PTAA $\\mathrm{\\Delta\\mAPbI_{3}}$ $(39\\upmu\\mathrm{m})/$ $\\mathrm{C_{60}/B C P/C u}$ at different ac frequencies. The carrier density increased with the decrease in ac frequency, indicating the existence of charge traps in the $\\mathrm{\\mathbf{MAPbI_{3}}}$ thin single crystal that contributed to the junction capacitance at low ac frequencies (large $E_{\\omega})$ . Figure 2B shows a representative spatial distribution of trap densities in the $\\mathrm{\\mathbf{MAPbI_{3}}}$ thin single crystal at the ac frequency of $10\\mathrm{kHz}$ by subtracting the free carrier density measured at high ac frequencies from the total carrier density measured at the 10-kHz frequency. As the profiling position changed from the interfaces to the interior of the single crystal, the trap density decreased. This result indicated that the majority of the trap states were near the surface of the $\\mathbf{MAPbI_{3}}$ thin single crystal. The free carrier density was also higher near the surface of the $\\mathbf{MAPbI_{3}}$ thin single crystal (Fig. 2A), indicating that both self-doping and trap states are caused by defects, most likely, of different kinds. \n\n![](images/4165aa98e742eedf6fcd5d67533615365bd62b02302e4d7d67eaa28763986b79.jpg) \nFig. 2. Spatial distributions of trap states in a $\\mathsf{M A P b l}_{3}$ thin single crystal. (A) Dependence of the carrier density on the profiling distance of a $39-\\upmu\\mathrm{m}$ -thick $\\mathsf{M A P b l}_{3}$ thin single crystal at different ac frequencies, as measured by DLCP. (B) Dependence of the trap density on the profiling distance of a $\\mathsf{M A P b l}_{3}$ thin single crystal measured at an ac frequency of $10~\\mathsf{k H z}$ . The carrier density measured at $500k H z$ is regarded as free carriers. (C) Schematics of a $\\mathsf{M A P b l}_{3}$ thin single crystal on a PTAA/ITO substrate before mechanical polish, after mechanical polish, and after oxysalt $[(C_{8}-N H_{3})_{2}S O_{4}]$ treatment. (D) Trap density near the junction barrier of a $\\mathsf{M A P b l}_{3}$ thin single crystal before mechanical polish, after mechanical polish, and after oxysalt treatment. \n\nTo figure out how sensitive DLCP is to the change in the trap density close to the surface of the $\\mathbf{MAPbI_{3}}$ thin single crystals, we varied the trap density at the top surface $\\mathrm{\\DeltaC}_{60}$ side) of the $\\mathbf{MAPbI_{3}}$ thin single crystal by polishing and treating it with $(\\mathrm{C_{8}-N H_{3})_{2}S O_{4}}$ before performing DLCP measurements (Fig. 2C). Recent work has demonstrated that surface wrapping with oxysalt can effectively passivate the defective surface of perovskites with the wide–band gap oxysalts (28). The trap density was reduced by about one order of magnitude after polishing the top surface of the $\\mathrm{\\mathbf{MAPbI_{3}}}$ thin single crystal and was further reduced after the surface treatment with $(\\mathrm{C_{8}-N H_{3})_{2}S O_{4}}$ (Fig. 2D). Because DLCP only measured the carrier density in the junction area, this result also validates the finding that the measured junction is located at the perovskite/ $\\mathrm{\\DeltaC}_{60}$ interface. Thus, the interface regions of the perovskite $\\prime{\\mathrm{C}}_{60}$ and the perovskite/TPAA were readily distinguished in the spatial distribution profiling of trap states. \n\nThe trap density distribution in the $\\mathbf{MAPbI_{3}}$ thin single crystal synthesized by the spaceconfined method was quite different from that in the bulk crystal. The trap densities varied by up to five orders of magnitude, and the trap density near both surfaces was two to four orders of magnitude higher than that in the bulk crystals. The trap density decreased gradually toward the center of the crystal, and its distribution along the normal direction was not symmetric, despite both surfaces of the thin single crystal contacting PTAA/ITO during the growth process. To understand these differences, we synthesized $\\mathbf{MAPbI_{3}}$ thin single crystals with different thicknesses (10 to ${\\it39}\\upmu\\mathrm{m}{\\it\\dot{\\Omega}}$ ) and investigated the variation of the trap density distribution with the change in the crystal thicknesses (Fig. 3A). The minimal bulk trap density $(N_{\\mathrm{T}\\operatorname*{min}})$ inside the $\\mathbf{MAPbI_{3}}$ thin single crystal, which occurred near the center of the crystal, decreased from ${\\sim}3.2\\times10^{12}$ to $1.9\\times$ $10^{11}~\\mathrm{{cm}^{-3}}$ as the thickness of the thin single crystal increased from 10 to $32\\upmu\\mathrm{m}$ and began to saturate with increased crystal thickness (Fig. 3B). The saturated $N_{\\mathrm{T}\\operatorname*{min}}$ of $1.8\\times10^{11}\\mathrm{cm}^{-3}$ approached that of the bulk $\\mathbf{MAPbI_{3}}$ single crystal synthesized in open-air solution (Fig. 1E). These results indicate that there is a critical crystal thickness for the $\\mathbf{MAPbI_{3}}$ thin single crystals synthesized by the space-confined method, below which the trap density inside the crystals was substantially higher than that in the bulk crystal. We speculate that the space-confined method may induce defects through the strain imposed by the mismatch of the substrates and the crystals during growth and that the strain inside the crystals may be released with the increase in crystal thickness. Another possible mechanism for defect formation is that the substrates affect the transport of ions for micrometer-scale channels. The microfluid would undergo laminar flow at low flow rates near the substrates (inset of Fig. 3B) (29). For the thinner single crystals, the averaged velocity of the solution flow would be reduced owing to the confinement of the boundary layer by the small space, resulting in not enough ions being delivered to the crystal for growth. Insufficient ion delivery to the crystal surface would create a deficiency for one type of ions, or misfit defects. Similarly, the trap density near the \n\n$\\mathrm{\\mathbf{MAPbI_{3}}}/$ PTAA interface also decreased with the increase in the crystal thickness and was essentially constant with further increases in crystal thickness (Fig. 3A). However, the imposed strains between the two sides of the single crystal and the substrates were not always identical because of the subtle difference in the roughness of the two PTAA/ITO substrates, which led to the different defect density distributions at the two surfaces of the crystals. The side with a higher defect density may have a weaker contact with the PTAA/ITO substrate, making the PTAA/ ITO substrate easier to be peeled off from this side. It is this defective side that $\\mathrm{C}_{60}$ was deposited on during the device fabrication process that was used. Moreover, the distribution of trap density in $\\mathbf{MAPbI_{3}}$ thin single crystals depended not only on the spacing of the two substrates but also on the substrate upon which the crystals grew. The latter also affects the strain inside the crystals and the microfluid of the precursor solution, as evidenced by the difference in the trap densities measured in the top and bottom subcrystals of the doublelayer sample in Fig. 1F. The top subcrystal had a much higher $N_{\\mathrm{T}\\operatorname*{min}}$ than the bottom $\\mathbf{MAPbI_{3}}$ thin single crystal grown directly on a PTAA/ ITO substrate (Fig. 3A). \n\nWe examined further the tDOS in energy space in the $\\mathbf{MAPbI_{3}}$ thin single crystal with a thickness of $39\\upmu\\mathrm{m}.$ . To verify the effectiveness of the DLCP in determining the tDOS, we derived the tDOS in the $\\mathrm{\\mathbf{MAPbI_{3}}}$ thin single crystal by both TAS and DLCP methods, because TAS is a well-established method to determine the tDOS in perovskite devices (15). The temperature-dependent differential capacitance spectra $\\left(-f{\\cdot}\\mathrm{d}C/\\mathrm{d}f{\\cdot}f,\\right)$ where $f$ is the frequency of the ac bias) and the Arrhenius plot of the characteristic frequencies with respect to the temperature $[\\ln(\\omega/T^{2})\\ –1/T]$ of the device are shown in fig. S6. Figure 3C shows the $E_{\\omega}\\mathrm{.}$ dependent $N_{\\mathrm{T}}$ for the $\\mathbf{MAPbI_{3}}$ thin single crystal measured by TAS. For the DLCP measurement, the tDOS could be estimated by the derivative of the carrier density with respect to $E_{\\omega},$ that is, $N_{\\mathrm{T}}\\left(E_{\\upomega}\\right)=\\mathrm{d}N/\\mathrm{d}(E_{\\upomega})$ . As the profiling distance was scanned from one side of the single crystal to the other, the energy distribution and spatial distribution of the trap states in the $\\mathbf{MAPbI_{3}}$ thin single crystal were mapped (Fig. 3D). \n\nThe tDOS measured by DLCP exhibited a similar feature to that measured by TAS (fig. S7). Both tDOS spectra showed three trap bands with $E_{\\omega}$ values of $0.27\\mathrm{eV}$ (zone I), 0.35 eV (zone II), and greater than $0.40\\mathrm{eV}$ (zone III). Previous studies speculated that the deep trap states were mainly related to the surface defects of the perovskite and that shallower trap states were more likely from inside the perovskite (15). The spatial and energy distributions of the tDOS in perovskites (Fig. 3D) indicated that the deep trap density at the MAPbI3/PTAA interface was $>100$ -fold higher than inside the $\\mathbf{MAPbI_{3}}$ thin single crystal, whereas the shallow trap density at the MAPbI3/PTAA interface was barely higher than those inside the single crystal. Deep traps were mainly located at the surface region of the $\\mathbf{MAPbI_{3}}$ thin single crystals, whereas the shallower traps were prevalent throughout the entire single crystals. This difference indicated their different origins, that is, shallow trap bands I and II may form from point defects in the bulk and deep trap band III originated from the dangling bonds at the material surface. The measured carrier densities near the $\\mathrm{MAPbI_{3}/C_{60}}$ interface at the ac frequencies from 1 to $50\\mathrm{kHz}$ were quite near each other (Fig. 2A), indicating a low deep trap density of states near the $\\mathrm{MAPbI_{3}/C_{60}}$ interface caused by the passivation effect of $\\mathrm{C}_{60}$ . \n\n# Trap distributions in polycrystalline perovskite films \n\nThe spatial and energetic distributions of trap states in polycrystalline perovskite thin films are crucial to understanding the performance of those solar cells. We first performed DLCP measurement on a typical planar-structured perovskite thin-film solar cell with the device structure of $\\mathrm{\\Delta[TO/PTAA/MAPbI_{3}/C_{60}/B C P/C u},$ , which has a typical PCE of $17.8\\%$ (table S1). The measured trap density distribution and tDOS mapping in the $\\mathrm{\\mathbf{MAPbI_{3}}}$ thin film are shown in fig. S8. The $\\mathbf{MAPbI_{3}}$ polycrystalline thin film shows a similar feature of trap distribution with the thin single crystals in which most of the deep trap states (trap band III) are located close to the MAPbI3/PTAA interface. Then, we carried out DLCP measurement on a high-performance solar cell with the device structure of ITO/PTAA $\\mathrm{^{\\prime}C s_{0.05}[H C(N H_{2})_{2}]_{0.70}}$ $(\\mathrm{CH_{3}N H_{3}})_{0.25}\\mathrm{PbI_{3}}(\\mathrm{Cs_{0.05}F A_{0.70}M A_{0.25}P b I_{3}})/$ $\\mathrm{C_{60}/B C P/C u}$ , in which the perovskite thin films were modified with the additive of 1,3- diaminopropane (30). The open circuit voltage $(V_{\\mathrm{OC}})$ , short-circuit current density $(J_{\\mathrm{SC}})$ , fill factors $(\\mathrm{FF}),$ and PCE of the solar cell were $1.15\\mathrm{V}_{:}$ $23.4\\mathrm{mAcm^{-2}}$ , $77.3\\%$ , and $20.8\\%$ , respectively (Fig. 4A). The spatial distribution of the carrier densities in the $\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.70}\\mathrm{MA}_{0.25}\\mathrm{PbI}_{3}$ solar cell is shown in fig. S9. The differences in the carrier densities measured at different ac frequencies revealed the presence of trap states in these perovskite thin films. The trap density at the perovskite $\\mathrm{^{\\prime}C}_{60}$ interface was about 10-fold lower than that at the perovskite/PTAA interface (fig. 4B), which might be caused by the passivation of $\\mathrm{C}_{60}$ on the surface defects of the perovskite thin film (15, 31). Both interfaces had a higher defect density compared with the interior of the perovskite films. \n\nIn the tDOS spectrum of the $\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.70}\\mathrm{MA}_{0.25}$ $\\mathrm{PbI_{3}}$ solar cell measured by TAS (Fig. 4C), the attempt-to-escape angular frequency ${\\mathfrak{o}}_{0}$ was derived from the temperature-dependent $c\\mathrm{-}f$ measurements, as detailed in the materials and methods. The tDOS spectrum contained three different trap centers, dividing the spectrum into three energy bands (marked as I, II, and areas where the fast Fourier transforms of the lattices were performed, with white and yellow indicating zone axes of [1 −1 −1] and [2 1 0], respectively. The red lines denote the orientation of the facets. (F) Fast Fourier transforms of the areas indicated in (E). (G) Measured and simulated $J-V$ curves of planar-structured solar cells based on $\\mathsf{M A P b l}_{3}$ polycrystalline thin films. The thin-film (single crystal) bulk and interface trap densities were adopted for the simulations. (H) Dependence of the PCE of the $\\mathsf{M A P b l}_{3}$ thin-film solar cell on the bulk and interface trap densities. The dashed lines denote the contour lines of certain PCE values, which are noted. \n\n![](images/5a9e110176c1d8cb4d75632d4b569833b26b797f8a97bcb7e09efc294af5e450.jpg) \nFig. 3. Thickness-dependent trap density distributions in $M A P b\\vert_{3}$ thin single crystals. (A) Dependence of the trap densities on the profiling distances of $\\mathsf{M A P b l}_{3}$ thin single crystals with different crystal thicknesses measured at an ac frequency of $10~\\mathsf{k H z}$ . The location of the $\\mathsf{M A P b l_{3}/C_{60}}$ interface for each crystal is aligned for comparison. The black dashed arrow indicates the trend of the change of minimal trap density $N_{\\top\\operatorname*{min}}$ in $\\mathsf{M A P b l}_{3}$ single crystals with different thicknesses. (B) Dependence of the $N_{\\top\\operatorname*{min}}$ in the $\\mathsf{M A P b l}_{3}$ thin single crystal on the crystal thickness. The horizontal dashed line indicates the $N_{\\top\\operatorname*{min}}$ value in a bulk $\\mathsf{M A P b l}_{3}$ single crystal. The inset shows a schematic of the laminar flow of the precursor solution between two PTAA/ITO glasses during the growth of the crystal. The arrows denote the direction of the laminar flow of the precursor solution, and the length of the arrow denotes the laminar flow velocity. (C) tDOS of a $\\mathsf{M A P b l}_{3}$ thin single crystal, as measured by the TAS method. The thickness of the $\\mathsf{M A P b l}_{3}$ thin single crystal was $39\\upmu\\mathrm{m}$ . (D) Spatial and energy mapping of the densities of trap states in the $\\mathsf{M A P b l}_{3}$ thin single crystal, as measured by DLCP. \n\n![](images/9b5d54ee0ffb33a8bd5cc0193bb5e1c056357cb85b29969ca76db4cf25e6d19a.jpg) \nFig. 4. Spatial and energetic distributions of trap states in perovskite thin films. (A) $J-V$ curve of the $\\mathsf{C s}_{0.05}\\mathsf{F A}_{0.70}\\mathsf{M A}_{0.25}\\mathsf{P b}\\mathsf{l}_{3}$ thin-film solar cells. The inset shows the device structure. (B) Dependence of the trap density on the profiling distance for the perovskite thin film in the solar cell measured at an ac frequency of $10k H z.$ (C) tDOS of the perovskite thin-film solar cell, as measured by the TAS method. (D) Spatial and energy mapping of the densities of trap states of the perovskite thin film in the solar cell, as measured by DLCP. (E) Cross-sectional HR-TEM image of the stack of perovskite and PTAA. The dashed squares mark the \n\nTable 1. Comparison of the minimal bulk trap densities and the interface trap densities between perovskite single crystals and thin films. The interconnected layers are listed in parentheses. The trap densities are calculated at an ac frequency of $10~\\mathsf{k H z}$ . The interface trap density values vary depending on different surface and interface conditions. \n\n\n
Perovskite materialMinimal bulk trap density (NT min) (cm-3)Interface trap density (cm-3)
MAPbBr3 single crystal (bulk)6.5 ×10101.8× 1012(C60) 1.8 × 1012 (Au)
MAPbl single crystal (bulk)1.8 ×10111.2×1012(C60) 1.2 × 1012 (Au)
MAPblg single crystal (thin)1.9×10l to 3.2 ×102.0 × 1013 to 1.1 × 1016 (0 1.5×1013 to 1.0×1015(PTAA)
CSo.05FAo7oMAo.5Pblim4.3 ×10141.2 ×107 (PTAA) 8.6×1015(C60)
Rbo.05CSo.05FAo.75MAo.15Pb(lo.95Bro.05)3fim5.7 ×10142.0×101(C60) 1.1 × 1017 (PTAA)
FAo.92MAo.0gPbl film7.9 × 10141.9×101(C0) 9.0×106(PTAA)
MAPbl3 film9.2 × 10141.2 × 107 (PTAA) 2.2×101(C60)
CSo.05FAo.8MAo.15Pbo.5Sno.5(l0.85Bro.15)3flm1.2 × 10151.5× 10 (C60) 1.1 × 1017 (PTAA)
\n\nIII). The trap distributions in bands I, II, and III of the perovskite thin film are centered at \\~0.33, 0.38, and $0.52\\mathrm{eV}$ , respectively. The spatial mapping of the tDOS in the perovskite thin film (Fig. 4D) revealed that the tDOSs at both interface regions were $>100$ -fold higher than that in the film. In addition, deep traps in band III were more localized at the perovskite/ PTAA interface, whereas shallower traps in bands I and II were enriched at both interfaces. This result showed that the perovskite surfaces of polycrystalline films were rather defective (31). \n\nTo understand the origin of the high deep trap density at the perovskite/TPAA interface, we examined this region by high-resolution transmission electron microscopy (HR-TEM). As shown in Fig. 4, E and F, the lattice had basically the same orientation with the zone axis of $[1-1-1]$ in the grain interior, whereas there were a large number of small crystals with sizes of a few nanometers and different orientations (zone axis of [2 1 0]) with respect to the grain interior at the region near the PTAA/perovskite interface. At least 10 samples were examined with different perovskite compositions. All of them had very similar morphology, confirming the heterogeneity of the perovskite films in the vertical direction (32), which we believe was caused by the deposition method–related grain-growth behavior that made the interface between the perovskite and the PTAA rather defective and rich in charge trap centers. Given the excellent passivation effect of $\\mathrm{C}_{60}$ on the deep trap states at the perovskite surface (33), the remaining deep trap states were mainly located near the perovskite/PTAA interface, which might limit the efficiency of the perovskite thin-film solar cells. \n\n# Perovskite single crystals versus polycrystalline films \n\nTo find out the differences between the trap density distributions in perovskite single crystals and polycrystalline thin films and in those with different compositions, we measured the $N_{\\mathrm{Tmin}}$ and the interface trap densities in several perovskite single crystals and polycrystalline thin films with different compositions (Table 1). The bulk $\\mathbf{MAPbI_{3}}$ or $\\mathbf{MAPbBr_{3}}$ single crystal showed a quite lo $\\mathrm{w}N_{\\mathrm{T}\\operatorname*{min}}(<2.0\\times$ $10^{11}\\mathrm{cm}^{-3})$ which increased to $3.0\\times10^{12}\\mathrm{~cm}^{-3}$ in $\\mathrm{\\mathbf{MAPbI_{3}}}$ thin single crystals, depending on their growth conditions. However, these values are still two to three orders of magnitude lower than that in $\\mathbf{MAPbI_{3}}$ polycrystalline thin films, which are generally formed by a very quick thin-film coating process. In addition, our current results signify the importance of proper surface-modification processes (mechanical polishing and oxysalt treatment) to reduce trap densities in perovskite single crystals. Similar scenarios could be applied to polycrystalline thin films to reduce the interface trap densities. \n\nTable 1 also lists the $N_{\\mathrm{T}\\operatorname*{min}}$ and the interface trap densities of several typical polycrystalline perovskite thin films used in planar-structured solar cells, including $\\mathrm{Cs_{0.05}F A_{0.70}M A_{0.25}P b I_{3}},$ $\\mathrm{Rb_{0.05}C s_{0.05}F A_{0.75}M A_{0.15}P b(I_{0.95}B r_{0.05})_{3}}$ , $\\mathrm{FA_{0.92}M A_{0.08}P b I_{3}}$ , $\\mathrm{\\mathbf{MAPbI}_{3}}$ , and $\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.8}$ $\\mathrm{MA_{0.15}P b_{0.5}S n_{0.5}(I_{0.85}B r_{0.15})_{3}}.$ . The current density– voltage $\\left(J\\ –V\\right)$ curves and trap density distributions of the solar cells fabricated based on these films are shown in fig. S10. The corresponding parameters of device performance are listed in table S1. Among these configurations, the $\\mathrm{Cs_{0.05}F A_{0.70}M A_{0.25}P b I_{3}}$ -based solar cell exhibited the highest PCE of $20.8\\%$ after optimizing the fabrication processes (30) and had the lowest $N_{\\mathrm{T}\\ \\operatorname*{min}}$ of $\\sim4.0\\times10^{14}~\\mathrm{cm}^{-3}$ , which was still more than two orders of magnitude greater than that in high-quality single crystals. For the perovskite solar cells fabricated based on the other compositions without comprehensive optimizations, the $\\mathrm{Rb}_{0.05}\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.75}\\mathrm{MA}_{0.15}\\mathrm{Pb}$ $(\\mathrm{I}_{0.95}\\mathrm{Br}_{0.05})_{3}$ -based solar cell showed a relatively high PEC of $19.6\\%$ , whereas $\\mathrm{FA_{0.92}M A_{0.08}P b I_{3}}$ and $\\mathbf{MAPbI_{3}}$ showed lower PCEs of ${\\sim}18.0\\%$ . Accordingly, the $N_{\\mathrm{T}\\operatorname*{min}}$ in $\\mathrm{Rb}_{0.05}\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.75}$ $\\mathbf{MA_{0.15}P b(I_{0.95}B r_{0.05})_{3}}$ was moderately lower than that in $\\mathrm{FA_{0.92}M A_{0.08}P b I_{3}}$ and $\\mathbf{MAPbI_{3}}$ . The tin-incorporated $\\mathrm{Cs_{0.05}F A_{0.8}M A_{0.15}P b_{0.5}S n_{0.5}}$ $(\\mathrm{I}_{0.85}\\mathrm{Br}_{0.15})_{3}$ film showed the highest $N_{\\mathrm{T}\\operatorname*{min}}$ of $\\sim1.2\\times10^{15}\\mathrm{cm}^{-3}$ among all the configurations, reflecting the relative defective nature of tincontaining thin films. \n\nThe trend of the variation in the PCE of these solar cells was basically in accordance with the change in the $N_{\\mathrm{T}\\operatorname*{min}}$ in different perovskite thin films. This finding signifies the importance of reducing the trap densities in the perovskite thin films for enhancing the device performances. Our current results demonstrate that intrinsic trap densities in perovskite polycrystalline thin films were closely related to the film compositions as well as the film fabrication process. For all the perovskite thin-film compositions, the interface trap density was in the range of ${\\sim}9.0\\times10^{15}$ to $2.0\\times10^{17}\\mathrm{cm}^{-3}$ , depending on the type of the charge transport layers. Overall, the trap density at the perovskite/PTAA interface was higher than that at the perovskite $\\mathrm{\\DeltaC_{60}}$ interface because of the formation of large amounts of small crystals near the perovskite/PTAA interface. This morphology points out an important direction to explore for further boosting the performance of perovskite solar cells or other electronic devices by reducing the trap density at the perovskite/PTAA interfaces. \n\n# Relationship of trap density and solar cell efficiency \n\nWe used the solar cell capacitance simulator to simulate both thin-film and single-crystal perovskite solar cells with varied trap densities. We first used the trap density and distribution measured by DLCP and TAS, which is detailed in fig. S11 and tables S2 and S3, to simulate a $\\mathbf{MAPbI_{3}}$ thin-film solar cell. Here, the capture cross sections of the bulk and interface trap states were determined by a global fitting of the experimental $J_{-}V$ curves (fig. S12). Figure 4G shows the simulated $J_{-}V$ curve of the $\\mathbf{MAPbI_{3}}$ thin-film solar cell with a bulk trap density of $5.0\\times10^{14}\\mathrm{cm}^{-3}$ and interface trap density of $1.0\\times10^{17}\\mathrm{cm}^{-3}$ obtained from the polycrystalline thin films, which was near the measured value. We simulated temperature-dependent $J_{\\cdot}V$ curves of the $\\mathbf{MAPbI_{3}}$ thin-film solar cell. As shown in fig. S13, the simulated $J_{-}V$ curves agree well with the measured $J{-}V$ curves at different temperatures, which indicates that the DLCP measurement range of traps is deep enough to predict the behavior of these solar cells. After reducing only the bulk trap density to $1.0\\times10^{13}\\mathrm{cm}^{-3}$ , the value attainable in single-crystalline $\\mathrm{\\mathbf{MAPbI_{3}}},$ , the PCE increased to $20.0\\%$ and saturated with any further decrease in the bulk trap density (Fig. 4H and fig. S14). This saturated PCE was mainly limited by the large interface trap density. If the interface trap density was reduced to that in a $\\mathbf{MAPbI_{3}}$ thin single crystal $(2.0\\times10^{15}\\mathrm{cm}^{-3},$ , the PCE could be further enhanced to $25.4\\%$ , which is near the PCE of $26.6\\%$ for a trap-free $\\mathbf{MAPbI_{3}}$ thin-film solar cell (Fig. 4G). Simulation of single-crystal solar cells also gave data that were a good match to the experimental data (27), which again showed that the PCE of the $\\mathrm{\\mathbf{MAPbI_{3}}}$ single-crystal solar cell could be further improved to $26.8\\%$ once the interface trap densities are reduced to that of the bulk trap density (fig. S15). \n\nLower–band gap perovskites are being studied to harvest more sunlight, so we simulated perovskite thin-film solar cells with band gaps of 1.50 and 1.47 eV, which correspond to the compositions of $\\mathrm{FA_{0.92}M A_{0.08}P b I_{3}}$ and $\\mathrm{FAPbI_{3}}$ (if it can be stabilized), respectively (34, 35). Assuming that these materials have the same trap densities (a bulk trap density of $5.0\\ \\times$ $10^{14}\\mathrm{cm}^{-3}$ and interface trap density of $1.0\\times$ $10^{17}~\\mathrm{cm}^{-3})$ and capture cross sections as regular polycrystalline $\\mathbf{MAPbI_{3}}$ thin films, the devices showed PCEs of 22.5 and $22.8\\%$ , respectively (fig. S16). The efficiencies could be further increased to 27.7 and $28.4\\%$ , respectively, when the trap densities in the thin film are substantially reduced to be the same as those in single crystals. \n\n# REFERENCES AND NOTES \n\n1. N.-G. Park, Mater. Today 18, 65–72 (2015). \n2. L. M. Herz, ACS Energy Lett. 2, 1539–1548 (2017). \n3. Q. Dong et al., Science 347, 967–970 (2015). \n4. C. Gehrmann, D. A. Egger, Nat. Commun. 10, 3141 (2019). \n5. S. B. Zhang, S.-H. Wei, A. Zunger, Phys. Rev. Lett. 78, \n4059–4062 (1997). \n6. K. X. Steirer et al., ACS Energy Lett. 1, 360–366 (2016). \n7. W.-J. Yin, T. Shi, Y. Yan, Appl. Phys. Lett. 104, 063903 (2014). \n8. C. Eames et al., Nat. Commun. 6, 7497 (2015). \n9. A. Walsh, D. O. Scanlon, S. Chen, X. G. Gong, S. H. Wei, Angew. \nChem. Int. Ed. 54, 1791–1794 (2015). \n\n10. G. J. Wetzelaer et al., Adv. Mater. 27, 1837–1841 (2015). \n11. W. Tress et al., Adv. Energy Mater. 5, 1400812 (2015). \n12. J. M. Ball, A. Petrozza, Nat. Energy 1, 16149 (2016). \n13. T. Leijtens et al., Adv. Energy Mater. 5, 1500962 (2015). \n14. C. Ran, J. Xu, W. Gao, C. Huang, S. Dou, Chem. Soc. Rev. 47, 4581–4610 (2018). \n15. Y. Shao, Z. Xiao, C. Bi, Y. Yuan, J. Huang, Nat. Commun. 5, 5784 (2014). \n16. Y. Hu et al., Adv. Energy Mater. 8, 1703057 (2018). \n17. I. Levine et al., ACS Energy Lett. 4, 1150–1157 (2019). \n18. C. M. Sutter-Fella et al., ACS Energy Lett. 2, 709–715 (2017). \n19. A. Musiienko et al., Energy Environ. Sci. 12, 1413–1425 (2019). \n20. E. T. Hoke et al., Chem. Sci. 6, 613–617 (2015). \n21. O. Hentz, Z. Zhao, S. Gradečak, Nano Lett. 16, 1485–1490 (2016). \n22. C. E. Michelson, A. V. Gelatos, J. D. Cohen, Appl. Phys. Lett. 47, 412–414 (1985). \n23. J. T. Heath, J. D. Cohen, W. N. Shafarman, J. Appl. Phys. 95, 1000–1010 (2004). \n24. H.-S. Duan et al., Adv. Funct. Mater. 23, 1466–1471 (2013). \n25. Z. Chen et al., Nat. Commun. 8, 1890 (2017). \n26. D. Shi et al., Science 347, 519–522 (2015). \n27. Z. Chen et al., ACS Energy Lett. 4, 1258–1259 (2019). \n28. S. Yang et al., Science 365, 473–478 (2019). \n29. H.-S. Rao, B.-X. Chen, X.-D. Wang, D.-B. Kuang, C.-Y. Su, Chem. Commun. 53, 5163–5166 (2017). \n30. W.-Q. Wu et al., Sci. Adv. 5, eaav8925 (2019). \n31. B. Chen, P. N. Rudd, S. Yang, Y. Yuan, J. Huang, Chem. Soc. Rev. 48, 3842–3867 (2019). \n32. E. M. Tennyson, T. A. S. Doherty, S. D. Stranks, Nat. Rev. Mater. 4, 573–587 (2019). \n33. Q. Wang et al., Energy Environ. Sci. 7, 2359–2365 (2014). \n34. Q. Jiang et al., Nat. Photonics 13, 460–466 (2019). \n35. T. Niu et al., Energy Environ. Sci. 11, 3358–3366 (2018). \n\n# ACKNOWLEDGMENTS \n\nFunding: This work was supported by the Center for Hybrid Organic Inorganic Semiconductors for Energy (CHOISE), an Energy Frontier Research Center funded by the Office of Basic Energy Sciences, Office of Science within the U.S. Department of Energy. The study of the silicon device was supported by the Solar Energy Technologies Office (SETO) within the U.S. Department of Energy under award no. DE-EE0008749. Partial study of the single crystal growth was supported by Defense Threat Reduction Agency \n\nunder Grant HDTRA1170054. Author contributions: J.H., Z.N., and C.B. designed the experiments. Z.N. and Y.L. synthesized the perovskite single crystals. Q.J., W.-Q.W., S.C., and B.C. fabricated the polycrystalline perovskite thin-film solar cells. B.H., Z.Y., and Z.H. fabricated the silicon solar cells. Z.N. and C.B. carried out the capacitance measurements for the devices. Z.N. conducted the solar cell simulations. S.C. and X.D. carried out electron microscope measurements for the perovskites. J.H. and Z.N. wrote the paper, and all authors reviewed the paper. Competing interests: None declared. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/367/6484/1352/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S16 \nTables S1 to S3 \nReferences (36–39) \n4 November 2019; accepted 25 February 2020 \n10.1126/science.aba0893 \n\n# Science \n\n# Resolving spatial and energetic distributions of trap states in metal halide perovskite solar cells \n\nZhenyi Ni, Chunxiong Bao, Ye Liu, Qi Jiang, Wu-Qiang Wu, Shangshang Chen, Xuezeng Dai, Bo Chen, Barry Hartweg, Zhengshan Yu, Zachary Holman and Jinsong Huang \n\nScience 367 (6484), 1352-1358. DOI: 10.1126/science.aba0893 \n\n# Mapping perovskite trap states \n\nThe high efficiency of hybrid inorganic-organic perovskite solar cells is mainly limited by defects that trap the charge carriers and lead to unproductive recombination. Ni et al. used drive-level capacitance profiling to map the spatial and energetic distribution of trap states in both polycrystalline and single-crystal perovskite solar cells. The interface trap densities were up to five orders of magnitude higher than the bulk trap densities. Deep traps were mainly located at the interface of perovskites and hole-transport layers, where processing created a high density of nanocrystals. These results should aid efforts aimed at avoiding trap-state formation or passivating such defects. \n\nScience, this issue p. 1352 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41586-020-2442-2", + "DOI": "10.1038/s41586-020-2442-2", + "DOI Link": "http://dx.doi.org/10.1038/s41586-020-2442-2", + "Relative Dir Path": "mds/10.1038_s41586-020-2442-2", + "Article Title": "A mobile robotic chemist", + "Authors": "Burger, B; Maffettone, PM; Gusev, VV; Aitchison, CM; Bai, Y; Wang, XY; Li, XB; Alston, B; Li, BY; Clowes, R; Rankin, N; Harris, B; Sprick, RS; Cooper, AI", + "Source Title": "NATURE", + "Abstract": "Technologies such as batteries, biomaterials and heterogeneous catalysts have functionsthat are defined by mixtures of molecular and mesoscale components. As yet, this multi-length-scale complexity cannot be fully captured by atomistic simulations, and the design of such materials from first principles is still rare(1-5). Likewise, experimental complexity scales exponentially with the number of variables, restricting most searches to narrow areas of materials space. Robots can assist in experimental searches(6-14)but their widespread adoption in materials research is challenging because of the diversity of sample types, operations, instruments and measurements required. Here we use a mobile robot to search for improved photocatalysts for hydrogen production from water(15). The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian search algorithm(16-18). This autonomous search identified photocatalyst mixturesthat were six times more active than the initial formulations, selecting beneficial components and deselecting negative ones. Our strategy uses a dexterous(19,20)free-roaming robot(21-24), automating the researcher ratherthan the instruments. This modular approach could be deployed in conventional laboratories for a range of research problems beyond photocatalysis.", + "Times Cited, WoS Core": 793, + "Times Cited, All Databases": 877, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000546767100015", + "Markdown": "# Article \n\n# A mobile robotic chemist \n\n# Check for updates \n\nBenjamin Burger1, Phillip M. Maffettone1, Vladimir V. Gusev1, Catherine M. Aitchison1, Yang Bai1, Xiaoyan Wang1, Xiaobo Li1, Ben M. Alston1, Buyi Li1, Rob Clowes1, Nicola Rankin1, Brandon Harris1, Reiner Sebastian Sprick1 & Andrew I. Cooper1 ✉ \n\nTechnologies such as batteries, biomaterials and heterogeneous catalysts have functions that are defined by mixtures of molecular and mesoscale components. As yet, this multi-length-scale complexity cannot be fully captured by atomistic simulations, and the design of such materials from first principles is still rare1–5. Likewise, experimental complexity scales exponentially with the number of variables, restricting most searches to narrow areas of materials space. Robots can assist in experimental searches6–14 but their widespread adoption in materials research is challenging because of the diversity of sample types, operations, instruments and measurements required. Here we use a mobile robot to search for improved photocatalysts for hydrogen production from water15. The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian search algorithm16–18. This autonomous search identified photocatalyst mixtures that were six times more active than the initial formulations, selecting beneficial components and deselecting negative ones. Our strategy uses a dexterous19,20 free-roaming robot21–24, automating the researcher rather than the instruments. This modular approach could be deployed in conventional laboratories for a range of research problems beyond photocatalysis. \n\nThe mobile robot platform is shown in Fig. 1a and Extended Data Fig. 1. It can move freely in the laboratory and locates its position using a combination of laser scanning coupled with touch feedback for fine positioning (Methods and Supplementary Video 1). This gave an $(x,y)$ positioning precision of $\\pm0.12\\mathsf{m m}$ and an orientation precision of $\\theta{\\pm}0.005^{\\circ}$ within a standard laboratory environment with dimensions $7.3\\mathsf{m}\\times11\\mathsf{m}$ (Fig. 1b; Extended Data Fig. 2; Supplementary Figs. 1–10). This precision allows the robot to carry out dexterous manipulations at the various stations in the laboratory (Fig. 1; Extended Data Fig. 3) that are comparable to those performed by human researchers, such as handling sample vials and operating instruments. The robot has human-like dimensions and reach (Fig. 1a, d) and it can therefore operate in a conventional, unmodified laboratory. Unlike many automated systems that can dispense only liquids, this robot dispenses both insoluble solids and liquid solutions with high accuracy and repeatability (Supplementary Figs. 12, 13, 16–20), broadening its utility in materials research. Factoring in the time needed to recharge the battery, this robot can operate for up to $21.6\\mathsf{h}$ per day with optimal scheduling. The robot uses laser scanning and touch feedback, rather than a vision system. It can therefore operate in complete darkness, if needed (Supplementary Video 2), which is an advantage when carrying out light-sensitive photochemical reactions, as here. The robot arm and the mobile base comply with safety standards for collaborative robots, allowing human researchers to work within the same physical space (Supplementary Information section 1.5). A video of the robot operating an autonomous experiment over a 48-h period is shown in Supplementary Video 1. \n\nThe benefits of combining automated experimentation with a layer of artificial intelligence (AI) have been demonstrated for flow reactors25, photovoltaic films13, organic synthesis8–10,14, perovskites26 and in formulation problems18. However, so far no approaches have integrated mobile robotics with AI for chemical experiments. Here, we built Bayesian optimization16–18 into a mobile robotic workflow to conduct photocatalysis experiments within a ten-dimensional space. Semiconductor photocatalysts that promote overall water splitting to produce both hydrogen and oxygen are still quite rare15. For many catalysts, a sacrificial hole scavenger is needed to produce hydrogen from water, such as triethylamine (TEA)27 or triethanolamine (TEOA)28, and these amines are irreversibly decomposed in the reaction. It has proved difficult to find alternative hole scavengers that compete with these organic amines29. \n\nOur objective was to identify bioderived hole scavengers with efficiencies that match petrochemical amines and that are not irreversibly decomposed, with the long-term aim of developing reversible redox shuttles. The photocatalyst that we chose was P10, a conjugated polymer that shows good HERs in the presence of TEOA28. We first used the robot to screen 30 candidate hole scavengers (Extended Data Fig. 4). This was done using a screening approach, without any AI. Initially, the robot loads a solid-dispensing station that weighs any solid components into sample vials (Fig. 1c), in this case the catalyst, P10. Next, the vials are transported 16 at a time in a rack to a dual liquid-dispensing station (Extended Data Fig. 3c), where the liquid components are added; here, $50{\\bf g}{\\bf l}^{-1}$ aqueous solutions of the candidate hole scavengers (Supplementary Videos 3, 4). The robot then places the vials into a capping station, which caps the vials under nitrogen (Supplementary Fig. 21; Supplementary Video 5). Optionally, the capped vials are then placed into a sonication station (Supplementary Fig. 23; Supplementary \n\n![](images/d0d159b94dac3f86f32df70fc84acca7bf2981e47e1fc2d0e0b67a8fb92282d8.jpg) \nFig. 1 | Autonomous mobile robot and experimental stations. a, Photograph showing robot loading samples into the photolysis station. b, Map of the laboratory generated by laser scanning showing positions of the eight stations; the orange crosshairs indicate recorded navigation locations and the robot position is indicated by the green rectangle. Inputs 1–3 are areas for the storage of empty vials or completed sample racks. GC, gas chromatography station. c, Robot loading empty sample vials into the solid-dispensing station before dispensing the photocatalyst. d, Loading the gas chromatography station with a new rack of samples for analysis. e, Storing racks of completed samples in Input Station 1 after gas chromatography analysis. \n\nVideo 3) to disperse the solid catalyst in the aqueous phase. The vials are then transported to a photolysis station, where they are illuminated with a mixture of ultraviolet and visible light (Fig. 1a; Extended Data Fig. 3b; Supplementary Fig. 24; Supplementary Video 6). After photolysis, the robot transfers the vials to a head space gas chromatography station where the gas phase is analysed for hydrogen (Fig. 1d) before storage of completed samples (Fig. 1e). Except for the capping station and the photolysis station, which were built specifically for this workflow, the other stations used commercial instruments with no physical hardware modifications: the robot operates them in essentially the same way that a human researcher would. \n\nConditional automation was used in this hole scavenger screen to repeat any hits; that is, samples that showed a hydrogen evolution rate (HER) of ${\\tt>}200\\upmu\\mathrm{molg^{-1}h^{-1}}$ were automatically re-analysed five times. Most of the 30 scavengers produced little or no hydrogen (Extended Data Fig. 4), except for l-ascorbic acid $(256\\pm24\\upmu\\mathrm{mol}\\mathbf{g}^{-1}\\mathsf{h}^{-1})$ and l-cysteine $(1,201\\pm88\\upmu\\mathrm{mol}\\mathbf{g}^{-1}\\mathsf{h}^{-1})$ . Analysis by $^1\\mathsf{H}$ nuclear magnetic resonance (NMR) spectroscopy showed that l-cysteine was cleanly converted to l-cystine (Supplementary Fig. 32), indicating that it may have potential as a reversible redox shuttle in an overall water splitting scheme30. \n\nWhile it showed promise as a hole scavenger, l-cysteine produced much less hydrogen than an aqueous solution of TEOA at the same gravimetric concentration $(2,985\\pm103\\upmu\\mathrm{mol}\\mathbf{g}^{-1}\\mathsf{h}^{-1}$ at $50\\mathrm{g}\\vert^{-1})$ . We therefore sought to increase the HER of the P10/l-cysteine system by using an autonomous robotic search based on five hypotheses (Fig. 2a). \n\n![](images/96152d39706b44f637e5b9f980cb6be72017946f442145cff739daf545c72c13.jpg) \nFig. 2 | Hypothesis-led autonomous search strategy. a, The robot searches chemical space to optimize the activity of the photocatalyst $^+$ scavenger combination according to five separate hypotheses. It does this by simultaneously varying the concentration of the ten chemical species shown here. b, Plot showing the size of the simplex, or the search space, created with a discretization of 19 concentrations for each liquid and 21 concentration levels for the solid catalyst, P10, which corresponds to the solid/liquid dispensing precision over the constrained space of the experiment. For this ten-component problem, the full simplex has 98,423,325 points. \n\nThe first hypothesis was that dye sensitization might improve light absorption and hence the HER, as found for the structurally related covalent organic framework, FS-COF31. Here, three dyes were investigated (Rhodamine B, Acid Red $87^{31}$ and Methylene Blue). Second, we hypothesized that pH might influence the catalytic activity (NaOH addition). The third hypothesis was that ionic strength could also be important32 (NaCl addition). Catalyst wettability is known to be a factor in photocatalytic hydrogen evolution using conjugated polymers33, so the addition of surfactants (sodium dodecyl sulphate, SDS, and polyvinylpyrrolidone, PVP) formed our fourth hypothesis. Fifth, we speculated that sodium disilicate might act as a hydrogen-bonding anchor for the scavenger, l-cysteine, or for the dyes, based on the observation that it aids in the absorption of dyes onto the surface of carbon nitride34. \n\n![](images/b0b230ce93aa2ed4b4e4187b78152f3457abb8b62553f205605949de532bfbc7.jpg) \nFig. 3 | Output from the autonomous robotic search. a, Plot showing hydrogen evolution achieved per experiment in an autonomous search that extended over 8 days. Sixteen experiments were performed per batch, along with two baseline controls. The baseline hydrogen evolution was $3.36{\\pm}0.30{\\upmu\\mathrm{mol}}$ (black squares). The maximum rate attained after 688 experiments was $21.05\\upmu\\mathrm{molh}^{-1}$ . The robot made 319 moves between stations \nand travelled a total distance of $2.17\\mathrm{km}$ during this 8-day experiment. b, Radar plot showing the evolution of the average sampling of the search space in millilitres; the scale denotes the fraction of maximum solution volume dispensed. The starting conditions (Batch 1) were chosen randomly. The best catalyst formulation found after 43 batches contained P10 $(5\\mathrm{mg})$ , NaOH (6 mg), l-cysteine $(200\\mathrm{mg})$ and $\\mathsf{N a}_{2}\\mathsf{S i}_{2}\\mathsf{O}_{5}(7.5\\mathsf{m g})$ in water $(5\\mathsf{m l})$ . \n\nThese five hypotheses had the potential to be synergistic or anti-synergistic; for example, ionic strength could either enhance or decrease dye absorption onto the surface of the photocatalyst. We therefore chose to explore all five hypotheses at once. This involved the simultaneous variation of the concentration of P10, l-cysteine, the three dyes, NaOH, NaCl, the two surfactants, and sodium disilicate, which equates to a ten-variable search space (Fig. 2a). The space was constrained by the need to keep a constant liquid volume $(5\\mathsf{m l})$ and therefore head space for gas chromatography analysis and by the minimal resolution for liquid dispensing module $(0.25\\mathrm{ml})$ and solid dispensing module $(0.2\\mathsf{m g})$ . \n\nProblems of this type are defined by a simplex that scales exponentially with size (Fig. 2b). For this specific search space, there were more than 98 million points. Full exploration of such a space is unfeasible, so we developed an algorithm that performs Bayesian optimization based on Gaussian process regression and parallel search strategy35 (see Methods). To generate a new batch, we build a surrogate model predicting the HER of potential formulations based on the measurements performed so far and quantify the uncertainty of prediction. Subsequent sampling points are chosen using a capitalist acquisition strategy, where a portfolio of upper confidence bound functions is generated on an exponential distribution of greed to create markets of varying risk aversion, which are searched for global maxima. Each market is given an agent that searches to return a global maximum, or batch of $k$ -best maxima. The uneven distribution of greed allows some suggested points to be highly exploitative, some to be highly explorative, and most to be balanced, thus making the strongest use of the parallel batch experiments. \n\nThe output from this autonomous robotic search is shown in Fig. 3a. The baseline HER for P10 and l-cysteine only (5 mg P10 in 5 ml of $20{\\bf g}{\\bf l}^{-1}$ l-cysteine) was $3.36{\\pm}0.30{\\upmu}{\\mathrm{molh}}^{-1}$ . Given that the robot would operate autonomously over multiple days, this two-component mixture was repeated throughout the search (two samples per batch) to check for long-term experimental stability (black squares in Fig. 3a). Initially, the robot started with random conditions and discovered multicomponent catalyst formulations that were mostly less active than P10 and l-cysteine alone (the first 22 experiments in Fig. 3a). The robot then discovered that adding NaCl provides a small improvement to the HER, validating the hypothesis that ionic strength is important. In the same period, the robot found that maximizing both P10 and l-cysteine increased the HER. In further experiments (15–100), the robot discovered that none of the three dyes or the two surfactants improves the HER; indeed, they are all detrimental, counter to our first and fourth hypotheses. These five components were therefore deselected after around 150 experiments (Fig. 4); that is, after about 2 days in real experimental time (Fig. 3a). Here, P10 differs from the structurally related crystalline fused-sulfone covalent organic framework (FS-COF), where the addition of Acid Red 87 increased the HER31. After 30 experiments, the robot learned that adding sodium disilicate improves the HER substantially in the absence of dyes (up to $15\\upmu\\mathrm{mol}$ after 300 experiments), while deprioritizing the addition of NaOH and NaCl. After 688 experiments, which amounted to 8 days of autonomous searching, the robot found that the optimum catalyst formulation is a \n\n# Article \n\n![](images/140e1f9732bcc7e2afe4cf88744100267920f7fa17c897e93a8052e3a6f2c427.jpg) \nFig. 4 | Selection and deselection of photocatalyst formulation components. Plots showing the mass (in milligrams for P10) or volume (millilitres for all other components) dispensed for the various components in the search space as a function of experiment. The photocatalyst, P10, and the scavenger, l-cysteine, are selected, along with sodium disilicate $(\\mathsf{N a}_{2}\\mathsf{S i}_{2}\\mathsf{O}_{5})$ and NaOH. All other components were deselected after around 150 experiments. The three dyes and the two surfactants had a negative effect on the HER. NaCl had a small positive effect, but less so than the four selected components, and it was therefore deselected. Note that NaOH was initially deselected, and not included in experiments 15–283 (see black arrow), while ${\\mathsf{N a}}_{2}{\\mathsf{S i}}_{2}{\\mathsf{O}}_{5}$ and l-cysteine were favoured. The positive effect of NaOH was initially masked by negative components such as the dyes. Later in the search, NaOH was favoured, ultimately in preference to $\\mathsf{N a}_{2}\\mathsf{S i}_{2}\\mathsf{O}_{5}$ illustrating the benefit of using an uneven distribution of greed in the search. \n\nmixture of NaOH, l-cysteine, sodium disilicate and P10, giving a HER of $21.05\\upmu\\mathrm{molh}^{-1}$ , which was six times higher than the starting conditions. \n\nA number of scientific conclusions can be drawn from these data. Increased ionic strength is beneficial for hydrogen production (NaCl addition), but not as beneficial as increasing the pH (NaOH/sodium disilicate addition), which also increases the ionic strength. We had not investigated surfactant addition before, but for the two surfactants studied here, at least, the effect on catalytic activity is purely negative. Intriguingly, the dye sensitization that we observed for a structurally similar covalent organic framework, FS-COF31, does not translate to this polymer, P10, possibly because the COF is porous whereas P10 is not. \n\nTo explore the dependence of the algorithmic search performance on the random starting conditions, we carried out 100 in silico virtual searches, each with a different random starting point, using a regression model and random noise to return virtual results (Supplementary Information section 7). Around 160 virtual experiments were needed, on average, to find solutions with $95\\%$ of the global maximum HER (Fig. 5). \n\nWe estimate that it would have taken a human researcher several months to explore these five hypotheses in the same level of detail using standard, manual approaches (Supplementary Fig. 31). Manual hydrogen evolution measurements require about 0.5 days of researcher time per experiment (1,000 experiments take 500 days). The semi-automated robotic methods that we developed recently33 can perform 100 experiments per day (a half-day to set up, plus a half-day for automatic dispensing and measurement; 1,000 experiments take \n\n10 days, of which 5 days are dedicated researcher time). The autonomous robot that we present here also requires half a day to set it up initially, but it then runs unattended over multiple days (1,000 experiments take 0.5 days of researcher time). Hence, the autonomous workflow is 1,000 times faster than manual methods, and at least ten times faster than semi-automated but non-autonomous robotic workflows. It is unlikely that a human researcher would have persevered with this multivariate experiment using manual approaches given that it might have taken 50 experiments or 25 days to locate even a modest enhancement in the HER (Fig. 3a). The platform allows us to tackle search spaces of a size that would otherwise be impossible, which is an advantage for problems where our current level of understanding does not allow us to reduce the number of candidate components to a more manageable number. There were ten components in the example given here, but search spaces with up to at least 20 components should be tractable with some modifications to the algorithm. \n\nIt took an initial investment of time to build this workflow (approximately 2 years), but once operating with a low error rate (Supplementary Fig. 38), it can be used as a routine tool. The time required to implement this approach in another laboratory would be much shorter, since much of the 2-year development timescale involved core protocols and software that are transferable to other research problems. Also, this modular approach to laboratory automation uses instruments in a physically unmodified form, so that it will be straightforward to add further modules, such as for NMR or X-ray diffraction, now that the basic principles are in place. This modularity makes our strategy applicable to a wide range of research problems beyond chemistry. The speed and efficiency of the method allow the exploration of large multivariate spaces, and the autonomous robot has no confirmation bias36; this raises the prospect of emergent function in complex, multi-component materials that we could not design in the conventional way. Autonomous mobile robots could also have extra advantages in experiments with especially hazardous materials, or where traceability and auditing are important, such as in pharmaceutical processes. \n\n![](images/75b9338941201082a61b675bbed5d7609418ad4f2c2a55fea6316bd049578650.jpg) \nFig. 5 | Virtual in silico experiments. Histogram showing the number of virtual experiments needed to reach $95\\%$ of the optimal HER, as determined by carrying out 100 in silico searches, each with a different random starting point. \n\nThis approach also has some limitations. For example, the Bayesian optimization is blind, in that all components have equal initial importance. This robotic search does not capture existing chemical knowledge, nor include theory or physical models: there is no computational brain. Also, this autonomous system does not at present generate and test scientific hypotheses by itself37. In the future, we propose to fuse theory and physical models with autonomous searches: for example, computed structures and properties1–5 could be used to bias searches towards components that have a higher likelihood of yielding the desired property. This will be important for search spaces with even larger numbers of components where purely combinatorial approaches may become inefficient. To give one example, energy–structure–function maps38 could be computed for candidate crystalline components to provide Boltzmann energy weightings39 for calculated properties, such as a charge transport or optical gap, to bias the robotic search. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-020-2442-2. \n\n5. Davies, D. W. et al. Computer-aided design of metal chalcohalide semiconductors: from chemical composition to crystal structure. Chem. Sci. 9, 1022–1030 (2018). \n6. King, R. D. Rise of the robo scientists. Sci. Am. 304, 72–77 (2011). \n7. Li, J. et al. Synthesis of many different types of organic small molecules using one automated process. Science 347, 1221–1226 (2015). \n8. Dragone, V., Sans, V., Henson, A. B., Granda, J. M. & Cronin, L. An autonomous organic reaction search engine for chemical reactivity. Nat. Commun. 8, 15733 (2017). \n9. Bédard, A.-C. et al. Reconfigurable system for automated optimization of diverse chemical reactions. Science 361, 1220–1225 (2018). \n10. Granda, J. M., Donina, L., Dragone, V., Long, D.-L. & Cronin, L. Controlling an organic synthesis robot with machine learning to search for new reactivity. Nature 559, 377–381 (2018). \n11. Tabor, D. P. et al. Accelerating the discovery of materials for clean energy in the era of smart automation. Nat. Rev. Mater. 3, 5–20 (2018). \n12. Langner, S. et al. Beyond ternary OPV: high-throughput experimentation and self-driving laboratories optimize multi-component systems. Preprint at https://arxiv.org/ abs/1909.03511 (2019). \n13. MacLeod, B. P. et al. Self-driving laboratory for accelerated discovery of thin-film materials. Preprint at https://arxiv.org/abs/1906.05398 (2019). \n14. Steiner, S. et al. Organic synthesis in a modular robotic system driven by a chemical programming language. Science 363, eaav2211 (2019). \n15. Wang, Z., Li, C. & Domen, K. Recent developments in heterogeneous photocatalysts for solar-driven overall water splitting. Chem. Soc. Rev. 48, 2109–2125 (2019). \n16. Shahriari, B., Swersky, K., Wang, Z., Adams, R. P. & Freitas, N. D. Taking the human out of the loop: a review of Bayesian optimization. Proc. IEEE 104, 148–175 (2016). \n17. Häse, F., Roch, L. M., Kreisbeck, C. & Aspuru-Guzik, A. Phoenics: a Bayesian optimizer for chemistry. ACS Cent. Sci. 4, 1134–1145 (2018). \n18. Roch, L. M. et al. ChemOS: orchestrating autonomous experimentation. Sci. Robot. 3, eaat5559 (2018). \n19. Chen, C.-L., Chen, T.-R., Chiu, S.-H. & Urban, P. L. Dual robotic arm “production line” mass spectrometry assay guided by multiple Arduino-type microcontrollers. Sens. Actuat. B 239, 608–616 (2017). \n20. Fleischer, H. et al. Analytical measurements and efficient process generation using a dual-arm robot equipped with electronic pipettes. Energies 11, 2567 (2018). \n21. Liu, H., Stoll, N., Junginger, S. & Thurow, K. Mobile robot for life science automation. Int. J. Adv. Robot. Syst. 10, 288 (2013). \n22.\t Liu, H., Stoll, N., Junginger, S. & Thurow, K. A fast approach to arm blind grasping and placing for mobile robot transportation in laboratories. Int. J. Adv. Robot. Syst. 11, 43 (2014). \n23. Abdulla, A. A., Liu, H., Stoll, N. & Thurow, K. A new robust method for mobile robot multifloor navigation in distributed life science laboratories. J. Contrib. Sci. Eng. 2016, 3589395 (2016). \n24. Dömel, A. et al. Toward fully autonomous mobile manipulation for industrial environments. Int. J. Adv. Robot. Syst. 14, https://doi.org/10.1177/1729881417718588 (2017). \n25. Schweidtmann, A. M. et al. Machine learning meets continuous flow chemistry: automated optimization towards the Pareto front of multiple objectives. Chem. Eng. J. 352, 277–282 (2018). \n26. Zhi, L. et al. Robot-accelerated perovskite investigation and discovery (RAPID): 1. Inverse temperature crystallization. Preprint at https://doi.org/10.26434/chemrxiv.10013090.v1 (2019). \n27. Matsuoka, S. et al. Photocatalysis of oligo (p-phenylenes): photoreductive production of hydrogen and ethanol in aqueous triethylamine. J. Phys. Chem. 95, 5802–5808 (1991). \n28. Shu, G., Li, Y., Wang, Z., Jiang, J.-X. & Wang, F. Poly(dibenzothiophene-S,S-dioxide) with visible light-induced hydrogen evolution rate up to 44.2 mmol h−1 g−1 promoted by ${\\sf K}_{2}{\\sf H P O}_{4}$ . Appl. Catal. B 261, 118230 (2020). \n29. Pellegrin, Y. & Odobel, F. Sacrificial electron donor reagents for solar fuel production. C. R. Chim. 20, 283–295 (2017). \n30. Sakimoto, K. K., Zhang, S. J. & Yang, P. Cysteine–cystine photoregeneration for oxygenic photosynthesis of acetic acid from $\\mathsf{C O}_{2}$ by a tandem inorganic–biological hybrid system. Nano Lett. 16, 5883–5887 (2016). \n31. Wang, X. et al. Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water. Nat. Chem. 10, 1180–1189 (2018). \n32. Schwarze, M. et al. Quantification of photocatalytic hydrogen evolution. Phys. Chem. Chem. Phys. 15, 3466–3472 (2013). \n33. Bai, Y. et al. Accelerated discovery of organic polymer photocatalysts for hydrogen evolution from water through the integration of experiment and theory. J. Am. Chem. Soc. 141, 9063–9071 (2019). \n34. Zhang, J. et al. H-bonding effect of oxyanions enhanced photocatalytic degradation of sulfonamides by $g{\\cdot}C_{3}\\mathsf{N}_{4}$ in aqueous solution. J. Hazard. Mater. 366, 259–267 (2019). \n35. Hutter, F., Hoos, H. H. & Leyton-Brown, K. Parallel Algorithm Configuration 55–70 (Springer, 2012). \n36. Mynatt, C. R., Doherty, M. E. & Tweney, R. D. Confirmation bias in a simulated research environment: an experimental study of scientific inference. Q. J. Exp. Psychol. 29, 85–95 (1977). \n37. King, R. D. et al. Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427, 247–252 (2004). \n38. Pulido, A. et al. Functional materials discovery using energy–structure–function maps. Nature 543, 657–664 (2017). \n39. Campbell, J. E., Yang, J. & Day, G. M. Predicted energy–structure–function maps for the evaluation of small molecule organic semiconductors. J. Mater. Chem. C 5, 7574–7584 (2017). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Article Methods \n\n# Robot specifications \n\nThe robot used was a KUKA Mobile Robot mounted on a KUKA Mobile Platform base (Fig. 1a; Extended Data Fig. 1). The robot arm has a maximum payload of $14\\mathrm{kg}$ and a reach of $820\\mathrm{mm}$ . The KUKA Mobile Platform base can carry payloads of up to $200\\mathrm{kg}$ . The robot arm and the mobile base have a combined mass of approximately $430\\mathrm{kg}$ . The movement velocity of the robot was restricted to $0.5\\mathsf{m s}^{-1}$ for safety reasons (section 1.5 of the Supplementary Information,). A multipurpose gripper was designed to grasp $10\\cdot\\mathrm{ml}$ gas chromatograph sample vials, solid dispensing cartridges, and a 16-position sample rack (Extended Data Fig. 5), thus allowing a single robot to carry out all of the tasks required for this workflow. This robot was specified to be a flexible platform for a wide range of research tasks beyond those exemplified here; for example, the $14\\upk\\mathrm{g}$ payload capacity for the arm is not fully used in these experiments (one rack of filled vials has a mass of $\\mathbf{\\sigma}_{580}\\mathbf{g},$ ), but it could allow for manipulations such as opening and closing the doors of certain equipment. Likewise, the height and reach of the robot allows for operations such as direct loading of samples into the gas chromatograph instrument (Fig. 1d). By contrast, a smaller and perhaps less expensive robot platform might require an additional, dedicated robot arm to accomplish this, or inconvenient modifications to the laboratory, such as lowering bench heights. \n\n# Robot navigation \n\nIn a process analogous to simultaneous localization and mapping $(\\mathsf{S L A M})^{40}$ , the robot tracks a cloud of possible positions, and updates its position to the best fit between the output of its laser scanners and the map for each position in the cloud. The position of the robot is determined by $x$ and $y$ (its position on the map) and $\\theta$ (its orientation angle). Histograms of the robot position measured over 563 movements are shown in Supplementary Figs. 2–5, which show that the $(x,y)$ positioning precision was better than $\\pm10\\mathsf{m m}$ and the orientation precision was less than $\\pm2.5^{\\circ}$ , as achieved within a real, working laboratory environment. This level of precision allows navigation to the various experimental stations in the laboratory, but it does not allow fine manipulations, such as placement of sample vials. The precision was therefore enhanced by using a touch-sensitive 6-point calibration method. Here, the robot touches six points on a cube that is associated with each experimental station to find the position and orientation of the cube relative to the robot (Supplementary Figs. 7–11). This increased the positioning precision to $\\pm0.12\\mathrm{mm}$ and the orientation precision to $\\pm0.005^{\\circ}$ . This makes it possible for the robot to operate instruments and to carry out delicate manipulations such as vial placements at a level of precision that is broadly comparable to a human operator. \n\n# Experimental stations \n\nThe workflow comprised six steps, each with its own station. Solid dispensing was carried out with a Quantos QS30 instrument (Mettler Toledo) (Fig. 1c; Supplementary Fig. 11; Extended Data Fig. 3a; Supplementary Video 3). Liquid dispensing was carried out with a bespoke system that used a 200 series Mini Peristaltic Pump (Williamson) and a PCG 2500-1 scale (Kern), to dispense liquids gravimetrically using a feedback loop (section 2.2 in Supplementary Information; Supplementary Video 5). This system showed excellent precision and accuracy for a range of aqueous and non-aqueous liquids over 20,000 dispenses (Supplementary Figs. 16, 17, 19, 20). A bespoke instrument was built (Labman) to allow both for sample inertization (to exclude oxygen) and cap crimping in one step. It would be straightforward to modify this platform to allow other gases to be introduced; for example, to study photocatalytic ${\\mathsf{C O}}_{2}$ reduction. The instrument used caps from a vibratory bowl feeder to cap-crimp $10^{-}\\mathsf{m l}$ headspace vials (section 2.2 in Supplementary Information; Supplementary Video 5). If required, a sonication station was used to disperse the solid photocatalyst in the aqueous solution, before reaction (Supplementary Fig. 23). Photolysis was carried out at a bespoke photolysis station (Fig. 1a) that uses vibration to agitate liquids and a light source that is composed of BL368 tubes and LED panels (Extended Data Fig. 5b; Supplementary Fig. 24; Supplementary Video 6). Gas chromatograph measurements were performed with a 7890B GC and a 7697A Headspace Sampler from Agilent GC (Supplementary Video 3; Extended Data Fig. 3d). The experimental stations were controlled by a process management system module, which contains all of the process logic for controlling the labware. Communication between the process management system and the stations was achieved using various communication protocols (TCP/IP over WIFI/LAN; RS-232), as detailed in section 2.7 in the Supplementary Information (Supplementary Fig. 28). \n\n# Autonomous search procedure and scheduling \n\nThe robot worked with batches of 16 samples per sample rack and ran 43 batches (688 experiments) during the search. Of these 688 experiments, 11 results were discarded because of workflow errors or because the system flagged that the oxygen level was too high (faulty vial seal). It took, on average, 183 min to prepare and photolyse each batch of samples and then 232 min per batch to complete the gas chromatograph analysis. The detailed timescales for each of the step in the workflow are shown in Extended Data Fig. 6. The work was heuristically scheduled in parallel, with the robot starting the oldest available scheduled job. While the robot was working on one job, other instruments, such as the solid dispenser, the photolysis station and the gas chromatograph, worked in parallel. This system can process up to six batches at once, but given the timescales for this specific workflow, where the preparation/reaction time is approximately equal to the analysis time, the robot processed two batches simultaneously. That is, it prepared samples and ran photolysis for one batch while analysing the hydrogen produced for the second batch using the gas chromatograph. The robot recharged its battery automatically in between two jobs when the battery charge reached a $25\\%$ threshold. The robot was charged but idle for approximately $32\\%$ of the time in this experiment, largely because of time spent waiting for the gas chromatograph analysis, which is the slow step. In principle, this time could be used to run other experiments in parallel. The autonomous workflow was programmed to alert the operator automatically when the system is out of stock (if, for example, it ran out of sample vials or stock solutions were low), or if a part of the workflow failed (section 8 of the Supplementary Information). Most errors could be reset remotely without being in the laboratory because all stations were equipped with 24/7 closed-circuit television cameras (Supplementary Fig. 39). \n\n# Bayesian search algorithm \n\nThe AI guidance for the autonomous mobile robot was a batched, constrained, discrete Bayesian optimization algorithm. Traditionally, Bayesian optimization is a serial algorithm tasked with finding the global maximum of an unknown objective function16. Here, this equates to finding the optimal set of concentrations in a multicomponent mixture for photocatalytic hydrogen generation. The algorithm builds a model that can be updated and queried for the most promising points to inform subsequent experiments. This surrogate model is constructed by first choosing a functional prior $\\phi_{\\mathrm{{orior}}}(\\theta),$ informed by existing chemical knowledge (if any). Given data $\\mathbf{\\dot{\\mathcal{D}}}$ and a likelihood model $\\phi_{\\mathrm{likelihood}}(\\mathcal{D}|\\theta)$ , this yields a posterior distribution of models using Bayes’ theorem: \n\n$$\n\\phi_{\\mathrm{posterior}}(\\theta|\\mathcal{D})=\\frac{\\phi_{\\mathrm{likelihood}}(\\mathcal{D}|\\theta)\\phi_{\\mathrm{prior}}(\\theta)}{\\phi(\\mathcal{D})}\n$$ \n\nThe Gaussian process prior used a Matern similarity kernel, constant scaling and homoscedastic noise41. This composite kernel allows for variable smoothness, catalytic activity and experimental noise. The form and respective hyperparameters were refined using cross-validation on other, historical photocatalysis datasets (350 experiments). Other alternatives for a functional prior included Bayesian neural networks17; but Gaussian processes were selected here for robustness and flexibility42. An acquisition function, $\\alpha_{\\mathrm{{UCB}}}$ , was assembled from the posterior distribution by considering the posterior mean, $\\mu(x)$ , and uncertainty, $\\sigma(x)$ . The maximum of this function was then used as the next suggested experiment. To balance exploitation (prioritizing areas where the mean is expected to be largest) and exploration (prioritizing areas where the model is most uncertain), we used an upper confidence bound that is dependent on a single hyperparameter, $\\beta$ , to govern how ‘greedy’ (exploitative) the search is: \n\n$$\n\\alpha_{\\mathsf{U C B}}(x;\\mathcal{D}):=\\mu(x)+\\beta\\sigma(x)\n$$ \n\nThe portfolio of acquisition functions for different values of $\\beta$ , which we call markets, was used to generate a batch. This ‘capitalist’ approach has the advantage of simple parallelization and is robust across variable batch sizes35. Our method allowed us to constrain the sum of all liquid components to $5\\mathrm{ml}$ to allow a constant gas headspace volume for gas chromatograph analysis. The sum total volume constraint was handled during the market searches; discretization, which was determined by instrument resolution, was handled after the market searches. The market search was completed using a large initial random sampling followed by a batch of seeded local maximizations using a sequential least-squares programming (SLSQP) algorithm as implemented in the scipy.optimize package. This maximization occurs in a continuous space, and the results are placed into discrete bins following the experimental precision. The explored space is tracked as a continuous variable for model building and as a discrete variable for acquisition function maximization. The algorithm was implemented using the scikit-learn and in scipy packages43. \n\n# Materials and synthetic procedures \n\nThe polymeric photocatalyst P10 was synthesized and purified according to a modification on a literature procedure44 (section 10 of the Supplementary Information). For solid dispensing, the polymer was ground with mortar and pestle before use. Sodium disilicate was obtained as a free sample from Silmaco. Tap water was purified with PURELAB Ultra System. All other materials were purchased from Sigma-Aldrich and used as received. \n\n# Data availability \n\nThe implementation of the liquid-dispensing station, photolysis station and the workflow, along with three-dimensional designs for labware developed in the project, are available at https://bitbucket.org/ ben_burger/kuka_workflow, the code for the robot at and the Bayesian optimizer is available at https://github.com/Taurnist/kuka_workflow_tantalus and https://github.com/CooperComputationalCaucus/ kuka_optimizer. Additional design details can be obtained from the authors upon request. \n\n40.\t Fuentes-Pacheco, J., Ruiz-Ascencio, J. & Rendón-Mancha, J. M. Visual simultaneous localization and mapping: a survey. Artif. Intell. Rev. 43, 55–81 (2015). \n41.\t Rasmussen, C. E. & Williams, C. K. I. Gaussian Processes for Machine Learning (MIT Press, 2006). \n42.\t Matthews, A. G. G., Rowland, M., Hron, J., Turner, R. E. & Ghahramani, Z. Gaussian process behaviour in wide deep neural networks. Preprint at https://arxiv.org/abs/1804.11271 (2018). \n43.\t Millman, K. J. & Aivazis, M. Python for scientists and engineers. Comput. Sci. Eng. 13, 9–12 (2011). \n44.\t Sachs, M. et al. Understanding structure-activity relationships in linear polymer photocatalysts for hydrogen evolution. Nat. Commun. 9, 4968 (2018). \n\nAcknowledgements We acknowledge financial support from the Leverhulme Trust via the Leverhulme Research Centre for Functional Materials Design, the Engineering and Physical Sciences Research Council (EPSRC) (grant number EP/N004884/1), the Newton Fund (grant number EP/R003580/1), and CSols Ltd. X.W. and Y.B. thank the China Scholarship Council for a PhD studentship. We thank KUKA Robotics for help with gripper design and the initial implementation of the robot. \n\nAuthor contributions B.B. developed the workflow, developed and implemented the robot positioning approach, wrote the control software, designed the bespoke photocatalysis station and carried out experiments. P.M.M. and V.V.G. developed the optimizer and its interface to the control software. X.L. advised on the photocatalysis workflow. C.M.A., Y.B. and X.L. synthesized materials. Y.B. performed kinetic photocatalysis experiments. X.W. performed NMR analysis and synthesized materials. B.L. carried out initial scavenger screening. R.C. and N.R. helped to build the bespoke stations in the workflow. B.H. analysed the robustness of the system, assisted with the development of control software, and operated the workflow during some experiments. B.M.A. helped to supervise the automation work. R.S.S. helped to supervise the photocatalysis work. A.I.C. conceived the idea, set up the five hypotheses with B.B., and coordinated the research team. Data was interpreted by all authors and the manuscript was prepared by A.I.C., B.B., P.M.M., V.V.G. and R.S.S. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41586-020- 2442-2. \nCorrespondence and requests for materials should be addressed to A.I.C. \nPeer review information Nature thanks Volker Krueger, Tyler McQuade and Magda Titirici for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n# Article \n\n![](images/5c74d28daafe49e8c17a93b9ba96bde514288b2b7e5a544f8899139a4954d798.jpg) \nExtended Data Fig. 1 | Mobile robotic chemist. The mobile robot used for this project, shown here performing a six-point calibration with respect to the black location cube that is attached to the bench, in this case associated with the solid cartridge station (see also Supplementary Fig. 11 and Extended Data Fig. 3a). \n\n![](images/3f4338c6e58f8498247f4ac774ad2c7022631bb14fc645b2763ec500bba6faf1.jpg) \n\nExtended Data Fig. 2 | Laboratory space used for the autonomous experiments. The key locations in the workflow are labelled. Other than the black locatio cubes that are fixed to the benches to allow positioning (see also Extended Data Fig. 1), the laboratory is otherwise unmodified. \n\n# Article \n\n![](images/07e10b4844f25a28aa020e5ac84b653329edac1291bb30b47b7fa0174bc94107.jpg) \n\nExtended Data Fig. 3 | Stations in the workflow. a, Photograph showing the robot at the solid dispensing / cartridge station. The two cartridge hotels can hold up to 20 different solids; here, four cartridges are located in the hotel on the left. The door of the Quantos dispenser is opened using custom workflow software that interfaces with the command software that is supplied with the instrument before loading the correct solid dispensing cartridge into the instrument (Supplementary Video 3). Since the KUKA Mobile Robot is free-roaming and has an $820\\mathrm{mm}$ reach, it would be simple to extend this modular approach to hundreds or even thousands of different solids given sufficient laboratory space. b, Photograph showing the KUKA Mobile Robot at the photolysis station (see also Supplementary Videos 3, 6). c, Photograph showing the KUKA Mobile Robot at the combined liquid handling/capping station. The robot can reach both the liquid stations and the Liverpool Inertization Capper-Crimper (LICC) station after six-point positioning, such that liquid addition, headspace inertization and capping can be carried out in a single coordinated process (see Supplementary Videos 3, 5), without any position recalibration. d, Photograph of the KUKA Mobile Robot parked at the headspace gas chromatography (GC) station. The gas chromatography instrument is a standard commercial instrument and was unmodified in this workflow. \n\n![](images/e576eb3b0dd5ea5c62d29985ae65ec666a5f587c537d93a7ebd58c059557f186.jpg) \nExtended Data Fig. 4 | Hydrogen evolution rates for candidate bioderived sacrificial hole scavengers. Results of a robotic screen for sacrificial hole scavengers using the mobile robot workflow. Of the 30 bioderived molecules trialed, only cysteine was found to compete with the petrochemical amine, \n\ntriethanolamine. Scavengers are labelled with the concentration of the stock solution that was used (5 ml volume; 5 mg P10). The error bars show the standard deviation. \n\n![](images/eec02b296e9f9eb556a79ccbeeab7f2ae3427befe7cace30ef3ff9b953818442.jpg) \nExtended Data Fig. 5 | Multipurpose gripper used in the workflow. The gripper is shown grasping various objects. a, The empty gripper; b, gripper holding a capped sample vial (top grasp); c, gripper holding an uncapped sample vial (side grasp); d, gripper holding a solid-dispensing cartridge; and \ne, gripper holding a full sample rack using an outwards grasp that locks into recesses in the rack. The same gripper was also used to activate the gas chromatography instrument using a physical button press (see Supplementary Video 3; 1 min 52 s). \n\n![](images/7c91f6127e0914175215bdb1476756b51194954e74ed0919932c23165581de32.jpg) \n\nExtended Data Fig. 6 | Timescales for steps in the workflow. Average timescales for the various steps in the workflow (sample preparation, photolysis and analysis) for a batch of 16 experiments. These averages were calculated over 46 separate batches. These average times include the time taken for the loading and unloading steps (for example, the photolysis time itself was $60\\mathrm{{min}}$ ; loading and unloading takes an average of 28 min per batch). The slowest step in the workflow is the gas chromatography analysis. " + }, + { + "id": "10.1126_science.abd4016", + "DOI": "10.1126/science.abd4016", + "DOI Link": "http://dx.doi.org/10.1126/science.abd4016", + "Relative Dir Path": "mds/10.1126_science.abd4016", + "Article Title": "Monolithic perovskite/silicon tandem solar cell with >29% efficiency by enhanced hole extraction", + "Authors": "Al-Ashouri, A; Köhnen, E; Li, B; Magomedov, A; Hempel, H; Caprioglio, P; Márquez, JA; Vilches, ABM; Kasparavicius, E; Smith, JA; Phung, N; Menzel, D; Grischek, M; Kegelmann, L; Skroblin, D; Gollwitzer, C; Malinauskas, T; Jost, M; Matic, G; Rech, B; Schlatmann, R; Topic, M; Korte, L; Abate, A; Stannowski, B; Neher, D; Stolterfoht, M; Unold, T; Getautis, V; Albrecht, S", + "Source Title": "SCIENCE", + "Abstract": "Tandem solar cells that pair silicon with a metal halide perovskite are a promising option for surpassing the single-cell efficiency limit. We report a monolithic perovskite/silicon tandem with a certified power conversion efficiency of 29.15%. The perovskite absorber, with a bandgap of 1.68 electron volts, remained phase-stable under illumination through a combination of fast hole extraction and minimized nonradiative recombination at the hole-selective interface. These features were made possible by a self-assembled, methyl-substituted carbazole monolayer as the hole-selective layer in the perovskite cell. The accelerated hole extraction was linked to a low ideality factor of 1.26 and single-junction fill factors of up to 84%, while enabling a tandem open-circuit voltage of as high as 1.92 volts. In air, without encapsulation, a tandem retained 95% of its initial efficiency after 300 hours of operation.", + "Times Cited, WoS Core": 1420, + "Times Cited, All Databases": 1485, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000597271300039", + "Markdown": "# SOLAR CELLS \n\n# Monolithic perovskite/silicon tandem solar cell with $>29\\%$ efficiency by enhanced hole extraction \n\nAmran Al-Ashouri1\\*, Eike Köhnen1\\*, Bor Li1, Artiom Magomedov2, Hannes Hempel3, Pietro Caprioglio1,4, José A. Márquez3, Anna Belen Morales Vilches5, Ernestas Kasparavicius2, Joel A. Smith6,7, Nga Phung6, Dorothee Menzel1, Max Grischek1,4, Lukas Kegelmann1, Dieter Skroblin8, Christian Gollwitzer8, Tadas Malinauskas2, Marko Jošt1,9, Gašper Maticˇ9, Bernd Rech10,11, Rutger Schlatmann5,12, Marko Topicˇ9, Lars Korte1, Antonio Abate6, Bernd Stannowski5,13, Dieter Neher4, Martin Stolterfoht4, Thomas Unold3, Vytautas Getautis2, Steve Albrecht1,11† \n\nTandem solar cells that pair silicon with a metal halide perovskite are a promising option for surpassing the single-cell efficiency limit. We report a monolithic perovskite/silicon tandem with a certified power conversion efficiency of $29.15\\%$ . The perovskite absorber, with a bandgap of 1.68 electron volts, remained phase-stable under illumination through a combination of fast hole extraction and minimized nonradiative recombination at the hole-selective interface. These features were made possible by a self-assembled, methyl-substituted carbazole monolayer as the hole-selective layer in the perovskite cell. The accelerated hole extraction was linked to a low ideality factor of 1.26 and single-junction fill factors of up to $84\\%$ , while enabling a tandem open-circuit voltage of as high as 1.92 volts. In air, without encapsulation, a tandem retained $95\\%$ of its initial efficiency after 300 hours of operation. \n\ntandem solar cell, consisting of a silicon 1 cell overlaid by a perovskite solar cell A (PSC) $(I)$ , could increase efficiencies of commercial mass-produced photovol■ taics beyond the single-junction cell limit $(\\boldsymbol{I},\\boldsymbol{2})$ without adding substantial cost (3, 4). The certified power conversion efficiency (PCE) of PSCs has reached up to $25.5\\%$ for single-junction solar cells (usual active area of $\\mathrm{\\sim}0.1\\mathrm{cm^{2}},$ ) (5), $24.2\\%$ for perovskite/CIGSe (copper-indium-gallium-selenide) tandem cells $(\\sim1~\\mathrm{cm}^{2})$ (5–7), $24.8\\%$ for all-perovskite tandem cells $(0.05\\mathrm{cm}^{2}$ ) $(\\boldsymbol{\\vartheta},\\boldsymbol{\\vartheta})$ , and $26.2\\%$ for the highest openly published perovskite/silicon tandem efficiency $\\mathrm{(\\sim1~cm^{2})}$ (10). Perovskite/ silicon tandem cells have additionally undergone technological advances in both stability and compatibility with textured silicon substrates (11–13). However, these perovskitebased tandem solar cells still have room for improvement, as practical limits for all these \n\ntandem technologies are well above $30\\%$ (14, 15). \n\nThe increase in PSC efficiency has been driven in part by advances in physical and chemical understanding of the defect and recombination mechanisms. Some reports presented near-perfect passivation of surfaces and grain boundaries, with photoluminescence quantum yields (PLQYs) approaching theoretical limits (16–18). Consequently, PSCs were reported with open-circuit voltage $(V_{\\mathrm{OC}})$ values of only a few tens of meV below their radiative limit (19–23). These values surpass those reached with crystalline silicon absorbers and are comparable with solar cells based on epitaxially grown GaAs (23, 24). However, perovskite compositions with a wider bandgap that are needed for high-efficiency tandem solar cells still show considerable $V_{\\mathrm{OC}}\\log\\sec\\left(I4,25\\right)$ . The main reasons include comparably low PLQYs of the absorber material itself, an unsuitable choice of selective contacts, and phase instabilities. Even state-ofthe-art perovskite/silicon tandem cells still have $V_{\\mathrm{OC}}$ values well below $1.9\\mathrm{V}.$ . \n\nWe present a strategy to overcome these issues simultaneously, demonstrated with a triplecation perovskite composition with a bandgap of $1.68\\ \\mathrm{eV}$ , which enables photostable tandem devices with a $V_{\\mathrm{OC}}$ of 1.92 V. We note that the charge extraction efficiency, and hence the fill factor (FF), of PSCs is still poorly understood. Although reported PSCs usually feature a small active area $(\\sim0.1~\\mathrm{cm}^{2})$ with small absolute photocurrents (a few milliamperes), and thus small series resistance losses at the contacts, typical FFs of high-efficiency devices generally range from 79 to $82\\%$ . However, on the basis of the detailed balance limit, PSCs should be able to deliver a FF of $90.6\\%$ at a bandgap of $1.6\\mathrm{eV}$ Wider-bandgap perovskite compositions near \n\n$1.7\\mathrm{eV}$ seem especially prone to low FFs, resulting in tandem cell FF values commonly below $77\\%.$ near current-matching conditions $(\\bar{\\cal U},\\bar{\\cal L}2,26).$ In optimized perovskite single-junction devices, the FFs only recently exceeded $80\\%$ , with a maximum value of $84.8\\%$ (27). \n\nOne reason for the low FF might be that there are only a few techniques for quantifying and analyzing the FF losses in PSCs. We show that intensity-dependent transient photoluminescence in combination with absolute photoluminescence is a viable technique for doing so. A main FF limitation of high-efficiency PSCs is the ideality factor $n_{\\mathrm{ID}},$ with typical values of 1.4 to 1.8 for high- $\\cdot V_{\\mathrm{OC}}$ devices (28), whereas established solar cell technologies reach values of 1 to 1.3 (29). Thus, an important goal for perovskite photovoltaics is to lower the ideality factor while minimizing nonradiative interface recombination to achieve a high $V_{\\mathrm{OC}}$ (28). We designed a self-assembled monolayer (SAM) with methyl group substitution as a holeselective layer, named Me-4PACz ([4-(3,6- dimethyl-9H-carbazol-9-yl)butyl]phosphonic acid) and show that a fast hole extraction went along with a lower ideality factor. Thus, FFs of up to $84\\%$ in p-i-n single-junction PSCs and ${>}80\\%$ in tandem devices were achieved. \n\nThe SAM provided both fast extraction and efficient passivation at the hole-selective interface. This combination slowed light-induced halide segregation of a tandem-relevant perovskite composition with 1.68-eV bandgap, allowed a PLQY as high as on quartz glass, and led to high single-junction device $V_{\\mathrm{OC}}$ values of ${\\tt>}1.23\\$ V. The single-junction improvements transferred into tandem devices, which allowed us to fabricate perovskite/silicon tandem solar cells with a certified PCE of $29.15\\%$ . This value surpasses the best silicon single-junction cell $(26.7\\%)$ and is comparable to the best GaAs solar cell (27) at the same area of $\\mathrm{~1~cm^{2}}$ . Under maximum power point (MPP) tracking in ambient air without encapsulation, a Me-4PACz tandem cell retained $95\\%$ of its initial efficiency after 300 hours. We used injectiondependent absolute electroluminescence (EL) spectroscopy to reconstruct the individual subcell current-voltage curves without the influence of series resistance (pseudo– $J_{\\cdot}V$ curves), which showed that the tandem device design that features only a standard perovskite film without additional bulk passivation could in principle realize PCE values up to $32.4\\%$ . \n\n# Stabilization of wide-bandgap perovskite with the hole-selective layer \n\nThe ideal top cell bandgap for perovskite absorbers in conjunction with CIGSe and Si bottom cells is \\~1.68 eV (30–32). These wider-bandgap compositions often feature a $\\mathrm{Br/I}$ ratio of ${>}20\\%$ , which can lead to phase instabilities caused by light-induced halide segregation, most strikingly evident from photoluminescence (PL) \n\nspectra that show a double-peak formation under continuous illumination (33, 34). Upon generation of charge carriers in the perovskite film, iodide-rich clusters can form that are highly luminescent because they serve as charge carrier sinks, given their lower bandgap relative to the surrounding material (35). As quantified by Mahesh et al., although some portion of the $V_{\\mathrm{OC}}$ loss is related to halide segregation, the dominant source of $V_{\\mathrm{OC}}\\mathrm{loss}$ is likely the generally low optoelectronic quality of the Br-rich mixed-halide perovskite absorbers, or high nonradiative recombination rates at their interfaces (35). Hence, to unambiguously determine the limitations and potentials of wide-bandgap compositions, it is necessary to find suitable charge-selective contacts that do not introduce further losses or instabilities. \n\nWe show that fast charge extraction paired with surface passivation can effectively suppress the formation of a double-peak emission in the PL, indicative of phase stabilization, and simultaneously enable a high quasi–Fermi level splitting (QFLS) and device performance. Rather than optimizing the perovskite composition or passivating the film, we chose a variant of the widely used Cs-, FA-, and MA-containing “triplecation” perovskite (36) that is highly reproducible (FA, formamidinium; MA, methylammonium) and focused on preparing an optimal chargeselective contact on which the perovskite film was deposited. We enlarged the bandgap by increasing the $\\mathrm{Br/I}$ ratio to obtain a 1.68-eV $23\\%$ Br) absorber instead of the commonly used 1.60 to $1.63\\ \\mathrm{eV}$ ${\\sim}17\\%$ Br), yielding a nominal precursor composition of $\\mathrm{Cs_{0.05}(F A_{0.77}M A_{0.23})_{0.95}P b(I_{0.77}B r_{0.23})_{3}}$ . \n\nA schematic of the device stack and the hole-selective layers (commonly abbreviated as HTLs, “hole-transporting layers”) used for PL measurements is shown in Fig. 1. We first compared the QFLS measured by absolute PL and then the PL stability of this perovskite composition prepared on indium tin oxide (ITO) substrates covered by the HTLs. In recently published high-PCE p-i-n (“inverted”) singlejunction and tandem PSCs, the polymer poly [bis(4-phenyl)(2,4,6-trimethylphenyl)amine] (PTAA) or the comparable poly[N,N′-bis(4- butylphenyl)-N,N′-bis(phenyl)-benzidine](polyTPD) is typically used (10, 11, 37, 38). Alternatively, SAMs based on carbazole, such as MeO-2PACz and 2PACz, can form passivated interfaces while allowing for low transport losses because they are ultrathin $\\left(<1\\mathrm{nm}\\right)$ (7). The introduction of a methyl-group substitution to the “lossless” hole-selective interface created by 2PACz (7) led to a more optimized alignment with the perovskite valence band edge (see energetic band edge diagram in fig. S1) with a similar dipole moment (\\~1.7 D) and resulted in faster charge extraction. The supplementary materials contain the synthesis scheme of the SAMs we used. In the literature concerning the n-i-p configuration of PSCs, methoxy substituents are prevalent in HTLs, with some reports of a possible passivation function at the perovskite interface (39–42). For the p-i-n configuration, however, the standard high-performance HTLs PTAA and polyTPD contain alkyl substituents. In the present study, we directly compared methoxy and methyl substituents in p-i-n cells with MeO-2PACz and Me-4PACz, with the results showing advantages for the methyl substitution with respect to both passivation and hole extraction. We tested the influence of the aliphatic chain length $(n)$ in carbazole-based SAMs without (nPACz) and with methyl substitution (Me-nPACz) on PSC performance and found an optimum FF at $n=2$ for nPACz and $n=4$ for Me-nPACz (see fig. S23). For $n=6$ , both SAMs led to current-voltage hysteresis. \n\nThe QFLS values of bare perovskite films (Fig. 1B) deposited on 2PACz and Me-4PACz were similar to that on quartz glass, commonly regarded as a perfectly passivated substrate (16). Perovskite compositions with high Br content typically segregate into I-rich phases indicated by increased PL intensity at lower photon energies, here at a wavelength of $780~\\mathrm{nm}$ (33). Pristine regions of the nonsegregated perovskite film emitted photons at a peak wavelength of ${\\sim}740\\ \\mathrm{nm}$ for perovskite deposited on glass (Fig. 1C) or ITO/PTAA (Fig. 1D), and a similar response was seen for the SAM MeO-2PACz (fig. S3) on ITO. However, the perovskite emission was more stable over time on ITO/2PACz and ITO/Me-4PACz substrates (Fig. 1E and fig. S3). The raw spectra are shown in fig. S4. \n\nAmong the studied HTLs, phase segregation was inhibited only if the perovskite was grown on a substrate that fulfilled the requirements of both fast charge extraction and good passivation; Fig. 1F shows that passivation alone was insufficient. The black curve shows a PL spectrum of the perovskite film on an insulating glass substrate that was covered by Me-4PACz after $10\\mathrm{min}$ of continuous spot illumination with 1-sun equivalent photon flux. The illuminated film showed signs of I-rich phases emitting at a center wavelength of ${\\sim}780~\\mathrm{nm}$ . The glass substrate ensured that no hole transfer out of the perovskite bulk occurred. In contrast, a conductive ITO substrate that allowed hole transmission in combination with Me-4PACz increased the PL stability, as evidenced by the sharp peak with emission centered at ${\\sim}740\\mathrm{nm}$ even after 10 min of spot illumination. \n\nA bare ITO substrate seemed to prevent charge accumulation as well, allowing a stable PL peak position at 1-sun intensity (spot size $0.12\\mathrm{cm}^{2}$ ; see fig. S6). The connection between charge accumulation in the perovskite and phase instability was reported in previous studies in which a reduced density of carriers increased the activation energy of mobile ion species and allowed the film to remain in its initial form (43, 44). Spot illumination $\\mathrm{(0.12\\mathrm{cm}^{2}}$ with 1-sun photon flux) represented increased stress testing on phase stability compared to full illumination because it created an outward driving force for ions from the illuminated area (45). Consequently, a smaller illumination spot (i.e., larger edge-to-area ratio) at the same illumination intensity showed a faster PL redshift (see figs. S5 and S6). To compare the degree of PL redshift and double-peak formation, we evaluated the ratio of the two emission center intensities at 740 and $780~\\mathrm{nm}$ for two different excitation fluences equivalent to 1-sun and 30-sun illumination (Fig. 1, G and H). At 1-sun–equivalent intensity, only 2PACz and Me-4PACz on ITO had a stable ratio. However, upon increasing the intensity and thus the charge carrier generation rate by a factor of 30, a Me-4PACz–covered ITO substrate differed from the 2PACz–covered substrate by still displaying a similarly stable PL intensity ratio. \n\nWe used transient photoluminescence (TrPL) to analyze charge carrier transfer into adjacent charge-selective layers (46). The full decay is governed by nonradiative, trap-assisted surface/ bulk recombination (mostly monoexponential decay), radiative recombination (“bimolecular,” second-order decay), and charge transfer effects, which can be disentangled if these time constants differ sufficiently from each other (18). Figure 2A presents PL transients of $1.68~\\mathrm{eV}-$ bandgap perovskite films on ITO/HTL substrates. With MeO-2PACz and PTAA, it was not possible to clearly differentiate between charge extraction and trap-assisted recombination because the nonradiative recombination was high (as evidenced by lower QFLS values relative to quartz glass; Fig. 1B) and because the transients did not saturate toward one process. In contrast, the PL transients for 2PACz and Me4PACz showed a clear monoexponential decay at later times, indicating Shockley-Read-Hall recombination $(47)$ . Fits to the TrPL transients (fig. S8) were used to compute the differential lifetime $\\tau=-\\{d\\ln[\\phi(t)]/d t\\}^{-1}$ (Fig. 2B), where $\\boldsymbol{\\phi}(t)$ is the time-dependent PL photon flux. In this representation, the processes that reduce the PL counts over time are separable, and the transient decay time (or “lifetime”) is directly readable at each time point (46). \n\nThe asymptotically reached high TrPL lifetimes of ${>}5~\\upmu\\mathbf{s}$ for both 2PACz and Me-4PACz suggests that there were minimal nonradiative recombination losses at the SAM interfaces. The charge transfer process at early times (until ${\\tilde{\\mathbf{\\Gamma}}}^{\\sim1}{\\mathrm{~}}\\upmu\\mathbf{s})$ led to a sharp rise of $\\boldsymbol{\\uptau}$ , resembling simulated curves by Krogmeier et al. (46). The transition from increasing lifetime to the plateau marks the end of charge transfer, and nonradiative first-order recombination becomes dominant. Because PLQY measurements of films on 2PACz and Me-4PACz indicated a similar level of interface recombination under the same charge generation conditions (see also fig. S9), the steepness of this rise was influenced by the charge transfer speed. The observed gradient for Me-4PACz implied a faster hole transfer to the underlying ITO relative to 2PACz, with the saturation starting after $\\sim300$ ns rather than ${\\sim}1\\upmu\\mathbf{s}$ . \n\nIn the charge carrier generation regime of this experiment $_{\\cdot\\sim1}$ sun, ${\\sim}3\\ \\times\\ {10}^{15}\\ \\mathrm{cm}^{-3},$ , trap-assisted recombination dominated, with the PL flux scaling proportionally to the density of photogenerated carriers $n,$ , as evidenced by intensity-dependent TrPL shown in fig. S9. Figure S9 further demonstrates that at higher generation conditions, the PL flux scaled proportionally to $n^{2}$ , where transients usually show a multiexponential signature, as seen with 2PACz and quartz (fig. S10). Nonetheless, in this regime the Me-4PACz transients remained monoexponential until generation densities exceeded ${\\sim}35$ suns equivalent. We interpret this as a consequence of a large hole-extraction flux, which causes first-order recombination to dominate even in this injection regime. \n\nWe quantify this phenomenon of persisting domination of first-order recombination in Fig. 2C by displaying the ratio of higher-order to first-order recombination for the different generation conditions (see supplementary text for the evaluation method). Comparison of Me-4PACz to 2PACz indicates that the holeextraction flux of Me-4PACz was larger by a factor of ${>}10$ , because the curvature of the TrPL transient only begins to resemble that of 2PACz at a factor of ${>}10$ higher generation density (indicated by the blue dashed line in Fig. 2C). \n\n![](images/6cc75888f97452b4cb4b00e160fe8325bfa307ae4780f7a7b8ba2640e3c42c16.jpg) \nFig. 1. Photoluminescence properties and stability assessment of perovskite films on different substrates. (A) Schematic description of the photoluminescence (PL) experiment and chemical structure of a general carbazole-based SAM, with R denoting a substitution, which in this work is either nothing (2PACz), a methoxy group (MeO-2PACz), or a methyl group (Me-4PACz). The number 2 or 4 denotes the number of the linear C atoms between the phosphonic acid anchor group and the conjugated carbazole main fragment. (B) Quasi–Fermi level splitting (QFLS) values of nonsegregated 1.68-eV bandgap perovskite films on a bare glass substrate and different hole-selective layers on the transparent and conductive indium tin oxide (ITO). Error bars denote the global error of the evaluation method $(-20\\mathrm{\\meV},$ ). (C to E) Time-dependent \nphotoluminescence spectra analyzing phase stability of perovskite absorbers with 1.68-eV bandgap. The perovskite films were deposited either on glass (C) or on ITO substrates with different hole-selective layers [(D) and (E)]. The color scale is at the far right. (F) PL spectra before (dashed lines) and after 600 s of light-soaking (solid lines) under 1-sun equivalent illumination in air, comparing the perovskite grown on Me-4PACz that had been deposited on a glass substrate and a conductive ITO substrate. (G) Ratio of PL intensities at $780\\mathsf{n m}$ (I-rich domains) and $740\\mathsf{n m}$ (neat perovskite) from the PL evolutions in (C), (D), (E), and two other hole-selective layers (see fig. S4; illumination spot size ${\\sim}0.12\\ \\mathsf{c m}^{2},$ , shown as a figure of merit for phase stability. (H) Ratio of PL intensities as in (G), but at higher illumination intensity through decrease of the excitation spot size to $0.4~\\mathsf{m m}^{2}$ . \n\nThe carrier mobilities determined by optical pump terahertz probe measurements (fig. S12) were similar between perovskite films grown on the different HTLs. To also exclude differences in perovskite composition and crystal orientation due to possible growth differences, we probed the effect of the HTL on these properties by grazing-incidence wide-angle x-ray scattering at the four-crystal monochromator beamline of the Physikalisch-Technische Bundesanstalt (48). Azimuthally integrated diffraction patterns collected on a movable PILATUS detector module (49) showed comparable composition in each case (fig. S13), with marginally increased $\\mathrm{PbI_{2}}$ scattering intensity on PTAA as we observed in our previous work (7). Comparing azimuthal intensity profiles for perovskite scattering features (fig. S14), we found a negligible difference in crystallographic orientation between the samples. \n\nOur complete solar cells were capped by $\\mathrm{C}_{60}$ as the electron-selective contact. The electron extraction speed did not limit the cell operation, as demonstrated by a time-resolved terahertz photoconductivity measurement combined with TrPL on a quartz/perovskite/ $\\mathrm{\\DeltaC}_{60}$ sample (fig. S11). We compared the decays of free charge carriers after interface-near carrier generation on both sample sides and found an electron transfer time constant of ${\\boldsymbol{\\sim}}1$ ns, substantially faster than hole transfer at the hole-selective layer (in the range of ${\\sim}100~\\mathrm{ns},$ ). The extraction velocity into the $\\mathrm{\\DeltaC}_{60}$ in our model was $1.6\\times10^{4}\\mathrm{cm/s}$ (see fig. S11 for details), a value similar to earlier reported velocities (46). \n\n# Performance of perovskite single-junction solar cells \n\nFor analysis at the solar cell level, we focused on the simple single-junction device stack glass/ ITO/HTL/perovskite/ $\\mathrm{^{\\prime}C_{60}/S n O_{2}/A g,}$ with the $\\mathrm{{SnO}_{2}}$ serving as a buffer layer for indium zinc oxide (IZO) sputtering in the fabrication of tandem solar cells (50). We found that the combination of fast charge extraction and passivated interface not only mitigated phase instability (see Fig. 1) but was also linked to an increased FF of solar cell devices, mainly by a decreased diode ideality factor of the PSCs. The FF is the major remaining parameter for which PSCs have not yet come close to the values of established solar cell technologies $(24,57)$ (see fig. S16 for FF comparisons), with the ideality factor being one of the main properties that limit high-efficiency PSCs (29). MeO-2PACz and 2PACz led to FFs of up to $82\\%$ (Fig. 3A), whereas with Me-4PACz the values were as high as $84\\%$ , representing ${\\sim}93\\%$ of the radiative limit. \n\nFigure 3B shows $J{-}V$ curves recorded at simulated AM1.5G illumination conditions, comparing champion PTAA and Me-4PACz cells of the same batch and showing the superior performance of the SAM. The ideality factors $n_{\\mathrm{ID}}$ for PSCs with different HTLs (Fig. 3C and Table 1) were ${\\sim}1.26$ for Me-4PACz, ${\\sim}1.42$ for 2PACz, 1.51 for MeO-2PACz, and \\~1.55 for PTAA cells. Figure S20 compares the $V_{\\mathrm{OC}}$ values achieved with the different HTLs. Despite the large differences in passivation at the holeselective interface, the differences in $V_{\\mathrm{OC}}$ were not as large (average difference of $30~\\mathrm{mV}$ between PTAA and Me-4PACz) because of the limiting nonradiative recombination at the $\\mathrm{C}_{60}$ interface. However, as reasoned above, the $\\mathrm{C}_{60}$ layer did not limit charge extraction, hence the different extraction speeds invoked by the HTLs directly influenced the FF values. The high FF with Me-4PACz was accompanied by high $V_{\\mathrm{OC}}$ values of up to $1.16~\\mathrm{V}_{:}$ ; when a LiF interlayer was placed between the perovskite and $\\mathrm{C}_{60}$ , we achieved a maximum voltage of 1.234 V (52, 53) (Fig. 3D and fig. S20). The combination of a high $V_{\\mathrm{OC}}$ with low $n_{\\mathrm{ID}}$ was previously considered as challenging for PSCs (28), and it allowed us to fabricate a perovskite single junction with a PCE of $20.8\\%$ with Me-4PACz (fig. S18) and a perovskite bandgap of $1.68~\\mathrm{eV}$ . \n\nTo investigate the FF values without the influence of series resistance losses, we measured intensity-dependent absolute PL spectra and computed the QFLS values [or implied $V_{\\mathrm{OC}}$ $\\mathrm{\\Delta}\\langle i V_{\\mathrm{oc}})]$ as a function of the illumination intensity. The derived data pairs of generation currents and $i V_{\\mathrm{OC}}$ values allowed the reconstruction of hypothetical, so-called pseudo–J-V curves, as recently shown in $(54)$ (Fig. 3D). The extracted FF and pseudo-FF values (FF in absence of transport losses) of bare perovskite films grown on different HTLs are summarized in Table 1, row 1. Both 2PACz and Me-4PACz enabled high “pseudo-FF” (pFF) values of ${\\sim}88\\%$ , which is $96.8\\%$ of the detailed balance limit and similar to the value achieved on a bare quartz substrate. PTAA allowed for a pFF of only $85.6\\%$ . \n\nThis analysis highlights how the SAMs formed a practically lossless interface between ITO and perovskite. Interestingly, when including a $\\mathrm{C}_{60}$ layer on top of the perovskite film, no \n\n![](images/9e8b72b4bc5c2899404bc7b7710e911fad6704f86a6ae98e7512ab1dd91eee3e.jpg) \nFig. 2. Role of charge transfer in transient photoluminescence (TrPL). (A) PL transients of perovskite on ITO/hole-selective layer substrates. The dashed lines indicate the background levels. (B) Computed differential lifetimes from fits to the transients in (A), showing the single-exponential decay time at each time of the transient, with early times shown in the inset. The inset highlights the region of the Me-4PACz and 2PACz transients that is governed by hole transfer into the ITO. Excitation density is similar to 1-sun conditions (fluence of ${\\sim}30\\mathsf{n J/c m}^{2}$ , $2\\times10^{15}$ to $3\\times10^{15}\\mathrm{cm}^{-3},$ . \nColors are as in (A). The shaded areas are a guide marking the approximate time domain in which the Me-4PACz transient is governed by charge transfer. (C) Ratio of higher-order processes to monoexponential decay in the TrPL transients, revealing that ${\\mathsf{M e}}{\\cdot}4{\\mathsf{P}}{\\mathsf{A C}}z$ not only extracts holes faster [inset in (B)] but does so at $^{-10}$ times the efficiency of 2PACz, because the Me-4PACz transient shows the same magnitude of radiative recombination only with charge carrier generation that is higher by a factor of \\~10 (comparison along the dashed line; see fig. S10 for details). \n\n![](images/8ba124e598d33bd96b86818df47b039355667ee58893d06b9dc7b2dec7d99250.jpg) \nFig. 3. Performance and fill factor loss analysis of p-i-n solar cells with different hole-selective layers. (A) Comparison of fill factor values of PSCs with the stack glass/ITO/HTL/perovskite $\\mathrm{^{\\prime}C_{60}/S n O_{2}/A g,}$ triple-cation perovskite absorber with 1.68-eV bandgap. All data are from cells made from the same perovskite precursor and contact processing batch. The boxes indicate the 25/75 percentiles; the whiskers indicate the 10/90 percentiles. (B) $J{-}V$ curves of the best cells of the batch in (A) and a $J\\cdot V$ curve of a Me-4PACz cell from another batch with LiF interlayer between $\\mathsf{C}_{60}$ and perovskite, reaching a $V_{\\mathrm{OC}}$ of $1.234\\mathrm{~V~}.$ . (C) Intensity-dependent open-circuit voltage $V_{\\mathrm{OC}}$ with linear fits (dashed lines). (D) Pseudo–J-V curves reconstructed from intensity-dependent \n\nTable 1. Comparison of “pseudo” fill factors (pFF) and implied open-circuit voltages $(i V_{\\mathrm{0c}})$ . The values were derived from suns-PL and suns- $\\cdot V_{\\mathrm{OC}}$ measurements for our perovskite film on all studied hole-selective layers and on quartz glass. The table also shows the maximum FF attained in $J-V$ measurements (max FF) (see also Fig. 3). “Half cell” refers to substrate/HTL/absorber, whereas “full cell” denotes the complete solar cell including $\\mathsf{C}_{60}$ , $\\mathsf{S n O}_{2}$ and $\\mathsf{A g}$ metal electrode. \n\n
Quartz glassPTAAMeO-2PACz2PACzMe-4PACz
pFF (%), half cell (suns-PL)87.985.685.588.387.5
pFF (%), half cell + C6o (suns-PL)85.385.385.385.385.3
pFF(%),full cell (suns-Voc)85.885.986.987.9
max FF (%), full cell (J-V)79.881.981.884.0
iVoc (V), half cell (absolute PL)1.2581.1851.2151.2441.248
niD, full cell (suns-Voc)1.551.511.421.26
\n\ndifferences between the studied HTLs for the $i V_{\\mathrm{OC}}$ and pFF were apparent (Fig. 3D, dashed lines; Table 1, row 2), as the $\\mathrm{C}_{60}$ layer sets an $i V_{\\mathrm{OC}}$ limitation through high nonradiative recombination rates (53). This limitation was only absolute PL measurements on the illustrated sample stack. The 2PACz and Me-4PACz curves almost coincide; the dashed lines represent pseudo–J-V curves from the sample variations including the electron-selective $\\mathsf{C}_{60}$ layer, with which all curves are comparable because of the limiting nonradiative recombination at the $\\mathsf{C}_{60}$ interface. (E) Pseudo–J-V curves reconstructed from the measurements in (C). Table 1 summarizes the FF values extracted from the pseudo–J-V curves. (F) Repartition of loss mechanisms lowering the cell’s FF below the detailed balance limit, comparing PTAA and Me-4PACz cells: nonradiative loss in neat material $[=$ radiative FF limit minus pFF of neat film), nonradiative interface loss $\\mathbf{\\Psi}=\\mathbf{\\Psi}$ pFF of neat film minus pFF of full cell), and transport loss $\\mathbf{\\bar{\\rho}}=\\mathbf{\\rho}$ pFF of full cell minus FF of measured solar cell). \n\novercome with a counter electrode on the $\\mathrm{C}_{60}$ (Fig. 3E and full devices), which underscores the role of the dipoles that Me-4PACz and 2PACz created at the ITO surface. The calculated molecular dipole value of the hole-transporting fragment is ${\\sim}0.2\\mathrm{~D~}$ for MeO-2PACz, ${\\sim}1.7\\mathrm{D}$ for Me-4PACz, and ${\\sim}2\\mathrm{~D~}$ for 2PACz. The positive dipoles shifted the work function of the ITO toward higher absolute numbers (fig. S2A), which presumably resulted in a higher builtin potential throughout the device (55, 56). A well-defined built-in potential can exist with the presence of a second electrode countering the ITO—in this case, Ag or Cu. Thus, when reconstructing the J-Vs from the suns- $\\cdot V_{\\mathrm{OC}}$ measurement on full devices in Fig. 3C to extract the pFF (Table 1, row 3), both 2PACz and Me4PACz overcame the pFF and $i V_{\\mathrm{OC}}$ limitations imposed by the $\\mathrm{C}_{60}$ layer (Fig. 3E). \n\nThe differences between the electrical $J_{-}V$ curves (max. FF $84\\%$ ) in Fig. 3B and pseudo– $J{-}V$ curves (max. FF ${\\sim}88\\%$ ) arose from transport losses caused by the finite mobility of the $\\mathrm{C}_{60},$ , non-optimized sample design, and ITO sheet resistance, as well as the measurement setup. Figure 3F summarizes a comparison of the different contributions to FF losses for PTAA density. Furthermore, the perovskite subcell is fitted with a single-diode model (solid brown line). The reconstructed tandem $J-V$ (dashed line) was calculated by adding the voltages of the subcells for each current density. The $J-V$ measurement under simulated 1-sun illumination of this cell is shown as a solid red line. Furthermore, a photograph of the tandem solar cell at high injection current is shown. Due to a bandgap of 1.68 eV, the subcell emits light in the visible wavelength range and thus, the emission is visible by eye and with a regular digital camera. \n\n![](images/6a65f61d09e93a1ee42930cb03b2c39ccc9ce4f8fb88bb542c2f7c477a6b2ba8.jpg) \nFig. 4. Characteristics of monolithic perovskite/silicon tandem solar cells using various HTLs. (A) Schematic stack of the monolithic perovskite/silicon tandem solar cell. (B) SEM image of a tandem cross section with Me-4PACz as HTL. (C) Statistics of the PCE of PTAA, MeO-2PACz, 2PACz, and Me-4PACz tandem solar cells from $J-V$ scans. (D) Certified $J-V$ curve measured at Fraunhofer ISE, including the MPP value and the device parameters (red), in comparison to a tandem cell with PTAA (gray) as HTL measured in-house. (E) External quantum efficiency (EQE) and reflection (denoted \nas 1-R) of the certified tandem cell measured in-house. The AM1.5G-equivalent current densities are given. (F) Long-term MPP track using a dichromatic LED illumination of nonencapsulated solar cells in air at a controlled temperature of $25^{\\circ}\\mathrm{C}$ and relative humidity of 30 to $40\\%$ . The data are normalized to the MPP average of the first $60\\mathrm{min}$ of each individual track to account for measurement noise. Because of the fast degradation, the MPP track of the PTAA $^+$ LiF cell is normalized to the first recorded value. The legend specifies each HTL and notes whether a LiF interlayer was used. \n\n![](images/1585a5a9b779480fc89983433503d6a01bc5ab8a43af3acaafadc95ce90a67e3.jpg) \nFig. 5. Luminescence subcell analysis of a tandem solar cell with Me-4PACz and LiF interlayer. (A) Absolute PL spectra of the subcells recorded under 1-sun equivalent illumination. The excitation wavelengths are 455 nm and $850~\\mathsf{n m}$ for the perovskite and silicon subcell, respectively. PL images constructed from the integrated PL fluxes are also shown. The edge length of the active area (inner square) is 1 cm. (B) Reconstructed $J-V$ curves calculated from injection-dependent electroluminescence (EL) measurements (open symbols) and shifted by the photogenerated current \n\nand Me-4PACz, derived from comparisons of the pseudo– $J_{\\cdot}V$ curves to the measured $J/F$ curves and radiative limits, as previously reported by Stolterfoht et al. (54). In addition to nonradiative losses at the PTAA interface (red), the film thickness $\\cdot{\\mathrm{-}}10\\mathrm{nm}$ , versus ${<}1\\mathrm{nm}$ with a SAM) and low conductivity of the PTAA led to greater transport losses than with Me-4PACz. \n\n# Integration into monolithic perovskite/silicon tandem solar cells \n\nEfficient passivation in combination with fast hole extraction of Me-4PACz in perovskite single junctions could be transferred into monolithic tandem solar cells, which led to higher FF, $V_{\\mathrm{OC}},$ and stability. A schematic stack of this solar cell is shown in Fig. 4A. We used a silicon heterojunction solar cell as the bottom cell (26), based on a $260\\mathrm{-}\\upmu\\mathrm{m}$ -thick ntype float-zone Si wafer processed as described in the supplementary materials. The textured rear side enhanced the near-infrared (NIR) absorption, whereas the polished front side enabled the deposition of spin-coated perovskite. The $20\\mathrm{-nm}$ ITO recombination layer also served as the anchoring oxide for the SAMs (7). The top cell, with the same 1.68-eV perovskite bandgap and nominal precursor composition $\\mathrm{Cs_{0.05}(F A_{0.77}M A_{0.23})_{0.95}P b(I_{0.77}B r_{0.23})_{3}}$ as analyzed above, formed the single-junction stack of ITO/HTL/perovskite/ $\\mathrm{(LiF)/C_{60}/S n O_{2}/I Z O/}$ Ag/LiF. Figure 4B shows a scanning electron microscopy (SEM) cross-section image of a part of the tandem solar cell; no obvious differences were observed between perovskite films on the different HTLs (fig. S24). The molecular SAM cannot be resolved with SEM. Figure S25 shows a photograph and layout of the tandem device. \n\nFigure 4C compares the PCE of tandem solar cells based on PTAA, MeO-2PACz, 2PACz, and Me-4PACz, with and without a LiF interlayer at the perovskite $\\mathrm{'C}_{60}$ interface. With PTAA, the LiF interlayer led to rapid degradation of the cells (see fig. S26 for individual parameters). Without the interlayer, we achieved an average PCE of $25.25\\%$ . In contrast, the average efficiency of MeO-2PACz and 2PACz was $26.21\\%$ and $26.56\\%$ , respectively. The use of a LiF interlayer for Me-4PACz cells increased the $V_{\\mathrm{OC}}$ but reduced the FF. Thus, both configurations reached a similar average PCE of $26.25\\%$ and $26.41\\%$ , respectively. However, with Me-4PACz the maximum PCEs $(<29\\%)$ 0 are higher than cells with 2PACz, mainly because of higher FF of up to $81\\%$ . These high FF values were achieved despite almost all cells being perovskite-limited (table S1). The statistics of all photovoltaic parameters are shown in fig. S26. The $J_{-}V$ measurements of the champion cells of each configuration are shown in fig. S28; the PV parameters are summarized in table S2. \n\nThe tandem solar cells did not reach FF values comparable to those in single-junction cells because of the larger active area $(1~\\mathrm{cm}^{2})$ and a transparent conductive oxide (TCO) without grid fingers, leading to increased series resistance. The cells showed very high $V_{\\mathrm{OC}}$ values of up to $\\mathrm{1.92V}$ (fig. S30). With a $V_{\\mathrm{OC}}$ of $\\mathrm{\\sim}715~\\mathrm{mV}$ from the bottom cell at half illumination (fig. S31), the contribution of the perovskite subcell was ${\\sim}1.2\\mathrm{V}$ . Figure 4D shows a direct comparison between champion PTAA and Me-4PACz tandem cells; besides the $50\\mathrm{-mV}$ improvement in $V_{\\mathrm{OC}},$ the enhanced hole extraction boosted the FF by ${\\sim}4\\%$ absolute. \n\nWe sent a tandem cell with Me-4PACz and a LiF interlayer to Fraunhofer ISE CalLab for independent certification (Fig. 4D; see fig. S32 for certificate). With a $V_{\\mathrm{OC}}$ of $1.90~\\mathrm{V}$ , FF of $79.4\\%$ , and a short-circuit current density $J_{\\mathrm{SC}}$ of $19.23\\mathrm{\\mA\\cm^{-2}}$ , the cell had a PCE of $29.01\\%$ when measuring from $J_{\\mathrm{SC}}$ to $V_{\\mathrm{OC}},$ similar to our in-house measurement (fig. S33) and was certified at the MPP with a PCE of $29.15\\%$ with a designated area of $1.064\\mathrm{cm}^{2}$ . This PCE surpasses other monolithic (10, 27) and fourterminal perovskite-based tandem solar cells $(57)$ and is on par with the best GaAs single cell with the same active area (27). \n\nFigure 4E shows the external quantum efficiency (EQE) of the certified tandem cell. Under AM1.5G-equivalent illumination conditions, the photogenerated current densities $J_{\\mathrm{ph}}$ in the perovskite and silicon subcells were $\\mathrm{1\\bar{9}.41\\ m A\\ c m^{-2}}$ and $20.18\\mathrm{\\mA\\cm^{-2}}$ , respectively, which agreed with the measured $J_{\\mathrm{SC}}$ of $19.23\\mathrm{mAcm^{-2}}$ . The tandem solar cell exhibited a nonideal current mismatch of 0.77 mA cm–2, and even though the perovskite cell sets the slope around $0\\mathrm{V}_{:}$ , the cell reached a FF of $79.5\\%$ . The cumulative photogenerated current density and loss caused by reflection were $39.59\\mathrm{mAcm^{-2}}$ and $2.57\\mathrm{mAcm^{-2}}$ , respectively. A comparison of EQEs and reflection losses between a cell of this work (planar front side) and a fully textured cell by Sahli et al. (58) is shown in fig. S34. \n\nAfter the certification, we fabricated more Me-4PACz tandem solar cells without a LiF interlayer (fig. S26), which showed average performance similar to that with LiF. The champion cell showed a higher FF of $81\\%$ and lower $V_{\\mathrm{OC}}$ of $\\ensuremath{\\mathrm{1.87~V}}$ than without LiF. Together with a $J_{\\mathrm{SC}}$ of $19.37\\mathrm{mAcm^{-2}}$ , this led to a PCE of $29.29\\%$ and a stabilized efficiency of $29.32\\%$ (fig. S35). \n\nWe measured the stability of different nonencapsulated tandem solar cells (Fig. 4F). To track the degradation induced by either the top or the bottom cell more carefully, we developed a dichromatic LED setup using \n\nLEDs with center emission wavelengths of $470\\ \\mathrm{nm}$ and $940~\\mathrm{nm}$ (fig. S36) and with independent intensity calibration and recording. We adjusted the mismatch so that the $J_{\\mathrm{ph}}$ in the individual subcells was equal to that measured under AM1.5G-equivalent illumination to maintain proper stability tracking of monolithic tandem solar cells (see below and supplementary text). The devices were measured under continuous MPP load (using voltage perturbation), at $25^{\\circ}\\mathrm{C}$ and in ambient air with 30 to $40\\%$ relative humidity. The photogenerated current densities of the subcells are given in table S3 and set which subcell is limiting. The degradation for a perovskitelimited tandem cell with Me-4PACz+LiF showed $75.9\\%$ of its initial efficiency $(29.13\\%)$ after 300 hours. When we substituted the Me-4PACz with PTAA (perovskite-limited), the PCE decreased to $74.5\\%$ of its initial PCE $(25.9\\%)$ after only 90 hours. \n\nWe additionally tracked a cell with Me4PACz as HTL without a LiF interlayer to test the intrinsic stability of the HTL/perovskite combination. After 300 hours, the cell still operated at $95.5\\%$ of its initial PCE. Although the cells were current-matched, this track monitors a degradation of the perovskite, as it directly translates into the performance of the tandem cell and no degradation of the Si subcell is expected within these time scales. Our comparison strongly suggests that the use of a LiF interlayer reduces the stability. As described in other reports (59–62), the decrease in stability might be caused by deterioration of the electrodes and $\\mathrm{C}_{60}$ interface upon migration of $\\mathrm{Li^{+}}$ and $\\mathrm{F}^{-}$ ions. We note that it is important to declare the mismatch conditions because the use of a NIR-poor spectrum would lead to a Si-limited cell and thus to a higher stability (see supplementary text). Comparing this result to state-of-the-art stability tests of nonencapsulated tandem solar cells in ambient conditions, where the cells retained $90\\%$ of initial PCE after 61 hours (58) and $92\\%$ after 100 hours (13), our Me-4PACz tandem solar cell showed a superior operational stability. \n\nIn addition to the long-term stability measurements at $25^{\\circ}\\mathrm{C},$ we conducted an MPP track of a Me-4PACz tandem cell at elevated temperatures. Following the procedure of Jošt et al., the temperature was successively increased from $25^{\\circ}$ to $85^{\\circ}\\mathrm{C}$ and back to $25^{\\circ}\\mathrm{C}$ $(\\mathit{63})$ . There was no loss in PCE after this 200-min procedure, despite the high MA and Br amount of the wide-bandgap perovskite used here (fig. S39). \n\n# Subcell J-V characteristics of a monolithic tandem solar cell \n\nOne downside of monolithic multijunction solar cells is that the subcell characteristics are barely accessible. External quantum efficiency measurements are the only subcellresolved measurements presented in almost all publications reporting multijunction solar cells. Here, we used absolute PL measurements in each subcell of a representative tandem solar cell (Me-4PACz $^+$ LiF). With this, we could estimate the QFLS, and thus the $V_{\\mathrm{OC}}$ was accessible for both subcells independently. For this, we used hyperspectral absolute PL imaging at equivalent 1-sun conditions with an illumination spot larger than the area of the solar cells. The PL spectra and the integrated images are shown in Fig. 5A. \n\nFrom the high-energy slope of the absolute PL spectra of the subcells, the individual implied $V_{\\mathrm{OC}}$ values were calculated: 1.18 V for the perovskite subcell and $0.72{\\mathrm{~V~}}$ for the Si subcell $(18,64)$ . From the PL spectra, we calculated the PLQY of both subcells, yielding values of $1.5\\%$ for Si and $0.02\\%$ for the perovskite. PLQY values exceeding $5\\%$ have already been demonstrated in perovskite single-junction devices for lower bandgaps (19). \n\nTo estimate the pseudo– $J_{\\cdot}V$ curves of the subcells, we performed absolute EL imaging, where the excess charge carriers are generated electrically to access the subcell characteristics (65–68). For each injected current, an EL image was recorded, from which the voltage of the subcells can be calculated from an average over the active area (fig. S40). With the reconstructed pseudo– $.J{\\cdot}V$ curves from injection current–dependent EL imaging, we analyzed the maximum possible efficiency of this cell stack with minimized charge transport losses (see supplementary materials for more details). We reconstructed both subcell $J_{-}V$ curves by calculating the implied voltage at each injected current, yielding a “pseudo” light–J-V $(J V_{\\mathrm{EL}})$ curve for each subcell after shifting it by the respective photogenerated current density $J_{\\mathrm{ph}}$ calculated from EQE measurements; these $J_{\\mathrm{ph}}$ values amounted to 18.7 and $20.6\\mathrm{\\mA\\cm^{-2}}$ for the top and bottom cell, respectively. The open symbols in Fig. 5B show the measured EL data points averaged over the perovskite and silicon subcell and shifted by their respective $J_{\\mathrm{ph}}$ values. \n\nFor the perovskite, we additionally fitted the data with a single-diode model to display the $J_{\\cdot}V$ curve over the whole voltage range, which was otherwise not accessible during the EL measurement. To obtain the tandem $\\mathcal{\\pi}_{\\mathrm{EL}},$ we added the voltages of the subcells for each current density. The dashed line shows the result. The reconstructed curve deviated from the electrically measured $J_{-}V$ curve under a solar simulator. This is mainly because EL gave access only to the internal voltage, whereas an electrical $J{-}V$ curve displays the current density versus external voltage (which is affected by series resistances; see supplementary text). Hence, a high FF $(87.8\\%)$ of the $J V_{\\mathrm{EL}}$ can be regarded as the maximum achievable value for this particular tandem cell if the electrodes and all charge-selective layers were free of series resistance losses. This would give a PCE of $31.7\\%$ , surpassing the theoretical PCE maximum of a silicon single cell $(29.4\\%)$ ) (69). Thus, this cell stack has the capacity to overcome the $30\\%$ barrier through technical optimization of the contacts alone. However, by adjusting the mismatch conditions, even higher efficiencies are achievable. \n\nTo find the requirements for the highest efficiency, we fit the silicon subcell with a single-diode model. We conducted SPICE (Simulation Program with Integrated Circuit Emphasis) simulations to sweep the photogenerated current densities in the subcell. The single-diode models of the silicon and perovskite subcells were connected in series (schematically shown in fig. S42A), and the cumulative current density was fixed to $39.3\\mathrm{\\mA\\cm^{-2}}$ (as calculated from EQE measurements for AM1.5G-equivalent illumination). Figure S42B shows the photovoltaic parameters as a function of the mismatch $(J_{\\mathrm{ph,Si}}-J_{\\mathrm{ph,Pero}})$ . As shown in a previous publication, the $V_{\\mathrm{{oc}}}$ is almost independent of the mismatch, whereas the FF is affected by it $(26)$ . A minimum FF occurs when the $J_{\\mathrm{ph,Si}}$ is $0.7\\mathrm{\\mA\\cm^{-2}}$ below the $J_{\\mathrm{ph,Pero}}$ . However, simultaneously the $J_{\\mathrm{SC}}$ is highest under this condition. In a current-matching situation, the highest efficiency is $32.43\\%$ . This sets an estimation for the efficiency potential upon reduction of all transport losses. Decreasing the limitations set by the hole extraction speed, as shown in this work, is a viable path for exploring this potential. \n\n# REFERENCES AND NOTES \n\n1. A. De Vos, J. Phys. D 13, 839–846 (1980). \n2. W. Shockley, H. J. Queisser, J. Appl. Phys. 32, 510–519 (1961). \n3. S. E. Sofia et al., Sustain. Energy Fuels 4, 852–862 (2020). \n4. Z. Li et al., Joule 2, 1559–1572 (2018). \n5. National Renewable Energy Laboratory, Best Research-Cell \nEfficiency Chart; www.nrel.gov/pv/cell-efficiency.html. \n6. T. Todorov et al., Adv. Energy Mater. 5, 1500799 (2015). \n7. A. Al-Ashouri et al., Energy Environ. Sci. 12, 3356–3369 \n(2019). \n8. R. Lin et al., Nat. Energy 4, 864–873 (2019). \n9. G. E. Eperon et al., Science 354, 861–865 (2016). \n10. D. Kim et al., Science 368, 155–160 (2020). \n11. J. Xu et al., Science 367, 1097–1104 (2020). \n12. Y. Hou et al., Science 367, 1135–1140 (2020). \n13. B. Chen et al., Joule 4, 850–864 (2020). \n14. M. Jošt, L. Kegelmann, L. Korte, S. Albrecht, Adv. Energy Mater. \n10, 1904102 (2020). \n15. Y. Jiang et al., J. Mater. Chem. C 4, 5679–5689 (2016). \n16. I. L. Braly et al., Nat. Photonics 12, 355–361 (2018). \n17. D. W. deQuilettes et al., ACS Energy Lett. 1, 438–444 \n(2016). \n\n18. T. Kirchartz, J. A. Márquez, M. Stolterfoht, T. Unold, Adv. Energy Mater. 10, 1904134 (2020). \n19. Z. Liu et al., ACS Energy Lett. 4, 110–117 (2019). \n20. P. Caprioglio et al., Sustain. Energy Fuels 3, 550–563 (2019). \n21. Q. Jiang et al., Nat. Photonics 13, 460–466 (2019). \n22. S. Yang et al., J. Am. Chem. Soc. 141, 5781–5787 (2019). \n23. L. Krückemeier, U. Rau, M. Stolterfoht, T. Kirchartz, Adv. Energy Mater. 10, 1902573 (2020). \n24. P. K. Nayak, S. Mahesh, H. J. Snaith, D. Cahen, Nat. Rev. Mater. 4, 269–285 (2019). \n25. A. Rajagopal, R. J. Stoddard, S. B. Jo, H. W. Hillhouse, A. K. Y. Jen, Nano Lett. 18, 3985–3993 (2018). \n26. E. Köhnen et al., Sustain. Energy Fuels 3, 1995–2005 (2019). \n27. M. A. Green et al., Prog. Photovolt. Res. Appl. 28, 3–15 (2020). \n28. P. Caprioglio et al., Adv. Energy Mater. 10, 2000502 (2020). \n29. M. A. Green, A. W. Y. Ho-Baillie, ACS Energy Lett. 4, 1639–1644 (2019). \n30. K. Jäger, L. Korte, B. Rech, S. Albrecht, Opt. Express 25, A473–A482 (2017). \n31. M. Jošt et al., Energy Environ. Sci. 11, 3511–3523 (2018). \n32. T. Leijtens, K. A. Bush, R. Prasanna, M. D. McGehee, Nat. Energy 3, 828–838 (2018). \n33. E. T. Hoke et al., Chem. Sci. 6, 613–617 (2015). \n34. D. J. Slotcavage, H. I. Karunadasa, M. D. McGehee, ACS Energy Lett. 1, 1199–1205 (2016). \n35. S. Mahesh et al., Energy Environ. Sci. 13, 258–267 (2020). \n36. M. Saliba et al., Energy Environ. Sci. 9, 1989–1997 (2016). \n37. M. Stolterfoht et al., Energy Environ. Sci. 12, 2778–2788 (2019). \n38. D. Luo et al., Science 360, 1442–1446 (2018). \n39. Q. Wang et al., Adv. Energy Mater. 9, 1900990 (2019). \n40. C. Huang et al., J. Am. Chem. Soc. 138, 2528–2531 (2016). \n41. A. Torres, L. G. C. Rego, J. Phys. Chem. C 118, 26947–26954 (2014). \n42. M. Saliba et al., Nat. Energy 1, 15017 (2016). \n43. Y. Lin et al., Nat. Commun. 9, 4981 (2018). \n44. B. Chen et al., Adv. Mater. 31, e1902413 (2019). \n45. N. Phung et al., Adv. Energy Mater. 10, 1903735 (2020). \n46. B. Krogmeier, F. Staub, D. Grabowski, U. Rau, T. Kirchartz, Sustain. Energy Fuels 2, 1027–1034 (2018). \n47. F. Staub et al., Phys. Rev. Appl. 6, 044017 (2016). \n48. M. Krumrey, G. Ulm, Nucl. Instrum. Methods Phys. Res. A 467–468, 1175–1178 (2001). \n49. D. Skroblin et al., Rev. Sci. Instrum. 91, 023102 (2020). \n50. K. A. Bush et al., Nat. Energy 2, 17009 (2017). \n51. J.-F. Guillemoles, T. Kirchartz, D. Cahen, U. Rau, Nat. Photonics 13, 501–505 (2019). \n52. J. Seo et al., Energy Environ. Sci. 7, 2642–2646 (2014). \n53. M. Stolterfoht et al., Nat. Energy 3, 847–854 (2018). \n54. M. Stolterfoht et al., Adv. Mater. 32, 2000080 (2020). \n55. N. Tessler, Y. Vaynzof, ACS Energy Lett. 5, 1260–1270 (2020). \n56. W. Wang et al., Adv. Funct. Mater. 30, 1909755 (2020). \n57. B. Chen et al., Nat. Commun. 11, 1257 (2020). \n58. F. Sahli et al., Nat. Mater. 17, 820–826 (2018). \n59. R. Quintero-Bermudez, J. Kirman, D. Ma, E. H. Sargent, R. Quintero-Torres, J. Phys. Chem. Lett. 11, 4213–4220 (2020). \n60. Z. Li et al., Energy Environ. Sci. 10, 1234–1242 (2017). \n61. S.-M. Bang et al., ACS Energy Lett. 5, 1198–1205 (2020). \n62. S. N. Habisreutinger et al., Nano Lett. 14, 5561–5568 (2014). \n63. M. Jošt et al., Adv. Energy Mater. 10, 2000454 (2020). \n64. T. Unold, L. Gütay, in Advanced Characterization Techniques for Thin Film Solar Cells, D. Abou‐Ras, T. Kirchartz, U. Rau, Eds. (Wiley-VCH, 2011), pp. 151–175. \n65. S. Chen et al., Sci. Rep. 5, 7836 (2015). \n66. D. Alonso-Alvarez, N. Ekins-Daukes, IEEE J. Photovoltaics 6, 1004–1011 (2016). \n67. S. Roensch, R. Hoheisel, F. Dimroth, A. W. Bett, Appl. Phys. Lett. 98, 251113 (2011). \n68. D. Hinken, K. Ramspeck, K. Bothe, B. Fischer, R. Brendel, Appl. Phys. Lett. 91, 182104 (2007). \n69. A. Richter, M. Hermle, S. W. Glunz, IEEE J. Photovoltaics 3, 1184–1191 (2013). \n\n# ACKNOWLEDGMENTS \n\nWe thank M. Gabernig, C. Ferber, T. Lußky, H. Heinz, C. Klimm, and M. Muske at the Institute for Silicon Photovoltaics, HelmholtzZentrum Berlin (HZB), and T. Hänel, T. Henschel, M. Zelt, H. Rhein, K. Meyer-Stillrich, and M. Hartig at PVcomB (HZB) for technical assistance. A.A.-A. thanks A. Merdasa for his expertise during construction of the steady-state PL setup. Ei.K. and S.A. thank C. Wolff (University of Potsdam) and K. Brinkmann (University of Wuppertal) for fruitful discussion at the beginning of the project. A.M. acknowledges A. Drevilkauskaite for help with the synthesis of 4PACz and 6PACz materials. Funding: Supported by Federal Ministry for Education and Research (BMBF) grant 03SF0540 within the project “Materialforschung für die Energiewende”; the Federal Ministry for Economic Affairs and Energy (BMWi)–funded project ProTandem (0324288C); the HyPerCells graduate school; the Helmholtz Association within the HySPRINT Innovation lab project and TAPAS project; the Helmholtz Association via HI-SCORE (Helmholtz International Research School) (M.G., P.C., S.A., and D.N.); the European Union’s Horizon 2020 research and innovation program under grant agreement 763977 of the PerTPV project; the Research Council of Lithuania under grant agreement S‐MIP‐19‐5/SV3‐1079 of the SAM project (A.M. and T.M.); Slovene Research Agency (ARRS) funding through research programs P2-0197 and J2-1727 (M.J., G.M., and M.T.); Deutsche Forschungsgemeinschaft projects 423749265 and 03EE1017C-SPP 2196 (SURPRISE and HIPSTER) (M.S., D.N., and S.A.); EPSRC and D. Lidzey for Ph.D. studentship funding via CDT-PV (EP/L01551X/1) (J.A.S.); and Erasmus+ (J.A.S.). Author contributions: A.A.-A., Ei.K., B.L., and S.A. planned the experiments, coordinated the work,and prepared the figures; Er.K., A.M., and T.M. designed and synthesized the Me-4PACz SAM and the $(M e\\mathrm{-})\\mathsf{n P A C}z$ series; A.A.-A. and B.L. processed the single-junction cells and optimized the SAM deposition; Ei.K. and B.L. processed the tandem cells; A.B.M.V. processed the Si bottom cells; A.A.-A., H.H., and J.A.M. conducted and analyzed the PL experiments; J.A.M., A.A.-A., and Ei.K. performed the EL studies. H.H. recorded the terahertz measurements and performed the data analysis; P.C., M.G., and M.S. conducted the pseudo–J-V and FF $\\cdot V_{\\mathrm{OC}}$ loss analysis (intensitydependent $V_{\\mathrm{OC}}$ and QFLS); D.M. performed the photoelectron spectroscopy; J.A.S., D.S., and N.P. performed crystallographic analysis; G.M., M.J., B.L., and Ei.K. designed and built the tandem aging setup and recorded the long-term MPP tracks; and S.A., V.G., M.S., T.U., T.M., C.G., R.S., M.T., La.K., A.A., D.N., B.S., and B.R. supervised the projects. All authors contributed to data interpretation and manuscript writing. Competing interests: HZB and Kaunas University of Technology have filed patents for the SAM molecules described above and their use in tandem solar cells. Data and materials availability: All data are available in the main text or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/370/6522/1300/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S39 \nTables S1 to S3 \nReferences (70–85) \n\n19 June 2020; accepted 30 October 2020 \n10.1126/science.abd4016 \n\n# Science \n\n# Monolithic perovskite/silicon tandem solar cell with $529\\%$ efficiency by enhanced hole extraction \n\nAmran Al-Ashouri, Eike Köhnen, Bor Li, Artiom Magomedov, Hannes Hempel, Pietro Caprioglio, José A. Márquez, Anna Belen Morales Vilches, Ernestas Kasparavicius, Joel A. Smith, Nga Phung, Dorothee Menzel, Max Grischek, Lukas Kegelmann, Dieter Skroblin, Christian Gollwitzer, Tadas Malinauskas, Marko Jost, Gasper Matic, Bernd Rech, Rutger Schlatmann, Marko Topic, Lars Korte, Antonio Abate, Bernd Stannowski, Dieter Neher, Martin Stolterfoht, Thomas Unold, Vytautas Getautis and Steve Albrecht \n\nScience 370 (6522), 1300-1309. DOI: 10.1126/science.abd4016 \n\n# Efficiency from hole-selective contacts \n\nPerovskite/silicon tandem solar cells must stabilize a perovskite material with a wide bandgap and also maintain efficient charge carrier transport. Al-Ashouri et al. stabilized a perovskite with a 1.68−electron volt bandgap with a self-assembled monolayer that acted as an efficient hole-selective contact that minimizes nonradiative carrier recombination. In air without encapsulation, a tandem silicon cell retained $95\\%$ of its initial power conversion efficiency of $29\\%$ after 300 hours of operation. \n\nScience, this issue p. 1300 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.aau1567", + "DOI": "10.1126/science.aau1567", + "DOI Link": "http://dx.doi.org/10.1126/science.aau1567", + "Relative Dir Path": "mds/10.1126_science.aau1567", + "Article Title": "A sustainable wood biorefinery for low-carbon footprint chemicals production", + "Authors": "Liao, YH; Koelewijn, SF; Van den Bossche, G; Van Aelst, J; Van den Bosch, S; Renders, T; Navare, K; Nicolai, T; Van Aelst, K; Maesen, M; Matsushima, H; Thevelein, JM; Van Acker, K; Lagrain, B; Verboekend, D; Sels, BF", + "Source Title": "SCIENCE", + "Abstract": "The profitability and sustainability of future biorefineries are dependent on efficient feedstock use. Therefore, it is essential to valorize lignin when using wood. We have developed an integrated biorefinery that converts 78 weight % (wt %) of birch into xylochemicals. Reductive catalytic fractionation of the wood produces a carbohydrate pulp amenable to bioethanol production and a lignin oil. After extraction of the lignin oil, the crude, unseparated mixture of phenolic monomers is catalytically funneled into 20 wt % of phenol and 9 wt % of propylene (on the basis of lignin weight) by gas-phase hydroprocessing and dealkylation; the residual phenolic oligomers (30 wt %) are used in printing ink as replacements for controversial para-nonylphenol. A techno-economic analysis predicts an economically competitive production process, and a life-cycle assessment estimates a lower carbon dioxide footprint relative to that of fossil-based production.", + "Times Cited, WoS Core": 745, + "Times Cited, All Databases": 772, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000522167400054", + "Markdown": "# A sustainable wood biorefinery for low–carbon footprint chemicals production \n\nYuhe Liao1\\*, Steven-Friso Koelewijn1, Gil Van den Bossche1, Joost Van Aelst1, Sander Van den Bosch1, Tom Renders1, Kranti Navare2, Thomas Nicolaï3, Korneel Van Aelst1, Maarten Maesen4, Hironori Matsushima4, Johan Thevelein3, Karel Van Acker2,5, Bert Lagrain1, Danny Verboekend1†, Bert F. Sels1\\* \n\n1Center for Sustainable Catalysis and Engineering, KU Leuven, Celestijnenlaan 200F, 3001 Heverlee, Belgium. 2Department of Materials Engineering, KU Leuven, Kasteelpark Arenberg 44, 3001 Leuven, Belgium. 3Laboratory of Molecular Cell Biology, KU Leuven, and Center for Microbiology, VIB, Kasteelpark Arenberg 31, 3001 Heverlee, Belgium. 4Lawter bvba, Ketenislaan 1C, Haven 1520, 9130 Kallo, Belgium. 5Center for Economics and Corporate Sustainability, KU Leuven, Warmoesberg 26, 1000 Brussels, Belgium. \n\n\\*Corresponding author. Email: bert.sels@kuleuven.be (B.F.S); yuhe.liao@kuleuven.be or yuhe.liao20@gmail.com (Y.L.) \n\n†Present address: Zeopore Technologies NV, Lelielaan 4, 3061 Bertem, Belgium. \n\nProfitability and sustainability of future biorefineries are dependent on efficient feedstock utilization. It is essential to valorize lignin when using wood. We have developed an integrated biorefinery that converts 78 wt. $\\%$ of birch into xylochemicals. Reductive catalytic fractionation of wood gives a carbohydrate pulp amenable to bioethanol production and a lignin oil. After extraction of lignin oil, the crude, unseparated mixture of phenolic monomers is catalytically funneled into 20 wt. $\\%$ of phenol and 9 wt. $\\%$ of propylene (on lignin basis) by gas-phase hydroprocessing/dealkylation, whereas the residual phenolic oligomers (30 wt. $\\%$ ) are used in printing ink as replacements for controversial para-nonylphenol. Techno-economic analysis predicts an economically competitive production, and life-cycle assessment estimates a lower $\\mathtt{C O}_{2}$ footprint relative to fossil-based production. \n\nPhotosynthetic carbon capture by plant biomass, as evidenced by the global tree cover potential of 4.4 billion hectares of canopy, is likely to be among the most effective strategies for climate change mitigation. $(I)$ With an average annual production of about 10 tons of dry biomass per hectare (2), such non-edible biomass represents an abundant feedstock of renewable carbon worldwide, and a prime candidate to sustainably produce fuels, chemicals and materials. (3, 4) Climate change mitigation through global forest restoration has the potential to capture more than 200 Gt of additional carbon at maturity, thereby reducing atmospheric carbon by about $25\\%$ . $(I)$ Together with exploitation of underutilized biomass, reforestation will increase future lignocellulose availability and offers great potential for an abundant and inexpensive supply of renewable carbon, provided that production and processing are sustainable. \n\nPetrochemicals are set to become the largest driver of global oil consumption in the future. $(5,6)$ A shift from fossil to renewable carbon resources can decouple chemical production from fossil resources and resulting $\\mathrm{CO_{2}}$ emissions. However, to be cost and environmentally competitive with fossil-based processes, it is imperative to maximize feedstock utilization. (7) There is thus a need for holistic biorefinery concepts that offer biomass valorization with low energy \n\nrequirements and high carbon (and mass) efficiency, providing existing and new markets with multiple products. The heterogeneous composition of lignocellulose, comprising entangled carbohydrate and lignin biopolymers, complicates its refining into value added products. Particularly, strategies that extract high value platform chemicals from lignin—a methoxylated phenylpropanoid biopolymer—are challenging due to its inherent recalcitrance and heterogeneity. (8–11) Functionalized aromatics, such as phenol, rather than hydrocarbons, are among the most suggested chemicals from lignin, but product yields on lignin weight basis are currently low (supplementary text ST1 and figs. S1 and S2). \n\nTo that end, we propose an integrated biorefinery that simultaneously produces phenol, propylene, and useful phenolic oligomers from in planta wood lignin, as well as a carbohydrate pulp amenable to bioethanol production (Fig. 1) to achieve a high carbon (and mass) efficiency. This work discloses the feedstock, process, and catalysis requirements (and challenges), and validates the techno-economic feasibility of producing (drop-in) chemicals (e.g., phenol and propylene) from lignin. We also demonstrate application and value proposition of the phenolic oligomers. \n\nThe first step of our approach rests on a specific type of lignin-first biorefining, termed reductive catalytic fractionation (RCF). (12–16) RCF of lignocellulose yields solid carbohydrate pulp and lignin oil by cleavage of ester and ether bonds as a result of tandem high-temperature solvolysis, hydrogenation, and hydrogenolysis either in batch or in (semi-)continuous mode over a metal catalyst in the presence of a reducing agent, such as hydrogen. The general consensus is that stabilization of the reactive intermediates formed by depolymerization of in planta lignin prevents formation of unreactive condensed lignin derivatives. (14) Near-complete delignification of hardwoods, such as birch and poplar, can be achieved without significant carbohydrate degradation. (16) Besides low molecular weight oligomers, the lignin oil contains few phenolic monomers in close-to-theoretical yields, viz. $50\\ \\mathrm{wt.\\%}$ for hardwoods. (16) However, maximal valorization of lignin oil into high value products, such as phenol, by technology that is profitable—but more importantly, sustainable—is key in demonstrating the potential of wood biorefineries. \n\nThe high yield of structurally similar phenolic monomers from conversion of wood lignin prompted us to design a process for their transformation toward phenol and propylene by catalytic funneling (fig. S4 and supplementary text ST2). A typical composition of phenolic monomers $\\mathit{50.5\\mathrm{wt.\\%}}$ on lignin basis, Fig. 2A and details in table S1) after RCF of birch wood in methanol over commercial $\\mathrm{Ru/C}$ includes 4-npropylguaiacol (PG; $19\\%$ ) and -syringol (PS; $67\\%$ ) as major components, with some others like 4-ethylguaiacol (EG) and –syringol. Pine wood gives 14 wt $\\%$ monomers yield due to low delignification/depolymerization efficiency. Although para-alkyl substituents are dominant in the monomers, considerably more polar groups, such as primary alcohols, remain in the oligomers (figs. S5 and S6, tables S2 and S3, and supplementary text ST3). This polarity difference facilitates isolation of distinct monomers through a simple extraction in $n$ -hexane under reflux (supplementary text ST4). This work demonstrates that a less than six-fold mass of $n$ -hexane to lignin oil allows cost-efficient extraction of more than 90 wt. $\\%$ of the lignin monomers (fig. S7). This procedure provides an optimum trade-off between extraction efficiency, solvent usage, and oligomers co-extraction. Additional (costly) separations toward individual phenolic monomers are not necessary because the crude monomeric extract can be catalytically funneled to the two products of interest, phenol and propylene. \n\nTo do so, the crude monomers mixture was first chemocatalytically hydroprocessed into $n$ -propylphenols (PPs) and ethylphenols (EPs). In contrast to previously reported approaches using (batch) liquid-phase and/or sulfided catalysts on pure compounds, (17–20) we pursued a solvent- and sulfur-free, continuous catalytic gas-phase hydroprocessing step. This procedure avoids product contamination as well as additional costs related to solvent loss and recovery. To establish the catalytic requirements for this selective hydroprocessing step, we initially studied commercially available PG, a representative monomer of the RCF lignin oil. The catalytic study explored several commercial metal catalysts (fig. S8). Non-noble metal Ni catalysts showed the highest PPs selectivity against other metals (figs. S8 and S9 and supplementary text ST5). Given the absence of a selectivity loss upon increased Ni content (Fig. 2, fig. S9B, and supplementary text ST5), highly loaded well-dispersed Ni catalysts are preferred because of their high catalytic activity (Fig. 2B). Acidic supports (e.g., silica-alumina) led to more undesirable (propyl)cresols (vide infra), whereas redox-active supports (e.g., anatase $\\mathrm{TiO_{2}}^{\\cdot}$ ) favor fully deoxygenated products such as $n$ - propylbenzene and $n$ -propylcyclohexane. Therefore, Ni is preferably supported on inert materials such as silica (fig. S8 and supplementary text ST5). After optimization, a $64\\ \\mathrm{wt.\\%}$ Ni on silica $\\mathrm{(Ni/SiO_{2})}$ ) catalyst reached $84\\%$ yield for PPs and EPs at a productivity of $4.5\\mathrm{kg\\cdotkg^{-1}\\cdot h^{-1}}$ (figs. S8 and S10 to S12 and supplementary text ST6). Side products include mainly $n$ -propylbenzene and propylcresols and minor others, such as cresols and $n$ -propylanisole (fig. S9). $\\mathrm{{Ni}/\\mathrm{{SiO_{2}}}}$ showed slight deactivation, but without loss of selectivity after 72 hours at $285^{\\circ}\\mathrm{C}$ (Fig. 2D). The catalytic performance can be restored by a reduction treatment (fig. S13). \n\nWe next investigated hydroprocessing of analytically pure representatives of the lignin oil monomers other than PG such as EG, isoeugenol, and PS (the most abundant monomer). For each compound, we observed high selectivity (75- $85\\%$ ) toward PPs and EPs at (near) complete conversion (Fig. 2E and fig. S14). Removal of both methoxy moieties in PS demanded longer contact time at higher temperature, achieving a selectivity for PPs and EPs of $77\\%$ at full conversion. This remarkable versatility in substrates is pivotal to the concept of funneling, and hence to the proposed lignin-to-phenol strategy, i.e., maximal conversion of different methoxylated alkylphenols to phenol (and propylene/ethylene). Kinetic studies showed that PG and 3-methoxyl-5- $n$ -propylphenol were the key intermediates of PS hydroprocessing (Fig. 2E and fig. S14D). Furthermore, a detailed study on the dominant reaction pathways revealed involvement of both demethoxylation and tandem demethylation-dehydroxylation pathways (figs. S15 to S18 and supplementary text ST7). \n\nWe ultimately moved to hydroprocessing of a crude unseparated mixture of monomers derived from RCF of pine and birch wood (Fig. 2E). At close-to-full conversion $(>90\\%)$ , the selectivity to PPs and EPs was similarly high for both crude monomer mixtures, yielding a quasi-identical products distribution compared to the reactions on pure compounds under the same conditions (Fig. 2E, fig. S19, and table S4). $\\mathrm{{Ni}/\\mathrm{{SiO_{2}}}}$ is thus robust to impurities (e.g., 4-methylsyringol) related to biomass feedstock. Gas chromatographic analysis showed that methoxy cleavage formed methane/ $\\mathrm{{H_{2}O}}$ and no $\\mathrm{CO/CO_{2}}$ (fig. S20). Analysis of the liquid condensate, obtained after condensing the gas-phase hydroprocessing products, confirmed the presence of mainly PPs and EPs, with minor side products such as (propyl)cresols and $n$ -propylbenzene in addition to water (table S4 and fig. S21). This crude liquid condensate is used directly in the next dealkylation step without intermediate separation or purification. \n\nWe previously reported stable continuous gas-phase dealkylation of analytically pure alkylphenols (i.e., 4-n-propyl- and 4-ethylphenol) to phenol and olefins over a commercial microporous ZSM-5 zeolite. (21) Co-feeding of water was crucial to maintain robust catalytic activity, (22) and hence the presence of water in the liquid alkylphenol condensate, formed during hydroprocessing, is beneficial. Given the higher complexity of the crude alkylphenol stream (e.g., impurities and bulkier molecules; table S4), it was anticipated that an identical commercial ZSM-5 would be inadequate due to site-access restriction and coke formation (fig. S22 and supplementary text ST8.1). To overcome these, we developed a tailor-made hierarchical ZSM-5 (Z140-H) catalyst with a balanced network of micro- and mesopores (figs. S22 and S24 and table S5). With this catalyst, we observed near-quantitative and selective dealkylation of the crude alkylphenol condensates, giving a combined yield for phenol and olefines of $82\\%$ at high temperature (Fig. 2, F and G, and figs. S25 and S26). We assessed the stability of Z140-H (deliberately at incomplete conversion) for biomass-derived crude alkylphenol streams (Fig. 2, F and G, and fig. S27). Side products were cresols, benzene, and trace amount of few others (figs. S28 and S29 and Fig. 2G). Cresols after separation can be selectively converted to phenol over USY (rather than ZSM-5) through bimolecular reactions (fig. S30 and supplementary text ST8.2). Investigation of the product formation routes revealed the involvement of carbenium chemistry, including isomerization, disproportionation, transalkylation and C-C cracking (fig. S31). Detailed kinetic studies (on 4-iPMP, PPs, EPs and $n$ -propylbenzene) demonstrated that zeolite hierarchization is indeed key in terms of activity and/or stability (figs. S32 to S35 and supplementary text ST8). Zeolite with large micropores, such as USY, although capable of converting sterically demanding alkylphenols, are lacking the (transition-state) pore confinement for shape-selective conversion. Confinement of the micropores such as in Z140-H is thus essential to achieve high selectivity. \n\nThis gas-phase technology thus enables the catalytic funneling of crude (unseparated) lignin monomer mixtures (extracted from the RCF lignin oil) into bio-phenol and biopropylene with 20 and $9\\mathrm{wt.\\%}$ yield on birch wood lignin basis, respectively (fig. S37). Use of lignin monomers of pine wood yields lower phenol and propylene amounts, 6.4 and 2.9 wt. $\\%$ respectively, due to a lower delignification/depolymerization efficiency of RCF with softwoods, and therefore, hardwoods, such as birch, are the preferred feedstock for producing phenol and propylene. The markets for these two (drop-in) xylochemicals are existing and well-established (fig. S1), and hence can be directly supplied with renewable substitutes. Currently, the largest share of phenol flows into bisphenol A (BPA) production. Nonetheless, anticipating a future post-BPA era, bio-phenol may be better employed for producing bio-aniline (via ammonolysis) and bio-caprolactam in existing facilities. Given the current uncertainty on final product purity, bio-propylene may be better suitable to produce chemicals, e.g., isopropanol (fig. S1). \n\nAs mentioned above, RCF of birch also produces a carbohydrate pulp $65\\mathrm{\\:wt.\\%}$ on wood basis composed of ${<}10\\ \\mathrm{wt.}\\%$ lignin, $60\\mathrm{wt.\\%}$ cellulose and 19 wt. $\\%$ hemicellulose) and phenolic oligomers $(30\\ \\mathrm{wt.\\%}\\$ on lignin basis). To ferment both glucose and xylose, the carbohydrate pulp was subjected to a semi-simultaneous saccharification-fermentation process, reaching a $40.2\\ \\mathrm{g\\L^{-1}}$ ethanol titer using an enzyme mixture for saccharification and an engineered yeast strain (MDS130) under non-optimized conditions (Fig. 3A and supplementary text ST9). Note that $\\mathrm{Ru/C}$ impurities (originating from the RCF unit) were tolerated during this biological conversion. Although we chose conversion of pulp into bioethanol for demonstration, other applications such as (news)paper, cardboard, (23) insulation materials, (24) and other chemicals (e.g., isosorbide, 2,5-furandicarboxylic acid, 1-butanol) are possible as well. \n\nA market for RCF phenolic oligomers (as obtained as a residue after extraction) does not currently exist. These oligomers have a high functionality content (3.46 mmol phenolic $\\mathrm{OH}\\mathrm{g}^{-1}.$ , $2.48\\mathrm{mmol}$ aliphatic $\\mathrm{OH}\\mathrm{g}^{-1},$ (fig. S6 and table S3), and lack the original phenolic inter-unit ether linkages (fig. S5 and table S2). To improve the overall profitability and sustainability of our proposed biorefinery, we investigated their potential to substitute fossil-based para-nonylphenol [a debated endocrine disruptor (25)] in lithographic printing ink. Ink production typically involves a three-step procedure: (i) resin formation from rosin, polyols, and (nonyl)phenols, (ii) varnish production by adding rape- and linseed oil, and (iii) coloration by admixing pigments (Fig. 3B and figs. S38 and S39). The intermediate resin made from RCF birch wood lignin oligomers did meet industrial specifications such as vacuum time and residue on filter (table S6, figs. S40 to S42, and supplementary text ST10). Next, the oligomer-based varnish formed a stable emulsion and showed similar water balance compared to para-nonylphenol-based as well as commercial resin-based ink-varnish (table S7, figs. S43 and S44, and supplementary text ST10). Finally, yellow-colored lithographic printing ink was made by admixing the renewable RCF oligomer-based varnish with pigments (Fig. 3B). RCF oligomers outperformed other lignin derivatives, such as methanosolv birch wood lignin and commercial acetosolv spruce wood lignin. Substitution of nonylphenol with acetosolv spruce wood lignin failed due to phase incompatibility and formation of observable black aggregates at the resin stage (supplementary text ST10). This case-study underlines the unexplored market potential of RCF phenolic oligomers in high-quality printing ink, in which they could serve as a renewable substitute for fossil-based nonylphenol. \n\nBased on the experimental data, we designed a process model to perform a techno-economic analysis (TEA; Fig. 1 and fig. S45). The process model integrates the three catalytic steps: (i) RCF of wood; (ii) hydroprocessing of crude monomers extract; and, (iii) dealkylation of crude alkylphenol product stream. In the first catalytic step, RCF of birch wood produces carbohydrate pulp and lignin oil, of which the latter is obtained by liquid/solid separation and solvent recuperation. From the lignin oil, monomers are readily isolated in a liquid $n$ -hexane extraction unit, followed by flash distillation to remove $n$ -hexane. The crude monomers extract and the RCF off-gas, containing $\\mathrm{H}_{2}$ and methane (originating from limited MeOH conversion in RCF), are fed to the second catalytic step. This gas-phase fixed-bed reactor contains the hydroprocessing catalyst $\\mathrm{(Ni/SiO_{2})}$ to yield alkylphenols. In the third catalytic step, this crude alkylphenol mixture, containing water, hydrogen and methane impurities, is fed without intermediate purification to the second fixed-bed reactor. This setup contains the dealkylation catalyst (Z140-H) to yield phenol and olefins. The presence of remaining hydrogen had no impact on the olefin formation (fig. S36). Next, product separation in a gas-liquid separator produces a liquid phenol stream and a gaseous mixture of water, olefins, $\\mathrm{{H_{2}}}$ and $\\mathrm{CH_{4}}$ . Finally, to obtain high purity phenol and propylene, impurities such as cresols and benzene (in the phenol fraction) and $\\mathrm{H_{2}/C H_{4}}$ (in the olefin fraction) can be removed by distillation. In this model, side streams related to sugar solubilization (during RCF), and benzene and cresols formation end up in a waste water stream. Methyl acetate, formed by methanolysis of the acetyl groups in (birch wood) hemicellulose, is largely separated in the methanol recovery distillation. Together with the excess $\\mathrm{H_{2}}$ , $\\mathrm{CH}_{4}$ , $\\mathrm{C_{2}H_{4}}$ , and small amounts of methanol (also from distillation), methyl acetate is incinerated/trigenerated to provide heating, cooling and electricity. Addition of external energy is not required to operate the integrated biorefinery. Overall, this process model design converts $1000~\\mathrm{kg}$ of birch wood into $653\\mathrm{kg}$ of raw carbohydrate pulp (for bioethanol), $64\\mathrm{kg}$ of lignin oligomers (for printing ink), $42\\ \\mathrm{kg}$ of phenol and $20~\\mathrm{kg}$ of propylene $(>99\\%)$ , which corresponds to a conversion of 78 wt. $\\%$ of the initial biomass into targeted products (figs. S46 and S47 and table S8). Possible solvent losses were studied, indicating a maximum loss of $1.4\\%$ of methanol due to (i) distillation, (ii) hydrogenolysis during RCF, and (iii) incorporation into chemicals (supplementary text ST11). \n\nThe TEA of our proposed biorefinery was calculated for an annual production of $\\mathbf{100~kt}$ of bio-phenol (i.e., average scale for fossil-based phenol production). Among the different process units, RCF and incineration/trigeneration are the highest contributors toward CAPEX due to the high cost of pressure reactors and energy integration, respectively (fig. S48 and supplementary text ST12). Investing in an incineration/trigeneration unit is however justified by its positive impact on the manufacture cost because of the significantly reduced energy costs. The highest contribution to the manufacturing cost is the feedstock (birch wood, 158 €·tonne−1, tables S9 and S10). Given the current pricing (table S9) of phenol (1300 €·tonne−1), propylene (830 €·tonne−1) and crude pulp (400 €·tonne−1), and using an estimate for the oligomers (1750 €·tonne−1, approaching that of nonylphenol), this resulted in an internal rate of return of $23\\%$ and a payout time of approximately four years for a plant with a lifetime of 20 years (table S11). A sensitivity study indicated that feedstock and product pricing have the largest economic impact (fig. S49 and supplementary ST12), while the influence of catalyst cost is negligible as long as the catalyst is sufficiently recyclable/reusable. In terms of RCF process parameters, shorter contact times and higher biomass concentrations are crucial factors to improve the profitability of this biorefinery, which implies the need to design a dedicated reactor. \n\nThe production of chemicals from biomass only makes sense if a lower $\\mathrm{CO_{2}}$ footprint is achieved. Thus, in addition to TEA, we performed a life-cycle assessment (LCA). Our proposed integrated birch wood biorefinery showed reduced global warming potentials (GWPs) for phenol $[0.736~\\mathrm{kg}$ $\\mathrm{CO_{2}}$ equivalent) and propylene $\\left(0.469\\mathrm{~kg~CO_{2}}\\right.$ equivalent) compared to their fossil-based counterparts $\\mathrm{1.73~kg}$ and $\\mathrm{1.47~kg}$ $\\mathrm{CO_{2}}$ equivalent, respectively; open and red symbols in Fig. 4, A and B, supplementary text ST13, and tables S12 to S14). Moreover, the GWP of the oligomers (proposed as substitute for para-nonylphenol with a GWP of $>\\mathbf{1.58\\kgCO_{2}}$ equivalent) and the carbohydrate pulp were calculated to be −0.949 and $-0.217\\mathrm{kg\\CO_{2}}$ equivalent, respectively (open symbols in Fig. 4, A and B). These negative values indicate a net consumption of $\\mathrm{CO_{2}}$ , i.e., a net carbon capturing effect for their production. Finally, to indicate opportunities for sustainability improvement, additional scenarios were analyzed, e.g., (i) the substitution of non-renewable $\\mathrm{H_{2}}$ , which has a high $\\mathrm{CO_{2}}$ contribution, by renewable $\\begin{array}{r}{\\mathrm{H}_{2},}\\end{array}$ , and (ii) inclusion of more sustainable forest management (Fig. 4 and fig. S52). Such integration scenarios unveil the possibility for $\\mathrm{CO_{2}}$ neutral wood biorefining with a total net consumption of $\\mathrm{CO_{2}}$ (i.e., negative GWP values) for each targeted product. \n\nBased on the proposed integrated biorefinery, respectively 78 and $76\\%$ of the initial mass and carbon content of birch wood can be economically and sustainably valorized into four high-value end-products, viz. phenol, propylene, oligomers and pulp (Fig. 4C and fig. S47). In our opinion, this process will constitute a clear incentive to make profitable, renewable, low-carbon footprint chemicals via the holistic biorefining of sustainable wood. \n\n# REFERENCES AND NOTES \n\n1. J.-F. Bastin, Y. Finegold, C. Garcia, D. Mollicone, M. Rezende, D. Routh, C. M. Zohner, T. W. Crowther, The global tree restoration potential. Science 365, 76–79 (2019). doi:10.1126/science.aax0848 Medline \n2. K. Van Meerbeek, B. Muys, M. Hermy, Lignocellulosic biomass for bioenergy beyond intensive cropland and forests. Renew. Sustain. Energy Rev. 102, 139–149 (2019). doi:10.1016/j.rser.2018.12.009 \n3. T. Werpy, G. Petersen, “Top value added chemicals from biomass: Volume I— Results of screening for potential candidates from sugars and synthesis gas” (National Renewable Energy Laboratory, 2004); www.osti.gov/biblio/15008859. \n4. J. E. Holladay, J. F. White, J. J. Bozell, D. Johnson, “Top value-added chemicals from biomass: Volume II—Results of screening for potential candidates from biorefinery lignin” (Pacific Northwest National Laboratory, 2007); www.osti.gov/biblio/921839. \n5. A. Kätelhön, R. Meys, S. Deutz, S. Suh, A. Bardow, Climate change mitigation potential of carbon capture and utilization in the chemical industry. Proc. Natl. Acad. Sci. U.S.A. 116, 11187–11194 (2019). doi:10.1073/pnas.1821029116 Medline \n6. International Energy Agency, “The future of petrochemicals: Towards a more sustainable chemical industry” (IEA Publications, France, 2018); www.connaissancedesenergies.org/sites/default/files/pdfactualites/the_future_of_petrochemicals.pdf). \n7. D. M. Alonso, S. H. Hakim, S. Zhou, W. Won, O. Hosseinaei, J. Tao, V. Garcia-Negron, A. H. Motagamwala, M. A. Mellmer, K. Huang, C. J. Houtman, N. Labbé, D. P. Harper, C. Maravelias, T. Runge, J. A. Dumesic, Increasing the revenue from lignocellulosic biomass: Maximizing feedstock utilization. Sci. Adv. 3, e1603301 (2017). doi:10.1126/sciadv.1603301 Medline \n8. A. J. Ragauskas, G. T. Beckham, M. J. Biddy, R. Chandra, F. Chen, M. F. Davis, B. H. Davison, R. A. Dixon, P. Gilna, M. Keller, P. Langan, A. K. Naskar, J. N. Saddler, T. J. Tschaplinski, G. A. Tuskan, C. E. Wyman, Lignin valorization: Improving lignin processing in the biorefinery. Science 344, 1246843 (2014). doi:10.1126/science.1246843 Medline \n9. C. Li, X. Zhao, A. Wang, G. W. Huber, T. Zhang, Catalytic transformation of lignin for the production of chemicals and fuels. Chem. Rev. 115, 11559–11624 (2015). doi:10.1021/acs.chemrev.5b00155 Medline \n10. Z. Sun, B. Fridrich, A. de Santi, S. Elangovan, K. Barta, Bright side of lignin depolymerization: Toward new platform chemicals. Chem. Rev. 118, 614–678 (2018). doi:10.1021/acs.chemrev.7b00588 Medline \n11. J. G. Linger, D. R. Vardon, M. T. Guarnieri, E. M. Karp, G. B. Hunsinger, M. A. Franden, C. W. Johnson, G. Chupka, T. J. Strathmann, P. T. Pienkos, G. T. Beckham, Lignin valorization through integrated biological funneling and chemical catalysis. Proc. Natl. Acad. Sci. U.S.A. 111, 12013–12018 (2014). doi:10.1073/pnas.1410657111 Medline \n12. I. Kumaniaev, E. Subbotina, J. Sävmarker, M. Larhed, M. V. Galkin, J. S. M. Samec, Lignin depolymerization to monophenolic compounds in a flow-through system. Green Chem. 19, 5767–5771 (2017). doi:10.1039/C7GC02731A \n13. E. M. Anderson, M. L. Stone, R. Katahira, M. Reed, G. T. Beckham, Y. RománLeshkov, Flowthrough reductive catalytic fractionation of biomass. Joule 1, 613– 622 (2017). doi:10.1016/j.joule.2017.10.004 \n14. W. Schutyser, T. Renders, S. Van den Bosch, S.-F. Koelewijn, G. T. Beckham, B. F. Sels, Chemicals from lignin: An interplay of lignocellulose fractionation, depolymerisation, and upgrading. Chem. Soc. Rev. 47, 852–908 (2018). doi:10.1039/C7CS00566K Medline \n15. Q. Song, F. Wang, J. Cai, Y. Wang, J. Zhang, W. Yu, J. Xu, Lignin depolymerization (LDP) in alcohol over nickel-based catalysts via a fragmentation–hydrogenolysis process. Energy Environ. Sci. 6, 994–1007 (2013). doi:10.1039/c2ee23741e \n16. S. Van den Bosch, W. Schutyser, R. Vanholme, T. Driessen, S.-F. Koelewijn, T. Renders, B. De Meester, W. Huijgen, W. Dehaen, C. Courtin, B. Lagrain, W. Boerjan, B. F. Sels, Reductive lignocellulose fractionation into soluble lignin-derived phenolic monomers and dimers and processable carbohydrate pulps. Energy Environ. Sci. 8, 1748–1763 (2015). doi:10.1039/C5EE00204D \n17. A. Vuori, J. B. Bredenberg, Hydrogenolysis and hydrocracking of the carbonAl2O3. Holzforschung 38, 253–262 (1984). doi:10.1515/hfsg.1984.38.5.253 \n18. N. Joshi, A. Lawal, Hydrodeoxygenation of 4-propylguaiacol (2-methoxy-4- propylphenol) in a microreactor: Performance and kinetic studies. Ind. Eng. Chem. Res. 52, 4049–4058 (2013). doi:10.1021/ie400037y \n19. H. L. Chum, D. K. Johnson, S. Black, M. Ratcliff, D. W. Goheen, in Advances in Solar Energy: An Annual Review of Research and Development, K. W. Böer, Ed. (Springer, 1988), pp. 91–200. \n20. X. Liu, C. Wang, Y. Zhang, Y. Qiao, Y. Pan, L. Ma, Selective Preparation of 4- Alkylphenol from Lignin-Derived Phenols and Raw Biomass over Magnetic CoFe@N-Doped Carbon Catalysts. ChemSusChem 12, 4791–4798 (2019). doi:10.1002/cssc.201901578 Medline \n21. D. Verboekend, Y. Liao, W. Schutyser, B. F. Sels, Alkylphenols to phenol and olefins by zeolite catalysis: A pathway to valorize raw and fossilized lignocellulose. Green Chem. 18, 297–306 (2016). doi:10.1039/C5GC01868D \n22. Y. Liao, R. Zhong, E. Makshina, M. d’Halluin, Y. van Limbergen, D. Verboekend, B. F. Sels, Propylphenol to phenol and propylene over acidic zeolites: Role of shape selectivity and presence of steam. ACS Catal. 8, 7861–7878 (2018). doi:10.1021/acscatal.8b01564 \n23. H. Sixta, Handbook of Pulp (Wiley, 2006). \n24. S. Schiavoni, F. D׳Alessandro, F. Bianchi, F. Asdrubali, Insulation materials for the building sector: A review and comparative analysis. Renew. Sustain. Energy Rev. 62, 988–1011 (2016). doi:10.1016/j.rser.2016.05.045 \n25. A. Soares, B. Guieysse, B. Jefferson, E. Cartmell, J. N. Lester, Nonylphenol in the environment: A critical review on occurrence, fate, toxicity and treatment in wastewaters. Environ. Int. 34, 1033–1049 (2008). doi:10.1016/j.envint.2008.01.004 Medline \n26. T. Renders, W. Schutyser, S. Van den Bosch, S. F. Koelewijn, T. Vangeel, C. M. Courtin, B. F. Sels, Influence of acidic $(H_{3}P O_{4})$ and alkaline (NaOH) additives on the catalytic reductive fractionation of lignocellulose. ACS Catal. 6, 2055–2066 (2016). doi:10.1021/acscatal.5b02906 \n27. C. W. Dence, in Methods in Lignin Chemistry, S. Y. Lin, C. W. Dence, Eds. (Springer, 1992), pp. 33–61. \n28. J. Snelders, E. Dornez, B. Benjelloun-Mlayah, W. J. J. Huijgen, P. J. de Wild, R. J. A. Gosselink, J. Gerritsma, C. M. Courtin, Biorefining of wheat straw using an acetic and formic acid based organosolv fractionation process. Bioresour. Technol. 156, 275–282 (2014). doi:10.1016/j.biortech.2014.01.069 Medline \n29. C. M. Courtin, H. Van den Broeck, J. A. Delcour, Determination of reducing end sugar residues in oligo- and polysaccharides by gas-liquid chromatography. J. Chromatogr. A 866, 97–104 (2000). doi:10.1016/S0021-9673(99)01064-X Medline \n30. C. Gourson, R. Benhaddou, R. Granet, P. Krausz, B. Verneuil, P. Branland, G. Chauvelon, J. F. Thibault, L. Saulnier, Valorization of maize bran to obtain biodegradable plastic films. J. Appl. Polym. Sci. 74, 3040–3045 (1999). doi:10.1002/(SICI)1097-4628(19991220)74:13<3040:AID-APP5>3.0.CO;2-M \n31. A. M. Silvestre-Albero, J. M. Juárez-Galán, J. Silvestre-Albero, F. RodríguezReinoso, Low-pressure hysteresis in adsorption: An artifact? J. Phys. Chem. C 116, 16652–16655 (2012). doi:10.1021/jp305358y \n32. C. A. Emeis, Determination of integrated molar extinction coefficients for infraredabsorption bands of pyridine adsorbed on solid acid catalysts. J. Catal. 141, 347– 354 (1993). doi:10.1006/jcat.1993.1145 \n33. L. A. Colón, L. J. Baird, in Modern Practice of Gas Chromatography, R. L. Grob, E. F. Barry, Eds. (Wiley, ed. 4, 2004), pp. 275–337. \n34. X. Meng, C. Crestini, H. Ben, N. Hao, Y. Pu, A. J. Ragauskas, D. S. Argyropoulos, Determination of hydroxyl groups in biorefinery resources via quantitative 31P NMR spectroscopy. Nat. Protoc. 14, 2627–2647 (2019). doi:10.1038/s41596-019- 0191-1 Medline \n35. P. Korntner, I. Sumerskii, M. Bacher, T. Rosenau, A. Potthast, Characterization of technical lignins by NMR spectroscopy: Optimization of functional group analysis by 31P NMR spectroscopy. Holzforschung 69, 807–814 (2015). doi:10.1515/hf2014-0281 \n36. W. Schutyser, S. Van den Bosch, J. Dijkmans, S. Turner, M. Meledina, G. Van Tendeloo, D. P. Debecker, B. F. Sels, Selective nickel-catalyzed conversion of model and lignin-derived phenolic compounds to cyclohexanone-based polymer building blocks. ChemSusChem 8, 1805–1818 (2015). \n37. N. Dowe, J. McMillan, “SSF experimental protocols: Lignocellulosic biomass hydrolysis and fermentation” (National Renewable Energy Laboratory, 2001); www.nrel.gov/docs/gen/fy08/42630.pdf. \n38. X. Ju, M. Bowden, M. Engelhard, X. Zhang, Investigating commercial cellulase performances toward specific biomass recalcitrance factors using reference substrates. Appl. Microbiol. Biotechnol. 98, 4409–4420 (2014). doi:10.1007/s00253-013-5450-4 Medline \n39. M. M. Demeke, H. Dietz, Y. Li, M. R. Foulquié-Moreno, S. Mutturi, S. Deprez, T. Den Abt, B. M. Bonini, G. Liden, F. Dumortier, A. Verplaetse, E. Boles, J. M. Thevelein, Development of a D-xylose fermenting and inhibitor tolerant industrial Saccharomyces cerevisiae strain with high performance in lignocellulose hydrolysates using metabolic and evolutionary engineering. Biotechnol. Biofuels 6, 89 (2013). doi:10.1186/1754-6834-6-89 Medline \n40. M. M. Demeke, F. Dumortier, Y. Li, T. Broeckx, M. R. Foulquié-Moreno, J. M. Thevelein, Combining inhibitor tolerance and D-xylose fermentation in industrial Saccharomyces cerevisiae for efficient lignocellulose-based bioethanol production. Biotechnol. Biofuels 6, 120 (2013). doi:10.1186/1754-6834-6-120 Medline \n41. Y.-B. Ha, M. Y. Jin, S.-S. Oh, D.-H. Ryu, Synthesis of an environmentally friendly phenol-free resin for printing ink. Bull. Korean Chem. Soc. 33, 3413–3416 (2012). doi:10.5012/bkcs.2012.33.10.3413 \n42. R. B. Bird, R. C. Armstrong, O. Hassager, Dynamics of Polymeric Liquids, Volume 1: Fluid Mechanics (Wiley, 1987). \n43. J. R. Couper, W. R. Penney, J. R. Fair, Chemical Process Equipment-Selection and Design (Revised 2nd Edition) (Gulf Professional Publishing, 2009). \n44. M. Weber, M. Weber, M. Kleine-Boymann, in Ullmann's Encyclopedia of Industrial Chemistry (Wiley, 2004), pp. 503–519. \n45. Ecoinvent version 3.3; https://www.ecoinvent.org/. \n46. ThinkStep Gabi professional database 2016; www.gabi-software.com. \n47. Phenol and Acetone CEFIC Petrochemicals Europe –Phenol and Acetone Sector Group September 2016; https://www.petrochemistry.eu/wpcontent/uploads/2018/01/EPD-Phenol-Acetone-10-16.pdf. \n48. P. Nuss, M. J. Eckelman, Life cycle assessment of metals: A scientific synthesis. PLOS ONE 9, e101298 (2014). doi:10.1371/journal.pone.0101298 Medline \n49. F. Zhu, J. A. Johnson, D. W. Ablin, G. A. Ernst, Efficient Petrochemical Processes: Technology, Design and Operation (Wiley, 2019). \n50. R. J. Schmidt, Industrial catalytic processes—phenol production. Appl. Catal. A. 280, 89–103 (2005). doi:10.1016/j.apcata.2004.08.030 \n51. R. Bal, M. Tada, T. Sasaki, Y. Iwasawa, Direct phenol synthesis by selective oxidation of benzene with molecular oxygen on an interstitial-N/Re cluster/zeolite catalyst. Angew. Chem. Int. Ed. 45, 448–452 (2006). doi:10.1002/anie.200502940 Medline \n52. C. O. Tuck, E. Pérez, I. T. Horváth, R. A. Sheldon, M. Poliakoff, Valorization of biomass: Deriving more value from waste. Science 337, 695–699 (2012). doi:10.1126/science.1218930 Medline \n53. R. Rinaldi, R. Jastrzebski, M. T. Clough, J. Ralph, M. Kennema, P. C. A. Bruijnincx, B. M. Weckhuysen, Paving the way for lignin valorisation: Recent advances in bioengineering, biorefining and catalysis. Angew. Chem. Int. Ed. 55, 8164–8215 (2016). doi:10.1002/anie.201510351 Medline \n54. G. J. Snell, D. T. Huibers, U.S. Patent US4409416A (1983). \n55. M. Wang, M. Liu, H. Li, Z. Zhao, X. Zhang, F. Wang, Dealkylation of lignin to phenol via oxidation-hydrogenation strategy. ACS Catal. 8, 6837–6843 (2018). doi:10.1021/acscatal.8b00886 \n56. G. J. Snell, D. T. Huibers, U.S. Patent US4420644A (1983). \n57. P. Ferrini, R. Rinaldi, Catalytic biorefining of plant biomass to non-pyrolytic lignin bio-oil and carbohydrates through hydrogen transfer reactions. Angew. Chem. Int. Ed. 53, 8634–8639 (2014). doi:10.1002/anie.201403747 Medline \n58. L. Shuai, M. T. Amiri, Y. M. Questell-Santiago, F. Héroguel, Y. Li, H. Kim, R. Meilan, C. Chapple, J. Ralph, J. S. Luterbacher, Formaldehyde stabilization facilitates lignin monomer production during biomass depolymerization. Science 354, 329– 333 (2016). doi:10.1126/science.aaf7810 Medline \n59. L. D. Eltis, R. Singh, in Lignin Valorization: Emerging Approaches, G. T. Beckham, Ed. (Royal Society of Chemistry, 2018), pp. 290–313. \n60. T. Nimmanwudipong, R. C. Runnebaum, D. E. Block, B. C. Gates, Catalytic conversion of guaiacol catalyzed by platinum supported on alumina: Reaction network including hydrodeoxygenation reactions. Energy Fuels 25, 3417–3427 (2011). doi:10.1021/ef200803d \n61. M. B. Griffin, F. G. Baddour, S. E. Habas, D. A. Ruddy, J. A. Schaidle, Evaluation of silica-supported metal and metal phosphide nanoparticle catalysts for the hydrodeoxygenation of guaiacol under ex situ catalytic fast pyrolysis conditions. Top. Catal. 59, 124–137 (2016). doi:10.1007/s11244-015-0512-8 \n62. M. Saidi, F. Samimi, D. Karimipourfard, T. Nimmanwudipong, B. C. Gates, M. R. Rahimpour, Upgrading of lignin-derived bio-oils by catalytic hydrodeoxygenation. Energy Environ. Sci. 7, 103–129 (2014). doi:10.1039/C3EE43081B \n63. W. Schutyser, G. Van den Bossche, A. Raaffels, S. Van den Bosch, S.-F. Koelewijn, T. Renders, B. F. Sels, Selective conversion of lignin-derivable 4-alkylguaiacols to 4-alkylcyclohexanols over noble and non-noble-metal catalysts. ACS Sustain. Chem. Eng. 4, 5336–5346 (2016). doi:10.1021/acssuschemeng.6b01580 \n64. G.-Y. Xu, J.-H. Guo, Y.-C. Qu, Y. Zhang, Y. Fu, Q.-X. Guo, Selective hydrodeoxygenation of lignin-derived phenols to alkyl cyclohexanols over a Rusolid base bifunctional catalyst. Green Chem. 18, 5510–5517 (2016). doi:10.1039/C6GC01097K \n65. Y. Nakagawa, M. Ishikawa, M. Tamura, K. Tomishige, Selective production of cyclohexanol and methanol from guaiacol over Ru catalyst combined with MgO. Green Chem. 16, 2197–2203 (2014). doi:10.1039/C3GC42322K \n66. L. Beránek, M. Kraus, Catalytic dealkylation of alkylaromatic compounds. XIV. The effect of structure of monoalkylbenzenes on their reactivity in hydrodealkylation on a nickel catalyst. Collect. Czech. Chem. Commun. 31, 566–575 (1966). doi:10.1135/cccc19660566 \n67. V. N. Bui, D. Laurenti, P. Afanasiev, C. Geantet, Hydrodeoxygenation of guaiacol with CoMo catalysts. Part I: Promoting effect of cobalt on HDO selectivity and activity. Appl. Catal. B 101, 239–245 (2011). doi:10.1016/j.apcatb.2010.10.025 \n68. V. N. Bui, D. Laurenti, P. Delichère, C. Geantet, Hydrodeoxygenation of guaiacol: Part II: Support effect for CoMoS catalysts on HDO activity and selectivity. Appl. Catal. B 101, 246–255 (2011). doi:10.1016/j.apcatb.2010.10.031 \n69. X. Zhang, Q. Zhang, T. Wang, L. Ma, Y. Yu, L. Chen, Hydrodeoxygenation of ligninderived phenolic compounds to hydrocarbons over $N i/{\\ S i O_{2}}–{Z r O_{2}}$ catalysts. Bioresour. Technol. 134, 73–80 (2013). doi:10.1016/j.biortech.2013.02.039 Medline \n70. J. Bredenberg, R. Ceylan, Hydrogenolysis and hydrocracking of the carbon-oxygen bond. 3. Thermolysis in tetralin of substituted anisoles. Fuel 62, 342–344 (1983). doi:10.1016/0016-2361(83)90093-5 \n71. A. Demirbaş, Mechanisms of liquefaction and pyrolysis reactions of biomass. Energy Convers. Manage. 41, 633–646 (2000). doi:10.1016/S0196- 8904(99)00130-2 \n72. R. N. Olcese, M. Bettahar, D. Petitjean, B. Malaman, F. Giovanella, A. Dufour, Gasphase hydrodeoxygenation of guaiacol over Fe/SiO2 catalyst. Appl. Catal. B 115– 116, 63–73 (2012). doi:10.1016/j.apcatb.2011.12.005 \n73. S. Song, J. Zhang, G. Gözaydın, N. Yan, Production of terephthalic acid from corn stover lignin. Angew. Chem. Int. Ed. 131, 4988–4991 (2019). doi:10.1002/ange.201814284 Medline \n74. L. Dong, Y. Xin, X. Liu, Y. Guo, C.-W. Pao, J.-L. Chen, Y. Wang, Selective hydrodeoxygenation of lignin oil to valuable phenolics over Au/Nb2O5 in water. Green Chem. 21, 3081–3090 (2019). doi:10.1039/C9GC00327D \n75. R. Srivastava, M. Choi, R. Ryoo, Mesoporous materials with zeolite framework: Remarkable effect of the hierarchical structure for retardation of catalyst deactivation. Chem. Commun. 2006 4489–4491 (2006). doi:10.1039/b612116k Medline \n76. F. Imbert, M. Guisnet, S. Gnep, Comparison of Cresol Transformation on USHY and HZSM-5. J. Catal. 195, 279–286 (2000). doi:10.1006/jcat.2000.2984 \n77. H. Fiege, in Ullmann's Encyclopedia of Industrial Chemistry (Wiley, 2000), pp. 419– 461. \n78. P. L. Spath, M. K. Mann, “Life cycle assessment of hydrogen production via natural gas steam reforming” (National Renewable Energy Laboratory, 2000); www.energy.gov/sites/prod/files/2014/03/f12/27637.pdf. \n79. E. Cetinkaya, I. Dincer, G. Naterer, Life cycle assessment of various hydrogen production methods. Int. J. Hydrogen Energy 37, 2071–2080 (2012). doi:10.1016/j.ijhydene.2011.10.064 \n80. J. Pérez-Ramírez, C. H. Christensen, K. Egeblad, C. H. Christensen, J. C. Groen, Hierarchical zeolites: Enhanced utilisation of microporous crystals in catalysis by advances in materials design. Chem. Soc. Rev. 37, 2530–2542 (2008). doi:10.1039/b809030k Medline \n81. The Mol-Instincts database; https://www.molinstincts.com. \n82. J. Kanai, J. A. Martens, P. A. Jacobs, On the nature of the active sites for ethylene hydrogenation in metal-free zeolites. J. Catal. 133, 527–543 (1992). doi:10.1016/0021-9517(92)90259-K \n\n# ACKNOWLEDGMENTS \n\nthank W. Vermandel for his assistance to produce lignin oil and R. Ooms and J. Maes for technical assistance during the catalytic testing. Funding: Y.L., G.V.d.B., D.V., J.V.A., and B.L. acknowledge funding from China Scholarship Council (201404910467), FISCH-ICON project MAIA (Flemish government), FWO (postdoc), Flanders Innovation & Entrepreneurship (postdoc), and the Industrial Research Fund KU Leuven (IOF fellow), respectively. S.-F.K. acknowledges FISCH-ARBOREF and BIOHArT (Interreg EU) funding from the Flemish government. K.V.Ae. acknowledges funding from FWO-SBO project Biowood. T.R. acknowledges KU Leuven internal research funds for a postdoctoral mandate (PDM). S.V.d.B acknowledges funding from KU Leuven internal research funds for a postdoctoral mandate (PDM), Flemish government for the FWO-SBO project Biowood, and Flanders Innovation & Entrepreneurship for an innovation mandate (postdoc). T.N. and J.T. acknowledge ARBOREF. Funding by BIOFACT (Excellence of Science, Federal government), supporting lignin conversion, is highly acknowledged. Competing interests: Y.L., B.F.S., J.V.A. and S.V.d.B. are inventors on patent application [attorney docket number 292-P15233US (ZL919134)] held/submitted by KU Leuven that covers lignocellulose refinery. Author contributions: Y.L. and B.F.S. conceived the idea and designed the experiments. Y.L. carried out the experimental work of the main catalysis research, while catalyst characterization and interpretation was assisted by D.V.; S.F.K. performed the liquid-liquid extraction separation work. G.V.d.B. and T.R. performed and interpreted the wood composition analysis and the processing experiments according to the lignin-first concept, and the preparation and analysis of a large batch of isolated lignin-first phenolic monomers; J.V.A., S.V.d.B. and B.L. composed and focused on the technoeconomic analysis with the kind assistance of Exyte. KN and K.V.Ac. performed the Life-cycle assessment; T.N. and J.T. performed the fermentation of the lignin-first carbohydrate pulp to bio-ethanol; K.V.Ae. conducted the characterization and analysis of phenolic oligomers. M.M. and H.M (both of Lawter) performed the production and characterization of the renewable resin and ink varnish. The text was initially composed by B.F.S., Y.L., S.F.K. and G.V.d.B., while all the authors further contributed to the discussion of the experimental work, and the final write-up of the manuscript. Data and materials availability: All data to support the conclusions of this manuscript are included in the main text or supplementary materials. \n\nSUPPLEMENTARY MATERIALS \nscience.sciencemag.org/cgi/content/full/science.aau1567/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S53 \nTables S1 to S14 \nReferences (26–82) \n\n21 May 2018; resubmitted 17 October 2019 \nAccepted 4 February 2020 \nPublished online 13 February 2020 \n10.1126/science.aau1567 \n\n![](images/19c34e2514dbc81a7ec6b981f408f277691ed7f494b11ec878f0ed364796c274.jpg) \nFig. 1. Proposed integrated biorefinery process for xylochemicals production from wood. Flow diagram of the chemical process to produce carbohydrate pulp, phenol, propylene, and phenolic oligomers from wood. \n\n![](images/79a581be3452d6cec7c12567b383d7b6cddbe96d0a44eff65e7d2b8106ea89b4.jpg) \nFig. 2. RCF of wood and catalytic funneling of lignin monomers to phenol and propylene. (A) RCF of (birch and pine) wood to lignin monomer, oligomers and carbohydrate pulp (details in supplementary materials); (B) Activity of selected supported nickel (Ni) catalysts for hydroprocessing of PG ( $285^{\\circ}\\mathrm{C}$ with low conversion $\\rvert<$ $20\\%$ , time-on-stream of 3 hours); (C) Selectivity to PPs versus PG conversion ( $285^{\\circ}\\mathrm{C}$ at different WHSV); (D) Evolution of conversion and products selectivity with time-on-stream over 64 wt. $\\%$ Ni/ $\\mathsf{S i O}_{2}$ for hydroprocessing of PG ( $285^{\\circ}\\mathrm{C}$ and 6.0 hours−1 WHSV); (E) Hydroprocessing of different lignin-derived phenolics (over 64 wt. $\\%$ $N i/\\mathsf{S i O}_{2}$ : EG, PG, isoeugenol and pine-derived monomers at $285^{\\circ}\\mathrm{C}$ and 8.2, 6.0, 4.4 and 6.0 hours−1 WHSV, respectively; PS(I), PS(II) and birch-derived monomers at $305^{\\circ}\\mathrm{C}$ and 7.1, 5.3 and 5.3 hours−1 WHSV, respectively). The data in (C) and (E) are taken at time-on-stream of 5 hours. Hydroprocessing constant reaction conditions: 1 bar of total pressure (0.4 bar $H_{2}$ partial pressure). Dealkylation of the hydroprocessing products from extracted (unseparated) monomer mixtures of (F) pine and (G) birch wood lignin oils at $410^{\\circ}\\mathrm{C}$ over Z140- H with time-on-stream at WHSV of 3.7 hours−1 and 2.8 hours−1, respectively. C-mol yield in (F) and (G) represents the carbon molar yield in the product stream. The theoretical yield $(84.7\\%)$ in (G) is the maximum combined yield of phenol and olefins based on the substrate composition (table S4). \n\n![](images/90498a805d1ee5958917b22df79db43a6c0d376026f4238ff7fbeb9cf581c0bb.jpg) \nFig. 3. Valorization of RCF birch wood carbohydrate pulp and phenolic oligomers. (A) Semi-simultaneous saccharification-fermentation of carbohydrate pulp (containing Ru/C catalyst) obtained after RCF of birch wood; (B) Step-wise synthesis of ink from RCF birch wood lignin oligomers, details in supplementary materials. \n\n![](images/d62860a0c915433ef004cb2123e999c945bea4477a0ada097963b61f3b159903.jpg) \nFig. 4. LCA and carbon flow for the proposed integrated biorefinery based on birch wood. (A and B) GWP of phenol, propylene, phenolic oligomers and carbohydrate pulp in this birch wood biorefinery with different scenarios (i.e. several hydrogen sources and/or forest management strategies). The GWP of ${\\sf H}_{2}$ is, respectively, 11.89 kg $\\mathsf{C O}_{2}$ equivalent, $8.20\\mathrm{~kg~CO}_{2}$ equivalent, and $0.97\\mathrm{~kg~CO}_{2}$ equivalent for non-renewable ${\\sf H}_{2}$ I, nonrenewable ${\\sf H}_{2}$ II, and renewable ${\\sf H}_{2}$ III (see supplementary materials). The GWP of phenolic oligomers from oil refinery is GWP of nonylphenol $(>1.58\\mathsf{k g}\\mathsf{C O}_{2}$ equivalent); (C) Carbon flow of this birch wood biorefinery. \n\n# Science \n\n# A sustainable wood biorefinery for low−carbon footprint chemicals production \n\nYuhe Liao, Steven-Friso Koelewijn, Gil Van den Bossche, Joost Van Aelst, Sander Van den Bosch, Tom Renders, Kranti Navare, Thomas Nicolaï, Korneel Van Aelst, Maarten Maesen, Hironori Matsushima, Johan Thevelein, Karel Van Acker, Bert Lagrain, Danny Verboekend and Bert F. Sels \n\npublished online February 13, 2020 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 61 articles, 7 of which you can access for free http://science.sciencemag.org/content/early/2020/02/12/science.aau1567#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1021_acs.chemmater.0c00359", + "DOI": "10.1021/acs.chemmater.0c00359", + "DOI Link": "http://dx.doi.org/10.1021/acs.chemmater.0c00359", + "Relative Dir Path": "mds/10.1021_acs.chemmater.0c00359", + "Article Title": "Raman Spectroscopy Analysis of the Structure and Surface Chemistry of Ti3C2Tx MXene", + "Authors": "Sarycheva, A; Gogotsi, Y", + "Source Title": "CHEMISTRY OF MATERIALS", + "Abstract": "Raman spectroscopy is one of the most useful tools for the analysis of two-dimensional (2D) materials. While MXenes are a very large family of 2D transition metal carbides and nitrides, there have been just a few Raman studies of materials from this family. Here, we report on a systematic study of the most widely used and most important MXene to date: Ti3C2Tx. By synthesizing material using different methods, we show that Raman spectra of Ti3C2Tx are affected not only by the composition and surface groups but also by intercalated species and stacking. Due to a plasmonic peak of Ti3C2Tx around 785 nm, resonullt conditions are achieved, enabling us to observe an extra peak at similar to 120 cm(-1), when excited with a red diode laser. We report differences in Raman spectra collected from single flakes of Ti3C2Tx colloidal solutions, and multilayer films. Lastly, we show how an undesirable photoluminescent background could serve as evidence of material degradation, which leads to the formation of defective titania and amorphous carbon. This study shows how Raman spectroscopy can be used for the characterization of important emerging 2D materials: MXenes.", + "Times Cited, WoS Core": 965, + "Times Cited, All Databases": 992, + "Publication Year": 2020, + "Research Areas": "Chemistry; Materials Science", + "UT (Unique WOS ID)": "WOS:000529878600017", + "Markdown": "# Raman Spectroscopy Analysis of the Structure and Surface Chemistry of $\\bar{\\Pi}_{3}\\bar{\\mathsf{C}}_{2}\\bar{\\mathsf{I}}_{x}$ MXene \n\nAsia Sarycheva and Yury Gogotsi\\* \n\nCite This: Chem. Mater. 2020, 32, 3480−3488 \n\n![](images/4469aa3bac63c342124cbf9e74e3d4aa6374e9df83fbed63900c0b6c529d66fd.jpg) \n\n# Read Online \n\n# ACCESS \n\n山 Metrics & More \n\nArticle Recommendations \n\nSupporting Information \n\nABSTRACT: Raman spectroscopy is one of the most useful tools for the analysis of twodimensional (2D) materials. While MXenes are a very large family of 2D transition metal carbides and nitrides, there have been just a few Raman studies of materials from this family. Here, we report on a systematic study of the most widely used and most important MXene to date: ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}.$ By synthesizing material using different methods, we show that Raman spectra of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ are affected not only by the composition and surface groups but also by intercalated species and stacking. Due to a plasmonic peak of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ around $785\\ \\mathrm{nm},$ resonant conditions are achieved, enabling us to observe an extra peak at ${\\sim}120~\\mathrm{cm^{-1}}$ , when excited with a red diode laser. We report differences in Raman spectra collected from single flakes of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{\\boldsymbol{x}{\\prime}}$ colloidal solutions, and multilayer films. Lastly, we show how an undesirable photoluminescent background could serve as evidence of material degradation, which leads to the formation of defective titania and amorphous carbon. This study shows how Raman spectroscopy can be used for the characterization of important emerging 2D materials: MXenes. \n\n![](images/fd53456fa47e3f9223dea124098340e2e5caedb2b9cd387daf9cb2469fccf2d5.jpg) \n\nM any different classes of two-dimensional (2D) material1s This fast, noninvasive, and sensitive method is able to record spectra even from single flakes of many 2D materials.2 Probably the best example is graphene, which has distinctive Raman features at around 1355 (D peak) and $1600~\\mathrm{{cm}^{-1}}$ (G peak), when a green laser is used, as well as a 2D peak at higher wavenumbers.3 −6 Also, a low-frequency mode C (shearing mode) was observed at $42~\\mathrm{cm^{-1}}$ and originated from the interlayer coupling, being sensitive to the number of graphene layers, like the 2D band.7 Raman spectroscopy stud on twisted bilayer graphene found the dependence of the G peak on the twisting angle.8 Raman spectroscopy was also used as a tool to look at effects beyond phonons, e.g., to observe electron− phonon and electron−electron interactions by applying a magnetic field.9 \n\nSimilar concepts were applied to the family of transition metal dichalcogenides (TMDs).10 Compared with graphene, the Raman spectrum of TMDs strongly depends on the excitation wavelength due to the existing band gap.11 When the excitation wavelength matches the band gap of the material, the resonant condition is observed, which can provide information about the electronic states of the material.12 One should note that an existing band gap is not the only criterion for resonant Raman observations. Other electronic transitions (interband transitions, plasmonic transitions, charge transfer) can yield resonance conditions once matched with the excitation wavelength.13,14 Nearly all known 2D materials were studied by Raman spectroscopy and the information obtained greatly impacted the understanding of not only the phonon structure and composition of the materials but also the mechanical,15 thermal,16 and electronic17,18 properties. This makes Raman spectroscopy an important characterization tool for new 2D materials, like MXenes. \n\nMXenes are a large family of 2D transitional metal carbides and nitrides that were discovered at Drexel University in 2011.19 MXenes are usually obtained by selective etching of parent MAX phases, where M is an early transition metal, A is an element of the A group, mostly group 13 or 14 of the periodic table (in particular, Al, Si, and Ga), and X stands for carbon and/or nitrogen. When immersed in fluoride solutions, the A element is etched away, leaving 2D sheets of transition metal carbides, nitrides, or carbonitrides.20 Since the synthesis occurs in aqueous media, MXenes acquire surface functional groups that make them hydrophilic: $\\scriptstyle=0$ $-\\mathrm{OH},$ , or $-\\mathrm{F}$ (if the etching is done in hydrofluoric acid, HF). Both, precursor synthesis and etching conditions, affect the MXene composition and, therefore, properties.20,21 For example, simulations show that different surface terminations of MXene can shift the Fermi level, as well as open or alter the band gap of the material.22 Properties are affected by intercalated species as well.23,24 Also, it was shown on $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ that flake size can affect the optical properties and conductivity.25 \n\nX-ray diffraction (XRD), which is commonly used for determining the crystal structure as well as the $d$ spacing of MXene films and powders, is not applicable to deposited single flakes or dispersions of single flakes.20,21 Energy-dispersive Xray spectroscopy (EDX) and X-ray photoelectron spectroscopy (XPS) have been used for elemental analysis of MXenes in vacuum. In contrast, Raman spectroscopy, which measures phonons (lattice vibrations), can provide information about bonding in the MXene structure. Raman spectroscopy detects molecular fingerprints and is sensitive to amorphous compounds as well as traces of transition metal oxides, which are often present in the structure of MXenes. However, the vibrational properties of MXenes have not received sufficient attention. \n\n![](images/9a71b0d71755c75cf2914db623796ee5fcfcb8b1d0b9ac5cf9ad432a2570d134.jpg) \n\n$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ monolayer lattice dynamic properties, including phonon dispersion, partial phonon density of states, and infrared- and Raman-active vibrations, have been predicted.26 Lattice vibrations are affected by surface groups $\\mathrm{T}_{\\boldsymbol{x}},$ as shown in the work of Hu et al.27 In addition, there were studies utilizing those calculations for peak assignment and monitoring changes during in situ electrochemical testing. Hu et al. showed how the peaks assigned to $\\scriptstyle=0$ , $-(\\mathrm{OH})_{\\cdot}$ , and $-\\mathrm{O}(\\mathrm{OH})$ groups change during electrochemical cycling.28,29 They showed, based on experimental data, that the computational model of the MXene structure should consider mixed terminations of O and OH. It is also known that plasmonic properties affect the Raman spectrum of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}.$ A resonance peak of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ emerges at $120~\\mathrm{{cm}^{-1}}$ when the laser wavelength is coupled with the plasmon resonance.30 Lioi et al. showed that the Raman spectrum of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ films is affected by the synthesis method, which suggests that Raman spectroscopy could be a tool for monitoring MXene quality as a function of the synthesis conditions. Lastly, a Raman spectrum has been collected from a 6-nm-thick MXene film, but no single-layer MXene spectra have been reported.30 \n\nIn this study, we utilized multiwavelength Raman spectroscopy to study $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ and determine the effects of the synthesis method, state of the material (single flakes, colloidal solution, stacked flakes), and intercalated species on Raman spectra. To avoid the local heterogeneity effects and produce statistically reliable results, we collected and averaged 100 spectra from different locations on each sample. The observed spectral differences indicate that even a slight variation in synthesis affects the vibrational properties of MXene flakes. A study combining atomic force microscopy (AFM) and Raman spectroscopy was conducted simultaneously to correlate the number of layers in a flake with the Raman peak position. Lastly, we used Raman spectroscopy as a tool to determine early signs of oxidation and sample degradation that are difficult to detect by other methods. This study emphasizes the versatility of Raman spectroscopy for MXene analysis as well as stresses the importance of selecting the right conditions to obtain informative Raman spectra and avoid artifacts. \n\n# RESULTS AND DISCUSSION \n\nWe have chosen $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ for this study as the most important MXene for many applications reported in more than 1000 articles.31−36 There are plenty of methods for the synthesis and delamination of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}^{^{\\bullet}}{}^{20,2\\dot{1},24,37,38}$ which result in variations in surface chemistry, interlayer spacing, flake size, and a number of defects. To vary these factors, we synthesized $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ via a LiF/HCl method, where HF is formed in situ by mixing LiF and HCl, via a mixed-acid method, where HF and HCl were mixed, and by etching in aqueous HF solutions of various concentrations: 5, 10, 20, and $30\\%$ , as described in the Experimental section and schematically presented in Figure 1a. \n\n![](images/3df8360ba6a9f706dba8579547c5be7ca1830a6c667ae2533c57d7070edf9ba1.jpg) \nFigure 1. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ synthesis and Raman peak assignment. (a) Schematic of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ synthesis and delamination procedures utilized in this study and schematics of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ at different stages of processing, including etching, intercalation, and delamination. (b) Deconvoluted Raman spectrum obtained from a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film synthesized by $_\\mathrm{HF-HCl}$ etching and excited with the $785~\\mathrm{nm}$ laser. The spectrum is divided into 3 regions: the flake region, which corresponds to a group vibration of carbon, two titanium layers, and surface groups, the $\\mathrm{T}_{x}$ region, which represents vibrations of the surface groups, and the carbon region, where both in-plane and outof-plane vibrations of carbon atoms are located. \n\nThe chemical top-down approach enabled the extraction of the material in different forms and concentrations based on the needs of this study: multilayer powder with no intercalants, claylike material with intercalants (e.g., ${\\mathrm{Li}^{+}}$ and water),24,39 single flakes on a $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate, colloidal suspension of delaminated flakes, as well as a vacuum-filtered film of delaminated material. \n\nBefore starting to analyze the complex and broad spectra of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}},$ one should look at theoretical studies of its vibrational properties , which help to navigate through the multiple Raman bands . Knowing that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ belongs to the point group $\\mathrm{D}_{3\\mathrm{d}}$ and keeping in mind that this is a unit cell, not a molecule, vibrations are described (in Mulliken symbols) as $4\\mathrm{E}_{\\mathrm{g}}+2\\mathrm{A}_{\\mathrm{lg}}+4\\mathrm{E}_{\\mathrm{u}}+2\\mathrm{A}_{2\\mathrm{u}}.$ Among these vibrations, $\\mathbf{E}_{\\mathrm{g}}$ and $\\mathbf{A}_{\\mathrm{lg}}$ correspond to Raman-active modes, whereas $\\mathbf{E}_{\\mathrm{u}}$ and $\\bar{\\bf A_{2u}}$ are IRactive. It is worth mentioning that $\\mathbf{E_{g}}$ and $\\mathbf{E}_{\\mathrm{u}}$ are doubly degenerate modes; therefore, they appear as one in irreducible representation. This corresponds to four active Raman modes: $\\mathrm{E_{g},}$ an in-plane vibration of Ti and C atoms, and $\\mathbf{A}_{\\mathrm{{lg}}},$ an out-ofplane vibration of Ti and C atoms. Two others correspond to in-plane and out-of-plane vibrations of C atoms. When the surface groups $(-\\mathrm{O},\\mathrm{-F})$ are added, the number of atoms in the unit cell increases; therefore, the number of vibrations increases accordingly. However, it is important to note that the unit cell with surface terminations becomes distorted and, therefore, the assignment to the $\\mathrm{D}_{3\\mathrm{d}}$ group is not accurate. Different surface terminations, intercalated, and adsorbed species may affect the lattice vibrations. Unit cell distortion and distribution of surface groups result in peak shifting and broadening. For example, Wang et al. refer to the lattice as “pseudo-P63/mmc”.40 \n\n![](images/160338f88752bc888fa944df9ea0bd54d5da8cc41470f25d9f9b19f76bcf55a1.jpg) \nFigure 2. Raman spectra from different states of MXene. (a) Versatility of Raman spectroscopy: all samples presented in the photo represent different states of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ analyzed with the Raman microscope. (b) Raman spectra of a multilayer powder, clay prepared by LiF−HCl etching, a single flake on a $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate, a colloidal suspension in water, and delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ films prepared by HF−HCl etching. For all samples, except for the single flake on the $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate, a $785\\mathrm{nm}$ laser was utilized. In the case of the single flake, we used a $633~\\mathrm{{nm}}$ laser. A strong peak of Si at $521~\\mathrm{{cm}^{-\\tilde{1}}}$ originates from the $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate. Sharp peaks observed in the case of liquid samples are attributed to a setup used in the study. Further information is available in Figure S2. \n\nBased on theoretical studies and our experimental data, we present a full peak assignment for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ . A Raman spectrum of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ has multiple features in the $100{-}800~\\mathrm{cm}^{-1}$ range. The presented spectrum is noticeably different from the precursor MAX phase $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (Figure S1). The $\\mathrm{A_{lg}(T i,\\ A l)}$ , also referred to as the $\\omega_{4}$ vibration of the MAX phase,41 is shifted toward lower wavenumbers. Instead of Al, now, this vibration also involves C and surface groups. The full width at half-maximum (FWHM) of the peak changes from $16~\\mathrm{{cm}^{-1}}$ (MAX phase) to $9c m^{-1}$ (MXene). Another out-of-plane vibration, $\\omega_{6},$ shifts toward higher wavenumbers, from 660 to $720~\\mathrm{cm}^{-1}$ . Peak broadening from 15 to $22~\\mathrm{cm}^{-1}$ occurs in the case of MXene. \n\nThe MXene Raman spectrum can be separated into several regions, as shown in Figure 1b. First comes the resonant peak,27 which is observed when the $785\\mathrm{nm}$ laser is used, and it is coupled with the plasmonic peak. Next is the flake region consisting of $\\mathrm{E_{g}(T i,C,O)}$ and $\\mathrm{A_{1g}(T i,C,O)}$ modes, which are in-plane and out-of-plane vibrations of titanium atoms in the outer layer as well as carbon and surface groups, respectively. It represents vibrations of the flake as group vibrations of Ti, C, and surface groups. This vibration is the stiffest and includes the maximum number of atoms from the MXene unit cell. Further, the region $230{-}470~\\mathrm{cm}^{-1}$ represents in-plane $\\mathrm{(E_{g})}$ vibrations of surface groups attached to titanium atoms. This region is solely affected by surface atoms; therefore, it potentially could be utilized to probe the surface chemistry of MXenes and its changes as a result of chemical or electrochemical reactions. The region between 580 and 730 $\\mathsf{c m}^{-1}$ is assigned mostly to carbon vibrations (both $\\mathbf{E_{\\mathrm{g}}}$ and $\\mathbf{A}_{\\mathrm{lg}})$ . The latter region has been used for fingerprinting of surface groups in various in situ electrochemical studies.42 \n\nRaman spectroscopy allows material analysis at each stage of synthesis and processing, including colloidal solutions. The variety of samples that were analyzed with a Raman microscope is presented in Figure 2a. Figure 2b shows the spectra of a multilayer powder, claylike material, a delaminated film, a single flake on a $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate, and a colloidal solution. All of the products were obtained using the HF−HCl etching of ${\\mathrm{Ti}_{3}}{\\mathrm{AlC}_{2}},$ with the exception of “clay” (MXene slurry having liquid crystalline properties), for which the LiF−HCl etching was utilized. \n\nFigure 2b shows the differences in Raman spectra recorded from different samples. Apart from the resonant peak, there are two distinct sharp peaks: $\\mathrm{A_{lg}(T i,O,C)}$ around $200~\\mathrm{{cm}^{-1}}$ and $\\mathrm{A_{lg}(C)}$ around $720~\\mathrm{cm}^{-1}$ . As one can notice, the $\\mathbf{A}_{\\mathrm{lg}}(\\mathbf{C})$ exhibits the biggest shift compared with the other peaks. The lowest wavenumber of this peak $'711~\\mathrm{cm}^{-1}$ for multilayer powder after HF-etching and ${\\bar{7}}19\\ {\\mathrm{cm}}^{-1}$ for HF-HCl etching) is observed in the multilayer form, where the vibrations are restricted due to the small interlayer spacing and stacking.38 \n\nOnce the intercalant is introduced, more water is forced between the layers, expanding the interlayer spacing. The presence of water also stiffens out-of-plane vibrations. The interlayer spacing becomes larger, which shifts the $\\mathrm{A_{lg}(C)}$ peak to ${\\sim}720~\\mathrm{cm^{-1}}$ . Interestingly enough, the same shift as that in the multilayer form is observed for a filtered and dried in a desiccator film. This can be explained by the presence of less water in the dried film, which stiffens out-of-plane vibrations as well as prevents sliding of flakes relative to each other. It is important to note that even though an intercalant is present in the filtered film, the vibration exhibits a similar frequency. On the other hand, in the case of single flakes deposited on the $\\mathrm{{\\calS}i}/^{}$ $\\mathrm{SiO}_{2}$ substrate, out-of-plane vibrations are restricted by the substrate on one side only, leading to an asymmetric peak, covering the range from 720 to $73\\bar{6}~\\mathrm{cm^{-1}}$ . One should note, though, that the spectra were collected using different laser exitations. However, as discussed further, no shifts are observed when the laser is changed. The peak shifts to higher wavenumbers $(726~\\mathrm{cm}^{-1})$ in the case of MXene flakes dispersed in water, where both sides of the flake are surrounded by $\\mathrm{H}_{2}\\mathrm{O}$ molecules. This is because there are fewer restrictions in liquid media and flakes can move freely. A similar peak at $725~\\mathrm{{\\bar{cm}}^{-1}}$ is observed in a claylike MXene, which is similar to solution: flakes are surrounded by $\\mathrm{H}_{2}\\mathrm{O}$ molecules where motion is less restricted than that in the dried restacked film. Therefore, a few monolayers of water enable unrestricted vibrations, similar to a colloidal solution. This observation is an indication that this peak is not only related to surface groups but to the flake-to-flake interaction. \n\nThe ratio of $\\mathrm{A_{lg}(C)/A_{l g}(T i,C,O)}$ peaks varies as well and it is most pronounced in the multilayer form when it is equal to 1.1. This is explained by the stacking of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\ensuremath{\\boldsymbol{x}}}$ flakes in a similar manner as in the parent MAX phase. Once the flakes are delaminated and restacked, the ratio increases to 1.2, meaning that the coupling between flakes is weakened due to the random orientation of flakes relative to each other. The ordering of M and X layers is decreased after etching compared with the parent MAX phase; therefore, the $\\bar{\\mathrm{A_{1g}(T i,C,O)}}$ vibration of the flake as a whole is weakened. Interestingly, the $\\mathbf{A}_{\\mathrm{lg}}(\\mathbf{C})$ peak exhibits a high intensity in both cases, indicating that vibrations of the carbon layer are not dependent on the flake orientation. The opposite effect is observed in the case of a single flake on the $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate. The ratio of $\\mathrm{\\bfA_{\\mathrm{lg}}(C)/}$ $\\mathrm{A_{1g}(T i,C,O)}$ is 0.9, meaning that $\\mathbf{A}_{1\\mathrm{g}}(\\mathrm{Ti},\\mathbf{C},\\mathbf{O})$ is higher in intensity since this is the vibration of the flake as a whole, similar to TMDs.43 In the case of the aqueous dispersion, the $\\mathbf{A}_{1\\mathrm{g}}(\\mathrm{Ti},\\mathbf{C},\\mathbf{O})$ peak has almost vanished due to the random orientation of the flakes in space and continuous movement. \n\n![](images/05087c9006e0468b2fd2d6d496d91963c0648338afe28ecb715a8a70104feafe.jpg) \nFigure 3. Effect of etching solutions and intercalants on vibrational modes of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}.$ . For each deconvoluted spectrum presented, a matrix of 100 spectra was recorded and averaged. Deconvolution was performed in WiRE 3.0 software using the Voigt function. (a) Raman spectra of multilayer and clay MXenes. (b) Effect of HF concentration on Raman spectra of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}.$ (c) Effect of different synthesis methods on delaminated vacuumassisted filtered films. For the delamination procedure, Li ions were intercalated in the case of $_\\mathrm{HF-HCl}$ and LiF−HCl etching, while TMAOH was used in the case of HF etching. (d) Raman spectrum of $100\\ \\mathrm{nm}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ flakes (HF−HCl etching) filtered into a film. \n\nOne should notice that the surface group region (230−470 $\\mathsf{c m}^{-1},$ ) is more pronounced in the case of delaminated flakes that are restacked in a filtered film, as well as in single flakes deposited on the $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate. In the case of water, this can be explained by decreased coupling between the flakes, which affects the out-of-plane peaks, strengthening the surface group vibrations. In the monolayer flake case, this region is more pronounced because there is no flake coupling that weakens the $\\mathbf{A}_{\\mathrm{lg}}$ peak. The random orientation of flakes within the plane of the delaminated film broadens the peaks of surface functional groups. \n\nRaman spectroscopy can also be utilized as a tool to monitor surface groups. Since surface chemistry depends on the etching method, as described in Figure 1a, a systematic study of the effect of the composition of the etching solution, particularly the HF concentration, on the Raman spectra of a MXene film was conducted (Figure 3). \n\nThe resonant excitation wavelength for all $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\vphantom{\\mathrm{T}}x}$ tested was $785\\ \\mathrm{nm}$ . To avoid the effect of roughness, spectra from delaminated restacked films were collected by mapping a $10\\times$ $10\\ \\mu\\mathrm m$ region, averaging a total of 100 spectra. The data on statistical analysis with standard deviations are presented in the Supporting Information (Table S1). Fitting procedure is discussed in the Experimental section. The main features of the spectra are presented in Figure 3. Figure 3a shows a comparison of multilayer samples produced by three etching methods. It is important to note that in the case of the in situ HF method, the multilayer sample was obtained by drying the clay material. In this case, ${\\mathrm{Ti}_{3}}{\\mathrm{C}_{2}}{\\mathrm{T}_{\\d x}}$ has intercalated Li ions; however, it was not delaminated. The spectra of intercalated clay and multilayer powder obtained by the $_\\mathrm{HF-HCl}$ method look similar. Both spectra have an increased intensity of the OH component of surface groups as well as similar positions of the $\\mathrm{A_{lg}(C)}$ peak. In contrast, the O component of the HFetched multilayer material is dominant in the spectrum, and the $\\mathrm{A_{lg}(C)}$ peak is shifted to $711~\\mathrm{{cm}^{-1}}$ . Adding HCl decreases $\\mathrm{\\ttpH}$ and results in a protonated surface. \n\nHowever, once the TMAOH intercalant is introduced after HF etching, the $\\mathbf{A}_{\\mathrm{lg}}(\\mathbf{C})$ peak position of the delaminated film shifts to $730~\\mathrm{cm^{-1}}$ . Such a dramatic shift can be explained by an increased interlayer spacing caused by the large intercalant molecules. Depending on the HF concentration, the $\\mathrm{A_{lg}(C)}$ peak downshifts with increasing HF concentration, as can be seen in Figure 3b. The ratio of $\\mathrm{\\DeltaA_{lg}(T i,\\Delta C,\\Delta T_{\\it x})/A_{l g}(C)}$ decreases with increasing HF concentration. A sharper and stronger $\\mathrm{A_{1g}(T i,C,T_{\\it x})}$ peak suggests a lower concentration of defects as well as a reduction of flake rotation relative to each other. \n\n![](images/feeeb89f491f47a790d472638102bc80a3a441e1f1c72de49d2e8d776b0024cc.jpg) \nFigure 4. Effect of excitation wavelength on Raman spectra. (a) Raman spectra of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ film obtained with 785, 633, and $514~\\mathrm{nm}$ lasers and a $20\\times$ objective, normalized to laser power. (b) Raman spectra of a $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film obtained with 785, 633, and $514~\\mathrm{nm}$ lasers and a $63\\times$ objective, normalized by laser power. (c) Raman spectra of a thin $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film on a $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate normalized by laser power. (d) Raman spectra from a single-layer ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ flake ( $1.6\\ \\mathrm{nm}$ thick), and two-layer ( $2.8~\\mathrm{nm}$ thick) and four-layer ( $5.2\\mathrm{nm}$ thick) flakes. (e) AFM image showing profiles of the analyzed substrate. One should note that there is always a layer of adsorbed water molecules under each flake. \n\nThe comparison of different etching methods was done by comparing a delaminated restacked film obtained by etching in HF, HF/HCl, and LiF/HCl (Figure 3c). Interestingly, the resonance peak shifts only in the case of $_\\mathrm{HF-HCl}$ etching. Resonant Raman peaks are correlated with the vibronic properties of the material and a change in the electronic properties of MXene may affect its resonant spectrum. This could explain the observed peak shift. It is known that different methods of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ synthesis lead to different electronic properties as a result of altering the surface chemistry and concentration of defects.20,22 \n\nThe $\\mathbf{A}_{1\\mathrm{g}}(\\mathrm{Ti},\\mathbf{C},\\mathbf{O})$ and $\\mathrm{A_{lg}(C)}$ peaks shift similarly in the case of HF/HCl and LiF/HCl etching. The main difference between Raman spectra from those films, besides the resonant peak shift, is in a shift of the $\\mathbf{A}_{\\mathrm{lg}}(\\mathbf{C})$ peak. In fact, as can be seen from Figure 2d, the difference is very similar to the one between LiF/HCl-etched clay and delaminated MXene. This indicates that there are significant differences between the samples produced by LiF/HCl and HF/HCl methods. The $\\mathrm{A_{1g}(T i,\\bar{C},O)}$ is higher in intensity in both, clay and delaminated states, which can be explained by no registry between the flakes in these samples. \n\nThere are many other factors that may affect Raman spectra. For example, Maleski et al.25 showed that the size of the flakes affects conductivity and light absorption. In this study, we prepared films using both, large as-prepared flakes and probesonicated small flakes. The resonance peak shifted to higher wavenumbers $\\left(123~\\mathrm{cm}^{-1}\\right)$ ) in the case of probe-sonicated flakes. The shift of both $\\mathrm{\\mathbf{A}_{l g}(C)}$ and $\\mathrm{A_{lg}(T i,\\bar{C},O)}$ peaks to lower wavenumbers in the case of the probe-sonicated film can be attributed to a greatly increased ratio of flake edges to the basal planes and, therefore, an increased concentration of defects. The difference can also be observed in the surface group region, around 366 and $506~\\mathrm{{cm}^{-1}}$ . This region is more pronounced in the case of small flakes. However, further studies need to be conducted to determine the correlation between the Raman shift and the concentration of defects. \n\nExcitation wavelength was also found to affect the spectra (Figure $\\scriptstyle4\\ a-c\\ )$ . With increasing wavelength, the peak that corresponds to $\\mathrm{E_{g}(T i,\\ C,\\ O)}$ appears and the ratio between out-of-plane vibrations of Ti, C, O, and carbon changes. Also, our preliminary data show that Raman spectroscopy, as described above, can be used as a tool for determining the number of layers on a substrate (Figure 4d,e). \n\nImportantly, it was observed that the peak around $120~\\mathrm{{cm}^{-1}}$ has a resonant nature. According to the work of El-Demellawi et al., $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ exhibits an interband transition at $1.6~\\mathrm{eV}_{;}$ , which translates to ${\\sim}785~\\mathrm{nm}$ .45 As a result of this transition, a broad peak appears in the UV−vis spectrum of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ at this wavelength.44 The resonance Raman effect occurs when the laser wavelength matches (red diode laser) or is somewhat shorter than the transition wavelength. For example, the 633 nm laser provides conditions for resonance; however, the peak is much lower in intensity. Similar effects were observed for $\\mathrm{Mo}S_{2},$ where resonant conditions were achieved with more than one laser.11 Figure $_{4\\mathsf{a}-\\mathsf{c}}$ also shows how the choice of the microscope objective matters for the Raman studies. Figure 4ac shows higher counts normalized by power for the $785~\\mathrm{nm}$ laser. This can be explained by the resonant conditions as well as the larger penetration depth of the light with a longer wavelength (larger volume analyzed). Also, the $\\mathrm{A_{lg}(C)}$ peak has a higher intensity when the $20\\times$ objective is used due to a larger spot size. This peak is primarily associated with carbon; therefore, the coupling of those vibrations stays the same throughout the whole film. On another note, the spectrum normalized by the power of the laser for a single flake shows that the $633~\\mathrm{{\\nm}}$ laser gives the most intense spectrum; however, the resonant peak is observed when the $785~\\mathrm{nm}$ laser is used. Here, the penetration depth of the MXene is always the same, as the flake has a constant thickness and only the volume of the underlying $\\mathrm{SiO}_{2}/\\mathrm{Si}$ that undergoes Raman scattering varies with the laser wavelength. The intensity of the $633~\\mathrm{nm}$ spectrum is the highest, as it is closer to the resonant line, but is in the visible range, which is preferable for the lens used. The $785~\\mathrm{nm}$ laser is weakened by the lens; however, the loss of intensity is compensated by the penetration depth in the case of spectra from the film. These findings show that both the laser and the lens determine the volume of the material sampled. For comparison, Figure S3 shows spectra collected from the $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX phase used as a precursor for MXene synthesis. One can notice that no resonance conditions are observed, unlike in the case of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}^{\\bullet}}$ Also, the MAX phase spectra have a low signal to noise ratio. One can explain this by the metallic nature of the MAX phase. More information about Raman spectroscopy of MAX phases can be found in the work of Presser et al.41 \n\n![](images/9378e7f09c61c72b3e9a21b87f1ab7e2a71db161a5ee537855406ecd8dae13b4.jpg) \nFigure 5. Degradation of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film detected with Raman spectroscopy. (a) Raman scattering and photoluminescence spectra obtained from three different spots of an anodically oxidized40 $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ film and plotted on the same scale. (b) Raman spectra of MXene oxidized as a result of the high laser power used. All spectra were collected with a $514~\\mathrm{nm}$ laser after $30~\\mathsf{s}$ of exposure to $100\\%$ power of 514, 633, and $785~\\mathrm{nm}$ lasers. (c) Photographs of spots on the film surface produced by laser irradiation and used for collecting spectra after laser ablation. Numbers show the laser power in mW. \n\nWe have also been able to detect spectra from single flakes of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ deposited on the $\\mathrm{Si}/\\mathrm{SiO}_{2}$ substrate (Figure 4d). With increasing number of flakes in a stack, the overall intensity increases. Noticeably, the relative intensity of $\\mathrm{E_{g}}$ inplane peaks increases as well. Interestingly, no significant peak shift was observed, unlike in the case of TMD.43 This may be explained by the broad shape of MXene peaks and the overall quality of the spectra. \n\noxide is usually amorphous and is not detectable by XRD. However, as is known from the literature,47 highly defective $\\mathrm{TiO}_{2}$ exhibits photoluminescence (PL). Raman spectra collected with different lasers and plotted in the nanometer range (Figure 5a) show a photoluminescence background. The PL peak at around $630~\\mathrm{{\\nm}}$ suggests the presence of a photoluminescent oxide. However, spectra collected from the edge of the region or from another region exhibit less photoluminescence. When a high-power laser was used, the film degraded and the formation of rutile, anatase, and free carbons was observed. Interestingly, the degree of oxidative damage depends not only on laser power but also on the wavelength used. The spectra in Figure 5b show the formation of anatase in the case of ablation with both 514 and $633~\\mathrm{nm}$ lasers at a power of $2.37\\mathrm{mW}.$ . However, one can notice that the spectrum after $633\\ \\mathrm{nm}$ laser irradiation is noisier and the $\\bar{\\mathbf{A}_{\\mathrm{lg}}}(\\mathbf{C})$ peak is shifted. The shorter wavelength results in a higher power that facilitates the transformation of MXene to anatase and then to rutile, indicating rise in temperature under the focused laser beam. These factors are important to consider when one analyzes MXene samples. \n\n# CONCLUSIONS \n\nAs users of Raman spectrometers know, photoluminescence (PL) as well as material degradation induced by the laser complicate recording of high-quality Raman spectra. However, they may also help to understand the material behavior. Figure 5a shows a spectrum of partially oxidized $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene produced as described in Tang et al.46 The initially formed \n\nRaman spectroscopy is able to provide information on the surface chemistry, stacking, and quality of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ Vibrations of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ consist of $\\mathbf{E_{\\mathrm{g}}}$ (in-plane) and $\\mathbf{A}_{\\mathrm{lg}}$ (out-of-plane) peaks, where the latter are sharper and stronger. Because of the plasmon resonance at ${\\sim}785~\\mathrm{\\nm}$ , Raman scattering at this wavelength is stronger; therefore, the use of this laser results in a cleaner spectrum. Moreover, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ exhibits a resonant Raman peak at around $120~\\mathrm{{cm}^{-1}}$ when the $785~\\mathrm{nm}$ solid-state laser is used. The whole spectrum of ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ in the wavenumber range of $100{-}8\\bar{0}0~\\mathrm{cm}^{-1}$ can be divided into four regions: the resonant peak, $\\mathbf{A}_{\\mathrm{lg}}$ out-of-plane vibrations of Ti, $\\mathrm{c},$ and O, the surface group vibrations region, and carbon vibrations region. These Raman features change depending on the synthesis method and the environment surrounding the MXene flakes. The most prominent changes occur with out-ofplane peaks, which are affected by both surface functional groups and the flake stacking. We have also shown that the choice of the laser excitation wavelength and the objective is important. The relative intensities of the peaks change with the excitation wavelength because the penetration depth and the spot size of the laser change. The compatibility of the Raman microscope optics at the desired wavelength should be considered as well. Lastly, we have shown how photoluminescence can be used to detect the amorphous and defective titanium oxides, providing an insight into sample oxidation. \n\n# MATERIALS \n\nThe materials used in this study were synthesized by selective etching of Al layers from $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . One gram of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ powder $<44~\\mu\\mathrm{m}$ particle size) was gradually added to the solution of a mixture of hydrochloric acid, HCl, and hydrofluoric acid, HF (Millipore-Sigma), or hydrofluoric acid and water, or a mixture of lithium fluoride and hydrochloric acid (in situ HF formation) as described elsewhere.20,31 The mixture was kept in an ice bath for $10~\\mathrm{min}$ and, afterward, was stirred for $24\\mathrm{~h~}$ at $35~^{\\circ}\\mathrm{C}$ . After etching, the mixture was washed five times by centrifugation in two $150~\\mathrm{mL}$ plastic centrifuge tubes at 3500 rpm for $2~\\mathrm{min}$ until the $\\mathsf{p H}$ of the supernatant reached $_{6-7}$ . In the case of in situ HF formation, the washing continued to the point of delamination. In the case of ${\\mathrm{HF/HCl}},$ the sediment was added to a cold $20\\%$ by weight solution of lithium chloride (LiCl) in water. The mixture was dispersed by manual shaking, stirred in an ice bath for 10 min, and then stirred at $25~^{\\circ}\\mathrm{C}$ overnight. After that, the MXene was washed three times until the supernatant became dark, which is an indication of the beginning of delamination. The unreacted MAX was separated by centrifugation at $3500~\\mathrm{rpm}$ for $1\\mathrm{min}$ and collected. After vacuum-assisted filtration of solutions, free-standing films were made. The thickness of MXene films ranged between 5 and $15\\ \\mu\\mathrm{m}$ . \n\nRaman Spectrometer. We used an inverted reflection mode Renishaw InVia (Gloucestershire, U.K.) instrument equipped with 20 $\\mathbf{\\nabla}\\times\\left(\\mathrm{NA}=0.4\\right)$ , $63\\times\\left(\\mathrm{NA}=0.7\\right)$ , $55\\times\\left(\\mathrm{NA}=0.45\\right)$ , and $100\\times\\mathrm{(NA=}$ 1.3) objectives and a diffraction-based room-temperature CCD spectrometer. These objectives were used for sample imaging as well. For the $_\\mathrm{He-Ne}$ $(633\\ \\mathrm{nm})$ and the diode $(785\\ \\mathrm{nm})$ lasers, we used a $1200~\\mathrm{line/mm}$ diffraction grating, and for the $\\mathbf{A}\\mathbf{r}^{+}$ laser (488 and ${514}~\\mathrm{nm}$ emissions), an $1800~\\mathrm{line/mm}$ grating. The power of the lasers was kept in the ${\\sim}0.5{-}1~\\mathrm{\\mW}$ range. The mapping was performed by raster scanning in the StreamLine mode at various $x\\cdot$ - axis steps. Inspectral range is limited by the grating. In the case of a 1200 line/mm grating, the number of wavenumbers per scan is around $400~\\mathrm{{cm}^{-\\mathrm{{i}}}}$ , therefore in order to scan the $100~\\mathrm{{\\dot{cm}^{-1}-800}}$ $\\mathsf{c m}^{-1}$ we performed the scan twice and stiched it manually. For measurements in solution, we used a quartz glass tube capillary with an inner diameter of $0.5\\mathrm{\\mm}$ . Fitting was performed in WiRE 3 software by substracting a linear baseline and fitting each spectrum with the Voight function. Since mapping results contain 2 spectral ranges, there were 2 baselines. \n\n# ASSOCIATED CONTENT \n\n# $\\bullet$ Supporting Information \n\nThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.chemmater.0c00359. \n\nComparison of Raman spectra of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and etched $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (Figure S1); spectrum of deionized water (Figure S2); spectra of MAX phase $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (Figure S3); peak deconvolution information (Table S1) (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Author \n\nYury Gogotsi − A. J. Drexel Nanomaterials Institute, and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19104, United States; $\\circledcirc$ orcid.org/0000-0001-9423-4032; Email: gogotsi@ drexel.edu \n\n# Author \n\nAsia Sarycheva − A. J. Drexel Nanomaterials Institute, and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19104, United States; orcid.org/0000-0002-5151-8980 \n\nComplete contact information is available at: https://pubs.acs.org/10.1021/acs.chemmater.0c00359 \n\nNotes The authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThe authors are thankful to Tyler Mathis for providing the MAX phase material, Mohamed Alhabeb and Dr. Kathleen Maleski for assisting with material synthesis, Dr. Mikhail Shekhirev for assisting with AFM imaging, and Eliot Precetti for editing the manuscript. This work was supported through the Fluid Interface Reactions, Structures, and Transport (FIRST) Center, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, and Office of Basic Energy Sciences. \n\n# REFERENCES \n\n(1) Gwénaël, G.; Colomban, P. Raman Spectroscopy of Nanomaterials: How Spectra Relate to Disorder, Particle Size and Mechanical Properties. Prog. Cryst. Growth Charact. Mater. 2006, 53, 1−56. (2) Paillet, M.; Parret, ${\\mathrm{R}},$ Sauvajol, J.-L.; Colomban, P. Graphene and Related 2D Materials: An Overview of the Raman Studies. J. Raman Spectrosc. 2018, 49, 8−12. \n(3) Tuinstra, F.; Koenig, J. L. Raman Spectrum of Graphite. J. Chem. Phys. 1970, 53, 1126−1130. \n(4) Ferrari, A. C.; Basko, D. M. Raman Spectroscopy as a Versatile Tool for Studying the Properties of Graphene. Nat. Nanotechnol. 2013, 8, 235−246. \n(5) Gogotsi, Y.; Libera, J. A.; Kalashnikov, N.; Yoshimura, M. Graphite Polyhedral Crystals. Science 2000, 290, 317−320. \n(6) Ferrari, A. C.; Meyer, J. C.; Scardaci, V.; Casiraghi, C.; Lazzeri, M.; Mauri, F.; Piscanec, S.; Jiang, S.; Novoselov, K. S.; Roth, S.; Geim, A. K. Raman Spectrum of Graphene and Graphene Layers. Phys. Rev. Lett. 2006, 97, No. 187401. \n(7) Tan, P. H.; Han, W. P.; Zhao, W. J.; Wu, A. H.; Chang, K.; Wang, H.; Wang, Y. F.; Bonini, N.; Marzari, N.; Pugno, N.; Savini, G. The Shear Mode of Multilayer Graphene. Nat. Mater. 2012, 11, 249− 300. \n(8) Havener, R. W.; Zhuang, H.; Brown, L.; Hennig, R. G.; Park, J. Angle-Resolved Raman Imaging of Interlayer Rotations and Interactions in Twisted Bilayer Graphene. Nano Lett. 2012, 12, 3162−3167. \n(9) Faugeras, C.; Orlita, M.; Potemski, M. Raman Scattering of Graphene-Based Systems in High Magnetic Fields. J. Raman Spectrosc. 2018, 49, 146−156. (10) Pimenta, M. A.; Del Corro, E.; Carvalho, B. R.; Fantini, C.; Malard, L. M. Comparative Study of Raman Spectroscopy in Graphene and $\\mathbf{MoS}_{2}$ -Type Transition Metal Dichalcogenides. Acc. Chem. Res. 2015, 48, 41−47. \n(11) Placidi, M.; Dimitrievska, M.; Izquierdo-Roca, V.; Fontané, X.; Castellanos-Gomez, A.; Pérez-Tomás, A.; Mestres, N.; EspindolaRodriguez, M.; López-Marino, S.; Neuschitzer, M.; Bermudez, V.; Yaremko, A.; Pérez-Rodríguez, A. Multiwavelength Excitation Raman Scattering Analysis of Bulk and Two-Dimensional $\\mathbf{MoS}_{2}$ : Vibrational Properties of Atomically Thin $\\mathbf{MoS}_{2}$ Layers. 2D Mater. 2015, 2, No. 035006. \n(12) Del Corro, E.; Terrones, H.; Elias, A.; Fantini, C.; Feng, S.; Nguyen, M. A.; Mallouk, T. E.; Terrones, M.; Pimenta, M. A. Excited Excitonic States in ${1\\mathrm{L}},2\\mathrm{L},3\\mathrm{L},$ and Bulk ${\\mathrm{WSe}}_{2}$ Observed by Resonant Raman Spectroscopy. ACS Nano 2014, 8, 9629−9635. \n(13) Arora, A. K.; Rajalakshmi, M. Resonance Raman Scattering from $\\mathrm{Cd}_{\\mathrm{l-x}}\\mathrm{Zn}_{\\mathrm{x}}S$ Nanoparticles Dispersed in Oxide Glass. J. Appl. Phys. 2000, 88, 5653−5657. \n(14) Richter, E.; Subbaswamy, K. R. Theory of Size-Dependent Resonance Raman Scattering from Carbon Nanotubes. Phys. Rev. Lett. 1997, 79, 2738−2741. \n(15) Mu, M.; Osswald, S.; Gogotsi, Y.; Winey, K. I. An in Situ Raman Spectroscopy Study of Stress Transfer between Carbon Nanotubes and Polymer. Nanotechnology 2009, 20, No. 335703. (16) Malekpour, H.; Balandin, A. A. Raman-Based Technique for Measuring Thermal Conductivity of Graphene and Related Materials. J. Raman Spectrosc. 2018, 49, 106−120. \n(17) Goli, P.; Khan, J.; Wickramaratne, D.; Lake, R. K.; Balandin, A. A. Charge Density Waves in Exfoliated Films of van Der Waals Materials: Evolution of Raman Spectrum in $\\mathrm{TiSe}_{2}$ . Nano Lett. 2012, 12, 5941−5945. \n(18) Ling, X.; Huang, S.; Hasdeo, E. H.; Liang, L.; Parkin, W. M.; Tatsumi, Y.; Nugraha, A. R.; Puretzky, A. A.; Das, P. M.; Sumpter, B. G.; Geohegan, D. B.; Kong, J.; Saito, R.; Drndic, M.; Meunier, V.; Dresselhaus, M. S. Anisotropic Electron-Photon and Electron-Phonon Interactions in Black Phosphorus. Nano Lett. 2016, 16, 2260−2267. (19) Naguib, M.; Kurtoglu, M.; Presser, V.; Lu, J.; Niu, J.; Heon, M.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Nanocrystals Produced by Exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 2011, 23, 4248−4253. \n(20) Alhabeb, M.; Maleski, K.; Anasori, B.; Lelyukh, P.; Clark, L.; Sin, S.; Gogotsi, Y. Guidelines for Synthesis and Processing of 2D Titanium Carbide $\\mathrm{\\Ti}_{3}\\mathrm C_{2}\\mathrm T_{\\mathrm{x}}$ MXene). Chem. Mater. 2017, 29, 7633. (21) Verger, L.; Xu, C.; Natu, V.; Cheng, H.-M.; Ren, W.; Barsoum, M. W. Overview of the Synthesis of MXenes and Other Ultrathin 2D Transition Metal Carbides and Nitrides. Curr. Opin. Solid State Mater. Sci. 2019, 23, 149−163. \n(22) Tang, $\\mathrm{Q.;}$ Zhou, Z.; Shen, P. Are MXenes Promising Anode Materials for Li Ion Batteries? Computational Studies on Electronic Properties and Li Storage Capability of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{X}_{2}$ $\\mathrm{\\langleX=F,}$ OH) Monolayer. J. Am. Chem. Soc. 2012, 134, 16909−16916. (23) Hart, J. L.; Hantanasirisakul, K.; Lang, A. ${\\mathrm{C.}}{\\mathrm{\\Omega}}$ Anasori, B.; Pinto, D.; Pivak, Y.; van Omme, J. T.; May, S. J.; Gogotsi, Y.; Taheri, M. L. Control of MXenes’ Electronic Properties through Termination and Intercalation. Nat. Commun. 2019, 10, No. 522. \n(24) Ghidiu, M.; Lukatskaya, M. R.; Zhao, M. $\\mathrm{Q.;}$ Gogotsi, Y.; Barsoum, M. W. Conductive Two-Dimensional Titanium Carbide “Clay” with High Volumetric Capacitance. Nature 2014, 516, 78− U171. \n(25) Maleski, K.; Ren, C. E.; Zhao, M.- $\\mathrm{Q.;}$ Anasori, B.; Gogotsi, Y. Size-Dependent Physical and Electrochemical Properties of TwoDimensional MXene Flakes. ACS Appl. Mater. Interfaces 2018, 10, 24491−24498. \n(26) Hu, T.; Wang, J.; Zhang, H.; Li, Z.; Hu, M.; Wang, X. Vibrational Properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{2}$ $\\mathrm{~T~}=\\mathrm{~O~}$ , F, OH) Monosheets by First-Principles Calculations: A Comparative Study. Phys. Chem. Chem. Phys. 2015, 17, 9997−10003. \n(27) Hu, T.; Hu, M.; Gao, B.; Li, W.; Wang, X. Screening Surface Structure of MXenes by High-Throughput Computation and Vibrational Spectroscopic Confirmation. J. Phys. Chem. C 2018, 122, 18501−18509. \n(28) Hu, M.; Li, Z.; Hu, T.; Zhu, S.; Zhang, C.; Wang, X. HighCapacitance Mechanism for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene by in Situ Electrochemical Raman Spectroscopy Investigation. ACS Nano 2016, 10, 11344−11350. \n(29) Hu, M.; Hu, T.; Li, Z.; Yang, Y.; Cheng, R.; Yang, J.; Cui, C.; Wang, X. Surface Functional Groups and Interlayer Water Determine the Electrochemical Capacitance of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene. ACS Nano 2018, 12, 3578−3586. \n(30) Lioi, D. B.; Neher, G.; Heckler, J. E.; Back, T.; Mehmood, F.; Nepal, D.; Pachter, ${\\mathrm{R}}.{\\mathrm{}}{\\mathrm{}}$ Vaia, R.; Kennedy, W. J. Electron-Withdrawing Effect of Native Terminal Groups on the Lattice Structure of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXenes Studied by Resonance Raman Scattering: Implications for Embedding MXenes in Electronic Composites. ACS Appl. Nano Mater. 2019, 2, 6087−6091. \n(31) Sarycheva, A.; Polemi, A.; Liu, Y.; Dandekar, K.; Anasori, B.; Gogotsi, Y. 2D Titanium Carbide (MXene) for Wireless Communication. Sci. Adv. 2018, 4, No. eaau0920. \n(32) Kim, S. J.; Koh, H. J.; Ren, C. E.; Kwon, O.; Maleski, K.; Cho, S. Y.; Anasori, B.; Kim, C. K.; Choi, Y. K.; Kim, J.; Gogotsi, Y.; Jung, H. T. Metallic $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene Gas Sensors with Ultrahigh Signal-toNoise Ratio. ACS Nano 2018, 12, 986−993. \n(33) Driscoll, N.; Richardson, A. G.; Maleski, K.; Anasori, B.; Adewole, O.; Lelyukh, P.; Escobedo, L.; Cullen, D. K.; Lucas, T. H.; Gogotsi, Y.; Vitale, F. Two-Dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene for HighResolution Neural Interfaces. ACS Nano 2018, 12, 10419−10429. (34) Shahzad, F.; Alhabeb, M.; Hatter, C. B.; Anasori, B.; Hong, S. M.; Koo, C. M.; Gogotsi, Y. Electromagnetic Interference Shielding with 2D Transition Metal Carbides (MXenes). Science 2017, 353, 1137−1140. \n(35) Li, R.; Zhang, L.; Shi, L.; Wang, P. MXene $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ : An Effective 2D Light-to-Heat Conversion Material. ACS Nano 2017, 11, 3752− 3759. \n(36) Lukatskaya, M. R.; Mashtalir, O.; Ren, C. E.; Dall’Agnese, Y.; Rozier, P.; Taberna, L.; Naguib, M.; Simon, P.; Barsoum, M. W.; Gogotsi, Y. Cation Intercalation and High Volumetric Capacitance of Two-Dimensional Titanium Carbide. Science 2013, 341, 1502−1505. (37) Ghidiu, M.; Kota, S.; Halim, J.; Sherwood, A. W.; Nedfors, N.; Rosen, J.; Mochalin, V. N.; Barsoum, M. W. Alkylammonium Cation Intercalation into $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (MXene): Effects on Properties and IonExchange Capacity Estimation. Chem. Mater. 2017, 29, 1099−1106. (38) Mashtalir, O.; Naguib, M.; Mochalin, V. N.; Dall’Agnese, Y.; Heon, M.; Barsoum, M. W.; Gogotsi, Y. Intercalation and Delamination of Layered Carbides and Carbonitrides. Nat. Commun. 2013, 4, No. 1716. \n(39) Verger, L.; Natu, V.; Ghidiu, M.; Barsoum, M. W. Effect of Cationic Exchange on the Hydration and Swelling Behavior of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{z}}$ MXenes. J. Phys. Chem. C 2019, 123, 20044−20050. \n(40) Wang, H.-W.; Naguib, M.; Page, K.; Wesolowski, D. J.; Gogotsi, Y. Resolving the Structure of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXenes through Multilevel Structural Modeling of the Atomic Pair Distribution Function. Chem. Mater. 2015, 28, 349−359. \n(41) Presser, V.; Naguib, M.; Chaput, L.; Togo, A.; Hug, G.; Barsoum, M. W. First-Order Raman Scattering of the MAX Phases: $\\mathrm{Ti}_{2}\\mathrm{AlN}.$ , $\\mathrm{Ti}_{2}\\mathrm{AlC}_{0.5}\\mathrm{N}_{0.5},$ ${\\mathrm{Ti}}_{2}{\\mathrm{AlC}},$ $(\\mathrm{Ti}_{0.5}\\mathrm{V}_{0.5})_{2}\\mathrm{AlC}$ , ${\\mathrm{V}}_{2}{\\mathrm{AlC}},$ ${\\mathrm{Ti}_{3}}\\mathrm{AlC}_{2},$ and $\\mathrm{Ti}_{3}\\mathrm{GeC}_{2}$ . J. Raman Spectrosc. 2012, 43, 168−172. \n(42) Hu, T.; Hu, M.; Li, Z.; Zhang, H.; Zhang, C.; Wang, J.; Wang, X. Covalency-Dependent Vibrational Dynamics in Two-Dimensional Titanium Carbides. J. Phys. Chem. A 2015, 119, 12977−12984. (43) Li, H.; Zhang, $\\mathrm{Q.;}$ Yap, C. C. $\\mathrm{R.},$ Tay, B. K.; Edwin, T. H. T.; Olivier, A.; Baillargeat, D. From Bulk to Monolayer $\\mathbf{MoS}_{2}$ : Evolution of Raman Scattering. Adv. Funct. Mater. 2012, 22, 1385−1390. (44) Hantanasirisakul, K.; Zhao, $\\mathrm{M.}\\mathrm{-}\\mathrm{Q.};$ Urbankowski, P.; Halim, J.; Anasori, B.; Kota, S.; Ren, C. E.; Barsoum, M. W.; Gogotsi, Y. Fabrication of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene Transparent Thin Films with Tunable Optoelectronic Properties. Adv. Electron. Mater. 2016, 2, No. 1600050. \n\n(45) El-Demellawi, J. K.; Lopatin, S.; Yin, J.; Mohammed, O. F.; Alshareef, H. N. Tunable Multipolar Surface Plasmons in 2D $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene Flakes. ACS Nano 2018, 12, 8485−8493. (46) Tang, J.; Mathis, T. S.; Kurra, N.; Sarycheva, A.; Xiao, X.; Hedhili, M. N.; Jiang, $\\mathrm{Q.;}$ Alshareef, H. N.; $\\mathrm{{Xu,}}$ B.; Pan, F.; Gogotsi, Y. Tuning the Electrochemical Performance of Titanium Carbide MXene by Controllable In Situ Anodic Oxidation. Angew. Chem., Int. Ed. 2019, 58, 17849−17855. (47) Abazović, N. D.; Č omor, M. I.; Dramićanin, M. D.; Jovanović, D. J.; Ahrenkiel, P.; Nedeljković, J. M. Photoluminescence of Anatase and Rutile $\\mathrm{TiO}_{2}$ Particles. J. Phys. Chem. B 2006, 110, 25366−25370. " + }, + { + "id": "10.1126_science.aay9972", + "DOI": "10.1126/science.aay9972", + "DOI Link": "http://dx.doi.org/10.1126/science.aay9972", + "Relative Dir Path": "mds/10.1126_science.aay9972", + "Article Title": "Rational design of layered oxide materials for sodium-ion batteries", + "Authors": "Zhao, CL; Wang, QD; Yao, ZP; Wang, JL; Sánchez-Lengeling, B; Ding, FX; Qi, XG; Lu, YX; Bai, XD; Li, BH; Li, H; Aspuru-Guzik, A; Huang, XJ; Delmas, C; Wagemaker, M; Chen, LQ; Hu, YS", + "Source Title": "SCIENCE", + "Abstract": "Sodium-ion batteries have captured widespread attention for grid-scale energy storage owing to the natural abundance of sodium. The performance of such batteries is limited by available electrode materials, especially for sodium-ion layered oxides, motivating the exploration of high compositional diversity. How the composition determines the structural chemistry is decisive for the electrochemical performance but very challenging to predict, especially for complex compositions. We introduce the cationic potential that captures the key interactions of layered materials and makes it possible to predict the stacking structures. This is demonstrated through the rational design and preparation of layered electrode materials with improved performance. As the stacking structure determines the functional properties, this methodology offers a solution toward the design of alkali metal layered oxides.", + "Times Cited, WoS Core": 717, + "Times Cited, All Databases": 755, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000586868600043", + "Markdown": "# BATTERIES \n\n# Rational design of layered oxide materials for sodium-ion batteries \n\nChenglong ${\\bf\\tt Z h a o1},{\\tt2}\\mathrm{*}$ , Qidi Wang3,4\\*, Zhenpeng $\\yen123$ , Jianlin Wang6, Benjamín Sánchez-Lengeling5, Feixiang $\\mathsf{D i n g}^{1,2}$ , Xingguo ${\\mathfrak{Q}}^{1,2}$ , Yaxiang ${\\mathsf{L}}{\\mathsf{u}}^{1,2}\\dag$ , Xuedong ${\\mathsf{B a i}}^{6}$ , Baohua $\\mathsf{L i}^{3}$ , Hong $\\mathbf{Li}^{2,2}$ , Alán Aspuru-Guzik $^{5,7}\\dag$ , Xuejie Huang1,2, Claude Delmas8†, Marnix Wagemaker9†, Liquan Chen1, Yong-Sheng ${\\mathsf{H}}{\\mathsf{u}}^{1,2,10}\\dag$ \n\nSodium-ion batteries have captured widespread attention for grid-scale energy storage owing to the natural abundance of sodium. The performance of such batteries is limited by available electrode materials, especially for sodium-ion layered oxides, motivating the exploration of high compositional diversity. How the composition determines the structural chemistry is decisive for the electrochemical performance but very challenging to predict, especially for complex compositions. We introduce the “cationic potential” that captures the key interactions of layered materials and makes it possible to predict the stacking structures. This is demonstrated through the rational design and preparation of layered electrode materials with improved performance. As the stacking structure determines the functional properties, this methodology offers a solution toward the design of alkali metal layered oxides. \n\nntegration of intermittent renewable energy sources demands the development of sustainable electrical energy storage systems $(I)$ . Compared with lithium (Li)–ion batteries, the abundance and low cost of \nsodium (Na) make Na-ion batteries promising \nfor smart grids and large-scale energy storage \napplications (2, 3). Li-ion layered oxides, with \n\nthe general formula $\\mathrm{LiTMO_{2}},$ have represented the dominant family of electrode materials for Li-ion batteries since 1980 (4). TM stands for one or multiple transition metal elements that facilitate the redox reaction associated with Li-ion (de-)intercalation. The layered structures are built up by edge-sharing $\\mathrm{\\TMO}_{6}$ octahedra, forming repeating layers between which \n\n![](images/1498f3bd08f6461e3db4b87cf15b1a28306117fbbb40c29d0ba3f0c3bfd6c0b5.jpg) \nFig. 1. Cationic potential and its use in Na-ion layered oxides. (A) Schematic illustration of crystal representative P2-type (hexagonal) and O3-type (rhombohedral) layered oxides. (B) Cationic potential of representative P2- and O3-type Na-ion layered oxides, considering the Na content, oxidation state of transition metals, and TM composition (see supplementary text and fig. S3 for details). \n\nLi ions are positioned in the octahedral (O) oxygen environment, leading to the so-called O-type stacking. The structure offers high compositional diversity, providing tunable electrochemical performance, of which well-known examples are $\\mathrm{LiCoO_{2}}$ and $\\mathrm{\\DeltaNi}$ -rich $\\mathrm{LiNi_{y}C o_{z}M n}$ $(\\mathrm{Al)_{1-y-Z}O_{2}}$ . In search of electrodes for Na-ion batteries, layered oxides $\\mathrm{(Na_{x}T M O_{2})}$ offered the natural starting point (5). However, a key difference is that for Na-ion oxides, in addition to O-type, P-type stacking can occur, in which P-type refers to prismatic Na-ion coordination (Fig. 1A). These stackings show distinctly different electrode performance, in which the most studied layered stacking configurations are P2 and O3 types (Fig. 1A), referring to the ABBA and ABCABC oxygen stacking, respectively $\\textcircled{6}$ . P2-type oxides usually provide higher Na-ion conductivity and better structural integrity against the O3 analogs, which is responsible for the high power density and good cycling stability (7). However, the lower initial Na content of P2-type electrodes limits the storage capacity in the first charge compared with high-Na-content O3-type materials (8). Usually, the structural transition between the O- and P-type can occur upon Na-ion (de)intercalation during (dis)charging, typically degrading cycle stability (2, 3). \n\nIn a search for electrodes with good chemical and dynamic stability and high Na storage performance, various P2- and O3-type Na-ion layered oxides have been synthesized and investigated (9, 10). However, effective guidelines toward the design and preparation of optimal electrode materials are lacking. Crystal structures of P2- and O3-type layered oxides can be differentiated on the basis of the ratio between the interlayer distance of the Na metal layer $d_{\\mathrm{(O-Na-O)}}$ and the TM layer distance $d_{(\\mathrm{o}}$ -TM-O) $(I I)$ , in which a ratio of ${\\sim}1.62$ distinguishes P2- and O3-type oxides (fig. S1 and table S1) (12). The larger ratio of P2-type oxides originates from the more localized electron distribution within the $\\mathrm{{TMO}_{2}}$ slabs, which results in a weaker repulsion between the adjacent $\\mathrm{NaO_{2}}$ slabs and consequentially a stronger repulsion between the adjacent $\\mathrm{{TMO}_{2}}$ slabs. This hints that the electron distribution plays an important role in the competition between the P- and O-type stackings in layered oxides. \n\nIonic potential $(\\Phi)$ is an indicator of the charge density at the surface of an ion, which is the ratio of the charge number $(n)$ with the ion radius $(R)$ introduced by G. H. Cartledge $(I3)$ , reflecting the cation polarization power. The ionic potential shows the expected increase with oxidation state and atom mass (fig. S2 and table S2), a consequence of the less localized orbitals. \n\nAiming at a simple descriptor for layered oxides, we express the extent of the cation electron density and its polarizability, normalized to the ionic potential anion (O), by defining the “cationic potential”: \n\n$$\n\\Phi_{\\mathrm{cation}}=\\overline{{\\frac{\\Phi_{\\mathrm{TM}}}{\\Phi_{\\mathrm{O}}}}}\\overline{{\\frac{\\Phi_{\\mathrm{Na}}}{\\Phi_{\\mathrm{O}}}}}\n$$ \n\nwhere $\\overline{{\\Phi_{\\mathrm{TM}}}}$ represents the weighted average ionic potential of TMs, defined as $\\overline{{\\Phi_{\\mathrm{TM}}}}=$ $\\sum\\frac{w_{\\mathrm{i}}n_{\\mathrm{i}}}{R_{\\mathrm{i}}}\\:;w_{\\mathrm{i}}$ is the content of $\\mathrm{\\Delta}T M_{\\mathrm{i}}$ having charge number $n_{\\mathrm{i}}$ and radius $R_{\\mathrm{i}};$ and $\\overline{{\\Phi_{\\mathrm{Na}}}}$ represents the weighted average ionic potential of Na defined as $\\begin{array}{r}{\\overline{{\\Phi_{\\mathrm{Na}}}}=\\frac{\\mathrm{x}}{R_{\\mathrm{Na}}}.}\\end{array}$ Charge balance in $\\mathrm{Na_{x}T M O_{2}}$ composition demands $\\sum w{\\mathrm{i}}n{\\mathrm{i}}=4-x,$ where $\\boldsymbol{x}$ represents Na cont ent and 4 is the total oxidation state to charge compensate $\\mathrm{O}^{2-}$ . \n\n![](images/f0823d8b8a1c738a25521fad9057dca5317ca643d45ba1a138f38b50b80b49fd.jpg) \nFig. 2. Designing an O3-type oxide. (A) Analysis of the cationic potential of Na-Li-Mn(Ti)-O oxides (see tables S8 and S9 for details). (B) XRD patterns of the targeted $\\Nu{\\sf a L i}_{1/3}{\\sf M n}_{2/3}0_{2}$ and the standard references. (C) Rietveld refinement of XRD pattern of $\\Nu\\mathsf{a L i}_{1/3}\\mp\\mathsf{i}_{1/6}\\mathsf{M n}_{1/2}\\mathsf{O}_{2}$ (see tables S10 to S12 for details). (D) Schematic illustration of the corresponding structure with the Li/Mn(Ti) ordering in the $\\mathrm{[Li_{1/3}T i_{1/6}M n_{1/2}]}0_{2}$ slabs. \n\n![](images/7c17879cb27cc0c31b7d135ca1cc7d569ce3ad25596dbb2b5e9bfad6970de0ac.jpg) \nFig. 3. Designing a P2-type oxide. (A) Analysis of cationic potential of Na-Li-Mn-O oxides (see tables S13 and S14 for details). (B) XRD patterns of $\\mathsf{N a L i}_{1/3}\\mathsf{T i}_{1/6}\\mathsf{M n}_{1/2}\\mathsf{O}_{2}$ and $N a_{5/6}L\\mathsf{i}_{5/18}\\mathsf{M}\\mathsf{n}_{13/18}0_{2}$ oxides. (C) Rietveld refinement of XRD pattern of $\\mathsf{N a}_{5/6}\\mathsf{L i}_{5/18}\\mathsf{M n}_{13/18}\\mathsf{O}_{2}$ (see tables S15 to S17 for details). (D) Schematic illustration of the corresponding structure with the Li/Mn ordering in the $[\\mathsf{L i}_{5/18}\\mathsf{M n}_{13/18}]0_{2}$ slabs. \n\nThe cationic potential $\\Phi_{\\mathrm{cation}}$ versus the weighted average Na ionic potential $\\overline{{\\Phi_{\\mathrm{Na}}}}$ of reported P2- and O3-type layered oxides results in the phase map shown in Fig. 1B. The distinct P2- and O3-type regions indicate that the cationic potential is an accurate descriptor of the interslab interaction and, thereby, the structural competition between P2- and O3-type structures. \n\nA larger cationic potential (Eq. 1) implies stronger TM electron cloud extend and interlayer electrostatic repulsion resulting in the P2-type structure, with more covalent TM-O bonds and an increased $d_{\\mathrm{(O-Na-O)}}$ distance (fig. S4). Opposing this, a larger mean Na ionic potential, achieved by increasing Na content, increases the shielding of the electrostatic repulsion between the $\\mathrm{{TMO}_{2}}$ slabs, favoring the O3-type structure. \n\nThe phase map (Fig. 1B) shows that very small differences in TM or Na content can result in a transition between P2- and O3-type structures. To illustrate this, we consider layered oxides with the composition $\\mathrm{Na_{2/3}T M O_{2}},$ which typically crystallizes in a P2-type structure for the low Na content, such as $\\mathrm{P2-Na_{2/3}C o O_{2}}\\left(I4\\right)$ or $\\mathrm{P2-Na_{2/3}N i_{1/3}T i_{2/3}O_{2}}(I5$ ). However, replacing $\\mathrm{Ni^{2+}}$ with $\\mathrm{Mg^{2+}}$ in $\\mathrm{P2\\mathrm{-}N a_{2/3}N i_{1/3}T i_{2/3}O_{2}},$ facilitated by their similar ionic radii (16), leads to $\\mathrm{Na_{2/3}M g_{1/3}T i_{2/3}O_{2}},$ for which the cationic potential predicts the O3-type structure, which is difficult to predict even with complex electrostatic energy calculations (15). In this case, the smaller ionic potential of $\\mathrm{Mg^{2+}}$ against $\\mathrm{Ni^{2+}}$ (Fig. 1B) decreases $\\Phi_{\\mathrm{cation}}$ ; the resulting lower covalence of $\\mathrm{Mg/Ti-O}$ bonds increases the charge carried by the oxygens and thereby weakens the repulsion between the TM layers, resulting in an O3-type structure (fig. S5, A and B, and tables S6 and S7). Substituting $\\mathrm{1/6\\Mg^{2+}}$ by $\\mathrm{Ni^{2+}}$ in $\\mathrm{Na_{2/3}M g_{1/3}T i_{2/3}O_{2}}$ to $\\mathrm{Na_{2/3}N i_{1/6}M g_{1/6}T i_{2/3}O_{2}}$ moves it back into a P2-type structure (fig. S5B), illustrating how near these compositions are to the line separating the P2- and O3-type phases. Several other examples demonstrating that the proposed cationic potential approach captures the subtle balance between the P2- and O3-type layered $\\mathrm{Na_{x}T M O_{2}}$ structures are provided in the supplementary text and figs. S5C and S6. \n\n![](images/9a9328b34f739690db415341dcb221806faa503b9ec1478af3848b812926c087.jpg) \nFig. 4. Cationic potential phase map for alkali metal layered oxides. Summary of reported alkali metal layered materials including Li-/Na-/K-ion oxides (see tables S18 and S19 for details). \n\nDelmas et al. $(6,77)$ used the Rouxel diagram (18) to distinguish $\\mathrm{Na_{x}T M O_{2}}$ stacking structures, demonstrating that both Na content and the ionicity and covalence of bonds are the important factors. However, this method only accounts for the difference in Pauling's electronegativity (fig. S7 and table S4), which makes it impossible to predict the structure of oxides with the same TMs in different oxidation states $(6,77)$ (e.g., $\\mathrm{{Mn^{4+}}}$ and $\\ensuremath{\\mathrm{Mn^{3+}}}$ in $\\mathrm{Na_{0.7}M n O_{2}};$ or for multiple-component systems (see supplementary text, fig. S8, and table S5 for details). The cationic potential correctly predicts the stacking structure for these cases, providing a guideline for the development of Na-ion layered oxides. \n\nUsing the cationic potential as a guide, we design specific stacking structures by controlling the Na content and TM composition. A notable starting point is $\\mathrm{NaLi_{1/3}M n_{2/3}O_{2}}$ , the analog of $\\mathrm{LiLi_{1/3}M n_{2/3}O_{2}(L i_{2}M n O_{3})};$ , providing capacity on the basis of oxygen redox chemistry. This composition has not been prepared so far, although theoretical calculations argue $\\mathrm{NaLi_{1/3}M n_{2/3}O_{2}}$ is stable in an O3-type structure (19). Various experimental conditions were attempted to prepare this composition in an O3-type structure, but always a P2-type component, in addition to other phases, was obtained. Lowering the cationic potential suggests that a possible route to prepare the O3-type structure is partial substitution of $\\mathrm{{Mn^{4+}}}$ by $\\mathrm{Ti}^{4+}$ (Fig. 2A), where $\\mathrm{Ti}^{4+}$ has a lower ionic potential. $\\mathrm{NaLi_{1/3}T i_{1/6}M n_{1/2}O_{2}}$ was successfully prepared in the predicted O3-type structure by a typical solid-state reaction (materials and methods). Notably, $\\mathrm{NaLi_{1/3}M n_{2/3}O_{2}}$ could not be synthesized as an O3-type structure by using the same method (Fig. 2B). Rietveld refinement of the $\\mathbf{\\boldsymbol{x}}$ -ray diffraction (XRD) pattern confirmed the layered rock-salt structure (Fig. 2C), in which the $\\mathrm{NaO_{2}}$ layers alternate with the mixed $\\mathrm{[Li_{1/3}T i_{1/6}M n_{1/2}]O_{2}}$ slabs (Fig. 2D). The $(l/3,l/3,l)$ superstructure peaks in $20^{\\circ}$ to $30^{\\circ}$ suggest $\\mathrm{Li/Mn(Ti)}$ ordering in a honeycomb pattern, which is also confirmed by the aberration-corrected scanning transmission electron microscopy (fig. S9). This ordered arrangement of Li and $\\mathbf{Mn}(\\mathrm{Ti})$ in the $\\mathrm{TMO_{2}}$ slabs has not been observed in O3-type Na-ion oxides with exclusively 3d TMs. The electrochemical properties (see supplementary text and fig. S10A for details) demonstrate an energy density of ${\\sim}630$ watt-hours (Wh) $\\mathbf{kg}^{-1}$ , higher than that of the reported O3-type electrodes. \n\nWe then use cationic potential to design a P2-type structure aiming at an anomalous high Na-content of $\\textstyle x>0.67$ , again starting from $\\mathrm{NaLi_{1/3}M n_{2/3}O_{2}}$ . To avoid formation of an O3-type structure, the dividing line in Fig. 1B demonstrates that we should increase the cationic potential (Eq. 1), assuming that $\\mathrm{{Na}}$ content remains constant, which can be realized by increasing the ionic potential at TM sites. On the basis of the cationic potential, a P2-type structure with $x=1$ $\\overline{{\\Phi_{\\mathrm{Na}}}}=9.8)$ will demand an extremely large TM ionic potential (larger than that of $\\mathrm{Mn^{4+}}$ , having the largest value among the widely used TMs). Therefore, the Na content in $\\mathrm{NaLi_{1/3}M n_{2/3}O_{2}}$ should be lowered, which can be achieved through charge compensation by decreasing the Li and increasing the Mn content. Following this route, the cationic potential predicts that $\\mathrm{Na_{5/6}L i_{5/18}M n_{13/18}O_{2}}$ composition with high Na content should have the P2-type structure (Fig. 3A), which was indeed successfully prepared (Fig. 3B). So far, layered oxides prepared with such high Na content usually crystallize as an O3-type structure. Compared with the O3-type $\\mathrm{NaLi_{1/3}T i_{1/6}M n_{1/2}O_{2}}$ , the (002) peak of the P2-type structure shifts toward lower diffraction angles, indicating the expected increase in the $\\scriptstyle{c}$ axis of the unit cell (Fig. 3B). Rietveld refinement of the XRD pattern reveals that this P2-type layered structure can be indexed in the hexagonal $P6_{3}$ space group (Fig. 3, C and D). The electron energy loss spectroscopy mapping reveals a uniform distribution of the Na, Mn, and O elements in the platelike particles (fig. S11). This as-prepared high-Na-content material has a considerably higher capacity of $>200$ milliampere-hours (mAh) $\\mathbf{g}^{-1}$ (fig. S10B). \n\nExtending the cationic potential to other alkali metal layered oxides, Li ion (fig. S12) and K ion (fig. S13), results in phase maps shown in Fig. 4. The cationic potential (Eq. 1) is found to increase from K to Na to Li ion owing to the increasing ability to shield the $\\mathrm{{TMO}_{2}}$ interslab interaction. As a consequence, $\\mathrm{K_{x}T M O_{2}}$ mainly crystallizes as the P2-type and $\\mathrm{Li_{x}T M O_{2}}$ as the O3-type structure, whereas $\\mathrm{Na_{x}T M O_{2}}$ is the most notable family, as the shielding strength is at the tipping point between P2- and O3-type structures. The distribution of reported layered electrodes exhibits a clear trend by clustering around the dividing line (Fig. 4). For more than 100,000 new compositions, up to quaternary compositions on the TM position, the cationic potential is used to calculate the most stable stacking structure, resulting in a distribution of compositions in the phase map around the dividing line (see figs. S14 and S15 and supplementary text for details). This demonstrates how the cationic potential can be used to predict the structure of new $\\mathrm{Na_{x}T M O_{2}}$ layered materials, on the basis of specific compositional demands. It is worth noting that the other parts far away from the line may also lead to other types of TM-oxide phases (e.g., rock salt, spinel), or may not lead to stable structures at all, which is the subject of ongoing investigations. \n\nIn summary, the ionic potential is a measure of the polarization of ions, mainly reflecting the influence of electrostatic energy on the system. Because the main difference between P- and O-type structures is the electrostatic polarization between $\\mathrm{{AO}_{2}}$ (A, alkali metals) and $\\mathrm{{TMO}_{2}}$ slabs, we can apply the proposed cationic potential method to distinguish and design materials, especially useful for Na-ion layered oxides. For entropy-dominated phases, disordered compounds resulting from mechanical milling (20), or oxides prepared under particular conditions (21, 22), metastable structures, or nonequilibrium phases (23), as well as the local distortion of TMs (e.g., due to Jahn-Teller effect on $\\ensuremath\\mathrm{{Mn^{3+}}}$ ), the cationic potential approach does not provide a sensible guideline. Moreover, the cationic potential only predicts whether the proposed material will crystallize in a ${\\mathrm{P}}\\mathrm{-}$ or O-type structure, and one composition has only one structure. The actual obtained phases depend strongly on the nature of precursors and the conditions/atmosphere of thermal treatment, among others, which may cause the difference in stoichiometry and dynamic process, leading to structural changes. Further structural information is required to decide whether the corresponding material is stable and/or synthesizable in practice and calls for extensive investigation. Additionally, prediction of stacking structures is challenging for density functional theory methods because of the difficulty of predicting the localized nature of TM orbitals, especially for complicated TM compositions that have an enormous configurational space. We demonstrated the use of cationic potentials to tune the $\\mathrm{TMO_{2}}$ interslab interaction, contributing to the important categories of layered materials. The currently known layered materials are either low-Na-content $(x\\:=\\:2/3)$ ) P2-type oxides or high-Na-content $(x=1)$ ) O3-type oxides; we suggest further exploration of high-Na-content P2-type oxides and low-Nacontent O3-type oxides through the as-proposed cationic potential. \n\n# REFERENCES AND NOTES \n\n1. B. Dunn, H. Kamath, J.-M. Tarascon, Science 334, 928–935 (2011). \n2. S.-W. Kim, D.-H. Seo, X. Ma, G. Ceder, K. Kang, Adv. Energy Mater. 2, 710–721 (2012). \n3. M. H. Han, E. Gonzalo, G. Singh, T. Rojo, Energy Environ. Sci. 8, 81–102 (2015). \n4. K. Mizushima, P. C. Jones, P. J. Wiseman, J. B. Goodenough, Mater. Res. Bull. 15, 783–789 (1980). \n5. N. Yabuuchi et al., Nat. Mater. 11, 512–517 (2012). \n6. C. Delmas, C. Fouassier, P. Hagenmuller, Physica B+C 99, 81–85 (1980). \n7. C. Fouassier, C. Delmas, P. Hagenmuller, Mater. Res. Bull. 10, 443–449 (1975). \n8. S. Komaba et al., Inorg. Chem. 51, 6211–6220 (2012). \n9. J. M. Paulsen, R. A. Donaberger, J. R. Dahn, Chem. Mater. 12, 2257–2267 (2000). \n10. J. Billaud et al., Energy Environ. Sci. 7, 1387–1391 (2014). \n11. M. Guilmard, L. Croguennec, C. Delmas, J. Power Sources 150, A1287–A1293 (2003). \n12. C. Zhao, M. Avdeev, L. Chen, Y.-S. Hu, Angew. Chem. Int. Ed. 57, 7056–7060 (2018). \n13. G. H. Cartledge, J. Am. Chem. Soc. 50, 2855–2863 (1928). \n14. C. Delmas, J.-J. Braconnier, C. Fouassier, P. Hagenmuller, Solid State Ion. 3-4, 165–169 (1981). \n15. Y.-J. Shin, M.-Y. Yi, Solid State Ion. 132, 131–141 (2000). \n16. G. Singh et al., Chem. Mater. 28, 5087–5094 (2016). \n17. C. Delmas, C. Fouassier, P. Hagenmuller, Mater. Res. Bull. 11, 1483–1488 (1976). \n18. J. Rouxel, J. Solid State Chem. 17, 223–229 (1976). \n19. D. Kim, M. Cho, K. Cho, Adv. Mater. 29, 1701788 (2017). \n20. T. Sato, K. Sato, W. Zhao, Y. Kajiya, N. Yabuuchi, J. Mater. Chem. A Mater. Energy Sustain. 6, 13943–13951 (2018). \n\n21. T. Uyama, K. Mukai, I. Yamada, Inorg. Chem. 58, 6684–6695 (2019). 22. M. H. Han et al., Electrochim. Acta 182, 1029–1036 (2015). 23. M. Bianchini et al., Nat. Mater. 19, 1088–1095 (2020). \n\n# ACKNOWLEDGMENTS \n\nFunding: This work was supported by the National Natural Science Foundation of China (51725206, 51421002, 21773303), National Key Technologies R&D Program of China (2016YFB0901500), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA21070500), Youth Innovation Promotion Association, Chinese Academy of Sciences (2020006), Beijing Municipal Science and Technology Commission (Z181100004718008), Beijing Natural Science Fund-Haidian Original Innovation Joint Fund (L182056), and the Netherlands Organization for Scientific Research (NWO) (under the VICI grant no. 16122). Computations were performed on the Niagara supercomputer at the SciNet HPC Consortium. SciNet is funded by the Canada Foundation for Innovation; the Government of Ontario, Ontario Research Fund-Research Excellence, and the University of Toronto. C.Z. also thanks to the State Scholarship Fund of China Scholarship Council (CSC). Author contributions: Y.-S.H. conceived this research and supervised this work with M.W., C.Z., and Q.W., who conceptualized the ionic potential method and developed the calculation on examples of Na-/Li-/K-ion layered oxides. C.Z. and Q.W. performed synthesis procedures, experimental investigation of NaLi1/3Ti1/6Mn1/2O2 and $N a_{5/6}L i_{5/18}\\mathsf{M n}_{13/18}0_{2}$ materials, and software programming to process and present collected data. F.D. synthesized the Na-Li-Cu-Fe-Mn-O materials. Z.Y., B.S.-L., and A.A.-G. predict Na-ion layered oxides tested by cationic potential. J.W. and X.B. performed STEM observation and analysis. C.Z., Q.W., Z.Y., M.W., Y.L., C.D., and Y.-S.H. wrote the manuscript. All authors participated in analyzing the experimental results and preparing the manuscript. C.Z., Q.W., and Z.Y. contributed equally to this work. Competing interests: All authors declare that they have no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/370/6517/708/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S15 \nTables S1 to S19 \nReferences (24–169) \n\n4 August 2019; accepted 18 September 2020 \n10.1126/science.aay9972 \n\n# Science \n\n# Rational design of layered oxide materials for sodium-ion batteries \n\nChenglong Zhao, Qidi Wang, Zhenpeng Yao, Jianlin Wang, Benjamín Sánchez-Lengeling, Feixiang Ding, Xingguo Qi, Yaxiang Lu, Xuedong Bai, Baohua Li, Hong Li, Alán Aspuru-Guzik, Xuejie Huang, Claude Delmas, Marnix Wagemaker, Liquan Chen and Yong-Sheng Hu \n\nScience 370 (6517), 708-711. DOI: 10.1126/science.aay9972 \n\n# Layering the charge \n\nLayered metal oxides such as lithium cobalt oxide have attracted great attention for rechargeable batteries. In lithium cells, only the octahedral structure forms, but in sodium cells, trigonal prismatic structures are also possible. However, there is a lack of understanding about how to predict and control the formation of each structure. Zhao et al. used the simple properties of ions, namely their charge and their radius appropriately weighted by stoichiometry, to determine whether sodium in the interlayers between the transition metal or other ion-oxide layers remain octahedral rather than switching over to trigonal prismatic coordination. \n\nScience, this issue p. 708 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41557-020-0481-9", + "DOI": "10.1038/s41557-020-0481-9", + "DOI Link": "http://dx.doi.org/10.1038/s41557-020-0481-9", + "Relative Dir Path": "mds/10.1038_s41557-020-0481-9", + "Article Title": "Coupling N2 and CO2 in H2O to synthesize urea under ambient conditions", + "Authors": "Chen, C; Zhu, XR; Wen, XJ; Zhou, YY; Zhou, L; Li, H; Tao, L; Li, QL; Du, SQ; Liu, TT; Yan, DF; Xie, C; Zou, YQ; Wang, YY; Chen, R; Huo, J; Li, YF; Cheng, J; Su, H; Zhao, X; Cheng, WR; Liu, QH; Lin, HZ; Luo, J; Chen, J; Dong, MD; Cheng, K; Li, CG; Wang, SY", + "Source Title": "NATURE CHEMISTRY", + "Abstract": "The use of nitrogen fertilizers has been estimated to have supported 27% of the world's population over the past century. Urea (CO(NH2)(2)) is conventionally synthesized through two consecutive industrial processes, N-2 + H-2 -> NH(3)followed by NH3 + CO2 -> urea. Both reactions operate under harsh conditions and consume more than 2% of the world's energy. Urea synthesis consumes approximately 80% of the NH(3)produced globally. Here we directly coupled N(2)and CO(2)in H2O to produce urea under ambient conditions. The process was carried out using an electrocatalyst consisting of PdCu alloy nulloparticles on TiO(2)nullosheets. This coupling reaction occurs through the formation of C-N bonds via the thermodynamically spontaneous reaction between *N=N* and CO. Products were identified and quantified using isotope labelling and the mechanism investigated using isotope-labelled operando synchrotron-radiation Fourier transform infrared spectroscopy. A high rate of urea formation of 3.36 mmol g(-1) h(-1) and corresponding Faradic efficiency of 8.92% were measured at -0.4 V versus reversible hydrogen electrode.", + "Times Cited, WoS Core": 676, + "Times Cited, All Databases": 706, + "Publication Year": 2020, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000540397300001", + "Markdown": "# Coupling N2 and $\\mathbf{CO}_{2}$ in H $_{2}\\mathbf{O}$ to synthesize urea under ambient conditions \n\nChen Chen1,10, Xiaorong Zhu2,10, Xiaojian Wen3,10, Yangyang Zhou1,10, Ling Zhou1, Hao Li1, Li Tao1, Qiling Li1, Shiqian $\\boldsymbol{\\mathsf{D}}\\boldsymbol{\\mathsf{u}}^{1}$ , Tingting Liu1, Dafeng Yan1, Chao Xie1, Yuqin Zou1, Yanyong Wang1, Ru Chen1, Jia Huo1, Yafei Li   2 ✉, Jun Cheng   3 ✉, Hui $\\mathsf{\\pmb{S u4}}$ , Xu Zhao4, Weiren Cheng $\\textcircled{10}4$ , Qinghua Liu   4 ✉, Hongzhen Lin5, Jun Luo $\\textcircled{10}6$ , Jun Chen   7 ✉, Mingdong Dong $\\textcircled{10}8$ , Kai Cheng9, Conggang Li $\\oplus9$ and Shuangyin Wang   1 ✉ \n\nThe use of nitrogen fertilizers has been estimated to have supported $27\\%$ of the world’s population over the past century. Urea $(C O(N H_{2})_{2})$ is conventionally synthesized through two consecutive industrial processes, $N_{2}+H_{2}\\rightarrow N H_{3}$ followed by $N H_{3}+C O_{2}\\rightarrow$ urea. Both reactions operate under harsh conditions and consume more than $2\\%$ of the world’s energy. Urea synthesis consumes approximately $80\\%$ of the $M H_{3}$ produced globally. Here we directly coupled $\\ensuremath{\\mathbb{N}}_{2}$ and $\\pmb{\\ c o_{2}}$ in ${\\bf H}_{2}\\circ$ to produce urea under ambient conditions. The process was carried out using an electrocatalyst consisting of PdCu alloy nanoparticles on $\\mathbf{\\bar{\\Pi}}\\mathbf{\\bar{\\Pi}}\\mathbf{0}_{2}$ nanosheets. This coupling reaction occurs through the formation of C–N bonds via the thermodynamically spontaneous reaction between $\\star_{\\mathsf{M}}=\\mathsf{N}^{\\star}$ and CO. Products were identified and quantified using isotope labelling and the mechanism investigated using isotope-labelled operando synchrotron-radiation Fourier transform infrared spectroscopy. A high rate of urea formation of $3.36\\mathrm{mmolg^{-1}h^{-1}}$ and corresponding Faradic efficiency of $8.92\\%$ were measured at –0.4 V versus reversible hydrogen electrode. \n\nver the past century, nitrogen fertilization has supported approximately $27\\%$ of the world’s population1. As urea is one of the most important nitrogen fertilizers with a high \nnitrogen content, the development of the urea industry is of great \nsignificance to meet the demands of an ever-increasing population. \n\nCurrently, the synthesis of urea is dominated by the reaction of $\\mathrm{NH}_{3}$ and $\\mathrm{CO}_{2}$ under harsh conditions ( $\\mathrm{150-}200^{\\circ}\\mathrm{C}$ , 150–250 bar) with large energy consumption. Moreover, complex equipment and multi-cycle synthetic processes are required to enhance the conversion efficiency2,3. The production of urea consumes approximately $80\\%$ of the global $\\mathrm{NH}_{3}$ (ref. 4), which is mainly derived from artificial $\\mathrm{N}_{2}$ fixation. The fixation of earth-abundant $\\mathrm{N}_{2}$ is challenging both scientifically and technologically due to the inertness of this molecule5. The industrial fixation of $\\Nu_{2}$ and $\\mathrm{H}_{2}$ to obtain ammonia has always been dominated by the Haber–Bosch process, operating at a high temperature and high pressure due to the high bonding energy of the $_{\\mathrm{N-N}}$ triple bond $(940.95\\mathrm{kJmol^{-1}},$ ) and consuming approximately $2\\%$ of world’s energy annually5–15. Thus, there have been extensive research activities to reduce the activation energy of the $\\mathrm{N}_{2}$ -to- $\\mathrm{\\cdotNH}_{3}$ reaction under milder conditions16–19. \n\nElectrocatalytic $\\mathrm{N}_{2}$ fixation under ambient conditions combines the advantages of the utilization of clean energy and protons directly from water20–23. However, current research mainly focuses on solo $\\mathrm{N}_{2}$ electrochemical fixation to generate $\\mathrm{NH}_{3}$ , and the post treatment of primary products—further applications have seldom been considered2,3. Actually, the separation of $\\mathrm{NH}_{3}$ in an aqueous electrolyte and its further purification to obtain gaseous $\\mathrm{NH}_{3}$ with high purity would make the subsequent urea synthesis complicated and unpractical. \n\nFor $\\mathrm{CO}_{2}$ fixation, carbon capture and sequestration (CCS) is mainly attributed to the formation of strong covalent bonds $(\\mathrm{C}-\\mathrm{N})^{24-27}$ , but the high energy consumption, high cost and leakage risk of the captured $\\mathrm{CO}_{2}$ prohibit further application of this method28. Compared with the direct electrolysis of $\\mathrm{CO}_{2},$ the electrolysis of CO tends to create multi-carbon products via more efficient C–C coupling29–31. On this basis, Jiao and co-workers creatively introduced ammonia as a source of nitrogen to realize $\\mathrm{C-N}$ coupling and the production of acetamides with a high rate and selectivity $(40\\%)$ under ambient conditions32. In consideration of the hurdles in $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ fixation and the increasing interest in photoor electro-driven $\\mathrm{C-N}$ bond formation32–34, we hypothesize that the simultaneous electrocatalytic coupling of $\\Nu_{2}$ and $\\mathrm{CO}_{2}$ would enable the formation of $\\mathrm{C-N}$ bonds and thus realize the conversion to urea under ambient conditions. \n\nHerein we demonstrate an approach for the electrochemical coupling of $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ in $\\mathrm{H}_{2}\\mathrm{O}$ to form urea with an electrocatalyst consisting of PdCu alloy nanoparticles on $\\mathrm{TiO}_{2}$ nanosheets. Apart from the design of the catalysts, the electrolyte used plays the key role in the evaluation of catalytic performance20,35. Feng et al. pointed out that the hydrogen evolution reaction (HER) can be efficiently suppressed in a neutral electrolyte to achieve ammonia synthesis with a high Faradic efficiency20,36, which is also applicable to this work. Following this guidance, efficient urea synthesis was achieved with a urea formation rate of $3.36\\mathrm{mmolg^{-1}h^{-1}}$ and a corresponding Faradic efficiency of $8.92\\%$ at $-0.4\\mathrm{V}$ versus reversible hydrogen electrode (RHE) in a flow cell. \n\nTheoretical calculations are of great significance to the selection of catalysts and the understanding of reaction mechanisms. Medford and co-workers have carried out substantial and pioneering research on this topic, developing a fundamental understanding of the molecular-scale processes that underlie the important and potentially transformative $\\Nu_{2}$ and $\\mathrm{CO}_{2}$ reduction processes37–40. Inspired by their instructive theory that the carbon radicals on the catalyst surface can interact strongly with $\\Nu_{2}$ molecules to facilitate the catalytic process33, possible mechanisms for $\\mathrm{C-N}$ bond formation via the thermodynamic spontaneous reaction between $\\boldsymbol{*}\\boldsymbol{\\mathrm{N}}\\mathrm{=}\\boldsymbol{\\mathrm{N}}^{\\ast}$ (the asterisks here indicate the side-on sorption of $\\mathrm{N}_{2}$ ) and CO were proposed, and the subsequent hydrogenations enable the generation of urea. The formation and evolution of chemical bonds during the electrocatalytic process were monitored by isotope-labelling operando synchrotron-radiation Fourier transform infrared spectroscopy (SR-FTIR). The generated urea was identified and quantified based on isotope-labelling experiments. \n\n# Results and discussion \n\nStructural characterization of electrocatalysts. $\\mathrm{TiO}_{2}$ nanosheets were prepared as catalyst supports. Defect engineering has been widely adopted to modulate the physicochemical properties of materials41. In this work, $\\mathrm{TiO}_{2}$ with oxygen vacancies (OVs) was easily fabricated by treatment of pristine $\\mathrm{TiO}_{2}$ nanosheets under a reduction atmosphere at an elevated temperature. The scanning electron microscopy (SEM) images in Supplementary Fig. 1 suggest the maintenance of the nanosheet structure after thermal treatment until the temperature was elevated to $600^{\\circ}\\mathrm{C}$ . The oxygen vacancies were characterized by electron paramagnetic resonance (EPR) spectroscopy, as illustrated in Supplementary Fig. 2, and a symmetric Lorentzian line with a $g$ value of 2.003 was obtained42. The EPR intensity increased with increasing treatment temperature and reached the highest intensity for $\\mathrm{TiO}_{2}$ -400 $\\mathrm{TiO}_{2}$ with thermal treatment at $400^{\\circ}\\mathrm{C}\\cdot$ ) but dropped for $\\mathrm{TiO}_{2}$ -600 ( $\\mathrm{TiO}_{2}$ with thermal treatment at $600^{\\circ}\\mathrm{C})$ , indicating that $\\mathrm{TiO}_{2}–400$ has the highest vacancy concentration. The presence of OVs was also confirmed by X-ray photoemission spectroscopy (XPS) and Raman spectroscopy (Supplementary Figs. 3 and 4). The formation of OVs could narrow the band gap of $\\mathrm{TiO}_{2}$ -400 (Supplementary Fig. 5) but did not change the crystalline phase (Supplementary Fig. 6). However, high-temperature annealing of $\\mathrm{TiO}_{2}$ -400 resulted in a slight decrease in the surface area (Supplementary Fig. 7). \n\nPdCu alloy nanoparticles on pristine $\\mathrm{TiO}_{2}$ and OV-rich $\\mathrm{TiO}_{2}$ nanosheets were fabricated via co-reduction of metal precursors. The SEM images in Supplementary Fig. 8 show the maintenance of the structure of $\\mathrm{TiO}_{2}$ after anchoring the nanoparticles. Typically, the transmission electron microscopy (TEM) image of $\\mathrm{Pd}_{1}\\mathrm{Cu}_{1}/$ $\\mathrm{TiO}_{2}–400$ displays homogeneous PdCu alloy nanoparticles (approximately $2\\mathrm{nm}$ ) loaded onto $\\mathrm{TiO}_{2}$ nanosheets (Fig. 1a). The lattice distance of $0.217\\mathrm{nm}$ in Fig. 1b shows the (111) interplanar distance of the face-centred cubic (FCC) PdCu alloy43, confirming the successful synthesis of PdCu alloy nanoparticles. \n\nThe high-resolution Pd $3d$ and Cu $2p$ XPS spectra were carried out to analyse the electronic properties of the PdCu alloy (as presented in Fig. 1c,d). Compared to the binding energy (BE) of Pd $3d_{5/2}$ for ${\\mathrm{Pd}}/{\\mathrm{TiO}}_{2}$ located at $334.9\\mathrm{eV},$ the BE of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ is shifted slightly to $335.2\\mathrm{eV}.$ Similarly, the BE of Cu $2p_{3/2}$ for $\\mathrm{Cu}/\\mathrm{TiO}_{2}$ is located at $932.3\\mathrm{eV}$ and shifts to $931.7\\mathrm{eV}$ for $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ . The shift of the BE is ascribed to the electronic interaction and charge transfer between Pd and Cu (ref. 44). Moreover, the BE of Pd $3d_{5/2}$ for $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ $\\mathrm{(Pd,Cu_{1}}$ supported on OV-rich $\\mathrm{TiO}_{2}$ ) shifts to $335.4\\mathrm{eV},$ and the BE of Cu $2p_{3/2}$ for $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ shifts to $931.6\\mathrm{eV},$ suggesting the enhancement of the interaction between PdCu alloy and ${\\mathrm{OV}}{\\cdot}{\\mathrm{TiO}}_{2}$ . For comparison, we also synthesized PdCu nanoparticles with different molar ratios (Supplementary Figs. 10 and 11). \n\nElectrochemical performance towards urea synthesis. Electrochemical urea synthesis by coupling $\\Nu_{2}$ and $\\mathrm{CO}_{2}$ in $\\mathrm{H}_{2}\\mathrm{O}$ was first carried out in an H-type cell (H cell, Supplementary Fig. 12). As shown in Supplementary Fig. 13, the diacetyl monoxime method was initially adopted to determine the concentration of urea by measuring the absorbance of the obtained pink solution at $525\\mathrm{nm}$ (ref. 45). The tests were carried out in the range of $-0.3\\mathrm{V}$ to $-0.8\\mathrm{V}$ versus RHE, and the electrochemical performance towards urea synthesis on $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ is summarized in Supplementary Fig. 14. A maximum urea formation rate of $0.12\\mathrm{mmolg^{-1}h^{-1}}$ and a corresponding Faradic efficiency of $0.66\\%$ were acquired at $-0.4\\mathrm{V}$ versus RHE. Beyond this negative potential, the performance towards urea synthesis decreased due to the limited capability for the activation of gaseous molecules. Once the potential decreased below $-0.4\\mathrm{V},$ the enhancement of the competing HER led to the sharp decrease in the urea formation rate and Faradic efficiency8. A similar trend was observed for electrocatalysts with various proportions of metal loading. \n\nAs illustrated in Supplementary Fig. 14, $\\mathrm{Pd}_{1}\\mathrm{Cu}_{1}/\\mathrm{TiO}_{2}$ presents the highest urea formation rate at $-0.4\\mathrm{V}$ among catalysts with different ratios of Pd and Cu. The sole nitrogen reduction reaction (NRR) and carbon dioxide reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ performances in H cells are summarized in Supplementary Figs. 15 and 16, respectively. $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ exhibits the highest $\\mathrm{NH}_{3}$ formation rate at $-0.4\\mathrm{V}$ due to the synergistic effect derived from a bimetal and optimization of the electronic structure. However, the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance for all catalysts is relatively poor compared to previously reported values46, which might be attributed to the low metal loads. However, $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ also presents higher Faradic efficiencies than mono-metal-loaded samples and a decline in the onset potential. It can be assumed that the high electrocatalytic activity towards urea synthesis is derived from the simultaneous improvements for NRR and $\\mathrm{CO}_{2}\\mathrm{RR}$ . \n\nPdCu alloy nanoparticles anchored on OV-rich $\\mathrm{TiO}_{2}$ nanosheets were fabricated, and the particle size of the PdCu alloys was controlled in the range of $2{-}4\\mathrm{nm}$ (Fig. 1a,b and Supplementary Fig. 17). $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ showed the best performance compared to the other compounds (Supplementary Fig. 18), and a urea formation rate of $0.1\\bar{9}\\mathrm{mmolg^{-1}h^{-1}}$ with a corresponding Faradic efficiency of $1.56\\%$ was acquired at $-0.4\\mathrm{V}$ versus RHE. The $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ was also improved (Supplementary Fig. 16), indicating the enhanced activation towards $\\mathrm{CO}_{2}$ fixation. Compared to the suppressed $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ after the participation of NRR, the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ is barely affected due to abundant adsorptive sites and high activation abilities for both $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ . The introduction of OVs enhanced the ability for activation on $\\Nu_{2}$ and $\\mathrm{CO}_{2}$ for $\\mathrm{Pd_{1}C u_{1}/T i O_{2}\\mathrm{-}400}$ , also facilitating the generation of urea. \n\nElectrochemical measurements for $\\mathrm{TiO}_{2}$ -400, $\\mathrm{Pd}/\\mathrm{TiO}_{2}–400$ and $\\mathrm{Cu}/\\mathrm{TiO}_{2}–400$ were also carried out (Supplementary Fig. 19). The application of alloy catalysts and optimization of alloy compositions are also crucial to the $\\scriptstyle{\\mathrm{C-C}}$ coupling in the $\\mathrm{CO}_{2}\\mathrm{RR}$ process47. The urea formation rate of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ -400 was obviously higher than that of the substrate and sample with a single metal anchored; thus, the effect of the alloy structure on the catalytic performance was further demonstrated. \n\n![](images/3b621fc6bde20fab5e18e1c755a93d8751226c8927d7e08a05b5f779a6880477.jpg) \nFig. 1 | Morphology and high-resolution XPS spectra of catalysts. a, TEM image of $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}–400$ ; the inset shows the distribution of the PdCu nanoparticles. The scale bar is $25\\mathsf{n m}$ . b, High-resolution TEM image of $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}–400$ 0. The scale bar is $2{\\mathsf{n m}}$ . c, Pd 3d XPS spectra of $\\mathsf{P d/T i O}_{2},$ $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/$ $\\mathsf{T i O}_{2}$ and $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}$ -400. d, Cu $2p$ XPS spectra of $\\mathsf{C u/T i O}_{2},$ $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}$ and $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}$ -400. \n\nThe support utilized here also plays a key role in boosting the electrocatalytic performance for urea synthesis. Carbon black (XC72R) with a higher conductivity than $\\mathrm{TiO}_{2}–400$ also served as the support for metal loading. Nevertheless, $\\mathrm{Pd_{1}C u_{1}/X C72R}$ exhibited a low urea formation rate (Supplementary Fig. 20), which might be ascribed to the weakened interaction between the metal and carbon support. The $\\mathrm{TiO}_{2}$ has been reported to stabilize the intermediates to promote $\\mathrm{CO}_{2}\\mathrm{RR}$ compared with a carbon support48, and the application of $\\mathrm{TiO}_{2},$ especially the OV-rich one, is crucial to promote the urea synthesis in this work. Thus the catalytic activity towards urea synthesis is due to the optimized electronic structure and the strong interaction between the metal and support. \n\nThe utilization of flow cells has been reported to improve electrocatalytic performance towards NRR12,49 and $\\mathrm{CO}_{2}\\mathrm{RR}^{46-48,50,51}$ and was introduced to boost the performance for electrochemical urea synthesis in this work. In contrast to the tests in conventional H cells, the tests in flow cells (Supplementary Fig. 21) possess efficient mass transport50 and higher fraction of coverage on electrode for gaseous reactants49,52, resulting in improved performance towards gas-consumption reactions. \n\nElectrochemical tests in the flow cell were conducted, and the liquid products were quantified by $\\mathrm{^{1}H}$ nuclear magnetic resonance (NMR) spectroscopy based on the linear relationship between concentrations and integral area (Supplementary Figs. 22–24). The gaseous products were quantified by gas chromatography (GC). \n\nCompared with the test in the H cell, in the flow cell, $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}.$ - 400 exhibited a higher ammonia formation rate $\\left(2.91\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}\\right)$ at $-0.4\\mathrm{V}$ versus RHE and presented a descending trend along with increasing applied negative potential (Fig. 2b). Furthermore, the $\\mathbf{CO}_{2}\\mathrm{RR}$ performance was also improved, as shown in Fig. 2c. As predicted, the urea formation rates in flow cells were substantially enhanced, and the highest yield rate of $3.36\\mathrm{mmolg^{-1}h^{-1}}$ was reached at $-0.4\\mathrm{V}.$ The Faradic efficiencies and corresponding current densities for tests in a $\\mathrm{CO}_{2}$ - and $\\Nu_{2}$ -saturated electrolyte are summarized in Fig. 2e. The results exhibit a lower ammonia yield at $-0.4\\mathrm{V}$ than the NRR results in Fig. 2b, indicating a modulated reaction pathway or the consumption of NRR intermediates to produce urea. Although the reaction was always dominated by hydrogen evolution, the catalyst also exhibited a desirable urea formation rate $\\left(3.36\\mathrm{mmolg^{-1}h^{-1}}\\right)$ and relatively high Faradic efficiency $(8.92\\%)$ compared to the low ammonia yield at $-0.4\\mathrm{V}.$ \n\nTo further boost the electrocatalytic performance53, tests with increasing concentrations of electrolyte were conducted at $-0.4\\mathrm{V}.$ An improvement of urea synthesis was observed with the increase in ${\\mathrm{KHCO}}_{3}$ concentration, and the highest yield rate of $3.76\\mathrm{mmolg^{-1}h^{-1}}$ with a corresponding Faradic efficiency of $9.43\\%$ was achieved (Supplementary Fig. 25). When the electrolyte concentration and the gas flow rate remain constant, the yield rate in this cell might be affected by the flow rate of the electrolyte50. Thus, control experiments with various electrolyte flow rates (1, 5, 10, 15, 20 and $25\\mathrm{mlmin^{-1}}.$ ) were performed. The urea formation rate increased as the flow rate increased, possibly attributed to the further enhanced mass transfer and rapid removal of products. The urea formation \n\n![](images/31a5945ee61c147d506eb64187d028b75aafe01e8fcc7810f24cb7229104fa6f.jpg) \nFig. 2 | Evaluation of the electrocatalytic performance of $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}–400$ in a flow cell. a, Schematic diagram for urea synthesis. The grey, navy, red and white spheres represent the C, N, O and H atoms, respectively. b, Ammonia synthesis with ${\\sf N}_{2}$ as the feeding gas at various potentials. c, CO production with ${\\mathsf{C O}}_{2}$ as the feeding gas. d, Urea generation with ${\\mathsf{C O}}_{2}$ and ${\\sf N}_{2}$ as feeding gases. e, The Faradic efficiencies and the total current densities for all products at various potentials. f, Mass spectra of derivation of urea with unmarked gas and isotope-labelling gas as feeding gases. The error bars represent the standard deviation for at least three independent measurements. \n\nrate reached its limit $(4.00\\mathrm{mmolg^{-1}h^{-1}})$ at a rate of $20\\mathrm{ml}\\mathrm{min}^{-1}$ . \nA similar trend was also observed for the Faradic efficiency. \n\nAs the chemisorption of $\\mathrm{N}_{2}$ is the initial step towards NRR, the $\\mathrm{N}_{2}$ chemisorption ability of the catalysts was measured by temperature-programmed desorption (TPD) with a mass detector. The results in Fig. 3a indicate that $\\mathrm{TiO}_{2}$ -400 has weak $\\mathrm{N}_{2}$ chemisorption. After anchoring metal nanoparticles, the catalysts exhibited substantial enhancement in the chemisorption of ${\\mathrm{N}}_{2},$ particularly for the alloy state. In addition to the enhanced intensity, peak shifts also appeared. The ${\\mathrm{Cu/TiO}}_{2}$ -400 spectrum presents a peak located at $234^{\\circ}\\mathrm{C};$ ; the peak shifts to $258^{\\circ}\\mathrm{C}$ for $\\mathrm{Pd}/\\mathrm{TiO}_{2}–400$ , and an additional peak at $360^{\\circ}\\mathrm{C}$ appears. The shift of the peak to a higher temperature indicates higher binding energies and stronger chemical adsorptions of gas molecules22. \n\nOwing to the electronic interaction of a bimetal, the TPD peaks further shift to higher temperatures ( $270^{\\circ}\\mathrm{C}$ and $380^{\\circ}\\mathrm{C}\\mathrm{)}$ ), indicating the superior chemical adsorption ability in the alloy state. Likewise, $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ also presents the highest ability for chemisorption of $\\mathrm{CO}_{2}$ (Fig. 3b). More importantly, the competitive sorption of $\\mathrm{CO}_{2}$ and $\\mathrm{N}_{2}$ was carried out, and only negligible shifts for all peak positions were observed, meaning benign competition existed in the chemical adsorption of $\\mathrm{CO}_{2}$ and ${\\mathrm{N}}_{2},$ resulting in efficient urea synthesis. \n\nExperimental mechanistic studies. To gain an in-depth understanding of the catalytic process, cutting-edge operando SR-FTIR was performed under working conditions54. The effective infrared signal is shown by a transmission mode in the FTIR results, which reveals that the negative peaks in the spectra represent the vibration absorption bands of key intermediates during the catalytic process. \n\nAs shown in Fig. 4, the SR-FTIR signals are clearly potential dependent. For the $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ electrode at a low potential of $-0.15\\mathrm{V},$ the vibration bands for NH, $\\mathrm{NH}_{2}$ and COOH were not detected, suggesting that the electroreduction of $\\mathrm{\\DeltaN}_{2}$ and $\\mathrm{CO}_{2}$ did not occur. When a potential of $-0.20\\mathrm{V}$ was applied, new weak vibration bands at $^{\\sim3,171}$ , ${\\sim}3{,}291$ and $\\sim3{,}441\\mathrm{cm}^{-1}$ , assigned to the stretching vibrations of $\\mathrm{NH}_{2}$ and NH, appeared (Fig. 4a)21,55,56. As the potential increased to $-0.25\\mathrm{V},$ new weak vibration bands at ${\\sim}1,699$ and $1,177-1,314\\mathrm{{cm}^{-1}}$ , assigned to the stretching vibrations of $\\scriptstyle{\\mathrm{C=O}}$ and C–O, respectively, were observed $(\\mathrm{Fig.4b})^{57}$ , implying that the slow electroreduction of $\\mathrm{CO}_{2}$ also occurred. Along with increasing potential (more negative than $-0.30\\mathrm{V}.$ ), the vibration intensities of $\\mathrm{NH}_{2}.$ , NH and $\\scriptstyle{\\mathrm{C=O}}$ gradually increased. At the same time, a stretching vibration of $\\mathrm{C-N}$ at $\\sim1{,}449\\mathrm{cm}^{-1}$ emerged (Fig. 4b)56,58 as the key bond for the formation of urea at $-0.30\\mathrm{V}.$ These vibration bands reached their peak values at $-0.40\\mathrm{V},$ which is consistent with the electrochemical performance measurements. The SR-FTIR results of the control experiments are also summarized in Supplementary Fig. 26. The vibration band intensities of NH and $\\mathrm{NH}_{2}$ for urea synthesis on $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ were higher than those of the sole NRR test and obviously higher than the test results for the $\\mathrm{CO}_{2}\\mathrm{RR}$ , consistent with the electrochemical test results. Moreover, the infrared signals of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ 0 were substantially superior to those of the support $(\\mathrm{TiO}_{2}–400)$ , indicating that the electrocatalytic active source is mainly PdCu alloy. \n\nTo further deepen the above analysis, isotope-labelling operando SR-FTIR experiments were conducted for the $\\mathrm{Pd}_{1}\\mathrm{Cu}_{1}/$ $\\mathrm{TiO}_{2}$ -400 catalyst under applied potentials of $-0.15$ to $-0.45\\mathrm{V}$ versus RHE with $^{15}\\mathrm{N}_{2}$ and/or $^{13}\\mathrm{CO}_{2}$ as the feeding gases. As seen from the isotope-labelling measurements in Fig. $^{4c,\\mathrm{d},}$ , the vibrations of $^{15}\\mathrm{N}\\mathrm{H}_{2};$ $^{15}\\mathrm{N}\\mathrm{H}$ and $^{13}{\\mathrm{C}}{=}\\mathrm{O}$ are shifted towards lower wavenumbers by $20{-}30\\mathrm{cm}^{-1}$ , and the vibration of $^{13}\\mathrm{C}\\mathrm{-}^{15}\\mathrm{N}$ is evidently shifted towards lower wavenumbers by $34\\mathrm{cm}^{-1}$ . These shifts are attributed to the isotope effect54, confirming the electroreduction of $\\Nu_{2}$ and $\\mathrm{CO}_{2}$ feeding gases during the reaction. The control experiments in Supplementary Figs. 27–29 further illustrate the possible occurrences of the NRR, the $\\mathrm{CO}_{2}\\mathrm{RR}$ and urea synthesis on $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ . \n\n![](images/a25e0d41c29091c06556f43364210434e5d9bc1b30123d96501c3e0315e29ead.jpg) \nFig. 3 | Sorption of gaseous molecules on catalysts. a, ${\\sf N}_{2}$ -TPD spectra of $T_{\\mathrm{i}}O_{2}$ -400, $\\mathsf{P d}/\\mathsf{T i O}_{2}$ -400, $\\mathsf{C u}/\\mathsf{T i O}_{2}–400$ and $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}$ -400. MS, mass spectrometry. b, ${\\mathsf{C O}}_{2}$ -TPD spectra of $\\mathsf{T i O}_{2}$ -400, $\\mathsf{P d}/\\mathsf{T i O}_{2}$ -400, $\\mathsf{C u/T i O}_{2}$ -400 and $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}$ -400. c, Competitive chemisorption of ${\\sf N}_{2}$ (red) and ${\\mathsf{C O}}_{2}$ (blue) on $\\mathsf{T i O}_{2}–400$ and $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}–400$ . \n\nThe electrochemical test on the bare glassy carbon electrode excluded the possibility of $\\mathrm{C-N}$ bond formation via the interaction between the carbon-containing electrode support and nitrogen gas (Supplementary Fig. 30). Summarizing the above results, it can be seen that $\\mathrm{N}_{2}$ activation started at $-0.20\\mathrm{V},$ and as the potential was increased to $-0.25\\mathrm{V},$ the intermediate of $^{*}{\\mathrm{COOH}}$ attributed to $\\mathrm{CO}_{2}$ activation was observed. The above results could serve as evidence for $\\mathrm{C-N}$ bond formation and the occurrence of electrocatalytic processes. \n\nTheoretical mechanistic studies. Density functional theory (DFT) calculations were carried out to further investigate the microscopic mechanism of this PdCu system using the computational hydrogen electrode $(\\mathrm{CHE})^{59}$ model, which has been previously proven to be applicable to $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ reduction reactions on metal surfaces. \n\nUrea production starts with $\\mathrm{N}_{2}$ adsorption on the PdCu surface with a side-on configuration. The side-on adsorption facilitates back feed of electrons from the $d$ orbitals of Pd and $\\mathtt{C u}$ to the $\\pi^{*}$ orbitals of ${\\mathrm{N}}_{2},$ reducing the $_{\\mathrm{N-N}}$ bond order60,61. According to the TPD results, the gas adsorption ability of the catalyst has been substantially enhanced, attributed mostly to the support effect and bimetal structure. The existence of activated $\\Nu_{2}$ molecules can further promote $\\mathrm{CO}_{2}\\mathrm{RR}$ to CO on adjacent metal sites. Supplementary Fig. 31 presents the optimized geometry of the key intermediate $^{*}{\\mathrm{COOH}}$ with and without the neighbouring $\\Nu_{2}$ . The corresponding free energy diagram indicates that the limiting potential of the $\\mathrm{CO}_{2}\\mathrm{RR}$ process can be reduced from $0.22\\mathrm{V}$ to $0.12\\mathrm{V}$ in the presence of co-adsorbed $\\mathrm{N}_{2}$ molecules. \n\nOnce the CO was released, the $\\boldsymbol{*}\\boldsymbol{\\mathrm{N}}\\mathrm{=}\\boldsymbol{\\mathrm{N}}^{\\ast}$ showed a strong effect on the CO due to the matched molecular orbitals. After binding with CO and formation of the tower-like urea precursor $\\boldsymbol{*}_{\\mathrm{NCON}^{*}}$ , the $_{\\mathrm{N-N}}$ bond was elongated from $1.14\\mathring\\mathrm{A}$ to $1.{\\dot{5}}8{\\dot{\\mathrm{A}}}$ , and the energy barrier of this process (presented in Fig. 5b) had a moderate $E_{\\mathrm{a}}$ value (approximately $+0.79\\mathrm{eV},$ on the PdCu surface. From a thermodynamic perspective, $^{*}\\mathrm{NCON^{*}}$ formation is exothermic, and the free energy change was calculated to be $-0.89\\mathrm{eV.}$ The competition reaction of $^{*}\\mathrm{NNH}$ formation is highly endothermic with an energy input of $+0.90\\mathrm{eV}.$ Thus, the release of the side product $\\mathrm{NH}_{3}$ can be greatly suppressed, and the positive $\\Delta G_{\\mathrm{\\Delta\\mathrm{NNH}}}^{*}$ provides an important premise for the high urea selectivity of PdCu systems. In all, the generation of intermediates $({}^{*}\\mathrm{NCON^{*}})$ via activating $\\Nu_{2}$ is thermodynamically and kinetically feasible, acting as the key factor for the effective urea production. \n\nBased on the above results, the production of CO at $-0.3\\mathrm{V}$ or $-0.4\\mathrm{V}$ versus RHE in this co-electrocatalysis system is possible; but the subsequent reaction could prohibit the release of CO macroscopically. Thus, the high yield rate of urea is mainly derived from the mutual promotion between the NRR and the $\\mathbf{CO}_{2}\\mathrm{RR}$ and both optimized reaction pathways. Furthermore, the amount of CO needs to be well controlled, as once the potential exceeds $-0.4\\mathrm{V},$ the decline in the yield rate for urea is ascribed to the excessive release of CO and its occupation of adsorptive sites for $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ to some extent. \n\nThe hydrogenation of $\\mathrm{\\DeltaN}$ can be assisted by the carbonyl functional group. The H atoms prefer to add to the $\\mathrm{~N~}$ atom directly connected with Cu to break the single $_{\\mathrm{N-N}}$ bond. The $\\mathsf{\\Pi}^{*}\\mathrm{NCONH}$ structural integrity can be well maintained after the first hydrogen atoms are added to the Cu-bound N atom due to the comparable $\\mathrm{{Cu-N}}$ and $\\mathrm{C-N}$ bond strengths. This can be further proven by the clear electron redistribution between the Pd and $\\mathtt{C u}$ atoms (Supplementary Fig. 32). The electron delocalization of $\\mathtt{C u}$ is much smaller than that of Pd, and the less positively charged Cu atoms with weaker $\\mathrm{{Cu-N}}$ bonds are more favourable for $\\boldsymbol{*}_{\\mathrm{NCON^{*}}}$ hydrogenation and $\\mathsf{\\Pi}^{*}\\mathrm{NCONH}$ stabilization. When H is added to ${}^{*}\\mathrm{NCONH}$ , two reaction pathways may occur. The distal product ${}^{*}\\mathrm{NCONH}_{2}$ was $+0.14\\mathrm{eV}$ more stable than the alternative product \\*NHCONH. The third proton-coupled electron transfer process was energy demanding and was the potential-limiting step of urea production. The limiting potential was $+0.64\\mathrm{V}$ and $+0.78\\mathrm{V}$ for the distal and alternative mechanisms, respectively. The subsequent reduction steps are exothermic, and the urea can be easily desorbed from the PdCu surfaces. \n\n![](images/416a13f79600cb9715c1d5f5297daa2a817eb133fc0e9845a71c5d2fb54f19fe.jpg) \nFig. 4 | Isotope-labelling operando SR-FTIR spectroscopy measurement results. a,b, Infrared signal in the range of $2,750\\mathrm{-}3,600\\mathsf{c m}^{\\mathrm{-1}}\\left(\\bar{\\mathbf{a}}\\right)$ and in the range of 1,100–1, $800\\ c m^{-1}\\left(6\\right.$ ) under various potentials for $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}–400$ during the electrocoupling of ${\\mathsf N}_{2}$ and ${\\mathsf{C O}}_{2}$ c,d, Isotope-labelling infrared signals in the range of $2,750{-}3,600\\mathsf{c m}^{-1}(\\mathsf{c}$ ) and in the range of 1,100–1 $,800\\mathsf{c m}^{-1}$ (d) at $-0.40\\vee$ versus RHE for $\\mathsf{P d}_{1}\\mathsf{C u}_{1}/\\mathsf{T i O}_{2}–400$ during the electrocoupling of $^{15}{\\mathsf N}_{2}$ and/or $^{13}{\\mathsf{C O}}_{2}$ processes. \n\n![](images/f4aff2d72219040b0b505c0d2e5d07cea037df0dddc602b2f30522a2b55047f2.jpg) \nFig. 5 | Theoretical calculation results for urea synthesis. a, Free energy diagram of urea production. b, The reaction pathway of $\\star_{\\mathsf{N C O N}^{\\star}}$ formation. The structures of the initial, transition and final states along with the $\\star_{\\mathsf{N C O N}}\\star$ formation are also presented. The green, orange, blue, red and grey balls represent Pd, Cu, N, O and C atoms, respectively. The line is simply to guide the eye. \n\nA detailed reaction mechanism with the most stable geometric structures of the reactants, intermediates and products throughout the urea formation is listed in Supplementary Fig. 32. The computational results reveal that the presence of $^{*}\\mathrm{N}_{2}$ can facilitate $\\mathrm{CO}_{2}$ reduction, and the reduced CO can further react with ${}^{*}\\mathrm{N}_{2}$ to form urea with ultrahigh activity and selectivity. \n\n# Conclusions \n\nThe fixation of gaseous molecules, particularly that of ${\\mathrm{N}}_{2},$ has attracted extreme attention but is challenging due to the intrinsic inertness of this molecule. This work not only focuses on the reduction of $\\Nu_{2}$ to ${\\mathrm{NH}}_{3}$ but, more importantly, aims to achieve the electrocatalytic coupling of $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ simultaneously to realize the green synthesis of urea under ambient conditions. With the rational design of the electrocatalyst, enhanced chemisorption and catalytic reactions of $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ were realized in the alloy state $\\mathrm{(Pd,Cu,/}$ $\\mathrm{TiO}_{2}–400\\dot{}$ ). The electrocatalytic process was monitored by operando SR-FTIR, and the products were identified and quantified via isotope-labelling experiments. Furthermore, possible mechanisms for urea synthesis were proposed. This work successfully realized $\\mathrm{C-N}$ bond formation and urea generation under ambient conditions, providing a pathway for the fixation of inert $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ (Supplementary Fig. 33). \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/ s41557-020-0481-9. \n\nReceived: 21 July 2019; Accepted: 1 May 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Erisman, J. W., Sutton, M. A., Galloway, J., Klimont, Z. & Winiwarter, W. How a century of ammonia synthesis changed the world. Nat. Geosci. 1, 636–639 (2008). \n2.\t Barzagli, F., Mani, F. & Peruzzini, M. From greenhouse gas to feedstock: formation of ammonium carbamate from $\\mathrm{CO}_{2}$ and $\\mathrm{NH}_{3}$ in organic solvents and its catalytic conversion into urea under mild conditions. Green Chem. 13, 1267–1274 (2011). \n3.\t Pérez-Fortes, M., Bocin-Dumitriu, A. & Tzimas, E. $\\mathrm{CO}_{2}$ utilization pathways: techno-economic assessment and market opportunities. Energy Procedia 63, 7968–7975 (2014). \n4.\t Giddey, S., Badwal, S. P. S. & Kulkarni, A. Review of electrochemical ammonia production technologies and materials. Int. J. Hydrog. Energy 38, 14576–14594 (2013). \n5.\t Service, R. F. Chemistry. New recipe produces ammonia from air, water, and sunlight. Science 345, 610 (2014). \n6.\t Chen, C. et al. B–N pairs enriched defective carbon nanosheets for ammonia synthesis with high efficiency. Small 15, 1805029 (2019). \n7.\t Licht, S. et al. Ammonia synthesis by $\\Nu_{2}$ and steam electrolysis in molten hydroxide suspensions of nanoscale $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ . Science 345, 637–640 (2014). \n8.\t Shi, M. M. et al. Au sub-nanoclusters on $\\mathrm{TiO}_{2}$ toward highly efficient and selective electrocatalyst for $\\Nu_{2}$ conversion to $\\mathrm{NH}_{3}$ at ambient conditions. Adv. Mater. 29, 1606550 (2017). \n9.\t Bao, D. et al. Electrochemical reduction of $\\mathrm{N}_{2}$ under ambient conditions for artificial $\\Nu_{2}$ fixation and renewable energy storage using $\\mathrm{N}_{2}/\\mathrm{NH}_{3}$ cycle. Adv. Mater. 29, 1604799 (2017). \n10.\tChen, G. F. et al. Ammonia electrosynthesis with high selectivity under ambient conditions via a $\\mathrm{Li^{+}}$ incorporation strategy. J. Am. Chem. Soc. 139, 9771–9774 (2017). \n11.\tLi, S. J. et al. Amorphizing of Au nanoparticles by $\\mathrm{CeO_{x}}$ –RGO hybrid support towards highly efficient electrocatalyst for $\\mathrm{N}_{2}$ reduction under ambient conditions. Adv. Mater. 29, 1700001 (2017). \n12.\tChen, S. et al. Electrocatalytic synthesis of ammonia at room temperature and atmospheric pressure from water and nitrogen on a carbon-nanotube-based electrocatalyst. Angew. Chem. Int. Ed. 56, 2699–2703 (2017). \n13.\tLan, R., Irvine, J. T. & Tao, S. Synthesis of ammonia directly from air and water at ambient temperature and pressure. Sci. Rep. 3, 1145 (2013). \n14.\tvan der Ham, C. J., Koper, M. T. & Hetterscheid, D. G. Challenges in reduction of dinitrogen by proton and electron transfer. Chem. Soc. Rev. 43, 5183–5191 (2014). \n15.\tGuo, C., Ran, J., Vasileff, A. & Qiao, S. Z. Rational design of electrocatalysts and photo(electro)catalysts for nitrogen reduction to ammonia $\\mathrm{(NH}_{3}^{\\cdot},$ under ambient conditions. Energy Environ. Sci. 11, 45–56 (2018). \n16.\tFoster, S. L. et al. Catalysts for nitrogen reduction to ammonia. Nat. Catal. 1, 490 (2018). \n17.\t Li, H., Shang, J., Ai, Z. & Zhang, L. Efficient visible light nitrogen fixation with BiOBr nanosheets of oxygen vacancies on the exposed {001} facets. J. Am. Chem. Soc. 137, 6393–6399 (2015). \n18.\tWang, S. et al. Light-switchable oxygen vacancies in ultrafine $\\mathrm{\\Bi_{5}O_{7}B r}$ nanotubes for boosting solar-driven nitrogen fixation in pure water. Adv. Mater. 29, 1701774 (2017). \n19.\tZheng, J. et al. Photoelectrochemical synthesis of ammonia on the aerophilic-hydrophilic heterostructure with $37.8\\%$ efficiency. Chem 5, 617–633 (2019). \n20.\tWang, J. et al. Ambient ammonia synthesis via palladium-catalyzed electrohydrogenation of dinitrogen at low overpotential. Nat. Commun. 9, 1795 (2018). \n21.\tYao, Y., Zhu, S., Wang, H., Li, H. & Shao, M. A spectroscopic study on the nitrogen electrochemical reduction reaction on gold and platinum surfaces. J. Am. Chem. Soc. 140, 1496–1501 (2018). \n22.\tGeng, Z. et al. Achieving a record-high yield rate of 120.9 for $\\mathrm{N}_{2}$ electrochemical reduction over Ru single-atom catalysts. Adv. Mater. 30, 1803498 (2018). \n23.\tYu, X. et al. Boron-doped graphene for electrocatalytic $\\Nu_{2}$ reduction. Joule 2, 1610–1622 (2018). \n24.\tInagaki, F., Matsumoto, C., Iwata, T. & Mukai, C. $\\mathrm{CO}_{2}$ -selective absorbents in air: reverse lipid bilayer structure forming neutral carbamic acid in water without hydration. J. Am. Chem. Soc. 139, 4639–4642 (2017). \n25.\tMcDonald, T. M., D’Alessandro, D. M., Krishna, R. & Long, J. R. Enhanced carbon dioxide capture upon incorporation of $N,N^{\\prime}$ -dimethylethylenediamine in the metal–organic framework CuBTTri. Chem. Sci. 2, 2022–2028 (2011). \n26.\t Flaig, R. W. et al. The chemistry of $\\mathrm{CO}_{2}$ capture in an amine-functionalized metal–organic framework under dry and humid conditions. J. Am. Chem. Soc. 139, 12125–12128 (2017). \n27.\tPlanas, N. et al. The mechanism of carbon dioxide adsorption in an alkylamine-functionalized metal–organic framework. J. Am. Chem. Soc. 135, 7402–7405 (2013). \n28.\tZhu, D. D., Liu, J. L. & Qiao, S. Z. Recent advances in inorganic heterogeneous electrocatalysts for reduction of carbon dioxide. Adv. Mater. 28, 3423–3452 (2016). \n29.\tJouny, M., Luc, W. & Jiao, F. High-rate electroreduction of carbon monoxide to multi-carbon products. Nat. Catal. 1, 748–755 (2018). \n30.\tLuc, W. et al. Two-dimensional copper nanosheets for electrochemical reduction of carbon monoxide to acetate. Nat. Catal. 2, 423–430 (2019). \n31.\tJouny, M., Hutchings, G. S. & Jiao, F. Carbon monoxide electroreduction as an emerging platform for carbon utilization. Nat. Catal. 2, 1062–1070 (2019). \n32.\tJouny, M. et al. Formation of carbon–nitrogen bonds in carbon monoxide electrolysis. Nat. Chem. 11, 846–851 (2019). \n33.\tComer, B. M. et al. The role of adventitious carbon in photo-catalytic nitrogen fixation by titania. J. Am. Chem. Soc. 140, 15157–15160 (2018). \n34.\tSrinivas, B., Kumari, V. D., Sadanandam, G., Subrahmanyam, C. H. M. & De, B. R. Photocatalytic synthesis of urea from in situ generated ammonia and carbon dioxide. Photochem. Photobiol. 88, 233–241 (2012). \n35.\tWang, J. et al. A bifunctional catalyst for efficient dehydrogenation and electro-oxidation of hydrazine. J. Mater. Chem. A 6, 18050–18056 (2018). \n36.\tHu, L. et al. Ambient electrochemical ammonia synthesis with high selectivity on Fe/Fe oxide catalyst. ACS Catal. 8, 9312–9319 (2018). \n37.\tComer, B. M. et al. Prospects and challenges for solar fertilizers. Joule 3, 1578–1605 (2019). \n38.\tMedford, A. J. et al. Assessing the reliability of calculated catalytic ammonia synthesis rates. Science 345, 197–200 (2014). \n39.\tDuyar, M. S. et al. A highly active molybdenum phosphide catalyst for methanol synthesis from CO and $\\mathrm{CO}_{2}$ . Angew. Chem. Int. Ed. 130, 15265–15270 (2018). \n40.\tAndersen, M. et al. Scaling-relation-based analysis of bifunctional catalysis: the case for homogeneous bimetallic alloys. ACS Catal. 7, 3960–3967 (2017). \n41.\tYan, D., Li, H., Chen, C., Zou, Y. & Wang, S. Defect engineering strategies for nitrogen reduction reactions under ambient conditions. Small Methods 3, 1800331 (2018). \n42.\t Wan, J. et al. Defect effects on $\\mathrm{TiO}_{2}$ nanosheets: stabilizing single atomic site Au and promoting catalytic properties. Adv. Mater. 30, 1705369 (2018). \n43.\tQiu, Y. et al. BCC-phased PdCu alloy as a highly active electrocatalyst for hydrogen oxidation in alkaline electrolytes. J. Am. Chem. Soc. 140, \n16580–16588 (2018). \n44.\tShi, M. M. et al. Anchoring PdCu amorphous nanocluster on graphene for electrochemical reduction of $\\Nu_{2}$ to $\\mathrm{NH}_{3}$ under ambient conditions in aqueous solution. Adv. Energy Mater. 8, 1800124 (2018). \n45.\tRahmatullah, M. & Boyde, T. R. C. Improvements in the determination of urea using diacetyl monoxime; methods with and without deproteinisation. Clin. Chim. Acta 107, 3–9 (1980). \n46.\tMa, S. et al. Electroreduction of carbon dioxide to hydrocarbons using bimetallic Cu-Pd catalysts with different mixing patterns. J. Am. Chem. Soc. \n139, 47–50 (2016). \n47.\tHoang, T. T. H. et al. Nanoporous copper-silver alloys by additive-controlled electrodeposition for the selective electroreduction of $\\mathrm{CO}_{2}$ to ethylene and ethanol. J. Am. Chem. Soc. 140, 5791–5797 (2018). \n48.\t Ma, S., Lan, Y., Perez, G. M. J., Moniri, S. & Kenis, P. J. A. Silver supported on titania as an active catalyst for electrochemical carbon dioxide reduction. ChemSusChem 7, 866–874 (2014). \n49.\tCook, R. L. & Sammells, A. F. Ambient temperature gas phase electrochemical nitrogen reduction to ammonia at ruthenium/solid polymer electrolyte interface. Catal. Lett. 1, 345–349 (1988). \n50.\tBilly, J. T. & Co, A. C. Experimental parameters influencing hydrocarbon selectivity during the electrochemical conversion of $\\mathrm{CO}_{2}$ . ACS Catal. 7, \n8467–8479 (2017). \n51.\t Albo, J. & Irabien, A. $\\mathrm{Cu}_{2}\\mathrm{O}$ -loaded gas diffusion electrodes for the continuous electrochemical reduction of $\\mathrm{CO}_{2}$ to methanol. J. Catal. 343, 232–239 (2016). \n52.\tWang, H. et al. Selective electrochemical reduction of nitrogen to ammonia by adjusting the three-phase interface. Research 2019, 1401209 (2019). \n53.\tHao, Y. et al. Promoting nitrogen electroreduction to ammonia with bismuth nanocrystals and potassium cations in water. Nat. Catal. 2, 448–456 (2019). \n54.\tCheng, W. R. et al. Lattice-strained metal–organic-framework arrays for bifunctional oxygen electrocatalysis. Nat. Energy 4, 115–122 (2019). \n55.\tColeman, M. M., Lee, K. H., Skrovanek, D. J. & Painter, P. C. Hydrogen bonding in polymers. 4. Infrared temperature studies of a simple polyurethane. Macromolecules 19, 2149–2157 (1986). \n56.\tManivannan, M. & Rajendran, S. Investigation of inhibitive action of urea- $\\cdot Z\\mathrm{n}^{2+}$ system in the corrosion control of carbon steel in sea water. Int. J. Engr. Sci. Technol. 3, 8048–8060 (2011). \n57.\t Buong, W. C., Nor, A. I., Wan, M. Z. W. Y. & Mohd, Z. H. Poly(lactic acid)/ poly(ethylene glycol) polymer nanocomposites: effects of graphene nanoplatelets. Polymers 6, 93–104 (2014). \n58.\tDaramola, M. O., Nicola, W. & Jacob, M. N. Effect of the presence of water-soluble amines on the carbon dioxide $\\left(\\mathrm{CO}_{2}\\right)$ adsorption capacity of amine-grafted poly-succinimide (PSI) adsorbent during $\\mathrm{CO}_{2}$ capture. Energy Procedia 86, 90–105 (2016). \n59.\tNørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n60.\tHonkala, K. et al. Ammonia synthesis from first-principles calculations. Science 307, 555–558 (2005). \n61.\tDuan, H. et al. Molecular nitrogen promotes catalytic hydrodeoxygenation. Nat. Catal. 2, 1078–1087 (2019). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. $\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 \n\n# Methods \n\nMaterials fabrication. The synthesis of $\\mathrm{TiO}_{2}$ nanosheets is described elsewhere42. $\\mathrm{TiO}_{2}$ nanosheets anchored with PdCu alloy nanoparticles were fabricated via the co-reduction of metal precursors by sodium borohydride. Typically, $30\\mathrm{mg}$ of $\\mathrm{TiO}_{2}$ nanosheets was dispersed into $20\\mathrm{ml}$ of distilled water with ultrasonic treatment for $30\\mathrm{min}$ . Then, air in the solution was expelled by argon gas flow. After that, the dissolved $\\mathrm{PdCl}_{2}$ $(3.6\\upmu\\mathrm{mol})$ and $\\mathrm{CuCl}_{2}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O}$ $3.6\\upmu\\mathrm{mol};$ ) were added dropwise to the dispersion of $\\mathrm{TiO}_{2}$ . Subsequently, $50\\mathrm{mg}$ of $\\mathrm{NaBH_{4}}$ in water $(5\\mathrm{ml})$ was added dropwise to the above solution for $30\\mathrm{min}$ . After reaction for another $^{2\\mathrm{h}}$ , the powder obtained was separated with centrifugation and washed with distilled water and ethanol several times, and then dried. More details are in Supplementary Table 1. The $\\mathrm{TiO}_{2}$ nanosheets were thermally treated in a reduction atmosphere (reduction gas contains $10\\mathrm{vol.\\%}$ hydrogen and $90\\mathrm{vol.\\%}$ argon) for $2\\mathrm{h}$ at various temperatures to achieve the fabrication of defective $\\mathrm{TiO}_{2}$ . PdCu alloy anchoring on defective $\\mathrm{TiO}_{2}$ nanosheets was synthesized via the same synthetic procedures as for the fabrication of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ except that the support was defective $\\mathrm{TiO}_{2}$ nanosheets. $\\mathrm{Pd_{1}C u_{\\mathrm{1}}/X C72R}$ was prepared by the same synthetic procedures as well, except XC72R was used as the support. \n\nMaterials characterization. The morphology was analysed by field emission SEM and TEM (FEI Tecnai G2 F20). X-ray diffraction measurements were performed on a D8 ADVANCE X-ray diffractometer (Bruker). The EPR measurements were carried out on a JEOL JES-FA200 spectrometer, and the XPS analysis was conducted with an ESCALAB 250 Xi X-ray photoelectron spectrometer. Diffuse reflectance spectra were acquired using a Cary 5000 spectrophotometer fitted with an integrating sphere attachment from $200{-}800\\mathrm{nm}$ with $\\mathrm{BaSO_{4}}$ as the reference. The Raman spectra of the catalysts were acquired on a Renishaw inVia Raman microscope. The specific surface areas of the catalysts were measured on a JW-BK200C (JWGB Sci. & Tech.) Specific Surface Area and Aperture Analyzer. The gaseous products for electrocatalytic reaction were quantified on a GC-2014C Shimadzu gas chromatograph. The $\\mathrm{^{1}H}$ NMR spectra were measured on an Ascend 600 NMR spectrometer equipped with an ultralow temperature probe. The mass spectra were collected on a GCMS-QP2020NX Shimadzu instrument. \n\nTPD measurements. TPD measurements were carried out on an AutoChem 2920 instrument. For the measurement of $\\Nu_{2}$ -TPD, $150\\mathrm{mg}$ of catalyst powder was placed in a glass tube and pretreated by the He gas flow at $150^{\\circ}\\mathrm{C}$ for 1 h, and then cooled to $50^{\\circ}\\mathrm{C}$ . The adsorption of $\\Nu_{2}$ was conducted in $\\Nu_{2}$ $(99.999\\%)$ ) gas flow for $^{3\\mathrm{h}}$ at $50^{\\circ}\\mathrm{C}$ . After purging with He $(99.999\\%$ ) gas for $0.5\\mathrm{h}$ to remove the residual ${\\mathrm{N}}_{2},$ , the sample was heated from $50^{\\circ}\\mathrm{C}$ to $400^{\\circ}\\mathrm{C}$ at a rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ . The TPD signal was recorded using a MS detector $(m/z=28)$ . The $\\mathrm{CO}_{2}$ -TPD measurement was the same as the measurement of $\\Nu_{2}$ -TPD except that the absorbent was instead $\\mathrm{CO}_{2}\\left(99.999\\%\\right)$ and the TPD signal was recorded using a MS detector $\\scriptstyle(m/z=44)$ . The competitive chemisorptions of $\\Nu_{2}$ and $\\mathrm{CO}_{2}$ were measured with the absorbent of mixed $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ (1:1, vol./vol.). The TPD signal was recorded using a MS detector and the data of $m/z=28$ and $m/z=44$ were collected. \n\nOperando SR-FTIR measurements. Operando SR-FTIR measurements were made at the infrared beamline BL01B of the National Synchrotron Radiation Laboratory (NSRL, China) through a homemade top-plate cell reflection infrared set-up with a $\\boldsymbol{Z}\\mathrm{n}\\mathrm{S}\\mathrm{e}$ crystal as the infrared transmission window (cut-off energy of $\\sim625\\mathrm{cm}^{-1}$ ).This end station was equipped with an FTIR spectrometer (Bruker $66\\mathrm{v}/\\mathrm{s})$ with a KBr beam splitter and various detectors (herein a liquid nitrogen cooled mercury cadmium telluride detector was used) coupled with an infrared microscope (Bruker Hyperion 3000) with a $\\times16$ objective, and could provide infrared spectroscopy measurement with a broad range of $15{-}4{,}000\\mathrm{cm}^{-1}$ as well as a high spectral resolution of $0.25\\mathrm{cm}^{-1}$ . The catalyst electrode was tightly pressed against the $\\mathrm{ZnSe}$ crystal window with a micrometre-scale gap in order to reduce the loss of infrared light. To ensure the quality of the obtained SR-FTIR spectra, the apparatus adopted a reflection mode with a vertical incidence of infrared light. Each infrared absorption spectrum was acquired by averaging 514 scans at a resolution of $2\\mathrm{cm}^{-1}$ . All infrared spectral acquisitions were carried out after a constant potential was applied to the electrode for $20\\mathrm{min}$ . The background spectrum of the catalyst electrode was acquired at an open-circuit voltage before each systemic measurement, and the measured potential ranges of the electrocoupling reaction were $-0.15$ to $-0.45\\mathrm{V}$ with an interval of $0.05\\mathrm{V}.$ . The in situ electrochemical cell is shown in Supplementary Fig. 34. \n\nElectrochemical characterization. The electrochemical test in the H cell was carried out on a CHI 660E electrochemical station in a three-electrode system. The pretreated Nafion 117 membrane (Dupont) served as the separator, and the electrolyte used in this work was $0.1\\mathrm{M}\\mathrm{KHCO}_{3}$ . Catalyst $\\left(2\\mathrm{mg}\\right)$ was dispersed in $950\\upmu\\mathrm{l}$ of ethanol and $50\\upmu\\mathrm{l}$ of Nafion $5\\mathrm{wt\\%}$ aqueous solution) with sonication for $30\\mathrm{min}$ to form a homogenous ink. Then, $100\\upmu\\mathrm{l}$ of catalyst ink was loaded onto a piece of carbon paper (Hesen) and dried naturally to obtain the working electrode; the geometric area of the working electrode was $1\\times1\\mathrm{cm}^{2}$ , and the catalyst loading was $0.2\\mathrm{mg}\\mathrm{cm}^{-2}$ . The reference electrode was an $\\mathrm{Ag/AgCl}$ electrode containing saturated KCl solution, and a carbon rod served as the counter electrode. Before electrochemical tests, the cathode part of the electrolyte was purged with the \n\ncorresponding gases for pre-saturation. After that, the flow rate was maintained at $30\\mathrm{ml}\\mathrm{min}^{-1}$ during the catalytic process. The provided applied potentials were against a $\\mathrm{Ag/AgCl}$ reference electrode (saturated KCl solution) and converted to the RHE reference scale using $E_{\\mathrm{RHE}}=E_{\\mathrm{Ag/AgCl}}+0.0591\\times\\mathrm{pH}+0.197$ . The $\\mathsf{p H}$ value was 6.8 for $\\mathrm{CO}_{2}$ -saturated electrolyte or $\\mathrm{N}_{2^{-}}$ and $\\mathrm{CO}_{2}$ -saturated electrolyte, and 8.3 for the $0.1\\mathrm{M}\\mathrm{KHCO}_{3}$ aqueous solution saturated solely with $\\Nu_{2}$ . The feeding gas contained $50\\mathrm{vol.}\\%\\mathrm{N}_{2}$ and $50\\mathrm{vol.}\\%\\mathrm{CO}_{2}$ for electrochemical urea synthesis, and this gas ratio was also adopted for isotope-labelling experiments and operando SR-FTIR measurements. \n\nThe flow cell configuration is depicted in Supplementary Fig. 21, consisting of a working electrode, anion exchange membrane and nickel foam anode. Catalyst $(0.8\\mathrm{mg})$ was deposited on the top side of carbon paper with a microporous layer. The combined catalyst and working electrode, anion exchange membrane and nickel anode were then positioned and clamped together using polytetrafluoroethylene (PTFE) spacers such that a liquid electrolyte could be introduced into the chambers between the anode and membrane, and between the membrane and the cathode. In the cathode part, a port drilled into the PTFE spacer was presented for an $\\mathrm{Ag/AgCl}$ reference electrode to be positioned a specific distance from the working electrode. For a typical electrochemical test in a flow cell, the electrolyte $(0.1\\mathrm{{MKHCO}_{3}}$ , $\\mathrm{100ml}$ was pre-saturated with $\\mathrm{N}_{2}$ or/ and $\\mathrm{CO}_{2}$ at a rate of $50\\mathrm{ml}\\mathrm{min}^{-1}$ for $30\\mathrm{min}$ the electrolyte was circulated through the cathode part and returned back to the reservoir using peristaltic pumps. The electrolyte flow was maintained at $10\\mathrm{ml}\\mathrm{min}^{-1}$ . The gas flow rate was kept constant at $30\\mathrm{ml}\\mathrm{min}^{-1}$ using a mass flow controller during the whole electrocatalytic process. The gas flow with the same rate was also circulated in the gas flow channel, and the outlet was linked to a GC instrument for the quantification of gaseous products. The electrolyte in the reservoir was extracted for further identification and quantification after the electrochemical test. \n\nProduct quantification and identification. The identification and quantification of urea and $\\mathrm{NH}_{3}$ were achieved by NMR spectroscopy. For the identification and quantification of $\\mathrm{NH}_{3}$ from NRR, the extracted electrolyte was acidized to reach the $\\mathrm{\\ttpH}$ value of ${\\sim}3$ by addition of an appropriate amount of $0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4},$ and a known amount of dimethylsulfoxide- $\\mathbf{\\cdotd}_{6}$ was used as an internal standard. The NMR spectrum was collected on an Ascend 600 NMR spectrometer equipped with an ultralow temperature probe. The presented data is the accumulated result of 2,048 scans. The full representative NMR spectra are displayed in Supplementary Fig. 22. The same conditions were adapted to the measurements of standard solutions. \n\nFor the identification and quantification of urea and $\\mathrm{NH}_{3}$ simultaneously from the electrocatalytic coupling reactions, the slow hydrolysis of urea to release $\\mathrm{NH}_{3}$ in an acid environment must be considered due to the relatively long time taken for data acquisition. The extracted electrolyte was initially subjected to the identification and quantification of urea without any post-processing. And then, the product urea was reacted with diacetyl monoxime to generate an acid-resistant chemical. Subsequently, the $\\mathrm{\\pH}$ value of this solution was adjusted to ${\\sim}3$ by addition of appropriate amounts of alkaline solution, and the ammonia in the electrolyte was identified and quantified. The isotope-labelled products possessed obvious differences in peak positions and characterizations compared to the unmarked ones, as illustrated in Supplementary Figs. 35 and 36. Based on this, the products of urea and ammonia from the electrocatalytic process could be identified. The concentration of urea or ammonia exhibits a linear relationship with the integral area of the characteristic peaks; thus the concentration of the products could be calculated via the equation of the calibration curves. \n\nThe concentration of urea in the electrolyte was also measured by the diacetyl monoxime method. With heating, the reaction between the diacetyl monoxime and urea in acid generated a pink product and reached the highest absorbance at $525\\mathrm{nm}$ (ref. 45). There was a linear relationship between the absorbance and the concentration of urea, and the concentration of urea after the electrochemical test was acquired according to the calibration curve (Supplementary Fig. 37). The concentrations of $\\mathrm{NH}_{3}$ and $\\mathrm{N}_{2}\\mathrm{H}_{4}$ were quantified by the indophenol blue method6 and the method of Watt and $\\mathrm{Chrisp}^{62}$ , respectively, as seen in Supplementary Figs. 38 and 39. \n\nThe Faradic efficiency is the ratio of the number of electrons transferred for the formation of urea to the total amount of electricity that flows through the circuit. Assuming six electrons were needed to form one urea $\\mathrm{(CO(NH_{2})_{2})}$ molecule, the Faradic efficiency for urea synthesis (FE) could be calculated as follows: $\\mathrm{FE}(\\%)=(6\\times F\\times C\\times V)/(60.06\\times Q)\\times100$ aInd the amount of urea (A) was calculated by the equation, $\\boldsymbol{A}=\\boldsymbol{C}\\times\\boldsymbol{V}$ wIhere $F$ is the Faraday constant, $Q$ is the electric quantity, $C$ is the concentration of generated urea and $V$ is the volume of the electrolyte. The formation rate of urea was averaged by the time, and the presented urea formation rate was the average value within the time frame of the tests. \n\nIsotope-labelling product quantification and identification. The isotope-labelling experiments for the identification of the products were carried out with labelled gases as feedstocks63 ( $^{15}\\mathrm{N}_{2}98\\%$ enrichment, $^{13}\\mathrm{CO}_{2}99\\%$ enrichment; Sigma). The electrochemical ammonia synthesis was performed on $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}–400$ under nitrogen gas $^{14}\\mathrm{N}_{2}$ or $^{15}\\mathrm{N}_{2})$ in a flow cell. The yield rate of ammonia was $2.91\\mathrm{mmolg^{-1}h^{-1}}$ at $-0.4\\mathrm{V}$ versus RHE for $^{14}\\mathrm{N}_{2},$ and a comparable value of $2.89\\mathrm{mmolg^{-1}h^{-1}}$ was obtained for $^{15}\\mathrm{N}_{2}$ (Supplementary Fig. 35). The yielded ammonia exhibits distinguishing characteristics in the NMR spectra (triplet peaks for $^{14}\\mathrm{N}\\mathrm{H}_{3}$ and doublet peaks for $^{15}\\mathrm{N}\\mathrm{H}_{3})$ 6. Moreover, a negligible yield rate $(0.05\\mathrm{mmolg^{-1}h^{-1}})$ was obtained in an Ar atmosphere. The results indicated the high electrocatalytic activity of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}$ -400 towards the NRR and confirmed that ammonia was produced by electrocatalysis rather than contamination. \n\nThe tests were conducted with $\\mathrm{N}_{2}$ and $\\mathrm{CO}_{2}$ as feedstocks, and the concentrations of ammonia and urea were both quantified by NMR. The catalyst exhibited very similar catalytic activity and selectivity for urea synthesis (relatively low yield for ammonia) in $^{12}\\mathrm{CO}_{2}$ and $^{14}\\mathrm{N}_{2}$ or $^{13}{\\mathrm{CO}}_{2}$ and $^{15}\\mathrm{N}_{2},$ and the isotope-labelled product could be intuitively distinguished due to the differences in peaks. The control experiments further proved the occurrence of electrochemical urea synthesis (Supplementary Fig. 36). Equally important, the product urea was identified by GC-MS. Trimethylsilyloxypyrimidine was obtained by derivatization (Fig. 2f) and subjected to GC-MS characterization due to the low decomposition temperature of urea. Compared with the main fragments of 153 and 168 for the unmarked product, the isotope-labelled product displayed main fragments of 156 and 171, revealing that the carbon and nitrogen in the product were both derived from gaseous molecules and that the carbon was barely derived from the bicarbonate electrolyte. \n\nThe urea formation rates quantified by the diacetyl monoxime method are comparable to those quantified by NMR (Supplementary Fig. 40), indicating the applicability of quantification by these two methods. Moreover, the electrochemical tests were carried out in a H cell with the addition of 100 ppm $\\mathrm{NH_{4}H C O_{3}},$ and $\\mathrm{CO}_{2}$ alone served as the feeding gas; however, only negligible amounts of urea were obtained, indicating that the generated urea was not derived from ammonia by an electrocatalytic process or contamination. Additionally, when the ammonium salt was replaced by $\\mathrm{\\Pi{HCOONH_{4}}}$ or $\\mathrm{CH_{3}C O O N H_{4}}$ and the feeding gas was substituted by ${\\bf N}_{2},$ only trace amounts of urea were obtained, thus excluding the generation of formic acid or acetate as an intermediate process in the urea synthesis (Supplementary Fig. 41). Electrochemical stability is crucial for the further application of electrocatalysts. The urea formation rate and Faradic efficiency remained stable over six cycles of electrocatalysis (Supplementary Fig. 42) in the H cell, and there was no obvious decay of the current density during electrocatalysis for 12 h (Supplementary Fig. 43), which indicated the high electrochemical stability of $\\mathrm{Pd_{1}C u_{1}/T i O_{2}}.$ 400. \n\nMass spectra measurement. After the electrochemical test, $600\\upmu\\mathrm{l}$ of electrolyte was extracted, followed by addition of $20\\upmu\\mathrm{l}$ of 1,1,3,3-tetramethoxypropane aqueous solution $(0.3\\mathrm{moll^{-1}})$ and $40\\upmu\\mathrm{l}$ of diluted hydrochloric acid $(250\\mathrm{gl^{-1}})$ . Then, the mixture reacted on the shake bed for 1 h at room temperature. The above product was then freeze-dried. After that, $200\\upmu\\mathrm{l}$ of anhydrous acetonitrile was added into the reactor, followed by the addition of $20\\upmu\\mathrm{l}$ of $N$ -methyl-N(trimethylsilyl)trifluoroacetamide. After reaction for another $\\boldsymbol{1\\mathrm{h}}$ at $60^{\\circ}\\mathrm{C},$ the final product of 2-trimethylsilyloxypyrimidine was analysed on a GCMS-QP2020 NX spectrometer (Shimadzu). \n\nComputational method. The DFT computations were performed via the plane-wave technique implemented in the Vienna Ab initio Simulation Package $\\mathrm{(VASP)^{64}}$ . The ion–electron interaction was described using the projector-augmented plane-wave (PAW) approach65. The generalized gradient approximation (GGA) expressed by the Perdew–Burke–Ernzerhof (PBE) functional66 and a $460\\mathrm{eV}$ cut-off for the plane-wave basis set were adopted in all computations. We created a $4\\times4$ supercell to simulate the PdCu surfaces and adopted a vacuum length of $20\\textup{\\AA}$ in the $z$ direction to avoid the longitudinal interlayer interaction. The geometry optimizations were performed using the conjugated gradient method, and the convergence threshold was set to be $10^{-5}\\mathrm{eV}$ in energy and $10^{-4}\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ in force. The Brillouin zone was represented by a Monkhorst–Pack special k-point mesh of $4\\times4\\times1$ for geometrical optimizations. The climbing image nudged elastic band $(\\mathrm{CI-NEB})^{67}$ method was implemented to simulate the $\\mathrm{^{*}N C O N^{*}}$ intermediate formation pathway. The deformation charge densities were performed via the following equation: \n\nwIhere the $\\rho_{\\mathrm{total}},\\rho_{\\mathrm{Cu}}$ and $\\rho_{\\mathrm{pd}}$ represent the charge densities of the PdCu system, Cu and Pd, respectively. The free energy of each reduction step can be obtained at zero bias potential using, \n\n$$\n\\Delta G=\\Delta E+\\Delta E_{\\mathrm{ZPE}}\\stackrel{\\sim}{+}T\\Delta S\n$$ \n\nwhere $\\Delta E$ is the reaction energy, $\\Delta E_{\\mathrm{zpE}}$ is the difference in zero-point energies, $T$ is the temperature (298.15 K) and ΔS is the reaction entropy. For absorbates, $E_{\\mathrm{ZPE}}$ and S were determined by vibrational frequencies calculations with a low-frequency cut-off of $\\sim45\\mathrm{cm}^{-1}$ , where all $3N$ degrees of freedom were treated as harmonic vibrational motions without considering contributions from the slab. The gaseous molecules were treated as an ideal gas, and their thermochemistry data were taken from the National Institute of Standards and Technology (NIST) database68. \n\n# Data availability \n\nAll data generated or analysed during this study are included in this Article (and its Supplementary Information). Data for Figs. 1–5 are available as source data with this paper. \n\n# Code availability \n\nThe computational codes used in the current work are available from the corresponding author on reasonable request. \n\n# References \n\n62.\tWatt, G. W. & Chrisp, J. D. Spectrophotometric method for determination of hydrazine. Anal. Chem. 24, 2006–2008 (1952). \n63.\tAndersen, S. Z. et al. A rigorous electrochemical ammonia synthesis protocol with quantitative isotope measurements. Nature 570, 504–508 (2019). \n64.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169 (1996). \n65.\tBlöchl, P. E. Projector augmented-wave method. Phys. Rev. B 24, 17953 (1994). \n66.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865 (1996). \n67.\tHenkelman, G., Uberuaga, B. P. & Jónsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000). \n68.\tComputational Chemistry Comparison and Benchmark Database (NIST, accessed 2016); http://cccbdb.nist.gov/ \n\n# Acknowledgements \n\nWe thank the National Natural Science Foundation of China (grant no. 21573066, 21825201, U1932212, U19A2017) and ARC DP170102320. \n\n# Author contributions \n\nS.W. conceived the project. C.C. and Y.Z. carried out most of the experiments and co-wrote the manuscript. X.Z., X.W., Y.L. and J.C. performed the theoretical calculations. Q.L., H.S., X.Z. and W.C. carried out the isotope-labelling operando SR-FTIR measurements. L.Z., L.T., H.L., Q.L., S.D., T.L., D.Y. and C.X. conducted part of the synthesis of catalysts and characterizations. Y.Z., Y.W., R.C. and J.H. analysed the data. H.L., J.L., J.C. and M.D. performed the partial characterizations of materials. K.C. and C.L. performed the collection and analysis of NMR spectra. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41557-020-0481-9. \n\nCorrespondence and requests for materials should be addressed to Y.L., J.C., Q.L., J.C. \nor S.W. \n\nReprints and permissions information is available at www.nature.com/reprints. " + }, + { + "id": "10.1038_s41467-020-16848-8", + "DOI": "10.1038/s41467-020-16848-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-16848-8", + "Relative Dir Path": "mds/10.1038_s41467-020-16848-8", + "Article Title": "Engineering unsymmetrically coordinated Cu-S1N3 single atom sites with enhanced oxygen reduction activity", + "Authors": "Shang, HS; Zhou, XY; Dong, JC; Li, A; Zhao, X; Liu, QH; Lin, Y; Pei, JJ; Li, Z; Jiang, ZL; Zhou, DN; Zheng, LR; Wang, Y; Zhou, J; Yang, ZK; Cao, R; Sarangi, R; Sun, TT; Yang, X; Zheng, XS; Yan, WS; Zhuang, ZB; Li, J; Chen, WX; Wang, DS; Zhang, JT; Li, YD", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Atomic interface regulation is thought to be an efficient method to adjust the performance of single atom catalysts. Herein, a practical strategy was reported to rationally design single copper atoms coordinated with both sulfur and nitrogen atoms in metal-organic framework derived hierarchically porous carbon (S-Cu-ISA/SNC). The atomic interface configuration of the copper site in S-Cu-ISA/SNC is detected to be an unsymmetrically arranged Cu-S1N3 moiety. The catalyst exhibits excellent oxygen reduction reaction activity with a half-wave potential of 0.918V vs. RHE. Additionally, through in situ X-ray absorption fine structure tests, we discover that the low-valent Cuprous-S1N3 moiety acts as an active center during the oxygen reduction process. Our discovery provides a universal scheme for the controllable synthesis and performance regulation of single metal atom catalysts toward energy applications.", + "Times Cited, WoS Core": 688, + "Times Cited, All Databases": 705, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000542988800003", + "Markdown": "# Engineering unsymmetrically coordinated Cu-S1N3 single atom sites with enhanced oxygen reduction activity \n\nHuishan Shang1,13, Xiangyi Zhou2,13, Juncai Dong 3,13, Ang Li4, Xu Zhao5, Qinghua Liu 5, Yue Lin $\\textcircled{1}$ 6, Jiajing Pei7, Zhi Li8, Zhuoli Jiang1, Danni Zhou1, Lirong Zheng3, Yu Wang 9, Jing Zhou9, Zhengkun Yang10, Rui Cao11, Ritimukta Sarangi11, Tingting Sun12, Xin Yang2, Xusheng Zheng5, Wensheng Yan $\\textcircled{1}$ 5, Zhongbin Zhuang 7, Jia Li 2✉, Wenxing Chen 1✉, Dingsheng Wang 8✉, Jiatao Zhang1✉ & Yadong Li8 \n\nAtomic interface regulation is thought to be an efficient method to adjust the performance of single atom catalysts. Herein, a practical strategy was reported to rationally design single copper atoms coordinated with both sulfur and nitrogen atoms in metal-organic framework derived hierarchically porous carbon $(S-C u-1S A/S N C)$ . The atomic interface configuration of the copper site in $S-C u-1S A/S N C$ is detected to be an unsymmetrically arranged $C u-S_{1}N_{3}$ moiety. The catalyst exhibits excellent oxygen reduction reaction activity with a half-wave potential of 0.918 V vs. RHE. Additionally, through in situ $\\mathsf{X}$ -ray absorption fine structure tests, we discover that the low-valent Cuprous- $S_{1}N_{3}$ moiety acts as an active center during the oxygen reduction process. Our discovery provides a universal scheme for the controllable synthesis and performance regulation of single metal atom catalysts toward energy applications. \n\nTehnqietuideiespvpfeoldroptiwhnietghaopfopaxliydcgvaeatinocnelsdecfotufeofludcteuslr seprasonuvdsitdamiesne anblle-eawie nobeparptgtoyer1ti–ue3s-. To realize energy conversion with highly efficiency, it’s crucial to improve the oxygen reduction reaction (ORR) procedure, among these electrochemical devices4,5. Currently platinum-based materials have been widely used for ORR, but are unfortunately precluded by their rarity and high price6. Although the newly developed catalysts with earth-abundant elements exhibit some fancy properties, the overall performance including activity and durability is still far from satisfactory7–10. Hence, the rational design of ideal oxygen electrode materials with low-cost but high activity and good stability under applied conditions remains a formidable challenge. \n\nDue to the high atomic utilization, single atom catalysts have gained great attention in heterogeneous catalysis, and significantly, they provide new horizons for the discovery of innovative materials to energy applications11–20. Especially, both theoretical and experimental explorations have suggested that isolated single metal- $\\mathbf{\\cdotN_{x}}$ $(\\mathrm{M}{-}\\mathrm{N}_{\\mathrm{x}})$ modified carbon-based materials can serve as desirable oxygen electrocatalysts with promising performance21–29. Particularly, density functional theory (DFT) calculations demonstrate the standard symmetrical planar fourcoordinated structure (denoted as $\\mathrm{M}{\\cdot}\\mathrm{N}_{4}$ moiety) might serve as the most favorable catalytic site for $\\mathrm{M}{\\cdot}\\mathrm{N}_{\\mathrm{x}}$ catalysts, seemingly supported by plenty of experimental results30–33. But some recent researches also point out that for the $\\mathrm{M}{\\cdot}\\mathrm{N}_{4}$ moiety, the large electronegativity of the symmetrical neighboring nitrogen atoms around the metal site would result in unsuitable free energy for adsorption the intermediate products34,35. Obviously, the nonoptimal adsorption of the ORR intermediates badly decreases the kinetic activity and hampers the performance. As a solution to overcome the obstacles, the adsorption strength of ORR intermediates in the active sites could be modified by adjusting the interface configuration of the central metal atoms to reduce the potential barriers, which results in boosted catalytic activity36,37. Due to the comparative weak electronegativity, sulfur-permeating seems to be an attractive method to adjust the electronic structures of the active sites, realizing the improvement of ORR performance38,39. Conventionally, the alien sulfur atoms are anchored in the carbon matrix surrounded by C or $\\mathrm{\\DeltaN}$ atoms, separated from the metal centers40–43. This regulation type of sulfur species can tune and enhance the kinetic activity of the M$\\mathrm{N}_{4}$ site by adjusting electron-withdrawing/donating properties. However, in this situation, the activity modification by the doped sulfur is indirect and limited. What about the direct engagement of metal and sulfur atoms? It means that at least one nitrogen atom in the symmetrical $\\mathrm{M}{\\cdot}\\mathrm{N}_{4}$ moiety has to be kicked off by sulfur invaders. Will the adjacent pairs of metal and sulfur to construct an unsymmetrical atomic interface to produce boosted effects for ORR? As far as we know, few reports have addressed this question44–46. \n\nHerein, we developed a hierarchically porous carbon based single copper atom catalyst toward ORR, by rationally controlling the unsymmetrical interface structure of central metal atoms, in which $\\mathtt{C u}$ was directly bonded with both sulfur and nitrogen atoms (denoted as S-Cu-ISA/SNC). The engineered $\\mathrm{S-Cu-I\\bar{S}A/}$ SNC demonstrated a half-wave potential of $\\bar{0}.918\\mathrm{V}$ vs. RHE in alkaline media, which reflected its boosted ORR performance. The activity of S-Cu-ISA/SNC compared to related materials follows the trend: S-Cu-ISA/SNC (single-atom $\\mathrm{Cu-S}_{1}\\mathrm{N}_{3}$ supported on N and S co-doped carbon polyhedron) ${\\tt>}\\mathrm{Cu}$ -ISA/SNC (single-atom $\\mathrm{Cu-N_{4}}$ supported on $\\mathrm{~N~}$ and S co-doped carbon polyhedron) ${\\tt>}\\mathrm{Cu}$ -ISA/NC (single-atom $\\mathrm{Cu-N_{4}}$ supported on N doped carbon polyhedron) ${\\mathrm{>Pt/C}}$ . Moreover, S-Cu-ISA/SNC displayed excellent stability with no obvious current decay after long-term ORR test. X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) revealed that the outstanding ORR activity originated from the formation of the unsymmetrical $\\mathrm{Cu}{-S_{1}}\\mathrm{N}_{3}$ atomic interface in the carbon matrix, and we also discovered that low-valent Cu $(+1)$ species worked as active sites for ORR. Furthermore, this strategy of atomic interface engineering could be used to other metals (Mn, Fe, Co, $\\mathrm{Ni,}$ etc.). \n\n# Results \n\nSynthesis and morphology characterizations of S-Cu-ISA/SNC. The sample was prepared through a three-step process (Supplementary Fig. 1). In step one, zeolitic imidazolate frameworks (ZIF-8) were adopted as molecular-scale cages to absorb and encapsulate the copper precursor. Typically, $\\mathrm{Cu}(\\mathsf{a c a c})_{2}$ was mixed with the precursors of ZIF-8 $(Z\\mathrm{n}^{2+}$ and 2-methylimidazole), and through a self-assembly process, $\\mathrm{Cu}(\\mathsf{a c a c})_{2}$ were committed to the ZIF-8 cages (Cu-ZIF-8). In the second step, Cu-ZIF-8 and sulfur powder were jointly dispersed in carbon tetrachloride $\\mathrm{(CCl_{4})}$ and then dried by stirring, ensuring the sulfur was absorbed on the surface of Cu-ZIF-8 powder (labeled as S-Cu-ZIF-8, Supplementary Figs. 2 and 3). In the final step, $S\\mathrm{-Cu}$ -ISA/SNC was obtained after the pyrolyzation of the S-Cu-ZIF-8 at $950^{\\circ}\\mathrm{C}$ under Ar atmosphere. It was necessary to noted that the formed metallic zinc was evaporated $(>907^{\\circ}\\mathrm{C})$ and meanwhile sulfur permeated in the ZIF-8 frameworks during pyrolysis47,48. Cu-ISA/SNC (S was separated from $\\mathrm{Cu}^{\\mathrm{\\cdot}}$ ), Cu-ISA/NC (S free), SNC (S, N comodified carbon) and NC (N-modified carbon) were also prepared as comparison. \n\nThe synthetic samples were characterized by Powder X-ray diffraction (PXRD) patterns and Raman spectra (Supplementary Fig. 4). The results indicated that the ZIF-8 derived carbon frameworks were poorly crystallized after pyrolysis and also implied that plenty of defects existed in the carbon substrate, which was favorable for the anchoring of isolated metal atoms49. The morphology of S-Cu-ISA/SNC was observed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Figure 1a showed that S-Cu-ISA/SNC roughly remained the polyhedral shape, but the surfaces became extremely bumpy. The TEM images (Fig. 1b and Supplementary Fig. 5a) indicated that the obtained sample possessed a highly open porous structure, meanwhile small Cu particles were not detected. The high-resolution transmission electron microscopy image (HRTEM) in Supplementary Fig. 5b told us that graphite carbon layers existed in the porous frameworks, which were beneficial for promoting the conductivity50. $\\Nu_{2}$ adsorptiondesorption isotherms (Supplementary Fig. 6) demonstrated the fairly high specific surface area and the hierarchically porous characteristics of S-Cu-ISA/SNC. Our further in-situ environmental microscopic studies (Supplementary Figs. 7, 8, Supplementary Note. 1 and Supplementary Movies 1-2) suggested that the permeation of sulfur played an important role for etching the carbon frameworks. The hierarchically porous architecture could facilitate the charge and mass transportation for electrochemical reactions51. Energy-dispersive X-ray spectroscopy (EDS) (Fig. 1c and Supplementary Fig. 9) in the scanning transmission electron microscope (STEM) indicated Cu, S and $\\mathrm{\\DeltaN}$ on the support were distributed uniformly. The Cu content in S-Cu-ISA/SNC was 0.73 $\\mathrm{at\\%}$ , according to the ICP-OES results. The monodispersion of Cu could be directly monitored by spherical aberration STEM (Fig. 1d, e and Supplementary Fig. 10). The Cu atoms were confirmed by isolated bright dots in the high-magnification HAADF-STEM image. The sizes of dots were below $2.0\\mathring\\mathrm{A}$ as shown in Supplementary Fig. 11. As elucidated in Fig. 1f, the distance between Cu atoms was more than $0.38\\mathrm{nm}$ , which confirmed that Cu existed in isolated feature in S-Cu-ISA/SNC. Furthermore, the SEM, TEM and HAADF-STEM characterizations of NC, SNC, Cu-ISA/NC and Cu-ISA/SNC were also exhibited, respectively (Supplementary Figs. 12–15). We found that all the S-added samples (S-Cu-ISA/SNC, Cu-ISA/SNC and SNC) displayed etched porous feature, compared to those without sulfur participation (Cu-ISA/NC and NC). Additionally, the $Z\\mathrm{n}$ content in S-Cu-ISA/SNC was as low as $0.028\\ \\mathrm{at\\%}$ according to the ICP-OES analysis, which excluded the possible influence to catalytic performance by the residue Zn species52. \n\n![](images/64c14de89002363ad0b6a9038b75f43e5cf2b974083cc13b7e9e1d7b5b275492.jpg) \nFig. 1 Morphology and composition characterizations of S-Cu-ISA/SNC. a SEM, b TEM and c EDS images of $S-C u-1S A/S N C,$ C (pink), N (green), S (yellow) and Cu (red). d HAADF-STEM image and e the magnified image of S-Cu-ISA/SNC. f The corresponding intensity profiles along the line $x-Y$ in e. \n\nChemical state and atomic structure analysis of S-Cu-ISA/SNC. To probe the electronic and atomic interplay of Cu, S, N and C in S-Cu-ISA/SNC, synchrotron-radiation-based soft XANES was carried out (Supplementary Note. 2)53. The $\\mathbf{L}_{3}$ edge and $\\mathrm{L}_{2}$ edge of Cu XANES in S-Cu-ISA/SNC located at $931.2\\mathrm{eV}$ and $950.9\\mathrm{eV}$ (Fig. 2a). The L-edge position of S-Cu-ISA/SNC was between those of CuPc and CuS, implying the possible formation of Cu-S and $\\mathrm{{Cu-N}}$ bonds, which was consistent with the XPS results (Supplementary Fig. 16). The carbon K-edge spectrum of S-CuISA/SNC (Fig. 2b) was dominated by four clearly peaks located at $285.5\\mathrm{eV}$ (peak a), $287.4\\mathrm{eV}$ (peak $\\left.\\mathbf{b}_{1}\\right\\vert$ ), $288.5\\mathrm{eV}$ (peak $\\mathbf{b}_{2}$ ) and $292.4\\mathrm{eV}$ (peak c), which could be attributed to the dipole transition of the C 1 s core electron to the $\\pi^{*}\\mathrm{C}=\\mathrm{C}$ , $\\pi^{*}{\\bf C}{\\cdot}\\bar{\\bf N}/\\bar{\\bf S}{\\cdot}{\\bf C},$ and $\\upsigma^{\\mathrm{*}}\\mathrm{C-C}$ orbitals54. The peak $\\mathbf{b}_{1}$ and peak $\\mathsf{b}_{2}$ suggested the existing of $\\mathrm{Cu-N}/\\mathrm{S}$ bonds at carbon matrix55. In addition, the electronic state of N in S-Cu-ISA/SNC could also be detected by the N Kedge XANES spectrum (Fig. 2c). The peaks $\\boldsymbol{\\mathrm{e}}_{1}$ , $\\boldsymbol{\\mathrm{e}}_{2}$ and f indicated the pyridinic and pyrrolic nitrogen; the peak $\\mathbf{g}$ denoted graphitic nitrogen54. The $\\mathrm{Cu-N}$ bond was also monitored by $\\mathrm{~N~}$ 1s XPS spectrum (Supplementary Fig. 16e). Furthermore, the $s\\mathrm{~L~}$ -edge XANES spectrum (Supplementary Fig. 17) of S-Cu-ISA/SNC showed obvious peaks (peak h-j) in the region of 163–167 eV corresponding to C-S-C coordination species, suggesting the anchor of S in the carbon skeleton56. The sulfur was further investigated by S K-edge XANES (Supplementary Fig. 18). In general, the valence of S was linear correlated to the K-edge position. We found that the sulfur in S-Cu-ISA/SNC was slightly positive charge, which might be attributed to the existence of S-N coordination, since N had higher electronegativity than S, as well as the existence of $\\mathrm{C}{\\cdot}\\mathrm{S}\\mathrm{O}_{\\mathrm{x}}$ species in the sample. The $\\textsf{S K}$ -edge EXAFS for S-Cu-ISA/SNC demonstrated the presence of S-C/N and S-Cu bonding, with FT peaks located at $1.3\\mathring\\mathrm{A}$ and $2.1\\mathring\\mathrm{A}$ , respectively (Supplementary Fig. 19). \n\n$\\mathrm{\\DeltaX}$ -ray absorption fine structure (XAFS) was carried out to gain insight into the interface structure at atomic scale. The position of the Cu K-edge absorption threshold was the reflection of average oxidation state of Cu species57,58. As illustrated in Fig. 2d, the edge position of S-Cu-ISA/SNC was between CuS and CuPc, demonstrating the average oxidation state of Cu was between the two references. In supplementary Fig. 20, the fitted oxidation state of $\\mathrm{Cu}$ in S-Cu-ISA/SNC from K-edge XANES spectra was 1.97, agreeing well with XPS and soft L-edge XANES analysis. The Fourier transform (FT) EXAFS spectra of S-Cu-ISA/SNC and the references (Cu foil, CuS and CuPc) were illustrated in Fig. 2e. We found that the sample exhibited one obvious FT peak located at $1.55\\mathrm{\\AA}$ , which was mainly attributed to the scattering of Cu-N coordination. Surprisingly, a shoulder peak located at $\\mathbf{\\check{1}.81\\:\\mathring{A}}$ was also detected. By contrast with other FT-EXAFS spectra, this signal in S-Cu-ISA/SNC was considered owing to Cu-S scattering (Supplementary Figs. 21 and 22), which indicated the formation of Cu-S bonding. Furthermore, there was no related peak corresponding to Cu-Cu coordination, compared with Cu foil. Due to the powerful resolution in both $k$ and $R$ spaces, the Cu Kedge wavelet transform (WT)-EXAFS was applied to investigated the atomic configuration of S-Cu-ISA/SNC (Fig. 2f)59. By comprehensive consideration of the Cu-N and Cu-S contributions, the WT contour plots in S-Cu-ISA/SNC exhibited the maximum peak at $3.9\\mathring{\\mathrm{A}}^{-1}$ . In addition, compared with the WT signals of $\\mathrm{Cu}$ foil, no Cu-Cu coordination was observed in S-CuISA/SNC (Supplementary Fig. 23). These further identified the isolated feature of Cu species in $\\mathrm{S-Cu-ISA/SNC^{60}}$ . \n\n![](images/c2be8eae7d99e5c3c61c83716ff9fc684ca237091af69c7680de5c9033d1c039.jpg) \nFig. 2 Chemical state and atomic local structure of S-Cu-ISA/SNC. a Cu L-edge XANES spectra of S-Cu-ISA/SNC, CuS and ${\\mathsf{C u P c}}$ . b C K-edge and c N K-edge XANES spectra of the $S-C u-1S A/S N C$ . d The experimental Cu K-edge XANES spectra of $S-C u-1S A/S N C$ and the references (Cu foil, CuS and CuPc). e FT $k^{3}$ -weighted Cu K-edge EXAFS spectra of $S-C u-1S A/S N C$ and the references. f WT-EXAFS plots of $S-C u$ -ISA/SNC, CuS and CuPc, respectively. g FTEXAFS fitting curves of S-Cu-ISA/SNC at Cu K-edge. h Schematic atomic interface model of $S-C u$ -ISA/SNC. \n\nQuantitatively, the structural parameters at Cu K-edge was extracted by least-square EXAFS fitting. The results were exhibited in Fig. ${2}\\mathrm{g},$ Supplementary Fig. 24 and Supplementary Table 1. It was observed that the fitting curves matched quite well with the experiment spectra. Depend on the results, the first shell of the central atom $\\mathrm{Cu}$ displayed a coordination number of four, directly connected by one S atom and three $\\mathrm{\\DeltaN}$ atoms, with the mean bond lengths of $2.32\\mathring{\\mathrm{A}}$ and $1.98\\mathring{\\mathrm{A}}$ , respectively (Fig. 2h). Furthermore, we investigated the simulated EXAFS spectra based on the models of $\\mathrm{Cu}{-S_{1}}\\bar{\\mathrm{N}}_{3}$ , Cu- $\\mathrm{S}_{2}\\mathrm{N}_{2}$ , Cu- $\\mathrm{.}S_{3}\\mathrm{N}_{1}$ and $\\mathrm{Cu-N_{4},}$ given in Supplementary Fig. 25a. We could find that when the atom number of sulfur increased from one to three, the FT peak intensity of $\\mathrm{Cu-S}$ increased understandably, compared to that of $\\mathrm{Cu-N^{61}}$ . The relative intensity of $\\mathrm{Cu-S}$ and $\\mathrm{Cu-N}$ in the $\\mathrm{Cu}{-S_{1}}\\mathrm{N}_{3}$ curve accorded quite well with the experimental spectrum. The theoretical XANES spectrum was also calculated based on the Cu$\\mathsf{S}_{1}\\mathsf{N}_{3}$ model (Supplementary Fig. 25b) as well as $\\mathrm{Cu-N_{4}}.$ , Cu- $\\mathrm{S}_{2}\\mathrm{N}_{2}$ and Cu- ${\\bf\\cdot}S_{3}\\bf N_{1}$ (Supplementary Fig. 26). We could see that the calculation result for $\\mathrm{Cu}{-}\\ensuremath{\\mathrm{S}}_{1}\\ensuremath{\\mathrm{N}}_{3}$ could best reproduce the main features of the experimental curve of $S\\mathrm{-Cu}$ -ISA/SNC. Moreover, we also tried linear combination fitting (LCF) of the experimental spectrum with the calculated spectrum for $\\mathrm{Cu-N_{4}}$ and experimental spectra for CuS and/or $\\bar{\\mathrm{Cu}}_{2}\\mathrm{S},$ as shown in Supplementary Figs. 27–29. We found that although the fitted curves near the edge seemed coincide with the experimental spectrum in some way, the curves after the white line were quite different, suggesting the absence of copper sulfide species. Based on the EXAFS fittings and simulations together with XANES calculations, the unsymmetrical $\\mathrm{Cu}{-S_{1}}\\mathrm{N}_{3}$ moiety in S-Cu-ISA/SNC was appropriately confirmed. The EXAFS results of Cu foil, CuS and CuPc were also exhibited in Supplementary Fig. 30 and Supplementary Table 1. By contrast, the EXAFS analysis of CuISA/NC and Cu-ISA/SNC were showed in Supplementary Figs. 31, 32 and Supplementary Table 1, respectively. Both the Cu species in Cu-ISA/NC and Cu-ISA/SNC existed in the form of symmetrical $\\mathrm{Cu-N_{4},}$ different from that of S-Cu-ISA/SNC. \n\nElectrocatalytic performance of S-Cu-ISA/SNC on ORR. The ORR activity of S-Cu-ISA/SNC was then evaluated in a typical three-electrode system (Supplementary Figs. 33 and 34). \n\n![](images/92de837c3d42737fe63767670a834e67dbd957ca52944793ff7276dca19bfb1d.jpg) \nFig. 3 ORR activity of S-Cu-ISA/SNC. a Polarization curves for S-Cu-ISA/SNC and the references. b The contrast between S-Cu-ISA/SNC and the references for $J_{k}\\left(0.85\\bigvee\\right)$ and $E_{\\mathcal{V}2}$ . c Contrasting the $\\boldsymbol{E_{o n s e t}}$ and $E_{\\mathcal{V}2}$ values for $S-C u-1S A/S N C$ and the catalysts in Supplementary Table 2. d The polarization curves of $S-C u-1S A/S N C$ at different rotating speeds. e The K-L plots for $S-C u-1S A/S N C$ . f The long-term durability tests of $S-C u-1S A/S N C,$ which was assessed by cycling the catalyst between 1.1 and $0.2\\mathrm{V}$ vs. RHE at $50\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . g Schematic diagram of $Z n$ -air battery. h Discharge polarization curves and power density plots of $S-C u$ -ISA/SNC and $\\mathsf{P t/C}$ -based $Z n$ -air batteries. \n\nAs illustrated in Fig. 3a, b and Supplementary Fig. 35 (the CV curves of S-Cu-ISA/SNC and $\\mathrm{Pt/C}$ were exhibited in Supplementary Fig. 36), all the three single copper atom samples (S-Cu-ISA/ SNC, Cu-ISA/SNC and Cu-ISA/NC) showed an optimistic performance. Especially, the S-Cu-ISA/SNC displayed an optimal activity with the highest kinetic current density $\\mathrm{\\bar{(}}J_{\\mathrm{k}}\\mathrm{\\bar{=}}35\\mathrm{mA}\\mathrm{\\bar{c}m}^{-2},$ ), as well as the most positive onset potential $(E_{\\mathrm{onset}})$ at $1.05\\mathrm{V}$ and half-wave potential $(E_{1/2})$ at $0.918\\mathrm{V}$ among the studied catalysts, and the catalytic activities of these catalysts followed the trend $\\mathrm{S\\mathrm{-}C u\\mathrm{-}I S A/S N C>C u\\mathrm{-}I S A/S N C>C u\\mathrm{-}I S A/N C.}$ The $E_{1/2}$ of $S\\mathrm{-Cu}$ - ISA/SNC was even $78\\mathrm{mV}$ higher than that of commercial $\\mathrm{Pt/C}$ $(0.84\\mathrm{V})$ . By contrast, NC and SNC frameworks derived from ZIF-8 demonstrated rather low $J_{\\mathbf{k}}$ $(0.024\\mathrm{mA}\\mathrm{cm}^{-2}$ and $1.3\\mathrm{mA}\\mathrm{cm}^{-2}$ ) and $E_{1/2}$ $0.66\\mathrm{V}$ and $0.79\\mathrm{V}$ , respectively), which indicated that in single copper atom catalysts, the $\\mathrm{Cu-S/N}$ or $\\mathrm{Cu-N}$ sites might serve as the active sites during ORR instead of the N-C or S-N-C. Furthermore, S-Cu-ISA/SNC surpassed all the other listed $\\mathtt{C u}$ -based ORR catalysts including some recently reported single Cu atom catalysts with isolated symmetrical $\\mathrm{Cu-N_{4}}$ centers62,63. The ORR activity of S-Cu-ISA/SNC was also compared with that of other nanostructured or single atom non-precious metal (Mn, Fe, Co, Ni, etc.) catalysts, and we found that S-Cu-ISA/SNC still demonstrated superior activity than those of them (Fig. 3c and Supplementary Table 2). \n\nKoutecky-Levich plots of S-Cu-ISA/SNC were obtained from linear sweep voltammetry (LSV) curves (Fig. 3d). The calculated electron transfer number of S-Cu-ISA/SNC was 4.0 (Fig. 3e), which was the same as the theoretical value for $\\mathrm{Pt/C}$ . As shown in the Supplementary Fig. 37, from 0.2 to $0.9\\mathrm{V}$ , the electron transfer number for S-Cu-ISA/SNC was in the range of 3.92-3.99 and the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield remained below $4\\%$ , indicating that the catalytic process on the S-Cu-ISA/SNC electrode underwent a high efficiency four-electron ORR process. The Tafel slope for S-CuISA/SNC ( $50\\mathrm{mV}$ decade−1) was much lower than that of $\\mathrm{Pt/C}$ 1 $\\mathrm{\\langle{90}m V}$ decade−1), further conforming the excellent ORR activity for S-Cu-ISA/SNC (Supplementary Fig. 38). Supplementary Figs. 39, 40 demonstrated that S-Cu-ISA/SNC exhibited excellent methanol tolerance. In Fig. 3f, after 5000 cycles, little change in $\\mathrm{E}_{1/2}$ was observed for S-Cu-ISA/SNC. The chronoamperometry at $0.90{\\mathrm{V}}$ vs. RHE of S-Cu-ISA/SNC catalyst showed that the ORR current remained $98\\%$ after $\\boldsymbol{100\\mathrm{h}}$ test (Supplementary Fig. 41). The HAADF images and EXAFS spectra (Supplementary Figs. 42, 43) also proved that S-Cu-ISA/SNC had excellent stability for ORR. When tested in acidic media (0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution), the S-Cu-ISA/SNC catalyst also exhibited improved activity (Supplementary Fig. 44). The catalyst displayed $\\mathrm{E}_{1/2}$ of $0.74\\mathrm{V}$ . The Tafel slope was $106.9\\mathrm{mV}$ decade $^{-1}$ . Furthermore, it showed comparable activity compared with other catalyst shown in \n\nSupplementary Table 3. In addition, S-Cu-ISA/SNC in acid possessed good stability as well (Supplementary Fig. 44f). \n\nAdditionally, we tested the potential application of S-Cu-ISA/ SNC in a home-made $Z\\mathrm{n}$ -air battery (Fig. $3\\mathrm{g}$ and Supplementary Fig. 45a). As exhibited in Fig. $3\\mathrm{h}$ , the Zn-air battery using S-CuISA/SNC catalyst as the air cathode displayed good activity. The maximum power density was $225\\mathrm{mW}\\dot{\\mathrm{cm}^{-2}}$ , outperformed $\\mathrm{Pt/C}$ $(155\\mathrm{mW}\\mathrm{c\\bar{m}}^{-2})$ as well as the listed catalysts in Supplementary Table 4. In Supplementary Fig. 45b, the specific capacity of the battery employing S-Cu-ISA/SNC as air-cathode was estimated to be $73\\dot{5}\\ \\mathrm{mAh\\g^{-1}}$ at the discharge of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ . Moreover, the S-Cu-ISA/SNC-based battery could robustly serve up to $50\\mathrm{h}$ with little discharge voltage decrease (Supplementary Fig. 45c), which indicated the outstanding durability for S-Cu-ISA/SNC based device. \n\nIn situ XAS measurements of S-Cu-ISA/SNC. In order to monitor the structural evolution of the isolated copper sites during ORR, potential-dependent Cu K-edge XAS of $\\bar{\\mathsf{S}}\\mathrm{-Cu-ISA/}$ SNC was carried out64,65. The in situ XAS tests were carried out using a home-made cell (Fig. 4a and Supplementary Fig. 46), and all the spectra were collected in fluorescence model by a common-used Lytle detector. The S-Cu-ISA/SNC sample was uniformly dropped on a carbon paper, ensuring that all the $\\mathrm{Cu}$ species took part in the ORR reaction (Supplementary Fig. 47). Firstly, the possible X-ray radiation damage on S-Cu-ISA/SNC was examined (Supplementary Fig. 48a), and it was found that the XANES region at Cu K-edge was with no obvious change after a longtime irradiation $(2\\mathrm{h})$ , suggesting that the radiation damage was negligible. Then the sample-loaded carbon paper was immersed in 0.1 M KOH solution, without electricity and oxygen inpouring. The collected XANES spectra (Supplementary Fig. 48b) implied that the solution has little influence on the structure before ORR test. The Cu K-edge in situ XANES spectra for S-Cu-ISA/SNC was examined at different potentials (Supplementary Fig. 49). The results were displayed in Fig. 4b and Supplementary Fig. 50, respectively. From $1.05\\mathrm{V}$ to $0.75\\mathrm{V}$ , the edge position was gradually moved to the lower energy, together with reduce of the white line intensity, which suggested a decrease of the valence of $\\mathtt{C u}$ in S-Cu-ISA/SNC during ORR. The trend could be reflected more clearly from the XANES difference curves (Fig. 4c). The average oxidation states (Fig. 4d and Supplementary Figs. 51 and 52) indicated that the valence of Cu species decreased from approximately $+2$ to $+1$ , implying that Cu $(+1)$ sites might work as the active centers for $\\mathrm{O}\\breve{\\mathrm{R}}\\mathrm{R}^{66,67}$ . When the applied potential returned from $0.75\\mathrm{V}$ to $1.05\\mathrm{V}$ , Cu XANES edge shifted back to higher energy along with increase of the white line peak (Supplementary Figs. 53 and 54). This provided unequivocal evidence that the XANES spectra as a function of applied potential were reversible, which might be due to the strong anchor effect of $\\mathrm{~N~}$ and S atom to the Cu sites. The reversible change of Cu valence state was a reflection of its significant contribution to the outstanding catalytic activity for ORR. \n\nIn addition, in situ EXAFS was conducted to monitor the atomic interface structure of the Cu sites during ORR (Fig. 4e and Supplementary Fig. 55). Figure 4e showed the corresponding $k^{3}$ - weighted FT-EXAFS spectra for S-Cu-ISA/SNC at $0.90\\mathrm{V}$ and $0.75\\mathrm{V}$ vs. RHE. Just like the ex situ data, the in situ FT-EXAFS curves still exhibited one main peak (Cu-N) along with a shoulder peak (Cu-S). However, under the realistic condition, the $\\mathrm{Cu-N}$ peaks appeared an obvious low-R move from $1.55\\mathring\\mathrm{A}$ to $1.49\\mathring{\\mathrm{A}}$ . This implied that the local structure of the active site was changed, which was monitored through the shrinking of $\\mathrm{Cu-N}$ bond length. The EXAFS curve-fitting results were exhibited in Supplementary Figs. 56, 57 and Supplementary Table 5, where three backscattering paths including Cu-N, Cu-O and $\\mathrm{Cu-S}$ were considered. The ex situ spectrum indicated the Cu-N bond lengths of $1.98\\mathring{\\mathrm{A}}$ , while the bond lengths were shortened to 1.94 $\\mathring\\mathrm{A}$ ( $\\mathrm{\\bar{0}}.90\\mathrm{\\mathrm{V}}$ vs. RHE) and $1.93\\mathring{\\mathrm{A}}$ ( $0.75{\\mathrm{~V~}}$ vs. RHE), respectively, at real-time working conditions. The most possible geometric configuration was considered as an isolated unsymmetrical Cu$\\mathsf{S}_{1}\\mathsf{N}_{3}$ moiety linked with the ${\\mathrm{OOH}}^{*}$ , ${}^{\\mathrm{O^{*}}}$ and ${\\mathrm{OH}}^{*}$ intermediates as shown in Fig. 4f, which was also detected by our in situ Fourier Transform infrared spectroscopy (FTIR) test (Supplementary Fig. 58)68. At the same time, the $\\mathrm{Cu-S}$ bond lengths were detected to be nearly unchanged and kept at about $\\overset{\\smile}{2.3}2\\mathring{\\mathrm{A}}$ . Moreover, Supplementary Fig. 59 showed the HAADF-STEM images at different areas of the S-Cu-ISA/SNC catalyst after in situ XAS tests, which suggested the absence of Cu clusters or small copper sulfide species. In short, the in situ spectroscopy analysis elucidated the electronic and atomic structure evolution of the $\\mathrm{Cu}{-}\\ensuremath{\\mathrm{S}}_{1}\\ensuremath{\\mathrm{N}}_{3}$ moiety in S-Cu-ISA/SNC and revealed that the lowvalence $(+1)$ Cu-N-bond-shrinking HOO-Cu- $\\phantom{}.S_{1}\\mathrm{N}_{3},$ $0{\\cdot}\\mathrm{Cu}{\\cdot}\\ensuremath{\\mathrm{S}_{1}}\\ensuremath{\\mathrm{N}_{3}}$ and $_\\mathrm{HO-Cu-S}_{1}\\mathrm{N}_{3}$ species might contribute to the good ORR activity. \n\n![](images/47da5ebdb29d5d8bd22acb4e3595f4da9629dbdbf9e68b5d72d5745d499cccdf.jpg) \nFig. 4 In situ XAFS characterization of S-Cu-ISA/SNC. a Schematic of the in situ electrochemical cell set-up. CE, counter electrode; WE, working electrode; RE, reference electrode. b Cu K-edge XANES spectra of S-Cu-ISA/SNC at various potentials during ORR catalysis in $\\mathsf{O}_{2}$ -saturated 0.1 M KOH. c Differential $\\Delta\\upmu\\times A N E S$ spectra obtained by subtracting the normalized spectrum at every potential to the spectrum recorded at $1.05\\mathrm{V}$ vs. RHE. d Current density as a function of potential for $S-C u-1S A/S N C$ (left) and the average oxidation number of $\\mathsf{C u}$ species in $S-C u-1S A/S N C$ as a function of potential (right). e $k^{3}$ -weighted FT-EXAFS at ex-situ, $0.90{\\mathrm{V}}$ and $0.75\\vee$ vs. RHE. The shaded region highlighted the variations in the peak position of the first coordination shell. f The proposed ORR mechanism for the $S\\mathrm{-}C\\upmu$ -ISA/SNC. \n\nTheoretical study of S-Cu-ISA/SNC on ORR. To understand the observed enhancement of ORR activity for S-Cu-ISA/SNC, DFT calculations were conducted to analyze the whole process of the four-electron ORR reaction on different Cu-centered moieties embedding in carbon matrix. Considering that the atomic radius of S was much larger than that of N or C atoms (Supplementary Table 6), we substituted two adjacent atoms of C or N by the S atom to maintain the stability of sulfur-doped structures in our calculations (Supplementary Fig. 60 and Supplementary Note. 3). Meanwhile, as shown in Supplementary Table 7, the formation energy of S-doped moiety rapidly increased with the number of the coordinated sulfur atoms bonded with central Cu atom, suggesting that the moiety with multi-S coordinated atoms bonded with central $\\mathtt{C u}$ atom (symmetrical Cu-para- $\\cdot S_{2}\\mathrm{N}_{2}$ or unsymmetrical Cu-ortho- $\\phantom{}\\cdot S_{2}\\Nu_{2}$ ) was much less stable than unsymmetrical $\\mathrm{Cu}{-S_{1}}\\mathrm{N}_{3}$ . With this prediction of stability, we comparably investigated the ORR activities of S-Cu-ISA/SNC (S was coordinated with $\\mathrm{Cu}^{\\mathrm{\\prime}}$ ), Cu-ISA/SNC (S was separated from $\\mathrm{Cu})$ ) and Cu-ISA/NC (S free), respectively, including the pristine graphene structures embedding with unsymmetrical Cu- $\\bar{\\mathbf{S}_{1}}\\bar{\\mathbf{N}_{3}}$ for S-Cu-ISA/SNC, S-doped graphene structures embedding with $\\mathrm{Cu-N_{4}}$ moieties $\\mathrm{'Cu{-}N_{4}{-}S_{1}{-}1}$ and $\\mathrm{Cu-N}_{4}{\\cdot}\\mathrm{S}_{1}{-}2,$ ) for Cu-ISA/SNC, and the pristine graphene structures embedding with the $\\mathrm{Cu-N_{4}}$ moiety for Cu-ISA/NC (Fig. 5a, b, Supplementary Figs. 61 and 62 and Supplementary Tables 7 and 8). According to the Sabatier principle, the best catalysts which located at the vertex of volcanotype plot should bind reaction intermediates neither too strongly nor too weakly69. In ORR reaction, for catalysts (such as Fe- ${\\bf\\cdot N_{4}}$ and $\\mathrm{{Mn-N_{4,}}}$ ) that strongly binded intermediates, locating at the left side of volcano-type plot, the potential-limiting step was the desorption of $\\mathrm{OH^{*}}$ intermediate. While for catalysts (such as Co$\\mathrm{N}_{4}$ and $\\mathrm{Ni-N_{4}}$ ) that weakly binded intermediates, locating at the right side of volcano-type plot, the potential-limiting step was the adsorption of ${\\mathrm{OOH}}^{*}$ intermediate70. Fig. 5a showed that the ORR activity of $\\mathrm{Cu-N_{4}}$ was far away from the vertex of the volcanotype plot and locates at the right side, suggesting that the $\\mathrm{Cu}$ atom in $\\mathrm{Cu-N_{4}}$ moiety binded ORR intermediates too weakly34,71. With the introduction of sulfur atoms, the ORR activities were improved greatly. Particularly, the Cu atom in unsymmetrical $\\mathrm{Cu-S}_{1}\\mathrm{N}_{3}$ moiety had the best ORR activity among all Cu-centered moieties (Fig. 5a, b), with the overpotential of $0.39\\mathrm{V}$ , which was even better than that of $\\mathrm{Fe-N_{4}}$ moiety. Thus, we demonstrated that the formation of the unsymmetrical $\\mathrm{Cu-S}_{1}\\mathrm{N}_{3}$ atomic interface in the carbon matrix benefited the improved ORR activity of the catalyst, which was consistent with the experimental results. \n\nTo further investigate the physical origin of the superior ORR performance for S-Cu-ISA/SNC, we also analyzed the electronic structures feature of different Cu-center moieties. As the electronegativity of S was smaller than that of N (Supplementary Table 6), Cu in S-Cu-ISA/SNC was likely to lose less valence electron since one coordinated N was substituted by S than $\\mathtt{C u}$ in Cu-ISA/NC (Fig. 5c and Supplementary Table 8)72. However, as shown in Fig. 5c, there was no clear linear correlation between the number of Bader charge of Cu and the adsorption free energy of ${{\\mathrm{O}}^{*}}$ for different moieties, suggesting that the superior ORR performance of S-Cu-ISA/SNC was not directly determined by the number of valance electron of Cu atom. Figure 5d, e showed the projected density of states (PDOS) for $d$ orbitals of Cu before and after ${{\\cal O}^{*}}$ adsorption on the $\\mathrm{Cu}{-}\\ensuremath{\\mathrm{S}}_{1}\\ensuremath{\\mathrm{N}}_{3}$ atomic interface of SCu-ISA/SNC, respectively. Clearly, due to the introduction of the coordinated S, the $\\mathtt{C u}$ atom in the $\\mathrm{Cu}{-}\\ensuremath{\\mathrm{S}}_{1}\\ensuremath{\\mathrm{N}}_{3}$ moiety had more electrons which occupied the $d_{x^{2}-y^{2}}$ orbital than that in the $\\mathrm{Cu-N_{4}}$ moiety (Supplementary Fig. 63). After the ${{\\mathrm{O}}^{*}}$ adsorption, for the $\\mathrm{Cu-N_{4}^{\\cdot}}$ moiety, the $\\boldsymbol{p}$ orbital of O and the $d_{z^{2}}$ orbital of Cu formed $\\upsigma$ bond. Meanwhile, the $\\boldsymbol{p}$ orbital of $\\mathrm{~O~}$ and only $d_{\\mathrm{yz}}$ and $d_{\\mathrm{xz}}$ orbitals of $\\mathrm{Cu}$ could form $\\pi$ bonds. For $\\mathrm{Cu}{-}\\ensuremath{\\mathrm{S}}_{1}\\ensuremath{\\mathrm{N}}_{3}$ moiety, the $\\upsigma$ bond was also derived from the $\\boldsymbol{\\mathrm{~O~}}_{P}$ orbital and the $\\\\\\\\mathrm{Cu}d_{z^{2}}$ orbital, while the $\\pi$ bonds originated from the $\\boldsymbol{\\mathrm{~O~}}_{P}$ orbital and the Cu $d_{\\mathrm{yz}},$ $d_{\\mathrm{xz}}$ as well as $d_{x^{2}-y^{2}}$ orbitals, which was quite different from that of $\\mathrm{Cu-N_{4}}$ (Fig. 5f, Supplementary Fig. 63). Dramatically, the additional $\\pi$ bonds contributed from the Cu $d_{x^{2}-y^{2}}$ orbitals strengthened the weak bonding of ORR intermediates, resulting in the boosted ORR performance of $\\mathrm{Cu}$ centers. Furthermore, it was clearly shown in Supplementary Fig. 61, for the unsymmetrical $\\mathrm{Cu-}\\dot{\\mathrm{S}}_{1}\\mathrm{N}_{3}$ atomic interface, the ${|\\mathrm{O^{*}}}$ intermediates of ORR were not located exactly at the top site of Cu atom, so the $\\mathrm{~O~}p$ orbital could interact with the $\\mathrm{Cu}\\ \\bar{d}_{x^{2}-y^{2}}$ orbitals. While for the symmetrical $\\mathrm{Cu-N_{4}}$ moiety, the ${{\\cal O}^{*}}$ intermediates of ORR were located at the top site of $\\mathrm{Cu}$ due to the symmetry confinement, without the interaction of $\\mathrm{~O~}_{P}$ orbital and Cu $d_{x^{2}-y^{2}}$ orbitals. Based on the experimental and theoretical results, the activity trend of ORR was well-confirmed. \n\nSynthesis and ORR performance of S-M-ISA/SNC $(\\mathbf{M}=\\mathbf{M}\\mathbf{n}$ , Fe, Co, Ni). The synthetic method could expand to other 3d metal (Mn, Fe, Co and $\\mathrm{\\DeltaNi,}$ etc.) (Supplementary Table 9). HAADF-STEM images identified the isolated feature of Mn, Fe, Co and Ni in the obtained catalysts, which was further revealed by FT-EXAFS curves (Fig. 6 and Supplementary Figs. 64–71). Quantitative EXAFS fittings were also carried out (Supplementary Table 10), which suggested the center metal coordinated directly with N and S atom to form M- $\\phantom{}\\cdot S_{1}\\mathrm{N}_{3}$ moiety at the atomic surface. The extended study identified the universal of the synthetic strategy. \n\nThe ORR catalytic activities of S-M-ISA/SNC (Mn, Fe, Co, Ni) was then evaluated by electrochemical measurements in $0.1\\mathrm{M}$ KOH. Supplementary Fig. 72 exhibited the LSV curves for S-MnISA/SNC, S-Fe-ISA/SNC, S-Co-ISA/SNC and S-Ni-ISA/SNC. As we could see, the samples of S-M-ISA/SNC ( $\\mathbf{\\dot{M}}=\\mathbf{M}\\mathbf{n}_{\\mathrm{\\Omega}}$ , Fe, Co, Ni) showed optimistic performance. The half-wave potential $\\left(\\operatorname{E}_{1/2}\\right)$ of S-Mn-ISA/SNC, S-Fe-ISA/SNC, S-Co-ISA/SNC and S-Ni-ISA/ SNC was $0.902\\mathrm{V},0.917\\mathrm{V},0.911\\mathrm{V}$ and $0.851\\mathrm{~V~}$ , respectively. The favorable ORR kinetics of S-Mn-ISA/SNC, S-Fe-ISA/SNC, S-CoISA/SNC and S-Ni-ISA/SNC was verified by kinetic current density $\\left(J_{\\mathrm{k}}\\right)$ of 14.5, 40.0, 27.0 and $5.1\\mathrm{mA}\\mathrm{cm}^{-2}$ (Supplementary Fig. 73). The Tafel slope of S-Mn-ISA/SNC, S-Fe-ISA/SNC, S-CoISA/SNC and S-Ni-ISA/SNC was calculated to be 83.8, 62.6, 72.5 and $91.7\\mathrm{mV}\\mathrm{dec}^{-1}$ (Supplementary Fig. 74). These results further demonstrated the desirable ORR kinetics for S-M-ISA/SNC, originating from the unsymmetrical $\\mathbf{M}{\\cdot}\\mathbf{S}_{1}\\mathbf{N}_{3}$ atomic interface structure. \n\n![](images/947c3afb41e6b5358d124d0fb8ba5315b0d696bbb07c11254a762fbb7ae75878.jpg) \nFig. 5 Theoretical ORR activity of S-Cu-ISA/SNC. a ORR overpotential $(\\eta_{\\tt O R R})$ as a function of $0^{\\star}$ adsorption free energy $(\\Delta G_{\\mathrm{O^{\\star}}})$ on different $\\mathtt{C u}$ -centered moieties. Gray, blue, orange and yellow balls represent C, N, $\\mathsf{C u}$ and S atoms, respectively. b Free-energy diagram for different $\\mathsf{C u}$ -centered moieties. c Relationship between the number of Bader charge of $\\mathsf{C u}$ and $\\Delta G_{\\mathrm{O^{\\star}}}$ for different $\\mathsf{C u}$ -centered moieties. Projected density of states of $\\mathsf{C u}$ and $0^{\\star}$ d before and e after $0^{\\star}$ adsorption for $C u-S_{1}N_{3}$ in $S-C u$ -ISA/SNC. f Molecular orbitals of $0^{\\star}$ adsorbed on $C u-S_{1}N_{3}$ in $S-C u-1S A/S N C$ . $\\upsigma$ and $\\boldsymbol{\\upsigma}^{\\star}$ represent the bonding and antibonding between $d_{z^{2}}$ orbital of Cu and $p$ orbital of O, $\\pi_{1}$ and $\\pi_{1}^{\\star}$ represent the bonding and antibonding between $d_{\\mathrm{y}z}/d_{\\mathrm{x}z}$ orbital of $\\mathsf{C u}$ and $p$ orbital of O, $\\pi_{2}$ represents the bonding between $d_{x^{2}-y^{2}}$ orbital of Cu and $p$ orbital of O. \n\n![](images/f34005eb7cda2b05fdbc21ea1fabf13bfc77554f142e4a6a917b752c64d7e6e7.jpg) \nFig. 6 HAADF-STEM and FT-EXAFS characterization of S-M-ISA/SNC $\\scriptstyle(\\mathbf{M}=\\mathbf{M}\\mathbf{n}_{1}$ Fe, Co, Ni). HAADF-STEM images of a S-Mn-ISA/SNC, c S-Fe-ISA/ SNC, e S-Co-ISA/SNC and g S-Ni-ISA/SNC. FT-EXAFS spectra of b S-Mn-ISA/SNC, d S-Fe-ISA/SNC, f S-Co-ISA/SNC and h S-Ni-ISA/SNC. \n\n# Discussion \n\nIn summary, we developed an single Cu atom ORR electrocatalyst consisting of unsymmetrical $\\mathrm{Cu-S}_{1}\\mathrm{N}_{3}$ complexes anchored in MOF-derived hierarchically porous carbon frameworks through an atomic interface engineering strategy. Benefiting from the rational construction of the active sites, the S-Cu-ISA/SNC sample exhibited outstanding ORR activity in alkaline media. Our experimental explorations and theoretical analysis revealed the enhanced ORR performance owed to the optimized atomic arrangement and density-of-states distribution of the $\\mathrm{Cu}{-}\\ensuremath{\\mathrm{S}}_{1}\\ensuremath{\\mathrm{N}}_{3}$ centers. The proposed strategy of local structure regulation may promote the research of advanced oxygen-involved reactions, as well as other electrochemical process. \n\n# Methods \n\nChemicals. Cupric Acetate Monohydrate $\\mathrm{(Cu(acac)}_{2}$ , $99\\%$ , Alfa Aesar), 2- methylimidazole (Acros), sulfur powder (325 mesh, $99.5\\%$ , Alfa), commercial $\\mathrm{Pt/C}$ ( $20\\mathrm{wt\\%}$ metal, Alfa Aesar), zinc nitrate hexahydrate $98\\%$ , Alfa Aesar), KOH (analytical grade, Sinopharm Chemical), carbon tetrachloride (innochem), analytical grade methanol (Sinopharm Chemical), Nafion D-521 dispersion (Alfa Aesar), N, N-dimethylformamide (DMF) (Sinopharm Chemical) were used without any further purification. The distilled water with a resistivity of $18.2~\\mathrm{M}\\Omega~\\mathrm{cm}^{-1}$ was used in all experiments. \n\nPreparation of S-Cu-ISA/SNC and the comparison samples. In a typical synthesis of S-Cu-ISA/SNC catalyst, firstly the precursors were prepared by mixing sulfur powder and $\\mathrm{Cu}$ -ZIF-8 (Supplementary Note. 4) in $20\\mathrm{ml}$ of mixture solution (carbon tetrachloride: ethanol $=4{:}1$ ) under sonication. The mass ration of sulfur powder and Cu-ZIF-8 is 1: 10. Subsequently, the solution was heated at $60^{\\circ}\\mathrm{C}$ under vigorous stirring until drying. Afterwards, the samples were pyrolyzed in quartz tube. The pyrolysis process was in the Ar atmosphere, maintaining $450^{\\circ}\\mathrm{C}$ $(2\\mathrm{h})$ and then $950^{\\circ}\\mathrm{C}$ $\\mathrm{\\cdot}4\\mathrm{h})$ . The ramping rate during the heating process was $5^{\\circ}\\mathrm{C}/$ min. For the comparison samples, SNC (without the addition of $\\mathrm{Cu}(\\mathsf{a c a c})_{2})$ was prepared as the same process. Cu-ISA/NC (single-atom $\\mathrm{Cu-N_{4}}$ supported on $_\\mathrm{~N~}$ doped carbon polyhedron, without the addition of S) and NC (N doped carbon polyhedron, without the addition of S and $\\mathrm{Cu}^{\\mathrm{\\prime}}$ ) were obtained by pyrolysis of CuZIF-8 and pure ZIF-8, respectively. The preparation of $\\mathrm{Cu}$ -ISA/SNC (single-atom $\\mathrm{Cu-N_{4}}$ supported on N and S co-doped carbon polyhedron) was described in Supplementary Note. 5. \n\nCharacterizations. We used the SEM (JSM-6700F), TEM (JEOL-JEM-1200EX) and TEM (JEOR-2100F) to characterize the morphology. The in situ ETEM was carried out in Titan G2 60-300 microscope (FEI) equipped with a probe Cscorrector, with voltage of $300\\mathrm{kV}$ . Using JEOL JEM-ARM200F to gain the HAADFSTEM images, the accelerating voltage was $300\\mathrm{kV}$ . The Bruker D8 ADVANCE Xray Diffractometer was performed to characterize XRD patterns. HORIBA Jobin Yvon (LabRAM HR Evolution) was used to perform the Raman measurements with the laser of $532\\mathrm{nm}$ . NOVA 4200e was used to obtain the BET surface area and the pore size distribution of the materials. \n\nElectrochemical measurements for ORR. We used the three-electrode cell to perform the electrochemical tests. The working electrode was rotating disk electrode (glassy carbon), with a diameter of $5\\mathrm{mm}$ . The counter electrode was graphite rod. The reference electrode was $\\mathrm{\\Ag/AgCl}$ (filled with saturated KCl solution) electrode. The experiment was performed in $0.1\\mathrm{{M}}$ KOH solution. All potentials have been converted to the RHE scale. Dispersing $1\\mathrm{mg}$ catalyst to the mixture solution ( $\\mathrm{0.75ml}$ isopropyl alcohol, $0.25\\mathrm{ml}$ deionized water, $0.02\\mathrm{ml}5\\%$ Nafion), the catalyst ink was successfully prepared after sonication. The catalyst loading on the surface of the glassy carbon electrode was $0.102\\mathrm{mg}\\mathrm{cm}^{-2}$ . Before ORR tests, we bubbled $\\Nu_{2}/\\mathrm{O}_{2}$ to make the system saturated. The CV tests of the catalyst under $\\Nu_{2}$ - and $\\mathrm{O}_{2}$ -saturated alkaline electrolyte were performed at $50\\mathrm{mVs^{-1}}$ . LSV test was measured in different rotating rate from 400 to $2250\\mathrm{rpm}$ . The electron selectivity was identified by rotating ring-disk electrode (RRDE) test (Supplementary Fig. 34). $1.23\\mathrm{V}$ vs. RHE was applied as the ring electrode potential. At the same time, the disk electrode was performed at $10\\mathrm{mVs^{-1}}$ . The detail for the electrochemical data processing was displayed in Supplementary Note. 6. \n\nZinc-air battery measurements. The S-Cu-ISA/SNC ink was uniformly dispersed onto teflon-coated carbon fiber paper, the loading is $1.0\\mathrm{mg}\\mathrm{cm}^{-2}$ , then using $60^{\\circ}\\mathrm{C}$ to make it dry. The $\\mathrm{Pt/C}$ electrode was synthesized in the same way. Furthermore, the anode was commercial $Z\\mathrm{n}$ foil $\\mathrm{(0.2\\:mm}^{\\cdot}$ ). And we polished it before use. The \n\n$Z\\mathrm{n}$ –air device was constructed by placing electrodes in $\\mathrm{O}_{2}$ saturated KOH solution (6M). \n\nEx situ XAFS measurements. The XAFS spectra (Cu, Mn, Fe, Co, Ni K-edge) were collected at 1W1B station in Beijing Synchrotron Radiation Facility (BSRF, operated at $2.5\\mathrm{GeV}$ with a maximum current of $250\\mathrm{mA}$ ), BL14W1 station in Shanghai Synchrotron Radiation Facility (SSRF, 3.5 GeV, $250\\mathrm{mA}$ ) and BL7-3 station in Stanford Synchrotron Radiation Lightsource (SSRL, 3 GeV, ${\\sim}500\\mathrm{mA}$ ), respectively. The XAFS data of the samples were collected at room temperature in fluorescence excitation mode using a Lytle detector. The samples were pelletized as disks of $13\\mathrm{mm}$ diameter with $1\\mathrm{mm}$ thickness using graphite powder as binder. The XAFS data processing was displayed in Supplementary Note. 7. \n\nIn situ synchrotron radiation XAFS and FTIR measurements. A catalyst modified carbon paper was used as working electrode, graphite rod as counter electrode and $\\mathrm{Ag/AgCl}$ (KCl-saturated) electrode as reference electrode. A home-made electrochemical cell was used for in situ XAFS measurements (Fig. 4a and Supplementary Fig. 46). The experiments were performed at BL14W1 station in SSRF. The detail of in situ XAFS measurements was exhibited in Supplementary Note. 8. The in situ FTIR tests were performed at the BL01B at NSRL through a home-made set-up with a ZnSe crystal as the infrared transmission window. The detail for the in situ FTIR measurements is described in Supplementary Note. 9. \n\nThe detail of DFT calculations. Spin polarized DFT calculations were performed within the Vienna ab initio Simulation Package (VASP) with the projector augmented wave (PAW) scheme73–75. The exchange correlation energy was described by using the generalized gradient approximation (GGA) with the Perdew-BurkeErnzerhof (PBE) functional76 Hubbard corrected DFT $(\\mathrm{DFT}+U)$ method was applied by considering on-site coulomb $(U)$ and exchange (J) interaction, with the $U_{-}J$ values taken from the ones used by Xu et al.33. The cutoff energy was set to be $500\\mathrm{eV}$ The total energy and forces convergence thresholds were set to be $10^{-5}\\mathrm{eV}$ and $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}\\mathbf{r}.$ , respectively. To prevent interaction between two neighboring surfaces, the vacuum layer thickness was set to $20\\textup{\\AA}$ The k-point sampling of the Brillouin zone was used by the $3\\times3\\times1$ grid for structural relaxation and the $5\\times$ $5\\times1$ grid for electronic structure calculations. The empirical DFT-D3 correction was used to describe van der Waals (vdW) interactions77. Atomic charges were calculated by using the atom-in-molecule (AIM) scheme proposed by Bader78,79. Following the RHE model developed by Nørskov et al, the voltage-dependent ORR free energy pathway during electrocatalysis reaction were obtained80. The free energies of ORR intermediates are defined as $G=E_{\\mathrm{DFT}}+E_{\\mathrm{ZPE}}\\ {T}$ S, where $E_{\\mathrm{DFT}},$ $E_{\\mathrm{ZPE}}$ , T and $s$ represent the calculated ground state energy, zero-point energy, temperature $(298\\mathrm{K})$ and the entropy, respectively. \n\n# Data availability \n\nThe data supporting the findings of this study are available within the article and its Supplementary Information files. All other relevant source data are available from the corresponding authors upon reasonable request. \n\nReceived: 29 November 2019; Accepted: 28 May 2020; Published online: 16 June 2020 \n\n# References \n\n1. Chu, S. & Majumdar, A. Opportunities and challenges for a sustainable energy future. Nature 488, 294–303 (2012). \n2. Armand, M. & Tarascon, J. M. Building better batteries. Nature 451, 652–657 (2008). \n3. Li, Y. & Dai, H. Recent advances in zinc-air batteries. Chem. Soc. Rev. 43, 5257–5275 (2014). \n4. Kulkarni, A., Siahrostami, S., Patel, A. & Norskov, J. K. Understanding catalytic activity trends in the oxygen reduction reaction. Chem. Rev. 118, 2302–2312 (2018). \n5. Stamenkovic, V. R., Strmcnik, D., Lopes, P. P. & Markovic, N. M. Energy and fuels from electrochemical interfaces. Nat. Mater. 16, 57–69 (2017). \n6. Shao, M., Chang, Q., Dodelet, J. & Chenitz, R. Recent advances in electrocatalysts for oxygen reduction reaction. Chem. Rev. 116, 3594–3657 (2016). \n7. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science. 355, eaad4998 (2017). \n8. Chu, S., Cui, Y. & Liu, N. The path towards sustainable energy. Nat. Mater. 16, 16–22 (2017). \n9. Xia, W., Mahmood, A., Liang, Z., Zou, R. & Guo, S. Earth-abundant nanomaterials for oxygen reduction. Angew. Chem. Int. Ed. 55, 2650–2676 (2016). \n10. Wu, G. & Zelenay, P. Nanostructured nonprecious metal catalysts for oxygen reduction reaction. Acc. Chem. Res. 46, 1878–1889 (2013). \n11. Wang, A., Li, J. & Zhang, T. Heterogeneous single-atom catalysis. Nat. Rev. Chem. 2, 65–81 (2018). \n12. Liu, L. & Corma, A. Metal catalysts for heterogeneous catalysis: from single atoms to nanoclusters and nanoparticles. Chem. Rev. 118, 4981–5079 (2018). \n13. Cui, X. et al. Bridging homogeneous and heterogeneous catalysis by heterogeneous single-metal-site catalysts. Nat. Catal. 1, 385–397 (2018). \n14. Fan, L. et al. Atomically isolated nickel species anchored on graphitized carbon for efficient hydrogen evolution electrocatalysis. Nat. Commun. 7, 10667 (2016). \n15. Zhang, L. et al. Graphene defects trap atomic Ni species for hydrogen and oxygen evolution reactions. Chem 4, 285–297 (2018). \n16. Weng, Z. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction to hydrocarbons on a heterogeneous molecular Cu catalyst in aqueous solution. J. Am. Chem. Soc. 138, 8076–8079 (2016). \n17. Copéret, C. et al. Surface organometallic and coordination chemistry toward single-site heterogeneous catalysts: strategies, methods, structures, and activities. Chem. Rev. 116, 323–421 (2016). \n18. Elgrishi, N., Chambers, M. B., Wang, X. & Fontecave, M. Molecular polypyridine-based metal complexes as catalysts for the reduction of $\\mathrm{CO}_{2}$ . Chem. Soc. Rev. 46, 761–796 (2017). \n19. Zhu, C., Fu, S., Shi, Q., Du, D. & Lin, Y. Single atom electrocatalysts. Angew. Chem. Int. Ed. 56, 13944–13960 (2017). \n20. Zhuang, Z., Kang, Q., Wang, D. & Li, Y. Single-atom catalysis enables longlife, high-energy lithium–sulfur batteries. Nano Res. https://doi.org/10.1007/ s12274-020-2827-4 (2020). \n21. Li, X., Rong, H., Zhang, J., Wang, D. & Li, Y. Modulating the local coordination environment of single-atom catalysts for enhanced catalytic performance. Nano Res. https://doi.org/10.1007/s12274-020-2755-3 (2020). \n22. Sun, T., Xu, L., Wang, D. & Li, Y. Metal organic frameworks derived single atom catalysts for electrocatalytic energy conversion. Nano Res. 12, 2067–2080 (2019). \n23. Zhang, X., Shao, J., Huang, W. & Dong, X. Three dimensional carbon substrate materials for electrolysis of water. Sci. China Mater. 61, 1143–1153 (2018). \n24. Yuan, K. et al. Boosting oxygen reduction of single iron active sites via geometric and electronic engineering: nitrogen and phosphorus dualcoordination. J. Am. Chem. Soc. 142, 2404–2412 (2020). \n25. Lee, S. H. et al. Design principle of Fe-N-C electrocatalysts: how to optimize multimodal porous structures? J. Am. Chem. Soc. 141, 2035–2045 (2019). \n26. Wagner, S. et al. Elucidating the structural composition of a Fe-N-C catalyst by nuclear- and electron-resonance techniques. Angew. Chem. Int. Ed. 58, 10486–10492 (2019). \n27. Cheng, C. et al. Atomic $\\mathrm{Fe-N_{x}}$ coupled open-mesoporous carbon nanofibers for efficient and bioadaptable oxygen electrode in $\\mathbf{Mg}$ -air batteries. Adv. Mater. 30, 1802669 (2018). \n28. Zitolo, A. et al. Identification of catalytic sites in cobalt-nitrogencarbon materials for the oxygen reduction reaction. Nat. Commun. 8, 957 (2017). \n29. Sa, Y. J. et al. A general approach to preferential formation of active Fe- $\\cdot\\mathrm{N_{x}}$ sites in Fe-N/C electrocatalysts for efficient oxygen reduction reaction. J. Am. Chem. Soc. 138, 15046–15056 (2016). \n30. Li, J. et al. Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells. Nat. Catal. 1, 935–945 (2018). \n31. Wan, X. et al. Fe-N-C electrocatalyst with dense active sites and efficient mass transport for high-performance proton exchange membrane fuel cells. Nat. Catal. 2, 259–268 (2019). \n32. Zitolo, A. et al. Identification of catalytic sites for oxygen reduction in ironand nitrogen-doped graphene materials. Nat. Mater. 14, 937–942 (2015). \n33. Xu, H., Cheng, D., Cao, D. & Zeng, X. C. A universal principle for a rational design of single-atom electrocatalysts. Nat. Catal. 1, 339–348 (2018). \n34. Ramaswamy, N., Tylus, U., Jia, Q. & Mukerjee, S. Activity descriptor identification for oxygen reduction on nonprecious electrocatalysts: Linking surface science to coordination chemistry. J. Am. Chem. Soc. 135, 15443–15449 (2013). \n35. Osmieri, L., Videla, A., Ocon, P. & Specchia, S. Kinetics of Oxygen electroreduction on Me-N-C (Me = Fe, Co, Cu) catalysts in acidic medium: Insights on the effect of the transition metal. J. Phys. Chem. C. 121, 17796–17817 (2017). \n36. Yang, Y. et al. O-, N-atoms-coordinated Mn cofactors within a graphene framework as bioinspired oxygen reduction reaction electrocatalysts. Adv. Mater. 30, e1801732 (2018). \n37. Xu, Q. et al. Coordination structure dominated performance of single-atomic Pt catalyst for anti-Markovnikov hydroboration of alkenes. Sci. China Mater. https://doi.org/10.1007/s40843-020-1334-6 (2020). \n38. Yang, H. B. et al. Identification of catalytic sites for oxygen reduction and oxygen evolution in N-doped graphene materials: development of highly efficient metal-free bifunctional electrocatalyst. Sci. Adv. 2, e1501122 (2016). \n39. Qiao, Y. et al. Sulfuration of an Fe-N-C catalyst containing $\\mathrm{Fe_{x}C/F e}$ species to enhance the catalysis of oxygen reduction in acidic media and for use in flexible Zn-Air batteries. Adv. Mater. 30, 1804504 (2018). \n40. Chen, Y. et al. Enhanced oxygen reduction with single-atomic-site iron catalysts for a zinc-air battery and hydrogen-air fuel cell. Nat. Commun. 9, 5422 (2018). \n41. Shen, H. et al. Synergistic effects between atomically dispersed Fe-N-C and CS-C for the oxygen reduction reaction in acidic media. Angew. Chem. Int. Ed. 56, 13800–13804 (2017). \n42. Mun, Y. et al. Versatile strategy for tuning ORR activity of a single $\\mathrm{Fe-N_{4}}$ site by controlling electron withdrawing/donating properties of carbon plane. J. Am. Chem. Soc. 141, 6254–6262 (2019). \n43. Chen, P. et al. Atomically dispersed iron-nitrogen species as electrocatalysts for bifunctional oxygen evolution and reduction reactions. Angew. Chem. Int. Ed. 56, 610–614 (2017). \n44. Zhuang, L. et al. Defect-induced Pt-Co-Se coordinated sites with highly asymmetrical electronic distribution for boosting oxygen-involving electrocatalysis. Adv. Mater. 31, 1805581 (2019). \n45. Bakandritsos, A. et al. Mixed-valence single-atom catalyst derived from functionalized graphene. Adv. Mater. 31, 1900323 (2019). \n46. Sun, Y. et al. Activity-selectivity trends in the electrochemical production of hydrogen peroxide over single-site metal-nitrogen-carbon catalysts. J. Am. Chem. Soc. 141, 12372–12381 (2019). \n47. Jiang, H. L. et al. From metal-organic framework to nanoporous carbon: Toward a very high surface area and hydrogen uptake. J. Am. Chem. Soc. 133, 11854–11857 (2011). \n48. Zhang, H. et al. Single atomic iron catalysts for oxygen reduction in acidic media: particle size control and thermal activation. J. Am. Chem. Soc. 139, 14143–14149 (2017). \n49. Jiang, R. et al. Edge-site engineering of atomically dispersed Fe- ${\\bf\\cdot N_{4}}$ by selective C–N bond cleavage for enhanced oxygen reduction reaction activities. J. Am. Chem. Soc. 140, 11594–11598 (2018). \n50. Chen, W. et al. Rational design of single molybdenum atoms anchored on Ndoped carbon for effective hydrogen evolution reaction. Angew. Chem. Int. Ed. 56, 16086–16090 (2017). \n51. Xia, B. Y. et al. A metal-organic framework-derived bifunctional oxygen electrocatalyst. Nat. Energy 1, 15006 (2016). \n52. Li, F. et al. Identifying the structure of $Z\\mathrm{n-N}_{2}$ active sites and structural activation. Nat. Commun. 10, 2623 (2019). \n53. Chen, J. NEXAFS investigations of transition metal oxides, nitrides, carbides, sulfides and other interstitial compounds. Surf. Sci. Rep. 30, 1–152 (1997). \n54. Chen, P. et al. Interfacial engineering of cobalt sulfide/graphene hybrids for highly efficient ammonia electrosynthesis. PNAS 116, 6635–6640 (2019). \n55. Tong, Y. et al. A bifunctional hybrid electrocatalyst for oxygen reduction and evolution: cobalt oxide nanoparticles strongly coupled to B, N-decorated graphene. Angew. Chem. Int. Ed. 56, 7121–7125 (2017). \n56. Zhao, Y. et al. Stereodefined codoping of sp-N and S atoms in few-layer graphdiyne for oxygen evolution reaction. J. Am. Chem. Soc. 141, 7240–7244 (2019). \n57. Yang, H. et al. A highly stable copper-based catalyst for clarifying the catalytic roles of ${\\mathrm{Cu}}^{0}$ and $\\mathrm{Cu^{+}}$ species in methanol dehydrogenation. Angew. Chem. Int. Ed. 57, 1836–1840 (2018). \n58. Lee, B. et al. Reversible and cooperative photoactivation of single-atom $\\mathrm{Cu/}$ $\\mathrm{TiO}_{2}$ photocatalysts. Nat. Mater. 18, 620–626 (2019). \n59. Funke, H., Scheinost, A. & Chukalina, M. Wavelet analysis of extended x-ray absorption fine structure data. Phys. Rev. B. 71, 094110 (2005). \n60. Fei, H. et al. General synthesis and definitive structural identification of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n61. Rehr, J. J. & Albers, R. C. Theoretical approaches to X-ray absorption fine structure. Rev. Mod. Phys. 72, 621–654 (2000). \n62. Qu, Y. et al. Direct transformation of bulk copper into copper single sites via emitting and trapping of atoms. Nat. Catal. 1, 781–786 (2018). \n63. Li, F. et al. Boosting oxygen reduction catalysis with abundant copper single atom active. Energy Environ. Sci. 11, 2263–2269 (2018). \n64. Weng, Z. et al. Active sites of copper-complex catalytic materials for electrochemical carbon dioxide reduction. Nat. Commun. 9, 415 (2018). \n65. Karapinar, D. et al. Electroreduction of $\\mathrm{CO}_{2}$ on single-site copper-nitrogendoped carbon material: selective formation of ethanol and reversible restructuration of the metal sites. Angew. Chem. Int. Ed. 58, 15098–15103 (2018). \n66. Iwase, K. et al. Copper-modified covalent triazine frameworks as non-noblemetal electrocatalysts for oxygen reduction. Angew. Chem. Int. Ed. 54, 11068–11072 (2015). \n67. Gentil, S. et al. Electrocatalytic $\\mathrm{O}_{2}$ reduction at a bio-inspired mononuclear copper phenolato complex immobilized on a carbon nanotube electrode. Angew. Chem. Int. Ed. 55, 2517–2520 (2016). \n68. Cheng, W. et al. Lattice-strained metal-organic-framework arrays for bifunctional oxygen electrocatalysis. Nat. Energy 4, 115 (2019). \n69. Che, M. Nobel prize in chemistry 1912 to Sabatier: Organic chemistry or catalysis? Catal. Today 218–219, 162–171 (2013). \n70. Bligaard, T. et al. The Brønsted-Evans-Polanyi relation and the volcano curve in heterogeneous catalysis. J. Catal. 224, 206–217 (2004). \n71. Sun, Y. et al. Activity-selectivity trends in the electrochemical production of hydrogen peroxide over single-site metal-nitrogen-carbon catalysts. J. Am. Chem. Soc. 141, 12372–12381 (2019). \n72. Wu, H. et al. Highly doped and exposed Cu(i)-N active sites within graphene towards efficient oxygen reduction for zinc-air batteries. Energy Environ. Sci. 9, 3736–3745 (2016). \n73. Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n74. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B. 54, 11169–11186 (1996). \n75. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B. 59, 1758–1775 (1999). \n76. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n77. Grimme, S. Semiempirical GGA-type density functional constructed with a long-range dispersion correction. J. Comput. Chem. 27, 1787–1799 (2006). \n78. Tang, W., Sanville, E. & Henkelman, G. A grid-based Bader analysis algorithm without lattice bias. J. Phys. Condens Matter 21, 084204 (2009). \n79. Bader, R. F. W. A quantum theory of molecular structure and its applications. Chem. Rev. 91, 893–928 (1991). \n80. Nørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuelcell cathode. J. Phys. Chem. B. 108, 17886–17892 (2004). \n\n# Acknowledgements \n\nThis work was supported by the National Key Research and Development Program of China (2017YFB0701600), the National Natural Science Foundation of China (Grant No. 51631001, 21801015, 51872030, 21643003, 51702016, 51501010, 11874036), the Guangdong Province Key Area R&D Program (2019B010940001), the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2017BT01N111), Basic Research Project of Shenzhen, China (JCYJ20170412171430026) and Beijing Institute of Technology Research Fund Program for Young Scholars (3090012221909), Fundamental Research Funds for the Central Universities. This work was also supported by the National Key R&D Program of China (2018YFA0702003) and the National Natural Science Foundation of China (21890383, 21671117, 21871159). The authors thank the BL1W1B and BL4B7A in the Beijing Synchrotron Radiation Facility (BSRF), BL14W1 in the Shanghai Synchrotron Radiation Facility (SSRF), BL01B, BL10B and BL12B in the National Synchrotron Radiation Laboratory (NSRL), BL11A in National Synchrotron Radiation Research Center (NSRRC), BL7-3 in Stanford Synchrotron Radiation Lightsource (SSRL) for help with characterizations. Tianjin and Guangzhou Supercomputing Center are also acknowledged for allowing the use of computational resources. \n\n# Author contributions \n\nW.C., D.W. and J.T.Z. conceived the idea, designed the study and wrote the paper. W.C. and H.S. carried out the sample synthesis, characterization and ORR measurement. W. C. carried out the XAFS characterizations and data analysis. J.D., Y.W., L.Z., R.C. and R.S. helped with the hard XAFS measurements and discussion. X.S.Z. helped with the XPS test. J.Z. and W.Y. helped with soft XAS test. A.L. performed the in-situ environmental microscopic measurements and analysis. Y.L. helped with the spherical aberration electron microscopy test and discussion. Z.Y. carried out the $Z\\mathrm{n}$ -air battery measurements. Q.L. and X.Z. performed the in-situ IR test and analysis. X.Y.Z., X.Y. and J.L. performed the DFT calculations. J.P. and Z.Z. helped with the electrochemical tests and data analysis. Z.J., D.Z. T.S. and Z.L. helped with the modification of the paper. Y.D.L. gave very useful suggestions. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-16848-8. \n\nCorrespondence and requests for materials should be addressed to J.L., W.C., D.W. or J.Z. \n\nPeer review information Nature Communications thanks Frédéric Jaouen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1103_PhysRevLett.125.247002", + "DOI": "10.1103/PhysRevLett.125.247002", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevLett.125.247002", + "Relative Dir Path": "mds/10.1103_PhysRevLett.125.247002", + "Article Title": "CsV3Sb5: A Z2 Topological Kagome Metal with a Superconducting Ground State", + "Authors": "Ortiz, BR; Teicher, SML; Hu, Y; Zuo, JL; Sarte, PM; Schueller, EC; Abeykoon, AMM; Krogstad, MJ; Rosenkranz, S; Osborn, R; Seshadri, R; Balents, L; He, JF; Wilson, SD", + "Source Title": "PHYSICAL REVIEW LETTERS", + "Abstract": "Recently discovered alongside its sister compounds KV3Sb5 and RbV3Sb5, CsV3Sb5 crystallizes with an ideal kagome network of vanadium and antimonene layers separated by alkali metal ions. This work presents the electronic properties of CsV3Sb5, demonstrating bulk superconductivity in single crystals with a T-c = 2.5 K. The normal state electronic structure is studied via angle-resolved photoemission spectroscopy and density-functional theory, which categorize CsV3Sb5 as a Z(2) topological metal. Multiple protected Dirac crossings are predicted in close proximity to the Fermi level (E-F), and signatures of normal state correlation effects are also suggested by a high-temperature charge density wavelike instability. The implications for the formation of unconventional superconductivity in this material are discussed.", + "Times Cited, WoS Core": 649, + "Times Cited, All Databases": 703, + "Publication Year": 2020, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000597151900015", + "Markdown": "# $\\mathbf{CsV}_{3}\\mathbf{S}\\mathbf{b}_{5}$ : A $\\mathbb{Z}_{2}$ Topological Kagome Metal with a Superconducting Ground State \n\nBrenden R. Ortiz,1,\\* Samuel M. L. Teicher ,1 Yong Hu ,2 Julia L. Zuo,1 Paul M. Sarte,1 Emily C. Schueller,1 A. M. Milinda Abeykoon,3 Matthew J. Krogstad ,4 Stephan Rosenkranz ,4 Raymond Osborn ,4 Ram Seshadri,1 Leon Balents ,5 Junfeng He,2 and Stephen D. Wilson 1,† 1Materials Department and California Nanosystems Institute, University of California Santa Barbara, Santa Barbara, California 93106, USA 2Hefei National Laboratory for Physical Sciences at the Microscale, Department of Physics and CAS Key Laboratory \nof Strongly-coupled Quantum Matter Physics, University of Science and Technology of China, Hefei, Anhui 230026, China National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, New York 11973, USA 4Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439-4845, USA \n5Kavli Institute for Theoretical Physics, University of California, Santa Barbara, Santa Barbara, California 93106, USA \n\n(Received 2 August 2020; accepted 4 November 2020; published 10 December 2020) \n\nRecently discovered alongside its sister compounds $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ and $\\mathrm{RbV}_{3}\\mathrm{Sb}_{5}$ , $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ crystallizes with an ideal kagome network of vanadium and antimonene layers separated by alkali metal ions. This work presents the electronic properties of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ , demonstrating bulk superconductivity in single crystals with a $T_{c}=2.5\\mathrm{~K~}$ . The normal state electronic structure is studied via angle-resolved photoemission spectroscopy and density-functional theory, which categorize $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ as a $\\mathbb{Z}_{2}$ topological metal. Multiple protected Dirac crossings are predicted in close proximity to the Fermi level $(E_{F})$ , and signatures of normal state correlation effects are also suggested by a high-temperature charge density wavelike instability. The implications for the formation of unconventional superconductivity in this material are discussed. \n\nDOI: 10.1103/PhysRevLett.125.247002 \n\nKagome metals are a rich frontier for the stabilization of novel correlated and topological electronic states. Depending on the degree of electron filling within the kagome lattice, a wide array of instabilities are possible, ranging from bond density wave order [1,2], charge fractionalization [3,4], spin liquid states [5], charge density waves [6], and superconductivity [1,7]. Additionally, the kagome structural motif imparts the possibility of topologically nontrivial electronic structures, where the coexistence of Dirac cones and flatbands promoting strong correlation effects may engender correlated topological states. For instance, the presence of magnetic order [8–10] in kagome compounds has been noted to stabilize novel quantum anomalous Hall behaviors, and electronelectron interactions in certain scenarios are proposed to drive the formation of topological insulating phases [11]. \n\nOne widely sought electronic instability on a two-dimensional kagome lattice is the formation of a superconducting ground state. Layered kagome metals that superconduct are rare, and the interplay between the nontrivial topology accessible via their electronic band structures and the formation of an intrinsic superconducting state makes this a particularly appealing space for realizing exotic ground states and quasiparticles. Unconventional superconductivity is predicted to emerge via nesting-driven interactions in heavily doped kagome lattices [12]. This mechanism, first pointed out in theories for doped graphene (which shares the hexagonal symmetry of the kagome lattice) [13,14], relies upon scattering between saddle points of a band at the $M$ points of the 2D Brillouin zone, which are relevant when the system possesses a nearly hexagonal Fermi surface proximate to a topological transition. Superconductivity potentially competes with a variety of other electronic instabilities at different fillings [11,15]. Realizing superconductivity in a two-dimensional kagome material that avoids these competing instabilities remains an open challenge. \n\nRecently, a new family of layered kagome metals that crystallize in the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ structure $\\mathbf{\\bar{A}}=\\mathbf{K}$ , Rb, Cs) was reported [16]. These materials crystallize into the P6=mmm space group, with a kagome network of vanadium cations coordinated by octahedra of Sb. The compounds are layered, with the kagome sheets separated by layers of the $A$ -site alkali metal ions (Fig. 1). Compounds across the series are high-mobility, two-dimensional metals with signatures of correlation effects and potential electronically driven symmetry breaking. Recent studies have further shown that one variant, $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , is a Dirac semimetal with an extraordinarily large anomalous Hall effect in the absence of long-range magnetic order [17]. Remarkably little, however, remains known about this new class of kagome metals, particularly with regards to their capacity for hosting correlated topological states. \n\nHere we identify that $\\mathrm{Cs}\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ , the heaviest member of the new kagome compounds, is a $\\mathbb{Z}_{2}$ topological metal with a superconducting ground state. Angle-resolved photoemission spectroscopy (ARPES) measurements combined with density-functional theory (DFT) calculations reveal the presence of multiple Dirac points near the Fermi level and predict topologically protected surfaces states only $0.05\\mathrm{eV}$ above the Fermi level at the $M$ points. Furthermore, both ARPES and DFT observe hexagonal Fermi surfaces, consistent with close proximity of saddle points at $M$ . Magnetization, heat capacity, and electrical resistivity measurements reveal the onset of superconductivity at $T_{c}=2.5\\textrm{K}$ and further identify a higher-temperature $T^{*}=$ $94~\\mathrm{K}$ transition suggestive of charge density wave order. Our work establishes $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ as a novel exfoliable, kagome metal with a superconducting ground state and protected Dirac crossings close to $E_{F}$ . \n\n![](images/40386be7f944705dffe9f2a0246535a4f7ebc025296ba7248e159e3cc937781c.jpg) \nFIG. 1. $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ is a layered compound with a structurally perfect kagome network of vanadium. There are two distinct Sb sites in the structure: (1) a simple hexagonal net woven into the kagome layer and (2) graphitelike layers of antimony (antimonene) above and below the kagome layer. All bonds $\\leq\\dot{3}.2\\mathrm{~\\AA~}$ have been drawn in the isometric perspective. \n\nSingle crystals of $\\mathrm{Cs}\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ were synthesized via a selfflux growth method [18]. Magnetization measurements were performed using a Quantum Design superconducting quantum interference device magnetometer (MPMS3) in vibrating-sample measurement mode, and resistivity and heat capacity measurements were performed using a Quantum Design Dynacool physical properties measurement system. ARPES measurements were obtained at the Stanford Synchrotron Radiation Lightsource (SSRL, beam line 5-2), a division of the SLAC National Accelerator Laboratory, using $120\\ \\mathrm{eV}$ photons with an energy resolution better than $20\\mathrm{\\meV}.$ . Temperature-dependent $\\mathbf{X}$ -ray diffraction data were collected at Brookhaven National Laboratory (beam line 28-ID-1) and at the Advanced Photon Source at Argonne National Laboratory (sector 6-ID-D). Rietveld refinements of temperature-dependent diffraction were performed using TOPAS Academic V6 [34]. Structure visualization was performed with the VESTA software package [19], and the electronic structure of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ was calculated in VASP v5.4.4 [35–37] using projector-augmented wave potentials [38,39] with details described in Supplemental Material [18]. \n\nFor an intuitive understanding of the $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ structure, we first consider the constituent sublattices. The hallmark two-dimensional kagome network is formed by the V1 sublattice and is interpenetrated by a simple hexagonal net of Sb1 antimony. All interatomic distances within the kagome layer are equal $(2.75\\mathrm{~\\AA~})$ , as required by the high symmetry of the V1 (Wyckoff $3g$ ) and Sb1 (Wyckoff $1b$ ) sites. The Sb2 sublattice creates graphitelike layers of Sb (antimonene) that encapsulate the kagome sheets. The Cs1 sublattice naturally fills the space between the graphitelike sheets, and the nearest Cs-Sb distance is nearly $\\Dot{4}\\ \\mathring{\\mathrm{A}}$ . \n\nBulk electronic properties of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ were studied via electron transport, magnetization, and heat capacity measurements. Figures 2(a)–2(c) show characterization data collected across a broad range of temperatures. Magnetization data collected under $\\mu_{0}H=1$ T are plotted as susceptibility $\\chi=(M/H)$ in Fig. 2(a) and show a hightemperature response $T>100~\\mathrm{K}$ ) consistent with Pauli paramagnetism. As a rough estimate, DFT calculations of the density of states at the Fermi level $g(E_{F})\\approx$ $10\\ \\mathrm{eV}^{-1}\\mathrm{cell}^{-1}$ estimate $\\chi\\approx200\\times10^{-6}$ emu $\\mathrm{Oe^{-1}m o l^{-1}}$ , which agrees reasonably well with the experimental data. At temperatures below $94~\\mathrm{~K~}$ , a sharp drop in the magnetization data denotes the onset of a phase transition, noted as $T^{*}$ . This transition also appears as an inflection point in the resistivity data shown in Fig. 2(b), where temperature-dependent resistivity data with current flowing both in the kagome planes $(\\rho_{a}b)$ and between the planes $(\\rho_{c})$ are plotted. The out-of-plane resistivity is nearly 600 times larger than in plane, emphasizing the two-dimensional nature of the Fermi surface. Heat capacity data plotted in Fig. 2(c) also illustrate a strong entropy anomaly at $T^{*}=94~\\mathrm{K}$ . The integrated entropy released through the $T^{*}$ transition is approximately $\\Delta S=1.6~\\mathrm{J}\\mathrm{mol}^{-1}\\mathrm{K}^{-1}$ and is naively too small to account for collective spin freezing of free $\\mathrm{\\DeltaV}$ moments. Instead, it likely arises from freezing within the charge sector [11], suggesting a potential charge or bond density wave anomaly that will be discussed later in this Letter. \n\nFigures 2(d)–2(f) show the onset of superconductivity in magnetization, resistivity, and heat capacity, respectively. In all cases, the onset of superconductivity occurs at approximately $T_{c}=2.5\\ \\mathrm{K}.$ Magnetization data reveal bulk superconductivity and a well-defined Meissner state, and heat capacity measurements show a sharp entropy anomaly at the superconducting transition, although, due to a limited temperature regime, we are unable to fully characterize the gapped behavior far below $T_{c}$ . The slight offset in the onset of $T_{c}$ in electrical resistivity [Fig. 2(e)] measurements is due to the high probe currents $\\mathrm{(8\\mA)}$ used in the dc measurement. Reduced currents show $T_{c}$ return to nominal values, although the data quality suffers significantly due to the low resistivity of $\\mathrm{Cs}\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ single crystals. \n\nHaving determined that $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ is a bulk kagome superconductor with a transition temperature $T_{c}=2.5\\:\\mathrm{K}$ , we next examine the normal state metal via a combination of ARPES measurements and DFT modeling. Figure 3(a) shows both ARPES and DFT modeling data with the hexagonal Brillouin zone superimposed on the $E=0~\\mathrm{eV}$ constant energy contour and high-symmetry points $K,M$ , and $\\Gamma$ labeled. Data collected with differing photon energies did not reveal any appreciable dispersion along $k_{z}$ , consistent with a quasi-2D band structure. ARPES data were collected at 50, 80, 100, and $120\\mathrm{K}$ , and no resolvable changes were observed in the band structure when transitioning through the $T^{*}$ transition. The DFT model shows remarkable agreement with the ARPES data, recovering all experimental observed crossings below the Fermi level. Figure 3(b) shows both the measured and calculated electronic structure hosts multiple Dirac points at finite binding energies. \n\n![](images/7c9ee718884e9dab75a42585fdb8649fe9761ce2fac4452da88f2e1a2bf305aa.jpg) \nFIG. 2. (a),(c),(e) Full temperature ranges for the magnetization, electrical resistivity, and heat capacity, respectively, shown for single crystals of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ . All measurements indicate the presence of an anomaly $T^{*}$ at $94~\\mathrm{K}$ , suspected to be an electronic instability (e.g., charge ordering). The inset in (a) shows line cuts through $\\mathbf{\\boldsymbol{x}}$ -ray diffraction data below and above $T^{*}$ . Dashed lines denote the appearance of half-integer reflections. (b),(d),(f) Field-dependent measurements at low temperatures, showing the onset of superconductivity in magnetization, resistivity, and heat capacity, respectively. The $T_{c}$ for $\\mathrm{CsV}_{3}\\mathrm{Sb}_{5}$ is approximately $2.5\\mathrm{~K~}$ , with a slight suppression in resistivity due to high probe currents. \n\nWhile inaccessible in the present ARPES data, the DFT model further reveals multiple topological band features slightly above the Fermi energy. The $\\bar{M}$ point is of particular interest, as $M$ is a time-reversal invariant momentum (TRIM) point. Figure 4 shows the results of a tight-binding calculation of surface states in $\\mathrm{Cs}\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ , where bright spots slightly above the Fermi energy indicate surface states. \n\nUnlike many heavily studied kagome lattices [e.g., $\\mathrm{ZnCu_{3}(O H)_{6}C l_{2}}$ [40–42], $\\mathrm{Fe}_{3}\\mathrm{Sn}_{2}$ [9,43], $\\begin{array}{r}{{\\bf M}{\\bf n}_{3}{\\bf G}{\\bf e}\\qquad}\\end{array}$ [44,45], and $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ [10,46,47]], $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ does not exhibit resolvable magnetic order. Given that $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ possesses both time-reversal and inversion symmetry as well as a continuous, symmetry-enforced, direct gap at every $k$ point, one can calculate the $\\mathbb{Z}_{2}$ topological invariant between each pair of bands near the Fermi level by simply analyzing the parity of the wave function at the TRIM points [48]. This analysis reveals a number of topologically nontrivial crossings between adjacent bands in the region $\\pm1\\ \\mathrm{eV}$ from the Fermi level. For clarity, we will focus on the surface states crossing at the $\\bar{M}$ point here with further analysis presented in Supplemental Material [18]. Figure 4(b) presents a close-up of the calculated surface states near the $\\bar{M}$ point. The surface states at the $\\bar{M}$ point manifest approximately $0.05\\mathrm{eV}$ above the Fermi energy. The apparent anisotropy in the calculated surface state dispersions ${\\bar{M}}{\\cdot}{\\bar{K}}$ versus $\\bar{M}$ - ¯Γ) derives from the direct “gap” moving up or down in energy depending on direction away from the $\\bar{M}$ point. This is not uncommon among topological metals [49–51]. \n\n![](images/d7f04edd67d2bccfb2a78ee89c3fec4e5a44a84e873ede9948144dc6ee552276.jpg) \nFIG. 3. Experimental ARPES data and comparison with DFT calculations. (a) A selection of constant energy maps at $80\\mathrm{K}$ are compared with DFT calculations, showing excellent agreement. The hexagonal Brillouin zone is superimposed on the $E=0~\\mathrm{eV}$ data. (b) ARPES and DFT data tracing from M-K-Γ-K-M reveal multiple Dirac points throughout the dispersion. Surface states can be observed in the DFT data at the $M$ point, slightly above $E_{F}$ . \n\nTopologically nontrivial surface states close to $E_{F}$ and the continuous direct gap throughout the Brillouin zone allow the identification of the normal state as a $\\mathbb{Z}_{2}$ topological metal [52,53]. The $T^{*}$ transition in this compound also suggests that electronic interactions are appreciable in this material. This transition is accompanied by a subtle change in the derivative of the lattice parameters, cell volume, and associated crystallographic parameters upon crossing $T^{*}$ [18]. Single-crystal $\\mathbf{X}$ -ray diffraction further shows the formation of a weak superlattice of charge scattering at half-integer reflections [an example shown in the inset in Fig. 2(a)] [18]. \n\nThe presence of a weak, structural superlattice is suggestive of a secondary structural response to a primary electronic order parameter such as a charge or bond density wave instability. Theoretical studies of partially filled kagome lattices predict a wide array of electronic order parameters [11]. The metallic nature of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ and its high degree of covalency makes formal charge assignment imprecise; however, in the ionic limit, the kagome lattice of V sites would possess one electron per triangle $(1/6$ filling). Charge density wave (CDW) order with a $(\\pi,0)$ in-plane wave vector consistent with our single-crystal x-ray diffraction data is predicted in spinful models and spinless fermion models of interacting electrons in a partially filled kagome lattice [11]. \n\n![](images/1c6e7b4aab09fe2a955fd79be9493c6bdaff7b35a99f50dd69b0c54ef7bf549c.jpg) \nFIG. 4. (a) Calculated band structure of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ along highsymmetry directions across the Brillouin zone. A continuous direct gap (shaded) is noted and high-symmetry points in the BZ are labeled. (b) Tight-binding model of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ showing topologically protected surface states that manifest at the timereversal invariant momentum $\\bar{M}$ point. \n\nNesting across a two-dimensional Fermi surface with an underlying hexagonal motif is also thought to promote the formation of a superconducting state [14]. Competing density wave instabilities may also arise, and, in the present case, scattering along the $(\\pi,0)$ wave vector would connect an enhanced density of states at saddle points near the Fermi energy at the $M$ points in $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ ’s band structure. To our knowledge, this is the first material example hosting the band structure, Fermi energy, and ground state requisite for this theoretical mechanism. Given the CDW-like instability observed at $T^{*}$ in this compound, interactions along this wave vector are likely enhanced and may promote a competition between CDW and superconducting instabilities. Although a structural superlattice exists, ARPES data do not resolve spectral broadening of the Fermi surface across the nested $M$ points, consistent with the long-range, weak nature of the high-temperature density wave order. Unconventional superconductivity with chiral $d$ -wave pairing may emerge in this scenario [1,13]. \n\nSuperconductivity manifest within an electronically twodimensional kagome lattice is rare unto itself. While other materials with kagome networks embedded within their lattice structures are known to superconduct (e.g., in certain silicides and borides [54,55]), all of these examples are inherently three-dimensional both structurally and electronically. $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ seemingly opens a unique opportunity for mapping to models of nesting-driven instabilities emergent within a two-dimensional kagome metal. Isostructural variants $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ and $\\mathrm{RbV}_{3}\\mathrm{Sb}_{5}$ host similar $T^{*}$ transitions at 80 and $104~\\mathrm{~K~}$ , respectively, likely indicative of a similar high-temperature density wave order [16]; however, superconductivity has been observed only in $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ to date. Understanding the interplay between the potentially competing $T^{*}$ order parameter and the formation of superconductivity across the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ family is an interesting topic for future study. \n\nThe $\\mathbb{Z}_{2}$ topological band structure of $\\mathrm{Cs}\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ may also be of interest for stabilizing the formation of Majorana modes within the vortex cores of a natively proximitized, superconducting surface state. Materials hosting both topologically nontrivial surface states and a native superconducting ground state are uncommon, with relatively few promising candidates identified in $\\mathrm{FeSe}_{\\left(1-x\\right)}\\mathrm{Te}_{x}$ [56–60], doped ${\\bf B i}_{2}{\\bf S e}_{3}$ [61–65], and $\\mathrm{Sn}_{(1-x)}\\mathrm{In}_{x}\\mathrm{Te}$ [66–68]. With relatively light electron doping (such as Ba substitution), $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ can likely be driven into a regime where such a proximitized topological surface state could be tested. \n\nIn summary, our results demonstrate that kagome metals can serve as a rich arena for exploring the interplay between correlated electron effects and superconductivity within a topologically nontrivial band structure. Our results demonstrate bulk superconductivity with $T_{c}=2.5\\textrm{K}$ in single crystals of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ and classify its normal state as a $\\mathbb{Z}_{2}$ topological metal with multiple topologically nontrivial band crossings in close proximity to the Fermi level. An anomalous CDW-like transition in the normal state suggests strong correlation effects and an electronic instability that weakly couples to the lattice. Future studies exploring the relation between this instability and the potential emergence of nesting-driven, unconventional superconductivity on the kagome lattice is motivated by our present results. \n\nS. D. W., R. S., L. B., and B. R. O. acknowledge support from the University of California Santa Barbara Quantum Foundry, funded by the National Science Foundation (NSF DMR-1906325). Research reported here also made use of shared facilities of the UC Santa Barbara Materials Research Science and Engineering Center (NSF DMR1720256). B. R. O. and P. M. S. also acknowledge support from the California NanoSystems Institute through the Elings fellowship program. S. M. L. T. has been supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1650114. This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE \n\nAC02-06CH11357. J.-F. H. and Y. H. were supported by the USTC start-up fund. The ARPES measurements were carried out under the user proposal program of SSRL, which is operated by the Office of Basic Energy Sciences, U.S. DOE, under Contract No. DE-AC02-76SF00515. This research used beam line 28-ID-1 of the National Synchrotron Light Source II, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Brookhaven National Laboratory under Contract No. DE-SC0012704. Shared computing facilities of the Center for Scientific Computing at UC Santa Barbara, supported by NSF CNS-1725797. Work at the Materials Science Division at Argonne National Laboratory (single crystal diffuse scattering) was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division. \n\n\\*ortiz.brendenr@gmail.com †stephendwilson@ucsb.edu \n[1] W.-S. Wang, Z.-Z. Li, Y.-Y. Xiang, and Q.-H. Wang, Phys. Rev. B 87, 115135 (2013). [2] S. V. Isakov, S. Wessel, R. G. Melko, K. Sengupta, and Y. B. Kim, Phys. Rev. Lett. 97, 147202 (2006). \n[3] A. O’Brien, F. Pollmann, and P. Fulde, Phys. Rev. B 81, 235115 (2010). [4] A. Rüegg and G. A. Fiete, Phys. Rev. B 83, 165118 (2011). [5] S. Yan, D. A. Huse, and S. R. White, Science 332, 1173 (2011). [6] H.-M. Guo and M. Franz, Phys. Rev. B 80, 113102 (2009). [7] W.-H. Ko, P. A. Lee, and X.-G. Wen, Phys. Rev. B 79, 214502 (2009). [8] M. Kang, L. Ye, S. Fang, J.-S. You, A. Levitan, M. Han, J. I. Facio, C. Jozwiak, A. Bostwick, E. Rotenberg et al., Nat. Mater. 19, 163 (2020). [9] L. Ye, M. Kang, J. Liu, F. Von Cube, C. R. Wicker, T. Suzuki, C. Jozwiak, A. Bostwick, E. Rotenberg, D. C. Bell et al., Nature (London) 555, 638 (2018). \n[10] N. Morali, R. Batabyal, P. K. Nag, E. Liu, Q. Xu, Y. Sun, B. Yan, C. Felser, N. Avraham, and H. Beidenkopf, Science 365, 1286 (2019). \n[11] J. Wen, A. Rüegg, C. C. Joseph Wang, and G. A. Fiete, Phys. Rev. B 82, 075125 (2010). \n[12] S.-L. Yu and J.-X. Li, Phys. Rev. B 85, 144402 (2012). \n[13] R. Nandkishore and A. V. Chubukov, Phys. Rev. B 86, 115426 (2012). \n[14] R. Nandkishore, L. Levitov, and A. Chubukov, Nat. Phys. 8, 158 (2012). \n[15] M. L. Kiesel, C. Platt, and R. Thomale, Phys. Rev. Lett. 110, 126405 (2013). \n[16] B. R. Ortiz, L. C. Gomes, J. R. Morey, M. Winiarski, M. Bordelon, J. S. Mangum, I. W. H. Oswald, J. A. RodriguezRivera, J. R. Neilson, S. D. Wilson et al., Phys. Rev. Mater. 3, 094407 (2019). \n[17] S.-Y. Yang, Y. Wang, B. R. Ortiz, D. Liu, J. Gayles, E. Derunova, R. Gonzalez-Hernandez, L. Smejkal, Y. Chen, S. S. Parkin et al., Sci. Adv. 6, eabb6003 (2020). \n[18] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevLett.125.247002 for experimental and theoretical details and supporting results, which includes Refs. [19–33]. \n[19] K. Momma and F. Izumi, J. Appl. Crystallogr. 44, 1272 (2011). \n[20] J. Sangster and A. Pelton, J. Phase Equilib. 18, 382 (1997). \n[21] A. Hammersley, S. Svensson, M. Hanfland, A. Fitch, and D. Hausermann, High Press. Res. 14, 235 (1996). \n[22] S. P. Westrip, J. Appl. Crystallogr. 43, 920 (2010). \n[23] G. Jennings, Crystal coordinate transformation workflow (CCTW), software available at https://sourceforge.net/ projects/cctw/. \n[24] R. Osborn and J. Wozniak, NexPy,” software available at https:github.com/nexpy/nexpy. \n[25] J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015). \n[26] S. Grimme, J. Comput. Chem. 27, 1787 (2006). \n[27] S. Grimme, S. Ehrlich, and L. Goerigk, J. Comput. Chem. 32, 1456 (2011). \n[28] J. P. Perdew, K. Burke, and M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996). \n[29] A. A. Mostofi, J. R. Yates, G. Pizzi, Y.-S. Lee, I. Souza, D. Vanderbilt, and N. Marzari, Comput. Phys. Commun. 185, 2309 (2014). \n[30] M. P. L. Sancho, J. M. L. Sancho, and J. Rubio, J. Phys. F 15, 851 (1985). \n[31] Q.-S. Wu, S.-N. Zhang, H.-F. Song, M. Troyer, and A. A. Soluyanov, Comput. Phys. Commun. 224, 405 (2018). \n[32] J. Gao, Q. Wu, C. Persson, and Z. Wang, arXiv:2002.04032. \n[33] G. F. Koster, Properties of the Thirty-Two Point Groups (MIT Press, Cambridge, MA, 1963), Vol. 24. \n[34] A. A. Coelho, J. Appl. Crystallogr. 51, 210 (2018). \n[35] G. Kresse and J. Hafner, Phys. Rev. B 49, 14251 (1994). \n[36] G. Kresse and J. Furthmüller, Phys. Rev. B 54, 11169 (1996). \n[37] G. Kresse and J. Furthmüller, Comput. Mater. Sci. 6, 15 (1996). \n[38] P. E. Blöchl, Phys. Rev. B 50, 17953 (1994). \n[39] G. Kresse and D. Joubert, Phys. Rev. B 59, 1758 (1999). \n[40] R. Braithwaite, K. Mereiter, W. Paar, and A. Clark, Mineral Mag. 68, 527 (2004). \n[41] D. E. Freedman, T. H. Han, A. Prodi, P. Müller, Q.-Z. Huang, Y.-S. Chen, S. M. Webb, Y. S. Lee, T. M. McQueen, and D. G. Nocera, J. Am. Chem. Soc. 132, 16185 (2010). \n[42] T.-H. Han, J. S. Helton, S. Chu, D. G. Nocera, J. A. Rodriguez-Rivera, C. Broholm, and Y. S. Lee, Nature (London) 492, 406 (2012). \n[43] Q. Wang, Q. Yin, and H. Lei, Chin. Phys. B 29, 017101 (2020). \n[44] A. K. Nayak, J. E. Fischer, Y. Sun, B. Yan, J. Karel, A. C. Komarek, C. Shekhar, N. Kumar, W. Schnelle, J. Kübler et al., Sci. Adv. 2, e1501870 (2016). \n[45] N. Kiyohara, T. Tomita, and S. Nakatsuji, Phys. Rev. Applied 5, 064009 (2016). \n[46] P. Vaqueiro and G. G. Sobany, Solid State Sci. 11, 513 (2009). \n[47] Q. Xu, E. Liu, W. Shi, L. Muechler, J. Gayles, C. Felser, and Y. Sun, Phys. Rev. B 97, 235416 (2018). \n[48] L. Fu and C. L. Kane, Phys. Rev. B 76, 045302 (2007). \n[49] B. Singh, X. Zhou, H. Lin, and A. Bansil, Phys. Rev. B 97, 075125 (2018). \n[50] I. Cucchi, A. Marrazzo, E. Cappelli, S. Riccò, F. Y. Bruno, S. Lisi, M. Hoesch, T. K. Kim, C. Cacho, C. Besnard, E. Giannini, N. Marzari, M. Gibertini, F. Baumberger, and A. Tamai, Phys. Rev. Lett. 124, 106402 (2020). \n[51] R. Yu, H. Weng, Z. Fang, X. Dai, and X. Hu, Phys. Rev. Lett. 115, 036807 (2015). \n[52] L. M. Schoop, L. S. Xie, R. Chen, Q. D. Gibson, S. H. Lapidus, I. Kimchi, M. Hirschberger, N. Haldolaarachchige, M. N. Ali, C. A. Belvin et al., Phys. Rev. B 91, 214517 (2015). \n[53] J. Nayak, S.-C. Wu, N. Kumar, C. Shekhar, S. Singh, J. Fink, E. E. Rienks, G. H. Fecher, S. S. Parkin, B. Yan et al., Nat. Commun. 8, 13942 (2017). \n[54] U. Rauchschwalbe, W. Lieke, F. Steglich, C. Godart, L. C. Gupta, and R. D. Parks, Phys. Rev. B 30, 444 (1984). \n[55] H.-Y. Lu, N.-N. Wang, L. Geng, S. Chen, Y. Yang, W.-J. Lu, W.-S. Wang, and J. Sun, Europhys. Lett. 110, 17003 (2015). \n[56] Z. Wang, P. Zhang, G. Xu, L. K. Zeng, H. Miao, X. Xu, T. Qian, H. Weng, P. Richard, A. V. Fedorov et al., Phys. Rev. B 92, 115119 (2015). \n[57] G. Xu, B. Lian, P. Tang, X.-L. Qi, and S.-C. Zhang, Phys. Rev. Lett. 117, 047001 (2016). \n[58] X. Wu, S. Qin, Y. Liang, H. Fan, and J. Hu, Phys. Rev. B 93, 115129 (2016). \n[59] P. Zhang, K. Yaji, T. Hashimoto, Y. Ota, T. Kondo, K. Okazaki, Z. Wang, J. Wen, G. Gu, H. Ding et al., Science 360, 182 (2018). \n[60] T. Machida, Y. Sun, S. Pyon, S. Takeda, Y. Kohsaka, T. Hanaguri, T. Sasagawa, and T. Tamegai, Nat. Mater. 18 811, (2019). \n[61] L. Fu and E. Berg, Phys. Rev. Lett. 105, 097001 (2010). \n[62] M. Kriener, K. Segawa, Z. Ren, S. Sasaki, and Y. Ando, Phys. Rev. Lett. 106, 127004 (2011). \n[63] S. Sasaki, M. Kriener, K. Segawa, K. Yada, Y. Tanaka, M. Sato, and Y. Ando, Phys. Rev. Lett. 107, 217001 (2011). \n[64] Z. Liu, X. Yao, J. Shao, M. Zuo, L. Pi, S. Tan, and C. Zhang, and Y. Zhang, J. Am. Chem. Soc. 137, 10512 (2015). \n[65] G. Du, Y. Li, J. Schneeloch, R. Zhong, G. Gu, H. Yang, H. Lin, and H.-H. Wen, Sci. China Phys. Mech. 60, 037411 (2017). \n[66] T. Sato, Y. Tanaka, K. Nakayama, S. Souma, T. Takahashi, S. Sasaki, Z. Ren, A. A. Taskin, K. Segawa, and Y. Ando, Phys. Rev. Lett. 110, 206804 (2013). \n[67] M. Novak, S. Sasaki, M. Kriener, K. Segawa, and Y. Ando, Phys. Rev. B 88, 140502(R) (2013). \n[68] C. M. Polley, V. Jovic, T.-Y. Su, M. Saghir, D. Newby, Jr., B. J. Kowalski, R. Jakiela, A. Barcz, M. Guziewicz, T. Balasubramanian et al., Phys. Rev. B 93, 075132 (2016). " + }, + { + "id": "10.1038_s41586-020-2208-x", + "DOI": "10.1038/s41586-020-2208-x", + "DOI Link": "http://dx.doi.org/10.1038/s41586-020-2208-x", + "Relative Dir Path": "mds/10.1038_s41586-020-2208-x", + "Article Title": "Enhanced ferroelectricity in ultrathin films grown directly on silicon", + "Authors": "Cheema, SS; Kwon, D; Shanker, N; dos Reis, R; Hsu, SL; Xiao, J; Zhang, HG; Wagner, R; Datar, A; McCarter, MR; Serrao, CR; Yadav, AK; Karbasian, G; Hsu, CH; Tan, AJ; Wang, LC; Thakare, V; Zhang, X; Mehta, A; Karapetrova, E; Chopdekar, R; Shafer, P; Arenholz, E; Hu, CM; Proksch, R; Ramesh, R; Ciston, J; Salahuddin, S", + "Source Title": "NATURE", + "Abstract": "Ultrathin ferroelectric materials could potentially enable low-power perovskite ferroelectric tetragonality logic and nonvolatile memories(1,2). As ferroelectric materials are made thinner, however, the ferroelectricity is usually suppressed. Size effects in ferroelectrics have been thoroughly investigated in perovskite oxides-the archetypal ferroelectric system(3). Perovskites, however, have so far proved unsuitable for thickness scaling and integration with modern semiconductor processes(4). Here we report ferroelectricity in ultrathin doped hafnium oxide (HfO2), a fluorite-structure oxide grown by atomic layer deposition on silicon. We demonstrate the persistence of inversion symmetry breaking and spontaneous, switchable polarization down to a thickness of one nullometre. Our results indicate not only the absence of a ferroelectric critical thickness but also enhanced polar distortions as film thickness is reduced, unlike in perovskite ferroelectrics. This approach to enhancing ferroelectricity in ultrathin layers could provide a route towards polarization-driven memories and ferroelectric-based advanced transistors. This work shifts the search for the fundamental limits of ferroelectricity to simpler transition-metal oxide systems-that is, from perovskite-derived complex oxides to fluorite-structure binary oxides-in which 'reverse' size effects counterintuitively stabilize polar symmetry in the ultrathin regime. Enhanced switchable ferroelectric polarization is achieved in doped hafnium oxide films grown directly onto silicon using low-temperature atomic layer deposition, even at thicknesses of just one nullometre.", + "Times Cited, WoS Core": 634, + "Times Cited, All Databases": 670, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000528065800018", + "Markdown": "# Article \n\n# Enhanced ferroelectricity in ultrathin films grown directly on silicon \n\nhttps://doi.org/10.1038/s41586-020-2208-x \n\nReceived: 15 July 2019 \n\nAccepted: 27 January 2020 \n\nPublished online: 22 April 2020 Check for updates \n\nSuraj S. Cheema1,13 ✉, Daewoong Kwon2,12,13, Nirmaan Shanker1,2, Roberto dos Reis3, Shang-Lin Hsu3,7, Jun Xiao4, Haigang Zhang5, Ryan Wagner5, Adhiraj Datar1,2, Margaret R. McCarter6, Claudy R. Serrao2, Ajay K. Yadav2, Golnaz Karbasian2, Cheng-Hsiang Hsu2, Ava J. Tan2, Li-Chen Wang1, Vishal Thakare1, Xiang Zhang4, Apurva Mehta8, Evguenia Karapetrova9, Rajesh V Chopdekar10, Padraic Shafer10, Elke Arenholz10,11, Chenming Hu2, Roger Proksch5, Ramamoorthy Ramesh1,6, Jim Ciston3 & Sayeef Salahuddin2,7 ✉ \n\nUltrathin ferroelectric materials could potentially enable low-power perovskite ferroelectric tetragonality logic and nonvolatile memories1,2. As ferroelectric materials are made thinner, however, the ferroelectricity is usually suppressed. Size effects in ferroelectrics have been thoroughly investigated in perovskite oxides—the archetypal ferroelectric system3. Perovskites, however, have so far proved unsuitable for thickness scaling and integration with modern semiconductor processes4. Here we report ferroelectricity in ultrathin doped hafnium oxide $\\left(\\mathsf{H f O}_{2}\\right)$ , a fluorite-structure oxide grown by atomic layer deposition on silicon. We demonstrate the persistence of inversion symmetry breaking and spontaneous, switchable polarization down to a thickness of one nanometre. Our results indicate not only the absence of a ferroelectric critical thickness but also enhanced polar distortions as film thickness is reduced, unlike in perovskite ferroelectrics. This approach to enhancing ferroelectricity in ultrathin layers could provide a route towards polarization-driven memories and ferroelectric-based advanced transistors. This work shifts the search for the fundamental limits of ferroelectricity to simpler transition-metal oxide systems—that is, from perovskite-derived complex oxides to fluorite-structure binary oxides—in which ‘reverse’ size effects counterintuitively stabilize polar symmetry in the ultrathin regime. \n\nFerroelectric materials exhibit stable states of collectively ordered electrical dipoles whose polarization can be reversed under an applied electric field5. Consequently, ultrathin ferroelectrics are of great technological interest for high-density electronics, particularly field-effect transistors and non-volatile memories2. However, ferroelectricity is typically suppressed at the scale of a few nanometres in the ubiquitous perovskite oxides6. First-principles calculations predict six unit cells to be the critical thickness in perovskite ferroelectrics1 owing to incomplete screening of depolarization fields3. Atomic-scale ferroelectricity in perovskites often fails to demonstrate polarization switching7,8, which is crucial for applications. Furthermore, attempts to synthesize ferroelectric perovskite films on silicon9,10 are impeded by chemical incompatibility4,11 and the high temperatures required for epitaxial growth. Since the discovery of ferroelectricity in ${\\mathsf{H f O}}_{2}$ -based thin films in $2011^{12}$ , fluorite-structure binary oxides (fluorites) have attracted considerable interest13 because they enable low-temperature synthesis and conformal growth in three-dimensional structures on silicon14,15, thereby overcoming many of the issues that restrict its perovskite counterparts in terms of complementary metal-oxide-semiconductor (CMOS) compatibility and thickness scaling16. Considering the extensive implications for future computing2,17,18, achieving ferroelectricity in sub $-2-\\mathsf{n m}$ -thick doped- ${\\bf\\cdot H f O}_{2}$ is highly desirable for realizing ultra-scaled CMOS-compatible ferroelectric-based devices beyond the 5 nm technology node19. \n\nHere we demonstrate ferroelectricity in ultrathin (1 nm thick) $\\mathsf{H f}_{0.8}Z\\mathsf{r}_{0.2}\\mathsf{O}_{2}(\\mathsf{H Z O})$ , grown by low-temperature atomic layer deposition (ALD) on silicon. Second harmonic generation and advanced scanning probe techniques establish the presence of inversion symmetry breaking and switchable electric polarization, respectively. Not only is ferroelectricity stabilized in ultrathin HZO, but spectroscopic and diffraction signatures of its fluorite-structure symmetry also indicate enhanced polar distortion in the ultrathin regime. Such size effects in this fluorite-structure system do not occur in its perovskite counterparts6, which can be understood from symmetry considerations. In symmetry relative to the bulk-stable centrosymmetric M-phase. Consequently, both intrinsic (surface energy) and extrinsic (confinement strain) mechanisms can favour ultrathin inversion symmetry breaking in fluorite-structures, in stark contrast to size effect trends perovskites (Extended Data Fig. 1). b, Cross-sectional ADF STEM image of 20-cycle (about $1.8\\mathsf{n m}$ ) HZO, demonstrating ultrathin HZO films on silicon via low-temperature ALD. The Si substrate is oriented along the [110] zone axis. c, Schematic heterostructure investigated in this work, detailing the ultrathin ferroelectric HZO layer deposited on $\\mathsf{S i}/\\mathsf{S i O}_{2},$ and the capping metal layer employed to impart confinement strain during post-deposition rapid thermal annealing (Methods). \n\n![](images/7c38a01651c507eecdbef9abb38e0319ceca52ac40a9352a00825cf86ab9b411.jpg) \nFig. 1 | Size effects in fluorite-structure ferroelectrics. a, In fluorite-structure ferroelectrics, the polar distortion present in the orthorhombic phase can be represented as the centre anion displacement (cyan) with respect to its surrounding cation tetrahedron (represented by cyan arrow); in the nonpolar tetragonal phase, the oxygen atom (blue) lies in the polyhedral centre of the tetrahedron. The evolution of the bulk-stable monoclinic polymorph to the high-symmetry tetragonal and polar orthorhombic phases in the fluorite-structure structure illustrates the role of size effects – surface energies favour higher symmetry – and confinement strain – distortions favour lower symmetry – on stabilizing inversion asymmetry. In fluorite-structures, the noncentrosymmetric O-phase is higher \n\nclassical perovskites, surface-energy-driven size effects at reduced dimensions favour the high-symmetry paraelectric phase (cubic) over the low-symmetry ferroelectric phase (tetragonal)20. Conversely, in fluorites, the noncentrosymmetric phase (orthorhombic $P c a2_{1},$ O-phase) is higher-symmetry relative to the bulk-stable centrosymmetric phase $(P2_{\\mathrm{{r}}}/c$ , M-phase)21. Consequently, surface energies can promote (destabilize) inversion symmetry breaking in fluorite (perovskite) ferroelectrics in the two-dimensional limit21,22. Owing to this size-induced noncentrosymmetry—that is, ‘reverse’ size effects (Fig. 1a, Extended Data Fig. 1)—HZO presents a promising model system in which to explore the ultrathin limits of ferroelectricity. \n\nThin films of HZO are grown using ALD down to ten cycles on oxidized silicon at $250^{\\circ}\\mathrm{C}$ . For reference, approximately 11 ALD cycles correspond to 1 nm thickness, as confirmed by X-ray reflectivity (XRR, Extended Data Fig. 2) and transmission electron microscopy (TEM, Extended Data Fig. 3). Subsequently, HZO films are capped by a metal and subjected to rapid thermal annealing—henceforth referred to as confinement strain (Fig. 1c)—to impart anisotropic thermal stresses. Confinement strain has been reported to help distort the high-symmetry tetragonal fluorite-structure polymorph $(P4_{2}/n m c$ , T-phase) into the polar O-phase13 (Fig. 1a). For confined ultrathin HZO films, X-ray diffraction analysis indicates a highly oriented noncentrosymmetric structure in contrast to polycrystalline thicker films (Extended Data Fig. 4). Inversion symmetry breaking in 10 cycle (about 1 nm) HZO films is confirmed by the presence of second harmonic generation (SHG) (Extended Data Fig. 5), previously employed to demonstrate ferroelectricity in a two-dimensional material23. \n\nBeyond inversion asymmetry, ferroelectricity also requires electrical switching between polarization states. Resonance-enhanced piezoresponse force microscopy (PFM) demonstrates bistable switching in $\\mathrm{Si}/\\mathrm{SiO}_{2}/\\mathrm{HZO}$ heterostructures (Fig. 2a). PFM phase images on ten-cycle HZO films (Fig. 2d) show well defined regions of $180^{\\circ}$ phase contrast— corresponding to remanent polarization states (Fig. 2b)—that can be rewritten in a non-volatile fashion. Notably, unpoled regions demonstrate the same phase contrast as positively poled regions (Fig. 2d), indicating that ultrathin HZO exhibits spontaneous polarization. In previous studies, field cycling is often required to ‘wake up’ the ferroelectricity in ${\\mathsf{H f O}}_{2}$ -based fluorites, which is attributed to a field-induced nonpolar-polar phase transition13. Here, atomic-scale thickness in tandem with mechanical confinement enhances the polar phase stability to exhibit spontaneous polarization, eliminating one of the most critical issues plaguing fluorite-structure ferroelectrics16. Rapid thermal annealing alone is insufficient for ferroelectricity; regions of HZO annealed without a metal capping layer do not exhibit ferroelectric signatures (Extended Data Fig. 6). This highlights the critical role of ultrathin confinement, and the strains imposed by such layering, on stabilizing the polar O-phase in ultrathin fluorite-structure films. \n\nAlong with phase contrast imaging, local PFM switching spectroscopy further confirms the robust ferroelectricity in ten-cycle HZO films, as demonstrated by $180^{\\circ}$ phase hysteresis and its butterfly-shape amplitude $(d_{33})$ loops (Fig. 2e). PFM spectroscopy was performed on metal electrodes to eliminate electrostatic artefacts from the tip24 and potential electromechanical contributions (Methods). In addition, careful monitoring of topography was performed during poling (Extended Data Fig. 7a) to detect the possibility of any electrochemical and electromechanical artefacts. Time-dependent PFM imaging (Extended Data Fig. 7b) on ten-cycle HZO illustrates polarization patterns sustained for at least $24\\mathsf{h}$ ; such long-term retention suggests that the PFM contrast is due to ferroelectric behaviour and not due to shorter-scale spurious effects often attributed to amorphous hafnia25. Furthermore, alternating voltage $(V_{\\mathrm{ac}})$ -dependent piezoresponse loops (Extended Data Fig. 7c) rule out electrostatic artefacts from charging25. Moving beyond the standard PFM optical beam detection method, interferometric displacement sensor (IDS) PFM measurements (Extended Data Fig. 7d) definitively demonstrate the ferroelectric origin of switching spectroscopy hysteresis in ten-cycle HZO. The recently developed IDS technique26 eliminates the long-range electrostatics and cantilever resonance artefacts that obfuscate typical voltage-modulated PFM. Contact IDS measurements demonstrate $180^{\\circ}$ phase hysteresis and butterfly-shaped $d_{33},$ which is indicative of ferroelectric behaviour free of electrostatic contributions26. A lack of electrostatically driven hysteresis is confirmed by off-surface measurements (Extended Data Fig. 7d). Along with IDS, scanning capacitance microscopy (SCM) provides another advanced scanning probe technique with which to probe ferroelectricity in ultrathin HZO. SCM differential capacitance spectroscopy on ten-cycle HZO demonstrates butterfly-shaped capacitance–voltage (C–V) hysteresis (Fig. 2c, Extended Data Fig. 8). The microwave-frequency detection in SCM (Methods) mitigates the leakage currents that prevent typical bulk electrical characterization of ultrathin ferroelectrics, and provides conclusive evidence of ferroelectric polarization switching. \n\n![](images/bad6ba3cc3421455941bc8f10c5db1efa4d08afed50786ae48b70936af4343af.jpg) \nFig. 2 | Electric polarization switching in ultrathin HZO. a, Schematic of the $\\mathrm{Si}/\\mathrm{SiO}_{2}(2\\mathrm{nm})/\\mathrm{HZO}(1$ nm) heterostructure investigated by scanning probe imaging. b, Schematic of the HZO unit cell in the ferroelectric orthorhombic structure (Pca21). The different-coloured oxygen atoms represent the displaced oxygen atoms (cyan) and the centrosymmetric oxygen atoms (blue) within the surrounding cation tetrahedron. The blue arrows labelled P denote the polarization directions corresponding to the acentric oxygen atomic displacements. c, Microwave-frequency SCM spectroscopy for a ten-cycle HZO film. The presence of butterfly-shaped C–V conclusively demonstrates ferroelectricity in ultrathin HZO, enabled by the high-frequency detection of differential capacitance (Methods). Microwave dC/dV measurements on multiple regions of ten-cycle HZO demonstrate the robust ferroelectric behaviour (Extended Data Fig. 8). d, Phase-contrast PFM images demonstrating stable, bipolar, remanent polarization states that can be \n\noverwritten into the opposite polarization state for a ten-cycle HZO film. We note that the unpoled outer perimeter matches phase contrast with the positively poled regime regardless of the poling-polarity sequence; this indicates that ultrathin HZO exhibits spontaneous polarization without requiring ‘wake-up’ effects to become ferroelectric. Time-dependent PFM imaging further demonstrates the robust ferroelectric contrast (Extended Data Fig. 7). e, Phase and amplitude switching spectroscopy loops for a ten-cycle HZO film, demonstrating ferroelectric-like hysteresis. Interferometry-based IDS PFM hysteresis loops confirm that the origin of switching spectroscopy hysteresis is free of artefacts (Extended Data Fig. 7) and switching-spectroscopy measurements demonstrating the critical role of confinement during phase annealing for stabilizing the polar phase in ultrathin HZO (Extended Data Fig. 6). \n\nTo examine the structural and electronic origins of ferroelectricity in HZO, we employ grazing-incidence X-ray diffraction (GI-XRD) and X-ray absorption spectroscopy (XAS) (Fig. 3). GI-XRD alone cannot unambiguously distinguish between certain fluorite-structure polymorphs in ultrathin HZO; as a complement to diffraction, XAS provides spectroscopic signatures of the polar O-phase and nonpolar T-phase. In particular, the T-phase nonpolar distortion $\\cdot D_{4h},$ fourfold prismatic symmetry) from regular tetrahedral to fluorite-structure symmetry does not split the degenerate $e$ orbitals $(d_{x^{2}-y^{2}},d_{3z^{2}-r^{2}})$ . Meanwhile, the O-phase polar rhombic pyramidal distortion $C_{2\\upsilon},$ twofold pyramidal symmetry) does split the e manifold, providing a symmetry-specific spectroscopic marker (Extended Data Fig. 9a,b). Owing to the $d^{0}$ electronic configuration present in ${\\mathsf{H}}{\\mathsf{f}}^{4+}({\\mathsf{Z}}{\\mathsf{r}}^{4+})$ , spectral weight from oxygen $K$ -edge XAS can be attributed solely to crystal field effects, providing additional insights into the degree of structural distortion. The spectral weight of the symmetry-split e regimes (Extended Data Fig. 9c) and pre-edge regime (Extended Data Fig. 9e) increases with decreasing thickness, indicative of more pronounced rhombic distortion and divergence from isotropic nearest-neighbour oxygen polyhedral coordination (Extended Data Fig. 9d), respectively. These spectral weight trends provide further evidence of ultrathin-enhanced distortions. In conjunction with XAS, X-ray linear dichroism (XLD) can also probe structural distortions owing to its sensitivity to orbital asymmetry. Nanospectroscopy via soft X-ray photoemission electron microscopy (PEEM) illustrates spatially resolved XLD contrast at $535\\mathrm{eV}$ (Extended Data Fig. 9f), corresponding to the $e$ -split rhombic distortion regime. This suggests that XLD at the O K edge is indeed sensitive to polar features in ultrathin HZO. Shifting to sample-averaged XLD at the $\\mathsf{Z r}M_{2}$ edge, the orbital polarization is found to increase from the thick (100-cycle) to ultrathin (ten-cycle) regime (Fig. 3c), indicative of increased oxygen polyhedral distortion (Fig. 3d) consistent with ultrathin-enhanced ferroelectricity. \n\nRemarkably, we also observe the emergence of crystallographic texturing of HZO films in the ultrathin regime (Fig. 1b, 3e). We note that many of the reflections in 100-cycle HZO, including the dominant (111), are absent in the GI-XRD spectra below 25 cycles owing to the geometric limitations of one-dimensional spectra (unable to detect all the reflections present in highly oriented films) (Methods). Tilted-geometry $(\\varphi-\\chi)$ diffraction (that is, pole figures) are required to access these oriented reflections at specific points, rather than polycrystalline-like rings, in reciprocal space. The spot-like patterns present in pole figures about the (111) reflections (Extended Data Fig. 4b) confirm the high degree of texturing in ultrathin HZO. Interestingly, this texturing happens despite local nanocrystalline regions observed in TEM for ultrathin films (for example, 15-cycle HZO in Extended Data Fig. 3d). Coinciding with the onset of texturing, the microstructural evolution below 25-cycle HZO manifests spectroscopically as inverted orbital polarization at the e  manifold (Fig.  3b), suggesting flipped polar-distortion-split $e$ levels $(d_{x^{2}-y^{2}}$ and $d_{3z^{2}-r^{2}})$ ). This indicates that sub-25-cycle ultrathin films enter a new electronic structure concurrently as the crystalline structure orders. Therefore, confinement strain in atomic-scale fluorite films could provide a route to tailor electronic structure and engineer polarization at the orbital level27, akin to epitaxial strain in perovskite films. \n\n![](images/fbe67296795591e8f5589d0ca14fcd3f7318f2fb66fcb9b0f76729a90276fb33.jpg) \nFig. 3 | Emergence of ‘reverse’ size effects in ultrathin HZO. a, Thickness-dependent XAS at the O K edge; spectral weight XAS trends indicate enhanced polyhedral disorder and tetrahedral and rhombic distortions in ultrathin films, illustrated by the crystal field splitting diagram for the fluorite-structure structural polymorphs and symmetry-specific XAS simulations (Extended Data Fig. 9a, b). The e and $t_{2}d\\cdot$ electron energy manifolds are set by the fluorite-structure tetrahedral symmetry (Extended Data Fig. 9a). b, Thickness-dependent XLD at the O K edge; the orbital polarization inversion below 25 cycles corresponds to the onset of highly oriented ultrathin films. c, Thickness-dependent orbital polarization and XLD (inset) at the $\\mathsf{Z r}M_{2}$ edge. The orbital polarization trend indicates ultrathin-enhanced $Z\\mathrm{r}{\\bf O}_{4}$ tetrahedral distortion, schematically represented in d by acentric oxygen atomic \ndisplacement (cyan atoms). e, Synchrotron GI-XRD demonstrating the emergence of highly oriented ultrathin films, consistent with ADF-STEM (Fig. 1b) and pole figure analysis of ultrathin HZO (Extended Data Fig. 4b). f, Thickness-dependent GI-XRD around the polar orthorhombic (111) reflection, demonstrating a systematic shift in $2\\theta_{\\mathrm{{u1}}}$ with thickness, and highlighting the limitation of GI-XRD geometry to detect the (111)-reflection below 25 cycles as the film becomes highly oriented (Extended Data Fig. 4). g, Thickness-dependent $d_{\\mathrm{{u1}}}$ lattice spacing and $2c/(a+b)$ structural aspect ratio, suggesting amplified polarization in the ultrathin limit, especially below 25 cycles. Dashed lines denote reported $d_{\\mathrm{{u1}}}$ and aspect ratio values for thicker ferroelectric HZO films. Aspect ratio values are extracted from the symmetry-split {200} planes (Methods). \n\nThe onset of highly ordered films also coincides with sharp rises in structural markers of distortion (Fig. 3g). The degree of rhombic distortion is captured by the lattice spacing $d_{\\mathrm{{u1}}},$ accordingly, $d_{\\mathrm{{u1}}}$ is tied to macroscopic polarization in $\\mathsf{H Z O}^{28,29}$ . We observe increasing $d_{\\mathrm{{u1}}}$ with decreasing thickness (Fig. 3g), as previously reported in epitaxial HZO films grown by pulsed laser deposition28,29, consistent with ultrathin-enhanced ferroelectricity. Notably, our low-temperature ALD-grown films on silicon can induce similar structurally induced phenomena observed in high-temperature pulsed-laser-deposition-grown epitaxial films on perovskite templates and extended to an even thinner limit. Furthermore, the $d_{\\mathrm{{u1}}}$ bifurcation below 25 cycles suggests a link between texturing and amplified distortion in the ultrathin regime. Another crystallographic signature, orthorhombic aspect ratio $(2c/a+b)$ , also indicates enhanced distortions in the ultrathin regime (Fig. 3g). Fluorite-structure orthorhombicity13 is akin to perovskite tetragonality $^{30}\\left(c/a\\right)$ ; these ratios serve as structural barometers of macroscopic polarization. The orthorhombic distortion present in ten-cycle HZO far exceeds any reported values for ${\\mathsf{H f O}}_{2}–Z{\\mathsf{r O}}_{2}$ polymorphs13: we find $510\\%$ aspect asymmetry, whereas $3-4\\%$ is typically reported for fluorite-structure ferroelectrics, consistent with our thicker films (Fig. 3g). Correspondingly, the tetrahedral and rhombic crystal field splitting energies in ultrathin films surpass expected polar fluorite-structure values by $1.3\\mathrm{eV}$ and 700 meV, respectively (Extended Data Fig. ${\\mathfrak{s g}}.$ ). Such colossal structural splittings are well beyond the reported limits of epitaxial strain in perovskite films27. Therefore, although prohibitive tunnel currents prevent accurate quantification of polarization from traditional polarization–voltage measurements, multiple structural gauges of polarization indicate substantial enhancement in the ultrathin limit. \n\nIn summary, several techniques self-consistently demonstrate robust ferroelectricity in HZO films of thickness down to 1 nm (Extended Data Fig. 2, 3), synthesized by low-temperature ALD on silicon. Remarkably, these experiments indicate that polar distortions are amplified in the ultrathin limit; diffraction markers $\\cdot d_{\\mathrm{{n}}}$ lattice spacing, structural aspect ratio) and spectroscopic signatures (orbital polarization, crystal \n\n# Article \n\nfield splitting) all demonstrate ultrathin enhancement. Such ‘reverse’ size effects oppose conventional perovskite ferroelectric trends6. Previous works on polycrystalline doped ${\\mathsf{H f O}}_{2}^{31-33}$ have explained thickness-dependent polarization trends based on the volume fraction of the ferroelectric O-phase. However, our observations are more consistent with studies of pseudo-epitaxial HZO films grown on perovskite templates28,29 in that we also observe substantial orientation in the ultrathin regime and enhancement of ferroelectricity with decreasing thickness. Importantly, our work demonstrates that this enhancement persists down to at least two fluorite-structure unit cell thickness, overcoming the deleterious depolarization field effects that would otherwise dominate a prototypical perovskite-structure ferroelectric in this ultrathin regime1,34. Further studies should explore how the current understanding of film synthesis, phase competition and polar distortion in HZO developed for thicker films $(>5\\mathsf{n m})^{35}$ evolves in the ultrathin regime $(<2\\mathsf{n m})$ . Our results indicate that harnessing confinement strain to amplify atomic displacements in ultrathin films provides a route towards enhancing electric polarization at the nanoscale beyond epitaxial strain36,37, akin to strain gradients in flexoelectricity38,39. From a technological perspective, direct monolithic integration of ultrathin doped $\\mathsf{H f O}_{2}\\mathsf{o n S i}/\\mathsf{S i O}_{2}$ paves the way for polarization-driven low-power memories (Extended Data Fig. 10) and ultra-scaled ferroelectrics-based transistors40,41. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at [https://doi.org/10.1038/s41586-020-2208-x]. \n\n1. Junquera, J. & Ghosez, P. Critical thickness for ferroelectricity in perovskite ultrathin films. Nature 422, 506–509 (2003). \n2. Mikolajick, T., Slesazeck, S., Park, M. & Schroeder, U. Ferroelectric hafnium oxide for ferroelectric random-access memories and ferroelectric field-effect transistors. MRS Bull. 43, 340–346 (2018). \n3. Dawber, M., Rabe, K. M. & Scott, J. F. Physics of thin-film ferroelectric oxides. Rev. Mod. Phys. 77, 1083–1130 (2005). \n4. Schlom, D. G., Guha, S. & Datta, S. Gate oxides beyond $S_{\\mathrm{IO}_{2}}^{\\mathrm{:}}$ MRS Bull. 33, 1017–1025 (2008). \n5. Lines, M. E. & Glass, A. M. Principles and Applications of Ferroelectrics and Related Materials (Oxford Univ. Press, 1977). \n6. Ahn, C., Rabe, K. & Triscone, J. Ferroelectricity at the nanoscale: local polarization in oxide thin films and heterostructures. Science 303, 488–491 (2004). \n7. Fong, D. D. et al. Ferroelectricity in ultrathin perovskite films. Science 304, 1650–1653 (2004). \n8. Tenne, D. A. et al. Probing nanoscale ferroelectricity by ultraviolet Raman spectroscopy. Science 313, 1614–1616 (2006). \n9. Warusawithana, M. P. et al. A ferroelectric oxide made directly on silicon. Science 324, 367–370 (2009). \n10. Dubourdieu, C. et al. Switching of ferroelectric polarization in epitaxial ${\\mathsf{B a T i O}}_{3}$ films on silicon without a conducting bottom electrode. Nat. Nanotechnol. 8, 748–754 (2013). \n11. Schlom, D. G. & Haeni, J. H. A thermodynamic approach to selecting alternative gate dielectrics. MRS Bull. 27, 198–204 (2002). \n12. Böscke, T. S., Müller, J., Bräuhaus, D., Schröder, U. & Böttger, U. Ferroelectricity in hafnium oxide thin films. Appl. Phys. Lett. 99, 102903 (2011). \n13.\t Park, M. H. et al. Ferroelectricity and antiferroelectricity of doped thin HfO2-based films. Adv. Mater. 27, 1811–1831 (2015). \n14. Robertson, J. High dielectric constant gate oxides for metal oxide Si transistors. Rep. Prog. Phys. 69, 327 (2006). \n15. Muller, J. et al. Ferroelectric hafnium oxide: a CMOS-compatible and highly scalable approach to future ferroelectric memories. In 2013 IEEE Int. Electron Devices Meet. (IEDM) 10.8.1–10.8.4 (IEEE, 2013). \n16.\t Park, M., Lee, Y., Mikolajick, T., Schroeder, U. & Hwang, C. Review and perspective on ferroelectric ${\\mathsf{H f O}}_{2}$ -based thin films for memory applications. MRS Commun. 8, 795–808 (2018). \n17. Wong, J. C. & Salahuddin, S. Negative capacitance transistors. Proc. IEEE 107, 49–62 (2019). \n18. Kwon, D. et al. Improved subthreshold swing and short channel effect in FDSOI n-channel negative capacitance field effect transistors. IEEE Electron Device Lett. 39, 300–303 (2018). \n19. Salahuddin, S., Ni, K. & Datta, S. The era of hyper-scaling in electronics. Nat. Electron. 1, 442–450 (2018). \n20. Merz, W. J. The effect of hydrostatic pressure on the Curie point of barium titanate single crystals. Phys. Rev. 78, 52 (1950). \n21. Ohtaka, O. et al. Phase relations and volume changes of hafnia under high pressure and high temperature. J. Am. Ceram. Soc. 84, 1369–1373 (2001). \n22.\t Materlik, R., Künneth, C. & Kersch, A. The origin of ferroelectricity in $\\mathsf{H f}_{1-x}\\mathsf{Z r}_{x}\\mathsf{O}_{2}$ : a computational investigation and a surface energy model. J. Appl. Phys. 117, 134109 (2015). \n23.\t Xiao, J. et al. Intrinsic two-dimensional ferroelectricity with dipole locking. Phys. Rev. Lett. 120, 227601 (2018). \n24.\t Vasudevan, R. K., Balke, N., Maksymovych, P., Jesse, S. & Kalinin, S. V. Ferroelectric or non-ferroelectric: why so many materials exhibit “ferroelectricity” on the nanoscale. Appl. Phys. Rev. 4, 021302 (2017). \n25. Balke, N. et al. Differentiating ferroelectric and nonferroelectric electromechanical effects with scanning probe microscopy. ACS Nano 9, 6484–6492 (2015). \n26. Collins, L., Liu, Y., Ovchinnikova, O. S. & Proksch, R. Quantitative electromechanical atomic force microscopy. ACS Nano 13, 8055–8066 (2019). \n27. Disa, A. S. et al. Orbital engineering in symmetry-breaking polar heterostructures. Phys. Rev. Lett. 114, 026801 (2015). \n28.\t Wei, Y. et al. A rhombohedral ferroelectric phase in epitaxially strained $\\mathsf{H f}_{0.5}Z\\mathsf{r}_{0.5}\\mathsf{O}_{2}$ thin films. Nat. Mater. 17, 1095–1100 (2018). \n29.\t Lyu, J., Fina, I., Solanas, R., Fontcuberta, J. & Sánchez, F. Growth window of ferroelectric epitaxial $\\mathsf{H f}_{0.5}Z\\mathsf{r}_{0.5}\\mathsf{O}_{2}$ thin films. ACS Appl. Electron. Mater. 1, 220–228 (2019). \n30.\t Schlom, D. G. et al. Elastic strain engineering of ferroic oxides. MRS Bull. 39, 118–130 (2014). \n31. Park, M. H. et al. Evolution of phases and ferroelectric properties of thin $\\mathsf{H f}_{0.5}Z\\mathsf{r}_{0.5}\\mathsf{O}_{2}$ films according to the thickness and annealing temperature. Appl. Phys. Lett. 102, 242905 (2013). \n32.\t Tian, X. et al. Evolution of ferroelectric $H\\mathsf{f}O_{2}$ in ultrathin region down to 3 nm. Appl. Phys. Lett. 112, 102902 (2018). \n33.\t Richter, C. et al. Si doped hafnium oxide—a “fragile” ferroelectric system. Adv. Electron. Mater. 3, 1700131 (2017). \n34.\t Stengel, M. & Spaldin, N. A. Origin of the dielectric dead layer in nanoscale capacitors. Nature 443, 679–682 (2006). \n35.\t Kim, S. J., Mohan, J., Summerfelt, S. R. & Kim, J. Ferroelectric $\\mathsf{H f}_{0.5}Z\\mathsf{r}_{0.5}\\mathsf{O}_{2}$ thin films: a review of recent advances. JOM 71, 246–255 (2019). \n36.\t Schlom, D. G. et al. Strain tuning of ferroelectric thin films. Annu. Rev. Mater. Res. 37, 589–626 (2007). \n37.\t Haeni, J. H. et al. Room-temperature ferroelectricity in strained $\\mathsf{S r T i O}_{3}$ Nature 430, 758–761 (2004). \n38. Zubko, P., Catalan, G. & Tagantsev, A. K. Flexoelectric effect in solids. Annu. Rev. Mater. Res. 43, 387–421 (2013). \n39. Jariwala, D., Marks, T. J. & Hersam, M. C. Mixed-dimensional van der Waals heterostructures. Nat. Mater. 16, 170–181 (2017). \n40.\t Kwon, D. et al. Negative capacitance FET with 1.8-nm-thick Zr-doped ${\\mathsf{H f O}}_{2}$ oxide. IEEE Electron Device Lett. 40, 993–996 (2019). \n41. Lee, M. H. et al. Physical thickness 1.x nm ferroelectric $\\mathsf{H f Z r O}_{\\mathrm{x}}$ negative capacitance FETs. In 2016 IEEE Int. Electron Devices Meet. (IEDM) 12.1.1–12.1.4, https://ieeexplore.ieee.org/ document/7838400/ (IEEE, 2016). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\n# Sample deposition and preparation \n\nThin films of $\\mathsf{H f}_{0.8}Z\\mathsf{r}_{0.2}\\mathsf{O}_{2}$ were grown by ALD in a Fiji Ultratech/ Cambridge Nanotech tool at $250^{\\circ}\\mathrm{C}$ , in which tetrakis (ethylmethylamino) hafnium and tetrakis (ethylmethylamino) zirconium precursors are heated to $75^{\\circ}\\mathbf{C}$ and water vapour is used as the oxidant. For metal-ferroelectric-insulator-semiconductor structures, heavily p-doped Si(100) substrates $(10^{19}\\thinspace\\mathrm{cm}^{-3})$ are first oxidized in ambient $\\mathbf{O}_{2}$ during an rapid thermal annealing step at $900^{\\circ}\\mathsf C$ for 60 s, forming about $2\\mathsf{n m}$ of thermal $\\mathsf{S i O}_{2}$ on Si. For metal-ferroelectric-metal structures, the Si substrate is coated with $30\\mathrm{nm}$ TiN. Subsequently, HZO is deposited at $250^{\\circ}\\mathrm{C}$ by ALD; a 4:1 ratio between the ${\\mathsf{H f O}}_{2}$ monolayer and the $Z\\mathbf{r}\\mathbf{O}_{2}$ monolayer sets the 80:20 stoichiometry of the deposited HZO, in which ten cycles corresponds to 1 nm of film. After ALD deposition, a top metal (W or TiN) is deposited by sputtering at room temperature. Finally, a rapid post-metal annealing at $500^{\\circ}\\mathrm{C}$ (30 s, ambient $\\mathsf{N}_{2}$ background) stabilizes the desired polar orthorhombic phase. For capacitor structures (scanning probe studies), the top electrodes are defined by photolithography and dry etching. For bare structures (structural studies), the top metal is removed by chemical etching to expose the HZO surface. Further details pertaining to ALD growth conditions, post-deposition processing, and so on are outlined in a previous work42. All thin film synthesis was performed at University of California, Berkeley; processing was performed at the Marvell Nanofabrication Laboratory at University of California, Berkeley. One nanometre of chemically grown $\\mathsf{S i O}_{2}$ on Si was prepared by the standard clean (SC-1) solution (5:1:1 $\\mathsf{H}_{2}\\mathsf{O}{:}\\mathsf{H}_{2}\\mathsf{O}_{2}{:}\\mathsf{N}\\mathsf{H}_{4}\\mathsf{O}\\mathsf{H}$ at $80^{\\circ}\\mathsf{C}$ for $10\\mathrm{{min}},$ ) after the Si wafer was cleaned in Piranha $120^{\\circ}\\mathrm{C}$ for 10 min) to remove organics and HF (50:1 ${\\mathsf{H}}_{2}{\\mathsf{O}}{:}{\\mathsf{H}}{\\mathsf{F}}$ at room temperature for 30 s) to remove any native oxide. Thinner $\\mathsf{S i O}_{2}$ was employed to help reduce depolarization fields and improve the electric field distribution through the ultrathin ferroelectric HZO layer. \n\n# Electron microscopy \n\nElectron microscopy was performed at the National Center for Electron Microscopy facility of the Molecular Foundry at LBNL as well as by Nanolab Technologies Inc., a commercial vendor. At the National Center for Electron Microscopy, TEM samples were prepared by mechanical polishing on an Allied High Tech Multiprep and subsequently Ar ion milled using a Gatan Precision Ion Milling System at shallow angles $(5^{\\circ}\\mathfrak{t o}3^{\\circ})$ with starting energies of 5 keV stepped down to a final cleaning energy of $200\\mathrm{eV}$ to reduce ion-induced damage. High-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images were recorded on TEAM I, an aberration-corrected FEI Titan 80–300 operated in STEM mode at $300\\mathsf{k V}$ with a convergence semi-angle of 17 mrad, 70 pA probe current, and collection angles ${>}40$ mrad. The local thicknesses of the respective HZO layers were determined from calibration to the Si(110) interplanar lattice spacing (Extended Data Fig. 3), consistent with global thicknesses extracted using XRR (Extended Data Fig. 2). \n\n# Scanning probe microscopy \n\nPiezoresponse microscopy and spectroscopy. PFM measurements (Extended Data Figs. 6, 7) were performed using a commercial scanning probe microscope (Asylum MFP-3D) at the University of California, Berkeley. Dual-frequency resonance-tracking $\\mathsf{P F M}^{43}$ was conducted using a conductive Pt/Ir-coated probe tip (NanoSensor PPP-EFM) to image written domain structures and measure switching-spectroscopy44 piezoelectric hysteresis loops. Resonance-enhanced PFM increases the signal-to-noise ratio for the detection of out-of-plane electric polarization, which is critical for ultrathin films. Contact was made to the bottom TiN electrode or heavily doped Si substrate for grounding in PFM studies. All PFM phase-contrast images and hysteresis loops shown were performed on ten-cycle (about 1 nm) HZO films unless otherwise indicated. PFM imaging was performed with the tip in direct contact with the HZO layer. Switching-spectroscopy hysteresis loops were measured on capacitor structures to help eliminate electrostatic artefacts from the tip45, mitigate possible electromechanical contributions24, and to yield more confined electric fields. $V_{\\mathrm{ac}}$ -dependent piezoresponse loops (Extended Data Fig. 7c) examined the ferroelectric origin of the PFM signal—as opposed to tip bias-induced artefacts25—in ultrathin HZO films. The piezoresponse OFF loop collapsed once $V_{\\mathrm{ac}}$ exceeded the coercive voltage46, as expected for ferroelectric behaviour. Piezoresponse is defined as Acosθ, where A and $\\theta$ are the PFM amplitude and phase, respectively45. We note that the non-ideal shape of the piezoresponse loops, particularly at higher voltages, are caused by non-ferroelectric artefacts from the additional dielectric $\\mathsf{S i O}_{2}$ layer through which most of the voltage is dropped. For all PFM studies, the bias was applied to the tip. \n\nEffective coercive field. The switching voltage from PFM loops exaggerate the coercive field of the ultrathin HZO layer once considering the potential distribution across the modified metal-oxidesemiconductor structure (oxide bilayer ${\\mathsf{S i O}}_{2}{\\cdot}{\\mathsf{H Z O}}$ ). The effective coercive field of the HZO layer can be determined using a simple dielectric-ferroelectric bilayer model, ignoring accumulation and depletion regions at the moment just to approximate the coercive field. Considering appropriate electrical boundary conditions across the oxide interface $(\\epsilon_{\\mathrm{DE}}E_{\\mathrm{DE}}{=}\\epsilon_{\\mathrm{FE}}E_{\\mathrm{FE}})$ , the voltage across the ferroelectric layer $(V_{\\mathrm{FE}})$ can be expressed in terms of the total voltage given by the PFM loop $(\\ensuremath{V_{\\mathrm{tot}}})$ : \n\n$$\nV_{\\mathrm{FE}}{=}\\left(1+\\frac{t_{\\mathrm{DE}}}{t_{\\mathrm{FE}}}\\frac{\\epsilon_{\\mathrm{FE}}}{\\epsilon_{\\mathrm{DE}}}\\right)^{-1}V_{\\mathrm{tot}}\n$$ \n\nwhere the dielectric constant for the oxide layers are taken as $\\epsilon_{\\mathrm{DE}}{=}3.9$ $(\\mathsf{S i O}_{2})$ and as $\\epsilon_{\\mathrm{FE}}{=}24(\\mathsf{H Z O})^{4,14}$ and the thicknesses of the oxide layers are $t_{\\mathrm{DE}}=2$ nm and $t_{\\mathrm{FE}}{=}1\\mathsf{n m}$ . These values yield $V_{\\mathrm{FE}}{=}V_{\\mathrm{tot}}/13$ , so the effective coercive field of the ten-cycle $\\left(1\\mathsf{n m}\\right)$ ferroelectric HZO layer is approximately $2\\mathsf{M V}\\mathsf{c m}^{-1}$ , consistent with values of thicker HZO films reported in the literature13. \n\nInterferometry. IDS PFM measurements (Extended Data Fig. 7d) were performed using a commercial scanning probe microscope (Asylum Cypher) with an integrated quantitative laser Doppler vibrometer at Asylum Research (Santa Barbara). This recently developed method26 eliminates crosstalk and other artefacts present in voltage-modulated piezo-measurements $(d_{33})$ by replacing the typical slope-sensitive optical beam detector with a displacement sensitive interferometer. By positioning the IDS laser directly over the tip, motion of the tip can be decoupled from spurious motion of the cantilever body. Motion of the cantilever body can be driven by long-range electrostatics and is influenced by the transfer function of the cantilever26. IDS measurements were performed with a $3\\mathsf{N}\\mathsf{m}^{-1}$ Ti/Ir coated cantilever placed on the bare 1-nm HZO surface at drive frequency $250\\mathsf{k H z}$ and average force $75\\mathsf{n N}.$ Off-surface loops (tip raised from surface), which measure the extrinsic electrostatic contributions26, were performed by changing the trigger value from deflection (force) to the $z$ -sensor read-out. The lack of hysteresis from off-surface (non-contact) loops further support the finding that the hysteresis observed from on-contact IDS measurements are free from electrostatic contributions. Typical voltage-modulated PFM measurements often display false ferroelectric hysteresis due to long-range cantilever dynamics inherent to detection by the optical beam detector, as observed from non-contact hysteresis in non-piezoelectric samples26. \n\nMicrowave capacitance. SCM measurements (Extended Data Fig. 8c) were performed using a commercial scanning probe microscope (Asylum Cypher) at Asylum Research (Santa Barbara). Differential \n\n# Article \n\ncapacitance (dC/dV) measurements were performed at 1.8-GHz frequency with a $40\\mathsf{k H z}$ lock-in frequency at $0.5{\\mathsf V}_{\\mathrm{ac}}$ . Pure Pt cantilevers (Rocky Mountain Nanotechnology) are placed on top of bare HZO surface (contact mode) on TiN-buffered Si for SCM measurements; dC/dV signals were extracted via $V_{\\mathrm{ac}}$ applied between the SCM tip and bottom electrode. Capacitance–voltage loops via SCM have been previously used to confirm ferroelectricity in $\\mathsf{S r B i}_{2}\\mathsf{T a}_{2}\\mathsf{O}_{9}$ (SBT) thin films47. The microwave-frequency nature of the measurement lends itself to probing ultrathin ferroelectrics, as it mitigates leakage contributions. For SCM measurements, the bias was applied to the sample (swept up to $\\pm8\\mathsf{V},$ ), not to the tip as is done for PFM measurements. \n\n# X-ray diffraction \n\nStructural characterization. Synchrotron GI-XRD (Extended Data Fig. 4a) was performed at the Sector 33-BM-C beamline of the Advanced Photon Source, Argonne National Laboratory. Using synchrotron GI-XRD, we investigated the structural evolution from polycrystalline bulk-like (100-cycle) HZO down to highly textured ultrathin ( $<25$ cycles) HZO in its polar orthorhombic $(P c a2_{1})$ phase, at grazing angle $\\scriptstyle\\leq\\theta=0.35^{\\circ}$ . The high flux from the synchrotron source $(\\lambda=0.775\\mathring\\mathbf{A}),$ ) enabled collection of sufficient diffraction intensity from the few crystallographic planes present in ultrathin HZO samples. High-resolution GI-XRD was also performed using a laboratory-based Panalytical X’Pert Pro X-ray diffraction system $\\mathrm{{CuK}_{\\alpha}}$ radiation, $\\lambda{=}1.54056\\mathring\\mathrm{A},$ ) on HZO films thicker than 2 nm at grazing angle $\\theta{=}0.35^{\\circ}$ . Previous work employed selected area electron diffraction48 and convergent beam electron diffraction49 to attribute ferroelectricity in ${\\mathsf{H f O}}_{2}$ -based films to the polar orthorhombic (Pca21) phase. The indexing of ultrathin HZO films performed in this work is consistent with the same polar orthorhombic phase determined from these previous electron diffraction studies. \n\nTexture analysis. Pole figures (Extended Data Fig. 4b) were measured at Sector 33-BM-C beamline of the Advanced Photon Source, Argonne National Laboratory. For fixed Q values—corresponding to the $d_{\\mathrm{{u}}}$ lattice spacing—the 4-circle Huber diffractometer rotated in-plane $(\\varphi)$ $360^{\\circ}$ at multiple values of out-of-plane tilt $(\\chi)$ . The PILATUS 100K pixel area detector collected volumetric reciprocal space data from which two-dimensional pole figure slices were plotted for shells of constant $Q_{z}$ . The four concentrated reflections for the {111} projection in $Q_{x}–Q_{y}$ space indicate highly oriented texture, rather than the diffuse rings expected for polycrystalline films. As indicated in the main text (Fig. 3), films thinner than 25 cycles display substantial texturing (Extended Data Fig. 4); in particular, the (111) reflection, which is dominant for thicker films, is diminished in GI-XRD spectra of ultrathin films owing to the geometric limitations of a one-dimensional pattern (it is unable to detect all reflections present in oriented films). This limitation necessitates tilted-geometry two-dimensional patterns (pole figures) in order to detect all reflections present in highly oriented films. Meanwhile, reflections corresponding to polycrystalline films exhibit continuous rings in two-dimensional $Q_{x}–Q_{y}$ reciprocal space, so any one-dimensional line-cut (GI-XRD spectra) would detect all reflections present. The results on ultrathin HZO films are in stark contrast to results on thicker films50,51 and indicate that, for such ultrathin films, crystallization and orientation need to be considered together. We also observed that for such thin films, the template for HZO growth needs to be atomically smooth. Therefore, the Si $S_{\\mathrm{i}}\\mathrm{O}_{2}$ interface employed in this work is critical; the growth surface is expected to have a larger role for ultrathin films than for thicker films. \n\nThickness confirmation. Synchrotron XRR of ultrathin HZO films (Extended Data Fig. 2)—performed at Sector 33-BM-C beamline of the Advanced Photon Source, Argonne National Laboratory and at Beamline 2-1 of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory—confirmed the thickness of sub2-nm films. Fitting analysis was performed with the Python package xrayutilities52. XRR of thicker HZO films $(>2\\mathsf{n m})$ was measured with the Panalytical X’Pert Pro system, and thickness fitting was performed with Panalytical software. The extracted growth rate of 11 cycles $\\mathsf{n m}^{-1}$ is consistent with results from TEM and literature13. \n\nStructural distortion analysis. For the polar orthorhombic phase $(P c a2_{1})$ , we consider the orthorhombic distortion (that is, orthorhombicity) as the aspect ratio: $2c/(a+b)$ to enable easier comparison to the tetragonal $(P4_{2}/n m)$ aspect ratio $c/a$ . Fluorite-structure orthorhombicity is meant to be analogous to the perovskite ferroelectric tetragonality $(c/a$ , where $c$ is the polar axis); both aspect ratios serve as a structural gauge of the macroscopic polarization because they are indicative of the polar distortion present in their respective structures53. Notably, the orthorhombic distortion present in HZO is enhanced in the ultrathin regime—opposite to the typical tetragonal distortion trend in perovskite ferroelectrics6—indicative of the ‘reverse’ size effects present in fluorite-structure ferroelectrics. For example, the tetragonal aspect ratio was shown to decrease with decreasing thickness in ferroelectric ${\\mathsf{P b T i O}}_{3}$ films53, while the orthorhombic aspect ratio is greatly enhanced in the ultrathin regime in our fluorite-structure HZO films (Fig. 3g). The orthorhombic distortion present in ten-cycle (about 1 nm) HZO far exceeds any reported values for ${\\mathsf{H f O}}_{2}–Z{\\mathsf{r O}}_{2}$ polymorphs: we find ${>}11\\%$ aspect asymmetry, while $3-4\\%$ is typically reported for fluorite-structure ferroelectrics31, consistent with our thicker films (Fig. 3g). Indeed, a strong relationship between this aspect ratio and the remanent polarization value has been experimentally demonstrated in thicker doped ${\\mathsf{H f O}}_{2}$ films54. Therefore, the colossal orthorhombic aspect ratio present in ten-cycle HZO is consistent with ultrathin-enhanced ferroelectricity. The orthorhombic aspect ratio is calculated from the position of various diffraction peaks indexed to the $P c a2_{1}$ phase (the 200, 020 and 002 peaks), using the following crystallographic relations: $a=2{\\cdot}d_{200},b=2{\\cdot}d_{020},c=2{\\cdot}d_{002}$ where $d_{200},d_{020}.$ and $d_{002}$ are the 200, 020 and 002 lattice spacings determined via Bragg’s law and the respective peak positions. These values are self-consistently checked against the 111 interplanar lattice spacing $(~1/d_{\\mathrm{111}}^{2}{=}1/a^{2}+\\dot{1/b}^{2}+1/c^{2}~;$ as well as against other orientations present in the diffraction spectra. The aspect ratio of the polar O-phase exceeds that of the T-phase $(c/a)$ for doped $\\mathsf{H f O}_{2}^{54}$ . Another structural marker indicates amplified distortions as thickness is reduced, namely the interplanar lattice spacing $d_{\\mathrm{{u1}}}$ . The origin of the left shift in the O-phase 111 (T-phase 101) reflection (Fig. 3f) with decreasing thickness (that is, decreasing ALD cycles) is typically attributed to the abovementioned phase transition (nonpolar T-phase to polar O-phase); the left shift of the peak in reciprocal space corresponds to an increase in real-space lattice spacing. Extending this analogy to the ultrathin regime in which the polar O-phase is already stabilized, the ultrathin enhancement of $d_{\\mathrm{{u1}}}(\\mathrm{{Fig.3g}})$ indicates a further increase in rhombic distortion (structurally represented by $d_{\\mathrm{{u}}}$ ). Recent works on epitaxial HZO films grown by high-temperature pulsed laser deposition on perovskite substrates also indicate increasing $d_{\\mathrm{{u}}}$ with decreasing thickness28,29; these works find the electric polarization to increase with increasing $d_{\\mathrm{{u1}}}$ . Similarly, we expect a larger polarization in our ultrathin films based on the $d_{\\mathrm{{u1}}}$ trend (Fig. 3g); notably, our low-temperature ALD-grown highly oriented films are mimicking the trends observed in high-temperature pulsed-laser-deposition-grown epitaxial films. \n\n# X-ray spectroscopy \n\nXAS and XLD. X-ray absorption spectroscopy (XAS) and XLD was performed at the Advanced Light Source beamline 4.0.2. XAS measurements were taken at the oxygen $K$ edge $(520-550\\mathrm{eV})$ and $\\mathsf{Z r}M_{2}$ edge (345–355 eV). X-rays were incident at $20^{\\circ}$ off grazing. XLD (XAS) was obtained from the difference (average) of horizontal and vertical linearly polarized X-rays. To eliminate systematic artefacts in the signal that drift with time, spectra were captured with the order of polarization rotation reversed (such as horizontal, vertical, vertical and horizontal) in successive scans. An elliptically polarizing undulator was used to tune polarization and photon energy of the synchrotron X-ray source55. XAS was recorded under total electron yield mode55. \n\nSimulated XAS and crystal field symmetry. Simulated XAS spectra for the various fluorite-structure polymorphs were computed through the Materials Project56 open-source database for the XAS spectrum57. In particular, the following symmetries for ${\\mathsf{H f O}}_{2}$ and $Z\\mathrm{r}0_{2}$ were investigated: monoclinic $\\scriptstyle P2_{1}/c$ (space group 14), orthorhombic $P c a2_{1}$ (space group 29), and tetragonal $P4_{2}/$ nmc (space group 137). Comparisons between HZO and the undoped fluorite-structure endmembers (in particular, qualitative comparison of splitting-induced spectroscopy features) are reasonable owing to the extremely low structural dissimilarity between the same polymorphs of ${\\mathsf{H f O}}_{2}$ and $Z\\mathrm{r}{\\bf O}_{2}.$ , as determined by pymatgen58. The T-phase $(P4_{2}/n m c)$ nonpolar distortion $(D_{4h},$ fourfold prismatic symmetry) from regular tetrahedral $\\cdot T_{d},$ full tetrahedral symmetry) fluorite-structure symmetry does not split the degenerate e bands $(d_{x^{2}-y^{2}},d_{3z^{2}-r^{2}})$ , as confirmed by experiment59 and the XAS simulations (Extended Data Fig. 9b). Meanwhile, the O-phase $(P c a2_{1})$ polar rhombic pyramidal distortion $\\cdot C_{2\\upsilon},$ twofold pyramidal symmetry) does split the $e$ -manifold based on crystal field symmetry (Extended Data Fig. 9b), providing a spectroscopic means to distinguish the T- and O-phases. The eightfold Hf-O (Zr-O) coordination (Extended Data Fig. 9d) in the tetragonal phase $(D_{2d}$ point group symmetry) can be decomposed into two tetrahedra that are the space inversion twins of one another. Therefore, crystal field splitting of the e levels matches that of a single tetrahedron59—that is, there is no further splitting. Meanwhile, the sevenfold Hf-O $(Z\\mathbf{r}{\\cdot}0)$ coordination (Extended Data Fig. 9d) in the orthorhombic phase cannot be decomposed into two tetrahedra; the additional rhombic distortion (not present in the T-phase) splits the e manifold. The simulated XAS spectra for T- and O-phase $Z\\mathbf{r}\\mathbf{O}_{2}$ (Extended Data Fig. 9b) supports this picture, because the additional spectroscopic feature present between the main e- and $t_{2}\\mathrm{.}$ absorption features in the O-phase is presumably caused by this additional symmetry-lowering distortion. The XAS spectra of the HZO thickness series (Extended Data Fig. 9c) demonstrates tetrahedral and rhombic splitting features closely matching the polar O-phase $(P c a2_{1})$ . This demonstrates a spectroscopic method for phase identification beyond diffraction—ambiguous owing to the nearly identical T- and O-phase lattice parameters13—whose signatures are more sensitive to the subtle structural distortions present as symmetry is lowered from the T- to the O-phase. \n\nCrystal field splitting. Notably, the crystal field distortions present in confined HZO films greatly exceed what is typically observed in bulk fluorite-structures and perovskite ferroelectrics (Extended Data Fig. 9g); the tetrahedral (rhombic) crystal field $\\Delta_{\\mathrm{{T}}}(\\Delta_{\\mathrm{{R}}})$ arising from the $T_{d}(C_{2\\upsilon})$ symmetry in ten-cycle HZO films is $1.3\\mathrm{eV}(0.7\\mathrm{eV})$ greater than what is expected from fluorite-structure $Z\\mathrm{r}{\\bf O}_{2}$ in the polar orthorhombic phase (Pca21). The computational XAS for the $P c a2_{1}$ phase already takes the polar distortion $(\\Delta_{\\tt R})$ into account; so the enhanced $\\Delta_{\\scriptscriptstyle{\\mathrm{R}}}$ in ultrathin confined films again points to enhanced polar distortions (consistent with diffraction-based results). Kindred efforts to uncover routes towards enhanced nanoscale distortions have been explored in complex perovskite heterostructures. For example, in nickelate perovskite superlattices, enormous $\\Delta_{e g}$ crystal field splitting (up to $0.8\\mathrm{eV},$ ) has been achieved via polar fields resulting from internal charge transfer27; $510\\%$ epitaxial strain would be required to induced such large ionic distortions in that particular system, well beyond the limits of epitaxial strain, which can only achieve $e_{g}$ splitting of about 300 meV (ref. 60). \n\nSpectral weight trends. The relative spectral weight of the $e$ and $t_{2}$ manifolds (Extended Data Fig. 9c) at the O K edge can also provide insight into the degree of structural distortion61. Owing to the $d^{0}$ electronic configuration present in $\\mathsf{H f}^{4+}(\\mathsf{Z r}^{4+})$ , all $d$ states are available for mixing with O $2p$ states, so the analysis of $e{\\cdot}t_{2}$ spectral weight can be simplified to be purely due to crystal field effects61. Tetrahedral symmetry lowers $e$ bands relative to $t_{2}$ bands due to the enhanced $t_{2}$ orbital overlap with oxygen $2p$ orbitals. The enhanced $t_{2}/e$ spectral weight as thickness is reduced (Extended Data Fig. 9c) indicates the preference for $_{02p}$ hybridization with Hf 5 $\\boldsymbol{d}(\\boldsymbol{Z}\\boldsymbol{\\Gamma}4\\boldsymbol{d})t_{2}$ orbitals, further exaggerating the disparity set by the tetrahedral symmetry as the symmetry is lowered to the polar O-phase. Additionally, the increase in spectral weight of the pre-edge shoulder (Extended Data Fig. 9e) provides further confirmation that structural distortions are amplified in the ultrathin limit. Pre-edge features at the $0K$ edge in complex transition metal oxides are commonly attributed to nearest-neighbour variations from typical oxygen polyhedral coordination as the symmetry is lowered by various distortions62. Analogously, here the pre-edge feature is attributed to variation from eightfold coordination in the T-phase $(N N=8)$ as the symmetry is lowered into the polar O-phase $(N N=7)$ (Extended Data Fig. 9d). On the unit cell level in the polar O-phase, the central metal cation is surrounded by an asymmetric oxygen coordination environment (note the 4 blue and 3 cyan oxygen atoms in Extended Data Fig. 9d) owing to the polar rhombic distortion of normal tetrahedral $(T_{d})$ symmetry; this polyhedral distortion can manifest as increased spectral weight at the oxygen $K$ pre-edge62. The critical $e$ manifold splitting due to the polar rhombic distortion also increases in spectral weight as thickness is reduced (Extended Data Fig. 9c). The XAS spectral weight trends mirror the structural indicators of ultrathin-enhanced distortion (Fig. 3c). \n\nOrbital polarization. In conjunction with XAS, XLD can also probe structural distortions owing to its sensitivity to orbital asymmetry, which can arise from inversion symmetry breaking. For example, in the perovskite ferroelectrics ${\\mathsf{P b T i O}}_{3}$ and ${\\bf B a T i O}_{3}.$ , the Ti $3d$ to O $2p$ orbital hybridization is essential for stabilizing the noncentrosymmetric structure63. Particularly at the 3d cation $L_{3,2}$ edge, orbital polarization extracted from XLD is used as a measure of the oxygen octahedral distortion in perovskites owing to the anisotropic hybridization between cation 3d and $_{02p}$ orbitals64. Accordingly, in fluorite-structure ferroelectrics, the magnitude of XLD present at the $\\boldsymbol{Z}\\boldsymbol{\\mathrm{r}}\\boldsymbol{M}_{3,2}$ edges can be a gauge of the degree of polyhedral distortion (in this case, a distortion of the oxygen tetrahedron) and the oxygen atomic asymmetry. Indeed, the orbital polarization at the Zr $M_{2}$ edge is enhanced as the thickness is reduced from the thick (100-cycle) to ultrathin (ten-cycle) regime (Fig. 3c), consistent with diffraction-based results demonstrating amplified structural distortions in the ultrathin limit. Spectroscopy can also help understand the evolution to highly textured films in the ultrathin limit (Fig. 3e, f), as XLD enables both element- and orbital-specific information by comparing polarization-dependent XAS spectra. GI-XRD across the thickness series (Fig. 3f) indicates that the degree of orientation substantially changes as the HZO drops below about $2.5\\mathsf{n m}$ (25 cycles). The microstructure change below 25 cycles also manifests as inverted orbital polarization at the oxygen K edge, particularly at the e manifold (Fig. 3b). Absorption of vertically and horizontally polarized light preferentially probes the polar-distortion-split $e$ levels (the $x^{2}y^{2}$ and $3z^{2}r^{2}$ d orbitals); the reversal of XLD sign indicates these levels are inverted with respect to one another. In perovskites, such a change in orbital polarization is often attributed to different signs of tetragonal distortion $(c/a)$ of the oxygen octahedron64. Analogously, here the change in microstructure across 20–25 cycles, namely, the emergence of highly oriented films, could allow confinement strain effects to distort the oxygen tetrahedron more coherently along the polar axis. This synergistic effect could potentially explain the enhanced distortions observed in the ultrathin regime. \n\nNanospectroscopy. PEEM was performed at the Advanced Light Source beamline 11.0.1. X-rays were incident at $30^{\\circ}$ off grazing, probing just the first few nanometres of film, spanning the entire ten-cycle (1 nm) HZO thickness. Nanospectroscopy point-by-point scans were \n\n# Article \n\nemployed to spatially resolve XLD contrast; at each specified energy value in the oxygen K edge $(520-550\\mathrm{eV})$ regime, PEEM images were taken for both values of the linear polarization (horizontal, vertical) across a $20{\\cdot}{\\upmu}\\mathrm{m}$ field of view $\\cdot1,000\\times1,000$ pixel grid). The exposure to high-flux synchrotron X-rays probably depolarized the ultrathin ferroelectric sample as photoelectrons were removed from the surface, as is observed in ultrathin films of ${\\bf B a T i O}_{3}$ and other ferroelectrics; PEEM-XLD images (Extended Data Fig. 9f) illustrate nanoscale domains at the energy range corresponding to the polar $e$ -split feature. Data processing to extract XLD contrast involved dividing images of opposite linear polarization, which eliminates topography and work function contrast. Topography and work function artefacts contribute at the pre-edge (about $530\\mathrm{eV},$ , whereas the intrinsic orbital anisotropy contributions manifest only at resonance (about 535 eV); the presence of XLD contrast only at resonance confirms the orbital asymmetry origins of XLD contrast in ultrathin HZO. Furthermore, the highly textured nature of the ultrathin films prevents the XLD contrast from averaging to zero (cancellation would be expected for a fully polycrystalline film) on a length scale smaller than the experimental resolution. \n\n# Optical spectroscopy \n\nSHG and inversion asymmetry. Nonlinear optical SHG was performed using a custom setup at University of California, Berkeley, as detailed in a previous work23. The excitation light was extracted using an optical parametric oscillator (Inspire HF 100, Spectra Physics, Santa Clara) pumped by a mode-locked Ti:sapphire oscillator. The excitation laser was linearly polarized by a 900–1,300 nm polarizing beamsplitter. The transmitted $p$ -polarized laser light can change its polarization by rotating an infrared half waveplate before pumping the sample. The laser is focused by a $50\\times$ near-infrared objective onto the sample. The SHG signal was detected in the backscattering configuration, analysed by a visible-range polarizer, and finally collected by a cooled charge-coupled device spectrometer. SHG was performed with a $960–\\mathsf{n m}$ pump and detected at $480\\mathsf{n m}$ under tilt incidence. SHG is commonly used to investigate piezoelectric and ferroelectric single crystals and thin films65 as the photon frequency-doubling process is allowed only in materials lacking inversion symmetry. \n\nField-dependent SHG. Electric-field-dependent SHG experiments were performed on the bare surface of ten-cycle (1 nm) HZO films (top metal was etched away after phase annealing). The HZO layer was then patterned into micrometre-sized islands to enable systematic identification of specific HZO regions; various islands were poled with an electric field (applied by a PFM tip), while other islands were left as is. The optical microscope identified the poled and unpoled islands, and the second harmonic signal was detected across various islands. Increased SHG intensity, sensitive to out-of-plane polarization in this tilt-incidence experimental geometry, in poled HZO islands suggests that the electric field increases the projection of out-of-plane polarization by aligning domains with different polarization directions. \n\n# Electrical characterization \n\nTunnel current measurements. Tunnel current measurements were performed using a commercial Semiconductor Device Analyzer (Agilent B1500) with a pulse generator unit to enable voltage pulses down to the microsecond regime. Samples were patterned into capacitors of various area, with W as the top electrode, and heavily doped Si $(10^{19}\\mathsf{c m}^{-3})$ as the bottom contact. The 19- $\\upmu\\mathrm{m}$ W tips (DCP-HTR 154-001, FormFactor) made electrical contact within a commercial probe station (Cascade Microtech). In tandem, conducting atomic force microscopy measurements were performed using a commercial scanning probe microscope (Asylum MFP-3D) at University of California, Berkeley. Current–voltage characteristics through the capacitor device were probed in the AFM by using a Keithley 2400 Source Measure Unit to bias the top electrode of the sample through 20-nm-radii Pt/Ir-coated AFM probes (25PtIr300B cantilever probe, Rocky Mountain Nanotechnology), grounded to the heavily doped Si substrate. \n\nCurrent–voltage hysteresis and tunnel electroresistance. We used voltage-polarity-dependent current–voltage hysteresis to rule out resistive switching mediated by dielectric breakdown and filamentary-type switching. For filamentary-mediated resistive switching—often observed in amorphous ${\\mathsf{H f O}}_{2}$ —the sense of hysteresis is dependent on the direction of the voltage sweep (that is, the initial polarity of the voltage waveform), which dictates the filament formation66. Meanwhile, ferroelectric tunnel junctions demonstrate the same sense of current–voltage hysteresis independent of the sweep direction; this voltage-polarity independence is indicative of polarization-mediated switching, as observed for our ultrathin ten-cycle (1 nm) HZO films (Extended Data Fig. 10e). To further investigate the origin of the resistive switching, tunnelling electroresistance hysteresis maps as a function of write voltage (at low read voltage) demonstrate saturating, abrupt hysteretic behaviour (Extended Data Fig. 10b, d) characteristic of polarization-driven switching67,68. Evidence of polarization-driven resistive switching from tunnelling electroresistance is provided for ten-cycle (1 nm) HZO films of two different compositions (Extended Data Fig. 10). Although many of the results presented here are for films with 4:1 Hf:Zr ratio, for comparison, we have included results and demonstrated ferroelectricity for a ten-cycle (1 nm) film with this modified 1:1 Hf:Zr ratio. Pioneering work on HZO in the thicker regime $(>5\\mathsf{n m})^{50,69,70}$ has shown that a 1:1 Hf:Zr ratio often demonstrates the best ferroelectric properties. Ferroelectric tunnel junctions based on composite ferroelectric-dielectric barriers using HZO in this thicker regime demonstrate promising polarization-driven resistive switching results71,72. Optimizing ferroelectric tunnel junction behaviour employing HZO in the ultrathin regime (around 1 nm) will need to be carefully studied. \n\n# Data availability \n\nThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. \n\n42.\t Karbasian, G. et al. Stabilization of ferroelectric phase in tungsten capped $\\mathsf{H f}_{0.8}\\mathsf{Z r}_{0.2}\\mathsf{O}_{2}$ Appl. Phys. Lett. 111, 022907 (2017). \n43.\t Rodriguez, B. J., Callahan, C., Kalinin, S. V. & Proksch, R. Dual-frequency resonance-tracking atomic force microscopy. Nanotechnology 18, 475504 (2007). \n44.\t Jesse, S., Lee, H. N. & Kalinin, S. V. Quantitative mapping of switching behavior in piezoresponse force microscopy. Rev. Sci. Instrum. 77, 073702 (2006). \n45.\t Hong, S. et al. Principle of ferroelectric domain imaging using atomic force microscope. J. Appl. Phys. 89, 1377–1386 (2001). \n46.\t Strelcov, E. et al. Role of measurement voltage on hysteresis loop shape in piezoresponse force microscopy. Appl. Phys. Lett. 101, 192902 (2012). \n47.\t Leu, C.-C. et al. Domain structure study of $\\mathsf{S r B i}_{2}\\mathsf{T a}_{2}\\mathsf{O}_{9}$ ferroelectric thin films by scanning capacitance microscopy. Appl. Phys. Lett. 82, 3493–3495 (2003). \n48.\t Chernikova, A. et al. Ultrathin $\\mathsf{H f}_{0.5}Z\\mathsf{r}_{0.5}\\mathsf{O}_{2}$ ferroelectric films on Si. ACS Appl. Mater. Interf. \n8, 7232–7237 (2016). \n49.\t Sang, X., Grimley, E. D., Schenk, T., Schroeder, U. & LeBeau, J. M. On the structural origins of ferroelectricity in $H\\mathsf{f O}_{2}$ thin films. Appl. Phys. Lett. 106, 162905 (2015). \n50.\t Böscke, T. Crystalline Hafnia and Zirconia Based Dielectrics for Memory Applications PhD thesis, Hamburg University of Technology, https://cuvillier.de/en/shop/publications/7 \n63-crystalline-hafnia-and-zirconia-based-dielectrics-for-memory-applications (2010). \n51.\t Zhao, C., Roebben, G., Heyns, M. M. & Van der Biest, O. Crystallisation and tetragonal-monoclinic transformation in $Z\\mathsf{r O}_{2}$ and ${\\mathsf{H f O}}_{2}$ dielectric thin films. Key Eng. Mater. 206–213, 1285–1288 (2001). \n52.\t Kriegner, D., Wintersberger, E. & Stangl, J. xrayutilities: a versatile tool for reciprocal space conversion of scattering data recorded with linear and area detectors. J. Appl. Cryst. 46, \n1162–1170 (2013). \n53.\t Lichtensteiger, C., Triscone, J., Junquera, J. & Ghosez, P. Ferroelectricity and tetragonality in ultrathin ${\\mathsf{P b T i O}}_{3}$ films. Phys. Rev. Lett. 94, 047603 (2005). \n54.\t Park, M. H. et al. A comprehensive study on the structural evolution of $H\\mathsf{f}O_{2}$ thin films doped with various dopants. J. Mater. Chem. C 5, 4677–4690 (2017). \n55.\t Young, A. T. et al. Variable linear polarization from an x-ray undulator. J. Synch. Rad. 9, \n270–274 (2002). \n56.\t Jain, A. et al. The Materials Project: a materials genome approach to accelerating materials innovation. APL Mater. 1, 011002 (2013). \n57.\t Mathew, K. et al. High-throughput computational X-ray absorption spectroscopy. Sci. Data 5, 180151 (2018). \n58.\t Ong, S. P. et al. Python Materials Genomics (pymatgen): a robust, open-source Python library for materials analysis. Comput. Mater. Sci. 68, 314–319 (2013). \n59.\t Cho, D.-Y., Jung, H.-S. & Hwang, C. S. Structural properties and electronic structure of $H^{\\dagger}\\mathsf{O}_{2}–Z\\mathsf{r}\\mathsf{O}_{2}$ composite films. Phys. Rev. B 82, 094104 (2010). \n60.\t Wu, M. et al. Strain and composition dependence of orbital polarization in nickel oxide superlattices. Phys. Rev. B 88, 125124 (2013). \n61.\t de Groot, F. et al. Oxygen 1s X-ray-absorption edges of transition-metal oxides. Phys. Rev. B 40, 5715–5723 (1989). \n62.\t de Groot, F. Multiplet effects in X-ray spectroscopy. Coord. Chem. Rev. 249, 31–63 (2005). \n63.\t Cohen, R. E. Origin of ferroelectricity in perovskite oxides. Nature 358, 136–138 (1992). \n64.\t Pesquera, D. et al. Surface symmetry-breaking and strain effects on orbital occupancy in transition metal perovskite epitaxial films. Nat. Commun. 3, 1189 (2012). \n65.\t Denev, S. A., Lummen, T. T. A., Barnes, E., Kumar, A. & Gopalan, V. Probing ferroelectrics using optical second harmonic generation. J. Am. Ceram. Soc. 94, 2699–2727 (2011). \n66.\t Bersuker, G. & Gilmer, D. Metal oxide resistive random-access memory (RRAM) technology. In Advances in Non-Volatile Memory and Storage Technology 288–340 (Elsevier, 2014). \n67.\t Chanthbouala, A. et al. Solid-state memories based on ferroelectric tunnel junctions. Nat. Nanotechnol. 7, 101–104 (2012). \n68.\t Gruverman, A. et al. Tunneling electroresistance effect in ferroelectric tunnel junctions at the nanoscale. Nano Lett. 9, 3539–3543 (2009). \n69.\t Müller, J. et al. Ferroelectricity in simple binary $Z\\mathsf{r O}_{2}$ and ${\\mathsf{H f O}}_{2}.$ Nano Lett. 12, 4318–4323 (2012). \n70.\t Park, M. H. et al. Surface and grain boundary energy as the key enabler of ferroelectricity in nanoscale hafnia-zirconia: a comparison of model and experiment. Nanoscale 9, \n9973–9986 (2017). \n71. Fujii, S. et al. First demonstration and performance improvement of ferroelectric ${\\mathsf{H f O}}_{2}$ -based resistive switch with low operation current and intrinsic diode property. In \n2016 IEEE Symposium on VLSI Technology 1–2 (IEEE, 2016). \n72.\t Max, B., Hoffmann, M., Slesazeck, S. & Mikolajick, T. Ferroelectric tunnel junctions based on ferroelectric-dielectric $\\mathsf{H f}_{0.5}Z\\mathsf{r}_{0.5}\\mathsf{O}2/\\mathsf{A l}_{2}\\mathsf{O}_{3}$ capacitor stacks. In 2018 48th European Solid-State Device Research Conference (ESSDERC) 142–145 (IEEE, 2018). \n\nAcknowledgements This research was supported in part by the Berkeley Center for Negative Capacitance Transistors (BCNCT), ASCENT (Applications and Systems-Driven Center for Energy-Efficient Integrated NanoTechnologies), one of the six centres in the JUMP initative \n\n(Joint University Microelectronics Program), an SRC (Semiconductor Research Corporation) programme sponsored by DARPA, the DARPA T-MUSIC (Technologies for Mixed-mode Ultra Scaled Integrated Circuits) programme and the UC MRPI (University of California Multicampus Research Programs and Initiatives) project. This research used resources of the Advanced Photon Source, a US Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under contract number DE-AC02- 06CH11357. This research used resources of the Advanced Light Source, which is a DOE Office of Science User Facility under contract number DE-AC02-05CH11231. Use of the Stanford Synchrotron Radiation Light source, SLAC National Accelerator Laboratory, is supported by the US DOE, Office of Science, Office of Basic Energy Sciences under contract number DE-AC02-76SF00515. Electron microscopy was performed at the Molecular Foundry, LBNL, supported by the Office of Science, Office of Basic Energy Sciences, US DOE (DE-AC02- 05CH11231). J.C. and R.d.R. acknowledge additional support from the Presidential Early Career Award for Scientists and Engineers (PECASE) through the US DOE. J.X and X.Z acknowledge support from the National Science Foundation (NSF) under grant 1753380 and the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research award OSR-2016-CRG5-2996. \n\nAuthor contributions Film synthesis was performed by S.S.C., G.K. and D.K. Device fabrication was performed by D.K. Electron microscopy was performed by R.d.R. and S.-L.H. under the supervision of J.C. and R.R., respectively, and analysis was performed by L.-C.W. under the supervision of S.S. Scanning probe microscopy was performed by S.S.C. and N.S. IDS measurements were performed and developed by R.W. and R.P. SCM was performed by H.Z. X-ray structural characterization was performed by S.S.C., N.S. and M.R.M. under the supervision of A.M. and E.K. X-ray spectroscopy and microscopy was performed by S.S.C. under the supervision of R.V.C., P.S. and E.A. Second harmonic generation was performed by J.X. under the supervision of X.Z. Electrical measurements were performed by S.S.C., N.S. and A.D. S.S.C. and S.S. co-wrote the manuscript. S.S. supervised the research. All authors contributed to discussions and commented on the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41586-020- $2208\\cdot x.$ Correspondence and requests for materials should be addressed to S.S.C. or S.S. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/8c50965e5a045313a8556b7f1bb81738e110945a6c91bd2bba8a97e76ec4a58a.jpg) \n\nExtended Data Fig. 1 | Size effects in fluorite- and perovskite-structure ferroelectrics. a, In perovskite ferroelectrics, the polar ‘tetragonal’ distortion (c/a) can be represented as the centre cation displacement with respect to its surrounding oxygen octahedron. b, In fluorite-structure ferroelectrics, the polar ‘rhombic’ distortion $(2c/(a+b))$ can be represented as the centre anion displacement with respect to its surrounding cation tetrahedron; in the nonpolar T-phase, the oxygen atom (blue) lies in the polyhedral centre of the tetrahedron. The evolution of the bulk-stable M-phase to the high-symmetry T-phase and polar O-phase in the fluorite-structure structure illustrates the role of size effects (surface energies favour higher symmetry) and confinement strain (distortions favour lower symmetry) on stabilizing inversion asymmetry. Surface energies are critical when considering the role of size effects on ferroelectricity; higher-symmetry phases are energetically favourable at reduced dimensions owing to lower unit cell volumes. In fluorite structures (perovskites), the noncentrosymmetric O-phase (T-phase) has higher (lower) symmetry than the bulk-stable centrosymmetric M-phase (C-phase). Consequently, surface energies help to counteract depolarization fields in fluorite-structure ferroelectrics—already diminished in fluorite structures relative to perovskites owing to its lower dielectric constant4—in the ultrathin regime. Therefore, both intrinsic (surface energies) and extrinsic (confinement strain) mechanisms can favour ultrathin inversion symmetry breaking in fluorite structures. Meanwhile, both surface and depolarization energies tend to destabilize inversion asymmetry in perovskite ferroelectrics, while epitaxial strain can stabilize symmetry-lowering polar distortions36. \n\n![](images/65a78b87aaf68b60bdee8f632273ed760a536a97092333572488fdca6a81f436.jpg) \nExtended Data Fig. 2 | Thickness verification of ultrathin HZO films from XRR. a, Laboratory diffractometer XRR of HZO thickness series, demonstrating clear fringes for thickness extraction present down to 20-cycle HZO. b, Synchrotron XRR of ultrathin HZO films, enabling thickness fitting analysis for sub-20-cycle films. c, HZO thickness as a function of ALD cycles, as \n\ndetermined by fitting analysis from XRR. The growth rate is about 11 cycles $\\mathsf{n m}^{-1}$ , verified across 10–100 ALD cycle films. Squares (circles) represent thicknesses extracted from fitting to synchrotron (laboratory diffractometer) XRR measurements. \n\n# Article \n\n![](images/f5aadbe339e90fd26a01945cb3011618f681b87f7a9d4564513d446c265aa400.jpg) \n\nExtended Data Fig. 3 | Thickness verification of ultrathin HZO films using TEM. a, HZO thickness as a function of ALD cycles, as determined by Si atomic lattice calibration from TEM imaging. The growth rate is ∼11 cycles nm−1, verified across 10–50 ALD cycle films, consistent with XRR (Extended Data Fig. 2). The red error bars reflect 2σ variation. b, Cross-sectional ADF STEM \n\nimage of 20 cycles HZO. c–e, Cross-section TEM images of ten-cycle HZO (c), 15-cycle HZO (d) and 40-cycle HZO (e). f–h, Wide field-of-view TEM images of ten-cycle HZO (f), 15-cycle HZO (g) and 40-cycle HZO (h) to provide a perspective of the heterostructure uniformity. The Si substrate is oriented along the [110] zone axis for all TEM images. \n\n![](images/30c46a78aed1ecd60663309416188d6d1cfccb88f2de5c1eb351b2b3f774297b.jpg) \n\nExtended Data Fig. 4 | Emergence of highly-textured films in the ultrathin regime. a, Synchrotron GI-XRD scans $\\overset{}{\\mathop{(\\lambda=0.775\\mathring{\\mathbf{A}}}}$ ) of HZO thickness series endmembers: 10-cycle and 100-cycle. The 100-cycle HZO film is indexed according to the polar orthorhombic phase Pca21. Many of the polycrystalline reflections, most notably the (111), are no longer present at an appreciable intensity in the ultrathin limit owing to the geometric constraints of one-dimensional spectra (unable to probe all reflections present in highly oriented films) (Methods). Instead tilted-geometry diffraction (pole figures) are used to access the oriented reflections. b, Pole figure of ten-cycle HZO, taken at a $Q_{x}$ slice corresponding to the film (111) lattice spacing. The radial direction represents χ, while the azimuthal direction represents $\\varphi$ $(0^{\\circ}-360^{\\circ}$ range). The presence of four intense peaks corresponding to the four \n\n(111)-projections indicate the highly textured nature of the ultrathin HZO film. The four Si (111)-projections would be expected at $\\varphi=45^{\\circ}$ off from the $Q_{x,y}$ principal axes at a smaller value of $\\cdot_{Q_{z}}$ . c, Schematic of the (311) (left) and (111) (right) close-packed planes in the fluorite-structure structure. All the cation sites lie on such planes, which minimize surface energy effects because only metal-oxygen dangling bonds are present out-of-plane. We note that all schematics reflect stacking of the respective planes to a total thickness of 1 nm, although ultrathin HZO films may not exhibit such stacking throughout the film. For ten-cycle films, {311} indexing is consistent with the relevant intensity (about $30^{\\circ}$ ) observed in the out-of-plane one-dimensional GI-XRD pattern (a), and the (111) reflections are present from the two-dimensional pole figure pattern (b). \n\n![](images/ea453e134f2524a7471494f37db9b5de98a83c5f847adb5565a7f4407d0e6ba8.jpg) \n\nExtended Data Fig. 5 | Inversion symmetry breaking in ultrathin HZO via SHG. a, Schematic of the SHG experimental setup, using a 960-nm pump and SHG intensity detected around $480\\mathrm{nm}$ under tilt incidence, which is sensitive to out-of-plane polarization (Methods). NIR, near-infrared; 1D, one-dimensional; PBS, polarized beam splitter; Obj, objective; LP, BP and SP represent long-pass, band-pass and short-pass filters; DMSP, dichroic short-pass mirror; M1, M2 and M3 refer to mirrors; OPO, optical parametric oscillator. b, Schematic of the ten-cycle HZO islands probed by SHG (Methods); micrometre-sized islands enabled identification of specific HZO regions either poled with an electric field (applied by a PFM tip) or left as is. For these experiments, heavily doped $(10^{19}\\mathsf{c m}^{-3})$ p-type Si substrates $(\\mathsf{p}^{++}\\mathsf{S i})$ are used to serve as the bottom electrode. c, SHG spectrum on a ten-cycle HZO film, comparing poled versus unpoled SHG intensity. Spontaneous polarization is demonstrated by the presence of SHG—allowed only for inversion asymmetric systems—in unpoled ten-cycle HZO. This is consistent with PFM phase contrast in unpoled HZO regions (Fig. 2c), indicating elimination of the ‘wake-up’ effects for ferroelectricity in ultrathin HZO. The enhanced SHG contrast in poled films—possibly due to the electric field converting a small fraction of the film to the polar phase or aligning polar domains—indicates that the mechanism behind the SHG contrast is field-tunable. This field-enhanced SHG is consistent with ferroelectric origins and would probably eliminate SHG contrast from surface effects. \n\n![](images/26d93b6abc36da9457baac565fad8da76758dc3e6959f009bc615061bcee6879.jpg) \n\nExtended Data Fig. 6 | Role of ultrathin confinement for polar phase stabilization. a, b, Schematic structure (left) probed by PFM (tip location indicated by arrows), topography (centre), and PFM phase contrast images (right) on ten-cycle HZO in a region that was uncapped (a) versus confined (b) by W (represented by ‘M’ for metal in the schematic) during phase annealing. Robust $180^{\\circ}$ phase contrast is only present for the confined HZO. c, Phase (left) and amplitude (right) switching spectroscopy loops $(V_{\\mathrm{dc}}=0$ , ‘OFF’ state) as a function of bias voltage on ten-cycle HZO films, demonstrating the critical role of confinement during phase annealing in stabilizing ferroelectricity in ultrathin HZO. $180^{\\circ}$ phase contrast and butterfly-shaped amplitude are present only for confined HZO. Therefore, both switching-spectroscopy PFM and PFM imaging illustrate the critical role of confinement during phase annealing for stabilizing the ferroelectric phase. For the PFM images, $\\pm7\\upnu$ was applied in a ‘box-in-box’ poling pattern directly on the HZO surface, and switching-spectroscopy PFM loops were measured on capacitor structures (Methods). d, Schematic structure (left) probed by PFM (tip location indicated by arrows) and PFM phase and amplitude hysteresis loops (right) as a function of bias voltage on 100-cycle HZO in a region that was confined by W during phase annealing. Thicker 100-cycle HZO also demonstrates ferroelectric behaviour. \n\n![](images/b0ad041e569b60247bf65719a43af031fd7238c6430ecaa509666ed26c57f857.jpg) \n\nExtended Data Fig. 7 | Eliminating artefacts from scanning probe microscopy. a, Topography and PFM phase contrast images for ten-cycle HZO which did not (left) and did (right) undergo annealing after ALD deposition. The terraced topography in the non-annealed film indicates that the weak phase contrast is falsely caused by field-induced topographic changes. This is consistent with charge injection or ion migration, which plague amorphous ${\\mathsf{H f O}}_{2}$ films25. Phase-annealed films do not display such field-induced topographic distortions yet demonstrate much clearer phase contrast, indicating the origin of PFM phase contrast in crystalline HZO films is different than that of amorphous HZO films. In the images shown, $\\pm7\\upnu$ were applied in a ‘box-in-box’ poling sequence. b, Time-dependent PFM phase contrast images on a ten-cycle HZO film across a 24-h period. In the images shown, $\\pm7\\upnu$ was applied in the indicated checkerboard poling pattern. c, Collapse of the PFM loop from $V_{\\mathrm{ac}}$ -series. Schematic capacitor structure probed by PFM (top) and piezoresponse as a function of $V_{\\mathrm{ac}}$ in the ‘OFF’ $(V_{\\mathrm{dc}}=0)_{,}^{}$ ) state (bottom), \n\ndemonstrating the collapse of the PFM loop as $V_{\\mathrm{ac}}$ approaches the coercive voltage. This provides further confirmation of the ferroelectric origin of the PFM signal as opposed to tip bias-induced mechanisms46. The non-ideal shape of the piezoresponse loops, particularly at higher voltages, is probably caused by non-ferroelectric contributions from the additional dielectric $\\mathsf{S i O}_{2}$ layer through which most of the voltage is dropped (Methods). d, IDS switching-spectroscopy measurements on ten-cycle (1 nm) HZO, demonstrating hysteresis for the PFM tip on-surface (top) versus no hysteresis for the tip off-surface (bottom). The on-surface loops indicate $180^{\\circ}$ phase hysteresis and butterfly-shaped $d_{33}$ indicative of ferroelectric behaviour. IDS PFM measurements (Methods) remove the long-range electrostatics and cantilever resonance artefacts that plague typical voltage-modulated PFM switching spectroscopy26. This ferroelectric origin of the hysteresis is further supported by non-hysteretic off-surface loops26, which probe electrostatic contributions. \n\n![](images/8a9653603a432bd14a4c67f936302954c84355034a03bf1a62e4669172d90874.jpg) \n\nExtended Data Fig. 8 | High-frequency capacitance characterization of ultrathin HZO. a, Schematic heterostructure of ultrathin HZO on metallic TiN probed the microwave capacitance measurements to eliminate contributions from the semiconducting Si substrate. b, PFM phase contrast (left) and topography (right) imaging for 10 cycles HZO on TiN-buffered Si. Ultrathin ferroelectricity persists on top of metallic underlayers as well as dielectric $\\mathsf{S i O}_{2}$ although the topography is rougher than the films on $\\mathsf{S i O}_{2}$ due to the inhomogeneity introduced by the sputtered TiN. c, SCM dC–dV spectroscopy loops taken on multiple bare regions of an ultrathin ten-cycle HZO film, demonstrating reproducible SCM response. The square $180^{\\circ}$ phase hysteresis and dC/dV loops, which integrates into the classic butterfly-shaped capacitance–voltage plot (Fig. 2c), provides conclusive evidence of ferroelectric polarization switching beyond PFM loops (Fig. 2e, Extended Data Fig. 6). The microwave-frequency nature of the SCM enables leakage-mitigated differential capacitance measurements of ultrathin films (Methods). d, PFM switching-spectroscopy loops taken on the same region of the ten-cycle HZO as the SCM measurements, confirming the ferroelectric-like phase and amplitude hysteresis. We note that the SCM and PFM switching spectroscopy was done using the Asylum Cypher scanning probe microscope at Asylum Research (Methods). \n\n![](images/3c952397def771f6be219988a4202aae8ff051fd328f389aa9ac051437a7a970.jpg) \n\ng \n\n\n
Material System1 (ev)2 (eV)StructureRef.
Perovskite BaTiO3。 =3.0=0.6Tetragonal (P4mm)mp5986
Fluorite ZrO2△r=3.3n/aTetragonal (P42/nmc)mp2574
Fluorite ZrO2△r =3.3△R=1.6Orthorhombic (Pca2)mp55605
Fluorite HZO (1 nm)△r=4.6△R=2.3Orthorhombic (Pca2)this work
\n\nExtended Data Fig. 9 | Ultrathin-enhanced distortions and polar signatures from spectroscopy. a, Crystal field splitting diagram for the fluorite-structure structural polymorphs; symmetry-induced $e$ -splitting provides a spectroscopic signature for the polar O-phase (Methods). b, Delineating symmetry-split energy regimes in oxygen K-edge XAS. Just as convergent beam electron diffraction provides signatures to demonstrate inversion symmetry breaking49, XAS provides spectroscopic signatures to distinguish between the nonpolar tetragonal and polar orthorhombic polymorphs (difficult to resolve from GI-XRD). Left, simulated XAS spectrum for tetragonal $Z\\mathbf{r}0_{2}(P4_{2}/n m c)$ and right, polar orthorhombic $Z\\mathrm{r}0_{2}(P c a2_{1})$ , both courtesy of the Materials Project56,57. The background colour shading denotes the symmetry-split regimes explained in the crystal field splitting diagram. c, Experimental XAS data on ultrathin HZO displays similar spectroscopic XAS features as the simulated polar O-phase (Pca21)—namely, relative $e/t_{2}$ spectral weight and splittings corresponding to tetrahedral $(\\Delta_{\\mathrm{T}})$ and rhombic $(\\Delta_{\\mathfrak{R}})$ distortions. Left, XAS of the HZO thickness series at the $0K$ edge, zooming in on the $e\\mathrm{\\cdot}$ and $t_{2}$ -regimes. Right, $\\mathbf{0}K\\mathbf{\\cdot}$ -edge spectral weight trends as a function of HZO thickness. The relative spectral weights from the $t_{2}/e$ and $e$ -split regimes indicate enhanced tetrahedral $(\\Delta_{\\mathrm{T}})$ and rhombic distortions $(\\Delta_{\\tt R})$ in ultrathin films, respectively, consistent with $C_{2v}$ symmetry of the polar O-phase. d, Schematic representation of the cation nearest-neighbour coordination dropping from $N N=8$ (T-phase) to $N N=7$ (polar O-phase) as the crystal symmetry is lowered. The disorder in oxygen polyhedral coordination (note \n\nthe different oxygen atoms denoted by the blue and cyan atoms in the polar O-phase) manifests as spectral weight in the pre-edge regime62. e, The experimental pre-edge spectral weight as a function of thickness, indicating ultrathin-enhanced polyhedral disorder. f, Top: PEEM-XLD images of ten-cycle (1 nm) HZO at the $\\mathbf{\\xi}_{0K}$ edge. Pre-edge images (left) exhibit no XLD contrast, while on-edge images (right)—at the energy corresponding to the polar-distortion split $e$ -regime—demonstrate XLD contrast. This suggests that XLD is indeed sensitive to polar features in ultrathin highly textured HZO. Bottom, line profile of the XLD intensity, demonstrating substantial variations in on-edge XLD data compared to noise for pre-edge XLD. g, Crystal field splitting energies in HZO-related transition metal oxide systems. The material system, primary crystal electric field $(\\Delta_{1})$ , secondary crystal electric field $(\\Delta_{2})$ , and structure for various systems related to HZO and perovskite ferroelectrics are shown, where $\\Delta_{\\mathrm{o}},\\Delta_{\\mathrm{t}},\\Delta_{\\mathrm{r}}$ and $\\Delta_{\\scriptscriptstyle{\\tt R}}$ corresponds to octahedral, tetragonal, tetrahedral, and rhombic crystal electric field (CEF), respectively. The reference crystal electric field values are taken from the Materials Project database57 (reference codes denoted by ‘mp’), and the experimental values are extracted via XAS energy-split features (b). The large tetrahedral $(\\Delta_{\\mathrm{T}})$ and rhombic $(\\Delta_{\\mathfrak{r}})$ crystal field splitting energies present in ten-cycle HZO films are much larger than expected values for the polar fluorite-structure $Z\\mathsf{r}\\mathsf{O}_{2}$ (b), which highlights the enhanced distortion present in ultrathin films subject to confinement strain, and is consistent with anomalously large structural distortions extracted from diffraction (Fig. 3g). \n\n![](images/8d66d08118b13117e8b87f7d9b795df528638a82b32bbc444e1890ea0c1eb808.jpg) \nExtended Data Fig. 10 | Ultrathin HZO ferroelectric tunnel junction. a, c, Tunnel current–voltage characterization of $\\mathrm{Si(p^{++})/S i O_{2}(1n m)/H Z O(\\sim1n m)/W}$ capacitor devices—demonstrated for ten-cycle HZO with Hf:Zr composition 4:1 (a) and 1:1 (c)—as a function of the write pulse (to set the ferroelectric polarization state). Tunnelling electroresistance behaviour is demonstrated for $\\pm2\\upnu$ write and $100\\mathrm{mV}$ read. Insets, linear-scale current–voltage characteristics of the two polarization-driven current states. b, d, Tunnelling electroresistance hysteresis map as a function of write voltage (demonstrated for ten-cycle HZO with Hf:Zr composition 4:1 (b) and 1:1 (d)) measured at 200 mV read voltage. The abrupt hysteretic behaviour and saturating tunnelling electroresistance is characteristic of polarization-driven switching67, as \n\nopposed to filamentary-based switching caused by electrochemical migration and/or oxygen vacancy motion (Methods). e, Current–voltage hysteresis sweeps ruling out non-polarization-driven resistive switching mechanisms (Methods). The device demonstrates current–voltage hysteresis at low voltage and voltage polarity-independent current–voltage hysteresis sense: both negative-positive-negative voltage polarity (left) and positive-negativepositive voltage polarity (right) demonstrate counter-clockwise hysteresis. Such behaviour rules out resistive switching mediated by dielectric breakdown and filamentary mechanisms66 and is consistent with polarization-driven switching. " + }, + { + "id": "10.1038_s41467-020-16266-w", + "DOI": "10.1038/s41467-020-16266-w", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-16266-w", + "Relative Dir Path": "mds/10.1038_s41467-020-16266-w", + "Article Title": "Universal mechanical exfoliation of large-area 2D crystals", + "Authors": "Huang, Y; Pan, YH; Yang, R; Bao, LH; Meng, L; Luo, HL; Cai, YQ; Liu, GD; Zhao, WJ; Zhou, Z; Wu, LM; Zhu, ZL; Huang, M; Liu, LW; Liu, L; Cheng, P; Wu, KH; Tian, SB; Gu, CZ; Shi, YG; Guo, YF; Cheng, ZG; Hu, JP; Zhao, L; Yang, GH; Sutter, E; Sutter, P; Wang, YL; Ji, W; Zhou, XJ; Gao, HJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Two-dimensional materials provide extraordinary opportunities for exploring phenomena arising in atomically thin crystals. Beginning with the first isolation of graphene, mechanical exfoliation has been a key to provide high-quality two-dimensional materials, but despite improvements it is still limited in yield, lateral size and contamination. Here we introduce a contamination-free, one-step and universal Au-assisted mechanical exfoliation method and demonstrate its effectiveness by isolating 40 types of single-crystalline monolayers, including elemental two-dimensional crystals, metal-dichalcogenides, magnets and superconductors. Most of them are of millimeter-size and high-quality, as shown by transfer-free measurements of electron microscopy, photo spectroscopies and electrical transport. Large suspended two-dimensional crystals and heterojunctions were also prepared with high-yield. Enhanced adhesion between the crystals and the substrates enables such efficient exfoliation, for which we identify a gold-assisted exfoliation method that underpins a universal route for producing large-area monolayers and thus supports studies of fundamental properties and potential application of two-dimensional materials. Here, the authors develop a one-step, contamination-free, Au-assisted mechanical exfoliation method for 2D materials, and isolate 40 types of single-crystalline monolayers, including elemental 2D crystals, metal-dichalcogenides, magnets and superconductors with millimetre size.", + "Times Cited, WoS Core": 631, + "Times Cited, All Databases": 687, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000536569900051", + "Markdown": "# Universal mechanical exfoliation of large-area 2D crystals \n\nYuan Huang1,2,12, Yu-Hao Pan3,12, Rong Yang1,2,12, Li-Hong Bao 1, Lei Meng1, Hai-Lan Luo 1, Yong-Qing Cai1, Guo-Dong Liu1, Wen-Juan Zhao1, Zhang Zhou1, Liang-Mei Wu1, Zhi-Li Zhu1, Ming Huang 4, Li-Wei Liu5, Lei Liu 6, Peng Cheng1, Ke-Hui Wu1, Shi-Bing Tian1, Chang-Zhi Gu 1, You-Guo Shi1, Yan-Feng Guo7, Zhi Gang Cheng $\\textcircled{1}^{1,2,8}$ , Jiang-Ping Hu1,2,8, Lin Zhao1,2,8, Guan-Hua Yang9, Eli Sutter $\\textcircled{1}$ 10, Peter Sutter $\\textcircled{1}$ 11 ✉, Ye-Liang Wang1,4, Wei Ji $\\textcircled{1}$ 2✉, Xing-Jiang Zhou1,2,8✉ & Hong-Jun Gao 1,8✉ \n\nTwo-dimensional materials provide extraordinary opportunities for exploring phenomena arising in atomically thin crystals. Beginning with the first isolation of graphene, mechanical exfoliation has been a key to provide high-quality two-dimensional materials, but despite improvements it is still limited in yield, lateral size and contamination. Here we introduce a contamination-free, one-step and universal Au-assisted mechanical exfoliation method and demonstrate its effectiveness by isolating 40 types of single-crystalline monolayers, including elemental two-dimensional crystals, metal-dichalcogenides, magnets and superconductors. Most of them are of millimeter-size and high-quality, as shown by transfer-free measurements of electron microscopy, photo spectroscopies and electrical transport. Large suspended two-dimensional crystals and heterojunctions were also prepared with high-yield. Enhanced adhesion between the crystals and the substrates enables such efficient exfoliation, for which we identify a gold-assisted exfoliation method that underpins a universal route for producing large-area monolayers and thus supports studies of fundamental properties and potential application of two-dimensional materials. \n\nT dwiom-deinmsieonsailoitnya-lcor(r2elDa)tedmqautearnitaulsm cpohnetninoumeenat1o–6, svuecahl as 2D superconductivity, magnetism, topologically protected states, and quantum transport1,7–11. Stacking 2D materials into van der Waals heterostructures leads to further emergent phenomena and derived device concepts12,13. The further discovery and application of their properties depend on the development of synthesis strategies for 2D materials and heterostructures6,14–18. Synthesis using crystal growth methods can now produce large (millimeter scale) single crystals of some 2D materials, notably graphene and hexagonal boron nitride, but the scalable growth of high-quality crystals has remained challenging18,19, with many 2D materials and especially heterostructures proving difficult to realize by bottom-up approaches. Ion-intercalation and liquid exfoliation are used as top-down approaches but, as chemical methods, they often cause contamination of the isolated 2D surfaces20,21. While some goldassisted exfoliation methods were demonstrated in layered chalcogenides22–24, those methods still bring unexpected contamination in samples prepared for electrical and optical measurements and thus reduce their performances when removing gold films with chemical solvents in additional steps. In light of this, a contamination-free, one-step and universal preparation strategy for large-area, high-quality monolayer materials is still lacking for both fundamental research and applications. \n\nIn the past 15 years, mechanical exfoliation has been a unique enabler of the exploration of emergent 2D materials. Most intrinsic properties of graphene, such as the quantum Hall effect25, massless Dirac Fermions26, and superconductivity27, were mostly observed on exfoliated flakes but are either inaccessible or suppressed in samples prepared by other methods17,28. While exfoliation often suffers from low yield and small sizes of the exfoliated 2D flakes5, many layered materials are, however, yet to be exfoliated into monolayers by established exfoliation methods. Such challenge of exfoliation limits their utility for scalable production of 2D crystals and complicates further processing, e.g., to fabricate heterostructures. These issues could be resolved by identifying suitable substrates that firmly adhere to 2D crystals without compromising their structure and properties, thus allowing the separation and transfer of the entire top sheet from a layered bulk crystal. Covalent-like quasi-bonding (CLQB), a recently uncovered non-covalent interaction with typical interaction energies of \\~0.5 eV per unit cell29–31, fits the requirements of the craving interaction between substrates and 2D layers. The intermediate interaction energy for CLQB is a balance of a reasonably large Pauli repulsion induced by interlayer wavefunction overlap and an enhanced dispersion attraction caused by more pronounced electron correlation in 2D layers with high polarizability. \n\nPromising candidate substrates for CLQB with 2D crystals are materials whose Fermi level falls in a partially filled band with mostly $s-$ or $\\boldsymbol{p}$ -electrons to prevent disrupting the electronic structure of 2D layers, and which have highly polarizable electron densities to ensure a large dispersion attraction. Noble metals meet these criteria and are easily obtained as clean solid surfaces. Group 11 (IB) coinage metals, i.e., Cu, Ag, and Au, remain as potential candidates after ruling out group 8–10 (VIII) metals of too strong hybridization, Al of high activity to 2D layers and in $\\mathrm{air}^{32,33}$ and closed-shell group 12 (IIB) metals (Zn, Cd, Hg). Among those three, Au interacts strongly with group 16 (VIA) chalcogens (S, Se, Te) and 17 (VIIA) halogens (Cl, Br, I), which terminate surfaces in most 2D materials. Together with its low chemical reactivity and air stability, Au appears promising for high-yield exfoliation of many 2D materials, which is also evidenced by three previous reports22–24. According to the periodic table, Pt may behave similarly to Au. However, the hybridization between $\\mathrm{\\Pt}$ and many 2D appears too strong to significantly change their electronic structures34. In addition, Au is mechanically softer than $\\mathrm{Pt},$ which may improve the interfacial contact under the gentle pressure applied during the exfoliation process. \n\n# Results \n\nTheoretical prediction of Au-assisted exfoliation. Density functional theory (DFT) calculations were employed to substantiate these arguments by comparing the interlayer binding energies of a large set of layered crystals with their adhesion energies to the Au (111) surface. A total of 58 layered materials, including 4 non-metallic elemental layers and 54 compounds comprised of metal and non-metal elements were considered in our calculations (see Fig. 1a). They belong to 18 space groups covering square, hexagonal, rectangular, and other lattices (Fig. 1b). The surfaces of all considered compound layers are usually terminated with group 16 (VIA) or 17 (VIIA) elements, e.g., S, Se, Te, Cl, Br, and I, with the exception of $\\mathrm{W}_{2}\\mathrm{N}_{3}$ . These atoms, together with group 15 (VA) elements, are expected to have substantial interactions with Au substrates, which is verified by our differential charge density (DCD) plots. \n\nFigure 1c–f shows the DCDs of graphene, black phosphorus (BP), $\\ensuremath{\\mathrm{MoS}}_{2}$ , and ${\\mathrm{RuCl}}_{3}$ monolayers adsorbed on Au (111), representing the interactions of Au with group 14 (IVA) to 17 (VIIA) atoms, respectively. The adhesion induced charge redistribution of graphene differs from those of the other three layers. While Au only introduces charge dipoles at the interface to graphene, significant covalent characteristics, i.e., charge reduction near the interfacial atoms and charge accumulation between them, were observable at the P/Au, S/Au, and $\\mathrm{Cl/Au}$ interfaces. The difference in charge redistribution is reflected in the smaller adhesion energy of graphene/Au ( $28\\mathrm{meV}\\mathring{\\mathrm{A}}^{-2}$ ; $0.15\\mathrm{eV}$ per unit cell) compared with those of the other three interfaces (56, 40, and $36\\mathrm{meV}\\mathring{\\mathrm{A}}^{-2}$ ; 0.80, 0.35, and $1.11\\mathrm{eV}$ per unit cell). The clearly covalent nature of the $\\mathsf{S}/\\mathrm{Au}$ interface is consistent with previous reports22–24 and confirms our expectation. Our results of DCD and electronic band structures (Supplementary Fig. 1), suggest the existence of CLQB at the S/Au, P/Au, and Cl/Au interfaces, which is confirmed by comparing the interlayer (0.23, 0.48, and $0.57\\mathrm{eV}$ per unit cell) and 2D crystal/Au (0.35, 0.80, and $1.11\\mathrm{eV}$ per unit cell) binding energies. Figure 1g and Supplementary Table 1 show the comparison of these energies for all 58 considered 2D crystals, where the 2D crystal/Au binding is invariably stronger than the corresponding interlayer binding. These results support the concept that the 2D crystal/Au interaction should be sufficient to overcome the interlayer attraction and facilitate exfoliating monolayers from a broad range of layered crystals. Here, we define a ratio $R_{\\mathrm{LA/IL}}$ as layer-Au over interlayer adhesion energies. Possible exceptions are those 2D materials whose $R_{\\mathrm{LA/IL}}$ values, while greater than 1, are substantially smaller than usual $R_{\\mathrm{LA/IL}}$ values $(>1.3)$ . Here, BN (1.07), ${\\mathrm{GeS}}_{2}$ (1.17), and graphene (1.24) are some examples. \n\nLarge-scale exfoliation of 40 two-dimensional monolayers. To test these theoretical predictions, we implemented the Au-assisted exfoliation of 2D materials as shown in Fig. 2a. Firstly, a thin layer of Au is deposited onto a substrate covered with a thin Ti or Cr adhesion layer. Then, a freshly cleaved layered bulk crystal on tape is brought in contact with the Au layer. Adhesive tape is placed on the outward side of the crystal, and gentle pressure is applied to establish a good layered crystal/Au contact. Peeling off the tape removes the major portion of the crystal, leaving one or few large-area monolayer flakes on the Au surface. Limited only by the size of available bulk crystals, these monolayer flakes are usually macroscopic in size (millimeters; see Methods for details). \n\n![](images/371467267e66d51ff73ed5670b36d786885b2cde93fbeccb6921323177f6a7a9.jpg) \nFig. 1 DFT calculated interlayer binding energies of 2D materials and adsorption energies on Au (111) surfaces. a Part of the periodic table, showing the elements involved in most 2D materials between groups 4 (IVB) and 17 (VIIA). b Eighteen space groups and typical structural configurations (top views) of the 2D materials. c–f DCD of four Au (111)/2D crystal interfaces with (non-metallic) terminating atoms between groups 14 (IVA) and 17 (VIIA). Isosurface values of these DCD plots are $5\\times10^{-4}$ e Bohr−3 (graphene), $1\\times10^{-2}$ e Bohr−3 (BP), and $1\\times10^{-3}$ e Bohr−3 ( $\\mathrm{~\\normalfont~.~}M\\circ\\mathsf{S}_{2}$ ${\\sf R u C l}_{3})$ , respectively. g Bar graph comparing the interlayer binding energies of 2D materials (blue cylinders) with their adsorption energies on $\\mathsf{A u}$ (111) (red cylinders). The visible red cylinders represent the difference between the $A u/2D$ crystal interaction and the interlayer interaction. \n\nOptical microscopy was used to examine the dimensions and uniformity of the exfoliated 2D crystals. Figure 2b shows an image of exfoliated $\\mathbf{MoS}_{2}$ monolayers reaching lateral dimensions close to $1\\mathrm{cm}$ on a $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate covered with Au $(2\\mathrm{nm})/\\mathrm{Ti}$ $(2{\\mathrm{nm}})$ . We also extended the base substrate from the $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate to transparent (quartz, sapphire; Fig. 2c) and flexible plastic supports (Fig. 2d). The transparency persists even for thicker $(\\sim10\\mathrm{nm}$ ) $\\mathrm{Au}/$ Ti layers although light transmission slightly decreases. This method can also be applied to CVD-grown wafer-scale transitionmetal-dichalcogenides (TMDCs) materials, such as $\\ensuremath{\\mathrm{MoS}}_{2}$ (Fig. 2e). The exfoliated monolayer flakes can be intactly transferred onto arbitrary substrates after removing gold layer by $\\mathrm{KI}/\\mathrm{I}_{2}$ etchant. Therefore, back-gated devices and heterostructures can be fabricated (see Methods and Supplementary Fig. 5 for details). \n\nX-ray photoelectron spectroscopy (XPS) was employed to further investigate the interaction between $\\ensuremath{\\mathrm{MoS}}_{2}$ and Au. Supplementary Fig. 2d shows an XPS spectrum of exfoliated $\\mathrm{MoS}_{2}$ near the Mo 3d region. Peaks centered at 226.5, 229, and $232\\mathrm{eV}$ result from $\\mathrm{~S~}2s,$ Mo $3d_{5/2}$ , and Mo $3d_{3/2}$ photoelectrons, respectively. There are no appreciable changes in terms of shape, binding energy, and width of the XPS peaks compared to those of bulk $\\mathbf{MoS}_{2}$ . Hence, the nearly unchanged XPS spectra confirm CLQB rather than covalent bonding between $\\mathbf{MoS}_{2}$ and the Au substrate. Supplementary Figs. 3 and 7 show Raman, photoluminescence (PL) and angle-resolved photoemission spectroscopy (ARPES) of a typical exfoliated $\\mathbf{MoS}_{2}$ monolayer. Sharp $E_{2\\mathrm{g}}$ and $\\boldsymbol{A}_{1\\mathrm{g}}$ Raman peaks at 386 and $406\\mathrm{cm}^{-1}$ , respectively, confirm the high quality of the $\\ensuremath{\\mathrm{MoS}}_{2}$ monolayer35. The pronounced Aexciton PL peak at $1.83\\mathrm{eV}$ indicates the exfoliated $\\ensuremath{\\mathrm{MoS}}_{2}$ on Au is still a direct-band gap semiconductor36. Metal substrates usually quench the PL intensity of monolayer $\\mathrm{MoS}_{2}{}^{23,24}$ ; however, our PL signal remains strong because of the thickness-tunable conductivity of our metal substrates, as elucidated later. \n\n![](images/d9cf96353c1b791eb077eff295980c49211a492c0df119499e4b5f9560d73958.jpg) \nFig. 2 Mechanical exfoliation of different monolayer materials with macroscopic size. a Schematic of the exfoliation process. b–d Optical images of exfoliated $M\\circ\\mathsf{S}_{2}$ on $\\mathsf{S i O}_{2}/\\mathsf{S i}$ , sapphire, and plastic film. e 2-inch CVD-grown monolayer ${M o S}_{2}$ film transferred onto a 4 inch $\\mathsf{S i O}_{2}/\\mathsf{S i}$ substrate. ${\\pmb{\\mathscr{f}}}{-}{\\pmb{\\mathscr{g}}}$ Optical images of large exfoliated 2D crystals: BP, FeSe, $\\mathsf{F e}_{3}\\mathsf{G e}\\mathsf{T e}_{2},\\mathsf{R u C l}_{3},$ $\\mathsf{P t S e}_{2},$ $\\mathsf{P t T e}_{2},$ , $\\mathsf{P d T e}_{2},$ and $\\mathsf{C r S i T e}_{3}$ . Those exfoliated monolayers highlighted in the red box are, so far, not accessible using other mechanical exfoliate method. h Optical image and Raman spectra of a ${M o S}_{2}/{\\sf W S e}_{2}$ heterostructure. i Raman and photoluminescence (PL) spectra of suspended monolayer ${\\mathsf{W S e}}_{2}$ j Optical image of suspended ${\\mathsf{W S e}}_{2}$ with different thicknesses (1 L to 3 L) and a PL intensity map of the suspended monolayer. \n\nWe applied the Au-assisted exfoliation method to other 2D crystals and have obtained a library of 40 large-area single-crystal monolayers, as shown in Fig. $2\\mathrm{f-g}$ and Supplementary Fig. 8. Besides transition-metal-dichalcogenides, the library contains metal monochalcogenides (e.g., GaS), black phosphorus, black arsenic, metal trichlorides (e.g., ${\\mathrm{RuCl}}_{3}.$ ), and magnetic compounds (e.g., $\\mathrm{Fe}_{3}\\mathrm{GeTe}_{2})$ . It is rather striking that some monolayers, i.e., FeSe, $\\mathrm{PdT}\\mathrm{e}_{2}.$ , and $\\mathrm{PtTe}_{2}.$ , become accessible by our exfoliation method. This method is, as we expected according to the smaller $R_{\\mathrm{LA/IL}}$ values (1.24 and 1.07), less effective for exfoliating graphene and h-BN monolayers, which are accessible by chemical vapor deposition. The exfoliated monolayer samples show high quality, as characterized by Raman and atomic force microscopy (Supplementary Figs. 9 and 10). Reactive samples were exfoliated in a glove box due to their stability issues in air. \n\n# Optical characterization of hetero- and suspended-structures. \n\nOur method also promotes preparation of van der Waals heterostructures and suspended 2D materials at human visible size scales. Figure 2h shows a typical monolayer $\\mathrm{MoS}_{2}/\\mathrm{WSe}_{2}$ heterostructure prepared using this method. Raman spectra (Fig. 2h) show the characteristic vibrational modes of both the $\\mathrm{MoS}_{2}$ and $\\mathsf{W S e}_{2}$ layers. PL spectra of this heterostructure sample is shown in Supplementary Fig. 6. Given the exceeding $R_{\\mathrm{LA/IL}}$ values over 1.30, patterned Au thin-films on substrates with holes, are also, most likely, able to exfoliate 2D crystals and thus to fabricate suspended monolayers, which is of paramount importance on studying intrinsic properties of 2D layers37,38. We show an example with suspended 1L-3L ${\\mathrm{WSe}}_{2}$ in (Fig. 2i), which can reach $90\\%$ coverage over at least tens of micrometers (Supplementary Fig. 11). The suspended monolayer film is detached from multilayer instead of transferring monolayer by organic films, which totally avoid polymer contamination. In comparison with supported samples on $\\mathrm{SiO}_{2}$ , the suspended $\\mathrm{WSe}_{2}$ (Fig. 2i) shows enhanced PL intensity (16 times) and sharper PL peak (full width at half maximum (FWHM): $34\\mathrm{meV}$ , compared with $64\\mathrm{meV}$ for supported ${\\mathrm{WSe}}_{2}.$ ) as shown in Supplementary Fig. 12. Since PL can be fully quenched on thicker metal film while well maintained on suspended area, therefore, we realized patterning of PL even on one monolayer flake (Fig. 2j). \n\nSurface characterization of as-exfoliated samples. High-quality macroscopic monolayers have practical advantages, for instance in establishing the lattice structure and electronic band structure of unexplored 2D materials or van der Waals stacks by scanning tunneling microscopy (STM) and ARPES. The Au-coated support facilitates such electron-based spectroscopy by eliminating charging effects associated with insulating (e.g., $\\mathrm{SiO}_{2}$ ) substrates while preserving the intrinsic electronic band structures. Figure 3a, b illustrates atomic-resolution STM images for as-exfoliated $\\mathsf{W S e}_{2}$ and $\\mathrm{T_{d}}\\mathrm{-}\\mathrm{MoT}\\mathrm{e}_{2}$ monolayers, which are challenging to image on insulating substrates due to charging effects. Low-energy electron diffraction with millimeter incident electron-beam size shows a single-phase diffraction pattern for $\\mathrm{MoTe}_{2}$ (Fig. 3c), indicating that it is a single-crystal at the millimeter scale. Figure 3d displays an ARPES map of the low-energy electronic structure of the $\\mathrm{WSe}_{2}$ monolayer, showing clear and sharp bands. The valence band features a single flat band around $\\Gamma$ and a large band splitting near K. Along the Γ-K line, one single band starts to split into two spin-resolved bands at $\\begin{array}{r}{k\\approx{\\frac{1}{3}}\\Delta\\bar{k}^{\\mathrm{\\bar{K}},\\Gamma}}\\end{array}$ , and the valence band maximum at K sits at ${\\sim}0.6\\mathrm{eV}$ higher than that at Γ. Figure 3e displays the symmetric band splitting spectra along $\\mathrm{K-M-\\bar{K}^{\\d}}$ arising from strong spin-orbit coupling mainly at the W site in the ${\\mathrm{WSe}}_{2}$ lattice39. These features constitute the critical signatures of band dispersion in monolayer TMDCs. Here it deserves an emphasis on the big advantage of large area of monolayer TMDCs, which make it quite feasible and easy to accurately measure the band structure by using standard ARPES technique40. \n\nFET Devices directly built on as-exfoliated layers. Even some previous studies proved to exfoliate large-area chalcogenides layers using gold $\\mathrm{\\hat{fulms}}^{22-24}$ ; however, further characterizations including optical and electrical measurements are usually achieved by an additional transfer process onto insulating substrate. Nevertheless, we show here that the conductivity of $\\mathrm{\\bar{\\Au/Ti}}$ adhesion layer can be drastically tuned by controlling its nominal thickness, which demonstrate that both optical measurements and device fabrication can be realized on this one-step exfoliated samples. Figure 4a, b shows that the $\\mathrm{\\Au/Ti}$ films become insulating (i.e., electrically discontinuous) if the combined thickness of Ti/Au decreases to $3\\mathrm{nm}$ or below41. Our exfoliation method is not apparently limited by the Au thickness, therefore, those largearea 2D crystals are expected to be exfoliated by either conducting or non-conducting Au-coated substrates. \n\nSupplementary Fig. 3c shows a $\\ensuremath{\\mathrm{MoS}}_{2}$ flake exfoliated by an electrically discontinuous (0.5 nm Ti, 1.5 nm Au) adhesion layer on a $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate (Fig. 4b inset and Supplementary Fig. 13), in which almost no lateral channel is available to carry current flow through the substrate. Although some prior studies used Au films to enhance exfoliation of $\\mathrm{MoS}_{2}$ , the PL intensity of their $\\ensuremath{\\mathrm{MoS}}_{2}$ samples was largely quenched22,24. By contrast, our $\\ensuremath{\\mathrm{MoS}}_{2}$ monolayer exfoliated using electrically discontinuous metal adhesion layers show intense PL signals (see Supplementary Figs. 3 and 4). Such electrically discontinuous layers also allow to fabrication of electronic devices directly from the as-exfoliated 2D monolayers. Figure 4c shows the trans-conductance curve of a prototype device, a field-effect transistor (FET) directly built on an as-exfoliated monolayer $\\mathbf{MoS}_{2}$ channel on $\\mathrm{Au}(\\mathrm{i}.5\\mathrm{nm})/\\mathrm{Ti}$ $(0.5\\mathrm{nm})/\\mathrm{SiO}_{2}/\\mathrm{Si}$ . Supplementary Fig. 14 shows the device layout. The device, controlled by an ionic-liquid top gate, shows a high on–off current ratio $(>\\dot{1}0^{6}$ at $T=2\\bar{2}0\\mathrm{K}$ ), comparable to usual $\\ensuremath{\\mathrm{MoS}}_{2}$ FETs directly fabricated on $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrates7,42. A subthreshold swing (SS) of $100\\mathrm{mV~dec^{-1}}$ . was derived, close to the best values reported in the literature7,43,44, ranging from $74\\mathrm{mV~dec^{-1}}$ . to $\\mathrm{\\bar{41}0m V~d e c^{-1}}$ . Given the previously reported capacitance value of $C_{\\mathrm{i}}=1.3{\\sim}2~{\\upmu}\\mathrm{F}~\\mathrm{cm}^{-2}$ for the ionic liquid45,46, we derived the field-effect mobility of $\\mathrm{22.1-32.7\\cm^{2}V^{-1}s^{-1}}$ for our ionic-liquid-gated $\\mathbf{MoS}_{2}$ device (Fig. 4c). The estimated mobility value is very close to that of our ordinary back-gated FET built with transferred $\\ensuremath{\\mathrm{MoS}}_{2}$ monolayer on $\\mathrm{Si}\\mathrm{\\bar{O}}_{2}/\\mathrm{Si}$ $(\\sim30\\mathrm{cm}^{2}\\mathrm{V}^{-1}s^{-1})$ and is also comparable with those values reported in the literature, i.e., tens of $\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ 47. A superconducting transition was also observed at $4.5\\mathrm{K}$ (Supplementary Fig. 15). All these results show good performance of the FET directly fabricated on the ultrathin metal adhesion layer and its potential for further improvements. We extended the individual FET to an FET array directly built on an exfoliated centimeter-scale single-crystal $\\ensuremath{\\mathrm{MoS}}_{2}$ flake using UV lithography (Supplementary Fig. 16), indicating great potential of our exfoliation method for fabrication of integrated circuit. Note that, for those FET devices with discontinuous metal layer underneath, the back gate does not work due to the screen effect. However, the 2D layers could be lifted off and transferred to other insulating substrates, e.g., oxidized Si wafer, by removing the gold layer. We also fabricated back-gated $\\mathbf{MoS}_{2}$ monolayer FET devices based on freshly transferred large-size $\\mathbf{MoS}_{2}$ flakes on $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrates. Supplementary Fig. 17 presents the results of electrical transport measurements of the back-gated FETs, which show high mobility $(\\sim30\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1})$ and large on–off ratio $(\\sim10^{7})$ . These values manifest that the transferred $\\ensuremath{\\mathrm{MoS}}_{2}$ monolayer still preserves its high quality (Supplementary Fig. 17; see Methods for details). Since electrical current is prone to flow through superconducting regions, the metal adhesion layer does not suppress the transition of an exfoliated layer from its normal state to its superconducting state. Figure 4d shows a $\\mathrm{T_{d}}\\mathrm{-}\\mathrm{MoT}\\mathrm{e}_{2}$ device, directly fabricated on a $2\\mathrm{nm}$ metal layer, undergoes a metalsuperconductor transition at $70\\mathrm{mK}$ , and reaches the zeroresistance at $30\\mathrm{mK}$ . A second onset, observed at $50\\mathrm{mK},$ is, most likely, a result of quantum fluctuation in 2D crystals. A previous study of bulk $\\mathrm{T_{d}}\\mathrm{-}\\mathrm{\\bar{MoT}}\\mathrm{e}_{2}$ showed an onset of superconductivity at $250\\mathrm{mK}$ and zero-resistance at a critical temperature $T_{\\mathrm{c}}=$ $100\\ \\mathrm{\\mK^{48}}$ . The difference between bulk and monolayer’s $T_{c}$ values may be primarily relevant with reduced dimensionality49. \n\n![](images/712b9a70129065792a1abb903d8c127e82c43b36bfee8081314dbf2d17fa399f.jpg) \nFig. 3 STM and ARPES measurements of 2D materials exfoliated onto conductive $\\pmb{\\mathsf{A u}}/\\pmb{\\mathsf{T i}}$ adhesion layers. a, b STM images of monolayer ${\\mathsf{W S e}}_{2}$ and ${\\mathsf{T}}_{\\mathsf{d}}.$ ${\\sf M o T e}_{2},$ respectively. c LEED pattern of monolayer $T_{\\mathrm{d}}\\mathrm{-}M\\circ\\mathsf{T e}_{2}$ . d, e Band structure of monolayer ${\\mathsf{W S e}}_{2}$ . d Original ARPES band structure of monolayer ${\\mathsf{W S e}}_{2}$ $\\langle h v=21.2\\mathsf{e V}.$ ) along $\\Gamma{\\cdot}\\ K$ high symmetry line. The valence band maximum (VBM) is positioned at K instead of Γ, which is an important signature of monolayer ${\\mathsf{W S e}}_{2}$ . e Second-derivative spectra of band dispersion along K–M–K’, showing clear spin-orbital coupling (SOC) induced spin-splitting bands. \n\n![](images/ab838f6f3feb199513c703c4cbf28404916731c972f678971e42a23a3d8d2e56.jpg) \nFig. 4 Electrical measurements of metal adhesion layers and of 2D materials exfoliated onto nonconductive metal films. a Electrical transfer curves of typical $\\mathsf{A u/T i}$ adhesion layers. b Two-terminal resistance of $\\mathsf{A u/T i}$ layers with different nominal thickness. The inset shows atomic force microscope (AFM) phase maps of two metal layers. c Gate voltage-conductance transfer characteristics of a top-gated $M\\circ\\mathsf{S}_{2}$ FET on $\\mathsf{S i O}_{2}/\\mathsf{S i}$ with Au (1.5 nm)/Ti $(0.5\\mathsf{n m})$ adhesion layer ${\\mathrm{:}}T=220\\mathsf{K},$ source−drain bias $V_{\\sf s d}=0.1\\vee)$ . Left inset: Optical image of the FET device with windows for the ionic-liquid top gate. Right inset: low-bias source-drain current-voltage characteristics for gate voltage $-0.5$ to $0.6\\mathsf{V}$ . d Temperature-dependent resistance of a $\\mathsf{T}_{\\mathsf{d}}{\\mathsf{-}}{\\mathsf{M}}\\circ\\mathsf{T}{\\mathsf{e}}_{2}$ flake exfoliated onto $\\mathsf{S i O}_{2}/\\mathsf{S i}$ with a $2{\\mathsf{n m}}$ metal adhesion layer. \n\n# Discussion \n\nOur combined results show that exfoliation assisted by an Au adhesion layer with covalent-like quasi bonding to a layered crystal provides access to a broad spectrum of large-area monolayer materials. This method is rather unique, especially for layered crystals that are difficult to exfoliate using conventional methods. The versatility of this approach is demonstrated here by using Au adhesion layers for exfoliation of large 2D sheets from 40 layered materials. The efficient transfer of most 2D crystals is rationalized by calculations that indicate interaction energies to Au exceeding the interlayer energy for most layered bulk crystals, graphene and hexagonal boron nitride being notable exceptions. Characterization of the large-area exfoliated monolayers flakes demonstrates that the flakes are of high quality. For research on atomically thin materials, the approach demonstrated here has immediate implications. The availability of macroscopic (millimeter scale) 2D materials can support the exploration of the properties of emergent families of ultrathin semiconductors, metals, superconductors, topological insulators, ferroelectrics, etc., as well as engineered van der Waals heterostructures. For applications of 2D materials, an efficient large-scale layer transfer method could force a paradigm shift. So far, exfoliation from bulk crystals has not been deemed technologically scalable. But once exfoliation becomes so consistent that the size of the resulting 2D layers is limited only by the dimensions and crystallinity of the source crystal, the focus of application-driven materials research may shift toward optimizing the growth of high-quality layered bulk crystals. Ironically, the fabrication of 2D materials for applications would then follow the well-established and highly successful example of silicon technology, where the extraction of wafers from large, high-quality single crystals has long been key to achieving the yields and reliability required for industrial applications. \n\n# Methods \n\nDFT calculations. DFT calculations were performed using the generalized gradient approximation for the exchange-correlation potential, the projector augmented wave method50,51, and a plane-wave basis set as implemented in the Vienna ab initio simulation package $\\mathrm{\\bar{(VASP)}}^{52}$ . The energy cutoff for the plane-wave basis set was set to 700 and $500\\mathrm{eV}$ for variable volume structural relaxation of pure 2D materials and invariant volume structural relaxation of these materials on Au (111) surface, respectively. Dispersion correction was made at the van der Waals density functional (vdW-DF) level, with the optB86b functional for the exchange potential53. Seven Au (111) layers, separated by a $15\\mathrm{\\AA}$ vacuum layer, were employed to model the surface. The four bottom layers were kept fixed and all other atoms were fully relaxed until the residual force per atom was less than $0.04\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ during structural relaxations of 2D layers on Au (111) and less than $0.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ during all other structural relaxations. Lattice constant of the Au (111) surface slab was varied to match those of 2D layers for keeping their electronic properties unchanged by external strain. The lattice mismatch between each 2D layer and the Au (111) surface was kept lower than $4.5\\%$ . A $k$ -mesh of $9\\times9\\times1$ was adopted to sample the first Brillouin zone of the primitive cell of the $\\mathrm{Au}(111)$ slab and the density of $k$ - mesh was kept fixed in other relaxation calculations. Differential charge density (DCD) between a 2D layer and the Au substrate represents the charge variation after the 2D layer attaching to Au and was derived using $\\Delta\\rho_{\\mathrm{DCD}}=\\rho_{\\mathrm{All}}-\\rho_{\\mathrm{Au}}-\\rho_{\\mathrm{2D}}$ . Here $\\rho_{\\mathrm{All}}$ is the total charge density of the 2D layer/Au(111) interface, while $\\rho_{\\mathrm{Au}}$ and $\\rho_{2\\mathrm{D}}$ are the total charge densities of the individual Au surface and the 2D layer, respectively. \n\nGold-assisted mechanical exfoliation. The metal layer deposition was completed in an electron evaporation system (Peva-600E). An adhesion metal layer (Ti or Cr) was first evaporated on Si substrate (with $300\\mathrm{nm}\\mathrm{SiO}_{2}$ film), after that Au film was deposited on the substrate. The thickness of Ti (or $\\mathrm{Cr}^{\\cdot}$ and Au can be well controlled by the evaporation rate $(0.5\\mathrm{\\AA}s^{-1})$ . After depositing metal layers on Si wafer, a fresh surface of layered crystal was cleaved from tape and put it onto the substrate. By pressing the tape vertically for about $1\\mathrm{min}$ , the tape can be removed from substrate. Large-area monolayer flakes can be easily observed by optical microscope or even by eyes. Most of the time, the size of monolayer flakes is limited by the size of bulk crystal. The glue residues mainly depend on different tapes, for the white tape (3 M scotch) or blue tape (Nitto), there will be some glue left on substrate, which can be removed by further annealing if required by the subsequent measurement. However, we can also use home-made polydimethylsiloxane (PDMS) to replace these tapes as transfer media, which can make the substrate much cleaner54. The thickness of $\\mathrm{\\Au/Ti}$ layer is a crucial factor. Once the thickness larger than $2\\mathrm{{nm}\\ A u/\\ 1\\mathrm{{nm}\\ T i}}$ , the success rate is more than $99.5\\%$ . However, the flake size will decrease to few hundred micrometers when the metal layer thinner than $1\\mathrm{{nm}\\ A u/\\ 1\\mathrm{{nm}\\ T i}}$ It is hard to get 2D flakes when metal thickness thinner than $0.5\\mathrm{nm}\\mathrm{Au}/0.5\\mathrm{nm}\\mathrm{Ti}$ . The optimal thickness of $\\mathrm{\\Au/Ti}$ is 2 $\\mathrm{nm}/2\\mathrm{nm}$ . Therefore, when the gold film is nonconductive and rough, the success rate will be affected. In terms of the substrate with hole array, the success rate for exfoliating suspended $\\mathbf{MoS}_{2}$ is also more than $99\\%$ once the metal thickness is larger than $\\mathrm{Au}(2\\mathrm{nm})/\\mathrm{Ti}(1\\mathrm{nm})$ and diameter of hole smaller than $5\\upmu\\mathrm{m}$ . The success rate decreases obviously if the hole diameter larger than $10\\upmu\\mathrm{m}$ . \n\nThe bulk crystals are mainly supplied by Dr. You Guo Shi’s and Dr. Yanfeng Guo’s groups. We also tested some crystals (such as $\\mathbf{MoS}_{2}$ , ${\\mathrm{WSe}}_{2}{\\mathrm{.}}$ from commercial companies, like HQ Graphene and 2D Semiconductors, all these crystals can be exfoliated into large-area monolayer, and the monolayer size mainly depends on the bulk crystal. The thickness of bulk crystal has some influence for the exfoliation process, but not very crucial. Once the bulk crystal is too thick (e.g., $>1\\mathrm{mm}$ ) it will be difficult to ensure the interface between crystal and substrate contact well. However, it is not necessary to make the bulk crystals too thin on tape (e.g., monolayer or few layer), because bulk crystal can be break into small pieces if cleave too many times by tape. Normally, we cleave 2–3 times from pristine bulk crystal before put onto substrate with metal film. The temperature and humidity is not very sensitive for the exfoliation, the authors and some of collaborators tested this exfoliation method in different counties (US, China, Singapore and Korea) and in different seasons (the whole year from Spring to Winter), we can always get large-area 2D flakes with high success rate. The exfoliation processes of the 2D materials mainly carried out in clean-room, and the temperature and humidity always keep at $25^{\\circ}\\mathrm{C}$ and $45\\%$ . While the exfoliation can be done in a glove box without exposure to air, the whole process lasts $1{-}2\\operatorname*{min}$ . \n\nSuspended samples preparation. Si wafer with $300{\\mathrm{nm~}}\\mathrm{SiO}_{2}$ was patterned by UV lithography, after that the hole array structures were prepared by reactive-ion etching. The diameter and depth of each hole is $5\\upmu\\mathrm{m}$ and $10\\upmu\\mathrm{m}$ . The metal layers $\\left(\\mathrm{Au}/\\mathrm{Ti};2\\mathrm{nm}/2\\mathrm{nm}\\right)$ deposited on the Si substrate with hole array before exfoliating layered materials on it. Large-area suspended 2D materials can be exfoliated on the hole array substrate. \n\nHeterostructure preparation. Schematic images for the details of fabrication procedure were shown in Supplementary Fig. 5. Firstly, we exfoliated large-area $\\ensuremath{\\mathrm{MoS}}_{2}$ and $\\mathrm{WSe}_{2}$ monolayers on two separate $\\mathrm{\\Au/Ti/SiO_{2}/S i}$ substrates, respectively. Then, PMMA was spin-coated onto the $\\ensuremath{\\mathbf{MoS}}_{2}$ monolayer and then the sample was put into $\\mathrm{KI}/\\mathrm{I}_{2}$ solution. After roughly $^{10\\mathrm{h}}$ of etching, the gold film was removed and the PMMA film together with the $\\ensuremath{\\mathbf{MoS}}_{2}$ flake detached from the $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate. In order to clean the ion residual, the PMMA film was washed three times using DI water. The next step lies in using the ${\\mathrm{WSe}}_{2}$ sample to pick up the $\\mathrm{PMMA}/\\mathrm{MoS}_{2}$ film from water. Since both $\\ensuremath{\\mathrm{MoS}}_{2}$ and $\\mathrm{WSe}_{2}$ flakes are several millimeters in size, no special alignment is need in this step if the twisting angle between these two layers is not specified. Additional baking at ${\\sim}100^{\\circ}\\mathrm{C}$ ensures the contact between these two layers. Next, we employed the same procedure, i.e., etching in $\\mathrm{KI}/\\mathrm{I}_{2}$ solution and three times washing using DI water, to remove the Au film from ${\\mathrm{WSe}}_{2}$ . A new substrate, e.g., $\\mathrm{SiO}_{2}/\\mathrm{Si}$ was used to pick up the heterobilayer from Di water. Finally, we removed the PMMA layer using acetone. \n\nMonolayer $M o S_{2}$ back-gated FET devices fabrication. After exfoliating largearea $\\ensuremath{\\mathbf{MoS}}_{2}$ on metal film ( $\\mathrm{\\DeltaAu/Ti}$ : $2\\mathrm{nm}/2\\mathrm{nm}\\cdot$ ), PMMA films were spin-coated on the substrates. Then, the samples were put into $\\mathrm{KI}/\\mathrm{I}_{2}$ solution for about $^{10\\mathrm{h}}$ . The PMMA films together with $\\ensuremath{\\mathbf{MoS}}_{2}$ can be detached from $\\mathrm{SiO}_{2}/\\mathrm{Si}$ substrate after etching gold film. The PMMA films with $\\ensuremath{\\mathbf{MoS}}_{2}$ were cleaned three times by DI water, after that the films were transferred onto new Si substrates (with $300\\mathrm{nm}$ $\\mathrm{SiO}_{2}$ layer) for device fabrication. Electron-beam lithography (EBL) is used to pattern an etch mask using poly(methyl) methacrylate (PMMA). The devices were fabricated after metal deposition ( $50\\mathrm{nm}$ Au, $10\\mathrm{nm}$ Ti) and lift-off. \n\nOptical characterization and measurement. The Raman and PL measurements were performed on WITec alpha300R and JY Horiba HR800 systems with a wavelength of $532\\mathrm{nm}$ and power at $0.6\\mathrm{mW}$ . Supplementary Fig. 9 presents the representative Raman spectra for monolayer and few-layer BP and $\\mathsf{a{\\mathrm{-RuCl}}}_{3}$ samples excited by $2.33\\mathrm{eV}$ radiation in vacuum environments. The laser power on the sample during Raman measurement was kept below $100\\upmu\\mathrm{W}$ in order to avoid sample damage and excessive heating. The silicon Raman mode at $520.7\\mathrm{cm}^{-1}$ was used for calibration prior to measurements and as an internal frequency reference. \n\nX-ray photoelectron spectroscopy characterization. The X-ray photoelectron spectroscopy (XPS, Thermo Scientific ESCALAB 250 Xi) was performed with Al Kα X-rays $(\\mathrm{h}\\upnu=1486.6\\mathrm{eV})$ in an analysis chamber that had a base pressure $<3\\times$ $10^{-9}$ Torr. Core spectra were recorded using a $50\\mathrm{eV}$ constant pass energy (PE) in $50\\mathrm{-}100\\upmu\\mathrm{m}$ small area lens mode (i.e., aperture selected area). The XPS peaks were calibrated using the adventitious carbon C1s peak position $(284.8\\mathrm{eV})$ ). \n\nScanning probe microscopy measurements. The AFM scanning (Veeco Multimode III) was used to check the thickness and surface morphology of those monolayer samples. The STM measurement was performed using a custom built, low-temperature, and UHV STM system at $300\\mathrm{K}.$ A chemically etched W STM tip was cleaned and calibrated against a gold (111) single crystal prior to the measurements. For STM and ARPES measurements, the 2D layers were exfoliated onto an $\\mathrm{Au(5nm)/Ti(2nm)/SiO_{2}(\\sim300n m)/S i}$ substrate. An annealing process at $500\\mathrm{K}$ for $^{2\\mathrm{h}}$ was performed to degas the samples after loading them into the highvacuum chamber. \n\nAngle-resolved photoemission spectroscopy measurement. High resolution ARPES measurements were carried out on our lab system equipped with a Scienta R4000 electron energy analyzer55. We use Helium discharge lamp as the light source, which can provide photon energies of $h\\nu=21.218\\mathrm{eV}$ (Helium I). The energy resolution was set at $10{-}20\\mathrm{meV}$ for band structure measurements (Fig. 3). The angular resolution is ${\\sim}0.3$ degree. The Fermi level is referenced by measuring on a clean polycrystalline gold that is electrically connected to the sample. The samples were measured in vacuum with a base pressure better than $5\\times\\bar{10}^{-11}$ Torr. The ARPES measurements for $\\mathrm{WSe}_{2}$ and $\\ensuremath{\\mathrm{MoS}}_{2}$ monolayers were carried out at roughly $30\\mathrm{K}$ using a home-build photoemission spectroscopy system with a VUV5000 Helium lamp. The spot diameter of the Helium lamp is $0.5\\mathrm{mm}$ . \n\nFET characterization and measurement. The electrical characteristic measurements were carried out in the probe station with the semiconductor parameter analyzers (Agilent $4156\\mathrm{C}$ and B1500) and oscilloscope. The ionic liquid used for top-gated $\\mathrm{MoS}_{2}$ FET device is N-diethyl-N-(2-methoxyethyl)-N-methylammonium bis-(trifuoromethylsulfonyl)-imide (DEME–TFSI), which has been widely used in 2D-material-based devices. \n\nOnline content. Methods, along with any Supplementary Information display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. \n\n# Data availability \n\nAll data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Information. Additional data related to this paper may be requested from the authors. \n\nReceived: 11 February 2020; Accepted: 21 April 2020; Published online: 15 May 2020 \n\n# References \n\n1. He, S. L. et al. Phase diagram and electronic indication of high-temperature superconductivity at $65~\\mathrm{K}$ in single-layer FeSe films. Nat. Mater. 12, 605–610 (2013). \n2. Zhang, C. et al. Engineering point-defect states in monolayer ${\\mathrm{WSe}}_{2}$ . ACS Nano \n13, 1595–1602 (2019). \n3. Ezawa, M. Valley-polarized metals and quantum anomalous hall effect in silicene. Phys. Rev. Lett. 109, 055502 (2012). \n4. Jiang, S. W., Li, L. Z., Wang, Z. F., Mak, K. F. & Shan, J. Controlling magnetism in 2D $\\mathrm{CrI}_{3}$ by electrostatic doping. Nat. Nanotechnol. 13, 549–553 (2018). \n5. Novoselov, K. S. et al. Electric field effect in atomically thin carbon films. Science 306, 666–669 (2004). \n6. Huang, Y. et al. Reliable exfoliation of large-area high-quality flakes of graphene and other two-dimensional materials. ACS Nano 9, 10612–10620 (2015). \n7. Radisavljevic, B., Radenovic, A., Brivio, J., Giacometti, V. & Kis, A. Single-layer $\\ensuremath{\\mathbf{MoS}}_{2}$ transistors. Nat. Nanotechnol. 6, 147–150 (2011). \n8. McGuire, M. A., Dixit, H., Cooper, V. R. & Sales, B. C. Coupling of crystal structure and magnetism in the layered, ferromagnetic insulator $\\mathrm{CrI}_{3}$ . Chem. Mater. 27, 612–620 (2015). \n9. Jiang, D. et al. High- $\\cdot\\mathrm{T}_{\\mathrm{c}}$ superconductivity in ultrathin $\\mathrm{Bi}_{2}\\mathrm{Sr}_{2}\\mathrm{CaCu}_{2}\\mathrm{O}_{8+\\mathbf{x}}$ down to half-unit-cell thickness by protection with graphene. Nat. Commun. 5, 5708 (2014). \n10. Tang, S. J. et al. Quantum spin Hall state in monolayer $1\\mathrm{T}^{\\circ}-\\mathrm{WT}\\mathbf{e}_{2}$ . Nat. Phys. \n13, 683–687 (2017). \n11. Zhang, Y. et al. Superconducting gap anisotropy in monolayer FeSe thin film. Phys. Rev. Lett. 117, 117001 (2016). \n12. Novoselov, K. S., Mishchenko, A., Carvalho, A. & Neto, A. H. C. 2D materials and van der Waals heterostructures. Science 353, 9439 (2016). \n13. Liu, Y. et al. Van der Waals heterostructures and devices. Nat. Rev. Mater. 1, \n16042 (2016). \n14. Wang, C. et al. Monolayer atomic crystal molecular superlattices. Nature 555, \n231–236 (2018). \n15. Li, X. S., Cai, W. W., Colombo, L. & Ruoff, R. S. Evolution of graphene growth on Ni and Cu by carbon isotope labeling. Nano Lett. 9, 4268–4272 (2009). \n16. Moon, I. K., Lee, J., Ruoff, R. S. & Lee, H. Reduced graphene oxide by chemical graphitization. Nat. Commun. 1, 73 (2010). \n17. Sutter, P. W., Flege, J. I. & Sutter, E. A. Epitaxial graphene on ruthenium. Nat. Mater. 7, 406–411 (2008). \n18. Meng, L. et al. Buckled silicene formation on Ir(111). Nano Lett. 13, 685–690 (2013). \n19. Liu, H., Du, Y. C., Deng, Y. X. & Ye, P. D. Semiconducting black phosphorus: synthesis, transport properties and electronic applications. Chem. Soc. Rev. 44, \n2732–2743 (2015). \n20. Coleman, J. N. et al. Two-dimensional nanosheets produced by liquid exfoliation of layered. Mater. Sci. 331, 568–571 (2011). \n21. Fan, X. B. et al. Fast and efficient preparation of exfoliated $2\\mathrm{H}\\ \\mathrm{MoS}_{2}$ nanosheets by sonication-assisted lithium intercalation and infrared laserinduced 1T to 2H phase reversion. Nano Lett. 15, 5956–5960 (2015). \n22. Desai, S. B. et al. Gold-mediated exfoliation of ultralarge optoelectronicallyperfect monolayers. Adv. Mater. 28, 4053–4058 (2016). \n23. Velicky, M. et al. Mechanism of gold-assisted exfoliation of centimeter-sized transition-metal dichalcogenide monolayers. ACS Nano 12, 10463–10472 (2018). \n24. Magda, G. Z. et al. Exfoliation of large-area transition metal chalcogenide single layers. Sci. Rep. 5, 14714 (2015). \n25. Zhang, Y. B., Tan, Y. W., Stormer, H. L. & Kim, P. Experimental observation of the quantum Hall effect and Berry’s phase in graphene. Nature 438, \n201–204 (2005). \n26. Novoselov, K. S. et al. Two-dimensional gas of massless Dirac fermions in graphene. Nature 438, 197–200 (2005). \n27. Cao, Y. et al. Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43–50 (2018). \n28. Hao, Y. F. et al. Oxygen-activated growth and bandgap tunability of large single-crystal bilayer graphene. Nat. Nanotechnol. 11, 426–431 (2016). \n29. Qiao, J. S., Kong, X. H., Hu, Z. X., Yang, F. & Ji, W. High-mobility transport anisotropy and linear dichroism in few-layer black phosphorus. Nat. Commun. 5, 4475 (2014). \n30. Hu, Z.-X., Kong, X., Qiao, J., Normand, B. & Ji, W. Interlayer electronic hybridization leads to exceptional thickness-dependent vibrational properties in few-layer black phosphorus. Nanoscale 8, 2740–2750 (2016). \n31. Qiao, J. et al. Few-layer Tellurium: one-dimensional-like layered elementary semiconductor with striking physical properties. Sci. Bull. 63, 159–168 (2018). \n32. Li, W. et al. Experimental realization of honeycomb borophene. Sci. Bull. 63, \n282–286 (2018). \n33. Deng, Y. et al. Gate-tunable room-temperature ferromagnetism in twodimensional $\\mathrm{Fe}_{3}\\mathrm{GeTe}_{2}$ . Nature 563, 94–99 (2018). \n34. Giovannetti, G. et al. Doping graphene with metal contacts. Phys. Rev. Lett. \n101, 026803 (2008). \n35. Li, H. et al. From bulk to monolayer $\\ensuremath{\\mathrm{MoS}}_{2}$ : evolution of Raman scattering. Adv. Funct. Mater. 22, 1385–1390 (2012). \n36. Mak, K. F., Lee, C., Hone, J., Shan, J. & Heinz, T. F. Atomically thin $\\mathbf{MoS}_{2}$ : a new Direct-gap semiconductor. Phys. Rev. Lett. 105, 136805 (2010). \n37. Du, X., Skachko, I., Barker, A. & Andrei, E. Y. Approaching ballistic transport in suspended graphene. Nat. Nanotechnol. 3, 491–495 (2008). \n38. Lee, C., Wei, X. D., Kysar, J. W. & Hone, J. Measurement of the elastic properties and intrinsic strength of monolayer graphene. Science 321, 385–388 (2008). \n39. Zhang, Y. et al. Electronic structure, surface doping, and optical response in epitaxial $\\mathrm{WSe}_{2}$ thin films. Nano Lett. 16, 2485–2491 (2016). \n40. Zhang, H. Y. et al. Resolving deep quantum-well states in atomically thin 2H$\\mathrm{MoTe}_{2}$ flakes by nanospot angle-resolved photoemission spectroscopy. Nano Lett. 18, 4664–4668 (2018). \n41. Frydendahl, C. et al. Optical reconfiguration and polarization control in semicontinuous gold films close to the percolation threshold. Nanoscale 9, \n12014–12024 (2017). \n42. Yoon, Y., Ganapathi, K. & Salahuddin, S. How good can monolayer $\\ensuremath{\\mathbf{MoS}}_{2}$ transistors be? Nano Lett. 11, 3768–3773 (2011). \n43. Liu, W., Sarkar, D., Kang, J. H., Cao, W. & Banerjee, K. Impact of contact on the operation and performance of back-gated monolayer $\\mathbf{MoS}_{2}$ field-effecttransistors. ACS Nano 9, 7904–7912 (2015). \n44. Kappera, R. et al. Phase-engineered low-resistance contacts for ultrathin $\\ensuremath{\\mathbf{MoS}}_{2}$ transistors. Nat. Mater. 13, 1128–1134 (2014). \n45. Zhan, C., Neal, J., Wu, J. & Jiang, D. E. Quantum effects on the capacitance of graphene-based electrodes. J. Phys. Chem. C. 119, 22297–22303 (2015). \n46. Fujimoto, T. & Awaga, K. Electric-double-layer field-effect transistors with ionic liquids. Phys. Chem. Chem. Phys. 15, 8983–9006 (2013). \n47. Ganatra, R. & Zhang, Q. Few-Layer $\\begin{array}{r}{\\mathbf{MoS}_{2};}\\end{array}$ a promising layered semiconductor. ACS Nano 8, 4074–4099 (2014). \n48. Qi, Y. P. et al. Superconductivity in Weyl semimetal candidate MoTe2. Nat. Commun. 7, 11038 (2016). \n49. Xi, X. et al. Ising pairing in superconducting $\\mathrm{Nb}{\\mathsf{S e}}_{2}$ atomic layers. Nat. Phys. \n12, 139–143 (2016). \n50. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n51. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n52. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n53. Klimes, J., Bowler, D. R. & Michaelides, A. Van der Waals density functionals applied to solids. Phys. Rev. B 83, 195131 (2011). \n54. Jain, A. et al. Minimizing residues and strain in 2D materials transferred from PDMS. Nanotechnology 29, 265203 (2018). \n55. Liu, G. D. et al. Development of a vacuum ultraviolet laser-based angleresolved photoemission system with a superhigh energy resolution better than \n1 meV. Rev. Sci. Instrum. 79, 023105 (2008). \n\n# Acknowledgements \n\nWe would like to thank Dr. Zhongming Wei, Xianjue Chen and Jia Wang for valuable discussions about XPS. This work is supported by the National Key Research and Development Program of China (Grant No. 2019YFA0308000, 2018YFA0305800, 2018YFE0202700, 2018YFA0704201), the Youth Innovation Promotion Association of CAS (2019007, 2018013, 2017013), the National Natural Science Foundation of China (Grant No. 11874405, 11622437, 61674171, 61725107, 61971035, and 11974422), the National Basic Research Program of China (Grant No. 2015CB921300), and the Strategic Priority Research Program (B) of the Chinese Academy of Sciences (Grant No. XDB25000000, XDB30000000), the Research Program of Beijing Academy of Quantum Information Sciences (Grant No. Y18G06). P.S. and E.S. acknowledge support by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award No. DESC0016343. Calculations were performed at the Physics Lab of High-Performance Computing of Renmin University of China and Shanghai Supercomputer Center. \n\n# Author contributions \n\nP.S., W.J., H.J.G., and X.J.Z. are equally responsible for supervising the discovery. Y.H. and R.Y. conceived the project. Y.H.P., J.P.H., and J.W. performed the DFT calculations. Y.H., H.L.L., and L.L. prepared all the mechanical exfoliation samples. Y.H. and R.Y. performed the Raman, PL and AFM measurements. M.H., J.W., P.S., and E.S. performed XPS measurement. Y.Q.C., G.D.L., L.Z., and W.J.Z. performed the ARPES measurement. Z.L.Z., P.C., K.H.W., L.M., Z.Z., L.W.L, and Y.L.W performed the STM and LEED measurement. Y.G.S. and Y.F.G. prepared bulk layered crystals. S.B.T., C.Z.G., Z.G.C., L. M.W. G.H.Y., and L.H.B. fabricated the transistors and performed the electrical measurements. Y.H., Y.H.P., R.Y., J.P.H., P.S., and W.J. analyzed data, wrote the manuscript and all authors discussed and commented on it. \n\n# Competing interests \n\nThe authors declare the following competing interests that three Chinese patents were filed (201910529797.7; 201910529796.2; 201910529623.0) by the Institute of Physics, Chinese Academy of Sciences, along with their researchers (Y.H., H.L.L., and X.J.Z). \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-16266-w. \n\nCorrespondence and requests for materials should be addressed to P.S., W.J., X.-J.Z. or H.-J.G. \n\nPeer review information Nature Communications thanks Peter Bøggild, Kai-Qiang Lin, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer review reports are available. \n\n# Reprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1126_science.aaz3985", + "DOI": "10.1126/science.aaz3985", + "DOI Link": "http://dx.doi.org/10.1126/science.aaz3985", + "Relative Dir Path": "mds/10.1126_science.aaz3985", + "Article Title": "Subwavelength dielectric resonators for nonlinear nullophotonics", + "Authors": "Koshelev, K; Kruk, S; Melik-Gaykazyan, E; Choi, JH; Bogdanov, A; Park, HG; Kivshar, Y", + "Source Title": "SCIENCE", + "Abstract": "Subwavelength optical resonators made of high-index dielectric materials provide efficient ways to manipulate light at the nulloscale through mode interferences and enhancement of both electric and magnetic fields. Such Mie-resonullt dielectric structures have low absorption, and their functionalities are limited predominulltly by radiative losses. We implement a new physical mechanism for suppressing radiative losses of individual nulloscale resonators to engineer special modes with high quality factors. optical bound states in the continuum (BICs). We demonstrate that an individual subwavelength dielectric resonator hosting a BIC mode can boost nonlinear effects increasing second-harmonic generation efficiency. Our work suggests a route to use subwavelength high-index dielectric resonators for a strong enhancement of light-matter interactions with applications to nonlinear optics, nulloscale lasers, quantum photonics, and sensors.", + "Times Cited, WoS Core": 697, + "Times Cited, All Databases": 744, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000509802700037", + "Markdown": "# OPTICS \n\n# Subwavelength dielectric resonators for nonlinear nanophotonics \n\nKirill Koshelev1,2, Sergey Kruk1, Elizaveta Melik-Gaykazyan1,3, Jae-Hyuck Choi4, Andrey Bogdanov2, Hong-Gyu Park4\\*, Yuri Kivshar1,2\\* \n\nSubwavelength optical resonators made of high-index dielectric materials provide efficient ways to manipulate light at the nanoscale through mode interferences and enhancement of both electric and magnetic fields. Such Mie-resonant dielectric structures have low absorption, and their functionalities are limited predominantly by radiative losses. We implement a new physical mechanism for suppressing radiative losses of individual nanoscale resonators to engineer special modes with high quality factors: optical bound states in the continuum (BICs). We demonstrate that an individual subwavelength dielectric resonator hosting a BIC mode can boost nonlinear effects increasing second-harmonic generation efficiency. Our work suggests a route to use subwavelength high-index dielectric resonators for a strong enhancement of light–matter interactions with applications to nonlinear optics, nanoscale lasers, quantum photonics, and sensors. \n\nigh-index resonant dielectric nanostructures emerged recently as a new platform for nano-optics and photonics ■ to complement plasmonic structures in a range of functionalities $(\\boldsymbol{I},\\boldsymbol{2})$ . Alldielectric nanoresonators benefit from low material losses and allow the engineering of artificial magnetic responses. Progress in alldielectric nanophotonics led to the development of efficient flat-optics devices that reached and even outperformed the capabilities of conventional bulk components (3). These advances motivated further diversification of applications of dielectric nanostructures (4), especially toward nonlinear optics (5–7). Efficiencies of nonlinear optical processes in all-dielectric nanostructures have exceeded by several orders of magnitude the efficiencies demonstrated in metallic nanoparticles with plasmonic resonances (8, 9). \n\nOne of the main limiting factors for high efficiencies of all-dielectric nanostructures as functional devices is the quality $\\mathbf{\\Psi}(\\mathbf{Q})$ factor of their resonant modes. Traditionally, response of dielectric nanoparticles is governed by loworder geometrical resonances, resulting in low Q factors. An elegant solution for Q-factor control and its increase is provided by the physics of bound states in the continuum (BICs). BICs were first proposed in quantum mechanics as localized electron waves with the energies embedded within the continuous spectrum of propagating waves (10). Recently, BICs have attracted considerable attention in photonics $(l l,l2)$ . Mathematical bound states have infinitely large $\\mathbf{Q}$ factors and vanishing resonant linewidth. In practice, BICs are limited by a finite sample size, material absorption, and structural imperfections (13), but they manifest themselves as resonant states with large $\\mathbf{Q}$ factors, also known as quasi-BICs or supercavity modes. Until now, optical BICs have been observed only for extended systems (12, 14–16) and used for various applications including lasing $(I7)$ and sensing (18). For individual isolated dielectric resonators, genuine nonradiative states require extreme material parameters diverging toward infinity or zero (19, 20). In realistic individual resonators, there are an infinite number of possible paths for radiation to escape (12), which limits the $\\mathbf{Q}$ factor substantially. However, the concept of quasi-BICs allows us to come close to reaching nonradiative states for individual dielectric resonators (21–23). The modes forming a quasiBIC belong to the same resonator, which allows the system footprint to be kept very small. Except for specific composite structures (24), such a small footprint is challenging to achieve for resonators relying on alternative mechanisms of localization, including whispering gallery mode resonators and cavities in photonic bandgap structures. \n\nHere, we studied individual dielectric nanoresonators hosting a quasi-BIC resonance at telecommunication wavelengths and demonstrated its capability for second-harmonic generation (SHG). Our subwavelength resonator exploits mutual interference of several Mie modes, which results in a quasi-BIC regime. We designed a 635-nm-tall nonlinear nanoresonator of cylindrical shape made of AlGaAs (aluminum gallium arsenide) placed on an engineered three-layer substrate $\\mathrm{(SiO_{2}/I T O/}$ $\\mathrm{{SiO}_{2})}$ ) (Fig. 1A). For a cylindrical particle, Mie resonances are classified with an azimuthal order and can be loosely sorted into two groups distinguished by the number of oscillations in the radial and axial directions [see part 1 of the supplementary text (25)]. We selected a pair of modes from different groups with uniform azimuthal field distribution (Fig. 1B), both of which demonstrated a magnetic dipolar behavior [see parts 1 and 2 of the supplementary text (25)]. By changing the resonator’s diameter, the spectral mismatch of dipolar modes can be decreased, which induces their strong coupling in the parametric space and produces the characteristic avoided resonance crossing of frequency curves (Fig. 1C). In the strong coupling regime, the modes are hybrid with a combination of radial or axial oscillations and thus do not belong to any of the defined groups [see part 1 of the supplementary text (25)]. Open boundaries of the nanoresonator enable constructive and destructive mode interference in the far field $\\left(26\\right)$ , which results in modification of the mode Q factors because of their identical dipolar nature (Fig. 1D). The quasi-BIC regime with suppressed dipolar radiation (Fig. 1E) and thus an increased $\\mathbf{Q}$ factor is reached for a particle of a specific diameter of ${\\sim}930\\ \\mathrm{nm}$ . \n\nWe further compensated for the decrease of the $\\mathbf{Q}$ factor induced by energy leakage into the substrate (27) by adding a layer of ITO (indium tin oxide) exhibiting an epsilon-nearzero transition acting as a conductor above a $1200\\mathrm{-nm}$ wavelength (e.g., at the quasi-BIC wavelength) and as an insulator below this wavelength [e.g., at the second harmonic (SH) wavelength]. The ITO layer is separated from the resonator by a $\\mathrm{SiO_{2}}$ spacer. The thickness of the $\\mathrm{SiO_{2}}$ spacer layer provides control over the phase of reflection, further enhancing the destructive interference of the two magnetic dipoles in the far field and thus increasing the Q factor (Fig. 1F). For the optimal spacer thickness between 300 and $400~\\mathrm{{nm}}$ , the $\\mathbf{Q}$ factor reaches the maximal predicted value of 235. \n\nWe fabricated a set of individual AlGaAs nanoresonators with diameters varying from 890 to ${980}\\mathrm{nm}$ from epitaxially grown AlGaAs (crystal axes orientation [100], $20\\%$ Al) by means of electron-beam lithography and a dry-etching process. The nanoparticles were subsequently transferred to a substrate made of a commercial film of ${300}{\\cdot}\\mathrm{nm}$ ITO on glass with an added $\\mathrm{SiO_{2}}$ spacer $350–\\mathrm{nm}$ thick [see materials and methods and part 7 of the supplementary text (25)]. We measured scattering spectra from individual nanoparticles with a laser tunable within the wavelength range of 1500 to $1700\\ \\mathrm{nm}$ . To maximize light coupling to the quasi-BIC mode, we illuminated each nanoresonator with a tightly focused, azimuthally polarized light [see the materials and methods and part 8 of the supplementary text (25)]. The scattering spectra are evaluated as the difference between the bare substrate reflectivity and the normalized measured backward scattering of the nanoresonator. We observed a symmetric peak with the extracted $\\mathbf{Q}$ factor of $188\\pm5$ for the particle diameter of ${\\sim}930\\mathrm{nm}$ , which corresponds to the quasiBIC condition [see Fig. 1G and the materials and methods (25) for details on the Q-factor extraction procedure]. We further measured the dependence of the $\\mathbf{Q}$ factor on the nanoresonator diameter (dots in Fig. 1D), which showed good agreement with numerical simulations. \n\nNext, we exploited the designed quasi-BIC resonator as a nonlinear nanoantenna for SH generation (Fig. 2A). At the SH wavelength, the nanoresonator supports a high-order Mie mode with a $\\mathbf{Q}$ factor of 65 [see part 1 of the supplementary text (25)]. For SH wavelengths, the material properties of ITO are similar to glass, so the spacer and ITO thickness are inessential. To increase the nonlinear conversion efficiency, we developed the consistent theory of SHG for nanoscale resonators using the eigenmode expansion method [see parts 4 and 5 of the supplementary text (25)], which goes beyond the phase-matching approach used for nonlinear optics of macroscopic structures (28). \n\nThe optical response of designed nonlinear nanoantenna is driven by the quasi-BIC with complex frequency $\\omega_{1}-i\\gamma_{1}$ and the SH Mie mode with frequency $\\mathrm{{\\omega}_{2}-\\mathrm{{\\dot{\\tau}}\\gamma_{2}}}$ . The total SH power radiated by the nanoresonator [see part 5 of the supplementary text (25)] is: \n\n$$\nP^{2\\infty}=\\propto\\kappa_{2}Q_{2}L_{2}\\kappa_{12}\\left[Q_{1}L_{1}\\kappa_{1}P^{\\infty}\\right]^{2}\n$$ \n\nThis expression allows a step-by-step explanation of the SHG process (Fig. 2B). The incident power $P^{\\omega}$ is coupled to the quasi-BIC depending on the spatial overlap $\\upkappa_{1}$ between the pump and the mode. The coupled power is resonantly enhanced depending on the quasi-BIC $\\mathbf{Q}$ factor $Q_{1}$ and damped by the spectral overlap factor $L_{1}(\\mathfrak{w})=\\gamma_{1}^{2}/\\left[\\left(\\mathfrak{w}-\\mathfrak{w}_{1}\\right)^{2}+\\right.$ $\\gamma_{1}^{2}]$ , which is the unity at the resonance. The efficiency of upconversion of the total accumulated power is determined by the crosscoupling coefficient $\\kappa_{12},$ which depends on the symmetry of the nonlinear susceptibility tensor of AlGaAs and the spatial overlap between the generated nonlinear polarization current and SH mode [see part 5 of the supplementary text (25)]. The converted SH power is increased by a high $\\mathbf{Q}$ factor of the SH mode but at the same time is decreased because of the spectral mismatch with the quasi-BIC, $L_{2}\\left(2\\upomega_{1}\\right)=\\upgamma_{2}^{2}/\\left[\\left(2\\upomega_{1}-\\upomega_{2}\\right)^{2}+\\upgamma_{2}^{2}\\right]$ . The outcoupling factor $\\upkappa_{2}(2\\upomega)$ determines a fraction of the radiated SH power and is the unity in spacer. (E) Simulated far-field patterns of the high-Q mode for disks of different diameters shown schematically. For calculations, $|\\pmb{\\mathsf{E}}|^{2}$ is normalized to the full mode energy. (F) Calculated Q factor of the quasi-BIC versus $\\mathsf{S i O}_{2}$ spacer thickness compared with the Q factors of a nanoresonator in air and on a bulk $\\mathsf{S i O}_{2}$ substrate (dashed lines). (G) Measured scattering spectrum and retrieved Q factor of the observed resonance for a disk with a diameter of ${\\sim}930~\\mathsf{n m}$ . \n\n![](images/c49070e778839baca56fd47de812d29abc7080519b696671a1d614929faeb960.jpg) \nFig. 1. Optical quasi-BIC mode in an individual dielectric nanoresonator. (A) Scanning electron micrograph (top) and schematic (bottom) of an individual dielectric nanoresonator. (B) Simulated near-field patterns of the two modes for different diameters. (C) Calculated mode wavelengths versus resonator diameter. (D) Calculated (lines) and measured (dots) Q factors of modes versus resonator diameter. Calculations in (C) and (D) are done for a 350-nm $\\mathsf{S i O}_{2}$ \n\n![](images/1b2be43b6ee2feee87326a7654fc50136b0364ac62d00bf1e33c1471d59f1164.jpg) \nFig. 2. Second-harmonic generation with a dielectric nanoantenna. (A) Diagram of the SHG in a nanoresonator under azimuthally polarized vector beam excitation. (B) Schematic of the SHG process in a nonlinear dielectric nanoantenna. Each term of the formula describes one step of the process. (C) Percentage of pump power coupled to the quasi-BIC for different polarizations of pump depending on the ratio between the beam waist radius $w_{0}$ and the pump wavelength. The calculation is \n\ndone for a free-standing nanoresonator in air. The diffraction limit is 0.61. (D) Spectral overlap $L_{2}(2\\omega_{\\mathrm{1}})$ between the high-Q mode at the pump frequency and the high-order Mie mode at the SH frequency versus the disk diameter. The inset shows the near-field profiles of both modes. (E) Experimental ellipsometry data for the permittivity of the ITO layer. Wavelength ranges of the excitation and collection are marked with red and blue shading, respectively. \n\nthe vicinity of ${\\mathfrak{o}}_{2}$ . The exact expressions for coupling coefficients $\\upkappa_{1},\\upkappa_{12},$ and $\\upkappa_{2}$ and the constant $\\mathbf{\\alpha}_{\\mathrm{~d~}}$ are given in part 5 of the supplementary text (25). Note that the effective mode volume does not appear in Eq. 1 because $\\upkappa_{12}$ takes into account the explicit spatial distributions of the electric field of the modes. \n\nWith this theoretical analysis, we can specify the optimal conditions to maximize the SHG efficiency from an individual dielectric nanoresonator. First, the spatial profile of the pump must be structured to match the distribution of the excited mode; therefore, we used the cylindrical vector beam with azimuthal polarization. We estimated $\\upkappa_{1}$ as $33\\%$ for the experimental conditions using a model of a free-standing resonator in air (Fig. 2C) [see parts 5 and 10 of the supplementary text (25)]. Next, the optimal structure must be resonant simultaneously at pump and SH wavelengths $(9)$ . Maximization of $Q_{1}$ is critical compared with maximization of $Q_{2}$ because of the quadratic over linear dependence of $P^{2\\infty}$ [see Eq. (1) and part 6 of the supplementary text (25)]. For the designed nanoresonator with a diameter of ${\\sim}930\\mathrm{nm}$ , the factor of spectral overlap reaches $50\\%$ (Fig. 2D). Finally, the collection efficiency must be increased, which can be achieved by engineering the substrate properties. The epsilon-near-zero transition of ITO makes it effectively “invisible” to the SH radiation, allowing it to propagate in both the forward and backward directions (Fig. 2E). \n\nTo perform systematic experimental analysis of the SHG enhancement in quasi-BIC resonators, we excited the fabricated set of nanoparticles with laser pulses of 2-ps duration in the wavelength range from 1500 to $1700\\mathrm{nm}$ [see the materials and methods and part 9 of the supplementary text (25)]. Figure 3, A to D, shows the maps of the SHG intensity versus the pump wavelength and resonator diameter for the nanoresonators pumped by the azimuthal, radial, and linearly polarized beams, respectively. The experimental data reveal a sharp enhancement of the nonlinear signal in the quasi-BIC regime selectively for the azimuthally polarized pump. We measured directionality diagrams of the SH signal in the backward and forward directions within the numerical apertures of a pair of confocal objective lenses [see Fig. 3, E and F, and part 12 of the supplementary text (25)]. The diagram in the backward direction features distinct maxima in four directions that are qualitatively similar to the theoretical SHG directionality shown in Fig. 2A and the far-field pattern of the mode excited at the SH wavelength [see part 1 of the supplementary text (25)]. Figure 4, A and B, shows a wavelength cut (at the quasi-BIC diameter of ${\\sim}930\\mathrm{nm}$ ) and a size cut (at the quasi-BIC wavelength of $1570\\mathrm{nm}$ ) of the measured 2D SHG maps (see Fig. 3, B to D). Both plots demonstrate that the observed SH intensity for the azimuthal pump surpasses the SH intensity for the other polarizations by several orders of magnitude, which confirms high spatial selectivity of the quasiBIC [see also part 3 of the supplementary text (25)]. With these experiments, we reached beyond the predictions of the theoretical model (see Fig. 2C) and measured an observable SH signal for radial and linear polarizations caused by off-resonant excitation of other nanoparticle modes (Fig. 4B). However, this signal remains several orders of magnitude lower compared with azimuthal polarization. We further experimentally measured the SHG conversion efficiency. The numerical analysis of quasi-BICs in a nonlinear nanoresonator [see Fig. 2 and (23)] does not account for the trade-off between pulse duration and laser damage threshold. The high $\\mathbf{Q}$ factor of the quasi-BIC requires relatively long pulses to pump the mode effectively. At the same time, a peak power of longer pulses becomes limited by the material laser damage threshold. From this point of view, theoretical or numerical analysis does not answer the question of whether a nanoresonator made of common dielectric materials can indeed function as an efficient nonlinear nanoantenna. \n\nWe conducted an experimental verification of this by detecting the peak pump power $P_{p}^{\\omega}$ incident onto the sample and the peak SH power $P_{p}^{2\\omega}$ captured by the two objective lenses in the forward and backward directions (Fig. 4C). The directly measured conversion efficiency ${\\cdot}P_{p}^{2\\infty}/(P_{p}^{\\infty})^{2}$ was $1.3\\times10^{-6}\\mathrm{W}^{-1}$ [see part 11 of the supplementary text (25)]. The observed SHG efficiency at the quasi-BIC was more than two orders of magnitude higher than that demonstrated with earlier implementations using other approaches $(5-7,9)$ . We further estimate the total SHG efficiency as $4.8\\times10^{-5}$ $\\mathbf{W}^{-1}$ using the common approach by taking into account only the coupled part of $P_{p}^{\\omega}$ , theoretically estimated as $33\\%$ , and the total SH power, estimated using the calculated collection efficiency of $24\\%$ . A detailed list of the experimental parameters and an elaborated comparison with the earlier results for individual nanoresonators is presented in part 13 of the supplementary text (25). The SHG efficiency of an individual nanoantenna demonstrated here is qualitatively comparable to the best-to-date efficiencies of nonlinear metasurfaces (29, 30) based on hybrid multiplequantum-well structures, whereas a quantitative comparison cannot be done without some ambiguity. Although high nonlinear coefficients $P_{p}^{2\\infty}/(P_{p}^{\\infty})^{2}$ were demonstrated in such systems in the far- to mid-infrared spectral ranges, the reported conversion efficiencies $P_{p}^{\\mathrm{2\\infty}}/P_{p}^{\\mathrm{\\infty}}$ of $2\\times{10}^{-4}\\%$ (29) and $7.5\\times10^{-2}\\%$ (30), respectively, remain low and are limited by a peak pump power of $100~\\mathrm{{mW}}$ that they can sustain, compared with $10\\mathrm{W}$ for our nanoresonator. \n\n![](images/104e749d4311095d749fcd50b541a2bab04660f21874871045a0681048a2571b.jpg) \nFig. 3. Experimental characterization of the SHG enhancement. (A) 3D map of SH intensity measured as a function of the pump wavelength and particle diameter for an azimuthally polarized beam. The SH intensity is normalized on the square of the pump power. (B to D) Top views of the maps of SHG with the azimuthal, radial, and linear pump, respectively. (E and F) Experimentally measured directionality diagrams of SHG for a nanoresonator with a diameter of ${\\sim}930~\\mathsf{n m}$ in the (E) backward and (F) forward direction. \n\n![](images/3165a6e6d02857bf27ff0b25d6afbbf70486d7a1b8847fd2adab2bc6daacc237.jpg) \nFig. 4. Experimental nonlinear conversion efficiency. (A and B) Measured SH intensity as a function of the pump wavelength for the nanoresonator with the diameter of ${\\sim}930~\\mathsf{n m}$ (A) and as a function of the nanoresonator diameter at a $1570-\\mathsf{n m}$ pump wavelength (B) for different pump polarizations. The SH intensity is normalized on the square of the pump power. (C) Measured peak SH power versus the peak pump power for a nanoresonator with a diameter of ${\\sim}930~\\mathsf{n m}$ $\\mathrm{\\Delta}\\log_{10}\\mathrm{~-~}\\log_{10}$ scale). Line shows the fit with a quadratic dependence with the nonlinear conversion coefficient $1.3\\times10^{-6}\\mathsf{W}^{-1}$ . \n\nOur results illustrate, for the first time to our knowledge, manifestation of high Q-factor optical modes in individual nanoresonators in the linear and nonlinear regimes governed by the physics of bound states in the continuum. \n\nOur experiments demonstrate that quasi-BIC engineering for individual nanoparticles in the optical frequency range is feasible despite fabrication tolerances and material absorption. Individual high- $\\mathbf{\\nabla}\\cdot\\mathbf{Q}$ nanoresonators with a subwavelength footprint promise specific applications as nonlinear nanoantennas, lowthreshold nanolasers, and compact quantum sources. \n\n# REFERENCES AND NOTES \n\n1. A. I. Kuznetsov, A. E. Miroshnichenko, M. L. Brongersma, Y. S. Kivshar, B. Luk’yanchuk, Science 354, aag2472 (2016). \n2. A. Arbabi, Y. Horie, M. Bagheri, A. Faraon, Nat. Nanotechnol. 10, 937–943 (2015). \n3. D. Lin, P. Fan, E. Hasman, M. L. Brongersma, Science 345, 298–302 (2014). \n4. S. Kruk, Y. Kivshar, ACS Photonics 4, 2638–2649 (2017). \n5. S. S. Kruk et al., Nano Lett. 17, 3914–3918 (2017). \n6. V. F. Gili et al., Opt. Express 24, 15965–15971 (2016). \n7. J. Cambiasso et al., Nano Lett. 17, 1219–1225 (2017). \n8. J. Butet, P. F. Brevet, O. J. Martin, ACS Nano 9, 10545–10562 (2015). \n9. M. Celebrano et al., Nat. Nanotechnol. 10, 412–417 (2015). \n10. J. von Neumann, E. Wigner, Phys. Z. 30, 465 (1929). \n\n11. D. C. Marinica, A. G. Borisov, S. V. Shabanov, Phys. Rev. Lett \n100, 183902 (2008). \n12. C. W. Hsu, B. Zhen, A. D. Stone, J. D. Joannopoulos, \nM. Soljačić, Nat. Rev. Mater. 1, 16048 (2016). \n13. Z. F. Sadrieva et al., ACS Photonics 4, 723–727 (2017). \n14. Y. Plotnik et al., Phys. Rev. Lett. 107, 183901 (2011). \n15. C. W. Hsu et al., Nature 499, 188–191 (2013). \n16. K. Koshelev, Y. Kivshar, Nature 574, 491–492 (2019). \n17. A. Kodigala et al., Nature 541, 196–199 (2017). \n18. A. Tittl et al., Science 360, 1105–1109 (2018). \n19. F. Monticone, A. Alù, Phys. Rev. Lett. 112, 213903 (2014). \n20. M. G. Silveirinha, Phys. Rev. A 89, 023813 (2014). \n21. M. V. Rybin et al., Phys. Rev. Lett. 119, 243901 (2017). \n22. A. A. Bogdanov et al., Adv. Photonics 1, 016001 (2019). \n23. L. Carletti, K. Koshelev, C. De Angelis, Y. Kivshar, Phys. Rev. \nLett. 121, 033903 (2018). \n24. M. P. Nezhad et al., Nat. Photonics 4, 395–399 (2010). \n25. See supplementary materials. \n26. J. Wiersig, Phys. Rev. Lett. 97, 253901 (2006). \n27. J. van de Groep, A. Polman, Opt. Express 21, 26285–26302 \n(2013). \n28. J. A. Armstrong, N. Bloembergen, J. Ducuing, P. S. Pershan, \nPhys. Rev. 127, 1918–1939 (1962). \n29. J. Lee et al., Nature 511, 65–69 (2014). \n30. J. Lee et al., Adv. Opt. Mater. 4, 664–670 (2016). \n\n# ACKNOWLEDGMENTS \n\nWe thank K. Ladutenko, B. Luther-Davies, D. Smirnova, and L. Wang for their valuable inputs into this project at various stages of its development. Funding: This work was supported by the Australian Research Council, the Strategic Fund of the Australian National University, the National Research Foundation of Korea (NRF) under grant no. 2018R1A3A3000666 funded by the Korean Government (MSIT), and the Russian Science Foundation under grant no. 18-72-10140. K.K. and A.B. acknowledge support from the Foundation for the Advancement of Theoretical Physics and Mathematics “BASIS.” Author contributions: K.K., S.K., and Y.K. conceived the research; K.K. and A.B. performed theoretical analysis, numerical simulations, and data analysis; J.-H.C. and H.-G.P. fabricated the samples; S.K. and E.M.-G. conducted experimental studies; K.K., S.K., and Y.K. wrote the manuscript based on input from all authors. Competing interests: The authors declare no competing interests. Data and materials availability: All data needed to evaluate the conclusions in this paper are available in the main text or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/367/6475/288/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S15 \nTable S1 \nReferences (31–43) \n\n5 September 2019; accepted 27 November 2019 \n10.1126/science.aaz3985 \n\n# Science \n\n# Subwavelength dielectric resonators for nonlinear nanophotonics \n\nKirill Koshelev, Sergey Kruk, Elizaveta Melik-Gaykazyan, Jae-Hyuck Choi, Andrey Bogdanov, Hong-Gyu Park and Yuri Kivshar \n\nScience 367 (6475), 288-292. DOI: 10.1126/science.aaz3985 \n\n# Enhancing optical nonlinearity \n\nIntense pulses of light interacting with a dielectric material can induce optical nonlinear behavior, whereby the frequency of the output light can be doubled or tripled or excited to even higher harmonics of the input light. Usually this interaction is weak and occurs over many thousands of wavelengths, typically requiring the combination of bulk volumes of material with a confining cavity. Using a mechanism of light confinement called bound states in the continuum, Koshelev et al. show that enhanced second-harmonic generation can be obtained in nanoscale subwavelength cylinders of a dielectric material. The results on these optical nanoantennas offer a platform for developing integrated nonlinear nanophotonic devices. \n\nScience, this issue p. 288 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_science.abb8985", + "DOI": "10.1126/science.abb8985", + "DOI Link": "http://dx.doi.org/10.1126/science.abb8985", + "Relative Dir Path": "mds/10.1126_science.abb8985", + "Article Title": "Vapor-assisted deposition of highly efficient, stable black-phase FAPbI3 perovskite solar cells", + "Authors": "Lu, HZ; Liu, YH; Ahlawat, P; Mishra, A; Tress, WR; Eickemeyer, FT; Yang, YG; Fu, F; Wang, ZW; Avalos, CE; Carlsen, BI; Agarwalla, A; Zhang, X; Li, XG; Zhan, YQ; Zakeeruddin, SM; Emsley, L; Rothlisberger, U; Zheng, LR; Hagfeldt, A; Grätzel, M", + "Source Title": "SCIENCE", + "Abstract": "Mixtures of cations or halides with FAPbI(3) (where FA is formamidinium) lead to high efficiency in perovskite solar cells (PSCs) but also to blue-shifted absorption and long-term stability issues caused by loss of volatile methylammonium (MA) and phase segregation. We report a deposition method using MA thiocyanate (MASCN) or FASCN vapor treatment to convert yellow delta-FAPbI(3) perovskite films to the desired pure alpha-phase. NMR quantifies MA incorporation into the framework. Molecular dynamics simulations show that SCN- anions promote the formation and stabilization of alpha-FAPbI(3) below the thermodynamic phase-transition temperature. We used these low-defect-density alpha-FAPbI(3) films to make PSCs with >23% power-conversion efficiency and long-term operational and thermal stability, as well as a low (330 millivolts) open-circuit voltage loss and a low (0.75 volt) turn-on voltage of electroluminescence.", + "Times Cited, WoS Core": 636, + "Times Cited, All Databases": 660, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000579169000046", + "Markdown": "# SOLAR CELLS Vapor-assisted deposition of highly efficient, stable black-phase FAPbI3 perovskite solar cells \n\nHaizhou Lu, Yuhang Liu, Paramvir Ahlawat, Aditya Mishra, Wolfgang R. Tress, Felix T. Eickemeyer, Yingguo Yang, Fan Fu, Zaiwei Wang, Claudia E. Avalos, Brian I. Carlsen, Anand Agarwalla, Xin Zhang, Xiaoguo Li, Yiqiang Zhan\\*, Shaik M. Zakeeruddin, Lyndon Emsley, Ursula Rothlisberger, Lirong Zheng\\*, Anders Hagfeldt\\*, Michael Grätzel\\* \n\nINTRODUCTION: Metal halide perovskite solar cells (PSCs) have reached a power-conversion efficiency (PCE) of $25.2\\%$ , thus exceeding other thin-film solar cells. $\\mathrm{FAPbI_{3}}$ (where FA is formamidinium) has been shown to be an ideal candidate for efficient, stable PSCs. Obtaining highly crystalline, stable, and pure $\\mathbf{\\alpha}_{\\mathrm{~\\mathfrak~{~d~}~}}$ -phase $\\mathrm{FAPbI_{3}}$ films has been of vital importance. However, $\\mathrm{FAPbI_{3}}$ undergoes a phase transition from the black $\\mathfrak{a}$ -phase to the photoinactive d-phase below $150^{\\circ}\\mathrm{C}.$ Previous approaches to overcoming this problem include mixing it with MA, Cs or Br ions. Here, we report a deposition method using methylammonium thiocyanate (MASCN) vapor treatment to convert ${\\delta\\mathrm{{-FAPbI}_{3}}}$ to the desired pure $\\upalpha$ -phase below the thermodynamic phase-transition temperature. Molecular dynamics (MD) simulations show that the $\\operatorname{scy}$ anions promote the formation and stabilization of $\\mathrm{\\mathbf{q}{\\mathrm{-FAPbI}}_{3}}$ . These vapor-treated $\\mathrm{FAPbI_{3}}$ PSCs exhibit outstanding photovoltaic and electroluminescent performance. \n\n![](images/32c8cd05d9c2a0487f8573d5fb186624fdf5de2623bab19c32b83b2b47a932a5.jpg) \nStable and phase pure MASCN vapor-treated $\\mathsf{F A P b l}_{3}$ films. Vapor-treated $\\mathsf{F A P b l}_{3}$ films were annealed at $85^{\\circ}\\mathrm{C}$ for 500 hours in an ${\\sf N}_{2}$ environment. \n\nRATIONALE: Although the phase transition from d- to $\\mathfrak{a}$ -phase $\\mathrm{FAPbI_{3}}$ requires a high temperature, the treatment of d-phase $\\mathrm{FAPbI_{3}}$ films with MASCN vapor allows the conversion to occur at temperatures below $\\mathrm{150^{\\circ}C}.$ MD simulations show that $\\operatorname{scN}^{-}$ ions preferentially adsorb on the surface of ${\\delta\\mathrm{-}\\mathrm{FAPbI_{3}}}$ to replace iodide ions that are bound to $\\mathrm{Pb^{2+}}$ . This process disintegrates the top layer of face-sharing octahedra and induces the transition to the corner-sharing architecture of $\\mathrm{\\Phi_{\\mathrm{{\\mathbf{\\mathrm{{ch}}}A P b I_{3}}}}}$ . Once the corner-sharing $\\mathbf{\\alpha}\\propto$ -form is formed on the top surface, this layer templates the progression of the phase transition from d- to $\\mathrm{\\Phi_{\\mathrm{{\\mathbf{a}}-\\mathrm{{FAPbI}_{3}}}}}$ toward the bulk. Once the pure $\\mathbf{\\mathrm{\\mathbf{q}}{\\mathrm{-FAPbI}}_{3}}$ is formed, its back conversion to the d-phase is prevented by a high energy barrier. \n\nRESULTS: We show a complete conversion from d- to $\\mathbf{\\mathrm{\\mathbf{\\mathrm{q}}\\mathrm{-FAPbI_{3}}}}$ at $100^{\\circ}\\mathrm{C}$ using the MASCN vapor treatment method. This phase transition can also be achieved using FASCN vapor. The vaportreated $\\mathrm{FAPbI_{3}}$ film remained in its pure black phase even after 500 hours of annealing at $85^{\\circ}\\mathrm{C},$ whereas the reference $\\mathrm{FAPbI_{3}}$ film formed mainly $\\mathrm{PbI_{2}}$ during the heat exposure. X-ray diffraction data showed an improved crystallinity and preferred orientation of the $\\mathrm{FAPbI_{3}}$ films after vapor treatment. One- and two-dimensional NMR experiments were used to probe changes in symmetry and quantify the incorporation of MA into the perovskite framework. Time-of-flight secondary ion mass spectrometry measurements confirmed that the MASCN content was mostly located near the surface region of the $\\mathrm{FAPbI_{3}}$ films. We used these low-defect-density $\\mathbf{\\mathrm{\\mathbf{q}}{\\mathrm{-FAPbI}}_{3}}$ films to make PSCs with $>23\\%$ PCE, long-term operational stability, low $(330\\mathrm{mV},$ open-circuit voltage $(V_{\\mathrm{oc}})$ loss, and low (0.75 V) turn-on voltage of electroluminescence. \n\nCONCLUSION: SCN– anions play a key role in promoting the formation and stabilization of $\\mathrm{\\mathbf{\\mathrm{q}{-}F A P b I_{3}}}$ . Vapor-treated $\\mathrm{FAPbI_{3}}$ films showed long-term thermal stability. MD simulations showed that the pure $\\mathrm{\\mathbf{a}{\\mathrm{-FAPbI}}_{3}}$ remained kinetically stable. These findings are important for developing stable and pure black-phase $\\mathrm{FAPbI_{3}}$ -based PSCs. Our vapor-treated $\\mathrm{FAPbI_{3}}$ PSCs showed high efficiency and good longterm stability under maximum power point tracking conditions. Because of its high $V_{\\mathrm{{oc}}}$ and high external quantum efficiency electroluminescence yield, pure $\\mathbf{\\mathrm{\\mathbf{d}}\\mathrm{-\\mathbf{F}A P b I_{3}}}$ will be useful for other applications such as light-emitting diodes and photodetectors.▪ \n\n# SOLAR CELLS Vapor-assisted deposition of highly efficient, stable black-phase FAPbI3 perovskite solar cells \n\nHaizhou ${\\mathbf{{L}}}{\\mathbf{u}}^{1,2}$ , Yuhang Liu2, Paramvir Ahlawat3, Aditya Mishra4, Wolfgang R. Tress1, Felix T. Eickemeyer2, Yingguo Yang5, Fan $\\mathsf{F u}^{6}$ , Zaiwei Wang1, Claudia E. Avalos4, Brian I. Carlsen1, Anand Agarwalla1, Xin Zhang7, Xiaoguo Li7, Yiqiang $Z h a n^{7*}$ , Shaik M. Zakeeruddin2, Lyndon Emsley4, Ursula Rothlisberger3, Lirong Zheng7\\*, Anders Hagfeldt1\\*, Michael Grätzel2\\* \n\nMixtures of cations or halides with $\\mathsf{F A P b l}_{3}$ (where FA is formamidinium) lead to high efficiency in perovskite solar cells (PSCs) but also to blue-shifted absorption and long-term stability issues caused by loss of volatile methylammonium (MA) and phase segregation. We report a deposition method using MA thiocyanate (MASCN) or FASCN vapor treatment to convert yellow $\\delta\\mathrm{-}\\mathsf{F A P b l}_{3}$ perovskite films to the desired pure $\\mathbf{a}$ -phase. NMR quantifies MA incorporation into the framework. Molecular dynamics simulations show that SCN– anions promote the formation and stabilization of $\\mathbf{\\Pi}_{\\mathbf{a}-\\mathsf{F A P b l}_{3}}$ below the thermodynamic phase-transition temperature. We used these low-defect-density $\\mathbf{a-FAPbl}_{3}$ films to make PSCs with $>23\\%$ power-conversion efficiency and long-term operational and thermal stability, as well as a low (330 millivolts) open-circuit voltage loss and a low (0.75 volt) turn-on voltage of electroluminescence. \n\netal halide perovskites are being widely investigated for many applications, including solar cells (1–10), light-emitting diodes (LEDs) (11–15), lasers (16), and photodetectors (17, 18). Within a dec \nade, the power-conversion efficiencies (PCEs) \nof perovskite solar cells (PSCs) have increased \nfrom $3.8\\%$ (19) to $25.2\\%$ (20), exceeding other \nthin-film solar cells and the market leader, \npolycrystalline silicon. Since 2015, formamidi \nnium (FA) has been the preferred cation used \nin almost all high-efficiency PSCs because these \nformulations are thermally more stable than \nperovskites containing methylammonium (MA) \nand because FA’s narrower bandgap is closer \nto the Shockley–Queisser optimum (4). Our \nprevious molecular dynamics (MD) studies \nshowed that FA reorientation was faster than \nthat of MA on the A-cation site of the perov \nskite, which led to enhanced stabilization and \nslower charge-carrier recombination (21, 22). \n\nAlso, $\\mathrm{FAPbI_{3}}$ has a Goldschmidt tolerance factor of 0.99 (2), which suggests a perfect crystalline perovskite structure with minimum distortions. Thus, $\\mathrm{FAPbI_{3}}$ perovskite could be an ideal candidate for efficient, stable PSCs. \n\nUnfortunately, a photoinactive d form of $\\mathrm{FAPbI_{3}}$ is the most stable phase at room temperature, and the crystallinity of $\\mathrm{FAPbI_{3}}$ film is normally poor even after high-temperature annealing. To avoid formation of the d-phase and to improve crystallinity, various complex perovskite compositions have been developed. For example, a combination of MA, Cs, and Br is commonly mixed with $\\mathrm{FAPbI_{3}}$ , especially for the record high-efficiency PSCs (2, 3, 5, 6). However, these mixed-perovskite compositions show an unwanted blue shift in their light absorption. Moreover, the mixed-perovskite precursor solutions can easily form precipitates when they are used for scale-up fabrications. Furthermore, MA is thermally unstable (4, 23), and $\\mathrm{Br/I}$ mixtures suffer from severe ion segregations under long-term light illuminations (24). Thus, a mixing strategy may be unfavorable for long-term operational stability. Our previous work showed that mixing Cs and Rb with $\\mathrm{FAPbI_{3}}$ could be an alternative way to improve the operational stability (4), but the resulting PCE was still smaller than that reported for the most efficient PSCs. Obtaining efficient, phase-pure, stable $\\mathrm{FAPbI_{3}}$ perovskite layers is of vital importance for the perovskite research field. \n\nIn contrast to the previous mixing strategies, manipulation of surface energy has been reported to stabilize perovskite phases and modify the grain growth orientations (25–29). For example, templated growth of oriented layered perovskites has been demonstrated for two-dimensional (2D) perovskites (28), and epitaxial growth and stabilization of $\\mathrm{\\mathbf{a}{\\mathrm{-FAPbI}}_{3}}$ has been reported recently (29). Swarnkar et al. showed that $\\mathbf{\\alpha_{\\mathrm{{\\alpha}}}\\mathbf{{CsPbI}_{3}}}$ can be stabilized in the form of colloidal quantum dots because of a large contribution of surface energy (26). Fu et al. reported that functionalizing the surface of $\\mathrm{FAPbI_{3}}$ with large organic molecules could lower the formation energy to stabilize $\\mathbf{\\mathrm{\\mathrm{q}{-}F A P b I}_{3}}$ at room temperature (27). However, the performance, stability, or both in these systems is still poor compared with those of mixed cation-halide PSCs (25). Motivated by these promising strategies of surface energy manipulations and our recent work using polyiodide vapor for scalable perovskites (30), we developed a MA thiocyanate (MASCN) or FASCN vapor treatment method for preparing efficient and stable $\\mathrm{\\Phi_{\\mathrm{{\\mathbf{{a}}\\mathrm{{-FAPbI}_{3}}}}}}$ PSCs. \n\n# Characterization of $\\mathsf{F A P b l}_{3}$ films \n\nFigure 1A illustrates the steps of this vapor treatment process. Yellow ${\\delta\\mathrm{-}\\mathrm{FAPbI_{3}}}$ film was obtained by spin-coating a precursor solution of equal molar FAI and $\\mathrm{PbI_{2}}$ mixture. The asfabricated ${\\delta\\mathrm{-FAPbI_{3}}}$ film was annealed at $100^{\\circ}\\mathrm{C}$ for 1 min. Then, the annealed film was put in a MASCN vapor environment for ${\\sim}5\\mathrm{~s~}$ until the yellow color changed to black. This vapor treatment was done under normal pressure because MASCN has a sublimation point of $\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\mathopen{}\\mathclose\\bgroup\\left.<100^{\\circ}\\mathrm{C},\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\aftergroup\\egroup\\right.$ which renders the entire treatment process low cost and of practical interest for industrial scale-up applications. \n\nFigure 1B shows x-ray diffraction (XRD) data of $\\mathrm{FAPbI_{3}}$ perovskite films before and after exposure to MASCN vapor, confirming a structural transformation from the yellow d-phase to the pure black $\\upalpha$ -phase. XRD data of $\\mathrm{FAPbI_{3}}$ films fabricated using the conventional method (reference $\\mathrm{FAPbI_{3}}.$ ) is also shown for comparison. Our results demonstrated that the reference $\\mathrm{FAPbI_{3}}$ films contained the yellow d-phase. However, for the vapor-treated $\\mathrm{FAPbI_{3}}$ films, the d-phase was effectively suppressed and the full-width at half-maxima of the reflection peaks were decreased accordingly because of the increased XRD intensities, indicating an increase in film crystallinity. Time-resolved XRD data of $\\mathrm{FAPbI_{3}}$ perovskite films under MASCN vapor treatment (fig. S1) showed that the d-phase vanished after only $\\sim5\\mathrm{~s~}$ . In particular, the preferred orientation along the (001) plane shown in Fig. 1B reflected a change of surface energy during the crystallization processes (31). Synchrotronbased 2D grazing-incidence XRD (2D-GIXRD) for $\\mathrm{FAPbI_{3}}$ films with and without MASCN vapor treatment (fig. S2) performed at incident angles of $0.05\\mathrm{^\\circ}_{\\mathrm{~i~}}$ , $0.10^{\\circ};$ , and $0.40^{\\circ}$ confirmed that the preferred orientation was along the (001) plane from the near surface to the bulk region of the vapor-treated $\\mathrm{FAPbI_{3}}$ films. \n\n![](images/bc2a46c29a353e02998e59bc022bea66d2cdef0e42873a054fcb35d77a03e59f.jpg) \nFig. 1. $\\mathsf{F A P b l}_{3}$ perovskite film characterization. (A) Simplified scheme presenting the MASCN vapor treatment process for pure black-phase $\\mathsf{F A P b l}_{3}$ perovskite films. (B) XRD patterns of $\\mathsf{F A P b l}_{3}$ perovskite films before (yellow) and after (red) vapor treatments, as well as the reference $\\mathsf{F A P b l}_{3}$ perovskite films fabricated with the conventional method. The black diamond indicates $\\mathsf{P b l}_{2}$ species. (C) UV-vis absorption and PL spectra of vapor-treated and reference $\\mathsf{F A P b l}_{3}$ perovskite films. (D and E) Top-view SEM images of (D) the reference $\\mathsf{F A P b l}_{3}$ perovskite films and (E) vapor-treated $\\mathsf{F A P b l}_{3}$ perovskite films. (F and G) Cross-sectional SEM images of (F) the reference $\\mathsf{F A P b l}_{3}$ perovskite films and (G) vapor-treated $\\mathsf{F A P b l}_{3}$ perovskite films. Scale bar, $1\\upmu\\mathrm{m}$ . \n\nFigure 1C illustrates the ultraviolet-visible (UV-vis) absorption and the photoluminescence (PL) spectra of the reference and vapor-treated $\\mathrm{FAPbI_{3}}$ films. Identical absorption onsets as well as PL peaks at $812\\mathrm{nm}$ can be seen, which implies that the vapor treatment did not induce a bandgap change. However, vapor-treated $\\mathrm{FAPbI_{3}}$ films showed stronger absorption over all wavelengths compared with the reference sample, which is consistent with the enhanced phase purity and crystallinity apparent from the XRD results. Unlike the present work, in other recent studies using MACl as an additive (5, 32, 33), a considerable amount of MA was doped inside the bulk $\\mathrm{FAPbI_{3}}$ . Our UV-vis absorption and PL emission matched the features of pure $\\mathrm{FAPbI_{3}},$ unlike the results in (5) and (32), where the features were blue-shifted. Also, the XRD peaks of the vapor-treated $\\mathrm{FAPbI_{3}}$ were identical to those of the reference pure $\\mathrm{FAPbI_{3}}$ (fig. S2). \n\nAs can be seen in the scanning electron microscopy (SEM) top-view images shown in Fig. 1, D and E, the grain size of $\\mathrm{FAPbI_{3}}$ films increased to ${\\tilde{\\mathbf{\\Gamma}}}\\{\\mathbf{\\Gamma}\\}\\upmu\\mathrm{m}$ after vapor treatment. \n\nAtomic-force microscopy images of the reference and vapor-treated $\\mathrm{FAPbI_{3}}$ films showed that the surface roughness was ${\\sim}15\\mathrm{nm}$ (fig. S3, A and B). The SEM images of the d-phase $\\mathrm{FAPbI_{3}}$ films, shown in fig. S3, C and D, demonstrate that the average grain size was ${\\sim}100~\\mathrm{nm}$ before the vapor treatment. Figure 1, F and G, are cross-sectional SEM images showing that the irregular reference $\\mathrm{FAPbI_{3}}$ perovskite crystals converted to monolithic grains from the top to the bottom after the vapor treatment. Our XRD data and SEM images show that vapor treatment with MASCN induced a yellow d- to black $\\mathfrak{a}$ -phase transformation below the phase transition temperature together with a recrystallization of the $\\mathrm{FAPbI_{3}}$ films. \n\nWe performed solid-state nuclear magnetic resonance (ssNMR) spectroscopy measurements to unravel the role of MASCN during the vapor treatment. Recently, we and others have shown that ssNMR can identify cation incorporation (22, 34–36), halide-mixing (37), cation dynamics (21), and atomic-level interface interactions (38) in PSCs. We first performed $\\mathrm{^{14}N}.$ –magic angle spinning (MAS)–NMR measurements to investigate the effect of atomic-level interaction from the MASCN presence on the intrinsic crystallographic symmetry of the parent $\\mathrm{FAPbI_{3}}$ lattice. The $\\mathrm{^{14}N}$ -MAS-NMR spectra of $\\mathrm{FAPbI_{3}}$ featured a $\\mathrm{^{14}N}$ spinning sideband (SSB) pattern, which corresponds to FA cation reorientation on the picosecond time scale (21). \n\nFigure 2, A and B, indicate that the SSB width was altered by the MASCN surface treatment. The width of the $\\mathrm{^{14}N}$ SSB manifold was correlated with the symmetry of the cuboctahedral cavity in which FA cation reorientation took place, whereby a narrower manifold indicated a symmetry closer to cubic (21, 22, 35). The MASCN-treated $\\mathrm{FAPbI_{3}}$ thin film featured three to four orders of SSB less in $\\mathrm{^{14}N}$ spectrum compared with the reference $\\mathrm{FAPbI_{3}}$ film, indicative that FA was in an environment closer to cubic symmetry for the treated film. For both the reference and the vapor-treated $\\mathrm{FAPbI_{3}},$ the central peak of the $\\mathrm{^{14}N}$ -MAS-NMR spectra had an identical shift. We concluded that MASCN was not incorporated into the perovskite lattice but rather most likely interacted with the surface of the $\\mathrm{FAPbI_{3}}$ films (39). During the annealing process, MA was doped into the surface of $\\mathrm{FAPbI_{3}}$ films, which was confirmed by the time-of-flight secondary ion mass spectrometry measurements (fig. S4). The concentration of both $\\mathrm{MA}^{+}$ and SCN– ions in the vapor-treated $\\mathrm{FAPbI_{3}}$ film decreased by a factor of ${>}30$ over a distance of $\\sim20\\mathrm{nm}$ from the surface to the bulk. The bulk of the vaportreated $\\mathrm{FAPbI_{3}}$ film showed negligible MASCN content, which was close to that of the reference $\\mathrm{FAPbI_{3}}$ film, in agreement with the 2DGIXRD measurements. \n\nWe performed $^1\\mathrm{H}$ -MAS-ssNMR experiments to assess the amount of MA cation that was present in $\\mathrm{FAPbI_{3}}$ after the MASCN treatment. Figure 2C shows the $^1\\mathrm{H}$ spectrum of MASCN powder, which identified two distinct $^1\\mathrm{H}$ environments corresponding to $\\mathrm{CH}_{3}$ at 3.05 and $\\mathrm{NH_{3}}^{+}$ at 7.45 ppm. $\\mathbf{MAPbI_{3}}$ and reference $\\mathrm{FAPbI_{3}}$ perovskites yielded signals at 3.5 and $6.5\\mathrm{ppm}$ , respectively, corresponding to MA (Fig. 2D), and at 7.5 and $8.2\\ \\mathrm{ppm}$ , respectively, corresponding to FA (Fig. 2E). Figure 2F shows the $^1\\mathrm{H}$ spectrum of vapor-treated $\\mathrm{FAPbI_{3}}$ perovskites, which for the FA protons is identical to that of reference FAPbI3. When the signal was enhanced eight times, small additional peaks at 3.5 and $6.3\\ \\mathrm{ppm}$ confirmed that MA was present in small quantities in a $\\mathrm{MA}_{x}\\mathrm{FA}_{1-x}\\mathrm{PbI}_{3}$ environment and was not present as MASCN or any other form of MA. This agreed with 2D $\\mathrm{^1H-^{1}H}$ spin diffusion measurements, where the appearance of the cross-peak (fig. S5) between MA and FA suggested that MA and FA moieties were within $10\\mathrm{~\\AA~}$ of each other. We also performed quantitative solid-state 1D measurements, which indicated that the MA makes up $1.8\\%$ of the vapor-treated $\\mathrm{FAPbI_{3}}$ film (see the supplementary materials, note S1). \n\n# MD simulations \n\nWe performed MD simulations to gain insights into the vapor treatment process (fig. S6). Simulation details and movies of the MD trajectories are provided in the supplementary materials. The $\\mathrm{{scN}^{-}}$ ions on the surface of ${\\delta\\mathrm{{-FAPbI}_{3}}}$ do not diffuse inside the face-sharing structure of ${\\delta\\mathrm{{-FAPbI}_{3}}}$ but remain at the surface (movie S1). Because of their strong affinity to $\\mathrm{Pb^{2+}}$ ions, $\\mathrm{scN}^{-}$ anions coordinate to $\\mathrm{Pb^{2+}}$ on the surface of ${\\delta\\mathrm{-}\\mathrm{FAPbI_{3}}}$ (movies S2 and S3). In particular, $\\mathrm{Pb^{2+}}$ ions are coordinated with the sulfur atoms of $\\mathrm{scN}^{-}$ (fig. S7) strongly enough that the $\\operatorname{scN}^{-}$ ions displace the iodides. This process disintegrates the top layer of facesharing octahedra and induces the transition to the corner-sharing architecture of $\\mathrm{\\Delta\\mathrm{a-FAPbI_{3}}}$ . Furthermore, the disruption of the topmost surface layer with $\\mathrm{{\\sc~SCN^{-}}}$ ions also helps the penetration of monovalent cations $(\\mathrm{MA}^{+})$ into the $\\mathrm{PbI}_{6}$ chains of ${\\delta\\mathrm{{-FAPbI}_{3}}}$ , which further helps the growth of $\\mathrm{\\Phi_{0.+FAPbI_{3}}}$ (movie S4), in agreement with our ssNMR analysis above. \n\n![](images/bb1c071a8d1eb0cb67cbeeaec34502a4da54e20e606810a43ac8b8f135b248b2.jpg) \nFig. 2. $\\mathbf{\\lambda^{14}N-}$ and $^1{\\mathsf{H}}$ -MAS-ssNMR spectroscopy measurements. (A and B) $^{14}\\mathsf{N}$ -MAS-ssNMR spectra at 21.1 T, $298\\mathsf{K},$ and 5 kHz MAS of (A) reference $\\mathsf{F A P b l}_{3}$ perovskites and (B) vapor-treated $\\mathsf{F A P b l}_{3}$ perovskites. (C to F) $^1\\mathsf{H}$ -MAS-ssNMR spectra at 21.1 T, $298\\mathsf{K},$ , and $20~\\mathsf{k H z}$ MAS of (C) MASCN powder, (D) bulkmechanochemical $\\mathsf{M A P b l}_{3}$ , (E) reference $\\mathsf{F A P b l}_{3}$ perovskites, and (F) vapor-treated $\\mathsf{F A P b l}_{3}$ perovskites. \n\nWe investigated the rearrangement of ions at the surface of ${\\delta\\mathrm{{-FAPbI}_{3}}}$ . Some parts of facesharing octahedra on the interface start to form corner-sharing Pb-I-SCN structures (fig. S8). With the addition of extra SCN– ions, cornersharing structures, which contain mixtures of SCN– ions and iodides, are formed and stabilized (fig. S9). The atomic view of this whole transformation from face-sharing to cornersharing octahedra is shown in Fig. 3 and movies S5 and S6. Further analysis reveals that the conversion of the face-sharing structure proceeds through the formation of edgesharing intermediates. This results mainly from the step-by-step addition of $\\mathrm{{scN}^{-}}$ ions around the $\\mathrm{Pb^{2+}}$ ions, as seen in movies S5 and S6. Our previous studies have also shown the formation of such intermediate structures before conversion to perovskites (40). Some domains of the mixed-corner and face-sharing structures formed during the simulation, and we found that $\\operatorname{scN}^{-}$ ions could also induce the formation of polytypes at the interface. \n\nWe observed the formation of localized structures similar to the well-known 4H polytypes of $\\mathrm{FAPbI_{3}}$ (movies S6 and S7 and fig. S10). We also generated a model of a periodic structure of 4H polytype with iodides replaced by SCN– and found that this structure remained stable after variable cell first-principles density functional theory (DFT) optimization (see the supplementary materials). We conclude that SCN– ions drive and stabilize the formation of corner-sharing structures upon contact formation with MASCN, which in turn triggers the conversion to $\\mathrm{\\Phi_{\\mathrm{{\\alpha}d-\\mathrm{{FAPbI_{3}}}}}}$ . This process can occur below the thermodynamic phase-transition temperature. A further illustration of the d- to $\\mathbf{\\alpha}\\propto$ -phase transition by SCN– ions from the surface to the bulk is shown in fig. S11. \n\n![](images/155342ae4d9e133ec2bb8ae03d7a29c62600f124e005ccddd3c8f3c682ea9a43.jpg) \nFig. 3. MD simulations showing a structural conversion. Representative snapshot from the MD simulations showing a structural conversion of (A) the initial face-sharing octahedra and (B) the corner-sharing octahedra. Pb-I octahedra are shown in green; iodide is shown as orange balls on corners. To highlight the structural transformation, red was chosen for octahedra on the interface. $\\mathsf{F A}^{+}$ and $\\mathsf{M A}^{+}$ ions are not shown for clarity. Selected $S C N^{-}$ ions are shown as ball and stick representations: sulfur is yellow, carbon is light blue, and nitrogen is dark blue (the other $S C N^{-}$ ions are not shown for clarity). \n\nTo confirm the role of $\\mathrm{{scN}^{-}}$ , we used FASCN instead of MASCN for vapor treatment of the d-phase $\\mathrm{FAPbI_{3}}$ . This treatment formed pure $\\mathbf{\\mathrm{\\mathbf{q}}{\\mathrm{-}}F\\mathbf{APbI}_{3}}$ even at an annealing temperature of only $100^{\\circ}\\mathrm{C}$ (fig. S12), far below the thermodynamic phase-transition temperature. In the absence of FASCN, the reference $\\mathrm{FAPbI_{3}}$ films annealed at $100^{\\circ}\\mathrm{C}$ mainly formed the d-phase. Thus, the complete transformation from the d- to $\\mathrm{\\mathbf{o}{\\mathrm{-FAPbI}}_{3}}$ also occurred in the absence of $\\mathrm{MA}^{+}$ ions, which agreed well with our MD simulations. We note that the $\\mathfrak{a}$ -phase $\\mathrm{FAPbI_{3}}$ remained kinetically stable; once the pure $\\mathbf{\\alpha}\\propto$ -phase $\\mathrm{FAPbI_{3}}$ formed, its transition back to the d-phase was restrained by a high potential energy barrier (fig. S13). \n\n# Photovoltaic and EL measurements \n\nAfter the successful preparation of pure $\\mathbf{\\mathrm{\\mathbf{a}{\\mathrm{-}}F A P b I{_3}}}$ with ordered and monolithic grains, we further investigated the performance of the corresponding PSCs. All PSCs were fabricated using an ITO $\\mathrm{\\DeltaSnO_{2}}$ /FAPbI3/Spiro-MeOTAD/Au configuration {where ITO is indium tin oxide and Spiro-MeOTAD is 2,2',7,7'-tetrakis[N,N-bis $_{p-}$ methoxyphenyl)amino]-9,9'-spirobifluorene} (Fig. 4A). A cross-sectional SEM image of the full device structure is given in fig. S14. Figure 4B demonstrates a PCE of $23.1\\%$ for one of our best $\\mathrm{FAPbI_{3}}$ PSCs with a short-circuit current density $(J_{\\mathrm{sc}})$ of $24.4\\mathrm{mA}/\\mathrm{cm}^{2}$ , open-circuit voltage $(V_{\\mathrm{oc}})$ of $1.165\\mathrm{V}$ , and fill factor (FF) of $81.3\\%$ . This device also exhibited negligible hysteresis under both forward and reverse scans between 0 and $1.2\\mathrm{V}$ . Details on the reproducibility of this vapor treatment technique are provided in fig. S15. \n\nWe validated the performance of our PSCs at the Photovoltaic Laboratory of the Institute of Micro Technique (IMT), Neuchâtel, Switzerland. The Wacom high-precision class AAA solar simulator available at the IMT photovoltaic laboratory closely mimics the solar spectrum in the absorption range of the PSCs in the range of 350 to $850\\mathrm{nm}$ , avoiding any substantial spectral mismatch between the simulated and true AM1.5G solar light source. The solar spectrum of the Wacom lamp is shown in the insert in fig. S16A. An efficiency of $22.4\\%$ was confirmed under the maximum power point (MPP) condition at IMT, which is near the $22.8\\%$ measured in our laboratory (fig. S16). As a comparison, the $J{-}V$ curves of the reference PSCs are given in fig. S17, which shows a relatively poor performance and large hysteresis. Figure 4C shows the corresponding incident photon-to-electron conversion efficiency (IPCE) curve and a projected $J_{\\mathrm{sc}}$ of $24.3\\mathrm{mA/cm^{2}}$ , obtained by integrating the IPCE over the AM1.5G standard spectrum. This value matched well the $J_{\\mathrm{sc}}$ of $24.4\\mathrm{mA}/\\mathrm{cm}^{2}$ measured under the solar simulator. Steady-state power output at MPP under 1 sun light-soaking conditions is shown in fig. S18. The rapid response and stable output indicated efficient charge extraction and negligible charge accumulation. \n\nOnce efficient carrier collection is achieved, the $V_{\\mathrm{{oc}}}$ becomes the main limiting factor for device efficiency. Figure 4D illustrates a $V_{\\mathrm{{oc}}}$ of 1.19 V obtained for one of the vapor-treated $\\mathrm{FAPbI_{3}}$ PSCs. The $J{-}V$ curves for this device were measured under a cooling air flow at $20.1^{\\circ}\\mathrm{C}.$ . A detailed determination of the measured $V_{\\mathrm{{oc}}}$ is shown in the supplementary materials, note S2. The temporal evolution of the $V_{\\mathrm{oc}}$ measured for $5\\ \\mathrm{min}$ under 0.9 sun is shown in fig. S19. Over this time period, the \n\n![](images/a800f78c17d741b11da5dab3be54b816e73e6e8e16a8b0d055e025342cfe80c7.jpg) \nFig. 4. Vapor-treated $\\mathsf{F A P b l}_{3}$ -based PSC characterization. (A) Simplified graph of planar-structure $\\mathsf{F A P b l}_{3}$ PSCs. (B) $J{-}V$ curves under both reverse and forward scan directions and power outputs under different bias voltages. (C) IPCE curve of $\\mathsf{F A P b}|_{3}$ PSCs over 300- to 900-nm wavelengths and integrated $J_{\\mathsf{s c}}$ over the AM1.5G standard spectrum. (D) $J{-}V$ curve of $\\mathsf{F A P b l}_{3}$ PSCs with a $V_{\\mathrm{oc}}$ of 1.19 V (measured at ${\\sf T}=20.1^{\\circ}{\\sf C}^{\\prime}$ ). (E) EL spectra of $\\mathsf{F A P b l}_{3}$ PSCs under different bias voltages from 0.75 to 1 V. (F) $\\mathsf{E Q E}_{\\mathsf{E L}}$ and current density of $\\mathsf{F A P b l}_{3}$ PSCs under bias voltages from 0 to $1.8\\ V$ ; a photograph of the luminescence of $\\mathsf{F A P b l}_{3}$ PSCs under 1.45 V bias voltage shown in the inset. \n\n$V_{\\mathrm{{oc}}}$ reached a stable plateau. From the emission spectra (Fig. 4E), we determined an Urbach energy of $14\\mathrm{meV}$ (fig. S20). Using these data, the IPCE, and the reciprocity relation $(4I)$ , we determined the theoretical radiative limit $V_{\\mathrm{{oc}}}$ to be \\~1.255 V [see the supplementary materials for details of this calculation and the influence of temperature (fig. S21)]. Thus, our measured $V_{\\mathrm{oc}}$ is only $65~\\mathrm{mV}$ below the radiative limit, and the voltage loss compared with the bandgap is only $330\\mathrm{mV}.$ . We derived a bandgap of $1.52~\\mathrm{eV}$ for $\\mathrm{FAPbI_{3}}$ using the Tauc plot (fig. S22), which is somewhat larger than reported values (42). To the best of our knowledge, our $\\mathrm{FAPbI_{3}}$ devices have the smallest $V_{\\mathrm{{oc}}}$ loss reported so far for PSCs, outperforming silicon solar cells and closely approaching that of GaAs photovoltaics (43). The $V_{\\mathrm{{oc}}}$ value is related to density of defects of the perovskite layer acting as centers for nonradiative recombination of photogenerated charge carriers. To investigate this loss channel, we measured the time-resolved PL of the reference and vapor-treated $\\mathrm{FAPbI_{3}}$ films. Figure S23 shows that the lifetime of the vaportreated $\\mathrm{FAPbI_{3}}$ is 299.3 ns, which is 3.7 times longer than that of the reference film. \n\nA solar cell’s photovoltage is directly related to the ability to extract its internal luminescence, as derived by Ross $(44)$ : \n\n$$\nV_{\\mathrm{oc}}=V_{\\mathrm{oc,rad}}+{\\frac{k T}{q}}\\mathrm{ln}(\\mathfrak{n}_{\\mathrm{ext}})\n$$ \n\nwhere $V_{\\mathrm{oc,rad}}$ is the radiative limit of opencircuit voltage, $k$ is the Boltzmann constant, $T$ is the temperature, $q$ is the electronic charge, and $\\boldsymbol{\\eta_{\\mathrm{ext}}}$ is the external luminescence quantum efficiency. For any solar cell technology to approach the radiative limit, efficient external electroluminescence (EL) is a necessity (45). Because we obtained a $V_{\\mathrm{{oc}}}$ approaching the radiative limit $V_{\\mathrm{oc,rad}},$ we expected a high external quantum efficiency of the EL $\\mathrm{(EQE_{EL})}$ from our $\\mathrm{FAPbI_{3}}$ -based PSCs. Figure 4E shows the EL spectra of FAPbI3-based PSCs, which were measured under different bias voltages in ambient conditions. An EL peak position can be seen at $810~\\mathrm{nm}$ , consistent with the above PL results. We detected EL emission even under a low bias voltage of $0.75\\mathrm{V}.$ . Thermal activation can contribute to reduce the turn-on voltage below the bandgap $'q$ of the active/emissive semiconductor. To the best of our knowledge, $0.75\\mathrm{V}$ is the lowest reported turn-on voltage value for perovskite-based devices, which suggests low leakage currents, low energy loss, or both, as well as almost perfectly balanced carrier injection and low nonradiative recombination. Figure 4F shows an $\\mathrm{EQE_{EL}}$ of $6.5\\%$ for an injection current density of $25\\mathrm{\\mA/cm^{2}}$ (corresponding to the $J_{\\mathrm{sc}}$ measured under 1 sun illumination). This result translated into a nonradiative loss as low as $70~\\mathrm{mV}$ (see the supplementary materials, note S2), which surpasses the reported values in the literature and even light emission from the best silicon solar cells. \n\nThe measured $\\mathrm{EQE_{EL}}$ was actually underestimated because of substantial emission losses from glass sheets, which could partially explain the $\\scriptstyle5-\\operatorname*{mV}$ difference between the measured and predicted nonradiative loss. An even higher $8.6\\%$ $\\mathrm{EQE_{EL}}$ was achieved with an injected current density $<100\\ \\mathrm{mA/cm^{2}}$ . These $\\mathrm{EQE_{EL}}$ values are among the highest ones reported in the literature. Compared with results published recently $(5,45)$ , our driving voltage was substantially smaller, resulting in an exceptional high peak wall-plug efficiency of $7.5\\%$ with a low bias voltage of $1.55\\mathrm{V}$ (fig. S24). Our devices exhibited a low rolloff under injected current densities up to $300\\mathrm{\\mA/cm^{2}}$ (fig. S25). These results contrast with the difficulties to reach high efficiency at high current densities, which has been a challenge for the other reported perovskite devices (5, 46), as well as organic LEDs (13). Therefore, our $\\mathrm{FAPbI_{3}}$ -based PSCs compare favorably with the state-of-the-art perovskite-based LEDs and even other organic LEDs. \n\n# Stability measurements \n\nWe investigated the operational stability of our FAPbI3-based PSCs because stability issues remain the main obstacle to the commercialization of PSCs. Reports of long-term stability under MPP-tracking conditions (operational stability) is still scarce for PSCs with a PCE exceeding $22\\%(3,5)$ . Unexpectedly, the reported operational stability of some high-efficiency \n\n![](images/bcded68ea6eab35deb8b99a29e827366e5925ea1e8e72195b2e8a0872f1ad235.jpg) \nFig. 5. Operational stability test of the vapor-treated $\\mathsf{F A P b l}_{3}$ -based PSCs. Tests were performed under 500 hours of MPP-tracking conditions for (A) PCE, (B) $J_{\\scriptscriptstyle\\mathrm{SC}},$ , (C) $V_{\\mathrm{oc}}$ , (D) FF, and (E) hysteresis factor $(P_{\\mathrm{rev}}/P_{\\mathrm{for}})$ . \n\nPSCs, in which 2D structures, Cs, or both have been used to improve the device stability, remains low (25, 47, 48). Recently, Seo et al. improved the stability using poly(3-hexylthiophene) as the hole-transporting material (6). However, the stability of their reference cell with standard Spiro-MeOTAD lagged far behind. \n\nWe determined the phase stability of the MASCN vapor-treated $\\mathrm{FAPbI_{3}}$ films under long-term heat stress at $85^{\\circ}\\mathrm{C}$ in an inert $\\mathrm{{N}_{2}}$ environment because $\\mathrm{FAPbI_{3}}$ undergoes a transition to a yellow phase below $\\mathrm{150^{\\circ}C}$ . Figure S26A shows the XRD data of the vapor-treated $\\mathrm{FAPbI_{3}}$ films annealed up to 500 hours. The black $\\mathfrak{a}$ -phase for all vapor-treated $\\mathrm{FAPbI_{3}}$ perovskite films persisted even after 500 hours of annealing at $85^{\\circ}\\mathrm{C}.$ . Conversely, the reference $\\mathrm{FAPbI_{3}}$ films degraded severely during the heat test and formed mainly $\\mathrm{PbI_{2}}$ (fig. S26B). We also investigated the shelf life of our vaportreated $\\mathrm{FAPbI_{3}}$ -based PSCs (fig. S27) and, after 2500 hours of storage in a dry box, the PCE remained at $97.8\\%$ of its initial value. \n\nWe performed long-term operational stability tests for 500 hours with MPP tracking under continuous 1 sun illumination for our $\\mathrm{FAPbI_{3}}$ PSCs. Figure 5A shows that the PCE of our $\\mathrm{FAPbI_{3}}$ PSCs remained at ${\\sim}90\\%$ of the initial value $(21.4\\%)$ after 500 hours of MPP measurements. The PCE partially recovered to $20.2\\%$ , which is $94.4\\%$ of the initial value after 12 hours of rest in open-circuit conditions in the dark, consistent with our previous reports (49). PV metrics derived from the $J{-}V$ curves, including $V_{\\mathrm{oc}},J_{\\mathrm{sc}},$ FF, and the hysteresis factor $(P_{\\mathrm{rev}}/P_{\\mathrm{for}})$ , are shown in Fig. 5, B to E. The $V_{\\mathrm{{oc}}}$ and $J_{\\mathrm{sc}}$ remained constant during 500 hours of MPP tracking, and the hysteresis factor remained near unity, suggesting minimal electronic charge trapping at interfaces. \n\nThe main degradation of our PSCs was the FF decline from 0.77 to 0.70 over the lightsoaking period. However, the FF largely recovered when the cell was left in the dark for a few hours, as shown by the final red point in Fig. 5D. Thus, the FF decrease was a reversible phenomenon and did not indicate permanent degradation of the device. During long-term light soaking, the PSC was subjected to an electric field originating from the voltage difference across the device at MPP. This electric field in turn caused migration of $\\mathrm{Li^{+}}$ ions across the film and dedoping of the hole conductor. As a result, the hole transport resistance increased, explaining the observed decline of FF. In the dark, the internal field vanished and the hole conductor recuperated most of the $\\mathrm{Li^{+}}$ ions, which led to the recovery of FF. Our devices did not exhibit appreciable hysteresis, which ruled out the decrease of the FF arising from ion movement within the perovskite layer and their trapping at charge defects present at the interface of the perovskite film with the electron or hole-selective contact material. However, apart from the outflow of $\\mathrm{Li^{+}}$ ions, inflow of iodide could dedope the hole conductor and increase the series resistance, which would contribute to the observed decrease of the FF (9). \n\n# Methods summary \n\nPSCs were fabricated using an $\\mathrm{ITO/SnO_{2}/}$ FAPbI3/Spiro-MeOTAD/Au configuration. ITO substrates were etched and properly cleaned before the deposition of an $\\mathrm{{SnO}_{2}}$ electrontransport layer. Commercially available $\\mathrm{{SnO}_{2}}$ nanoparticle solution was diluted and spincoated onto the cleaned ITO substrates in ambient air conditions, similar to previous reports (5). Then, the substrates were annealed at $\\mathrm{150^{\\circ}C}$ for $30\\mathrm{min}$ . Just before perovskite layer deposition, the $\\mathrm{{SnO}_{2}}$ layer was treated with UV-ozone for $15\\mathrm{min}$ . The $\\mathrm{FAPbI_{3}}$ perovskite precursor solution was spin-coated on top of the as-fabricated $\\mathrm{{SnO}_{2}}$ layer, and chlorobenzene was used as an antisolvent during the spincoating process. For the reference $\\mathrm{FAPbI_{3}}$ , the spin-coated perovskite film was annealed at $100^{\\circ}\\mathrm{C}$ for 1 min and then at $150^{\\circ}\\mathrm{C}$ for $20~\\mathrm{{min}}$ . For the vapor-treated $\\mathrm{FAPbI_{3}},$ , after 1 min of annealing at $100^{\\circ}\\mathrm{C},$ , the yellow d-phase $\\mathrm{FAPbI_{3}}$ film was put on top of the MASCN or FASCN vapor atmosphere for 5 s until the color of the film changed from yellow to black. The MASCN or FASCN vapor atmosphere was generated by heating these substances on a hot plate. After the annealing, the $\\mathrm{FAPbI_{3}}$ perovskite film was passivated by choline chloride. For the hole-transport layer, a SpiroOMeTAD solution was spin-coated on top of the perovskite. Finally, $80\\mathrm{-nm}$ gold was evaporated under high vacuum. \n\nFor the MD simulations, we constructed a large supercell of d-phase $\\mathrm{FAPbI_{3}}$ with 28,800 atoms (2400 stoichiometric units of $\\mathrm{FAPbI_{3}}.$ ). We followed a similar procedure as used in our previous work (50). Considering that polytypes play an important role in the crystallization of $\\mathrm{FAPbI_{3}}$ , we upgraded the previously used force field to be able to simulate all of the experimentally known polytypes (2H, 4H, 6H, and 3C) of $\\mathrm{FAPbI_{3}}$ . At first, we equilibrated this supercell by performing 10-ns variable-cell isothermal-isobaric simulations at 370 K. Next, we exposed this supercell to $\\mathrm{\\mathbf{MA}^{+}}$ and $\\mathrm{scN^{-}}$ ions (fig. S6). With this setup, we again performed an equilibrium run for 2 ns in an isothermal-isobaric ensemble at $370\\mathrm{K}$ with a force field for SCN– ions available from literature $(5I)$ . Interaction parameters between different heterogeneous species were calculated with mixing rules. All production runs were performed in an isothermal-isobaric ensemble ranging from 20 to 100 ns. All simulations were performed with Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code (31 March 2017) (52). \n\nMore details of the materials, device fabrication, characterization, MD simulation, and \n\nREFERENCES AND NOTES \n1. W. Nie et al., Solar cells. High-efficiency solution-processed perovskite solar cells with millimeter-scale grains. Science 347, 522–525 (2015). doi: 10.1126/science.aaa0472; pmid: 25635093 \n2. M. Saliba et al., Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). doi: 10.1126/science.aah5557; pmid: 27708053 \n3. W. S. Yang et al., Iodide management in formamidiniumlead-halide-based perovskite layers for efficient solar cells. Science 356, 1376–1379 (2017). doi: 10.1126/science.aan2301; pmid: 28663498 \n4. S. H. Turren-Cruz, A. Hagfeldt, M. Saliba, Methylammoniumfree, high-performance, and stable perovskite solar cells on a planar architecture. Science 362, 449–453 (2018). doi: 10.1126/science.aat3583; pmid: 30309904 \n5. Q. Jiang et al., Surface passivation of perovskite film for efficient solar cells. Nat. Photonics 13, 460–466 (2019). doi: 10.1038/s41566-019-0398-2 \n6. E. H. Jung et al., Efficient, stable and scalable perovskite solar cells using poly(3-hexylthiophene). Nature 567, 511–515 (2019). doi: 10.1038/s41586-019-1036-3; pmid: 30918371 \n7. S. Bai et al., Planar perovskite solar cells with long-term stability using ionic liquid additives. Nature 571, 245–250 (2019). doi: 10.1038/s41586-019-1357-2; pmid: 31292555 \n8. S. Yang et al., Stabilizing halide perovskite surfaces for solar cell operation with wide-bandgap lead oxysalts. Science 365, 473–478 (2019). doi: 10.1126/science.aax3294; pmid: 31371610 \n9. Y. Wang et al., Stabilizing heterostructures of soft perovskite semiconductors. Science 365, 687–691 (2019). doi: 10.1126/ science.aax8018; pmid: 31416961 \n10. J. Tong et al., Carrier lifetimes of ${\\mathrm{>}}1{\\upmu}{\\mathrm{s}}$ in Sn-Pb perovskites enable efficient all-perovskite tandem solar cells. Science 364, 475–479 (2019). doi: 10.1126/science.aav7911; pmid: 31000592 \n11. K. Lin et al., Perovskite light-emitting diodes with external quantum efficiency exceeding 20 per cent. Nature 562, 245–248 (2018). doi: 10.1038/s41586-018-0575-3; pmid: 30305741 \n12. Y. Cao et al., Perovskite light-emitting diodes based on spontaneously formed submicrometre-scale structures. Nature 562, 249–253 (2018). doi: 10.1038/s41586-018- 0576-2; pmid: 30305742 \n13. W. Xu et al., Rational molecular passivation for highperformance perovskite light-emitting diodes. Nat. Photonics 13, 418–424 (2019). doi: 10.1038/s41566-019-0390-x \n14. B. Zhao et al., High-efficiency perovskite–polymer bulk heterostructure light-emitting diodes. Nat. Photonics 12, 783–789 (2018). doi: 10.1038/s41566-018-0283-4 \n15. T. Matsushima et al., High performance from extraordinarily thick organic light-emitting diodes. Nature 572, 502–506 (2019). doi: 10.1038/s41586-019-1435-5; pmid: 31358964 \n16. G. Xing et al., Low-temperature solution-processed wavelength-tunable perovskites for lasing. Nat. Mater. 13, 476–480 (2014). doi: 10.1038/nmat3911; pmid: 24633346 \n17. Y. C. Kim et al., Printable organometallic perovskite enables large-area, low-dose X-ray imaging. Nature 550, 87–91 (2017). doi: 10.1038/nature24032; pmid: 28980632 \n18. W. Pan et al., Cs2AgBiBr6 single-crystal X-ray detectors with a low detection limit. Nat. Photonics 11, 726–732 (2017). doi: 10.1038/s41566-017-0012-4 \n19. A. Kojima, K. Teshima, Y. Shirai, T. Miyasaka, Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). doi: 10.1021/ ja809598r; pmid: 19366264 \n20. National Renewable Energy Laboratory, “Best research-cell efficiency chart” (2020); www.nrel.gov/pv/cell-efficiency.html. \n21. D. J. Kubicki et al., Cation dynamics in mixed-cation $(\\mathsf{M A})_{\\times}(\\mathsf{F A})_{1-\\times}\\mathsf{P b}|_{3}$ hybrid perovskites from solid-state NMR. J. Am. Chem. Soc. 139, 10055–10061 (2017). doi: 10.1021/ jacs.7b04930; pmid: 28641413 \n22. D. J. Kubicki et al., Formation of stable mixed guanidiniummethylammonium phases with exceptionally long carrier lifetimes for high-efficiency lead iodide-based perovskite photovoltaics. J. Am. Chem. Soc. 140, 3345–3351 (2018). doi: 10.1021/jacs.7b12860; pmid: 29429335 \n23. Z. Wang et al., High irradiance performance of metal halide perovskites for concentrator photovoltaics. Nat. Energy 3, 855–861 (2018). doi: 10.1038/s41560-018-0220-2 \n\nDFT calculations can be found in the supplementary materials. \n\n24. S. Draguta et al., Rationalizing the light-induced phase separation of mixed halide organic-inorganic perovskites. Nat. Commun. 8, 200 (2017). doi: 10.1038/s41467-017-00284-2; pmid: 28779144 \n25. J. W. Lee et al., 2D perovskite stabilized phase-pure formamidinium perovskite solar cells. Nat. Commun. 9, 3021 (2018). doi: 10.1038/s41467-018-05454-4; pmid: 30069012 \n26. A. Swarnkar et al., Quantum dot-induced phase stabilization of a-CsPbI3 perovskite for high-efficiency photovoltaics. Science 354, 92–95 (2016). doi: 10.1126/science.aag2700; pmid: 27846497 \n27. Y. Fu et al., Stabilization of the Metastable Lead Iodide Perovskite Phase via Surface Functionalization. Nano Lett. 17, 4405–4414 (2017). doi: 10.1021/acs.nanolett.7b01500; pmid: 28595016 \n28. J. Wang et al., Templated growth of oriented layered hybrid perovskites on 3D-like perovskites. Nat. Commun. 11, 582 (2020). doi: 10.1038/s41467-019-13856-1; pmid: 31996680 \n29. Y. Chen et al., Strain engineering and epitaxial stabilization of halide perovskites. Nature 577, 209–215 (2020). doi: 10.1038/ s41586-019-1868-x; pmid: 31915395 \n30. I. Turkevych et al., Strategic advantages of reactive polyiodide melts for scalable perovskite photovoltaics. Nat. Nanotechnol. 14, 57–63 (2019). doi: 10.1038/s41565-018-0304-y; pmid: 30478274 \n31. B. J. Foley et al., Controlling nucleation, growth, and orientation of metal halide perovskite thin films with rationally selected additives. J. Mater. Chem. 5, 113–123 (2017). doi: 10.1039/ C6TA07671H \n32. M. Kim et al., High rate li-ion batteries with cation-disordered cathodes. Joule 3, 1064–1079 (2019). doi: 10.1016/ j.joule.2019.01.002 \n33. H. Min et al., Efficient, stable solar cells by using inherent bandgap of a-phase formamidinium lead iodide. Science 366, 749–753 (2019). doi: 10.1126/science.aay7044; pmid: 31699938 \n34. W. Xiang et al., Europium-doped CsPbI2Br for stable and highly efficient inorganic perovskite solar cells. Joule 3, 205–214 (2019). doi: 10.1016/j.joule.2018.10.008 \n35. D. J. Kubicki et al., Phase Segregation in Cs-, Rb- and K-Doped Mixed-Cation $(\\mathsf{M A})_{\\mathsf{x}}(\\mathsf{F A})_{1-\\mathsf{x}}\\mathsf{P b}|_{3}$ Hybrid Perovskites from Solid-State NMR. J. Am. Chem. Soc. 139, 14173–14180 (2017). doi: 10.1021/jacs.7b07223; pmid: 28892374 \n36. D. J. Kubicki et al., Phase segregation in potassium-doped lead halide perovskites from $39k$ solid-state NMR at 21.1 T. J. Am. Chem. Soc. 140, 7232–7238 (2018). doi: 10.1021/ jacs.8b03191; pmid: 29779379 \n37. B. A. Rosales et al., Persistent dopants and phase segregation in organolead mixed-halide perovskites. Chem. Mater. 28, 6848–6859 (2016). doi: 10.1021/acs.chemmater.6b01874 \n38. E. A. Alharbi et al., Atomic-level passivation mechanism of ammonium salts enabling highly efficient perovskite solar cells. Nat. Commun. 10, 3008 (2019). doi: 10.1038/s41467-019- 10985-5; pmid: 31285432 \n39. M. Tavakoli et al., Addition of adamantylammonium iodide to hole transport layers enables highly efficient and electroluminescent perovskite solar cells. Energy Environ. Sci. 11, 3310–3320 (2018). doi: 10.1039/C8EE02404A \n40. P. Ahlawat et al., Atomistic mechanism of the nucleation of methylammonium lead iodide perovskite from solution. Chem. Mater. 32, 529–536 (2019). doi: 10.1021/ acs.chemmater.9b04259 \n41. W. Tress et al., Predicting the open-circuit voltage of CH3NH3PbI3 perovskite solar cells using electroluminescence and photovoltaic quantum efficiency spectra: The role of radiative and non-radiative recombination. Adv. Energy Mater. 5, 1400812 (2015). doi: 10.1002/aenm.201400812 \n42. G. E. Eperon et al., Formamidinium lead trihalide: A broadly tunable perovskite for efficient planar heterojunction solar cells. Energy Environ. Sci. 7, 982–988 (2014). doi: 10.1039/c3ee43822h \n43. M. A. Green et al., Solar cell efficiency tables (version 51). Prog. Photovolt. Res. Appl. 26, 3–12 (2018). doi: 10.1002/pip.2978 \n44. R. T. Ross, Some thermodynamics of photochemical systems. J. Chem. Phys. 46, 4590–4593 (1967). doi: 10.1063/1.1840606 \n45. O. D. Miller, E. Yablonovitch, S. R. Kurtz, Strong Internal and External Luminescence as Solar Cells Approach the Shockley–Queisser Limit. IEEE Journal of Photovoltaics 2, 303–311 (2012). doi: 10.1109/JPHOTOV.2012.2198434 \n46. J. J. Yoo et al., An interface stabilized perovskite solar cell with high stabilized efficiency and low voltage loss. Energy Environ. Sci. 12, 2192–2199 (2019). doi: 10.1039/C9EE00751B \n47. D. Yang et al., High efficiency planar-type perovskite solar cells with negligible hysteresis using EDTA-complexed $\\mathsf{S n O}_{2}$ . Nat. Commun. 9, 3239 (2018). doi: 10.1038/s41467-018-05760-x; pmid: 30104663 \n48. Q. Li et al., Efficient perovskite solar cells fabricated through CsCl-enhanced $\\mathsf{P b l}_{2}$ precursor via sequential deposition. Adv. Mater. 30, 1803095 (2018). doi: 10.1002/adma.201803095 \n49. W. Tress et al., Performance of perovskite solar cells under simulated temperature-illumination real-world operating conditions. Nat. Energy 4, 568–574 (2019). doi: 10.1038/ s41560-019-0400-8 \n50. L. Hong et al., Guanine-stabilized formamidinium lead iodide perovskites. Angew. Chem. Int. Ed. 59, 4691–4697 (2020). doi: 10.1002/anie.201912051; pmid: 31846190 \n51. G. Tesei, V. Aspelin, M. Lund, Specific cation effects on $S C N^{-}$ in bulk solution and at the air-water interface. J. Phys. Chem. B 122, 5094–5105 (2018). doi: 10.1021/ acs.jpcb.8b02303; pmid: 29671594 \n52. S. Plimpton, Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117, 1–19 (1995). doi: 10.1006/ jcph.1995.1039 \n\n# ACKNOWLEDGMENTS \n\nWe thank B. P. Darwich and D. W. Bi for technical support; beamline BL17B1, BL14B1, BL08U, and BL01B1 staff at the SSRF for \n\nproviding the beamline; and the Swiss National Supercomputing Centre (CSCS) and EPFL computing center (SCITAS) for their support. Funding: This work was partially supported by the National Natural Science Foundation of China (grant no. 61774046). H.L. thanks the China Postdoctoral Science Foundation for support from Funded Project 2017M611440 and the Shanghai Institute of Intelligent Electronics and Systems for postdoctoral fellowship support. F.F. thanks the Swiss Federal Office of Energy (SFOE)-BFE for funding (project no. SI/501805-01). U.R. thanks the Swiss National Science Foundation for funding through the NCCR MUST and individual grant 200020_185092. M.G. acknowledges financial support from the European Union’s Horizon 2020 research and innovation program (grant no. 826013) and the King Abdulaziz City for Science and Technology (KACST). A.H. thanks the Swiss National Science Foundation for support (project “Fundamental studies of dye-sensitized and perovskite solar cells” funded by grant no. 200020_185041). Author contributions: H.L. conceived the study, fabricated all the devices, conducted the relevant measurements, and wrote the first draft of the manuscript. M.G. proposed experiments and wrote the final version of the manuscript. P.A. and U.R. were responsible for the simulations. Y.L. synthesized some necessary materials for the experiments. A.M., C.E.A., and L.E. conducted the ssNMR measurements and analysis. B.I.C. helped to conduct the PL measurements. A.A. helped to conduct the long-term operational stability measurements. W.R.T. and F.T.E. conducted the EL and $\\mathsf{E Q E}_{\\mathsf{E L}}$ measurements as well as the radiative limit $\\mathsf{V}_{\\mathrm{OC}}$ calculations. Y.Y. performed the 2D-GIXRD measurements. F.F. conducted the time-of-flight secondary ion mass spectrometry measurements. Z.W. conducted the UV-vis and XRD measurements. S.M.Z. coordinated the whole project. Y.Z., L.Z., A.H., and M.G. supervised the project. H.L., A.H., and M.G. revised the manuscript and addressed the reviewers’ comments. All authors analyzed the data and contributed to the discussions. Competing interests: The authors declare no competing interests. M.G. has a part-time affiliation with Max Planck Institute for Solid State Research, Stuttgart, Germany. S.M.Z. has a part-time affiliation with King Abdulaziz University, Jeddah, Saudi Arabia. Data and materials availability: The data that support the findings of this study are available from the corresponding author upon request. All other data needed to evaluate the conclusions in this study are provided in either the manuscript or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/370/6512/eabb8985/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S27 \nReferences (53–66) \nMovies S1 to S7 \n26 March 2020; accepted 5 August 2020 \n10.1126/science.abb8985 \n\n# Science \n\n# Vapor-assisted deposition of highly efficient, stable black-phase FAPbI3 perovskite solar cells \n\nHaizhou Lu, Yuhang Liu, Paramvir Ahlawat, Aditya Mishra, Wolfgang R. Tress, Felix T. Eickemeyer, Yingguo Yang, Fan Fu, Zaiwei Wang, Claudia E. Avalos, Brian I. Carlsen, Anand Agarwalla, Xin Zhang, Xiaoguo Li, Yiqiang Zhan, Shaik M. Zakeeruddin, Lyndon Emsley, Ursula Rothlisberger, Lirong Zheng, Anders Hagfeldt and Michael Grätzel \n\nScience 370 (6512), eabb8985. DOI: 10.1126/science.abb8985 \n\n# Moving a perovskite into the black \n\nThe bandgap of the black $\\upalpha$ -phase $\\mathsf{F A P b l}_{3}$ (where FA is formamidinium) is nearly ideal for solar cells, but it is unstable with respect to the photoinactive yellow δ-phase. Lu et al. found that a film of the yellow phase was converted to a highly crystalline black phase by vapor exposure to methylammonium thiocyanate at $100^{\\circ}\\mathsf{C}$ , and it retained this structure after 500 hours at $\\mathtt{\\i}85^{\\circ}\\mathsf{C}$ . Solar cells fabricated with this material had a power conversion efficiency of more than $23\\%$ . After 500 hours under maximum power tracking and a period of dark recovery, $94\\%$ of the original efficiency was retained. \n\nScience, this issue p. eabb8985 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1126_sciadv.aba9624", + "DOI": "10.1126/sciadv.aba9624", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.aba9624", + "Relative Dir Path": "mds/10.1126_sciadv.aba9624", + "Article Title": "A breathable, biodegradable, antibacterial, and self-powered electronic skin based on all-nullofiber triboelectric nullogenerators", + "Authors": "Peng, X; Dong, K; Ye, CY; Jiang, Y; Zhai, SY; Cheng, RW; Liu, D; Gao, XP; Wang, J; Wang, ZL", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Mimicking the comprehensive functions of human sensing via electronic skins (e-skins) is highly interesting for the development of human-machine interactions and artificial intelligences. Some e-skins with high sensitivity and stability were developed; however, little attention is paid to their comfortability, environmental friendliness, and antibacterial activity. Here, we report a breathable, biodegradable, and antibacterial e-skin based on all-nullofiber triboelectric nullogenerators, which is fabricated by sandwiching silver nullowire (Ag NW) between polylactic-coglycolic acid (PLGA) and polyvinyl alcohol (PVA). With micro-to-nullo hierarchical porous structure, the e-skin has high specific surface area for contact electrification and numerous capillary channels for thermal-moisture transfer. Through adjusting the concentration of Ag NW and the selection of PVA and PLGA, the antibacterial and biodegradable capability of e-skins can be tuned, respectively. Our e-skin can achieve real-time and self-powered monitoring of whole-body physiological signal and joint movement. This work provides a previously unexplored strategy for multifunctional e-skins with excellent practicability.", + "Times Cited, WoS Core": 715, + "Times Cited, All Databases": 735, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000543504100033", + "Markdown": "# M A T E R I A L S S C I E N C E \n\nXiao Peng1,2\\*, Kai Dong1,2\\*, Cuiying $\\boldsymbol{\\mathsf{Y}}\\boldsymbol{\\mathsf{e}}^{1,2}$ , Yang Jiang1,2, Siyuan Zhai3, Renwei Cheng1,2, Di Liu1,2, Xiaoping Gao4, Jie Wang1,2†, Zhong Lin Wang1,2,5† \n\n# A breathable, biodegradable, antibacterial, and self-powered electronic skin based on all-nanofiber triboelectric nanogenerators \n\nCopyright $\\circledcirc$ 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\nMimicking the comprehensive functions of human sensing via electronic skins (e-skins) is highly interesting for the development of human-machine interactions and artificial intelligences. Some e-skins with high sensitivity and stability were developed; however, little attention is paid to their comfortability, environmental friendliness, and antibacterial activity. Here, we report a breathable, biodegradable, and antibacterial e-skin based on all-nanofiber triboelectric nanogenerators, which is fabricated by sandwiching silver nanowire (Ag NW) between polylactic-co-­ glycolic acid (PLGA) and polyvinyl alcohol (PVA). With micro-to-nano hierarchical porous structure, the e-skin has high specific surface area for contact electrification and numerous capillary channels for thermal-moisture transfer. Through adjusting the concentration of Ag NW and the selection of PVA and PLGA, the antibacterial and bio­ degradable capability of e-skins can be tuned, respectively. Our e-skin can achieve real-time and self-powered monitoring of whole-body physiological signal and joint movement. This work provides a previously unexplored strategy for multifunctional e-skins with excellent practicability. \n\n# INTRODUCTION \n\nAs the largest organ of the body, human skin not only has the basic functions of protection, secretion, and respiration but also is an important somatosensory system for human to perceive, interact, and communicate with our physical world $(l{-}3)$ . Considerable interests have been stimulated to develop bioinspired e-skins by mimicking features and functionalities of natural skin that have broad applications in wearable individual-centered health monitoring (4–6), intelligent prostheses and robotics (7, 8), human-machine interfaces (9–11), and artificial intelligences (12, 13). On the basis of different physical sensing mechanisms, such as piezoresistivity, capacitance, piezoelectricity, and triboelectricity, e-skins are able to detect and quantify a diversity of environmental stimuli, including temperature, humidity, pressure, vibration, and haptics, through transforming them into real-time and visualized electronic impulses (7, 14–18). In particular, triboelectric nanogenerator (TENG) is a newly developed energy-harvesting technology that can convert ubiquitous mechanical energy into precious electricity based on the coupling effect of contact electrification and electrostatic induction (19–23). With the advantages of low cost, simple structure, easy to access, diverse material option, and high conversion efficiency, TENG has a broad application potential in both wearable power supplying and self-powered sensing, making it a promising candidate for energy autonomous e-skins (14, 24–26). \n\nIt is well known that flexibility, stretchability, sensitivity, ultraconformality, and mechanical durability are the most concerned and the most popular research directions of e-skins, which are also relatively easy to implement. Recently, aiming to improving the comprehensive performance of e-skins, special functionalities, such as recyclability (3), self-healing (27), shape memory (28), electro­ luminescence (29), and mechanoluminescence (30) are gradually added or integrated. Although the above aspects have been optimized and improved continuously, the comfort, safety, and health of e-skins are always neglected, which hinders their practical applications to a great extent. Therefore, the e-skins with desired comfortability and practicability must have the performance of breathability, biodegradability, and antibacterial activity. Breathability is an important means to adjust thermal-moisture balance and achieve gas exchange between the human body and the external environment (31, 32). However, most high-performance e-skins take the membranes as electrodes or substrates, which may cause skin discomfort and even induce inflammation and itching. In addition, considering that e-skins are excellent media for microorganism growth due to prolonged contact with human skin or unhealthy indoor air quality, antibacterial characteristic is a vital performance optimization for e-skins to inhibit bacterial growth and prevent bacterial infections (33–35). Furthermore, the majority of materials are not disposable, which may become electronic wastes at the end of their service life period and even harm the human body or pollute the environment (36–38). Nontoxic biodegradable electronics that can function over the prescribed time frames and then fully degrade into nonharmful constitutes without any adverse long-term side effects would reduce electronic waste disposal and environmental impact. Therefore, the performance optimization and large-scale practical application of e-skins should take the breathability, biodegradability, and antibacterial activity into account. \n\nHere, we designed a flexible, stretchable, breathable, biodegradable, and antibacterial e-skin on the basis of all-nanofiber TENGs for effective mechanical energy harvesting and whole-body physiological signal monitoring. By sandwiching the silver nanowire $(\\mathrm{AgNW})$ electrode between the top polylactic-co-glycolic acid (PLGA) triboelectric layer and the bottom polyvinyl alcohol (PVA) substrate, the allnanofiber TENG–based e-skin with multilayer interlaced nanofiber network and numerous three-dimensional micro-to-nano hierarchical pores provides high specific surface area for contact electrification and pressure sensing and multiple interfiber capillary channels for thermal-moisture transfer. The e-skin exhibits remarkable antibacterial activity against Escherichia coli and Staphylococcus aureus, which can effectively inhibit bacterial growth and prevent bacterial infections. In addition, the e-skin can regulate its service life period from hours to weeks through the selection and collocation of degradable PLGA and PVA. With the maximum peak power density of $130\\mathrm{mW}\\mathrm{m}^{-2}$ and the voltage response pressure sensitivity of $0.011\\mathrm{~kPa}^{-1}$ , the all-nanofiber TENG–based e-skin is able to realize the whole-body monitoring of physiological signal (e.g., microexpression, pulse, respiration, and vocalization) and joint movement (e.g., knuckle, elbow, knee, and ankle) in a real-time, noninvasive, and self-powered manner. Our work presents a comfortable, safe, and pollution-free e-skin with energy-harvesting and highly sensitive capability by integrating breathability, biodegradability, and antibacterial activity, which helps to promote more practical and environmentally friendly applications of e-skins in human-machine interface and artificial intelligence. \n\n# RESULTS Structural design and composition characterization of all-nanofiber TENG–based e-skin \n\nAs conceptually shown in Fig. 1A, the all-nanofiber TENG–based e-skin that integrates breathability, biodegradability, and antibacterial activity can be conveniently and conformally attached onto the epidermis. The e-skin consists of three functional layers, including the top PLGA for contact electrification and water proofing, the middle Ag NWs for conducting electrode and antibacterial agent, and the bottom PVA for flexible substrate and skin contact (Fig. 1B). According to the structural sequence, the e-skin is represented as the top layer/middle layer/down layer, for example, PLGA/Ag NWs/ PVA. The fabrication procedures of the e-skin are illustrated in fig. S1, which are further described in Materials and Methods in detail. Both PLGA and PVA nanofiber networks are prepared via a facile electrospinning strategy. Fourier transform infrared (FTIR) spectra of PLGA and PVA nanofibers indicate that their chemical compositions and structural characteristics will not change after electrospinning (fig. S2). The hydrophobic PLGA with contact angle of $115^{\\circ}$ can effectively prevent water from diffusing to the electrode, whereas the hydrophilic PVA (contact angle, $38^{\\circ}$ ) as a wicking layer can rapidly absorb heat and sweat from the body and timely diffuse to the outside. As displayed in fig. S3, the red water drops are well suspended on the PLGA surface while rapidly diffused to the surrounding on the PVA nanofiber film. Ag NWs with an average diameter of $167\\mathrm{nm}$ (fig. S4) are tangled together to form a continuous percolated network (lower right in Fig. 1B) on the top of the PVA nanofibers, which provide a continuous electron transport pathway with high conductivity and good mechanical flexibility. Numerous three-dimensional micro-to-nano hierarchical pores constructed by the multilayer stacking nanofiber networks endow the e-skin with high flexibility, appropriate stretchability, large specific surface area, outstanding breathability, and high structural stability. In addition, gas and water molecules can easily pass through interfiber capillary channels to adjust the thermal-moisture equilibrium of the microenvironment between human skin and outer environment. \n\nThe microstructural morphologies and diameter distributions of the PLGA and PVA nanofibers are optimized through adjusting the electrospinning parameters, such as solution concentrations, applied voltages, flow rates, and receiving distances (figs. S5 to S10). The optimum electrospinning conditions for the PLGA nanofibers are 8.5 weight $\\%$ (wt $\\%$ ), $15~\\mathrm{kV}$ , and $0.45~\\mathrm{ml/hour}$ , and those for the PVA nanofibers are 10 wt $\\%$ , $25\\mathrm{kV}$ , and $0.5~\\mathrm{ml}$ /hour. The surface morphologies of the optimized PLGA and PVA nanofibers observed by scanning electron microscopy (SEM) are shown in Fig. 1 (C and D), in which their corresponding average fiber diameters are 600 and $130~\\mathrm{nm}$ . The photographs of the prepared all-nanofiber e-skin are exhibited in Fig. 1E, indicating that it is ultralight $(80~\\mathrm{mg})$ ) and rather thin $(120~\\upmu\\mathrm{m})$ and can be conformally wound on complex curved surfaces and even be stretched to $100\\%$ strain level. The disordered interconnected nanofiber networks can be gradually oriented along the direction of external loads, providing good stretchability and excellent deformability for the e-skin. X-ray diffraction (XRD) analysis on different nanofiber films confirm that the $\\mathrm{Ag}$ element in $\\mathrm{Ag}$ NWs is not oxidized during long-term use (Fig. 1F). In addition, the excellent oxidation resistance of $\\mathrm{Ag}$ NWs is further verified after prolonged exposure to air and even a period of respiratory operation (fig. S11 and note S1). The cross-sectional (Fig. 1G) and surface (Fig. 1H) SEM images and corresponding energy-dispersive x-ray spectrometry (EDX) elemental mappings of the all-nanofiber e-skin confirm that the $\\mathrm{Ag}$ NW electrode is sandwiched between the top PLGA triboelectric layer and the bottom PVA substrate. In addition, uniform elemental distribution, continuous conductive network, and surface undulating texture can be also observed from these images. The fluctuation degree of nanofibers is characterized by atomic force microscopy (AFM), showing that there are obvious height gradients at the location of nanofibers (fig. S12). Because of the addition of Ag NWs, the thermal stability of the e-skin is also greatly improved compared with pure PLGA and PVA nanofiber films (fig. S13). \n\n# Stretchability, breathability, and electrical output performance \n\nFor electronics in direct contact with skin, the first concern is their wearability and comfortability, which mainly involve flexibility, stretchability, and air and moisture permeability. In addition to the excellent flexibility, as described above, the tensile properties of different nanofiber films are also evaluated by uniaxial tensile tests (fig. S14). Both the tensile strength and toughness of PLGA are higher than those of PVA, making it more suitable for surface packaging (Fig. 2A). The interface adhesion between Ag NWs and PVA nanofibers is helpful to improve the tensile strength of the $\\mathrm{AgNW{s/}}$ PVA nanofiber film. The asynchronous tensile fracture between PLGA and PVA results in the progressive failure behavior of the composite nanofiber film, leading to the degradation of mechanical properties of e-skins. However, the e-skin can meet the requirement of actual application, considering that the maximum strain tolerance of human arm skin is about $27\\%$ . In addition, the tensile capability of the e-skin can be further improved by choosing PLGA as both the triboelectric layer and the substrate. The electrode resistance of our e-skins at different tensile strain levels is measured (figs. S15 and S16) and further discussed (note S2). With the increase in tensile strain, the percolation network of $\\mathrm{Ag}$ NWs is first oriented along the stretching direction, then separated from each other, and lastly blocked with the fracture of the device (fig. S17). Therefore, the higher the tensile strain level is, the more obvious the increase in electrode resistance will be. Breathability represents the property of fabric to exchange air and moisture between skin and environment, which plays a vital role in regulating and maintaining the temperature and humidity balance of human surface microenvironment. The air permeabilities of different nanofiber films are also measured (fig. S18). There are numerous micro/nanopores in the multilayer stacked nanofiber network, making it easy for gas and water molecules to transport through interfiber channels. Although the addition of Ag NWs leads to the air permeability of e-skin lower than that of its single components even under the same thickness (Fig. 2B), the breathability of e-skin $(\\sim120\\ \\mathrm{mm\\s^{-1}})$ is still far higher than that of commercial jeans $(\\sim10\\:\\mathrm{mm}\\:s^{-1},$ ). In addition, the air permeability of e-skin decreases with the increase in nanofiber film thickness (Fig. 2B) but improves with the increase in pressure difference (Fig. 2C). Moreover, the increase in ambient humidity will weaken the air permeability of e-skin, which is due to that the dimensional swelling of fiber caused by moisture absorption leads to the reduction in porosity and part of the water will block the passage (fig. S19). Nevertheless, the air permeability remains $40\\ \\mathrm{mm\\s^{-1}}$ at the relative humidity of $80\\%$ . The microenvironment established between skin and environment is composed of numerous micro-to-nano hierarchical pores and crisscrossed interfiber channels, which can exchange and balance gas and water molecules timely, dynamically, and reversibly according to the internal and external conditions so as to achieve the thermal-moisture comfort of the human body (inserted in Fig. 2C). Here, the thermal-moisture stability and comfortability of the all-­nanofiber e-skin are further discussed in note S3. \n\n![](images/b93da14a39f42133a0bdcccb54e42c7340482ae38d6730d69f4b1d2f678e7421.jpg) \nFig. 1. Structural design and composition characterization of the all-nanofiber TENG–based e-skin. (A) Application scenario of the breathable, biodegradable, and antibacterial e-skin that can be conveniently and conformally attached onto the epidermis. (B) Schematic illustration of the three-dimensional network structure of the all-nanofiber TENG–based e-skin. The images of the water contact angle and molecular structure of PLGA and PVA are inserted on the top left and lower left, respectively. The surface scanning electron microscopy (SEM) image of the Ag NW electrode is inserted on the lower right (scale bar, $2\\upmu\\mathrm{m})$ ). (C and D) Optimized surface morphology SEM images of (C) PLGA (scale bar, $10\\upmu\\mathrm{m}\\mathrm{;}$ ) and (D) PVA (scale bar, $2\\upmu\\mathrm{m};$ ) nanofiber films, in which their respective diameter distributions are shown in the upper right. (E) Photograph images of the e-skin with total thickness of $120\\upmu\\mathrm{m}$ that can be wound onto a glass rod and stretched to $100\\%$ strain level. (F) Comparison of x-ray diffraction (XRD) profile among different nanofiber films. a.u., arbitrary units. (G) Cross-sectional (scale bars, $50\\upmu\\mathrm{m};$ ) and (H) surface morphology (scale bars, $20\\upmu\\mathrm{m};$ SEM images of the all-nanofiber TENG–based e-skin with energy-dispersive $\\mathsf{x}$ -ray spectrometry (EDX) elemental mappings. Photo credit: X.P., Beijing Institute of Nanoenergy and Nanosystems. \n\nOur all-nanofiber TENG–based e-skin will operate in a singleelectrode mode when the inner $\\mathrm{Ag}$ NW electrode is grounded through external resistance. The electricity generation and transmission mechanism of the TENG-based e-skin are illustrated in fig. S20, which is realized by the periodic contact and separation movements between the e-skin and its contact object. The induced potential difference between the inner electrode and the ground will cause charge transfer between them and then generate an instantaneous current. As a result, a contact-separation process between the e-skin and the contact object will generate an alternating potential and current through external loads. The detailed explanations of the working mechanism of the e-skin are conducted in note S4. In addition, a finite element analysis was established by using COMSOL Multiphysics to observe the potential distribution of every component in the e-skin from full contact to complete separation (fig. S21). The electrical output capability of TENGs is often reflected by the open-circuit voltage $(V_{\\mathrm{OC}})$ , short-circuit current $(I_{\\mathrm{SC}})$ , and charge transfer $(Q_{\\mathrm{SC}})$ . The corresponding electrical outputs of the two kinds of e-skins (PLGA/Ag NWs/PVA and PVA/Ag NWs/PVA) were measured with polytetrafluoroethylene (PTFE) film $\\left(0.1\\mathrm{-mm}\\right)$ thickness) as the contact material under the loading frequencies from 1 to $5\\mathrm{Hz}$ (Fig. 2, D to F, and fig. S22). It is found that the $V_{\\mathrm{OC}}$ and $Q_{\\mathrm{SC}}$ are approximately stable, but the $I_{\\mathrm{SC}}$ presents a growth trend. The inconsistent variation of electrical output characteristics with loading frequency is explained in fig. S23 and note S5 (39). Taking PTFE film as the counter friction layer, PLGA/Ag NWs/ PVA e-skin has slightly higher electrical output than $\\mathrm{PVA}/\\mathrm{AgNWs}/$ PVA e-skin, which can be attributed to the higher electron transfer quantity of PLGA than that of PVA (note S6) (40, 41). At the applied frequency of $3\\:\\mathrm{Hz}$ , the electrical output performance of our e-skins is further measured by connecting varied external resistances in series. As the value of resistance increases, the current density tends to decrease, but the voltage shows an upward trend, which is ruled by Ohm’s law (Fig. 2G). Moreover, the voltage and current output of the PLGA/Ag NWs/PVA e-skin are higher than those of the PVA/Ag NWs/PVA e-skin within the whole resistance range. The power density was calculated as \n\n![](images/8de6102544e351688e7a5ec85515749f5c7c43e85025b9aa76b1fb71d8c5a65c.jpg) \nFig. 2. Stretchability, breathability, and electrical output performance. (A) Uniaxial tensile stress-strain behaviors of PVA, Ag NWs/PVA, PLGA, PLGA/Ag NWs/PVA, and PLGA/Ag NWs/PLGA nanofiber films. (B) Thickness dependence of the air permeability of PVA, PLGA, and PLGA/Ag NWs/PVA nanofiber films. (C) Differential pressure response to the air permeability of PLGA/Ag NWs/PVA nanofiber films. The diagram of the air and moisture flow directions in the microenvironment between human skin and outer environment is inserted. (D to F) Frequency-response characteristics of the PLGA/Ag NWs/PVA e-skin, including (D) $V_{\\mathrm{OC}},\\left(\\mathsf{E}\\right)I_{\\mathsf{S C}},$ and (F) $\\boldsymbol{Q}_{\\mathsf{S C}},$ . (G and H) Comparison of (G) output voltage and current density, as well as (H) peak power density between the PLGA/Ag NWs/PVA and the PVA/Ag NWs/PVA e-skins under varied external resistances. (I) Analysis of charging performance between the two e-skins under different capacitance capacities. (J) Thickness-dependent charge output densities of the e-skin. Only the thickness of PLGA is varied, while that of Ag NWs/PVA is fixed. (K) Normalized output voltage response to a wide range of pressure. (L) Voltage response of the e-skin with relative contact-separation motion to different materials. \n\n$$\nP=I^{2}R/A\n$$ \n\nwhere $I$ is the output current under the corresponding resistance $R,$ and $A$ is the effective contact area. The maximum areal power density of the PLGA/Ag NWs/PVA e-skin is ${\\sim}130\\ \\mathrm{mW}\\ \\mathrm{m}^{-2}$ at a matched resistance of $\\sim500$ megohms, which is four times more than that of the PVA/Ag NWs/PVA e-skin (Fig. 2H). The charging capability of the e-skins to different commercial capacitors is also analyzed and compared (Fig. 2I). The result shows that charging speeds accelerate with the increase in capacitances. For example, the voltage of the $1{-}\\upmu\\mathrm{F}$ capacitor can reach $22{\\mathrm{~V~}}$ , while that of the $47{\\cdot}\\upmu\\mathrm{F}$ capacitor is only $2\\mathrm{~V~}$ after charging for $50~\\mathrm{s}$ . Moreover, the charging ability of the PVA/Ag NWs/PVA e-skin is obviously weaker than that of the PLGA/Ag NWs/PVA e-skin at the same charging time. The remarkable power output ability of the e-skin makes it a promising candidate in the field of wearable power supply and self-powered sensors in the future. \n\nThe impact of nanofiber film thickness on the electricity-generating capability of e-skin is also discussed (Fig. 2J). It is worth noting that only the thickness of the PLGA triboelectric layer is varied, whereas those of the PVA substrate and the Ag NW electrode are fixed. The increase in triboelectric layer thickness is not only beneficial to fully contact with outer objects but also can reduce the charge leakage caused by electrode exposure. The pressure sensitivity of our e-skin is measured over a large pressure range (Fig. 2K). The pressure sensitivity of the e-skin is defined as the slope of normalized voltage versus pressure curve, i.e. \n\n$$\nS=d(\\Delta V/V_{\\mathrm{{S}}})/d P_{\\mathrm{{F}}}\n$$ \n\nwhere $\\Delta V$ is the relative change in voltage, $V_{\\mathrm{{S}}}$ is the saturation voltage, and $P_{\\mathrm{F}}$ is the applied pressure. The e-skin exhibits almost a linear relationship within a pressure of $40\\mathrm{{kPa}}$ , with a voltage response pressure sensitivity of $\\mathsf{\\Lambda}_{0.011\\mathrm{kPa}}^{-1}$ . The contact electrification ability of our e-skin response to different contact materials is also investigated. The amplitude and polarization of $V_{\\mathrm{OC}}$ depend on the relative ability of a material to lose or gain electrons when contacting with the e-skin. Compared with PLGA, all the latex, polymethyl methacrylate, aluminum (Al), polyethylene terephthalate (PET), kapton, and PTFE are tending to gain electrons and, therefore, are more tribo-negative, whereas nylon and cotton are more tribo-positive (Fig. 2L). The larger the difference in the ability of losing/gaining electrons between two contacting materials, the more electrostatic charges generate at the interface and thus the higher output $V_{\\mathrm{OC}}$ . Moreover, the mechanical durability of the e-skin was verified for 50,000 cycles of repeated loading-unloading under the pressure of $40\\mathrm{N}$ and the frequency of $3\\:\\mathrm{Hz}$ (fig. S24). The voltage profile displays no noticeable fluctuation during the repetitive pushing tests, confirming that the performance of our e-skin is stable for long-term service. \n\n# Antibacterial and biodegradable test \n\nOn account of the e-skin being placed directly on the upper epidermis of the human body, its antimicrobial activity is extremely important. Silver exhibits a broad-spectrum biocidal property against specific bacteria, fungi, and viruses, making it the most promising antimicrobial agent for a wide range of medical application. Here, the antibacterial activities of the all-nanofiber TENG–based e-skins against two typical bacteria, i.e., gram-negative E. coli and gram-positive S. aureus (fig. S25), were determined by the commonly used zone of inhibition and colony count methods. For the zone of inhibition method, the diameter of the bacteriostatic zone represents the antibacterial ability. The diameters of the zone of inhibition against $E$ . coli and S. aureus for the PLGA/Ag NWs/PVA nanofiber film were 10 and $12\\mathrm{mm}$ , respectively, whereas the pure PVA and PLGA nanofiber films with an initial diameter of $8~\\mathrm{mm}$ show no antibacterial properties against both bacteria (Fig. 3, A and C, and fig. S26). The colony count method is further adopted to investigate the bactericidal efficacy of samples through the concentration of the survival colony bacteria in solution. After 24-hour incubation, the residual colonies for both E. coli and S. aureus on the agar petri dish are obviously less than the original (Fig. 3B). In addition, the bactericidal efficacy or killing efficiency for $E$ . coli and S. aureus achieves up to 54 and $88\\%$ , respectively (Fig. 3C). The results from the zone of inhibition and colony count experiments indicate that our e-skin with $\\mathrm{Ag}\\mathrm{NW}$ electrode has good antibacterial performance. It should be noted that antimicrobial properties can be improved gradually with the increase in $\\mathrm{Ag}\\mathrm{NW}$ additive amount. The main antibacterial mechanism of our e-skin involves the release of silver ions that change the respiration or permeability of cell films, then penetrate into the bacteria, and continue to destroy by possibly interacting with the thiol groups of cellular proteins (42, 43). \n\nBiodegradation is another major property of our e-skin, which enables it to function over prescribed time frames and then physically degrade into nonharmful constituents. PLGA and PVA are wellknown synthetic biodegradable materials, which can decompose over a period of time. For comparison purpose, the in vitro biodegradation tests of several types of nanofiber films were studied for 50 days, including PVA, PLGA, Ag NWs/PVA, PVA/Ag NWs/ PVA, and PLGA/Ag NWs/PVA. The variations of their photographs and weight loss under corresponding degradation periods were recorded (Fig. 3, D and E, and fig. S27). The results showed that PVA presented rapid autocatalytic hydrolysis and bulk degradation after 3 days of incubation, whose weight loss was up to $90\\%$ . Moreover, it almost completely disappeared after 30 days of degradation. In contrast, the degradation cycle of the Ag NWs/PVA nanofiber film was slightly longer, because the existence of Ag NWs improved the impregnation resistance. The degradation morphologies and weight loss of the Ag NWs/PVA and PVA/Ag NWs/PVA nanofiber films were highly similar, which further verified the rapid hydrolysis ability of PVA. In contrary to PVA, PLGA has a strong resistance to weight loss and water absorption in the initial stage (0 to 21 days), but slightly shrinks and curls due to hydrolytic cleavage of the polymer backbone (fig. S28) (40, 44). However, the degradation process of PLGA will be greatly accelerated after incubation over 30 days. Concurrently, crack appears on the surface of the PLGA nanofiber film and its density increases as the degradation time continues (Fig. 3F and fig. S28). In addition, the degradation time of our e-skin is adjustable based on the thickness of the PLGA or PVA film (fig. S29). Under the same thicknesses of the PLGA film and Ag NW layer, the weight loss of the PLGA/Ag NWs/PVA film increases with the increase in PVA film thickness. However, for the fixed thickness of the Ag NWs/PVA layer, the weight loss of the PLGA/ Ag NWs/PVA film decreases first (before degradation of 21 days) \n\n![](images/c138242f24d23531d260a9e580184b21bea7423ff94299357e6078fdebfa404c.jpg) \nFig. 3. Antibacterial activity and biodegradation process. (A) Photographs of inhibition zone of (i) PVA, (ii) PLGA, and (iii) PLGA/Ag NWs/PVA nanofiber films before (left) and after (right) 24-hour incubation. (B) Photographs of colonies of S. aureus and E. coli before and after coculturing for 24 hours. (C) Diameter of inhibition zone and antibacterial efficiency of the PLGA/Ag NWs/PVA nanofiber film after 24-hour incubation. (D) Sequential photographs of in vitro biodegradation of (i) PVA, (ii) Ag NWs/ PVA, and (iii) PLGA/Ag NWs/PVA nanofiber films in phosphate-buffered saline (PBS) solutions (scale bar, 1 cm). (E) Weight loss rates of different nanofiber films within the degradation period of 50 days. (F) Surface morphology SEM images of the PLGA nanofiber film before (top) and after (bottom) the 50-day degradation (scale bars, $5\\upmu\\mathrm{m}_{\\cdot}^{\\cdot}$ ). Photo credit: X.P., Beijing Institute of Nanoenergy and Nanosystems. \n\nand then increases with the increase in PLGA film thickness. The detailed discussion is presented in note S7. Combining the rapid degradation of PVA and the slow degradation of PLGA, the PLGA/ Ag NWs/PVA shows moderate biodegradability. Although this unsynchronized degradation process may weaken the service performance of our e-skin, it can be well tuned by selecting the same materials as both the triboelectric layer and the substrate. Please note that although human sweat will weaken the electrical output ability of our e-skin (fig. S30), the PVA film can keep its structure stable without deformation, contraction, dissolution, or damage even at the maximum amount of human sweat (fig. S31) (45). It is also worth noting that the biodegradation of our e-skin has a notable negative impact on its electrical output performance, and the decline trend is more obvious as the degradation time continues (fig. S32), which can help us to better play the functions of our e-skin by mastering its gradual power attenuation ability. \n\n# Whole-body physiological and motion monitoring \n\nThe human body is a multisensory system with unique physiological signal characteristics for different parts. On the basis of the excellent pressure sensitivity and conformal ability, our e-skins are able to monitor various forms of human physiological signals for medical diagnosis and disease prevention in a rapid, real-time, noninvasive, and user-interactive way. Considering that a conformal and intimate contact between the e-skin and the human skin is paramount for subtle monitoring, the e-skins are conformally attached on the corresponding body parts with the aid of biocompatible medical bandages (Fig. 4A). All of these physiological data may have great clinical significance in modern medical diagnosis. Frowning, blinking, smiling, and other facial expressions are the most intuitive platforms to convey human emotions and are also the main external communication channels for general paralyzed patients. By sticking an e-skin on the forehead, regular and repeatable voltage signals are monitored during normal and frown alternating movements (Fig. 4B). Tiny muscle movements caused by microexpression can be easily captured by the voltage signal variations. Subtle voltage signals induced by blinking can also be collected by mounting an e-skin on the eyelid (Fig. 4C). Moreover, the differences of frequency and amplitude between normal blinking and rapid blinking can also be distinguished. Respiration is a primary vital sign that helps to assess health conditions, such as sleep quality and mood change, which can be reflected by the flow of breath, or the expansion and contraction of the chest and abdomen during inhalation and exhalation (46). To detect the flow of breath, the e-skin was placed on the vent of a conventional mask that could respond to the voltage signal changes during repeated oral breathing (Fig. 4D). Typically, one complete breathing cycle involves inhalation and exhalation, which generates an ascending and a descending voltage signal, respectively. More comprehensive respiratory information was obtained by situating the e-skin at the part of the chest or abdomen. The repeatable respiratory pattern from the abdomen was recorded with four distinctive breathing states including normal (shallow), slow, rapid, and deep (Fig. 4E). \n\nThe heart rate or pulse is often used as one of the critical vital signs to assess the physical and mental state of a person, which can be measured from the radial artery at the wrist or from the carotid artery at the neck. The real-time radial artery pulse signals with regular and repeatable shape are recorded in $15\\mathrm{~s~}$ by the e-skin when it is attached to a wrist as a pulse detector, indicating the frequency of 84 beats/min (Fig. 4G). In addition, a typical wrist pulse waveform is extracted with three characteristic peaks containing $\\mathrm{{^\\circP^{\\circ}}}$ (percussion wave), “T” (tidal wave), and “D” (diastolic wave), which are related to the systolic and diastolic blood pressure, the ventricular pressure, and the heart rate (47). In comparison to the radial artery pulse, the jugular venous pulse (JVP) can provide more valuable information for diagnosing heart diseases. As shown in Fig. 4F, the pulse frequency of the subject is 87 beats/min, which is consistent with the result of the radial artery pulse test. Similarly, a typical JVP waveform comprises three characteristic peaks, i.e., $^\\alpha\\mathrm{A}^{\\prime\\prime}$ (atrial systole), $^{\\mathfrak{c}}\\mathrm{C}^{\\mathfrak{n}}$ (tricuspid bulging), and $\\ensuremath{\\mathrm{^{\\alpha}v^{\\alpha}}}$ (systolic filling of the atrium), and two descents, i.e., $\\mathrm{^{*}X^{\\mathfrak{n}}}$ (atrial relaxation) and $\\mathrm{^{\\alpha}Y^{\\alpha}}$ (early ventricular filling) (48). The pulse frequency detected from the radial artery and JVP match well with those of normal adults. Voice recognition was achieved by conformally attaching the e-skin onto the throat to distinguish different words or phrases, such as “energy,” “energy harvesting,” “nano,” and “nanogenerator” (Fig. 4H). Each word was recorded four times, and similar voltage signal characteristics for each curve can be seen, indicating the good repeatability for voice recognition. In addition, good consistency of voltage signal characteristics can be maintained between a word and its extended phrases (Fig. 4I and fig. S33). The ability of voice recognition might be useful for people with damaged vocal cords to rehabilitate their speech ability by training to control their throat muscle movement, which can also promote the implementation of remote human-machine interaction and control (49). \n\n![](images/33fca0074c7f667133c3a0dc2e82f0e031f27f0967f8212ddba2bb568d744446.jpg) \nFig. 4. Whole-body monitoring of physiological signal and joint movement. (A) Schematic illustration of a human body model with the detected parts marked with black solid circles. The photographs of corresponding detection parts in human body are also inserted. (B) Voltage response to the frown movement by attaching an e-skin on the forehead. (C) Monitoring of blinking behaviors by attaching an e-skin on the eyelid. (D) Normal oral breathing state monitoring by integrating an e-skin on a dust mask. The voltage signal during a single cycle of inhaling and exhaling is inserted. (E) Abdominal respiratory monitoring by pasting an e-skin on the human belly, including shallow (normal), slow, rapid, and deep. (F) Generated voltage signals in response to the jugular venous pulse (JVP) from the neck. A complete waveform is enlarged in the upper right. (G) Real-time monitoring of the radial artery pulse by attaching an e-skin to the wrist. The right enlarged is one complete radial artery pulse waveform containing $\"\\mathsf{P},\"\\mathrm{\\Delta}\\mathsf{T},\"$ and $\"\\mathsf{D}^{\\prime\\prime}$ peaks. (H) Sound and speech pattern recognition by mounting an e-skin on a volunteer’s throat to detect his vocal cord vibrations. (I) Enlarged voltage signals from (H) for the analysis of repeatability, continuity, and stability. The regions marked with blue, yellow, and pink represent the voltage signals generated by the pronunciation of $^{\\prime\\prime}{\\sf e},^{\\prime\\prime}\\stackrel{\\prime\\prime}{\\sf n}{\\sf o},^{\\prime\\prime}$ and “dʒi,” respectively. (J) Detection of the finger bending angles by attaching an e-skin to the knuckle. (K) Detection of the arm flexion by attaching an e-skin to the elbow. (L) Detection of the leg swing angles by attaching an e-skin to the knee. (M) Detection of the foot movement states by fixing an e-skin on the heel. Note that all units of the abscissa are times. Photo credit: X.P., Beijing Institute of Nanoenergy and Nanosystems. \n\nOur e-skin not only exhibits a remarkable response to the above subtle skin-level detections but can also track small bending movements of major joints, such as the knuckle, elbow, knee, and ankle. For example, the e-skin was fixed on the lateral knuckle of the index finger to record the voltage response under the bending-releasing cycles, with the bending angle from 30° to $120^{^{\\circ}}$ (Fig. 4J). Similar motion angle detections of the elbow (Fig. 4K) and the knee (Fig. 4L) were realized by adhering the e-skins on corresponding joints (bent and straightened to varying degrees). The voltage signals exhibit superior reproducibility under a certain joint bending angle, which confirms the excellent working stability and reliability of the e-skins. The slight difference in the output frequency of voltage signals is due to the inconsistency of the motion behaviors. The increase in voltage outputs at a large bending angle is attributed to the increase in contact area between the e-skin and the joints. The recognition and control of joint motion angle are helpful to realize the real-time and remote operation of robot movement, which, in turn, promotes the development of human-machine interaction and artificial intelligence. The human movement state is an important index to evaluate exercise intensity, which can be monitored by installing the e-skin on the ankle. As shown in Fig. 4M, there are notable differences in the amplitude and frequency of the generated voltage signals, which can well distinguish walking from running. From these demonstrations, it can be found that various physiological characteristics and movement behaviors can be transformed into readable, quantized, and real-time voltage signals through our e-skins, which is beneficial to realize parallel and whole-body physiological and motion monitoring. Therefore, it is expected that our e-skins will have promising applications in the fields of personal health monitoring, rehabilitation of patients, athletic performance monitoring, and human motion tracing for entertainments. \n\n# DISCUSSION \n\nThe seamless integration of excellent electrical responses and diversified practical functions is a major breakthrough in the development of e-skins. Here, a flexible, stretchable, conformal, and energy autonomous all-nanofiber TENG–based e-skin with special functions such as high sensitivity, breathability, biodegradability, and antibacterial activity has been developed for the detection of physiological characteristics and movement states of the whole body. The allnanofiber intercross network designed by sandwiching Ag NW electrode between the top PLGA triboelectric layer and the bottom PVA substrate contributes to the formation of a three-dimensional micro-to-nano porous hierarchical structure, which not only provides high specific surface area for contact electrification and pressure response but also ensures the thermal-moisture balance and wearing comfort of the surface skin microenvironment. Because of the biocidal property of $\\mathrm{Ag}$ NWs, the e-skin shows remarkable antibacterial effect on $E.$ . coli and S. aureus. The service life of the e-skin can also be tuned from hours to weeks based on the selection and collocation of biodegradable PLGA and PVA. In addition, the e-skin based on the single electrode mode TENG has a maximum matching peak power density of $130\\mathrm{mW}\\mathrm{m}^{-2}$ and a voltage response pressure sensitivity of $0.0\\dot{1}1\\mathrm{~kPa}^{-1}$ , which enables it to realize the whole-body physiological signal monitoring such as blinking, pulsing, speaking, and respiring, and major joint motion detections, including knuckle, elbow, knee, and ankle. On the basis of the merits of highly sensitive self-powered electrical responses, diversified practical functions, and remarkable human/environmental friendliness, the e-skin can assist the human body to navigate our physical world with ease. Although there are some aspects of the e-skin that need to be further optimized and improved, such as the asynchronous mechanical and degradation properties of its components, and the potential impact of humidity (e.g., human sweat) and pollutants, they can promote the research of e-skins to pay more attention to their practicability, such as comfortability, environmental friendliness, and antibacterial property while pursuing their high mechanical stability and high sensing sensitivity. \n\n# MATERIALS AND METHODS Materials \n\nPVA $(M_{\\mathrm{w}}=89,000$ to 98,000; $99\\%$ hydrolyzed) was obtained from Sigma-Aldrich Chemical Co. Ltd. PLGA (75:25, $M_{\\mathrm{w}}=66,000$ to 107,000) and hexafluoro-2-propanol (HFIP) were purchased form Aladdin Chemical Co. Ltd. Ag NW solution with an average diameter of $160~\\mathrm{{nm}}$ was provided by Nanjing XFNANO Materials Tech Co. Ltd. Deionized (DI) water was used in all of the experiments. All purchased chemicals were of analytical purity. \n\n# Fabrication of all-nanofiber e-skin \n\n(i) Water-soluble PVA precursor was dissolved in DI water at concentrations ranging from 8 to 11 wt $\\%$ , and then stirred for about 2 hours at $90^{\\circ}\\mathrm{C}$ . It was placed in a plastic syringe equipped with a 20-gauge metal needle. The collector covered with aluminum foil was placed $15\\ \\mathrm{cm}$ from the needle. The applied electric potentials ranging from 25 to $28\\mathrm{kV}$ were applied by a high-voltage supply at the tip of the syringe needle. The PVA solution was subsequently electrospun at a constant flow rate. The electrospun PVA nanofibers were collected on aluminum foils positioned at a certain distance away from the injector nozzle. After electrospinning, PVA meshes were dried overnight under vacuum at room temperature to remove the residual water and then carefully peeled off from the aluminum foil. (ii) The PVA/Ag NW film was obtained by a vacuum filtration method. A piece of PVA nanofiber scaffold with the PET frame was used as a filtration film, and a diluted $\\ensuremath{\\mathrm{Ag}}\\ensuremath{\\mathrm{NW}}$ dispersion was poured onto the PVA scaffold and vacuum filtrated by a sucking pump. A piece of copper foil was attached to the surface as the lead-out electrode. (iii) PLGA was dissolved in HFIP using a magnetic stirrer with concentrations ranging from 6.5 to 9.5 wt $\\%$ for 12 hours. PLGA solution was fed into a plastic syringe fitted with a 23-gauge stainless steel blunt needle. The injection rate was adjusted from 0.3 to $1.0\\mathrm{ml}$ /hour. High voltage (9 to $18\\mathrm{kV}$ ) was applied to the needle tip until a fluid jet was ejected. The aluminum foil covered with a $\\mathrm{PVA/Ag}$ NW nanofiber film was used as the collector. The distance between the needle tip and the collector was fixed at $15\\mathrm{cm}$ . The PLGA nanofiber scaffold was dried overnight under vacuum at room temperature. \n\n# Antibacterial test \n\nThe zone of inhibition is a clear area of interrupted growth underneath and along sides of the test material and indicates the bioactivity of the specimen on the basis of American Association of Textile Chemists and Colorists (AATCC 147). It is a qualitative test for the bacteriostatic activity by the diffusion of antibacterial agent through agar. The bacterial strains of gram-negative E. coli (CGMCC 1.8723) and gram-positive S. aureus (CGMCC 1.2155) used in this study were obtained from China General Microbiological Culture Collection Center (CGMCC). In particular, glassware, suction nozzles, and culture medium were sterilized in an autoclave at a high pressure of 0.1 MPa and a temperature of $120^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ before experiments. After cultivation in sterilized Luria-Bertani (LB) broth and then incubation at $37^{\\circ}\\mathrm{C}$ with a shaking incubator for 24 hours, both $E$ . coli and S. aureus colonies were completely distributed on the empty agar plate (fig. S25). The concentration of bacterial suspensions was ${10}^{8}$ colony-forming units $(\\mathrm{CFU})/\\mathrm{ml}$ throughout the antibacterial testing. The zone of inhibition method was performed on the basis of the modified Kirby-Bauer method. The PVA, PLGA, and PLGA/Ag NWs/PVA nanofiber films were made into discs, with diameters of approximately $8\\mathrm{mm}$ by using a hydraulic pressure and placed on the $E_{\\sun}$ . coli and S. aureus growth agar plates. The colony count method or the kinetic test was usually used to estimate antibacterial properties through the concentration of the survival colonies bacteria in cocultured solution. First, original bacterial suspensions were washed three times with phosphate-buffered saline (PBS; $\\mathrm{pH}7.4,$ ) solution to a concentration of $\\mathrm{i0^{8}C F U/m l}$ . Then, our samples were poured into the washed culture medium and incubated in a shaking bath for 1 hour. Third, the incubated solution was diluted five times to a certain concentration. The resulting bacterial PBS suspensions $(100~\\upmu\\mathrm{l})$ were spread on gelatinous LB agar plates, culturing at $37^{\\circ}\\mathrm{C}$ for 24 hours. The number of survival colonies was counted manually. The tests were repeated three times for each bacteria. \n\n# In vitro biodegradation test \n\nFive types of nanofiber films were prepared for biodegradation tests, which are PVA, PLGA, Ag NWs/PVA, PVA/Ag NWs/PVA, and PLGA/ $\\mathrm{AgNWs/PVA}$ . The dimensions of all the samples were fixed as $2\\mathrm{cm}$ by $2\\mathrm{cm}$ . Each sample was put in a $50\\mathrm{-ml}$ centrifuge tube, which was then filled with $30~\\mathrm{ml}$ of PBS $\\mathrm{(pH}7.4\\mathrm{)}$ solution. The PBS was autoclaved before use. Afterward, the tubes were placed in an incubator on a shaker table at $100~\\mathrm{rpm}$ at $37^{\\circ}\\mathrm{C}$ . The PBS buffer was refreshed weekly. To measure the weight change of samples for various periods (3, 10, 14, 21, 30, 40, and 50 days), samples were taken out from the PBS solution, then rinsed with DI water to remove the residual PBS solution, and dried in a vacuum oven at room temperature overnight. The weight loss in percentage was calculated according to a simple equation, i.e., weight loss $(\\%)=\\left(W_{0}-W_{\\mathrm{n}}\\right)/W_{0}\\times100$ , where $W_{0}$ is the initial weight and $W_{\\mathrm{n}}$ is the weight at a given degradation days. \n\n# Characterizations and measurements \n\nThe surface morphology and elemental component of the e-skin were characterized by field emission scanning electron microscope (Hitachi SU8020) equipped with EDX. The static water contact angle of the nanofiber films was performed by a contact angle analyzer (SL200B, Kino). The surface roughness of the e-skin was measured by AFM (Bruker, USA). The thermal stability of the nanofiber films was performed by thermogravimetric analysis (Pyris). XRD (Xper3 power) was used to characterize the crystalline structure of samples. An FTIR (VERTEX80v, Brucker) spectrometer was used to measure the infrared spectra of samples. Mechanical tensile behaviors were conducted using an ESM301/Mark-10 tester under a constant speed of $10\\mathrm{mm}s^{-1}$ . The TENG-based e-skin was driven by a linear motor (Linmot E1100) for electrical measurement. A programmable electrometer (Keithley, model 6514) was used to test the open-circuit voltage, short-circuit current, and transferred charges. The software platform was constructed on the basis of LabVIEW. The applied force on the e-skin was measured by a compression dynamometer (Vernier LabQuest Mini). The thickness of the nanofiber film was measured by a thickness tester (CHY-CA, PARAM). The air permeability was measured by using an air permeability apparatus (YG461E, Wenzhou Fangyuan Instrument Co. Ltd., China) according to the ASTM D 737-75 standard test method under varied pressure drops. \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi content/full/6/26/eaba9624/DC1 \n\nREFERENCES AND NOTES .\t X. Yu, Z. Xie, Y. Yu, J. Lee, A. Vazquez-Guardado, H. Luan, J. Ruban, X. Ning, A. Akhtar, D. Li, B. Ji, Y. Liu, R. Sun, J. Cao, Q. Huo, Y. Zhong, C. M. Lee, S. Y. Kim, P. Gutruf, C. Zhang, Y. Xue, Q. Guo, A. Chempakasseril, P. Tian, W. Lu, J. Y. Jeong, Y. J. Yu, J. Cornman, C. S. Tan, B. H. Kim, K. H. Lee, X. Feng, Y. Huang, J. A. Rogers, Skin-integrated wireless haptic interfaces for virtual and augmented reality. Nature 575, 473–479 (2019). 2.\t S. Wang, J. Xu, W. Wang, G.-J. N. Wang, R. Rastak, F. Molina-Lopez, J. W. Chung, S. Niu, V. R. Feig, J. Lopez, T. Lei, S.-K. Kwon, Y. Kim, A. M. Foudeh, A. Ehrlich, A. Gasperini, Y. Yun, B. Murmann, J. B.-H. Tok, Z. Bao, Skin electronics from scalable fabrication of an intrinsically stretchable transistor array. Nature 555, 83–88 (2018). 3.\t Z. Zou, C. Zhu, Y. Li, X. Lei, W. Zhang, J. Xiao, Rehealable, fully recyclable, and malleable electronic skin enabled bydynamic covalent thermoset nanocomposite. Sci. Adv. 4, eaaq0508 (2018). 4.\t T. Q. Trung, N. E. Lee, Flexible and stretchable physical sensor integrated platforms for wearable human-activity monitoringand personal healthcare. Adv. Mater. 28, 4338–4372 (2016). 5.\t X. Wang, Y. Gu, Z. Xiong, Z. Cui, T. Zhang, Silk-molded flexible, ultrasensitive, and highly stable electronic skin for monitoring human physiological signals. Adv. Mater. 26, 1336–1342 (2014). 6.\t Y. Zhang, T. H. Tao, Skin-friendly electronics for acquiring human physiological signatures. Adv. Mater. 31, e1905767 (2019). 7.\t K. Dong, Z. Wu, J. Deng, A. C. Wang, H. Zou, C. Chen, D. Hu, B. Gu, B. Sun, Z. L. Wang, A stretchable yarn embedded triboelectric nanogenerator as electronic skin for biomechanical energy harvesting and multifunctional pressure sensing. Adv. Mater. 30, 1804944 (2018). \n8.\t A. Chortos, J. Liu, Z. Bao, Pursuing prosthetic electronic skin. Nat. Mater. 15, 937–950 (2016). 9.\t C. Wang, D. Hwang, Z. Yu, K. Takei, J. Park, T. Chen, B. Ma, A. Javey, User-interactive electronic skin for instantaneous pressure visualization. Nat. Mater. 12, 899–904 (2013). \n10.\t K. Dong, J. Deng, W. Ding, A. C. Wang, P. Wang, C. Cheng, Y.-C. Wang, L. Jin, B. Gu, B. Sun, Z. L. Wang, Versatile core-sheath yarn for sustainable biomechanical energy harvesting and real-time human-interactive sensing. Adv. Energy Mater. 8, 1801114 (2018). 11.\t Y.-C. Lai, J. Deng, R. Liu, Y.-C. Hsiao, S. L. Zhang, W. Peng, H.-M. Wu, X. Wang, Z. L. Wang, Actively perceiving and responsive soft robots enabled by self-powered, highly extensible, and highly sensitive triboelectric proximity- and pressure-sensing skins. Adv. Mater. 30, 1801114 (2018). \n12.\t Y. Zang, F. Zhang, C.-a. Di, D. Zhu, Advances of flexible pressure sensors toward artificial intelligence and health care applications. Mater. Horiz. 2, 140–156 (2015). \n13.\t K. Dong, X. Peng, Z. L. Wang, Fiber/fabric-based piezoelectric and triboelectric nanogenerators for flexible/stretchable and wearable electronics and artificial intelligence. Adv. Mater. 32, 1902549 (2019). \n14.\t X. Wang, L. Dong, H. Zhang, R. Yu, C. Pan, Z. L. Wang, Recent progress in electronic skin. Adv. Sci. 2, 1500169 (2015). \n15.\t Y. Lee, J. Park, A. Choe, S. Cho, J. Kim, H. Ko, Mimicking human and biological skins for multifunctional skin electronics. Adv. Funct. Mater. 30, 1904523 (2019). \n16.\t Q. Hua, J. Sun, H. Liu, R. Bao, R. Yu, J. Zhai, C. Pan, Z. L. Wang, Skin-inspired highly stretchable and conformable matrix networks for multifunctional sensing. Nat. Commun. 9, 244 (2018). \n17.\t C. K. Jeong, S. B. Cho, J. H. Han, D. Y. Park, S. Yang, K.-I. Park, J. Ryu, H. Sohn, Y.-C. Chung, K. J. Lee, Flexible highly-effective energy harvester via crystallographic and computational control of nanointerfacial morphotropic piezoelectric thin film. Nano Res. 10, 437–455 (2017). \n18.\t C. Baek, J. H. Yun, J. E. Wang, C. K. Jeong, K. J. Lee, K.-I. Park, D. K. Kim, A flexible energy harvester based on a lead-free and piezoelectric BCTZ nanoparticle-polymer composite. Nanoscale 8, 17632–17638 (2016). \n19. Z. L. Wang, On the first principle theory of nanogenerators from Maxwell's equations. Nano Energy 68, 104272 (2019). \n20.\t K. Dong, J. Deng, Y. Zi, Y.-C. Wang, C. Xu, H. Zou, W. Ding, Y. Dai, B. Gu, B. Sun, Z. L. Wang, 3D orthogonal woven triboelectric nanogenerator for effective biomechanical energy harvesting and as self-powered active motion sensors. Adv. Mater. 29, 1702648 (2017). \n21.\t Z. L. Wang, A. C. Wang, On the origin of contact-electrification. Mater. Today 30, 34–51 (2019). \n22. K. Dong, Y.-C. Wang, J. Deng, Y. Dai, S. L. Zhang, H. Zou, B. Gu, B. Sun, Z. L. Wang, A highly stretchable and washable all-yarn-based self-charging knitting power textile composed of fiber triboelectric nanogenerators and supercapacitors. ACS Nano 11, 9490–9499 (2017). \n23.\t J. Wang, C. Wu, Y. Dai, Z. Zhao, A. Wang, T. Zhang, Z. L. Wang, Achieving ultrahigh triboelectric charge density for efficient energy harvesting. Nat. Commun. 8, 88 (2017). \n24.\t C. García Núñez, L. Manjakkal, R. Dahiya, Energy autonomous electronic skin. npj Flexible Electronics 3, 1 (2019). \n25.\t J. Wang, S. Li, F. Yi, Y. Zi, J. Lin, X. Wang, Y. Xu, Z. L. Wang, Sustainably powering wearable electronics solely by biomechanical energy. Nat. Commun. 7, 12744 (2016). \n26.\t H. S. Wang, C. K. Jeong, M.-H. Seo, D. J. Joe, J. H. Han, J.-B. Yoon, K. J. Lee, Performance-enhanced triboelectric nanogenerator enabled by wafer-scale nanogrates of multistep pattern downscaling. Nano Energy 35, 415–423 (2017). \n27.\t J. Deng, X. Kuang, R. Liu, W. Ding, A. C. Wang, Y.-C. Lai, K. Dong, Z. Wen, Y. Wang, L. Wang, H. J. Qi, T. Zhang, Z. L. Wang, Vitrimer elastomer-based jigsaw puzzle-like healable triboelectric nanogenerator for self-powered wearable electronics. Adv. Mater. 30, 1705918 (2018). \n28.\t R. Liu, X. Kuang, J. Deng, Y.-C. Wang, A. C. Wang, W. Ding, Y.-C. Lai, J. Chen, P. Wang, Z. Lin, H. J. Qi, B. Sun, Z. L. Wang, Shape memory polymers for body motion energy harvesting and self-powered mechanosensing. Adv. Mater. 30, 1705195 (2018). \n29.\t C. Larson, B. Peele, S. Li, S. Robinson, M. Totaro, L. Beccai, B. Mazzolai, R. Shepherd, Highly stretchable electroluminescent skin for optical signaling and tactile sensing. Science 351, 1071–1074 (2016). \n30.\t J. Park, Y. Lee, M. H. Barbee, S. Cho, S. Cho, R. Shanker, J. Kim, J. Myoung, M. P. Kim, C. Baig, S. L. Craig, H. Ko, A hierarchical nanoparticle-in-micropore architecture for enhanced mechanosensitivity and stretchability in mechanochromic electronic skins. Adv. Mater. 31, e1808148 (2019). \n31.\t M. Li, K. Chang, W. Zhong, C. Xiang, W. Wang, Q. Liu, K. Liu, Y. Wang, Z. Lu, D. Wang, A highly stretchable, breathable and thermoregulatory electronic skin based on the polyolefin elastomer nanofiber membrane. Appl. Surf. Sci. 486, 249–256 (2019). \n32.\t M. S. de Medeiros, D. Chanci, C. Moreno, D. Goswami, R. V. Martinez, Waterproof, breathable, and antibacterial self-powered e-textiles based on omniphobic triboelectric nanogenerators. Adv. Funct. Mater. 29, 1904350 (2019). \n33.\t M. Ma, Z. Zhang, Z. Zhao, Q. Liao, Z. Kang, F. Gao, X. Zhao, Y. Zhang, Self-powered flexible antibacterial tactile sensor based on triboelectric-piezoelectric-pyroelectric multi-effect coupling mechanism. Nano Energy 66, 104105 (2019). \n34.\t J. Tian, H. Feng, L. Yan, M. Yu, H. Ouyang, H. Li, W. Jiang, Y. Jin, G. Zhu, Z. Li, Z. L. Wang, A self-powered sterilization system with both instant and sustainable anti-bacterial ability. Nano Energy 36, 241–249 (2017). \n35.\t S. Wang, Q. Li, B. Wang, Y. Hou, T. Zhang, Recognition of different rough surface based highly sensitive silver nanowire-graphene flexible hydrogel skin. Ind. Eng. Chem. Res. 58, 21553–21561 (2019). \n36.\t R. Pan, W. Xuan, J. Chen, S. Dong, H. Jin, X. Wang, H. Li, J. Luo, Fully biodegradable triboelectric nanogenerators based on electrospun polylactic acid and nanostructured gelatin films. Nano Energy 45, 193–202 (2018). \n37.\t K. Parida, J. Xiong, X. Zhou, P. S. Lee, Progress on triboelectric nanogenerator with stretchability, self-healability and bio-compatibility. Nano Energy 59, 237–257 (2019). \n38.\t S. Wang, J. Y. Oh, J. Xu, H. Tran, Z. Bao, Skin-inspired electronics: An emerging paradigm. Acc. Chem. Res. 51, 1033–1045 (2018). \n39.\t S. Niu, S. Wang, L. Lin, Y. Liu, Y. S. Zhou, Y. Hu, Z. L. Wang, Theoretical study of contactmode triboelectric nanogenerators as an effective power source. Energy Environ. Sci. 6, 3576–3583 (2013). \n40.\t Q. Zheng, Y. Zou, Y. Zhang, Z. Liu, B. Shi, X. Wang, Y. Jin, H. Ouyang, Z. Li, Z. L. Wang, Biodegradable triboelectric nanogenerator as a life-time designed implantable power source. Sci. Adv. 2, e1501478 (2016). \n41.\t H. Zou, Y. Zhang, L. Guo, P. Wang, X. He, G. Dai, H. Zheng, C. Chen, A. C. Wang, C. Xu, Z. L. Wang, Quantifying the triboelectric series. Nat. Commun. 10, 1427 (2019). \n42.\t Z. Zhang, Y. Wu, Z. Wang, X. Zhang, Y. Zhao, L. Sun, Electrospinning of Ag nanowires/ polyvinyl alcohol hybrid nanofibers for their antibacterial properties. Mater. Sci. Eng. C 78, 706–714 (2017). \n43.\t C. Tang, W. Sun, J. Lu, W. Yan, Role of the anions in the hydrothermally formed silver nanowires and their antibacterial property. J. Colloid Interface Sci. 416, 86–94 (2014). \n44.\t H. K. Makadia, S. J. Siege, Poly lactic-co-glycolic acid (PLGA) as biodegradable controlled drug delivery carrier. Polymers 3, 1377–1397 (2011). \n45.\t C. A. Machado-Moreira, F. M. Smith, A. M. J. van den Heuvel, I. B. Mekjavic, N. A. S. Taylor, Sweat secretion from the torso during passively-induced and exercise-related hyperthermia. Eur. J. Appl. Physiol. 104, 265–270 (2008). \n46.\t Y. Khan, A. E. Ostfeld, C. M. Lochner, A. Pierre, A. C. Arias, Monitoring of vital signs with flexible and wearable medical devices. Adv. Mater. 28, 4373–4395 (2016). \n47.\t W. W. Nichols, Clinical measurement of arterial stiffness obtained from noninvasive pressure waveforms. Am. J. Hypertens. 18, 3S–10S (2005). \n48.\t C. Wang, X. Li, H. Hu, L. Zhang, Z. Huang, M. Lin, Z. Zhang, Z. Yin, B. Huang, H. Gong, S. Bhaskaran, Y. Gu, M. Makihata, Y. Guo, Y. Lei, Y. Chen, C. Wang, Y. Li, T. Zhang, Z. Chen, A. P. Pisano, L. Zhang, Q. Zhou, S. Xu, Monitoring of the central blood pressure waveform via a conformal ultrasonic device. Nat. Biomed. Eng. 2, 687–695 (2018). \n49.\t S. Lee, J. Kim, I. Yun, G. Y. Bae, D. Kim, S. Park, I.-M. Yi, W. Moon, Y. Chung, K. Cho, An ultrathin conformable vibration-responsive electronic skin for quantitative vocal recognition. Nat. Commun. 10, 2468 (2019). \n\n# Acknowledgments \n\nFunding: We are grateful for the support received from the Minister of Science and Technology (grant no. 2016YFA0202704) and the National Natural Science Foundation of China (grant nos. 61774016, 51432005, 5151101243, and 51561145021). No formal approval for the experiments involving human volunteers was required. The volunteers took part following informed consent. Author contribution: X.P., K.D., J.W., and Z.L.W. conceived the project and designed the e-skin. X.P., K.D., C.Y., Y.J., R.C., and D.L. fabricated the e-skin and designed and performed the experiments. X.P., K.D., and S.Z. conducted the antibacterial test. X.P., K.D., and X.G. conducted the air permeability test. X.P., K.D., J.W., and Z.L.W. analyzed the data and prepared the manuscript. All authors discussed the results and commented on the manuscript. Competing interests: X.P., K D., J.W., and Z.L.W. are inventors on a patent related to this work that is currently under review with the State Intellectual Property Office of P. R. China (serial no. 202010333458.4, 26 April 2020). The other authors declare that they have no conflict of interest. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 19 January 2020 \nAccepted 15 May 2020 \nPublished 26 June 2020 \n10.1126/sciadv.aba9624 \n\nCitation: X. Peng, K. Dong, C. Ye, Y. Jiang, S. Zhai, R. Cheng, D. Liu, X. Gao, J. Wang, Z. L. Wang, A breathable, biodegradable, antibacterial, and self-powered electronic skin based on allnanofiber triboelectric nanogenerators. Sci. Adv. 6, eaba9624 (2020). \n\n# ScienceAdvances \n\n# A breathable, biodegradable, antibacterial, and self-powered electronic skin based on all-nanofiber triboelectric nanogenerators \n\nXiao Peng, Kai Dong, Cuiying Ye, Yang Jiang, Siyuan Zhai, Renwei Cheng, Di Liu, Xiaoping Gao, Jie Wang and Zhong Lin Wang \n\nSci Adv 6 (26), eaba9624. DOI: 10.1126/sciadv.aba9624 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 49 articles, 3 of which you can access for free http://advances.sciencemag.org/content/6/26/eaba9624#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41560-020-0576-y", + "DOI": "10.1038/s41560-020-0576-y", + "DOI Link": "http://dx.doi.org/10.1038/s41560-020-0576-y", + "Relative Dir Path": "mds/10.1038_s41560-020-0576-y", + "Article Title": "Dynamic stability of active sites in hydr(oxy)oxides for the oxygen evolution reaction", + "Authors": "Chung, DY; Lopes, PP; Martins, PFBD; He, HY; Kawaguchi, T; Zapol, P; You, HD; Tripkovic, D; Strmcnik, D; Zhu, YS; Seifert, S; Lee, SS; Stamenkovic, VR; Markovic, NM", + "Source Title": "NATURE ENERGY", + "Abstract": "The poor activity and stability of electrode materials for the oxygen evolution reaction are the main bottlenecks in the water-splitting reaction for H-2 production. Here, by studying the activity-stability trends for the oxygen evolution reaction on conductive (MOxHy)-O-1, Fe-(MOxHy)-O-1 and Fe-(MMOxHy)-M-1-O-2 hydr(oxy)oxide clusters (M-1 = Ni, Co, Fe; M-2 = Mn, Co, Cu), we show that balancing the rates of Fe dissolution and redeposition over a MOxHy host establishes dynamically stable Fe active sites. Together with tuning the Fe content of the electrolyte, the strong interaction of Fe with the MOxHy host is the key to controlling the average number of Fe active sites present at the solid/liquid interface. We suggest that the Fe-M adsorption energy can therefore serve as a reaction descriptor that unifies oxygen evolution reaction catalysis on 3d transition-metal hydr(oxy)oxides in alkaline media. Thus, the introduction of dynamically stable active sites extends the design rules for creating active and stable interfaces. Understanding what underpins the activity and stability of oxygen evolution catalysts is an ongoing issue in the field of water splitting. Now, researchers show that balancing the rate of Fe dissolution and deposition over a metal hydr(oxy)oxide host yields dynamically stable Fe active sites, with the Fe-host interaction key to the performance.", + "Times Cited, WoS Core": 690, + "Times Cited, All Databases": 711, + "Publication Year": 2020, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000520704000014", + "Markdown": "# Dynamic stability of active sites in hydr(oxy) oxides for the oxygen evolution reaction \n\nDong Young Chung $\\mathbb{\\oplus1}$ , Pietro P. Lopes $\\left({\\mathfrak{P}}\\right)^{\\cdot}$ 1, Pedro Farinazzo Bergamo Dias Martins $@^{1}$ , Haiying He   2, Tomoya Kawaguchi1, Peter Zapol $\\oplus1$ , Hoydoo $\\mathbf{\\boldsymbol{Y}}\\mathbf{\\boldsymbol{o}}\\mathbf{\\boldsymbol{u}}_{\\mathrm{~}}^{1}$ , Dusan Tripkovic3, Dusan Strmcnik1, Yisi Zhu1, Soenke Seifert4, Sungsik Lee   4, Vojislav R. Stamenkovic1 and Nenad M. Markovic   1 ✉ \n\nThe poor activity and stability of electrode materials for the oxygen evolution reaction are the main bottlenecks in the watersplitting reaction for $H_{2}$ production. Here, by studying the activity–stability trends for the oxygen evolution reaction on conductive $\\mathbf{M}^{1}\\mathbf{O}_{x}\\mathbf{H}_{y},$ Fe–M1OxHy and $\\mathbf{Fe}{\\boldsymbol{-}}\\mathbf{M}^{1}\\mathbf{M}^{2}\\mathbf{O}_{x}\\mathbf{H}_{y}$ hydr(oxy)oxide clusters $(M^{1}=M)$ , $\\scriptstyle\\mathbf{co},$ Fe; $M^{2}=\\mathbf{M}\\mathbf{n},{\\mathbf{C}}\\circ,{\\mathbf{C}}\\mathbf{u})$ , we show that balancing the rates of Fe dissolution and redeposition over a $M O_{x}H_{y}$ host establishes dynamically stable Fe active sites. Together with tuning the Fe content of the electrolyte, the strong interaction of Fe with the $M O_{x}H_{y}$ host is the key to controlling the average number of Fe active sites present at the solid/liquid interface. We suggest that the Fe–M adsorption energy can therefore serve as a reaction descriptor that unifies oxygen evolution reaction catalysis on 3d transition-metal hydr(oxy)oxides in alkaline media. Thus, the introduction of dynamically stable active sites extends the design rules for creating active and stable interfaces. \n\nPrcoalgrienstserifnactehse, feuncdoampeansstianlguneldecrtsrtoadnedinmgatoefriaelsec(trcoatcahleysmtsi-) and hydrated (solvated) ions in the double layer, has begun to revolutionize the development of alternative energy systems as a viable replacement to fossil fuel technology. At the core of this transition lies the oxygen evolution reaction (OER), an important electrochemical process in hydrogen production in water electrolysers1, corrosion2, metal/air batteries3,4 and the synthesis of new chemicals from $\\mathrm{CO}_{2}$ reduction5. Not surprisingly, a wide variety of materials have been evaluated as active OER catalysts for water electrolysers, ranging from noble-metal oxides (for example, ${\\mathrm{RuO}}_{2}$ and $\\mathrm{Ir}\\mathrm{{O}}_{2})^{6,7}$ , transition-metal oxides8–10 and perovskite-type oxide structures11,12 to $3d$ transition-metal-based hydr(oxy)oxides13–17. Together with changes to surface structure and composition, tuning the double layer through the use of covalent and non-covalent interactions is another effective strategy to improve catalytic activity18,19, but it has not been consistently demonstrated for the $\\mathrm{OER}^{20,21}$ . Despite progress in increasing the activity, much less is known about the stability of these interfaces during oxygen evolution, an important aspect to guide the practical design of OER materials that require both high activity and stability. \n\nRecently, it has been found that many OER active materials suffer severe dissolution during reaction21–24, which implies that high activity in the OER is always accompanied by elevated metal dissolution rates (thermodynamic material instability)25,26. To take into account both activity and stability, the activity–stability factor $(\\mathrm{ASF})^{27}$ was suggested as a metric that evaluates the ratio between the rate of $\\mathrm{O}_{2}$ production (activity) and metal dissolution (stability), measured simultaneously using the in situ inductively coupled plasma mass spectrometry (ICP-MS) method28–30. However, the fact that dissolution occurs indicates that the surface atoms are dynamic, which is inconsistent with the common view of the electrochemical interface as a static environment. The traditional view is that all the components are ‘frozen’ in space (static active sites), and only the reactants and products are mobile. This static view has begun to change as dynamic phenomena have been observed during the OER on metal oxide31,32 and perovskite12,33,34 surfaces, suggesting that activity and stability can be simultaneously enhanced. Thus, understanding the dynamic properties of the entire interface can open up the possibility of designing materials and interfaces that are no longer bound by severe thermodynamic instability. \n\nHere, by learning from the functional links between activity and stability established for monometallic (M) and Fe-modified (Fe–M) hydr(oxy)oxide materials, we demonstrate that the creation of a dynamically stable interface (concomitant dissolution and redeposition of active sites) is possible after manipulation of both electrode and electrolyte components. The occurrence of dynamic active sites was verified by employing several experimental methods, both in  situ and ex  situ, in combination with isotopic labelling and ICP-MS experiments, confirming the formation of a highly active and dynamically stable catalyst. Further experimental and theoretical analysis suggests that this process is most effective (high ASF) when there is an optimum electrochemical interface, that is, a strong interaction between a stable host and a continuous exchange of active species, a concept that could be extended to other systems with modified hosts and active sites. \n\n# Activity and stability trends for monometallic ${\\mathsf{M O}}_{x}{\\mathsf{H}}_{y}$ \n\nWe begin by establishing in situ the activity–stability trend, and thus ASF values, for the OER in alkaline media $(0.1\\mathrm{M}\\ \\mathrm{KOH})$ on welldefined monometallic $3d\\mathrm{~M~}$ hydr(oxy)oxide $(\\mathrm{MO}_{x}\\mathrm{H}_{y};$ ${\\bf M}={\\bf N i}$ $\\begin{array}{r}{\\mathrm{Co},}\\end{array}$ Fe) clusters deposited over Pt(111), as shown in Fig. 1. These $\\mathrm{MO}_{\\boldsymbol{x}}\\mathrm{H}_{\\boldsymbol{y}}$ clusters have the benefits of well-defined surface area (roughness factor ${\\bf\\Psi}=1{\\bf\\Psi}$ ), synthesis with good control of sub-monolayer coverage over the platinum surface (maximum at $50\\%$ , Fig. 1a)19,35,36 as well as good electronic conductivity, needed for the determination of ASF (Supplementary Fig. 1). Because the presence of small amounts of impurities in the electrolyte can cause significant variations in the electrochemical performance, even more so in alkaline media13,37–39, we chose to purify further high-purity commercial KOH by employing an electrolytic method (see Supplementary Note 1 and Fig. 2 for details). \n\n![](images/d7cf2b927a61c15bd8bdbfc6ca9771240eb0a2277690a2476a0a0761db8b9755.jpg) \nFig. 1 | Activity–stability trend of 3d M hydr(oxy)oxides. a, STM images $(40\\times40\\mathsf{n m})$ of Pt(111) and $N i(O H)_{2}/\\mathsf{P t}(171)$ . b,c, Simultaneous in situ evaluation of OER activity (b) and monitoring of the metal dissolution rates $\\mathbf{\\eta}(\\bullet)$ of ${M O}_{x}{\\Hat{\\mathrm{H}}}_{y}$ ( ${\\mathrm{.}}M=N i.$ , Co, Fe) in purified 0.1 M KOH revealing that Fe hydr(oxy)oxide is the most active site for the OER in an alkaline environment, but also the most unstable. In c, scale bars are shown for each element. RHE, reversible hydrogen electrode. d–f, Summary of the activity–stability relationship for ${M O}_{x}{\\Hat{\\mathsf{H}}}_{y}$ ( ${\\mathrm{.}}M=N i$ , Co, Fe) obtained at $1.7\\mathsf{V},$ highlighting the dissolution rates (d) and current densities (e) for all three metal hydr(oxy)oxides, suggesting that Ni hydr(oxy)oxide is the most technologically relevant material within the monometallic series due its high stability, as indicated by its ASF (f). Measurements were taken at least three times and average values are presented with the standard error bar. \n\nFigure $^{1\\mathrm{b,c}}$ shows the results of monitoring simultaneously the rates of $\\mathrm{O}_{2}$ production (current densities) and the rates of metal dissolution using our stationary probe rotating disk electrode (SPRDE) coupled to an ICP-MS spectrometer28, revealing that $\\mathrm{FeO}_{x}\\mathrm{H}_{\\mathrm{\\ell}}$ is more active in the OER than $\\mathrm{CoO}_{x}\\mathrm{H}_{y}$ and ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ (ref. 40). Although the activity is the highest for the Fe-containing substrate, its potentialdependent dissolution rate at OER potentials is three orders of magnitude higher than those observed for the Co- and Ni-based hydr(oxy)oxides (Fig. 1d, approx. 12.1, 0.023 and $0.004\\mathrm{ng}\\mathrm{cm}^{-2}\\mathrm{s}^{-1}$ , respectively). By comparing the activity and stability at $1.7\\mathrm{V},$ the stability trend observed is $\\mathrm{NiO_{\\itx}H_{\\it y}>C o O_{\\it x}H_{\\it y}>>F e O_{\\it x}H_{\\it y},}$ which is the exact opposite trend measured for OER activity, $\\mathrm{NiO}_{x}\\mathrm{H}_{y}{<}\\mathrm{CoO}_{x}\\mathrm{H}_{y}{<}\\mathrm{FeO}_{x}\\mathrm{H}_{y}$ (Fig. 1e). \n\nAs a consequence of its higher dissolution rate, Fe hydr(oxy) oxide shows a significant drop in OER activity during its initial five cycles (poor activity retention) followed by a decrease in the amount of Fe dissolution in every consecutive cycle (Supplementary Fig. 3), a direct consequence of active-site depletion at the electrode surface41,42. Similar results were obtained from chronoamperometry measurements at constant voltage $(1.7\\mathrm{V},1\\mathrm{h})$ , indicating that severe dissolution of Fe undermines its use as an OER catalyst, whereas $\\mathrm{NiO}_{x}\\mathrm{H}_{\\mathrm{\\ell}}$ shows the highest stability without any appreciable activity loss (Supplementary Fig. 3). These results serve as the basis for activity–stability relationships on M hydr(oxy)oxides, best summarized by the ASF values calculated at $1.7\\mathrm{V}$ (Fig. 1f). As a rule of thumb, the ASF evaluates the extent to which a material produces $\\mathrm{O}_{2}$ molecules (specific for the OER) for a given amount of dissolution of the active site. Therefore, the higher the ASF of a material, the more $\\mathrm{O}_{2}$ is produced per dissolved active site. The conclusion after evaluation of the ASF values for the ${\\mathrm{FeO}}_{{\\mathrm{{}}_{x}}}{\\mathrm{H}}_{{\\mathrm{{}}_{y}}},$ $\\mathrm{CoO}_{x}\\mathrm{H}_{\\mathrm{\\it_{)}}}$ and $\\mathrm{NiO}_{x}\\mathrm{H}_{;}$ sites is that the Ni-based hydr(oxy)oxide is the most promising durable catalyst for $\\mathrm{O}_{2}$ production in this series, as the elevated ASF reflects its extremely high stability despite its poor OER activity. Further evaluation of the Faradaic efficiency for $\\mathrm{O}_{2}$ production $\\left(\\mathrm{FE}_{\\mathrm{oxygen}}\\right)$ on $\\mathrm{MO}_{x}\\mathrm{H}_{y}$ was performed by using the rotating ring-disk electrode (RRDE) method (Supplementary Fig. 4). The high $\\mathrm{FE}_{\\mathrm{oxygen}}$ values for Ni and Co hydr(oxy)oxide (over $99\\%$ ) indicate that most of the current originates from $\\mathrm{O}_{2}$ evolution and not side reactions such as $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production or from corrosion currents. On the other hand, the measured Faradaic efficiency of $\\mathrm{FeO}_{x}\\mathrm{H}_{\\mathrm{3}}$ shows poor stability $(\\sim88\\%)$ , which is in good agreement with its ASF value, and no formation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (Supplementary Fig. 5). \n\n![](images/40ec1fc25129fc28289d2d55d522d305c6248672b1e6c134caa9c2f956b34a50.jpg) \nFig. 2 | Activity–stability trend of Fe–M hydr(oxy)oxides and observation of dynamic Fe exchange by isotopic labelling experiments. a,b, Summary of the results of the activity–stability study of Fe–M hydr(oxy)oxides during chronoamperometry experiments at $1.7\\vee$ for 1 h in ‘Fe-free’ purified KOH (a) and in a KOH solution containing 0.1 ppm Fe $(\\bullet)$ , revealing the high dependence of OER activity retention on the presence of Fe in the electrolyte. c–f, The total amount of Fe in the Fe- $\\cdot\\mathsf{N i O}_{x}\\mathsf{H}_{y}$ electrode (c,d) and OER activity (e,f) during chronoamperometry measurements at $1.7\\vee$ show Fe dissolution from the electrode surface accompanied by OER activity loss in the ‘Fe-free’ electrolyte (c,e). The schematic diagram in e depicts the dissolution process. Similar chronoamperometry experiments performed in electrolyte containing 0.1 ppm $^{57}\\mathsf{F e}$ (d,f) reveal Fe dynamic exchange (dissolution and redeposition) at the interface during OER catalysis, as the quick dissolution of $^{56}\\mathsf{F e}$ from the electrode is followed by immediate redeposition of 57Fe from the electrolyte. The dynamic exchange preserves the overall Fe content at the electrode surface, which is reflected in the high OER activity that does not decrease during the course of the experiment. The schematic diagram in f depicts both the Fe dissolution and redeposition processes, with balanced rates brought about by the trace level of Fe in the electrolyte. \n\n# Activity and stability trends for $F e-M O_{x}H_{y}$ \n\nAs Ni- and Co-based hydr(oxy)oxide systems incorporating Fe have been shown to display significant activity in alkaline media13,37, we added Fe nitrate to the purified electrolyte to form ${\\mathrm{Fe}}{\\mathrm{-}}{\\mathrm{MO}}_{x}{\\mathrm{H}}_{y}$ (Fe–Ni and Fe–Co) and compared their activity–stability trends. Scanning tunnelling microscopy (STM) revealed that the cluster height increases slightly with respect to the monometallic systems (Supplementary Fig. 6), suggesting that Fe is selectively adsorbed on the Ni and Co hydr(oxy)oxide substrates. Further quantification of Fe incorporation revealed an Fe content of 15 to $28\\%$ by weight in the Co- and Ni-containing $\\mathrm{MO}_{x}\\mathrm{H}_{\\mathrm{\\ell}}$ clusters, respectively (Supplementary Fig. 6). \n\nThe OER activity trend for ${\\mathrm{Fe}}{\\mathrm{-}}{\\mathrm{MO}}_{x}{\\mathrm{H}}_{y}$ (Fig. 2a and Supplementary Fig. 7) is reversed when compared with the results for monometallic systems (Fig. 1), decreasing in the order $\\mathrm{Fe-NiO}_{x}\\mathrm{H}_{y}{>}\\mathrm{F}$ e– $\\mathrm{CoO}_{x}\\mathrm{H}_{y}{>}\\mathrm{FeO}_{x}\\mathrm{H}_{y}$ . At $1.7\\mathrm{V},$ the current density on bimetallic ${\\mathrm{Fe-NiO}}_{x}{\\mathrm{H}}_{y}$ is nine times higher than that observed with pure ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y},$ and it is enhanced about three times on ${\\mathrm{Fe-CoO}}_{x}{\\mathrm{H}}_{y}$ clusters in comparison with pure ${\\mathrm{CoO}}_{\\mathrm{{}}x}{\\mathrm{H}}_{\\gamma},$ highlighting the fact that a small amount of Fe in a material can significantly enhance its OER activity and that current enhancement originates from actual $\\mathrm{~O}_{2}$ evolution (Supplementary Fig. 8). In addition, this Fe effect is observed regardless of support $\\mathrm{{Pt}}(111)$ , glassy carbon, nickel or cobalt metal surfaces), indicating that the $\\mathrm{MO}_{x}\\mathrm{H}_{y}$ –Fe interaction is key to promoting the OER (Supplementary Fig. 9). \n\nTogether with the trends in catalytic activity, it is important to establish the stability trends for bimetallic hydr(oxy)oxides so that ultimately we can determine their technological relevance based on the ASF values. Surprisingly, the trend in stability, as measured by the activity retention for the Fe-containing $\\mathrm{MO}_{\\boldsymbol{x}}\\mathrm{H}_{\\boldsymbol{y}}$ clusters, is highly dependent on the presence of trace levels of Fe in the electrolyte $(\\mathrm{Fe^{n+}(a q.)}=0.1\\mathrm{ppm})$ . In pure KOH solutions, the activities of the ${\\mathrm{Fe-NiO}}_{x}{\\mathrm{H}}_{y}$ and ${\\mathrm{Fe-CoO}}_{x}{\\mathrm{H}}_{y}$ samples show a remarkable deactivation after just 1 h of potential hold at $1.7\\mathrm{V}$ (Fig. 2a), reducing the initial high activities to almost the same levels as the monometallic hydr(oxy)oxides (Supplementary Fig. 10). However, the addition of $\\mathrm{Fe^{n+}}(\\mathrm{aq.})$ to the electrolyte effectively prevents activity loss under the same test conditions (Fig. 2b). \n\nOn the one hand, in  situ measurement of dissolution rates from ${\\mathrm{Fe-NiO}}_{x}{\\mathrm{H}}_{y}$ during potential cycling (Supplementary Fig. 11) shows that the total amount of Ni dissolution is still negligible. However, Fe still leaches from ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ at a rate almost two orders of magnitude greater than $\\mathrm{\\DeltaNi}$ itself, although not as fast as observed from the pure monometallic hydr(oxy)oxide system (Fig. 1). The same trend is observed in ${\\mathrm{Fe-CoO}}_{x}{\\mathrm{H}}_{y}$ (Supplementary Fig. 11), suggesting that the lack of stability (poor activity retention) in the ${\\mathrm{Fe-MO}}_{x}{\\mathrm{H}}_{y}$ systems when ${\\mathrm{Fe}}^{\\mathrm{n+}}(\\mathrm{aq.})$ is not present in the electrolyte is related to the dissolution of Fe active sites, notably due the depletion of the initial Fe content from the electrode surface. On the other hand, evaluation of Fe dissolution when the electrolyte contains ${\\mathrm{Fe}}^{\\mathrm{n}+}(\\mathrm{aq.})$ reveals the same dissolution process as shown in Supplementary Fig. 11, although the OER activity levels remain elevated and unchanged throughout the experiment. \n\nFrom the results of the activity and stability studies of M and Fe–M hydr(oxy)oxides, there are three important features to emphasize. First, during the OER, Fe active sites are very unstable, regardless of whether they are present in Fe or as Fe–M hydr(oxy) oxides. Second, despite the high initial activity, the subsequent activity decay observed for Fe-containing $\\mathrm{MO}_{x}\\mathrm{H}_{y}$ systems is related to Fe depletion through dissolution. Third, preserving the high activity levels can be achieved only when the electrolyte contains ${\\mathrm{Fe}}^{\\mathrm{n}+}(\\mathrm{aq.})$ even though Fe dissolution from the surface will still occur (Supplementary Fig. 12). The fact that these results indicate that the material itself is not absolutely stable, but OER activity can be sustained over time, implies that a significant Fe dynamic exchange is continuously taking place at the interface. \n\nTo confirm this dynamic Fe exchange at the interface we measured the total amount of $^{56}\\mathrm{Fe}$ and $^{57}\\mathrm{Fe}$ in the electrode using ICP-MS at different stages of the chronoamperometry experiments (see details in the Methods section), providing information about the kinetics of dissolution as well as the kinetics of $\\mathrm{Fe^{n+}}(\\mathrm{aq.})$ redeposition. Therefore, by starting with $^{56}\\mathrm{Fe}$ in the electrode and $^{57}\\mathrm{Fe}$ in the electrolyte, any loss of $^{56}\\mathrm{Fe}$ and gain of $^{57}\\mathrm{Fe}$ can be traced back to dissolution and deposition events occurring during the OER, respectively. As a control experiment, Fig. 2c shows potential hold experiments on ${\\mathrm{Fe}}{\\mathrm{-NiO}}_{x}{\\mathrm{H}}_{y}$ in which a continuous decrease of Fe in the electrode during polarization is observed, followed by OER deactivation (Fig. 2e). This is in line with the results shown in Fig. 2a, emphasizing that Fe dissolution decreases the number of active sites on the electrode surface. However, when $0.1\\mathrm{ppm}^{57}\\mathrm{Fe}$ is in the electrolyte $(^{57}\\mathrm{Fe^{n+}(a q.)})$ , dissolution of $^{56}\\mathrm{Fe}$ occurs at the same rate as in Fig. 2c $(\\sim0.53\\mathrm{ng}\\mathrm{cm}^{-2}s^{-1})$ , but the amount of $^{57}\\mathrm{Fe}$ in the electrode increases at a similar rate to the $^{56}\\mathrm{Fe}$ loss $(\\sim0.56\\mathrm{ng}\\mathrm{cm}^{-2}s^{-1}$ , Fig. 2d). This results in an overall Fe content, $^{56}\\mathrm{Fe}+{}^{57}\\mathrm{Fe}$ , that is constant throughout the experiment. Note that half of the $^{56}\\mathrm{Fe}$ in the electrode has already exchanged with $^{57}\\mathrm{Fe}$ in less than $1\\mathrm{min}$ and $^{57}\\mathrm{Fe/Fe}$ reaches $70\\%$ after $^{\\mathrm{1h,}}$ confirming that rapid Fe dissolution and redeposition happens at the interface during OER. Interestingly, as a consequence of dynamic exchange, the overall Fe content in the electrode remains constant, preserving the total number of active sites for the OER, and thus eliminating any catalytic deactivation (Fig. 2f). This further supports the fact that Fe is an intimate part of the active site for the OER in alkaline media when combined with Ni or Co hydr(oxy)oxides. \n\nThe ability of Fe to promote OER activity on Ni and Co hydr(oxy)oxides has been reported before, but the origin of such activity enhancement remains elusive. Many reports identify $\\mathrm{\\DeltaNi}.$ promoted by Fe, as the active sites43,44, whereas others indicate that Fe could be the source of the OER enhancement45,46, with relevant considerations of the role of plane or edge sites and substitutional doping47–50. Given the trends observed for $\\mathrm{MO}_{x}\\mathrm{H}_{y}$ (Fig. 1), it is clear that pure $\\mathrm{\\DeltaNi}$ cannot be the active site, strongly suggesting that Fe acts as the active site. This assertion is further supported by in situ X-ray absorption near-edge spectroscopy (XANES) analysis (Supplementary Fig. 13), and consideration of other electrocatalytic reactions, such as the hydrogen evolution reaction (Supplementary Fig. 14), preclude Ni or Co as the effective active sites (electronically modified by Fe) for the $\\mathrm{OER^{51}}$ . However, it is clear that Fe species at the interface together with Ni and Co oxide hosts are critical for achieving high levels of $\\mathrm{O}_{2}$ production. \n\n# Dynamically stable Fe as active site for oxygen evolution \n\nBy controlling the ${\\mathrm{Fe}}^{\\mathrm{n}+}(\\mathrm{aq.})$ concentration in the electrolyte, increasing the ${\\mathrm{Fe}}^{\\mathrm{n}+}(\\mathrm{aq.})$ content above $0.1\\mathrm{ppm}$ does not lead to any further increase in OER activity (Fig. 3a), nor an increase in the amount of Fe incorporated into either the Ni or Co hydr(oxy)oxide (Fig. 3b). These results indicate that OER activity is linked to the amount of Fe present in the $\\mathrm{MO}_{x}\\mathrm{H}_{y}$ and that there is an Fe saturation coverage (monolayer, ML) for each surface. The linear relationship between \n\nOER and Fe coverage reveals that the factors contributing to the promotion of the OER on ${\\mathrm{Fe-NiO}}_{x}{\\mathrm{H}}_{y}$ and ${\\mathrm{Fe-CoO}}_{x}{\\mathrm{H}}_{y}$ are not unique to each bimetallic system (Fig. 3c), but rather, form part of a general description of the active sites linked to the number of dynamic stable sites (Fe). \n\nDensity functional theory (DFT) calculations reveal that the $\\Delta\\bar{G}_{\\mathrm{Fe-M}}$ values (Fe average adsorption free energy on ${\\mathrm{MO}}_{x}{\\mathrm{H}}_{y}$ sites) aIre strongly dependent on the substrate nature (Supplementary Fig. 15). In simple terms, a more negative $\\Delta\\bar{G}_{\\mathrm{Fe-M}}$ value implies a higher Fe saturation coverage on ${\\mathrm{MO}}_{x}{\\mathrm{H}}_{y}$ . IFigure 3d summarizes the Fe adsorption free-energy trends for the ${\\mathrm{Ni}}.$ Co and Fe $\\mathrm{MO}_{x}\\mathrm{H}_{y}$ substrates, revealing that Fe adsorption on $\\mathrm{FeO}_{x}\\mathrm{H}_{y}$ is unfavourable and that ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ shows the strongest interaction with ${\\mathrm{Fe}}^{\\mathrm{n}+}(\\mathrm{aq.})$ $(-0.69\\mathrm{eV}$ at a coverage of $0.25\\mathrm{ML}$ ), and consequently the highest Fe coverage in this series, providing a good match with the experimental values (Supplementary Fig. 16). Furthermore, the rate of Fe dissolution depending on the host $(\\mathrm{FeO}_{x}\\mathrm{H}_{y}{>}>\\mathrm{CoO}_{x}\\mathrm{H}_{y}{>}\\mathrm{NiO}_{x}\\mathrm{H}_{y})$ is also affected by the Fe adsorption energy $\\mathrm{(Fe>\\dot{r}_{\\mathrm{dep}}C_{\\mathrm{Fe}}^{0},$ Fig. 2e). \n\nConsiIdering that continuous elemental dissolution and redeposition occurs during the OER, our ‘dynamic stable active site (Fe)/host pair’ concept could be seen as similar to the self-healing mechanism suggested in previous work31,32. Unlike self-healing, the regeneration of the active sites in a dynamic stable state necessarily requires a ‘specific host’ with a strong interaction with the dynamic ‘active sites’. In this scenario, Fe species would be the active sites that can be dynamically stable only because of their interaction with stable $\\mathrm{NiO}_{x}\\mathrm{H}_{y}$ or $\\mathrm{CoO}_{x}\\mathrm{H},$ clusters. By contrast, the simple self-healing process of Fe on $\\mathrm{FeO}_{x}\\mathrm{\\dot{H}}_{y}$ (Fig. 2a,b) is not sufficiently effective for Fe to be fully adsorbed on the electrode surface and unleash its OER catalytic activity. Unlike static interfaces, the dynamic stable condition counterbalances the intrinsic high dissolution rate of the active sites by promoting their redeposition through tailored electrode– electrolyte interactions. \n\n![](images/e745591c63f095d795280fdf013ac1217e31c607575d0482f857d5a968233a83.jpg) \nFig. 3 | Dynamically stable Fe as active site for OER. a,b, Effect of Fe concentration in the electrolyte on OER activity (a) and Fe mass retained $(\\pmb{6})$ in Fe–Ni and Fe–Co hydr(oxy)oxide clusters, revealing that Fe adsorption saturates at high Fe concentrations (above 0.1 ppm). c, The correlation between absolute OER activity and Fe coverage on both Fe–Ni and Fe–Co hydr(oxy)oxides indicates that OER catalysis enhancement increases linearly with average Fe coverage as a result of stronger Fe–M hydr(oxy)oxide interactions. Note that the arrows indicate maximum Fe surface coverage on the Ni (red) and Co (blue) substrates. Measurements were taken at least three times and average values are presented with the standard error bar. d, DFT calculations of the average adsorption free energies for Fe on M hydr(oxy)oxide at a coverage of $0.25\\mathsf{M L}$ . The adsorption free energy of the Fe complex on FeOOH is set to zero because it is unfavourable. e, Schematic diagram of the ‘dynamically stable’ active-site/host pair at the electrode/electrolyte interface, highlighting the role of M hydr(oxy)oxide as a suitable host for Fe species to stay at the interface long enough to catalyse the conversion of ${\\mathsf{O H}}^{-}$ into $\\mathsf{O}_{2}$ molecules, with the presence of Fe in the electrolyte ensuring that Fe species can return to the interface and redeposit at hydr(oxy)oxide sites. \n\nFrom the point of view of OER activity, there are two routes to maximize catalysis. First, increasing the absolute number of dynamic Fe active sites can be achieved by increasing the surface area of the host material. Although this strategy seems trivial, it is the only pathway available if the material properties related to Fe adsorption $(\\Delta G_{\\mathrm{Fe-M}})$ cannot be tuned. This is shown when a steady increase in the amount of ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ deposited on $\\mathrm{Pt}(111)$ , for instance, results in an increase in the absolute OER activity both in pure KOH as well as in electrolyte containing ${\\mathrm{Fe}}^{\\mathrm{n+}}(\\mathrm{aq.})$ at saturation levels. Despite these increases in absolute activity, the ratio between OER currents with and without ${\\mathrm{Fe}}^{\\mathrm{n}+}(\\mathrm{aq.})$ , called the activity enhancement factor $(I_{\\mathrm{Fe}}/I)$ , remains the same for all amounts of Ni hydr(oxy)oxides (Supplementary Fig. 18). \n\nSecond, the number of dynamic Fe species can be increased by tuning the Fe adsorption $(\\Delta G_{\\mathrm{Fe-M}})$ on the host materials. Based on the DFT trend in which $\\Delta G_{\\mathrm{Fe-M}}$ shows an inverse relationship with the bond energy ( $\\cdot\\Delta G_{\\mathrm{M-O}}$ ; Supplementary Fig. 15), we screened other $3d$ transition metals in an attempt to find $\\mathrm{MO}_{\\boldsymbol{x}}\\mathrm{H}_{\\boldsymbol{y}}$ host candidates better than ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ (Supplementary Fig. 19). Figure 4a shows that the elements to the left of Fe in the periodic table do not show any OER activity enhancement with Fe. Because the M–O bond becomes stronger towards the left of the periodic table53, Fe adsorption is unfavourable. In the opposite direction (to the right of Fe), activity enhancement is clearly observable and is the highest for $\\mathrm{CuO}_{x}\\mathrm{H}_{y}$ . Although Cu hydr(oxy)oxide shows the highest activity enhancement factor, its high dissolution rate prevents its use as a practical $\\mathrm{MO}_{x}\\mathrm{H}_{y}$ host (Supplementary Fig. 20). \n\nBy doping the Ni hydr(oxy)oxide cluster with various other $3d$ transition metals as dopants (Mn, Co and $\\mathrm{Cu}$ ) we were able to further tune the Fe adsorption energy and consequently improve OER activity levels. Following the trend in the enhancement factor on pure ${3d\\mathrm{MO}_{x}}\\mathrm{H}_{y},$ doping ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ with Cu atoms $(\\mathrm{NiCuO}_{x}\\mathrm{H}_{y},$ see Supplementary Fig. 21) leads to superior OER activity $(40.5\\mathrm{mAcm^{-2}})$ ) in KOH containing 0.1 ppm Fe, which is 1.4 times higher than that of ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ with ${\\mathrm{Fe}}^{{\\mathrm{n}}+}({\\mathrm{aq.}})$ (Fig. 4b). Furthermore, the activity enhancement factor $(I_{\\mathrm{Fe}}/I)$ of NiCu hydr(oxy)oxide surpasses that of pure $\\mathrm{NiO}_{x}\\mathrm{H}_{y},$ although it is still lower than that of pure $\\mathrm{CuO}_{x}\\mathrm{H}_{y}$ . The increase in Fe surface coverage revealed by ICP-MS and supported by DFT analysis suggests that the high activity of ${\\mathrm{NiCuO}}_{x}{\\mathrm{H}}_{y}$ clusters originate from the increase in Fe adsorption energy, and consequently higher average Fe coverage, making it the most suitable Fe host (Supplementary Fig. 22). This trend is further validated by the observed linear relationship between OER activity and the number of dynamic Fe species measured on the NiMn and NiCo hydr(oxy)oxides (Fig. 4c and Supplementary Fig. 23). Although further promotion of OER activity can occur through a synergistic interaction of the support ${(\\mathrm{MO}_{x}\\mathrm{H}_{y})}$ ) with Fe, caused by electronic (or geometric) effects or a possible new reaction mechanism/pathway45,49,50, our observations strongly support the idea that the number of dynamic stable sites (Fe) can be regarded as a general descriptor of the active sites, as described in equation (2). It is likely that the Fe–M adsorption energy, which determines the saturation coverage of Fe on a given ${\\mathrm{MO}}_{x}{\\mathrm{H}}_{y},$ may be more relevant than the M–O adsorption energy as activity descriptor6. \n\n![](images/d55c12df2752d7707ac1f370b3333588828a6235eceaa15a1aacf0a5caae6b9c.jpg) \nFig. 4 | Interface (dynamic active species/host pair) design for highly active and durable system. a, The activity enhancement trend for Fe incorporation into 3d transition-metal hydr(oxy)oxides indicates that the Fe interaction (Fe adsorption energy increases with each element, from left to right (red dashed line)) shows an inverse correlation with the M–O bond energy (blue dashed line). b, OER activity of Ni (left) and NiCu (right) hydr(oxy)oxides in pure KOH and KOH containing 0.1 ppm Fe. The insets show the potential–current density plots in the OER region. c, The correlation between absolute OER activity with Fe surface coverage on NiM (Cu, Co, Mn) and Ni hydr(oxy)oxides indicates that OER catalysis enhancement increases linearly with average Fe coverage. The plot clearly demonstrates that ‘dynamic stable Fe’ is a general descriptor for OER activity. d, A comparison of the ASF values of different Fe–M and M hydr(oxy)oxides reveals that engineering dynamic active-site/host pairs with a high number of dynamic Fe species and a stable host is a key design principle. Measurements were taken at least three times and average values are presented with the standard error bar. \n\nFrom a stability point of view, in situ ICP-MS indicates that Cu in NiCu hydr(oxy)oxide is more stable in the OER potential window than pure ${\\mathrm{CuO}}_{x}{\\mathrm{H}}_{y},$ although it does start to dissolve at potentials above $2.1\\mathrm{V}$ versus RHE (Supplementary Fig. 24). Constant current density measurements performed at $10\\mathrm{mAcm}^{-2}$ , which is considered as a benchmark for OER stability54, and high Faradaic efficiency $(>99\\%)$ also indicate a superior electrochemical stability without appreciable activity loss (Supplementary Fig. 24), verifying that Fe $\\mathsf{\\Pi}_{\\cdot-\\mathrm{NiCuO}_{x}\\mathrm{H}_{j}}$ y shows not only high material stability (decreased rates of dissolution), but also superior catalytic stability (stable chronoamperometry). \n\nFinally, our observations suggest a way to maximize the ASF values for OER materials to achieve high activity and stability simultaneously (Fig. 4d). The Fe-containing samples (red bars in Fig. 4d) show high ASF values compared with the ‘Fe-free’ samples (blue bars in Fig. 4d) due to the high activity gained from hosting Fe active sites. The use of Ni and Cu as hydr(oxy)oxide hosts leads to a better ASF value due to simultaneous improvement in the activity enhancement factor (stronger Fe adsorption) and the prevention of Cu dissolution due to ${\\mathrm{Ni-Cu}}$ interactions. This stabilization effect is shown with ${\\mathrm{NiCoO}}_{x}{\\mathrm{H}}_{y},$ as it displays an elevated ASF value due to the prevention of Co dissolution by ${\\mathrm{NiO}}_{x}{\\mathrm{H}}_{y}$ , but $\\mathrm{CoO}_{x}\\mathrm{H}_{\\mathrm{\\Omega}}$ and $\\operatorname{NiCoO}_{x}\\mathrm{H}_{y}$ have similar OER activities (Supplementary Fig. 25). As a result, active-species/host pairs overcome the limitations placed on the ASF by material instability of both active sites and additional atoms present to tailor ${\\mathrm{Fe}}{\\mathrm{-}}{\\mathrm{MO}}_{x}{\\mathrm{H}}_{\\mathrm{\\mathrm{+}}}$ interactions. \n\n# Conclusions \n\nIn summary, we have investigated activity–stability trends for the OER on conductive M ( $\\begin{array}{r}{{\\bf\\nabla}\\mathrm{M}={\\bf N i}.}\\end{array}$ , Co, Fe) and Fe–M hydr(oxy)oxide clusters and found dynamically stable Fe as a result of dissolution and redeposition at the electrolyte/host interface, which provides a general description for OER activity and stability. By realizing that this dynamic stability overcomes the limitations imposed by the thermodynamic instability of oxide materials at OER potentials, we propose that the design of new materials should be focused on attaining a high number of dynamically stable active sites within a stable host under solid/liquid interfacial control. We have demonstrated an example of how these design rules can increase Fe use, by preparing Fe–NiCu hydr(oxy)oxide with higher OER activity than the Cu-free material. In the future, the design of new activesite/host pairs may lead to the discovery of new (electro)chemical interfaces that are simultaneously highly active and highly stable for the OER. \n\n# Methods \n\nChemicals. High-purity, trace-analysis grade potassium hydroxide hydrate (Trace SELECT, Fluka) was further purified as discussed below. All transition metals used here, Ni, Co and Fe nitrate hexahydrates and Cu and Mn nitrate hydrates $(99.995\\%$ metal basis, Sigma Aldrich), were employed as supplied. Electrolytes were prepared with Milli-Q Millipore deionized (DI) water. All gases (argon, oxygen and hydrogen) were of $99.9999\\%$ quality (Airgas). \n\nElectrolyte purification and confirmation of electrolyte purity. Electrolyte (KOH) purification to control the cation concentration was conducted by prolonged electrolysis (5 d) using Ni wire $(3.925\\mathrm{cm}^{2}$ , Puratronic, $99.999\\%$ , Alfa Aesar) as both working and counter electrode, motivated by previous reports13,37. Electrolysis purification was conducted inside a plastic cell made out of fluoropolymer material to avoid contamination from glass components. We confirmed the purity of the electrolyte by electrochemical methods using $\\mathrm{Pt}(111)$ cyclic voltammetry (CV). Based on a previous report38, small amounts of cation (Ni, Co and Fe) in alkaline electrolyte affect the CV shape of Pt(111) significantly. Inspired by the high sensitivity and clear observation of a cation effect on electrochemical performance, we compared the CV of $\\mathrm{Pt}(111)$ after ten potential cycles from 0.05 to $0.9\\mathrm{V}$ with the initial CV of $\\mathrm{Pt}(111)$ obtained in our purified electrolyte (for detailed information see Supplementary Fig. 2 and Note 1). To maximize the mass transport of any possible impurities in the electrolyte, CV was performed with a rotating electrode at $1{,}600\\mathrm{r.p.m}$ . By our method, in purified KOH, there was no change before and after CV cycling, indicating that our method can efficiently remove any trace level of impurities that could affect electrochemical performance. \n\nExtended surface electrode preparation and metal hydroxide deposition. $\\mathrm{Pt}(111)$ single-crystal electrode ( $_{(6-\\mathrm{mm}}$ diameter) was prepared by inductive heating for $7\\mathrm{{min}}$ at ${\\sim}1{,}100^{\\circ}\\mathrm{C}$ in a flow of argon/hydrogen $3\\%$ hydrogen). The annealed crystal was cooled slowly to room temperature under an inert atmosphere and immediately covered with a drop of DI water. To screen the candidates for host materials, a $6\\mathrm{-mm}$ -diameter metal electrode was used. Before the experiments, the electrode was prepared by mirror polishing with alumina powder and then immersed in KOH solution to reach saturation conditions. The electrodes were then assembled into a rotating disk electrode (RDE). Polarization curves were recorded in argon-saturated electrolyte. By potential cycling between the underpotential deposition of hydrogen $\\mathrm{(H_{upd})}$ and hydroxide adsorption $\\mathrm{(OH_{ad})}$ region in the presence of $1{-}100\\mathrm{ppm}$ transition-metal nitrate, metal hydr(oxy)oxide layers were deposited on $\\mathrm{Pt}(111)$ . The surface coverage of the $\\mathrm{MO}_{x}\\mathrm{H}_{\\mathrm{\\it_}}$ layer was controlled by the number of potential cycles and concentration of the cation. The mass loading of hydr(oxy)oxide was confirmed by ICP-MS and repetitive analysis was conducted at least three times for each element. Fe–M hydroxide samples were prepared by spike experiments with 0.1 ppm Fe nitrate hexahydrate (the $^{56}\\mathrm{Fe}/^{57}\\mathrm{Fe}$ ratio was 92:2 and is denoted as $^{56}\\mathrm{Fe}$ in the manuscript) in the electrolyte. The Fe surface coverage (ML) on Fe–M hydr(oxy)oxides was calculated from the mass ratio between Fe and M (Ni, Co, Cu and $\\mathbf{M}\\mathbf{n}$ ) based on the STM and CV results. The mass ratios of the dopant M in NiM samples were 25.8 $\\mathrm{[cu]}$ , 26.2 (Co) and $24.8\\%$ $\\left(\\mathrm{Mn}\\right),$ . \n\nElectrochemical measurements. Electrochemical measurements were controlled using an Autolab PGSTAT 302N potentiostat. A typical three-electrode configuration in a fluoropolymer-based cell was used to avoid contamination from glass components in the alkaline media. To avoid any contamination from previous experiments, the cell was thoroughly rinsed with DI water and then DI water was boiled in the cell before every experiment. A glassy carbon rod and $\\mathrm{\\Ag/}$ AgCl were used as the counter and reference electrodes, respectively. To avoid any contamination from the glassy carbon counter electrode as a result of its use in previous experiments, the glassy carbon was thoroughly washed with $1\\mathrm{MHCl}$ and immersed in boiling DI water before every experiment. OER measurements were carried out by cycling the electrode up to $1.7\\mathrm{V}$ versus RHE. The iR drop compensation was conducted during measurements. The current densities reported in this paper were normalized by the geometric area of the $\\mathrm{Pt}(111)$ substrate $(0.283\\mathrm{cm}^{2})$ ). Potential hold experiments were also carried out on the hydroxide $\\langle\\mathrm{Pt}(111)$ systems to study the stability at 1.7 V versus RHE. Constant current density measurements of Fe–NiCu hydr(oxy)oxide were conducted in KOH containing 0.1 ppm Fe at $10\\mathrm{mAcm}^{-2}$ . All electrochemical measurements were conducted in ‘Fe-free’ electrolyte purified by our protocol unless indicated otherwise in the manuscript. For the isotopic-labelling experiment, $0.1\\mathrm{ppm}$ Fe in KOH was prepared with the $^{57}\\mathrm{Fe}$ precursor from Alfa Aesar (the $^{56}\\mathrm{Fe}/^{57}\\mathrm{Fe}$ ratio was 3:95.5 and is denoted as $^{57}\\mathrm{Fe}$ in the manuscript). Because the background value was too high to observe Fe dynamics if $0.1\\mathrm{ppm}$ Fe was present in the electrolyte, we analysed the Fe isotopes in the Fe–M hydr(oxy)oxides by preparing the electrodes with $^{56}\\mathrm{Fe}$ and conducting electrochemical analysis in 57Fe-containing KOH electrolyte. To quantify the amount of Fe ( $^{56}\\mathrm{Fe}$ and $^{57}\\mathrm{Fe}$ ) in the electrode during chronoamperometry measurements, the electrode (Fe–M hydr(oxy)oxide) was thoroughly dissolved in $0.1\\mathrm{M}\\mathrm{HNO}_{3}$ and analysed by ICP-MS. All electrochemical measurements were performed at least three times and average values are presented with the standard error bar. \n\nSTM and atomic force microscopy measurements. For cluster-shape and heightinformation analyses, STM images were acquired with a Digital Instruments MultiMode Dimension STM controlled by a Nanoscope III control station using $\\mathrm{Pt}(111)$ , Ni hydr(oxy)oxide on Pt(111) and Fe–Ni hydr(oxy)oxide on Pt(111). During the STM measurements, the microscope supporting the sample was enclosed in a pressurized cylinder under a CO atmosphere. Atomic force microscopy (AFM) images were collected in soft tapping mode (Bruker Dimension ICON) to measure the topography of NiCu hydr(oxy)oxide deposition on Pt(111). The AFM data were processed using the GWYDDION (version 2.53) software package. \n\nIn situ XANES measurements. XANES measurements were performed at the 12-ID-C beamline of the Advanced Photon Source of the Argonne National Laboratory. A custom-made in situ electrochemical X-ray cell with a $6\\mathrm{-mm}$ diameter of $\\mathrm{Pt}(111)$ single crystal and a $\\mathrm{\\Ag/AgCl}$ reference electrode was used in grazing-incidence geometry (digital photograph images for the in situ set-up are presented in Supplementary Fig. 9a). The experimental geometry was similar to that used previously in grazing-incidence fluorescence X-ray absorption spectroscopy (GIF-XAS)55. The grazing angle of incidence was fixed at the total external reflection angle of the X-rays $(\\sim0.5^{\\circ})$ for the $\\mathrm{Pt}(111)$ substrate. Under this condition, the electric field at the surface is enhanced to achieve a maximum sensitivity of the elements on the surface. A Vortex detector (Hitachi High-technologies Science America) with an active area of $1\\mathrm{cm}^{2}$ and an energy resolution of ${\\sim}120\\mathrm{eV}$ was used. A cobalt filter for Ni K-edge XANES and a Mn filter for Fe K-edge XANES were used and the detector was positioned at $90^{\\circ}$ to the horizontally polarized incoming X-rays to suppress elastic scattering. Then, the detector distance was set to ${\\sim}3\\mathrm{cm}$ from the surface to optimize the signal-tobackground ratio. The spectra were normalized by the incident X-ray intensity and processed using the ATHENA software (Ifeffit 1.2.12). \n\nX-ray photoelectron spectroscopy analysis. X-ray photoelectron spectroscopy analysis was conducted using an Ommicron EA-125 hemispherical energy analyser with an Al $\\mathrm{K}_{\\alpha}$ X-ray source. \n\nIn situ ICP-MS coupled to SPRDE. The set-up for ICP-MS analysis coupled to SPRDE has been described in a previous report28. Metal ions such as Fe (56 and 57 amu), Co (59 amu), Mn (55 amu), Cu (64 amu) and Ni (60 amu) were detected with a PerkinElmer NexION 350S spectrometer coupled to an SPRDE. Electrochemical measurements were conducted in the same way as described in the Electrochemical measurements section. \n\nASF calculation. The ASF values were calculated according to our previous report27 as follows: \n\n$$\n\\mathrm{ASF}={\\frac{I-S}{S}}{\\bigg|}_{\\eta}\n$$ \n\nwhere $I$ indicates the rate of $\\mathrm{~\\i~}_{\\mathrm{~O~}_{2}}$ production (equivalent to the OER current density) and S indicates the rate of host metal dissolution (equivalent to the dissolution current density) at constant overpotential $\\eta$ . When dynamic stable Fe is incorporated into the host materials (Fe-containing KOH), the ASF (dynamic Fe–M hydr(oxy)oxide) values are simply the ASF values obtained for the corresponding values without Fe multiplied by the activity enhancement factor $\\left({\\frac{I_{\\mathrm{Ee}}}{I}}\\right)$ . \n\n$$\n\\mathrm{ASF}(\\mathrm{dynamicFe-Mhydr(oxy)oxide})=\\mathrm{ASF}(\\mathrm{withoutFe})\\times\\left({\\frac{I_{\\mathrm{Fe}}}{I}}\\right)\n$$ \n\nRRDE measurement for quantifying O2 production and calculation of FEoxygen. To quantify the actual production of $\\mathrm{O}_{2}$ and calculate the $\\mathrm{FE}_{\\mathrm{oxygen}};$ we used the RRDE method with a platinum ring. To calibrate the collection efficiency in the gas evolving reaction, the hydrogen evolution reaction was used (see detailed discussion in Supplementary Note 2). To calculate $\\mathrm{FE}_{\\mathrm{oxygen}};$ we measured each sample twice with different ring potentials (1.1 V for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and $0.4\\mathrm{V}$ for $\\mathrm{O}_{2}$ ). The production of $\\mathrm{O}_{2}$ was monitored using a ring potential of $0.4\\mathrm{V}$ versus RHE because at this potential the $\\mathrm{~O}_{2}$ reduction is in diffusional control while preventing $\\mathrm{H}_{\\mathrm{upd}},$ which would allow the $2e^{-}$ pathway during $\\mathrm{~O}_{2}$ reduction. For $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , we chose 1.1 V as it is a high enough potential for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ oxidation (diffusion-limiting region) while being below the thermodynamic potential of $\\mathrm{~O}_{2}$ evolution (1.23 V). $\\mathrm{FE}_{\\mathrm{oxygen}}$ is defined as follows: \n\n$$\n\\mathrm{FE_{oxygen}=\\frac{O_{2}e v o l u t i o n\\ c u r r e n t{(r i n g\\ c u r r e n t)}}{T o t a l\\ c u r r e n t{(d i s k\\ c u r r e n t)}}\\times C o l l e c t i o n\\ e f f i c i e n c t{(c o m p l i c u r n e n t)}}\n$$ \n\nComputational methods. Electronic structure calculations were performed within the framework of DFT with periodic boundary conditions using the VASP program56. All surface calculations were carried out using the implicit solvation model implemented in the VASPsol package and including the effects of electrostatics, cavitation and dispersion on the interaction between solute and solvent57,58. The Perdew–Burke–Ernzerhof (PBE) exchange-correlation functional59 and the van der Waals interactions described by a pairwise force field using \n\nthe DFT-D2 method of Grimme60 were used for all calculations. The projector augmented wave method and plane wave basis sets were used with energy cut-offs of $520\\mathrm{eV}$ for full cell geometry optimization and $400\\mathrm{eV}$ for geometry optimization with fixed cell parameters. Transition-metal elements were treated by the $\\mathrm{PBE+U}$ method with $U_{\\mathrm{eff}}=5.5,$ , 4.4 and $3.3\\mathrm{eV}$ for Ni, Co and Fe, respectively61. Transitionmetal oxyhydroxide MOOH $\\mathbf{M}=\\mathbf{Ni}$ , Co, Fe) monolayers were modelled by $2\\times4(001)$ periodic slabs using supercells (consisting of 16 MOOH units) with a vacuum layer of more than $20\\mathrm{\\AA}$ placed along the $z$ direction. The surface Brillouin zone was sampled with a $3\\times3\\times1$ Monkhorst–Pack k-point mesh. The total energy was converged to $10^{-5}\\mathrm{eV}$ for each electronic step using the self-consistent field method. All atoms were allowed to relax during the structure optimization until the force on each atom was below $0.03\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . Bader charge analysis was conducted to analyse the charge populations62. The XANES spectra were calculated using the ab initio multiple scattering code FEFF963 based on the optimized geometries to help interpret the experimental results. \n\nTo evaluate the adsorption energy of the Fe species on a surface site (denoted by $*^{\\prime}$ ) we chose the solvated $\\mathrm{Fe(OH)_{3}(H_{2}O)_{3}}$ molecular complex as a reference, in which Fe has sixfold coordination and a formal charge state of $+3$ . The adsorption reaction can be written as: \n\n$$\n^{*}+\\mathrm{Fe(OH)}_{3}(\\mathrm{H}_{2}\\mathrm{O})_{3}{\\longrightarrow}\\mathrm{Fe(OH)}_{3}{^{*}}+3\\mathrm{H}_{2}\\mathrm{O}\n$$ \n\nThe differential Fe adsorption energy $(\\Delta G_{\\mathrm{Fe-M}})$ on a metal oxyhydroxide surface is calculated as follows: \n\n$$\n\\Delta G_{\\mathrm{Fe-M}}=G_{(n+1)\\mathrm{Fe^{\\star}}}-G_{(n)\\mathrm{Fe^{\\star}}}-G_{\\mathrm{Fe-mol}}+3G_{\\mathrm{H2O-mol}}\n$$ \n\nwhere $n$ represents the number of Fe complexes adsorbed on the surface per supercell and $G_{(n+1)\\mathrm{Fe^{*}}}$ , $G_{(n)\\mathrm{Fe^{*}}}$ , $G_{\\mathrm{Fe-mol}}$ and $G_{\\mathrm{H2O-mol}}$ represent the free energies of the surface cell with $n+1$ adsorbed Fe species, the surface cell with $n$ adsorbed Fe species, an $\\mathrm{Fe(OH)}_{3}(\\mathrm{H}_{2}\\mathrm{O})_{3}$ molecular complex and a $\\mathrm{H}_{2}\\mathrm{O}$ molecule in solution under standard conditions, respectively. The average Fe adsorption energy $\\left(\\Delta\\bar{G}_{\\mathrm{Fe-M}}\\right)$ on a metal oxyhydroxide surface is calculated as follows: \n\n$$\n\\Delta\\bar{G}_{\\mathrm{Fe-M}}=(G_{(n)\\mathrm{Fe^{*}}}-G_{^{\\star}})/n-G_{\\mathrm{Fe-mol}}+3G_{\\mathrm{H2O-mol}}\n$$ \n\nwhere G\\* represents the free energy of the surface cell without adsorbed Fe species. \n\nThe total electronic energy of each system was obtained from the electronic structure calculation in VASP. The free energy was calculated by adding a Gibbs free-energy correction (including contributions from the zero-point energy, enthalpy and entropy) to the total energy calculated in VASP. The Gibbs free-energy corrections were calculated at $25^{\\circ}\\mathrm{C}$ using the standard statistical mechanical model after frequency calculations in VASP. For surface systems, calculated vibrational frequencies were used for the free-energy corrections. For the molecular Fe complex, entropy contributions, including vibrational, translational and rotational contributions, were taken into account. Solvation effects were taken into account using the implicit solvent model to calculate the solvation energy in VASP. For the $\\mathrm{H}_{2}\\mathrm{O}$ molecule in the liquid phase, the free-energy correction was calculated using the equivalent gas-phase freeenergy contribution at a saturated vapour pressure of $3534\\mathrm{Pa}$ (ref. 64). The calculated free-energy corrections are listed in Supplementary Tables 2–4. The structural information generated in the DFT calculations is shown at the end of Supplementary Data 1. \n\n# Data availability \n\nAll data are available in the main text, Supplementary Information and Source Data files. Data generated from DFT calculations can be found in Supplementary Data 1. \n\nReceived: 22 August 2019; Accepted: 7 February 2020; Published online: 16 March 2020 \n\n# References \n\n1.\t Stamenkovic, V. R., Strmcnik, D., Lopes, P. P. & Markovic, N. M. Energy and fuels from electrochemical interfaces. Nat. Mater. 16, 57–69 (2016). \n2.\t Uhlig, H. H. Corrosion and corrosion control. (Wiley: 1985). \n3.\t Peng, Z., Freunberger, S. A., Chen, Y. & Bruce, P. G. A reversible and higher-rate Li- $\\mathrm{~O}_{2}$ battery. Science 337, 563–566 (2012). \n4.\t Lim, H. et al. Reaction chemistry in rechargeable Li- ${\\bf\\nabla}\\cdot{\\bf O}_{2}$ batteries. Chem. Soc. Rev. 46, 2873–2888 (2017). \n5.\t She, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science 355, eaad4998 (2017). \n6.\t Rossmeisl, J., Qu, Z. W., Zhu, H., Kroes, G. J. & Norskov, J. K. Electrolysis of water on oxide surfaces. J. Electroanal. Chem. 607, 83–89 (2007). \n7.\t Seitz, L. C. et al. A highly active and stable $\\mathrm{IrO}_{x}/\\mathrm{SrIrO}_{3}$ catalyst for the oxygen evolution reaction. Science 353, 1011–1014 (2016). \n8.\t Man, I. C. et al. Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem 3, 1159–1165 (2011). \n9.\t Kim, J. S., Kim, B., Kim, H. & Kang, K. Recent progress on multimetal oxide catalysts for the oxygen evolution reaction. Adv. Energy Mater. 8, \n1702774 (2018). \n10.\tZhang, M., Respinis, M. & Frei, H. Time-resolved observations of water oxidation intermediates on a cobalt oxide nanoparticle catalyst. Nat. Chem. 6, 362–367 (2014). \n11.\tSuntivich, J., May, K. J., Gasteiger, H. A., Goodenough, J. B. & Shao-Horn, Y. A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles. Science 334, 1383–1385 (2011). \n12.\tFabbri, E. et al. Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting. Nat. Mater. 16, 925–931 (2017). \n13.\tTrotochaud, L., Young, S. L., Ranney, J. K. & Boettcher, S. W. Nickel iron oxyhydroxide oxygen evolution electrocatalysts: the role of intentional and incidental iron incorporation. J. Am. Chem. Soc. 136, 6744–6753 (2014). \n14.\tRoy, C. et al. Impact of nanoparticle size and lattice oxygen on water oxidation on ${\\mathrm{NiFeO}}_{x}{\\mathrm{H}}_{y}$ . Nat. Catal. 1, 820–829 (2018). \n15.\tZhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n16.\tDionigi, F. & Strasser, P. NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes. Adv. Energy Mater. 6, 1600621 (2016). \n17.\tHuang, Z. et al. Chemical and structural origin of lattice oxygen oxidation in $\\scriptstyle\\mathbf{Co-Zn}$ oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). \n18.\tStrmcnik, D. et al. The role of non-covalent interactions in electrocatalytic fuel-cell reactions on platinum. Nat. Chem. 1, 466–472 (2009). \n19.\tSubbaraman, R. et al. Enhancing hydrogen evolution activity in water splitting by tailoring $\\mathrm{Li^{+}{-N i}(O H)}_{2}$ -Pt interfaces. Science 334, 1256–1260 (2011). \n20.\tYang, C., Fontaine, O., Tarascon, J. -M. & Grimaud, A. Chemical recognition of active oxygen species on the surface of oxygen evolution reaction electrocatalysts. Angew. Chem. Int. Ed. 129, 8778–8782 (2017). \n21.\t Garcia, A. C., Touzalin, T., Nieuwland, C., Perini, N. & Koper, M. T. M. Enhancement of oxygen evolution activity of nickel oxyhydroxide by electrolyte alkali cations. Angew. Chem. Int. Ed. 58, 12999–13003 (2019). \n22.\tDanilovic, N. et al. Activity–stability trends for the oxygen evolution reaction on monometallic oxides in acidic environments. J. Phys. Chem. Lett. 5, 2474–2478 (2014). \n23.\tChang, S. H. et al. Functional links between stability and reactivity of strontium ruthenate single crystals during oxygen evolution. Nat. Commun. 5, 4191 (2014). \n24.\tDanilovic, N. et al. Using surface segregation to design stable Ru-Ir oxides for the oxygen evolution reaction in acidic environments. Angew. Chem. Int. Ed. 53, 14016–14021 (2014). \n25.\tGabbri, E. & Schmidt, T. J. Oxygen evolution reaction—the enigma in water electrolysis. ACS Catal. 8, 9765–9774 (2018). \n26.\tBinninger, T. et al. Thermodynamics explanation of the universal correlation between oxygen evolution activity and corrosion of oxide catalysts. Sci. Rep. 5, 12167 (2015). \n27.\tKim, Y. et al. Balancing activity, stability and conductivity of nanoporous core-shell iridium/iridium oxide oxygen evolution catalysts. Nat. Commun. 8, 1449 (2017). \n28.\tLopes, P. P. et al. Relationships between atomic level surface structure and stability/activity of platinum surface atoms in aqueous environments. ACS Catal. 6, 2536–2544 (2016). \n29.\tFrydendal, R. et al. Benchmarking the stability of oxygen evolution reaction catalysts: the importance of monitoring mass losses. ChemElectroChem 1, 2075–2081 (2014). \n30.\tGeiger, S. et al. The stability number as a metric for electrocatalyst stability benchmarking. Nat. Catal. 1, 508–515 (2018). \n31.\tLutterman, D. A., Surendranath, Y. & Nocera, D. G. A self-healing oxygen-evolving catalyst. J. Am. Chem. Soc. 131, 3838–3839 (2009). \n32.\tHuynh, M., Bediako, D. K. & Nocera, D. G. A functionally stable manganese oxide oxygen evolution catalyst in acid. J. Am. Chem. Soc. 136, 6002–6010 (2014). \n33.\tMefford, J. T. et al. Water electrolysis on $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ perovskite electrocatalysts. Nat. Commun. 7, 11053 (2016). \n34.\tGrimaud, A. et al. Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution. Nat. Chem. 9, 457–465 (2017). \n35.\tSubbaraman, R. et al. Trends in activity for the water electrolyzer reactions on $3d\\mathrm{\\M(Ni,Co,Fe,Mn)}$ hydr(oxy)oxide catalysts. Nat. Mater. 11, 550–557 (2012). \n36.\t Zeng, Z., Chang, K., Kubal, J., Markovic, N. M. & Greeley, J. Stabilization of ultrathin (hydroxyl)oxide films on transition metal substrates for electrochemical energy conversion. Nat. Energy 2, 17070 (2017). \n37.\tCorrigan, D. A. The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes. J. Electrochem. Soc. 134, 377–384 (1987). \n38.\tSubbaraman, R. et al. Origin of anomalous activities for electrocatalysts in alkaline electrolytes. J. Phys. Chem. C. 116, 22231–22237 (2012). \n39.\tWang, J. et al. In situ formation of molecular Ni-Fe active sites on heteroatom-doped graphene as a heterogeneous electrocatalyst toward oxygen evolution. Sci. Adv. 4, eaap7970 (2018). \n40.\tBurke, M. S. et al. Revised oxygen evolution reaction activity trends for first-row transition-metal (oxy)hydroxides in alkaline media. J. Phys. Chem. Lett. 6, 3737–3742 (2015). \n41.\tBurke, M. S. et al. Oxygen evolution reaction electrocatalysis on transition metal oxides and (oxy)hydroxides: activity trends and design principles. Chem. Mater. 27, 7549–7558 (2015). \n42.\tZou, S. et al. Fe (oxy)hydroxide oxygen evolution reaction electrocatalysis: intrinsic activity and the roles of electrical conductivity, substrate, and dissolution. Chem. Mater. 27, 8011–8020 (2015). \n43.\tLi, N. et al. Influence of iron doping on tetravalent nickel content in catalytic oxygen evolving films. Proc. Natl Acad. Sci. USA 114, 1486–1491 (2017). \n44.\tGörlin, M. et al. Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni–Fe oxide water splitting electrocatalysts. J. Am. Chem. Soc. 138, 5603–5614 (2016). \n45.\tFriebel, D. et al. Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting. J. Am. Chem. Soc. 137, 1305–1313 (2015). \n46.\tChen, J. Y. C. et al. Operando analysis of NiFe and Fe oxyhydroxide electrocatalysts for water oxidation: detection of $\\mathrm{Fe^{4+}}$ by Mössbauer spectroscopy. J. Am. Chem. Soc. 137, 15090–15093 (2015). \n47.\tXiao, H., Shin, H. & Goddard, W. A. Synergy between Fe and Ni in the optimal performance of $(\\mathrm{Ni,Fe})\\mathrm{OOH}$ catalysts for the oxygen evolution reaction. Proc. Natl Acad. Sci. USA 115, 5872–5877 (2018). \n48.\tGoldsmith, Z. K. et al. Characterization of NiFe oxyhydroxide electrocatalysts by integrated electronic structure calculations and spectroelectrochemistry. Proc. Natl Acad. Sci. USA 114, 3050–3055 (2017). \n49.\t Stevens, M. B., Trang, C. D. M., Enman, L. J., Deng, J. & Boettcher, W. Reactive Fe-sites in Ni/Fe (oxy)hydroxide are responsible for exceptional oxygen electrocatalysis activity. J. Am. Chem. Soc. 139, 11361–11364 (2019). \n50.\tSong, F. et al. An unconventional iron nickel catalyst for the oxygen evolution reaction. ACS Cent. Sci. 5, 558–568 (2019). \n51.\t Diaz-Morales, O., Ledezma-Yanz, I., Koper, M. T. M. & Calle-Vallejo, F. Guidelines for the rational design of Ni-based double hydroxide electrocatalysts for the oxygen evolution reaction. ACS Catal. 5, 5380–5387 (2015). \n52.\tBard, A. J. & Faulkner, L. R. Electrochemical Methods (Wiley, 2001). \n53.\tHammer, B. & Norskov, J. K. Theoretical surface science and catalysis— calculations and concepts. Adv. Catal. 45, 71–129 (2000). \n54.\tMcCrory, C. C. L., Jung, S., Peters, J. C. & Jaramillo, T. F. Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 135, 16977–16987 (2013). \n55.\tRhee, C. K. et al. Osmium nanoislands spontaneously deposited on a Pt(111) electrode: an XPS, STM and GIF-XAS study. J. Electroanal. Chem. 554, 367–378 (2003). \n56.\tKresse, G. & Furthmuller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n57.\t Mathew, K., Sundararaman, R., Letchworth-Weaver, K., Arias, T. A. & Henning, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 140, 084106 (2014). \n58.\tMathew, K., Chaitanya Kolluru, V. S., Mula, S., Steinmann, S. N. & Henning, R. G. Implicit self-consistent electrolyte model in plane-wave densityfunctional theory. J. Chem. Phys. 151, 234101 (2019). \n59.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phy. Rev. Lett. 77, 3865–3868 (1996). \n60.\tGrimme, S. Semiempirical GGA-type density functional constructed with a long-range dispersion correction. J. Comput. Chem. 27, 1787–1799 (2006). \n61.\tDurarev, S. L., Botton, G. A., Savrasov, S. Y., Humphreys, C. J. & Sutton, A. P. Electron-energy-loss spectra and structural stability of nickel oxide: an LSDA $+\\mathsf{U}$ study. Phys. Rev. B 57, 1505–1509 (1998). \n62.\tSanville, E., Kenny, S. D., Smith, R. & Henkelman, G. Improved grid-based algorithm for bader charge allocation. J. Comput. Chem. 28, 899–908 (2007). \n63.\t Rehr, J. J., Kas, J. J., Vila, F. D., Prange, M. P. & Jorissen, K. Parameter-free calculatons of X-ray spectra with FEFF9. Phys. Chem. Chem. Phys. 12, 5503–5513 (2010). \n64.\t Peterson, A. A. & Norskov, J. K. Activity descriptor for $\\mathrm{CO}_{2}$ electroreduction to methane on transition-metal catalysts. J. Phys. Chem. Lett. 3, 251–258 (2012). \n\n# Acknowledgements \n\nThe research was carried out at Argonne National Laboratory and supported by the Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division. Use of the Center for Nanoscale Materials and the Advanced Photon Source, Office of Science user facilities, was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, under contract no. DE-AC02-06CH11357. T.K. thanks the Japan Society for the Promotion of Science for Postdoctoral Fellowship. H.H. acknowledges the funding support from the Visiting Faculty Program of the Department of Energy. \n\n# Author contributions \n\nD.Y.C., P.P.L. and N.M.M. designed the experiments. D.Y.C., P.P.L. and P.F.B.D.M. conducted the electrochemical measurements and analysis. H.H. and P.Z. performed DFT calculations and analysis. D.Y.C., T.K., H.Y., S.S. and S.L. conducted in situ XANES measurements and analysis. D.T. and Y.Z. carried out STM and AFM analyses. D.S. and V.R.S. discussed and commented on the results. D.Y.C., P.P.L., P.Z. and N.M.M. wrote the manuscript. All authors approved the final version of the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-020-0576-y. \nCorrespondence and requests for materials should be addressed to N.M.M. \nReprints and permissions information is available at www.nature.com/reprints. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 " + }, + { + "id": "10.1038_s41467-019-14054-9", + "DOI": "10.1038/s41467-019-14054-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-14054-9", + "Relative Dir Path": "mds/10.1038_s41467-019-14054-9", + "Article Title": "Graded intrafillable architecture-based iontronic pressure sensor with ultra-broad-range high sensitivity", + "Authors": "Bai, NN; Wang, L; Wang, Q; Deng, J; Wang, Y; Lu, P; Huang, J; Li, G; Zhang, Y; Yang, JL; Xie, KW; Zhao, XH; Guo, CF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Sensitivity is a crucial parameter for flexible pressure sensors and electronic skins. While introducing microstructures (e.g., micro-pyramids) can effectively improve the sensitivity, it in turn leads to a limited pressure-response range due to the poor structural compressibility. Here, we report a strategy of engineering intrafillable microstructures that can significantly boost the sensitivity while simultaneously broadening the pressure responding range. Such intrafillable microstructures feature undercuts and grooves that accommodate deformed surface microstructures, effectively enhancing the structural compressibility and the pressure-response range. The intrafillable iontronic sensor exhibits an unprecedentedly high sensitivity (S-min > 220 kPa(-1)) over a broad pressure regime (0.08 Pa-360 kPa), and an ultrahigh pressure resolution (18 Pa or 0.0056%) over the full pressure range, together with remarkable mechanical stability. The intrafillable structure is a general design expected to be applied to other types of sensors to achieve a broader pressure-response range and a higher sensitivity.", + "Times Cited, WoS Core": 600, + "Times Cited, All Databases": 631, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000551459800005", + "Markdown": "# Graded intrafillable architecture-based iontronic pressure sensor with ultra-broad-range high sensitivity \n\nNingning Bai1,4, Liu Wang 1,2,4, Qi Wang1, Jue Deng1,2, Yan Wang1, Peng Lu1, Jun Huang1, Gang Li1, Yuan Zhang1, Junlong Yang1, Kewei Xie1, Xuanhe Zhao $\\textcircled{1}$ 2 & Chuan Fei Guo 1,3\\* \n\nSensitivity is a crucial parameter for flexible pressure sensors and electronic skins. While introducing microstructures (e.g., micro-pyramids) can effectively improve the sensitivity, it in turn leads to a limited pressure-response range due to the poor structural compressibility. Here, we report a strategy of engineering intrafillable microstructures that can significantly boost the sensitivity while simultaneously broadening the pressure responding range. Such intrafillable microstructures feature undercuts and grooves that accommodate deformed surface microstructures, effectively enhancing the structural compressibility and the pressure-response range. The intrafillable iontronic sensor exhibits an unprecedentedly high sensitivity $(S_{\\mathsf{m i n}}>220\\mathsf{k P a^{-1}})$ over a broad pressure regime $\\left(0.08\\mathsf{P a}\\mathsf{-}360\\mathsf{k P a}\\right)$ , and an ultrahigh pressure resolution ( $\\cdot18\\mathsf{P a}$ or $0.0056\\%$ ) over the full pressure range, together with remarkable mechanical stability. The intrafillable structure is a general design expected to be applied to other types of sensors to achieve a broader pressure-response range and a higher sensitivity. \n\nlexible pressure sensors and electronic skins (e-skins) have attracted much interest because of their capability to sense mechanical stimuli and have thus been envisioned as key technologies for the applications of health monitoring1–3, artificial intelligence4,5, and human-machine interfaces6–8. A capacitive pressure sensor (CPS), a device that consists of two electrodes sandwiching a soft dielectric between them, transduces pressure stimuli to capacitance signals. While CPSs often present advantages of high-drift stability and a simple structure, and are considered as a promising selection for high-performance flexible pressure sensing9–13, they exhibited limited sensitivity (S) and low-pressure resolution over a broad pressure range or a saturated response at high pressures. A conventional piezo-CPS usually employs a blanket dielectric film that is incompressible and viscoelastic, resulting in the device exhibiting low-sensitivity together with low-response speed. Engineering the dielectric film with microstructured surfaces has proven to be an effective method to improve both sensitivity and response speed14–16. These applied microstructured surfaces include a wide variety of topographical structures such as micro-pyramid arrays1,3,16,17, wrinkles18,19, micro-domes20, micro-pillar arrays21,22, and other cone-like patterns directly molded from natural prototypes such as plant leaves23–25. Such structures, however, are mechanically stable upon compression, and thus respond effectively only under low pressures. As a result, this strategy fails to produce an adequately high sensitivity for sensors over a wide pressure range $\\mathrm{(\\dot{S}_{m a x}<2k\\check{P}a^{-1})^{16,21,2\\dot{6},27}}$ . Recently, incorporating an elastomer with ionic liquid as the dielectric has emerged as a method for further enhancing the sensitivity25,28–31. By forming electron double layers (EDLs) at the dielectric/electrode interface32,33, the capacitance of iontronic devices can be remarkably elevated due to the atomic scale distance $({\\sim}1\\ \\mathrm{nm})$ between positive and negative charges at the EDL interface, significantly promoting the piezo-capacitive effect upon compression. While both high sensitivity and high-pressure resolution at pressures over $\\mathrm{{i00kPa}}$ are demanded for various applications such as robotic manipulation, pressure monitoring in human body, and pressure tests in high-speed fluids, current microstructured CPSs, including supercapacitive iontronic e-skins and sensors, suffer from limited or saturated response under high pressures $(>100$ kPa)20,25,29,30,34,35. The unreconciled tradeoff between high sensitivity and a broad working range of pressures for flexible pressure sensors (not limited only to capacitive-type sensors) is attributed to the low compressibility of the stable microstructures, along with their structural stiffening with increasing pressure. \n\nHere, we propose an iontronic flexible pressure sensor using a graded intrafillable architecture (GIA) consisting of unstable protruding microstructures of various heights, denoted as protrusions, that can easily buckle or bend upon compression, as well as complementary undercuts and grooves that allow for additional compressibility by accommodating the compressed protrusions. Such intrafillability plays a crucial role in promoting structural compressibility while simultaneously forming full contact area with the electrode, leading to a high sensitivity $(220{-}3300\\mathrm{kPa^{-}}^{1}),$ ) and a high-pressure resolution (on the order of $10\\mathrm{Pa})$ over a broad pressure range up to $360\\mathrm{kPa}$ . The sensors also show exceptional mechanical stability without noticeable fatigue over 5000 compression/release cycles at a high pressure of $300\\mathrm{{\\bar{kPa}}}$ , or over 2000 bending/unbending cycles at a bending radius (R) of $6.5\\mathrm{mm}$ . Given the large specific capacitance of the iontronic interface, the sensors exhibit a high-signal intensity and low noise when scaled down to the microscale (exemplified by $50\\times50~{\\upmu\\mathrm{m}}$ devices), such that they are expected to be an ideal candidate for a high-density sensing pixels array, which has also been experimentally demonstrated in this work. The sensors studied here will be highly useful when applied to robot manipulation, pressure measurement in high-speed fluids (including aviation tests), where high-pressure resolution at highpressure regimes is required. Additionally, the method of using GIA for highly sensitive pressure sensing over a broad pressure range, as a general mechanical design, will be effective when applied to other tactile sensors employing different material systems or different sensing mechanisms. \n\n# Results \n\nPrinciples of GIA design and the sensing mechanism. The term intrafillability we called here refers to the capability of a structure to accommodate its deformed portion by means of self-filling. Distinct from even surfaces, key morphological features of an intrafillable structure are the undercuts and grooves on the surface that can offer spaces to accommodate surrounding structures undergoing deformation. To elucidate the underlying mechanism by which a GIA produces remarkable sensitivity over a broad pressure regime, we investigated four representative microstructures by performing finite element analysis (FEA) (Fig. 1a): a hemisphere; a tilted pillar; an intrafillable pillar without gradient; and the GIA. In general, soft materials used for fabricating pressure sensors are incompressible, that is, the material preserves its volume during mechanical deformation. In the absence of interior voids (i.e., foam structure) or surface grooves, bulk structures made of incompressible materials exhibit high resistance to external pressure, yielding a low structural compressibility, which has been clearly exemplified by the hemisphere in Fig. 1a. \n\nThe tilted pillar in Fig. 1a represents a class of unstable protruding structures which can buckle down when compressed. However, the buckled pillar still presents rapidly increasing pressure-resistance once intimate contact is formed, performing like stable structures. Distinctly, the GIA, which has dense surface undercuts and grooves that can accommodate buckled protrusions, will improve the structural compressibility because of the following two aspects. First, the pillars buckle and start to fill into the surface undercuts upon compression, allowing for large deformations before they fully contact the bottom (see Fig. 1a, in the case of $50\\mathrm{kPa})$ . Second, due to the uneven nature of the surface undercuts, there still exist some gaps between the buckled pillars and the surface undercuts after contact forms (see Fig. 1a, at $100\\mathrm{kPa},$ ). These gaps will be gradually filled as pressure grows, which allows the structure to be further compressed over high pressures (see Fig. 1a, from 50 to $400\\mathrm{kPa},$ ). \n\nIn addition to the surface undercuts, by further introducing a height gradient among the distributed protrusions, the electrode will come into shorter protrusions after the taller ones buckle, resulting in a gradually increasing contact area between the GIA film and the electrode over a wide pressure regime. Meanwhile, the initial contact area $A_{0}$ prior to applying pressure is accordingly minimized such that the normalized change of contact area ${\\Delta A}/{A_{0}}$ of the GIA shows a substantial growth with increasing pressure in comparison to the other microstructures investigated (Fig. 1b). Such a significant increase of the normalized contact area subsequently escalates the specific capacitance due to the formation of EDLs at the iontronic GIA film/electrode interface, i.e., $C_{\\mathrm{EDL}},$ which is about 5–6 orders of magnitude higher than its non-iontronic counterparts. As illustrated in Fig. 1c, there are a large number of low molar positive and negative ion pairs distributed in the iontronic GIA film. When the voltage is applied, electrons on the electrode and the counter ions in the GIA aggregate within the contact area at a nanometer distance, elevating the capacitance33,34. \n\nA specific sandpaper with bulging grains and underlying holes (Supplementary Fig. 1a) was found to be an ideal template for fabricating such a GIA film (Supplementary Fig. 1b). Figure 1d illustrates the fabrication process for the GIA-based iontronic pressure sensor, in which the GIA-based $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ film (blue) and Au (brown) are employed as the dielectric and electrode, respectively. $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ solution is casted on the sandpaper to be cured, followed by demolding. For the ionic $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{\\bar{P}O}_{4}$ film, the protrusions are molded from the holes of the sandpaper, while the grooves and undercuts are molded from the bulging grains. Figure 1e is a tilt-view scanning electron microscopy (SEM) image of the $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ film demolded from the template, showing graded protrusions and surface grooves, as well as undercuts that are highlighted by white dashed circles. Cross-sectional view SEM images (Fig. 1f) also exhibit these protrusions and undercuts, confirming that the $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ film is a legitimate GIA as we proposed. We also experimentally visualized the increase of contact area between $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ GIA film and electrode under increasing pressure by dyeing the electrodes with ink (Supplementary Fig. 2a). Consistent with the FEA results, the contact area shows a substantial increase as the pressure increases, even in the high-pressure regime (Supplementary Fig. 2b). \n\n![](images/60179ab2743bcd60e16868cd9a5ebd4253d46fcc2f5aefa07b9d5fbf29bc4c89.jpg) \nFig. 1 Principles of graded intrafillable architecture (GIA) design and the sensing mechanism. a Stress distribution of simulation results for different architectures under pressures up to $400\\mathsf{k P a}$ : a hemisphere; a tilted pillar, an intrafillable pillar without gradient, and the GIA. b Contact area variation between the dielectric layers with different architectures and an opposing electrode under a broad sensing range $(0-400\\mathsf{k P a})$ . c Schematic illustration for the functioning of the iontronic pressure sensor before and after applying pressure. d Schematic illustration of the preparation of a GIA-based iontronic pressure sensor. e A $45^{\\circ}$ tilt-view and f cross-sectional view SEM images of the $\\mathsf{P V A}/\\mathsf{H}_{3}\\mathsf{P O}_{4}$ GIA film, showing grooves and undercuts. \n\nSensing properties of the GIA-based iontronic pressure sensor. The sensitivity of a capacitive-type pressure sensor is defined as $S=\\delta(\\Delta C/C_{0})/\\delta P$ ; where $C$ and $C_{0}$ are the measured capacitance and the initial capacitance before applying pressure $(P)$ , respectively. A high sensitivity is achieved when a small change in pressure leads to a large capacitance change $\\Delta C$ . For noniontronic CPS, $\\Delta C$ stems from the reduction in dielectric thickness and effective dielectric constant, which is usually limited to a few times that of $C_{0}$ . Distinctly, $\\Delta C/C_{0}$ of iontronic sensors can reach up to $10^{6}$ due to the formation of EDLs at the dielectric/ electrode interface. The sensitivity of the GIA-based iontronic sensor studied here exhibits an unprecedentedly high value over a wide pressure range (Fig. 2a). The averaged sensitivity is $S_{1}\\sim$ $3302.9\\dot{\\mathrm{kPa}}^{-1}$ (or $3.{\\overset{\\vartriangle}{3}}\\operatorname*{Pa}^{-{\\overset{\\vartriangle}{1}}}.$ ) when the pressure is below $10\\mathrm{kPa}$ , and is $S_{2}\\sim671.7\\mathrm{kPa^{-1}}$ within the pressure range of $10\\mathrm{-}100\\mathrm{kPa}$ . In the high-pressure regime $({>}10\\bar{0}\\mathrm{kPa})$ , the sensor exhibits a nearly linear response with a sensitivity $S_{3}\\sim229.9\\mathrm{kPa}^{-1}$ up to $360\\mathrm{kPa}$ . Surprisingly, the minimum sensitivity of our sensor is higher than the maximum sensitivity of any previously reported CPS3,16,23–25,29,36. Note that such a remarkable sensing performance is quite stable over a few samples (Supplementary Fig. 3). Three phases of the sensitivity can be briefly elucidated as follows. Before pressure is applied, the contact area of the GIA/electrode interface is substantially small (Supplementary Fig. 4), thus the initial capacitance $C_{0}$ is only several pF due to minimal EDL formation, and almost independent of test frequency (Supplementary Fig. 5a). As the pressure gradually increases to $10\\mathrm{kPa}$ , the electrode come into contact with the tip of more taller protrusions (See experiments in Supplementary Fig. 2b at $10\\mathrm{kPa}$ and FEA in Supplementary Fig. 4), resulting in a larger frequencydependent EDL capacitance, which is an intrinsic characteristic of iontronic sensors (Supplementary Fig. 5b). The transition from a low initial capacitance $(C_{0}\\sim\\mathrm{pF)}$ to iontronic supercapacitance $(C\\sim\\mathrm{nF})$ produces an ultrahigh sensitivity in the low-pressure regime. After that, when the pressure increases up to $100\\mathrm{kPa}$ , buckling of taller protrusions takes place, followed by the intrafilling and contact with surface grooves (Fig. 1a, at $50\\mathrm{kPa}$ . During this process, more microscale EDL capacitors are formed in parallel, leading to increasing capacitance. As the pressure further increases, the intrafilling advances by means of substituting more interfacial gaps with buckled protrusions, and in the meanwhile the electrode comes to contact with protrusions of lower altitude, allowing for a steady escalation of EDL formation until most gaps are filled. \n\n![](images/4a383feec3fa7eab8bf57fafbaa8443a3fa4567a4e4b92b596705d57ae243cc2.jpg) \nFig. 2 Sensing properties of the iontronic pressure sensor. a Change of capacitance over the pressure range up to $360\\mathsf{k P a}$ . b Limit of detection (LOD). c Response time at the frequency of $1k H z$ . d Working stability tested over 5,000 cycles under a high pressure of $300\\mathsf{k P a}$ . e Bending responses over 2,000 cycles at a bending radius (R) of $\\mathord{\\sim}6.5\\mathsf{m m}$ . \n\nIn addition, our sensor exhibits a low limit of detection (LOD) of $0.08\\mathrm{Pa}$ as evidenced in Fig. 2b. To evaluate the dynamic response speed of the sensor, a weight of $10\\mathrm{g}$ (equivalent pressure ${\\sim}5\\mathrm{{kPa})}$ was gently placed on the pressure sensor followed by a quick release revealing a 9 ms response time and an $18\\mathrm{ms}$ relaxation time (Fig. 2c), which are much faster than those of human skin $\\left(30-50\\mathrm{ms}\\right)$ and existing microstructured piezo$\\mathrm{CPSs^{16,17,22,37,38}}$ . For flexible pressure sensors, high-mechanical durability under long-time or cyclic use also plays a crucial role in the reliable input-output relation. Repeated compression/release test over 5000 cycles with a peak pressure of $300\\mathrm{kPa}$ was performed, and the sensor exhibits no signal drift or fluctuation (Fig. 2d) and negligible hysteresis (Supplementary Fig. 6) during the cyclic tests. In addition to the cyclic compression testing, we also investigated the flexibility of the device by testing signal stability under cyclic bends. Figure 2e suggests that our device maintains a remarkable mechanical robustness without noticeable fatigue after 2000 bending/unbending cycles with a bending radius of $6.5\\mathrm{mm}$ . The high reliability under cyclic bending indicates that our sensor is a promising candidate for detecting bending-related body motion. We prepared a $3\\ \\mathrm{~mm}\\times15\\ \\mathrm{mm}$ sensor and evaluated its capability of detecting the bending of human finger and elbow joints (Supplementary Fig. 7a, b), confirming that different bending conditions can be easily distinguished according to the signal change. In addition, the sensor was found to be capable of detecting the pulse in a human radial artery, and the signal shows a perfect waveform with quite strong characteristic peaks (Supplementary Fig. 7c). The aforementioned merits, including ultrahigh sensitivity, broad working range of pressure, short response/relaxation time, and high stability to mechanical loadings, all indicate the great potential of our device for various applications from health monitoring to wearable sensors, and for intelligent robotics. \n\nStability under different levels of relative humidity and different temperatures is also critical to real applications since humidity and temperature often affect the response of iontronic capacitive devices. Here, the iontronic pressure sensor is well packaged, such that the humidity change does not affect the signal (Supplementary Fig. 8a), while increasing temperature results in higher capacitance signal intensity (Supplementary Fig. 8b) due to the improved mobility of ions under higher temperature. The iontronic pressure sensor would, therefore, need to be calibrated to eliminate temperature effects when it is used beyond room temperature. \n\nExtremely high-pressure resolution. A key advantage of our GIA-based iontronic pressure sensor is its sufficiently high sensitivity over a broad pressure regime, and its high-sensitivity under high pressure allows for a high-pressure resolution. Existing CPS or e-skins with surface microstructured dielectric often present low sensitivity or a saturated response above $50\\mathrm{kPa}$ , and thus their pressure resolution is expected to be quite low. An ideal flexible pressure sensor, however, should detect tiny changes in pressure not only under low pressures but also under extremely high pressures, as schematically illustrated in Fig. 3a. The sensing performance of our device under three different reference pressures of $P_{0}=3$ , 30, and $300\\mathrm{kPa}$ is presented in Fig. $3\\mathrm{b-d}$ , respectively. For the test, the device was first compressed to a reference pressure, followed by consecutively adding three lightweight metal nuts, each weighing about $\\mathrm{420mg,}$ which corresponds to an effective pressure increment of $\\Delta P\\sim85\\mathrm{Pa}$ , and capacitance was measured throughout the process. It shows that each pressure increment successfully leads to a stepped escalation of the capacitance with a swift response, and a steady signal is also confirmed for each pressure increment. \n\nSeveral experiments were carried out to further demonstrate such extraordinary pressure resolution at high pressures. We first prepared a circle-shaped device with a radius of $8\\mathrm{mm}$ and loaded it by placing it under a connecting rod $\\operatorname{12.5g}$ radius $8\\mathrm{mm}$ ) and three concrete bricks $({\\sim}6.4\\mathrm{kg})$ , i.e., equivalent to a reference pressure $P_{0}=320\\mathrm{kPa}$ , and we then gently put a pencil $(\\Delta P\\sim300$ $\\mathrm{Pa})$ , a layer of pencil shavings $(\\Delta P\\sim40\\mathrm{Pa})$ , and feather-like fibers $(\\Delta P\\sim18\\mathrm{Pa})$ in sequence on top of the bricks (Fig. 3e). The corresponding capacitance changes are displayed in Fig. 3f, which shows that each tiny pressure change can be precisely recorded and differentiated. In another experiment, a square-shaped sensor with a lateral size of ${\\sim}1\\mathrm{cm}$ was placed under the rear wheel of a car $(2000\\mathrm{kg},$ which generates a pressure of a few hundred kilopascals), as indicated by the arrow in Fig. 3g. A bag of paper towels weighting only $1.7\\mathrm{kg}$ was taken from the trunk of the car and then reloaded, and the capacitance changes were successfully detected as shown in Fig. 3h. Such a tiny pressure change cannot be discriminated by using iontronic sensors with other stable microstructures, such as microcones (Supplementary Fig. 9). This sensor is also capable of distinguishing the embarkation/ debarkation of a $50\\mathrm{kg}$ female passenger with a large capacitance change $(\\sim12\\mathrm{nF})$ , as shown in Fig. 3i. Additionally, the measured signal also confirms that our sensor responses swiftly and sensitively to dynamic pressures (e.g., the circled oscillations in Fig. 3i reflect vibrations when the passenger gets into and out of the car), while providing stable output for static pressures with superior recoverability. Incorporating the morphological features of GIA, i.e., graded protrusions and surface undercuts, with ionic characteristics eventually leads to the prominent sensing behavior of our device over a sufficiently large pressure range. \n\n![](images/4f11b191b5a924aa432c39d060897f86eb32f4a83fd9c10c30f4c73ba4799d9e.jpg) \nFig. 3 Extremely high-sensing resolution of the graded intrafillable architecture (GIA)-based iontronic pressure sensor. a Schematic illustration of the response of the iontronic pressure sensor to low and high pressure, and detection of micro pressure under high pressure. b–d Detection of micro pressure under loading pressures of b $3\\mathsf{k P a}$ , $\\mathtt{c30}\\mathtt{k P a}$ , and d $\\mid300\\mathsf{k P a}_{\\iota}$ , respectively. e Detection of different micro pressure objects placed on three concrete bricks weighing $320\\mathsf{k P a}$ . f Capacitance signals corresponding to panel e. $\\pmb{\\mathsf{g}}$ Experimental set-up of a car with a GIA-based iontronic pressure sensor bonded under a rear tire, the test frequency is $10k H z$ . h Capacitance signals corresponding to a loaded, unloaded, and reloaded $1.7\\upk g$ bag of paper towels in the trunk of the car. i Capacitance signals corresponding to a $50\\up k g$ female passenger getting into and out of the car. The test frequency is $10k\\mathsf{H}z$ . \n\n![](images/1f0e41f1093ff849d6206828425b3c38c6bf802cff7b7954db2b3defbf2c8169.jpg) \nFig. 4 Comparison of the sensitivity of our pressure sensor with existing capacitive sensors. \n\nAs summarized in Fig. 43,14,16,20,23–25,29,36,39–41, our GIAbased iontronic pressure sensor shows an incomparably high sensitivity and an ultrabroad work range of pressure, outperforming existing piezo-CPS reported in the literature to the best of our knowledge. It is also worth noting that the sensitivity and working range of the GIA-based iontronic pressure sensor can be readily scaled by changing only the material moduli while maintaining other parameters the same (e.g., structures, ion density, and loading condition). According to Persson contact theory for randomly rough surface42, the normalized contact area can be expressed as \n\n$$\n\\frac{\\Delta A}{A_{0}}=\\alpha\\frac{P}{E}\n$$ \n\nwhere $\\alpha$ is a geometric parameter, which depends only on surface morphology. Therefore, for a specific surface structure (i.e., $\\alpha$ is constant), a larger modulus will render a higher sensing range while compromises the sensitivity simultaneously. This implication can also be supported by simulations of a specific GIA with different Young’s moduli of $E_{0}$ ; $2E_{0}$ and $5E_{0}$ (Supplementary Fig. 10a). The corresponding normalized contact area ${\\bar{\\Delta}A}/A_{0}$ as a function of applied pressure are shown in Supplementary Fig. 10b, which clearly suggests that the sensing range is increased when the material gets stiffer. \n\nThe high-pressure resolution of the sensor is of great importance. Although pressure-resolution is a critical parameter for conventional pressure sensors that are used in industry, it has been overlooked in $\\boldsymbol{\\mathbf{\\mathit{e}}}$ -skins or flexible pressure sensors. For reference, human skin can typically resolve a pressure difference of $7\\%$ under small pressures43. Our flexible sensor can recognize micro-pressure as low as $3\\mathrm{Pa}$ under a low pressure of $3\\mathrm{kPa}$ (Supplementary Fig. 11). More importantly, at an extremely high pressure of $320\\mathrm{kPa}$ , our flexible sensor still presents a highpressure resolution of $18\\mathrm{{Pa}}$ , or $0.0056\\%$ , which is at least four orders of magnitude higher than that of human skin. Such a sensor will be quite useful in the accurate manipulation of heavy objects by robots, as well as pressure resolution for wind tunnel tests. For example, the pressure mapping of a plane model in a high pressure wind tunnel test requires pressure sensors that can work over three atm with a minimal pressure resolution of 100 Pa. Although a few commercial sensors are already available, e.g., the PSI 8400 system44, those sensors are often bulky, non-flexible, and need to be implanted in the plane body by drilling holes. Here, our sensors can resolve even smaller pressure change (18 Pa) under the high pressure required in wind tunnel tests, and are thus reasonably envisaged as flexible skins that are thin, costeffective, and easily attached onto the curvilinear surfaces of a plane model for pressure mapping. Other applications where high flexibility and high-pressure resolution over a broad pressure range are required simultaneously may be found for our sensors. \n\nSpatial resolution of GIA-based micro-sensor arrays. Directcapacitive-type pressure sensors often suffer from low-specific capacitance and thus the signal is susceptible to noise when the devices are scaled down to the microscale. The iontronic sensor studied here is based on EDL capacitance or supercapacitance that allows for high-resolution pressure sensing with a high signal-to-noise ratio. Three micro-sensors with areas of $50~{\\upmu\\mathrm{m}}\\times$ $50\\upmu\\mathrm{m},100\\upmu\\mathrm{m}\\times100\\upmu\\mathrm{m},$ and $200~{\\upmu\\mathrm{m}}\\times200~{\\upmu\\mathrm{m}}$ were fabricated and their real-time responses to cyclic loading/unloading testing under a peak pressure $P=10\\mathrm{kPa}$ are presented in Fig. 5a. \n\nOwing to the high and stable capacitance density (Supplementary Table 1), our micro-sensors are able to maintain a reliable sensing performance with a high-signal intensity and negligible noise with an area of at least $50\\upmu\\mathrm{m}\\times50\\upmu\\mathrm{m}$ . Therefore, our iontronic sensors can be used for electronics skins for highresolution pressure mapping on the scale of ${\\sim}100\\upmu\\mathrm{m}$ . A microsensor array of $6\\times6$ pixels over an area of $1.6\\ \\mathrm{mm}\\times1.6\\mathrm{mm}$ (Fig. 5b, pixel–pixel spacing is $150\\upmu\\mathrm{m})$ with each sensing pixel being a circular sensor of $60\\upmu\\mathrm{m}$ in diameter was used to verify the pressure mapping on the sub-millimeter scale, and the microelectrode is displayed in the inset of Fig. 5b. A tiny chip $(0.2\\:\\mathrm{g})$ was placed on the skin, partially covering it at two different locations and orientations, and a pressure of $50\\mathrm{kPa}$ was applied for each. The location information was recorded and is precisely reflected in the corresponding pressure mapping images shown in Fig. 5c, d. It should be noted that no transistors were used in our micro-sensor array, while transistors are otherwise required for devices with high-spatial resolution, significantly simplifying the fabrication and reducing the cost. \n\nThe GIA-based iontronic sensor proposed in this work exhibits high sensitivity and high-pressure resolution over a wide pressure-sensing range due to the high intrafillability. Such a mechanical design is general for enhancing structural compressibility by intrafilling, and is also expected to be effective in other types of sensors, such as non-iontronic piezo-capacitive, piezo-resistive, and triboelectric sensors, for sensitive pressure sensing with a broad working range of pressure. For instance, we compared the sensitivity between non-iontronic GIA-based and hemispherical microstructurebased sensors (Supplementary Fig. 12a), and the GIA-based sensor exhibits a sensitivity significantly higher than that of the sensor with micro-hemispheres up to $\\dot{3}60\\mathrm{{kPa}}$ (Supplementary Fig. 12b). However, in the absence of EDL, the capacitance change of non-iontronic sensors are only limited to a few times the initial value. Therefore, the sensitivity for non-iontronic pressure sensors is much smaller than that of the iontronic pressure sensors (Supplementary Fig. 12c, d). It is also worth noting that ionic film (Young’s modulus $E\\sim2.5\\mathrm{MPa}_{\\it.}$ ) is much softer than its non-ionic counterpart $(E\\sim67\\mathrm{MPa})$ (Supplementary Fig. 13), which undoubtedly benefits the sensor and leads to higher sensitivity. \n\n![](images/c21cb8d8579efc65e9a00b2b62126d86e834eb1bcc4b7a01c68042bc01b6cccc.jpg) \nFig. 5 Spatial resolution of graded intrafillable architecture (GIA)-based micro-sensor arrays. a Capacitance response of GIA-based micro-sensors with different sizes (square: $50~{\\upmu\\mathrm{m}}\\times50~{\\upmu\\mathrm{m}}$ , $100\\upmu\\mathrm{m}\\times100\\upmu\\mathrm{m}.$ , and $200\\upmu\\mathrm{m}\\times200\\upmu\\mathrm{m})$ at the pressure of $10\\mathsf{k P a}$ . b GIA-based micro sensor array ( $(6\\times6$ pixels) with circular sensing pixels. At right is the micro-electrode (pixel diameter, $60\\upmu\\mathrm{m};$ ; pixel spacing, ${150\\upmu\\mathrm{m}};$ . c, d Pressure distribution mapping of the microsensor array in the shapes of c a rectangle and d a triangle $(50\\models\\mathsf{P a})$ . \n\n# Discussion \n\nUsing a graded intrafillable architecture, in which easy-to-buckle protrusions and underlying undercuts and grooves that accommodate compressed microstructures are introduced, the ionic film effectively improves a sensor’s structural compressibility via intrafilling. Capacitive-type sensors incorporating ionic film with such a GIA are able to simultaneously achieve a maximum sensitivity over $3\\mathrm{Pa}^{-1}$ , and a large pressure-response range to at least $360\\mathrm{kPa}$ , at which the sensitivity reaches over $200\\mathrm{\\check{kPa}}^{-1}$ . The sensors also exhibit a high-pressure resolution ${\\sim}18\\mathrm{Pa}$ (or $0.0056\\%)$ at a high pressure of $320\\mathrm{{kPa}}$ . The high sensitivity over a broad pressure range stems from the micro-protrusions that buckles upon compression, as well as the intrafillable design that can accommodate deformed structures. The intrafillable structures, in the meanwhile, contribute to a rapid response speed of less than $10\\mathrm{m}s_{;}$ , as well as high stability over 5000 loading/ unloading cycles at a peak pressure of $300\\mathrm{{kPa}}$ . We envisage that our GIA-based iontronic pressure sensor can find a verity of applications in health monitoring, electronic skins for tactile sensing, and pressure measurement in aerodynamics. We also believe that the intrafillable structure provides a general design strategy for other types of tactile sensors with a high sensitivity over a broad pressure range. \n\n# Methods \n\nFinite element analysis. FEA was performed using the commercial package ABAQUS 6.14. The $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ -based GIA was modeled as an incompressible neo-Hookean material with Young’s modulus $E\\sim2.5\\mathrm{MPa}$ according to experimental measurement. The PI-Au electrode $\\mathrm{'}E\\sim3\\mathrm{GPA})$ was simply treated as a rigid plate (not shown in Fig. 1a) and compressed downward. All contact interactions were assumed to be frictionless without penetration. Materials moduli were characterized in Supplementary Fig. 13. The complete simulation process is provided in the Supplementary Movie. The initial GIA/electrode contact area $(A_{0})$ in FEA was evaluated at a pressure of $100\\mathrm{Pa}$ . \n\nPreparation of $P V A/H_{3}P O_{4}$ ionic films as the dielectric. To realize the proposed GIA, we adopted a commercial sandpaper (roughness of no. $10000\\ {\\#}^{\\cdot}$ as the template. First, $_{2\\mathrm{g}}$ of polyvinyl alcohol (PVA, Mw \\~ 145,000, from Aladdin Industrial Corporation) was dissolved into $18{\\mathrm{g}}$ of deionized water, followed by stirring at $90^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ until it dissolved completely. After the PVA solution cooled to room temperature $(22^{\\circ}\\mathrm{C})$ , $1.65\\mathrm{mL}$ $\\mathrm{{H_{3}P O_{4}}}$ ( $\\cdot\\mathrm{AR},\\geq85\\%$ , Shanghai Macklin Biochemical Co., Ltd.) was added and stirred for $^{2\\mathrm{h}}$ . The $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ solution was then poured onto the sandpaper and cured at room temperature for $12\\mathrm{h}$ . \n\nPreparation of electrodes and the iontronic pressure sensor. E-beam evaporator (HHV TF500) was used to deposit gold $(100\\mathrm{nm})$ on the surface of flexible polyimide film (PI, thickness: $40\\upmu\\mathrm{m}\\dot{}$ ) to obtain the flexible PI-Au electrodes. The PI-Au film was then cut into certain sizes using a laser cutter (WE6040), such as sizes of $7\\ \\mathrm{mm}\\times7\\ \\mathrm{mm}$ , $3\\mathrm{mm}\\times3\\mathrm{mm}$ , $3\\mathrm{mm}\\times15\\mathrm{mm}$ , as well as circular shapes of $3\\mathrm{mm}$ and $8\\mathrm{mm}$ in diameters for different tests. The PVA/ $\\mathrm{{H_{3}P O_{4}}}$ film was sandwiched between two PI-Au electrodes. Finally, the flexible iontronic pressure sensor was edge-packaged using 3M Scotch tapes. \n\nFabrication of the micro-electrodes and micro-sensor arrays. The fabrication process for the micro-electrodes is shown in Supplementary Fig. 14. First, a positive photoresist (Ruihong RZJ304) with a thickness of $3\\upmu\\mathrm{m}$ on PI film was obtained by spin-coating at $2500\\mathrm{rpm}$ for $30~\\mathrm{s}$ . After drying at $100^{\\circ}\\mathrm{C}$ for $180s$ the PI film coated with the positive photoresist was photo-patterned by exposure to ultraviolet light for 8 s with the crosslinked region defined by the photomask. The film was then developed in developing solution (Ruihong, RZX3038) for $60\\mathrm{s},$ followed by hard baking at $120^{\\circ}\\mathrm{C}$ for $90~\\mathrm{s}$ Next, a Au film was evaporated on the patterned film by using E-beam evaporation. Finally, the photoresist in the unexposed areas was dissolved in a mixture of acetone and isopropanol with a volume ratio of 1:1. Utilizing the above mentioned method, we fabricated square micro electrodes with lateral sizes of $50\\upmu\\mathrm{m}$ , $100\\upmu\\mathrm{m}$ and $200\\upmu\\mathrm{m}$ . The micro-sensor array $(6\\times6$ pixels, and each sensing pixel is a circle of $60\\upmu\\mathrm{m}$ diameter, and the pixel–pixel spacing is $150{\\upmu\\mathrm{m}}\\mathrm{,}$ was prepared by the same method except for using a different mask pattern. The $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ film was then sandwiched between a PI-Au electrode and the micro-array electrode to prepare the micro-pixel array. The conductive thread electrodes were connected to the micro-sensor by using an anisotropic conductive adhesive. \n\nCharacterization and measurements. The microstructures of the $\\mathrm{PVA}/\\mathrm{H}_{3}\\mathrm{PO}_{4}$ film were characterized by using field-emission scanning electron microscope (FESEM, TESCAN). The capacitance was measured by using an LCR meter (E4980AL, KEYSIGHT). The external pressure was applied and measured accurately by using a force gauge with a computer-controlled stage (XLD-20E, Jingkong Mechanical Testing Co., Ltd). The stability tests were carried out using an iontronic pressure sensor with a size of $3\\mathrm{mm}$ in diameter. The bending cycles of the flexible iontronic pressure sensor were evaluated using a smart stretching tester (WS150-100). The measurement of the radial artery pulse wave was carried out by attaching the iontronic pressure sensor to the wrist where the pulse could be detected at a testing frequency of $0.1\\mathrm{MHz}$ . All other capacitance signals were tested at a frequency of 1 kHz unless otherwise specified, and all sensor size was set to $7\\mathrm{mm}\\times7\\mathrm{mm}$ unless otherwise specified. \n\n# Data availability \n\nAll relevant data sets generated during and/or analyzed during the current study are available from the corresponding author upon request. \n\nReceived: 12 August 2019; Accepted: 10 December 2019; Published online: 10 January 2020 \n\n# References \n\n1. Schwartz, G. et al. Flexible polymer transistors with high pressure sensitivity for application in electronic skin and health monitoring. Nat. Commun. 4, 1859 (2013). \n2. Kim, J. et al. Soft wearable pressure sensors for beat-to-beat blood pressure monitoring. Adv. Healthc. Mater. 8, e1900109 (2019). \n3. Boutry, C. M. et al. A sensitive and biodegradable pressure sensor array for cardiovascular monitoring. Adv. Mater. 27, 6954–6961 (2015). \n4. Lu, N. & Kim, D.-H. Flexible and stretchable electronics paving the way for soft robotics. Soft Robot 1, 53–62 (2014). \n5. Rus, D. & Tolley, M. T. Design, fabrication and control of soft robots. Nature 521, 467 (2015). \n6. Zhou, Z. et al. Supersensitive all-fabric pressure sensors using printed textile electrode arrays for human motion monitoring and human-machine. Interact. J. Matter Chem. C. 6, 13120–13127 (2018). \n7. Guo, Y. et al. A flexible wearable pressure sensor with bioinspired microcrack and interlocking for full-range human–machine interfacing. Small 14, 1803018 (2018). Sundaram, S. et al. Learning the signatures of the human grasp using a scalable tactile glove. Nature 569, 698–702 (2019). \n9. Zang, Y., Zhang, F., Di, C-A. & Zhu, D. Advances of flexible pressure sensors toward artificial intelligence and health care applications. Mater. Horiz. 2, 140–156 (2015). \n10. Lucarotti, C., Oddo, C. M., Vitiello, N. & Carrozza, M. C. Synthetic and bioartificial tactile sensing: A review. Sensors 13, 1435–1466 (2013). \n11. Wang, X., Liu, Z. & Zhang, T. Flexible sensing electronics for wearable/ attachable health monitoring. Small 13, 1602790 (2017). \n12. Xu, F. et al. Recent developments for flexible pressure sensors: a review. Micromachines 9, 580 (2018). \n13. Li, J., Bao, R., Tao, J., Peng, Y. & Pan, C. Recent progress in flexible pressure sensor arrays: from design to applications. J. Matter Chem. C. 6, 11878–11892 (2018). \n14. Chhetry, A., Kim, J., Yoon, H. & Park, J. Y. Ultrasensitive interfacial capacitive pressure sensor based on a randomly distributed microstructured iontronic film for wearable applications. ACS Appl Mater. Interfaces 11, 3438–3449 (2018). \n15. He, Z. et al. Capacitive pressure sensor with high sensitivity and fast response to dynamic interaction based on graphene and porous nylon networks. ACS Appl Mater. Interfaces 10, 12816–12823 (2018). \n16. Mannsfeld, S. C. et al. Highly sensitive flexible pressure sensors with microstructured rubber dielectric layers. Nat. Mater. 9, 859 (2010). \n17. Yang, J. C. et al. Microstructured porous pyramid-based ultrahigh sensitive pressure sensor insensitive to strain and temperature. ACS Appl Mater. Interfaces 11, 19472–19480 (2019). \n18. Xu, F. & Zhu, Y. Highly conductive and stretchable silver nanowire conductors. Adv. Mater. 24, 5117–5122 (2012). \n19. Luo, J. et al. Ultrasensitive self-powered pressure sensing system. Extrem. Mech. Lett. 2, 28–36 (2015). \n20. Boutry, C. M. et al. A hierarchically patterned, bioinspired e-skin able to detect the direction of applied pressure for robotics. Sci. Robot 3, eaau6914 (2018). \n21. Luo, Y. et al. Flexible capacitive pressure sensor enhanced by tilted micropillar arrays. ACS Appl Mater. Interfaces 11, 17796–17803 (2019). \n22. Yang, J. et al. Flexible, tunable and ultrasensitive capacitive pressure sensor with micro-conformal graphene electrodes. ACS Appl Mater. Interfaces 11, 14997–15006 (2019). \n23. Li, T. et al. Flexible capacitive tactile sensor based on micropatterned dielectric layer. Small 12, 5042–5048 (2016). \n24. Wan, Y. et al. Natural plant materials as dielectric layer for highly sensitive flexible electronic skin. Small 14, 1801657 (2018). \n25. Qiu, Z. et al. Ionic skin with biomimetic dielectric layer templated from calathea zebrine leaf. Adv. Funct. Mater. 28, 1802343 (2018). \n26. Baek, S. et al. Flexible piezocapacitive sensors based on wrinkled microstructures: toward low-cost fabrication of pressure sensors over large areas. RSC Adv. 7, 39420–39426 (2017). \n27. Liu, F. et al. An omni‐healable and highly sensitive capacitive pressure sensor with microarray. Struct. Chem: Eur. J. 24, 16823–16832 (2018). \n28. Nie, B., Li, R., Cao, J., Brandt, J. D. & Pan, T. Flexible transparent iontronic film for interfacial capacitive pressure sensing. Adv. Mater. 27, 6055–6062 (2015). \n29. Cho, S. H. et al. Micropatterned pyramidal ionic gels for sensing broad-range pressures with high sensitivity. ACS Appl Mater. Interfaces 9, 10128–10135 (2017). \n30. Zhu, Z., Li, R. & Pan, T. Imperceptible epidermal–iontronic interface for wearable sensing. Adv. Mater. 30, 1705122 (2018). \n31. Nie, B., Li, R., Brandt, J. D. & Pan, T. Iontronic microdroplet array for flexible ultrasensitive tactile sensing. Lab a Chip 14, 1107–1116 (2014). \n32. Keplinger, C. et al. Stretchable, transparent, ionic conductors. Science 341, 984–987 (2013). \n33. Sun, J. Y., Keplinger, C., Whitesides, G. M. & Suo, Z. Ionic skin. Adv. Mater. 26, 7608–7614 (2014). \n34. Hammock, M. L., Chortos, A., Tee, B. C., Tok, J. B. & Bao, Z. 25th anniversary article: The evolution of electronic skin (e-skin): a brief history, design considerations, and recent progress. Adv. Mater. 25, 5997–6038 (2013). \n35. Boesel, L. F., Greiner, C., Arzt, E. & del Campo, A. Gecko-inspired surfaces: a path to strong and reversible dry adhesives. Adv. Mater. 22, 2125–2137 (2010). \n36. Lee, J. et al. Conductive fiber‐based ultrasensitive textile pressure sensor for wearable electronics. Adv. Mater. 27, 2433–2439 (2015). \n37. Zeng, X. et al. Tunable, ultrasensitive, and flexible pressure sensors based on wrinkled microstructures for electronic skins. ACS Appl. Mater. Interfaces 11, 21218–21226 (2019). \n38. Chortos, A. & Bao, Z. Skin-inspired electronic devices. Mater. Today 17, 321–331 (2014). \n39. Pruvost, M., Smit, W. J., Monteux, C., Poulin, P. & Colin, A. Polymeric foams for flexible and highly sensitive low-pressure capacitive sensors. NPJ Flex. Electron 3, 7 (2019). \n40. Yoo, J. Y. et al. Industrial grade, bending‐insensitive, transparent nanoforce touch sensor via enhanced percolation effect in a hierarchical nanocomposite film. Adv. Funct. Mater. 28, 1804721 (2018). \n41. Liu, W. & Yan, C. Direct printing of stretchable elastomers for highly sensitive capillary pressure sensors. Sensors 18, 1001 (2018). \n42. Persson, B. N. Contact mechanics for randomly rough surfaces. Surf. Sci. Rep. 61, 201–227 (2006). \n43. Pang, X. -D., Tan, H. Z. & Durlach, N. I. Manual discrimination of force using active finger motion. Percept. Psychophys. 49, 531–540 (1991). \n44. PSI 8400 System. NASA, www.nasa.gov/aeroresearch/aavp/aetc/testtechnology/pressure/gallery1. \n\n# Acknowledgements \n\nWe thank the Materials Characterization and Preparation Center of SUSTech for assistance in the preparation of electrodes and support in materials characterization. This research was supported by the Innovation Committee of Shenzhen Municipality (Grant No. JCYJ20170817111714314), the National Natural Science Foundation of China (Nos. U1613204 and 51771089), the “Science Technology the Shenzhen Sci-Tech Fund (No. KYTDPT20181011104007), and the “Guangdong Innovative and Entrepreneurial Research Team Program” under Contract No. 2016ZT06G587. \n\n# Author contributions \n\nN.B., L.W. and C.G. designed the GIA structure. L.W. conducted the FEA. L.W. and C.G. wrote the paper. N.B. conducted the majority of the experiments. Q.W., J.D., Y.W., P.L., J.H. helped prepare the electrodes. G.L., Y.Z., J.Y., and K.X. participated in the discussion of experimental results. X.Z. and C.G. revised the manuscript. All authors reviewed and commented on the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 019-14054-9. \n\nCorrespondence and requests for materials should be addressed to C.F.G. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1038_s41467-020-15478-4", + "DOI": "10.1038/s41467-020-15478-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-15478-4", + "Relative Dir Path": "mds/10.1038_s41467-020-15478-4", + "Article Title": "Lamella-nullostructured eutectic zinc-aluminum alloys as reversible and dendrite-free anodes for aqueous rechargeable batteries", + "Authors": "Wang, SB; Ran, Q; Yao, RQ; Shi, H; Wen, Z; Zhao, M; Lang, XY; Jiang, Q", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Metallic zinc is an attractive anode material for aqueous rechargeable batteries because of its high theoretical capacity and low cost. However, state-of-the-art zinc anodes suffer from low coulombic efficiency and severe dendrite growth during stripping/plating processes, hampering their practical applications. Here we show that eutectic-composition alloying of zinc and aluminum as an effective strategy substantially tackles these irreversibility issues by making use of their lamellar structure, composed of alternating zinc and aluminum nullolamellas. The lamellar nullostructure not only promotes zinc stripping from precursor eutectic Zn88Al12 (at%) alloys, but produces core/shell aluminum/aluminum sesquioxide interlamellar nullopatterns in situ to in turn guide subsequent growth of zinc, enabling dendrite-free zinc stripping/plating for more than 2000h in oxygen-absent aqueous electrolyte. These outstanding electrochemical properties enlist zinc-ion batteries constructed with Zn88Al12 alloy anode and KxMnO2 cathode to deliver high-density energy at high levels of electrical power and retain 100% capacity after 200hours. Aqueous rechargeable Zn-ion batteries are attractive energy storage devices, but their wide adoption is impeded by the irreversible metallic Zn anode. Here the authors report lamellar-nullostructured eutectic Zn/Al alloys as reversible and dendrite-free anodes for improved battery performance.", + "Times Cited, WoS Core": 596, + "Times Cited, All Databases": 619, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000525081200010", + "Markdown": "# Lamella-nanostructured eutectic zinc–aluminum alloys as reversible and dendrite-free anodes for aqueous rechargeable batteries \n\nSheng-Bo Wang 1,2, Qing Ran 1,2, Rui-Qi Yao 1, Hang Shi 1, Zi Wen 1, Ming Zhao $\\textcircled{1}$ 1, Xing-You Lang 1✉ & Qing Jiang 1✉ \n\nMetallic zinc is an attractive anode material for aqueous rechargeable batteries because of its high theoretical capacity and low cost. However, state-of-the-art zinc anodes suffer from low coulombic efficiency and severe dendrite growth during stripping/plating processes, hampering their practical applications. Here we show that eutectic-composition alloying of zinc and aluminum as an effective strategy substantially tackles these irreversibility issues by making use of their lamellar structure, composed of alternating zinc and aluminum nanolamellas. The lamellar nanostructure not only promotes zinc stripping from precursor eutectic $Z n_{88}\\mathsf{A l}_{12}$ $(a t\\%)$ ) alloys, but produces core/shell aluminum/aluminum sesquioxide interlamellar nanopatterns in situ to in turn guide subsequent growth of zinc, enabling dendritefree zinc stripping/plating for more than $2000{\\mathsf{h}}$ in oxygen-absent aqueous electrolyte. These outstanding electrochemical properties enlist zinc-ion batteries constructed with $Z n_{88}\\mathsf{A l}_{12}$ alloy anode and ${\\mathsf{K}}_{x}{\\mathsf{M}}{\\mathsf{n O}}_{2}$ cathode to deliver high-density energy at high levels of electrical power and retain $100\\%$ capacity after 200 hours. \n\nidespread utilization of plentiful but only intermittently available solar and wind power has raised urgent demand for the development of safe, cost-effective, and reliable grid-scale energy storage technologies for efficient integration of renewable energy sources1,2. Among many electrochemical energy storage technologies, rechargeable battery based on $Z\\mathrm{n}$ metal chemistry in neutral aqueous electrolyte is one of the most attractive devices by virtue of metallic $Z\\mathrm{n}$ having high volumetric and gravimetric capacity $(5854\\mathrm{mAh}\\mathrm{cm}^{-3}$ and 820 mAh $\\mathbf{g}^{-1}.$ ), low $\\mathrm{Zn}/\\mathrm{Zn}^{2+}$ redox potential $(-0.76\\mathrm{V}$ versus standard hydrogen electrode), high abundance and low $\\cos\\mathrm{t}^{3,4}$ . Along with high ionic conductivities (up to $1\\mathrm{{Scm}^{-1}},$ ) of aqueous electrolytes and two-electron redox reaction of $Z\\mathrm{n}/\\mathrm{Zn}^{2+}$ that favor high rate capability and high energy density, respectively, aqueous rechargeable $Z\\mathrm{n}$ -ion batteries (AR-ZIBs) promise safe and lowcost high-density energy storage/delivery at fast charge/discharge rates for stationary grid storage applications5,6. This has prompted the recent renaissance of $\\mathrm{A\\check{R}-Z I\\bar{B s}^{4,7,8}}$ , with the development of various cathode materials including polymorphous manganese dioxides9–13, vanadium oxides14–19, Prussian blue analogues (PBAs)20,21 and quinone analogs22 for hosting/delivering $\\scriptstyle{\\dot{Z}}\\ n^{2+}$ and/or $\\mathrm{H^{+}}$ via insertion/extraction or chemical conversion reactions23–25. However, no matter which advanced material is employed as the cathode, state-of-the-art AR-ZIBs are persistently plagued by the irreversibility issues of traditional metallic Zn anode5,6,8,26, such as dendrite formation and growth $\\phantom{-}5,6,8,27,28$ and low coulombic efficiency (CE) associated with side reactions (e.g., hydrogen evolution, corrosion, and by-product formation) during the stripping/plating processes29–31. Although the $Z\\mathrm{n}$ dendrite formation could be effectively alleviated in neutral electrolytes compared with in alkaline solutions7–9, it is inherently unavoidable because of the unique metallurgic characteristics of monometallic $Z\\mathrm{n}^{27,31}$ . Furthermore, there always take place uncontrollable shape changes to produce abundant cracks or defects in the repeated processes of $Z\\mathrm{n}$ stripping/plating32,33. The structural irreversibility triggers further $Z\\mathrm{n}$ dendrite growth due to uneven distribution and slow diffusion of $Z\\mathrm{n}^{2+}$ ions at the $Z\\mathrm{n}$ metal/electrolyte interface33 and continuously depletes Zn and electrolyte via supplementary side reactions30,31, leading to rapid and remarkable capacity fading and short lifespan of AR-ZIBs. Therefore, it is highly desirable to explore novel $Z\\mathrm{n}$ -based anode materials that can circumvent these irreversibility issues for constructing high-performance AR-ZIBs. \n\nHere we report that a class of eutectic $Z\\mathrm{n/Al}$ alloys with an alternating Zn and Al lamellar nanostructure as reversible and dendrite-free anode materials significantly improve electrochemical performance of aqueous rechargeable zinc-manganese oxide batteries ( $\\mathrm{\\cdot}\\mathrm{\\cdot}\\mathrm{\\cdot}\\mathrm{\\cdot}\\mathrm{\\Omega}$ -Mn AR-ZIBs). The unique lamellar structure promotes the reversibility of stripping/plating of $Z\\mathrm{n}$ by making use of symbiotic less-noble Al lamellas, which in-situ form interlamellar nanopatterns with an ${\\mathrm{Al}}/{\\mathrm{Al}_{2}}{\\mathrm{O}}_{3}$ core/shell structure. Therein, the Al protects against irreversible by-product of $\\mathrm{{znO}}$ or $Z\\mathrm{n}(\\mathrm{OH})_{2}$ while the insulating ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ shell prevents the electroreduction of $Z\\mathrm{n}^{2+}$ ions on the ${\\mathrm{Al}}/{\\mathrm{Al}_{2}}{\\mathrm{O}}_{3}$ patterns and thus guides their electrodeposition on the precursor $Z\\mathrm{n}$ sites, substantially eliminating the formation and growth of $Z\\mathrm{n}$ dendrites. As a result, the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ $(\\mathrm{at\\%})$ alloys exhibit superior dendrite-free $Z\\mathrm{n}$ stripping/plating behaviors, with remarkably low and stable overpotential, for more than $2000\\mathrm{h}$ in $\\mathrm{O}_{2}$ -absent aqueous $\\mathrm{ZnSO_{4}}$ electrolyte. The outstanding electrochemical properties enable the $Z\\mathrm{n}$ -Mn AR-ZIBs constructed with eutectic $\\bar{\\mathrm{Zn}_{88}}\\mathrm{Al}_{12}$ alloy anode and ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ cathode to deliver energy density of ${\\sim}230\\mathrm{Wh}\\mathrm{kg}^{-1}$ (based on the mass of ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ cathode) at high levels of electrical power while retaining ${\\sim}100\\%$ capacity after more than 200 hours. By adjusting the anode-tocathode mass ratio to 3:1, the overall energy density of $Z\\mathrm{n-Mn}$ \n\nAR-ZIB can reach ${\\sim}142\\mathrm{Wh}\\mathrm{kg}^{-1}$ based on total mass of anode and cathode. The strategy of eutectic-composition alloying could open an avenue to the development of high-performance metallic anodes for next-generation secondary batteries. \n\n# Results \n\nEutectic alloying strategy for Zn dendrite suppression. Zn metal is a classic anode material but works as a hostless electrode to store/deliver energy via the electrochemical plating/stripping of $Z\\mathrm{n}$ , during which the $Z\\mathrm{n}^{2+}$ cations thermodynamically prefer to form nuclei at the dislocated sites and grow into initial protuberances on the surface of $Z\\mathrm{n}$ substrate with uncontrollable $Z\\mathrm{n}$ redistribution (Fig. 1a)27–29,31,33. In particular, the tips of protuberances not only have higher potentials34 but consist of highdensity low-coordination steps and kinks with lower activation energy, both of which facilitate further growth of dendrites (Fig. 1b)29. To circumvent these irreversibility problems, here we propose an eutectic-composition alloying strategy based on $Z\\mathrm{n}/\\mathrm{Al}$ alloy system, wherein the eutectic structure is composed of alternating Zn and Al lamellas. Although the standard equilibrium potential of $\\mathrm{Al}^{3+}/\\mathrm{Al}$ $(-1.66\\mathrm{V}$ versus SHE) is much lower than that of $Z\\mathrm{n}^{2+}/\\mathrm{Zn}^{35}$ , the formation of ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ shell on the Al lamellas protects against the dissolution of Al and thus allows the selectively electrochemical stripping/plating of $Z\\mathrm{n}$ in aqueous electrolyte35,36. Their distinct electrochemical behaviors enable the different roles of $Z\\mathrm{n}$ and Al lamellas in the charge/discharge processes: the former supplying $Z\\mathrm{n}^{2+}$ charge carriers and the latter serving as 2D hosting skeleton to accommodate the $Z\\mathrm{n}$ plating (Fig. 1c). Owing to the insulating $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ shell that substantially blocks the electron transfer from Al to the $Z\\mathrm{n}^{2+}$ cations35, there forms a positive electrostatic shield around the ${\\mathrm{Al}}/{\\mathrm{Al}_{2}}{\\mathrm{O}}_{3}$ lamellas without the reduction of $Z\\mathrm{n}^{2+37}$ , enlisting the ${\\mathrm{Al}}/{\\mathrm{Al}_{2}}{\\mathrm{O}}_{3}$ nanopatterns to guide the uniform Zn deposition at their interlayer spacing along the $Z\\mathrm{n}$ precursor sites (Fig. 1d). \n\nPreparation and characterization of eutectic Zn-Al alloys. Eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ $(\\mathrm{at\\%})$ alloys are produced by a facile and scalable metallurgic procedure, viz. alloying pure Zn and Al metals and pouring casting at various cooling rates from ${\\sim}10$ to ${\\sim}300\\mathrm{K}s^{-1}$ . Supplementary Fig. 1 shows typical X-ray diffraction (XRD) patterns of eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloys, with the major peaks corresponding to the primary hexagonal closest packed (hcp) Zn phase (JCPDS 04-0831), apart from the weak ones attributed to the face-centered cubic (fcc) $\\mathtt{a}$ -Al phase (JCPDS 04-0787) (Fig. 2a). Distinguished from hypoeutectic $\\mathrm{Zn}_{50}\\mathrm{Al}_{50}$ alloy that is composed of random eutectic mixtures of $Z\\mathrm{n}$ and Al (Supplementary Figs. 2 and $3)^{38}$ , the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloys exhibit an ordered lamellar structure of alternating $Z\\mathrm{n}$ and Al lamellas. As a result of the rapid solidification triggered Al phase precipitation as well as the balance between the lateral diffusion of excess Zn and Al in the liquid just ahead of the solid/liquid interface and the creation of $\\mathrm{Zn/Al}$ interfacial area during the solidification process39,40, the thickness of $Z\\mathrm{n}$ or Al lamellas, or the interlamellar spacing $(\\uplambda)$ , decreases with the cooling rates (Fig. 2b). Figure 2c–e show representative optical micrographs of the lamella-structured eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloys, which are prepared at the cooling rates of ${\\sim}10$ , ${\\sim}30$ and ${\\sim}300\\dot{\\mathrm{K}}s^{-1}$ , respectively. At the slow cooling rate of ${\\sim}10\\mathrm{K}s^{-1}$ , the $\\lambda$ of the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy is ${\\sim}450\\mathrm{nm}$ (Fig. 2c and Supplementary Fig. 4a), i.e., ${\\sim}350\\mathrm{nm}$ thick Zn lamellas (sagging stripes) alternatingly sandwiched by the Al ones (protruding stripes) with thickness of ${\\sim}100\\mathrm{nm}$ (Supplementary Fig. 5). The unique lamellar structure is further illustrated by scanning electron microscope (SEM) backscattered electron image and the corresponding energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) elemental mappings, with the uniform distribution of alternating Zn and Al lamellas (Fig. 2f). While increasing the cooling rate to ${\\sim}300\\mathrm{K}s^{-1}$ , the $\\lambda$ reaches ${\\sim}1850~\\mathrm{~nm}$ , with ${\\sim}1200\\mathrm{-nm}$ -thick Zn lamellas and ${\\sim}650\\mathrm{-nm}.$ 一 thick Al lamellas (Fig. 2e and Supplementary Fig. 4c). Figure $2\\mathrm{g}$ shows a typical high-resolution transmission electron microscope (HRTEM) image of $Z\\mathrm{n}/\\mathrm{Al}$ interfacial region, demonstrating the symbiotic Zn and Al lamellas viewed along their $\\left\\langle0001\\right\\rangle$ and 〈111〉 zone axis. The fast Fourier transform (FFT) patterns of the selected areas in Fig. $2\\mathrm{g}$ confirm the fcc Al phase (Fig. 2h) and the hcp Zn phase (Fig. 2i) separated from each other during the solidification process39,40. \n\n![](images/b9d4d13a84fa3a8d5aab4f82538f3f2326dfafe47ecdb5153548ca3a6436ef08.jpg) \nFig. 1 Schematic illustration of eutectic strategy for dendrite and crack suppression. a Monometallic Zn electrodes with abundant cracks or defects that are produced by uncontrollable volume change in the $Z n$ stripping/plating processes. b Growth of $Z n$ dendrites triggered by uncontrollable volume change and tip effect. c Eutectic $Z n/A l$ alloys with a lamellar structure composed of alternative $Z n$ and Al nanolamellas in-situ produce core/shell interlayer patterns during the $Z n$ stripping to guide the subsequent $Z n$ plating. d The $A l/A l_{2}O_{3}$ interlayer patterns associated with insulative $A|_{2}O_{3}$ shield facilitate the uniform deposition of Zn. \n\nDespite the immiscibility of $Z\\mathrm{n}$ and Al metals, the lamellastructured eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ exhibits remarkable alloy nature, with a superior oxidation-resistance capability in air and aqueous electrolytes compared with monometallic $Z\\mathrm{n}$ , because of the formation of stable and passive ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ surface layer, which protects against the further oxidation39,40. As shown in optical photographs (Supplementary Fig. 6a), the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy still displays a metallic lustre after exposed to air for five days, in sharp contrast with monometallic Zn that undergoes severe oxidation. Furthermore, the thinner the interlamellar spacing, the higher the oxidation-resistance capability. Even when immersing in the $\\mathrm{O}_{2}$ -present $\\mathrm{ZnSO_{4}}$ aqueous electrolyte for $72\\mathrm{{h}}$ , the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy with $\\lambda={\\sim}450\\mathrm{nm}$ does not display evident change (Supplementary Fig. 6b). The superior oxidation-resistance behavior of eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloys is further demonstrated by their EIS measurements, which are performed on the basis of a classic three-electrode configuration with $\\mathrm{Pt}$ foil as the counter electrode and an $\\mathrm{Ag/AgCl}$ electrode as the reference electrode, in the $\\mathrm{O}_{2}$ -present $\\mathrm{ZnSO_{4}}$ electrolyte (Fig. 3a and Supplementary Fig. 7b). In the Nyquist plot, the EIS spectra of eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloys, hypoeutectic $\\mathrm{Zn}_{50}\\mathrm{Al}_{50}$ alloy and monometallic $Z\\mathrm{n}$ display characteristic semicircles with distinct diameters in the high- and middle-frequency range. At high frequencies, the intercept at the real part represents the intrinsic resistance of both electrolyte and electrode $(R_{\\mathrm{I}})$ ; in the middle-frequency range, the diameter of semicircle corresponds to the charge transfer resistance $(R_{\\mathrm{CT}})$ and the double-layer capacitance $(C_{\\mathrm{F}})$ ; and the slope of the inclined line at flow frequencies is the Warburg resistance $(Z\\mathrm{w})$ . Based on the equivalent circuit with these general descriptors (Supplementary Fig. 7a), the EIS spectra are analyzed using the complex nonlinear least-squares fitting method. Supplementary Fig. 7c compares the $R_{\\mathrm{I}}$ values of all $Z\\mathrm{n}$ -based electrodes immersed in the $\\mathrm{O}_{2}$ -present electrolyte for $^{\\textrm{\\scriptsize1h}}$ , wherein the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ with $\\lambda=$ ${\\sim}450\\mathrm{nm}$ has the lowest $R_{\\mathrm{I}}$ value $\\left(\\sim11\\Omega\\right)$ because of the outstanding oxidation-resistance property. Even extending the immersion time to $\\mathrm{10h}$ , the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ still maintains ${\\sim}11\\Omega$ whereas the $Z\\mathrm{n}$ electrode has the $R_{\\mathrm{I}}$ value to increase to ${\\sim}22\\Omega$ from ${\\sim}18\\Omega$ . The large change of $R_{\\mathrm{I}}$ value indicates the inferior oxidation-resistance capability of the monometallic Zn. Owing to their different oxidation-resistance capabilities, there form distinct oxide layers to depress the Zn stripping/plating kinetics, indicated by the increase of $R_{\\mathrm{CT}}$ value. When immersed in the $\\mathrm{O}_{2}$ -present electrolyte for 1 and $\\mathrm{10h}.$ , the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ with $\\lambda={\\sim}450$ nm exhibits exceptional stability with the $R_{\\mathrm{CT}}$ value changing from ${\\sim}32\\Omega$ to ${\\sim}36\\Omega_{;}$ , in sharp contrast with the monometallic $Z\\mathrm{n}$ electrode with a remarkable change of $R_{\\mathrm{CT}}$ from ${\\sim}96\\Omega$ to ${\\sim}177\\Omega$ (Fig. 3b). This is probably because there lacks a passivation film on the $Z\\mathrm{n}$ lamella surface in virtue of the protection of neighboring Al lamellas5,26. More impressively, the superior oxidation-resistance capability enlists the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloys to be more conducive to electron transfer during the electrochemical $Z\\mathrm{n}$ stripping/plating processes in the $\\mathrm{O}_{2}$ - absent $\\mathrm{ZnSO_{4}}$ aqueous electrolyte. As demonstrated by EIS spectra in Fig. 3c, the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ with $\\lambda={\\sim}450\\mathrm{nm}$ has the $R_{\\mathrm{I}}$ and $R_{\\mathrm{CT}}$ values of as low as ${\\sim}9\\Omega$ and ${\\sim}24~\\Omega$ , respectively (Fig. 3d and Supplementary Fig. 7e). Although the increase of $\\lambda$ may weaken the protecting effect of Al on the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ , the value of $R_{\\mathrm{CT}}$ is only about half of that of the monometallic Zn $(\\sim82\\Omega)$ (Fig. 3d and Supplementary Fig. 8). \n\n![](images/4784c62970118c122569e05ae9432e2335215ae24cf67bb1a90cb9236639afaf.jpg) \nFig. 2 Microstructure characterization of eutectic Zn/Al alloys. a XRD patterns of monometallic Zn, hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ and eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys. The line patterns show reference cards 04-0831 for hcp Zn (blue) and 04-0787 for fcc Al (dark yellow) according to JCPDS. b Thickness of Zn and Al layers in lamella-nanostructured eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys that are produced at various cooling rates. c–e Optical micrographs of lamella-nanostructured eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys with lamella spacing of $\\sim450\\mathsf{n m}$ (c), ${\\sim}1050\\mathsf{n m}$ (d) and ${\\sim}1850\\mathsf{n m}$ (e). Scale bar, $10\\upmu\\mathrm{m}$ (c–e), Typical SEM image lamellananostructured eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys with lamella spacing of $\\sim450\\mathsf{n m}$ and the corresponding EDS element mapping of $Z n$ and Al. Scale bar, $2\\upmu\\mathrm{m}$ . g, HRTEM image of $Z n/A l$ interface of eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys $\\begin{array}{r}{\\left(\\lambda={\\sim}450~\\mathrm{nm}\\right.}\\end{array}$ ). Scale bar, 1 nm. h, i, FFT patterns of selected areas of HRTEM image $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ that correspond to fcc Al ${\\bf\\Pi}({\\bf h})$ and hcp $Z n$ (i), respectively. \n\nElectrochemical properties of eutectic $\\mathbf{Z_{n_{88}}A l_{12}}$ alloys. To investigate the Zn stripping/plating behaviors of the $Z\\mathrm{n}$ -based electrodes, electrochemical measurements are performed on symmetric batteries that are constructed with two identical electrodes. Figure 4a shows the voltage profiles of the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ symmetric battery during the Zn plating/stripping processes at various current densities in the $\\mathrm{O}_{2}$ -absent $\\mathrm{ZnSO_{4}}$ electrolyte, comparing with those of the hypoeutectic $\\mathrm{Zn}_{50}\\mathrm{Al}_{50}$ and monometallic $Z\\mathrm{n}$ ones. The battery based on the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy with $\\lambda={\\sim}450\\mathrm{nm}$ exhibits a relatively flat and stable voltage plateau with the absolute overpotential of ${\\sim}20\\mathrm{mV}$ at the rate of 1C (where 1C represents a one-hour complete charge or discharge at the current density of $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ ), much lower than the value of symmetric $Z\\mathrm{n}$ battery $\\mathrm{\\Gamma(\\sim101~mV)}$ . The less polarization is probably due to the unique eutectic structure of alternating $Z\\mathrm{n}$ and Al lamellas in the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy. Therein, the constituent Al lamellas not only protect against the passivation of the electroactive $Z\\mathrm{n}$ but reduce the local current density of $Z\\mathrm{n}$ stripping/plating via the formation of core/shell $\\mathrm{Al}/\\mathrm{Al}_{2}\\mathrm{O}_{3}$ lamellar nanopatterns (Supplementary Fig. 9a)41,42, which guide the uniform Zn electrodeposition in the subsequent plating process (Supplementary Fig. 9b). During the Zn stripping/plating, the XRD and Raman spectroscopy characterizations evidence the absence of passivation film on the electroactive $Z\\mathrm{n}$ lamellas of $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ (Supplementary Fig. 10a, c), which usually forms on the monometallic Zn electrode. As shown in Supplementary Fig. 10b, d for the $Z\\mathrm{n}$ electrode after cycling test, there appear neoformative diffraction peaks and characteristic Raman bands corresponding to $\\mathrm{Zn}_{4}\\mathrm{\\bar{SO}_{4}(O H)}_{6}\\mathrm{\\cdotH}_{2}\\mathrm{O}$ in addition to $\\mathrm{ZnO^{4,8,11,43}}$ . These observations are in agreement with surface chemical states of $Z\\mathrm{n}$ or/and Al, which are analyzed by $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS). After cycling test, the surface $Z\\mathrm{n}$ of monometallic Zn electrode is completely oxidized because of the formation of $\\mathrm{Zn_{4}S O_{4}(O H)_{6}.H_{2}O}$ and $\\mathrm{znO}$ (Supplementary Fig. 11a), different from that of the pristine one with primary metallic $Z\\mathrm{n}^{0}$ in addition to some $\\scriptstyle\\sum\\ n^{2+}$ due to the initial surface oxidation (Supplementary Fig. 11b). While for the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ electrode after cycling test, the $\\mathtt{Z n\\ 2p}$ and Al 2p XPS spectra reveal that the surface Zn maintains almost the same chemical states as that in the pristine one (Supplementary Fig. 11c, e), but the metallic Al mainly becomes $\\mathrm{Al}^{3\\bar{+}}$ as a consequence of the formation of ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ shell (Supplementary Fig. 11d, f). As the stripping/plating rate increases to 5C, the overpotential of the symmetric $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ battery only increases to ${\\sim}82\\mathrm{mV},$ , implying the excellent rate capability of eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy electrode. The high reversibility of Zn stripping/plating on the eutectic $\\mathrm{Zn}_{88}\\mathrm{\\bar{Al}}_{12}$ alloy electrode is further attested by chronocoulometry measurements based on a three-electrode cell, in which the Zn electrodes are employed as the reference and counter electrodes (inset of Supplementary Fig. 12). The $Z\\mathrm{n}$ stripping/plating on the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy is highly reversible, with the CE of $\\sim100\\%$ , during the cycling test for more than 100 cycles (Supplementary Fig. 12). \n\n![](images/6b8dca910454bfe2bfc4488cc00ac9cf46d508fdd4b95dcbd87e4d44df5dcc38.jpg) \nFig. 3 Oxidation-resistance capability of Zn metal and eutectic Zn/Al alloys. a Electrochemical impedance spectra (EIS) of eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys with various lamellar spacings $(\\lambda=\\sim450$ , ${\\sim}1050$ and ${\\sim}1850\\mathsf{n m})$ , hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ alloy and monometallic Zn after immersed in the $\\mathsf{O}_{2}$ -present $Z n S O_{4}$ aqueous electrolytes for 1 h. b Evolutions of the charge transfer resistances $(R_{\\mathsf{C T}})$ of eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys with various lamellar spacings $(\\lambda=\\sim450$ , ${\\sim}1050$ and $\\sim1850\\ \\mathrm{nm};$ , hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ alloy and monometallic $Z n$ when extending the immersing time from 1 to $10\\mathsf{h}$ in the $\\mathsf{O}_{2}$ -present $Z n S O_{4}$ aqueous electrolytes. c, d EIS spectra of eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys with various lamellar spacings $(\\lambda=\\sim450$ , ${\\sim}1050$ and $\\sim1850\\ \\mathrm{nm},$ , hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ alloy and monometallic $Z n$ (c) and their corresponding $R_{\\mathsf{C T}}$ values $({\\pmb d})$ in the $\\mathsf{O}_{2}$ -absent $Z n S O_{4}$ aqueous electrolyte for $1\\mathfrak{h}$ . \n\nDuring a long-term $Z\\mathrm{n}$ stripping/plating cycling measurement, the voltage profile of $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ battery does not display any evident voltage hysteresis or change even for more than $2000\\mathrm{h}$ , in sharp contrast to those of the $\\mathrm{Zn}_{50}\\mathrm{Al}_{50}$ and $Z\\mathrm{n}$ ones with much larger voltage hysteresis and fluctuation after 100 and 26 hours, respectively (Fig. 4b). Specifically, there takes place an abrupt voltage drop after a dramatic voltage increase in the $Z\\mathrm{n}$ battery, which is caused by a short circuit of battery due to the formation of $Z\\mathrm{n}$ dendrites. EIS spectra also justify the outstanding stability of the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy electrode during the Zn stripping/plating processes because of the unique eutectic structure (Fig. 4c–e). Furthermore, the fact that inductively coupled plasma optical emission spectroscopy (ICP-OES) cannot detect $\\bar{\\mathrm{A}^{1}}^{3+}$ ions in the $\\mathrm{O}_{2}$ -absent aqueous electrolytes demonstrates the chemical stability of $\\mathrm{Al}/\\mathrm{Al}_{2}\\mathrm{O}_{3}$ interlamellar nanopatterns (Supplementary Table 1), which in turn guide the deposition of $Z\\mathrm{n}$ after a longterm cycling test of the $\\bar{Z_{\\bar{\\Pi}_{88}}}\\mathrm{Al}_{12}$ . As shown in Fig. 4f, the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy electrode still keeps a smooth surface after more than 1000 cycles of $Z\\mathrm{n}$ stripping/plating. This is distinctly distinguished from the cycled hypoeutectic $\\mathrm{Zn}_{50}\\mathrm{Al}_{50}$ and monometallic Zn electrodes even in fewer cycles, wherein the former displays an uneven porous structure (Fig. 4g) and the latter undergoes severe growth of dendrites and cracks (Fig. 4h). The addition of $\\mathrm{Mn}^{2+}$ ions in the aqueous $\\mathrm{ZnSO_{4}}$ electrolyte does not remarkably influence the $Z\\mathrm{n}$ stripping/plating behavior of $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy. As shown in Supplementary Fig. 13, the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ battery exhibits almost the same voltage-time profiles in the $^{2\\mathrm{M}}$ $\\mathrm{ZnSO_{4}^{\\cdot}}$ electrolyte without/with 0.2 M $\\mathrm{MnSO_{4}}$ . While in the $\\mathrm{ZnSO_{4}}$ electrolyte with the $\\mathrm{O}_{2}$ concentration of $16.59\\mathrm{mgL^{-1}}$ , the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ battery exhibits a stable voltage profile for more than 400 hours (Supplementary Fig. 14a), followed by slightly increasing voltage hysteresis due to the morphology evolution probably triggered by the partial oxidation of Zn via the reactions (Supplementary Fig. 14b)8,43: $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}+\\mathrm{O}_{2}+\\mathrm{H}_{2}\\mathrm{O}\\rightarrow\\mathrm{Al}_{2}\\mathrm{O}_{3}+$ $\\mathrm{Zn(\\bar{O}H)_{2}+Z n^{\\cdot2+}\\Sigma+\\bar{\\ e}^{-}}$ and $\\mathrm{Zn(OH)}_{2}+2e^{-}\\rightarrow\\mathrm{ZnO}+\\mathrm{H}_{2}\\mathrm{O}^{11}$ . Nevertheless, the lamellar structure of alternating $Z\\mathrm{n}$ and Al lamellas significantly alleviate structure changes, in comparison with the electrodes of hypoeutectic $\\mathrm{Zn}_{50}\\mathrm{Al}_{50}$ alloy and monometallic $Z\\mathrm{n}$ (Supplementary Fig. 14c–e). \n\nElectrochemical performance of Zn-ion full batteries. In view of the outstanding electrochemical properties, the lamella-structured eutectic $\\mathrm{Zn}_{88}\\mathrm{A}\\bar{\\mathrm{l}}_{12}$ alloy with $\\lambda={\\sim}450\\mathrm{nm}$ is used as the anode to couple with potassium manganese oxide $\\left(\\mathrm{K}_{x}\\mathrm{MnO}_{2}\\right)$ cathode material for demonstrating its actual application in $Z\\mathrm{n}$ -ion full batteries, with an aqueous electrolyte containing $2\\mathrm{M}\\mathrm{~ZnSO_{4}}$ and 0.2 M $\\mathrm{MnSO_{4}}$ . Therein, tetragonal $\\mathrm{a}{\\mathrm{-K}}_{x}\\mathrm{MnO}_{2}$ nanofibers are synthesized by a stirring hydrothermal approach (Supplementary Fig. $15)^{44}$ . Supplementary Fig. 16a shows typical cyclic voltammetry (CV) curves of $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ full battery in the aqueous electrolytes, without and with the presence of $\\mathrm{O}_{2},$ exhibiting a similar $Z\\mathrm{n}$ storage/delivery behavior with well-defined redox peaks during the charge/discharge processes4,7,8,10–12. It implies that the electrolyte in the absence of $\\mathrm{O}_{2}$ does not substantially change the $Z\\mathrm{n}^{\\dot{2}+}$ (de-)intercalation mechanism within the ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ i.e., $\\delta\\mathrm{Zn}^{2+}+2\\delta\\mathrm{e}^{-}+\\mathrm{K}_{x}\\mathrm{MnO}_{2}\\leftrightarrow$ $\\delta\\mathrm{ZnK}_{x}\\mathrm{MnO_{2}}^{4,7,8,10-12}$ , except for boosting the reaction kinetics of $Z\\mathrm{n}$ stripping/plating due to the absence of passivation oxide (e.g., $\\mathrm{znO}$ or $\\mathrm{Zn}(\\mathrm{OH})_{2})$ on the $Z\\mathrm{n}$ lamella surface of the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ (Supplementary Fig. 16b). \n\nFigure 5a compares representative CV curve of $Z\\mathrm{n}$ -ion batteries that are constructed with the ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ cathode and the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ or $Z\\mathrm{n}$ anode, in the $\\mathrm{O}_{2}$ -absent aqueous electrolyte. The use of different anode materials, i.e., the lamella-structured eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy and the single-phase structured monometallic $Z\\mathrm{n}$ , enlists them to exhibit distinct voltammetric behaviors. Relative to the $\\mathrm{Zn}/\\mathrm{K}_{x}\\mathrm{MnO}_{2}$ battery, the $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ has remarkably enhanced current density and shifts anodic/cathodic peaks to more negative/positive voltages, respectively, indicating that the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ is more conducive to the $Z\\mathrm{n}$ storage/delivery than the $Z\\mathrm{n}^{4,7,8,18}$ . As a result, the $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ battery exhibits a superior rate capability in the scan rates from 0.3 to $5\\mathrm{mV}s^{-1}$ (Supplementary Fig. 17a, b). As shown in Fig. 5b, the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}/$ ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ achieves a specific capacity of as high as ${\\sim}294\\mathrm{mAhg^{-1}}$ at $0.3\\mathrm{mVs^{-1}}$ . Even when the scan rate is increased to $5\\mathrm{mV}\\bar{\\mathsf{s}}^{-1}$ (i.e., the discharge time of 160 s), it still retains the capacity of ${\\sim}145\\ \\mathrm{mAh\\g^{-1}}$ , about four-fold higher than the value of the $Z\\mathrm{n}/$ ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ battery $({\\sim}36\\mathrm{mAh}\\mathrm{g}^{-1},$ ). The expectation that the lamella-structured eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy ameliorates the kinetics of $Z\\mathrm{n}$ strippling/plating is further verified by the EIS analysis (Fig. 5c), with the $R_{\\mathrm{CT}}$ value of the $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ being ${\\sim}66$ $\\Omega$ lower than that of the $\\mathrm{Zn/K_{\\itx}M n O_{2}}$ (inset of Fig. 5c). Figure 5d presents typical voltage profiles for the charge/discharge processes of $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ and $\\mathrm{Zn}/\\mathrm{K}_{x}\\mathrm{MnO}_{2}$ batteries at a current density of $0.3\\mathrm{Ag}^{-1}$ , with the plateaus that are consistent with the redox peaks in the CV curves shown in Fig. 5a. Because of the improved $Z\\mathrm{n}$ stripping/plating in the eutectic $\\bar{Z}\\mathrm{n}_{88}\\mathrm{Al}_{12}$ anode, the $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ evidently outperforms the $\\mathrm{Zn/K_{\\itx}M n O_{2}}$ at various charge/discharge rates (Fig. 5e and Supplementary Fig. 18). As shown in the Ragone plot, the energy densities of $\\mathrm{Z\\bar{n}_{88}A l_{12}/K_{\\it x}M n O_{2}}$ battery, based on the mass of ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ cathode, reaches ${\\sim}230\\dot{\\mathrm{Wh}}\\mathrm{kg^{-1}}$ , more than four-fold higher than the value of $\\mathrm{Zn/K_{\\itx}M n O_{2}}$ at the electrical power of ${\\sim}550\\mathrm{\\kW}$ $\\ k g^{-1}$ . Based on the total mass of anode and cathode in the full $\\mathrm{Z\\bar{n}_{88}A l_{12}/K_{\\it x}M n O_{2}}$ battery, the overall energy density can reach ${\\sim}142\\mathrm{Wh}\\mathrm{kg}^{-1}$ by lowering the anode-to-cathode mass ratio to 3:1 (Supplementary Fig. 19). Supplementary Fig. 20 shows the self-discharge performance of the $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ battery. In the $\\mathrm{O}_{2}$ -absent electrolyte, the voltage of $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ battery drops to $1.481\\mathrm{V}$ in ${\\sim}13\\mathrm{h}$ , slower than the one with the $\\mathrm{O}_{2}$ -present electrolyte, of which the voltage decreases to $1.472\\mathrm{V}$ in ${\\sim}6\\mathrm{h}$ . The evident voltage drop is due to the pseudocapacitive discharge behavior, which is probably boosted by the presence of $\\mathrm{O}_{2}$ . While in the subsequent $\\mathsf{600h}.$ the $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ batteries with the $\\mathrm{O}_{2}$ -present and $\\mathrm{O}_{2}$ -absent electrolytes exhibit a voltage plateau with very low self-discharge $(\\sim\\dot{0.1}\\mathrm{mV}\\mathrm{h}^{-1})$ because of ultralow insertion kinetics of $\\bar{Z_{\\mathrm{n}}}^{2+23-25,43}$ . The cycling life of $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ batteries is tested by galvanostatic charge/discharge at current densities of 0.5 and $5\\mathrm{Ag^{-1}}$ , respectively (Fig. 5f and Supplementary Fig. 21). The significant capacitance retention, about $100\\%$ of the initial capacitance after more than $200\\mathrm{h}$ or 5000 cycles, indicates its impressive long-term durability with nearly $100\\%$ efficiency in the voltage window between 1.0 and $1.8\\mathrm{V}$ . In sharp contrast, the $\\mathrm{Zn/K_{\\itx}M n O_{2}}$ battery undergoes fast capacity degradation (Fig. 5f). This probably results from the irreversibility issues of monometallic $Z\\mathrm{n}$ , i.e., the dendrite formation and growth associated with side reactions, in view that the ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ cathode still maintains the initial morphology and crystallographic structure after the cycling measurement (Supplementary Fig. 22). \n\n![](images/86db9eb5cb29e615f75d1d04a8c3ba58b4ec9378f01ee2f5845789e2b75ae7c0.jpg) \nFig. 4 Electrochemical performance of symmetric batteries of Zn or $z_{n-A l}$ alloy electrodes. a Comparison of voltage profiles for monometallic Zn, hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ and eutectic $Z n_{88}\\mathsf{A l}_{12}$ $(\\lambda=\\sim450\\:\\mathsf{n m})$ symmetric batteries during Zn stripping/plating at various current densities from 1 to $5{\\mathsf{C}}$ in aqueous $Z n S O_{4}$ electrolyte with the absence of $\\mathsf{O}_{2},$ where $1{\\mathsf{C}}=0.5{\\mathsf{m A}}{\\mathsf{c m}}^{-2}$ . b Long-term $Z n$ stripping/plating cycling of symmetric batteries of monometallic Zn, hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ or eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloys $(\\lambda={\\sim}450\\mathsf{n m})$ at the current density of $0.5\\mathsf{m A c m}^{-2}$ in aqueous $Z n S O_{4}$ electrolyte with the absence of $\\mathsf{O}_{2}$ . c–e Comparisons of EIS spectra for eutectic $Z n_{88}\\mathsf{A l}_{12}$ $(\\lambda=\\sim450\\:\\mathrm{nm})$ ) (c), hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ $(\\blacktriangleleft)$ monometallic $Z n$ (e) symmetric batteries after the $\\mathsf{1^{s t}}$ and $100^{\\mathrm{th}}$ cycles in aqueous $Z n S O_{4}$ electrolyte in the absence of $\\mathsf{O}_{2}$ . Inset: Expanded view for EIS of $Z n_{88}\\mathsf{A l}_{12}$ . f–h SEM images of eutectic $Z n_{88}\\mathsf{A l}_{12}$ $(\\lambda=\\sim450\\:\\mathsf{n m}$ ) $(\\bullet),$ hypoeutectic $Z n_{50}\\mathsf{A l}_{50}$ $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ monometallic Zn $(\\boldsymbol{\\mathsf{h}}),$ electrodes after long-term Zn stripping/plating cycling measurements for 2000, 520, and $42\\mathsf{h}$ in aqueous $Z n S O_{4}$ electrolyte with the absence of $\\mathsf{O}_{2},$ respectively. Scale bare, $5\\upmu\\mathrm{m}$ (f–h). \n\n![](images/020c056230debc77d4d6fdf5b003f882db0e60bc8021eaebdfaf49315f77749e.jpg) \nFig. 5 Electrochemical performance of zinc-ion full batteries. a Typical CV curves for $Z n_{88}\\mathsf{A l}_{12}/\\mathsf{K}_{x}\\mathsf{M}\\mathsf{n O}_{2}$ and $Z{\\mathsf{n/K}}_{x}M{\\mathsf{n O}}_{2}$ batteries, which are constructed with the ${\\mathsf{K}}_{x}{M}{\\mathsf{n}}{\\mathsf{O}}_{2}$ nanofibers as the cathode and the eutectic $Z n_{88}\\mathsf{A l}_{12}$ alloy $(\\lambda=\\sim450\\:\\mathrm{nm})$ or the monometallic $Z n$ as the anode, in the $\\mathsf{O}_{2}$ -absent $Z n S O_{4}$ aqueous electrolyte. Scan rate: $0.3\\mathsf{m V s}^{-1}$ . b Specific capacities for $Z n_{88}\\mathsf{A l}_{12}/\\mathsf{K}_{x}\\mathsf{M}\\mathsf{n O}_{2}$ and $Z n/{\\mathsf{K}}_{x}{\\mathsf{M n O}}_{2}$ batteries at various scan rates. c EIS spectra of $Z n_{88}\\mathsf{A l}_{12}/\\mathsf{K}_{x}\\mathsf{M}\\mathsf{n O}_{2}$ and $Z n/K_{\\times}M{\\mathsf{n O}}_{2}$ batteries and their corresponding $R_{\\mathsf{C T}}$ values (inset) in the $\\mathsf{O}_{2}$ -absent $Z n S O_{4}$ aqueous electrolyte. d Typical voltage profiles of $Z n_{88}\\mathsf{A l}_{12}/\\mathsf{K}_{x}\\mathsf{M}\\mathsf{n O}_{2}$ and $Z n/{\\sf K}_{x}{\\sf M}{\\sf n}{\\sf O}_{2}$ batteries at the charge/discharge current density of $0.3\\mathsf{A g}^{-1}$ . e Comparison for rate capabilities of $Z n_{88}\\mathsf{A l}_{12}/\\mathsf{K}_{x}\\mathsf{M}\\mathsf{n O}_{2}$ and $Z n/{\\sf K}_{x}{\\sf M}{\\sf n}{\\sf O}_{2}$ batteries at various rates from 1 to 5 C. f Capacity retention and coulombic efficiency of the $Z n_{88}\\mathsf{A l}_{12}/\\mathsf{K}_{x}\\mathsf{M}\\mathsf{n O}_{2}$ battery in a long-term cycling test at $0.5\\mathsf{A g}^{-1}$ , comparing with those of the $Z n/{\\sf K}_{x}{\\sf M}{\\sf n}{\\sf O}_{2}$ battery. \n\n# Discussion \n\nIn summary, we have proposed eutectic-composition alloying, based on the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy with a lamellar structure composed of alternating $Z\\mathrm{n}$ and Al nanolamellas, as an effective strategy to tackle irreversibility issues of $Z\\mathrm{n}$ metal anode caused by the growth of dendrites and cracks during the stripping/plating processes. By virtue of symbiotic less-noble Al lamellas, which not only protects the constituent $Z\\mathrm{n}$ lamellas from the formation of irreversible $\\mathrm{znO}$ or $\\mathrm{Zn(OH)}_{2}$ by-product but also in-situ form stable ${\\mathrm{Al}}/{\\mathrm{Al}_{2}}{\\mathrm{O}}_{3}$ interlamellar patterns during the Zn stripping and in turn guide subsequent growth of $Z\\mathrm{n}$ , the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ $(\\mathrm{at\\%})$ alloys exhibit superior dendrite-free Zn stripping/plating behaviors, with low overpotential and high coulombic efficiency, for more than $2000\\mathrm{h}$ in $\\mathrm{O}_{2}$ -absent aqueous $\\mathrm{ZnSO_{4}}$ electrolyte. The use of the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy as the anode enlists the $Z\\mathrm{n}$ - ion full batteries with the ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ cathode to deliver energy density of ${\\sim}230\\mathrm{Wh}\\mathrm{kg}^{-1}$ (based on the mass of ${\\mathrm{K}}_{x}{\\mathrm{MnO}}_{2}$ cathode) at high levels of electrical power and retain ${\\sim}100\\%$ capacity after a long-term charge/discharge cycling measurement, remarkably outperforming the battery based on monometallic $Z\\mathrm{n}$ anode. By adjusting the anode-to-cathode mass ratio to 3:1, the overall energy density of Zn-Mn AR-ZIB can reach ${\\sim}142$ Wh $\\ k g^{-1}$ based on total mass of anode and cathode. The strategy of eutectic-composition alloying can also be extended to other metal anodes for the development of next-generation secondary batteries. \n\n# Methods \n\nPreparation of Zn-Al alloys and ${\\pmb{\\kappa}}_{\\pmb{x}}{\\pmb{M}}{\\pmb{\\ n}}{\\pmb{0}}_{2}$ nanofibers. The $\\mathrm{Zn}_{x}\\mathrm{Al}_{100-x}$ ( $\\langle x=50$ , 88, $100\\ \\mathrm{at\\%}$ ) alloys made of high-purity Zn $(99.994\\%$ and Al $(99.996\\%$ were prepared by induction melting in high-purity alumina crucibles within Ar air. These alloy ingots were produced through pouring casting, of which the cooling rates were controlled by making use of different casting moulds, i.e., the heated iron moulds $(\\sim10\\mathrm{K}s^{-1})$ and the copper moulds with air- $(\\sim30\\mathrm{K}s^{-1})$ and watercooling $(\\sim300\\mathrm{K}s^{-1})$ methods. The as-cast $\\mathrm{Zn}_{x}\\mathrm{Al}_{100-x}$ ingots were cut into alloy sheets with thickness of ${\\sim}400\\upmu\\mathrm{m}$ along the perpendicular direction of lamellar structure and further polished for the use as the anodic electrodes. The synthesis of $\\mathrm{K}_{0.12}\\mathrm{MnO}_{2}$ nanobelts was carried out by a modified hydrothermal method. Typically, the Teflon-lined steel autoclave filled with the mixture of 40-mM $\\mathrm{KMnO}_{4}$ and $\\mathrm{40{-}m M N H_{4}C l}$ was heated at $150^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ in an oil bath and magnetically stirred at a speed of $250\\mathrm{rpm}$ . The as-synthesized $\\mathrm{K}_{0.12}\\mathrm{MnO}_{2}$ nanomaterials were collected and washed with ultrapure water for five times using a centrifuge to remove residues. \n\nStructural and chemical characterizations. The metallographic microstructure of $\\mathrm{Zn}_{x}\\mathrm{Al}_{100-x}$ alloy sheets was investigated by using a confocal laser scanning microscope (OLS3000, Olympus) after conventional grinding and mechanical polishing, followed by chemical etching in acetic picric solution ( $\\mathrm{\\zeta}5\\mathrm{ml}\\mathrm{HNO}_{3}$ and 5 ml HF, ${\\mathfrak{s o}}\\mathrm{ml}$ ultrapure water). The electron micrographic structures were characterized by using a field-emission scanning electron microscope (JEOL, JSM6700F, 15 kV) equipped with an X-ray energy-dispersive microscopy, and a fieldemission transmission electron microscope (JEOL, JEM-2100F, $200\\mathrm{kV},$ ). XRD measurements were conducted on a D/max2500pc diffractometer using Cu Kα radiation. Ion concentrations in electrolytes were analyzed by inductively coupled plasma optical emission spectrometer (ICP-OES, Thermo electron). XPS analysis was conducted on a Thermo ECSALAB 250 with an Al anode. Charging effects were compensated by shifting binding energies based on the adventitious C 1s peak $(284.8\\mathrm{eV})$ . \n\nElectrochemical measurements. Symmetrical cells were assembled with two identical $\\mathrm{Zn}_{x}\\mathrm{Al}_{100-x}$ alloy or pure $Z\\mathrm{n}$ sheets $0.5\\mathrm{cm}\\times0.5\\mathrm{cm}\\times40\\mathrm{\\}\\upmu\\mathrm{m})$ , which were separated by glass fiber membrane (GFM) in 2 M $\\mathrm{ZnSO_{4}}$ aqueous solution with/ without $\\Nu_{2}$ purgation. Electrochemical stripping/plating behaviors of $Z_{\\mathrm{{n}/Z n}}2+$ were measured by galvanostatic charge and discharge at various current densities from 1 to $5\\mathrm{mA}\\mathrm{cm}^{-\\tilde{2}}$ . The cycling durability tests were performed at the current density of $0.5\\operatorname{mA}{\\mathsf{c m}}^{-2}$ . To prove its feasibility of the lamella-structured eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy anodes in practical aqueous rechargeable $Z\\mathrm{n}$ -ion batteries, full cells were further assembled with the $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy sheet as the anode, the $\\mathrm{K}_{0.12}\\mathrm{MnO}_{2}$ as the cathode, the GFM as the separator, with the 2M $\\mathrm{ZnSO_{4}}$ aqueous solution containing $0.2\\mathrm{M}\\mathrm{MnSO_{4}}$ as the aqueous electrolyte. Therein, the $\\mathrm{K}_{0.12}\\mathrm{MnO}_{2}$ electrodes were prepared by homogeneously mixing $\\mathrm{K}_{0.12}\\mathrm{MnO}_{2}$ nanobelts, super-P acetylene black conducting agent and poly(vinylidene difluoride) binder with a weight ratio of 70:20:10 in N-methyl-2-pyrrolidone (NMP), and then pasting on stainless steel foil with the loading mass of $1.0\\mathrm{mg}\\mathrm{cm}^{-2}$ . Cyclic voltammetry was conducted on an electrochemical analyzer (Ivium Technology) in the voltage range of 1 and $1.8\\mathrm{V}$ at scan rates from 0.3 to $5\\mathrm{mV}\\mathrm{s}^{-1}$ . Electrochemical impedance spectroscopy (EIS) measurements were performed in sealed cells with $\\mathrm{O}_{2}$ - or $\\Nu_{2}$ -saturated aqueous $2\\mathrm{M}$ $\\mathrm{ZnSO_{4}}$ electrolytes over the frequency ranging from $100\\mathrm{kHz}$ to $10\\mathrm{mHz}$ with an amplitude of $10\\mathrm{mV}$ at room temperature. The rate capability and cycling performance were carried out on a battery test system. Self-discharge measurements were carried out by charging $\\mathrm{Zn_{88}A l_{12}/K_{\\it x}M n O_{2}}$ to $1.8\\mathrm{V}_{:}$ , followed by open-circuit potential self-discharging for $600\\mathrm{h}$ . The coulombic efficiency (CE) of Zn plating/ stripping was evaluated by chronocoulometry method, in which the eutectic $\\mathrm{Zn}_{88}\\mathrm{Al}_{12}$ alloy or pure $Z\\mathrm{n}$ electrode were used as the working electrode and the $Z\\mathrm{n}$ foils as the counter and reference electrodes in the three-electrode cell in the $\\mathrm{O}_{2}$ - absent $2\\:\\mathrm{M}\\:\\mathrm{ZnSO_{4}}$ electrolyte. The chronocoulometry measurements were conducted at the potential of $-0.2$ and $0.2\\mathrm{V}$ (versus $Z_{\\mathrm{{n}}/\\dot{Z}\\mathrm{{n}}^{2+}}$ ) for $600s\\mathrm{.}$ respectively to plate and stripe $Z\\mathrm{n}$ . The CE was calculated by the stripping/plating capacities. \n\n# Data availability \n\nAll relevant data are available from the corresponding authors upon request. \n\nReceived: 30 September 2019; Accepted: 13 March 2020; Published online: 02 April 2020 \n\n# References \n\n1. Dunn, B., Kamath, H. & Tarascon, J. M. Electrical energy storage for the grid: a battery of choices. Science 334, 928–935 (2011). \n2. Yang, Z. et al. Electrochemical energy storage for green grid. Chem. Rev. 111, 3577–3613 (2011). \n3. Kim, H. et al. Metallic anodes for next-generation secondary batteries. Chem. Soc. Rev. 42, 9011–9034 (2013). \n4. Ming, J., Guo, J., Xia, C., Wang, W. & Alshareef, H. N. Zinc-ion batteries: materials, mechanisms, and applications. Mater. Sci. Eng. R. 135, 58–84 (2019). \n5. Parker, J. F. et al. Rechargeable nickel-3D zinc batteries: an energy-dense, safer alternative to lithium-ion. Science 356, 415–418 (2017). \n6. Hu, E. & Yang, X. Q. Rejuvenating zinc batteries. Nat. Mater. 17, 480–481 (2018). \n7. Song, M., Tan, H., Chao, D. & Fan, H. J. Recent advances in Zn-ion batteries. Adv. Funct. Mater. 28, 1802564 (2018). \n8. Fang, G., Zhou, J., Pan, A. & Liang, S. Recent advances in aqueous zinc-ion batteries. ACS Energy Lett. 3, 2480–2501 (2018). \n9. Shoji, T., Hishinuma, M. & Yamamoto, T. Zinc-manganese dioxide galvanic cell using zinc sulphate as electrolyte. Rechargeability of the cell. J. Appl. Electrochem. 18, 521–526 (1988). \n10. Xu, C., Li, B., Du, H. & Kang, F. Energetic zinc ion chemistry: the rechargeable zinc ion battery. Angew. Chem. Int. Ed. 51, 933–935 (2012). \n11. Pan, H. et al. Reversible aqueous zinc/manganese oxide energy storage from conversion reaction. Nat. Energy 1, 16039 (2016). \n12. Zhang, N. et al. Rechargeable aqueous zinc-manganese dioxide batteries with high energy and power densities. Nat. Commun. 8, 405 (2017). \n13. Huang, J. et al. Polyaniline-intercalated manganese dioxide nanolayers as a high-performance cathode material for an aqueous zinc-ion battery. Nat. Commun. 9, 2906 (2018). \n14. Kundu, D., Adams, B. D., Duffort, V., Vajargah, S. H. & Nazar, L. F. A highcapacity and long-life aqueous rechargeable zinc battery using a metal oxide intercalation cathode. Nat. Energy 1, 16119 (2016). \n15. Yan, M. et al. Water-lubricated intercalation in $\\mathrm{V}_{2}\\mathrm{O}_{5}{\\cdot}\\mathrm{nH}_{2}\\mathrm{O}$ for high-capacity and high-rate aqueous rechargeable zinc batteries. Adv. Mater. 30, 1703725 (2018). \n16. Xia, C., Guo, J., Li, P., Zhang, X. & Alshareef, H. N. Highly stable aqueous zinc-ion storage using a layered calcium vanadium oxide bronze cathode. Angew. Chem. Int. Ed. 57, 3943–3948 (2018). \n17. Yang, Y. et al. $\\mathrm{Li^{+}}$ intercalated $\\mathrm{V}_{2}\\mathrm{O}_{5}{\\cdot}\\mathrm{nH}_{2}\\mathrm{O}$ with enlarged layer spacing and fast ion diffusion as an aqueous zinc-ion battery cathode. Energy Environ. Sci. 11, 3157–3162 (2018). \n18. Chao, D. et al. A high-rate and stable quasi-solid-state zinc-ion battery with novel 2D layered zinc orthovanadate array. Adv. Mater. 30, 1803181 (2018). \n19. Kundu, D. et al. Aqueous vs. nonaqueous $Z\\mathrm{n}$ -ion batteries: consequences of the desolvation penalty at the interface. Energy Environ. Sci. 11, 811–892 (2018). \n20. Zhang, L., Chen, L., Zhou, X. & Liu, Z. Towards high-voltage aqueous metalion batteries beyond $1.5~\\mathrm{V}$ The zinc/zinc hexacyanoferrate system. Adv. Energy Mater. 5, 1400930 (2015). \n21. Xia, C. et al. Rechargeable aqueous zinc-ion battery based on porous framework zinc pyrovanadate intercalation cathode. Adv. Mater. 30, 1705580 (2018). \n22. Zhao, Q. et al. High-capacity aqueous zinc batteries using sustainable quinone electrodes. Sci. Adv. 4, eaao1761 (2018). \n23. Sun, W. et al. $\\mathrm{Zn/MnO}_{2}$ battery chemistry with $\\mathrm{H^{+}}$ and $\\mathrm{Zn}^{2+}$ coinsertion. J. Am. Chem. Soc. 139, 9775–9778 (2017). \n24. Wang, F. et al. Reversible oxygen redox chemistry in aqueous zinc-ion batteries. Angew. Chem. Int. Ed. 58, 7062–7067 (2019). \n25. Li, H., McRae, L., Firby, C. J. & Elezzabi, A. Y. Rechargeable aqueous electrochromic batteries utilizing Ti-substituted tungsten molybdenum oxide based $\\scriptstyle{Z_{\\mathrm{{n}}}}^{2+}$ ion intercalation cathodes. Adv. Mater. 31, 1807065 (2019). \n26. Parker, J. F., Chervin, C. N., Nelson, E. S., Rolison, D. R. & Long, J. W. Wiring zinc in three-dimension re-writes battery performance-dendrite-free cycling. Energy Environ. Sci. 7, 1117–1124 (2014). \n27. Yufit, V. et al. Operando visualization and multi-scale tomography studies of dendrite formation and dissolution in zinc batteries. Joule 3, 1–18 (2019). \n28. Higashi, S., Lee, S. W., Lee, J. S., Takechi, K. & Cui, Y. Avoiding short circuits from zinc metal dendrites in anode by backside-plating configuration. Nat. Commun. 7, 11801 (2016). \n29. Zeng, X., Hao, J., Wang, Z., Mao, J. & Guo, Z. Recent progress and perspectives on aqueous $Z\\mathrm{n}$ -based rechargeable batteries with mild aqueous electrolytes. Energy Storage Mater. 20, 410–437 (2019). \n30. Wang, F. et al. Highly reversible zinc metal anode for aqueous batteries. Nat. Mater. 17, 543–549. \n31. Yang, H., Cao, Y., Ai, X. & Xiao, L. Improved discharge capacity and suppressed surface passivation of zinc anode in dilute alkaline solution using surfactant additives. J. Power Sources 128, 97–101 (2004). \n32. Xiong, W. et al. Controlling the sustainability and shape change of the zinc anode in rechargeable aqueous $\\mathrm{Zn/LiMn}_{2}\\mathrm{O}_{4}$ battery. Energy Storage Mater. 15, 131–138 (2018). \n33. Diggle, J. W., Despic, A. R. & Bockris, J. O. ′M. The Mechanism of the dendritic electrocrystallization of zinc. J. Electrochem. Soc. 116, 1503–1514 (1969). \n34. Monroe, C. & Newman, J. Dendrite growth in lithium/polymer systems: a propagation model for liquid electrolytes under galvanostatic conditions. J. Electrochem. Soc. 150, A1377–A1384 (2003). \n35. Elia, G. A. et al. An overview and future perspectives of aluminum batteries. Adv. Mater. 28, 7564–7579 (2016). \n36. Sun, L., Chien, C. L. & Searson, P. C. Fabrication of nanoporous nickel by electrochemical dealloying. Chem. Mater. 16, 3125–3129 (2004). \n37. Ding, F. et al. Dendrite-free lithium deposition via self-healing electrostatic shield mechanism. J. Am. Chem. Soc. 135, 4450–4456 (2013). \n38. Salgado-Ordorica, M. A. & Rappaz, M. Twinned dendrite growth in binary aluminum alloys. Acta Mater. 56, 5708–5718 (2008). \n39. Cahn, R.W. & Haasen, P. Physical Metallurgy. (Netherlands, 1996). \n40. Jackson, K. A. & Hunt, J. D. Lamellar and rod eutectic growth. Metal. Soc. AIME 236, 1129–1141 (1966). \n41. Xu, W. et al. Lithium metal anodes for rechargeable batteries. Energy Environ. Sci. 7, 513–537 (2014). \n42. Liang, Z. et al. Composite lithium metal anode by melt infusion of lithium into a 3D conducting scaffold with lithiophilic coating. Proc. Natl Acad. Sci. USA 113, 2862–2867 (2016). \n43. Wan, F. et al. Aqueous rechargeable zinc/sodium vanadate batteries with enhanced performance from simultaneous insertion of dual carrier. Nat. Commun. 9, 1656 (2018). \n44. Tang, X. et al. Mechanical force-driven growth of elongated bending $\\mathrm{TiO}_{2}$ - based nanotubular materials for ultrafast rechargeable lithium ion batteries. Adv. Mater. 26, 6111–6118 (2014). \n\n# Acknowledgements \n\nThis work was supported by National Natural Science Foundation of China (No. 51871107, 51631004), Top-notch Young Talent Program of China (W02070051), Chang Jiang Scholar Program of China (Q2016064), the Program for JLU Science and Technology Innovative Research Team (JLUSTIRT, 2017TD-09), the Fundamental Research Funds for the Central Universities, and the Program for Innovative Research Team (in Science and Technology) in University of Jilin Province. \n\n# Author contributions \n\nX.Y.L. and Q.J. conceived and designed the experiments. S.B.W., Q.R., R.Q.Y., H.S., Z.W., and M.Z. carried out the fabrication of materials and performed the electrochemical measurements and microstructural characterizations. X.Y.L. and Q.J. wrote the paper, and all authors discussed the results and commented on the manuscript. \n\n# Competing Interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-15478-4. \n\nCorrespondence and requests for materials should be addressed to X.-Y.L. or Q.J. \n\nPeer review information Nature Communications thanks Fei Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1038_s41467-020-15926-1", + "DOI": "10.1038/s41467-020-15926-1", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-15926-1", + "Relative Dir Path": "mds/10.1038_s41467-020-15926-1", + "Article Title": "Quantifying and understanding the triboelectric series of inorganic non-metallic materials", + "Authors": "Zou, HY; Guo, LT; Xue, H; Zhang, Y; Shen, XF; Liu, XT; Wang, PH; He, X; Dai, GZ; Jiang, P; Zheng, HW; Zhang, BB; Xu, C; Wang, ZL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Contact-electrification is a universal effect for all existing materials, but it still lacks a quantitative materials database to systematically understand its scientific mechanisms. Using an established measurement method, this study quantifies the triboelectric charge densities of nearly 30 inorganic nonmetallic materials. From the matrix of their triboelectric charge densities and band structures, it is found that the triboelectric output is strongly related to the work functions of the materials. Our study verifies that contact-electrification is an electronic quantum transition effect under ambient conditions. The basic driving force for contact-electrification is that electrons seek to fill the lowest available states once two materials are forced to reach atomically close distance so that electron transitions are possible through strongly overlapping electron wave functions. We hope that the quantified series could serve as a textbook standard and a fundamental database for scientific research, practical manufacturing, and engineering. The mechanism of contact electrification remains a topic of debate. Here, the authors present a quantitative database of the triboelectric charge density and band structure of many inorganic materials, verifying that contact electrification between solids is an electron quantum transition effect.", + "Times Cited, WoS Core": 626, + "Times Cited, All Databases": 647, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000531855500023", + "Markdown": "# Quantifying and understanding the triboelectric series of inorganic non-metallic materials \n\nHaiyang Zou1,5, Litong Guo1,2,5, Hao Xue1,3,5, Ying Zhang1, Xiaofang Shen3, Xiaoting Liu3, Peihong Wang1, $\\mathsf{X u\\Pi}\\mathsf{H e}^{1}$ , Guozhang Dai1, Peng Jiang1, Haiwu Zheng1, Binbin Zhang1, Cheng $\\mathsf{X}\\mathsf{u}^{1,2}$ & Zhong Lin Wang1,4✉ \n\nContact-electrification is a universal effect for all existing materials, but it still lacks a quantitative materials database to systematically understand its scientific mechanisms. Using an established measurement method, this study quantifies the triboelectric charge densities of nearly 30 inorganic nonmetallic materials. From the matrix of their triboelectric charge densities and band structures, it is found that the triboelectric output is strongly related to the work functions of the materials. Our study verifies that contact-electrification is an electronic quantum transition effect under ambient conditions. The basic driving force for contactelectrification is that electrons seek to fill the lowest available states once two materials are forced to reach atomically close distance so that electron transitions are possible through strongly overlapping electron wave functions. We hope that the quantified series could serve as a textbook standard and a fundamental database for scientific research, practical manufacturing, and engineering. \n\nT hneomceontoanct-healtecotrcicfiucrastifonr (llCEm) efrfieaclts iswhai uhnrievfersaltopthweo- materials that are electrically charged after physical contact. However, CE is generally referred to as triboelectrification (TE) in conventional terms. In fact, TE is a convolution of CE and tribology, while CE is a physical effect that occurs only due to the contact of two materials without rubbing against each other, and tribology refers to mechanical rubbing between materials that always involves debris and friction1. \n\nThe key parameters for CE, the surface charge density, the polarity, and the strength of the charges, are strongly dependent on the materials2–5. The triboelectric series describes materials’ tendency to generate triboelectric charges. The currently existing forms of triboelectric series are mostly measured in a qualitative method in the order of the polarity of charge production. Recently, a standard method6 has been established that allows this material “gene” of triboelectric charge density (TECD) to be quantitatively measured by contacting a tested material with a liquid metal using the output of a triboelectric nanogenerator (TENG) under fixed conditions. A table has been set for over 55 different types of organic polymer films. In comparison, inorganic materials have different atomic structures and band structures from polymers; therefore, it is necessary to quantify the triboelectric series for a wide range of common solid inorganic materials and study their triboelectric series in order to establish a fundamental understanding about their underlying mechanisms. \n\nOne of the oldest unresolved problems in physics is the mechanism of $\\mathrm{CE^{7,8}}$ . Many studies have been done on the analysis of the amount of the generated charges, including the correlation of charge amount with chemical nature2, electrochemical reactions9, work function10, ion densities11, thermionic emission9, triboemission12,13, charge affinity14, surface conditions and circumstances15, and flexoelectricity16. These studies focus on certain samples and quantitative data measured under various environmental conditions. The sample difference and the variance in the measurement conditions would cause large errors, and the mechanism studies based on a small dataset may not be reliable enough to derive a general understanding of the phenomenon. A systematic analysis based on a high-quality quantified database acquired in a universal standard method with a large volume of samples would provide more accurate data and facilitate a comprehensive understanding of the relationship between CE and the materials’ intrinsic properties. \n\nHere, we applied a standard method to quantify the triboelectric series for a wide range of inorganic non-metallic materials. Nearly 30 common inorganic materials have been measured, and the triboelectric series is listed by ranking the TECDs. By comparing the work functions of these materials, we find that the polarity of the triboelectric charges and the amount of charge transfer are closely related to their work functions. The triboelectric effect between inorganic materials and a metal is mainly caused by electronic quantum mechanical transitions between surface states, and the driving force of CE is electrons seeking to fill the lowest available states. The only required condition for CE is that the two materials are forced into the atomically close distance so that electronic transitions are possible between strongly overlapping wave functions. \n\n# Results \n\nThe principles of measurement and experimental setup. Nonmetallic inorganics are mostly synthesized at high temperature, they are hard materials with high surface roughness, and it is a challenge to make an accurate measurement of the TECD between solid–solid interfaces due to poor intimacy with inaccurate atomicscale contact. To avoid this limitation, we measured the TECD of the tested materials with liquid metal (mercury) as the contacting counterpart as we used for organic polymer materials6. The basic principle for measuring the TECD relies on the mechanism of TENG, which is shown in Fig. 1a–d. Details about the measurement technique and the experimental design as well as the standard experimental conditions have been reported previously6. The measurement method relies on the principle of TENG in contactseparation mode (Fig. 1b)3,17. When the two materials are separated, the negative surface charges would induce positive charges at the copper electrode side (Fig. 1c). When the gap distance reaches an appropriate distance $d_{1}$ , charges fully transfer to balance the potential difference (Fig. 1d). When the tested material is pushed back in contact with liquid mercury, the charges flow back (Fig. 1e). The TECD is derived from the amount of charge flow between the two electrodes. \n\nThe tested materials were purchased from vendors or synthesized through a pressing and sintering process in our lab (Supplementary Table 1). The tested materials were carefully cleaned with isopropyl alcohol by cleanroom wipers and dried by an air gun. Then, the specimens were deposited by a layer of Ti 1 $(15\\mathrm{nm})$ ) and a thick layer of Cu (above $300\\mathrm{nm},$ at the back as an electrode, and have a margin size of $2\\mathrm{mm}$ to avoid a short circuit when the sample contacts with mercury. \n\nThe measured TECD. One group of typical signals measured for mica–mercury are shown in Fig. 2. The open-circuit voltage reached up to $145.4\\mathrm{V}$ (Fig. 2a). A total of $69.6\\mathrm{nC}$ electrons (Fig. 2b) flowed between the two electrodes. For each type of material, at least three samples were measured to minimize the measurement errors. The results were recorded after the measured value reached its saturation level. This will eliminate the initial surface charges on the samples. Figure 2c shows the output of three samples of mica measured at different times, and the measured values have good repeatability (Fig. 2d) and stability. \n\nThe TECD refers to the transferred triboelectric charges per unit area of the CE surface. Nearly 30 kinds of common inorganic non-metallic materials were measured, and their triboelectric series is presented in Fig. 3. The quantified triboelectric series shows the materials’ capabilities to obtain or release electrons during the CE with the liquid metal. We have introduced a normalized TECD $\\alpha$ in our previous study \n\n$$\n\\alpha=\\frac{\\sigma}{|\\sigma_{\\mathrm{PTFE}}|},\n$$ \n\nwhere $\\sigma$ is the measured TECD of material. Here, we keep using the same standard for these inorganic materials for reference, so that the values are comparable. The average TECD values and the normalized TECDs $\\alpha$ of the measured materials are both listed in Table 1. The more negative the $\\alpha$ value is, the more negative charges it will get from mercury, and vice versa. If two materials have a large difference of $\\alpha$ values, they will produce higher triboelectric charges when rubbed together (Supplementary Fig. 1). In contrast, the less difference of $\\alpha$ values, the fewer charges exchange between them. The triboelectric series is validated by cross-checking (Supplementary Figs. 2 and 3). \n\nMechanism of CE for inorganic non-metallic materials. The standard measurement quantifies the TECD of various materials, the obtained values are only dependent on the materials. It remains to be systematically investigated, such as why different materials have a different amount of charges transferred; why some materials will become positively charged, but others were negatively charged after contact and separation with the same material; why the polarity of charge can be switched when they were contacted with different materials. \n\n![](images/df6c906c4d4a80822200a3b519ba11bab402c422c23c9d7bbafe5f3f40db1f21.jpg) \nFig. 1 Experimental setup and the working mechanism of the measurement technique. a Schematic diagram of the measurement system for the triboelectric charge density. b–e Schematic diagram of the mechanism for measuring the surface charge density. b Charges transferred between the two materials owing to the contact-electrification effect. There is no potential difference between the two materials when they are fully contacted with each other. c When the two materials are separated, the positive charges in mercury flow into the copper side in order to keep the electrostatic equilibrium. d When the gap goes beyond a specific distance $L,$ there is no current flow between two electrodes. e When the material is in contact with mercury again, the positive charges flow from copper to mercury due to the induction of the negative charges on the surface of the inorganic material. \n\nHere, we compare the TECD values with the relative work functions of the two contacting materials. In this study, all inorganic non-metallic materials were contacted with mercury. The work function of mercury is $\\emptyset_{\\mathrm{Hg}}=4.475\\mathrm{eV}^{11}$ . The work functions of the tested materials are listed in Supplementary Table 2. The work functions of inorganic non-metallic materials are determined by materials themselves, but can be modified by crystallographic orientation, surface termination and reconstruction, and surface roughness, and so on. Therefore, some materials have a wide range of work functions in the literature. As shown in Fig. 4, as the work functions of materials decrease, the TECD values increase from $-62.66$ to $61.80\\upmu\\mathrm{C}\\mathrm{cm}^{-2}$ . The work function is related to the minimum thermodynamic energy needed to remove an electron from a solid to a point just outside the solid surface. Our results show that electron transfer is the main origin of CE between solids and metal18. In addition, the polarity of the CE charges is determined by the relative work functions of materials. When the work function of the tested material A is smaller than the work function of mercury, $\\begin{array}{r}{\\varnothing_{\\mathrm{A}}<\\varnothing_{\\mathrm{Hg}},}\\end{array}$ the tested materials will be positively charged after intimate contact with mercury; when the work functions of tested material B are close to the work function of mercury, $\\emptyset_{\\mathrm{B}}\\approx\\emptyset_{\\mathrm{Hg}}$ the tested material $\\mathbf{B}$ will be little electrically charged; when the work functions of tested material C are larger than the work function of mercury, $\\varnothing_{\\mathrm{C}}{>}\\varnothing_{\\mathrm{Hg}},$ the tested materials will be negatively charged. The TECDs of tested materials are strongly dependent on the work function difference. If the two materials have a larger difference of work functions, they will have more electrons transferred. These results show that electron transfer during CE is related to the band structure and energy level distribution. The electrons flow from the side that has high energy states to the side having low energy states. \n\n![](images/ae253db3712199bbfa9a673e7daa69d94555bbdfc9a1444cc9064d7831205af7.jpg) \nFig. 2 A set of typical measured signals of tested samples. a Open-circuit voltage of mica during the processes of contact and separation with mercury. b Curve of transferred charge between the two electrodes under short-circuit condition. c Measured charge transferred for three different samples of mica. d Stability of the measured values for many cycles of operation. Source data are provided as a Source Data file. \n\nThe quantum mechanical transition model is proposed to explain the CE of inorganic non-metallic materials. Suppose we have a material A, which has a higher Fermi level than the Fermi level of the metal. The disruption of the periodic-potential function results in a distribution of allowed electric energy states within the bandgap, shown schematically in Fig. 5a, along with the discrete energy states in the bulk material. When the material is brought into intimate contact with the metal, the Fermi levels must be aligned (Fig. 5b), which causes the energy bands to bend and the surface states to shift as well. Normally, the energy states below the Fermi level of material A— $E_{\\mathrm{FA}}$ are filled with electrons and the energy states above $E_{\\mathrm{FA}}$ are mostly empty if the temperature is relatively low. Therefore, the electrons at the surface states above $E_{\\mathrm{FA}}$ will flow into the metal, thus the metal gets negatively charged, and the originally neutralized material A becomes positively charged for losing electrons. The electrons that flowed from semiconductors or insulators to metals are mainly from the surface energy states. If the work functions of two materials (B and metal) are equal, there will be little electron transfer (Fig. 5c, d); therefore, it would have no electrification. When the work function of tested material C is lower than the work function of the metal (Fig. 5e), the Fermi levels tend to level, surface energy states shift down, and electrons flow reversely from metal to fill the empty surface states in material C to reach the aligned Fermi level (Fig. 5f). Thus, the tested material will be negatively charged and the metal becomes positively charged. \n\nIf two materials have a large difference of work functions, there are many discrete allowed surface states that electrons are able to transit; the surface is able to carry more charges after contact or friction. If the difference is low, few discrete surface states exist for electrons transition; the surface will be less charged. The surface charge density can be changed by contact with different materials, due to the different levels of work functions. The polarity of surface charges can be switched as well, since they have different directions of electron transition. \n\n![](images/ca8c9e037bbb7fc32f39cb19faec8af766693486a34b6253190425b988eca6fb.jpg) \nFig. 3 Quantified triboelectric series of some common inorganic nonmetalic materials. The error bar indicates the range within a standard deviation. Source data are provided as a Source Data file. \n\nFor inorganic non-metallic materials, the dielectric constant is an important parameter. We have analyzed the relationship between dielectric constant and TECD. From the Gauss theorem, if we ignore the edge effect, the ideal induced short circuit transferred charge in the inorganic material–mercury TENG process is given by6,17: \n\n$$\nQ_{\\mathrm{SC}}=\\frac{S\\sigma_{c}x(t)}{\\frac{d_{1}\\varepsilon_{0}}{\\varepsilon_{1}}+x(t)},\n$$ \n\nwhere $\\varepsilon_{1}$ is the dielectric permittivity of the inorganic material, $d_{1}$ is the thickness, $x(t)$ is the separation distance over time $t,$ and $\\sigma_{\\mathrm{c}}$ is the surface charge density. From Eq. (1), under the measured conditions, $d_{1}\\ll\\ x(t)$ , and the part of $\\frac{d_{1}\\varepsilon_{0}}{\\varepsilon_{1}}$ can be ignored. Therefore, the dielectric constant will not influence the charge transfer $Q_{\\mathrm{SC}}$ and the surface charge density $\\sigma_{\\mathrm{c}}$ . As expected, the relation of TECD and dielectric constant of these materials is shown in Fig. 4; the measured TECDs are not affected by the dielectric constant of materials. \n\n# Discussion \n\nA quantum mechanical transition always describes an electron jumping from one state to another on the nanoscale, while CE between solids is a macroscopic quantum transition phenomenon. Materials have a large scale of surface states to store or lose electrons, and charge transfer between two triboelectric materials is based on the capacitive model, so it can reach a significantly high voltage $(>100\\mathrm{\\V})^{19}$ , which is different from the contact potential (mostly ${<}1\\mathrm{V}$ )20. The quantum transition model between the surface energy states explains how electrons are accumulated or released at the surfaces of inorganic dielectric materials and how the surface becomes charged, while the contact potential model only explains carrier diffusion inside semiconductors24. The surface modification technologies, including impurity and doping elements, surface termination and reconstruction21, surface roughness22, and curvature effect23 can tune the TECD. Based on the proposed model, it is suggested that the fundamental driving force of CE is that electrons fill the lowest available energy levels if there is little barrier. When the two materials have reached atomically close distance, electron transition is possible between strongly overlapping electron wave functions25,26. \n\n
Table 1 Triboelectric series of materials and their TECD.
Materials (μCm-2)Average TECD STDEVα
Mica61.80 1.630.547
Float glass 40.200.850.356
Borosilicate glass 38.631.180.342
BeO 9.060.210.080
PZT-5 8.820.160.078
MgSiO3 2.720.070.024
CaSiO3 2.380.150.021
Bi4Ti3O12 2.020.210.018
Bio.5Nao.5TiO3 1.760.050.016
NiFe2O4 1.750.070.0155
Bao.65Sro.35TiO3 1.280.110.011
BaTiO3 1.270.080.0112
PZT-41.24 0.120.011
ZnO 0.860.040.008
NiO 0.530.050.005
SnO2 0.460.020.004
SiC 0.310.070.003
CaTiO3 0.240.020.002
ZrO2 0.090.070.001
Cr2O0.02 0.010.00013
FeO30.00 0.020.000
AlO3-1.58 0.14-0.014
TiO2-6.41 0.18-0.057
AIN -13.241.35-0.117
BN -16.900.97-0.149
Clear very high--39.95 2.04-0.353
temperature glass ceramic Ultra-high-temperature -62.660.47-0.554
quartz glass
\n\nSTDEV, standard deviation. Note: The $\\alpha$ refers to the measured triboelectric charge density of tested materials over the absolute value of the measured triboelectric charge density of the reference material (PTFE). \n\nThe work functions are determined by the compositions of compounds, chemical valence state, electronegativity15, crystallographic orientation27, temperature19, defects28,29, and so on. Accordingly, the calculation of work functions can be used as a comparison of a materials’ property of TE and to estimate their triboelectric output. In addition, the work functions can be modified to improve the TE for enhancing the triboelectric effect for energy harvesting30–33 and sensing34,35, or reduce the electrical discharge due to CE to improve safety. \n\nIn summary, we have quantitatively measured the triboelectric series of some common inorganic non-metallic materials under defined conditions. The TECD data obtained depends only on the nature of the material. This serves as a basic data source for investigating the relevant mechanism of CE, and a textbook standard for many practical applications such as energy harvesting and self-powered sensing. The study verifies that the electron transfer is the origin of CE for solids, and that CE between solids is a macroscopic quantum mechanical transition effect that electrons transit between the surface states. The driving force for CE is that electrons tend to fill the lowest available surface states. Furthermore, the TE output could be roughly estimated and compared by the calculation of work functions, and ajusted by the modification of the material's work function through a variety of methods. \n\n![](images/97362ae1c69acfa0696d6bd8e11da8092dff9e0c328063b270c9b2630fd9be07.jpg) \nFig. 4 The influence of work function and dielectric constant on contactelectrification. a Relationship between the triboelectric charge density and work functions of materials. b Relationship between the triboelectric charge density and dielectric constant. Source data are provided as a Source Data file. \n\n# Methods \n\nSample preparation. The tested materials were purchased from vendors or synthesized through a pressing and sintering process. Some of the ceramic specimens, such as $\\mathrm{Mg}\\mathrm{Si}\\mathrm{O}_{3}$ , $\\mathrm{CaSiO}_{3}$ , $\\mathrm{Bi}_{4}\\mathrm{Ti}_{3}\\mathrm{O}_{12}$ $\\mathrm{Bi}_{0.5}\\mathrm{Na}_{0.5}\\mathrm{TiO}_{3}.$ , $\\mathrm{NiFe}_{2}\\mathrm{O}_{4},$ $\\mathbf{Ba}_{0.65}\\mathbf{Sr}_{0.35}\\mathrm{TiO}_{3}.$ ${\\mathrm{BaTiO}}_{3}.$ and $\\mathrm{CaTiO}_{3}$ , were prepared using a conventional solid-state reaction and solid-phase sintering. Some materials, such as $\\mathrm{znO}$ , NiO, $\\mathrm{SnO}_{2}$ , $\\mathrm{Cr}_{2}\\mathrm{O}_{3}$ $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ , and $\\mathrm{TiO}_{2}$ , were prepared by solid-phase sintering method using commercial ceramic powders. The details were described below. \n\nFor $\\mathrm{Mg}\\mathrm{SiO}_{3}$ , the high-purity $\\mathrm{MgO}$ $(99.5\\%)$ and $\\mathrm{SiO}_{2}$ $(99.5\\%)$ ) powders were baked at $80~^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ to remove hygroscopic moisture and mixed in an ethanol medium by ball milling for $^{8\\mathrm{h}}$ according to the stoichiometric formula. The slurry was dried at $110^{\\circ}\\mathrm{C}$ for $^{10\\mathrm{h}}$ and the dried powder was calcined at $1100^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h},}$ and then ball-milled in an ethanol medium for $^{8\\mathrm{h}}$ . After drying again, the obtained powders were granulated with polyvinyl alcohol as a binder and pressed into green disks with a diameter of 2 in. and a thickness of $1\\mathrm{mm}$ under a pressure of $30\\mathrm{MPa}$ Next, the green disks were heated at $600^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ to remove the binder, and then sintered at $1400^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . After the obtained ceramic disks were polished on both sides, the gold electrode was sputtered on one side. \n\nOther samples, including $\\mathrm{CaSiO}_{3}$ , $\\mathrm{Bi}_{4}\\mathrm{Ti}_{3}\\mathrm{O}_{12}$ , $\\mathrm{Bi}_{0.5}\\mathrm{Na}_{0.5}\\mathrm{TiO}_{3}$ , ${\\mathrm{NiFe}}_{2}{\\mathrm{O}}_{4}$ , $\\mathrm{Ba}_{0.65}\\mathrm{Sr}_{0.35}\\mathrm{TiO}_{3}$ , $\\mathrm{BaTiO}_{3}$ , and $\\mathrm{CaTiO}_{3}$ , are prepared similarly to $\\mathrm{Mg}\\mathrm{Si}\\mathrm{O}_{3}$ , except that there are differences in the temperature and holding time of powder calcination and ceramic sintering. Specific parameters for different samples are listed in the Supplementary Table 1. \n\nFor single element oxide, including $\\mathrm{znO}$ , NiO, $\\mathrm{SnO}_{2}$ $\\mathrm{Cr}_{2}\\mathrm{O}_{3}$ , ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3},$ and $\\mathrm{TiO}_{2}$ , the samples are directly prepared by solid-phase sintering method using commercial powders as the raw materials. Taking zinc oxide as an example, the high-purity $\\mathrm{znO}$ powders $(99.5\\%)$ were granulated with polyvinyl alcohol as a binder and pressed into green disks with a diameter of 2 in. and a thickness of $1\\mathrm{mm}$ under a pressure of 30 \n\n![](images/98bd1795a9a26f93f3d72dd9ec9e1aea1aec8362ca0182255f8eb169494f8456.jpg) \nFig. 5 Electronic quantum transition model of contact-electrification between a dielectric and metal. a When a dielectric A is brought into contact with the metal as shown in the figures, some electrons on the surface states flow into metal to seek the lowest energy states. b The energy bands bend to align the Fermi levels. Most electrons at the surface energy states above the balanced Fermi level flow into metal and left an equal amount of holes at the surface (as shown in green box). Thus, the original neutrally charged dielectric A turns to have positive charges on the surfaces due to the electrons lose. c, d When a dielectric B is brought into contact with the metal, the Fermi levels are balanced, the surface energy states equal. There are no quantum transitions between the two materials. e When a dielectric C contacts the metal, electrons on the surface of the metal flow into the dielectric C to seek the lowest energy levels. f The energy bands shift to align the Fermi levels. Electrons flow from metal to dielectric C to fill the empty surface states due to the difference of energy levels (as shown in the green box). The original neutrally charged dielectric C turns to carry negative charges on the surfaces by obtaining electrons. \n\nMPa. Next, the green disks were heated at $600^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ to remove the binder, and then sintered at $\\mathrm{i}200^{\\circ}\\mathrm{C}$ for $1.5\\mathrm{h}$ . After the obtained ceramic disks were polished on both sides, the gold electrode was sputtered on one side. \n\nSamples, such as AlN, $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ , BeO, mica, float glass, borosilicate glass, PZT-5, SiC, $\\mathrm{ZrO}_{2}$ , BN, clear very high-temperature glass ceramic, and ultra-hightemperature quartz glass, were directly purchased from different companies, which were also listed in the Supplementary Table 1. \n\nThe materials were washed with isopropyl alcohol, cleaned with cleanroom wipers, and dried by an air gun. Then, the materials were deposited with a layer of Ti $\\mathrm{{[10\\nm)}}$ and a thick layer of copper (above $300\\mathrm{nm}$ ) with a margin size of $2\\mathrm{mm}$ by E-beam evaporator (Denton Explorer). \n\nThe measurement of TECDs. The samples were placed on the linear motor and moved up and down automatically with the help of the linear motor control program and system. For some inorganic compounds, the TECDs are relatively small; the turbulent caused by the motion of tested samples would cause some noise because of the friction between the platinum wire and mercury. Therefore, the platinum wire was then designed to go through the bottom of the Petri dish and fully immersed in the liquid metal, and sealed by epoxy glue. In this way, there is no contact and separation between them; therefore, the noise is minimized. \n\nThe sample’s surfaces were carefully adjusted to ensure the precisely right contact between the tested material and the liquid mercury. The position and angles were adjusted by a linear motor, a high load lab jack (Newport 281), and a two-axis tilt and rotation platform (Newport P100-P). The short-circuit charge $Q_{\\mathrm{SC}}$ and open-circuit voltage $V_{\\mathrm{OC}}$ of the samples were measured by a Keithley 6514 electrometer in a glove box with an ultra-pure nitrogen environment (Airgas, $99.999\\%$ ). The environmental condition was fixed at $20\\pm1^{\\circ}\\mathrm{C}$ , 1 atm with an additional pressure of $1{-}1.5\\mathrm{in}$ . height of $\\mathrm{H}_{2}\\mathrm{O}$ and $0.43\\%$ relative humidity. In addition, samples were kept in the glove box overnight to eliminate the water vapor on the surface of the samples. \n\n# Data availability \n\nThe datasets generated during and/or analyzed during the current study are available from the corresponding author. The source data underlying Figs. 2a–d, 3, and 4a–b are provided as a Source Data file. \n\nReceived: 12 January 2020; Accepted: 30 March 2020; Published online: 29 April 2020 \n\n# References \n\n1. Wang, Z. L. On the first principle theory of nanogenerators from Maxwell’s equations. Nano Energy 104272 (2019). \n2. Henniker, J. Triboelectricity in polymers. Nature 196, 474 (1962). \n3. Zi, Y. L. et al. Standards and figure-of-merits for quantifying the performance of triboelectric nanogenerators. Nat. Commun. 6, 8376 (2015). \n4. Seol, M. et al. Triboelectric series of 2D layered materials. Adv. Mater. 30, \n1801210 (2018). \n5. Williams, M. W. The dependence of triboelectric charging of polymers on their chemical compositions. J. Macromol. Sci. Polym. Rev. 14, 251–265 (1976). \n6. Zou, H. Y. et al. Quantifying the triboelectric series. Nat. Commun. 10, 1427 (2019). \n7. Terris, B. D., Stern, J. E., Rugar, D. & Mamin, H. J. Contact electrification using force microscopy. Phys. Rev. Lett. 63, 2669–2672 (1989). \n8. Shaw, P. E. The electrical charges from like solids. Nature 118, 659–660 (1926). \n9. Hsu, S. M. & Gates, R. S. Effect of materials on tribochemical reactions between hydrocarbons and surfaces. J. Phys. D 39, 3128–3137 (2006). \n10. Davies, D. K. Charge generation on dielectric surfaces. J. Phys. D 2, 1533–1537 (1969). \n11. Horn, R. G., Smith, D. T. & Grabbe, A. Contact electrification induced by monolayer modification of a surface and relation to acid-base interactions. Nature 366, 442–443 (1993). \n12. Nakayama, K. & Hashimoto, H. Triboemission of charged-particles and photons from wearing ceramic surfaces in various hydrocarbon gases. Wear \n185, 183–188 (1995). \n13. Wang, Y. et al. Triboemission of hydrocarbon molecules from diamond-like carbon friction interface induces atomic-scale wear. Sci. Adv. 5, eaax9301 (2019). \n14. Lee, B. W. & Orr, D. E. The triboelectric series. https://alphalabinc.com/ triboelectric-series (2009). \n15. Fowle, F. E. Smithsonian Physical Tables 322 (Smithsonian Institution, Washington, 1921). \n16. Mizzi, C. A., Lin, A. Y. W. & Marks, L. D. Does flexoelectricity drive triboelectricity? Phys. Rev. Lett. 123, 116103 (2019). \n17. Niu, S. M. et al. Theoretical study of contact-mode triboelectric nanogenerators as an effective power source. Energy Environ. Sci. 6, \n3576–3583 (2013). \n18. Wang, Z. L. & Wang, A. C. On the origin of contact-electrification. Mater. Today 30, 34–51 (2019). \n19. Xu, C. et al. Raising the working temperature of a triboelectric nanogenerator by quenching down electron thermionic emission in contact-electrification. Adv. Mater. 30, 1803968 (2018). \n20. Streetman, B. G. & Banerjee, S. Solid State Electronic Devices (Prentice-Hall, Englewood Cliffs, 2001). \n21. Greiner, M. T., Chai, L., Helander, M. G., Tang, W. M. & Lu, Z. H. Transition metal oxide work functions: the influence of cation oxidation state and oxygen vacancies. Adv. Funct. Mater. 22, 4557–4568 (2012). \n22. Li, W. & Li, D. Y. On the correlation between surface roughness and work function in copper. J. Chem. Phys. 122, 064708 (2005). \n23. Xu, C. et al. Contact-electrification between two identical materials: curvature effect. ACS Nano 13, 2034–2041 (2019). \n24. Neaman, D. A. Semiconductor Physics and Devices: Basic Principles (Irwin, Chicago, 1997). \n25. Xu, C. et al. On the electron-transfer mechanism in the contact-electrification effect. Adv. Mater. 30, 1706790 (2018). \n26. Li, S. M., Zhou, Y. S., Zi, Y. L., Zhang, G. & Wang, Z. L. Excluding contact electrification in surface potential measurement using Kelvin probe force microscopy. ACS Nano 10, 2528–2535 (2016). \n27. Smoluchowski, R. Anisotropy of the electronic work function of metals. Phys. Rev. 60, 661–674 (1941). \n28. Lany, S., Osorio-Guillen, J. & Zunger, A. Origins of the doping asymmetry in oxides: Hole doping in NiO versus electron doping in ZnO. Phys. Rev. B 75, 241203 (2007). \n29. Henrich, V. E. & Cox, P. A. The Surface Science of Metal Oxides (Cambridge University Press, Cambridge, 1996). \n30. Lin, Z. et al. Rationally designed rotation triboelectric nanogenerators with much extended lifetime and durability. Nano Energy 68, 104378 (2020). \n31. Lin, Z. M. et al. Super-robust and frequency-multiplied triboelectric nanogenerator for efficient harvesting water and wind energy. Nano Energy 64, 103908 (2019). \n32. Chen, J. et al. Micro-cable structured textile for simultaneously harvesting solar and mechanical energy. Nat. Energy 1, 16138 (2016). \n33. Shi, K. M. et al. Dielectric modulated cellulose paper/PDMS-Based triboelectric nanogenerators for wireless transmission and electropolymerization applications. Adv. Funct. Mater. 30, 1904536 (2019). \n34. Wu, Z. et al. Multifunctional sensor based on translational-rotary triboelectric nanogenerator. Adv. Energy Mater. 9, 1901124–1901124 (2019). \n35. He, X. et al. A hierarchically nanostructured cellulose fiber-based triboelectric nanogenerator for self-powered healthcare products. Adv. Funct. Mater. 28, 1805540–1805540 (2018). \n\n# Acknowledgements \n\nThis work was financially supported by the Hightower Chair Foundation in Georgia Tech \n\n# Author contributions \n\nZ.L.W. supervised and guided the project; H. Zou, L.G., H.X., and X.H. fabricated the devices; H.X., X.S., and X.L. synthesized the materials; H. Zou, Y.Z., and P.W. designed the measurement; L.G., H.X., H. Zou, G.D., P.J., B.Z., C.X., and H.Z. performed the experiments; L.G., H. Zou, and H.X. analyzed the data, H. Zou proposed the model; the manuscript was prepared with input from all authors. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-15926-1. \n\nCorrespondence and requests for materials should be addressed to Z.L.W. \n\nPeer review information Nature Communications thanks Junghyo Nah and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. 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If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1039_c9ee03087e", + "DOI": "10.1039/c9ee03087e", + "DOI Link": "http://dx.doi.org/10.1039/c9ee03087e", + "Relative Dir Path": "mds/10.1039_c9ee03087e", + "Article Title": "Discordant nature of Cd in PbSe: off-centering and core-shell nulloscale CdSe precipitates lead to high thermoelectric performance", + "Authors": "Cai, ST; Hao, SQ; Luo, ZZ; Li, X; Hadar, I; Bailey, T; Hu, XB; Uher, C; Hu, YY; Wolverton, C; Dravid, VP; Kanatzidis, MG", + "Source Title": "ENERGY & ENVIRONMENTAL SCIENCE", + "Abstract": "We report a novel hierarchical microstructure in the PbSe-CdSe system, which collectively contributes to significant enhancement in thermoelectric performance, with ZT(ave) similar to 0.83 across the 400-923 K temperature range, the highest reported for p-type, Te-free PbSe systems. We have investigated the local atomic structure as well as the microstructure of a series of PbSe-xCdSe materials, up to x = 10%. We find that the behavior of the Cd atoms in the octahedral rock salt sites is discordant and results in off-center displacement and distortion. Such off-centered Cd in the PbSe matrix creates (1) L-sigma electronic energy band convergence, (2) a flattened L band, both contributing to higher Seebeck coefficients, and (3) enhanced phonon scattering, which leads to lower thermal conductivity. These conclusions are supported by photoemission yield spectroscopy in air (PYSA), solid state Cd-111, Se-77 NMR spectroscopy and DFT calculations. Above the solubility limit (>6%CdSe), we also observe endotaxial CdSe nullo-precipitates with core-shell architecture formed in PbSe, whose size, distribution and structure gradually change with the Cd content. The nullo-precipitates exhibit a zinc blende crystal structure and a tetrahedral shape with significant local strain, but are covered with a thin wurtzite layer along the precipitate/matrix interface, creating a core-shell structure embedded in PbSe. This newly discovered architecture causes a further reduction in lattice thermal conductivity. Moreover, potassium is found to be an effective p-type dopant in the PbSe-CdSe system, leading to an enhanced power factor, a maximum ZT of similar to 1.4 at 923 K for Pb0.98K0.02Se-6%CdSe.", + "Times Cited, WoS Core": 456, + "Times Cited, All Databases": 622, + "Publication Year": 2020, + "Research Areas": "Chemistry; Energy & Fuels; Engineering; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000508857600012", + "Markdown": "# Discordant nature of Cd in PbSe: off-centering and core–shell nanoscale CdSe precipitates lead to high thermoelectric performance† \n\nSongting Cai, $\\textcircled{1}$ a Shiqiang Hao,a Zhong-Zhen Luo,bc Xiang Li,d Ido Hadar, Trevor P. Bailey, $\\textcircled{1}$ e Xiaobing Hu, $\\textcircled{1}$ af Ctirad Uher,e Yan-Yan Hu, dg Christopher Wolverton,a Vinayak P. Dravid $\\textcircled{1}$ \\*af and Mercouri G. Kanatzidis \\*b \n\nWe report a novel hierarchical microstructure in the PbSe–CdSe system, which collectively contributes to significant enhancement in thermoelectric performance, with $Z T_{\\mathrm{ave}}\\sim0.83$ across the $400{-}923\\ \\mathsf{K}$ temperature range, the highest reported for p-type, Te-free PbSe systems. We have investigated the local atomic structure as well as the microstructure of a series of PbSe–xCdSe materials, up to $x=10\\%$ . We find that the behavior of the Cd atoms in the octahedral rock salt sites is discordant and results in off-center displacement and distortion. Such off-centered Cd in the PbSe matrix creates (1) $L-\\Sigma$ electronic energy band convergence, (2) a flattened L band, both contributing to higher Seebeck coefficients, and (3) enhanced phonon scattering, which leads to lower thermal conductivity. These conclusions are supported by photoemission yield spectroscopy in air (PYSA), solid state ${}^{111}{\\mathsf{C d}}_{}$ $^{77}\\mathsf{S e}$ NMR spectroscopy and DFT calculations. Above the solubility limit $1>6\\%00\\mathsf{S e})$ , we also observe endotaxial CdSe nano-precipitates with core–shell architecture formed in PbSe, whose size, distribution and structure gradually change with the Cd content. The nano-precipitates exhibit a zinc blende crystal structure and a tetrahedral shape with significant local strain, but are covered with a thin wurtzite layer along the precipitate/matrix interface, creating a core–shell structure embedded in PbSe. This newly discovered architecture causes a further reduction in lattice thermal conductivity. Moreover, potassium is found to be an effective p-type dopant in the PbSe–CdSe system, leading to an enhanced power factor, a maximum $Z T$ of $\\mathord{\\sim}1.4$ at $923\\mathsf{K}$ for Pb0.98K0.02Se–6%CdSe. \n\n# Broader context \n\nThermoelectric (TE) devices can convert between thermal and electrical energy and are considered a promising energy-saving technology. Historically, PbSe has been considered as an inferior chalcogenide analog to PbTe, which is one of the top performing TE materials. The much larger abundance of Se compared to Te and higher melting point, however, make PbSe attractive for development with the aim of raising its performance closer to PbTe. This work demonstrates a synergistic combination of mechanisms in p-type PbSe brought about by the addition of CdSe to achieve an enhancement in the power factor and a concomitant reduction in the thermal conductivity, eventually yielding a high peak ZT of $\\sim1.4$ with a record average $Z T_{\\mathrm{ave}}\\sim0.83$ across $400{\\-}923\\mathrm{~K~}$ . This significant advance is realized by all-scale microstructure construction via Cd alloying. Both theoretical and experimental results reveal that $\\operatorname{Cd}^{2+}$ sits at an off-centered position in the PbSe lattice, leading to both electronic band convergence and low-frequency phonon modes. Moreover, tetrahedral CdSe nano-precipitates with core–shell architecture formed above the solubility limit, inducing significant strain and thus a further reduction in lattice thermal conductivity. The new insights into the exquisite role of Cd in PbSe provide better understanding for design of more efficient thermoelectric materials. \n\n# Introduction \n\nThermoelectric (TE) devices are able to convert between thermal and electrical energy directly and reversibly,1,2 and are considered as a promising energy-saving technology thanks to their advantages such as no moving parts, service free operation and excellent environmental stability.3 Therefore, the desire to see TE applications more broadly implemented is strong, but these have been limited because of their high cost and low conversion efficiencies.4–6 The factors determining the conversion efficiency of TE devices are strongly interrelated and make performance improvements challenging.2,7–9 The efficiency of TE materials is determined by the figure of merit $Z T=S^{2}\\sigma T/\\kappa_{\\mathrm{tot}}=S^{2}\\sigma T/(\\kappa_{\\mathrm{ele}}+\\kappa_{\\mathrm{latt}})$ , where $s$ , ${\\sigma},{\\cal T},{\\kappa}_{\\mathrm{tot}},{\\kappa}_{\\mathrm{ele}}$ and $\\kappa_{\\mathrm{latt}}$ represent the Seebeck coefficient, electrical conductivity, absolute temperature, total thermal conductivity, electronic thermal conductivity and lattice thermal conductivity, respectively. The overall performance of TE devices, in fact, depends on the average ZT $(Z T_{\\mathrm{ave}})$ , where ZTave ¼ Th 1 TcÐ Tch ZTdT (Th and Tc are the absolute temperature of the hot side and cold side, respectively). Therefore, in practical applications of thermoelectric materials in device modules, $Z T_{\\mathrm{ave}}$ is the key figure of merit that determines the device efficiency, not the maximum $Z T$ achieved at some temperature. $Z T_{\\mathrm{ave}}$ must be as high as possible over as broad a temperature range as possible. In fact, the main reasons a high maximum $Z T$ is generally pursued are derived from the desire to also obtain higher $Z T_{\\mathrm{ave}}$ . Because most leading materials in this field contain rare and expensive tellurium (e.g. PbTe and $\\mathbf{Bi}_{2}\\mathrm{Te}_{3})$ ,10 there is a strong drive to develop next generation highly efficient, lower cost thermoelectric materials.11–13 \n\nDuring the past decade, remarkable milestones have been reached in enhancing $Z T$ by improving the power factor $\\left(\\mathbf{PF}=S^{2}\\sigma\\right).$ ),14–25 or reducing the lattice thermal conductivity. The latter was realized through the design of strengthened phonon scattering by hierarchical construction of microstructures, especially in lead chalcogenides, $^{1,21,22,26-32}$ or by finding intrinsically low thermal conductivity in complex crystal structures.33–43 Lead telluride (PbTe) has a remarkable electronic conduction band (CB) and valence band (VB) and can be tuned by alloying into n-type (e.g. PbTe-CdTe,44 PbTe-PbS,45 PbTe-Ge/Si,46 etc.) or p-type (e.g. PbTe- $.\\mathbf{Mg/Ca/Sr},$ 47 PbTe-PbS,48 etc.). Because of the desire to reduce or eliminate the use of scarce tellurium, recently significant progress has been made in sulfide PbS analogs such as p-type $\\mathrm{Pb}_{0.975}\\mathrm{Na}_{0.025}\\mathrm{S}-3\\%\\mathrm{Cd}\\mathrm{S}$ $Z T\\sim1.3$ at $923\\ \\mathrm{K})^{29}$ or n-type $\\mathrm{Pb}_{0.9865}\\mathrm{Ga}_{0.0125}\\mathrm{In}_{0.001}\\mathrm{S}$ $\\mathit{Z T}\\sim1.0$ at 923 K). The enhanced performance in these Te-free systems is promising, but still inferior to PbTe. In contrast to PbTe, the PbSe analog has several noteworthy advantages: (1) a much larger abundance of Se and therefore lower cost, (2) a higher melting point and thus potentially a wider operation temperature range, and (3) lower lattice thermal conductivity. Hence, PbSe is a promising alternative for PbTe if one can tune its performance to a comparable level.50 The main disadvantage of PbSe relative to PbTe originates from its larger energy separation of the light hole L and heavy hole $\\Sigma$ valence bands $\\mathrm{PbTe}\\sim0.14\\:\\mathrm{eV}$ , while PbSe $\\sim$ $0.27\\ \\mathrm{eV}$ at room temperature), leading to lower power factors. \n\nZhao et al. reported effective strategies51 for improving the overall thermoelectric properties of p-type PbSe via CdS alloying and Na doping, where band convergence and nanostructuring were claimed to be responsible for the power factor enhancement and thermal conductivity decrease, respectively. Follow-up work by Tan et al. on the $\\mathrm{\\bfPb_{1-x}N a_{x}S e}$ –CdTe (p-type) system21 as well as by Qian et al. on $\\mathrm{Pb}_{1-x}\\mathrm{Sb}_{x}\\mathrm{Se-CdSe}$ (n-type)32 also gave record performance, which further proves the significant role Cd plays in PbSe. These previous studies only considered relatively low concentrations of Cd alloying and added other variables such as carrier dopants (Na or Sb) or anion substitution (Te or S) concurrently. Therefore, the exclusive effect of Cd on PbSe with respect to the solubility, micro/ band-structure, phonon behavior, interactions with other dopants, etc. has not yet been addressed in any detail. \n\nIn this contribution, in an effort to decouple various factors involved in optimizing this system, and to better understand the role of $\\operatorname{Cd}^{2+}$ in a rock salt lattice, we focused on PbSe–xCdSe compositions with large alloying concentration $x$ up to $10\\%$ . With the help of solid-state NMR spectroscopy and DFT calculations, we probed the behavior of Cd atoms in PbSe solid solution sitting in the Pb sites of the rock salt structure. The previous studies did not address the local structure of Cd atoms in the lattice as it is generally assumed that it is a straightforward replacement of the octahedral $\\mathrm{Pb}^{2+}$ atoms. However, the classical coordination chemistry of $\\operatorname{Cd}^{2+}$ with chalcogen based ligands indicates that the tetrahedral coordination environment is strongly preferred. The following question then arises: is the $\\operatorname{Cd}^{2+}$ ion stable in the perfect octahedral site imposed by the rock salt structure of PbSe? We expect an inherent conflict to exist between the tetrahedral coordination preference of Cd and the octahedral geometry of its hosting site, which could lead to significant local deviations, such as off-centering, in the structure from the ideal state. We refer to guest atoms found in this situation as discordant. In the present case, we find that the off-centering leads to both strengthened phonon-scattering in the low frequency regime and a converged, more flattened electronic band structure than in pure PbSe, all of which contribute to strongly enhanced thermoelectric performance. In addition, using advanced electron microscopy, we observe that above $6\\%$ CdSe content, CdSe precipitates in tetrahedral shape nucleate and form from the super-saturated solid solution. These have a zinc blende structure in their core and a wurtzite structure as a shell along the CdSe/PbSe phase boundary. This is a novel nanostructure and results in a further decrease of thermal conductivity due to induced significant local strain. Lastly, potassium doping is an effective p-type dopant in PbSe, leading to marked increases in the thermoelectric performance. The maximum ZT value of $\\mathord{\\sim}1.4$ is obtained in $\\mathrm{Pb_{0.98}K_{0.02}S e-6\\%C d S e}$ , with a promising average $Z T_{\\mathrm{ave}}$ of $\\sim0.83$ at 400–923 K, which is the highest reported to date in a p-type, Te-free PbSe system. \n\n# Results and discussion \n\n# Phases and optical properties \n\nThe powder X-ray diffraction (PXRD) patterns of PbSe–xCdSe and $\\mathbf{Pb_{0.98}K_{0.02}S e}–x\\mathbf{C}\\mathbf{d}S\\mathbf{e}$ $(x=0{-}10\\%$ samples indicate that all peaks can be indexed to the rock-salt PbSe phase (space group: $F m\\bar{3}m$ , ICSD# 38294) with a slight shift to higher angle with increasing Cd concentration, see Fig S1(a) and (b) $\\bigl(\\mathrm{ESI\\dag}\\bigr)$ . No second phases are observable within the detection limit of PXRD. Since the $d$ -spacings of CdSe-ZB (CdSe-ZB, space group: $F\\bar{4}3m$ , ICSD# 41528) and PbSe are extremely close, it is hard to conclude whether the shift of peaks comes from a second phase or lattice contraction after Cd substitution of Pb. \n\nThe band gap of the materials increases from $\\sim0.24\\ \\mathrm{eV}$ for pure PbSe to $\\sim0.41$ eV for PbSe–8%CdSe as determined by infrared absorption measurements, Fig. 1(a) and (b). The band gap of the PbSe– ${\\cdot10\\%}$ CdSe sample is slightly lower than that of the PbSe– $8\\%$ CdSe sample, and the raw spectrum exhibits a noticeably different shape compared with the other samples, indicating that Cd might have reached its solubility limit in PbSe and created a second phase. The details of the CdSe solubility within PbSe will be discussed later. \n\nTo understand how Cd alloying modifies the electronic band edge positions of PbSe, we performed photoemission yield spectroscopy in air (PYSA) at room temperature. This technique determines the work functions of undoped PbSe–xCdSe and doped $\\mathbf{Pb}_{0.98}\\mathbf{K}_{0.02}\\mathbf{S}\\mathrm{e}$ –xCdSe samples (for the spectra see Fig. S2, $\\mathrm{ESI\\dag}\\$ ). The work function can be estimated by fitting the linear region of the spectra (see the ESI†). For undoped PbSe–xCdSe, with low carrier concentration, the work function essentially reflects the top of the L-valence band position versus a vacuum. Therefore, adding the measured band gap values to it gives the conduction band position, see Fig. 1(c). These results clearly indicate that the band gap widening is attributed to both the valence band edge moving deeper in energy (from ${\\bf5.03\\ e V}$ for pure PbSe to $5.10\\ \\mathrm{eV}$ for PbSe– $8\\%$ CdSe) and the conduction band moving higher in energy (from $4.78\\ \\mathrm{eV}$ for pure PbSe to $4.70\\ \\mathrm{~eV}$ for $\\mathrm{PbSe-}8\\%\\mathrm{CdSe})$ . The work functions of several potassium-doped samples show a slight increase in energy, indicating that the top of the L-valence band moves slightly lower. Assuming that the $\\Sigma$ -valence band position remains unchanged (supported by DFT calculations shown in Fig. 5(c)), we can then estimate the energy offset between the $\\mathbf{L}\\mathbf{-}$ and $\\Sigma$ -bands $(\\Delta E_{\\mathrm{L-}\\Sigma})$ in different samples based on the fact that $\\Delta E_{\\mathrm{L-}\\Sigma}$ of pure PbSe is $\\sim0.25$ eV.25 $\\Delta E_{\\mathrm{L}-\\Sigma}$ decreases from 0.25 to $0.19\\ \\mathrm{{\\eV}}$ as seen in Fig. 1(d). This value approaches the $0.15~\\mathrm{eV}~\\Delta E_{\\mathrm{L}-\\Sigma}$ value of PbTe. \n\n![](images/5f5300b307e9b5cd9376d8345b6cb4ac04359efc699b253bd271cfecbfcd2157.jpg) \nFig. 1 (a) Infrared absorption spectra for PbSe–xCdSe samples after SPS (spark plasma sintering). (b) Estimated electronic band gaps $E_{\\mathfrak{g}}$ . An increase of $E_{\\mathfrak{g}}$ can be observed from $\\sim0.24\\ \\mathrm{eV}$ for pure PbSe to $\\sim0.41$ eV for PbSe– $8\\%C\\mathsf{d}S\\mathsf{e}.$ , followed by a slight decrease in $\\mathsf{P b S e-10\\%C d S e}$ . (c) Energies of conduction band (CB) and valence band (VB) edges (work functions) for PbSe–xCdSe samples, shown in black and red squares, respectively. Three valence band edges for potassium-doped samples are shown in blue triangles. (d) Experimentally estimated energy differences between L- and $\\Sigma$ -valence bands, the error bars in these values are $\\pm0.01$ eV. \n\n# Discordant Cd atoms in PbSe probed with DFT calculations and solid-state NMR \n\nIt is known that the vast majority of Cd chalcogenide compounds including CdSe in the wurtzite and zinc blende crystal structure have Cd atoms in tetrahedral sites surrounded by Se atoms.52,53 Therefore, substituting Pb with Cd in PbSe will lead to an uncommon and destabilizing octahedral environment for Cd. Intuitively, Cd might tend to shift its lattice position from the center of the octahedral site to lower its energy. Density functional theory (DFT) calculations indicate that when the Cd atoms shift away from the lattice-imposed octahedral center, the overall energy of the system does decrease. The results suggest that a shift of $\\sim0.01\\mathring\\mathbf{A}$ away from the octahedral center along the [111] direction brings the system to the minimum total energy, Fig. 2(a) and (b). In addition, the existence of negative frequencies in the DFT-calculated phonon dispersion curves when placing Cd at the center of the PbSe lattice (Fig. 7(b)) also indicates instability of the on-centered Cd atoms and a tendency for off-center displacement. This aspect will be discussed in more detail later. \n\nWe employed solid-state NMR spectroscopy as a powerful tool to probe the local structural environment of $^{77}\\mathrm{Se}$ as well as 111Cd.30,52,54,55 We used the Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence to acquire $^{77}\\mathrm{Se}\\ \\mathrm{NMR}$ , in order to enhance the spectral sensitivity as well as to achieve broad band excitation. The static $^{77}\\mathrm{Se}$ CPMG NMR spectra together with the corresponding simulations of CdSe, PbSe, PbSe–3%CdSe and PbSe– $10\\%$ CdSe phases are shown in Fig. 2(c). The 77Se NMR spectrum of wurtzite CdSe shows only one component with an isotropic shift of $-470~\\mathrm{ppm}$ and a small shift anisotropy of $35~\\mathrm{ppm}$ . The $^{77}\\mathrm{Se}$ NMR spectrum of PbSe exhibits a resonance at $-635~\\mathrm{ppm}$ with a shift anisotropy of 37 ppm. The relatively small $^{77}\\mathrm{Se}$ NMR shift anisotropies of both CdSe and PbSe are due to their high coordination symmetry. Once a small amount of Cd is alloyed into PbSe, line broadening with changes in the $^{77}\\mathrm{Se}$ shift are observed. A more complex $^{77}\\mathrm{Se}$ NMR spectrum with 3 components is obtained for PbSe–3%CdSe. The chemical shift differences among these three components reflect the different electronic environments. The major component resonating at $-632~\\mathrm{ppm}$ is assigned to PbSe with a slightly increased shift anisotropy from $37~\\mathrm{ppm}$ to $48~\\mathrm{ppm}$ , indicating a more disordered Se structural environment than in pure PbSe. The two minor broad resonances are likely from Se directly coordinated to Cd at an off-center position. Specifically, one resonance at $-560\\mathrm{ppm}$ is assigned to Se atoms closer to the adjacent discordant Cd atoms. The other minor resonance at $-720~\\mathrm{ppm}$ reflects Se atoms lying farther apart from Cd atoms. As the Cd fraction increases from $3\\%$ to $10\\%$ , the above-mentioned resonances continue to be observed but the off-center components become stronger. As seen in Table S1 $\\left(\\mathrm{ESI}\\dag\\right)$ , the shift anisotropy parameter used in the simulation significantly increases for all three sites. An additional broad $^{77}\\mathrm{Se}$ resonance, however, is observed at $-275~\\mathrm{ppm}$ with a shift anisotropy of $140~\\mathrm{ppm}$ for the PbSe– $10\\%$ CdSe sample, which is assigned to wurtzite CdSe and zinc blende CdSe occurring as second phases. \n\n![](images/d1e22bfada67b334306129d021bda982f3e7bce01ce5290d187633340ac785aa.jpg) \nFig. 2 (a) System energy change with respect to the Cd off-centering distance from the octahedral site center along the [111] crystallographic direction. A local minimum is reached when the displacement is $\\sim0.01\\mathring{\\mathsf{A}}$ The energy profile shown as a solid line from a regular octahedral site to a local minimum off-centered site is calculated by the Nudged Elastic Band method,56 while the dashed line away from the off-center position is evaluated by static DFT calculations. (b) Local atomic structure of off-centered Cd in PbSe. (c) $^{77}\\mathsf{S e}\\mathsf{C P M G}$ static NMR spectra and the corresponding simulations of CdSe-WZ, PbSe, $\\mathsf{P b S e-3\\%C d S e}$ and $\\mathsf{P b S e-10\\%C d S e}$ . (d) $^{111}{\\mathsf{C d}}$ NMR spectra and the corresponding simulations of CdSe, PbSe– $-3\\%$ CdSe, and $\\mathsf{P b S e-10\\%C d S e}$ . The NMR parameters used for the simulation are listed in Tables S1 and S2 (ESI†). \n\nMore direct Cd structural information can be extracted from the $^{111}{\\bf C d}$ NMR spectra of CdSe, PbSe– ${\\cdot}3\\%$ CdSe, and PbSe– $10\\%\\mathrm{CdSe}$ , as shown in Fig. 2(d). The $^{111}{\\mathrm{Cd}}$ NMR spectrum of the CdSe sample shows a resonance at $-230$ ppm with a shift anisotropy of $310\\mathrm{\\ppm}$ . As $\\mathbf{\\mathrm{Pb}}$ is replaced by Cd in PbSe– $3\\%{\\mathrm{CdSe}}$ , one broad resonance is observed with a shift anisotropy of $390\\ \\mathrm{\\ppm}$ , implying the solid-solution state formed after Cd alloying. With a further increase of the Cd content $\\mathrm{(PbSe-10\\%CdSe)}$ , the shift anisotropy significantly increases from $390~\\mathrm{ppm}$ to $480~\\mathrm{ppm}$ , indicating a more asymmetric Cd local environment. In addition, a minor broad component appears resonating at $-220~\\mathrm{ppm}$ because of second phase formation of extra CdSe, which agrees with the $^{77}\\mathrm{Se}$ NMR results presented above and the TEM results to be discussed later. Therefore, it can be concluded that Cd atoms in PbSe are off-centered from exactly in the octahedral site. \n\n# Novel nanostructuring in PbSe–xCdSe materials \n\n(1) Tetrahedral nano-precipitates in PbSe–xCdSe with core– shell architecture. According to the existing phase diagram57 as well as the trend of the band gap change, we expect Cd to exceed the solubility limit at some concentration. Therefore, we performed advanced electron microscopy studies on the un-doped PbSe–xCdSe samples. Fig. 3(a) displays a typical high-angle annular dark field STEM (HAADF-STEM) image of the PbSe–10%CdSe sample, highlighting mainly the mass contrast in the specimen. Interestingly, numerous faceted precipitates can be observed within each grain of the PbSe matrix. Along the 2-D projection of the electron beam, the precipitates appear as triangles with a size range of 50 to $200\\ \\mathrm{nm}$ . The contrast variation verifies that the precipitates are tetrahedra in 3-D. All the edges of the precipitates in one grain are parallel to each other, indicating a preferred growth plane as well as coherency between the two phases. According to the chemical mappings performed with energy dispersive spectroscopy (EDS), the second phases are rich in Cd and severely deficient in Pb, whereas Se is uniformly distributed across both phases, Fig. 3(b). \n\n![](images/034f4a907ca1abededec21955e569c2b7ca637b06f966769fa0e45518930994e.jpg) \nFig. 3 Scanning/transmission electron microscopy (S/TEM) analyses of PbSe–10%CdSe. (a) High-angle annular dark field image. A large amount of triangular nano-precipitates is embedded within the grains of the matrix. (b) EDS mapping of a selected area in (a). (c) Typical TEM image of a precipitate sitting in the matrix. The diffraction contrast highlights three different regions: the matrix, the main body of the precipitate and $\\sim20$ nm thick layers as shells between the interfaces. (d) Selected area diffraction pattern (SAED) taken along the [110] zone axis of the matrix, revealing that the interface is the wurtzite CdSe phase. (e) High-resolution STEM image (HRSTEM) with a HAADF mode image of one edge of the precipitate and the matrix. The atomic stacking of the matrix, the matrix–shell interface, the shell, and the core of the precipitate is highlighted in $(\\mathsf{f})-(\\mathsf{i})$ , respectively. \n\nFig. 3(c) is a low magnification bright field TEM image with one precipitate situated in the matrix. Clearly, the diffraction contrast in the image divides the specimen into three regions, namely the matrix, the main body of the precipitate and two $\\sim20\\ \\mathrm{nm}$ thick bands sandwiched between the interfaces. The selected area diffraction pattern (SAED) including all three regions in Fig. 3(c) is shown in Fig. 3(d). The main brightest spots belong to rock-salt PbSe (space group: $F m\\bar{3}m$ , ICSD# 38294) \n\nand zinc blende CdSe phases (CdSe-ZB, space group: $F\\bar{4}3m$ , ICSD# 41528) along the [110] zone axis. Since the difference in lattice parameter between these two phases is very small $(a=$ $6.128\\mathring{\\mathrm{~A~}}$ for PbSe and $a=6.077\\mathring{\\mathrm{~A~}}$ for CdSe-ZB), diffraction spot splitting can only be seen far away from the transmission beam. It should be noted that under our synthesis methods, the main CdSe second phase precipitated out from the PbSe matrix is the zinc blende structure, while the thermodynamically stable phase for CdSe is actually wurtzite.53 The streaking and the two sets of extra spots observed along the $\\{111\\}$ planes of the matrix belong to the hexagonal wurtzite CdSe phase (CdSe-WZ, space group: $P6_{3}m c$ , ICSD# 415784) along the [100] zone axis. The series of dark field images in Fig. S3 $\\bigl(\\mathrm{ESI\\dag}\\bigr)$ further reveal that the wurtzite CdSe diffraction spots come exclusively from the two bands in the interface between the PbSe and the CdSe phase. \n\nTo visualize the atomic arrangement as well as additional details in the interface region, we employed aberration corrected (probe) high-resolution STEM imaging. Fig. 3(e) is a typical HAADF image taken along the [110] zone axis of the matrix, revealing endotaxial precipitation. From the zoom-in versions shown in Fig. 3(f)–(i), the differences in atom stacking can be easily seen. Atoms in the PbSe solid solution region and the core of the CdSe precipitate (zinc blende CdSe) exhibit ABC/ABC stacking but turn into AB/AB in the hexagonal wurtzite phase at the shell (wurtzite CdSe). Moreover, several stacking faults can be observed within the shell because of the small energy cost for stacking fault formation.58 \n\nWe performed similar studies on the PbSe–8%CdSe and PbSe– $6\\%$ CdSe samples. In particular, precipitates with the exact same shape but smaller size $(\\sim20\\ \\mathrm{nm})$ are observed in the $8\\%$ CdSe sample, see Fig S4(a) and (b) $\\left(\\mathrm{ESI\\dag}\\right)$ . The shell at the interface here is around $\\sim7\\ –8$ atomic layers. For the PbSe– $6\\%C\\mathrm{d}\\mathrm{se}$ sample, as shown in Fig. S5 $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ of a triple junction of three grains, the elements distribute homogeneously both inside the grain and along the grain boundaries. The highresolution TEM image and the SAED diffraction pattern further confirm the formation of the PbSe–CdSe solid solution. Taken together, the solubility of CdSe in un-doped PbSe is above $6\\%$ under such synthesis and processing methods. Above the solubility limit, endotaxial tetrahedral precipitates with core– shell architecture can be observed, whose size increases from $\\sim20\\ \\mathrm{nm}$ to $\\sim200\\ \\mathrm{nm}$ when the CdSe concentration changes from $8\\%$ to $10\\%$ . \n\n(2) Effect of potassium doping on the nanostructures of PbSe–xCdSe. After elucidating the role of Cd alloyed in the undoped PbSe matrix, we proceeded to optimize the thermoelectric properties using potassium doping. Adding extra elements such as potassium into the PbSe lattice, however, could change the underlying thermodynamics/kinetics of the ternary PbSe–xCdSe system, leading to changes in the nanostructure. Therefore, we performed more TEM analyses on the potassium doped samples and we observed a decrease in CdSe solubility as well as a different nucleation–growth behavior. \n\nFig. 4(a) is a typical dark field TEM image of $\\mathbf{Pb_{0.98}K_{0.02}S e-}$ $6\\%$ CdSe, highlighting a significant number of very small $(\\sim5\\mathrm{{nm})}$ precipitates embedded in the matrix. The SAED pattern inset confirms its rock-salt PbSe phase, and the image is taken along the [110] zone axis. Although no extra spots can be detected, there is significant diffuse diffraction, indicating a high degree of strain in the sample. Moreover, according to the highresolution TEM image in Fig. 4(b), these precipitates also exhibit the same tetrahedral shape as the ones described above, but with no wurtzite shell being present at the interface. The absence of the wurtzite shell in this sample may be due to the smaller size of the precipitates (caused by the presence of K, indirect influence), or the direct influence of K. In addition, we observe obvious microstructural differences between this work and previously reported PbSe–Cd systems.21,32,51 These differences may originate from the different dopants used in the samples as well as possible artifacts from ion-beam damage during TEM sample preparation in some previous studies.59 \n\n![](images/1163dcaba3d8a4d0ea0b4139f859570f7243817d26d458f63b02d63eb66e016f.jpg) \nFig. 4 (a) Bright field TEM image of $\\mathsf{P b}_{0.98}\\mathsf{K}_{0.02}\\mathsf{S e}-6\\%C\\mathsf{d}\\mathsf{S e}$ taken along the [110] zone axis. A large amount of triangular precipitates of $\\sim5\\mathsf{n m}$ in size can be observed. The inset is the selected diffraction pattern. (b) Highresolution TEM image of a selected area in (a), revealing the coherent interface between the zinc blende CdSe second phase and the PbSe matrix. \n\nWith increasing CdSe amount in the samples, micron-scale CdSe second phases with irregular shapes appear, as shown in the STEM image for $\\mathrm{Pb_{0.98}K_{0.02}S e}–8\\%C\\mathrm{d}S\\mathrm{e}$ in Fig. S7 $\\bigl(\\mathrm{ESI\\dag}\\bigr)$ . Given the shape of the second phase and the elemental distribution, its formation may be via a different mechanism. For example, the added potassium could shift the eutectic point of the PbSe–CdSe system to lower temperature, which would cause the CdSe second phase to nucleate already from the liquid phase when its concentration is high. \n\n# Boosting thermoelectric performance via K doping \n\nAlthough typically Na is the standard p-type dopant used in lead chalcogenides, K doping is much less investigated and in previous work it has been shown to be an effective dopant.60–62 We therefore decided to use it in this work for the first time in a PbSe–CdSe based system. Fig. 5(a) and (b) show the temperaturedependent $\\left(300\\ \\mathrm{K}{-}923\\ \\mathrm{K}\\right)$ electronic properties of $\\mathbf{Pb_{0.98}K_{0.02}S e-}$ xCdSe $(x=0{-}10\\%)$ . All samples behave as degenerate semiconductors, where the electrical conductivities (Fig. 5(a)) decrease at elevated temperatures because of electron–phonon scattering. A noticeable deviation from the normal $\\sigma\\sim1/T$ relationship is observed in the low temperature range (300–500 K) and it is attributed to grain boundary scattering,63 which is diminished in the high temperature region where the thermoelectric properties are most interesting. At room temperature, $\\sigma$ significantly decreases with rising Cd concentration typically from $\\sim3100~\\mathrm{~S~}\\mathrm{cm}^{-1}$ in $\\mathbf{Pb_{0.98}K_{0.02}S e}$ to $\\sim950~\\mathrm{S~cm}^{-1}$ in $\\mathrm{Pb_{0.98}K_{0.02}S e-6\\%C d S e}$ . \n\n![](images/0c7fd371b667c9e27ab68e7165f765c78381594205acd6e241e483761f53207c.jpg) \nFig. 5 (a) and (b) Temperature-dependent electrical conductivity and Seebeck coefficients for $\\mathsf{P b}_{0.98}\\mathsf{K}_{0.02}\\mathsf{S e}-x\\mathsf{C d}\\mathsf{S}\\epsilon$ $(x=0-10\\%)$ . (c) DFT calculated band structures for the $\\mathsf{P b}_{27-n}\\mathsf{C d}_{n}\\mathsf{S e}_{27}$ supercell, where $n=0$ , 1, 2. \n\nThe Seebeck coefficients are positive, indicating that they are p-type semiconductors with holes as the dominant carriers, Fig. 5(b). Specifically, the Seebeck coefficient gradually increases with increasing CdSe amount up to $6\\%$ . The highest coefficient of $\\sim290\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ is obtained in $\\mathrm{Pb}_{0.98}\\mathrm{K}_{0.02}\\mathrm{Se}-6\\%\\mathrm{CdS}\\epsilon$ e at $923\\mathrm{~K~}$ . \n\nTo better understand the nature of the electronic structure and the enhanced Seebeck coefficient, we performed DFT calculations on both PbSe–CdSe and pure PbSe, Fig. 5(c). Compared to pure PbSe, two important changes can be seen after adding Cd into the matrix: first, a lower energy offset between the L and $\\Sigma$ bands (from 0.27 to $0.15\\mathrm{eV}$ , band convergence) induces a larger band gap (the energy offset between the conduction band and L band, $\\Delta E_{\\mathrm{c-L}}\\mathrm{\\stackrel{.}{}}$ ). This result has been confirmed experimentally by the optical band gap and work function measurements discussed above. Second, adding Cd leads to noticeable flattening of the L band. The flattened band results in an increased effective mass relative to PbSe (from 0.27 to $0.65m_{\\mathrm{e.}}^{\\cdot}$ ), as shown in Table S3 $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ . Indeed, such an increase in $m^{*}$ is experimentally supported by the room temperature Hall measurements, see Table S4 $\\bigl(\\mathrm{ESI}\\dag\\bigr)$ . Based on the Pisarenko relation and assuming a single parabolic band contributing to carrier conduction, we calculated the room temperature effective masses for the samples. In agreement with the simulations, the Cd containing sample exhibits a dramatic increase in effective mass. Specifically, the effective mass of $\\mathbf{Pb_{0.98}K_{0.02}S e}$ is $\\sim0.31m_{\\mathrm{e}}$ , consistent with the value reported in other pure PbSe samples elsewhere.51 However, the effective mass of the sample with $6\\%\\mathrm{CdSe}$ is estimated as $3\\times$ higher, reaching $\\sim1m_{\\mathrm{e}}$ . Both the band convergence and band flattening are therefore beneficial for enhancing the Seebeck coefficient. Combining the Seebeck coefficient with the electrical conductivity results, a high power factor of ${\\sim}14\\upmu\\mathrm{W}\\mathrm{cm}\\mathrm{K}^{-1}$ is obtained at $723\\mathrm{~K~}$ for $\\mathrm{Pb_{0.98}K_{0.02}S e-2\\%C d S e}$ (Fig. S8, $\\mathrm{ESI\\dag}$ ). \n\nTo decouple the effect of K doping and Cd alloying on the thermal transport behavior, we studied the temperaturedependent thermal properties of doped and un-doped PbSe– xCdSe. Fig. 6(a) shows the temperature-dependent total thermal conductivity data for the undoped PbSe–xCdSe $(x\\:=\\:0{-}10\\%)$ 1 sample. Since no significant electron/hole carriers are present, all samples behaved as non-degenerate semiconductors with decreasing thermal conductivity as the temperature increases and apparent bipolar diffusion occurred above $600\\mathrm{K}$ . Therefore, the total thermal conductivities reflect the lattice phonon conductivity with negligible contribution from the electronic part. Notably, the bipolar diffusion in all Cd-alloyed samples is clearly suppressed compared to pure PbSe because of the widening of the electronic band gap. Moreover, $\\kappa_{\\mathrm{tot}}$ of the samples gradually decreases up to $8\\%C d\\mathrm{{Se}}$ , followed by a slight increase for the PbSe– $.10\\%$ CdSe sample. Specifically, compared with pure PbSe having $\\kappa_{\\mathrm{tot}}\\sim1.8~\\mathrm{{Wm^{-1}}~K^{-1}}$ at room temperature, $\\kappa_{\\mathrm{tot}}$ of the $3\\%$ $\\left(\\sim1.5\\mathrm{Wm}^{-1}\\mathrm{K}^{-1}\\right)$ , $6\\%$ $\\%\\left(\\sim1.3\\mathrm{Wm}^{-1}\\mathrm{K}^{-1}\\right)$ and $8\\%\\left({\\sim}1.1\\mathrm{Wm}^{-1}\\mathrm{K}^{-1}\\right)$ samples has dropped $\\sim16\\%$ , $\\sim25\\%$ and $40\\%$ , respectively. \n\nIn comparison, the temperature-dependent thermal transport properties for the samples of $\\mathrm{Pb}_{0.98}\\mathrm{K}_{0.02}\\mathrm{Se}-x\\mathrm{Cd}\\mathrm{St}$ $(x=0{-}10\\%)$ are shown in Fig. 6(b). Generally, the total thermal conductivity of the samples significantly decreases as the CdSe fraction increases. Typically, the $\\kappa_{\\mathrm{tot}}$ of $\\sim3.8~\\mathrm{Wm}^{-1}~\\mathrm{K}^{-1}$ drops to $\\sim2.0~\\mathrm{Wm}^{-1}~\\mathrm{K}^{-1}$ for $\\mathrm{Pb_{0.98}K_{0.02}S e-6\\%C d S e}.$ , and to ${\\sim}1.8~\\mathrm{Wm}^{-1}~\\mathrm{K}^{-1}$ for $\\mathrm{Pb}_{0.98}\\mathrm{K}_{0.02}\\mathrm{Se}-10\\%\\mathrm{Cd}$ Se. The lowest total thermal conductivity of $\\sim0.8~\\mathrm{Wm}^{-1}~\\mathrm{K}^{-1}$ is obtained in the $6\\%C\\mathrm{d}\\mathrm{se}$ sample at $923\\mathrm{~K~}$ with a corresponding lattice thermal conductivity of $\\sim0.6~\\mathrm{Wm}^{-1}~\\mathrm{K}^{-1}$ . \n\nTo explore the primary physical reasons for Cd inducing the significant lattice thermal conductivity reductions observed, we performed DFT-based phonon calculations using a structure model with discordant Cd atoms in PbSe. In this model the calculated phonon dispersions indicate a much lower vibration frequency for the acoustic branches compared to pure PbSe, resulting in a lower longitudinal Debye temperature, Fig. 7(a). Moreover, the average phonon velocity of the Cd-alloyed PbSe structure is about $2300\\mathrm{~m~s^{-1}}$ , much lower than the $2614~\\mathrm{m}~\\mathrm{s}^{-1}$ for pure PbSe. In addition, compared to the pure PbSe, the relatively strong attraction of the off-centered Cd with its nearest Se atoms induces longer bonds between the next nearest neighbor Pb (Pb NN) and Se. Because the calculations indicate that the Pb and Cd atoms contribute the most to the acoustic phonon transport (frequency $<40\\mathrm{cm}^{-1}$ ) with a negligible role played by Se, only changes in Pb will be considered here. \n\n![](images/e02d6757b9c76b478f15fb04e040c4d213a90bef06c562fbe871d422cea39395.jpg) \nFig. 6 Temperature-dependent (a) total thermal conductivity of PbSe– $x C{\\mathsf{d}}{\\mathsf{S e}}$ $(x=0-10\\%)$ and (b) and (c) total thermal conductivity and lattice thermal conductivity of $\\mathsf{P b}_{0.98}\\mathsf{K}_{0.02}\\mathsf{S e}-x\\mathsf{C d}\\mathsf{S e}$ $(x\\:=\\:0\\mathrm{-}10\\%)$ , respectively. The lattice thermal conductivity of these samples was determined by subtracting the electronic part from $\\kappa_{\\mathrm{tot}},$ namely $\\kappa_{\\mathsf{l a t t}}=\\kappa_{\\mathsf{t o t}}-\\kappa_{\\mathsf{e l e}}$ , where $\\kappa_{\\mathrm{ele}}$ is calculated based on the Wiedemann–Franz law $\\kappa_{\\mathrm{ele}}=L\\sigma T,$ with $\\boldsymbol{L}$ the Lorenz number.64 \n\n![](images/1daab8f68b1b58616c7d1e7e4d92e0bf8bd8389e4a63309cf9a5acbecb7f9678.jpg) \nFig. 7 (a) Phonon dispersion curves (on the $\\mathsf{P b}_{26}\\mathsf{C d S e}_{27}$ supercell) with acoustic branches highlighted with different colors. (b) Phonon dispersion curves of PbSe with Cd sitting on the center of the octahedral site (on-center). Significant imaginary frequencies exist, indicating instability of such a structure. (c) Corresponding projected density of states (DOS) of PbSe with off-centered Cd in the matrix (off-center). The density of states from next nearest neighbor Pb atoms (Pb NN, red line) is shifted to the low frequency regime compared with the ones lying farther away from Cd atoms (Pb far, blue line). (d) DFT-calculated lattice thermal conductivity of off-centered PbSe–CdSe with different concentrations of Cd. \n\nThe discordant Cd atom creates a strong local strain field affecting not only its own coordination environment but also the next nearest neighbor Pb atoms, as shown with the red line in Fig. 7(c). These low frequency vibrations are even lower than those of other Pb atoms lying farther (Pb far) from the Cd atoms, which are shown with the blue line. As a result, the discordant Cd and the induced distorted local Pb environments synergistically contribute to lowering the lattice thermal conductivities. This is illustrated by the DFT-calculated lattice thermal conductivity of the off-centered structure in Fig. 7(d). As a comparison, the phonon dispersion curves of PbSe with Cd sitting on the center of the octahedral site (on-center) were calculated, see Fig. 7(b). It is known that the acoustic modes are considered for lattice thermal conductivity calculations in the Debye–Callaway methods, where accurate Gr¨uneisen parameters, phonon velocities and Debye temperatures are necessary. However, for a phonon dispersion with significant imaginary frequencies indicating instability of such an on-center structure, the above parameters are not correct and hence the lattice thermal conductivity cannot be evaluated. \n\nCollectively, in the solid solution samples with $<6\\%{\\mathrm{Cd}}$ , we attribute the significant decrease of the thermal conductivity to the discordant Cd atom nature and the corresponding local distorted $\\mathbf{Pb}$ atomic environment. Above the solubility limit, a further decrease of $\\kappa_{\\mathrm{latt}}$ comes from the faceted nanoprecipitates in the range $5\\mathrm{-}50\\ \\mathrm{nm}$ . Any differences observed between the doped and un-doped samples mainly originate from solubility and microstructure changes. \n\n![](images/848fb41f98f32b4636fa8df7ea72e6687fa61211bc4072203fba0a3623697d77.jpg) \nFig. 8 (a) Temperature-dependent $Z T$ of $\\mathsf{P b}_{0.98}\\mathsf{K}_{0.02}\\mathsf{S e}-x\\mathsf{C d}\\mathsf{S e}$ $(x=0\\mathrm{-}10\\%)$ samples. (b) Comparison of average $Z T$ $(Z T_{\\mathsf{a v e})}$ from $400{-}923\\ \\mathsf{K}$ among state-of-the-art p-type, Te-free PbSe systems.30,51,65 \n\nCombining the improved electronic and thermal properties presented above, a remarkable gain in the overall thermoelectric performance is obtained, as shown in the temperaturedependent $Z T$ of $\\mathrm{Pb}_{0.98}\\mathrm{K}_{0.02}\\mathrm{Se}-x\\mathrm{CdSe}$ $(x=0{-}10\\%$ ). Specifically, a $Z T$ of $\\sim1.4$ at $923\\mathrm{~K~}$ is achieved for the $6\\%$ CdSe sample, higher than all other concentrations owing to the appearance of nanoprecipitates that diminish the thermal transport. Because of the band flattening effects, the Seebeck coefficient and ZT from $300{-}500~\\mathrm{K}$ are higher than previous studies on PbSe. This leads to a high average $Z T_{\\mathrm{ave}}$ of $\\sim0.83$ (400–923 K), the highest reported value in p-type, Te-free PbSe-based systems.30,51,65 This is a significant figure of merit because it is slightly lower or even comparable to most PbTe-based materials and relevant to obtaining high conversion efficiency in devices (Fig. 8).44,47,66,67 \n\n# Concluding remarks \n\nThe insertion of Cd in octahedral Pb sites in the rock-salt structure of PbSe causes strong local distortion in the coordination environment of Cd because of its preferred tetrahedral binding. The Cd atoms are discordant with the Pb sites in the rock-salt lattice and prefer the off-centered position close to $\\sim0.01\\mathring\\mathbf{A}$ away from the normal octahedral center based on solid state NMR spectroscopy and DFT calculations. The induced distorted local Pb environments contribute to lower lattice thermal conductivities. The Cd alloying also leads to bandgap enlargement, $_{\\mathrm{L-}\\sum}$ band convergence and L band flattening, enhancing the Seebeck coefficient. Above the solubility limit of $6\\%$ , CdSe nucleates and grows in the PbSe matrix as a second phase. The tetrahedral nano-precipitates show a core–shell morphology with a zinc blende structure inside and wurtzite outside along the phase boundary. This is a novel three-phase nanostructure and further contributes to depressed thermal transport when the precipitate size is around $20{-}50~\\mathrm{nm}$ in PbSe–8%CdSe. After adding potassium as a p-type dopant, the solubility of CdSe is decreased to below $6\\%$ . In $\\mathrm{Pb_{0.98}K_{0.02}S e-6\\%C d S e}$ , the zinc blende tetrahedral precipitates are $\\sim5\\ \\mathrm{nm}$ and lack the wurtzite layer. Such small nano-precipitates with significant local strain lead to an additional reduction in lattice thermal conductivity to a very low value of $\\sim0.6\\mathrm{Wm}^{-1}\\mathrm{K}^{-1}$ at $923\\mathrm{~K~}$ . Combined with the enhanced electronic properties, a high $Z T$ of $\\sim1.4$ is realized in $\\mathrm{Pb}_{0.98}\\mathrm{K}_{0.02}\\mathrm{Se}-6\\%\\mathrm{Cd}\\mathrm{\\Omega}$ Se with $Z T_{\\mathrm{ave}}\\sim0.83$ . The $Z T_{\\mathrm{ave}}$ is the highest achieved in p-type, Te free PbSe systems and could enable the fabrication of high efficiency PbSe-based devices.4 \n\n# Author contributions \n\nS. C. designed and carried out the thermoelectric experiments. S. C., Z.-Z. L. and M. G. K analyzed the electrical and thermal transport data. Z.-Z. L. helped with synthesis. S. H. and C. W. carried out the first principles band structure and phonon dispersion calculations. X. L. and Y.-Y. H. carried out the solid-state NMR experiment and analyzed the NMR data. S. C., X. H. and V. P. D. carried out the TEM experiment and analyzed the TEM results. S. C. and I. H. carried out the photoemission spectroscopy experiment and analyses. Z.-Z. L., T. P. B. and C. U. carried out the Hall measurements. \n\n# Conflicts of interest \n\nThere are no conflicts to declare. \n\n# Acknowledgements \n\nThis work was primarily supported by the Department of Energy, Office of Science, Basic Energy Sciences under grant DE-SC0014520. This work made use of the EPIC facility of Northwestern University’s NUANCE Center, which has received support from the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF ECCS-1542205); the MRSEC program (NSF DMR-1720139) at the Materials Research Center; the International Institute for Nanotechnology (IIN); the Keck Foundation; and the State of Illinois, through the IIN. User Facilities are supported by the Office of Science of the \n\nU.S. Department of Energy under Contract No. DE-AC02-06CH11357 and DE-AC02-05CH11231. Access to facilities of high performance computational resources at Northwestern University is acknowledged. PYSA measurements were carried out with equipment acquired by ONR grant N00014-18-1-2102. Y.-Y. Hu and X. Li acknowledge the support from the National Science Foundation (DMR-1847038). The solid-state NMR experiments were carried out at the NHMFL, which is supported by the National Science Foundation Cooperative Agreement (DMR-1644779) and the State of Florida. The research of T. P. B. and C. U. is supported by a grant from the U.S. Department of Energy under Award number DE-SC0018941. \n\n# References \n\n1 G. Tan, L.-D. Zhao and M. G. Kanatzidis, Rationally Designing High-Performance Bulk Thermoelectric Materials, Chem. Rev., 2016, 116(19), 12123–12149, DOI: 10.1021/acs.chemrev.6b00255. \n2 W. G. Zeier, A. Zevalkink, Z. M. Gibbs, G. Hautier, M. G. Kanatzidis and G. J. Snyder, Thinking Like a Chemist: Intuition in Thermoelectric Materials, Angew. Chem., Int. Ed., 2016, 55(24), 6826–6841, DOI: 10.1002/anie.201508381. \n3 X. Zhang and L.-D. Zhao, Thermoelectric Materials: Energy Conversion between Heat and Electricity, J. Materiomics, 2015, 1(2), 92–105, DOI: 10.1016/j.jmat.2015.01.001. \n4 G. Tan, M. Ohta and M. G. Kanatzidis, Thermoelectric Power Generation: From New Materials to Devices, Philos. Trans. R. Soc., A, 2019, 377(2152), 20180450, DOI: 10.1098/ rsta.2018.0450. \n5 P. Jood, M. Ohta, A. Yamamoto and M. G. Kanatzidis, Excessively Doped PbTe with Ge-Induced Nanostructures Enables High-Efficiency Thermoelectric Modules, Joule, 2018, 2(7), 1339–1355, DOI: 10.1016/j.joule.2018.04.025. \n6 X. Hu, P. Jood, M. Ohta, M. Kunii, K. Nagase, H. Nishiate, M. G. Kanatzidis and A. Yamamoto, Power Generation from Nanostructured PbTe-Based Thermoelectrics: Comprehensive Development from Materials to Modules, Energy Environ. Sci., 2016, 9(2), 517–529, DOI: 10.1039/C5EE02979A. \n7 J. He, M. G. Kanatzidis and V. P. Dravid, High Performance Bulk Thermoelectrics via a Panoscopic Approach, Mater. Today, 2013, 16(5), 166–176, DOI: 10.1016/j.mattod.2013.05.004. \n8 G. J. Snyder and E. S. Toberer, Complex Thermoelectric Materials, Nat. Mater., 2008, 7(2), 105–114, DOI: 10.1038/ nmat2090. \n9 A. Mehdizadeh Dehkordi, M. Zebarjadi, J. He and T. M. Tritt, Thermoelectric Power Factor: Enhancement Mechanisms and Strategies for Higher Performance Thermoelectric Materials, Mater. Sci. Eng., R, 2015, 97, 1–22, DOI: 10.1016/ j.mser.2015.08.001. \n10 H. Mamur, M. R. A. Bhuiyan, F. Korkmaz and M. Nil, A Review on Bismuth Telluride $\\left({\\bf B i}_{2}{\\mathrm{Te}}_{3}\\right)$ Nanostructure for Thermoelectric Applications, Renewable Sustainable Energy Rev., 2018, 82, 4159–4169, DOI: 10.1016/j.rser.2017.10.112. \n11 J. Mao, H. Zhu, Z. Ding, Z. Liu, G. A. Gamage, G. Chen and Z. Ren, High Thermoelectric Cooling Performance of N-Type $\\mathbf{Mg}_{3}\\mathbf{Bi}_{2}$ -Based, Mater. Sci., 2019, 365(6452), 495–498, DOI: 10.1126/science.aax7792. \n$\\boldsymbol{12}\\mathrm{~\\textmu~}$ Lu and D. T. Morelli, Natural Mineral Tetrahedrite as a Direct Source of Thermoelectric Materials, Phys. Chem. Chem. Phys., 2013, 15(16), 5762–5766, DOI: 10.1039/C3CP50920F. \n13 Z. Liu, J. Mao, J. Sui and Z. Ren, High Thermoelectric Performance of $\\mathfrak{a}$ -MgAgSb for Power Generation, Energy Environ. Sci., 2018, 11(1), 23–44, DOI: 10.1039/C7EE02504A. \n14 Y. Takagiwa, Y. Pei, G. Pomrehn and G. J. Snyder, Dopants Effect on the Band Structure of PbTe Thermoelectric Material, Appl. Phys. Lett., 2012, 101(9), 092102, DOI: 10.1063/1.4748363. \n15 G. Tan, F. Shi, J. W. Doak, H. Sun, L.-D. Zhao, P. Wang, C. Uher, C. Wolverton, V. P. Dravid and M. G. Kanatzidis, Extraordinary Role of $\\mathbf{H}\\mathbf{g}$ in Enhancing the Thermoelectric Performance of P-Type SnTe, Energy Environ. Sci., 2015, 8(1), 267–277, DOI: 10.1039/C4EE01463D. \n16 V. L. Kuznetsov, L. A. Kuznetsova, A. E. Kaliazin and D. M. Rowe, High Performance Functionally Graded and Segmented ${\\bf B i}_{2}\\mathrm{Te}_{3}$ -Based Materials for Thermoelectric Power Generation, $J.$ Mater. Sci., 2002, 37(14), 2893–2897, DOI: 10.1023/A: 1016092224833. \n17 G. Tan, S. Hao, J. Zhao, C. Wolverton and M. G. Kanatzidis, High Thermoelectric Performance in Electron-Doped $\\mathrm{\\bfAgBi}_{3}\\mathrm{\\bfS}_{5}$ with Ultralow Thermal Conductivity, J. Am. Chem. Soc., 2017, 139(18), 6467–6473, DOI: 10.1021/jacs.7b02399. \n18 A. Banik, U. S. Shenoy, S. Anand, U. V. Waghmare and K. Biswas, Mg Alloying in SnTe Facilitates Valence Band Convergence and Optimizes Thermoelectric Properties, Chem. Mater., 2015, 27(2), 581–587, DOI: 10.1021/cm504112m. \n19 S. Aminorroaya Yamini, T. Ikeda, A. Lalonde, Y. Pei, S. Xue Dou and G. Jeffrey Snyder, Rational Design of P-Type Thermoelectric PbTe: Temperature Dependent Sodium Solubility, $J.$ Mater. Chem. A, 2013, 1(31), 8725–8730, DOI: 10.1039/C3TA11654A. \n20 Q. Zhang, F. Cao, W. Liu, K. Lukas, B. Yu, S. Chen, C. Opeil, D. Broido, G. Chen and Z. Ren, Heavy Doping and Band Engineering by Potassium to Improve the Thermoelectric Figure of Merit in P-Type PbTe, PbSe, and $\\mathrm{PbTe}_{1-y}\\mathrm{Se}_{y},\\$ J. Am. Chem. Soc., 2012, 134(24), 10031–10038, DOI: 10.1021/ ja301245b. \n21 G. Tan, S. Hao, S. Cai, T. P. Bailey, Z. Luo, I. Hadar, C. Uher, V. P. Dravid, C. Wolverton and M. G. Kanatzidis, All-Scale Hierarchically Structured p-Type PbSe Alloys with High Thermoelectric Performance Enabled by Improved Band Degeneracy, J. Am. Chem. Soc., 2019, 141(10), 4480–4486, DOI: 10.1021/jacs.9b00967. \n22 S. Cai, Z. Liu, J. Sun, R. Li, W. Fei and J. Sui, Enhancement of Thermoelectric Properties by Na Doping in Te-Free p-Type AgSbSe 2, Dalton Trans., 2015, 44(3), 1046–1051, DOI: 10.1039/C4DT03059A. \n23 Y. Pei, H. Wang and G. J. Snyder, Thermoelectric Materials: Band Engineering of Thermoelectric Materials (Adv. Mater. 46/2012), Adv. Mater., 2012, 24(46), 6124, DOI: 10.1002/ adma.201290290. \n24 G. Tan, F. Shi, S. Hao, H. Chi, T. P. Bailey, L.-D. Zhao, C. Uher, C. Wolverton, V. P. Dravid and M. G. Kanatzidis, Valence Band Modification and High Thermoelectric Performance in SnTe Heavily Alloyed with MnTe, J. Am. Chem. Soc., 2015, 137(35), 11507–11516, DOI: 10.1021/jacs.5b07284. \n25 T. J. Slade, T. P. Bailey, J. A. Grovogui, X. Hua, X. Zhang, J. J. Kuo, I. Hadar, G. J. Snyder, C. Wolverton and V. P. Dravid, et al., High Thermoelectric Performance in PbSe–NaSbSe2 Alloys from Valence Band Convergence and Low Thermal Conductivity, Adv. Energy Mater., 2019, 9(30), 1901377, DOI: 10.1002/aenm.201901377. \n26 Z.-Z. Luo, S. Hao, X. Zhang, X. Hua, S. Cai, G. Tan, P. Bailey, T. Ma, R. Uher and C. Wolverton, C., et al., Soft Phonon Modes from Off-Center Ge Atoms Lead to Ultralow Thermal Conductivity and Superior Thermoelectric Performance in n-Type PbSe–GeSe, Energy Environ. Sci., 2018, 11(11), 3220–3230, DOI: 10.1039/C8EE01755G. \n27 Y. Luo, S. Cai, X. Hua, H. Chen, Q. Liang, C. Du, Y. Zheng, J. Shen, J. Xu and C. Wolverton, et al., High Thermoelectric Performance in Polycrystalline SnSe Via Dual-Doping with Ag/Na and Nanostructuring With Ag8SnSe6, Adv. Energy Mater., 2019, 9(2), 1803072, DOI: 10.1002/aenm.201803072. \n28 L. Chaput, A. Togo, I. Tanaka and G. Hug, Phonon-Phonon Interactions in Transition Metals, Phys. Rev. B: Condens. Matter Mater. Phys., 2011, 84(9), 094302, DOI: 10.1103/ PhysRevB.84.094302. \n29 L.-D. Zhao, J. He, S. Hao, C.-I. Wu, T. P. Hogan, C. Wolverton, V. P. Dravid and M. G. Kanatzidis, Raising the Thermoelectric Performance of P-Type PbS with Endotaxial Nanostructuring and Valence-Band Offset Engineering Using CdS and ZnS, J. Am. Chem. Soc., 2012, 134(39), 16327–16336, DOI: 10.1021/ja306527n. \n30 J. M. Hodges, S. Hao, J. A. Grovogui, X. Zhang, T. P. Bailey, X. Li, Z. Gan, Y.-Y. Hu, C. Uher and V. P. Dravid, et al., Chemical Insights into PbSe– $x\\%$ HgSe: High Power Factor and Improved Thermoelectric Performance by Alloying with Discordant Atoms, J. Am. Chem. Soc., 2018, 140(51), 18115–18123, DOI: 10.1021/jacs.8b11050. \n31 Z.-G. Chen, X. Shi, L.-D. Zhao and J. Zou, High-Performance SnSe Thermoelectric Materials: Progress and Future Challenge, Prog. Mater. Sci., 2018, 97, 283–346, DOI: 10.1016/j.pmatsci. 2018.04.005. \n32 X. Qian, H. Wu, D. Wang, Y. Zhang, J. Wang, G. Wang, L. Zheng, S. J. Pennycook and L.-D. Zhao, Synergistically Optimizing Interdependent Thermoelectric Parameters of N-Type PbSe through Alloying CdSe, Energy Environ. Sci., 2019, 12(6), 1969–1978, DOI: 10.1039/C8EE03386B. \n33 C. Chen, W. Xue, S. Li, Z. Zhang, X. Li, X. Wang, Y. Liu, J. Sui, X. Liu and F. Cao, et al., Zintl-Phase Eu2ZnSb2: A Promising Thermoelectric Material with Ultralow Thermal Conductivity, Proc. Natl. Acad. Sci. U. S. A., 2019, 116(8), 2831–2836, DOI: 10.1073/pnas.1819157116. \n34 D. Qin, B. Cui, L. Yin, X. Zhao, Q. Zhang, J. Cao, W. Cai and J. Sui, Tin Acceptor Doping Enhanced Thermoelectric Performance of N-Type Yb Single-Filled Skutterudites via Reduced Electronic Thermal Conductivity, ACS Appl. Mater. Interfaces, 2019, 11(28), 25133–25139, DOI: 10.1021/acsami.9b05243. \n35 X. Chen, H. Wu, J. Cui, Y. Xiao, Y. Zhang, J. He, Y. Chen, J. Cao, W. Cai and S. J. Pennycook, et al., Extraordinary Thermoelectric Performance in N-Type Manganese Doped Mg3Sb2 Zintl: High Band Degeneracy, Tuned Carrier Scattering Mechanism and Hierarchical Microstructure, Nano Energy, 2018, 52, 246–255, DOI: 10.1016/j.nanoen.2018.07.059. \n36 Y. Pei, C. Chang, Z. Wang, M. Yin, M. Wu, G. Tan, H. Wu, Y. Chen, L. Zheng and S. Gong, et al., Multiple Converged Conduction Bands in $\\mathrm{~K~}_{2}\\mathrm{~Bi~}_{8}\\mathrm{~Se~}_{13}$ : A Promising Thermoelectric Material with Extremely Low Thermal Conductivity, J. Am. Chem. Soc., 2016, 138(50), 16364–16371, DOI: 10.1021/ jacs.6b09568. \n37 Z.-G. Chen, X. Shi, L.-D. Zhao and J. Zou, High-Performance SnSe Thermoelectric Materials: Progress and Future Challenge, Prog. Mater. Sci., 2018, 97, 283–346, DOI: 10.1016/j.pmatsci. 2018.04.005. \n38 W. Shi, M. Gao, J. Wei, J. Gao, C. Fan, E. Ashalley, H. Li and Z. Wang, Tin Selenide (SnSe): Growth, Properties, and Applications, Adv. Sci., 2018, 5(4), 1700602, DOI: 10.1002/ advs.201700602. \n39 L.-D. Zhao, G. Tan, S. Hao, J. He, Y. Pei, H. Chi, H. Wang, S. Gong, H. Xu and V. P. Dravid, et al., Ultrahigh Power Factor and Thermoelectric Performance in Hole-Doped Single-Crystal SnSe, Science, 2016, 351(6269), 141–144, DOI: 10.1126/science.aad3749. \n40 L.-D. Zhao, S.-H. Lo, Y. Zhang, H. Sun, G. Tan, C. Uher, C. Wolverton, V. P. Dravid and M. G. Kanatzidis, Ultralow Thermal Conductivity and High Thermoelectric Figure of Merit in SnSe Crystals, Nature, 2014, 508(7496), 373–377, DOI: 10.1038/nature13184. \n41 J. Zhao, S. Hao, S. M. Islam, H. Chen, S. Ma, C. Wolverton and M. G. Kanatzidis, Quaternary Chalcogenide Semiconductors with 2D Structures: $\\ensuremath{\\mathbf{Rb}}_{2}\\ensuremath{\\mathrm{ZnBi}_{2}}\\ensuremath{\\mathrm{Se}}_{5}$ and $\\mathrm{Cs}_{6}\\mathrm{Cd}_{2}\\mathrm{Bi}_{8}\\mathrm{Te}_{17}$ , Inorg. Chem., 2018, 57(15), 9403–9411, DOI: 10.1021/acs.inorgchem. 8b01383. \n42 Y. K. Lee, Z. Luo, S. P. Cho, M. G. Kanatzidis and I. Chung, Surface Oxide Removal for Polycrystalline SnSe Reveals Near-Single-Crystal Thermoelectric Performance, Joule, 2019, 3(3), 719–731, DOI: 10.1016/j.joule.2019.01.001. \n43 C. Chang, M. Wu, D. He, Y. Pei, C.-F. Wu, X. Wu, H. Yu, F. Zhu, K. Wang and Y. Chen, et al., 3D Charge and 2D Phonon Transports Leading to High Out-of-Plane ZT in n-Type SnSe Crystals, Science, 2018, 360(6390), 778–783, DOI: 10.1126/science.aaq1479. \n44 Y. Pei, A. D. LaLonde, N. A. Heinz and G. J. Snyder, High Thermoelectric Figure of Merit in PbTe Alloys Demonstrated in PbTe-CdTe, Adv. Energy Mater., 2012, 2(6), 670–675, DOI: 10.1002/aenm.201100770. \n45 S. Aminorroaya Yamini, H. Wang, D. Ginting, D. R. G. Mitchell, S. X. Dou and G. J. Snyder, Thermoelectric Performance of n-Type $\\mathrm{\\big(PbTe\\big)_{0.75}\\big(P b S\\big)_{0.15}\\big(P b S e\\big)_{0.1}}$ Composites, ACS Appl. Mater. Interfaces, 2014, 6(14), 11476–11483, DOI: 10.1021/ am502140h. \n46 J. R. Sootsman, J. He, V. P. Dravid, C.-P. Li, C. Uher and M. G. Kanatzidis, High Thermoelectric Figure of Merit and Improved Mechanical Properties in Melt Quenched PbTe–Ge and PbTe– ${\\bf G e}_{1-x}\\mathrm{Si}_{x}$ Eutectic and Hypereutectic Composites, J. Appl. Phys., 2009, 105(8), 083718, DOI: 10.1063/1.3093833. \n47 G. Tan, F. Shi, S. Hao, L.-D. Zhao, H. Chi, X. Zhang, C. Uher, C. Wolverton, V. P. Dravid and M. G. Kanatzidis, NonEquilibrium Processing Leads to Record High Thermoelectric Figure of Merit in PbTe–SrTe, Nat. Commun., 2016, 7, 12167, DOI: 10.1038/ncomms12167. \n48 D. Wu, L.-D. Zhao, X. Tong, W. Li, L. Wu, Q. Tan, Y. Pei, L. Huang, J.-F. Li and Y. Zhu, et al., Superior Thermoelectric Performance in PbTe–PbS Pseudo-Binary: Extremely Low Thermal Conductivity and Modulated Carrier Concentration, Energy Environ. Sci., 2015, 8(7), 2056–2068, DOI: 10.1039/ C5EE01147G. \n49 Enhancement of Thermoelectric Performance for n-Type PbS through Synergy of Gap State and Fermi Level Pinning | Journal of the American Chemical Society https://pubs.acs.org/doi/10.1021/jacs.9b01889 (accessed Aug 17, 2019). \n50 Recent progress and futuristic development of PbSe thermoelectric materials and devices | Elsevier Enhanced Reader https://reader.elsevier.com/reader/sd/pii/S2468606918300510? token $\\mathbf{\\Sigma}=\\mathbf{\\Sigma}$ 6E816C1A71AFFCEF38DFE02E8CE21ECB84D26666- B4A586E6881DDC3D8DA59BDAB72880571BF9CB4C3B7FC58A5CE55E54 (accessed May 6, 2019)., DOI: 10.1016/ j.mtener.2018.06.010. \n51 L.-D. Zhao, S. Hao, S.-H. Lo, C.-I. Wu, X. Zhou, Y. Lee, H. Li, K. Biswas, T. P. Hogan and C. Uher, et al., High Thermoelectric Performance via Hierarchical Compositionally Alloyed Nanostructures, J. Am. Chem. Soc., 2013, 135(19), 7364–7370, DOI: 10.1021/ja403134b. \n52 C. I. Ratcliffe, K. Yu, J. A. Ripmeester, Md Badruz Zaman, C. Badarau and S. Singh, Solid State NMR Studies of Photoluminescent Cadmium Chalcogenide Nanoparticles, Phys. Chem. Chem. Phys., 2006, 8(30), 3510, DOI: 10.1039/b606507b. \n53 M. P. Kulakov and I. V. Balyakina, Solid State WurtziteSphalerite Transformation and Phase Boundaries in ZnSe-CdSe, J. Cryst. Growth, 1991, 113(3–4), 653–658, DOI: 10.1016/0022- 0248(91)90101-A. \n54 M. G. Berrettini, G. Braun, J. G. Hu and G. F. Strouse, NMR Analysis of Surfaces and Interfaces in 2-Nm CdSe, J. Am. Chem. Soc., 2004, 126(22), 7063–7070, DOI: 10.1021/ja037228h. \n55 R. K. Harris, E. D. Becker, S. M. Cabral de Menezes, R. Goodfellow and P. Granger, NMR Nomenclature: Nuclear Spin Properties and Conventions for Chemical Shifts. IUPAC Recommendations 2001. International Union of Pure and Applied Chemistry. Physical Chemistry Division. Commission on Molecular Structure and Spectroscopy, Magn. Reson. Chem., 2002, 40(7), 489–505, DOI: 10.1002/mrc.1042. \n56 G. Henkelman and H. J´onsson, Improved Tangent Estimate in the Nudged Elastic Band Method for Finding Minimum Energy Paths and Saddle Points, $J.$ Chem. Phys., 2000, 113(22), 9978–9985, DOI: 10.1063/1.1323224. \n57 Z. F. Tomashik, G. S. Olejnik and V. N. Tomashik, Phase diagram of the PbSe–CdSe system, Neorg. Mater., 1980, 16(2), 261–263. \n58 S. Takeuchi, K. Suzuki, K. Maeda and H. Iwanaga, StackingFault Energy of II–VI Compounds, Philos. Mag. A, 1985, 50(2), 171–178, DOI: 10.1080/01418618408244220. \n59 X. Zhang, S. Hao, G. Tan, X. Hu, E. W. Roth, M. G. Kanatzidis, C. Wolverton and V. P. Dravid, Ion Beam Induced Artifacts in Lead-Based Chalcogenides, Microsc. Microanal., 2019, 1–9, DOI: 10.1017/S1431927619000503. \n60 Q. Zhang, F. Cao, W. Liu, K. Lukas, B. Yu, S. Chen, C. Opeil, D. Broido, G. Chen and Z. Ren, Heavy Doping and Band Engineering by Potassium to Improve the Thermoelectric Figure of Merit in P-Type PbTe, PbSe, and PbTe1-YSey, J. Am. Chem. Soc., 2012, 134(24), 10031–10038, DOI: 10.1021/ja301245b. \n61 J. Androulakis, I. Todorov, D.-Y. Chung, S. Ballikaya, G. Wang, C. Uher and M. Kanatzidis, Thermoelectric Enhancement in PbTe with K or Na Codoping from Tuning the Interaction of the Light- and Heavy-Hole Valence Bands, Phys. Rev. B: Condens. Matter Mater. Phys., 2010, 82(11), 115209, DOI: 10.1103/ PhysRevB.82.115209. \n62 Z. Wang, X. Yang, D. Feng, H. Wu, J. Carrete, L.-D. Zhao, C. Li, S. Cheng, B. Peng and G. Yang, et al., Understanding Phonon Scattering by Nanoprecipitates in Potassium-Doped Lead Chalcogenides, ACS Appl. Mater. Interfaces, 2017, 9(4), 3686–3693, DOI: 10.1021/acsami.6b14266. \n63 J. J. Kuo, S. D. Kang, K. Imasato, H. Tamaki, S. Ohno, T. Kanno and G. J. Snyder, Grain Boundary Dominated Charge Transport in $\\mathbf{Mg}_{3}\\mathbf{Sb}_{2}$ -Based Compounds, Energy Environ. Sci., 2018, 11(2), 429–434, DOI: 10.1039/C7EE03326E. \n64 H.-S. Kim, Z. M. Gibbs, Y. Tang, H. Wang and G. J. Snyder, Characterization of Lorenz Number with Seebeck Coefficient Measurement, APL Mater., 2015, 3(4), 041506, DOI: 10.1063/ 1.4908244. \n65 H. Wang, Z. M. Gibbs, Y. Takagiwa and G. J. Snyder, Tuning Bands of PbSe for Better Thermoelectric Efficiency, Energy, Environ. Sci., 2014, 7(2), 804–811, DOI: 10.1039/C3EE43438A. \n66 S. Sarkar, X. Zhang, S. Hao, X. Hua, T. P. Bailey, C. Uher, C. Wolverton, V. P. Dravid and M. G. Kanatzidis, Dual Alloying Strategy to Achieve a High Thermoelectric Figure of Merit and Lattice Hardening in P-Type Nanostructured PbTe, ACS Energy Lett., 2018, 3(10), 2593–2601, DOI: 10.1021/ acsenergylett.8b01684. \n67 G. Tan, X. Zhang, S. Hao, H. Chi, T. P. Bailey, X. Su, C. Uher, V. P. Dravid, C. Wolverton and M. G. Kanatzidis, Enhanced Density-of-States Effective Mass and Strained Endotaxial Nanostructures in Sb-Doped $\\mathbf{Pb_{0.97}C d_{0.03}T e}$ Thermoelectric Alloys, ACS Appl. Mater. Interfaces, 2019, 11(9), 9197–9204, DOI: 10.1021/acsami.8b21524. " + }, + { + "id": "10.1038_s41586-020-1994-5", + "DOI": "10.1038/s41586-020-1994-5", + "DOI Link": "http://dx.doi.org/10.1038/s41586-020-1994-5", + "Relative Dir Path": "mds/10.1038_s41586-020-1994-5", + "Article Title": "Closed-loop optimization of fast-charging protocols for batteries with machine learning", + "Authors": "Attia, PM; Grover, A; Jin, N; Severson, KA; Markov, TM; Liao, YH; Chen, MH; Cheong, B; Perkins, N; Yang, Z; Herring, PK; Aykol, M; Harris, SJ; Braatz, RD; Ermon, S; Chueh, WC", + "Source Title": "NATURE", + "Abstract": "Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines(1,2). One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years(3-5). Furthermore, both large parameter spaces and high sampling variability(3,6,7) necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users(8,9). We combine two key elements to reduce the optimization cost: an early-prediction model(5), which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm(10,11), which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.", + "Times Cited, WoS Core": 538, + "Times Cited, All Databases": 577, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000543762000001", + "Markdown": "# Article \n\n# Closed-loop optimization of fast-charging protocols for batteries with machine learning \n\nhttps://doi.org/10.1038/s41586-020-1994-5 \n\nReceived: 6 August 2019 \n\nAccepted: 19 December 2019 \n\nPublished online: 19 February 2020 Check for updates \n\nPeter M. Attia1,7, Aditya Grover2,7, Norman Jin1, Kristen A. Severson3, Todor M. Markov2, Yang-Hung Liao1, Michael H. Chen1, Bryan Cheong1,2, Nicholas Perkins1, Zi Yang1, Patrick K. Herring4, Muratahan Aykol4, Stephen J. Harris1,5, Richard D. Braatz3 ✉, Stefano Ermon2 ✉ & William C. Chueh1,6 ✉ \n\nSimultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3–5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces. \n\nOptimal experimental design (OED) approaches are widely used to reduce the cost of experimental optimization. These approaches often involve a closed-loop pipeline where feedback from completed experiments informs subsequent experimental decisions, balancing the competing demands of exploration—that is, testing regions of the experimental parameter space with high uncertainty—and exploitation—that is, testing promising regions based on the results of the completed experiments. Adaptive OED algorithms have been successfully applied to physical science domains, such as materials science1,2,12–14, chemistry15,16, biology17 and drug discovery18, as well as to computer science domains, such as hyperparameter optimization for machine learning19,20. However, while a closed-loop approach is designed to minimize the number of experiments required for optimizing across a multi-dimensional parameter space, the time (and cost) per experiment may remain high, as is the case for lithium-ion batteries. Therefore, an OED approach should account for both the number of experiments and the cost per experiment. Multi-fidelity optimization approaches have been developed to learn from both inexpensive, noisy signals and expensive, accurate signals. For example, in hyperparameter optimization for machine learning algorithms, several low-fidelity signals for predicting the final performance of an algorithmic configuration (for example, extrapolated learning curves19,20, rapid testing on a subset of the full training dataset21) are used in tandem with more complete configuration evaluations22,23. For lithium-ion batteries, classical \n\n# Article \n\n![](images/b9d25a890ae53043c9b16c527b371fa098f78249747470b0c387fec852e30591.jpg) \nFig. 1 | Schematic of our CLO system. First, batteries are tested. The cycling data from the first 100 cycles (specifically, electrochemical measurements such as voltage and capacity) are used as input for an early outcome prediction of cycle life. These cycle life predictions from a machine learning (ML) model are subsequently sent to a BO algorithm, which recommends the next protocols to test by balancing the competing demands of exploration (testing protocols with high uncertainty in estimated cycle life) and exploitation \n(testing protocols with high estimated cycle life). This process iterates until the testing budget is exhausted. In this approach, early prediction reduces the number of cycles required per tested battery, while optimal experimental design reduces the number of experiments required. A small training dataset of batteries cycled to failure is used both to train the early outcome predictor and to set BO hyperparameters. In future work, design of battery materials and processes could also be integrated into this closed-loop system. \n\nmethods such as factorial design that use predetermined heuristics to select experiments have been applied24–26, but the design and use of low-fidelity signals is challenging and unexplored. These previously considered approaches do not discover and exploit the patterns present in the parameter space for efficient optimization, nor do they address the issue of time per experiment. \n\nIn this work, we develop a closed-loop optimization (CLO) system with early outcome prediction for efficient optimization over large parameter spaces with expensive experiments and high sampling variability. We employ this system to experimentally optimize fastcharging protocols for lithium-ion batteries; reducing charging times to approach gasoline refuelling time is critical to reduce range anxiety for electric vehicles8,9 but often comes at the expense of battery lifetime. Specifically, we optimize over a parameter space consisting of 224 unique six-step, ten-minute fast-charging protocols (that is, how current and voltage are controlled during charging) to find charging protocols with high cycle life (defined as the battery capacity falling to $80\\%$ of its nominal value). Our system uses two key elements to reduce the optimization cost (Extended Data Fig. 1). First, we reduce the time per experiment by using machine learning to predict the outcome of the experiment based on data from early cycles, well before the batteries reach the end of life5. Second, we reduce the number of experiments by using a Bayesian optimization (BO) algorithm to balance the exploration–exploitation tradeoff in choosing the next round of experiments10,11. Testing a single battery to failure under our fast-charging conditions requires approximately 40 days, meaning that when 48 experiments are performed in parallel, assessing all 224 charging protocols with triplicate measurements takes approximately 560 days. Here, using CLO with early outcome prediction, only 16 days were required to confidently identify protocols with high cycle lives (48 parallel experiments). In a subsequent validation study, we find that CLO ranks these protocols by lifetime accurately (Kendall rank correlation coefficient, 0.83) and efficiently (15 times less time than a baseline ‘brute-force’ approach that uses random search without early prediction). Furthermore, we find that the charging protocols identified as optimal by CLO with early prediction outperform existing fast-charging protocols designed to avoid lithium plating (a common fast-charging degradation mode), the approach suggested by conventional battery wisdom4,8,9,26. This work highlights the utility of combining CLO with inexpensive early outcome predictors to accelerate scientific discovery. \n\nCLO with early outcome prediction is depicted schematically in Fig. 1. The system consists of three components: parallel battery cycling, an early predictor for cycle life and a BO algorithm. At each sequential round, we iterate over these three components. The first component is a multi-channel battery cycler; the cycler used in this work tests 48 batteries simultaneously. Before starting CLO, the charging protocols for the first round of 48 batteries are chosen at random (without replacement) from the complete set of 224 unique multi-step protocols (Methods). Each battery undergoes repeated charging and discharging for 100 cycles (about 4 days; average predicted cycle life 905 cycles), beyond which the experiments are terminated. \n\nThese cycling data are then fed as input to the early outcome predictor, which estimates the final cycle lives of the batteries given data from the first 100 cycles. The early predictor is a linear model trained via elastic net regression27 on features extracted from the charging data of the first 100 cycles (Supplementary Table 1), similar to that presented in Severson et al.5. Predictive features include transformations of both differences between voltage curves and discharge capacity fade trends. To train the early predictor, we require a training dataset of batteries cycled to failure. Here, we used a pre-existing dataset of 41 batteries cycled to failure (cross-validation root-mean-square error, 80.4 cycles; see Methods and Supplementary Discussion 1). Whereas obtaining this dataset itself requires running full cycling experiments for a small training set of batteries (the cost we are trying to offset), this one-time cost could be avoided if pretrained predictors or previously collected datasets are available. If unavailable, we pay an upfront cost in collecting this dataset; this dataset could also be used for warm-starting the BO algorithm. The size of the dataset collected should best tradeoff the upfront cost in acquiring the dataset to train an accurate model with the anticipated reduction in experimentation requirements for CLO. \n\nFinally, these predicted cycle lives from early-cycle data are fed into the BO algorithm (Methods and Supplementary Discussion 2), which recommends the next round of 48 charging protocols that best balance the exploration–exploitation tradeoff. This algorithm (Methods and Supplementary Discussion 2) builds on the prior work of Hoffman et al.10 and Grover et al.11. The algorithm maintains an estimate of both the average cycle life and the uncertainty bounds for each protocol; these estimates are initially equal for all protocols and are refined as additional data are collected. Crucially, to reduce the total optimization cost, our algorithm performs these updates using estimates from the early outcome predictor instead of using the actual cycle lives. The mean and uncertainty estimates for the cycle lives are obtained via a Gaussian process (Methods), which has a smoothing effect and allows for updating the cycle life estimates of untested protocols with the predictions from related protocols. The closed-loop process repeats until the optimization budget, in our case 192 batteries tested (100 cycles each), is exhausted. \n\n![](images/52e2ebbd06b58469921ab0dda55b3ebd80dd818325678b16075ce759ce79d277.jpg) \nFig. 2 | Structure of our six-step, ten-minute fast-charging protocols. Currents are defined as dimensionless C rates; here, 1C is 1.1 A, or the current required to fully (dis)charge the nominal capacity (1.1 A h) in 1 h. a, Current versus SOC for an example charging protocol, 7.0C–4.8C–5.2C–3.45C (bold lines). Each charging protocol is defined by five constant current (CC) steps followed by one constant voltage (CV) step. The last two steps (CC5 and CV1) are identical for all charging protocols. We optimize over the first four constant-current steps, denoted CC1, CC2, CC3 and CC4. Each of these steps comprises a $20\\%$ SOC window, such that CC1 ranges from $0\\%$ to $20\\%$ SOC, CC2 \nranges from $20\\%$ to $40\\%500$ , and so on. CC4 is constrained by specifying that all protocols charge in the same total time $(10\\mathrm{{min})}$ from $0\\%$ to $80\\%500$ . Thus, our parameter space consists of unique combinations of the three free parameters CC1, CC2 and CC3. For each step, we specify a range of acceptable values; the upper limit is monotonically decreasing with increasing SOC to avoid the upper cutoff potential (3.6 V for all steps). b, CC4 (colour scale) as a function of CC1, CC2 and CC3 (on the x, y and z axes, respectively). Each point represents a unique charging protocol. \n\nOur objective is to find the charging protocol which maximizes the expected battery cycle life for a fixed charging time (ten minutes) and state-of-charge (SOC) range (0 to $80\\%$ ). The design space of our 224 sixstep extreme fast-charging protocols is presented in Fig. 2a. Multi-step charging protocols, in which a series of different constant-current steps are applied within a single charge, are considered advantageous over single-step charging for maximizing cycle life during fast charging4,8, though the optimal combination remains unclear. As shown in Fig. 2b, each protocol is specified by three independent parameters (CC1, CC2 and CC3); each parameter is a current applied over a fixed SOC range $(0{-}20\\%,20{-}40\\%$ and $40\\text{\\textperthousand}$ , respectively). A fourth parameter, CC4, is dependent on CC1, CC2, CC3 and the charging time. Given constraints on the current values (Methods), a total of 224 charging protocols are permitted. We test commercial lithium iron phosphate (LFP)/graphite cylindrical batteries (A123 Systems) in a convective environmental chamber ( $30^{\\circ}\\mathbf{C}$ ambient temperature). A maximum voltage of 3.6 V is imposed. These batteries are designed to fast-charge in 17 min (rate testing data are presented in Extended Data Fig. 2). The cycle life decreases dramatically with faster charging time4,5, motivating this optimization. Since the LFP positive electrode is generally considered to be stable4,5, we select this battery chemistry to isolate the effects of extreme fast charging on graphite, which is universally employed in lithium-ion batteries. \n\nIn all, we ran four CLO rounds sequentially, consisting of 185 batteries in total (excluding seven batteries; see Methods). Using early prediction, each CLO round requires four days to complete 100 cycles, resulting in a total testing time of sixteen days—a major reduction from the 560 days required to test each charging protocol to failure three times. Figure 3 presents the predictions and selected protocols (Fig. 3a), as well as the evolution of cycle life estimates over the parameter space as the optimization progresses (Fig. 3a). Initially, the estimated cycle lives for all protocols are equal. After two rounds, the overall structure of the parameter space (that is, the dependence of cycle life on charging protocol parameters CC1, CC2 and CC3) emerges, and a prominent region with high cycle life protocols has been identified. The confidence of CLO in this high-performing region is further improved from round 2 to round 4, but overall the cycle life estimates do not change substantially (Extended Data Fig. 3). By learning and exploiting the structure of the parameter space, we avoid evaluating charging protocols with low estimated cycle life and concentrate more resources on the highperforming region (Extended Data Figs. 3–5). Specifically, 117 of 224 protocols are never tested (Fig. 3c); we spend $67\\%$ of the batteries testing $21\\%$ of the protocols (0.83 batteries per protocol on average). CLO repeatedly tests several protocols with high estimated cycle life to decrease uncertainties due to manufacturing variability and the error introduced by early outcome prediction. The uncertainty is expressed as the prediction intervals of the posterior predictive distribution over cycle life (Extended Data Figs. 3g, 4, 5). \n\nTo the best of our knowledge, this work presents the largest known map of cycle life as a function of charging conditions (Extended Data Fig. 5). This dataset can be used to validate physics-based models of battery degradation. Most fast-charging protocols proposed in the battery literature suggest that current steps decreasing monotonically as a function of SOC are optimal to avoid lithium plating on graphite, a well-accepted degradation mode during fast charging4,8,9,26. In contrast, the protocols identified as optimal by CLO (for example, Fig. 3d) are generally similar to single-step constant-current charging (that is, $\\mathbf{CC1}\\approx\\mathbf{CC}2\\approx\\mathbf{CC}3\\approx\\mathbf{CC}4)$ . Specifically, of the 75 protocols with the highest estimated cycle lives, only ten are monotonically decreasing (that is, $\\mathbf{CC}_{i}{\\geq}\\mathbf{CC}_{i+1}$ for all i) and two are strictly decreasing (that is, $\\mathbf{CC}_{i}>$ $\\mathbf{CC}_{i+1})$ . We speculate that minimizing parasitic reactions caused by heat generation may be the operative optimization strategy for these cells, as opposed to minimizing the propensity for lithium plating (Supplementary Discussion 3). While the optimal protocol for a new scenario would depend on the selected charge time, SOC window, temperature control conditions and battery chemistry, this unexpected result highlights the need for data-driven approaches for optimizing fast charging. \n\n# Article \n\n![](images/57adaf43064c50291962c705101f4a157cdf383cc528afb5d4d74e7c893f9ea5.jpg) \nFig. 3 | Results of closed-loop experiments. a, Early cycle life predictions per round. The tested charging protocols and the resulting predictions are plotted for rounds 1–4. Each point represents a charging protocol, defined by CC1, CC2 and CC3 (the x, y and z axes, respectively). The colour scale represents cycle life predictions from the early outcome prediction model. The charging protocols in the first round of testing are randomly selected. As the BO algorithm shifts from exploration to exploitation, the charging protocols selected for testing by the closed loop in subsequent rounds fall primarily into the high-performing region. b, Evolution of the parameter space per round. The colour scale represents cycle life, as estimated by the BO algorithm. The initial cycle life \nestimates are equivalent for all protocols; as more predictions are generated, the BO algorithm updates its cycle life estimates. The CLO-estimated mean cycle lives after four rounds for all fast-charging protocols in the parameter space are also presented in Extended Data Fig. 5 and Supplementary Table 3. c, Distribution of the number of repetitions for each charging protocol (excluding failed batteries). Only 46 of 224 protocols $(21\\%)$ are tested multiple times. d, Current versus SOC for the top three fast-charging protocols, as estimated by CLO. CC1–CC4 are displayed in the legend. All three protocols have relatively uniform charging (that is, $\\mathbf{CC1}\\approx\\mathbf{CC}2\\approx\\mathbf{CC}3\\approx\\mathbf{CC}4;$ . \n\nWe validate the performance of CLO with early prediction on a subset of nine extreme fast-charging protocols. For each of these protocols, we cycle five batteries each to failure and use the sample average of the final cycle lives as an estimate of the true lifetimes. We use this validation study to (1) confirm that CLO is able to correctly rank protocols based on cycle life, (2) compare the cycle lives of protocols recommended by CLO to protocols inspired by the battery literature and (3) compare the performance of CLO to baseline ablation approaches for experimental design. The charging protocols used in validation, some of which are inspired by existing battery fast-charging literature (see Methods), span the range of estimated cycle lives (Extended Data Fig. 6 and Extended Data Table 1). We adjust the voltage limits and charging times of these literature protocols to match our protocols, while maintaining similar current ratios as a function of SOC. Whereas the literature protocols used in these validation experiments are generally designed for batteries with high-voltage positive electrode chemistries, fast-charging optimization strategies generally focus on the graphitic negative electrode4,8. For these nine protocols, we validate the ‘CLO-estimated’ cycle lives against the sample average of the five final cycle lives. \n\n![](images/73f69396a8d137dd4c4a7a88dbcde7d660aca35299297c1351566be6795e6ad4.jpg) \nFig. 4 | Results of validation experiment. a, Discharge capacity versus cycle number for all batteries in the validation experiment. The nine validation protocols include the top three protocols as estimated by CLO (‘CLO top 3’), four protocols inspired by the battery literature39–44 (‘Literature-inspired’) and two protocols selected to obtain a representative sampling from the distribution of CLO-estimated cycle lives among the validation protocols (‘Other’). b, Comparison of early-predicted cycle lives from validation to closed-loop estimates, averaged on a protocol basis. Each ten-minute charging protocol is tested with five batteries. Error bars represent the $95\\%$ confidence intervals. c, Observed versus early-predicted cycle life for the validation experiment. Although our early predictor tends to overestimate cycle life, \nprobably owing to calendar ageing effects (Supplementary Discussion 4), the trend is correctly captured (Pearson correlation coefficient $r{=}0.86$ . d, Final cycle lives from validation, sorted by CLO ranking. The length of each bar and the annotations represents the mean final cycle life from validation per protocol. Error bars represent the $95\\%$ confidence intervals. e, Ablation study of various optimization approaches using the protocols and data in the validation set (Methods). Error bars represent the $95\\%$ confidence intervals $(n=2,000,$ ). With contributions from both early prediction and Bayesian optimization, CLO can rapidly identify high-performing charging protocols. The gains from Bayesian optimization are larger when resources are constrained (Extended Data Fig. 8). \n\nThe validation results are presented in Fig. 4. The discharge capacity fade curves (Fig. 4a) exhibit the nonlinear decay typical of fast charg$\\mathrm{ing}^{5,7}$ . If we apply our early-prediction model to the batteries in the validation experiment, these early predictions (averaged over each protocol) match the CLO-estimated mean cycle lives well (Pearson correlation coefficient $r=0.93$ ; Fig. 4b). This result validates the performance of the BO component of CLO in particular, since the CLOestimated cycle lives were inferred from early predictions. However, our early-prediction model exhibits some bias (Fig. 4c), probably owing to calendar ageing effects from different battery storage times28 (Supplementary Table 2 and Supplementary Discussion 4). Despite this bias in our predictive model, we generally capture the ranking well (Kendall rank correlation coefficient, 0.83; Fig. 4d and Extended Data Fig. 7). At the same time, we note that the final cycle lives for the top-ranked protocols are similar. Furthermore, the optimal protocols identified by CLO outperform protocols inspired by previously published fastcharging protocols (895 versus 728 cycles on average; Extended Data Fig. 6 and Extended Data Table 1). This result suggests that the efficiency of our approach does not come at the expense of accuracy. \n\nOur method greatly reduces the optimization time required compared to baseline optimization approaches (Fig. 4e). For instance, a procedure that does not use early outcome prediction and simply selects protocols randomly to test begins to saturate at a competitive performance level after about 7,700 battery-hours of testing. To achieve a similar level of performance, CLO with both early outcome prediction and the BO algorithm requires only 500 battery-hours of testing. For this small-scale validation experiment, we observe that the early-prediction component of CLO greatly reduces the time per experiment. Here, random selection is equivalent to a pure exploration strategy and can achieve a performance similar to the BO-based approaches for smaller experimental budgets. In later stages, random selection is eventually outperformed by BO-based approaches, which exploit the structure across the protocols and focus on reducing the uncertainty in the promising regions of the parameter space. Although these results are specific to this validation study, we observe similar or larger gains in simulations when fewer batteries or fewer parallel experiments (relative to the size of the parameter space) are available (Extended Data Fig. 8). The relative gains from BO over random selection are largest with minimal resources. \n\nFinally, we compare our early predictor with other low-fidelity predictors proposed in state-of-the-art multi-fidelity optimization algorithms \n\n# Article \n\nin the literature19,20, and find that our approach outperforms these algorithms (Supplementary Discussion 2 and Supplementary Table 4). The generic early-prediction models in these previous works fit composites of parametric functions to the capacity fade curves, while our model uses additional features recorded at every cycle (for example, voltage). This result highlights the value of designing predictive models for the target application in multi-fidelity optimization. \n\nIn summary, we have successfully accelerated the optimization of extreme fast charging for lithium-ion batteries using CLO with early outcome prediction. This method could extend to other fast-charging design spaces, such as pulsed26,28 and constant-power8 charging, as well as to other objectives, such as slower charging and calendar ageing. Additionally, this work opens up new applications for battery optimization, such as formation29, adaptive cycling30 and parameter estimation for battery management system models31. Furthermore, provided that a suitable early outcome predictor exists, this method could also be applied to optimize other aspects of battery development, such as electrode materials and electrolyte chemistries. Beyond batteries, our CLO approach combining black-box optimization with early outcome prediction can be extended to efficiently optimize other physical1,2,18 and computational22,32 multi-dimensional parameter spaces that involve time-intensive experimentation, illustrating the power of data-driven methods to accelerate the pace of scientific discovery. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-020-1994-5. \n\n1. Tabor, D. P. et al. Accelerating the discovery of materials for clean energy in the era of smart automation. Nat. Rev. Mater. 3, 5–20 (2018). \n2. Butler, K. T., Davies, D. W., Cartwright, H., Isayev, O. & Walsh, A. Machine learning for molecular and materials science. Nature 559, 547–555 (2018). \n3. Baumhöfer, T., Brühl, M., Rothgang, S. & Sauer, D. U. Production caused variation in capacity aging trend and correlation to initial cell performance. J. Power Sources 247, 332–338 (2014). \n4. Keil, P. & Jossen, A. Charging protocols for lithium-ion batteries and their impact on cycle life—an experimental study with different 18650 high-power cells. J. Energy Storage 6, 125–141 (2016). \n5. Severson, K. A. et al. Data-driven prediction of battery cycle life before capacity degradation. Nat. Energy 4, 383–391 (2019). \n6. Schuster, S. F., Brand, M. J., Berg, P., Gleissenberger, M. & Jossen, A. Lithium-ion cellto-cell variation during battery electric vehicle operation. J. Power Sources 297, 242– 251 (2015). \n7. Harris, S. J., Harris, D. J. & Li, C. Failure statistics for commercial lithium ion batteries: a study of 24 pouch cells. J. Power Sources 342, 589–597 (2017). \n8. Ahmed, S. et al. Enabling fast charging—a battery technology gap assessment. J. Power Sources 367, 250–262 (2017). \n9. Liu, Y., Zhu, Y. & Cui, Y. Challenges and opportunities towards fast-charging battery materials. Nat. Energy 4, 540–550 (2019). \n10. Hoffman, M. W., Shahriari, B. & de Freitas, N. On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning. In Proc. 17th Int. Conf. on Artificial Intelligence and Statistics (AISTATS) Vol. 33, 365–374 (Proceedings of Machine Learning Research, 2014); http://proceedings.mlr.press/v33/ hoffman14.html. \n11.\t Grover, A. et al. Best arm identification in multi-armed bandits with delayed feedback. In Proc. 21st Int. Conf. on Artificial Intelligence and Statistics (AISTATS) Vol. 84, 833–842 (Proceedings of Machine Learning Research, 2018); http://proceedings.mlr.press/v84/ grover18b.html. \n12. Nikolaev, P. et al. Autonomy in materials research: a case study in carbon nanotube growth. npj Comput. Mater. 2, 16031 (2016). \n13. Ling, J., Hutchinson, M., Antono, E., Paradiso, S. & Meredig, B. High-dimensional materials and process optimization using data-driven experimental design with well-calibrated uncertainty estimates. Integr. Mater. Manuf. Innov. 6, 207–217 (2017). \n14.\t Balachandran, P. V., Kowalski, B., Sehirlioglu, A. & Lookman, T. Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning. Nat. Commun. 9, 1668 (2018). \n15. Bédard, A.-C. et al. Reconfigurable system for automated optimization of diverse chemical reactions. Science 361, 1220–1225 (2018). \n16. Granda, J. M., Donina, L., Dragone, V., Long, D.-L. & Cronin, L. Controlling an organic synthesis robot with machine learning to search for new reactivity. Nature 559, 377–381 (2018). \n17. King, R. D. et al. The automation of science. Science 324, 85–89 (2009). \n18. Schneider, G. Automating drug discovery. Nat. Rev. Drug Discov. 17, 97–113 (2018). \n19. Domhan, T., Springenberg, J. T. & Hutter, F. Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves. In Proc. 24th Int. Conf. on Artificial Intelligence 3460–3468 (AAAI Press, 2015). \n20.\t Klein, A., Falkner, S., Springenberg, J. T. & Hutter, F. Learning curve prediction with Bayesian neural networks. In Proc. 2017 Int. Conf. on Learning Representations 1–16 (2017); https://openreview.net/forum?id=S11KBYclx. \n21.\t Petrak, J. Fast Subsampling Performance Estimates for Classification Algorithm Selection. Technical Report TR-2000-07, 3–14 (Austrian Research Institute for Artificial Intelligence, 2000); http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.28.330 5&rep=rep1&type=pdf. \n22.\t Li, L., Jamieson, K., DeSalvo, G., Rostamizadeh, A. & Talwalkar, A. Hyperband: a novel bandit-based approach to hyperparameter optimization. J. Mach. Learn. Res. 18, 1–52 (2018). \n23.\t Hutter, F., Hoos, H. H. & Leyton-Brown, K. Sequential model-based optimization for general algorithm configuration. In Proc. 5th Int. Conf. on Learning and Intelligent Optimization 507–523 (Springer, 2011). \n24. Luo, Y., Liu, Y. & Wang, S. Search for an optimal multistage charging pattern for lithium-ion batteries using the Taguchi approach. In Region 10 Conf. (TENCON 2009) 1–5, https://doi. org/10.1109/TENCON.2009.5395823 (IEEE, 2009). \n25.\t Liu, Y., Hsieh, C. & Luo, Y. Search for an optimal five-step charging pattern for Li-ion batteries using consecutive orthogonal arrays. IEEE Trans. Energ. Convers. 26, 654–661 (2011). \n26.\t Schindler, S., Bauer, M., Cheetamun, H. & Danzer, M. A. Fast charging of lithium-ion cells: identification of aging-minimal current profiles using a design of experiment approach and a mechanistic degradation analysis. J. Energy Storage 19, 364–378 (2018). \n27.\t Zou, H. & Hastie, T. Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B 67, 301–320 (2005). \n28. Keil, P. et al. Calendar aging of lithium-ion batteries. I. Impact of the graphite anode on capacity fade. J. Electrochem. Soc. 163, A1872–A1880 (2016). \n29.\t Wood, D. L., Li, J. & Daniel, C. Prospects for reducing the processing cost of lithium ion batteries. J. Power Sources 275, 234–242 (2015). \n30.\t Zimmerman, A. H., Quinzio, M. V. & Monica, S. Adaptive charging method for lithium-ion battery cells. US Patent US6204634B1 (2001). \n31.\t Park, S., Kato, D., Gima, Z., Klein, R. & Moura, S. Optimal experimental design for parameterization of an electrochemical lithium-ion battery model. J. Electrochem. Soc. 165, A1309–A1323 (2018). \n32.\t Smith, J. S., Nebgen, B., Lubbers, N., Isayev, O. & Roitberg, A. E. Less is more: sampling chemical space with active learning. J. Chem. Phys. 148, 241733 (2018). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\n# Experimental \n\nCommercial high-power lithium iron phosphate (LFP)/graphite A123 APR18650M1A cylindrical cells were used in this work (packing date 2015-09-26, lot number EL1508007-R). These cells have a nominal capacity of 1.1 A h and a nominal voltage of 3.3 V. All currents are defined in units of C rate; here, 1C is 1.1 A, or the current required to fully (dis) charge the nominal capacity (1.1 A h) in 1 h. The manufacturer’s recommended fast-charging protocol is 3.6C (3.96 A) CC-CV. The rate capability of these cells is shown in Extended Data Fig. 2. The graphite and LFP electrodes are $40\\upmu\\mathrm{m}$ thick and ${80\\upmu\\mathrm{m}}$ thick, respectively, as quantified via X-ray tomography (Zeiss Xradia 520 Versa). \n\nThe cells were cycled with various charging protocols but identically discharged. Cells were charged with one of 224 candidate six-step, tenminute charging protocols from $0\\%$ to $80\\%$ SOC, as detailed below. After a five-second rest, all cells then charged from $80\\%$ to $100\\%$ SOC with a 1C CC-CV charging step to $3.6\\mathsf{V}$ and a current cutoff of $\\mathbf{C}/20$ . After another five-second rest, all cells subsequently discharged with a CC-CV discharge at 4C to $2.0\\upnu$ and a current cutoff of C/20. The cells rested for another five seconds before the subsequent charging step started. The lower and upper cutoff voltages were 2.0 V and $3.6\\mathsf{V}.$ respectively, as recommended by the manufacturer. In this work, cycle life is defined as the number of cycles until the discharge capacity falls below $80\\%$ of the nominal capacity. \n\nAll cells were tested in cylindrical fixtures with 4-point contacts on a 48-channel Arbin Laboratory Battery Testing battery cycler placed in an environmental chamber (Amerex Instruments) at $30^{\\circ}\\mathrm{C}$ . The cycler calibration was validated before the state of the experiment. \n\nIn the closed-loop experiment, four experiments did not reach 100 cycles owing to contact issues either at the start or partially through the experiment. These experiments were run on channels 17 and 27 in round 1 (oed_0) and channels 4 and 5 in round 2 (oed_1). Additionally, in each round, one protocol per round that should have been selected (that is, with a top-48 upper bound) was not selected and replaced with the protocol with the 49th-highest upper bound owing to a processing error (Extended Data Fig. 4), but this error is not expected to have a large effect. Additional experimental issues are documented in the notes of the data repository. \n\n# Charging protocol and parameter space design \n\nCells were charged with one of 224 different four-step charging protocols. Each of the first four steps is a single constant-current step applied over a $20\\%$ SOC range; thus, the 224 charging protocols represent different combinations of current steps within the $0\\%$ to $80\\%$ SOC range. We can define the charging time from $0\\%$ to $80\\%$ SOC by: \n\n$$\nt_{0-80\\%}={\\frac{0.2}{\\mathrm{CC1}}}+{\\frac{0.2}{\\mathrm{CC2}}}+{\\frac{0.2}{\\mathrm{CC3}}}+{\\frac{0.2}{\\mathrm{CC4}}}\n$$ \n\nIn all protocols considered here, we constrain $t_{0\\cdot80\\%}$ to be 10 min. We now write CC4 as a function of the first three charging steps, as: \n\n$$\n\\mathsf C{C4}=\\frac{0.2}{\\frac{10}{60}-\\left(\\frac{0.2}{\\mathsf C\\mathsf C1}+\\frac{0.2}{\\mathsf C\\mathsf C2}+\\frac{0.2}{\\mathsf C\\mathsf C3}\\right)}\n$$ \n\nThus, each protocol can be uniquely defined by CC1, CC2 and CC3. \n\nEach independent parameter can take on one of the following discrete values: 3.6C, 4.0C, 4.4C, 4.8C, 5.2C and 5.6C. Furthermore, CC1 can take on values of 6.0C, 7.0C and 8.0C, and CC2 can take on values of 6.0C and 7.0C. CC4 is not allowed to exceed 4.81C. The maximum allowable current for each parameter decreases with increasing SOC to avoid reaching the upper cutoff voltage of 3.6 V. With these constraints, a total of 224 charging protocols are permitted. \n\nFor a consistent protocol nomenclature, we define each fast-charging protocol as CC1-CC2-CC3-CC4. For example, the charging protocol with the highest CLO-estimated mean cycle life is written 4.8C-5.2C5.2C-4.160C. \n\n# Early outcome predictor \n\nThe early outcome predictor for cycle life is similar to that presented in Severson et al.5. This linear model predicts the final $\\mathbf{log}_{10}$ cycle life (number of cycles to reach $80\\%$ of nominal capacity, or 0.88 A h) using features from the first 100 cycles. The training set is identical to the one used in Severson et al.5 and consists of 41 batteries. The linear model takes the form: \n\n$$\n\\widehat{y_{i}}=\\widehat{\\mathbf{w}}^{\\mathrm{T}}\\mathbf{x}_{i}\n$$ \n\nHere $\\widehat{y_{i}}$ is the predicted cycle life for battery $i,\\pmb{x}_{i}$ is a $p$ -dimensional feature vector for battery i and $\\widehat{\\mathbf{w}}$ is a $p$ -dimensional model coefficient vector. Features are $z$ -scored (mean-subtracted and normalized by the standard deviation) to the training set before model evaluation. \n\nRegularization, or simultaneous feature selection and model fitting, was performed using the elastic net27. Regularization penalizes overly complex fits to improve both generalizability and interpretability. Specifically, the coefficient vector $\\widehat{\\mathbf{w}}$ is found via the following expression: \n\n$$\n\\widehat{w}=\\mathrm{argmin}_{w}\\bigg[\\|y-X w\\|_{2}^{2}+\\lambda(\\frac{1-\\alpha}{2}\\|w\\|_{2}^{2}+\\alpha\\|w\\|_{1})\\bigg]\n$$ \n\nHere λ and $\\alpha$ are hyperparameters; λ is a non-negative scalar and $\\alpha$ is a scalar between 0 and 1. The first term minimizes the squared loss, and the second term performs both continuous shrinkage and automatic feature selection. During model development, we apply fourfold crossvalidation and Monte Carlo sampling with the training set to optimize the values of the hyperparameters λ and $\\alpha$ . \n\nAs in Severson et al.5, the available features were based on the difference between discharge voltage curves of cycles 100 and 10, or trends in the discharge capacity. The five selected features, their corresponding weights and the $z$ -scored values are presented in Supplementary Table 1. The training (cross-validated) error was 80.4 cycles $(10.2\\%)$ ; the test error on a test set from Severson et al.5 was 122 cycles $(12.6\\%)$ . \n\nThe early predictor automatically flags predictions as anomalous if the $95\\%$ prediction interval exceeds 2,000 cycles. The two-tailed $95\\%$ prediction interval is computed by: \n\n$$\n95\\%\\mathsf{P l}=2t_{(a/2,n-p)}\\times\\mathsf{R M S E}\\sqrt{1+x_{i}^{\\top}(X^{\\top}X)^{-1}x_{i}}\n$$ \n\nwhere $t$ is the Student’s $t$ value, $\\alpha$ is the significance level (0.05 for $95\\%$ confidence), $n$ is the number of samples, $p$ is the number of features, RMSE is the root-mean-square error of the training set (in units of cycles), $x_{i}$ is the vector of selected features for battery i and $\\chi$ is the matrix of selected features for all observations in the training set. \n\nIn the closed-loop experiment, three tests returned predictions with a prediction interval outside of the threshold; these anomalous predictions were excluded. These tests were run on channel 27 in round 1 (oed_0), channel 12 in round 3 (oed_2) and channel 6 in round 4 (oed_3). Furthermore, in the validation experiment, one test returned a prediction with a prediction interval outside of the threshold (channel 12; 3.6C-6.0C-5.6C-4.755C), although the final cycle life was reasonable. \n\nWe note that the predictions from this model exhibited systematic bias for the cells in the validation experiments, which we attribute to the increased calendar ageing of these cells relative to the training set (Supplementary Table 2 and Supplementary Discussion 4). \n\n# Article \n\n# Bayesian optimization algorithm \n\nTo perform optimal experimental design, we consider the setting of best-arm identification using multi-armed bandits. Here each arm is a charging protocol and the goal is to identify the best arm, or equivalently the charging protocol with the highest expected cycle life. Many variants of the problem have been studied in prior work33–35; our algorithm builds on the approaches of Hoffman et al.10 and Grover et al.11. We consider further modifications in Supplementary Discussion 2. \n\nIn particular, we assume a Bayesian regression setting, where there exists an unknown set of parameters $(\\theta\\in R^{d})$ that relate a charging protocol $x$ to its cycle life (a scalar) via a Gaussian likelihood function. Here, $x$ denotes the CC1, CC2, CC3 configurations of a charging protocol, which is projected onto a $d$ -dimensional feature vector $\\varphi(x)$ . We set $d=224$ , and the feature representations $\\varphi(x)$ are obtained by approximating a radial-basis function kernel, $K(x_{i},x_{j})=\\exp(\\gamma\\vert\\vert x_{i}-x_{j}\\vert\\vert_{2}^{2})$ , using Nystroem’s method. Here, $x_{i}$ and $x_{j}$ are the CC1, CC2 and CC3 configurtions for two arbitrary charging protocols and the inverse of the kernel bandwidth, $\\gamma{>}0$ is treated as a hyperparameter. \n\nThe Gaussian likelihood function relates a charging protocol to its cycle life distribution. For a protocol $x_{i}$ , the mean of this likelihood function is given as $\\theta^{\\mathrm{{r}}}\\varphi(x)$ . The variance of this likelihood function is the sum of two uncertainty terms, both of which we assume to be homoskedastic (that is, uniform across all protocols). The first term is the empirical variance averaged across the repeated runs of individual protocols present in the training dataset (same as that used for training the early predictor). This accounts for variability due to exogenous factors such as manufacturing. Second, since we do not wait for an experiment to complete, the likelihood variance additionally needs to accommodate an additional uncertainty term due to the early outcome prediction component of the pipeline. We do so by computing the residual variance of the early predictions on the held-out portion of the dataset and set the aforementioned uncertainty term to be the maximum of the residual variances. We assume that the two sources of uncertainty are independent, and hence the overall variance of the likelihood distribution is given by the sum of the squares of both variance terms described above. \n\nTo perform inference over the unknown parameters $\\theta$ and subsequent predictions of cycle lives, we employ a Gaussian process. In a Gaussian process, the prior over $\\theta$ is assumed to be isotropic Gaussian; such a prior is conjugate to the Gaussian likelihood, and as a consequence the Gaussian posterior can be obtained in closed-form via the Bayes rule. This posterior is used to define a Gaussian predictive distribution over the cycle life for any given charging protocol with mean $\\mu$ and variance $\\sigma^{2}$ . \n\nFinally, to select a charging protocol, we optimize an acquisition function based on upper confidence bounds. The acquisition function selects protocols where the noisy predictive distribution over cycle life has high mean $\\mu$ (to encourage exploitation) and high variance $\\sigma^{2}$ (to encourage exploration). The mean and upper and lower confidence bounds for any arm i is given by $\\mu_{k,i}\\pm\\beta_{k}\\sigma_{k,i}$ at round $k$ , such that the relative weighting of the two terms is controlled by the exploration tradeoff hyperparameter, $\\beta>0$ . The exploration tradeoff hyperparameter at round $k,\\beta_{k},$ is decayed multiplicatively at every round of the closed loop by another hyperparameter, $\\varepsilon\\in(0,1]$ , as given by ${\\beta_{k}}\\mathrm{{=}}{\\beta_{0}}{\\varepsilon^{k}}$ . \n\n# BO hyperparameter optimization \n\nThe BO algorithm relies on eight hyperparameters, each of which can be categorized as either a resource hyperparameter, a parameter space hyperparameter or an algorithm hyperparameter. We note that the BO algorithm runs in the fixed-budget setting; here, the budget refers to the number of iterations of the closed loop we run, excluding validation experiments. We describe each category of hyperparameters below; the values of each hyperparameter are tabulated in Supplementary Table 5. \n\nResource hyperparameters are specified by the available testing resources. The ‘batch size’ represents the number of parallel tests. We set a batch size of 48 given our 48-channel battery cycler. The ‘budget’ represents the number of batches tested during CLO. The budget excludes batches used to develop the early predictor and validation batches. The budget is typically constrained by either the available testing time or the number of cells. In this case, we set a budget of 4, yielding a cell budget of 192 cells and a time budget of 16 days (4 days per batch of 48 cells tested for 100 cycles). \n\nParameter space hyperparameters are specified by the optimization problem. Here, we use the same data available from the training set of the early predictor to estimate these parameters, despite a different charging protocol structure. The ‘standardization mean’ represents the estimated mean cycle life across all protocols. The ‘standardization standard deviation’ represents the estimated standard deviation of cycle life across all protocols; in other words, this parameter represents the range of cycle lives in the parameter space. The ‘likelihood standard deviation’ represents the estimated standard deviation of a single protocol tested multiple times, which is a measure of the sampling error; this sampling error includes both the intrinsic variability and the prediction error. \n\nAlgorithm hyperparameters control the performance of the Bayesian optimization algorithm. γ is the kernel bandwidth, which controls the interaction strength between neighbouring protocols in the parameter space. High γ favours under-smoothing of the parameter space, that is, the protocols have weak relationships with their neighbours. $\\beta_{0}$ represents the initial value of $\\boldsymbol{\\beta}$ , the exploration tradeoff hyperparameter; $\\beta$ controls the balance of exploration versus exploitation. $\\mathsf{H i g h}\\beta_{0}$ favours exploration over exploitation. ε represents the decay constant of beta per round; as the experiment progresses, $\\varepsilon$ shifts towards stronger exploitation (given by $\\beta_{k}=\\beta_{0}\\varepsilon^{k}$ , where $\\beta_{k}$ represents the exploration constant at round $k$ , 0-indexed). High ε favours a rapid transition from exploration to exploitation. \n\nThe algorithm hyperparameters were estimated by creating a physics-based simulator based on the range of cycle lives obtained in the preliminary batch, testing all hyperparameter combinations on the simulator, and selecting the hyperparameter combination with the best performance (that is, that which most consistently obtains the true cycle life). These results are visualized in Extended Data Fig. 9; we note that the performance of BO is relatively insensitive to the selected combination of algorithm hyperparameters, meaning sufficiently high performance can be achieved even with suboptimal algorithm hyperparameters. Other approaches, such as using the early-predictor training dataset, are also possible for optimization of the algorithm hyperparameters (Supplementary Discussion 1). \n\n# Physics-based simulator \n\nWe used a physics-based simulator for hyperparameter optimization; this simulator allows us to estimate the shape and range of cycle lives in the parameter space, although the simulator is not designed to be an accurate representation of battery degradation during fast charging. This finite element simulator was originally designed to estimate the heat generation during charging in an 18650 cylindrical battery by approximating the battery as a long cylinder, which simplifies to a onedimensional radial heat transfer problem. The equations and thermal properties were sourced from Drake et al.36 and Çengel and Boles37. The output from these simulations is a matrix of temperature as a function of both radial position and time. We use total solid-electrolyte interphase (SEI) growth as a proxy for degradation. First, we estimate the temperature dependence of SEI growth from the C/10 series of figure 7 from Smith et al.38 (Supplementary Table 6). Simultaneously, we compute the expected temperature profiles in the battery as a function of charging protocol with respect to time and position. We then approximate the kinetics of SEI growth with an Arrhenius equation, such that SEI growth increases with increasing temperature. SEI growth (in arbitrary units) is calculated for each temperature element in the position-time array via: \n\n$$\n\\scriptstyle D=\\sum_{r}\\sum_{t}\\exp\\left(-{\\frac{E_{\\mathrm{a}}}{k_{\\mathrm{B}}T}}\\right)\n$$ \n\nwhere $D$ is the degradation parameter, $E_{\\mathrm{a}}$ is the effective activation energy for SEI growth (Supplementary Table 6) and $k_{\\mathrm{{B}}}$ is Boltzmann’s constant. The cycle life is then calculated from the degradation parameter using the range of expected cycle lives (as estimated from the early-predictor training dataset): \n\n$$\n\\mathrm{Cycle\\life\\=\\500+}C/D\n$$ \n\nwhere $c$ is a constant $(5\\times10^{-11})$ ) that scales $D$ to reasonable values of cycle life. \n\n# Validation experiments \n\nAfter the closed-loop experiment completed, we selected nine protocols to test to failure (five batteries per charging protocol). This experiment allowed us to (1) evaluate the performance of the closed loop by comparing the CLO-estimated mean cycle lives to the mean cycle life of multiple batteries tested to failure for multiple protocols, (2) compare the protocols with the highest CLO-estimated mean cycle lives to conventional fast-charging protocol design principles from the battery literature, and (3) generate a small dataset with which we can evaluate the performance of the closed loop relative to baseline optimization approaches. \n\nThe selected protocols are displayed in Extended Data Fig. 6 and Extended Data Table 1. Of our nine fast-charging protocols, three were the top three CLO-estimated protocols; four were based on approximations of multi-step fast-charging protocols in the battery literature (see Extended Data Table 1); and two were selected to obtain a representative sampling from the distribution of CLO-estimated cycle lives. The four protocols based on approximations of multi-step fast-charging protocols in the battery literature were obtained by determining the current ratios between various steps and translating those ratios to our ten-minute fast-charging space. The voltage limits were consistent with our charging protocols, that is, 2.0 V and 3.6 V. \n\nFive batteries per charging protocol were tested to obtain a reasonable estimate of the true cycle lives. In this experiment, one test returned a prediction with a prediction interval outside of the threshold (channel 12; 3.6C-6.0C-5.6C-4.755C) and was excluded. A comparison of the three different methods for cycle life results (CLO, early predictions from validation, and final measurements from validation) are presented in Extended Data Fig. 7. \n\n# Validation ablation study \n\nFor the ablation study using the charging protocols and data from the validation experiments, we systematically compared the full closedloop system against three other ablation baselines which use (1) only early prediction (no BO exploration–exploitation, purely random exploration), (2) only BO exploration–exploitation (no early prediction), (3) purely random exploration without any early prediction. As highlighted earlier, since the final cycle lives for the protocols in the validation study have a noticeable bias that can be explained by calendar ageing (Supplementary Discussion 4), we perform a simple additive bias correction for each of the final cycle lives beforehand to suppress any undesirable influence of this bias in interpreting the results. \n\nWe run the four ablation baselines for a varying number of sequential rounds. Since our validation space is relatively small (nine charging protocols, five batteries tested per protocol in our validation dataset), we run only one battery per round (that is, we assume a one-channel battery cycler). The baselines that use BO exploration–exploitation additionally require hyperparameters to be specified before beginning the experiment, as described in the Methods section ‘BO hyperparameter optimization’. The best hyperparameters are chosen separately for each round based on the performance obtained on the physics-based simulator, averaged over 100 random seeds. \n\nWhen an ablation baseline queries for the cycle life of a given charging protocol, the returned value corresponds to one of the five runs in our validation dataset, chosen via random sampling with replacement (that is, bootstrapped). The experimental time cost of this query is equal to 100 cycles for ablation baselines that use early prediction and equals the full cycle life otherwise. Finally, to account for the randomness at the beginning of the experiment (that is, round 0 when every ablation baseline randomly selects a protocol), we report the performance of each ablation baseline averaged over a sequence of 2,000 randomly initialized experiments. To specify the y-axis of Fig. 4e, we assume that each full cycle (charging, discharging, resting) requires one hour of experimental testing. \n\n# Overpotential analysis \n\nTo determine the dependence of overpotential on current and SOC during charging (Extended Data Fig. 2e–f), we perform a pseudo-galvanostatic intermittent titration technique experiment on two minimally cycled batteries and two degraded batteries ( $80\\%$ of nominal capacity remaining). We probe currents ranging from 3.6C to 8C at $20\\%$ , $40\\%$ , $60\\%$ and $80\\%$ SOC, mirroring the current and SOC values used in charging protocol design. In this experiment, we start at an initial SOC $20\\%$ lower than the target, for example, we start at $0\\%$ SOC to probe $20\\%$ SOC. We then charge at a given current rate, for example, 3.6C, until we reach $20\\%$ SOC. The cell rests for 1 h, and then the cell discharges at 1C back to $0\\%500$ . We repeat this sequence for all current values, after which we charge the cell at 1C to the next initial SOC, for example, $20\\%$ SOC to probe $40\\%$ SOC, and repeat for each SOC of interest. \n\nTo compute the overpotential, we compare the voltage at the start and end of the 1-h rest periods. Nearly all of the potential drop occurs immediately $(<100\\mathrm{m}\\mathsf{s})$ after the start of the rest period. Given the linear trends observed (implying ohmic-limited rate capability), we then perform a linear fit on each overpotential-current series. In these fits, the slope represents the ohmic resistance. \n\n# Data availability \n\nThe datasets used in this study are available at https://data.matr.io/1. \n\n# Code availability \n\nThe CLO code, data and figures associated with this manuscript are available at https://github.com/chueh-ermon/battery-fast-chargingoptimization. The data processing and early-prediction code are available at https://github.com/chueh-ermon/BMS-autoanalysis. The charging protocol generation code (automated creation of battery cycler tests) is available at https://github.com/chueh-ermon/automateArbin-schedule-file-creation. \n\n33.\t Shahriari, B., Swersky, K., Wang, Z., Adams, R. P. & de Freitas, N. Taking the human out of the loop: a review of Bayesian optimization. Proc. IEEE 104, 148–175 (2016). \n34.\t Audibert, J.-Y., Bubeck, S. & Munos, R. Best arm identification in multi-armed bandits. In Proc. 23rd Conf. on Learning Theory (COLT) 41–53 (2010); http://certis.enpc.fr/\\~audibert/ Mes%20articles/COLT10.pdf. \n35.\t Srinivas, N., Krause, A., Kakade, S. M. & Seeger, M. W. Information-theoretic regret bounds for Gaussian process optimization in the bandit setting. IEEE Trans. Inf. Theory \n58, 3250–3265 (2012). \n36.\t Drake, S. J. et al. Measurement of anisotropic thermophysical properties of cylindrical Li-ion cells. J. Power Sources 252, 298–304 (2014). \n37.\t Çengel, Y. A. & Boles, M. A. Thermodynamics: An Engineering Approach (McGraw-Hill Education, 2015). \n38.\t Smith, A. J., Burns, J. C., Zhao, X., Xiong, D. & Dahn, J. R. A high precision coulometry study of the SEI growth in Li/graphite cells. J. Electrochem. Soc. 158, A447–A452 (2011). \n39.\t Zhang, S. S. The effect of the charging protocol on the cycle life of a Li-ion battery. J. Power Sources 161, 1385–1391 (2006). \n\n# Article \n\n40.\t Kim, J. M. et al. Battery charging method and battery pack using the same. US Patent Application US20160226270A1 (2016). \n41.\t Lee, M.-S., Song, S.-B., Jung, J.-S. & Golovanov, D. Battery charging method and battery pack using the same. US Patent US9917458B2 (2018). \n42.\t Notten, P. H. L., Op het Veld, J. H. G. & van Beek, J. R. G. Boostcharging Li-ion batteries: a challenging new charging concept. J. Power Sources 145, 89–94 (2005). \n43.\t Paryani, A. Low temperature charging of Li-ion cells. US Patent US8552693B2 (2013). \n44.\t Mehta, V. H. & Straubel, J. B. Fast charging with negative ramped current profile. US Patent US8643342B2 (2014). \n\nAcknowledgements This work was supported by the Toyota Research Institute through the Accelerated Materials Design and Discovery programme. P.M.A. was supported by the Thomas V. Jones Stanford Graduate Fellowship and the National Science Foundation Graduate Research Fellowship under grant number DGE-114747. A.G. was supported by a Microsoft Research PhD Fellowship and a Stanford Data Science Scholarship. N.P. was supported by the SAIC Innovation Center through the Stanford Energy 3.0 industry affiliates programme. S.J.H. was supported by the Assistant Secretary for Energy Efficiency, Vehicle Technologies Office of the US Department of Energy under the Advanced Battery Materials Research Program. X-ray tomography was performed at the Stanford Nano Shared Facilities, supported by the National Science Foundation under award ECCS-1542152. We thank A. Anapolsky, L. Attia, C. Cundy, J. \n\nHirshman, S. Jorgensen, G. McConohy, J. Song, R. Smith, B. Storey and H. Thaman for discussions. \n\nAuthor contributions P.M.A., N.J., Y.-H.L., M.H.C., N.P. and W.C.C. conceived and conducted the experiments. A.G., T.M.M., B.C. and S.E. developed the Bayesian optimization algorithm and incorporated early outcome predictions into the closed loop. P.M.A. and K.A.S. performed the early-prediction modelling. P.M.A., Z.Y., P.K.H. and M.A. performed data management. P.M.A., A.G., N.J., S.J.H., S.E. and W.C.C. interpreted the results. All authors edited and reviewed the manuscript. R.D.B., S.E. and W.C.C. supervised the work. \n\nCompeting interests S.E., W.C.C., A.G., T.M.M., N.P. and P.M.A. have filed a patent application related to this work: US Patent Application No. 16/161,790 (16 October 2018). \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41586-020- 1994-5. Correspondence and requests for materials should be addressed to R.D.B., S.E. or W.C.C. Peer review information Nature thanks Marius Bauer, Matthias Seeger and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/557c8aa9a21d61fbae9f05477748cfaec8746bc3a3731aebc1a3aecfff2a259d.jpg) \n\nExtended Data Fig. 1 | Illustrations of early outcome predictor and BO components of CLO. a, Illustration of early outcome prediction for two cells (A and B) using data from only the first 100 cycles. Two discharge capacity features are generated: the second-cycle discharge capacity, $Q_{\\mathrm{d},2}^{}$ , and the difference between the maximum and second-cycle discharge capacities, $\\boldsymbol{\\mathrm{max}}(Q_{\\mathrm{d}})-Q_{\\mathrm{d},2}$ . Three voltage features are generated: the logarithm of the minimum, variance and the skewness of the difference in voltage curves between cycles 100 and 10. These five features are combined in a linear model to predict the final cycle life, or the number of cycles until the capacity falls below 0.88 A h. The weights and scalings of each feature are determined by training the model on a training set using the elastic net; the weights and scaling values are presented in Supplementary Table 1. See Severson et al.7 and \n\nMethods for additional details. b, Illustration of the BO principle. The desired output, cycle life, has a true functional dependence on charging protocol parameters (such as CC1). Here, we show a one-dimensional model (that is, just dependent on one parameter, CC1) for simplicity. By performing Gaussian process regression on the available data, we develop a probabilistic estimate of the true function; our goal is for the estimate to match the true function. The next data point selected is that which maximizes the upper confidence bound (UCB), which is selected by either high uncertainty (exploration) or high predicted value (exploitation). Once this point is selected (right panel), the next point selected is, again, that which maximizes the upper confidence bound. \n\n![](images/186fc6bd659a7db1145d122afcbc5f37e77c09bbf22e2d735547dcb76ff6e7ed.jpg) \nExtended Data Fig. 2 | Cell characterization. a, b, Voltage versus capacity during rate testing of A123 18650M1A cylindrical cells under charge (a) and discharge (b). The (dis)charge step not under investigation is cycled at 1C to isolate the rate of each step; for example, the charge rate test is performed with 1-C discharge steps. We note that the discharge rate capability is much higher than that of charge. c, d, Battery surface temperature (‘can temperature’) versus capacity during rate testing under charge (c) and discharge (d). The can temperature is measured via a type T thermocouple secured with thermal \nepoxy. e, f, Overpotential as a function of SOC and C rate (see Methods section ‘Overpotential analysis’ for details of the measurement) for a minimally cycled cell (e) and an aged cell at $80\\%$ of nominal capacity (f). The trend lines are linear fits of the overpotential as a function of current at fixed SOC (excluding outliers). We note that both of the relationships are linear (indicating that the rate capability is ohmically limited) and that the SOC dependence is weak, particularly for the minimally cycled cell. The initial internal resistance, averaged over two cells and all four SOCs, is $33\\mathsf{m}\\Omega$ . \n\n![](images/93d90fea3e445b57de4bf4072360d4aa42d3ebcd20e469f73dfc434605963414.jpg) \nExtended Data Fig. 3 | Additional optimization results. a, b, Mean of the absolute difference in CLO-estimated cycle lives with increasing rounds, expressed as both percentage change (a) and absolute change (b). These changes are relatively small beyond round 2, suggesting that the closed loop can perform well with even smaller time or battery budgets. c, Change in Kendall rank correlation coefficient with increasing rounds. From round 3 to round 4, the ranking of the top protocols shifts, but the cycle lives of these top protocols are similar. d, Distribution of CLO-estimated mean cycle lives after round 4. The mean and standard deviation are 943 cycles and 126 cycles, respectively. e, Correlation between CLO-estimated mean cycle lives and the sum of squared currents, a simplified measure of heat generation $(P=I^{2}R)$ . This relationship suggests that minimizing heat generation, as opposed to avoiding \nlithium plating, may be the operative optimization strategy for these cells under these conditions. f, Standard deviation $(\\sigma_{4,i})$ versus mean $(\\mu_{4,i})$ of the BO predictive distribution over cycle life after round 4. The standard deviation quantifies the uncertainty in the cycle life estimates and is generally low for protocols estimated to have high mean cycle life, since these protocols are probed more frequently. We start with a relatively wide, flat prior (standard deviation 164) and therefore the uncertainty intervals after four rounds are also wide. g, Mean $\\pm$ standard deviation of the predictive distribution over cycle life after round 4 $(\\mu_{4,i}\\pm\\sigma_{4,i})$ for all charging protocols, sorted by their rank after round 4. The legend indicates the number of repetitions for each protocol (excluding failed batteries). \n\n![](images/222a20753cccbe00023eed36b07269bd8cbff88a824b66c1dc7c3c90bfaf72db.jpg) \n\nExtended Data Fig. 4 | See next page for caption. \n\nExtended Data Fig. 4 | Means and upper/lower confidence bounds $(\\pmb{\\mu}_{k,i}\\pmb{\\beta}_{k}\\pmb{\\sigma}_{k,i})$ on cycle life per round k. Protocol indices on the x-axis are sorted by rank after round 4. The weighted interval around the estimated mean, $\\beta_{k}\\sigma_{k,i}\\mathrm{=}(\\beta_{0}\\varepsilon^{k})\\sigma_{k,i},$ weights the protocol-specific standard deviation at round $k$ , $\\sigma_{k,i}$ (estimated by the Gaussian process model) with the exploration tradeoff hyperparameter at round $k,\\beta_{k}$ . The upper and lower confidence bounds are plotted for all charging protocols before round 1 (a) and after rounds 1 (b), 2 (c), 3 (d) and 4 (e). The predictive distributions for all charging protocols have identical means and standard deviations before the first round of testing. Because the standard deviations are weighted by $\\beta_{k}{=}\\beta_{0}\\varepsilon^{k}$ and $\\scriptstyle{\\varepsilon=0.5}$ , the \n\nweighted confidence bounds rapidly decrease with increasing round number, favouring exploitation (examination of protocols with high means). The BO algorithm recommends the 48 protocols with the highest upper bounds (red points); the upper bounds are high either due to high uncertainty (exploration) or high means (exploitation). The algorithm rapidly shifts from exploration to exploitation as $\\scriptstyle{\\varepsilon_{k}}$ rapidly shrinks the upper bounds with increasing round index. We note that one protocol per round that should have been selected (that is, with a top-48 upper bound) was not selected owing to a processing error; instead, the protocol with the 49th-highest upper bound was selected. \n\n![](images/90d8cce5d47ad87a047f9db8ac8c6926b6080f3cbd415daea8acae788e9f9d87.jpg) \nExtended Data Fig. 5 | Mean and standard deviation of the CLO-estimated $\\mathsf{C C3}=3.6\\mathsf{C}$ , 4.0C, 4.4C, 4.8C, 5.2C, 5.6C and 6.0C, respectively. CC4 is predicted distribution over cycle lives after round 4. In this two-dimensional represented by the contour lines. Note that the protocols with the highest cycle representation, mean estimated cycle life (colour scale) and standard deviation lives generally have the smallest standard deviations, since these protocols of cycle life (marker size) after round 4 are presented as a function of CC1, CC2 have been tested repeatedly. and CC3 (the x axis, y axis and panels a–f, respectively). Panels a–f represent \n\n![](images/a33d5d83462f16cf5c5f50c8b18c453daff0270a11b9fe21bdb04b7574cfcc80.jpg) \nExtended Data Fig. 6 | Selected protocols for validation. The three protocols with the highest CLO-estimated mean cycle lives are shown in panels b, c and d. The protocols shown in panels a, f, g and h are approximations of previously proposed battery fast-charging protocols (Extended Data Table 1). The remaining two protocols, shown in panels e and i, were selected to obtain a representative sampling from the entire distribution of CLO-estimated cycle lives. The annotations on each panel represent the cycle lives of each protocol \nas estimated by CLO (‘CLO’), early outcome prediction from validation (‘Early prediction’), and the final cycle lives from validation (‘Final’). In the annotations, the errors represent the CLO-estimated standard deviation after round 4 $(\\sigma_{k,4})$ for the CLO-estimated cycle lives and the $95\\%$ confidence intervals for the early-predicted and final cycle lives from validation $\\scriptstyle(n=5;n=4$ for the early predictions of 3.6C-6.0C-5.6C-4.755C) (a). \n\n![](images/d97748526ed42451da7be97b085bf855a44740217d5ee266f676e14a345196d1.jpg) \n\nExtended Data Fig. 7 | Validation ablation analysis. We perform pairwise comparisons of the cycle lives of the nine validation protocols, as estimated from three sources: closed-loop estimates after four rounds, early predictions from the validation experiment and final cycle lives from the validation experiment. Panels a–c compare closed-loop estimates to early predictions from validation, panels d–f compare final cycle lives from validation to early predictions from validation, and panels g–i compare final cycle lives from validation to closed-loop estimates. The first column (a, d and g) compares cycle lives averaged on a protocol basis; the second column (b, e and h) \n\ncompares cycle lives on a battery (cell) basis; and the third column (c, f and i) compares the predicted ranking by cycle life via each method. Orange points represent the top three CLO-estimated protocols, blue points represent protocols inspired by the battery literature (Methods), and green points represent protocols selected to sample the distribution of estimated cycle lives. The error bars represent the $95\\%$ confidence intervals $(n=5;n=4$ for the early predictions of 3.6C-6.0C-5.6C-4.755C). The Pearson correlation coefficient and Kendall rank correlation coefficients are displayed for all relevant cycle life and ranking plots, respectively. \n\n![](images/bfd9bf3550e5661e183903ae566ee71c65475e9d37a050671c9a5a71e38e3830.jpg) \n\nExtended Data Fig. 8 | Closed-loop performance under resource constraints. Comparison of the closed loop with and without the Bayesian optimization algorithm (that is, with and without the explore/exploit component) as a function of number of channels and number of rounds in the 224-protocol space, using the first-principles simulator as the ground-truth source for cycle lives. Early prediction is not included. Each point represents the mean of 100 simulations; error bars represent the $95\\%$ confidence intervals $(n=100)$ ). Early prediction is not incorporated into these simulations. The complete closed loop (that is, with Bayesian optimization) consistently outperforms the closed loop without Bayesian optimization. Bayesian optimization offers the largest advantage when the number of channels is low relative to the number of protocols. \n\n# Article \n\n![](images/d62d259a02f63e1715b3d01d93d1c670641bddc07b134750f3e640d5bf509d58.jpg) \nExtended Data Fig. 9 | Hyperparameter sensitivity analysis on a cycle life simulator. The true cycle life of the best charging protocol as estimated by CLO, averaged over ten random seeds, is plotted as a function of the initial exploration constant $(\\beta_{0})$ , the exploration decay factor (ε) and the kernel bandwidth $(\\gamma)$ . The values of all other hyperparameters are consistent with the values indicated in the ‘BO hyperparameter optimization’ Methods section and \n\nin Supplementary Table 5. Overall, CLO achieves acceptable performance over a range of hyperparameter combinations; the highest-cycle-life protocols as estimated by the best and worst hyperparameter combinations differ by only 60 cycles. In our real-world CLO experiment, the selected hyperparameters are $\\beta_{0}=5.0,\\varepsilon=0.5$ and $\\gamma=1_{\\AA}$ ; this combination performed well on a variety of simulated parameter spaces and budgets. \n\nExtended Data Table 1 | Selected charging protocols for validation \n\n\n
Charging protocolCLO-estimated cycle lifeEarly-predicted cyl life fromFinal cycle life valfration)Source
3.6C-6.0C-5.6C- 4.755C1103 ± 1311013 ± 115755 ±81 Zhang39
4.4C-5.6C-5.2C- 4.252C1174 ± 761056 ± 127884± 132Protocol with third-highest CLO-estimated mean cycle life
4.8C-5.2C-5.2C- 4.160C1185 ± 781047 ± 49890 ± 90Protocol with highest CLO- estimated mean cycle life
5.2C-5.2C-4.8C- 4.160C1183 ± 861098 ± 134912 ±118Protocol with second-highest CLO-estimated mean cycle life
6.0C-5.6C-4.4C- 3.834C954 ± 164963 ± 26880±85
7.0C-4.8C-4.8C- 3.652C876 ± 183964± 43870 ± 70Samsung patents40,41
8.0C-4.4C-4.4C- 3.940C818± 212854 ± 44702 ± 51Notten et al.42
8.0C-6.0C-4.8C- 3.000C775 ±273698 ± 40584± 60Tesla patents43,44
8.0C-7.0C-5.2C- 2.680C648 ± 174580± 68496 ± 49
\n\nThe columns represent the CLO-estimated mean cycle lives of each protocol, early predictions in the validation experiment and the final tested cycle lives. For the CLO-estimated cycle lives, the errors represent the CLO-estimated standard deviation after round 4 $(\\sigma_{k,4})$ . For the early-predicted and final cycle lives from validation, the errors represent $95\\%$ confidence intervals $(n=5;$ but $n=4$ for the early predictions of 3.6C-6.0C-5.6C-4.755C). The two protocols without a source were selected to obtain a representative sampling from the distribution of CLO-estimated cycle lives. Literature fast-charging protocols are from refs. 39–44. " + }, + { + "id": "10.1038_s41377-020-0326-8", + "DOI": "10.1038/s41377-020-0326-8", + "DOI Link": "http://dx.doi.org/10.1038/s41377-020-0326-8", + "Relative Dir Path": "mds/10.1038_s41377-020-0326-8", + "Article Title": "Strategies to approach high performance in Cr3+-doped phosphors for high-power NIR-LED light sources", + "Authors": "Jia, ZW; Yuan, CX; Liu, YF; Wang, XJ; Sun, P; Wang, L; Jiang, HC; Jiang, J", + "Source Title": "LIGHT-SCIENCE & APPLICATIONS", + "Abstract": "Optics: Visibly powerful near-infrared light-emitting diodes A near-infrared light-emitting (NIR-LED) diode that emits high-power light could pave the way for the development of next-generation monitoring and detecting devices. Although solid-state NIR-LEDs are used in such devices, their narrow emission band limits their range of applications. Broadband NIR-emitting phosphor-converted LEDs offer the best solution. However, creating NIR phosphors that are sufficiently excited by blue light is challenging. Now, a team of Chinese and American researchers, led by Yongfu Liu from the Chinese Academy of Sciences, has created a NIR-LED that emits light in the 700-900 nm with an output of 109.9 mW at 520 mA after excitation with blue light. The device has the highest recorded power rating to date and could be used in applications from bioimaging and night-vision technologies, to monitoring food and medicines. Broadband near-infrared (NIR)-emitting phosphors are key for next-generation smart NIR light sources based on blue LEDs. To achieve excellent NIR phosphors, we propose a strategy of enhancing the crystallinity, modifying the micromorphology, and maintaining the valence state of Cr3+ in Ca3Sc2Si3O12 garnet (CSSG). By adding fluxes and sintering in a reducing atmosphere, the internal quantum efficiency (IQE) is greatly enhanced to 92.3%. The optimized CSSG:6%Cr3+ exhibits excellent thermal stability. At 150 degrees C, 97.4% of the NIR emission at room temperature can be maintained. The fabricated NIR-LED device emits a high optical power of 109.9 mW at 520 mA. The performances of both the achieved phosphor and the NIR-LED are almost the best results until now. The mechanism for the optimization is investigated. An application of the NIR-LED light source is demonstrated.", + "Times Cited, WoS Core": 561, + "Times Cited, All Databases": 587, + "Publication Year": 2020, + "Research Areas": "Optics", + "UT (Unique WOS ID)": "WOS:000533075300001", + "Markdown": "# Strategies to approach high performance in Cr3+-doped phosphors for high-power NIR-LED light sources \n\nZhenwei Jia1,2, Chenxu Yuan1,3, Yongfu Liu 1, Xiao-Jun Wang4, Peng Sun1, Lei Wang2, Haochuan Jiang1 and Jun Jiang1 \n\n# Abstract \n\nBroadband near-infrared (NIR)-emitting phosphors are key for next-generation smart NIR light sources based on blue LEDs. To achieve excellent NIR phosphors, we propose a strategy of enhancing the crystallinity, modifying the micromorphology, and maintaining the valence state of $C r^{3+}$ in $\\mathsf{C a}_{3}\\mathsf{S c}_{2}\\mathsf{S i}_{3}\\mathsf{O}_{12}$ garnet (CSSG). By adding fluxes and sintering in a reducing atmosphere, the internal quantum efficiency (IQE) is greatly enhanced to $92.3\\%$ . The optimized $C S S G{:}6\\%C r^{3+}$ exhibits excellent thermal stability. At $150^{\\circ}C,$ $97.4\\%$ of the NIR emission at room temperature can be maintained. The fabricated NIR-LED device emits a high optical power of $109.9\\mathsf{m W}$ at $520\\mathrm{mA}$ The performances of both the achieved phosphor and the NIR-LED are almost the best results until now. The mechanism for the optimization is investigated. An application of the NIR-LED light source is demonstrated. \n\n# Introduction \n\nNIR spectroscopy has good penetration for organic matter, and it has drawn attention for application in monitoring foods and medicines, bioimaging, and night vision1–6. Smart NIR light sources, an emerging field, are proposed to be combined with smart phones to achieve convenient and fast applications7–9. In contrast to traditional tungsten filament lamps and halogen lamps, only light-emitting diodes (LEDs) that have a solid state and a small size are suitable for smart NIR devices. However, NIR-LED chips can only give narrow NIR emissions, which limits their applications10–12. Broad NIR-emitting phosphor-converted (pc) LEDs, adopting the technology of pc-white LEDs13–19, are believed to be the best solution. White LEDs are commonly based on blue-LED chips. Thus, how to achieve broad NIR phosphors that can be efficiently excited by blue light is one of the most important challenges20. \n\nRecently, a number of NIR phosphors were realized21–44. Among them, ${\\mathrm{Cr}}^{3+}$ usually manifests a high efficiency, and the IQE can reach $58-\\dot{7}5\\%^{31-37}$ . The radiant power is $14.7{-}54.29\\mathrm{mW}$ when driven at $100{-}130\\mathrm{mA}^{34-40}$ . A high radiant power is beneficial for monitoring and detection. Liu et al made great progress in improving the radiant power, which was enhanced from $7{-}18.2\\mathrm{mW}^{42,43}$ to $65.2\\mathrm{mW}^{44}$ when driven at $350\\mathrm{mA}.$ To achieve high radiance, a highpower LED chip operating at a high current is usually needed. In this situation, the large amount of heat will result in a high temperature on the surface of the chip. Thus, the greatest challenge is how to make NIR phosphors have excellent thermal stability to overcome the thermal quenching effect, in addition to a high QE for NIR phosphors. \n\nWe note that ${\\mathrm{Cr}}^{3+}$ has a high QE in garnets34,35. The silicate garnet $\\mathrm{Ca_{3}S c_{2}S i_{3}O_{12}}$ (CSSG) is a promising host for $\\mathrm{Ce}^{3+}$ due to its excellent thermal stability and high $\\mathrm{QE^{45-47}}$ . Fortunately, ${\\mathrm{Cr}}^{3+}$ can be excited by blue light and show broadband NIR emission in $\\mathrm{CSSG^{39}}$ . Unfortunately, the reported luminescence (IQE: $12.8\\%$ ) and thermal stability were low because the ${\\mathrm{Cr}}^{3+}$ luminescence suffered from impurities and oxidation of ${\\mathrm{Cr}}^{4+}$ when the material was sintered in air39. Based on our previous experience, we propose a strategy to optimize $\\mathrm{CSSG}{\\mathrm{:Cr}}^{3+}$ by enhancing the crystallinity, modifying the micromorphology, and maintaining the valence state of ${\\mathrm{Cr}}^{3+}$ . By adding fluxes and sintering in a CO reducing atmosphere, the IQE is greatly enhanced to $92.3\\%$ . At $150^{\\circ}\\mathrm{C},$ $97.4\\%$ of the NIR emission at room temperature can be maintained, indicating excellent thermal stability. When combined with a high-power $460\\mathrm{nm}$ blue chip, the estimated radiant power of the fabricated pcLED even reaches $109.9\\mathrm{mW}$ when driven at $520\\mathrm{mA}.$ . The properties of both the optimized $\\mathrm{CSSG{:}C r^{3+}}$ and the achieved NIR-LED are almost the best results to date as far as we know. Benefiting from the high radiant power, the pcNIR-LED device has good application potential in nightvision technology. \n\n![](images/27fb2f92b65c5f1737eaa5eaedab6e66fa6b5d6f651a14f2866d6d7ead2f023b.jpg) \nFig. 1 Optimization of the NIR emission. a Coordination of $({\\mathsf{S c}}/{\\mathsf{C r}}){\\mathsf{O}}_{6}$ in CSSG. b Photoluminescence (PL) and photoluminescence excitation (PLE) spectra of $C S S G3\\%C r^{3+}$ . c Relative PL intensities of the samples with and without fluxes sintered in air and a CO atmosphere. d PL intensities of $C S S G3\\%C r^{3+},$ , xwt% $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ $(\\chi=0.5$ , 0.8, 1, 1.5, 2, 3, 4, 5, 6). e PL intensities of $C{\\sf S S G}{\\mathrm{;}}y\\%C{\\sf r}^{3+}$ , $1\\mathrm{wt\\%}$ $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ $(y=1,2,3,4,5,6)$ . \n\nIn this work, mechanisms for optimization were investigated. The electron–phonon coupling (EPC) mechanism in CSSG that usually determines the ${\\dot{\\mathrm{Cr}}}^{3+}$ luminescence is revealed for the first time. Many types of ${\\mathrm{Cr}}^{3+}$ -doped NIR phosphors have been discovered. We believe that this work provides an effective strategy to optimize and discover more ${\\mathrm{Cr}}^{3+}$ -doped NIR phosphors using only a simple method. Moreover, this work will advance the development and application of next-generation smart NIR light sources. \n\n# Results \n\n# Optimization of CSSG:Cr3+ \n\nCSSG belongs to a cubic crystal system with the space group of Iα3d (Fig. S1). Ca, Sc, and Si are coordinated with 8, 6, and 4 oxygen atoms, respectively $45\\substack{-47}$ . Considering the effective ionic radii of Ca2+ (1.12 Å), Sc3+ $(0.745\\:\\mathrm{\\AA})$ , ${\\mathrm{Si}}^{4+}$ $(0.26\\mathring\\mathrm{A})$ , and ${\\mathrm{Cr}}^{3+}$ $(r=0.615\\mathrm{\\AA})$ , it is believed that ${\\mathrm{Cr}}^{3+}$ occupies the $\\sec^{3+}$ site due to the close radii and same ionic valence39. Thus, ${\\mathrm{Cr}}^{3+}$ suffers from a weak crystal field (CF) environment in the $\\mathrm{ScO}_{6}$ octahedron (Fig. 1a). The spin-allowed transitions of $^{4}\\mathrm{{A_{2g}}\\rightarrow^{4}}$ $\\mathrm{T_{1g}(^{4}F)}$ and $^4\\mathrm{{A_{2g}\\to^{4}T_{2g}(^{4}F)}}$ lead to two excitation bands centered at 460 and $640\\mathrm{nm}$ , respectively (Fig. 1b). The spin-forbidden transition of $\\mathrm{^4A_{2g}}\\rightarrow\\mathrm{^2Eg}(\\mathrm{^2G})$ (R-line) at ${\\sim}701\\mathrm{nm}$ is also detected. Under $460\\mathrm{nm}$ excitation, $\\mathrm{CSSG}{\\mathrm{:Cr}}^{3+}$ shows a broad NIR emission peaking at ${\\sim}770\\mathrm{nm}$ with a full-width at half maximum (FWHM) value of $\\sim1750\\mathrm{cm}^{-1}$ $(\\sim110\\mathrm{nm})$ , arising from the ${^4\\mathrm{T}}_{2\\mathrm{g}}(^{4}\\mathrm{F})$ to $^{4}\\mathrm{{A}_{2}}$ transition of ${\\mathrm{Cr}}^{3+}$ in the weak CF. \n\n$\\mathrm{CSSG}{\\mathrm{:Cr}}^{3+}$ synthesized in an air atmosphere exhibits a weak NIR emission (Figs. S2–5), which could be attributed to a lower crystallinity and oxidation of $\\mathrm{Cr}^{3+39}$ . For the optimized ${\\mathrm{Cr}}^{3+}$ concentration, that is, $\\mathrm{CSSG}{:}3\\%\\mathrm{Cr}^{3+}$ , its IQE and external quantum efficiency (EQE) are quite low, only ${\\sim}12.8\\%$ and $4.8\\%$ , respectively (Fig. S6). To enhance the luminescence by improving the crystallinity, fluxes of $\\mathrm{\\DeltaNH_{4}F}$ , $\\mathrm{CaF}_{2}$ , $\\mathrm{H}_{3}\\mathrm{BO}_{3},$ LiF, and $\\mathrm{Li_{2}C O_{3}}$ were added during the synthesis under the air condition. The NIR emission of the flux-free sample was set as the normalized standard. As Fig. 1c shows, $\\mathrm{H_{3}B O_{3}}$ , LiF, and $\\mathrm{Li_{2}C O_{3}}$ enhance the luminescence, while $\\mathrm{\\DeltaNH_{4}F}$ and $\\mathrm{CaF}_{2}$ decrease the luminescence. Thus, $\\mathrm{H_{3}B O_{3}}$ , LiF, and $\\mathrm{Li_{2}C O_{3}}$ were selected, and $\\mathrm{CSSG}{:}3\\%\\mathrm{Cr}^{3+}$ was sintered in a CO reducing atmosphere to further maintain the state of ${\\mathrm{Cr}}^{3+}$ . It is noted that the luminescence is greatly enhanced by $2{\\sim}3$ times. $\\mathrm{Li_{2}C O_{3}}$ has the best effect, and the optimal amount is $1\\mathrm{wt\\%}$ (Fig. 1d). Correspondingly, the IQE and EQE of $\\mathrm{CSSG}{:}3\\%\\mathrm{Cr}^{3+}$ reach $\\sim77.8\\%$ and $15.5\\%$ , respectively. Moreover, by adding $1\\mathrm{wt\\%}$ $\\mathrm{Li_{2}C O_{3}}$ and sintering in CO, the ${\\mathrm{Cr}}^{3+}$ concentration is optimized to $6\\%$ (Fig. 1e). Then, the achieved EQE of $\\mathrm{CSSG}{:}6\\%\\mathrm{Cr}^{3+}$ even reaches $21.5\\%$ . Here, the QE is the measured result. Due to the limitation of the measurement, up to $850\\mathrm{nm}$ , the results are smaller than the actual values, which will be illustrated later. Therefore, the actual QE is almost the best value among NIR phosphors as far as we know. \n\n# Crystal structures and micromorphology \n\nTo clarify the enhancement of the optimized $\\mathrm{CSSG}{\\mathrm{:Cr}}^{3+}$ compared with the initial phosphor, the crystal structures and micromorphology were studied. For $\\mathrm{CSSG}{:}3\\%\\mathrm{Cr}^{3+}$ sintered in air (Fig. 2a), the X-ray diffraction (XRD) pattern mainly shows a garnet phase of CSSG (PDF # 72-1969), but a few impurity phases of $\\mathrm{SiO}_{2}$ and $\\mathrm{Sc}_{2}\\mathrm{O}_{3}$ are also observed. These impurity phases can also be observed in the SEM-EDS mapping images. Ca, Sc, Si, O, and $C\\mathrm{{r}}$ are inhomogeneously distributed in the square region, in which Sc is rich and Si and $C\\mathrm{{a}}$ are absent. \n\nFor $\\mathrm{CSSG}{:}3\\%\\mathrm{Cr}^{3+}$ sintered in CO with $1\\mathrm{wt\\%}$ $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ (Fig. 2b), the $\\mathrm{SiO}_{2}$ and $\\mathrm{Sc}_{2}\\mathrm{O}_{3}$ impurities are quite low in the XRD pattern. The distributions of elements are more homogeneous. In addition, the diffraction peak intensity of the CSSG phase increases (Fig. 2c). These results demonstrate that the enhanced crystallinity of the CSSG phase is one of the reasons for the improvement of the ${\\mathrm{Cr}}^{3+}$ NIR emissions. \n\nThe $\\mathrm{CSSG3^{\\circ}/\\mathrm{\\Omega}}0\\mathrm{Cr}^{3+}$ phosphor has a particle size of ${\\sim}10\\upmu\\mathrm{m}$ (Fig. 2d). The particle displays a small variation in the cathodoluminescence (CL), as the $\\mathrm{CL}$ image shows. The bright region (point I) and the dark region (point II) are only different in CL intensity. Their normalized CL spectra are almost the same, having an emission peak at ${\\sim}760\\mathrm{nm}$ and an FWHM of $1583{-}1590\\mathrm{cm}^{-1}$ $(93-94\\mathrm{nm})$ , similar to the photoluminescence (PL) spectrum in Figs. S2–S5. \n\n# Diagnosis of the valence state of $\\mathsf{C r}^{3+}$ \n\nTo diagnose the change in the ionic valence of Cr, X-ray photoelectron spectroscopy (XPS), diffuse reflection (DR), and electron paramagnetic resonance (EPR) results for $\\mathrm{CSSG}{:}3\\%\\mathrm{Cr}^{3+}$ sintered in air and CO are given in Fig. 3. The binding energies at 99, 344, 399, and $528\\mathrm{eV}$ are from Si-2p, Ca-2p, Sc-2p, and O-1s, respectively. The binding energy at $40\\mathrm{eV}$ for $\\mathrm{Cr-}3\\mathrm{p}$ is detected in the two samples48. The changes in $\\mathrm{Cr}$ are not apparent in the XPS spectra. However, in the DR spectra (Fig. 3c), the absorption band of ${\\mathrm{Cr}}^{4+}$ (at ${\\sim}1140\\mathrm{nm},$ is clearly identified for the sample sintered in air in addition to the absorption band of ${\\mathrm{Cr}}^{3+}$ (at $\\mathord{\\sim}460$ and ${640\\mathrm{nm}})^{34,35}$ . This means that some ${\\mathrm{Cr}}^{3+}$ ions are oxidized into ${\\mathrm{Cr}}^{4+}$ even though $\\mathrm{Cr}_{2}\\mathrm{O}_{3}$ is used as the raw material. For the sample sintered in CO, the ${\\mathrm{Cr}}^{4+}$ absorption band almost disappears, and only the ${\\mathrm{Cr}}^{3+}$ absorption band is observed. This means that ${\\dot{\\mathrm{Cr}}}^{3+}$ is well maintained in the CO reducing atmosphere. \n\nIn the $\\mathrm{3d^{3}}$ electronic configuration of ${\\mathrm{Cr}}^{3+}$ , three electrons occupy the $\\mathrm{~d~}$ orbitals and give rise to a total spin of $S=3/2$ . $^{4}\\mathrm{{A_{2g}(F)}}$ is the ground state for ${\\mathrm{Cr}}^{3+}$ . In an octahedral crystal field, the $\\mathrm{{^4F}}$ state splits into a singlet orbital $^{4}\\mathrm{A}_{2\\mathrm{g}}$ and two orbitals $^4\\mathrm{T}_{1\\mathrm{g}}$ and $^4\\mathrm{T}_{2\\mathrm{g}},$ thus causing EPR signals49. As Fig. 3d shows, the sharp peaks at $g=3.8\\mathrm{-}3.9$ belong to the isolated ${\\mathrm{Cr}}^{3+}$ ion, and the peaks at approximately $g=2$ represent the first neighbor ${\\mathrm{Cr}}^{3+}$ $-\\mathrm{\\bar{Cr}^{3+}\\ p a i r^{42-44,49}}$ . The EPR intensity for the sample sintered in CO is stronger than that for the sample sintered in air, demonstrating an increased ratio of ${\\dot{\\mathrm{Cr}}}^{3+}$ . Combining the DR and EPR results, it is claimed that ${\\mathrm{Cr}}^{3+}$ can be maintained and increased in the reducing atmosphere, which is another reason for the improvement of the ${\\mathrm{Cr}}^{3+}$ NIR luminescence. \n\n# Temperature-dependent NIR emissions \n\nFigure $4\\mathsf{a}-\\mathsf{c}$ shows the temperature-dependent luminescence of $\\mathrm{CSSG}{:}6\\%\\mathrm{Cr}^{3+}$ . The integrated PL intensity at $25^{\\circ}\\mathrm{C}$ is set as the normalized standard, and $97.4\\%$ can still be maintained at $150^{\\circ}\\mathrm{C}$ for the phosphor sintered in CO, whereas $85.6\\%$ can be maintained for the phosphor sintered in air. The temperature dependence of the emission intensity can be well fitted by the Arrhenius formula, and the activation energy is calculated to be ${\\Delta E=0.336\\mathrm{eV}}$ for the optimized sample, compared with $\\Delta E=0.220\\mathrm{eV}$ for the initial sample (Fig. 4b). When the temperature increases from 25 to $300^{\\circ}\\mathrm{C},$ the peak position redshifts from ${\\sim}783$ to ${\\sim}807\\mathrm{nm}$ (Fig. 4d), attributed to the decreased CF caused by lattice expansion. The FWHM increases from 1483 to $1551\\mathrm{cm}^{-1}$ (92.3 to $100.2\\mathrm{nm},$ , attributed to the strengthened EPC effect that will be discussed in the following. \n\nFigure 4e shows the PLE and PL spectra of $\\mathrm{CSSG}{:6\\%}\\mathrm{Cr}^{3+}$ at $77\\mathrm{K}$ with a step size of $0.05\\mathrm{nm}$ . The transitions from $^{4}\\mathrm{A}_{2\\mathrm{g}}$ to ${^4\\mathrm{T}}_{2\\mathrm{g}}(^{4}\\mathrm{F})$ and ${^4\\mathrm{T}_{1\\mathrm{g}}}(^{4}\\mathrm{F})$ are centered at $15,670\\mathrm{cm}^{-1}$ ( ${\\sim}636\\mathrm{nm})$ and $22,050\\mathrm{cm}^{-1}$ $(\\sim453\\mathrm{nm})$ , respectively. The R-line is only detected in the PLE spectrum at $698.3\\mathrm{nm}$ $(\\sim14,320\\mathrm{cm}^{-1},$ . The peak at ${\\sim}713\\mathrm{nm}$ $(\\sim14,030\\mathrm{cm}^{-1}),$ ) is observed in both the PL and PLE spectra, which is assigned to the zero-phonon line (ZPL) for the ${^4\\mathrm{T}}_{2}(^{4}\\mathrm{F})$ and $\\mathrm{^{4}A_{2g}}$ transition (Fig. S7). The energy gap between ${}^{2}\\mathrm{E}_{\\mathrm{g}}({}^{2}\\mathrm{G})$ and the ${^4\\mathrm{T}}_{2\\mathrm{g}}(^{4}\\mathrm{F})$ ZPL was evaluated to be ${\\sim}290\\mathrm{cm}^{-1}$ , indicating a strong spin–orbit coupling (SOC) of the ${}^{2}\\mathrm{E}_{\\mathrm{g}}({}^{2}\\mathrm{G})$ and ${^4\\mathrm{T}}_{2\\mathrm{g}}(^{4}\\mathrm{F})$ states50. Thus, the fluorescent decay curve shows a biexponential model with a lifetime of ${\\sim}190\\upmu\\mathrm{s}$ (Fig. S8–S9). \n\n![](images/d52b6a85f822033f1a0cdecce4af247929409938c0da9ba7ab0fcc3d891e319b.jpg) \nFig. 2 Crystal structures and micromorphology. a, b XRD patterns, SEM images, and EDS mappings for $C S S G3\\%C r^{3+}$ sintered in air and sintered in CO with $1w t\\%$ $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ . c XRD peak intensities. d CL image and normalized CL spectra at points I and II for $C S S G3\\%C r^{3+}$ sintered in CO. The insert shows the CL intensities at points I and II. \n\nThe PL spectrum has a maximum peak at $\\sim12,980\\mathrm{cm}^{-1}$ $(\\sim770\\mathrm{nm})$ with a FWHM of $1560\\mathrm{cm}^{-1}$ $(\\sim93\\mathrm{nm})$ . The corresponding Stokes shift is ${\\sim}2700\\mathrm{cm}^{-1}$ . The peak at $730\\mathrm{nm}$ $({\\sim}13,\\bar{7}00\\mathrm{cm}^{-1})$ is the phonon satellite of the ZPL. The energy difference between the ZPL and its phonon satellite is determined to be ${\\sim}330\\mathrm{cm}^{-1}$ , which corresponds to one of the vibrational modes $\\left(\\hbar\\boldsymbol{w}\\right)$ that couple with the ${^4\\mathrm{T}_{2\\mathrm{g}}(^{4}\\mathrm{F})}\\to{^4\\mathrm{A}_{2\\mathrm{g}}}$ transition (Fig. S7). \n\nA Stokes shift has a relationship of $(2S+1)\\hbar w$ , where $S$ is the Huang–Rhys parameter; thus, $S$ is determined to be between 3 and 4, which is smaller than the value $(\\sim6)$ for $\\mathrm{LSGG}{\\mathrm{:Cr}}^{3+31}$ . Both the broadband emissive characteristic and the large Stokes shift indicate a stronger EPC for the $\\mathrm{^{4}T_{2g}(^{4}F)\\rightarrow^{4}A_{2g}}$ transition in $\\mathrm{CSSG}{\\mathrm{:}}\\mathrm{Cr}^{3+}$ . A stronger EPC leads to a larger S value28–31. At a low temperature (77 K), the EPC effect is weak. Thus, the FWHM value at $77\\mathrm{K}$ decreases by ${\\sim}190\\mathrm{cm}^{-1}$ compared with the FWHM of $1750\\mathrm{cm}^{-1}$ $(\\sim110\\mathrm{nm})$ at RT. \n\nIt is worth noting that the ratio in the range of $650{-}725\\mathrm{nm}$ increases and the emission shows a blueshift with increasing temperature. The small energy gap ( $\\langle\\sim$ $290\\mathrm{cm}^{-1},$ between $^2\\mathrm{E_{g}}$ and the $^4\\mathrm{T}_{2\\mathrm{g}}$ ZPL leads to mixing of the ${}^{2}\\mathrm{E}_{\\mathrm{g}}({}^{2}\\mathrm{G})$ and ${}^{4}\\mathrm{T}_{2\\mathrm{g}}(^{4}\\mathrm{F})$ states. When the temperature increases, electronic transfer from the $^4\\mathrm{T}_{2\\mathrm{g}}$ state to the $^2\\mathrm{E_{g}}$ state is strengthened with the assistance of EPC. Thus, the radiative transitions from the ${}^{2}\\mathrm{E}_{\\mathrm{g}}({}^{2}\\mathrm{G})$ state increase, and blueshifts are observed. \n\n![](images/05ea3a9ca9be33a607dae42754a611ce7bf6cd6b6c62261c68d30f04f5f9f450.jpg) \nFig. 3 Diagnosis of the valence state of Cr. a, b $\\mathsf{X P S},$ c DR, and d EPR results of $C S S G3\\%C r^{3+}$ calcined in air and CO. \n\n# Performance of the fabricated NIR-LED device \n\nThe $\\mathrm{CSSG}{:}6\\%\\mathrm{Cr}^{3+}$ phosphor shows a green color (Fig. 5a). Based on the optimized phosphor and a high-power blue chip, an NIR-LED device was fabricated and is displayed in Fig. 5b–d. The electroluminescence (EL) spectra, optical powers, and conversion efficiencies of the device depending on the driving current $(\\varLambda)$ are given in Fig. 5e–h. The strong emission peak at ${\\sim}460\\mathrm{nm}$ comes from the blue chip. The broad NIR emission band comes from ${\\mathrm{CSSG}}{:}{\\mathrm{Cr}}^{3+}$ . The optical powers of both the total radiance and NIR light increase with increasing current until reaching maxima of 97.8 and $64.7\\mathrm{mW};$ , respectively, at $520\\mathrm{mA}$ . \n\nThe conversion efficiency from the emitted blue light to NIR light (ηNIR/blue light) drops from 33.5 to $12.3\\%$ when the driving current increases from 100 to $600\\mathrm{mA}$ . Correspondingly, the conversion efficiency from the input electronic power to NIR emissions $\\left(\\mathfrak{\\eta}_{\\mathrm{NIR/input}}\\right)$ decreases from 7.2 to $2.3\\%$ . ηNIR/input is much lower than ηNIR/blue light. The lower photoelectric conversion efficiency (ηblue light/input) from the input electronic power to blue light should be responsible for this phenomenon because the ηblue light/input of the used blue chip, ranging from 31.9 to $19.4\\%$ at $100{-}600\\mathrm{mA}_{\\mathrm{{}}}$ , is not very high (Fig. S9). If the used blue chip is efficient, then ηNIR/input can be greatly enhanced further. \n\nOn the other hand, only $84.3\\%$ of the NIR emission can be detected due to the limitation of the measurement range, up to $850\\mathrm{nm}$ (Fig. 5h). If the $15.7\\%$ unmeasured part is taken into account, then the actual NIR optical power should be $76.8\\mathrm{mW}$ at $520\\mathrm{mA}$ . Thus, the total optical power even reaches $109.9\\mathrm{mW}$ , which is much higher than the performances reported until now44. \n\nThe QEs discussed above are the measured results. The QE and radiant power were measured by using the same spectrometer. If the unmeasured part is also taken into account, then the IQE and EQE can actually reach $92.3\\%$ and $25.5\\%$ , respectively, which are almost the best results as far as we know up to now. \n\n# Applications in night vision \n\nFigure 6 shows the application of the NIR-LED for night vision. Visible images taken by a visible camera are colorful when water, milk, and cups are illuminated by either fluorescent light or NIR light. The logo is clear under fluorescent light. However, only black-and-white images are captured by an NIR camera. When the NIR-LED is off, nothing can be captured. When the NIR-LED is on, the logo is much clearer when it is taken by the NIR camera than when it is taken by the visible camera, especially the logo on the surface of the glass filled with transparent water. These results indicate that the achieved $\\mathrm{CSSG{:}C r^{3+}}$ phosphor enables the NIR-LED to have good application in night-vision technology. Potential applications in monitoring foods and medicines are also expected for such NIR phosphors and NIR-LED light sources. \n\n![](images/6aa8270a97ffceccb0d0529fe44cc6ee5752a5b732c38c3150fb1ad3103110c8.jpg) \nFig. 4 Luminescence dependence on temperature for $\\mathsf{C S S G:6\\%C r^{3+}}$ . a PL and b normalized PL spectra. c Integrated PL intensities for the sample sintered in air and the optimized sample. The dotted line is the fitting result for the Arrhenius equation. d Peak positions and FWHM values. The temperature ranges from 25 to $300^{\\circ}\\mathsf{C}$ . e PL and PLE spectra at $77\\mathsf{K}.$ \n\n# Discussion \n\nIn conclusion, $\\mathrm{CSSG}{\\mathrm{:Cr}}^{3+}$ exhibits broad NIR emission from 700 to $900\\mathrm{nm}$ under blue light excitation. The previously reported $\\mathrm{CSSG}{\\mathrm{:Cr}}^{3+}$ synthesized in air has low IQE $(12.8\\%)$ and EQE $(4.8\\%)$ , limiting its performance in pc-NIR-LED devices. By adding fluxes and synthesizing in a CO reducing atmosphere, the IQE and EQE are greatly improved to $77.8\\%$ and $21.5\\%$ , respectively. If the unmeasured part is taken into account, then the actual IQE and EQE should reach $92.3\\%$ and $25.5\\%$ , respectively, which is almost the best result among the NIR phosphors developed until now. Investigation of the crystal structures and micromorphology demonstrated that the improvement arises from the modification of the crystallinity and the maintenance of ${\\mathrm{Cr}}^{3+}$ . The achieved $\\mathrm{CSSG}{:}6\\%\\mathrm{Cr}^{3+}$ exhibits excellent thermal stability, and $97.4\\%$ of the emission intensity at room temperature can still be maintained at $150^{\\circ}\\mathrm{C}$ . Thus, when it was used in a high-power blue chip, the fabricated NIR-LED showed a high optical power of nearly $110\\mathrm{mW}$ at $520\\mathrm{mA}$ , which is almost the best performance among NIR-LED light sources. \n\n![](images/057cd6a55456e1fbc245d65b217a73d92b8a1e8f3bb39eded50943ee0355ef8b.jpg) \nFig. 5 Performance of the fabricated high-power NIR-LED device. a Body color of the $C S S G{:}6\\%C\\mathsf{r}^{3+}$ phosphor under sunlight. b NIR-LED device fabricated using the optimized phosphor and a $460\\mathsf{n m}$ blue LED. c Working state of the NIR-LED taken without a filter and d with a longpass filter at $650\\mathsf{n m}$ . e EL spectra, f output optical powers, and $\\mathfrak{g}$ conversion efficiencies of the NIR-LED depending on the driving current. h EL spectrum fitted by the Gaussian formula. \n\n![](images/9a0ed319594324d4d95549a2dce6c13492d82752bdc3a2a0458d0701d54b7c38.jpg) \nFig. 6 Applications for night vision. Visible images and NIR images of water and milk illuminated by fluorescent light and the fabricated NIRLED light. \n\nAmong the reported NIR phosphors, ${\\mathrm{Cr}}^{3+}$ is an important activator, and its luminescence is determined by both the selected host and the synthesis technology. We believe that this work provides an effective strategy to optimize NIR phosphors using only a simple but the best method. Thus, it will inspire more researchers to achieve much better performance of known NIR phosphors and advance development of next-generation smart NIR-LED light sources. \n\n# Materials and methods Synthesis \n\nSamples with the nominal composition of $\\mathrm{Ca}_{3}\\mathrm{Sc}_{2}$ - $\\mathrm{_{x}S i_{3}O_{12}}\\mathrm{:}y\\mathrm{Cr}^{3+}$ , xwt% flux were synthesized by a hightemperature solid-state reaction. The starting materials of $\\mathrm{CaCO_{3}}$ $(99.9\\%)$ , $\\mathrm{Sc}_{2}\\mathrm{O}_{3}$ $(99.9\\%)$ , $\\mathrm{SiO}_{2}$ (AR), and $\\mathrm{Cr}_{2}\\mathrm{O}_{3}$ $(99.95\\%)$ and fluxes of $\\mathrm{\\DeltaNH_{4}F}$ , $\\mathrm{CaF}_{2},$ $\\mathrm{\\bfH}_{3}\\mathrm{\\bfBO}_{3}.$ , LiF, and $\\mathrm{Li_{2}C O_{3}}$ were weighed according to the nominal composition and then ground in an agate mortar for $30\\mathrm{min}$ . After that, the powders were sintered at $1450^{\\circ}\\mathrm{C}$ for $3\\ensuremath{\\mathrm{h}}$ in air and a CO atmosphere. \n\n# Fabrication of pc-NIR-LEDs \n\nNIR-LEDs were fabricated using the optimized NIR phosphor $\\mathrm{CSSG}{:}6\\%\\mathrm{Cr}^{3+}$ and high-power blue-LED chips $(460\\mathrm{nm})$ . The phosphors were thoroughly mixed with epoxy resin and then coated on the chips. \n\n# Characterization \n\nXRD patterns were measured by a Bruker D8 X-ray diffractometer with $\\mathrm{Cu}~\\mathrm{K}\\upalpha$ radiation $(\\lambda=1.54056\\mathring\\mathrm{A})$ at $40\\mathrm{kV}$ and $40\\mathrm{mA}$ . DR spectra were measured by a LAMBDA 950. PL and PLE spectra at $\\mathrm{RT-}300^{\\circ}\\mathrm{C}$ were characterized by a Hitachi F-4600. PL and PLE spectra at 77 K were measured by a Horiba FL-311 by dipping the sample in liquid nitrogen. EPR data were recorded on a Bruker E500 with the X-band frequencies $(\\approx9.845\\:\\mathrm{GHz})$ and a microwave power of $0.63\\mathrm{mW}$ . XPS was performed on a Kratos Axis Ultra DLD. IQEs and EQEs were recorded by an Otsuka Photal Electronics QE-2100. A field-emission scanning electron microscope (FE-SEM, Hitachi S-4800) equipped with an energy dispersive X-ray spectroscopy (EDS) system and a CL system (MonoCL4, Gatan) was used to measure the morphology. EL spectra and performances of fabricated pc-NIR-LED devices were measured by an integrating sphere (Labsphere), and data were collected by a multichannel photodetector (MCPD-9800, Otsuka Photal Electronics). Visible images and NIR images were taken by a visible camera (SONY \n\nILCE-7M2K) and an NIR camera (Work Power UC500M), respectively. \n\n# Acknowledgements \n\nThis work is financially supported by the National Key Research and Development Program of China (2016YFC0104502, 2017YFC0111602), Fujian Institute of Innovation, Chinese Academy of Sciences (FJCXY18040203), Public Projects of Zhejiang Province (LGG18E020007), Science and Techology Major Project of Ningbo Municipality (2017C110028), and Natural Science Foundation of Shanxi Province (201801D121020, 201801D221132). \n\n# Author details \n\n1Ningbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China. 2College of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan 030024, China. 3University of Chinese Academy of Sciences, Beijing 100049, China. 4Department of Physics, Georgia Southern University, Statebore, GA 30460, USA \n\n# Author contributions \n\nY.L. and L.W. initiated the research. The design of the experiments took shape with input from all the authors. Z.J. and C.Y. performed the experiments and measurement with support from P.S. and prepared the draft of the paper. X.W., H.J., and J.J. discussed the paper. All authors assisted in the editing of the final paper. \n\n# Conflict of interest \n\nThe authors declare that they have no conflict of interest. \n\nSupplementary information is available for this paper at https://doi.org/ 10.1038/s41377-020-0326-8. \n\nReceived: 11 February 2020 Revised: 7 April 2020 Accepted: 28 April 2020 \nPublished online: 15 May 2020 \n\n# References \n\n1. Tang, X. et al. Dual-band infrared imaging using stacked colloidal quantum dot photodiodes. Nat. Photonics 13, 277–282 (2019). \n2. Gu, Y. Y. et al. High-sensitivity imaging of time-domain near-infrared light transducer. Nat. Photonics 13, 525–531 (2019). \n3. Tuong Ly, K. et al. Near-infrared organic light-emitting diodes with very high external quantum efficiency and radiance. Nat. Photonics 11, 63–68 (2017). \n4. Pan, Z. W. et al. Sunlight-activated long-persistent luminescence in the nearinfrared from $\\mathsf{C r}^{3+}$ -doped zinc gallogermanates. Nat. Mater. 11, 58–63 (2011). \n5. Zeng, B. B. et al. Hybrid graphene metasurfaces for high-speed mid-infrared light modulation and single-pixel imaging. Light.: Sci. Appl. 7, 51 (2018). \n6. Liang, Y. J. et al. New function of the ${\\mathsf{Y b}}^{3+}$ ion as an efficient emitter of persistent luminescence in the short-wave infrared. Light.: Sci. Appl. 5, e16124 (2016). \n7. Dincer, C. et al. Disposable sensors in diagnostics, food, and environmental monitoring. Adv. Mater. 31, 1806739 (2019). \n8. Zampetti, A., Minotto, A. & Cacialli, F. Near-infrared (NIR) organic light-emitting diodes (OLEDs): challenges and opportunities. Adv. Funct. Mater. 29, 1807623 (2019). \n9. Tessler, N. et al. Efficient near-infrared polymer nanocrystal light-emitting diodes. Science 295, 1506–1508 (2002). \n0. Zhao, X. F. & Tan, Z. K. Large-area near-infrared perovskite light-emitting diodes. Nat. Photonics 14, 215–218 (2020). \n11. Lukovic, M. et al. LED-based Vis-NIR spectrally tunable light source—the optimization algorithm. J. Eur. Optical Soc.-Rapid Publ. 12, 19 (2016). \n2. Filippo, R., Taralli, E. & Rajteri, M. LEDs: sources and intrinsically bandwidthlimited detectors. Sensors 17, 1673 (2017). \n13. Yao, Q. et al. YAG: $\\mathsf{C e}^{3+}$ transparent ceramic phosphors brighten the nextgeneration laser-driven lighting. Adv. Mater. https://doi.org/10.1002/ adma.201907888 (2020). \n14. Liu, Y. F. et al. An excellent cyan-emitting orthosilicate phosphor for NUVpumped white LED application. J. Mater. Chem. C. 5, 12365–12377 (2017). \n15. Liu, Y. F. et al. $\\mathsf{B a}_{9}\\mathsf{L u}_{2}\\mathsf{S i}_{6}\\mathsf{O}_{24}\\mathrm{:}\\mathsf{C e}^{3+}$ : an efficient green phosphor with high thermal and radiation stability for solid-state lighting. Adv. Optical Mater. 3, \n1096–1101 (2015). \n16. Wei, Y. et al. New strategy for designing orangish-red-emitting phosphor via oxygen-vacancy-induced electronic localization. Light.: Sci. Appl. 8, 15 (2019). \n17. Zhao, M. et al. Emerging ultra-narrow-band cyan-emitting phosphor for white LEDs with enhanced color rendition. Light; Sci. Appl. 8, 38 (2019). \n18. Senden, T. et al. Quenching of the red ${\\ensuremath{\\mathsf{M}}}{\\ensuremath{\\mathsf{n}}}^{4+}$ luminescence in $M n^{4+}$ -doped fluoride LED phosphors. Light.: Sci. Appl. 7, 8 (2018). \n19. Dai, P. P. et al. A single $\\mathsf{E u}^{2+}$ -activated high-color-rendering oxychloride whitelight phosphor for white-light-emitting diodes. Light.: Sci. Appl. 5, e16024 (2016). \n20. De Guzman, G. N. A. et al. Near-infrared phosphors and their full potential: a review on practical applications and future perspectives. J. Lumin. 219, 116944 (2020). \n21. Du, J. R. & Poelman, D. Identifying near‐infrared persistent luminescence in ${\\mathsf{C r}}^{3+}$ ‐doped magnesium gallogermanates featuring afterglow emission at extremely low temperature. Adv. Optical Mater. 8, 1901848 (2020). \n22. Lyu, T. S. & Dorenbos, P. Designing thermally stimulated $1.06\\mu\\mathrm{m}\\ N\\mathrm{d}^{3+}$ emission for the second bio-imaging window demonstrated by energy transfer from ${\\mathrm{Bi}}^{3+}$ in La-, Gd-, Y-, and $\\mathsf{L u P O}_{4}.$ . Chem. Eng. J. 372, 978–991 (2019). \n23. Song, E. H. et al. Heavy $M n^{2+}$ doped $M g A l_{2}O_{4}$ phosphor for high-efficient near-infrared light-emitting diode and the night-vision application. Adv. Optical Mater. 7, 1901105 (2019). \n24. Qiao, J. W. et al. Divalent europium-doped near-infrared-emitting phosphor for light-emitting diodes. Nat. Commun. 10, 5267 (2019). \n25. Zhao, F. Y. et al. Double perovskite $\\mathsf{C s}_{2}\\mathsf{A g l n C l}_{6}\\mathsf{:C r}^{3+}$ : broadband and nearinfrared luminescent materials. Inorg. Chem. Front. 6, 3621–3628 (2019). \n26. Wang, C. P. et al. An ultra-broadband near-infrared $\\mathsf{C r}^{3+}.$ -activated gallogermanate $M g_{3}G a_{2}G e O_{8}$ phosphor as light sources for food analysis. ACS Appl. Electron. Mater. 1, 1046–1053 (2019). \n27. Dai, D. J. et al. Broad band emission near-infrared material $M g_{3}mathsf{G a}_{2}\\mathsf{G e O}_{8};C r^{3+}$ : substitution of Ga-In, structural modification, luminescence property and application for high efficiency LED. $\\mathcal{I}.$ Alloy. Compd. 806, 926–938 (2019). \n28. Malysa, $\\mathsf{B}_{\\cdot},$ Meijerink, A. & Jüstel, T. Temperature dependent luminescence ${\\mathsf{C r}}^{3+}$ -doped $G d A l_{3}(B O_{3})_{4}$ and $\\mathsf{Y A l}_{3}(\\mathsf{B O}_{3})_{4}.$ . J. Lumin. 171, 246–253 (2016). \n29. Malysa, B. et al. On the influence of calcium substitution to the optical properties of $\\mathsf{C r}^{3+}$ doped $\\mathsf{S r S C}_{2}\\mathsf{O}_{4}.$ J. Lumin. 190, 234–241 (2017). \n30. Malysa, $\\mathsf{B}_{\\cdot},$ Meijerink, A. & Jüstel, T. Temperature dependent photoluminescence of $\\mathsf{C r}^{3+}$ doped ${\\mathsf{S r}}_{\\otimes}{\\mathsf{M g L a}}({\\mathsf{P O4}})_{7}.$ Optical Mater. 85, 341–348 (2018). \n31. Malysa, B., Meijerink, A. & Jüstel, T. Temperature dependent $\\mathsf{C r}^{3+}$ photoluminescence in garnets of the type $X_{3}S C_{2}G a_{3}O_{12}$ $(X=L\\cup,$ Y, Gd, La). J. Lumin. \n202, 523–531 (2018). \n32. Zeng, H. T. et al. Two-site occupation for exploring ultra-broadband nearinfrared phosphor - double-perovskite $L a_{2}M g Z r O_{6};C r^{3+}$ . Chem. Mater. 31, \n5245–5253 (2019). \n33. Yu, D. C. et al. Non-rare-earth ${\\N a_{3}\\mathsf{A l F}_{6}}{:\\mathsf{C r}^{3+}}$ phosphors for far-red light-emitting diodes. ACS Appl. Electron. Mater. 1, 2325–2333 (2019). \n34. Zhang, L. L. et al. $\\mathsf{C r}^{3+}.$ -doped broadband NIR garnet phosphor with enhanced luminescence and its application in NIR spectroscopy. Adv. Optical Mater. 7, 1900185 (2019). \n35. Zhang, L. L. et al. A high efficiency broad-band near-infrared $\\mathsf{C a}_{2}\\mathsf{L u}Z\\mathsf{r}_{2}\\mathsf{A l}_{3}\\mathsf{O}_{12}\\mathrm{:}$ ${\\mathsf{C r}}^{3+}$ garnet phosphor for blue LED chips. J. Mater. Chem. C. 6, 4967–4976 (2018). \n36. Shao, Q. Y. et al. Photoluminescence properties of a ${\\mathsf{S c B O}}_{3}{:}\\mathsf{C r}^{3+}$ phosphor and its applications for broadband near-infrared LEDs. RSC Adv. 8, 12035–12042 (2018). \n37. Xu, X. X. et al. Highly efficient and thermally stable ${\\mathsf{C r}}^{3+}$ -activated silicate phosphors for broadband near-infrared LED applications. Chem. Eng. J. 383, 123108 (2020). \n38. Shao, Q. Y. et al. Broadband near-infrared light source derived from $C r^{3+}$ -doped phosphors and a blue LED chip. Opt. Lett. 43, 5251–5254 (2018). \n39. Yao, L. Q. et al. Broadband emission of single-phase $\\cos\\tt C_{2}S i_{3}O_{12}.c r^{3+}/L n^{3+}$ $(\\mathsf{L}\\mathsf{n}=\\mathsf{N}\\mathsf{d},$ Yb, Ce) phosphors for novel solid-state light sources with visible to near-infrared light output. Ceram. Int. 45, 14249–14255 (2019). \n40. Hayashi, D. et al. A broadband LED source in visible to short-wave-infrared wavelengths for spectral tumor diagnostics. Appl. Phys. Lett. 110, 233701 (2017). \n41. Huang, W. T. et al. Broadband $C r^{3+}$ , $\\mathsf{S n}^{4+}$ -doped oxide nanophosphors for infrared mini light-emitting diodes. Angew. Chem. Int. Ed. 58, 2069–2072 (2019). \n42. Lee, C. et al. Chromium(III)-doped fluoride phosphors with broadband infrared emission for light-emitting diodes. Inorg. Chem. 59, 376–385 (2020). \n43. Rajendran, V. et al. Super broadband near-infrared phosphors with high radiant flux as future light sources for spectroscopy applications. ACS Energy Lett. 3, 2679–2684 (2018). \n44. Rajendran, V. et al. Ultra-broadband phosphors converted near-infrared light emitting diode with efficient radiant power for spectroscopy applications. ACS Photonics 6, 3215–3224 (2019). \n45. Shimomura, Y. et al. Photoluminescence and crystal structure of greenemitting $\\mathsf{C a}_{3}\\mathsf{S c}_{2}\\mathsf{S i}_{3}\\mathsf{O}_{12}\\mathrm{:}\\mathsf{C e}^{3+}$ phosphor for white light emitting diodes. J. Electrochem. Soc. 154, J35–J38 (2007). \n46. Liu, Y. F. et al. Generation of broadband emission by incorporating $N^{3-}$ into $\\mathrm{Ca_{3}S c_{2}S i_{3}O_{12}}\\mathrm{:}\\mathrm{Ce}^{3+}$ garnet for high rendering white LEDs. J. Mater. Chem. 21, 6354–6358 (2011). \n47. Liu, Y. F. et al. Tunable full-color-emitting $\\mathrm{Ca_{3}S c_{2}S i_{3}O_{12}}.\\mathrm{Ce}^{3+},$ $\\mathsf{M n}^{2+}$ phosphor via charge compensation and energy transfer. Chem. Commun. 47, 10677–10679 (2011). \n48. Scierka, S. J. et al. Determination of the distribution of chromium oxidation states in reduced $C r/\\mathsf{A l}_{2}\\mathsf{O}_{3}$ catalysts from XPS by factor analysis and curve fitting. Surf. Interface Anal. 20, 901–908 (1993). \n49. Edgar, A. & Hutton, D. R. Exchange-coupled pairs of $C r^{3+}$ ions in emerald. J. Phys. C: Solid State Phys. 11, 5051–5063 (1978). \n50. Struve, B. & Huber, G. The effect of the crystal field strength on the optical spectra of $\\mathsf{C r}^{3+}$ in gallium garnet laser crystals. Appl. Phys. B 36, 195–201 (1985). " + }, + { + "id": "10.1002_adma.202001537", + "DOI": "10.1002/adma.202001537", + "DOI Link": "http://dx.doi.org/10.1002/adma.202001537", + "Relative Dir Path": "mds/10.1002_adma.202001537", + "Article Title": "Weighted Mobility", + "Authors": "Snyder, GJ; Snyder, AH; Wood, M; Gurunathan, R; Snyder, BH; Niu, CN", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "Engineering semiconductor devices requires an understanding of charge carrier mobility. Typically, mobilities are estimated using Hall effect and electrical resistivity meausrements, which are are routinely performed at room temperature and below, in materials with mobilities greater than 1 cm(2) V-1 s(-1). With the availability of combined Seebeck coefficient and electrical resistivity measurement systems, it is now easy to measure the weighted mobility (electron mobility weighted by the density of electronic states). A simple method to calculate the weighted mobility from Seebeck coefficient and electrical resistivity measurements is introduced, which gives good results at room temperature and above, and for mobilities as low as 10(-3) cm(2) V-1 s(-1), mu w=331cm2Vs(m omega cm rho) (T300 K)-3/2[ exp[ |S|kB/e-2]1+exp[-5(|S|kB/e-1) ]+3 pi 2|S|kB/e1+exp[5(|S|kB/e-1) ] ]Here, mu(w) is the weighted mobility, rho is the electrical resistivity measured in m omega cm, T is the absolute temperature in K, S is the Seebeck coefficient, and k(B)/e = 86.3 mu V K-1. Weighted mobility analysis can elucidate the electronic structure and scattering mechanisms in materials and is particularly helpful in understanding and optimizing thermoelectric systems.", + "Times Cited, WoS Core": 640, + "Times Cited, All Databases": 656, + "Publication Year": 2020, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000532658500001", + "Markdown": "# Weighted Mobility \n\nG. Jeffrey Snyder,\\* Alemayouh H. Snyder, Maxwell Wood, Ramya Gurunathan, Berhanu H. Snyder, and Changning Niu \n\nEngineering semiconductor devices requires an understanding of charge carrier mobility. Typically, mobilities are estimated using Hall effect and electrical resistivity meausrements, which are are routinely performed at room temperature and below, in materials with mobilities greater than $\\mathsf{1c m^{2}V^{-1}s^{-1}}$ . With the availability of combined Seebeck coefficient and electrical resistivity measurement systems, it is now easy to measure the weighted mobility (electron mobility weighted by the density of electronic states). A simple method to calculate the weighted mobility from Seebeck coefficient and electrical resistivity measurements is introduced, which gives good results at room temperature and above, and for mobilities as low as $\\mathsf{I}0^{-3}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1},$ \n\n$$\n\\mu_{\\mathrm{w}}=331\\frac{\\mathrm{cm}^{2}}{\\mathrm{Vs}}\\left(\\frac{\\mathrm{m}\\Omega\\mathrm{cm}}{\\rho}\\right)\\left(\\frac{T}{300\\mathrm{K}}\\right)^{-3/2}\\left[\\frac{\\exp\\left[\\frac{|S|}{k_{\\mathrm{B}}/e}-2\\right]}{1+\\exp\\left[-5\\left(\\frac{|S|}{k_{\\mathrm{B}}/e}-1\\right)\\right]}+\\frac{\\frac{3}{\\pi^{2}}\\frac{|S|}{k_{\\mathrm{B}}/e}}{1+\\exp\\left[5\\left(\\frac{|S|}{k_{\\mathrm{B}}/e}-1\\right)\\right]}\\right]\n$$ \n\nHere, $\\mu_{\\mathrm{w}}$ is the weighted mobility, $\\rho$ is the electrical resistivity measured in $\\mathsf{m}\\Omega\\mathsf{c m}$ , $\\tau$ is the absolute temperature in K, S is the Seebeck coefficient, and $k_{\\mathrm{{B}}}/\\mathrm{{e}}=86.3~\\upmu\\mathrm{{V}}~\\upkappa^{-1}$ . Weighted mobility analysis can elucidate the electronic structure and scattering mechanisms in materials and is particularly helpful in understanding and optimizing thermoelectric systems. \n\nCharge carrier mobility is perhaps the most important material parameter to experimentally characterize in order to understand or engineer semiconductor electronic devices. The optimization of carrier mobility is critical to research fields ranging from organic semiconductors to photovoltaics to thermoelectrics.[1–3] Mobility is usually defined with the Drude–Sommerfeld free electron model $1/\\rho=\\sigma=n e\\mu$ where $\\rho$ is the electrical resistivity, $\\sigma$ is the electrical conductivity, $n$ is the charge carrier concentration, $e$ the electronic charge, and $\\mu$ the drift mobility. Historically, the easiest way to characterize mobility is through the Hall effect, where the Hall mobility can be defined as $\\mu_{\\mathrm{H}}=$ $\\sigma R_{\\mathrm{H}}$ with $R_{\\mathrm{H}}$ as the Hall resistance.[4] In most cases where the charge transport is dominated by a single band, the Hall mobility is a good estimate (within $10{-}20\\%$ ) for the the drift mobility.[5] \n\nWith the proliferation of Seebeck coefficient measurement systems, particularly in laboratories studying thermoelectric materials,[6,7] the weighted mobility is an independent measurement giving similar information. This can be particularly helpful when there are other magnetic effects to consider in the Hall measurements, such as the anomalous Hall effect, and the measured Hall resistance does not seem to correlate well with the actual charge carrier concentration $(R_{\\mathrm{H}}=1/e n_{\\mathrm{H}})$ or mobility.[8] The weighted mobility measurement is also practicable in regimes where the Hall resistivity measurement is difficult, such as at high temperatures or with low mobility bulk systems.[2,9] \n\nThe weighted mobility, like the Hall mobility, can be defined as a simple function of two measured properties (Figure 1), Seebeck coefficient S and electrical conductivity $\\sigma$ (the Hall mobility is a function of \n\nHall resistance and electrical conductivity). The function used for weighted mobility and Hall mobility are derived from the simple free electron model using a constant mean-free-path. Equation (1) is a simple analytic form for the weighted mobility that approximates the exact Drude–Sommerfeld free electron model within $3\\%$ for thermopower values $\\vert S\\vert>20\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ . \n\n$$\n\\mu_{\\mathrm{w}}=\\frac{3h^{3}\\sigma}{8\\pi e\\left(2m_{e}k_{\\mathrm{B}}T\\right)^{3/2}}\\left[\\frac{\\exp\\left[\\frac{\\left|S\\right|}{k_{\\mathrm{B}}/e}-2\\right]}{1+\\exp\\left[-5\\left(\\frac{\\left|S\\right|}{k_{\\mathrm{B}}/e}-1\\right)\\right]}+\\frac{\\frac{3}{\\pi^{2}}\\frac{\\left|S\\right|}{k_{\\mathrm{B}}/e}}{1+\\exp\\left[5\\left(\\frac{\\left|S\\right|}{k_{\\mathrm{B}}/e}-1\\right)\\right]}\\right]\n$$ \n\nAn equivalent form using the electrical resistivity $\\rho=1/\\sigma$ is given in the abstract. \n\nIn the free electron model, the weighted mobility is a (temperature dependent) material property that is independent of doping whereas the drift mobility depends on doping through the free charge carrier concentration n. Generally, the weighted mobility $\\mu_{\\mathrm{w}}$ is related to the drift mobility $\\mu$ by \n\n$$\n\\mu_{\\mathrm{w}}\\approx\\mu\\Biggl(\\frac{m^{*}}{m_{e}}\\Biggr)^{3/2}\n$$ \n\n![](images/8cf56d0e527baaa944fd3b550c26c044aadf230f82f507ca8df6e98912411714.jpg) \nFigure 1.  Mobility measurements using the Hall or Seebeck effects. Hall mobility $\\mu_{\\mathsf{H}}$ is measured using the Hall effect (in a magnetic field B) and electrical resistivity, while the weighted mobility $\\mu_{\\mathrm{w}}$ is measured using measurements of the Seebeck effect (voltage produced from a temperature difference $T_{\\mathfrak{h}}-T_{\\mathfrak{c}})$ and electrical resistivity. \n\nwhere $m^{*}$ is the density of states effective mass and $m_{e}$ is the electron mass. Because the density of electron states is proportional to $m^{*3/2}$ , we think of $\\mu_{\\mathrm{w}}$ as the electron mobility weighted by the density of electron states. \n\nThe measured weighted mobilities of well known thermoelectric semiconductors such as $\\mathrm{PbTe^{[10]}}$ and $\\mathrm{Mg}_{3}\\mathrm{Sb}_{2}[11]$ are essentially the same as the Hall mobility except for the density of states $m^{*3/2}$ factor in $\\mu_{\\mathrm{w}}$ (Figure 2). Indeed, combining Hall, Seebeck, and conductivity measurements to estimate a density of states effective mass is a common analysis technique.[5,12,13] For example, the weighted mobility of most good thermoelectric materials decreases with temperature because the electrons are scattered by phonons. In the simple model for acousticphonon scattering (or deformation potential phonon scattering theory), the decrease in weighted mobility occurs with temperature as $T^{-3/2}$ whereas the Hall mobility transitions between $T^{-3/2}$ for lightly doped semiconductors to $T^{-1}$ for heavily doped semiconductors or metals (Figure 2). In some materials, grain boundary,[14] disorder,[15] or ionized impurity scattering[16] might contribute, which will be observed in different temperature and carrier concentration dependencies of the mobility. The weighted mobility gives nearly the same information about charge carrier mobility as the Hall mobility and thus can be used to investigate charge carrier transport mechanisms much in the same way the Hall mobility has been used. \n\nBecause of the relative ease of Seebeck compared to Hall effect measurements, the weighted mobility could easily become the most common method to determine the charge transport mechanism. Some 4000 samples have Seebeck and conductivity measurements readily available on StarryData2[17] whereas only relatively few samples have reported Hall effect data. Compiling the 153 samples with both Seebeck coefficient and electrical conductivity as a function of temperature (Figure  3), it is clear from the decreasing mobility with temperature that phonon scattering of the charge carriers typically dominates. A few samples show weighted mobility increasing with temperature at low temperature before following the usual trend of decreasing with temperature (phonon scattering). In several cases this increasing mobility with temperature has been attributed to thermally activated conductivity at grain boundaries,[14,18] although ionized impurity scattering can also give a qualitatively similar effect. \n\nParticularly for materials with low mobility, the weighted mobility appears to be an even better measure of drift mobility than measurements of Hall mobility. The same data, showing weighted mobility on a logarithmic scale (Figure  3b) gives reasonable trends even for materials with weighted mobility less than $10^{-3}\\ \\mathrm{cm}^{2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ . Hall mobility is not commonly reported on materials with mobility less than $1\\ \\mathrm{cm}^{2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ because the signal is very small.[4] The low weighted mobilities increase with temperature suggesting defects (grain boundaries, ionized impurities) are responsible for the low mobility and higher mobilities are possible with defect or microstructure engineering. \n\n![](images/5786b67154f726e04125948aa19587b9234dc40474b8cb890e6769a3cf5eb14a.jpg) \nFigure 2.  Similar behavior of Hall mobility $\\mu_{\\mathsf{H}}$ and weighted mobility $\\mu_{\\mathrm{w}},$ which uses measurements of the Seebeck coefficient. A) The $\\mu_{\\mathsf{H}}$ and $\\mu_{\\mathrm{w}}$ of n-type PbTe (StarryData2 Paper ID $777^{[70]}$ ) are both monotonously decreasing with temperature as expected from increased phonon scattering and simply scaled by the density-of-states effective mass $m^{*3/2}/m_{e}^{3/2}\\approx0.25$ . The Hall mobility $\\mu_{\\mathsf{H}}$ is expected to decrease with increasing doping,[10] but the weighted mobility $\\mu_{\\mathrm{w}}$ is expected to be similar for samples with different doping as observed. B) The mobility of polycrystalline n-type $\\mathsf{M g}_{3}\\mathsf{S b}_{1.5}\\mathsf{B i}_{0.5}[71]$ is suppressed at low temperature due to electrical resistance at grain boundaries. This effect is observed equally (scaled by $m^{*3/2}/m_{e}^{3/2}\\approx7.8)$ in both $\\mu_{\\mathsf{H}}$ and $\\mu_{\\mathrm{w}}$ for samples with differing grain size. \n\n![](images/ec6f016c93632f6c5ab4f2d840fecc67497c98ac4467164e973c67125c521431.jpg) \nFigure 3.  Weighted mobility calculated from the reported Seebeck coefficient and electrical conductivity of 153 samples from the StarryData2 website.[17] The weighted mobilities generally decrease with temperature (linear scale above) as expected from phonon scattering of electrons. Several samples show physically reasonable values for mobility less than $\\mathsf{1~c m^{2}~V^{-1}~s^{-1}}$ (log scale below) which is very difficult to measure using the Hall effect. \n\nThe weighted mobility, like the Hall mobility, can be used to compare the experimental properties of materials to help decide if different properties are due to differences in doping, electronic structure or scattering. An ideal material that follows the Drude–Sommerfeld model exactly with a parabolic band will have a weighted mobility that does not change with doping; any differences could be a sign of complexity in the band structure or scattering, such as nonparabolic bands or multiple bands. Scattering differences are most easily seen in the temperature dependence where departures from simple phonon scattering will give a deviation from the simple $\\bar{T^{3}}/2$ . For example, low mobility below room temperature could be a sign of grain boundary resistance[14,18] \n\nThe weighted mobility is even more important when studying thermoelectric materials as it most directly measures the electronic qualities that make a good thermoelectric material. The thermoelectric figure of merit $z T$ is optimized with doping. The $z T$ that an optimally doped material can achieve is proportional to the thermoelectric quality factor $B^{[12,13,19]}$ \n\n$$\nB=\\left(\\frac{k_{\\mathrm{B}}}{e}\\right)^{2}\\frac{8\\pi e\\left(2m_{e}k_{\\mathrm{B}}T\\right)^{3/2}}{3h^{3}}\\cdot\\frac{\\mu_{\\mathrm{w}}}{\\kappa_{\\mathrm{L}}}T\n$$ \n\nwhich is proportional to the weighted mobility divided by the lattice thermal conductivity $\\mu_{\\mathrm{w}}/\\kappa_{\\mathrm{L}}$ . Thus any strategy to improve a material for thermoelectric use by reducing $\\kappa_{\\mathrm{L}}$ needs also to consider the effect on $\\mu_{\\mathrm{w}}.$ \n\nThe weighted mobility, $\\mu_{\\mathrm{w}},$ is a better descriptor of the inherent electronic transport properties of a thermoelectric material for thermoelectric use than $S^{2}\\sigma,$ and now with the use of Equation (1), is almost as easy to calculate from the experimental S and $\\rho$ . Historically, $S^{2}\\sigma,$ referred to as the thermoelectric “power factor” has been discussed to evaluate improvements in the electronic properties of thermoelectric materials or when thermal conductivity measurements are unavailable. However, $S^{2}\\sigma$ depends on doping and does not optimize where $z T$ does, overemphasizing more metallic doping concentrations because it ignores the impact of the electronic thermal conductivity to $z T.$ $S^{2}\\sigma$ is frequently overanalyzed to the point where it is incorrectly concluded that a high $S^{2}\\sigma$ is preferable even at the expense of lower $z T$ .[20] An optimized thermoelectric design will produce more power using a material with higher $z T$ because the higher efficiency ensures it will produce more power from the heat flowing through it.[21] Therefore, rather than comparing $S^{2}\\sigma,$ it is more useful to compare $\\mu_{\\mathrm{w}}$ values. \n\nIt is important to note that the definition of $\\mu_{\\mathrm{w}}$ using Equation (1) from the measured quantities S and $\\rho$ does not require any assumptions. Nonparabolic, multiband, alternate scattering, and other effects in the data are not neglected. These effects will be noticed as deviations from trends not expected from the simple free electron model $(\\mu_{\\mathrm{w}}(E_{\\mathrm{F}})=\\mathrm{con}{\\cdot}$ stant) that should be explainable by incorporating the relevant physics in a model for $\\mu_{\\mathrm{w}}$ that then can be compared with the experimental values. \n\nIndeed, prior discussions of weighted mobility, using Equation (2) as the definition,[22–24] have relied on parabolic band and scattering assumptions. This begs the question as to the validity in real materials where these assumptions are demonstrably incomplete. Here, in contrast, we define weighted mobility as an experimental value with Equation (1), and use Equation (2) only to interpret the experimental result. \n\nEquations (1) and (3) are motivated from the ideal expression for $\\mu_{\\mathrm{w}}$ of the free electron (parabolic band) Drude–Sommerfeld model with constant mean-free-path (same result as acoustic phonon scattering, $s=1$ in ref. [25]). This requires solving the following two parametric equations for the transport coefficient $\\sigma_{\\mathrm{E}_{0}}$ as a function of S and $\\rho$ , where $\\eta$ (the reduced Fermi level) is the parameter: \n\n$$\n1/\\rho=\\sigma=n e\\mu=\\sigma_{\\mathrm{E}_{0}}\\cdot\\ln(1+e^{\\eta})\n$$ \n\n$$\n\\sigma_{\\mathrm{E}_{0}}={\\frac{8\\pi e\\left(2m_{e}k_{\\mathrm{B}}T\\right)^{3/2}}{3h^{3}}}\\mu_{\\mathrm{w}}\n$$ \n\n$$\nS=\\frac{k_{\\mathrm{B}}}{e}\\left[\\frac{\\displaystyle\\int_{0}^{\\infty}\\frac{\\varepsilon}{1+e^{\\varepsilon-\\eta}}d\\varepsilon}{\\ln(1+e^{\\eta})}-\\eta\\right]\n$$ \n\nThe numerator on the left side of Equation (1) $\\left(\\exp\\ [\\frac{|S|}{k_{\\mathrm{B}}/e}-2\\right]\\right)$ is the analytic result in the non-degenerate limit ( $\\eta\\ll0$ , intrinsic semiconductor), while the numerator on the right side of Equation (1) $\\left(\\frac{3}{\\pi^{2}}\\frac{|S|}{k_{\\mathrm{B}}/e}\\right)$ is the analytic result for the degenerate limit ( $\\hphantom{\\eta\\gg0}$ , metal). The functions in the denominators are sigmoid functions with parameters (5 and 1) that give a maximum error of $3\\%$ to the exact Drude–Sommerfeld result. A smaller maximum error could be achieved with more precise parameters (e.g., 5.34 and 1.14) but $3\\%$ is within the typical uncertainty of Seebeck and resistivity measurements. \n\nIn real materials, the Seebeck coefficient and electrical resistivity can be affected by many mechanisms not accounted for in the free electron model. At low temperatures and materials with high lattice thermal conductivity, for example, the Seebeck coefficient is strongly affected by phonon drag and so the Hall mobility has been a better descriptor for mobility of simple crystalline materials for low temperature physics rather than the weighted mobility. \n\nHowever, the weighted mobility is preferable to Hall mobility for many samples under certain conditions. For example, at high temperatures and for complex materials with low mobility, the Hall resistance can be difficult or even not possible to measure, whereas the Seebeck coefficient may be easy to measure. Practical examples of such systems include organic semiconductors as well as complex solar cell and thermoelectric materials.[2,26] Many of the examples in Figure  3 have such low weighted mobilities that Hall effect measurements are not possible and often not attempted. $\\mathrm{La}_{3-x}\\mathrm{Te}_{4}[27]$ and $\\mathrm{Yb}_{14}\\mathrm{MnSb}_{11},{}^{[28]}$ for example, are good thermoelectric materials with decent mobility, on the order of $2\\ \\mathrm{cm}^{2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-1};$ , but the Hall coefficient is barely measurable. Materials in Figure 3 with even lower mobility are likely not possible to measure by Hall effect in bulk form. Also, materials with magnetic elements or impurities often have Hall effect that is not interpretable as charge carrier concentration. This is likely due to the anomalous Hall effect from the internal magnetism or magnetic impurities. For example, rare-earth filled iron-based skutterudites[8] have Hall coefficients that do not correlate well with other electronic transport properties. \n\nThe Hall mobility $\\mu_{\\mathrm{H}}~=~\\sigma R_{\\mathrm{H}}~$ and Hall concentration $n_{\\mathrm{H}}=1/e R_{\\mathrm{H}}$ as used here[4] is the simple degenerate limit of the Drude–Sommerfeld model. The Drude–Sommerfeld drift mobility and Hall mobility decreases with charge carrier concentration (as $n^{-1/3}$ at high concentrations) as observed in n-PbTe (Figure  2). The weighted mobility, as defined here, is a constant for a Drude–Sommerfeld metal and so would not depend on $n$ . The weighted mobility can be thought of as a non-degenerate (low n) value for mobility which should not change for samples with different doping and therefore better for analyzing small changes in band structures with alloying.[29] In addition, the exact, free electron, acoustic phonon scattering result would require an additional term (the Hall factor $r_{\\mathrm{H}})$ ). Since this $r_{\\mathrm{H}}$ is only a function of the reduced Fermi level $(\\eta)$ it could, in principle, be measured from the Seebeck coefficient (much like the Lorenz factor[30]). However, because the non-degenerate $r_{\\mathrm{H}}$ differs only by $18\\%$ ,[5] it is preferable not to require an additional measurement, instead simply realizing that variations of $n_{\\mathrm{H}}$ or $\\mu_{\\mathrm{H}}$ less than $20\\%$ can be expected even within a parabolic band system. If such differences in $n_{\\mathrm{H}}$ or $\\mu_{H}$ are worthy of discussion, the Hall factor should be calculated more precisely for the material in question using accurate band structures and scattering rates. \n\nBoth the measured weighted mobility and the Hall mobility tend to be small in compensated materials with both n-type and p-type charge carriers; smaller in comparison to that of the dominant charge carrier alone. While the conductivities of both charge carriers are positive and add together, both the Hall voltage and Seebeck coefficient will reduce in magnitude as they depend on the sign of the charge carriers.[27] As a result a bipolar or composite sample (sample with compensating phases or grain boundaries) has a smaller Hall voltage and thermopower $(\\left|S\\right|)$ , and therefore the doping level appears higher than one would expect for either charge carrier. This results in a rapid decrease in $\\mu_{\\mathrm{w}}$ and $\\mu_{\\mathrm{H}}$ with increasing temperature as charge carriers are excited across the band gap. The fact that Hall voltage is weighted by the square of the partial conductivities compared to the linear weighting of Seebeck (Supporting Information) may make $\\mu_{\\mathrm{H}}$ more sensitive to unusual bipolar behavior than μw. \n\nWeighted mobility as defined here is an experimental material parameter that can easily be computed from the measured values of the Seebeck coefficient and electrical conductivity, which needs no additional assumptions. Weighted mobility can be used like the Hall mobility to characterize drift mobility, the most basic material parameter in transport theory. The weighted mobility is actually a better descriptor of the inherent transport property than Hall mobility because it is more independent of charge carrier concentration and magnetic impurities and has a more consistent temperature dependence (above about 100 K). The weighted mobility is easy to measure with commercial instruments and is orders of magnitude more sensitive than the Hall effect for low mobility materials. In thermoelectric materials, the weighted mobility is the quantitative measure of how good a material's electronic transport properties are for thermoelectric applications by characterizing the $S^{2}\\sigma$ term in $z T$ .[1] Without the need of a high strength magnet to measure the Hall coefficient, the weighted mobility offers insight into a most basic material property with a relatively easy Seebeck measurement. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nG.J.S. and R.G. acknowledge NSF DMREF award# 1729487 and DOE Award DE-AC02-76SF00515. C.N. acknowledges DOE SBIR award DE-SC0019679. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Author Contributions \n\nG.J.S. conceived the idea in discussions with M.W., A.S. fit the parameters in Equation (1). A.S., R.G., and C.N. downloaded and processed the data. B.H.S. drew figures in Figure 3 and retrieved the missing Hall data from the original source. All authors reviewed the manuscript. \n\n# Keywords \n\nelectrical transport, electrical measurements, mobility, organic semiconductors, photovoltaics, semiconductors, thermoelectrics \n\nReceived: March 3, 2020 Revised: April 5, 2020 Published online: \n\n[11]\t M.  Wood, J. J.  Kuo, K.  Imasato, G. J.  Snyder, Adv. Mater. 2019, 31, 1902337. \n[12]\t S. D. Kang, G. J. Snyder, arXiv:1710.06896 [cond-mat.mtrl-sci], 2017. \n[13]\t A.  Zevalkink, D. M.  Smiadak, J. L.  Blackburn, A. J.  Ferguson, M. L.  Chabinyc, O.  Delaire, J.  Wang, K.  Kovnir, J.  Martin, L. T.  Schelhas, T. D.  Sparks, S. D.  Kang, M. T.  Dylla, G. J.  Snyder, B. R. Ortiz, E. S. Toberer, Appl. Phys. Rev. 2018, 5, 021303. \n[14]\t J. J.  Kuo, S. D.  Kang, K.  Imasato, H.  Tamaki, S.  Ohno, T.  Kanno, G. J. Snyder, Energy Environ. Sci. 2018, 11, 429. \n[15]\t H.  Xie, H.  Wang, C.  Fu, Y.  Liu, G. J.  Snyder, X.  Zhao, T.  Zhu, Sci. Rep. 2014, 4, 6888. \n[16]\t H.  Wang, Y.  Pei, A. D.  LaLonde, G. J.  Snyder, Material Design Considerations Based on Thermoelectric Quality Factor, Springer, Berlin/ Heidelberg, Germany 2013, pp. 3–32. \n[17]\t Y. Katsura, M. Kumagai, T. Kodani, M. Kaneshige, Y. Ando, S. Gunji, Y. Imai, H. Ouchi, K. Tobita, K. Kimura, K. Tsuda, Sci. Technol. Adv. Mater. 2019, 20, 511. \n[18]\t J.  de  Boor, T.  Dasgupta, H.  Kolb, C.  Compere, K.  Kelm, E.  Mueller, Acta Mater. 2014, 77, 68. \n[19]\t Y. Pei, H. Wang, G. J. Snyder, Adv. Mater. 2012, 24, 6125. \n[20]\t W. Liu, H. S. Kim, Q. Jie, Z. Ren, Scr. Mater. 2015, 111, 3. \n[21]\t L. L. Baranowski, G. J. Snyder, E. S. Toberer, J. Appl. Phys. 2014, 115, 126102. \n[22]\t G. D.  Mahan, In Solid State Physics, Vol. 51 (Eds: F. Spaepen, H. Ehrenreich), Academic Press, New York 1998, p. 81. \n[23]\t G. A. Slack, New Materials and Performance Limits for Thermoelectric Cooling, CRC Press, Boca Raton, FL, USA 1995. \n[24]\t H. J. Goldsmid, Introduction to Thermoelectricity, Springer, New York 2016. \n[25]\t S. D. Kang, G. J. Snyder, Nat. Mater. 2017, 16, 252. \n[26]\t N. C. Greenham, S. Tiwari, Opt. Quantum Electron. 2009, 41, 69. \n[27]\t A. F. May, J.-P. Fleurial, G. J. Snyder, Phys. Rev. B 2008, 78, 125205. \n[28]\t E. S.  Toberer, S. R.  Brown, T.  Ikeda, S. M.  Kauzlarich, G. J.  Snyder, Appl. Phys. Lett. 2008, 93, 062110. \n[29]\t Y. Xiao, D. Wang, Y. Zhang, C. Chen, S. Zhang, K. Wang, G. Wang, S. J. Pennycook, G. J. Snyder, H. Wu, L.-D. Zhao, J. Am. Chem. Soc. 2020, 142, 4051. \n[30]\t H.-S. Kim, Z. M. Gibbs, Y. Tang, H. Wang, G. J. Snyder, APL Mater. 2015, 3, 041506. " + }, + { + "id": "10.1038_s41377-020-0264-5", + "DOI": "10.1038/s41377-020-0264-5", + "DOI Link": "http://dx.doi.org/10.1038/s41377-020-0264-5", + "Relative Dir Path": "mds/10.1038_s41377-020-0264-5", + "Article Title": "Ultrafast and broadband photodetectors based on a perovskite/organic bulk heterojunction for large-dynamic-range imaging", + "Authors": "Li, CL; Wang, HL; Wang, F; Li, TF; Xu, MJ; Wang, H; Wang, Z; Zhan, XW; Hu, WD; Shen, L", + "Source Title": "LIGHT-SCIENCE & APPLICATIONS", + "Abstract": "Perovskites peer into near-infrared Novel photodetectors developed by researchers in China provide imaging in the near-infrared (NIR) region with record-breaking efficiency and speed. A new class of semiconducting materials called organic-inorganic hybrid perovskites (OIHPs) display excellent optical and electrical properties for thin-film solar cells, LEDs and light detectors. To expand their detection range to NIR, which is useful for biomedical applications, OIHPs can be combined with structures called organic bulk-heterojunctions (BHJs). Now, Weida Hu, Liang Shen and co-workers at Jilin University, Chinese Academy of Sciences and Peking University have designed new OIHP-BHJ photodetectors that efficiently detect a wide range of both visible and NIR radiation. Their prototype sensors have ultra-fast response times of just 5.6 nulloseconds and remain sensitive even in low brightness, suggesting that they could accelerate the movement of OIHP devices from lab tests to commercial imaging. Organic-inorganic hybrid perovskite (OIHP) photodetectors that simultaneously achieve an ultrafast response and high sensitivity in the near-infrared (NIR) region are prerequisites for expanding current monitoring, imaging, and optical communication capbilities. Herein, we demonstrate photodetectors constructed by OIHP and an organic bulk heterojunction (BHJ) consisting of a low-bandgap nonfullerene and polymer, which achieve broadband response spectra up to 1 mu m with a highest external quantum efficiency of approximately 54% at 850 nm, an ultrafast response speed of 5.6 ns and a linear dynamic range (LDR) of 191 dB. High sensitivity, ultrafast speed and a large LDR are preeminent prerequisites for the practical application of photodetectors. Encouragingly, due to the high-dynamic-range imaging capacity, high-quality visible-NIR actual imaging is achieved by employing the OIHP photodetectors. We believe that state-of-the-art OIHP photodetectors can accelerate the translation of solution-processed photodetector applications from the laboratory to the imaging market.", + "Times Cited, WoS Core": 537, + "Times Cited, All Databases": 565, + "Publication Year": 2020, + "Research Areas": "Optics", + "UT (Unique WOS ID)": "WOS:000517904800001", + "Markdown": "# Ultrafast and broadband photodetectors based on a perovskite/organic bulk heterojunction for large-dynamic-range imaging \n\nChenglong Li1, Hailu Wang2,3, Fang Wang2,3, Tengfei Li4, Mengjian Xu2, Hao Wang2,3, Zhen Wang2,3, Xiaowei Zhan4, Weida Hu $\\boldsymbol{\\mathfrak{P}}^{2,3}$ and Liang Shen1 \n\n# Abstract \n\nOrganic-inorganic hybrid perovskite (OIHP) photodetectors that simultaneously achieve an ultrafast response and high sensitivity in the near-infrared (NIR) region are prerequisites for expanding current monitoring, imaging, and optical communication capbilities. Herein, we demonstrate photodetectors constructed by OIHP and an organic bulk heterojunction (BHJ) consisting of a low-bandgap nonfullerene and polymer, which achieve broadband response spectra up to $1\\upmu\\mathrm{m}$ with a highest external quantum efficiency of approximately $54\\%$ at $850{\\mathsf{n m}}$ , an ultrafast response speed of 5.6 ns and a linear dynamic range (LDR) of 191 dB. High sensitivity, ultrafast speed and a large LDR are preeminent prerequisites for the practical application of photodetectors. Encouragingly, due to the high-dynamicrange imaging capacity, high-quality visible-NIR actual imaging is achieved by employing the OIHP photodetectors. We believe that state-of-the-art OIHP photodetectors can accelerate the translation of solution-processed photodetector applications from the laboratory to the imaging market. \n\n# Introduction \n\nServing as technical functional components for the translation of optical signals into electrical signals, photodetectors have received extensive attention and have been applied in various fields, including industrial production, military affairs, biochemical detection, optical communication, and scientific research1–10. The versatility and availability of photodetectors always depend on a few predominant factors: the photoresponse speed, sensitivity to lower brightness, detection band in which photodetectors can efficaciously detect light and dynamic range response11–16. Correspondingly, the key photodetector parameters that are to used to evaluate these performance factors are the response time or speed, spectral responsivity $(R)$ , noise current, external quantum efficiency $(E Q E)$ , specific detectivity $(D^{*})$ and linear dynamic range $\\mathrm{(LDR)}^{17-20}$ . Recently, the exploration of high-performance photodetectors has gradually become a research focus in the field of optoelectronics and high-quality imaging. \n\nOrganic-inorganic hybrid perovskites (OIHPs) are emerging materials that have been progressively enabling new thin-film optoelectronics, including solar cells21–27, light-emitting diodes28,29 and photodetectors14,16,30–36. The extensive application of hybrid perovskites can be attributable to their excellent optical and electrical properties, including a direct bandgap, large absorption coefficient, high carrier mobility, and low trap density37–40. Therefore, OIHP photodetectors have demonstrated high $R_{:}$ high $D^{*}$ , an ultrafast response speed and a high LDR when combined with device structure engineering11,18,41. However, the detection range of $\\mathbf{MAPbI}_{3}$ (either polycrystalline films or thin single crystals) is limited to the wavelength region below $820\\mathrm{nm}$ and does not cover the near-infrared (NIR) range, which severely limits its application, especially in biomedical imaging. To overcome this problem, an advantageous strategy has been demonstrated: combining OIHP and an organic bulk heterojunction (BHJ) consisting of donor-acceptor materials with light absorption in the NIR region16,35,36,42. Shen et al. reported a composite photodetector based on $\\mathbf{MAPbI}_{3}$ and PDPPTDTPT/PCBM, which exhibited a wider detection wavelength extending to $950\\mathrm{nm}$ with a 5 ns ultrafast response time16. This work provided an effective way of achieving both a wider and faster response for next-generation photodetectors. However, the sole flaw of the photodetectors was that the EQE value in the NIR region failed to reach a similar value to that in the UV-visible range, which resulted from the weak NIR absorption of the low-bandgap polymer and a mismatched energy level alignment at the interface between the OIHP and BHJ layers. Wang et al. reported photodetectors based on $\\mathrm{\\Delta}\\mathrm{MAPbI{_3}}$ and PDPP3T/ $\\mathrm{PC}_{71}\\mathrm{BM}$ BHJ, achieving a slightly higher $E Q E$ of $40\\%$ in the NIR region. However, the achieved response time on the order of microseconds cannot easily meet the application requirements36. Recently, Wu et al. demonstrated a broadband photodetector with an $E Q E$ of $70\\%$ in the NIR region by coating PTB7-Th:IEICO-4F on $\\mathrm{MAPbI_{3}}^{35}$ . However, the photodetectors did not display an inspiring performance in terms of a lower noise current and an extremely fast response time. State-of-the-art OIHP broadband photodetectors should have a high EQE value in the NIR region, high sensitivity and an ultrafast response speed. However, no such results have been reported to date. Compared with previously reported NIR materials such as PDPPTDTPT, PDPP3T, and IEICO-4F, a fused-ring electron acceptor named F8IC with a lower bandgap and higher electron mobility has been successfully synthesized43. F8IC exhibits an extremely low bandgap of $1.43\\mathrm{eV_{:}}$ which matches well with the energy levels of the polymer donor PTB7-Th (highest occupied molecular orbital (HOMO) energy level of $-5.20\\mathrm{eV}_{\\mathrm{i}}$ , Lowest Unoccupied Molecular Orbital (LUMO) energy level of $-3.59\\mathrm{eV})$ to constitute the organic BHJ. The structural formulas of the two materials are shown in the inset of Fig. 1b. Polymer solar cells (PSCs) based on a PTB7-Th:F8IC blend have shown a power conversion efficiency (PCE) of $10.9\\%$ with a high $E Q E$ extending into the NIR region43. Furthermore, the higher electron mobility of F8IC is ten times higher than that of IEICO$\\mathrm{4F^{44,45}}$ , enabling a faster response speed for hybrid photodetectors. In addition, the absorption of fullerenes in the NIR region is very weak, resulting in a low NIR response. The nonfullerene F8IC has a stronger NIR absorption and a better energy level alignment to match the perovskite layers than a fullerene system. F8IC generates excitons, which can be dissociated into electrons and holes under NIR light excitation. Photogenerated electrons will directly transfer to $C_{60}$ and then be collected by the cathodes, while NIR photogenerated holes can be transported to perovskite through PTB7-Th and finally arrive at the anodes through the PTAA layer. Herein, an organic BHJ consisting of PTB7-Th:F8IC is introduced into OIHP to structure photodetectors, yielding a broad $E Q E$ covering $1000\\mathrm{nm}$ with a peak of $54\\%$ in the NIR region. In addition, the photodetectors exhibit a high $D^{*}$ of over $2.3\\times10^{11}$ Jones $\\mathsf{\\Gamma}(\\mathrm{cm\\Hz^{1/2}\\ W^{-1}})$ at $870\\mathrm{nm}$ and an ultrafast response time of $5.6\\mathrm{ns}$ . To the best of our knowledge, this is the top-ranking level response speed reported for NIR OIHP photodetectors. More importantly, the broadband photodetector has practical application ability, which is demonstrated with high-quality imaging in both the visible and NIR ranges due to its high-dynamic-range imaging capacity. We believe that state-of-the-art hybrid perovskite photodetectors can provide a powerful supplement for inorganic counterparts to meet more energetic requirements. \n\n![](images/bc8d7b0e7243b1ce479dd02c88f41adddd87703f431b5fdd7ca4935c40cea964.jpg) \nFig. 1 a Schematic device structure of the photodetectors. b Absorption spectra of different films by spin coating. Chemical structures of F8IC an PTB7-Th (inset). \n\n# Results and discussion \n\nFig. 1a shows a schematic structure of the OIHP/BHJ photodetectors, which consist of indium tin oxide (ITO)/ poly(bis(4-phenyl) (2,4,6-trimethylphenyl) amine (PTAA)/ $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ $\\mathrm{(MAPbI_{3})}$ /F8IC:PTB7-Th/ $C_{60}/$ 2,9-dimethyl4,7- diphenyl-1,10-phenanthroline (BCP)/copper $\\mathrm{(Cu)}$ . The OIHP polycrystalline films were grown equably on PTAAmodified ITO conductive glass, and the F8IC:PTB7-Th film acted as an NIR light photosensitive layer on the OIHP active layer. Fig. 1b shows the absorption spectra of pure $M{\\mathrm{APbI}_{3}},$ F8IC:PTB7-Th and MAPbI3/F8IC:PTB7-Th composite films. The BHJ film reveals a dominant absorption band covering $550\\mathrm{nm}$ to $1000\\mathrm{nm}$ with a visible peak at $710\\mathrm{nm}$ and an NIR peak at $850\\mathrm{nm}$ . Benefitting from the NIR complementation, the MAPbI3/F8IC:PTB7-Th composite film exhibits a broader absorption in the region of $400{-}1000\\mathrm{nm}$ than pure $\\mathrm{MAPbI}_{3}$ $(400-780\\mathrm{nm},$ ), confirming the theoretical feasibility of fabricating UV-visNIR broadband photodetectors. \n\nFig. 2a shows the $E Q E$ spectra of perovskite/BHJ photodetectors measured at zero bias. The response spectrum of the photodetectors can be extended to $1000\\mathrm{nm}$ , which is in accordance with the composite absorption range. The photoresponse provided by the BHJ is ideally complementary to that of halide perovskites, significantly enhancing the $E Q E$ spectra from \n\n600 to $1000\\mathrm{nm}$ for the $\\mathbf{MAPbI}_{3}$ photodetectors. Encouragingly, the $E Q E$ value of $54\\%$ at $850\\mathrm{nm}$ for the perovskite/BHJ photodetectors provides direct evidence that the charge carriers generated in the NIR region can be sufficiently collected by the electrodes. Fig. 2b displays the energy level diagram of the perovskite/BHJ photodetectors. In principle, a strictly matched energy level for electron and hole transport can enable good device performance. The NIR photogenerated holes may be extracted completely by $\\mathbf{MAPbI_{3}}$ due to the proper alignment of the energy level. To deeply investigate the mechanism of the charge transport in the interface between the organic BHJ and perovskite, photoluminescence (PL) spectra of the films were measured as shown in Fig. 2c using excitation light at $380\\mathrm{nm}$ . The PL intensity of F8IC:PTB7- $\\mathrm{Th}/\\mathrm{MAPbI_{3}}$ decreases sharply compared with that of $\\mathrm{F8IC/MAPbI_{3}}$ , indicating that more electrons are extracted and transported through the films when mixing F8IC and PTB7-Th as the donoracceptor $\\mathrm{BHJ}^{46,47}$ . The luminescence characteristics provide direct evidence that a more brilliant interface state and interlayer coupling is achieved between the $\\mathbf{MAPbI}_{3}$ and F8IC:PTB7-Th layer and that the carriers can transfer effectively at the interface. The NIR photogenerated electrons will be collected by the cathode through the $C_{60}$ electron transport layer, and the NIR photogenerated holes can be transported via perovskite to the ITO anode owing to the high hole mobility of $\\mathbf{MAPbI_{3}}$ . On the other hand, the UV-visible photogenerated electrons in the perovskite layer can be transported to the cathode through the organic BHJ layer and $C_{60},$ with the photogenerated holes collected directly by the anode. This working photodetector mechanism ensures the effective detection of both UVvisible and NIR light, which provides theoretical guidance for broadband photodetection. \n\n![](images/66151856c7933b43cffb5702476c3f80ea57a4fc6a728b1cd7853557c1dcdc88.jpg) \nFig. 2 a EQE curves of the perovskite/organic BHJ hybrid photodetectors, pure perovskite and pure BHJ devices at zero bias and $70\\vdash\\l\\vdash$ b Band energy level alignment of the perovskite/organic BHJ hybrid photodetectors in this study. c PL of the film of $M A P b|_{3}$ bound to different materials. d Responsivity of the corresponding perovskite/organic BHJ hybrid broadband photodetector. \n\nFig. 2d indicates the responsivity $(R)$ curves of the photodetectors, which can be expressed from the $E Q E$ curve according to the equation \n\n$$\nR=E Q E\\times q\\lambda/h c\n$$ \n\nwhere $h$ is Plank’s constant, $c$ is the velocity of light, $q$ is the absolute value of the electron charge, and $\\lambda$ is the light wavelength. The OIHP photodetectors exhibit a wide range from $300\\mathrm{nm}$ to $1000\\mathrm{nm}$ , and the peak in the NIR region can reach up to $0.37\\mathrm{AW}^{-1}$ $(870\\mathrm{nm})$ accompanied by approximately $0.43\\mathrm{\\AW}^{-1}$ in the visible spectrum. Fig. 3a displays the dark current and photocurrent (under air mass $1.5\\mathrm{G}$ illumination) density curve of the perovskite/organic BHJ photodetectors for voltages ranging between $-0.3$ and $1.2\\mathrm{V}$ . The dark current density is as low as $3.4\\times10^{-8}\\mathrm{Acm}^{-2}$ at $-0.1\\mathrm{V}$ , suggesting a relatively low noise current and high sensitivity. As shown in Fig. 3b (inset), the noise current of the perovskite/BHJ photodetector is $3.6\\times10^{-13}\\mathrm{A}\\mathrm{Hz}^{-1}$ at $70\\mathrm{Hz}$ (corresponding to the frequency of the $E Q E$ measurement). The actual detection capability of the photodetectors to monitor weak signals can be expressed by the specific detectivity $(D^{*})$ determined by the responsivity and noise of the photodetectors, which can be calculated by the following equations:48 \n\n$$\n\\begin{array}{l}{{\\displaystyle D^{*}=\\frac{\\sqrt{A B}}{N E P}\\left(c m H z^{-1/2}W^{-1}o r J o n e s\\right)}}\\\\ {{\\displaystyle\\mathrm{NEP}=\\frac{i_{n}}{R}\\left(\\mathbb{W}\\mathrm{Hz}^{-1/2}\\right)}}\\end{array}\n$$ \n\nwhere $A$ is the active layer area, $i_{\\mathrm{n}}$ is the noise current, $B$ is the bandwidth and NEP is the noise equivalent power. As shown in Fig. 3b, the hybrid perovskite/organic BHJ photodetectors exhibit a $D^{*}$ of $2.{\\overset{\\cdot}{3}}\\times10^{11}$ Jones $(\\mathrm{cm\\bar{H}z^{1/2}W^{-1}})$ in the $870\\mathrm{nm}$ NIR region, indicating the high performance of the fabricated broadband photodetector. Fig. 3c displays the trap density of states $(t_{\\mathrm{DOS}})$ obtained by thermal admittance spectroscopy of two different devices48,49. The pure perovskite photodetectors possess a relatively large density of defect states of $3\\times{10}^{18}$ to $\\mathsf{\\bar{6}}\\times10^{18}\\mathrm{m^{-3}e V^{-1}}$ without the BHJ. However, the hybrid perovskite/BHJ device exhibits reduction in $t_{\\mathrm{{DOS}}}$ of nearly one order of magnitude. This result can perfectly verifies the low trap density of our broadband photodetectors and is important for a fast photodetector response. \n\nIn practical photodetector applications, especially in an imaging system, a constant responsivity covering a large range of light intensities is critically significant for extracting the specific intensity of the detected light from the corresponding photocurrent. The linear weak-light response range is always characterized by the linear dynamic range (LDR), defined as an optical power margin within which the output photocurrent is linearly proportional to optical signal input: \n\n$$\n\\mathrm{LDR}=20\\times\\log{\\frac{P_{\\mathrm{max}}}{P_{\\mathrm{min}}}}\n$$ \n\nwhere $P_{\\mathrm{max}}$ and $P_{\\mathrm{min}}$ are the upper and lower limits of the optical power in a particular range. Notably, a sufficiently large LDR means maintaining a constant responsivity from strong light to weak light conditions and is a precondition for weak light sensing. Fig. 3d, e show the LDR of photodetectors illuminated by LEDs with different wavelengths ( $475\\mathrm{nm}$ and $870\\mathrm{nm})$ . It can be clearly observed that the photocurrent density increases linearly for a dynamic light intensity ranging from $2.5\\mathrm{pW}\\mathrm{cm}^{-2}$ to $5.6\\mathrm{mW}\\mathrm{cm}^{-2}$ with the $475\\mathrm{nm}$ LED and $1.5\\mathrm{pW}\\mathrm{cm}^{-2}$ to $5.6\\mathrm{mW}\\mathrm{cm}^{-2}$ with the $870\\mathrm{nm}$ LED. This result corresponds to LDR values of 187 dB $(475\\mathrm{nm})$ and 191 dB $(870\\mathrm{nm})$ , respectively, demonstrating the universal applicability of our device to various light sources, which is an essential prerequisite in a high-quality imaging system. Such a linear response may result from the excellent carrier transport property of the perovskite with the BHJ and the low electron trap density in the whole photodetector. \n\nFinally, the response speed of this broadband photodetector is discussed in detail to completely characterize its performance parameters. The light response speed is a significant core performance parameter that determines the quality of photodetectors. A general method that is used to meausre an ultrafast response speed is the transient photocurrent $\\left(\\mathrm{TPC}\\right)^{12,14}$ . The photodetectors collect the pulsed light signal emitted by a pulsed laser, and then the photogenerated carriers can be driven by a built-in potential field or external voltage bias applied to the respective electrodes. Therefore, the response speed can be defined as the photocurrent decay time from the peak down to approximately $1/\\mathrm{e}$ after a single exponential fit to the TPC curve. Excited by a pulsed laser at a wavelength of $850\\mathrm{nm}.$ , the normalized TPC curves of the photodetectors with different active areas are shown in Fig. 3f. The response time of the perovskite/organic BHJ photodetectors is calculated to be 145 ns for a relatively large active area of $4.4\\mathrm{mm}^{2}$ and 19 ns for small devices with an area of $0.6\\mathrm{mm}^{2}$ . This indicates that the response time is limited by the resistance-capacitance (RC) time constant, which is typically mixed with the carrier transit time, resulting in a deviation of the actual response speed. \n\n![](images/f88c1f1b4de327dca340aadfd36da66b3c65967825200c215e068500a00b74cf.jpg) \nFig. 3 a Photocurrent density (under air mass $1.5\\mathsf{G}$ illumination) and dark current density curves of the broadband photodetectors. b Specific detectivity $D^{*}$ of the broadband photodetector at various light wavelengths under a bias voltage of $-0.1\\ V.$ c Trap density of states curves of the perovskite/BHJ hybrid photodetectors. d Linear dynamic range of the broadband photodetectors under $475\\mathrm{-nm}$ LED illumination with various light intensities. The solid line represents linear fitting to the data. e LDR under $870–\\mathsf{n m}$ LED illumination. f Transient photocurrent curves of the broadband photodetector with device areas of 0.6 and $4.4\\mathsf{m m}^{2}$ . Inset: TPC curve of the ultrafast photodetectors with a smaller area of $0.1\\mathrm{mm}^{2}$ . \n\n$$\nf_{\\mathrm{-3dB}}^{-2}=\\left({\\frac{3.5}{2\\pi t_{\\mathrm{tr}}}}\\right)^{-2}+\\left({\\frac{1}{2\\pi\\mathrm{RC}}}\\right)^{-2}\n$$ \n\nwhere $t_{\\mathrm{tr}}$ is the carrier transit time and the RC time is the resistance-capacitance time constant of the circuit. In Fig. 3f (inset), to ensure the operation of the device, we reduced the area of the best performing device to $0.1\\mathrm{mm}^{2}$ and obtained an ultrafast speed of 5.6 ns at zero bias. This ultrafast response is also commendable in the field of infrared photodetectors50. The outstanding response speed is due to a variety of causes, including the low trap density of the active layers, higher carrier mobility of the transport layers and suppression of the RC time. Herein, the RC time and transit time of the whole device are estimated based on the reported carrier mobility of the material and the actual thickness of each layer of the photodetectors. The calculation process is described in the supporting information, which obtains an RC time of 2.3 ns as calculated by Eqs. 1 and 2 in the SI, indicating the veracity of the practically measured response speed of 5.6 ns by the TPC method. The response time of the perovskite/organic BHJ photodetectors with an active area of $4.4\\mathrm{mm}^{2}$ was also tested by the standard square wave method, and a rise/fall time of ${\\sim}35/20\\upmu\\mathrm{s}$ was obtained, as shown in Supplementary Fig. S2. \n\nTo further demonstrate the practical feasibility of the high-performance broadband photodetectors, we explored the functional role of the devices in imaging technology51–54. Generally, the photosensitive component in mature imaging fields such as digital cameras is a charge-coupled device (CCD), which can sense light and convert the image into digital form. From a functional point of view, the CCD components can be replaced with perovskite/BHJ broadband photodetectors to a certain extent. Herein, we adopt a high-performance imaging experiment to verify the high detectivity, broadband detection and ultrafast response of the OHIP photodetectors. The broadband photodetector scans the imaging target in two dimensions via the driving of the twodimensional turntable, and the photocurrent of each pixel is recorded, avoiding the complicated structure of array imaging sensors. Considering that the response of the perovskite/BHJ photodetectors covers a wide wavelength range, including the NIR region, a blackbody-like, radiant heat source is employed as an imaging target. Detailed imaging devices and processes are shown in Fig. 4a. The light of the imaging target passes through the optical system, which can be focused on the sample by lenses. An $830\\mathrm{-nm}$ long-pass filter is placed in front of the lens to eliminate the effects of the band before $830\\mathrm{nm}$ when NIR imaging alone is required. The current generated by the sample flows through resistance, and the voltage signal across the resistance can be output by the amplifier. The corresponding image is transmitted from the output voltage of each pixel to the computer via the gray code operator55. Fig. 4b shows the visible and NIR imaging results of the radiation source. The profile of the heat coil can be clearly captured in both the visible and NIR bands, and the change in the photocurrent intensity of the corresponding graphical position displays an obvious difference between the visible and NIR regions. This means that our device can completely distinguish the target in the environment and restore the display to a certain extent, highlighting the visible-NIR dual-waveband recognition imaging ability of perovskite broadband photodetectors. Moreover, for more realistic scenarios, we designed SITP letter graphics on an LED screen to verify the imaging capability of perovskite photodetectors for a more complex target. Using the same method, a highquality image is achieved based on the corresponding voltage and position, which is illustrated in Fig. 4c. The pattern of letters with sharp boundaries is obtained, and simultaneously, the consistency of the position or distance between the images and objects proves the high fidelity of our photodetectors in the field of imaging. Here, we attribute the results to the high-dynamic-range imaging (HDRI) capability of the photodetectors, which is a crucial feature for high-quality imaging. When the high brightness and shadow areas of an actual image object have sharp contrast, image sensors with an inferior HDRI capability tend to obscure low-brightness targets with noise. The high brightness of a target will result in corresponding pixel saturation and even overflow, leading to an unclear image. In this study, the optical power exhibits a gradient from the background to the pattern body, meaning that the three parts of the “background - pattern edge - pattern body” have different optical powers. By successfully capturing this difference and demonstrating a significant imaging result, the preeminent HDRI capability of the perovskite photodetector is validated. The intensities of white light signals are clearly distinguished by the contrasting colors in Fig. 4c. The dynamic photocurrent intensity along the dotted line reveals the weak light extraction ability of the broadband photodetector and the realization of large-dynamic-range imaging. Benefiting from the excellent intrinsic performance of perovskite photodetectors with high sensitivity, low noise, and a large LDR, the difficulty of complex algorithm processing for high-quality imaging is greatly reduced. Moreover, relevant studies may further improve the imaging capabilities by adjusting the device size, adding pixels, and designing an array geometry. \n\n![](images/427fd9de9b868a8edc039c2369a2bfe1ed861b87484d1c390d45b7dc94371117.jpg) \nFig. 4 a Schematic of the image scanning system and actual imaging for the OIHP photodetector. b Visible and NIR (with an $830–\\mathsf{n m}$ longpass filter) imaging results of the heat coil. c Imaging of SITP (an abbreviation of Shanghai Institute of Technology and Physics) letter graphics under LED illumination. The white and blue lines in the figure represent the normalized photocurrent signal intensity. \n\nIn summary, we have demonstrated solution-processed UV-vis-NIR broadband photodetectors based on $\\mathbf{MAPbI}_{3}$ and an organic BHJ, achieving broadband response spectra up to $1000\\mathrm{nm}$ with an $E Q E$ peak of $54\\%$ in the NIR region. The response time of 5.6 ns represents the fastest speed of perovskite broadband photodetectors. Importantly, the large LDR of the photodetectors contributes to high-dynamic-range imaging, and the superior processing capacity of the photodetectors for actual imaging applications has practical application value in many fields. We believe that our results can inspire more fundamental or extended studies in the future. \n\n# Materials and methods Materials \n\n$\\mathrm{PbI}_{2}$ $(>99.99\\%)$ , MAI, and PTAA were purchased from Xi’an p-OLED (Xi’an China). Bathocuproine (BCP) and fullerene $\\left(\\mathrm{C}_{60}\\right)$ were obtained from Lumtec (Taiwan, China). PTB7-Th was purchased from A One Material (Taiwan, China). These materials were used as received. \n\n# Device fabrication and measurements \n\nAll of the solutions were prepared at room temperature in an air environment. The PTAA was dissolved in toluene at a concentration of $2\\mathrm{mg}\\mathrm{mL}^{-1}$ . To fabricate the perovskite film, we adopted the common one-step method: $\\mathrm{PbI}_{2}$ and MAI molar ratio 1:1 was dissolved in a 9:1 DMF (dimethylformamide):DMSO (dimethyl sulfoxide) mixed solution to make a $\\mathbf{MAPbI}_{3}$ prosomatic solution with a concentration of $0.75\\mathrm{mol}\\mathrm{mL}^{-1}$ , and the solution was magnetically stirred at $60^{\\circ}\\mathrm{C}$ until completely dissolved. For the organic donor-acceptor BHJ layer, F8IC: PTB7-Th were mixed and dissolved in chlorobenzene (CB) in a 1:1 proportion (the concentration of the mixed solution was $10\\mathrm{mg/mL}$ ). Then, the mixed solution was magnetically stirred at room temperature for $6{-}10\\mathrm{h}$ . \n\nThe macrostructure of our photodetector is shown in Fig. 1b. The ITO substrates were ultrasonically cleaned by acetone and ethanol for $20\\mathrm{min}$ and treated with UV ozone for $10\\mathrm{min}$ . Then, a thin PTAA layer was simply spin-coated at $4000{\\mathrm{r.p.m}}$ . for $40\\mathrm{{s}}$ on the ITO surface, and the substrates were baked at $100^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . The $\\mathbf{MAPbI}_{3}$ solution was deposited onto the prepared HTL films at $4000{\\mathrm{r.p.m}}$ . for $40{\\mathsf s}$ , cleaned by anhydrous toluene, and then annealed at $100^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ to obtain a perovskite active layer. Subsequently, the hybrid F8IC: PTB7-Th solution was spin-coated on the perovskite film at $2000~\\mathrm{\\rpm}$ and annealed at $80^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . $\\mathrm{C}_{60}$ (varying the thickness as required) and BCP (7 nm) were thermally evaporated by vapor deposition onto the organic BHJ layer. The evaporation rates was approximately $0.03\\mathrm{nm/s}$ for C6 $_{\\mathrm{~\\tiny~3~}0.03\\mathrm{~nm/s~}}$ for BCP, and $0.06\\mathrm{nm/s}$ for Cu. Finally, the devices were completed by depositing a 100-nm Cu electrode. Thus far, a device with an effective area of $0.044\\mathrm{cm}^{-2}$ has been completely manufactured. \n\nA Shimadzu UV-1700 Pharma Spec UV spectrophotometer was used to measure the absorption spectra of the OIHP photodetectors. A Shimadzu RF 5301 fluorescence spectrophotometer was used to obtain the PL spectra of our devices. The external quantum efficiencies were measured by a Crowntech $\\mathrm{\\DeltaQ}$ test Station 1000 AD measurement system. The $J{-}V$ curves of our photodetectors in the dark and under illumination were obtained by a Keithley 2601 source meter. The incident light was provided by AM $1.5\\mathrm{G}$ solar illumination with an Oriel $300\\mathrm{W}$ solar simulator intensity of $100\\mathrm{mW}\\mathrm{cm}^{-2}$ . The noise current was analyzed by a ProPlus 9812D waferlevel 1/f noise characterization system. The measurement of the response speed was carried out by the transient photocurrent (TPC) method: A gold probe was used in the TPC measurement to minimize the external impact caused by the poor transmission of the electrical signals. The area of the pulsed beam was $10\\mathrm{mm}^{2}$ , larger than the device area. The rated power of the Ti:Sapphire femtosecond laser is $1\\mathrm{W}$ , with a $1\\mathrm{kHz}$ repetition rate. The pulsed Ti-sapphire femtosecond laser was prepared as the optical source, and the luminescence wavelength was set to $850\\mathrm{nm}$ , with frequency doubling and a pulse duration of 150 fs. The photodetectors collected the pulsed light signal emitted by the pulsed laser, and then a 1 GHz oscilloscope with a 5 GHz sampling rate recorded the current pulse and generated the corresponding TPC curve. The response speed can be defined as the photocurrent decay time from the peak down to approximately $1/\\mathrm{e}$ after a single exponential fit to the TPC curve. To minimize the influence of the inductance of the whole circuit, the cables connecting the device and oscilloscope should be as short as possible and connected with a fast $(6\\mathrm{GHz})$ bayonet NeillConcelman connector. In addition, the measurement environment was kept at room temperature with no light sources other than the lasers. In addition, the environmental conditions of the photodetector performance measurement were room temperature $(25^{\\circ}\\mathrm{C})$ , $20\\%$ humidity, and normal pressure. The imaging process was generally conducted at room temperature $(25^{\\circ}\\mathrm{C})$ , a humidity of $>45\\%$ , and an imaging time of $>\\mathrm{1h}$ . \n\n# Acknowledgements \n\nThe authors are grateful to the National Natural Science Foundation of China (Grant no. 61875072), Joint Fund of Pre-research for the Ministry of Equipment and Education (Grant no. 6141A02033409), International Cooperation and Exchange Project of Jilin Province (Grant no. 20170414002GH), Science and Technology Project of Education Department of Jilin Province (Grant no. JJKH20190011KJ), Key Research Project of Frontier Science of CAS (Grant no. QYZDB-SSW-JSC031), Fund of Shanghai Natural Science Foundation (Grant nos. 19XD1404100, 18ZR1445900, 19YF1454600, and 18ZR1445800), Open Fund of the State Key Laboratory of Integrated Optoelectronics (Grant no. IOSKL2019KF05), Special Grants from China Post-doctoral Science Foundation (pre-station) (Grant no. 2019TQ0333), and Fund of SITP Innovation Foundation (Grant no. CX-239, CX-292) for supporting this work. \n\n# Author details \n\n1State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 2699 Qianjin Street, Changchun 130012, China. 2State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, 500 Yutian Road, Shanghai 200083, China. 3University of Chinese Academy of Sciences, Beijing 100049, China. 4Department of Materials Science and Engineering, College of Engineering, Key Laboratory of Polymer Chemistry and Physics of Ministry of Education, Peking University, Beijing 100871, China \n\n# Author contributions \n\nL.S. and W.H. conceived the concept and designed the experiments. C.L. and H. W. performed the device fabrication and characterization. C.L., H.W. and F.W. performed the data analysis. T.L. and $\\times.2.$ helped in the synthesis of F8IC. All authors contributed to writing and reviewing the manuscript. \n\n# Conflict of interest \n\nThe authors declare that they have no conflict of interest. \n\nSupplementary information is available for this paper at https://doi.org/ 10.1038/s41377-020-0264-5. \n\nReceived: 1 December 2019 Revised: 28 January 2020 Accepted: 15 \nFebruary 2020 \nPublished online: 03 March 2020 \n\n# References \n\n1. Bi, C. et al. Understanding the formation and evolution of interdiffusion grown organolead halide perovskite thin films by thermal annealing. J. Mater. Chem. A 2, 18508–18514 (2014). \n2. Fang, Y. J. et al. Highly narrowband perovskite single-crystal photodetectors enabled by surface-charge recombination. Nat. Photonics 9, 679–686 (2015). \n3. De Arquer, F. P. G. et al. Solution-processed semiconductors for nextgeneration photodetectors. Nat. Rev. Mater. 2, 16100 (2017). \n4. Koppens, F. H. L. et al. Photodetectors based on graphene, other twodimensional materials and hybrid systems. Nat. Nanotechnol. 9, 780–793 (2014). 5. Maria, A. et al. Solution-processed infrared photovoltaic devices with $>10\\%$ monochromatic internal quantum efficiency. Appl. Phys. Lett. 87, 213112 (2005). 6. Xie, Y. M. et al. Broad-spectral-response nanocarbon bulk-heterojunction excitonic photodetectors. Adv. Mater. 25, 3433–3437 (2013). 7. Long, M. S. et al. Palladium diselenide long-wavelength infrared photodetector with high sensitivity and stability. ACS Nano 13, 2511–2519 (2019). 8. Zhou, X. K., Yang, D. Z. & Ma, D. G. Extremely low dark current, high responsivity, all-Polymer photodetectors with spectral response from 300 nm to 1000 nm. Adv. Optical Mater. 3, 1570–1576 (2015). 9. Dong, R. et al. An ultraviolet-to-NIR broad spectral nanocomposite photodetector with gain. Adv. Optical Mater. 2, 549–554 (2014). \n10. Simone, G. et al. Organic photodetectors and their application in large area and flexible image sensors: the role of dark current. Adv. Funct. Mater., https:// doi.org/10.1002/adfm.201904205 (2019). \n11. Dou, L. T. et al. Solution-processed hybrid perovskite photodetectors with high detectivity. Nat. Commun. 5, 5404 (2014). \n12. Fang, Y. J. & Huang, J. S. Resolving weak light of sub-picowatt per square centimeter by hybrid perovskite photodetectors enabled by noise reduction. Adv. Mater. 27, 2804–2810 (2015). \n13. Sutherland, B. R. et al. Sensitive, fast, and stable perovskite photodetectors exploiting interface engineering. ACS Photonics 2, 1117–1123 (2015). \n14. Shen, L. et al. A self-powered, sub-nanosecond-response solution-processed hybrid perovskite photodetector for time-resolved photoluminescence-lifetime detection. Adv. Mater. 28, 10794–10800 (2016). \n15. Shen, L. et al. A highly sensitive narrowband nanocomposite photodetector with gain. Adv. Mater. 28, 2043–2048 (2016). \n16. Shen, L. et al. Integration of perovskite and polymer photoactive layers to produce ultrafast response, ultraviolet-to-near-infrared, sensitive photodetectors. Mater. Horiz. 4, 242–248 (2017). \n17. Guo, F. W. et al. A nanocomposite ultraviolet photodetector based on interfacial trap-controlled charge injection. Nat. Nanotechnol. 7, 798–802 (2012). \n18. Dong, R. et al. High-gain and low-driving-voltage photodetectors based on organolead triiodide perovskites. Adv. Mater. 27, 1912–1918 (2015). \n19. Gong, X. et al. High-detectivity polymer photodetectors with spectral response from $300\\ \\mathsf{n m}$ to 1450 nm. Science 325, 1665–1667 (2009). \n20. Zimmerman, J. D. et al. Porphyrin-tape $10\\text{\\textperthousand}$ organic photodetectors with $6.5\\%$ external quantum efficiency in the near infrared. Adv. Mater. 22, 2780–2783 (2010). \n21. Yang, W. S. et al. Iodide management in formamidinium-lead-halide–based perovskite layers for efficient solar cells. Science 356, 1376–1379 (2017). \n22. Tan, H. R. et al. Efficient and stable solution-processed planar perovskite solar cells via contact passivation. Science 355, 722–726 (2017). \n23. Jeon, N. J. et al. A fluorene-terminated hole-transporting material for highly efficient and stable perovskite solar cells. Nat. Energy 3, 682–689 (2018). \n24. Kagan, C. R., Mitzi, D. B. & Dimitrakopoulos, C. D. Organic-inorganic hybrid materials as semiconducting channels in thin-film field-effect transistors. Science 286, 945–947 (1999). \n25. Kojima, A. et al. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n26. Heo, J. H. et al. Efficient inorganic-organic hybrid heterojunction solar cells containing perovskite compound and polymeric hole conductors. Nat. Photonics 7, 486–491 (2013). \n27. Chen, Q. et al. Planar heterojunction perovskite solar cells via vapor-assisted solution process. J. Am. Chem. Soc. 136, 622–625 (2014). \n28. Tan, Z. K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n29. Chin, X. Y. et al. Lead iodide perovskite light-emitting field-effect transistor. Nat. Commun. 6, 7383 (2015). \n30. Adinolfi, V. et al. Fast and sensitive solution-processed visible-blind perovskite UV photodetectors. Adv. Mater. 28, 7264–7268 (2016). \n31. Shrestha, S. et al. High-performance direct conversion X-ray detectors based on sintered hybrid lead triiodide perovskite wafers. Nat. Photonics 11, 436–440 (2017). \n32. Ka, I. et al. High-performance nanotube-enhanced perovskite photodetectors. Sci. Rep. 7, 45543 (2017). \n33. Wu, X. H. et al. Distinguishable detection of ultraviolet, visible, and infrared spectrum with high-responsivity perovskite-based flexible photosensors. Small \n14, 1800527 (2018). \n34. Kim, Y. C. et al. Printable organometallic perovskite enables large-area, lowdose X-ray imaging. Nature 550, 87–91 (2017). \n35. Wu, G. et al. Perovskite/organic bulk-heterojunction integrated ultrasensitive broadband photodetectors with High near-infrared external quantum efficiency over $70\\%.$ Small 14, 1802349 (2018). \n36. Wang, Y. K. et al. Perovskite/polymer hybrid thin films for high external quantum efficiency photodetectors with wide spectral response from visible to near-infrared wavelengths. Adv. Optical Mater. 5, 1700213 (2017). \n37. Bi, D. Q. et al. Efficient luminescent solar cells based on tailored mixed-cation perovskites. Sci. Adv. 2, e1501170 (2016). \n38. Park, N. G. et al. Towards stable and commercially available perovskite solar cells. Nat. Energy 1, 16152 (2016). \n39. Correa-Baena, J. P. et al. Promises and challenges of perovskite solar cells. Science 358, 739–744 (2017). \n40. Green, M. ${\\mathsf A}_{\\cdot},$ Ho-Baillie, A. & Snaith, H. J. The emergence of perovskite solar cells. Nat. Photonics 8, 506–514 (2014). \n41. Saidaminov, M. I. et al. Perovskite photodetectors operating in both narrowband and broadband regimes. Adv. Mater. 28, 8144–8149 (2016). \n42. Sun, H. X. et al. Ultrahigh-performance self-Powered flexible double-twisted fibrous broadband perovskite photodetector. Adv. Mater. 30, 1706986 (2018). \n43. Dai, S. X. et al. Enhancing the performance of polymer solar cells via core engineering of NIR-absorbing electron acceptors. Adv. Mater. 30, 1706571 (2018). \n44. Yao, H. F. et al. Design and synthesis of a low bandgap small molecule acceptor for efficient polymer solar cells. Adv. Mater. 28, 8283–8287 (2016). \n45. Yao, H. F. et al. Design, synthesis, and photovoltaic characterization of a small molecular acceptor with an ultra-narrow band gap. Angew. Chem. Int. Ed. 56, \n3045–3049 (2017). \n46. Kim, J. et al. Excitation density dependent photoluminescence quenching and charge transfer efficiencies in hybrid perovskite/organic semiconductor bilayers. Adv. Energy Mater. 8, 1802474 (2018). \n47. Wolff, C. M. et al. Reduced interface-mediated recombination for high opencircuit voltages in $C H_{3}N H_{3}P b l_{3}$ solar cells. Adv. Mater. 29, 1700159 (2017). \n48. Wei, H. T. et al. Trap engineering of CdTe nanoparticle for high gain, fast response, and low noise P3HT:CdTe nanocomposite photodetectors. Adv. Mater. 27, 4975–4981 (2015). \n49. Fang, Y. J. et al. Large gain, low noise nanocomposite ultraviolet photodetectors with a linear dynamic range of 120 dB. Adv. Optical Mater. 2, \n348–353 (2014). \n50. Ullbrich, S. et al. Fast organic near-infrared photodetectors based on chargetransfer absorption. J. Phys. Chem. Lett. 8, 5621–5625 (2017). \n51. Lee, S. J. et al. A monolithically integrated plasmonic infrared quantum dot camera. Nat. Commun. 2, 286 (2011). \n52. Wilkins, S. W. et al. Phase-contrast imaging using polychromatic hard X-rays. Nature 384, 335–338 (1996). \n53. Gu, L. L. et al. 3D Arrays of 1024-pixel image sensors based on lead halide perovskite nanowires. Adv. Mater. 28, 9713–9721 (2016). \n54. Deng, W. et al. Aligned single-crystalline perovskite microwire arrays for highperformance flexible image sensors with long‐term stability. Adv. Mater. 28, \n2201–2208 (2016). \n55. Wang, P. et al. Arrayed van der Waals broadband detectors for dual-band detection. Adv. Mater. 29, 1604439 (2017). " + }, + { + "id": "10.1038_s41929-020-0498-x", + "DOI": "10.1038/s41929-020-0498-x", + "DOI Link": "http://dx.doi.org/10.1038/s41929-020-0498-x", + "Relative Dir Path": "mds/10.1038_s41929-020-0498-x", + "Article Title": "A fundamental look at electrocatalytic sulfur reduction reaction", + "Authors": "Peng, LL; Wei, ZY; Wan, CZ; Li, J; Chen, Z; Zhu, D; Baumann, D; Liu, HT; Allen, CS; Xu, X; Kirkland, AI; Shakir, I; Almutairi, Z; Tolbert, S; Dunn, B; Huang, Y; Sautet, P; Duan, XF", + "Source Title": "NATURE CATALYSIS", + "Abstract": "The fundamental kinetics of the electrocatalytic sulfur reduction reaction (SRR), a complex 16-electron conversion process in lithium-sulfur batteries, is so far insufficiently explored. Here, by directly profiling the activation energies in the multistep SRR, we reveal that the initial reduction of sulfur to the soluble polysulfides is relatively easy owing to the low activation energy, whereas the subsequent conversion of the polysulfides into the insoluble Li2S2/Li2S has a much higher activation energy, contributing to the accumulation of polysulfides and exacerbating the polysulfide shuttling effect. We use heteroatom-doped graphene as a model system to explore electrocatalytic SRR. We show that nitrogen and sulfur dual-doped graphene considerably reduces the activation energy to improve SRR kinetics. Density functional calculations confirm that the doping tunes the p-band centre of the active carbons for an optimal adsorption strength of intermediates and electroactivity. This study establishes electrocatalysis as a promising pathway to tackle the fundamental challenges facing lithium-sulfur batteries.", + "Times Cited, WoS Core": 593, + "Times Cited, All Databases": 612, + "Publication Year": 2020, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000564491500001", + "Markdown": "# A fundamental look at electrocatalytic sulfur reduction reaction \n\nLele Peng $\\mathbf{\\textcircled{1}{}^{1}}$ , Ziyang Wei1, Chengzhang Wan1, Jing Li1, Zhuo Chen $\\oplus2$ 2, Dan Zhu1, Daniel Baumann1, Haotian Liu2, Christopher S. Allen $\\textcircled{10}3.4$ , Xiang $\\mathsf{\\pmb{X}}\\mathsf{\\pmb{u}}^{1}$ , Angus I. Kirkland $\\textcircled{10}3.4$ , Imran Shakir2,5, Zeyad Almutairi   5, Sarah Tolbert1,6, Bruce Dunn2,6, Yu Huang   2,6 ✉, Philippe Sautet   1,7 ✉ and Xiangfeng Duan   1,6 ✉ \n\nThe fundamental kinetics of the electrocatalytic sulfur reduction reaction (SRR), a complex 16-electron conversion process in lithium–sulfur batteries, is so far insufficiently explored. Here, by directly profiling the activation energies in the multistep SRR, we reveal that the initial reduction of sulfur to the soluble polysulfides is relatively easy owing to the low activation energy, whereas the subsequent conversion of the polysulfides into the insoluble ${\\bf L i}_{2}\\mathbb{S}_{2}/{\\bf L i}_{2}\\mathbb{S}$ has a much higher activation energy, contributing to the accumulation of polysulfides and exacerbating the polysulfide shuttling effect. We use heteroatom-doped graphene as a model system to explore electrocatalytic SRR. We show that nitrogen and sulfur dual-doped graphene considerably reduces the activation energy to improve SRR kinetics. Density functional calculations confirm that the doping tunes the $\\pmb{p}$ -band centre of the active carbons for an optimal adsorption strength of intermediates and electroactivity. This study establishes electrocatalysis as a promising pathway to tackle the fundamental challenges facing lithium–sulfur batteries. \n\nhe sulfur reduction reaction (SRR) in lithium–sulfur chemistry undergoes a complex 16-electron conversion process, transforming $S_{\\mathrm{8}}$ ring molecules into a series of soluble lithium polysulfides (LiPSs) with variable chain lengths before fully converting them into insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ products. This 16-electron SRR process is of considerable interest for high-density energy storage with a theoretical capacity of $1{,}672\\mathrm{mAhg^{-1}}$ , but the chemistry is plagued by sluggish sulfur reduction kinetics and the polysulfide (PS) shuttling effect. In practical Li–S cells, these effects limit the rate capability and cycle $\\mathrm{life}^{1,2}$ . These limitations are fundamentally associated with the slow and complex reduction reaction involving $S_{\\mathrm{{8}}}$ ring molecules. In general, the insulating nature of elemental sulfur and its reduced products, and the sluggish charge transfer kinetics lead to incomplete conversion of $S_{8}$ molecules into soluble LiPSs. These polysulfides may shuttle across the separator to react with and deposit on the lithium anode, resulting in rapid capacity fading3. Considerable efforts have been devoted to combating the PS shuttling effect, typically by employing a passive strategy that uses various sulfur host materials to physically or electrostatically trap the LiPSs in the cathode structure4–13. These passive confinement/entrapping strategies have partly mitigated the PS shuttling effect and led to improved performance, but are fundamentally incapable of completely preventing the dissolution of LiPSs into the electrolyte. \n\nThe PS shuttling effect originates from the formation, dissolution and accumulation of LiPS intermediates in the electrolyte. In this regard, the slow conversion kinetics of the soluble LiPSs into the insoluble final products leads to continued accumulation of LiPSs in electrolyte that exacerbates the PS shuttling effect14,15. An electrocatalytic approach to accelerate the conversion of soluble \n\nLiPS intermediates into insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ seems to be a natural strategy to prevent the accumulation and shuttling of LiPSs. The use of electrocatalysis would address the PS shuttling effect while simultaneously improving the rate capability. Although the concept of an electrocatalytic approach has been suggested in a few recent studies16–18, the fundamental electrocatalytic kinetics of the SRR are largely unexplored and the underlying basis for using such an electrocatalytic effect to address the PS shuttling issues has not been clearly addressed. \n\nHerein we report a systematic investigation of electrocatalytic SRR kinetics. To understand the catalytic performance of various heteroatom-doped holey graphene framework (HGF) electrocatalysts and their impact on battery performance, we focus on fundamental electrocatalytic studies by systematically probing the reduction kinetics, activation energies and reduction mechanisms. By directly profiling the activation energies in the multistep SRR, we establish how the conversion kinetics differ for each step and reveal that the initial reduction of $S_{\\mathrm{{s}}}$ ring molecules to the soluble PSs is relatively easy owing to the low activation energy $\\left(E_{\\mathrm{a}}\\right)$ , whereas the subsequent conversion of the PSs into the insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ is more difficult due to its much higher $E_{\\mathrm{a}}$ . Herein we used heteroatom-doped HGF as a model system for electrocatalytically tailoring SRR kinetics to accelerate the PS conversion process and combat the PS shuttling effect. Within this system, which consists of a nitrogen and sulfur dual-doped HGF (N,S-HGF) and non-doped or single-doped counterparts, the N,S-HGF exhibits superior SRR catalytic activity with considerably improved kinetics, including higher exchange current density $(J_{0})$ , larger electron transfer number, lower interfacial charge transfer resistance and lower $E_{\\mathrm{a}}.$ Density functional theory (DFT) calculations reveal that the edge carbon atoms adjacent to the heteroatoms serve as the catalytic centres for SRR, and nitrogen and sulfur dual-doping tunes the $\\boldsymbol{p}$ -band centre of the active carbon atoms to achieve an optimal LiS radical adsorption, minimizing the overpotential. Exploiting the unique SRR electrocatalytic performance, the N,S-HGF based electrodes exhibit much improved rate capability and cycling stability, suggesting the electrocatalytic approach represents a promising strategy to tackle the fundamental challenges facing Li–S batteries. \n\n![](images/3b54841064aca3c5d7d738433a0ce9e644d58ace75c57bd006e9638665ac90de.jpg) \nFig. 1 | Activation energy in sulfur reduction and PS conversion reaction. a, A schematic illustration of the SRR process involving the LiPS evolution. b, Discharge profile of the ${\\mathsf{K C B}}/{\\mathsf{S}}$ cathode. The red dashed curve represents the expected LiPS conversion enhanced by catalyst design. c, EIS measurements at various temperatures at $2.7\\mathsf{V}.$ Inset: simplified-contact Randles-equivalent circuit. $Z^{\\prime}$ and $Z^{\\prime\\prime}$ indicate the real and imaginary impedance, respectively; $R_{5},$ internal resistance including the resistances of the electrolyte solution and electrodes; $R_{\\mathsf{C T}}$ resistance associated with charge transfer; $Z_{\\mathrm{w}},$ Warburg resistance; $C_{\\mathsf{s u r f}\\prime}$ capacitance contributed by the surface deposition of $\\mathsf{L i}_{2}\\mathsf{S}_{2}/\\mathsf{L i}_{2}\\mathsf{S};C_{\\mathsf{C T}},$ capacitance contributed by the charge transfer process. d, An Arrhenius plot showing the linear relationship between logarithmic values of the reciprocal of charge transfer resistance and the reciprocal of absolute temperatures for 2.7 V, 2.4 V, 2.1 V and $1.8\\mathsf{V}.$ e, Activation energy profiles at various voltages, highlighting the final step conversion of LiPSs into insoluble products is the rate-determining step and responsible for PS accumulation and shuttling. Error bars indicate the standard deviation of three independent electrodes. \n\n# Results \n\nActivation energy barrier in PS evolution. The sulfur reduction reaction in Li–S chemistry involves multistep evolution of LiPSs during the discharge process. $S_{\\mathrm{8}}$ ring molecules first react with lithium ions to form long-chain $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ at ${\\sim}2.7{-}2.4\\mathrm{V}$ versus the $\\mathrm{Li}/$ $\\mathrm{Li^{+}}$ electrode and then, through successive cleavage of S–S bonds, transform into a series of shorter-chain LiPSs. The moieties include $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ or $\\mathrm{Li}_{2}\\mathrm{S}_{4}$ at ${\\sim}2.3\\substack{-2.1\\mathrm{~V~}}$ before transformation into insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}$ and $\\operatorname{Li}_{2}S$ products at ${\\sim}2.1\\mathrm{-}1.7\\mathrm{V}$ (refs. 19,20) (Fig. 1a,b). The initial cleavage of $S_{8}$ ring molecules is regarded as a relatively easy process, whereas subsequent cleavage into shorter-chain LiPSs becomes progressively more difficult, and the last steps of the conversion into insoluble products are particularly slow21,22. The SRR kinetics at each step may be fundamentally represented by $E_{\\mathrm{a}}$ . To this end, we have experimentally determined $E_{\\mathrm{a}}$ for each step of the PS conversion process by probing the charge transfer resistance at the corresponding voltages under various temperatures in a standard Ketjen carbon black/sulfur (KCB/S) composite cathode $(1\\mathrm{mg}\\mathrm{cm}^{-2})$ (Fig. 1c,d). To stabilize the voltage for a specific conversion step, the cell was discharged to the desired potential and held at the same potential (chronoamperometry) until the output current remained constant. Electrochemical impedance spectroscopy (EIS) was then performed at $100\\mathrm{mV}$ intervals from $2.7\\mathrm{V}$ to \n\n$1.7\\mathrm{V}$ in a frequency range from $10\\mathrm{mHz}$ to $100\\mathrm{kHz}$ with an alternating current amplitude of $5\\mathrm{mV}.$ \n\nSupplementary Fig. 1 shows the simplified-contact Randles-equivalent circuit fitting EIS of the device, where the first semicircle is attributed to the deposition of the insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ on the surface $(R_{\\mathrm{surf}})$ , the second semicircle is attributed to the charge transfer process $(R_{\\mathrm{CT}})$ , and the tail line represents the Warburg resistance $(Z_{\\mathrm{w}})$ in the $\\operatorname{KCB}/\\operatorname{S}$ cathode23. By fitting the charge transfer resistance measured at different temperatures into the Arrhenius equation (Fig. 1c,d), we can derive $E_{\\mathrm{a}}$ at each measurement voltage. Overall, the resulting $E_{\\mathrm{a}}$ (Fig. 1e) shows a low value of $0.12\\mathrm{eV}$ at $2.7\\mathrm{V}$ (corresponding to the initial step conversion from $S_{\\mathrm{8}}$ to $\\mathrm{Li}_{2}\\mathrm{S}_{8},$ ), which increases to $0.24\\mathrm{eV}$ at $2.4{-}2.1\\mathrm{V}$ (corresponding to the conversion from $\\mathrm{Li}_{2}\\mathrm{S}_{8}$ to $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ and/or $\\mathrm{Li}_{2}\\mathrm{S}_{4}.$ ) and then reaches a maximum value of $0.33\\mathrm{eV}$ at $1.8\\mathrm{V}$ (for the final conversion into insoluble products). These $E_{\\mathrm{a}}$ studies clearly demonstrate that the conversion of the $S_{\\mathrm{{8}}}$ ring molecules to soluble LiPSs is relatively easy, whereas the conversion of LiPSs into the final insoluble products is more difficult and represents the rate-determining step for practical Li–S batteries. As most LiPSs (occurring at 2.7 V, $2.3\\mathrm{V}$ and $2.1\\mathrm{V}$ ) are soluble in the electrolyte, the slow conversion of such soluble LiPS intermediates into insoluble final products leads to accumulation of LiPSs in the electrolyte and thus is primarily responsible for the PS shuttling effect and rapid capacity fading. To this end, designing proper electrocatalysts that can lower such energy barriers and accelerate the conversion of soluble LiPS intermediates into insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ , may offer an attractive approach that directly addresses the root cause of the PS shuttling challenge. \n\nRational design of heteroatom-doped HGF catalysts. We chose a series of heteroatom-doped HGFs as model catalysts to explore the electrocatalytic SRR. The materials include the pristine HGF as well as nitrogen-doped, sulfur-doped, and nitrogen and sulfur dual-doped HGFs (N-HGF, S-HGF and N,S-HGF, respectively). A typical hydrothermal process (see Methods) was used to synthesize a 3D hierarchical HGF architecture with continuous graphene network structure for excellent electron transport, and fully interconnected micropores and nanopores for efficient mass transport and $\\mathrm{Li^{+}}$ diffusion (Fig. 2a,b and Supplementary Fig. 2)24,25. The holey graphene structure also provides abundant edge sites for heteroatom incorporation. It is known that the edge sites in the graphene matrix are active for various functionalizations due to the structural inhomogeneity26,27. The hydrothermal or thermal annealing process may be used for incorporating selected heteroatoms at the edge sites while retaining the $s p^{2}$ -bonded carbon basal plane. \n\n![](images/cdf843a6d8d5d64fcb3b9b0c4c416dbfaed0e58dd2a5388f687404489a4e4d55.jpg) \nFig. 2 | Material characterizations of the N,S-HGF. a, A photograph of freestanding N,S-HGF with different sizes and the corresponding thin film. Scale bar, 1 cm. b, A scanning electron microscopy (SEM) image of the N,S-HGF showing the hierarchical porous structure. Scale bar, $2\\upmu\\mathrm{m}$ . c,d, High-resolution XPS spectra of nitrogen 1s $\\mathbf{\\eta}(\\bullet)$ and sulfur $2p$ (d). a.u., arbitrary units. e, ADF-STEM images of N,S-graphene nanosheets showing the isolated pores and the location of sulfur dopants in the graphene matrix. Scale bar, $2{\\mathsf{n m}}$ . f, An enlarged ADF-STEM image of N,S-graphene nanosheets. The bright dots represent the sulfur dopant on the graphene plane, showing a thiophene-type C–S–C bond structure. Scale bar, 1 nm. \n\nThe chemical compositions and the bonding structures between the dopants and carbons in the heteroatom-doped HGF were characterized by X-ray photoelectron spectroscopy (XPS). An XPS survey scan of the N,S-HGF samples (Supplementary Fig. 3a) clearly showed the distinct peaks for nitrogen $(\\sim400\\mathrm{eV})$ and sulfur $(\\sim164.5\\$ and $228.2\\mathrm{eV},$ , demonstrating the successful doping of nitrogen and sulfur in graphene. The dopant contents in the samples can be estimated from the XPS survey results. The atomic ratios of nitrogen and sulfur dopants in N,S-HGF are around $2.6\\mathrm{at\\%}$ and $2.3{\\mathrm{at\\%}}$ , respectively. High-resolution XPS spectra of the nitrogen elements in N,S-HGF may be deconvoluted into three peaks at $398.6\\mathrm{eV},$ $399.7\\mathrm{eV}$ and $401.2\\mathrm{eV}$ (Fig. 2c), which may be attributed to pyridinic nitrogen, pyrrolic nitrogen and graphitic nitrogen, respectively. Sulfur atoms primarily form the thiophene-type $C{\\mathrm{-}}S{\\mathrm{-}}C$ bonds, as validated by the XPS peaks at 163.6 and $164.7\\mathrm{eV}$ (Fig. 2d), with a minor amount of sulfate and sulfide groups28. X-ray photoelectron spectroscopy characterizations for the single-doped counterparts were also conducted for comparison (Supplementary Fig. 3). \n\nThe bonding structures in the heteroatom-doped HGF can also be directly verified by annular dark-field scanning transmission electron microscopy (ADF-STEM). It is clear that the sulfur atoms (the bright dots in Fig. 2e) are only bonded with the carbon atoms in the form of thiophene-type bonds (Fig. 2f) at the edge sites of the nanopores $(\\sim1-2\\mathrm{nm})$ ; however, the nitrogen dopant is not visible in the STEM image due to the very close atomic number and little elemental contrast between nitrogen and carbon. The ADF-STEM characterizations can also provide helpful insights for the structural model constructions in our DFT calculations. \n\nActivity, kinetics and mechanism of the electrocatalytic SRR. To experimentally explore the fundamental electrocatalytic behaviour of the heteroatom-doped HGFs for the SRR, we carried out a series of electrochemical measurements including linear sweep voltammetry (LSV) and EIS, in combination with rotating disk electrode (RDE) measurements following the protocols well developed in the oxygen reduction reaction community29. Before the LSV experiments, the N,S-HGF electrode was activated by cyclic voltammetry for 50 cycles at $10\\mathrm{mVs^{-1}}$ in the non-Faradaic range to reach a stable electrochemical active surface area (Supplementary Fig. 4). Figure 3a shows the SRR polarization curves of different heteroatom-doped HGF samples deposited on a glassy carbon electrode (where the geometric area is $0.196\\mathrm{cm}^{2}.$ ). In general, the SRR LSV curve exhibits similar features to those of the oxygen reduction reaction, including an onset potential, diffusion-limited current density $(J_{\\mathrm{D}})$ and half-wave potential $(E_{1/2})$ . The $E_{1/2}$ for the N,S-HGF was $2.22\\mathrm{V},$ which is considerably higher than those of N-HGF (2.05 V), S-HGF (2.03 V) and pristine HGF (2.00 V), suggesting an overall lower overpotential for the N,S-HGF. \n\nThe use of LSV curves to determine the Tafel slope $(\\eta)$ and $J_{0}$ provides the key kinetic parameters that characterize the reaction kinetics and catalytic activity of a given electrocatalyst. Smaller $\\eta$ and higher $J_{0}$ are important indicators of faster reaction kinet$\\mathrm{ic}s^{30-33}$ . Notably, N,S-HGF catalysts exhibited the smallest $\\eta$ of \n\n![](images/0a4bdb5908623b29179797227ed87bc915197840d8f58fbec1b6dc1dda0d0112.jpg) \nFig. 3 | Catalytic SRR activity and kinetic analyses of heteroatom-doped HGFs in RDE. a, Linear sweep voltammetry curves of heteroatom-doped HGFs towards sulfur reduction. b, Tafel plots of heteroatom-doped HGFs. c, An electron transfer number comparison among heteroatom-doped HGFs. $\\boldsymbol{J}_{\\mathrm{geo}^{\\prime}}$ geometric current density. d, Electrochemical impedence spectroscopy of heteroatom-doped HGFs in SRR. e, Arrhenius plot showing the linear relationship between logarithmic values of the reciprocal of charge transfer resistance and the reciprocal of absolute temperatures. f, Activation energies for the SRR process among various heteroatom-doped HGFs at the onset potential. Error bars indicate the standard deviation of three independent electrodes. \n\n$80\\mathrm{mVdec^{-1}}$ compared with 157, 188 and $274\\mathrm{mV}\\mathrm{dec}^{-1}$ for N-HGF, S-HGF and pristine HGF, respectively (Fig. 3b), indicating considerably accelerated reaction kinetics and higher electrocatalytic activity. Extrapolating the Tafel plot to zero overpotential gives a $J_{0}$ of $0.12\\mathrm{mAcm}^{-2}$ for the N,S-HGF catalyst (Supplementary Discussion), which is higher than those obtained in the other samples $(0.10\\mathrm{mAcm}^{-2}$ for N-HGF, $0.09\\mathrm{mAcm}^{-2}$ for S-HGF and $0.07\\mathrm{mAcm}^{-2}$ for HGF). \n\nThe $J_{\\mathrm{D}}$ value for N,S-HGF is also considerably higher than those for the N-HGF, S-HGF and pristine HGF catalysts. $J_{\\mathrm{D}}$ is dependent on the active mass loading on the glassy carbon electrode and reaches a peak at a mass loading of $0.1\\mathrm{mg}\\mathrm{cm}^{-2}$ (Supplementary Fig. 5a). To understand the SRR mechanism with the presence of catalysts, the electron transfer numbers in the SRR process were calculated by using the $J_{\\mathrm{D}}$ according to the Koutecky–Levich equation (Supplementary Discussion)34. The Koutecky–Levich plots of N,S-HGF catalysts (Supplementary Fig. 5b), that is, $J^{-1}$ versus $\\omega^{-1/2}$ , show excellent linearity, suggesting first-order reaction kinetics for the reduction of sulfur molecules dissolved in the electrolyte. The slopes of the Koutecky– Levich plots give electron transfer numbers for the SRR catalysed by different materials. The N,S-HGF catalyst exhibits an apparent electron transfer number of ${\\sim}7.8$ , suggesting an overall 8-electron reduction process with a theoretical conversion of $S_{8}$ into $S_{8}^{\\mathrm{~8-}}$ (equivalent to $4\\mathrm{S}_{2}^{2-},$ ). By contrast, the electron transfer numbers of N-HGF, S-HGF and pristine HGF can be calculated as ${\\sim}5.9$ , ${\\sim}4.6$ and ${\\sim}3.3$ , respectively (Fig. 3c). The larger electron transfer number observed with the N,S-HGF catalyst suggests that it can promote more complete sulfur reduction and more rapid conversion of LiPS into the insoluble products, whereas the single-doped catalysts can only convert $S_{\\mathrm{{8}}}$ molecules into a mixture of both high- and low-order LiPSs, and the pristine HGF catalyst can only reduce $S_{8}$ molecules into high-order $\\mathrm{Li}_{2}\\mathrm{S}_{4}$ . These analyses clearly suggest that N,S-HGF is a much more effective catalyst at driving the reduction of $S_{8}$ molecules into solid-state products as indicated by the RDE measurements. \n\nTo further understand the origin of the improved catalytic activity and kinetics of N,S-HGF-catalysed SRR, we have conducted EIS measurements at the onset potential (where the SRR just starts) to probe the charge transfer resistance. Charge transfer is an essential step where ions and electrons are transferred to the active centres to participate in the reaction. The charge transfer kinetics at the catalyst–adsorbate interface therefore represents the primary factor determining the electrocatalytic SRR kinetics35. The EIS curves (Fig. 3d and Supplementary Fig. 6a) show that the N,S-HGF catalysts exhibit the smallest charge transfer resistance $(2.5\\Omega\\mathrm{cm}^{2})$ during the SRR in comparison with those of N-HGF $(7.0\\Omega\\mathrm{cm}^{2})$ , S-HGF $(12.9\\Omega\\mathrm{cm}^{2})$ and pristine HGF $(15.4\\Omega\\mathrm{cm}^{2})$ , suggesting its superior charge transfer kinetics. \n\nWe extended these EIS measurements and determined the temperature dependence of charge transfer resistance at the onset potential. This enabled us to extract the $E_{\\mathrm{a}}$ by using the Arrhenius equation (Supplementary Fig. 6b)36. The logarithmic values of the reciprocal of the charge transfer resistance obeyed a linear relationship with the inverse of the absolute temperature (Fig. 3e). Following the Arrhenius relation, we determined $E_{\\mathrm{a}}$ to be $0.06\\mathrm{eV}$ for N,S-HGF, $0.09\\mathrm{eV}$ for N-HGF, $0.15\\mathrm{eV}$ for S-HGF and $0.23\\mathrm{eV}$ for pristine HGF (Fig. 3f). Having the lowest $E_{\\mathrm{a}}$ is consistent with the superior kinetics of N,S-HGF for electrocatalytic SRR. \n\nTheoretical modelling of the activity origin on SRR. To better understand the fundamental origins of the SRR catalytic activity of the heteroatom-doped HGFs, we performed DFT calculations to elucidate how heteroatom doping affects the catalytic activity. The fundamental SRR process for the catalysts involves a series of reduction reactions that progress from $S_{\\mathrm{8}}$ ring molecules to the final product of $\\operatorname{Li}_{2}S$ $(\\mathrm{S}_{8}\\to\\mathrm{Li}_{2}\\mathrm{S}_{8}\\to\\mathrm{Li}_{2}\\mathrm{S}_{6}\\to\\mathrm{Li}_{2}\\mathrm{S}_{4}\\to\\mathrm{Li}_{2}\\mathrm{S}_{2}\\to\\mathrm{Li}$ ${}_{2}S,$ ) following four basic steps (diffusion, adsorption, reaction and desorption). It is generally believed that moderate adsorption (not too strong or too weak) of the adsorbate on the catalytic sites is the key prerequisite for an efficient electrocatalyst. As inspired by the research on heteroatom-doped carbon materials for the oxygen reduction reaction, the carbon atoms adjacent to the heteroatoms are the preferential binding sites for the sulfur intermediates rather than the heteroatoms themselves due to the charge redistribution induced by the heteroatom doping37. Our calculations indicate that the adsorption energy of the PS intermediates on carbon atoms of the basal plane is too weak and that on the heteroatoms is too strong (Supplementary Fig. 7). The carbon atoms adjacent to the heteroatoms therefore provide the optimal adsorption sites and are the most probable active sites for the catalytic SRR process. \n\n![](images/bbbd72ab93f1f1b2eca0cbd01009d498a53ba2d244fccebb541a7b25152a4951.jpg) \nFig. 4 | DFT calculations on the activity origin of the heteroatom-doped HGFs on SRR. a, Model constructions showing the interaction between three representative active sites in N,S-HGF with the microsolvated LiS radical adsorbates. b, A volcano plot linking the overpotential for the final step to the adsorption energies of the LiS radical intermediate on different active sites (triangles, squares and circles represent the active sites at different armchair, zigzag and inner defect edges, respectively). c, $p$ -band centre shift and modification of the pDOS of the catalytic carbon atoms induced by nitrogen and sulfur dual-doping: non-doped HGF (top) and N,S-HGF (bottom). $E_{\\scriptscriptstyle{\\mathsf{F}}\\prime}$ Fermi level energy. d, The relation between the $p$ -band centre and LiS adsorption energy at different active carbons. The purple dashed line represents the adsorption energy associated with the top of the volcano in b. The data points labelled A, D, Z in b and d correspond to the representative structures shown in a. \n\nAs the final reaction $(\\mathrm{Li}_{2}\\mathrm{S}_{2}+2\\mathrm{Li}^{+}+2e^{-}\\rightarrow2\\mathrm{Li}_{2}\\mathrm{S})$ represents the rate-determining step with considerably larger $E_{\\mathrm{a}}$ than the other conversion steps, we focus our calculations on the final two-electron process as we investigate the catalytic properties of different possible structures (Supplementary Discussion). We assumed that the conversion of $\\mathrm{Li}_{2}\\mathrm S_{2}$ to $\\operatorname{Li}_{2}S$ undergoes a step reaction that involves the formation of a LiS radical intermediate, which is solvated by the 1,3-dioxolane (DOL) solvent and interacts with the catalytic active site. Unlike previous theoretical models that only dealt with the ideal scenario in which the $\\mathrm{Li^{+}}$ ion was located in a vacuum state without considering the solvation by the electrolyte solvents38,39, we constructed a microsolvation state model that is closer to the practical conditions (Fig. 4a). In this approach we consider the $\\mathrm{Li^{+}}$ ion in LiS as solvated by three explicit DOL molecules, and the ensemble is placed in an implicit continuum solvent model of dielectric constant 7.0. The microsolvated LiS intermediate interacting with the active site $(^{*})$ denoted as 3DOL-LiS\\*, as expressed in the following equations: \n\n$$\n3\\mathrm{DOL}+\\mathrm{Li}_{2}\\mathrm{S}_{2}+\\mathrm{Li}^{+}+e^{-}+^{*}\\longrightarrow3\\mathrm{DOL}\\mathrm{-LiS}^{*}+\\mathrm{Li}_{2}\\mathrm{S}\n$$ \n\n$$\n3\\mathrm{DOL-LiS^{*}+L i^{+}}+e^{-}\\rightarrow\\mathrm{Li_{2}S+^{*}+3D O L}\n$$ \n\nDue to the strong cationic nature of $\\mathrm{Li^{+}}$ , the microsolvation approach of combining explicit and implicit solvent serves as an effective approach for correctly describing the solvation of the reactant (Supplementary Fig. 8). \n\nAccording to equations (1) and (2), the adsorption Gibbs free energy of $\\mathrm{LiS^{*}}$ $(\\Delta G(\\mathrm{LiS^{*}}))$ on the active sites can be expressed in equation (3) and the Gibbs free energy $(\\Delta G)$ of the final two steps can be written as a function of $\\Delta G(\\mathrm{LiS^{*}})$ : \n\n$$\n\\begin{array}{r}{\\Delta G(\\mathrm{LiS^{*}})=G(\\mathrm{3DOL.}\\mathrm{LiS^{*}})-G(^{*})-3G(\\mathrm{DOL})-G(\\mathrm{Li})}\\\\ {-G(\\mathrm{Li}_{2}\\mathrm{S}_{2})+G(\\mathrm{Li}_{2}\\mathrm{S})}\\end{array}\n$$ \n\n$$\n\\Delta G_{1}=\\Delta G\\big(\\mathrm{LiS}^{*}\\big)\n$$ \n\n$$\n\\Delta G_{2}=-\\Delta G(\\mathrm{LiS}^{*})+2G(\\mathrm{Li}_{2}\\mathrm{S})-2G(\\mathrm{Li})-G(\\mathrm{Li}_{2}\\mathrm{S}_{2})\n$$ \n\nThe catalytic activity is closely related to the thermodynamic overpotential for the $\\mathrm{Li}_{2}\\mathsf{S}_{2}$ to $\\operatorname{Li}_{2}S$ conversion reaction, which appears in a volcano plot as a function of $\\Delta G(\\mathrm{LiS^{*}})$ when catalysed at different catalytic sites, with special sites reaching the optimal value40. $\\Delta G(\\mathrm{LiS^{*}})$ for carbon atoms on the basal plane of graphene are in the region of weak adsorption, which is because the distortion of $C{\\mathrm{-}}C$ bonds induced by the carbon hybridization change from $s p^{2}$ to $s p^{3}$ requires too much energy that cannot be compensated by C–S bond formation during the catalytic SRR process. The edge carbon atoms, however, provide the opportunity to show reasonable adsorption energy as the distortion is much easier. In this regard, the carbon atoms located at the armchair edge, zigzag edge and inner defect edge were considered as various active sites to analyse the adsorption energy and the catalytic activity (Fig. 4a). Notably, the O/OH group on the zigzag/armchair/defective models is verified not to benefit the generation of structures with reasonable stabilities and improved catalytic properties (Supplementary Table 1). \n\n![](images/4c50e03210c27b869170c69d5ba8cdf768764016cefef82ec964beb005babf29.jpg) \nFig. 5 | Activation energy profiles and overall performance of the heteroatom-doped HGF cathodes in Li–S coin cells. a, Activation energies for heteroatom-doped HGFs at various voltages. Error bars in a indicate the standard deviation of three independent coin cells. b, Charge/discharge curves of the heteroatom-doped HGF-based sulfur cathodes at 0.1 C. c, Potential difference between the anodic and cathodic sweep in heteroatom-doped HGFs at different C rates; d, Rate capability of the heteroatom-doped HGF-based sulfur cathodes from 0.1 C to 2 C with the sulfur loading of $4\\mathsf{m g c m}^{-2}$ . e, Cycling stability of the heteroatom-doped HGF-based sulfur cathodes at 1 C with the sulfur loading of $4\\mathsf{m g c m}^{-2}$ . \n\nGoverned by the Sabatier principle, the relationship between the overpotential and the adsorption energy displays a volcano shape (Fig. 4b), where several edge carbon sites on the N,S-HGF catalyst and on the N-HGF, S-HGF and HGF catalyst models (Supplementary Fig. 9) are compared. For the structures on the left side, step 2 is the potential limiting step, whereas on the right side of the volcano, the potential is limited by reaction step 1. Perfect non-doped graphene presents sites that bind LiS either too strongly (such as on the zigzag edge, $-3.00\\mathrm{eV})$ or too weakly (such as on the armchair edge, $-1.73\\mathrm{eV},$ ) and they are therefore intrinsically bad catalytic sites. As for the inner defective non-doped HGF, the edge carbon atoms show a hybrid geometry between armchair and zigzag edges. This structure results in a favourable adsorption energy of $-2.14\\mathrm{eV},$ presenting a good compromise of LiS binding and consequently a low overpotential. Moreover, N,S dual-doping further provides finer tuning, pushing the N,S-HGF system almost at the top of the volcano plot and further decreasing the overpotential to a negligible value. The adsorption energy calculation results can be experimentally verified by the PS-adsorption experiments (Supplementary Fig. 10). \n\nTo unravel the origin of the high catalytic SRR activity, we considered the doping process as an approach to engineering the $\\boldsymbol{p}$ -orbital of the catalytic sites and thereby the catalytic performance (Fig. 4c). Inspired by $d$ -band centre theory for metallic catalysts41, we used the $\\boldsymbol{p}$ -band centre for the density of states projected on the active carbon as a descriptor of the electronic structure of the heteroatom-doped catalysts and found a relationship with the adsorption energy of LiS (Fig. 4d). Before adsorption, the valence $\\boldsymbol{p}$ -band in the projected density of states $\\mathrm{(pDOS)}$ of the sulfur atom in the LiS radical shows an isolated feature. After adsorption on the catalysts, a considerable change to the pDOS shape of the valence $\\boldsymbol{p}$ -band arises from the bonding with the $\\boldsymbol{p}$ -orbital of the catalytic carbon atoms (Supplementary Fig. 11). The bonding strength, according to classical bonding theory, is related to the energy gap between these bonding orbitals: as the $\\boldsymbol{p}$ -orbital of sulfur atom in LiS radical can be considered at constant position, tuning the position of the $\\boldsymbol{p}$ -orbital of catalytic carbon atoms to manipulate the adsorption can be achieved by heteroatom doping. N–S dual-doping generally provides an intermediate $\\boldsymbol{p}$ -band centre energy, hence a moderate bonding strength with the LiS radical, thus leading to the optimal catalytic activity. The $\\boldsymbol{p}$ -band centre also provides an opportunity to estimate the performance of different sites without the demanding calculation of the adsorbed structure. In addition to the $\\boldsymbol{p}$ -band theory, other factors that may influence the catalytic activity, such as charge, dipole and strain effect, have also been discussed (Supplementary Fig. 12) and the results show that the correlation between these factors and the adsorption energy is not significantly better than the $\\boldsymbol{p}$ -band centre. \n\nSRR in Li–S battery. Although previous RDE measurements (Fig. 3) demonstrated superior electrocatalytic SRR activities for N,S-HGF catalysts in an open cell environment, it is of practical importance to evaluate the effect of electrocatalysis on device performance. Accordingly, we systematically explored the $E_{\\mathrm{a}}$ profiles and overall performance of the heteroatom-doped HGF cathodes in Li–S coin cells. First, we conducted the same $E_{\\mathrm{a}}$ measurements by determining the temperature-dependent EIS curves at various voltages (Supplementary Fig. 13) to verify that selected catalysts are capable of accelerating the LiPS conversion, particularly the rate-determining step. The EIS curves of different HGF catalysts show similar behaviours to that of the $\\mathsf{K C B}/\\mathsf{S}$ cathode, and among them the N,S-HGF catalyst exhibits the smallest charge transfer resistance. Figure 5a shows the $E_{\\mathrm{a}}$ profiles at various voltages for the four different catalyst-based cathodes (loading of $1\\mathrm{mg}\\mathrm{cm}^{-2},$ . Overall, the $E_{\\mathrm{a}}$ for non-doped HGF displays a similar stepwise profile to that of the control device made from the standard KCB/S composite cathode (see Fig. 1e), that is, there are relatively low $E_{\\mathrm{a}}$ values at the initial reduction stage $({\\sim}2.7{-}2.5\\mathrm{V})$ , which increase at the median reduction stage $(\\sim2.4\\mathrm{-}2.0\\mathrm{V})$ and peak at the final reduction stage $(\\sim1.9\\mathrm{-}1.7\\mathrm{V})$ , again confirming that the last steps of conversion into insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ products are the rate-determining steps. With the introduction of heteroatom dopants, the activation energies are reduced considerably, especially for final rate-determining step. Overall, the activation energies follow a similar trend to that observed in RDE studies in that the values decrease in the order from HGF, S-HGF, N-HGF to N,S-HGF. In particular, the maximum $E_{\\mathrm{a}}$ decreases from ${>}0.32\\mathrm{eV}$ in HGF to $0.12\\mathrm{eV}$ in N,S-HGF electrodes for the final LiPS conversion into insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ . \n\nThe different $E_{\\mathrm{a}}$ values for the four heteroatom-doped HGFs can also account for the different polarization voltage gaps (Fig. $^{5\\mathrm{b},\\mathrm{c})}$ . As shown in Fig. 5b, N,S-HGF exhibited the smallest polarization voltage gap $(152\\mathrm{mV})$ between anodic and cathodic sweeps among the four different samples at the current density of $0.2\\mathrm{C}$ . Moreover, as a larger current density would induce more severe polarization and larger voltage gaps, because of the considerably better catalytic activity and lowered $E_{\\mathrm{a}}$ for the N,S-HGF catalyst, the increase in voltage gap from $0.05\\mathrm{C}$ to $2\\mathrm{C}$ is only $130\\mathrm{mV}$ (from $140\\mathrm{mV}$ to $270\\mathrm{mV}.$ ). This value is considerably lower than those of N-HGF $(210\\mathrm{mV})$ , S-HGF $(370\\mathrm{mV})$ and non-doped HGF $\\mathrm{541mV},$ catalysts (Fig. 5c and Supplementary Fig. 14). \n\nTo directly evaluate the impact of the electrocatalysts in battery performance, we have further compared the rate capability and cycling behaviour of the Li–S coin cells assembled with different catalysts. For a sulfur mass loading of $4\\mathrm{mg}\\mathrm{cm}^{-2}$ , the N,S dual-doped HGF electrodes exhibited excellent rate capability, delivering specific capacities of 1,390, 840 and $577\\mathrm{mAhg^{-1}}$ at 0.1 C, 1 C and $^{2\\mathrm{C},}$ respectively (Fig. 5d). By contrast, with lower catalytic activity, the N-HGF, S-HGF, and pristine HGF displayed considerably lower capacity, especially at a high rate. Furthermore, the acceleration of PS conversion into solid $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ reduces the PS accumulation and thus effectively mitigates the PS shuttling effect, leading to improved cycling stability. The N,S dual-doped HGF electrodes displayed an extremely low capacity decay of $0.025\\%$ per cycle at 1 C for 500 cycles, compared with those of $0.054\\%$ per cycle, $0.098\\%$ per cycle and $0.162\\%$ per cycle for the N-HGF, S-HGF and pristine HGF, respectively (Fig. 5e). Such comparisons clearly highlight the greatly enhanced performance that results from the improved SRR catalytic activity. \n\nIn summary, we have conducted a systematic investigation of SRR kinetics by directly profiling the activation energies in the multistep SRR process. We reveal that the initial reduction of $S_{8}$ ring molecules to the soluble LiPSs is relatively easy with low $E_{\\mathrm{a}}$ , whereas the subsequent conversion of the LiPSs into the insoluble $\\mathrm{Li}_{2}\\mathrm S_{2}/\\mathrm{Li}_{2}\\mathrm S$ is more difficult with much higher $E_{\\mathrm{a}},$ which fundamentally contributes to the accumulation of PSs in electrolyte and exacerbates the PS shuttling effect. Heteroatom-doped graphene was used as a model system to demonstrate that the electrocatalytic strategy can accelerate the PS conversion kinetics and mitigate the PS shuttling effect. Experimental results and theoretical calculations establish that dual-doped N,S-HGF exhibited superior electrocatalytic SRR activity with considerably lower charge transfer resistance and a greatly reduced $E_{\\mathrm{a}},$ leading to Li–S cells that exhibit significant improvements in rate capability and cycling stability. These studies establish that electrocatalytic SRR is a promising pathway to highly robust Li–S batteries. Beyond the heteroatom model system described in current study, the same approach can be applied to many other potential SRR electrocatalysts, including single transition metal atom catalysts42, metal oxides or metal sulfides43. \n\n# Methods \n\nSynthesis of graphene oxide and heteroatom-doped holey graphene framework. Graphene oxide was prepared according to a modified Hummers’ method44. Briefly, 6 g natural graphite (325 mesh, Sigma-Aldrich) was added into $140\\mathrm{ml}$ concentrated sulfuric acid under vigorous stirring in an ice-water bath, followed by slowly adding $_{3\\mathrm{g}}$ sodium nitrate (Sigma-Aldrich) and $18\\mathrm{g}$ potassium permanganate (Sigma-Aldrich). Due to the strong acidity of sulfuric acid and strong oxidizabilities of the sodium nitrate and potassium permanganate, it is necessary to keep the temperature near $0^{\\circ}\\mathrm{C}$ to avoid the fast oxidation of the graphite and any kinds of unsafe accidents. After stirring for $30\\mathrm{min}$ , the reaction system was transferred into a water bath at $\\sim50^{\\circ}\\mathrm{C},$ and was kept stirring till the mixture forming a thick paste. Successively, the system was transferred back to the ice-water bath, followed by drop-wise addition of ${\\sim}11$ iced deionized water. The mixture was then centrifuged and washed by using $1{:}10\\mathrm{HCl}$ aqueous solution for three times followed by repeated washing with deionized water. The final solution was dialysed for one week to remove the extra $\\mathrm{H^{+}}$ ions absorbed on the graphene oxide surfaces. Heteroatom-doped HGFs were synthesized by reacting the dopant sources with the holey graphene oxide (HGO) aqueous dispersion through a typical hydrothermal method. Aqueous dispersion of HGO was synthesized according to our previous method24 by mixing $50\\mathrm{ml}$ of $2\\mathrm{GO}\\mathrm{mg}\\mathrm{ml}^{-1}$ GO aqueous dispersion solution with $5\\mathrm{ml}$ of $30\\%$ $\\mathrm{H}_{2}\\mathrm{O}_{2}$ aqueous solution at $100^{\\circ}\\mathrm{C}$ under stirring for 2 h. Specifically, $10\\mathrm{mmol}$ of $\\mathrm{NH}_{4}\\mathrm{SCN}$ powders were added into the $10\\mathrm{ml}$ of $2\\mathrm{mg}\\mathrm{ml}^{-1}$ HGO dispersion, followed by magnetic stirring and sonication for $2\\mathrm{h}$ to dissolve the $\\mathrm{NH_{4}S C N}$ thoroughly. The mixed dispersion was then transferred into an autoclave and heated at $180^{\\circ}\\mathrm{C}$ for $^{6\\mathrm{h}}$ . After the hydrothermal treatment, a free-standing $^{\\mathrm{~N},S}$ -HGF hydrogel can be obtained. The hydrogel was then freeze-dried and annealed at $900^{\\circ}\\mathrm{C}$ for $\\ensuremath{\\mathrm{1h}}$ to obtain the N,S-HGF aerogel45. The control samples (namely, N-HGF, S-HGF and pristine HGF) were synthesized by changing the dopant source into urea and $\\mathrm{Na}_{2}\\mathrm{S}$ or without dopant sources, following the same procedures. Note that the dopant concentration of each catalyst has been optimized before the final presentation. The results presented in the manuscript are based on the optimized samples with the best electrochemical performance and structural integrity simultaneously. \n\nPreparation of the electrolyte and $\\bf L i_{6}S_{6}$ catholyte. The electrolyte (denoted as blank electrolyte) was made of 1 M lithium bis(trifluoromethanesulfonyl) imide (Sigma-Aldrich) and $0.2\\ensuremath{\\mathrm{M}}$ lithium nitrate (Sigma-Aldrich) in the mixed dimethoxyethane (Sigma-Aldrich) and DOL(Sigma-Aldrich) solution (1:1 by volume). The $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte (1 M) was prepared by reacting the sublimed sulfur (Sigma-Aldrich) with $\\mathrm{Li}_{2}S$ (Sigma-Aldrich) in stoichiometric proportion in the blank electrolyte. The mixture was vigorously stirred at $50^{\\circ}\\mathrm{C}$ in an argon-filled glove box overnight to produce a brownish-red $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte solution. The PS-adsorption test was conducted by immersing $3\\mathrm{mg}$ of the heteroatom-doped HGF catalysts in $3\\mathrm{ml}$ of $10\\mathrm{mM}$ $\\mathrm{Li}_{2}\\mathrm{S}_{4}$ solutions at room temperature for 24 h. \n\nElectrochemical measurements. The electrocatalytic SRR activity was tested by using a CHI 760E electrochemical workstation (CH Instruments) coupled with the RDE technique (Pine Research Instrumentation) in an argon-filled glovebox. $10\\upmu\\mathrm{l}$ of $2\\mathrm{mg}\\mathrm{ml}^{-1}$ catalyst ink (made by sonicating $2\\mathrm{mg}$ catalysts in $\\mathrm{1ml}$ ethanol and $20\\upmu15\\mathrm{wt\\%}$ Nafion solution) was drop-cast onto a freshly polished glassy carbon electrode $(0.196\\mathsf{c m}^{2})$ to form a flat film electrode with an areal mass loading of $0.1\\mathrm{mg}\\mathrm{cm}^{-2}$ (for all catalysts). The electrochemical test was performed in a two-electrode open-cell located in the glovebox, by using lithium foil as the counter and reference electrode and the catalyst film as working electrode. The electrolyte solution used for SRR tests was 4 mM $S_{\\mathrm{{s}}}$ molecules dissolved in the blank electrolyte. Before the SRR electrocatalysis test, the catalyst film electrode was first activated in the blank electrolyte by scanning the cyclic voltammetry in the range of $3.1\\mathrm{V}$ to $3.0\\mathrm{V}$ for 50 cycles at $10\\mathrm{mVs^{-1}}$ . Linear sweep voltammetry measurements were then conducted in the $S_{\\mathrm{s}}$ solution with the sweep rate of $20\\mathrm{mVs^{-1}}$ in the voltage range of $3.3\\mathrm{V}$ to 1 V. Meanwhile, the LSV curve in the blank electrolyte should also be recorded as the background curve, which is used to obtain the realistic LSV profile of SRR. \n\nThe overall electrochemical performance of the catalyst was conducted in the CR2032 coin cells assembled in an argon-filled glovebox. The catalyst electrode was prepared by directly pressing the aerogel into a freestanding thin film, and the mass of the thin film can be controlled by tuning the height of the aerogel. Afterwards, $\\mathrm{Li}_{2}\\mathrm{S}_{6}$ catholyte was directly used as sulfur source to drop cast in the catalyst electrode. In our experiment, we set the mass ratio of the sulfur in the cathodes as $67\\%$ unless otherwise specified. The sulfur cathodes were then directly assembled into a CR2032 coin cell with lithium foil, Celgard 2500 separator and blank electrolyte (E:S ratio $\\mathrm{\\Omega}=5{:}1\\upmu\\mathrm{l}\\mathrm{mg}^{-1}\\mathrm{\\Omega},$ ). Cyclic voltammetry curves were recorded in the voltage range of $1.7\\mathrm{V}{-2.7\\mathrm{V}}$ at a scanning rate of $0.2\\mathrm{mVs^{-1}}$ . The charge/ discharge curves were tested in the voltage range of $1.7\\mathrm{V}{-2.7\\mathrm{V}}$ at various C rates $(1\\mathrm{C}=1,670\\mathrm{mAhg^{-1}}$ ), and rate capability was evaluated by testing the capacity at $0.1\\mathrm{C},0.2\\mathrm{C},0.5\\mathrm{C}$ , 1 C and 2 C. Electrochemical impedance spectroscopy tests were performed at specific voltage values in the frequency range of 1 MHz to $0.01\\mathrm{Hz}$ with an amplitude of $5\\mathrm{mV.}$ A Linkam stage (HFSX350) was used to control the temperature during the $E_{\\mathrm{a}}$ measurements. \n\nMaterial characterizations. The morphology and structure of the resulting materials were characterized by SEM (Zeiss Supra 40VP), XPS (Kratos AXIS Ultra DLD spectrometer) and Raman spectroscopy (RM 2000 Microscopic confocal Raman spectrometer Horiba LABHR using a $488\\mathrm{nm}$ laser beam). Annular dark-field scanning transmission electron microscopy imaging was performed on an aberration-corrected JEOL ARM300CF STEM equipped with a JEOL ETA corrector operated at an accelerating voltage of $80\\mathrm{kV}_{:}$ located in the electron Physical Sciences Imaging Centre (ePSIC) at Diamond Light Source. ADF imaging was performed at $80\\mathrm{keV}$ with a CL aperture of $30\\upmu\\mathrm{m}$ , convergence semi-angle of $24.8\\mathrm{mrad}$ , beam current of $12\\mathrm{pA}$ and acquisition angle of 27–110 mrad. \n\nCharacterizations. Characterizations were carried out using SEM (JEOL JSM6700F FE-SEM) with energy dispersive spectroscopy, TEM (T12 Quick CryoEM and CryoET FEI; acceleration voltage, 120 KV. Titan S/TEM FEI; acceleration voltage, $300\\mathrm{KV}.$ ), X-ray diffraction (Panalytical X’Pert Pro X-ray Powder Diffractometer), atomic force microscopy (Bruker Dimension Icon Scanning Probe Microscope), ultraviolet–visible–near infrared spectroscopy (Shimadzu 3100 PC), Raman and photoluminescence spectroscopy (Horiba, $488\\mathrm{nm}$ laser wavelength) and XPS (AXIS Ultra DLD). For the photoluminescence spectra collection, exfoliated monolayer $\\mathbf{MoS}_{2}$ nanosheets were used after the bis(trifluoromethane) sulfonimide treatment. The transport characteristic measurements were conducted at room temperature under ambient conditions (in vacuum and dark) with a probe station and a computer-controlled analogue-to-digital converter. \n\nDFT calculations. Major parts of calculations are performed with $\\mathrm{DFT^{46}}$ using the Vienna ab initio simulation package47. Perdew–Burke–Ernzerhof48 functional at the generalized gradient approximation level. Cutoff energy of basis set is $500\\mathrm{eV}$ cutoff as required by the Li_sv pseudopotential to give a reasonable description of lithium related species. The dDsC dispersion correction is applied49,50. Solvation effects are described using an implicit dielectric model as implemented in the VaspSol51 addon package. The cavitation energy contribution is neglected for numeric stability. The accuracy is set to be ACCURATE as recommend by VaspSol. All calculations are spin-polarized. The atomic coordinates of the optimized models are provided in Supplementary Data 1. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding authors on reasonable request. \n\nReceived: 21 January 2020; Accepted: 20 July 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Manthiram, A., Fu, Y., Chung, S.-H., Zu, C. & Su, Y.-S. Rechargeable lithium–sulfur batteries. Chem. Rev. 114, 11751–11787 (2014). \n2.\t Pang, Q., Liang, X., Kwok, C. Y. & Nazar, L. F. Advances in lithium–sulfur batteries based on multifunctional cathodes and electrolytes. Nat. Energy 1, 16132 (2016). \n3.\t Mikhaylik, Y. V. & Akridge, J. R. Polysulfide shuttle study in the Li/S battery system. J. Electrochem. Soc. 151, A1969–A1976 (2004). \n4.\t Ma, L., Hendrickson, K. E., Wei, S. & Archer, L. A. Nanomaterials: Science and applications in the lithium–sulfur battery. Nano Today 10, 315–338 (2015). \n5.\t Seh, Z. W., Sun, Y., Zhang, Q. & Cui, Y. Designing high-energy lithium–sulfur batteries. Chem. Soc. Rev. 45, 5605–5634 (2016). \n6.\t Bonaccorso, F. et al. Graphene, related two-dimensional crystals, and hybrid systems for energy conversion and storage. Science 347, 1246501 (2015). \n7.\t Guo, B. et al. Highly dispersed sulfur in a porous aromatic framework as a cathode for lithium–sulfur batteries. Chem. Comm. 49, 4905–4907 (2013). \n8.\t Li, L. et al. Stabilizing sulfur cathodes using nitrogen-doped graphene as a chemical immobilizer for LiS batteries. Carbon 108, 120–126 (2016). \n9.\t He, J. et al. Freestanding 1T MoS2/graphene heterostructures as a highly efficient electrocatalyst for lithium polysulfides in Li–S batteries. Energy Environ. Sci. 12, 344–350 (2019). \n10.\tPeng, L., Zhu, Y., Chen, D., Ruoff, R. S. & Yu, G. Two-dimensional materials for beyond-lithium-ion batteries. Adv. Energy Mater. 6, 1600025 (2016). \n11.\tCui, Z., Zu, C., Zhou, W., Manthiram, A. & Goodenough, J. B. Mesoporous titanium nitride-enabled highly stable lithium–sulfur batteries. Adv. Mater. 28, 6926–6931 (2016). \n12.\tWang, D. et al. A general atomic surface modification strategy for improving anchoring and electrocatalysis behavior of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{2}$ MXene in lithium–sulfur batteries. ACS Nano 13, 11078–11086 (2019). \n13.\tZheng, J. et al. lewis acid–base interactions between polysulfides and metal organic framework in lithium sulfur batteries. Nano Lett. 14, 2345–2352 (2014). \n14.\tJi, X. & Nazar, L. F. Advances in Li–S batteries. J. Mater. Chem. 20, 9821–9826 (2010). \n15.\tBruce, P. G., Freunberger, S. A., Hardwick, L. J. & Tarascon, J.-M. Li– ${\\bf-O}_{2}$ and Li–S batteries with high energy storage. Nat. Mater. 11, 19–29 (2012). \n16.\tDu, Z. et al. Cobalt in nitrogen-doped graphene as single-atom catalyst for high-sulfur content lithium–sulfur batteries. J. Am. Chem. Soc. 141, 3977–3985 (2019). \n17.\tXu, Z.-L. et al. Exceptional catalytic effects of black phosphorus quantum dots in shuttling-free lithium sulfur batteries. Nat. Commun. 9, 4164 (2018). \n18.\tPark, J. et al. Tungsten disulfide catalysts supported on a carbon cloth interlayer for high performance Li–S battery. Adv. Energy Mater. 7, 1602567 (2017). \n19.\tWild, M. et al. Lithium sulfur batteries, a mechanistic review. Energy Environ. Sci. 8, 3477–3494 (2015). \n20.\tBarchasz, C. et al. Lithium/sulfur cell discharge mechanism: An original approach for intermediate species identification. Anal. Chem. 84, 3973–3980 (2012). \n21.\tWang, L. et al. A quantum-chemical study on the discharge reaction mechanism of lithium-sulfur batteries. J. Energy Chem. 22, 72–77 (2013). \n22.\t Yin, Y.-X., Xin, S., Guo, Y.-G. & Wan, L.-J. Lithium–sulfur batteries: electrochemistry, materials, and prospects. Angew. Chem. Int. Ed. 52, 13186–13200 (2013). \n23.\t Tan, G. et al. Burning lithium in $\\mathrm{CS}_{2}$ for high-performing compact $\\operatorname{Li}_{2}S$ –graphene nanocapsules for Li–S batteries. Nat. Energy 2, 17090 (2017). \n24.\tSun, H. et al. Three-dimensional holey-graphene/niobia composite architectures for ultrahigh-rate energy storage. Science 356, 599–604 (2017). \n25.\tXu, Y. et al. Holey graphene frameworks for highly efficient capacitive energy storage. Nat. Commun. 5, 4554 (2014). \n26.\tDuan, J., Chen, S., Jaroniec, M. & Qiao, S. Z. Heteroatom-doped graphene-based materials for energy-relevant electrocatalytic processes. ACS Catal. 5, 5207–5234 (2015). \n27.\tZhou, H. et al. Understanding defect-stabilized noncovalent functionalization of graphene. Adv. Mater. Interfaces 2, 1500277 (2015). \n28.\tWang, X. et al. Heteroatom-doped graphene materials: syntheses, properties and applications. Chem. Soc. Rev. 43, 7067–7098 (2014). \n29.\tPaulus, U. A., Schmidt, T. J., Gasteiger, H. A. & Behm, R. J. Oxygen reduction on a high-surface area Pt/Vulcan carbon catalyst: a thin-film rotating ring-disk electrode study. J. Electroanal. Chem. 495, 134–145 (2001). \n30.\tSuen, N.-T. et al. Electrocatalysis for the oxygen evolution reaction: recent development and future perspectives. Chem. Soc. Rev. 46, 337–365 (2017). \n31.\tLi, M. et al. Single-atom tailoring of platinum nanocatalysts for high-performance multifunctional electrocatalysis. Nat. Catal. 2, 495–503 (2019). \n32.\tLi, M. et al. Ultrafine jagged platinum nanowires enable ultrahigh mass activity for the oxygen reduction reaction. Science 354, 1414–1419 (2016). \n33.\tLu, Y.-C., He, Q. & Gasteiger, H. A. Probing the lithium–sulfur redox reactions: a rotating-ring disk electrode study. J. Phys. Chem. C 118, 5733–5741 (2014). \n34.\tZhou, R., Zheng, Y., Jaroniec, M. & Qiao, S.-Z. Determination of the electron transfer number for the oxygen reduction reaction: from theory to experiment. ACS Catal. 6, 4720–4728 (2016). \n35.\tBazant, M. Z. Theory of chemical kinetics and charge transfer based on nonequilibrium thermodynamics. Acc. Chem. Res. 46, 1144–1160 (2013). \n36.\tOgihara, N. et al. Theoretical and experimental analysis of porous electrodes for lithium-ion batteries by electrochemical impedance spectroscopy using a symmetric cell. J. Electrochem. Soc. 159, A1034–A1039 (2012). \n37.\tLi, M., Zhang, L., Xu, Q., Niu, J. & Xia, Z. N-doped graphene as catalysts for oxygen reduction and oxygen evolution reactions: Theoretical considerations. J. Catal. 314, 66–72 (2014). \n38.\tZhou, G., Paek, E., Hwang, G. S. & Manthiram, A. Long-life Li/polysulphide batteries with high sulphur loading enabled by lightweight three-dimensional nitrogen/sulphur-codoped graphene sponge. Nat. Commun. 6, 7760 (2015). \n39.\tJi, Z. et al. Anchoring lithium polysulfides via affinitive interactions: electrostatic attraction, hydrogen bonding, or in parallel? J. Phys. Chem. C 119, 20495–20502 (2015). \n40.\tNørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n41.\tHammer, B. & Nørskov, J. K. Why gold is the noblest of all the metals. Nature 376, 238–240 (1995). \n42.\tFei, H. et al. Single atom electrocatalysts supported on graphene or graphene-like carbons. Chem. Soc. Rev. 48, 5207–5241 (2019). \n43.\tWang, D. & Astruc, D. The recent development of efficient earth-abundant transition-metal nanocatalysts. Chem. Soc. Rev. 46, 816–854 (2017). \n44.\tXu, Y., Sheng, K., Li, C. & Shi, G. Self-assembled graphene hydrogel via a one-step hydrothermal process. ACS Nano 4, 4324–4330 (2010). \n45.\tFei, H. et al. General synthesis and definitive structural identification of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n46.\tKohn, W. & Sham, L. J. Self-consistent equations including exchange and correlation effects. Phys. Rev. 140, A1133–A1138 (1965). \n47.\tKresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993). \n48.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n49.\tSteinmann, S. N. & Corminboeuf, C. Comprehensive benchmarking of a density-dependent dispersion correction. J. Chem. Theory Comput. 7, \n3567–3577 (2011). \n50.\tSteinmann, S. N. & Corminboeuf, C. A generalized-gradient approximation exchange hole model for dispersion coefficients. J. Chem. Phys. 134, \n044117 (2011). \n51.\tMathew, K., Sundararaman, R., Letchworth-Weaver, K., Arias, T. A. & Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 140, \n084106 (2014). \n52.\tTowns, J. et al. XSEDE: accelerating scientific discovery. Comput. Sci. Eng. 16 \n62–74 (2014). \n\n# Acknowledgements \n\nThis work is supported by the Center for Synthetic Control Across Length-scales for Advancing Rechargeables, an Energy Frontier Research Center funded by the US \n\nDepartment of Energy, Office of Science Basic Energy Sciences programme under award DE-SC0019381. Y.H. acknowledges the support by Office of Naval Research through grant no. N00010141712608 (initial effort on catalyst preparation and rotating disc electrode electrochemical characterizations). I.M. and Z.A. acknowledge the support by the International Scientific Partnership Program (ISPP-147) at King Saud University. We acknowledge the Electron Imaging Center at UCLA for SEM technical support and the Nanoelectronics Research Facility at UCLA for device fabrication technical support. We thank Diamond Light Source for access and support in use of the electron Physical Science Imaging Centre (MG23956). The calculations were performed on the Hoffman2 cluster at UCLA Institute for Digital Research and Education (IDRE), The National Energy Research Scientific Computing Center (NERSC), and the Extreme Science and Engineering Discovery Environment (XSEDE)52, which is supported by National Science Foundation grant number ACI-1548562, through allocation TG-CHE170060. \n\n# Author contributions \n\nX.D., Y.H. and L.P. conceived and designed the experimental research. P.S. and Z.W. designed and performed the DFT calculations. L.P. performed the experiments and conducted the data analysis with contributions from C.W., J.L., Z.C., D.Z., D.B., H.L., X.X., I.S., Z.A., S.T., B.D., Y.H. and X.D. C.S.A. and A.I.K. contributed to the TEM characterizations. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-020-0498-x. \n\nCorrespondence and requests for materials should be addressed to Y.H., P.S. or X.D \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 " + }, + { + "id": "10.1038_s41467-019-13739-5", + "DOI": "10.1038/s41467-019-13739-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-13739-5", + "Relative Dir Path": "mds/10.1038_s41467-019-13739-5", + "Article Title": "Nitrogen-rich covalent organic frameworks with multiple carbonyls for high-performance sodium batteries", + "Authors": "Shi, RJ; Liu, LJ; Lu, Y; Wang, CC; Li, YX; Li, L; Yan, ZH; Chen, J", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Covalent organic frameworks with designable periodic skeletons and ordered nullopores have attracted increasing attention as promising cathode materials for rechargeable batteries. However, the reported cathodes are plagued by limited capacity and unsatisfying rate performance. Here we report a honeycomb-like nitrogen-rich covalent organic framework with multiple carbonyls. The sodium storage ability of pyrazines and carbonyls and the up-to twelve sodium-ion redox chemistry mechanism for each repetitive unit have been demonstrated by in/ex-situ Fourier transform infrared spectra and density functional theory calculations. The insoluble electrode exhibits a remarkably high specific capacity of 452.0 mAh g(-1), excellent cycling stability (similar to 96% capacity retention after 1000 cycles) and high rate performance (134.3 mAh g(-1) at 10.0 A g(-1)). Furthermore, a pouch-type battery is assembled, displaying the gravimetric and volumetric energy density of 101.1 Wh kg(cell)(-1) and 78.5 Wh L-cell(-1), respectively, indicating potentially practical applications of conjugated polymers in rechargeable batteries.", + "Times Cited, WoS Core": 561, + "Times Cited, All Databases": 570, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000551458600007", + "Markdown": "# Nitrogen-rich covalent organic frameworks with multiple carbonyls for high-performance sodium batteries \n\nRuijuan Shi1, Luojia Liu1, Yong Lu $\\textcircled{1}$ 1, Chenchen Wang1, Yixin Li1, Lin Li $\\textcircled{1}$ 1, Zhenhua Yan1 & Jun Chen 1\\* \n\nCovalent organic frameworks with designable periodic skeletons and ordered nanopores have attracted increasing attention as promising cathode materials for rechargeable batteries. However, the reported cathodes are plagued by limited capacity and unsatisfying rate performance. Here we report a honeycomb-like nitrogen-rich covalent organic framework with multiple carbonyls. The sodium storage ability of pyrazines and carbonyls and the up-to twelve sodium-ion redox chemistry mechanism for each repetitive unit have been demonstrated by in/ex-situ Fourier transform infrared spectra and density functional theory calculations. The insoluble electrode exhibits a remarkably high specific capacity of $452.0\\mathsf{m A h\\ g}^{-1},$ excellent cycling stability ${\\sim}96\\%$ capacity retention after 1000 cycles) and high rate performance $(134.3\\mathsf{m A h}\\mathsf{g}^{-1}$ at ${10.0\\mathsf{A}}\\mathsf{g}^{-1};$ . Furthermore, a pouch-type battery is assembled, displaying the gravimetric and volumetric energy density of 101.1 Wh $\\mathsf{k g}^{-1}\\mathsf{c e l l}$ and $78.5\\mathsf{W h}\\mathsf{L^{-1}}_{\\mathsf{c e l l}},$ respectively, indicating potentially practical applications of conjugated polymers in rechargeable batteries. \n\novalent organic frameworks (COFs), which are a class of polymers with designable periodic skeletons and ordered nanopores, have been demonstrated potential applications widely in the fields such as catalysis, semiconductors, proton conduction, and gas capture1–6. Moreover, COFs with controllable pore size and redox sites can also be applied in the field of electrochemical energy storage and conversion7–9. For efficient battery electrode applications, the skeletons of COFs need contain active groups such as $\\scriptstyle{\\mathrm{C=O}}$ and $\\mathrm{C}{=}\\mathrm{N}$ bonds where O and $\\mathrm{\\DeltaN}$ atoms could combine with ions (e.g. ${\\mathrm{Li^{+}}}$ , $\\mathrm{{Na^{+}}}$ , and $\\mathrm{K}^{+})^{10-12}$ . In addition, the nanopores should be large enough to accommodate ions like $\\mathrm{Na^{+}}$ without evident volume expansion and promote facile ions transport13. Generally, COFs-based electrode materials show the merits of low cost, environmental friendliness, structural designability, and sustainability14,15. \n\nIn fact, the application of COFs-based cathode materials for rechargeable batteries is just in the beginning16,17. For example, Kaskel’s group reported a microporous $(1.4\\mathrm{nm})$ bipolar COFs with active triazine rings and inactive benzene rings in the skeletons as an organic electrode for sodium-ion batteries, showing specific capacities of ${\\sim}200$ and $10\\mathrm{mAhg^{-1}}$ at 0.01 and $10\\mathrm{Ag^{-\\bar{1}}}$ , respectively18. Subsequently, Wang’s group designed three different types of exfoliated COFs for lithium batteries, exhibiting specific capacities of 145, 210, and $110\\mathrm{mAhg^{-1}}$ for anthraquinone-based, benzoquinone-based, and nitroxyl radical-based COFs, respectively19. Recent work revealed that the pentacenetetrone-based $\\pi$ -conjugated COFs with active $\\scriptstyle{\\mathrm{C=O}}$ bonds and inactive linkage groups in the skeletons displayed a discharge capacity of ${\\bar{\\sim}}12{\\bar{0}}\\operatorname{mAh}\\mathbf{g}^{-1}$ at a high rate of $\\bar{5}.0\\mathrm{\\dot{A}}\\mathrm{g}^{-1}$ and a capacity retention of $86\\%$ after 1000 cycles at $1.0\\mathrm{A}\\bar{\\mathrm{g}}^{-1}$ in sodium batteries20. The reported COFs-based cathodes for rechargeable batteries are still plauged by low capacity $({\\sim}200\\ \\mathrm{mAh}\\ \\mathbf{\\bar{g}}^{-1},$ and inferior rate capability, limiting their further applications21,22. The limited capacity of COFsbased cathodes can be ascribed to the introduction of inactive components (e.g., benzene skeleton, boronate esters, and hydrazones), which are used as the linkages to connect active groups within the molecules23–25. Additionally, the relatively poor electronic and ionic conductivities of the reported COFsbased electrode materials lead to their inferior rate capability26,27. The reported method to improve the rate performance of COFs is combining with conductive carbon materials such as graphene28–30. However, the addition of too many carbon materials inevitably decreases the whole energy density of practical batteries. Overall, realizing COFs-based cathode materials with high capacity and high-rate performance is still challenging nowadays. \n\nHerein, we report the design, synthesis and battery application of a COF with triquinoxalinylene and benzoquinone units (TQBQ) in the skeletons via a triple condensation reaction between tetraminophenone (TABQ) and cyclohexanehexaone (CHHO). Benefiting from the absence of inactive linkage groups in the skeletons, the TQBQ-COF electrode shows a high reversible capacity of $452.0\\ \\mathrm{mAh\\g^{-1}}$ and maintains $352.3\\ \\mathrm{\\overline{{~mAh~g^{-1}}}}$ after 100 cycles at $0.02\\mathrm{Ag^{-1}}$ in sodium batteries. Furthermore, the introduction of N atoms reduces the energy gap between the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO), resulting in enhanced electronic conductivity $(\\sim10^{-9}\\mathrm{Scm^{-1}})$ and high ionic conductivity $(\\sim10^{-4}\\mathrm{Scm}^{\\dot{-}1}$ for the discharged product). As a result, the TQBQ-COF shows a high rate capability of $134.3\\mathrm{mAhg^{-1}}$ at $10.0\\mathrm{Ag^{-1}}$ . In addition, the insoluble TQBQ-COF electrode exhibits excellent cycling stability with a capacity retention of $96\\%$ after 1000 cycles at $\\bar{1}.0\\mathrm{A}\\mathrm{g}^{-1}$ . Moreover, the combination of in/ex-situ Fourier transform infrared (FTIR) spectra and density functional theory (DFT) calculations demonstrate that the pyrazines $\\scriptstyle(\\mathrm{C}=\\mathrm{N})$ ) and carbonyls $(\\mathrm{C=O})$ are the active sites, and per TQBQ-COF repetitive unit could store twelve $\\mathrm{Na^{+}}$ ions, including six $\\mathrm{Na^{+}}$ ions within the TQBQ-COF plane and another six $\\mathrm{Na^{+}}$ ions outside the plane. The Mulliken charges of the two types of Na atoms and their adjacent $\\mathrm{~N~}$ and $\\mathrm{~O~}$ atoms can be obtained according to the accurate atomic coordinates of $\\mathrm{Na_{12}T Q B Q-C O F}$ . Furthermore, the average atomic valences of Na, O, and $\\mathrm{\\DeltaN}$ in $\\mathrm{Na_{12}T Q B Q-C O F}$ are calculated to be $+1,-1$ , and $-0.5$ , respectively. In addition, a pouch-type sodium battery with a capacity of $81\\mathrm{mAh}$ is fabricated, showing the way for the application of large batteries. \n\n# Results \n\nDesign and synthesis of TQBQ-COF. To achieve high capacity and good rate performance, a TQBQ-COF was designed by removing inactive linkage groups in the skeletons and doping heteroatoms. The TQBQ-COF with dual redox sites ( $\\scriptstyle(\\sum=\\mathbf{O}$ and $\\mathrm{C=N}$ were synthesized via a solvothermal reaction31 between TABQ and CHHO at $100^{\\circ}\\mathrm{C}$ for $^{48\\mathrm{h}}$ (Supplementary Fig. 1), followed by heated at $140^{\\circ}\\mathrm{C}$ under Ar bubbling for another $6\\mathrm{h}$ . After further annealing at $200^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ under argon atmosphere, the product was achieved as a dark-red powder with a yield of $80\\%$ . The facile synthetic process is beneficial for the large-scale preparation of TQBQ-COF. The TQBQ-COF materials consist of multiple carbonyls and pyrazine groups, where carbonyls are used as redox sites and the active pyrazine sites act as the linkage blocks to form the two-dimensional (2D) conjugated framework. As the carbonyls and pyrazine groups are both designed to be redox sites for TQBQ-COF electrode, a theoretical capacity of $515\\mathrm{\\mAh\\g^{-1}}$ (based on one repetitive unit marked inside the yellow dotted line in Fig. 1a) could be obtained. DFT calculations are applied to calculate the optimized structures of TQBQ-COF, showing a hexagonal micropore of $11.4\\mathring{\\mathrm{A}}$ and a packing distance of $3.07\\mathrm{\\check{A}}$ according to the simulated AB stacking model (Fig. 1b). \n\nStructural characterizations. The FTIR spectra of TQBQ-COF exhibits two distinct absorption peaks at $162\\bar{7}\\mathrm{cm}^{-1}$ and $1545\\mathrm{cm}^{-1}$ (Supplementary Fig. 2), which can be assigned to the stretching vibration modes of carbonyls $\\scriptstyle(\\mathrm{C=O})$ and imides $({\\mathsf{C}}{=}{\\mathsf{N}})$ , respectively28,31. In addition, the peaks of the heat-treated TQBQCOF at $13\\dot{6}5\\mathrm{cm}^{-1}$ and $3373\\mathrm{cm}^{-\\bar{1}}$ (corresponding to the stretching vibration of $\\mathrm{C-N}$ and $_\\mathrm{N-H}$ of TABQ-COF) both show obvious decrease in their peak intensity, suggesting the polymerization of the starting reagents. All peaks in the solid-state $^{13}\\mathrm{C}$ NMR spectrum of TQBQ-COF are marked in the indicated groups of the inset chemical structure (Supplementary Fig. 3). The peaks at about $170\\mathrm{ppm}$ and 143 ppm can be assigned to the carbonyl groups and the formation of imide bonds by the Schiff base reaction32, respectively, further confirming the structure of TQBQ-COF. The proportion of carbon, nitrogen, and oxygen elements account for 53.1, 23.8, and $22.0\\mathrm{wt\\%}$ from the elemental analysis (Supplementary Table 1). The excess content of oxygen element can be ascribed to the edge groups or small molecules (such as $\\mathrm{H}_{2}\\mathrm{O};$ , $\\mathrm{CO}_{2}.$ and $\\mathrm{CH}_{3}\\mathrm{OH})$ absorbed in the pores. \n\nThe crystallinity of TQBQ-COF was investigated by Powder X-Ray Diffraction (PXRD) and high-resolution transmission electron microscopy (HRTEM), as shown in Fig. 1. The strong diffraction peak at $28.24^{\\circ}$ is attributed to the (002) plane (Fig. 1c), which is related to the interlayer distance of $3.0\\pm0.2\\mathring\\mathrm{A}$ between the conjugated TQBQ-COF layers of the simulated AB stacking model (Fig. 1b). The peaks at $13.74^{\\circ}$ and $19.84^{\\circ}$ could be assigned to $(-220)$ and (201) facets, respectively. In addition, the peak at $15.69^{\\circ}$ in PXRD pattern could be assigned to the d-spacing of (0–11) plane, which is in agreement with the pore size of ${\\sim}5.6\\mathrm{\\AA}$ of the AB stacking model of TQBQ-COF. Affected by the strong $\\mathtt{p}{-}\\pi$ interaction between the adjacent 2D layers, TQBQ-COF layers tend to contact with each other by an alternative staggered stacking model (AB stacking model, Fig. 1b and Supplementary Fig. $4)^{\\tilde{3}1}$ . HRTEM image also shows that TQBQ-COF has a moderate crystallinity with periodicities (Fig. 1d), and the obvious lattice fringe distance $(0.30\\mathrm{nm})$ is well referring to the interlayer distance of TQBQ-COF layers. As shown in Fig. 1e, the selected area electron diffraction (SAED) pattern shows the alignment of the hexagonal pore along the (002), (201) and (600) facets of TQBQ-COF with d-spacing of ${\\sim}3.0\\mathrm{\\AA}.$ , ${\\sim}4.6\\mathrm{\\AA},$ and ${\\sim}2.4\\mathrm{\\AA}.$ respectively. Therefore, both the experimental PXRD and HRTEM results match the proposed AB stacking model well. It is noted that a few mismatching peaks are still existing between the experiment PXRD result and the simulation AB stacking pattern in Fig. 1c, which could be ascribed to the existence of the AA/AB' stacking model from a little isotropic powder (Supplementary Fig. 4a). Meanwhile, the HRTEM elemental mappings show uniform distribution of C, N, and O (Supplementary Fig. 5). The TQBQ-COF materials with a few defects and porous structure could combine with $\\mathrm{Na^{+}}$ well, similar to the sodium storage behavior of disordered soft and hard carbons33. \n\n![](images/a1c413bcc6d0881552e4caf1f52eb4d68be418c0cd97aeb7d8a6c1cb3bd3fcb4.jpg) \nFig. 1 Structure and characterizations of TQBQ-COF materials. a The chemical structure and possible electrochemical redox mechanism of TQBQ-COF with a theoretical capacity of $515\\mathsf{m A h g}^{-1}$ . b Top and side views of the schematic AB stacking model of TQBQ-COF layers with a packing distance of $3.07\\AA$ . c PXRD pattern and the simulated AB/AB' stacking models of TQBQ-COF powder. d High-resolution TEM image of TQBQ-COF with a multilayer stacking space of ${\\sim}0.30\\mathsf{n m}$ . Scale bar, $5\\mathsf{n m}$ . e SAED pattern of (002), (201), and (600) facets of TQBQ-COF from d. Scale bar, $5\\mathsf{n m}^{-1}$ . \n\nX-ray photoelectron spectroscopy (XPS) was performed to further confirm the chemical compositions of TQBQ-COF. The characteristic bands for the K-edge of carbon, nitrogen, and oxygen elements are exhibited without any other impurities from the survey scan XPS spectrum (Supplementary Fig. 6). The C1s spectrum (Supplementary Fig. 7a) mainly displays $\\mathrm{C=C},$ $\\scriptstyle{\\mathrm{C=O}}$ , and $\\mathrm{C}{=}\\mathrm{N}$ at 284.5, 287.8, and $287.0\\mathrm{eV}$ , respectively. The binding energy of $\\mathrm{C}{=}\\mathrm{N}$ is close to that of $\\scriptstyle{\\mathrm{C=O}}$ , which can be attributed to the delocalization of lone pair electrons of N and O atoms on the $\\pi$ -conjugated aromatic structure of TQBQ- $\\mathrm{\\COF^{31}}$ . The peak at $399.6\\mathrm{eV}$ is derived from the $\\mathrm{C}{=}\\mathrm{N}$ of the pyrazine moiety34 in the N1s spectrum (Supplementary Fig. 7b). All the results confirm the stable chemical compositions of TQBQ-COF. \n\nMorphology characterizations. The scanning electron microscope (SEM) images (Fig. 2a, Supplementary Fig. 8a, b) show a porous-honeycomb morphology of TQBQ-COF with irregular pores, which can also be observed from the TEM image (Supplementary Fig. 8c). As TEM result has shown the $\\mathrm{~d~}$ -spacing of $\\mathrm{\\stackrel{.}{\\sim}}3.0\\mathrm{\\AA}$ between each TQBQ-COF monolayer, a ${\\sim}5.0\\mathrm{nm}$ height of TQBQ-COF layers is corresponding to 16 layers of TQBQ-COF monolayers in the AFM image (Fig. 2b), which is smaller than that of graphene sheets $(0.34\\mathrm{nm})$ . In addition, Raman spectrum (Supplementary Fig. 8d) gives two peaks at ${\\sim}1326\\mathrm{cm}^{-1}$ (D bands) and $15\\dot{2}1\\mathrm{cm}^{-1}$ (G bands), where the D bands are derived from the $s p^{3}\\mathrm{~C~}$ and bent $s p^{2}$ C structures and the G bands referring to the conjugated $s\\bar{p^{2}}\\mathrm{C}$ structure. Combined with AFM and TEM results, the value of $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ (0.84) from Raman spectrum suggests moderate defect level for the 2D structure of TQBQ-COF layers35. \n\n$\\Nu_{2}$ adsorption-desorption isotherms measurements were performed to test the surface area and pore distribution of TQBQ-COF powder. The pristine TQBQ-COF with a specific surface area of $46.95\\mathrm{m}^{2}\\mathrm{g}^{-1}$ was shown in Supplementary Fig. 9. After annealing it at $200^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ the specific surface areas of the heat-treated sample can reach up to $94.36\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , with a micropore size of $1.18\\mathrm{nm}$ (Supplementary Fig. 10). The enlarged surface area can be attributed to the volatilization of small molecules absorbed into the holes. According to the isotherm type (Fig. 2c), most of void spaces in TQBQ-COF come from mesopores. The $t{\\cdot}$ -Plot analyses (the inset of Fig. 2c) was added to elucidate the microporous properties of TQBQ-COF. The $t$ -Plot results show that the micropores exist inside the TQBQ-COF. Therefore, the most pores of TQBQ-COF are mesopores, accompanied with some micropores. \n\nThermogravimetric analysis of the as-prepared TQBQ-COF shows a weight loss below $120^{\\circ}\\mathrm{C}$ due to the small molecules absorbed into the mesopores, while the heat-treated sample displays higher thermal stability (Supplementary Fig. 11). The heat-treated TQBQ-COF with larger surface area and more stable structure can favor ion diffusion and accommodate the intercalation of large $\\mathrm{Na^{+}}$ ions. Furthermore, the electronic conductivity is achieved as $1.973\\times10^{-9}\\mathrm{Scm^{-1}}$ according to the linear sweep voltammetry curves (Supplementary Fig. 12). The calculated band gap of TQBQ-COF is less than $1.0\\mathrm{eV}$ according to the density of states (DOS) (Fig. 2d), demonstrating the intrinsic semiconductor property of TQBQ-COF. Note that the ionic conductivity of asprepared TQBQ-COF was not tested because it does not contain $\\bar{\\bf N}\\bar{\\bf a}^{\\bar{+}}$ . Instead, we tested the ionic conductivity of the discharged product (discharged to $0.8\\mathrm{V},$ ) by electrochemical impedance frequency response36. As shown in Supplementary Fig. 13, the high-frequency part relates to the electronic and ionic resistance 1 $\\cdot R_{\\mathrm{e}}$ and $R_{\\mathrm{i}}^{\\mathrm{\\cdot}}$ ), and the low-frequency part corresponds to the electronic resistance $(R_{\\mathrm{e}})$ . Therefore, the ionic conductivity is calculated to be as high as $5.53\\times10^{-4}\\mathrm{Scm^{-1}}$ (detailed calculation process can be seen in the Supplementary Methods). The conductive TQBQ-COF material with rich nitrogen atoms and porous conjugated structure is able to facilitate electrons transport and $\\mathrm{Na^{+}}$ ions diffusion among the abundant redox sites27. \n\n![](images/1d092da25920a4536f265b831898d5140b0df3b20bd9dddb5a343e10eec977ff.jpg) \nFig. 2 Characterizations of TQBQ-COF. a The SEM image of TQBQ-COF powder. Scale bar, $100\\mathsf{n m}$ . b AFM height image of TQBQ-COF material. The inserted line shows a height of ${\\sim}5.0\\mathsf{n m}$ for 16 monolayers of TQBQ-COF. Scale bar, $300\\mathsf{n m}$ . c ${\\sf N}_{2}$ adsorption/desorption isotherms of the heat-treated TQBQ-COF. The inset is the $t$ -Plot analyses of the heat-treated sample. d The DOS of the simulated AB stacking structure for TQBQ-COF. \n\n$\\mathbf{In/Ex}$ -situ FTIR and ex-situ XPS on the TQBQ-COF electrodes. Before the study of the sodium-storage mechanism, the electrochemical performance of the TQBQ-COF electrode is investigated through the assembled coin-type SIB. The electrochemical impedance spectroscopies (EIS) of the TQBQ-COF electrodes were firstly tested in the electrolyte of $1.0\\mathrm{M}\\mathrm{\\NaPF_{6}}$ dissolved in diethylene glycol dimethyl ether (DEGDME) and propylene carbonate (PC), respectively (Supplementary Fig. 14). The charge transfer resistance (semicircles in high-frequency regions) of TQBQ-COF electrode in NaPF6/DEGDME $(150\\Omega)$ is much less than that in ${\\mathrm{NaPF}}_{6}/{\\mathrm{PC}}$ $(700\\Omega)$ . This can be attributed to the lager radius of $[\\mathrm{NaPC}3]^{+}$ solvation configuration and the high charge transfer resistance of $\\mathrm{{Na}}$ anode in the PC-based electrolyte (Supplementary Figs. 15, 16, and 17). Furthermore, \n\nTQBQ-COF is indeed insoluble in $\\mathrm{NaPF}_{6}/$ DEGDME (Supplementary Fig. 18). However, the electrolyte of NaPF6/DEGDME can wet the TQBQ-COF electrode plate in 5 s (Supplementary Fig. 19), implying the good wettability of $\\mathrm{NaPF}_{6}/$ DEGDME for the TQBQ-COF electrodes. Therefore, the applied electrolyte is 1.0 M NaPF6/DEGDME in the following experiments. \n\nIn-situ FTIR was applied to investigate the sodium storage mechanism of the TQBQ-COF electrode during electrochemical process. Figure 3a shows the discharging and charging curves $\\bar{(0.8\\mathrm{-}3.7\\mathrm{V}}$ , at $0.02\\mathrm{Ag^{-1}})$ of TQBQ-COF electrode for the initial two cycles. Notably, the TQBQ-COF electrode can achieve a high capacity of $505.3\\dot{\\mathrm{mAh}}\\mathrm{g}^{-1}$ (corresponding to $12~\\mathrm{{Na^{+}}}$ ions with each TQBQ-COF repetitive unit) when discharged the cell to $0.8\\mathrm{V}$ , and exhibit a reversible performance when recharged to $3.7\\mathrm{V}$ . The characteristic peaks of carbonyls and pyrazines for pristine TQBQCOF electrode are located at ${\\sim}1627$ and $1545\\mathrm{cm}^{-1}$ , respectively. As shown in Fig. 3b, the two characteristic peaks gradually become weak in the discharging process, coinciding with the sequential coordination of $\\mathrm{Na^{+}}$ ions with the active sites on the TQBQ-COF layer. The peak at $1627\\mathrm{cm}^{-1}$ almost disappears when discharged to $0.8\\mathrm{V}_{:}$ , while the characteristic peak at $1\\bar{5}\\dot{4}\\bar{5}\\mathrm{cm}^{-1}$ is still leaving a faint peak. Combined with the ex-situ FTIR results (Supplementary Figs. 20 and 21), the peak of the $\\scriptstyle{\\mathrm{C}}={\\mathrm{C}}$ mode could be assign to $\\stackrel{\\cdot}{\\sim}1600\\ c m^{-1}$ . Thus, the faint peak $(1550-1620\\mathrm{cm}^{-1},$ at fully discharged state in the ex-situ FTIR results is mostly owing to the existing of $\\scriptstyle{\\mathrm{C}}={\\mathrm{C}}$ and the residual $\\mathrm{C}{=}\\mathrm{N}$ for $\\mathrm{Na}_{n}\\mathrm{TQBQ-COF}$ 1 $\\begin{array}{r}{{'}n=1\\mathrm{-}12{'}}\\end{array}$ . It is noted that the in-situ FTIR is helpful to detect the sequential structure change for TQBQ-COF electrode, but it could not eliminate the interference of the electrolyte and the testing condition. The in-situ and ex-situ FTIR measurements could work well with each other to exhibit the $\\mathrm{Na^{+}}$ storage process. The $\\mathrm{Na^{+}}$ storage ability for both carbonyls and pyrazines of the TQBQ-COF electrode can be confirmed by the corresponding peaks change. In the charging process, the characteristic peaks of $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ and $\\mathrm{C}{=}\\mathrm{N}$ reemerge gradually and ultimately strengthen back to the pristine state. The same phenomenon occured in the second cycle, showing a reversible intercalation/ deintercalation process of $\\mathrm{Na^{+}}$ in the TQBQ-COF electrode. \n\n![](images/c759610691a01229c07fb1edb0f0122239c1c14864b6ebbea20a8f3b491f4ab9.jpg) \nFig. 3 Sequential structure evolution of active sites for TQBQ-COF electrodes during sodiation/desodiation processes. a Discharge and charge profiles of TQBQ-COF electrode at $0.02\\mathsf{A g}^{-1}$ in the voltage range of $0.8\\substack{-3.7V}$ in the initial two cycles. b In-situ FTIR spectra collected at different states corresponding to a. c The C1s XPS spectra of TQBQ-COF electrodes at different charge/discharge states marked in a. \n\nThe sodiation/desodiation process was further investigated by the ex-situ XPS spectra in Fig. 3c. The peaks of ${\\mathrm{C}}={\\mathrm{O}}$ $(287.6\\mathrm{eV})$ and $\\mathrm{C}{=}\\mathrm{N}$ $(287.0\\mathrm{eV})$ weaken gradually when discharged the cell to $1.6\\mathrm{V}$ , and become very weak as discharged to $0.8\\mathrm{V}$ . In contrast, the peaks of $\\mathrm{C-}\\mathrm{\\overset{.}{N}}$ $(285.6\\mathrm{eV})$ and $C{\\mathrm{-}}\\mathrm{O}$ $(286.2\\mathrm{eV})$ emerge gradually during the discharging process, and show obvious when discharged to $0.8\\mathrm{V}$ . The evolution of peaks of ${\\mathrm{C}}=$ O, $\\mathrm{C}{=}\\mathrm{N}$ , $C{\\mathrm{-}}\\mathrm{O}$ , and $\\mathrm{C-N}$ all exhibit a reverse trend, and all peaks in the C1s spectra are almost identical to the pristine state when the battery is recharged to $3.7\\mathrm{V}$ . The results indicate that both carbonyl groups and pyrazine sites have involved in the total sodiation and desodiation processes, which is in good agreement with the in/ex-situ FTIR results. The in/ex-situ FTIR spectra manifest that the carbonyl groups and pyrazine sites can almost simultaneously react with $\\mathrm{Na^{\\bar{+}}}$ ions. Moreover, the ex-situ XPS and the following DFT calculations could support this result as well. The possible reason why O and $\\mathrm{~N~}$ atoms simultaneously react with $\\mathrm{Na^{+}}$ ions is the minor difference in electronegativity between O and $\\mathrm{~N~}$ atoms on the conjugated structure of TQBQ-COF. \n\nDFT calculations during sodiation/desodiation. DFT calculations were applied to identify the sequential structural evolution of TQBQ-COF during sodiation and desodiation processes. Firstly, the DFT calculations were used to calculate the optimized structures of TQBQ-COF layers and the configurations after different degrees of sodiation. The molecular structure of TQBQCOF is simulated by one ring unit, whose outer edges are saturated with hydrogen atoms, as shown in Fig. 4a. After optimizing, the configuration of one TQBQ-COF unit is determined to be a planar hexagonal structure with a micropore diameter of $11.4\\mathring{\\mathrm{A}}$ , which is in good agreement with the BET results (with a micropore diameter of $1.18\\mathrm{nm}$ , Supplementary Fig. 10). Secondly, using molecular electrostatic potential (MESP) method37, six equivalent minima of ESP value are found in the middle of two adjacent nitrogen atoms within the molecular plane. These ESP minima correspond to six $\\mathrm{Na^{+}}$ accommodation sites. Thus, 6 $\\mathrm{Na^{+}}$ ions are placed at these sites and the consequent ${\\mathrm{Na}}_{6}{\\mathrm{TQBQ-}}$ COF unit is optimized to be a slightly curled surface, which can be attributed to the tension among both nitrogen and oxygen atoms and sodium ions. \n\nTo clarify the stabilization effect of both nitrogen and oxygen atoms towards $\\mathrm{Na^{+}}$ , orbital composition analyses of the LUMO of TQBQ-COF molecule was performed (Fig. 4b). The results show that nitrogen atoms account for $22.21\\%$ of the LUMO composition while that of oxygen atoms is $19.72\\%$ . The similar percentage of nitrogen and oxygen in the orbital composition of LUMO indicates that both nitrogen and oxygen atoms stabilized the $\\mathrm{Na^{+}}$ ions collaboratively, which are in good accordance with the experimental FTIR and XPS tests where the intensities of peaks of $\\mathrm{C}{=}\\mathrm{N}$ bonds and $\\scriptstyle{\\mathrm{C=O}}$ groups weaken simultaneously. In addition, the MESP and LUMO patterns of the two TQBQ-COF repetitive units (Supplementary Fig. 22) also exhibit same priority of $\\scriptstyle{\\mathrm{C=O}}$ in accommodating $\\mathrm{Na^{+}}$ ions, confirming that one repetitive ring unit is sufficient for simulating all ${\\mathrm{C}}={\\mathrm{O}}$ groups in an extended structure of TQBQ-COF. As a result, the first $6\\mathrm{\\bar{N}a^{+}}$ ions storage process should be depicted as per $\\mathrm{Na^{+}}$ accommodated between every two adjacent nitrogen atoms as well as two oxygen atoms in per unit plane of TQBQ-COF. \n\nThe MESP of $\\mathrm{Na_{6}T Q B Q-C O F}$ is calculated to find the rest of the $\\mathrm{Na^{+}}$ ion accommodation sites. A total of 12 ESP minima are found on a $\\mathrm{Na}_{6}$ TQBQ-COF unit, in which each carbonyl oxygens accommodated 2 ESP minima with a $1.8{\\cdot}\\mathring{\\mathrm{A}}$ distance between the minimum and the molecular surface. To prevent an over crowded sodiated configuration which would lead to large steric hindrance, one $\\mathrm{Na^{+}}$ is placed near each carbonyl in $\\mathrm{Na_{6}\\mathrm{\\bar{TQBQ-COF}}}$ unit to form the initial structure of $\\mathrm{Na}_{12}\\mathrm{TQBQ-COF}$ . The optimized geometry of $\\mathrm{Na_{12}T Q B Q-C O F}$ is also a curled surface similar to that of a $\\mathrm{Na_{6}T Q B Q-C O F}$ unit. Moreover, the accurate atomic coordinates of $\\mathrm{Na}_{12}$ TQBQ-COF are provided in Supplementary Table 2. From the atomic coordinates of $\\mathrm{Na_{12}T Q B Q-\\bar{C}O F}$ , we can obtain the Mulliken charges of each atom (such as O, N, Na). The Mulliken charges of two Na atoms with different chemical environment and their adjacent $\\mathrm{~N~}$ and $\\mathrm{~o~}$ atoms are marked in Fig. 4c. Furthermore, the average atomic valences of Na, O, and $\\mathrm{~N~}$ in $\\mathrm{Na}_{12}\\mathrm{TQBQ-COF}$ are calculated to be $+1,-1$ , and $-0.5;$ respectively. The coordination environment of the two sets of $\\mathrm{Na^{\\bar{+}}}$ ions in $\\mathrm{Na}_{12}\\mathrm{TQBQ-COF}$ is also analyzed using Mayer bond order in Supplementary Fig. 23 and Supplementary Table 3. The sodium ions located within the molecular plane of the TQBQCOF are coordinated by all four nitrogen and oxygen atoms (O-29, O-123, N-30, and N-56), while the sodium ions outside the molecular plane are only coordinated by one nitrogen atom (N-56) and one oxygen atom (O-123). Further MESP calculation on $\\mathrm{Na_{12}T Q B Q-C O F}$ exhibits no $\\mathrm{Na^{+}}$ accommodation site in the unit ring (Supplementary Fig. 24), confirming that only $12\\mathrm{\\Na}^{+}$ ions can access to each unit of the TQBQ-COF. Therefore, the next $6~\\mathrm{Na^{+}}$ ions storage process can be depicted as per $\\mathrm{Na^{+}}$ located between two adjacent oxygen and nitrogen atoms outside of TQBQ-COF plane. \n\n![](images/7df2009b878a9c0f45f71e14ebf028d042ea508eed3fab32a8ac51a5de7220e4.jpg) \nFig. 4 The up-to 12 $\\pmb{{\\mathsf{N a}}}^{+}$ ions redox chemistry mechanism for each TQBQ-COF repetitive unit. a Schematic diagram of two-step sodiation and desodiation process of the TQBQ-COF electrode obtained via the molecular electrostatic potential (MESP) method. The diameter of the TQBQ-COF unit by the DFT calculations is $\\begin{array}{r}{11.4\\mathring{\\mathsf{A}},}\\end{array}$ and the values inside the ring unit of the MESP figures indicate the ESP minima. b LUMO plot for per TQBQ-COF repetitive unit. c Mulliken charges of two $\\mathsf{N a}$ atoms with different chemical environment and their adjacent N and O atoms in $\\mathsf{N a}_{12}\\mathsf{T Q B Q-C O F}$ . \n\nTo further understand the sequential energy evolution of the TQBQ-COF accompanying the multiple-electron transfer, the corresponding voltages during sodiation are also calculated by DFT calculations. The energy values of $\\mathrm{Na}_{n}\\mathrm{TQBQ-COF}$ $(n=1,2$ , 5, 6, 7, 11, and 12) are defined by single point energy and Gibbs free energy (Supplementary Table 4). Thus, their corresponding redox potentials can be obtained (Supplementary Fig. 25). The average voltage plateaus corresponding to the first $\\bar{5}\\mathrm{Na}^{+}$ ions and following $6\\ \\mathrm{{Na}^{+}}$ ions storage are calculated to be $2.79\\mathrm{V}$ and $1.59\\mathrm{V}$ , respectively. \n\nElectrochemical performance. Subsequently, we investigated the electrochemical performance of TQBQ-COF electrode. The CV curves display two obvious couples of redox peaks (Fig. 5a), which can be ascribed to the successive two-step sodiation/desodiation process. The peak at $2.2\\mathrm{V}$ is in consistent with first 6 $\\mathrm{Na^{+}}$ ions located inside the ring plane of TQBQ-COF, while the peak at $1.5\\mathrm{V}$ can be assigned to the next $6~\\mathrm{Na^{+}}$ ions stored outside the ring plane of TQBQ-COF, which are in good agreement with DFT calculations. The galvanostatic charge–discharge profile of the TQBQ-COF electrode in sodium battery delivers an initial discharge capacity of 452.0 mAh $\\mathbf{g}^{-1}$ (at $\\begin{array}{r}{0.02\\mathrm{Ag}^{-1}}\\end{array}$ , $1\\sim3.6\\mathrm{V},$ ) in Fig. 5b. It exhibits a high reversible capacity of ${\\sim}400\\ \\mathrm{mAhg^{-1}}$ in the following 10 cycles and maintains a capacity of $352.3\\mathrm{mAhg^{-1}}$ after 100 cycles. In addition, the compaction density of the TQBQ-COF pellet calculated from Supplementary Fig. 26 is $\\sim1.63\\mathrm{gcm}^{-3}$ , thus the volumetric energy of the TQBQCOF electrode is calculated to be ${\\sim}1252\\mathrm{Wh}\\mathrm{L}^{-1}$ TQBQ-COF (based on the capacity of $452.0\\mathrm{mAh}$ $\\mathbf{g}^{-1}$ TQBQ-COF at $0.\\dot{0}2\\dot{\\mathrm{A}}\\mathrm{g}^{-1},$ ). The wide scan of XPS spectra (Supplementary Fig. 27) manifest some new peaks in the TQBQ-COF electrode after recharged to $3.7\\mathrm{V}$ , which is associated with the formation of solid electrolyte interface (SEI) around the TQBQ-COF cathode. The capacity loss could be explained by the XPS results (formation of SEI) or some unstable sites for $\\dot{\\mathrm{Na^{+}}}$ storage. As shown in Supplementary Fig. 28, the self-discharge performance was evaluated after standing the fully-charged cell (after 5th cycle) for $24\\mathrm{h}$ , and $92\\%$ of original capacity was retained after fully discharged at $0.2\\mathrm{C}$ ( $1~{\\mathrm{C}}=400{\\mathrm{m}}{\\mathrm{\\bar{A}h}}{\\mathrm{g}}^{-1},$ . The good sodium storage performance could be attributed to the stability of the TQBQ-COF material and less side reactions of the electrolyte. \n\n![](images/488570a1f9f3455d9333c6a50efe0f27224e83d003401a578ab720afa9e768c7.jpg) \nFig. 5 Electrochemical properties of the TQBQ-COF electrodes between the voltage range from 1.0 V to 3.6 V. a CV curves of the TQBQ-COF electrode at a scan rate of $0.2\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . b Charge–discharge profiles of the TQBQ-COF electrode at $0.02\\mathsf{A g}^{-1}$ . c The rate performance of the TQBQ-COF electrode from the current density of 0.1 to ${10\\mathsf{A}}{\\mathsf{g}}^{-1},$ then back to $0.1\\mathsf{A}\\mathsf{g}^{-1}$ . d Long cycling stability of TQBQ-COF electrodes at different current densities (0.1, 0.5, and $1.0\\mathsf{A}\\mathsf{g}^{-1})$ . The capacities are all calculated based on the mass of TQBQ-COF. e The selected charge/discharge curves of pouch-type Na//TQBQ-COF batteries at a current of $50\\mathsf{m A}$ . The capacity is calculated based on the mass of the full cell. \n\nThe TQBQ-COF electrode shows reversible capacities of 278.6, 234.0, 180.6, and $134.3\\mathrm{mAhg^{-1}}$ (Supplementary Fig. 29) at 0.3, 1.0, 5.0, and $10.0\\mathrm{Ag}^{-1}$ , respectively. As the current density was decreased to $0.1\\mathrm{\\AA}\\mathrm{g}^{-1}$ , the capacity of TQBQ-COF electrode could also reach up to ${\\sim}300\\bar{\\mathrm{mAhg^{-1}}}$ . Figure 5c presents the corresponding rate performance of the TQBQ-COF electrode. The coulombic efficiency varies once the current density changes, which is likely caused by the concentration polarization inside the battery. Notably, an impressive capacity of $134.3\\mathrm{mAh}$ $\\mathbf{g}^{-1}$ can be achieved after discharging the cell in only $48\\:s$ (at $1\\bar{0.0}\\mathrm{Ag^{-1}}.$ ), showing an excellent rate performance. CV measurement was employed to estimate diffusion kinetics of $\\mathrm{Na^{+}}$ at different scan rates, ranging from 0.2 to $2.0\\:\\mathrm{mV}\\:s^{-1}$ (Supplementary Fig. 30). Based on the equation: \n\n$$\ni=a\\nu^{b}\n$$ \n\nwhere $i$ is the peak current, $\\nu$ is the scan rate, and $a$ and $b$ are constants. When the value of $b$ is close to 0.5, it shows a $\\mathrm{Na^{+}}$ diffusion controlled process; while it presents a supercapacitor behavior when $b\\approx1$ . The battery with TQBQ-COF electrode shows the value of $b$ is close to 0.9, which is in consistent with the supercapacitor-like rate performance, delivering fast kinetics for $\\mathrm{N}\\bar{\\mathsf{a}}^{+}$ storage34. The $\\mathrm{Na^{+}}$ diffusion coefficient $({D_{\\mathrm{Na}}}^{+})$ was calculated to be ${\\sim}10^{-11}\\mathrm{Scm}^{-1}$ , both by the CV methods38 and the galvanostatic intermittent titration technique measurement (Supplementary Fig. 31)29. The detailed calculation process for the ${\\mathrm{{\\bar{\\calD}}_{N a}}}^{+}$ can be seen in the Supplementary Methods. As a result, the good reaction kinetics, high porous feature and nitrogendoping conjugated structure guarantee the TQBQ-COF electrodes with high capacity and high rate capability for sodium batteries. \n\nThe specific capacity of TQBQ-COF electrode can reach $327.2\\mathrm{mAhg^{-1}}$ at $\\bar{0}.1\\mathrm{A}\\dot{\\mathrm{g}}^{-1}$ in Fig. 5d, and a capacity retention of ${\\sim}89\\%$ after 400 cycles is achieved. Moreover, the long cycling stability of the TQBQ-COF electrode is obtained (Fig. 5d). After 1000 cycles at $0.5\\mathrm{Ag}^{-1}$ and $1.0\\mathrm{Ag}^{-1}$ , they exhibit a reversible capacity of 236.5 and $213.6\\operatorname{mAh}\\mathbf{g}^{-1}$ , yielding a capacity retention of $91.3\\%$ and $96.4\\%$ , respectively. The specific capacity of the TQBQ-COF electrode shows an increasing trend for the initial 10 cycles at the large currents owing to the slow process to open the ion transport channel for the TQBQ-COF electrode, and the capacity retention is calculated based on the 10th cycle. Moreover, the TQBQ-COF delivers a high Coulombic efficiency of $\\sim100\\%$ , and the energy efficiency is around $85\\%$ (Supplementary Fig. 32), showing good cycling stability and highenergy efficiency39. \n\nThe excellent cycling stability of the TQBQ-COF electrode could be ascribed to its inherent stable feature and the high $D_{\\mathrm{Na}}\\mathrm{^{+}}$ . Additionally, the weak peak in the UV-vis spectra of TQBQ-COF electrodes in $\\mathrm{NaPF_{6}/D E G D M E}$ indicates the poor solubility of the discharged and recharged products (Supplementary Fig. 33). TQBQ-COF electrode remains low impedance after 500 $(169.4\\Omega)$ and 1000 cycles $(220.2\\Omega)$ in Supplementary Fig. 34, and shows no obvious cracks in the plate after 500 cycles (Supplementary Fig. 35). The TQBQ-COF electrode displays high-energy density and upper power density (Supplementary Fig. 36 and Supplementary Table 5) when compared with current reported organic cathodes for sodium batteries. Furthermore, a pouch-type 81 mAh sodium battery with Na anode, TQBQ-COF cathode, and ${\\mathrm{NaPF}}_{6}$ -DEGDME electrolyte was constructed, showing a capacity of $75.3\\mathrm{mAh}$ after 20 cycles at a current of $50\\mathrm{mA}$ (Fig. 5e). The detailed assembly process of the pouch-type sodium batteries can be seen in Supplementary Methods. The capacity $(54.4\\mathrm{mAh}\\mathrm{g}^{-1}\\mathrm{_{cell}^{})}$ for the 6th cycle normalized by the whole mass $(1.49\\mathrm{g})$ of the pouch-cell is shown in Supplementary Fig. 37 and Supplementary Table 6. With a voltage plateau of $1.86\\mathrm{V}$ , the pouch-type sodium battery exhibits an outstanding energy density of $10\\mathrm{i.i\\mathrm{Wh}k g^{-1}}$ (based on the mass of the whole cell), demonstrating the potentially practical applications of TQBQ-COF. As the volume of the pouch-cell is 1.92 $(6\\times8\\times$ $0.04)~\\mathrm{cm}^{3}$ , the volumetric energy of the total pouch-cell is calculated to be $78.5\\mathrm{Wh}\\mathrm{L}^{-1}$ . The porous and nitrogen-doped structure of TQBQ-COF facilitates the rapid ions/electrons transport among the multiple active sites, and hence endows the TQBQ-COF electrodes with outstanding cycling stability and rate performance for sodium batteries. \n\n# Discussion \n\nWe have successfully synthesized a TQBQ-COF with multiple active sites and nanoporous structure for high-efficiency electrochemical sodium storage. The pyrazines as well as carbonyls act as redox sites in the nitrogen-rich conjugated structure of TQBQCOF. The up-to $12\\ \\mathrm{Na}^{+}$ redox chemistry mechanism of each TQBQ-COF repetitive unit is demonstrated by the in/ex-situ FTIR methods and DFT calculations. The insoluble TQBQ-COF electrode exhibits a remarkably high specific capacity of $452.0\\:\\mathrm{mAh}\\:\\mathrm{g}^{-1}$ at $0.02\\mathrm{Ag^{-1}}$ , excellent cycling stability $(\\sim96\\%$ after 1000 cycles at $1.0\\mathrm{Ag^{-1}}\\rangle$ ) and good rate capability $(1\\dot{3}4.3\\mathrm{mAh}\\mathrm{g}^{-1}$ at $10.0\\mathrm{{Ag}^{-1}},$ ). The superior rate performance can be attributed to the honeycomblike morphology and high electronic conductivity $(1.973\\times\\mathrm{\\dot{1}0^{-9}S}$ $\\mathrm{cm}^{-1}$ ) of TQBQ-COF. Moreover, the TQBQ-COF-based pouchtype battery shows a capacity of $81\\mathrm{mAh}$ and a voltage plateau of $1.86\\mathrm{V}_{:}$ , corresponding to the gravimetric and volumetric energy density of $10\\mathrm{{i.1Wh\\bar{k}g^{-1}}}$ and $78.5\\mathrm{Wh}\\mathrm{L}^{-1}$ (based on the whole pouch-type cell), respectively. This work sheds light on the design and application of COFs with multiple redox sites for high-energy and high-power sodium batteries. \n\n# Methods \n\nSynthesis of TQBQ-COF. CHHO $(5.0\\mathrm{g},16.0\\mathrm{mmol})$ ) and TABQ $(4.0\\mathrm{g},24.0\\mathrm{mmol})$ were put into the flask bottom under argon atmosphere, and $150\\mathrm{mL}$ mixture of deoxygenated acetic acid/ethanol (v/v 1:1) was slowly added. After stirred at room temperature for $30\\mathrm{min}$ , the mixture was heated at $100^{\\circ}\\mathrm{C}$ for $^{48\\mathrm{h},}$ followed by heated at $140^{\\circ}\\mathrm{C}$ under Ar bubbling for another $^{6\\mathrm{h}}$ . A dark-red powder was achieved after rinsed by massive water, methanol, and acetone, respectively. Moreover, the resultant powder was further washed with water and methanol by Soxhlet extractor for $^{12\\mathrm{h}}$ . The sample was finally annealed at $200^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ under argon atmosphere. \n\nMaterial characterization. The structure of the resultant TQBQ-COF material was examined by solid-state $^{13}\\mathrm{C}$ NMR with Inova $400\\mathrm{MHz}$ Spectrometer (Varian Inc., USA), and Fourier transform infrared spectroscopy (FTIR, Bruker \n\n5700 TENSOR П) in range of $400{-}4000~\\mathrm{cm}^{-1}$ . Powder XRD (Rigaku Mini$\\mathrm{Flex}600\\times$ -ray generator, Cu Kα radiation, $\\lambda=1.54178\\mathrm{\\AA}$ ), high-resolution transmission electron microscopy (HRTEM) and the selected area electron diffraction (SAED) pattern (Taols F200X G2) were applied to investigate the crystallinity and the microstructure of the TQBQ-COF powder. The elemental distributions of the TQBQ-COF material and the relevant electrodes before and after discharge/charge were characterized by scanning electron microscopy-Energy dispersive spectrum mapping (SEM-EDS), elemental analysis (EA, vario EL CUBE), and X-ray photoelectron spectroscopy (XPS, Perkin Elmer PHI 1600 ESCA), respectively. The morphologies of the TQBQ-COF material and the relevant electrodes were observed by scanning electron microscopy (SEM, JEOL JSM7500F), transmission electron microscopy (TEM, Taols F200X G2), and $\\Nu_{2}$ adsorption/desorption measurement (BEL Sorp mini). Moreover, Raman (DXR Microscope, Thermo Fisher Scientific with excitation at $532\\mathrm{nm}$ ) and TG-DSC analyzer (NETZSCH, STA 449 F3) were separately carried out to examine the structure and the stability of TQBQ-COF material, respectively. \n\nTQBQ-COF. $^{13}\\mathrm{C}$ NMR $400\\mathrm{{MHz}}$ , Magic Angle Spinning): $\\delta$ (ppm): 210 $\\mathrm{(m)}$ ; 172 (m); and 145 $(\\mathrm{m})$ . Elemental analysis: calculated for $\\mathrm{C}_{30}\\mathrm{N}_{12}\\mathrm{O}_{6}$ : C, $57.69\\%$ ; N, $26.92\\%$ ; O, $15.38\\%$ found: C, $53.12\\%$ ; N, $23.76\\%$ ; H, $2.17\\%$ . FTIR (ATR, $\\mathsf{c m}^{-1}$ ): 1,627; 1,545; 1,367; 1,263; 1,098; 1,022; and 802. \n\nElectrochemical measurements. The electrochemical performance of the TQBQCOF electrodes including galvanostatic charge/discharge, CV and EIS were evaluated in CR2032-type coin cells with sodium disks applied as the counter electrodes. Moreover, the glass microfiber membrane (Whatman GF/D, Aldrich) was used as the separator, and $1.0\\mathrm{M}\\mathrm{NaPF}_{6}/\\mathrm{DEGDMF}$ solution was applied as the electrolyte. The TQBQ-COF electrode was prepared by mixing $50\\mathrm{wt\\%}$ TQBQ-COF powders, $40\\mathrm{wt\\%}$ Super P and $10\\mathrm{wt\\%}$ polyvinylidene fluoride (PVDF) in the homogenate locket, dispersing the mixture in anhydrous $N$ -methyl-2-pyrrolidinone (NMP) and casting the resulting slurry on an Al foil, followed by drying it at $80^{\\circ}\\mathrm{C}$ in vacuum for $^{12\\mathrm{h}}$ . Finally, punched the Al foil into circular electrodes and stored them in Ar-filled glovebox before the assembly of the cells. Galvanostatic charge/ discharge was performed on LAND-CT2001A battery instrument (LAND Electronic Co., Wuhan China). CV was carried out in the voltage range of $0.8{\\sim}3.8\\mathrm{V}$ at a scan rate of $0.2\\:\\mathrm{mV}\\:s^{-1}$ and EIS was carried out on a Parstat 263 A electrochemical workstation (AMETEK Co.) in a frequency range of $10^{5}–0.01\\mathrm{Hz}$ . With a cathode-limited design, the cell capacity was determined based on the mass of TQBQ-COF by deducting the capacity contribution from Super P. \n\nIn/Ex-situ FTIR and ex-situ XPS spectroscopy. To monitor the structural evolution of active materials in charge/discharge processes, the TQBQ-COF electrodes for in-situ FTIR measurement were containing $80\\mathrm{wt\\%}$ active material, $10\\mathrm{wt\\%}$ Super P, and $10\\mathrm{wt\\%}$ PTFE. After hand mixing, the slurry was casted onto the stainless steel net, and the electrodes were dried at $60^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ under vacuum. The process to prepare the cell for in-situ FTIR testing is in the Ar-filled glove box. During the test, a stream of Ar flow was used to protect the discharging/charging products from oxidized in attenuated total reflection (ATR) pattern. Based on the CV results, the assembled cells were cycled at a current density of $0.02\\mathrm{Ag^{-1}}$ in the range of $0.8\\mathrm{-}3.7\\:\\mathrm{V}$ for in-situ FTIR measurements. TQBQ-COF electrodes for ex-situ FTIR testing contain $70\\mathrm{wt\\%}$ active material, $20\\mathrm{wt\\%}$ Super P, and $10\\mathrm{\\mt{\\%}}$ PVDF. The preparation was made in the same way as the approach mentioned above. The samples for ex-situ FTIR tests were obtained by disassembling the labeled cells in the argon-filled glovebox, and washing the electrodes with glycol dimethyl ether (DME) for three times, followed by dried in vacuum. The products at different charge and discharge states were tested in a stream of Ar flow using the ATR pattern. \n\nTQBQ-COF electrodes for XPS testing contain $60\\mathrm{wt\\%}$ active material, $30\\mathrm{wt\\%}$ Super P, and $10\\mathrm{\\mt\\%}$ PVDF. Samples were prepared by disassembling the labeled cells in the Ar-filled glovebox, and washing the electrodes with glycol dimethyl ether (DME) for three times, followed by dried in vacuum. Finally, the products at different charge and discharge states were tested in the argon atmosphere. \n\nDensity functional theory calculations. Becky’s three-parameter exchange function combined with Lee-Yang-Parr correlation functional (B3LYP) method with $_{6-31\\mathrm{G}}$ (d) basis $\\mathsf{s e t}^{40}$ was applied for the geometric optimization of the TQBQ-COF. All molecular structures were optimized using Gaussian 16 software package under B3LYP/6–31 G (d) level of theory followed by vibrational frequency calculations and to further confirm their stability. To simulate the solvation effect, single point energy calculations were performed using the SMD solvation model at $\\mathrm{B}3\\mathrm{LYP}/6{-}31+\\mathrm{G}$ (d, p) level with a solvent dielectric constant $(\\varepsilon)^{41}$ of 7.2 which reliably describes the polarity of experimentally used electrolyte solvent DEGDME. The molecular electrostatic potential (MESP) method was applied to predict the sodiation sites of TQBQ-COF using Multiwfn 3.6 software42, by which the Mayer bond order analysis43 and the density of states (DOS) were also carried out. In addition, the accurate atomic coordinates of $\\mathrm{Na_{12}T Q B Q-C O F}$ were calculated by Gaussian 16 software package, from which the Mulliken charges of two types of $\\mathrm{{Na}}$ atoms and their adjacent N and O atoms can be obtained. \n\nThe sodiation/desodiation process of the potential active sites was revealed by orbital composition analyses of the lowest unoccupied molecular orbital (LUMO), to clarify the stabilization effect of both nitrogen and oxygen atoms towards sodium ions. The MESP of TQBQ-COF and $\\mathrm{\\DeltaNa_{6}T Q B Q-C O F}$ were calculated to find the rest of $\\mathrm{Na^{+}}$ accommodation sites. In addition, the average voltages of the above two stages were predicted by the equation: \n\n$$\nV=-{\\frac{\\Delta G}{n F}}\n$$ \n\nwhere $V$ is the voltage, $\\Delta G$ is the standard Gibbs free energy change during the two sodiation processes, $n$ is the number of electrons transferred, and $F$ is the Faraday constant. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 15 May 2019; Accepted: 13 November 2019; Published online: 10 January 2020 \n\n# References \n\nHuang, N., Wang, P. & Jiang, D. L. Covalent organic frameworks: a materials platform for structural and functional designs. Nat. Rev. Mater. 1, 16068 (2016). \n2. Diercks, C. S. & Yaghi, O. M. The atom, the molecule, and the covalent organic framework. Science 355, 1585 (2017). \n3. Zhong, W. F. et al. A covalent organic framework bearing single Ni sites as a synergistic photocatalyst for selective photoreduction of $\\mathrm{CO}_{2}$ to CO. J. Am. Chem. Soc. 141, 7615–7621 (2019). \n4. Kim, T. W. et al. Ultrafast charge transfer coupled with lattice phonons in two-dimensional covalent organic frameworks. Nat. Commun. 10, 1873 (2019). \n5. Xu, H., Tao, S. S. & Jiang, D. L. Proton conduction in crystalline and porous covalent organic frameworks. Nat. Mater. 15, 722–726 (2016). \n6. Guan, X. Y. et al. Chemically stable polyarylether-based covalent organic frameworks. Nat. Chem. 11, 587–594 (2019). \n7. Wang, Z. L. et al. Few layer covalent organic frameworks with graphene sheets as cathode materials for lithium-ion batteries. Nanoscale 11, 5330–5335 (2019). \n8. Li, Y. J. et al. Conductive microporous covalent triazine-based framework for high-performance electrochemical capacitive energy storage. Angew. Chem. Int. Ed. 57, 7992–7996 (2018). \n9. DeBlase, C. R. et al. Cation-dependent stabilization of electrogenerated naphthalene diimide dianions in porous polymer thin films and their application to electrical energy storage. Angew. Chem. Int. Ed. 54, 13225–13229 (2015). \n10. Xu, S. Q. et al. A nitrogen-rich 2D $\\mathsf{s p}^{2}$ -carbon-linked conjugated polymer framework as a high-performance cathode for lithium-ion batteries. Angew. Chem. Int. Ed. 57, 1–6 (2018). \n11. Wu, S. F. et al. Highly durable organic electrode for sodium-ion batteries via a stabilized a-C radical intermediate. Nat. Commun. 7, 13318 (2016). \n12. Liu, Y. et al. Activating aromatic rings as Na-Ion storage sites to achieve high capacity. Chem 4, 2463–2478 (2018). \n13. Feng, X., Ding, X. S. & Jiang, D. L. Covalent organic frameworks. Chem. Soc. Rev. 41, 6010–6022 (2012). \n14. Ding, S. Y. & Wang, W. Covalent organic frameworks (COFs): from design to applications. Chem. Soc. Rev. 42, 548–568 (2013). \n15. Zhao, Q., Zhu, Z. Q. & Chen, J. Molecular engineering with organic carbonyl electrode materials for advanced stationary and redox flow rechargeable batteries. Adv. Mater. 29, 1607007 (2017). \n16. Xiao, P. T. & Xu, Y. X. Recent progress in two-dimensional polymers for energy storage and conversion: design, synthesis, and applications. J. Mater. Chem. A 6, 21676–21695 (2018). \n17. Jiang, C. et al. Constructing universal ionic sieves via alignment of twodimensional covalent organic frameworks (COFs). Angew. Chem. Int. Ed. 57, 16072–16076 (2018). \n18. Sakaushi, K. et al. Aromatic porous-honeycomb electrodes for a sodiumorganic energy storage device. Nat. Commun. 4, 1485 (2013). \n19. Wang, S. et al. Exfoliation of covalent organic frameworks into few-layer redox-active nanosheets as cathode materials for lithium-ion batteries. J. Am. Chem. Soc. 139, 4258–4261 (2017). \n20. Li, H. Y. et al. Large π‑conjugated porous frameworks as cathodes for sodiumion batteries. J. Phys. Chem. Lett. 9, 3205–3211 (2018). \n21. Wu, Z. Z. et al. Recent progress in metal–organic polymers as promising electrodes for lithium/sodium rechargeable batteries. J. Mater. Chem. A 7, 4259–4290 (2019). \n22. Schon, T. B., Mcallister, B. T., Li, P. F. & Seferos, D. S. The rise of organic electrode materials for energy storage. Chem. Soc. Rev. 45, 6345–6404 (2016). \n23. Wu, Y. W. et al. Quinone electrode materials for rechargeable lithium/sodium ion batteries. Adv. Energy Mater. 7, 1700278 (2017). \n24. Zhou, J. W. & Wang, B. Emerging crystalline porous materials as a multifunctional platform for electrochemical energy storage. Chem. Soc. Rev. 46, 6927–6945 (2017). \n25. Liang, Y. L. & Yao, Y. Positioning organic electrode materials in the battery landscape. Joule 7, 008 (2018). \n26. Wang, C. L. et al. Extended π-conjugated system for fast-charge and -discharge sodium-ion batteries. J. Am. Chem. Soc. 137, 3124–3130 (2015). \n27. Mahmood, J. et al. Nitrogenated holey two-dimensional structures. Nat. Commun. 6, 6486 (2015). \n28. Luo, Z. Q. et al. A microporous covalent organic framework with abundant accessible carbonyls for lithium-ion batteries. Angew. Chem. Int. Ed. 37, 9443–9446 (2018). \n29. Lei, Z. D. et al. Boosting lithium storage in covalent organic framework via activation of 14-electron redox chemistry. Nat. Commun. 9, 576 (2018). \n30. Chen, X. D. et al. Few-layered boronic ester based covalent organic frameworks/carbon nanotube composites for high-performance K-organic batteries. ACS Nano 13, 3600–3607 (2019). \n31. Lin, Z. Q. et al. Solution-processed nitrogen-rich graphene-like holey conjugated polymer for efficient lithium ion storage. Nano Energy 41, 117–127 (2017). \n32. Peng, C. X. et al. Reversible multi-electron redox chemistry of $\\pi$ -conjugated N-containing heteroaromatic molecule-based organic cathodes. Nat. Energy 2, 17074 (2017). \n33. Yabuuchi, N., Kubota, K., Dahbi, M. & Komaba, S. Research development on sodium-ion batteries. Chem. Rev. 114, 11636–11682 (2014). \n34. Kou, Y. et al. Supercapacitive energy storage and electric power supply using an aza-fused p-conjugated microporous framework. Angew. Chem. Int. Ed. 50, 8753–8757 (2011). \n35. Ferrari, A. C. Raman spectroscopy of amorphous, nanostructured, diamondlike carbon, and nanodiamond. Philos. Trans. R. Soc. Lond. A 362, 2477–2512 (2004). \n36. Wang, C. S. & Hong, J. Ionic/Electronic conducting characteristics of LiFeP $\\mathrm{\\DeltaO_{4}}$ cathode materials. Electrochem. Solid-State Lett. 10, A65–A69 (2007). \n37. Miao, L. C. et al. The structure-electrochemical property relationship of quinone electrodes for lithium-ion batteries. Phys. Chem. Chem. Phys. 20, 13478–13484 (2018). \n38. Levi, M. D. & Aurbach, D. The mechanism of lithium intercalation in graphite film electrodes in aprotic media. Part 1. High resolution slow scan rate cyclic voltammetric studies and modeling. J. Electroanal. Chem. 421, 79–88 (1997). \n39. Ding, Y. et al. Pathways to widespread applications: development of redox flow batteries based on new chemistries. Chem 5, 1–24 (2019). \n40. Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n41. Kadam, A. et al. Comparative performance evaluation and systematic screening of solvents in a range of Grignard reactions. Green Chem. 15, 1880–1888 (2013). \n42. Liu, L. J. et al. Molecular electrostatic potential: a new tool to predict the lithiation process of organic battery materials. J. Phys. Chem. Lett. 9, 3573–3579 (2018). \n43. Li, L. et al. Infrared spectra of the HAnX and $\\mathrm{H}_{2}\\mathrm{AnX}_{2}$ molecules ( ${\\mathrm{.}}\\mathrm{An}{=}\\mathrm{Th}$ and U, $\\scriptstyle\\mathrm{X=Cl}$ and Br) in argon matrices supported by electronic structure calculations. Chem. Eur. J. 25, 1795–1805 (2019). \n\n# Acknowledgements \n\nThis work was supported by the National Programs for Nano-Key Project (2017YFA0206700), the National Natural Science Foundation of China (21835004), and 111 Project from the Ministry of Education of China (B12015). The calculations in this work were performed on TianHe-1(A), National Supercomputer Center in Tianjin. \n\n# Author contributions \n\nJ.C. proposed the concept and supervised the work; R.J.S. designed and performed the experiments; L.J.L. performed the DFT calculations and explained the sodiation process; Y.L. and C.C.W. performed the batteries assembly; Z.H.Y., Y.X.L. and L.L. helped to perform the experiments and analyze the data; all authors contributed to the discussion and the manuscript preparation. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 019-13739-5. \n\nCorrespondence and requests for materials should be addressed to J.C. \n\nPeer review information Nature Communications thanks Ken Sakaushi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1016_j.chempr.2019.12.008", + "DOI": "10.1016/j.chempr.2019.12.008", + "DOI Link": "http://dx.doi.org/10.1016/j.chempr.2019.12.008", + "Relative Dir Path": "mds/10.1016_j.chempr.2019.12.008", + "Article Title": "Enabling Direct H2O2 Production in Acidic Media through Rational Design of Transition Metal Single Atom Catalyst", + "Authors": "Gao, JJ; Yang, HB; Huang, X; Hung, SF; Cai, WZ; Jia, CM; Miao, S; Chen, HM; Yang, XF; Huang, YQ; Zhang, T; Liu, B", + "Source Title": "CHEM", + "Abstract": "The electrochemical oxygen reduction reaction in acidic media offers an attractive route for direct hydrogen peroxide (H2O2) generation and on-site applications, Unfortunately there is still a lack of cost-effective electrocatalysts with high catalytic performance. Here, we theoretically designed and experimentally demonstrated that a cobalt single-atom catalyst (Co SAC) anchored in nitrogen-doped graphene, with optimized adsorption energy of the *OOH intermediate, exhibited a high H2O2 production rate, which even slightly outperformed the state-of-the-art noble-metal-based electrocatalysts. The kinetic current of H2O2 production over Co SAC could reach 1 mA/cm(disk)(2) at 0.6 V versus reversible hydrogen electrode in 0.1 M HClO4 with H2O2 faraday efficiency > 90%, and these performance measures could be sustained for 10 h without decay. Further kinetic analysis and operando X-ray absorption study combined with density functional theory (DFT) calculation demonstrated that the nitrogen-coordinated single Co atom was the active site and the reaction was rate-limited by the first electron transfer step.", + "Times Cited, WoS Core": 534, + "Times Cited, All Databases": 562, + "Publication Year": 2020, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000519997200011", + "Markdown": "# Article Enabling Direct H O Production in Acidic Media through Rational Design of Transition Metal Single Atom Catalyst \n\n![](images/526c527198eb18576f8e29c458ab8917862fa81d0a109bbdd2ff0fb223f5b0c6.jpg) \n\nJiajian Gao, Hong bin Yang, Xiang Huang, ..., Yanqiang Huang, Tao Zhang, Bin Liu \n\nyqhuang@dicp.ac.cn (Y.H.) liubin@ntu.edu.sg (B.L.) \n\n# HIGHLIGHTS \n\nSingle-atom catalysts (SACs) for $H_{2}O_{2}$ production were theoretically designed \n\nCobalt SAC exhibited the highest activity and selectivity for $H_{2}O_{2}$ production \n\nIn situ XAS tracked the dynamic process of the $C o N_{4}$ active sites \n\nKinetic analysis identified the ratedetermining step of the reaction \n\nBy combining theoretical and experimental methods, Gao et al. systematically studied the relationship between the structure of transition metal (Mn, Fe, Co, Ni, and Cu) single-atom catalyst anchored in nitrogen-doped graphene and the catalytic performance of hydrogen peroxide $(\\mathsf{H}_{2}\\mathsf{O}_{2})$ synthesis via electrochemical two-electron oxygen reduction reaction (ORR) $(2e^{-}\\mathsf{O R R})$ . The thus designed Co single-atom catalyst can function as a highly active and selective catalyst for $H_{2}O_{2}$ synthesis and even slightly outperforms state-of-the-art noble-metal-based electrocatalysts in acidic media. \n\nGao et al., Chem 6, 1–17 \nMarch 12, 2020 $\\circledcirc$ 2019 Published by Elsevier Inc. \nhttps://doi.org/10.1016/j.chempr.2019.12.008 \n\n# Article Enabling Direct H O Production in Acidic Media through Rational Design of Transition Metal Single Atom Catalyst \n\nJiajian Gao,1,6 Hong bin Yang,2,6 Xiang Huang,3,6 Sung-Fu Hung,4 Weizheng Cai,1 Chunmiao Jia,1 Shu Miao,5 Hao Ming Chen,4 Xiaofeng Yang,5 Yanqiang Huang,5,\\* Tao Zhang,5 and Bin Liu1,7,\\* \n\n# SUMMARY \n\nThe electrochemical oxygen reduction reaction in acidic media offers an attractive route for direct hydrogen peroxide $(H_{2}O_{2})$ generation and on-site applications. Unfortunately there is still a lack of cost-effective electrocatalysts with high catalytic performance. Here, we theoretically designed and experimentally demonstrated that a cobalt single-atom catalyst (Co SAC) anchored in nitrogendoped graphene, with optimized adsorption energy of the $\\star_{\\mathsf{O O H}}$ intermediate, exhibited a high $H_{2}O_{2}$ production rate, which even slightly outperformed the state-of-the-art noble-metal-based electrocatalysts. The kinetic current of $H_{2}O_{2}$ production over Co SAC could reach $1\\mathsf{m A}/\\mathsf{c m}_{\\mathsf{d i s k}}^{2}$ at $0.6\\mathsf{V}$ versus reversible hydrogen electrode in 0.1 M ${\\mathsf{H C l O}}_{4}$ with ${\\sf H}_{2}{\\sf O}_{2}$ faraday efficiency $>90\\%.$ , and these performance measures could be sustained for $10\\ h$ without decay. Further kinetic analysis and operando X-ray absorption study combined with density functional theory (DFT) calculation demonstrated that the nitrogen-coordinated single Co atom was the active site and the reaction was rate-limited by the first electron transfer step. \n\n# INTRODUCTION \n\nAs one of the 100 most important chemicals in the world, hydrogen peroxide $(H_{2}O_{2})$ is a valuable and environmentally friendly oxidizing agent with a wide range of applications, ranging from the provision of clean water to the synthesis of valuable chemicals as well as being a potential energy carrier.1–3 The current industrial synthesis of $H_{2}O_{2}$ involves an energy-intensive anthraquinone oxidation-reduction step, which requires elaborate and large-scale equipment and at the same time generates substantial waste.3,4 An attractive alternative route for direct on-site production of ${\\sf H}_{2}{\\sf O}_{2}$ is through an electrochemical process in a fuel cell setup (anode: $\\mathsf{H}_{2}\\to2\\mathsf{e}^{-}+2\\mathsf{H}^{+}$ ; cathode: $\\mathrm{O}_{2}+2\\mathrm{e}^{-}+2\\mathsf{H}^{+}\\to\\mathsf{H}_{2}\\mathrm{O}_{2},E^{0}=0.695\\mathsf{V})$ , where the oxygen reduction reaction (ORR) occurs via a two-electron pathway. Substantial efforts devoted in recent years to this fuel cell concept have aimed at efficiently generating electricity with a simultaneous high-yield production of ${\\sf H}_{2}{\\sf O}_{2}$ in basic media.5–8 Indeed, recent results have suggested negligible room for further improvements in the activity and selectivity of carbon-based materials for ${\\sf H}_{2}{\\sf O}_{2}$ synthesis in basic media.3,6,7,9,10 Unfortunately, the production of $H_{2}O_{2}$ in basic media has several drawbacks: (1) $H_{2}O_{2}$ is less stable and can self-decompose in bases (especially at $\\mathsf{p H}>9)^{11}$ ; (2) there is no commercially competitive anion exchange membrane with comparable stability and conductivity to that of the proton exchange membrane (PEM) for device development3; and (3) ${\\sf H}_{2}{\\sf O}_{2}$ is more widely used in acidic media with stronger oxidation ability than in basic media. For example, Fenton’s reagent, which is mostly applied in \n\n# The Bigger Picture \n\nHydrogen peroxide is a valuable chemical with extensive applications, but the current industrial production method is energy-intensive and generates substantial waste. The electrochemical oxygen reduction reaction in acidic media offers an attractive route for direct hydrogen peroxide generation and on-site applications. Unfortunately, there is still a lack of cost-effective electrocatalysts with high catalytic performance. Here, by combining theoretical calculations and experimental methods, we demonstrate that an atomically dispersed cobalt anchored in nitrogen-doped carbon can function as a highly active and selective electrocatalyst for direct hydrogen peroxide synthesis. This cobalt single-atom catalyst combines the advantages of both homogeneous catalysts of cobalt macrocycles (well-defined active sites) and heterogeneous metalnitrogen-carbon catalysts (high catalytic performance) together, showing promising application in electrosynthesis device. \n\norganic synthesis and effluent treatment, has an optimal pH range of 2.5–3.5.12 Therefore, there is a great industrial motivation to improve ${\\sf H}_{2}{\\sf O}_{2}$ catalysis in acidic media, more specifically using PEM-type apparatus.3,13–15 Previously, mercury-alloyed platinum or palladium16,17 nanoparticles supported on carbon, as state-ofthe-art catalysts, have been investigated for ${\\sf H}_{2}{\\sf O}_{2}$ synthesis via ORR in acidic media. However, these catalysts contain precious noble metals and toxic mercury, thus limiting their potential applications in ${\\sf H}_{2}{\\sf O}_{2}$ production. Although homogeneous molecular catalysts such as cobalt macrocycles are highly selective for $H_{2}O_{2}$ production via ORR,18 the low activity and poor stability hinder their possible applications. Transition metals such as cobalt particles19 or manganese species20 loaded on nitrogenated carbon materials can also be used to produce ${\\sf H}_{2}{\\sf O}_{2}$ but lack high activity. Meanwhile, the non-uniform structure in these catalysts hinders their identification of active sites, mechanistic study, and further rational optimization. In short, there is still a lack of cost-effective electrocatalysts with high catalytic performance for $H_{2}O_{2}$ synthesis in acidic media. In recent years, single-atom catalysts (SACs) with well-defined active centers have drawn great attention for their particularly high activity and selectivity in various chemical reactions.21–23 In principle, to increase the selectivity of ${\\sf H}_{2}{\\sf O}_{2}$ production through ORR, O–O bond breaking needs to be minimized. Benefiting from the desirable features of SACs, in which the active sites are atomically isolated, the adsorption of $\\mathsf{O}_{2}$ on SACs is usually of the end-on type, rather than $\\upmu$ -peroxo coordination, which therefore could reduce the possibility of $0{\\cdot}0$ bond splitting.18,24,25 This implies that SACs would be suitable for ${\\sf H}_{2}{\\sf O}_{2}$ generation via ORR. Previous studies of metal-nitrogen-carbon materials mainly focus on the electrocatalytic activity toward four-electron ORR to $H_{2}O$ for fuel cells applications,26–30 whereas unfavorable two-electron ORR to ${\\sf H}_{2}{\\sf O}_{2}$ is rarely studied in detail. Although there are few studies of their electrocatalytic activities toward two-electron ORR for ${\\sf H}_{2}{\\sf O}_{2}$ production,19,20 the fundamental aspects such as active center and reaction mechanism as well as practical electrolytic cell device aspects remain poorly understood. Here, by combining theoretical and experimental methods, the relation between the structure of transition metal (Mn, Fe, Co, Ni, and $\\mathsf{C u}$ ) SACs anchored in nitrogen-doped graphene and the catalytic performance of ${\\sf H}_{2}{\\sf O}_{2}$ synthesis via ORR was systematically studied. Both theoretically predicted activity-volcano relation and experimental results show that the Co SAC possesses optimal d-band center and can function as a highly active and selective catalyst for ${\\sf H}_{2}{\\sf O}_{2}$ synthesis via ORR and even slightly outperforms state-of-the-art noble-metal-based electrocatalysts in acidic media. \n\n# RESULTS AND DISCUSSION \n\nInspired by previous work,16 we first investigated the ORR process on various transition metal SACs anchored in nitrogen-doped graphene for producing ${\\sf H}_{2}{\\sf O}_{2}$ or $H_{2}O$ along a $2\\:e^{-}$ or $4\\:\\mathrm{e}^{-}$ pathway, respectively, by DFT calculations using a computational hydrogen electrode model (details are given in Experimental Procedures). The two-electron $(2~\\mathsf{e}^{-})$ pathway to ${\\sf H}_{2}{\\sf O}_{2}$ via ORR comprises two proton-coupled electron transfer steps with only one intermediate $(^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H})$ : \n\n$$\n\\ast+\\mathsf{O}_{2}+\\mathsf{H}^{+}+\\mathsf{e}^{-}\\to\\ast\\mathsf{O O H}\n$$ \n\n(Equation 1) \n\n$$\n\\mathrm{*OOH}+\\mathsf{H}^{+}+\\mathsf{e}^{-}\\to\\mathsf{H}_{2}\\mathsf{O}_{2}+\\ast\n$$ \n\n(Equation 2) \n\nwhere the asterisk $(^{\\star})$ denotes the active site of the catalyst. In contrast, for the $4\\:\\mathrm{e}^{-}$ ORR pathway, four proton-coupled electron transfer steps are included, in which $\\mathrm{O}_{2}$ is reduced to $\\star_{\\mathsf{O O H},\\star_{\\mathsf{O},\\star_{\\mathsf{O H},}}}$ , and $H_{2}O$ in sequence, as displayed in Figure 1A. Theoretically, an ideal catalyst for ${\\sf H}_{2}{\\sf O}_{2}$ synthesis should minimize the kinetic \n\n# Chem \n\n![](images/ea86b73105e31daa7961d9aaf10cf0e9ec69872506f185c95efc57494414907e.jpg) \nFigure 1. DFT Calculations \n\n(A) Schematic of ORR along the $2\\ e^{-}$ or $4\\:\\mathrm{e}^{-}$ pathway on transition metal SACs $\\langle{\\mathsf{M}}={\\mathsf{M}}{\\mathsf{n}}$ , Fe, Co, ${\\mathsf{N i}},$ and $\\mathsf{C u}$ ) anchored in N-doped graphene. (B) Binding energy of $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ , $^{\\star}\\mathrm{O},$ and $^{\\star}\\mathsf{O}\\mathsf{H}$ on M-SAC ${\\bf\\cal M}={\\sf M}{\\sf n}.$ , Fe, Co, ${\\mathsf{N i}}$ , and Cu) and d-bond center (open circle) of M atom in M-SAC ${\\mathrm{(}}M=M{\\mathrm{n}}$ , Fe, Co, Ni, and Cu). \n(C) Activity-volcano curves of ORR via the $2\\ e^{-}$ or $4\\:e^{-}$ pathway. The limiting potential is plotted as a function of $\\Delta G_{\\mathrm{\\star_{OH}}}$ . The gradual change in color indicates the catalyst window for producing $H_{2}O_{2}$ . \n(D) Free energy diagrams of $2\\ e^{-}$ ORR on the SACs at $\\mathsf{U}=0.7$ V versus RHE. \n\nbarriers for Equations 1 and 2 to provide high activity. Meanwhile, the catalyst needs to maximize the barrier for $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ dissociation or reduction to $^{\\star}\\mathrm{O}$ and $^{\\star}\\mathrm{OH}$ (the intermediates of the $4~{\\mathfrak{e}}^{-}$ ORR pathway to $H_{2}O)$ to achieve high selectivity.16 Here, density functional theory (DFT) calculations revealed that $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ , $^{\\star}\\mathrm{O},$ and $^{\\star}\\mathrm{OH}$ were all energetically favored to adsorb on the top site of the metal (M) atom (the most stable configurations are shown in Figure S2). Therefore, the activity of ORR is mainly dependent on the electronic interaction of the intermediates with the M atom rather than the geometrical effects. Figure 1B shows that the binding energies of ${\\star}_{\\mathsf{O O H},\\mathsf{\\star}_{\\mathsf{O}}},$ and $^{\\star}\\mathrm{OH}$ are generally scaled with the number of valence electrons in the M atom from manganese to copper. The larger the number of valence electrons in M, the weaker the binding of these intermediates to the M atom, which is because the d-band center of M atom shifts down in energy relative to the Fermi level from Mn to Cu (Figure 1B).31 In detail, the anti-bonding states derived from the coupling between d-orbitals of M atom and $2{\\mathsf{p}}$ -orbitals of bonded O atom of intermediates are shifted down in energy and thus are more filled, which weakens the M–O bonding from Mn to Cu. Then, to compare the ORR activities of these SACs, we calculated the free energy diagrams (Figure S3) and constructed the activity-volcano plots for both the $2e^{-}$ and $4e^{-}$ pathways by using $\\Delta G_{\\mathrm{\\star_{OH}}}$ as a descriptor, as shown in Figure 1C. For an ideal $2\\:\\mathsf{e}^{-}$ ORR catalyst, the adsorption of $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ should be thermoneutral at the equilibrium potential $\\ensuremath{\\left(\\mathsf{U}\\right)}=0.7\\:\\forall$ versus reversible hydrogen electrode [RHE]), corresponding to $\\Delta\\mathsf{G}_{\\star\\mathrm{OOH}}=\\sim3.5\\ \\pm\\ 0.2\\ \\mathsf{e V}.$ 16 However, in striking contrast to the $2\\:\\mathsf{e}^{-}$ ORR, even for the optimal catalyst, an overpotential of ${\\sim}0.4\\lor$ was required to drive the $4e^{-}$ reduction of $\\mathrm{O}_{2}$ to $H_{2}O$ , because of the scaling relation between $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ and $^{\\star}\\mathrm{OH}$ (Figure S3F), i.e., $\\Delta\\mathsf{G}_{\\star_{\\mathsf{O O H}}}=0.747\\ \\Delta\\mathsf{G}_{\\star_{\\mathsf{O H}}}+3.32\\ \\mathrm{eV},$ , and similar results have also been found in other models.32–34 From Figure 1C, it can be seen that the ORR on the Ni and $\\mathsf{C u}$ SACs prefers the $2\\:\\mathrm{e}^{-}$ pathway but with a large overpotential because of the large $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ reduction barrier (Figures S3D and S3E) and high $\\mathrm{O}_{2}$ activation energy (Figure 1D), implying that these two catalysts would exhibit low activity but high selectivity for $H_{2}O_{2}$ production. \n\nBy contrast, the binding of $\\mathrm{O}_{2}$ on the Mn and Fe SACs is so strong (Figure 1D) that it becomes more downhill in free energy for $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ reduction to $^{\\star}\\mathrm{O}$ (Figures S3A and S3B). Therefore, the $4\\:\\mathrm{e}^{-}$ pathway dominates over the $2\\:\\mathfrak{e}^{-}$ pathway on the Mn and Fe SACs, thus causing much lower selectivity for ${\\sf H}_{2}{\\sf O}_{2}$ . In addition, the Fe SAC should possess the highest ORR activity via the $\\textit{4}\\boldsymbol{\\mathrm{e}}^{-}$ pathway among the five SACs because of its optimized adsorption energy of oxygenated intermediates (Figures 1B and 1C). Considering the relatively stronger binding energies of Fe and Mn SACs toward ORR species, it is possible that the backside of these two catalysts are covered by ${}^{\\star}\\mathsf{O}\\mathsf{H}\\mathsf{o r}^{\\star}\\mathsf{O}$ . Supplemental calculation results show that the backsides are possibly covered by $^{\\star}\\mathrm{OH}$ under ORR working potentials (Figure S4). However, this does not obviously change the $\\textit{4e}^{-}$ ORR activity (Figure S5), but instead could slightly enhance the $2\\mathsf{e}^{-}$ ORR activity (Figure S6) for ${\\sf H}_{2}{\\sf O}_{2}$ production. Significantly, the Co SAC with optimal d-band center shows $\\Delta G^{\\star}\\mathsf{\\Gamma}_{\\mathrm{OOH}}=3.54\\mathrm{eV}$ at $\\mathsf{U}=0.7\\:\\backslash$ versus RHE (Figure 1D) for the $2\\:\\mathfrak{e}^{-}$ pathway, neither too strong nor too weak, being positioned nearly at the vertex of the activity-volcano map (Figure 1C), suggesting that the Co SAC would be highly active for the $2\\:e^{-}$ pathway. In addition, the higher barrier for $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ reduction to the $^{\\star}\\mathrm{O}$ intermediate on the Co SAC (Figure S3C) compared with those on the Mn and Fe SACs (Figures S3A and S3B) would enhance the selectivity of the Co SAC to $H_{2}O_{2}$ . Combined with the predicted high activity, it can be anticipated that the yield of ${\\sf H}_{2}{\\sf O}_{2}$ on the Co SAC would be the highest among the five SACs. \n\nSubsequently, we synthesized five different transition metal SACs anchored in nitrogen-doped carbon (NC) (Mn–NC, Fe–NC, Co–NC, Ni–NC, and Cu–NC) via pyrolysis of melamine, L-alanine, and the corresponding metal acetate mixture (details are given in Experimental Procedures). NC was also prepared by the same method without adding a metal salt for comparison. This synthesis method can be easily scaled up and Figure S8 shows a digital photograph of the SACs obtained by batch synthesis. Figures 2A and S9 show representative scanning electron microscopy (SEM) images of the as-synthesized SACs (Figures 2A and S9 for Co–NC, and Figures S9B–S9F for the rest), which display aggregated two-dimensional (2D) platelets. No obvious Co particles can be observed in the transmission electron microscopy (TEM) images of Co–NC (Figures 2B and S10A), similar to the absence of the corresponding metal particles in the other SACs (Figures S10B–S10F), suggesting that the metal species are highly dispersed in the carbon matrix. The Brunauer-Emmett-Teller (BET) surface areas of the six samples (Mn–NC, Fe–NC, Co–NC, Ni–NC, Cu–NC, and NC) obtained from ${\\sf N}_{2}$ adsorption isotherms (Figure S11A) are in the range of 360– $670~\\mathsf{m}^{2}/\\mathsf{g}$ with total pore volumes of $1.5{-}2.2~\\mathsf{c m}^{3}/\\mathsf{g}$ (Table S4). All samples have \n\n# Chem \n\n![](images/fb143a06ebcc53e60a1e84257837e51de16e49fdd06e55a907631e72cbbefb49.jpg) \nFigure 2. Characterization of the Single Atom Catalysts \n(A) SEM image of ${\\mathsf{C o}}{\\mathsf{-N C}};$ scale bar, $1~\\upmu\\mathrm{m}$ . (B) TEM image of ${\\mathsf{C o}}{\\mathsf{-N C}};$ scale bar, $50~\\mathsf{n m}$ . (C) HAADF-STEM image of ${\\mathsf{C o}}{\\mathsf{-N C}};$ scale bar, $2{\\mathsf{n m}}$ . (D–F) XRD patterns (D) Raman spectra (E) and Fourier transformation of the EXAFS spectra (F) of the synthesized catalysts. \n\nsimilar pore size distribution. The pore sizes show a wide distribution from several to a few tens of nanometers (Figure S11B), and the pores themselves are mainly formed from the folds or holes in the carbon matrix. The atomic-scale dispersion of the metals was confirmed by aberration-corrected high-angle annular dark field scanning TEM (HAADF-STEM). The bright spots with diameter of ${\\sim}0.2\\ \\mathsf{n m}$ in Figure 2C are atomically dispersed Co species in Co–NC. Very similar HAADF-STEM images of the other transition metal catalysts are displayed in Figure S12. The X-ray diffraction (XRD) patterns (Figure 2D) show that all five of the transition metal SACs, together with NC, exhibit a single, similar, broad characteristic diffraction peak of the carbon (002) at $25.8^{\\circ}$ , suggesting a low degree of crystallization. No other diffraction peaks of metal, metal nitride, or metal oxide are discernible, agreeing well with the TEM and HAADF-STEM results. The Raman spectra (Figure 2E) of the six samples also show very similar patterns with two vibrational bands: the d-band at $1,350~{\\mathsf{c m}}^{-1}$ is the characteristic peak of vacancies or defects in graphene35,36 and the G band at $1,580~{\\mathsf{c m}}^{-1}$ is the characteristic peak of graphitic layers, which corresponds to the in-plane vibration of $\\mathsf{s p}^{2}$ chains associated with the $\\mathsf{E}_{2\\mathsf{g}}$ symmetry.35,37 The relative intensities of D to G band for the six catalysts are nearly identical, suggesting that they have similarly disordered or defective carbon structures. To further examine the structure of the catalysts, we measured extended $\\mathsf{X}$ -ray absorption fine structure (EXAFS) spectra. Figure 2F shows the Fourier transformation (FT) of the EXAFS spectra of five transition metal catalysts, exhibit only one strong peak at an interatomic distance of ${\\sim}1.3\\mathrm{~\\AA~}$ (without phase correction, the same below), which is typical for metal-N bonds.26,38,39 In addition, the EXAFS spectra of some commercial metal phthalocyanines (M-PC, ${\\mathsf{M}}{=}{\\mathsf{F e}}$ , Co, Ni, and Cu) were measured and Fourier transformation of the EXAFS spectra are shown in Figure S13A for reference. All of them show quite similar peaks at interatomic distances of ${\\sim}1.3-$ $1.5\\mathring{\\mathsf{A}},$ suggesting that the transition metals are mainly coordinated with nitrogen, as was the case in the synthesized SACs. No strong metal-metal bonds (which have interatomic distances of ${\\sim}2.1\\ \\mathring{\\mathsf{A}}$ in metal foils as shown in Figure S13B) can be observed in Figure 1F, moreover, the EXAFS data can be fitted well with the model proposed in above DFT calculation section (Figure S14 and Table S5), further proving that the metal species are mainly atomically dispersed, consistent with the HAADF-STEM results (Figures 2C and S12). In addition, the valence states of the metals in the catalysts were also examined through measurement of their K-edge X-ray absorption near-edge structure (XANES) spectra and comparison with those of metallic foils and metal phthalocyanines (Figure S15). Comparison of the first derivative XANES for M–NC catalysts with references indicates that the metals in M–NC are all in positive oxidation states.39 The composition of the catalysts was analyzed by X-ray photoelectron spectroscopy (XPS) (Figure S16). The carbon, nitrogen, and oxygen contents of all the catalysts display very similar spectra and valance states, and the estimated atomic percentages of N in the transition metal SACs are ${\\sim}6{-}7$ atom $\\%$ (Table S6), which are higher than that in metal-free NC (3.5 atom $\\%$ ). Moreover, the much-enhanced relative intensities of N species coordinated with metal $(\\sim398.8~\\mathrm{eV})$ ) in M–NC compared with bare NC (Figure S17), suggesting that the transition metal and N can stabilize each other in carbon materials by formation of M–N bonds. The metal contents in the catalysts determined by inductively coupled plasma-atomic emission spectroscopy (ICP-AES) are in the range of $1.0\\substack{-1.6}$ wt $\\%$ (Table S6). By comparison with the typical binding energies of metallic and oxidic states of the corresponding elements (Figure S18 and Table S7), it is deduced that all five metals in the catalysts show positive valance states, agreeing with the XANES spectra (Figure S15) and previous reports.38,39 \n\nTo examine the catalytic performance, we conducted electrochemical ORR tests in 0.1 M ${\\mathsf{H C l O}}_{4}$ on a rotating ring disk electrode (RRDE) at room temperature $(24\\pm1^{\\circ}\\mathsf C)$ . Figure S19 shows the cyclic voltammetry (CV) curves of the six catalysts acquired in $O_{2}$ -saturated and ${\\sf N}_{2}$ -saturated 0.1 M ${\\mathsf{H C l O}}_{4}$ . All the catalysts exhibit similar curves in ${\\sf N}_{2}$ atmosphere, suggesting their comparable double layer capacitances. Under $\\O_{2}$ atmosphere, the reduction peak of oxygen occurs at $0.1{-}0.2\\ V$ versus RHE for Mn–NC, Ni–NC, ${\\mathsf{C u\\mathrm{-}N C}},$ , and NC, whereas Fe–NC and Co–NC display reduction peaks of $\\mathsf{O}_{2}$ at higher potentials ${\\mathrm{\\Omega}}_{:\\sim0.45\\ \\vee}$ versus RHE). Subsequently, we conducted linear sweep voltammetry (LSV) measurements on the RRDE and the results are shown in Figure 3A. As expected, Co–NC and Fe–NC show much higher activity for ORR and had onset potentials at around $0.7\\:\\forall$ versus RHE. The ring current of Co–NC, which corresponds to the oxidation of ${\\sf H}_{2}{\\sf O}_{2}$ also starts at around $0.7~\\mathrm{V}$ and the calculated faraday efficiency for ${\\sf H}_{2}{\\sf O}_{2}$ (Figure 3B) shows that ${C o\\mathrm{-}N C}$ is highly selective for $H_{2}O_{2}$ production in the entire potential range of $0{-}0.7~\\mathsf{V}$ versus RHE. The kinetic current of $H_{2}O_{2}$ production over ${C o\\mathrm{-}N C}$ reached $1\\ m\\mathsf{A}/\\mathsf{c m}_{\\mathsf{d i s k}}^{2}$ (corresponding to a mass-normalized current density of 40 $\\mathsf{A}/\\mathsf{g}_{\\mathsf{c a t a l y s t}}.)$ at $0.6\\mathrm{~V~}$ versus RHE with ${\\sf H}_{2}{\\sf O}_{2}$ faraday efficiency $>90\\%$ . In contrast, Fe–NC shows a much lower selectivity for ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2},$ consistent with the above DFT predictions and previous reports.27,28,40 Although the other catalysts, Mn–NC, Ni–NC, ${\\mathsf{C u\\mathrm{-}N C}}.$ and NC, are also highly selective for ${\\sf H}_{2}{\\sf O}_{2}$ (Figure 3B), their catalytic activities are much poorer. The electron transfer number is calculated according to reported method19 and shown in Figure S20A. The number over ${C o\\mathrm{-}N C}$ is close to 2, agreeing with its selectivity for ${\\sf H}_{2}{\\sf O}_{2}$ . The turnover frequency (TOF) values of the catalysts for ${\\sf H}_{2}{\\sf O}_{2}$ production at different potentials were calculated \n\n![](images/879cc65d0c22824ae12462ee14cce28c1021698edbeaebef1edef6a0d2ff49b0.jpg) \nFigure 3. ORR Performances \n\n(A) LSV curves of the catalysts in $\\mathrm{O}_{2}$ -saturated $0.1\\ \\mathsf{M}\\ \\mathsf{H C l O}_{4}$ . \n(B) Faradic efficiency of $H_{2}O_{2}$ production as a function of potential. \n(C) Benchmarking of Co–NC for $H_{2}O_{2}$ synthesis: Tafel plots of mass-transport corrected current densities for $H_{2}O_{2}$ production in acidic media (solid line) and alkaline media (dash line). Detailed cited references can be found in Table S8 in the Supplemental Information. \n(D) Stability tests of $C o{\\mathrm{-}}N C$ at potential of $0.5{\\:\\vee}$ versus RHE in $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{\\mid\\mitMHClO_{4}}$ . \n\n(Figure S20B) and the highest TOF value of $2.5\\mathsf{s}^{-1}$ was obtained for ${C o\\mathrm{-}N C}$ at a potential of $0.5\\mathrm{V}$ versus RHE. The above experimental results are consistent with our DFT calculations (Figure 1), which show that $C o{\\mathrm{-}}N C$ is at the top of the activity-volcano map for ${\\sf H}_{2}{\\sf O}_{2}$ production reaction. In addition, we further examined the electrochemical characteristics of the transition metal SACs in ${\\sf N}_{2}$ -saturated $0.1\\mathsf{M H C l O}_{4}$ containing 0.1 M ${\\sf H}_{2}{\\sf O}_{2}$ to monitor their catalytic activity for ${\\sf H}_{2}{\\sf O}_{2}$ oxidation $({\\mathsf{H}}_{2}{\\mathsf{O}}_{2}\\to$ $\\mathsf{O}_{2}+2\\mathsf{H}^{+}+2\\mathsf{e}^{-}$ , $\\mathsf{E}^{0}=0.695\\ \\mathsf{V})$ and reduction $(\\mathsf{H}_{2}\\mathsf{O}_{2}+2\\mathsf{H}^{+}+2\\mathsf{e}^{-}\\to2\\mathsf{H}_{2}\\mathsf{O},$ $\\mathsf{E}^{0}=$ $1.763\\:\\forall)$ , which are closely related to their selectivities for ${\\sf H}_{2}{\\sf O}_{2}$ . It can be observed from the LSV curves (Figure S21) that the oxidation of ${\\sf H}_{2}{\\sf O}_{2}$ over ${C o\\mathrm{-}N C}$ starts at $0.75\\mathrm{\\:V}$ versus RHE, very close to the onset potential $(0.7\\vee$ versus RHE, Figure 3A) of its reverse reaction, namely reduction of $\\mathsf{O}_{2}$ to ${\\sf H}_{2}{\\sf O}_{2}$ $(\\mathsf{O}_{2}+2\\mathsf{H}^{+}+2\\mathsf{e}^{-}\\to\\mathsf{H}_{2}\\mathsf{O}_{2},$ $\\mathsf E^{0}=0.695\\:\\forall)$ . Therefore, the reduction of $\\mathrm{O}_{2}$ to ${\\sf H}_{2}{\\sf O}_{2}$ over ${C o\\mathrm{-}N C}$ is nearly reversible, and this is consistent with the high activity of ${C o\\mathrm{-}N C}$ for $\\mathrm{O}_{2}$ reduction to ${\\sf H}_{2}{\\sf O}_{2}$ and our DFT calculations. Figure S21 further shows that Fe–NC can efficiently reduce ${\\sf H}_{2}{\\sf O}_{2}$ to ${\\mathsf{H}}_{2}{\\mathsf{O}},$ thus leading to its much lower selectivity for $H_{2}O_{2}$ production (Figure 3B). Moreover, as deduced from the DFT calculation, Mn–NC should also possess low selectivity for $H_{2}O_{2}$ , because of its strong adsorption of oxygen intermediates. However, Mn–NC in fact shows relatively high selectivity for $H_{2}O_{2}$ , close to that of NC in the ORR (Figure 3B), possibly because the adsorption of oxygenated species is so strong that it blocks the Mn active sites, making Mn–NC behave similarly to bare NC. Meanwhile, $C u\\mathrm{-}N C$ and Ni–NC are less active for ${\\sf H}_{2}{\\sf O}_{2}$ reduction and oxidation because of their too weak adsorption of oxygenated intermediates. Figures 3C and S22 (mass-normalized activity) compares the performances of state-of-the-art catalysts for ${\\sf H}_{2}{\\sf O}_{2}$ production through ORR. It can be seen that ${C o\\mathrm{-}N C}$ is the most effective catalyst for ${\\sf H}_{2}{\\sf O}_{2}$ synthesis (Table S8), which even slightly outperforms the best previously reported catalyst in acidic media, a Pd-Hg alloy. The effect of the catalyst loading amount on the ORR performance for Co– NC and other SACs was further optimized (Figure S23). Reducing the loading of Co–NC slightly improves the selectivity for ${\\sf H}_{2}{\\sf O}_{2}$ . As shown in Figure S21, ${\\sf H}_{2}{\\sf O}_{2}$ as an intermediate can be further reduced to $H_{2}O$ over $C o{\\mathrm{-}}N C$ . Thus, decreasing the catalyst loading amount reduces the residence time of ${\\sf H}_{2}{\\sf O}_{2}$ on the catalyst surface, so that less $H_{2}O_{2}$ is reduced to $H_{2}O$ , therefore increasing the ${\\sf H}_{2}{\\sf O}_{2}$ selectivity. The rotating speed of the RRDE was found to have little influence on the selectivity for ${\\sf H}_{2}{\\sf O}_{2}$ (Figure S24). Additionally, NC loaded with Co nanoparticles $(\\mathsf{C o}_{\\mathsf{N P s}}/\\mathsf{N C})$ was also prepared for comparison (Figure S25), but its ORR activity was much lower than ${C o\\mathrm{-}N C}$ (Figure S26). Considering that cobalt porphyrins and phthalocyanines are known for their high selectivities for ${\\sf H}_{2}{\\sf O}_{2}$ generation by ORR despite their rapidly decaying activities in acidic conditions,18,27,41 we prepared tetra-amino-cobalt(II) phthalocyanine (Co-TAPC) loaded on carbon nanotubes (Co-TAPC/commercial carbon nanotubes [CNT]) and tested its ORR performance (Figure S27). However, although the $H_{2}O_{2}$ selectivity of Co-TAPC/CNT was high, the activity was much lower than Co–NC. The catalytic ORR performances of all six catalysts together with CNT were also tested in alkaline conditions $(0.1\\mathsf{M}\\mathsf{K}\\mathsf{O}\\mathsf{H})$ ). All of the catalysts exhibited higher activity for ORR in alkaline conditions (Figure S28) than in acidic media and had markedly increased current density at the same potential versus RHE. Among the studied catalysts, NC, CNT, and even blank glassy carbon electrode (GCE) exhibited high selectivity for ${\\sf H}_{2}{\\sf O}_{2}$ production in alkaline media (Figures S28B and S28D). However, these carbon-based materials show very poor ORR performance in acidic conditions, as shown in Figures 3A and S26. This trend is consistent with previous reports,5–7,10 and might be attributed to the different affinity of protons and hydroxyls toward the various functional groups present on the surface of the catalysts at different pH.42 \n\n
Pleasecitethtialabliectcididighasgnfinge Atom Catalyst, Chem (2019),https://doi.org/10.1016/j.chempr.2019.12.008
\n\nBesides activity, stability is another important consideration for a catalyst in practical use. The stability of Co–NC was studied at $0.5\\mathsf{V}$ versus RHE in $0.1\\mathsf{M H C l O}_{4}$ both under static and rotating conditions. The currents of both the ring and the disk electrode remained stable for $10\\mathfrak{h}$ without obvious decay (Figure 3D); the slightly increased current of the ring electrode can be attributed to the gradually accumulated ${\\sf H}_{2}{\\sf O}_{2}$ in the electrolyte. The selectivity for ${\\sf H}_{2}{\\sf O}_{2}$ determined by titration method (details are given in Experimental Procedures) remained as high as ${\\sim}88\\%$ throughout the entire process. Figure S31 compares the LSV curves of ${C o\\mathrm{-}N C}$ before and after the stability test. A change can be observed in the kinetic range, which might stem from partial detachment of the catalyst from the electrode or some deactivation occurred. The stability of Co–NC was further confirmed by CV cycling for 5,000 cycles (Figure S32). Half-cell experiment at fixed potential of 0.5 and $0.4\\mathsf{V}$ versus RHE chronoamperometry test was further conducted to imitate real case ${\\sf H}_{2}{\\sf O}_{2}$ production. An average $H_{2}O_{2}$ production rate of 80 and $275\\mathsf{m m o l}_{\\mathsf{H}_{2}\\mathsf{O}_{2}\\mathsf{g}}$ c\u0001a1talyst $\\mathfrak{h}^{-1}$ is obtained at $0.5\\mathsf{V}$ and $0.4\\mathsf{V}$ versus RHE, respectively (Figure S33). \n\nThe HAADF-STEM images of the used catalysts show that the Co species are still atomically dispersed (Figure S34), demonstrating the good catalytic stability of Co–NC in the $H_{2}O_{2}$ synthesis process. \n\nFrom the above-mentioned DFT calculations, we found that the first step $(^{\\star}+{\\mathsf{O}}_{2}+$ $\\mathsf{H}^{+}+\\mathsf{e}^{-}\\rightarrow{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H})$ was the thermodynamic potential-determining step for ORR on Co–NC. To shed more light on the reaction mechanism, we performed kinetic analysis to experimentally probe the rate-determining step. First, the kinetic current of \n\n![](images/49cbff21d471270fe551fd08898d12fec7e1e4279eed58dfc761db23ea563fb1.jpg) \nFigure 4. Reaction Mechanism Analysis \n\n(A) Kinetic current of ORR over Co–NC at different $\\mathrm{O}_{2}$ partial pressures in 0.1 M ${\\mathsf{H C l O}}_{4}$ $\\mathsf{p}\\mathsf{H}=1.53)$ . \n(B) Reaction orders of $\\mathrm{O}_{2}$ at different potentials in $0.1\\ \\mathsf{M}\\ \\mathsf{H C}\\mathsf{l O}_{4}$ . \n(C) Kinetic current of ORR over $C o{\\mathrm{-}}N C$ at different ${\\mathsf{p H}}$ and $\\mathsf{P}_{\\mathsf{O}2}=1$ atm. \n(D) Reaction orders of $\\mathsf{H}^{+}$ at different potentials and $\\mathsf{P}_{\\mathrm{O}2}=1$ atm. \n(E) Operando EXAFS spectra of $\\mathsf{C o\\mathrm{-}N C}$ collected during ${\\sf H}_{2}{\\sf O}_{2}$ synthesis process; $\"\\mathsf{O C P^{\\prime\\prime}}$ stands for open-circuit potential. \n(F) Proposed reaction steps of $H_{2}O_{2}$ synthesis over $C o\\mathrm{-}N C$ . \n\nORR on Co–NC was obtained by Koutecky–Levich analysis from the LSV curves acquired at different rotating speeds (Figures S35 and S36). The reaction order of $\\mathsf{O}_{2}$ was determined by performing ORR at different $\\mathsf{O}_{2}$ partial pressures. Figure 4A shows the kinetic current as a function of overpotential at different $\\mathrm{O}_{2}$ partial pressures. Then, the logarithm of the kinetic current versus the logarithm of the $\\mathsf{O}_{2}$ partial pressure was plotted as shown in Figure 4B, from which, we can deduce that the reaction order of $\\mathsf{O}_{2}$ (slope of the line) varied from 0.53 to 0.90 as the overpotential increased from 0 to $250\\mathsf{m V}$ . Simultaneously, the Tafel slope increased from $\\sim110\\ensuremath{\\mathrm{mV}}$ ${\\mathsf{d e c}}^{-1}$ to ${\\sim}140\\ m\\lor\\ d\\mathrm{ec}^{-1}$ , and finally to ${\\sim}240\\ m\\lor\\ d\\mathrm{ec}^{-1}$ as the overpotential increased from 0 to $250~\\mathrm{mV}$ (Figure 4A). Figures 4C and 4D show the effect of $\\mathsf{p H}$ $(\\mathsf{H}^{+}$ concentration) on the activity of ORR over Co–NC. By the same analysis as performed for Figures 4A and 4B, the reaction order of $\\mathsf{H}^{+}$ in the rate-determining step is $-0.05\\sim-0.07$ , very close to zero, as shown in Figure 4D. Thus, it is suggested that $\\mathsf{H}^{+}$ is not involved in the rate-limiting step, namely, the protonation process is fast. By combining Figures 4A–4D and Table S9, it is deduced that the rate-determining step of ${\\sf H}_{2}{\\sf O}_{2}$ synthesis over Co–NC is as follows: $\\star+\\mathsf{O}_{2}+\\mathsf{e}^{-}\\rightarrow\\star\\mathsf{O}_{2}{}^{-},$ which is covered in the DFT calculation predicted thermodynamic potential-determining step $(^{\\star}\\ +\\ \\mathsf{O}_{2}\\ +\\ \\mathsf{H}^{+}\\ +\\ \\mathsf{e}^{-}\\ \\to\\ {^{\\star}\\mathrm{OOH}})$ .43 In detail, at relatively low overpotential $(<50\\mathrm{\\mV})$ , it is mainly controlled by the electron transfer step of adsorbed $\\mathrm{O}_{2}$ . $({}^{\\star}\\mathsf{O}_{2}+\\mathsf{e}^{-}\\to{}^{\\star}\\mathsf{O}_{2}{}^{-})$ . The electron transfer step becomes faster by increasing the overpotential. Then the overall reaction rate is more limited by the $\\mathsf{O}_{2}$ adsorption process, which agrees well with the observed gradually increasing Tafel slope and reaction order of $\\mathrm{O}_{2}$ . To monitor the change of Co electronic state and coordination environment, operando X-ray absorption spectroscopy (XAS) was conducted to probe the change of the Co K-edge under ${\\sf H}_{2}{\\sf O}_{2}$ synthesis conditions in $0.1~\\mathsf{M}$ ${\\mathsf{H C l O}}_{4}$ . The EXAFS spectrum of the ${C o\\mathrm{-}}{\\mathsf{N C}}$ in air is nearly the same as that of Co– NC immersed in electrolyte saturated with ${\\sf N}_{2}$ , and the $C o-N$ distance is $1.25\\mathring{\\mathsf{A}}$ in both cases (Figure S37). After switching ${\\sf N}_{2}$ to $O_{2},$ , a dramatic enhancement of Fourier transformed intensity and slight increase of $C o\\mathrm{-N}$ distance to $1.35\\mathring{\\mathsf{A}}$ are observed (Figure S38), indicating the adsorption of $\\mathsf{O}_{2}$ onto Co atoms, which pulls the Co atoms out of plane. This result agrees with the DFT calculations, which show that oxygen species are energetically favored to adsorb on the top site of Co atoms. At the potential of $0.6\\mathsf{V}$ versus RHE, part of the adsorbed $\\mathsf{O}_{2}$ is transformed to ${\\sf H}_{2}{\\sf O}_{2}$ via ORR, and the $C o\\mathrm{-N}$ distance decreases to $1.32\\mathring{\\mathsf{A}}$ (Figure 4E). At lower potentials, the transformation of adsorbed $\\mathsf{O}_{2}$ to ${\\sf H}_{2}{\\sf O}_{2}$ via ORR becomes more rapid, and the surface coverage of $\\mathrm{O}_{2}$ becomes much lower because of the limited rate of $\\mathsf{O}_{2}$ adsorption, which explains the further decrease of the $C o-N$ distance to $1.29\\mathring{\\mathsf{A}}$ at $0.3\\mathrm{V}$ versus RHE. Additionally, the $C o-N$ bond distance recovers to its initial value $(1.35\\mathring{\\mathsf{A}})$ after the potential returns to that of open-circuit conditions and the EXAFS spectra in $\\boldsymbol{\\mathsf{k}}$ -space also show similar trend (Figure S37). The operando XANES of Co– NC were also collected (Figure S37). Comparison of the spectra in ${\\sf N}_{2^{-}}$ and $\\mathrm{O}_{2}$ - (Figure S38B) atmosphere shows an increase in intensity of XANES in $O_{2}$ , suggesting molecular $\\mathsf{O}_{2}$ adsorption on the cobalt centers in ${\\mathsf{C o-N C}},$ , which agrees with previous report.29 This trend matches very well with the kinetic analysis. Figure 4F displays a schematic illustration of the ORR steps taking place on ${C o\\mathrm{-}N C}$ for $H_{2}O_{2}$ production, in which step 2 is the rate-limiting process at higher potential whereas step 1 becomes rate-limiting at lower potential. After $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ is formed, further reduction to $H_{2}O_{2}$ is rapid, and the active sites are vacated by the desorption of $H_{2}O_{2}$ to complete the catalytic cycle. \n\nIn summary, DFT calculations predicted that a cobalt-based SACs anchored in a NC matrix would outperform other transition metal SACs for $H_{2}O_{2}$ production through ORR. Then, those transition metal SACs were successfully synthesized. Just as predicted by the DFT calculations, Co–NC experimentally behaved as a highly active and selective electrocatalyst for ${\\sf H}_{2}{\\sf O}_{2}$ synthesis via oxygen reduction in acidic media. A kinetic current density of $1\\mathsf{m A}/\\mathsf{c m}^{2}$ was reached on Co–NC at a potential of $0.6\\mathsf{V}$ versus RHE with ${\\sf H}_{2}{\\sf O}_{2}$ selectivity ${>}90\\%$ , and these performance measures could be sustained for $10\\mathsf{h}$ continuous operation without decay. The optimized adsorption energy of oxygenated intermediates on ${C o\\mathrm{-}}{\\mathsf{N C}}$ with optimal d-band center as compared with other transition metal (Mn, Fe, ${\\mathsf{N i}},$ and $\\mathsf{C u}$ ) SACs is chiefly responsible for its high activity and selectivity toward $H_{2}O_{2}$ production. A kinetic analysis and operando X-ray absorption study combined with DFT calculations demonstrated that nitrogen-coordinated Co single atom was the active site for $H_{2}O_{2}$ synthesis through ORR and the reaction was rate-limited in the first proton-coupled electron transfer step. This work combines the advantages of both homogeneous catalysts of cobalt macrocycles (well-defined active sites) and heterogeneous catalysts (high catalytic performance) together, moreover, operando XAS combined with kinetics analysis in this work tracked the dynamic change of nitrogen-coordinated cobalt active center under reaction condition, which together lead to higher catalytic performance with enhanced understanding of the reaction process. \n\n# EXPERIMENTAL PROCEDURES \n\n# Catalyst Preparation \n\nChemicals: melamine $(C_{3}H_{6}N_{6},99\\%)$ , L-alanine $(\\mathsf{C}_{3}\\mathsf{H}_{7}\\mathsf{N O}_{2},98\\%)$ , cobalt(II) acetate tetrahydrate $(\\mathsf{C o}(\\mathsf{C}\\mathsf{H}_{3}\\mathsf{C O}_{2})_{2}\\cdot4\\mathsf{H}_{2}\\mathsf{O},$ $99\\%$ ), manganese(II) acetate $(N n(C H_{3}C O_{2})_{2},$ , \n\n# Chem \n\n$98\\%$ ), iron(II) acetate $(\\mathsf{F e}(\\mathsf{C}\\mathsf{H}_{3}\\mathsf{C O}_{2})_{2},$ $99.99\\%$ , nickel(II) acetate tetrahydrate $(N i(C H_{3}C O_{2})_{2}\\cdot4H_{2}O,98\\%)$ , nickel(II) phthalocyanine $(\\mathsf{C}_{32}\\mathsf{H}_{16}\\mathsf{N}_{8}\\mathsf{N i},85\\%),$ copper(II) acetate $(\\mathsf{C u}(\\mathsf{C H}_{3}\\mathsf{C O}_{2})_{2},$ , $98\\%$ ), copper(II) phthalocyanine $(C_{32}\\mathsf{H}_{16}\\mathsf{N}_{8}\\mathsf{C u}_{.}$ , sublimed grade, $99\\mathrm{~\\%~}$ ), hydrochloric acid (HCl, $37\\%$ ), nitric acid $(\\mathsf{H N O}_{3}$ , $70\\%$ ), hydrogen peroxide solution $(H_{2}O_{2})$ 30 wt $\\%$ in water), and cerium(IV) sulfate $(\\mathsf{C e}(\\mathsf{S O}_{4})_{2},\\mathsf{98}\\%)$ were purchased from Sigma-Aldrich and absolute ethanol was bought from Merck. Cobalt(II) phthalocyanine $(C_{32})H_{16}N_{8}C o$ , $95\\%$ , product code: 41496) and Iron(II) phthalocyanine $(C_{32}\\mathsf{H}_{16}\\mathsf{N}_{8}\\mathsf{F e}$ , $96\\%$ , product code: 39262) were purchased from Alfa Aesar. Multi-walled carbon nanotubes (CNT, 10–20 nm diameter, $5-15~{\\upmu\\mathrm{m}}$ length) were bought from TCI chemical company. All chemicals were used directly without further purification. De-ionized water was obtained from Millipore $\\bigcirc$ water purification system. Transition metal SACs were synthesized according to our previous method38 with slight modification. In a typical synthesis, $12{\\mathfrak{g}}$ of melamine, $_{2\\mathfrak{g}}$ of L-alanine, and $50\\mathrm{mg}$ of transition metal acetate were homogeneously mixed by ball milling for $1\\ h$ . Then, $15~\\mathsf{m L}$ of ethanol mixed with $3~\\mathrm{mL}$ of hydrochloric acid was added and the slurry was put in a mortar. The mixture was milled in a fume hood until all ethanol was evaporated. The resultant solid was dried in an oven at $60^{\\circ}\\mathsf{C}$ overnight and ball milled again for $1\\ h$ . The thus obtained powder was pyrolyzed under flowing ${\\sf N}_{2}$ atmosphere in a tube furnace with the following ramping program: from room temperature to $600^{\\circ}\\mathsf{C}$ at a ramping rate of $2.5^{\\circ}C/\\min$ , then hold at $600^{\\circ}\\mathsf{C}$ for $120\\mathrm{min}$ , ramp to $900^{\\circ}\\mathsf{C}$ at $5^{\\circ}C/\\mathsf{m i n}$ and hold for $90\\mathrm{min}.$ , finally the furnace was naturally cooled down to room temperature. The obtained black solid materials were grinded and then washed by $2M H C l$ aqueous solution at $80^{\\circ}\\mathsf{C}$ for $24\\mathsf{h}$ under stirring to remove metal particles. For copper-based material, 1 M $H N O_{3}$ was used to remove copper metal particles. The acid-washed materials were dried and then annealed again in ${\\sf N}_{2}$ at $800^{\\circ}\\mathsf{C}$ for $1\\ h$ at a heating rate of $10^{\\circ}C/\\min$ to recover the crystallinity. The thus obtained SACs were marked as Mn–NC, Fe–NC, Co–NC, Ni–NC, and Cu–NC, respectively, according to the metal acetate used. NC was synthesized by the same method without adding metal acetate and undergoing acid washing. Co nanoparticle supported on NC with Co content of 2 wt $\\%$ was prepared by impregnation method: $200\\mathrm{mg}$ of NC was dispersed in $20\\mathsf{m l}$ L mixed solution of water and ethanol (volume ratio 1:1) containing $18~\\mathsf{m g}$ of cobalt(II) acetate tetrahydrate. The mixture was heated to $80^{\\circ}\\mathsf{C}$ in an oil bath under stirring to evaporate the solution. The obtained solid was then calcined at $400^{\\circ}\\mathsf C$ in ${\\sf N}_{2}$ atmosphere for $2h$ . The obtained catalyst was marked as $\\mathsf{C o}_{\\mathsf{N P s}}/\\mathsf{N C}$ . In addition, tetra amino cobalt(II) phthalocyanine (Co-TAPC) was synthesized and loaded on CNT according to the method reported in literature,44,45 and the catalyst was marked as Co-TAPC/CNT. \n\n# Characterization \n\nPowder XRD was performed on a Bruker D2 Phaser using $\\mathsf{C u}\\ K\\alpha$ radiation with a LYNXEYE detector at $30\\up k\\upvee$ and $10~\\mathrm{mA}$ . The morphological information was examined with field-emission SEM (FESEM, JEOL JSM-6700F). Sub angstrom-resolution high-angle annular dark field scanning transmission electron microscopy (HAADFSTEM) characterization was conducted on a JEOL JEMARM200F STEM and TEM with a guaranteed resolution of $0.08~\\mathsf{n m}$ . The metal content in the catalysts was quantified by inductively coupled plasma-atomic emission spectroscopy (ICP-AES, PerkinElmer). ${\\sf N}_{2}$ adsorption-desorption was performed on an Autosorb-6 (Quantachrome) at $77~\\mathsf{K}.$ . Before analysis, the samples were degassed at $200^{\\circ}\\mathsf{C}$ for $5\\textmd{h}$ . BET surface area was calculated in the P/Po range of 0.05–0.2. Pore size destitution was obtained by Barrett-Joyner-Halenda (BJH) method by using the adsorption branch. Pore volume was calculated by the adsorption amount at $\\mathsf{P}/\\mathsf{P}_{\\circ}=0.985$ . Raman spectra were recorded on a Renishaw INVIA Reflex Raman spectrometer using $514\\mathsf{n m}$ laser as the excitation source. XPS measurements were carried out on a \n\nThermofisher ESCALAB 250Xi photoelectron spectrometer (Thermofisher Scientific) using a monochromatic Al $\\mathsf{K}\\boldsymbol{\\mathfrak{a}}$ X-ray beam $(1,486.6\\ \\mathrm{eV})$ . XAS including both XANES and EXAFS at Mn, Fe, Co, Ni, and Cu K-edge were collected in total-fluorescence-yield mode at ambient air in BL-01C1 at the National Synchrotron Radiation Research Center (NSRRC), Taiwan. The spectra were obtained by subtracting the baseline of pre-edge and normalizing to the post-edge. EXAFS analysis was conducted using Fourier transform on $\\mathsf{k}_{3}$ -weighted EXAFS oscillations to evaluate the contribution of each bond pair to Fourier transform peak. Operando measurement in a typical three-electrode setup was performed in a specially designed Teflon container with a window sealed by Kapton tape with continuous gas bubbling. X-ray was allowed to transmit through the tape and electrolyte, so that the signal of XAS could be collected in total-fluorescence-yield mode in BL-01C1 at NSRRC, Taiwan. \n\n# Electrochemical Measurements \n\nThe electrochemical performance of various catalysts was evaluated in a three-electrode configuration with carbon rod as the counter electrode and Ag-AgCl electrode with saturated KCl salt bridge as the reference electrode on a RRDE setup (AFE6R1PT model; disk $\\mathsf{O D}=5.0~\\mathsf{m m}$ ; ring $\\mathsf{O D}=7.50~\\mathsf{m m}$ ; ring $|\\mathsf{D}=6.50\\mathsf{m m}$ ; Pine Research Instrumentation, USA) and a CHI (760E) potentiostat. $0.1\\mathrm{~M~HClO}_{4}$ was prepared by diluting perchloric acid $70\\%$ , $99.999\\%$ trace metals basis, Sigma) with Millipore $\\bigcirc$ water. 0.1 M KOH was prepared by dissolving KOH pellets (semiconductor grade, $99.99\\%$ trace metals basis, Sigma) in Millipore $\\bigcirc$ water $(15\\mathsf{M}\\Omega)$ . A RHE was made with two Pt plates as working and counter electrodes to calibrate the $\\mathsf{A g-A g C l}$ electrode and ${\\sf H}_{2}$ was bubbled over the working electrode. Potentials reported here are referenced to the RHE scale as follows: $E_{\\mathsf{R H E}}=E_{\\mathsf{A g/A g C l}}+0.197\\vee+$ $0.059\\lor\\times\\mathsf{P H}$ or standard hydrogen electrode (SHE) scale: $E_{\\mathsf{S H E}}=E_{\\mathsf{A g/A g C l}}+0.197\\vee$ . To prepare the working electrode, the catalyst ink that was prepared by ultrasonically mixing $5\\mathsf{m g}$ of the catalyst, $0.98{\\mathrm{mL}}$ of Millipore Q $H_{2}O$ (15 MU), $0.98~\\mathrm{mL}$ of isopropyl alcohol, and $40\\upmu\\up L$ of 5 wt $\\%$ D520 Nafion dispersion solution was drop-casted on freshly polished RRDE. In a typical measurement, $2~\\upmu\\upiota$ of catalyst ink was used, which corresponds a catalyst loading amount of $25~{\\upmu\\mathsf{g}}/{\\mathsf{c m}}_{\\mathsf{d i s k}}^{2}$ . Before collecting the electrochemical data, the electrolyte was bubbled with purified $\\mathsf{O}_{2}$ or ${\\sf N}_{2}$ for $30~\\mathrm{{min}}$ . Subsequently the working electrode together with $\\mathsf{P t}$ ring were cycled for ten cycles between 0 and $1.0\\vee$ versus RHE at a scan rate of $500~\\mathrm{mV}~\\mathsf{s}^{-1}$ to achieve a stable performance. CV curves were recorded in the potential range of $0{-}1.1~\\mathsf{V}$ versus RHE at $500\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ under static condition with saturated ${\\sf N}_{2}$ or $\\mathrm{O}_{2}$ . LSV curves were recorded at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ with $100\\%$ solution ohmic drop correction under 1,600 rpm or other indicated rotation speed; the potential of the Pt ring in the working electrode was set at $1.2\\lor$ versus RHE. In kinetic analysis, according to the Henry’s law, the $\\mathrm{O}_{2}$ concentration is proportional to its partial pressure in the gas phase, thus partial pressure is used to control the concentration of $\\mathrm{O}_{2}$ in electrolyte. In detail, the partial pressure of $\\mathrm{O}_{2}$ was adjusted by diluting $\\mathsf{O}_{2}$ flow with Argon at controlled flow rate. For example, $\\mathsf{O}_{2}$ partial pressure of $25\\mathsf{k P a}$ was obtained by mixing gas of $\\mathrm{O}_{2}$ $50m L/\\min)$ and argon $(150\\mathrm{mL/min})$ . For different pH (1.5 3.0), KOH tablet was added to 0.1 M ${\\sf H}_{3}{\\sf P}{\\sf O}_{4}$ solution to tune the ${\\mathsf{p H}}$ and $K N O_{3}$ was added to adjust the ionic strength.46 Considering that $\\mathrm{O}_{2}$ partial pressure and concentration of $\\mathsf{H}^{+}$ can influence the equilibrium potential of the reaction $(\\mathrm{O}_{2}+2\\mathrm{e}^{-}+2\\mathsf{H}^{+}\\to $ $H_{2}O_{2})$ according to the Nernst equation: $\\begin{array}{r}{\\mathsf E_{O_{2}/H_{2}O_{2}}=\\mathsf E_{O_{2}/H_{2}O_{2}}^{0}-\\frac{\\mathsf R T}{z\\mathsf F}|\\mathsf n\\frac{a_{\\mathrm{O}_{2}}a_{\\mathrm{H}^{+}}^{2}}{a_{\\mathsf H_{2}O_{2}}},}\\end{array}$ where $E_{{O_{2}}/{H_{2}}{O_{2}}}^{0}=0.695\\:\\forall$ (versus standard hydrogen electrode) is the standard potential of the reaction at $\\mathsf{O}_{2}$ partial pressure of 1 atm, the activity of ${\\mathsf{H}}^{+}\\left(a_{{\\mathsf{H}}+}\\right)$ and ${\\sf H}_{2}{\\sf O}_{2}$ $(a_{1+12}\\cos2)$ equal 1 mol/L. Here, due to the unknown value of $a_{H2}=2$ in the electrolyte solution, we just assume it as $1\\mathrm{mol/L}$ to get a pseudo-equilibrium potential. Then, the \n\n# Chem \n\nchange of $\\mathrm{O}_{2}$ partial pressure and activity of $\\mathsf{H}^{+}$ would reach a new pseudo-equilibrium potential $E_{O_{2}/H_{2}O_{2}}$ . The overpotential is defined as $\\upeta=E_{\\mathsf{a p p l i e d}}-E_{O_{2}/H_{2}O_{2}}$ , Eapplied is the potential (versus SHE) applied to the working electrode, $E_{O_{2}/H_{2}O_{2}}$ is the pseudo-equilibrium potential at designated $\\mathrm{O}_{2}$ pressure and $\\mathsf{H}^{+}$ activity. It should be noted that the overpotential defined here is not a strict one due to the unknown true value of equilibrium potential, but it still can be used as the driving force of the reaction for kinetic analysis. \n\n${\\sf H}_{2}{\\sf O}_{2}$ selectivity was calculated on rotating ring disk electrode based on the currents of both disk and ring electrode according to: \n\n${\\sf H}_{2}{\\sf O}_{2}$ selectivity or Faraday efficiency: $\\begin{array}{r}{\\mathsf{H}_{2}\\mathsf{O}_{2}\\left(\\%\\right)=200\\frac{I_{R}/N}{I_{D}~+~I_{R}/N}}\\end{array}$ where $I_{{\\sf R}}$ is the ring current, $I_{\\mathsf{D}}$ is the disk current and $N$ is the collection efficiency of the RRDE (0.25), which is calibrated by the redox of potassium ferricyanide (Figure S29). \n\nDuring stability test, H-type electrochemical cell with working and counter electrode separated by Nafion film was used to avoid further oxidation of ${\\sf H}_{2}{\\sf O}_{2}$ on the anode. The formation rate of ${\\sf H}_{2}{\\sf O}_{2}$ in half-cell experiment was conducted in $\\mathsf{O}_{2}$ saturated $0.1\\ \\mathsf{M}\\mathsf{H C}\\mathsf{l O}_{4}$ in a H-type cell. The working electrode is prepared with carbon paper $(1\\times1~\\mathsf{c m})$ by coating catalysts with loading amount of $100\\mathrm{\\:\\upmu\\upg/cm}^{2}$ .The concentration of ${\\sf H}_{2}{\\sf O}_{2}$ in electrolyte during stability test was determined by cerium sulfate titration $(2\\mathsf{C e}^{4+}+\\mathsf{H}_{2}\\mathsf{O}_{2}\\to2\\mathsf{C e}^{3+}+\\mathsf{O}_{2}+2\\mathsf{H}^{+})$ as detailed in literature.7 The concentration of ${\\mathsf{C e}}^{4+}$ was measured by ultraviolet -visible spectrometer (JINGHUA Instruments, Model: 754PC) at $316{\\mathsf{n m}}$ and the calibration curve is shown in Figure S30. \n\n# DFT Calculation Method Calculation Details \n\nSpin-polarized DFT calculations were performed using the generalized gradient approximation (GGA) in the form of Perdew–Burke–Ernzerhof (PBE) for the exchange-correlation potentials,47,48 the projector augmented wave (PAW) pseudopotential for the core electrons,49 and a $480~\\mathrm{eV}$ cutoff energy for the valence electrons as implemented in the Vienna ab initio simulation package (VASP).50,51 Transition metals are likely trapped in the vacancies of graphene at various levels of nitrogen doping. The porphyrinic moieties containing 3D transition metal such as Fe and Co are reported to be good ORR catalyst.30 Herein, we investigated ORR of $2\\ e^{-}$ and $4~{\\mathfrak{e}}^{-}$ pathways on the nitrogen and transition metal atom $\\mathsf{T M}=$ Mn, Fe, Co, Ni, and $\\mathsf{C u}$ ) co-doped graphene. The single transition metal atom dispersed catalysts are simulated using a cluster model (formula of $C_{40}\\mathsf{H}_{16}\\mathsf{N}_{4}\\mathsf{M}).$ in which the M atom is bound with four pyrrolic nitrogen atoms. Here, we choose cluster model other than periodic one based on two considerations: first, previous studies reported that the porphyrins containing 3d transition metals show promising activity toward production of $H_{2}O_{2}$ .30,52,53 If periodic model is constructed using the skeleton of the porphyrin molecule embedded with a metal atom as the basic unit, eight-membered carbon rings inevitably exist, which is significantly different from the honeycomb structure of graphene. Second, previous experimental and DFT studies proposed that the periodic model with $\\mathsf{M N}_{4}$ group $\\langle{\\mathsf{M}}=$ transition metal, ${\\sf N}=$ nitrogen) compactly embedded in graphene cannot correctly predict the ORR and ${\\mathsf{C O}}_{2}$ reduction activities of these SACs.30,54 Therefore, the cluster model is selected here. The cluster is placed in a box in the size of $30\\times30\\times13\\mathrm{~\\AA~},$ with vacuum layers of $\\sim13\\mathring{\\mathsf{A}}$ along vertical and lateral directions to decouple the interaction between neighboring images. The energies of gas-phase ${\\sf H}_{2}$ and $H_{2}O$ molecules were calculated in a cubic supercell with length of $20\\mathring{\\mathsf{A}}$ . All atoms are free to relax until the net force per atom is less than $0.02\\mathrm{~eV}/\\mathring{A}$ . We consider the possible spin state of transition metal atom with and without adsorbates and confirm the most stable adsorption configurations of $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ , $^{\\star}\\mathrm{O}$ , and $^{\\star}\\mathrm{OH}$ . The corresponding binding energies and spin states are listed in Tables S1 and S2. The stability of SACs is evaluated via calculating the formation energy, which is defined as: \n\n$$\nE_{f o r m}=E_{T M/g r a}-E_{g r a}-E_{T M-b u l k}\n$$ \n\nwhere $E_{T M/g r a}$ , $E_{g r a,}$ , and $E_{T M-b u l k}$ represent the energies of TM and N co-doped graphene, N-doped graphene, and TM atom in the bulk phase. \n\nAccording to this definition, a more negative formation energy is, the more stable of the SAC will be. The calculated formation energies of these SACs $(E_{f o r m})$ are all negative and are shown in Figure S1, indicating that such single atom dispersed structures are thermodynamically stable. The d-band center of the transition metal atom in SAC is defined as: \n\n$$\n{\\mathsf{d}}_{\\mathsf{c e n t e r}}={\\frac{\\int_{-\\infty}^{+\\infty}{\\bigl(}\\varepsilon-E_{\\mathsf{F}}{\\bigr)}n(x)d\\varepsilon}{\\int_{-\\infty}^{+\\infty}n(x)d\\varepsilon}}\n$$ \n\nwhere $n(x)$ and $E_{\\mathsf{F}}$ are the projected density of states of the $d.$ -orbitals of M atom in $C_{40}\\mathsf{H}_{16}\\mathsf{N}_{4}\\mathsf{M}$ and the corresponding fermi level of $\\mathsf{C}_{40}\\mathsf{H}_{16}\\mathsf{N}_{4}\\mathsf{M}$ , respectively. \n\nModel of pyridinic N coordinated Co SAC was also used for calculation and given in Figure S7 for reference. \n\n# Free Energy Diagram and Activity-Volcano Curve \n\nThe ORR after $2e^{-}$ and $4e^{-}$ mechanisms produces $H_{2}O$ and $H_{2}O_{2},$ respectively. The associative $4\\:e^{-}$ reaction is composed of elementary steps $(\\mathsf{c},\\mathsf{d},\\mathsf{e},$ and f): \n\n$$\n\\ast+O_{2(g)}+H^{+}+e^{-}\\rightarrow O O H^{\\ast}\n$$ \n\n$$\n{O O H^{*}+H^{+}+e^{-}}\\rightarrow{O^{*}+H_{2}O_{(I)}}\n$$ \n\n$$\nO^{*}+H^{+}+e^{-}{\\rightarrow}O H^{*}\n$$ \n\n$$\nO H^{*}+H^{+}+e^{-}\\rightarrow H_{2}O_{(I)}+*\n$$ \n\nThe ORR of $2\\ e^{-}$ mechanism comprises of elementary steps $(\\mathfrak{g}$ and $\\mathsf{h}$ ): \n\n$$\n*+O_{2(g)}+H^{+}+e^{-}\\rightarrow O O H^{*}\n$$ \n\n$$\nO O H^{*}+H^{+}+e^{-}\\rightarrow H_{2}O_{2(I)}+*\n$$ \n\nThe asterisk $(^{\\star})$ denotes the active site of the catalyst. \n\nThe free energy for each reaction intermediate is defined as: \n\n$$\nG=E_{D F T}+E_{Z P E}-T S+E_{s o l}\n$$ \n\n$E_{D F T}$ is the electronic energy calculated by DFT, $E_{Z P E}$ denotes the zero point energy estimated within the harmonic approximation, and TS is the entropy at $298.15~\\mathsf{K}$ $(\\mathsf{T}=298.15\\mathsf{K})$ . The $E_{Z P E}$ and TS of gas-phase molecules and reaction intermediates are listed in Table S3. For the concerted proton-electron transfer, the free energy of a pair of proton and electron $(\\mathsf{H}^{+}+\\mathsf{e}^{-})$ was calculated as a function of applied potential relative to RHE (U versus RHE), i.e., $\\upmu(\\mathsf{H}^{+})+\\upmu(\\mathsf{e}^{-})=\\frac{1}{2}\\upmu(\\mathsf{H}_{2})-\\mathsf{e U}_{\\rho}$ , according to the computational hydrogen electrode (CHE) model proposed by Nørskov.55 In \n\n# Chem \n\naddition, the solvent effect is reported to play an important role in the ORR. In our calculations, the solvent corrections $(E_{s o l})$ for $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ and $^{\\star}\\mathrm{OH}$ are $0.45\\mathrm{eV}$ in accordance with previous studies.56,57 We used the energies of $H_{2}O$ and ${\\sf H}_{2}$ molecules calculated by DFT together with experimental formation energy of $H_{2}O$ $4.92\\ \\mathrm{eV})$ to construct the free energy diagram. The free energies of $O_{2}$ , $^{\\star}\\mathsf{O}\\mathsf{O}\\mathsf{H}$ , $^{\\star}\\mathrm{O},$ , and $^{\\star}\\mathrm{OH}$ at a given potential $\\mathsf{U}$ relative to RHE are defined as: \n\n$$\n\\Delta G(\\mathsf{O}_{2})=4.92-4\\mathsf{e U}\n$$ \n\n$$\n\\Delta G(\\mathrm{OOH})=G(\\mathrm{OOH^{\\ast}})+\\frac{3G(\\mathsf{H}_{2})}{2}-G(\\ast)-2G(\\mathsf{H}_{2}\\mathrm{O})-3\\mathrm{e}\\mathsf{U}\n$$ \n\n$$\n\\Delta G(\\mathrm{O})=G(\\mathrm{O}^{*})+G({\\mathsf{H}}_{2})-G(*)-G({\\mathsf{H}}_{2}\\mathrm{O})-2{\\mathsf{e U}}\n$$ \n\n$$\n\\Delta G(\\boldsymbol{\\mathrm{O}}\\boldsymbol{\\mathsf{H}})=G(\\boldsymbol{\\mathrm{O}}\\mathsf{H}^{*})+\\frac{G(\\mathsf{H}_{2})}{2}-G(*)-G(\\mathsf{H}_{2}\\boldsymbol{\\mathrm{O}})-\\mathsf{e}\\mathsf{U}\n$$ \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information can be found online at https://doi.org/10.1016/j.chempr. \n2019.12.008. \n\n# ACKNOWLEDGMENTS \n\nWe would like to acknowledge funding support from the National Key R&D Program of China (2016YFA0202804), Singapore Ministry of Education Academic Research Fund (AcRF) Tier 1: RG10/16 and RG111/15, Tier 2: MOE2016-T2-2-004, and the financial support from Jiangsu Specially-Appointed Professor program. \n\n# AUTHOR CONTRIBUTIONS \n\nJ.G., H.Y., and B.L. conceived and designed the project. X.H. carried out the theoretical calculations. S.H. and H.M.C. performed the X-ray absorption experiments. W.C., C.J., S.M., X.Y., and Y.H. contributed to the structure characterizations. J.G. and B.L. prepared the manuscript. All authors contributed and reviewed the manuscript. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: August 8, 2019 \nRevised: September 29, 2019 \nAccepted: December 9, 2019 \nPublished: January 16, 2020 \n\n# REFERENCES \n\nproduction of $H_{2}O_{2};$ A focus on the catalysis. \nACS Catal. 8, 4064–4081. \n1. Myers, R.L. (2007). The 100 Most Important Chemical Compounds: A Reference Guide, First edition (Greenwood Publishing Group). \n2. Freakley, S.J., He, Q., Harrhy, J.H., Lu, L., Crole, D.A., Morgan, D.J., Ntainjua, E.N., Edwards, J.K., Carley, A.F., Borisevich, A.Y., et al. (2016). Palladium-tin catalysts for the direct synthesis of $H_{2}O_{2}$ with high selectivity. Science 351, \n965–968. \n3. Yang, S., Verdaguer-Casadevall, A., Arnarson, L., Silvioli, L., C\u0001 oli\u0003c, $\\mathsf{V}_{\\cdot,\\prime}$ Frydendal, R., Rossmeisl, J., Chorkendorff, I., and Stephens, I.E.L. (2018). Toward the decentralized electrochemical \n4. Yi, Y., Wang, L., Li, G., and Guo, H. (2016). A review on research progress in the direct synthesis of hydrogen peroxide from hydrogen and oxygen: noble-metal catalytic method, fuel-cell method and plasma method. Catal. Sci. Technol. 6, 1593–1610. \n5. Iglesias, D., Giuliani, A., Melchionna, M., Marchesan, S., Criado, A., Nasi, L., Bevilacqua, M., Tavagnacco, C., Vizza, F., Prato, M., and Fornasiero, P. (2018). N-doped graphitized carbon nanohorns as a forefront electrocatalyst in highly selective $O_{2}$ reduction to $H_{2}O_{2}$ . Chem 4, 106–123. \n6. Kim, H.W., Ross, M.B., Kornienko, N., Zhang, L. Guo, J., Yang, P., and McCloskey, B.D. (2018). Efficient hydrogen peroxide generation using reduced graphene oxide-based oxygen reduction electrocatalysts. Nat. Catal. 1, 282–290. \n7. Lu, Z., Chen, G., Siahrostami, S., Chen, Z., Liu, K., Xie, J., Liao, L., Wu, T., Lin, D., Liu, Y., et al. (2018). High-efficiency oxygen reduction to hydrogen peroxide catalysed by oxidized carbon materials. Nat. Catal. 1, 156–162. 8. Melchionna, M., Fornasiero, P., and Prato, M. (2019). The rise of hydrogen peroxide as the main product by metal-free catalysis in oxygen reductions. Adv. Mater. 31, e1802920. 9. Mounfield, W.P., Garg, A., Shao-Horn, Y., and Roma´ n-Leshkov, Y. (2018). Electrochemical oxygen reduction for the production of hydrogen peroxide. Chem 4, 18–19. \n10. Sun, Y., Sinev, I., Ju, W., Bergmann, A., Dresp, S., Ku¨ hl, S., Sp ¨ori, C., Schmies, H., Wang, H., Bernsmeier, D., et al. (2018). Efficient electrochemical hydrogen peroxide production from molecular oxygen on nitrogen-doped mesoporous carbon catalysts. ACS Catal. 8, 2844–2856. \n11. Qiang, Z., Chang, J.H., and Huang, C.P. (2002). Electrochemical generation of hydrogen peroxide from dissolved oxygen in acidic solutions. Water Res. 36, 85–94. \n12. Kuo, W.G. (1992). Decolorizing dye wastewater with Fenton’s reagent. Water Res. 26, 881–886. \n13. Jirkovsky´, J.S., Panas, I., Ahlberg, E., Halasa, M., Romani, S., and Schiffrin, D.J. (2011). Single atom hot-spots at Au-Pd nanoalloys for electrocatalytic $H_{2}O_{2}$ production. J. Am. Chem. Soc. 133, 19432–19441. \n14. Murayama, T., Tazawa, S., Takenaka, S., and Yamanaka, I. (2011). Catalytic neutral hydrogen peroxide synthesis from $O_{2}$ and $H_{2}$ by PEMFC fuel. Catal. Today 164, 163–168. \n15. Barros, W.R.P., Reis, R.M., Rocha, R.S., and Lanza, M.R.V. (2013). Electrogeneration of hydrogen peroxide in acidic medium using gas diffusion electrodes modified with cobalt (II) phthalocyanine. Electrochim. Acta 104, 12–18. \n16. Siahrostami, S., Verdaguer-Casadevall, A., Karamad, M., Deiana, D., Malacrida, P., Wickman, B., Escudero-Escribano, M., Paoli, E.A., Frydendal, R., Hansen, T.W., et al. (2013). Enabling direct $H_{2}O_{2}$ production through rational electrocatalyst design. Nat. Mater. 12, 1137–1143. \n17. Verdaguer-Casadevall, A., Deiana, D., Karamad, M., Siahrostami, S., Malacrida, P., Hansen, T.W., Rossmeisl, J., Chorkendorff, I., and Stephens, I.E. (2014). Trends in the electrochemical synthesis of $H_{2}O_{2};$ enhancing activity and selectivity by electrocatalytic site engineering. Nano Lett. 14, 1603–1608. \n18. Pegis, M.L., Wise, C.F., Martin, D.J., and Mayer, J.M. (2018). Oxygen reduction by homogeneous molecular catalysts and electrocatalysts. Chem. Rev. 118, 2340–2391. \n19. Campos, M., Siriwatcharapiboon, W., Potter, R.J., and Horswell, S.L. (2013). Selectivity of cobalt-based catalysts towards hydrogen peroxide formation during the reduction of oxygen. Catal. Today 202, 135–143. \n20. Yamanaka, I., Onizawa, T., Suzuki, H., Hanaizumi, N., Nishimura, N., and Takenaka, S. (2012). Study of direct synthesis of hydrogen peroxide acid solutions at a heat-treated MnCl–porphyrin/activated carbon cathode from ${\\sf H}_{2}$ and $O_{2}.$ . J. Phys. Chem. C 116, 4572– 4583. \n21. Wang, A., Li, J., and Zhang, T. (2018). Heterogeneous single-atom catalysis. Nat. Rev. Chem. 2, 65–81. \n22. Yang, X.F., Wang, A., Qiao, B., Li, J., Liu, J., and Zhang, T. (2013). Single-atom catalysts: a new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748. \n23. Cui, X., Li, W., Ryabchuk, P., Junge, $\\mathsf{K}_{\\cdot,\\prime}$ and Beller, M. (2018). Bridging homogeneous and heterogeneous catalysis by heterogeneous single-metal-site catalysts. Nat. Catal. 1, 385–397. \n24. Montemore, M.M., van Spronsen, M.A., Madix, R.J., and Friend, C.M. (2018). $\\mathrm{O}_{2}$ activation by metal surfaces: implications for bonding and reactivity on heterogeneous catalysts. Chem. Rev. 118, 2816–2862. \n25. Yang, S., Kim, J., Tak, Y.J., Soon, A., and Lee, H. (2016). Single-atom catalyst of platinum supported on titanium nitride for selective electrochemical reactions. Angew. Chem. Int. Ed. 55, 2058–2062. \n26. Yin, P., Yao, T., Wu, Y., Zheng, L., Lin, Y., Liu, W., Ju, H., Zhu, J., Hong, X., Deng, Z., et al. (2016). Single cobalt atoms with precise Ncoordination as superior oxygen reduction reaction catalysts. Angew. Chem. Int. Ed. 55, 10800–10805. \n27. Zagal, J.H., and Koper, M.T. (2016). Reactivity descriptors for the activity of molecular MN4 catalysts for the oxygen reduction reaction. Angew. Chem. Int. Ed. 55, 14510–14521. \n28. Chung, H.T., Cullen, D.A., Higgins, D., Sneed, B.T., Holby, E.F., More, K.L., and Zelenay, P. (2017). Direct atomic-level insight into the active sites of a high-performance PGM-free ORR catalyst. Science 357, 479–484. \n29. Zitolo, A., Ranjbar-Sahraie, N., Mineva, T., Li, J., Jia, Q., Stamatin, S., Harrington, G.F., Lyth, S.M., Krtil, P., Mukerjee, S., et al. (2017). Identification of catalytic sites in cobaltnitrogen-carbon materials for the oxyge reduction reaction. Nat. Commun. 8, 957. \n30. Zitolo, A., Goellner, $\\mathsf{V}_{\\cdot,\\prime}$ Armel, V., Sougrati, M.T., Mineva, T., Stievano, L., Fonda, E., and Jaouen, F. (2015). Identification of catalytic sites for oxygen reduction in iron- and nitrogen-doped graphene materials. Nat. Mater. 14, 937–942. \n31. Hammer, B., and Nørskov, J.K. (2000). Theoretical surface science and catalysis— calculations and concepts. Adv. Catal. 45, 71–129. \n32. Koper, M.T.M. (2011). Thermodynamic theory of multi-electron transfer reactions: implications for electrocatalysis. J. Electroanal. Chem. 660, 254–260. \n33. Christensen, R., Hansen, H.A., Dickens, C.F., Nørskov, J.K., and Vegge, T. (2016). Functional independent scaling relation for ORR/OER catalysts. J. Phys. Chem. C 120, 24910–24916. \n34. Kulkarni, A., Siahrostami, S., Patel, A., and Nørskov, J.K. (2018). Understanding catalytic activity trends in the oxygen reduction reaction. Chem. Rev. 118, 2302–2312. \n35. Ferrari, A.C. (2007). Raman spectroscopy of graphene and graphite: disorder, electron– phonon coupling, doping and nonadiabatic effects. Solid State Commun. 143, 47–57. \n36. Yang, H.B., Miao, J., Hung, S.F., Chen, J., Tao, H.B., Wang, X., Zhang, L., Chen, R., Gao, J., Chen, H.M., et al. (2016). Identification of catalytic sites for oxygen reduction and oxygen evolution in N-doped graphene materials: development of highly efficient metal-free bifunctional electrocatalyst. Sci. Adv. 2, e1501122. \n37. Malard, L.M., Pimenta, M.A., Dresselhaus, G., and Dresselhaus, M.S. (2009). Raman spectroscopy in graphene. Phys. Rep. 473, 51–87. \n38. Yang, H.B., Hung, S.-F., Liu, S., Yuan, K., Miao, S., Zhang, L., Huang, X., Wang, H.-Y., Cai, W., Chen, R., et al. (2018). Atomically dispersed Ni(I) as the active site for electrochemical ${\\mathsf{C O}}_{2}$ reduction. Nat. Energy 3, 140–147. \n39. Fei, H., Dong, J., Feng, Y., Allen, C.S., Wan, C., Volosskiy, B., Li, M., Zhao, Z., Wang, Y., Sun, H., et al. (2018). General synthesis and definitive structural identification of $M N_{4}C_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72. \n40. Jia, Q., Ramaswamy, N., Hafiz, H., Tylus, U., Strickland, K., Wu, G., Barbiellini, B., Bansil, A. Holby, E.F., Zelenay, P., and Mukerjee, S. (2015). Experimental observation of redoxinduced Fe-N switching behavior as a determinant role for oxygen reduction activity. ACS Nano 9, 12496–12505. \n41. Durand, R.R., and Anson, F.C. (1982). Catalysis of dioxygen reduction at graphite electrodes by an adsorbed cobalt(II) porphyrin. J. Electroanal. Chem. Interfacial Electrochem. 134, 273–289. \n42. Rojas-Carbonell, S., Artyushkova, K., Serov, A., Santoro, C., Matanovic, I., and Atanassov, P. (2018). Effect of pH on the activity of platinum group metal-free catalysts in oxygen reduction reaction. ACS Catal. 8, 3041–3053. \n43. Koper, M.T.M. (2013). Analysis of electrocatalytic reaction schemes: distinction between rate-determining and potentialdetermining steps. J. Solid State Electrochem. 17, 339–344. \n44. Somashekarappa, M.P., Keshavayya, J., and Sampath, S. (2002). Self-assembled molecular films of tetraamino metal (Co, Cu, Fe) phthalocyanines on gold and silver. Electrochemical and spectroscopic characterization. Pure Appl. Chem. 74, 1609– 1620. \n45. Mugadza, T., and Nyokong, T. (2009). Synthesis and characterization of electrocatalytic conjugates of tetraamino cobalt (II) phthalocyanine and single wall carbon nanotubes. Electrochim. Acta 54, 6347–6353. \n46. Huynh, M., Bediako, D.K., and Nocera, D.G. (2014). A functionally stable manganese oxide oxygen evolution catalyst in acid. J. Am. Chem. Soc. 136, 6002–6010. \n47. Perdew, J.P., Burke, K., and Ernzerhof, M. (1996). Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865– 3868. \n48. Perdew, J.P., Ernzerhof, M., and Burke, K. (1996). Rationale for mixing exact exchange \n\n# Chem \n\nwith density functional approximations. \nJ. Chem. Phys. 105, 9982–9985. \n49. Kresse, G., and Joubert, D. (1999). From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, \n1758–1775. \n50. Kresse, G., and Furthm ¨uller, J. (1996). Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186. \n51. Kresse, G., and Furthm ¨uller, J. (1996). Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50. \n52. Gou ´erec, P., and Savy, M. (1999). Oxygen reduction electrocatalysis: ageing of pyrolyzed cobalt macrocycles dispersed on an active carbon. Electrochim. Acta 44, 2653–2661. \n53. van Veen, J.A.R., van Baar, J.F., Kroese, C.J., Coolegem, J.G.F., De Wit, N., and Colijn, H.A. (1981). Oxygen reduction on transition-metal porphyrins in acid electrolyte I. Activity. Ber. Bunsenges. Phys. Chem. 85, 693–700. \n54. Pan, F., Zhang, H., Liu, K., Cullen, D., More, K., Wang, M., Feng, Z., Wang, $\\mathsf{G}_{\\cdot,\\prime}$ Wu, G., and Li, Y. (2018). Unveiling active sites of CO2 reduction on nitrogen-coordinated and atomically dispersed iron and cobalt catalysts. ACS Catal. 8, 3116–3122. \n55. Nørskov, J.K., Rossmeisl, J., Logadottir, A. Lindqvist, L., Kitchin, J.R., Bligaard, $\\top_{\\cdot,\\prime}$ and Jo´ nsson, H. (2004). Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892. \n56. Calle-Vallejo, F., Mart´ınez, J.I., and Rossmeisl, J. (2011). Density functional studies of functionalized graphitic materials with late transition metals for oxygen reduction reactions. Phys. Chem. Chem. Phys. 13, 15639– 15643. \n57. Xu, H., Cheng, D., Cao, D., and Zeng, X.C. (2018). A universal principle for a rational design of single-atom electrocatalysts. Nat. Catal. 1, 339–348. " + }, + { + "id": "10.1126_science.aba1628", + "DOI": "10.1126/science.aba1628", + "DOI Link": "http://dx.doi.org/10.1126/science.aba1628", + "Relative Dir Path": "mds/10.1126_science.aba1628", + "Article Title": "A piperidinium salt stabilizes efficient metal-halide perovskite solar cells", + "Authors": "Lin, YH; Sakai, N; Da, P; Wu, JY; Sansom, HC; Ramadan, AJ; Mahesh, S; Liu, JL; Oliver, RDJ; Lim, J; Aspitarte, L; Sharma, K; Madhu, PK; Morales-Vilches, AB; Nayak, PK; Bai, S; Gao, F; Grovenor, CRM; Johnston, MB; Labram, JG; Durrant, JR; Ball, JM; Wenger, B; Stannowski, B; Snaith, HJ", + "Source Title": "SCIENCE", + "Abstract": "Longevity has been a long-standing concern for hybrid perovskite photovoltaics. We demonstrate high-resilience positive-intrinsic-negative perovskite solar cells by incorporating a piperidinium-based ionic compound into the formamidinium-cesium lead-trihalide perovskite absorber. With the bandgap tuned to be well suited for perovskite-on-silicon tandem cells, this piperidinium additive enhances the open-circuit voltage and cell efficiency. This additive also retards compositional segregation into impurity phases and pinhole formation in the perovskite absorber layer during aggressive aging. Under full-spectrum simulated sunlight in ambient atmosphere, our unencapsulated and encapsulated cells retain 80 and 95% of their peak and post-burn-in efficiencies for 1010 and 1200 hours at 60 degrees and 85 degrees C, respectively. Our analysis reveals detailed degradation routes that contribute to the failure of aged cells.", + "Times Cited, WoS Core": 540, + "Times Cited, All Databases": 567, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000548751700053", + "Markdown": "# SOLAR CELLS \n\n# A piperidinium salt stabilizes efficient metal-halide perovskite solar cells \n\nYen-Hung $\\pmb{\\mathrm{Lin}}^{1\\ast}$ , Nobuya Sakai1, Peimei Da1, Jiaying $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{2}$ , Harry C. Sansom1, Alexandra J. Ramadan1, Suhas Mahesh1, Junliang Liu3, Robert D. J. Oliver1, Jongchul $\\pmb{\\mathrm{lim^{1}}}\\dagger$ , Lee Aspitarte4, Kshama Sharma5, P. K. Madhu5, Anna B. Morales‐Vilches6, Pabitra K. Nayak1,5, Sai Bai7, Feng Gao7, Chris R. M. Grovenor3, Michael B. Johnston1, John G. Labram4, James R. Durrant2,8, James M. Ball1, Bernard Wenger1, Bernd Stannowski6, Henry J. Snaith1\\* \n\nLongevity has been a long-standing concern for hybrid perovskite photovoltaics. We demonstrate high-resilience positive-intrinsic-negative perovskite solar cells by incorporating a piperidinium-based ionic compound into the formamidinium-cesium lead-trihalide perovskite absorber. With the bandgap tuned to be well suited for perovskite-on-silicon tandem cells, this piperidinium additive enhances the open-circuit voltage and cell efficiency. This additive also retards compositional segregation into impurity phases and pinhole formation in the perovskite absorber layer during aggressive aging. Under full-spectrum simulated sunlight in ambient atmosphere, our unencapsulated and encapsulated cells retain 80 and $95\\%$ of their peak and post-burn-in efficiencies for 1010 and 1200 hours at $60^{\\circ}$ and $85^{\\circ}\\mathsf{C}$ , respectively. Our analysis reveals detailed degradation routes that contribute to the failure of aged cells. \n\nT wo-terminal monolithic perovskite-onsilicon tandem cells appear to be one of the most promising photovoltaic technologies for near-term commercial-scale deployment (1, 2). These cells feature a wide bandgap perovskite “top cell” that absorbs in a region of the solar spectrum complementary to that of the silicon “bottom cell,” and such solar cells have been demonstrated with a certified power conversion efficiency (PCE) reaching $29.1\\%$ (3). \n\nThere is often a compromise between achieving high efficiency and long-term stability. The presence of methylammonium (MA) as the A-site cation in the perovskite absorber, which leads to more rapid decomposition under elevated temperature, light exposure, and atmosphere (4), can be alleviated by substitution with formamidinium (FA) or compositions of FA and cesium (Cs) (5–7). However, the use of MA persists in many recent reports on the highestefficiency perovskite cells in the form of the mixed-cation CsFAMA or FAMA perovskites $(\\delta,\\mathcal{O})$ . Also, the organic hole conductor 2,2',7,7'- tetrakis $[N,N\\cdot$ -di(4-methoxyphenyl)amino]- 9,9'-spirobifluorene (Spiro-OMeTAD) and the additives required to deliver high efficiency are detrimental to the stability of perovskite cells (10–12) but are often used in the highest PCE single-junction perovskite cells (9, 12). Finally, molecular passivation of defects in the perovskite absorber is a common route to increase the solar cell efficiency (13) but often introduces additional thermal instabilities. The absorber layers and cells can revert to their unpassivated state after thermal treatment at temperatures as low as $60^{\\circ}$ to $85^{\\circ}\\mathrm{C}$ (9). \n\nThus, efforts are required to simultaneously deliver efficiency enhancements and improve long-term stability. We recently reported that incorporation of an imidazolium-based ionic liquid into positive-intrinsic-negative (p-i-n) perovskite solar cells, which use the triple cation perovskite as the absorber layer and nickel oxide (NiO) as the p-type layer, can improve both efficiency and long-term stability (14). However, the best-quality NiO p-type layers require annealing at ${\\sim}400^{\\circ}\\mathrm{C},$ which makes their integration with Si heterojunction bottom cells challenging, because these bottom cells cannot be processed above $200^{\\circ}\\mathrm{C}$ owing to the sensitivity of the amorphous silicon passivation and charge extraction layers. We also found that this imidazolium-based ionic liquid is incompatible with the use of low-temperature processible organic p-type layers. Moreover, we carried out thermal stability tests in nitrogen at $85^{\\circ}\\mathrm{C}$ and found that, when using NiO p-type layers, the cells were considerably less stable than cells that use poly(4-butylphenyl-diphenylamine) \n\n(polyTPD) as the hole-transport material, which we show in fig. S1. \n\nIn this study, we demonstrate high-performance p-i-n perovskite solar cells using thermally stable CsFA-based lead-halide perovskite absorber layers, low-temperature processed organic charge extraction layers, and the organic ionic solid additive 1-butyl-1-methylpiperidinium tetrafluoroborate ([BMP] $^{+}[\\mathrm{BF_{4}}]^{-})$ ). The incorporation of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ into the perovskite absorber suppressed deep trap states, improved performance, and enhanced the operational stability of cells stressed under full-spectrum sunlight at elevated temperatures up to $85^{\\circ}\\mathrm{C}$ . \n\nWe screened a number of ionic salts as additives for improving the efficiency of perovskite solar cells, with the commonality of having a large chemically stable organic cation and a $\\mathrm{[BF_{4}]}^{-}$ anion. At low concentrations, $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ (see Fig. 1A for the chemical structure) resulted in a particularly positive influence in photovoltaic performance. We depict the device architecture in Fig. 1A, where polyTPD and [6,6]-phenyl- $\\mathrm{.c_{61}}$ -butyric acid methyl ester (PCBM) were used as the holetransporting and electron-transporting layers, respectively. The scanning electron microscopy (SEM) image for a representative p-i-n cell based on a perovskite composition of $\\mathrm{Cs_{0.17}F A_{0.83}P b(I_{0.77}B r_{0.23})_{3}}$ and $0.25\\mathrm{~mol~}\\%$ $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ (with respect to the Pb content) is shown in Fig. 1B. \n\nTo demonstrate the performance enhancement potential of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ , we fabricated mixed halide perovskites with a low Br content $\\mathrm{Cs_{0.17}F A_{0.83}P b(I_{0.90}B r_{0.10})_{3}},$ , which we have found to be the best composition for maximum efficiency of single-junction cells. In Fig. 1C and fig. S2, we show typical current density– voltage $\\left(J\\mathbf{-}V\\right)$ characteristics for the $0.25\\mathrm{mol}\\%$ $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified and control devices, and the statistical results of the device performance parameters are shown in Fig. 1D. A champion $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ device (Fig. 1E) exhibited an open-circuit voltage $(V_{\\mathrm{OC}})$ of $1.12\\mathrm{~V~}$ , a short-circuit current density $(J_{\\mathrm{SC}})$ of $22.8\\ \\mathrm{mA{\\cdot}c m^{-2}}$ , and a fill factor (FF) of 0.79, resulting in a PCE of $20.1\\%$ and a steady-state power output (SPO) of $20.1\\%$ . The corresponding external quantum efficiency (EQE) (fig. S3) yielded an integrated $J_{\\mathrm{SC}}$ with a negligible variation $(\\sim2.5\\%)$ from the measured $J_{\\mathrm{SC}}.$ . The addition of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ in the perovskite light absorber led to very high performance for MA-free single-junction p-i-n perovskite solar cells compared with reports to date (5, 15). \n\nFor a perovskite-on-silicon tandem solar cell, balancing the light absorption between the constituent subcells is key to achieving current matching to maximize PCE (16, 17). Following $(I7)$ , we simulated the evolution of subcell $J_{\\mathrm{SC}}$ values in perovskite-on-silicon tandem cells as a function of absorber layer thickness for perovskite bandgaps of 1.56, 1.66, and 1.76 eV (Fig. 1F). \n\n![](images/092b37343ab9043ca4716dc9b8e8e7a8bff5e90fa2f1c3c9fbac62795e0529d6.jpg) \nFig. 1. Perovskite solar cell characterization. (A) Schematic of the p-i-n perovskite solar cell and the chemical structure of [BMP] $^+[B F_{4}]^{-}$ . BCP, bathocuproine; PCBM, phenyl- $\\mathrm{.c_{61}}$ -butyric acid methyl ester; PolyTPD, poly(4-butylphenyl-diphenylamine); F4-TCNQ, tetrafluoro-7,7,8,8- tetracyanoquinodimethane. (B) SEM image of the full device stack made from $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ with $0.25~\\mathrm{mol}~\\%$ [BMP] $^{+}[\\mathsf{B F}_{4}]^{-}$ . Scale bar, $500~\\mathsf{n m}$ . (C) J-V characteristics of the representative $0.25~\\mathrm{mol}~\\%$ [BMP]+[BF4] modified $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.90}\\mathsf{B r}_{0.10})_{3}$ and control (Ctrl) devices measured from the forward-bias (FB) to short-circuit (SC) scans under simulated air mass 1.5 sunlight and corresponding SPO. (D) Statistical results of device parameters for $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.90}\\mathsf{B r}_{0.10})_{3}$ -based devices. (E) J-V characteristics for the champion \ncell with $0.25\\:\\mathrm{mol}\\:\\%$ [BMP] $^{+}[\\mathsf{B F}_{4}]^{-}$ modified $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.90}\\mathsf{B r}_{0.10})_{3}$ h, power conversion efficiency. (Inset) corresponding SPO and current density measured under SPO $(J_{\\mathsf{S P O}})$ . (F) Modeling of the thickness-dependent subcell $J_{\\mathrm{SC}}$ for perovskite-on-silicon tandem cells with perovskites of different bandgaps. The evolution of perovskite subcell $J_{\\mathrm{SC}}$ is shown in blue, and the corresponding Si subcell $J_{\\mathrm{SC}}$ is shown in red. (G) $J-V$ characteristics of the representative $0.25\\:\\mathrm{mol}\\:\\%$ [BMP] $^+[B F_{4}]^{-}$ modified and control devices using $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ . (H) Corresponding SPO, EQE, and integrated $J_{\\mathrm{SC}}$ for the devices shown in (G). The integrated $J_{\\mathrm{SC}}$ values for the modified and control devices are 18.8 and $19.0\\ m{\\cdot}{\\mathsf{c m}}^{-2}$ , respectively. (I) Statistical results of device parameters for $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ -based devices. \n\nThe ideal thickness for a $1.66\\mathrm{eV}$ bandgap was $\\sim500\\mathrm{nm}$ , which falls into a common perovskite processing window (15). We also modeled the subcell $J_{\\mathrm{SC}}$ with various bandgaps for a ${500-}\\mathrm{nm}$ perovskite layer (fig. S4), and a $\\ensuremath{\\mathrm{1.66~eV}}$ bandgap was also nearly ideal for maximizing energy yield for monolithic perovskiteon-silicon tandem cells deployed in real-world locations (18). \n\nBy tuning the $\\mathrm{I/Br}$ composition, we found that $\\mathrm{Cs_{0.17}F A_{0.83}P b(I_{0.7}B r_{0.23})_{3}}$ perovskite delivered the desired $1.66\\:\\mathrm{eV}$ bandgap, as determined from the derivative of the EQE spectrum, (fig. S5). We optimized the single-junction cells using different $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ concentrations ranging from 0.0 (control) to $0.3\\mathrm{mol}\\%$ ; the device performance parameters from a large batch of cells are summarized in fig. S6. With increasing concentrations of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ , we observed that $V_{\\mathrm{OC}}$ rose from an average of 1.11 $\\mathrm{v}$ for the control device to $>\\mathrm{{l.l6V}}$ for the $0.3\\mathrm{mol}\\%$ $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified device; $J_{\\mathrm{SC}}$ did not vary appreciably relative to the control. However, on average, the FF increased at low concentrations but tended to decrease at higher concentrations of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ . Thus, devices with $0.25~\\mathrm{mol}~\\%$ [BMP] $^{+}\\mathrm{[BF_{4}]^{-}}$ exhibited the highest PCEs. Characteristic $J{-}V$ curves for an optimized $0.25\\mathrm{mol}\\%$ $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified perovskite solar cell and a control device are shown in Fig. 1G, and the corresponding SPOs are shown in Fig. 1H. The corresponding forward and reverse direction $J_{-}V$ scans are shown in fig. S7. The $0.25\\mathrm{mol}\\%$ $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ device exhibited a $V_{\\mathrm{OC}}$ of $1.16~\\mathrm{V}_{:}$ , a $J_{\\mathrm{SC}}$ of $19.5\\ \\mathrm{mA{\\cdot}c m^{-2}}$ , and a FF of 0.77, yielding a PCE of $17.3\\%$ . The control device, which exhibited a lower PCE of $16.6\\%$ , had a $V_{\\mathrm{OC}}$ of 1.11 V and a FF of $0.75$ . The corresponding SPOs were 16.5 and $15.7\\%$ for the modified and control devices, respectively. We show a set of statistical results obtained from 15 individual cells of each type in Fig. 1I. The EQE (Fig. 1H, inset) was in good agreement with the $J_{\\mathrm{SC}}$ measured from the $J.$ -V scans (Fig. 1G). With the addition of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ , the cells generally exhibited an increase in $V_{\\mathrm{OC}},$ FF, and PCE. The $J_{\\mathrm{SC}}$ was similar or slightly higher with the optimum piperidinium content for all perovskite compositions. \n\nTo understand the impact on the optoelectronic characteristics of the perovskite films with the addition $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ , we carried out a series of spectroscopic measurements, including transient photovoltage (TPV) (fig. S8A), charge extraction (fig. S8B), time-resolved photoluminescence (TRPL) (fig. S9A), steady-state photoluminescence (SSPL) (fig. S9B), and transient photoconductivity (TPC) (fig. S10) on half-complete or complete device structures, and time-resolved microwave conductivity (TRMC) (figs. S11 and S12) and in-plane transient photoconductivity (ip-TPC) (fig. S13) on isolated perovskite films. We found that adding $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ did not compromise charge carrier mobilities (figs. S10B, S12, and S13A). Furthermore, from light intensity–dependent $V_{\\mathrm{OC}}$ and charge-extraction measurements of complete devices, we observed a reduced ideality factor and capacitance (or reduced total stored charge density) for the $\\mathrm{\\Delta[BMP]^{+}[B F4]^{-}}$ modified devices under low light intensity (fig. S8B). We also observed a slower TRPL decay and more than double the SSPL intensity in the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ film (fig. S9). These results were consistent with a reduced density of deep trap sites in the $[\\mathrm{BMP]^{+}[\\mathrm{BF4}]^{-}}$ modified devices. Further analysis of the optoelectronic and spectroscopic characterizations is provided in the supplementary text section of the supplementary materials. \n\nTo reveal how $\\mathrm{[BMP]^{+}[B F4]^{-}}$ was distributed within the perovskite layer, we used highresolution nanoscale secondary ion mass spectrometry (nanoSIMS). We present the secondary electron and elemental mapping for the ${}^{19}\\mathrm{F}^{-}$ and $^{11}{\\bf B}^{16}{\\bf O}_{2}^{-}$ distributions in a $\\mathrm{Cs_{0.17}F A_{0.83}P b}$ $(\\mathrm{I_{0.77}B r_{0.23}})_{3}$ perovskite film in Fig. 2, A to C. In Fig. 2A, the $^{19}\\mathrm{F}^{-}$ signals show agglomeration and, despite yielding much lower intensities, the $\\mathrm{^{11}B^{16}O_{2}}^{-}$ intensity map (Fig. 2B) coincided reasonably well with the $^{19}\\mathrm{F}^{-}$ map. We show the three-dimensional (3D) visualization of the entire ${}^{19}\\mathrm{F}^{-}$ dataset in Fig. 2D, where we observed that the ${}^{19}\\mathrm{F}^{-}$ signal originated from roughly spherical regions a few hundred nanometers in diameter that were evenly distributed over the surveyed volume. Both the depth (fig. S14A) and line (fig. S14B) profiles revealed that, in addition to the agglomerates, a small amount of F could be detected throughout the perovskite. \n\nFrom this nanoSIMS characterization, we deduce that most of the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ molecules were localized in isolated aggregates that presumably accumulated between the perovskite domains, but small amounts penetrated the entire volume of the film. This distribution differs from that of the imidazolium-based ionic liquid, which we have previously used with NiO p-type layers. For that material, the predominant accumulation of $\\mathrm{[BF_{4}]^{-}}$ was at the buried NiO-perovskite interface (14). Presumably, the distribution throughout the entire volume of the perovskite film helped the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ ionic salt enhance the performance of the cells when we used the poly-TPD organic hole conductor. We attempted to observe interactions between the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ and the perovskites using solid-state nuclear magnetic resonance (ssNMR) and x-ray photoemission spectroscopy (XPS), which we show in the supplementary text and figs. S15 and S16, respectively. However, we observed no discernible differences between the control and modified samples. \n\nWe also carried out characterizations to assess the stability of the CsFA perovskite compounds after the addition of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ . Ultraviolet-visible (UV-vis) absorption spectra (fig. S17) and x-ray diffraction (XRD) \n\n![](images/b1512e3aaeb4586533931f783b0644ee682afb62bee09cd1a5665cfd9f4a6991.jpg) \nFig. 2. High-resolution secondary ion mass spectrometry and x-ray diffraction analysis. (A and B) $^{19}\\mathsf{F}^{-}$ and $^{11}{\\sf B}^{16}\\bar{0}_{2}^{-}$ ion maps for the F and B distributions toward the top surface of a \\~500-nm $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ with $0.25~\\mathsf{m o l~\\%~[B M P]^{+}[B F_{4}]^{-}}$ perovskite film. (C) Secondary electron map for the sputtered surface morphology ${\\sim}60\\ \\mathsf{n m}$ below the sample surface. The squares denoted in (A) to (C) are to indicate the corresponding regions of highly localized F and B concentrations. (D) A reconstructed 3D map \n\n(stretched in the z direction for clarity) showing the distribution of the $^{19}\\mathsf{F}^{-}$ signals through the perovskite layer. (E and F) XRD series for the gaining of the unencapsulated control and $0.25~\\mathrm{mol}~\\%$ $[\\mathsf{B M P}]^{+}[\\mathsf{B F}_{4}]^{-}$ modified $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ perovskite films, respectively, prepared on FTO glass substrates. The XRD peaks corresponding to $\\mathsf{P b l}_{2}$ $^{\\circ}+$ symbol), FTO (asterisk symbol), and the secondary cubic perovskite phase $\\mathrm{_{\\cdot}}$ symbol) are marked. h, hours. \n\npatterns (Fig. 2, E and F) were obtained for the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified and control $\\mathrm{Cs_{0.17}F A_{0.83}P b(I_{0.77}B r_{0.23})_{3}}$ perovskite films aged under simulated full-spectrum sunlight at $60^{\\circ}\\mathrm{C}$ in ambient air (relative humidity in the laboratory was $\\sim50\\%$ ). The absorption edge of the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified sample exhibited a minor change for the first 264 hours (fig. S17A), whereas the control sample exhibited a clear redshift in the absorption edge, which moved from ${\\sim}750~\\mathrm{nm}$ to ${>}775$ nm (fig. S17B). This redshift in absorption also coincides with a redshift in the EQE spectrum of complete solar cells aged in a similar manner (fig. S18), indicating that a similar change is occurring, albeit at a slower rate, in the complete devices. The XRD measurements did not reveal any noticeable formation of lead halide $(\\sim12.7^{\\circ})$ with aging time for both the control (Fig. 2E) and modified (Fig. 2F) samples, which is usually observed during degradation of MA-containing perovskites because of the loss of methylammonium iodide (4). Conversely, a small $\\mathrm{PbI_{2}}$ peak present at $12.7^{\\circ}$ in both the control and modified films early on disappeared during aging. During the time series, the main perovskite phase peaks broadened (fig. S19) and decreased in intensity, and additional peaks at $14.6^{\\circ}$ and $20.7^{\\circ},$ as well as a low-angle peak at $11.3^{\\circ},$ , appeared during long aging in the control film. \n\nThe broadening of the main phase can be explained by orthorhombic strain. Before aging, we fit the main perovskite phase to an orthorhombic cell in space group Pnma, with lattice parameters of $a=8.801(1)\\mathrm{\\AA},$ , $\\begin{array}{r}{b=8.8329(3)\\mathrm{\\AA},}\\end{array}$ and $c=12.4940(5)\\mathrm{\\AA}$ and a volume of $g_{71.3(2)\\AA^{3}}$ for the control film, and $a=8.8146(3)\\mathrm{\\AA},$ $b=$ $8.8333(9)\\mathrm{\\AA},$ and $c=12.4892(9)\\mathrm{\\AA}$ for the modified film with a larger volume of $972.4(1)\\mathrm{\\AA}^{3}$ . Both are larger than the orthorhombic perovskite $\\upgamma\\mathrm{-CsPbI_{3}}$ [volume $=947.33(5)\\mathrm{\\AA}^{3}](79)$ , indicating the mixed CsFA phase. The lowering of symmetry from cubic to orthorhombic was needed to fit the XRD data well (fig. S20). We refined the orthorhombic unit cell across the aging series and defined the orthorhombic strain as S $(\\%)=$ $100\\times\\sqrt{\\left(\\frac{\\sqrt{2}a}{\\sqrt{2}b}-1\\right)^{2}+\\left(\\frac{\\sqrt{2}b}{c}-1\\right)^{2}+\\left(\\frac{\\sqrt{2}a}{c}-1\\right)^{2}}$ which we show in fig. S21A. The orthorhombic strain in the control and modified films increased at a similar rate; however, the control sample started with a slightly more orthorhombic phase. \n\nThe orthorhombic strain was the only sign of change in the XRD pattern for the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified samples at aging times less than 360 hours. Comparison of spectra showed that the orthorhombic strain did not have a large effect on the absorption. The additional peaks at $\\mathbf{14.6^{\\circ}}$ and $20.7^{\\circ}$ appeared for the control sample after the first aging step of 168 hours and for the modified sample between 264 and 360 hours of aging. These peaks were fitted to a cubic unit cell in the $P m\\Bar{3}m$ space group and could not be fitted with the unit cells of any of the relevant binary halide salts. For the modified sample aged at 360 hours, the cubic unit cell has a volume of 217(1) $\\mathrm{\\AA}^{3}$ , which is within error of the reported volume of $\\mathrm{FAPbBr_{3}}$ $[217.45(2)\\AA^{3}]$ (20). The XRD peaks associated with this second phase are indicated with the ‡ symbol in Fig. 2, E and F, and fig. S22. \n\nSegregation of $\\mathrm{FAPbBr_{3}}$ would leave the main phase rich in Cs and I. Iodide enrichment was consistent with the redshift seen in absorption spectra (fig. S17), and the time at which these phases emerged in the XRD patterns coincides with the timing for the redshift. The volume of the main orthorhombic perovskite phase and the secondary $\\mathrm{FAPbBr_{3}}$ perovskite phase both initially increased over time but started to decrease for the control after the 264-hour aging (fig. S21, B and C). This decrease suggests that after the initial separation of $\\mathrm{FAPbBr_{3}},$ other compositional changes continued, either because of mixing of the halides or external factors. At the same time, the intensity of the main phase peaks decreased, and the decrease was faster in the control sample. The peak at $11.3^{\\circ},$ which appeared in the control sample after 456 hours (fig. S23) but was suppressed in the modified sample, was previously ascribed to the nonperovskite yellow hexagonal ${\\delta\\mathrm{{-FAPbI}_{3}}}$ phase (21, 22), which can form in the perovskite film when the Cs or FA content is strongly unbalanced (7, 21, 23). \n\nIn an attempt to visualize the impurity phases generated during aging, we performed optical microscopy measurements on the fresh and aged control (fig. S24) and $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified (fig. S25) $\\mathrm{Cs_{0.17}F A_{0.83}P b(I_{0.77}B r_{0.23})_{3}}$ perovskite films grown on fluorine-doped tin oxide (FTO) glass. The aged samples were subjected to 500 hours of the same aging environmental parameters that were applied to the XRD samples. The microscope was backlit with a halogen lamp, with optional additional photoexcitation from the front with a ${375-\\mathrm{nm}}$ UV light-emitting diode (LED) to induce photoluminescence. Both the fresh control and $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified films appeared orange-red in color and had wrinkled surface characteristic of the antisolvent quenching spin-coating fabrication method (24) and showed no clear difference with or without UV illumination. After aging, the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified films appeared to be predominantly unchanged. \n\nIn contrast, for the control films, we observed a strong darkening in color and the appearance of large dark domains. Upon UV illumination, these dark domains emitted blue light. The blue emission was consistent with these regions containing some wider gap impurity phase material, most likely the nonperovskite hexagonal ${\\delta\\mathrm{{-FAPbI}_{3}}}$ phase (21, 22). In addition to these coarse features, we observed numerous white or yellow bright spots in images of the aged control samples (fig. S24, C to F). From SEM images of the same samples, which we present in fig. S26, we confirmed that these bright spots were pinholes in the film. The presence of these pinholes in the aged control films, which were absent from the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified films, was a key difference. The addition of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ appeared to have prevented the formation of the blue-emitting impurity phase, inhibited $\\mathrm{FAPbBr_{3}}$ impurity phase growth, and strongly suppressed pinhole formation (fig. S26D). \n\nWe investigated the operational stability of $\\mathrm{Cs_{0.17}F A_{0.83}P b(I_{0.77}B r_{0.23})_{3}}$ -based perovskite solar cells aged at open-circuit condition under fullspectrum sunlight at elevated temperatures in ambient air (relative humidity in the laboratory was $\\sim50\\%$ ). We first examined the stability of unencapsulated devices aged at $60^{\\circ}\\mathrm{C}.$ The average SPOs and PCEs obtained from eight individual devices for each condition are shown in Fig. 3, A and B, respectively, and the evolution of the device parameters is plotted in fig. S27. For both the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified and control devices, we observed a positive lightsoaking effect that enhanced the SPO and PCE values by ${\\sim}2\\%$ absolute during the first few days of aging, whereas the average SPO and PCE of the control devices dropped below the initial performance after $^{72}$ hours and continuously decreased to ${\\sim}5\\%$ absolute efficiency after 216 hours. The efficiency of the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified devices improved over the first few hundred hours, likely because of the photobrightening effect (25) resulting from passivation of defects in the perovskite film via reaction with photogenerated superoxide and peroxide species (26). \n\nOu $\\mathrm{tr}\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified devices remained highly operational, decreasing to $80\\%$ of the peak SPO and PCE $(T_{80,\\mathrm{ave}})$ within an average time of 944 and 975 hours, respectively. We observed that the $V_{\\mathrm{OC}}$ remained beyond its initial level for $>1000$ hours at close to $1.2\\mathrm{V}$ (fig. S27A). The unencapsulated devices appear to be much more stable than the isolated perovskite films aged under the same conditions. This is likely because of the PCBM and BCP electron extraction layer and the CrAu electrode partially encapsulating the perovskite film, by inhibiting ingress of atmosphere and loss of degradation products (10, 27–29). Our champion $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ device exhibited the measured and estimated lifetimes through a linear extrapolation for $80\\%$ of the peak SPO and PCE (i.e., $T_{80,\\mathrm{champ}})$ of 1010 and 2630 hours, respectively (30). The difference in $T_{80,\\mathrm{{champ}}}$ between SPO and PCE originates from nonnegligible hysteresis in the $J_{-}V$ scans from the aged samples (fig. S28). We benchmark our stability results against the long-term stability data from the literature (table S1). Most stability studies are performed on encapsulated cells or cells in an inert atmosphere. Previous reports from unencapsulated cells in ambient atmosphere have delivered $T_{80}$ of ${\\sim}100$ hours under similar aging conditions $(I4)$ , or similar $T_{80}$ lifetimes, but at $25^{\\circ}\\mathrm{C}$ in Colorado at a relative humidity of $15\\%$ , dropping to ${\\sim}30$ hours at $70^{\\circ}\\mathrm{C}$ (12). \n\n![](images/55a9a3ba9e26a30c87a619114de2f417aa4daaab817552a90735bedc6c3cd347.jpg) \nFig. 3. Long-term operational stability. (A) Evolution of SPOs of unencapsulated $0.25~\\mathrm{mol}~\\%$ [BMP] $^+[\\mathsf{B F}_{4}]^{-}$ modified and control (Ctrl) $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ perovskite solar cells (eight cells for each condition), aged under full-spectrum sunlight at $60^{\\circ}\\mathrm{C}$ in ambient air. The $95\\%$ confidence interval for the $\\mathsf{S P O s}$ of the modified devices is shown as a green band. The champion cell with the $[\\mathsf{B M P}]^{+}[\\mathsf{B F}_{4}]^{-}$ additive is indicated with yellow stars, and the black dotted line is a guide to the eye. The intersections between the data points and the black and green dashed-dotted lines show $T_{80,\\mathrm{champ}}$ for the champion cell and $\\bar{T}_{80,\\tt a v e}$ for eight individual \ncells, respectively. (B) Corresponding PCEs for (A). (C) Evolution of SPOs of encapsulated $0.25~\\mathrm{mol}~\\%$ $[\\mathsf{B M P}]^{+}[\\mathsf{B F}_{4}]^{-}$ modified and control $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ cells aged under full-spectrum sunlight at $85^{\\circ}\\mathrm{C}$ in ambient air (six cells for each condition). The early burn-in region ${\\sim}264$ hours) is determined using a linear model (coefficient of determination $R^{2}=96.8\\%)$ . The intersection between the linear extrapolation for the data (red dashed line) and black dotted line estimated the lifetime for $95\\%$ of the post-burn-in SPO (Est. ${\\tau_{\\mathfrak{g}}}_{5,\\mathrm{ave}})$ from six individual cells. (D) Corresponding PCEs for (C). In all figures, the error bars denote standard deviations. \n\nTo explore the stability of our cells under higher elevated temperatures, we sealed them in a nitrogen atmosphere with glass cover slides and UV-cured epoxy resin and aged the encapsulated devices under full-spectrum sunlight at $85^{\\circ}\\mathrm{C}$ in air. Figure S29 shows the evolution of the device parameters. The $J{-}V$ scans for the champion $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ device at different aging stages are shown in fig. S30. At this temperature, a clear burn-in effect was observed in the SPOs (Fig. 3C) and PCEs (Fig. 3D) for both the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified and control devices. The SPO of the control devices decreased rapidly to $<6\\%$ absolute efficiency after 264 hours, whereas the modified devices retained an operational SPO of ${\\sim}12\\%$ absolute over the aging period. We estimated the lifetime of 1200 hours at $95\\%$ of the post-burn-in efficiency $(T_{95,\\mathrm{ave}})$ , using a linear extrapolation of the post-burn-in SPO (Fig. 3C) (14, 30). \n\nMuch variation in aging conditions for perovskite solar cells occurs between laboratories, so it is not feasible to compare results directly. With respect to our previous best-inclass, the $T_{80}$ lifetime of our unencapsulated cells at $60^{\\circ}\\mathrm{C}$ in this study is ${\\sim}7$ times longer (14). The post-burn-in $T_{95,\\mathrm{ave}}$ SPO lifetime of our encapsulated cells at $85^{\\circ}\\mathrm{C}$ was 1200 hours, three times longer than our previous best-inclass cells, which were stressed at $75^{\\circ}\\mathrm{C}$ and gave a $T_{95,\\mathrm{ave}}$ of $\\sim360$ hours (14). Considering that we would expect about a twofold increase in the degradation rate with a $10^{\\circ}\\mathrm{C}$ increase in temperature (31), the cells in this study appear to degrade at approximately one sixth the speed. \n\nTo elucidate the degradation mechanism in complete cells, we carried out XPS analysis on the unencapsulated device stacks, absent of electrodes, before and after a 300-hour lightsoaking aging process at $60^{\\circ}\\mathrm{C}.$ . The XPS spectra of the core levels relevant to the perovskite elements were measured, and full peak positions, spectra, and fittings can be found in figs. S31 to S33 and table S2. Subtle differences between the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ and control devices were observed in the C 1s, N 1s core levels, but these additional peaks correspond to the presence of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ . The $\\mathrm{~I~}3d_{5/2}$ core levels for both the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ and control devices show that aging resulted in the emergence of an additional peak at ${\\sim}620\\mathrm{eV}$ next to the main peak at ${\\sim}618\\ \\mathrm{eV},$ , which is attributed to ${\\boldsymbol{\\mathrm{I}}}^{-}$ . This peak at the higher binding energy could correspond to either the formation of $\\mathrm{{IO_{2}}^{-}}$ , which has been previously observed in methylammonium lead triiodide (32), or to the formation of methyl iodide (33). \n\nThe Pb 4f core level spectra demonstrated a clear difference between the aged devices with and without $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ . In the aged control devices, we observed two peaks at 138.0 and 139.1 eV $\\mathrm{(Pb4f_{7/2})}$ , whereas in the devices with $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ we only observed one peak at 137.8 eV. The peaks at ${\\sim}138~\\mathrm{eV}$ correspond to the presence of $\\mathrm{Pb^{2+}}$ , while the peak at 139.1 eV corresponds to $\\mathrm{PbO_{x}}$ . This result suggests that, when aged, the control devices formed lead oxide, which is a product formed from a photooxidative degradation process (34). The addition of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ inhibited lead oxidation. \n\n![](images/fed9f547f4863c9d40c6aa8b7727d67fe764ab422e05b136ce070308a0b0d18c.jpg) \nFig. 4. Iodine-loss analysis of $\\mathsf{P b l}_{2}$ and perovskite films. (A and B) Topsurface SEM images of $\\mathsf{P b l}_{2}$ films: (A) fresh and (B) aged under ${\\sim}0.32$ suns white LED illumination at $85^{\\circ}\\mathrm{C}$ in a nitrogen-filled glove box for 6 hours. Scale bars, $1\\upmu\\mathrm{m}$ . (C) Schematic of the iodine-loss experimental setup: Vials filled and sealed in nitrogen, containing perovskite films fully submerged in toluene, were exposed to full-spectrum sunlight at $60^{\\circ}\\mathsf{C}$ in \nambient air. (D) Photo of the sealed vials with the control and $0.25~\\mathrm{mol}~\\%$ [BMP] $^+[\\mathsf{B F}_{4}]^{-}$ additive modified $\\mathsf{C s}_{0.17}\\mathsf{F A}_{0.83}\\mathsf{P b}(\\mathsf{I}_{0.77}\\mathsf{B r}_{0.23})_{3}$ perovskite samples, taken after 4 hours of light and heat exposure. (E and F) Ten UV-vis absorbance spectra recorded for the toluene solution taken from the (E) control and (F) [BMP] $^+[\\mathsf{B F}_{4}]^{-}$ vials at different aging times. (G) Evolution of absorbance recorded at $500~\\mathsf{n m}$ . \n\nTo understand how $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ can improve the stability of the perovskite film, we first review the mechanisms that have been proposed to explain the photoinduced degradation processes of metal halide perovskites. The role of oxygen and moisture has been extensively discussed, in particular for MAcontaining perovskites (35–37). However, for perovskite films prepared in inert atmosphere and encapsulated, photodegradation is still observed. A key factor in the photodegradation is the generation of $\\mathrm{I}_{2}$ under illumination, which has been observed experimentally via a range of analytic methods, including electrochemistry (38), optical absorption (38), and mass spectrometry (39). The detrimental role of $\\mathrm{I}_{2}$ has been established for silver electrodes (40) but also directly upon the perovskite (41). \n\nSeveral mechanisms have been proposed to explain the generation of $\\mathrm{I}_{2}$ . They have in common the capture of a hole by an iodide ion $(\\mathrm{I}^{-})$ , with ${\\mathrm{~\\cal~I~}}^{-}$ being either in its lattice site $(\\mathrm{I}_{\\mathrm{I}}^{\\mathrm{x}}+\\mathrm{h}^{\\bullet}\\rightarrow\\mathrm{I}_{\\mathrm{I}}^{\\bullet}$ in Kröger-Vink notation) (26, 42), as an interstitial ion from a Frenkel pair $(\\mathrm{I}_{\\mathrm{i}}^{'}+\\mathrm{h}^{\\bullet}\\rightarrow\\mathrm{I}_{\\mathrm{i}}^{\\mathrm{x}})$ (43), or becoming interstitial upon hole capture $(\\mathrm{I}_{\\mathrm{I}}^{\\mathrm{x}}+\\mathrm{h}^{\\bullet}\\rightarrow\\mathrm{I}_{\\mathrm{i}}^{\\mathrm{x}}+\\mathrm{V}_{\\mathrm{I}}^{\\bullet})$ (38). To generate gaseous iodine $(\\mathrm{{I}_{2}),}$ two neutral atoms $(\\mathrm{I_{i}^{x}}$ or I•) need to diffuse and combine. Owing to the ability to release iodine from the surface of the film, and the likelihood of a higher vacancy density at the surface than in the bulk of the grains, this process is more likely to happen at the surface of the grains, leading to the release of iodine and the generation of a pair of iodide vacancies $(\\mathrm{2V_{I}^{\\bullet}})$ . \n\nThe exact nature of the detrimental effect of $\\mathrm{I}_{2}$ on the perovskite is still under debate (41). Fu et al. investigated these effects in detail and found that $\\mathrm{PbI_{2}}$ was more prone to degradation than the perovskite itself and that voids were left in the films of $\\mathrm{PbI_{2}}$ upon prolonged exposure to light and heat $(44)$ . We repeated Fu et al.’s experiments for the photodegradation of $\\mathrm{PbI_{2}}$ at elevated temperatures under light in a nitrogen atmosphere (figs. S34 and S35) and confirmed the observed generation of lead (fig. S36) and pinholes in the films (Fig. 4, A and B). Although slower than for $\\mathrm{\\mathbf{MA}^{+}}$ - containing perovskites, this degradation pathway was also observed in FACs perovskites, indicating that the $\\mathrm{I}_{2}$ generation process is related to the lead-halide framework. \n\nWe confirmed a faster release of $\\mathrm{I}_{2}$ from our control perovskite films versus the $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ modified films during light soaking, from UV-vis absorption spectrum of toluene, after exposing toluene-submersed films to light and heat (Fig. 4, C to G) (38, 41). The presence of voids (or pinholes, Fig. 4B) in the $\\mathrm{PbI_{2}}$ films (and control perovskite films, fig. S26) after aging can be explained by the loss of volume during $\\mathrm{I}_{2}$ release, upon conversion to metallic lead. The presence of $\\mathrm{PbO}_{\\mathrm{x}}$ in the degraded unencapsulated devices (fig. S32) is also consistent with the formation of metallic lead, with subsequent oxidization to $\\mathrm{PbO_{x}}$ or $\\mathrm{Pb(OH)_{2}}$ in ambient air, which both have a much higher density than the perovskite. \n\nIn light of this degradation mechanism, we discuss the stabilization induced by the ionic additive. For degradation to occur, hole-trapping is likely to require interstitial ${\\boldsymbol{\\mathrm{I}}}^{-}$ (43), and two neutral interstitial iodine atoms need to diffuse together and combine to form $\\mathrm{I}_{2}$ . Therefore, this reaction could be slowed by either reducing the overall density of Frenkel defects (iodide vacancies and/or interstitial pairs) or by reducing the diffusivity of interstitials. As with most crystalline materials, defect densities are usually highest on the crystal surface (45). Therefore, we would expect the interstitials or Frenkel defects to mostly diffuse around the surfaces of the polycrystalline domains, where the highest density of defects exists. \n\nIf crystallization in the presence of $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ leads to reduced Frenkel defect densities, then this would have the effect of reducing the number of sites available for iodide oxidation. Furthermore, if $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ adsorbs to these surface defects, it is likely to block or inhibit the further migration of such defects, slowing down the diffusivity of interstitial iodide or neutral iodine interstitials, reducing the rate of $\\mathrm{I}_{2}$ formation. Finally, $\\mathrm{[BMP]^{+}[B F_{4}]^{-}}$ does appear to reduce the amount of residual $\\mathrm{PbI_{2}}$ in the films, by improving the crystallization (as indicated in Fig. 2). Because $\\mathrm{I}_{2}$ generation occurs preferentially at $\\mathrm{PbI_{2}}$ sites (44), minimizing the amount of residual $\\mathrm{PbI_{2}}$ may play a crucial role. \n\n# REFERENCES AND NOTES \n\n1. W. Chen et al., Adv. Mater. 30, e1800515 (2018). \n2. T. Leijtens, K. A. Bush, R. Prasanna, M. D. McGehee, Nat. Energy 3, 828–838 (2018). \n3. The National Renewable Energy Laboratory, Best Research-Ce Efficiency Chart; www.nrel.gov/pv/cell-efficiency.html. \n4. S. N. Habisreutinger, D. P. McMeekin, H. J. Snaith, R. J. Nicholas, APL Mater. 4, 091503 (2016). \n5. D. P. McMeekin et al., Science 351, 151–155 (2016). \n6. G. E. Eperon et al., Energy Environ. Sci. 7, 982–988 (2014). \n7. J.-W. Lee et al., Adv. Energy Mater. 5, 1501310 (2015). \n8. M. Saliba et al., Energy Environ. Sci. 9, 1989–1997 (2016). \n9. Q. Jiang et al., Nat. Photonics 13, 460–466 (2019). \n10. S. N. Habisreutinger et al., Nano Lett. 14, 5561–5568 (2014). \n11. Y. Hou et al., Science 358, 1192–1197 (2017). \n12. J. A. Christians et al., Nat. Energy 3, 68–74 (2018). \n13. S. N. Habisreutinger, N. K. Noel, H. J. Snaith, R. J. Nicholas, Adv. Energy Mater. 7, 1601079 (2017). \n14. S. Bai et al., Nature 571, 245–250 (2019). \n15. S. H. Turren-Cruz, A. Hagfeldt, M. Saliba, Science 362, 449–453 (2018). \n16. E. Köhnen et al., Sustain. Energy Fuels 3, 1995–2005 (2019). \n17. L. Mazzarella et al., Adv. Energy Mater. 9, 1803241 (2019). \n18. M. T. Hörantner, H. J. Snaith, Energy Environ. Sci. 10, 1983–1993 (2017). \n19. R. J. Sutton et al., ACS Energy Lett. 3, 1787–1794 (2018). \n20. S. Govinda et al., J. Phys. Chem. C 122, 13758–13766 (2018). \n21. W. Rehman et al., Energy Environ. Sci. 10, 361–369 (2017). \n22. Z. Li et al., Chem. Mater. 28, 284–292 (2016). \n23. C. Yi et al., Energy Environ. Sci. 9, 656–662 (2016). \n24. K. A. Bush et al., ACS Energy Lett. 3, 1225–1232 (2018). \n25. D. W. deQuilettes et al., Nat. Commun. 7, 11683 (2016). \n26. J. S. W. Godding et al., Joule 3, 2716–2731 (2019). \n27. K. A. Bush et al., Nat. Energy 2, 17009 (2017). \n28. M. Kaltenbrunner et al., Nat. Mater. 14, 1032–1039 (2015). \n29. R. Prasanna et al., Nat. Energy 4, 939–947 (2019). \n30. M. V. Khenkin et al., Nat. Energy 5, 35–49 (2020). \n31. H. J. Snaith, P. Hacke, Nat. Energy 3, 459–465 (2018). \n32. G. Rajendra Kumar et al., Phys. Chem. Chem. Phys. 18, 7284–7292 (2016). \n33. X. L. Zhou, F. Solymosi, P. M. Blass, K. C. Cannon, J. M. White, Surf. Sci. 219, 294–316 (1989). \n34. Y. X. Ouyang et al., J. Mater. Chem. A. 7, 2275–2282 (2019). \n35. R. Brenes, C. Eames, V. Bulović, M. S. Islam, S. D. Stranks, Adv. Mater. 30, e1706208 (2018). \n36. Z. Andaji-Garmaroudi, M. Anaya, A. J. Pearson, S. D. Stranks, Adv. Energy Mater. 10, 1903109 (2020). \n37. N. Aristidou et al., Nat. Commun. 8, 15218 (2017). \n38. G. Y. Kim et al., Nat. Mater. 17, 445–449 (2018). \n39. Z. N. Song et al., Sustain. Energy Fuels 2, 2460–2467 (2018). \n40. Y. Kato et al., Adv. Mater. Interfaces 2, 1500195 (2015). \n41. S. Wang, Y. Jiang, E. J. Juarez-Perez, L. K. Ono, Y. Qi, Nat. Energy 2, 16195 (2016). \n42. J. Verwey, J. Schoonman, Physica 35, 386–394 (1967). \n43. S. G. Motti et al., Nat. Photonics 13, 532–539 (2019). \n44. F. Fu et al., Energy Environ. Sci. 12, 3074–3088 (2019). \n45. A. Pimpinelli, J. Villain, Physics of Crystal Growth (Cambridge Univ. Press, 2010). \n\n# ACKNOWLEDGMENTS \n\nY.-H.L. thanks N. Noel and W. Li from the University of Oxford (UK) for the discussion on the effect of ionic molecules on perovskites and for assisting with ssNMR sample preparation and optical microscopic imaging, respectively. J. Liu acknowledges the assistance of J. Marrow from the University of Oxford (UK), who provided access to the Avizo software packages to perform 3D virtualization of the nanoSIMS data. Funding: This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) grants EP/S004947/1 and EP/P006329/1. J. Liu and C.R.M.G. are grateful for support for the nanoSIMS facility from EPSRC under grant EP/M018237/1. S.M. is grateful for the support of the \n\nRhodes Scholarship (India and Worcester). R.D.J.O. gratefully acknowledges the Penrose Scholarship for funding his studentship. Author contributions: Y.-H.L. and H.J.S. conceived of the concept, designed the experiments, analyzed the data, and wrote the manuscript. H.J.S. supervised and guided the project. Y.-H.L. performed the fabrication, optimization, and characterization of the perovskite films and solar cells. Y.-H.L. conducted optical microscopy measurements. Y.-H.L. and N.S. conducted UV-vis, XRD, and FTIR characterization and analysis. N.S. performed SEM characterization and material analysis. P.D. and S.B. screened ionic additives and conducted early assessments for single-junction cells. Y.-H.L. and P.D. performed cell thermal-stability measurement on p-type layers. J.W. conducted CE, TPV, and TPC and analyzed the data with J.R.D. H.C.S. conducted analysis on XRD results to deduce degradation mechanism with Y.-H.L. and N.S. A.J.R. performed XPS characterization and analyzed the data with Y.-H.L. and N.S. S.M. performed numerical modeling. J. Liu conducted nanoSIMS characterization and analyzed the results with Y.-H.L., P.K.N., and C.R.M.G. R.D.J.O. conducted EQE measurements and analyzed the data with M.B.J. J. Lim conducted ip-TPC characterization. L.A. and J.G.L. performed TRMC characterization. K.S. and P.K.M. performed ssNMR and analyzed the data with P.K.N. A.B.M.-V. and B.S. contributed to the planning of the experiments to tune the bandgap of the perovskite solar cells and optical modeling. B.W. contributed to degradation mechanism analysis. J.M.B. set up ${\\sf N}_{2}$ aging system, characterized the EQE spectrum of aged devices, and evaluated spectrum mismatch factors. Y.-H.L. analyzed the data with H.J.S. F.G. provided suggestions for ionic additives. All authors discussed the results and contributed to the writing of the paper. Competing interests: H.J.S. is a cofounder, chief scientific officer, and a director of Oxford PV Ltd. Oxford University has filed a patent related to the subject matter of this manuscript. Data and materials availability: All data needed to evaluate the conclusions of the paper are present in the paper or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/369/6499/96/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S36 \nTables S1 to S2 \nReferences (46–80) \n10 November 2019; accepted 5 May 2020 \n10.1126/science.aba1628 \n\n# Science \n\n# A piperidinium salt stabilizes efficient metal-halide perovskite solar cells \n\nYen-Hung Lin, Nobuya Sakai, Peimei Da, Jiaying Wu, Harry C. Sansom, Alexandra J. Ramadan, Suhas Mahesh, Junliang Liu, Robert D. J. Oliver, Jongchul Lim, Lee Aspitarte, Kshama Sharma, P. K. Madhu, Anna B. Morales-Vilches, Pabitra K. Nayak, Sai Bai, Feng Gao, Chris R. M. Grovenor, Michael B. Johnston, John G. Labram, James R. Durrant, James M. Ball, Bernard Wenger, Bernd Stannowski and Henry J. Snaith \n\nScience 369 (6499), 96-102. DOI: 10.1126/science.aba1628 \n\n# Stable perovskites with ionic salts \n\nIonic liquids have been shown to stabilize organic-inorganic perovskite solar cells with metal oxide carrier-transport layers, but they are incompatible with more readily processible organic analogs. Lin et al. found that an ionic solid, a piperidinium salt, enhanced the efficiency of positive-intrinsic-negative layered perovskite solar cells with organic electron and hole extraction layers. Aggressive aging testing showed that this additive retarded segregation into impurity phases and pinhole formation in the perovskite layer. \n\nScience, this issue p. 96 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41467-019-13874-z", + "DOI": "10.1038/s41467-019-13874-z", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-13874-z", + "Relative Dir Path": "mds/10.1038_s41467-019-13874-z", + "Article Title": "Grain structure control during metal 3D printing by high-intensity ultrasound", + "Authors": "Todaro, CJ; Easton, MA; Qiu, D; Zhang, D; Bermingham, MJ; Lui, EW; Brandt, M; StJohn, DH; Qian, M", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Additive manufacturing (AM) of metals, also known as metal 3D printing, typically leads to the formation of columnar grain structures along the build direction in most as-built metals and alloys. These long columnar grains can cause property anisotropy, which is usually detrimental to component qualification or targeted applications. Here, without changing alloy chemistry, we demonstrate an AM solidification-control solution to printing metallic alloys with an equiaxed grain structure and improved mechanical properties. Using the titanium alloy Ti-6Al-4V as a model alloy, we employ high-intensity ultrasound to achieve full transition from columnar grains to fine (similar to 100 mu m) equiaxed grains in AM Ti-6Al-4V samples by laser powder deposition. This results in a 12% improvement in both the yield stress and tensile strength compared with the conventional AM columnar Ti-6Al-4V. We further demonstrate the generality of our technique by achieving similar grain structure control results in the nickel-based superalloy Inconel 625, and expect that this method may be applicable to other metallic materials that exhibit columnar grain structures during AM.", + "Times Cited, WoS Core": 525, + "Times Cited, All Databases": 574, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000511897900003", + "Markdown": "# Grain structure control during metal 3D printing by high-intensity ultrasound \n\nC.J. Todaro 1, M.A. Easton $\\textcircled{1}$ 1, D. Qiu 1, D. Zhang1, M.J. Bermingham $\\textcircled{1}$ 2, E.W. Lui $\\textcircled{1}$ 1, M. Brandt $\\textcircled{1}$ 1, D.H. StJohn $\\textcircled{1}$ 2 & M. Qian1\\* \n\nAdditive manufacturing (AM) of metals, also known as metal 3D printing, typically leads to the formation of columnar grain structures along the build direction in most as-built metals and alloys. These long columnar grains can cause property anisotropy, which is usually detrimental to component qualification or targeted applications. Here, without changing alloy chemistry, we demonstrate an AM solidification-control solution to printing metallic alloys with an equiaxed grain structure and improved mechanical properties. Using the titanium alloy Ti-6Al-4V as a model alloy, we employ high-intensity ultrasound to achieve full transition from columnar grains to fine $(\\sim100\\upmu\\mathrm{m})$ equiaxed grains in AM Ti-6Al-4V samples by laser powder deposition. This results in a $12\\%$ improvement in both the yield stress and tensile strength compared with the conventional AM columnar Ti-6Al-4V. We further demonstrate the generality of our technique by achieving similar grain structure control results in the nickel-based superalloy Inconel 625, and expect that this method may be applicable to other metallic materials that exhibit columnar grain structures during AM. \n\nFagurseia fine-anbtaus efedrd mbey hslemasadolld im–vleiqtmipadonoiulnfst ratfnuardcinsgtoe(ewApMtdemphpreeorlciaeqtsusiredes metal. As a result, the solidification process shows a strong epitaxial growth tendency from layer to layer while the number of nucleation events is limited due to both the absence of potent nucleant particles and the small melt pool volume (consumed quickly by epitaxial growth). This leads to columnar grains along the build direction in most additively manufactured metallic materials, which cause property anisotropy, reduce mechanical performance and increase tendency toward hot tearing. Therefore, a key objective for metal AM is to replace coarse columnar grains with fine, equiaxed grains throughout the part1–4. \n\nThe titanium alloy Ti-6Al-4V is the benchmark alloy of the titanium industry and the most extensively studied alloy for metal $\\mathbf{AM}^{5}$ . In fact, it has essentially been used as a yardstick for assessing the capability of each metal AM process developed to date6. However, Ti-6Al-4V fabricated by different fusion-based AM processes exhibits a strong columnar grain structure7–10. The columnar prior- $\\boldsymbol{\\cdot}\\beta$ grains in AM-fabricated Ti-6Al-4V feature the strong ${\\<}001>$ orientation along the build direction. This gives rise to a $\\upbeta\\rightarrow\\upalpha$ transformation texture8,11–15, which is an important concern for AM qualification16,17 because of the resulting anisotropy of mechanical properties14,15,18–20. In addition, the coarse columnar prior- $\\cdot\\beta$ grains may further degrade the strength of Ti-6Al-4V according to the Hall–Petch relationship established for lamellar $\\mathsf{a{-}}\\upbeta$ Ti-6Al- $4\\mathrm{V}^{21-23}$ (exceptions can exist24). \n\nIntroducing potent nucleant particles by inoculation can realize the columnar-to-equiaxed transition by the Hunt criterion25. Varying the AM process parameters to change the thermal gradient $G$ and growth velocity $V$ in the melt pool has the potential to achieve equiaxed grains as well7. However, the low $G$ values required for equiaxed solidification of metallic alloys are not easily encountered during AM. For example, according to the $G\\mathrm{-}V$ plots established for Ti-6Al- $4\\mathrm{V}^{7}$ and Inconel 718 (ref. 26), it requires one or two orders of magnitude lower $G$ values to realize equiaxed solidification of each alloy during AM. The combination of nucleant particles with process control can enlarge the equiaxed region on the $G\\mathrm{-}V$ plot. This has proved particularly effective for AM of Al-based metals via the addition of $\\mathrm{Al}_{3}(\\mathrm{Sc},\\mathrm{Zr})^{27}$ , $\\mathrm{TiB}_{2}$ (ref. 28), $\\mathrm{Al}_{3}\\mathrm{Zr}$ (ref. 1) and $\\operatorname{TiC}^{29}$ nucleants. Unfortunately, it remains challenging to find a stable and potent nucleant for many commercially important alloys. Ti-6Al-4V is one such alloy. In fact, the introduction of foreign nucleant particles unavoidably changes the chemistry and cleanliness of the alloy. In addition, if the nucleant particles agglomerate together in the liquid metal to form clusters, which is difficult to completely avoid, significant undesired side-effects or consequences can occur in subsequent processing or demanding applications. In that regard, achieving fine equiaxed grains without the assistance of nucleant particles is preferred if practical. \n\nThe application of high-intensity ultrasound to crystallization from liquid to solid can noticeably affect the properties of the crystalline material30. Ultrasonic irradiation of liquids can cause acoustic cavitation: the formation, growth and implosive collapse of bubbles, which occurs instantly in molten metals (0.00003 s) by recent ultrafast in situ synchrotron X-ray imaging of the process31. Bubble collapse emits intense, localized shock waves of temperatures of ${\\sim}5000^{\\circ}\\mathrm{C},$ , pressures of ${\\sim}100\\mathrm{MPa}$ (1000 bar) and heating and cooling rates of ${>}10^{10~\\circ}\\mathrm{C}~s^{-1}$ (ref. 32). Acoustic cavitation during solidification of metal systems agitates the melt to activate nuclei naturally present in the alloy33,34, proving useful in promoting fine equiaxed grains in welding35,36 and traditional casting processes37,38. However, successful suppression of the columnar grain structures during AM by ultrasound has not been reported to date. \n\nBased on our long-term studies of ultrasonic grain refinement of light alloys $^{37,39-\\breve{4}2}$ , we employ high-intensity ultrasound to control the solidification and grain structure of AM-fabricated Ti6Al-4V. This development enables complete transition of columnar prior- $\\cdot\\beta$ grains into equiaxed fine grains $(\\sim100\\upmu\\mathrm{m})$ , leading to a $12\\%$ improvement in both the yield stress and tensile strength. We further demonstrate that the proposed approach applies to AM of nickel-based superalloy Inconel 625, which shows strong columnar grains as well by fusion-based AM43–45, and therefore anticipate that it can equally apply to the AM of other metallic materials. Assessment of the ultrasonic field during AM reveals that the selection of the ultrasound transducer element can be an important practical consideration for ultrasonic grain refinement during large-volume AM and a solution is recommended. \n\n# Results \n\nHigh-intensity ultrasound during AM of titanium alloy Ti6Al-4V. Ti-6Al-4V samples without and with high-intensity ultrasound were prepared using laser-based directed energy deposition (DED). The experimental details are described in the ‘Methods’ section. The ultrasound was introduced into the melt by directly depositing the alloy on the working surface of the Ti6Al-4V sonotrode vibrated at $20\\mathrm{kHz}$ (Fig. 1), where the sonotrode material is chosen to be Ti-6Al-4V (for AM of another alloy, the sonotrode material can be replaced accordingly). The maximum achievable amplitude at the sonotrode face is $30\\upmu\\mathrm{m}$ . The ultrasonic intensity $I$ is defined by34: \n\n![](images/9ed7aed6c4f5579057a80546a42aac2074e989eea9c9fd92a138d8fc2b287a3e.jpg) \nFig. 1 High-intensity ultrasound during metal AM. Cross-sectional schematic showing metal AM by laser-based DED onto an ultrasound sonotrode vibrated at $20k H z$ . The formation of acoustic cavitation and streaming in the liquid metal by high-intensity ultrasound can vigorously agitate the mel during solidification, thereby promoting significant structural modification or refinement. \n\n![](images/2c008ebbddb1e376bce57c3ca02a87aa22d935e2b3fcee8a33d7b872c515f293.jpg) \nFig. 2 Grain refinement of the AM-fabricated Ti-6Al-4V by high-intensity ultrasound. a, b Optical microscopy images of the samples without (a) and with (b) ultrasound. c, d Polarized light microscopy images showing large columnar grains (c) and fine equiaxed grains (d). e, f Histograms of the prior- $\\cdot\\upbeta$ grain size (e) and prior- $\\cdot\\upbeta$ grain aspect ratio (f) for the samples without and with ultrasound measured from traced prior- $\\cdot\\upbeta$ grain images (see Supplementary Fig. 1). The prior- $\\cdot\\upbeta$ grain boundaries in $\\pmb{c}$ and d are traced in white. Scale bars, 1 mm. \n\n$$\nI=\\frac{1}{2}\\rho c(2\\pi f A)^{2},\n$$ \n\nwhere $\\rho$ is the liquid density, $c$ the sound velocity in the liquid, $f$ the frequency and $A$ is the amplitude. The nominal intensity at the sonotrode–melt interface is $>13\\times10^{3}\\mathrm{W}\\mathrm{cm}^{-2}$ at $A=30\\upmu\\mathrm{m}$ , where $\\rho=4208\\mathrm{kg}\\mathrm{m}^{-3}$ (ref. 46) and $c=4407\\mathrm{m}s^{-1}$ (ref. 47) for molten Ti. This value is two orders of magnitude greater than the threshold required for cavitation $(I_{c})$ in molten light metals $(\\sim100\\mathrm{W}\\mathrm{cm}^{-2}$ (ref. 34)), suggesting that the ultrasound applied has the potential to produce significant structural refinement33,34. \n\nMicrostructure. Microstructural analysis reveals a substantial difference between the AM-fabricated Ti-6Al-4V samples with and without ultrasound (Fig. 2). The sample without ultrasound exhibits columnar prior- $\\cdot\\upbeta$ grains of several millimeters in length and ${\\sim}0.5\\mathrm{mm}$ in width traversing multiple deposited layers as expected (Fig. 2a, c). In contrast, the sample with ultrasound shows fine $(\\sim100\\upmu\\mathrm{m})$ , equiaxed prior- $\\cdot\\beta$ grains (Fig. 2b, d). The effect of ultrasound on grain refinement can be evaluated by examining the change in the prior- $\\cdot\\upbeta$ grain number density, which is directly correlated to nucleation48. The prior- $\\cdot\\upbeta$ grain number density increases from $3.3\\mathrm{mm}^{-2}$ to $65.0\\mathrm{m}\\mathrm{\\bar{m}}^{-2}$ by ultrasound, confirming that ultrasound enhances nucleation during solidification. The distribution of both the prior- $\\cdot\\upbeta$ grain size and prior- $\\upbeta$ grain aspect ratio changes dramatically by ultrasound (Fig. 2e, f), reflecting the much-improved prior- $\\cdot\\upbeta$ grain structure homogeneity. \n\nTo further identify the effect of high-intensity ultrasound on the AM-fabricated Ti-6Al-4V microstructure, the samples with and without ultrasound were analyzed by scanning electron microscopy (SEM). A basketweave-like $\\mathsf{a}{-}\\upbeta$ microstructure is observed inside the prior- $\\upbeta$ grains in both cases (Fig. 3a–d). The $\\mathtt{a}$ -lath thickness is similar along the build height with and without ultrasound (see Supplementary Fig. 2). Additionally, no statistical difference is identified in the distribution of the $\\mathtt{a}$ -lath thickness between the samples without and with ultrasound (Fig. 3e, f). This suggests that the thermal conditions during the $\\beta\\to{\\mathfrak{a}}$ transformation that control the scale of the $\\mathsf{a}{-}\\upbeta$ microstructure are largely unaffected by ultrasound. This is not surprising as ultrasound, at the intensity level applied, is not expected to affect the solid-state transformation in metallic alloys. \n\nTo assess any potential change in crystallographic texture, electron backscatter diffraction (EBSD) analysis was applied to Ti-6Al-4V samples additively manufactured with and without ultrasound. The results are summarized in Fig. 4. Without ultrasound, the α phase exhibits a clear crystallographic orientation with a maximum multiples of uniform distribution (MUD) value of 4.5 (a measure of the crystallographic preferred orientation strength; maximum $\\mathrm{{MUD}}\\stackrel{\\cdot}{=}1.0$ corresponds to a random texture). More specifically, without ultrasound, the $c$ -axis of many of the α crystals is tilted ${\\sim}45^{\\circ}$ about the columnar or growth direction of the $\\upbeta$ phase (Fig. 4a, e), measured from the pole figure. This texture has been reported previously8,11–15. With ultrasound, the maximum MUD value is reduced from 4.5 to 2.0 (Fig. 4c, f), substantially weakening the texture of the α phase. \n\n![](images/f137b903c0f94defdafbea903c23170a830c50eb59641324b432705b913892d0.jpg) \nFig. 3 Microstructure characterization of the AM-fabricated Ti-6Al-4V with and without high-intensity ultrasound. a–d SEM images showing the $\\alpha-\\beta$ structure inside the prior- $\\upbeta$ grains of the samples without (a, c) and with (b, d) ultrasound. e, f Histograms of the $\\mathbf{\\alpha}\\propto$ -lath thickness of the samples without (e) and with $(\\pmb{\\uparrow})$ ultrasound. The prior- $\\boldsymbol{\\cdot}\\boldsymbol{\\upbeta}$ grain boundaries in a and b are traced in white. Scale bars, $50\\upmu\\mathrm{m}$ in a, b and $5\\upmu\\mathrm{m}$ in c, d. \n\nIn the case of the prior- $\\boldsymbol{\\cdot}\\beta$ grains, without ultrasound, the majority of the prior- $\\upbeta$ grains analyzed show a strong ${<}001>$ crystallographic orientation (maximum $\\mathrm{MUD}=6.0$ ; Fig. 4b, g), consistent with previous studies8,11–15. With ultrasound, the maximum MUD value for the prior- $\\upbeta$ grains is reduced from 6.0 to 2.7 (Fig. 4d, h), and the resulting equiaxed prior- $\\boldsymbol{\\cdot}\\beta$ grain structure (Fig. 4d) has effectively avoided the characteristic ${<}001>$ texture, while no other preferred texture is detected. These observations are consistent with the understanding that an equiaxed grain structure has no preferred crystallographic texture. \n\nTensile properties. Tensile engineering stress–strain curves (Fig. 5a and Supplementary Fig. 3) show that the yield stress $\\sigma_{\\mathrm{y}}$ and tensile strength $\\sigma_{\\mathrm{TS}}$ of the as-built Ti-6Al-4V are both increased by ${\\sim}12\\%$ by ultrasound (e.g., from $980~\\pm~13~\\mathrm{MPa}$ to $1094\\pm18$ MPa for $\\sigma_{\\mathrm{y}},$ detailed tensile properties are listed in Supplementary Table 1). It should be stressed that the enhanced tensile properties are achieved without increasing the impurity levels of the alloy (see Supplementary Table 2). Both groups of samples show a strain-to-failure (ε) value of ${\\sim}5\\%$ , which is typical of as-built DED-processed Ti-6Al- $4\\mathrm{V}^{49,50}$ . Small pores are found on the fracture surfaces (see Supplementary Fig. 4a, b). Additionally, lack-of-fusion defects perpendicular to the build direction are visible on the polished cross-sections (see Supplementary Fig. 4c, d). The presence of such defects deteriorates the tensile ductility of DED-processed Ti-6Al- $4\\mathrm{V}^{49,50}$ . \n\nTo put the strength improvement by ultrasound into context, the change in yield stress of AM-fabricated Ti-6Al-4V by ultrasound vs. that by chemical approaches is plotted in Fig. 5b and also listed in Supplementary Table 3. Deploying ultrasound, without modifying alloy composition, results in a greater increase in yield stress than alloying with $\\mathbf{B}^{51}$ , $\\mathrm{LaB}_{6}$ (ref. 51) and $C^{52}$ . \n\nA recent study has revealed that texture can affect the tensile yield stress of additively manufactured $\\mathsf{a{-}}\\upbeta$ Ti-6Al-4V by $3-5\\%^{15}$ . This is less than half of the percentage increase in the yield stress observed in Fig. 5a $(\\sim12\\%)$ . To understand the major contributing factor to this increase, Fig. 5c plots the literature data9,10,14,19,20,23,53–57 and our experimental data on the yield stress of AM-fabricated $\\mathsf{a}{-}\\upbeta$ Ti-6Al-4V vs. the inverse square root of the prior- $\\cdot\\beta$ grain size $(d)$ (see Supplementary Table 4 for the detailed data). An approximate Hall–Petch relationship is observed. This implies that the resulting equiaxed prior- $\\cdot\\beta$ grain size has played a major role in improving the yield stress in this study $(\\sim7\\%$ out of the total $12\\%$ of increase). \n\nWe note that post-AM heat treatments below the $\\upbeta$ -transus temperature including hot isostatic pressing are often applied to Ti-6Al-4V for improved strength–ductility combinations and property consistency8,9. Such heat treatments do not change the prior- $\\upbeta$ grain structures7,10,14. Hence, the effect of the ultrasoundinduced microstructural changes, i.e., the equiaxed prior- $\\cdot\\beta$ grains, reduced prior- $\\upbeta$ grain size and substantially weakened texture, on mechanical properties shown in Fig. 5, is expected to survive after common post-AM heat treatments. \n\nExtension to further alloy systems. To test the generality of our approach, we have similarly applied high-intensity ultrasound to AM of Inconel 625 using a custom-made stainless-steel 4140 sonotrode (see details in the ‘Methods’ section). The sample fabricated without ultrasound exhibits columnar primary $\\upgamma$ grains of $500\\upmu\\mathrm{m}$ in length and $150\\upmu\\mathrm{m}$ in width with a strong ${\\tt<}001>$ texture (Fig. 6a, c and Supplementary Fig. 5). In contrast, the application of ultrasound produces predominately equiaxed primary $\\upgamma$ grains of only a few microns in size (much finer than Ti6Al-4V) with a near random crystallographic texture (Fig. 6b, d). This confirms the generality of the ultrasonic approach for AM of different metallic materials. \n\n![](images/d8bad0e9c4b379f88ca2dd46a16c6e7091f6a65d8163710d789c3d9a64d600ee.jpg) \nFig. 4 Texture changes in AM-fabricated Ti-6Al-4V by high-intensity ultrasound. a, c Inverse pole figure maps along the build direction $(z)$ for the $\\upalpha$ phase (measured by EBSD) in samples without (a) and with (c) ultrasound. b, d Inverse pole figure maps along the build direction $(z)$ for the $\\upbeta$ phase (reconstructed from the $\\upalpha$ phase maps in a and c) in samples without (b) and with (d) ultrasound. e, f {0001} contoured pole figures (in MUD: multiples of uniform distribution) of the measured $\\upalpha$ phase in samples without (e) and with (f) ultrasound. g, h {001} contoured pole figures (in MUD) of the reconstructed $\\upbeta$ phase in samples without $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ and with ${\\bf\\Pi}({\\bf h})$ ultrasound. Black lines in b and d indicate high angle grain boundaries (misorientation ${>}10^{\\circ};$ . Scale bars, $250\\upmu\\mathrm{m}$ . \n\nTo further showcase the capability of our approach for solidification control during AM, we fabricated a microstructurally graded Inconel 625 sample that exhibits an alternating columnar/equiaxed/columnar grain structure along its build height, as shown in Fig. 6e. This was achieved by simply turning on and off the high-intensity ultrasound during AM. The approach thus also offers an alternative means of fabricating graded grain structures during AM. \n\ninsights into the potential practical application of ultrasonic grain refinement of alloys made by AM. The sonotrode working face (made of Ti-6Al-4V) is in resonance at the frequency of the piezoelectric transducer when the initial sonotrode length $z_{0}$ is maintained (Fig. 7a). The effective length of the Ti-6Al-4V sonotrode increases by the sample build height $z$ during AM, where the sample being built is also Ti-6Al-4V by design (the same concept can apply to the AM of other alloys). Consequently, the AM-fabricated part oscillates with different amplitude $A$ values along the sample build height $z$ as a result of changing resonance conditions. The amplitude $A$ as a function of the build height $z$ can be described by a wave equation: \n\n$$\nA(z)=A_{0}c o s\\frac{2\\pi f}{\\nu}z,\n$$ \n\n# Discussion \n\nThe high-intensity ultrasonic field during AM of Ti-6Al-4V is analyzed as a function of build height to gain fundamental \n\nwhere $A_{0}$ is the amplitude at the sonotrode working face $(30\\upmu\\mathrm{m})$ and $\\nu$ is the sound velocity in solid Ti-6Al-4V ( ${\\bf\\Pi}^{'}{\\sim}0.2\\mathrm{-}0.25$ inch $\\upmu\\mathrm{s}^{-1}$ or ${\\sim}5000{\\-}6100\\ \\mathrm{m}s^{-1}$ (refs. 58,59)). \n\n![](images/4c9abbb4289fa9665ec86a45cdd9e7bcb260803ab50939cace3d05c8fd9a68d0.jpg) \nFig. 5 Tensile properties of AM-fabricated Ti-6Al-4V. a Engineering stress–strain curves of the as-built samples without and with ultrasound (all curves are shown in Supplementary Fig. 3). The error bars represent one standard deviation of three tests. b Change in yield stress of AM-fabricated Ti-6Al-4V by chemical addition51,52 compared to ultrasound in this work. See Supplementary Table 3 for data and references. c Tensile yield stress with the inverse of square root of prior- $\\upbeta$ grain size from the literature9,10,14,19,20,23,53–57 and this work. See Supplementary Table 4 for data and references. The solid line in c represents the Hall-Petch line $(\\sigma_{\\boldsymbol{\\mathsf{y}}}=\\sigma_{0}+k d^{-1/2}$ , $\\sigma_{0}$ : friction stress; k: material constant; d: grain size) of best fit while the dashed lines define $\\pm0.15\\sigma_{0}$ (where $\\sigma_{0}=710\\ \\mathsf{M P a})$ along the linear fit. \n\n![](images/5f92c6241bfa30f84049ce366dce1fdf938508e0910b84dbc9ef5a22fa669d6e.jpg) \nFig. 6 AM of Inconel 625 with and without high-intensity ultrasound. a, b Inverse pole figure maps along the build direction $(z)$ for the $\\boldsymbol{\\upgamma}$ phase in samples without (a) and with (b) ultrasound. c, d {001} contoured pole figures (in MUD: multiples of uniform distribution) of the $\\boldsymbol{\\upgamma}$ phase in samples without (c) and with (d) ultrasound. The contoured pole figure in c was obtained using the larger area EBSD data provided in Supplementary Fig. 5. e Inverse pole figure map along the build direction $(z)$ of a sample fabricated by turning the ultrasound on and off during AM. Scale bars, $250\\upmu\\mathrm{m}$ . \n\nBy combining Eqs. (1) and (2), the ultrasound intensity $I$ as a function of the build height $z$ is given by: \n\n$$\nI(z)={\\frac{1}{2}}\\rho c\\biggl(2\\pi f A_{0}\\cos{\\frac{2\\pi f}{\\nu}}z\\biggr)^{2}.\n$$ \n\nThe intensity $(I)$ values calculated from Eq. (3) up to a build height of $500\\mathrm{mm}$ are plotted in Fig. 7b, which vary in a wavelike pattern with a periodicity of $\\mathord{\\sim}125\\mathrm{mm}$ . The intensity applied during AM of a $10\\mathrm{-mm}$ high Ti-6Al-4V sample remains effectively constant and is two orders of magnitude greater than the threshold for acoustic cavitation, which is essential for significant ultrasonic grain refinement33,34. These results can therefore be used to explain the experimental observations of the $10\\mathrm{-mm}$ high Ti-6Al-4V sample with high-intensity ultrasound, which shows fine equiaxed prior- $\\upbeta$ grains along its height. \n\n![](images/6b524cd3c8a2580adb7e8a3c001bf9058525730cc1e688db6ae65bbeb15eb055.jpg) \nFig. 7 High-intensity ultrasound conditions during AM of Ti-6Al-4V. a Change in amplitude by Eq. (2) versus the vertical axis of the acoustic system. b Change in intensity by Eq. (3) versus build height. The red dashed line in b corresponds to the intensity required to overcome the cavitation threshold in molten light metals $(I_{\\mathrm{c}}\\geq100\\mathsf{W}\\mathsf{c m}^{-2}$ (ref. 34)). The gray regions in b denote when cavitation is non-operative. \n\nThe ultrasound intensity $(I)$ initially drops from the peak value to zero when the build height increases from zero to ${\\sim}62.5\\mathrm{mm}$ (the acoustic half wavelength, Fig. 7b) and then returns to the peak value when the build height reaches the acoustic wavelength $(\\sim125\\mathrm{mm})$ . This pattern repeats itself when the build height increases further (Fig. 7b). Consequently, the ultrasound intensity $I$ required to produce cavitation for structural refinement is intermittently unsatisfied. This reveals the limitation of using a piezoelectric transducer, which is unable to maintain a constant amplitude A with sample build height $z$ . To overcome this problem, it is better to use a magnetostrictive transducer that can be automatically tuned to the variable resonance condition by adjusting the frequency. This, coupled to a specially designed slotted block sonotrode with a wide output face, would enable the peak intensity to be maintained with build height and facilitate grain refinement throughout large AM-fabricated parts. However, it should be noted that the geometry of the additively manufactured components may affect the ultrasonication conditions, which could become a practical concern when fabricating complex shapes and deserves further investigation. \n\nFor conventional ultrasonic grain refinement in a large volume of melt, the basic grain refinement mechanisms are generally clear, i.e., cavitation is essential for the production of a large number of nuclei or crystallites (up to four different mechanisms may be operative34,40)31,60–62, while acoustic streaming is important for their distribution from the sonotrode region to the rest of the melt63,64. Due to the very small melt pool $\\left(\\sim0.8\\mathrm{mm}\\right)$ during AM, the distribution effect of acoustic streaming on grain refinement can be assumed to be minimal, because the entire small melt pool is effectively ultrasonicated. As detailed in Supplementary Note 1, the DED process employed in this study offers far more than sufficient time for cavitation to occur $(\\sim0.00003\\ s)$ in the melt pool. On the other hand, the ultrasound intensity employed in this study far exceeds the threshold for cavitation in molten Ti-6Al-4V, estimated according to the surface tension of molten Ti-6Al-4V $(\\sim1.05\\mathrm{N}\\mathrm{m}^{-1})$ during AM, compared with that of molten Al $({\\sim}0.9\\mathrm{N}\\mathrm{m}^{-1})$ and the detailed measurements of cavitation in molten Al by $\\mathrm{Eskin}^{34}$ . In that regard, cavitation can be assumed to be the predominant reason for the grain refinement observed. \n\nFinally, this work is restricted to DED for ultrasonic grain refinement during AM. Previous studies have shown that stimulating solidification control during wire-fed welding processes is possible by ultrasonically vibrating the weld $\\mathrm{pool}^{\\tilde{3}5,\\tilde{6}5}$ . Since both wire-fed welding and wire-fed AM deposition processes share similar fundamental principles, we anticipate that the scheme presented in this study can be extended to wire-fed AM processes. However, the vibrating sonotrode may risk disrupting the layer of powder after recoating on a powder bed fusion AM system. In that regard, the inoculation path for grain refinement may be more applicable to metal AM by powder bed fusion processes. \n\nTo conclude, high-intensity ultrasound has been used to address a long-standing problem in metal AM, namely strong epitaxial growth facilitating the formation of columnar grains oriented along the build direction. Herein, the application of ultrasound during AM of Ti-6Al-4V enables the formation of a fully equiaxed structure, which improves the microstructural homogeneity, significantly reduces the prior- $\\cdot\\beta$ grain size and substantially weakens the solidification texture. This work highlights the important role of prior- $\\cdot\\beta$ grain refinement in the tensile properties of AM Ti-6Al-4V. Assessment of the ultrasonic conditions reveals that the selection of the ultrasound transducer element can be an important practical consideration for structural refinement of large-volume AM-fabricated parts and the use of a magnetostrictive transducer is recommended. To assess the generality of our approach, the ultrasonic grain refinement method is successfully applied to the AM of Inconel 625, including the creation of an alternating columnar/equiaxed/ columnar Inconel 625 grain structure along the build height by simply switching on and off the ultrasound during AM. We expect that this technique can be extended to the AM of other metallic materials. \n\n# Methods \n\nSample preparation. Gas-atomized extra low interstitial (ELI) grade Ti-6Al-4V powder of $45{\\mathrm{-}}90\\upmu\\mathrm{m}$ was used for AM by a laser-based DED system (Trumpf, TruLaser Cell 7020). Samples consisted of $10\\mathrm{mm}\\times10\\mathrm{mm}\\times10\\mathrm{mm}$ cubes for microstructural examination and $24\\:\\mathrm{mm}\\times8\\:\\mathrm{mm}\\times10\\:\\mathrm{mm}$ (length, width and height) blocks for tensile testing. The samples without high-intensity ultrasound were built on a Ti-6Al-4V plate using a laser power of $250\\mathrm{W}$ , laser spot size of 0.61 mm, scan speed of $600\\mathrm{{minmin^{-1}}}$ and overlap ratio of $50\\%$ . The ultrasound provides additional input power to the melt in the form of acoustic power. To prevent overheating of the melt pool, the laser power was reduced from $250\\mathrm{W}$ to $150\\mathrm{W}$ by keeping other parameters unchanged. The samples were built on the working face of a $25\\mathrm{-mm}$ diameter Ti-6Al-4V sonotrode (Fig. 1). Detailed optical microscopy analysis has revealed that the porosity on the polished cross-sections of the Ti-6Al-4V samples with and without ultrasound was similar, in the range of $0.7{-}0.9\\ \\mathrm{area\\%}$ (see Supplementary Fig. 6). The sonotrode working face was driven by a 500-W piezoelectric transducer (Sonic Systems, L500) operating at $20\\mathrm{kHz}$ . \n\nGas-atomized Inconel 625 powder of $45{\\mathrm{-}}90\\upmu\\mathrm{m}$ was used for AM of Inconel 625 by laser-based DED (Trumpf, TruLaser Cell 7020). Cuboidal samples with dimensions of $10\\mathrm{mm}\\times10\\mathrm{mm}\\times5\\mathrm{mm}$ (length, width, height) were built for microstructural characterization. The sample without high-intensity ultrasound was built on a 4140 stainless-steel plate using a laser power of $300\\mathrm{W}$ , laser spot size of $0.61\\mathrm{mm}$ , scan speed of $600\\mathrm{{mm}\\mathrm{{min^{-1}}}}$ and overlap ratio of $50\\%$ . The sample with ultrasound was built on a $25\\mathrm{-mm}$ diameter 4140 stainless-steel sonotrode using the same parameters for the sample without ultrasound, other than a reduced laser power of $120\\mathrm{W}$ . \n\nChemical analysis using inductively coupled plasma-atomic emission spectroscopy (ICP-AES) and LECO combustion was done on the Ti-6Al-4V samples with and without high-intensity ultrasound to evaluate if any extra interstitial solute was introduced into the melt during ultrasonic irradiation. This is because an increase in interstitial content may account for both grain refinement due to constitutional supercooling66 and increased strength through solid solution strengthening67. The results indicate that there was negligible additional interstitial pickup by ultrasound (see Supplementary Table 2). \n\nMicrostructure characterization and tensile testing. The Ti-6Al-4V cube samples were cut in half along the build direction and prepared for microstructural characterization by standard techniques with final polishing by $0.04\\upmu\\mathrm{m}$ colloidal silica suspension. The microstructure was first examined by SEM (FEI, Verios 460L) in the backscattered electron mode. Then the samples were etched with Kroll’s reagent and examined by optical microscopy under polarized light to distinguish the prior- $\\cdot\\beta$ grains by their crystal orientation68. The prior- $\\upbeta$ grain boundaries were manually traced and the total number of prior- $\\cdot\\upbeta$ grains within each view was divided by the area to obtain the prior- $\\cdot\\beta$ grain number density $(\\mathrm{m}\\mathrm{m}^{-2})$ ). The images of the traced prior- $\\cdot\\beta$ grains (see Supplementary Fig. 1c, d) were analyzed using ImageJ software69 to obtain statistical distributions of the prior- $\\upbeta$ grain size and prior- $\\cdot\\beta$ grain aspect ratio. Lamellar spacing measurements were made on SEM images taken along the build height of each sample by the linear intercept method. Three fields of view were analyzed at each build height resulting in ${\\sim}40\\$ line segments per data point. EBSD analysis (accelerating voltage of $20\\mathrm{kV}$ , probe current of $13\\mathrm{nA}$ , step size of $0.5\\upmu\\mathrm{m}$ , working distance of $15\\mathrm{mm}$ and sample-tilt angle of $70^{\\circ}$ ) was conducted using a scanning electron microscope (JEOL, JSM-7200F) equipped with an EBSD detector (Oxford Instruments, NordlysMax2). A montage of 56 individual tiles of EBSD data comprising a total area of ${\\sim}0.6\\ \\mathrm{mm}\\times1.2$ mm per sample was used to obtain the texture data. The orientation information of the $\\upbeta$ phase was reconstructed from the α phase EBSD data using the software package $\\mathrm{ARPGE}^{70}$ . \n\nThe Inconel 625 samples were sectioned along the build direction and prepared for microstructural characterization by standard techniques with final polishing by $0.04\\upmu\\mathrm{m}$ colloidal silica suspension. Microstructural analysis was conducted by EBSD (accelerating voltage of $20\\mathrm{kV}$ , probe current of 16 nA, step size of $1.5\\upmu\\mathrm{m}$ (Fig. 6a and Supplementary Fig. 5) or $0.5\\upmu\\mathrm{m}$ (Fig. 6b, e), working distance of $15\\mathrm{mm}$ and sample-tilt angle of $70^{\\circ}$ ) using a scanning electron microscope (JEOL, JSM-7200F) equipped with an EBSD detector (Oxford Instruments, NordlysMax2). \n\nThe as-built Ti-6Al-4V block samples were cut into flat tensile specimens transverse to the build direction with a gauge length of $12\\mathrm{mm}$ , width of $2\\mathrm{mm}$ and thickness of $1\\mathrm{mm}$ . Tensile testing with an initial strain rate of $2.5\\times10^{-4}{{\\sf s}}^{-1}$ was performed on three specimens per condition using a universal testing machine (MTS, 810) equipped with a non-contact laser extensometer (MTS, LX500). \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 30 March 2019; Accepted: 4 December 2019; Published online: 09 January 2020 \n\n# References \n\n1. Martin, J. H. et al. 3D printing of high-strength aluminium alloys. Nature 549, \n365–369 (2017). \n2. Barriobero-Vila, P. et al. Peritectic titanium alloys for 3D printing. Nat. Commun. 9, 3426 (2018). \n3. Bermingham, M. J., StJohn, D. H., Krynen, J., Tedman-Jones, S. & Dargusch, M. S. Promoting the columnar to equiaxed transition and grain refinement of titanium alloys during additive manufacturing. Acta Mater. 168, 261–274 (2019). \n4. DebRoy, T. et al. Scientific, technological and economic issues in metal printing and their solutions. Nat. Mater. 18, 1026–1032 (2019). \n5. Polmear, I., StJohn, D. H., Nie, J.-F. & Qian, M. Light Alloys: Metallurgy of the Light Metals. (Butterworth-Heinemann, Oxford, 2017). \n6. Qian, M., Xu, W., Brandt, M. & Tang, H. P. Additive manufacturing and postprocessing of Ti-6Al-4V for superior mechanical properties. MRS Bull. 41, \n775–783 (2016). \n7. Kobryn, P. A. & Semiatin, S. L. The laser additive manufacture of Ti-6Al-4V. JOM 53, 40–42 (2001). \n8. Al-Bermani, S. S., Blackmore, M. L., Zhang, W. & Todd, I. The origin of microstructural diversity, texture, and mechanical properties in electron beam melted Ti-6Al-4V. Metall. Mater. Trans. A 41a, 3422–3434 (2010). \n9. Vilaro, T., Colin, C. & Bartout, J. D. As-fabricated and heat-treated microstructures of the Ti-6Al-4V alloy processed by selective laser melting. Metall. Mater. Trans. A 42a, 3190–3199 (2011). \n10. Bermingham, M. J., Nicastro, L., Kent, D., Chen, Y. & Dargusch, M. S. Optimising the mechanical properties of Ti-6Al-4V components produced by wire plus arc additive manufacturing with post-process heat treatments. J. Alloys Compd. 753, 247–255 (2018). \n11. Kobryn, P. A. & Semiatin, S. L. Microstructure and texture evolution during solidification processing of Ti-6Al-4V. J. Mater. Process. Technol. 135, 330–339 (2003). \n12. Antonysamy, A. A., Meyer, J. & Prangnell, P. B. Effect of build geometry on the $\\upbeta$ -grain structure and texture in additive manufacture of Ti-6Al-4V by selective electron beam melting. Mater. Charact. 84, 153–168 (2013). \n13. Simonelli, M., Tse, Y. Y. & Tuck, C. On the texture formation of selective laser melted Ti-6Al-4V. Metall. Mater. Trans. A 45a, 2863–2872 (2014). \n14. de Formanoir, C., Michotte, S., Rigo, O., Germain, L. & Godet, S. Electron beam melted Ti–6Al–4V: microstructure, texture and mechanical behavior of the as-built and heat-treated material. Mater. Sci. Eng. A 652, 105–119 (2016). \n15. Hayes, B. J. et al. Predicting tensile properties of Ti-6Al-4V produced via directed energy deposition. Acta Mater. 133, 120–133 (2017). \n16. F42 Committee. WK49229 New Guide for Orientation and Location Dependence Mechanical Properties for Metal Additive Manufacturing (ASTM International, 2015). \n17. Seifi, M., Salem, A., Beuth, J., Harrysson, O. & Lewandowski, J. J. Overview of materials qualification needs for metal additive manufacturing. JOM 68, 747–764 (2016). \n18. Yang, J. J., Yu, H. C., Wang, Z. M. & Zeng, X. Y. Effect of crystallographic orientation on mechanical anisotropy of selective laser melted Ti-6Al-4V alloy. Mater. Charact. 127, 137–145 (2017). \n19. Simonelli, M., Tse, Y. Y. & Tuck, C. Effect of the build orientation on the mechanical properties and fracture modes of SLM Ti-6Al-4V. Mater. Sci. Eng. A 616, 1–11 (2014). \n20. Carroll, B. E., Palmer, T. A. & Beese, A. M. Anisotropic tensile behavior of Ti6Al-4V components fabricated with directed energy deposition additive manufacturing. Acta Mater. 87, 309–320 (2015). \n21. Sen, I., Tamirisakandala, S., Miracle, D. & Ramamurty, U. Microstructural effects on the mechanical behavior of B-modified Ti-6Al-4V alloys. Acta Mater. 55, 4983–4993 (2007). \n22. Tan, X. et al. Graded microstructure and mechanical properties of additive manufactured Ti-6Al-4V via electron beam melting. Acta Mater. 97, 1–16 (2015). \n23. Ren, Y. M. et al. Microstructure and deformation behavior of Ti-6Al-4V alloy by high-power laser solid forming. Acta Mater. 132, 82–95 (2017). \n24. Kar, S. et al. Modeling the tensile properties in $\\upbeta$ -processed $\\upalpha/\\upbeta$ Ti alloys. Metall. Mater. Trans. A 37, 559–566 (2006). \n25. Hunt, J. D. Steady-state columnar and equiaxed growth of dendrites and eutectic. Mater. Sci. Eng. 65, 75–83 (1984). \n26. Raghavan, N. et al. Numerical modeling of heat-transfer and the influence of process parameters on tailoring the grain morphology of IN718 in electron beam additive manufacturing. Acta Mater. 112, 303–314 (2016). \n27. Spierings, A. B., Dawson, K., Voegtlin, M., Palm, F. & Uggowitzer, P. J. Microstructure and mechanical properties of as-processed scandium-modified aluminium using selective laser melting. CIRP Ann. 65, 213–216 (2016). \n28. Li, X. P. et al. Selective laser melting of nano- $\\cdot\\mathrm{TiB}_{2}$ decorated AlSi10Mg alloy with high fracture strength and ductility. Acta Mater. 129, 183–193 (2017). \n29. Lin, T. C. et al. Aluminum with dispersed nanoparticles by laser additive manufacturing. Nat. Commun. 10, 4124 (2019). \n30. Flynn, H. G. in Physical Acoustics (ed Mason, W. P.) 57–172 (Academic Press, New York, 1964). \n31. Wang, B. et al. Ultrafast synchrotron X-ray imaging studies of microstructure fragmentation in solidification under ultrasound. Acta Mater. 144, 505–515 (2018). \n32. Suslick, K. S. & Price, G. J. Applications of ultrasound to materials chemistry. Annu. Rev. Mater. Sci. 29, 295–326 (1999). \n33. Abramov, O. V. Ultrasound in Liquid and Solid Metals (CRC Press, Boca Raton, 1994). \n34. Eskin, G. I. & Eskin, D. G. Ultrasonic Treatment of Light Alloy Melts 2nd edn (CRC Press, Boca Raton, 2014). \n35. Cui, Y., Xu, C. L. & Han, Q. Y. Microstructure improvement in weld metal using ultrasonic vibrations. Adv. Eng. Mater. 9, 161–163 (2007). \n36. Yuan, T., Kou, S. D. & Luo, Z. Grain refining by ultrasonic stirring of the weld pool. Acta Mater. 106, 144–154 (2016). \n37. Ramirez, A., Qian, M., Davis, B., Wilks, T. & StJohn, D. H. Potency of highintensity ultrasonic treatment for grain refinement of magnesium alloys. Scr. Mater. 59, 19–22 (2008). \n38. Atamanenko, T. V., Eskin, D. G., Zhang, L. & Katgerman, L. Criteria of grain refinement induced by ultrasonic melt treatment of aluminum alloys containing Zr and Ti. Metall. Mater. Trans. A 41a, 2056–2066 (2010). \n39. Qian, M. & Ramirez, A. An approach to assessing ultrasonic attenuation in molten magnesium alloys. J. Appl. Phys. 105, 013538 (2009). \n40. Qian, M., Ramirez, A. & Das, A. Ultrasonic refinement of magnesium by cavitation: clarifying the role of wall crystals. J. Cryst. Growth 311, 3708–3715 (2009). \n41. Ramirez, A., Qian, M., Davis, B. & Wilks, T. High-intensity ultrasonic grain refinement of magnesium alloys: role of solute. Int. J. Cast. Metal. Res. 22, 260–263 (2009). \n42. Qian, M., Ramirez, A., Das, A. & StJohn, D. H. The effect of solute on ultrasonic grain refinement of magnesium alloys. J. Cryst. Growth 312, 2267–2272 (2010). \n43. Dinda, G. P., Dasgupta, A. K. & Mazumder, J. Laser aided direct metal deposition of Inconel 625 superalloy: Microstructural evolution and thermal stability. Mater. Sci. Eng. A 509, 98–104 (2009). \n44. Murr, L. E. et al. Microstructural architecture, microstructures, and mechanical properties for a nickel-based superalloy fabricated by electron beam melting. Metall. Mater. Trans. A 42a, 3491–3508 (2011). \n45. Li, S. et al. Microstructure characteristics of Inconel 625 superalloy manufactured by selective laser melting. J. Mater. Sci. Technol. 31, 946–952 (2015). \n46. Paradis, P. F. & Rhim, W. K. Non-contact measurements of thermophysical properties of titanium at high temperature. J. Chem. Thermodyn. 32, 123–133 (2000). \n47. Casas, J., Keita, N. M. & Steinemann, S. G. Sound velocity in liquid titanium, vanadium and chromium. Phys. Chem. Liq. 14, 155–158 (1984). \n48. Wang, G., Dargusch, M. S., Eskin, D. G. & StJohn, D. H. Identifying the stages during ultrasonic processing that reduce the grain size of aluminum with added Al3Ti1B master alloy. Adv. Eng. Mater. 19, 1700264 (2017). \n49. Beese, A. M. & Carroll, B. E. Review of mechanical properties of Ti-6Al-4V made by laser-based additive manufacturing using powder feedstock. JOM 68, 724–734 (2016). \n50. Lewandowski, J. J. & Seifi, M. Metal additive manufacturing: a review of mechanical properties. Annu. Rev. Mater. Res. 46, 151–186 (2016). \n51. Bermingham, M. J., McDonald, S. D. & Dargusch, M. S. Effect of trace lanthanum hexaboride and boron additions on microstructure, tensile properties and anisotropy of Ti-6Al-4V produced by additive manufacturing. Mater. Sci. Eng. A 719, 1–11 (2018). \n52. Mereddy, S. et al. Trace carbon addition to refine microstructure and enhance properties of additive-manufactured Ti-6Al-4V. JOM 70, 1670–1676 (2018). \n53. Edwards, P. & Ramulu, M. Fatigue performance evaluation of selective laser melted Ti–6Al–4V. Mater. Sci. Eng. A 598, 327–337 (2014). \n54. Xu, W. et al. Additive manufacturing of strong and ductile Ti–6Al–4V by selective laser melting via in situ martensite decomposition. Acta Mater. 85, 74–84 (2015). \n55. Qiu, C. et al. Fabrication of large Ti–6Al–4V structures by direct laser deposition. J. Alloys Compd. 629, 351–361 (2015). \n56. Xu, W., Lui, E. W., Pateras, A., Qian, M. & Brandt, M. In situ tailoring microstructure in additively manufactured Ti-6Al-4V for superior mechanical performance. Acta Mater. 125, 390–400 (2017). \n57. Wilson-Heid, A. E., Wang, Z., McCornac, B. & Beese, A. M. Quantitative relationship between anisotropic strain to failure and grain morphology in additively manufactured Ti-6Al-4V. Mater. Sci. Eng. A 706, 287–294 (2017). \n58. ASM International Handbook Committee. Properties and Selection: Nonferrous Alloys and Special-Purpose Materials. in ASM Handbook.Vol. 2. (ASM International, Materials Park, OH, 1990). \n59. Rosenberg, Z. & Meybar, Y. Determination of changes in the sound-velocity in shock loaded Ti-6Al-4V with in-material Manganin gauges. J. Phys. D. 16, L193 (1983). \n60. Wang, F. et al. A refining mechanism of primary $\\mathrm{\\Al}_{3}\\mathrm{Ti}$ intermetallic particles by ultrasonic treatment in the liquid state. Acta Mater. 116, 354–363 (2016). \n61. Wang, F., Tzanakis, I., Eskin, D., Mi, J. & Connolley, T. In situ observation of ultrasonic cavitation-induced fragmentation of the primary crystals formed in Al alloys. Ultrason. Sonochem. 39, 66–76 (2017). \n62. Wang, F. et al. A synchrotron X-radiography study of the fragmentation and refinement of primary intermetallic particles in an Al-35 Cu alloy induced by ultrasonic melt processing. Acta Mater. 141, 142–153 (2017). \n63. Wang, G., Croaker, P., Dargusch, M., McGuckin, D. & StJohn, D. Simulation of convective flow and thermal conditions during ultrasonic treatment of an Al-2Cu alloy. Comput. Mater. Sci. 134, 116–125 (2017). \n64. Wang, G. et al. The role of ultrasonically induced acoustic streaming in developing fine equiaxed grains during the solidification of an Al-2 pct Cu alloy. Metall. Mater. Trans. A 50, 5253–5263 (2019). \n65. Cui, Y., Xu, C. L. & Han, Q. Effect of ultrasonic vibration on unmixed zone formation. Scr. Mater. 55, 975–978 (2006). \n66. Bermingham, M. J., McDonald, S. D., Dargusch, M. S. & StJohn, D. H. Effect of oxygen on the $\\upbeta$ -grain size of cast titanium. Mater. Sci. Forum 654, 1472–1475 (2010). \n67. Liu, Z. & Welsch, G. Effects of oxygen and heat treatment on the mechanical properties of alpha and beta titanium alloys. Metall. Trans. A 19, 527–542 (1988). \n68. Vander Voort, G. F. Metallography: Principles and Practice. (ASM International, Materials Park, OH, 1999). \n69. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012). \n70. Cayron, C. ARPGE: a computer program to automatically reconstruct the parent grains from electron backscatter diffraction data. J. Appl. Crystallogr. 40, 1183–1188 (2007). \n\n# Acknowledgements \n\nThis research work was supported by the Australian Research Council (ARC) Discovery Projects DP150104719 and DP140100702 and the ExoMet Project co-funded by the European Commission’s 7th Framework Programme (contract FP7-NMP3-LA2012-280421), by the European Space Agency and by the individual partner organizations. M.A.E., D.Q. and D.H.S. further acknowledge the support of the ARC Discovery Project DP160100560. M.J.B. acknowledges the support of the School of Mechanical and Mining Engineering at The University of Queensland as well as the ARC Discovery Early Career Researcher Award DE160100260. We thank both the Microscopy and Microanalysis Facility (RMMF) and the Advanced Manufacturing Precinct (AMP) at RMIT University for their facilities and technical assistance. In addition, we thank Sonic Systems Ltd (Somerset, UK) for their timely design and support. \n\n# Author contributions \n\nC.J.T. and M.Q. conceived the idea. C.J.T., D.Q. and D.Z. fabricated the samples. C.J.T. and E.W.L. performed the tensile tests. C.J.T. performed all other remaining experiments. C.J.T. drafted the manuscript, and C.J.T., M.A.E., D.Q., D.Z., M.J.B., E.W.L., M.B., D.H.S. and M.Q. interpreted, discussed and edited the manuscript. C.J.T. and M.Q. finalized the manuscript, including preparing the detailed response letter. M.Q. supervised the work. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 019-13874-z. \n\nCorrespondence and requests for materials should be addressed to M.Q. \n\nPeer review information Nature Communications thanks Peter Collins, Douglas Hofmann and the other, anonymous, reviewer for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1016_j.joule.2020.05.018", + "DOI": "10.1016/j.joule.2020.05.018", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2020.05.018", + "Relative Dir Path": "mds/10.1016_j.joule.2020.05.018", + "Article Title": "Hydrated Eutectic Electrolytes with Ligand-Oriented Solvation Shells for Long-Cycling Zinc-Organic Batteries", + "Authors": "Yang, WH; Du, XF; Zhao, JW; Chen, Z; Li, JJ; Xie, J; Zhang, YJ; Cui, ZL; Kong, QY; Zhao, ZM; Wang, CG; Zhang, QC; Cui, GL", + "Source Title": "JOULE", + "Abstract": "Despite their intrinsic safety and cost-effectiveness, aqueous zinc (Zn)-organic batteries have been struggling with the rapid performance degradation arising from the poor reversibility of Zn anodes and the dissolution of cathodes. Here, we present a new aqueous eutectic electrolyte by coupling a hydrated Zn salt (Zn(ClO4)(2)center dot 6H(2)O) exclusively with a neutral ligand (succinonitrile) to mitigate these issues. The unique aqua Zn2+ solvates with a succinonitrile-assisted solvation shell enable an unusual Zn/Zn2+ reversibility of 98.4% Coulombic efficiency along with smooth Zn deposition. Moreover, all water molecules contribute to the formation of the eutectic network, resulting in a delayed oxidation and suppressed solvating ability. When a quinone-based polymermaterial (38 wt% sulfur content) is utilized as a cathode, the Zn-organic battery with this aqueous eutectic electrolyte exhibits an unprecedented cyclability with a low capacity decay rate (0.004% per cycle over 3,500 cycles) and superior low-temperature performance.", + "Times Cited, WoS Core": 546, + "Times Cited, All Databases": 565, + "Publication Year": 2020, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000551427400020", + "Markdown": "# Article Hydrated Eutectic Electrolytes with LigandOriented Solvation Shells for Long-Cycling Zinc-Organic Batteries \n\nWuhai Yang, Xiaofan Du, Jingwen Zhao, ..., Cunguo Wang, Qichun Zhang, Guanglei Cui \n\nzhaojw@qibebt.ac.cn (J.Z.) qczhang@ntu.edu.sg (Q.Z.) cuigl@qibebt.ac.cn (G.C.) \n\n# HIGHLIGHTS \n\nMixing a hydrated Zn salt with a ligand leads to a new aqueous eutectic Zn electrolyte \n\n![](images/b4b58bd1720fa0f256ccd3f52968af72626a3c535d248740972a088bddb88546.jpg) \n\nA ligand-assisted solvation structure enables the reversible Zn plating/stripping \n\nThe absence of free water suppresses the dissolution of organic cathodes \n\nThe commonly accepted nonideal perchlorate anion is stabilized in the eutectic network \n\n$Z n$ -organic batteries are unstable in conventional aqueous electrolytes from both anode and cathode aspects. We demonstrated a new hydrated eutectic electrolyte based on a simple formulation of a hydrated Zn salt and a neutral ligand, in which the reorganized solvation shell of $Z n^{2+}$ and low activity of water molecules allow high-efficient Zn plating/stripping and suppress the dissolution of organic cathodes. \n\nYang et al., Joule 4, 1557–1574 July 15, 2020 ª 2020 Elsevier Inc. https://doi.org/10.1016/j.joule.2020.05.018 \n\n# Article Hydrated Eutectic Electrolytes with Ligand-Oriented Solvation Shells for Long-Cycling Zinc-Organic Batteries \n\nWuhai Yang,1,3,5 Xiaofan Du,1,5 Jingwen Zhao,1,\\* Zheng Chen,1 Jiajia Li,1 Jian Xie,2 Yaojian Zhang,1 Zili Cui,1 Qingyu Kong,4 Zhiming Zhao,1 Cunguo Wang,3 Qichun Zhang,2,\\* and Guanglei Cui1,6,\\* \n\n# SUMMARY \n\nDespite their intrinsic safety and cost-effectiveness, aqueous zinc (Zn)-organic batteries have been struggling with the rapid performance degradation arising from the poor reversibility of Zn anodes and the dissolution of cathodes. Here, we present a new aqueous eutectic electrolyte by coupling a hydrated Zn salt $(\\mathsf{Z n}(\\mathsf{C l O}_{4})_{2}\\cdot6\\mathsf{H}_{2}\\mathsf{O})$ exclusively with a neutral ligand (succinonitrile) to mitigate these issues. The unique aqua $Z n^{2+}$ solvates with a succinonitrile-assisted solvation shell enable an unusual $Z n/Z n^{2+}$ reversibility of $98.4\\%$ Coulombic efficiency along with smooth Zn deposition. Moreover, all water molecules contribute to the formation of the eutectic network, resulting in a delayed oxidation and suppressed solvating ability. When a quinone-based polymer material (38 wt % sulfur content) is utilized as a cathode, the Zn-organic battery with this aqueous eutectic electrolyte exhibits an unprecedented cyclability with a low capacity decay rate $(0.004\\%$ per cycle over 3,500 cycles) and superior low-temperature performance. \n\n# INTRODUCTION \n\nAmong the ‘‘beyond-lithium-ion’’ chemistries explored currently, aqueous zinc (Zn) batteries hold great practicability, partially owing to their rich research history and commercial advances in their single-use cell types. Recent strides have been made to couple Zn anodes with various types of cathode materials to further explore their performance limits.1–3 Unlike inorganic cathodes, organic hosts featured with the weak intermolecular van der Waals (vdW) forces are intrinsically superior in storing charge-dense ions.4–6 On the basis of the tunability of organic structures, unique ion-storage mechanisms can also be anticipated.7–10 However, the currently available aqueous Zn electrolytes are far from ideal for the Zn-organic batteries: (1) the reactive hydrated $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ ion induces severe side reactions and non-uniform Zn deposition;11 (2) the discharge products on organic cathode side tend to be dissolved by free water molecules in bulk electrolyte.12 \n\nAgainst this background, the emerging superconcentrated solvent-in-salt electrolytes (SISEs) offer opportunities to stabilize the $Z n$ -organic batteries. Given the absence or minimum of free solvents in SISEs,13–15 the suppression effect on anodic dissolution of certain components (such as current collectors, transition metals, and even polysulfides) has been demonstrated in battery chemistries traditionally thought unstable in diluted systems.15–17 Moreover, the reorganized solvation shell of metal cations (typically associated with coordinating anions) brings potential benefits for manipulating the metal electrodeposition.18–28 However, most SISEs are \n\n# Context & Scale \n\nAqueous Zn batteries in conjunction with organic cathodes are attractive owning to their safe, green, and low-cost characteristics. However, their rechargeability has been plagued by the lack of suitable electrolytes that can support both the reactive Zn and the soluble organic materials. This work represents our new finding in aqueous Zn electrolytes with the hydrated eutectic nature, which involves a simple formulation based on mixing a hydrated Zn salt with a neutral ligand. The participation of the ligand in the primary $Z n^{2+}$ solvation shell plays a pivotal role in stabilizing Zn plating/stripping with smooth deposits and suppressed side reactions. Importantly, all water molecules are isolated from each other due to the eutectic network and remain bound in the metal coordination sphere (outer shell), significantly inhibiting the dissolution of organic cathodes, and thus achieving a minimal capacity decay $(0.004\\%$ per cycle) for $Z n$ -organic batteries, even if the Zn excess is limited. \n\ncostly on account of the existence of excess reaction-irrelevant ions, which compromises the economic benefits anticipated for Zn batteries.29 Also, compared with the monovalent counterparts, the bivalent $Z n^{2+}$ ion bears stronger Coulombic traps from anions, while the conceivable ‘‘simple’’ Zn salts that can venture into the aqueous SISE regime have been limited, hitherto, to $Z_{n}C l_{2}$ exclusively.30–32 Unfortunately, the concentrated $Z n C l_{2}$ solutions would inherit the corrosiveness of Lewis acidic metal halides (in the form of oligomeric $[Z\\mathsf{n}_{x}C|_{(2x+2)}]^{2-}$ ions),32 and their susceptibility to oxidation of ${\\mathsf{C l}}^{-}$ also limits the possible operating voltage.33,34 Hence, there is a great need to pursue alternative aqueous Zn electrolytes with more benign nature. \n\nA critical metric for ideal multivalent-metal electrolytes is the effectiveness of the regulated metal coordination environments, which further determines chemical and physical characteristics of the electrolyte.35–38 The emergence of ionic liquid (IL) analogs, named as liquid coordination complexes or deep eutectic solvents, provides a clever tactic to engineer the multivalent-metal speciation.39–43 Differing from traditional ILs formed using cost-incurring organic cations, these liquids are typically obtained via the heterolytic cleavage of metal halides (e.g., $\\mathsf{A l C l}_{3},\\mathsf{G a C l}_{3},$ and $Z_{n}C l_{2})$ with neutral ligands at eutectic ratios, leading to both cationic and anionic metal complexes as constituent ions.44–46 Given that ligands can be viewed as molecular solvents, the compositions and electrochemical properties of these eutectics are analogous to those of ‘‘classical’’ SISEs. On the other hand, although the rechargeable battery applications rule out the fragile halometallate anions, halide-free eutectics have merely been touched upon. Only recently were protic amide-based ligands proved to eutectically liquefy (after moderate heating) considerable amounts of $Z n$ salts (at least 1/8 mol of Zn to per mole of ligand) with weakly Lewis basic anions, such as trifluoromethylsulfonate $(\\mathsf{T}\\mathsf{f}\\mathsf{O}^{-})$ and bis(trifluoromethylsulfonyl)imide $(\\mathsf{T}\\mathsf{F}\\mathsf{S}\\mathsf{I}^{-}),$ , which largely depend on the strong coordination of amides with both cations and anions.26,47 In fact, due to the bipolar nature, water molecules have been used as chemical building blocks for eutectic networks;48,49 correspondingly, the improved conductivity and lowered viscosity arising from the hydration effect could be leveraged. However, such eutectic $H_{2}O$ systems suffer from a hydration-limit that dictates the structure transition from a ‘‘water-in-eutectic’’ to an ordinary ‘‘aqueous solution’’ regime.48 The unavoidable absorption of water during processing would further interrupt the original metal coordination. Thus, in an attempt to balance the features from both eutectic and aqueous electrolytes, it is of particular significance to accurately control the degree of hydration in a cost-efficient and easyhandling way. \n\nHere, we report a new class of hydrated eutectic Zn electrolytes with a precise hydration level based on a simple formulation—mixing a low-cost hydrated salt $(Z\\mathsf{n}(\\mathsf{C l O}_{4})_{2}\\cdot6\\mathsf{H}_{2}\\mathsf{O})$ and a neutral ligand (succinonitrile, SN). Especially, no additional water is involved, except for the crystallization water from the constituent of $Z n(C l O_{4})_{2}\\cdot6H_{2}O$ . Importantly, we demonstrate that the aqua cationic Zn species and corresponding water molecules’ coordination states can be reorganized in this ligand-assisted eutectic system. The Lewis basic SN essentially participates in the primary solvation shell of $Z n^{2+}$ ion, in a manner of forming the hydration-deficient complexes, $[Z\\mathsf{n}({\\mathsf{O}}\\mathsf{H}_{2})_{\\boldsymbol{x}}({\\mathsf{S}}\\mathsf{N})_{\\boldsymbol{y}}]^{2+}$ cations, which allows dendrite-free Zn plating/stripping with an average Coulombic efficiency (CE) of $98.4\\%$ . Meanwhile, the portion of water replaced by SN contributes to the formation of the hydrated eutectic structure and is mainly sequestered in the outer solvation shell of $Z n^{2+}$ cations, ensuring the reversible reactions of organic cathodes with negligible dissolution. This beneficial synergy arising from anode and cathode sides brings unprecedented cycling stability (over 3,500 cycles at $0.3\\mathsf{C})$ to aqueous Zn-organic batteries using a cathode of poly(2,3-dithiino-1,4-benzoquinone) (abbreviated as PDB). The eutectic nature (rich intermolecular interactions) of this aqueous electrolyte further guarantees stable low-temperature operation even at $-20^{\\circ}\\mathsf C$ . \n\n# RESULTS AND DISCUSSION \n\nIn response to the considerable challenges (i.e., dendrite growth and parasitic reactions) encountered with aqueous $Z n$ metal anodes, different strategies have been pursued.50–60 Designing new functional Zn electrolytes, rather than modifying the anode via complicated and tedious surface engineering, would allow a promising pathway toward simplified and cheaper battery construction. It is known that $Z n^{2+}$ is generally solvated by six water molecules (octahedral coordination in the primary solvation shell) in routine aqueous solutions, forming the typical hydrated $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ ions.61–63 The strong interaction between $Z n^{2+}$ and water significantly weakens the $0{\\cdot}\\mathsf{H}$ bond within the water molecules, and as such, the deprotonation could prevail, generating deprotonated hydroxyl species that have a detrimental effect on rechargeability of metallic Zn anodes.64,65 Little information is available on tailoring the typical hydrated $Z n$ species and surrounding hydrogen-bonded localized water structure. A very recent paper reported that the high population of organic anions forces them into the vicinity of $Z n^{2+}$ to form close ion pairs instead of $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ , and surface passivation can be effectively prevented. However, the use of large amount of organic salts apparently reduces the economic benefits of Zn batteries. Moreover, the low-temperature availability could be compromised by the tendency of multi-phase coexistence.66 \n\nIn the cyanide-containing baths used for industrial Zn electroplating, the strong coordination between $Z n^{2+}$ and $C{\\mathsf{N}}^{-}$ , which significantly elevates the polarization potentials, helps to obtain smooth Zn coating.67 Inspired by this well-developed chemical wisdom, neutral molecules containing function-similar groups (such as nitriles) could be used to achieve analogous effects on the Zn electrochemistry. SN is regarded as a logical choice, also given its affordability, wide availability, moderate Lewis basicity (donor number, $D N=15$ ),68 and relatively high polarity (dielectric constant, $\\varepsilon=55$ ) to dissolve various types of salts.69 It should be noted that although SN keeps a plastic-crystal phase at room temperature, the strong nitrile-nitrile dipolar associations that dictate the regular long-range crystalline lattice can be weakened by surrounding the nitrile with other dipoles. It is known that water (dipole moment, 1.8546 D) is able to build hydrogen bridges to nitrogen atoms of intra- and interchains in polyacrylonitrile, resulting in a reduction in $T_{\\mathrm{m}}$ .70,71 In this consideration, the linear configuration of SN with two cyano terminals allows a high tendency toward hydration, enriching the intermolecular interactions required for the eutectic liquid system. As for Zn source, hydrated inorganic salts $({\\cal Z}n({\\mathsf{C}}|{\\mathsf{O}}_{4})_{2}\\cdot6{\\mathsf{H}}_{2}{\\mathsf{O}},$ $Z n(N O_{3})_{2}\\cdot6H_{2}O$ and $Z n(S O_{4})_{2}\\cdot7H_{2}O)$ can serve as a better compared with organic imide salts, such as $Z_{\\mathsf{n}}({\\mathsf{T}}{\\mathsf{F}}{\\mathsf{S}}{\\mathsf{I}})_{2}$ and $Z_{\\mathsf{n}}({\\mathsf{T}}\\dagger{\\mathsf{O}})_{2}$ , because the formers are inexpensive, stable to moisture and air, and particularly contain certain amounts of crystal water. \n\nBased on the above points, the mixtures of SN with simple hydrated salts were prepared at varying Zn salt/SN molar ratios (1:4, 1:8, and 1:12), respectively. All mixtures were heated to $80^{\\circ}\\mathsf{C}$ for 30 min and then cooled to room temperature. As observed in Figures 1A–1C, $Z n(S O_{4})_{2}\\cdot7H_{2}O$ and $Z n(N O_{3})_{2}\\cdot6H_{2}O$ are almost insoluble in SN, while homogeneous, colorless solutions composed of SN and $Z n(C l O_{4})_{2}\\cdot6H_{2}O$ can be obtained at room temperature. These eutectics can remain stable in liquid state for up to three months without any observed phase separation. Moreover, when exposed to the open atmosphere for $48\\mathsf{h}$ , the $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ eutectics experienced a slight decrease in weight (Figure 1D), demonstrating the lowered water activity because of a hydration effect, in sharp contrast to the common aqueous electrolytes (1 $M Z n(C l O_{4})_{2}$ and even saturated $Z n(C l O_{4})_{2}$ solution). The ionic conductivity, viscosity, and thermal behavior of as-prepared eutectics are strongly dependent on the Zn salt/SN ratio (Figures 1E and 1F). Although increasing the SN content leads to higher conductivities and lower viscosities, the typical endothermic peak $(-32.5^{\\circ}\\mathsf{C}$ and $-39.6^{\\circ}\\mathsf C,$ respectively) associated with the rigid-to-plastic-crystal transition appear for the 1:12 and 1:16 cases, suggesting the presence of SN clusters that are not participating in the eutectic network.69 The eutectic solution with a $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ ratio of 1:8 (denoted as ZS) possesses a collection of wellbalanced properties, including a high conductivity $(5.52~\\mathsf{m S}~\\mathsf{c m}^{-1}.$ ), a low viscosity $(25.4\\mathsf{m P a}\\mathsf{s}^{-1}.$ ) as well as a lowest-eutectic temperature $(-95.3^{\\circ}\\mathsf{C})$ . Thus, this electrolyte formulation, without the addition of extra water, was further explored for modifying aqueous $Z n$ electrochemistry. Correspondingly, for comparative purposes, an aqueous electrolyte (labeled as ZW) with the same Zn molar concentration as ZS, namely the $Z n(C l O_{4})_{2}\\cdot6H_{2}O/H_{2}O$ molar ratio of 1:8, was adopted as a control group. \n\n![](images/03254fa72c79df6619f7e537dd67753e80f9f1d889ed26722fdfdbd520e23a83.jpg) \n \nFigure 1. Preparation and Physical Characterization of the Hydrated Eutectic Electrolytes (A–C) The solubility of (A) $Z n(S O_{4})_{2}\\cdot7H_{2}O,$ (B) $Z n(N O_{3})_{2}\\cdot6H_{2}O,$ and ( $\\Rightarrow2n(C l O_{4})_{2}\\cdot6H_{2}O$ in SN (the Zn salt/SN molar ratios are 1:4, 1:8, and 1:12 from left to right). (D) The weight retention of different electrolytes in the air $(25^{\\circ}\\mathsf{C})$ . (E) Viscosity and conductivity of the $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ eutectic solutions (the molar ratios of $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ are 1:4, 1:6, 1:8, 1:10, and 1:12). (F) DSC data of the $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ mixtures with the different $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ molar ratios (1:4, 1:6, 1:8, 1:12, and 1:16). (G) Ohmic-corrected CV curves of Zn plating/stripping using SS as the working electrode and $Z n$ as the reference and counter electrodes in ZS $(Z\\mathsf{n}(\\mathsf{C l O}_{4})_{2}\\cdot6\\mathsf{H}_{2}\\mathsf{O}/\\mathsf{S N}$ molar ratio of 1:8) and ZW $(Z_{n}(\\mathsf{C l O}_{4})_{2}{\\cdot}6\\mathsf{H}_{2}\\mathsf{O}/\\mathsf{H}_{2}\\mathsf{O}$ molar ratio of 1:8) at scan rate of $1.0\\:\\mathrm{mVs^{-1}}$ . \n\nFigure 1G shows the ohmic-corrected cyclic voltammetry (CV) responses of stainless steel (labeled as $S S)/Z n$ asymmetric cells. An increased nucleation overpotential compared with ZW can be observed for ZS, which is indicative of the expected ‘‘brightener’’ function. Scanning electron microscopy (SEM) images of the morphologies of Zn metal plated at $-0.3{\\\\mathrm{V}}$ are exhibited visually in Figures 2A, S1, and S2. Severe cracking and irregular protuberances are shown for the aqueous Zn electrolyte (i.e., ZW), which would cause cell shorting and premature failure. Interestingly, ZS produced a highly uniform Zn coating featured with tightly packed micrometer-sized crystalline mosaics. An observation worth noting is that, by the X-ray photoelectron spectroscopy (XPS), both $Z n^{2+}$ and SN signals coexist on the surface of plated Zn, while SN could be also embedded into the plated layer (Figure S3). Such observations clearly demonstrate the positive role of SN in regulating the Zn deposition. Given the high-entropy state and the absence of free SN in ZS, SN molecules are more likely absorbed on the $Z n$ surface in the form of coordinationally saturated species.72–74 The brightener effect of ZS on the metal deposition is thereby relied on the $Z n^{2+}$ desolvation from the active SN-associated Zn solvates at the interface. \n\n![](images/97344331f947af01a7017385c5991fbc84f4c3dcaf678df42a1cff220d5d763b.jpg) \ne 2. Comparison of Electrochemical $Z n/Z n^{2+}$ Reactions in ZS and ZW Electrolytes \n(A) Typical SEM images (insets show magnified SEM images of the deposited $Z n$ metal on SS with a better resolution) of Zn metal after plating on SS fo $0.5{\\ h}$ at $-0.3{\\\\mathrm{V}}$ (versus $Z n/Z n^{2+}$ ). (B–E) Galvanostatic $Z n$ plating/stripping curves and CE in (B and C) ZW and (D and E) ZS at a current density of $0.5\\mathsf{m A c m}^{-2}$ and an areal capacity of 0.5 mAh $\\mathsf{c m}^{-2}$ (final voltage is $0.5\\mathrm{V};$ ; SS was used as working electrode). (F and G) Discharge/charge curves of symmetric $Z n/Z n$ cells at (F) $0.05\\mathsf{m A c m}^{-2}(0.5\\mathsf{m A h c m}^{-2}$ ; $5.95\\%$ of $Z n$ inventory in ZS and $2.47\\%$ of Zn inventory in ZW) and $\\mathsf{G})0.2\\mathsf{m A}\\mathsf{c m}^{-2}(2.0\\mathsf{m A h}\\mathsf{c m}^{-2}$ ; $23.80\\%$ of $Z n$ inventory in ZS and $9.91\\%$ of $Z n$ inventory in ZW), respectively (each cycle lasts for $10\\mathrm{~h~}$ ). (H) XRD patterns of $Z n$ anodes of $Z n/Z n$ symmetric cells after plating/stripping cycling $(0.5\\mathsf{m A h\\ c m}^{-2}$ for each cycle) for $320{\\mathsf{h}}$ in ZW and $800{\\ h}$ in ZS. \n\nCE, an important parameter for evaluating rechargeability of metallic anodes, was measured by utilizing SS as the working electrode and $Z n$ foils as both the reference and counter electrodes at a practical areal capacity of $0.5\\mathsf{m A h c m}^{-2}$ (current density: $0.5\\mathsf{m A c m}^{-2})$ . From Figure 2B, erratic stripping signals based on ZW are observed in fewer than 10 cycles, which could be attributed to the competitive side reactions (i.e., hydrogen evolution and passivation).49 In contrast, a much smoother and regular voltage profile was achieved for ZS, along with a high average CE of $98.4\\%$ from cycle 45 to 90 (Figures 2D and 2E), significantly outperforming that (average CE $\\angle{\\cdot}$ $50\\%$ ) in ZW (Figure 2C) under the same condition. Notably, when the deposition capacity was increased to $2.0\\mathsf{m A h}\\mathsf{c m}^{-2}$ , a $3.70\\upmu\\mathrm{m}$ thick Zn layer obtained on SS conformed to the expected thickness of $3.42\\upmu\\mathrm{m}$ , representing the compact Zn coating by virtue of the high CE (Figure S4). Even at a high current density of $2.0\\mathsf{m A c m}^{-2}.$ , ZS still supported dendrite-free Zn deposition (Figures S5 and S6). It should be pointed out that the differences in CE and Zn morphology between ZS and ZW are too large to arise solely from the absorbed SN species, which is evidenced by the fact that lowlevel CEs and irregular Zn coating could naturally occur (Figure S7), as long as $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ solvates dominate in electrolytes (Figure S8).75 In this regard, an altered $Z n^{2+}$ solvation structure in ZS is expected to dictate the electrochemical process. In consideration of the comparable ionic conductivity of ZS with ZW $(17.66~\\mathsf{m}\\mathsf{S}~\\mathsf{c m}^{-1},$ ), the moderate increase in the voltage hysteresis during plating/stripping (Figure 2D) further suggests the intimate interaction between SN and $Z n^{2+}$ .76 \n\nAny feasible electrolyte for Zn batteries has to be thermodynamically stable with metallic Zn, as highlighted by our previous works.49,55 A lower current density along with a higher corrosion potential observed in a linear polarization experiment (Figure S9) indicates enhanced thermodynamic stability of ZS against Zn metal as compared with ZW. In order to visually exhibit this difference, two Zn plates were immersed in ZS and ZW, respectively (Figure S10). After 10 days, the dense white by-products accumulated on the Zn surface in ZW; however, not much change was noticed in the ZS case. \n\nThe $Z n/Z n$ symmetric cells under galvanostatic conditions were conducted to probe the long-term cycling stability of ZS and ZW. As illustrated in Figures 2F and 2G, after cycling for $69\\mathfrak{h}$ at an areal capacity of $0.5\\mathsf{m A h c m}^{-2}$ and for $40\\mathsf{h}$ at an areal capacity of $2.0\\ m{\\mathsf{A h\\ c m}}^{-2}$ , the sudden and irreversible rise of the polarization voltage appeared in cells with ZW. Then, these cells were disassembled and the overproduction of undesired insulating products (i.e., $Z n_{4}C l O_{4}(O H)_{7}$ and $Z n_{5}(O H)_{8}C l_{2})$ were detected from X-ray diffraction (XRD) (Figure 2H). It is noted that the competitive gas evolution also occurred, as verified by the apparent volume expansion of the testing cells (Figure S11). The side-reaction mechanism in ZW could be summarized as follows: \n\n$$\n5\\overline{{Z}}\\mathsf{n}^{2+}+2\\mathsf{C}|\\mathsf{O}_{4}^{-}+8\\mathsf{H}_{2}\\mathsf{O}+16\\mathsf{e}^{-}\\longrightarrow\\mathsf{Z}\\mathsf{n}_{5}(\\mathsf{O H})_{8}\\mathsf{C l}_{2}+8\\mathsf{O H}^{-}\n$$ \n\n$$\n4Z n+8H_{2}O+C l O_{4}^{-}\\rightarrow Z n_{4}C l O_{4}(O H)_{7}+4H_{2}\\uparrow+O H^{-}\n$$ \n\n$$\n4Z n^{2+}+C l O_{4}^{-}+7O H^{-}\\rightarrow Z n_{4}C l O_{4}(O H)_{7}\n$$ \n\nIn contrast, the cells using ZS exhibited stable polarization voltages with much extended cycling life (over $800{\\ h}$ at $0.5~\\mathsf{m A h}~\\mathsf{c m}^{-2}$ and over $400{\\mathsf{h}}$ at $2.0\\mathsf{m A h\\ c m}^{-2}$ without any potential fluctuation or shorting), which is expected given the improved CE and thermodynamic stability with Zn. Moreover, the XRD pattern of the cycled Zn plate taken at the top of charge with the maximum amount of $Z n^{2+}$ reduced confirms that the deposition layer is predominantly zerovalent Zn (Figure 2H). These findings lend support to the fact that the use of the ZS electrolyte is able to support the reversible Zn chemistry. \n\n![](images/5c6cd42ffe089a1b96862906505227d4b15c15a86c1b7fb0ab9a935de66bb304.jpg) \nFigure 3. Structural Characterization of ZS and ZW Electrolytes \n(A) Raw data (dash lines) and peak fitting (red lines) of Raman spectra of ZS and ZW. (B) Raman spectra of $Z n(C l O_{4})_{2}/H_{2}O/\\mathsf{S N}$ mixtures $(Z\\mathsf{n}(\\mathsf{C}|\\mathsf{O}_{4})_{2}/\\mathsf{H}_{2}\\mathsf{O}/\\mathsf{S N}$ molar ratios: 0:6:8, 0.1:6:8, 0.2:6:8, 0.5:6:8, and 1:6:8) between 2,350 to $2,150\\mathsf{c m}^{-1}$ (C) The structure (obtained from single-crystal XRD, $50\\%$ thermal probability ellipsoids) of single-crystal solids precipitated from ZS. (D) The chemical shifts for $^{17}\\mathrm{O}$ nuclei (water) of $Z n(C l O_{4})_{2}/H_{2}O/\\mathsf{S N}$ mixtures $(Z\\mathsf{n}(\\mathsf{C l O}_{4})_{2}/\\mathsf{H}_{2}\\mathsf{O}/\\mathsf{S N}$ molar ratios: 1:14:1, 1:14:2, 1:14:4, 1:14:6, and 1:14:8). (E) Raman spectra of ZS, ZW, and pure water. \n\nClearly, the introduction of a Lewis basic ligand could deviate the liquid structure from a conventional aqueous solution state. To illuminate this deviation, Raman spectroscopic study was first undertaken. The spectrum of ZW displays one weak peak at ${\\sim}390~\\mathsf{c m}^{-1}$ assigned to the symmetric stretch of the octahedral $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ (Figure 3A). Based on the literature77 and our datum (Figure S12), the $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ cation, which disappears almost in ZS (Figure 3A), also exists in $Z n(C l O_{4})_{2}\\cdot6H_{2}O$ salt. This suggests that the $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ species is severely disturbed by SN. In particular, a specific interplay could be expected between $Z n^{2+}$ and SN. Shown in Figure 3B is the Raman spectra of ${\\mathsf{C}}\\equiv\\mathsf{N}$ stretching vibration modes of SN in the range of $2,325{-}2,225~\\mathsf{c m}^{-1}$ with varying $Z n(C l O_{4})_{2}/H_{2}O/\\mathsf{S N}$ ratios; of note, the $S N/H_{2}O$ molar ratio, which is fixed at 8:6 is consistent with that in ZS. Upon the addition of $Z n(C l O_{4})_{2},$ , a blueshifted peak which centers at $2,300{\\mathsf{c m}}^{-1}$ and assigns to the $\\mathsf{C}\\equiv\\mathsf{N}$ stretching mode of SN bound to the $Z n^{2+}$ cation becomes visible and grows in intensity.78 This phenomenon demonstrates the participation of SN in building the $Z n^{2+}$ solvation shell in ZS. In order to realize a complete identification of the Zn species, the Raman spectrum of ZS was deconvoluted and the result is shown in Figure S13. According to the relative area of these peaks, the average coordination number of SN coordinated to each $Z n^{2+}$ is calculated to be \n\n2.7.79,80 Thus, it is likely that $[Z\\mathsf{n}(\\mathsf{S N})_{2}]^{2+}$ , $[Z_{\\mathsf{n}}(\\mathsf{S N})_{3}]^{2+}$ , and even $[Z_{\\mathsf{n}}(\\mathsf{S N})_{4}]^{2+}$ species coexist in ZS. This speculation can be proven by mass spectroscopy (MS) analysis, which detected exact mass-to-charge ratios corresponding to $[Z_{\\mathsf{n}}(\\mathsf{S N})_{2}]^{2+}$ $[Z_{\\mathsf{n}}(\\mathsf{O H}_{2})(\\mathsf{S N})_{2}]^{2+}$ , $[\\mathsf{Z n}(\\mathsf{O H}_{2})_{2}(\\mathsf{S N})_{2}]^{2+}$ , $[Z_{\\mathsf{n}}(\\mathsf{S N})_{3}]^{2+}$ , and $[Z\\mathsf{n}(\\mathsf{S N})_{4}]^{2+}$ (Figure S14). Apparently, the major $Z n$ species are by no means simple, and there is a delicate equilibrium between various SN-containing $Z n^{2+}$ complexes. \n\nConsidering that the aforementioned measurements were unable to reveal the equilibrium species and provide direct structural information, single crystals were generated in situ from ZS and characterized by single-crystal XRD.81 As is visible in Figure 3C, the crystal structure reveals that the $Z n^{2+}$ cation is coordinated by four cyano groups (i.e., two SN molecules coordinate to one $Z n^{2+}$ in all) and two water molecules; the cationic charge is balanced by the two persistent $\\mathsf{C l O}_{4}^{-}$ anions. Such a solvation scheme demonstrates the favorable energetics of SN around $Z n^{2+}$ cations. On the other hand, it should be noted that the predominant cationic species is $[{\\cal Z}{\\sf n}({\\sf O H}_{2})_{2}({\\sf S N})_{2}]^{2+}$ rather than $[Z_{\\mathsf{n}}(\\mathsf{S N})_{3}]^{2+}$ or $[Z\\mathsf{n}(\\mathsf{S N})_{4}]^{2+}$ . One possible explanation for this is that SN in the solvation shell could have stronger repulsive interactions with neighboring SN molecules. However, due to the smaller size of water than SN, the repulsive interactions between SN and water would be weaker, and as such, some water molecules remain favorably in the primary solvation shell of $Z n^{2+}$ coordinated by two SN molecules. In the meantime, Raman spectrum of the single crystals precipitated from ZS further confirms the absence of $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ (Figure S15). \n\nSince both cathodic and anodic stabilities of electrolytes are closely associated with the most vulnerable moiety, it is necessary to identify the state of water. The $^{17}\\mathrm{O}$ nuclear magnetic resonance (NMR) spectra of the $Z n(C l O_{4})_{2}/H_{2}O/\\mathsf{S N}$ liquid samples are shown in Figure 3D. In order to guarantee the accuracy of measuring data, $D_{2}O$ was used as internal standard. It should be noted that a fixed $H_{2}O/Z n$ molar ratio of 14:1 was applied because the NMR signal for the 6:1 molar ratio is too weak to obtain reliable data. The $^{17}\\mathrm{O}$ (water) response is shown to be rather sensitive to the presence of Zn salt in the aqueous electrolyte. This is due to the fact that the Lewis acidic $Z n^{2+}$ can directly interact with the lone-pair electrons of water oxygen, while a suppressed $Z n^{2+}\\cdot H_{2}O$ coordination results in the shielding, as reflected by the upshift in its chemical shift. Upon increasing the concentration of SN, the chemical shift continues to shift to higher frequency, indicating that water molecules initially solvating $Z n^{2+}$ are replaced by SN gradually. However, SN has a negligible effect on the state of $\\mathsf{C l O}_{4}^{-}$ anions as verified by the almost unchanged $^{17}\\mathrm{O}$ signal with varying $Z n(C l O_{4})_{2}/H_{2}O/\\mathsf{S N}$ ratios (Figure S16). \n\nBased on the NMR results, it is logical to deduce that pooling of water molecules substituted by SN could result in significant water-water hydrogen bonding, in a manner analogous to conventional aqueous solutions. However, from linear sweep voltammetry (LSV), it is clear that the anodic stability of ZS is improved to $2.55\\mathrm{~V~}$ (versus $Z n/Z n^{2+}$ ), as compared with $2.40\\mathrm{V}$ in ZW (Figure S17). As previously reported in lithium hydrate melts, the water molecule donates its lone-pair electrons of the oxygen atom when it coordinated with ${\\mathsf{L i}}^{+}$ (Lewis acid), which lowers the highest occupied molecular orbital level of water and thereby raises its oxidation potential.82 Despite a change in the coordination state of water caused by SN, a suppressed water activity compared with that in dilute aqueous electrolytes is still obtained in ZS, which likely arises from the unique intermolecular interactions in the eutectic system. To examine the validity of this hypothesis, the O-H stretching modes of water were explored by Raman test (Figure 3E). For the pure water and ZW, both the O–H symmetric $(\\sim3,200\\ c m^{-1}),$ ) and asymmetric $(\\sim3,400\\ c m^{-1})$ ) stretching vibration modes give rise to a broad band, representing the aggregation of ‘‘free’’ (not participating in the $Z n^{2+}$ solvation) water molecules. In ZS, however, this broad peak disappears while a sharp peak, characteristic of crystalline hydrates, is shown at ${\\sim}3,600~{\\ c m}^{-1}$ . These findings are rather similar with those observed in hydrate-melt electrolytes and suggest that water molecules are mostly present in a ‘‘confined’’ state in ZS rather than the ‘‘free’’ state.76,83 \n\n![](images/f6673498cecee76bde942ea31df8db506e35d8049a334d5081c0a84e6a47d492.jpg) \nigure 4. Theoretical Simulations and Schematic Illustration of an Integrated Discussion on the ZS and ZW Electroly (A) 3D snapshot obtained by MD simulations and representative $Z n^{2+}$ -solvation structure in the ZS electrolyte. (B) RDFs for $Z n^{2+}-N$ (SN) and $Z n^{2+}-0$ (water) from MD simulations of ZS. (C and D) Schematic diagrams of $Z n^{2+}$ solvation structure and corresponding interfacial reactions in (C) ZW and (D) ZS. \n\nThe modified solvation structure in ZS was also investigated by theoretical approaches. A summary of the binding energy data obtained by density functional theory (DFT) calculations is tabulated in Table S2. The total binding energy for $Z n-H_{2}O,$ , $-4.490\\mathrm{eV},$ , is much smaller than that for $Z n-S N$ $(-6.159\\ \\mathrm{eV})$ , corroborating that Zn complexes based on SN possess higher desolvation energy. Molecular dynamics (MD) simulations in conjunction with resulting radial distribution functions (RDFs) revealing distributions of nearest-neighbor molecules were further used to articulate the liquid structure of ZS. Figure 4A displays a typical solvation structure of $Z n^{2+}$ , which is highly in agreement with the single-crystal datum. It is worth mentioning that three-coordinate and four-coordinate $Z n^{2+}$ complexes by SN also exist (Figure S18), which is in accord with MS results. RDFs shown in Figure 4B provide additional evidence of $Z n^{2+}$ (central ion) coordination to both SN and $H_{2}O$ . Two sharp peaks of the $z_{n-N}$ pair and the $Z n\\mathrm{-O}$ pair are identified at 3.0 and $2.7\\mathring{\\mathsf{A}},$ respectively, corresponding to the primary solvation shell of $Z n^{2+}$ ion. Of particular note is that another peak can be observed at $3.8\\mathring{\\mathsf{A}}$ for the $z_{n-\\mathrm{O}}$ pair, suggesting that water molecules replaced by SN enter the second solvation shell. Combined with LSV and Raman data, it is clear that these water molecules remain tightly bound to the solvation sphere of the cation, which is dramatically different from the free state of water clusters. \n\nThe pictures of the $Z n^{2+}$ solvation structures are visualized and interfacial reaction mechanisms between electrolytes and Zn anode are also displayed (Figures 4C and 4D). As mentioned above, due to the presence of the fragile $Z_{\\mathsf{n}}[\\mathsf{O H}_{2}]_{6}{}^{2+}$ in ZW, parasitic reactions including passivation, corrosion and hydrogen evolution, compete with the $Z n/Z n^{2+}$ redox processes and against each other. In ZS, it is certain that the primary solvation shell of $Z n^{2+}$ is mostly occupied by the SN molecules (primary solvation number $\\leq4$ ). The coordination of SN to $Z n^{2+}$ ions reduces the affinities between $Z n^{2+}$ and water, thus significantly mitigating the parasitic reactions that occurred at the $Z n$ -aqueous electrolyte interface. The enhanced interfacial stability may be also contributed by the suppressed perchlorate decomposition, though the perchlorate anions are often reactive in aqueous solutions.84 Concomitantly, it is the intimate $Z n^{2+}$ -SN interaction that increases the $Z n^{2+}$ desolvation energy in a moderate way, enabling smooth Zn deposition. Even if the displacement of water by SN for the $Z n^{2+}$ solvation occurs, the water molecules that are liberated from the primary solvation shell most likely stay in the outer shell of the metal coordination sphere and maintain a persistent, albeit relatively weak, attraction with the central cation. Thus, the enhancement of anodic stability could be rationalized. Note that the eutectic nature of ZS affords rich internal interactions (e.g., $H_{2}O-S N$ and $H_{2}O-$ ${\\mathsf{C l O}}_{4}{}^{-})$ , which further saturate the bipolar coordination sites of water molecules.85 This could be another possible reason for the much lower than expected free water content. Given the limited solvating ability arising from the scarcity of free water molecules, this unique aqueous system can be promisingly exploited to suppress dissolution of organic cathode materials in traditional aqueous electrolytes. \n\nBy virtue of the high capacity in lithium- and sodium-storage, carbonyl compounds (e.g., quinones, carboxylates, anhydrides, imides, and ketones) have been widely considered for metal-ion batteries.86 However, there are only very few pioneering reports on their use in the aqueous batteries on account of the high solubility of discharge products. Noteworthy, given the absence of free water beyond the routine aqueous solutions, a suppressed dissolution of the carbonyl-based cathodes can be anticipated based on the present ZS electrolyte, in a manner somewhat analogous to that of the ‘‘salt-in-solvent’’ electrolytes with absence of free solvent inhibiting the dissolution of lithium polysulfides in lithium-sulfur batteries. \n\nA quinone-based polymer, PDB, which was reported to possess a high capacity and cycling stability in the lithium-storage system,87,88 was applied as an example for aqueous Zn-organic batteries. The electrochemical behavior of PDB in ZS was first investigated by CV. At a scan rate of $1\\mathrm{m}\\mathrm{V}\\mathsf{s}^{-1}$ , PDB only displays one pair of redox peaks apparently arising from the $Z n^{2+}$ insertion/extraction (Figure 5A). Increasing scan rate shifts the cathodic peak to lower potential and the anodic peak to higher potential, respectively (Figure S19A). The linear fit of the logarithmic relationship between peak current and scan rate shows that slopes of anodic and cathodic peaks are 0.68 and 0.70, clarifying that deintercalation/intercalation of $Z n^{2+}$ from/into PDB contains a portion of pseudocapacitance (Figure S19B). In quinones, the active redox centers have been verified to be the carbonyl groups $(C=\\mathsf{O})$ by ex situ Fourier transform infrared (FTIR) investigations.89 It was also reported that polymers with the thioether bonds (C S C), which do not undergo bond cleavage during the redox reactions, could behave more stably as compared to those with disulfide bonds. To shed light on the ion-storage mechanism of PDB in ZS, the ex situ FTIR analysis was performed, and the corresponding spectra of PDB cathode at progressive states of charge and discharge were collected (Figures S20A and S20C). The intensity of the peak at $\\sim1.630\\ c m^{-1}$ , assigned to the stretching vibration of carbonyl, becomes very weak after full discharge and can be recovered after charge, confirming that the redox center is carbonyl. To explore whether the $Z n^{2+}$ insertion/extraction is implemented in the redox processes, we conducted XPS and energy-dispersive spectrometry (EDS) mapping. The XPS results (Figure S20B) illustrate the appearance of divalent Zn-element in cathode during discharge and the decrease of $Z n$ signal after recharged to $1.5~\\mathsf{V}.$ In addition, a reversible Zn occurring and/or disappearing response also could be obviously recognized by comparing EDS mapping images of PDB at pristine, fully discharged and fully recharged states as shown in Figure S20D. \n\n![](images/eb01298e4d77ca4a2f54634a431a91fd0382d9be813f3846e0f20abe5f29a4b8.jpg) \nFigure 5. Electrochemical Behaviors of the PDB/Zn Cell Using ZS and ZW Electrolytes (A) CV curves of the Zn anode (black line) against the PDB cathode (orange line) in ZS at 1.0 and $0.5~\\mathsf{m V s}^{-1}$ , respectively. (B) Electrochemical characterization of the PDB/ZS/Zn battery at room temperature and low temperature $(0.15\\mathsf{C})$ . (C) Long-term cycling of PDB in ZW (0.15 C) and ZS (0.15 and $0.30\\mathrm{C})$ respectively. \n\nA characterization of the cycling performance is pivotal to accessing the effectiveness of the ZS electrolyte in inhibiting the PDB dissolution. The PDB/ZW/Zn cell decays rapidly to $\\sim50\\%$ of its initial capacity in less than 80 cycles (at 0.15 C, $1\\subset{}=319$ $\\mathsf{m A g}^{-1}$ , based on the mass of the active cathode material), which implies the severe dissolution of the discharge products (Figure 5C). In sharp contrast, the PDB/ZS/Zn cell exhibits a much better stability with a high capacity retention of $\\sim91.0\\%$ after 1,000 cycles and ${\\sim}85.4\\%$ after over 3,500 cycles at $0.3~{\\mathsf{C}};$ near $100\\%$ CE is also observed at both rates. Note that a practical configuration with the Zn/PDB mass ratio of ${\\sim}5{:}2$ (only ${\\sim}19\\times\\mathsf{e x c e s s}Z{\\mathsf{n}};$ ) was applied for the PDB/ZS/Zn cell, considering the high CE of Zn stripping/plating in ZS. During initial cycling stage, we noticed that the cell capacity increased gradually and eventually stabilized. This phenomenon could be ascribed to the slow activation progress or the enhancement in utilization of active material. To further demonstrate the distinction of electrochemical performance between ZS and ZW, the separators were taken out from the disassembled cells after cycling (Figure S21). The separator used in ZW turned yellow and S-containing species was detected by SEM-EDS mapping measurement, which is reasonably attributed to the dissolution of the active PDB. As expected, no color change accompanied by the negligible S element can be observed for the cycled separator in ZS, hence providing clear evidence that ZS can suppress the PDB dissolution effectively. \n\nAfter the above investigations, rate performance and low-temperature stability of the cycled PDB/ZS/Zn cell were also tested. At room temperature, the PDB/ZS/Zn cell delivers a discharge capacity of ${\\sim}100\\ m\\mathsf{A h}\\ \\mathsf{g}^{-1}$ at $0.15\\mathrm{C}$ and ${\\sim}60\\ m\\mathsf{A h\\ 9}^{-1}$ at ${1.2}\\mathsf{C},$ respectively. After cycling at varying rates, the capacity of PDB could immediately turn back to almost $100\\%$ of its initial capacity at 0.15 C (Figure S22). Aqueous alkali-ion batteries suffer severe power loss at temperatures below $0^{\\circ}\\mathsf C.$ , limiting their use in applications, such as electric vehicles and tools in cold climates and high-altitude drones. From the data of differential scanning calorimeter (DSC) (Figure 1F), we can observe that the freezing point of ZS is below $-90^{\\circ}\\mathsf C,$ which could be beneficial for batteries to operate at ultra-low temperatures. To demonstrate the operating temperature range, the $Z n/Z n$ symmetric cell under galvanostatic conditions was performed between $-20^{\\circ}\\mathsf C$ and $90^{\\circ}\\mathsf{C}$ (Figure S23). Smooth voltage profiles were obtained at both high and low temperatures in ZS. As a comparison, a sudden polarization occurred in ZW when the working temperature was raised to $90^{\\circ}\\mathsf{C}$ . The PDB/ ZS/Zn cell exhibits a stable specific capacity of $95~\\mathrm{mAh}~\\mathfrak{g}^{-1}$ at $25^{\\circ}\\mathsf{C}$ . As the working temperature decreases to $-20^{\\circ}\\mathsf C$ (Figure 5B), the same cell indeed operated well, and a reversible charge/discharge of ${\\sim}50\\ m{\\sf A h}\\ {\\sf g}^{-1}$ can still be retained, demonstrating the benefit of hydrated eutectic electrolytes for low-temperature battery applications. \n\nAn inorganic $Z n$ -storage material, ${\\mathsf{V O P O}}_{4}.$ , was further applied to show the versatility of ZS as Zn electrolytes. The CV of the $\\mathsf{V O P O}_{4}/Z\\mathsf{S}/Z\\mathsf{n}$ battery is displayed in Figure S28A over a voltage range of $0.50{-}2.00\\mathrm{~V~}$ at a scan rate of $0.01\\mathrm{~mV}\\mathsf{s}^{-1}$ . Three prominent oxidation peaks at 1.10, 1.60, and $\\boldsymbol{1.80\\vee}$ as well as three reduction peaks at 1.60, 1.25, and $0.95\\mathsf{V}$ demonstrate the reversible redox processes of $\\mathsf{V O P O}_{4}$ cathode based on ZS. We also performed the analysis of the ex situ Zn K-edge X-ray absorption near-edge structure (XANES) on cathodic ${\\mathsf{V O P O}}_{4}$ in charge (potentiostated at 1.60, 1.70, 1.80, and 2.00 V) and discharge (potentiostated at 1.40, 1.20, 1.00, and 0.60 V) states (Figure S28C). The progressive increase and/or decrease in the intensity of the Zn signal clearly illustrates the insertion/extraction of $Z n^{2+}$ in $V\\mathsf{O P O}_{4}$ . Although the present ligand-oriented strategy for modifying electrolyte structure is customized for aqueous Zn-organic batteries, the results suggest the possibility for ZS to support other high-voltage multivalent cation-storage cathodes. \n\n# Conclusions \n\nBy mixing a neutral ligand with moderate Lewis basicity and a simple hydrated Zn salt, we developed hydrated eutectic electrolytes where the active Zn species and the water state are decoupled from traditional aqueous electrolytes but are highly suitable for the $Z n$ -organic batteries from both anode and cathode aspects. The present electrolyte system features simple formulation, low cost and convenient operation. Correspondingly, the PDB/ZS/Zn cell exhibits an excellent charge-discharge cycling with low degradation $(0.004\\%$ per cycle over 3,500 cycles). It should be noted that the remarkable cell performance is attributed to ZS that stabilizes not only Zn metal anode but also the organic cathode. RDFs, MS, and Raman results reveal that SN enters the primary solvation shell of $Z n^{2+}$ , causing the transformation from $[Z_{\\mathsf{n}}(\\mathsf{O}\\mathsf{H}_{2})_{6}]^{2+}$ to $[Z\\mathsf{n}({\\mathsf{O}}\\mathsf{H}_{2})_{\\boldsymbol{x}}({\\mathsf{S}}\\mathsf{N})_{\\boldsymbol{y}}]^{2+}$ (the equilibrium species, as revealed in single-crystal XRD, is $[Z\\mathsf{n}({\\mathsf{O}}\\mathsf{H}_{2})_{2}({\\mathsf{S}}\\mathsf{N})_{2}]^{2+})$ . One direct result of this solvation change is concerned with the drastic improvement in electrochemical behavior of electrolyte. Deposited $Z n$ in ZS is highly uniform and has a mosaic-like morphology, on account of the binding affinity of $Z n^{2+}$ and SN as evidenced by DFT calculation. Additionally, the suppressed interaction between $Z n^{2+}$ and water makes perchlorate anions insusceptible to decomposition. These factors work in synergy to guarantee the long-term cycling stability of $Z n$ anode. Furthermore, analysis of our theoretical simulations and spectral results reveals that the water molecules substituted by SN depart from the primary solvation shell of $Z n^{2+}$ and remain hydration state in the eutectic structure, resulting in the scarcity of free water, which restrains the PDB dissolution and also improves the anodic decomposition of ZS. The present strategy of taming the electrolyte structure, therefore, provides an encouraging path toward creating long-life Zn-organic batteries. \n\n# EXPERIMENTAL PROCEDURES \n\n# Resource Availability \n\nLead Contact Guanglei Cui. Correspondence: cuigl@qibebt.ac.cn. \n\n# Materials Availability \n\nThe single crystals of the $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ mixture (the $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ molar ratio is 1:8) were generated in situ by heating at around $80^{\\circ}\\mathsf{C}$ for $4\\ h$ and the mixture rested at room temperature for $12\\mathrm{~h~}$ . The slightly wet crystal was rapidly transferred to the cold ${\\sf N}_{2}$ stream on the instrument. The measurements were conducted on a Bruker Smart Apex II diffractometer using $C u-K a$ radiation $(\\lambda\\ =\\ 1.54178\\ \\mathring{\\mathsf{A}})$ with a graphite monochromator at $\\begin{array}{r}{130\\ \\mathsf{K}.}\\end{array}$ The crystallographic data and structure refinement are presented in Table S1, and the accession number for the $[Z\\mathsf{n}(\\mathsf{O H}_{2})_{2}(\\mathsf{S N})_{2}][\\mathsf{C l O}_{4}]_{2}$ reported in this paper is [The Cambridge Crystallographic Data Centre]: CCDC 1978982. \n\n# Data and Code Availability \n\nAll data needed to evaluate the conclusions in the paper are present in the paper or the Supplemental Information. \n\n# Synthesis of Poly(2,3-dithiin-1,4-benzoquinone) (PDB) \n\n2,3,5,6-tetrafluorocyclohexa-2,5-diene-1,4-dione $(0.9\\mathsf{g},0.005\\mathsf{m o l})$ ) and $N a_{2}S\\cdot9H_{2}O$ $(4.8\\mathrm{~g},0.02\\mathrm{~mol})$ ) were dissolved into a mixture solvent of ethanol $(40~\\mathrm{mL})$ and water $(50~\\mathrm{mL})$ . This solution was stirred at $80^{\\circ}\\mathsf{C}$ for $3h$ , then $30\\mathrm{mLN}$ , N-Dimethylformamide (DMF) solution containing 2,3,5,6-tetrafluorocyclohexa-2,5-diene-1,4-dione $(0.9\\ 9,0.005\\ \\mathrm{mol})$ was added. After refluxing for $10\\mathsf{h}$ , the mixture was allowed to cool down to room temperature, and the pH value was adjusted to 3–4 by $5\\%$ hydrochloric acid (HCl). Then the precipitate was collected by filtration and washed by DMF, water, and ethanol. After washing the precipitate by ethanol with Soxhlet extractor, pure PDB was obtained as a black powder. The FTIR spectrum and SEM image of as-prepared PDB are shown in Figures S24 and S25. \n\n# Synthesis of VOPO4 \n\n$4.8\\ \\mathfrak{g}$ of $V_{2}O_{5}$ powders (Aldrich) and $26.6~\\mathsf{m L}$ concentrated ${\\sf H}_{3}{\\sf P}{\\sf O}_{4}$ $85\\%$ , Aldrich) were dispersed in $115.4\\mathrm{mL}$ of deionized water. The mixed dispersion was then refluxed at $110^{\\circ}\\mathsf C$ for $16\\mathrm{~h~}$ . Thereafter, the dispersion was permitted cool down to room temperature. The yellow-greenish precipitate was finally collected by centrifugation and washed several times with water and acetone. The resulting sample was dried in vacuum at $60^{\\circ}\\mathsf{C}$ for $3h$ .90 The XRD pattern and SEM images of as-prepared $\\mathsf{V O P O}_{4}$ are shown in Figures S26 and S27. \n\n# Preparation of Electrolytes and Electrodes and Fabrication of Cells \n\nSN and $Z n(C l O_{4})_{2}\\cdot6H_{2}O$ were all purchased from Aladdin. The preparation of electrolytes was carried out by mixing SN and $Z n(C l O_{4})_{2}\\cdot6H_{2}O$ with molar ratios of 4:1, 6:1, 8:1, 10:1, and 12:1 at $353\\mathsf{K}$ until clear liquids were obtained. The PDB or $\\mathsf{V O P O}_{4}$ powders were mixed with Super $\\mathsf{P}$ additives and polyvinylidene fluoride with a weight ratio of 6:2:2 in N-Methyl pyrrolidone solvent. The mixture powders were ground with a pestle for $30~\\mathrm{min}$ . Homogeneous PDB or $\\mathsf{V O P O}_{4}$ electrode slurries were obtained, and the slurries were uniformly pasted onto SS foils with doctor blade and dried in an oven at $60^{\\circ}\\mathsf{C}$ for $12\\mathrm{~h~}$ . SS with a thickness of $0.05~\\mathsf{m m}$ (FJ100, Feintool) was used as current collector. Coin cells (2032 type) were assembled by sandwiching glass fiber paper soaked with electrolytes between the prepared cathode electrodes and $Z n$ anodes in an open atmosphere. Each cell contains $150~\\upmu\\up L$ of ZS $(8.41\\mathsf{m A h}$ of Zn) and ZW $20.18~\\mathrm{{mAh}}$ of Zn). The mass loading of PDB cathode is ${\\sim}0.21\\ m\\ g\\ c m^{-2}$ . A galvanostatic electrodeposition method was used to deposit Zn of ${\\sim}0.42m\\Delta{\\ h}\\ c m^{-2}$ on SS to prepare Zn anodes for long-cycling tests. The SS foil was washed using $5\\%H C l$ , and then deionized water to remove surface impurities. \n\n# Electrochemical Tests \n\nElectrochemical impedance spectroscopy experiments were conducted using the Biologic VMP-300 potentiostat with a frequency selected in the range from 7 MHz to $100~\\mathrm{{mHz}}$ . The galvanostatic discharge/charge measurements were performed on LAND CT2001A test system. The CV, LSV, and linear polarization measurement were conducted using Biologic VMP300. Linear polarization technique was performed by scanning between $-0.25$ and $0.25\\mathrm{~V~}$ (versus Ewe) from its open circuit voltage at the rate of $0.166\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . The working, counter and reference electrodes were Zn, platinum and $\\mathsf{A g}/\\mathsf{A g C l}$ , respectively. \n\n# Material Characterizations \n\nEDS and SEM experiments were conducted with a field emission scanning electron microscope (SEM, Hitachi S-4800). XRD patterns were recorded using a Bruker-AXS Micro-diffractometer (D8 ADVANCE) with $\\mathsf{C u-K}\\alpha1$ radiation $(\\lambda\\:=\\:1.5405\\:\\mathring{\\mathsf{A}})$ , and cycled Zn plates were washed by ethanol before XRD tests. Viscosity $(\\upeta)$ of the electrolytes was measured on a BROOKFIELD R/S Plus at $25^{\\circ}\\mathsf{C}$ and $4.24~\\mathsf{r p m}~\\mathsf{s}^{-1}$ . Highdefinition mass spectra (HDMS) were obtained on a MS spectrometer equipped with an atmospheric ionization electrospray source (Agilent 1290 UPLC/6540 QTOF), and methanol was adopted as solvent. The Raman spectra was recorded by using Thermo Scientific DXRXI system with excitation from an Ar laser at $532{\\mathsf{n m}}$ . The single crystals of the $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ mixture (the $Z n(C|O_{4})_{2}\\cdot6H_{2}O/5N$ molar ratio is 1:8) were generated in situ by heating at around $80^{\\circ}C$ for $4h$ , and the mixture rested at room temperature for $12\\mathsf{h}$ . The slightly wet crystal was rapidly transferred to the cold ${\\sf N}_{2}$ stream on the instrument. The measurements were conducted on a Bruker Smart Apex II diffractometer using $C u-K a$ radiation $(\\lambda=1.54178\\mathrm{~\\AA~}$ with a graphite monochromator at $130\\mathsf{K}$ . The crystallographic data and structure refinement are presented in Table S1, and CCDC 1978982 corresponds to $[Z\\mathsf{n}(\\mathsf{O}\\mathsf{H}_{2})_{2}(\\mathsf{S}\\mathsf{N})_{2}][\\mathsf{C}|\\mathsf{O}_{4}]_{2}$ . The $^{17}\\mathrm{O}$ NMR analyses were conducted with a Bruker AV400 spectrometer $(25^{\\circ}\\mathsf{C})$ , using $5~\\mathrm{mm}$ tubes. XPS investigation was performed with Thermo Scientific ESCA Lab $250\\mathrm{\\timesi}$ . Differential scanning calorimeter (DSC) was used to evaluate the thermal properties of the electrolytes. Samples were scanned from $-100^{\\circ}\\mathsf{C}-25^{\\circ}\\mathsf{C}$ at a rate of $5^{\\circ}C\\operatorname*{min}^{-1}$ under a nitrogen atmosphere. \n\nFTIR measurements were carried out on a Perkin-Elmer spectrometer in the transmittance mode. XANES analyses were carried out at ODE beamline at synchrotron SOLEIL, France. The XANES spectra were processed using the Athena and Artemis software packages. \n\n# MD Simulations and DFT Calculations \n\nMD simulations were performed on the electrolyte mixtures (SN, $Z n(C l O_{4})_{2}$ and $H_{2}O)$ to observe the structure changes of the electrolyte mixtures. First, the optimized electrolyte molecules were packed in a periodic box to construct the bulk systems; the compositions of simulated electrolytes are given in Table S3. The molar ratios of the electrolyte mixtures was 8:1:6 for SN, $Z n(C l O_{4})_{2},$ and $H_{2}O$ . The simulation cells contained 800 SN, $100Z n(\\mathsf{C l O}_{4})_{2},$ and $600\\ H_{2}O$ . Subsequently, all mixture systems were equilibrated by canonical ensemble (NVT) MD simulations for 1 ns at $303\\mathrm{~K~}$ and atmospheric pressure, followed by constant-pressure–constant-temperature (NPT) MD simulations for 10 ns with a 1 fs time step. All MD simulations were performed using the Forcite code.91 The temperature was controlled by a Nose-Hoover Langevin (NHL) thermostat and the pressure was controlled by a Berendsen barostat.92,93 The Ewald scheme94 and atom-based cutoff method (i.e., a radius of $15.5\\mathrm{~\\AA})$ were applied to treat electrostatic and van der Waals (vdW) interactions, respectively. All the partial atomic charges were defined using the COMPASSII force field. All quantum chemical calculations were performed by applying the DFT method with the B3LYP level and $6{-}311+6$ (d, p) basis set using Gaussian 09 program package. The structural optimization was determined by minimizing the energy without imposing molecular symmetry constraints. The binding energies of the $Z n^{2+}-H_{2}O$ and $Z n^{2+}-S N$ were defined as the interaction between different molecule fragments, composed of the interaction between $Z n^{2+}$ , SN, and $H_{2}O$ . The binding energy $\\mathsf{E}_{1}$ was calculated according to Equation 4, the expression as follows: \n\n$$\nE_{1}=E_{t o t a l}–n E(X)\n$$ \n\n(Equation 4) \n\nwhere $\\mathsf{E}_{\\mathsf{t o t a l}}$ is the structure total energy, $\\mathsf E(\\boldsymbol{\\mathsf{X}})$ is the energy of different molecule fragments $(X=2n^{2+}$ , SN, and $H_{2}O)$ , and $n$ is the number of corresponding molecule fragments according to the different structure configurations. \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental Information can be found online at https://doi.org/10.1016/j.joule. \n2020.05.018. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the Programs of the National Key R&D Program of China (grant no. 2018YFB0104300), the National Natural Science Foundation of China (grant no. 21975271, U1706229), the National Science Fund for Distinguished Young Scholars (grant no. 51625204), the Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDA22010600), Key Research and Development Plan of Shandong Province P. R. China (grant no. 2017CXZC0505) and DICP & QIBEBT Fund (grant no. DICP & QIBEBT UN201707). This original research was supported by funding from the Youth Innovation Promotion Association of Chinese Academy of Sciences (2019214). The authors gratefully acknowledge Prof. Liquan Chen for helpful discussions. We acknowledge assistance from SOLEIL beamline staff (the data of X-ray absorption spectroscopy were obtained on beamline ODE, under the support of proposal 20170287). \n\n# AUTHOR CONTRIBUTIONS \n\nW.Y., J.Z., Q.Z., and G.C. conceived the idea. W.Y., C.W., J.Z., and G.C. designed the experiments. W.Y., J.L., and J.X. performed the material preparation and chemical characterization. X.D. performed MD simulations and DFT calculations. Z.C., Z.Z., Z.C., and Y.Z. helped with electrochemical measurements. Q.K. performed the XANES experiment. All authors discussed and analyzed the data. W.Y., J.Z., Q.K., Q.Z., and G.C. wrote the manuscript. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: January 27, 2020 \nRevised: March 17, 2020 \nAccepted: May 28, 2020 \nPublished: July 1, 2020 \n\n# REFERENCES \n\n1. Kundu, D., Adams, B.D., Duffort, $\\mathsf{V}_{\\cdot,\\prime}$ Vajargah, S.H., and Nazar, L.F. (2016). A high-capacity and long-life aqueous rechargeable zinc battery using a metal oxide intercalation cathode. Nat. Energy 1, 16119. \n2. Song, M., Tan, H., Chao, D.L., and Fan, H.J. (2018). Recent advances in Zn-ion batteries. Adv. Funct. Mater. 28, 1802564. \n3. Parker, J.F., Ko, J.S., Rolison, D.R., and Long, J.W. (2018). Translating materials-level performance into device-relevant metrics for zinc-based batteries. Joule 2, 2519–2527. \n4. Kundu, D., Oberholzer, P., Glaros, C., Bouzid, A., Tervoort, E., Pasquarello, A., and Niederberger, M. (2018). Organic cathode for aqueous Zn-ion batteries: taming a unique phase evolution toward stable electrochemical cycling. Chem. Mater. 30, 3874–3881. \n5. Liang, $\\Upsilon_{\\cdot,\\prime}$ and Yao, Y. (2018). Positioning organic electrode materials in the battery landscape. Joule 2, 1690–1706. \n6. Blanc, L.E., Kundu, D., and Nazar, L.F. (2020). Scientific challenges for the implementation of Zn-ion batteries. Joule 4, 771–799. \n7. Liang, Y., Tao, $Z.,$ and Chen, J. (2012). Organic electrode materials for rechargeable lithium batteries. Adv. Energy Mater. 2, 742–769. \n8. Schon, T.B., McAllister, B.T., Li, P.F., and Seferos, D.S. (2016). The rise of organic electrode materials for energy storage. Chem. Soc. Rev. 45, 6345–6404. \n9. Song, Z., and Zhou, H. (2013). Towards sustainable and versatile energy storage devices: an overview of organic electrode materials. Energy Environ. Sci. 6, 2280–2301. \n10. Fan, X., Wang, F., Ji, X., Wang, R., Gao, T., Hou, S., Chen, J., Deng, T., Li, X., Chen, L., et al. (2018). A universal organic cathode for ultrafast lithium and multivalent metal batteries. Angew. Chem. Int. Ed. 57, 7146–7150. \n11. Yufit, V., Tariq, F., Eastwood, D.S., Biton, M., Wu, B., Lee, P.D., and Brandon, N.P. (2019). Operando visualization and multi-scale tomography studies of dendrite formation and dissolution in zinc batteries. Joule 3, 485–502. \n12. Zhao, $\\scriptstyle\\bigcirc_{\\cdot,}$ Huang, W., Luo, Z., Liu, L., Lu, Y., Li, Y., Li, L., Hu, J., Ma, H., and Chen, J. (2018). High-capacity aqueous zinc batteries using sustainable quinone electrodes. Sci. Adv. 4, eaao1761. \n13. Zang, X., Shen, C., Sanghadasa, M., and Lin, L. (2019). High-voltage supercapacitors based on aqueous electrolytes. ChemElectroChem 6, 976–988. \n14. Lim, J., Park, K., Lee, H., Kim, J., Kwak, K., and Cho, M. (2018). Nanometric water channels in water-in-Salt lithium ion battery electrolyte. J. Am. Chem. Soc. 140, 15661–15667. \n15. Wang, J., Yamada, Y., Sodeyama, K., Chiang, C.H., Tateyama, Y., and Yamada, A. (2016). Superconcentrated electrolytes for a highvoltage lithium-ion battery. Nat. Commun. 7, 12032. \n16. Suo, L., Hu, Y.S., Li, H., Armand, M., and Chen, L. (2013). A new class of Solvent-in-Salt electrolyte for high-energy rechargeable metallic lithium batteries. Nat. Commun. 4, 1481. \n17. McOwen, D.W., Seo, D.M., Borodin, O., Vatamanu, J., Boyle, P.D., and Henderson, W.A. (2014). Concentrated electrolytes: decrypting electrolyte properties and reassessing Al corrosion mechanisms. Energy Environ. Sci. 7, 416–426. \n18. Xu, K. (2014). Electrolytes and interphases in Liion batteries and beyond. Chem. Rev. 114, 11503–11618. \n19. Qian, J., Henderson, W.A., Xu, W., Bhattacharya, P., Engelhard, M., Borodin, O., and Zhang, J.G. (2015). High rate and stable cycling of lithium metal anode. Nat. Commun. 6, 6362. \n20. Naveed, A., Yang, H., Yang, J., Nuli, Y., and Wang, J. (2019). Highly reversible and rechargeable safe Zn batteries based on a triethyl phosphate electrolyte. Angew. Chem. Int. Ed. 58, 2760–2764. \n21. Wang, F., Borodin, O., Gao, T., Fan, X., Sun, W., Han, F., Faraone, A., Dura, J.A., Xu, $\\mathsf{K}_{\\cdot,\\prime}$ and Wang, C. (2018). Highly reversible zinc metal anode for aqueous batteries. Nat. Mater. 17, 543–549. \n22. Jeong, S.-K., Seo, H.-Y., Kim, D.-H., Han, H.-K., Kim, J.-G., Lee, Y.B., Iriyama, Y., Abe, T., and Ogumi, Z. (2008). Suppression of dendritic lithium formation by using concentrated electrolyte solutions. Electrochem. Commun. 10, 635–638. \n23. Yamada, Y., Furukawa, K., Sodeyama, K., Kikuchi, K., Yaegashi, M., Tateyama, Y., and Yamada, A. (2014). Unusual stability of acetonitrile-based superconcentrated electrolytes for fast-charging lithium-ion batteries. J. Am. Chem. Soc. 136, 5039–5046. \n24. Takada, $\\mathsf{K}_{\\cdot,\\prime}$ Yamada, $\\Upsilon_{\\cdot,\\cdot}$ Watanabe, E., Wang, J., Sodeyama, K., Tateyama, Y., Hirata, K., Kawase, T., and Yamada, A. (2017). Unusual passivation ability of superconcentrated electrolytes toward hard carbon negative electrodes in sodium-ion batteries. ACS Appl. Mater. Interfaces ${\\boldsymbol{\\mathscr{G}}}_{\\prime}$ 33802–33809. \n25. Suo, L., Borodin, O., Gao, T., Olguin, M., Ho, J., Fan, $\\mathsf{X}_{\\cdot,\\prime}$ Luo, C., Wang, C., and Xu, K. (2015). \"Water-in-salt\" electrolyte enables highvoltage aqueous lithium-ion chemistries. Science 350, 938–943. \n26. Qiu, H., Du, X., Zhao, J., Wang, Y., Ju, J., Chen, Z., Hu, Z., Yan, D., Zhou, $\\mathsf{X}.,$ and Cui, G. (2019). Zinc anode-compatible in-situ solid electrolyte interphase via cation solvation modulation. Nat. Commun. 10, 5374. \n27. Rajput, N.N., Qu, X., Sa, N., Burrell, A.K., and Persson, K.A. (2015). The coupling between stability and ion pair formation in magnesium electrolytes from first-principles quantum mechanics and classical molecular dynamics. J. Am. Chem. Soc. 137, 3411–3420. \n28. Li, M., Wang, C., Chen, Z., Xu, K., and Lu, J. (2020). New concepts in electrolytes. Chem. Rev. \n29. Ren, X., Chen, S., Lee, H., Mei, D., Engelhard, M.H., Burton, S.D., Zhao, W., Zheng, J., Li, $\\Omega.,$ Ding, M.S., et al. (2018). Localized highconcentration sulfone electrolytes for highefficiency lithium-metal batteries. Chem 4, 1877–1892. \n30. Zhang, C., Holoubek, J., Wu, X., Daniyar, A., Zhu, L., Chen, C., Leonard, D.P., Rodrı´guezPe´ rez, I.A., Jiang, J.X., Fang, C., and Ji, X. (2018). A ZnCl2 water-in-salt electrolyte for a reversible Zn metal anode. Chem. Commun. (Camb.) 54, 14097–14099. \n31. Wilcox, R.J., Losey, B.P., Folmer, J.C., Martin, J.D., Zeller, M., and Sommer, R. (2015). Crystalline and liquid structure of zinc chloride trihydrate: a unique ionic liquid. Inorg. Chem. 54, 1109–1119. \n32. Chen, C.Y., Matsumoto, K., Kubota, K., Hagiwara, R., and Xu, Q. (2019). A roomtemperature molten hydrate electrolyte for rechargeable zinc–air batteries. Adv. Energy Mater. 9, 1900196. \n33. Smart, N.G., Gamboa-Aldeco, M., and Bockris, J.O.M. (1993). Corrosion mechanisms of iron in concentrated acidic zinc chloride media. Corros. Sci. 34, 759–777. \n34. Ruh, A., and Spiegel, M. (2006). Thermodynamic and kinetic consideration on the corrosion of Fe, Ni and Cr beneath a molten KCl-ZnCl2 mixture. Corros. Sci. 48, 679–695. \n35. Mandai, T., and Johansson, P. (2016). Haloaluminate-free cationic aluminum complexes: structural characterization and physicochemical properties. J. Phys. Chem. C 120, 21285–21292. \n36. Muldoon, J., Bucur, C.B., and Gregory, T. (2014). Quest for nonaqueous multivalent secondary batteries: magnesium and beyond. Chem. Rev. 114, 11683–11720. \n37. Doe, R.E., Han, R., Hwang, J., Gmitter, A.J., Shterenberg, I., Yoo, H.D., Pour, N., and Aurbach, D. (2014). Novel, electrolyte solutions comprising fully inorganic salts with high anodic stability for rechargeable magnesium batteries. Chem. Commun. (Camb.) 50, 243–245. \n38. Pour, N., Gofer, Y., Major, D.T., and Aurbach, D. (2011). Structural analysis of electrolyte solutions for rechargeable Mg batteries by stereoscopic means and DFT calculations. J. Am. Chem. Soc. 133, 6270–6278. \n39. Angell, M., Zhu, G., Lin, M.C., Rong, Y., and Dai, H. (2019). Ionic liquid analogs of AlCl3 with urea derivatives as electrolytes for aluminum batteries. Adv. Funct. Mater. 30, 1901928. \n40. Coleman, F., Srinivasan, G., and Swad\u0001zbaKwa\u0001sny, M. (2013). Liquid coordination complexes formed by the heterolytic cleavage of metal halides. Angew. Chem. Int. Ed. 52, 12582–12586. \n41. Zhang, C., Ding, Y., Zhang, L., Wang, X., Zhao, Y., Zhang, X., and Yu, G. (2017). A sustainable redox-flow battery with an aluminum-based, deep-eutectic-solvent anolyte. Angew. Chem. Itd. Ed. 129, 7562–7567. \n42. Li, C., Patra, J., Li, J., Rath, P.C., Lin, M.H., and Chang, J.K. (2020). A novel moisture-insensitive and low-corrosivity ionic liquid electrolyte for rechargeable aluminum batteries. Adv. Funct. Mater. 30, 1909565. \n43. Fang, Y., Yoshii, K., Jiang, X., Sun, X.-G., Tsuda, T., Mehio, $\\mathsf{N}_{\\cdot,\\prime}$ and Dai, S. (2015). An AlCl3 based ionic liquid with a neutral substituted pyridine ligand for electrochemical deposition of aluminum. Electrochim. Acta 160, 82–88. \n44. Abood, H.M.A., Abbott, A.P., Ballantyne, A.D., and Ryder, K.S. (2011). Do all ionic liquids need organic cations? Characterisation of [AlCl2\\$nAmide]+AlCl4- and comparison with imidazolium based systems. Chem. Commun. 47, 3523–3525. \n45. Tang, B., and Row, K.H. (2013). Recent developments in deep eutectic solvents in chemical sciences. Monatsh. Chem. 144, 1427– 1454. \n46. Hong, S., Sun, X., Lian, H., Pojman, J.A., and Mota-Morales, J.D. (2020). Zinc chloride/ acetamide deep eutectic solvent-mediated fractionation of lignin produces high- and lowmolecular-weight fillers for phenolformaldehyde resins. J. Appl. Polym. Sci. 137, 48385. \n47. Zhang, J., Zhao, J., Du, H., Zhang, Z., Wang, S., and Cui, G. (2018). Amide-based molten electrolyte with hybrid active ions for rechargeable Zn batteries. Electrochim. Acta 280, 108–113. \n48. Hammond, O.S., Bowron, D.T., and Edler, K.J. (2017). The effect of water upon deep eutectic solvent nanostructure: an unusual transition from ionic mixture to aqueous solution. Angew. Chem. Int. Ed. 56, 9782–9785. \n49. Zhao, J., Zhang, J., Yang, W., Chen, B., Zhao, Z., Qiu, H., Dong, S., Zhou, X., Cui, G., and Chen, L. (2019). ‘‘Water-in-deep eutectic solvent’’ electrolytes enable zinc metal anodes for rechargeable aqueous batteries. Nano Energy 57, 625–634. \n50. Kang, Z., Wu, $\\mathsf{C}_{\\cdot,\\prime}$ Dong, L., Liu, W., Mou, J., Zhang, J., Chang, Z., Jiang, B., Wang, G., Kang, F., and Xu, C. (2019). 3D porous copper skeleton supported zinc anode toward high capacity and long cycle life zinc ion batteries. ACS Sustain. Chem. Eng. 7, 3364–3371. \n51. Pan, J., Xu, Y.Y., Yang, H., Dong, Z., Liu, H., and Xia, B.Y. (2018). Advanced architectures and relatives of air electrodes in Zn-air batteries. Adv. Sci. (Weinh.) 5, 1700691. \n52. Lee, B.S., Cui, S., Xing, X., Liu, H., Yue, X., Petrova, $\\mathsf{V}_{\\cdot,\\prime}$ Lim, H.D., Chen, R., and Liu, P. (2018). Dendrite suppression membranes for rechargeable zinc batteries. ACS Appl. Mater. Interfaces 10, 38928–38935. \n53. Schmid, M., and Willert-Porada, M. (2017). Electrochemical behavior of zinc particles with silica based coatings as anode material for zinc air batteries with improved discharge capacity. J. Power Sources 351, 115–122. \n54. Stock, D., Dongmo, S., Walther, F., Sann, J., Janek, J., and Schro¨ der, D. (2018). Homogeneous coating with an anionexchange ionomer improves the cycling stability of secondary batteries with zinc anodes. ACS Appl. Mater. Interfaces 10, 8640– 8648. \n55. Zhao, Z., Zhao, J., Hu, Z., Li, J., Li, J., Zhang, Y., Wang, C., and Cui, G. (2019). Long-life and deeply rechargeable aqueous Zn anodes enabled by a multifunctional brightenerinspired interphase. Energy Environ. Sci. 12, 1938–1949. \n56. Kang, L., Cui, M., Jiang, F., Gao, Y., Luo, H., Liu J., Liang, W., and Zhi, C. (2018). Nanoporous CaCO3 coatings enabled uniform Zn stripping/ plating for long-life zinc rechargeable aqueous batteries. Adv. Energy Mater. 8, 1801090. \n57. Wu, T.-H., Zhang, Y., Althouse, Z.D., and Liu, N. (2019). Nanoscale design of zinc anodes for high-energy aqueous rechargeable batteries. Mater. Today Nano 6, 100032. \n58. Parker, J.F., Chervin, C.N., Pala, I.R., Machler, M., Burz, M.F., Long, J.W., and Rolison, D.R. (2017). Rechargeable nickel-3D zinc batteries: an energy-dense, safer alternative to lithiumion. Science 356, 415–418. \n59. Sun, K.E., Hoang, T.K., Doan, T.N., Yu, Y., Zhu, X., Tian, Y., and Chen, P. (2017). Suppression of dendrite formation and corrosion on zinc anode of secondary aqueous batteries. ACS Appl. Mater. Interfaces 9, 9681–9687. \n60. Schmid, M., and Willert-Porada, M. (2018). Zinc particles coated with bismuth oxide based glasses as anode material for zinc air batteries with improved electrical rechargeability. Electrochim. Acta 260, 246–253. \n61. Mink, J., Ne´ meth, C., Hajba, L., Sandstro¨ m, M. and Goggin, P.L. (2003). Infrared and Raman spectroscopic and theoretical studies of hexaaqua metal ions in aqueous solution. J. Mol. Struct. 661–662, 141–151. \n62. Fujii, T., Moynier, F., Pons, M.-L., and Albare\\` de, F. (2011). The origin of Zn isotope fractionation in sulfides. Geochim. Cosmochim. Acta 75, 7632–7643. \n63. James, D.W., Armishaw, R.F., and Frost, R.L. (1978). Structure of aqueous solutions. A librational band study of hydration in solutions containing dipositive and tripositive metal ions. Aust. J. Chem. 31, 1401–1410. \n64. Barnum, D.W. (1983). Hydrolysis of cations. Formation constants and standard free energies of formation of hydroxy complexes. Inorg. Chem. 22, 2297–2305. \n65. Mainar, A.R., Iruin, E., Colmenares, L.C., Kvasha, A., de Meatza, I., Bengoechea, M. Leonet, O., Boyano, I., Zhang, $Z.,$ and Blazquez, J.A. (2018). An overview of progress in electrolytes for secondary zinc-air batteries and other storage systems based on zinc. J. Energy Storage 15, 304–328. \n66. Borodin, O., Suo, L., Gobet, M., Ren, X., Wang, F., Faraone, A., Peng, J., Olguin, M., Schroeder, M., Ding, M.S., et al. (2017). Liquid structure with nano-heterogeneity promotes cationic transport in concentrated electrolytes. ACS Nano 11, 10462–10471. \n67. Chen, Y.H., Yeh, H.W., Lo, N.C., Chiu, C.W., Sun, I.W., and Chen, P.Y. (2017). Electrodeposition of compact zinc from the hydrophobic Brønsted acidic ionic liquidbased electrolytes and the study of zinc stability along with the acidity manipulation. Electrochim. Acta 227, 185–193. \n68. Suleman, M., Kumar, Y., and Hashmi, S.A. (2015). Solid-state electric double layer capacitors fabricated with plastic crystal based flexible gel polymer electrolytes: effective role \n\nof electrolyte anions. Mater. Chem. Phys. 163, \n\n161–171. \n69. Alarco, P.J., Abu-Lebdeh, $\\mathsf{Y}_{\\cdot,\\prime}$ Abouimrane, A., and Armand, M. (2004). The plastic-crystalline phase of succinonitrile as a universal matrix for solid-state ionic conductors. Nat. Mater. 3, 476–481. \n70. Min, B.G., Son, T.W., Jo, W.H., and Choi, S.G. (1992). Thermal stability of polyacrylonitrile in the melt formed by hydration. J. Appl. Polym. Sci. 46, 1793–1798. \n71. Bashir, Z., Church, S.P., and Waldron, D. (1994). Interaction of water and hydrated crystallization in water-plasticized polyacrylonitrile films. Polymer 35, 967–976. \n72. Hammond, O.S., Bowron, D.T., Jackson, A.J., Arnold, T., Sanchez-Fernandez, A., Tsapatsaris, $\\mathsf{N}_{\\cdot,\\prime}$ Garcia Sakai, $\\mathsf{V}_{\\cdot,\\prime}$ and Edler, K.J. (2017). Resilience of malic acid natural deep eutectic solvent nanostructure to solidification and hydration. J. Phys. Chem. B 121, 7473–7483. \n73. Cui, $\\intercal_{\\cdot,\\prime}$ Lahiri, A., Carstens, $\\intercal_{\\cdot,\\prime}$ Borisenko, N., Pulletikurthi, G., Kuhl, C., and Endres, F. (2016). Influence of water on the electrified ionic liquid/solid interface: a direct observation of the transition from a multilayered structure to a double-layer structure. J. Phys. Chem. C 120, 9341–9349. \n74. Smith, E.L., Abbott, A.P., and Ryder, K.S. (2014). Deep eutectic solvents (DESs) and their applications. Chem. Rev. 114, 11060–11082. \n75. Rudolph, W.W., and Pye, C.C. (1999). Zinc(II) hydration in aqueous solution: a Raman spectroscopic investigation and an ab initio molecular orbital study of zinc(II) water clusters. J. Solut. Chem. 28, 1045–1070. \n76. Yamada, Y., Usui, K., Sodeyama, K., Ko, S., Tateyama, $\\mathsf{Y}_{\\cdot,\\prime}$ and Yamada, A. (2016). Hydratemelt electrolytes for high-energy-density aqueous batteries. Nat. Energy 1, 1619. \n77. Patel, M.B., Agarwal, A., and Bist, H.D. (1983). Single crystal Raman spectra of magnesium and zinc perchlorate hexahydrates. J. Raman Spectrosc. 14, 406–409. \n78. Zuur, A.P., Reintjes, A.H.L., and Groeneveld, W.L. (2010). Complexes with ligands containing nitrile groups.: part VIII. Organic nitriles as ligand. Rec. Trav. Chim. Pays-Bas 89, 385–391. \n79. Ghazvini, M.S., Pulletikurthi, G., Lahiri, A., and Endres, F. (2016). Electrochemical and spectroscopic studies of zinc acetate in 1-ethyl3-methylimidazolium acetate for zinc electrodeposition. ChemElectroChem $^{3,}$ 598–604. \n80. Liu, Z., El Abedin, S.Z., and Endres, F. (2015) Raman and FTIR spectroscopic studies of 1- ethyl-3-methylimidazolium trifluoromethylsulfonate, its mixtures with water and the solvation of zinc ions. ChemPhysChem 16, 970–977. \n81. Du, A., Zhang, Z., Qu, H., Cui, Z., Qiao, L., Wang, L., Chai, J., Lu, T., Dong, S., Dong, T. et al. (2017). An efficient organic magnesium borate-based electrolyte with non-nucleophilic characteristics for magnesium–sulfur battery. Energy Environ. Sci. 10, 2616–2625. \n82. Yoshida, K., Nakamura, M., Kazue, Y. Tachikawa, N., Tsuzuki, S., Seki, S., Dokko, K., and Watanabe, M. (2011). Oxidative-stability enhancement and charge transport mechanism in glyme-lithium salt equimolar complexes. J. Am. Chem. Soc. 133, 13121– 13129. \n83. Zheng, Q., Miura, S., Miyazaki, K., Ko, S., Watanabe, E., Okoshi, M., Chou, C.P., Nishimura, Y., Nakai, H., Kamiya, T., et al. (2019). Sodium- and potassium-hydrate melts containing asymmetric imide anions for highvoltage aqueous batteries. Angew. Chem. Int. Ed. 58, 14202–14207. \n84. La´ ng, G., Inzelt, G., Vrabecz, A., and Hora´ nyi, G. (2005). Electrochemical aspects of some specific features connected with the behavior of iron group metals in aqueous perchloric acid/perchlorate media. J. Electroanal. Chem. 582, 249–257. \n85. Kaur, S., Gupta, A., and Kashyap, H.K. (2020). How hydration affects the microscopic \n\nstructural morphology in a deep eutectic \n\nsolvent. J. Phys. Chem. B 124, 2230–2237. \n86. Xie, J., and Zhang, Q. (2016). Recent progress in rechargeable lithium batteries with organic materials as promising electrodes. J. Mater. Chem. A 4, 7091–7106. \n87. Xie, J., Wang, Z., Gu, P., Zhao, Y., Xu, Z.J., and Zhang, Q. (2016). A novel quinone-based polymer electrode for high performance lithium-ion batteries. Sci. China Mater. 59, 6–11. \n88. Xie, J., Wang, Z., Xu, Z.J., and Zhang, Q. (2018). Toward a high-performance all-plastic full battery with a’single organic polymer as both cathode and anode. Adv. Energy Mater. 8, 1703509. \n89. Vizintin, A., Bitenc, J., Kopac\u0003 Lautar, A., Pirnat, $\\mathsf{K}_{\\cdot,\\cdot}$ Grdadolnik, J., Stare, J., Randon-Vitanova, A., and Dominko, R. (2018). Probing electrochemical reactions in organic cathode materials via in operando infrared spectroscopy. Nat. Commun. 9, 661. \n90. Peng, L., Zhu, Y., Peng, X., Fang, Z., Chu, W., Wang, Y., Xie, Y., Li, Y., Cha, J.J., and Yu, G. (2017). Effective interlayer engineering of twodimensional ${\\mathsf{V O P O}}_{4}$ nanosheets via controlled organic intercalation for improving alkali ion storage. Nano Lett. 17, 6273–6279. \n91. Sun, H. (1998). COMPASS: an ab initio forcefield optimized for condensed-phase applicationsoverview with details on alkane and benzene compounds. J. Phys. Chem. B 102, 7338–7364. \n92. Berendsen, H.J.C., Postma, J.P.M., van Gunsteren, W.F., DiNola, A., and Haak, J.R. (1984). Molecular Dynamics with coupling to an external bath. J. Chem. Phys. 81, 3684–3690. \n93. Samoletov, A.A., Dettmann, C.P., and Chaplain, M.A.J. (2007). Thermostats for ‘‘slow’’ configurational modes. J. Stat. Phys. 128, 1321– 1336. \n94. Tosi, M.P. (1964). Cohesion of ionic solids in the born model. Solid State Phys. 16, 1–120. " + }, + { + "id": "10.1038_s41929-020-00546-1", + "DOI": "10.1038/s41929-020-00546-1", + "DOI Link": "http://dx.doi.org/10.1038/s41929-020-00546-1", + "Relative Dir Path": "mds/10.1038_s41929-020-00546-1", + "Article Title": "Performance enhancement and degradation mechanism identification of a single-atom Co-N-C catalyst for proton exchange membrane fuel cells", + "Authors": "Xie, XH; He, C; Li, BY; He, YH; Cullen, DA; Wegener, EC; Kropf, AJ; Martinez, U; Cheng, YW; Engelhard, MH; Bowden, ME; Song, M; Lemmon, T; Li, XS; Nie, ZM; Liu, J; Myers, DJ; Zelenay, P; Wang, GF; Wu, G; Ramani, V; Shao, YY", + "Source Title": "NATURE CATALYSIS", + "Abstract": "The development of catalysts free of platinum-group metals and with both a high activity and durability for the oxygen reduction reaction in proton exchange membrane fuel cells is a grand challenge. Here we report an atomically dispersed Co and N co-doped carbon (Co-N-C) catalyst with a high catalytic oxygen reduction reaction activity comparable to that of a similarly synthesized Fe-N-C catalyst but with a four-time enhanced durability. The Co-N-C catalyst achieved a current density of 0.022 A cm(-2) at 0.9 ViR-free (internal resistance-compensated voltage) and peak power density of 0.64 W cm(-2) in 1.0 bar H-2/O-2 fuel cells, higher than that of non-iron platinum-group-metal-free catalysts reported in the literature. Importantly, we identified two main degradation mechanisms for metal (M)-N-C catalysts: catalyst oxidation by radicals and active-site demetallation. The enhanced durability of Co-N-C relative to Fe-N-C is attributed to the lower activity of Co ions for Fenton reactions that produce radicals from the main oxygen reduction reaction by-product, H2O2, and the significantly enhanced resistance to demetallation of Co-N-C.", + "Times Cited, WoS Core": 538, + "Times Cited, All Databases": 568, + "Publication Year": 2020, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000594808400003", + "Markdown": "# Performance enhancement and degradation mechanism identification of a single-atom Co–N–C catalyst for proton exchange membrane fuel cells \n\nXiaohong Xie   1,11, Cheng ${\\mathsf{H e}}^{2,11}$ , Boyang $\\mathsf{L i}^{3}$ , Yanghua He ${\\textcircled{1}}4$ , David A. Cullen $\\textcircled{1}$ 5, Evan C. Wegener6, A. Jeremy Kropf $\\textcircled{10}6$ , Ulises Martinez $\\textcircled{10}$ 7, Yingwen Cheng8, Mark H. Engelhard $\\textcircled{1}$ 9, Mark E. Bowden9, Miao Song10, Teresa Lemmon1, Xiaohong S. Li1, Zimin Nie1, Jian Liu1, Deborah J. Myers6, Piotr Zelenay $\\left.\\frac{\\sqrt{5}}{4}\\right|$ 7, Guofeng Wang3, Gang Wu $\\textcircled{10}$ 4 ✉, Vijay Ramani $\\textcircled{10}2\\boxtimes$ and Yuyan Shao   1 ✉ \n\nThe development of catalysts free of platinum-group metals and with both a high activity and durability for the oxygen reduction reaction in proton exchange membrane fuel cells is a grand challenge. Here we report an atomically dispersed Co and N co-doped carbon (Co–N–C) catalyst with a high catalytic oxygen reduction reaction activity comparable to that of a similarly synthesized Fe–N–C catalyst but with a four-time enhanced durability. The Co–N–C catalyst achieved a current density of $\\mathbf{0.022A\\mathsf{cm}^{-2}}$ at $\\pmb{0.9V_{\\mathrm{iR-free}}}$ (internal resistance-compensated voltage) and peak power density of $\\pmb{0.64}\\pmb{W}\\pmb{\\mathrm{cm}}^{-2}$ in 1.0 bar ${\\bf H}_{2}/\\bar{\\bf O}_{2}$ fuel cells, higher than that of non-iron platinum-group-metal-free catalysts reported in the literature. Importantly, we identified two main degradation mechanisms for metal (M)–N–C catalysts: catalyst oxidation by radicals and active-site demetallation. The enhanced durability of Co–N–C relative to Fe–N–C is attributed to the lower activity of Co ions for Fenton reactions that produce radicals from the main oxygen reduction reaction by-product, ${\\bf H}_{2}{\\bf O}_{2},$ and the significantly enhanced resistance to demetallation of Co–N–C. \n\nPrcloetaon exncehragnygecomnevemrbsiroaned(PevEicMe)s f tuhelatcerllesqaurierehighig-ehflfyiciaecnticvye, catalysts for the oxygen reduction reaction (ORR) at the cathode1,2. Platinum-group metals (PGMs) have the highest ORR activity and are currently used as the cathode catalysts in PEM fuel cells3–5; they account for approximately half of the total PEM fuel cell cost under mass production6 and the high cost precludes their large-scale application. Transition metal and nitrogen co-doped carbon (M–N–C, $\\mathrm{M}=\\mathrm{Fe}$ , Co, Mn, Sn and so on7,8) catalysts are the most promising alternatives to PGM catalysts, yet they are not efficient enough in acidic media because of the sluggish ORR kinetics and they are not durable enough for practical applications9. Considerable effort has therefore been invested in overcoming these problems, with efforts focused, in part, on modifying the catalysts’ structures and the chemistry of M–N–C (refs 10,11). The formation of atomically dispersed $_{\\mathrm{M-N-C}}$ catalytic sites and maximizing their volumetric density have emerged as effective approaches to improve the ORR activity12–16. In particular, single-atom Fe–N–C catalysts have been extensively studied and have demonstrated high ORR activity16–18. However, Fe–N–C catalysts tend to degrade quickly in the oxidizing, acidic PEM fuel cell environment19. The degradation mechanisms remain elusive and need further investigation, even though several mechanisms, such as carbon oxidation by hydroxyl and/or hydroperoxyl radicals20,21, demetallation of Fe active sites22,23 and an increase in mass- and/or charge-transport resistance24, have been proposed. Even worse, the dissolved Fe ions from $\\mathrm{Fe-N-C}$ are detrimental to fuel cells’ durability as they catalyse radical formation from $\\mathrm{H}_{2}\\mathrm{O}_{2}$ through Fenton reactions and the radicals degrade the organic ionomers and membranes25,26 as well as the Fe–N–C catalyst itself27,28. Therefore, the replacement of Fe with metals that do not catalyse Fenton reactions is necessary, with Co being the most investigated29. Nevertheless, to date, ${\\mathrm{Co-N-C}}$ catalysts have exhibited inferior ORR activity and higher yields of the product of the two-electron $(2\\mathrm{e}^{-})$ reduction of oxygen, $\\mathrm{H}_{2}\\mathrm{O}_{2},$ than Fe–N–C catalysts. \n\nTo improve the ORR activity of ${\\mathrm{Co-N-C}}$ catalysts, one can increase the density of the $\\mathrm{CoN}_{x}$ sites considered to be catalytically active30. However, previous works indicate that increasing the Co content in the catalyst precursors typically leads to the formation of Co nanoparticles, which are not active for the ORR, and consumes Co atoms that would otherwise be available for the $\\mathrm{CoN}_{x}$ site formation31,32. The configuration between Co, N and C is one of the key factors to affect ORR activity. Previous density functional theory (DFT) calculations predicted that the coordination state of $\\mathrm{CoN}_{x}$ determines the electronic structure of Co, which significantly affects the binding energy of the oxygen species (for example, $\\mathrm{O}_{2},$ $\\mathrm{H}_{2}\\mathrm{O}_{2},$ $\\mathrm{OH^{*}}$ and ${\\mathrm{OOH}}^{*}.$ with the Co centre and thus leads to variations in ORR activity33,34. Experimentalists identified possible active site structures created using various synthetic approaches30,34,35. These studies suggest that increasing the density of $\\mathrm{CoN}_{x}$ sites and manipulating the $\\mathrm{Co-N}$ coordination in $\\scriptstyle\\mathrm{Co-N-C}$ catalysts should improve their ORR catalytic activity. \n\nConventional synthetic approaches that involve pyrolysis of the mixtures of Co, N and C precursors often result in a heterogeneous local environment for the $\\mathrm{CoN}_{x}$ site36–38. Zeolitic imidazole frameworks (ZIF-8) were recently used as effective precursors to synthesize ${\\mathrm{Co-N-C}}$ catalysts due to their capability to yield $\\mathrm{CoN}_{x}$ sites and form porous structures during the pyrolysis39. Their high surface area and abundant micropores offer the flexibility to dope Co-containing molecules or Co ions into the structure40, and thus represent an attractive direction for further optimization of the Co–N–C catalysts. \n\nHere we report a single-atom $\\scriptstyle\\mathrm{Co-N-C}$ catalyst synthesized by introducing and maintaining a high content of atomic $\\mathrm{CoN}_{x}$ sites to enhance the ORR activity in an acidic environment. Our approach is to increase the density of single Co sites by immobilizing the ligand-chelated $\\mathrm{CoN}_{x}$ moieties in the micropores of ZIF-8 through a solution synthesis pathway, distinct from previous works in which Co was doped into ZIF-8 through a $\\scriptstyle\\mathbf{Co-Zn}$ ion exchange32,41. In our approach, we take advantage of ZIF-8’s unique hydrocarbon networks that function as protective fences between individual Co atoms, which decrease their mobility and avoid $\\scriptstyle\\mathrm{Co}$ agglomeration. The $\\mathrm{CoN}_{x}$ moieties in the ZIF-8 micropores are directly converted into $\\mathrm{CoN}_{x}$ sites with high-temperature pyrolysis. Our extensive physical characterization reveals a high density of atomically dispersed Co and the $\\mathrm{CoN}_{x}$ structure is believed to be porphyrin like, $\\mathrm{CoN}_{4}\\mathrm{C}_{12},$ in nature. The catalyst exhibits a high ORR activity, with a half-wave potential $(E_{1/2})$ of $0.82\\mathrm{V}$ versus the reversible hydrogen electrode (RHE) at a $0.6\\mathrm{mgcm}^{-2}$ loading in a rotating ring-disk electrode (RRDE) test, a current density of 0.022 A cm−2 at 0.9 ViR-free (internal resistance-compensated voltage) and a peak power density of $0.64\\mathrm{W}\\mathrm{cm}^{-2}$ in 1.0 bar $\\mathrm{{H}}_{2}/\\mathrm{{O}}_{2}$ fuel cell tests, which are the highest fuel cell activities reported for non-Fe $\\mathrm{\\Delta\\M-N-C}$ cathodes (Supplementary Table 1). Further, the $\\scriptstyle\\mathrm{Co-N-C}$ catalyst was found to be much more durable than an Fe–N–C catalyst synthesized using the same approach, and this superior durability is attributed to the lower activity of Co ions for the Fenton reactions (and thus lower rates of radical formation and catalyst attack by the radicals) and the significantly enhanced resistance to demetallation of the $\\scriptstyle\\mathrm{Co-N-C}$ . We identified important differences in the demetallation of $\\scriptstyle\\mathrm{Co-N-C}$ versus ${\\mathrm{Fe-N-C}},$ as $\\scriptstyle\\mathrm{Co-N-C}$ demonstrates a fivefold reduced demetallation. We also observed that the presence of oxygen in the environment dramatically increases demetallation for Fe–N–C, consistent with our theoretical simulation results. \n\n# Results \n\nElectrocatalyst synthesis and characterization. The synthesis of Co–N–C catalysts is schematically shown in Fig. 1a. We introduced Co during the growth of ZIF-8 by adding ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ (acac, acetylacetonate) and $\\mathrm{Zn(NO_{3})_{2}{\\cdot}6H_{2}O}$ together with 2-methylimidazole $\\mathrm{{(mIm)}}$ in methanol. The ZIF-8 networks were formed with the assembly of $Z\\mathrm{n}^{2+}$ and $\\mathrm{mIm}$ , and ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ molecules were encapsulated in ZIF-8 micropores (denoted as $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}{-}8_{\\cdot}$ ) (Supplementary Fig. 1). Fourier difference analysis from powder X-ray diffraction (PXRD) confirms the formation of ZIF-8 and the presence of a guest molecule, that is, ${\\mathrm{Co}}({\\mathrm{acac}})_{3},$ in the ZIF-8 micropores as a result of encapsulation (Supplementary Fig. 2 and Supplementary Note 1). The absence of the PXRD peaks characteristic of ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ indicates that it was not present as a separate crystalline entity. X-ray absorption spectroscopy (XAS) analysis indicates that the Co K-edge X-ray absorption near-edge structure (XANES) spectrum for $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ is the same as that for ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ (Supplementary Fig. 3 and Supplementary Note 2) and differs from that for Co-doped ZIF- $8^{42}$ . This confirms that ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ molecules were confined in the ZIF-8 micropores and that direct Co doping into ZIF-8 did not occur. Moreover, the pore size distribution analysis shows a substantial diminution of $9{-}\\mathrm{\\bar{1}}3\\mathrm{\\:\\mathring{A}}$ and the formation of $13{-}17\\mathring{\\mathrm{A}}$ micropores in $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ as compared with those of bare ZIF-8 (Supplementary Fig. 4), and thermogravimetric analysis shows that the stability of ${\\mathrm{Co}}({\\mathrm{acac}})_{3}$ in $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ was enhanced compared with that of ${\\mathrm{Co}}({\\mathsf{a c a c}})_{3}$ (Supplementary Fig. 5), which provides additional evidence for such an encapsulation43,44. \n\nThe obtained $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ and additional mIm were ultrasonically redispersed in methanol followed by a solvothermal treatment at $140^{\\circ}\\mathrm{C}$ for four hours to convert $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ into $\\mathrm{Co}(\\mathrm{mIm})_{4}@\\mathrm{ZIF}{-}8$ through ligand exchange (acac to mIm). XANES analyses confirm the successful ligand exchange (Supplementary Fig. 3 and Supplementary Note 2), which was also evidenced by a distinct colour change of the precursors from sage green for $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ to purple for $\\mathrm{Co}(\\mathrm{mIm})_{4}@\\mathrm{ZIF}{-}8$ (Supplementary Fig. 6). The Fourier difference map (Supplementary Fig. 2 and Supplementary Note 1), pore size distribution (Supplementary Fig. 4) and thermogravimetric analysis (Supplementary Fig. 5) of $\\mathrm{Co}(\\mathrm{mIm})_{4}@\\mathrm{ZIF}{-}8$ show characteristics that are similar to those of $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ , which indicates that $\\mathrm{Co(mIm)_{4}}$ is encapsulated in the ZIF-8 micropores. $\\mathrm{Co}(\\mathrm{mIm})_{4}@\\mathrm{ZIF}{-}8$ precursors were pyrolysed at $1,000^{\\circ}\\mathrm{C}$ under an Ar gas atmosphere. The $Z\\mathrm{n}$ in ZIF-8 easily evaporates at temperatures above $950^{\\circ}\\mathrm{C},$ and $\\mathrm{Co(mIm)_{4}}$ within the ZIF-8 micropores is directly converted into atomically dispersed $\\mathrm{CoN}_{x}$ sites in porous carbon (this catalyst is designated as $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0,1.0$ means $a t\\%$ of Co in the catalyst)). During the pyrolysis, the hydrocarbon networks of ZIF-8 served as a protective fence to prevent Co agglomeration. To understand the role of the ligand exchange, the $\\bar{\\mathrm{Co}}(\\mathrm{acac})\\mathrm{-NC}(1.0)$ catalyst was also synthesized by the same method but without the acac to mIm ligand exchange of the $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ precursors. \n\nFigure 1b shows the morphology of the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ : a rhombododecahedron shape and a rough surface. Highly disordered carbons with randomly oriented graphitic domains and less dense, pore-like morphologies are observed in the bright-field (BF) scanning transmission electron microscopy (STEM) image (Fig. 1c). High-angle annular dark-field (HAADF) STEM images (Fig. 1d and Supplementary Fig. 7a,b) indicate that $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ is rich in atomic Co sites. PXRD results verify the absence of a detectable amount of crystalline Co phases, which indicates that $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ is substantially free of metallic Co or Co carbide (Supplementary Fig. 2). The electron energy loss point spectrum, taken by placing the electron probe directly on a single atom, as shown in the inset to Fig. 1e by the bright dot (red cross) in the HAADF-STEM image, shows the co-location of Co and $\\mathrm{N}_{:}$ , which suggests that single Co atoms are coordinated by N (ref. 32). Quantitative elemental analysis by $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) (Supplementary Table 2) and STEM energy-dispersive X-ray spectroscopy (Supplementary Fig. 8) reveal that the Co content in the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ is $1.0\\ \\mathrm{at\\%}$ , which is among the highest when compared with those of other non-Fe M–N–C ORR catalysts for an acidic environment34,41. No Fe or Mn was detected in $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ by XPS (Supplementary Table 2), which was further confirmed by inductively coupled plasma optical emission spectrometry (ICP-OES; Supplementary Table 3). By contrast, $\\mathrm{Co}(\\mathrm{acac}){-}\\mathrm{NC}(1.0)$ showed a similar Co content as that of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ , but with less single-atom Co (Co clusters co-existing with atomically dispersed Co) (Supplementary Fig. 7c,d), as further confirmed by PXRD (Supplementary Fig. 2) and XAS (Supplementary Fig. 9 and Supplementary Note 3) analysis. Note that Co in ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ is not directly coordinated with N, Co–N coordination in $\\mathrm{Co}(\\mathrm{acac}){-}\\mathrm{NC}(1.0)$ must arise from the ZIF-8 ligand. Meanwhile, the formation of a heterogeneous structure of the $\\mathrm{Co}(\\mathrm{acac}){-}\\mathrm{NC}(1.0)$ catalyst is probably due to ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ decomposition at relative low temperatures (Supplementary Fig. $5)^{45}$ to form Co atoms that may be mobile at a high temperature and thereby aggregate into Co clusters. \n\n![](images/7db8668f727e2050ec362fc9fdff32b2b34a8e168e9873466ed6ae44b037599d.jpg) \nFig. 1 | Synthesis and characterization of the atomically dispersed Co–N–C catalyst. a, A two-step encapsulation and ligand-exchange approach effectively introduces $C o N_{4}$ complexes into the ZIF-8 micropores. Subsequent one-step pyrolysis produces atomic $C o N_{4}$ sites dispersed into porous carbon. b,c, Representative BF-STEM images of the Co(mIm)–NC(1.0) catalyst. d,e, HAADF-STEM image (d) and electron energy loss point spectrum (e) to verify the Co–N coexistence at the atomic level in the Co(mIm)–NC(1.0) catalyst. (The HAADF-STEM image inset in e shows where the electron energy loss point spectrum was taken.) a.u., arbitrary units. \n\nFurther evidence for $\\mathrm{CoN}_{x}$ coordination and information as to the local chemical environment were obtained from XAS. As shown in Fig. 2a, the Co K-edge XANES spectrum edge energy $(\\sim7,730\\mathrm{eV})$ for $\\bar{\\mathrm{Co}}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)\\$ is similar to that for the $\\mathbf{\\boldsymbol{C}}\\mathbf{0}^{\\mathrm{{u}}}$ reference samples, which shows that the valence state of Co in $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ ) is $^{2+}$ , consistent with previous results30,34,46. Careful examination of the pre-edge region $^{7,708-7,710\\mathrm{eV}}$ shows that $\\mathrm{Co}(\\mathrm{mIm})-$ $\\mathrm{NC}(1.0)$ shows a higher pre-edge peak intensity compared with that of octahedral $\\mathrm{Co^{\\mathrm{u}}(N O_{3})_{2}{\\cdot}6H_{2}O}$ (ref. 34) and square planar $\\mathbf{\\boldsymbol{C}}\\mathbf{0}^{\\mathrm{{II}}}$ phthalocyanine47. This indicates that $C\\mathrm{{o}}$ in $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ is in a less centrosymmetric coordination environment, for example, non-planar $\\mathrm{CoN}_{x},$ than those in the literature cited. A comparison of our experimental XANES spectrum with the XANES simulation of Zitolo et  al.30 further indicates that the XANES region of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ best matches that of $\\mathrm{CoN}_{x}$ in a micropore-hosted porphyrinic coordination environment, that is, non-planar $\\mathrm{CoN}_{4}\\mathrm{C}_{12}$ (Supplementary Fig. 10). From both the Fe Mössbauer spectroscopic and XANES analyses (Supplementary Fig. 11 and Supplementary Note 4), a similarly synthesized $\\mathrm{Fe(mIm)-}$ – $\\mathrm{NC}(1.0)$ catalyst that has a similar atomic metal dispersion and carbon structure (Supplementary Fig. 12) to that of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ ) also has a micropore-hosted porphyrin-like $\\mathrm{FeN}_{4}\\mathrm{C}_{12}$ structure. \n\nSimilar structures are reported in the literature for $\\scriptstyle\\mathrm{Co-N-C}$ and Fe–N–C catalysts synthesized using same methods12,30,48. \n\nThe Fourier transform (FT) of the extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) spectrum for $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ , which has not been phase corrected, exhibits a prominent peak at ${\\sim}1.4\\mathring\\mathrm{A}$ corresponding to the first coordination shell of $\\mathrm{CoN}_{x}$ (Fig. 2b)30,49. The coordination number (CN) of $\\mathrm{CoN}_{x},$ derived from the EXAFS fit, is $3.9\\pm0.5$ and the $\\mathrm{Co-N}$ bond length is $1.93\\pm0.01\\mathring\\mathrm{A}$ (Supplementary Table 4), which indicates the dominant $\\mathrm{CoN}_{x}$ in $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ is $\\mathrm{CoN_{4}}$ A very minor $\\scriptstyle\\mathbf{Co-Co}$ peak arising from Co metal is also evident at ${>}2\\mathring{\\mathrm{A}}$ in the FT. Further analysis of the CN for this scattering path and comparison with that of metallic Co foil shows that metallic Co comprises ${\\sim}4\\%$ of the total Co in the catalyst (Supplementary Table 4). The lack of second-shell scattering indicates that the $\\scriptstyle{\\mathrm{Co}}$ clusters are small, consistent with the PXRD (Supplementary Fig. 2) and HAADF-STEM (Fig. 1d and Supplementary Fig. 7) results, which show that the vast majority of Co is atomically dispersed. Both the $\\mathrm{Co-N}$ and the Co–Co scattering paths are observed in the FT of the EXAFS of Co(acac)– NC(1.0); however, unlike $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ , a notable amount of Co–Co scattering is observed, estimated to be ${\\sim}11\\%$ of the total Co. Second-shell scattering was observed for $\\mathrm{Co}(\\mathrm{acac}){-}\\mathrm{NC}(1.0)$ , which indicates that the Co clusters are larger than in $\\mathrm{Co}(\\mathrm{mIm})-$ NC(1.0). This is consistent with the observation from the STEM images, which show both atomic $\\mathrm{CoN}_{x}$ sites and Co clusters (Supplementary Fig. 7), and from the PXRD results, which show the presence of crystalline Co (Supplementary Fig. 2). \n\nMicropores are known to host the majority of $\\mathrm{MN}_{x}$ active sites in $\\mathrm{\\Delta\\M-N-C}$ catalysts50–52. Surface area analysis shows similar Brunauer–Emmett–Teller surface areas and dominant micropore surface areas for all the Co catalysts (Supplementary Table 5). \n\n![](images/5e07ee19d38b34b5b2681073d3dce6316c8ea740d4cc7d0d289541440b24c475.jpg) \nFig. 2 | Structural characterization of the Co–N–C catalysts. a,b, Co K-edge XANES spectra (a) and Fourier transforms of the EXAFS spectra (b) for $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ , Co(acac)–NC(1.0) and the reference samples. c, Micropore distribution for different $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(x)$ (x is the $a t\\%$ of Co) catalysts as a function of Co content (using the non-local DFT method). d, Plan view of presumed porphyrin-like ${\\mathsf{C o N}}_{4}{\\mathsf{C}}_{10}$ sites in the micropores. \n\nAn in-depth micropore distribution analysis from the non-local DFT method shows a substantial diminution of $9{-}13\\mathring\\mathrm{A}$ micropores in $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}$ with a systematic increase in the Co doping content from 0.28 to $1.0\\mathrm{at\\%}$ (Fig. 2c), as compared with that of NC derived from bare ZIF-8, which can be interpreted as indicative of micropore-hosted $\\mathrm{CoN_{4}}$ sites that inhabit the micropores of NC. $\\mathrm{MN_{4}}$ ${\\bf\\dot{M}}={\\bf F}{\\bf e}$ or Co) active sites in micropores of M–N–C catalysts typically have the non-planar porphyrin-like $\\mathrm{MN}_{4}\\mathrm{C}_{12}$ structure30,53, as depicted in Fig. 2d, consistent with our analysis from the XANES and Mössbauer spectroscopic results. \n\nORR activity. The ORR activity of catalysts was first evaluated in $\\mathrm{O}_{2}$ -saturated 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ using the RRDE technique. Without Co doping, the NC catalyst showed a poor activity with a very low onset potential $\\cdot E_{\\mathrm{onset}}$ $E$ at a current density of $0.1\\mathrm{mAcm^{-2}}$ ) of $0.78\\mathrm{V}$ and $E_{1/2}$ of only 0.61 V versus RHE (Fig. 3a). By contrast, Co doping significantly enhanced the ORR activity. $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ exhibited a high ORR activity with an $E_{\\mathrm{onset}}$ of $0.93\\mathrm{V}$ and $E_{1/2}$ of $0.82\\mathrm{V},$ which are only ${\\sim}25$ and $\\sim35\\mathrm{mV},$ respectively, less than that of the $\\mathrm{Pt/C}$ catalyst $20\\mathrm{wt\\%}$ Pt on Vulcan Carbon, Fuel Cell Store), albeit with a ten times lower loading for the $\\mathrm{Pt}$ (that is, $600\\upmu\\mathrm{g}\\mathsf{c m}^{-2}$ for the M–N–C catalysts versus $60\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ for $\\mathrm{Pt}{\\dot{}}$ ). This ORR activity is among the best for a non-Fe PGM-free ORR catalyst in acids (Supplementary Table 6). $\\mathrm{Co}(\\mathrm{acac}){-}\\mathrm{NC}(1.0)$ exhibits an $E_{\\mathrm{onset}}$ of $0.86\\mathrm{V}$ and an $E_{1/2}$ of $0.77\\mathrm{V},$ both much lower than that of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ , which indicates that the ligand exchange step leads to an improved ORR activity. The influence of the Co doping amount on the ORR activity was also investigated. The activity was found to increase continuously with increasing Co content (Fig. 3a and Supplementary Fig. 13) in the catalyst. This indicates that the ORR activity is directly related to the $\\mathrm{CoN_{4}}$ concentration as the majority of Co in $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}$ is atomic Co in the form of porphyrin-like $\\mathrm{CoN}_{4}\\mathrm{C}_{12},$ as evidenced from the above HAADF-STEM, XRD, XANES and pore distribution analyses. We note that $1.0{\\mathrm{at\\%}}$ is the highest Co content for $\\mathrm{Co}(\\mathrm{mIm}){\\cdot}\\mathrm{NC}$ that we could obtain using our current synthesis method, most probably due to limitations in the amount of ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ that could be encapsulated in ZIF-8 micropores during precursor synthesis (Supplementary Table 3). Further improvement is expected through the development of new approaches to encapsulate more ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ in the ZIF-8 host. The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ is below $1.5\\%$ (Fig. 3b), as determined by RRDE tests, which indicates a dominant four-electron $\\left(4\\mathrm{e}^{-}\\right)$ ORR pathway. This $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield is lower than those previously reported for $\\scriptstyle\\mathrm{Co-N-C}$ catalysts (Supplementary Fig. 14). When the catalyst loading on the disk electrode was decreased from 600 to $37.5\\upmu\\mathrm{gcm}^{-2}$ , the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield remained very low $(<5\\%)$ (Supplementary Fig. 14), which confirms the predominantly $4\\mathrm{e}^{-}$ instead of $2\\mathrm{e}^{-}+2\\mathrm{e}^{-}$ ORR pathway. \n\nThe best-performing $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}$ catalyst was further evaluated in PEM fuel cell cathodes. In the fuel cells tested with 1.0 bar $\\mathrm{H}_{2}/$ $\\mathrm{O}_{2}\\mathrm{:}$ , the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst generated high current densities of $0.022\\mathrm{Acm}^{-2}$ at $0.9\\mathrm{V_{iR-free}}$ (Fig. 3c) and $0.044\\mathrm{Acm}^{-2}$ at $0.87\\mathrm{V}_{\\mathrm{iR-free}},$ that is, only $30\\mathrm{mV}$ lower than the US Department of Energy activity target of $0.044\\mathrm{Acm}^{-2}$ at $0.90\\mathrm{V_{iR\\mathrm{-free}}}$ (ref. 54). Moreover, the fuel cell achieved a peak power density of $0.64\\mathrm{W}\\mathrm{cm}^{-2}$ (Fig. 3d), which is the best-reported activity for a non-Fe PGM-free catalyst in $\\mathrm{H}_{2}/$ $\\mathrm{O}_{2}\\mathrm{PEM}$ fuel cells (Supplementary Table 1). Under practical 1.0 bar $\\mathrm{H}_{2}/$ air conditions, the fuel cell generated a peak power density of $0.32\\mathrm{W}\\mathrm{cm}^{-2}$ , among the highest performance reported for a non-Fe PGM-free PEM fuel cell cathode catalyst. We attribute the high ORR activity and fuel cell performance to a combined effect of the high active-site density of the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst (Fig. 1d) and the high accessibility of active sites. The high porosity of the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ itself (particularly, the abundance of ${>}2\\mathrm{nm}$ meso- and/or macropores (Fig. 2c)) and the catalyst layer (abundance of ${>}50\\mathrm{nm}$ macropores (Supplementary Fig. 15)) enhance the mass transfer, and the uniform Nafion ionomer distribution within the catalyst layer (Supplementary Fig. 15) benefits ion transfer and the formation of triple-phase boundaries55. \n\n![](images/b9619aec6e619bd3ee46aa9494271b1e9ca99d5bdb1c4f7181ad1a411b6116f8.jpg) \nFig. 3 | RRDE and PEM fuel cell performance measurements. a, Steady-state ORR polarization plots for different ${\\mathsf{C o}}({\\mathsf{m l m}}){\\mathsf{-N C}}$ catalysts as a function of Co content $(\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(x))$ , Co(acac)–NC(1.0) and $\\mathsf{C o}$ -free NC in $0.5M$ ${\\mathsf{H}}_{2}{\\mathsf{S O}}_{4},$ and for $20\\%$ Pt/C $60\\upmu\\up g$ Pt on the electrode disk) in $0.1M\\mathsf{H C l O}_{4}$ under $\\mathsf{O}_{2}$ saturation. Test conditions: $25^{\\circ}\\mathsf{C}$ , rotation speed of 900 r.p.m. and catalyst loading on RDE of $600\\upmu\\upxi{\\mathsf{c m}}^{-2}$ . b, Four-electron selectivity (that is, ${\\sf H}_{2}{\\sf O}_{2}$ yield) of the ORR on the electrodes (ring potentia $\\mathbf{\\lambda}=1.3\\lor\\cdot$ ). c, $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ activity at $0.9V_{\\mathrm{iR-free}}$ measured under 1.0 bar ${\\sf H}_{2}/\\sf O_{2},$ cathode loading of $5.8\\mathsf{m g}_{\\mathsf{c o(m l m)}-\\mathsf{N C(1.0)}}\\mathsf{c m}^{-2}$ and anode loading of $0.3\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2}$ , $80^{\\circ}C$ and $100\\%$ relative humidity (RH). d, Fuel cell performance (dashed-dot: power density, full line: polarization curves) of $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ measured under 1.0 bar ${\\sf H}_{2}/\\sf{O}_{2}$ and ${\\sf H}_{2}/\\sf a i r$ , cathode loading of $6.3\\mathsf{m g}_{\\mathsf{c o(m l m)}-\\mathsf{N C(1.0)}}\\mathsf{c m^{-2}}$ anode loading of $0.3\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2}$ , $80^{\\circ}\\mathsf C$ , $100\\%$ RH. \n\nCatalyst durability. The durability of the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{C}(1.0)$ catalyst was first studied using RRDE and compared with that of the similarly synthesized $\\mathrm{Fe}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst. After 10,000 potential cycles from 0.6 to $1.0\\mathrm{V}$ versus RHE in an $\\mathrm{~O}_{2}$ -purged $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte, we observed only an $11\\%$ current density degradation at $0.85\\mathrm{V}$ for $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ (Fig. 4a), over four times less than that for $\\mathrm{Fe}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ , which degraded by $47\\%$ (Fig. 4b). Further, $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ exhibited a much smaller loss in $E_{1/2}$ $(8\\mathrm{mV})$ , $20\\mathrm{mV}$ lower than that for $\\mathrm{Fe}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ $28\\mathrm{mV}$ loss in $\\scriptstyle{E_{1/2}},$ ). The increases in capacitive current (Fig. 4a inset) and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield (Fig. 4c) for $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ after the durability tests are much lower than those for $\\mathrm{Fe(mIm)}{-}\\mathrm{NC}(1.0)$ (Fig. 4b inset and Fig. 4c), which indicates a much lower oxidation and degradation of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ . $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ also has a higher durability than that of $\\mathrm{Fe(mIm)}{-}\\mathrm{NC}(1.0)$ when subjected to a 100 hour hold at a potential of $0.7\\mathrm{V}$ in an $\\mathrm{O}_{2}$ -purged 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte. After the 100 hour tests, the current density at $0.85\\mathrm{V}$ for $\\mathrm{Co}(\\mathrm{mIm})-$ NC(1.0) decreases by $17\\%$ , much less than the $58\\%$ observed for $\\mathrm{Fe}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ (Supplementary Fig. 16a–c). \n\nTo evaluate catalyst durability in the more practical fuel cell environment, we held the voltage of fuel cells that contained the two cathode catalysts, $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ and $\\mathrm{Fe}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ , at $0.7\\mathrm{V}$ for 100 hours with 1.0 bar $\\mathrm{H}_{2}$ on the anode and 1.0 bar air on the cathode. During the tests, the fuel cell current density at $0.7\\mathrm{V}$ degraded by $20.5\\%$ for the fuel cell with the $\\mathrm{Co}(\\mathrm{mIm})-$ NC(1.0) cathode versus $46.8\\%$ for the fuel cell with the $\\mathrm{Fe}(\\mathrm{mIm})-$ NC(1.0) cathode (Fig. 4d and Supplementary Fig. 17a,b). Given the similar properties of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ and $\\mathrm{\\ddot{F}e(m I m)-N C(1.0)}$ , that is, the same metal–nitrogen coordination, same atomic dispersion and same carbon structure (Supplementary Fig. 10–12), we attribute the enhanced durability of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ to the lower activity of Co ions for the radical-generating Fenton reactions56,57 and to the intrinsic stability of the $\\mathrm{CoN_{4}}$ sites. However, a more in-depth study is needed as to the mechanism of M–N–C catalyst degradation and why $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ is more durable. In the case of PGM-free $\\mathrm{M-N-C}$ catalyst, there are very limited studies on degradation mechanisms, most of which focused on $\\mathrm{Fe-N-C}$ (refs $^{20-22,27,28,58,59})$ and revealed the main degradation mechanisms, which included catalyst oxidation by radicals and active site demetallation. Experiments and theoretical simulations to elucidate and compare the degradation mechanisms for the $\\scriptstyle\\mathrm{Co-N-C}$ and Fe–N–C catalysts of this study are described in the next section. \n\n![](images/2354abefa63549faabfb46316f73dc7204589c4aeeefdcfe32d59c0ea9b35fd8.jpg) \nFig. 4 | Catalysts durability studied on RRDE and MEA. a,b, Steady-state ORR polarization plots and (insets) CV before and after the potential cycling $(0.6\\ –1.0\\lor$ versus RHE: $\\mathsf{O}_{2}$ -purged $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4},$ $50\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}.$ , 200 r.p.m., $25^{\\circ}\\mathsf{C})$ for the $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ (a) and Fe(mIm)–NC(1.0) (b) catalysts. c, ${\\sf H}_{2}{\\sf O}_{2}$ percentage of the ORR on $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ and Fe(mIm)–NC(1.0) before and after the potential cycling (ring potentia $\\mathbf{\\lambda}=1.3\\lor\\cdot$ . d, Durability tests of the $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ and Fe(mIm)–NC(1.0) catalysts in MEA in 1 bar $\\mathsf{H}_{2},$ /air at a constant cell voltage of $0.7\\mathrm{V}$ for $\\mathsf{100h}$ . \n\nCatalyst degradation mechanisms. Chemical oxidation of M–N–C catalysts by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ -derived radicals, not by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ itself20,27,57, rather than by electrochemical oxidation, has been proposed as one of the key mechanisms of PGM-free $\\mathrm{\\Delta\\M-N-C}$ catalyst degradation during normal fuel cell operations. Here we first studied the degradation of the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst with a focus on chemical oxidation. \n\nKey experiments to determine the likely mechanism of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ degradation involved in  situ determination of $\\mathrm{CO}_{2}$ in an operating PEM fuel cell (Supplementary Fig. 18). $\\mathrm{CO}_{2}$ emission was found to increase abruptly after the gas feed to the cathode was switched from $\\Nu_{2}$ to $\\mathrm{O}_{2}$ at a cell voltage of $\\mathrm{~\\i~}0.3\\mathrm{V}$ (Fig. 5a). \n\n$\\mathrm{CO}_{2}$ emission slightly decreased when the cell voltage was switched from 0.3 to $0.8\\mathrm{V},$ whereas $\\mathrm{CO}_{2}$ emission increased when the cell voltage was switched back to $0.3\\mathrm{V}.$ $\\mathrm{CO}_{2}$ emission decreased substantially after the gas feed to the cathode was switched back from $\\mathrm{O}_{2}$ to $\\Nu_{2}$ . These results confirm that the majority of $\\mathrm{CO}_{2}$ was from the chemical oxidation of catalysts and not from the electrochemical oxidation, which is electrode potential dependent. The chemical oxidation is most probably caused by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ -derived radicals as it happens during oxygen reduction. We propose that the carbon oxidation of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ follows two main pathways: pathway I is the direct oxidation to $\\mathrm{CO}_{2}.$ mainly of very unstable carbon (and surface functional groups), most of which occurs in the early stages of the fuel cell operations, or by uncontrolled transient $\\mathrm{~O}_{2}$ in and/or out and fuel cell voltage change, as can be seen from the transient $\\mathrm{CO}_{2}$ spikes (Fig. $_{5\\mathrm{a},\\mathrm{c})}$ ; and pathway II is the oxidation to surface functional groups (reversible oxidation) and further to $\\mathrm{CO}_{2}$ (irreversible oxidation), which lasts until the end of the catalyst’s life. During the experiment, $\\mathrm{CO}_{2}$ emission from pathway I decreases rapidly, whereas $\\mathrm{CO}_{2}$ emission from pathway II maintains a downward trend after the transient is observed. Strong evidence is given in the literature for the reversible surface oxidation of carbon20,59. We also observed reversible surface oxidation, which includes the partial recovery of the ORR activity of the catalyst on catalyst renewal (Supplementary Fig. 16d) and the increase in capacitive current of the catalyst in cyclic voltammetry (CV) measurements in Ar-saturated $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ after a durability test in $\\mathrm{~O}_{2}$ (Fig. 4a,b insets), particularly in the redox potential region of the quinone/ hydroquinone couple58. \n\n![](images/1707f7c21d34ff4cf5b6e32d9d3811eb205eaf304ede3b8cd08d5838e661771e.jpg) \nFig. 5 | Fundamental understanding of degradation mechanisms. a, In situ ${\\mathsf{C O}}_{2}$ emission test from the fuel cell cathode with the $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ catalyst (top: current density generated under the displayed conditions (gas, voltage); bottom: ${\\mathsf{C O}}_{2}$ emissions during the voltage steps shown on top). b, Normalized current density at a voltage of $0.85\\mathsf{V}$ after voltage-step cycling $.0.4\\mathsf{V}$ for 55 min and $0.85\\mathsf{V}$ for 5 min) for $50\\mathsf{h}$ (cycles). Test conditions: cathode catalyst loading $6.3\\mathsf{m g}_{\\mathsf{c o(m l m)}-\\mathsf{N C}(1.0)}\\mathsf{c m}^{-2}$ , anode loading $0.3\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2}$ , 1.0 bar ${\\sf H}_{2}/\\sf{O}_{2},$ $80^{\\circ}\\mathsf{C}$ , $70\\%$ RH. c, Comparison of ${\\mathsf{C O}}_{2}$ emissions from fuel cell cathodes with the $\\mathsf{C o}(\\mathsf{m l m}){\\mathsf{-N C}}(1.0)$ and Fe(mIm)–NC(1.0) catalysts (1.0 bar ${\\sf H}_{2}/\\sf{O}_{2},$ $100\\%$ RH, $80^{\\circ}C)$ . d,e, ICP-OES (d) and RRDE $(E_{1/2})$ (e) results of the metal leaching experiments. The metal leaching amount was recorded after electrochemical cycling ( $_{.0.6\\vee}$ for 3 s, open circuit voltage (OCV) for 3 s, 10 h) in $A r-$ and $\\mathsf{O}_{2}$ -purged 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at $25^{\\circ}\\mathsf{C}$ and in $\\mathsf{O}_{2}$ -purged 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at $80^{\\circ}C$ . The error bars represent standard deviations and were determined from two independent experiments performed under the given conditions. $\\mathbf{\\widehat{f}},$ Atomistic structures of simulation models of porphyrin-like $M N_{4}C_{12}$ ( $\\cdot M=F e$ or Co) active sites with M–N bond lengths of $2.01\\mathring{\\mathsf{A}}$ and $1.94\\mathring{\\mathsf{A}}$ , and their corresponding $\\mathsf{O}_{2}$ adsorption configurations on the M site. C, grey; N, blue; M, purple; $\\mathsf{O},$ red; H, white. $\\scriptstyle{\\pmb{\\mathsf{g}}},$ Predicted thermochemical constants of losing an M atom from the porphyrin-like $M N_{4}C_{12}$ ( ${\\sf M}={\\sf F e}$ or Co) sites. The number in parentheses reflects the bond length of $M-N$ and a higher value of $\\Delta G$ indicates a better resistance to metal leaching. \n\nTherefore, we applied a voltage-step test protocol modified from a protocol presented previously27 to maximize the effect of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and the related radicals on the M–N–C ORR catalyst’s durability. In brief, the current density at a cell voltage of $0.85\\mathrm{V}$ for the 1.0 bar $\\mathrm{H}_{2}/$ $\\mathrm{O}_{2}$ PEM fuel cell was measured for 5 minutes followed by holding the fuel cell at various cell voltages (0.40, 0.65 or $\\ensuremath{0.80\\mathrm{V}}.$ ) for $55\\mathrm{{min}}$ - utes, followed by measuring the fuel cell current density at $0.85\\mathrm{V}$ for 5 minutes. The cycle was then repeated. Our durability tests showed a faster degradation at lower cell voltages (Supplementary Fig. 19). This can be explained in terms of the radical attack of the catalyst, which is more severe at higher ORR current densities, that is, lower cell voltages, which are amenable to producing higher amounts of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and thus radicals27. Besides the formation of $\\mathrm{CO}_{2},$ the oxidation of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ by radicals may lead to the formation of surface-functionalized groups, which have been shown to decrease the turnover frequency of active sites and thus degrade the catalyst58. \n\nWe then performed durability tests in membrane electrode assemblies (MEAs) with $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ and $\\mathrm{Fe(mIm)}{-}\\mathrm{NC}(1.0)$ using the above voltage-step test protocol with $\\mathrm{H}_{2}/\\mathrm{O}_{2}$ atmospheres on the anode/cathode. The MEA with the Co(mIm)–NC(1.0) cathode catalyst was much more durable than that with the $\\mathrm{Fe(mIm)-}$ NC(1.0) cathode catalyst (Supplementary Fig. 17c,d), as can be seen from the percentage of current density retention at $0.85\\mathrm{V}$ after the 50 hour test (Fig. 5b). The $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ MEA retained $50\\%$ of its initial current density, whereas the $\\mathrm{Fe}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ MEA retained $<5\\%$ . The enhanced durability of the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ MEA is probably due in part to the alleviated oxidation by radicals (probably due to the lower activity of Co ions for the Fenton reactions56,57), as evidenced by the much lower cathode $\\mathrm{CO}_{2}$ emissions in the MEA studies observed for the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ cathode than for the $\\mathrm{Fe}(\\mathrm{mIm}){\\cdot}\\mathrm{NC}(1.0)$ cathode (Fig. 5c). The results from acidic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ treatment, an experiment presented in Choi et al.20 and Bae et  al.59 to study the radical-induced degradation of $\\mathrm{\\Delta\\mathbf{M}\\mathrm{-}N\\mathrm{-}\\boldsymbol{C}}$ catalysts, confirm the much less radical attack of $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ ) than that of $\\mathrm{Fe(mIm)\\mathrm{-NC(1.0)}}$ (Supplementary Fig. 20). \n\nThe other major degradation mechanism proposed in the literature is demetallation22,60. To quantify the demetallation of $\\mathrm{Co}(\\mathrm{mIm})-$ NC(1.0) and $\\mathrm{Fe}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ and to determine its dependence on experimental conditions, the two catalysts were electrochemically cycled between 0.6 and $1.0\\mathrm{V}$ (versus RHE) in Ar- and $\\mathrm{~O}_{2}$ -purged $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and the amount of metal leached from the catalysts was determined using ICP-OES. Only a small amount of metal leached out from both catalysts when cycled in Ar-purged $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at $25^{\\circ}\\mathrm{C}$ (Fig. 5d), which indicates that the Co and Fe atoms in the catalysts are relatively stable under such conditions. However, the amount of leached Fe increased to $6.5\\mathrm{wt\\%}$ when cycled in $\\mathrm{~O}_{2}$ -purged 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at $25^{\\circ}\\mathrm{C}$ whereas the change in the amount of Co leached was minimal. Cycling in $\\mathrm{~O}_{2}$ -purged $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at an elevated temperature of $80^{\\circ}\\mathrm{C}$ caused a significantly increased metal leaching for both the catalysts. However, much less Co was leached than Fe $7.3\\mathrm{wt\\%}$ Co versus $40\\mathrm{wt\\%}$ Fe). This indicates that $\\mathrm{~O}_{2}$ promotes Fe–N–C demetallation at $25^{\\circ}\\mathrm{C}$ , but does not substantially enhance ${\\mathrm{Co-N-C}}$ demetallation; the extent of demetallation is much more severe for Fe–N–C than for $\\scriptstyle\\mathrm{Co-N-C}$ at $80^{\\circ}\\mathrm{C},$ the typical PEM fuel cell temperature, and therefore $\\scriptstyle\\mathrm{Co-N-C}$ is more resistant to demetallation than Fe–N–C under such conditions. The RRDE ORR activity tests before and after the demetallation experiments indicated that the activity decay of $\\scriptstyle\\mathrm{Co-N-C}$ was much lower than that of Fe–N–C (Fig. 5e and Supplementary Fig. 21). \n\nTo understand the observed trend of the stability of Co–N–C and ${\\mathrm{Fe-N-C}},$ , we performed first principles DFT calculations to predict the tendency for demetallation of $\\mathrm{MN_{4}}$ active sites. Our experimental results from XAS, Mössbauer spectroscopy and pore distribution analysis suggested that the primary existence of porphyrin-like $\\mathrm{MN}_{4}\\mathrm{C}_{12}$ ( $\\mathrm{M}=\\mathrm{Fe}$ or $\\mathrm{Co}$ ) moieties as the ORR active sites in our catalysts; hence, we focused on modelling the demetallation process of such a porphyrin-like $\\mathrm{MN}_{4}\\mathrm{C}_{12}$ site (Fig. 5f and Supplementary Figs. 22 and 23). We also conducted the same modelling study on alternative in-plane $\\mathrm{CoN}_{4}\\mathrm{C}_{10}$ (Supplementary Fig. 24) and pyridinic-N-based $\\mathrm{MN}_{2+2}\\mathrm{C}_{4+4}$ sites30 (Supplementary Fig. 25). The proposed leaching mechanism of M from those $\\mathrm{MN_{4}}$ sites shows that the M atom moves away from the $\\mathrm{N_{4}}$ -coordinated state to the carbon surface, adsorbing on two $\\mathrm{\\DeltaN}$ atoms, whereas the other two N atoms form $_\\mathrm{N-H}$ bonds with H from the acidic environment. Note that at a high electrode potential $(U)$ , for example, $0.9\\mathrm{V}>U>0.5\\mathrm{V},$ $\\mathrm{FeN_{4}}$ sites were predicted to be covered by $\\mathrm{OH^{*}}$ under thermodynamic conditions, but there are no adsorbates on $\\mathrm{CoN_{4}}$ sites in this potential range61. Thus, we calculated the Gibbs free energy change $(\\Delta G)$ for the demetallation of $\\mathrm{FeN_{4}}$ and $\\mathrm{CoN_{4}}$ sites without adsorbates and with $\\mathrm{O}_{2}$ adsorbates, as well as the case with ${\\mathrm{O}}_{2}{\\mathrm{-OH}}^{*}$ co-adsorbates only for $\\mathrm{FeN_{4}}$ (Supplementary Figs. 22–25). We found that all the $\\mathrm{MN_{4}}$ sites without adsorbates require more than $3.0\\mathrm{eV}$ $\\Delta G$ for demetallation, which implies that they are stable under such conditions, consistent with our demetallation experiment results in a deaerated environment. More importantly, our DFT results further show that adding an $\\mathrm{O}_{2}$ onto those sites significantly decreases the $\\Delta G$ values for demetallation (Supplementary Table 7), which indicates that, from the thermodynamic point of view, $\\mathrm{~O}_{2}$ promotes the demetallation. In particular, we predict that the free energy barrier required for demetallation from porphyrin-like $\\mathrm{FeN}_{4}\\mathrm{C}_{12}$ sites with $\\mathrm{O}_{2}\\mathrm{-OH^{*}}$ co-adsorbates becomes negative (Fig. 5g), which shows a severe demetallation tendency for Fe–N–C. As $\\mathrm{OH^{*}}$ does not have a similar affinity to porphyrin-like $\\mathrm{CoN}_{4}\\mathrm{C}_{12}$ sites, ${\\mathrm{Co-N-C}}$ is predicted to better resist demetallation than Fe–N–C. Note that we only calculated the $\\Delta G$ for metal leaching, but the rate of metal leaching is also related to the kinetic activation energy for the metal leaching, which is often larger than or at least no less than $\\Delta G$ This explains why, in our demetallation experiments, $\\mathrm{O}_{2}$ does not have a substantial impact on $\\scriptstyle\\mathrm{Co-N-C}$ demetallation at $25^{\\circ}\\mathrm{C},$ as $\\Delta G$ for all the $\\mathrm{CoN}_{x}$ demetallation is much higher than $0\\mathrm{eV.}$ Furthermore, our DFT results reveal that the stability of porphyrin-like $\\mathrm{CoN}_{4}\\mathrm{C}_{12}$ against metal leaching is related to the $\\mathrm{Co-N}$ bond length. With a decrease in $\\mathrm{Co-N}$ bond length from 2.01 to $1.94\\mathring{\\mathrm{A}}$ (Supplementary Figs. 21 and 22), it was found that $\\Delta G$ for metal leaching from $\\mathrm{~O}_{2}$ adsorbed porphyrin-like $\\mathrm{CoN}_{4}\\mathrm{C}_{12}$ increases from $0.55\\mathrm{eV}$ to $0.84\\mathrm{eV}$ (Fig. 5f, $\\mathrm{~O}_{2}$ environment). Note that the DFT optimized $\\mathrm{Co-N}$ bond length is $\\bar{2}.01\\mathring{\\mathrm{A}}$ for the porphyrin-like $\\mathrm{CoN}_{4}\\mathrm{C}_{12}$ sites, whereas our EXAFS analysis shows that the $\\mathrm{Co-N}$ bond length is $1.94\\mathring{\\mathrm{A}}$ in our catalyst. The shortened $\\mathrm{Co-N}$ bond length is probably the origin of the remarkable stability with an excellent tolerance against demetallation during the ORR for the Co–N–C catalyst. \n\n# Conclusions \n\nA high-performance atomically dispersed $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst was synthesized via the immobilization and fencing of $\\mathrm{\\dot{C}o N_{4}}$ moieties in ZIF-8 micropores with an encapsulation–ligand exchange approach. This approach significantly increases the density of $\\mathrm{CoN}_{x}$ sites and therefore catalytic ORR activity. The $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst achieved the compelling current density of $0.022\\mathrm{Acm}^{-2}$ at $0.9\\mathrm{V_{iR-free}}$ and $0.044\\mathrm{Acm}^{-2}$ at $0.87\\mathrm{V_{iR\\mathrm{-free}}}$ (only $30\\mathrm{mV}$ less than the target of the US Department of Energy (DOE) and peak power density of $0.64\\mathrm{W}\\mathrm{cm}^{-2}$ in $\\mathrm{H}_{2}/\\mathrm{O}_{2}$ PEM fuel cell tests, the highest activities reported for non-Fe $_{\\mathrm{M-N-C}}$ ORR catalysts. We applied extensive physical characterization to the $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst and verified that our approach results in predominantly atomically dispersed Co sites. The ORR active sites, most probably porphyrin-like $\\mathrm{CoN}_{4}\\mathrm{C}_{12}$ active sites, in $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ are predominantly located inside the carbon micropores. More importantly, our $\\mathrm{Co}(\\mathrm{mIm}){-}\\mathrm{NC}(1.0)$ catalyst exhibits significantly enhanced durability compared with that of the similarly synthesized $\\mathrm{Fe(mIm)}{-}\\mathrm{NC}(\\mathrm{i}.0)$ catalyst. Our extensive degradation mechanism studies indicate that chemical oxidation of the catalyst by radicals and active site demetallation (particularly in the presence of $\\mathrm{O}_{2}$ and at elevated temperatures) are primarily responsible for $\\mathrm{M-N-C}$ catalyst degradation. Both degradation paths appear to be alleviated for the $\\scriptstyle\\mathrm{Co-N-C}$ catalyst relative to those for the similarly synthesized Fe–N–C catalyst. This approach to forming a high density of single-atom $\\mathrm{CoN}_{x}$ active sites provides a promising way to develop highly active and durable Fe-free, PGM-free ORR catalysts for PEM fuel cells. \n\n# Methods \n\nSynthesis of $\\mathbf{Co}(\\mathbf{acac})_{3}@\\mathbf{ZIF}\\mathbf{-}\\mathbf{8}$ precursors. $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}{-}8$ precursors with different Co contents were synthesized by varying the $\\mathrm{Co}(\\mathsf{a c a c})_{3}$ amount against mIm in a certain volume of methanol during the ZIF-8 formation (mass ratios of ${\\mathrm{Co}}(\\mathrm{acac})_{3}{\\mathrm{:mIm}}$ were 0.16, 0.32, 0.63 and 1.27). For $\\mathrm{Co}(\\mathrm{acac})_{3}){:}\\mathrm{mIm}=1.27$ typically $3.94\\mathrm{g}$ of mIm were dissolved in $\\boldsymbol{100}\\mathrm{ml}$ of methanol with stirring in a flask. The other $\\boldsymbol{100}\\mathrm{ml}$ of methanol contained $3.57\\mathrm{g}$ of ${\\mathrm{Zn}}({\\mathrm{NO}}_{3}){\\bullet}6{\\mathrm{H}}_{2}{\\mathrm{O}}$ and $5\\mathrm{g}$ of ${\\mathrm{Co}}(\\mathsf{a c a c})_{3}$ . The two solutions were mixed in a flask, which was kept at $60^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ for ZIF-8 crystal growth. The obtained precipitant was separated by centrifugation and thoroughly washed with methanol. \n\nSynthesis of $\\mathbf{Co}(\\mathbf{mIm})_{4}@\\mathbf{ZIF}\\mathbf{-}\\mathbf{8}$ precursors. $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8\\ (\\$ $\\left(1.0{\\bf g}\\right)$ was ultrasonically redispersed in $50\\mathrm{ml}$ of methanol with additional mIm (mass ratio of $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF-8:mIm}\\mathrm{was}\\ 1$ ). The dispersion was transferred into a $\\mathrm{100ml}$ Teflon-lined autoclave and kept at $140^{\\circ}\\mathrm{C}$ for 4 h. After cooling to room temperature, the product was separated by centrifugation and washed serval times with methanol and finally dried at $120^{\\circ}\\mathrm{C}$ under vacuum overnight. \n\nSynthesis of Co catalysts. The $\\mathrm{Co}(\\mathrm{acac})_{3}@\\mathrm{ZIF}-8$ and $\\mathrm{Co}(\\mathrm{mIm})_{4}@\\mathrm{ZIF}{-}8$ powders were transferred to ceramic boats and placed in a tube furnace. The furnace was heated to $1,000^{\\circ}\\mathrm{C}$ at a heating rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ , and then held at $1,000^{\\circ}\\mathrm{C}$ for $^\\mathrm{1h}$ under an Ar environment before being naturally cooled to room temperature. The obtained materials were directly used without additional treatment. \n\nSynthesis of Fe catalyst. The $\\mathrm{Fe(mIm)-NC(1.0)}$ catalyst was synthesized using the same method as that for the Co catalyst, and included ligand exchange with an $\\mathrm{Fe}(\\mathrm{acac})_{3}{:}\\mathrm{mIm}$ mass ratio of 1.27. \n\nMaterial characterization. The crystal phases in catalyst samples were studied using powder XRD on a Rigaku SmartLab SE Bragg-Brentano diffractometer using a Cu source $\\overset{\\prime}{\\lambda}=1.5418\\overset{\\gimel}{\\mathrm{\\AA}}.$ ), a variable incident divergence slit and a $\\scriptstyle{\\mathrm{D/teX}}$ Ultra 250 1D high-speed position-sensitive detector. XPS was carried out using a Kratos AXIS Ultra DLD XPS system equipped with a hemispherical energy analyser and a monochromatic Al $\\mathrm{K}\\upalpha$ source operated at $15\\mathrm{keV}$ and 150 W. The pass energy was fixed at $40\\mathrm{eV}$ for all of the high-resolution scans. All the peaks were adjusted using the C 1s peak at $285.0\\mathrm{eV}$ as the reference. ICP-OES analysis was performed with a Perkin Elmer Optima 7300 DV ICP/OES instrument equipped with a Meinhard nebulizer and cyclonic spray chamber. Surface area and pore distribution analysis of the samples were measured by $\\Nu_{2}$ adsorption at 77 K with an Autosorb iQ Gas Sorption System (Quantachrome Instruments, a brand of Anton Paar). The samples were degassed under vacuum at $100^{\\circ}\\mathrm{C}$ (10 h) before the adsorption measurements. The surface area was determined using the seven-point Brunauer–Emmett–Teller method. The non-local DFT method was used for micropore distribution determination. BF-STEM and HAADF-STEM images were captured in a Nion UltraSTEM (U100) operated at $60\\mathrm{keV}$ and equipped with a Gatan Enfina electron energy loss spectrometer at Oak Ridge National Laboratory. Co and Fe K-edge XANES and EXAFS experiments were carried out at beamline 10-ID (Materials Research Collaborative Access Team, Advanced Photon Source, Argonne National Laboratory). Data reduction, data analysis and EXAFS fitting were performed with the Athena, Artemis and IFEFFIT software packages62. \n\nElectrochemical measurements. Electrochemical testing was carried out in a three-electrode set-up controlled by an electrochemical workstation $\\mathrm{CHI}660\\mathrm{D}$ , CH Instruments). A graphite rod was used as a counter electrode and $\\mathrm{Ag/AgCl}$ (4.0 M KCl; Pine Instrument) as a reference electrode. The $\\mathrm{Ag/AgCl}$ reference electrode was calibrated to a RHE in $\\mathrm{H}_{2}$ -saturated 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ before each measurement. To prepare the working electrode, $10\\mathrm{mg}$ of catalyst was mixed with ${1,980\\upmu\\mathrm{l}}$ of $70\\%$ isopropanol solution and $20\\upmu\\mathrm{l}$ of $5\\mathrm{wt\\%}$ Nafion ionomers by sonication for 1 h. Subsequently, $30\\upmu\\mathrm{l}$ of the ink was drop cast onto an RRDE (Pine Instrument) to cover an area of $0.2472{\\mathrm{~cm}}^{2}\\left(0.6{\\mathrm{mg}}{\\mathrm{cm}}^{-2}\\right)$ . All the potentials are converted into the RHE scale. CVs in Ar-saturated 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at $50\\mathrm{mVs^{-1}}$ were recorded until repeatable CVs were obtained. ORR polarization curves were measured in the steady-state mode under staircase voltammetric conditions with a step of $0.025\\mathrm{V}$ by holding for 25 s at each potential in the range from 1.0 to $0.0\\mathrm{V}$ in $\\mathrm{~O}_{2}$ -purged $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at $25^{\\circ}\\mathrm{C}$ and at a rotation rate of $900\\mathrm{r.p.m}$ . Four-electron selectivity was determined by measuring the ring current at $1.3\\mathrm{V}$ versus RHE and calculating the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield. Catalyst durability was studied by potential cycling from 0.6 to $1.0\\mathrm{V}$ versus RHE in $\\mathrm{O}_{2}$ -purged 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at a scan rate of $50\\mathrm{mVs^{-1}}$ . Potential-hold experiments at 0.7 V were also performed to determine the catalyst durability. A commercial $\\mathrm{Pt/C}$ catalyst $20\\mathrm{wt\\%}$ Pt on carbon; Fuel Cell Store) was used as a PGM reference catalyst, which was tested in $\\mathrm{~O}_{2}$ -saturated $0.1\\mathrm{M}\\mathrm{HCl}\\mathrm{O}_{4}$ with a Pt loading of $60\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ . \n\nPEM fuel cell testing. The catalyst $(0.1\\mathrm{g)}$ was suspended in $6\\mathrm{ml}$ of methanol solvent. The desired amount of Nafion suspension in the alcohols was added and the mixture was sonicated for $10\\mathrm{min}$ before use. The MEA was fabricated by spraying the catalyst–ionomer ink onto a Nafion HP membrane, with the resulting active area of $5.0\\mathrm{cm}^{2}$ . The MEA was assembled in the fuel cell hardware by placing the gas diffusion layers on each side of the membrane. Fuel cell polarization curves were recorded in a constant-current mode at $100\\%$ RH and $80^{\\circ}\\mathrm{C}$ under both 1.0 bar $\\mathrm{H}_{2}/\\mathrm{O}_{2}$ and 1.0 bar $\\mathrm{H}_{2}/{\\mathrm{air}}.$ The PEM fuel cell durability tests were conducted using a voltage-step protocol, in which the cell voltage was varied between selected cell voltages (0.4, 0.65 and $0.8\\mathrm{V}_{\\cdot}$ ), held for $55\\mathrm{min}$ at each voltage followed by $5\\mathrm{{min}}$ holds at $0.85\\mathrm{V}$ to measure the performance loss. A fuel cell was also held at $0.7\\mathrm{V}$ for $\\boldsymbol{100}\\mathrm{h}$ for durability testing. \n\nDemetallation experiments. The catalyst $\\left(20\\mathrm{mg}\\right)$ was mixed with $^{3,980\\upmu\\mathrm{l}}$ of $70\\%$ isopropanol solution and $20\\upmu\\mathrm{l}$ of $5\\mathrm{wt\\%}$ Nafion by sonication for 1 h, the catalyst ink was drop cast onto a $5c\\mathrm{m}^{-2}$ carbon filter electrode to achieve a catalyst loading of $4\\mathrm{mg}\\mathrm{cm}^{-2}$ . The carbon filter electrode was subjected to potential cycling between 0.6 and $1.0\\mathrm{V}$ versus RHE in $30\\mathrm{ml}$ of $0.5\\mathbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at a scan rate of $50\\mathrm{mVs^{-1}}$ for $10\\mathrm{{h}}$ , under Ar and $\\mathrm{O}_{2}$ saturation at $25^{\\circ}\\mathrm{C}$ and under $\\mathrm{O}_{2}$ saturation at $80^{\\circ}\\mathrm{C}$ . The post-treated catalyst was collected for further electrochemical tests, and the electrolyte was collected for ICP-OES analysis. \n\nComputational method. We performed first principles DFT calculations using the Vienna ab initio calculation package63,64. The projector augmented wave pseudopotential65,66 was used to describe the core electrons and a plane wave basis set with a kinetic energy cutoff of $400\\mathrm{eV}$ was applied to expand the wave functions. The Perdew–Burke–Ernzerhof generalized gradient approximation was used to describe the electronic exchange correlation $^{67,68}$ . Three types of active sites, porphyrin-like $\\mathrm{MN}_{4}\\mathrm{C}_{12}$ ( $\\mathrm{M}=\\mathrm{Fe}$ or $\\mathrm{Co}$ ), in-plane $\\mathrm{MN}_{4}\\mathrm{C}_{10}$ and pyridinic-N-based $\\mathrm{MN}_{2+2}\\mathrm{C}_{4+4}$ (refs $^{12,30,48}_{,}$ ), were considered in the present work. There are $50\\mathrm{C},$ , 4 N, 1 M and $^{6\\mathrm{H}}$ atoms included in porphyrin-like ${\\mathrm{MN}}_{4}{\\mathrm{C}}_{12},$ in-plane $\\ensuremath{\\mathrm{MN}}_{4}\\ensuremath{\\mathrm{C}}_{10}$ has 26 C, 4 N and $1\\mathrm{M}$ atoms, whereas pyridinic-N-based $\\mathrm{MN}_{2+2}\\mathrm{C}_{4+4}$ consists of $34\\mathrm{C}$ , $\\ensuremath{4\\mathrm{N}},\\ensuremath{4\\mathrm{H}}$ and 1 M atoms. The atomistic structures were optimized until the forces fell below $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . A vacuum thickness of $14\\mathrm{\\AA}$ was introduced between two adjacent layers. Zero-point energy corrections were included in all the energies reported in this work. Details for the calculations of $\\Delta G$ values are provided in the note to Supplementary Table 7. The coordinates of the optimized models are given in Supplementary Data 1. \n\nFrom Supplementary Figs. 22–25a,b, the leaching of the central M atom in $\\mathrm{MN}_{4}$ and $\\mathrm{MN}_{4}–\\mathrm{O}_{2}$ can be described using the following reactions (s is the number of carbon atoms): \n\n$$\n\\mathrm{MN}_{4}\\mathrm{C}_{s}+2\\mathrm{H}^{+}+2\\mathrm{e}^{-}=\\mathrm{M}-\\mathrm{H}_{2}\\mathrm{N}_{4}\\mathrm{C}_{s}\n$$ \n\n$$\n\\mathrm{MN}_{4}\\mathrm{C}_{s}-\\mathrm{O}_{2}+2\\mathrm{H}^{+}+2\\mathrm{e}^{-}=\\mathrm{MO}_{2}-\\mathrm{H}_{2}\\mathrm{N}_{4}\\mathrm{C}_{s}\n$$ \n\nFurthermore, it was reported that $\\mathrm{FeN_{4}}$ exhibited a high coverage of OH from ${\\sim}0.5$ to ${\\sim}0.9\\mathrm{V},$ whereas there is no OH adsorbate on the surface of $\\mathrm{CoN_{4}}$ in this potential window61,69. Therefore, $\\mathrm{FeN_{4}\\mathrm{-OH}}$ was used to study the durability of $\\mathrm{FeN_{4}}$ at potentials ${>}0.5\\mathrm{V}$ with the three-electron pathway. The leaching of the central Fe atom in $\\mathrm{FeN_{4}O H}$ and $\\mathrm{FeN}_{4}\\mathrm{OH}{-}\\mathrm{O}_{2}$ can be described using the following reactions: \n\n$$\n\\mathrm{FeN}_{4}\\mathrm{C}_{s}\\mathrm{OH}+2\\mathrm{H}^{+}+2\\mathrm{e}^{-}=\\mathrm{HO}-\\mathrm{Fe}-\\mathrm{H}_{2}\\mathrm{N}_{4}\\mathrm{C}_{s}\n$$ \n\n$$\n\\mathrm{FeN}_{4}\\mathrm{C}_{s}\\mathrm{OH}-\\mathrm{O}_{2}+2\\mathrm{H}^{+}+2\\mathrm{e}^{-}=\\mathrm{HO}-\\mathrm{FeO}_{2}-\\mathrm{H}_{2}\\mathrm{N}_{4}\\mathrm{C}_{s}\n$$ \n\n# Data availability \n\nThe data that support the findings of this study are available within the paper and its Supplementary Information or from the corresponding author upon reasonable request. \n\nReceived: 12 March 2020; Accepted: 28 October 2020; Published online: 30 November 2020 \n\nReferences \n1.\t Debe, M. K. Electrocatalyst approaches and challenges for automotive fuel cells. Nature 486, 43–51 (2012). \n2.\t Wang, X. X., Swihart, M. T. & Wu, G. Achievements, challenges and perspectives on cathode catalysts in proton exchange membrane fuel cells for transportation. Nat. Catal. 2, 578–589 (2019). \n3.\t Kongkanand, A. & Mathias, M. F. The priority and challenge of high-power performance of low-platinum proton-exchange membrane fuel cells. J. Phys. Chem. Lett. 7, 1127–1137 (2016). \n4.\t Stephens, I. E. L., Rossmeisl, J. & Chorkendorff, I. Toward sustainable fuel cells. Science 354, 1378–1379 (2016). \n5.\t Ott, S. et al. Ionomer distribution control in porous carbon-supported catalyst layers for high-power and low Pt-loaded proton exchange membrane fuel cells. Nat. Mater. 19, 77–85 (2020). \n6.\t Thompson, S. T. et al. Direct hydrogen fuel cell electric vehicle cost analysis: system and high-volume manufacturing description, validation, and outlook. J. Power Sources 399, 304–313 (2018). \n7.\t He, Y. H., Liu, S. W., Priest, C., Shi, Q. R. & Wu, G. Atomically dispersed metal–nitrogen–carbon catalysts for fuel cells: advances in catalyst design, electrode performance, and durability improvement. Chem. Soc. Rev. 49, 3484–3524 (2020). \n8.\t Luo, F. et  al. $P$ -block single-metal-site tin/nitrogen-doped carbon fuel cell cathode catalyst for oxygen reduction reaction. Nat. Mater. 19, 1215–1223 (2020). \n9.\t Shao, Y. Y., Dodelet, J. P., Wu, G. & Zelenay, P. PGM-free cathode catalysts for PEM fuel cells: a mini-review on stability challenges. Adv. Mater. 31, e1807615 (2019). \n10.\tBarkholtz, H. M. & Liu, D. J. Advancements in rationally designed PGM-free fuel cell catalysts derived from metal–organic frameworks. Mater. Horiz. 4, 20–37 (2017). \n11.\tGupta, S. et al. Engineering favorable morphology and structure of Fe–N–C oxygen-reduction catalysts through tuning of nitrogen/carbon precursors. Chemsuschem 10, 774–785 (2017). \n12.\tZitolo, A. et al. Identification of catalytic sites for oxygen reduction in iron- and nitrogen-doped graphene materials. Nat. Mater. 14, 937–942 (2015). \n13.\tChung, H. T. et al. Direct atomic-level insight into the active sites of a high-performance PGM-free ORR catalyst. Science 357, 479–483 (2017). \n14.\tChen, M. J., He, Y. H., Spendelow, J. S. & Wu, G. Atomically dispersed metal catalysts for oxygen reduction. ACS Energy Lett. 4, 1619–1633 (2019). \n15.\tChen, Y. J. et al. Single-atom catalysts: synthetic strategies and electrochemical applications. Joule 2, 1242–1264 (2018). \n16.\tProietti, E. et al. Iron-based cathode catalyst with enhanced power density in polymer electrolyte membrane fuel cells. Nat. Commun. 2, 416 (2011). \n17.\tWan, X. et al. Fe–N–C electrocatalyst with dense active sites and efficient mass transport for high-performance proton exchange membrane fuel cells. Nat. Catal. 2, 259–268 (2019). \n18.\tZhang, H. G. et al. Single atomic iron catalysts for oxygen reduction in acidic media: particle size control and thermal activation. J. Am. Chem. Soc. 139, 14143–14149 (2017). \n19.\t Osmieri, L., Cullen, D. A., Chung, H. T., Ahluwalia, R. K. & Neyerlin, K. C. Durability evaluation of a Fe–N–C catalyst in polymer electrolyte fuel cell environment via accelerated stress tests. Nano Energy 78, 105209 (2020). \n20.\tChoi, C. H. et al. The Achilles’ heel of iron-based catalysts during oxygen reduction in an acidic medium. Energy Environ. Sci. 11, 3176–3182 (2018). \n21.\tLefevre, M. & Dodelet, J. P. Fe-based catalysts for the reduction of oxygen in polymer electrolyte membrane fuel cell conditions: determination of the amount of peroxide released during electroreduction and its influence on the stability of the catalysts. Electrochim. Acta 48, 2749–2760 (2003). \n22.\tChenitz, R. et al. A specific demetalation of $\\mathrm{Fe-N_{4}}$ catalytic sites in the micropores of $\\mathrm{NC\\_Ar+NH_{3}}$ is at the origin of the initial activity loss of the highly active $\\mathrm{Fe/N/C}$ catalyst used for the reduction of oxygen in PEM fuel cells. Energy Environ. Sci. 11, 365–382 (2018). \n23.\tSantori, P. G. et al. Effect of pyrolysis atmosphere and electrolyte $\\mathrm{\\ttpH}$ on the oxygen reduction activity, stability and spectroscopic signature of $\\mathrm{FeN}_{x}$ moieties in Fe–N–C catalysts. J. Electrochem. Soc 166, F3311 (2019). \n24.\tGoellner, V. et al. Degradation of $\\mathrm{Fe/N/C}$ catalysts upon high polarization in acid medium. Phys. Chem. Chem. Phys. 16, 18454–18462 (2014). \n25.\tRamaswamy, N., Hakim, N. & Mukerjee, S. Degradation mechanism study of perfluorinated proton exchange membrane under fuel cell operating conditions. Electrochim. Acta 53, 3279–3295 (2008). \n26.\tGubler, L., Dockheer, S. M. & Koppenol, W. H. Radical (HO, H and HOO) formation and ionomer degradation in polymer electrolyte fuel cells. J. Electrochem. Soc. 158, B755–B769 (2011). \n27.\tYin, X. & Zelenay, P. Kinetic models for the degradation mechanisms of PGM-free ORR catalysts. ECS Trans. 85, 1239–1250 (2018). \n28.\tBanham, D. et al. Critical advancements in achieving high power and stable nonprecious metal catalyst-based MEAs for real-world proton exchange membrane fuel cell applications. Sci. Adv. 4, eaar7180 (2018). \n29.\tWang, X. X., Prabhakaran, V., He, Y. H., Shao, Y. Y. & Wu, G. Iron-free cathode catalysts for proton-exchange-membrane fuel cells: cobalt catalysts and the peroxide mitigation approach. Adv. Mater. 31, 1805126 (2019). \n30.\tZitolo, A. et al. Identification of catalytic sites in cobalt–nitrogen–carbon materials for the oxygen reduction reaction. Nat. Commun. 8, 957 (2017). \n31.\tSun, T. T. et al. Single-atomic cobalt sites embedded in hierarchically ordered porous nitrogen-doped carbon as a superior bifunctional electrocatalyst. Proc. Natl Acad. Sci. USA 115, 12692–12697 (2018). \n32.\tWang, X. X. et al. Nitrogen-coordinated single cobalt atom catalysts for oxygen reduction in proton exchange membrane fuel cells. Adv. Mater. 30, 1706758 (2018). \n33.\t Kattel, S., Atanassov, P. & Kiefer, B. Catalytic activity of $\\mathrm{Co-N}_{x}/\\mathrm{C}$ electrocatalysts for oxygen reduction reaction: a density functional theory study. Phys. Chem. Chem. Phys. 15, 148–153 (2013). \n34.\tHe, Y. H. et al. Highly active atomically dispersed $\\mathrm{CoN_{4}}$ fuel cell cathode catalysts derived from surfactant-assisted MOFs: carbon-shell confinement strategy. Energy Environ. Sci. 12, 250–260 (2019). \n35.\tXiao, M. L. et al. Identification of binuclear $\\mathrm{Co}_{2}\\mathrm{N}_{5}$ active sites for oxygen reduction reaction with more than one magnitude higher activity than single atom $\\mathrm{CoN_{4}}$ site. Nano Energy 46, 396–403 (2018). \n36.\tWu, G., More, K. L., Johnston, C. M. & Zelenay, P. High-performance electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt. Science 332, 443–447 (2011). \n37.\tSong, J. Y. et al. Core–shell $\\mathrm{Co/CoN_{x}}@\\mathrm C$ nanoparticles enfolded by Co–N doped carbon nanosheets as a highly efficient electrocatalyst for oxygen reduction reaction. Carbon 138, 300–308 (2018). \n38.\tCheng, Q. Q. et al. Co nanoparticle embedded in atomically-dispersed Co–N–C nanofibers for oxygen reduction with high activity and remarkable durability. Nano Energy 52, 485–493 (2018). \n39.\tZhang, H. G., Osgood, H., Xie, X. H., Shao, Y. Y. & Wu, G. Engineering nanostructures of PGM-free oxygen-reduction catalysts using metal–organic frameworks. Nano Energy 31, 331–350 (2017). \n40.\tPark, K. S. et al. Exceptional chemical and thermal stability of zeolitic imidazolate frameworks. Proc. Natl Acad. Sci. USA 103, 10186–10191 (2006). \n41.\tYin, P. Q. et al. Single cobalt atoms with precise N-coordination as superior oxygen reduction reaction catalysts. Angew. Chem. Int. Ed. 55, 10800–10805 (2016). \n42.\tHillman, F. et al. Rapid microwave-assisted synthesis of hybrid zeolitic– imidazolate frameworks with mixed metals and mixed linkers. J. Mater. Chem. A 5, 6090–6099 (2017). \n43.\tStrickland, K. et al. Highly active oxygen reduction non-platinum group metal electrocatalyst without direct metal–nitrogen coordination. Nat. Commun. 6, 7343–7351 (2015). \n44.\tLiedana, N., Galve, A., Rubio, C., Tellez, C. & Coronas, J. CAF@ZIF-8: one-step encapsulation of caffeine in MOF. ACS Appl. Mater. Inter. 4, 5016–5021 (2012). \n45.\tLalancette, R. A., Syzdek, D., Grebowicz, J., Arslan, E. & Bernal, I. The thermal decomposition and analyses of metal tris-acetylacetonates. J. Therm. Anal. Calorim. 135, 3463–3470 (2019). \n46.\t Pan, F. P. et al. Unveiling active sites of $\\mathrm{CO}_{2}$ reduction on nitrogen-coordinated and atomically dispersed iron and cobalt catalysts. ACS Catal. 8, 3116–3122 (2018). \n47.\t Swarbrick, J. C., Weng, T. C., Schulte, K., Khlobystov, A. N. & Glatzel, P. Electronic structure changes in cobalt phthalocyanine due to nanotube encapsulation probed using resonant inelastic X-ray scattering. Phys. Chem. Chem. Phys. 12, 9693–9699 (2010). \n48.\tFei, H. L. et al. General synthesis and definitive structural identification of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n49.\tZiegelbauer, J. M. et al. Direct spectroscopic observation of the structural origin of peroxide generation from Co-based pyrolyzed porphyrins for ORR applications. J. Phys. Chem. C 112, 8839–8849 (2008). \n50.\tLefevre, M., Proietti, E., Jaouen, F. & Dodelet, J. P. Iron-based catalysts with improved oxygen reduction activity in polymer electrolyte fuel cells. Science 324, 71–74 (2009). \n51.\tJaouen, F., Lefevre, M., Dodelet, J. P. & Cai, M. Heat-treated $\\mathrm{Fe/N/C}$ catalysts for $\\mathrm{O}_{2}$ electroreduction: are active sites hosted in micropores? J. Phys. Chem. B 110, 5553–5558 (2006). \n52.\tKramm, U. I. et al. Structure of the catalytic sites in Fe/N/C-catalysts for $\\mathrm{~O}_{2}$ -reduction in PEM fuel cells. Phys. Chem. Chem. Phys. 14, 11673–11688 (2012). \n53.\tMineva, T. et al. Understanding active sites in pyrolyzed Fe–N–C catalysts for fuel cell cathodes by bridging density functional theory calculations and 57Fe Mössbauer spectroscopy. ACS Catal. 9, 9359–9371 (2019). \n54.\tThe Hydrogen and Fuel Cell Technologies Office Multi-year Research, Development, and Demonstration Plan (US Department of Energy, 2017). \n55.\tUddin, A. et al. High power density platinum group metal-free cathodes for polymer electrolyte fuel cells. ACS Appl. Mater. Inter. 12, 2216–2224 (2020). \n56.\tKinumoto, T. et al. Durability of perfluorinated ionomer membrane against hydrogen peroxide. J. Power Sources 158, 1222–1228 (2006). \n57.\tGoellner, V., Armel, V., Zitolo, A., Fonda, E. & Jaouen, F. Degradation by hydrogen peroxide of metal–nitrogen–carbon catalysts for oxygen reduction. J. Electrochem. Soc. 162, H403–H414 (2015). \n58.\tKumar, K. et al. On the influence of oxygen on the degradation of Fe–N–C catalysts. Angew. Chem. Int. Ed. 59, 3235–3243 (2020). \n59.\t Bae, G., Chung, M. W., Ji, S. G., Jaouen, F. & Choi, C. H. pH effect on the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ -induced deactivation of Fe–N–C catalysts. ACS Catal. 10, 8485–8495 (2020). \n60.\tFerrandon, M. et al. Stability of iron species in heat-treated polyaniline–iron– carbon polymer electrolyte fuel cell cathode catalysts. Electrochim. Acta 110, 282–291 (2013). \n61.\tLuo, J. H., Hong, Z. S., Chao, T. H. & Cheng, M. J. Quantum mechanical screening of metal- $\\mathrm{.N_{4}}$ -functionalized graphenes for electrochemical anodic oxidation of light alkanes to oxygenates. J. Phys. Chem. C 123, 19033–19044 (2019). \n62.\tRavel, B. & Newville, M. Athena, Artemis, Hephaestus: data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 12, 537–541 (2005). \n63.\tKresse, G. & Furthmuller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comp. Mater. Sci. 6, 15–50 (1996). \n64.\tSun, G. Y. et al. Performance of the Vienna ab initio simulation package (VASP) in chemical applications. J. Mol. Struc. Theochem. 624, 37–45 (2003). \n65.\tBlochl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n66.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n67.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 78, 1396–1396 (1997). \n68.\tErnzerhof, M. & Scuseria, G. E. Assessment of the Perdew–Burke–Ernzerhof exchange-correlation functional. J. Chem. Phys. 110, 5029–5036 (1999). \n69.\t Li, J. K., Alsudairi, A., Ma, Z. F., Mukerjee, S. & Jia, Q. Y. Asymmetric volcano trend in oxygen reduction activity of Pt and non-Pt catalysts: in situ identification of the site-blocking effect. J. Am. Chem. Soc. 139, 1384–1387 (2017). \n\n# Acknowledgements \n\nThe authors acknowledge support from the US Department of Energy, Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office (DOE-EERE-HFTO) through the Electrocatalysis consortium (ElectroCat) and the DOE programme managers, D. Papageorgopoulos, S. Thompson, D. Peterson and G. Kleen. The XPS measurement was performed using EMSL(grid.436923.9), a DOE Office of Science user facility sponsored by the Biological and Environmental Research programme. PNNL is operated by Battelle for the US DOE under contract DE-AC05- 76RLO1830. X-ray spectroscopy experiments were performed at MRCAT at the Advanced Photon Source (APS), a DOE Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under contract no. DE-AC02- 06CH11357. The operation of MRCAT is supported both by DOE and the MRCAT member institutions. Argonne National Laboratory is operated for the US DOE by the University of Chicago Argonne LLC under contract no. DE-AC02-06CH11357. Electron microscopy was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. The DFT calculations were performed on the computers of the University of Pittsburgh Center for Research Computing as well as the Extreme Science and Engineering Discovery Environment (XSEDE), which is funded by National Science Foundation grant no. ACI-1053575. \n\n# Author contributions \n\nX.X. and Y.S. formulated the concept. X.X. performed the synthesis and electrochemical tests. C.H. and V.R. performed the PEM fuel cell tests and analysed the data. Y.H. and X.S.L. conducted the Brunauer–Emmett–Teller and non-local DFT analyses, J.L. the thermogravimetric analysis, Z.N. and M.E.B. the PXRD analysis and T.L. the ICP-OES analysis. D.A.C. and M.S. performed the electron microscopy characterization. M.H.E. performed the XPS tests. E.C.W., A.J.K. and D.J.M. acquired and analysed the XAS data. G. Wang and B.L. performed the DFT calculations and analysed the results. Y.C. performed the Mössbauer measurements and analysed the data. U.M. and P.Z. performed the in situ $\\mathrm{CO}_{2}$ emission tests and analysed the data. G. Wu provided guidance on \n\ncatalyst design, synthesis and characterization. Y.S. supervised the research. X.X., Y.S., G. Wu, G. Wang, D.J.M. and P.Z. co-wrote the paper. All the authors discussed and commented on the manuscript. The views and opinions of the authors expressed here do not necessarily state or reflect those of the US government or any agency thereof. Neither the US government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness or usefulness of any information, apparatus, product or process disclosed, or represents that its use would not infringe privately owned rights. \n\n# Competing interests \n\nBattelle Memorial Institute has filed a USPTO provisional patent application (no. 62/985,713) on the Co–N–C catalyst and its synthesis reported in this paper; the inventors are Y.S. and X.X.; the status is provisional; and the title is ‘A High-Performing and Stable Platinum Group Metal (PGM) Catalyst for Fuel Cells’. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-020-00546-1. \n\nCorrespondence and requests for materials should be addressed to G.W., V.R. or Y.S. \n\nPeer review information Nature Catalysis thanks Anatoly Frenkel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nThis is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020 " + }, + { + "id": "10.1038_s41467-020-17934-7", + "DOI": "10.1038/s41467-020-17934-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-17934-7", + "Relative Dir Path": "mds/10.1038_s41467-020-17934-7", + "Article Title": "Lattice oxygen activation enabled by high-valence metal sites for enhanced water oxidation", + "Authors": "Zhang, N; Feng, XB; Rao, DW; Deng, X; Cai, LJ; Qiu, BC; Long, R; Xiong, YJ; Lu, Y; Chai, Y", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Anodic oxygen evolution reaction (OER) is recognized as kinetic bottleneck in water electrolysis. Transition metal sites with high valence states can accelerate the reaction kinetics to offer highly intrinsic activity, but suffer from thermodynamic formation barrier. Here, we show subtle engineering of highly oxidized Ni4+ species in surface reconstructed (oxy)hydroxides on multicomponent FeCoCrNi alloy film through interatomically electronic interplay. Our spectroscopic investigations with theoretical studies uncover that Fe component enables the formation of Ni4+ species, which is energetically favored by the multistep evolution of Ni2+-> Ni3+-> Ni4+. The dynamically constructed Ni4+ species drives holes into oxygen ligands to facilitate intramolecular oxygen coupling, triggering lattice oxygen activation to form Fe-Ni dual-sites as ultimate catalytic center with highly intrinsic activity. As a result, the surface reconstructed FeCoCrNi OER catalyst delivers outstanding mass activity and turnover frequency of 3601A g(metal)(-1) and 0.483s(-1) at an overpotential of 300mV in alkaline electrolyte, respectively. Electrocatalytic water oxidation is facilitated by high valence states, but these are challenging to achieve at low applied potentials. Here, authors report a multicomponent FeCoCrNi alloy with dynamically formed Ni4+ species to offer high catalytic activity via lattice oxygen activation mechanism.", + "Times Cited, WoS Core": 543, + "Times Cited, All Databases": 553, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000564248600004", + "Markdown": "# Lattice oxygen activation enabled by high-valence metal sites for enhanced water oxidation \n\nNing Zhang 1,2,7, Xiaobin Feng3,4,7, Dewei Rao 5,7, Xi Deng6, Lejuan Cai1,2, Bocheng Qiu1,2, Ran Long 6, Yujie Xiong6, Yang Lu $\\textcircled{1}$ 3,4✉ & Yang Chai 1,2✉ \n\nAnodic oxygen evolution reaction (OER) is recognized as kinetic bottleneck in water electrolysis. Transition metal sites with high valence states can accelerate the reaction kinetics to offer highly intrinsic activity, but suffer from thermodynamic formation barrier. Here, we show subtle engineering of highly oxidized ${\\mathsf{N i}}^{4+}$ species in surface reconstructed (oxy) hydroxides on multicomponent FeCoCrNi alloy film through interatomically electronic interplay. Our spectroscopic investigations with theoretical studies uncover that Fe component enables the formation of ${\\mathsf{N i}}^{4+}$ species, which is energetically favored by the multistep evolution of ${\\mathsf{N i}}^{2+}{\\to}{\\mathsf{N i}}^{3+}{\\to}{\\mathsf{N i}}^{4+}$ . The dynamically constructed ${\\mathsf{N i}}^{4+}$ species drives holes into oxygen ligands to facilitate intramolecular oxygen coupling, triggering lattice oxygen activation to form Fe-Ni dual-sites as ultimate catalytic center with highly intrinsic activity. As a result, the surface reconstructed FeCoCrNi OER catalyst delivers outstanding mass activity and turnover frequency of 3601 A $\\mathtt{g}_{\\mathrm{metal}}-1$ and $0.483{\\sf s}^{-1}$ at an overpotential of $300\\mathsf{m V}$ in alkaline electrolyte, respectively. \n\nn recent few decades, there have been continuous developments towards water electrolysis, as the cathodically electrolytic hydrogen is proposed as an ideal energy carrier for the storage of sustainable but intermittent energy, such as wind and solar energy1–3. Current bottleneck mainly originates from fourelectron process in anodic oxygen evolution reaction (OER), which requires large overpotential to surmount its sluggish reaction kinetics4,5. However, the high cost and instability of state-of-the-art iridium- and ruthenium-based electrocatalysts largely prevent their practical applications6,7. Earth-abundant catalysts based on $3d$ transition metals have been demonstrated as the promising alternatives for OER, especially in alkaline electrolyte $8–13$ . Meanwhile, experimental and theoretical studies reach a consensus that late transition metals with high valence states exhibit superior activities2,14–16. The increased holes in $d.$ band of highly oxidized metal species can enhance the covalency of metal–oxygen (M–O) bonds to promote the charge transfer9,14. More importantly, high valency typically induces the downshift of metal $d$ -band to penetrate $\\boldsymbol{p}$ -band of oxygen ligands17. The redox electrochemistry of oxygen ligands will be triggered by driving holes into the related oxygen $\\boldsymbol{p}$ -band, making lattice oxygen atoms electrophilic to participate in water oxidation, so called lattice oxygen activation mechanism $(\\mathrm{LOM})^{12,17,18}$ . This alternative pathway facilitates the direct lattice oxygen coupling (LOC) by sharing the ligand holes, thereby lowering the limiting energy barrier. Thus, we can expect that rationalization of LOM pathway with highly oxidized metal species provides a promising avenue to maximize efficiency of OER electrocatalysts. However, according to the Pourbaix diagrams, it usually requires more elevated potential to realize deep oxidation of metal species15,16, causing the thermodynamically unfavorable formation of highly oxidized metal species. Those disadvantages make LOM pathway unpredictable and hinder the exploitation of efficient OER electrocatalysts. Therefore, it is highly desirable to steer the highly oxidized metal species with minimizing their formation energy. \n\nIn general, the OER electrocatalysts undergo the surface reconstruction into (oxy)hydroxides, independent of initial composition and structure19–21, wherein the structural flexibility of (oxy)hydroxides enables the dynamic self-optimization of catalytically active sites. This dynamic reconstruction normally involves oxidation of metal sites, along with adsorption of oxygen species and/or deprotonation of hydroxyl. Therefore, the redox electrochemistry is directly related to the chemical affinity between metal sites and oxygen species, which can be subtly manipulated by the variation of electronic states11,21–23. Multimetal-based electrocatalysts typically endows more superior activities than single-metal catalysts, as the interatomically electronic interplay can efficiently modulate the electronic structure of metal sites that can hardly achieve for single-metal catalysts, offering an effective approach to tune the redox electrochemistry and engineer highly oxidized metal species24–26. Owing to their structural complicacy, it is still a challenging task to rationally design efficient multimetal OER catalysts with high valence metal sites and fundamentally understand their structure-activity correlation. \n\nMulticomponent alloy (MCA) materials have recently received extensive attention because of their unique intrinsic properties27,28. The adjustable components make them feasible to serve as templates for multimetal-based electrocatalysts. By rational engineering, it enables the formation of highly oxidized metal species and tune on LOM. Here, we demonstrate that an FeCoCrNi MCA film can dynamically form highly oxidized metal species during OER process with decreasing formation energy after undergoing irreversible surface reconstruction. Our spectroscopic investigations and theoretical simulations reveal that the interatomically electronic interplay in surface reconstructed multimetal (oxy)hydroxide $(\\mathrm{MO}_{x}\\mathrm{H}_{y})$ plays a key role on subtly engineering highly oxidized $\\mathrm{Ni^{4+}}$ species to favor LOM pathway. Fe component induces electron depletion in $\\mathrm{\\DeltaNi}$ species to ensure the dynamic formation of $\\mathrm{Ni^{4+}}$ species. Meanwhile, a multistep evolution of $\\mathrm{Ni^{2+}{\\longrightarrow}N i^{3+}{\\longrightarrow}N i^{4+}}$ lowers the overall energy barrier of $\\mathrm{Ni^{4+}}$ formation, facilitated by pre-adsorbed bridging hydroxyl at Ni-Co site. The constructed $\\mathrm{\\bar{Ni^{4+}}}$ species drives holes into oxygen ligands to tune on intramolecular LOC via Mars-van Krevelen-like mechanism, thereby evoking LOM pathway. A unique Fe–Ni dual-site with oxygen vacancies (OVs) is formed after desorbing the coupled peroxo-like oxygen species to serve as ultimate catalytic center, substantially promoting OER activity. \n\n# Results \n\nPreparation and characterizations of catalytic systems. A twostep procedure was used to prepare the multimetal-based electrocatalysts, as shown in Fig. 1a. We firstly employed magnetron sputtering method (Supplementary Fig. 1)29,30 to deposit MCA films (quaternary FeCoCrNi and ternary FeCrNi and ${\\mathrm{CoCrNi}}^{\\prime}$ on pretreated carbon clothes (CCs). Scanning electron microscopy (SEM) images (Fig. 1b and Supplementary Figs. 2 and 3) demonstrate that the films are tightly and uniformly coated on the surface of CCs. The characteristic peak at $2\\uptheta=44.2\\up^{\\circ}$ in X-ray diffraction (XRD) patterns (Supplementary Fig. 4) of MCA films can be indexed to (111) lattice planes of face-centered cubic (FCC) phase30. Transmission electron microscope (TEM) image of FeCoCrNi MCA sample (Supplementary Fig. 5) displays its polycrystalline feature, as the film is composed by interconnected nanocrystals with the size of ${\\sim}5\\mathrm{nm}$ (see magnified TEM image in Fig. 1c). The related High-resolution TEM (HRTEM) image together with corresponding fast Fourier transform (FFT) pattern (Fig. 1d) exhibit the ordered lattice fringes with a spacing of $2.1\\mathring\\mathrm{A}$ , which can be assigned to the (111) planes, in good agreement with XRD peaks. To examine the elemental composition and distribution in MCA films, energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) mapping images were collected, which clearly demonstrate the uniformly elemental distribution throughout the measured region (Supplementary Fig. 6). Quantitative analysis reveals the elemental distribution is nominally equiatomic with slightly lower Cr concentration (ca. $80\\%$ , coinciding with inductively coupled plasma mass spectrometry (ICP-MS) results (Supplementary Fig. 7 and Supplementary Table 1). The homogenous elemental distribution is reaffirmed by 3D atomic-probe tomography (APT) in atomic scale30, where 3D APT probing reconstruction images (Fig. 1e) show negligible segregation and clustering. Besides, Xray photoelectron spectroscopy (XPS) was adopted to characterize the electronic states of MCA films (Supplementary Figs. 8 and 9 and Supplementary Table 2). The MCA films exhibit the metallic feature with inevitable surface oxidation. The oxidized degree of various metal components is well distinguished and positively correlates to the related metal reduction potentials (Supplementary Table 3). More details are discussed in Supplementary Note 1. \n\nWe further activated MCA films using an electrochemical cyclic voltammetry (CV) scanning procedure (Supplementary Fig. 10a–c). The electrochemical activated FeCoCrNi, FeCrNi, and CoCrNi MCA films (namely, EA-FCCN, EA-FCN, and EACCN, respectively) were investigated comprehensively to resolve the morphologic and electronic structure information. SEM (Supplementary Fig. 10d–f) and TEM (Supplementary Fig. 11) images show rough surface along with numerous nanosheets, clarifying the irreversible reconstruction. Besides, XRD patterns (Supplementary Fig. 12) confirm the reconstruction into $\\mathrm{\\bar{MO}}_{x}\\mathrm{H}_{y},$ which is reasonable in an alkaline electrolyte19–21. The electrochemical activated MCA films were also studied by XPS to affirm the electronic states of metal components (Fig. 1f and Supplementary Fig. 13). The recorded spectrums are largely differentiated with those of pristine MCA films, where all of the metal components exhibit the thorough oxidation (deconvoluted results are summarized in Supplementary Table 4). Specifically, Ni $2p$ XPS spectra (Fig. 1f) indicates two dominant spin-orbit peaks of $\\mathrm{Ni}^{2\\bar{+}}$ species in (oxy)hydroxide with secondary $\\mathrm{Ni}^{3+}$ species. Differently, ${\\mathrm{Co}}^{3+}$ species is dominant compared to ${\\mathrm{Co}}^{2+}$ species, while Fe and Cr components are fully oxidized to $\\dot{\\mathbf{M}}^{3+}$ species (see Supplementary Fig. 13 and Supplementary Note 2 for detailed discussions). Although we can still collect the signal of Cr species, the dramatically decreased intensity (less than $10\\%$ retaining, see Supplementary Fig. 15) indicates its leaching during electrochemical activation31. The removal of Cr component is probably ascribed to its early oxidation and amphoteric characteristics. Furthermore, we interpret that the reconstruction is a surface engineering without altering the bulk matrix, corroborated by depth-dependent XPS spectra with $\\mathrm{Ar^{+}}$ plasma etching (Supplementary Figs. 14–16) and ICP-MS analysis (Supplementary Fig. 17). This surface reconstruction can retain the bulk conductivity of the alloy film, guaranteeing the effective bulk charge transfer during electrocatalytic process. Given the surface oxidation, we also collected O 1s XPS spectra (Fig. 1g). The deconvolution shows three characteristic peaks at 529.8, \n\n![](images/088e4f739079ffe980b755f7815240669528cafc15d1080e1eb5ce0f73e0b016.jpg) \nFig. 1 Characterizations of as-prepared electrocatalysts. a Schematic illustration of the electrocatalyst preparation. b–e Structural characterizations of pristine FeCoCrNi MCA film. b SEM image. Scan bar, $10\\upmu\\mathrm{m}$ . Insert shows the Partially magnified SEM image. Scan bar, $1\\upmu\\mathrm{m}$ . c Magnified TEM image. Scan bar, $2{\\mathsf{n m}}$ . d HRTEM image. Scan bar, 1 nm. Insert is the corresponding FFT pattern. e 3D APT probing reconstruction images of ${\\mathsf{N i}}$ (green), Fe (red), Co (pink), and Cr (olive) atom positions. Scan bar, $20\\mathsf{n m}$ . f–h Electronic characterizations of electrochemical activated MCA films. High-resolution (f) Ni $2p$ and $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ O 1s XPS spectra. h Ni L-edge ${\\mathsf{s}}\\mathsf{X A S}$ spectra. \n\n531.3, and $532.6\\mathrm{eV}$ (marked as O–I, O–II, and O–III), assignable to oxygen species in M–O, M–OH, and adsorbed $\\mathrm{H}_{2}\\mathrm{O}$ at OVs, respectively13,32. The dominant hydroxyl species (O–II peak) reaffirms the reconstructed ${\\mathrm{MO}}_{x}{\\mathrm{H}}_{y}$ on MCA films. It is noteworthy that both O–I and O–III peaks increase in Fealloyed films (Supplementary Fig. 18), unveiling that Fe component favors the dissociation of $_\\mathrm{O-H}$ bond and formation of OVs, which potentially benefits the catalytic activity. \n\nConsidering the surface reconstruction of MCA films, we further used a more surface sensitive technique—soft $\\mathrm{\\DeltaX}$ -ray adsorption spectroscopy (sXAS) with total electron yield (TEY) mode (detecting depth is a few nanometers)—to probe the $3d$ electronic information of surface metal species16,24,33. Metal $L$ - edge sXAS spectra derived from dipole-allowed $p\\to d$ electron transition can sensitively monitor the unoccupied states in $d$ - orbitals of transition metals, where lower electron density embodies inversely higher white line intensity in the spectra10,25. For our samples, Ni component demonstrates characteristic white line of $\\mathrm{Ni}^{2+}$ species (Fig. 1h), while ${\\mathrm{Co}}^{3+}$ and $\\mathrm{Fe}^{3+}$ species are recognized to dominantly exist (Supplementary Fig. 19)10,16,24,25, matching the results of XPS spectra. More importantly, the intensities of white lines are distinctly varied, which implies the electronic modulation of surface metal species. Typically, $O_{\\mathrm{h}}$ - symmetric Metal atoms interact with bridging oxygen $(\\mu{-}\\mathrm{O})$ \n\n![](images/d4758b352ccf0ace3a0aa3729ec62f74e08c63519a87a43723f0aebc57d27759.jpg) \nFig. 2 Electrochemical OER activity evaluations. a LSV polarization curves of various catalysts in $\\mathsf{O}_{2}$ -saturated 1-M KOH solution at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . b Mass activities and TOFs of various catalysts at overpotential of $300\\mathsf{m V}$ . c Tafel plots of various catalysts derived from polarization curves in Fig. 3a. d LSV polarization curves of EA-FCCN before and after 3000 CV cycles for stability test. Inset is $20-11$ chronoamperometric curves with the initial current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ . \n\nthrough $\\pi$ -donation in (oxy)hydroxide structures, forming M–OM moiety (Supplementary Fig. 20a)22. Due to different electronic occupancy in $\\pi$ -symmetric $d$ -orbitals (i.e., $t_{2\\mathrm{g}}$ -orbitals), partial electron transfer (PET) can be triggered through $\\mu{-}\\mathrm{O}$ ligand, leading to the electron density fluctuation (Supplementary Fig. 20b)22,25,34. The strength of PET can be determined by the occupancy in $t_{2\\mathrm{g}}$ -orbitals, namely, $\\mathrm{Fe}^{3+}{\\mathrm{-}}\\mathrm{O}{\\mathrm{-}}\\mathrm{Ni}^{2+}>\\mathrm{Fe}^{3+}{\\mathrm{-}}\\mathrm{O}{\\mathrm{-}}\\dot{\\mathrm{Co}}^{3+}$ $\\mathrm{>Co^{\\mathrm{\\dot{3}+\\_{\\cdot}O-N i^{2\\bar{+}}}}}$ (left metal atom serves as the electron acceptor, see details in Supplementary Note 3), which well coincides with varied white line intensities of sXAS spectra. Taking Ni species as an instance (Fig. 1h), the higher white line intensities of our samples related to pure Ni sample (EA-Ni) indicates the electron density decrease due to PET from $\\mathrm{Ni}^{2+}$ to $\\mathrm{Fe}^{3+}/\\mathrm{Co}^{3}$ . Furthermore, the stronger PET in $\\mathrm{Fe}^{3+}{\\cdot}\\mathrm{O}{-}\\mathrm{Ni}^{2+}$ moiety gives rise to more electron depletion in $\\mathrm{Ni}^{2+}$ species, leading to the further increased white line intensities for EA-FCN and EA-FCCN related to EA-CCN. The interatomically electronic interplay through PET in M–O-M moiety can delocalize and redistribute the electrons in $d$ -orbitals of surface metal atoms, thereby largely influencing the catalytic activity25,34. \n\nEvaluation of electrocatalytic OER activity. Figure 2a displays the collected linear sweep voltammogram (LSV) polarization curves of various catalysts, clearly showing that our electrochemical activated MCA films significantly outperform the benchmark ${\\mathrm{RuO}}_{2}$ catalyst. An overpotential of $304\\mathrm{mV}$ is required for EA-CCN to achieve a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ (normalized by geometrical area of electrode), which further decreases to 255 and $221\\mathrm{mV}$ for EA-FCN and EA-FCCN, respectively (Supplementary Fig. 21). The substantially improved activity implies that the interatomically electronic interplay in surface ${\\mathrm{MO}}_{x}{\\mathrm{H}}_{y}$ plays a pivotal role on water oxidation24–26. It is noteworthy that EA-FCCN only requires the overpotentials of 281 and $301\\mathrm{mV}$ to reach the large current densities of 200 and $400\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively, exhibiting its superiority as the potential OER electrocatalyst candidate for practical applications. To assess the activity of our catalysts more fairly, specific activities were normalized by the electrochemically active surface areas (ECSAs), which were estimated by double-layer capacitances $\\left(C_{\\mathrm{dl}}s\\right)$ (see Supplementary Fig. 22 and Supplementary Table 5). As displayed in Supplementary Fig. 23, although ECSA of EA-FCCN is relative larger, the determined specific activity of EA-FCCN is still superior to that of EA-FCN and EA-CCN catalysts. Moreover, in order to assess the intrinsic activity, we also calculated the mass activities and TOFs (Supplementary Fig. 24) on the basis of the total deposited metal amount. To be specific, EA-FCCN delivers a high mass activity of 3601 A $\\mathrm{g}_{\\mathrm{metal}}-1$ at an overpotential of $300\\mathrm{mV}$ , while 1183, 101, and $37\\mathrm{A}\\mathrm{\\bar{g}}_{\\mathrm{metal}}-1$ are only observed for EA-FCN, EA-CCN, and ${\\mathrm{RuO}}_{2}$ , respectively (Fig. 2b). Similar tendency can also be observed for TOFs (Fig. 2b), where the TOF of EA-FCCN reaches $0.483\\:s^{-1}$ at an overpotential of $300\\mathrm{mV}$ 3.2, 34.5, and 41.1 times higher than that of EA-FCN, EA-CCN, and $\\mathrm{RuO}_{2}$ , respectively. Notably that the determined intrinsic activity values are inevitably underestimated, because only the surface metal species can endow veritably active sites rather than the whole deposited alloy $\\mathrm{{flm}}^{24}$ . Such a remarkable OER activity of our as-obtained OER electrocatalysts (particularly for EAFCCN) is superior to most of previously reported earth-abundant transition metal OER electrocatalysts (Supplementary Table 6). \n\n![](images/dcf89931d0b81194b3f019fd2b99bc50e008ccbb8ca51362486df250fa6ac7b0.jpg) \nFig. 3 Identifications of ultimate active sites toward OER. a Steady CV scanning curves of electrochemical activated MCA films. b Electrochemical in situ Raman spectra of EA-FCCN at the range of $350{-}700~\\mathsf{c m}^{-1}$ at the operated potentials from 1.1 to $1.5\\mathrm{V}$ versus RHE. c δ(Ni-O)-to- $\\cdot\\nu$ (Ni-O) ratios in electrochemical in situ Raman spectra of various catalysts related to the operated potentials. d, e Ex situ $\\mathsf{s x A S}$ measurements of various catalysts. d Ni Ledge and (e) $\\textsf{O}K$ -edge ${\\mathsf{s}}\\mathsf{X A S}$ spectra. Dash and solid lines represent the spectrums collected at open circuit condition and the operated potentials (i.e., 1.5 V for EA-FCCN, $1.55\\mathrm{V}$ for EA-FCN, and $1.6\\vee$ for EA-CCN), respectively. f Schematic representation of activating oxygen ligands induced by ${\\mathsf{N i}}^{4+}$ species in Mott-Hubbard model. $\\pmb{\\mathsf{g}}$ Computational $3d$ -orbitals PDOS diagrams of localized Ni site adjacent to $\\mathsf{F e/C o}$ in various oxyhydroxide models, together with the related band centers. \n\nTo probe reaction kinetics, the Tafel plots of our catalysts were drawn, as depicted in Fig. 2c. The Tafel slope of EA-CCN is determined to be $51.4\\mathrm{m}\\bar{\\mathrm{V}}\\mathrm{dec}^{-1}$ , which considerably decreases to 42.6 and $38.7\\mathrm{mV}\\mathrm{dec}^{-1}$ for EA-FCN and EA-FCCN, respectively. The decreased Tafel slopes indicate the accelerated reaction kinetics and the probable change of rate-limiting step $(\\mathrm{RLS})^{4,5}$ . Moreover, we measured the electrochemical impedance spectroscopy (EIS), where the smallest semicircle in Nyquist plot of EA-FCCN (Supplementary Fig. 25) indicates apparent decrease of interfacial charge transfer resistance $(R_{\\mathrm{ct}})$ , inducing the facilitated charge transfer to promote OER activity. \n\nStability was assessed through CV scanning and chronoamperometry tests. LSV polarization curve of EA-FCCN is well retained after $3000\\mathrm{CV}$ scanning cycles (Fig. 2d), in which only an anodic shift of $8\\mathrm{mV}$ is additional to reach a large current density of $400\\mathrm{mA}\\mathrm{cm}^{-2}$ . Besides, chronoamperometric curve of EAFCCN (inset in Fig. 2d) displays a slightly decayed current density (decreasing only by ${\\sim}7\\%$ ) after $20\\mathrm{{\\bar{-h}}}$ continuous test, whereas ${\\mathrm{RuO}}_{2}$ catalyst rapidly deactivates within $6\\mathrm{h}$ , further corroborating the excellent stability. Structural characterizations (SEM and XPS, see Supplementary Figs. 26–27) after chronoamperometric test manifests that EA-FCCN is nearly remained without disturbing the bulk MCA film. \n\nMonitoring the dynamic evolution of metal sites during OER process. Our activity evaluations exhibit the superiority of Feinvolved electrocatalysts (especially for EA-FCCN) toward water oxidation. It is surmised that the interatomically electronic interplay in multimetal species plays a vital role on constructing highly active center to accelerate the reaction kinetics. Unfortunately, although unremitting efforts have been put, the catalytic mechanism is still ambiguous and elusive, especially for the critical role of Fe site, wherein some proposals are even conflicting. Many researchers proposed Ni site as catalytic center with Fe as a promoter. For instance, Görlin et al. reported that $\\mathrm{Fe}^{3+}$ species diminished the charge contribution process of $\\mathrm{Ni^{4+}}$ and stabilized $\\mathrm{Ni}^{2+}$ to improve the catalytic activity35. Oppositely, $\\mathrm{Fe}^{3+}$ species were also regarded as Lewis acid center to promote the formation of $\\mathrm{Ni^{4+}}$ species36,37, inducing the exacerbated geometric distortions and electronic structural variation38,39. Meanwhile, high valence $\\mathrm{Fe^{4+}}$ site was also detected by Mössbauer Spectroscopy to destabilize $\\mathrm{Ni}^{3+}$ species in the NiOOH lattice22. Apart from Ni site as active center, attentions have also been put on whether Fe species can act as catalytic site. Evidences were offered by Friebel et al., in which $\\mathrm{Fe}^{3+\\cdot_{-}}\\mathrm{O}$ bond was shortened during catalytic process and $\\mathrm{Fe}^{3+}$ site indeed offered a lower computational overpotential than Ni site40. This Fe catalytic center was also been experimentally strengthened by $^{18}\\mathrm{O}$ -labbelled in situ Raman characterizations41. Moreover, investigations also demonstrated that $\\mathrm{Fe}^{3+}$ could further evolve to high valence $\\mathrm{Fe^{4+}}$ in $\\mathrm{Fe^{4+}=0}$ motif, contributing to the highly catalytic activity42,43. Very recently, Markovic and coworkers proposed a novel viewpoint that Fe site offered the high catalytic activity but must be preserved through the dynamic balance of Fe dissolution and redeposition on metal hydroxide surface44. Upon those complicated interpretations, it is of high importance for us to fundamentally understand the veritably catalytic sites and related reaction pathway in our catalytic system. \n\nGiven the dynamic surface reconstruction of catalysts prior to water oxidation, the redox electrochemistry of metal species in various catalysts are investigated, which is supposed to be decisive for constructing active sites11,21. As displayed in steady CV scanning curves (Fig. 3a), the anodic oxidation peaks can be ascribed to by $\\mathrm{Ni}^{2\\mp}{\\rightarrow}\\mathrm{Ni}^{3/4+}$ oxidation along with hydroxyl deprotonation23,45,46. Two facts can support our conjecture: (1) $\\mathrm{Ni}^{\\hat{2}+}$ , ${\\mathrm{Co}}^{3+}$ , and $\\mathrm{Fe}^{3+}$ species predominantly exist on the surface of $\\mathrm{Cr}$ -leached ${\\mathrm{MO}}_{x}{\\mathrm{H}}_{y}$ (evidenced by XPS and sXAS, vide supra); and (2) oxidation of ${\\mathrm{Co}}^{3+}$ and $\\mathrm{Fe}^{3+}$ species typically requires much more elevated potentials21,22. The oxidation of $\\mathrm{Ni}^{2+}$ species signifies further surface evolution into oxyhydroxides to offer the veritably active sites for OER19,47. The varied oxidation peaks for different catalysts imply their divergent evolution of $\\mathrm{Ni}^{2\\bar{+}}$ species. The peak for EA-FCN $\\mathrm{1.44V}$ (versus RHE)) positively shifts compared to that of EA-CCN $(1.29\\mathrm{V})$ and EA-FCCN $(\\mathrm{1}.32\\mathrm{V})$ , indicating that $\\mathrm{Ni}^{2+}$ oxidation is largely delayed by $\\mathrm{Fe}^{3+}$ species in $\\mathrm{EA-FCN}^{22,23,46}$ . To understand the surface evolution, we monitored the dynamic changes of out catalysts using electrochemical in situ Raman spectroscopy. Two characteristic Raman signals of $\\mathrm{Ni}^{3+\\ldots}\\mathrm{O}$ at 472 and $\\dot{5}54\\mathrm{cm}^{-1}$ can be gradually recognized on the recorded spectrums with the elevated potentials (Fig. 3b and Supplementary Fig. 28), which can be indexed to the $E_{\\mathrm{g}}$ bending vibration $(\\delta(\\mathrm{Ni-O}))$ and $\\boldsymbol{A}_{1\\mathrm{g}}$ stretching vibration ( $\\dot{\\mathbf{\\zeta}}_{\\nu}$ (Ni-O)) mode in nickel oxyhydroxide (NiOOH), respectively46,47. The emergence of Raman signals is well associated with the anodic oxidation peaks in positive CV scanning curves (Supplementary Fig. 29), reaffirming the dynamic surface reconstruction into oxyhydroxides. Notably, the variation of $\\delta(\\mathrm{Ni-O})$ -to- $\\nu(\\mathrm{Ni\\mathrm{-}O)}$ ratios (labelled to $I_{\\delta/\\nu.}$ ) are obviously different for our catalysts (Fig. 3c), signifying the distinguishing lattice structure of formed NiOOH. Generally, NiOOH contains $\\beta$ and $\\gamma$ phases, where the intensity of $\\nu(\\mathrm{Ni-O})$ is relatively lower (i.e., higher $I_{\\delta/\\nu,}$ ) in $\\gamma\\mathrm{.}$ NiOOH due to its looser structure with more disorder45,47. As observed in Fig. 3c, the initial $I_{\\delta/\\nu}$ values for EA-CCN and EAFCCN are about 1.2, while it aberrantly reaches 1.55 for EA-FCN. Such a higher $I_{\\delta/\\nu}$ for EA-FCN manifests the direct formation of $\\gamma{\\mathrm{-NiOOH}}$ structure when surface oxidation occurs45,47. It is regarded that highly oxidized $\\mathrm{Ni^{4+}}$ species exists in $\\gamma{\\mathrm{-NiOOH}}$ due to the statistic $\\mathrm{Ni}$ valency of $+3.{\\dot{6}}^{36,48}$ . Therefore, we infer that $\\mathrm{Ni}^{2+}$ species can be directly oxidized to $\\mathrm{Ni^{4+}}$ species in EAFCN, while normal $\\mathrm{Ni}^{3+}$ species is initially formed in EA-CCN and EA-FCCN. Based on the Pourbaix diagrams, the deep $\\mathrm{Ni^{2+}{\\_}N i^{4+}}$ oxidation is energetically unfavorable15,16, which interprets the anodically shifted oxidation peak of EA-FCN in CV scanning curve (Fig. 3a). Moreover, we speculate that the direct $\\mathrm{Ni^{4+}}$ formation is accomplished by assistance of $\\mathrm{Fe}^{3+}$ species due to the robust PET effect in Fe-O-Ni moiety, which efficiently withdraws the electrons from Ni to Fe, stabilizing $\\mathrm{Ni^{4+}}$ species (see “Discussions” in Supplementary Note $3)^{22,\\breve{3}8}$ . Given that highly oxidized $\\mathrm{Ni^{4+}}$ species offers higher intrinsic activity36–39, only a little potential barrier of $45\\mathrm{mV}$ is applied for EA-FCN to reach a current density of $10\\mathrm{mAcm^{-1}}$ after $\\mathrm{Ni}^{2+}$ oxidation (Supplementary Fig. 30). Contrarily, a much larger potential barrier $(344\\mathrm{mV})$ is essential for EA-CCN with only $\\mathrm{\\tilde{Ni}}^{3\\bar{+}}$ species during OER process. Different from EA-CCN, profited from the existence of $\\bar{\\mathrm{Fe}^{3+}}$ species, $\\gamma$ -NiOOH structure with $\\mathrm{Ni^{4+}}$ species is also constructed in EA-FCCN when the potential is further elevated, as monitored by in situ Raman spectra (Fig. 3c, $I_{\\delta/\\upnu}=1.56$ at potential of $1.5\\mathrm{V})$ . Therewith, a substantially reduced potential barrier $\\mathrm{.131mV}$ , Supplementary Fig. 30) is required for EA-FCCN to initiate OER. In view of the initially formed $\\beta$ -NiOOH structure with only $\\mathrm{Ni}^{3+}$ species, we proposed a multistep evolution of Ni species (i.e., $\\mathrm{Ni^{2+}{\\longrightarrow}N i^{3+}{\\longrightarrow}N i^{\\hat{4}+}},$ ) in EA-FCCN during OER process, which can bypass the energy obstacle of direct $\\mathrm{\\DeltaNi^{4+}}$ formation, lowering the overall potential barrier to initiate OER. \n\nThe ultimate electronic states of metal species at OER conditions were also substantiated by ex situ sXAS after treatment at different operated potentials10,16,33. As disclosed in $\\scriptstyle{\\mathrm{Co}}$ and Fe $L$ -edge sXAS spectra (Supplementary Fig. 31), ${\\mathrm{Co}}^{3+}$ and $\\mathrm{Fe}^{3+}$ species are well maintained without further oxidation at OER conditions. However, Ni species undergoes distinctive evolution (Fig. 3d). Additional white line (blue-shift of ${\\sim}2.8\\mathrm{eV}$ against the main peak of $\\mathrm{Ni}^{2+}$ species) can be recognized in Ni L-edge sXAS spectra for EA-FCN and EA-FCCN at OER conditions, which can be ascribed to dynamically formed $\\mathrm{Ni^{4+}}$ species10,16, in line with electrochemical in situ Raman measurements. Considering the correlation between structural evolution and OER activity, we conclude that the dynamically formed $\\mathrm{Ni^{4+}}$ species in EA-FCN and EA-FCCN serves as veritably active sites for (at least plays a decisive role on) the OER. \n\nUpon the distinctive Ni states in different catalysts during catalytic process, one can envision that the electronic structure should be largely steered25,39. For late transition metals, $d$ -orbitals can be further split into electron-filled lower Hubbard band (LHB) and empty upper Hubbard band (UHB) owing to strong d-d onsite Coulomb interaction $(U)$ , namely Mott-Hubbard splitting12,49. Zaanen-Sawatzky-Allen scheme depicts that the increased valence of metal cation with orbital volume shrinkage (e.g., highly oxidized $\\mathrm{Ni^{4+}}$ species) can expand $U$ to exacerbate this splitting36,50. Thus, LHB will downshifts to probably penetrate $\\boldsymbol{p}$ -band of oxygen ligands as schemed in Fig. 3f, exhibiting charge-transfer insulator character. This modulation of electronic structure can be visualized by the computational $3d.$ -orbtial partial density of states (PDOS) diagrams of localized Ni sites adjacent to $\\mathrm{Fe/Co}$ in our established metal oxyhydroxide models (labelled to MOOH, see Supplementary Fig. 32 and Supplementary Note 4)48,51. As plotted in Fig. 3g, the computed $d$ -band centers $(\\varepsilon_{\\mathrm{d}})$ apparently downshifts for Fe-involved $\\mathrm{(FeCrNi)OOH}$ and (FeCoCrNi)OOH models, far away from the Fermi level $(E_{\\mathrm{F}})$ . As the PDOS below $E_{\\mathrm{F}}$ describes the occupied $3d$ -orbitals distribution, we can regard the related $\\varepsilon_{\\mathrm{d}}$ as LHB-band center $(\\varepsilon_{\\mathrm{LHB}})$ . Similarly, UHB-band center $(\\varepsilon_{\\mathrm{UHB}})$ can also be calculated from PDOS diagrams based on the orbital distribution above $E_{\\mathrm{F}}$ (Fig. 3g). Here we qualitatively determine $U$ as the energy difference between $\\varepsilon_{\\mathrm{LHB}}$ and $\\varepsilon_{\\mathrm{UHB}}$ (i.e., $\\delta(\\varepsilon_{\\mathrm{UHB}}-\\varepsilon_{\\mathrm{LHB}});$ , showing that Fe-involved models deliver the enlarged $U$ values (Supplementary Fig. 33). We ascribe the enlarged $U$ along with downshifted LHB to the dynamically formed high valence $\\mathrm{Ni^{4+}}$ species, as experimentally evidenced by Raman and sXAS measurements. \n\nTo deeply investigate the influence of this altered electronic structure, the evolution of surface oxygen species was monitored by ex situ O $K$ -edge sXAS spectra. Figure 3e exhibits the shoulder adsorption (located at ${\\sim}529\\mathrm{eV}.$ ) prior to the pre-edge absorption for EA-FCN and EA-FCCN at OER conditions. This meaningful signal can be assigned to activated oxygen ligands containing localized holes (i.e., $\\mathrm{O}^{(2-\\delta)-})^{52,53}$ . Its concomitant emergence with $\\mathrm{Ni^{4+}}$ species manifests that the formed $\\mathrm{O}^{(2-\\delta)-}$ species is derived from the downshifted $3d$ -band of $\\mathrm{Ni^{4+}}$ species, just as predicted by computational PDOS diagrams. Therefore, oxygen ligands can thermodynamically lose the electrons from $\\boldsymbol{p}$ -band, leaving holes to destabilize and activate themselves, as schemed in Fig. 3f. The localized holes enable oxygen ligands electrophilic and chemically active to participate in water oxidation through LOM pathway. Moreover, it can also be observed that O $K\\cdot$ -edge sXAS spectra exhibit the increased intensity at OER conditions for all the catalysts (Fig. 3e), indicating the enhanced metal–oxygen covalency to promote the charge transfer between metal center and oxygen atoms during OER process9,39. \n\nIn-depth understanding of reaction pathway. As mentioned above, the highly oxidized $\\mathrm{Ni^{4+}}$ species is dynamically formed and activates the lattice oxygen ligands with electron holes, acting as a crucial knob on promoting OER activity. To shed more light on catalytic nature, density functional theory (DFT) simulations were conducted to systematically screen the evolution of surface oxygen species on different oxyhydroxide models, considering both LOM and adsorbate evolution mechanism (AEM) pathways (see computational details in Supplementary Note 5)12,18. The lattice and adsorbed oxygen atoms in the models are marked to $\\mathrm{O}_{l}$ and $\\mathrm{~O}_{a},$ respectively. For $\\mathrm{(CoCrNi)OOH}$ and $\\mathrm{(FeCoCrNi)}$ OOH models, $\\bar{\\mathrm{OH^{-}}}$ adsorption (namely, forming Ni $-\\mu{\\mathrm{-}}\\mathrm{O}_{a}\\mathrm{H}$ -Co motif) is more energetically preferential than deprotonation of Ni-terminated hydroxyl ( $\\mathrm{Ni-}\\eta\\mathrm{-O}_{l}\\mathrm{H},$ ), while $(\\mathrm{FeCrNi)OOH}$ model exhibit inverse scene (Fig. 4a). Moreover, the negative Gibbs free energy difference $(\\Delta G)$ of Ni- $\\mathbf{\\partial}\\cdot\\eta\\mathbf{-O}_{l}\\mathbf{H}$ deprotonation on (FeCrNi) OOH model $(-0.10\\mathrm{eV})$ means its spontaneous nature, indicating the further evolution of Ni site to $\\mathrm{\\bar{Ni^{4+}}}$ species. Meanwhiles, the deprotonated $\\mathrm{(FeCrNi)OOH}$ model after structural relaxation (inset in Fig. 4a) contains an Fe $\\mathsf{\\Omega}_{-}(\\mu{-}\\mathrm{O}_{l}\\mathrm{O}_{l}){-}\\mathrm{Ni}$ motif with $_{\\mathrm{O-O}}$ bond length of $\\overset{\\cdot}{1.39\\mathrm{\\AA}}$ (Supplementary Fig. 34b). The formed peroxo-like $\\mu{\\mathrm{-}}\\mathrm{O}_{l}\\mathrm{O}_{l}$ species is inferred to derive from intramolecularly nucleophilic coupling of deprotonated $\\eta\\mathrm{-O}_{l}$ atoms, which contains ligand holes introduced by highly oxidized $\\mathrm{Ni^{4+}}$ species, as proofed by O $K$ -edge sXAS (Fig. 3e). This evolution manifests that oxygen evolution proceeds with a direct Mars-van Krevelenlike mechanism on $\\mathrm{(FeCrNi)OOH}$ model, undergoing LOM pathway through desorbing $\\mu{\\mathrm{-}}\\mathrm{O}_{l}\\mathrm{O}_{l}$ species (Supplementary Fig. 35a, left). Meanwhile, this Fe- $(\\mu{\\mathrm{-}}\\mathrm{O}_{l}\\mathrm{O}_{l})$ -Ni motif also indicates Fe–Ni dual-site as ultimate catalytic center for oxygen evolution (see Supplementary Fig. 36 and Supplementary Note 6). Afterwards, $\\mathrm{\\bar{OH}^{-}}$ anions will refill the oxygen vacancies at Fe–Ni dualsite and loop the deprotonation-coupling-desorption process (Supplementary Fig. 35a, right). The simulated energy barrier diagram of OER cycling (Supplementary Fig. 35b) exhibits that RLS is the deprotonation of Fe- $\\eta$ -OH with an energy uphill of $1.54\\mathrm{eV}$ . \n\nNow we turn to the oxygen evolution on (FeCoCrNi)OOH and $(\\mathrm{CoCrNi)OOH}$ models after $\\mathrm{OH^{-}}$ pre-adsorption. Computational results demonstrate that intramolecular LOC can also occurs on (FeCoCrNi)OOH model after Ni- $\\eta{\\mathrm{-O}}_{l}{\\mathrm{H}}$ deprotonation 1 $\\Delta G=1.36\\mathrm{eV}$ , see Supplementary Fig. 37), forming $\\mu{\\mathrm{-}}\\mathrm{O}_{l}\\mathrm{O}_{l}$ species with bond length of $1.41\\mathring{\\mathrm{A}}$ (see Supplementary Fig. 34a). The successful LOC indicates that (FeCoCrNi)OOH model also evolves oxygen molecule via LOM pathway, analogous to $(\\mathrm{FeCrNi)OOH}$ model. Peroxo-like oxygen species is experimentally discerned by electrochemical in situ Raman spectra (Supplementary Fig. 38). The broad signals at the range of $850{\\dot{-}}1150\\thinspace\\mathrm{cm^{-1}}$ can be assignable to active oxygen species in Ni $(\\mathrm{OO})^{-}$ species54,55, whose emergence in EA-FCN and EA-FCCN strengthens the preferential step of intramolecular LOC. Then, we simulated the OER cycling at Fe–Ni dual-site and determined the first $\\mathrm{OH^{-}}$ adsorption as RLS with an energy barrier of $1.43\\mathrm{eV}$ for (FeCoCrNi)OOH model (Fig. 4b). The lower energy barrier related to $\\mathrm{(FeCrNi)OOH}$ model predicts the more superior OER activity of EA-FCCN catalyst, coinciding with the experimental results. The bridging pre-adsorbed $\\mathrm{OH^{-}}$ at Ni-Co site does not directly involve OER process but acts as an electron-withdrawing modifier to favor hydroxyl deprotonation56,57, thereby reducing the overall barrier of OER cycling. Conventional AEM pathway is also considered through direct deprotonation of adsorbed $\\mu\\mathrm{-O}_{a}\\mathrm{H}.$ , delivering an energy barrier as high as $1.94\\mathrm{eV}$ (Supplementary Fig. 39). The computed energy barrier manifests that LOM pathway is more energetically favorable on (FeCoCrNi)OOH model (Fig. 4c). In terms of (CoCrNi)OOH model, inverse result is observed that AEM pathway hold a lower energy barrier than LOM pathway (Fig. 4c and Supplementary Fig. 40). In comparison of Fe-involved model, (CoCrNi)OOH model requires a more elevated energy uphill to furnish the OER cycling, foreboding the lower intrinsic activity of EA-CCN catalyst. We speculate that the oxygen atoms can hardly be activated by the ligand holes without the high valence $\\mathrm{Ni^{4+}}$ species, leading to the unfavorable $_{\\mathrm{O-O}}$ bond formation via $\\bar{\\mathrm{OH^{-}}}$ nucleophilic attack (i.e., RLS) for $(\\mathrm{CoCrNi)OOH}$ model. Taken together, we conclude that oxygen molecule evolves via LOM pathway for EAFCN and EA-FCCN catalysts and AEM pathway for EA-CCN pathway, respectively. Moreover, it should also be noted that Feinvolved models show the much looser structure than (CoCrNi) OOH model during OER cycling (reflected by metal-metal bond length variation in Supplementary Fig. 41), indicating the geometric distortion near Fe site. This distortion was reported to favor Ni species evolution, thereby improving the catalytic activity38. \n\nThe proposed free energy diagrams manifest that O–O coupling is significantly facilitated and no longer limits the reaction for LOM pathway in Fe-involved models. As known, LOM pathway typically involves the non-concerted protonelectron transfer step of RLS (Supplementary Fig. 42), originating from the mismatch of electron transfer kinetics and hydroxide affinity at the oxide/electrolyte interface (see details in Supplementary Note 7)12,18. Thus, proton-electron transfer is decoupled in RLS, exhibiting a pH-dependent activity. As expected, our Feinvolved catalysts shows much more sensitive correlation between $\\mathrm{\\pH}$ and OER activity (Fig. 4d and Supplementary Fig. 43), strengthening the argument of LOM pathway. To further clarify the oxidation of lattice oxygen ligands, an $^{18}\\mathrm{O}$ isotope-labelled experiment was designed18,20, as schemed in Supplementary Fig. 44. When $^{18}\\mathrm{O}$ -labelled catalysts with $\\mathrm{M}^{18}\\mathrm{O}_{x}^{\\mathrm{-}}\\mathrm{\\bar{H}}_{y}$ surface (Supplementary Fig. 45) are used to carry out OER, EA-FCCN and EA-FCN catalysts generate $^{18}\\mathrm{O}$ -labelled products (i.e., $^{16}\\mathrm{O}^{18}\\mathrm{O}$ and $^{18}\\mathrm{O}_{2}$ molecule) while EA-CCN cannot, as detected by MS (Fig. 4e). This straightforward evidence unambiguously corroborates the participation of lattice oxygen ligands into oxygen evolution for our Fe-involved catalysts. \n\nBy combining experimental evidences with simulated results, we propose an overall illustration towards OER on (FeCoCrNi) OOH model to rationalize the enhanced OER activity of corresponding EA-FCCN catalyst, as depicted in Fig. 4f. The interatomically electron interplay plays an organizing knob throughout the whole process on optimization of the reaction pathway. $\\mathrm{Ni^{4+}}$ species are favorably formed through a multistep evolution $\\mathrm{(Ni^{2+}{\\{\\vec{\\tau}\\rightarrow N i^{3+}\\vec{\\tau}\\rightarrow N i^{4+}\\}}}$ induced by the electronic modulation through Fe-O-Ni moiety and pre-adsorbed $\\mu\\mathrm{-}\\mathrm{O}_{a}\\mathrm{H}$ species at Ni-Co site, introducing holes into oxygen ligands to evoke LOM pathway via Mars-van Krevelen-like mechanism, then driving the construction of $\\mathrm{Fe-Ni}$ dual-site as ultimate catalytic center to loop the water oxidation. As a result, benefiting from the favorable formation of $\\mathrm{Ni^{4+}}$ species and dynamically constructed Fe–Ni dual-site, EA-FCCN catalyst offers low overpotential and superb activity for OER. \n\n# Discussion \n\nIn summary, we have demonstrated an FeCoCrNi MCA film as highly efficient OER electrocatalyst after irreversible surface reconstruction into $\\mathrm{Cr}$ -leached multimetal (oxy)hydroxides. High oxidized $\\mathrm{Ni^{4+}}$ species is dynamically formed and subtly engineered by the interatomically electronic interplay, playing a decisive role on constructing ultimate catalytic center, as fundamentally understood through electrochemical voltammetry, in situ Raman spectroscopy and ex situ sXAS techniques, as well as theoretical simulations. Fe component is unveiled to induce electron depletion in Ni species to ensure the formation of $\\mathrm{Ni^{4+}}$ species. Meanwhile, the high energy barrier of $\\mathrm{Ni^{4+}}$ formation is alleviated by a multistep evolution of $\\mathrm{Ni^{2+}{\\longrightarrow}N i^{3+}{\\longrightarrow}N i^{4+}}$ , which is facilitated by pre-absorbed hydroxyl at Ni-Co site. The formed $\\mathrm{Ni^{4+}}$ species enable oxygen ligands electrophilic through introducing holes, favoring intramolecular LOC to evoke LOM pathway via Mars-van Krevelen-like mechanism, corroborated by $^{18}\\mathrm{O}$ isotope-labelled experiments. An Fe–Ni dual-site is proposed to be dynamically constructed as ultimate catalytic center, achieving high OER activity and accelerating the reaction kinetics. As a result, the surface reconstructed FeCoCrNi MCA film electrocatalyst delivers the excellent mass activity and turnover frequency (TOF) of $3601\\mathrm{{Ag}_{m e t a l}-1}$ and $0.483\\thinspace s^{-1}$ at an overpotential of $300\\mathrm{mV}$ in alkaline electrolyte, respectively. This work endows a guideline for the exploration of advanced OER electrocatalysts as well as broadens the applications of multicomponent alloy materials toward catalysis. \n\n![](images/e6b7af16c02c4b7aab476c41219e6cad5782332444b334d8470fd00986a92688.jpg) \nFig. 4 Investigations of proposed OER pathway. a Free energy comparation between $\\mathsf{O H^{-}}$ adsorption and lattice hydroxyl deprotonation in different models. b Free energy diagram of OER cycling at Fe–Ni dual-site on (FeCoCrNi)OOH model. c The determined $\\Delta G$ of RLS via LOM and AEM pathway in different models. d The determined current densities of various catalysts at $1.5\\mathrm{V}$ versus RHE under different pH values. e The detected MS signals of generated oxygen molecule using $^{18}\\mathrm{O}$ isotope-labelled catalysts. The signals are normalized through initializing the intensity of $^{16}\\mathsf{O}_{2}$ as 1000 a.u. f Schematic illustration of the proposed overall OER pathway for EA-FCCN catalyst. The black and blue oxygen atoms represent lattice and adsorbed oxygen, respectively. \n\n# Methods \n\nChemicals. High purity alloy targets $(>99.99\\%)$ ) were customized from Beijing JAH TECH Co., Ltd, which were prepared by metallurgy using high purity $(>99.99\\%)$ metals (nickel, cobalt, iron, and chromium) as raw materials. Ruthenium oxide ${\\mathrm{RuO}}_{2}$ , $99.95\\%$ ) was purchased from Adamas-beta. $^{18}\\mathrm{O}$ isotope-labelled $\\mathrm{H}_{2}^{\\mathrm{~}18}\\mathrm{O}$ (97 $\\mathrm{{atom\\%}}$ of $^{18}\\mathrm{O}$ ) was purchased from J&K. Carbon black (VXC-72R) was obtained from CABOT. Carbon cloth (CC, W0S1009) was purchased from CeTech Co., Ltd. Other chemicals were obtained from Aladdin. The water used in all experiments was de-ionized (DI). \n\nDeposition of MCA films on CCs. A series of nominally equiatomic MCA films (i.e., FeCoCrNi, FeCrNi, and CoCrNi) with the thickness of about $100\\mathrm{nm}$ were deposited on CC substrates from the related alloy targets through a magnetron sputtering method at room temperature29,30. Prior to sputtering, the targets were initially cleaned by $\\mathrm{Ar^{+}}$ bombardment for $2\\mathrm{min}$ to remove the surface oxide and possible contaminants. CC substrates were ultrasonically cleaned using acetone, ethanol, and de-ionized water for $30\\mathrm{min}$ , respectively. High purity argon was introduced into the vacuum chamber once the base pressure was below $5.0\\times10^{-4}$ Pa. The total flow of argon flow rate was fixed at $12\\mathrm{sccm}$ (standard cubic centimeters per minute) and the rotation speed was $10\\mathrm{rpm}$ (revolutions per minute) to homogenize the alloy composition and film thickness. The substrates were neither cooled nor heated during deposition. The thickness of MCA films was adjusted by the sputtering time while other parameters were kept constant. \n\nElectrochemical activation of MCA films. Surface activation of MCA films coated on CCs were performed by the electrochemical CV scanning in a standard threeelectrode electrochemical cell using 1-M KOH solution as electrolyte. The MCA film samples, platinum plate and $\\mathrm{Hg/HgO}$ (1-M KOH) served as working electrode, counting electrode and reference electrode, respectively. In all, 200 cycles of CV scanning were conducted for each sample in the potential region from 0 to $0.6\\mathrm{V}$ versus $\\mathrm{Hg/HgO}$ at a sweep rate of $100\\mathrm{\\bar{mV}s^{-1}}$ to activate the surface. The electrochemical activated FeCoCrNi, FeCrNi and CoCrNi MCA films were simplified as EA-FCCN, EA-FCN, and EA-CCN, respectively. \n\nMaterial characterizations. SEM and EDS images were taken on a JEOL JSM6490 field emission scanning electron microscope operated at $5\\mathrm{kV}$ with EDS detector. Transmission electron microscope (TEM), high-resolution TEM (HRTEM), and selected area electron diffraction (SAED) images were collected on a JEOL JEM-2100F field-emission high-resolution transmission electron microscope operated at $200\\mathrm{kV}$ . The samples were prepared through ion-milling at the temperature of $223\\mathrm{K}.$ 3D atomic-probe tomography (APT) characterizations were performed in a CAMEACA LEAP 5000 XR local electrode atom probe. The specimens were analyzed at $45\\mathrm{K}$ in laser mode at a laser energy of $^{100}\\mathrm{p}]$ , pulse rate of $200\\mathrm{kHz}$ , and detection rate of $0.5\\%$ . Imago Visualization and Analysis Software (IVAS) version 3.8 was used for creating the 3D reconstructions and conducting the data analysis. X-ray diffraction (XRD) patterns were recorded by using a Rigaku SmartLab X-ray diffractometer with Cu-Kα radiation $(\\lambda=1\\dot{.}5418\\check{\\mathrm{A}})$ ). The loading mass of samples on CC were measured with a Thermo Scientific Plasma Quad 3 inductively coupled plasma mass spectrometry (ICP-MS) after dissolving the samples with aqua regia solution. Each sample was measured for three times to minimize the error. XPS spectra were collected on a Thermo Scientific Escalab 250Xi X-ray photoelectron spectrometer, using non-monochromatized Al-Kα Xray $(1486.6\\mathrm{eV})$ as the excitation source. \n\nElectrochemical measurements. All of the electrochemical measurements for OER were performed using a $\\mathrm{CHI}660\\mathrm{D}$ electrochemical workstation (Shanghai Chenhua, China) in a standard three-electrode electrochemical cell with $\\mathrm{O}_{2}$ -saturated 1-M KOH solution as electrolyte58. The as-prepared MCA/CC samples $(1\\times1$ $\\mathrm{cm}^{2}$ ) act as working electrode. Commercial $\\mathrm{RuO}_{2}$ powder mixing with conductive carbon black $(20\\mathrm{wt\\%})$ was drop-coated on a pretreated CC with the loading mass of $0.5\\mathrm{mg}\\mathrm{cm}^{-2}$ , serving as the benchmark catalyst. A platinum plate $(1\\times1\\mathrm{{cm}}^{2},$ ) and $\\mathrm{Hg/HgO}$ (1-M KOH) served as counting electrode and reference electrode, respectively. The measured potentials versus $\\mathrm{Hg/HgO}$ could be converted to the potentials versus reversible hydrogen electrode (RHE) by Equation (1): \n\n$$\nE_{\\mathrm{RHE}}=E_{\\mathrm{Hg/HgO}}+0.098+0.059\\times\\mathrm{pH}\n$$ \n\nPrior to the assessment of electrochemical performance, several CV scanning cycles were performed to stabilize the catalysts. LSV polarization curves were measured at a sweep rate of $5\\mathrm{mVs^{-1}}$ , and the potentials were corrected by $95\\%$ -iR compensation to eliminate the effect of solution resistance59. The Tafel plots were obtained by the corresponding LSV polarization curves plotted as overpotential versus the log current $(\\log[j])$ ). The stability tests were performed by chronoamperometry for $20\\mathrm{h}$ at the initial current density of ${\\sim}10\\mathrm{mA}\\mathrm{cm}^{-2}$ and CV scanning for 3000 cycles in the potential region from 0.2 to $0.7\\mathrm{V}$ versus $\\mathrm{Hg/HgO}$ at a sweep rate of $100\\mathrm{mVs^{-1}}$ . $C_{\\mathrm{dl}}$ was determined from the CV scanning curves measured in the non-Faradaic potential range from 0.85 to $1\\mathrm{V}$ versus RHE. The sweep rates were set to be 2, 5, 10, 20, 30, $50\\mathrm{mVs^{-1}}$ , respectively. $C_{\\mathrm{dl}}$ was estimated by plotting the $\\Delta J=(J_{+}-J_{-})/2$ at $0.925\\mathrm{V}$ versus RHE against the sweep rates. ECSA was calculated by Equation (2): \n\n$$\n\\mathrm{ECSA}=C_{\\mathrm{dl}}/C_{s}\\times A\n$$ \n\nwhere $C_{\\mathrm{s}}$ is the capacitance of an atomically smooth planar surface $(0.04\\mathrm{mF}\\ \\mathrm{cm}^{-2}$ in alkaline media60), and $A$ is the electrode area $\\cdot1\\mathrm{cm}^{-2}$ for our working electrodes). EIS were carried out in ZAHNER Electrochemical workstation with the frequency ranging from $10^{-2}$ to $10^{5}\\mathrm{Hz}$ with an amplitude of $5\\mathrm{mV}$ . To assess the intrinsic activity of our as-obtained samples, both mass activities and TOFs were calculated by Eqs. (3) and (4): \n\n$$\n{\\mathrm{massactivity}}=(j\\times A)/m\n$$ \n\n$$\n\\mathrm{TOF}=(j\\times A)/(4\\times F\\times n)\n$$ \n\nwhere $j$ was the current density, $A$ was the geometric area of electrode, $F$ was the Faraday constant $(96,485{\\mathrm{C}}{\\mathrm{mol}}^{-1})_{,}$ ), $m$ was the loading mass of sample, and $n$ was the number of active sites. For our assessment, the loading mass of samples was determined by ICP-MS, and all the deposited metal atoms were considered to be the active sites. To performed $^{18}\\mathrm{O}$ isotope-labelled experiments, MCA films were firstly activated in $^{18}\\mathrm{{O}}$ -labelled $\\mathrm{Na^{18}O H}$ electrolyte to form $\\mathrm{M}^{18}\\mathrm{O}_{x}\\mathrm{H}_{y}$ surface (schemed in Supplementary Fig. 43). Then, OER measurements were conducted in a sealed electrochemical cell with $\\Nu_{2}$ -saturated $\\mathrm{K^{16}O H}$ electrolyte at a current density of ca. 10 $\\operatorname{mA}{\\mathrm{cm}}^{-2}$ for $2\\mathrm{min}$ . Afterwards, the gas product was extracted and analyzed using gas chromatography-mass spectrometry (GC-MS, 7890A and 5975C, Agilent). \n\nElectrochemical in situ Raman spectra measurements. Electrochemical in situ Raman spectra were recorded in the WITEC alpha300R confocal Raman imaging equipment using a $633\\mathrm{-nm}$ laser with the power of $17\\mathrm{mW}$ . The Raman frequencies were corrected using silicon wafer. A home-built top-plate electrochemical cell was used for in situ Raman spectra measurements, in which a platinum plate and $\\mathrm{\\Ag/\\Omega}$ AgCl (saturated KCl) served as counting electrode and reference electrode, respectively. $\\mathrm{O}_{2}$ -saturated 1-M KOH solution was act as electrolyte to inject into the cell. To monitor the evolution of catalyst samples during OER process, Raman spectrum was collected after a constant potential was applied to the catalyst electrode for $10\\mathrm{min}$ . Each Raman spectrum was obtained by the integration time of 10 s with accumulating 5 times. \n\nEx situ sXAS measurements. Ex situ metal (Ni, Co, and Fe) $L$ -edge and O $K$ -edge sXAS measurements after treatment at different operated potentials were performed at the beamline BL12B-a of National Synchrotron Radiation Laboratory (NSRL) in Hefei, China. The electron beam energy of the storage ring was $800\\mathrm{MeV}$ with an average stored current of $300\\mathrm{mA}$ . A bending magnet was connected to the beamline and equipped with three gratings covering photon energies from 100 to $1000\\mathrm{eV}$ with an energy resolution of ${\\sim}0.2\\mathrm{eV}$ . All of data were recorded in the TEY mode by collecting the sample drain current under a vacuum greater than $5\\times10^{-8}$ Pa. The resolving power of the grating was typically $E/\\Delta E=1000$ , and the photon flux was $5\\times10^{8}$ photons per second. The catalyst samples were pretreated under different operated potentials for $10\\mathrm{min}$ , in which the operated potentials were desired to ensure the proceeding of OER (i.e., 1.5, 1.55 and $1.6\\mathrm{V}$ versus RHE for EA-FCCN, EA-FCN and EA-CCN, respectively). Afterwards, the as-treated samples were freeze-quenched by liquid $\\Nu_{2}$ and stored in liquid $\\Nu_{2}$ before sXAS measurements to minimize the surface degradation15,21. For sXAS tests, the astreated samples were taken out from liquid $\\Nu_{2}$ and quickly put into a high vacuum chamber. The related sXAS spectra were collected at room temperature. \n\nTheoretical simulations. DFT simulations were performed with the Vienna ab initio simulation package (VASP)61,62. The generalized gradient approximation (GGA) of the Perdew-Burke-Ernzerhof (PBE) functional63 and the projector augmented-wave (PAW) potential64 were employed. Grimme method65 was used to consider the weak van der Waals’ for layer materials. $\\beta$ -NiOOH with $(10-14)$ - terminated surface was selected as our pristine slab model51, and $4\\times4$ supercell was established. The periodic boundary condition (PBC) was set with a $20\\textup{\\AA}$ vacuum region above surface to avoid the attractions from adjacent periodic mirror images. To simplify our calculations, other metal atoms (i.e., Fe, Co, and $\\mathrm{Cr}$ ) were introduced into the slab model to substitute for (sub)surface Ni atoms, simulating the catalytic sites of multimetal (oxy)hydroxides structure formed during OER process (see Supplementary Note 4). An energy cutoff of $500\\mathrm{eV}$ was used for the plane-wave expansion of the electronic wave function for all numerical calculations with a Monkhorst-Pack mesh of $5\\times5\\times1$ . The force and energy convergence criterion were set to be $10^{-2}\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ and $10^{-5}\\mathrm{eV}$ , respectively. The relative location of various metal atoms was determined by the slab model with the lowest energy. \n\nThe computational hydrogen electrode (CHE) model66–68 was applied to simulate the OER pathway and determine the reaction energy barrier for different slab models. Various oxygen species intermediates were considered and the related adsorption energy $(\\Delta E_{\\mathrm{ads}})$ of those intermediates were calculated according to Eq. (5): \n\n$$\n\\Delta E_{\\mathrm{ads}}=E_{\\mathrm{total}}-E_{\\mathrm{sub}}-E_{\\mathrm{ads}}\n$$ \n\nwhere $E_{\\mathrm{total}},$ $E_{\\mathrm{sub}},$ and $E_{\\mathrm{ads}}$ represent the total energies of the systems, the substrates, and the adsorbates, respectively. The Gibbs free energy change $(\\Delta G)$ of each step was defined as Eq. (6): \n\n$$\n\\Delta G=\\Delta E+\\Delta Z P E--T\\Delta S\n$$ \n\nwhere $\\Delta E$ is the electronic energy difference, ΔZPE and $\\Delta S$ are the difference of zero-point energies and the change of entropy, respectively, which were estimated from the vibrational frequencies, and $T=298.15\\mathrm{K}$ . The computational details were shown in Supplementary Note 5. \n\n# Data availability \n\nThe data supporting the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 5 February 2020; Accepted: 24 July 2020; Published online: 13 August 2020 \n\n# References \n\n1. Roger, I., Shipman, M. A. & Symes, M. D. Earth-abundant catalysts for electrochemical and photoelectrochemical water splitting. Nat. Rev. Chem. 1, 0003 (2017). \n2. Hwang, J. et al. Perovskites in catalysis and electrocatalysis. Science 358, 751–756 (2017). \n3. Kibsgaard, J. & Chorkendorff, I. Considerations for the scaling-up of water splitting catalysts. Nat. Energy 4, 430–433 (2019). \n4. Suen, N. T. et al. Electrocatalysis for the oxygen evolution reaction: recent development and future perspectives. Chem. Soc. Rev. 46, 337–365 (2017). \n5. Song, F. et al. Transition metal oxides as electrocatalysts for the oxygen evolution reaction in alkaline solutions: an application-inspired renaissance. J. Am. Chem. Soc. 140, 7748–7759 (2018). \n6. Shi, Q., Zhu, C., Du, D. & Lin, Y. Robust noble metal-based electrocatalysts for oxygen evolution reaction. Chem. Soc. Rev. 48, 3181–3192 (2019). \n7. Seitz, L. C. et al. A highly active and stable $\\mathrm{IrO}_{x}/\\mathrm{SrIrO}_{3}$ catalyst for the oxygen evolution reaction. Science 353, 1011–1014 (2016). \n8. Hunter, B. M., Gray, H. B. & Müller, A. M. Earth-abundant heterogeneous water oxidation catalysts. Chem. Rev. 116, 14120–14136 (2016). \n9. Suntivich, J., May, K. J., Gasteiger, H. A., Goodenough, J. B. & Shao-Horn, Y. A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles. Science 334, 1383–1385 (2011). \n10. Cheng, W. et al. Lattice-strained metal-organic-framework arrays for bifunctional oxygen electrocatalysis. Nat. Energy 4, 115–122 (2019). \n11. Wu, T. et al. Iron-facilitated dynamic active-site generation on spinel $\\mathrm{CoAl}_{2}\\mathrm{O}_{4}$ with self-termination of surface reconstruction for water oxidation. Nat. Catal. 2, 763–772 (2019). \n12. Huang, Z.-F. et al. Chemical and structural origin of lattice oxygen oxidation in $\\mathrm{Co-Zn}$ oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). \n13. Qiu, B. et al. $\\mathrm{CeO}_{2}$ -induced interfacial $C o^{2+}$ octahedral sites and oxygen vacancies for water oxidation. ACS Catal. 9, 6484–6490 (2019). \n14. Grimaud, A. et al. Activation of surface oxygen sites on an iridium-based model catalyst for the oxygen evolution reaction. Nat. Energy 2, 16189 (2016). \n15. Bergmann, A. et al. Reversible amorphization and the catalytically active state of crystalline $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ during oxygen evolution. Nat. Commun. 6, 8625 (2015). \n16. Zheng, X. et al. Theory-driven design of high-valence metal sites for water oxidation confirmed using in situ soft X-ray absorption. Nat. Chem. 10, 149–154 (2018). \n17. Grimaud, A., Hong, W. T., Shao-Horn, Y. & Tarascon, J. M. Anionic redox processes for electrochemical devices. Nat. Mater. 15, 121 (2016). \n18. Grimaud, A. et al. Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution. Nat. Chem. 9, 457–465 (2017). \n19. Fabbri, E. et al. Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting. Nat. Mater. 16, 925–931 (2017). \n20. Roy, C. et al. Impact of nanoparticle size and lattice oxygen on water oxidation on NiFeOxHy. Nat. Catal. 1, 820–829 (2018). \n21. Bergmann, A. et al. Unified structural motifs of the catalytically active state of Co(oxyhydr)oxides during the electrochemical oxygen evolution reaction. Nat. Catal. 1, 711–719 (2018). \n22. Chen, J. Y. C. et al. Operando analysis of NiFe and Fe oxyhydroxide electrocatalysts for water oxidation: detection of $\\mathrm{Fe^{4+}}$ by Mössbauer spectroscopy. J. Am. Chem. Soc. 137, 15090–15093 (2015). \n23. Trotochaud, L., Young, S. L., Ranney, J. K. & Boettcher, S. W. Nickel–iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation. J. Am. Chem. Soc. 136, 6744–6753 (2014). \n24. Zhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n25. Jiang, J. et al. Atomic-level insight into super-efficient electrocatalytic oxygen evolution on iron and vanadium co-doped nickel (oxy)hydroxide. Nat. Commun. 9, 2885 (2018). \n26. Zuo, Y. et al. Valence engineering via dual-cation and boron doping in pyrite selenide for highly efficient oxygen evolution. ACS Nano 13, 11469–11476 (2019). \n27. Yao, Y. et al. Carbothermal shock synthesis of high-entropy-alloy nanoparticles. Science 359, 1489–1494 (2018). \n28. George, E. P., Raabe, D. & Ritchie, R. O. High-entropy alloys. Nat. Rev. Mater. 4, 515–534 (2019). \n29. Liao, W. et al. Nanocrystalline high-entropy alloy (CoCrFeNiAl0.3) thin-film coating by magnetron sputtering. Thin Solid Films 638, 383–388 (2017). \n30. Gao, L. et al. High-entropy alloy (HEA)-coated nanolattice structures and their mechanical properties. Adv. Eng. Mater. 20, 1700625 (2018). \n31. Xu, D. et al. The role of Cr doping in NiFe oxide/(oxy)hydroxide electrocatalysts for oxygen evolution. Electrochim. Acta 265, 10–18 (2018). \n32. Yan, Z. et al. Anion insertion enhanced electrodeposition of robust metal hydroxide/oxide electrodes for oxygen evolution. Nat. Commun. 9, 2373 (2018). \n33. Mueller, D. N., Machala, M. L., Bluhm, H. & Chueh, W. C. Redox activity of surface oxygen anions in oxygen-deficient perovskite oxides during electrochemical reactions. Nat. Commun. 6, 6097 (2015). \n34. Zhao, S. et al. Ultrathin metal-organic framework nanosheets for electrocatalytic oxygen evolution. Nat. Energy 1, 16184 (2016). \n35. Görlin, M. et al. Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni–Fe oxide water splitting electrocatalysts. J. Am. Chem. Soc. 138, 5603–5614 (2016). \n36. Li, N. et al. Influence of iron doping on tetravalent nickel content in catalytic oxygen evolving films. Proc. Natl Acad. Sci. USA 114, 1486–1491 (2017). \n37. Xiao, H., Shin, H. & Goddard, W. A. Synergy between Fe and Ni in the optimal performance of (Ni,Fe)OOH catalysts for the oxygen evolution reaction. Proc. Natl Acad. Sci. USA 115, 5872–5877 (2018). \n38. Smith, R. D. L. et al. Geometric distortions in nickel (oxy)hydroxide electrocatalysts by redox inactive iron ions. Energy Environ. Sci. 11, 2476–2485 (2018). \n39. Bak, J., Bin Bae, H. & Chung, S.-Y. Atomic-scale perturbation of oxygen octahedra via surface ion exchange in perovskite nickelates boosts water oxidation. Nat. Commun. 10, 2713 (2019). \n40. Friebel, D. et al. Identification of highly active Fe stes in (Ni,Fe)OOH for electrocatalytic water splitting. J. Am. Chem. Soc. 137, 1305–1313 (2015). \n41. Lee, S., Banjac, K., Lingenfelder, M. & Hu, X. Oxygen isotope labeling experiments reveal different reaction sites for the oxygen evolution reaction on nickel and nickel iron oxides. Angew. Chem. Int. Ed. 58, 10295–10299 (2019). \n42. Goldsmith, Z. K. et al. Characterization of NiFe oxyhydroxide electrocatalysts by integrated electronic structure calculations and spectroelectrochemistry. Proc. Natl Acad. Sci. USA 114, 3050–3055 (2017). \n43. Hunter, B. M. et al. Trapping an iron(VI) water-splitting intermediate in nonaqueous media. Joule 2, 747–763 (2018). \n44. Chung, D. Y. et al. Dynamic stability of active sites in hydr(oxy)oxides for the oxygen evolution reaction. Nat. Energy 5, 222–230 (2020). \n45. Klaus, S., Cai, Y., Louie, M. W., Trotochaud, L. & Bell, A. T. Effects of Fe electrolyte impurities on $\\mathrm{Ni(OH)_{2}/N i O O H}$ structure and oxygen evolution activity. J. Phys. Chem. C. 119, 7243–7254 (2015). \n46. Louie, M. W. & Bell, A. T. An investigation of thin-film Ni–Fe oxide catalysts for the electrochemical evolution of oxygen. J. Am. Chem. Soc. 135, 12329–12337 (2013). \n47. Huang, J. et al. Identification of key reversible intermediates in selfreconstructed nickel-based hybrid electrocatalysts for oxygen evolution. Angew. Chem. Int. Ed. 58, 17458–17464 (2019). \n48. Shin, H., Xiao, H. & Goddard, W. A. In silico discovery of new dopants for Fedoped Ni oxyhydroxide $(\\mathrm{Ni_{1-x}F e x O O H})$ catalysts for oxygen evolution reaction. J. Am. Chem. Soc. 140, 6745–6748 (2018). \n49. Assat, G. & Tarascon, J.-M. Fundamental understanding and practical challenges of anionic redox activity in Li-ion batteries. Nat. Energy 3, 373–386 (2018). \n50. Zaanen, J., Sawatzky, G. A. & Allen, J. W. Band gaps and electronic structure of transition-metal compounds. Phys. Rev. Lett. 55, 418–421 (1985). \n51. Bajdich, M., García-Mota, M., Vojvodic, A., Nørskov, J. K. & Bell, A. T. Theoretical investigation of the activity of cobalt oxides for the electrochemical oxidation of water. J. Am. Chem. Soc. 135, 13521–13530 (2013). \n52. Yabuuchi, N. et al. Origin of stabilization and destabilization in solid-state redox reaction of oxide ions for lithium-ion batteries. Nat. Commun. 7, 13814 (2016). \n53. Shan, J., Ling, T., Davey, K., Zheng, Y. & Qiao, S.-Z. Transition-metal-doped RuIr bifunctional nanocrystals for overall water splitting in acidic environments. Adv. Mater. 31, 1900510 (2019). \n54. Trześniewski, B. J. et al. In situ observation of active oxygen species in Fecontaining Ni-based oxygen evolution catalysts: the effect of pH on electrochemical activity. J. Am. Chem. Soc. 137, 15112–15121 (2015). \n55. Garcia, A. C., Touzalin, T., Nieuwland, C., Perini, N. & Koper, M. T. M. Enhancement of oxygen evolution activity of nickel oxyhydroxide by electrolyte alkali cations. Angew. Chem. Int. Ed. 58, 12999–13003 (2019). \n56. Xiao, M. et al. Climbing the apex of the ORR volcano plot via binuclear site construction: electronic and geometric engineering. J. Am. Chem. Soc. 141, \n17763–17770 (2019). \n57. Cao, L. et al. Identification of single-atom active sites in carbon-based cobalt catalysts during electrocatalytic hydrogen evolution. Nat. Catal. 2, 134–141 (2019). \n58. Wei, C. et al. Recommended practices and benchmark activity for hydrogen and oxygen electrocatalysis in water splitting and fuel cells. Adv. Mater. 31, \n1806296 (2019). \n59. Gong, M. et al. An advanced Ni–Fe layered double hydroxide electrocatalyst for water oxidation. J. Am. Chem. Soc. 135, 8452–8455 (2013). \n60. McCrory, C. C. L., Jung, S., Peters, J. C. & Jaramillo, T. F. Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 135, 16977–16987 (2013). \n61. Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquidmetal-amorphous-semiconductor transition in germanium. Phys. Rev. B 49, \n14251–14269 (1994). \n62. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n63. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n64. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n65. Grimme, S., Antony, J., Ehrlich, S. & Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 132, 154104 (2010). \n66. Nørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuelcell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n67. Rossmeisl, J., Logadottir, A. & Nørskov, J. K. Electrolysis of water on (oxidized) metal surfaces. Chem. Phys. 319, 178–184 (2005). \n68. Peterson, A. A., Abild-Pedersen, F., Studt, F., Rossmeisl, J. & Nørskov, J. K. How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels. Energy Environ. Sci. 3, 1311–1315 (2010). \n\n# Acknowledgements \n\nThis work was supported by Research Grant Council of Hong Kong (Grant No. N_PolyU540/17), the Hong Kong Polytechnic University (Grant No. G-YW2A), and Science, Technology and Innovation Commission of Shenzhen (JCYJ20180507183424383). X.F. and Y.L. are grateful to the support from City University of Hong Kong (Grant No. 9610461) and the funding supporting from Shenzhen Science and Technology Innovation \n\nCommittee (JCYJ20170413141157573). Theoretical simulation was supported by the National Natural Science Foundation of China (Grant No. 51801075) and performed on TianHe-2 at Lvliang Cloud Computing Center of China. D.R. gratefully acknowledge the support of Jiangsu Overseas Visiting Scholar Program for University Prominent Young and Mid-aged Teachers and Presidents. We also thank the beamline BL12B-a in the National Synchrotron Radiation Laboratory (NSRL) in Hefei, China for the support of sXAS measurements. \n\n# Author contributions \n\nY.C. supervised this project. N.Z. and Y.C. conceived the original concept, analyzed the data and wrote the paper. X.F. performed synthesis and characterizations of MCA films. N.Z., L.C. and B.Q. carried out electrochemical measurements and discussed the results. D.R. performed DFT simulations. X.D. and R.L. helped N.Z. to conduct Raman and sXAS tests. X.Y. and Y.L. revised the manuscript and triggered helpful discussion. All authors discussed the results and commended on paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-17934-7. \n\nCorrespondence and requests for materials should be addressed to Y.L. or Y.C. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contributions to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1016_S1872-2067(19)63382-6", + "DOI": "10.1016/S1872-2067(19)63382-6", + "DOI Link": "http://dx.doi.org/10.1016/S1872-2067(19)63382-6", + "Relative Dir Path": "mds/10.1016_S1872-2067(19)63382-6", + "Article Title": "Enhanced photocatalytic H2-production activity of WO3/TiO2 step-scheme heterojunction by graphene modification", + "Authors": "He, F; Meng, AY; Cheng, B; Ho, WK; Yu, JG", + "Source Title": "CHINESE JOURNAL OF CATALYSIS", + "Abstract": "Sunlight-driven photocatalytic water-splitting for hydrogen (H-2) evolution is a desirable strategy to utilize solar energy. However, this strategy is restricted by insufficient light harvesting and high photogenerated electron-hole recombination rates of TiO2-based photocatalysts. Here, a graphene-modified WO3/TiO2 step-scheme heterojunction (S-scheme heterojunction) composite photocatalyst was fabricated by a facile one-step hydrothermal method. In the ternary composite, TiO2 and WO3 nulloparticles adhered closely to reduced graphene oxide (rGO) and formed a novel S-scheme heterojunction. Moreover, rGO in the composite not only supplied abundant adsorption and catalytically active sites as an ideal support but also promoted electron separation and transfer from the conduction band of TiO2 by forming a Schottky junction between TiO2 and rGO. The positive cooperative effect of the S-scheme heterojunction formed between WO3 and TiO2 and the Schottky heterojunction formed between TiO2 and graphene sheets suppressed the recombination of relatively useful electrons and holes. This effect also enhanced the light harvesting and promoted the reduction reaction at the active sites. Thus, the novel ternary WO3/TiO2/rGO composite demonstrated a remarkably enhanced photocatalytic H-2 evolution rate of 245.8 Fmol g(-1) h(-1), which was approximately 3.5-fold that of pure TiO2. This work not only presents a low-cost graphene-based S-scheme heterojunction photocatalyst that was obtained via a feasible one-step hydrothermal approach to realize highly efficient H-2 generation without using noble metals, but also provides new insights into the design of novel heterojunction photocatalysts. (C) 2020, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.", + "Times Cited, WoS Core": 531, + "Times Cited, All Databases": 556, + "Publication Year": 2020, + "Research Areas": "Chemistry; Engineering", + "UT (Unique WOS ID)": "WOS:000495145800003", + "Markdown": "# Article (Special Issue on Photocatalytic ${\\sf H}_{2}$ Production and ${\\mathsf{C O}}_{2}$ Reduction) \n\n# Enhanced photocatalytic $\\mathbf{H}_{2}$ -production activity of WO3/TiO2 step-scheme heterojunction by graphene modification \n\nFei He a, Aiyun Meng a, Bei Cheng a, Wingkei Ho b,#, Jiaguo Yu a,c,\\* \n\na State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, International School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China \nb Department of Science and Environmental Studies and State Key Laboratory in Marine Pollution, The Education University of Hong Kong, Tai Po, N. T. Hong Kong, China \nc Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nArticle history: Received 28 February 2019 Accepted 16 April 2019 Published 5 January 2020 \n\nKeywords: \nStep-like heterojunction \nS-scheme heterojunction \nS heterojunction \nPhotocatalyst \nHydrogen generation \n\nSunlight-driven photocatalytic water-splitting for hydrogen $\\left(\\mathrm{H}_{2}\\right)$ evolution is a desirable strategy to utilize solar energy. However, this strategy is restricted by insufficient light harvesting and high photogenerated electron–hole recombination rates of $\\mathrm{TiO}_{2}$ -based photocatalysts. Here, a graphene-modified $\\mathrm{WO_{3}/T i O_{2}}$ step-scheme heterojunction (S-scheme heterojunction) composite photocatalyst was fabricated by a facile one-step hydrothermal method. In the ternary composite, $\\mathrm{TiO}_{2}$ and $\\mathsf{W O}_{3}$ nanoparticles adhered closely to reduced graphene oxide (rGO) and formed a novel S-scheme heterojunction. Moreover, rGO in the composite not only supplied abundant adsorption and catalytically active sites as an ideal support but also promoted electron separation and transfer from the conduction band of $\\mathrm{TiO}_{2}$ by forming a Schottky junction between $\\mathrm{TiO}_{2}$ and $\\boldsymbol{\\mathrm{rG0}}$ . The positive cooperative effect of the S-scheme heterojunction formed between $\\mathsf{W O}_{3}$ and $\\mathrm{TiO_{2}}$ and the Schottky heterojunction formed between $\\mathrm{TiO}_{2}$ and graphene sheets suppressed the recombination of relatively useful electrons and holes. This effect also enhanced the light harvesting and promoted the reduction reaction at the active sites. Thus, the novel ternary $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite demonstrated a remarkably enhanced photocatalytic $\\mathrm{H}_{2}$ evolution rate of $245.8\\ \\upmu\\mathrm{mol\\g^{-1}h^{-1}}$ which was approximately 3.5-fold that of pure $\\mathrm{TiO}_{2}$ This work not only presents a low-cost graphene-based S-scheme heterojunction photocatalyst that was obtained via a feasible one-step hydrothermal approach to realize highly efficient $\\mathrm{H}_{2}$ generation without using noble metals, but also provides new insights into the design of novel heterojunction photocatalysts. \n\n$\\textcircled{c}2020$ , Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nHydrogen $\\left(\\mathrm{H}_{2}\\right)$ , a source of clean and high-heat-density secondary energy, is one of the promising energy carriers that can satisfy the ever-increasing energy and environmental demands [1–3]. Photocatalytic water splitting for $\\mathrm{H}_{2}$ production has received great attention owing to its simplicity and recyclability, and involves the conversion of solar energy to chemical energy with the help of a photocatalyst, sunlight, and water at room temperature [4–6]. Since the pioneering work of Fujishima and \n\nHonda on $\\mathrm{TiO}_{2}$ electrodes for photoelectrochemical water splitting, various semiconductors, including $\\mathrm{TiO}_{2}$ [7], CdS [8,9], ${\\sf W O}_{3}$ [10], $\\mathrm{C_{3}N_{4}}$ [11,12], and $z\\mathrm{no}$ [13,14], have been explored to develop highly active, robust, and low-cost photocatalysts and photoelectrodes for industrial application. By virtue of its high stability, environmental friendliness, and low cost [15], $\\mathrm{TiO}_{2}$ has been extensively studied and plays a vital role in $\\mathrm{H}_{2}$ production, pollutant degradation [16,17], and $\\mathsf{C O}_{2}$ reduction [18,19]. However, pure $\\mathrm{TiO}_{2}$ photocatalyst exhibits unsatisfactory photocatalytic activity owing to insufficient light harvesting (no more than $5\\%$ ) and a high photogenerated electron–hole recombination rate [2,20], which severely restrict its industrial application. To date, a myriad of strategies have been proposed for enhancing the photocatalytic activity, such as loading noble metals [21], doping metallic or non-metallic elements [22], and constructing heterojunctions [23–25]. \n\nHeterojunction construction by integrating two semiconductors is a universal strategy owing to its effectiveness in spatially separating the photoexcited electron–hole pairs via appropriate band alignments between the semiconductors [1,26]. Recently, a new step-scheme heterojunction (S-scheme heterojunction) concept was proposed to explain the increased charge transfer rate observed at the interface of two photocatalysts with staggered band structures [27]. Typically, a S-heterojunction photocatalyst is formed between a reduction photocatalyst and an oxidation photocatalyst. In general, reduction photocatalysts display comparatively higher conduction bands (CBs) and Fermi levels. On the contrary, oxidation photocatalysts exhibit comparatively lower CBs and Fermi levels. Intriguingly, $\\mathsf{W O}_{3},$ with a relatively narrow bandgap, between 2.4 and $2.8~\\mathrm{eV}$ [28], is a representative oxidation-type photocatalyst that is amenable to the fabrication of S-heterojunction composites. Owing to its large work function $\\left(6.23~\\mathrm{eV}\\right)$ and low Fermi level [27], the electrons in the CB of $\\mathsf{W O}_{3}$ can scarcely exhibit a reduction capacity, based on thermodynamics [29], and are therefore relatively useless for photocatalytic $\\mathrm{H}_{2}$ -evolution reactions. By taking advantage of the S-scheme charge transfer mechanism, the unnecessary electrons in the CB of ${\\sf W O}_{3}$ can be recombined with the comparatively useless holes in the valence band (VB) of $\\mathrm{TiO}_{2}$ Consequently, the separation of useful photoinduced charge carriers at the heterogeneous interface is promoted, and the high redox capacities of the electrons in the CB of $\\mathrm{TiO}_{2}$ and the holes in the VB of ${\\sf W O}_{3}$ are retained. Additionally, $\\mathsf{W O}_{3}$ demonstrates strong light absorption and great resistance to photocorrosion [30]. As reported, $\\boldsymbol{\\mathsf{W O3}}$ can extend its light absorption range to the visible or even near infrared (NIR) region when coupled with $\\mathrm{TiO}_{2}$ to construct a ${\\mathrm{TiO}_{2}}/{\\mathrm{W}}0_{3}\\{$ -scheme heterojunction [31,32]. \n\nReduced graphene oxide (rGO) with a two-dimensional (2D) honeycomb lamella of C atoms is a prospective candidate for the electron container and acceptor in heterogeneous photocatalytic systems that can facilitate the shuttling of photoexcited electrons for water-splitting reaction [33]. In addition to its excellent thermal conductivity and large carrier mobility, rGO exhibits a high theoretical specific surface area and thereby offers abundant adsorption and catalytic sites for photocatalytic reactions [34]. The presence of rGO can also extend the range of light absorption to the visible region and even to the infrared region, which may induce a positive photothermal effect and increase the photocatalytic $\\mathrm{H}_{2}$ yield. Recently, ternary composite photocatalysts have emerged as alluring candidates for photocatalytic $\\mathrm{H}_{2}$ evolution because of their cooperative effect on the successive charge transfer occurring between three different components, such as ZnO-MoS2-rGO [35], $\\mathrm{TiO}_{2}{\\cdot}\\mathrm{MnO}_{x}{\\cdot}\\mathrm{Pt}$ [36], and $\\mathrm{g{-}C_{3}N_{4}/R P/M o S_{2}}$ (RP denotes red phosphorus) [37]. Therefore, it is desirable to fabricate a rGO-based composite photocatalyst to enhance the photocatalytic activity and stability [38]. \n\nHerein, we reported a facile one-step hydrothermal method to synthesize $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}$ S-heterojunction photocatalyst by graphene modification (WTG). $\\mathrm{TiO}_{2}$ and $\\mathsf{W O}_{3}$ formed a S-scheme heterostructure with a strong interaction at the interface, which facilitated charge transfer and separation. The S-scheme mechanism was evidenced by the greatly improved $\\mathrm{H}_{2}$ evolution performance. Additionally, rGO acted as a supporting matrix and an electron transfer channel, supplied surface active sites, enhanced the light absorption, and exhibited a unique photothermal effect in WTG composite. The cooperative effect of rGO and $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}$ heterojunction promoted the photocatalytic reaction. Consequently, WTG composites exhibited higher photocatalytic $\\mathrm{H}_{2}$ generation activities than pure $\\mathrm{TiO}_{2}$ . \n\n# 2. Experimental \n\n# 2.1. Photocatalyst preparation \n\nThe $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite was fabricated by a one-step hydrothermal approach. All the reagents employed were analytical grade and used without further purification. GO was synthesized from commercial graphite powder by using modified Hummer’s method [39]. Typically, for the preparation of the WTG sample, a GO suspension $(3\\ \\mathrm{mL},1\\ \\mathrm{mg\\mL^{-1}})$ was diluted in a mixed solution of distilled water $35~\\mathrm{mL}$ ) and ethanol $(17.5~\\mathrm{mL})$ and sonicated for $15~\\mathrm{min}$ . Then, D- $^{(+)}$ -glucose (20 mg) was dissolved in the GO suspension and stirred for $10\\mathrm{min}$ . Subsequently, $1.3~\\mathrm{mL}$ of $\\mathrm{Ti(0C_{4}H_{9})_{4}}$ (TBOT) as the Ti source, which was dissolved in ethanol (9 mL), was added dropwise to the mixture under magnetic stirring. After $30~\\mathrm{min}$ , $0.13~\\mathrm{mmol}$ of $N a_{2}\\mathrm{WO}_{4}{\\cdot}2\\mathrm{H}_{2}0$ was added to the solution, and its pH was adjusted to 2 with hydrochloric acid (1 M). An hour later, the milky mixture was transferred to a Teflon-lined stainless-steel autoclave and kept at $180^{\\circ}\\mathrm{C}$ for $12\\mathrm{~h~}$ . The resultant dark grey precipitate was washed with distilled water and ethanol thoroughly and freeze-dried overnight to yield $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite. In the composite, the theoretical mass ratio of rGO to $\\mathrm{TiO}_{2}$ was $1\\%,$ and the theoretical mass ratio of ${\\sf W O}_{3}$ to $\\mathrm{TiO}_{2}$ was $10\\%$ . The sample was designated as WTG. \n\nSimilarly, $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}$ was synthesized by following the same procedure as detailed above, except for the addition of GO. Likewise, $\\mathrm{TiO}_{2}/\\mathrm{rGO}$ was prepared by removing the step involving $N a_{2}\\mathrm{WO}_{4}{\\cdot}2\\mathrm{H}_{2}0$ and $\\mathsf{p H}$ adjustment. Pristine $\\mathsf{W O}_{3}$ was produced from the $N a_{2}\\mathrm{W}0_{4}{\\cdot}2\\mathrm{H}_{2}0$ solution of $\\boldsymbol{\\mathrm{pH}}=2$ . To prepare pure ${\\mathrm{TiO}}_{2},$ the TBOT ethanol solution was added to a mixture of distilled water and ethanol. All the samples were subjected to the aforementioned hydrothermal process. The as-prepared ${\\sf W O}_{3}/{\\mathrm{Ti}}0_{2}$ , $\\mathrm{TiO}_{2}/\\mathrm{rGO}$ , and pristine $\\mathsf{W O3}$ and $\\mathrm{TiO}_{2}$ were designated as WT, TG, W, and T, respectively. Inductively coupled plasma (ICP)-optical emission spectrometry was conducted to investigate the actual contents of Ti and W elements. The results are listed in Table 1. \n\n# 2.2. Characterization \n\nPowder X-ray diffraction (XRD) was performed by using a D/MAX-RB diffractometer (Rigaku, Japan) with $\\operatorname{Cu}K_{\\alpha}$ radiation. To characterize the morphological structures and microscopic details of the samples, field-emission scanning electron microscopy (FESEM) images were obtained by using a JSM-7500F scanning electron microscope (SEM; JEOL, Japan). Transmission electron microscopy (TEM) was carried out by using a JEM-2100F instrument $\\begin{array}{r}{(\\mathrm{IEOL},}\\end{array}$ Japan) with an accelerating voltage of $200~\\mathrm{kV}.$ . The pore size distribution and specific surface area were obtained from nitrogen $\\left(\\mathsf{N}_{2}\\right)$ adsorption-desorption isotherms on a Micromeritics ASAP 2020 instrument. The specific surface area results were determined by using the adsorption data in the relative pressure $\\left(P/P0\\right)$ range 0.05–0.3. Raman spectra were recorded with the help of a micro-Raman spectrometer (Renishaw inVia, U.K.). X-ray photoelectron spectroscopy (XPS) measurements were performed by using an ESCALAB 250 Xi electron spectrometer (Thermo Scientific Corporation, USA) to estimate the surface elemental composition and chemical states. To investigate the optical properties of the samples, the UV-vis diffuse reflectance spectra (DRS) were obtained by using a Shimadzu UV 2600 UV-vis spectrometer with $\\mathsf{B a S O}_{4}$ as the reference. The elemental contents were analyzed on an ICP-optical emission spectrometer (Prodigy 7, Leeman Labs Inc.). \n\n# 2.3. Photocatalytic H2 generation test \n\nThe photocatalytic activities of the samples were evaluated based on the photocatalytic yields of $\\mathrm{H}_{2}$ from water splitting in a $100~\\mathrm{{mL}}$ Pyrex flask. First, $50~\\mathrm{mg}$ of a sample was suspended by ultrasonication in $80~\\mathrm{mL}$ of $20\\mathrm{vol}\\%$ aqueous methanol solution. Then, the sealed system was bubbled with ${\\sf N}_{2}$ for $0.5\\mathrm{~h~}$ to ensure anaerobic conditions during photocatalytic water splitting. A 350 W Xe arc lamp was used as the light source. After an hour of irradiation, $0.4~\\mathrm{mL}$ of gas was extracted from the flask by using a syringe to analyze the $\\mathrm{H}_{2}$ concentration by gas chromatography (GC-14C, Shimadzu, Japan) with the assistance of a thermal conductivity detector. Photocatalytic $\\mathrm{H}_{2}$ production cycled tests were conducted by continuously sampling gas from the flask at an interval of an hour and rebubbling the solution with ${\\sf N}_{2}$ for $0.5\\mathrm{~h~}$ every $^{3\\mathrm{~h~}}$ . The apparent quantum efficiency (AQE) was measured under the irradiation of four low-power light-emitting diode (LED) lamps $(\\lambda=365~\\mathrm{{nm}})$ ). The AQE can be computed by the following equation. \n\nTable 1 Elemental contents of the prepared samples. \n\n\n
SampleTi (wt%)W (wt%)
WTG61.636.52
WT63.176.58
TG75.45-
\n\n$$\n{\\mathrm{AQE}}={\\frac{2\\times{\\mathrm{Amount~of}}{\\mathrm{H}}_{2}{\\mathrm{~yielded}}}{\\mathrm{Total~number~of~incident~photons}}}\\times100\\%\n$$ \n\n# 2.4. Photoelectrode fabrication and photoelectrochemical measurements \n\nPhotoelectrochemical measurements were conducted on a typical three-electrode system by using a CHI-660C electrochemical workstation (Chenhua Instrument, Shanghai, China). A Pt wire and $\\mathrm{\\DeltaAg/AgCl}$ electrode were employed as the counter and reference electrodes, respectively. The working electrode was the photocatalyst film, which was deposited on the conductive surface of a F-doped tin oxide (FTO) glass with an active area of ca. $1\\mathrm{cm}^{2}$ . The preparation process was as follows: $20~\\mathrm{mg}$ of the photocatalyst was added to $1~\\mathrm{mL}$ of ethanol and ground to a sticky slurry for approximately $0.5\\mathrm{~h~}$ Afterwards, the homogeneous paste was evenly applied on the conductive surface of the FTO glass by doctor blading technique and then dried in air. A LED ( $\\lambda=365~\\mathrm{{nm}}$ ) with an intensity of ca. 44.0 $\\mathrm{\\mW\\cm^{-2}}$ acted as the light source. A volume of $20~\\mathrm{mL}$ of $0.5\\mathrm{M}$ aqueous $\\mathrm{{Na2SO_{4}}}$ solution was used as the electrolyte. The initial bias potential in the transient photocurrent responses and electrochemical impedance spectroscopy (EIS) tests was the open-circuit voltage. \n\n# 3. Results and discussion \n\n# 3.1. Physicochemical properties of the samples \n\nA facile one-step hydrothermal method was utilized to fabricate the samples, and the as-obtained samples, including pristine $\\mathsf{W O3}$ and $\\mathrm{TiO_{2},W O_{3}/T i O_{2},T i O_{2}/r G0,}$ and $\\mathrm{WO_{3}/T i O_{2}/r G0,}$ were designated as W, T, WT, TG, and WTG, respectively. The representative SEM images of WTG are shown in Fig. 1. The pristine $\\mathrm{TiO}_{2}$ and $\\boldsymbol{\\mathsf{W O3}}$ tended to self-aggregate with the irregular bulk. However, for the WTG composites, the $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ particles were homogeneously mixed, thus forming a $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}$ heterostructure via strong interactions between $\\mathrm{TiO}_{2}$ and $\\boldsymbol{\\mathsf{W O3}}$ The particles were closely and evenly grown in-situ on the anchoring sites of GO, which implied that the graphene sheets prevented the $\\mathrm{TiO}_{2}$ and WO3 nanoparticles from assembling as an underlying substrate in WTG. This intimate interaction is beneficial for electron transfer from the $\\mathrm{TiO}_{2}$ or $\\mathsf{W O}_{3}$ particles to the graphene sheet during photoexcitation. After the hydrothermal treatment, the $\\mathrm{rG}0$ retained the morphology of micron-sized 2D sheets with spontaneous wrinkles. The $\\mathrm{TiO}_{2}$ and WO3 nanoparticles adhering to the oxidized graphene prevented the naked sheets from restacking, thus preserving the active surfaces. In addition, in the EDS elemental mapping images of WTG (Fig. 1(c)), the distributions of C, O, Ti, and W elements all matched well with the outline of the FESEM image, which suggested that the $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ particles were evenly decentralized on the surface of rGO. \n\n![](images/1b582b62d79528b955919759f241e38eeeaec649300a96c7991512fdb2a410a7.jpg) \nFig. 1. (a, b) SEM images of the WTG samples; (c) EDS elemental maps of Ti, O, C, and W in the WTG sample. \n\nFor a better illustration of the microstructure, the $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite was characterized by TEM. Fig. 2(a) clearly shows that highly dispersed nanoparticles of $\\mathrm{TiO}_{2}$ and WO3 were deposited on the surface of the transparent and wrinkled $\\mathrm{rG}0$ nanosheets. The particle sizes were ca. $10\\ \\mathrm{nm}$ on average. Moreover, the $\\mathsf{W O}_{3}$ particles were tightly connected with the $\\mathrm{TiO}_{2}$ particles even after ultrasonication, which suggested the formation of a heterostructure interface instead of a simple physical mixture. In the HRTEM image (Fig. 2(b)), the lattice fringe spacings of 0.35 and $0.19\\mathrm{nm}$ corresponded to the (101) and (200) planes of the $\\mathrm{TiO}_{2}$ nanoparticles [40], whereas the lattice spacing of $0.27{\\mathrm{nm}}$ corresponded to the (022) planes of monoclinic $\\mathsf{W O}_{3},$ , which suggested that the ${\\sf W O}_{3}$ existed in the monoclinic form [10]. \n\nXRD (Fig. 3) was employed to investigate the phase structures of the samples. For the T sample, the characteristic diffraction peaks at 25.1°, $38.6^{\\circ}$ , $46.4^{\\circ}\\mathrm{~}$ and $55.1^{\\circ}$ well matched with those of anatase $(\\mathrm{JCPDS}\\oplus21{\\cdot}1272)$ ) [41]. The diffraction peaks of W indicated that WO3 crystallized in the monoclinic phase (JCPDS # 71-2141) [30]. For TG, WT, and WTG, the observed characteristic peaks could be attributed to anatase. No evidence of a tungsten oxide phase was found in the XRD patterns of WTG and WT. Besides, no peak shift was observed in the composites, compared with the case of pristine ${\\mathrm{TiO}}_{2},$ which suggested that the crystal structure of anatase was maintained. Similar broad diffraction peaks of the anatase phase were observed, which indicated small crystallite sizes. Monoclinic $\\boldsymbol{\\mathsf{W O3}}$ was not observed in the WTG and WT samples, because the amount of $\\mathsf{W O}_{3}$ was too low to be revealed by XRD. The amounts of $\\mathsf{W}$ element in WTG and WT were 6.52 and 6.58 $\\mathrm{wt\\%}$ , respectively, which were obtained by ICP analysis. According to a previous report, $\\mathsf{W O}_{3}$ is present in the form of highly dispersed nanocrystallites or clusters when its content is very low. At least $8\\mathrm{wt\\%}$ of ${\\sf W O}_{3}$ is necessary to cover the $\\mathrm{TiO}_{2}$ surface with a monolayer, the thickness of which can be determined by XRD [42–44]. Moreover, after the hydrothermal treatment, no characteristic diffraction peak of GO or graphene was found in the patterns of TG and WTG, which was ascribed to the low concentration and inherently low diffraction intensity of rGO relative to those of metallic oxides [45]. \n\n![](images/1c6b85a06a75dd291e0ee8751d7112a2947f5c019f6a8e3eb8a1b577aededaaa.jpg) \nFig. 2. TEM (a) and HRTEM (b) images of the WTG composite. \n\n![](images/42c1016cd3549d604688c31dc07c68e37fcb108ee21488e747f80353b430be86.jpg) \nFig. 3. XRD patterns of the T, W, TG, WT, and WTG samples. \n\nRaman spectra were recorded to verify the presence of C in the composites and reveal the significant structural change from GO to rGO after the hydrothermal reaction. In Fig. 4(a), the Raman spectrum of GO showed two typical peaks at approximately 1351 (D band) and $1586~\\mathrm{cm^{-1}}$ (G band), which were attributed to the breathing mode of the $\\mathbf{k}$ -point phonons of $\\boldsymbol{A}_{1\\mathrm{g}}$ symmetry and first-order scattering of the $E_{^{2\\mathrm{g}}}$ vibration mode of $s p^{2}$ -bonded C atoms [46], respectively. The D band moved to $1344~\\mathrm{cm}^{-1}$ for WTG, while the G band moved to 1600 $\\mathrm{cm}^{-1}$ for both TG and WTG (Fig. 4(b)), which indicated the reduction of GO and interaction between rGO and particles [47]. In comparison with that of pure GO, the $\\mathrm{D/G}$ intensity ratios $\\left({I_{\\mathrm{D}}}/{I_{\\mathrm{G}}}\\right)$ of WTG and TG apparently increased. The increase in $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ indicated that the size of the $s p^{2}$ domains within the plane decreased in terms of the average value, which further testified the transformation from GO to rGO [48,49]. For the T sample shown in Fig. 4(a), the several typical bands observed at 399, 518, and $640~\\mathrm{cm^{-1}}$ were ascribed to the $\\mathrm{B_{1g(1)},}$ $\\mathrm{A_{1g}+B_{1g(2)}}$ , and $\\operatorname{E}_{\\operatorname{g}(2)}$ modes of anatase, respectively. For W, the major Raman bands at 807 and $717\\ \\mathrm{cm}^{-1}$ were ascribed to W–O stretching modes, and the other two bands at 273 and $327~\\mathrm{cm}^{-1}$ corresponded to the W–O bending modes of bridging O, which are characteristic of monoclinic $\\mathsf{W O}_{3}$ [50]. Bands of anatase were observed in the spectra of the corresponding composites, whereas no traces of monoclinic ${\\sf W O}_{3}$ were found in the WT and WTG samples. The results reflected the fact that the signal of ${\\sf W O}_{3}$ is too weak relative to that of $\\mathrm{TiO}_{2}$ . Strikingly, in the $\\mathrm{TiO}_{2}$ composites, no shift in the main Raman scattering bands was found, compared with the case of pure $\\mathrm{TiO}_{2},$ , which was sensitive to the insertion of ions into the $\\mathrm{TiO}_{2}$ unit cell, suggesting that ion diffusion had not occurred in the composites [51]. \n\nXPS was employed to investigate the surface chemical states of the WTG composite photocatalysts. Fig. 5(a) shows that the XPS C 1s pattern of the $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite can be deconvoluted into four peaks at 284.8, 285.3, 286.6, and $289.1\\mathrm{eV}.$ which can be assigned to the surface adventitious C (C–C), epoxide and hydroxyl C (C–O), and carbonyl $\\scriptstyle(\\mathsf{C}=0)$ and carboxyl $_{(0-\\mathsf{C}=0)}$ groups, respectively [52]. The results testified to the existence of rGO. The O 1s XPS pattern (Fig. 5(b)) displayed three peaks at 530.3, 531.9, and $533.2~\\mathrm{eV}.$ , corresponding to lattice O (Ti–O, W–O), hydroxyl O (–OH), and the O of the C–O or $\\scriptstyle{\\mathsf{C}}=0$ bonds [53], respectively. Fig. 5(c) shows the high-resolution Ti $2p$ spectra of T, WTG, and WTG obtained under light irradiation that reveals two symmetrical peaks corresponding to Ti $2p_{3/2}$ and Ti $2p_{1/2}$ of ${\\mathrm{TiO}}_{2},$ respectively [54]. Notably, the binding energy of Ti $2p$ for WTG showed a positive shift, compared with that for pristine $\\mathrm{TiO}_{2},$ suggesting that electrons transferred from $\\mathrm{TiO}_{2}$ to rGO or ${\\sf W O}_{3}$ at the interfaces. \n\n![](images/63ec8a05aae98f75a56ba4cbb8e47d4a1681c64146044a782c6fec6dd07be37f.jpg) \nFig. 4. (a) Raman spectra of the T, WT, WTG, TG, GO, and W samples; (b) enlarged spectra of the GO, TG, and WTG samples in the range 1100–175 $\\mathbf{cm}^{-1}$ . \n\nIn the W $4f$ spectrum of $\\mathrm{\\Delta}\\mathsf{W}.$ , shown in Fig. 5(d), the main peaks at approximately 37.7 and $35.6~\\mathrm{eV}$ are observed, which result from $\\textsf{W}4f_{5/2}$ and $\\textsf{W}4f_{7/2}$ of $\\mathsf{W}^{6+}$ , respectively [55]. Two shoulder peaks assigned to $\\mathsf{W}^{5+}$ and centered at approximately 37.5 and $35.4~\\mathrm{eV}$ are also noticed [56]. The appearance of $\\mathsf{W}^{5+}$ implied the existence of O vacancies, which was in accordance with the UV-vis DRS. From the peak areas, we could roughly estimate that the ratio of $\\mathsf{W}^{5+}$ to $\\mathsf{W}^{6+}$ was 0.279:1. For the WTG sample, a well-resolved doublet at 36.6 $\\mathrm{~(W~}4f_{7/2})$ and $38.7~\\mathrm{eV}$ $(\\textsf{W}4f_{5/2})$ indicated the existence of the $\\mathsf{W}^{6+}$ species of stoichiometric ${\\sf W O}_{3}$ [57], which overlapped with Ti $3p$ at $37.6~\\mathrm{eV}$ [58]. Therefore, both $\\mathrm{TiO}_{2}$ and $\\boldsymbol{\\mathsf{W O3}}$ were successfully anchored on the $\\mathrm{rG}0$ nanosheets. As reported [56], the W $4f$ peaks of the composite shifted to higher binding energies, which confirmed the massive decrease in the number of unsaturated W ions. \n\n![](images/808bb3574bd7fa8dd755a2d59cebee3f9d525e0ab3bdbb9b0ebda810686c3933.jpg) \nFig. 5. High-resolution XPS patterns of C 1s (a) and O 1s (b) of WTG composites; (c) in situ and ex situ XPS patterns of Ti $2p$ of T and WTG samples; (d) high-resolution XPS patterns of W $4f$ of W and WTG samples. The in situ XPS patterns were recorded under light irradiation. \n\n![](images/36eac0e15ca6befcf7b21de81ce0d45e9fab07d717875255e919fd6181b31570.jpg) \nFig. 6. N2 adsorption-desorption isotherms and the corresponding pore size distribution curves (insets) of the $\\mathrm{\\DeltaT}$ and WT (a), and TG and WTG (b) samples. \n\n${\\sf N}_{2}$ adsorption-desorption measurements were conducted to characterize the specific surface areas and pore size distributions of the samples. In Fig. 6, the representative ${\\sf N}_{2}$ adsorption-desorption isotherms of T and WT (Fig. 6(a)), and TG and WTG (Fig. 6(b)), correspond to type IV, which indicate the existence of large mesopores and macropores. According to the International Union of Pure and Applied Chemistry classification, the isotherms of the T and WT samples exhibited an obvious H2-type hysteresis with ink-bottle mesopores that are derived from the aggregation of the $\\mathrm{TiO}_{2}$ and $\\mathsf{W O}_{3}$ nanoparticles. For the TG and WTG samples shown in Fig. 6(b), the isotherms exhibited a combination of H2 and H3 hysteresis loops, which were associated with the pores caused by the aggregated nanoparticles and the slit-shaped mesopores due to the stacking of the rGO sheets [59], respectively. Accordingly, the Barret-Joyner-Halenda pore size distributions (shown in the insets of Fig. 6(a) and (b)) displayed a relatively wide range, 2–100 nm, with a distinct peak at ca. $10\\mathrm{nm}$ , which coincided with the results of TEM analysis. In addition, the Brunauer-Emmett-Teller (BET) specific surface areas of WTG and TG (Table 2) were 165 and $160{\\mathrm{~m}}^{2}{\\mathrm{~g}}^{-1}$ , respectively, which were larger than those of the other two samples, indicating that the presence of graphene tended to boost the specific surface areas and provided abundant active sites for adsorption and surface reactions. \n\nUV-vis DRS were utilized to determine the optical absorption properties of the samples (Fig. 7). Obviously, pure $\\mathrm{TiO}_{2}$ exhibited an intrinsic absorbance edge at $388~\\mathrm{nm}$ , which was ascribed to its bandgap of $3.20~\\mathrm{eV}$ For the W sample, ${\\sf W O}_{3}$ revealed a large light absorption edge at $466~\\mathrm{{nm}}$ , corresponding to its inherently narrow bandgap of $2.66~\\mathrm{eV}$ . Interestingly, the absorption curve of ${\\sf W O}_{3}$ revealed a slight increase from 500 to $900\\mathrm{nm}.$ , which was a combined result of the excitation via the d $\\rightarrow{\\mathsf{d}}$ internal transitions of the W ions [60], polaron hopping [61], and the absorption induced by localized surface plasmon resonance [62]. In contrast with the commercial yellow-colored $\\mathsf{W O}_{3},$ the blue-green color of the tungsten oxide obtained in this work (inset of Fig. 7) proved that it existed partially in its sub-stoichiometric phases, which was associated with the defect levels introduced by O vacancies below the CB. The presence of O vacancies was beneficial for the photocatalytic reactions [63]. The $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}$ composite displayed increased absorption in the wavelength range corresponding to the UV, visible, and NIR regions, which was attributed to the intrinsic optical absorption of $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ with O vacancies. With the introduction of graphene, the TG and WTG samples extended their broad background absorption range to the visible-light region, because graphene not only decreased the optical reflection but also was associated with the electronic transitions $\\mathbf{n}\\rightarrow$ $\\uppi^{*}$ between the n-orbits of the O species and graphene and the $\\uppi\\rightarrow\\uppi^{*}$ of graphene [64]. Moreover, graphene can convert light to heat under optical irradiation, which accelerates the reaction. The photothermal conversion abilities of the samples were measured by using a thermos-imager. Fig. 8 exhibits the variations in the surface temperatures of the T, W, GO, and WTG samples. In fact, the surface temperatures of $\\mathrm{\\DeltaT}$ and W changed slightly under LED illumination $(365~\\mathrm{nm},~44.0~\\mathrm{mW}$ $\\mathrm{cm}^{-2}.$ ) for $20s.$ . Under the same conditions, the average temperatures of the GO and WTG surfaces increased by 9.1 and $4.5^{\\circ}\\mathrm{C},$ respectively. These results revealed the photothermal conversion characteristic of GO. \n\nTable 2 Texture properties of the prepared samples. \n\n\n
SampleABET (m² g-1)PV (cm3g-1)APS (nm)
T1540.318.1
TG1600.358.9
WT1450.267.2
WTG1650.307.3
\n\nABET: specific surface area; PV: pore volume; APS: average pore size. \n\n![](images/12e3c060d92b646407e3b28c734f48e78e509e86d91254df0f7f1211a57e8cbc.jpg) \nFig. 7. UV-vis DRS of the T, W, WT, TG, and WTG samples. The insets show the colors of the corresponding samples. \n\nElectron spin resonance (ESR) spectroscopy was employed to further monitor the presence and concentrations of O vacancies, as it is a pivotal tool that is used to examine unpaired spins in magnetism. Fig. 9 shows that the spectrum of ${\\sf W O}_{3}$ contains an asymmetric resonance signal (signal A), identified as that of $\\mathsf{W}^{5+}$ [65], and another signal (signal B) at the g-value of 1.9036, which was typical of O (paramagnetic O–) defects [66]. The pristine $\\mathrm{TiO}_{2}$ exhibited a weak, slightly anisotropic paramagnetic response that was centered at approximately $g=2.0027$ ; it resulted from the localized $\\mathrm{Ti^{3+}}3d^{1}$ states, which was consistent with the results of a previous study [67]. Notably, the spectrum of WT showed superparamagnetic behavior at $g=$ 2.0034. The slight increase in $g$ indicated interaction at the heterogeneous surface between $\\mathrm{TiO}_{2}$ and $\\mathsf{W O}_{3},$ which influenced the magnetic surroundings of the unpaired spins. Furthermore, the signal intensity was significantly enhanced, which reflected the increase in the concentration of O vacancies; this can be observed in the orange line of WT in the figure. The presence of O vacancies, which serve as shallow donors, is favorable for enhancing the electron density in n-type semiconductors and thus increasing the electrical conductivity. Moreover, they can improve the adsorption of surface species, making these composites attractive as photocatalytic materials [68]. \n\n![](images/3cde6a23b65e9dbde8596170158e87448c977dde02ae3730832a7f76fa522710.jpg) \nFig. 8. Device schematics and changes in the surface temperatures of (a–c) T, (d–f) W, $\\left(\\mathrm{g-i}\\right)$ GO, and $(\\mathrm{j-l})$ WTG samples under LED illumination $365\\mathrm{nm},$ , $44.0\\mathrm{{mW}c m^{-2}}.$ ) for $20s.$ . \n\n![](images/c152d9ad5454f716004f3f718f6304676bcfc3324921dad33d8927f9f6f188b2.jpg) \nFig. 9. ESR spectra of the T, W, and WT samples. \n\n# 3.2. Photocatalytic activity and stability \n\nThe performances of the photocatalysts in $\\mathrm{H}_{2}$ generation via water splitting were evaluated under irradiation with a Xe arc lamp. In the preliminary control experiments, we did not detect appreciable $\\mathrm{H}_{2}$ evolution in the absence of irradiation or photocatalysts, which suggested that $\\mathrm{H}_{2}$ was generated by photocatalysts through a series of reactions under irradiation. Fig. 10(a) shows that the W, G, and WG samples exhibit no $\\mathrm{H}_{2}$ generation activity, while pure $\\mathrm{TiO}_{2}$ displays a relatively low photocatalytic activity, attributable to the large recombination rate of the electrons in the CB and the holes in the VB. After combination with $1\\mathrm{wt\\%}$ graphene, the $\\mathrm{H}_{2}$ evolution activity of the TG sample increased, and was approximately 2.6-fold that of pure ${\\mathrm{TiO}}_{2},$ which was ascribed to the formation of a Schottky junction between $\\mathrm{TiO}_{2}$ and $\\boldsymbol{\\mathrm{rG}}0$ . The electrons in the $\\mathrm{TiO}_{2}$ CB tended to migrate to rGO, with a lower Fermi level and greater carrier mobility, which inhibited the recombination of the charge carriers. Furthermore, the presence of rGO as an ideal support for photocatalytic reactions offered numerous adsorption and catalytic sites, which extended the light absorption range to the visible region and even to the IR region and induced a positive photothermal effect. \n\nFor the WT sample, the $\\mathrm{H}_{2}$ yield rate was $105.2\\upmu\\mathrm{mol}\\ \\mathrm{g}^{-1}\\mathrm{h}^{-1},$ which was approximately 1.5 times that of pure $\\mathrm{TiO}_{2}$ . Hence, the improved photocatalytic activity can not only be attributed to the improved light harvesting, because WT displayed limited UV-visible light absorption. This finding might be attributed to the formation of the $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}$ S-scheme heterostructure, which expedited both the separation of useful electrons and holes and the recombination of relatively useless electrons and holes. Over the WTG composite, the $\\mathrm{H}_{2}$ evolution rate was greatly enhanced to $245.8\\ \\upmu\\mathrm{mol}\\ \\mathbf{g}^{-1}\\ \\mathbf{h}^{-1},$ , which was approximately 2.3 times that over WT. Further, the AQE of the WTG composite was measured as $1.4\\%$ at the wavelength of $365\\mathrm{nm}$ . The superior activity of WTG implied that rGO and the S-scheme heterojunction between ${\\sf W O}_{3}$ and $\\mathrm{TiO}_{2}$ had a positive synergistic effect that maximized the separation and transfer efficiency of the useful photogenerated electrons and holes. Fig. 10(c) shows the photocatalytic stability of the WTG sample, which was investigated over four consecutive cycles under the same conditions. Obviously, no remarkable deactivation was detected after four runs, indicating that the $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite displayed good stability. \n\n![](images/f1fced8877e6955807043d5a817ccd9a6f52efe93fd0984b5e794e6756286510.jpg) \nFig. 10. (a) Photocatalytic activities of the prepared samples; (b) the stability of the $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite. \n\n# 3.3. Electrochemical properties \n\nPhotoelectrochemical measurements were employed to investigate the migration of the photoinduced charge carriers. Fig. 11(a) and (b) shows that all five samples exhibit relatively settled photocurrent curves with several on-off runs under intermittent ultraviolet $(365\\mathrm{~nm})$ irradiation. The WTG sample showed remarkably increased photocurrent density, compared with those of the other four monocomponent and dual-component photocatalysts, which was consistent with the photocatalytic performances. This increase in the photocurrent indicated an enhancement in the photogenerated charge carrier separation efficiency due to the ${\\mathrm{TiO}_{2}}/{\\mathrm{W}}0_{3}$ S-scheme heterostructure in the presence of the highly conductive rGO for electron transfer. \n\n![](images/fb9f5737401bb88d43016477371148183b94eba91bb01665e9ecbe971bb211af.jpg) \nFig. 11. Photoelectrochemical characteristics of the prepared samples. (a) Transient photocurrent responses (at $365\\mathrm{nm}$ ) of the as-prepared samples; (b) enlarged graphs of the W and WT samples; (c) EIS Nyquist plots of the T, W, TG, WT, and WTG samples; and (d) enlarged graphs of the W, WT, and TG samples. \n\nIn addition, the photocurrent responses of the five samples revealed different characteristics. When light was turned off, the photocurrents of the T, W, and TG samples sharply dropped to zero. Afterwards, the photocurrent intensity of the W sample gradually increased even after the removal of irradiation, whereas those of the T and TG samples remained zero. By considering the change in the color of ${\\sf W O}_{3}$ to blue from yellow upon irradiation, we can deduce that electrons were released during reoxidation of $\\mathsf{W}^{6+}/\\mathsf{W}^{5+}$ , which was reported in previous work [69,70]. By contrast, the photocurrents of the WT and WTG samples slowly decreased to zero upon turning off the light, due to the reversible oxidation of $\\mathsf{W}^{5+}$ to $\\mathsf{W}^{6+}$ . \n\nThe charge transfer kinetics was further investigated by using EIS. Fig. 11(c) and (d) shows that the WTG sample displayed the smallest semicircle relative to those of the other samples, which suggested that the $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite exhibited the lowest interfacial electron-transfer resistance, which was beneficial for improving the separation and migration rates of the photoinduced charge carriers. \n\n# 3.4. Photocatalytic mechanism \n\nThe Mott-Schottky plots were analyzed to ascertain the band structures of the $\\mathrm{~T~}$ and $\\mathsf{W}$ samples. In Fig. 12, the Mott-Schottky plots of $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ exhibited positive slopes at $1000\\ \\mathrm{Hz},$ which was typically characteristic of an n-type semiconductor. From the $\\mathbf{x}$ -intercepts, the extrapolated flat-band potentials of $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ were obtained as $-0.84$ and $-0.50\\mathrm{~V~}$ versus the saturated $\\mathrm{\\Ag/AgCl}$ reference electrode $\\mathrm{(pH=7)}$ ), respectively. \n\nWith reference to the Mott-Schottky plots, the flat-band potentials of $\\mathrm{TiO}_{2}$ and $\\boldsymbol{\\mathsf{W O3}}$ can be calculated according to the following conversion formula: \n\n$E(\\mathrm{RHE})=E(\\mathrm{Ag}/\\mathrm{AgCl})+E^{\\uptheta}+0.059\\:\\mathrm{pH}$ (2) where $E^{\\boldsymbol{\\Theta}}\\left({\\mathrm{Ag}}/{\\mathrm{AgCl}}\\right)=0.197{\\mathrm{~V}},$ and the flat-band potentials of $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ were $-0.23$ and $0.11\\mathrm{V}$ (vs. RHE, $\\mathrm{\\boldmath~\\pH}=0\\dot{\\mathrm{\\boldmath~\\sigma~}}$ ), respectively. It was speculated that the bandgaps of $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ were approximately 3.2 and $2.6~\\mathrm{eV}$ , based on the UV-vis DRS. Both the CB and VB energy levels of $\\mathrm{TiO}_{2}$ were higher than those of ${\\sf W O}_{3}$ . The redox potential of graphene/graphene•- was –0.08 V [71]. \n\nThermodynamically, the CB electrons of ${\\sf W O}_{3}$ and the internal electrons of rGO cannot participate in the photocatalytic $\\mathrm{H}_{2}$ -production reactions. Interestingly, the $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}/\\mathrm{rG}0$ composite exhibited 3.5-fold $\\mathrm{H}_{2}$ evolution activity compared to that of pure $\\mathrm{TiO}_{2}$ . If the charge carriers of the WTG sample are transferred in accordance with the traditional type-II model, the electrons in the CB of $\\mathrm{TiO}_{2}$ would migrate to the CB of ${\\sf W O}_{3}$ with decreased reduction ability, while the holes in the VB of $\\mathsf{W O}_{3}$ would migrate to the VB of $\\mathrm{TiO}_{2}$ with decreased oxidization ability, under illumination. However, transfer of the electrons accumulated in the CB of WO3 to rGO would be thermodynamically unfavorable and retard the continual charge transfer from the CB of TiO2. In this case, the WTG composite would show almost no photocatalytic $\\mathrm{H}_{2}$ -production activity, which is distinctly opposite to the result obtained experimentally. \n\nThe TEM and XPS analyses showed that the S-scheme heterojunction was formed at the interface between $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ in the WTG and WT samples. The work function of $\\mathsf{W O}_{3}$ is greater than that of ${\\mathrm{TiO}}_{2},$ and the difference drives the charge transfer from $\\mathrm{TiO}_{2}$ to $\\mathsf{W O}_{3}$ upon contact until the Fermi levels equilibrate [72]. Consequently, a built-in electric field can be formed at the heterogeneous interface that is directed from $\\mathrm{TiO}_{2}$ to $\\mathsf{W O}_{3}$ that favors the transfer and separation of the photogenerated charge carriers. In light of the S-scheme mechanism (Fig. 13), under optical irradiation, the relatively useless photoinduced electrons in the CB of ${\\sf W O}_{3}$ will migrate to the VB of $\\mathrm{TiO}_{2}$ via the intimate interface and recombine with the relatively useless holes under the driving force of the built-in electronic field. This process expedites the separation of the relatively useful electrons in the CB of $\\mathrm{TiO}_{2}$ and the holes in the VB of ${\\sf W O}_{3}$ and maintains their high reduction and oxidation abilities, respectively. Furthermore, the electrons collected in the CB of $\\mathrm{TiO}_{2}$ are prone to migration to the surface of rGO via the \n\n![](images/f14ae35739af7cd65250d73a49be64b52f9055bc78b89b8ca8156f9e2ec03097.jpg) \nFig. 12. Mott-Schottky plots of W (a) and T (b) samples. \n\n![](images/390456d115871f0ee260dfdde78e540a799ed37177ff08d4dd69cfd0cd4311d9.jpg) \nFig. 13. Schematic illustration of the S-scheme heterojunction-based charge transfer mechanism in $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite. \n\nSchottky junction owing to their 2D $\\uppi$ -conjugation structure and relatively lower potential than the CB of ${\\mathrm{TiO}}_{2},$ which facilitates free flow along the conductive network. The process further facilitates the migration of electrons, thus avoiding the accumulated electrons in the CB of TiO2 from retarding the continual photocatalytic excitation of electron from the VB of $\\mathrm{TiO}_{2}$ in the S-scheme heterojunction system. As for the in situ XPS pattern of Ti $2p$ of the WTG sample, the binding energy of Ti $2p$ under light irradiation exhibited a slight shift relative to that measured in darkness, which was a result of the combination of the S-scheme heterojunction and the Schottky junction, where electrons migrated from ${\\sf W O}_{3}$ across $\\mathrm{TiO}_{2}$ to rGO. From a macroscopic viewpoint, the transfer of photogenerated electrons occurs like a “step,” with $\\mathrm{TiO}_{2}$ acting as a “bridge”. \n\nIn summary, in the ternary $\\mathrm{WO_{3}/T i O_{2}/r G0}$ composite system, the cross-coupling effect of rGO and the S-scheme heterojunction formed between $\\mathrm{TiO}_{2}$ and $\\mathsf{W O}_{3}$ suppresses the recombination of comparatively useful carriers and provides a variety of potential pathways for charge carrier transfer. In addition, the use of rGO as a supporting matrix can provide more surface-active sites and enhance the light absorption. The collective and positive synergy of $\\boldsymbol{\\mathrm{rG0}}$ and the S-scheme heterojunction formed between $\\mathrm{TiO}_{2}$ and ${\\sf W O}_{3}$ results in a large driving force for the photocatalytic reaction, which increases the water-splitting $\\mathrm{H}_{2}$ -evolution activity. \n\n# 4. Conclusions \n\nWe successfully fabricated a graphene-modified $\\mathsf{W O}_{3}/\\mathrm{TiO}_{2}$ S-scheme heterojunction photocatalyst. The WTG composite was prepared by a facile one-step hydrothermal approach, and exhibited superior photocatalytic activity for $\\mathrm{H}_{2}$ production through water splitting, which was 3.5-fold that of bare $\\mathrm{TiO}_{2}$ under the same conditions. It was observed that the positive cooperative effect between the S-scheme heterojunction formed between WO3 and $\\mathrm{TiO}_{2}$ and the Schottky heterojunction formed between $\\mathrm{TiO}_{2}$ and graphene sheets could effectively suppress the recombination of useful carriers, enhance the light harvest, and increase the number of active sites for the reduction reaction. This work provides new insights for the design and fabrication of novel S-scheme heterojunction photocatalysts and highlights the potential of utilizing the unique properties of rGO to design inexpensive, active photocatalysts with durability and stability for $\\mathrm{H}_{2}$ production. \n\n# References \n\n[1] W. Yu, D. Xu, T. Peng, J. Mater. Chem. A, 2015, 3, 19936–19947. \n[2] J. Fu, J. Yu, C. Jiang, B. Cheng, Adv. Energy Mater., 2018, 8, 1701503. \n[3] Q. Xu, L. Zhang, J. Yu, S. Wageh, A. A. Al-Ghamdi, M. Jaroniec, Mater. Today, 2018, 21, 1042–1063. \n[4] M. Tapajna, R. Stoklas, D. Gregusova, F. Gucmann, K. Husekova, S. Hascik, K. Frohlich, L. Toth, B. Pecz, F. Brunner, J. Kuzmik, Appl. Surf. Sci., 2017, 426, 656–661. \n[5] F. Ye, H. F. Li, H. T. Yu, S. Chen, X. Quan, Appl. Surf. Sci., 2017, 426, 177–184. \n[6] R. Shen, J. Xie, Q. Xiang, X. Chen, J. Jiang, X. Li, Chin. J. Catal., 2019, 40, 240–288. \n[7] D. C. Sun, W. Y. Yang, L. Zhou, W. Z. Sun, Q. Li, J. K. Shang, Appl. Catal. B, 2016, 182, 85–93. \n[8] A. Y. Meng, B. C. Zhu, B. Zhong, L. Y. Zhang, B. Cheng, Appl. Surf. Sci., 2017, 422, 518–527. \n[9] T. Di, Q. Xu, W. Ho, H. Tang, Q. Xiang, J. Yu, ChemCatChem, 2019, 11, 1394–1411. \n[10] W. Yu, J. Chen, T. Shang, L. Chen, L. Gu, T. Peng, Appl. Catal. B, 2017, 219, 693–704. \n\n# Graphical Abstract \n\nChin. J. Catal., 2020, 41: 9–20 doi: S1872-2067(19)63382-6 \n\n# Enhanced photocatalytic $\\mathbf{H}_{2}$ -production activity of ${\\bf W O3/T i O_{2}}$ step-scheme heterojunction by graphene modification \n\nFei He, Aiyun Meng, Bei Cheng, Wingkei Ho \\*, Jiaguo Yu ,\\* Wuhan University of Technology, China; The Education University of Hong Kong, China; King Abdulaziz University, Saudi Arabia \n\n$\\mathrm{WO_{3}/T i O_{2}}$ S-scheme heterojunction photocatalysts modified by graphene (WTG) exhibited remarkably enhanced photocatalytic $\\mathrm{H}_{2}$ -production activities. \n\n![](images/640fc14457d7215cdccb99219c5817d84a5aebfc7a0031fda5d7f3ccbedd1830.jpg) \n\n[11] Fu, Z Li, Q. Liu, Yang, H. Tang, Chinese J. Catal., 2017, 38, 2160–2170. \n[12] S. Meng, X. Ning, T. Zhang, S. F. Chen, X. Fu, Phys. Chem. Chem. Phys., 2015, 17, 11577–11585. \n[13] F. C. Romeiro, M. A. Rodrigues, L. A. J. Silva, A. C. Catto, L. F. da Silva, E. Longo, E. Nossol, R. C. Lima, Appl. Surf. Sci., 2017, 423, 743–751. \n[14] S. Wang, B. Zhu, M. Liu, L. Zhang, J. Yu, M. Zhou, Appl. Catal. B, 2019, 243, 19–26. \n[15] J. Low, B. Cheng, J. Yu, Appl. Surf. Sci., 2017, 392, 658–686. \n[16] Y. Li, F. T. Liu, Y. Chang, J. Wang, C. W. Wang, Appl. Surf. Sci., 2017, 426, 770–780. \n[17] Z. Wang, T. Hu, K. Dai, J. Zhang, C. Liang, Chin. J. Catal., 2017, 38, 2021–2029. \n[18] W. L. Dai, J. J. Yu, Y. Q. Deng, X. Hu, T. Y. Wang, X. B. Luo, Appl. Surf. Sci., 2017, 403, 230–239. \n[19] Y. K. Sohn, W. X. Huang, F. Taghipour, Appl. Surf. Sci., 2017, 396, 1696–1711. \n[20] X. Ma, Q. Xiang, Y. Liao, T. Wen, H. Zhang, Appl. Surf. Sci., 2018, 457, 846–855. \n[21] F. Y. Xu, Y. Le, B. Cheng, C. J. Jiang, Appl. Surf. Sci., 2017, 426, 333–341. \n[22] J. Li, Y. Peng, X. H. Qian, J. Lin, Appl. Surf. Sci., 2018, 452, 437–442. \n[23] K. Qi, B. Cheng, J. Yu, W. Ho, Chin. J. Catal., 2017, 38, 1936–1955. \n[24] W. Yu, S. Zhang, J. Chen, P. Xia, M. H. Richter, L. Chen, W. Xu, J. Jin, S. Chen, T. Peng, J. Mater. Chem. A, 2018, 6, 15668–15674. \n[25] J. Xu, J. Yue, J. Niu, M. Chen, F. Teng, Chin. J. Catal., 2018, 39, 1910–1918. \n[26] J. Wang, Z. Zhang, X. Wang, Y. Shen, Y. Guo, P. K. Wong, R. Bai, Chin. J. Catal., 2018, 39, 1792–1803. \n[27] J. Fu, Q. Xu, J. Low, C. Jiang, J. Yu, Appl. Catal. B, 2019, 243, 556–565. \n[28] J. Jin, J. Yu, D. Guo, C. Cui, W. Ho, Small, 2015, 11, 5262–5271. \n[29] Y. P. Xie, G. Liu, L. Yin, H. M. Cheng, J. Mater. Chem., 2012, 22, 6746–6751. \n[30] L. Jiang, X. Yuan, G. Zeng, J. Liang, X. Chen, H. Yu, H. Wang, Z. Wu, J. Zhang, T. Xiong, Appl. Catal. B, 2018, 227, 376–385. \n[31] D. Spanu, S. Recchia, S. Mohajernia, P. Schmuki, M. Altomare, Appl. Catal. B, 2018, 237, 198–205. \n[32] H. Q. Gao, P. Zhang, J. H. Hu, J. M. Pan, J. J. Fan, G.S. Shao, Appl. Surf. Sci., 2017, 391, 211–217. \n[33] J. K. Mu, C. Y. Hou, G. Wang, X. M. Wang, Q. H. Zhang, Y. G. Li, H. Z. Wang, M. F. Zhu, Adv. Mater., 2016, 28, 9491–9497. \n[34] X. Li, J. Yu, M. Jaroniec, X. Chen, Chem. Rev., 2019, 119, 3962–4179. \n[35] S. Kumar, N. L. Reddy, H. S. Kushwaha, A. Kumar, M. V. Shankar, K. Bhattacharyya, A. Halder, V. Krishnan, ChemSusChem, 2017, 10, 3588–3603. \n[36] A. Meng, L. Zhang, B. Cheng, J. Yu, ACS Appl. Mater. Interfaces, 2019, 11, 5581–5589. \n[37] H. Zhao, S. N. Sun, Y. Wu, P. P. Jiang, Y. M. Dong, Z. C. J. Xu, Carbon, 2017, 119, 56–61. \n[38] Y. Lu, X. Cheng, G. Tian, H. Zhao, L. He, J. Hu, S.-M. Wu, Y. Dong, G.-G. Chang, S. Lenaerts, S. Siffert, G. Van Tendeloo, Z.-F. Li, L.-L. Xu, X.-Y. Yang, B.-L. Su, Nano Energy, 2018, 47, 8–17. \n[39] H. Zou, B. He, P. Kuang, J. Yu, K. Fan, Adv. Funct. Mater., 2018, 28, 1706917. \n[40] L. Pan, J. Zhang, X. Jia, Y.-H. Ma, X. Zhang, L. Wang, J.-J. Zou, Chin. J. Catal., 2017, 38, 253–259. \n[41] B. Li, B. Xi, Z. Feng, Y. Lin, J. Liu, J. Feng, Y. Qian, S. Xiong, Adv. Mater., 2018, 30, 1705788. \n[42] B. Gao, Y. Ma, Y. Cao, W. Yang, J. Yao, J. Phys. Chem. B, 2006, 110, 14391–14397. \n[43] K. K. Akurati, A. Vital, J. P. Dellemann, K. Michalow, T. Graule, D. Fetti, A. Baiker, Appl. Catal. B, 2008, 79, 53–62. \n[44] A. Gutierrez-Alejandre, J. Ramirez, G. Busca, Langmuir, 1998, 14, 630–639. \n[45] X. Li, J. G. Yu, S. Wageh, A. A. Al-Ghamdi, J. Xie, Small, 2016, 12, 6640–6696. \n[46] D. Xu, L. Li, R. He, L. Qi, L. Zhang, B. Cheng, Appl. Surf. Sci., 2018, 434, 620–625. \n[47] Q. Xiang, J. Yu, M. Jaroniec, J. Am. Chem. Soc., 2012, 134, 6575–6578. \n[48] A. Kumar, L. Rout, L. S. K. Achary, A. Mohanty, R. S. Dhaka, P. Dash, RSC Adv., 2016, 6, 32074–32088. \n[49] A. H. Mady, M. L. Baynosa, D. Tuma, J. J. Shim, Appl. Catal. B, 2017, 203, 416–427. \n[50] H. Khan, M.G. Rigamonti, G.S. Patience, D.C. Boffito, Appl. Catal. B, 2018, 226, 311–323. \n[51] C. Sotelo-Vazquez, R. Quesada-Cabrera, M. Ling, D. O. Scanlon, A. Kafizas, P. K. Thakur, T. L. Lee, A. Taylor, G. W. Watson, R. G. Palgrave, J. R. Durrant, C. S. Blackman, I. P. Parkin, Adv. Funct. Mater., 2017, 27, 1605413. \n[52] J. Yu, J. Jin, B. Cheng, M. Jaroniec, J. Mater. Chem. A, 2014, 2, 3407–3416. \n[53] J. H. Pan, W.I. Lee, Chem. Mater., 2006, 18, 847–853. \n[54] F. Xu, J. Zhang, B. Zhu, J. Yu, J. Xu, Appl. Catal. B, 2018, 230, 194–202. \n[55] X. Zhou, X. Zheng, B. Yan, T. Xu, Q. Xu, Appl. Surf. Sci., 2017, 400, 57–63. \n[56] Q. Liu, F. Wang, H. Lin, Y. Xie, N. Tong, J. Lin, X. Zhang, Z. Zhang, X. Wang, Catal. Sci. Technol., 2018, 8, 4399–4406. \n[57] M. Seifollahi Bazarjani, M. Hojamberdiev, K. Morita, G. Zhu, G. Cherkashinin, C. Fasel, T. Herrmann, H. Breitzke, A. Gurlo, R. Riedel, J. Am. Chem. Soc., 2013, 135, 4467–4475. \n[58] M. Karbalaei Akbari, Z. Hai, Z. Wei, C. Detavernier, E. Solano, F. Verpoort, S. Zhuiykov, ACS Appl. Mater. Interfaces, 2018, 10, 10304–10314. \n[59] M. Thommes, K. Kaneko, A. V. Neimark, J. P. Olivier, F. Rodriguez-Reinoso, J. Rouquerol, K. S. W. Sing, Pure Appl. Chem., 2015, 87, 1051–1069. \n[60] K. He, J. Xie, X. Luo, J. Wen, S. Ma, X. Li, Y. Fang, X. Zhang, Chinese J. Catal., 2017, 38, 240–252. \n[61] S. K. Deb, Sol. Energy Mater. Sol. Cells, 2008, 92, 245–258. \n[62] S. Cong, F. Geng, Z. Zhao, Adv. Mater., 2016, 28, 10518–10528. \n[63] L. Liu, Y. Jiang, H. Zhao, J. Chen, J. Cheng, K. Yang, Y. Li, ACS Catal., 2016, 6, 1097–1108. \n[64] J. Low, B. Cheng, J. Yu, M. Jaroniec, Energy Storage Mater., 2016, 3, 24–35. \n[65] P. Srinivasa Rao, S. Bala Murali Krishna, S. Yusub, P. Ramesh Babu, C. Tirupataiah, D. Krishna Rao, J. Mol. Struct., 2013, 1036, 452–463. \n[66] N. Zhang, X. Li, Y. Liu, R. Long, M. Li, S. Chen, Z. Qi, C. Wang, L. Song, J. Jiang, Y. Xiong, Small, 2017, 13, 1701354. \n[67] Z. Wang, C. Yang, T. Lin, H. Yin, P. Chen, D. Wan, F. Xu, F. Huang, J. Lin, X. Xie, M. Jiang, Adv. Funct. Mater., 2013, 23, 5444–5450. \n[68] Z.-F. Huang, J. Song, L. Pan, X. Zhang, L. Wang, J. J. Zou, Adv. Mater., 2015, 27, 5309–5327. \n[69] Z. He, J. Fu, B. Cheng, J. Yu, S. Cao, Appl. Catal. B, 2017, 205, 104–111. \n[70] J. Fu, C. Bie, B. Cheng, C. Jiang, J. Yu, ACS Sustain. Chem. Eng., 2018, 6, 2767–2779. \n[71] J. Low, J. Yu, W. Ho, J. Phys. Chem. Lett., 2015, 6, 4244–4251. \n[72] J. Low, B. Dai, T. Tong, C. Jiang, J. Yu, Adv. Mater., 2019, 31, 1802981. \n\n# 石墨烯修饰三氧化钨/二氧化钛S型异质结增强的光催化产氢活性 \n\n何 菲a, 孟爱云a, 程 蓓a, Wingkei Ho b,#, 余家国a,c,\\*a武汉理工大学材料复合新技术国家重点实验室, 材料科学与工程国际化示范学院, 湖北武汉430070,中国b香港教育大学科学与环境学系, 海洋污染国家重点实验室, 香港, 中国c沙特阿卜杜勒阿齐兹国王大学科学部物理系, 吉达21589, 沙特阿拉伯 \n\n摘要: 太阳光驱动的光催化分解水产氢是利用太阳能解决当前能源危机和环境问题的理想策略. 二氧化钛由于其稳定、环境友好和成本低等优点受到广泛研究, 在光催化领域具有不可或缺的作用. 然而, 纯二氧化钛光催化剂具有光生电子-空穴复合率高、太阳能利用率低等缺点, 使其在光催化产氢领域的应用受到限制. 迄今为止, 人们探索了多种改性策略来提高二氧化钛的光催化活性, 如贵金属负载、金属或非金属元素掺杂、构建异质结等. \n\n通过复合两个具有合适能带排布的半导体来构建异质结可以大大提高光生载流子的分离, 被认为是一种有效的解决方案. 最近提出了一种新的S型异质结概念, 以解释不同半导体异质界面载流子转移分离的问题. S型异质结是在传统Ⅱ型和Z型(液相Z型、全固态Z型、间接Z型、直接Z型)基础上提出的, 但又扬长避短, 优于传统Ⅱ型和Z型. 通常, S型异质结是由功函数较小、费米能级较高的还原型半导体光催化剂和功函数较大、费米能级较低的氧化型半导体光催化剂构建而成.三氧化钨禁带宽度较小 $(2.4{-}2.8\\ \\mathrm{\\eV})$ , 功函数较大, 是典型的氧化型光催化剂, 也是构建S型异质结的理想半导体光催化剂.根据S型电荷转移机制, 三氧化钨/二氧化钛复合物在光辐照下, 三氧化钨导带上相对无用的电子与二氧化钛价带上相对无用的空穴复合, 二氧化钛导带上还原能力较强的电子和三氧化钨价带上氧化能力较强的空穴得以保留, 从而在异质界面上实现了氧化还原能力较强的光生电子-空穴对的分离. 同时, 石墨烯作为一种蜂窝状碳原子二维材料, 是理想的电子受体,在异质结光催化剂中能及时转移电子. 而且, 石墨烯具有较好的导热性和电子迁移率, 光吸收强, 比表面积大, 可为光催化反应提供丰富的吸附和活性位点, 已经被认为是一种重要催化剂载体和光电分解水产氢的有效共催化剂. \n\n本文采用简便的一步水热法制备石墨烯修饰的三氧化钨/二氧化钛S型异质结光催化剂. 光催化产氢性能测试表明, 三氧化钨/二氧化钛/石墨烯复合材料的光催化产氢速率显著提高 $(245.8~\\upmu\\mathrm{mol}~\\mathrm{g}^{-1}~\\mathrm{h}^{-1})$ , 约为纯 $\\mathrm{TiO}_{2}$ 的3.5倍. 高分辨透射电子显微镜、拉曼光谱和X射线光电子能谱结果证明了 $\\mathrm{TiO}_{2}$ 和 $\\mathrm{WO}_{3}$ 纳米颗粒的紧密接触, 并成功负载在还原氧化石墨烯(rGO)上.X射线光电子能谱中Ti $2p$ 结合能的增加证实 $\\mathrm{TiO}_{2}$ 和 $\\mathrm{WO}_{3}$ 之间强的相互作用和S型异质结的形成. 此外, 复合材料中的rGO大大拓展了复合物的光吸收范围(紫外-可见漫反射光谱), 增强了光热转换效应, 而且rGO与TiO2之间形成肖特基结, 促进了$\\mathrm{TiO}_{2}$ 导带电子的转移和分离. 总之, $\\mathrm{WO}_{3}$ 和 $\\mathrm{TiO}_{2}$ 的S型异质结与 $\\mathrm{TiO}_{2}$ 和rGO之间的肖特基异质结的协同效应抑制了相对有用的电子和空穴的复合, 有利于氧化还原能力较强的载流子的分离和进一步转移, 加速了表面产氢动力学, 于是增强了三元复合光催化剂的光催化产氢活性. \n\n关键词: 像梯形的异质结; S型异质结; S异质结; 光催化剂; 光解水产氢 \n\n收稿日期: 2019-02-28. 接受日期: 2019-04-16. 出版日期: 2020-01-05. \n\\*通讯联系人. 电话: (027)87871029; 传真: (027)87879468; 电子信箱: jiaguoyu@yahoo.com \n#通讯联系人. 电子信箱: keithho@eduhk.hk \n基金来源: 国家自然科学基金(U1705251, 21871217, 21573170,21433007); 国家重点研发计划项目 (2018YFB1502001).本文的电子版全文由Elsevier出版社在ScienceDirect上出版(http://www.sciencedirect.com/science/journal/18722067). " + }, + { + "id": "10.1093_nsr_nwz137", + "DOI": "10.1093/nsr/nwz137", + "DOI Link": "http://dx.doi.org/10.1093/nsr/nwz137", + "Relative Dir Path": "mds/10.1093_nsr_nwz137", + "Article Title": "A highly alkaline-stable metal oxide@metal-organic framework composite for high-performance electrochemical energy storage", + "Authors": "Zheng, SS; Li, Q; Xue, HG; Pang, H; Xu, Q", + "Source Title": "NATIONAL SCIENCE REVIEW", + "Abstract": "Most metal-organic frameworks (MOFs) hardly maintain their physical and chemical properties after exposure to alkaline aqueous solutions, thus precluding their use as potential electrode materials for electrochemical energy storage devices. Here, we present the design and synthesis of a highly alkaline-stable metal oxide@MOF composite, Co3O4 nullocube@Co-MOF (Co3O4@Co-MOF), via a controllable and facile one-pot hydrothermal method under highly alkaline conditions. The obtained composite possesses exceptional alkaline stability, retaining its original structure in 3.0 M KOH for at least 15 days. Benefitting from the exceptional alkaline stability, unique structure, and larger surface area, the Co3O4@Co-MOF composite shows a specific capacitance as high as 1020 F g(-1) at 0.5 A g(-1) and a high cycling stability with only 3.3% decay after 5000 cycles at 5 A g(-1). The as-constructed solid-state flexible device exhibits a maximum energy density of 21.6 mWh cm(-3).", + "Times Cited, WoS Core": 541, + "Times Cited, All Databases": 555, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000528014900011", + "Markdown": "# RESEARCH ARTICLE \n\n# MATERIALS SCIENCE \n\n# A highly alkaline-stable metal oxide $@$ metal-organic framework composite for high-performance electrochemical energy storage \n\nShasha Zheng,1 Qing Li,1 Huaiguo Xue,1 Huan Pang,1,\\* Qiang Xu1,2,\\* \n\n1School of Chemistry and Chemical Engineering, and Institute for Innovative Materials and Energy, Yangzhou University, Yangzhou 225009, China. \n2AIST-Kyoto University Chemical Energy Materials Open Innovation Laboratory (ChEMOIL), National Institute of Advanced Industrial Science and Technology (AIST), Kyoto 606- 8501, Japan. \n\nE-mails: huanpangchem@hotmail.com ; panghuan@yzu.edu.cn ; q.xu@aist.go.jp ; qxuchem@yzu.edu.cn \n\n# ABSTRACT \n\nMost of metal-organic frameworks (MOFs) hardly maintain their physical and chemical properties after exposure to alkaline aqueous solutions, thus precluding their use as potential electrode materials for electrochemical energy storage devices. Here, we present the design and synthesis of a highly alkaline-stable metal oxide@MOF composite, $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocube@Co-MOF $(\\mathbf{C}\\mathbf{o}_{3}\\mathbf{O}_{4}@\\mathbf{C}\\mathbf{o}\\mathbf{-}\\mathbf{M}\\mathbf{O}\\mathbf{F})$ , via a controllable and facile one-pot hydrothermal method under a highly alkaline condition. The obtained composite possesses exceptional alkaline stability, retaining its original structure in 3.0 M KOH for at least 15 days. Benefiting from the exceptional alkaline stability, unique structure, and larger surface area, the Co3O4@Co-MOF composite shows a specific capacitance as high as $1020\\mathrm{~F~g}^{-1}$ at $0.5\\mathrm{~A~g^{-1}}$ and a high cycling stability with only $3.3\\%$ decay after 5000 cycles at $5\\mathrm{~A~g~}^{-1}$ . The asconstructed solid-state flexible device exhibits a maximum energy density of $21.6\\mathrm{mWh}\\mathrm{cm}^{-3}$ . \n\nKeywords: metal-organic framework, metal oxide, composite, electrochemical energy storage, flexible supercapacitor \n\n# INTRODUCTION \n\nMetal-organic frameworks (MOFs) are formed via self-assembly of metal ions and organic linkers [1–3]. Due to their superior properties, such as their large surface area, high porosity and structure tunability, MOFs have recently emerged as one type of important porous materials and have attracted intense interest in many fields, such as gas storage and separation [4–7], catalysis [8–11], and energy storage [12–15]. Nevertheless, MOFs still have a few weak points, which impede the use of their full potential to a great extent. For example, most of MOFs manifest inferior properties for electrical conduction and have limited chemical stability (in water, especially alkaline conditions), preventing them from exhibiting their best performance in the field of electrochemistry [16–19]. Fortunately, hybriding MOFs with a variety of functional materials to generate MOF composites can integrate the merits and mitigate the shortcomings of both parent materials [20–23]. \n\nMetal oxide nanomaterials with controllable shape, size, crystallinity and functionality are widely applied in many fields [24–27]. Because of their high theoretical specific capacitance, low cost, and great reversibility, they are considered ideal pseudocapacitive electrode materials, but they have high surface energies and are prone to aggregation, leading to loss of the pseudocapacitive performance [28–30]. In addition, metal oxides usually display only small surface areas, which has largely restricted the use of metal oxides as electrode materials for electrochemical energy storage [31,32]. Consequently, finding a costeffective method to increase the specific surface areas of metal oxides is crucial for achieving high pseudocapacitive activity. \n\nHere, we report a strategy to integrate the advantages of both metal oxides and MOFs by hybriding metal oxides with MOFs having large surface areas, in which each component retains its own identity while contributing extraordinary characteristics to the whole system [33,34]. MOFs with high surface areas provide appropriate spaces for the electrochemical reaction and intercalation/de-intercalation of cations (e.g., ${\\mathrm{Li}}^{+}$ $\\mathrm{{i}^{+},\\mathrm{{Na}^{+},\\mathrm{{K}^{+}}}}$ , and $\\boldsymbol{\\mathrm{H}}^{+}$ ) during energy storage processes [13,35,36], while the presence of metal oxides effectively increases redox active sites [37–39]. We have successfully synthesized Co-MOF sheet (Co-MOF, $\\mathrm{Co_{2}(p t c d a)}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O}_{\\cdot}$ , ptcda=perylene-3,4,9,10-tetracarboxylic dianhydride) through a simple one-pot hydrothermal method from the coordination of ptcda and ${\\mathrm{Co}}^{2+}$ . Interestingly, $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocubes grow on the surface of Co-MOF sheet, forming the $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF composite at $\\mathrm{pH}{=}11{-}13$ , which shows exceptional alkaline stability in 3.0 M KOH. Using the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}-$ MOF composite as electrode for a supercapacitor, the specific capacitance reaches $1020\\mathrm{F~g}^{-1}$ at $0.5\\mathrm{Ag}^{-1}$ in 3.0 M KOH. It shows a high rate capability with more than $96.7\\%$ capacitance retention even at $5\\mathrm{Ag}^{-1}$ . In addition, an aqueous/solid-state flexible electrochemical capacitor energy storage device has been successfully fabricated using $\\mathbf{C}_{0_{3}}\\mathbf{O}_{4}@\\mathbf{C}_{0}$ -MOF and activated carbon (AC), which displays high capacity and excellent cycling stability. \n\n# RESULTS AND DISCUSSION \n\nThe $\\mathrm{Co_{3}O_{4}@C o-M O F}$ composite was synthesized through a one-pot solvothermal method (Figure 1). The reaction of ptcda $(\\mathbf{C}_{24}\\mathrm{H}_{8}\\mathbf{O}_{6})$ and cobalt acetate tetrahydrate $(\\mathrm{Co(CH_{3}C O O)_{2}\\cdot4H_{2}O)\\ (C_{24}H_{8}O_{6}:C o(C H_{3}C O O)_{2}\\cdot4H_{2}O=1:1)}$ in water at $100~^{\\mathrm{{o}}}\\mathrm{{C}}$ for $12\\mathrm{~h~}$ with a $\\mathrm{C_{24}H_{8}O_{6}\\ensuremath{\\mathrm{~:~}}N a O H}$ ratio of $1:4$ affords leaf-like Co-MOF sheet (Co-MOF, $\\mathrm{Co_{2}C_{24}H_{8}O_{6}(O H)_{4},\\ \\sim5\\ \\mu m}$ in width and $8~{\\upmu\\mathrm{m}}$ in length), which has been confirmed by scanning electron microscopy (SEM) measurements (see Supplementary Figure S1c,d). Keeping the amount of $\\mathrm{C_{24}H_{8}O_{6}}$ and $\\mathrm{Co(CH_{3}C O O)_{2}{\\cdot}4H_{2}O}$ unchanged, a decrease in the $\\mathrm{C}_{24}\\mathrm{H}_{8}\\mathrm{O}_{6}:\\mathrm{NaOH}$ ratio to $1:2$ gives a mixture of Co-MOF and unreated ptcda (CoMOF+ptcda), while an increase in the $\\mathrm{C}_{24}\\mathrm{H}_{8}\\mathrm{O}_{6}:\\mathrm{NaOH}$ ratio to $1:6$ results in the formation of a composite of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocubes and Co-MOF $(\\mathbf{C}_{03}\\mathbf{O}_{4}@\\mathbf{C}_{0-}\\mathbf{M}\\mathbf{O}\\mathbf{F})$ (Figure 2a, see Supplementary Figure S1a,b,e,f). Under the same reation condition, the reation of $\\mathrm{Co(CH_{3}C O O)_{2}{\\cdot}4H_{2}O}$ and NaOH with a molar ratio of $1:6$ without ptcda produces $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocubes (see Supplementary Figure S2). \n\nSEM and transmission electron microscopy (TEM) measurements of $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF indicate that the $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocubes with approximate average size of $50\\ \\mathrm{nm}$ are uniformly dispersed on both sides of Co-MOF (Figure 2b-d). Fringes with lattice spacings of 0.243 and $0.466~\\mathrm{nm}$ for the (311) and (111) faces, respectively, along with the selected area electron diffraction (SAED) pattern, confirm the good crystalline characteristics of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocubes (Figure 2e,f). The high-angle annular dark-feld scanning TEM (HAADF-STEM) combined with elemental mapping measurements reveal that C, O, and Co are distributed throughout the entire sheets (Figure $\\pmb{2}\\mathrm{g}$ ). At the same time, the concentrations of O and Co dispersed on the nanocubes are relatively high. From these results, it was concluded that hybrid $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocubes were successfully synthesized on the Co-MOF. The color changes from red (CoMOF+ptcda), reddish brown (Co-MOF) to black $(\\mathbf{C}\\mathbf{o}_{3}\\mathbf{O}_{4}@\\mathbf{C}\\mathbf{o}\\mathbf{-}\\mathbf{M}\\mathbf{O}\\mathbf{F})$ (see Supplementary Figure S3). \n\nX-ray diffraction (XRD) measurements further confirm that the as-prepared composite is composed of Co-MOF and $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (JCPDS No. 42-1467) (see Supplementary Figure S4). The major diffraction peaks at 6.2, 7.1, 15.3, 19.3, and $22.0^{\\circ}$ , which can be indexed to the (001), (002), (110), (201), and (202) facets, respectively, of the Co-MOF, agree with those reported for the isostructural Zn-MOF with a formula $\\mathrm{Zn}_{2}(\\mathrm{ptcda}){\\cdot}2\\mathrm{H}_{2}\\mathrm{O}$ in the literature [40]. The structure analysis of Co-MOF is displayed in Supplementary Figure S5. The $\\scriptstyle{\\left[\\mathbf{CoO}_{6}\\right]}$ octahedral local structure leads to the connection of perylene cores to each other, forming a 3D open framework with wavy layered structure. The formation of controllable interlayer spacing through the interaction between ptcda and ${\\mathrm{Co}}^{2+}$ is beneficial to ion migration between organic layers. X-ray photoelectron spectroscopy (XPS) was performed to determine the chemical states of the Co, O, and C elements of the as-obtained $\\mathrm{Co_{3}O_{4}@C o-M O F}$ (see Supplementary Figures S6-S8). The Co 2p spectra indicates that there are two types of Co species, the two fitting peaks at 780.6 and $796.3\\ \\mathrm{eV}$ are ascribed to ${\\mathrm{Co}}^{2+}$ , while another two fitting peaks at 779.3 and $794.5\\ \\mathrm{eV}$ are attributed to ${\\mathrm{Co}}^{3+}$ . The peaks at 780.6 and $796.3\\ \\mathrm{eV}$ are ascribed to the sum of ${\\mathrm{Co}}^{2+}$ of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and Co-MOF [41–43]. The O 1s and C 1s spectra of the samples indirectly verified the formation of $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF (see Supplementary Figures S7, S8). In addition, the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF composites exhibit a high Brunauer-Emmett-Teller (BET) surface area of $453.5\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}$ , which is remarkably larger than those of other samples (BET surface areas for Co-MOF+ptcda and Co-MOF are 313.6 and $445.2\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , respectively) (see Supplementary Figure S9). As shown in Supplementary Figure S10, the pore size distribution for the Barrett-Joyner-Halenda (BJH) adsorption branch implies that the mesopores of the samples were below $20~\\mathrm{nm}$ . Furthermore, the pore size distribution was calculated through the Saito-Foley (SF) method, finding that the micropores were centered at $0.5\\mathrm{-}1~\\mathrm{nm}$ . These results clearly indicate the coexistence of micropores and mesopores in the samples. Therefore, the samples have a high specific surface area for better electrolyte permeation to access more redox active sites. \n\nThe electrochemical capacitive properties of Co-MOF, $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , and $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF electrodes were evaluated in a three-electrode system in 3.0 M KOH. For comparison, we have also mechanically mixed $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and Co-MOF together with a mass ratio of $1:4$ (the mass ratio calculation process is shown in Supporting Information, Figures S11, S12, Table S2), and the obtained mixture is named $^{5}{\\mathrm{C}}_{}0_{3}{\\mathrm{O}}_{4}{+}{\\mathrm{C}}_{}0$ -MOF” (see Supplementary Figure S13). From cyclic voltammetry (CV) curves of the as-obtained electrodes at different potentials and scan rates, the as-obtained electrodes mainly provide faradaic pseudocapacitive behavior, which is different from that of electric double-layer behavior (see Supplementary Figures S14, S15) [44,45]. The surrounding area from the CV curve of the $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF is larger than that of the Co-MOF, $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , and $C_{0_{3}}\\mathrm{O}_{4}\\mathrm{+}\\mathrm{C}_{0}$ -MOF (Figure 3a). These redox peaks come largely from the pseudocapacitance produced through faradaic redox reactions. However, the charge storage mechanism of electrode material is still very less understood at the atomic level. The structural and valence changes of metal oxides/hydroxides during the charge/discharge process have recently been studied by in situ and operando observations, which offer novel insight into the energy storage mechanism of electrode material [46–48]. It is found that there is no large-scale structural evolution in the process of discharging and charging, but only a few minor migration or adjustment of atom/ion species. Moreover, the highly reversible conversion of $\\mathrm{Co_{3}O_{4}/C o O O H}$ can avoid morphological fracture caused by volume changes during cations deintercalation/intercalation procedures. The possible reaction mechanism for Co-MOF and $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ is as follows: \n\n$$\n\\begin{array}{r l}&{\\mathrm{Co(II)_{2}(p t c d a)\\cdot2H_{2}O}+\\mathrm{OH}^{-}\\leftrightarrow\\mathrm{Co(III)_{2}O H(p t c d a)\\cdot2H_{2}O}+\\mathrm{e}^{-}}\\\\ &{\\mathrm{Co_{3}O_{4}}+\\mathrm{OH}^{-}+\\mathrm{H}_{2}O\\leftrightarrow3\\mathrm{CoOOH}+\\mathrm{e}^{-}}\\\\ &{\\mathrm{CoOOH}+\\mathrm{OH}^{-}\\leftrightarrow\\mathrm{CoO_{2}}+\\mathrm{H}_{2}O+\\mathrm{e}^{-}}\\end{array}\n$$ \n\nTo evaluate the electrochemical properties of the as-obtained electrodes, galvanostatic charge-discharge (GCD) curves were generated (Figure 3b). At $0.5\\mathrm{~A~g~}^{-1}$ , the MOF-based materials possess high charge-discharge voltages (0.65 V), which are higher than that of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (0.6 V). As well, the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF displays the longest charge-discharge time. The specific capacitances were calculated from the GCD curves (see Supplementary Figure S16) of the as-obtained electrodes at 0.5, 1, 2, 5, and $8\\mathrm{Ag}^{-1}$ (Figure 3c, the calculation is shown in Supporting Information). We can see that the specific capacitance of the $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF composites $(1020\\mathrm{~F~g~}^{-1})$ is much higher than those of $C_{0_{3}}\\mathrm{O}_{4}\\mathrm{+}\\mathrm{C}_{0}$ -MOF $(606\\mathrm{~F~g^{-1}})$ ), $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ $(479\\mathrm{~F~g}^{-1})$ , and Co-MOF $(356\\mathrm{~F~g~}^{-1})$ at $0.5\\mathrm{{Ag}^{-1}}$ , as well as those of most recently reported metal oxides [49–51], MOFs [12,52,53], and MOF composites [54] (see Supplementary Tables S3-6). Interestingly, the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}.$ -MOF offer excellent rate capability through retaining a capacitance of $861\\mathrm{~F~g}^{-1}$ when the current density increases 16 times $(8{\\mathrm{~A~g~}}^{-1})$ . Even at the current density of $32\\mathrm{~A~g^{-1}}$ , the capacitance can still reach $469\\mathrm{~F~g^{-1}}$ (see Supplementary Figure S17), which proves the rate capability of $\\mathrm{Co_{3}O_{4}@C o-M O F}$ as good as some recently reported high-performance MOF-based materials [46,52,55] (see Supplementary Tables S7). After 5000 cycles, the $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF decayed only $3.1\\%$ compared with its initial capacity. Additionally, large decays were observed for $C_{0_{3}}\\mathrm{O}_{4}\\mathrm{+}\\mathrm{C}_{0}$ -MOF $(10.9\\%)$ , $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ $(17.8\\%)$ , and Co-MOF $(65.2\\%)$ (Figure 3d). The conductivity of the as-obtained electrodes was also evaluated via electrochemical impedance spectroscopy (EIS) in the frequency range of $0.01{-}10^{5}~\\mathrm{Hz}$ with open-circuit conditions (see Supplementary Figure S18). Moreover, the charge-transfer resistance $(R_{c t})$ of the electrode was calculated by the Zsimp-Win software. The $R_{c t}$ of $\\mathbf{C}_{0_{3}}\\mathbf{O}_{4}@\\mathbf{C}_{0}$ -MOF was remarkably low, similar to those of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , Co-MOF, and $\\mathrm{Co_{3}O_{4}+C o-M O F}$ . In addition, the curves showed that the $R_{c t}$ after 5000 cycles is marginally larger than that of the original, which further evidences the stability of the composites. \n\nTo further investigate the chemical stabilities and understand the charge-discharge, SEM and TEM images of $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF after cycling were obtained (see Supplementary Figures S19-21). The morphology change of $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}.$ MOF is negligible, and a number of nanopores can be found in the HRTEM image. Furthermore, the corresponding elemental mapping images of $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}-\\mathrm{N}$ MOF after cycling indicate that the element K was distributed in the entire Co-MOF, which may be due to the occurrence of $\\mathrm{K}^{+}$ intercalation/deintercalation in the MOF pores during charging/discharging. The chemical stabilities of Co-MOF and $\\mathrm{Co_{3}O_{4}@C o-M O F}$ were checked in $3.0\\mathrm{~M~}$ KOH. $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF can retain the original morphology after immersion in 3.0 M KOH for 0 h, $24\\mathrm{~h~}$ , 7 days and 15 days, whereas CoMOF collapses even only for $24\\mathrm{h}$ (Figure 4a-d, see Supplementary Figures S22, S23). This is because of the preparation of $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF in a strong alkaline conditions $\\scriptstyle(\\mathrm{pH}=11-13$ ) as well as the growth of highly stable $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ on the surface of the Co-MOF, while Co-MOF were formed at $\\mathrm{\\pH=}6.8$ . In addition, Co-MOF is relatively more stable than $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF in the acidic solution, which may be due to the different synthesis condition (Figures S24, S25). Further, the XRD patterns and XPS spectra of $\\mathrm{Co_{3}O_{4}@C o-M O F}$ after immersion in the alkaline solution for $0\\mathrm{{h}}$ and 15 days and after cycling for 5000 cycles show that $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}-$ MOF can maintain their framework after cycling and immersion in the alkaline solution, which further confirms their good stability (Figure 4e,f,h). After immersion and cycling, the element K was found to exist in $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF, whose $\\mathbf{A}\\mathbf{t}\\%$ after cycling was 3 times that of composites after immersion (Figure ${\\pmb{4}}\\mathrm{{g}}$ , see Supplementary Figure S26). Such an interesting phenomenon can be explained by the occurrence of $\\mathrm{K}^{+}$ intercalation/deintercalation in the MOF pores during charging/discharging and ion exchange in the solution, but for the immersion process, only ion exchange occurs. \n\nAqueous/solid-state flexible devices were constructed based on positive (the as-prepared nanomaterials) and negative (AC) materials according to the method we reported previously (Supporting Information) [32,54]. The specific capacitance of activated carbon electrode was $168\\mathrm{~F~g^{-1}}$ at $\\lVert.0\\mathrm{~A~g~}^{-1}$ (see Supplementary Figure S27). Based on the specific capacitance values and potential windows, the mass ratio between the positive and negative electrode was set at 1:4 in the as-assembled device. In an aqueous electrolyte, the working potential range was expanded to 0-1.55 V (see Supplementary Figures S28, S29). Supplementary Figure S31a shows that there are more than one set of redox peaks in the CV curves, and the CV curves are not rectangular, perhaps because of $\\mathrm{Co_{3}O_{4}@C o-M O F}$ for the surface redox mechanism of $\\operatorname{Co}(\\operatorname{II})$ to $\\operatorname{Co}(\\operatorname{III})$ from Co-MOF and $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , respectively. The specific capacitance of the $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF//AC aqueous device can reach $228~\\mathrm{mF~cm^{-2}}$ at $0.5~\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ , much higher than that of $\\mathrm{Co}_{3}\\mathrm{O}_{4}\\mathrm{+Co}$ -MOF//AC $(163~\\mathrm{mF~cm^{-2}},$ ), $\\mathrm{Co_{3}O_{4}//A C}$ (129 mF cm2), and Co-MOF//AC $(97~\\mathrm{mF~cm}^{-2}$ ) (see Supplementary Figures S30, S31c). Based on the thickness of the electrode (see Supplementary Figure S32), the corresponding volumetric capacitances are obtained (Table S3). The specific capacitance of the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF//AC aqueous device is $96.2\\%$ of its initial capacitance after 5000 cycles (see Supplementary Figure S31d), which verifies the superb cycling property. Benefiting from the good conductivity of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , the Co3O4@Co-MOF//AC aqueous device has a lower $R_{c t}$ (see Supplementary Figure S33), which agrees well with its good electrochemical property. \n\nThe solid-state flexible devices were also constructed via a facile method (see more details in Supporting Information). All CV curves of the as-obtained solid-state flexible devices showed obvious oxidation and deoxidization peaks, indicating typical faradaic pseudocapacitive behavior (see Supplementary Figures S34, S35). Specifically, the CV curves of the $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF//AC solid-state flexible device retained their original shapes as the scan rate increased from 5 to $100\\mathrm{~mV~s}^{-1}$ , indicating their excellent rate performance. The specific capacitance change vs. potential exhibits that the as-prepared MOF-based material solid-state flexible devices have the highest specific capacitance at $1.50~\\mathrm{V}_{;}$ whereas for the $\\mathrm{Co_{3}O_{4}//A C}$ solid-state flexible device, the highest specific capacitance is located at 1.40 V (Figure 5a, Supplementary Figure S36). The $\\mathrm{Co}_{3}\\mathrm{O}_{4}@$ Co-MOF//AC solid-state flexible device exhibits a high specific capacitance of $192~\\mathrm{mF~cm^{-2}}$ at $0.5\\mathrm{\\mA\\cm^{-2}}$ , which is remarkably higher than those of all other devices (specific capacitances for Co-MOF, $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $C_{0_{3}}\\mathrm{O}_{4}\\mathrm{+}\\mathrm{C}_{0}$ -MOF are 87, 123 and $151~\\mathrm{mF~cm}^{-2}$ , respectively) (Figure 5b, Supplementary Figure S37). Interestingly, at $5\\mathrm{mA}\\mathrm{cm}^{-2}$ , the $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF//AC solid-state flexible device provides a superb rate capability via keeping the capacitance of $166\\mathrm{\\mF\\cm^{-2}}$ . After 5000 cycles, only $4.3\\%$ of the capacitance of the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF//AC solid-state flexible device was lost, which confirms the good cycling ability (Figure 5c). Moreover, the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}-$ MOF//AC solid-state flexible device revealed a low $R_{c t}$ value of $17\\Omega$ , similar to that of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ $(15~\\Omega)$ . On the other hand, Co-MOF exhibited a slightly higher $R_{c t}$ value of $23\\ \\Omega$ compared with $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF, indicating that the combination of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and Co-MOF effectively improved the electrical conductivity to some extent (see Supplementary Figure S38). The power density and energy density are crucial for actual application. The $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}-$ MOF//AC solid-state flexible device indicated a peak energy density of $21.6\\mathrm{\\mW}$ h $\\mathrm{cm}^{-3}$ (Figure 5d). Furthermore, the peak power density of the solid-state flexible device was $1373.2\\ \\mathrm{mW\\cm^{-3}}$ at $5\\mathrm{\\mA\\cm^{-2}}$ . The maximum energy density of the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF//AC solid-state flexible device was larger than those of all other devices. More importantly, the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF//AC solid-state flexible device was used to power a green light-emitting diode (LED). A green LED could be powered for approximately $4\\mathrm{min}$ after charging for $30~\\mathrm{s}$ . \n\nTo measure the flexibility of the as-fabricated solid-state flexible device, the obtained solid-state flexible device was tested under different bending degrees for each 100 cycles. It is clear that the obtained solid-state flexible device lost only $0.28\\%$ under different bending degrees for 400 cycles (Figure 6a), and TEM images of $\\mathrm{Co_{3}O_{4}@C o-M O F}$ after 400 bending cycles were obtained (see Supplementary Figure S39). The morphology change of $\\mathrm{Co_{3}O_{4}@C o-M O F}$ is negligible, which further confirms their excellent flexibility and stability. The CV curves under the four bending degrees are nearly unchanged, which further demonstrates that the obtained solid-state flexible device can work well under flexed conditions (Figure 6b). Moreover, the environmental stability of the device was also examined by applying different pressures to the device. CV curves with different load weights from 10 to $60\\ \\mathrm{g}$ change slightly (Figure 6c). In the meantime, the obtained solid-state flexible device was tested under different load pressures for each 100 cycles, and the device demonstrated only $0.22\\%$ loss under different load pressures after 400 cycles (Figure 6d). The device was measured at different temperatures from $\\boldsymbol{-20}^{\\circ}\\boldsymbol{\\mathrm{C}}$ to $80~^{\\circ}\\mathrm{C}$ , but the area under the CV curve did not change much (Figure 6e). Compared with that at room temperature $(25^{\\circ}\\mathrm{C})$ , the area under the CV curve mildly increased at $80~^{\\circ}\\mathrm{C}$ , while it very slightly decreased at - $20~^{\\circ}\\mathrm{C}$ . The reason might be the increased ion transport rate at elevated temperatures. When the temperature is higher than $80~^{\\circ}\\mathrm{C}$ , the solid-state electrolyte changes into gel electrolyte, and thus we choose $80~^{\\circ}\\mathrm{C}$ as the highest temperature. \n\n# CONCLUSIONS \n\nIn summary, a composite of cobalt oxide nanocubes on Co-MOF sheet $(\\mathrm{Co_{3}O_{4}@C o-M O F})$ were successfully synthesized via a one-pot hydrothermal reaction under a highly alkaline condition. Without hybriding with $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , Co-MOF can provide an appropriate space for the electrochemical reaction and intercalation/de-intercalation of $\\mathrm{K}^{+}$ during the energy storage process, but the alkaline stability of pristine Co-MOF is poor, resulting in capacitance as low as $356\\mathrm{~F~g^{-1}}$ . The presence of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ on the surface of Co-MOF effectively improves the alkaline stability, increases redox active sites, leading to dramatic enhancement of capacitance to $1020\\mathrm{~F~g}^{-1}$ at $0.5\\mathrm{~A~g~}^{-1}$ . Such a highly alkaline-stable $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF composite shows significant advantages for application as an electrochemical capacitor energy storage device electrode in terms of enhanced durability and capacitance. The $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}-$ MOF composite shows a high cycling stability after 5000 cycles with only $3.3\\%$ decay at 5 A $\\mathbf{g}^{-1}$ . More remarkably, the as-constructed aqueous/solid-state device showed high specific capacitance, wonderful cycle stability, and high energy density. In addition, the as-fabricated solid-state flexible device showed excellent mechanical flexibility and environmental stability. Considering the merits of facile synthetic method, simple construction and outstanding properties, the $\\mathrm{Co}_{3}\\mathrm{O}_{4}@\\mathrm{Co}$ -MOF//AC solid-state flexible device opens up bright prospects in portable, flexible and lightweight electronic applications. \n\n# SUPPLEMENTARY DATA \n\nSupplementary data are available at NSR online. \n\n# FUNDING \n\nThis work was supported by the National Natural Science Foundation of China (21671170, 21875207, 21673203), the Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (TAPP), Program for New Century Excellent Talents of the University in China (NCET-13-0645), the Six Talent Plan (2015-XCL-030), and Qinglan Project. We also acknowledge the Priority Academic Program Development of Jiangsu Higher Education Institutions and the technical support we received at the Testing Center of Yangzhou University. \n\n# REFERENCES \n\n1 Yaghi OM, Li G and Li H. Selective binding and removal of guests in a microporous metal-organic framework. Nature 1995; 378:703–706. \n\n2 Rosi NL, Kim J and Eddaoudi M et al. Rod Packings and Metal-Organic Frameworks Constructed from Rod-Shaped Secondary Building Units. J Am Chem Soc 2005; \n127:1504–1518. \n3 Shen K, Zhang L and Chen X et al. Ordered macro-microporous metal-organic framework single crystals. Science 2018; 359:206–210. \n4 Li J, Wang X and Zhao G et al. Metal-organic framework-based materials: superior adsorbents for the capture of toxic and radioactive metal ions. Chem Soc Rev 2018; \n47:2322–2356. \n5 Jeong GY, Singh AK and Kim MG et al. Metal-organic framework patterns and membranes with heterogeneous pores for flow-assisted switchable separations. Nat Commun 2018; 9:3968. \n6 Chen CX, Wei ZW and Jiang JJ et al. Dynamic Spacer Installation for Multirole MetalOrganic Frameworks: A New Direction toward Multifunctional MOFs Achieving Ultrahigh Methane Storage Working Capacity. J Am Chem Soc 2017; 139:6034–6037. \n7 Yang W, Li X and Li Y et al. Applications of Metal-Organic‐Framework‐Derived Carbon Materials. Adv Mater 2018; 31:1804740. \n8 Chen YZ, Wang ZU and Wang H et al. Singlet Oxygen-Engaged Selective PhotoOxidation over Pt Nanocrystals/Porphyrinic MOF: The Roles of Photothermal Effect and Pt Electronic State. J Am Chem Soc 2017; 139:2035–2044. \n9 Yang Q, Xu Q and Jiang HL. Metal-organic frameworks meet metal nanoparticles: synergistic effect for enhanced catalysis. Chem Soc Rev 2017; 46:4774–4808. \n10 Yang X, Sun JK and Kitta M et al. Encapsulating highly catalytically active metal nanoclusters inside porous organic cages. Nat Catal 2018; 1:214–220. \n\nZhao S, Wang Y and Dong J et al. Ultrathin metal-organic framework nanosheets for electrocatalytic oxygen evolution. Nat Energy 2016; 1:16184. \n\nSheberla D, Bachman JC and Elias JS et al. Conductive MOF electrodes for stable supercapacitors with high areal capacitance. Nat Mater 2017; 16:220–224. \n\nWang L, Feng X and Ren L et al. Flexible Solid-State Supercapacitor Based on a Metal-Organic Framework Interwoven by Electrochemically-Deposited PANI. J Am Chem Soc 2015; 137:4920–4923. \nWang Y, Song Y and Xia Y. Electrochemical capacitors: mechanism, materials, systems, characterization and applications. Chem Soc Rev 2016; 45:5925–5950. Jiang H, Liu XC and Wu Y et al. Metal-Organic Frameworks for High ChargeDischarge Rates in Lithium-Sulfur Batteries. Angew Chem Int Ed 2018; 57:3916–3921. Wang L, Han Y and Feng X et al. Metal-organic frameworks for energy storage: Batteries and supercapacitors. Coord Chem Rev 2016; 307:361–381. \nWang HL, Zhu QL and Zou RQ et al. Metal-Organic Frameworks for Energy Applications. Chem 2017; 2:52–80. \nZheng SS, Li XR and Yan BY et al. Transition-Metal (Fe, Co, Ni) Based MetalOrganic Frameworks for Electrochemical Energy Storage. Adv Energy Mater 2017; 7:1602733. \nLu XF, Liao PQ and Wang JW et al. An Alkaline-Stable, Metal Hydroxide Mimicking Metal-Organic Framework for Efficient Electrocatalytic Oxygen Evolution. J Am Chem Soc 2016; 138:8336–8339. \nZheng SS, Xue HG and Pang H. Supercapacitors based on metal coordination materials. Coord Chem Rev 2018; 373:2–21. \n\nYi FY, Zhang R and Wang H et al. Metal-Organic Frameworks and Their Composites: Synthesis and Electrochemical Applications. Small Methods 2017; 1:1700187. \n\nDou S, Song J and Xi S et al. Boosting Electrochemical $\\mathrm{CO}_{2}$ Reduction on MetalOrganic Frameworks via Ligand Doping. Angew Chem Int Ed 2019; 58:4041–4045. \n\nKim SH, Lee HH and Kim JM et al. Heteromat-framed metal-organic coordination polymer anodes for high-performance lithium-ion batteries. Energy Storage Mater 2019; doi:10.1016/j.ensm.2019.02.010 \n\nWang Q and O’Hare D. Recent Advances in the Synthesis and Application of Layered Double Hydroxide (LDH) Nanosheets. Chem Rev 2012; 112:4124–4155. \n\nJiang J, Li Y and Liu J et al. Recent Advances in Metal Oxide-based Electrode Architecture Design for Electrochemical Energy Storage. Adv Mater 2012; 24:5166– 5180. \n\nLi X, Wei J and Li Q et al. Nitrogen-Doped Cobalt Oxide Nanostructures Derived from Cobalt-Alanine Complexes for High-Performance Oxygen Evolution Reactions. Adv Funct Mater 2018; 28:1800886. \n\nChen LF, Yu ZY and Wang JJ et al. Metal-like fluorine-doped $\\upbeta$ -FeOOH nanorods grown on carbon cloth for scalable high-performance supercapacitors. Nano Energy 2015; 11:119–128. \n\nZhai T, Wan L and Sun S et al. Phosphate Ion Functionalized $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ Ultrathin Nanosheets with Greatly Improved Surface Reactivity for High Performance Pseudocapacitors. Adv Mater 2017; 29:1604167. \n\nLi B, Gu P and Feng Y et al. Ultrathin Nickel-Cobalt Phosphate 2D Nanosheets for Electrochemical Energy Storage under Aqueous/Solid-State Electrolyte. Adv Funct Mater 2017; 27:1605784. \n\nGrote F, Yu ZY, and Wang JL et al. Self-Stacked Reduced Graphene Oxide Nanosheets Coated with Cobalt-Nickel Hydroxide by One-Step Electrochemical Deposition toward Flexible Electrochromic Supercapacitors. Small 2015; 11:4666– 4672. \n\n31 Gao S, Sun Y and Lei F et al. Ultrahigh Energy Density Realized by a Single-Layer $\\upbeta$ - ${\\mathrm{Co}}(\\mathrm{OH})_{2}$ All-Solid-State Asymmetric Supercapacitor. Angew Chem Int Ed 2014; 53:12789–12793. \n\nLiao Q, Li N and Jin S et al. All-Solid-State Symmetric Supercapacitor Based on $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ Nanoparticles on Vertically Aligned Graphene. ACS Nano 2015; 9:5310–5317. \n\nZhan W, Kuang Q and Zhou J et al. Semiconductor $@$ Metal-Organic Framework CoreShell Heterostructures: a Case of ZnO@ZIF-8 Nanorods with Selective Photoelectrochemical Response. J Am Chem Soc 2013; 135:1926–1933. \n\nZhu QL and Xu Q. Metal-organic framework composites. Chem Soc Rev 2014; \n43:5468–5512. \n\nWei T, Zhang M and Wu P et al. POM-based metal-organic framework/reduced graphene oxide nanocomposites with hybrid behavior of battery-supercapacitor for superior lithium storage. Nano Energy 2017; 34:205–214. \n\nHu X, Shao W and Hang X et al. Superior Electrical Conductivity in Hydrogenated Layered Ternary Chalcogenide Nanosheets for Flexible All-Solid-State Supercapacitors. Angew Chem Int Ed 2016; 128:5827–5832. \n\nYang J, Zhang F and Lu H et al. Hollow Zn/Co ZIF Particles Derived from Core-Shell ZIF-67@ZIF-8 as Selective Catalyst for the Semi-Hydrogenation of Acetylene. Angew Chem Int Ed 2015; 54:10889–10893. \n\nYu J, Mu C and Yan B et al. Nanoparticle/MOF composites: preparations and applications. Mater Horizons 2017; 4:557–569. \n\nLian X, Fang Y and Joseph E et al. Enzyme-MOF (metal-organic framework) composites. Chem Soc Rev 2017; 46:3386–3401. \n\nZhao J, Li M and Sun J et al. Metal-Oxide Nanoparticles with Desired Morphology Inherited from Coordination-Polymer Precursors. Chem A Eur J 2012; 18:3163–3168. \n\n41 Xu L, Jiang Q and Xiao Z et al. Plasma-Engraved $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ Nanosheets with Oxygen Vacancies and High Surface Area for the Oxygen Evolution Reaction. Angew Chem Int Ed 2016; 55:5277–5281. \n\nZhao L, Dong B and Li S et al. Interdiffusion Reaction-Assisted Hybridization of TwoDimensional Metal-Organic Frameworks and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ Nanosheets for Electrocatalytic Oxygen Evolution. ACS Nano 2017; 11:5800–5807. \n\nWang Y, Zhou T and Jiang K et al. Reduced Mesoporous $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ Nanowires as Efficient Water Oxidation Electrocatalysts and Supercapacitor Electrodes. Adv Energy Mater 2014; 4:1400696. \n\nZhai T, Sun S and Liu X et al. Achieving Insertion-Like Capacity at Ultrahigh Rate via Tunable Surface Pseudocapacitance. Adv Mater 2018; 30:1706640. \n\nWang J, Xu Y and Ding B et al. Confined Self-Assembly in Two-Dimensional Interlayer Space: Monolayered Mesoporous Carbon Nanosheets with In-Plane Orderly Arranged Mesopores and a Highly Graphitized Framework. Angew Chem Int Ed 2018; 57:2894–2898. \n\nDeng T, Lu Y, and Zhang W et al. Inverted Design for High-Performance Supercapacitor Via ${\\mathrm{Co}}(\\mathrm{OH})_{2}$ -Derived Highly Oriented MOF Electrodes. Adv Energy Mater 2018; 8:1702294. \n\nLi HB, Yu MH, and Wang FX et al. Amorphous nickel hydroxide nanospheres with ultrahigh capacitance and energy density as electrochemical pseudocapacitor materials. Nat Commun 2013; 4:1894. \n\nDeng T, Zhang W, and Arcelus O et al. Atomic-level energy storage mechanism of cobalt hydroxide electrode for pseudocapacitors. Nat Commun 2017; 8:15194. \n\nMeng F, Fang $Z$ and Li $Z$ et al. Porous $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ materials prepared by solid-state thermolysis of a novel Co-MOF crystal and their superior energy storage performances for supercapacitors. J Mater Chem A 2013; 1:7235. \n\n50 Chen S, Xue M and Li Y et al. Rational design and synthesis of $\\mathrm{Ni_{x}C o_{3-x}O_{4}}$ nanoparticles derived from multivariate MOF-74 for supercapacitors. J Mater Chem A 2015; 3:20145–20152. \n\n51 Zhang YZ, Wang Y and Xie YL et al. Porous hollow $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ with rhombic dodecahedral structures for high-performance supercapacitors. Nanoscale 2014; \n6:14354–14359. \n52 Qu C, Jiao Y, and Zhao B et al. Nickel-based pillared MOFs for high-performance supercapacitors: Design, synthesis and stability study. Nano Energy 2016; 26:66–73. \n53 Yan Y, Gu P and Zheng SS et al. Facile synthesis of an accordion-like Ni-MOF superstructure for high-performance flexible supercapacitors. J Mater Chem A 2016; \n4:19078–19085. \n54 Zhang YZ, Cheng T and Wang Y et al. Flexible Supercapacitors: A Simple Approach to Boost Capacitance: flexible Supercapacitors Based on Manganese Oxides $@$ MOFs via Chemically Induced In Situ Self-Transformation. Adv Mater 2016; 28:5241–5241. \n55 Yang J, Zheng C, Xiong P, Li Y, Wei M. Zn-doped Ni-MOF material with a high supercapacitive performance. J Mater Chem A 2014; 2:19005–19010. \n\n# Figure Captions \n\n![](images/72963ee357dcc2d6dd2a07cd226df63225c666061dfb8bbf9cae7dae4cdf9ec3.jpg) \nFigure 1. Schematic illustration of one-pot hydrothermal synthesis of $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF composite. \n\n![](images/e79e11efda20f44e641fdee854d249ae4449df5bb3d3a141e2a93f7feb8375ec.jpg) \nFigure 2. Microscopic characterization. a,b) SEM images, c) schematic morphology, and d) TEM images of $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF. e,f) HRTEM images of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (Inset of f), SAED pattern). g) HAADF-STEM image of $\\mathbf{Co_{3}O_{4}@C o}$ -MOF and corresponding elemental mapping of C-K, O-K, Co-K. \n\n![](images/7e4d697e5daee7a6acd4cf748b8d499c5f55db11c96b71620fdbd8aec3193271.jpg) \nFigure 3. Electrochemical results of as-prepared electrodes (Co-MOF, $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , $\\mathrm{Co}_{3}\\mathrm{O}_{4}\\mathrm{+Co}\\mathrm{.}$ - MOF, $\\mathrm{Co_{3}O_{4}@C o-M O F)}$ in a three-electrode cell in $3.0\\ \\mathrm{M}$ KOH aqueous solution, a) CV curves with a scan rate at $30\\mathrm{~mV~s^{-1}}$ . b) GCD curves at a current density $\\underline{{0.5}}\\mathrm{~A~g~}^{-1}$ . c) The specific capacitance changing vs. current densitiy from $0.5\\mathrm{~A~g~}^{-1}$ to $8{\\mathrm{~A~g~}}^{-1}$ , and d) cycling performance at ${5\\mathrm{Ag}^{-1}}$ for 5000 cycles. \n\n![](images/213ebe35545306d3e39909dde6833981183e0f225fd76dd13b2f43500c58341e.jpg) \nFigure 4. $\\mathbf{a}_{1}{-}\\mathbf{d}_{1}^{\\prime}$ ) Optical images of $\\mathrm{Co_{3}O_{4}@C o-M O F}$ after immersion in $3.0\\mathrm{{M}}$ KOH for $0\\mathrm{{h}}$ , 24 h, 7 days and 15 days, $\\mathbf{a}_{2}{-}\\mathbf{d}_{2}{\\mathrm{.}}$ ) the corresponding SEM images. e,f) XPS spectra, g) contents of Co, C, O, K, h) XRD patterns of $\\mathbf{Co}_{3}\\mathbf{O}_{4}@$ Co-MOF for $_{0\\mathrm{~h~}}$ , 15 days and after cycling for 5000 cycles. \n\n![](images/933ced56dc545c0199aae465b8795128df433e9788b34da5143d1fa6a65793c1.jpg) \nFigure 5. Electrochemical measurements of the as-prepared solid-state flexible devices. a) Specific capacitance change vs. potential, b) specific capacitance change vs. current density, c) cycling property at $5\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ , d) ragone plot exhibiting the relationship between energy density and power density (Inset of d), optical image of the flexible device with solid-state electrolyte). \n\n![](images/0e4201f133b1df04cf42ae4d3e6a3f2878063ff1173602e6b9eac158fa1329e8.jpg) \nFigure 6. Electrochemical flexibility measurements of the as-prepared $\\mathbf{Co}_{3}\\mathbf{O}_{4}@\\mathbf{Co}$ -MOF//AC solid-state flexible device. a) Specific capacitance after 400 bending cycles with different bending degrees, b) CV curves at $50~\\mathrm{mV~\\hat{s}^{-1}}$ with four bending degrees, c) CV curves under different load pressures, d) specific capacitance after 400 cycles under different load pressures, e) CV curves at different temperatures. " + }, + { + "id": "10.1038_s41467-019-14278-9", + "DOI": "10.1038/s41467-019-14278-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-019-14278-9", + "Relative Dir Path": "mds/10.1038_s41467-019-14278-9", + "Article Title": "Quantifying electron-transfer in liquid-solid contact electrification and the formation of electric double-layer", + "Authors": "Lin, SQ; Xu, L; Wang, AC; Wang, ZL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Contact electrification (CE) has been known for more than 2600 years but the nature of charge carriers and their transfer mechanisms still remain poorly understood, especially for the cases of liquid-solid CE. Here, we study the CE between liquids and solids and investigate the decay of CE charges on the solid surfaces after liquid-solid CE at different thermal conditions. The contribution of electron transfer is distinguished from that of ion transfer on the charged surfaces by using the theory of electron thermionic emission. Our study shows that there are both electron transfer and ion transfer in the liquid-solid CE. We reveal that solutes in the solution, pH value of the solution and the hydrophilicity of the solid affect the ratio of electron transfers to ion transfers. Further, we propose a two-step model of electron or/and ion transfer and demonstrate the formation of electric double-layer in liquid-solid CE.", + "Times Cited, WoS Core": 537, + "Times Cited, All Databases": 554, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000511940400003", + "Markdown": "# Quantifying electron-transfer in liquid-solid contact electrification and the formation of electric double-layer \n\nShiquan Lin1,2, Liang Xu 1,2, Aurelia Chi Wang3 & Zhong Lin Wang 1,2,3\\* \n\nContact electrification (CE) has been known for more than 2600 years but the nature of charge carriers and their transfer mechanisms still remain poorly understood, especially for the cases of liquid–solid CE. Here, we study the CE between liquids and solids and investigate the decay of CE charges on the solid surfaces after liquid–solid CE at different thermal conditions. The contribution of electron transfer is distinguished from that of ion transfer on the charged surfaces by using the theory of electron thermionic emission. Our study shows that there are both electron transfer and ion transfer in the liquid–solid CE. We reveal that solutes in the solution, pH value of the solution and the hydrophilicity of the solid affect the ratio of electron transfers to ion transfers. Further, we propose a two-step model of electron or/and ion transfer and demonstrate the formation of electric double-layer in liquid–solid CE. \n\nontact electrification (CE) (or triboelectrification in general terms) is a universal but complicated phenomenon, which has been known for more than 2600 years. The solid-solid CE has been studied using various methods and different mechanisms were proposed (Electron transfer1,2, ion transfer3 and material transfer4–6 were used to explain different types of CE phenomena for various materials). In parallel, CE between liquid–solid is rather ubiquitous in our daily life, such as flowing water out of a pipe is charged, which is now the basis of many technologies and physical chemical phenomena, such as the liquid–solid triboelectric nanogenerators $(\\mathrm{TENGs})^{7-10}$ , hydrophobic and hydrophilic surfaces, and the formation of electric double-layer (EDL)11–14. However, understanding about the liquid–solid CE is rather limited and the origin about the formation of EDL remains ambiguous owing to the lacking of fundamental understanding about charge transfer at interfaces. The most important issue in the CE mechanism is the identity of charge carriers (electrons or/and ions), which has been debated for decades in the solid-solid $\\mathrm{CE}^{15,16}$ . Most recently, charge carriers have been identified as electrons for solid-solid CE based on temperature dependent effect and photoexcitation effect on the charged surfaces, and the ion transfer is out of consideration17–19. \n\nAs for the case of liquid–solid CE, it is usually assumed to be ion transfer without any detailed studies, simply because ions are often present in liquids, such as $\\mathrm{H^{+}}$ and $\\mathrm{OH^{-}}$ in water. Regarding the nature of EDL, the charging of the isolated surfaces in a liquid is considered to be induced by ionization or dissociation of surface groups and the adsorption or binding of ions from liquid onto the solid surface20. From these points of view, the charge carriers in liquid–solid CE is naturally assumed to be ions and transfer of electrons has not been even considered. However, Wang et al. has proposed a “electron-cloud-potential-well” model for explaining CE in a general case, in which the electron transfer in CE is considered to be induced by the overlap of electron clouds as a result of mechanically forced contact18. At a liquid–solid interface, the molecules in a liquid collide with atoms on the solid surface owing to liquid pressure, which may lead to the overlap of electron clouds and result in electron transfer. Hence, there is still dispute about the identity of charge carriers in the liquid–solid CE, which is one of the most fundamental questions in CE and physical chemistry as well. Such a question can now be answered using the surface charge decay experiments at different temperatures for distinguishing electron transfer from ion transfer in liquid–solid contact17,18. This is because electrons are easily emitted from the solid surface as induced by thermionic emission, while ions usually bind with the atoms on the solid surface, and they are rather hard to be removed from the surface in comparison to electrons especially when the temperature is not too high. \n\nHere we show the CE in liquid–solid and the charge density on solid surfaces after the contact measured using Kelvin probe force microscopy $(\\mathrm{KPFM})^{21-24}$ . We investigate the decay of CE charges on the solid surfaces at different temperatures. We particularly study the effects of solutes in the aqueous solution, $\\mathrm{\\pH}$ value of the aqueous solution and the hydrophilicity of the solid surfaces on the liquid–solid CE. We have analyzed the ratio of electron transfers to ion transfers in the liquid–solid CE for the first time according to the thermionic emission theory, to the best of our knowledge. Lastly, we propose a model about the formation of the EDL based on the understanding of the charge transfer at liquid–solid interface, providing a distinct mechanism from the general understanding in classical physical chemistry. \n\n# Results \n\nThe CE between the DI water and the $\\mathbf{SiO}_{2}$ . Here, flat insulating ceramic thin films, such as $\\mathrm{SiO}_{2}$ , ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ , $\\mathrm{MgO}$ , ${\\mathrm{Ta}}_{2}{\\mathrm{O}}_{5},$ , $\\mathrm{HfO}_{2}$ , AlN, and $\\mathrm{Si}_{3}\\mathrm{N}_{4}.$ , deposited on highly doped silicon wafers, were used as solid samples. The liquids were chosen as deionized water (DI water) and different aqueous solutions, including NaCl, HCl and NaOH solutions. In the experiments, the liquid dropped from a grounded needle and slid across the ceramic surface, as shown in Fig. 1a. After the liquid being vaporized, the surface charge densities on the ceramic surfaces were measured by using KPFM at different substrate temperatures. According to previous studies, ions will be produced by ionization reaction on the oxide and nitride surfaces when they contact the aqueous solutions25–29. For example, $\\mathrm{O^{-}}$ ions will be generated by the ionization reaction on the $\\mathrm{SiO}_{2}$ surface as shown below (The hydroxyl on the $\\mathrm{SiO}_{2}$ surface is usually produced by adsorbing water molecules in the air or contacting with water)29: \n\n$$\n\\equiv\\mathrm{Si}-\\mathrm{OH}+\\mathrm{OH}^{-}\\Leftrightarrow\\equiv\\mathrm{Si}-\\mathrm{O}^{-}+\\mathrm{H}_{2}\\mathrm{O}\n$$ \n\nAs introduced above, electrons may be another type of charge carrier on the $\\mathrm{SiO}_{2}$ surface after contacting with aqueous solutions. Hence, we assume that there are both $\\mathrm{O^{-}}$ ions and electrons on the liquid sliding trace on the $\\mathrm{SiO}_{2}$ surface, as shown in the inset in the Fig. 1a. When the $\\mathrm{SiO}_{2}$ sample is heated by the sample heater, the electrons will be thermally excited and emitted from the surface, as shown in Fig. 1b, while the $\\mathrm{O^{-}}$ ions may stay on the surface since they formed covalent bonds with the Si atoms on the $\\mathrm{SiO}_{2}$ surface. (As shown in the ab initio molecular dynamics simulations in the Supplementary Note 1, Supplementary Figs. 1, 2, and the simulation results are shown in Supplementary Movies 1–7). This means that, if heating can induce obvious decay of CE charges on the $\\mathrm{SiO}_{2}$ surface, it may be mainly caused by thermal emission of electrons. \n\nIn the experiments, the CE between the $\\mathrm{SiO}_{2}$ and the DI water was first performed, and Fig. 1c gives the results of the temperature effect on the decay of CE charges on the $\\mathrm{SiO}_{2}$ surfaces. It is obvious that the $\\mathrm{SiO}_{2}$ is negatively charged and the charge density on the $\\mathrm{SiO}_{2}$ surface is about $-810\\upmu\\mathrm{Cm}^{-2}$ (negative sign means that the charges are negative) after the contact with the DI water. In Fig. 1c, the temperature affects the decay of the negative charges on the $\\mathrm{SiO}_{2}$ surface significantly. The surface charge density on $\\mathrm{SiO}_{2}$ remains almost unchanged at $313\\mathrm{K}$ and slight decay of the surface charge density is observed at $343\\mathrm{K}$ . As the sample temperature continues to rise, the decay rate of the surface charges increases. But some charges (about $-180\\upmu\\mathrm{Cm}^{-2})$ cannot be removed even when the temperature rises up to $434\\mathrm{K}$ and $473\\mathrm{K}$ (these charges can be called as “sticky” charges that remain on surfaces even when the temperature is raised). For the removable charges, the decay behaviors are consistent with the thermionic emission theory, in which the electrons are considered to obtain more energy and the electron density decay faster at higher temperatures. Moreover, it is found that the charge density decay exponentially and the decay curve follows the electron thermionic emission model as described by the following equation, which was proposed in our previous studies (The curve fitting results are shown in Supplementary Fig. 3)17,18. Hence, the removable charges in the CE between the $\\mathrm{SiO}_{2}$ and the DI water can be identified as electrons. \n\n$$\n\\sigma=e^{-a t}\\sigma_{e}+\\sigma_{s}\n$$ \n\nwhere $\\sigma$ denotes the CE charge density on the sample surface, $\\sigma_{e}$ denotes the initial density of charges on the sample surface, which can be removed by thermal excitation, $\\sigma_{s}$ denotes the density of the “sticky” charges, which cannot be removed by heating and $t$ denotes the decay time. \n\nFor the “sticky” charges, charging and heating cycle tests were performed to observe their behaviors, as shown in Fig. 1d. In every cycle of the testes, the $\\mathrm{SiO}_{2}$ sample contacts with the DI water first, and then it is heated to $513\\mathrm{K}$ and maintains for 10 min to remove the electrons on the surface. In the first cycle, the $\\mathrm{SiO}_{2}$ is negatively charged when it contacts with the DI water, and the density of the “sticky” charges is $-180\\upmu\\mathrm{Cm}^{-2}$ as expected. It is found that the density of the “sticky” charges increases to $-300$ $\\upmu\\mathrm{Cm}^{-2}$ in the second cycle and it continuously increases with the number of the cycles. After five cycles of experiments, the density of the “sticky” charges reaches a saturation value, and there are not removable charges on the $\\mathrm{SiO}_{2}$ surface. These behaviors suggest that the “sticky” charges should be ions, such as $\\mathrm{O^{-}}$ ions, instead of electrons. As shown in Supplementary Fig. 4, in each contact with the DI water, both electrons and $0^{-}$ ions are attached on the surface. Electrons are emitted as temperature rises, while the $\\mathrm{O^{-}}$ ions cannot be removed in the subsequent heating if the temperature is not too high. In the next cycle of introducing water droplet, more $0^{-}$ ions are produced in the ionization reaction and accumulate on the $\\mathrm{SiO}_{2}^{-}$ surface since it has not reached saturation. With the increase of cycles on introducing water droplets, the concentration of $\\dot{\\mathrm{~O~}^{-}}$ ions continues to rise and more “available charge positions and densities” are filled, thus, it becomes harder for the $\\mathrm{SiO}_{2}$ to gain more electrons in the CE, resulting in a decrease of the electron density on the surface. A few cycles later, the density of the ions reaches a saturated value, which remains stable even in the followed heating process. \n\n![](images/093d5c2ecb2fadadecde1b1b28c3a9cac0ee0132780fdd586427fbb18f386420.jpg) \nFig. 1 Temperature effect on the CE between the DI water and the $\\mathbf{SiO}_{2}$ . (a) The setup of the charging experiments, where the negative charges generated on the $\\mathsf{S i O}_{2}$ surface could be electrons and $\\mathsf{O}^{-}$ ions induced by surface ionization reaction. ( $'0^{\\prime}$ is the Oxygen atom, ‘Si’ is the silicon atom and $'0^{-\\prime}$ is the $\\circled{\\scriptsize{1}}$ xygen ion). (b) The setup of AFM platform for the thermionic emission experiments. (c) The decay of the CE charge (induced by contacting with the DI water at room temperature) on the $\\mathsf{S i O}_{2}$ surface at different substrate temperatures. (d) The CE charge density on the $\\mathsf{S i O}_{2}$ sample surface in the charging (contacting with the DI water at room temperature) and heating (at $513\\mathsf{K}$ for $10\\mathsf{m i n}.$ ) cycle tests. (Error bar are defined as s. d.). \n\nBased on the analysis, it turns out that electrons can be distinguished from ions in the CE by performing the thermionic emission experiments. The removable and the “sticky” charges in the experiments are identified as electrons and ions, respectively. And the results suggest that there are both electron and ion transfers in the CE between the $\\mathrm{SiO}_{2}$ and the DI water. The density of transferred electrons is measured to be $-630\\upmu\\mathrm{Cm}^{-2}$ and the density of transferred ions is about $-180\\upmu\\mathrm{Cm}^{-2}$ . It means that the electron transfer, which account for $77\\%$ of the total charges, is dominant in the CE between $\\mathrm{SiO}_{2}$ and DI water in very first contact. \n\nEffects of the solutes and the liquid pH value on the CE. Further, the effects of the solutes in the liquid and $\\mathrm{\\pH}$ value of the liquid on the liquid–solid CE were studied. The CE between the $\\mathrm{SiO}_{2}$ and different aqueous solutions, including NaCl, HCl and NaOH solutions, was performed and the electron transfer and ion transfer in the CE were separated by the heat-induced charge decay experiments. Figure 2a gives the effect of the NaCl concentration on the transferred charge density in the CE between the $\\mathrm{SiO}_{2}$ and the $\\mathrm{\\DeltaNaCl}$ solution. It is found that the charge density on the $\\mathrm{SiO}_{2}$ surfaces decreases with the increase of the NaCl concentration. This result is consistent with the previous studies about the liquid–solid TENG, in which the salt solution is the liquid and the output of the TENG decreases with the increase of the salt concentration30,31. The effect was not clearly explained before, because there was no method to identify the charge carriers. Here, the decay of the charge density on the $\\mathrm{SiO}_{2}$ surfaces is performed at $433\\mathrm{K}$ after the CE between the $\\mathrm{SiO}_{2}$ and the NaCl solutions, and the results are shown in Fig. 2b. It can be seen that the charge density decays exponentially, which is the same as the CE between the $\\mathrm{SiO}_{2}$ and the DI water as introduced above. The density of removable charges (electrons) on the $\\mathrm{SiO}_{2}$ surfaces decreases with the increase of the NaCl concentration, while the “sticky” charges (ions) density remains almost unchanged when the $\\mathrm{SiO}_{2}$ contacts with the NaCl solutions of different concentrations. It implies that the decrease of the charge density on the $\\mathrm{SiO}_{2}$ induced by the increase of the NaCl concentration is mainly due to the decrease of the electron transfer, which might be caused by the increase of the dielectric constant of the NaCl solution that facilitate the discharge after charging. Different from electron transfer, the ion transfer will not be significantly affected by the NaCl concentration in the first contact (Fig. 2b). This result is easy to understand, because there are no $\\mathrm{Na^{+}}$ or $\\mathrm{Cl^{-}}$ in the ionization reaction (chemical formula 1), which produce the required $\\mathrm{O^{-}}$ ions on the $\\mathrm{SiO}_{2}$ surface. Figure 2c gives the CE charge density on the $\\mathrm{SiO}_{2}$ sample surface in the charging (contacting with $0.4\\mathrm{M}\\mathrm{NaCl}$ solution) and heating ( $.513\\mathrm{K}$ for 10 min) cycle tests. The results show that the saturated ion density in the CE between $0.4\\mathrm{M}$ NaCl solution and $\\mathrm{SiO}_{2}$ is slightly lower than that between DI water and $\\mathrm{SiO}_{2}$ (Fig. 1d). The difference in the saturated ion density may be caused by the covering of the crystallized NaCl on the $\\mathrm{SiO}_{2}$ surface in the subsequent heating processes, which blocks the progress of ionization reaction. \n\n![](images/a77b89984c55a72cb2fdd2da5ac5987e4c029ee9e3900b0b58d1848cfc344af6.jpg) \nFig. 2 Temperature effect on the CE between the $\\sin O_{2}$ and aqueous solutions. (a) The effects of the NaCl concentration on the CE between the $\\mathsf{S i O}_{2}$ and the ${\\mathsf{N a C l}}$ solutions. (b) The decay of the CE charge at $433\\mathsf{K}$ which is induced by contacting with the NaCl solutions. (c) The CE charge density on the $\\mathsf{S i O}_{2}$ sample surface in the charging (contacting with 0.4 M NaCl solution at room temperature) and heating (513 K for $10\\mathsf{m i n}.$ cycle tests. (d) The decay of the CE charge at $433\\mathsf{K},$ which is induced by contacting with the pH 11 HCl solution and the $\\mathsf{p H3N a O H}$ solution. The charging and heating cycle testes when the liquids are (e) the pH 11 NaOH solution and $(\\pmb{\\uparrow})$ the pH 3 HCl solution. (Error bar are defined as s. d.). \n\nDifferent from $\\mathrm{Na^{+}}$ or $\\mathrm{Cl}^{-}$ , it can be seen that the $\\mathrm{OH^{-}}$ plays an important role in the generation of the $0^{-}$ ions on the $\\mathrm{SiO}_{2}$ surface from the chemical formula 1. Hence, the density of the transferred ions on the $\\mathrm{SiO}_{2}$ surface may be affected by the pH value of the solutions. Figure 2d shows the decay of the surface charge density on the $\\mathrm{SiO}_{2}$ surface, which is produced by contacting with the $\\mathrm{pH}\\ 11\\ \\mathrm{NaOH}$ solution and $\\mathrm{pH}\\ 3\\ \\mathrm{H}\\dot{\\mathrm{Cl}}$ solution. When the $\\mathrm{pH}$ value of the solution increases to 11, the electron transfers decrease, and the density of transferred ions (about $-230\\upmu\\mathrm{Cm}^{-2},$ is slightly higher than that when the pH value of liquid is 7 (DI water). And the difference can also be observed in the charging and heating tests, in which the saturated ion density on the $\\mathrm{SiO}_{2}$ surface when the liquid is the $\\mathrm{pH}11$ $\\mathrm{\\DeltaNaOH}$ solution is higher than that when the liquid is the DI water, as shown in Fig. 2e. This is caused by the increase of the $\\mathrm{OH^{-}}$ concentration in the solution, which promotes the ionization reaction (chemical formula 1). When the $\\mathsf{p H}$ value of the solution changes to 3, the electron transfer direction and the polarity of the transferred ions on the $\\mathrm{SiO}_{2}$ surface reverse from negative to positive (Fig. 2d). And the charging and heating cycle tests in Fig. 2 f show that the positive ions also accumulate on the $\\mathrm{SiO}_{2}$ surface. In this case, the positive ions on the $\\mathrm{SiO}_{2}$ surface are produced by another ionization reaction, as shown below26–28. \n\n$$\n\\equiv\\mathrm{Si}-\\mathrm{OH}+\\mathrm{H}^{+}\\Leftrightarrow\\equiv\\mathrm{Si}-\\mathrm{OH}_{2}^{+}\n$$ \n\nThe effects of $\\mathrm{\\tt{pH}}$ value on the CE between liquids and various ceramics are shown in Supplementary Fig. 5. The results are similar to the pH effects on the $\\mathrm{SiO}_{2}$ surface. When the $\\mathsf{p H}$ value of the solution was 11, the transferred ions on the ceramic surfaces are negative as shown in Supplementary Fig. 5a–c. When the $\\mathsf{p H}$ value of the solution changes to 3, the polarity of the transferred ions also reverses to be positive as shown in Supplementary Fig. 5d–f. This means that the effects of $\\mathrm{\\pH}$ value on the ionization reaction for different ceramics are consistent. \n\nThese results show that no matter what the aqueous solution is, there are always both electron transfer and ion transfer in liquid–solid CE. The electron transfers between aqueous solution and solid is sensitive to solutes in the liquids, such as $\\mathrm{{Na^{+}}}$ , $\\mathrm{Cl^{-}}$ , $\\mathrm{OH^{-}}$ and $\\mathrm{H^{+}}$ etc. While the ion transfer is mainly affected by the $\\mathrm{\\pH}$ value of the solution, which dominates the ionization reactions on the insulator surfaces. \n\nSolid effects on the liquid–solid CE. As another side in the liquid–solid CE, different solids were also tested in the thermionic emission experiments. As shown in Fig. 3a–f, the CE charge decay in the CE between the DI water and different insulating ceramics was performed, including $\\mathrm{MgO}$ , $\\mathrm{Si}_{3}\\mathrm{N}_{4},$ $\\mathrm{Ta}_{2}\\mathrm{O}_{5}$ , $\\mathrm{HfO}_{2}.$ , $\\bar{\\bf A l}_{2}\\bf O_{3}$ and AlN. (The surface ionization reaction equations between water molecules and these materials are shown in Supplementary \n\n![](images/91c7e6789f65c5adbc5b8f337829bb6c4cc81d0b694ee5f7f74f889b499fc2db.jpg) \nFig. 3 Temperature effect on the CE between the DI water and the solids. The decay of CE charges (induced by contacting with the DI water at room temperature) on a $M g O$ , b $\\mathsf{S i}_{3}\\mathsf{N}_{4},$ c $\\mathsf{T a}_{2}\\mathsf{O}_{5}$ , d ${\\mathsf{H}}{\\mathsf{f}}{\\mathsf{O}}_{2}$ , e $A l_{2}O_{3},$ and f AlN surfaces at $433\\mathsf{K},$ and the amount of the electron transfer and the ion transfer in the CE between the DI water and different insulators. g The relation between the electron transfer to the ion transfer ratio and the DI water contact angle (WCA) of the materials. h The schematic of WCA effects on the ion transfer and electron transfer in liquid–solid CE. $\\gamma_{L},\\gamma_{S},$ and $\\gamma_{L-S}$ denote the liquid–gas interfacial tension, solid–gas interfacial tension and liquid–solid interfacial tension, respectively. (Error bar are defined as s. d.). \n\nNote 2). It is found that all of the charge decay curves follow the electron thermionic emission model, hence the removable charges are electrons and the “sticky” charges are ions as analyzed above. The electron transfer and the ion transfer are marked in Fig. 3a–f, it can be seen that the ratio of electron transfers to ion transfers (E/I) highly depends on the type of solid. For the CE between the AlN and the DI water, more than $88\\%$ of the total transferred charges are electrons. But in the CE between the $\\mathrm{Si}_{3}\\mathrm{N}_{4}$ and the DI water, electron transfer is only $31\\%$ of the total charge transfer. In order to test the interaction between a liquid and a solid at the interface, the water contact angle (WCA) of the ceramics was measured and the results are shown in Fig. 3g. It is noticed that the $\\mathrm{E/I}$ ratio slightly increases with the increase of the WCA when the WCA of materials is less than $90^{\\circ}$ . When the WCA of the materials increase to be larger than $90^{\\circ}$ , such as $92.2^{\\circ}$ for the $\\mathrm{SiO}_{2}$ and $97.0^{\\circ}$ for the AlN, the E/I ratio increases rapidly. For the $\\mathrm{SiO}_{2}$ and the AlN, the $\\mathrm{E/I}$ ratios are 3.5 and 7.5, respectively. Actually, the WCA is dependent on the liquid–solid, solid-gas, liquid-gas interfacial tensions, which are related to the interfacial energy of two phases, as shown in the Fig. 3h. The interfacial energy between a hydrophilic surface $({\\mathrm{WCA}}<90^{\\circ},$ and water is usually lager than that between a hydrophobic surface $({\\mathrm{WCA}}>90^{\\circ},$ and water. It means that the interaction between the water molecules and the solid surface with small WCA is usually stronger than that between water molecules and the solid surface with large WCA. And the Oxygen atoms or Hydrogen atoms in water molecules are more likely to form covalent bonds with the atoms on the hydrophilic surface. In other words, the surface ionization reaction is more likely to occur and leading to the generation of ions on the hydrophilic solid surface. On the contrary, the surface ionization reaction between the hydrophobic solid surfaces and water is less likely to occur, and the CE between the solid and aqueous solution is electron-dominated. \n\nIt needs to be mentioned that the polarity of the transferred electrons and transferred ions not necessary to be the same in liquid–solid CE. As shown in Fig. 3a, the MgO obtains electrons and positive ions at the same time in the CE between $\\mathrm{MgO}$ and DI water (Supplementary Fig. 6a), and the positive charge density on the $\\mathrm{MgO}$ surface increases in the heating due to the emission of electrons. For the CE between AlN and DI water, the AlN loses electrons and obtains negative ions (Supplementary Fig. 6b). These results suggest that the electron transfer and ion transfer in liquid–solid CE are independent of each other. Furthermore, it may be possible that the electron transfer and ion transfer could be segregated on different surface areas, but remain proved experimentally. \n\n![](images/0083083144788c3da6eee3cad97b9fa410c4e186bfe5b05392acb4822d728f72.jpg) \nFig. 4 Mechanism of liquid–solid CE and formation of electric doublelayer. a The liquid contacts a virgin surface (before CE). b The water molecules and ions in the liquid impact the virgin surface and electron transfer between the water and the surface. c The surface is charged and the charge carriers are mainly electrons $\\mathsf{\\backslash W C A>90^{\\circ}}$ , $\\mathsf{p H}=7\\mathrm{:}$ ), some ions may be generated on the surface caused by the ionization reaction etc. d The opposite polarity ions are attracted to migrate toward the charged surface by the Coulomb force, electrically screening the first charged layer. \n\nAccording to the results, the CE between solid and liquid can be affected by the $\\mathrm{\\pH}$ value of the aqueous solution, solutes in the aqueous solution and the hydrophilicity of the solids. Nevertheless, there is always electron transfer in the CE between liquid (aqueous solution) and solid. This result was predicted in the “two-step” model first proposed by Wang et al.32, but was not included at all in the classical explanation regarding the formation of the EDL. Combining the experiment results and the “two-step” model32, a new picture for the liquid–solid CE and the formation of the EDL is proposed, as shown in Fig. 4. In the first step, the liquid contacts a virgin solid surface (Fig. 4a), the molecules and ions, including $_\\mathrm{H}_{2}\\mathrm{O}$ , cation, anion etc., will impact the solid surface due to the thermal motion and the pressure from the liquid (Fig. 4b). During the impact, electrons will transfer between the solid atoms and water molecules owing to the overlap of the electron clouds of the solid atoms and water molecules18, and the ionization reaction may also occur simultaneously on the solid surface. Hence there will be both electrons and ions generated on the surface. As an example, the electron transfer plays a dominated role in the CE between the $\\mathrm{SiO}_{2}$ and DI water, as shown in Fig. 4c. In the second step, the opposite ions in the liquid would be attracted to migrate toward the charged surface by the electrostatic interactions, forming an $\\mathrm{EDL},$ as shown in Fig. 4d. \n\nAn atom with extra/deficient electrons are referred as ion, therefore, the transferred electrons on the solid surface is considered as the first step to make the “neutral” atoms on solid surface become ions in the “two-step” model32. From this perspective, the ions produced by the ionization reaction in the experiments can also be considered as the “neutral” atoms with extra electrons. The difference is that the transferred electrons directly induced by the collisions between the atoms in the liquid and the atoms on the solid surface were usually trapped in the surface states, while the extra electrons of the “neutral” atoms produced in the ionization reaction were trapped in the atomic orbitals of the atoms (the atomic orbitals can be considered as the special surface states of solids generated in the ionization reaction). There is no essential difference between the electrons in the surface states and those in the atomic orbitals. However, the potential barrier of the surface states to prevent the electrons from emitting in the heating process might be lower than that of atomic orbitals. Hence, the electrons in the surface states of the solid are removable, while the electrons in the atomic orbitals are tightly bonded on the solid surfaces. \n\nAlso, the surface charge density (electrons and ions) in the liquid–solid CE is not as dense as that appearing in text book drawing. The highest transferred electron density in our experiments is $-630\\upmu\\mathrm{C}\\mathrm{m}^{-2}$ in the CE between $\\mathrm{SiO}_{2}$ and DI water, which corresponds to ${\\sim}1$ excess electron per $250\\mathrm{nm}^{2}$ . Thus, the probability of electron transfer in liquid–solid CE is usually less than one out of $\\sim2500$ surface atoms. The transferred ion density in CE between $\\mathrm{SiO}_{2}$ and DI water is $-180\\upmu\\mathrm{C}\\mathrm{m}^{-2}$ , which corresponds to ${\\sim}10^{-}$ ion per $1000\\mathrm{nm}^{2}$ . Accordingly, the distance between two adjacent electrons on $\\mathrm{SiO}_{2}$ surface is ${\\sim}16\\mathrm{nm}$ , and the distance between two adjacent $\\mathrm{O^{-}}$ ions is $\\sim30\\mathrm{nm}$ as shown in Fig. 4c. These distances are much larger than the thickness of Stern layer, which is of the order of a few ångstroms20. Hence, the distance of two adjacent charges (electrons or/and ions) should be considered in the structure of the EDL. \n\n# Discussion \n\nIn conclusion, the CE between liquid and solid was performed and the temperature effect on the decay of the CE charge on the ceramic surfaces was investigated. It is revealed that there are both electron transfer and ion transfer in the liquid–solid CE. The results suggest that the solutes in the aqueous solution, such as $\\mathrm{Na^{+}}$ and $\\mathrm{Cl^{-}}$ etc., can reduce the electron transfer between aqueous solution and solid. And the ion transfers in the liquid–solid CE induced by the ionization reaction can be significantly affected by the pH value of the liquid. Besides, it is found that the CE between hydrophilic surfaces and aqueous solutions is likely dominated by ion transfer; and the CE between hydrophobic surfaces and aqueous solutions is more likely to be dominated by electron transfer. This is the first time that the “two-step” model about the formation of $\\mathrm{EDL},$ in which the electron transfer plays a dominant role in liquid–solid CE, is verified experimentally. Our results may have great implications in the studies of TENG and EDL. \n\n# Methods \n\nSample preparation. The $\\mathrm{SiO}_{2}$ layer was deposited on high doped silicon wafer by thermal oxidation. The $\\mathrm{Si}_{3}\\mathrm{N}_{4},$ $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ , $\\mathrm{Ta}_{2}\\mathrm{O}_{5}$ , MgO, $\\mathrm{HfO}_{2}$ AlN layers were deposited on high doped silicon surfaces by magnetron sputtering, and the thickness of all the layers were $100\\mathrm{nm}$ . The DI water with a resistivity of $18.2\\mathrm{M}\\Omega$ cm used here was produced by deionizer (HHitech, China). Before the experiments, all the samples were heated for $10\\mathrm{min}$ at $513\\mathrm{K}$ to remove the charge on the surfaces. After the heat treatment, the charge density of the ceramic surfaces was measured to be about $0\\upmu\\mathrm{C}\\mathrm{m}^{-2}$ , except the $\\mathrm{MgO}$ and $\\mathrm{Si}_{3}\\mathrm{N}_{4}$ . The “sticky” charge density on the $\\mathrm{{\\bfMgO}}$ and $\\mathrm{Si}_{3}\\mathrm{N}_{4}$ surface was about $800\\upmu\\mathrm{C}\\mathrm{m}^{-2}$ and $-250\\upmu\\mathrm{C}\\mathrm{m}^{=2}$ before the CE with solutions, respectively. The “sticky” charges on the $\\mathrm{MgO}$ and $\\mathrm{Si}_{3}\\mathrm{N}_{4}$ surfaces may be the ions generated by the ionization reaction between the samples and the water molecules in the air, since the $\\mathrm{{\\calMgO}}$ and $\\mathrm{Si}_{3}\\mathrm{N}_{4}$ are most hydrophilic in these ceramics. \n\nKPFM experiments. The experiments were performed on commercial AFM equipment Multimode 8 (Bruker, USA). NSC 18 (MikroMash, USA; Au coated; tip radius: $25\\mathrm{nm};$ spring constant: $2.8\\mathrm{Nm}^{-1}$ ) was used as the conductive tip here. The sample temperature was controlled by the sample heater and the tip temperature was controlled by the tip heater independently. In all the experiments, the temperature of the sample and the tip remained consistent. The tapping amplitude was $350\\mathrm{mV}$ , the scan size was $5\\upmu\\mathrm{m}$ and the lift height was set to $50\\mathrm{nm}$ in the KPFM measurements. In order to acquire the data from a big region, the KPFM was manual operated to scan different positions on the whole sample surface ${\\sqrt{>20}}$ positions). All the heating and charge measurements are performed in an Ar atmosphere. The changes of surface charge density were demonstrated not caused by the adsorption and desorption of the water molecules on $\\mathrm{SiO}_{2}$ surface, as shown in Supplementary Note 3 and Supplementary Fig. 7. And the observed changes in the surface potential in our experiments were not due to the temperature effects on the measurements, as shown in Supplementary Note 4 and Supplementary Fig. 8. \n\nCalculation of surface charge density. In previous studies, the transferred charge density on the insulating surfaces was calculated by the following equation: \n\n$$\n\\Delta\\sigma=\\frac{\\Delta V\\varepsilon_{0}\\varepsilon_{s a m p l e}}{t_{s a m p l e}}\n$$ \n\nwhere $\\Delta\\sigma$ denotes the transferred charge density, $\\Delta V$ denotes the change of surface potential after the CE, $\\scriptstyle{\\varepsilon_{0}}$ denotes the vacuum dielectric constant, $\\varepsilon_{s a m p l e}$ denotes the relative dielectric constant of the sample and $t_{s a m p l e}$ denotes the thickness of the insulating layer. \n\nIn our experiments, the absolute charge density on the sample surface need to be calculated. In this case, the contact potential difference (CPD) between the tip and the substrate of the samples should be considered, and the absolute charge density on the insulating surfaces can be expressed as following (the calculations are shown in the Supplementary Note 5 and Supplementary Fig. 9): \n\n$$\n\\sigma=\\frac{(V+C P D_{t i p-s a m p l e})\\varepsilon_{0}\\varepsilon_{s a m p l e}}{t_{s a m p l e}}\n$$ \n\nwhere $\\sigma$ denotes the absolute charge density on the sample surfaces, $V$ denotes the surface potential of the samples and the $C P D_{t i p-s a m p l e}$ is the CPD between the tip and the substrate of the samples. \n\n# Data availability \n\nAll data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Information. Additional data related to this paper may be requested from the authors. The source data underlying all figures can be found in the Source Data file. \n\nReceived: 22 August 2019; Accepted: 16 December 2019; Published online: 21 January 2020 \n\n# References \n\n1. Gibson, H. Linear free energy relations. V. triboelectric charging of organic solids. J. Am. Chem. Soc. 97, 3832–3833 (1975). \n2. Sakaguchi, M., Makino, M., Ohura, T. & Iwata, T. Contact electrification of polymers due to electron transfer among mechano anions, mechano cations and mechano radicals. J. Electrostat. 72, 412–416 (2014). \n3. McCarty, L. & Whitesides, G. Electrostatic charging due to separation of ions at interfaces: contact electrification of ionic electrets. Angew. Chem. Int. Ed. 47, 2188–2207 (2008). \n4. Sutka, A. et al. The role of intermolecular forces in contact electrification on polymer surfaces and triboelectric nanogenerators. Energy Environ. Sci. 12, 2417–2421 (2019). \n5. Pandey, R., Kakehashi, H., Nakanishi, H. & Soh, S. Correlating material transfer and charge transfer in contact electrification. J. Phys. Chem. C 122, 16154–16160 (2018). \n6. Baytekin, H. et al. The mosaic of surface charge in contact electrification. Science 333, 308–312 (2011). \n7. Xu, M. et al. A highly-sensitive wave sensor based on liquid-solid interfacing triboelectric nanogenerator for smart marine equipment. Nano Energy 57, 574–580 (2019). \n8. Cho, H. et al. Toward sustainable output generation of liquid-solid contact triboelectric nanogenerators: the role of hierarchical structures. Nano Energy 56, 56–64 (2019). \n9. Lin, Z., Cheng, G., Lin, L., Lee, S. & Wang, Z. L. Water-solid surface contact electrification and its use for harvesting liquid-wave energy. Angew. Chem. Int. Ed. 52, 12545–12549 (2013). \n10. Yang, X., Chan, S., Wang, L. & Daoud, W. Water tank triboelectric nanogenerator for efficient harvesting of water wave energy over a broad frequency range. Nano Energy 44, 388–398 (2018). \n11. Brown, M., Goel, A. & Abbas, Z. Effect of electrolyte concentration on the stern layer thickness at a charged interface. Agew. Chem. Int. Ed. 55, 3790–3794 (2016). \n12. Toney, M. et al. Voltage-dependent ordering of water-molecules at an electrode-electrolyte interface. Nature 368, 444–446 (1994). \n13. Li, C. et al. In situ probing electrified interfacial water structures at atomically flat surfaces. Nat. Mater. 18, 697–701 (2019). \n14. Janssen, M., Griffioen, E., Biesheuvel, P., Roij, R. & Erne, B. Coulometry and calorimetry of electric double layer formation in porous electrodes. Phys. Rev. Lett. 119, 166002 (2017). \n15. Lowell, J. & Rose-Innes, A. Contact electrification. Adv. Phys. 29, 947–1023 (1980). \n16. Lacks, D. & Sankaran, R. Contact electrification of insulating materials. J. Phys. D: Appl. Phys. 44, 453001 (2011). \n17. Lin, S. et al. Electron transfer in nanoscale contact electrification: effect of temperature in the metal-dielectric case. Adv. Mater. 31, 1808197 (2019). \n18. Xu, C. et al. On the electron-transfer mechanism in the contact-electrification effect. Adv. Mater. 30, 1706790 (2018). \n19. Lin, S., Xu, L., Zhu, L., Chen, X. & Wang, Z. L. Electron transfer in nanoscale contact electrification: photon excitation effect. Adv. Mater. 31, 1808197 (2019). \n20. J. Israelachvili, Intermolecular and Surface Forces, University of California Santa Barbara, California, USA, 2011. \n21. Terris, B. D., Stern, J. E., Rugar, D. & Mamin, H. J. Contact electrification using force microscopy. Phys. Rev. Lett. 63, 2669–2672 (1989). \n22. Lin, S. & Shao, T. Bipolar charge transfer induced by water: experimental and first-principles studies. Phys. Chem. Chem. Phys. 19, 29418–29423 (2017). \n23. Nonnenmacher, M., O’Boyle, M. P. & Wickramasinghe, H. K. Kelvin probe force microscopy. Appl. Phys. Lett. 58, 2921–2923 (1991). \n24. Schonenberger, C. & Alvarado, S. F. Observation of single charge-carriers by force microscopy. Phys. Rev. Lett. 65, 3162–3164 (1990). \n25. Raiteri, R., Martinoia, S. & Grattarola, M. pH-dependent charge density at the insulator-electrolyte interface probed by a scanning force microscope. Biosens. Bioelectron. 11, 1009–1017 (1996). \n26. Davis, J., James, R. & Leckie, J. Surface ionization and complexation at oxidewater interface. 1. Computation of electrical double-layer properties in simple electrolytes. J. Colloid Interf. Sci. 63, 480–499 (1978). \n27. Lagstrom, T., Gmur, T., Quaroni, L., Goel, A. & Brown, M. Surface vibrational structure of colloidal silica and its direct correlation with surface charge density. Langmuir 31, 3621–3626 (2015). \n28. Bousse, L., Rooij, N. & Bergveld, P. Operation of chemically sensitive fieldeffect sensors as a function of the insulator-electrolyte interface. IEEE T. Electron Dev. 30, 1263–1270 (1983). \n29. Gmur, T., Goel, A. & Brown, M. Quantifying specific ion effects on the surface potential and charge density at silica nanoparticle-aqueous electrolyte interfaces. J. Phys. Chem. C 120, 16617–16625 (2016). \n30. Cao, S. et al. Fully-enclosed metal electrode-free triboelectric nanogenerator for scavenging vibrational energy and alternatively powering personal electronics. Adv. Eng. Mater. 21, 1800823 (2019). \n31. Choi, D. et al. Spontaneous occurrence of liquid-solid contact electrification in nature: toward a robust triboelectric nanogenerator inspired by the natural lotus leaf. Nano Energy 36, 250–259 (2017). \n32. Wang, Z. L. & Wang, A. On the origin of contact-electrification. Mater. Today 30, 34–51 (2019). \n\n# Acknowledgements \n\nWe would like to thank Prof. Ding Li, Prof. Xiangyu Chen, Dr. Fei Zhan, and Dr Jianjun Luo for helpful discussions. Research was supported by the National Key R & D Project from Minister of Science and Technology (2016YFA0202704), National Natural Science Foundation of China (Grant Nos. 51605033, 51432005, 5151101243, 51561145021), Beijing Municipal Science & Technology Commission (Z171100000317001, Z171100002017017, Y3993113DF). \n\n# Author contributions \n\nS.L. and Z.L.W. conceived the idea and designed the experiment. S.L. carried out the liquid–solid contact electrification experiments. A.C.W., S.L. and Z.L.W. contributed to the electric double-layer theory. S.L., L.X. and Z.L.W. wrote the manuscript. All the authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 019-14278-9. \n\nCorrespondence and requests for materials should be addressed to Z.L.W. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41467-020-18062-y", + "DOI": "10.1038/s41467-020-18062-y", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-18062-y", + "Relative Dir Path": "mds/10.1038_s41467-020-18062-y", + "Article Title": "Iron phthalocyanine with coordination induced electronic localization to boost oxygen reduction reaction", + "Authors": "Chen, KJ; Liu, K; An, PD; Li, HJW; Lin, YY; Hu, JH; Jia, CK; Fu, JW; Li, HM; Liu, H; Lin, Z; Li, WZ; Li, JH; Lu, YR; Chan, TS; Zhang, N; Liu, M", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Iron phthalocyanine (FePc) is a promising non-precious catalyst for the oxygen reduction reaction (ORR). Unfortunately, FePc with plane-symmetric FeN4 site usually exhibits an unsatisfactory ORR activity due to its poor O-2 adsorption and activation. Here, we report an axial Fe-O coordination induced electronic localization strategy to improve its O-2 adsorption, activation and thus the ORR performance. Theoretical calculations indicate that the Fe-O coordination evokes the electronic localization among the axial direction of O-FeN4 sites to enhance O-2 adsorption and activation. To realize this speculation, FePc is coordinated with an oxidized carbon. Synchrotron X-ray absorption and Mossbauer spectra validate Fe-O coordination between FePc and carbon. The obtained catalyst exhibits fast kinetics for O-2 adsorption and activation with an ultralow Tafel slope of 27.5mVdec(-1) and a remarkable half-wave potential of 0.90V. This work offers a new strategy to regulate catalytic sites for better performance. Iron phthalocyanine with a 2D structure and symmetric electron distribution around Fe-N-4 active sites is not optimal for O-2 adsorption and activation. Here, the authors report an axial Fe-O coordination induced electronic localization strategy to enhance oxygen reduction reaction performance.", + "Times Cited, WoS Core": 540, + "Times Cited, All Databases": 553, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000568893000012", + "Markdown": "# Iron phthalocyanine with coordination induced electronic localization to boost oxygen reduction reaction \n\nKejun Chen1,9, Kang Liu1,9, Pengda $\\mathsf{A n}^{1,2}$ , Huangjingwei Li1, Yiyang Lin1, Junhua Hu 3, Chuankun Jia4, Junwei $\\mathsf{F u}^{1}$ , Hongmei Li1, Hui Liu5, Zhang Lin $\\textcircled{1}$ 5, Wenzhang ${\\mathsf{L i}}^{6},$ Jiahang $\\mathsf{L i}^{7}$ , Ying-Rui $\\mathsf{L u}^{8}$ , Ting-Shan Chan8, Ning Zhang2 & Min Liu 1✉ \n\nIron phthalocyanine (FePc) is a promising non-precious catalyst for the oxygen reduction reaction (ORR). Unfortunately, FePc with plane-symmetric $\\mathsf{F e N}_{4}$ site usually exhibits an unsatisfactory ORR activity due to its poor $\\mathsf{O}_{2}$ adsorption and activation. Here, we report an axial Fe–O coordination induced electronic localization strategy to improve its $\\mathsf{O}_{2}$ adsorption, activation and thus the ORR performance. Theoretical calculations indicate that the Fe–O coordination evokes the electronic localization among the axial direction of $0-F e N_{4}$ sites to enhance $\\mathsf{O}_{2}$ adsorption and activation. To realize this speculation, FePc is coordinated with an oxidized carbon. Synchrotron X-ray absorption and Mössbauer spectra validate Fe–O coordination between FePc and carbon. The obtained catalyst exhibits fast kinetics for $\\mathsf{O}_{2}$ adsorption and activation with an ultralow Tafel slope of $27.5\\mathsf{m V}\\mathsf{d e c}^{-1}$ and a remarkable half-wave potential of $0.90{\\mathrm{V}}$ . This work offers a new strategy to regulate catalytic sites for better performance. \n\nSitmenricine st,htceh oalxeyntgiecergnaycrteifvdfiauctcietoinocnyofroefoaxfcyutigeolen mines the energy efficiency of fuel cells and metal-air bat- Rnt)dodmaicrectcealtlle–yr tdrebtteahrte$(\\mathrm{O}_{2})$ kinetics of ORR is crucial for these devices1–6. Though platinum (Pt)-based catalysts exhibit excellent $\\mathrm{O}_{2}$ adsorption and activation abilities in ORR, the high price and low reserve sternly restrict their large-scale applications $7-10$ . Exploring non-Pt ORR catalysts with high efficiency is imperative for further development of fuel cells and metal–air batteries11–13. Among the reported non- $\\cdot\\mathrm{Pt}$ ORR catalysts, iron phthalocyanine (FePc) molecular catalyst has aroused much attentions due to its special $\\mathrm{FeN_{4}}$ active site and low reaction energy barrier during ORR processes14–16. However, FePc possesses a typical two dimensional and plane symmetric structure, which leads to the symmetric electron distribution in the well-defined $\\mathrm{FeN_{4}}$ -active sites and is not conducive to the $\\mathrm{O}_{2}$ adsorption and activation17,18. Therefore, breaking the symmetry of electronic density would be an effective strategy to enhance the $\\mathrm{O}_{2}$ adsorption/activation and then greatly improve the ORR activity of the FePc catalyst. \n\nFrom the molecular structure, FePc with a tetracoordinate planar $\\mathrm{FeN_{4}}$ center offers extra coordination sites in the axial direction19,20, suggesting the symmetric electronic density can be modulated by suitable axial coordination20–23. Generally, the organic ligands with rich electron-donating functional groups, including oxygenic, nitrogenous, and sulfurous species, can be easily employed to coordinate with $\\mathrm{FePc}^{24-26}$ . However, organic ligands are not favored for electrocatalysis due to their poor conductivity. Modifying the surface of conductive carbon materials with oxygenic groups for stronger electron donation to FePc provides an alternative way to overcome the problem of conductivity, and realize axial coordination of $\\mathrm{O-FeN_{4}}$ sites17,26,27. The axial coordination of $_{\\mathrm{O-FeN_{4}}}$ can break the electronic distribution symmetry of Fe, leading to better oxygen adsorption and activation abilities, and superior ORR activity than those of the FePc catalyst with symmetric $\\mathrm{FeN_{4}}$ sites. \n\nIn this work, we design a composite catalyst (FeAB–O) by coordination of the FePc molecule with oxygen-containing groups on an $\\mathrm{O}_{2}$ plasma-treated acetylene black (AB–O) matrix to achieve efficient $\\mathrm{O}_{2}$ adsorption and ORR. Theoretical calculations show that the axial O coordination $\\mathrm{(O-FeN_{4})}$ sites greatly break the electronic distribution symmetry of Fe and lead to electron localization on O. The obvious electronic localization on $_{\\mathrm{O-FeN_{4}}}$ sites is beneficial for the axial $\\mathrm{O}_{2}$ adsorption and activation. X-ray adsorption experiments and the $\\mathrm{O}_{2}$ adsorption/ desorption tests confirm the axial O coordination and outstanding $\\mathrm{O}_{2}$ adsorption capacity of the FeAB–O catalyst, respectively. The ORR performance measurements show that the optimized FeAB–O catalyst has an ultralow Tafel slope of $2\\mathsf{\\Tilde{7}.5\\ m V\\ d e c^{-1}}$ and a superior half-wave potential of $0.90\\mathrm{V}$ vs. reversible hydrogen electrode (RHE), which is 30 and $50\\mathrm{mV}$ higher than FePc supported onto acetylene black (AB) without axial O coordination $({\\mathrm{FePc}}/{\\mathrm{AB}})$ and $\\mathrm{Pt/C},$ respectively. This work opens a new avenue to improve the ORR performance of metal phthalocyanine catalysts, and inspires electronic localization of active sites for regulating catalytic reaction activity. \n\n# Results \n\nTheoretical calculations. Axial O coordination in FeAB–O and no O coordination in FePc/AB were clearly showed in the schematic diagrams (Fig. 1a), which leads to obvious differences on the electron localization functions (Fig. 1b). As expected, the FePc/AB shows a symmetric charge distribution. Instead, strong electronic localization on the axial O atom accompanying with axial asymmetrical electronic distribution of $\\mathrm{O-FeN_{4}}$ sites can be observed in FeAB–O. By analyzing the charge density differences and spin density (Supplementary Figs. 1 and 2), we found that the charges number and spin polarization of the symmetrical $\\mathrm{FeN_{4}}$ site did not significantly change, due to their weaker interaction. However, the axial O coordination accepts partial charges from the $\\mathrm{FeN_{4}}$ site to form the electron localization in $\\mathrm{FeAB-O}^{28-30}$ , which break the symmetry of electronic density near the $\\mathrm{FeN_{4}}$ site and change the spin polarization of $\\mathrm{FeN_{4}}$ site, obviously. \n\nTo study the interaction between catalysts and the adsorbed $\\mathrm{O}_{2}$ , the $\\mathrm{O}_{2}$ adsorption energy, charge density differences (between catalysts and adsorbed $\\mathrm{O}_{2}$ ), Bader charge analysis, projected density of states (PDOS), and spin density were performed (Fig. 1c, Supplementary Figs. 3 and $4)^{31}$ . As predicted, the FeAB–O shows much higher $\\mathrm{O}_{2}$ adsorption energy of $0.92\\mathrm{eV}$ than that of $\\mathrm{FePc/AB}$ with $0.72\\mathrm{eV}$ . Correspondingly, the charge transfers from FeAB–O and FePc/AB to the adsorbed $\\mathrm{O}_{2}$ (Fig. 1c) are 0.38 and $0.28~e_{;}$ respectively. In addition, the PDOS and spin density of ${{\\mathrm{O}}_{2}}^{*}$ adsorption on the FeAB–O show that the $3d$ electrons of Fe and the $2p$ electrons of $\\mathrm{~O~}$ form stronger hybrid states below the Fermi level, and the spin polarization of oxygen molecule was broken (Supplementary Figs. 3 and 4). These results reveal that electronic localization on axial O coordination $\\mathrm{(O-FeN_{4}}$ sites) enhances $\\mathrm{O}_{2}$ adsorption and activation. \n\nTo study the effect of electronic localization on the ORR processes, the free energies of ORR pathways on FeAB–O and FePc/AB were calculated (Fig. 1d). The free energy diagrams also show that the intermediate species adsorbed on FeAB–O is more stable than that on $\\mathrm{Fe/AB}$ . Both the rate-determining steps on FeAB–O and FePc/AB are the oxygen adsorption/activation steps: \n\n$$\n\\mathrm{O}_{2}{^{*}}+\\mathrm{H}^{+}+e^{-}\\rightarrow\\mathrm{OOH}{^{*}}\n$$ \n\nThus, the stable adsorption of reactant (oxygen) can facilitate the process of ORR. The corresponding overpotential of ORR on FeAB–O and FePc/AB are 0.70 and $\\bar{0.80\\mathrm{V}}$ , respectively, suggesting the superior ORR performance of FeAB–O than that of FePc/AB. Therefore, the axial Fe–O coordination-induced electronic localization to improve the $\\mathrm{O}_{2}$ adsorption and activation can boost the ORR performance. \n\nCatalyst synthesis and characterization. Inspired by the theoretical prediction, the FeAB–O catalyst was prepared by compositing of FePc with the AB–O in dimethyformamide (DMF) solution. The control sample without O coordination (FePc/AB) was obtained by direct physical mixture of FePc and AB. X-ray diffraction (XRD) patterns and Fourier transform infrared (FTIR) spectra reveal that both FeAB–O and FePc/AB are comprised of carbon and FePc (Fig. 2a and Supplementary Fig. 5)32,33. Scanning electron microscope (SEM) and transmission electron microscope (TEM) images (Supplementary Figs. 6a–d and 7a) show uniform carbon nanoparticles, and there is no agglomerate FePc (Supplementary Fig. 6e) to be detected on the carbon matrix in FeAB–O. The elemental mapping from Supplementary Fig. 7b–f display overlapped distribution of C, N, O, and Fe, verifying the uniform distribution of FePc in FeAB–O. \n\nIn order to investigate the presence of axial O coordination, high-resolution X-ray photon spectroscopy (XPS) spectra and synchrotron X-ray absorption spectra were conducted (Fig. 2b–d). The fitted ratio of Fe–O to Fe–N bonds in FeAB–O shows obvious increase compared with that in $\\mathrm{FePc}/\\mathrm{AB}^{34}$ , indicating more axial O coordination with $\\mathrm{FeN_{4}}$ sites in FeAB–O. X-ray absorption nearedge spectra (XANES) of Fe K-edge (Fig. 2c) show obvious positive shift in FeAB–O compared with in FePc/AB, indicating the change of electronic structure of $\\mathrm{Fe}^{35}$ . Moreover, a pre-edge peak around $7114\\mathrm{eV}$ can be indexed to the square-planar and centrosymmetric $\\mathrm{Fe-N_{4}}$ structure of $\\mathrm{FePc}^{36-38}$ . It should be mentioned that FeAB–O exhibits a lower peak intensity of in-plane $\\mathrm{FeN_{4}}$ structure than that of $\\mathrm{FePc/AB}$ , which can be attributed to the axial coordination breaking the in-plane $\\mathrm{Fe-N_{4}}$ structure17,39. Additionally, extended X-ray absorption fine structure (EXAFS) spectra of Fe K-edge show that the coordination number of Fe in FeAB–O is higher than the precise four nitrogen-coordination $\\mathrm{(FeN_{4})}$ and lower than the six-oxygen coordination $\\left(\\mathrm{FeO}_{6}\\right)$ in ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ , respectively40,41. These characterization results prove the formation of axial O coordination between the FePc and oxygen group of AB–O in FeAB-O. \n\n![](images/e3d1c9689c872014b61e46e84d7a05a9366778b0701e83088445606aa7289dec.jpg) \nFig. 1 Theoretical calculations. a Molecular structure models. b Electron localization functions and c Bader charge transfers and the $\\mathsf{O}_{2}$ adsorption energies of FeAB–O and FePc/AB. d Free energy diagrams of ORR pathways on FeAB–O and $\\mathsf{F e P c/A B}$ . \n\n![](images/6aa46ffab8c96e10fff9ce0c6862d1ef1b526f29f16a8c3a8ce504c99344b207.jpg) \nFig. 2 Structure characterization. a $x{\\mathsf{R D}}$ patterns of the pristine FeAB–O, FePc/AB, AB, AB–O, and FePc. b $\\mathsf{X P S}$ Fe $2p$ spectra of the FeAB–O and $\\mathsf{F e P c/A B}$ . c XANES spectra at Fe K-edge of the FeAB–O, $\\mathsf{F e P c/A B}$ , Fe, and $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ . d Extended $\\mathsf{X}$ -ray absorption fine structure (EXAFS) spectra of Fe K-edge in the FeAB–O, FePc/AB, and $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ . \n\n![](images/ccac54dff5c8253de92f0bafae4c88d7bcfdfb502c8d1d0aff8dab1c0abf7853.jpg) \nFig. 3 The Oxygen adsorption ability. a $^{57}\\mathsf{F e}$ Mössbauer transmission spectrum. b The oxygen adsorption–desorption tests. c TGA curves in air atmosphere. d The $\\mathsf{O}_{2}$ -TPD curves of FeAB–O and $\\mathsf{F e P c/A B}$ . \n\nTo obtain more structure information, the $^{57}\\mathrm{Fe}$ Mössbauer spectra were collected at $300\\mathrm{K}$ . As shown in Fig. 3a, the Mössbauer spectrum of FePc/AB has a doublet peaks (D1), which can be assigned to the square planar $\\mathrm{FeN_{4}}$ species20. As for FeAB–O, there is a small D1 doublet peaks and two obvious D2 and D3 doublet peaks. The D2 peaks are from the $\\mathrm{O-FeN_{4}}$ species, and the D3 peaks can be attributed to the $\\mathrm{O-FeN_{4}}$ sites with surface-adsorbed $\\mathrm{O}_{2}$ molecule $(\\mathrm{O-FeN}_{4}{\\mathrm{-O}_{2}})^{39}$ . No clear $\\mathrm{O}_{2}$ adsorption signal can be observed in FePc/AB. These results confirmed the axial O coordination of $\\mathrm{O-FeN_{4}}$ and the enhanced $\\mathrm{O}_{2}$ adsorption. \n\nTo prove the enhanced $\\mathrm{O}_{2}$ adsorption, the $\\mathrm{O}_{2}$ adsorption–desorption performances were measured (Fig. 3b–d and Supplementary Fig. 8). Obviously, FeAB–O exhibits stronger $\\mathrm{O}_{2}$ adsorption response than FePc/AB, suggesting better $\\mathrm{O}_{2}$ adsorption ability of FeAB–O than that of $\\mathrm{FePc/AB^{42}}$ . The $\\mathrm{O}_{2}$ temperature-programmed desorption (TPD) measurements were also performed to investigate the $\\mathrm{O}_{2}$ adsorption property. According to the thermogravimetry analysis (TGA) of FeAB–O and FePc/AB (Fig. 3c), the weight loss at 380 and $507^{\\circ}\\mathrm{C}$ can be ascribed to the decomposition of FePc and carbon, respectively. In Fig. 3d, the $\\mathrm{O}_{2}$ -desorption peaks located at $340^{\\circ}\\bar{\\mathrm{C}}$ can be assigned to the release of chemistry-adsorbed $\\mathrm{O}_{2}$ in the samples43. Interestingly, the $\\mathrm{O}_{2}$ -desorption peak of FeAB–O is higher than that of $\\mathrm{FePc/AB}$ , indicating the robust $\\mathrm{O}_{2}$ adsorption ability of FeAB–O. \n\nEvaluating catalyst performance for ORR. To identify the electrochemical ORR properties of catalysts, the cyclic voltammetry (CV) was measured in $0.1\\mathrm{M}\\mathrm{KOH}$ . As presented in Fig. 4a, the CV curve of FeAB–O in $\\mathrm{N}_{2}$ -saturated electrolyte contains two pairs of peaks located at 0.8 and $0.3\\mathrm{V}$ . The former is indexed to the reduction/oxidation peaks of $\\mathrm{Fe}^{3+}/\\mathrm{Fe}^{2+}$ , the latter is signed to redox couple of $\\mathrm{Fe}^{2+}/\\mathrm{Fe}^{\\dot{+}38}$ . With the increasing of dissolved $\\mathrm{O}_{2}$ molecule, obvious new reduction peaks located at about $0.9\\mathrm{V}$ occur and increase, even beyond the reduction peak of $\\mathrm{Fe}^{3+}/\\mathrm{Fe}^{2+}$ , suggesting the active site of variable $\\mathrm{O-FeN_{4}}$ . However, the $\\mathrm{FePc}/$ AB and the pristine FePc display was negligible in these two groups of peaks in Supplementary Fig. 9a, suggesting that the oxygenic carbon coordination with FePc via Fe–O is beneficial for electronic delocalization of Fe to form the active site. The CV curves of the control samples under $\\Nu_{2}$ and $\\mathrm{O}_{2}$ -saturated electrolyte were also conducted and shown in Supplementary Fig. 9b–d. All the samples exhibit obvious oxygen reduction peaks and FeAB–O displays the most positive potential, indicating the optimal ORR performance of FeAB–O. \n\nNext, the linear scan voltammetry (LSV) curves of FeAB–O and $\\mathrm{FePc/AB}$ were conducted to further study their ORR properties (Fig. 4b). The theoretical calculations, electrochemical impedance spectroscopy (EIS), and resistance tests (Supplementary Fig. 10 and Supplementary Note 1) demonstrate that the electrons can transfer from the electrode to FePc molecule through the Fe–O bonds with the help of electric field. Thus, FeAB–O presents a remarkable $E_{1/2}$ of $0.90{\\mathrm{V}}$ and a calculated kinetic current density $(J_{\\mathrm{k}})$ of $24.0\\mathrm{mA}\\mathrm{cm}^{-2}$ at $0.88{\\mathrm{V}}$ , which are much superior to FePc/AB $(E_{1/2}=0.87\\:\\mathrm{V}$ , $J_{\\mathrm{k}}{=}1.9\\mathrm{mA}\\mathrm{cm}^{-2}$ at $0.88\\mathrm{V})$ and $\\mathrm{Pt/C}$ $(E_{1/2}=0.85\\:\\mathrm{V}$ , $J_{\\mathrm{k}}{=}4.0\\mathrm{mA}\\mathrm{cm}^{-2}$ at $0.88\\mathrm{V},$ . Instead, the AB, AB–O, and FePc only exhibit inferior half-wave potentials $(E_{1/2})$ and limited current density $\\left(J_{\\mathrm{L}}\\right)$ in Supplementary Fig. 11a. Moreover, FePc is physically mixed with AB–O (FePc/AB–O) to exclude the effect of carbon substrate. As expected, the FePc/AB–O displays the alike performance of FePc/ \n\n![](images/df6c54bf971fefb00ff301e26a5d726da6f45350267e471d52fca8c9458e71ca.jpg) \nFig. 4 Electrochemical ORR performances. a Cyclic voltammetry profiles of FeAB–O in ${\\sf N}_{2}$ -saturated and $\\mathsf{O}_{2}$ -dissolved 0.1 M KOH solution. b ORR polarization curves of FeAB–O, ${\\mathsf{F e P c/A B}}.$ , and $\\mathsf{P t/C}$ in $\\mathsf{O}_{2}$ -saturated 0.1 M KOH. c Values of half-wave potentials and $J_{\\mathrm{k}}$ at $0.88\\mathsf{V}$ of FeAB–O, FePc/AB, and Pt/C. d Corresponding Tafel plots of FeAB–O, FePc/AB, and $\\mathsf{P t/C}$ . e Electron transfer numbers and proportion of produced $H_{2}O_{2}$ in FeAB–O and $\\mathsf{P t/C.f l{\\mathsf{I}}\\mathsf{I}/\\mathsf{I}}$ chronoamperometry responses (in $\\mathsf{O}_{2}$ -saturated $0.1{\\ensuremath{\\mathsf{M}}}$ KOH with a rotation of $1600\\mathsf{r p m})$ of FeAB–O and $\\mathsf{P t/C}$ . \n\nAB in Supplementary Fig. 11b. Based on these results, the introduction of axial O coordination in $\\mathrm{O-FeN_{4}}$ sites can greatly boost the performance of ORR. The ORR catalytic activity of FeAB–O is superior to most of reported Fe–N–C catalysts in recent literatures (Supplementary Table 1). Notably, the FeAB–O has the most excellent Tafel slope of $27.5\\:\\mathrm{mV}\\:\\mathrm{diec^{-1}}$ , which is lower than those of FePc/AB $(37.5\\mathrm{mV}\\mathrm{dec}^{-1})_{} $ and $\\mathrm{Pt/C}$ ( $71\\mathrm{mV}$ $\\operatorname*{dec}^{-1}.$ ), confirming the fastest kinetic process of FeAB–O for $\\mathrm{O}_{2}$ adsorption/activation and ORR. \n\nThe selectivity of ORR in FeAB–O was studied by rotating ring disk electrode (RRDE) measurements. Compared with $\\mathrm{Pt/C,}$ the higher electron transfer number and lower $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield can be observed in FeAB–O (Fig. 4e), indicating the ORR on FeAB–O is a typical four-electron reduction process, and the main product is $_{\\mathrm{H}_{2}\\mathrm{O}}$ . \n\nTo explore the practical application of FeAB–O, long-term catalytic stability and methanol tolerance tests were performed at reduced potential of $0.4\\mathrm{V}$ vs. RHE. As for the traditional $\\mathrm{Pt/C}$ catalyst, Pt nanoparticles tend to aggregate after long-term ORR measurements, which leads to a decrease in activity and durability44. In this work, the ORR current density of FeAB–O maintained a level of $99.2\\%$ for over $10{,}000\\:s$ chronoamperometric I-t tests, exceeding that of $\\mathrm{Pt/C}$ $(93.5\\%)$ \n\nand $\\mathrm{FePc/AB}$ $(88.3\\%)$ (Fig. 4f and Supplementary Fig. 12a). The outstanding durability of FeAB–O for ORR can be attributed to the high dispersity and stability of the $\\mathrm{O-FeN_{4}}$ sites17,45. No current oscillation was observed in FeAB–O when methanol is added (Supplementary Fig. 12b), while a clear decline of current appears in $\\mathrm{Pt/C}.$ . A home-made aluminum–air battery was used to evaluate the practical performance of FeAB–O. The battery with FeAB–O as cathode catalyst shows higher open potential than that with $\\mathrm{Pt/C}$ as cathode catalyst (Supplementary Fig. 12c). The corresponding discharge plots of long-term discharge were performed at current density of $50\\mathrm{m}\\mathrm{\\bar{A}}\\mathrm{cm}^{-2}$ . As shown in Supplementary Fig. 12d, the FeAB–O exhibits superior performance than that of the commercialized $\\mathrm{Pt/C}$ . These results demonstrated that FeAB–O has excellent potential for practical application. \n\nTo further confirm the importance of the axial O coordination of $_{\\mathrm{O-FeN_{4},}}$ FeAB with less axial O coordination was prepared by compositing of FePc with AB treated by $\\mathrm{O}_{2}$ -plasma for only 10 min in DMF solution. XRD and FT-IR characterization results (Supplementary Fig. 13a, b) prove the presence of FePc and carbon in FeAB. The $\\mathrm{Fe}2p$ XPS spectrum (Supplementary Fig. 13c) indicates the presence of axial O coordination in FeAB. The EXAFS results (Supplementary Fig. 13d) show the order of \n\nFe coordination number is $\\mathrm{FeAB-O>FeAB>FePc/AB}$ . These structural characterizations confirm the axial O coordination in FeAB is between FeAB–O and $\\mathrm{FePc/AB}$ . As we expected, the electrochemical ORR performance of FeAB (Supplementary Fig. 14a, b) is also between FeAB–O and $\\mathrm{FePc/AB}$ , confirming the axial $\\mathrm{~O~}$ coordination induced the electronic localization, which improves the $\\mathrm{O}_{2}$ adsorption and then boosts ORR activity of catalysts. \n\n# Discussion \n\nIn summary, we proposed a coordination-induced electronic localization strategy to tune the $\\mathrm{O}_{2}$ adsorption ability and ORR performance of $\\mathrm{FeN_{4}}$ sites in FePc. DFT calculations demonstrated that the axial O coordination of $_{\\mathrm{O-FeN_{4}}}$ sites breaks the symmetrical electronic density and promotes the electronic localization of Fe sites. XPS, XAS, Mössbauer spectra, and $\\mathrm{O}_{2}$ adsorption/desorption processes indicated the enhanced ORR catalytic activity is ascribed to the strengthened $\\mathrm{O}_{2}$ adsorption and accelerated charge transfer from Fe to $\\mathrm{O}_{2}$ molecule. As a result, the FeAB–O with optimal axial O coordination exhibited a record Tafel slope of $27.5\\mathrm{\\dot{m}V\\ d e c^{-1}}$ and one of the best half-wave potential of $0.90{\\mathrm{V}}$ vs. RHE, which was much superior to commercial $\\mathrm{Pt/C}$ . The axial $\\mathrm{~o~}$ coordination number is positively correlated to ORR performance. This work provides a new strategy to regulate the electronic localization property of catalytic active sites for affecting the adsorption of the reactants and accelerating catalytic reactions. \n\n# Methods \n\nChemicals and materials. FePc, dimethylformamide (DMF), potassium chloride (KCl), indium hydroxide $\\left(\\mathrm{In}(\\mathrm{OH})_{3}\\right)$ , zinc oxide $\\left(\\mathrm{ZnO}\\right)$ , sodium stannate $(\\mathrm{Na}_{2}\\mathrm{SnO}_{3})$ , and potassium hydroxide (KOH) were bought from Shanghai Aladdin reagent co. Ltd. $\\mathrm{Pt/C}$ $(20~\\mathrm{wt\\%})$ ) and the raw AB were purchased from Alfa Aesar and Shenzhen Kejing co. Ltd, respectively. All of the chemical reagents were used as received without any other purification. \n\nSynthesis of catalysts. The surface of the AB was decorated with oxygencontaining groups by $\\mathrm{O}_{2}$ -plasma treatment. Typically, the raw AB was treated in the $\\mathrm{O}_{2}$ plasma for $30\\mathrm{min}$ with $100\\mathrm{W}$ generator power (denoted as AB–O). Then, the as obtained AB–O $\\ensuremath{(25\\mathrm{mg})}$ was added into $60~\\mathrm{mL}$ of DMF solution encompassed $5\\mathrm{mg}$ of FePc. To get the uniform suspension, the mixture solution was subjected to ultrasonical treatment for $^{\\textrm{1h}}$ and then stirred overnight at room temperature. Finally, the FeAB–O composite was collected by filtration of the resulting solution and washing with ethanol. The obtained sample was dried in vacuum at $60^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . The FeAB with less axial O coordination was obtained by the same steps just by replacing the AB–O matrix with AB treated by $\\mathrm{O}_{2}$ -plasma for $10\\mathrm{min}$ at 100 W. The FePc/AB and FePc/AB–O were obtained by direct physical mixture of FePc with the AB and AB–O, respectively. \n\nCharacterizations. XRD data was collected by using a RIGAKU Rint-2000 X-ray diffractometer (graphite monochromatized Cu-Kα radiation with $\\lambda=1.54184\\mathrm{\\AA}$ ). X-ray photoelectron spectroscopy (XPS) was measured by Thermo ESCALAB 250XI. FTIR measurements were performed by the Thermo iS50. The thermogravimetric experiments were conducted on TG 209 F3 Tarsus under the air atmosphere from the room temperature to $900^{\\circ}\\mathrm{C}$ with heating rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ . Scanning electron microscopy (SEM) was measured by a Quanta 200 field-emission SEM system. The transmission electron microscopy (TEM) images were achieved on Tecnai G2 F20. The $^{57}\\mathrm{Fe}$ Mössbauer spectra were achieved by using an MS-500 instrument (Germany, Wissel) in transmission geometry with constant acceleration mode at room temperature. The $\\mathrm{O}_{2}$ -TPD of the samples was measured using AutoChem II 2920 apparatus. The catalyst $(100\\mathrm{mg})$ was pretreated at $150^{\\circ}\\mathrm{C}$ and purged with helium (He) for $^{2\\mathrm{h}}$ , and then cooled down to room temperature. And then, the catalyst was purged with $5\\%$ $_\\mathrm{O_{2}/H e}$ at $25^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . Finally, the desorption profile of $\\mathrm{O}_{2}$ was recorded online under the atmosphere of He. \n\nElectrochemical measurements. All of the electrochemical experiments were implemented with an electrochemical station of Auto Lab in a typical threeelectrode system. The $\\mathrm{Ag/AgCl}$ (saturated KCl) electrode, carbon rod, and glassy carbon electrode (GCE) were used as the reference electrode, counter electrode, and working electrode, respectively. In this work, all electrode potentials were \n\nreferenced to the reversible hydrogen elecrtrode (RHE) based on the following calculation equations: \n\n$$\nE_{\\mathrm{RHE}}=E_{\\mathrm{AgCl}}^{0}+E_{\\mathrm{AgCl}}+0.059\\times\\mathrm{pH}\n$$ \n\nwhere $E_{\\mathrm{AgCl}}^{0}$ (saturated $\\operatorname{KCl})=0.197\\operatorname{V}\\ (25^{\\circ}\\mathrm{C}).$ \n\nThe catalyst ink was prepared by ultrasonic dispersion of $4\\mathrm{mg}$ of catalyst in a hybrid solution included $60\\upmu\\mathrm{L}$ of Nafion $(5\\mathrm{wt\\%})$ , $470\\upmu\\mathrm{L}$ of alcohol, and $470\\upmu\\mathrm{L}$ of $\\mathrm{H}_{2}\\mathrm{O}$ . All of the catalysts were cast onto the RDE $(0.1\\dot{9}625\\mathrm{cm}^{-2},$ ) and RRDE $(0.2475\\mathrm{cm}^{-2},$ ) with a loading amount of $0.2\\mathrm{mg}\\mathrm{cm}^{-2}$ , and contrast sample of $\\mathrm{Pt/C}$ was dropped RRDE with a loading amount of $\\bar{0.1}\\mathrm{mg}\\mathrm{cm}^{-2}$ . Cyclic voltammograms (CV) measurements were performed with scan rate of $50\\mathrm{mVs^{-1}}$ in the $\\Nu_{2}$ or $\\mathrm{O}_{2}.$ - satureated $0.1\\mathrm{M}\\mathrm{KOH}$ solution. The catalytic activity of samples was evaluated by using linear sweep voltammetry (LSV) at scan rate of $10\\mathrm{m}\\bar{\\mathrm{V}}\\mathrm{s}^{-1}$ with different rotation rates. The electron transfer number $(n)$ of catalysts was calculated through the Koutecky–Levich (K–L) equations: \n\n$$\n{\\frac{1}{J}}={\\frac{1}{J_{\\mathrm{L}}}}+{\\frac{1}{J_{\\mathrm{k}}}}={\\frac{1}{B\\omega^{1/2}}}+{\\frac{1}{J_{\\mathrm{k}}}}\n$$ \n\n$$\nB=0.62n F D_{\\mathrm{o}}^{2/3}\\nu^{-1/6}C_{\\mathrm{o}}\n$$ \n\nwhere $J,J_{\\mathrm{L}},$ and $J_{\\mathrm{k}}$ represents the measured, diffusion-limiting, and the kinetic current density, individually. $\\omega$ is the electrode-rotating angular velocity, $F$ is the Faraday constant $(96,485\\mathrm{Cmol^{-1}},$ ), $D_{\\mathrm{o}}$ is the diffusion coefficient of $\\mathrm{O}_{2}$ $(1.9\\times10^{-5}\\mathrm{cm}^{2}s^{-1}$ in $0.1\\mathrm{M}\\mathrm{KOH},$ , $\\nu$ is kinetic viscosity $(0.01\\mathrm{cm}^{2}s^{-1})$ of the electrolyte, and $C_{\\mathrm{o}}$ is the density of $\\mathrm{O}_{2}$ $1.2\\times10^{-6}\\mathrm{mol}\\dot{\\mathrm{cm}}^{-3},$ . \n\nTafel slope was achieved from the Tafel equation: \n\n$$\nE=a+b\\log(J_{k})\n$$ \n\nwhere $E$ is the applied potential of LSV tests, $^a$ is a constant, $^{b}$ is the Tafel slope and $J_{\\mathrm{k}}$ is the kinetic current density. Moreover, the yields of peroxide species and the electron transfer number can be calculated from the LSV of RRDE measurement at $1600\\mathrm{rpm}$ via as following equation: \n\n$$\nn=4\\frac{I_{\\mathrm{D}}}{I_{\\mathrm{D}}+I_{\\mathrm{R}}/N}\n$$ \n\n$$\n\\mathrm{H}_{2}\\mathrm{O}_{2}(\\%)=200\\frac{I_{\\mathrm{R}}/N}{I_{\\mathrm{D}}+(I_{\\mathrm{R}}/N)}\n$$ \n\nwhere $\\boldsymbol{I_{\\mathrm{D}}}$ and $I_{\\mathrm{R}}$ is the disk current and ring current, respectively. The $N$ represents the current collection efficiency equaled to 0.37 of the RRDE in our experimental system. \n\nAssembly of Al–air batteries. In a typical Al–air batteries, the polished aluminum plate is used as anode. The electrolyte is $6\\mathrm{M}\\mathrm{KOH}$ contained 0.0005 M $\\mathrm{In(OH)}_{3},$ $0.0075\\mathrm{M}\\mathrm{ZnO}$ , and 0.01 M $\\mathrm{Na}_{2}\\mathrm{SnO}_{3};$ the gas diffusion electrode with catalystloading amount of $2.0\\mathrm{mg}\\mathrm{cm}^{-2}$ is employed as cathode in a home-made cell model. As a control, the commercial $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%})$ was also assembled in similar mode. The measurement of batteries was performed on the LAND testing system. \n\nComputation methods. Our simulation study was calculated by using the Vienna ab initio simulation package (VASP)46. The PAW potentials describe the interaction of electron–ion47. The generalized gradient approximation of Perdew–Burke–Ernzerhof (PBE) was employed to describe the electron–electron exchange and correlation functional48. A plane wave cutoff energy of $400\\mathrm{eV}$ was applied in our calculations. A rectangular supercell containing 180 carbon atoms are used as substrate. Spin-polarized calculations were employed for all systems. van der Waals (VDW) forces were corrected with the D2 method of Grimme49. The Gamma-point-only grid was used during the optimization. The convergence criterion was set $0.02\\mathrm{e}\\mathrm{\\overset{.}{V}\\overset{.}{A}^{-1}}$ for the force and $10^{-5}\\mathrm{eV}$ per atom for energy. We used the correlation energy (U) of $4\\mathrm{eV}$ and the exchange energy $(J)$ of $1\\mathrm{eV}$ for Fe $3d$ orbitals50. \n\nThe Gibbs free energy can be expressed as \n\n$$\n\\Delta G=\\Delta E+\\Delta\\mathrm{ZPE}-T\\cdot\\Delta S\n$$ \n\nwhere $\\Delta E$ is the reaction energy calculated by the DFT methods, ΔZPE the changes in zero-point energies, and $\\Delta S$ the entropy during the reaction, respectively. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author on reasonable request. \n\nReceived: 14 January 2020; Accepted: 29 July 2020; Published online: 20 August 2020 \n\n# References \n\n1. Guo, D. et al. Active sites of nitrogen-doped carbon materials for oxygen reduction reaction clarified using model catalysts. Science 351, 361 (2016). \n2. Pegis, M. L., Wise, C. F., Martin, D. J. & Mayer, J. M. Oxygen reduction by homogeneous molecular catalysts and electrocatalysts. Chem. Rev. 118, 2340–2391 (2018). \n3. Li, W., Yu, A., Higgins, D. C., Llanos, B. G. & Chen, Z. Biologically inspired highly durable iron phthalocyanine catalysts for oxygen reduction reaction in polymer electrolyte membrane fuel cells. J. Am. Chem. Soc. 132, 17056–17058 (2010). \n4. Wang, Q. et al. Bioinspired fiber-like porous $\\mathrm{Cu/N/C}$ electrocatalyst facilitating electron transportation toward oxygen reaction for metal-air batteries. Nanoscale 10, 15819–15825 (2018). \n5. He, T. et al. Architecture of $\\mathrm{CoN_{x}}$ single clusters on nanocarbon as excellent oxygen reduction catalysts with high-efficient atomic utilization. Nanoscale 9, 8341–8348 (2017). \n6. Wu, N. et al. Facile synthesis of FeCo@NC core-shell nanospheres supported on graphene as an efficient bifunctional oxygen electrocatalyst. Nano Res. 10, 2332–2343 (2017). \n7. Li, J. et al. Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells. Nat. Catal. 1, 935–945 (2018). \n8. Rowley-Neale, S. J. et al. 2D molybdenum disulphide $(2\\mathrm{D}\\mathrm{-}\\mathrm{MoS}_{2})$ ) modified electrodes explored towards the oxygen reduction reaction. Nanoscale 8, 14767–14777 (2016). \n9. Cheng, Y. et al. Iron single atoms on graphene as nonprecious metal catalysts for high-temperature polymer electrolyte membrane fuel cells. Adv. Sci. 6, 1802066 (2019). \n10. Zhou, B. et al. Platinum nanostructures via self-assembly of an amyloid-like peptide: a novel electrocatalyst for the oxygen reduction. Nanoscale 5, 2669–2673 (2013). \n11. Chen, Y. et al. Enhanced oxygen reduction with single-atomic-site iron catalysts for a zinc-air battery and hydrogen-air fuel cell. Nat. Commun. 9, 5422 (2018). \n12. Zhao, L. et al. Cascade anchoring strategy for general mass production of high-loading single-atomic metal-nitrogen catalysts. Nat. Commun. 10, 1278 (2019). \n13. Liu, J. et al. Confining ultrasmall bimetallic alloys in porous N–carbon for use as scalable and sustainable electrocatalysts for rechargeable Zn–air batteries. J. Mater. Chem. A 7, 12451–12456 (2019). \n14. Zhang, Z., Dou, M., Ji, J. & Wang, F. Phthalocyanine tethered iron phthalocyanine on graphitized carbon black as superior electrocatalyst for oxygen reduction reaction. Nano Energy 34, 338–343 (2017). \n15. Wang, Y., Yuan, H., Li, Y. & Chen, Z. Two-dimensional iron-phthalocyanine (Fe-Pc) monolayer as a promising single-atom-catalyst for oxygen reduction reaction: a computational study. Nanoscale 7, 11633–11641 (2015). \n16. Fu, J., Jiang, K., Qiu, X., Yu, J. & Liu, M. Product selectivity of photocatalytic $\\mathrm{CO}_{2}$ reduction reactions. Mater. Today 32, 222–243 (2020). \n17. Cao, R. et al. Promotion of oxygen reduction by a bio-inspired tethered iron phthalocyanine carbon nanotube-based catalyst. Nat. Commun. 4, 2076 (2013). \n18. Han, Y. et al. Electronic structure engineering to boost oxygen reduction activity by controlling the coordination of the central metal. Energy Environ. Sci. 11, 2348–2352 (2018). \n19. Peng, Y. et al. Probing the influence of the center atom coordination structure in iron phthalocyanine multi-walled carbon nanotube-based oxygen reduction reaction catalysts by X-ray absorption fine structure spectroscopy. J. Power Sources 291, 20–28 (2015). \n20. Li, Z. et al. The marriage of the $\\mathrm{FeN_{4}}$ moiety and MXene boosts oxygen reduction catalysis: Fe $3d$ electron delocalization matters. Adv. Mater. 30, 1803220 (2018). \n21. Jiang, Y. et al. Enhanced catalytic performance of Pt-free iron phthalocyanine by graphene support for efficient oxygen reduction reaction. ACS Catal. 3, 1263–1271 (2013). \n22. Li, J. et al. Structural and mechanistic basis for the high activity of Fe–N–C catalysts toward oxygen reduction. Energy Environ. Sci. 9, 2418–2432 (2016). \n23. Sedona, F. et al. Tuning the catalytic activity of $\\mathrm{Ag}(110)$ -supported Fe phthalocyanine in the oxygen reduction reaction. Nat. Mater. 11, 970–977 (2012). \n24. Nemykin, V. N., Purchel, A. A., Spaeth, A. D. & Barybin, M. V. Probing the electronic properties of a trinuclear molecular wire involving isocyanoferrocene and iron(II) phthalocyanine motifs. Inorg. Chem. 52, 11004–11012 (2013). \n25. Janczak, J. & Kubiak, R. Pyrazine control of the supramolecular chemistry of iron(ii) and cobalt(ii) phthalocyanines. CrystEngComm 12, 3599–3606 (2010). \n26. Han, Z., Han, X., Zhao, X., Yu, J. & Xu, H. Iron phthalocyanine supported on amidoximated PAN fiber as effective catalyst for controllable hydrogen peroxide activation in oxidizing organic dyes. J. Hazard. Mater. 320, 27–35 (2016). \n27. Martin, B. & Autschbach, J. Kohn–Sham calculations of NMR shifts for paramagnetic 3d metal complexes: protocols, delocalization error, and the curious amide proton shifts of a high-spin iron(ii) macrocycle complex. Phys. Chem. Chem. Phys. 18, 21051–21068 (2016). \n28. Mukherjee, M., Samanta, M., Banerjee, P., Chattopadhyay, K. K. & Das, G. P. Endorsement of manganese phthalocyanine microstructures as electrocatalyst in ORR: experimental and computational study. Electrochim. Acta 296, 528–534 (2019). \n29. Wei, Y. et al. New strategy for designing orangish-redemitting phosphor via oxygen-vacancy-induced electronic localization. Light-Sci. Appl. 8, 15 (2019). \n30. Zhou, Y. et al. Dopant-induced electron localization drives $\\mathrm{CO}_{2}$ reduction to $\\mathbf{C}_{2}$ hydrocarbons. Nat. Chem. 10, 974–980 (2018). \n31. Liu, K. et al. Single-atom transition metals supported on black phosphorene for electrochemical nitrogen reduction. Nanoscale 12, 4903–4908 (2020). \n32. Chen, K. et al. Untying thioether bond structures enabled by “voltage-scissors” for stable room temperature sodium–sulfur batteries. Nanoscale 11, 5967–5973 (2019). \n33. Chen, K., Hou, H., Huang, C., Ji, X. & Qiu, X. Constructing hierarchical sulfur-doped nitrogenous carbon nanosheets for sodium-ion storage. Nanotechnology 28, 445604 (2017). \n34. Yan, X. et al. The effect of oxygen content of carbon nanotubes on the catalytic activity of carbon-based iron phthalocyanine for oxygen reduction reaction. Electrochim. Acta 281, 562–570 (2018). \n35. Xue, Z. et al. Missing-linker metal-organic frameworks for oxygen evolution reaction. Nat. Commun. 10, 5048 (2019). \n36. Ramaswamy, N., Tylus, U., Jia, Q. & Mukerjee, S. Activity descriptor identification for oxygen reduction on nonprecious electrocatalysts: linking surface science to coordination chemistry. J. Am. Chem. Soc. 135, 15443–15449 (2013). \n37. Jia, Q. et al. Experimental observation of redox-induced Fe–N switching behavior as a determinant role for oxygen reduction activity. ACS Nano 9, 12496–12505 (2015). \n38. Alsudairi, A. et al. Resolving the iron phthalocyanine redox transitions for ORR catalysis in aqueous media. J. Phys. Chem. Lett. 8, 2881–2886 (2017). \n39. Cheng, W. et al. Boosting defective carbon by anchoring well-defined atomically dispersed metal- ${\\bf\\cdot N_{4}}$ sites for ORR, OER, and $Z\\mathrm{n}$ –air batteries. Appl. Catal. B Environ. 260, 118198 (2020). \n40. Fu, J. et al. Graphitic carbon nitride with dopant induced charge localization for enhanced photoreduction of $\\mathrm{CO}_{2}$ to $\\mathrm{CH}_{4}$ Adv. Sci. 6, 1900796 (2019). \n41. Fu, J. et al. Graphitic carbon nitride based single-atom photocatalysts. Front. Phys. 15, 33201 (2020). \n42. Cao, S. et al. Ultrasmall CoP nanoparticles as efficient cocatalysts for photocatalytic formic acid dehydrogenation. Joule 2, 549–557 (2018). \n43. Liu, Z., Li, J. & Wang, R. $\\mathrm{CeO}_{2}$ nanorods supported M–Co bimetallic oxides $\\mathbf{\\dot{M}}=\\mathbf{F}\\mathbf{e}$ Ni, Cu) for catalytic CO and $\\mathrm{C_{3}H_{8}}$ oxidation. J. Colloid Int. Sci. 560, 91–102 (2020). \n44. Nie, Y. et al. Pt/C trapped in activated graphitic carbon layers as a highly durable electrocatalyst for the oxygen reduction reaction. Chem. Commun. 50, 15431–15434 (2014). \n45. Guo, J. et al. The synthesis and synergistic catalysis of iron phthalocyanine and its graphene-based axial complex for enhanced oxygen reduction. Nano Energy 46, 347–355 (2018). \n46. Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquidmetal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994). \n47. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953 (1994). \n48. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865 (1996). \n49. Grimme, S. Semiempirical GGA‐type density functional constructed with a long‐range dispersion correction. J. Comput. Chem. 27, 1787–1799 (2006). \n50. Zhou, J. & Sun, Q. Magnetism of phthalocyanine-based organometallic single porous sheet. J. Am. Chem. Soc. 133, 15113–15119 (2011). \n\n# Acknowledgements \n\nThe authors gratefully thank the International Science and Technology Cooperation Program (Grant Nos. 2017YFE0127800 and 2018YFE0203400), Natural Science Foundation of China (Grant Nos. 21872174 and U1932148), Hunan Provincial Science and Technology Program (No. 2017XK2026), Project of Innovation-Driven Plan in Central South University (2017CX003, 20180018050001), Shenzhen Science and Technology Innovation Project (Grant No. JCYJ20180307151313532), Ministry of Science and Technology, Taiwan (Contract No. MOST108-2113-M-213-006), China Postdoc Innovation Talent Support Program, China Postdoctoral Science Foundation (Grant No. 2018M640759), Thousand Youth Talents Plan of China, and Hundred Youth Talents Program of Hunan. \n\n# Author contributions \n\nM.L., N.Z., and H.M.L. conceived the project; K.C. and M.L. designed the experiments and analyzed the results. K.C., P.A., H.J.W.L., Y.Y.L., and J.L. synthesized the samples, performed the electrochemical experiments, and analyzed the results. K.L. and H.L. carried out the simulations and wrote the corresponding section. K.L., Y.Y.L., Y.-R.L. and T.-S.C. conducted the XAS measurements. J.F., C.J., Z.L., J.H., and W.L. carried out the electron microscope measurements. All authors read and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-18062-y. \n\nCorrespondence and requests for materials should be addressed to M.L. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1016_j.cpc.2019.106949", + "DOI": "10.1016/j.cpc.2019.106949", + "DOI Link": "http://dx.doi.org/10.1016/j.cpc.2019.106949", + "Relative Dir Path": "mds/10.1016_j.cpc.2019.106949", + "Article Title": "DScribe: Library of descriptors for machine learning in materials science", + "Authors": "Himanen, L; Jäger, MOJ; Morooka, EV; Canova, FF; Ranawat, YS; Gao, DZ; Rinke, P; Foster, AS", + "Source Title": "COMPUTER PHYSICS COMMUNICATIONS", + "Abstract": "DScribe is a software package for machine learning that provides popular feature transformations (descriptors) for atomistic materials simulations. DScribe accelerates the application of machine learning for atomistic property prediction by providing user-friendly, off-the-shelf descriptor implementations. The package currently contains implementations for Coulomb matrix, Ewald sum matrix, sine matrix, Many-body Tensor Representation (MBTR), Atom-centered Symmetry Function (ACSF) and Smooth Overlap of Atomic Positions (SOAP). Usage of the package is illustrated for two different applications: formation energy prediction for solids and ionic charge prediction for atoms in organic molecules. The package is freely available under the open-source Apache License 2.0. Program summary Program Title: DScribe Program Files doi: http://dx.doLorg/10.17632/vzrs8n8pk6.1 Licensing provisions: Apache-2.0 Programming language: Python/C/C++ Supplementary material: Supplementary Information as PDF Nature of problem: The application of machine learning for materials science is hindered by the lack of consistent software implementations for feature transformations. These feature transformations, also called descriptors, are a key step in building machine learning models for property prediction in materials science. Solution method: We have developed a library for creating common descriptors used in machine learning applied to materials science. We provide an implementation the following descriptors: Coulomb matrix, Ewald sum matrix, sine matrix, Many-body Tensor Representation (MBTR), Atom centered Symmetry Functions (ACSF) and Smooth Overlap of Atomic Positions (SOAP). The library has a python interface with computationally intensive routines written in C or C++. The source code, tutorials and documentation are provided online. A continuous integration mechanism is set up to automatically run a series of regression tests and check code coverage when the codebase is updated. (C) 2019 The Authors. Published by Elsevier B.V.", + "Times Cited, WoS Core": 520, + "Times Cited, All Databases": 569, + "Publication Year": 2020, + "Research Areas": "Computer Science; Physics", + "UT (Unique WOS ID)": "WOS:000503093400032", + "Markdown": "# Journal Pre-proof \n\nDScribe: Library of descriptors for machine learning in materials science \n\nLauri Himanen, Marc O.J. Jäger, Eiaki V. Morooka, Filippo Federici Canova, Yashasvi S. Ranawat, David Z. Gao, Patrick Rinke, Adam S. Foster \n\nPII: S0010-4655(19)30304-2 \nDOI: https://doi.org/10.1016/j.cpc.2019.106949 \nReference: COMPHY 106949 \n\nTo appear in: Computer Physics Communications \n\nReceived date : 17 April 2019 \nRevised date : 14 August 2019 \nAccepted date : 24 August 2019 \n\nPlease cite this article as: L. Himanen, M.O.J. Jäger, E.V. Morooka et al., DScribe: Library of descriptors for machine learning in materials science, Computer Physics Communications (2019), doi: https://doi.org/10.1016/j.cpc.2019.106949. \n\nThis is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. \n\n$\\mathfrak{O}$ 2019 Published by Elsevier B.V. \n\n# DScribe: Library of Descriptors for Machine Learning in Materials Science \n\nLauri Himanen $^{\\mathrm{a},\\ast}$ , Marc O. J. J¨agera, Eiaki V. Morookaa, Filippo Federici Canova $^{\\mathrm{a,b}}$ , Yashasvi S. Ranawat $\\mathrm{a}$ , David Z. Gao $^{\\mathrm{b,c}}$ , Patrick Rinke $^{\\mathrm{a,f}}$ , Adam S. Foster $^{\\cdot\\mathrm{a},\\mathrm{d},\\mathrm{e}}$ \n\naDepartment of Applied Physics, Aalto University, P.O. Box 11100, 00076 Aalto, Espoo, Finland bNanolayers Research Computing Ltd., 1 Granville Court, Granville Road, London, N12 0HL, United Kingdom cDepartment of Physics, Norwegian University of Science and Technology, NO-7491 Trondheim, Norway $d$ Graduate School Materials Science in Mainz, Staudinger Weg 9, 55128, Germany eWPI Nano Life Science Institute (WPI-NanoLSI), Kanazawa University , Kakuma-machi, Kanazawa 920-1192, Japan fTheoretical Chemistry and Catalysis Research centre, Technische Universit¨at Mu¨nchen, Lichtenbergstr. 4, D-85747 Garching, Germany \n\n# Abstract \n\nDScribe is a software package for machine learning that provides popular feature transformations (“descriptors”) for atomistic materials simulations. DScribe accelerates the application of machine learning for atomistic property prediction by providing user-friendly, off-the-shelf descriptor implementations. The package currently contains implementations for Coulomb matrix, Ewald sum matrix, sine matrix, Many-body Tensor Representation (MBTR), Atom-centered Symmetry Function (ACSF) and Smooth Overlap of Atomic Positions (SOAP). Usage of the package is illustrated for two different applications: formation energy prediction for solids and ionic charge prediction for atoms in organic molecules. The package is freely available under the open-source Apache License 2.0. \n\nKeywords: machine learning, materials science, descriptor, python, open source \n\n# 1. Introduction \n\nMachine learning of atomistic systems is a highly active, interdisciplinary area of research. The power of machine learning lies in the ability of interpolating existing calculations with surrogate models to accelerate predictions for new systems [1– 4]. The set of possible applications is very rich, including high-throughput search of stable compounds with machine learning based energy predictions for solids [5–8], accelerated molecular property prediction [9–11], creation of new force-fields based on quantum mechanical training data [12– 19], search for catalytically active sites in nanoclusters [20–24] and efficient optimization of complex structures [25–27]. \n\n![](images/f5b885e3a1ab5303a1b931a18b1285f58453dfddbcf4406d0761d32eab34f149.jpg) \nFigure 1: Typical workflow for making machine learning based materials property predictions for atomistic structures. An atomic structure is transformed into a numerical representation called a descriptor. This descriptor is then used as an input for a machine learning model that is trained to output a property for the structure. There is also a possibility of combining the descriptor and learning model together into one inseparable step. \n\nAtomistic machine learning establishes a relationship between the atomic structure of a system and its properties. This so called structureproperty relation is illustrated in Fig. 1. It is analogous to the structure-property relation in quantum mechanics. For a set of nuclear charges $\\{Z_{i}\\}$ and atomic positions $\\{R_{i}\\}$ of a system, the solution of the Schr¨odinger equation $\\hat{H}\\Phi=E\\Phi$ yields the properties of the system since both the Hamiltonian $\\hat{H}$ and the wave function $\\Phi$ depend only on $\\{Z_{i}\\}$ and $\\{R_{i}\\}$ . Atomistic machine learning bypasses the computationally costly step of solving the Schr¨odinger equation $^{1}$ by training a surrogate model. Once trained, the surrogate model is typically very fast to evaluate facilitating almost instant structure-property predictions. \n\nUnlike for the Schr¨odinger equation, the nuclear charges and atomic positions are not a suitable input representation of atomistic systems for machine learning. They are, for example, not rotationally or translationally invariant. If presented with atomic positions, the machine learning method would have to learn rotational and translational invariance for every data set, which would significantly increase the amount of required training data. For this reason, the input data has to be transformed into a representation that is suitable for machine learning. This transformation step is often referred to as feature engineering and the selected features are called a descriptor [28]2. Various feature engineering approaches have been proposed [5–9, 14, 16, 33–40], and often multiple approaches have to be tested to find a suitable representation for a specific task [41]. Features are often based on the atomic structure, but it is also common to extend the input to other system properties [5, 28, 36, 42]. \n\nThere are several requirements for good descriptors in atomistic machine learning [6, 7]. We identify the following properties to be most important for an ideal descriptor: \n\ni) Invariant with respect to spatial translation of the coordinate system: isometry of space. \nii) Invariant with respect to rotation of the coordinate system: isotropy of space. \niii) Invariant with respect to permutation of atomi indices: changing the enumeration of atoms does not affect the physical properties of the system. \niv) Unique: there is a single way to construct a descriptor from an atomic structure and the descriptor itself corresponds to a single property. v) Continuous: small changes in the atomic structure should translate to small changes in the descriptor. \nvi) Compact: the descriptor should contain sufficient information of the system for performing the prediction while keeping the feature count to minimum. \nvii) Computationally cheap: the computation of the descriptor should be significantly faster than any existing computational model for directly calculating the physical property of interest. \n\nIn this article we present the DScribe package that can be used to transform atomic structures into machine-learnable input features. The aim of this software is to provide a coherent and easily extendable implementation for atomistic machine learning and fast prototyping of descriptors. There already exist libraries like QML [43], Amp[44], Magpie [45], quippy [46], ChemML [47] and matminer [48] which include a subset of descriptors as a part of a bigger framework for materials data analytics. DScribe follows this spirit but specializes on providing efficient and scalable descriptor transformations and is agnostic to the framework used for doing the actual data analytics. \n\nCurrently in the DScribe package we include descriptors that can be represented in a vectorial form and are not dependent on any specific learning model. By decoupling the descriptor creation from the machine learning model, the user can experiment in parallel with various descriptor/model combinations and has the possibility of directly applying emerging learning models on existing data. This freedom to switch between machine learning models becomes important because currently no universally best machine model exists for every problem, as stated by the “No Free Lunch Theorem” [49]. In practice this means that multiple models have to be tested to find optimal performance. Furthermore, vectorial features provide easier insight into the importance of certain features and facilitate the application of unsupervised learning methods, such as clustering and subsequent visualization with informative “materials maps” [50–52]. \n\nDescriptors that encode an atomic structure are typically designed to either depict a local atomi environment, or the structure as a whole. Global descriptors encode information about the whole atomic structure. These global descriptors can be used to predict properties related to the structure as a whole, such as molecular energies [9], formation energies [5] or band gaps [36]. In this work we cover four such global descriptors: the Coulomb matrix [9], the Ewald sum matrix [7], the sine matrix [7] and the Many-Body Tensor Representation (MBTR) [6]. Local descriptors are instead used to represent a localized region in an atomic structure, and are thus suitable for predicting localized properties, like atomic forces [13], adsorption energies[23], or properties that can be summed from local contributions. In this article we discuss two local descriptors, Atomcentered Symmetry functions (ACSFs) [16] and the Smooth Overlap of Atomic Positions (SOAP) [14]. \n\nWe first introduce the descriptors that have been implemented in the DScribe package and then we discuss the structure and usage of the package. After this we illustrate the applicability of the package by showing results for formation energy prediction of periodic crystals and partial charge prediction for molecules. We conclude, by addressing the impact and future extensions of this package. \n\n# 2. Descriptors \n\nHere we briefly introduce the different descriptors that are currently implemented in DScribe. \n\n1 In some cases, we have deviated from the original \n2 literature due to computational or other reasons, \n3 \n3 and if so this is explicitly mentioned. For more \n4 in-depth presentations of the descriptors we refer the reader to the original research papers. At the end of this section we also discuss methods for organizing the descriptor output so that it can be effectively used in typical machine learning applications. \n\n# 2.1. Coulomb matrix \n\nThe Coulomb matrix [9] encodes the atomic species and inter-atomic distances of a finite system in a pair-wise, two-body matrix inspired by the form of the Coulomb potential. The elements of this matrix are given by: \n\n$$\nM_{i j}^{\\mathrm{Coulomb}}=\\left\\{\\begin{array}{l l}{0.5Z_{i}^{2.4}}&{\\forall i=j}\\\\ {\\frac{Z_{i}Z_{j}}{|{\\cal R}_{i}-{\\cal R}_{j}|}}&{\\forall i\\ne j}\\end{array}\\right.\n$$ \n\nwhere $Z$ is the atomic number, and $\\lvert R_{i}-R_{j}\\rvert$ is the Euclidean distance between atoms $i$ and $j$ . The form of the diagonal terms was determined by fitting the potential energy of neutral atoms [53]. \n\n# 2.2. Ewald sum matrix \n\nThe Ewald sum matrix [7] can be viewed as a logical extension of the Coulomb matrix for periodic systems. In periodic systems each atom is infinitely repeated in the three crystal lattice vector directions, a, b and $\\mathbf{c}$ and the electrostatic interaction between two atoms becomes \n\n$$\n\\phi_{i j}=\\sum_{\\bf n}{\\frac{Z_{i}Z_{j}}{|{\\bf R}_{i}-{\\bf R}_{j}|+\\bf n}}\n$$ \n\nwhere $\\scriptstyle\\sum_{\\mathbf{n}}$ is the sum over all lattice vectors $\\mathbf{n}=$ $h\\mathbf{a}+k\\mathbf{b}+l\\mathbf{c}$ . \n\nFor $h,k,l\\rightarrow\\infty$ , this sum converges only conditionally and will become infinite if the system is not charge neutral. In the Ewald sum matrix, the Ewald summation technique [54, 55] and a neutralizing background charge [56] is used to force this sum to converge. One can separate the total Ewald energy into pairwise components, which will result in the following matrix: \n\n$$\nM_{i j}^{\\mathrm{Ewald}}=\\left\\{\\begin{array}{l l}{\\phi_{i j}^{\\mathrm{real}}+\\phi_{i j}^{\\mathrm{recip}}+\\phi_{i j}^{\\mathrm{self}}+\\phi_{i j}^{\\mathrm{bg}}}&{\\forall\\:i=j}\\\\ {2\\left(\\phi_{i j}^{\\mathrm{real}}+\\phi_{i j}^{\\mathrm{recip}}+\\phi_{i j}^{\\mathrm{bg}}\\right)}&{\\forall\\:i\\neq j}\\end{array}\\right.\n$$ \n\nwhere the terms are given by \n\n$$\n\\begin{array}{l}{{\\displaystyle{\\phi_{i j}^{\\mathrm{real}}=\\frac{1}{2}Z_{i}Z_{j}\\sum_{n^{\\prime}}\\frac{\\mathrm{erfc}\\left(\\alpha|{\\bf R}_{i}-{\\bf R}_{j}+{\\bf n}|\\right)}{|{\\bf R}_{i}-{\\bf R}_{j}+{\\bf n}|}}\\qquad(2)}}}\\\\ {{\\displaystyle{\\phi_{i j}^{\\mathrm{recip}}=\\frac{2\\pi}{V}Z_{i}Z_{j}\\sum_{{\\bf G}}\\frac{e^{-|{\\bf G}|^{2}/(2\\alpha)^{2}}}{|{\\bf G}|^{2}}\\cos\\left({\\bf G}\\cdot({\\bf R}_{i}-{\\bf R}_{j})\\right)}}}\\end{array}\n$$ \n\n$$\n\\begin{array}{r l}&{\\phi_{i j}^{\\mathrm{self}}=\\left\\{\\begin{array}{l l}{-\\frac{\\alpha}{\\sqrt{\\pi}}Z_{i}^{2}}&{\\forall~i=j}\\\\ {0}&{\\forall~i\\neq j}\\end{array}\\right.}\\\\ &{\\phi_{i j}^{\\mathrm{bg}}=\\left\\{\\begin{array}{l l}{-\\frac{\\pi}{2V\\alpha^{2}}Z_{i}^{2}}&{\\forall~i=j}\\\\ {-\\frac{\\pi}{2V\\alpha^{2}}Z_{i}Z_{j}}&{\\forall~i\\neq j}\\end{array}\\right.}\\end{array}\n$$ \n\nHere the primed notation means that when $\\mathbf{\\nabla}_{\\mathbf{n}}=\\mathbf{0}$ the pairs $i=j$ are not taken into account. $\\alpha$ is the screening parameter controlling the size of the gaussian charge distributions used in the Ewald method, $\\dot{\\bf G}$ is a reciprocal space lattice vector with an implicit $2\\pi$ prefactor and $V$ is the volume of the cell. A more detailed derivation is given in the supplementary information. By default we use the value $\\begin{array}{r}{\\alpha=\\sqrt{\\pi}\\left(\\frac{N}{V^{2}}\\right)^{1/6}}\\end{array}$ [57], where $N$ is the number of atoms in the unit cell. \n\nIt is important to notice that the off-diagonal contribution φself + $\\begin{array}{r}{\\phi_{i j}^{\\mathrm{self}}+\\phi_{i j}^{\\mathrm{bg}}=-\\frac{\\pi}{2V\\alpha^{2}}Z_{i}Z_{j}\\ \\forall\\ i\\ \\ne\\ j}\\end{array}$ given here differs from the original work. In the original formulation this sum was defined as [7] $\\begin{array}{r}{\\phi_{i j}^{\\mathrm{self}}+\\phi_{i j}^{\\mathrm{bg}}=-\\frac{\\alpha}{\\sqrt{\\pi}}(Z_{i}^{2}+Z_{j}^{2})-\\frac{\\pi}{2V\\alpha_{*}^{2}}(Z_{i}+Z_{j})^{2}\\forall\\:i\\neq j}\\end{array}$ Our correction makes the total matrix elements independent of the screening parameter $\\alpha$ , which is not the case in the original formulation. \n\nFor numerical purposes, the sums in eqs. 2 and 3 are cut off by $n~\\leq~n_{\\mathrm{cut}}$ and $G\\leq G_{\\mathrm{cut}}$ . By default we use the values $G_{\\mathrm{cut}}=2\\alpha\\sqrt{-\\ln A}$ and $n_{\\mathrm{cut}}={\\sqrt{-\\ln A}}/\\alpha[57]$ , where the small positive parameter $A$ controls the accuracy of the sum and can be determined by the user. \n\n# 2.3. Sine matrix \n\nThe Ewald sum matrix encodes the correct Coulomb interaction between atoms, but can become computationally heavy especially for large systems. The sine matrix [7] captures some important features of interacting atoms in a periodic system with a much reduced computational cost. The matrix elements are defined by \n\n![](images/170596344c4a75f2f11f7f433b1d65cd762f99da25d2a9370abfa51adb8dba9f.jpg) \nFigure 2: Illustration of the Coulomb matrix, Ewald sum matrix and sine matrix for a periodic diamond structure. The used atomic structure for the conventional diamond cell is shown on the left. The color scale (legend on the right) is used to illustrate the magnitude of the matrix elements. \n\n$$\nM_{i j}^{\\mathrm{sine}}=\\left\\{\\begin{array}{l l}{0.5Z_{i}^{2.4}}&{\\forall~i=j}\\\\ {\\phi_{i j}}&{\\forall~i\\ne j}\\end{array}\\right.\n$$ \n\nwhere \n\n$$\n\\phi_{i j}=Z_{i}Z_{j}|\\mathbf{B}\\cdot\\sum_{k=\\{x,y,z\\}}\\hat{\\mathbf{e}}_{k}\\sin^{2}\\left(\\pi\\mathbf{B}^{-1}\\cdot({\\pmb R}_{i}-{\\pmb R}_{j})\\right)|^{-1}\n$$ \n\nHere $\\mathbf{B}$ is a matrix formed by the lattice vectors and $\\hat{\\mathbf{e}}_{k}$ are the cartesian unit vectors. This functional form has no physical interpretation, but it captures some of the properties of the Coulomb interaction, such as the periodicity of the crystal lattice and an infinite energy when two atoms overlap. \n\nThe Coulomb, Ewald sum and sine matrices for diamond are depicted in Fig. 2. Notice that the matrices given here are not unique, as different cell sizes can be used for a periodic crystal, and the indexing of the rows and columns depends on the ordering of atomic indices in the structure. Section 2.7 discusses some ways to overcome the issues related to this non-uniqueness. \n\nBy construction the Coulomb matrix is not periodic as manifested by the unequivalent row elements in the matrix (one carbon in the system has four bonded neighbours, three carbons have two neighbours and four carbons have a single bonded neighbour). Conversely, both the Ewald sum and the sine matrix are periodic and correctly encode the identical environment of the carbon atoms in the lattice. As a result, each row and each column has the same matrix elements, but neighbouring rows and columns are shifted by one element relative to each other. Unlike the other matrices, Ewald sum matrix often contains negative elements due to the interaction of the positive atomic nuclei with the added uniform negative background charge. This energetically favourable interaction shifts the off-diagonal elements down in energy compared to the other two matrices. Moreover, the diagonal elements of the Ewald sum matrix encode the physical selfinteraction of atoms with their periodic copies, instead of the potential energy of the neutral atoms. \n\n# 2.4. Many-body Tensor Representation \n\nThe many-body tensor representation (MBTR) [6] encodes finite or periodic structures by breaking them down into distributions of differently sized structural motifs and grouping these distributions by the involved chemical elements. In MBTR, a geometry function $g_{k}$ is used to transform a configuration of $k$ atoms into a single scalar value representing that particular configuration. Our implementation provides terms up to $k\\mathbf{\\Psi}=$ 3, and provides the following geometry functions $g_{1}(Z_{l})$ : $\\mathcal{L}_{l}$ (atomic number), $g_{2}(R_{l},R_{m})$ : $|R_{l}-$ Rm| (distance) or R 1R (inverse distance) and $g_{3}({\\pmb R}_{l},{\\pmb R}_{m},{\\pmb R}_{n})$ : $\\angle(R_{l}-R_{m},R_{n}-R_{m})$ (angle) or $\\cos(\\angle(R_{l}-R_{m},R_{n}-R_{m}))$ (cosine of angle). These scalar values are then broadened by using \n\n1 kernel density estimation with a gaussian kernel, \n2 leading to the following distributions $\\mathcal{D}_{k}$ \n\n$$\n\\mathcal{D}_{1}^{l}(x)=\\frac{1}{\\sigma_{1}\\sqrt{2\\pi}}e^{-\\frac{\\left(x-g_{1}(Z_{l})\\right)^{2}}{2\\sigma_{1}^{2}}}\n$$ \n\n$$\n\\mathcal{D}_{2}^{l,m}(x)=\\frac{1}{\\sigma_{2}\\sqrt{2\\pi}}e^{-\\frac{\\left(x-g_{2}\\left(R_{l},R_{m}\\right)\\right)^{2}}{2\\sigma_{2}^{2}}}\n$$ \n\n$$\n\\mathcal{D}_{3}^{l,m,n}(x)=\\frac{1}{\\sigma_{3}\\sqrt{2\\pi}}e^{-\\frac{\\left(x-g_{3}\\left(R_{l},R_{m},\\mathbf{R}n\\right)\\right)^{2}}{2\\sigma_{3}^{2}}}\n$$ \n\nHere $\\sigma_{k}$ is the standard deviation of the gaussian kernel and $x$ runs over a predefined range of values covering the possible values for $g_{k}$ . A weighted sum of the distributions $\\mathcal{D}_{k}$ are then made separately for each possible combination of $k$ chemical species present in the dataset. For $k=1,2,3$ these distributions are given by \n\n$$\n\\begin{array}{r l r}{\\mathrm{MBTR}_{1}^{Z_{1}}(x)}&{=\\displaystyle\\sum_{l}^{|Z_{1}|}w_{1}^{l}\\mathcal{D}_{1}^{l}(x)}&&{\\mathrm{(10)}}\\\\ {\\mathrm{MBTR}_{2}^{Z_{1},Z_{2}}(x)}&{=\\displaystyle\\sum_{l}^{|Z_{1}|}\\sum_{m}w_{2}^{l,m}\\mathcal{D}_{2}^{l,m}(x)}&&{\\mathrm{(12)}}\\\\ {\\mathrm{MBTR}_{3}^{Z_{1},Z_{2},Z_{3}}(x)}&{=\\displaystyle\\sum_{l}^{|Z_{1}|}\\sum_{m}^{|Z_{2}|}\\sum_{n}^{|Z_{3}|}w_{3}^{l,m,n}\\mathcal{D}_{3}^{l,m,n}(x)}&\\end{array}\n$$ \n\nwhere the sums for $\\it l$ , $m$ and $n$ run over all atoms with the atomic number $Z_{1}$ , $Z_{2}$ or $Z_{3}$ respectively, and $w_{k}$ is a weighting function that is used to control the importance of different terms. When calculating MBTR for periodic systems, the periodic copies of atoms in neighbouring cells are taken into account by extending the original cell with periodic copies. When a periodic system is extended in this way, certain sets of atoms may get counted multiple times due to translational symmetry. Like in the original formulation [6] we require that one of the atoms, $l$ , $m$ or $n$ , must be in the original cell. In addition, our implementation ensures that each translationally unique combination of the atoms is counted only once. This makes the MBTR output for different cells representing the same material identical up to a size extensive scalar multiplication factor. Unlike in the original formulation, we don’t include the possible correlation between chemical elements directly in equations (10)–(12). We don’t however lose any generality, as the correlation between chemical elements can be introduced as a postprocessing step that combines information from the different species. \n\nFor $k=1$ , typically no weighting is used: $w_{1}^{l}=$ 1. In the case of $k\\stackrel{_{\\perp}}{=}2$ and $k=3$ , the weighting function can, however be used to give more importance to values that correspond to configuration where the atoms are closer together. For fully periodic systems, a weighting function must be used, as otherwise the sums in equations (10)– (12) do not converge. For $k=2,3$ we provide exponential weighting functions of the form \n\n$$\n\\begin{array}{r l}&{w_{2}^{l,m}=e^{-s_{k}\\left|R_{l}-{\\pmb R}_{m}\\right|}}\\\\ &{w_{3}^{l,m,n}=e^{-s_{k}\\left(\\left|{\\pmb R}_{l}-{\\pmb R}_{m}\\right|+\\left|{\\pmb R}_{m}-{\\pmb R}_{n}\\right|+\\left|{\\pmb R}_{l}-{\\pmb R}_{n}\\right|\\right)}}\\end{array}\n$$ \n\nwhere the parameter $s_{k}$ can be used to effectively tune the cutoff distance. For computational purposes a cutoff of $w_{k}^{\\mathrm{min}}$ can be defined to ignore any contributions for which $w_{k}0}\\end{array}\\right.\n$$ \n\nwhere $Y_{l}^{m}$ corresponds to the complex orthonormalized spherical harmonics defined as \n\n$$\nY_{l}^{m}(\\theta,\\phi)={\\sqrt{\\frac{(2l+1)}{4\\pi}\\frac{(l-m)!}{(l+m)!}}}P_{l}^{m}(\\cos{\\theta})e^{i m\\phi}\n$$ \n\nand $P_{l}^{m}$ are the associated Legendre polynomials. \n\nThe final rotationally invariant output from our SOAP implementation is the partial power \n\n1 spectra [51] vector $\\mathbf{p}$ where the individual vector \n2 elements are defined as: \n\n$$\np_{n n^{\\prime}l}^{Z_{1},Z_{2}}=\\pi\\sqrt{\\frac{8}{2l+1}}\\sum_{m}\\left(c_{n l m}^{Z_{1}}\\right)^{*}c_{n^{\\prime}l m}^{Z_{2}}\n$$ \n\nThe vector $\\mathbf{p}$ is constructed by concatenating the elements pnZ1n,′lZ2 for all unique atomic number pairs $Z_{1},Z_{2}$ , all unique pairs of radial basis functions $n,n^{\\prime}$ up to $n_{\\mathrm{max}}$ and the angular degree values $\\it l$ up to lmax. \n\nSpherical harmonics are a natural orthogonal and complete set of functions for the angular degrees of freedom. For the radial degree of freedom the selection of the basis set is not as trivial and multiple approaches may be used. In our implementation we, by default, use a set of spherical primitive gaussian type orbitals $g_{n l}(r)$ as radial basis functions. These basis functions are defined as \n\n$$\n\\begin{array}{l l r}{\\displaystyle{g_{n l}(r)=\\sum_{n^{\\prime}=1}^{n_{\\mathrm{max}}}\\beta_{n n^{\\prime}l}\\phi_{n^{\\prime}l}(r)}}\\\\ {\\displaystyle{\\phi_{n l}(r)=r^{l}e^{-\\alpha_{n l}r^{2}}.}}\\end{array}\n$$ \n\nThis basis set allows analytical integration of the $c_{n l m}$ coefficients defined by equation (19). This provides a speedup over various other radial basis functions that require numerical integration. Our current implementation provides the analytical solutions up to $l\\leq9$ , with the possibility of adding more in the future. \n\nThe decay parameters $\\alpha_{n}$ are chosen so that each non-orthonormalized function $\\phi_{n l}$ decays to a threshold value of $10^{-3}$ at a cutoff radius taken on an evenly spaced grid from $\\mathrm{1\\AA}$ to $r_{\\mathrm{cut}}$ with a step of $\\frac{r_{\\mathrm{cut}}-1}{n_{\\mathrm{max}}}$ . Thus the parameter $\\widehat{r_{\\mathrm{cut}}}$ controls the maximum reach of the basis and a better sampling can be obtained by increasing the number of basis functions n . \n\nThe weights $\\beta_{n n^{\\prime}l}$ are chosen so that the radial basis functions are orthonormal. For each value of angular degree $l$ , the orthonormalizing weights $\\beta_{n n^{\\prime}l}$ can be calculated with L¨owdin orthogonal \n\n![](images/f7b5d1186cd90e85a087518a75e1f05084a9433f0da6a18f936e2a101bfbd22d.jpg) \nFigure 5: Plot of the a) gaussian type orbital and b) polynomial radial basis functions, defined by equations (24) and (28) respectively. The basis functions here correspond to the orthonormalized set with $r_{\\mathrm{cut}}=3$ and up to $n_{\\mathrm{max}}=4$ . Notice that the polynomial basis is independent of the spherical harmonics degree $l$ , whereas the form of the gaussian type orbital basis depends on $l$ and the examples here are given for $l=0,1,2$ . \n\nization [61]: \n\n$$\n\\begin{array}{r}{\\beta=S^{-1/2}\\qquad(2}\\\\ {S_{n n^{\\prime}}=\\langle\\phi_{n l}|\\phi_{n^{\\prime}l}\\rangle=\\displaystyle\\int_{0}^{\\infty}\\mathrm{d}r r^{2}r^{l}e^{-\\alpha_{n l}r^{2}}r^{l}e^{-\\alpha_{n^{\\prime}l}r^{2}}}\\end{array}\n$$ \n\nwhere the matrix $\\beta$ contains the weights $\\beta_{n n^{\\prime}l}$ and $S$ is the overlap matrix. \n\nWe also provide an option for using the radial basis consisting of cubic and higher order polynomials, as introduced in the original SOAP article \n\n[14]. This basis set is defined as: \n\n$$\n\\begin{array}{l}{\\displaystyle g_{n}(\\boldsymbol{r})=\\sum_{n^{\\prime}=1}^{n_{\\mathrm{max}}}\\beta_{n n^{\\prime}}\\phi_{n^{\\prime}}(\\boldsymbol{r})}\\\\ {\\phi_{n}(\\boldsymbol{r})=(r-r_{\\mathrm{cut}})^{n+2}}\\end{array}\n$$ \n\nThe calculations with this basis are performed with efficient numerical integration and currently support $l_{\\mathrm{max}}\\leq20$ . \n\nThe two different basis sets are compared in Figure 5. Most notably the form of the gaussian type orbitals depend on the angular degree $l$ , whereas the polynomial basis is independent of this value. It is also good to notice that between these two radial basis functions the definition of $r_{\\mathrm{cut}}$ is somewhat different – whereas the polynomial basis is guaranteed to decay to zero at $r_{\\mathrm{cut}}$ , the gaussian basis only approximately decays near this value and the decay is also affected by the orthonormalization. \n\n2.7. Descriptor usage as machine learning input In this section we discuss some of the methods for organizing the output from descriptors so that it can be efficiently used as input for machine learning. \n\nThe descriptor invariance against permutations of atomic indices – property iii) in the introduction – is directly achieved in MBTR, SOAP and ACSF by stratifying the output according to the involved chemical elements. The output is always ordered by a predefined order determined by the chemical elements that are included in the dataset, making the output independent of the indexing of individual atoms. The three matrix descriptors – the Coulomb matrix, Ewald sum matrix, and sine matrix – are, however, not invariant with respect to permutation of atomic indices, as the matrix columns and rows are ordered by atomic indices. However, there are different approaches for enforcing invariance for these matrices. One way is to encode the matrices by their eigenvalues, which are invariant to changes in the column and row ordering [9]. Another way is to order the rows and columns by a chosen norm, typically the Euclidean norm [33]. A third approach is to augment the dataset by creating multiple slightly varying matrices for each structure. \n\nIn this approach multiple matrices are drawn from a statistical set of sorted matrices where Gaussian noise is added to the row norms before sorting [33]. When the learning algorithm is trained over this ensemble of matrices it becomes more robust against small sorting differences that can be considered noise. All of these three approaches are available in our implementation. \n\nMachine learning algorithms also often require constant-sized input. Once again the stratification of the descriptor output by chemical elements makes the output for MBTR, ACSF and SOAP constant size. For the matrix descriptors a common way to achieve a uniform size for geometries with different amount of atoms, is by introducing zero-padding. This means that we first have to determine the largest system in the dataset. If this system has $N_{\\mathrm{max}}$ , we allocate matrices of size $N_{\\mathrm{max}}\\times N_{\\mathrm{max}}$ or a vectors or size $N_{\\mathrm{max}}$ if using matrix eigenvectors. The descriptor for each system will fill the first $N^{2}$ or $N$ many entries, with the rest being set to zero. If the machine-learning algorithms expects a one-dimensional vector as input, the two-dimensional matrices can be flattened by concatenating the rows together into a single vector. \n\nLocal descriptors, such as ACSF and SOAP, encode only local spatial regions and cannot be directly used as input for performing predictions related to entire structures. There are, however, various ways for combining information from multiple local sites to form a prediction for an entire structure. The descriptor output for multiple local sites can simply be averaged, a custom kernel can be used to combine information from multiple sites [51, 62] or the predicted property can in some cases be directly modeled as a sum of local contributions [13]. \n\n# 3. Software structure \n\nWe use python as the default interfacing language through which the user interacts with the library. This decision was motivated by the existence of various python libraries, including ase [63], pymatgen [64] and quippy [46], that supply tools for creating, reading, writing and manipu \n\n1 lating atomic structures. Our python interface \n2 does not, however, restrict the implementation to \n3 be made entirely in python. Python can easily \n4 interact with software libraries written with highperformance, statically typed languages such as C, C++ and Fortran. We use this dual approach by performing some of the most computationally heavy calculations either in C or $\\mathrm{C}{+}{+}$ . \n\n![](images/c72489cef5e1ec5d1a40994000801e7415d8433bb316291045053224adbde628.jpg) \nFigure 6: Example of creating descriptors with DScribe. The structures are defined as ase.Atoms objects, in this case by using predefined molecule geometries. The usage of all descriptors follows the same pattern: a) a descriptor object is initialized with the desired configuration b) the number of features can be requested with get number offeatures c) the actual output is created with createmethod that takes one or multiple atomic structures and possibly other arguments, such as the number of parallel jobs to use. \n\nAn example of creating a descriptor for an atomic structure with the library is demonstrated in Fig. 6. It demonstrates the workflow that is common to all descriptors in the package. For each descriptor we define a class, from which objects can be instantiated with different descriptor specific setups. \n\nAll the descriptors have the sparse-parameter that controls whether the created output is a dense or a sparse matrix. The possibility for creating a sparse output is given so that large and sparsely filled output spaces can be handled, as typically encountered when a dataset contains large amounts of different chemical elements. Various machine learning algorithms can make use of this sparse matrix output with linear algebra routines specifically designed for sparse data structures. \n\nOnce created, the descriptor object is ready to be used and provides different methods for interacting with it. All of the descriptors implement two methods: get number of features and create The get number of features-method can be used for querying the final number of features for the descriptor, even before a structure has been provided. This dimension can be used for initializing and reserving storage space for the resulting output array. create accepts one or multiple atomistic structures as an argument, and possibly other descriptor-specific arguments. It returns the final descriptor output that can be used in machine learning applications. To define atomic structures we use the ase.Atoms-object from the ase package[63]. The Atoms-objects are easy to create from structure files or build with the utilities provided by ase. \n\nAs the creation of a descriptor for an atomic system is completely independent from the other systems, it can be easily parallelized with data parallelism. For convenience we provide a possibility of parallelizing the descriptor creation for multiple samples over multiple processes. This can be done by simply providing the number of parallel jobs to instantiate with the n jobs-parameter as demonstrated in Figure 6. \n\nThe DScribe package is structured such that new descriptors can easily be added. We provide a python base-class that defines a standard interface for the descriptors through abstract classes. One of our design goals is to provide a codebase in which researchers can make their own descriptors available to the whole community. All descriptor implementations are accompanied by a test module that defines a set of standard tests. These tests include tests for rotational, translational and index permutation invariance, as well as other tests for checking the interface and functionality of the descriptor. We have adapted a continuous integration system that automatically \n\n1 runs a series of regression tests when changes in 2 the code are introduced. The code coverage is simultaneously measured as a percentage of visited code lines in the python interface. \n\nThe source code is directly available in github at https://github.com/SINGROUP/dscribe and we have created a dedicated home page at https: //singroup.github.io/dscribe/ that provides additional tutorials and a full code documentation. For easy installation the code is provided through the python package index (pip) under the name dscribe. \n\n![](images/9185bd23a3a7f644d88a8e3c44d684cc1817cfdfd663521c7fa0be0fe790b00e.jpg) \nFigure 7: Distribution of the formation energies together with the mean $(\\mu)$ , standard deviation ( $\\sigma$ ) and mean absolute deviation (MAD). \n\n# 4. Results and discussion \n\nThe applicability of the software is demonstrated by using the different descriptors in building a prediction model for formation energies of inorganic crystal structures and ionic charges of atoms in organic molecules. The used datasets are publicly available at Figshare (https://doi. org/10.6084/m9.figshare.c.4607783). These examples demonstrate the usage of the package in supervised machine learning tasks, but the output vectors can be as easily used in other learning tasks. For example the descriptors can be used as input for unsupervised clustering algorithms such as T-distributed stochastic neighbor embedding (T-SNE) [65] or Sketchmap [50] to analyse structure-property relations in structural and chem ical landscapes. \n\nFor simplicity we here restrict the machine learning model to be kernel ridge regression (KRR) as implemented in the scikit-learn package [66]. However, the vectorial nature of the output from all the introduced descriptors does not impose any specific learning scheme, and many other regressors can be used, including neural networks, decision trees and support vector regression. \n\n# 4.1. Formation energy prediction for inorganic crystals \n\nWe demonstrate the use of multiple descriptors on the task of predicting the formation energy of inorganic crystals. The data comes from the Open Quantum Materials Database (OQMD) 1.1 [67]. We selected structures with a maximum of 10 atoms per unit cell and a maximum of 6 different atomic elements. Unconverged systems were filtered by removing samples which have a formation energy that is more than two standard deviations away from the mean, resulting in the removal of 96 samples. After these selections, 222 215 samples were left. The distribution of the formation energies is shown in Figure 7. The models are trained and tested on total dataset sizes of 1024, 2048, 4096, 8192 and 16384, from which 80% is used as training data and $20\\%$ as test data. These sizes are selected as they are successive powers of two making them equidistant on a logarithmic grid. For each dataset size the results are averaged over three different random selections. The resulting mean absolute errors are given in Figure 8. A full breakdown of the results for each descriptor and dataset size along with other performance metrics – including root mean square error, squared Pearson correlation coefficient and maximum error – are given in the Supplementary Information. \n\nThe Coulomb matrix, Ewald sum matrix and sine matrix are used for the prediction with matrix rows and columns sorted by their Euclidean norm, and using the unit cell that was used for performing the formation energy calculation. The Coulomb matrix does not take the periodicity of the structure into account, but is included as a baseline for the other methods. We include MBTR with different values of $k$ and for each $k$ we individually optimize $\\sigma$ and $s_{k}$ with grid search. Figure 9 shows the error for each tested MBTR term, and the best performing one is included in Figure \n\n![](images/9ece6060b15c6d08526f1a15260a4b3238ffe69eb7ed2b986305d078a01d5fe8.jpg) \nFigure 8: Mean absolute error for formation energies in the test set as a function of training set size. The data consists of inorganic crystals from the OQMD database. The predictions are performed with kernel ridge regression and five different descriptors: Ewald sum matrix, Coulomb matrix, sine matrix, MBTR $\\mathcal{\\kappa}$ =1,2,3 and an averaged SOAP output for all atoms in the crystal. The figure shows an average over three randomly selected datasets, with the standard deviation shown by the shaded region. \n\n8. To test the energy prediction by combining information from multiple local descriptors, as discussed in 2.7, we also include results using a simple averaged SOAP output for all atoms in the simulation cell. For SOAP we use the gaussian type orbital basis and fix $n_{\\mathrm{max}}=8$ and $l_{\\mathrm{max}}\\equiv8$ , but optimize the cutoff $r_{\\mathrm{cut}}$ and gaussian width $\\sigma$ individually with grid search. \n\nThe possible descriptor hyperparameters are optimized at a subset of $2^{12}=4096$ samples with 5-fold cross-validation and 80%/20%-training/test split. The KRR kernel width and the regularization parameter are also allowed to vary on a logarithmic grid during the descriptor hyperparameter search. The use of a smaller subset allows much quicker evaluation for the hyperparameters than optimizing the hyperparameters for each size individually, but the transferability of these optimized hyperparameters to different sizes may affect the results slightly. After finding the optimal descriptor setup, it is used in training a model for all the different dataset sizes. The same cross-validation setup as for the descriptor hyperparameter optimization is used, but now with a finer grid for the KRR kernel width. The hyperparameter grids and optimal values for both the descriptors and kernel ridge regression are found in the Supplementary Information together with additional details. \n\n![](images/9d7b1d6866315084f5adaef66444c242def0ce71ca49f1caa1361a916bda8fab.jpg) \nFigure 9: Breakdown of the error for formation energies in the test set for different MBTR-terms. The predictions are performed with kernel ridge regression and four different MBTR configurations: MBTR $k{=}1$ , MBTR $\\scriptstyle{k=2}$ , MBTR $k{=}3$ and $\\mathrm{MBTR}_{k=1,2,3}$ which includes all three terms, each term normalized to unit length. The figure shows an average over three randomly selected datasets, with the standard deviation shown by the shaded region. \n\n# 4.2. Ionic charge prediction for organic molecules \n\nTo demonstrate the prediction of local properties with the DScribe package, a prediction of ionic charges in small organic molecules is performed with the different local descriptors included in the package. The dataset consists of Mulliken charges calculated at the CCSD level for the GDB9 dataset of 133 885 neutral molecules [68]. The structures contain up to nine atoms and five different chemical species: hydrogen, carbon, nitrogen, oxygen, and fluorine with 1 230 122, 846 \n\n![](images/9a6e17462fb7b8abcde676ca02bbd3e253cd89c159b6cdd2aefd30e8ba98b091.jpg) \nFigure 10: Parity plot of ionic charge prediction results from the test set against true CCSD ionic charges. The predictions are performed with kernel ridge regression using $\\mathrm{SOAP_{gto}}$ (gaussian type orbital basis), $\\operatorname{SOAP}_{\\operatorname{poly}}$ (polynomial basis) and ACSF. The mean absolute error (MAE), root mean square error (RMSE), squared Pearson correlation coefficient $\\mathrm{\\Delta^{R^{2}}}$ ) and maximum error are also shown together with the total error distribution in the inset. \n\n![](images/cb7d9e381ae1251d2bac17f4dd46d1b409864140bfc3f157ee38c706be8f7e2a.jpg) \nFigure 11: Distribution of the ionic charges for each chemical species together with the mean $(\\mu)$ , standard deviation $(\\sigma)$ and mean absolute deviation (MAD). \n\n557, 139 764, 187 996 and 3314 atoms present for each species respectively. The distribution of the ionic charges for each species is shown in Figure 11. The geometries have been relaxed at the B3LYP/6-31G(2df,p) level and no significant forces were present in the static CCSD calculation. The models are trained and tested on a subset of 10 000 samples per chemical species (except fluorine, for which only 3314 atoms were available and all are used), from which $80\\%$ is used as training data and 20% as test data. The combined parity plots for all five chemical species together with error metrics are given in Figure 10. A breakdown of the results for each species separately is given \n\n# in the Supplementary Information. \n\nThe prediction is performed with the two local descriptors included in the package, SOAP and ACSF. For SOAP we perform the prediction with both radial basis functions: the polynomial basis $(\\mathrm{SOAP_{poly}}$ ) and the gaussian type orbital radial basis $(\\mathrm{SOAP_{gto}}$ ). For them we fix $n_{\\mathrm{max}}=8$ and $l_{\\mathrm{max}}=8$ , but optimize the cutoff $r_{\\mathrm{cut}}$ and Gaussian width $o$ with grid search. For ACSF we use 10 radial functions $G^{2}$ and 8 angular functions $G^{3}$ . The cutoff value $r_{\\mathrm{cut}}$ is shared between the radial and angular functions and it is optimized with grid search. More details about the used ACSF symmetry functions are found in the Supplementary Information. \n\nDescriptor hyperparameters are optimized with grid search separately for each species on a smaller set of 2500 sample atoms with 5-fold cross-validation and 80%/20%-training/test split. Both the KRR kernel width and the regularization parameter are allowed to vary on a logarithmic grid during the descriptor hyperparameter search. After finding the optimal descriptor setup, it is used in training a model for full dataset of 10 000 samples (except for fluorine with 3314 total samples). The training is done with the same cross-validation setup as for the descriptor hyperparameter optimization, but now with finer grid for the KRR kernel width. The hyperparameter grids and optimal values for both the descriptors and kernel ridge regression are found in the Supplementary Information together with additional details. \n\n# 4.3. Discussion \n\nThe formation energy prediction demonstrates that our implementation performs consistently and offers insight into the performance of the different descriptors. Special care must be taken in interpreting the results, as there exist different variations of the different descriptors. For example, as discussed in section 2.7, there are different ways to combine information from multiple local SOAP-outputs, and different geometry functions and cutoff types may be used for the MBTR. The learning rates also depend on the chosen machine learning model. \n\nWith SOAPaverage and a training set of 0.8 $2^{14}=13107$ samples the best mean absolute error of 0.117 eV/atom is achieved. It has been demonstrated that a similar mean absolute error (0.09 eV/atom [5] and 0.12 eV/atom [40]) can be used for virtual screening of materials by stability. The fact that the training data contains 89 chemical elements and various structural phases makes highly accurate predictions challenging and the error is still relatively large when compared against the mean absolute deviation of 0.493 eV/atom for the labels. As shown by earlier research [29, 32, 69], the prediction error can be reduced further by using a learning model with a more intelligent scheme for combining local structural information. \n\nOur results for the Ewald sum matrix and the sine matrix reflect the results reported earlier, where a formation energy prediction was performed for a similar set of data from the Materials Project [70]. They report MAE for the Ewald sum matrix to be 0.49 eV and for the sine matrix to be 0.37 eV [7] with a training set of 3000 samples, whereas we find MAE for the Ewald sum matrix to be 0.36 eV and for the sine matrix to be 0.24 eV with a training set of 3276 samples. The performance improvement in our results can be explained by differences in the contents of the used dataset. We, however, recover the same trend of the sine matrix performing better, even when issues in the original formulation of the Ewald sum matrix (as discussed in section 2.2) were addressed. The low performance of the more accurate charge interaction in the Ewald model and the relatively small difference between the performance of the Coulomb and sine matrix may indicate that for this task the information of the potential energy of the neutral atoms – contained on the diagonal of both the sine and Coulomb matrix – largely controls the performance. \n\nWith respect to the individual performance of the different MBTR parts, the $k=2$ terms containing distance information performs best, whereas the angle information contained in $k~=~3$ and the simple composition information contained by $k=1$ lag behind. However, the best MBTR performance is achieved by combining the information from all of the terms. It is also surprising how well the simple averaging scheme for SOAP performs in the tested dataset range. When extrapolating the performance to larger datasets, it can however be seen that MBTR may provide better results. \n\nThe charge prediction test illustrates that the ionic charges of different species in organic molecules may be learned accurately on the CCSD level just by observing the local arrangement of atoms up to a certain radial cutoff. On average the mean absolute error is around 0.005-0.01 e when using up to 10 000 samples for each species. \n\nThe best mean absolute error of 0.0054 $e$ and root mean square error of 0.0100 $e$ is achieved with SOAP $\\mathrm{gto}$ . A similar root mean square error of 0.016 $e$ was achieved in a recent machine learning based partial charge prediction for druglike molecules using charges extracted from DFT electron density[71]. The machine learned partial charges offer a great balance between accuracy and computational cost, making them an attractive alternative to full quantum chemical calculations or empirical charge models. Potential applications include the parametrization of partial charges in classical molecular dynamics and quantitative structure–activity relationship (QSAR) mo els [71]. \n\nFigure 11 shows that the deviation of the charg in the dataset depends on the species, which is also transferred to a species-specific variation of the prediction error included in the Supplementary Information. As to be expected, the charge of the multi-valent species – C, N, O – varies much more in the CCSD data and is much harder to predict than the charge of the low valence species H and F. Predicting the ionic charge of carbon is most difficult and so most of the outliers correspond to carbon atoms, with a few noticeable outliers corresponding also to oxygen and nitrogen atoms. \n\nOur comparison shows that there is little difference between the predictive performance of the two radial bases used for SOAP. With our current implementation there is, however, a notable difference in the speed of creating these descriptors. For identical settings ( $n_{\\mathrm{max}}=8$ , $l_{\\mathrm{max}}=8$ , $r_{\\mathrm{cut}}~=~5$ , and $\\sigma=0.1$ ), the gaussian type orbital basis is over four times faster to calculate than the polynomial basis. This difference originates largely from the numerical radial integration, which is required for the polynomial basis but not for the gaussian type orbital basis. The prediction performance of ACSF does not fall far behind SOAP and it might be possible to achieve the same accuracy by using a more advanced parameter calibration for the symmetry functions. The symmetry functions used in ACSF are easier to tune for capturing specific structural properties, such as certain pairwise distances or angles formed by three atoms. This tuning can, however, be done only if such intuition is available a priori, and in general consistently improving the performance by changing the used symmetry functions can be hard. \n\n# 5. Conclusions \n\nThe recent boom in creating machine learnable fingerprints for atomistic systems, or descriptors, has led to a plethora of available options for materials science. The software implementations for these descriptors is, however, often scattered across different libraries or missing altogether, making it difficult to test and compare \n\ndifferent alternatives. \n\nWe have collected several descriptors in the DScribe software library. DScribe has an easyto-use python-interface, with C/C++ extensions for the computationally intensive tasks. We use a set of regression tests to ensure the validity of the implementation, and provide the source code together with tutorials and documentation. We have demonstrated the applicability of the package with the supervised learning tasks of formation energy prediction for crystals and the charge prediction for molecules. The DScribe descriptors are compatible with general-purpose machine learning algorithms, and can also be used for unsupervised learning tasks. In the future we plan to extend the package with new descriptors and also welcome external contributors. \n\n# 6. Acknowledgements \n\nWe acknowledge the computational resources provided by the Aalto Science-IT project. This project has received funding from the Jenny and Antti Wihuri Foundation and the European Union’s Horizon 2020 research and innovation programme under grant agreements number no. 676580 NOMAD and no. 686053 CRITCAT. \n\n[1] K. Takahashi, Y. Tanaka, Materials informatics: a journey towards material design and synthesis, Dalton Trans. 45 (26) (2016) 10497–10499. \n[2] L. Zdeborov´a, Machine learning: New tool in the box, Nat. Phys. 13 (5) (2017) 420–421. \n[3] J. E. Gubernatis, T. Lookman, Machine learning in materials design and discovery: Examples from the present and suggestions for the future, Phys. Rev. Materials 2 (12) (2018) 120301. \n[4] K. T. Butler, D. W. Davies, H. Cartwright, O. Isayev, A. Walsh, Machine learning for molecular and materials science, Nature 559 (7715) (2018) 547–555. \n[5] L. Ward, R. Liu, A. Krishna, V. I. Hegde, A. Agrawal, A. Choudhary, C. Wolverton, Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations, Phys. Rev. B 96 (2) (2017) 1–12. \n[6] H. Huo, M. Rupp, Unified Representation of Molecules and Crystals for Machine Learning, arXiv e-prints arXiv:1704.06439. \n[7] F. Faber, A. Lindmaa, O. A. v. Lilienfeld, R. Armiento, Crystal structure representations for machine learning models of formation energies, Int. J. Quantum Chem. 115 (16) (2015) 1094–1101. \n[8] A. Seko, H. Hayashi, K. Nakayama, A. Takahashi, I. Tanaka, Representation of compounds for machinelearning prediction of physical properties, Phys. Rev. B 95 (14) (2017) 144110. \n[9] M. Rupp, A. Tkatchenko, K.-R. Mu¨ller, O. A. von Lilienfeld, Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning, Phys. Rev. Lett. 108 (2012) 058301. \n[10] A. Stuke, M. Todorovic´, M. Rupp, C. Kunkel, K. Ghosh, L. Himanen, P. Rinke, Chemical diversity in molecular orbital energy predictions with kernel ridge regression, J. Chem. Phys. 150 (20) (2019) 204121. \n[11] K. Ghosh, A. Stuke, M. Todorovic´, P. B. Jørgensen, M. N. Schmidt, A. Vehtari, P. Rinke, Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra, Adv. Sci. 6 (9) (2019) 1801367. \n[12] J. S. Smith, O. Isayev, A. E. Roitberg, ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost, Chem. Sci. 8 (2017) 3192–3203. \n[13] A. P. Bart´ok, M. C. Payne, R. Kondor, G. Cs´anyi, Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons, Phys. Rev. Lett. 104 (13) (2010) 1–4. \n[14] A. P. Bart´ok, R. Kondor, G. Cs´anyi, On representing chemical environments, Phys. Rev. B 87 (2013) 184115. \n[15] S. Chmiela, A. Tkatchenko, H. E. Sauceda, I. Poltavsky, K. T. Schu¨tt, K.-R. Mu¨ller, Machine learning of accurate energy-conserving molecular force fields, Sci. Adv. 3 (5) (2017) e1603015. \n[16] J. Behler, Atom-centered symmetry functions for constructing high-dimensional neural network potentials, J. Chem. Phys. 134 (7) (2011) 074106. \n[17] J. Behler, Perspective: Machine learning potentials for atomistic simulations, J. Chem. Phys. 145 (17) (2016) 170901. \n[18] Y. Li, H. Li, F. C. Pickard, B. Narayanan, F. G. Sen, M. K. Y. Chan, S. K. R. S. Sankaranarayanan, B. R. Brooks, B. Roux, Machine Learning Force Field Parameters from Ab Initio Data, J. Chem. Theory Comput. 13 (9) (2017) 4492–4503. \n[19] T. L. Jacobsen, M. S. Jørgensen, B. Hammer, On-theFly Machine Learning of Atomic Potential in Density Functional Theory Structure Optimization, Phys. Rev. Lett. 120 (2) (2018) 026102. \n[20] Z. Li, S. Wang, W. S. Chin, L. E. Achenie, H. Xin, High-throughput screening of bimetallic catalysts enabled by machine learning, J. Mater. Chem. A 99 (2017) 016105. \n[21] B. R. Goldsmith, J. Esterhuizen, J. X. Liu, C. J. Bartel, C. Sutton, Machine learning for heterogeneous catalyst design and discovery, AIChE Journal 64 (7) (2018) 2311–2323. \n[22] A. J. Chowdhury, W. Yang, E. Walker, O. Mamun, A. Heyden, G. A. Terejanu, Prediction of Adsorption Energies for Chemical Species on Metal Catalyst Surfaces Using Machine Learning, J. Phys. Chem. C 122 (49) (2018) 28142–28150. \n[23] M. O. J. J¨ager, E. V. Morooka, F. F. Canova, L. Himanen, A. S. Foster, Machine learning hydrogen adsorption on nanoclusters through structural descriptors, npj Comput. Mater. 4 (2018) 37. \n[24] A. F. Zahrt, J. J. Henle, B. T. Rose, Y. Wang, W. T. Darrow, S. E. Denmark, Prediction of higherselectivity catalysts by computer-driven workflow and machine learning, Science 363 (6424) (2019) eaau5631. \n[25] S. Kiyohara, H. Oda, T. Miyata, T. Mizoguchi, Prediction of interface structures and energies via virtual screening, Sci. Adv. 2 (11) (2016) e1600746. \n[26] P. Zalake, S. Ghosh, S. Narasimhan, K. G. Thomas, Descriptor-Based Rational Design of TwoDimensional Self-Assembled Nanoarchitectures Stabilized by Hydrogen Bonds, Chem. Mater. 29 (17) (2017) 7170–7182. \n[27] M. Todorovic´, M. U. Gutmann, J. Corander, P. Rinke, Bayesian inference of atomistic structure in functional materials, npj Comput. Mater. 5 (2019) 35. \n[28] L. M. Ghiringhelli, J. Vybiral, S. V. Levchenko, C. Draxl, M. Scheffler, Big Data of Materials Science: Critical Role of the Descriptor, Phys. Rev. Lett. 114 (2015) 105503. \n[29] T. Xie, J. C. Grossman, Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties, Phys. Rev. Lett. 120 (14) (2018) 145301. \n[30] F. Arbabzadah, S. Chmiela, K. R. Mu¨ller, A. Tkatchenko, Quantum-chemical insights from deep tensor neural networks, Nat. Commun. 8 (2017) 6–13. \n[31] J. Gilmer, S. S. Schoenholz, P. F. Riley, O. Vinyals, G. E. Dahl, Neural Message Passing for Quantum Chemistry, Proceedings of the 34th International Conference on Machine Learning (2017) 1263–1272. \n[32] K. T. Schu¨tt, H. E. Sauceda, P. J. Kindermans, A. Tkatchenko, K. R. Mu¨ller, SchNet - A deep learning architecture for molecules and materials, J. Chem. Phys. 148 (24) (2018) 241722. \n[33] G. Montavon, K. Hansen, S. Fazli, M. Rupp, F. Biegler, A. Ziehe, A. Tkatchenko, A. V. Lilienfeld, K.-R. Mu¨ller, Learning Invariant Representations of Molecules for Atomization Energy Prediction, in: F. Pereira, C. J. C. Burges, L. Bottou, K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 25, Curran Associates, Inc., 440– 448, 2012. \n[34] K. Hansen, F. Biegler, R. Ramakrishnan, W. Pronobis, O. A. Von Lilienfeld, K. R. Mu¨ller, A. Tkatchenko, Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space, J. Phys. Chem. Lett. 6 (12) (2015) 2326–2331. \n[35] M. Gastegger, L. Schwiedrzik, M. Bittermann, F. Berzsenyi, P. Marquetand, WACSF - Weighted atom-centered symmetry functions as descriptors in machine learning potentials, J. Chem. Phys. 148 (24) (2018) 241709. \n[36] O. Isayev, C. Oses, C. Toher, E. Gossett, S. Curtarolo, A. Tropsha, Universal fragment descriptors for predicting properties of inorganic crystals, Nat. Commun. 8 (2017) 15679. \n[37] F. A. Faber, A. Lindmaa, O. A. Von Lilienfeld, R. Armiento, Machine Learning Energies of 2 Million Elpasolite (ABC2D6) Crystals, Phys. Rev. Lett. 117 (13) (2016) 2–7. \n[38] F. A. Faber, A. S. Christensen, B. Huang, O. A. von Lilienfeld, Alchemical and structural distribution based representation for universal quantum machine learning, J. Chem. Phys. 148 (24) (2018) 241717. \n[39] W. Pronobis, A. Tkatchenko, K.-R. M¨uller, ManyBody Descriptors for Predicting Molecular Properties with Machine Learning: Analysis of Pairwise and Three-Body Interactions in Molecules, J. Chem. Theory Comput. 14 (6) (2018) 2991–3003. \n[40] K. Choudhary, B. DeCost, F. Tavazza, Machine learning with force-field-inspired descriptors for materials: Fast screening and mapping energy landscape, Phys. Rev. Materials 2 (2018) 083801. \n[41] F. A. Faber, L. Hutchison, B. Huang, J. Gilmer, S. S. Schoenholz, G. E. Dahl, O. Vinyals, S. Kearnes, P. F. Riley, O. A. Von Lilienfeld, Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error, J. Chem. Theory Comput. 13 (11) (2017) 5255–5264. \n[42] R. Ouyang, S. Curtarolo, E. Ahmetcik, M. Scheffler, L. M. Ghiringhelli, SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates, Phys. Rev. Materials 2 (2018) 083802. \n[43] A. S. Christensen, F. A. Faber, B. Huang, L. A. Bratholm, A. Tkatchenko, K.-R. Muller, O. A. von Lilienfeld, QML: A Python Toolkit for Quantum Machine Learning, URL https://github.com/ qmlcode/qml, 2019. \n[44] A. Khorshidi, A. A. Peterson, Amp: A modular approach to machine learning in atomistic simulations, Computer Physics Communications 207 (2016) 310 – 324, ISSN 0010-4655, URL http://www.sciencedirect.com/science/ article/pii/S0010465516301266. \n[45] Magpie: A Materials-Agnostic Platform for Informatics and Exploration, URL https://bitbucket.org/ wolverton/magpie, 2019. \n[46] QUIP and quippy documentation, URL http:// libatoms.github.io/QUIP, 2019. \n[47] M. Haghighatlari, J. Hachmann, ChemML – A Machine Learning and Informatics Program Suite for Chemical and Materials Data Mining, URL https: //hachmannlab.github.io/chemml, 2019. \n[48] L. Ward, A. Dunn, A. Faghaninia, N. Zimmermann, S. Bajaj, Q. Wang, J. Montoya, J. Chen, K. Bystrom, M. Dylla, K. Chard, M. Asta, K. Persson, G. Snyder, I. Foster, A. Jain, Matminer: An open source toolkit for materials data mining, Comput. Mater. Sci. 152 (2018) 60–69, ISSN 0927-0256. \n[49] D. H. Wolpert, W. G. Macready, No free lunch theorems for optimization, IEEE Trans. Evol. Comput. 1 (1) (1997) 67–82. \n[50] M. Ceriotti, G. A. Tribello, M. Parrinello, Simplifying the representation of complex free-energy landscapes using sketch-map, Proc. Natl. Acad. Sci. U.S.A. 108 (32) (2011) 13023–13028. \n[51] S. De, A. P. Bart´ok, G. Cs´anyi, M. Ceriotti, Comparing molecules and solids across structural and alchemical space, Phys. Chem. Chem. Phys. 18 (20) (2016) 13754–13769. \n[52] O. Isayev, D. Fourches, E. N. Muratov, C. Oses, K. Rasch, A. Tropsha, S. Curtarolo, Materials cartography: Representing and mining materials space using structural and electronic fingerprints, Chem. Mater. 27 (3) (2015) 735–743. \n[53] R. Ramakrishnan, M. Hartmann, E. Tapavicza, O. A. von Lilienfeld, Electronic spectra from TDDFT and machine learning in chemical space, J. Chem. Phys. 143 (8) (2015) 084111. \n[54] P. P. Ewald, Die Berechnung optischer und elektrostatischer Gitterpotentiale, Ann. Phys. 369 (3) (1921) 253–287. \n[55] A. Y. Toukmaji, J. A. Board, Ewald summation techniques in perspective: a survey, Comput. Phys. Commun. 95 (2) (1996) 73–92. \n[56] J. S. Hub, B. L. de Groot, H. Grubmu¨ller, G. Groenhof, Quantifying Artifacts in Ewald Simulations of Inhomogeneous Systems with a Net Charge, J. Chem. Theory Comput. 10 (1) (2014) 381–390. \n[57] R. A. Jackson, C. R. Catlow, Computer Simulation Studies of Zeolite Structure, Mol. Simul. 1 (4) (1988) 207–224. \n[58] N. Gerrits, K. Shakouri, J. Behler, G.-J. Kroes, Accurate Probabilities for Highly Activated Reaction of Polyatomic Molecules on Surfaces Using a HighDimensional Neural Network Potential: CHD3 + Cu(111), J. Phys. Chem. Lett. 10 (2019) 1763–1768. \n[59] N. Artrith, A. Urban, An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO2, Comput. Mater. Sci. 114 (2016) 135–150. \n[60] T. T. Nguyen, E. Sze´kely, G. Imbalzano, J. Behler, G. Cs´anyi, M. Ceriotti, A. W. G¨otz, F. Paesani, Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation \n\nModel. 58 (3) (2018) 579–590. \n\nmany-body expansions, J. Chem. Phys. 148 (24) (2018) 241725. \n[61] P. L¨owdin, On the Non-Orthogonality Problem Connected with the Use of Atomic Wave Functions in the Theory of Molecules and Crystals, J. Chem. Phys. 18 (3) (1950) 365–375. \n[62] M. J. Willatt, F. Musil, M. Ceriotti, A Data-Driven Construction of the Periodic Table of the Elements, arXiv e-prints arXiv:1807.00236. \n[63] A. H. Larsen, J. J. Mortensen, J. Blomqvist, I. E. Castelli, R. Christensen, M. Du ak, J. Friis, M. N. Groves, B. Hammer, C. Hargus, E. D. Hermes, P. C. Jennings, P. B. Jensen, J. Kermode, J. R. Kitchin, E. L. Kolsbjerg, J. Kubal, K. Kaasbjerg, S. Lysgaard, J. B. Maronsson, T. Maxson, T. Olsen, L. Pastewka, A. Peterson, C. Rostgaard, J. Schiøtz, O. Schu¨tt, M. Strange, K. S. Thygesen, T. Vegge, L. Vilhelmsen, M. Walter, Z. Zeng, K. W. Jacobsen, The atomic simulation environment – a Python library for working with atoms, Journal of Physics: Condensed Matter 29 (27) (2017) 273002. \n[64] S. P. Ong, W. D. Richards, A. Jain, G. Hautier, M. Kocher, S. Cholia, D. Gunter, V. L. Chevrier, K. A. Persson, G. Ceder, Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis, Comput. Mater. Sci. 68 (2013) 314–319. \n[65] L. van der Maaten, G. Hinton, Visualizing Data using t-SNE, J. Mach. Learn. Res. 9 (2008) 2579–2605. \n[66] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, E. Duchesnay, Scikit-learn: Machine Learning in Python, J. Mach. Learn. Res. 12 (2011) 2825–2830. \n[67] J. E. Saal, S. Kirklin, M. Aykol, B. Meredig, C. Wolverton, Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD), JOM 65 (11) (2013) 1501–1509. \n[68] R. Ramakrishnan, P. O. Dral, M. Rupp, O. A. von Lilienfeld, Quantum chemistry structures and properties of 134 kilo molecules, Sci. Data 1 (2014) 140022. \n[69] C. Chen, W. Ye, Y. Zuo, C. Zheng, S. P. Ong, Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals, Chem. Mater. 31 (9) (2019) 3564–3572. \n[70] A. Jain, S. P. Ong, G. Hautier, W. Chen, W. D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, K. a. Persson, The Materials Project: A materials genome approach to accelerating materials innovation, APL Mater. 1 (1) (2013) 011002. \n[71] P. Bleiziffer, K. Schaller, S. Riniker, Machine Learning of Partial Charges Derived from High-Quality Quantum-Mechanical Calculations, J. Chem. Inf. \n\n# PROGRAM SUMMARY \n\nProgram Title: DScribe \nProgram Files doi: http://dx.doi.org/10.17632/vzrs8n8pk6.1 \nLicensing provisions: Apache-2.0 \nProgramming language: Python/C/C++ \nSupplementary material: Supplementary Information as PDF \nNature of problem: The application of machine learning for materials science is hindered by the lack of consistent software implementations for feature transformations. These feature transformations, also called descriptors, are a key step in building machine learning models for property prediction in materials science. \nSolution method: We have developed a library for creating common descriptors used in machine learning applied to materials science. We provide an implementation the following descriptors: Coulomb matrix, Ewald sum matrix, sine matrix, Many-body Tensor Representation (MBTR), Atom-centered Symmetry Functions (ACSF) and Smooth Overlap of Atomic Positions (SOAP). The library has a python interface with computationally intensive routines written in $\\mathrm{C}$ or C++. The source code, tutorials and documentation are provided online. A continuous integration mechanism is set up to automatically run a series of regression tests and check code coverage when the codebase is updated. " + }, + { + "id": "10.1002_adma.202004670", + "DOI": "10.1002/adma.202004670", + "DOI Link": "http://dx.doi.org/10.1002/adma.202004670", + "Relative Dir Path": "mds/10.1002_adma.202004670", + "Article Title": "Coexisting Single-Atomic Fe and Ni Sites on Hierarchically Ordered Porous Carbon as a Highly Efficient ORR Electrocatalyst", + "Authors": "Zhu, ZJ; Yin, HJ; Wang, Y; Chuang, CH; Xing, L; Dong, MY; Lu, YR; Casillas-Garcia, G; Zheng, YL; Chen, S; Dou, YH; Liu, P; Cheng, QL; Zhao, HJ", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "The development of oxygen reduction reaction (ORR) electrocatalysts based on earth-abundant nonprecious materials is critically important for sustainable large-scale applications of fuel cells and metal-air batteries. Herein, a hetero-single-atom (h-SA) ORR electrocatalyst is presented, which has atomically dispersed Fe and Ni coanchored to a microsized nitrogen-doped graphitic carbon support with unique trimodal-porous structure configured by highly ordered macropores interconnected through mesopores. Extended X-ray absorption fine structure spectra confirm that Fe- and Ni-SAs are affixed to the carbon support via Fe-N(4)and Ni-N(4)coordination bonds. The resultant Fe/Ni h-SA electrocatalyst exhibits an outstanding ORR activity, outperforming SA electrocatalysts with only Fe- or Ni-SAs, and the benchmark Pt/C. The obtained experimental results indicate that the achieved outstanding ORR performance results from the synergetic enhancement induced by the coexisting Fe-N(4)and Ni-N(4)sites, and the superior mass-transfer capability promoted by the trimodal-porous-structured carbon support.", + "Times Cited, WoS Core": 510, + "Times Cited, All Databases": 528, + "Publication Year": 2020, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000569825900001", + "Markdown": "# Coexisting Single-Atomic Fe and Ni Sites on Hierarchically Ordered Porous Carbon as a Highly Efficient ORR Electrocatalyst \n\nZhengju Zhu, Huajie Yin,\\* Yun Wang, Cheng-Hao Chuang, Lei Xing, Mengyang Dong, Ying-Rui Lu, Gilberto Casillas-Garcia, Yonglong Zheng, Shan Chen, Yuhai Dou, Porun Liu, Qilin Cheng, and Huijun Zhao\\* \n\nThe development of oxygen reduction reaction (ORR) electrocatalysts based on earth-abundant nonprecious materials is critically important for sustainable large-scale applications of fuel cells and metal–air batteries. Herein, a hetero-single-atom (h-SA) ORR electrocatalyst is presented, which has atomically dispersed Fe and Ni coanchored to a microsized nitrogen-doped graphitic carbon support with unique trimodal-porous structure configured by highly ordered macropores interconnected through mesopores. Extended X-ray absorption fine structure spectra confirm that Fe- and Ni-SAs are affixed to the carbon support via $F e-N_{4}$ and $N i-N_{4}$ coordination bonds. The resultant Fe/Ni h-SA electrocatalyst exhibits an outstanding ORR activity, outperforming SA electrocatalysts with only Fe- or Ni-SAs, and the benchmark $\\mathsf{P t}/\\mathsf{C}$ . The obtained experimental results indicate that the achieved outstanding ORR performance results from the synergetic enhancement induced by the coexisting $F e-N_{4}$ and $N i-N_{4}$ sites, and the superior mass-transfer capability promoted by the trimodal-porous-structured carbon support. \n\nThe development of oxygen reduction reaction (ORR) electrocatalysts based on earth-abundant nonprecious materials to replace the scarce platinum-group-metal-based ones is critically important for sustainable large-scale commercial applications of fuel cells and metal–air batteries.[1] The extensive research efforts over the recent years have led to a variety of nonprecious ORR electrocatalysts.[2] Among them, the nitrogen-coordinated transition-metal (TM) single-atoms (SAs) supported on carbon substrates have emerged as a new class of ORR electrocatalysts with enormous potentials.[3–5] These SA electrocatalysts (SAECs) anchor TM-SAs to the carbon substrates via TM– nitrogen $(\\mathrm{TM}-\\mathrm{N}_{x})$ coordination bonds that also act as the ORR active sites. It has been commonly accepted that the ORR activity of such $\\mathrm{TM}{-}\\mathrm{N}_{x}$ -coordinated SA sites can be promoted by optimizing the binding strengths of ORR intermediates (e.g., $\\mathrm{\\ddot{\\iota}O}_{2}$ $\\mathrm{\\\"{ooH}}$ , $\\mathrm{\\mathrm{^{*}O H}}$ , $^{*}\\mathrm{O}^{\\mathrm{'}}$ ) to the active site via the altering of their electronic structures.[6] Various approaches have been reported to alter the electronic structures of $\\mathrm{TM}-\\mathrm{N}_{x}$ -coordinated SA sites by modulating N types and coordinating numbers,[7] partially replacing N with other nonmetal elements (e.g., O, S, and P),[8] or the chemical compositions of carbon substrates.[9] Recently, the hetero-SAs (h-SAs) involving two different TMs (e.g., Co/Zn, Fe/Co, Fe/ Zn) have been successfully anchored to the carbon substrates as ORR SAECs.[10] Such an approach takes the advantage of the coexistence of two different TM-SA sites, through the pairing and/or long-range coupling to alter each other’s coordination environments, hence the electronic structures, to enhance ORR performance.[11,12] \n\nIt is well-known that the performance of an electrocatalyst is determined not only by its intrinsic activity, but also the number of accessible active sites. The latter depends heavily on the dimension, geometry, and more profoundly, the pore structure of the electrocatalyst. Due to the high intrinsic activity nature of SAs and the relatively low solubility of $\\mathrm{O}_{2}$ in aquatic media, a high performance ORR SAEC needs to be affixed on a carbon support with optimal pore structures.[13,14] Ideally, a carbon substrate should possess a trimodal-porous structure: abundant micropores $(<2\\ \\mathrm{\\nm})$ to expose large numbers of $\\mathrm{TM-N}_{x}$ -coordinated SA active sites, mesopores $(2-50\\ \\mathrm{nm})$ to facilitate local accessibility, and macropores $(>50\\ \\mathrm{nm})$ to promote long-range mass transfer.[13,15] The mostly reported SAECs to date are nanoparticle (NP) forms with sizes between 10 and $100\\ \\mathrm{nm}$ that only possess micro- and mesopores, while the macropores can only be formed by the randomly packed NPs on the substrate electrode, resulting in the uncontrollable distribution and connectivity of mesopores and macropores.[16,17] To this end, the controllably anchoring SAs to a microsized trimodal-porous carbon support with the mesopore-interconnected ordered macropores structure could be an effective solution to achieve rapid mass transfer to all accessible SA active sites, however, yet to be realized due to the challenges involved in the synthetic processes. \n\nHerein, we report a h-SA ORR electrocatalyst with atomically dispersed Fe and Ni coanchored to a microsized trimodalporous structured nitrogen-doped graphitic carbon support with highly ordered macropores (denoted as $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC})$ . A template method is innovatively combined with wet-chemistry metal-ion impregnation and pyrolysis to simultaneously fabricate the uniquely configured trimodal-porous carbon support with highly ordered macropores interconnected by mesopores, and anchor Fe- and Ni-SAs via the $\\mathrm{Fe-N_{4}}$ and $\\mathrm{Ni-N_{4}}$ coordination bonds. The resultant $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ with Fe/Ni h-SAs possesses outstanding ORR activity, outperforming the SAECs with only Fe- or Ni-SAs, and the benchmark $\\mathrm{Pt/C}$ . The obtained experimental results indicate that the outstanding ORR performance of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ is resulted from the synergetic enhancement induced by the coexisting $\\mathrm{Fe-N}_{4}{\\cdot}$ and $\\mathrm{Ni-N_{4}}.$ coordinated SA sites, and the superior mass transfer promoted by the trimodal-porous structure of the carbon support. \n\nFigure  1a schematically illustrates the synthetic procedure of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ . In brief, the presynthesized polystyrene spheres (PSs, $270\\ \\mathrm{nm}$ in diameter) were first assembled into a 3D-ordered PS template (Figure S1a–c, Supporting Information).[18] The $\\mathrm{Fe}^{3+}$ and $\\mathrm{Ni}^{2+}$ were then impregnated via the formation of ZIF-8 $\\mathrm{\\cdot\\ZIF=}$ zeolitic imidazolate framework) on the PS template in the presence of both $\\mathrm{Fe}^{3+}$ and $\\mathrm{Ni^{2+}}$ (denoted as (Fe, Ni)-ZiF- $8@\\mathrm{PS}$ , Figure S1d (Supporting Information)). The obtained (Fe, Ni)-ZiF- $8@\\mathrm{PS}$ was subjected to pyrolysis to decompose PSs and carbonize ZIF-8 (Figure S2, Supporting Information), while simultaneously anchor Fe and Ni to the formed carbon support, resulting in the uniformly sized and cuboctahedron-shaped $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ with an average size of $1.6~{\\upmu\\mathrm{m}}$ (Figure 1b and Figures S3a and S4a (Supporting Information)). The scanning electron microscopy (SEM), transmission electron microscopy (TEM), and high-angle annular darkfield scanning transmission electron microscopy (HAADFSTEM) images of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ (Figure 1c–e, and Figures S3b and S4b (Supporting Information)) reveal a cuboctahedronshaped structure with 3D-ordered macropores $(\\approx180\\ \\mathrm{nm})$ ) interconnected by $30{\\mathrm{-}}60\\ \\mathrm{nm}$ mesopores channels. Other than the mesopore channels, the abundant mesopores sized from 3 to $50\\ \\mathrm{nm}$ are presented on the carbon wall architectures (Figure S5, Supporting Information). The pore structure characteristics were further analyzed by $\\mathrm{N}_{2}$ adsorption–desorption isotherms (Figure $\\mathrm{1f,g}^{\\prime}$ and summarized in Table S1 (Supporting Information), which confirm the presence of micropores and reveal a Brunauer–Emmett–Teller (BET) surface area of $800.9~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ with an external surface area of $289.7\\mathrm{m}^{2}\\mathrm{g}^{-1}$ [3c,13,19] These results confirm the unique trimodal-porous structure of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ . To further illustrate the formation of the hierarchical porous structure, $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{C}$ with the average size of $85\\ \\mathrm{nm}$ and $1.4~{\\upmu\\mathrm{m}}$ , respectively, were fabricated without the assistance of PS template (Figures S6 and S7, Supporting Information). The external surface area of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{C}$ $(85~\\mathrm{nm})$ and $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{C}$ $(1.4\\upmu\\mathrm{m})$ are found to be greatly reduced to 190 and $88.7\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , corresponding to $24.6\\%$ and $16.4\\%$ of their total BET surface areas, respectively (Figure 1f and Table S1 (Supporting Information)). The pore size distribution analyses (Figure  1g) indicate the absence of meso-/macropores in $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{C}$ $(1.4\\upmu\\mathrm{m})$ and macropores in $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{C}$ ( $\\mathrm{85~nm})$ , confirming the vital role of PS template to attain the trimodal-porous structures. \n\nOther structural and compositional properties of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ were obtained. The high-resolution TEM image, X-ray diffraction (XRD) pattern, and Raman spectrum of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ (Figures S5, S8, and S9, Supporting Information) confirm a highly graphitized carbon support.[4a,9c] The XRD pattern indicates the absence of the crystalline forms of Fe and Ni nano­particles. The N 1s spectrum of X-ray photoelectron spectroscopy (XPS) (Figure S10, Supporting Information) confirms the presence of N-doped graphitic carbons and metal $\\cdot\\mathrm{N}_{x}$ coordination bonding.[20] Additionally, the N K-edge X-ray absorption near-edge structure (XANES) spectrum (Figure S11, Supporting Information) reveals the existence of pyridine-like N $({\\approx}398.5\\ \\mathrm{eV})$ , graphitic N $\\scriptstyle(\\approx401.5\\mathrm{~eV})$ , and metal $\\mathrm{\\DeltaN}_{x}$ bonding $(\\approx399.8\\ \\mathrm{eV})$ , which are consistent with the XPS results.[20] The HAADF-STEM image (Figure  2a), the corresponding energy dispersive X-ray spectroscopy (Figure S12, Supporting Information), and elemental mapping (Figure S13, Supporting Information) demonstrate the presence of the atomically dispersed Fe and Ni species.[21] The Fe and Ni contents determined by the inductively coupled plasma-mass spectrometry (ICP-MS) are 1.35 and $0.47~\\mathrm{wt\\%}$ , respectively, corresponding to a Fe:Ni mole ratio of 3.0 (Table S2, Supporting Information). \n\nThe synchrotron-based XANES and the extended X-ray absorption fine structure (EXAFS) spectra were obtained to further confirm $\\mathrm{Fe-N}_{x}$ and $\\mathrm{Ni}{-}\\mathrm{N}_{x}$ coordination bonding configurations and their SA status. The Fe K-edge XANES spectra of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ and the corresponding reference samples (Figure  2b) reveal that the absorption edge position of Fe in $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ closes to that of iron phthalocyanine (FePc), indicating a $+2$ valence state.[7a,22] The similar pre-edge profiles between Fe in $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ and FePc imply the formation of $\\mathrm{Fe-N}_{x}$ coordination.[22] Applying similar analysis to the Ni \n\n![](images/f3ac3d11af2a09b5db8c3ea943a8f2e0d0264999f4cc4ed8c7fe7a41b4acd732.jpg) \nFigure 1.  a) Schematic diagram illustrating the synthetic procedure of $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C};$ b,c) SEM and d,e) TEM images of $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C};\\mathsf{f}$ ) $\\mathsf{N}_{2}$ adsorption–desorption isotherms and g) pore-size distributions of F $\\mathsf{e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ , $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{C}$ ( $(85\\ \\mathsf{n m})$ ), and $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{C}$ $(7.4\\upmu\\mathrm{m})$ . \n\nK-edge XANES spectra (Figure  2c) of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ and the reference samples of Ni, NiO, and nickel phthalocyanine (NiPc) disclose the presence of $+2$ valence state Ni and $\\mathrm{Ni}{-}\\mathrm{N}_{x}$ coordination.[23] The Fe and Ni K-edge EXAFS spectra of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ (Figure 2d,e) display a Fe peak centered at $1.48\\mathrm{~\\AA~}$ , which closes to that of FePc $(1.{\\overset{\\cdot}{5}}0\\ {\\overset{\\cdot}{\\operatorname{A}}})$ and a Ni peak centered at $1.30\\mathrm{~\\AA~}$ which is almost identical to that of NiPc, further confirming the presence of $\\mathrm{Fe-N}_{x^{\\ast}}$ and $\\mathrm{Ni}{-}\\mathrm{N}_{x}.$ -coordinated SA sites in $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ . Importantly, the absented peaks at 2.2 and $2.1\\mathrm{~\\AA~}$ , respectively, from Fe and Ni K-edge EXAFS spectra of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ confirm the absence of FeFe and NiNi metallic bonds, implying the atomically dispersed Fe and Ni SAs in $\\mathrm{\\vec{\\mathrm{fe}}}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ Furthermore, the least-square EXAFS fitting was performed to depict structural parameters of Fe and \n\nNi in the $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ (Figure S14 and Table S3, Supporting Information). Based on the above characterizations, as proposed in Figure $2\\mathrm{f},$ it is reasonable to conclude that Fe and Ni atoms in $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ are dispersed separately in the forms of $\\mathrm{Fe-N}_{4}{\\cdot}$ and $\\mathrm{Ni-N_{4}}$ -coordinated SA sites. \n\nIn order to identify the ORR activity origin, the synthetic procedure shown in Figure 1a was also used to synthesize the N-doped carbons without both Fe and Ni (OC), and with only Fe-SAs $(\\mathrm{Fe-N}_{x}/\\mathrm{OC})$ or Ni-SAs $(\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC})$ (Figures S15–S17, Supporting Information) that possesses similar size, geometry, and trimodal-porous structures as that of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ . The ICP-MS-determined Fe-SA content in $\\mathrm{Fe}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ and Ni-SA content in $\\mathrm{Ni-N}_{x}/\\mathrm{OC}$ are 1.41 and $0.57\\mathrm{\\wt\\%}$ , respectively.[4a] For comparative purpose, the 400 and $220~\\mathrm{nm}$ PSs were used to synthesize $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OCs}$ with the average macropore sizes of 117 (denoted as $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}{-}117)$ ) and $281~\\mathrm{nm}$ (denoted as $\\mathrm{Fe/Ni–N}_{x}/\\mathrm{OC}{-}281\\}$ ) (Figures S18 and S19, Supporting Information). The BET surface areas of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}{\\cdot}117$ and $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}{-}281$ are determined to be 796.4 and $\\mathsf{993.5\\ m^{2}\\ g^{-1}}$ , respectively (Table S1, Supporting Information). \n\n![](images/fd28b82aaab304e7a7ee64f132f95f8e3c7c99405a3b61f1a6dfc7b92b358a10.jpg) \nFigure 2.  a) HAADF-STEM image of $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C};\\mathsf{k}$ ) Fe K-edge XANES spectra and c) Ni K-edge XANES spectra with a zoomed-in view in the inset; d,e) Fourier transforms of EXAFS spectra of $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ , Fe metal foil, $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ , and FePc at Fe K-edge (d), and $\\mathsf{F e/N i}\\mathrm{-N}_{x}/\\mathsf{O C}$ , Ni foil, NiO, and NiPc at Ni K-edge (e); f) proposed structural model of $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ . \n\nThe ORR performances of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ , OC, $\\mathrm{Ni-N}_{x}/\\mathrm{OC}$ , $\\mathrm{Fe-N}_{x}/\\mathrm{OC}$ , and $\\mathrm{Pt/C}$ $(20\\mathrm{\\wt\\%})$ in both $\\mathrm{O}_{2}$ -saturated alkaline $(0.1\\textrm{M K O H}$ ) and acid $(0.1\\mathrm{~M~HClO}_{4})$ media were first evaluated. A rotating ring-disk electrode (RRDE) with the immobilized target electrocatalysts on its glassy-carbon disk was used as the working electrode. Figure 3a shows the voltammograms of different electrocatalysts in the $\\mathrm{O}_{2}$ -saturated $0.1~\\mathrm{~\\bf~M~}$ KOH. Among them, $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ exhibits the best ORR activity with a half-wave potential $(E_{1/2})$ of $0.938\\mathrm{V},$ which is 267, 90, 84, and $66~\\mathrm{mV}$ higher than that of OC $(E_{1/2}=0.671\\:\\mathrm{V}$ ), $\\mathrm{Ni-N}_{x}/\\mathrm{OC}$ $(E_{1/2}=0.848\\:\\mathrm{V})$ , $\\mathrm{Fe-N}_{x}/\\mathrm{OC}$ $(E_{1/2}=0.854\\:\\mathrm{V})$ , and the benchmark $\\mathrm{Pt/C}$ $(E_{1/2}=0.872\\mathrm{~V)}$ ), respectively. In addition, the observed ORR limiting current densities of ${\\approx}6.4,{\\approx}6.1$ , and $\\approx5.9\\mathrm{\\mA\\cm^{-2}}$ , respectively, from $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ , $\\mathrm{Ni-N}_{x}/\\mathrm{OC}$ , and $\\mathrm{Fe-N}_{x}/\\mathrm{OC}$ are larger than that from $\\mathrm{Pt/C}$ $({\\approx}5.1\\mathrm{\\mA\\cm^{-2}})$ , reflecting the superior mass transfer properties of the trimodal-porous carbon structures. The excellent ORR activity of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ can be further evidenced by its smallest Tafel plot slope $(59.9\\mathrm{mV}\\mathrm{dec}^{-1})$ 1 among all the investigated samples (Figure  3b). The ORR kinetic current density $\\left(J_{\\mathrm{k}}\\right)$ of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ at $0.90{\\mathrm{~V~}}$ is found to be $28.1\\mathrm{mA}\\mathrm{cm}^{-2}$ , 15.1 and 109 times of that for $\\mathrm{Fe-N}_{x}/\\mathrm{OC}$ $(1.87~\\mathrm{mA}~\\mathrm{cm}^{-2})$ and $\\mathrm{Ni-N}_{x}/\\mathrm{OC}$ $(0.258~\\mathrm{mA~cm^{-2}},$ ), respectively, and also much higher than that of $\\mathrm{Pt/C}$ $(2.39\\mathrm{\\mA\\cm^{-2}})$ . An average transferred electron number $(n)$ of 3.96 can be determined from the Koutechy–Levich (K–L) plot derived from the corresponding voltammograms of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ (Figure  3c), signifying a four-electron ORR pathway, which is consistent with the RRDE measurement results (Figure S20a, Supporting Information). The acidic ORR performances in $0.1\\textbf{M}$ $\\mathrm{{HClO}_{4}}$ were investigated (Figure  3d). Impressively, $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ also exhibits an outstanding acidic ORR activity with a $E_{1/2}$ of $0.840~\\mathrm{V},$ which is 335 and $64\\mathrm{mV}$ higher than that of $\\mathrm{Ni-N}_{x}/\\mathrm{OC}$ $(E_{1/2}=0.505\\:\\mathrm{V})$ and $\\mathrm{Fe}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ $(E_{1/2}=0.776~\\mathrm{V})$ , and only $21\\mathrm{mV}$ lower than that of the benchmark $\\mathrm{Pt/C}$ $(E_{1/2}=0.861\\mathrm{~V~}$ ). The superior acidic ORR activity of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ can be further evidenced by its smallest Tafel plot slope $(60.1\\mathrm{mV}\\mathrm{dec^{-1}})$ among all the samples investigated, including the benchmark $\\mathrm{Pt/C}$ (Figure  3e). A four-electron acidic ORR process is confirmed by the K–L plot (Figure  3f) and RRDE measurement results (Figure S20b, Supporting Information). The above experimental results demonstrate that in both alkaline and acidic media, the coexisting Fe and Ni SAs in $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ possess superior \n\n![](images/fe02a369f76bdb5dc82e1559ad88285a24effb0fe5212ba928f090bd049344c2.jpg) \nFigure 3.  a) ORR polarization curves of $\\mathsf{F e/N i-N}_{x}/\\mathsf{O C}$ , Fe $\\ensuremath{\\mathsf{N}}_{x}/\\ensuremath{\\mathsf{O C}}$ , $\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ , OC, and $\\mathsf{P t/C}$ in $\\mathsf{O}_{2}$ -saturated $0.7~\\mathsf{m}$ KOH under a rotating rate of 1600 rpm, and b) the corresponding Tafel plots; c) ORR polarization curves of $\\mathsf{F e/N i}\\mathrm{-N}_{x}/\\mathsf{O C}$ in $0.1~\\mathsf{m}$ KOH at different rotating rates with the corresponding K–L plots in the inset; d) ORR polarization curves of $\\mathsf{F e/N i-N}_{x}/\\mathsf{O C}$ , $\\mathsf{F e}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ , ${\\sf N i-N}_{x}/{\\sf O C}$ , and $\\mathsf{P t}/\\mathsf{C}$ in $\\mathsf{O}_{2}$ -saturated $0.7~\\mathsf{m}$ ${\\mathsf{H C l O}}_{4}$ under a rotating rate of 1600  rpm, and e) the corresponding Tafel plots; f) ORR polarization curves of $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ in 0.1 m ${\\mathsf{H C l O}}_{4}$ at different rotating rates with the corresponding K–L plots in the inset; g) ORR polarization curves of $\\mathsf{F e/N i-N}_{x}/\\mathsf{O C}$ , $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{C}$ $(7.4\\upmu\\mathrm{m})$ , Fe/NiNx/OC-117, and $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}{-}28\\mathsf{I}$ in $\\mathsf{O}_{2}$ -saturated $0.1~\\mathsf{m}$ KOH under a rotating rate of 1600 rpm; h,i) ORR polarization curves of $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ before and after 5000 cycles in $\\mathsf{O}_{2}$ -saturated $0.1~\\mathsf{m}$ KOH (h) and 0.1 m ${\\mathsf{H C l O}}_{4}$ (i) under a rotating rate of 1600 rpm. \n\nORR activities than that of $\\mathrm{Fe-N}_{x}/\\mathrm{OC}$ and $\\mathrm{Ni-N}_{x}/\\mathrm{OC}$ with only Fe- or Ni-SAs, which could be due to the h-SA-induced synergetic effect. Density functional theory calculations were carried out to gain further insights into the relationship between h-SA coordination configuration and ORR performance (please see the Supporting Information for details). The acquired results (Figure S21, Supporting Information) unveil the transfer of charges from Ni atom to Fe atom through the conjugated $\\pi$ bond of graphene, indicating that such long-range interaction between adjacent $\\mathrm{Ni-N_{4}}$ and $\\mathrm{Fe-N_{4}}$ could collectively modulate the electronic structure of Fe in $\\mathrm{Fe-N_{4}}$ to further increase ORR activity.[6d,12a,24] The achieved ORR performances by $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ in both alkaline and acidic media exceeded the recently reported high performance Fe- and Ni-based electrocatalysts (Table S4, Supporting Information). \n\n![](images/d663716dc926ff0aa8f750aaf08f68dc7c0e9e1138ef23ad9919adbd0c7b61d7.jpg) \nFigure 4.  a) An illustrative diagram of a Zn–air battery and PEMFC with an $\\mathsf{F e}/\\mathsf{N i}{-}\\mathsf{N}_{x}/\\mathsf{O C}$ cathode; b) discharge polarization curves and the corresponding power density plots of the Zn–air batteries with $\\mathsf{F e/N i}\\mathrm{-N}_{x}/\\mathsf{O C}$ and $\\mathsf{P t/C}$ as cathodes; c) discharge polarization curves and the corresponding power density plots of PEMFC with $\\mathsf{F e/N i}\\mathrm{-N}_{x}/\\mathsf{O C}$ as cathode using ${\\sf H}_{2}/{\\sf O}_{2}$ and $\\mathsf{H}_{2}/$ air as fuels. \n\nThe effect of hierarchical porous structure on the ORR performance was also investigated using $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OCs}$ with different sizes of macropores in $\\mathrm{O}_{2}$ -saturated $0.1~\\mathrm{~\\bf~M~}$ KOH (Figure  3g). The $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{Cs}$ $(1.4~\\mathrm{\\\\mum})$ without ordered macropores and mesopores exhibit poor ORR activity with a $E_{1/2}$ potential of $0.855\\mathrm{~V~}$ and a limiting current density of ${\\approx}4.2\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ due to the poor mass transport conditions. The $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}{-}281$ possesses large-sized macropores, hence the superior long-range mass transport capability, however, it also exhibits poor ORR activity $(E_{1/2}=0.842\\mathrm{~V})$ than that of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ with $180~\\mathrm{nm}$ macropores, which is due to the significantly reduced mesoporous structures (mesopore volume $=0.221\\ \\mathrm{cm}^{3}\\ \\mathrm{g}^{-1})$ . The $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}{-}117$ possesses abundant mesopores, but compared to $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OCs}$ with $180~\\mathrm{{nm}}$ macropores, its relatively small average macropore size of $117\\ \\mathrm{nm}$ leads to a decreased long-range mass transport capability, hence the decreased ORR activity.[19] These results confirm that an optimized 3D hierarchical porous structure of the carbon support is critically important to realize the full catalytic potentials of SAECs. In addition, the effect of Fe and Ni h-SA contents on ORR performance was investigated (Table S2 and Figure S22, Supporting Information). Obviously, $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ possesses a minimal ORR overpotential, indicating that an optimum ORR activity could only be achieved when both Fe/Ni ratio and h-SA contents are optimized. \n\nBoth alkaline and acidic stabilities of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ were evaluated by the voltammetric (Figure 3h,i) and chronoamperometric tests (Figure S23, Supporting Information). The characteristics of the recorded voltammograms over 5000 cycles from both alkaline and acidic media are almost unchanged, signifying the superior cycling stability of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ . For the chronoamperometric tests over a period of $30\\ 000\\ \\mathrm{~s~}$ , an ${\\approx}95\\%$ and $92\\%$ original current densities are retained, respectively, from alkaline and acidic media, demonstrating the superior long-term stability of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ . Impressively, the highly ordered porous structure of $\\mathrm{Fe}/\\mathrm{Ni}{-}\\mathrm{N}_{x}/\\mathrm{OC}$ can be well maintained after the above long-term stability test (Figure S24, Supporting Information). Furthermore, negligible ORR current decay can be observed after the addition of methanol into $0.1\\textbf{M}$ KOH electrolyte, confirming a high methanol tolerance ability of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ (Figure S25, Supporting Information). \n\nThe performance of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ as the cathode material in rechargeable $Z\\mathrm{n}$ –air battery and proton-exchange membrane fuel cell (PEMFC) under $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ and $\\mathrm{H}_{2}.$ –air conditions were evaluated (Figure  4). As illustrated in Figure S26 (Supporting Information), the $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ also exhibits superior activity and stability toward oxygen evolution reaction comparable to $\\mathrm{IrO}_{2}$ . As a result, the Zn–air battery with $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ -­based air cathode can achieve a high open-circuit voltage of $1.525\\mathrm{~V~}$ (Figure S27a, Supporting Information) and a peak power density of $148\\mathrm{~mW~cm^{-2}}$ at $210\\mathrm{\\mA\\cm^{-2}}$ , which is 1.63 times of that achieved by $\\mathrm{Pt/C}$ -based cathode $(91.0\\mathrm{mW}\\mathrm{cm}^{-2}$ at $150\\mathrm{\\mA\\cm^{-2}}$ , Figure 4b) and exceeds most of reported ORR electrocatalysts (Table S5, Supporting Information). The discharge curves shown in Figure $\\mathrm{{s}27\\mathrm{{b}}}$ (Supporting Information) reveal that under a high current density of $50\\mathrm{\\mA}\\ \\mathrm{cm}^{-2}$ , the $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ -based Zn–air battery can generate a specific capacity of $712\\ \\mathrm{mAh\\g^{-1}}$ , larger than that of the $\\mathrm{Pt/C}$ -based one $(608\\mathrm{~mAh~g^{-1})}$ . As shown in Figure S27c (Supporting Information), an insignificant voltage loss from ${\\approx}0.98$ to $_{\\approx1.07}\\cdot$ V after 300 successive charge/discharge cycles under a current density of $20\\mathrm{\\mA\\cm^{-2}}$ demonstrates a superior cycle performance of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ -based cathode. For the PEMFC using $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ as fuels, the open-circuit voltages of 0.96 and $0.95\\mathrm{V}_{:}$ and the maximum power densities of 0.58 and $0.36\\mathrm{~W~cm}^{-2}$ are obtained under 1.0 and 0.3 bars, respectively, indicating a high ORR activity of $\\mathrm{Fe/Ni-N}_{x}/\\mathrm{OC}$ -based cathode (Figure  4c), outperforming the reported $\\mathrm{Fe{-}N{-}C}$ and $\\mathrm{Mn-N-C}$ catalysts.[9b,25] For the PEMFC using $\\mathrm{H}_{2}$ –air as fuels, a maximum power density of $0.21\\mathrm{W}\\mathrm{cm}^{-2}$ is readily achievable (Figure 4c). \n\nIn summary, we have innovatively utilized a template method combined with wet-chemistry metal-ion impregnation and pyrolysis to controllably coanchored Fe- and Ni-SAs to an uniquely configured trimodal-porous carbon support with highly ordered macropores interconnected by mesopores via the $\\mathrm{Fe-N_{4}}$ and $\\mathrm{Ni-N_{4}}$ coordination bonds, and demonstrated the use of hetero-SA electrocatalyst to dramatically enhance ORR electrocatalytic activity and the device performance for $Z\\mathrm{n}.$ –air battery and PEMFC. Our experimental results revealed that collectively optimizing the catalyst’s intrinsic activity and mass transport capability is an effective strategy for catalyst design. The findings of this work open an avenue to rationally design electrocatalysts for other reactions such as $\\mathrm{CO}_{2}$ and $\\mathrm{N}_{2}$ reduction reactions involving dissolved gas reactants. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nZ.Z. and H.Y. contributed equally to this work. This work was financially supported by the Australian Research Council (ARC) Discovery Project (Grant No. DP170104834) and the Griffith University Postdoctoral Fellowships (2016 and 2017). \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\nelectrocatalysis, fuel cell, hierarchically porous structure, oxygen reduction reaction, single atom catalyst \n\nReceived: July 8, 2020 Revised: August 21, 2020 Published online: \n\n[1]\t a) M. K.  Debe, Nature 2012, 486, 43; b) E. I.  Solomon, S. S.  Stahl, Chem. Rev. 2018, 118, 2299; c) X. X.  Wang, M. T.  Swihart, G.  Wu, Nat. Catal. 2019, 2, 578; d) T. P.  Zhou, N.  Zhang, C. Z.  Wu, Y.  Xie, Energy Environ. Sci. 2020, 13, 1132. \n[2]\t a) A. A. Gewirth, J. A. Varnell, A. M. DiAscro, Chem. Rev. 2018, 118, 2313; b) U.  Martinez, S.  Komini Babu, E. F.  Holby, H. T.  Chung, X. Yin, P. Zelenay, Adv. Mater. 2019, 31, 1806545; c) R. Paul, L. Zhu, H. Chen, J. Qu, L. M. Dai, Adv. Mater. 2019, 31, 1806403. \n[3]\t a) A.  Zitolo, V.  Goellner, V.  Armel, M. T.  Sougrati, T.  Mineva, L.  Stievano, E.  Fonda, F.  Jaouen, Nat. Mater. 2015, 14, 937; b) Y. J.  Chen, S. F.  Ji, Y. G.  Wang, J. C.  Dong, W. X.  Chen, Z.  Li, R. A. Shen, L. R. Zheng, Z. B. Zhuang, D. S. Wang, Y. D. Li, Angew. Chem., Int. Ed. 2017, 56, 6937; c) X. Wan, X. F. Liu, Y. C. Li, R. H. Yu, L. R.  Zheng, W. S.  Yan, H.  Wang, M.  Xu, J. L.  Shui, Nat. Catal. 2019, 2, 259; d) H. G. Zhang, H. T. Chung, D. A. Cullen, S. Wagner, U. I.  Kramm, K. L.  More, P.  Zelenay, G.  Wu, Energy Environ. Sci. 2019, 12, 2548; e) H. G. Zhang, S. Hwang, M. Y. Wang, Z. X. Feng, S.  Karakalos, L. L.  Luo, Z.  Qiao, X. H.  Xie, C. M.  Wang, D.  Su, Y. Y. Shao, G. Wu, J. Am. Chem. Soc. 2017, 139, 14143. \n[4]\t a) J. Z.  Li, M. J.  Chen, D. A.  Cullen, S.  Hwang, M. Y.  Wang, B. Y.  Li, K. X.  Liu, S.  Karakalos, M.  Lucero, H. G.  Zhang, C.  Lei, H.  Xu, G. E.  Sterbinsky, Z. X.  Feng, D.  Su, K. L.  More, G. F.  Wang, Z. B.  Wang, G.  Wu, Nat. Catal. 2018, 1, 935; b) Y. T.  Qu, Z. J.  Li, W. X.  Chen, Y.  Lin, T. W.  Yuan, Z. K.  Yang, C. M.  Zhao, J.  Wang, C.  Zhao, X.  Wang, F. Y.  Zhou, Z. B.  Zhuang, Y.  Wu, Y. D.  Li, Nat. Catal. 2018, 1, 781; c) S.  Liu, Z. D.  Li, C. L.  Wang, W. W.  Tao, M. X.  Huang, M.  Zuo, Y.  Yang, K.  Yang, L. J.  Zhang, S.  Chen, P. P.  Xu, Q. W.  Chen, Nat. Commun. 2020, 11, 938; d) Q.  Xu, C. X.  Guo, S. B.  Tian, J.  Zhang, W. X.  Chen, W.-C.  Cheong, L.  Gu, L. R.  Zheng, J. P.  Xiao, Q.  Liu, B. J.  Li, D. S.  Wang, Y. D.  Li, Sci. China Mater. 2020, 63, 972. \n[5]\t a) C. Z.  Wan, X. F.  Duan, Y.  Huang, Adv. Energy Mater. 2020, 10, 1903815; b) D.  Zhao, Z. W.  Zhuang, X.  Cao, C.  Zhang, Q.  Peng, C.  Chen, Y. D.  Li, Chem. Soc. Rev. 2020, 49, 2215; c) Y. H.  He, S. W. Liu, C. Priest, Q. R. Shi, G. Wu, Chem. Soc. Rev. 2020, 49, 3484; d) X. Y.  Li, H. P.  Rong, J. T.  Zhang, D. S.  Wang, Y. D.  Li, Nano Res. 2020, 13, 1842; e) Y. J. Chen, S. F. Ji, C. Chen, Q. Peng, D. S. Wang, Y. D. Li, Joule 2018, 2, 1242. \n[6]\t a) A.  Kulkarni, S.  Siahrostami, A.  Patel, J. K.  Nørskov, Chem. Rev. 2018, 118, 2302; b) J. K. Li, F. Jaouen, Curr. Opin. Electrochem. 2018, 9, 198; c) W.  Wang, Q. Y.  Jia, S.  Mukerjee, S. L.  Chen, ACS Catal. 2019, 9, 10126; d) Y. Z.  Zhu, J.  Sokolowski, X. C.  Song, Y. H.  He, Y. Mei, G. Wu, Adv. Energy Mater. 2020, 10, 1902844. \n[7]\t a) R.  Jiang, L.  Li, T.  Sheng, G. F.  Hu, Y. G.  Chen, L. Y.  Wang, J. Am. Chem. Soc. 2018, 140, 11594; b) I. Matanovic, K. Artyushkova, P.  Atanassov, Curr. Opin. Electrochem. 2018, 9, 137; c) N.  Zhang, T. P. Zhou, M. L. Chen, H. Feng, R. L. Yuan, C. A. Zhong, W. S. Yan, Y. C. Tian, X. J. Wu, W. S. Chu, C. Z. Wu, Y. Xie, Energy Environ. Sci. 2020, 13, 111. \n[8]\t a) Y. J. Chen, S. F. Ji, S. Zhao, W. X. Chen, J. C. Dong, W. C. Cheong, R. G. Shen, X. D. Wen, L. R. Zheng, A. I. Rykov, S. C. Cai, H. L. Tang, Z. B. Zhuang, C. Chen, Q. Peng, D. S. Wang, Y. D. Li, Nat. Commun. 2018, 9, 5422; b) Y. H.  Han, Y. G.  Wang, R. R.  Xu, W. X.  Chen, L. R.  Zheng, A. J.  Han, Y. Q.  Zhu, J.  Zhang, H. B.  Zhang, J.  Luo, C. Chen, Q. Peng, D. S. Wang, Y. D. Li, Energy Environ. Sci. 2018, 11, 2348; c) J. Q. Zhang, Y. F. Zhao, C. Chen, Y. C. Huang, C. L. Dong, C. J.  Chen, R. S.  Liu, C. Y.  Wang, K.  Yan, Y. D.  Li, G. X.  Wang, J. Am. Chem. Soc. 2019, 141, 20118; d) S. B. Zhang, M. Jin, T. F. Shi, M. M.  Han, Q.  Sun, Y.  Lin, Z. H.  Ding, L. R.  Zheng, G. Z.  Wang, Y. X. Zhang, H. M. Zhang, H. J. Zhao, Angew. Chem., Int. Ed. 2020, 59, 13423; Angew. Chem. 2020, 132, 13525. \n[9]\t a) V. Armel, S. Hindocha, F. Salles, S. Bennett, D. Jones, F. Jaouen, J. Am. Chem. Soc. 2017, 139, 453; b) M. J.  Workman, A.  Serov, L.-k.  Tsui, P.  Atanassov, K.  Artyushkova, ACS Energy Lett. 2017, 2, 1489; c) Y.  Mun, S.  Lee, K.  Kim, S.  Kim, S.  Lee, J. W.  Han, J.  Lee, J. Am. Chem. Soc. 2019, 141, 6254. \n[10]\t a) J.  Wang, Z. Q.  Huang, W.  Liu, C. R.  Chang, H. L.  Tang, Z. J.  Li, W. X. Chen, C. J. Jia, T. Yao, S. Q. Wei, Y. Wu, Y. D. Li, J. Am. Chem. Soc. 2017, 139, 17281; b) Z. Y. Lu, B. Wang, Y. F. Hu, W. Liu, Y. F. Zhao, R. O.  Yang, Z. P.  Li, J.  Luo, B.  Chi, Z.  Jiang, M. S.  Li, S. C.  Mu, S. J.  Liao, J. J.  Zhang, X. L.  Sun, Angew. Chem., Int. Ed. 2019, 58, 2622; c) M. L.  Xiao, Y. T.  Chen, J. B.  Zhu, H.  Zhang, X.  Zhao, L. Q. Gao, X. Wang, J. Zhao, J. J. Ge, Z. Jiang, S. L. Chen, C. P. Liu, W. Xing, J. Am. Chem. Soc. 2019, 141, 17763; d) G. X. Zhang, Y. Jia, C.  Zhang, X. Y.  Xiong, K.  Sun, R. D.  Chen, W. X.  Chen, Y.  Kuang, L. R.  Zheng, H. L.  Tang, W.  Liu, J. F.  Liu, X. M.  Sun, W. F.  Lin, H. J. Dai, Energy Environ. Sci. 2019, 12, 1317. \n[11]\t a) E. F. Holby, C. D. Taylor, Sci. Rep. 2015, 5, 9286; b) M. A. Hunter, J. M. T. A. Fischer, Q. H. Yuan, M. Hankel, D. J. Searles, ACS Catal. 2019, 9, 7660. \n[12]\t a) Q. K.  Li, X. F.  Li, G. Z.  Zhang, J.  Jiang, J. Am. Chem. Soc. 2018, 140, 15149; b) Y. L. Han, Q. K. Li, K. Ye, Y. Luo, J. Jiang, G. Z. Zhang, ACS Appl. Mater. Interfaces 2020, 12, 15271. \n[13]\t S. H.  Lee, J.  Kim, D. Y.  Chung, J. M.  Yoo, H. S.  Lee, M. J.  Kim, B. S. Mun, S. G. Kwon, Y. E. Sung, T. Hyeon, J. Am. Chem. Soc. 2019, 141, 2035. \n[14]\t a) K. Karan, Curr. Opin. Electrochem. 2017, 5, 27; b) L. Xing, Chem. Eng. Sci. 2018, 179, 198. \n[15]\t a) F. Jaouen, M. Lefèvre, J. P. Dodelet, M. Cai, J. Phys. Chem. B 2006, 110, 5553; b) Y. B.  Li, H. M.  Zhang, Y.  Wang, P. R.  Liu, H. G.  Yang, X. D. Yao, D. Wang, Z. Y. Tang, H. J. Zhao, Energy Environ. Sci. 2014, 7, 3720; c) Y. C.  Wang, L.  Huang, P.  Zhang, Y. T.  Qiu, T.  Sheng, Z. Y.  Zhou, G.  Wang, J. G.  Liu, M.  Rauf, Z. Q.  Gu, W. T.  Wu, S. G. Sun, ACS Energy Lett. 2017, 2, 645. \n[16]\t a) O. H.  Kim, Y. H.  Cho, S. H.  Kang, H. Y.  Park, M.  Kim, J. W.  Lim, D. Y. Chung, M. J. Lee, H. Choe, Y. E. Sung, Nat. Commun. 2013, 4, 2473; b) B. Z. Fang, J. H. Kim, M. Kim, J. S. Yu, Chem. Mater. 2009, 21, 789. \n[17]\t a) J.  Liang, Y.  Zheng, J.  Chen, J.  Liu, D.  Hulicova-Jurcakova, M.  Jaroniec, S. Z.  Qiao, Angew. Chem., Int. Ed. 2012, 51, 3892; b) J. Liang, X. Du, C. Gibson, X. W. Du, S. Z. Qiao, Adv. Mater. 2013, 25, 6226; c) S. L.  Lee, D. H.  Kwak, S. B.  Han, Y. W.  Lee, J. Y.  Lee, I. A.  Choi, H. S.  Park, J. Y.  Park, K. W.  Park, ACS Catal. 2016, 6, 5095; d) L. Xiao, Q. Q. Yang, M. J. Wang, Z. X. Mao, J. Li, Z. D. Wei, J. Mater. Sci. 2018, 53, 15246. \n[18]\t K.  Shen, L.  Zhang, X. D.  Chen, L. M.  Liu, D. L.  Zhang, Y.  Han, J. Y.  Chen, J. L.  Long, R.  Luque, Y. W.  Li, B. L.  Chen, Science 2018, 359, 206. \n[19]\t H. T.  Chung, D. A.  Cullen, D.  Higgins, B. T.  Sneed, E. F.  Holby, K. L. More, P. Zelenay, Science 2017, 357, 479. \n[20]\t B.  Bayatsarmadi, Y.  Zheng, Y. H.  Tang, M.  Jaroniec, S. Z.  Qiao, Small 2016, 12, 3703. \n[21]\t J. Gu, C. S. Hsu, L. C. Bai, H. M. Chen, X. L. Hu, Science 2019, 364, 1091. \n[22]\t H. L. Fei, J. C. Dong, Y. X. Feng, C. S. Allen, C. Z. Wan, B. Volosskiy, M. F.  Li, Z. P.  Zhao, Y. L.  Wang, H. T.  Sun, P. F.  An, W. X.  Chen, Z. Y.  Guo, C. I.  Lee, D. L.  Chen, I.  Shakir, M. J.  Liu, T. D.  Hu, Y. D.  Li, A. I.  Kirkland, X. F.  Duan, Y.  Huang, Nat. Catal. 2018, 1, 63. \n[23]\t L. L.  Zhang, D. B.  Liu, Z.  Muhammad, F.  Wan, W.  Xie, Y. J.  Wang, L. Song, Z. Q. Niu, J. Chen, Adv. Mater. 2019, 31, 1903955. \n[24]\t D. Y.  Zhang, W. X.  Chen, Z.  Li, Y. J.  Chen, L. R.  Zheng, Y.  Gong, Q. H. Li, R. A. Shen, Y. H. Han, W. C. Cheong, L. Gu, Y. D. Li, Chem. Commun. 2018, 54, 4274. \n[25]\t J. Z.  Li, H. G.  Zhang, W.  Samarakoon, W. T.  Shan, D. A.  Cullen, S.  Karakalos, M. J.  Chen, D. M.  Gu, K. L.  More, G. F.  Wang, Z. X.  Feng, Z. B.  Wang, G.  Wu, Angew. Chem., Int. Ed. 2019, 58, 18971. " + }, + { + "id": "10.1126_science.aaz7681", + "DOI": "10.1126/science.aaz7681", + "DOI Link": "http://dx.doi.org/10.1126/science.aaz7681", + "Relative Dir Path": "mds/10.1126_science.aaz7681", + "Article Title": "A general method to synthesize and sinter bulk ceramics in seconds", + "Authors": "Wang, CW; Ping, WW; Bai, Q; Cui, HC; Hensleigh, R; Wang, RL; Brozena, AH; Xu, ZP; Dai, JQ; Pei, Y; Zheng, CL; Pastel, G; Gao, JL; Wang, XZ; Wang, H; Zhao, JC; Yang, B; Zheng, XY; Luo, J; Mo, YF; Dunn, B; Hu, LB", + "Source Title": "SCIENCE", + "Abstract": "Ceramics are an important class of materials with widespread applications because of their high thermal, mechanical. and chemical stability. Computational predictions based on first principles methods can be a valuable tool in accelerating materials discovery to develop improved ceramics. It is essential to experimentally confirm the material properties of such predictions. However, materials screening rates are limited by the long processing times and the poor compositional control from volatile element loss in conventional ceramic sintering techniques. To overcome these limitations, we developed an ultrafast high-temperature sintering (UHS) process for the fabrication of ceramic materials by radiative heating under an inert atmosphere. We provide several examples of the UHS process to demonstrate its potential utility and applications, including advancements in solid-state electrolytes, mufticomponent structures, and high-throughput materials screening.", + "Times Cited, WoS Core": 493, + "Times Cited, All Databases": 544, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000531178400047", + "Markdown": "# CERAMICS \n\n# A general method to synthesize and sinter bulk ceramics in seconds \n\nChengwei Wang1\\*, Weiwei Ping1\\*, Qiang Bai1\\*, Huachen $\\mathsf{c u i}^{2,3\\ast}$ , Ryan Hensleigh2,3\\*, Ruiliu Wang1, Alexandra H. Brozena1, Zhenpeng $\\mathsf{X u}^{2,3}$ , Jiaqi Dai1, Yong $\\mathsf{P e i}^{4}$ , Chaolun Zheng4, Glenn Pastel1, Jinlong $\\mathsf{G a o}^{1}$ , Xizheng Wang1, Howard Wang1, Ji-Cheng Zhao1, Bao Yang4, Xiaoyu (Rayne) Zheng2,3†, Jian Luo5†, Yifei $\\mathsf{M o}^{1}\\dag$ , Bruce Dunn6, Liangbing ${\\mathsf{H}}{\\mathsf{u}}^{1,7}\\dag$ \n\nCeramics are an important class of materials with widespread applications because of their high thermal, mechanical, and chemical stability. Computational predictions based on first principles methods can be a valuable tool in accelerating materials discovery to develop improved ceramics. It is essential to experimentally confirm the material properties of such predictions. However, materials screening rates are limited by the long processing times and the poor compositional control from volatile element loss in conventional ceramic sintering techniques. To overcome these limitations, we developed an ultrafast high-temperature sintering (UHS) process for the fabrication of ceramic materials by radiative heating under an inert atmosphere. We provide several examples of the UHS process to demonstrate its potential utility and applications, including advancements in solid-state electrolytes, multicomponent structures, and high-throughput materials screening. \n\nC eramics are widely used in electronics, energy storage, and extreme environments because of their high thermal, U mechanical, and chemical stability. The sintering of ceramics is a technology that can be traced back to more than 26,000 years ago $(I)$ . Conventional ceramic sintering often requires hours of processing time (2), which can become an obstacle for the high-throughput discovery of advanced ceramic materials. The long sintering time is particularly problematic in the development of ceramic-based solidstate electrolytes (SSEs)—which are critical for new batteries with improved energy efficiency and safety (3, 4)—because of the severe volatility of Li and Na during sintering (5–9). \n\nSubstantial effort has been devoted to the development of innovative sintering technologies, such as microwave-assisted sintering, spark plasma sintering (SPS), and flash sintering. Microwave-assisted sintering of ceramics often depends on the microwave absorption properties of the materials or uses susceptors $(I O,I I)$ . The SPS technique requires that dies are used to compress the ceramic while sintering (12), which makes it more difficult to sinter specimens with complex three-dimensional (3D) structures. Furthermore, SPS normally produces only one specimen at a time, though special tooling can and has been made to fabricate multiple samples. The more-recently developed flash sintering (13), photonic sintering $(I4)$ , and rapid thermal annealing (RTA) (15) methods display a high heating rate of ${\\sim}10^{3}$ to $10^{4\\mathrm{{o}}}\\mathrm{{C}/\\mathrm{{min}}}$ . However, flash sintering typically requires expensive Pt electrodes and is material specific. Although flash sintering can be applied to many ceramics, flash sintering conditions depend strongly on the electrical characteristics of the material $(I6)$ , which limits the general applicability of this method as well as its utility for high-throughput processing when a material’s properties are unknown. Photonic sintering temperatures are normally too low to sinter ceramics $(I4,I7)$ . RTA has been used successfully to sinter ZnO (15), but this method can only provide a sintering temperature of up to ${\\sim}1200^{\\circ}\\mathrm{C}$ with expensive commercial equipment. \n\nTo meet the needs of modern ceramics and foster material innovation, we report a ceramic synthesis method, called ultrafast hightemperature sintering (UHS), that features a uniform temperature distribution, high heating ${\\mathrm{^{*}}}\\mathrm{{\\sim}}10^{3}$ to $10^{40}\\mathrm{C/min}\\rangle$ and cooling rates (up to $10^{40}\\mathrm{C/min})$ , and high sintering temperatures (up to $3000^{\\circ}\\mathrm{C})_{\\prime}$ . The ultrahigh heating rates and temperatures enable ultrafast sintering times of \\~10 s (Fig. 1A), far outpacing those of most conventional furnaces. To conduct the process, we directly sandwich a pressed green pellet (Fig. 1B) of ceramic precursor powders between two Joule-heating carbon strips that rapidly heat the pellet through radiation and conduction to form a uniform high-temperature environment (fig. S1) for quick synthesis (solidstate reaction) and reactive sintering (Fig. 1C). \n\nIn an inert atmosphere, these carbon heating elements can provide a temperature of up to ${\\sim}3000^{\\circ}\\mathrm{C}$ (fig. S2), which is sufficient to synthesize and sinter virtually any ceramic material. The short sintering time also helps to prevent volatile evaporation and undesirable interdiffusion at the interfaces of multilayer structures. Additionally, the technique is scalable because the processing is decoupled from the intrinsic properties of materials (unlike flash sintering; table S3), thereby allowing general and rapid ceramic synthesis and sintering. The UHS process is also compatible with the 3D printing of ceramic precursors, producing novel post-sintering structures in addition to well-defined interfaces between multilayer ceramic compounds. Furthermore, the speed of UHS enables the rapid experimental validation of new material predictions from computation, which facilitates materials discovery spanning a wide range of compositions. Several applications may benefit from this methodology, including thin-film SSEs and battery applications. \n\nIn a typical UHS process, the heating elements ramp up from room temperature to the sintering temperature in ${\\sim}30~\\mathrm{s}$ or less (Fig. 2A, bottom), a process that would typically take a conventional furnace several hours to complete (fig. S3). This temperature ramping stage is followed by ${\\sim}10~\\mathrm{s}$ of isothermal sintering and then rapid cooling (in ${\\sim}5~\\mathrm{s}$ ). These times and conditions are attractive compared with those of other sintering methods (fig. S4 and table S3) (11, 12, 16). As a demonstration of the process, we synthesized Ta-doped $\\mathrm{Li_{6.5}L a_{3}Z r_{1.5}T a_{0.5}O_{12}}$ (LLZTO), a garnet-type Li-ion–conductive ceramic proposed for SSE applications (18). In the UHS technique, the precursors of LLZTO quickly react and densify (Fig. 2A, top) in ${\\sim}40~\\mathrm{s}$ (\\~30 s of temperature ramping and \\~10 s of isothermal sintering), as the temperature of the heater approaches ${\\sim}1500^{\\circ}\\mathrm{C}$ (movie S1). The high sintering temperature and short sintering time of the UHS technique produce a relatively small grain size of $8.5\\pm2.0\\upmu\\mathrm{m}$ (Fig. 2B) and a high relative density of $\\sim97\\%$ (fig. S5). By contrast, the conventional furnace–sintered garnet features a microstructure with larger grains of $13.5\\pm5\\upmu\\mathrm{m}$ (Fig. 2C). This rapid sintering and densification observed in the materials produced by the UHS method may originate from (i) fast kinetics from the high sample temperature, (ii) additional chemical driving force beyond the normal capillary driving force for densification caused by the simultaneous reaction and sintering process, or (iii) the ultrahigh heating rates enhancing the densification rates (15, 19). \n\nIn general, sintering involves competition between the coarsening and densification of particles. Surface diffusion can dominate at low temperatures and causes coarsening and neck growth without densification, whereas grain boundary and bulk diffusion are more important at high temperatures, leading to fast densification. The ultrahigh heating rates of UHS bypass the low-temperature region, thereby reducing the coarsening of particles and maintaining a higher capillary driving force for sintering, similar to that observed in other ultrafast heating schemes, such as flash sintering and other exotic heating methods (15, 19). The lower activation energies (fig. S5) also suggest that sintering and grain growth mechanisms in the UHS process are somewhat different from those in conventional sintering methods (20). In some cases, particularly for some solid electrolytes of complex chemistries, a small fraction of a liquid can form at the high processing temperature in UHS, which further promotes densification as ultrafast liquid-phase sintering (21). \n\nThe long sintering time of conventional syntheses can lead to Li loss in garnet SSEs \n\n![](images/5332e39af922a2dbc68f44ebd0fb89a5b526efd6db9f029ba0742981ad2cf57d.jpg) \nFig. 1. Rapid sintering process and setup for ceramic synthesis. (A) Schematic of the UHS synthesis process, in which the pressed green pellet of precursors is directly sintered into a dense ceramic component at a high sintering temperature of up to $3000^{\\circ}\\mathrm{C}$ in ${\\sim}10~\\mathsf{s}$ . (B and C) Photographs of the UHS sintering setup at room temperature \n\n![](images/9d01e1d4a42c5686267af12afd077574ad1c4704f0db38d73055229f473be1c0.jpg) \nwithout applying current (B), and at ${\\sim}1500^{\\circ}\\mathrm{C}$ (C), in which the closely packed heating strips surrounding the pressed green pellet provide a uniform temperature distribution that enables rapid ceramic sintering. \nFig. 2. Rapid sintering of ceramic materials. (A) Typical temperature profile of the UHS process. The whole process takes <1 min. The SEM images demonstrate the reaction process of the LLZTO ceramic over a $10\\mathrm{-}\\mathsf{s}$ isothermal hold of UHS sintering. RT, room temperature. (B and C) Fracture cross-sectional \n\nSEM images of UHS-sintered (B) and conventional furnace–sintered (C) LLZTO. (D) Li loss of different LLZTO samples sintered from precursors with 0, 10, and $20\\%$ excess Li by means of the the UHS technique and a conventional furnace. (E) Pictures of various ceramics sintered by the UHS technique in ${\\sim}10~\\mathsf{s}$ . \n\ncaused by the evaporation of Li and the formation of secondary phases that lead to lower ionic conductivity (22). In contrast, the UHS technique enables us to tune the sintering time in units of seconds, which provides excellent control in terms of the Li content and grain growth. As a comparison, we sintered a series of LLZTO precursor formulations featuring 0, 10, and $20\\%$ excess Li using either the UHS technique or a conventional furnace. Using inductively coupled plasma mass spectrometry, we observed severe Li loss in the furnacesintered LLZTO samples (up to $99\\%$ ) but ${<}4\\%$ loss in the UHS samples. This was true even for the sample made without excess Li (Fig. 2D). \n\n![](images/44afb4b3e125a5ad8756eafd92d196c772f7276adff70fb929778a1d59df74de.jpg) \nFig. 3. Rapid sintering technique for ceramic screening. (A) Accelerated materials discovery enabled by computational prediction and rapid synthesis. (B) The computational workflow for predicting new garnet compositions. The phase stabilities of candidate compounds with different cation combinations were evaluated by the energy above hull $(E_{\\mathrm{hull}})$ in comparison with the lowest-energy phase equilibria. (C) The table lists the predicted garnet compositions with different stabilities. (D) Pictures of the garnet materials (featuring different colors from the usual white) sintered by \nmeans of the UHS technique and predicted by computation. The LNdZTO garnet can change color under different light sources (e.g., a fluorescent light bulb and sunlight) because of the Alexandrite effect (34). (E) Schematic of a 20 by 5 matrix for cosintering 100 ceramic samples with the UHS technique in just ${\\sim}10~\\mathsf{s}$ . (F) Pictures of the UHS setup for cosintering 10 garnet samples. The top image is the side view of the UHS cosintering process. (G) The voltage and current profiles of the symmetric cell with a thick Li electrode cycled at different current densities. \n\nThe time-of-flight secondary ion mass spectroscopy results confirmed the uniform distributions of all elements in the UHS-sintered LLZTO (fig. S6). Both the densification and Li-evaporation rates increase with temperature as thermally activated processes, but the garnet densification rate likely increases faster than the evaporation rate. This leads to less Li loss with a much shorter sintering time sufficient for densification. The schematic timetemperature-transformation diagram (fig. S7) illustrates the evolution of density and composition of the LLZTO garnet in the UHS process. We identified a pure cubic garnet phase from x-ray diffraction (XRD) patterns of the UHS garnet, whereas the severe Li loss in the conventional furnace–sintered samples leads to a side reaction (fig. S8). Furthermore, the LLZTO samples synthesized with the UHS technique had an ionic conductivity of ${\\sim}1.0\\pm$ $0.1\\mathrm{mS}/\\mathrm{cm}$ (fig. S9), which is among the highest reported for garnet-based SSEs (8, 18, 23). \n\nWe can apply our UHS method to synthesize a wide range of high-performance ceramics. As a demonstration, we successfully sintered alumina $(\\mathrm{Al_{2}O_{3}},>96\\%$ density), $\\mathrm{Y_{2}O_{3}}$ -stabilized $\\mathrm{zrO_{2}}$ (YSZ, ${>}95\\%$ density, with an ultrafine grain size of $265\\pm85\\mathrm{{nm}}$ ), $\\mathrm{Li_{1.3}A l_{0.3}T i_{1.7}(P O_{4})_{3}}$ (LATP, ${>}90\\%$ density), and $\\mathrm{Li_{0.3}L a_{0.567}T i O_{3}}$ (LLTO, ${>}94\\%$ density) directly from pressed green pellets of precursor powders and all in under 1 min (Fig. 2E). $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ and YSZ are two typical structural ceramics with excellent mechanical properties and high sintering temperatures, whereas LATP and LLTO are Li-ion conductors used in solid-state batteries (3, 24). The UHS materials featured pure phases that we identified with XRD, which was indicative of no side reactions (fig. S10). We used scanning electron microscopy (SEM) images to show that the well-sintered grains have low porosity and the fractured cross sections are uniform in microstructure (figs. S11 to S14). The pressureless sintering process and short processing time of the UHS technique also resulted in fewer solid diffusion–related side reactions or sample-carbon heater contamination issues (figs. S15 to S17) than often encountered in SPS (25). We hypothesize that the ultrahigh heating rate and short sintering time can kinetically minimize the likelihood of such side reactions. The technique is particularly suitable for high-throughput screening of bulk ceramics compared with different ceramic synthesis techniques. \n\nThe ability of the UHS method to rapidly and reliably synthesize a wide range of ceramics enables us to quickly verify new materials predicted by computation and accelerate the screening rate for bulk ceramic materials (Fig. 3A). We used lithium garnet compounds $\\mathrm{(Li_{7}A_{3}B_{2}O_{12}}$ ; A $\\mathbf{\\Sigma}=\\mathbf{\\Sigma}$ La group, $\\mathbf{B}=\\mathbf{M}\\mathbf{o},\\mathbf{W}$ , Sn, or Zr) as a model system to demonstrate this rapid screening ability that is enabled by computational prediction and the UHS process. We used density functional theory calculations to predict and evaluate the energies of a large number of compounds with other non-Li cation combinations based on garnet structures (Fig. 3B). The phase stabilities of these computer-generated hypothetical $\\mathrm{Li}_{7}$ -garnet compounds (Fig. 3C) are described by the lower value of the energy above hull $(E_{\\mathrm{hull}})$ , which we determined from the energy difference of the compound in comparison with the stable phase equilibria on the phase diagram (26). A material with a small $E_{\\mathrm{hull}}$ (color-coded green) should feature good phase stability, and a high $E_{\\mathrm{hull}}$ (color-coded red) suggests an unstable phase. Our compositional screening captured most known stoichiometric $\\mathrm{Li}_{7}$ garnets, such as $\\mathrm{Li_{7}L a_{3}Z r_{2}O_{12}},$ $\\mathrm{Li_{7}N d_{3}Z r_{2}O_{12}},$ , and $\\mathrm{Li_{7}L a_{3}S n_{2}O_{12}}$ $(I8)$ , which validated the computational method. \n\nWe selected the computationally predicted $\\mathrm{Zr^{-}}$ and Sn-based garnet compositions featuring small $E_{\\mathrm{hull}}$ values (Fig. 3C) for experimental verification, including $\\mathrm{Li_{7}P r_{3}Z r_{2}O_{12}}$ $(\\mathrm{LPrZO})$ , $\\mathrm{Li_{7}S m_{3}Z r_{2}O_{12}}$ (LSmZO), $\\mathrm{Li_{7}N d_{3}Z r_{2}O_{12}}$ (LNdZO), $\\mathrm{Li_{7}N d_{3}S n_{2}O_{12}}$ (LNdSnO), and $\\mathrm{Li_{7}S m_{3}S n_{2}O_{12}}$ (LSmSnO). We also synthesized the corresponding 0.5 Ta-doped compositions in the B site [e.g., $\\mathrm{Li}_{6.5}\\mathrm{Sm}_{3}\\mathrm{Zr}_{1.5}\\mathrm{Ta}_{0.5}\\mathrm{O}_{12}$ (LSmZTO)]. New garnet compounds were well synthesized and sintered (figs. S18 to S22) in as little as $10\\mathrm{~s~}$ , with uniform grain size and microstructure. The final relative densities were in the range of 91 to $96\\%$ , with a typical grain size of 2 to $10~\\upmu\\mathrm{m}$ . We confirmed the garnet structure (cubic phase for B site doped; tetragonal phase for nondoped) using XRD (fig. S23). Our garnet compounds exhibited different optical properties and were not the typical white color, owing to the different Lagroup elements (Fig. 3D). Our garnets also had ionic conductivities of ${\\sim}10^{-4}\\ \\mathrm{S/cm}$ (e.g., LNdZTO, fig. S24), which are comparable to those of LLZO garnets (18, 22). We also attempted to synthesize some unstable garnet compounds that we predicted by computation, such as $\\mathrm{Li_{7}G d_{3}Z r_{2}O_{12}}$ . As expected, even though the SEM image shows well sintered grains (fig. S25A), the XRD pattern indicates that the composition did not form the garnet phase (fig. S25B), which verifies our computational predictions. \n\nThe fast sintering rate of UHS also enables cosintering of multiple materials simultaneously, which permits even faster screening of materials or devices. In practical ceramic synthesis, sintering can be the most timeconsuming process, especially when the optimized sintering parameters have not been developed for new compositions. However, with the UHS sintering technique, 100 ceramic pellets can be rapidly cosintered using a 20 by 5 matrix setup (Fig. 3E), with an area of just ${\\sim}12$ cm by $3\\ \\mathrm{cm}$ (for a pellet size of $5~\\mathrm{mm}$ ). This setup is practical for materials screening processes. As a demonstration of this scalability, we synthesized 10 garnet compositions (see compositions listed in the supplementary materials) by cosintering directly from the corresponding green bodies (Fig. 3F). In comparison, although SPS is currently considered a high-throughput method to fabricate bulk ceramic specimens, it typically produces just one specimen in ${\\boldsymbol{\\sim}}1$ to 2 hours. Moreover, SPS cannot easily be carried out in parallel as it requires multiple expensive SPS instruments. \n\nUltrafast heating at high temperatures for only seconds can also reduce or eliminate the segregation of detrimental impurities and defects at grain boundaries. This process may have beneficial effects for solid electrolytes and many other structural and functional ceramics. Using LLZTO garnet pellets as a proof of concept, we conducted a symmetric Li stripping-plating study to systematically characterize the electrochemical properties of the UHS garnet SSE. Because of the challenge in diagnosing the short circuit in the symmetric cell configuration (27), we applied in situ neutron depth profiling (NDP) (28) to confirm that the UHS LLZTO garnet SSE can conduct Li ions at high current densities without short-circuiting (fig. S26, A, B, and C). We show that the Li-LLZTO-Li symmetric cell with a thick ${\\mathrm{>}}100{\\mathrm{~}}\\upmu\\mathrm{m}{\\mathrm{}}{\\mathrm{,}}$ ) Li metal coating demonstrates a critical current density as high as $3.2\\mathrm{mA}/\\mathrm{cm}^{2}$ (Fig. 3G and fig. S26D), which is among the highest reported values for planar garnet-based SSEs (18, 29). We have conducted long-term cycling of the LiLLZTO-Li symmetric cell (fig. S27), which can cycle for $>400$ hours at a current density of $0.2\\ \\mathrm{\\mA/cm^{2}}$ , indicating excellent cycling stability. \n\nMultilayer ceramics have advantages for various applications, including battery electrolytes, but they are challenging to sinter because of interdiffusion at high temperatures. We synthesized a LATP/LLZTO bilayer SSE without detectable side reaction or cross-diffusion using the UHS technique (Fig. 4A). The LLZTO garnet is stable against the Li metal anode, and the LATP features superior oxidation stability compared with the LLZTO (fig. S28) (30). Conventional furnace sintering results in severe interdiffusion and side reactions at the interface (fig. S29). \n\nIntroducing low–melting point materials into ceramics is a general approach to achieving a dense structure at a lower sintering temperature. We sintered a ceramic composite SSE by adding $\\mathrm{Li_{3}P O_{4}}$ to the LLZTO garnet, in which the $\\mathrm{Li_{3}P O_{4}}$ can melt at ${\\sim}1200^{\\circ}\\mathrm{C}$ and weld with the LLZTO particles to form a dense composite pellet (Fig. 4B) by means of ultrafast liquid-phase sintering, with reduced side reactions and cross-doping compared with the conventional approach (fig. S30). \n\n![](images/2a92ac02ab033946cc8dca6a2c558ffba7e352f04def1bf11cff7d2d3a1153c5.jpg) \nFig. 4. Structures enabled by the UHS sintering technique. (A and B) Schematics and energy dispersive spectroscopy mapping of the cosintered LATP-LLZTO bilayer SSE (A) and the $\\mathsf{L L Z T O-L i_{3}P O_{4}}$ composite SSE (B). (C) Photographs of the SiOC polymer precursor printed as a single material. (D) Photographs of the SiOC samples sintered by the UHS method, showing the uniform material shrinkage and maintained structures. (E) Four UHS-sintered complex structures with different \nrepeating units. (F) The multilayer 3D-printed SiOC polymer precursor (doped with Al and Co) and the corresponding UHS-sintered structure. (G) Elemental mapping of the Co- and Al-doped boundary of the UHS-sintered and conventional furnace–sintered SiOC samples. (H) The piezoresistance versus the stress induced by the magnetic force of the 3D-printed magnetic flux density sensor device sintered by UHS and conventional sintering. $\\Delta{\\sf R}$ is the change in the piezoresistance. \n\nThe UHS technique can also sinter ceramic structures with complex geometries. This is notable because the SPS technique is incompatible with 3D-printed structures. We successfully sintered polymer-derived ceramics (silicon oxycarbide, SiOC) with uniform shrinking and well-maintained structures (Fig. 4, C and D, and movie S2). Additionally, the structures can be stacked to form a more complex 3D lattice design (Fig. 4E). 3D-printed structures and devices with different spatially distributed materials have applications emerging from various combinations of mechanical, thermal, or other properties (31–33). However, cosintering of these structures is challenging because of cross-diffusion. To explore the capabilities of UHS for such complex designs, we 3Dprinted multimaterial honeycomb structures featuring Al-doped SiOC (for piezoresistivity response) and Co-doped SiOC (for magnetic response, Fig. 4F) to form a magnetic flux sensor (fig. S31). The UHS sintering maintains the perfect registration of the structures with minimal diffusion of dopants caused by the short sintering time (Fig. 4G). Additionally, the 3D-printed magnetic flux sensor device effectively converts magnetic fields into voltage signals (fig. S31). In contrast, the conventional sintering method suffers from substantial diffusion between the different materials (Fig. 4G), which results in poor sensitivity of piezoresistive sensing (Fig. 4H and fig. S31). \n\nThe rapid sintering enables the potential for scalable, roll-to-roll sintering of ceramics because the precursor film can quickly pass through the heating strips to achieve continuous UHS. The thin, high-temperature carbon heater in the UHS technique is also highly flexible and can conformally wrap around structures for rapid sintering of unconventional shapes and devices (fig. S32). There are several other potential opportunities. First, UHS can be readily extended to a broad range of nonoxide high-temperature materials, including metals, carbides, borides, nitrides, and silicides, because of its extremely high temperature. Second, UHS may also be used to fabricate functionally graded materials (beyond the simple multilayers demonstrated in this work) with minimum undesirable interdiffusion. Third, the ultrafast, far-from-equilibrium nature of the UHS process may produce materials with nonequilibrium concentrations of point defects, dislocations, and other defects or metastable phases that lead to desirable properties. Finally, this UHS method allows a controllable and tunable temperature profile to enable the control of sintering and microstructural evolution. \n\n# REFERENCES AND NOTES \n\n1. P. B. Vandiver, O. Soffer, B. Klima, J. Svoboda, Science 246, 1002–1008 (1989). \n2. E. M. Rabinovich, J. Mater. Sci. 20, 4259–4297 (1985). \n3. Z. Zhang et al., Energy Environ. Sci. 11, 1945–1976 (2018). \n4. A. Manthiram, X. Yu, S. Wang, Nat. Rev. Mater. 2, 16103 (2017). \n5. Y. Li, J. T. Han, C. A. Wang, H. Xie, J. B. Goodenough, J. Mater. Chem. 22, 15357–15361 (2012). \n6. M. Nyman, T. M. Alam, S. K. McIntyre, G. C. Bleier, D. Ingersoll, Chem. Mater. 22, 5401–5410 (2010). \n7. I. Garbayo et al., Adv. Energy Mater. 8, 1702265 (2018). \n8. X. Huang et al., Energy Storage Mater. 22, 207–217 (2019). \n9. R. Pfenninger, M. Struzik, I. Garbayo, E. Stilp, J. L. M. Rupp, Nat. Energy 4, 475–483 (2019). \n10. R. R. Mishra, A. K. Sharma, Compos. Part A Appl. Sci. Manuf. 81, 78–97 (2016). \n11. M. Oghbaei, O. Mirzaee, J. Alloys Compd. 494, 175–189 (2010). \n12. O. Guillon et al., Adv. Eng. Mater. 16, 830–849 (2014). \n13. M. Cologna, B. Rashkova, R. Raj, J. Am. Ceram. Soc. 93, 3556–3559 (2010). \n14. D. Angmo, T. T. Larsen-Olsen, M. Jørgensen, R. R. Søndergaard, F. C. Krebs, Adv. Energy Mater. 3, 172–175 (2013). \n15. Y. Zhang, J. Nie, J. M. Chan, J. Luo, Acta Mater. 125, 465–475 (2017). \n16. M. Yu, S. Grasso, R. Mckinnon, T. Saunders, M. J. Reece, Adv. Appl. Ceramics 116, 24–60 (2017). \n17. A. Albrecht, A. Rivadeneyra, A. Abdellah, P. Lugli, J. F. Salmerón, J. Mater. Chem. C 4, 3546–3554 (2016). \n18. V. Thangadurai, S. Narayanan, D. Pinzaru, Chem. Soc. Rev. 43, 4714–4727 (2014). \n19. W. Ji et al., J. Eur. Ceram. Soc. 37, 2547–2551 (2017). \n20. A. Sharafi, C. G. Haslam, R. D. Kerns, J. Wolfenstine, J. Sakamoto, J. Mater. Chem. A 5, 21491–21504 (2017). \n21. R. P. Rao et al., Chem. Mater. 27, 2903–2910 (2015). \n22. E. Yi, W. Wang, J. Kieffer, R. M. Laine, J. Mater. Chem. A 4, 12947–12954 (2016). \n23. Y. Jin et al., Nat. Energy 3, 732–738 (2018). \n24. J. C. Bachman et al., Chem. Rev. 116, 140–162 (2016). \n25. G. Bernard-Granger, N. Benameur, C. Guizard, M. Nygren, Scr. Mater. 60, 164–167 (2009). \n26. S. P. Ong, L. Wang, B. Kang, G. Ceder, Chem. Mater. 20, 1798–1807 (2008). \n27. P. Albertus, S. Babinec, S. Litzelman, A. Newman, Nat. Energy 3, 16–21 (2018). \n28. C. Wang et al., J. Am. Chem. Soc. 139, 14257–14264 (2017). \n29. N. J. Taylor et al., J. Power Sources 396, 314–318 (2018). \n30. Y. Zhu, X. He, Y. Mo, J. Mater. Chem. A 4, 3253–3266 (2016). \n31. A. Bandyopadhyay, B. Heer, Mater. Sci. Eng. Rep. 129, 1–16 (2018). \n32. R. Lakes, Appl. Phys. Lett. 90, 221905 (2007). \n33. X. Kuang et al., Sci. Adv. 5, eaav5790 (2019). \n34. I. P. Roof, M. D. Smith, E. J. Cussen, H. C. zur Loye, J. Solid State Chem. 182, 295–300 (2009). \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge the support of the Maryland NanoCenter, its Surface Analysis Center and AIM Laboratory, and the NIST Center for Neutron Research. We also acknowledge M. R. Zachariah and D. J. Kline from the University of California, Riverside, for their contributions to the temperature measurement. Funding: This work is not directly funded. J.L. acknowledges support from the Air Force Office of Scientific Research (AFOSR) (FA9550-19-1-0327) and X.Z. acknowledges support from the National Science Foundation (CMMI1727492) and AFOSR (FA9550-18-1-0299). Author contributions: L.H. and C.W. developed the UHS concept and designed the overall experiments. Y.M. and Q.B. conducted the computational predictions and simulation analysis. X.Z. designed the 3D printing experiment. C.W. and W.P. carried out the UHS sintering experiments, electrochemical measurements, and SEM imaging. R.W. helped prepare the samples and conduct the XRD measurements. J.D. created the 3D illustrations. G.P. and J.G. performed XRD characterization. X.W. conducted the temperature profile measurement. H.W. and C.W. performed the NDP measurement. X.Z., H.C., R.H., and Z.X. conducted the material synthesis for 3D printing and characterization. B.Y., C.Z., and Y.P. conducted the measurements of thermal properties and temperature simulations. J.L. contributed to the mechanistic understanding and some sintering experimental designs and analysis. L.H., C.W., A.H.B., Y.M., X.Z., J.L., B.D., and J.-C.Z. collectively wrote and revised the paper. All authors discussed the results and commented on the manuscript. Competing interests: The authors declare no competing interests. A provisional patent application, titled “High Temperature Process for Ceramics and other Solid Materials,” has been applied for through the University of Maryland (U.S. provisional patent 62/849578). Data and materials availability: All data are available in the manuscript or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/368/6490/521/suppl/DC1 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S32 \nTables S1 to S3 \nReferences (35–56) \nMovies S1 and S2 \n8 October 2019; accepted 1 April 2020 \n10.1126/science.aaz7681 \n\n# Science \n\n# A general method to synthesize and sinter bulk ceramics in seconds \n\nChengwei Wang, Weiwei Ping, Qiang Bai, Huachen Cui, Ryan Hensleigh, Ruiliu Wang, Alexandra H. Brozena, Zhenpeng Xu, Jiaqi Dai, Yong Pei, Chaolun Zheng, Glenn Pastel, Jinlong Gao, Xizheng Wang, Howard Wang, Ji-Cheng Zhao, Bao Yang, Xiaoyu (Rayne) Zheng, Jian Luo, Yifei Mo, Bruce Dunn and Liangbing Hu \n\nScience 368 (6490), 521-526. DOI: 10.1126/science.aaz7681 \n\n# Speedy ceramic sintering \n\nSynthesizing ceramics can require heating for long times at high temperatures, making the screening of high-through-put materials challenging. C. Wang et al. developed a new ceramic-sintering technique that uses resistive heating of thin carbon strips to ramp up and ramp down temperature quickly. This method allows for the quick synthesis of a wide variety of ceramics while mitigating the loss of volatile elements. Ultrafast sintering is ideal for synthesizing many compositions to screen for ideal properties for a variety of applications, including the development of new solid-state electrolytes. \n\nScience, this issue p. 521 \n\nARTICLE TOOLS \n\n# SUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41560-020-0666-x", + "DOI": "10.1038/s41560-020-0666-x", + "DOI Link": "http://dx.doi.org/10.1038/s41560-020-0666-x", + "Relative Dir Path": "mds/10.1038_s41560-020-0666-x", + "Article Title": "Highly selective electrocatalytic CO2reduction to ethanol by metallic clusters dynamically formed from atomically dispersed copper", + "Authors": "Xu, HP; Rebollar, D; He, HY; Chong, LN; Liu, YZ; Liu, C; Sun, CJ; Li, T; Muntean, JV; Winulls, RE; Liu, DJ; Xu, T", + "Source Title": "NATURE ENERGY", + "Abstract": "Direct electrochemical conversion of CO(2)to ethanol offers a promising strategy to lower CO(2)emissions while storing energy from renewable electricity. However, current electrocatalysts offer only limited selectivity toward ethanol. Here we report a carbon-supported copper (Cu) catalyst, synthesized by an amalgamated Cu-Li method, that achieves a single-product Faradaic efficiency (FE) of 91% at -0.7 V (versus the reversible hydrogen electrode) and onset potential as low as -0.4 V (reversible hydrogen electrode) for electrocatalytic CO2-to-ethanol conversion. The catalyst operated stably over 16 h. The FE of ethanol was highly sensitive to the initial dispersion of Cu atoms and decreased significantly when CuO and large Cu clusters become predominullt species. Operando X-ray absorption spectroscopy identified a reversible transformation from atomically dispersed Cu atoms to Cu(n)clusters (n = 3 and 4) on application of electrochemical conditions. First-principles calculations further elucidate the possible catalytic mechanism of CO(2)reduction over Cu-n. Electrocatalytically reducing CO(2)to ethanol can provide renewably generated fuel, but catalysts are often poorly selective for this conversion. Here the authors use a Cu catalyst to produce ethanol with high selectivity. Cu dispersion is key to the performance and operando studies indicate that it changes under reaction conditions.", + "Times Cited, WoS Core": 499, + "Times Cited, All Databases": 524, + "Publication Year": 2020, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000552931500004", + "Markdown": "# Highly selective electrocatalytic $\\mathbf{CO}_{2}$ reduction to ethanol by metallic clusters dynamically formed from atomically dispersed copper \n\nHaiping Xu $\\textcircled{10}1,2,7$ , Dominic Rebollar1,2,7, Haiying He $\\textcircled{10}3$ , Lina Chong1, Yuzi Liu $\\textcircled{10}$ 4, Cong Liu   1 ✉, Cheng-Jun Sun5, Tao Li   2,5 ✉, John V. Muntean1, Randall E. Winans $\\textcircled{10}5$ , Di-Jia Liu $\\textcircled{10}1.6\\boxtimes$ and Tao Xu   2 ✉ \n\nDirect electrochemical conversion of $\\pmb{\\mathrm{co}}_{2}$ to ethanol offers a promising strategy to lower $\\mathbf{co}_{2}$ emissions while storing energy from renewable electricity. However, current electrocatalysts offer only limited selectivity toward ethanol. Here we report a carbon-supported copper ${\\bf({\\bf{C u}})}$ catalyst, synthesized by an amalgamated $\\pmb{\\ c u}$ –Li method, that achieves a single-product Faradaic efficiency (FE) of $91\\%$ at −0.7 V (versus the reversible hydrogen electrode) and onset potential as low as −0.4 V (reversible hydrogen electrode) for electrocatalytic $\\mathbf{co}_{2}$ -to-ethanol conversion. The catalyst operated stably over 16 h. The FE of ethanol was highly sensitive to the initial dispersion of $\\pmb{\\ c u}$ atoms and decreased significantly when $\\cos$ and large Cu clusters become predominant species. Operando $\\pmb{\\ x}$ -ray absorption spectroscopy identified a reversible transformation from atomically dispersed Cu atoms to $\\mathbf{cu}_{n}$ clusters $\\tan=3$ and 4) on application of electrochemical conditions. First-principles calculations further elucidate the possible catalytic mechanism of $\\pmb{\\mathrm{co}}_{2}$ reduction over $\\mathbf{cu}_{n}.$ \n\narbon capture, sequestration and conversion technologies are widely being researched as possible solutions to mitigate rising $\\mathrm{CO}_{2}$ levels1,2. The electrochemical $\\mathrm{CO}_{2}$ reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ to hydrocarbon fuels and chemicals using renewable electricity offers an attractive ‘carbon-neutral’ or even ‘carbon-negative’ strategy3,4. Various metals5–8, alloys9,10, metal oxides11,12, metal chalcogenides and organometallic complexes have been investigated as the electrocatalysts for $\\mathrm{CO}_{2}\\mathrm{RR}^{13,14}$ . Key challenges facing the current $\\mathrm{CO}_{2}\\mathrm{RR}$ electrocatalyst and electrolyser designs include: how to improve energy efficiency by reducing the overpotentials; how to increase the process selectivity by enhancing a single-product Faradaic efficiency (FE) and how to reduce the system and operating costs by increasing current density and catalyst durability. \n\nAmong various products from ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ higher hydrocarbons $(\\mathrm{C}_{2},$ $\\mathrm{C}_{3},\\ldots\\right)$ , such as ethanol, are particularly valuable. Electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ to ethanol is known over supported metal, particularly Cu-based catalysts8,15,16. To our knowledge, the lowest onset potential of conversion to ethanol is $-0.57\\mathrm{V}$ versus reversible hydrogen electrode (RHE) with FE of $1.9\\%$ (ref. 8). A breakthrough FE of $63\\%$ conversion to ethanol with a current density of $2.1\\mathrm{mAcm^{-2}}$ at $-1.2\\mathrm{V}$ versus RHE was achieved over a Cu nanoparticle/N-doped graphene catalyst16. Another study found that the $\\mathrm{CO}_{2}\\mathrm{RR}$ catalytic sites are originated from the low-coordinated surface atoms at the edge of Cu nanoparticles $(\\mathrm{NPs})^{17}$ . Synthesis of Cu NP with ultrasmall dimension showed to improve the catalytic selectivity18,19. Catalysts comprising single atom (SA) Cu or Ni ligated by nitrogen in organometallic complex or embedded in carbonaceous substrate have been identified effective mainly in electrochemically converting $\\mathrm{CO}_{2}$ to CO and $\\mathrm{H}_{2}$ (refs. 20,21). A very recent study, however, also reported a FE of $55\\%$ for $\\mathrm{CO}_{2}$ -to-ethanol at $-1.2\\mathrm{V}$ versus RHE over such catalyst22. These studies suggested that, not only the metal particle dispersion but also the nature of the substrate, could modify the electronic state and the stereochemistry of the active sites, which, in turn, alters the reaction path and catalytic mechanism. \n\nTo better understand the catalytic mechanism for improving activity and selectivity requires an ideal catalyst containing active sites as similar as possible, so that the final product can be analysed on the basis of the assumption of the same catalytic pathways. For a SA electrocatalyst, this means all the metal atoms are atomically and uniformly dispersed under the similar chemical environment as prepared. Under the reaction conditions, these atoms are therefore most likely to follow a similar path in forming active site and transition intermediates. In reality, however, $100\\%$ dispersed SA under identical chemical environments is difficult to prepare, particularly when heat treatment is involved. \n\nHere, we report the preparation of commercial carbon-supported $\\mathrm{Cu}\\ \\mathrm{SA}$ catalysts by an amalgamated $\\mathrm{{Cu-Li}}$ method. The catalysts demonstrated highly selective $\\mathrm{CO}_{2}$ -to-ethanol conversion with FE reaching ${\\sim}91\\%$ at $-0.7\\mathrm{V}$ versus RHE and an onset potential as low as $-0.4\\mathrm{V}$ with FE of ${\\sim}15\\%$ . The FE of the catalysts maintained at roughly $90\\%$ without degradation for $16\\mathrm{h}$ . The $\\mathrm{CO}_{2}$ -to-ethanol FE is favoured by high initial dispersion of single Cu atoms. Operando synchrotron X-ray absorption spectroscopy revealed that such dispersion played a critical role in a reversible transformation between $\\mathrm{Cu}\\ \\mathrm{SA}$ and $\\mathrm{Cu}_{n}$ $\\stackrel{\\cdot}{n}=3$ and 4) as the active sites during the electrocatalytic reaction, which is further supported by density functional theory (DFT) calculation. This study helps to explain the limited FE observed in the previous studies and shed light on further improving $\\mathrm{CO}_{2}\\mathrm{RR}$ catalysts through rational design. \n\n![](images/ee366496fe6ce83a878adf0dffc3680dc74b1d2f7b929e69cd94a2deec146956.jpg) \nFig. 1 | Catalyst synthesis. Step-by-step preparation of the carbon-supported Cu SA catalyst using an amalgamated $\\mathsf{C u}$ –Li method. \n\n# Catalyst synthesis and characterization \n\nThe catalyst synthesis is shown in Fig. 1. Briefly, the bulk Cu is added into molten lithium until it is fully dissolved under sonication. Cu remains to be atomically isolated during quenching of lithium melting to room temperature, followed by converting Li to LiOH under humidified air to form a Cu–LiOH mixture. After blending the mixture with carbon support (XC-72) and leaching away LiOH with water, the Cu atoms are transferred over to the carbon surface. Since the transfer process occurs at an ambient temperature, the Cu atom migration and agglomeration are kept to a minimum and mainly remain in an atomically dispersed form. During the water rinsing, a highly basic solution from the dissolved LiOH activates the carbon surface to form hydroxyl and carboxyl groups, as evidenced by infrared spectroscopic study (Supplementary Fig. 1). The Cu atoms are ligated by the oxygenated groups, and so have different chemical environments from the previous studies22. \n\nFive catalysts with increasing Cu nominal loading of $x w t\\%$ , with $x$ ranging from 0.1 to 6 over XC-72, were prepared, each denoted $\\mathrm{Cu/C}–x$ . Their actual Cu loadings were analysed and are listed in Supplementary Table 1. The state of Cu dispersion was first studied by high-angle annular dark-field and aberration-corrected scanning transmission electron microscopy (HAADF–STEM) combined with an energy dispersive X-ray (EDX) spectroscopy22,23. Figure 2a is a representative HAADF–STEM image of the catalyst $\\mathrm{Cu/C{-}0.4}$ . The data indicates that all the $\\mathrm{Cu}$ atoms existed as isolated SAs and no NPs were detected. Figure 2b details a line of non-bonded Cu SAs marked by yellow circles. The intensity profile obtained from the line scan along the red line over isolated atoms in Fig. 2b shows individual peaks with a full-width at half-maximum of ${\\sim}1.37\\mathring\\mathrm{A}$ (Fig. 2c), close to the reported Cu atom radius $(1.28\\mathring{\\mathrm{A}})^{24}$ . When the Cu loading increased to $0.8\\mathrm{wt\\%}$ , isolated and loosly clustered $\\mathrm{cu}$ atoms were formed (Supplementary Fig. 2). The clusters were composed of randomly assembled Cu atoms with the interatomic distances longer than those in the metallic $\\mathrm{CuNPs^{19}}$ . EDX study proves that $\\mathrm{Cu}$ is the only metal element on the carbon (Supplementary Fig. 3). As the Cu loading further increased to $1.6\\mathrm{wt\\%}$ , a mixture of isolated Cu SAs and amorphous Cu NP were observed (Supplementary Fig. 4). X-ray diffraction (XRD) patterns showed a trace amount of CuO in $\\mathrm{Cu}/\\mathrm{C}{-}1.6$ and, to a lesser degree, in $\\mathrm{Cu/C}$ - 0.4 samples (Fig. 2d). No detectable Cu metal peak was observed. \n\nThe coordination structures of the Cu atom in as-prepared catalysts were quantitatively analysed by the radial distribution function extracted from the extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) with $k^{2}$ -weight in $R$ space, as the examples of $\\mathrm{Cu/C{-}0.4}$ and $\\mathrm{Cu}/\\mathrm{C}{-}1.6$ given in Fig. 2e. We analysed the first coordination shell of $\\mathtt{C u O}$ and found the coordination number decreased from 3.29 $(\\pm0.62)$ to 2.25 $(\\pm0.52)$ as the $\\mathtt{C u}$ loading increased from 0.1 to $6\\mathrm{wt\\%}$ (Supplementary Table 2 and Supplementary Fig. 5). The observation indicates that, at very low Cu loadings of 0.1 to $0.4\\mathrm{wt\\%}$ , Cu in the as-synthesized catalysts is predominately in the form of a SA coordinated by four oxygen atoms (possibly two from hydroxyl groups on the carbon substrate and two from labile $\\mathrm{H}_{2}\\mathrm{O}$ molecules). As the Cu loading increased to $0.8\\mathrm{wt\\%}$ or higher, the Cu–Cu shell appeared with coordination numbers of 1.84 $(\\pm0.56)$ obtained for $\\mathrm{Cu}/\\mathrm{C}{-}0.8$ and 3.08 $(\\pm0.62)$ obtained for $\\mathrm{Cu}/\\mathrm{C}{-}6$ , respectively. These coordination numbers are still notably lower than that of the fully coordinated Cu found in very large Cu crystallites or $\\mathtt{C u}$ foil (coordination number, 12), indicating very small average Cu NP sizes (Supplementary Fig. 6 and Supplementary Table 3). Note that increasing the coordination number of $\\mathrm{{Cu-Cu}}$ will lower the coordination number of $\\mathtt{C u O}$ since X-ray absorption spectroscopy is a measurement averaged over all Cu species. Our analysis suggests that the Cu species in as-synthesized catalysts evolves from mainly $\\operatorname{Cu}\\operatorname{SA}$ to the mixture of Cu SA, CuO and Cu clusters as Cu loading increases. Such an observation also agrees well with the HAADF– STEM results. \n\nWe also investigated X-ray absorption near-edge structure (XANES) to better understand the electronic structure in assynthesized catalysts25,26. Figure 2f shows the Cu $k$ -edge XANES spectra of the $\\mathrm{{Cu}/\\mathrm{{C}}\\mathrm{{-}}0.4}$ and $\\mathrm{Cu}/\\mathrm{C}{-}1.6$ , together with the references of copper(II) acetylacetonate $[\\mathrm{Cu}(\\mathrm{AcAc})_{2}]$ , which contains a 4-O ligated $\\mathrm{{Cu}(I I)}$ simulating Cu SA in the ionic form, CuO and copper foil. The edge feature of $\\mathrm{Cu/C{-}0.4}$ resembles the mixture dominated by $\\operatorname{Cu}(\\operatorname{AcAc})_{2}$ with a minor contribution by CuO. This is confirmed by linear combination fitting (LCF) (Supplementary Fig. 7) showing that most Cu is in the SA form coordinated by four O atoms. ${\\mathrm{Cu/C}}.$ - 1.6, on the hand, has the XANES feature with high percentage contributions from ${\\mathrm{Cu}}({\\mathrm{AcAc}})_{2},$ CuO and Cu metal. This observation is consistent with EXAFS analysis. XANES also lent an important quantitative analysis of different Cu species in the samples by simulating the range with the LCF of that of the reference compounds at different fractions (Supplementary Methods). We first applied $\\operatorname{Cu}(\\operatorname{AcAc})_{2}$ , CuO and Cu metal as references to simulate the amount of Cu SAs, oxide and metallic NP sin each as-synthesized catalysts. Simulated spectra with minimal deviation from the experimental data were obtained by least-square fitting (Supplementary Fig. 7). The fractions of each component at different catalyst Cu loadings are listed in Supplementary Table 4 and Supplementary Fig. 7c. \n\n![](images/9f9dda0b6da72ed1dce7d9d0076e5abb4aab5f62572f88fc30ca61e5d5247300.jpg) \nFig. 2 | Catalyst structure characterizations. a,b, Representative HAADF–STEM images of ${\\mathsf{C u}}/{\\mathsf{C}}{\\cdot}0.4$ showing the presence of isolated Cu species marked by yellow circles. Scale bars: a, $2{\\mathsf{n m}}$ and b, 1 nm. c, Intensity profile of a single atomic column following the red line in b. Two red lines with a black square at the centre mark the halfwidth of one peak associated with the radius of an SA. d, XRD patterns of catalysts with $\\mathsf{C u}$ loading of 0.4 and $1.6\\mathrm{wt\\%}$ . The broad peaks at $25^{\\circ}$ and $43^{\\circ}$ are due to the XC-72 carbon support. e, Fourier transform of $k^{2}$ -weighted R space χ EXAFS data of the catalysts plus ${\\mathsf{C u}}(\\mathsf{A c A c})_{2}$ as a reference. f, Cu $k$ -edge normalized XANES spectra as a function of incident photon energy (E) for the catalyst samples plus ${\\mathsf{C u}}({\\mathsf{A c A c}})_{2},$ CuO and $\\mathsf{C u}$ foil as references. \n\nA systematic drop of $\\operatorname{Cu}\\operatorname{SA}$ fraction and the rise of $\\mathrm{{CuO/Cu}}$ metal components were clearly seen as the $\\mathtt{C u}$ loading in the catalyst increased. We also applied $\\mathrm{{Cu}/\\mathrm{{C}-0.1}}$ in the place of $\\operatorname{Cu}(\\operatorname{AcAc})_{2}$ as the SA reference assuming that all $\\mathtt{C u}$ atoms in this sample were atomically dispersed. Similar trends in SA, CuO and Cu metal concentration changes were also observed with the values of each fraction being only slightly different from that using $\\operatorname{Cu}(\\operatorname{AcAc})_{2}$ as a reference (Supplementary Table 5 and Supplementary Fig. 7d). \n\n# Electrocatalytic $C O_{2}R R$ measurement \n\nThe electrocatalytic $\\mathrm{CO}_{2}\\mathrm{RR}$ performances of the catalysts were evaluated by linear sweep voltammetry (LSV), cyclic voltammetry and chronoamperometry on a rotating disc electrode (RDE) in $0.1\\mathrm{M}$ ${\\mathrm{KHCO}}_{3}$ electrolyte solution. (Supplementary Fig. 8) We chose RDE because its polished graphite surface is fully covered by the catalyst with a more accurate area current density calculation and it contributes no byproduct to the electrocatalytic reactions. Figure 3a shows LSVs over $\\mathrm{{Cu/C{-}0.4}}$ in the Ar- and $\\mathrm{CO}_{2}$ -purged electrolytes. A notably enhanced current density in $\\mathrm{CO}_{2}$ saturated over Ar-purged electrolyte is attributed to the direct $\\mathrm{CO}_{2}\\mathrm{RR}$ through solvated $\\mathrm{CO}_{2}$ (ref. 27). Similarly, cyclic voltammetry curves with or without saturated $\\mathrm{CO}_{2}$ clearly displayed $\\mathbf{CO}_{2}\\mathrm{RR}$ activity in the potential range from 0 to $-1.5\\mathrm{V}$ (Supplementary Fig. 9a). As the baseline, the electrode containing carbon treated by the same Li melt/LiOH process, except without the addition of Cu, yielded a far lower current density and produced a minor amount of hydrogen at a substantially more negative potential (Supplementary Fig. 10). Figure 3b showed the FEs and $\\mathrm{CO}_{2}\\mathrm{RR}$ product distributions as the function of applied potentials from $-0.4$ to $-1.2\\mathrm{V}$ over $\\mathrm{Cu/C{-}0.4}$ . Representative nuclear magnetic resonance (NMR) spectra of the ethanol produced in the electrolyte are shown in Supplementary Fig. 11. We detected the active potential for ethanol formation as low as $-0.4\\mathrm{V}$ with a decent FE of ${\\sim}15\\%$ . At $-0.3\\mathrm{V},$ we did not observe any ethanol production. The observation suggests that the actual onset potential is in between $-0.3$ and $-0.4\\mathrm{V},$ or an overpotential between $-0.39$ and $-0.49\\mathrm{V}$ given the equilibrium potential of $0.09\\mathrm{V}$ (ref. 7). The FE for ethanol reached as high as ${\\sim}91\\%$ at a low potential of $-0.6$ and $-0.7\\mathrm{V}.$ To our knowledge, this value represents the highest FE for direct electrocatalytic $\\mathrm{CO}_{2}$ -to-ethanol conversion among Cu-based catalysts2,8,16,28. A chronoamperometry study over a $16\\mathrm{-h}$ span at $-0.7\\mathrm{V}$ showed an excellent stability in both current density and FE of $\\mathrm{CO}_{2}$ -to-ethanol over $\\mathrm{{Cu/C{-}0.4}}$ (Fig. 3c). The current stability was also observed at various potentials from $-0.4$ to $-1.2\\mathrm{V}$ (Supplementary Fig. 9b). Furthermore, the electrochemical double layer capacity (EDLC) was found to be essentially identical before and after chronoamperometry measurement at different potentials (Supplementary Fig. 12). \n\nTo better understand the catalytic mechanism, the $\\mathbf{CO}_{2}\\mathrm{RR}$ catalysis over $\\mathrm{{Cu/C\\mathrm{{-}\\mathrm{{X}}}}}$ catalysts with nominal $\\mathrm{cu}$ loadings of 0.1, 0.8, 1.6 and $6\\mathrm{wt\\%}$ were also studied. LSVs over these catalysts show a rise of $\\mathrm{CO}_{2}\\mathrm{RR}$ current density with the incremental increase of the Cu loading, as one would have expected, since more active centres were added (Supplementary Fig. 13). For each catalyst, LSV, cyclic voltammetry, FE and product distribution, as well as chronoamperometry at different electrode potentials were measured (Supplementary Figs. 14–17). All the catalysts demonstrated enhanced current densities in LSV and cyclic voltammetry in $\\mathrm{CO}_{2}$ saturated over Ar-purged electrolytes. All catalysts showed excellent stability, as demonstrated by the steady current density as the function of time at every voltage in the chronoamperometric measurement. We noticed that the FE and CO2RR product distributions became very different, however, as the Cu loading increased beyond $0.8\\mathrm{wt\\%}$ . The total current density represents the overall conversion of $\\mathrm{CO}_{2}$ to all products. After analysing FE trends for each product, we found that the intrinsic rate of $\\mathrm{CO}_{2}$ -to-ethanol in terms of turnover frequency (TOF) actually decreased with an increase in the catalyst’s Cu loading, as will be discussed later. The Cu-based mass activities of $\\mathrm{CO}_{2}$ -to-ethanol conversion for all catalysts are plotted in Supplementary Fig. 18. \n\n![](images/e86219c098c4df82fc146a3065c702f6cee7a0ed1da0af316ba4739f633d5020.jpg) \nFig. 3 | Electrocatalytic $C O_{2}R R$ measurement over ${\\mathsf{C u/C-O}}.4.$ a, LSVs of ${\\mathsf{C u}}/{\\mathsf{C}}{\\cdot}{0.4}$ in $\\mathsf{A r}$ and ${\\mathsf{C O}}_{2}$ saturated 0.1 M $K{\\mathsf{H C O}}_{3}$ at electrochemical potential (E) from 0 to $-1.5\\vee$ versus RHE (scan rate, $50\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1})$ . ${\\boldsymbol{j}},$ current density. b, FE and the product distribution at different polarization potentials. The data were averaged over three repeated measurements with the standard deviations marked by black error bars for ethanol and red error bars for the total products. Note that total FEs of less than $100\\%$ at the potential $\\leq-1.0\\vee$ are attributed to the uncounted hydrocarbons detected by gas chromatography. At $-0.4\\mathsf V,$ less than $100\\%$ FE may be due to the concentration of unidentified product $(\\mathsf{s})$ too low to detect at low current density. c, FE and current density as a function of time during chronoamperometric electrolysis at $-0.6\\mathsf{V}.$ \n\nFigure 4a shows the FEs of the ethanol formation at different potentials obtained from the individual catalysts studied. For ${\\mathrm{Cu/C}}.$ 0.1, $\\mathrm{{Cu/C{-}0.4}}$ and $\\mathrm{Cu}/\\mathrm{C}{-}0.8$ , the FEs for ethanol formation followed an almost identical profile to the active potential starting as low as $-0.4\\mathrm{V}$ and reaching a peak value of ${>}90\\%$ at $-0.7\\mathrm{V}.$ Once the $\\mathrm{Cu}$ loading reached $1.6\\mathrm{wt\\%}$ or higher; however, the ethanol FE profile underwent a drastic change. First, the ethanol production potential was shifted to a slightly more negative voltage of $-0.5\\mathrm{V}.$ Second, the peak FE value at $-0.8\\mathrm{V}$ dropped notably to less than $40\\%$ . Analysis of FEs of other products found that the production of hydrogen, and to a lesser degree CO, inversely correlates to that of ethanol (Fig. 4b and Supplementary Fig. 19), whereas other species, such as acetone, methane and formic acid, showed no clear correlation at all. This observation indicates the existence of competing catalytic pathways between ethanol and $\\mathrm{H}_{2}$ or CO formation. Furthermore, such a pathway is very sensitive to Cu loading and the state of Cu in the catalyst. \n\nFigure $\\mathtt{4c}$ shows the Tafel plots derived from the ethanolproducing current density at different polarization overpotentials $(\\eta)$ over all five catalysts. Catalysts $\\mathrm{{Cu}/\\mathrm{{C}}\\mathrm{{-}0.1}}$ , $\\mathrm{{Cu/C^{-}{0.4}}}$ and ${\\mathrm{Cu/C}}.$ 0.8 demonstrated almost identical Tafel slopes at the low voltage domain, indicating that these three catalysts follow similar electrocatalytic kinetics at this voltage range even at different current densities. For catalysts $\\mathrm{Cu}/\\mathrm{C}{-}1.6$ and $\\mathrm{Cu}/\\mathrm{C}{-}6_{\\mathrm{:}}$ however, the Tafel slope increased nearly threefold, indicating substantially slower $\\mathbf{CO}_{2}\\mathrm{RR}$ kinetics that were possibly influenced by a different catalytic mechanism. \n\nThese pieces of experimental evidence suggest that the electrocatalytic mechanism switches as the Cu metal loading increases. As mentioned, the fraction of $\\mathrm{Cu\\SA}$ in the as-prepared catalyst decreases with an increase of Cu loading, whereas the total number of Cu SAs per gram of catalyst increases almost linearly and remains as the principal component at a Cu loading of ${<0.8\\mathrm{wt\\%}}$ . When the loading doubled to $1.6\\mathrm{wt\\%}$ or higher, the combined fraction of CuO and ${\\mathrm{Cu}}^{0}$ NPs become dominant at ${>}65\\%$ (Supplementary Fig. 7 and Supplementary Table 4). Such a transition from SA to NP in the catalyst led to a sudden drop of FE and EDLC (Supplementary Fig. 20 and Supplementary Table 6) and appears to be responsible for the shift in $\\mathbf{CO}_{2}\\mathrm{RR}$ mechanism and kinetics. The observation indicates that the atomically dispersed Cu in the as-synthesized catalyst correlates well with the $\\mathrm{CO}_{2}$ -to-ethanol conversion. $\\mathtt{C u O}$ and metal NP, on the other hand, promote the competing side reactions to the byproducts. This relationship was further revealed by an operando X-ray absorption measurements (XAS) study described next. From the FE value, total current density and number of Cu SAs, we calculated the ethanol formation current density and TOF per Cu atom assuming the active site is the associated SAs in the catalyst. Figure 4d shows that the partial current density to ethanol conversion measured at $-0.7\\mathrm{V}.$ It grew proportionally to the $\\mathrm{Cu}\\mathrm{SA}$ number, as one would have expected, before its abrupt descent at the transition point of $0.8\\mathrm{-}1.6\\mathrm{wt\\%}$ . The highest TOF of $\\mathrm{CO}_{2}$ -to-ethanol was found to be $0.037\\mathrm{s^{-1}C u}$ per site, a reasonable value given the multi-step electron and proton transfers and non-electrochemical $C{\\mathrm{-}}C$ coupling involved. Figure 4d also shows that the TOF declined gradually with an increase in SA number. Since the TOF over individual active sites should be unchanged under the same voltage, we speculate that such a decline may be due to the presence of competing reactions with other products. The solvated $\\mathrm{CO}_{2}$ has low concentration in the bicarbonate electrolyte. As Cu loading increases, $\\mathrm{CO}_{2}$ conversion to other byproducts such as $\\mathrm{H}_{2}$ and CO increases over different catalytic sites such as a large Cu cluster, competing for limited numbers of solvated $\\mathrm{CO}_{2}$ and leading to lower TOF of direct $\\mathrm{CO}_{2}$ -to-ethanol conversion. We also calculate the TOFs of individual compounds at $-0.7\\mathrm{V}$ for several catalysts. (Supplementary Table 7) \n\nOur study indicates that initial $\\mathtt{C u}$ atom dispersion in the as-synthesized catalyst plays a critical role in improving FE and reducs onset potential for direct $\\mathrm{CO}_{2}$ -to-ethanol electrochemical conversion. The catalyst displayed excellent FE compared to the previously studies on $\\mathrm{CO}_{2}$ -to-ethanol and other hydrocarbon conversions (Supplementary Tables 8 and 9). As more Cu NPs form at higher Cu loading, competing reactions over Cu cluster/NP can dominate catalysis, therefore changing the make-up of the final product. Such an experimental observation is highly important in the catalyst design for direct $\\mathrm{CO}_{2}$ -to-ethanol conversion. The remaining question is, however, how do the Cu SAs in the as-synthesized catalyst participate and affect $\\mathrm{CO}_{2}\\mathrm{RR}$ catalytic mechanism? \n\n# Catalyst structure during electrocatalysis \n\nWe first examined the HAADF–STEM of $\\mathrm{{Cu}/\\mathrm{{C}}\\mathrm{{-}}0.4}$ after a $16\\mathrm{-h}$ $\\mathrm{CO}_{2}\\mathrm{RR}$ chronoamperometric run at $-0.7\\mathrm{V}$ (Supplementary \n\n![](images/4201c2cd4871583c76c78fe990a4fb76f1121c68c0abdb04a5194a5f31b8f79c.jpg) \nFig. 4 | Electrochemical properties of $\\mathsf{c u/c}$ at different loading. a, FE of ${\\mathsf{C O}}_{2}$ -to-ethanol at different potentials over catalysts of different Cu loadings. b, FE of ${\\sf H}_{2}$ formation at different potentials over different catalysts. The data were averaged over three repeated measurements. The error bars represent the standard deviation. c, Tafel plots of polarization overpotential $(\\eta)$ versus ethanol partial current density of different catalysts. d, The partial current density for ethanol conversion (blue bar) and TOF of ethanol (red line) as the function of total number of Cu SAs per gram of the catalyst in asprepared catalysts. \n\nFig. 21) and found Cu remains atomically dispersed. We also studied EXAFS and XANES of $\\mathrm{Cu/C{-}0.4}$ before (pre $\\mathrm{Cu/C)}$ and after (post $\\mathrm{Cu/C)}$ chronoamperometric measurement (Fig. 5a,b). The Fourier transformed $\\chi$ function in $k^{2}$ -weighted $R$ space showed an almost fully coordinated $\\mathtt{C u O}$ shell for both pre and post $\\mathrm{Cu/C}$ catalysts, indicating that Cu remains as atomically dispersed $\\mathrm{Cu}^{+2}$ ligated by four oxygens after extended hours of electrocatalysis. The XANES also showed that the $\\mathrm{Cu}$ in both samples is in the $+2$ oxidation state with a slightly higher white intensity in post $\\mathrm{Cu/C{-}0.4}$ from higher oxygen coordination (Fig. 5b). \n\nWe further interrogated the electronic and coordination structures of $\\mathtt{C u}$ in $\\mathrm{Cu/C{-}\\bar{0}{.}4}$ during $\\mathrm{CO}_{2}\\mathrm{RR}$ through operando XAS measurement (Supplementary Fig. 22). As soon as the cell voltage was applied at $-0.7\\mathrm{V}$ (the optimized $\\mathrm{CO}_{2}$ -to-ethanol conversion potential), immediate reduction from ionic to metallic Cu was observed (Fig. 5c). The XANES spectrum predominantly resembles that of ${\\mathrm{Cu}}^{0}$ with a minor component of $\\mathrm{Cu^{+}}\\left(\\mathrm{Cu}_{2}\\mathrm{O}\\right)$ . Further decreasing cell voltage to $-1.0\\mathrm{V}$ did not result in any notable change. EXAFS analysis also found the Cu first shell coordination switched from $\\mathtt{C u O}$ to mainly $\\mathrm{{Cu-Cu}}$ under the electrochemical potential with a coordination number of 2 $(\\pm0.9)$ or 3 $(\\pm1.2)$ (Fig. 5d and Supplementary Table 9), indicating the formation of ultrasmall Cu moiety, $\\operatorname{Cu}_{n},$ where $n=3$ or 4. Such Cu moieties have stable geometric shapes of equilateral triangles or tetrahedrons. The $\\mathrm{{Cu-Cu}}$ bond length $(R)$ was found to be shorter than that in Cu foil, agreeing with the theoretical calculation29. Combined XANES and EXAFS results indicated that a transformation from atomically dispersed $\\mathrm{Cu}^{+2}$ to metallic $\\mathrm{Cu}_{3}$ or $\\mathrm{Cu}_{4}$ under a reducing potential, served as the active sites for $\\mathrm{CO}_{2}$ -to-ethanol conversion. Once the cell voltage was switched off to stop the electrocatalytic reaction (post $\\mathrm{Cu}/\\mathrm{C}{-}0.{\\dot{4}};$ , the \n\nCu oxidation state and first coordination shell reversed from Cu–Cu to $\\mathtt{C u O}$ ligation at a $\\mathrm{Cu}^{+2}$ oxidation state, suggesting a re-oxidation of $\\mathrm{Cu}_{n}$ to the oxidized Cu SA in a $\\mathrm{CO}_{2}$ -saturated electrolyte. This also reaffirmed the observation of $\\operatorname{Cu}\\operatorname{SA}$ remaining to be oxidized and atomically dispersed after extended hours of electrocatalysis. Similar Cu SA-to-cluster transformation over a N-decorated carbon surface during electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ was also recently reported22. \n\nThe operando XAS study revealed an important phenomenon in our catalyst, which is the existence of a dynamic and reversible transformation between SA to the $\\mathrm{Cu}_{n}$ active site under the reaction conditions. In Fig. 5e, we postulate a catalytic mechanism as follows. Before ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ the Cu ion is anchored by four oxygens from the hydroxyl group and water. Under the operating potential, an electron will be transferred from the carbon support to reduce $\\mathrm{Cu}^{+2}$ to $\\mathrm{Cu^{\\mathrm{0}}}$ , which subsequently forms $\\mathrm{Cu}_{3}$ or $\\mathrm{Cu}_{4}$ by coalescing with Cu atoms nearby. The Cu moiety will be ligated by the surface hydroxyl group and serve as the transient active site to bind with $\\mathrm{CO}_{2}$ in the electrolyte. The conversion of $\\mathrm{CO}_{2}$ -to-ethanol is completed through sequential steps of proton and electron transfers. In the absence of an electric field, Cu moiety is highly unstable and can be easily oxidized by the weak oxidant such as soluble $\\mathrm{CO}_{2}$ , reverting back to Cu SA ions and completing the catalysis loop. Such a mechanism is further elucidated by the DFT calculations that follow. \n\n# DFT calculations \n\nDFT calculations were performed in attempt to gain mechanistic insights into the electrochemical reduction of $\\mathrm{CO}_{2}$ on the catalyst. As briefly depicted in Fig. 5e, a four-coordinate $\\mathrm{{Cu}(I I)}$ site is proposed to be the structure of the as-synthesized catalyst (precatalyst) resulting from the interactions of $\\mathtt{C u}$ with the hydroxylate graphene in the electrolyte (Fig. 6a and Supplementary Fig. 23), in which $\\mathtt{C u(I I)}$ is coordinated with two oxyl groups on graphene and two $_\\mathrm{H}_{2}\\mathrm{O}$ molecules, agreeing well with the XAS measurements (Fig. 5a–d). \n\n![](images/43858402957aff2b1a478ac4ececaa0c3c30ea5eb2db76fb92f23c06c3fdbbeb.jpg) \nFig. 5 | Operando XAS study on the Cu $C O_{2}R R$ active site. a, Fourier transform of $k^{2}$ -weighted R space $\\chi$ EXAFS data of the postmortem catalysts of ${\\mathsf{C u}}/{\\mathsf{C}}{\\cdot}0.4$ after 16 h chronoamperometry measurement and ${\\mathsf{C u}}({\\mathsf{A c A c}})_{2}$ as a reference. b, $\\mathsf{C u}k$ -edge normalized XANES spectra of the postmortem catalyst sample of ${\\mathsf{C u}}/{\\mathsf{C}}{\\cdot}{0.4}$ after 16 h chronoamperometry measurement and ${\\mathsf{C u}}({\\mathsf{A c A c}})_{2}$ as references. c, In situ $\\mathsf{C u}k$ -edge XANES spectra of pre $\\mathsf{C u/C-O.4}$ , ${\\mathsf{C u}}/{\\mathsf{C}}{\\cdot}{0.4}$ at $-0.7\\vee$ versus RHE and $-1.0\\vee$ versus RHE and post $C\\cup/C{\\cdot}0.4.$ d, Fourier transform of $k^{2}$ -weighted $\\chi$ function in $R$ space of the catalysts plus ${\\mathsf{C u}}(\\mathsf{A c A c})_{2}$ as a reference (pre ${\\mathsf{C u}}/{\\mathsf{C}}{\\cdot}0.4$ refers to the catalyst measured before reduction potential was applied; post ${\\mathsf{C u}}/{\\mathsf{C}}{\\mathsf{-}}0.4$ refers to the catalyst after ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ at $-0.7$ and $-1.0\\vee$ versus RHE). e, The hypothesized reaction mechanism suggested by the operando measurements. \n\nDuring the electrochemical reaction, however, our calculations show that the reduction of the $\\mathrm{{Cu}(I I)}$ site to lower oxidation states (that is, $\\mathtt{C u(I)}$ and $\\operatorname{Cu}(0)$ , Supplementary Fig. 24) by $\\left(\\mathrm{H^{+}}+\\mathrm{e^{-}}\\right)$ is thermodynamically favourable. The reduction of Cu could lead to formation of few-atom clusters, as observed by operando XAS (Fig. 5c,d and Supplementary Table 10). To simplify the calculation, a supported $\\mathrm{Cu}_{3}$ cluster model was used to represent the catalytic site (Figs. 5e and $6\\ensuremath{\\mathrm{b}}$ and Supplementary Data 1), assuming a $\\mathrm{Cu}_{4}$ cluster would share a similar mechanism. The calculated average partial charge on Cu atoms of $\\mathrm{Cu}_{3}$ is $+0.15\\mathrm{e}^{-}$ , due to the interaction between one of the $\\mathtt{C u}$ atoms and the hydroxyls on graphene. The graphene hydroxyls, which are abundant from the synthesis (Supplementary Fig. 1), probably play a critical role in anchoring the $\\mathrm{Cu}_{3}$ on the support as an intermediate species during catalysis. \n\nA reaction network for $\\mathrm{CO}_{2}\\mathrm{RR}$ to ethanol, derived from two main mechanisms, that is, the $\\mathrm{HCOO^{*}}$ mechanism and the $\\scriptstyle\\mathrm{CO^{*}}$ mechanism, was thoroughly investigated using the computational hydrogen electrode approach30 (Supplementary Fig. 25). On the basis of reaction free energies, the $\\mathrm{HCOO^{*}}$ pathway is calculated to be more energetically favourable by forming coadsorbed $(\\mathrm{HCOOH^{*}+H C O O H^{*}})$ ) (State 5, Fig. 6a), followed by further reduction of one of the adsorbed $\\mathrm{HCOOH^{*}}$ to form $\\mathrm{CH_{3}^{\\ast}+H C O O H^{\\ast}}$ (State 10, Fig. 6a). Subsequently, the second $\\mathrm{HCOOH^{*}}$ is reduced to form $\\mathrm{CH}_{3}{^{*}}+\\mathrm{H}_{2}\\mathrm{CO}{^{*}}$ (State 12, Fig. 6a), which undergoes a $C{\\mathrm{-}}C$ bond formation to form ethanol (Fig. 6c). The computed $\\mathrm{CO^{*}}$ pathway (Supplementary Fig. 26 and Supplementary Data 2) requires higher reaction free energies in several steps than the $\\mathrm{HCOO^{*}}$ pathway. Nonetheless, the FE distribution (Fig. 3b) shows that both \n\nHCOOH and CO are formed, along with ethanol at the potentials above or below $-0.6$ and $-0.7\\mathrm{V}$ where ethanol has its peak FE. This trend indicates that both $\\mathrm{HCOO^{*}}$ and $\\mathrm{CO^{*}}$ pathways could be competitive in forming ethanol. A more comprehensive understanding of the reaction mechanism would require complex kinetic analysis, which should be the focus of future studies. \n\nThe calculated overpotential $(-0.49\\mathrm{V})$ is found to be qualitatively agreeable with the experimental overpotential (between $-0.39$ and $-0.49\\mathrm{V},$ Fig. 3b), given that the simplified models without including the explicit solvent and electric double layer were used. The non-electrochemical free energy barrier of the C–C bond formation step ( $\\cdot12\\to13$ , Fig. 6c) is calculated to be $0.83\\mathrm{eV},$ which could account for the low overall turnover rate observed experimentally (Fig. 4d). The reaction pathways of other products were also investigated (Supplementary Fig. 25 and Supplementary Table 11). Ligation of the transient $\\mathrm{Cu}$ active centre by the hydroxyl group on carbon surface appears to account for the main distinction in controlling the selectivity to ethanol between our Cu catalyst versus the reported Cu on nitrogen-doped carbon22. \n\n# Conclusions \n\nWe have systematically investigated several carbon-supported Cu catalysts prepared using amalgamated Cu–Li as the precursor. The catalysts demonstrated high FE $(\\sim91\\%$ at $-0.7\\mathrm{V}$ and low onset potential $(-0.4\\mathrm{V})$ during the conversion of $\\mathrm{CO}_{2}$ -to-ethanol. Experimental study, combining with the DFT calculation, revealed the vital role of Cu SA in the as-prepared catalyst in controlling the active site formation and catalytic performance. Operando XAS results show a dynamic transformation of $\\mathtt{C u\\ S A}$ to $\\mathrm{Cu}_{n}$ under $\\mathrm{CO}_{2}\\mathrm{RR}$ potentials, which is reversible on the cutoff of cell voltage. The surface hydroxyl group plays a crucial role in modulating the interaction between the catalytic centre and the carbon substrates, which affects the catalysis mechanism. This study calls for more fundamental investigations on the atomically dispersed electrocatalyst in $\\mathrm{CO}_{2}$ to chemical conversion for practical application. \n\n![](images/3ca78628559adf5226381967c25df71d773e9de643249060a5a8988923737ca8.jpg) \nFig. 6 | DFT calculations. a, Calculated reaction pathway of electrochemical reduction of ${\\mathsf{C O}}_{2}$ to ethanol on the supported Cu cluster catalyst at 0 and $-0.41\\vee$ applied voltage. An \\* denotes the catalytic site. Steps $12\\rightarrow13$ $(C H_{3}^{\\star}+H_{2}C O^{\\star}\\rightarrow C H_{3}C H_{2}O^{\\star})$ is a chemical reaction (that is, C–C bond formation), and is assumed not to be affected by external electrical potential. All the other elementary steps are electrochemical reaction steps, in which each step involves transfer of a $(\\mathsf{H}^{+}+\\mathsf{e}^{-})$ pair to the reaction site. The step with the highest reaction free energy $(0.41\\mathrm{eV})$ is found to $4\\rightarrow5$ $(\\mathsf{H C O O H^{\\star}+H C O O^{\\star}+}$ $\\mathsf{H}^{+}+\\mathsf{e}^{-}\\to\\mathsf{H C O O H}^{\\star}+\\mathsf{H C O O H}^{\\star})$ . Therefore, the calculated limiting potential is $-0.41\\mathsf{V},$ and the calculated overpotential is $-0.49\\vee$ (refer to specific computational details in the Supplementary Methods). b, Calculated structures of the catalyst and intermediate states. c, Reaction $12\\rightarrow13$ with a transition state. The free energy barrier for this step is calculated to be 0.83 eV. Cu, O, C and H atoms are in brown, red, grey and blue, respectively. \n\n# Methods \n\nMaterials. All the reagents were purchased from commercial sources, such as lithium metal $(99.97\\%$ Sigma-Aldrich), ${\\mathrm{KHCO}}_{3}$ ( $99.7\\%$ Sigma-Aldrich and Nafion solution ${\\sim}5\\%$ in a mixture of lower aliphatic alcohols and water, Sigma-Aldrich). All the solvents used were purified using a standard procedure. \n\nCatalysts were synthesized in an Ar-filled glovebox, (oxygen level ${<}0.3\\mathrm{ppm}$ ) similar to previously reported methods31. For $\\mathrm{Cu/C{-}0.4}$ sample, for example, $0.258\\mathrm{mol}$ of lithium $(99.9\\%$ Sigma-Aldrich) was added into a nickel crucible and heated to $320^{\\circ}\\mathrm{C}$ to form molten lithium with a mirror surface. Then, $0.312\\mathrm{mmol}$ $\\mathrm{({\\sim}20m g)}$ of Cu wires $(99.9\\%$ Alfa-Aesar) were added into the molten lithium. A tip ultrasonic homogenizer was used to ensure a homogeneous dispersion of the bulk Cu wires into SAs and prevent them from precipitation and reaggregation in molten Li while the molten lithium was maintained at $320^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ . The melted metal was then quickly poured onto a clean 316-stainless steel plate to quench the solid solution to avoid metal segregation. After cooling, the Cu–Li solid solution was taken from the glovebox and was placed in an ambient environment, before being cut into small pieces. The lithium was then slowly converted to LiOH under humidified air at ambient temperature. The $\\mathrm{Cu}\\mathrm{SA}$ embedded LiOH powder was uniformly mixed with $4.84\\mathrm{g}$ carbon black support (Vulcan XC-72) by grinding with an agate mortar and pestle. The resulting mixture was filtered with copious amounts of de-ionized water to leach off LiOH. Finally, the remaining solid was separated and dried in a vacuum at $60^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ , forming the catalyst with $0.4\\mathrm{wt\\%}$ Cu over carbon black $\\mathrm{\\Cu/C-0.4)}$ . Catalysts of different Cu mass loadings, $0.1\\mathrm{wt\\%}$ $\\mathrm{(Cu/C-0.1)}$ ), $0.8\\mathrm{wt\\%}$ $\\mathrm{\\Cu/C{-}0.8)}$ , $1.6\\mathrm{wt\\%}$ $\\mathrm{\\Cu}/\\mathrm{C}{-}1.6)$ and $6\\mathrm{wt\\%}$ $\\mathrm{\\langleCu/C{-}\\it6\\rangle}$ , were prepared using the same procedure. \n\nCharacterization. Powder XRD measurement was carried out on a Rigaku Miniflex diffractometer with $\\operatorname{Cu}\\ K\\upalpha$ radiation $(\\lambda=1.5406\\mathrm{\\AA}$ ). Samples were prepared by placing them on a silicon zero diffraction plate with amorphous carbon-based grease. SAs and clusters were visualized using HAADF–STEM at the University of Illinois, Chicago, which is a probe-corrected JEOL JEMARM200CF equipped with a $200\\mathrm{-kV}$ cold-field emission gun. This STEM is also equipped with an EDX spectroscopy analyser (Oxford EDX XMAX80 system). The samples were prepared by using ultra-thin carbon film covered gold transmission electron microscopy grids (TED PELLA, Inc.) to collect the samples dispersed in ethanol under sonication. The gold grids were then dried at $60^{\\circ}\\mathrm{C}$ . A JEOL 2100F transmission electron microscopy operated at $200\\mathrm{kV}$ was also used to prescreen the samples to check whether any NPs were present. XAS involving operando XANES and EXAFS were performed at both 12- and 20-BM (beamlines) of the Advanced Photon Source (APS) at the Argonne National Laboratory to investigate the local environment around the Cu atoms of $\\mathrm{{Cu/C\\mathrm{{-}\\mathrm{{X}}}}}$ samples. The XANES spectroscopy was performed in fluorescence mode due to the low loading of Cu on carbon at the $\\operatorname{Cu}k$ edge $(9,659\\mathrm{eV})$ . The Cu foil EXAFS was measured for energy calibration for each scan of the samples. For each sample, several scans were taken and averaged to gain a better signal-to-noise ratio. \n\nLCF. LCF was used as a standard analytic tool in XAS software Athena. The analysis was based on the principle that the XANES spectrum of a mixture containing many components is composed by the linear superposition of the XANES spectra of the individual component32. The LCF is calculated using normalized $\\upmu(E)$ spectra of the compounds in the mixture at narrow energy range around the absorption edge. Our analysis was conducted in an energy range of $-20\\mathrm{eV}$ below to $+20\\mathrm{eV}$ above the copper $k$ edge. LCF reconstructs the sample spectrum using a combination of normalized model spectra of CuO, $\\operatorname{Cu}(\\mathrm{AcAc})_{2}$ and Cu foil, since both cupric oxide and copper metal clusters were found by XRD and EXAFS in the higher Cu loading samples. It is worth noting that there is no standard XANES for $\\operatorname{Cu}\\operatorname{SA}$ . We selected $\\operatorname{Cu}(\\operatorname{AcAc})_{2}$ since it contains the single $\\mathrm{Cu}^{+2}$ ligated by four oxygens from two acetylacetonates. The hydrocarbons in $\\operatorname{Cu}(\\operatorname{AcAc})_{2}$ interfere little with the electronic structure of $\\mathrm{{Cu},}$ therefore this serves as a good reference. Our EXAFS analysis on $\\mathrm{{Cu/C/-0.1}}$ , the sample with the lowest copper loading and highest dispersion, found that Cu is almost all coordinated by roughly four oxygens. We therefore also applied $\\mathrm{{Cu}/\\mathrm{{C}-0.1}}$ in the place of $\\operatorname{Cu}(\\operatorname{AcAc})_{2}$ as the SA reference for LCF analysis assuming that the copper in this sample was completely atomically dispersed. LCF plots in both methods are provided in Supplementary Fig. 7. The weight fraction of Cu in each phase and the quality of the fitting (R factor and reduced $\\chi^{2}$ ) are provided in Supplementary Tables 4 and 5, respectively. Both models provided similar accuracy of fit, demonstrated by similar $R$ factors and reduced $\\chi^{2}$ . The weight fraction of Cu in each component, although different in absolute value as expected, is generally consistent between the two models. We selected the model using $\\mathrm{Cu}(\\mathrm{AcAc})_{2}$ , CuO and Cu foil for quantitative calculations for the electrocatalytic property due to the concern that $\\mathrm{CuO}$ was found in $\\mathrm{Cu/C{-}0.4}$ , even at very low levels, by analysing the XRD result. \n\nOperando XAS characterization of Cu SA catalyst. To investigate the electronic configuration and coordination structure of the $\\operatorname{Cu}\\operatorname{SA}$ catalysts under operating conditions, operando XAS measurements were performed over a custom-made electrochemical cell containing a catalyst-coated graphene sheet as the working electrode, an $\\mathrm{\\Ag/AgCl}$ reference electrode and a platinum wire counter electrode. The electrochemical cell contained $0.1\\mathrm{{MKHCO}_{3}}$ solution as the electrolyte, constantly purged by a flowing $\\mathrm{CO}_{2}$ . All XAS data were collected at the $\\operatorname{Cu}k$ edge in fluorescence mode. The $\\mathrm{{Cu}/\\mathrm{{C}}\\mathrm{{-}}0.4}$ catalyst was used as the representative sample. Cu foil and CuO were used as the references. To better understand the oxidation state and coordination structural changes in the $\\mathrm{Cu}\\mathrm{SA}$ samples, we also conducted X-ray absorption spectroscopy (XAS) studies on the $\\mathrm{{Cu/C{-}0.4}}$ sample before (pre $\\mathrm{Cu/C)}$ and after (post $\\mathrm{Cu/C}_{\\mathrm{,}}$ the chronoamperometric measurement under $-0.7\\mathrm{V}$ versus RHE for 16 h. \n\nElectrochemical measurements. All electrochemical measurements were carried out at ambient temperature and pressure in an electrochemical cell using a RDE with $5\\mathrm{mm}$ diameter as the working electrode (PINE Instrument) operated by a CHI760E potentiostat. The counter electrode was a gold wire separated by a glass tube with felt and the reference electrode was an $\\mathrm{Ag/AgCl}$ (3 M KCl, Sigma). The reference electrode was calibrated against a RHE (HydroFlex, Gaskatel). Before the measurement, the $0.1\\mathrm{{MKHCO}_{3}}$ aqueous electrolyte was saturated by $\\mathrm{CO}_{2}$ $(99.999\\%^{\\cdot}$ through purging for 1 h at $\\mathrm{pH}6.8$ , and a flow of $\\mathrm{CO}_{2}$ was maintained throughout the entire electrochemical measurement. All potentials measured were calculated with respect to the RHE scale in V (versus ${\\mathrm{RHE}})=\\mathrm{V}$ (versus $\\mathrm{Ag/}$ AgC $\\mathrm{1,3MKCl)+0.210V+0.0591\\timespH}$ A small portion of the electrolyte was extracted from the cell after 4,000-s run at the designated cell potential and soluble $\\mathrm{CO}_{2}$ conversion products were analysed by NMR. The gas-phase products were collected in a multilayer gas sampling bag and analysed by gas chromatography. LSV and cyclic voltammetry at a scan rate of $50\\mathrm{mVs^{-1}}$ were performed before and after chronoamperometry tests at different potentials. The current density was calculated on the basis of the total current divided by the geometric area of $\\mathrm{RDE}^{33}$ . EDLCs of $\\mathrm{Cu/C\\mathrm{-}{\\bf X}}$ were measured before and after electrolysis according to the following procedure: cyclic voltammetry curves were first taken between $-0.3$ and $-0.4\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ (3 M KCl) at various scan rates $\\mathbf{\\Psi}(\\mathrm{mV}\\mathbf{s}^{-1})$ while keeping the solution still. The currents were then extracted at $-0.35\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ (3 M KCl) as a function of the scan rate, leading to a slope for each sample before and after electrolysis. The slope of the plot equals capacitance of measured the samples. \n\nFE calculation. On the basis of the definition of $\\mathrm{FE^{11}}$ : \n\n$$\n\\mathrm{FE}_{i}=\\frac{Q_{i}}{Q_{\\mathrm{total}}}\n$$ \n\nwhere $i$ represents different products such as $\\mathrm{H}_{2},$ $\\mathrm{CO,CH_{4},H C O O H}$ and ethanol. $Q_{i}$ and $Q_{\\mathrm{total}}$ are the number of charges transferred to the product and the total number of charges passed into the solution, respectively. For gas-chromatography analysis data and ideal gas law, the partial current density of each product was calculated as follows34: \n\n$$\nJ={\\frac{\\mathrm{Peak}\\arctan\\alpha\\times\\mathrm{flow}\\mathrm{rate}}{\\times}}{\\frac{n F P^{0}}{R T}}\\times{\\frac{1}{\\mathrm{electrodearea}}}\n$$ \n\nwhere $\\alpha$ is a conversion factor based on calibration of the gas-chromatography equipment with standard sample, $P^{0}=1.01\\times10^{5}\\mathrm{Pa}$ , $R$ is the gas constant, $F$ is Faraday’s constant and $\\begin{array}{r}{T{=}273.15\\mathrm{K}}\\end{array}$ , $n$ is the number of electrons required for the gas products of CO, $\\mathrm{CH}_{4}$ and $\\mathrm{H}_{2}$ . Two electrons were required for the CO and $\\mathrm{H}_{2,\\cdot}$ and eight electrons were required for $\\mathrm{CH}_{4}$ . \n\nFE for formation of gas products, such as $\\mathrm{CH}_{4},\\mathrm{H}_{2},$ , CO, was calculated as follows11: \n\n$$\n\\mathrm{FE}=\\frac{n F V\\nu P^{0}}{R T i}\\times100\\%\n$$ \n\nwhere $n$ is the number of electrons required for products, $V\\left(\\mathrm{vol\\%}\\right)$ is the volume concentration of gas in the gas bag from the electrochemical cell, $\\nu$ $(\\mathrm{ml}\\mathrm{min}^{-1}$ \n\nat room temperature and ambient pressure) is the gas flow rate, $i$ (mA) is the steady-state cell current, $P{=}1.01{\\times}10^{5}\\mathrm{Pa}$ , $T=273.15\\mathrm{K}$ , $F{=}96{,}485\\mathrm{Cmol^{-1}}$ and $R{=}8.314\\mathrm{Jmol^{-1}K^{-1}}$ . \n\nOn the basis of the $^{1}\\mathrm{H}$ nuclear magnetic resonance analysis, the peaks were quantified by integrating the area below it. The relative peak area can be calculated as follows:11 \n\n$$\n{\\mathrm{Relative~peak~area~ratio~(ethanol)}}={\\frac{\\mathrm{Triplet~peak~areat1.09~ppm~(ethanol)}}{\\mathrm{Singlet~peak~areat2.6~ppm~(DMSO)}}}\n$$ \n\nThe FE for formation of liquid products, such as ethanol, acetone and formic acid, was calculated as follows: \n\n$$\n\\mathrm{FE}=\\frac{\\alpha n F}{Q}\\times100\\%\n$$ \n\nwhere $\\alpha$ is the number of electrons required for each product, $n$ is the number of products (mol), $F$ is the Faradaic constant and $Q$ is the total charge passed during the overall run. \n\nChronoamperometry measurements. FE and current density of $\\mathrm{CO}_{2}\\mathrm{RR}$ electrolysis under the constant potential were studied to verify the catalyst stability. Measurements were taken between $-0.4$ and $-1.2\\mathrm{V}$ to ensure a full range analysis at $1{,}600\\mathrm{r.p.m}$ . under a continuous flow of $\\mathrm{CO}_{2}$ at 30 standard cubic centimetres per minute (sccm) for ${4,000s}$ . For durability analysis of the $\\mathrm{CO}_{2}\\mathrm{RR}$ process, the electrolyte was taken out of the electrochemical cell every 2 h to quantify the product by NMR measurement. \n\nGas-chromatography analysis. The gas-phase products were collected in a multilayer gas sampling bag and identified by gas chromatography $\\left({\\mathrm{HP~}}6890\\right.$ Series gas-chromatography system). The gas-chromatography system was equipped with a packed HeysepD column. Argon (Praxair $99.999\\%$ ) was used as the carrier gas and was calibrated with $\\operatorname{H}_{2},$ $\\mathrm{CH}_{4};$ $\\mathrm{C_{2}H_{4}}$ and CO. During constant potential electrolysis, effluent gas from the working compartment was collected at $30\\mathrm{-min}$ intervals and injected into the sampling loop of the gas-chromatography system. The separated gas products were analysed by a flame ionization detector with a methanizer (for CO, methane and other possible hydrocarbon gas concentrations) and a thermal conductivity detector (for $\\mathrm{H}_{2}$ concentration). The calibration curves were constructed from certified gas standards by $\\mathrm{CO}_{2}$ dilution using mass flow controllers. The products were quantified by the conversion factor derived from the standard calibration gases and was calculated on the basis of its average peak area. \n\n${}^{1}\\mathbf{H}$ Nuclear magnetic resonance analysis. NMR spectroscopy was used to quantify the yield of liquid products, such as ethanol, acetic acid, acetone and other compounds produced during constant potential electrolysis (4,000 s). Liquid products were recorded on a Bruker Avance III NMR spectrometer operating at $11.7\\mathrm{T}$ $(500\\mathrm{MHz^{1}H})_{,}^{\\cdot}$ ) using dimethyl sulfoxide (DMSO, $99.9\\%$ ) as an internal standard. To avoid problems arising from the analyte having different T1 values, the same spectral acquisition parameters were used for all spectra to ensure complete relaxation and quantification. The acquisition parameters were: time domain data size (TD), 65536; number of dummy scans (DS), 2; number of scans (NS), 16; loop count time domain (TD0), 1; spectral width (SW), $19.9899\\mathrm{ppm};$ spectral width in Hertz (SWH), $10,000\\mathrm{Hz};$ filter width (FW), $125,000\\mathrm{Hz}$ ; pause width (pw), 45o; delay 1 (d1), 5 s and delay 2 (d2), 0 s. For sample preparation for NMR measurement, a $700\\mathrm{-}\\upmu\\mathrm{l}$ electrolyte sample was mixed with $35\\upmu\\mathrm{l}$ of internal standard solution. The internal standard solution was prepared by mixing $14\\mathrm{ml}$ of ${\\bf D}_{2}\\mathrm{O}$ with $10.0\\upmu\\mathrm{l}$ of DMSO, equivalent to $10\\mathrm{mM}$ of DMSO in $\\mathrm{D}_{2}\\mathrm{O}$ Standard curves for each product were prepared by the relative peak area ratio. \n\nComputational methods. DFT calculations were performed to study the active site structure of the Cu catalyst and the reaction mechanism of the electrocatalytic $\\mathrm{CO}_{2}$ reduction. The reaction free energy of each elementary electrochemical step was calculated using the computational hydrogen electrode method proposed by Norskov et al.30,35,36. The calculations of all the structures and total energies were carried out using the PBE functional37 with a plane-wave basis set implemented in the Vienna Ab initio Simulation Package $(\\mathrm{v}.5.3.3)^{37-40}$ . An energy cutoff of $400\\mathrm{eV}$ was used, and the Γ-point and a $3\\times3\\times1$ k-point mesh were used to sample the Brillouin zones for the molecules and graphene supported systems, respectively. For the reduced graphene oxide model (Supplementary Fig. 23a), a unit cell with 72 carbon atoms was constructed and a 15-Å vacuum space above the surface was created to separate the surface slab and its periodic image. All molecules were placed in a $2\\mathrm{{0}}\\times20\\times20\\mathrm{{\\AA}}^{3}$ box. The Gibbs free energy corrections were calculated in the gas phase at $25^{\\circ}\\mathrm{C}$ using the standard statistical mechanical model used by the Gaussian09 program package13. The solvation effect at the water-solid interface was taken into account by adding an energy correction to the calculated total energy of certain adsorbates30. Detailed computational models and methodologies are provided in the Supplementary Methods. \n\nAs described in the experimental section, the formation of the single-site Cu catalyst results from a sequence of reactions: the dissociation of bulk Cu to Li-solvated Cu atoms and the conversion of a single Cu to $\\mathrm{Cu(OH)}_{2}$ under a humidified air and alkaline solution at ambient temperature. Explicitly, the interaction between LiOH and carbon leads to hydroxyl-decorated graphene structures (Supplementary Fig. 23a). The interaction between $\\mathrm{Cu(OH)}_{2}$ and hydroxyl-decorated graphene results in the single-site Cu precatalyst (Supplementary Fig. 23b). Our calculations show that this reaction is energetically favourable (Supplementary Fig. 23b). The resulting precatalyst has a four-coordinate $\\mathrm{Cu^{+2}}$ site coordinated with two oxyl groups on graphene and two $\\mathrm{H}_{2}\\mathrm{O}$ ligands. The calculated precatalyst Cu site agrees well with the experimental XRD and ex situ XAS measurements, in which the coordination number of copper is 3.22 $\\left(\\pm0.66\\right)$ . \n\n# Data availability \n\nThe authors declare that all data are available in the main text, Supplementary Information and Source Data files. Data generated from DFT calculations can be found in Supplementary Data 1 and Supplementary Data 2. Source data are provided with this paper. \n\nReceived: 15 February 2019; Accepted: 2 July 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Goeppert, A., Czaun, M., Jones, J.-P., Surya Prakash, G. K. & Olah, G. A. $\\mathrm{CO}_{2}$ capture and recycling to chemicals, fuels and materials: enabling technologies. Chem. Soc. Rev. 43, 7995–8048 (2014). \n2.\t Zhou, Y. S. et al. Dopant-induced electron localization drives $\\mathrm{CO}_{2}$ reduction to $\\mathbf{C}_{2}$ hydrocarbons. Nat. Chem. 10, 974–980 (2018). \n3.\t Tilman, D., Hill, J. & Lehman, C. Carbon-negative biofuels from low-input high diversity grassland biomass. Science 314, 1598–1600 (2006). \n4.\t Lehmann, J. A handful of carbon. Nature 447, 143–144 (2007). \n5.\t Zheng, X. L. et al. Sulfur-modulated tin sites enable highly selective electrochemical reduction of $\\mathrm{CO}_{2}$ to formate. Joule 1, 794–805 (2017). \n6.\t Fang, Y. & Flake, J. Electrochemical reduction of $\\mathrm{CO}_{2}$ at functionalized Au electrodes. J. Am. Chem. Soc. 139, 3399–3405 (2017). \n7.\t Kuhl, K. P., Cave, E. R., Abram, D. N. & Jaramillo, T. F. New insights into the electrochemical reduction of carbon dioxide on metallic copper surfaces. Energy Environ. Sci. 5, 7050–7059 (2012). \n8.\t Kim, D., Kley, C. S., Li, Y. F. & Yang, P. D. Copper nanoparticle ensembles for selective electroreduction of $\\mathrm{CO}_{2}$ to $\\mathrm{C}_{2}\\mathrm{-C}_{3}$ products. Proc. Natl Acad. Sci. USA 114, 10560–10565 (2017). \n9.\t Kim, D., Resasco, J., Yu, Y., Asiri, A. & Yang, P. D. Synergistic geometric and electronic effects for electrochemical reduction of carbon dioxide using gold–copper bimetallic nanoparticles. Nat. Commun. 5, 4948 (2016). \n10.\tZheng, X. et al. Theory-guided $\\mathrm{{\\calSn/Cu}}$ alloying for efficient $\\mathrm{CO}_{2}$ electroreduction at low overpotentials. Nat. Catal. 1, 1–7 (2018). \n11.\tRen, D. et al. Selective electrochemical reduction of carbon dioxide to ethylene and ethanol on copper(I) oxide catalysts. ACS Catal. 5, 2814–2821 (2015). \n12.\tChen, Y. H. & Kanan, M. W. Tin oxide dependence of the $\\mathrm{CO}_{2}$ reduction efficiency on tin electrodes and enhanced activity for tin/tin oxide thin-film catalysts. J. Am. Chem. Soc. 134, 1986–1989 (2015). \n13.\tLin, S. et al. Covalent organic frameworks comprising cobalt porphyrins for catalytic $\\mathrm{CO}_{2}$ reduction in water. Science 349, 1208–1213 (2015). \n14.\tCrawley, M. R. et al. Rhenium phosphazane complexes for electrocatalytic $\\mathrm{CO}_{2}$ reduction. Organometallics 38, 1664–1676 (2019). \n15.\tLuna, P. D. et al. Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction. Nat. Catal. 1, 103–110 (2018). \n16.\tSong, Y. et al. High-selectivity electrochemical conversion of $\\mathrm{CO}_{2}$ to ethanol using a copper nanoparticle/N-doped graphene electrode. Chemistry Select. 1 6055–6061 (2016). \n17.\tXie, H., Wang, T. Y., Liang, J. S., Li, Q. & Sun, S. H. Cu-based nanocatalysts for electrochemical reduction of $\\mathrm{CO}_{2}$ . Nano Today 21, 41–54 (2018). \n18.\t Wang, Y. et al. $\\mathrm{CO}_{2}$ reduction to acetate in mixtures of ultrasmall $({\\mathrm{Cu}}){\\dot{n}},({\\mathrm{Ag}})m$ bimetallic nanoparticles. Proc. Natl Acad. Sci USA 115, 278–283 (2017). \n19.\tDuan, Y. X. et al. Amorphizing of Cu nanoparticles toward highly efficient and robust electrocatalyst for $\\mathrm{CO}_{2}$ reduction to liquid fuels with high Faradaic efficiencies. Adv. Mater. 30, 1706194 (2018). \n20.\tWeng, Z. et al. Active sites of copper-complex catalytic materials for electrochemical carbon dioxide reduction. Nat. Commun. 9, 415 (2018). \n21.\tYang, H. B. et al. Atomically dispersed Ni(i) as the active site for electrochemical $\\mathrm{CO}_{2}$ reduction. Nat. Energy 3, 140–147 (2018). \n22.\tDilan Karapinar et al. Electroreduction of $\\mathrm{CO}_{2}$ on single-site copper-nitrogen-doped carbon material: selective formation of ethanol and reversible restructuration of the metal sites. Angew. Chem. Int. Ed. 58, 2–8 (2019). \n23.\tWei, H. S. et al. FeOx-supported platinum single-atom and pseudo-single-atom catalysts for chemoselective hydrogenation of functionalized nitroarenes. Nat. Commun. 5, 5634 (2017). \n24.\tHouse, J. E. Inorganic Chemistry (Elsevier Inc., 2013). \n25.\tJiang, K. et al. Isolated Ni single atoms in graphene nanosheets for high-performance $\\mathrm{CO}_{2}$ reduction. Energy Environ. Sci. 11, 893–903 (2018). \n26.\tMalta, G. et al. Identification of single-site gold catalysis in acetylene hydrochlorination. Science 355, 1399–1403 (2017). \n27.\tWu, J. Achieving highly efficient, selective, and stable $\\mathrm{CO}_{2}$ reduction on nitrogen-doped carbon nanotubes. ACS Nano. 9, 5364–5371 (2015). \n28.\tXie, M. S. et al. Amino acid modified copper electrodes for the enhanced selective electroreduction of carbon dioxide towards hydrocarbons. Energy Environ. Sci. 9, 1687–1695 (2016). \n29.\tGuvelioglu, G. H., Ma, P. P. & He, X. Y. First principles studies on the growth of small Cu clusters and the dissociative chemisorption of $\\mathrm{H}_{2}$ . Phys. Rev. B. 73, 155436–155446 (2006). \n30.\tPeterson, A. A., Abild-Pedersen, F., Studt, Felix, Rossmeisl, J. & Jens Nørskov, K. How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels. Energy Environ. Sci. 3, 1311–1315 (2010). \n31.\tXu, T. et al. Synthesis of supported platinum nanoparticles from Li-Pt solid solution. J. Am. Chem. Soc. 132, 2151–2153 (2010). \n32.\tDatta, S. et al. Use of X-Ray absorption spectroscopy (XAS) to speciate manganese in airborne particulate matter from 5 counties across the US. Environ. Sci. Technol. 46, 3101–3109 (2012). \n33.\t Li, S. J., Han, K. H., Si, P. C., Li, J. X. & Lu, C. M. High–performance activated carbons prepared by KOH activation of gulfweed for supercapacitors. Int. J. Electrochem. Sci. 13, 1728–1743 (2018). \n34.\tHuang, Y., Handoko, A. D., Hirunsit, P. & Yeo, B. S. Electrochemical reduction of $\\mathrm{CO}_{2}$ using copper single-crystal surfaces: effects of $\\scriptstyle\\mathrm{CO^{*}}$ coverage on the selective formation of ethylene. ACS Catal. 7, 1749–1756 (2017). \n35.\tPeterson, A. A. & Nørskov, J. K. Activity descriptors for $\\mathrm{CO}_{2}$ electroreduction to methane on transition-metal catalysts. J. Phys. Chem. Lett. 3, 251–258 (2012). \n36.\tLiu, X. Y. et al. Understanding trends in electrochemical carbon dioxide reduction rates. Nat. Commun. 8, 15438 (2017). \n37.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n38.\tKresse, G. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993). \n39.\tKresse, G. Theory of the crystal structures of selenium and tellurium: the effect of generalized-gradient corrections to the local-density approximation. Phys. Rev. B 49, 14251–14269 (1994). \n40.\tKresse, G. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n\n# Acknowledgements \n\nThis material is based on work supported by Laboratory Directed Research and Development funding from Argonne National Laboratory, provided by the Director, Office of Science, of the US Department of Energy (DOE) under contract no. DE-AC02- 06CH11357. The works performed at Argonne National Laboratory’s Center for Nanoscale Materials and APS, US DOE Office of Science User Facilities, are supported by Office of Science, US DOE under contract no. DE-AC02-06CH11357. Part of the DFT calculations were also performed using the computational resources provided by the Laboratory Computing Resource Center at the Argonne National Laboratory. T.X. acknowledges the financial support from the XSD visiting scientist program at APS at Argonne. C.L.’s work is supported by the US DOE, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences, under contract no. DE-AC02-06CH11357 (Argonne National Laboratory). The views and opinions of the authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof; neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, nor usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. We also acknowledge I. Hwang for verification of our EXAFS simulation by Artemis. \n\n# Author contributions \n\nD.-J.L. and T.X. designed and supervised the experiment with assistance from C.L. and T.L. C.L. led and H.H. assisted the computational investigations. T.L. led and H.X., L.C., Y.L., C.S., J.V.M. and R.E.W. assisted the characterization of catalysts structure and catalysis products. H.X. and D.R. synthesized catalysts, conducted electrochemical study and data analysis. H.X., H.H., C.L., D.-J.L. and T.X. wrote the manuscript. \n\n# Competing interests \n\nAn US patent application (US 2019/0276943 A1) on amalgamated metal—Li catalyst synthesis for $\\mathrm{CO}_{2}$ conversion with D.-J. Liu, T. Xu, H. Xu and D. Rebollar as the \n\ncoinventors was filed by UCHICAGO ARGONNE, LLC. The authors declare no other competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-020-0666-x. \n\nCorrespondence and requests for materials should be addressed to C.L., T.L., D.-J.L. \nor T.X. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 " + }, + { + "id": "10.1021_acsnullo.9b07708", + "DOI": "10.1021/acsnullo.9b07708", + "DOI Link": "http://dx.doi.org/10.1021/acsnullo.9b07708", + "Relative Dir Path": "mds/10.1021_acsnullo.9b07708", + "Article Title": "Synthesis of Mo4VAlC4 MAX Phase and Two-Dimensional Mo4VC4 MXene with Five Atomic Layers of Transition Metals", + "Authors": "Deysher, G; Shuck, CE; Hantanasirisakul, K; Frey, NC; Foucher, AC; Maleski, K; Sarycheva, A; Shenoy, VB; Stach, EA; Anasori, B; Gogotsi, Y", + "Source Title": "ACS nullO", + "Abstract": "MXenes are a family of two-dimensional (2D) transition metal carbides, nitrides, and carbonitrides with a general formula of Mn+1XnTx, in which two, three, or four atomic layers of a transition metal (M: Ti, Nb, V, Cr, Mo, Ta, etc.) are interleaved with layers of C and/or N (shown as X), and T-x represents surface termination groups such as -OH, =O, and -F. Here, we report the scalable synthesis and characterization of a MXene with five atomic layers of transition metals (Mo4VC4Tx), by synthesizing its Mo4VAlC4 MAX phase precursor that contains no other MAX phase impurities. These phases display twinning at their central M layers which is not present in any other known MAX phases or MXenes. Transmission electron microscopy and X-ray diffraction were used to examine the structure of both phases. Energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and high- resolution scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy were used to study the composition of these materials. Density functional theory calculations indicate that other five transition metal-layer MAX phases (M'M-4 '' AlC4) may be possible, where M' and M '' are two different transition metals. The predicted existence of additional Al-containing MAX phases suggests that more M5C4Tx MXenes can be synthesized. Additionally, we characterized the optical, electronic, and thermal properties of Mo4VC4Tx. This study demonstrates the existence of an additional subfamily of M5X4Tx MXenes as well as a twinned structure, allowing for a wider range of 2D structures and compositions for more control over properties, which could lead to many different applications.", + "Times Cited, WoS Core": 506, + "Times Cited, All Databases": 532, + "Publication Year": 2020, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000510531500015", + "Markdown": "# Synthesis of Mo VAlC MAX Phase and TwoDimensional Mo4VC4 MXene with Five Atomic Layers of Transition Metals \n\nGrayson Deysher,† Christopher Eugene Shuck, $\\dagger\\textcircled{\\pm}$ Kanit Hantanasirisakul, $\\dagger\\textcircled{\\circ}$ Nathan C. Frey,‡ Alexandre C. Foucher, $\\sharp\\oplus$ Kathleen Maleski, $\\dag\\textcircled{\\pmb{\\phi}}$ Asia Sarycheva,† Vivek B. Shenoy,‡ Eric A. Stach,‡ Babak Anasori, $\\ast,\\dag,\\S_{\\ensuremath{\\mathbb{P}}}$ and Yury Gogotsi\\*,† \n†Department of Materials Science and Engineering, and A.J. Drexel Nanomaterials Institute, Drexel University, Philadelphia, Pennsylvania 19104, United States \n‡Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States §Department of Mechanical and Energy Engineering, and Integrated Nanosystems Development Institute, Purdue School of Engineering and Technology, Indiana University−Purdue University Indianapolis, Indianapolis, Indiana 46202, United States \n\n\\*S Supporting Information \n\nABSTRACT: MXenes are a family of two-dimensional (2D) transition metal carbides, nitrides, and carbonitrides with a general formula of $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x},$ in which two, three, or four atomic layers of a transition metal (M: Ti, Nb, V, Cr, Mo, Ta, etc.) are interleaved with layers of C and/or N (shown as $\\mathbf{X}$ ), and $\\mathbf{T}_{x}$ represents surface termination groups such as $-\\mathbf{O}\\mathbf{H},\\mathbf{\\Lambda}=\\mathbf{O}$ , and $-\\mathbf{F}$ . Here, we report the scalable synthesis and characterization of a MXene with five atomic layers of transition metals $\\left(\\mathbf{Mo_{4}}\\mathbf{VC_{4}}\\mathbf{T}_{x}\\right)$ , by synthesizing its $\\mathbf{Mo_{4}V A l C}_{4}$ MAX phase precursor that contains no other MAX phase impurities. These phases display twinning at their central M layers which is not present in any other known MAX phases or MXenes. Transmission electron microscopy and $\\mathbf{X}$ -ray diffraction were used to examine the structure of both phases. Energy-dispersive $\\mathbf{X}$ -ray spectroscopy, $\\mathbf{X}$ -ray photoelectron spectroscopy, Raman spectroscopy, and highresolution scanning transmission electron microscopy with energy-dispersive $\\mathbf{X}$ -ray spectroscopy were used to study the composition of these materials. Density functional theory calculations indicate that other five transition metal-layer MAX phases $\\left(\\mathbf{M}^{\\prime}_{4}\\mathbf{M}^{\\prime\\prime}\\mathbf{AlC}_{4}\\right)$ may be possible, where $\\mathbf{M}^{\\prime}$ and $\\mathbf{M}^{\\prime\\prime}$ are two different transition metals. The predicted existence of additional Al-containing MAX phases suggests that more $\\mathbf{M}_{5}\\mathbf{C}_{4}\\mathbf{T}_{x}$ MXenes can be synthesized. Additionally, we characterized the optical, electronic, and thermal properties of $\\mathbf{Mo}_{4}\\mathbf{VC}_{4}\\mathbf{T}_{x},$ . This study demonstrates the existence of an additional subfamily of ${\\bf M}_{5}{\\bf X}_{4}{\\bf T}_{x}$ MXenes as well as a twinned structure, allowing for a wider range of 2D structures and compositions for more control over properties, which could lead to many different applications. \n\n![](images/46c7a9565309d447a94c5a525d3b204422deae77b8edc9a9e7fe04d2de639c51.jpg) \n\nKEYWORDS: MXene, two-dimensional, MAX phase, synthesis, structure, properties \n\nT wo-dimensional (2D) materials such as graphene, hexagonal boron nitride, and transition metal dichalcogenides have gained significant attention due to their interesting electronic,1 photonic,2 electrochemical,3 and optical4 properties. The 2D nature of these materials allows for different applications compared to their bulk counterparts, including applications such as transitors,1 solar cells, touch screens,2 biosensors,3 and lasers.4 In 2011, MXenes were introduced as a family of 2D materials.5 MXenes are 2D transition metal carbides and nitrides that have the formula unit $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x}$ where M stands for an early transition metal (Ti, Nb, V, Cr, Mo, Ta, etc.), X stands for carbon and/or nitrogen, $\\mathrm{T}_{x}$ represents surface terminations such as $-\\mathrm{OH},=$ O, and ${\\mathrm{-F}},$ , and $n$ is an integer from 1 to 3.6 Here, the common notation $\\mathbf{M}_{n+1}\\mathbf{X}_{n}$ will be used and we do not show the $\\mathrm{T}_{x}$ for brevity. Within the $\\mathbf{M}_{2}\\mathbf{X},$ $\\mathbf{M}_{3}\\mathbf{X}_{2},$ and $\\mathbf{M}_{4}\\mathbf{X}_{3}$ MXene structures that have been previously reported, there are several compositional possibilities including monometal MXenes, ordered double metal MXenes with in-plane and out-of-plane ordering $\\big(\\big(\\mathbf{M}^{\\prime}\\mathbf{M}^{\\prime\\prime}\\big)_{n+1}\\mathbf{X}_{n}\\big),^{6}$ divacancy MXenes with the formula unit $\\mathrm{M}_{1.33}\\mathrm{X},^{7}$ and solid-solution MXenes containing a mixture of multiple metals in the M sites.8 \n\nMXenes have become increasingly studied due to their exceptional properties such as high volumetric capacitance, antibacterial properties,10 electrochromic behavior,11 ,12 high electronic conductivity,13 and optical transparency.14 These properties are beneficial for numerous applications including energy storage,6,15 catalysis,16,17 antennas and RFID tags,1 electromagnetic interference (EMI) shielding,19,20 sensors,21 and plasmonic metamaterials.22 Furthermore, it has been shown that the MXene composition and structure play a vital role in the observed propertie s.23−28 A list of MXenes that have been experimentally synthesized and reported in the literature, including the one reported here, is shown in Figure 1. \n\n![](images/c0679a4db978c606c3bbc32a946bb1b5d63e0d77b31ae1b48601b89d14a9074b.jpg) \nFigure 1. MXenes reported to date. Twelve $\\mathbf{M}_{2}\\mathbf{X}$ MXenes $\\mathbf{\\gamma}(n=1)$ ,7,15,29−36 nin $\\mathrm{~e~M}_{3}\\mathrm{X}_{2}\\left(n=2\\right),{}^{5,33,37-41}$ and eight $\\mathbf{M}_{4}\\mathbf{X}_{3}\\mathbf{\\Gamma}\\big(n=3\\big)^{8,33,37,40,42-44}$ have been synthesized. The MXene reported here is marked by an asterisk $(^{*})$ . There are also many other MXene compositions that have been theoretically explored $^{40,45,46}$ and a variety of solid-solutions that have been produced. \n\n![](images/aaadf9022714ed6d22f1d8b6d14fd150eeb0320aa2aadcd1a20be30b02410585.jpg) \nFigure 2. XRD patterns of $\\mathbf{Mo_{4}V A l C_{4}}$ MAX phase powder, $\\mathbf{Mo_{4}V C_{4}}$ multilayer MXene powder, and free-standing film of delaminated $\\bf{M o}_{4}V C_{4}$ MXene. Insets on the top of each XRD pattern show optical images of the corresponding powders/film. The scale bars on the optical images are $\\textbf{1c m}$ . Top right inset shows a closeup view of the (002) peak shift indicating exfoliation and delamination. The c-LP values are provided for all three XRD patterns at the top of the (002) peaks in the inset. \n\nMXenes are produced by the selective chemical etching of specific atomic planes from layered carbide/nitride precursors. Most commonly, $\\mathbf{M}_{n+1}\\mathbf{AX}_{n}$ (MAX) phases are the precursor materials and MXenes are produced by selectively etching the A layers, where A represents Al or Si.6,47 The resulting MXene structure is dependent on its MAX phase precursor, which has limited the MXene family to materials with 2, 3, or 4 atomic layers of transition metal(s). Here, we introduce a MXene with five atomic layers of transition metals $\\left(\\mathbf{M}_{5}\\mathbf{X}_{4}\\right)$ by synthesizing its precursor MAX phase with five atomic layers of transition metals. \n\nTrace impurities of higher order MAX phases $\\left(n>3\\right)$ have previously been observed including $\\mathrm{Ta}_{6}{\\mathrm{Al}}{{\\dot{\\mathrm{C}}}_{5}},^{48}$ and $\\mathrm{Ti}_{7}\\mathrm{SnC}_{6}$ 49 however, both have only existed as a secondary component in a mixture with $\\mathbf{M}_{2}\\mathbf{A}\\mathbf{X}$ or as intergrown layers in other MAX phases. Similarly to the MAX phase reported here, $(\\mathrm{TiNb})_{5}\\mathrm{AlC}_{4}^{50}$ has been synthesized as a $\\mathrm{{\\bfM}}_{\\mathrm{{s}}}\\mathrm{{AlC}}_{4}$ phase; however, its impurities include $\\mathbf{M}_{2}\\mathrm{AlC}$ and $\\mathrm{{\\bfM}}_{4}\\mathrm{{AlC}}_{3}$ MAX phases. The presence of other MAX phases as impurities makes synthesizing a phase pure MXene almost impossible. In general, the presence of different MAX phases $({\\bf M}_{2}{\\bf A C},$ and $\\mathrm{{\\bfM}}_{4}\\mathrm{{AC}}_{3,}\\cdot\\mathrm{{\\bf\\Lambda}}$ ) as impurities results in a mixture of MXene (for example, $\\mathbf{M}_{2}\\mathbf{C}$ and $\\mathbf{M}_{4}\\mathbf{C}_{3}$ in a $\\ensuremath{\\mathbf{M}}_{5}\\ensuremath{\\mathbf{C}}_{4}$ MXene). Furthermore, due to similar MXene densities and their 2D nature, separating the resulting mixed MXenes is challenging. Therefore, a $\\mathrm{M}_{5}\\mathrm{AX}_{4}$ MAX phase with no other MAX phase impurities is required to synthesize phase pure $\\mathrm{M}_{5}\\mathrm{X}_{4}$ MXene. \n\nHere we present $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase with no other MAX phase impurities, allowing for the synthesis of sufficiently phase pure $\\mathrm{Mo_{4}V C_{4}}$ MXene. We provide structural characterization by high-resolution scanning transmission electron microscopy (HR-STEM), X-ray diffraction (XRD), scanning electron microscopy (SEM), and atomic force microscopy (AFM). In addition, chemical characterization by energy-dispersive X-ray spectroscopy (EDS) and $\\mathrm{x}$ -ray photoelectron spectroscopy (XPS) is presented, with the optical, electrical, and thermal stability properties of $\\mathrm{Mo_{4}V C_{4}}$ determined with UV−vis-NIR spectrophotometry, temperature-dependent resistivity, and thermogravimetric analysis (TGA), respectively. Density functional theory (DFT) calculations were used to show the theoretical stabilities of other $\\mathrm{{\\bfM}}_{5}\\mathrm{{AX}_{4}}$ phases. The scalable synthesis of $\\mathrm{Mo_{4}V A l C_{4}}$ and the demonstration of $\\mathrm{Mo_{4}V C_{4}}$ MXene shows that there is an additional family of phases to be explored with the potential for many other $\\mathrm{{\\bfM}}_{5}\\mathrm{{X}}_{4}$ MXenes to be synthesized. Due to the increased number of atomic layers in their structure, MXenes with five atomic transition metal layers could potentially have exceptional mechanical properties allowing for stronger metal matrix composites, better EMI shielding capabilities,51 and higher electrical conductivity for electronic applications. \n\n![](images/69a88942f0437fada34285dd0daba516d464109f253f92c3a96a84ef9d060d08.jpg) \nFigure 3. Microscopic analysis of MAX and MXene. (A) SEM micrograph of $\\mathbf{Mo_{4}V A l C}_{4}$ MAX phase powder. (B) Atomic-resolution dark field STEM micrograph of $\\mathbf{Mo_{4}V A l C}_{4}$ MAX phase with inset SAED pattern of the [001] zone axis. The scale bar for the SAED pattern is 1 $\\mathring{\\mathbf{A}}^{-1}$ . (C) Dark field STEM micrograph of $\\mathbf{Mo_{4}V A l C_{4}}$ MAX phase. The solid circles on the right represent the atoms. (D) SEM micrograph of $\\mathbf{Mo_{4}V C_{4}}$ multilayer MXene powder. (E) Dark field STEM micrograph of $\\mathbf{Mo_{4}V C_{4}}$ multilayer MXene powder showing stacked 2D flakes with 5 layers of bright atoms $\\mathbf{\\Gamma}(\\mathbf{M_{0}}/\\mathbf{V}$ layers). (F) Dark field STEM micrograph of $\\mathbf{Mo_{4}V C_{4}}$ MXene showing a herringbone-type structure. An atomic schematic and mirror plane are shown by solid circles on the right and a dashed line, respectively. (G) SEM micrograph of a single $\\bf{M o}_{4}V C_{4}$ flake drop-cast onto a porous alumina substrate. $\\mathbf{\\Pi}(\\mathbf{H})$ AFM micrograph of $\\bf{M o}_{4}V C_{4}$ flakes. (I) Height profiles of the AFM scans shown in $\\mathbf{H}$ , showing an average thickness of $2.5\\ \\mathrm{nm}$ . \n\n# RESULTS AND DISCUSSION \n\nSynthesis and Structural Characterization. To identify the optimal chemistry for $\\mathrm{{\\bfM}}_{5}\\mathrm{{AlC}}_{4}$ synthesis, we mixed six sets of starting powder mixtures with $\\mathrm{Mo}_{x}{:}\\mathrm{V}_{5-x}$ ratios where $x=5$ , 4, 3, 2, 1, and 0. We performed X-ray powder diffraction measurements on the powder produced after the MAX synthesis process at $1650~^{\\circ}\\mathrm{C}$ and determined that only the sample with a Mo:V ratio of 4:1 produced a $\\mathrm{{\\bfM}}_{5}\\mathrm{{AlC}}_{4}$ phase, as shown in Supporting Figure 1. Then, a smaller interval was selected, where $x=3.50$ , 3.75, 4.00, 4.25, and 4.50. These studies indicate that the Mo:V ratio range for which a $\\mathrm{{\\bfM}}_{5}\\mathrm{{AlC}}_{4}$ phase is stable is very narrow. These results are further discussed in Supporting Information (Supporting Figure 2). In brief, the $\\mathrm{Mo}_{x}\\mathrm{V}_{\\mathrm{5-x}}\\mathrm{AlC}_{4}$ phase can be synthesized when the Mo:V ratio in the initial mixed powders is between 3.75:1.25 and 4.25:0.75. Supporting Figure 2 also shows an expansion in the a lattice parameter $\\left(a{\\mathrm{-}}\\mathrm{LP}\\right)$ with increasing Mo content, which indicates that different Mo:V ratios are possible in the $\\mathrm{(MoV)}_{5}\\mathrm{AlC}_{4}$ structure, most likely as a solid-solution of Mo and V on the M sites. For the remainder of the characterization and synthesis of MXene described subsequently, we used $\\mathrm{(MoV)}_{5}\\mathrm{AlC}_{4}$ synthesized by mixing precursor powders with a Mo:V ratio of 4:1. \n\nWe also used XRD to examine the crystal structure of both the $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase and $\\mathrm{Mo_{4}V C_{4}}$ MXene (Figure 2). $\\mathrm{Mo_{4}V A l C_{4}}$ has a structure similar to other MAX phases; however, several of the peaks in the XRD pattern do not exactly match with the characteristic peaks of a typical $P6_{3}/\\$ mmc MAX structure. The (002) peak occurs at $6.26^{\\circ}$ indicating a $\\mathbf{\\Psi}_{c}$ lattice parameter $\\left(c\\mathrm{-}\\mathrm{LP}\\right)$ of $28.22\\mathrm{~\\AA~},$ , which is similar to $(\\mathrm{TiNb})_{5}\\mathrm{AlC}_{4},$ as reported previously.50 This is among the largest $\\boldsymbol{\\mathscr{c}}$ -LP of the known MAX phases. For comparison, $\\mathrm{Ti}_{2}\\mathrm{AlC}$ , ${\\mathrm{Ti}}_{3}{\\mathrm{AlC}}_{2},$ and $\\mathrm{Ta}_{4}\\mathrm{AlC}_{3}$ have $\\boldsymbol{\\mathscr{c}}$ -LPs of 1 $3.6\\bar{1}0\\mathrm{~\\normalfont~\\AA~},\\L^{52}18.578\\mathrm{~\\normalfont~\\mathring{A}~},\\L^{53}$ and $23.708\\mathrm{~\\normalfont~\\AA,^{54}~}$ respectively. $\\mathrm{Mo_{4}V A l C_{4}}$ powder contains impurity phases of $\\mathbf{Mo}_{2}\\mathbf{C}$ , VC, $\\mathrm{Al}_{4}\\mathrm{C}_{3},$ and $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ . The $\\mathrm{{Al}}_{4}\\mathrm{{C}}_{3}$ is dissolved during the HClcleaning step (Supporting Figure 3). The presence of ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ is most likely due to the addition of ${\\mathrm{V}}_{2}{\\mathrm{O}}_{3}$ in the starting powder. As we describe in Supporting Information, although we do not fully understand the role of $0.05~\\mathrm{mol}$ of vanadium oxide in this MAX formation, its presence is required to form a $\\mathrm{{\\bfM}}_{5}\\mathrm{{AC}}_{4}$ phase with the conditions reported here. It is possible that the oxygen acts as a catalyst for this reaction by partially substituting for carbon on the lattice forming oxicarbide, which might stabilize the structure. Additionally, the extra heat produced during the thermal reduction of ${\\mathrm{V}}_{2}{\\mathrm{O}}_{3}$ by Al might push the sample into the $(\\mathrm{MoV})_{5}\\mathrm{AlC}_{4}$ region of this quaternary phase diagram. Without the addition of ${\\mathrm{V}}_{2}{\\mathrm{O}}_{3},$ the resulting powder was $\\mathrm{Mo}_{2}\\mathrm{C}$ and VC (Supporting Figure 4). \n\nTable 1. EDS Measurements of Mo:V:Al:C:F:O Atomic Ratios for the MAX Phase (3 Particles Measured), Multilayer MXene (6 Particles Measured), and Free-Standing Film of Delaminated MXene (5 Spots Measured)a \n\n\n
sample MoVAl CF0
Mo4VAIC43.89 ± 0.021.11 ± 0.020.29 ± 0.130.41 ± 0.080.15 ± 0.02
Mo4VC4 (multilayer)4.06 ± 0.070.94 ± 0.075.72 ± 0.460.54 ± 0.031.83 ± 0.07
Mo4VC4 (delaminated)4.04 ± 0.040.96 ± 0.04-1.80 ± 0.290.01 ± 0.010.47 ± 0.12
\n\naThe values shown are atomic percentage normalized so that $\\begin{array}{r}{\\left(\\mathrm{MoV}\\right)\\it{\\Psi}=\\it{5}}\\end{array}$ . Error is defined as 1 standard deviation. \n\nSimilar to other Al-containing MAX phases, we attempted to selectively etch the Al layers with hydrofluoric acid (HF). During the first centrifugation wash cycle after the HF selective etching, the supernatant had a slight green tint (Supporting Figure 5). This is likely due to the dissolution of V from the MAX/MXene since any $\\mathrm{v}$ -containing impurities remaining after the HCl treatment, such as V-based carbides, would not be dissolved by HF. The process of optimizing the synthesis method is described in Supporting Information (Supporting Figures $6{-}7\\cdot$ ). After selective etching and the removal of the Al layers from the MAX structure, the resulting multilayer MXene (002) peak shifts to a lower $2\\theta_{,}$ , which is due to the increased $\\scriptstyle{c}\\cdot$ - LP $\\left(3\\bar{6}.0\\mathring{\\mathrm{A}}\\right)$ compared to the MAX precursor $(28.2\\mathring{\\mathrm{A}})$ . This is comparable to other reported increases in $\\boldsymbol{c}$ -LP after etching.37,44 After delamination of the resulting powder with tetramethylammonium hydroxide (TMAOH), a colloid with a concentration of ${\\sim}0.25~\\mathrm{\\mg/mL}$ was obtained. By vacuum filtering the colloid, a free-standing film of $\\mathrm{Mo_{4}V C_{4}}$ was made. The (002) peak of the resulting film is shifted to an even lower $2\\theta$ after delamination as a result of the further increase in $\\boldsymbol{\\mathscr{c}}$ -LP (39.4 Å) due to the exfoliation of the MXene flakes and intercalation of tetramethylammonium cations used in the delamination process. This indicates an increase in c-LP of 3.4 Å. Similar increases in c-LP after complete delamination have also been reported for other MXenes, such as $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (4.48 Å).47 \n\nMicroscopy. Scanning electron microscopy of $\\mathrm{Mo_{4}V A l C_{4}}$ (Figure 3A) shows the typical layered structure for MAX phase particles. To confirm the five-transition-metal-layered structure of $\\mathrm{Mo_{4}V A l C}_{4},$ transmission electron microscopy was used (Figure 3B,C). The alternating layered structurewith darker layers occurring every sixth layersuggests that slabs of $\\mathrm{Mo}_{4}\\mathrm{VC}_{4}$ are sandwiched between single Al layers (layers of carbon atoms are not visible). HR-STEM high-angle annular dark field (HAADF) imaging shows brighter atomic layers (lighter weight Al layers) alternating with slabs of darker atoms (heavier Mo/V layers) (Supporting Figure 8A). A selected area electron diffraction (SAED) pattern of the [001] zone axis confirms a hexagonal crystal structure (Figure 3B inset). \n\nAfter etching, the Al is removed and the particles become accordion-like (Figure 3D). HR-STEM (Figure 3E,F) shows the five atomic layers of $\\mathrm{Mo/V}$ that are no longer sandwiched between layers of Al, confirming that conversion to $\\mathrm{Mo}_{4}\\mathrm{VC}_{4}$ MXene was achieved. Upon further examination at higher resolution, it was discovered that the center $\\mathrm{Mo/V}$ plane of atoms is a twinned plane, forming a herringbone-type structure (Figure 3F). This clarifies why the XRD patterns did not completely match the typical $P6_{3}/m m c$ structure of MAX phases. Further research is required to fully determine the atomic positions and space group of $\\mathrm{Mo_{4}V A l C_{4}}$ MAX and $\\mathrm{Mo_{4}V C_{4}}$ MXene. \n\nAfter delamination, some of the $\\mathrm{Mo_{4}V C_{4}}$ colloid was dropcast onto porous alumina, and SEM shows an individual 2D flake (Figure 3G). TEM micrographs of a single $\\mathrm{Mo_{4}V C_{4}}$ flake (Supporting Figure 8B,C) show a thickness of ${\\sim}1.3~\\mathrm{nm}$ which is similar to the thickness of the $\\mathrm{Mo_{4}V C_{4}}$ slabs in the MAX structure. Atomic force microscopy results (Figure 3H,I) show the $\\mathrm{Mo_{4}V C_{4}}$ MXene flake has a thickness of $2.50\\pm0.33\\ \\mathrm{nm}$ . Comparatively, $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ ${\\mathit{\\Omega}}(n=2{\\mathit{\\Omega}}_{\\mathrm{{:}}}$ , a MXene with three transition metal layers) has a thickness of $1.60\\ \\mathrm{nm}$ when measured with AFM.55 Reported AFM thickness values include the MXene flake as well as any absorbed water molecules or other adsorbed species. The cross-section of a film of $\\mathrm{Mo_{4}V C_{4}}$ flakes showing layers of delaminated flakes stacked flat on top of each other is provided in Supporting Figure 8D. \n\nCompositional Characterization. After determining the atomic structure, we turned our attention to the composition. As a qualitative tool, we used energy-dispersive X-ray spectroscopy and standard-less quantification to study the compositions of the $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase particles after HCl washing, $\\mathrm{Mo_{4}V C_{4}}$ multilayer MXene particles, and the freestanding film of delaminated MXene (Table 1). Since the MAX powder likely contained binary carbide impurities that remained after HCl washing, EDS analysis was done on particles with a visible layered structure, similar to Figure 3A, and the measured compositions were averaged. Surprisingly, the atomic percentage of aluminum was much lower than the stoichiometric amount for the MAX phase. Upon further examination with TEM, it was discovered that in addition to five-layer slabs of $\\mathrm{Mo/V}$ sandwiched between Al layers, thicker slabs of $\\mathrm{Mo/V}$ layers are also present in some locations (Supporting Figure 9). There are occasionally slabs of up to 20 $\\mathrm{Mo/V}$ layers observed. This can explain why there is a lower than expected Al ratio. Additionally, the reduction of ${\\bf V}_{2}{\\bf O}_{3}$ by Al to form $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ could also contribute to this and a high concentration of Al vacancies may be present. The MXene showed no presence of aluminum and instead showed the presence of fluorine and oxygen terminations ${\\left({\\mathrm{T}_{x}}\\right)}$ . This indicates that the etching was successful, and terminations are present on the MXene surface. \n\n![](images/3de5a1207aa5a4a25410d87ba3c4dfb9f29e29816d3725d500c63ffff3d12e4f.jpg) \nFigure 4. High-resolution XPS spectra of a $\\mathbf{Mo_{4}V C_{4}}$ free-standing film. (A) Mo 3d. (B) V 2p. (C) C 1s regions. \n\n![](images/42429fff4cdc8a51f85856ffcde4a4a0710af16c4d75dd116ada287864f4b990.jpg) \nFigure 5. Raman spectra of MAX and MXene. (A) $\\mathbf{Mo_{4}V A l C_{4}}$ MAX phase, (B) $\\mathbf{Mo_{4}V C_{4}}$ multilayer MXene, and (C) free-standing film of delaminated $\\mathbf{Mo_{4}V C_{4}}$ MXene. \n\nWhile the Mo:V ratio used for synthesizing the $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase was 4:1, the resulting material had a ratio of $\\mathrm{Mo}_{3.89}{:}\\mathrm{V}_{1.11}$ (Table 1). After the HF treatment, the resulting $\\mathrm{Mo_{4}V C_{4}}$ MXene had a ratio of $\\mathbf{Mo}_{4.06}\\mathrm{:V}_{0.94}$ . After delamination with TMAOH, the ratio remained about the same $\\mathrm{Mo}_{4.04}{:}\\mathrm{V}_{0.96}$ . The fluctuations in the Mo:V ratio are likely within reasonable error of the EDS detector, which means the selective etching was done for Al layers. The slight change in the $\\mathrm{Mo/V}$ ratio might also be due to dissolution of some V atoms from the surface layer of the carbide, which agrees with the green color of the solution during the first wash. The amount of F present decreases after delamination. It has been shown previously that delamination with TMAOH decreases the F content,57 specifically for Mo-containing MXenes.58,59 Nonetheless, the F content even before delamination is still significantly lower compared to Ti-based MXenes,60 which is in agreement with previously reported work indicating that Mo on the surface preferentially bonds with −OH or $\\scriptstyle=0$ terminations rather than −F.61 Also, a decreased O content was observed after delamination; however, the accuracy of the EDS detector for O is limited so we do not report this as a quantitative result. \n\nA high-resolution EDS spectrum was also obtained to determine whether the Mo/V layers were ordered or disordered solid-solutions (Supporting Figure 10). There is a distinct ordering with regard to the $\\mathrm{Mo/V}$ slabs alternating with Al layers as shown by the periodic Al peaks. The spectra for Mo and V within the slabs are generally homogeneous, and therefore it is concluded that the $\\mathrm{Mo/V}$ layers are solidsolutions of Mo and V. Despite this conclusion, a higher brightness of the middle layer (Supporting Figure 11) was observed in select instances, suggesting possible enrichment with Mo. \n\nX-ray photoelectron spectroscopy was used to quantify the transition metal ratio, and the C content in $\\mathrm{Mo_{4}V C_{4}}$ MXene. The Mo 3d region (Figure 4A) can be adequately fitted with two doublets corresponding to Mo bonded to carbon and surface termination at 228.47 eV $\\left(231.68~\\mathrm{eV}\\right)$ and Mo in the ${\\mathrm{Mo}}^{4+}$ oxidation state at $229.59~\\mathrm{{\\sc~eV}}(232.83~\\mathrm{{\\eV}).}$ which corresponds to small amount of oxides presented in the freestanding film. Similarly, the $\\mathtt{V}2\\mathtt{p}$ region can also be fitted with two doublets centered at ${513.38\\ \\mathrm{eV}}$ $(520.84~\\mathrm{eV})$ and 514.94 eV (522.81 eV) corresponding to $\\mathrm{V}^{2+}$ and $\\mathrm{V}^{3+}$ states, respectively, as shown in Figure 4B.30 Both doublets in the $\\textsf{V}2\\mathsf{p}$ regions are assigned to $\\mathrm{\\DeltaV}$ bonded to C atoms in the MXene structure. The difference in oxidation states of V might come from different surface terminations bonded on the $\\mathrm{\\DeltaV}$ atom on the surface, which implies that $\\mathrm{\\DeltaV}$ is positioned in different transition metal layers (bonded to C and terminations), another indication of solid-solution in the transition metal layers. The C 1s region (Figure 4C) was fitted by 5 peaks, corresponding to C−Mo/V, C−C, C−H, C−O, and $_\\mathrm{C-OO}$ at 283.15, 284.56, 285.31, 286.48, and $289.12\\ \\mathrm{eV},$ , respectively. The atomic ratio was deduced from the intensity of only the peaks related to MXene, e.g., only $\\mathrm{C-Mo/V}$ peak in C region was used in this calculation. The calculated ratio was $\\mathrm{Mo}_{4.10}\\mathrm{V}_{0.90}\\mathrm{C}_{2.99}$ which agrees with the ratio of Mo:V obtained from EDS results. The amount of C is below the expected stoichiometry, similar to many MXenes, possibly because of the presence of C vacancies in their precursor MAX phases.62 This high concentration of C vacancies may also be required to form this higher $n$ MAX phase. It was shown for $\\mathrm{V}_{4}\\mathrm{AlC}_{3}$ that the structure is only stable with the presence of $11\\%$ carbon vacancies.63 The low amount of C could also be due to a substitution of $\\mathrm{~O~}$ for some of the C sites during the synthesis of $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase. XPS results also indicate that no Al is present after etching and the amount of $\\mathrm{~F~}$ surface termination is very small, in agreement with our EDS results (no more than $10\\%$ of the total surface termination) (Supporting Figure $12\\mathrm{\\A},\\mathrm{B}$ ). \n\n![](images/69f7f1c6e85372c84cd579cb506adc5fff4d1e70e5f86b93da608885b60bef6c.jpg) \nFigure 6. Thermal stability of $\\mathbf{Mo_{4}V C_{4}}$ . (A) Thermogravimetric analysis of $\\bf{M o}_{4}V C_{4}$ MXene film. The sample experienced 6 drops in its weight due to water, $\\mathbf{OH}^{-}$ termination groups, TMAOH, and the MXene decomposition. (B) Mass spectrometry results indicating the removal of CO, $\\mathbf{OH}^{-}/\\mathbf{NH}_{3},$ , $\\mathbf{H_{2}O/N H_{4}}^{+}$ , $\\mathbf{NH}_{2}^{-}$ , and $\\mathbf{CO}_{2}$ from the MXene film that correspond to the sample’s weight loss. (C) XRD patterns of the resulting material after the drops in sample weight. Inset shows a close view of the peak shift in the XRD pattern of the material as prepared, heated to $\\mathbf{150}^{\\circ}\\mathbf{C},$ ${\\bf500}^{\\circ}{\\bf C},$ and $900^{\\circ}\\mathbf{C}$ with the respective $\\boldsymbol{\\mathbf{\\mathit{c}}}$ -LPs. The broad peaks at ${\\sim}20^{\\circ}$ in the 900 and $\\mathbf{1500^{\\circ}C}$ patterns are due to the double-sided tape that was used to hold the film pieces to the glass slide during XRD measurements. \n\nThe Raman spectra of HCl-washed $\\mathrm{Mo_{4}V A l C}_{4},$ multilayer $\\mathrm{Mo}_{4}\\mathrm{VC}_{4},$ and a free-standing film of delaminated $\\mathrm{Mo_{4}V C_{4}}$ MXene (Figure 5) show broad peaks in the range below 1000 $\\mathsf{c m}^{-1}$ that correspond to vibrations of metals with oxygen and carbon. Both molybdenum and vanadium carbides exhibit bands below $700~\\mathrm{{cm}^{-1}}$ . Cubic VC exhibits one band64 at 250 $\\mathrm{cm}^{-1}.$ , and hexagonal $\\mathbf{Mo}_{2}\\mathbf{C}$ shows a number of peaks around $143~\\mathrm{{cm}^{-1}}$ as well as one band at $650~\\mathrm{{cm}^{-1}}$ .65 Aluminum carbide has a distinct band around $850~\\mathrm{{cm}^{-1}}$ .66 The band position is at higher frequencies due to atomic mass differences between Mo, V, and Al. No bands around $850~\\mathrm{cm}^{-1}$ are found in the Raman spectrum of MAX phase which suggests the absence of $\\mathrm{{Al}}_{4}\\mathrm{{C}}_{3}$ in the MAX phase. \n\nRaman spectra have been described for MXenes with other $n$ values such as $\\mathrm{M}_{2}\\mathrm{X},^{67}\\mathrm{M}_{3}\\mathrm{X}_{2},^{68}$ and $\\mathbf{M}_{4}\\mathbf{X}_{3}$ .69 Following the trend, $\\mathrm{Mo_{4}V C_{4}}$ is expected to exhibit M, X, and $\\mathrm{T}_{x}$ group vibrations, $\\mathrm{T}_{x}$ atom vibrations, and $\\mathrm{\\DeltaX}$ atom vibrations. The obtained spectra follow this trend. Three regions of vibrations are observed. The region between 100 and $300~\\mathrm{{cm}^{-1}}$ corresponds to V, Mo, C, and surface group vibrations followed by the surface group region at $350{-}500~\\mathrm{cm}^{-1}$ and carbon vibration region at $500{-}70{0}~\\mathrm{cm}^{-1}$ . The peaks are broad and overlapping. In contrast, Raman spectra of ordered MXenes $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}$ and $\\mathbf{Mo}_{2}\\mathrm{Ti}_{2}\\mathbf{C}_{3}$ exhibit sharp bands in the region below $1000~\\mathrm{{cm}^{-1}}$ .27 Since Raman vibrations in solids represent the vibrations of a unit cell, distortions of neighboring unit cells due to varying M-elements will lead to broadening of Raman peaks due to different frequencies of the vibrations.70 Moreover, since Raman bands depend on the element’s mass, broadening will be even more pronounced when the interchangeable elements have a large difference in mass.70 This again indicates that there are solid-solutions on the M sites within the MAX and MXene structure. Additionally, traces of free carbon are observed in the MAX phase sample (the peak at about $1600~\\mathrm{{cm}^{-1}},$ ). \n\nThermal Analysis. The thermal stability of a $\\mathrm{Mo_{4}V C_{4}}$ film was determined by thermogravimetric analysis coupled with mass spectrometry (MS) under Ar flow. The thermogram (Figure 6A) shows several significant drops in the weight of the sample upon heating. The first weight loss step, which peaked at $125\\ ^{\\circ}\\mathrm{C},$ is due to the removal of $_\\mathrm{H}_{2}\\mathrm{O}$ molecules that were trapped in between the $\\mathrm{Mo_{4}V C_{4}}$ flakes from the filtration of the MXene colloid as shown by the $\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{OH^{-}}$ peaks in the mass spectra (Figure 6B).26 The XRD pattern of a sample treated at $150~^{\\circ}\\mathrm{C}$ under Ar flow (Figure 6C) reveals a shift in the (002) peak indicating a decrease in c-LP of $4\\textup{\\AA}$ from the as-prepared sample. This is due to the compaction of the flakes after the $\\mathrm{H}_{2}\\mathrm{O}$ removal. The amount of compaction indicates that possibly two layers of $_\\mathrm{H}_{2}\\mathrm{O}$ molecules were present as the molecular radius of $_{\\mathrm{H}_{2}\\mathrm{O}}$ is ${\\sim}2.75$ Å. The second weight loss step, which peaked at $342^{\\circ}\\mathrm{C},$ is due to the removal of residual TMAOH between the flakes as shown by the $\\mathrm{NH}_{2}^{-}$ , $\\mathrm{CO}_{2},$ CO, $\\mathrm{OH^{-}/N H_{3}},$ and $\\mathrm{H}_{2}\\mathrm{O}/\\mathrm{NH}_{4}^{+}$ peaks in the mass spectra (Figure 6B).25,26,71 For a sample treated at 500 °C under Ar flow, there is a further shift in the (002) peak indicating a decrease in $c$ -LP of $3.8\\mathring{\\mathrm{~A~}}$ from the sample treated at $150^{\\circ}\\mathrm{C}$ and a total of $7.8\\mathring\\mathrm{\\mathrm{A}}$ decrease in $c$ -LP from the as-prepared sample (Figure 6C). \n\n![](images/188d15a933e4a770419545cbdf7aa08bcfde1b4f5172c9a1e11e2c71cf43abfb.jpg) \nFigure 7. Temperature-dependent electrical properties of MXene. (A) Electrical resistivity as a function of temperature for $\\bf{M o}_{4}V C_{4}$ annealed at 150 and ${\\bf500}^{\\circ}{\\bf C}.$ (B) Magnetoresistance of $\\mathbf{Mo_{4}V C_{4}}$ under an external magnetic field perpendicular to the sample surface. \n\nThis decrease in c-LP from as-prepared to treated at $500~^{\\circ}\\mathrm{C}$ is smaller than those reported for $\\mathbf{Mo}_{2}\\mathbf{C}$ (17.9 Å), $\\mathbf{Mo}_{2}\\mathrm{TiC}_{2}$ (13.3 Å), and $\\mathbf{Mo}_{2}\\mathrm{Ti}_{2}\\mathbf{C}_{3}$ (15 Å), possibly because those MXenes were delaminated with tetrabutylammonium hydroxide which has a larger radius of $8{-}9.9\\ \\mathrm{\\AA}^{27}$ The removal of additional water suggests that some is retained even after the weight loss step at $125^{\\circ}\\mathrm{C}$ . The ionic radius of $\\mathrm{TMA}^{+}$ is $3.2\\mathring{\\mathrm{A}},$ which indicates that there is likely one layer of $\\mathrm{TMA}^{+}$ ions between the layers with some $\\mathrm{H}_{2}\\mathrm{O}$ retained. \n\nOverall, our TGA-MS results show that $\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{TMA}^{+}$ ions occupy similar amounts of space between the MXene flakes. The temperatures for the removal of residual $\\mathrm{H}_{2}\\mathrm{O}$ and TMAOH are in agreement with previously reported results for another Mo-containing MXene; $\\mathrm{\\hat{M}o}_{2}\\mathrm{C}$ .26 Our results indicate that Mo-containing MXenes have similar thermal behaviors due to similar bonding strengths between Mo and molecules on the surface, but these behaviors have been shown to be different than MXenes with other M elements. The next weight loss began at ${\\sim}505\\ ^{\\circ}\\mathrm{C}$ and was indicated by C leaving the structure as CO. This is similar to the behavior exhibited by $\\mathrm{{\\bf{Mo}}}_{2}\\mathrm{{C}}$ .26 Defunctionalization of the surface producing two peaks at 638 and $742^{\\circ}\\mathrm{C}$ (Figure 6A) allows recrystallization of carbide. After the heat treatment at $900~^{\\circ}\\mathrm{C}$ under Ar flow the resulting material is no longer $\\mathrm{Mo_{4}V C_{4}}$ MXene, and instead decomposes to form an orthorhombic $(\\mathrm{Mo},\\mathrm{V})_{2}\\mathrm{C}$ phase. Heating to $1500~^{\\circ}\\mathrm{C}$ transformed much of the orthorhombic $(\\mathrm{Mo},\\mathrm{V})_{2}\\mathrm{C}$ phase to cubic $(\\mathrm{Mo},\\mathrm{V})\\mathrm{C},$ as marked in Figure 6C. However, the exact structure of these bulk carbides was not analyzed in this study. \n\nElectrical and Optical Properties. The electrical resistivity of an as-prepared $\\mathrm{Mo_{4}V C_{4}}$ free-standing film was measured with a 4-point probe. The thickness and resistivity values were quite uniform (standard deviation $=0.82\\ \\mu\\mathrm{m}$ and $0.10~\\mathrm{m}\\Omega\\ \\mathrm{cm}$ , respectively). The resistivity was measured to be $4.18~\\mathrm{m}\\Omega~\\mathrm{cm}$ (conductivity $240~\\mathrm{S/cm}_{\\cdot}$ ). To remove the effects of water and TMAOH intercalants, the as-prepared sample was heated at $500~^{\\circ}\\mathrm{C}$ in an Ar atmosphere for $s\\mathrm{h}$ . We chose 500 $^{\\circ}\\mathrm{C}$ annealing temperature based on our TGA results (Figure 6). After heat-treatment, the sample’s electrical resistivity decreased to $1.20~\\mathrm{\\m}\\Omega~\\mathrm{cm}$ (conductivity $833\\mathrm{~\\thinspaceS/cm},$ . This electrical resistivity is similar to another Mo-based MXene; $\\mathbf{Mo}_{2}\\mathrm{Ti}_{2}\\mathbf{C}_{3}$ $\\left(1.63\\:\\mathrm{\\stackrel{.}{m}\\Omega\\mathrm{cm}}\\right)$ .27 Interestingly, two thinner Mobased MXenes, $\\mathbf{Mo}_{2}\\mathbf{C}$ and $\\mathrm{Mo}_{2}\\mathrm{TiC}_{2},$ have much lower resistivities of $0.80~\\mathrm{m}\\Omega$ cm and $0.67~\\mathrm{m}\\Omega~\\mathrm{cm}$ , respectively.27 It is expected that a thicker MXene would have a lower resistivity due to additional paths for electrons to travel within a flake; however, this is not the case for the film measured here. We hypothesize that due to the increased thickness of $\\mathrm{Mo}_{4}\\mathrm{VC}_{4},$ the flakes are probably more rigid and might not stack well and might have gaps between adjacent flakes leading to fewer conductive paths. In other words, this can be due to the interflake resistivity rather than the intraflake resistivity. New measurement techniques are needed to measure the intrinsic properties of MXenes, such as electrical resistivity. \n\nThe electrical resistivity of $\\mathrm{Mo}_{4}\\mathrm{VC}_{4}$ films as a function of temperature was measured after drying at $150~^{\\circ}\\mathrm{C}$ in a vacuum oven and annealing at $500~^{\\circ}\\mathrm{C}$ under an Ar atmosphere. The results (Figure 7A) show that the resistivity gradually increases as temperature decreases. The trend was similar for both samples, although the sample annealed at $500^{\\circ}\\mathrm{C}$ had a slightly lower absolute resistivity. Interestingly, the room-temperature resistivity of this MXene only reduced by ${\\sim}0.4\\ \\mathrm{\\m}\\Omega$ cm, compared to the dried sample, after annealing at $500~^{\\circ}\\mathrm{C}$ . This indicates that large $d.$ -spacing caused by TMAOH intercalation does not largely affect the electron transport property of this MXene, unlike what was observed for $\\mathrm{Ti}_{3}\\mathrm{CN}$ MXene, where an order of magnitude reduction in room-temperature resistivity was observed after annealing at $400^{\\circ}\\mathrm{C}$ .25 The smaller decrease in resistivity could also be due to poor stacking of thick and rigid $\\mathrm{Mo_{4}V C_{4}}$ flakes, so that even after annealing, the flakes do not align well, having poor connections with neighboring flakes, as discussed above. The effect of TMAOH on temperature-dependent resistivity can be seen by comparing the overlaid temperature-dependent resistivity curves for as produced and annealed MXene (Supporting Figure 13A). The trend is similar although the $500^{\\circ}\\mathrm{C}$ -annealed sample exhibits a less drastic increase in resistivity with decreasing temperature. The abrupt increase of the resistivity seen in the $150\\ ^{\\circ}\\mathrm{C}.$ annealed sample (black curve) at ${\\sim}250\\mathrm{K}$ is most likely due to freezing of the remaining water and TMAOH molecules. \n\nThe magnetoresistance was measured at $10~\\mathrm{~K~}$ with a magnetic field up to $5\\mathrm{T}$ applied perpendicular to the sample surface. $\\mathrm{Mo_{4}V C_{4}}$ exhibits a positive MR as shown in Figure 7B, which is similar to other Mo-containing MXenes,58,59 while many other MXenes exhibit a negative MR.58,72 The reason for the positive MR observed in Mo-containing MXenes is currently unclear and a topic requiring further research. However, the strength of magnetoresistance was almost negligible for the sample annealed at $500~^{\\circ}\\mathrm{C}$ . This indicates that the magnetoresistance might be related to interflake electron transport rather than an intrinsic property of the MXene flakes. Hall measurements of both samples at $10\\mathrm{~K~}$ indicates carrier concentration of $2.52\\times10^{22}\\mathrm{cm}^{-3}$ and $1.37\\times$ $10^{22}~\\mathrm{cm}^{-3}$ for the $150~^{\\circ}\\mathrm{C}\\mathrm{-}$ and $500~^{\\circ}\\mathrm{C}$ -annealed samples, respectively. Both samples exhibit negative Hall slope (Supporting Figure 13B) suggesting that electrons are the major carrier.73 The carrier mobility increases from $0.10\\ \\mathrm{cm}^{2}/\\$ V s for the $150~^{\\circ}\\mathrm{C}.$ -annealed samples to $0.36~\\mathrm{cm}^{2}/\\mathrm{V}$ s for the $500^{\\circ}\\mathrm{C}$ -annealed samples, mostly likely due to less scattering in the absence of TMAOH and water. \n\n![](images/19cdde4a2e98bbca82d05d0fbe9e34ac5ff46240dca893625bbca449570d0622.jpg) \nFigure 8. DFT predictions of MAX phases and MXenes. (A) Formation energies for solid-solution $\\mathbf{Mo_{4}V A l C_{4}}$ configurations (black dots) compared to ordered $\\mathbf{Mo_{4}V A l C}_{4}$ (purple diamond). (B) DFT calculated formation energies of ordered $\\mathbf{M^{\\prime}}_{4}\\mathbf{M^{\\prime\\prime}A l C}_{4}$ MAX phases. Most are predicted to be stable except for some Mo and W compositions. \n\nThe optical properties were evaluated by measuring the extinction per path length $(\\mathrm{Ext}/1)$ of delaminated $\\mathrm{Mo_{4}V C_{4}}$ solutions with varying concentrations and transmission of $\\mathrm{Mo_{4}V C_{4}}$ thin films (Supporting Figures 14−15). As determined with UV−vis-NIR spectroscopy, the extinction coefficient at $550\\ \\mathrm{nm}\\ (\\varepsilon_{550})$ was determined to be $34.4\\mathrm{~L~g^{-1}}$ $\\mathsf{c m}^{-1}$ . Thin film transmission measurements show there is a decrease in transparency with increasing wavelength from 300 to $1000\\ \\mathrm{nm}$ (Supporting Figure 15). MXenes with an n value of 1 or 2, such as $\\mathrm{Ti}_{2}\\mathrm{C},$ , ${\\mathrm{V}}_{2}{\\mathrm{C}}_{\\mathrm{i}}$ , $\\mathrm{Ti}_{3}\\mathrm{CN}_{.}$ , and ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2},$ interact with light within the visible spectrum displaying compositiondependent extinction.13,14,74 Notably, $\\mathrm{Ti}_{2}\\mathrm{C}$ shows a broad extinction peak at $550\\ \\mathrm{nm},$ , which shifts to lower energy for ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2},$ as indicated by a broad extinction peak between 700 and $800\\ \\mathrm{nm}$ and strong decrease in transparency in the infrared region.14 In comparison, $\\mathrm{Mo_{4}V C_{4}}$ exhibits a featureless absorption spectrum from the visible to near-infrared range (400 to $2500\\ \\mathrm{nm},$ ), hinting at fundamental differences in how the material interacts with electromagnetic radiation compared to MXenes with a $n$ value of 1 or 2. To the best of our knowledge, the optical properties of MXenes with $n$ larger than 2 have not been reported and future studies exploring the relationship between atomic thickness and optical properties are imperative. Due to the featureless spectrum, a potential application of this material could include fabricating low loss and high optical figure of merit (FOM) transparent conducting electrodes. Realization of this application will require efforts focused on optimization of the thin film quality and identification of the optical coefficients in the wavelength region in which the material will operate. \n\nDensity Funtional Theory. Density functional theory calculations were performed to determine the preferred termination groups that can exist on the surface of $\\mathrm{Mo_{4}V C_{4}}$ \n\nMXene. The results of these calculations indicate that $-\\mathrm{OH}$ is the most preferred termination group with $-9.10\\ \\mathrm{eV}$ formation energy. $\\scriptstyle=0$ and $-\\mathrm{F}$ terminations are not as stable $(-5.39\\ \\mathrm{eV}$ and −6.56 eV, respectively) which agrees with the experimental results presented here (Figure 4). With regard to the $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase, DFT calculations were used to determine the stabilities of 18 quasirandom solid-solution configurations as well as an ordered configuration with one layer of $\\mathrm{v}$ sandwiched between four layers of Mo (two layers of Mo on each side as shown in Figure 8A). Examples of these quasi-random structures are provided in Supporting Figure 16. Each of these phases were predicted to be stable, in agreement with experimental results. For $\\mathrm{Mo_{4}V A l C}_{4},$ there are solidsolution configurations that are more stable than an ordered configuration; thus, it is more preferred for $\\mathrm{Mo_{4}V A l C_{4}}$ to exist as a solid-solution. The most stable solid-solution configuration that we calculated had $a$ and $\\boldsymbol{\\mathscr{c}}$ lattice parameters of 3.04 and $28.52\\mathrm{~\\AA},$ respectively. This agrees well with our experimental results obtained with XRD $\\l{a}=2.99$ and $c=$ $28.22\\mathrm{~\\AA~}$ ). \n\nDFT calculations were also performed to determine the thermodynamic stability of other $\\mathrm{{\\bfM}}_{5}\\mathrm{{AlC}}_{4}$ MAX phases. Specifically, the formation energies of ordered $\\mathbf{M^{\\prime}}_{4}\\mathbf{M^{\\prime\\prime}A l C}_{4}$ compositions were calculated where $\\mathbf{M}^{\\prime}$ and $\\mathbf{M}^{\\prime\\prime}$ were Hf, Zr, Ti, Ta, Nb, V, Sc, Mo, and W. A summary of the predicted stability of these phases is shown in Figure 8B. The exact formation energy values are provided in Supporting Table 2. It is expected for many of the compositions examined here, that there may be at least one solid-solution structure that is more stable than the compositionally equivalent ordered structure. We present calculations for ordered MAX structures as a simple exploration of stability trends and many of their compositionally equivalent $\\mathbf{M^{\\prime}}_{4}\\mathbf{M^{\\prime\\prime}A l C}_{4}$ solid-solution phases will likely be even more stable. \n\nInterestingly, other phases studied, such as ordered phases containing Hf, $\\mathrm{Zr,}$ and Ta, are predicted to be more stable than the synthesized $\\mathrm{Mo_{4}V A l C_{4}}$ . The effect that the $\\mathbf{M}^{\\prime}$ element has on the stability was determined to be much greater than that of $\\mathbf{M}^{\\prime\\prime}$ . W- and Mo-containing compositions are the least stable and are the only two $\\mathbf{M}^{\\prime}$ elements that produce some unstable compositions. For both Mo- and W-based MAX phases specifically, it is known that Mo and W avoid stacking with C in a face-centered cubic structure (FCC),40 so adding another \n\nM element can allow for Mo- and W-based MAX/MXene to be synthesized as the additional M element will occupy some of the FCC sites, thus relieving stress within the crystal structure. However, here we considered only ordered phases in Figure 8B and compositions predicted to be unstable may still have other stable solid-solution configurations. These calculations also show that most of the M elements can achieve a higher stability when they are combined with another M element. The only exception to this is Hf which is most stable when $\\mathbf{M}^{\\prime}=\\mathbf{M}^{\\prime\\prime}$ . Worth noting are the specific elements that best stabilize the material. Higher stability occurs when Hf, $\\mathrm{Zr,}$ ${\\mathrm{Ti}},$ and Ta are the $\\mathbf{M}^{\\prime}$ or $\\mathbf{M}^{\\prime\\prime}$ element. This agrees with previous work where these elements were predicted to stabilize MAX phases,63 and the lower formation energies were correlated with the difference in ionic radius between the M atoms.75 MAX phases with $\\mathbf{M}=\\mathbf{Cr}$ or Mn are reserved for a future study, as we expect many of these phases have stable magnetic ground states, and a more detailed study is needed to properly characterize these systems. \n\nTo thoroughly explore the configurational space of the $\\mathrm{Mo_{4}V A l C_{4}}$ system, we performed cluster expansion calculations around the concentration $X_{\\mathrm{Mo}}=0.8$ with the ATAT (Alloy Theoretical Automated Toolkit) package (Supporting Table 3).76 The converged ground-state solid-solution structure has an energy $15.8~\\mathrm{\\meV}/\\$ atom lower than the ordered symmetric phase. The low energy structures generated during the cluster expansion calculations show that V avoids the middle layer in solid-solution. In this composition range, V prefers to occupy layers 2 and 4 in order to maximize the number of favorable $_{\\mathrm{Mo-V}}$ bonds and stabilize the crystal structure. \n\nBased on the crystal structure observed with TEM, we have additionally examined a nontypical MAX phase structure $\\mathrm{Mo_{4}V A l C_{4}}$ with $P\\overline{{6}}m2$ symmetry, rather than the traditional $P6_{3}/m m c$ space group,77 because this symmetry exhibits a herringbone-type structure like that observed with TEM, and the simulated XRD pattern for this structure matches well with our experimental results. We find that the $\\mathrm{Mo_{4}V A l C_{4}}$ phase exhibiting $P\\overline{{6}}m2$ symmetry also prefers a disordered solidsolution, with a solid-solution ground-state energy that is 67.8 meV/atom lower than the ordered, symmetric phase. The low energy structures exhibit the same Mo-rich middle layers. Interestingly, the ground state in the $P\\overline{{6}}m2$ geometry is 31.8 meV/atom lower in energy than the ground state in the $P6_{3}/\\$ mmc geometry. This indicates that further study, both experimentally and theoretically, is required to confirm the structure of $\\mathrm{Mo_{4}V A l C_{4}}$ and other theoretically predicted quaternary $\\mathrm{{\\bfM}}_{\\mathrm{{s}}}\\mathrm{{AlC}}_{4}$ phases. However, the disordered nature and Mo-rich inner layer are independent of the space group. \n\nThese calculations show that there is potential for expansion to other $\\mathrm{{\\bfM}}_{5}\\mathrm{{AlC}}_{4}$ MAX phases, allowing for more $\\mathrm{{\\bfM}}_{5}\\mathrm{{X}}_{4}$ MXenes to be produced. It is important to note that while many of these ordered $\\mathbf{M^{\\prime}}_{4}\\mathbf{M^{\\prime\\prime}A l C}_{4}$ phases were determined to be stable compared to their respective unary phases, there may be binary carbides, intermetallics, or other competing MAX phases that are more stable for these compositions. Full evaluation of the possibilities for the synthesis of more $\\mathbf{M}^{\\prime}_{4}\\mathbf{M}^{\\prime\\prime}\\mathbf{X}_{4}$ MXenes requires solid-solution calculations, precise determination of this five-layered crystal structure, dynamical and phase stability analysis,75 and calculation of exfoliation energies.46 The work presented here provides only trends in stability as a function of M element composition. Future studies will include detailed examinations of solid-solutions over various compositions and stability with respect to other competing phases. The results presented here give some insight and direction into the huge space of additional structures to explore with computation and machine learning78 to accelerate the expansion of the MXene family. \n\n# CONCLUSIONS \n\nHere, we report $\\mathrm{Mo}_{4}\\mathrm{VC}_{4},$ a MXene with nine atomic layers (five transition metal and four carbon) synthesized from a $\\mathrm{{\\bfM}}_{5}\\mathrm{{AX}_{4}}$ phase precursor, $\\mathrm{Mo_{4}V A l C_{4}},$ that contained no other MAX phase impurities. $\\mathrm{Mo_{4}V A l C_{4}}$ is the only known MAX phase to exhibit twinning on the center M layers of atoms, which makes $\\mathrm{Mo_{4}V C_{4}}$ MXene different from all other known MXenes for the two reasons stated above. This MXene is disordered on the M site as indicated by high-resolution EDS. Besides the scalable synthesis method, we present structural and chemical analysis of both $\\mathrm{Mo_{4}V A l C_{4}}$ and $\\mathrm{Mo}_{4}\\mathrm{VC}_{4},$ as well as thermal stability, optical, and electronic characterization of $\\mathrm{Mo_{4}V C_{4}}$ . In addition, DFT results show the great potential for discovering additional $\\mathrm{M}_{5}\\mathrm{AX}_{4}$ phases. Due to their higher thickness, $\\mathrm{M}_{5}\\mathrm{X}_{4}$ MXenes could have the potential to be useful in many applications including, but not limited to, structural materials, optoelectronic devices with high figure of merit, and electronics. $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase and $\\mathrm{\\bar{M}o_{4}V C_{4}}$ MXene venture into the $\\mathrm{M}_{5}\\mathrm{X}_{4}$ territory for the MXene family of 2D materials. \n\n# EXPERIMENTAL METHODS \n\nSynthesis of ${\\mathsf{M o}}_{4}{\\mathsf{V A l C}}_{4}$ MAX. Molybdenum ( $99.9\\%$ Alfa Aesar, $-250\\ \\mathrm{mesh})$ , vanadium $(99.5\\%$ Alfa Aesar, $-325\\ \\mathrm{mesh},$ ), vanadium(III) oxide ( $98\\%$ Sigma-Aldrich), aluminum $(99.5\\%$ Alfa Aesar, $-325$ mesh), and graphite ( $99\\%$ Alfa Aesar, $-325\\mathrm{\\mesh},$ powders were hand-mixed with an agate mortar and pestle for $\\bar{\\mathsf{S}}\\operatorname*{min}$ in a molar ratio of 4:0.9:0.05:1.2:3.5 $\\left(\\mathrm{Mo};\\mathrm{V};\\mathrm{V}_{2}\\mathrm{O}_{3};\\mathrm{Al};\\mathrm{C}\\right)$ . To determine the proper Mo:V mixing ratio, we mixed a series different ratios from $0\\%$ to $100\\%$ Mo (Supporting Figure 1). The mixtures were heated in alumina crucibles at a rate of $3~{}^{\\circ}{\\bf C}/{\\mathrm{min}}$ to $1650~^{\\circ}\\mathrm{C}$ under $350~\\mathrm{{\\cm}}^{3}/\\mathrm{{min}}$ flowing argon in a tube furnace (Carbolite Gero) and held for $^{4\\mathrm{~h~}}$ before passive cooling to room temperature. After removal from the furnace, the sintered blocks of $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase were drilled with a tabletop drill press with a carbide drill bit to form a powder. To dissolve metallic and oxide impurities, $_{15\\mathrm{~g~}}$ of this powder was then stirred in $50~\\mathrm{mL}$ of HCl ( $36.5\\mathrm{-}38\\%$ Fisher Chemical) for $^{18\\mathrm{~h~}}$ The HCl was washed out through a series of centrifugations at $3500~\\mathrm{rpm}$ (2550 rcf) for $3~\\mathrm{\\min}$ , decanting the acidic supernatant, and redispersing the sediment in deionized (DI) water. The exact washing procedure is described in Supporting Information. After washing, the MAX powder was dried in a vacuum desiccator for $^{18\\mathrm{~h~}}$ at $2\\bar{5}~^{\\circ}\\mathrm{C}$ . Then the powder was sieved to a particle size $<75\\ \\mu\\mathrm{m}$ . \n\nSynthesis of $\\mathsf{{M o}}_{4}\\mathsf{v}C_{4}$ MXene. A simplified schematic for the synthesis of $\\mathrm{Mo_{4}V C_{4}}$ MXene is shown in Figure 9. To synthesize multilayer MXene, $_{4\\textrm{g}}$ of the MAX powder was slowly added to 40 mL of HF $48-51\\%$ Arcos Organics). The sample was stirred with a polytetrafluoroethylene (PTFE)-coated stir bar at $400~\\mathrm{{rpm}}$ and heated in an oil bath at $50~^{\\circ}\\mathrm{C}$ for 8 days. After that, the mixture was washed with the same washing procedure previously described in the MAX synthesis section (detailed washing procedure is described in Supporting Information). After the $\\mathsf{p H}$ of the mixture was more than 6, the multilayer MXene was collected on a MF-Millipore $0.45~\\mu\\mathrm{m}$ mixed cellulose esters (MCE) membrane by vacuum-assisted filtration. The wet multilayer MXene powder was then dried in a vacuum desiccator for $^{18\\mathrm{~h~}}$ at $25~^{\\circ}\\mathrm{C}$ . \n\nExfoliation of the multilayer MXene was achieved by dispersing $0.25\\mathrm{~g~}$ of multilayer $\\mathrm{Mo_{4}V C_{4}}$ powder in a $10~\\mathrm{mL}$ solution of 10 wt $\\%$ tetramethylammonium hydroxide (TMAOH, 25 wt $\\%$ − diluted to 10 wt $\\%$ , Sigma-Aldrich) and stirred at $400~\\mathrm{rpm}$ at $25~^{\\circ}\\mathrm{C}$ for $24\\mathrm{~h~}$ . \n\n![](images/539ddc7d014beaedfad5774e25b99eacd8fc96ce5279b41bccafe0cf5c2bf505.jpg) \nFigure 9. $\\mathbf{Mo_{4}V A l C_{4}}$ MAX phase is etched with HF to produce $\\mathbf{Mo_{4}V C_{4}}$ MXene. The fluorine ions selectively remove the Al layers of the MAX structure to form ${\\bf A l F}_{3}$ and surface terminations bond to the basal planes of the resulting MXene. Afterward, the MXene flakes are held together by weak van der Waals forces and can be delaminated by introducing tetramethylammonium $\\left(\\mathbf{TMA}^{+}\\right)$ ions that intercalate between the layers, forcing them apart. This results in a colloidal suspension of 2D MXene flakes. \n\nAnother series of washing cycles was used to remove the TMAOH, as detailed in Supporting Information. In brief, the mixture was centrifuged at $8000~\\mathrm{rpm}$ $\\left(8230\\ \\mathrm{rcf}\\right)$ for $30~\\mathrm{min}$ to settle the material and, after decanting the alkaline supernatant, the sediment was redispersed with DI water and this was repeated 5 times. High-speed centrifugation was needed due to the stability of the $\\mathrm{Mo_{4}V C_{4}}$ flakes in the alkaline solution. Once the decanted supernatant had a $\\mathrm{\\ttPH}<8.$ , the remaining sediment was redispersed in $30~\\mathrm{mL}$ of DI water and bath sonicated $\\langle100\\mathrm{W},40\\mathrm{kHz}\\rangle$ for $^\\mathrm{~1~h~}$ with argon bubbling through it. After sonication, the solution was centrifuged at $3500~\\mathrm{rpm}$ (2550 rcf) for $^{\\textrm{1h}}$ . The resulting supernatant was carefully removed with a pipet to avoid redispersal of, and contamination with, the multilayer MXene/MAX phase sediment and transferred into a separate bottle. \n\n$\\pmb{M_{0}}_{4}\\pmb{\\mathsf{V C}}_{4}$ Film Preparation. To obtain a free-standing film of $\\mathrm{Mo}_{4}\\mathrm{VC}_{4},$ the colloid containing delaminated MXene flakes was filtered by vacuum-assisted filtration through a Celgard membrane (Celgard $3501{-}64~\\mathrm{nm}$ porous polypropylene). The resulting MXene films were dried in a vacuum desiccator for $^{18\\mathrm{~h~}}$ at $25~^{\\circ}\\mathrm{C}$ . \n\nStructural Characterization. Crystal structures were characterized with XRD. Rigaku SmartLab and MiniFlex X-ray diffractometers were used and Ni-filtered $\\mathrm{Cu-K}\\alpha$ radiation was used at $40\\mathrm{kV}/30\\mathrm{mA}$ and $40\\ \\mathrm{kV}/15\\ \\mathrm{mA},$ , respectively. The step size of the scan was $0.01^{\\circ}$ with a step duration of $4s$ for the as-produced $\\mathrm{Mo_{4}V A l C_{4}}$ and $2\\:s$ for the multilayer $\\mathrm{Mo_{4}V C_{4}}$ powder and $\\mathrm{Mo_{4}V C_{4}}$ film. Supporting Table 1 provides the position of XRD peaks, $d$ spacings, and corresponding intensities for the as-prepared $\\mathrm{Mo_{4}V A l C_{4}}$ sample powder from $3^{\\circ}$ to $120^{\\circ}$ . \n\nMicroscopy. SEM micrographs were obtained with a Zeiss Supra 50VP scanning electron microscope and an FEI Strata DB235 Dual Beam Focused Ion Beam SEM. Transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), and selected area electron diffraction (SAED) were performed on a JEOL JEM F200 and JEOL NEOARM at an operating voltage of $200~\\mathrm{kV}$ . The colloid containing delaminated $\\mathrm{Mo_{4}V C_{4}}$ flakes and particles of $\\mathrm{Mo_{4}V A l C_{4}}$ and multilayer $\\mathrm{Mo_{4}V C_{4}}$ were drop-cast onto TEM grids. AFM was performed with a Bruker Multimode 8 with a Si tip (Budget Sensors Tap300Al-G; $f_{0}=300\\ \\mathrm{kHz},\\ k=40\\ \\mathrm{N/m})$ with a standard tapping mode in air. The colloid containing delaminated $\\mathrm{Mo_{4}V C_{4}}$ flakes was drop-cast onto oxygen plasma-cleaned $\\mathrm{SiO}_{2}/\\mathrm{Si}$ wafers for the AFM measurement. \n\nCompositional Characterization. Chemical compositions were determined by EDS measurements. EDS spectra of the MAX phase and multilayer MXene particles, drop-cast onto carbon tape, were recorded by a FEI Strata DB235 Dual Beam Focused Ion Beam SEM with EDS with $125\\ \\mathrm{kV}$ beam and an average of 360,000 counts per spectrum. High-resolution EDS spectra of the MAX and MXene atomic layers were recorded with a JEOL NEOARM operating in STEM mode at $200~\\mathrm{kV}$ . \n\nChemical compositions were also determined with XPS. XPS spectra were collected by a spectrometer (Physical Electronics, Versa Probe 5000, MN) using a monochromatic Al $\\mathrm{K}\\alpha$ X-ray source with $200\\ \\mu\\mathrm{m}$ spot size. Charge neutralization was performed using a dualbeam charge neutralizer. The sample was sputtered with Ar ions (2 $\\operatorname{kV},2\\ \\mu\\mathrm{A})$ for $2\\ \\mathrm{min}$ inside the analysis chamber. High-resolution spectra were collected at a pass energy of $23.5~\\mathrm{eV}$ with a step size of $0.05~\\mathrm{eV_{i}}$ whereas the survey spectra were collected at a pass energy of $117~\\mathrm{eV}$ with a step size of $0.5\\ \\mathrm{eV}.$ . The quantification and peak fitting of the core-level spectra was performed using Casa XPS software package with Shirley-type background. \n\nRaman spectra were obtained with an inverted reflection mode Renishaw (2008, Gloucestershire, UK) instrument, equipped with $63\\times$ $\\mathrm{\\left(NA=0.7\\right.}$ ) objectives and a diffraction-based room-temperature spectrometer. The laser line used was ${514}\\mathrm{nm}$ (Ar laser with 488 and ${514}~\\mathrm{{nm}}$ emissions) with an $1800\\ \\mathrm{line/mm}$ grating. The power of the laser was kept in the ${\\sim}0.5{-}1~\\mathrm{mW}$ range. Mapping was performed by raster scanning in the streamline mode at a $0.5\\mu$ x-axis step, the final spectra were an average of all collected data. Fitting was performed in Renishaw WiRE 3.4 software. The $\\mathrm{Mo_{4}V A l C_{4}}$ MAX phase and $\\mathrm{Mo_{4}V C_{4}}$ multilayer MXene powder were pressed in a $13\\mathrm{-mm}.$ - diameter die to form pellets that were analyzed with the spectrometer. \n\nOptical Properties. UV−vis-NIR spectrophotometry spectra were obtained by spray-coating thin films of $\\mathrm{Mo_{4}V C_{4}}$ onto oxygen plasma-cleaned glass slides. Films of various thickness were measured with UV−vis-NIR spectrophotometry from 300 to $1000\\ \\mathrm{nm}$ (Thermo Scientific Evolution 201) and from 1100 to $2500~\\mathrm{{nm}}$ (Nicolet iS50R FT-IR) operating in transmission mode. Glass slides were used as a blank. Transmission was measured on three locations on each film and the average spectra are reported. Thin film surface roughness values were obtained by optical profilometry measurements (VKseries, Keyence). Optical properties of MXene colloidal solutions were measured in a concentration range between 0.01 and $0.04{\\mathrm{~mg}}$ $\\mathrm{mL}^{-1}$ . A $10\\mathrm{mm}$ path length quartz cuvette filled with deionized water was used as a blank. The measured extinction was normalized to the path length $(\\mathrm{Ext}/1)$ , plotted versus concentration, and fit to the Beer Lambert equation, where the extinction coefficient was calculated from the slope of the linear trend. The analysis was conducted at 550 nm and from $200{-}1000\\ \\mathrm{nm}$ . \n\nElectrical Properties. Electrical resistivity was measured using a Jandel cylindrical four-point probe with a ResTest Test Unit. The thickness of $\\mathrm{Mo_{4}V C_{4}}$ MXene films was measured with a micrometer. The thickness of each film and the resistivity were measured at 10 places on each film and the average values are reported. \n\nTemperature-dependence of resistivity and Hall measurements were performed in physical property measurement system (PPMS, Evercool II, Quantum Design). Free-standing MXene films were wired to the PPMS sample holder using silver wire and silver paint in 4-point and van de Pauw configurations. The resistance of the film was recorded from 10 to $300~\\mathrm{K}$ with a heating/cooling rate of $4~\\mathrm{K}/\\AA$ min. Magnetoresistance (MR) and Hall resistance were measured at $10\\mathrm{~K~}$ with a magnetic field up to $5\\mathrm{~T~}$ applied perpendicular to the sample surface. \n\nThermal Analysis. The thermal stability of a $\\mathrm{Mo}_{4}\\mathrm{VC}_{4}$ film was studied by thermogravimetric analysis (SDT 650, TA Instruments) connected to a mass spectrometer (Discovery, TA Instruments). Freestanding MXene films with masses around ${\\mathfrak{s}}\\operatorname{mg}$ were packed in a 90 $\\mu\\mathrm{L}$ alumina pan and heated to $1500~^{\\circ}\\mathrm{C}$ at a constant heating rate of $10~\\mathrm{^{\\circ}C/m i n}$ under Ar atmosphere $(100\\ \\mathrm{mL}/\\mathrm{min}),$ ). The furnace was purged with Ar gas $\\left(100\\mathrm{\\mL/min}\\right)$ for $^\\textrm{\\scriptsize1h}$ before the analysis to remove air residue. \n\nDensity Functional Theory Calculations. The Vienna Ab-Initio Simulation Package $\\mathrm{(VASP)}^{79}$ was used for all DFT calculations. Structural relaxations were performed with the Perdew−Burke− Ernzerhof (PBE)80 exchange-correlation functional and projector augmented wave (PAW) pseudopotentials,81 with a $520~\\mathrm{eV}$ planewave basis cutoff, a $8\\times8\\times1$ Γ centered k-point mesh for structural relaxations, and forces on each atom converged to below $10^{-2}~\\mathrm{eV/\\mathring{A}}$ . Electronic property calculations and total energies were converged to $10^{-8}\\mathrm{eV}$ and a dense $18\\times18\\times1\\Gamma$ centered $k$ -point mesh was used. 2 $\\times\\ 2\\times\\ 1$ supercells (with 32 Mo atoms and $\\textsuperscript{8\\ V}$ atoms) were constructed to approximate disordered $\\mathrm{Mo_{4}V C_{4}}$ solid-solutions. The Mo:V composition of 4:1 was kept fixed in all solid-solution calculations and 18 configurations were generated by randomly positioning the Mo and $\\mathrm{\\DeltaV}$ atoms in the structure. Meshes were adjusted appropriately for $2\\ \\times\\ 2\\ \\times\\ 1$ supercell solid-solution calculations. We have optimized the ordered and ground state disordered $\\mathrm{Mo_{4}V A l C_{4}}$ structures with the PBEsol functional.82 The a and $\\mathbf{\\Phi}_{c}$ lattice constants change by less than $1\\%$ compared to calculations with PBE, and the solid-solutions are more favorable than the ordered configurations, regardless of functional choice. We have used reference energies from the Materials Project. The calculations for the stabilities of other $\\mathbf{M^{\\prime}}_{4}\\mathbf{M^{\\prime\\prime}A l C}_{4}$ MAX phases were limited to ordered phases where $\\mathbf{{M}^{\\prime\\prime}}$ was sandwiched between two atomic layers of $\\mathbf{M}^{\\prime}$ on both sides. Calculations of formation energies relative to the most stable unary phases provide trends in stability. However, the materials with negative formation energies could decompose into competing binary carbide, intermetallic, or other MAX phases that are more stable. Likewise, there may be materials with more stable solid-solution phases that have not been considered here. The work presented here is meant to provide trends in stability as a function of M element composition. \n\n# ASSOCIATED CONTENT \n\n# $\\otimes$ Supporting Information \n\nThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsnano.9b07708. \n\nAdditional results from the synthesis of $\\mathrm{Mo_{4}V A l C_{4}},$ including detailed synthesis procedure for washing and etching $\\mathrm{Mo_{4}V A l C_{4}}$ and delamination of $\\mathrm{Mo_{4}V C_{4}}$ MXene; optimization of the delamination process; TEM micrographs; high-resolution EDS line scan of the MAX phase structure; XPS results; overlaid version of the electrical resistivity; UV−vis-NIR extinction and transmission spectra; XRD and DFT exact values; sample crystal structures used for the DFT calculations. (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Authors \n$^*\\mathrm{E}$ -mail: gogotsi@drexel.edu. \n$^*\\mathrm{E}$ -mail: banasori@iupui.edu. \nORCID \nGrayson Deysher: 0000-0003-0482-8991 \nChristopher Eugene Shuck: 0000-0002-1274-8484 \n\nKanit Hantanasirisakul: 0000-0002-4890-1444 \nNathan C. Frey: 0000-0001-5291-6131 \nAlexandre C. Foucher: 0000-0001-5042-4002 \nKathleen Maleski: 0000-0003-4032-7385 \nEric A. Stach: 0000-0002-3366-2153 \nBabak Anasori: 0000-0002-1955-253X \nYury Gogotsi: 0000-0001-9423-4032 \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis work was funded by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, grant #DE-SC0018618. The authors would like to acknowledge the usage of the XRD, XPS, and SEM/EDS instrumentation provided by Drexel University Core Research Facility (CRF) and the University of Pennsylvania. C. Hatter (Drexel University) is acknowledged for providing additional TEM micrographs. Y. Yang and S. J. May (Drexel University) are acknowledged for helping with temperature-dependence of resistivity measurements. A. Fafarman (Drexel University) is acknowledged for access to the vis-NIR machine. V.B.S acknowledges support from the Army Research Office by contract W911NF-16-1-0447 and also grants CMMI-1727717 and EFMA-542879 from the National Science Foundation. N.C.F. was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. This work was performed in part at the Singh Center for Nanotechnology at the University of Pennsylvania, a member of the National Nanotechnology Coordinated Infrastructure (NNCI) network, which is supported by the National Science Foundation (Grant NNCI-1542153). The authors gratefully acknowledge use of facilities and instrumentation supported by NSF through the University of Pennsylvania Materials Research Science and Engineering Center (MRSEC) (DMR-1720530). This research used resources of the Center for Functional Nanomaterials, which is a U.S. DOE Office of Science Facility, at Brookhaven National Laboratory under Contract No. DESC0012704. A.C.F. acknowledges support from Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), under Award # DE-SC0012573. \n\n# REFERENCES \n\n(1) Wang, ${\\textsc{Q}}{\\mathrm{~H}}.$ .; Kalantar-Zadeh, K.; Kis, A.; Coleman, J. N.; Strano, M. S. Electronics and Optoelectronics of Two-Dimensional Transition Metal Dichalcogenides. Nat. Nanotechnol. 2012, 7, 699− 712. \n(2) Bonaccorso, F.; Sun, Z.; Hasan, T.; Ferrari, A. Graphene Photonics and Optoelectronics. Nat. Photonics 2010, 4, 611. \n(3) Shao, Y.; Wang, J.; Wu, H.; Liu, J.; Aksay, I. A.; Lin, Y. Graphene Based Electrochemical Sensors and Biosensors: A Review. Electroanalysis 2010, 22, 1027−1036. \n(4) Watanabe, K.; Taniguchi, T.; Kanda, H. Direct-bandgap Properties and Evidence for Ultraviolet Lasing of Hexagonal Boron Nitride Single Crystal. Nat. Mater. 2004, 3, 404. \n(5) Naguib, M.; Kurtoglu, M.; Presser, V.; Lu, J.; Niu, J. J.; Heon, M.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Nanocrystals Produced by Exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 2011, 23, 4248−4253. (6) Anasori, B.; Lukatskaya, M. R.; Gogotsi, Y. 2D Metal Carbides and Nitrides (MXenes) for Energy Storage. Nat. Rev. Mater. 2017, 2, 16098. \n(7) Tao, $\\mathrm{Q.;}$ Dahlqvist, M.; Lu, J.; Kota, S.; Meshkian, R.; Halim, J.; Palisaitis, J.; Hultman, L.; Barsoum, M. W.; Persson, P. O. TwoDimensional $\\mathbf{Mo}_{1.33}\\mathbf{C}$ MXene with Divacancy Ordering Prepared from Parent 3D Laminate with In-Plane Chemical Ordering. Nat. Commun. 2017, 8, 14949. \n(8) Yang, J.; Naguib, M.; Ghidiu, M.; Pan, L. M.; Gu, J.; Nanda, J.; Halim, J.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Nb-Based $\\mathbf{M}_{4}\\mathbf{C}_{3}$ Solid Solutions (MXenes). J. Am. Ceram. Soc. 2016, 99, 660− 665. \n(9) Lukatskaya, M. R.; Mashtalir, O.; Ren, C. E.; Dall’Agnese, Y.; Rozier, P.; Taberna, P. L.; Naguib, M.; Simon, P.; Barsoum, M. W.; Gogotsi, Y. Cation Intercalation and High Volumetric Capacitance of Two-Dimensional Titanium Carbide. Science 2013, 341, 1502−1505. (10) Huang, K.; Li, Z.; Lin, J.; Han, G.; Huang, P. Two-Dimensional Transition Metal Carbides and Nitrides (MXenes) for Biomedical Applications. Chem. Soc. Rev. 2018, 47, 5109−5124. \n(11) Hantanasirisakul, K.; Zhao, M. $\\mathrm{Q.;}$ Urbankowski, P.; Halim, J.; Anasori, B.; Kota, S.; Ren, C. E.; Barsoum, M. W.; Gogotsi, Y. Fabrication of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene Transparent Thin Films with Tunable Optoelectronic Properties. Adv. Electron. Mater. 2016, 2, 1600050. (12) Salles, P.; Pinto, D.; Hantanasirisakul, K.; Maleski, ${\\mathrm{K}}.{\\mathrm{}}$ Shuck, C. E.; Gogotsi, Y. Electrochromic Effect in Titanium Carbide MXene Thin Films Produced by Dip-Coating. Adv. Funct. Mater. 2019, 29, 1809223. \n(13) Alhabeb, M.; Maleski, K.; Anasori, B.; Lelyukh, P.; Clark, L.; Sin, S.; Gogotsi, Y. Guidelines for Synthesis and Processing of TwoDimensional Titanium Carbide $\\mathrm{\\Ti}_{3}\\mathrm C_{2}\\mathrm T_{\\boldsymbol x}$ MXene). Chem. Mater. 2017, 29, 7633−7644. \n(14) Dillon, A. D.; Ghidiu, M. J.; Krick, A. L.; Griggs, J.; May, S. J.; Gogotsi, Y.; Barsoum, M. W.; Fafarman, A. T. Highly Conductive Optical Quality Solution-Processed Films of 2D Titanium Carbide. Adv. Funct. Mater. 2016, 26, 4162−4168. \n(15) Naguib, M.; Halim, J.; Lu, J.; Cook, K. M.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. New Two-Dimensional Niobium and Vanadium Carbides as Promising Materials for Li-Ion Batteries. J. Am. Chem. Soc. 2013, 135, 15966−15969. \n(16) Gao, G.; O’Mullane, A. P.; Du, A. 2D MXenes: A New Family of Promising Catalysts for the Hydrogen Evolution Reaction. ACS Catal. 2017, 7, 494−500. \n(17) Ran, J.; Gao, G.; Li, F.-T.; Ma, T.-Y.; Du, A.; Qiao, S.-Z. $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene Co-Catalyst on Metal Sulfide Photo-Absorbers for Enhanced Visible-Light Photocatalytic Hydrogen Production. Nat. Commun. 2017, 8, 13907. \n(18) Sarycheva, A.; Polemi, A.; Liu, Y.; Dandekar, K.; Anasori, B.; Gogotsi, Y. 2D Titanium Carbide (MXene) for Wireless Communication. Sci. Adv. 2018, 4, No. eaau0920. \n(19) Shahzad, F.; Alhabeb, M.; Hatter, C. B.; Anasori, B.; Hong, S. M.; Koo, C. M.; Gogotsi, Y. Electromagnetic Interference Shielding with 2D Transition Metal Carbides (MXenes). Science 2016, 353, 1137−1140. \n(20) Han, M.; Yin, X.; Hantanasirisakul, K.; Li, X.; Iqbal, A.; Hatter, C. B.; Anasori, B.; Koo, C. M.; Torita, T.; Soda, Y. Anisotropic MXene Aerogels with a Mechanically Tunable Ratio of Electromagnetic Wave Reflection to Absorption. Adv. Opt. Mater. 2019, 7, 1900267. \n(21) Kim, S. J.; Koh, H.-J.; Ren, C. E.; Kwon, O.; Maleski, K.; Cho, S.-Y.; Anasori, B.; Kim, C.-K.; Choi, Y.-K.; Kim, J. Metallic $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene Gas Sensors with Ultrahigh Signal-to-Noise Ratio. ACS Nano 2018, 12, 986−993. \n(22) Hantanasirisakul, K.; Gogotsi, Y. Electronic and Optical Properties of 2D Transition Metal Carbides and Nitrides (MXenes). Adv. Mater. 2018, 30, 1804779. \n(23) Hart, J. L.; Hantanasirisakul, K.; Lang, A. C.; Anasori, B.; Pinto, D.; Pivak, Y.; van Omme, J. T.; May, S. J.; Gogotsi, Y.; Taheri, M. L. Control of MXenes’ Electronic Properties through Termination and Intercalation. Nat. Commun. 2019, 10, 522. \n\n(24) Shuck, C. E.; Han, M.; Maleski, K.; Hantanasirisakul, $\\mathrm{K.},$ Kim, S. J.; Choi, J.; Reil, W.; Gogotsi, Y. Effect of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX Phase on Structure and Properties of Resultant $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene. ACS Appl. Nano Mater. 2019, 2, 3368−3376. (25) Hantanasirisakul, K.; Alhabeb, M.; Lipatov, A.; Maleski, K.; Anasori, B.; Salles, P.; Ieosakulrat, C.; Pakawatpanurut, P.; Sinitskii, A.; May, S. J. Effects of Synthesis and Processing on Optoelectronic Properties of Titanium Carbonitride MXene. Chem. Mater. 2019, 31, 2941−2951. (26) Seredych, M.; Shuck, C. E.; Pinto, D.; Alhabeb, M.; Precetti, E.; Deysher, G.; Anasori, B.; Kurra, N.; Gogotsi, Y. High-Temperature Behavior and Surface Chemistry of Carbide MXenes Studied by Thermal Analysis. Chem. Mater. 2019, 31, 3324−3332. (27) Kim, H.; Anasori, B.; Gogotsi, Y.; Alshareef, H. N. Thermoelectric Properties of Two-Dimensional Molybdenum-Based MXenes. Chem. Mater. 2017, 29, 6472−6479. (28) Bao, W.; Shuck, C. E.; Zhang, W.; Guo, X.; Gogotsi, Y.; Wang, G. Boosting Performance of $_{\\mathrm{Na-S}}$ Batteries Using Sulfur-Doped $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene Nanosheets with a Strong Affinity to Sodium Polysulfides. ACS Nano 2019, 13, 11500−11509. (29) Soundiraraju, B.; George, B. K. Two-Dimensional Titanium Nitride $\\left(\\mathrm{Ti}_{2}\\mathbf{N}\\right)$ MXene: Synthesis, Characterization, and Potential Application as Surface-Enhanced Raman Scattering Substrate. ACS Nano 2017, 11, 8892−8900. (30) Urbankowski, P.; Anasori, B.; Hantanasirisakul, K.; Yang, L.; Zhang, L.; Haines, B.; May, S. J.; Billinge, S. J.; Gogotsi, Y. 2D Molybdenum and Vanadium Nitrides Synthesized by Ammoniation of 2D Transition Metal Carbides (MXenes). Nanoscale 2017, 9, 17722− 17730. (31) Kurtoglu, M.; Naguib, M.; Gogotsi, Y.; Barsoum, M. W. First Principles Study of Two-Dimensional Early Transition Metal Carbides. MRS Commun. 2012, 2, 133−137. (32) Meshkian, R.; Näslund, L.-Å.; Halim, J.; Lu, J.; Barsoum, M. W.; Rosen, J. Synthesis of Two-Dimensional Molybdenum Carbide, ${\\bf M o}_{2}{\\bf C},$ from the Gallium Based Atomic Laminate $\\mathbf{Mo}_{2}\\mathbf{Ga}_{2}\\mathbf{C}$ . Scr. Mater. 2015, 108, 147−150. (33) Abdelmalak, M. N. MXenes: A New Family of Two-Dimensional Materials and its Application as Electrodes for Li-Ion Batteries; Drexel University: Philadelphia, 2014. (34) Meshkian, R.; Dahlqvist, M.; Lu, J.; Wickman, B.; Halim, J.; Thörnberg, J.; Tao, $\\mathrm{Q.;}$ Li, S.; Intikhab, S.; Snyder, J. W-Based Atomic Laminates and Their 2D Derivative $\\mathsf{W}_{1.33}\\mathrm{C}$ MXene with Vacancy Ordering. Adv. Mater. 2018, 30, 1706409. (35) Halim, J.; Palisaitis, J.; Lu, J.; Thörnberg, J.; Moon, E.; Precner, M.; Eklund, P.; Persson, P. Å.; Barsoum, M.; Rosen, J. Synthesis of Two-Dimensional $\\mathrm{Nb}_{1.33}\\mathrm{C}$ (MXene) with Randomly Distributed Vacancies by Etching of the Quaternary Solid Solution $(\\mathrm{Nb}_{2/3}\\mathrm{Sc}_{1/3})_{2}\\mathrm{AlC}$ MAX Phase. ACS Appl. Nano Mater. 2018, 1, 2455−2460. (36) Persson, I.; El Ghazaly, A.; Tao, $\\mathrm{Q.;}$ Halim, J.; Kota, S.; Darakchieva, V.; Palisaitis, J.; Barsoum, M. W.; Rosen, J.; Persson, P. O. Tailoring Structure, Composition, and Energy Storage Properties of MXenes from Selective Etching of In-Plane, Chemically Ordered MAX Phases. Small 2018, 14, 1703676. (37) Naguib, M.; Mashtalir, O.; Carle, J.; Presser, V.; Lu, J.; Hultman, L.; Gogotsi, Y.; Barsoum, M. W. Two-Dimensional Transition Metal Carbides. ACS Nano 2012, 6, 1322−1331. (38) Zhou, J.; Zha, X.; Zhou, X.; Chen, F.; Gao, G.; Wang, S.; Shen, C.; Chen, T.; Zhi, C.; Eklund, P. Synthesis and Electrochemical Properties of Two-Dimensional Hafnium Carbide. ACS Nano 2017, 11, 3841−3850. (39) Zhou, J.; Zha, X.; Chen, F. Y.; Ye, $\\mathrm{Q.;}$ Eklund, P.; Du, S.; Huang, $\\scriptstyle\\mathrm{Q}\\$ A Two-Dimensional Zirconium Carbide by Selective Etching of $\\mathrm{Al}_{3}\\mathrm{C}_{3}$ from Nanolaminated $\\mathrm{Zr}_{3}\\mathrm{Al}_{3}\\mathrm{C}_{5}$ . Angew. Chem. 2016, 128, 5092−5097. (40) Anasori, B.; Xie, Y.; Beidaghi, M.; Lu, J.; Hosler, B. C.; Hultman, L.; Kent, P. R.; Gogotsi, Y.; Barsoum, M. W. TwoDimensional, Ordered, Double Transition Metals Carbides (MXenes). ACS Nano 2015, 9, 9507−9516. \n\n(41) Meshkian, R.; Tao, $\\mathrm{Q.;}$ Dahlqvist, M.; Lu, J.; Hultman, L.; Rosen, J. Theoretical Stability and Materials Synthesis of a Chemically Ordered MAX Phase, $\\mathrm{Mo}_{2}S{\\mathrm{cAlC}_{2}},$ and Its Two-Dimensional Derivate ${\\bf M o}_{2}S c C_{2}$ MXene. Acta Mater. 2017, 125, 476−480. \n(42) Urbankowski, P.; Anasori, B.; Makaryan, T.; Er, D.; Kota, S.; Walsh, P. L.; Zhao, M.; Shenoy, V. B.; Barsoum, M. W.; Gogotsi, Y. Synthesis of Two-Dimensional Titanium Nitride $\\mathrm{Ti}_{4}\\mathrm{N}_{3}$ (MXene). Nanoscale 2016, 8, 11385−11391. \n(43) Tran, M. H.; Schäfer, T.; Shahraei, A.; Dürrschnabel, M.; Molina-Luna, L.; Kramm, U. I.; Birkel, C. S. Adding a New Member to the MXene Family: Synthesis, Structure, and Electrocatalytic Activity for the Hydrogen Evolution Reaction of $\\mathrm{V}_{4}\\mathrm{C}_{3}\\mathrm{T}_{x}.$ ACS Appl. Energy Mater. 2018, 1, 3908−3914. \n(44) Ghidiu, M.; Naguib, M.; Shi, C.; Mashtalir, O.; Pan, L.; Zhang, B.; Yang, J.; Gogotsi, Y.; Billinge, S. J.; Barsoum, M. W. Synthesis and Characterization of Two-Dimensional $\\mathrm{Nb}_{4}\\mathrm{C}_{3}$ (MXene). Chem. Commun. 2014, 50, 9517−9520. \n(45) Tan, T. L.; Jin, H. M.; Sullivan, M. B.; Anasori, B.; Gogotsi, Y. High-Throughput Survey of Ordering Configurations in MXene Alloys Across Compositions and Temperatures. ACS Nano 2017, 11, 4407−4418. \n(46) Khazaei, M.; Ranjbar, A.; Esfarjani, K.; Bogdanovski, D.; Dronskowski, R.; Yunoki, S. Insights into Exfoliation Possibility of MAX Phases to MXenes. Phys. Chem. Chem. Phys. 2018, 20, 8579− 8592. \n(47) Alhabeb, M.; Maleski, K.; Mathis, T. S.; Sarycheva, A.; Hatter, C. B.; Uzun, S.; Levitt, A.; Gogotsi, Y. Selective Etching of Silicon from $\\mathrm{Ti}_{3}\\mathrm{SiC}_{2}$ (MAX) to Obtain 2D Titanium Carbide (MXene). Angew. Chem., Int. Ed. 2018, 57, 5444−5448. \n(48) Lin, Z.; Zhuo, M.; Zhou, Y.; Li, M.; Wang, J. Microstructures and Theoretical Bulk Modulus of Layered Ternary Tantalum Aluminum Carbides. J. Am. Ceram. Soc. 2006, 89, 3765−3769. (49) Zhang, J.; Liu, B.; Wang, J.; Zhou, Y. Low-Temperature Instability of $\\mathrm{Ti}_{2}\\mathrm{SnC}$ : A Combined Transmission Electron Microscopy, Differential Scanning Calorimetry, and X-Ray Diffraction Investigations. J. Mater. Res. 2009, 24, 39−49. \n(50) Zheng, L.; Wang, J.; Lu, X.; Li, F.; Wang, J.; Zhou, Y. $(\\mathrm{Ti}_{0.5}\\mathrm{Nb}_{0.5})_{5}\\mathrm{AlC}_{4}$ : A New-Layered Compound Belonging to MAX Phases. J. Am. Ceram. Soc. 2010, 93, 3068−3071. \n(51) Xie, Y.; Kent, P. Hybrid Density Functional Study of Structural and Electronic Properties of Functionalized $\\mathrm{Ti}_{\\mathrm{n+1}}\\mathrm{X}_{\\mathrm{n}}$ ( $\\mathrm{\\:\\left.X=\\right.}$ C, N) Monolayers. Phys. Rev. B: Condens. Matter Mater. Phys. 2013, 87, 235441. \n(52) Zhou, Y.; Sun, Z. Electronic Structure and Bonding Properties of Layered Machinable $\\mathrm{Ti}_{2}\\mathrm{AlC}$ and $\\mathrm{Ti}_{2}\\mathrm{AlN}$ ceramics. Phys. Rev. B: Condens. Matter Mater. Phys. 2000, 61, 12570. \n(53) Tzenov, N. V.; Barsoum, M. W. Synthesis and Characterization of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . J. Am. Ceram. Soc. 2000, 83, 825−832. \n(54) Lin, Z.; Zhuo, M.; Zhou, Y.; Li, M.; Wang, J. Structural Characterization of a New Layered-Ternary $\\mathrm{Ta}_{4}\\mathrm{AlC}_{3}$ Ceramic. J. Mater. Res. 2006, 21, 2587−2592. \n(55) Lipatov, A.; Lu, H.; Alhabeb, M.; Anasori, B.; Gruverman, A.; Gogotsi, Y.; Sinitskii, A. Elastic Properties of 2D $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene Monolayers and Bilayers. Sci. Adv. 2018, 4, No. eaat0491. \n(56) Newbury, D. E. Standardless Quantitative Electron-Excited XRay Microanalysis by Energy-Dispersive Spectrometry: What is Its Proper Role? Microsc. Microanal. 1998, 4, 585−597. \n(57) Naguib, M.; Unocic, R. R.; Armstrong, B. L.; Nanda, J. LargeScale Delamination of Multi-Layers Transition Metal Carbides and Carbonitrides “MXenes. Dalton Trans 2015, 44, 9353−9358. \n(58) Anasori, B.; Shi, C.; Moon, E. J.; Xie, Y.; Voigt, C. A.; Kent, P. R.; May, S. J.; Billinge, S. J.; Barsoum, M. W.; Gogotsi, Y. Control of Electronic Properties of 2D Carbides (MXenes) by Manipulating Their Transition Metal Layers. Nanoscale Horiz 2016, 1, 227−234. (59) Halim, J.; Kota, S.; Lukatskaya, M. R.; Naguib, M.; Zhao, M. $\\mathrm{Q.;}$ Moon, E. J.; Pitock, J.; Nanda, J.; May, S. J.; Gogotsi, Y. Synthesis and Characterization of 2D Molybdenum Carbide (MXene). Adv. Funct. Mater. 2016, 26, 3118−3127. (60) Halim, J.; Cook, K. M.; Naguib, M.; Eklund, P.; Gogotsi, Y.; Rosen, J.; Barsoum, M. W. X-Ray Photoelectron Spectroscopy of Select Multi-Layered Transition Metal Carbides (MXenes). Appl. Surf. Sci. 2016, 362, 406−417. \n(61) Seh, Z. W.; Fredrickson, K. D.; Anasori, B.; Kibsgaard, J.; Strickler, A. L.; Lukatskaya, M. R.; Gogotsi, Y.; Jaramillo, T. F.; Vojvodic, A. Two-Dimensional Molybdenum Carbide (MXene) as an Efficient Electrocatalyst for Hydrogen Evolution. ACS Energy Lett. 2016, 1, 589−594. \n(62) Etzkorn, J.; Ade, M.; Hillebrecht, H. $\\mathrm{V}_{2}\\mathrm{AlC}$ , $\\mathrm{V}_{4}\\mathrm{AlC}_{3-x}$ (x≈ 0.31), and $\\mathrm{V}_{12}\\mathrm{Al}_{3}\\mathrm{C}_{8}$ : Synthesis, Crystal Growth, Structure, and Superstructure. Inorg. Chem. 2007, 46, 7646−7653. \n(63) Dahlqvist, M.; Alling, B.; Rosén, J. Stability Trends of MAX Phases from First Principles. Phys. Rev. B: Condens. Matter Mater. Phys. 2010, 81, 220102. \n(64) Zeiger, M.; Ariyanto, T.; Krüner, B.; Peter, N. J.; Fleischmann, S.; Etzold, B. J.; Presser, V. Vanadium Pentoxide/carbide-derived Carbon Core−Shell Hybrid Particles for High Performance Electrochemical Energy Storage. J. Mater. Chem. A 2016, 4, 18899−18909. (65) Li, T.; Luo, W.; Kitadai, H.; Wang, X.; Ling, X. Probing the Domain Architecture in 2D Alpha- $\\mathsf{M o}_{2}\\mathrm{C}$ via Polarized Raman. Adv. Mater. 2019, 31, 1807160. \n(66) Sun, Y.; Cui, H.; Gong, L.; Chen, J.; She, J.; Ma, Y.; Shen, P.; Wang, C. Carbon-in- ${\\bf\\cdot A l_{4}C}_{3}$ Nanowire Superstructures for Field Emitters. ACS Nano 2011, 5, 932−941. \n(67) Hu, T.; Hu, M.; Li, Z.; Zhang, H.; Zhang, C.; Wang, J.; Wang, X. Covalency-Dependent Vibrational Dynamics in Two-Dimensional Titanium Carbides. J. Phys. Chem. A 2015, 119, 12977−12984. (68) Hu, T.; Wang, J.; Zhang, H.; Li, Z.; Hu, M.; Wang, X. Vibrational Properties of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{2}$ $(\\mathrm{T}=\\ 0,$ , F, OH) Monosheets by First-Principles Calculations: A Comparative Study. Phys. Chem. Chem. Phys. 2015, 17, 9997−10003. \n(69) Zhao, S.; Meng, X.; Zhu, K.; Du, F.; Chen, G.; Wei, Y.; Gogotsi, Y.; Gao, Y. Li-Ion Uptake and Increase in Interlayer Spacing of $\\mathrm{Nb}_{4}\\mathrm{C}_{3}$ MXene. Energy Storage Mater. 2017, 8, 42−48. \n(70) Gouadec, G.; Colomban, P. Raman Spectroscopy of Nanomaterials: How Spectra Relate to Disorder, Particle Size and Mechanical Properties. Prog. Cryst. Growth Charact. Mater. 2007, 53, 1−56. (71) Yang, S.; Evmiridis, N. Synthesis of Omega Zeolite Without Use of Tetramethylammonium (TMA) Ions. In Studies in Surfuce Science and Catalysis, Weitkamp, J.; Karge, H. G.; Pfeifer, H.; Hölderich, W., Eds.; Elsevier: New York, 1994; Vol. 84, pp 155−162. (72) Ouisse, T.; Barsoum, M. W. Magnetotransport in the MAX Phases and Their 2D Derivatives: MXenes. Mater. Res. Lett. 2017, 5, 365−378. \n(73) Kasap, S. O. Principles of Electronic Materials and Devices; McGraw-Hill: New York, 2006; Vol. 2. \n(74) Ying, G.; Kota, S.; Dillon, A. D.; Fafarman, A. T.; Barsoum, M. W. Conductive Transparent $\\mathrm{V}_{2}\\mathrm{CT}_{x}$ (MXene) Films. FlatChem. 2018, 8, 25−30. \n(75) Ashton, M.; Hennig, R. G.; Broderick, S. R.; Rajan, K.; Sinnott, S. B. Computational Discovery of Stable $\\mathbf{M}_{2}\\mathbf{AX}$ Phases. Phys. Rev. B: Condens. Matter Mater. Phys. 2016, 94, 054116. \n(76) Van De Walle, A.; Asta, M.; Ceder, G. The Alloy Theoretic Automated Toolkit: A User Guide. CALPHAD: Comput. Coupling Phase Diagrams Thermochem. 2002, 26, 539−553. \n(77) Sokol, M.; Natu, V.; Kota, S.; Barsoum, M. W. On the Chemical Diversity of the MAX Phases. Trends in Chem. 2019, 1, 210−223. \n(78) Frey, N. C.; Wang, J.; Vega Bellido, G. I. n.; Anasori, B.; Gogotsi, Y.; Shenoy, V. B. Prediction of Synthesis of 2D Metal Carbides and Nitrides (MXenes) and Their Precursors with Positive and Unlabeled Machine Learning. ACS Nano 2019, 13, 3031−3041. (79) Kresse, G.; Furthmüller, J. Efficient Iterative Schemes for Ab Initio Total-Energy Calculations Using a Plane-Wave Basis Set. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 11169. \n(80) Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865. (81) Kresse, G.; Joubert, D. From Ultrasoft Pseudopotentials to the Projector Augmented-Wave Method. Phys. Rev. B: Condens. Matter Mater. Phys. 1999, 59, 1758. \n(82) Perdew, J. P.; Ruzsinszky, A.; Csonka, G. I.; Vydrov, O. A.; Scuseria, G. E.; Constantin, L. A.; Zhou, X.; Burke, K. Restoring the Density-Gradient Expansion for Exchange in Solids and Surfaces. Phys. Rev. Lett. 2008, 100, 136406. " + }, + { + "id": "10.1038_s41586-020-2285-x", + "DOI": "10.1038/s41586-020-2285-x", + "DOI Link": "http://dx.doi.org/10.1038/s41586-020-2285-x", + "Relative Dir Path": "mds/10.1038_s41586-020-2285-x", + "Article Title": "A biomimetic eye with a hemispherical perovskite nullowire array retina", + "Authors": "Gu, LL; Poddar, S; Lin, YJ; Long, ZH; Zhang, DQ; Zhang, QP; Shu, L; Qiu, X; Kam, M; Javey, A; Fan, ZY", + "Source Title": "NATURE", + "Abstract": "A biomimetic electrochemical eye is presented that has a hemispherical retina made from a high-density array of perovskite nullowires that are sensitive to light, mimicking the photoreceptors of a biological retina. Human eyes possess exceptional image-sensing characteristics such as an extremely wide field of view, high resolution and sensitivity with low aberration(1). Biomimetic eyes with such characteristics are highly desirable, especially in robotics and visual prostheses. However, the spherical shape and the retina of the biological eye pose an enormous fabrication challenge for biomimetic devices(2,3). Here we present an electrochemical eye with a hemispherical retina made of a high-density array of nullowires mimicking the photoreceptors on a human retina. The device design has a high degree of structural similarity to a human eye with the potential to achieve high imaging resolution when individual nullowires are electrically addressed. Additionally, we demonstrate the image-sensing function of our biomimetic device by reconstructing the optical patterns projected onto the device. This work may lead to biomimetic photosensing devices that could find use in a wide spectrum of technological applications.", + "Times Cited, WoS Core": 517, + "Times Cited, All Databases": 550, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000534818200010", + "Markdown": "# Article \n\n# A biomimetic eye with a hemispherical perovskite nanowire array retina \n\nhttps://doi.org/10.1038/s41586-020-2285-x \n\nReceived: 10 April 2019 \n\nAccepted: 17 March 2020 \n\nPublished online: 20 May 2020 Check for updates \n\nLeilei Gu1, Swapnadeep Poddar1, Yuanjing Lin1,2, Zhenghao Long1, Daquan Zhang1, Qianpeng Zhang1, Lei Shu1, Xiao Qiu1, Matthew Kam1, Ali Javey2,3 & Zhiyong Fan1 ✉ \n\nHuman eyes possess exceptional image-sensing characteristics such as an extremely wide field of view, high resolution and sensitivity with low aberration1. Biomimetic eyes with such characteristics are highly desirable, especially in robotics and visual prostheses. However, the spherical shape and the retina of the biological eye pose an enormous fabrication challenge for biomimetic devices2,3. Here we present an electrochemical eye with a hemispherical retina made of a high-density array of nanowires mimicking the photoreceptors on a human retina. The device design has a high degree of structural similarity to a human eye with the potential to achieve high imaging resolution when individual nanowires are electrically addressed. Additionally, we demonstrate the image-sensing function of our biomimetic device by reconstructing the optical patterns projected onto the device. This work may lead to biomimetic photosensing devices that could find use in a wide spectrum of technological applications. \n\nBiological eyes are arguably the most important sensing organ for most of the animals on this planet. In fact, our brains acquire more than $80\\%$ of information about our surroundings via our eyes4. A human eye with a concavely hemispherical retina and light-management components is particularly notable for its exceptional characteristics including a wide field of view (FOV) of $150^{\\circ}-160^{\\circ}$ , a high resolution of 1 arcmin per line pair at the fovea and excellent adaptivity to the optical environment1. Particularly, the domed shape of the retina has the merit of reducing the complexity of optical systems by directly compensating the aberration from the curved focal plane5. Mimicking human eyes, artificial vision systems are just as essential in autonomous technologies such as robotics. Particularly for humanoid robots, the vision system should resemble that of a human in appearance to enable amicable human–robot interaction, in addition to having superior device characteristics. In principle, a hemispherical image sensor design mimicking that of the human retina can achieve this goal. However, commercial charge-coupled device (CCD) and complementary-metal-oxide-semiconductor (CMOS) image sensors are mainly using planar device structures shaped by mainstream planar microfabrication processes, making hemispherical device fabrication almost impossible. \n\nHere we demonstrate an artificial visual system using a spherical biomimetic electrochemical eye (EC-EYE) with a hemispherical retina made of a high-density perovskite nanowire array grown using a vapour-phase approach. An ionic liquid electrolyte was used as a front-side common contact to the nanowires and liquid-metal wires were used as back contacts to the nanowire photosensors, mimicking human nerve fibres behind the retina. Device characterizations show that the EC-EYE has a high responsivity, a reasonable response speed, a low detection limit and a wide FOV. The EC-EYE also demonstrates the basic function of a human eye to acquire image patterns. In addition to its structural similarity with a human eye, the hemispherical artificial retina has a nanowire density much higher than that of photoreceptors in a human retina and can thus potentially achieve higher image resolution, which is bolstered by implementation of a single-nanowire ultrasmall photodetector. \n\nFigure 1 shows a comparison of the human (Fig. 1a–c) and EC-EYE imaging systems (Fig. 1d–f). The human visual system has two eye bulbs for optical sensing, millions of nerve fibres for data transmission and a brain for data processing. The human brain has enormous capability for parallel processing: neuroelectric signals from about a million nerve fibres can be processed simultaneously, enabling high-speed image processing and recognition6. The internal structure of a human eye (Fig. 1b) has a lens, a spherical cavity and a hemispherical retina, which is the core component required to convert optical images to neuroelectric signals. Its hemispherical shape simplifies optical design, resulting in an extraordinarily large FOV of about $155^{\\circ}$ with a wide visual perception of the surroundings1. There are about 100–120 million photoreceptors and rod and cone cells, vertically assembled in the retina in a dense and quasi-hexangular manner (Fig. 1c), with a density of around 10 million per square centimetre and an average pitch of $3\\upmu\\mathrm{m}$ , leading to a high imaging resolution comparable to that of the state-of-the-art CCD/CMOS sensors7. However, the nerve fibre layer is at the front surface of the human retina, causing light loss and blind spot issues (Supplementary Fig. 1)1. Figure 1d, e illustrates the schematic of our biomimetic visual system, which consists of a lens, a photosensor array on a hemispherical substrate and thin liquid-metal wires as electrical contacts. These components mimic the biological eye’s lens, retina and the nerve fibres behind the retina, respectively. Of these, the key component is the artificial retina made of a high-density array of perovskite nanowires grown inside a hemispherical porous aluminium oxide membrane (PAM) via a vapour-phase deposition process8–10. \n\n![](images/033c04b2a807b00c495bf6ca140795f575f6889131f726e1044acca5fb5d8a5f.jpg) \nFig. 1 | Overall comparison of the human visual system and the EC-EYE working mechanism of EC-EYE (e) and perovskite nanowires in the PAM imaging system. a–c, Schematic of the human visual system (a), the human eye template and their crystal structure (f). (b) and the retina (c). d–f, Schematic of our EC-EYE imaging system (d), the \n\nA more detailed structure of the EC-EYE is in Fig. 2a, and the fabrication process is in Methods and Supplementary Fig. 2. The nanowires serve as light-sensitive working electrodes. The tungsten (W) film on aluminium (Al) hemispherical shell works as the counter electrode. In between two electrodes, ionic liquid is used to fill in the cavity, serving as the electrolyte and mimicking the vitreous humour in the human eye. The flexible eutectic gallium indium liquid-metal wires in soft rubber tubes are used for signal transmission between the nanowires and external circuitry with a discontinuous indium layer between the liquid metal and the nanowires to improve contact (Supplementary Fig. 3). An individual photodetector can be addressed and measured by selecting the corresponding liquid-metal wire. This resembles the working principle of the human retina, in which groups of photoreceptors are individually connected with nerve fibres11, enabling suppressed interference among pixels and high-speed parallel processing of the neuroelectric signals. We note that the liquid-metal wires are behind the sensing material, thus avoiding the light-loss and blind-spot problems of the human retina. As a proof of concept, we fabricated a $10\\times10$ photodetector array with a pitch of $\\mathrm{1.6}\\mathrm{mm}$ . The minimum size of each sensing pixel is limited by the diameter of the liquid-metal wire, which is difficult to reduce to a few micrometres12. To further reduce pixel size and enhance the spatial imaging resolution, another approach to fabricating the sensor pixel array with a pixel area of about $1\\upmu\\mathrm{m}^{2}$ per pixel using metal microneedles has been developed. \n\nPreviously, there have been a few inspiring works reporting hemispherical image sensors using deformed, folded or individually assembled photodetectors13–15. The photodetectors in those works were mainly pre-fabricated on planar substrates, then transferred to a hemispherical supporting material or folded into a hemispherical shape. It is challenging to achieve small individual pixel size and high imaging resolution owing to the complexity of the fabrication process. Here light-sensing nanowires were grown in a hemispherical template, and thus a structure akin to that of the human retina has been formed in a single step. We chose formamidinium lead iodide $(\\mathsf{F A P b l}_{3})$ as the model material for nanowire growth here owing to its excellent optoelectronic properties and decent stability9,16. The nanowire growth and characterization details can be found in Methods and Supplementary Figs. 4 and 5. In principle, other types of inorganic nanowires made of Si, Ge, GaAs and so on can also be grown using the well documented vapour– liquid–solid process17–20. Figure 2b, c shows the side and top views of a completed EC-EYE. Figure 2d, e presents scanning electron microscopy (SEM) images of the hemispherical PAM and the nanowires located at the bottom of the nanochannels, respectively. The single-crystalline (Fig. 2f) nanowires have a pitch of $500\\mathsf{n m}$ , corresponding to a density of $4.6\\times10^{8}\\mathrm{cm}^{-2}$ , which is much higher than that of the photoreceptors in human retina, indicating the potential to achieve a high imaging resolution if proper electrical contacts can be achieved21. \n\nFigure 3a shows the schematic of a single pixel measurement. A collimated light beam is focused on the pixels at the centre of the retina. Figure 3b plots the energy-band alignment for the entire device showing charge-carrier separation routes under light excitation. Figure 3c presents the current–voltage characteristics exhibiting the asymmetric photoresponse caused by asymmetric charge transportation at the two sides of the nanowires (Fig. 3b). Previous electrochemical characterizations have shown that the redox reactions of $\\Gamma/\\ensuremath{\\mathrm{I}_{3}}^{-}$ pairs22,23 occur at the nanowire/electrolyte and tungsten film/electrolyte interfaces and that ion transportation inside the electrolyte contributes to the photoresponse (Supplementary Fig. 6). The inset of Fig. 3c shows the transient response of the device to chopped light (see Supplementary Figs. 7 and 8 for more results). The relatively fast and highly repeatable response indicates that the device has excellent photocurrent stability and reproducibility. The response and recovery time are found to be $32.0\\mathrm{ms}$ and $40.8\\mathrm{ms}$ , respectively. Further electrochemical analysis of the critical nanowire/electrolyte interface reveals that the device transmission electron microscopy image of a single-crystalline perovskite nanowire. g, Photograph of the polydimethylsiloxane (PDMS) socket, which improves the alignment of the liquid-metal wires. \n\n![](images/5d9b2b2a336e7f12e6ae773cd5e7dd7525aeb5969ac6e7ecc02347c6aacbc223.jpg) \nFig. 2 | Detailed structure of our EC-EYE. a, Exploded view of EC-EYE. b, c, Side view (b) and top view (c) of a completed EC-EYE. d, Low-resolution cross-sectional SEM image of the hemispherical PAM/nanowires. e, Cross-sectional SEM images of nanowires in PAM. f, High-resolution \n\n![](images/1b0f739e242604b14456a66347aa48ca024bd58b6083ad3e5a2863b5e08c08ae.jpg) \nFig. 3 | Photodetection performance characterization of individual pixels. a, Schematic setup of individual pixel measurement. b, Working mechanism of an individual pixel under $-3\\ensuremath{\\mathsf{V}}$ bias voltage. BMIMI, 1-butyl3-methylimidazolium iodide. c, Current–voltage curves under different illuminations and the transient response of individual pixels under the illumination of simulated sunlight with an intensity o $\\cdot50\\mathrm{m}\\mathrm{W}\\mathrm{cm}^{-2}$ . The \ncurrent–voltage curves represent one cycle of the cyclic-voltammetry measurement. Scan rate, $100\\mathrm{mVs^{-1}}.$ . d, Illumination-intensity-dependent photocurrent and responsivity of an individual pixel. The lowest light intensity is $0.3\\upmu\\mathrm{W}\\mathsf{c m}^{-2}$ . e, Device schematic and transient photoresponse of single-nanowire-based and four-nanowire-based individual pixels. f, Schematic and SEM image of the Ni microneedle contact to the nanowire array. \n\n![](images/29cf5bdfcdb0febfd323d0bebb1cfe8d592cdbc725f75bb62f60b7b1d8953c64.jpg) \nFig. 4 | Image-sensing demonstration of EC-EYE. a, Back-view photo of an projection on a flat plane. d, e, The schematic (d) and calculated (e) FOV of th EC-EYE mounted on a printed circuit board. b, Schematic illustration of the planar and hemispherical image-sensing systems. measurement setup. c, The reconstructed image (letter ‘A’) of EC-EYE and its \n\nresponse time depends on the kinetics of multiple types of ions at that interface (Supplementary Fig. 9). Electrochemical impedance spectroscopy measurements (Supplementary Fig. 10) demonstrate that device structural optimization and ionic liquid concentration increase can substantially reduce the charge-transfer resistance $(R_{\\mathrm{ct}})$ at the nanowire/ electrolyte interface, leading to reduction of the device response and recovery times to 19.2 ms and $23.9\\mathrm{{ms}}$ . This is much faster than that of human eyes, whose response and recovery times range from 40 ms to 150 ms (ref. 24). Meanwhile, increasing ionic liquid concentration leads to light absorption loss (Supplementary Fig. 11), so further optimization of the ionic liquid composition will be of benefit. \n\nFigure 3d shows the dependence of the photocurrent and responsivity on the illumination intensity, with a large dynamic range from $0.3\\upmu\\mathrm{W}\\mathsf{c m}^{-2}$ to $50\\mathsf{m w}\\mathsf{c m}^{-2}$ . The photocurrent can be fitted with a quasi-linear power-law relationship $(I=A{\\times}P^{0.69})$ , where I is the photocurrent, $P$ represents the irradiance power and A is a coefficient. Intriguingly, the responsivity increases when reducing illumination intensity. It can reach up to $303.2\\mathsf{m A W}^{-1}.$ , which is among the highest for reported photoelectrochemical photodetectors (Supplementary Table 1). And it is on par with that of the solid-state photodetectors based on perovskite nanowire arrays reported earlier8,9. Under the lowest radiation level measured, the average number of photons received per second by an individual nanowire can be estimated at 86 photons (Supplementary Information). This sensitivity is on par with that of human cone cells25. The corresponding specific detectivity is calculated as about $1.1\\times10^{9}$ Jones for $0.3\\upmu\\mathrm{W}\\mathsf{c m}^{-2}$ incident light. The spectral responsivity shows a broad-band response with a clear cut-off at $810\\mathsf{n m}$ (Supplementary Fig. 12). Supplementary Fig. 13 demonstrates the stability and repeatability of an individual pixel for $2\\mathsf{H z}$ light continuously chopped for 9 h. It indicates that although there are drifts for both the dark and light current, there is no obvious device performance degradation after 64,800 cycles. \n\nAs mentioned, one of the primary merits of using high-density nanowire arrays for artificial retina is their potential for high image resolution. Although liquid-metal fibre contacts to nanowires are convenient and image resolution is already on par with that of a number of existing bionic eyes in use26–28, it is challenging to reduce pixel size down to the few-micrometres level. Therefore, we explored two more contact strategies to achieve ultrasmall pixel size. As shown in Fig. 3e, a single nanowire was deterministically grown in a single nanochannel opened using a focused ion beam; then a single pixel with 500-nm lateral size and a footprint of about $0.22\\upmu\\mathrm{m}^{2}$ was achieved (Methods and Supplementary Fig. 14). Using the same approach, a pixel of 4 nanowires was also fabricated. The SEM images in Supplementary Fig. 15 show the controllable growth of nanowires, including the nanowire numbers and positions. The photoresponses of these two devices are shown in Fig. 3e. To form an array of ultrasmall pixels, nickel (Ni) microneedles were vertically assembled on top of a PAM using a magnetic field and thus each microneedle can address 3 nanowires, forming a pixel with lateral size of about $1\\upmu\\mathrm{m}$ and pitch of $200\\upmu\\mathrm{m}$ . The details of this contact strategy are illustrated in Supplementary Figs. 16 and 17. Figure 3f schematically shows the device connected to copper wires, which serve as signal transmission lines. The lateral size of the contact region is $2\\mathsf{m m}$ . \n\nAfter characterization of individual sensor pixels, we measured the full device imaging functionality. A photograph of the device is shown in Fig. 4a and Supplementary Fig. 18a, b. The liquid-metal wires are connected to a computer-controlled $100\\times1$ multiplexer via a printed circuit board. The measurement system design is shown in Fig. 4b and the corresponding circuit diagram is shown in Supplementary Fig. 18c. The image-sensing function was examined by projecting optical patterns onto the EC-EYE, after which the photocurrent of each sensor pixel was recorded. Before pattern generation and recognition, the consistency of the dark and light currents of all pixels was verified. Supplementary Fig. 19a, b depicts the dark- and light-current images obtained under $-3\\mathsf{V}$ bias voltage, showing that all 100 pixels have consistent photoresponse with relatively small variation. To reconstruct the optical pattern projected on the EC-EYE, a photocurrent value was converted to a greyscale number between 0 and 255 (Supplementary Information). \n\n# Article \n\nFigure 4c shows the imaged character ‘A’ and its projection onto a flat plane. Supplementary Fig. 20 shows images of letters ‘E’, ‘I’ and ‘Y’. The Supplementary Video shows the dynamic process of EC-EYE capturing the letters ‘E’, ‘Y’ and ‘E’ sequentially. Compared to planar image sensors based on a crossbar structure, the device presented here delivers a higher contrast with clearer edges because each individual pixel is better isolated from the neighbouring pixels (Supplementary Fig. 21)7. Besides an EC-EYE with liquid-metal contacts, we also fabricated a small electrochemical image sensor with microneedle contacts. This imager, with an active area of $2\\mathsf{m m}\\times2\\mathsf{m m}$ , was assembled into a mini-camera together with other optical parts (see Supplementary Figs. 22 and 23). Supplementary Fig. 23 shows its imaging functionality. Meanwhile, the magnetic microneedle alignment strategy developed here also works very well for the whole hemispherical surface. Supplementary Fig. 24 shows that the ${50}{\\cdot}{\\upmu\\mathrm{{m}}}$ -thick Ni microwires are well aligned onto the surface of a hemispherical PAM. Although we have successfully fabricated ultrasmall pixels here and implemented microneedle manual alignment onto the nanowires, better high-throughput strategies to align large numbers of electrodes on nanowires with precision could be developed. For instance, a high-precision robotic arm equipped with a piezo actuator can be used to place Ni microneedles onto the hemispherical PAM, assisted by a magnetic field and a high-resolution optical monitoring system (Supplementary Fig. 24c). Better approaches could address individual nanowires in a more deterministic manner. \n\nCompared to a planar image sensor, the hemispherical shape of our EC-EYE ensures a more consistent distance between pixels and the lens, resulting in a wider FOV and better focusing onto each pixels (Fig. 4d). The diagonal visual field of our hemispherical EC-EYE is about $100.1^{\\circ}$ , whereas that of a planar device is only $69.8^{\\circ}$ (Fig. 4e). Moreover, this angle of view can be further improved to approach the static vertical FOV of a single human eye (about $130^{\\circ})^{29}$ , by optimizing the pixel distribution on the hemispherical retina. \n\nHere we have demonstrated a biomimetic eye with a hemispherical retina made of high-density light-sensitive nanowires. Its structure has a high degree of similarity to that of a human eye with potential to achieve higher imaging resolution if a better contact strategy can be implemented. The processes developed tackle the challenge of fabricating optoelectronic devices on non-planar substrates with high integration density. Furthermore, this work may inspire biomimetic designs of optical imaging devices that could find application in scientific instrumentation, consumer electronics and robotics. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-020-2285-x. \n\n1. Atchison, D. A. & Smith, G. Optics of the Human Eye Vol. 35 (Butterworth-Heinemann, 2000). \n2. Zhang, J., Con, C. & Cui, B. Electron beam lithography on irregular surfaces using an evaporated resist. ACS Nano 8, 3483–3489 (2014). \n3. Qin, D., Xia, Y. & Whitesides, G. M. Soft lithography for micro-and nanoscale patterning. Nat. Protocols 5, 491–502 (2010). \n4. Pocock, D. C. D. Sight and knowledge. Trans. Inst. Br. Geogr. 6, 385–393 (1981). \n5. Jung, I. et al. Dynamically tunable hemispherical electronic eye camera system with adjustable zoom capability. Proc. Natl Acad. Sci. USA 108, 1788–1793 (2011). \n6. Nassi, J. J. & Callaway, E. M. Parallel processing strategies of the primate visual system. Nat. Rev. Neurosci. 10, 360–372 (2009). \n7. Jonas, J. B., Schneider, U. & Naumann, G. O. Count and density of human retinal photoreceptors. Graefes Arch. Clin. Exp. Ophthalmol. 230, 505–510 (1992). \n8. Gu, L. et al. 3D arrays of 1024-pixel image sensors based on lead halide perovskite nanowires. Adv. Mater. 28, 9713–9721 (2016). \n9. Gu, L. et al. Significantly improved black phase stability of $\\mathsf{F A P b l}_{3}$ nanowires via spatially confined vapor phase growth in nanoporous templates. Nanoscale 10, 15164–15172 (2018). \n10.\t Waleed, A. et al. Lead-free perovskite nanowire array photodetectors with drastically improved stability in nanoengineering templates. Nano Lett. 17, 523–530 (2017). \n11. Schein, S. J. Anatomy of macaque fovea and spatial densities of neurons in foveal representation. J. Comp. Neurol. 269, 479–505 (1988). \n12.\t Dickey, M. D. et al. Eutectic gallium-indium (EGaIn): a liquid metal alloy for the formation of stable structures in microchannels at room temperature. Adv. Funct. Mater. 18, 1097–1104 (2008). \n13.\t Song, Y. M. et al. Digital cameras with designs inspired by the arthropod eye. Nature 497, 95–99 (2013). \n14. Ko, H. C., Stoykovich, M. P., Song, J., Malyarchuk, V. & Rogers, J. A. A hemispherical electronic eye camera based on compressible silicon optoelectronics. Nature 454, 748–753 (2008). \n15.\t Zhang, K. et al. Origami silicon optoelectronics for hemispherical electronic eye systems. Nat. Commun. 8, 1782 (2017). \n16. Han, Q. et al. Single crystal formamidinium lead iodide $(\\mathsf{F A P b l}_{3})$ : insight into the structural, optical, and electrical properties. Adv. Mater. 28, 2253–2258 (2016). \n17. Fan, Z. et al. Ordered arrays of dual-diameter nanopillars for maximized optical absorption. Nano Lett. 10, 3823–3827 (2010). \n18. Fan, Z. et al. Three-dimensional nanopillar-array photovoltaics on low-cost and flexible substrates. Nat. Mater. 8, 648–653 (2009). \n19. Ramdani, M. R. et al. Fast growth synthesis of GaAs nanowires with exceptional length. Nano Lett. 10, 1836–1841 (2010). \n20.\t Wen, C. Y. et al. Formation of compositionally abrupt axial heterojunctions in silicon-germanium nanowires. Science 326, 1247–1250 (2009). \n21. Wandell, B. A. Foundations of Vision Vol. 8 (Sinauer Associates, 1995). \n22. Boschloo, G. & Hagfeldt, A. Characteristics of the iodide/triiodide redox mediator in dye-sensitized solar cells. Acc. Chem. Res. 42, 1819–1826 (2009). \n23.\t Kawano, R. & Watanabe, M. Equilibrium potentials and charge transport of an $\\mathsf{I}^{-}/\\mathsf{I}_{3}^{-}$ redox couple in an ionic liquid. Chem. Commun. 3, 330–331 (2003). \n24.\t Rayner, K., Smith, T. J., Malcolm, G. L. & Henderson, J. M. Eye movements and visual encoding during scene perception. Psychol. Sci. 20, 6–10 (2009). \n25.\t Mustafi, D., Engel, A. H. & Palczewski, K. Structure of cone photoreceptors. Prog. Retin. Eye Res. 28, 289–302 (2009). \n26.\t Fujikado, T. et al. Evaluation of phosphenes elicited by extraocular stimulation in normals and by suprachoroidal-transretinal stimulation in patients with retinitis pigmentosa. Graefes Arch. Clin. Exp. Ophthalmol. 245, 1411–1419 (2007). \n27.\t Ayton, L. N. et al. First-in-human trial of a novel suprachoroidal retinal prosthesis. PLoS One 9, e115239 (2014). \n28.\t Shivdasani, M. N. et al. Factors affecting perceptual thresholds in a suprachoroidal retinal prosthesis. Invest. Ophthalmol. Vis. Sci. 55, 6467–6481 (2014). \n29.\t Navarro, R. The optical design of the human eye: a critical review. J. Optom. 2, 3–18 (2009). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\n# Fabrication of EC-EYE \n\nThe EC-EYE fabrication process started with deforming a ${500}{\\cdot}{\\upmu\\mathrm{m}}$ -thick Al sheet on a set of hemispherical moulds to obtain a hemispherical Al shell, which then underwent a standard two-step anodization process to form PAM with thickness $40\\upmu\\mathrm{m}$ and nanochannel pitch and diameter of $500\\mathsf{n m}$ and $120\\mathsf{n m}$ , respectively, on the Al surface. A barrier thinning process and Pb electrodeposition were carried out to obtain Pb nanoclusters at the bottom of the PAM channels. Next, the outer layer of PAM and the residual Al were etched away to obtain a freestanding PAM with Pb, which was then transferred into a tubular furnace to grow perovskite nanowires about ${5\\upmu\\mathrm{m}}$ long. The detailed nanowire growth condition can be found in ref. 9. A 20-nm-thick indium layer was evaporated onto the PAM back surface to serve as the adhesion layer. We note that this indium layer will not cause short-circuiting between pixels owing to its discontinuous morphology (Supplementary Fig. 3). To obtain the liquid-metal contact array, a hedgehog-shaped mould was fabricated using 3D printing, from which a complementary PDMS socket with $10\\times10$ hole array (hole size $700\\upmu\\mathrm{m}$ , pitch $1.6\\mathsf{m m}$ ) was cast. Eutectic gallium indium liquid metal was then injected into thin soft tubes (inner diameter $400\\upmu\\mathrm{m}$ , outer diameter $700\\upmu\\mathrm{m}$ ) to form liquid-metal wires. Then 100 tubes were inserted into the holes on the PDMS socket and the whole socket was attached to the PAM/nanowire surface to form a $10\\times10$ photodetector array. These long soft tubes can be directly connected to a printed circuit board and thus the complex wire bonding process is avoided. A circular hole was opened on another Al shell, which was then coated with a tungsten film working as the counter electrode of the EC-EYE. After mounting the aperture (Eakins, SK6), the Al shell was subsequently fixed onto the front side of PAM by epoxy. Ionic liquid 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (BMIMTFSI) mixed with $1v o l\\%$ 1-butyl-3-methylimidazolium iodide (BMIMI) was then injected and a convex lens (diameter $1.2\\mathrm{cm}$ , focal length $\\mathsf{1.6}\\mathsf{c m}\\dot{}$ ) was then glued to the hole on Al shell to seal the device. After curing, the EC-EYE device fabrication was completed. \n\n# Fabrication of microneedle-based electrochemical image sensor \n\nFreestanding $40{\\cdot}{\\upmu}{\\m} $ -thick PAM was fabricated using the standard anodization process, NaOH etching and ${\\sf H g C l}_{2}$ solution etching. Ion milling was used to remove the barrier layer to achieve through-hole PAM (Supplementary Fig. 17a). Then a 1- $\\upmu\\mathrm{m}$ -thick Cu film was thermally evaporated onto the through-hole PAM to serve as the electrode for the subsequent Ni and Pb electrochemical deposition (Supplementary Fig. 17b). Next, to expose the Ni nanowires, the copper layer was removed by $\\mathbf{A\\boldsymbol{r}^{+}}$ ion milling and the PAM was partially etched away by reactive ion etching. The exposed Ni nanowires were about $3\\upmu\\mathrm{m}$ long (Supplementary Fig. 17c). The chip was moved into a tubular furnace for perovskite nanowire growth (Supplementary Fig. 17c). The PAM chip was fixed onto a cylindrical electromagnet $(0-50\\mathrm{mT})$ with Ni nanowires facing upward (Supplementary Fig. 17d). Meanwhile, Ni microwires of diameter ${50\\upmu\\mathrm{m}}$ were sharpened in a mixed acidic solution $(100\\mathsf{m l}$ $0.25\\mathsf{M H C l}$ aqueous solution $+100\\mathrm{ml}$ ethylene glycol) under a bias of 1 V, with Ni microwires as the working electrodes and the tungsten coil as the counter electrode. The resulting Ni microwires have sharp tips, with curvature radius of 100–200 nm. The Ni needle was then gently placed onto the PAM substrate with the magnetic field ‘on’. Owing to the magnetic force, the ferromagnetic Ni microneedles can engage into the Ni nanowire forest to form an effective electrical contact to the nanowires (Supplementary Fig. 17d). To facilitate the Ni microwire placement, a mask with $10\\times10$ hole array (hole diameter $100\\upmu\\mathrm{m}$ , pitch $200\\upmu\\mathrm{m})$ ) was used to align the Ni microneedles (Supplementary Fig. 17d). After placement, ultraviolet epoxy was dropped between the mask and the PAM substrate. Copper enamelled wire with diameter of $60\\upmu\\mathrm{m}$ was inserted into the hole to form an electrical contact bridging the Ni microneedle and external printed circuit board (Supplementary Fig. 17e). \n\n# Fabrication of single- and multiple-nanowire-based electrochemical photodetectors \n\nFreestanding planar PAM was fabricated by standard two-step anodization followed by ${\\mathsf{H g C l}}_{2}$ etching. The freestanding PAM was then transferred into the focused ion beam (FEI Helios G4 UX) to selectively etch away the barrier layer (Supplementary Fig. 14c). To facilitate the etching, the chip was bonded onto an Al substrate with the barrier layer side facing up. After focused-ion-beam etching (etching voltage $30\\upk\\upnu,$ , etching current 26 nA), a 500-nm-thick Cu layer was evaporated onto the barrier layer side to serve as the electrode for the subsequent Pb electrochemical deposition (Supplementary Fig. 14d). Next, the chip was moved into a tubular furnace for perovskite nanowire growth (Supplementary Fig. 14e). Then a Cu wire was bonded onto the Cu side of PAM with carbon paste and the whole chip was fixed onto a glass substrate by ultraviolet epoxy. After curing, ionic liquid was dropped onto the top of the PAM (Supplementary Fig. 14e) and a tungsten probe was inserted into the ionic liquid for photoelectric measurement. The photoresponse was measured with $-3\\mathsf{V}$ bias and $50\\mathsf{m}\\mathsf{w}\\mathsf{c m}^{-2}$ light intensity. \n\n# Material and photodetector characterization \n\nThe SEM images and energy dispersive X-ray mapping of the PAM were characterized using a field-emission scanning electron microscope (JEOL JSM-7100F equipped with a Si (Li) detector and PGT 4000T analyser). The X-ray diffraction patterns of the $\\mathsf{F A P b l}_{3}$ nanowire arrays in PAM were obtained using a Bruker D8 $\\mathsf{x}$ -ray diffractometer. Transmission electron microscope images were obtained using a TEM JEOL (2010) with 200-kV acceleration voltage. The ultraviolet–visible absorption was measured with a Varian Cary 500 spectrometer. The photoluminescence and time-resolved photoluminescence measurements were carried out on an Edinburgh FS5 fluorescence spectrometer. The cyclic-voltammetry measurements based on a two-electrode configuration were performed on an electrochemical workstation (CHI 660E, China) at a scan rate of $100\\mathrm{mVs^{-1}}$ with attenuated simulated sunlight (Newport, Solar Spectral Irradiance Air Mass 1.5) as the light source. The current–time curves of individual pixels were measured using the probe station of a HP4156A with neutral-density filters to tune the light intensity. An additional chopper was used to chop light into square wave optical signals with different frequencies. The electrochemical impedance spectra were measured by a potentiostat (Gamry SG 300) in the range 300 kHz to $100\\mathsf{H z}$ , with an amplitude of $10\\mathrm{mV}$ under a bias of $-3{\\sf V}.$ . The working electrodes were connected to the liquid metal. The reference and counter electrodes were connected to the tungsten electrode. \n\n# Image-sensing characterization of EC-EYE \n\nThe image-sensing performance of EC-EYE was characterized by using a home-built system consisting of a multiplexer, a pre-amplifier, a laptop computer and a Labview program (https://www.ni.com/zh-cn/ shop/labview.html). The schematic of the system can be found in Fig. 4b. Specifically, Keithley 2400 was used to provide the bias voltage. The current meter (PXI4130, National Instruments), together with the multiplexer (PXI2530B, National Instruments), was installed inside of a chassis (PXI1031, National Instruments). The whole system is controlled by a home-built Labview program. To carry out the measurements, various optical patterns were generated by PowerPoint slides and projected onto the device by a projector. A convex lens was used to focus the pattern and different neutral-density filters were inserted between the projector and image sensor to tune the light intensity. \n\n# Reporting summary \n\nFurther information on research design is available in the Nature Research Reporting Summary linked to this paper. \n\n# Article \n\n# Data availability \n\n# The data that support the findings of this study are provided in the main text and the Supplementary Information. More data are available from the corresponding author upon reasonable request. \n\nAcknowledgements This work was supported by the National Natural Science Foundation of China (project 51672231) and the Science and Technology Plan of Shenzhen (JCYJ20170818114107730), the General Research Fund (projects 16237816, 16309018 and 16214619) from the Hong Kong Research Grant Council, Hong Kong Innovation Technology Commission (project ITS/115/18) and The Hong Kong University of Science and Technology (HKUST) Fund of Nanhai (grant number FSNH-18FYTRI01). We acknowledge support received from the Material Characterization and Preparation Facility (MCPF, particularly Y. Cai for her technical assistance with the focused ion beam), the Nanosystem Fabrication Facility (NFF), the Center for 1D/2D Quantum Materials and the State Key Laboratory on Advanced Displays and Optoelectronics at HKUST. We also thank D. Wang (Chemistry Department, Boston College), M. Shao (Department of Chemical and Biological Engineering, HKUST) and Q. Chen (Department of Mechanical and Aerospace Engineering, HKUST) for their discussions on the electrochemical impedance spectroscopy measurements.  The images in Fig. 1a–d and Supplementary Fig. 1 were created by Fantastic Color Animation Technology Co., Ltd (2020). \n\nAuthor contributions Z.F. and L.G. conceived the ideas of the work. L.G., Z.L., D.Z., Q.Z. and L.S. contributed to PAM fabrication, perovskite and Ni nanowire growth. S.P. contributed to the focused-ion-beam process. Y.L. developed the photoelectrochemical working mechanism. L.G., Z.L. and X.Q. worked on Ni microneedle assembly and EC-EYE device characterizations. L.G., Y.L., M.K., A.J. and Z.F. carried out the data analysis and wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41586-020- $2285-x$ . Correspondence and requests for materials should be addressed to Z.F. Peer review information Nature thanks Dae-Hyeong Kim, Hongrui Jiang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. " + }, + { + "id": "10.1038_s41586-020-2260-6", + "DOI": "10.1038/s41586-020-2260-6", + "DOI Link": "http://dx.doi.org/10.1038/s41586-020-2260-6", + "Relative Dir Path": "mds/10.1038_s41586-020-2260-6", + "Article Title": "Tunable correlated states and spin-polarized phases in twisted bilayer-bilayer graphene", + "Authors": "Cao, Y; Rodan-Legrain, D; Rubies-Bigorda, O; Park, JM; Watanabe, K; Taniguchi, T; Jarillo-Herrero, P", + "Source Title": "NATURE", + "Abstract": "The recent discovery of correlated insulator states and superconductivity in magic-angle twisted bilayer graphene(1,2) has enabled the experimental investigation of electronic correlations in tunable flat-band systems realized in twisted van der Waals heterostructures(3-6). This novel twist angle degree of freedom and control should be generalizable to other two-dimensional systems, which may exhibit similar correlated physics behaviour, and could enable techniques to tune and control the strength of electron-electron interactions. Here we report a highly tunable correlated system based on small-angle twisted bilayer-bilayer graphene (TBBG), consisting of two rotated sheets of Bernal-stacked bilayer graphene. We find that TBBG exhibits a rich phase diagram, with tunable correlated insulator states that are highly sensitive to both the twist angle and the application of an electric displacement field, the latter reflecting the inherent polarizability of Bernal-stacked bilayer graphene(7,8). The correlated insulator states can be switched on and off by the displacement field at all integer electron fillings of the moire unit cell. The response of these correlated states to magnetic fields suggests evidence of spin-polarized ground states, in stark contrast to magic-angle twisted bilayer graphene. Furthermore, in the regime of lower twist angles, TBBG shows multiple sets of flat bands near charge neutrality, resulting in numerous correlated states corresponding to half-filling of each of these flat bands, all of which are tunable by the displacement field as well. Our results could enable the exploration of twist-angle- and electric-field-controlled correlated phases of matter in multi-flat-band twisted superlattices.", + "Times Cited, WoS Core": 451, + "Times Cited, All Databases": 509, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000623832900002", + "Markdown": "# Article \n\n# Tunable correlated states and spin-polarized phases in twisted bilayer–bilayer graphene \n\nhttps://doi.org/10.1038/s41586-020-2260-6 \n\nReceived: 24 March 2019 \n\nAccepted: 12 February 2020 \n\nPublished online: xx xx xxxx \n\n# Check for updates \n\nYuan Cao1 ✉, Daniel Rodan-Legrain1, Oriol Rubies-Bigorda1, Jeong Min Park1, Kenji Watanabe2, Takashi Taniguchi2 & Pablo Jarillo-Herrero2 ✉ \n\nThe recent discovery of correlated insulator states and superconductivity in magic-angle twisted bilayer graphene1,2 has enabled the experimental investigation of electronic correlations in tunable flat-band systems realized in twisted van der Waals heterostructures3–6. This novel twist angle degree of freedom and control should be generalizable to other two-dimensional systems, which may exhibit similar correlated physics behaviour, and could enable techniques to tune and control the strength of electron–electron interactions. Here we report a highly tunable correlated system based on small-angle twisted bilayer–bilayer graphene (TBBG), consisting of two rotated sheets of Bernal-stacked bilayer graphene. We find that TBBG exhibits a rich phase diagram, with tunable correlated insulator states that are highly sensitive to both the twist angle and the application of an electric displacement field, the latter reflecting the inherent polarizability of Bernal-stacked bilayer graphene7,8. The correlated insulator states can be switched on and off by the displacement field at all integer electron fillings of the moiré unit cell. The response of these correlated states to magnetic fields suggests evidence of spin-polarized ground states, in stark contrast to magic-angle twisted bilayer graphene. Furthermore, in the regime of lower twist angles, TBBG shows multiple sets of flat bands near charge neutrality, resulting in numerous correlated states corresponding to half-filling of each of these flat bands, all of which are tunable by the displacement field as well. Our results could enable the exploration of twist-angle- and electric-field-controlled correlated phases of matter in multi-flat-band twisted superlattices. \n\nElectronic correlations play a fundamental role in condensed-matter systems where the bandwidth is comparable to or less than the Coulomb energy between electrons. These correlation effects often manifest themselves as intriguing quantum phases of matter, such as ferromagnetism, superconductivity, Mott insulators or fractional quantum Hall states. Understanding, predicting and characterizing these correlated phases is of great interest in modern condensed-matter physics research and pose challenges to both experimentalists and theorists. Recent studies of twisted graphene superlattices have provided us with an ideal tunable platform to investigate electronic correlations in two dimensions1,2,9–11. Tuning the twist angle of two-dimensional (2D) van der Waals heterostructures to realize novel electronic states, an emerging field referred to as ‘twistronics’, has enabled physicists to explore a variety of novel phenomena12–16. When two layers of graphene are twisted by a specific angle, the phase diagram in the system exhibits correlated insulator states with similarities to Mott insulator systems1,17, as well as unconventional superconducting states upon charge doping2,9,11,18. These effects might be originating from the many-body interactions between the electrons, when the band structure becomes substantially narrow as the twist angle approaches the first magic angle $\\theta{=}1.1^{\\circ}$ (refs. 3–5). \n\nHere we extend the twistronics research on graphene superlattices to a novel system with electrical displacement field tunability—twisted bilayer–bilayer graphene (TBBG), which consists of two sheets of untwisted Bernal-stacked bilayer graphene stacked together at an angle $\\theta$ , as illustrated in Fig. 1a. The band structure of bilayer graphene is highly sensitive to the applied perpendicular electric displacement field7,19,20, and therefore provides us with an extra knob to control the relative strength of electronic correlations in the bands17. Similar to twisted bilayer graphene $\\left(\\mathsf{T B G}\\right)^{3-5}$ , the band structure of TBBG is flattened near about $1.1^{\\circ}$ (Fig. $2{\\bf e}\\mathrm{-}{\\bf g})^{21}$ . For devices with a twist angle near this value, our experiments show that the correlated insulator behaviour at $n_{\\mathrm{s}}/2,n_{\\mathrm{s}}/4$ and $3n\\mathrm{\\Omega}/4$ can be sensitively turned on and off by the displacement field, where $n_{\\mathrm{s}}$ is the density corresponding to fully filling one spin- and valley-degenerate superlattice band22,23. From their response to magnetic fields, all of these correlated states probably have a spin-polarized nature, with the $n_{\\mathrm{s}}/2$ state having a $g\\mathbf{\\cdot}$ factor of about 1.5 for parallel fields, close to the bare electron spin $g$ -factor of 2. In contrast, devices with a smaller twist angle of $0.84^{\\circ}$ show multiple displacement-field-tunable correlated states at higher fillings, consistent with the presence of several sets of correlated flat bands in the electronic structure. The combination of twist angle, electric displacement field and magnetic field provides a rich arena to investigate novel correlated phenomena in the emerging field of twistronics. \n\n# Article \n\n![](images/6c03e0d44a3c8141dd354223e07f45be62822f8db4168e6f220099cf7134c3b6.jpg) \nFig. 1 | Structure and transport characterization of TBBG. a, TBBG consists of two sheets of Bernal-stacked bilayer graphene twisted at an angle θ. b, Schematic of a typical TBBG device with top and bottom gates and a Hall-bar geometry for transport measurements. $\\c-e$ , Measured longitudinal resistance $R_{x x}=V_{x x}/I$ and low-field Hall coefficient $R_{\\mathrm{H}}{=}\\mathbf{d}/\\mathbf{d}B(V_{x y}/I)$ as functions of carrier density n in three devices with twist angles $\\theta{=}1.23^{\\circ}\\left(\\mathbf{c}\\right),1.09^{\\circ}\\left(\\mathbf{d}\\right)$ and $0.84^{\\circ}(\\mathbf{e})$ . The vertical dashed lines denote multiples of the superlattice density $n_{\\mathrm{s}}$ , where the peaking of $\\cdot_{R_{x x}}$ and sign changing of $\\cdot_{R_{\\mathrm{H}}}$ indicate the Fermi energy crosses a band edge of the superlattice bands. f, Resistance of the $1.09^{\\circ}$ TBBG device \nversus both $V_{\\mathrm{tg}}$ and $V_{\\mathrm{bg}}$ . The charge density n and displacement field $D$ are related to the gate voltages by a linear transformation (Methods). The superlattice densities $\\pm n_{s}$ and the half-filling at $n_{s}/2$ are indicated by dashed lines parallel to the $D$ axis. Correlated insulator states are observed at $n_{\\mathrm{s}}/2$ filling in finite displacement fields. CNP, charge neutrality point. g, Map of low-field Hall coefficient $R_{\\mathrm{H}}$ (left) and resistance $R_{x x}$ (right) near the $n_{s}/2$ correlated states for the $1.09^{\\circ}$ TBBG device (the vertical dashed lines indicate $n_{s}/2)$ . We find that accompanying the onset of the correlated insulator states at $D/\\varepsilon_{\\scriptscriptstyle0}{\\approx}\\pm0.18\\mathsf{V}\\mathsf{n m}^{-1}$ , a new sign change of the Hall coefficient also emerges. \n\nWe fabricated high-mobility dual-gated TBBG devices with the previously reported ‘tear and stack’ method22,23, using exfoliated Bernal-stacked bilayer graphene instead of monolayer graphene. The devices presumably have an AB–AB stacking configuration where the top and bottom bilayers retain the same AB stacking order, in contrast to the AB–BA structure that was predicted to show topological effects24. We measured the transport properties of six small-angle devices, and here we focus on three of the devices with twist angles $\\theta{=}1.23^{\\circ}$ , $1.09^{\\circ}$ and $0.84^{\\circ}$ (see Extended Data Fig. 1 for other devices). The samples are all of high quality, as evident in the Landau fan diagrams, with Hall mobilities that can exceed 1 $\\scriptstyle10,000\\ c m^{2}\\mathbf{V}^{-1}\\mathbf{S}^{-1}$ , shown in Extended Data Fig. 2. Figure 1c–e shows the longitudinal resistance $R_{x x}$ and the low-field Hall coefficient $R_{\\mathrm{H}}=\\mathrm{d}R_{x y}/\\mathrm{d}B$ versus charge density for these three devices at a temperature of $T{=}41$ , where $B$ is the magnetic field perpendicular to the sample. In a superlattice, the electronic band structure is folded in the mini-Brillouin zone, defined by the moiré periodicity4. Each band in the mini-Brillouin zone can accommodate a total charge density of $\\dot{n}_{\\mathrm{s}}=4/A$ , where A is the size of the moiré unit cell and the pre-factor accounts for the spin and valley degeneracies4,21,22. The experimental results show a sign change in the Hall coefficient $R_{\\mathrm{H}}$ at each multiple of $\\dot{n}_{\\mathrm{s}}$ (vertical dashed lines in Fig. $\\displaystyle{\\mathbf{1}\\mathbf{c}\\mathbf{-}\\mathbf{e}})$ , indicating the switching of hole-like pockets to electron-like pockets, and peaks in $\\boldsymbol{R_{x x}},$ indicating the crossing of new band edges (for $\\theta{=}0.84^{\\circ}$ , the band edges at $-\\ensuremath{n_{s}}$ and $\\pm2n_{\\mathrm{s}}$ may have only small gaps or may even be semi-metallic, and hence do not exhibit prominent peaks in $\\textstyle R_{x x},$ ). The sharpness of the peaks confirms that the devices exhibit relatively low disorder and have well-defined twist angles. \n\nIn the $\\pmb{\\theta}=\\mathbf{1.}23^{\\circ}$ and $\\theta=1.09^{\\circ}$ devices, we observe signatures of newly formed gaps at $n_{\\mathrm{s}}/2$ when a displacement field $D$ is applied perpendicular to the device. The dual-gate device geometry allows us to independently vary the total charge density $n$ and $D$ (see Methods for details of the transformation between gate voltages and $(n,$ $|D\\rangle$ ). Figure 1f shows the resistance map in the top gate voltage–bottom gate voltage $(V_{\\mathrm{tg}}-V_{\\mathrm{bg}})$ space for the $\\theta{=}1.09^{\\circ}$ device. At $D=0$ , no insulating behaviour other than the full-filling gaps at $\\pm n_{s}$ is observed. However, when a displacement field $D$ is applied in either direction, an insulating state appears at $n_{\\mathrm{s}}/2$ for a range of $|D|$ . This new insulating state induced by the displacement field is further examined by measuring the Hall coefficient $R_{\\mathrm{H}}$ versus $n$ and $D$ , as shown in the left panel of Fig. 1g $\\scriptstyle\\cdot\\theta=1.09^{\\circ}$ device), and comparing with $R_{x x}$ shown in the right panel. At the onset of the insulating states at $D/\\varepsilon_{0}{\\approx}\\pm0.18\\mathsf{V}\\mathsf{n m}^{-1}$ , where $\\scriptstyle{\\varepsilon_{0}}$ is the vacuum permittivity, $R_{\\mathrm{H}}$ develops additional sign changes adjacent to the insulating states, suggesting the creation of new gaps by the displacement field. The insulating states disappear when $D/\\varepsilon_{0}$ exceeds $^{\\pm0.35\\mathsf{V}\\mathsf{n m}^{-1}}$ . In both the $\\pmb{\\theta}{=}\\mathbf{1.09}^{\\circ}$ device and the $\\pmb{\\theta}=\\mathbf{1.}23^{\\circ}$ devices, we find signatures of the onset of correlated behaviour at $n{=}{-}n_{\\mathrm{s}}/2$ and $D=0$ , but no well-developed insulating state is observed (Extended Data Fig. 1, Methods). \n\nIn the $\\theta{=}1.23^{\\circ}$ device, we observe a similar but more intricate hierarchy of tunable insulating states that stem from the interplay of correlations, the superlattice bands and the magnetic field. Figure 2a shows the $n$ –D resistance map for the $\\theta{=}1.23^{\\circ}$ TBBG device measured at ${\\cal T}=0.07$ K. Noticeably, as $|D|$ is increased, the insulating state at charge neutrality $\\scriptstyle n=0$ strengthens in the same way as in the Bernal-stacked bilayer graphene7,19,20, while the superlattice gaps at $\\pm n_{s}$ weaken and eventually disappear (at $|D|/\\varepsilon_{0}>0.6\\mathsf{V}\\mathsf{n m}^{-1}$ for the $+n_{s}$ insulating state and at $|D|/\\varepsilon_{0}>0.35\\mathsf{V}\\mathsf{n m}^{-1}$ for the $-\\ensuremath{n_{s}}$ insulating state). The band structures of TBBG in zero and finite external displacement fields calculated using d, Normalized resistance curves versus temperature at various densities between 0 and $n_{s}/2\\approx1.77\\times10^{12}{\\mathrm{cm}}^{-2}$ , which are indicated by dashed lines in b. Away from the charge neutrality point, all resistance curves show approximately linear R–T behaviour above 10 K, with similar slopes (Extended Data Fig. 3). e–g, Calculated band structure (left) and density of states (DOS; right) for $\\theta{=}1.23^{\\circ}$ TBBG at $\\Delta V=0$ (e), $\\Delta V=6\\mathrm{mV}$ (f) and $\\Delta V{=}12\\mathsf{m V}(\\mathbf{g})$ , where ΔV is the potential difference between adjacent graphene layers induced by the external displacement field (assumed to be the same between all layers). Single-particle bandgaps in the dispersion are highlighted green (below and above the flat bands) and purple (at charge neutrality) bars. \n\n![](images/5d69894973bb99f7bc4a8f8e96a4a140fa8cc1c37290304ea106e25b55a17b26.jpg) \nFig. 2 | Displacement-field-tunable correlated insulator states in TBBG. a, Colour plot of resistance versus charge density n and displacement field $D$ ( $\\cdot\\theta{=}1.23^{\\circ}$ device, section 1, see Methods). The green dashed line cutting through the $D<0$ correlated state is the linecut along which b is taken (for the $\\theta{=}1.23^{\\circ}$ device, section 2, see Methods). b, Resistance versus n and T at a fixed $D/\\varepsilon_{0}{=}{-}0.38\\mathrm{V}\\mathrm{nm}^{-1}$ . The correlated insulator states at $n_{\\mathrm{s}}/4$ and $n_{\\mathrm{s}}/2$ are suppressed by increasing the temperature. c, Resistance at density $n_{\\mathrm{s}}/2$ versus displacement field and temperature. The resistance shows a maximum at approximately $D/\\varepsilon_{\\scriptscriptstyle0}=\\pm0.4\\mathsf{V}\\mathsf{n m}^{-1}$ , the region where the correlated insulator state is present. The inset shows the thermal activation gap extracted from temperature dependence at different values of $D$ across the $n\\sqrt{2}$ state. \n\na continuum approximation are shown in Fig. $2\\mathrm{e-g}$ (see Methods for details). It should be noted that, although TBBG has twice the number of graphene layers than TBG, the band counting is the same, that is, each band (spin and valley degenerate) accommodates four electrons per moiré unit cell. At zero displacement field, the calculated gap at the charge neutrality is negligible, while the superlattice gaps above and below the flat bands are non-zero. When the displacement field is increased, the charge neutrality gap quickly widens while the superlattice gaps become smaller and eventually vanish, in agreement with our experimental observations. \n\nAt intermediate displacement fields around $D/\\varepsilon_{0}{=}{-}0.38\\mathsf{V}\\mathsf{n m}^{-1}$ , we observe the insulating states not only at $n_{\\mathrm{s}}/2$ over a wider range of $D$ , but also at $n_{\\mathrm{s}}/4$ over a smaller range (Fig. 2a). We attribute these states to a Mott-like mechanism similar to those observed in TBG, which results from the Coulomb repulsion of the electrons in the flat bands when each unit cell hosts exactly one or two electrons, corresponding to $n_{\\mathrm{s}}/4$ and $n_{\\mathrm{s}}/2$ fillings, respectively. The $n_{s}/4$ state requires a finer tuning of $D$ to be revealed, possibly due to the smaller gap size. This is evident from Fig. 2b, where we show the resistance versus $n$ and temperature T with the displacement field $D/\\varepsilon_{0}$ fixed at $-0.38\\mathsf{V}\\mathsf{n m}^{-1}$ . While the $n_{\\mathrm{s}}/2$ state persists up to approximately 8 K, the $n_{\\mathrm{s}}/4$ state disappears at less than $3\\mathsf{K}$ , indicating a smaller gap. Figure 2c shows the resistance of the $n_{\\mathrm{s}}/2$ state versus the displacement field and temperature. The ‘optimal’ displacement field to reach the maximal resistance is approximately $\\pm0.4\\mathrm{V}\\mathrm{nm}^{-1}$ . As the temperature increases, the peak in $R_{x x}$ not only decreases in value but also broadens in $D$ . In the inset, we show the evolution of the gap versus the displacement field. At temperatures higher than 10 K and away from the charge neutrality point, the transport is dominated by a linear R–T behaviour similar to that observed in TBG (Fig. 2d, see also Extended Data Fig. 3, Methods)2,9,25,26. \n\nFigure 3 shows the response of the various correlated states to magnetic fields in the perpendicular or in-plane direction with respect to the sample plane. Figure 3a–c shows the $n{-}D$ maps of the resistance for the $\\theta{=}1.23^{\\circ}$ device at $B=0$ T, $B_{\\perp}{=}8$ T and $B_{||}=8$ T, respectively. The plots focus on densities from $\\scriptstyle n=0$ to $n=n_{s}$ . Figure 3a shows the band insulator states at $\\scriptstyle n=0$ and $n=n_{\\mathrm{s}}^{\\mathrm{\\Delta}}$ , as well as the correlated insulating states at $n_{\\mathrm{s}}/2$ and $n_{\\mathrm{s}}/4$ (encircled by dashed lines), but not at $3n\\mathrm{\\Omega}/4$ filling at this zero magnetic field. Interestingly, at $B_{\\perp}=8$ T (Fig. 3b), the correlated insulating states at $n_{\\mathrm{s}}/4$ and $n_{\\mathrm{s}}/2$ vanish at their original positions centred around $D/\\varepsilon_{0}=-0.38\\mathrm{V}\\ensuremath{\\mathrm{nm}}^{-1}$ , whereas new insulating states appear at $n=n_{\\mathrm{s}}/4,D/\\varepsilon_{0}\\approx-0.2$ to $-0.35\\mathsf{V}\\mathsf{n m}^{-1}$ , and $n=n_{s}/2$ , $D/\\varepsilon_{0}\\approx-0.45$ to $-0.6\\mathsf{V}\\mathsf{n m}^{-1}$ , above and below their original positions at $B=0$ , respectively. A new correlated insulating state also now appears at $3n\\mathrm{{}}_{\\mathrm{s}}/4,D/\\varepsilon_{0}\\approx-0.4$ to $-0.5\\mathsf{V}\\mathsf{n m}^{-1}$ . However, no such strong shift is observed with in-plane magnetic field (Fig. 3c). At $B_{||}=8$ T, the correlated insulating states are clearly visible at all integer electron fillings $(n_{\\mathrm{s}}/4,n_{\\mathrm{s}}/2,3n_{\\mathrm{s}}/4)$ near $D/\\varepsilon_{\\scriptscriptstyle0}=-0.38\\mathsf{V}\\mathsf{n m}^{-1}$ . Figure 3d, e shows the evolution of the $n_{\\mathrm{s}}/2$ insulating state as a function of ${\\bf\\ddot{\\theta}}_{\\perp}$ and $B_{||}$ . An abrupt shift in the range of $D$ for which the insulating state appears occurs at $B_{\\perp}{=}5\\mathsf{T}$ , whereas the insulating state strengthens monotonically with the in-plane magnetic field. \n\n![](images/aaa3722b578fd697daa7e1e30d13ccbc6b217d16e4a867e0537103898ace9d81.jpg) \nFig. 3 | Magnetic field response of the displacement-field-tunable correlated insulator states in TBBG. a–c, Resistance plot for the $\\theta{=}1.23^{\\circ}$ TBBG device in magnetic fields of $\\scriptstyle\\mathbf{B}=0$ (a), $B_{\\perp}{=}8$ T perpendicular to the sample (b) and $B_{||}=8$ T parallel to the sample (c). All measurements are taken at sample temperature ${\\cal T}=0.07\\:\\mathsf{K}$ . Various correlated states at integer electron fillings of the moiré unit cell are indicated by dashed circles. At zero field, only the $n_{\\mathrm{s}}/4$ and $n_{s}/2$ states appear around $|D|/\\varepsilon_{0}=0.38\\mathrm{V}\\mathrm{nm}^{-1}$ (denoted by blue dashed lines). In a perpendicular field of 8 T, the $n_{\\mathrm{s}}/4$ state shifts towards lower $|D|$ , the $n_{\\mathrm{s}}/2$ state shifts towards higher $|D|$ and a $3n\\sqrt{4}$ state also emerges. In a parallel field of 8 T, however, the position of the states barely shifts but their resistance increases monotonically. d, e, Resistance at $n=n_{\\mathrm{s}}/2$ versus displacement field \nand magnetic field applied perpendicular (d) and in-plane (e) with respect to the device. While the correlated insulator state monotonically strengthens in $B_{||},$ the perpendicular field induces a phase transition at around $B_{\\perp}{=}5\\mathsf{T}$ , where the correlated state abruptly shifts to higher $|D|$ . f, g, Temperature dependence of the resistance at the $n_{\\mathrm{s}}/2$ insulator in perpendicular (f) and in-plane (g) magnetic fields. The insets show the thermal activation gaps extracted from the Arrhenius fits $(R\\approx{\\tt e}^{-\\frac{\\Delta\\alpha}{2k_{\\mathrm{B}}T}}$ , where $k_{\\mathrm{{B}}}$ is the Boltzmann constant) in the main figures (solid lines) versus the magnitude of the field in the respective orientation. Error bars correspond to a confidence level of 0.99. The linear fit of the thermal activation gap gives a $g$ -factor of about 3.5 for the perpendicular field (up to 5 T only) and 1.5 for the in-plane field (entire field range). \n\nThe key difference between the effects of the perpendicular and in-plane magnetic fields lies in the fact that the lateral dimension of the unit cell in TBBG, about $10\\mathsf{n m}$ , is much larger than the thickness of the system, about 1 nm. Therefore, while both fields couple equally to the spins of the correlated electrons, $B_{\\parallel}$ has a much weaker (but non-zero) effect on the orbital movement of the electrons. To theoretically understand the behaviour of the correlated insulating states in a magnetic field, we first have to identify their ground state. Figure 3f, g shows the evolution of the thermal activation gap of the $n_{\\mathrm{s}}/2$ state in both $B_{\\perp}$ and $B_{\\parallel}$ . We find a $g$ -factor of $g_{\\perp}{\\approx}3.5$ for the perpendicular direction (up to 5 T before the shift occurs) and a $g$ -factor of $g_{\\scriptscriptstyle||}\\approx1.5$ for the in-plane direction. $g_{\\parallel}$ is close to (but less than) $g=2$ , which is expected for a spin-polarized ground state with contribution from only the electron spins. This difference is theoretically expected because of finite in-plane orbital effects27. Therefore, on the basis of these measurements, we may conclude that the correlated insulating states have a spin-polarized nature. These observations establish TBBG as a distinctive system from the previously reported magic-angle TBG system1,2,9, which exhibits half-filling insulating states that are shown to be spin unpolarized, as they are suppressed by an in-plane magnetic field. In $B_{\\perp}$ , however, one would expect orbital effects to have a more substantial role. We may attribute the larger $g_{\\perp}$ of about 3.5 to exchange-induced enhancement effects, similar to what is observed in Landau levels of gallium arsenide quantum wells and graphene28,29. In Extended Data Fig. 4, we provide additional magnetic field response data for the $n_{\\mathrm{s}}/4$ and the $3n\\mathrm{\\Omega}/4$ states. Both of these states also exhibit a spin-polarized behaviour, as they become more resistive under the in-plane magnetic field. \n\nIn addition to the discussion above, we noticed that all the correlated insulating states in the $\\theta=1.23^{\\circ}$ TBBG device, whether at zero magnetic field or high magnetic fields, lie within the range $D/\\varepsilon_{0}{\\approx}-0.6$ to $-0.2\\mathsf{V}\\mathsf{n m}^{-1}$ . Coincidentally, this is also the range where both the gap at the charge neutrality $(n=0)$ and the gap at the superlattice density $(n=n_{s})$ are well developed (that is, the case in Fig. 2f). On the basis of this observation, we suggest that the displacement field tunability of the correlated states is tied to the modulation of the single-particle bandgaps by the displacement field27. When either gap at $\\scriptstyle n=0$ or $\\scriptstyle n=n_{s}$ is absent, the thermally excited or disorder-scattered carriers from the upper or lower bands would suppress the ordering of the electrons and hence the correlated states. Further theoretical work is needed to reveal the detailed structure of the displacement field dependence of the correlated states. \n\n![](images/62bd8fb9b20a73329b7fe39e0d935d7f8576eb955e60f46bf79f6d13517a0355.jpg) \nFig. 4 | Correlated insulator states in a multi-flat-band system. a, b, Calculated band structure of $\\theta{=}0.84^{\\circ}$ TBBG without an interlayer potential (a) and with an interlayer potential $\\Delta V=18\\mathrm{mV}$ (b). Near charge neutrality, within a 50-meV window, there are in total six sets of flat bands spanning densities $-3n_{s}\\mathbf{to}3n_{s}$ . Upon applying a displacement field, these bands are further flattened and separated from each other, which makes them more prone to giving rise to correlated states at each half-filling. c, Resistance map of $\\mathsf{a}\\theta{=}0.84^{\\circ}$ TBBG device measured at ${\\cal T}{=}0.07\\kappa$ . The top axis is the charge density normalized to the superlattice density $n_{s}$ . Besides the $D$ -tunable gaps at multiples of $\\dot{n}_{\\mathrm{s}}$ we find signatures of correlated states at $n/n_{\\mathrm{s}}{=}{-}1/2,{-}1/4$ for $|D|/\\varepsilon_{0}>0.4\\mathsf{V}\\mathsf{n m}^{-1}$ , which are indicated by dashed circles. d, Resistance as a \nfunction of charge density and perpendicular magnetic field B when a displacement is present, $D/\\varepsilon_{0}=0.6\\mathsf{V}\\mathsf{n m}^{-1}$ . We find clear correlated states at $n/n_{s}{=}-1/2,1/4$ and 1/2, and also evidences at 3/2 and 5/2 fillings, as indicated by arrows (blue and green arrows indicate half-fillings and quarter-filling, respectively). e, For comparison, when no displacement field is present, we do not find any signature of half-filling correlated states. Owing to the formation of a superlattice, we also observe Hofstadter butterfly related features when $B$ is such that the magnetic flux in each unit cell is equal to $\\varphi_{\\scriptscriptstyle0}/2,\\varphi_{\\scriptscriptstyle0}/3,\\varphi_{\\scriptscriptstyle0}/4$ and so on, where $\\varphi_{\\mathrm{0}}=h/e$ is the flux quantum, h and e being Planck’s constant and electron charge, respectively. \n\nWe have also investigated the regime of substantially smaller twist angles. Unlike the case of TBG, further reduction of the twist angle of TBBG to $0.84^{\\circ}$ results not in one, but rather three pairs of flat bands, separated from other bands by bandgaps (Fig. 4a). The application of an electrical displacement field further flattens these bands and separates them from each other (Fig. 4b). This would imply that all electrons within the density range $-3n_{\\mathrm{s}}$ to $+3n_{\\mathrm{s}}$ might experience strong Coulomb interactions and that their correlations can get further enhanced by applying a displacement field. These predictions from the band theory are consistent with our experimental observations. In Fig. 4c, where we show the resistance map of the $\\theta{=}0.84^{\\circ}$ TBBG device versus $n$ and $D$ , we indeed find that the weak signatures of the $-n\\sqrt{2}$ and $-n_{\\mathrm{s}}/4$ correlated insulating states appear only at high displacement fields $|D|/\\varepsilon_{0}{>}0.4\\mathsf{V}\\mathsf{m}^{-1}$ (encircled by white dashed lines). The full-filling gaps at $\\pm n_{s}$ and $\\pm2n_{\\mathrm{s}}$ are tunable by the displacement field to different extents as well. \n\nAs we turn on a perpendicular magnetic field, a series of correlated insulator states appear across the entire density range spanning the multiple flat bands. Figure 4d, e shows the Landau fan diagrams at $D/\\varepsilon_{0}{=}0.6\\mathsf{V}\\mathsf{m}^{-1}$ and $D=0$ , respectively. At zero displacement field, the Landau fan shows a complicated Hofstadter butterfly pattern due to commensurate flux threading into the unit cell12–14 (see also Methods, Extended Data Fig. 2), but no correlated state is observed at half-fillings or quarter-fillings. We note that a resistive region appears at $n{\\approx}1.63n_{\\mathrm{s}}$ in Fig. 4e, which does not coincide with any commensurate filling and might be ascribed to twist-angle inhomogeneity in the sample. In contrast, at $D/\\varepsilon_{0}=0.6\\ V\\mathrm{nm^{-1}}$ , we find clear signatures of correlated states at $n_{\\mathrm{s}}/2$ and $-n\\sqrt{2}$ in the centre flat bands, and weak evidences at $3n_{\\mathrm{s}}/2$ and $5n_{\\mathrm{s}}/2$ in the upper flat bands. All of these half-filling correlated states appear to be enhanced by the application of a perpendicular magnetic field, which we attribute to the same spin/orbital combined enhancement of the correlated gaps as in the $n_{\\mathrm{s}}/2$ state of the $\\theta{=}1.23^{\\circ}$ device (Fig. 3f). The correlated states at $\\pm n\\sqrt{2}$ appear to be much stronger than the states at $3n\\mathrm{\\sqrt{2}}$ and $5n_{\\mathrm{s}}/2$ in high magnetic fields, consistent with the fact that from our calculations, the pair of bands closer to charge neutrality is much flatter than the other two pairs farther away from charge neutrality, as can be seen in Fig. 4b. The resistance of the quarter-filling state at $n_{s}/4$ , however, does not increase monotonically with the perpendicular field, but rather eventually gets suppressed at $5\\mathsf{T}$ . \n\nOur results show that TBBG exhibits a rich spectrum of correlated phases tunable by twist angle, electric displacement field and magnetic field, enabling further studies of strongly correlated physics and topology in multi-flat-band systems21. \n\n# Article \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-020-2260-6. \n\n1. Cao, Y. et al. Correlated insulator behaviour at half-filling in magic-angle graphene superlattices. Nature 556, 80–84 (2018). \n2. Cao, Y. et al. Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43–50 (2018). \n3. Suárez Morell, E., Correa, J. D., Vargas, P., Pacheco, M. & Barticevic, Z. Flat bands in slightly twisted bilayer graphene: tight-binding calculations. Phys. Rev. B 82, 121407 (2010). \n4. Bistritzer, R. & MacDonald, A. H. Moiré bands in twisted double-layer graphene. Proc. Natl Acad. Sci. USA 108, 12233–12237 (2011). \n5. Lopes dos Santos, J. M. B., Peres, N. M. R. & Castro Neto, A. H. Continuum model of the twisted graphene bilayer. Phys. Rev. B 86, 155449 (2012). \n6. Carr, S. et al. Twistronics: manipulating the electronic properties of two-dimensional layered structures through their twist angle. Phys. Rev. B 95, 075420 (2017). \n7. McCann, E. & Koshino, M. The electronic properties of bilayer graphene. Rep. Prog. Phys. 76, 056503 (2013). \n8. Castro Neto, A. H., Guinea, F., Peres, N. M. R., Novoselov, K. S. & Geim, A. K. The electronic properties of graphene. Rev. Mod. Phys. 81, 109–162 (2009). \n9. Yankowitz, M. et al. Tuning superconductivity in twisted bilayer graphene. Science 363, 1059–1064 (2019). \n10. Sharpe, A. L. et al. Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene. Science 365, 605–608 (2019). \n11. Lu, X. et al. Superconductors, orbital magnets and correlated states in magic-angle bilayer graphene. Nature 574, 653–657 (2019). \n12. Hunt, B. et al. Massive Dirac fermions and Hofstadter butterfly in a van der Waals heterostructure. Science 340, 1427–1430 (2013). \n13.\t Ponomarenko, L. A. et al. Cloning of Dirac fermions in graphene superlattices. Nature 497, 594–597 (2013). \n14.\t Dean, C. R. et al. Hofstadter’s butterfly and the fractal quantum Hall effect in moiré superlattices. Nature 497, 598–602 (2013). \n15.\t Krishna Kumar, R. et al. High-temperature quantum oscillations caused by recurring Bloch states in graphene superlattices. Science 357, 181–184 (2017). \n16.\t Li, G. et al. Observation of Van Hove singularities in twisted graphene layers. Nat. Phys. 6, 109–113 (2010). \n17. Chen, G. et al. Evidence of a gate-tunable Mott insulator in a trilayer graphene moiré superlattice. Nat. Phys. 15, 237–241 (2019). \n18. Chen, G. et al. Signatures of tunable superconductivity in a trilayer graphene moiré superlattice. Nature 572, 215–219 (2019). \n19. Oostinga, J. B., Heersche, H. B., Liu, X., Morpurgo, A. F. & Vandersypen, L. M. K. Gate-induced insulating state in bilayer graphene devices. Nat. Mater. 7, 151–157 (2008). \n20.\t Zhang, Y. et al. Direct observation of a widely tunable bandgap in bilayer graphene. Nature 459, 820–823 (2009). \n21.\t Zhang, Y.-H., Mao, D., Cao, Y., Jarillo-Herrero, P. & Senthil, T. Nearly flat Chern bands in moiré superlattices. Phys. Rev. B 99, 075127 (2019). \n22. Cao, Y. et al. Superlattice-induced insulating states and valley-protected orbits in twisted bilayer graphene. Phys. Rev. Lett. 117, 116804 (2016). \n23.\t Kim, Y. et al. Charge inversion and topological phase transition at a twist angle induced Van Hove singularity of bilayer graphene. Nano Lett. 16, 5053–5059 (2016). \n24.\t Koshino, M. Band structure and topological property of twisted double bilayer graphenes. Phys. Rev. B 99, 235406 (2019). \n25.\t Polshyn, H. et al. Large linear-in-temperature resistivity in twisted bilayer graphene. Nat. Phys. 15, 1011–1016 (2019). \n26.\t Cao, Y. et al. Strange metal in magic-angle graphene with near Planckian dissipation. Phys. Rev. Lett. 124, 076801 (2020). \n27.\t Lee, J. Y. et al. Theory of correlated insulating behaviour and spin-triplet superconductivity in twisted double bilayer graphene. Nat. Commun. 10, 5333 (2019). \n28.\t Raymond, A. et al. Gigantic exchange enhancement of spin $g$ -factor for two-dimensional electron gas in GaAs. Solid State Commun. 55, 271–274 (1985). \n29.\t Young, A. F. et al. Spin and valley quantum Hall ferromagnetism in graphene. Nat. Phys. 8, 550–556 (2012). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 \n\n# Methods \n\n# Fabrication and measurement \n\nThe reported devices were fabricated with two sheets of Bernal-stacked bilayer graphene and encapsulated by two hexagonal boron nitride (hBN) flakes. Both bilayer graphene and hBN were exfoliated on $\\mathsf{S i O}_{2}/\\mathsf{S i}$ substrates, and the thickness and quality of the flakes were confirmed with optical microscopy and atomic force microscopy. A modified polymer-based dry pick-up technique was used for the fabrication of the heterostructures. A poly(bisphenol A carbonate) (PC)/ polydimethylsiloxane (PDMS) layer on a glass slide was positioned in the micro-positioning stage to first pick up an hBN flake at around $100^{\\circ}\\mathsf C$ . The van der Waals interaction between the hBN and bilayer graphene then allowed us to tear the bilayer graphene flake, which was then rotated at a desired angle and stacked at room temperature. The resulting hBN/bilayer graphene/bilayer graphene heterostructure was released on another hBN flake on a palladium/gold back gate that was pre-heated to $170^{\\circ}\\mathrm{C}$ , using a hot-transfer method30,31. The desired geometry of the devices was achieved with electron beam lithography and reactive ion etching. The electrical contacts and top gate were deposited by thermal evaporation of chromium/gold, making edge contacts to the encapsulated graphene32. \n\nElectronic transport measurements were performed in a dilution refrigerator with a superconducting magnet, with a base electronic temperature of $70\\mathrm{mK}$ . The data were obtained with low-frequency lock-in techniques. We measured the current through the sample amplified by $10^{7}\\mathsf{V}\\mathsf{A}^{-1}$ and the four-probe voltage amplified by 1,000, using SR-830 lock-in amplifiers that were all synchronized to the same frequency between around 1 and $20{\\mathsf{H}}z$ . For resistance measurements, we typically used a voltage excitation of less than $100\\upmu\\upnu$ or current excitation of less than 10 nA. \n\n# List of measured TBBG devices \n\nFollowing the definition given in the main text and accounting for offsets in the gate voltages due to impurity doping, $n$ and $D$ are related to the top and bottom gate voltages $V_{\\mathrm{tg}}$ and $V_{\\mathrm{bg}}$ by \n\n$$\nn=[c_{\\mathrm{tg}}(V_{\\mathrm{tg}}-V_{\\mathrm{tg},0})+c_{\\mathrm{bg}}(V_{\\mathrm{bg}}-V_{\\mathrm{bg},0})]/e\n$$ \n\n$$\nD=[-c_{\\mathrm{tg}}(V_{\\mathrm{tg}}-V_{\\mathrm{tg,0}})+c_{\\mathrm{bg}}(V_{\\mathrm{bg}}-V_{\\mathrm{bg,0}})]/2\n$$ \n\nExtended Data Table 1 lists the twist angles and parameters $c_{\\mathrm{tg}}$ (top gate capacitance per area), $c_{\\mathrm{{bg}}}$ (bottom gate capacitance per area), $V_{\\mathrm{tg},0}$ (top gate voltage offset), $V_{\\log,0}$ (bottom gate voltage offset) and $n_{\\mathrm{s}}$ (superlattice density) for all devices discussed in this work, including those shown in the Extended Data figures. $e$ is unit electron charge. These parameters are estimated to satisfy that all diagonal features in the $V_{\\mathrm{tg}}^{}{-}V_{\\mathrm{bg}}$ maps are rotated to be vertical in the corresponding $n{-}D$ maps, and the features should be symmetrical with respect to $D=0$ after the transformation. \n\nIn Extended Data Fig. 1a–f, we show $V_{\\mathrm{tg}}^{}{-}V_{\\mathrm{bg}}^{}$ resistance maps for all six TBBG devices we measured. Extended Data Fig. 1c, d was measured in the same TBBG sample, but in different sample regions that are approximately $27\\upmu\\mathrm{m}$ apart (sections 1 and 2, respectively). Both regions have identical parameters (hence the two identical rows in Extended Data Table 1), with the same twist angle $\\theta{=}1.23^{\\circ}$ , and also nearly identical transport characteristics. The two sections are electrically disconnected via etching, but the extracted twist angles from the data have a difference of less than $0.01^{\\circ}$ , suggesting very uniform twist angles across this entire sample. \n\nIn almost all TBBG samples, we noticed a peculiar cross-like pattern around $(n,D)=(-n\\sqrt{2},0)$ , that is, near p-side half-filling of the superlattice band. This is especially apparent in the $1.09^{\\circ}$ and $1.23^{\\circ}$ devices, which are highlighted in Extended Data Fig. 1g, h. The p-side band does not exhibit a strong $D$ -tunable correlated state as elaborated in the main text, possibly due to the larger bandwidth compared with its n-side counterpart. This cross-like pattern might represent an onset of correlated behaviour near half-filling of the band. Further experimental work and theoretical insight are needed to understand this phenomenon. \n\n# Sample quality and Landau fans \n\nTo demonstrate the high quality of our fabricated TBBG devices, we measured the Landau fan diagrams and Hall mobilities of all three devices discussed in the main text, as shown in Extended Data Fig. 2. The Hall mobilities are extracted from the ratio between the Hall coefficient $R_{\\mathrm{H}}$ and longitudinal resistance at small magnetic fields $(B<0.5\\mathsf{T})$ . All three samples exhibit high Hall mobilities close to or above $100,000{\\mathrm{cm}}^{2}{\\boldsymbol{\\mathsf{V}}}^{-1}{\\boldsymbol{\\mathsf{s}}}^{-1}$ . \n\nAll three devices also show clear Landau fans starting from about 1 T. The filling factor of each level is labelled in the lower panels of each plot. In particular, due to the lower angle of the $\\theta{=}0.84^{\\circ}$ device, its Landau fan displays a complicated Hofstadter’s butterfly pattern starting from 3 T. \n\n# Linear R–T behaviour \n\nExtended Data Fig. 3 shows the resistance versus temperature behaviour, at different densities, observed across several small-angle TBBG devices. In the $1.23^{\\circ}$ device, we find approximately linear $R{-}T$ behaviour above 10 K for densities ranging from around $0.5\\times10^{12}$ to $2.5\\times10^{12}{\\mathrm{cm}}^{-2}$ , encompassing the $n_{\\mathrm{s}}/2$ correlated state. The resistance slope in this range of densities does not vary very substantially, ranging from around 210 to $350\\Omega\\mathsf{K}^{-1}$ . As all our devices have length-to-width ratios close to one, these slope values are therefore close to those reported in TBG25,26. In stark contrast, the resistance behaviour in the hole-doping side $(n<0)$ , as shown in Extended Data Fig. 3b, shows qualitatively different behaviour: it does not show linear $R{-}T$ characteristics, at least up to $30\\mathsf{K}$ , and the resistance value is about an order of magnitude smaller than on the electron-doping side. These data are consistent with the picture that the electron-doping band is flatter than the hole-doping band, therefore exhibiting more pronounced correlated phenomena, examples being the $n_{s}/2$ insulator state and the linear $R{-}T$ behaviour. Extended Data Fig. 3c shows $R{-}T$ curves close to the $n_{\\mathrm{s}}/2$ state. \n\nThe data for the $1.09^{\\circ}$ device show a similar trend of linear R–T behaviour starting around $_{5-10\\mathsf{K}}$ , as shown in Extended Data Fig. 3d. \n\nIn the $0.84^{\\circ}$ device, we find a very different behaviour. There is a region of sublinear or approximately linear R–T behaviour at all densities, except at multiples of $\\dot{n}_{\\mathrm{s}}$ , but the resistance slope is now strongly dependent on the charge density $n$ . The slope approximately follows a power la w dRTxx ∝ na where a ≈ −1.77 (see inset). \n\n# Theoretical methods \n\nThe band structures shown in the main text are calculated using a continuum model based on the original continuum model for $\\mathsf{T B G}^{4,5}$ , which qualitatively captures most of the important features of the bands in TBBG including displacement-field dependence. To the lowest order, the continuum model of twisted graphene superlattices is built on the approximation that the interlayer coupling between the A/B sublattice of one layer and the $\\mathbf{A}/\\mathbf{B}$ sublattice of the other layer has a sinusoidal variation over the periodicity of the moiré pattern. For the three possible directions of interlayer connections between the wave vectors in the Brillouin zone, there are three connection matrices \n\n$$\nH_{1}=w\\left(\\begin{array}{c c}{{1}}&{{1}}\\\\ {{1}}&{{1}}\\end{array}\\right)\n$$ \n\n$$\nH_{2}{=}w\\left(\\begin{array}{c c}{{\\omega^{2}}}&{{1}}\\\\ {{\\omega}}&{{\\omega^{2}}}\\end{array}\\right)\n$$ \n\n# Article \n\n$$\nH_{3}=w\\left(\\begin{array}{l l}{\\omega}&{1}\\\\ {\\omega^{2}}&{\\omega}\\end{array}\\right)\n$$ \n\nwhere $w$ is the interlayer hopping energy and $\\omega=\\exp(2\\uppi i/3).H_{i,\\alpha\\beta},$ with $\\alpha\\beta{=}\\mathsf{A}$ , B represents the hopping between sublattice $\\alpha$ in the first layer to sublattice $\\beta$ in the second layer, with momentum transfer determined by i (see ref. 4 for definition). Note that in this gauge choice, the origin of rotation is chosen where the B sublattice of the first layer coincides with the A sublattice of the second layer, so that the $H_{i,\\mathrm{BA}}$ component has zero phase while the other terms acquire phases. A different gauge choice is equivalent to an interlayer translation, which has been shown to have a negligible effect in the case of small twist angles4,5. \n\nTo extend this formulation to TBBG, we add a simplified bilayer graphene Hamiltonian \n\n$$\nH_{\\mathrm{b}}{=}\\left(\\begin{array}{l l}{0}&{0}\\\\ {w_{\\mathrm{b}}}&{0}\\end{array}\\right)\n$$ \n\nbetween the non-twisted layers. The momentum transfer is zero since the bilayers are not twisted and the coupling is constant over the moiré unit cell. For simplicity, we consider only the ‘dimer’ coupling in the bilayer, neglecting second-nearest-neighbour hopping terms and trigonal warping terms. The two bilayers in TBBG (layers 1–2 and layers 3–4) have the same stacking order, that is, for zero twist angle the total stacking would be ‘ABAB’ instead of ‘ABBA’. In the calculations used in the main text, we used parameters $\\scriptstyle w=0.1{\\mathrm{eV}}$ and $\\begin{array}{r}{w_{\\mathrm{b}}=0.4\\mathrm{eV},}\\end{array}$ so that when either parameter is turned off we obtain either the two non-interacting bilayer graphene $(w=0)$ or the non-interacting TBG and two-monolayer graphene $\\begin{array}{r}{(w_{\\mathrm{b}}=0)}\\end{array}$ ). \n\n# Additional magnetic-field-response data \n\nExtended Data Fig. 4 shows the response of correlated states at $n_{\\mathrm{s}}/4$ and $3n\\mathrm{{\\sqrt{4}}}$ in a perpendicular or in-plane magnetic field, similar to Fig. 3d, e, for the $\\theta{=}1.23^{\\circ}$ device. For the $n_{\\mathrm{s}}/4$ state, we also find a signature of a phase transition at $D/\\varepsilon_{0}=-0.36\\mathrm{V}\\mathsf{n m}^{-1}$ , manifesting as a shift of the $D$ location of the correlated insulator as $B_{\\perp}$ exceeds $6\\mathsf{T}.$ The $3n\\mathrm{\\Omega}/4$ state shows an overall monotonic increase of resistance and exhibits no shift in the position in $D$ . In an in-plane field, however, as shown in Extended Data Fig. 4b, d, both quarter-filling states show a monotonic enhancement as $B_{\\parallel}$ is increased, suggesting that they may have a similar spin-polarized ground state as the $n_{\\mathrm{s}}/2$ state. \n\n# Current–voltage curves and the impact of excitation current on ${\\pmb g}$ -factor \n\nIn Extended Data Fig. 5, we have plotted the current–voltage $(I{-}V)$ curves and differential resistance curves of the $\\theta{=}1.23^{\\circ}$ device when it is in the correlated insulator states at $n_{\\mathrm{s}}/4$ and $n_{\\mathrm{s}}/2$ . In the insulator states, we find a highly nonlinear region near zero d.c. bias $I_{\\mathrm{b}}{=}0$ where the differential resistance $\\mathrm{d}V_{x x}/\\mathrm{d}I_{\\mathrm{b}}$ is substantially enhanced. This is in agreement with the existence of a small energy gap, which is overcome at higher bias voltages/currents. Outside of the insulator regions (such as shown in Extended Data Fig. 5b), the I–V curves are mostly linear. For measuring the $g\\mathrm{.}$ -factors at $n_{\\mathrm{s}}/2$ , we therefore used a much smaller excitation current of 0.1 nA to truthfully measure the differential resistance at $I_{\\mathrm{b}}{=}0$ . \n\nWe comment here on the effect of the a.c. excitation current on the measured gap sizes and the $g$ -factor. When sourcing an a.c. bias current to measure the resistance using a lock-in technique, we effectively measure a weighted average of the differential resistance near zero bias. Owing to the highly nonlinear I–V curve at the $n_{\\mathrm{s}}/2$ state, if the a.c. excitation is large, this average value will be much less than the peak value. Furthermore, the average value measured in this case can have a very different temperature dependence compared with the zero-bias value. For example, although to the best of our knowledge there is no detailed analysis of the high-bias behaviour in the correlated insulator state of TBG, TBBG or related systems, if one considers the high-bias transport to have a contribution from a mechanism similar to Zener breakdown in semiconductors in an electrical field, the current is essentially independent of the temperature. There could be other contributions to the high-bias transport as well, but in general their temperature dependence would not be identical to the zero-bias peak. In the Arrhenius fit that we use to extract the gap size, the gap size Δ is basically equal to how fast the resistance exponentially rises with $T^{1}$ . Therefore, a reduction of temperature dependence means that by averaging the higher bias differential resistance one would substantially underestimate the energy gap Δ, and also the $g$ -factor $g\\propto\\delta{\\varDelta}/\\delta{\\varDelta}$ . \n\nIn Extended Data Fig. 6, we compare the Arrhenius fits of the resistance at $n_{\\mathrm{s}}/2$ and $n_{\\mathrm{s}}/4$ states, using a small excitation (0.1 nA) and a larger excitation (around 5–10 nA). We indeed find that by using an excessive excitation, both the gap size Δ and the $g\\mathrm{.}$ factor are substantially underestimated. In particular, owing to the larger nonlinearity at the $n_{s}/2$ state, its $g\\mathrm{.}$ factor is underestimated by a factor of about three by using the larger excitation. Therefore, one should keep these nonlinear effects in mind when doing temperature-dependent measurements on such resistive states to obtain accurate results. \n\n# Data availability \n\n# The data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\n30.\t Pizzocchero, F. et al. The hot pick-up technique for batch assembly of van der Waals heterostructures. Nat. Commun. 7, 11894 (2016). \n31.\t Purdie, D. G. et al. Cleaning interfaces in layered materials heterostructures. Nat. Commun. 9, 5387 (2018). \n32.\t Wang, L. et al. One-dimensional electrical contact to a two-dimensional material. Science \n342, 614–617 (2013). \n\nAcknowledgements We acknowledge discussions with S. Todadri, L. Fu, P. Kim, X. Liu, S. Fang and E. Kaxiras. This work was supported by the National Science Foundation under award DMR-1809802 (data analysis by Y.C.), the Center for Integrated Quantum Materials under NSF grant DMR-1231319 (fabrication by D.R.-L.), the US DOE, BES Office, Division of Materials Sciences and Engineering under award DE-SC0001819 (g-factor analysis by J.M.P.), and the Gordon and Betty Moore Foundation's EPiQS Initiative through grant GBMF4541 to P.J.-H. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT, Japan, A3 Foresight by JSPS and the CREST (JPMJCR15F3), JST. This work made use of the Materials Research Science and Engineering Center Shared Experimental Facilities supported by the National Science Foundation (DMR-0819762) and of Harvard’s Center for Nanoscale Systems, supported by the NSF (ECS-0335765). D.R.-L. acknowledges partial support from Fundació Bancaria “la Caixa” (LCF/BQ/AN15/10380011) and from the US Army Research Office grant number W911NF-17-S-0001 (measurements). O.R.-B. acknowledges support from Fundació Privada Cellex. \n\nAuthor contributions Y.C., D.R.-L., O.R.-B. and J.M.P contributed to sample fabrication and transport measurements. Y.C., D.R.-L., O.R.-B., J.M.P and P.J.-H. performed data analysis. K.W. and T.T. provided h-BN samples. Y.C., D.R.-L., O.R.-B., J.M.P. and P.J.-H. wrote the manuscript with input from all co-authors. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nCorrespondence and requests for materials should be addressed to Y.C. or P.J.-H. Peer review information Nature thanks Ming-Hao Liu, Hu-Jong Lee and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/bb50b7a7400a6fcf16e630c00672e1a5f3ee27945a8fc6e7abec59e3b79c6d3c.jpg) \nExtended Data Fig. 1 $V_{\\mathrm{tg}}^{}-V_{\\mathrm{bg}}^{}$ resistance maps of measured TBBG devices. a–f, Resistance versus $V_{\\mathrm{tg}}$ and $V_{\\mathrm{bg}}$ for the six TBBG devices measured, which correspond to the six rows shown in Extended Data Table 1, respectively. \ng, h, Cross-like feature near $-n_{\\mathrm{s}}/2$ in TBBG samples with twist angles $\\theta=1.23^{\\circ}\\left(\\mathbf{g}\\right)$ and $\\theta{=}1.09^{\\circ}\\left(\\mathbf{h}\\right)$ , which might signal the onset of a correlated state. \n\n# Article \n\n![](images/1dfac528a6e78b6aa4db2578c70ea1ea082a40114416d23deb67f296f76b844c.jpg) \nExtended Data Fig. 2 | Landau fan diagrams and Hall mobilities of the TBBG devices. a, Resistance of the $1.09^{\\circ}$ sample versus carrier density and perpendicular magnetic field. b, Hall mobility $\\mu_{\\mathrm{Hall}}$ (left axis) and Hall coefficient $R_{\\mathrm{H}}$ (right axis) in the $1.09^{\\circ}$ sample at different carrier densities. \n\n![](images/9de79f0e581694fed2d889d4a3f1895af67bf5c5b5486fe0d46c0c4b96a02489.jpg) \nc–f, Same measurements as in a, b but for the $0.84^{\\circ}(\\mathbf{c},\\mathbf{d})$ and $1.23^{\\circ}$ (e, f) samples, respectively. All measurements are taken at $T{<}100\\mathsf{m K}$ . The data for the $1.09^{\\circ}$ device are taken at $D/\\varepsilon_{0}=0.2\\mathsf{V}\\mathsf{n m}^{-1}$ while the data for the other two devices are taken at $D=0$ . \n\n![](images/17953dfdf233518d3c0e8b92b2d43241dd301087f07e31187e9fc122fbe96188.jpg) \nExtended Data Fig. 3 | Linear resistance versus temperature behaviour in R–T behaviour in the $1.09^{\\circ}$ device. The inset shows the slope $\\mathrm{d}R_{x x}/\\mathrm{d}T.$ TBBG. a, b, Resistance versus temperature curves at different charge densities e, Density-dependent sublinear/linear R–T behaviour in the $0.84^{\\circ}$ device. The in the $..23^{\\circ}$ sample for the electron-doping side (a) and the hole-doping side (b). inset shows the slope $\\mathrm{d}R_{x x}$ /dT versus n in log–log scale. The slope is The inset in a shows the slope $\\mathrm{d}R_{x x}/\\mathrm{d}T$ of the linear R–T behaviour as a function proportional to $n$ to the power of −1.77. of $\\dot{n}$ for ${\\cal T}{\\bf>}{\\bf10}{\\bf K}.$ c, Selected R–T curves near $n_{\\mathrm{s}}/2$ from a. d, Similar linear \n\n# Article \n\n![](images/fb98dbbc25afe4cac288dadc881567c7bc7d4009796ff70c4ed5b1233fb91724.jpg) \nExtended Data Fig. 4 | Additional magnetic field response of TBBG devices. a–d, Response of the $n_{s}/4$ (a, b) and $3n\\mathrm{\\sqrt{4}}$ (c, d) states in perpendicular magneti field (a, c) and in-plane magnetic field (b, d) for the $\\theta{=}1.23^{\\circ}$ device. \n\n![](images/1cc95f59332f3fd2a2e320118c7446fa2683b6e857162cc81c87c1b400098c46.jpg) \nExtended Data Fig. 5 | I–V curves in the 1 $.23^{\\circ}$ TBBG device at different b lies between them. The left axis is the longitudinal voltage $V_{x x}$ and the right carrier densities. $D/\\varepsilon_{\\scriptscriptstyle0}=-0.38\\mathrm{V}\\mathrm{nm}^{-1}$ . $\\mathsf{a-c}$ , The densities correspond axis is the differential resistance $\\mathrm{d}V_{x x}/\\mathrm{d}I_{\\mathrm{b}}$ . approximately to the $n_{s}/4$ (a) and $n_{s}/2$ (c) insulating states while the density for \n\n# Article \n\n![](images/a7561eb9e63d601868d4eb7f631eb9ae68fb17116de153430ae9892732d932f2.jpg) \nExtended Data Fig. 6 | Comparison of the gap sizes and the g-factor using small and large excitations. a, b, The Arrhenius fits of the resistance at the $n_{\\mathrm{s}}/2$ state of the $1.23^{\\circ}$ TBBG device in an in-plane magnetic field. c, d, The same fits for the $n_{s}/4$ state. a and c are measured using a current excitation of 0.1 nA, \n\nwhile b and d are measured using a voltage excitation of around $100\\upmu\\upnu_{\\cdot}$ , which induces a current of around 5–10 nA in the sample. The insets in each panel show the corresponding g-factor fittings. In general, by using an excessive excitation, both the energy gaps and the $g$ -factor will be underestimated. \n\nExtended Data Table 1 | List of TBBG devices discussed in the main text and Extended Data figures \n\n\n
0()Ctg(F/m²)Cbg(F/m²)Vtg,o(V)Vbg,o(V)ns(cm-2)
1.096.63×10-45.02×10-40.300.582.75×1012
1.231.06×10-37.14×10-40.41-0.043.55×1012
1.231.06×10-37.14×10-40.41-0.043.55×1012
0.846.87×10-46.38×10-40.060.081.65×1012
0.791.06×10-33.57×10-40.180.671.45×1012
1.09(*)1.03×10-35.12×10-40.280.452.75×1012
\n\nThe last device is marked with an asterisk to differentiate it from the first device, which happens to have the same twist angle, but it is a totally independent device fabricated on a separate chip. " + }, + { + "id": "10.1038_s41467-020-19214-w", + "DOI": "10.1038/s41467-020-19214-w", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-19214-w", + "Relative Dir Path": "mds/10.1038_s41467-020-19214-w", + "Article Title": "Engineering active sites on hierarchical transition bimetal oxides/sulfides heterostructure array enabling robust overall water splitting", + "Authors": "Zhai, PL; Zhang, YX; Wu, YZ; Gao, JF; Zhang, B; Cao, SY; Zhang, YT; Li, ZW; Sun, LC; Hou, JG", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Rational design of the catalysts is impressive for sustainable energy conversion. However, there is a grand challenge to engineer active sites at the interface. Herein, hierarchical transition bimetal oxides/sulfides heterostructure arrays interacting two-dimensional MoOx/MoS2 nullosheets attached to one-dimensional NiOx/Ni3S2 nullorods were fabricated by oxidation/hydrogenation-induced surface reconfiguration strategy. The NiMoOx/NiMoS heterostructure array exhibits the overpotentials of 38mV for hydrogen evolution and 186mV for oxygen evolution at 10mAcm(-2), even surviving at a large current density of 500mAcm(-2) with long-term stability. Due to optimized adsorption energies and accelerated water splitting kinetics by theory calculations, the assembled two-electrode cell delivers the industrially relevant current densities of 500 and 1000mAcm(-2) at record low cell voltages of 1.60 and 1.66V with excellent durability. This research provides a promising avenue to enhance the electrocatalytic performance of the catalysts by engineering interfacial active sites toward large-scale water splitting. While water splitting is an appealing carbon-neutral strategy for renewable energy generation, there is a need to develop new active, cost-effective catalysts. Here, authors prepare a nickel-molybdenum oxide/sulfide heterojunctions as bifunctional H-2 and O-2 evolution electrocatalysts.", + "Times Cited, WoS Core": 516, + "Times Cited, All Databases": 525, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000591379900004", + "Markdown": "# Engineering active sites on hierarchical transition bimetal oxides/sulfides heterostructure array enabling robust overall water splitting \n\nPanlong Zhai1,5, Yanxue Zhang2,5, Yunzhen Wu1,5, Junfeng Gao2, Bo Zhang1, Shuyan Cao1, Yanting Zhang1, Zhuwei Li1, Licheng Sun $\\textcircled{1}$ 1,3,4 & Jungang Hou1✉ \n\nRational design of the catalysts is impressive for sustainable energy conversion. However, there is a grand challenge to engineer active sites at the interface. Herein, hierarchical transition bimetal oxides/sulfides heterostructure arrays interacting two-dimensional $M O O_{\\times}/\\$ $M o S_{2}$ nanosheets attached to one-dimensional ${\\sf N i O}_{\\sf x}/{\\sf N i}_{3}{\\sf S}_{2}$ nanorods were fabricated by oxidation/hydrogenation-induced surface reconfiguration strategy. The NiMoOx/NiMoS heterostructure array exhibits the overpotentials of $38\\mathsf{m V}$ for hydrogen evolution and 186 $\\mathsf{m V}$ for oxygen evolution at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ , even surviving at a large current density of $500~\\mathrm{{mA}}$ $\\mathsf{c m}^{-2}$ with long-term stability. Due to optimized adsorption energies and accelerated water splitting kinetics by theory calculations, the assembled two-electrode cell delivers the industrially relevant current densities of 500 and $1000\\mathsf{m A c m}^{-2}$ at record low cell voltages of 1.60 and $\\ensuremath{1.66\\vee}$ with excellent durability. This research provides a promising avenue to enhance the electrocatalytic performance of the catalysts by engineering interfacial active sites toward large-scale water splitting. \n\nTifhsesausgiebsln1e. Tastohileountsuosnf itlneo oev narelctroegrmynefa iotvhme wopraroehbry edelrmeocsg onf eisneirsrgayation is electrocatalytic water splitting, involving hydrogen evolution reaction (HER) and oxygen evolution reaction $(\\mathrm{OER})^{2}$ Generally, noble materials, Pt for HER and $\\mathrm{RuO}_{2}$ or $\\mathrm{IrO}_{2}$ for OER, are typical electrocatalysts. Nevertheless, the practical application is limited by the use of noble materials owing to the scarcity and the high cost. To this end, it is interesting to produce bifunctional materials by the integration of OER and HER catalysts towards water splitting in various media3. To address the challenges, catalyzing HER, OER and overall water splitting have been conducted by extensive catalysts, such as oxides, hydroxides, phosphides, nitrides and chalcogenides4–11. Thus, it is urgently needed to design earth-abundant and low-cost non-noble-metal catalysts for industrial applications. \n\nAmong various materials, Mo- and Ni-based sulfides are promising transition-metal electrocatalysts. To improve the performance of these catalysts, various strategies, such as morphology engineering, defect engineering, and heterostructure engineering have been adopted in this field. Architectural nanostructures have been controlled by the synthesis regulation of the electrocatalysts owe to inherent anisotropy and high flexibility5–8. Inspired by the advantages of the architectures, the integration of different nanostructures can effectively optimize the electrocatalytic performance. For example, $\\mathrm{MoO}_{3}$ nanodots supported on $\\ensuremath{\\mathrm{MoS}}_{2}$ monolayer, $\\mathrm{MoNi_{4}}$ anchored $\\mathrm{MoO}_{2}$ cuboids or $\\mathbf{MoO}_{3-\\mathbf{X}}$ nanorods and $\\mathrm{NiS_{2}/N\\mathrm{-NiMoO_{4}}}$ nanosheets/nanowires have been produced for the excellent electrocatalytic water splitting12–15, providing an appealing platform with the hierarchical nanostructures. Apart from morphology engineering, the hybrids can be extensively constructed by use of different transition-metal electrocatalysts through heterostructure engineering, regulating electron transfer and active site as well as the activity owe to the construction of coupling interfaces and the synergistic effect of the heterostructures. For instance, a large number of the heterostructures, such as $\\mathrm{NiMo/NiMoO}_{x}^{\\mathrm{~8~}}$ , $\\mathrm{C\\bar{o}_{3}O_{4}/F e_{0.33}C o_{0.66}P^{16}}$ , $\\mathrm{Ni}_{2}\\mathrm{P}/\\mathrm{Ni}\\mathrm{P}_{2}^{\\phantom{}17}$ $\\mathrm{NiFe(OH)}_{x}/\\mathrm{FeS^{18}}$ , $\\mathrm{Pt}_{2}\\mathrm{W}/\\mathrm{WO}_{3}{}^{19}$ , $\\mathrm{CuCo}/\\mathrm{CuCoO}_{x}^{20}$ , ${\\mathrm{Co}}(\\mathrm{OH})_{2}/$ $\\mathrm{PANI}^{21}$ , $\\mathrm{FeOOH/Co/FeOOH^{22}}$ , ${\\mathrm{Co}}_{0.85}{\\mathrm{Se}}/{\\mathrm{NiFe}}/{\\mathrm{;}}$ graphene23, $\\mathrm{Ni}_{3}\\mathrm{N}/$ $\\mathrm{VN}^{24}$ , NiCu–NiCuN25, have been extensively synthesized for the enhanced electrochemical activities. Typically, sulfides-based heterostructures, such as $\\mathrm{CoS}$ -doped $\\mathrm{\\bar{\\beta}-C o(O H)_{2}/M o S_{2+x}}^{26}$ $\\mathrm{MoS}_{2}/\\mathrm{Fe}_{5}\\mathrm{Ni}_{4}\\mathrm{S}_{8}{}^{27}$ , $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}^{28}$ , $\\bar{\\mathrm{NiS}}_{2}/\\mathrm{MoS}_{2}^{29}$ , $\\mathrm{MoS}_{2}/\\mathrm{Co}_{9}\\mathrm{S}_{8}/$ $\\mathrm{Ni}_{3}\\mathrm{S}_{2}/\\mathrm{Ni}^{30}$ , and $\\mathrm{MoS}_{2}/(\\mathrm{Co},\\mathrm{Fe},\\mathrm{Ni})_{9}\\mathrm{S}_{8}$ coupled FeCoNi-based arrays31, have been systematically explored for the improved activities of electrochemical water splitting. With regard to transition-metal dichalcogenides, $\\mathrm{MoS}_{2}$ and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ materials have been substantially explored as HER electrocatalysts32–35. However, the HER performance of transition metal sulfides is limited by poor charge transport, low active site reactivity, and inefficient electrical contact with the supported catalysts36. Especially, the generation of $\\mathrm{{\\calS}-H_{\\mathrm{ads}}}$ bonds (H atoms adsorption, $\\mathrm{H_{ads}})$ on the surface of metal sulfides is beneficial for $\\mathrm{H}$ adsorption, while it is difficult to conduct the conversion of the $\\mathrm{H}_{\\mathrm{ads}}$ to $\\mathrm{H}_{2}{}^{36,37}$ . However, the OER performance of metal sulfides remains far from satisfactory27–31. Owe to long-time durability as major obstacle, there is less report about the electrocatalysts, delivering large catalytic current densities (e.g., 500 and $1000\\mathrm{mAcm}^{=2}.$ ) for practical application38–41. Based on the above-mentioned analysis, it is essential to design the rational heterostructures through the combined regulation of architectural morphology and heterostructures, engineering active sites, optimizing energy adsorption, and accelerating water splitting kinetics towards large-scale electrolysis. $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ \n\nHerein, three-dimensional (3D) heterostructure array is fabricated by surface reconfiguration strategy through oxygen plasma as oxidation treatment and subsequent hydrogenation regulation by use of NiMoS architecture as the precursor, interacting two-dimensional (2D) $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ nanosheets attached to one-dimensional (1D) $\\mathrm{NiO}_{x}/\\mathrm{Ni}_{3}\\mathrm S_{2}$ nanorods array. As-synthesized $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array presents the remarkable electrocatalytic performance, achieving the low overpotentials of 38, 89, 174, and $236\\mathrm{mV}$ for HER and 186, 225, 278, and $334\\mathrm{mV}$ for OER at 10, 100, 500, and $1000\\mathrm{mAcm}^{-2}$ , even surviving at large current densities of 100 and 500 mA cm−2 with long-term stability. The remarkable electrocatalytic performance of transition bimetal oxides/sulfides heterostructure array as the industrially promising electrocatalyst is ascribed to not only the simultaneous modulation of component and geometric structure, but also the systematic optimization of charge transfer, abundant electrocatalytic active sites, and exceptionally synergistic effect of the heterostructure interfaces. The turnover frequency (TOF) of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array at the overpotential of $100\\mathrm{mV}$ is ${\\sim}45$ times higher than that of NiMoS array. Density functional theory calculations reveal that the coupling interface between $\\mathrm{NiMoO}_{x}$ and NiMoS optimizes adsorption energies and accelerates water splitting kinetics, thus promoting the electrocatalytic performance. Especially, the assembled two-electrode cell by use of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array delivers the industrially required current densities of 500 and $1000\\mathrm{mAcm}^{-2}$ at the low cell voltages of 1.60 and $1.66\\mathrm{V}$ , along with excellent durability, thus holding great promise for industrial water splitting application. \n\n# Results \n\nSynthesis and characterization. The hierarchical $\\mathrm{NiMoO}_{x}/$ NiMoS array was fabricated by oxidation/hydrogenation-induced surface reconfiguration strategy by use of NiMoS precursor, assembling as two-electrode cell towards industrially electrocatalytic water splitting (Fig. 1 and Supplementary Fig. 1). To determine the crystal structure, X-ray diffraction (XRD) patterns of NiMoS-based arrays are showed (Supplementary Fig. 2). Based on the hydrothermal reaction, the representative peaks of the precursors can be assigned to the planes of $\\mathbf{MoS}_{2}$ phase (JCPDS No. 37-1492) and $\\mathrm{Ni}_{3}\\bar{\\mathrm{S}}_{2}$ phase (JCPDS No. 44-1418), confirming the formation of individual $\\mathrm{MoS}_{2}$ and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ as well as $\\ensuremath{\\mathrm{MoS}}_{2}/$ $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructure as the precursors (Supplementary Fig. 2a). After oxygen plasma as oxidation treatment and subsequent hydrogenation regulation, several $\\mathrm{MoO}_{3}$ (JCPDS No.47-1320), $\\mathrm{MoO}_{2}$ (JCPDS No. 50-0739), and NiO (JCPDS No.44-1159) phases as well as the mixed $\\mathrm{MoO_{3}/M o O_{2}/N i O/N i}$ phases are observed in $\\mathbf{MoS}_{2}$ , $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , and $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ (Supplementary Fig. 2b). Thus, all above-mentioned results demonstrate the successful formation of $\\Nu\\mathrm{iO_{x}/N i_{3}S_{2}}$ , $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ and $\\mathrm{NiMoO}_{x}/$ NiMoS heterostructure arrays. \n\nTo confirm the geometric morphologies of individual arrays by scanning electron microscope (SEM), as shown in Fig. 2a, d, $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets as the precursor with an average size over $1\\upmu\\mathrm{m}$ are homogeneously supported on the conductive substrate. While the rough surface of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ array as the precursor is observed (Supplementary Fig. 3). Interestingly, two-dimensional (2D) $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets with an average size below $1\\upmu\\mathrm{m}$ are attached to one-dimensional (1D) $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanorods array on 3D foam substrate, resulting into the formation of hierarchical $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ (denoted as NiMoS) heterostructure array (Fig. 2b, e). After the oxidation/hydrogenation treatment of NiMoS array, there is no obvious change upon the main morphology for 3D $\\mathrm{NiMoO}_{x}/$ NiMoS heterostructure array. However, the small size and rough surface of $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array are observed in comparison of $\\ensuremath{\\mathrm{MoS}}_{2}$ in NiMoS array (Fig. 2cf). Meanwhile, the energy-dispersive X-ray (EDX) spectra and elemental mapping (Fig. 2 and Supplementary Fig. 4) indicate the molar content of $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ about $6.1\\%$ and the homogeneous element distribution in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array. Thus, the abovementioned analysis indicates the formation of $\\mathrm{NiMoO}_{x}/$ NiMoS array as 3D integrated architectures. \n\n![](images/15fe8860f3d3b39379b53ac106e662b640bd82642c90bc40ef9dc306644c549e.jpg) \nFig. 1 Schematic representation of synthesis and overall water splitting. a Synthesis illustration of transition bimetal oxides/sulfides heterostructure array. b NiMoOx/NiMoS array as two-electrode-cell towards large-scale electrolysis. Colored balls represent various elements (blue: Mo, pink: S, red: O, yellow: Ni). \n\n![](images/8708a1035e86ef3d03106c967b1b9def37fa1a4f9465da9529146460cf432b5b.jpg) \nFig. 2 Morphological and structural characterizations. SEM images of a, d $M\\circ\\mathsf{S}_{2}$ , b, e NiMoS, c, f NiMoOx/NiMoS. g–j Elemental mapping images of NiMoOx/NiMoS. Scale bar, a–c $5\\upmu\\mathrm{m}$ ; d–f $1\\upmu\\mathrm{m};$ g–j $10\\upmu\\mathrm{m}$ . \n\n![](images/f6bb50ff8edfa4e90fa55448f074b610d27827419b71e9fe8c0645199363184a.jpg) \nFig. 3 Morphological and structural characterizations. TEM and HRTEM images of a, d NiMoS and b, c, e NiMoOx/NiMoS. f–i Elemental distribution mapping of Ni, Mo, S, and O in NiMoOx/NiMoS. Scale bar, a, b 500 nm; c–e 5 nm; f–i $200\\mathsf{n m}$ . \n\nTo check the details of the morphology, transition electron microscope (TEM) and high-resolution TEM observations verify the architectures of NiMoS and $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ heterostructure arrays, indicating that $\\ensuremath{\\mathrm{MoS}}_{2}$ and $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ nanosheets are attached to $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ nanorods arrays, respectively (Fig. 3). Compared to $\\mathbf{MoS}_{2}$ and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ in NiMoS nanostructures, the characteristic lattice fringes of 0.62, 0.33, and $0.246\\mathrm{nm}$ can be assigned to the (002) plane of $\\ensuremath{\\mathrm{MoS}}_{2}$ , (011) plane of $\\mathrm{MoO}_{3}.$ , and (100) plane of $\\mathrm{MoO}_{2}$ and even more, the (101) plane of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and the (112) plane of $\\mathrm{NiO}_{x}$ can be proven by the lattice fringes of 0.41 and $0.113\\mathrm{nm}$ in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ heterostructures. Typically, the arrangements of $\\mathrm{MoO_{x}}$ and $\\mathrm{NiO}_{x}$ layers are observed on the surface of $\\ensuremath{\\mathrm{MoS}}_{2}$ and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , indicating the formation of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ heterostructure array. Moreover, the elemental mappings by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) confirm the uniform distribution of Ni, Mo, S, and O (Fig. 3 and Supplementary Fig. 5). Therefore, the whole results of SEM and TEM analysis confirm the formation of 3D $\\mathrm{NiMoO_{x}/l}$ NiMoS heterostructure array as the integrated architectures. \n\nTo conduct the chemical valences of the heterostructures, Xray photoelectron spectroscopy (XPS) spectrum has been tested in Fig. 4. With regard to Mo $3d$ regions, the main peak could be split into two distinct peaks of Mo $\\bar{3}d_{5/2}$ $229.1\\mathrm{eV})$ and Mo $3d_{3/2}$ $(\\bar{2}32.4\\mathrm{eV})$ , indicating the dominance of $\\mathrm{Mo^{4+}}$ in NiMoS (Supplementary Fig. 6)8,42. The peaks at 855.2, 861.5, 872.9 and $879.5\\mathrm{eV}$ can be indexed to Ni $2p_{3/2}$ and Ni $2{p}_{1/2}$ orbitals as well as two satellites in NiMoS (Supplementary Fig. 6)25. However, the signals at 229.3, 232.4, and $235.5\\mathrm{eV}$ can be indexed to $\\mathrm{Mo}^{4+}3d_{5/}$ 2, $\\begin{array}{r l}{\\mathrm{Mo}^{4+/6+}}&{{}3d_{3/2,}}\\end{array}$ and ${\\mathrm{Mo}}^{6+}$ $3d_{3/2}$ orbitals, confirming the existence of $\\mathrm{Mo^{4+}}$ and $\\mathrm{Mo}^{6+}$ in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ owe to the formation of $\\mathrm{MoO}_{\\mathrm{x}}{}^{26}$ . For $\\mathrm{Ni}2\\mathrm{p}$ orbitals, there is a shift upon the peak positions and the two new peaks at 854.6 and $8\\bar{5}2.6\\mathrm{eV}$ , demonstrating the existence of Ni–O bonds and metallic $\\mathrm{Ni}^{0}$ and the formation of $\\mathrm{NiO}_{x}$ species in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}^{8,25}$ . Typically, the signals at 529.5 and $531.5\\mathrm{eV}$ for O 1s belong to typical metaloxygen bonds and oxygen vacancies in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ heterostructure8. With regard to $\\mathrm{~s~}2p$ peaks, the negative shift is observed in $\\mathrm{NiMoO_{x}^{-}/N i M o S}$ with the increasing temperature of thermal treatment, demonstrating the loss of S and the formation of S vacancies43. The similar phenomenon of O 1s and S $2p$ is observed in $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ and $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ heterostructures (Supplementary Fig. 7–8). Thus, the combined analysis demonstrates the successful synthesis of hierarchical transition bimetal oxides/sulfides heterostructure array. \n\nElectrocatalytic HER performance. The electrocatalytic performance of various arrays in the three-electrode system was conducted through a linear scan voltammogram (LSV) in 1 M KOH solution at $25^{\\circ}\\mathrm{C}$ . The polarization curves of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}.$ $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ , $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ and NiMoS heterostructure arrays are presented in Fig. 5a, together with commercial $\\mathrm{Pt/C}$ and Ni foam (Supplementary Fig. 9). In comparison of NiMoS (219, 392, and $611\\mathrm{mV}.$ , $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ (163, 282, and $430\\mathrm{mV}.$ ), $\\mathrm{NiO}_{x}/\\mathrm{Ni}_{3}S_{2}$ (67, \n\n![](images/c4b8e9fab8ac1712cbf899d4898bea9804e1bcdeb5f9e9c87caa08ce8fadaebb.jpg) \nFig. 4 XPS spectra of NiMoOx/NiMoS. High-resolution XPS signals of a Mo 3d, b Ni $2p,$ c O 1s, d S $2p$ of $\\mathsf{N i M o O}_{x}$ /NiMoS array with different therma treatment temperatures. \n\n![](images/556d5fac6cbb322df53de18627c7b241e0523b668ff8b0474ae09505d1995be9.jpg) \nFig. 5 HER catalytic performance. a HER polarization curves, b overpotentials at typical current densities, c Tafel slopes of NiMoS, ${M o O_{x}}/{M o S_{2}}$ , $\\mathsf{N i O}_{x}/$ $N i_{3}S_{2},$ and NiMoOx/NiMoS. d Time-dependent current density curves of NiMoOx/NiMoS at typical potentials. Inset: polarization curves of NiMoOx/NiMoS for the stability test. \n\n175, and $307\\mathrm{mV},$ ), $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array delivers the current densities of 10, 100, and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ at the low overpotentials of 38, 89 and $174\\mathrm{mV}$ , respectively, even requiring a low overpotential of $236\\mathrm{mV}$ at a large current density of $1000\\mathrm{mAcm}^{-2}$ towards HER (Fig. 5b). It is worth mentioning that $\\mathrm{NiMoO}_{x}/$ NiMoS array could surpass commercial $\\mathrm{Pt/C}$ catalyst at the high overpotentials while comparable HER activity at the low potentials. Compared to most reported HER catalysts (Supplementary Table 1), the overpotential of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array at a current density of $10\\mathrm{mA}\\mathrm{\\bar{cm}}^{-2}$ is smaller than those of $\\mathbf{MoS}_{2}$ $(170\\mathrm{mV})^{44}$ , CoFeZr oxides $(104\\mathrm{mV})^{6}$ , $\\mathrm{CoS–Co(OH)}_{2}@\\mathrm{MoS}_{2+x}$ $(140\\mathrm{mV})^{26}$ , $\\mathrm{MoS}_{2}/\\mathrm{Fe}_{5}\\mathrm{Ni}_{4}\\mathrm{S}_{8}$ $(120\\mathrm{mV})^{27}$ , $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ $(110\\mathrm{mV})^{28}$ , $\\ensuremath{\\mathrm{MoS}}_{2}/\\ensuremath{\\mathrm{\\Omega}}$ $\\mathrm{Co_{9}S_{8}}/\\mathrm{Ni_{3}S_{2}}$ $(113\\mathrm{mV})^{30}$ , and O-CoMoS $(97\\mathrm{mV})^{42}$ , etc. To regulate the capacities of charge transfer and active sites of NiMoS, it is interesting to determine the precise condition of plasma oxidation and hydrogenation treatment (Supplementary Fig. 10), indicating the best oxygen plasma power of $100\\mathrm{W}$ and appropriate hydrogenation temperature of $400^{\\circ}\\mathrm{C}$ of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array. To conduct HER kinetic mechanism, the lowest Tafel slope (Fig. 5c), $38\\mathrm{mV}$ per decade of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array is obtained in comparison of $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ $(65\\mathrm{mV}\\mathrm{dec}^{-1}),$ , $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ (98 $\\mathrm{mVdec}^{-1}.$ ), NiMoS $(169\\mathrm{mV}\\mathrm{dec}^{-1}),$ ), indicating the rapid HER kinetics of $\\mathrm{NiMoO_{x}/N i M o S}$ array owe to the advantages of the construction of 3D heterostructured architectures and the introduction of the defects. After the analysis of electrochemical impedance spectroscopy (EIS), the lowest charge transfer resistance of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array due to the generation of defective species and metallic Ni is obtained in comparison of $\\mathrm{NiO}_{x}/\\mathrm{Ni}_{3}S_{2}$ $\\bar{\\mathrm{MoO_{x}/M o S_{2}}}$ , and NiMoS (Supplementary Fig. 10). To explore the intrinsic electrocatalytic performance of each active sites, the turnover frequency (TOF) is calculated (Supplementary Table 2–3). The TOF value of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array $(\\bar{1}.97s^{-1})$ at the overpotential of $100\\mathrm{mV}$ is ${\\sim}45$ times higher than that of NiMoS array $(0.0435s^{-1})$ . Moreover, mass activity, $436\\mathrm{Ag^{-1}}$ of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array is calculated at the overpotential of $200\\mathrm{mV}$ (Supplementary Fig. 11), which is better than other nonnobel metal electrocatalysts (Supplementary Table 4). Generally, the electrochemically active surface area (ECSA) is regarded as an estimation of active sites and is proportional to the double-layer capacitance $\\mathrm{(C_{dl})^{45-47}}$ . The highest $C_{\\mathrm{dl}}$ values of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array among all catalysts implies the maximum electroactive area (Supplementary Fig. 12). Moreover, the current of $\\mathrm{NiMoO}_{x}/$ NiMoS and commercial $\\mathrm{Pt/C}$ supported on $\\mathrm{\\DeltaNi}$ plate was normalized to ECSA (Supplementary Figs. 13–16), demonstrating a higher instrinsic activity of $\\mathrm{NiMoO_{x}/N i M o S}$ catalyst in comparison of commercial $\\mathrm{Pt/C}$ . Owe to the stability as pivot criterion for practical application, the time-dependent current density curves confirm that there is no obvious change upon the current densities of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ at 0.089 and $\\mathrm{\\dot{0}.174\\mathrm{V}}$ vs. RHE over $50\\mathrm{h}$ (Fig. 5d). Afterwards, the amount of hydrogen evolution of $\\mathrm{NiMoO_{x}/N i M o S}$ array is measured in comparison of theoretical quantity (Supplementary Fig. 17), presenting a promising Faradaic efficiency of $99.6\\pm0.3\\%$ towards real water splitting into hydrogen. Based on the above-mentioned analysis, the synergistic action of morphology and heterostructure engineering upon $\\mathrm{NiMoO_{x}/N i M o S}$ array can modulate the unique architectures, optimize the charge transfer and catalytic active sites, and thus improve HER performance. \n\nElectrocatalytic OER performance. In general, the efficiency is always limited by OER as major barrier for overall water splitting. In our system, $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array exhibits the best OER performance among all arrays, together with commercial $\\mathrm{IrO}_{2}$ catalyst and Ni foam (Fig. 6a and Supplementary Fig. 18). In comparison of NiMoS (370, 437, and $526\\mathrm{mV},$ , $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ (266, 332, and \n\n$438\\mathrm{mV},$ , $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ (214, 267, and $366\\mathrm{mV},$ , as-synthesized $\\mathrm{NiMoO_{x}/N i M o S}$ array presents the low overpotentials of 186, 225, and $278\\mathrm{mV}$ at current densities of 10, 100, and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ , and delivers a large current density of $1000\\mathrm{mAcm}^{-2}$ at $334\\mathrm{mV}$ towards OER (Fig. 6b), satisfying the requirements for commercial electrocatalytic application (for example, $j\\geq500\\mathrm{mA}\\mathrm{cm}^{-2}$ at $\\eta\\leq$ $300\\mathrm{mV})^{48-51}$ . Compared to most reported OER catalysts (Supplementary Table 5), the overpotential of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array at $\\mathrm{\\bar{10}m A}\\mathrm{cm}\\mathrm{\\dot{^{-2}}}$ is still lower than those of O-CoMoS $(272\\mathrm{mV})^{42}$ , CoS- $\\mathrm{Co(OH)}_{2}@\\mathrm{MoS}_{2+x}$ $(380\\mathrm{mV})^{26}$ , $\\mathrm{MoS}_{2}/\\mathrm{Fe}_{5}\\mathrm{Ni}_{4}\\mathrm{S}_{8}$ $(204\\mathrm{mV})^{27}$ , $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ $(218\\mathrm{mV})^{28}$ , and iron-substrate-derived electrocatalyst $(269\\mathrm{mV})^{48}$ , etc. Especially, the influence of oxygen plasma power and hydrogenation temperature upon the OER performance of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array is determined (Supplementary Fig. 19), confirming the best plasma power of $100\\mathrm{W}$ and thermal treatment temperature at $\\bar{4}00^{\\circ}\\mathrm{C}$ of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array. To in-depth understand the OER kinetic mechanism, the lowest Tafel slope, $34\\mathrm{mV}$ per decade of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ is achieved in comparison of $\\bar{\\mathrm{NiO}}_{x}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ $(56\\mathrm{mV}\\mathrm{dec}^{-1})$ , $\\mathrm{MoO}_{x}/$ $\\ensuremath{\\mathrm{MoS}}_{2}$ $(62\\mathrm{mV}\\mathrm{dec}^{-1})_{.}$ ), NiMoS $(74\\mathrm{mV}\\mathrm{dec}^{-1},$ ), demonstrating the fast OER kinetics of $\\mathrm{NiMoO_{x}/N i M o S}$ (Fig. 6c). Remarkably, the largest $C_{\\mathrm{dl}}$ value of $21.5\\mathrm{mF}\\mathrm{cm}^{-2}$ of $\\mathrm{NiMoO_{x}/N i M o S}$ is obtained by the evaluation of ECSA among all arrays (Supplementary Fig. 20), indicating the production of abundant active sites in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array. Especially, the high ECSA of $\\mathrm{NiMoO}_{x}/$ NiMoS array confirms the advantages of the exposured component and geometric structures of sufficient electrocatalytic active sites. Interestingly, the high-valence Mo and Ni species are obtained in $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array during the OER process (Supplementary Fig. 24), indicating the possible generation of hydroxyl oxides as the actual surface active sites and thus enhancing the OER activities owe to the synergistic action of 3D architectures and the heterostructures. In particular, $\\mathrm{NiMoO}_{x}/$ NiMoS array can preserve OER activities at 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ with the potentials of 1.455 and $1.508\\mathrm{V}$ vs. RHE over $50\\mathrm{h}$ (Fig. 6d), indicating the fascinating OER stability. Typically, the amount of oxygen evolution of $\\mathrm{NiMoO_{x}/N i M o S}$ array is measured in comparison of theoretical quantity (Supplementary Fig. 21), presenting OER Faradaic efficiency of $97.5\\pm0.4\\%$ owe to the synergistic effect of the morphology and heterostructure engineering. \n\nElectrocatalytic performance for overall water splitting. Inspired by excellent HER and OER performance, $\\mathrm{NiMoO}_{x}/$ NiMoS array was assembled as cathode and anode in the twoelectrode system. Impressively, the robust catalytic performance is achieved by as-synthesized $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}||\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ electrode (Fig. 7a), requiring the low cell voltages of 1.46, 1.62, 1.75, and $1.82\\mathrm{V}$ at 10, 100, 500, and $1000\\mathrm{mAcim}^{-2}$ in 1 M KOH at $25^{\\circ}\\mathrm{C}$ In comparison of $_\\mathrm{Ni-Fe-MoN}52$ , $\\mathrm{Fe}_{0.09}\\mathrm{Co}_{0.13}{-}\\mathrm{Ni}\\mathrm{Se}_{2}{^{53}}$ , $\\mathrm{NC/CoCu/CoCu\\bar{O}_{x}^{20}}$ , $\\mathrm{MoS}_{2}/\\mathrm{Co_{9}S_{8}}/\\mathrm{Ni_{3}S_{2}}^{30}$ , $\\mathrm{Pt-CoS}_{2}{}^{47}$ , NC/ $\\mathrm{NiCu/NiCuN}^{25}$ , $\\mathrm{NC/NiMo/NiMoO}_{x}^{8}$ , $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}^{54}$ , $\\mathrm{O-CoMoS^{42}}$ , $\\mathrm{N}{\\cdot}\\mathrm{Ni}\\mathrm{MoO}_{4}/\\mathrm{Ni}\\mathrm{S}_{2}^{15}$ , $\\mathrm{MoS}_{2}/\\mathrm{Ni}\\mathrm{S}^{55}$ , $\\mathrm{P-Co_{3}O_{4}}^{56}$ , $\\mathrm{Ni}/\\mathrm{Mo}_{2}\\mathrm{C}^{57}$ , $\\mathrm{CoNi}$ $\\mathrm{(OH)_{x}}\\mid\\mathrm{NiN}_{x}^{58}$ , $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}{}^{59}$ , $\\mathrm{FeOOH^{60}}$ , $\\mathrm{Ni}_{5}\\mathrm{P}_{4}^{61}$ , $\\mathrm{NiCo/NiCoO}_{x}^{\\phantom{-}62}$ , $\\mathrm{Fe-Ni@NC-CNT^{63}}$ , $\\mathrm{Co_{{x}}P O_{4}}/\\mathrm{CoP^{64}}$ , and commercial $\\mathrm{Pt}/\\mathrm{C}||\\mathrm{Ir}\\mathrm{O}_{2}$ electrodes (Fig. 7c and Supplementary Table 6), the lower voltage at $10\\mathrm{mA}\\mathrm{cm}^{=_{2}}$ is obtained for $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array. Owe to excellent electrocatalytic performance, the two-electrode cell can also be evaluated by a $1.5\\mathrm{V}$ AAA battery (Supplementary Fig. 22). Based on the analysis of the superaerophobicity by bubble contact tests (Supplementary Fig. 23), the superior bubble contact angle, $151.2^{\\circ}$ of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ is obtained, demonstrating that this typical architecture could facilitate the release of the evolved gas bubbles and thus avoid the block of the catalyst active site. To be interesting, the hydrogen and oxygen bubbles escape effectively from the surface of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array (Supplementary Movie). Moreover, the industrial environment is employed to explore the potential for industrialization applications. Typically, the record low voltages of 1.60 and $1.66{\\mathrm{V}}$ of the two-electrode system in $6\\mathrm{M}\\mathrm{KOH}$ solution at $60^{\\circ}\\mathrm{C}$ are achieved for the industrial current densities of 500 and $1000\\mathrm{mAcm}^{-2}$ , respectively, and it is still better than that of $\\mathrm{Pt/C||IrO}_{2}$ couple (Fig. 7b and Supplementary Tabel 7). Compared to the reported electrocatalysts with the large current densities (e.g., 500 and $1000\\mathrm{mAcim}^{-2}.$ ), such as $\\mathrm{Ni}\\mathrm{\\bar{M}o N}@\\mathrm{NiFeN}^{65}$ , nickel-cobalt complexes hybridized $\\mathrm{MoS}_{2}{}^{66}$ , Ni-P-B/paper49, NiVIr-LDH ||NiVRu$\\mathrm{\\dot{I}D H^{50}}$ , phosphorus-doped $\\mathrm{Fe}_{3}\\dot{\\mathrm{O}}_{4}^{51}$ , graphdiyne-sandwiched layered double-hydroxide nanosheets67, N,S-coordinated Ir nanoclusters embedded on N,S-doped graphene68, $\\mathrm{Co}_{3}\\mathrm{Mo}/\\mathrm{Cu}^{69}$ , and $\\mathrm{FeP/Ni_{2}P}$ hybrid70, all aforementioned analysis confirm that as-prepared $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array could be served as promising industrial candidate for overall water splitting. With regard to the operating stability as important metric, this typical two-electrode cell can maintain the excellent electrocatalytic activity at a large current density of $500\\mathrm{mA}\\mathrm{cm}^{-2}$ at the voltage of $1.75\\mathrm{V}$ over 500 h without obvious degradation in 1 M KOH solution at $25^{\\circ}\\mathrm{C}$ (Fig. 7d). After HER, there is no obvious change upon the binding energies of various metal ions (Supplementary Fig. 24). However, the positive shift of two peaks located at 856.3 and $874.1\\mathrm{eV}$ is observed in the XPS of $\\mathtt{N i}2\\mathtt{p}$ , demonstrating that the oxidation of $\\mathrm{Ni}^{2+}$ to high valence state of $\\mathrm{Ni}^{3+}$ , alone with the existence of new peak at $869.05\\mathrm{eV}$ (Supplementary Fig. 24), thus indicating the formation of hydroxides and oxyhydroxides as the real active sites during OER process30–34. Although the hydroxides and oxyhydroxides are formed on the surface of $\\mathrm{NiMoO_{x}/N i M o S}$ array, there is no apparent change upon the morphology of the heterostructures (Supplementary Fig. 25), indicating the superior stability. Based on the above analysis, it is proven that $\\mathrm{NiMoO}_{x}/$ \n\n![](images/01bae8bbe3f8cfae856c59638324025410c6d6ab12c52c877284a04107d6929c.jpg) \nFig. 6 OER catalytic performance. a OER polarization curves, b overpotentials at typical current densities, c Tafel slopes of NiMoS, ${M o O_{x}}/{M o S_{2}}$ , $\\mathsf{N i O}_{x}/$ $N i_{3}S_{2},$ and NiMoOx/NiMoS. d Time-dependent current density curves of NiMoOx/NiMoS at typical potentials. Inset: polarization curves of $\\mathsf{N i M o O}_{x}$ /NiMoS for the durability test. \n\nNiMoS array is excellent and stable system for overall water splitting, presenting the industrial hope. \n\nFirst-principles calculations. To explore the original relationship between the intrinsically catalytic activity and the electronic and atomic structures of the interface of $\\mathrm{\\DeltaNiMoO\\mathrm{{_{x}/N i M o S}}}$ , density functional theory calculations were performed to conduct the Gibbs free energies of every step in HER and OER (Supplementary Fig. 26–33). The hydrogen absorption energy $(\\Delta G_{\\mathrm{H^{*}}})$ is generally considered as the key descriptor for evaluating the performance of $\\mathrm{HER}^{71}$ . The sulfur sites of $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ and $\\mathrm{MoO}_{x}/$ $\\bar{\\mathbf{MoS}}_{2}$ exhibit much lower $\\Delta G_{\\mathrm{H^{*}}}$ relative to that of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and $\\ensuremath{\\mathrm{MoS}}_{2}$ (Fig. 8a and Supplementary Fig. 29–32), indicating that the integration of the oxides and sulfides enables the favorable $\\mathrm{H^{*}}$ adsorption and the tremendous decrement of thermodynamic barriers for hydrogen production. Especially, the oxidation/ hydrogenation-induced surface reconfiguration results into the fabrication of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ heterostructure. The sulfur species serve as the distinctive active sites for the optimized hydrogen adsorption with nearly zero $\\Delta G_{\\mathrm{H^{*}}}$ $(0.003\\mathrm{eV})$ , in comparison of $\\mathrm{NiO}_{x}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ $(\\Delta G_{\\mathrm{H^{*}}}=0.074\\mathrm{eV})$ and $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ $\\Delta G_{\\mathrm{H^{*}}}=0.422$ $\\mathrm{eV},$ . Since oxygen-free NiMoS shows much more negative $\\Delta G_{\\mathrm{H^{*}}}$ $\\left(-0.284\\mathrm{eV}\\right)$ comparing to $\\mathrm{NiMoO_{x}/N i M o S,}$ it is hypothesized that the oxide species of the unique multi-interfaces may avoid the excessively strong adsorption of $\\mathrm{H^{*}}$ and bring about the facile intermediates desorption. Theoretically, water oxidation in alkaline medium involves four concerted proton-electron transfer steps72. The absorption configurations and calculated free energy profiles of OER steps are presented (Figs. 8b-8d). Obviously, the potential rate-determining step (PDS) of NiMoS heterostructures is the third electrochemical step from $^*\\mathrm{O}$ to $^{*}\\mathrm{OOH}$ with an energy barrier of $1.80\\mathrm{eV}$ . The $^{*}{\\mathrm{OOH}}$ species on $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ heterostructures are greatly stabilized and overpotential is largely reduced to $0.85\\mathrm{V}$ with the PDS of forming molecule $\\mathrm{O}_{2}$ . In comparison of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}.$ , it is of noted that the oxide species in $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ and $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ heterointerfaces have small evident impact on the decrement of overpotential (Supplementary Fig. 29–32). Therefore, the multi-interfaces of bimetal oxides/sulfides heterostructures are indispensible for the favorable stabilization of intermediates and accelerated electrochemical kinetics. In order to undestand the charge transfer between the $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ interface, charge density difference was performed (Supplementary Fig. 33). It is clear that a remarkable charge transfer across the interface, facilitates the fast electron transfer during the electrocatalytic process. Overall, the theory simulations and experiments demonstrate that the excellent OER and HER activities are facilitated by the synergetic effect of the oxidation/hydrogenation-induced surface reconfiguration. \n\n![](images/c194144e16ec54c775347812eb826d563d1191c616e662ce1eb793ca642d2cd2.jpg) \nFig. 7 Electrocatalytic performance for overall water splitting. a, b Polarization curves by two-electrode system in a 1 M KOH at $25^{\\circ}\\mathsf{C}$ and b 6 M KOH at $60^{\\circ}\\mathsf C$ . c Comparison of the cell voltage at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ for NiMoOx/NiMoS with previously reported catalysts8,15,20,25,30,42,47,52–64. d Chronoamperometric test at $1.75\\mathrm{V}$ in $1.0\\mathsf{M}\\mathsf{K}\\mathsf{O}\\mathsf{H}$ at $25^{\\circ}\\mathsf{C}$ . \n\nIn this case, the robust electrocatalytic activity is firstly ascribed to 3D hierarchical heterostructures of $\\mathrm{NiMoO_{x}/N i M o S}$ array owe to the excellent mass transport and gas permeability. Secondly, the constructed interfaces among various heterostructures not only produce together the activities of different materials, but also facilitate the charge transfer and brings exceptionally synergistic effect of typical catalysts by oxidation/hydrogenation-induced surface reconfiguration strategy. Thirdly, the generation of defective species in hierarchical heterostructures could optimize electric conductivity and generate abundant active sites, confirming by low resistances and large ECSAs. Finally, the synergistic effect of the morphology and heterostructure engineering in $\\mathrm{NiMoO_{x}/N i M o S}$ array promotes the generation of abundant active sites by engineering active sites, optimizing adsorption energies, and accelerating water splitting kinetics. All advantages promote the robust catalytic performance of NiMoOx/NiMoS array as a typical catalyst, offering a prospective solution of hierarchical electrocatalysts for practical water splitting applications. \n\n![](images/c53e7781b9335f6c235b78c7bc6ab0f2d717d95dc1e4bea75d891ec4f67e855d.jpg) \nFig. 8 Origin of HER/OER activities on NiMoOx/NiMoS. a Chemisorption models and corresponding Gibbs free energy of H on the interface of $N i_{3}S_{2}/$ $M o S_{2}$ and $\\mathsf{N i M o O}_{\\times}$ /NiMoS, on the surface of ${\\sf N i O}_{\\sf x}/{\\sf N i}_{3}{\\sf S}_{2}$ (S) and on the edge of ${M o O_{\\times}}/{M o S_{2}}$ (Mo). b OH, O, and OOH intermediates adsorption configurations for OER on the interface of (top) ${\\sf N i}_{3}{\\sf S}_{2}/{\\sf M o S}_{2}$ and (bottom) $\\mathsf{N i}M\\circ\\mathsf{O}_{\\mathsf{x}},$ /NiMoS. c, d The free energy diagrams for OER on the interface of c ${\\sf N i}_{3}{\\sf S}_{2}/{\\sf M o S}_{2}$ and (d) NiMoOx/NiMoS heterostructures. Cyan, yellow, red, green, and gray balls, respectively, represents H, S, O, Mo, and Ni atoms. \n\n# Discussion \n\nIn summary, hierarchical transition bimetal oxides/sulfides array was fabricated by oxidation/hydrogenation-induced surface reconfiguration strategy by use of NiMoS architectures as the precursor, interacting two-dimensional $\\mathrm{MoO}_{x}/\\mathrm{MoS}_{2}$ nanosheets attached to one-dimensional $\\Nu\\mathrm{iO}_{x}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ nanorods array. To optimize the electrocatalytic performance, the influence of oxygen plasma power and hydrogenation temperature upon HER and OER performance of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array was explored, confirming the best plasma power of $100\\mathrm{W}$ and appropriate thermal treatment temperature at $400^{\\circ}\\mathrm{C}$ . Benefiting from heterostructure engineering, as-synthesized $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array presents the remarkable electrocatalytic performance, achieving low overpotentials of 38, 89, 174, and $236\\mathrm{mV}$ for HER and 186, 225, 278, and $334\\mathrm{mV}$ for OER at 10, 100, 500 and $1000\\mathrm{mAcm}^{-2}$ , even surviving at large current density of 100 and $500\\mathrm{mA}\\mathrm{cm}^{-2}$ with long-term stability. The extraordinarily enhanced electrocatalytic performance of transition bimetal oxides/sulfides heterostructure array as the typical model is ascribed to not only the simultaneous modulation of component and geometric structure, but also the systematic optimization of charge transfer, abundant electrocatalytic active sites and exceptionally synergistic effect of heterostructure interfaces. Density functional theory calculations reveal that the coupling interface between $\\mathrm{NiMoO_{x}}$ and NiMoS optimizes adsorption energies and accelerates water splitting kinetics, thus promoting the catalytic performance. Especially, the assembled two-electrode cell by use of $\\mathrm{NiMoO}_{x}/\\mathrm{NiMoS}$ array delivers the industrially required current densities of 500 and $1000\\mathrm{mAcm}^{-2}$ at record low cell voltages of 1.60 and $1.66\\mathrm{V}$ , along with excellent durability, outperforming most of transition metal-based bifunctional electrocatalysts reported to date. Given hierarchical transition heterostructures array as typical model, this work could open up the avenues to the development of excellent electrocatalysts by engineering active sites for large-scale energy conversion applications. \n\n# Methods \n\nMaterials. Ni foam was purchased from Suzhou Jiashide Metal Foam Co. Ltd. Ni $(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ , $(\\mathrm{NH_{4}})\\mathrm{Mo}_{7}\\mathrm{O}_{24}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ , thiourea and KOH was purchased from \n\nAladdin. $\\mathrm{Pt/C}$ $20\\mathrm{wt\\%}$ Pt on Vulcan XC-72R) and Nafion $(5\\mathrm{wt\\%})$ were purchased from Sigma-Aldrich. All chemicals were used as received without further purification. The water used throughout all experiments was purified through a Millipore system. \n\nFabrication of NiMoOx/NiMoS heterostructure array. 0.07 M $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O},$ $0.01\\mathrm{M}$ $(\\mathrm{NH_{4}})\\mathrm{Mo_{7}O_{24}{\\cdot}4H_{2}O}$ and $0.30\\mathrm{M}$ thiourea were dissolved into $15\\mathrm{mL}$ deionized water and stirred for $10\\mathrm{min}$ under room temperature. Then the solution was transferred to a $25\\mathrm{mL}$ Teflon-lined steel autoclave with nickel foam. After hydrothermal reaction at $200^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ , NiMoS precursor was obtained through washing with deionized water and then dried in an oven at $60^{\\circ}\\mathrm{C}$ . As-obtained NiMoS precursors were irradiated by RF plasma under an oxygen flow (RF power, $50{\\sim}150\\mathrm{W})$ for the oxidation treatment. Afterward the arrays were annealed up to $300{-}500^{\\circ}\\mathrm{C}$ in $\\mathrm{H}_{2}/\\mathrm{Ar}$ (0.05/0.95) for the typical hydrogenation regulation, thus resulting into the synthesis of $\\mathrm{NiMoO_{x}/N i M o S}$ heterostructure array by oxidation/ hydrogenation-induced surface reconfiguration strategy. In comparison, asobtained $\\Nu\\mathrm{iO}_{\\mathrm{x}}/\\Nu\\mathrm{i}_{3}\\mathrm{S}_{2}$ and $\\mathrm{MoO_{x}/M o S_{2}}$ heterostructure arrays were synthesized in parallel by the same procedure as that of $\\mathrm{NiMoO_{x}/N i M o S}$ array expect for in absence of $(\\mathrm{NH_{4}})\\mathrm{Mo_{7}O_{24}{\\cdot}4H_{2}O}$ or $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ in hydrothermal reaction. \n\nStructural characterization. Powder XRD patterns of the products were tested with X-ray diffractometer (Japan Rigaku Rotaflex) by $\\mathrm{Cu}\\ K_{\\mathrm{a}}$ radiation $(\\lambda=1.5418$ nm, $40\\mathrm{kV}$ , $40\\mathrm{mA}$ ) at room temperature. SEM images of the products were captured by a field-emission scanning electron microscope (SEM, FEI Nova Nano SEM 450). TEM images of the products were performed on transmission electron microscopy (TEM, FEI TF30). The chemical states of the samples were determined by XPS in a Thermo VG ESCALAB250 surface analysis system. The shift of binding energy due to relative surface charging was corrected using the C 1 s level at $284.6\\mathrm{eV}$ as an internal standard. \n\nElectrochemical measurements. The electrocatalytic HER and OER performance of different electrocatalysts $(1\\mathrm{cm}^{2})$ were evaluated using a typical three-electrode system in $\\Nu_{2}$ and $\\mathrm{O}_{2}$ -saturated 1 M KOH electrolyte, respectively. All polarization curves at $1\\mathrm{mV}\\mathrm{s}^{-1}$ were corrected with iR compensation. The mass loading of NiMoS-based electrocatalysts was tested according to the mass difference. Commercial $\\mathrm{IrO}_{2}$ or $20\\mathrm{wt\\%}$ Pt/C was dispersed in ethanol solution with Nafion and then the ink was dropped by a micropipettor on Ni foam. The EIS tests were measured by AC impedance spectroscopy at the frequency ranges $10^{6}$ to $0.1\\mathrm{Hz}$ . According to the Nernst equation $(E_{\\mathrm{RHE}}=E_{\\mathrm{Hg/HgO}}+0.059\\mathrm{pH}+0.098)$ , where $E_{\\mathrm{RHE}}$ was the potential vs. a reversible hydrogen potential, $E_{\\mathrm{Hg/HgO}}$ was the potential vs. $\\mathrm{Hg/HgO}$ electrode, and $\\mathrm{\\tt{pH}}$ was the $\\mathrm{\\tt{pH}}$ value of electrolyte. To determination of Faradaic efficiency, the Faradaic efficiency of HER or OER catalyst is defined as the ratio of the amount of experimentally determined hydrogen or oxygen to that of the theoretically expected hydrogen or oxygen from the HER or OER reaction in $1\\mathrm{M}\\mathrm{KOH}$ aqueous solution by use of an online gas chromatography system (GC, Techcomp GC $7890\\mathrm{T}$ , Ar carrier gas, Thermo Conductivity Detector). As for the theoretical value, we assumed that $100\\%$ current efficiency during the reaction, which means only the HER or OER process was occurring at the working electrode. The theoretically expected amount of hydrogen or oxygen was then calculated by applying the Faraday law, which states that the passage of $96485.4\\mathrm{C}$ causes 1 equivalent of reaction. \n\nFirst-principle calculations. Density functional theory calculations were carried out by the Vienna ab initio simulation package (VASP), using the planewave basis with an energy cutoff of $400\\mathrm{eV}$ , the projector augmented wave pseudopotentials, and the generalized gradient approximation parameterized by Perdew, Burke, and Ernzerhof (GGA-PBE) for exchange-correlation functional73. The Brillouin zones of the supercells were sampled by $4\\times4\\times1$ uniform k point mesh. With fixed cell parameters, the model structures were fully optimized using the convergence criteria of $10^{-5}\\mathrm{eV}$ for the electronic energy and $10^{-2}\\mathrm{eV}/\\mathring{\\mathrm{A}}$ for the forces on each atom. The supercells dimension in $\\mathbf{x}$ and y was 11.598 Å and $12.243\\mathrm{\\AA}$ , respectively. The vacuum region in the $\\textbf{z}$ direction was adopted large than $15\\mathrm{\\AA}$ so that the spurious interactions of neighboring models are negligible. Then O atom was used to replace the S atom on the edge of $\\mathbf{MoS}_{2}$ and the surface of $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ and the interface of $\\ensuremath{\\mathrm{MoS}}_{2}$ and $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ , respectively74. To simulate the edge, the surface and interface incorporate with the oxides. Both spin-polarized and spin-unpolarized computations were performed. The computational results show that both NiMoS and $\\mathrm{NiMoO_{x}/N i M o S}$ are magnetic. In addition, we applied the DFT-D3 (BJ) method to evaluate the van der Waals (vdW) effect in all calculations. \n\nThe Gibbs free energy of the intermediates for HER and OER process, that is, H, OH, O, and OOH, can be calculated $\\mathrm{as}^{75,76}$ \n\n$$\n\\Delta G=E_{\\mathrm{ads}}+\\Delta E_{\\mathrm{ZPE}}-T\\Delta S\n$$ \n\nwhere $E_{\\mathrm{ads}}$ is the adsorption energy of intermediate, $\\Delta E_{\\mathrm{ZPE}}$ is the zero point energy difference between the adsorption state and gas state, $T$ is the temperature, and $\\Delta S$ is the entropy various between the adsorption and gas phase. For adsorbates, $E_{\\mathrm{ZPE}}$ and S are obtained from vibrational frequencies calculations with harmonic approximation and contributions from the slabs are neglected, whereas for \n\nmolecules these values are taken from NIST-JANAF thermochemical Tables77. The contributions are listed (Supplementary Table 8). Usually, the vibration entropy of hydrogen adsorption on the substrate is small, the entropy of hydrogen adsorption is $\\Delta S\\approx-1/2S^{\\circ}$ , where $S^{0}$ is the entropy of $\\mathrm{H}_{2}$ in the gas phase at the standard conditions. The corrected for free energy equation was defined by \n\n$$\n\\Delta G=E_{\\mathrm{ads}}+0.24\\mathrm{eV}\n$$ \n\nThe intermediates adsorption energy $E_{\\mathrm{ads}}$ for $^*\\mathrm{H}$ , \\*OH, $^*\\mathrm{O}$ , and $^{*}\\mathrm{OOH}$ can be used as DFT ground state energy calculated as \n\n$$\n\\begin{array}{r l}&{\\Delta E_{\\mathrm{\\cdotH}}=E(\\mathrm{\\Psi}^{\\ast}\\mathrm{H})-E(\\mathrm{\\Psi}^{\\ast})-1/2E(\\mathrm{H}_{2})}\\\\ &{\\Delta E_{\\mathrm{\\cdotOOH}}=E(\\mathrm{\\Psi}^{\\ast}\\mathrm{OOH})-E(\\mathrm{\\Psi}^{\\ast})-\\left(2E_{\\mathrm{H}_{2}\\mathrm{\\cdotO}}-3/2E_{\\mathrm{H}_{2}}\\right)}\\\\ &{\\Delta E_{\\mathrm{\\cdotO}}=E(\\mathrm{\\Psi}^{\\ast}\\mathrm{O})-E(\\mathrm{\\Psi}^{\\ast})-\\left(E_{\\mathrm{H}_{2}\\mathrm{\\cdotO}}-E_{\\mathrm{H}_{2}}\\right)}\\\\ &{\\Delta E_{\\mathrm{\\cdotOH}}=E(\\mathrm{\\Psi}^{\\ast}\\mathrm{OH})-E(\\mathrm{\\Psi}^{\\ast})-\\left(E_{\\mathrm{H}_{2}\\mathrm{\\cdotO}}-1/2E_{\\mathrm{H}_{2}}\\right)}\\end{array}\n$$ \n\nThe OER process in alkaline medium generally occur through the following steps: \n\n$$\n\\begin{array}{r l r l}&{\\mathrm{~\\Psi~^*_+OH^{-}\\to O H^{*}_+e^{-}~}}&&{\\Delta G_{1}}\\\\ &{\\mathrm{~\\cup~H^{*}_+O H^{-}\\to^*_O+H_{2}O+e^{-}~}}&&{\\Delta G_{2}}\\\\ &{\\mathrm{~\\Psi~^*_\\mathrm{O}+O H^{-}\\to O O H^{*}_+e^{-}~}}&&{\\Delta G_{3}}\\\\ &{\\mathrm{~\\cup~OH^{*}_+O H^{-}\\to O_2+H_{2}O+e^{-}~}}&&{\\Delta G_{4}}\\end{array}\n$$ \n\nwhere \\* denotes adsorption active site on the substrate. \n\n$$\n\\begin{array}{c}{\\Delta G_{1}=\\Delta G\\mathrm{*_{oH}}}\\\\ {\\ }\\\\ {\\Delta G_{2}=\\Delta G\\mathrm{*_{0}}-\\Delta G\\mathrm{*_{OH}}}\\\\ {\\ }\\\\ {\\Delta G_{3}=\\Delta G\\mathrm{*_{OOH}}-\\Delta G\\mathrm{*_{0}}}\\\\ {\\ }\\\\ {\\Delta G_{4}=4.92-\\Delta G\\mathrm{*_{OOH}}}\\end{array}\n$$ \n\nThe overpotential $\\mathfrak{n}$ is defined as \n\n$$\n\\eta=\\operatorname*{max}\\{\\Delta G_{1},\\Delta G_{2},\\Delta G_{3},\\Delta G_{4}\\}-1.23\\mathrm{eV}\n$$ \n\n# Data availability \n\nThe data that support the findings of this work are available from the corresponding author upon reasonable request. \n\nReceived: 7 April 2020; Accepted: 1 October 2020; Published online: 29 October 2020 \n\n# References \n\n1. Jiao, Y. et al. Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions. Chem. Soc. Rev. 44, 2060–2086 (2015). \n2. Xia, Z. & Guo, S. Strain engineering of metal-based nanomaterials for energy electrocatalysis. Chem. Soc. Rev. 48, 3265–3278 (2019). \n3. Wei, C. et al. Approaches for measuring the surface areas of metal oxide electrocatalysts for determining their intrinsic electrocatalytic activity. Chem. Soc. Rev. 48, 2518–2534 (2019). \n4. Zou, X. & Zhang, Y. Noble metal-free hydrogen evolution catalysts for water splitting. Chem. Soc. Rev. 44, 5148–5180 (2015). \n5. Pi, Y. et al. Trimetallic oxyhydroxide coralloids for efficient oxygen evolution electrocatalysis. Angew. Chem. Int. Ed. 56, 4502–4506 (2017). \n6. Huang, L. et al. Zirconium-regulation-induced bifunctionality in 3D cobaltiron oxide nanosheets for overall water splitting. Adv. Mater. 31, 1901439 (2019). \n7. Hao, S. et al. NiCoMo hydroxide nanosheet arrays synthesized via chloride corrosion for overall water splitting. ACS Energy Lett. 4, 952–959 (2019). \n8. Hou, J. et al. Active sites intercalated ultrathin carbon sheath on nanowire arrays as integrated core-shell architecture: highly efficient and durable electrocatalysts for overall water splitting. Small 13, 1702018 (2017). \n9. Yang, L. et al. Efficient oxygen evolution electrocatalysis in acid by a perovskite with face-sharing $\\mathrm{IrO}_{6}$ octahedral dimmers. Nat. Commun. 9, 5236 (2018). \n10. Chen, H. et al. Promoting subordinate, efficient ruthenium sites with interstitial silicon for Pt-Like electrocatalytic activity. Angew. Chem. Int. Ed. 58, 11409 (2019). \n11. Liang, X. et al. Activating inert, nonprecious perovskites with iridium dopants for efficient oxygen evolution reaction under acidic conditions. Angew. Chem. Int. Ed. 58, 17631 (2019). \n12. Huang, L. B. et al. Self-limited on-site conversion of $\\mathbf{MoO}_{3}$ nanodots into vertically aligned ultrasmall monolayer $\\ensuremath{\\mathbf{MoS}}_{2}$ for efficient hydrogen evolution. Adv. Energy Mater. 8, 1800734 (2018). \n13. Zhang, J. et al. Efficient hydrogen production on $\\mathrm{{MoNi}_{4}}$ electrocatalysts with fast water dissociation kinetics. Nat. Commun. 8, 15437 (2017). \n14. Chen, Y. Y. et al. Self-templated fabrication of $\\mathrm{MoNi_{4}/M o O_{3-x}}$ nanorod arrays with dual active components for highly efficient hydrogen evolution. Adv. Mater. 29, 1703311 (2017). \n15. An, L. et al. Epitaxial heterogeneous interfaces on $\\mathrm{N-NiMoO_{4}/N i S_{2}}$ nanowires/ nanosheets to boost hydrogen and oxygen production for overall water splitting. Adv. Funct. Mater. 29, 1805298 (2019). \n16. Zhang, X. et al. $\\mathrm{Co_{3}O_{4}/F e_{0.33}C o_{0.66}P}$ interface nanowire for enhancing water oxidation catalysis at high current density. Adv. Mater. 30, 1803551 (2018). \n17. Liu, T. et al. Interfacial electron transfer of ${\\mathrm{Ni}}_{2}{\\mathrm{P}}{\\mathrm{-Ni}}{\\mathrm{P}}_{2}$ polymorphs inducing enhanced electrochemical properties. Adv. Mater. 30, 1803590 (2018). \n18. Niu, S. et al. Autogenous growth of hierarchical $\\mathrm{NiFe(OH)_{x}/F e S}$ nanosheet‐ on‐microsheet arrays for synergistically enhanced high‐output water oxidation. Adv. Funct. Mater. 29, 1902180 (2019). \n19. Peng, Y. W. et al. Polyoxometalate‐derived ultrasmall $\\mathrm{Pt}_{2}\\mathrm{W}/\\mathrm{W}\\mathrm{O}_{3}$ heterostructure outperforms platinum for large‐current‐density $\\mathrm{H}_{2}$ evolution. Adv. Energy Mater. 9, 1900597 (2019). \n20. Hou, J. et al. Promoting active sites in core-shell nanowire array as MottSchottky electrocatalysts for efficient and stable overall water splitting. $A d\\nu$ . Funct. Mater. 28, 1704447 (2018). \n21. Feng, J. X. et al. $\\mathrm{Co(OH)}_{2}@\\mathrm{PANI}$ hybrid nanosheets with 3D networks as high-performance electrocatalysts for hydrogen evolution reaction. Adv. Mater. 27, 7051–7057 (2015). \n22. Feng, J. X. et al. FeOOH/Co/FeOOH hybrid nanotube arrays as highperformance electrocatalysts for the oxygen evolution reaction. Angew. Chem. Int. Ed. 55, 3694–3698 (2016). \n23. Lei, C. et al. Efficient alkaline hydrogen evolution on atomically dispersed $\\mathrm{Ni-N_{x}}$ species anchored porous carbon with embedded Ni nanoparticles by accelerating water dissociation kinetics. Energy Environ. Sci. 12, 149–156 (2019). \n24. Yan, H. et al. Anion-modulated HER and OER activities of 3D Ni-V-based interstitial compound heterojunctions for high-efficiency and stable overall water splitting. Adv. Mater. 31, 1901174 (2019). \n25. Hou, J. et al. Electrical behavior and electron transfer modulation of nickelcopper nanoalloys confined in nickel-copper nitrides nanowires array encapsulated in nitrogen-doped carbon framework as robust bifunctional electrocatalyst for overall water splitting. Adv. Funct. Mater. 28, 1803278 (2018). \n26. Yoon, T. & Kim, K. S. One-step synthesis of CoS-Doped $\\upbeta$ -Co $(\\mathrm{OH})_{2}@$ amorphous $\\ensuremath{\\mathbf{MoS}}_{2+\\ensuremath{\\mathbf{x}}}$ hybrid catalyst grown on nickel foam for highperformance electrochemical overall water splitting. Adv. Funct. Mater. 26, 7386–7393 (2016). \n27. Wu, Y. et al. Coupling interface constructions of $\\mathrm{MoS}_{2}/\\mathrm{Fe}_{5}\\mathrm{Ni}_{4}\\mathrm{S}_{8}$ heterostructures for efficient electrochemical water splitting. Adv. Mater. 30, 1803151 (2018). \n28. Zhang, J. et al. Interface engineering of $\\mathrm{MoS}_{2}/\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ heterostructures for highly enhanced electrochemical overall-water-splitting activity. Angew. Chem. Int. Ed. 55, 6702–6707 (2016). \n29. An, T. et al. Interlaced ${\\mathrm{NiS}}_{2}{\\mathrm{-}}{\\mathrm{MoS}}_{2}$ nanoflake-nanowires as efficient hydrogen evolution electrocatalysts in basic solutions. J. Mater. Chem. A 4, 13439–13443 (2016). \n30. Yang, Y. et al. Hierarchical nanoassembly of $\\mathrm{MoS_{2}/C o_{9}S_{8}/N i_{3}S_{2}/N i}$ as a highly efficient electrocatalyst for overall water splitting in a wide $\\mathrm{\\tt{pH}}$ range. J. Am. Chem. Soc. 141, 10417–10430 (2019). \n31. Li, H. et al. Systematic design of superaerophobic nanotube-array electrode comprised of transition-metal sulfides for overall water splitting. Nat. Commun. 9, 2452 (2018). \n32. Wang, X. et al. Single-atom vacancy defect to trigger high-efficiency hydrogen evolution of $\\ensuremath{\\mathrm{MoS}}_{2}$ . J. Am. Chem. Soc. 142, 4298 (2020). \n33. Luo, Z. et al. Reactant friendly hydrogen evolution interface based on dianionic $\\ensuremath{\\mathbf{MoS}}_{2}$ surface. Nat. Commun. 11, 1116 (2020). \n34. He, W. et al. Fluorine-anion-modulated electron structure of nickel sulfide nanosheet arrays for alkaline hydrogen evolution. ACS Energy Lett. 4, 2905 (2019). \n35. Feng, L. et al. High-index faceted $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanosheet arrays as highly active and ultrastable electrocatalysts for water splitting. J. Am. Chem. Soc. 137, 14023 (2015). \n36. Zhu, H. et al. When cubic cobalt sulfide meets layered molybdenum disulfide: A core–shell system toward synergetic electrocatalytic water splitting. Adv. Mater. 27, 4752 (2015). \n37. Feng, J. et al. Efficient hydrogen evolution on Cu nanodots-decorated $\\mathrm{Ni}_{3}\\mathrm{S}_{2}$ nanotubes by optimizing atomic hydrogen adsorption and desorption. J. Am. Chem. Soc. 140, 610 (2018). \n38. Chen, D. et al. Preferential cation vacancies in perovskite hydroxide for the oxygen evolution reaction. Angew. Chem. Int. Ed. 57, 8691–8696 (2018). \n39. Xiao, Z. et al. Filling the oxygen vacancies in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ with phosphorus: an ultra-efficient electrocatalyst for overall water splitting. Energy Environ. Sci. 10, 2563–2569 (2017). \n40. Wang, Y. et al. 3D carbon electrocatalysts in situ constructed by defect-rich nanosheets and polyhedrons from NaCl-sealed zeolitic imidazolate frameworks. Adv. Funct. Mater. 28, 1705356 (2018). \n41. Smith, R. et al. Photochemical route for accessing amorphous metal oxide materials for water oxidation catalysis. Science 340, 60–63 (2013). \n42. Hou, J. et al. Vertically aligned oxygenated- ${\\mathrm{CoS}}_{2}{\\mathrm{-MoS}}_{2}$ heteronanosheet architecture from polyoxometalate for efficient and stable overall water splitting. ACS Catal. 8, 4612–4621 (2018). \n43. Meng, L. et al. Simultaneous manipulation of O-doping and metal vacancy in atomically thin $\\mathrm{Zn}_{10}\\mathrm{In}_{16}\\mathrm{S}_{34}$ nanosheet arrays toward improved photoelectrochemical performance. Angew. Chem. Int. Ed. 57, 16882–16887 (2018). \n44. Li, H. et al. Activating and optimizing $\\mathbf{MoS}_{2}$ basal planes for hydrogen evolution through the formation of strained sulphur vacancies. Nat. Mater. 15, 48 (2015). \n45. Kibsgaard, J. & Jaramillo, T. F. Molybdenum phosphosulfide: An active, acidStable, earth-abundant catalyst for the hydrogen evolution reaction. Angew. Chem. Int. Ed. 53, 14433 (2014). \n46. Kibsgaard, J. et al. Designing an improved transition metal phosphide catalyst for hydrogen evolution using experimental and theoretical trends. Energy Environ. Sci. 8, 3022 (2015). \n47. Han, X. et al. Ultrafine Pt nanoparticle-decorated pyrite-type $\\mathrm{CoS}_{2}$ nanosheet arrays coated on carbon cloth as a bifunctional electrode for overall water splitting. Adv. Energy Mater. 8, 1800935 (2018). \n48. Liu, Y. et al. Corrosion engineering towards efficient oxygen evolution electrodes with stable catalytic activity for over 6000 hours. Nat. Commun. 9, 2609 (2018). \n49. Hao, W. et al. Fabrication of practical catalytic electrodes using insulating and eco-friendly substrates for overall water splitting. Energy Environ. Sci. 13, 102–110 (2020). \n50. Wang, D. et al. Atomic and electronic modulation of self-supported nickelvanadium layered double hydroxide to accelerate water splitting kinetics. Nat. Commun. 10, 3899 (2019). \n51. Zhang, J. et al. Modulation of inverse spinel $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ by phosphorus doping as an industrially promising electrocatalyst for hydrogen evolution. Adv. Mater. 31, 1905107 (2019). \n52. Zhu, C. et al. Fe-Ni-Mo nitride porous nanotubes for full water splitting and Zn-air batteries. Adv. Energy Mater. 8, 1802327 (2018). \n53. Sun, Y. et al. Strong electronic interaction in dual-cation-incorporated $\\mathrm{NiSe}_{2}$ nanosheets with lattice distortion for highly efficient overall water splitting. Adv. Mater. 30, 1802121 (2018). \n54. Lin, J. et al. Defect-rich heterogeneous $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}$ nanosheets electrocatalysts for efficient overall water splitting. Adv. Sci. 6, 1900246 (2019). \n55. Zhai, Z. et al. Dimensional construction and morphological tuning of heterogeneous $\\mathrm{MoS}_{2}/\\mathrm{NiS}$ electrocatalysts for efficient overall water splitting. J. Mater. Chem. A 6, 9833–9838 (2018). \n56. Wang, Z. et al. Phosphorus-doped $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanowire array: a highly efficient bifunctional electrocatalyst for overall water splitting. ACS Catal. 8, 2236–2241 (2018). \n57. Li, M. et al. Ni strongly coupled with $\\mathrm{Mo}_{2}\\mathrm{C}$ encapsulated in nitrogen-doped carbon nanofibers as robust bifunctional catalyst for overall water splitting. Adv. Energy Mater. 9, 1803185 (2019). \n58. Li, S. et al. Co-Ni-based nanotubes/nanosheets as efficient water splitting electrocatalysts. Adv. Energy Mater. 6, 1501661 (2016). \n59. Sivanantham, A., Ganesan, P. & Shanmugam, S. Hierarchical $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanowire arrays supported on Ni foam: an efficient and durable bifunctional electrocatalyst for oxygen and hydrogen evolution reactions. Adv. Funct. Mater. 26, 4661–4672 (2016). \n60. Liu, B. et al. Iron vacancies induced bifunctionality in ultrathin feroxyhyte nanosheets for overall water splitting. Adv. Mater. 30, 1803144 (2018). \n61. Ledendecker, M. et al. The synthesis of nanostructured $\\mathrm{Ni}_{5}\\mathrm{P}_{4}$ films and their use as a non-noble bifunctional electrocatalyst for full water splitting. Angew. Chem. Int. Ed. 54, 12361–12365 (2015). \n62. Yan, X. et al. From water oxidation to reduction: transformation from $\\mathrm{Ni}_{\\mathrm{x}}\\mathrm{Co}_{3}$ - $\\mathrm{_xO_{4}}$ nanowires to $\\mathrm{NiCo/NiCoO_{x}}$ heterostructures. ACS Appl. Mater. Interfaces 8, 3208–3214 (2016). \n63. Zhao, X. et al. Bifunctional electrocatalysts for overall water splitting from an iron/nickel-based bimetallic metal-organic framework/dicyandiamide composite. Angew. Chem. Int. Ed. 57, 8921–8926 (2018). \n64. Yang, Y. et al. Porous cobalt-based thin film as a bifunctional catalyst for hydrogen generation and oxygen generation. Adv. Mater. 27, 3175–3180 (2015). \n65. Yu, L. et al. Non-noble metal-nitride based electrocatalysts for highperformance alkaline seawater electrolysis. Nat. Commun. 10, 5106 (2019). \n66. Li, H. et al. Amorphous nickel-cobalt complexes hybridized with 1T-phase molybdenum disulfide via hydrazineinduced phase transformation for water splitting. Nat. Commun. 8, 15377 (2019). \n67. Hui, L. Overall water splitting by graphdiyne-exfoliated and -sandwiched layered double-hydroxide nanosheet arrays. Nat. Commun. 9, 5309 (2018). \n68. Wang, Q. et al. Coordination engineering of iridium nanocluster bifunctional electrocatalyst for highly efficient and pH-universal overall water splitting. Nat. Commun. 11, 4246 (2020). \n69. Shi, H. et al. Spontaneously separated intermetallic ${\\bf C o}_{3}{\\bf M o}$ from nanoporous copper as versatile electrocatalysts for highly efficient water splitting. Nat. Commun. 11, 2940 (2020). \n70. Yu, F. et al. High-performance bifunctional porous non-noble metal phosphide catalyst for overall water splitting. Nat. Commun. 9, 2551 (2018). \n71. Nørskov, J. K. et al. Trends in the exchange current for hydrogen evolution. $J.$ Electrochem. Soc. 152, J23–J26 (2005). \n72. Koper, M. T. M. Theory of multiple proton–electron transfer reactions and its implications for electrocatalysis. Chem. Sci. 4, 2710–2723 (2013). \n73. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865 (1996). \n74. Peng, L. et al. Rationally design of monometallic NiO- ${\\bf N i}_{3}\\mathrm{S}_{2}/\\mathrm{NF}$ heteronanosheets as bifunctional electrocatalysts for overall water splitting. $J.$ Catal. 369, 345–351 (2019). \n75. Zhang, B. et al. Integrating Rh species with NiFe-layered double hydroxide for overall water splitting. Nano Lett. 20, 136–144 (2020). \n76. Rossmeisl, J., Logadottir, A. & Nørskov, J. K. Electrolysis of water on (oxidized) metal surfaces. Chem. Phys. 319, 178–184 (2005). \n77. NIST-JANAF Thermochemical Tables. https://janaf.nist.gov/. \n\n# Acknowledgements \n\nThis work was supported by National Natural Science Foundation of China (Nos. 21972015, 51672034), Young top talents project of Liaoning Province (No. XLYC1907147), Joint Research Fund Liaoning-Shenyang National Laboratory for Materials Science (No. 2019JH3/30100003), the Fundamental Research Funds for the Central Universities (No. DUT20TD06), the Swedish Research Council, and the K&A Wallenberg Foundation. \n\n# Author contributions \n\nJ.H. supervised this study. J.H., P.Z., and Y.W. conceived the idea. P.Z. and Y.W. planned and carried out the experiments, collected, and analyzed the experimental data. S.C. performed SEM and TEM characterizations. Y.Z. and J.G. conducted theoretical calculations. P.Z., Y.W., and J.H. wrote the paper. All the authors have discussed the results and wrote the paper together. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-19214-w. \n\nCorrespondence and requests for materials should be addressed to J.H. \n\nPeer review information Nature Communications thanks Fangyi Cheng, Batyr Garlyyev, and other, anonymous, reviewers for their contributions to the peer review of this work. Peer review reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1038_s41467-020-14289-x", + "DOI": "10.1038/s41467-020-14289-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-14289-x", + "Relative Dir Path": "mds/10.1038_s41467-020-14289-x", + "Article Title": "Regenerable and stable sp2 carbon-conjugated covalent organic frameworks for selective detection and extraction of uranium", + "Authors": "Cui, WR; Zhang, CR; Jiang, W; Li, FF; Liang, RP; Liu, JW; Qiu, JD", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Uranium is a key element in the nuclear industry, but its unintended leakage has caused health and environmental concerns. Here we report a sp(2) carbon-conjugated fluorescent covalent organic framework (COF) named TFPT-BTAN-AO with excellent chemical, thermal and radiation stability is synthesized by integrating triazine-based building blocks with amidoxime-substituted linkers. TFPT-BTAN-AO shows an exceptional UO22+ adsorption capacity of 427mgg(-1) attributable to the abundant selective uranium-binding groups on the highly accessible pore walls of open 1D channels. In addition, it has an ultra-fast response time (2s) and an ultra-low detection limit of 6.7nM UO22+ suitable for on-site and real-time monitoring of UO22+, allowing not only extraction but also monitoring the quality of the extracted water. This study demonstrates great potential of fluorescent COFs for radionuclide detection and extraction. By rational designing target ligands, this strategy can be extended to the detection and extraction of other contaminullts. Porous materials for uranium capture have been developed in the past, but materials for simultaneous uranium capture and detection are scarce. Here the authors develop a stable covalent organic framework capable of adsorbing and detecting uranyl ions.", + "Times Cited, WoS Core": 503, + "Times Cited, All Databases": 516, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000558877100005", + "Markdown": "# Regenerable and stable $s p^{2}$ carbon-conjugated covalent organic frameworks for selective detection and extraction of uranium \n\nWei-Rong Cui1, Cheng-Rong Zhang1, Wei Jiang1, Fang-Fang Li1, Ru-Ping Liang1, Juewen Liu2 & Jian-Ding Qiu 1\\* \n\nUranium is a key element in the nuclear industry, but its unintended leakage has caused health and environmental concerns. Here we report a $\\displaystyle s p^{2}$ carbon-conjugated fluorescent covalent organic framework (COF) named TFPT-BTAN-AO with excellent chemical, thermal and radiation stability is synthesized by integrating triazine-based building blocks with amidoxime-substituted linkers. TFPT-BTAN-AO shows an exceptional $\\mathsf{U O}_{2}2+$ adsorption capacity of $427\\mathsf{m g g}^{-1}$ attributable to the abundant selective uranium-binding groups on the highly accessible pore walls of open 1D channels. In addition, it has an ultra-fast response time $(2\\mathsf{s})$ and an ultra-low detection limit of $6.7\\mathsf{n M}\\cup\\mathsf{O}_{2}{}^{2+}$ suitable for on-site and real-time monitoring of $\\mathsf{U O}_{2}2+$ , allowing not only extraction but also monitoring the quality of the extracted water. This study demonstrates great potential of fluorescent COFs for radionuclide detection and extraction. By rational designing target ligands, this strategy can be extended to the detection and extraction of other contaminants. \n\nW ith a low-carbon footprint, nuclear energy has a critical role in the global energy system1–3. Owing to the widespread use of nuclear power, large-scale uranium \nmining, nuclear accidents, and improper disposal of nuclear \nwastes, a large quantity of radioactive uranium has penetrated into \nthe environment mainly in the form of $\\mathrm{UO}_{2}{}^{2+\\ 4-\\hat{6}}$ . Thus, regen \nerable materials for concurrent $\\mathrm{UO}_{2}{^{2+}}$ detection and extraction \nare demanded for environmental monitoring and protection. \n\nSome porous materials such as porous organic polymers $(\\mathrm{POPs})^{7}$ , metal-organic frameworks $\\mathbf{\\bar{(MOFs)}}^{8}$ , and hydrogels4 have been developed for this purpose. However, the performance of amorphous POPs is affected by its irregular pores, burying a large fraction of porosity9, and hindering fast mass transfer needed for real-time response10. Although MOFs have regular pores and good crystallinity8, stability under extreme conditions (acid, base, temperature, and radiation) remains a challenge11–13. High stability is particularly important for the extraction of $\\mathrm{U}\\bar{\\mathrm{O}}_{2}{}^{2+}$ , as the sample matrix is likely to be strongly radioactive and acidic. Therefore, it remains a synthetic challenge for realtime detection and regenerable extraction of $\\mathrm{UO}_{2}{}^{2+}$ . \n\nCovalent organic frameworks (COFs) are a class of porous crystalline polymers with significant advantages for application in catalysis14–1 8, gas storage19–22, and metal ion extraction23–27 owing to excellent chemical and thermal stability, flexible topological connectivity, and tunable functionality28–30. COFs with tunable porosity and large specific surface area might be ideal for extracting radionuclides such as $\\mathrm{UO}_{2}{}^{2+}$ . In addition, postmodification can rationally place various functional units within the periodic arrays to optimize the performance. At present, various COFs based on the Schiff base reaction (for example, COF-TpAb-AO1, and $o{\\mathrm{-}}\\mathrm{TDCOF}^{3}.$ ) have been developed for the extraction of $\\mathrm{UO}_{2}{^{2+}}$ . However, their major covalent bonds, such as the boron–oxygen and imine bonds, are susceptible to irradiation, acid, and base, which greatly limit their regeneration and practical application3,31,32. \n\nRecently, considerable attention has been paid to the construction of olefin-based COFs synthesized by the Knoevenagel condensation reaction. Although the $\\displaystyle s p^{2}$ -carbon bond are very stable, the reversibility of $s p^{2}$ -carbon bond formation is poor, making the synthesis of $s p^{\\dot{2}}$ -carbon-linked COFs extremely challenging33. Since 2016, several examples of $s p^{2}$ -carbon COFs have been reported, such as $s p^{2}\\mathrm{c}\\mathrm{-}\\mathrm{COF}^{3\\bar{4}}$ , TP- $\\mathrm{COF}^{35}$ , Por- $s p^{2}\\mathrm{c}\\mathrm{-}\\mathrm{COF}^{33}$ , and $\\mathrm{g-C_{34}N_{6}}.$ $\\mathrm{COF}^{36}$ . However, their application for the detection or extraction of $\\mathrm{UO}_{2}{}^{2+}$ has not been explored. More importantly, the exploration of COFs for fluorescence detection of $\\mathrm{UO}_{2}\\dot{2}+$ is still in its infancy, and most $\\mathrm{UO}_{2}{}^{2+}$ -sensing platforms are often hampered by poor selectivity and a long response $\\mathrm{time}^{37-40}$ . \n\nWe herein report a $\\ s p^{2}$ carbon-conjugated COF for simultaneous detection and extraction of $\\mathrm{UO}_{2}{}^{2+}$ by integrating triazine-based building blocks with amidoxime-substituted linkers. This $\\ensuremath{s p}^{2}$ carbon-conjugated COF not only has good luminescence yield, but also excellent chemical and thermal stability. Its selective binding of $\\mathrm{UO}_{2}{}^{2+}$ is obtained by introducing amidoxime functional groups as ligands in the open 1D channels. Its real-time fluorescence response to $\\mathrm{UO}_{2}{}^{2+}$ can be visually observed and recycling was also confirmed using reversible uranium binding. \n\n# Results \n\n$\\scriptstyle s p^{2}$ carbon-conjugated COF for reversible uranium binding. To achieve an acid, base, and radiation stable, strongly fluorescent and selective $\\mathrm{UO}_{2}{}^{2+}$ -binding COF, we had the following materials design considerations. Most current COFs relied on the boron–oxygen and imine bonds35. However, such reversible bonds lead to relatively poor stability. In addition, their weak $\\pi$ -electron delocalization over the framework hinders fluorescence yield36. Carbon–carbon double bonds ( $\\scriptstyle\\cdot\\ C=\\mathbf{C}-\\$ are more stable and can keep conjugated $\\pi$ -electrons, which can overcome the above challenges36,41. In addition, their intrinsic open 1D channels and regular porous structures facilitate exposure of binding sites, boosting rapid diffusion, and mass transfer. Thus, by introducing specific metal-binding sites on the pore walls, the $s p^{2}$ carbon-conjugated COF may serve for high performance $\\mathrm{~\\bar{U}O}_{2}{}^{2+}$ extraction under harsh conditions. \n\nOur synthesis is depicted in Fig. 1. 2,4,6-tris(4-formylphenyl)- 1,3,5-triazine (TFPT) and ${}_{2,2^{\\prime},2^{\\prime\\prime}}$ -(benzene-1,3,5-triyl)triacetonitrile (BTAN) were polymerized through the Knoevenagel reaction, yielding a cyano-based COF (TFPT-BTAN). To overcome the low reversibility of the Knoevenagel reaction, we optimized the solvent, catalyst, and temperature (Supplementary Table 1 and Supplementary Fig. 1 in Supplementary Information), and highly crystalline TFPT-BTAN was prepared by condensing TFPT and BTAN in a mixture of $o$ -DCB and $^{4\\mathrm{M}}$ DBU (10:1 by vol.) at $90^{\\circ}\\mathrm{C}.$ Subsequently, TFPT-BTAN was subjected to amidoximation by treating it with an excess of $\\mathrm{NH}_{2}\\mathrm{OH}{\\cdot}\\mathrm{HCl}$ at $85^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ to give TFPT-BTAN-AO. Our synthetic strategy not only constructed a highly stable $\\pi$ -conjugated skeleton as the fluorophore, but also introduced dense amidoxime groups as the uranium receptors. These unique features are expected to facilitate real-time detection and efficient extraction of $\\mathrm{U}\\bar{\\mathrm{O}}_{2}{}^{2+}$ . \n\nThe chemical structure and composition of TFPT-BTAN were determined by Fourier transform infrared (FT-IR) and solid-state $^{13}\\mathrm{C}$ CP/MAS NMR spectroscopy. In the FT-IR spectra of TFPTBTAN (Supplementary Fig. 2), the characteristic vibration peak of -CN (at ${\\sim}\\bar{2}\\bar{2}41\\mathrm{cm}^{-1}$ ) was observed for both BTAN monomer and TFPT-BTAN. A stretching vibration peak of $\\scriptstyle\\mathrm{C=O}$ (at $\\sim1698\\mathrm{cm}^{-1}.$ ) was found in the TFPT monomer and it completely disappeared in TFPT-BTAN, indicating a high degree of condensation. The solidstate $^{13}\\mathrm{C}$ CP/MAS NMR of TFPT-BTAN further confirmed highly efficient condensation, supported by the peaks at ${\\sim}113$ and ${\\sim}171$ ppm assigned to the carbon atoms in cyano and triazine moieties, respectively (Supplementary Fig. 3). \n\nTo determine the structure of TFPT-BTAN, powder X-ray diffraction (PXRD) experiments were performed (Fig. 2a). A strong peak at $5.8^{\\circ}$ (2θ) is assigned to the diffraction from the (100) plane, indicating a highly crystalline of TFPT-BTAN37. The other peaks at $9.8^{\\circ},~\\mathrm{11}.2^{\\circ},$ and $26.3^{\\circ}$ (2θ) are assigned to the diffractions of (110), (200), and (001) planes, respectively. Our PXRD pattern matches well with the AA stacking model of the simulated TFPT-BTAN structure, and the Pawley refined PXRD pattern fits well with experimental data $(R_{\\mathrm{p}}=2.85\\%$ and $R_{\\mathrm{wp}}=$ $4.27\\%$ ), as demonstrated by the negligible difference (Supplementary Fig. 4 and Supplementary Table 2). The above results indicate that TFPT-BTAN has open 1D channels ( $\\mathrm{1.5nm}$ in diameter) and the interlayer distance of the framework is $3.5\\mathring\\mathrm{A}$ . To evaluate the details of the pore features of TFPT-BTAN, $\\mathrm{N}_{2}$ adsorption–desorption experiments were performed. The Brunauer-Emmett-Teller (BET) surface area of TFPT-BTAN was determined to be $1062\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , and the pore-size distribution centered at $1.44\\mathrm{nm}$ based on non-local density functional theory, which matches well with the model (Fig. 2b)30. \n\nWe prepared TFPT-BTAN-AO by reacting crystalline and porous TFPT-BTAN with $\\mathrm{NH}_{2}\\mathrm{OH}{\\cdot}\\mathrm{HCl}$ . The PXRD pattern of TFPT-BTAN-AO shows a diffraction pattern comparable to the one of TFPT-BTAN with a strong diffraction peak at $5.8^{\\circ}$ (Fig. 2a), indicating that crystallinity was well retained after the amidoximation process. $\\mathrm{N}_{2}$ adsorption–desorption isotherm were performed to verify pore accessibility after the post-modification process, affording isotherms comparable to those of TFPT-BTAN. The BET surface area was evaluated to be $803\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , indicating that porosity was well retained after the amidoximation process (Fig. 2c). \n\n![](images/3e7ec99d1a672992444fa921a9f685a9195a186f5f007e1b567d6731b83561ac.jpg) \nFig. 1 Schematic of synthetic TFPT-BTAN-AO. a Synthesis of TFPT-BTAN and TFPT-BTAN-AO. b Side and top c views of an eclipsed AA-stacking model of TFPT-BTAN (light green, C; blue, N; light gray, H). d Graphic view of TFPT-BTAN-AO (light green, C; red, O; blue, N; light gray, H). \n\nAs shown in Supplementary Fig. 5, the vibration peak of -CN (at $\\sim2241\\mathrm{cm}^{-1}.$ ) disappeared in TFPT-BTAN-AO, and the vibration peaks of the amidoxime groups can be observed at 1403 and 1707 $\\mathsf{\\bar{c}m}^{-1}$ , confirming the successful amidoximation1. Furthermore, solid-state $^{13}\\mathrm{C}$ CP/MAS NMR spectra confirmed this successful conversion, as indicated by the disappearance of the peak at ${\\sim}113$ ppm that is assigned to carbon atoms in the cyano groups together with the concomitant appearance of a peak at ${\\sim}156\\mathrm{ppm}$ assigned to the carbon atoms in amidoxime groups (Supplementary Fig. 3)1,35. The obtained TFPT-BTAN and TFPT-BTAN-AO were pale-yellow powders. The scanning electron micrograph of TFPT-BTAN shows a porous network structure (Fig. 2d), which did not change after amidoxime functionalization (Fig. 2e), indicating that TFPTBTAN-AO can be rapidly and thoroughly penetrated with $\\mathrm{UO}_{2}{}^{2+}$ . Thermogravimetric analysis profiles revealed that both the TFPT-BTAN and TFPT-BTAN-AO were stable up to $320^{\\circ}\\mathrm{C},$ indicating that good thermal stability (Supplementary Fig. 6). In addition, we treated TFPT-BTAN-AO under different harsh conditions for $12\\mathrm{{h}}$ to study chemical stability. The FT-IR spectra (Fig. 2f and Supplementary Fig. 7a) and PXRD (Fig. $2\\mathrm{g}$ and Supplementary Fig. 7b) both show that TFPT-BTAN-AO retained the same characteristic peaks after the treatments, confirming its remarkable chemical stability. In order to reflect the superior stability of TFPT-BTAN-AO compared with other COFs, two $\\beta$ -ketoenamine COFs (Tp-Bpy and Tp-BD) were synthesized by the reported method30. After treatment with high concentrations of nitric acid $3.0\\mathrm{M}$ and $5.0\\mathrm{M}$ ), the crystallinity of Tp-Bpy and Tp-BD was completely destroyed (Supplementary Fig. 7c and d), whereas our TFPT-BTAN-AO maintained good crystallinity and stability. The results show that TFPT-BTAN-AO has superior stability in high concentration nitric acid compared with $\\beta$ -ketoenamine COFs. Moreover, TFPT-BTAN-AO retained a high residual mass $(\\geq93.5\\%)$ after treatment with different concentrations of nitric acid, further indicating its excellent stability (Supplementary Table 3). All of these indicated successful synthesis of stable TFPT-BTAN-AO. \n\nSelective sensing of $\\mathbf{UO}_{2}{^{2+}}$ . After demonstrating the synthesis, we then studied the sensing performance of our COF. The normalized fluorescence spectra of TFPT-BTAN and TFPT-BTANAO dispersed in water are shown in Supplementary Fig. 8. Compared with TFPT-BTAN, the aminoximation process introduced a large amount of -OH and - $\\begin{array}{r}{-\\mathrm{NH}_{2}.}\\end{array}$ thereby reducing the conjugation effect in the TFPT-BTAN-AO. As a result, the emission spectrum of TFPT-BTAN-AO blue shifted compared to \n\n![](images/1432da4c214cf3458c2bbcb3c7b53070aa43624519b7385599543be2250ec181.jpg) \nFig. 2 Characterization of TFPT-BTAN and TFPT-BTAN-AO. a PXRD profiles. Nitrogen adsorption–desorption isotherms of b TFPT-BTAN and $\\bullet$ TFPTBTAN-AO. Insets: the pore-size distributions calculated from non-local density functional theory. SEM images of d TFPT-BTAN and e TFPT-BTAN-AO. f FT-IR spectra and $\\pmb{\\mathrm{\\pmb{g}}}\\mathsf{P}\\mathsf{X}\\mathsf{R}\\mathsf{D}$ profiles of TFPT-BTAN-AO before and after treatment with water $(100^{\\circ}\\mathsf{C})$ , HCl (1 M), NaOH (1 M), and $\\boldsymbol{\\upgamma}$ -ray irradiation ( $50\\up k\\mathsf{G y},$ $200\\mathsf{k G y})$ . \n\nTFPT-BTAN, which further indicates successful amidoximation. By excitation at $277\\mathrm{nm}$ , TFPT-BTAN-AO emitted bright blue fluorescence at $460\\mathrm{nm}$ , showing a high absolute fluorescence quantum yield of $4.3\\%$ . With a high-quantum yield and specific affinity uranium-binding groups, we then studied its $\\bar{\\mathrm{UO}}_{2}{^{2+}}$ -sensing performance. A stock solution of TFPT-BTANAO was added to the solution containing $\\mathrm{UO}_{2}{}^{2+}$ , and then diluted with ultrapure water for fluorescence measurement (Supplementary Fig. 9). The fluorescence of TFPT-BTAN-AO was significantly quenched by $\\mathrm{UO}_{2}{}^{2+}$ , and the optimal $\\mathrm{\\tt{pH}}$ for detection was at 6.0 (Supplementary Fig. 10). Importantly, TFPTBTAN-AO responded very quickly to $\\bar{\\mathrm{UO}}_{2}{^{2+}}$ , and the system can reach equilibrium within $2s$ (Supplementary Fig. 11), much faster than other detection systems (Supplementary Table 4). These results suggest that the 1D channels could promote the rapid diffusion and mass transfer of $\\mathrm{UO}_{2}{^{2+}}$ and achieve real-time detection. \n\nTo test selectivity, $\\mathrm{UO}_{2}{^{2+}}$ $(20\\upmu\\mathrm{M})$ was added directly to the TFPT-BTAN-AO aqueous dispersion, whereas other metal ions were added at $50\\upmu\\mathrm{M}$ (Fig. 3 and Supplementary Fig. 12). Only $\\mathrm{UO}_{2}{}^{2+}$ caused significant fluorescence quenching, other metal ions have little effect on the $\\mathrm{UO}_{2}{}^{2+}$ detection, and it can be visually observed under a portable $365\\mathrm{nm}$ UV lamp, indicating that TFPT-BTAN-AO has good selectivity for $\\mathrm{UO}_{2}{^{2+}}$ attributable to the specific affinity between $\\mathrm{UO}_{2}{}^{2+}$ and amidoxime groups1, and the fluorescence quenching property of $\\mathrm{UO}_{2}{}^{2+}$ . \n\nHighly sensitive sensing of $\\mathbf{UO}_{2}{^{2+}}$ . To explore the sensitivity, the fluorescence spectra of TFPT-BTAN-AO were measured at different $\\mathrm{UO}_{2}{}^{2+}$ concentrations (Fig. 4a). The fluorescence intensity of TFPT-BTAN-AO decreased with the increasing concentration of $\\mathrm{UO}_{2}{^{2+}}$ and $87\\%$ of the fluorescence was quenched with $20\\upmu\\mathrm{M}$ $\\mathrm{UO}_{2}{^{2+}}$ . In addition, the fluorescence response to $\\mathrm{UO}_{2}{}^{2+}$ was clearly observed under a $365\\mathrm{nm}$ UV lamp. Figure 4b shows a good calibration curve for the fluorescence intensity of TFPT-BTAN-AO at $460\\mathrm{nm}$ versus $\\mathrm{UO}_{2}{^{2+}}$ concentration $(0.02\\mathrm{-}6.0\\upmu\\mathrm{M})$ with a high correlation coefficient of 0.993. The limit of detection of the TFPF-BTAN-AO was determined as $6.7\\mathrm{nM}\\mathrm{UO}_{2}{}^{2+}$ (Supplementary Fig. 13), well below the World Health Organization contamination limit for $\\mathrm{UO}_{2}{^{2+}}$ in drinking water $(63\\mathrm{nM})^{7}$ . Therefore TFPF-BTAN-AO can be used for high sensitivity detection of $\\mathrm{UO}_{2}{}^{2+}$ . \n\nInteraction between TFPT-BTAN-AO and $\\mathbf{UO}_{2}{^{2+}}$ . FT-IR and X-ray photoelectron spectroscopy (XPS) were applied to investigate the effective uranium-binding and fluorescence quenching. The FT-IR spectrum of TFPT-BTAN-AO after treatment with $\\mathrm{UO}_{2}{}^{2+}$ shows a new peak at $916\\mathrm{cm}^{-1}$ , which can be attributed to the vibration of $_{\\mathrm{O=U=O}}$ (Supplementary Fig. 14)42. In addition, the appearance of N-H bending vibration at $1613\\mathrm{cm}^{-1}$ after treatment with $\\mathrm{UO}_{2}{}^{2+}$ indicates the presence of a chemisorption process8. After treating the TFPT-BTAN-AO with $\\mathrm{U}\\dot{\\mathrm{O}}_{2}{}^{2+}$ , distinctive U $4f.$ binding energy peaks emerged, revealing that $\\mathrm{UO}_{2}{}^{2+}$ was successfully loaded onto the TFPT-BTAN-AO (Supplementary Fig. 15)43,44. \n\nIn the high-resolution XPS spectrum of $\\mathrm{~N~}1\\:s$ of the TFPTBTAN-AO (Fig. 5a), the two binding energy peaks at 399.7 and $398.8\\mathrm{eV}$ are assigned to $\\mathrm{C}{\\cdot}\\mathrm{N}$ and $\\mathrm{C}{=}\\mathrm{N}$ , respectively, which correspond to the nitrogen atoms in the TFPT-BTAN-AO framework42,45. After treatment with $\\mathrm{UO}_{2}{}^{2+}$ , the N 1 s XPS spectrum of the TFPT-BTAN-AO was observed under the same measurement conditions (Fig. 5b). Comparing the $\\mathrm{~N~}1\\:s$ binding energy peaks in the two samples, a new N-U peak $(401.1\\mathrm{eV})$ formed, and the peak located at $399.7\\mathrm{eV}$ of the TFPT-BTAN-AO moved $0.22\\mathrm{eV}$ to a higher binding energy after treatment with $\\mathrm{UO}_{2}{}^{2+}$ . However, the $\\mathrm{~N~}1\\:s$ peaks at $398.8\\mathrm{eV}$ in Fig. 5a, b show no shift after treatment with $\\mathrm{UO}_{2}{^{2+}}$ , revealing that the nitrogen atoms of the $\\mathrm{C}{=}\\mathrm{N}$ did not bind to $\\mathrm{UO}_{2}{}^{2+}$ . Comparing the $\\mathrm{~O~l~s~}$ peaks in the two samples (Fig. 5c, d), it is clearly observed that a new O-U peak $(531.3\\mathrm{eV})$ formed, and the O 1 s core peak of the TFPT-BTAN-AO moved $0.2\\mathrm{eV}$ to a higher binding energy after treatment with $\\mathrm{UO}_{2}{}^{2+}$ . Based on the above results, it is speculated that the adsorption of $\\mathrm{UO}_{2}{^{2+}}$ onto the TFPT-BTAN-AO is a chemical process, and both the amino and hydroxyl groups in TFPT-BTAN-AO are coordinated with $\\mathrm{UO}_{2}{}^{2+}$ (Fig. 5e), similar to the previously reported binding mode46. \n\nThe quenching effect of $\\mathrm{UO}_{2}{}^{2+}$ on TFPT-BTAN-AO was further studied by time-resolved fluorescence spectroscopy. The fluorescence decay profile shows that TFPT-BTAN-AO has a lifetime of 3.1 ns (Supplementary Fig. 16, red curve). Upon addition of $\\mathrm{UO}_{2}{}^{2+}$ , the lifetime decreased to 1.8 ns (blue curve), which is consistent with a decrease in fluorescence intensity. $\\mathrm{UO}_{2}{^{2+}}$ induced quenching of TFPT-BTAN-AO likely to proceed by a photoinduced electron transfer (PET) process from the framework to $\\mathrm{UO}_{2}{}^{2+}$ . \n\n![](images/262f4311f7a811343314039638166e2accf0b4f32ad738220555a8da3597c447.jpg) \nFig. 3 Selectivity investigations. Fluorescence intensity of TFPT-BTAN-AO at 460 nm in the presence of various metal ions and mixed ions. Concentrations of $\\mathsf{U O}_{2}\\mathsf{2}+$ and other metal ions were $20\\upmu\\upmu$ and $50\\upmu\\mathsf{M},$ respectively. Photographs showing the fluorescence emission change (under a portable 365 nm UV lamp) of TFPT-BTAN-AO with various metal ions. Error bars represent S.D. $n=3$ independent experiments. \n\n![](images/627e5107c3d525f1049cc7a9af995251d08c370db0a88a80fc34e0a4577c16c0.jpg) \nFig. 4 Sensitivity investigations. a Fluorescence emission spectra of TFPT-BTAN-AO upon gradual addition of $\\mathsf{U O}_{2}{}^{2+}\\left(\\lambda_{\\mathrm{ex}}=277\\mathsf{n m}\\right)$ . Inset photos show the fluorescence emission change (under a $365\\mathsf{n m}\\mathsf{U V}$ lamp) of TFPT-BTAN-AO after addition of $\\mathsf{U O}_{2}\\mathsf{{^{2+}}}$ . b Fluorescence intensity at $460\\mathsf{n m}$ versus the concentration of $\\mathsf{U O}_{2}\\mathsf{2}+$ . Inset: The linear calibration plot for $\\mathsf{U O}_{2}\\mathsf{2}+$ detection. Error bars represent S.D. $n=3$ independent experiments. \n\nEfficient extraction of $\\mathbf{UO}_{2}{^{2+}}$ . Given the very stable $(\\mathrm{-C=C-})$ bonds and abundant selective $\\mathrm{UO}_{2}{}^{2+}$ -binding groups on the 1D channels, this material may serve for high performance $\\mathrm{UO}_{2}{}^{2+}$ extraction under harsh conditions. To test the importance of the regular porous structure for adsorbing $\\mathrm{UO}_{2}{^{2+}}$ , an amorphous analog named POP-TB was synthesized and subjected to the same amidoximation to give POP-TB-AO (Supplementary Figs. 17–19). Both the COF-based materials and their amorphous POP analogs were demonstrated very similar FT-IR spectra and nitrogen element contents before and after the amidoximation process (Supplementary Figs. 20 and 21), indicating similar amidoxime functionalization processes. \n\nThe adsorption isotherm of TFPT-BTAN-AO has a much steeper adsorption curve for $\\mathrm{UO}_{2}{}^{2+}$ (Fig. 6a), indicating that its affinity for $\\mathrm{U}\\dot{\\mathrm{O}}_{2}{}^{2+}$ is higher than that of corresponding POP-TB$\\mathrm{AO}^{24}$ . All the adsorption experimental data are in good agreement with the Langmuir isotherm model, and the correlation coefficients are higher than 0.99 (Supplementary Fig. 22). Surprisingly, the maximum adsorption capacity for $\\mathrm{\\dot{U}O}_{2}\\mathrm{\\dot{^2}+}$ on TFPT-BTAN-AO $(427\\mathrm{mgg^{-1}})$ is much higher than that of POP-TB-AO $(353\\mathrm{mgg^{-1}};$ , and is located among the top of different types of adsorbents (Supplementary Table 5). Importantly, the superior performance of TFPT-BTAN-AO exceeded all previously reported COFs for $\\mathrm{UO}_{2}{}^{2+}$ extraction, like COF-TpDb-AO $(\\dot{4}08\\dot{\\mathrm{mg}}\\mathrm{g^{-1}})^{1}$ , ACOF $(169\\mathrm{mgg^{-1}})^{43}$ , and $o$ -GS-COF $(144.2\\mathrm{mg}\\mathrm{g}^{-1})^{3}$ . The uranium content loaded on the framework was calculated based on the ICP-MS results, this capacity means that $66.8\\%$ accessibility of the amidoxime groups in TFPT-BTAN-AO were used to extract $\\mathrm{UO}_{2}{}^{2+}$ . The TFPTBTAN-AO showed exceptional performance in extraction of $\\mathrm{UO}_{2}{}^{2+}$ in terms of saturated adsorption capacity as compared to POP-TB-AO, suggesting the important role of the adsorbent’s architecture. This surprisingly high saturation $\\mathrm{UO}_{2}{}^{2+}$ extraction capacity can be attributed to synergistic effect of the rich and even distribution of amidoxime groups on the pore walls and the higher accessibility of $\\mathrm{UO}_{2}{}^{2+}$ in the open 1D channel. \n\n![](images/57f265bd0c835c640512ac2e90b44f280f7a2b5cb14b1b95c401c26418524329.jpg) \nFig. 5 XPS data, fits, and interaction between TFPT-BTAN-AO and $\\mathfrak{u o}_{2}{\\mathfrak{z}}^{2+}$ . XPS spectra of the N 1 s region of TFPT-BTAN-AO a before and b after treatment with $\\mathsf{U O}_{2}\\mathsf{{^{2+}}}$ . XPS spectra of the O 1 s region of TFPT-BTAN-AO c before and d after treatment with $\\mathsf{U O}_{2}\\mathsf{2}+$ . e Schematic diagram of the interaction between TFPT-BTAN-AO and $\\mathsf{U O}_{2}\\mathsf{2}+$ . \n\nIn addition to the high adsorption capacity, TFPT-BTAN-AO also extracted $\\mathrm{UO}_{2}{}^{2+}$ from aqueous solution more rapidly compared with POP-TB-AO (Fig. 6b). All the adsorption kinetics data are in good agreement with the pseudo-second-order model, and the correlation coefficients are higher than 0.995 (Supplementary Fig. 23). It is worth noting that TFPT-BTAN-AO can achieve a saturation capacity of about $98\\%$ within $45\\mathrm{{min}}$ . This is in sharp contrast to the long contact times required for other uranium sorbent materials, which typically range from hours to $\\mathrm{days^{7,47-49}}$ . For comparison, POP-TB-AO took $85\\mathrm{min}$ to reach $95\\%$ of its equilibrium adsorption capacity. \n\nApart from rapid equilibration, TFPT-BTAN-AO also has higher extraction capacity with an equilibrium capacity of 417 $\\mathrm{m}\\bar{\\bf g}{\\bf g}^{-1}$ , whereas POP-TB-AO only reaches $336\\mathrm{m}\\bar{\\mathrm{g}}\\mathrm{g}^{-1}$ (Supplementary Fig. 24). Considering that TFPT-BTAN-AO and POPTB-AO have similar chemical compositions, the high absorption capacity and rapid adsorption kinetics should be attributed to their different pore structures. The rapid kinetics of TFPTBTAN-AO can be attributed to the hierarchical pores structure and the evenly and densely distributed chelating sites on the pore walls to facilitate rapid diffusion of $\\mathrm{UO}_{2}{}^{2+}$ throughout the framework (Supplementary Fig. 25). In contrast, the pore structure in POP-TB-AO is irregular, making it more susceptible to clogging, thus greatly impairing their adsorption performance. \n\nFor practical applications, extraction of $\\mathrm{U}\\dot{\\mathrm{O}_{2}}^{2+}$ under various harsh conditions is highly desirable. Considering that $\\mathrm{UO}_{2}{}^{2+}$ is mainly present in the acidic environment and hydrolysis occurs at a higher $\\mathsf{p H}$ (Supplementary Fig. 26), adsorption experiments were performed at $\\mathrm{pH}<5.0$ . Supplementary Fig. 27 shows the adsorption capacity of $\\mathrm{UO}_{2}{^{2+}}$ on TFPT-BTAN-AO at different $\\mathsf{p H}$ values. Obviously, the adsorption capacity increases as the system $\\mathrm{\\tt{pH}}$ value rises from 1.0 to 4.0. \n\nAs nuclear fuel reprocessing and wastewater are usually treated under highly acidic conditions, it is necessary to evaluate the effect of solution acidity on $\\mathrm{UO}_{2}{}^{2+}$ extraction by TFPT-BTAN-AO (Supplementary Fig. 27). Surprisingly, TFPT-BTAN-AO showed high adsorption capacity in highly acidic media, the saturated capacity in $3.0\\mathrm{M}$ nitric acid was calculated to be $128\\mathrm{mgg^{-1}}$ , this capacity is much higher than COF-IHEP1 $\\mathrm{70}\\mathrm{mgg^{-1}}$ , 2 M nitric acid)50. To further confirm the chemical stability and excellent uranium extraction performance of TFPT-BTAN-AO, the adsorption capacities of TFPT-BTAN-AO after treatment with water $(100^{\\circ}\\mathrm{C})$ , HCl (1 M), ${\\mathrm{HNO}}_{3}$ (0.1–5.0 M), NaOH (1 M), and $\\upgamma$ -ray irradiation $(50\\mathrm{kGy}$ , $200\\mathrm{kGy}$ ) were also studied (Supplementary Fig. 28). The results verified that the uranium extraction performance of TFPT-BTAN-AO was almost unchanged after treatment under various extreme conditions, indicating that TFPTBTAN-AO has excellent stability and practical application potential. This feature is a significant advantage over imine-based COFs sorbents that typically suffer from the decomposition of structures under extreme conditions1,3. \n\n![](images/dbfff5c2b9ec23580108354c6db2c55f03f4fc54535136978f9d99cb6f4d28af.jpg) \nFig. 6 $\\yen1023,4$ adsorption isotherms and kinetics investigations. a Adsorption isotherm of $\\mathsf{U O}_{2}2+$ on TFPT-BTAN-AO and POP-TB-AO $\\left(\\mathsf{p}\\mathsf{H}\\ 4.0\\right)$ . b Adsorption kinetics of $\\mathsf{U O}_{2}\\mathsf{{^{2+}}}$ on TFPT-BTAN-AO and POP-TB-AO $\\left(\\mathsf{p}\\mathsf{H}\\ 4.0\\right)$ . c The removal efficiency of $\\mathsf{U O}_{2}\\mathsf{2}+$ under different pH conditions. d The selective adsorption of the test ions. Error bars represent S.D. $n=3$ independent experiments. \n\nIn addition, the uranium concentration reduced from 9.952 ppm to $8.45\\mathrm{ppb}$ and 6.17 ppb at $\\mathsf{p H}$ values of 2 and 12, respectively (Fig. 6c). It is well below the US Environmental Protection Agency (EPA) uranium-containing wastewater discharge standard $(30{\\mathrm{ppb}})^{1}$ . To evaluate the affinity of TFPTBTAN-AO toward $\\mathrm{UO}_{2}{}^{2+}$ , additional selective extraction experiments with $9.952\\mathrm{ppm}$ $\\mathrm{UO}_{2}{}^{2+}$ $\\left(V/m=5000\\mathrm{mLg^{-1}}\\right)$ ) were carried out. The calculated distribution coefficient $K_{d}$ $(8.3\\times10^{6}\\mathrm{mLg^{-1}},$ is much larger than the distinguishing standard $(1.0\\times10^{4}\\mathrm{mLg^{-1}})$ ), which is generally considered to be a good adsorbent (Fig. 6d), indicating the excellent affinity of TFPT-BTAN-AO for $\\mathrm{UO}_{2}{}^{2+47}$ . We attribute the enormous distribution coefficient to the specific affinity for $\\mathrm{UO}_{2}{}^{2+}$ provided by the 1D open channel amidoxime groups in TFPT-BTAN-AO. The above results indicate the superiority of TFPT-BTAN-AO as a promising candidate for uranium extraction. \n\nReversible binding for regeneration. One of the unique advantages of TFPT-BTAN-AO is that the very stable framework provides the most critical foundation for the reversible binding of $\\mathrm{\\hat{U}O}_{2}{}^{2+}$ . We found that the fluorescence of TFPT-BTAN-AO can be easily recovered by ${\\mathrm{Na}}_{2}{\\mathrm{CO}}_{3}$ (1 M) aqueous solution (Fig. 7a). To confirm the practical reusability of TFPT-BTAN-AO as an adsorbent, we conducted multiple adsorption–desorption experiments and found that sodium carbonate has a high elution efficiency $(>95\\%)$ even after six cycles (Fig. 7b). In addition, elution of $\\mathrm{UO}_{2}{^{2+}}$ with sodium carbonate did not affect the adsorption performance of TFPT-BTAN-AO, and maintained a high adsorption capacity $(>87\\%)$ even after six cycles. More importantly, owing to the excellent stability of the framework, TFPT-BTAN-AO crystal structure and functional groups were well preserved after recycling, as evidenced by PXRD and FT-IR results (Supplementary Fig. 29 and Fig. 7c). It is worth noting that TFPT-BTAN-AO can be cycled at least six times without noticeable influence of response to $\\mathrm{UO}_{2}{}^{2+}$ or sensitivity, and this exceptional regeneration can be observed by the naked eye under a portable UV lamp (Supplementary Fig. 30). So far, this is the first demonstration of COF-based regenerable detection and extraction of $\\mathrm{UO}_{2}{}^{2+}$ . The above results indicate that TFPTBTAN-AO has great potential for simultaneous detection and extraction of $\\mathrm{U}\\bar{\\mathrm{O}}_{2}{}^{2+}$ . Importantly, such regeneration is almost impossible for previously reported imine-based COFs adsorbents. \n\n# Discussion \n\nIn summary, we have successfully developed a strongly fluorescent COF for real-time detection and efficient extraction of $\\mathrm{UO}_{2}{}^{2+}$ . Different from previous COF sorbents relying on imine bond $\\scriptstyle(-C=N-)$ , our COF used very stable carbon–carbon double bonds $\\scriptstyle(-C=C-)$ . Our COF combines strong fluorescence, excellent stability, dense, and evenly distributed amidoxime groups, and highly accessible binding sites through the open 1D channel. With these advantages, TFPT-BTAN-AO achieved real-time sensitive detection, efficient extraction, and efficient regeneration by simply adding carbonate. Given the wealth of knowledge in designing contaminant-specific ligands, this strategy may extend to the detection and extraction of other environmental contaminants. \n\n![](images/84bd4fa0b9491994832f9c458a815386696371ca39d6a5526075f7c71e56b737.jpg) \nFig. $\\7\\mathbf{u}\\mathbf{o}_{2}\\mathsf{\\pmb{2}}+$ adsorption and regeneration investigations. a Schematic diagram of TFPT-BTAN-AO regeneration detection and extraction of $\\mathsf{U O}_{2}\\mathsf{{^{2+}}}$ . b The $\\mathsf{U O}_{2}{}^{2+}$ adsorption capacity (left axis) and elution efficiency (right axis) of TFPT-BTAN-AO in six successive adsorption–desorption cycles. c FT-IR spectra of TFPT-BTAN-AO, TFPT-BTAN-AO after extraction of $\\mathsf{U O}_{2}{}^{2+},$ and TFPT-BTAN-AO after desorption of $\\mathsf{U O}_{2}\\mathsf{{^{2+}}}$ by the ${\\sf N a}_{2}{\\sf C O}_{3}$ $\\left\\langle1.0\\mathrm{mol}\\lfloor-1\\right\\rangle$ aqueous solution. Error bars represent S.D. $n=3$ independent experiments. \n\n# Methods \n\nMaterials. 2,4,6-Tris(4-bromophenyl)-1,3,5-triazine, $n$ -BuLi, hydroxylamine hydrochloride $\\mathrm{(NH_{2}O H{\\cdot}H C l)},$ , DBU, and triethylamine were purchased from Saan Chemical Technology (Shanghai) Co., Ltd. Benzaldehyde and 1,3,5-tris(bromomethyl)benzene were purchased from Jilin Chinese Academy of Sciences-Yanshen Technology Co., Ltd. Mesitylene, 1,4-dioxane, acetone, chloroform $\\mathrm{(CHCl_{3})}$ , tetrahydrofuran (THF), N,N-dimethylformamide, sodium bicarbonate, sodium cyanide, $n$ -hexane, $n$ -BuOH, NaOH, EtONa, $\\mathrm{Cs}_{2}\\mathrm{CO}_{3}$ , piperidine, pyridine, 1,2-dichlorobenzene, and $\\mathrm{MgSO_{4}}$ were purchased from Sinopharm Chemical Reagent Co., Ltd. Ultrapure water was prepared from the Millipore system $(18.25\\mathrm{M}\\Omega\\mathrm{-}\\mathrm{cm})$ . All the purchased reagents were of analytical grade and used without further purification. \n\nSynthesis of model compound. To a $25\\mathrm{mL}$ Pyrex tube, benzaldehyde $\\left(63.67\\mathrm{mg};\\right.$ $0.60\\mathrm{mmol}$ ), ${}_{2,2^{\\prime},2^{\\prime\\prime}}$ -(benzene-1,3,5-triyl)triacetonitrile $(39.04\\mathrm{mg},0.20\\mathrm{mmol},$ ), oDCB $(5\\mathrm{mL})$ and DBU aqueous solution $(0.5\\mathrm{mL},4\\mathrm{M}$ ) were added. The mixture was sonicated for 10 minutes, degassed by three freeze–pump–thaw cycles, sealed under vacuum and heated at $90^{\\circ}\\mathrm{C}$ for 3 days. The reaction mixture was cooled to room temperature, the precipitate was filtered and washed several times with ethanol. The product was obtained as a pale-yellow solid. Yield: $72\\%$ . $^1\\mathrm{H}$ NMR ( $\\mathrm{CDCl}_{3}$ , $\\delta\\left(\\mathrm{{ppm})}$ ): 7.99 $(\\mathrm{m},6\\mathrm{H}$ , ArH), 7.96 (s, 3 H, Ar-H), 7.71 (s, 3 H, vinyl), 7.52 (m, 9 H, Ar-H). $^{13}\\mathrm{C}$ NMR (DMSO- $\\mathrm{d}^{6}$ , δ (ppm)): 150.44, 140.99, 138.61, 136.29, 134.54, 134.24, 129.01, 122.75, 114.31. Elemental analysis: calculated C $(86.25\\%)$ ), H $(4.61\\%)$ ), N $(9.14\\%)$ and observed C $(86.09\\%$ , H $(4.45\\%)$ ), N $(9.03\\%)$ . \n\nSynthesis of TFPT-BTAN COF. To a $25\\mathrm{mL}$ Pyrex tube, $^{2,4,6}$ -tris(4-formylphenyl)-1,3,5-triazine $(78.68\\mathrm{mg},0.20\\mathrm{mmol}$ ), ${}_{2,2^{\\prime},2^{\\prime\\prime}}$ -(benzene-1,3,5-triyl)triacetonitrile (39.04 mg, 0.20 mmol), $o$ -DCB $\\mathrm{\\nabla{\\cdot}\\mathbf{m}L})$ ) and DBU aqueous solution (0.5 mL, 4 M) were added. The mixture was sonicated for 10 minutes, degassed by three freeze–pump–thaw cycles, sealed under vacuum and heated at $90^{\\circ}\\mathrm{C}$ for 5 days. The reaction mixture was cooled to room temperature, and a pale-yellow precipitate was collected by centrifugation, washed several times with methanol, $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}$ and THF, respectively. It was then Soxhlet extracted in $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}$ and THF for $24\\mathrm{h}$ and dried under vacuum at $80^{\\circ}\\mathrm{C}$ for $12\\mathrm{{h}}$ to afford pale-yellow powder, $67\\%$ yield. Elemental analysis: calculated C $(79.10\\%)$ , H $(5.53\\%)$ , N $(15.37\\%)$ ), and observed C $(74.31\\%)$ , H $(5.72\\%)$ , N $(15.65\\%)$ . For other conditions, follow the same experimental procedure to obtain TFPT-BTAN COF, as shown in the Supplementary Table 1. \n\nSynthesis of TFPT-BTAN-AO. The TFPT-BTAN $(0.4{\\bf g})$ was swollen in absolute ethanol $\\mathrm{\\langle40mL\\rangle}$ for $20\\mathrm{min}$ , followed by the addition of $\\mathrm{\\DeltaNH_{2}O H{\\cdot}H C l}$ $(1.0\\mathrm{g})$ and N $(\\mathrm{CH}_{2}\\mathrm{CH}_{3})_{3}$ $(1.5{\\mathrm{g}})$ . After stirring at $85^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ , the mixture was filtered, washed with excess water and finally dried at $60^{\\circ}\\mathrm{C}$ under vacuum. The pale-yellow solid obtained was expressed as TFPT-BTAN-AO. Elemental analysis: calculated C $(66.96\\%$ ), H $(6.09\\%)$ , N $(19.52\\%)$ ), and observed C $(65.31\\%)$ , H $(6.22\\%)$ , N $(19.75\\%)$ . \n\nSynthesis of POP-TB. To a $25\\mathrm{mL}$ Pyrex tube, 2,4,6-Tris(4-formylphenyl)-1,3,5- triazine ( $78.68\\mathrm{mg}$ $0.20\\mathrm{mmol}$ ), ${}_{2,2^{\\prime},2^{\\prime\\prime}}$ -(benzene-1,3,5-triyl)triacetonitrile $(39.04\\mathrm{mg}$ , $0.20\\mathrm{mmol}$ ), 1,4-dioxane $(5\\mathrm{mL})$ , and NaOH aqueous solution (0.5 mL, 4 M) were added. The mixture was sonicated for 10 minutes, degassed by three freeze–pump–thaw cycles, sealed under vacuum and heated at $90^{\\circ}\\mathrm{C}$ for 5 days. The reaction mixture was cooled to room temperature, and a pale-yellow precipitate was collected by centrifugation, washed several times with methanol, $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}$ , and THF, respectively. It was then Soxhlet extracted in $\\mathrm{CH}_{2}\\mathrm{Cl}_{2}$ and THF for $24\\mathrm{h}$ and dried under vacuum at $80^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ to afford pale-yellow powder, $70\\%$ yield. Elemental analysis: observed C $(74.16\\%)$ , H $(5.64\\%)$ ), N $(15.53\\%)$ . \n\nSynthesis of POP-TB-AO. The POP-TB $(0.4{\\bf g})$ was swollen in absolute ethanol $\\mathrm{(40~mL)}$ ) for $20\\mathrm{min}$ , followed by the addition of $\\mathrm{NH}_{2}\\mathrm{OH}{\\cdot}\\mathrm{HCl}$ $\\left(1.0{\\mathrm{g}}\\right)$ and N $\\mathrm{(CH_{2}C H_{3})_{3}}$ $(1.5{\\mathrm{g}})$ . After stirring at $85^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ , the mixture was filtered, washed with excess water and finally dried at $60^{\\circ}\\mathrm{C}$ under vacuum. The pale-yellow solid obtained was expressed as POP-TB-AO. Elemental analysis: observed C $(65.15\\%)$ , H $(6.13\\%)$ , N $(19.58\\%$ ). \n\n# Data availability \n\nAll data are either provided in the Article and its Supplementary Information or are available from the corresponding author upon request. \n\nReceived: 24 September 2019; Accepted: 18 December 2019; Published online: 23 January 2020 \n\n# References \n\n1. Qi, S. et al. Covalent organic frameworks as a decorating platform for utilization and affinity enhancement of chelating sites for radionuclide sequestration. Adv. Mater. 30, 1705479 (2018). \n2. Abney, C. W. et al. Materials for the recovery of uranium from seawater. Chem. Rev. 117, 13935–14013 (2017). \n3. Wen, R. et al. Graphene-synergized 2D covalent organic framework for adsorption: a mutual promotion strategy to achieve stabilization and functionalization simultaneously. J. Hazard. Mater. 358, 273–285 (2018). \n4. Xiao, F. et al. Smart photonic crystal hydrogel material for uranyl ion monitoring and removal in water. Adv. Funct. Mater. 27, 1702147 (2017). \n5. Sun, Q. et al. Bio-inspired nano-traps for uranium extraction from seawater and recovery from nuclear waste. Nat. Commun. 9, 1644 (2018). \n6. Ma, S. et al. Efficient uranium capture by polysulfide/layered double hydroxide composites. J. Am. Chem. Soc. 137, 3670–3677 (2015). \n7. Xu, M. et al. Highly fluorescent conjugated microporous polymers for concurrent adsorption and detection of uranium. J. Mater. Chem. A 7, 11214–11222 (2019). \n8. Liu, W. et al. Highly sensitive and selective uranium detection in natural water systems using a luminescent mesoporous metal–organic framework equipped with abundant lewis basic sites: a combined batch, X-ray absorption spectroscopy, and first principles simulation investigation. Environ. Sci. Technol. 51, 3911–3921 (2017). \n9. Aguila, B. et al. Efficient mercury capture using functionalized porous organic polymer. Adv. Mater. 29, 1700665 (2017). \n10. Fu, Y. et al. Sulfur-rich covalent triazine polymer nanospheres for environmental mercury removal and detection. Polym. Chem. 9, 4125–4131 (2018). \n11. Xu, L. et al. Nano-MOF+ technique for efficient uranyl remediation. ACS Appl. Mater. Interfaces 11, 21619–21626 (2019). \n12. Ly, H. G. T. et al. Superactivity of MOF-808 toward peptide bond hydrolysis. J. Am. Chem. Soc. 140, 6325–6335 (2018). \n13. Paille, G. et al. A fully noble metal-free photosystem based on cobaltpolyoxometalates immobilized in a porphyrinic metal–organic framework for water oxidation. J. Am. Chem. Soc. 140, 3613–3618 (2018). \n14. Lu, S. et al. Synthesis of ultrafine and highly dispersed metal nanoparticles confined in a thioether-containing covalent organic framework and their catalytic applications. J. Am. Chem. Soc. 139, 17082–17088 (2017). \n15. Aiyappa, H. B. et al. Cobalt-modified covalent organic framework as a robust water oxidation electrocatalyst. Chem. Mater. 28, 4375–4379 (2016). \n16. Pachfule, P. et al. Diacetylene functionalized covalent organic framework (COF) for photocatalytic hydrogen generation. J. Am. Chem. Soc. 140, 1423–1427 (2018). \n17. Bhadra, M. et al. Predesigned metal-anchored building block for in situ generation of Pd nanoparticles in porous covalent organic framework: application in heterogeneous tandem catalysis. ACS Appl. Mater. Interfaces 9, 13785–13792 (2017). \n18. Bhadra, M. et al. Triazine functionalized porous covalent organic framework for photo-organocatalytic E–Z isomerization of olefins. J. Am. Chem. Soc. 141, 6152–6156 (2019). \n19. Ning, H. et al. Two-dimensional covalent organic frameworks for carbon dioxide capture through channel-wall functionalization. Angew. Chem. 127, 3029–3033 (2015). \n20. Rabbani, M. G. et al. A 2D mesoporous imine-linked covalent organic framework for high pressure gas storage applications. Chem. Eur. J. 19, 3324–3328 (2013). \n21. Li, Z. et al. An azine-linked covalent organic framework: synthesis, characterization and efficient gas storage. Chem. Eur. J. 21, 12079–12084 (2015). \n22. El-Mahdy, A. F. M. et al. Hollow microspherical and microtubular [3+3] carbazole-based covalent organic frameworks and their gas and energy storage applications. ACS Appl. Mater. Interfaces 11, 9343–9354 (2019). \n23. Sun, Q. et al. Postsynthetically modified covalent organic frameworks for efficient and effective mercury removal. J. Am. Chem. Soc. 139, 2786–2793 (2017). \n24. Huang, N. et al. Stable covalent organic frameworks for exceptional mercury removal from aqueous solutions. J. Am. Chem. Soc. 139, 2428–2434 (2017). \n25. Ding, S.-Y. et al. Thioether-based fluorescent covalent organic framework for selective detection and facile removal of mercury(II). J. Am. Chem. Soc. 138, 3031–3037 (2016). \n26. Li, Y. et al. Fabrication of hydrazone-linked covalent organic frameworks using alkyl amine as building block for high adsorption capacity of metal ions. ACS Appl. Mater. Interfaces 11, 11706–11714 (2019). \n27. Mon, M. et al. Fine-tuning of the confined space in microporous metal–organic frameworks for efficient mercury removal. J. Mater. Chem. A 5, 20120–20125 (2017). \n28. Cui, W.-R. et al. Covalent organic framework nanosheet-based ultrasensitive and selective colorimetric sensor for trace $\\mathrm{Hg}^{2+}$ detection. ACS Sustain. Chem. Eng. 7, 9408–9415 (2019). \n29. Diercks, C. S. et al. Reticular electronic tuning of porphyrin active sites in covalent organic frameworks for electrocatalytic carbon dioxide reduction. J. Am. Chem. Soc. 140, 1116–1122 (2018). \n30. Cui, W.-R. et al. Covalent organic framework nanosheets for fluorescence sensing via metal coordination. ACS Appl. Nano Mater. 2, 5342–5349 (2019). \n31. Ding, S.-Y. et al. Construction of covalent organic framework for catalysis: Pd/ COF-LZU1 in suzuki-miyaura coupling reaction. J. Am. Chem. Soc. 133, 19816–19822 (2011). \n32. Zhang, G. et al. Water-dispersible PEG-curcumin/amine-functionalized covalent organic framework nanocomposites as smart carriers for in vivo drug delivery. Nat. Commun. 9, 2785 (2018). \n33. Chen, R. et al. Designed synthesis of a 2D porphyrin-based $s p^{2}$ carbonconjugated covalent organic framework for heterogeneous photocatalysis. Angew. Chem. Int. Ed. 58, 6430–6434 (2019). \n34. Jin, E. et al. Two-dimensional $s p^{2}$ carbon–conjugated covalent organic frameworks. Science 357, 673 (2017). \n35. Zhao, Y. et al. Fully conjugated two-dimensional $s p^{2}$ -carbon covalent organic frameworks as artificial photosystem I with high efficiency. Angew. Chem. Int. Ed. 58, 5376–5381 (2019). \n36. Xu, J. et al. An olefin-linked covalent organic framework as a flexible thin-film electrode for a high-performance micro-supercapacitor. Angew. Chem. Int. Ed. 58, 12065–12069 (2019). \n37. Zhang, Z. et al. 3,4-Hydroxypyridinone-modified carbon quantum dot as a highly sensitive and selective fluorescent probe for the rapid detection of uranyl ions. Environ. Sci. 6, 1457–1465 (2019). \n38. Li, Y. et al. Growth of high-quality covalent organic framework nanosheets at the interface of two miscible organic solvents. Nanoscale Horiz. 3, 205–212 (2018). \n39. Zhang, D. et al. Colorimetric peroxidase mimetic assay for uranyl detection in sea water. ACS Appl. Mater. Interfaces 7, 4589–4594 (2015). \n40. Wen, J. et al. Aggregation-induced emission active tetraphenylethene-based sensor for uranyl ion detection. J. Hazard. Mater. 318, 363–370 (2016). \n41. Bi, S. et al. Two-dimensional semiconducting covalent organic frameworks via condensation at arylmethyl carbon atoms. Nat. Commun. 10, 2467 (2019). \n42. Liu, X. et al. Amidoxime-functionalized hollow carbon spheres for efficient removal of uranium from wastewater. ACS Sustain. Chem. Eng. 7, 10800–10807 (2019). \n43. Li, X. et al. Solvent- and catalyst-free synthesis of an azine-linked covalent organic framework and the induced tautomerization in the adsorption of U (vi) and Hg(ii). Green. Chem. 21, 649–657 (2019). \n44. Aguila, B. et al. Design strategies to enhance amidoxime chelators for uranium recovery. ACS Appl. Mater. Interfaces 11, 30919–30926 (2019). \n45. Ma, C. et al. Sunlight polymerization of poly(amidoxime) hydrogel membrane for enhanced uranium extraction from seawater. Adv. Sci. 6, 1900085 (2019). \n46. Zhao, S. et al. A Dual-surface amidoximated halloysite nanotube for highefficiency economical uranium extraction from seawater. Angew. Chem. Int. Ed. 131, 15121–15127 (2019). \n47. Xiong, X. H. et al. Ammoniating covalent organic framework (COF) for highperformance and selective extraction of toxic and radioactive uranium ions. Adv. Sci. 6, 1900547 (2019). \n48. Barber, P. S. et al. Surface modification of ionic liquid-spun chitin fibers for the extraction of uranium from seawater: seeking the strength of chitin and the chemical functionality of chitosan. Green. Chem. 16, 1828–1836 (2014). \n49. Zheng, T. et al. Overcoming the crystallization and designability issues in the ultrastable zirconium phosphonate framework system. Nat. Commun. 8, 15369 (2017). \n50. Yu, J. et al. Phosphonate-decorated covalent organic frameworks for actinide extraction: a breakthrough under highly acidic conditions. CCS Chem. 1, 286–295 (2019). \n\n# Acknowledgements \n\nWe gratefully acknowledge the supports from the National Natural Science Foundation of China (21675078, 21775065, and 21976077), and the Natural Science Foundation of Jiangxi Province (20165BCB18022). \n\n# Author contributions \n\nJ.-D.Q. conceived and designed the research. W.-R.C. performed the synthesis and conducted the experiments, and C.-R.Z., W.J. and F.-F.L. performed the characterizations. W.-R.C., R.-P.L., J.L. and J.-D.Q. participated in drafting the paper and gave approval to the final version of the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-14289-x. \n\nCorrespondence and requests for materials should be addressed to J.-D.Q. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1002_anie.202003842", + "DOI": "10.1002/anie.202003842", + "DOI Link": "http://dx.doi.org/10.1002/anie.202003842", + "Relative Dir Path": "mds/10.1002_anie.202003842", + "Article Title": "Coordination Tunes Selectivity: Two-Electron Oxygen Reduction on High-Loading Molybdenum Single-Atom Catalysts", + "Authors": "Tang, C; Jiao, Y; Shi, BY; Liu, JN; Xie, ZH; Chen, X; Zhang, Q; Qiao, SZ", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "Single-atom catalysts (SACs) have great potential in electrocatalysis. Their performance can be rationally optimized by tailoring the metal atoms, adjacent coordinative dopants, and metal loading. However, doing so is still a great challenge because of the limited synthesis approach and insufficient understanding of the structure-property relationships. Herein, we report a new kind of Mo SAC with a unique O,S coordination and a high metal loading over 10 wt %. The isolation and local environment was identified by high-angle annular dark-field scanning transmission electron microscopy and extended X-ray absorption fine structure. The SACs catalyze the oxygen reduction reaction (ORR) via a 2 e(-) pathway with a high H2O2 selectivity of over 95 % in 0.10 m KOH. The critical role of the Mo single atoms and the coordination structure was revealed by both electrochemical tests and theoretical calculations.", + "Times Cited, WoS Core": 486, + "Times Cited, All Databases": 508, + "Publication Year": 2020, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000524335500001", + "Markdown": "# Angewandte International Edition Chemie \n\nwww.angewandte.org \n\n# Accepted Article \n\nTitle: Coordination Tunes Selectivity: Two-Electron Oxygen Reduction on High-Loading Molybdenum Single-Atom Catalysts \n\nAuthors: Cheng Tang, Yan Jiao, Bingyang Shi, Jia-Ning Liu, Zhenhua Xie, Xiao Chen, Qiang Zhang, and Shizhang Qiao \n\nThis manuscript has been accepted after peer review and appears as an Accepted Article online prior to editing, proofing, and formal publication of the final Version of Record (VoR). This work is currently citable by using the Digital Object ldentifier (DOl) given below. The VoR will be published online in Early View as soon as possible and may be different to this Accepted Article as a result of editing. Readers should obtain the VoR from the journal website shown below when it is published to ensure accuracy of information. The authors are responsible for the content of this Accepted Article. \n\nTo be cited as: Angew. Chem. Int. Ed. 10.1002/anie.202003842 Angew.Chem.10.1002/ange.202003842 \n\nLink to VoR: http://dx.doi.org/10.1002/anie.202003842 \nhttp://dx.doi.org/10.1002/ange.202003842 \n\n# Coordination Tunes Selectivity: Two-Electron Oxygen Reduction on High-Loading Molybdenum Single-Atom Catalysts \n\nCheng Tang,alt Yan Jiao,alt Bingyang Shi,bl Jia-Ning Liu, Zhenhua Xie,d Xiao Chen, Qiang Zhang, and Shi-Zhang Qiao\\*[a] \n\nAbstract: Single-atom catalysts (SACs) have great potential in electrocatalysis. Their performance can be rationally optimized by tailoring the center metal atoms, adjacent coordinative dopants, and metal loading. However, it is still of great challenge due to the limited synthesis approach and insufficient understanding of the structureproperty relation.Herein,we reported a new kind of Mo SAC with a unique O, S-dual coordination and a high metal loading over $10\\mathrm{\\:wt\\%}$ The isolation feature and local environment was identified by highangle annular dark-field scanning transmission electron microscopy and extended X-ray absorption fine structure.The obtained SACs can catalyze oxygen reduction reaction via $2\\mathsf{e}^{-}$ pathway with a high ${\\sf H}_{2}{\\sf O}_{2}$ selectivity above $95\\%$ in $0.10\\mathrm{~M~}\\mathsf{K O H}$ . The critical role of Mo single atoms and the coordination structure was revealed by both electrochemical tests and theoretical calculations.This work enriches the family of SACs and highlights the importance of local coordination, thus rendering new opportunities to tune the activity and selectivity in multi-electron electrocatalysis. \n\nSingle-atom catalysts (SACs) have recently emerged as an important class of electrocatalysts which can integrate the merits of both homogeneous and heterogeneous catalysts.[1-2] Their well-defined single atomic geometry and electronic structures can be rationally tailored by changing the center metal atoms (Pt, Ru, Fe, Co, Ni, Cu, etc.), adjacent coordinative dopants (N, O, S, etc.), and coordination numbers, thus enabling a flexible reaction tunability in this material platform.[3-9] For example, atomically dispersed $\\mathsf{F e\\mathrm{-}N\\mathrm{_{x}\\mathrm{-}C}}$ moieties are the most widely investigated SACs for oxygen reduction reaction (ORR) via $4\\mathsf{e}^{-}$ pathway,[10-11] while both $\\mathsf{F e\\mathrm{-}O\\mathrm{-}C}$ and ${\\mathsf{C o}}{\\mathsf{-N}}_{x-\\mathsf{C}}$ are reported to be highly selective for $2\\mathsf{e}^{-}$ pathway.[12-13] Meanwhile for $\\mathsf{C O}_{2}$ reduction reaction, most efforts on SACs can only promote $2\\mathsf{e}^{-}$ pathway to CO with high selectivity,[14-15] but the single-atom cobalt immobilized by phthalocyanine ligands can generate methanol with a remarkable Faradaic efficiency over $40\\%$ [16] \n\nSuch flexible tunability of multi-electron reaction pathways reveals great opportunities of SACs in achieving distinctive electrocatalysis performance.[17-18] Although significant efforts have been devoted to design and fabricate different kinds of SACs for a wide variety of reactions,[1,19-21] less attention has been paid to tailor the local coordination structures other than conventional metal- $\\mathsf{\\Pi}\\cdot\\mathsf{N}_{x-\\mathsf{C}}$ moieties.[22-23] It is hindered due to the limited synthesis approach for targeted SACs with well-designed and tunable structures.[2] Besides, it is still difficult to unambiguously identify the exact local environment of SACs, thus plaguing the establishment of a definitive correlation between structure and performance.[4] Moreover, isolated metal atoms are inclined to migrate and agglomerate during synthesis or reaction. It is highly challenging to synthesize single atomic sites with high metal loading $(>10\\ \\mathsf{w t\\%})$ and large-scale production,[2, 6, 24-25] which is essential to the practical application. Therefore, the next breakthrough in SAC-based electrocatalysis is regarded to rely on the facile tailor of local coordination structures with high metal loading, and comprehensive understanding of the structureproperty relation.[26] \n\nHerein, we successfully fabricated a new kind of Mo SACs by MgO-templated pyrolysis of mixed precursors. The metal loading can be higher than $10\\mathrm{\\Omega}\\mathrm{wt\\%}$ due to the synergistic glucosechelating and defect-trapping effects. The Mo single atoms with a unique oxygen and sulfur dual coordination were unambiguously identified by advanced microscopy and spectroscopy techniques. This material was demonstrated to exhibit distinct ORR performance via $2\\mathsf{e}^{-}$ pathway with a ${\\sf H}_{2}{\\sf O}_{2}$ selectivity higher than $95\\%$ . The Mo single atom complex was confirmed as the activity origin by a series of electrochemical tests. Theoretical calculation was further employed to study the fundamental structure-property relation based on several models,which revealed the crucial role of the local coordination structure in SACs for targeted electrocatalytic performance. \n\nThe high-loading Mo single atoms were in situ anchored onto porous oxygen, sulfur-doped graphene (OsG) frameworks during the MgO-templated pyrolysis of a C/S/Mo precursor mixture, followed by a leaching treatment to remove the MgO templates and possible Mo-based nanoparticles. The carbon precursor glucose can adequately chelate metal precursors in solution and thus well isolate them before pyrolysis.[6, 27] For comparison, a series of samples with different Mo contents were also synthesized under otherwise identical conditions with different amount of Mo precursors. They are denoted as OsG, Mo/OSGL,Mo/OsG-M and Mo/OSG-H, respectively (see experimental details in the Supporting Information). Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images show that all four samples exhibit similar structures (Figure 1a, Figure S1-S3). The sheet-like graphene framework is highly porous and constructed by curved ultrathin graphene layers owing to its self-limiting growth behavior on MgO templates (Figure 1b).[28] There are no obvious nanoparticles observed in TEM images (Figure 1a, Figure S3) and no characteristic peaks in X-ray diffraction (XRD) and Raman spectra corresponding to any Mo species in $\\mathsf{M o}_{1}/\\mathsf{O S G}$ samples (Figure S4), suggesting the thorough removal of any nanoparticles by harsh acid treatment. \n\n![](images/b912c5cd892e221405921907c11caaf5569502d649e459a3eea382985217482c.jpg) \nFigure 1. Structural characterization of Mo/OSG-H sample. a,b)TEM images of Mo/OSG-H.c) HAADF-STEM image of Mo/OSG-H with circles marking some single Mo atoms. The inset linear profile represents the intensity across four Mo atoms marked by the arrow.d)Pseudo-color surface plot corresponding to the HAADF-STEM image. \n\nTo clearly examine the spatial distribution of Mo in atomic level, high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) analysis was conducted. As shown in Figure 1c, numerous bright spots in a single-atom size $(\\sim1.2\\tt{A}$ inset of Figure 1c) can be clearly observed and identified as isolated Mo atoms in $_{M O_{1}/\\mathsf{O S G}-H}$ .Figure 1d presents the pseudo-color surface plot derived from the HAADF-STEM image in Figure 1c. The isolated blue peaks indicate the single Mo atoms more vividly and unambiguously, and the irregular red regions represent the mesopores in the graphene framework. It is noteworthy that the Mo single atoms preferentially decorate along the defective edges of mesopores in graphene (Figure 1d), implying the defect effect on trapping and stabilizing single metal atoms.[29-30] More HAADF-STEM images were captured from different regions to confirm the uniformity of Mo isolation, as provided in Figure S5. The isolated bright spots can also be observed in Mo/OSG-M and Mo/OSG-L, while the number is declined with the decrease of Mo loading (Figure S6). The Moloading content determined by inductively coupled plasma optical emission spectroscopy (ICP-OES) is 13.47 wt%, $6.89~\\mathrm{wt\\%}$ and $0.21~\\mathrm{wt\\%}$ for Mo/OsG-H, M, and L, respectively. \n\nThe electronic structure evolution after Mo decoration was further studied by Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and synchrotron-based $\\mathsf{X}$ -ray absorption spectroscopy (XAS). After the loading of Mo atoms, the characteristic D and G bands in Raman spectra broaden significantly and the G band displays an obvious blue-shift $(\\sim22$ $\\mathsf{c m}^{-1},$ ,with an increased $\\mathsf{I}_{\\mathsf{D}}/\\mathsf{I}_{\\mathsf{G}}$ ratio from 0.33 for OSG to 1.28 for $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ (Figure S7 and S8). In the C K-edge spectra for $_{M O_{1}/\\mathsf{O S G-H}}$ (Figure S9), the intensity of the peak at $285.4~\\mathsf{e V}$ assigned to the $\\pi^{\\star}$ excitation of $c=c$ (ring) decreases obviously, while that at $288.4\\:\\mathsf{e V}$ derived from the $\\uppi^{\\star}$ excitation of C-O/S-C increases obviously. These results indicate that the incorporation of Mo atoms can significantly alter the electronic structure and intrinsic disorder of the graphene matrix. The valence state of Mo in $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ was investigated by XPS, and the Mo 3d spectrum is best fitted by the coexistence of $86\\%$ ${M O}^{6+}$ and $14\\%$ ${\\mathsf{M o}}^{4+}$ (Figure 2a), in consistence with that for previously reported atomic ${\\mathsf{M o}}{\\mathsf{-N}}_{x}{\\mathsf{-C}}$ catalysts.[31] It is notable that in the high-resolution O 1s and S 2p spectra, an obvious peak corresponding to Mo-O and Mo-S bond is observed respectively (Figure 2b and 2c). \n\nThe chemical state and local environment of Mo was further investigated by the X-ray adsorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectra. As shown in Figure 2d and Figure S10, the linear combination fitting of Mo K-edge position of $_{M\\circ_{1}/\\mathsf{O S G}-H}$ reveals about $80.2\\%$ of ${M O}^{6+}$ $(M O O_{3})$ and $19.8\\%$ of ${\\mathsf{M o}}^{4+}$ $(\\mathsf{M o S}_{2})$ ,not far from the XPS results. In Figure 2e, the Fourier transform (FT) EXAFS spectrum of $M O_{1}/\\mathrm{OSG-H}$ shows that the main peak locates around $1.2\\tt{A}$ with small shoulders within $1.8{\\sim}3.2\\mathrm{~\\AA}$ .To assign the above peaks, the wavelet transform (WT) EXAFS was carried outfor the $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ sample as well as the standards (Figure 2f). Referring to the WT-EXAFS feature of $N a_{2}M o O_{4}$ , the peak at ${\\sim}1.2\\mathsf{A}$ on $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ could be assigned to the Mo-O bond. Two additional weak maxima are observed at (2.0 A,5.1 $\\mathbb{A}^{-1}$ )and (2.7A, $9.3\\mathring{\\mathsf{A}}^{-1}$ on $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ ,which should result from the back-scattering from the relatively light and heavy atoms, respectively.[32-3] Comparing with the WT-EXAFS features on ${\\mathsf{M o S}}_{2}$ ,i.e.,Mo-S bond $(1.9\\mathsf{A},6.7\\mathsf{A}^{-1})$ )and Mo-Mo bond $(2.8\\mathbb{A}$ $9.1\\mathring{\\mathsf{A}}^{-1},$ , the two weak maxima are most likely correlated with the Mo-S bond and Mo-(S)-Mo bond, consistent with the XPS analyses.Moreover, the absence of the corresponding feature of the Mo-Mo bond (Mo foil: $(2.5\\mathbb{A},8.1\\mathbb{A}^{-1})_{.}^{}$ )further validates the atomic dispersion of Mo on the graphene framework. In what follows, EXAFS fittings with the Mo- $\\phantom{+}O_{3}S\\ –C$ and mixture $(M O-O_{4}-$ C and ${\\mathsf{M o S}}_{2}$ ) models are attempted to obtain a deeper insight into the local coordination environment, whereas neither of them gives a reasonable fitting result (Figures S11 and Table S1). It is most likely due to the heterogeneity of the local coordination structures with such a high Mo loading amount $(>10\\ \\mathrm{wt\\%})$ ,which wouldcomplicatetheEXAFSfitting.However,the aforementioned WT-EXAFS results have indicated that the Mo atoms in $_{M O_{1}/\\mathsf{O S G-H}}$ should be atomically dispersed on the oxygen, sulfur-doped graphene framework and be very likely coordinated in a mixture of Mo-O and Mo-S moieties. \n\n![](images/a3de9c6d74018d16c9f6146d74a3a7ffad7fb12585ddd982070054be11648d94.jpg) \nFigure 2. Spectroscopic features of $_{M O_{1}/\\mathsf{O S G-H}}$ :a)High-resolution Mo 3d, b) O 1s and c) S 2p XPS spectra of $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ and OSG. d) XANES and e) FTEXAFS curves of the Mo K edge.f)WT-EXAFS of Mo/OSG-H, ${\\mathsf{M o S}}_{2}$ $N a_{2}M O O_{4}$ and Mo foil. \n\nCompared to various SACs reported so far, the as-fabricated $_{\\mathsf{M o}_{1}/\\mathsf{O S G}}$ material possess distinctive metal center (Mo) and coordination environment (O, S). The derived unique structures and resulting electronic states provide new opportunities to tune the activity and selectivity in electrocatalysis. The ORR performance was evaluated in $\\mathsf{O}_{2}$ -saturated $0.10\\mathrm{~M~}\\mathsf{K O H}$ using the rotating ring-disk electrode (RRDE) technique with a catalyst loading of $0.10~{\\mathsf{m g}}~{\\mathsf{c m}}^{-2}$ . All potentials are calibrated to a reversible hydrogen electrode (RHE) and the linear scan voltammogram (LSV) profiles were obtained by subtracting the capacitive current in ${\\sf N}_{2}$ -saturated electrolyte from the $\\O_{2}$ , saturated ORR current (Figure S12a). As displayed in Figure 3a, the $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ delivers a high onset potential $(\\mathord{\\sim}0.78\\lor$ vs.RHE for $-0.1\\mathsf{m A c m^{-2}}$ ) and large diffusion-limiting disk current density $(-2.78\\mathsf{m A c m}^{-2}$ at $0.30\\mathrm{V}$ ) approaching the theoretical limit for $2\\mathsf{e}^{-}$ ORR. It also exhibits fast ORR kinetics with a low Tafel slope of $54.7~\\mathsf{m V}~\\mathsf{d e c}^{-1}$ (Figure S12b). The calculated ${\\sf H}_{2}{\\sf O}_{2}$ selectivity of $\\mathsf{M o}_{1}/\\mathsf{O S G}\\cdot\\mathsf{H}$ is larger than $95\\%$ and the electron transfer number is around 2.1 for a wide range of potential (Figure 3b), revealing a highly selective $2\\mathsf{e}^{-}$ pathway. This selectivity is superior to most reported catalysts in alkaline such as atomic $F e{\\mathrm{-}}0_{x}{\\mathrm{-}}\\mathsf{C}\\left(\\mathsf{-}95\\%\\right)$ [13] edge site-rich nanocarbon $(90-95\\%)$ [34] oxidized carbon nanotube $(\\sim90\\%)$ ,[35] B-C-N material $(80{\\sim}90\\%)$ [36] and atomic Co$\\mathsf{N}_{x-\\mathsf{C}}$ 1 $(80-90\\%$ ).[37] Contrastively, the ${\\sf H}_{2}{\\sf O}_{2}$ selectivity of OSG is only $35\\%$ with a much larger electron transfer number of 3.3, suggesting the crucial contribution of Mo single atoms towards ${\\sf H}_{2}{\\sf O}_{2}$ generation. \n\nThe excellent electrocatalytic stability of $_{M O_{1}/\\mathsf{O S G-H}}$ was also demonstrated by the chronoamperometric test at a constant disk potential of 0.45 V vs. RHE (Figure 3c). More than $91\\%$ of the initial disk current can be retained after a prolonged operation of $^\\textrm{\\scriptsize8h}$ . The apparent ring current and ${\\sf H}_{2}{\\sf O}_{2}$ selectivity gradually increase after 2 h which should be ascribed to the accumulation of ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ products in the electrolyte (Figure 3c, Figure S13). After refreshing the electrolyte, the LSV curve and high ${\\sf H}_{2}{\\sf O}_{2}$ selectivity over $94\\%$ are indeed recovered (Figure 3a). Given the activity degradation but selectivity improvement of OSG after the prolonged test (Figure S14), the gradual disk current degradation of $_{M O_{1}/\\mathsf{O S G-H}}$ can be attributed to the deterioration of the relatively unstable $4\\mathsf{e}^{-}$ -selective sites (such as topological defects) rather than the $2\\tt e^{-}$ -selective Mo-O/S-C moieties in the oxidizing environment $(\\mathsf{H}_{2}\\mathsf{O}_{2})$ . Post-catalysis HAADF-STEM characterization also confirms the structural stability of Mo single atoms (Figure S15). Additionally, the electrochemical ${\\sf H}_{2}{\\sf O}_{2}$ reduction reaction $(\\mathsf{H}_{2}\\mathsf{O}_{2}\\mathsf{R}\\mathsf{R})$ activity was evaluated in $\\mathsf{N}_{2}\\mathsf{-}$ saturated 0.10 M KOH containing $10~\\mathsf{m M}$ ${\\sf H}_{2}{\\sf O}_{2}$ .As shown in Figure 3d, the $H_{2}O_{2}R R$ current density of $_{M O_{1}/\\mathsf{O S G-H}}$ is less than $-0.1\\mathsf{m A c m}^{-2}$ when the potential is more positive than $0.40\\mathrm{V}$ vs. RHE. It is similar to that of OsG, revealing poor activity towards ${\\sf H}_{2}{\\sf O}_{2}$ reduction on the Mo-O/S-C active sites. Consequently, the $_{M O_{1}/\\mathsf{O S G-H}}$ catalyst with high-loading Mo single atoms is confirmed as an excellent candidate for $2\\mathsf{e}^{-}$ ORR towards ${\\sf H}_{2}{\\sf O}_{2}$ electrosynthesis owing to its high ORR activity $(\\sim-3\\mathsf{m A}\\mathsf{c m}^{-2},$ 。, high ${\\sf H}_{2}{\\sf O}_{2}$ selectivity $(>95\\%)$ , low $H_{2}O_{2}R R$ activity( $<-0.1$ mA cm 2), and excellent stability in a wide operating potential range from $0.40\\mathrm{V}$ to $0.60\\mathrm{V}$ vs. RHE (Figure 3d). \n\n![](images/5e9b728d844385b47f2ef65ebe7767d2e334242b88467a8ba17209e0a51dbba9.jpg) \nFigure 3. Electrocatalytic performance of $_{M O_{1}/\\mathsf{O S G-H}}$ samplefor $2\\mathsf{e}^{-}$ ORR.a) ORR disk current density $(j_{\\mathrm{disk}})$ together with the ring currents $({j_{\\mathrm{{ring}}}})$ at a fixed potential of $1.20\\mathrm{V}$ vs.RHE.The dash line presents the LSV curve after longterm test and refreshing the electrolyte.b) Calculated electron transfer number (n) and ${\\sf H}_{2}{\\sf O}_{2}$ selectivity $(H_{2}O_{2}\\%)$ . c) Stability measurement of $_{M O_{1}/\\mathsf{O S G}-H}$ at a fixed disk potential of $0.45\\mathrm{\\vee}$ vs.RHE.The current densities are calculated based on the area of disk electrode.d) LSV curves of ${\\sf H}_{2}{\\sf O}_{2}$ reduction reaction recordedin ${\\sf N}_{2}$ -saturated $0.10~\\mathsf{M}$ KOH containing 10 mM ${\\sf H}_{2}{\\sf O}_{2}$ e)ORR disk current density together with the ring currents for $_{M O_{1}/\\mathsf{O S G-H}}$ recorded in $\\mathsf{O}_{2}$ , saturated electrolytes of different pH values.f)Relationship between ${\\sf H}_{2}{\\sf O}_{2}$ selectivity and the Mo content determined by ICP-OES. \n\nThe ORR kinetics and selectivity of $\\mathsf{M o}_{1}/\\mathsf{O S G}$ catalysts were further investigated in electrolytes of different pH values. As shown in Figure 3e, the LSV curves exhibit similar diffusionlimiting disk current densities, gradually increased overpotentials and decreased ring currents as the pH value changes from 13.2 to 8.7. The calculated Tafel slopes in the low current density region are $54.7~\\mathrm{mV}~\\mathrm{dec}^{-1}$ in ${\\mathsf{p H}}13.2$ , $68.1~\\mathsf{m V}~\\mathsf{d e c}^{-1}$ in $\\mathsf{p H}10.9$ and $69.4~\\mathsf{m V}\\mathsf{d e c}^{-1}$ in ${\\mathsf{p H}}8.7$ ,respectively (Figure S16). Besides, the ${\\sf H}_{2}{\\sf O}_{2}$ selectivity gradually decreases from $95\\pm1\\%$ to $86\\pm4\\%$ and to $77\\pm3\\%$ when the electrolyte changes from alkaline to neutral (Figure 3f). The pH-dependent selectivity degradation is consistent with other reports,[12,35] which can be ascribed to the higher working electrode potential range in lower pH values that decreases the possibility of ${\\sf H}_{2}{\\sf O}_{2}$ (or $\\mathsf{O O H^{-}},$ )desorption from catalyst (Figure S17).[38] The activity and selectivity of ORR was also evaluated under acidic condition (O.o5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}.$ )in a practical point of view[39-40] As shown in Figure S18, the ${\\sf H}_{2}{\\sf O}_{2}$ selectivity is achieved around $62\\%$ with a large overpotential and limited activity. The ORR performance in acid is expected to be further improved by optimizing the mesoporous structure of the graphene framework, heteroatom doping, and local coordination structures of metal sites.[12,35, 41-47] \n\nTo confirm the role of atomic Mo-O/S-C sites, the ORR performance of $\\mathsf{M o}_{1}/\\mathsf{O S G}$ samples with different Mo loading was also studied. All samples deliver similar onset potentials and diffusion-limiting disk current densities, while the ring current varies obviously (Figure S19).More specifically, the calculated ${\\sf H}_{2}{\\sf O}_{2}$ selectivity is positively correlated to the Mo content determined by ICP-OES (Figure 3f), increasing from $35\\pm0.7\\%$ , $59\\pm1.5\\%$ , $78\\pm1\\%$ , to $95\\pm1\\%$ for OSG, $\\mathsf{M o}_{1}/\\mathsf{O S G}\\mathrm{-}\\mathsf{L}$ , ${\\mathsf{M o}}_{1}/{\\mathsf{O S G-}}$ M, and $_{M O_{1}/\\mathsf{O S G}-H}$ ,respectively. The possible contribution from Mg species was rationally excluded due to the ultralow concentration of Mg $(<0.0086~\\mathrm{wt\\%})$ )determined by inductively coupled plasma mass spectroscopy (lCP-MS). The above experimental studies clearly verify that the atomically dispersed Mo-O/S-C sites are responsible for the highly active and selective $2\\mathsf{e}^{-}$ ORR pathway. \n\nTo further reveal the relation between electrocatalytic activity and local coordination structure of single metal atoms, density functional theory (DFT) calculations were performed on various Mo-O/S-C structures. According to the above characterization of experimentally synthesized samples, our models feature single atomic Mo center with different coordination environments, which vary from pure O $(M{\\circ}{-}\\mathsf{O}_{4}{-}\\mathsf{C})$ )and pure S $(M_{}0-S_{4}-C)$ to O/S mixture $(\\mathsf{M o-O}_{3}\\mathsf{S-C})$ , as shown in Figure S20. On each of the models, four atoms surrounding metal doping position were initially selected as possible active sites, including Mo itself, a sulfur or oxygen atom, and two carbon atoms (from the five membered ring and six membered ring) as marked in Figure S20a. After geometry optimization, free energy diagrams were constructed to facilitate the identification of active sites. As shown in Figure 4a, at the reaction equilibrium potential of $2\\mathsf{e}^{-}$ ORR,Mo single atom supported by a local environment composed by pure oxygen $(M{\\circ}{-}\\mathsf{O}_{4}{-}\\mathsf{C})$ )shows a highly positive intermediate free energy $(0.74\\:\\mathrm{eV})$ . However, when a sulfur atom is introduced into the coordination environment, the critical ${\\mathsf{O O H}}^{\\star}$ adsorption is significantly enhanced $(0.35~\\mathsf{e V})$ ,indicating a much facilitated reaction thermodynamics based on microkinetic modelling method. As shown in Figure 4b, OOH\\* adsorbs on the carbon atom next to sulfur in the $_{\\mathsf{M o-O}_{3}\\mathsf{S}-\\mathsf{C}}$ structure. The distance between two oxygen atoms in ${\\mathsf{O O H}}^{\\star}$ is $1.49\\mathrm{~\\AA~}$ ,and is much elongated comparing to the original $_{0-0}$ distance (1.21 A) in $\\mathsf{O}_{2}$ Additionally, the bond length between oxygen from ${\\mathsf{O O H}}^{\\star}$ and active carbon center is $1.50\\mathsf{A}$ Electron charge difference analysis (Figure S21) shows electron depletion on Mo atom; this indicates when OOH\\* adsorption happens, electrons transfer from Mo atom to the adsorption location. Bader charge analysis shows that the Mo atom loses 0.86 electrons with adsorbed ${\\mathsf{O O H}}^{\\star}$ (comparing to the standalone Mo atom), suggesting the crucial contribution of Mo to the OOH\\* binding ability in the Mo- $\\phantom{+}O_{3}S\\ –C$ structure.When more sulfur is introduced into the coordination environment for Mo such as Mo- ${\\boldsymbol{\\cdot}}{\\mathsf{S}}_{4}$ -C structure,the $2\\mathsf{e}^{-}$ ORR process is further facilitated due to the enhanced reaction intermediate adsorption strength (0.14 eV for ${\\mathsf{O O H}}^{\\star}.$ . On such structure, as displayed in Figure 4c, the active site remains to be the carbon atom in a six membered ring adjacent to the sulfur dopant. Therefore, the DFT calculations unravel the critical role of the local coordination structure in SACs, which can significantly alter the electronic structure and adsorption behavior on active sites, leading to promising tunability in reaction activity and selectivity. \n\n![](images/7e873fed789e44491da1dbce2e0c7a0170ca49340d01f107a0febfa9e9c056a5.jpg) \nFigure 4. Reaction mechanism of single Mo atom supported by O, S-doped graphene substrate.a) Free energy diagram of $2\\mathsf{e}^{-}$ ORR on three investigated substrates at equilibrium potential of the reaction.b) Atomic configuration of OOH\\* adsorption on Mo-O3S-C.c) Atomic configuration of ${\\mathsf{O O H}}^{\\star}$ adsorption on $_{\\mathsf{M o-S}_{4}-\\mathsf{C}}$ \n\nIn summary, a new kind of Mo SACs with oxygen and sulfur dual coordination was facilely fabricated for highly selective $2\\mathsf{e}^{-}$ oxygen reduction to ${\\sf H}_{2}{\\sf O}_{2}$ . A high metal loading more than $10\\mathrm{wt\\%}$ was achieved due to the synergistic glucose-chelating and defecttrapping effects. The local structure and coordination environment of Mo single atoms was identified by HAADF-STEM and XANES characterizations at atomic level. By combining electrochemical tests and theoretical calculations, the Mo single atom complex was identified as the activity origin of the highly-selective $2\\mathsf{e}^{-}$ ORR pathway, and the specific local coordination (such as ${\\mathsf{M o}}{-}{\\mathsf{S}}_{4}{-}{\\mathsf{C}}$ and $_{M\\circ-\\mathsf{O}_{3}\\mathsf{S}-\\mathsf{C})}$ )was revealed to influence the adsorption behavior and reaction pathway significantly, resulting in high activity and selectivity. This work offers a general and versatile synthesis approach for well-defined SACs, and highlights the critical role of local coordination environments on electrocatalytic activity and selectivity. It is expected to open up a new avenue towards the further development of SACs and can be extended to other important multi-electron electrocatalysis systems, such as $\\mathsf{C O}_{2}$ reduction and ${\\sf N}_{2}$ reduction reactions. \n\n# Acknowledgements \n\nThis work was financially supported by the Australian Research Council (DP160104866,LP160100927, DP190103472 and FL170100154). XAS measurement was undertaken on the soft Xray beamline at Australian Synchrotron. XAFS measurements used the resources of 7-BM (QAS) of the National Synchrotron Light Source Il, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Brookhaven National Laboratory (Contract No. DE-SCoo12704). DFT computations within this research was undertaken with the support of resourcesand services from the National Computational Infrastructure (NCl) which is supported by the Australian Government, and Phoenix HPC from the University of Adelaide. The authors thank for the helpful discussion with Dr. Yao Zheng, Laiquan Li, Dr. Bin-Wei Zhang,Xin Liu, and Dazhi Yao. \n\n# Conflict of interest \n\nThe authors declare no conflict of interest. \n\nKeywords: single atom catalyst $\\cdot$ local coordination $\\cdot\\cdot$ oxygen reduction $\\cdot\\cdot$ selectivity·electrosynthesis \n\n[1] A.Q.Wang,J.Li,T.Zhang,Nat.Rev. Chem.2018,2,65-81. \n[2] J.Wang, Z. J.Li,Y.Wu,Y.D. Li,Adv. Mater. 2018,30,1801649. \n[3] Y. Jiao, Y. Zheng, P.Chen, M. Jaroniec, S.Z. Qiao, J. Am. Chem. Soc. 2017,139, 18093-18100. \n[4] H. L.Fei, J. C.Dong,Y. X.Feng, C.S.Alln, C. Z.Wan,B.Volosskiy, M.F.Li, Z.P. Zhao, Y. L.Wang, H.T. Sun, P.F.An, W.X.Chen, Z.Y. Guo, C. Lee, D. L. Chen, I. Shakir, M. J. Liu, T. D. Hu, Y. D. Li, A. I. Kirkland, X.F. Duan,Y. Huang, Nat. Catal.2018,1,63-72. \n[5] H.Z.Yang,L. Shang, Q.H. Zhang, R. Shi, G.I. N.Waterhouse, L. Gu, T.R.Zhang,Nat.Commun.2019, 10,4585. \n[6] L. Zhao, Y. Zhang, L.B.Huang, X. Z. Liu, Q. H. Zhang, C.He, Z.Y.Wu, L.J. Zhang, J. P.Wu, W.L.Yang, L.Gu, J.S.Hu, L. J.Wan, Nat. Commun.2019,10,1278. \n[7] L. Wang, M. X. Chen, Q. Q. Yan, S. L. Xu, S. Q.Chu, P.Chen, Y. Lin, H. W.Liang,Sci.Adv.2019,5,eaax2. \n[8] X. Liu, Y. Jiao, Y. Zheng, M. Jaroniec, S. Z. Qiao, J. Am. Chem. Soc. 2019,141,9664-9672. \n[9] E. Jung, H. Shin, B.-H. Lee, V.Efremov, S. Lee, H. S. Lee, J. Kim, W. Hooch Antink, S. Park, K.-S. Lee, S.-P. Cho, J. S. Yoo, Y.-E. Sung, T. Hyeon,Nat.Mater.2020,doi: 10.1038/s41563-019-0571-5. \n[10] Y. J. Chen, S.F. Ji, Y. G.Wang, J. C. Dong, W. X. Chen, Z. Li, R. A. Shen,L.R. Zheng, Z.B. Zhuang, D. S. Wang, Y. D. Li, Angew. Chem. Int. Ed.2017,56,6937-6941. \n[11] Z. Zhang, J. Sun,F.Wang,L.Dai, Angew. Chem.Int.Ed.2018,57, 9038-9043. \n[12] Y.Y.Sun, L. Silvioli,N.R. Sahraie,W. Ju, J. K.Li, A. Zitolo, S.Li, A. Bagger, L. Arnarson, X.L. Wang, T. Moeller, D. Bernsmeier, J. Rossmeisl,F.Jaouen,P.Strasser, J.Am. Chem.Soc.2019,141,12372- 12381. \n[13] K. Jiang, S.Back, A. J.Akey, C. Xia, Y.F. Hu, W.T. Liang,D.Schaak, E. Stavitski, J. K. Norskov, S. Siahrostami, H. T. Wang, Nat. Commun. 2019,10,3997. \n[14] Y. Cheng, S. Yang, S. P. Jiang, S. Wang, Small Methods 2019,3, 1800440. \n[15] S. Liu, H. B. Yang, S.-F. Hung, J. Ding, W. Cai, L. Liu, J. Gao, X. Li, X. Ren, Z.Kuang,Y. Huang, T. Zhang,B. Liu, Angew. Chem. Int. Ed.2020, 59,798-803. \n[16] Y.Wu, Z. Jiang,X. Lu,Y. Liang, H.Wang,Nature 2019,575,639-642. \n[17] A.R.Singh, B.A. Rohr, J.A. Schwalbe, M. Cargnello, K. Chan, T.F. Jaramillo, I. Chorkendorff, J. K. Norskov, ACS Catal. 2017, 7, 706-709. \n[18] S.Yang, A. Verdaguer-Casadevall, L. Arnarson, L. Silvio,V. Colic,R. Frydendal, J. Rossmeisl, I. Chorkendorff, I. E. L. Stephens, ACS Catal. 2018,8, 4064-4081. \n[19] C. Z. Zhu, S.F. Fu, Q. R. Shi, D. Du, Y. H. Lin, Angew. Chem. Int. Ed. 2017,56,13944-13960. \n[20] B.W. Zhang, Y. X. Wang, S. L.Chou, H. K. Liu, S. X. Dou, Small Methods 2019,3,1800497. \n[21] H. Fei, J. Dong, D.Chen, T. Hu, X. Duan, I. Shakir, Y. Huang, X. Duan, Chem. Soc. Rev. 2019, 48, 5207-5241. \n[22] J. Zhang, Y. Zhao, C. Chen, Y. C. Huang, C. L. Dong, C. J. Chen, R. S. Liu, C. Wang, K. Yan, Y. Li, G.Wang, J. Am. Chem. Soc. 2019,141, 20118-20126. \n[23] K.Yuan, D.F.Lutzenkirchen-Hecht, L.Li, L. Shuai,Y. Li, R.Cao,M. Qiu, X. Zhuang,Y.Chen,M.K.H.Leung,U.Scherf,J.Am.Chem.Soc.2020, 142,2404-2414. \n[24] J.Wu, L.Xiong,B.Zhao,M.Liu,L.Huang,Small Methods,2020,4, 1900540. \n[25] J.Wu, H. Zhou, Q. Li, M. Chen, J.Wan, N. Zhang, L. Xiong, S.Li, B.Y. Xia,G.Feng,M. Liu, L.Huang,Adv.Energy Mater. 2019, 9,1900149. \n[26] Y. J. Chen, S.F. Ji, C.Chen, Q.Peng, D. S.Wang,Y. D. Li, Joule 2018, 2,1242-1264. \n[27] C.Tang,B.Wang,H.F.Wang, Q.Zhang,Adv. Mater.2017, 29,1703185. \n[28] C.Tang,H.F.Wang,J.Q.Huang,W.Qian,F.Wei,S.Z.Qiao, Q.Zhang, Electrochem.Energy Rev.2019,2,332-371. \n[29] Y.Q.Zhang, L. Guo, L. Tao, Y.B. Lu, S.Y.Wang, Small Methods 2019, 3,1800406. \n[30] L. Z. Zhang,Y. Jia, G. P.Gao, X. C.Yan, N. Chen, J. Chen, M.T. Soo, B. Wood, D. J.Yang, A. J. Du, X. D. Yao, Chem 2018, 4, 285-297. \n[31] L. L. Han, X. J. Liu, J. P.Chen, R. Q.Lin, H. X. Liu, F. Lu, S.Bak, Z. X. Liang,S. Z.Zhao, E. Stavitski, J. Luo, R. R.Adzic, H. L.L. Xin, Angew. Chem. Int.Ed.2019, 58,2321-2325. \n[32] H.Funke,M.Chukalina,A. Rossberg, Phys. Scripta.20o5,T115,232- 234. \n[33] H.Funke,A. C.Scheinost, M. Chukalina, Phys. Rev. B 2005, 71, 094110. \n[34] Y.J. Sa, J.H.Kim,S.H. Joo,Angew.Chem. Int. Ed.2019,58,1100- 1105. \n[35] Z.Y. Lu, G. X.Chen, S.Siahrostami, Z.H.Chen, K. Liu, J. Xie, L. Liao, T. Wu, D. C. Lin, Y. Y. Liu, T. F. Jaramillo, J. K. Norskov, Y. Cui, Nat. Catal. 2018, 1, 156-162. \n[36] S.C.Chen, Z. H. Chen, S. Siahrostami, D. Higgins, D. Nordlund, D. Sokaras, T. R. Kim, Y. Z. Liu, X. Z. Yan, E. Nilsson, R. Sinclair, J. K. Norskov,T.F.Jaramillo,Z.N.Bao, J.Am.Chem.Soc.2018,140,7851- 7859. \n[37] B. Q.Li,C.X. Zhao,J.N.Liu, Q.Zhang,Adv.Mater.2019,31,1808173. \n[38] N.Ramaswamy, S.Mukerjee,J. Phys. Chem. C 2011,115,18015- 18026. \n[39] S.Siahrostami,A. Verdaguer-Casadevall,M.Karamad, D.Deiana,P. Malacrida, B.Wickman, M. Escudero-Escribano,E. A. Paoli,R. Frydendal,T.W. Hansen,I. Chorkendorff, I. E. L. Stephens,J. Rossmeisl, Nat.Mater.2013,12,1137-1143. \n[40] H.Y.Sheng, E. D. Hermes, X.H.Yang, D.W.Ying, A.N. Janes, W.J. Li, J.R.Schmidt, S. Jin,ACS Catal. 2019,9,8433-8442. \n[41] T.P.Fellinger, F. Hasche, P. Strasser, M.Antonietti, J. Am. Chem. Soc. 2012, 134, 4072-4075. \n[42] J.Park,Y.Nabae,T.Hayakawa,M. A.Kakimoto,ACS Catal.2014,4, 3749-3754. \n[43] Y. M. Liu, X.Quan, X.F.Fan, H.Wang, S.Chen, Angew. Chem. Int. Ed. 2015,54,6837-6841. \n[44] Y.Y. Sun,I. Sinev, W. Ju, A. Bergmann, S. Dresp, S. Kuhl, C. Spori, H. Schmies, H. Wang, D. Bernsmeier, B. Paul, R. Schmack, R. Kraehnert, B. Roldan Cuenya, P.Strasser, ACS Catal. 2018, 8, 2844-2856. \n[45] J. Gao, H.b.Yang,X. Huang, S.-F.Hung, W.Cai, C. Jia, S. Miao, H. M. Chen, X. Yang, Y. Huang, T. Zhang, B. Liu, Chem 2020,doi: 10.1016/j.chempr.2019.12.008. \n[46] D.Iglesias,A. Giuliani, M.Melchionna, S.Marchesan,A.Criado, L.Nasi, M.Bevilacqua,C.Tavagnacco,F.Vizza,M.Prato, P.Fornasiero,Chem 2018,4,106-123. \n[47] C.H.Choi, M. Kim,H.C.Kwon, S. J. Cho, S.Yun, H. T. Kim, K. J. J. Mayrhofer,H.Kim,M.Choi,Nat. Commun.2016,7,10922. \n\n# Entry for the Table of Contents \n\n![](images/037404e64aa8f5a1ca2880849e7711419dbeb7fbb8118bd0a793e81e707ffe1b.jpg) \n\nCoordination tunes selectivity:Mosingle-atom catalyst(SAC)with a uniqueO,S-dual coodination exhibited outstanding ${\\sf H}_{2}{\\sf O}_{2}$ selectivity above $95\\%$ in oxygen reduction reaction.Both electrochemicaltests and theoretical calculations revealed the criticalrole of thecodinatinstructureinSACs,highlightingnewpptuniestounetheactivityandselectivityinmultielectronelectcatalysis. \n\n![](images/33e5e9e4d0bd1540691e8d9b28710916bf921670293288ef0f33f2fee76f259f.jpg) \n\nThis article is protected by copyright. All rights reserved. " + }, + { + "id": "10.1038_s41467-020-15078-2", + "DOI": "10.1038/s41467-020-15078-2", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-15078-2", + "Relative Dir Path": "mds/10.1038_s41467-020-15078-2", + "Article Title": "Ultra-high open-circuit voltage of tin perovskite solar cells via an electron transporting layer design", + "Authors": "Jiang, XY; Wang, F; Wei, Q; Li, HS; Shang, YQ; Zhou, WJ; Wang, C; Cheng, PH; Chen, Q; Chen, LW; Ning, ZJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Tin perovskite is rising as a promising candidate to address the toxicity and theoretical efficiency limitation of lead perovskite. However, the voltage and efficiency of tin perovskite solar cells are much lower than lead counterparts. Herein, indene-C-60 bisadduct with higher energy level is utilized as an electron transporting material for tin perovskite solar cells. It suppresses carrier concentration increase caused by remote doping, which significantly reduces interface carriers recombination. Moreover, indene-C-60 bisadduct increases the maximum attainable photovoltage of the device. As a result, the use of indene-C-60 bisadduct brings unprecedentedly high voltage of 0.94 V, which is over 50% higher than that of 0.6 V for device based on [6,6]-phenyl-C61-butyric acid methyl ester. The device shows a record power conversion efficiency of 12.4% reproduced in an accredited independent photovoltaic testing lab.", + "Times Cited, WoS Core": 498, + "Times Cited, All Databases": 510, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000549162600022", + "Markdown": "# Ultra-high open-circuit voltage of tin perovskite solar cells via an electron transporting layer design \n\nXianyuan Jiang 1,3, Fei Wang 1,3, Qi Wei 1, Hansheng Li 1, Yuequn Shang $\\textcircled{1}$ 1, Wenjia Zhou $\\textcircled{1}$ 1, Cheng Wang1,2, Peihong Cheng 1, Qi Chen $\\textcircled{1}$ 2, Liwei Chen $\\textcircled{1}$ 2 & Zhijun Ning1✉ \n\nTin perovskite is rising as a promising candidate to address the toxicity and theoretical efficiency limitation of lead perovskite. However, the voltage and efficiency of tin perovskite solar cells are much lower than lead counterparts. Herein, indene- $C_{60}$ bisadduct with higher energy level is utilized as an electron transporting material for tin perovskite solar cells. It suppresses carrier concentration increase caused by remote doping, which significantly reduces interface carriers recombination. Moreover, indene- ${\\cdot}C_{60}$ bisadduct increases the maximum attainable photovoltage of the device. As a result, the use of indene- $C_{60}$ bisadduct brings unprecedentedly high voltage of $0.94\\mathsf{V}.$ , which is over $50\\%$ higher than that of $0.6\\mathsf{V}$ for device based on [6,6]-phenyl-C61-butyric acid methyl ester. The device shows a record power conversion efficiency of $12.4\\%$ reproduced in an accredited independent photovoltaic testing lab. \n\nalide perovskites are rising as star materials for next一 generation solar cells. However, the state of the art lead perovskite still needs to be upgraded since: firstly, the heavy metal character of lead may cause an environmental concern1,2; secondly, according to Shockley–Queisser limitation, the highest efficiency of lead perovskite is $<31\\%$ due to its large bandgap $(1.55\\mathrm{eV})^{3}$ . The development of alternative perovskite materials is therefore highly desirable. Tin perovskite is regarded as an ideal candidate due to its narrow bandgap and environmental benign character4. Up to now, tin perovskite solar cell (PSC) demonstrates the highest efficiency among all kinds of lead-free perovskites5. \n\nDespite the rapid development of tin PSCs, the efficiency is much lower than lead perovskite nowadays. One critical factor is the extremely low open-circuit voltage. High defect density in the film is one important factor contributing to the low voltage6. Some methods are implemented to reduce defect density of tin perovskite, e.g., addition of reductive additives7–9, and perovskite dimensionality manipulation10–12, which increased the voltage of the device from $0.3\\mathrm{V}$ to $0.6\\mathrm{V}$ (ref. 13). However, compared to its bandgap $(1.35\\mathrm{eV})$ , the voltage loss of tin PSCs is still over $0.7\\mathrm{V}$ , much larger than that of lead perovskite. It is highly desirable to clarify the mechanism for the low voltage of tin PSCs and find solutions. \n\nAnother possible factor for the low voltage of tin PSCs could be the deep Lowest Unoccupied Molecular Orbital (LUMO) energy level of electron transporting layers (ETLs), e.g., [6,6]-phenyl- $C_{61}$ -butyric acid methyl ester (PCBM)14,15 and buckminsterfullerene $(\\mathrm{C}_{60})^{16-18}$ , which limited the maximum attainable photovoltage19. \n\nHere, we introduce indene- $C_{60}$ bisadduct (ICBA) as ETL for tin PSCs to replace the generally used PCBM. ICBA with shallower energy level brings a larger maximum attainable voltage and it suppresses iodide remote doping that reduces interface carriers recombination. As a result, the use of ICBA as ETL improves the voltage of the device to $0.94\\mathrm{V}$ , which is significantly higher than that of the device using PCBM as ETL $(0.6\\mathrm{V})$ . The device based on ICBA demonstrates an unprecedentedly high efficiency of $12.4\\%$ , which is almost $30\\%$ higher than the highest efficiency reported up to now20–22. Moreover, the device shows excellent shelf stability by maintaining $90\\%$ of the initial efficiency for over 3800 hours. This work clarifies the mechanism for the low voltage of tin PSCs, and presents a strategy to increase the voltage and efficiency of tin PSCs. \n\n# Results \n\nPerovskite film structure. Perovskite films are prepared using a typical anti-solvent method via a one-step process (details can be found in Methods section). We tune the concentration of PEA $\\mathrm{(PEA=C_{6}H_{5}C H_{2}C H_{2}N H_{3}^{+})}$ in precursors to get the $\\mathrm{PEA}_{x}$ $\\mathrm{FA}_{1-x}\\mathrm{SnI}_{3}$ $\\mathrm{(FA=HC(NH_{2})_{2}+};$ perovskites (abbreviated as PEAx, $x=0$ and 15). Films are prepared on poly(3, 4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT)18 substrates to control the nucleation and orientation of perovskite. $\\mathrm{NH_{4}S C N}$ (SCN) is used as additive to modify perovskite film growth. \n\nWe characterized the crystal structure by X-ray diffraction (XRD). The diffraction peaks of the perovskite film with $\\mathrm{NH_{4}S C N}$ (PEA15-SCN) show a higher intensity (Fig. 1a) and a smaller fullwidth half-maximum (FWHM) value (Fig. 1b), indicating a larger domain size for PEA15-SCN film. \n\nWe then studied the microstructure of perovskite film by grazing-incidence wide-angle X-ray scattering (GIWAXS). The strong diffraction spot in 90 degree shows that PEA15-SCN film is perpendicularly grown on the substrate along [100] direction23,24 (Supplementary Figs. 2–4). Both films with and without SCN grown on PEDOT show similar diffraction spots from single layer and double layer structures at both small and large grazing-incidence angles (Supplementary Fig. 3). This is completely different from the image of hierarchy structure grown on $\\mathrm{NiO_{X}}$ substrate12. We conclude that low dimensional structures homogeneously distribute in the film, which can be ascribed to the higher binding energy of PEA and FA molecules on PEDOT substrate, as calculated by density functional theory (DFT) simulation (Supplementary Fig. 6, Supplementary Table 1). \n\nWe performed spectroscopy characterization to study the structure of the films further. The absorption edge of the film based on PEA15-SCN $(905\\mathrm{nm})$ is quite close to that of threedimensional (3D) structure PEA0 $(917\\mathrm{nm}$ ; Supplementary Fig. 7a), implying the presence of 3D-like structures in the film. In combination with GIWAXS measurement, it can be speculated that part of PEA molecules are consumed for constructing twodimensional (2D) and 2D-like structures, which are mixed with 3D structures in the film (Supplementary Fig. 8). The absorption spectrum of PEA15-SCN film demonstrates a lower Urbach energy of ${\\sim}65\\mathrm{meV}$ (Fig. 1c), which indicates the reduced defect concentration with the addition of $\\mathrm{NH_{4}S C N}$ (refs. 25,26). Scanning electron microscope (SEM) images of PEA15 and PEA15- SCN films are similar and both of them show smooth morphology (Fig. 1d). \n\nDevice structure design. We measured the energy levels of the perovskite films for device structure design. Based on ultraviolet photoelectron spectroscopy (UPS), the Fermi level and valence band minimum for PEA15-SCN perovskite film (Fig. 2a) are calculated to be $-4.52\\mathrm{eV}$ and $-5.08\\mathrm{eV}_{:}$ , respectively. Combining the optical bandgaps of $1.39\\mathrm{eV}$ for PEA15-SCN determined by Tauc plots (Supplementary Fig. 7b), the conduction band maximum of perovskite film is calculated to be $-3.69\\mathrm{eV}$ for PEA15- SCN (Fig. 2b). Considering the shallow conduction band position of tin perovskite, the typically used $\\operatorname{ETL},$ such as PCBM shows a large energy level offset due to its much deeper band position. Since the maximum attainable photovoltage is determined by the quasi-Fermi level splitting, $\\begin{array}{r}{\\bar{V}_{\\mathrm{OC}}=\\frac{1}{q}\\left(\\bar{E_{\\mathrm{Fn}}}-E_{\\mathrm{Fp}}\\right)}\\end{array}$ , the use of shallower energy level ETL could increase the $V_{\\mathrm{OC}}$ of the device27. Therefore, we used ICBA as ETL, since it has a LUMO level of $-3.74\\mathrm{eV}$ shallower than the commonly used PCBM of $-3.91\\mathrm{eV}$ (ref. 28). \n\nDevice performance. We fabricated the device based on PEA15- SCN films above using ICBA and PCBM as ETL, respectively. The device based on ICBA achieved a much-enhanced voltage up to $0.94\\mathrm{V}$ (Fig. 3a). The efficiency certified in an independent lab is up to $12.4\\%$ $\\prime_{S C}=0.94\\:\\mathrm{V}$ , $J_{\\mathrm{SC}}{=}17.4\\mathrm{mAcm}\\dot{^{-}}2$ , $\\mathrm{FF}=75\\%$ ; Table 1, Supplementary Fig. 9). This is ${\\sim}30\\%$ higher than the best value reported up to now20–22. In contrast, the device based on PCBM shows much worse efficiency of $7.7\\%$ (Fig. 3b, Supplementary Fig. 10), and the voltage is only $0.60\\mathrm{V}$ . The device based on ICBA shows a low hysteresis as the current density–voltage $\\left(J-V\\right)$ curves under reverse and forward scan overlapped well (Fig. 3b). The integrated photocurrent density $(17.3\\mathrm{\\:mA}\\mathrm{cm}^{-2}.$ ) obtaining from the external quantum efficiency (EQE) spectra of PEA15-SCN device (Fig. 3c) agrees closely with current density $(J_{\\mathrm{SC}})$ in the $J{-}V$ curves. Moreover, the device performance shows good reproducibility (Fig. 3d, Supplementary Fig. 11). \n\nWe then fabricated devices based on PEA15 and ICBA for comparison, which shows $V_{\\mathrm{OC}}$ of $0.78\\mathrm{V}$ , much smaller than that the film with SCN (Table 1). Despite the current density of the film is comparable to that based on PEA15-SCN, the overall efficiency of the device is only $10.1\\%$ . \n\n![](images/e66794e6a97f7b6f9e7208454c002e5c9fa1506d9a39cba2b949576ee727bde9.jpg) \nFig. 1 Perovskite film characterization. a XRD spectra of perovskite films and b the corresponding FWHM values of (100) peak. c The Urbach energy perovskite films. d SEM images of perovskite films. The scale bar is $1\\upmu\\mathrm{m}$ . \n\n![](images/1e654441a93abd090944afa5a686836a35b700c88b0661c631586eecf6bc6636.jpg) \nFig. 2 Band structure of tin PSCs. a UPS spectra of secondary electron cutoff and valence band of perovskite films. b Schematic illustration of energ levels. Dashed lines represent the quasi-Fermi level of ICBA $(E_{\\mathsf{F}\\mathsf{n}-1})$ , PCBM $(E_{\\mathsf{F}\\mathsf{n}-\\mathsf{P}})$ , and PEDOT $(E_{\\mathsf{F p}})$ . \n\nThe PEA15-SCN device shows good shelf stability: the encapsulated device maintained $90\\%$ of the initial performance for as long as 3800 hours (Fig. 3e). Steady-state power conversion efficiency (PCE) measurement was carried out to evaluate the operation stability of the device. The device showed stable efficiency at continuous operation at maximum power point for $150\\mathrm{s}$ (Fig. 3f). However, under longer time illumination, the efficiency decay slows, and the device loses $50\\%$ of its initial performance after continuous operation for over $300\\mathrm{{min}}$ under amplitude modulation (AM) 1.5 illumination (Supplementary Fig. 13). The efficiency decay might be ascribed to the ion migration or accumulation of carriers at the interface. \n\nDevice characterization. To clarify the mechanism for the muchenhanced voltage and performance of the device based on ICBA, we studied the interface recombination between perovskite and ETL. Firstly, scanning Kelvin probe microscopy (SKPM) was employed to analyze interfacial energy level alignment of perovskite/ETL interface (Fig. 4a, Supplementary Figs. 14 and 15)29. The surface potential of ICBA is $20\\mathrm{mV}$ higher than perovskite, indicating that the Fermi level of ICBA is $20\\mathrm{meV}$ higher than that of perovskite. Similarly, we deduced that the Fermi level of PCBM is ${\\sim}100\\mathrm{meV}$ higher than perovskite (Fig. 4a). Hence, it can be calculated that the Fermi level of PCBM is $80\\mathrm{meV}$ higher than that of ICBA. Considering that the LUMO level of PCBM is deeper than ICBA (Fig. 4b), the higher Fermi level of PCBM indicates that more states are occupied by electrons, i.e., it has higher electron density27. This can be attributed to remote doping from iodide, which can act as donor to inject electrons into ETL (ref. 30). In contrast, the shallow LUMO level of ICBA prohibits electron injection from iodide, giving rise to less electron density. The existence of iodide in ETL can be ascribed to ion migration in perovskite film30. \n\n![](images/4db933898ae7c9c0597aafb9fd1f5354425a317b82bfbbd971884f166590e0de.jpg) \nFig. 3 Photovoltaic performances of tin PSCs. a Cross-section SEM image of PEA15-SCN device. The scale bar is $200\\mathsf{n m}$ . b $J-V$ curves of the certified PEA15-SCN device with ICBA and champion device of PEA15-SCN film with PCBM. c EQE curve and integrated $J_{S C}$ of the certified PEA15-SCN device. d Histograms for PCE and $V_{\\mathsf{O C}}$ of PEA15-SCN device. e The stability of encapsulated PEA15-SCN device stored in ${\\sf N}_{2}$ atmosphere. f Stabilized power output for the PEA15-SCN device (at $\\phantom{0}{.81}\\veebar$ under simulated AM $1.56$ solar illumination at $100\\mathsf{m w c m}^{-2}$ . \n\n
Table 1 Summary of the best performance devices with ICBA.
DevicePCE (%)Voc (V)Jsc (mA cm-2)FF (%)
PEDOT/PEA15/ICBA10.10.78 0.6017.8 17.172
PEDOT/PEA15-SCN/ PCBM7.774
PEDOT/PEA15-SCN/ ICBA12.40.9417.475
\n\nThe high electron density of PCBM could aggravate interface carrier recombination with p-type tin perovskite $\\mathrm{\\bar{f}l m}^{31}$ . We hence performed time-resolved photoluminescence (TRPL) decay measurement to test the interface carriers recombination. The TRPL of different perovskite films shows a bi-exponential decay (Fig. 4c), including a fast component $(\\tau_{1})$ , and a slow component $(\\tau_{2})^{32}$ (Table 2). The fast component can be ascribed to the rapid carriers recombination across the interfaces of perovskite and transporting layer33. The perovskite film contacting PCBM shows a smaller $\\tau_{1:}$ , indicating faster carriers recombination at the interface. We used electroluminescence (EL) measurement under bias to estimate the interface recombination further34,35. As shown in Fig. 4d, PEA15-SCN device with ICBA shows an obvious EL peak, while extremely weak EL peak is observed for device with PCBM. The much higher EL intensity shows that the interface recombination is significantly suppressed, agreeing well with TRPL characterization. \n\nWe then used a model to quantitatively calculate the voltage loss due to interface carrier recombination. The $V_{\\mathrm{OC}}$ loss $(\\Delta V_{\\mathrm{OC}}^{\\mathrm{nrad}})$ of non-radiative decay at perovskite/ETL interface can be estimated by external radiative efficiency (ERE) from EL measurement based on the following equation36: \n\n$$\n\\Delta V_{\\mathrm{OC}}^{\\mathrm{nrad}}=\\frac{-k_{\\mathrm{B}}T}{q}\\mathrm{lnERE}\n$$ \n\nWhere ERE is the electroluminescent EQE of the device. Based on the ERE of PEA15 and PEA15-SCN (Supplementary Fig. 16), the $\\Delta V_{\\mathrm{OC}}^{\\mathrm{nrad}}$ are determined to be $417\\mathrm{mV}$ and $226\\mathrm{mV}$ for the device based on PCBM and ICBA, respectively. Hence, we conclude that interface recombination is another important factor that responsible for the low voltage of the device based on PCBM. \n\nTo investigate the function of the addition of $\\mathrm{NH_{4}S C N}$ in the film to device performances, we performed transient photovoltage (TPV) and transient photocurrent (TPC) measurements to test the density of defect states in the bandgap directly37 (Fig. 4e). The film with $\\mathrm{\\DeltaNH_{4}S C N}$ shows less density of defect states inside the bandgap, especially in the region close to the conduction band. We tested $V_{\\mathrm{OC}}$ versus illumination intensity curves (Fig. 4f) and found that slope for the device based on PEA15-SCN is smaller than that based on PEA15, indicating the decrease of recombination of the film. Furthermore, the low Urbach energy of PEA15- SCN film in absorption spectra indicates the decrease of defect density as well. The reduced defect density of the film can be ascribed to the increase of domain size that reduced the grain boundary of the film, as discussed above. The reduced density of defects of SCN-treated film brings increased voltage and efficiency of the device. \n\n![](images/df014c51962d9d5a458fe63e986746e077e0094533f73eb4f093369403bea78e.jpg) \nFig. 4 Recombination and defect density characterization. a Surface potential distribution of PEA15-SCN/PCBM and PEA15-SCN/ICBA from SKPM measurement. The insert images are AFM topography images for the corresponding samples. b The schematic diagrams of interface recombination for the two samples. c Time-resolved photoluminescence kinetics at $840\\mathsf{n m}$ for the ITO/PEDOT/perovskite/ETL films after encapsulation. d Electroluminescence spectra of perovskite films under bias voltage of $2\\mathsf{V}$ . e The density of states in the bandgap calculated from TPV and TPC. f $V_{\\mathrm{OC}}$ versus illumination intensity for the devices. \n\n# Discussion \n\nIn this work, we develop a device structure of tin PSCs using ICBA as ETL. The higher LUMO energy level of ICBA improves the maximum attainable voltage of the device and reduces the remote doping caused interface recombination. Furthermore, the use of $\\mathrm{N\\bar{H}_{4}S\\bar{C}N}$ as additive and PEDOT as hole transporting layer for perovskite growth reduces the defect density of the film. As a result, we are able to realize an unprecedentedly high voltage of $0.94\\mathrm{V}$ for tin PSCs. Finally, we achieve a certified PCE up to $12.4\\%$ , which is almost $30\\%$ higher than the highest efficiency reported. With the open-circuit voltage approaching its theoretic limitation, this work indicates a huge potential for efficiency improvement of tin PSCs. \n\n
Table 2 Decay time of PEA15-SCN film with ICBA and PCBM.
T (ns)T2 (ns)
ICBA 1.112.1
PCBM 0.252.2
\n\n# Methods \n\nDevice fabrication. $\\mathrm{SnI}_{2}$ , formamidinium iodide (FAI), phenethylammonium iodide (PEAI), and $\\mathrm{NiO_{X}}$ were prepared according to literatures12,13. N,N-dimethylformamide (DMF), dimethyl sulfoxide (DMSO), chlorobenzene, isopropyl alcohol, $\\mathrm{SnF}_{2}$ , and $\\mathrm{NH_{4}S C N}$ were purchased from Sigma-Aldrich. Cleaned indium tin oxide (ITO) glass was treated in an ultraviolet ozone (UVO) machine for $20\\mathrm{min}$ before fabrication. The PEDOT (Heraeus-Clevios P VP AI 4083) solution was spin coated onto ITO substrate at $6000\\mathrm{rpm}$ for $60\\mathrm{{s}}$ and then annealed at $140^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . A $0.8\\mathbf{M}$ perovskite precursor (PEAI:FAI $:\\mathrm{SnI}_{2};\\mathrm{SnF}_{2}=0.15{:}0.85{:}1{:}0.075)$ and with or without $\\mathrm{NH}_{4}\\mathrm{SCN}$ $5\\mathrm{mol\\%})$ ) were added in mixed solvent $\\mathrm{(DMF{:}D M S O=}$ $4{:}1\\mathrm{V}/\\mathrm{V})$ and stirred at $70^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . The precursor was spin coated at $1000\\mathrm{rpm}$ and $5000\\mathrm{rpm}$ for $10\\mathrm{{s}}$ and $^{30s,}$ respectively. And $600\\upmu\\mathrm{L}$ toluene (Sinopharm Chemical Reagent Co. Ltd., redistilled) was dropped during the second process at eighth second. The substrate was then annealed at $70^{\\circ}\\mathrm{{C}}$ for $10\\mathrm{min}$ . The films of PEA15 and PEA0 were made by the same procedure. A total of $18\\mathrm{mg}\\mathrm{mL}^{-1}$ ICBA (1- Material) or PCBM (nano-C) in chlorobenzene was spin coated at $1000\\mathrm{rpm}$ for $^{30\\mathrm{{s},}}$ and then annealed at $70^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . Saturated bathocuproine in isopropyl alcohol was spin coated at $6000\\mathrm{rpm}$ for $^{30\\mathrm{{s},}}$ followed by annealing at $70^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . All precursors were filtered with $0.22\\upmu\\mathrm{m}$ polytetrafluoroethylene (PTFE) filters before spin coated. Finally, $100\\mathrm{nm}$ Ag layer was deposited under vacuum of $<10^{-7}$ torr using an Angstrom Engineering deposition system. \n\nFilm characterizations. XRD was recorded on a Bruker D8 Advance using Cu Kα source $(\\lambda=1.54\\mathrm{\\AA}$ ). PL spectra were carried out by the exciting wavelength at $480\\mathrm{nm}$ of spectrofluorometer (Fluorolog; HORIBA FL-3) with a standard 450 W Xenon CW lamp. TRPL spectroscopy at $840\\mathrm{nm}$ was measured using Fluorolog HORIBA FL-3 with a pulsed source at $504\\mathrm{nm}$ DeltaDiode DD-510L. The UV–vis spectra of the perovskite films deposited on PEDOT were recorded by UV–vis spectrophotometer (Agilent cary5000). SEM images were recorded on JSM-7800. UPS was performed for films on PEDOT using a Thermo Fisher ESCALAB 250XI, and the samples were transferred from glovebox to vacuum chamber with a portable transfer capsule. Curve fitting was performed using the Thermo Avantage software. The curves were corrected based on the C1s peak at $284.8\\mathrm{eV}$ . GIWAXS studies were performed at the BL16B1 beamline of Shanghai Synchrotron Radiation Facility (SSRF), Shanghai, China, using beam energy of $10\\mathrm{keV}$ $(\\lambda=1.24\\mathrm{\\AA})$ ) and a Mar 225 detector. The grazing-incidence angles for all films were $0.2^{\\circ}$ and $1.0^{\\circ}$ , respectively. GIXGUI Matlab toolbox was utilized for necessary corrections of GIWAXS raw patterns and collecting the azimuth angle38. \n\nDevice characterization. $J{-}V$ curves were measured using a Keithley 2400 source unit under simulated AM $1.5\\mathrm{G}$ solar illumination at $100\\mathrm{\\overline{{m}}W}\\mathrm{cm}^{-2}$ (1 sun). The light intensity was calibrated by means of a KG-5 Si diode with a solar simulator (Enli Tech, Taiwan). The devices are measured in reverse scan $(1.0\\mathrm{-}0\\mathrm{V},$ step $0.01\\mathrm{V}$ ) and forward scan ( $_{0-1.0\\mathrm{V}}$ , step $0.01\\mathrm{V}$ ) with a delay time of $30\\mathrm{ms}$ . The $J{-}V$ curves for all devices were measured by masking the active area using a metal mask with an area of $0.04\\mathrm{cm}^{2}$ . The steady-state PCE was performed at $_{0.81\\mathrm{V}}$ . Devices were stored and tested in the same nitrogen-filled glovebox (Vigor). \n\nThe EQE spectra were measured by a commercial system (Solar cell scan 100, Beijing Zolix Instruments Co., Ltd). The cells were subjected to monochromatic illumination (150 W Xe lamp passing through a monochromator and appropriate filters). The light intensity was calibrated by a standard photodetector (QE-B3/ S1337-1010BQ, Zolix). The light beam was chopped at $^{180\\mathrm{Hz}},$ and the response of the cell was acquired by a Stanford Research SR830 lock-in amplifier. \n\nTPV and TPC measurements were carried out using a setup comprising a $532\\mathrm{nm}$ wavelength laser to provide steady-state bias light, a $640\\mathrm{nm}$ wavelength laser, and an oscilloscope. A power-adjustable $532\\mathrm{nm}$ wavelength laser was used to get a steady $V_{\\mathrm{OC}}$ of the device. A $640\\mathrm{nm}$ diode laser was used to modulate the $V_{\\mathrm{OC}}$ on top of a constant light bias. The pulse duration was set to $1\\upmu\\mathrm{s}$ and the repetition rate to $50\\mathrm{Hz}$ by the function generator of the oscillator. The digital oscilloscope recorded the data induced by the light perturbation, using 1 MΩ input impedance for the TPV measurement and $50\\Omega$ impedance for TPC measurement. We determined the charge generated (ΔQ) in the devices by integrating the TPC curve by the $640\\mathrm{nm}$ laser pulse without $532\\mathrm{nm}$ light bias present. The calculated $C=$ $\\Delta Q/\\Delta V_{\\mathrm{OC}}$ result is the capacitance. The total charge carrier was obtained by integrating the $C$ versus $V_{\\mathrm{OC}}.$ . The carrier concentration $(n)$ for each open-circuit voltage was calculated by dividing each charge carriers with the device volume. The density of states (DOS) in the mid-gap can be obtained by differentiating the carrier density with respect to the $V_{\\mathrm{OC}}$ following a previously reported procedure37. \n\nThe current density–luminance–radiance (J–V–R) characteristics were measured by a Keithley 2400 source meter, and a fiber integrating sphere (FOIS-1) couple with a QE Pro 650 spectrometer (Ocean Optics). The devices were tested on \n\ntop of the integrating sphere, and only forward light emission could be collected. \nAll device test processes were carried out in the $\\Nu_{2}$ -filled glovebox. \n\nFirst-principles calculations. First-principles calculations were performed within the framework of DFT using plane-wave pseudopotential methods, as implemented in the Vienna Ab-initio Simulation Package39. The generalized gradient approximation formulated by Perdew, Burke, and Ernzerhof was used as the exchange–correlation functional. The electron–core interactions were described by the projector augmented-wave40 method for the pseudo potentials. The cutoff energy for the plane-wave basis set used to expand the Kohn–Sham orbitals was $400\\mathrm{eV}$ The Gamma-centered $k$ -point mesh with a grid spacing of $2\\pi\\times0.03\\mathrm{{\\AA^{-1}}}$ was used for electronic Brillouin zone integration. For adsorption energy calculation, the vacuum thickness was set to be $2\\bar{0}\\mathrm{\\AA}$ . The equilibrium structural parameters (including both lattice parameters and internal coordinates) of each involved bulk material were obtained via total energy minimization by using the conjugate gradient algorithm, with the force convergence threshold of $\\dot{0}.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ ; for slab structures, only the internal coordinates are relaxed. The optB86b-vdW (ref. 41) functional is adopted throughout the whole calculation. \n\nSKPM measurement. The amplitude-modulation SKPM was operated combined with a Cypher S atomic force microscopy (AFM; Asylum Research, Oxford Instruments) and a HF2LI Lock-in amplifier (Zurich Instruments) in $\\Nu_{2}$ -filled glovebox. The resonance frequency $\\omega_{0}$ and spring constant of AFM conducting tips are ${\\sim}127\\mathrm{kHz}$ and $5.0\\mathrm{Nm}^{-1}$ , respectively. \n\nTin PSC certification at SIMIT (Shanghai, China). The device certification tests were performed at an independent lab (SIMIT, Chinese Academy of Sciences). And SIMIT is accredited by China National Accreditation Service for Conformity Assessment (CNAS) to ISO/IEC 17025 and by the International Laboratory Accreditation Cooperation (ILAC) Mutual Recognition Arrangement. \n\nA silicon reference solar cell (PVM1211, NREL_ISO tracking#:1974) was used to set the irradiance at $100\\mathrm{mW}\\mathrm{cm}^{-2}$ at standard testing conditions in accordance with IEC 60904-3 ed.2 AM $1.5\\mathrm{G}$ . J–V characteristics of tin PSCs were measured under simulated sunlight by steady-state class AAA solar simulator according to IEC 60904-9 ed.2. The spectral mismatch was calculated and mismatch correction was performed according to IEC 60904-7 ed.3. The $J{-}V$ curves were measured in forward and reverse scans with a scanning speed of $90\\mathrm{mVs^{-1}}$ . \n\nEncapsulation method. Devices were encapsulated by quartz glass and UV-glue for J–V, EQE, TRPL, TPV, and TPC measurements. Films were double sealed by plastic bags before XRD, SEM, PL, UV–vis, and GIWAXS measurements. \n\nReporting summary. Further information on experimental design is available in the Nature Research Reporting Summary linked to this paper. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 16 June 2019; Accepted: 12 February 2020; Published online: 06 March 2020 \n\n# References \n\n1. Abate, A. J. J. Perovskite solar cells go lead free. Joule 1, 659–664 (2017). \n2. Yu, D. et al. Stability improvement under high efficiency—next stage development of perovskite solar cells. Sci. China Chem. 62, 684–707 (2019). \n3. Correa-Baena, J. P. et al. Promises and challenges of perovskite solar cells. Science 358, 739–744 (2017). \n4. Shi, Z. et al. Lead‐free organic–inorganic hybrid perovskites for photovoltaic applications: recent advances and perspectives. Adv. Mater. 29, 1605005 (2017). \n5. Diau, E. W.-G., Jokar, E. & Rameez, M. Strategies to improve performance and stability for tin-based perovskite solar cells. ACS Energy Lett. 4, 1930–1937 (2019). \n6. Ke, W. & Kanatzidis, M. G. Prospects for low-toxicity lead-free perovskite solar cells. Nat. Commun. 10, 965 (2019). \n7. Marshall, K. P., Walker, M., Walton, R. I. & Hatton, R. A. Enhanced stability and efficiency in hole-transport-layer-free CsSnI3 perovskite photovoltaics. Nat. Energy 1, 16178 (2016). \n8. Lee, S. J. et al. Fabrication of efficient formamidinium tin iodide perovskite solar cells through SnF2-pyrazine complex. J. Am. Chem. Soc. 138, 3974–3977 (2016). \n9. Tai, Q. et al. Antioxidant grain passivation for air‐stable tin‐based perovskite solar cells. Angew. Chem. Int. Ed. 58, 806–810 (2019). \n10. Qiu, J., Xia, Y., Chen, Y. & Huang, W. Management of crystallization kinetics for efficient and stable low-dimensional Ruddlesden-Popper (LDRP) lead-free perovskite solar cells. Adv. Sci. 6, 1800793 (2018). \n11. Shao, S. et al. Enhancing the crystallinity and perfecting the orientation of formamidinium tin iodide for highly efficient Sn-based perovskite solar cells. Nano Energy 60, 810–816 (2019). \n12. Wang, F. et al. 2D-quasi-2D-3D hierarchy structure for tin perovskite solar cells with enhanced efficiency and stability. Joule 2, 2732–2743 (2018). \n13. Liao, Y. et al. Highly oriented low-dimensional tin halide perovskites with enhanced stability and photovoltaic performance. J. Am. Chem. Soc. 139, \n6693–6699 (2017). \n14. Liu, X., Wang, Y. B., Xie, F. X., Yang, X. D. & Han, L. Y. Improving the performance of inverted formamidinium tin iodide perovskite solar cells by reducing the energy-level mismatch. ACS Energy Lett. 3, 1116–1121 (2018). \n15. Kayesh, M. E. et al. Coadditive engineering with 5-ammonium valeric acid iodide for efficient and stable Sn perovskite solar cells. ACS Energy Lett. 4, \n278–284 (2018). \n16. Liao, W. et al. Lead-free inverted planar formamidinium tin triiodide perovskite solar cells achieving power conversion efficiencies up to $6.22\\%$ . Adv. Mater. 28, 9333–9340 (2016). \n17. Zhao, Z. et al. Mixed-organic-cation tin iodide for lead-free perovskite solar cells with an efficiency of $8.12\\%$ . Adv. Sci. 4, 1700204 (2017). \n18. Shao, S. et al. Highly reproducible sn-based hybrid perovskite solar cells with $9\\%$ efficiency. Adv. Energy Mater. 8, 1702019 (2018). \n19. Nishikubo, R., Ishida, N., Katsuki, Y., Wakamiya, A. & Saeki, A. Minute-scale degradation and shift of valence-band maxima of (CH3NH3)SnI3 and HC (NH2)2SnI3 perovskites upon air exposure. J. Phys. Chem. C 121, \n19650–19656 (2017). \n20. Jokar, E., Chien, C. H., Tsai, C. M., Fathi, A. & Diau, E. W. G. Robust tinbased perovskite solar cells with hybrid organic cations to attain efficiency approaching $10\\%$ . Adv. Mater. 31, 1804835 (2019). \n21. Ran, C. et al. Conjugated organic cations enable efficient self-healing FASnI3 solar cells. Joule 3, 3072–3087 (2019). \n22. Wu, T. et al. Efficient and stable tin-based perovskite solar cells by introducing π-conjugated Lewis base. Sci. China Chem. 63, 107–115 (2019). \n23. Tsai, H. et al. High-efficiency two-dimensional Ruddlesden–Popper perovskite solar cells. Nature 536, 312 (2016). \n24. Byun, J. et al. Efficient visible quasi‐2D perovskite light‐emitting diodes. Adv. Mater. 28, 7515–7520 (2016). \n25. Urbach, F. J. P. R. The long-wavelength edge of photographic sensitivity and of the electronic absorption of solids. Phys. Rev. 92, 1324 (1953). \n26. De Wolf, S. et al. Organometallic halide perovskites: sharp optical absorption edge and its relation to photovoltaic performance. J. Phys. Chem. Lett. 5, \n1035–1039 (2014). \n27. Lin, Y. et al. Matching charge extraction contact for wide-bandgap perovskite solar cells. Adv. Mater. 29, 1700607 (2017). \n28. He, Y. J., Chen, H. Y., Hou, J. H. & Li, Y. F. Indene-C60 bisadduct: a new acceptor for high-performance polymer solar cells. J. Am. Chem. Soc. 132, \n1377–1382 (2010). \n29. Zhang, M. et al. Reconfiguration of interfacial energy band structure for highperformance inverted structure perovskite solar cells. Nat. Commun. 10, 4593 (2019). \n30. Zhao, T., Chueh, C.-C., Chen, Q., Rajagopal, A. & Jen, A. K. Y. Defect passivation of organic-inorganic hybrid perovskites by diammonium iodide toward highperformance photovoltaic devices. ACS Energy Lett. 1, 757–763 (2016). \n31. Wolff, C. M. et al. Reduced interface-mediated recombination for high opencircuit voltages in CH3NH3PbI3 solar cells. Adv. Mater. 29, 1700159 (2017). \n32. Shi, D. et al. Solar cells. Low trap-state density and long carrier diffusion in organolead trihalide perovskite single crystals. Science 347, 519–522 (2015). \n33. Stranks, S. D. et al. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n34. Jiang, Q. et al. Surface passivation of perovskite film for efficient solar cells. Nat. Photon. 13, 460–466 (2019). \n35. Luo, D. et al. Enhanced photovoltage for inverted planar heterojunction perovskite solar cells. Science 360, 1442–1446 (2018). \n36. Krückemeier, L., Rau, U., Stolterfoht, M. & Kirchartz, T. How to report record open‐circuit voltages in lead‐halide perovskite solar cells. Adv. Energy Mater. \n10, 1902573 (2019). \n37. Ip, A. H. et al. Hybrid passivated colloidal quantum dot solids. Nat. Nanotechnol. 7, 577–582 (2012). \n38. Jiang, Z. GIXSGUI: a MATLAB toolbox for grazing-incidence X-ray scattering data visualization and reduction, and indexing of buried three-dimensional periodic nanostructured films. J. Appl. Crystallogr. 48, 917–926 (2015). \n39. Kresse, G. & FurthmüllerJ. J. Pr. B. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169 (1996). \n40. Blochl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n41. Klimeš, J., Bowler, D. R. & Michaelides, A. Van der Waals density functionals applied to solids. Phys. Rev. B 83, 195131 (2011). \n\n# Acknowledgements \n\nThe authors gratefully acknowledge financial support from the National Key Research and Development Program of China (under grant nos. 2016YFA0204000 and 2016YFA0200700), ShanghaiTech start-up funding, 1000 young talent program, National Natural Science Foundation of China (61935016, U1632118, 21571129, 21625304, and 21875280), Shanghai key research program (16JC1402100), and Centre for Highresolution Electron Microscopy (CħEM), SPST, ShanghaiTech University under contract no. EM02161943. The authors appreciate the high-performance computing (HPC) Platform of ShanghaiTech University. The authors appreciate the BL16B1 beamline of Shanghai Synchrotron Radiation Facility (SSRF), Shanghai, China. The authors appreciate Dr. Na Yu, Rong Gao, and the Instrument Analysis Center of ShanghaiTech University. \n\n# Author contributions \n\nX.J. and F.W. contributed equally to this work. X.J., F.W., and Z.N. designed and directed the study. X.J. and F.W. contributed to all the experimental work. Q.W. carried out and interpreted the DFT studies. H.L. performed the PL, TRPL, and XRD measurements. Y.S. helped to carry out GIWAXS, and EL measurements and data analysis. W.Z. supervised the EQE and TPV measurements. P.C. supervised the UPS measurement. C.W., Q.C., and L.C. conducted the SKPM measurement and data analysis. Z.N. supervised the whole project. X.J., F.W., and Z.N write the manuscript. All authors discussed the results and commented on the final manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-15078-2. \n\nCorrespondence and requests for materials should be addressed to Z.N. \n\nPeer review information Nature Communications thanks Ashraful Islam and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41467-020-17752-x", + "DOI": "10.1038/s41467-020-17752-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-17752-x", + "Relative Dir Path": "mds/10.1038_s41467-020-17752-x", + "Article Title": "Revealing the role of crystal orientation of protective layers for stable zinc anode", + "Authors": "Zhang, Q; Luan, JY; Huang, XB; Wang, Q; Sun, D; Tang, YG; Ji, XB; Wang, HY", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Rechargeable aqueous zinc-ion batteries are a promising candidate for next-generation energy storage devices. However, their practical application is limited by the severe safety issue caused by uncontrollable dendrite growth on zinc anodes. Here we develop faceted titanium dioxide with relatively low zinc affinity, which can restrict dendrite formation and homogenize zinc deposition when served as the protective layer on zinc anodes. The as-prepared zinc anodes can be stripped and plated steadily for more than 460h with low voltage hysteresis and flat voltage plateau in symmetric cells. This work reveals the key role of crystal orientation in zinc affinity and its internal mechanism is suitable for various crystal materials applied in the surface modification of other metal anodes such as lithium and sodium. Zinc affinity plays a key role in the zinc plating and stripping processes but its internal mechanism is still unclear. Here, the authors report a protective layer with controllable zinc affinity by adjusting the crystal orientation to suppress the dendrite growth on the zinc anode interface.", + "Times Cited, WoS Core": 509, + "Times Cited, All Databases": 520, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000561098400014", + "Markdown": "# Revealing the role of crystal orientation of protective layers for stable zinc anode \n\nQi Zhang1, Jingyi Luan1, Xiaobing Huang2, Qi Wang1, Dan Sun1, Yougen Tang1, Xiaobo Ji1 & Haiyan Wang 1✉ \n\nRechargeable aqueous zinc-ion batteries are a promising candidate for next-generation energy storage devices. However, their practical application is limited by the severe safety issue caused by uncontrollable dendrite growth on zinc anodes. Here we develop faceted titanium dioxide with relatively low zinc affinity, which can restrict dendrite formation and homogenize zinc deposition when served as the protective layer on zinc anodes. The asprepared zinc anodes can be stripped and plated steadily for more than $460\\mathsf{h}$ with low voltage hysteresis and flat voltage plateau in symmetric cells. This work reveals the key role of crystal orientation in zinc affinity and its internal mechanism is suitable for various crystal materials applied in the surface modification of other metal anodes such as lithium and sodium. \n\nchieving higher energy density is the main development tendency for the next-generation battery system1. Metal anodes, such as lithium (Li), sodium (Na), and zinc $(Z\\boldsymbol{\\mathrm{n}})$ , with high theoretical capacity and low electrochemical potential are considered as the most promising materials to meet this requirement2,3. However, the electrochemical performance of metal anodes is seriously affected by the dendrite formation during repeated charging and discharging. Metal dendrites are easily detached from anode mainbody and the newly exposed metal would react with electrolyte, leading to low Coulombic efficiency4,5. More seriously, separators may be punctured by the continuous dendrite growth, which directly causes the short circuit and poor cycle life of batteries6,7. Therefore, it is important to solve this issue for the industrialization of metal anodes. \n\nMany approaches have been developed to achieve safer metal anodes, which mainly focus on two aspects: (1) improving metal deposition on current collectors. Nucleation can be facilitated by a three-dimensional structure with a uniform local electric field8,9. Some metal-affinity modification layers induced on current collectors are conducive to the adsorption of metal ions, which can guide the deposition and further alleviate dendrites10–12. (2) Optimizing the interface between metal and electrolyte. An artificial solid electrolyte interface (SEI) or an additional layer with inferior metal affinity can be applied as a protective layer to restrict dendrite growth13,14. Metal affinity is a key criterion to judge the applicable functions (guiding or restricting). However, taking titanium dioxide $\\left(\\mathrm{TiO}_{2}\\right)$ for example, it can be used both for modification of current collectors and protection of metal anodes according to previous reports15–17. These results seem contradictory because good metal affinity is required when $\\mathrm{TiO}_{2}$ is used as a decoration on current collectors to homogenize metal deposition while low metal affinity is necessary if it is served as a protective layer18,19. $\\mathrm{TiO}_{2}$ can be simultaneously applied to two different metal modification strategies with opposite requirements, indicating that there is an ambiguous internal mechanism affecting its metal affinity. Considering that exposed facets of a crystal have a great influence on catalytic activity, metal affinity may be also controllable by adjusting surface exposure20,21. \n\nIn this work, the interactions between $Z\\mathrm{n}$ and different facets of $\\mathrm{TiO}_{2}$ are first investigated by density functional theory (DFT) calculation and it is concluded that the (0 0 1) and (1 0 1) facets of $\\mathrm{TiO}_{2}$ show relatively low $Z\\mathrm{n}$ affinity. Accordingly, $\\mathrm{TiO}_{2}$ with highly exposed $(0\\ 0\\ \\mathrm{~\\i~})$ facet is prepared and applied as the protective layer for Zn metal anodes. The (0 0 1) faceted $\\mathrm{TiO}_{2}$ layer can effectively prevent Zn dendrites from growing vertically and stabilize the interface between anode and electrolyte. As a result, the modified $Z\\mathrm{n}$ anode exhibits long-term cycle life during $Z\\mathrm{n}$ stripping and plating. \n\n# Results \n\nTheoretical analysis and characterization of faceted $\\mathbf{TiO}_{2}$ . The mechanism for the interaction between $Z\\mathrm{n}$ and different facets of $\\mathrm{TiO}_{2}$ is first investigated by DFT calculation. As shown in Fig. 1a–c and Supplementary Figs. 1 and 2, the models of $Z\\mathrm{n}$ atoms attached to $\\mathrm{TiO}_{2}$ surfaces and $Z\\mathrm{n}$ surfaces were constructed. The $Z\\mathrm{n}$ affinity of $\\mathrm{TiO}_{2}$ surfaces can be judged by comparing the binding energy of $Z\\mathrm{n}$ atom attached to the $\\mathrm{TiO}_{2}$ surface and $Z\\mathrm{n}$ surface. It can be considered that a $\\mathrm{TiO}_{2}$ facet is with high Zn affinity if the binding energy of $Z\\mathrm{n}$ atom attached to the corresponding $\\mathrm{TiO}_{2}$ facet is higher than that on the $Z\\mathrm{n}$ surface. As summarized in Fig. 1d, the binding energy between Zn atom and $\\mathrm{TiO}_{2}$ (1 0 0) facet is $-0.95\\mathrm{eV}$ , higher than that between $Z\\mathrm{n}$ atom and $Z\\mathrm{n}$ surfaces $(-0.68$ and $-0.{\\dot{8}}6\\mathrm{eV})$ , indicating that $Z\\mathrm{n}$ prefers to deposit on $\\mathrm{TiO}_{2}$ (1 0 0) facet in comparison to $Z\\mathrm{n}$ surface. It is detrimental for a protective layer since this priority can lead to the growth of $Z\\mathrm{n}$ dendrites upon the layer and deactivate the protective effect. In contrast, there is a weaker absorption of $Z\\mathrm{n}$ on $\\mathrm{TiO}_{2}$ $(0\\mathrm{~0~1)~}$ and (1 0 1) facets with the binding energy of $-0.63$ and $-0.45\\mathrm{eV}$ , respectively, which is mainly because the more exposure of the lower coordinated Ti on these facets exhibits more intense repulsion to Zn atom22. The interaction between $Z\\mathrm{n}$ and different $\\mathrm{TiO}_{2}$ facets is illustrated in Fig. 1e. According to the above analysis, the facet orientation plays a key role in $Z\\mathrm{n}$ affinity and suitable materials for a protective layer can be achieved by controlling the exposure of specific facet. \n\nAs shown in Fig. 1f, the X-ray diffraction (XRD) patterns of the as-prepared faceted $\\mathrm{TiO}_{2}$ $\\left(\\mathrm{F}{-}\\mathrm{TiO}_{2}\\right)$ and commercial $\\mathrm{TiO}_{2}$ (C$\\mathrm{TiO}_{2}\\mathrm{.}$ ) can be indexed to anatase $\\mathrm{TiO}_{2}$ . The average thickness along the growth direction of a crystal $(D)$ can be calculated by Scherrer equation23,24: \n\n$$\nD=\\frac{K\\lambda}{\\beta{\\mathrm{cos}}\\theta}\n$$ \n\nwhere $K,\\lambda,\\beta,$ and $\\theta$ represent Scherrer constant, the wavelength of X-ray, full width at half maximum (FWHM) of diffraction peak and Bragg angle, respectively. For a specific crystal orientation, the larger FWHM in the XRD pattern indicates the smaller $D$ in this direction, in other words, the larger exposed area of the corresponding facet (Supplementary Fig. 3)25. Accordingly, the broader $\\mathbf{\\Sigma}(0\\ 0\\ 4)$ peak in $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ demonstrates the larger exposure of $(0\\ 0\\ 1)$ facet and the narrower (2 0 0) peak $\\mathrm{F}{-}\\mathrm{Ti}\\mathrm{\\bar{O}}_{2}$ corresponds to the larger crystal size parallel to (0 0 1) facet, which is also the evidence of the relatively higher exposed area of (0 0 1) facet in comparison with $\\mathrm{C}{\\cdot}\\mathrm{TiO}_{2}\\dot{^{26}}$ . In Raman spectra (Supplementary Fig. 4), the characteristic peaks of anatase $\\mathrm{TiO}_{2}$ appear at $392.3\\mathrm{cm}^{-1}$ (symmetric bending vibration, $\\mathbf{B}_{1\\mathbf{g}})$ , $51\\dot{3}.\\dot{7}\\mathrm{cm}^{-1}$ (antisymmetric bending vibration, $\\mathbf{A}_{1\\mathrm{g}})$ , $636.5\\mathrm{cm}^{-1}$ (symmetric stretching vibration, $\\mathrm{E_{g}})^{27}$ . The 3-coordinated titanium (Ti) atoms on the $\\bar{(0\\mathrm{~0~}1)}$ surface (Supplementary Fig. 5a) with lower coordination number than the 5-coordinated Ti atoms on $\\left(100\\right)$ surface (Supplementary Fig. 5b) tend to show stronger bending vibration28. Therefore, the weaker $\\mathbf{A}_{1\\mathbf{g}}$ and $\\mathbf{B}_{1\\mathbf{g}}$ peaks in the Raman spectrum of $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ suggest its higher exposure of (0 0 1) facet. Transmission electron microscopy (TEM) images (Supplementary Fig. 6) clearly show the nanosheet structure of $\\bar{\\mathrm{F}}{\\cdot}\\mathrm{TiO}_{2}$ with average width and thickness of 50 and $5\\mathrm{nm}$ , respectively. From the side view of $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ nanosheet (Fig. 1g), lattice fringes with a lattice spacing of $0.235\\mathrm{nm}$ are observed, which demonstrates that the [0 0 1] direction is perpendicular to the top surface. Figure 2h is the top-view high-resolution transmission electron microscopy (HRTEM) image of $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ nanosheet. There are orthogonal lattice fringes with equal lattice spacing $(0.19\\mathrm{nm})$ inside the nanosheet (Fig. 1i), corresponding to [1 0 0] and [0 1 0] directions (both belong to $<1\\ 0\\ 0>$ family of directions). Therefore, the normal direction of top surface is [0 0 1] direction perpendicular to both $\\left[1~0~0\\right]$ and $\\left[0\\ 1\\ 0\\right]$ directions29. According to the observation of side-view and top-view HRTEM images, it is confirmed that (0 0 1) facet is the highly exposed top surface of F$\\mathrm{TiO}_{2}$ nanosheet. Another set of orthogonal lattice fringes corresponding to [1 0 1] and [0 1 0] directions (Fig. 1j) indicates the existence of $(10-1)$ or $\\left(-101\\right)$ facets (equivalent to (1 0 1) facet because of the tetragonal symmetry) at the edge of nanosheet30. Besides, the side surface intersects the top (0 0 1) surface at an obtuse angle (Fig. 1g and Supplementary Fig. 6c). It can be concluded that the side surface of $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ nanosheet is (1 0 1) facet rather than the vertical $\\left(100\\right)$ facet. The percentage of the exposed (0 0 1) and (1 0 1) facets can be calculated to be $83\\%$ and $17\\%$ , respectively, by considering the nanosheet as a compressed square frustum. With regard to $\\mathrm{C}{\\cdot}\\mathrm{TiO}_{2}$ (Supplementary Fig. 7), it exhibits a nanoparticle morphology with an average diameter of $20\\mathrm{nm}$ and the irregular lattice fringes indicate its random growth orientation, which leads to more exposure of $\\mathrm{TiO}_{2}$ (1 0 0) facets. The large area of extra $\\mathrm{TiO}_{2}$ (1 0 0) facet is detrimental to prevent the growth of $Z\\mathrm{n}$ dendrites. Accordingly, it is believed that $\\mathrm{F-TiO}_{2}$ nanosheets with exposed $(0\\ 0\\ 1)$ and (1 0 1) facets can completely shield $Z\\mathrm{n}$ and restrict the formation of dendrites. \n\n![](images/2273739f048cb770d33f1ead358c0938147e18d00b33ec677d32601b7632dffd.jpg) \nFig. 1 Theoretical simulation and characterization of $\\pmb{\\operatorname{F}}\\pmb{\\operatorname{TiO}}_{2}$ . Calculations models of Zn absorbed on a $\\mathsf{T i O}_{2}$ (0 0 1) facet, b $\\mathsf{T i O}_{2}$ (1 0 0) facet, and $\\bullet Z_{n}$ (0 0 1) facet. d Calculated binding energies of Zn atom with different facets. e Schematic illustration of the interaction between Zn and anatase $\\mathsf{T i O}_{2}$ with different exposed facets. f XRD patterns of $\\mathsf{F}\\mathrm{-}\\mathsf{T i O}_{2}$ and $C-T i O_{2}$ . g–j HRTEM images of $F-T i O_{2}$ . Scale bars: $5\\mathsf{n m}$ . \n\n![](images/eacc250e097b6c802c70ff57379b933a59400b37c7856579c8af9a3dee811fb4.jpg) \nFig. 2 Zn deposition behavior of the prepared anodes. a Schematic illustration of the $Z n$ plating process with different coating layers. b CV curves of $Z n-Z n$ symmetric cells using $Z\\mathsf{F}@\\mathsf{F}\\boldsymbol{-}\\mathsf{T i O}_{2}$ anode measured at $1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . Peak areas of $Z n$ stripping/plating reactions (c) and corresponding Coulombic efficiency (d) of the prepared Zn anodes in $Z n-Z n$ symmetric cells. \n\nElectrochemical performance of $\\mathbf{F}\\mathbf{-}\\mathbf{TiO}_{2}$ as a protective layer. $\\mathrm{TiO}_{2}$ protective layer was introduced on Zn anode by a simple blade coating method and the corresponding XRD pattern (Supplementary Fig. 8) demonstrates that the composite $Z\\mathrm{n}$ anode is successfully synthesized. The $Z\\mathrm{n}$ plating process on different Zn anodes is illustrated in Fig. 2a. Charges and ions tend to accumulate on the small tips at the surface of commercial Zn foil anodes when there is an impressed voltage. The resulting uneven interfacial electric field and ion concentration can induce preferential $Z\\mathrm{n}$ growth and eventually lead to the formation of $Z\\mathrm{n}$ dendrites during the repeated stripping and plating cycles31. When using $\\mathrm{C}{\\mathrm{-}}\\mathrm{TiO}_{2}$ as the intermediate layer, Zn tends to grow on the surface of $\\mathrm{TiO}_{2}$ layer with a higher Zn affinity. For comparison, the $Z\\mathrm{n}$ plating reaction can be well confined under the protective layer and the smooth $Z\\mathrm{n}$ layer can be deposited on the $Z\\mathrm{n}$ anode by faceting the $\\mathrm{TiO}_{2}$ to specific orientations with low $Z\\mathrm{n}$ affinity. The cyclic voltammetry (CV) curves of $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ coated Zn foil $(\\mathrm{ZF}@\\mathrm{F}\\mathrm{-}\\mathrm{TiO}_{2})$ in $Z\\mathrm{n-Zn}$ symmetric cells (Fig. 2b) can almost maintain the identical shapes in comparison with the changed peaks of $\\mathrm{C}{\\cdot}\\mathrm{TiO}_{2}$ coated $Z\\mathrm{n}$ foil $(Z{\\mathrm{F}}@{\\mathrm{C}}{\\mathrm{-TiO}}_{2})$ and $Z\\mathrm{n}$ foil (ZF) (Supplementary Fig. 9), which indicates the superior reversibility of $Z\\mathrm{n}$ stripping/plating in $Z{\\mathrm{F}}@{\\mathrm{F}}–{\\mathrm{TiO}}_{2}$ anode. The peak areas of each redox reaction of CV curves can be obtained by integration operation (Fig. 2c). The larger peak area of $\\mathrm{ZF}@\\mathrm{F}$ - $\\mathrm{TiO}_{2}^{\\bar{}}$ anode reflects the enhanced interfacial activity for $Z\\mathrm{n}$ deposition32. $Z\\mathrm{n}^{2+}$ driven by the electric field and concentration gradient migrate toward the $Z\\mathrm{n}$ anode and tend to be repulsed by the $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ layer at the interface, leading to the $Z\\mathrm{n}^{2+}$ accumulation near the anode surface. The increased $Z\\mathrm{n}^{2+}$ concentration can not only activate more binding sites for $Z\\mathrm{n}$ deposition but also accelerate the $Z\\mathrm{n}^{2+}$ transfer rate on the surface to alleviate the uneven $Z\\mathrm{n}^{2+}$ distribution, which is beneficial to the ordered interfacial Zn deposition33,34. Moreover, the highest Coulombic efficiency (reduction/oxidation) of $\\mathrm{ZF}@\\mathrm{F-TiO}_{2}.$ among all the prepared anodes (Fig. 2d) is also the evidence of its superior reversibility, which can be ascribed to the more uniform $Z\\mathrm{n}$ deposition and less formation of “dead $Z\\mathrm{n}^{\\prime\\prime}$ . $\\mathrm{TiO}_{2}$ coated $Z\\mathrm{n}$ foils exhibit better hydrophilicity than pure Zn foil (Supplementary Fig. 10), indicating that electrolyte can penetrate $\\mathrm{TiO}_{2}$ layers to facilitate $Z\\mathrm{n}^{2+}$ transport towards anode surface. The voltage profiles of the first ten cycles of zinc-stainless steel $(Z\\mathrm{n}\\mathrm{-}S\\mathrm{S})$ cells were recorded, which are shown in Supplementary Fig. 11. Pure $Z\\mathrm{n}$ foil fails rapidly within $600\\mathrm{{min}}$ due to the short circuit caused by the formation of dendrites. And the cycling stability of the cells is significantly improved when $Z\\mathrm{n}$ foils are coated with the $\\mathrm{TiO}_{2}$ interface layer. Specifically, $Z{\\mathrm{F}}@{\\mathrm{F}}–{\\mathrm{TiO}}_{2}$ exhibits longer cycling life than $\\scriptstyle\\sum\\mathrm{F}@\\mathrm{C}-\\mathrm{TiO}_{2}$ , indicating its better Zn reversibility achieved by the specific exposed facets. \n\nZn anodes were extracted from $Z\\mathrm{n-SS}$ cells and their digital photographs are shown in Supplementary Fig. 12. Some unevenly distributed crystals are formed on the surface of ZF and $Z{\\mathrm{F}}@{\\mathrm{C}}.$ $\\mathrm{TiO}_{2}$ , while $\\mathrm{ZF}@\\mathrm{F}–\\mathrm{TiO}_{2}$ can maintain the original structure of F$\\mathrm{TiO}_{2}$ layer. Scanning electron microscope (SEM) images of these cycled electrodes were also compared with the fresh anodes (Fig. 3). The morphologies of $\\mathrm{ZF}@\\mathrm{F}–\\mathrm{TiO}_{2}$ and $\\mathrm{ZF}@\\mathrm{C}\\ –\\mathrm{TiO}_{2}$ are consistent before cycling. $\\mathrm{TiO}_{2}$ coating layer with a smooth surface and uniform thickness $(20\\upmu\\mathrm{m})$ is in close contact with $Z\\mathrm{n}$ foil. After cycling, there is no obvious change in $Z{\\mathrm{F}}@{\\mathrm{F}}{\\mathrm{-TiO}}_{2}$ and its interface is still tightly combined. The well-defined distribution of Ti and $Z\\mathrm{n}$ in the energy dispersive X-ray (EDX) mapping images (Fig. 3c, f) also demonstrates the good reversibility during stripping and plating cycles. As shown in Fig. 3j, $\\mathbf{k},$ Zn sheets ( $3\\upmu\\mathrm{m}$ in length) are observed on the surface of cycled $\\mathrm{ZF}@\\mathrm{C}\\ –\\mathrm{TiO}_{2}$ , which is easily turned into $Z\\mathrm{n}$ dendrites and causes the safety problem. $\\mathrm{C}{\\mathrm{-}}\\mathrm{TiO}_{2}$ layer seems ineffective due to a large amount of $Z\\mathrm{n}$ transferred from Zn foil and the formation of void space at the interface. The process of $Z\\mathrm{n}$ transfer to the surface can be seen in the EDX mapping image (Fig. 3l). Supplementary Fig. 13 exhibits the more disordered surface with the wild growth of $Z\\mathrm{n}$ dendrites on the cycled pure $Z\\mathrm{n}$ foil, which is in agreement with the short-circuited $Z\\mathrm{{\\bar{n}-}}S S$ cell within 10 cycles. From the different morphologies mentioned above, it is proved that the facet orientation plays an important role in adjusting $Z\\mathrm{n}$ deposition behavior and $\\mathrm{TiO}_{2}$ protective layer with highly exposed $(0\\ 0\\ 1)$ facet with low Zn affinity can completely confine the Zn deposition in the restricted space. Besides, the $\\mathrm{TiO}_{2}$ layer on the cycled anodes was removed by using methyl-2-pyrrolidinone (NMP) to dissolve polyvinylidene difluoride (PVDF) in the layers. As seen from the SEM images of the $Z\\mathrm{n}$ surface after cycling (Supplementary Fig. 14), Zn deposition in ${\\mathrm{ZF}@\\mathrm{F}}{\\mathrm{-TiO}_{2}}$ is flat and tends to accumulate parallel to the $Z\\mathrm{n}$ surface, which also suggests the limited $Z\\mathrm{n}$ growth by $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ protective layer with decreased Zn affinity. \n\nThe positive effect of the $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ layer on $Z\\mathrm{n}$ plating behavior was further investigated by testing the cycling stability of $Z\\mathrm{n}$ anodes in $Z_{\\mathrm{{n}/Z_{\\mathrm{{n}}}}}$ symmetric cells. As shown in Fig. 4a, $\\mathrm{ZF}@\\mathrm{F}$ - $\\mathrm{TiO}_{2}$ can be operated steadily for more than $460\\mathrm{h}$ at $1\\mathrm{mA}\\mathrm{cm}^{-2}$ for $1\\mathrm{mAh}\\mathrm{cm}\\bar{-}2$ , which is much superior to $\\mathrm{ZF@C\\mathrm{-}T i O}_{2}$ $(\\mathrm{190h})$ and ZF $(20\\mathrm{h})$ . When increasing the current density to $2\\mathrm{mA}\\mathrm{cm}^{-2}$ and the specific capacity to $2\\mathrm{\\mAh}\\mathrm{cm}^{-2}$ (Fig. 4b), $\\mathrm{ZF@F–TiO}_{2}$ can still charge and discharge for $280\\mathrm{h}$ in contrast to the quick failure of $\\mathrm{ZF@C\\mathrm{-}T i O}_{2}$ and ZF with the shorter lifespan of 115 and $15\\mathrm{h}$ , respectively. Besides, $Z{\\mathrm{F}}@{\\mathrm{F}}–{\\mathrm{TiO}}_{2}$ exhibits the most stable voltage plateau and the lowest voltage hysteresis, reflecting the enhanced Zn transfer kinetics35. The electrochemical performance of $Z{\\mathrm{F}}@{\\mathrm{F}}–{\\mathrm{TiO}}_{2}$ is competitive in comparison with several $Z\\mathrm{n}$ anodes using protective coating materials (Supplementary Table 1). The full cells were assembled with the as-prepared $Z\\mathrm{n}$ anodes and commercial manganese dioxide $\\mathrm{(MnO}_{2}^{\\cdot}$ cathode. The full cell using $\\mathrm{ZF@C\\mathrm{-}T i O}_{2}$ anode exhibits the lowest polarization voltage and best cycling performance with the capacity retention ratio of $84.1\\%$ after 300 cycles (Supplementary Fig. 15). The enhanced full cell performance using the $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ layer suggests its potential for practical application. \n\n# Discussion \n\nHigh-performance $Z\\mathrm{n}$ anode without external dendrite growth was fabricated by coating $\\mathrm{TiO}_{2}$ with highly exposed (0 0 1) facet on commercial $Z\\mathrm{n}$ foil. Benefiting from the specific crystal orientation of $\\mathrm{TiO}_{2}$ with abomination to $Z\\mathrm{n}$ absorption, $\\dot{Z}\\mathrm{n}^{2+}$ transferred by the electric field was enriched on the anode surface. Thus, the increased interfacial $Z\\mathrm{n}^{2+}$ concentration could induce uniform nucleation and the further $Z\\mathrm{n}$ deposition was guided to grow laterally. The as-prepared $Z\\mathrm{n}$ anode exhibited superior $Z\\mathrm{n}$ stripping and plating performance with a long lifespan ( $460\\mathrm{h}$ at $1\\mathrm{\\mA}\\mathrm{cm}^{-2}$ for $1\\mathrm{m}\\bar{\\mathrm{Ah}}\\mathrm{cm}^{-2}$ ). More importantly, the strategy to change the $Z\\mathrm{n}$ affinity by adjusting the exposure of the facet provides a deep insight into the internal mechanism of metal affinity and can be extended to interfacial modification for other metal anodes. \n\n![](images/f23672e61e27a75cdc38c846b8f04c26dfa5bd0e1f149bb70aebadd81dd567d5.jpg) \nFig. 3 Morphology evolution of the prepared Zn anodes. SEM and the corresponding EDX mapping images of a–f $Z\\mathsf{F}@\\mathsf{F}\\boldsymbol{-}\\mathsf{T i O}_{2}$ and $\\mathbf{g}{\\mathsf{-}}\\mathbf{l}\\mathsf{Z}\\mathsf{F}@\\mathsf{C}{\\mathsf{-}}\\mathsf{T}\\mathsf{i}\\mathsf{O}_{2}$ before and after 10 cycles in $Z n-S S$ cells. Scale bar: $40\\upmu\\mathrm{m}$ . \n\n# Methods \n\nSynthesis of $F-T i O_{2}$ . Tetrabutyl titanate $\\mathrm{.10~mL}$ Aladdin) and hydrofluoric acid ( $1.2\\mathrm{mL}$ , $40\\mathrm{wt\\%}$ , Sinopharm) were added into a $50~\\mathrm{mL}$ Teflon-lined autoclave and then maintained at $180^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . The precipitates were collected by vacuum filtration then washed by ethanol and dried at $80^{\\circ}\\mathrm{C}$ for $^{6\\mathrm{h}}$ . \n\nFabrication of $\\pmb{\\mathrm{ZF}}(\\pmb{\\mathcal{a}})\\pmb{\\mathsf{F}}\\pmb{-}\\pmb{\\mathsf{T i O}}_{2}.$ . $\\mathrm{F}{\\mathrm{-TiO}}_{2}$ and PVDF were mixed in a weight ratio of 9:1 with NMP as the dispersant. The slurry was pasted onto $Z\\mathrm{n}$ foil $(30\\upmu\\mathrm{m})$ and dried at $80^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ under vacuum. For comparison, $\\mathrm{ZF@C\\mathrm{-}T i O}_{2}$ was also prepared by replacing $\\mathrm{F}{\\mathrm{-}}\\mathrm{TiO}_{2}$ with $\\mathrm{C}{\\mathrm{-TiO}_{2}}$ . \n\nCharacterizations. XRD was tested by a Bruker D8 X-ray diffractometer with monochromatized Cu Kα radiation (wavelength $=1.5406\\mathrm{\\dot{A}}$ ). Raman spectra were recorded using a Renishaw inVia spectrometer using an excitation wavelength of $532\\mathrm{nm}$ . Morphologies of the prepared $\\mathrm{TiO}_{2}$ and $Z\\mathrm{n}$ anodes were characterized by SEM (Nova NanoSEM 230) and TEM (Tecnai G2 F20 S-TWIN). The contact angle was measured by a drop shape analyzer (DSA100). \n\nElectrochemical measurements. Coin-type cells (CR2025) were assembled for $Z{\\mathrm{n-Zn}}$ symmetric cells, Zn-SS half cells and $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ full cells with glass fiber as separator and $1\\mathrm{M}$ zinc sulfate $\\mathrm{(ZnSO_{4})}$ ) aqueous solution as the electrolyte. Battery performance was evaluated using a Neware battery testing system. CV measurement for $Z{\\mathrm{n-Zn}}$ symmetric cells was conducted on a CHI760E electrochemical workstation in the voltage range of $-0.1\\mathrm{-}0.1\\:\\mathrm{V}$ . Zn-SS half cells were cycled with a specific capacity of $1\\ \\mathrm{mAh}\\mathrm{cm}^{-2}$ at $1\\mathrm{mA}\\mathrm{cm}^{-2}$ for the charging process and a cutoff potential of $-0.3{\\mathrm{V}}$ at $1\\mathrm{mA}\\mathrm{cm}^{-2}$ for the discharging process. Full cells were cycled between 1.0 and $2.0\\mathrm{V}$ using commercial $\\mathrm{MnO}_{2}$ (Macklin) as the cathode. In all, $0.1\\mathrm{{M}}$ manganese sulfate $\\mathrm{(MnSO_{4})}$ was added in the $\\mathrm{ZnSO_{4}}$ electrolyte to prevent $\\mathrm{Mn}^{2+}$ dissolution. \n\nComputational details. The first-principles calculations were conducted using generalized gradient approximation (GGA) and Perdew–Burke–Ernzerhof (PBE) exchange-correlation functional in DMol3 module of Materials Studio (version 8.0) of Accelrys Inc. An all-electron numerical basis set with polarization functions (DNP basis set) and a DFT-D method within the Grimme scheme was employed. The convergence tolerance was set to $1.0\\times10^{-5}\\mathrm{Ha}$ ( $\\mathrm{1Ha=27.21eV},$ for energy, $2.0\\times\\mathrm{\\dot{1}}0^{-3}\\mathrm{Ha}\\mathrm{\\mathring{A}}^{-1}$ for maximum force and $5.0\\times$ $10^{-3}\\mathrm{\\AA}$ for maximum displacement. Common facets of $\\mathrm{TiO}_{2}$ and $Z\\mathrm{n}$ were investigated in this simulation, including $\\mathrm{TiO}_{2}$ (0 0 1), $\\mathrm{TiO}_{2}$ (1 0 0), $\\mathrm{TiO}_{2}$ (1 0 1), Zn (0 0 1) and Zn (1 0 0). Each facet was set as a five-layer $3\\times3$ supercell with top three-layer atoms releasable. $Z\\mathrm{n}$ atom was placed in the vertex of the oxygen octahedron of the $\\mathrm{TiO}_{2}$ facet or the tetrahedral vertex of the $Z\\mathrm{n}$ facet before geometry optimization. Binding energy $(E_{\\mathrm{b}})$ was calculated by the following equation: \n\n$$\nE_{\\mathrm{b}}=E_{\\mathrm{total}}-E_{\\mathrm{sub}}-E_{\\mathrm{Zn}}\n$$ \n\n$E_{\\mathrm{total}}$ , $E_{\\mathrm{sub}},$ and $E_{\\mathrm{Zn}}$ represent the total energy of the facet combined with $Z\\mathrm{n}$ atom, the energy of the facet and the energy of $Z\\mathrm{n}$ atom, respectively. \n\n![](images/6378a814235859d84fe6275da6d89855d882a7a5c189da2ccb86385863f4ced0.jpg) \nFig. 4 Electrochemical performance of prepared Zn anodes. Cycling performance $Z n-Z n$ symmetric cells at a $1\\mathsf{m A c m}^{-2}$ for $1\\mathsf{m A h c m}^{-2}$ and b $2\\mathsf{m A c m}^{-2}$ for $2\\mathsf{m A h c m}^{-2}$ . \n\n# Data availability \n\nThe data sets generated and/or analyzed in this study are available from the corresponding author on reasonable request. \n\nReceived: 24 November 2019; Accepted: 2 July 2020; Published online: 07 August 2020 \n\n# References \n\n1. Lee, B., Paek, E., Mitlin, D. & Lee, S. W. Sodium metal anodes: emerging solutions to dendrite growth. Chem. Rev. 119, 5416–5460 (2019). \n2. Lu, Z. et al. Graphitic carbon nitride induced micro-electric field for dendritefree lithium metal anodes. Adv. Energy Mater. 9, 1803186 (2019). \n3. Grey, C. P. & Tarascon, J. M. Sustainability and in situ monitoring in battery development. Nat. Mater. 16, 45 (2016). \n4. Shen, X. et al. Lithium anode stable in air for low-cost fabrication of a dendrite-free lithium battery. Nat. Commun. 10, 900 (2019). \n5. Meng, J., Chu, F., Hu, J. & Li, C. Liquid polydimethylsiloxane grafting to enable dendrite-free Li plating for highly reversible Li-metal batteries. Adv. Funct. Mater. 29, 1902220 (2019). \n6. Wu, J. et al. Ultralight layer-by-layer self-assembled $\\ensuremath{\\mathbf{MoS}}_{2}$ -polymer modified separator for simultaneously trapping polysulfides and suppressing lithium dendrites. Adv. Energy Mater. 8, 1802430 (2018). \n7. Zhang, Q. et al. The Three-dimensional dendrite-free zinc anode on a copper mesh with a zinc-oriented polyacrylamide electrolyte additive. Angew. Chem. Int. Ed. 58, 2–9 (2019). \n8. Yang, C. P., Yin, Y. X., Zhang, S. F., Li, N. W. & Guo, Y. G. Accommodating lithium into 3D current collectors with a submicron skeleton towards long-life lithium metal anodes. Nat. Commun. 6, 8058 (2015). \n9. Zeng, Y., et al. Dendrite-free zinc deposition induced by multifunctional CNT frameworks for stable flexible Zn-ion batteries. Adv. Mater. 31, 1903675 (2019). \n10. Chen, X. et al. Lithiophilicity chemistry of heteroatom-doped carbon to guide uniform lithium nucleation in lithium metal anodes. Sci. Adv. 5, eaau7728 (2019). \n11. Zhang, Q., Luan, J., Sun, D., Tang, Y. & Wang, H. Plasma-treated $\\mathrm{Ti}^{3+}$ -doped sodium titanate nanosheet arrays on titanium foil as a lithiophilic current collector for a stable lithium metal anode. Chem. Commun. 55, 6551–6554 (2019). \n12. Luan, J. et al. Plasma-strengthened lithiophilicity of copper oxide nanosheet–decorated Cu foil for stable lithium metal anode. Adv. Sci. 6, 1901433 (2019). \n13. Liu, F. et al. Fabrication of hybrid silicate coatings by a simple vapor deposition method for lithium metal anodes. Adv. Energy Mater. 8, 1701744 (2018). \n14. Deng, K. et al. Single-ion conducting artificial solid electrolyte interphase layers for dendrite-free and highly stable lithium metal anodes. J. Mater. Chem. A 7, 13113–13119 (2019). \n15. Xue, P., Sun, C., Li, H., Liang, J., & Lai, C. Superlithiophilic amorphous $\\mathrm{SiO}_{2}{\\mathrm{-TiO}}_{2}$ distributed into porous carbon skeleton enabling uniform lithium deposition for stable lithium metal batteries. Adv. Sci. 6, 1900943 (2019). \n16. Zhou, M., Lyu, Y., Liu, Y. & Guo, B. Porous scaffold of $\\mathrm{TiO}_{2}$ for dendrite-free lithium metal anode. J. Alloy. Compd. 791, 364–370 (2019). \n17. Nan, Y., Li, S., Li, B. & Yang, S. An artificial $\\mathrm{TiO}_{2}/$ lithium n-butoxide hybrid SEI layer with facilitated lithium-ion transportation ability for stable lithium anodes. Nanoscale 11, 2194–2201 (2019). \n18. Zhao, Z. et al. Long-life and deeply rechargeable aqueous $Z\\mathrm{n}$ anodes enabled by a multifunctional brightener-inspired interphase. Energy Environ. Sci. 12, \n1938–1949 (2019). \n19. Bai, M. et al. A scalable approach to dendrite-free lithium anodes via spontaneous reduction of spray-coated graphene oxide layers. Adv. Mater. 30, \n1801213 (2018). \n20. Li, C. et al. Facet-dependent photoelectrochemical performance of $\\mathrm{TiO}_{2}$ nanostructures: an experimental and computational study. J. Am. Chem. Soc. \n137, 1520–1529 (2015). \n21. Wang, S., Liu, G. & Wang, L. Crystal facet engineering of photoelectrodes for photoelectrochemical water splitting. Chem. Rev. 119, 5192–5247 (2019). \n22. Liu, G. et al. Enhanced photoactivity of oxygen-deficient anatase $\\mathrm{TiO}_{2}$ sheets with dominant $\\left\\{001\\right\\}$ facets. J. Phys. Chem. C. 113, 21784–21788 (2009). \n23. D’Agostino, A. Determination of thin metal film thickness by X-ray diffractometry using the Scherrer equation, atomic absorption analysis and transmission/reflection visible spectroscopy. Anal. Chim. Acta 262, 269–275 (1992). \n24. Zhu, J. et al. Solvothermally controllable synthesis of anatase $\\mathrm{TiO}_{2}$ nanocrystals with dominant {001} facets and enhanced photocatalytic activity. Cryst. Eng. Commun. 12, 2219–2224 (2010). \n25. Wang, J., Zhang, P., Li, X., Zhu, J. & Li, H. Synchronical pollutant degradation and $\\mathrm{H}_{2}$ production on a $\\mathrm{Ti}^{3+}$ -doped $\\mathrm{TiO}_{2}$ visible photocatalyst with dominant (001) facets. Appl. Catal. B: Environ. 134, 198–204 (2013). \n26. Liu, X., Dong, G., Li, S., Lu, G. & Bi, Y. Direct observation of charge separation on anatase $\\mathrm{TiO}_{2}$ crystals with selectively etched {001} facets. J. Am. Chem. Soc. \n138, 2917–2920 (2016). \n27. Xu, H., Ouyang, S., Li, P., Kako, T. & Ye, J. High-active anatase $\\mathrm{TiO}_{2}$ nanosheets exposed with $95\\%$ {100} facets toward efficient $\\mathrm{H}_{2}$ evolution and $\\mathrm{CO}_{2}$ photoreduction. ACS Appl. Mater. Interfaces 5, 1348–1354 (2013). \n28. Tian, F., Zhang, Y., Zhang, J. & Pan, C. Raman Spectroscopy: A new approach to measure the percentage of anatase $\\mathrm{TiO}_{2}$ exposed (001) facets. J. Phys. Chem. C. 116, 7515–7519 (2012). \n29. Jun, Y. et al. surfactant-assisted elimination of a high energy facet as a means of controlling the shapes of $\\mathrm{TiO}_{2}$ nanocrystals. J. Am. Chem. Soc. 125, \n15981–15985 (2003). \n30. Wu, N. et al. Shape-enhanced photocatalytic activity of single-crystalline anatase $\\mathrm{TiO}_{2}$ (101) nanobelts. J. Am. Chem. Soc. 132, 6679–6685 (2010). \n31. Yang, Q. et al. Do zinc dendrites exist in neutral zinc batteries: a developed electrohealing strategy to in situ rescue in-service batteries. Adv. Mater. 31, 1903778 (2019). \n32. Zhang, Q. et al. A facile annealing strategy for achieving in situ controllable $\\mathrm{Cu}_{2}\\mathrm{O}$ nanoparticle decorated copper foil as a current collector for stable lithium metal anodes. $J.$ Mater. Chem. A 6, 18444–18448 (2018). \n33. Zhang, C. et al. A $\\mathrm{{ZnCl}}_{2}$ water-in-salt electrolyte for a reversible Zn metal anode. Chem. Commun. 54, 14097–14099 (2018). \n34. Xie, X. et al. Manipulating the ion-transfer kinetics and interface stability for high-performance zinc metal anodes. Energy Environ. Sci. 13, 503–510 (2020). \n35. Zuo, T. et al. Graphitized carbon fibers as multifunctional 3D current collectors for high areal capacity Li anodes. Adv. Mater. 29, 1700389 (2017). \n\n# Acknowledgements \n\nThis research was financially supported by the National Nature Science Foundation of China (No. 21975289), Hunan Provincial Research and Development Plan in Key Areas (2019GK2033) and Hunan Provincial Science and Technology Plan Project of China (No. 2017TP1001 and No. 2018RS3009). \n\n# Author contributions \n\nH.W. designed the experiment and participated in the analysis of results and in discussing and writing the paper. Q.Z. participated in the experimental design, synthesized the samples, carried out the characterizations and wrote the manuscript. Y.T. provided valuable advice and participated in helpful discussions. X.H and D.S. analyzed the data and edited the paper. X.J participated in discussions on the paper. J.L and Q.W. helped to characterize the materials. All authors have read and approved the final paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-17752-x. \n\nCorrespondence and requests for materials should be addressed to H.W. \n\nPeer review information Nature Communications thanks Seung-Tae Hong, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, \ndistribution and reproduction in any medium or format, as long as you give appropriate \ncredit to the original author(s) and the source, provide a link to the Creative Commons \nlicense, and indicate if changes were made. The images or other third party material in \nthis article are included in the article’s Creative Commons license, unless indicated \notherwise in a credit line to the material. If material is not included in the article’s Creative \nCommons license and your intended use is not permitted by statutory regulation or \nexceeds the permitted use, you will need to obtain permission directly from the copyright \nholder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. " + }, + { + "id": "10.1038_s41929-020-00525-6", + "DOI": "10.1038/s41929-020-00525-6", + "DOI Link": "http://dx.doi.org/10.1038/s41929-020-00525-6", + "Relative Dir Path": "mds/10.1038_s41929-020-00525-6", + "Article Title": "High-valence metals improve oxygen evolution reaction performance by modulating 3dmetal oxidation cycle energetics", + "Authors": "Zhang, B; Wang, L; Cao, Z; Kozlov, SM; de Arquer, FPG; Dinh, CT; Li, J; Wang, ZY; Zheng, XL; Zhang, LS; Wen, YZ; Voznyy, O; Comin, R; De Luna, P; Regier, T; Bi, WL; Alp, EE; Pao, CW; Zheng, LR; Hu, YF; Ji, YJ; Li, YY; Zhang, Y; Cavallo, L; Peng, HS; Sargent, EH", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Multimetal oxyhydroxides have recently been reported that outperform noble metal catalysts for oxygen evolution reaction (OER). In such 3d-metal-based catalysts, the oxidation cycle of 3dmetals has been posited to act as the OER thermodynamic-limiting process; however, further tuning of its energetics is challenging due to similarities among the electronic structures of neighbouring 3dmetal modulators. Here we report a strategy to reprogram the Fe, Co and Ni oxidation cycles by incorporating high-valence transition-metal modulators X (X = W, Mo, Nb, Ta, Re and MoW). We use in situ and ex situ soft and hard X-ray absorption spectroscopies to characterize the oxidation transition in modulated NiFeX and FeCoX oxyhydroxide catalysts, and conclude that the lower OER overpotential is facilitated by the readier oxidation transition of 3dmetals enabled by high-valence modulators. We report an similar to 17-fold mass activity enhancement compared with that for the OER catalysts widely employed in industrial water-splitting electrolysers.", + "Times Cited, WoS Core": 521, + "Times Cited, All Databases": 537, + "Publication Year": 2020, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000579724100002", + "Markdown": "# High-valence metals improve oxygen evolution reaction performance by modulating 3d metal oxidation cycle energetics \n\nBo Zhang   1,12 ✉, Lie Wang   1,12, Zhen $\\mathsf{C a o}^{2,12}$ , Sergey M. Kozlov $\\textcircled{10}2$ , F. Pelayo García de Arquer3, Cao Thang Dinh $\\textcircled{10}3$ , Jun Li4, Ziyun Wang $\\textcircled{10}3$ , Xueli Zheng $\\textcircled{10}3$ , Longsheng Zhang1, Yunzhou Wen $\\textcircled{10}$ 1, Oleksandr Voznyy $\\oplus3$ , Riccardo Comin3, Phil De Luna $\\oplus3$ , Tom Regier5, Wenli $B i^{6}$ , E. Ercan Alp   7, Chih-Wen Pao8, Lirong Zheng9, Yongfeng ${\\sf H}{\\sf u}^{5}$ , Yujin Ji $\\textcircled{10}10$ , Youyong Li $\\textcircled{1}$ 10, Ye Zhang11, Luigi Cavallo   2 ✉, Huisheng Peng $\\oplus1\\boxtimes$ and Edward H. Sargent   3 ✉ \n\nMultimetal oxyhydroxides have recently been reported that outperform noble metal catalysts for oxygen evolution reaction (OER). In such $3d\\cdot$ -metal-based catalysts, the oxidation cycle of 3d metals has been posited to act as the OER thermodynamic-limiting process; however, further tuning of its energetics is challenging due to similarities among the electronic structures of neighbouring 3d metal modulators. Here we report a strategy to reprogram the Fe, Co and Ni oxidation cycles by incorporating high-valence transition-metal modulators X $\\mathbf{(}\\mathbf{X}\\mathbf{=}\\mathbf{W},$ Mo, $\\mathbb{M}\\boldsymbol{\\mathbf{b}},$ Ta, Re and MoW). We use in situ and ex situ soft and hard $\\pmb{\\ x}$ -ray absorption spectroscopies to characterize the oxidation transition in modulated NiFeX and FeCoX oxyhydroxide catalysts, and conclude that the lower OER overpotential is facilitated by the readier oxidation transition of 3d metals enabled by high-valence modulators. We report an \\~17-fold mass activity enhancement compared with that for the OER catalysts widely employed in industrial water-splitting electrolysers. \n\nhe oxygen evolution reaction (OER), used at the anodic side in hydrogen evolution and carbon dioxide reduction systems, suffers from an excess voltage (overpotential) relative to that mandated by the thermodynamic value of the products1–9. Since the cost of renewable electricity will dominate the cost of renewable fuel production10, lowering the overpotentials contributes to lowering the cost of producing synthetic fuels11. \n\nFirst-row $(3d)$ transition-metal oxides are promising electrocatalysts for OER and are used in commercial electrolysers6,9,12–15. The catalytic performance of multimetal oxyhydroxides consisting of $3d$ transition metals is improved by introducing additional elements that affect the electronic structure of the catalyst as a whole16–20, influencing the adsorption energies of intermediate species. This strategy was employed in ternary systems such as FeCoW metal oxyhydroxide to achieve catalysts that, with optimized $\\mathrm{OH^{*}}$ , ${{\\cal O}^{*}}$ and $\\mathrm{\\Gamma_{OOH^{*}}}$ adsorption energies on the surface of the catalyst, exhibited OER performance superior to that of noble metal catalysts16. \n\nIt has been noted that in single-metal $\\upbeta$ -CoOOH frameworks, Co oxidation cycling through a $\\mathrm{Co}^{3+}/\\mathrm{Co}^{4+}$ transition is the thermodynamic-limiting process (TLP), and the largest contributor to the OER overpotential21. Modelling has predicted that facet manipulation in this framework can lead to a shift in cycling in $\\mathrm{Co}^{3+}/\\mathrm{Co}^{4+}$ towards a lower valence of $\\mathrm{Co^{2+}/C o^{3+}/C o^{4+}}$ , in turn enabling lower overpotentials21. This intriguing prediction has, however, not yet been proven in multinary $3d$ metal oxyhydroxide systems. Previous work has demonstrated the incorporation of high-valence W (ref. 22), Ta (ref. 22) and Mo (ref. 23) to stabilize the otherwise unstable low-charge $\\mathrm{Fe}^{2+}$ . \n\nHere we posit a general doping strategy: the addition of metallic dopants with high-valence charges modulate $3d$ metals (Fe, Co and Ni) towards lower energetics of valence charge transition, and hence better catalytic OER performance. We present a physical model of OER in multinary metal oxyhydroxides, screen different dopants and study the modulation of Fe, Co and Ni valence states. We synthesize and characterize, using in  situ and ex  situ X-ray absorption spectroscopy (XAS), catalysts consisting of NiFeX and FeCoX (where ${\\mathrm{X}}={\\mathrm{W}}_{:}$ Mo, Nb, Ta, Re and MoW), and find good agreement with modelling results. As a result, we report a 17-fold mass activity enhancement compared with the state-of-art catalysts in industrial hydrogen generation systems. \n\n# Results \n\nDensity functional theory (DFT) calculations. We began by building a FeCo oxyhydroxide model based on an established computational framework21 (Fig. 1 and Supplementary Fig. 1). The surface terminal groups were determined per the Pourbaix diagram (region (i) in Supplementary Fig. 2), and the trend of electronic properties of the metal atoms within the FeCoOOH model was investigated via the Bader charge and magnetization (Fig. 1a). Computational studies revealed that Co before OER exhibits a $^{\\sim3+}$ charge, leading to a $^{3+/4+}$ transition cycle during OER, corresponding to the TLP due to $\\mathrm{OH}^{*}$ formation on the catalyst surface, which agreed well with the literature21. \n\n![](images/81422c2c6baf8b94744b872124e715cefcdcc8fb4a5c0f52994d59635134a2a9.jpg) \nFig. 1 | Density functional simulation findings. a, Statistical analysis of the calculated Bader charge and magnetization obtained for Fe, Co and Ni within the oxyhydroxide framework from \\~200 different configurations. The computed relative magnetizations for each component are consistent with the values predicted from crystal field theory for an octahedral environment. The error bars were calculated as the standard deviation: ${\\sf s.d.}=\\sqrt{\\sum_{i=1}^{n}\\left(x_{i}-\\bar{x}\\right)^{2}/(n-1)}$ . b, Two-dimensional map of the overpotentials generated by assuming $\\Delta E_{\\mathrm{00H}}=E_{\\mathrm{0H}}+3.2$ (ref. 21) for different dopants in FIeCoX and NiFeX catalysts: the overpotential can be reduced significantly with the high-valence charge metals. c,d, The OER cycles for FeCoX (c) and NiFeX (d), with the terminal group determined by the Pourbaix calculations (pink, Co; orange, Fe; blue, Ni; green, high-valence metal; red, ${\\sf O};$ grey, H), and the Bader charge on the active metal site is listed. a.u., arbitrary units. \n\nIn computational studies, we doped high-valence metals into FeCo oxyhydroxides, forming FeCoX systems $\\mathrm{\\ddot{X}}=\\mathrm{Mo}$ , W, Nb, Ta and Re), and Co and Fe showed a lower charge state (see Fig. 1a, Supplementary Figs. 3 and 4 and Supplementary Table 1). The OER cycle of the FeCoX catalysts demonstrates a lower valence charge transition of the Co active site (Fig. 1c), in contrast with the conventional high-valence charge transition cycle. FeCoX systems were found to enable the lowest overpotentials for OER in this system (Fig. 1b and Supplementary Table 2). We ascribed this decrement in overpotential to the lower electron affinity of active sites in the FeCoX system compared to that of the FeCo control, which reduces the energy required to stimulate electron transfer. \n\nWe extended the model to NiFe oxyhydroxide systems using the same metal dopants (Supplementary Fig. 5), and the surface terminal groups were also determined per the Pourbaix diagram (region (i) in Supplementary Fig. 6). We found that all studied NiFeX oxyhydroxides with higher valence charge dopants induced lower oxidation states of Ni and Fe than those in the pristine NiFe oxyhydroxide controls (Fig. 1a, Supplementary Figs. 7 and 8 and Supplementary Table 1), leading to a lower charge oxidation cycling of active sites during OER and therefore decreased overpotential (Fig. 1b,d and Supplementary Table 3). \n\nBased on the fact that ${\\mathrm{X}}{=}{\\mathrm{Mo}}$ and W lead to the highest predicted activity, we further evaluated the overpotential of the quaternary metal oxyhydroxides, consisting of two best dopants together. It was found that the predicted activity can be further improved in FeCoX systems (FeCoMoW in Fig. 1b). \n\nMaterials synthesis and characterization. We sought to investigate experimentally these concepts, preparing a suite of NiFeX and FeCoX oxyhydroxides and controls. We used a room-temperature sol-gel process16; after drying in vacuum, samples in the powder form were obtained (Supplementary Fig. 9). High-resolution transmission electron microscopy (HRTEM), selected-area electron diffraction, energy-dispersive X-ray spectroscopy mapping and X-ray diffraction (XRD) (Supplementary Figs. 10–24) revealed an amorphous structure. TEM images (Supplementary Figs. 10–23) and laser particle size analysis (Supplementary Fig. 25) also show that these catalysts form agglomerated particles with sizes above $100\\mathrm{nm}$ . We further performed extended X-ray absorption fine structure characterization to evaluate the distribution of different metals. Taking the FeCoMoW sample, for example (Supplementary Fig. 26), the Mo K-edge and W $\\mathrm{L}_{3}$ -edge extended X-ray absorption fine structure and fitting results indicate that peaks associated with Mo-O-Co/Fe and W-O-Co/Fe are presented. These suggest that Mo, W and the $3d$ metal in the FeCoMoW sample were dispersed efficiently, which is in alignment with the structures we modelled, and is required to maximize the effect of modulation16. \n\n![](images/42c0f0d76f817a32376b01f2937a27be8b044267b0d157f29a72c3e02d4c30fa.jpg) \nFig. 2 | Oxidation state transition of 3d metal in modulated catalysts. a, TEY ${\\mathsf{s}}\\mathsf{X A S}$ scans of NiFe, NiFeMo and NiFeMoW at the Fe L edge. b, TEY sXAS scans of FeCo, FeCoW, and FeCoMoW at the Fe L edge. c, Concentration of $\\mathsf{F e}^{2+}$ species in all NiFeX and FeCoX samples. $\\mathsf{F e}^{2+}$ data are obtained by linear combination analysis of Fe L-edge TEY ${\\mathsf{s}}\\mathsf{X A S}$ results. d, The in situ Fe L-edge TEY ${\\mathsf{s}}\\mathsf{X A S}$ spectra of FeCo and FeCoMoW. e, The in situ Co K-edge XANES spectra of FeCo and FeCoMoW. f, In situ Ni K-edge XANES spectra of NiFe and NiFeMo. \n\nTo characterize the oxidation state of $3d$ metal atoms in these materials before OER, we carried out ex situ soft XAS (sXAS) measurements monitoring $2p$ to $3d$ transitions in the L edges of $_{3d}$ metals in total electron yield (TEY) mode, which is surface sensitive and valence sensitive24,25. NiFe and FeCo samples (Fig. 2a,b) yielded a significant amount of trivalent $\\mathrm{Fe}^{3+}$ . In contrast, NiFeMo, NiFeMoW, FeCoMo and FeCoMoW exhibited a dominant amount of ${\\mathrm{Fe}}^{2+}$ species with the main peak at $707.2\\mathrm{eV}$ and a shoulder peak at $718.7\\mathrm{eV}$ at the $\\mathrm{L}_{3}$ edge (Fig. $^{2\\mathrm{a},\\mathrm{b}}$ ). A series of time-dependent Fe L-edge XAS measurements was also performed to eliminate the possible beam damage from XAS to form the $\\mathrm{Fe}^{2+}$ (Supplementary Note 1 and Supplementary Fig. 27). Thereafter, linear combination fitting of these spectra over two reference Fe oxides (FeO for $\\mathrm{Fe}^{2+}$ and $\\mathrm{Fe(OH)}_{3}$ for $\\mathrm{Fe}^{3+}$ ) allowed us to estimate the molar ratio of ${\\mathrm{Fe}}^{2+}$ and $\\mathrm{Fe}^{3+}$ (Supplementary Figs. 28 and 29), with the results shown in Fig. $2c$ and Supplementary Table 4. The high-valence metal modulated NiFe and FeCo samples exhibited higher $\\mathrm{Fe}^{2+}$ percentages than those binary controls, in agreement with DFT predictions on the trend of oxidation states. \n\n![](images/3f709b411a8435830ed5c85c5802cacc5705232e025fa8185e39bb2ff884b114.jpg) \nFig. 3 | Performance of NiFeX and FeCoX catalysts in 1 M KOH electrolyte at $25\\circ.$ a,b, OER polarization curves of NiFeX catalysts (a) and FeCoX catalysts (b) on carbon paper measured with a $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ scan rate, with $95\\%$ iR correction. c,d, Turnover frequency trends as a function of potential for NiFeX catalysts (c) and FeCoX catalysts $(\\pmb{\\mathsf{d}})$ on carbon paper measured with a $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ scan rate, with $95\\%$ iR correction. e,f, Overpotentials at current density $10\\mathsf{m A c m}^{-2}$ tested versus $\\mathsf{F e}^{2+}$ ratio in NiFeX catalysts (e) and FeCoX catalysts (f). RHE, reversible hydrogen electrode. \n\nFurthermore, we measured the oxidation state of Fe using off-line Mössbauer spectroscopy in transmission mode for FeCoMoW (Supplementary Fig. 30) and hard XAS in Fe K-edge for NiFeMo (Supplementary Fig. 31). Both Mössbauer spectra and K-edge X-ray absorption near edge structure (XANES) results showed significant $\\mathrm{Fe}^{2+}$ . After linear combination fitting with reference samples (FeO for ${\\mathrm{Fe}}^{2+}$ and $\\mathrm{Fe(OH)}_{3}$ for $\\mathrm{Fe}^{3+},$ ), the results show a decreased ratio of $F e^{2+}\\left(11\\%\\right)$ in FeCoMoW and $\\mathrm{Fe}^{2+}$ $(20\\%)$ in NiFeMo compared to the Fe L-edge XAS results, which is a finding we ascribe to the fact that L-edge XAS is more surface sensitive than that of K-edge XAS and Mössbauer spectroscopy25,26. This suggests that the high-valence-metal modulation on $3d$ metals is more prominent on the catalyst surface, which can therefore tune the oxidation cycle energetics of $3d$ metals and the adsorption energies of intermediate species during the $\\mathrm{OER^{16}}$ . \n\nTo assess the influence of high-valence metals on the oxidation transition of $3d$ metals, we carried out in situ Fe L-edge XAS under different applied potentials. First, we applied a bias of $+1.4\\mathrm{V}$ at the OER region to oxidize all Fe atoms to $\\mathrm{Fe}^{3+}$ in both FeCoMoW and FeCo samples (Fig. 2d). When the bias was changed to $+0.6\\mathrm{V}$ (0.1 V lower than the thermodynamic equilibrium potential of $\\mathrm{Fe}^{3+}/\\mathrm{Fe}^{2+},$ , $\\mathrm{Fe}^{3+}$ in the FeCoMoW sample switched to a $+2$ oxidation state, while it did not change in the FeCo sample. This suggests that the oxidation transition of Fe occurs easier in FeCoMoW than it does in the binary control, which is consistent with DFT calculations. \n\nWe further conducted in  situ Co K-edge (Fig. 2e) and L-edge XAS (Supplementary Fig. 32). At the initial state (before the OER) of all the studied FeCo-based samples, Co is in a ${\\mathrm{Co}}^{2+}$ configuration. At oxidizing bias during the OER, $\\mathrm{Co}^{2+}$ species were fully oxidized to higher valence states in the FeCoMoW sample, but they retained a ${\\mathrm{Co}}^{\\bar{2}+}$ character in FeCo. Upon switching the applied potential from 1.5 to $1.2\\mathrm{V}$ (Supplementary Fig. 33), the oxidation state of Co changed to a low valence in the FeCoMoW sample, which did not happen in the FeCo sample. The ex situ Co L-edge XAS spectra after the OER (Supplementary Fig. 34) also showed consistent results. Furthermore, the oxidation transition of Ni in NiFe during the OER was also studied by in situ Ni K-edge XAS (Fig. 2f), and a similar conclusion was obtained. \n\nThe above XAS results indicate that the energy barriers of the oxidation transition of $3d$ metals are lower in high-valence-metal modulated systems than in binary controls. Previous studies have shown that $3d$ metal oxides with a lower oxidation barrier exhibit increased OER activities27–29. The present DFT studies also predicted that more facile oxidation transitions of $3d$ metals lead to increased OER activity. We further characterized the oxidation of high-valence metal during OER: the results indicate that the oxidation state did not change (Supplementary Note and Supplementary Fig. 35). \n\nElectrocatalytic performance. We sought then to characterize the catalytic performance of the series of NiFeX and FeCoX oxyhydroxides in the three-electrode configuration in 1 M KOH electrolytes at room temperature (see Methods). As shown in Fig. 3, NiFeX and FeCoX exhibit lower overpotentials at $10\\mathrm{mAcm}^{2}$ , an improvement of $37\\mathrm{mV}$ and $54\\mathrm{mV}$ compared with those of NiFe and FeCo catalysts, respectively (Supplementary Table 4). When compared with previous reports under the same testing conditions30, the overpotential of NiFeMo is only $180\\mathrm{mV}$ at $10\\mathrm{\\mA}\\mathrm{cm}^{2}$ (Supplementary Fig. 36). \n\n![](images/7a5f7bb8fcc7f27024ed94f854fb624e87e07995ab1b5a69f45017ed6c81a10d.jpg) \nFig. 4 | Performance of NiFeMo catalysts in industrial electrolyser systems. a, Photograph of an industrial electrolyser device. b, Enlarged view of the industrial electrolyser. c, Schematic illustration of the structure of an electrolyser cell. d, Polarization curves measured during water electrolysis using a NiFeMo electrode (red) and a commercial Raney Ni electrode (blue) as an anode, respectively, and a commercial Ru electrode as a cathode. e, The cell voltage of the electrolyser held at $300\\mathsf{m A c m}^{-2}$ for $12\\mathsf{h}$ at $80-85^{\\circ}C$ and $2M P a$ . \n\nTo challenge further the posited link between ${\\mathrm{Fe}}^{2+}$ and the catalytic performance for OER, we varied the composition and checked the relative concentrations of $\\mathrm{Fe}^{2+}$ in each sample obtained using Fe L-edge XAS in TEY mode. For NiFe-based catalysts, the NiFeMo, NiFeW, NiFeNb, NiFeTa, NiFeRe and NiFeMoW exhibited significantly higher $\\mathrm{Fe}^{2+}$ ratio than that of the NiFe control, in agreement with the simulation results (Figs. 1 and 3e). For FeCo-based catalysts, a higher ratio of ${\\mathrm{Fe}}^{2+}$ led to lower overpotentials (Figs. 1 and 3f). Note that, although the catalysts with a higher $\\mathrm{Fe}^{2+}$ content result in lower overpotentials, the correlation is not perfect and there are some exceptions. In addition, a possible correlation between the dopants’ covalent radii and performance was also investigated, and no clear correlation was found (Supplementary Fig. 37). \n\nTo distinguish the effects of catalyst surface area versus intrinsic performance, we investigated the turnover frequencies (TOFs). We used data obtained in $1\\mathrm{M}\\ \\mathrm{KOH}$ electrolyte at room temperature with $95\\%$ iR correction (where $i$ is current measured and $R$ is resistance) at different potentials to calculate TOFs. NiFeMoW and FeCoMoW outperform control samples, exhibiting approximately \n\n17 times and 21 times higher TOFs than binary NiFe and FeCo controls at $300\\mathrm{mV}$ overpotential, respectively (Fig. 3c,d). \n\nPerformance under industrial conditions. We also carried out the same testing under industrial conditions ( $30\\%$ KOH and at $85^{\\circ}\\mathrm{C})$ ), and observed trends that are consistent with those reported above (Supplementary Fig. 38). The corresponding mass activities of the NiFeX and FeCoX based on the total loading mass of the ternary and quaternary oxides are enhanced compared with the NiFe and FeCo controls (Supplementary Fig. 39). To characterize performance stability, we carried out water electrolysis by using NiFeMo catalysts and a commercial $\\mathtt{R u}$ electrode as anode and cathode, respectively. The resultant electrolyser delivered $300\\mathrm{mAcm}^{-2}$ at ${\\sim}1.7\\mathrm{V}$ consistently over $120\\mathrm{h}$ (Supplementary Fig. 40), indicating high stability of the catalysts. We also carried out water oxidation by cyclic voltammetry measurements at $50\\mathrm{mV}s^{-1}$ , and observed no appreciable decrease in the current densities over 2,000 cycles (Supplementary Fig. 41). To assess the performance of the catalysts on an industrial scale, we implemented these in industrial hydrogen generation systems (Fig. 4a). The central part of the system is the electrolyser (Fig. $^\\mathrm{4b,c,\\cdot}$ ). Under various applied cell potentials, the current densities (normalized by loading mass) of the cell with the NiFeMo electrode are 17 times higher than the cell with a commercial Raney Ni electrode (Fig. 4d). When compared at identical current density, NiFeMo also exhibits a lower cell voltage compared with Raney Ni catalysts. We observed no appreciable increase in the cell voltage during initial studies of $12\\mathrm{-h}$ continuous operation (Fig. 4e). \n\n# Conclusions \n\nIn summary, this work describes how the incorporation of high-valence metal modulators promotes the catalytic activity of multinary 3d metal compounds for OER. We offer a picture wherein the modulators lower the oxidation states of surface active sites (for example, Fe, Co and Ni) within their respective oxidation cycles. A synthetic route that seeks the homogeneous addition of such dopants, which is an approach based on a sol-gel process, enables charge redistribution across the catalyst. This allows the oxidation cycle of Fe, Co and Ni sites to be optimized, under OER operation, towards a more energetically favoured rate-limiting process. In situ and ex situ X-ray absorption spectroscopies suggest that $\\mathrm{Fe}^{2+}$ facilitates the cycling of Ni and Co species between $^{2+}$ and $^{3+}$ oxidation states. The NiFeMo was used in the industrial electrolyser system and exhibited ${\\sim}17$ times higher mass activity than commercial Raney Ni catalysts. \n\n# Methods \n\nDensity functional simulations. We used the VASP package to perform simulations with the revised Perdew–Burke–Ernzerhof exchange correlation functional augmented with Hubbard Coulomb interaction potential (U) corrections for $d$ -electrons taken from Materials project (https://materialsproject. org) $\\prime U({\\mathrm{Fe}})=5.3{\\mathrm{eV}},$ $U({\\mathrm{Mo}}){=}4.38\\mathrm{eV},$ , $U(\\mathrm{W}){=}6.2\\mathrm{eV},$ $U({\\mathrm{Co}}){=}3.32\\mathrm{eV},$ $U(\\mathrm{Ta}){=}2.3\\mathrm{eV}$ , $U({\\mathrm{Re}})=2.7\\mathrm{eV},$ , $U({\\mathrm{Nb}}){=}1.3\\mathrm{eV},$ ). Valence electrons were described with a $400–\\mathrm{eV}$ plane-wave basis set and $0.05\\mathrm{-}\\mathrm{eV}$ Gaussian smearing of electronic density. Core electrons were described using the projector augmented-wave (PAW) method. We calculated 50 different spin states for each configuration and the discussion is based on the states that yield the lowest electronic energies. The employed slabs for FeCoX systems were constructed based on a six-layer supercell of CoOOH with lateral dimensions of $5.77\\times9.31\\mathrm{\\AA}^{2}$ . The reciprocal space was simulated using a $3\\times3\\:k$ -point mesh. The employed slabs for NiFeX systems were constructed based on a six-layer supercell of NiFeOOH with lateral dimensions of $6.147\\times12.459\\mathring{\\mathrm{A}}^{2}$ . The reciprocal space was simulated using a $4\\times2\\:k$ -point mesh. The thermodynamic corrections to electronic energies were taken from the literature16. The optimized models can be found in Supplementary Data 1. \n\nPourbaix diagram calculations. Using the constructed model, we provided a systematic Pourbaix diagram calculation including over 3,000 structural optimizations. We demonstrated surface coverage and the terminal groups for both FeCo and NiFe oxyhydroxides. For each type of oxyhydroxide, we counted the possible surface terminal groups, including the empty site, O-terminated and OH-terminated groups. For each configuration, we used $\\mathrm{JSPIN}=2$ in the VASP package to relax the magnetization. We then tested 50 different spin states near the relaxed magnetization using NUPDOWN in the VASP package and chose the configuration with the lowest energy. For instance, if the $\\mathrm{JSPIN}=2$ calculation gave magnetization $=70$ , we re-made the optimization using all the 51 possibilities NUPDOWN $\\in$ [45, 95]. In total, the Pourbaix diagram was obtained through 6,630 calculations. The applied voltage corrections and $\\mathrm{\\DeltapH}$ corrections were performed using the following equation: \n\n$$\n\\Delta G_{\\mathrm{corr}}=\\Delta G-e U-0.059\\mathrm{pH}\n$$ \n\nwhere $U$ is the applied voltage and $e$ is the electron transferred during the electrochemical reaction. The pH variation can be evaluated using the following chemical equation: \n\n$$\n\\begin{array}{l}{{{\\mathrm{}^{*}+\\mathrm{H}_{2}\\mathrm{O}\\rightarrow\\mathrm{O}^{*}+2\\mathrm{H}^{+}+2\\mathrm{e}^{-}}}}\\\\ {{{}}}\\\\ {{{\\mathrm{}^{*}+\\mathrm{H}_{2}\\mathrm{O}\\rightarrow\\mathrm{OH}^{*}+\\mathrm{H}^{+}+\\mathrm{e}^{-}}}}\\end{array}\n$$ \n\nThe Pourbaix diagram calculation was made to obtain the surface coverage and the terminal groups for both FeCoX oxyhydroxides and NiFeX oxyhydroxides. The related results are provided as Supplementary Figs. 2 and 6 for the FeCo and NiFe systems, respectively. \n\nChemicals. Iron (iii) chloride $\\mathrm{(FeCl_{3})}$ , cobalt (ii) chloride $\\mathrm{(CoCl_{2})}$ , nickel chloride $(\\mathrm{NiCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}),$ ), tungsten (vi) chloride $\\mathrm{(WCl}_{6})$ , molybdenum (v) chloride $(\\mathrm{MoCl}_{5})$ , Niobium chloride $(\\mathrm{Nb}{\\mathrm{Cl}}_{5})$ , Tantalum chloride $(\\mathrm{TaCl}_{5})$ , Rhenium chloride $(\\mathrm{ReCl}_{5})$ , ethanol $(\\geq99.5\\%)$ and propylene oxide $(\\geq99\\%)$ were purchased from Sigma-Aldrich. $^{57}\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ for preparing $^{57}\\mathrm{FeCl}_{3}$ was bought from Cyclotron Instruments. All the chemicals were used without further purification. \n\nSynthesis of multimetal oxyhydroxides. All multimetal oxyhydroxides were synthesized using a modified aqueous sol-gel technique16. For every ternary mutltimetal oxyhydroxide, the molar ratio of its three metal chloride precursors was 1:1:1. Taking NiFeMo, for example, ${\\mathrm{NiCl}}_{2}{\\cdot}6{\\mathrm{H}}_{2}\\mathrm{O}$ $0.9\\mathrm{mmol};$ , anhydrous $\\mathrm{FeCl}_{3}$ $\\left(0.9\\mathrm{mmol}\\right)$ and $\\mathrm{\\:MoCl_{5}}$ ( $\\mathrm{(0.9mmol)}$ were first dissolved in ethanol $\\mathrm{(4ml)}$ in a vial. Then a trace amount of deionized water $\\left(0.21\\mathrm{ml}\\right)$ with ethanol $(2\\mathrm{ml})$ was prepared in another vial. After chilling, the solutions were mixed and propylene oxide $(1\\mathrm{ml})$ was slowly added to the mixed solution. Thereafter, a wet gel was formed. The wet gel was aged for $24\\mathrm{h}$ and soaked in acetone for another 5 days. Then the wet gel was dried in a vacuum or with supercritical $\\mathrm{CO}_{2}$ at room temperature. For the FeCoMoW or NiFeMoW samples, anhydrous $\\mathrm{FeCl}_{3}$ $\\mathrm{0.7mmol}$ ), $\\mathrm{CoCl}_{2}$ or ${\\mathrm{NiCl}}_{2}{\\cdot}6{\\mathrm{H}}_{2}\\mathrm{O}$ $\\mathrm{(0.7mmol)}$ ), $\\mathbf{MoCl}_{5}$ $\\mathrm{0.7mmol)}$ and $\\mathrm{wCl}_{6}$ ( $0.7\\mathrm{mmol}\\cdot$ were dissolved in ethanol $\\mathrm{(4ml)}$ in a vial. The remainder of the procedure was the same. FeCo, NiFe and other ternary oxyhydroxides were synthesized following a process similar to that for NiFeMo oxyhydroxides. \n\nSynthesis of multimetal oxyhydroxides containing $^{57}\\mathbf{Fe}$ . $^{57}\\mathrm{FeCl}_{3}$ was firstly prepared by dissolving $^{57}\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ in excess concentrated hydrochloric acid solution. Then the clear orange solution was evaporated via vacuum distillation until the slurry was formed, which was dissolved in ethanol. The remaining steps were the same as above. \n\nCharacterization. High-resolution transmission electron microscopy, selected-area electron diffraction and energy-dispersive X-ray spectroscopy were carried out using a Hitachi HF3300 electron microscope at an accelerating voltage of $200\\mathrm{kV}.$ The samples were prepared by dropping catalyst powder dispersed in ethanol onto carbon-coated copper TEM grids (Ted Pella) using micropipettes, which were then dried under ambient conditions. The powder XRD patterns were measured on a Bruker D8 Advance spectrometer. \n\nXAS measurements. Ex situ sXAS measurements were performed at the Spherical Grating Monochromator (SGM) beamline of the Canadian Light Source, the BL08U1-A beamlines at Shanghai Synchrotron Radiation Facility and the 4B9B beamline of Beijing Synchrotron Radiation Facility. All samples were scanned from 700 to $735\\mathrm{eV}$ in $0.1\\mathrm{eV}$ steps for the Fe $\\mathrm{L}_{2}$ and $\\mathrm{~L}_{3}$ absorption edges and from 765 to $820\\mathrm{eV}$ in $0.1\\mathrm{eV}$ steps for the $\\mathrm{CoL}_{2}$ and $\\mathrm{L}_{3}$ absorption edges. Surface-sensitive absorption spectra were recorded using TEY. \n\nIn situ sXAS measurements were performed at the SGM beamline of the Canadian Light Source. The window of the sample cells was mounted at an angle of roughly $45^{\\circ}$ with respect to both the incident beam and the detectors. All measurements were made at room temperature in the fluorescence mode using Amptek silicon drift detectors (SDDs) with 1,024 emission channels (energy resolution ${\\sim}120\\mathrm{eV}.$ ). Four SDDs were employed simultaneously. For every edge, the scanning time was $30s$ and the scans were repeated ten times, and the fluorescence of every edge was collected at the same absorption edge. The partial fluorescence yield was extracted from all SDDs by the summation of the corresponding metal L emission lines. \n\nIn situ and ex situ hard XAS measurements were performed at the 1W1B beamline of the Beijing Synchrotron Radiation Facility, the BL14W1 beamline at the Shanghai Synchrotron Radiation Facility, the SuperXAS beamline at the Swiss Light Source and the Taiwan Photon Source 44A beamline. The in situ experiment was conducted in a homemade triangular electrochemical cell, and working electrodes were prepared by loading catalyst samples on carbon paper. The spectra were obtained from 8.1 to $9.1\\mathrm{keV}$ for $\\mathrm{NiK}$ -edge XAS, 6.8 to $7.7\\mathrm{keV}$ for Fe K-edge XAS, 7.5 to $8.6\\mathrm{keV}$ for Co K-edge XAS, 19.8 to $20.8\\mathrm{keV}$ for Mo K-edge XAS, 10.0 to $11.0\\mathrm{keV}$ for W $\\mathrm{L}_{3}$ -edge XAS and at $0.5\\mathrm{eV}$ steps at the near edge. \n\nMössbauer spectroscopy measurements. The Mössbauer experiments were carried out using an off-line Mössbauer spectrometer in APS Mössbauer Laboratory (Advanced Photon Sources, Argonne National Laboratory) using a $^{57}\\mathrm{Co}$ source, and not a synchrotron radiation source. The $^{57}\\mathrm{Co}$ source at the APS Mössbauer Laboratory was $10\\mathrm{mCi}$ and it was newly purchased. Data analysis was conducted using in-house software. \n\nElectrochemical measurements. Electrochemical measurements were performed using a three-electrode configuration connected to Autolab PGSTAT302N and PGSTAT204N. The working electrode was carbon paper (TGP-H-060, TORAY) or Ni foam (thickness, $1.8\\mathrm{mm}$ ). $\\mathrm{Hg/HgO}$ and platinum plates were used as reference and counter electrodes, respectively. To load the catalyst on the working electrode, $10\\mathrm{mg}$ of catalyst was dispersed in $\\mathrm{1ml}$ of ethanol, followed by the addition of ${80\\upmu\\mathrm{l}}$ of Nafion solution. The suspension was sonicated for $30\\mathrm{min}$ to prepare a homogeneous ink. The catalytic electrode was prepared by spray coating the catalyst ink on carbon paper or Ni foam with a loading mass of about $1.67\\mathrm{mgcm}^{-2}$ . The area of the catalytic electrode was fixed to $0.5\\times0.{\\bar{5}}{\\mathrm{cm}}^{2}$ by coating with \n\npolyimide tape or water-resistant silicone glue for electrochemical testing. Cyclic voltammetry measurements at $50\\mathrm{mVs^{-1}}$ were performed for three cycles before the recording of linear scan voltammetry at $5\\mathrm{mVs^{-1}}$ for each sample. \n\nThe performances tested under industrial conditions (Supplementary Figs. 26–29) were done on Ni foam at $30\\%$ KOH solution with a temperature of $85\\pm1^{\\circ}\\mathrm{C}$ . The industrial-scale measurements were performed using an electrolyser at the Purification Equipment Research Institute of CSIC, China (http://www. peric718.com/Home/). A $10\\times10.5\\mathrm{cm}^{2}$ NiFeMo electrode and commercial Ru electrode were used as anode and cathode, respectively. A commercial Raney Ni electrode was used as a control. \n\nWe used electrochemical impedance spectroscopy to determine the uncompensated resistance (R). The resistance values were $2.3\\Omega$ for NiFe, $2.4\\Omega$ for NiFeMo, $2.4\\Omega$ for NiFeW, $2.1\\Omega$ for NiFeTa, $2.6\\Omega$ for NiFeNb, $2.8\\Omega$ for NiFeRe, $2.4\\Omega$ for NiFeMoW, $2.5\\Omega$ for FeCo, $2.7\\Omega$ for FeCoW, $2.3\\Omega$ for FeCoMo, $2.2\\Omega$ for FeCoTa, $2.4\\Omega$ for FeCoNb, $2.6\\Omega$ for FeCoRe and $2.1\\Omega$ for FeCoMoW on carbon paper electrode. The resistance values were $0.37\\Omega$ for NiFe, $0.38\\Omega$ for NiFeMo, $0.37\\Omega$ for NiFeW, $0.35\\Omega$ for NiFeTa, $0.34\\Omega$ for NiFeNb, $0.36\\Omega$ for NiFeRe, $0.35\\Omega$ for NiFeMoW, $0.39\\Omega$ for FeCo, $0.37\\Omega$ for FeCoW, $0.36\\Omega$ for FeCoMo, $0.35\\Omega$ for FeCoTa, $0.36\\Omega$ for FeCoNb, $0.35\\Omega$ for FeCoRe and $0.36\\Omega$ for FeCoMoW on Ni foam electrode. At all potentials tested on carbon paper and Ni foam electrodes, the potential was manually corrected using Ohm’s law: \n\n$$\nE=E_{\\mathrm{applied}}-95\\%i R\n$$ \n\nwhere $E_{\\mathrm{applied}}$ is applied potential, i is the current measured and there is compensation for $95\\%$ of the resistance $R$ . \n\nTOF calculations. TOF is defined as the frequency of the reaction per active site, which is used to compare the intrinsic activity of different catalysts. For OER, the TOF value is usually calculated by the equation: \n\n$$\n\\mathrm{TOF}=\\frac{\\mathrm{j}\\times\\mathrm{A}\\times\\eta}{4\\times\\mathrm{F}\\times\\mathrm{n}}\n$$ \n\nwhere $j$ is the current density after $95\\%$ iR compensation, $A$ is the geometric area of the electrode, $\\eta$ is the Faradic efficiency, $F$ is Faraday’s constant and $n$ is the molar number of active sites. In our study, we assumed Ni and Co as active sites for NiFeX and FeCoX catalysts, and the number $n$ was estimated via the total loading mass, according to the equation: \n\n$$\nn={\\frac{m\\times N_{\\mathrm{A}}}{M_{\\mathrm{w}}}}\n$$ \n\nwhere $m$ is the loading mass, $N_{A}$ is Avogadro’s constant and $M_{\\mathrm{w}}$ is the molecular weight of the catalysts. \n\n# Data availability \n\nThe data that support the findings of this study are available on the Zenodo platform (https://zenodo.org/record/4008830) (ref. 31). \n\nReceived: 16 February 2019; Accepted: 15 September 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Zhang, J., Zhao, Z., Xia, Z. & Dai, L. A metal-free bifunctional electrocatalys for oxygen reduction and oxygen evolution reactions. Nat. Nano. 10, 444–452 (2015). \n2.\t Ng, J. W. D. et al. Gold-supported cerium-doped NiOx catalysts for water oxidation. Nat. Energy 1, 16053 (2016). \n3.\t Liang, Y. et  al. $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocrystals on graphene as a synergistic catalyst for oxygen reduction reaction. Nat. Mater. 10, 780–786 (2011). \n4.\t Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: Insights into materials design. Science 355, eaad4998 (2017). \n5.\t Seitz, L. C. et al. A highly active and stable $\\mathrm{IrO}_{\\scriptscriptstyle x}/\\mathrm{SrIrO}_{\\scriptscriptstyle3}$ catalyst for the oxygen evolution reaction. Science 353, 1011–1014 (2016). \n6.\t Bergmann, A. et al. Unified structural motifs of the catalytically active state of Co(oxyhydr)oxides during the electrochemical oxygen evolution reaction. Nat. Catal. 1, 711–719 (2018). \n7.\t Guan, J. et al. Water oxidation on a mononuclear manganese heterogeneous catalyst. Nat. Catal. 1, 870–877 (2018). \n8.\t Martin-Sabi, M. et al. Redox tuning the Weakley-type polyoxometalate archetype for the oxygen evolution reaction. Nat. Catal. 1, 208–213 (2018). \n9.\t Roy, C. et al. Impact of nanoparticle size and lattice oxygen on water oxidation on ${\\mathrm{NiFeO}}_{x}{\\mathrm{H}}_{y}$ . Nat. Catal. 1, 820–829 (2018). \n10.\tJouny, M., Luc, W. & Jiao, F. High-rate electroreduction of carbon monoxide to multi-carbon products. Nat. Catal. 1, 748–755 (2018). \n11.\tJouny, M., Luc, W. & Jiao, F. General Techno-Economic analysis of $\\mathrm{CO}_{2}$ electrolysis systems. Ind. Eng. Chem. Res. 57, 2165–2177 (2018). \n12.\tGalán-Mascarós, J. R. Water oxidation at electrodes modified with earth-abundant transition-metal catalysts. ChemElectroChem 2, 37–50 (2015). \n13.\tSubbaraman, R. et al. Trends in activity for the water electrolyser reactions on 3d M(Ni,Co,Fe,Mn) hydr(oxy)oxide catalysts. Nat. Mater. 11, 550–557 (2012). \n14.\tRoger, I., Shipman, M. A. & Symes, M. D. Earth-abundant catalysts for electrochemical and photoelectrochemical water splitting. Nat. Rev. Chem. 1, 0003 (2017). \n15.\tFabbri, E. et al. Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting. Nat. Mater. 16, 925–931 (2017). \n16.\tZhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n17.\tRosalbino, F., Delsante, S., Borzone, G. & Scavino, G. Electrocatalytic activity of crystalline Ni–Co–M ( $\\mathbf{\\dot{M}}=\\mathbf{Cr},$ Mn, Cu) alloys on the oxygen evolution reaction in an alkaline environment. Int. J. Hydrog. Energy 38, 10170–10177 (2013). \n18.\t Chen, J. Y. C., Miller, J. T., Gerken, J. B. & Stahl, S. S. Inverse spinel NiFeAlO $\\mathsf{I}_{4}$ as a highly active oxygen evolution electrocatalyst: promotion of activity by a redox-inert metal ion. Energy Environ. Sci. 7, 1382–1386 (2014). \n19.\t Gerken, J. B., Shaner, S. E., Masse, R. C., Porubsky, N. J. & Stahl, S. S. A survey of diverse earth abundant oxygen evolution electrocatalysts showing enhanced activity from Ni-Fe oxides containing a third metal. Energy Environ. Sci. 7, 2376–2382 (2014). \n20.\tFriebel, D. et al. Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting. J. Am. Chem. Soc. 137, 1305–1313 (2015). \n21.\t Bajdich, M., García-Mota, M., Vojvodic, A., Nørskov, J. K. & Bell, A. T. Theoretical investigation of the activity of cobalt oxides for the electrochemical oxidation of water. J. Am. Chem. Soc. 135, 13521–13530 (2013). \n22.\tNovák, M. et al. Primary oxide minerals in the system $\\mathrm{WO}_{3}–\\mathrm{Nb}_{2}\\mathrm{O}5–\\mathrm{TiO}_{2}–$ $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ –FeO and their breakdown products from the pegmatite No. 3 at Dolní Bory-Hatě, Czech Republic. Eur. J. Mineral. 20, 487–499 (2008). \n23.\tKuepper, K. et al. Electronic and magnetic properties of highly ordered $\\mathrm{Sr}_{2}\\mathrm{FeMoO}_{6}.$ . Phys. Stat. Sol. (a) 201, 3252–3256 (2004). \n24.\tLiu, X., Yang, W. & Liu, Z. Recent progress on synchrotron-based in-situ soft X-ray spectroscopy for energy materials. Adv. Mater. 26, 7710–7729 (2014). \n25.\tde Groot, F. M. F. et al. 1s2p resonant inelastic X-ray scattering of iron oxides. J. Phys. Chem. B 109, 20751–20762 (2005). \n26.\tMitsui, T. in Magmas Under Pressure (eds Kono, Y. & Sanloup, C.) 179–210 (Elsevier, 2018). \n27.\tZheng, X. et al. Theory-driven design of high-valence metal sites for water oxidation confirmed using in situ soft X-ray absorption. Nat. Chem. 10, 149–154 (2018). \n28.\t Liu, P. F., Yang, S., Zheng, L. R., Zhang, B. & Yang, H. G. ${\\mathrm{Mo}}6+$ activated multimetal oxygen-evolving catalysts. Chem. Sci. 8, 3484–3488 (2017). \n29.\tLiu, P. F., Yang, S., Zheng, L. R., Zhang, B. & Yang, H. G. Electrochemical etching of α-cobalt hydroxide for improvement of oxygen evolution reaction. J. Mater. Chem. A 4, 9578–9584 (2016). \n30.\tQiu, Z., Tai, C.-W., Niklasson, G. A. & Edvinsson, T. Direct observation of active catalyst surface phases and the effect of dynamic self-optimization in NiFe-layered double hydroxides for alkaline water splitting. Energy Environ. Sci. 12, 572–581 (2019). \n31.\tZhang, B. et al. High-valence metals improve OER performance by modulating 3d metal oxidation cycle energetics. Zenodo Digital Repository https://doi.org/10.5281/zenodo.4008830 (2020). \n\n# Acknowledgements \n\nThis work was supported by MOST (grant no. 2016YFA0203302), NSFC (grant nos. 21875042, 21634003 and 51573027), STCSM (grant nos. 16JC1400702 and 18QA1400800), SHMEC (grant no. 2017-01-07-00-07-E00062) and Yanchang Petroleum Group. This work was also supported by The Programme for Professor of Eastern Scholar at Shanghai Institutions of Higher Learning. This work was supported by the Ontario Research Fund—Research Excellence Program, NSERC and the CIFAR Bio-Inspired Solar Energy program. This work has also benefited from the use of the SGM beamlines at Canadian Light Source; the 1W1B and 4B9B beamlines at the Beijing Synchrotron Radiation Facility; the BL14W1, BL08U1-A beamline at Shanghai Synchrotron Radiation Facility; and the 44A beamline at Taiwan Photon Source (TPS). Mössbauer spectroscopy measurements were conducted at the Advanced Photon Source, a Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract DE-AC02-06CH11357. We acknowledge the Paul Scherrer Institut, Villigen, Switzerland, for provision of synchrotron radiation beamtime at the beamline SuperXAS of the SLS and would like to thank M. Nachtegaal for assistance. We thank M. García-Melchor and Y. Zhang for discussions on DFT calculations. We thank J. Wu for the assistance with the TEM measurements. We thank R. Wolowiec and D. Kopilovic for their assistance. For computer time, this research used the resources of the Supercomputing Laboratory at KAUST. \n\n# Author contributions \n\nE.H.S., H.P., B.Z. and L.C. supervised the project. B.Z. designed the project. L.W. and B.Z. carried out the experiments. Z.C., S.M.K. and Z.W. carried out the DFT simulations. L.W., X.Z., L. Zhang, Y.W., C.W.P., L. Zheng and J.L. carried out XAS measurements. \n\nT.R. assisted in situ XAS experiments. L.W., F.P.G.A., R.C. and J.L. performed the XAS results analysis. O.V., Z.W. and P.D.L. assisted with the DFT simulations. W.B. and E.E.A. carried out the Mössbauer spectroscopy experiment and data analysis. C.T.D. and Y.H. contributed to discussions about the experiments. Y.J. and Y.L. contributed to the discussions about DFT simulations. Y.Z. assisted with TEM and XRD measurements. B.Z., L.W., Z.C., F.P.G.A., S.M.K., H.P. and E.H.S. wrote the manuscript. All authors discussed the results and assisted during manuscript preparation. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-020-00525-6. \n\nCorrespondence and requests for materials should be addressed to B.Z., L.C., H.P. or E.H.S. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 " + }, + { + "id": "10.1016_j.actamat.2020.07.063", + "DOI": "10.1016/j.actamat.2020.07.063", + "DOI Link": "http://dx.doi.org/10.1016/j.actamat.2020.07.063", + "Relative Dir Path": "mds/10.1016_j.actamat.2020.07.063", + "Article Title": "Origin of dislocation structures in an additively manufactured austenitic stainless steel 316L", + "Authors": "Bertsch, KM; de Bellefon, GM; Kuehl, B; Thoma, DJ", + "Source Title": "ACTA MATERIALIA", + "Abstract": "In this experiment, the origin of dislocation structures in AM stainless steels was systematically investigated by controlling the effect of thermal stress through geometric constraints for the first time. Stainless steel 316L parts were produced in the form of 1D rods, 2D walls, and 3D rectangular prisms to evaluate the effect of constraints to thermal expansion/shrinkage on the development of defect microstructures and to elucidate the origin of additively manufactured (AM) dislocation microstructures. Dislocation density, organization, chemical micro-segregation, precipitate structures, and misorientations were analyzed as a function of increasing constraints around solidifying material in 1D, 2D, and 3D components built using both directed energy deposition (DED) and powder-bed selective laser melting (SLM). In DED parts, the dislocation density was not dependent on local misorientations or micro-segregation patterns, but evolved from approximately rho(perpendicular to)approximate to 10(12) m(-)(2) in 1D parts to rho(perpendicular to) approximate to 10(14) m(-2) in 3D parts, indicating that it is primarily thermal distortions that produce AM dislocation structures. In DED 3D parts and SLM parts, dislocation densities were highest (rho(perpendicular to) approximate to 10(14) m(-2)) and corresponded to the formation of dislocation cells approximately 300-450 nm in diameter. Dislocation cells overlapped with dendrite micro-segregation in some but not all cases. The results illustrate that dendritic micro-segregation, precipitates, or local misorientations influence how the dislocations organize during processing, but are not responsible for producing the organized cell structures. This work shows that AM dislocation structures originate due to thermal distortions during printing, which are primarily dictated by constraints surrounding the melt pool and thermal cycling. (C) 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.", + "Times Cited, WoS Core": 497, + "Times Cited, All Databases": 516, + "Publication Year": 2020, + "Research Areas": "Materials Science; Metallurgy & Metallurgical Engineering", + "UT (Unique WOS ID)": "WOS:000577994500003", + "Markdown": "Full length article \n\n# Origin of dislocation structures in an additively manufactured austenitic stainless steel 316L \n\nK.M. Bertsch a b c ∗, G. Meric de Bellefon a b B. Kuehl a b D.J. Thoma a b \n\na Department of Materials Science and Engineering, University of Wisconsin-Madison, 1550 Engineering Dr., WI 53706, USA b Grainger Institute for Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA c awrence Livermore National Laboratory, Livermore, CA 94550, USA \n\n# a r t i c l e i n f o \n\nArticle history: \nReceived 24 May 2020 \nRevised 27 July 2020 \nAccepted 28 July 2020 \nAvailable online 14 August 2020 \n\nKeywords: \nAdditive manufacturing \nDislocations \nDendrites \nTransmission electron microscopy \nOrientation mapping \n\n# a b s t r a c t \n\nIn this experiment, the origin of dislocation structures in AM stainless steels was systematically investigated by controlling the effect of thermal stress through geometric constraints for the first time. Stainless steel 316L parts were produced in the form of “1D” rods, “2D” walls, and \"3D\" rectangular prisms to evaluate the effect of constraints to thermal expansion/shrinkage on the development of defect microstructures and to elucidate the origin of additively manufactured (AM) dislocation microstructures. Dislocation density, organization, chemical micro-segregation, precipitate structures, and misorientations were analyzed as a function of increasing constraints around solidifying material in 1D, 2D, and 3D components built using both directed energy deposition (DED) and powder-bed selective laser melting (SLM). In DED parts, the dislocation density was not dependent on local misorientations or micro-segregation patterns, but evolved from approximately $\\rho_{\\perp}=\\quad10^{12}m^{-2}$ in 1D parts $\\mathsf{\\Pi}\\mathsf{\\Pi}\\mathsf{\\Lambda}[0\\rho_{\\perp}=\\mathsf{\\Omega}10^{14}m^{-2}$ in 3D parts, indicating that it is primarily thermal distortions that produce AM dislocation structures. In DED 3D parts and SLM parts, dislocation densities were highest $(\\rho_{\\perp}\\approx~10^{14}~\\mathrm{m^{-2}}^{\\cdot}$ and corresponded to the formation of dislocation cells approximately $300{-}450~\\mathrm{nm}$ in diameter. Dislocation cells overlapped with dendrite micro-segregation in some but not all cases. The results illustrate that dendritic micro-segregation, precipitates, or local misorientations influence how the dislocations organize during processing, but are not responsible for producing the organized cell structures. This work shows that AM dislocation structures originate due to thermal distortions during printing, which are primarily dictated by constraints surrounding the melt pool and thermal cycling. \n\n$\\mathfrak{O}$ 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. \n\n# 1. Introduction \n\nMetal additive manufacturing (AM) allows for greater design freedom than conventional fabrication methods [1–3] In addition, AM fabrication of stainless steel (SS) 316L has been shown to produce material with a combination of both high strength and ductility that is not typically observed in conventionally-processed SS 316L [4–6] The improved mechanical properties have been attributed to grain boundary strengthening [7] or, more frequently, to dislocation cell structures with solute micro-segregation that develop in AM metals [6 8 . Elucidating the mechanism of formation of these dislocation structures can enable better control over the microstructure of AM metals and alloys for property optimization. Several potential mechanisms for the formation of these AM dislocation structures have been proposed [4 9 and are briefly described below. \n\nIn the first proposed mechanism, constitutional stresses arising due to solute enrichment that develops in inter-dendritic regions during directional solidification induce distortions that are accommodated by dislocations [8 10 . The magnitude of the constitutional stresses is dependent on the magnitude of micro-segregation and the segregating species. Dislocation densities in AM steels have been estimated to be approximately $10^{13}–10^{14}\\ \\mathrm{m}^{-2}$ [4 7 11- 13 . These dislocation densities are orders of magnitude higher than the densities induced by the constitutional stresses accompanying the micro-segregation developed during directional solidification of e.g. Cu (on the order of $10^{11}~\\mathrm{m}^{-2}$ [11] This suggests that the micro-segregation in AM cell walls may be insufficient to generate all of the observed dislocations. \n\nIn another proposed mechanism, the fine, distributed precipitates that are typically present along the enriched inter-dendritic regions are proposed to introduce coherency strains and misfit dislocations [14] The formation of these dislocations has been proposed to contribute to the observed dislocation densities, and to act as a network of barriers to subsequent dislocation motion thereby dictating the overall dislocation structure. \n\nYet another proposed mechanism claims that misorientations between dendrites are accommodated by interfacial, “geometrically necessary” dislocations (GNDs), which lock in the dislocation structure spacing to that of the dendrites [5 15 . Boundaries made up of these GNDs, or geometrically necessary boundaries (GNBs), are detectable using orientation analysis and would be expected to act as obstacles to subsequent mobile dislocations. In this mechanism, dislocation networks are suggested to originate during solidification due to constitutional stresses, precipitate networks, or interdendritic misorientations, which sets up a framework for any dislocations formed after solidification to organize around. \n\nIn a fourth mechanism, it has been suggested that thermal expansion and contraction after solidification and during rapid, local heating and cooling cycles introduces significant plastic strain [11 16–18 . In this case, contrary to the first three mechanisms, dislocations nucleate due to thermal distortions after solidification, and subsequently interact with dendrite micro-segregation patterns, precipitate networks, or interdendritic misorientation networks. The majority of proposed mechanisms in the literature assume that some amount of the dislocation content is produced by thermal distortions, but propose different mechanics for the nucleation of the initial dislocations and for the alignment/organization of structures as they evolve. \n\nA final proposed mechanism suggests that the dislocation cells form first due to thermal stresses, and chemical micro-segregation occurs to dislocation walls later [18] However, this theory that segregation occurs after dislocation cell formation does not address the alignment of micro-segregation patterns with dendrites (along {001} planes in cubic materials) [19] The dendritic nature of the cell networks suggests the chemical micro-segregation occurs during solidification instead of after. \n\nDespite extensive observation of AM SS 316L dislocation structures in the literature, the majority of experiments are designed to evaluate the effects of these structures on material response, such that many questions remain regarding the origin of these structures. In this study, we implement a novel experimental approach to test the validity of the postulated mechanisms by separating thermal stress effects from solidification effects on dislocation structure development. \n\nThe freedom afforded by AM allows for the reduction of geometrical constraints surrounding solidifying material. Printing with directed energy deposition (DED) allowed for the creation of “1D” rods by moving the print head continuously upwards in the build direction. In these \"1D\" parts, the only physical constraint present to resist thermal contraction of material after solidification existed at the bottom of the rod, with the remainder of the material free to shrink upon cooling in any direction. In “2D” walls, the solidifying material was constrained by existing solid material from both the bottom of the melt pool and in the scanning direction behind the melt pool, but not in the through-thickness dimension of the wall. In \"3D\" parts, the solidifying material became constrained in the build direction, opposite the scanning direction, and additionally in the through-thickness direction since the melt pool penetrated previous layers and adjacent hatches. \n\nA similar part design was adopted using powder-bed selective laser melting (SLM), where a bed of metal powder is swept over the build plate to build up each layer, to investigate the generality of results obtained for DED. In SLM, the geometric constraints could not be eliminated as completely as in DED since the process is necessarily discontinuous. However, reducing the amount of surrounding material to create quasi-1D and -2D parts allowed for analysis of the effect of increasing constraints in a qualitative manner in SLM parts for comparison to DED. \n\nTable 1 Chemical compositions of SLM and DED parts in wt%. \n\n\n
CrNiMnSiCCuN0
SLM18.3913.941.470.30.0040.00220.0650.043
DED18.0613.791.580.320.0050.00950.0720.037
\n\nThe systematic elimination of geometric constraints allowed for systematic manipulation of the thermal stresses in a new way., which was critical to definitively identify the driving force for AM dislocation structure formation. \n\n# 2. Experimental Procedure \n\n# 2.1. Printing \n\n# 2.1.1. Directed energy deposition \n\nAn Optomec Laser Engineered Net Shaping (LENS) MR-7 unit was used to fabricate DED parts, with SS 316L powder (45– $150\\ \\mu\\mathrm{{m})}$ supplied by Carpenter $\\textsuperscript{\\textregistered}$ . The scanning strategies utilized for the different geometries are shown in Fig. 1 \n\nLaser scanning directions are indicated by arrows. Build direction is vertical. \n\n1D rods were built by continuously moving the print head directly upwards in the build direction after turning on the laser. Material was added continuously under the $600~{\\upmu\\mathrm{m}}$ laser spot until a rod $25~\\mathrm{mm}$ tall was built. Parameters included a laser power $200~\\mathsf{W}$ and a vertical print head velocity of $1.5\\ \\mathrm{mm}/s$ . \n\nThe 2D walls were built semi-continuously such that each layer consisted of a single track with a snake scan strategy to move between layers, e.g. each new track began where the previous track ended, as shown in Fig. 1 Walls were $25\\mathrm{\\mm}$ wide $\\mathrm{~x~}25\\mathrm{~mm}$ tall, with print parameters of laser power 400 W, laser scan speed $8.5\\ \\mathrm{mm}/s$ , and layer spacing $0.254~\\mathrm{mm}$ Different laser powers and scan speeds than used for the 1D rod were necessary, since the laser power and speed that allowed for continuous building of 2D walls did not successfully create 1D rods and vice versa. 1D rods and 2D walls were printed onto standard 316L base plates. \n\nThe 3D rectangular prism geometry was $50~\\mathrm{mm}$ long $\\mathrm{~x~}10\\ \\mathrm{mm}$ wide $\\mathrm{~x~3~mm~}$ tall, with a hatch spacing of $0.35\\ \\mathrm{mm}$ and a snake scan strategy between passes within the same layer, as indicated in Fig. 1 A contour deposit was made to outline each new layer, and each layer was rotated $90^{\\circ}$ relative to the previous layer scan direction. Laser power 275 W, scan speed $8.5\\ \\mathrm{mm}/s$ , and layer thickness $0.254~\\mathrm{mm}$ were used for 3D components. The 3D prism was printed onto a 316L base plate that had been cold-rolled to $80\\%$ thickness reduction and solution-annealed in an Ar atmosphere at $1050^{\\circ}\\mathsf C$ for one hour prior to deposition to remove preexisting defect structures. \n\nChemical analysis was used to analyze the printed material composition in the 3D parts, as shown in Table 1 \n\n# 2.1.2. Selective laser melting \n\nSLM parts were manufactured in an EOS M290 laser powderbed fusion unit using SS 316L powder $(15{-}45\\ \\mu\\mathrm{m})$ provided by $\\mathsf{E O S@}$ . The powder-bed SLM process required SLM 1D rods to be built layer-by-layer (instead of continuously), with each layer represented by a single “point”. Since the EOS printing software slices parts into representative triangles, each “point” layer consisted of a triangle with sides $100~{\\upmu\\mathrm{m}}$ . The triangles were approximately the same size as the laser beam diameter (nominally $80~\\ensuremath{\\upmu\\mathrm{m}})$ , such that each triangle ended up as a single point during the deposition. Thus, the print speed effectively dictated the laser dwell time for each layer of the 1D rods. 1D rods were built $13~\\mathrm{mm}$ tall, with 100 W laser power, $775\\ \\mathrm{mm}/s$ scan speed, and layer thickness of $0.02\\ \\mathrm{mm}$ . Additionally, a support structure $5~\\mathrm{mm}$ tall was deposited between the build plate and the SLM rods (as well as other SLM parts) for easier removal. \n\n![](images/dd24efaf036de1de8c46a231aa2e7d592fea185010084d173d28cf92644711ca.jpg) \nFig. 1. Schematic illustrating laser scan strategy and geometry for DED 1D, 2D, and 3D parts. Laser scanning directions are indicated by arrows. Build direction is vertica \n\nSLM 2D walls were built with laser power 100 W, scan speed $675\\ \\mathrm{mm}/s$ , and layer thickness $0.02\\ \\mathrm{mm}$ . Walls typically exhibited large distortions due to residual stresses, particularly near the ends of the walls, and frequently did not build completely up to the desired height. The wall selected for dislocation structure analysis was built up to the desired $13~\\mathrm{mm}$ height. The area selected for transmission electron microscopy (TEM) foil extraction was in the middle of the wall, away from the obvious distortions. \n\nSLM 3D prisms $3\\ \\mathrm{mm}$ tall were built using standard print parameters recommended by EOS for SS 316L, with laser power $195~\\mathsf{W},$ , scan speed $1083\\ \\mathrm{mm}/s$ , and layer thickness $0.02\\ \\mathrm{mm}$ . The scan strategy was the same as that used with the DED parts, but with hatch spacing of $0.09\\ \\mathrm{mm}$ and a necessarily larger number of layers to build up an equivalent amount of material. \n\nChemical analysis of SLM and DED 3D parts revealed similar bulk compositions across the two methods, with no compositional differences greater than $0.3~\\mathrm{wt\\%}$ , as shown in Table 1 \n\n# 2.2. Preparation and microscopy \n\nSpecimens were removed from build plates using a low speed saw or manually, except for one DED 3D prism. This DED 3D prism was left on the build plate and sectioned perpendicular to the long axis for analysis of the microstructure across the base plate interface. This allowed for direct comparison of melted/resolidified regions with unmelted regions that experienced identical local thermal and strain histories in the DED 3D material. Specimens (including the sectioned base plate specimen) were mounted in epoxy and mechanically polished down to a $0.05~{\\upmu\\mathrm{m}}$ grit silica solution, then electrolytically etched with $0.05~\\mathrm{M}$ oxalic acid solution at approximately $6\\:\\vee$ for $60~s$ each, such that any mechanical damage layer was effectively removed. Analysis of the dendrite structures revealed by etching was performed in either a Zeiss LEO 1530 Gemini field emission scanning electron microscope (SEM) operated at $5~\\mathrm{kV}$ or a FEI Helios G4 plasma focused ion beam (PFIB) CXe with an Elstar M SEM column operated at $5~\\mathrm{kV}.$ . \n\nThin foils for transmission electron microscopy (TEM) analysis were extracted using FIB machining in the FEI Helios PFIB and a Zeiss Auriga model Ga FIB. Foils were extracted across primary dendrite arms. A protective Pt layer was applied during the FIB machining process to preserve surface topography created by etching; the Pt layer was edited out of images for clarity. Secondary dendrite arm spacing (SDAS) and cooling rates were measured near the locations selected for TEM analysis. For the DED 3D part, a specimen was extracted that extended across primary dendrite arms in the deposited AM material and across the interface with the annealed base plate. Additional TEM specimens were extracted from DED and SLM 3D parts by mechanically grinding parts into foils less than $200~{\\upmu\\mathrm{m}}$ thick, then punching out $3\\ \\mathrm{mm}$ TEM disks. Disks were polished to electron transparency using a Struers Tenupol Twin-Jet polisher with A2 solution at $-20^{\\circ}C$ and $12~\\mathsf{V}$ for approximately $15\\ \\mathrm{min}$ . \n\nScanning TEM $(S/\\mathrm{TEM})$ analysis of the defect microstructures was performed in an FEI Tecnai TF-30 S/TEM operated at $300~\\mathrm{kV}$ and in an FEI Titan 80–200 aberration-corrected TEM operated at $200~\\mathrm{kV}.$ Bright field (BF) imaging was performed using the diffraction contrast STEM technique with a [011] zone-axis beam direction unless otherwise noted. Specimens with multiple grains were imaged with each grain at a [011] zone axis condition at different tilt angles, and montages were stitched together such that the physical appearance of the grain boundaries was maintained. Orientation mapping of the foils was performed using transmission electron backscatter diffraction (t-EBSD) in the Helios PFIB equipped with an Hikari camera, with step sizes approximately $40\\ \\mathrm{nm}$ and operating voltage $25\\mathrm{-}30~\\mathrm{kV}.$ Orientation analysis was performed utilizing the MTEX software package [20] and MATLAB functions. \n\nEnergy dispersive spectroscopy (EDS) analysis was performed across dislocation structures in DED specimens in the Titan S/TEM using a 128 eV-resolution detector. The purpose of EDS mapping was to confirm that interdendritic micro-segregation was present in the DED material and that the spacing of the microsegregation observed in TEM specimen microstructures corresponded to the dendrite spacing observed on surfaces after etching. In SLM SS 316L material, micro-segregation has previously been shown to overlap with both primary dendrite arms observed on etched/polished surfaces as well as with internal dislocation cell structures [5 6 10 18 . In this study, dendrites were observed on etched surfaces with the same spacing as dislocation structures. This was considered sufficient to confirm the presence of interdendritic micro-segregation at dislocation cell walls in SLM specimens, and it was not considered necessary to perform EDS mapping for SLM materials. \n\n# 3. Results \n\n# 3.1. Dendrite arm spacing and cooling rates \n\nPrimary and secondary dendrite arms were observed in all specimens upon etching. The dendrite structures are shown in the SEM images of Fig. 2 with the locations from which cross-sectional TEM specimens were extracted via FIB indicated by black rectangles. \n\nWhen etched, SS 316L material with interdendritic microsegregation forms protrusions at the interdendritic regions between primary dendrite arms due to the different local chemistry. In this study, dendrite arms are enriched in Cr, Mn, and Mo, and somewhat depleted in Fe, indicating enhanced resistance of the interdendritic regions to chemical etching relative to the matrix [18 21 . These interdendritic regions are typically referred to as dendrite arms, even though the primary dendrite is actually the region between these protrusions. FIB milling of etched surfaces confirmed that dendrite arms corresponded to surface protrusions in this study. Subsequently, surface protrusions observed in TEM specimens extracted via FIB are said to indicate the location of dendrite arms in the current work. The average primary dendrite arm spacing (PDAS) for each specimen geometry is shown in Table 2 \n\n![](images/bffecf734ca9eef045440549016fd74e716cb8540fdfa9393c9d07c02ef9eea7.jpg) \nFig. 2. SEM of microstructures for a-f, DED pecimens, nd g-l, SLM pecimens. Boxes indicate IB liftout ocations; build direction s vertical. FIB extraction was not used o prepare TEM specimens in SLM 3D material. \n\nTable 2 Primary dendrite arm spacing (PDAS) measured for TEM lamellae extracted via FIB machining for dislocation structure analysis. \n\n\n
DEDSLM
1D2D3D1D2D3D
PDAS[μm]6.5 +/-0.15.8 +/-0.8Base: 1.9 +/-0.3 Center: 2.2 +/-0.30.27 +/-0.040.39 +/-0.10.46 +/-0.1
\n\nSDAS was measured from SEM images for each specimen. These measurements allowed for calculation of the cooling rate via the following relationship: \n\n$$\n\\lambda_{2}=B\\dot{\\varepsilon}^{-n}\n$$ \n\nwhere $\\lambda_{2}$ is the SDAS in μm, $\\dot{\\varepsilon}$ is the cooling rate in $\\mathsf{K}/\\mathsf{s}$ and the constants $\\mathtt{B}=25$ and $\\mathrm{n}=0.28$ for SS 316L [22–24] For each specimen, measurements were taken from at least five different areas of the specimen, and each measurement consisted of an average spacing between at least seven consecutive secondary dendrite arms. Cooling rates calculated from SDAS measurements varied over several orders of magnitude across the different materials and geometries, as shown in Table 3 Note that the SDAS listed in \n\nTable 3 is different than the PDAS listed in Table 2 and illustrated in Fig. 2 \n\nCooling rates for DED 1D rods and 2D walls were calculated from SDAS measurements taken within $0.5\\mathrm{-}1~\\mathrm{\\mm}$ of the base plate, near the sites of extraction of TEM lamellae. These locations were selected for analysis in order to compare the microstructures that formed in regions with cooling rates that were as close as possible to those observed in the 3D DED parts. For the DED 3D parts, microstructural analysis of dislocation structures was performed both near the base plate and at the center of the part, so cooling rates for both locations are given in Table 3 In SLM parts, measurements were taken approximately $7{-}10~\\mathrm{mm}$ from the base plate ( $2{-}5\\ \\mathrm{mm}$ from the end of the support structures). \n\nIn the following, the results for each specimen are presented in order of dislocation density and structures first, followed by the correlation of dislocation structures with dendrite microsegregation profiles, precipitate structures, and lastly local misorientations. \n\n# 3.2. DED microstructures \n\n# 3.2.1. DED 1D \n\nTEM specimens for DED 1D rods were extracted across primary dendrites approximately $450~{\\upmu\\mathrm{m}}$ from the bottom of the rod, as shown in Fig. 2a and b. The dislocation structure of the 1D rod material is shown in the bright-field diffraction-contrast STEM image Fig. 3a. Multiple grains were captured in the foil, as indicated by the sharp background contrast changes across grain boundaries; grains are labeled 1–3 for clarity. Dislocations were sparse and typically isolated in the 1D rod structures, for example near the arrowhead labeled “D” in Fig. 3 with no organization into cell structures. \n\nTable 3 Cooling rates $[\\mathsf{K}/\\mathsf{s}]$ measured from SDAS for regions analyzed with TEM. \n\n\n
DEDSLM
1D2D3D1D2D3D
SDAS [μm]2.9 +/-0.43.0 +/-0.1Base: 1.0 +/-0.2 Center: 1.1 +/-0.10.24 +/-0.040.23 +/-0.040.26 +/-0.04
Cooling rate [K/s]3x1032 x103Base: 1 x 105 Center: 7 x 1042x1072 x1071x 107
\n\n![](images/cff21895ec54c7785c6f131ed54314e2f3de1093c13e31182223a6fbd688bf30.jpg) \nFig. 3. a. Bright-field zone-axis STEM of defect structures in DED 1D rod. Surface protrusions due to etching of regions with interdendritic micro-segregation are labeled PD and indicated by arrows. Ferrite inclusions, oxide precipitates, and dislocations ndicated by F”, P”, nd D”, espectively. Different grains abeled 1, 2, nd 3. b. t-EBSD misorientation map of the grains shown in a. Color online. \n\nLine-intercept analysis of the dislocation density [25] suggested a density on the order of $2\\textup{x}10^{12}\\ \\mathrm{m}^{-2}$ for a foil thickness of approximately $200\\ \\mathrm{nm}$ (measured via edge-on SEM imaging). This method is subject to inaccuracies due to projection effects, loss of dislocations during sample preparation, and inaccuracies in measuring foil thickness [26] such that we consider these measurements to have an error range of within an order of magnitude. Dislocation densities are tabulated in Table 4 \n\nSurface protrusions corresponding to primary dendrite arms are labeled PD and indicated by arrows in Fig. 3a. The dendrites are seen in the SEM image of Fig. 2b. EDS analysis was performed along a line perpendicular to the primary dendrite arms direction to define the interdendritic micro-segregation profiles. EDS line scan analysis for the 1D rod microstructure is shown in Fig. 4 \n\nFe content changed up to $5\\mathrm{\\wt\\%}$ across dendrite arms, while Cr content varied up to $4\\mathrm{\\mt\\%}$ . Depressions in the Fe profile correspond to local peaks in the Cr profile, occurring at approximately $6~{\\upmu\\mathrm{m}}$ intervals. Enrichment of both Mn (from $1\\mathrm{\\Delta\\wt\\%}$ to $2\\ \\mathrm{wt\\%}$ and Mo $(1-3~\\mathrm{wt\\%})$ was observed at the same locations as Cr enrichment (not shown for clarity). The spacing of micro-segregation peaks corresponds with the average $6.5~{\\upmu\\mathrm{m}}$ spacing measured for the primary dendrite arms (Table 2 , which are indicated by the arrows labeled “PD” in Fig. 4 as expected. Most importantly, the micro-segregation profiles were observed to be regular within the microstructure and did not correlate to any dislocation structures. This demonstrates that the presence of dendrites and chemical inhomogeneity does not necessarily produce dislocations. \n\nPrecipitate structures were also analyzed as a potential source of dislocations. Precipitates consisted of either ferrite or oxide precipitates, as indicated by the labels F and P, respectively, in Fig. 3 Ferrite inclusions, identified through t-EBSD crystallographic analysis, typically exhibited irregular morphologies and occurred at grain boundaries (although they were not limited to grain boundaries), and were $500\\ \\mathrm{nm}$ in diameter on average. Oxide precipitates, identified via EDS mapping, were typically Si oxides with Cr and Mn enrichment, exhibited regular spherical morphologies, and were $250~\\mathrm{{nm}}$ in diameter on average. Oxide precipitates were distributed throughout the matrix, and although some were observed near dislocations, there was no evident correlation between the presence of dislocations and precipitate formation. \n\nOrientation image mapping via t-EBSD was used to evaluate whether misorientations inherently exist between most dendrites, and if so, whether these can be linked to dislocation structures. A misorientation map is shown in Fig. 3b for the same area shown in Fig. 3a. In the map, points are colorized according to the relative misorientation of that point with respect to the mean orientation of the grain to which it belongs. Grain boundaries are indicated by thick black lines. Points with a confidence index less than 0.01 were excluded from the analysis and are shown in white as is the background. Ferrite inclusions were removed from the analysis and are shown in white as well, for example as labeled F in Fig. 3b. \n\nMisorientations did not correspond with dendrite structures, instead being distributed throughout the material and concentrated near grain boundaries. Dislocations appeared frequently to be SSDs without notable local misorientation fluctuations, indicating that interdendritic misorientations were not essential to formation of dislocation structures in the 1D DED material. Despite the low dislocation density in the 1D rods, misorientations up to 3 were observed across grains, with the highest local fluctuations near grain boundaries, as shown in the bottom two grains in Fig. 3b. The top grain in Fig. 3b exhibited higher misorientations, but the measurement in the uppermost grain was affected by a much lower foil thickness observed near the top of the foil due to FIB milling. Within the two lower grains, orientation changes were not observed to occur periodically or correspond to dendrites, indicating that misorientations are not inherent to dendrite structures in the AM material, and that the dislocations present were not inherently tied to any misorientations between dendrites. \n\nTable 4 Dislocation densities $[\\mathsf{m}^{-2}]$ measured using the line-intercept technique and average dislocation ell ize. \n\n\n
DEDSLM
1D2D3D1D2D3D
p [m-2]2 x10123 x10131x10143 x10143 x10144x1014
d [nm]-370280400470
\n\n![](images/896dc45a0ab6c60db515e33d83b2193fe58be5274976d963658690a9a5c870b1.jpg) \nFig. 4. a. HAADF-STEM of DED 1D rod material, b. EDS data collected from left to right along the line indicated in a. Surface features corresponding to interdendritic micro-segregation labeled PD and indicated by arrows. Color online. \n\n# 3.2.2. DED 2D \n\nThe defect microstructure in DED 2D walls exhibited dislocation density an order of magnitude higher than in 1D rods at approximately $3\\mathrm{~x~}10^{13}\\mathrm{~m}^{-2}$ as shown in Fig. 5a. The higher dislocation density coincided with an increased interaction of dislocations, such that they formed pileups at some grain boundaries and dislocation tangles but had not begun to organize into the dislocation walls typical of higher dislocation densities [27] As in Fig. 3, multiple grains were captured in the extracted region, and are labeled 1–3 in Fig. 5a for clarity. \n\nPrimary dendrites were observed corresponding to surface protrusions as indicated by arrows labeled “PD” in Fig. 5a. The PDAS measured at the surface are approximately $6~{\\upmu\\mathrm{m}}$ , consistent with the data in Table 2 Most importantly, the PDAS did not coincide with any change in the dislocation density or arrangement, which stayed approximately constant over the measured regions. \n\nEDS analysis was performed along a line perpendicular to the direction of the primary dendrite arms as indicated in Fig. 6 Fe and Cr content fluctuated approximately $5\\mathrm{\\wt\\%}$ and $3\\mathrm{\\wt\\%}$ , respectively, which is of similar magnitude to that observed in 1D material. Note that micro-segregation occurred over a slightly larger length scale, approximately ${\\mathfrak{s}}\\mu\\mathrm{m}.$ , in the region scanned than the scale of PDAS (average $6~\\mu\\mathrm{m})$ (Table 2 . This is attributed to the proximity of a grain boundary to the line scan, which would affect micro-segregation of diffusing species by acting as a sink during cooling after solidification. These observations confirm that a chemically inhomogeneous structure was present with a repeating length scale that was not mirrored in the dislocation structure, which was not periodic or in cells. \n\nPrecipitate and ferrite particle structures, labeled $\\mathrm{~\\bf~P~}$ and F respectively in Fig. 5a, were confirmed to have similar composition, size, and distributions as those observed in 1D DED material. In 2D walls, dense tangles of dislocations were observed in the immediately vicinity of most particles (within approximately $100~\\mathrm{{nm}}$ ) than in the matrix, for example as shown in Fig. 7 near the precipitates labeled P. However, dislocation pileups, walls, or bands were not observed around the particle structures, such that it remains unclear whether precipitates or dislocations were formed first during microstructural development. \n\n![](images/57d6946e7a7ce2d4dd88c0789efb5778378aa98cfdb7a0eec5829b033082b283.jpg) \nFig. 5. a. Bright-field zone-axis STEM of microstructures in the DED 2D wall, b. tEBSD misorientation map of the region shown in a. PD indicates protrusions on the etched surface due to interdendritic micro-segregation, D dislocations, F ferrite inclusions, and P oxide precipitates. Color online. \n\nAs shown in the orientation map Fig. 5b, intragranular misorientations were limited to less than approximately 3 over a similar area as analyzed in the 1D specimen. Local orientation deviations were not associated with dendrites and were not observed across every dislocation wall or tangle, and locally higher dislocation densities (for example near grain boundaries) were not necessarily associated with misorientations, again indicating that the dislocations were not a product of accommodating differently oriented dendrites. \n\n# 3.2.3. DED 3D \n\nThe DED 3D microstructure was observed directly across the interface with the base plate to compare the deposited, directionally solidified microstructure with that of the pre-annealed base plate, as shown in Fig. 2 The base plate (below the melt pool boundary) experienced nearly the same local thermal and stress-strain history as the adjacent deposit but was not melted and re-solidified. While dendrites were present in the deposited material and not in the base plate, no observable difference in dislocation density was found. Dislocation microstructures across the interface are illustrated in Fig. 8 \n\n![](images/198b95fbb0a57e5cf26a931cb703616a80daaa8dc8a469146c2d3ff6ce1562db.jpg) \nFig. 6. a. HAADF-STEM image of DED 2D microstructure, b. EDS line scan analysis of micro-segregation profiles, taken from left to right along line indicated in a. Surface protrusion due to etching of interdenritic micro-segregation labeled PD. Color online. \n\nEquiaxed dislocation cells were observed in both the base plate and the deposited material with an average diameter of approximately $370\\ \\mathrm{nm}$ , for example as outlined and labeled C in Fig. 8 These dislocation cells are typical of those observed in SS 316L after deformation [28 29 . In the deposited 3D prism material and in the base plate, the dislocation density was an order of magnitude higher than in the 2D walls, at approximately $1\\mathrm{~x~}10^{14}\\mathrm{~m}^{-2}$ These density measurements were found to agree with diffraction-based measurements of the dislocation density in similar AM steels [7 13 within an order of magnitude. \n\nWhile the fine, equiaxed dislocation cells did not change between the base plate and solidified material, a micro-segregation structure was identified in the only deposited material. The microsegregation appeared as a network with an average diameter of approximately $1.9~{\\upmu\\mathrm{m}}$ , corresponding to the PDAS. The dendritic micro-segregation network was superimposed on the dislocation cell structure, and where they overlapped, dislocation walls were thicker and enriched in Cr/depleted in Fe. An example is outlined with the dashed line labeled DCW (for “dendritic cell wall”) in Fig. 8 Examples of the correlation between the thick DCWs and etched, dendritic surface protrusions are arrowed in Fig. 8 Thus, while dislocation cell formation occurred independently of local micro-segregation, there was some overlap between dendrites and wall structures. \n\nQualitative differences between the cell wall structures with and those without micro-segregation were also observed, indicating different mechanisms of organization. DCWs, outlined with dashed lines in Fig. 9a and shown at higher magnification in Fig. 9b, were not only typically qualitatively wider than other walls, but also contained dislocations that appeared more tangled. In comparison, the regular cell walls had qualitatively more dislocations with straight segments, as shown in Fig. 9c. Tilting of samples in the microscope and observations of grains with different orientations indicated that these differences were general and not due to local projection effects. \n\n![](images/d386cb517e85758f61a4b18d86fe7a70f598119e56b42a174f5452cb32ffd086.jpg) \nFig. 7. Bright-field zone-axis STEM of material shown in Fig. 5 illustrating dislocations (“D”) organized into tangles and precipitates $(\"\\mathrm{P\"})$ \n\n![](images/20214d95a9d5956bce79ddc07e38fcc74f63e44cb4fe8dee05d52393bfd73112.jpg) \nFig. 8. Bright-field zone-axis STEM imaging of the microstructure across the interface between the as-deposited material of the DED 3D prism and the pre-annealed base plate. The interface is indicated by the dashed line, and surface protrusions due to etching of primary dendrites on the sample surface are indicated with arrows. Examples of dislocation ell walls re outlined, with equiaxed dislocation ells with uniform composition labeled C and cell walls overlapping with dendrite segregation labeled DCW. \n\nCr and Fe micro-segregation profiles were found to be similar to the Cr micro-segregation profiles observed in the 1D and 2D DED samples, as shown in the EDS maps in Fig 10 Note that EDS and orientation mapping were performed on $3\\ \\mathrm{mm}$ disk specimens instead of the sample extracted via FIB across the interface with the base plate (Fig. 8 , as the FIB sample was damaged during handling after S/TEM analysis. \n\nThe spacing of the solute-rich regions corresponded to the PDAS, $1.9\\ \\upmu\\mathrm{m}$ on average (Table 2 , indicating that these were dendrites. While the large, segregated cells frequently appeared equiaxed in images of the thin foils, their matching to the PDAS and solute enrichment supports that they were likely all dendrites elongated in ${<}001>$ crystallographic directions, as confirmed in some specimens. \n\nPrecipitate structures were not limited to dislocation walls, and were not present in all dislocation walls, indicating a lack of correlation between precipitation of second phases and dislocation wall formation. Precipitates exhibited similar size, composition, and distribution as those in the 1D and 2D components. Although many were found in the solute-rich large cell walls, they were also observed in the walls of the smaller cells with uniform composition and within the cell interiors. Ferrite was observed in the solidified DED material near the base plate, but no ferrite was observed in the DED 3D material a few mm away from the base plate. \n\nIn the 3D DED material, misorientations between DCWs were found not to be a requirement for dislocation cell wall formation. Orientation mapping was performed near the edge of a $3\\ \\mathrm{mm}$ TEM disk, as shown in Fig. 11 Three grains, with grain boundaries indicated by black lines, were captured in the map near the edge of electropolished hole, which appears at the bottom right. Large dendritic cells were observed via TEM and were visible in the image quality analysis of the mapped region. The DCWs were traced in the image quality map, then overlaid on the misorientation map to reveal any correlation between DCWs and local orientation deviations. Misorientations up to 5 were observed over a range of approximately $20~\\mu\\mathrm{{m}}$ , and tended to be highest near grain boundaries, as shown in Fig. 11 Local orientation deviations were not observed across the majority of the dendritic dislocation cell walls, although some correlations occurred, for example near the arrow in Fig. 11 \n\n![](images/da86f01835670432e9b84ee1bfbe4f3e51f16115b04197d67b70751ec621841b.jpg) \nFig. 9. Bright-field one-axis STEM mages of dislocation tructures n s-deposited DED 3D ectangular prisms. . Dislocation ell walls with micro-segregation DCW, dashed lines and arrow) and uniform-composition cells, b. DCW, c. walls of equiaxed cells with uniform composition. \n\n![](images/ef06dac4417437ee721528055a94b65d7869b4c05452380d283418f7584c06be.jpg) \nFig. 10. a. HAADF-STEM image and b. EDS mapping of the boxed region in a, illustrating Cr micro-segregation and Fe depletion at large dislocation cell walls. Color online. \n\n# 3.3. SLM microstructures \n\n# 3.3.1. Thermal constraints \n\nIn SLM parts, the melt pool penetration of the substrate and the time required to spread new powder layers between layers were both greater than in DED parts. These differences changed the solidification behavior such that even in the SLM 1D rods, thermal contraction was not unconstrained as it was in DED 1D rods. In SLM materials, the melt pool appeared to penetrate up to $200\\ \\mu\\mathrm{{m}}$ into the substrate, while layers were built in $20\\ \\mu\\mathrm{{m}}$ increments. For example, analysis of the top of the SLM 1D rods (where the approximate shape of the deposit was preserved for the final layer) indicated that melt pools were up to $180~{\\upmu\\mathrm{m}}$ deep, as shown in Fig. 2g by the line labeled as the layer boundary. The melt pool profile typically extended up to $100~{\\upmu\\mathrm{m}}$ deeper in the center of the part than at the edges, suggesting that the deposited material was surrounded and constrained by the substrate upon solidification. Similar penetration of the substrate by new layers was observed for SLM 2D walls and 3D components, confirming that the deposited material was constrained in all SLM parts. Despite the presence of these constraints, the volume of substrate material surrounding the melt pool should have been smallest in 1D rods, larger in 2D walls, and largest in 3D prism. Correspondingly, the magnitude of the constraints was still expected to increase with increasing part dimension in SLM parts. \n\n![](images/aa941fc80f16f447249ee60f7e31eba95c26e77d898c8534faf6a5b1b34cac26.jpg) \nFig. 11. Map of misorientation relative to the grain mean orientation for a $3\\ \\mathrm{mm}$ disk prepared from the DED 3D rectangular prism, with approximate locations of dislocation cells traced in gray. Each point colorized according to the color bar shown at the right. Color online. \n\n# 3.3.2. Dislocation microstructures \n\nThe microstructure of the SLM materials differed from the DED materials in terms of scale, density, and organization. Dislocation densities ranged from $3{-}4\\mathrm{~x~}10^{14}\\mathrm{~m}^{-2}$ in SLM materials, as listed in Table 4 Defect microstructures in SLM material showed organization into cells elongated on {001}-type crystallographic planes (instead of equiaxed cells), as shown in Fig. 12 for a. 1D, b. 2D, and c. 3D components. The average cell sizes were $280~\\mathrm{{nm}}$ , $400~\\mathrm{{nm}}$ , and $470\\ \\mathrm{nm}$ in 1D, 2D, and 3D SLM parts, respectively (Table 4 . These average dislocation cell sizes matched the PDAS observed on the etched surfaces, which were $270~\\mathrm{{nm}}$ , $390~\\mathrm{{nm}}$ , and $460~\\mathrm{{nm}}$ in 1D, 2D, and 3D material, respectively (Table 2 . \n\nSEM imaging during FIB milling of etched surfaces and $S/\\mathrm{TEM}$ imaging after extraction of TEM lamellae revealed coincidence of dislocation cells with dendritic micro-segregation patterns in SLM specimens. Dislocation cells have been frequently reported to overlap with dendritic micro-segregation profiles with spacing 400– $600\\ \\mathrm{nm}$ for SLM SS 316L [5 6 10 18 30–32 . Consequently, EDS analysis was not considered necessary to verify that dislocation cells overlapped with dendrites in SLM specimens, although additional EDS analysis is being pursued in ongoing studies. \n\n1D SLM dislocation structures are shown in the edge-on orientation in Fig. 12a, with the end-on orientation shown at higher magnification in the inset. \n\nIn the 1D SLM material, dislocation cell walls were organized loosely, with substantial dislocation density between the cells, in contrast to the more densely packed cell structures typically reported for SLM SS 316L [6] Although dislocations were organized sufficiently such that cell walls could be delineated from the interiors, discrete dislocations could frequently still be discerned within the cell walls, Fig. 12a inset. Line-intercept measurements indicated an approximate dislocation density of $3\\mathrm{~x~}10^{14}\\mathrm{~m}^{-2}$ which represents a slight increase relative to DED 3D parts but is within the same order of magnitude. \n\nIn SLM 2D parts, shown in Fig. 12b, dislocation cells were only observed in the end-on orientation due to the sample orientation. The cell structures were approximately $400~\\mathrm{{nm}}$ in diameter on average, slightly higher than in 1D SLM parts, and the cell walls appeared denser and tighter than in 1D material. Dislocation density was approximately the same as in SLM 1D parts at approximately $3\\mathrm{~x~}10^{14}\\mathrm{~m}^{-2}$ \n\n![](images/a7b08224ba7ee95e4b4f851ebd48697e8debd679aa275211c5ea5ca27b55b0bc.jpg) \nFig. 12. Bright-field STEM images of dislocation structures in a. SLM 1D rods viewed edge-on, with end-on view inset; b. SLM 2D wall material viewed end-on; and c. 3D material viewed edge-on, with end-on view inset. \n\nIn 3D SLM parts, shown in Fig. 12c, dislocation cells were largest at approximately $470\\ \\mathrm{nm}$ average diameter, similar to other observations in SLM SS 316L parts [5 6 10 18 . The elongated, periodic structures shown in the edge-on orientation in Fig. 12c, indicated parallel to the dashed lines, were observed to extend throughout all grains. Qualitatively, dislocation walls were denser than those observed in SLM 1D rods, such that individual dislocations were unable to be delineated within walls. The estimated dislocation density was $4\\mathrm{~x~}10^{14}\\mathrm{~m}^{-2}$ which is in agreement with reports in the literature [13] \n\n# 3.3.3. Precipitates \n\nFine precipitates approximately $15\\ \\mathrm{nm}$ in diameter on average were present in all SLM specimens, primarily in cell walls but also in cell interiors. These were confirmed for SLM 3D structures to be Si, Mn, and Cr oxides, as reported in other studies of SLM 316L [6 33 . No differences were observed in the precipitate composition, average size, or distribution for SLM 1D-3D parts. Here, oxides were primarily observed within cell walls, although some were found within cell interiors as well. No ferrite was observed. \n\n![](images/4a1cc15220b1e007933d104ff8949d3aa8af856d3a4fbf2d45f08238a67d637b.jpg) \nFig. 13. Maps of the misorientation of each point relative to the grain mean orientation collected from transmission EBSD data for a. SLM 1D rods, b. SLM 2D walls, and c. SLM 3D material. Note different spatial scales in a, b, and c. Color online. \n\n# 3.3.4. Misorientations \n\nOrientation mapping of SLM materials indicated that in general, larger orientation gradients developed in SLM parts compared to DED, as shown in the orientation maps in Fig. 13 (note the different scale than in the DED misorientation maps). However, orientation gradients were once again not present across most cell walls, indicating that local misorientations are not required to form the cell walls. \n\nIn SLM 1D and 2D materials, dislocation cells were observed via TEM across the entire regions shown in Fig. 13a and b, but local misorientations were observed only across of fraction of these cell walls, for example as shown near the arrows in Fig. 13a and b. In the SLM 3D material, misorientations followed similar patterns, Fig. 13c. In the large grain labeled 1 in Fig. 13c, dislocation cells were observed in TEM to be in an edge-on orientation across the entire grain, along the direction indicated by the arrow. It is clear in Fig. 13 that orientation deviations occurred in random patterns and not across the elongated, straight cell structures. \n\n# 4. Discussion \n\n# 4.1. Summary of microstructural observations \n\nThe most important observations made in this study were as follows. \n\n1 Dislocation density increased with increasing constraints around the melt pool. a Density increased by an order of magnitude with each increase in part dimension in DED parts. b In SLM parts, dislocation density and organization in cell walls increased qualitatively with increasing part dimensionality. \n\n2 Dendrites were observed in all specimens. \n\na Dendrites existed without overlapping dislocation structures in DED 1D and 2D parts. \nb In DED 3D parts, dendrites overlapped some dislocation cell walls, but many dislocation cell walls with uniform composition existed between the dendrites. \nc In SLM parts, dislocation structures exhibited the same spacing and orientation as dendrites, and spacing increased with increasing part dimensionality. \n3 Precipitates were not correlated with the location of dislocation wall formation, and precipitate density was not correlated with dislocation density. \n4 Misorientations were not observed across all dislocation walls in all components. Misorientations were not observed across all dendrites. Thus, neither the formation of dendrites nor the formation of dislocation walls was inherently tied to the presence of a local misorientation. \n\nIn the following, the results are shown to support the hypothesis that thermal shrinkage and expansion in a constrained medium are the primary sources for the dislocations observed in AM parts. In other words, the dislocation density and structure are determined by the residual stresses and strains developed after solidification. The studied solidification microstructural features investigated, specifically dendrites, precipitate networks, and misorientations between dendrites, did not produce substantial dislocation density independently of thermal stress/strain. The influence of these solidification features was to affect the organization of dislocations later in the process, after dislocations were produced by the thermal cycling. \n\n# 4.2. Geometrical constraints and micro-segregation \n\n# 4.2.1. DED \n\nThe increase in constraints from 1D to 2D to 3D DED parts led to an increase in dislocation density from $10^{12}\\ m^{-2}$ to $\\bar{10}^{13}\\ m^{-2}$ to $10^{14}\\ \\mathrm{m}^{-2}$ respectively, indicating a correlation between dimensionality/constraints and deformation microstructure. Defect microstructures are depicted schematically in Fig. 14 where the dendrite growth direction (GD) is vertical from bottom to top, interdendritic regions exhibiting micro-segregation are shown in green (for example “ID segregation” in Fig. 14a), and individual dislocations are shown in black. \n\n1D DED microstructures showed that in the absence of constraints to thermal contraction after solidification, dislocation density is minimal. This material showed that dendrites can exist without being accommodated by dislocations, so any coherency stresses induced by compositional changes are alone insufficient to nucleate enough dislocations to begin interacting or organizing into walls. The 1D microstructure is depicted in Fig. 14a, with discrete, sparse dislocations shown in black distributed throughout the matrix and the ID regions. \n\n![](images/3d4c298eef3807b145c003447537f71f35338b6900a6a5f97cf94d41c16f8506.jpg) \nFig. 14. Schematic illustrating dendrite (green) and dislocation (black) structures in a. 1D, b. 2D, and c, d. 3D materials. Solidification/dendrite growth direction indicated from bottom to top. Precipitates labeled “P”, growth direction “GD” is vertical. Color online. \n\nIn the 2D DED case, dislocation density increased by an order of magnitude with the introduction of constraints in the build direction, as shown schematically in Fig. 14b. This indicates that the dislocation density is directly tied to the geometric constraints to thermal volume changes. The lack of increased organization around dendritic patterns further confirms that the ability of dendrites to produce and trap dislocations is alone insufficient to create organized dislocation cell structures. \n\nIn 3D DED parts, dislocation density increased by another order of magnitude, becoming high enough to create dense, organized dislocation cell walls similar to those typically formed under tensile, compressive, or torsional loading [34–36] These structures are depicted in Fig. 14c. The adjacent material in the base plate exhibited similar dislocation density and dislocation structures, despite the lack of a solidification structure. Since the deposit and adjacent base plate material share only thermal history and similar strains, but not the directional solidification features, this confirms that the density and length scale of AM dislocation structures are primarily determined by stress/strain history. \n\nDendrite micro-segregation appeared to have a minimal influence, and only on dislocation walls that directly overlapped them. DCWs appeared to be thick and comprised primarily tangled dislocation segments, while dislocation cell walls without microsegregation formed between and subdividing dendrites with more straight dislocation segments, as depicted in Fig. 14c. This indicates that the interdendritic regions with micro-segregation are not always the most energetically favorable place for dislocations to organize. Consequently, it can be concluded that dislocation cell formation tends to follow patterns observed in conventional materials, except for walls that form in the immediate vicinity of dendrites. \n\nBirnbaum et al. [18] suggested that chemical micro-segregation to dislocation walls in AM materials is driven by strain aging occurring after dislocation structure formation. The presence of dendrites without dislocations in the 1D DED material in this study confirms that the micro-segregation occurs early in the process during solidification, as dendrites typically form, and is not based on dislocations acting as sinks for segregants. In the 3D DED material, the presence of micro-segregation only at some dislocation walls further validates that the micro-segregation is not a general or post-solidification phenomenon. Finally, the micro-segregation patterns fall on {001} crystal planes, which is expected for dendrites in cubic materials, and which is not typical of dislocation structures in FCC metals deformed conventionally from room temperature to approximately $600^{\\circ}\\mathsf C$ [28 29 37 38 . \n\n# 4.2.2. SLM \n\nAlthough it was not possible to minimize constraints in 1D or 2D SLM parts as effectively as in DED parts, the magnitude of constraints was still expected to be different between 1D, 2D, and 3D SLM parts. This hypothesis was supported by observations that the organization of dislocation walls was qualitatively different between 1D, 2D, and 3D SLM parts, similar to observations made in DED materials. Thus, the geometric constraints and residual stresses and strains still had an influence on the dislocation structures. \n\nUnlike in 3D DED material, dislocation walls in SLM materials overlapped directly with primary dendrites, as depicted in Fig. 14d. The dislocation cell size also increased from 1D-3D in SLM materials, even though the dislocation density stayed within the same range or slightly increased from 1D-3D. This could be interpreted as an increased importance of dendrites in SLM materials compared to DED. However, the greater correlation between dendrite arms and dislocation cells in SLM parts can be attributed to how much closer the dendrite spacing was to the dislocation cell size as follows. \n\nIn the 316L base plate with no solidification features that the 3D DED prism was printed on, a dislocation density on the order of $10^{14}~\\mathrm{m}^{-2}$ corresponded to a dislocation cell diameter of $370~\\mathrm{{nm}}$ on average. In conventional materials, dislocation cell size is inversely related to dislocation density after deformation, with established relationships that depend on the alloy and composition [27 39 40 . The SLM and DED specimens had similar compositions (Table 1 , indicating that they should exhibit similar cell sizes at similar dislocation densities. For the SLM materials with dislocation density slightly higher than in the 316L base plate but still on the order of $10^{14}\\ m^{-2}$ dislocation cells would therefore be estimated to be slightly smaller size on average than $370~\\mathrm{{nm}}$ In all SLM parts, the PDAS fell within $+1-25\\%$ of the predicted average dislocation cell size of less than $370\\ \\mathrm{nm}$ . In the 3D DED part, the PDAS was approximately $50\\%$ of the $370~\\mathrm{{nm}}$ average dislocation cell size. Since it appears favorable for dislocation walls in close proximity of dendrites to organize aligned with the dendrite micro-segregation, as shown in Figs. 8 and 9 then it follows that if dendrite walls would be within close proximity to all dislocation walls, they would naturally interact and overlap. Consequently, there would be more opportunity to form dislocation walls between/subdividing dendrites in DED material than in SLM. \n\nWhile the magnitude of micro-segregation was not quantified in SLM material relative to that observed in DED material, it is considered unlikely that differences in the magnitude of microsegregation drove the differences between SLM and DED dislocation structures. Greater micro-segregation of the same elements or different segregating species, particularly elements with greater atomic mismatch relative to Fe, could be posited to increase constitutional stresses due to solute segregation in SLM 316L, creating more dislocations and greater dislocation trapping at dendrites [8] However, SLM materials have been shown to exhibit a dislocation structure with all cells aligned with dendrites even in the presence of relatively low amounts of micro-segregation of elements including Cr and Mo [6 8 . This supports the notion that high levels of chemical micro-segregation are not necessary to cause overlap of dislocation cells with dendrites. Therefore, the presence of dislocation walls overlapping with dendrites is primarily driven by the degree of difference between the PDAS and the preferred dislocation cell size for the observed density. \n\n# 4.3. Precipitate networks \n\nThe results support the notion that precipitate networks were not critical to dislocation production or organization, and they have at most an ancillary influence on the development of AM dislocation structures. \n\n# 4.4. Misorientations between solidifying dendrites \n\nOrientation differences between dendrites at solidification were not found to be sufficient to form boundaries composed largely of GNDs. Classically, dislocation structures in metals can be classified in one of two categories, either GNDs or statistically stored dislocations (SSDs). GNDs are accompanied by local lattice rotations and accommodate local shape or orientation changes, while SSDs do not [36 41–44 . If misorientations between dendrite arms were large enough to warrant accommodation by dislocations, these dislocations would necessarily be GNDs. \n\nOrientation mapping of DED 1D and 2D parts indicated that in material with dendrites but not dislocation cells, local misorientations did not accompany dendrite arms, as shown in Figs. 3 and 5. This indicates that dendrites are not inherently misoriented relative to one another, and their presence does not necessarily produce GNDs. 3D DED and all SLM parts showed that in material with both dendrites and dislocation cell structures, local misorientations still did not generally accompany dendrites, as shown in Figs. 11 and 13 Thus, even when dislocation walls coincided dendrites, they did not necessarily comprise GNDs, indicating that GNDs and local misorientations are not critical to the formation of AM dislocation structures. \n\nWhile the misorientations across cell walls were only observed post mortem and not during the initial stages of formation, the misorientation across a cell wall only tends to increase with increasing strain/deformation [36] Thus, it is considered unlikely that misorientations were present across all dendrite walls during formation that were not observed post mortem. The results do not preclude the possibility that misorientations between dendrites may be accommodated by GNDs, or that these GNDs could influence some dislocation structures. The evidence simply indicates that misorientations are neither the primary element causing nucleation of dislocations nor the most influential factor in dislocation structure organization. \n\nThe observation that lattice misorientations increase with geometric constraints, and thus thermal stresses, is supported by additional larger-scale analysis of grain average misorientations and kernel average misorientations (KAM) obtained via EBSD analysis of the surfaces of bulk samples, shown in Supplemental Fig. 1 and 2. Generally, an increase in the average degree of misorientation and the KAM was observed with increasing geometric constraints. Studies investigating the correlations between these surface orientation analyses and dislocation structures are ongoing. \n\n# 4.5. Linking processing parameters and dislocation structures \n\nIf stresses and strains induced by thermal distortions dictate the dislocation density, and solidification microstructures (particularly primary dendrite arms) influence the dislocation organization, it is important to develop methods to control thermal distortions and solidification features. Thermal distortions/residual stresses and dendrite structures have been shown to be influenced by thermal gradients, cooling rate during solidification, and number of thermal cycles [5 45 46 , all of which can be controlled by manipulating AM processing parameters. \n\nCooling rate influences thermal distortions by setting the effective strain rate, since it would determine the time in which the volume shrinks, and by influencing local temperature and strain gradients. Cooling rate may be increased by increasing the volume of cooler substrate material surrounding the deposited hot melt pool, or by decreasing the temperature of the substrate relative to the melt. An increased volume of substrate relative to melt pool size was achieved in the current study as dimensions were increased from 1D to 3D. Part to melt pool volume ratio was also increased from DED to SLM for 3D parts, since 3D parts were similarly sized but the laser spot size was $600~{\\upmu\\mathrm{m}}$ in DED and $100~{\\upmu\\mathrm{m}}$ in SLM. In both situations an increase in dislocation density was observed. Cooling rate and thermal gradients were also increased in SLM relative to DED due to a lower substrate temperature in SLM, which occurred since the time between layers was longer in SLM to allow for recoating compared to the continuous deposition with DED. \n\nCooling rate during solidification also influences dendrite spacing, with higher cooling rates leading to smaller spacing (especially of secondary dendrite arms) [19] Increasing dendrite size has been shown to effectively increase the dislocation cell spacing in SLM 316L SS [5] \n\nThermal gradients control how localized thermal distortions are around the melt pool, and thus control strain localization. Higher strain localization would result in accommodation by locally higher dislocation densities, which, when produced throughout a part, would induce overall higher dislocation densities. Higher thermal gradients in SLM parts corresponded to higher dislocation densities compared to DED parts in this work. However, thermal gradient and cooling rate are directly related, so the sole influence of thermal gradient could not be discerned in this study, requiring additional work varying thermal gradients while keeping cooling rates constant. \n\nFinally, the number of heating and cooling cycles or laser scan passes within a layer can be expected to influence the dislocation density. If dislocations are induced each time material is heated by close proximity to the melt pool and subsequently cooled down, then increasing the number of cycles would increase the final density. It has been shown that decreasing the layer height, and thereby increasing the number of layers, increases distortion while reducing residual stresses [46] Since layers are smaller in SLM than in DED parts, a part of the same size experiences significantly more heating/cooling cycles in SLM, which would partially explain the differences observed in DED and SLM dislocation density. Additionally, DED parts experienced an increasing number of heating and cooling cycles with increasing dimensionality, starting from 1D rods which experienced no repeated cycling. \n\nDuring cooling from freezing temperature (approximately $1400^{\\circ}\\mathrm{C})$ to room temperature in SS 316L, thermal contraction can amount to local strains of up to $1.7\\%$ [17] Dislocation densities measured in SLM 316L both in this study, Table 4 and in other works, have indicated densities on the order of $10^{14}{-}10^{15}\\ \\mathrm{m}^{-2}$ in3D components, which is close to that observed at $20\\%$ cold work [4 13 47 . However, even single tracks of material deposited by AM have exhibited cellular dislocation structures without thermal cycling [8] Thus, thermal cycling is not considered to be a requirement for development of a dislocation structure, but represents a viable method to increase dislocation density if desired. \n\nIn conclusion, the results of this study suggest that controlling print parameters to manipulate cooling rate, thermal gradient, and number of passes/hatch spacing or number of layers would provide a viable means to control the dislocation structures in AM 316L SS, and ultimately the mechanical properties. \n\n# 5. Conclusions \n\nThis study is the first to reveal the origin of dislocation structures in AM SS 316L by systematically manipulating thermal stresses in AM components by altering the geometric constraints on the fabricated samples. The results indicated the following: \n\n1 The primary source of dislocations in AM materials is deformation induced by thermal expansion/shrinkage in a constrained medium. \n2 Dendritic micro-segregation influences dislocation structure orientation and scale if the average primary dendrite arm spacing is close to the average dislocation cell size that would form for the observed dislocation density. \n3 Constitutional stresses due to micro-segregation, coherency strains due to precipitation networks, and misorientations between dendrites are not the sources of dislocation structures in AM 316L SS. \n4 Features that can be controlled by manipulating processing parameters to influence dislocation structure development and density include: a Cooling rate. This determines the spacing of dendrite arms, which act as obstacles to dislocation motion, as well as the effective strain rate during cooling. b Thermal gradient. This determines the localization of the stresses and strains. c Hatch and layer spacing. These determine the number of heating and cooling cycles, which determines the number of times a part is distorted locally and the amount of accumulated strain that is accommodated by dislocations. d Melt pool penetration of the substrate. This determines the direction and magnitude of geometric constraints that are present around newly deposited material during shrinkage. \n\nThe relationships outlined above give several potential means of controlling the dislocation microstructure in AM materials to further improve properties and mechanical response. \n\n# Declaration of competing interest \n\nThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \n\n# Acknowledgements \n\nThe electron microscopy was carried out using facilities and instrumentation that are partially supported by the National Science Foundation (NSF) through the Materials Research Science and \n\nEngineering Center (DMR-1720415 . The authors would like to acknowledge further support from the Department of Energy / National Nuclear Security Administration under Award Number DENA0003921 the NSF-DMREF through the grant DMR-1728933 and NSF through the grant CMMI-1561899 Authors would also like to thank the Grainger Institute for Engineering for seeding this research activity. The EOS M290 was supported with UW2020 WARF Discovery Institute funds. KMB gratefully acknowledges support from Lawrence Livermore National Laboratory Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under Contract DE-AC52-07NA27344 Disclaimer: This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. \n\n# Supplementary materials \n\nSupplementary material associated with this article can be found, in the online version, at doi:10.1016/j.actamat.2020.07.063 \n\n# References \n\n[1] T. DebRoy, H.L. Wei, J.S. Zuback, T. Mukherjee, J.W. Elmer, J.O. Milewski, A M. Beese, A Wilson-Heid, A De, W. Zhang, Additive manufacturing of metallic components – Process, structure and properties, Prog. Mater Sci. 92 (2018) 112–224 https://doi.org/10.1016/j.pmatsci.2017.10.001 \n[2] W.E. Frazier, Metal Additive Manufacturing: A Review, J. Mater. Eng. Perform. 23 (6) (2014) 1917–1928 https://doi.org/10.1007/s11665-014-0958- . \n[3] D. Herzog, V. Seyda, E. Wycisk, C. Emmelmann, Additive manufacturing of metals, Acta Mater 117 (2016) 371–392 https://doi.org/10.1016/j.actamat.2016.07. 019 \n[4] M. Shamsujjoha, S.R. Agnew, J.M. Fitz-Gerald, W.R. Moore, T.A. Newman, High strength and ductility of additively manufactured 316L stainless steel explained, Metall. Mater. Trans. A 49 (7) (2018) 3011–3027 https://doi.org/10. 1007/s11661-018-4607-2. \n[5] L. Liu, Q. Ding, Y. Zhong, J. Zou, J. Wu, Y.-L. Chiu, J. Li, Z. Zhang, Q. Yu, Z. Shen, Dislocation network in additive manufactured steel breaks strength–ductility trade-off, Mater. Today 21 (4) (2018) 354–361 https://doi.org/10.1016/j.mattod. 2017.11.004. \n[6] Y.M. Wang, T. Voisin, J.T. McKeown, J. Ye, N.P. Calta, Z. Li, Z. Zeng, Y. Zhang, W. Chen, T.T. Roehling, R.T. Ott, M.K. Santala, Philip J. Depond, M.J. Matthews, A.V. Hamza, T. Zhu, Additively manufactured hierarchical stainless steels with high strength and ductility, Nat. Mater. 17 (2017) 63 https://doi.org/10.1038/ nmat5021. \n[7] C.A. Bronkhorst, J.R. Mayeur, V. Livescu, R. Pokharel, D.W. Brown, G.T. Gray, Structural representation of additively manufactured 316L austenitic stainless steel, Int. J. Plast. 118 (2019) 70–86 https://doi.org/10.1016/j.ijplas.2019.01.012 \n[8] K. Saeidi, X. Gao, Y. Zhong, Z.J. Shen, Hardened austenite steel with columnar sub-grain tructure ormed by aser melting, Mater. Sci. Eng. A 625 2015) 221– 229 https://doi.org/10.1016/j.msea.2014.12.018 \n[9] Y. Zhong, L. Liu, S. Wikman, D. Cui, Z. Shen, Intragranular cellular segregation network structure strengthening 316L stainless steel prepared by selective laser melting, J, Nucl. Mater. 470 (2016) 170–178 https://doi.org/10.1016/j. jnucmat.2015.12.034. \n10] Z. Sun, X. Tan, S.B. Tor, W.Y. Yeong, Selective laser melting of stainless steel 316L with low porosity and high build rates, Mater. Des 104 (2016) 197–204 https://doi.org/10.1016/j.matdes.2016.05.035 \n[11] A Rukwied, A W. Ruff, W.A. Willard, Study of the cellular solidification structure in a continuously cast high purity copper, Metall. Mater. Trans. B 2 (8) (1971) 2105–2114 https://doi.org/10.1007/bf02917538. \n[12] D.W. Brown, D.P. Adams, L. Balogh, J.S. Carpenter, B. Clausen, G. King, B. Reedlunn, T.A. Palmer, M.C. Maguire, S.C. Vogel, In situ neutron diffraction study of the influence of microstructure on the mechanical response of additively manufactured 304L tainless teel, Metall. Mater. Trans. A 48 12) 2017) 6055– 6069 https://doi.org/10.1007/s11661-017-4330-4 \n[13] R. Pokharel, . Balogh, D.W. Brown, B. Clausen, G.T. Gray, V. Livescu, S.C. Vogel, S. Takajo, Signatures of the unique microstructure of additively manufactured steel observed via diffraction, Scripta Mater 155 (2018) 16–20 https://doi.org/ 10.1016/j.scriptamat.2018.06.008 \n[14] D.A. Ramirez, L.E. Murr, E. Martinez, D.H. Hernandez, J.L. Martinez, B.I. Machado, F. Medina, P. Frigola, R.B. Wicker, Novel precipitate– microstructural architecture developed in the fabrication of solid copper components by additive manufacturing using electron beam melting, Acta Mater 59 (10) (2011) 4088–4099 https://doi.org/10.1016/j.actamat.2011.03.033 \n[15] Y.S.J. Yoo, T.A. Book, M.D. Sangid, J. Kacher, Identifying strain localization and dislocation processes n atigued nconel 718 manufactured rom elective aser melting, Mater. Sci. Eng. A 724 (2018) 444–451 https://doi.org/10.1016/j.msea. 2018.03.127. \n[16] B. Barkia, P. Aubry, P. Haghi-Ashtiani, T. Auger, L. Gosmain, F. Schuster, H. Maskrot, On the origin of the high tensile strength and ductility of additively manufactured 316L stainless steel: Multiscale investigation, J, Mater. Sci. Technol. 41 (2020) 209–218 https://doi.org/10.1016/j.jmst.2019.09.017 \n[17] S. Gorsse, C. Hutchinson, M. Gouné, R. Banerjee, Additive manufacturing of metals: a brief review of the characteristic microstructures and properties of steels, Ti-6Al-4V and high-entropy alloys, Sci. Technol. Adv. Mat. 18 (1) (2017) 584–610, doi:10.1080/14686996.2017.1361305 \n[18] A.J. Birnbaum, J.C. Steuben, E.J. Barrick, A.P. Iliopoulos, J.G. Michopoulos, Intrinsic strain aging, \u00053 boundaries, and origins of cellular substructure in additively manufactured 316L, Addit. Manuf. 29 2019) 100784 https://doi.org/10. 1016/j.addma.2019.100784 \n[19] W. Kurz D.J. Fisher ,, Fundamentals of solidification, Trans Tech Publications, Aedermannsdorf, Switzerland, 1986. \n[20] F. Bachmann, R. Hielscher, H. Schaeben, Grain detection from 2d and 3d EBSD data—Specification of the MTEX algorithm, Ultramicroscopy 111 (12) (2011) 1720–1733 https://doi.org/10.1016/j.ultramic.2011.08.002 \n[21] D.A. Porter, K.E. Easterling, Phase transformations in metals and alloys Van Nostrand Reinhold, New York, 1981. \n[22] J.W. Elmer, S.M. Allen, T.W. Eagar, Microstructural development during solidification of stainless steel alloys, Metall. Trans. A 20 (10) (1989) 2117–2131 https://doi.org/10.1007/bf02650298. \n[23] D.J. Thoma, G.K. ewis, R.B. Nemec, Solidification behavior during directed ight fabrication, Los Alamos National Laboratory, 1995. \n[24] D.J.C. Thoma, Lewis, G.K. & Nemec, R.B. , Directed light fabrication of ironbased materials, Los Alamos National Laboratory, 1995. \n[25] D.M. Norfleet, D.M. Dimiduk, S.J. Polasik, M.D. Uchic, M.J. Mills, Dislocation structures and their relationship to strength in deformed nickel microcrystals, Acta Mater. 56 (13) (2008) 2988–3001 https://doi.org/10.1016/j.actamat.2008. 02.046. \n[26] P.B. Hirsch, Electron microscopy of thin crystals, Butterworths, London, 1965. \n[27] M.R. Staker, D.L. Holt, The dislocation cell size and dislocation density in copper deformed at temperatures between 25 and $700^{\\circ}\\mathsf C$ Acta Metall. 20 (4) (1972) 569–579 https://doi.org/10.1016/0001-6160(72)90012-0 \n[28] X. eaugas, H. Haddou, Grain-size effects on ensile behavior of nickel nd AISI 316L stainless steel, Metall. Mater. Trans. A 34 (10) (2003) 2329–2340 https: //doi.org/10.1007/s11661-003-0296-5 \n[29] X. Feaugas, H. Haddou, Effects of grain size on dislocation organization and internal tresses developed under ensile oading n cc metals, Philos. Mag. 87 (7) (2007) 989–1018 https://doi.org/10.1080/14786430601019441 \n[30] T.G. Gallmeyer, S. Moorthy, B.B. Kappes, M.J. Mills, B. Amin-Ahmadi, A.P. Stebner, Knowledge of process-structure-property relationships to engineer better heat treatments for laser powder bed fusion additive manufactured Inconel 718, Addit. Manuf. 31 (2020) 100977 https://doi.org/10.1016/j.addma. \n2019.100977 [31] P. Krakhmalev, G. redriksson, K. Svensson, . Yadroitsev, . Yadroitsava, M. Thuvander, R. Peng, Microstructure, solidification texture, and thermal stability of \n316 L stainless steel manufactured by laser powder bed fusion, Metals 8 (8) (2018) 643 https://doi.org/10.3390/met8080643 [32] Y. Zhong, L. Liu, J. Zou, X. Li, D. Cui, Z. Shen, Oxide dispersion strengthened stainless steel 316L with superior strength and ductility by selective laser melting, , Mater. Sci. Technol. 2019) https://doi.org/10.1016/j.jmst.2019.11.004 [33] G. Meric de Bellefon, K.M. Bertsch, M.R. Chancey, Y.Q. Wang, D.J. Thoma, nfluence of olidification tructures on adiation-induced welling n n dditivelymanufactured austenitic stainless steel, J, Nucl. Mater. 523 (2019) 291–298 https://doi.org/10.1016/j.jnucmat.2019.06.012 [34] D. Kuhlmann-Wilsdorf, Theory of plastic deformation: - properties of low energy dislocation structures, Mater. Sci. Eng. A 113 (1989) 1–41 http://dx.doi. org/10.1016/0921-5093(89)90290-6 [35] D. Kuhlmann-Wilsdorf, J.H. Van Der Merwe, Theory of dislocation cell sizes in deformed metals, Mater. Sci. Eng. 55 (1) (1982) 79–83 https://doi.org/10.1016/ \n0025-5416(82)90086-6 [36] N. Hansen, New discoveries n deformed metals, Metall. Mater. Trans. A 32 12) (2001) 2917–2935 https://doi.org/10.1007/s11661-001-0167- $\\mathbf{\\boldsymbol{x}}.$ [37] D.J. Michel, J. Moteff, A.J. Lovell, Substructure of type 316 stainless steel deformed in slow tension at temperatures between $21^{\\circ}$ and $816^{\\circ}C$ Acta Metall. \n21 (9) (1973) 1269–1277 https://doi.org/10.1016/0001-6160(73)90168-5 [38] S.N. Monteiro, H.-J. Kestenbach, Influence of grain orientation on the dislocation ubstructure in austenitic stainless steel, Metall. Trans. A 6 (4) (1975) 938 https://doi.org/10.1007/bf02672323 [39] D.L. Holt, Dislocation cell formation in metals, J, Appl. Phys. 41 (8) (1970) \n3197–3201 https://doi.org/10.1063/1.1659399 [40] U.F. Kocks, H. Mecking, Physics and phenomenology of strain hardening: the FCC case, Prog. Mater Sci. 48 (3) (2003) 171–273 https://doi.org/10.1016/ S0079-6425(02)00003-8. [41] D.A. Hughes, Q. Liu, D.C. Chrzan, N. Hansen, Scaling of microstructural parameters: Misorientations of deformation induced boundaries, Acta Mater 45 (1) (1997) 105–112 https://doi.org/10.1016/S1359-6454(96)00153-X. [42] D.L. McDowell, A persp on trends in multiscale plasticity, Int. J. Plast. 26 (9) (2010) 1280–1309 /doi.org/10.1016/j.ijplas.2010.02.008. [43] H. Mughrabi, On the role train gradients and long-range internal stresses in the composite model ystal plasticity, Mater. Sci. Eng. A 317 (1) (2001) \n171–180 https:/ /S0921-5093(01)01173-X [44] D. Kuhlmann-Wilsdorf, Hansen Geometrically necessary, incidental and subgrain boundaries, Scr. Metall. Mater. 25 (7) (1991) 1557–1562 https://doi. org/10.1016/0956-716X(91)904 [45] T. Mukherjee, H.L. Wei, A. De, . DebRoy, Heat and fluid flow in additive manufacturing – Part II: Powder bed fusion of stainless steel, and titanium, nickel and aluminum base alloys, Comput. Mater. Sci. 150 (2018) 369–380 https://doi.org/10.1016/j.commatsci.2018.04.027 [46] T. Mukherjee, W. Zhang, T. DebRoy, An mproved prediction of esidual tresses and distortion in additive manufacturing, Comput. Mater. Sci. 126 (2017) 360– \n372 https://doi.org/10.1016/j.commatsci.2016.10.003 [47] S. Murugesan, P. Kuppusami, E. Mohandas, M. Vijayalakshmi, X-ray diffraction Rietveld analysis of cold worked austenitic stainless steel, Mater. Lett. 67 (1) (2012) 173–176 https://doi.org/10.1016/j.matlet.2011.09.065 " + }, + { + "id": "10.1038_s41560-020-0577-x", + "DOI": "10.1038/s41560-020-0577-x", + "DOI Link": "http://dx.doi.org/10.1038/s41560-020-0577-x", + "Relative Dir Path": "mds/10.1038_s41560-020-0577-x", + "Article Title": "Highly quaternized polystyrene ionomers for high performance anion exchange membrane water electrolysers", + "Authors": "Li, DG; Park, EJ; Zhu, WL; Shi, QR; Zhou, Y; Tian, HY; Lin, YH; Serov, A; Zulevi, B; Baca, ED; Fujimoto, C; Chung, HT; Kim, YS", + "Source Title": "NATURE ENERGY", + "Abstract": "Alkaline anion exchange membrane (AEM) electrolysers to produce hydrogen from water are still at an early stage of development, and their performance is far lower than that of systems based on proton exchange membranes. Here, we report an ammonium-enriched anion exchange ionomer that improves the performance of an AEM electrolyser to levels approaching that of state-of-the-art proton exchange membrane electrolysers. Using rotating-disk electrode experiments, we show that a high pH (>13) in the electrode binder is the critical factor for improving the activity of the hydrogen- and oxygen-evolution reactions in AEM electrolysers. Based on this observation, we prepared and tested several quaternized polystyrene electrode binders in an AEM electrolyser. Using the binder with the highest ionic concentration and a NiFe oxygen evolution catalyst, we demonstrated performance of 2.7 A cm(-2) at 1.8 V without a corrosive circulating alkaline solution. The limited durability of the AEM electrolyser remains a challenge to be addressed in the future. Anion exchange membrane water electrolysers have potential cost advantages over proton exchange membrane electrolysers, but their performance has lagged behind. Here the authors investigate the cause of the poor performance of anion exchange membrane electrolysers and design ionomers that can overcome some of the challenges.", + "Times Cited, WoS Core": 490, + "Times Cited, All Databases": 517, + "Publication Year": 2020, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000518736900003", + "Markdown": "# Highly quaternized polystyrene ionomers for high performance anion exchange membrane water electrolysers \n\nDongguo Li   1,5, Eun Joo Park1,5, Wenlei Zhu2,5, Qiurong $\\mathsf{S h i}^{2}$ , Yang Zhou2, Hangyu Tian2, Yuehe Lin   2 ✉, Alexey Serov $\\textcircled{10}3$ , Barr Zulevi $\\textcircled{10}3$ , Ehren Donel Baca $\\textcircled{10}4$ , Cy Fujimoto4, Hoon T. Chung1 and Yu Seung Kim   1 ✉ \n\nAlkaline anion exchange membrane (AEM) electrolysers to produce hydrogen from water are still at an early stage of development, and their performance is far lower than that of systems based on proton exchange membranes. Here, we report an ammonium-enriched anion exchange ionomer that improves the performance of an AEM electrolyser to levels approaching that of state-of-the-art proton exchange membrane electrolysers. Using rotating-disk electrode experiments, we show that a high pH $(>13)$ in the electrode binder is the critical factor for improving the activity of the hydrogen- and oxygen-evolution reactions in AEM electrolysers. Based on this observation, we prepared and tested several quaternized polystyrene electrode binders in an AEM electrolyser. Using the binder with the highest ionic concentration and a NiFe oxygen evolution catalyst, we demonstrated performance of $2.7\\mathsf{A c m}^{-2}$ at 1.8 V without a corrosive circulating alkaline solution. The limited durability of the AEM electrolyser remains a challenge to be addressed in the future. \n\nater electrolysis utilizes electrical energy to split water into hydrogen and oxygen. Low-temperature water electrolysis represents a key technology for a renewable energy economy as it can be used to efficiently store the electricity from renewable energy sources in chemical bonds in the form of high-purity hydrogen1. Low-temperature water electrolysis uses either a concentrated KOH solution, proton exchange membrane (PEM) or AEM as the electrolyte2. \n\nThe primary advantage of water electrolysis with a circulating alkaline solution is that it allows for the use of inexpensive platinum group metal (PGM)-free catalysts, which perform as well as or better than PGM-based catalysts under alkaline conditions3,4. However, relatively low hydrogen production rates and the sensitivity to differential pressures have been significant limitations of the use of alkaline electrolysers5. In traditional alkaline electrolysers, the liquid alkaline electrolyte $(30-40\\mathrm{wt\\%}$ KOH) is circulated through the electrodes, which are separated by a porous diaphragm membrane (Fig. 1a). \n\nTypical alkaline water electrolysis operates at a current density of $300{-}400\\operatorname*{mAcm}^{-2}$ at $60{-}90^{\\circ}\\mathrm{C}$ with a cell voltage between $1.7{-}2.4\\mathrm{V}$ (refs. 3,6). Furthermore, the liquid KOH electrolyte is highly sensitive to $\\mathrm{CO}_{2}$ in the ambient air, readily forming ${\\mathrm{K}}_{2}{\\mathrm{CO}}_{3}$ (ref. 7). The formation of ${\\mathrm{K}}_{2}{\\mathrm{CO}}_{3}$ reduces the anodic reaction and ionic conductivity8, and ${\\mathrm{K}}_{2}{\\mathrm{CO}}_{3}$ precipitates in the pores of the gas diffusion layer to block ion transfer9. Therefore, the overall performance of electrolysis decreases when using a KOH solution as an electrolyte. \n\nElectrolysers based on ion exchange membranes can replace the liquid electrolyte with a polymer electrolyte; thus, they do not require the circulation of a liquid electrolyte. PEM water electrolysers typically operate at higher constant current densities ( $1{-}3\\operatorname{Acm}^{-2}$ at ${\\sim}2.0\\mathrm{V}.$ than that of alkaline electrolysers because a highly conductive PEM is used (Fig. 1b). Recently, much higher current densities have been reported (for example, $6\\mathrm{Acm}^{-2}$ at $1.92\\mathrm{V}$ (ref. 10) and ${\\sim}20\\mathrm{Acm}^{-2}$ at ${\\sim}2.8\\mathrm{V}$ (ref. 11)). The use of solid electrolytes in PEM water electrolysis allows compact system design with durable/resistant structural properties at high differential pressures $(200{-}400\\mathrm{psi})^{12,13}$ . The operation of an electrolyser at high differential pressures brings the advantage of delivering pressurized hydrogen to the end-user14. However, one distinct disadvantage of PEM water electrolysis is the high capital cost of the cell stack due to expensive acid-tolerant stack hardware, as well as the high PGM loading required for the electrodes15. \n\nOver the past few years, polymeric AEMs have been developed for electrochemical devices (Fig. $\\mathrm{1c)^{16-18}}$ . Alkaline AEM electrolysis offers the benefits of both PEM electrolysis and electrolysis with a circulating liquid electrolyte, including the possible use of PGMfree catalysts without much performance loss19–21; the use of pure water or a low concentration of the alkaline solution instead of concentrated alkaline electrolytes; and low ohmic loss due to the highly conductive and thin AEMs, comparable to that of PEMs. In addition, the membrane-based design allows a differential pressure operation and reduction in the size and weight of the electrolyser, and the hydrocarbon membranes used in AEMs are less expensive than the perfluorinated membranes used in PEM electrolysers. \n\nThe reported performance of AEM electrolysers is reasonably high with a circulating alkaline electrolyte. Outstanding performance has been reported for an AEM electrolyser using Sustainion, a polystyrene-based membrane with quaternized imidazolium as an anion exchangeable group22. In that work, the researchers obtained $1\\mathrm{Acm}^{-2}$ in 1 M KOH at $60^{\\circ}\\mathrm{C}$ at $1.63\\mathrm{V}$ for a PGM catalyst and $1.9\\mathrm{V}$ for a PGM-free catalyst. Recently, even better performance has been reported using a membrane-based alkaline electrolyser with nickelbased electrodes23. The researchers obtained $1.7\\mathrm{Acm}^{-2}$ at $1.8\\mathrm{V}$ with a circulating $24\\mathrm{wt\\%}$ KOH solution (over 5 M) at $80^{\\circ}\\mathrm{C}.$ . However, the use of a corrosive, concentrated alkaline electrolyte is a significant disadvantage to the membrane-based alkaline electrolyser system. By stark contrast, the performance of pure water-fed AEM electrolysers has been reported to be much lower. To our knowledge, the best-reported performance for a pure water-fed AEM electrolyser so far is $400\\mathrm{mAcm}^{-2}$ at $1.8\\mathrm{V}$ (refs. 24–28), which is more than one order of magnitude smaller than its state-of-the-art PEM counterpart14. The low efficiency of the pure water-fed AEM electrolyser is puzzling, considering that the performance of state-of-the-art AEM fuel cells is approaching, or even surpassing, that of PEM fuel cells29–32. \n\n![](images/1da4b637ddb58c99364c0bce9fc8f141f4eab867d03d0ad105bf70af5aab6d54.jpg) \nFig. 1 | Schematic of low-temperature water electrolysis cells. a, KOH-circulating alkaline electrolyser consisting of a PGM-free electrode (Ni, Fe), diaphragm membrane and ${\\mathsf{K O H}}$ electrolyte. b, PEM electrolyser consisting of a PGM-based porous electrode $(\\mathsf{I r O}_{2},$ Pt), perfluorosulfonic acid PEM/ionomer and PGM current collectors. c, AEM electrolyser consisting of a PGM-free electrode (Ni based), hydrocarbon AEM/ionomer and PGM-free current collectors. \n\nHere, we report a systematic approach to achieve a high-performance AEM electrolyser. We found that the high concentration of the quaternary ammonium group is required for the high activity of the hydrogen and oxygen evolution reactions in an AEM electrolyser. We also found that phenyl groups in the ionomer backbone have a detrimental impact by forming acidic phenols at high anode potentials. We designed highly quaternized polystyrene ionomers to demonstrate AEM electrolyser performance comparable with that of a state-of-the-art PEM electrolyser. Finally, we discuss the durability challenge of the AEM electrolyser as a future direction. \n\n# Performance-limiting factors of AEM electrolysers \n\nTo investigate the performance-limiting factors of the AEM electrolyser, we performed several rotating disk electrode (RDE) experiments. The RDE experiments provide information on the different requirements of electrolytes used in fuel cell and electrolyser operations by measuring the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), oxygen reduction reaction (ORR) and hydrogen oxidation reaction (HOR). \n\nFigure 2 shows the polarization curves of the OER using $\\mathrm{IrO}_{2}$ and HER using a polycrystalline platinum electrode (Pt poly) as a function of NaOH concentration. The OER and HER activity for the AEM electrolyser significantly increased as the NaOH concentration increased from $0.01\\mathrm{M}$ $\\mathrm{(pH}=12,$ ) to 1 M $\\mathrm{\\langlepH=14\\rangle}$ ). By contrast, the electrochemical activity of fuel cells showed a maximum at an intermediate NaOH concentration. The HOR activity of $\\mathrm{Pt}$ poly exhibited maximum activity at $0.02\\mathrm{M}\\mathrm{NaOH}$ (Fig. 2b, inset). The HOR activity loss at a higher NaOH concentration $(>0.1\\mathrm{M})$ was accompanied by a lower diffusion-limiting current density, too. The lower HOR activity of $\\mathrm{\\Pt}$ poly with the concentrated \n\nNaOH solution is explained by cumulative cation–hydroxide–water co-adsorption33,34, which limits the hydrogen access to the catalyst surface. The co-adsorption does not impact the HER and OER activity as the adsorption occurs from 0 to $0.9\\mathrm{V}.$ The impact of the $\\mathrm{\\DeltaNaOH}$ concentration on the ORR activity of Pt poly showed a similar trend to that of HOR (Supplementary Fig. 1). The ORR activity of Pt poly increased as the NaOH concentration increased from 0.01 to $0.1\\mathrm{M}$ , then began to decrease as the NaOH concentration further increased to 1 M. Note that the diffusion-limiting current density of the ORR polarization curves also significantly decreased with the high concentration of NaOH. \n\nThese RDE results suggest that the concentration of ammonium hydroxide required for AEM electrolysers and AEM fuel cells may be different. For AEM electrolysers, an ionomer with a higher ionexchange capacity (IEC) is more desirable, but for AEM fuel cells, an ionomer with an intermediate IEC may perform better. For AEM fuel cells, ionomers with higher IEC cause limited gas transport due to undesirable cation–hydroxide–water co-adsorption. Furthermore, an ionomer with high IEC can create significant flooding in fuel cells. By contrast, electrode flooding does not take place for electrolysers. This observation is consistent with the fact that the high performance of alkaline electrolysers was obtained by circulating a high molar concentration of alkaline electrolyte35–37. \n\n# Ionomer design criteria for AEM electrolysers \n\nThe RDE experiments indicate that providing high pH $(>13)$ conditions in the electrodes is essential for preparing high-performance AEM electrolysers. Currently available anion exchange ionomers have two critical issues that may limit a high pH environment in AEM electrolysers. The first issue is the presence of phenyl groups in the ionomer backbone. Our recent studies have shown that the phenyl group in the ionomer backbone may be oxidized at OER potentials and produce a phenolic compound37, which is acidic $(\\mathsf{p}K_{\\mathrm{a}}\\mathsf{=}9.6)$ . Specifically, the proton in the phenol group can be deprotonated to neutralize the hydroxide of the ammonium functional groups. Unfortunately, most stable alkaline ionomers contain phenyl groups in their backbone structure. Consequently, AEM electrolysers using ionomers containing a phenyl group are not entirely free from adverse phenol formation. \n\nThere are a few essential observations regarding the electrochemical oxidation of the phenyl group. The rate of phenol formation is related to the adsorption energy of the phenyl group on the surface of OER catalysts38, and unsubstituted phenyl groups in the polymer side chain have a more detrimental impact compared with the ammonium-substituted phenyl group39. The structure and the size of the backbone fragments in the polyaromatics strongly influence the phenyl adsorption while the side-chain functionalized phenyl group showed a much lower adsorption energy because of the competing adsorption with ammonium groups40. In addition, $\\mathrm{Pt}$ bimetallic catalysts such as PtRu, PtNi or PtMo can efficiently reduce the phenyl adsorption energy. \n\n![](images/49c041123960aa3a6f6e1305e63c8597f1c6f80912999170bfa6dfc535a7a318.jpg) \nFig. 2 | Impact of NaOH concentration on activities of electrocatalysts. a, OER voltammogram of $\\mathsf{I r O}_{2}$ . b, HER/HOR voltammogram of Pt poly electrode (the magnified lower HOR potential region shown in the right inset). The OER and $H E R/H O R$ voltammograms were recorded with $I R$ drop correction. All curves were recorded at room temperature with a $10\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ scan rate and a rotating speed of 1,600 r.p.m. The cell potential is expressed versus reversible hydrogen electrode (RHE). \n\nThe second issue is the low concentration of ammonium hydroxide functional groups in anion exchange ionomers. The IEC of typical anion exchange ionomers developed for AEM fuel cells is usually around 1.5 mequiv. $\\mathbf{g}^{-1}$ (refs. $^{41,42}$ ). With the ionomer, the estimated ammonium concentration in the water-filled electrode is relatively low, ${\\sim}0.1\\mathrm{M}$ . Inhomogeneous distribution of the ionomer in the electrode further reduces the reaction efficiency and hydroxide conduction. Therefore, ionomers with a higher IEC should be beneficial to increase the performance of an AEM electrolyser. \n\nFor the synthesis of a high-IEC ionomer, several criteria need to be considered. First, there is a limitation on the maximum number of ammonium groups per polymer repeating unit. For example, the maximum IEC of the quaternized polyphenylene from the reported acid-catalysed synthetic route is 2.6 mequiv. $\\mathbf{g}^{-1}$ (ref. 43). Even with multi-cation functionalization, the maximum IEC of quaternized polymers is often limited to $\\sim3.0$ mequiv. $\\mathbf{g}^{-1}$ (refs. $^{44,45}$ ). Anion exchange ionomers with a high IEC often undergo a crosslinking reaction during the functionalization process, which makes further processing difficult. When anion exchange ionomers are synthesized to have a high IEC they often become soluble in water, thus unsuitable for electrode applications. \n\n![](images/e2b2c6ec5788e30ea53861eecb51e1c41abaf02af4fb325f2acdbc1c4527ff4d.jpg) \nFig. 3 | The chemical structure of the polymeric materials used for the study. a, A series of trimethyl ammonium functionalized polystyrenes (TMA- $\\cdot x)$ was used for ionomeric binders. b, HTMA-DAPP was used as the AEM. \n\n# Synthesis of AEM and model ionomers \n\nBased on the ionomer design strategy above, we prepared a series of trimethyl ammonium functionalized polystyrene ionomers (see Fig. 3a, TMA- $x,$ , where $x$ denotes the molar percentage of quaternized benzyl ammonium). The detailed synthetic procedures and characterization of the ionomers are described in the Methods and in Supplementary Table 1 and Supplementary Fig. 2. We designed the ionomers to have some unique characteristics compared with the conventional ionomeric binders developed for AEM fuel cells29–32. First, the aliphatic polymer backbone does not contain a phenyl group. The absence of the phenyl group in the polymer backbone removes the chance of possible phenyl adsorption and resultant acidic phenol formation. Second, the polymer backbone does not contain long non-ionic alkyl chains that may reduce the polymer solubility. Third, and most importantly, all phenyl groups in the side chains have substituted ammonium or amine groups that minimize phenyl group adsorption and help to maintain a high pH. \n\nWe have synthesized the ionomers and found their IECs to vary from 2.2 to 3.3 mequiv. $\\mathbf{g}^{-1}$ . For AEMs, we have prepared a hexamethyl trimethyl ammonium-functionalized Diels–Alder polyphenylene (HTMA-DAPP; Fig. 3b)46. The hydroxide conductivity of HTMA-DAPP was $120\\mathrm{mScm^{-1}}$ at $80^{\\circ}\\mathrm{C}$ . The polyphenylene backbone in the high-molecular-weight HTMA-DAPP polymer $(M_{\\mathrm{w}}{=}76,000\\mathrm{gmol^{-1}})$ provides excellent mechanical strength (tensile stress $\\mathrm{\\hbar}{>}20\\mathrm{MPa}$ at $90\\%$ relative humidity (RH) at $50^{\\circ}\\mathrm{C}$ ). By contrast, quaternized polystyrene is too brittle for casting membranes and is therefore not suitable for AEM water electrolyser applications that require mechanically stable AEMs. The alkaline stability of HTMA-DAPP is excellent, with minimal degradation for ${>}3,000\\mathrm{h}$ in $4\\mathrm{M}\\mathrm{NaOH}$ at $80^{\\circ}\\mathrm{C}$ (ref. 47). The alkaline stability of these AEMs allows for AEM electrolyser testing at an operating temperature of up to $85^{\\circ}\\mathrm{C}$ . \n\nSeveral operating parameters influence the performance of an AEM electrolyser. We evaluated the AEM electrolyser performance from a baseline membrane electrode assembly (MEA) fabricated with a $\\mathrm{Pt-Ru}$ cathode, $\\mathrm{IrO}_{2}$ anode, HTMA-DAPP AEM and the control HTMA-DAPP ionomer under different operating conditions (Supplementary Fig. 3). The ionomer content in the electrode was $4.5\\mathrm{wt\\%}$ , which was determined from the optimum ionomer content for AEM fuel cells30. Under pure water-fed conditions, the MEA exhibits a current density of $107\\mathrm{mAcm}^{-2}$ at $1.8\\mathrm{V}$ and $60^{\\circ}\\mathrm{C}$ . With a $0.1\\mathrm{MNaOH}$ feed, the performance increased 3.5-fold $(376\\mathrm{mA}\\mathrm{cm}^{-2}$ at $1.8\\mathrm{V}$ and $60^{\\circ}\\mathrm{C},$ ). As the operating temperature was increased to $85^{\\circ}\\mathrm{C},$ , the current density of the electrolyser fed pure water rose to $224\\mathrm{mAcm}^{-2}$ . The performance of this AEM electrolyser was comparable with that reported for a typical AEM electrolyser48. \n\n# Impact of ionomer on AEM electrolyser performance \n\nFigure 4a summarizes the progression of performance improvements in the electrolyser fed pure water using our ionomer design strategy. The first performance improvement was achieved by adjusting ionomer content. The current density of a MEA with $9\\mathrm{wt\\%}$ ionomer in the electrode (two times higher than the baseline) was $405\\mathrm{mAcm}^{-2}$ at $1.8\\mathrm{V}$ (red curve), which is a 1.8-fold increase from the baseline MEA. The higher performance may be due to the increased concentration of ammonium hydroxides in the electrode, which is beneficial to HER and OER. Next, we integrated a MEA with TMA ionomers that exhibited higher IEC values at the higher ionomer content. The performance of the MEA using TMA53 $\\mathrm{\\cdot}\\mathrm{IEC}=2.6$ mequiv. $\\mathbf{g}^{-1}.$ ) significantly increased (blue curve). At $1.8\\mathrm{V},$ the current density was $791\\mathrm{mAcm}^{-2}$ , a 2.0-fold increase from the MEA with TMA-45. The current density at $1.8\\mathrm{V}$ of the MEAs with TMA-62 (purple curve) and TMA-70 (green curve) further increased to 860 and $1,360\\mathrm{mAcm}^{-2}$ , respectively. The current density of TMA-70-bonded MEA was 1.7-fold higher than that of the TMA-53-bonded MEA and 6-fold higher than the baseline MEA at $1.8\\mathrm{V}.$ \n\nWe also investigated the impact of the phenyl group in the ionomer on the performance of the AEM electrolyser (Fig. 4b). For this experiment, we compared two MEAs, which were identical except for the electrode binder. The first one is an HTMA-DAPPbonded MEA, and the second is a TMA-53-bonded MEA. The ionomer content and IEC for the two MEAs were identical, $9\\mathrm{wt\\%}$ and 2.6 mequiv. $\\mathbf{g}^{-1}$ , respectively. When $0.1\\mathrm{M}\\ \\mathrm{NaOH}$ electrolyte was used, the electrolyser performance was similar $(954\\mathrm{mAcm}^{-2}$ for HTMA-DAPP MEA versus $1,052\\mathrm{mAcm}^{-2}$ for TMA-53 MEA at $1.8\\mathrm{V},$ . However, when pure water was used, the TMA-53-bonded MEA showed a notably superior performance compared with the DAPP-HTMA-bonded MEA $484\\mathrm{mA}\\mathrm{cm}^{-2}$ for HTMA-DAPP MEA versus $630\\mathrm{mAcm}^{-2}$ for TMA-53 MEA at 1.8 V). This result indicates that the electrolyser performance is less sensitive with $0.1\\mathrm{M}$ NaOH, probably because acidic phenols from phenyl group oxidation were neutralized by the alkaline solution. \n\nThe impact of the phenyl oxidation on the performance of the electrolyser fed pure water still appears to be small. However, we observed the adverse impact of phenyl oxidation is much more significant during the first few hours of operation. Supplementary Fig. 4 shows the cell voltage change of the HTMA-DAPP-based electrolyser at a constant current density of $100\\mathrm{mAcm}^{-2}$ . The cell voltage of the MEA rapidly increased from 1.6 to $2.1\\mathrm{V}$ within $^{3\\mathrm{h}}$ of operation at $60^{\\circ}\\mathrm{C},$ indicating that the performance loss due to the phenyl oxidation can be significant as more phenyl groups at the catalyst–ionomer interface oxidized in the relatively short time. We have estimated the extent of the oxidation reaction at the interface of the HTMA-DAPP ionomer and catalyst by measuring the $\\mathrm{\\pH}$ and ohmic resistance of the tetramethylammonium hydroxide (TMAOH) as a function of the concentration of phenol (Supplementary Table 2). The $\\mathrm{\\pH}$ of the $1.6\\mathrm{M}$ TMAOH solution decreases from 14.2 to 11.4 when only $25\\%$ of the phenyl group of the HTMA-DAPP polymer backbone is converted to phenol (Supplementary Fig. 5). Furthermore, the solution conductivity decreased substantially from 165 to $25\\mathrm{mScm^{-1}}$ , which also may impact the reaction kinetics of the electrocatalysts. These results indicated that ionomers with a phenyl-free backbone structure are beneficial to AEM electrolysers fed pure water. \n\nThe performance of the TMA-70-bonded MEA was further evaluated using PGM-free catalysts. For the anode, we selected a NiFe nanofoam catalyst49, as the OER activity of the PGM-free catalyst exhibited better performance than that of an $\\mathrm{IrO}_{2}$ catalyst in the RDE experiments (Supplementary Fig. 6). The detailed synthesis and scanning electron micrograph image of the NiFe catalyst are described in the Methods and Supplementary Fig. 7. \n\n![](images/52d00571409a1b8ee3dfc242c47e5bdc794f0a0016c503aa75d0496b59b38504.jpg) \nFig. 4 | Impact of ionomer on AEM performance. a, The performance of MEAs employing the TMA ionomers; AEM, HTMA-DAPP $26\\upmu\\mathrm{m}$ thick); anode, $\\cdot0_{_{2}}(2.5\\mathsf{m g}\\mathsf{c m}^{-2})$ ; cathode, $\\mathsf{P t R u/C}$ $50\\mathrm{wt\\%}$ Pt, $25w t\\%$ u, $2\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2})$ . Performance was measured at $85^{\\circ}C$ under ambient pressure with pure water circulating in the anode and cathode. b, Comparison of MEA performance between HTMA-DAPP-bonded and TMA-53-bonded MEAs at $60^{\\circ}\\mathsf C$ . \n\nThe optimum ionomer content of the NiFe anode catalyst was determined by measuring the MEA performance with four different ionomer content values (Supplementary Fig. 8). The ionomer content of around $20\\mathrm{wt\\%}$ exhibited the highest performance. Figure 5 shows the AEM electrolyser performance of the NiFeanode-catalysed MEAs under conditions of being fed 1 and $0.1\\mathrm{M}$ $\\mathrm{\\DeltaNaOH}$ solutions $(60^{\\circ}\\mathrm{C})$ and pure water $(85^{\\circ}\\mathrm{C})$ . We obtained high current densities, approximately 5.3, 3.2 and $2.7\\mathrm{Acm}^{-2}$ , at $1.8\\mathrm{V}$ under conditions of being fed 1 M NaOH, 0.1 M NaOH and pure water, respectively. The superior performance with the NiFe-anodecatalysed MEA compared with the $\\mathrm{IrO}_{2}$ -anode-catalysed MEA is consistent with the RDE results presented in Supplementary Fig. 6. Note that the performance of the electrolyser fed pure water is comparable with that of an electrolyser fed $1\\mathrm{M\\NaOH}$ at low potentials. However, the performance of the electrolyser fed pure water was limited at higher current densities, probably due to the reactant water mass transport issue. Supplementary Fig. 9 schematically describes the mass transport issue of the AEM electrolyser fed pure water. For the AEM electrolyser fed pure water, the interface between the catalyst and polymer electrolyte is smaller than that between the catalyst and polymer/liquid electrolyte of the electrolyser fed $1\\mathrm{MNaOH}.$ . At this condition, the transport of reactant water to the catalyst surface for the AEM electrolyser fed pure water is limited by the high concentration of product gas bubbles. In addition, the higher resistance of the electrolyser fed pure water impacts the overall performance in the region with higher cell voltage. \n\n![](images/33479553ec51a27016d2e8db2cd7448bd4ffc714cc0cf11a09d962a43a1ff8c1.jpg) \nFig. 5 | AEM electrolyser performance catalysed by a PGM-free anode. The performance of MEAs employing PGM-free catalysts (the magnified region of the current density between 0.0 and $0.6\\mathsf{A c m}^{-2}$ , shown in the inset). AEM, HTMA-DAPP $26\\upmu\\mathrm{m}$ thickness); anode, NiFe nanofoam $(3\\mathsf{m g c m^{-2}})$ ; cathode, $\\mathsf{P t R u/C}$ ( $50\\mathrm{wt\\%}$ Pt, $25\\mathsf{w t\\%}$ Ru, $2\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2})$ or NiMo/C ( $2\\mathsf{m g}_{\\mathsf{N i M o}}\\mathsf{c m}^{-2})$ . The ionomer content at the cathode was $20\\upnu\\up t\\%$ . The performance was measured under ambient pressure at $60^{\\circ}\\mathsf C$ for NaOH solution and $85^{\\circ}C$ for pure water flowing in both the anode and the cathode. The performance of a state-of-the-art PEM electrolyser11 is also shown. PEM electrolyser, PEM 3 M 825 EW $50\\upmu\\mathrm{m}$ thickness); anode, $0.25\\mathsf{m g c m^{-2}}|\\mathsf{r}$ -NSTF; cathode, $0.25\\mathsf{m g c m}^{-2}$ Pt-NSTF measured at $80^{\\circ}\\mathsf{C}$ . \n\nThe performance of the NiFe-anode-catalysed MEA was compared with that of a state-of-the-art PEM electrolyser using PGM catalysts11. In the kinetic region, at cell voltages of less than $1.58\\mathrm{V}, $ the NiFe-catalysed MEA outperformed the PEM electrolyser (Fig. 5, inset). For example, at $1.5\\mathrm{V},$ the current density of the NiFecatalysed MEA was $300\\mathrm{mAcm}^{-2}$ , which is approximately two times higher than that of the PEM MEA catalysed by $\\mathrm{IrO}_{2}$ and a nanostructured thin film (NSTF). However, in the mass-transport-controlled region, at a cell current density greater than $\\sim1\\mathrm{Acm}^{-2}$ , the PEM-based MEA outperformed the AEM-based MEA. The AEM electrolyser with a circulating 1 M KOH solution showed comparable performance with the PEM electrolyser in the region of high current density. \n\nWe have further investigated the performance of the TMA-70- bonded MEAs using PGM-free NiMo/C HER catalyst50. The HER activity of the NiMo/C catalyst was significantly lower compared with the $\\mathrm{PtRu/C}$ catalyst (Supplementary Fig. 10); the overpotential of NiMo/C was $82\\mathrm{mV}$ at $-1\\mathrm{mA}\\mathrm{cm}^{-2}$ versus $13\\mathrm{mV}$ for $\\mathrm{PtRu/C}$ . The detailed synthesis and X-ray powder diffraction pattern of the NiMo catalysts are described in the Methods and Supplementary Fig. 11. The performance of the NiMo/C-cathode-catalysed MEA was relatively low compared with the $\\mathrm{PtRu/C}$ -cathode-catalysed MEA, which is in line with our RDE results. Nonetheless, we obtained a high current density of $906\\mathrm{mAcm}^{-2}$ at $1.8\\mathrm{V}.$ The performance of the PGM-free MEA can be compared with that of a PGM-free Sustainion-based MEA (Supplementary Fig. 12). The performance of TMA-70-bonded MEAs exceeds the previously reported best-performing Sustainion-based MEA in 1 M alkaline solution $\\mathrm{(1,717{mAcm}^{-2}}$ for TMA-70 MEA versus $495\\mathrm{mAcm}^{-2}$ for Sustainion MEA at $1.8\\mathrm{V}$ ). Note that both high-performing polymer electrolytes are quaternized ammonium polystyrenes (polymer backbone free of phenyl groups). However, TMA-70 has a much higher IEC (3.3 versus 1.1 mequiv. $\\mathbf{g}^{-1}$ ), thus providing higher $\\mathrm{\\pH}$ conditions, which confirms our strategy toward making higherperforming AEM electrolysers. \n\n![](images/e9b9235ba9bf51a0e949a95d3bd53ddd34956c3e4307e7e6572d9b714c71a60d.jpg) \nFig. 6 | Durability of AEM electrolysers catalysed by NiFe anodes. a, Durability of the MEAs using the TMA-70 ionomer at $85^{\\circ}C$ and $60^{\\circ}\\mathsf C$ at a constant current density of $200\\mathsf{m A c m^{-2}}$ . b, Durability of the MEA using the TMA-53 ionomer at $60^{\\circ}\\mathsf C$ at a constant current density of $200\\mathsf{m A c m}^{-2}$ . In all cases, deionized water was flowing on the anode only, and HTMA-DAPP and $\\mathsf{P t R u/C}$ were used as the AEM and the catalyst on the cathode, respectively. \n\nWe also investigated the durability of the AEM electrolyser fed pure water. Figure 6a shows a short-term durability test of a NiFe-catalysed AEM electrolyser at a constant current density of $200\\mathrm{mAcm}^{-2}$ . At both 60 and $85^{\\circ}\\mathrm{C},$ the cell voltage rapidly increased within $\\mathord{\\sim}10\\mathrm{h}$ . We observed that catalyst particles were washed out from both the anode and cathode outlet streams, suggesting that the high IEC ionomer (TMA-70) did not hold the catalyst particles during continuous operation. The binding strength of the ionomer increased as we used the same ionomer with a lower IEC at $60^{\\circ}\\mathrm{C}$ Figure 6b shows the short-term durability test of the AEM electrolyser using the TMA-53 ionomer. Note that the cell potential is stable for more than $\\boldsymbol{100}\\mathrm{h}$ after an initial voltage increase from 1.75 to $2.1\\mathrm{V}.$ The initial voltage increase during the first $40\\mathrm{{h}}$ is likely due to phenyl oxidation, which occurred at a much slower rate compared with the all-HTMA-TMA system shown in Supplementary Fig. 4. The limited durability shown in Fig. 6 indicates that more research is needed on the long-term stability of the electrolyser for it to make a practical system. \n\n# Conclusions \n\nIn this paper, we presented a model electrode binder that boosts the AEM electrolyser performance to be comparable with that of state-of-the-art PEM electrolysers but using a PGM-free catalyst. The electrode binder was synthesized based on the RDE results that showed the importance of high local pH for efficient HER and OER. By removing the phenyl groups from the polymer backbone, we can prevent acidic phenol formation that can neutralize the quaternary ammonium hydroxide and reduce the electrolyte $\\mathrm{\\DeltapH}$ . Further, a $\\mathrm{\\pH}$ increase of the electrodes was achieved by increasing ionomer content and IEC. The AEM electrolyser employing the quaternized ammonium polystyrene ionomer exhibited outstanding performance even without a circulating alkaline solution. Notably, the performance of $2.7\\mathrm{Acm}^{-2}$ at $1.8\\mathrm{V}$ and $85^{\\circ}\\mathrm{C}$ with a NiFe OER catalyst demonstrates the potential of combining the benefits of PEM electrolysers and cost-efficient alkaline electrolysers. This study also showed a MEA activity of $900\\mathrm{mAcm}^{-2}$ at $1.8\\mathrm{V}$ for NiMo/C-catalysed HER and NiFe-catalysed OER. The relatively low performance of the NiMo/C–HER catalyst suggests more research is needed for further performance improvements in AEM electrolysers. In addition, improving the durability of the water-fed electrolyser would be the next technical challenge for a practical system. The approach demonstrated in this manuscript provides critical insight towards the preparation of high-performing AEM water electrolyser systems that could be more cost effective and lead to more-efficient clean-energy storage opportunities. \n\n# Methods \n\nPreparation of quaternized polystyrene. The quaternized polystyrene was synthesized using polyvinyl benzyl chloride and subsequent quaternization to yield trimethylammonium as the cation (Supplementary Fig. 2a). The general procedure of quaternized polystyrene51 is described. Polyvinylbenzyl chloride $\\mathrm{500mg}$ , Sigma-Aldrich) was dissolved in dimethyl sulfoxide (DMSO; $15\\mathrm{ml}$ ) in a $40\\mathrm{ml}$ vial, and trimethylamine (0.7 equiv. for TMA-70, $50\\mathrm{wt\\%}$ aq. solution) was added to the solution. After stirring at room temperature for 3 h, 4-fluorophenythylamine (0.33 equiv.) was added, and the solution was stirred for $12\\mathrm{h}$ at $80^{\\circ}\\mathrm{C}$ . The solution was precipitated in a mixture of ethyl acetate and tetrahydrofuran and washed thoroughly to isolate the product as an off-white powder. The powder was dissolved in methanol and precipitated in ethyl acetate for purification. The powder was treated with $1\\mathrm{MNaOH}$ solution to exchange counter ions with hydroxide, washed thoroughly with deionized water and dried under vacuum. The obtained ionomer was then dissolved in ethanol to make a $5\\mathrm{wt\\%}$ ionomeric binder solution. The solubility of the ionomer was controlled by the ratio of hydrophilic and hydrophobic blocks of the ionomer and its counter anion. The synthesized ionomers with an IEC of 2.2 to 3.3 mequiv. $\\mathbf{g}^{-1}$ in hydroxide form are readily soluble in alcoholic solvents, including methanol, ethanol and ethylene glycol. The highIEC ionomer (3.3 mequiv. $\\mathbf{g}^{-1})$ in chloride form is soluble in water; however, once the counter anion was replaced with hydroxide, the solubility in water was much decreased. The ionomers with an IEC value of ${>}3.3$ mequiv. $\\mathbf{g}^{-1}$ are soluble in water regardless of the counter anion, and would not be suitable for the AEM electrolyser. \n\nPreparation of quaternized polyphenylene. HTMA-DAPP was prepared as described in previous papers39,46,47. First, brominated alkyl-ketone-functionalized DAPP was synthesized by reacting DAPP with 6-bromohexanoyl chloride in the presence of aluminium chloride. The ketone group of the polymer was reduced with trifluoroacetic acid and triethylsilane. The brominated polymer was cast onto a glass plate from chloroform. After drying, the membrane was aminated by immersing in trimethylamine solution $45\\%$ wt/wt in water) for $48\\mathrm{h}$ . The resulting membrane was then immersed in $0.5\\mathrm{M}$ HBr for $2\\mathrm{h}$ to convert the membrane to a brominated form. The brominated membrane was converted to a hydroxide form by immersing in $0.5\\mathrm{MNaOH}$ at $80^{\\circ}\\mathrm{C}$ Ionomer dispersion was prepared from the brominated membrane by dissolving in DMSO ( $5\\mathrm{wt\\%}$ solution) at $80^{\\circ}\\mathrm{C}$ . \n\nIonomer structure characterization. The $\\mathrm{^{1}H}$ nuclear magnetic resonance (NMR) spectra were collected with a Bruker $500\\mathrm{NMR}$ spectrometer at room temperature, and chemical shifts were referenced to the solvent residue peak of DMSO- $\\mathbf{d}_{6}$ at \n\n$2.50\\mathrm{ppm}$ . The experimental IEC values of the ionomers in chloride form were determined by Mohr titration. A sample of ionomers $\\mathrm{100\\pm5mg}$ in chloride form) was fully dissolved in deionized water $(10\\mathrm{ml})$ with heating and sonication. The ionomer solution was titrated with $0.1\\mathrm{M}\\mathrm{Ag}\\mathrm{NO}_{3}$ using $\\mathrm{K_{2}C r O_{4}}$ as a colorimetric indicator. The experimental IEC of the ionomers (mequiv. $\\mathbf{g}^{-1}.$ ) was calculated from the following equation: \n\n$$\n\\mathrm{IEC}\\left(\\mathrm{mequiv.g^{-1}}\\right)=\\left(\\Delta V_{\\mathrm{AgNO3}}\\times C_{\\mathrm{AgNO3}}\\right)/W_{\\mathrm{dry}}\n$$ \n\nwhere $V_{\\mathrm{AgNO3}}$ is the volume of $\\mathrm{AgNO}_{3}$ titrated, $C_{_{\\mathrm{AgNO3}}}$ is the concentration of $\\mathrm{AgNO}_{3}$ solution and $W_{\\mathrm{dry}}$ is the dry mass of the ionomer. The average IEC value from two titration methods was used for each ionomer sample. \n\nIon conductivity of polystyrene ionomers. Due to the brittle nature of the polystyrene-based ionomers, the ion conductivity in chloride form was measured in solution form in deionized water at the same molar concentration at $80^{\\circ}\\mathrm{C}$ for comparison52. The solution ionic conductivity of the ionomers was measured with AC electrochemical impedance spectroscopy (Solartron 1260 gain-phase analyser) using a custom liquid cell with stainless steel electrodes (electrode diameter $1\\mathrm{cm}$ ), that were $1\\mathrm{cm}$ apart, encased in polypropylene casing (Supplementary Table 1). All samples were prepared at $\\mathrm{TMA}{=}0.36\\mathrm{M}$ in deionized water. \n\nIon conductivity of quaternized polyphenylene. The ion conductivity $(\\sigma)$ of the HTMA-DAPP membrane was measured from AC impedance spectroscopy data (Solartron 1260 gain-phase analyser). Measurements were carried out under fully hydrated conditions at $80^{\\circ}\\mathrm{C}$ where the cell was immersed in deionized water. The hydroxide conductivity was calculated according to the following equation: \n\n$$\n\\sigma\\big(\\mathrm{mS}\\mathrm{cm}^{-1}\\big)=\\frac{L}{\\big(R\\times W\\times T\\big)}\n$$ \n\nwhere $L$ is the distance between the two inner Pt plates $(1.456\\mathrm{cm}^{\\cdot}$ ), R is the resistance of the AEM in ohm, and W and $T$ are the width and the thickness of the AEM in centimetres, respectively. \n\nMolecular weight of quaternized polyphenylenes. A Viscotek VE2001 was used in gel permeation chromatography (GPC) analysis with a Viscotek VE 3580 RI detector relative to polystyrene standards in THF. Polymers were dissolved in THF at a concentration of ${\\sim}0.5\\%$ (wt/vol.) and passed through a two-micrometre syringe frit in preparation for analysis. \n\nSynthesis and characterization of 3D $\\mathbf{Ni}_{2}\\mathbf{Fe}_{1}$ nanofoams. The synthesis method was modified based on a previously published paper49. The synthesis of 3D $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ nanofoams was scaled up by using more-concentrated $\\mathrm{NiCl}_{2}$ and $\\mathrm{FeCl}_{3}$ precursors than previously described. In a typical synthesis, a stock solution of 2 M metal chloride was prepared by dissolving $2.592\\mathrm{g}\\mathrm{NiCl_{2}}$ and $3.244\\ \\mathrm{FeCl_{3}}$ in $10\\mathrm{ml}$ deionized water to form a dark green and dark yellow solution, respectively. The $2\\mathrm{MNaBH_{4}}$ was freshly prepared by dissolving $0.378\\mathrm{g}$ powder in $5\\mathrm{ml}$ deionized water. A mixed solution of $0.665\\mathrm{ml}$ of $\\mathrm{NiCl}_{2}$ and $0.335\\mathrm{ml}$ of $\\mathrm{FeCl}_{3}$ was quickly injected into the prepared $\\mathrm{\\DeltaNaHB_{4}}$ solution with stirring at room temperature. The stirring was maintained for about $1\\mathrm{min}$ , and the black dispersion was set aside until the next day. Black 3D $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ nanofoams were precipitated at the bottom of the container, and the supernatant was colourless. After freeze-drying, 3D $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ nanofoams were obtained. Supplementary Fig. 7 shows the scanning electron microscopy (SEM) images of the 3D $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ nanofoams. \n\nSEM. SEM images were recorded by an FEI Apreo VolumeScope Field Emission SEM with an accelerating voltage of $30\\mathrm{kV}$ and a current of $0.8\\mathrm{nA}$ in the tube. The sample was first freeze-dried overnight. Then a small amount of the powder (about $1\\mathrm{mm}$ height of powder in a 5-inch disposable Pasteur pipet) was transferred onto an SEM stub with a carbon conductive tab. The stub was put in the sample chamber, followed by reducing the pressure to a vacuum at $1\\times10^{-5}$ Torr. The working distance was kept at $5\\mathrm{mm}$ . The stigmator alignment and beam shift were calibrated before taking the image. \n\nSynthesis and characterization of $\\bf N i_{9}M o_{1}/C$ catalysts. The general synthetic method for NiMo/C catalysts is described in a previous paper50. The ratio between Ni and Mo was calculated to be a 90:10 atomic ratio. The total amount of $\\mathrm{Ni}_{9}\\mathrm{Mo}_{1}$ was calculated to be $5\\mathrm{g}.$ resulting in a $50\\mathrm{wt\\%}$ loading of active material on KetjenBlack600 (KB). The calculated amount of $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ (Sigma-Aldrich) was dissolved in $250\\mathrm{ml}$ of deionized water under constant stirring using an overhead stirrer; $5\\mathrm{g}$ of KB (Akzo Nobel) was added to the solution of nickel nitrate, and the mixture was stirred for 1 h. Ammonium molybdate (Sigma-Aldrich) was dissolved in a separate glass beaker using $25\\mathrm{ml}$ of deionized water. A clear solution of ammonium molybdate was added to the slurry of KB in nickel nitrate, and the mixture was stirred an additional $30\\mathrm{min}$ ; $_{4\\mathrm{g}}$ of urea (Sigma-Aldrich) was added to the slurry. The excess of NaOH was added to the slurry in order to precipitate nickel and molybdenum hydroxides. The mother liquor was decanted several times, and $\\mathrm{Ni}_{\\mathrm{g}}\\mathrm{Mo}_{1}(\\mathrm{OH})_{x}/\\mathrm{KB}$ was washed on a filtration system until the pH of the solution reached ${\\sim}7\\$ . The obtained wet powder was dried overnight at $T{=}85^{\\circ}\\mathrm{C}$ in air. The powder was ball-milled at $400\\mathrm{r.p.m}$ . for $20\\mathrm{min}$ using planetary ball-mill, agate jar and agate milling media. The fine powder was placed in a quartz boat and reduced in $7\\%\\mathrm{H}_{2}$ using a $1\\mathrm{{lmin^{-1}}}$ flow rate, $T{=}500^{\\circ}\\mathrm{C}$ and $t=1.5\\mathrm{h}$ . The furnace was cooled down in a nitrogen flow until $T=25^{\\circ}\\mathrm{C},$ , and the sample was passivated with $1\\%\\mathrm{O}_{2}$ in nitrogen using a flow rate of $250\\mathrm{ml}\\mathrm{min}^{-1}$ . The obtained catalyst was used in all electrochemical tests. \n\nX-ray powder diffraction (XRD). XRD spectra of NiMo/C catalysts were recorded at 2 s per 0.05 2-θ step using a Rigaku MiniFlex 600 diffractometer with monochromated Cu $\\mathrm{K}_{\\upalpha}$ radiation and analysed with Rigaku PDXL software and Crystallography Open Database (COD) Data Sets for phase identification. \n\nRDE studies. The OER activity of $\\mathrm{IrO}_{2}$ and $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ was evaluated by RDE studies. To obtain the $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ inks $(2\\mathrm{mg}\\mathrm{ml}^{-1},$ ), $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ nanofoams were uniformly dispersed in deionized water. Then $20\\upmu\\mathrm{l}$ of the inks were dropped onto the surface of a polished and cleaned glassy carbon RDE ( $0.247\\mathrm{cm}^{2}$ area) and dried at $60^{\\circ}\\mathrm{C}$ . After that, ${5\\upmu\\mathrm{l}}$ of $0.05\\mathrm{wt\\%}$ Nafion was spread on the catalysts and dried. An $\\mathrm{IrO}_{2}$ slurry $(2\\mathrm{mg}\\mathrm{ml}^{-1},$ was obtained by mixing the powder into the aqueous solution deposited on the RDE using the previously described method for $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ . For the $\\mathrm{\\ttpH}$ effect for HER and HOR, the polycrystalline platinum electrode $5\\mathrm{mm}$ in diameter, Pine Research Instrumentation) was used. The electrochemical measurements were performed using a CHI 660E workstation (CH Instruments) for $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ or a Bio-logic SP-200 for the pH effect, with a graphite carbon rod and a $\\mathrm{Hg/HgO}$ electrode as the counter and reference electrode, respectively. For the HER/HOR performance comparison of NiMo/C and $\\mathrm{PtRu/C}$ , the NiMo/C and $\\mathrm{PtRu/C}$ were made into $2\\mathrm{mg}\\mathrm{ml}^{-1}$ and $0.5\\mathrm{mg}\\mathrm{ml}^{-1}$ inks, respectively. The metal loading on the glassy carbon disk was $100\\upmu\\mathrm{gcm}^{-2}$ of NiMo and $19\\upmu\\mathrm{gcm}^{-2}$ of PtRu. Nafion D521 was diluted to $0.1\\mathrm{wt\\%}$ in the ink to help the catalyst stick on the electrode. The HOR/HER curves were recorded in hydrogen saturated $0.1\\mathrm{MNaOH}$ . Potentials were converted to RHE by measuring the voltage at zero current of the HER/HOR curve in a hydrogen-saturated electrolyte on a Pt electrode. The scan rate of all the linear sweep voltammetry was kept at $5\\mathrm{mVs^{-1}}$ unless otherwise stated in the text. During the linear sweep, the RDE was continuously rotated at 1,600 r.p.m. to remove the generated bubbles. The voltammetry was $I R$ corrected. \n\nConductivity and pH measurement of TMAOH and phenol mixture. Based on the IEC of our HTMA-DAPP membrane/ionomer, we calculated the average number of ammonium groups per repeating unit to be 3.5. There are ten phenylene groups per repeating unit. To explore the impact of phenyl oxidation on the electrolyser performance, we mixed TMAOH with phenol. The molar ratio between TMAOH and phenol represented the extent of phenol formation on the HTMA-DAPP backbone. For example, 3.5:1 of TMAOH/phenol would be equal to $10\\%$ of phenol formation. The pH and conductivity of a series of TMAOH/ phenol solutions were measured using a sympHony pH probe and a sympHony conductivity probe, respectively, connected to a VWR B30PCI Benchtop pH/ conductivity/ISE multimeter. The probes were calibrated before the measurement with the standards provided by the National Institute of Standards and Technology. The results are summarized in Supplementary Table 2. \n\nMEA fabrication and performance evaluation of AEM electrolysers. The end plates and graphite flow field for the cathode were supplied by Fuel Cell Technologies. The platinum-coated titanium flow field for the anode and the platinized titanium gas diffusion layers (GDLs) were provided by Giner Labs. SGL 29 BC was used as the cathode GDL. For the anode, $\\mathrm{IrO}_{2}$ (Alfa Aesar) or $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ (as-synthesized) catalysts were mixed with ionomer in aqueous solution (1:4 water and isopropanol). For the cathode, $\\mathrm{PtRu/C}$ (Alfa Aesar $50\\mathrm{wt\\%}$ Pt and $25\\mathrm{wt\\%}$ Ru) or $\\mathrm{Ni_{9}M o_{1}/C}$ catalyst was mixed with ionomer in aqueous solution (1:4 water and isopropanol). The catalyst inks were painted onto the GDLs $(5\\mathrm{cm}^{2}$ ; anode, platinized titanium; cathode, SGL 29 BC) to make gas diffusion electrodes (GDEs). The metal loading is around $2.5\\mathrm{mgcm}^{-2}$ for $\\mathrm{IrO}_{2}$ , $3\\mathrm{mgcm}^{-2}$ for $\\mathrm{Ni}_{2}\\mathrm{Fe}_{1}$ , $2\\mathrm{mg}_{\\mathrm{pt}}\\mathrm{cm}^{-2}$ for $\\mathrm{PtRu/C}$ and $2\\mathrm{mg}\\mathrm{cm}^{-2}$ for $\\mathrm{Ni_{9}M o_{1}/C}$ . The HTMA-DAPP membrane was immersed in $1\\mathrm{MNaOH}$ for 2 h and then rinsed with Milli-Q water to convert the acetate anion into the hydroxide anion. The HTMA-DAPP membrane, GDEs and Teflon gaskets were assembled into a single cell with 60 inch-pounds torque. The cell was tested by a Biologic SP-200 potentiostat in combination with an HCV$304830\\mathrm{A}/48\\mathrm{V}$ power booster. The cell was first cycled between $1.3\\mathrm{V}$ and $2.0\\mathrm{V}$ at $20\\mathrm{mVs^{-1}}$ while flowing $0.1\\mathrm{MNaOH}$ solution on both the anode and cathode at $60^{\\circ}\\mathrm{C}$ until the polarization curves stabilized. Then polarization curves were recorded between 1.3 and $1.8\\mathrm{V}$ while flowing $1.0\\mathrm{MNaOH}$ solution on both the anode and cathode at $60^{\\circ}\\mathrm{C}.$ $20\\mathrm{mVs^{-1}}$ . The alkaline solution was purged by flowing approximately $500\\mathrm{ml}$ of Milli-Q water. Then the polarization curve was recorded between 1.3 and $2.0\\mathrm{V}$ at $20\\mathrm{mVs^{-1}}$ while flowing Milli-Q water at $85^{\\circ}\\mathrm{C}$ . \n\n# Data availability \n\nThe authors declare that the data supporting the findings of this study are available within the paper, Supplementary Information and Source Data files. Further data beyond the immediate results presented here are available from the corresponding authors upon reasonable request. \n\nReceived: 20 September 2019; Accepted: 6 February 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Abbasi, R. et al. A roadmap to low-cost hydrogen with hydroxide exchange membrane electrolyzers. Adv. Mater. 31, 1805876 (2019). \n2.\t Vincent, I. & Bessarabov, D. Low cost hydrogen production by anion exchange membrane electrolysis: a review. Renew. Sustain. Energy Rev. 81, 1690–1704 (2018). \n3.\t Buttler, A. & Spliethoff, H. Current status of water electrolysis for energy storage, grid balancing and sector coupling via power-to-gas and power-toliquids: a review. Renew. Sustain. Energy Rev. 82, 2440–2454 (2018). \n4.\t Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into matrials design. Science 355, eaad4998 (2017). \n5.\t Zeng, K. & Zhang, D. K. Recent progress in alkaline water electrolysis for hydrogen production and applications. Prog. Energy Combust. Sci. 36, 307–326 (2010). \n6.\t Schmidt, O. et al. Future cost and performance of water electrolysis: an expert elicitation study. Int. J. Hydrog. Energy 42, 30470–30492 (2017). \n7.\t Gulzow, E. & Schulze, M. Long-term operation of AFC electrodes with $\\mathrm{CO}_{2}$ containing gases. J. Power Sources 127, 243–251 (2004). \n8.\t Gulzow, E. Alkaline fuel cells: a critical view. J. Power Sources 61, 99–104 (1996). \n9.\t Naughton, M. S., Brushett, F. R. & Kenis, P. J. A. Carbonate resilience of flowing electrolyte-based alkaline fuel cells. J. Power Sources 196, 1762–1768 (2011). \n10.\tBernt, M. & Gasteiger, H. A. Influence of ionomer content in $\\mathrm{IrO}_{2}/\\mathrm{TiO}_{2}$ electrodes on PEM water electrolyzer performance. J. Electrochem. Soc. 163, F3179–F3189 (2016). \n11.\tLewinski, K. A., van der Vliet, D. F. & Luopa, S. M. NSTF advances for PEM electrolysis—the effect of alloying on activity of NSTF electrolyzer catalysts and performance of NSTF based PEM electrolyzers. ECS Trans. 69, 893–917 (2015). \n12.\tBabic, U., Suermann, M., Buehi, F. N., Gubler, L. & Schmidt, T. J. Reviewidentifying critical gaps for polymer electrolyte water electrolysis development. J. Electrochem. Soc. 164, F387–F399 (2017). \n13.\tLi, H. et al. Effects of operating conditions on performance of hightemperature polymer electrolyte water electrolyzer. J. Power Sources 318, 192–199 (2016). \n14.\tBarbir, F. PEM electrolysis for production of hydrogen from renewable energy sources. Sol. Energy 78, 661–669 (2005). \n15.\tAyers, K. E. et al. Characterization of anion exchange membrane technology for low cost electrolysis. ECS Trans. 45, 121–130 (2013). \n16.\tHickner, M. A., Herring, A. M. & Coughlin, E. B. Anion exchange membranes: current status and moving forward. J. Polym. Sci. Pol. Phys. 51, 1727–1735 (2013). \n17.\tVarcoe, J. R. et al. Anion-exchange membranes in electrochemical energy systems. Energy Environ. Sci. 7, 3135–3191 (2014). \n18.\tPark, E. J. & Kim, Y. S. Quaternized aryl ether-free polyaromatics for alkaline membrane fuel cells: synthesis, properties, and performance—a topical review. J. Mater. Chem. A 6, 15456–15477 (2018). \n19.\tNiether, C. et al. Improved water electrolysis using magnetic heating of FeC–Ni core–shell nanoparticles. Nat. Energy 3, 476–483 (2018). \n20.\tSuntivich, J., May, K. J., Gasteiger, H. A., Goodenough, J. B. & Shao-Horn, Y. A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles. Science 334, 1383–1385 (2011). \n21.\tZhao, S. L. et al. Ultrathin metal–organic framework nanosheets for electrocatalytic oxygen evolution. Nat. Energy 1, 16184 (2016). \n22.\t Kaczur, J. J., Yang, H. Z., Liu, Z. C., Sajjad, S. A. & Masel, R. I. Carbon dioxide and water electrolysis using new alkaline stable anion membranes. Front. Chem. 6, 263 (2018). \n23.\tKraglund, M. R. et al. Ion-solvating membranes as a new approach towards high rate alkaline electrolyzers. Energy Environ. Sci. 12, 3313–3318 (2019). \n24.\tLeng, Y. J. et al. Solid-state water electrolysis with an alkaline membrane. J. Am. Chem. Soc. 134, 9054–9057 (2012). \n25.\t Parrondo, J. et al. Degradation of anion exchange membranes used for hydrogen production by ultrapure water electrolysis. RSC Adv. 4, 9875–9879 (2014). \n26.\tPandiarajan, T., Berchmans, L. J. & Ravichandran, S. Fabrication of spinel ferrite based alkaline anion exchange membrane water electrolysers for hydrogen production. RSC Adv. 5, 34100–34108 (2015). \n27.\tXiao, L. et al. First implementation of alkaline polymer electrolyte water electrolysis working only with pure water. Energy Environ. Sci. 5, 7869–7871 (2012). \n28.\tFan et al. Poly(bis-arylimidazoliums) possessing high hydroxide ion exchange capacity and high alkaline stability. Nat. Comm. 10, 2306 (2019). \n29.\tOmasta, T. J. et al. Beyond catalysis and membranes: visualizing and solving the challenge of electrode water accumulation and flooding in AEMFCs. Energy Environ. Sci. 11, 551–558 (2018). \n30.\tMaurya, S. et al. Rational design of polyaromatic ionomers for alkaline membrane fuel cells with ${>}1$ W $c\\mathrm{m}^{-2}$ power density. Energy Environ. Sci. 11, 3283–3291 (2018). \n31.\tWang, J. et al. Poly(aryl piperidinium) membranes and ionomers for hydroxide exchange membrane fuel cells. Nat. Energy 4, 392–398 (2019). \n32.\t Huang, G. et al. Composite poly(norbornene) anion conducting membrnaes for achieving durability, water management and high power $(3.4~\\mathrm{W/cm^{2}},$ ) in hydrogen/oxygen alkaline fuel cells. J. Electrochem. Soc. 166, F637–F644 (2019). \n33.\t Chung, H. T., Martinez, U., Chlistunoff, J., Matanovic, I. & Kim, Y. S. Cation-hydroxide-water co-adsorption inhibits the alkaline hydrogen oxidation reaction. J. Phys. Chem. Lett. 7, 4464–4469 (2016). \n34.\tDumont, J. H. et al. Unusally high concentration of alkyl ammonium hydroxide in the cation-dydroxide-water coadsorbed layer on Pt. ACS Appl. Mater. Interfaces 12, 1825–1831 (2020). \n35.\tTrzesniewski, B. J. et al. In situ observation of active oxygen species in Fe-containing Ni-based oxygen evolution catalysts: the effect of $\\mathrm{\\tt{pH}}$ on electrochemical activity. J. Am. Chem. Soc. 137, 15112–15121 (2015). \n36.\tKraglund, M. R. et al. Zero-gap alkaline water electrolysis using ion-solvating polymer electrolyte membranes at reduced KOH concentrations. J. Electrochem. Soc. 163, F3125–F3131 (2016). \n37.\tLi, D. et al. Phenyl oxidation impacts the durability of alkaline membrane water electrolyzer. ACS Appl. Mater. Interfaces 11, 9696–9701 (2019). \n38.\tMatanovic, I. et al. Adsorption of polyaromatic backbone impacts the performance of anion exchange membrane fuel cells. Chem. Mater. 31, 4195–4204 (2019). \n39.\t Maurya, S., Fujimoto, C. H., Hibbs, M. R., Villarrubia, C. N. & Kim, Y. S. Toward improved alkaline membrane fuel cell performance using quaternized aryl-ether free polyaromatics. Chem. Mater. 30, 2188–2192 (2018). \n40.\t Li, D., Chung, H. T., Maurya, S., Matanovic, I. & Kim, Y. S. Impact of ionomer adsorption on alkaline hydrogen oxidation activity and fuel cell performance. Curr. Opin. Electrochem. 12, 189–195 (2018). \n41.\tPoynton, S. D. et al. Preparation of radiation-grafted powders for use as anion exchange ionomers in alkaline polymer electrolyte fuel cells. J. Mater. Chem. A 2, 5124–5130 (2014). \n42.\tJeon, J. Y. et al. Synthesis of aromatic anion exchange membranes by Friedel-Crafts bromoalkylation and cross-linking of polystyrene block copolymers. Macromolecules 52, 2139–2147 (2019). \n43.\tLee, W. H., Kim, Y. S. & Bae, C. Robust hydroxide ion conducting poly(biphenyl alkylene)s for alkaline fuel cell membranes. ACS Macro Lett. 4, 814–818 (2015). \n44.\tZhu, L., Yu, X. D. & Hickner, M. A. Exploring backbone-cation alkyl spacers for multi-cation side chain anion exchange membranes. J. Power Sources 375, 433–441 (2018). \n45.\tWang, J. H. et al. Structure-property relationships in hydroxide-exchange membranes with cation strings and high ion-exchange capacity. ChemSusChem 8, 4229–4234 (2015). \n46.\tHibbs, M. R. Alkaline stability of poly(phenylene)-based anion exchange membranes with various cations. J. Polym. Sci. B Polym. Phys. 51, 1736–1742 (2013). \n47.\tPark, E. J. et al. Alkaline stability of quaternized Diels-Alder polyphenylenes. Macromolecules 52, 5419–5428 (2019). \n48.\tChoe, Y. K. et al. Alkaline stability of benzyl trimethyl ammonium functionalized polyaromatics: a computational and experimental study. Chem. Mater. 26, 5675–5682 (2014). \n49.\tFu, S. F. et al. Ultrafine and highly disordered Ni2Fe1 nanofoams enabled highly efficient oxygen evolution reaction in alkaline electrolyte. Nano Energy \n44, 319–326 (2018). \n50.\tKabir, S. et al. Platinum group metal-free NiMo hydrogen oxidation catalysts: high performance and durability in alkaline exchange membrane fuel cells. J. Mater. Chem. A 5, 24433–24443 (2017). \n51.\t Lee, K.-S., Spendelow, J. S., Choe, Y.-K., Fujimoto, C. & Kim, Y. S. An operationally flexible fuel cell based on quaternary ammonium–biphosphate ion pairs. Nat. Energy 1, 16120 (2016). \n52.\tGao, H., Li, J. & Lian, K. Alkaline quaternary ammonium hydroxides and their polymer electrolytes for electrochemical capacitors. RSC Adv. 4, \n21332–21339 (2014). \n\n# Acknowledgements \n\nWe gratefully acknowledge research support from the HydroGEN Advanced Water Splitting Materials Consortium, established as part of the Energy Materials Network under the US Department of Energy, Office of Energy Efficiency and Renewable Energy, Fuel Cell Technologies Office (program manager: D. Peterson). Los Alamos National Laboratory is operated by Triad National Security under the US Department of Energy, under contract no. 89233218CNA000001. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, a wholly owned subsidiary of Honeywell International, for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. Y.L. acknowledges research support from the JCDREAM. We thank A. Dattelbaum for constructive criticism of the manuscript. \n\n# Author contributions \n\nY.S.K. designed the experiments. D.L. carried out the electrochemical analysis and electrolyser test. E.J.P., E.D.B and C.F. synthesized the polymeric materials. W.Z., Q.S., Y.Z., H.T. and Y.L. synthesized and characterized the NiFe catalysts. A.S. and B.Z. synthesized and characterized the NiMo/C catalysts. D.L., E.J.P., W.Z., Y.L., A.S. and Y.S.K. contributed to writing the article. Y.S.K. initiated the collaborative project. Y.L., B.Z. and Y.S.K. supervised and guided the work. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41560-020-0577-x. \n\nCorrespondence and requests for materials should be addressed to Y.L. or Y.S.K. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 " + }, + { + "id": "10.1038_s41467-020-15873-x", + "DOI": "10.1038/s41467-020-15873-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-15873-x", + "Relative Dir Path": "mds/10.1038_s41467-020-15873-x", + "Article Title": "Direct evidence of boosted oxygen evolution over perovskite by enhanced lattice oxygen participation", + "Authors": "Pan, YL; Xu, XM; Zhong, YJ; Ge, L; Chen, YB; Veder, JPM; Guan, DQ; O'Hayre, R; Li, MR; Wang, GX; Wang, H; Zhou, W; Shao, ZP", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "The development of oxygen evolution reaction (OER) electrocatalysts remains a major challenge that requires significant advances in both mechanistic understanding and material design. Recent studies show that oxygen from the perovskite oxide lattice could participate in the OER via a lattice oxygen-mediated mechanism, providing possibilities for the development of alternative electrocatalysts that could overcome the scaling relations-induced limitations found in conventional catalysts utilizing the adsorbate evolution mechanism. Here we distinguish the extent to which the participation of lattice oxygen can contribute to the OER through the rational design of a model system of silicon-incorporated strontium cobaltite perovskite electrocatalysts with similar surface transition metal properties yet different oxygen diffusion rates. The as-derived silicon-incorporated perovskite exhibits a 12.8-fold increase in oxygen diffusivity, which matches well with the 10-fold improvement of intrinsic OER activity, suggesting that the observed activity increase is dominulltly a result of the enhanced lattice oxygen participation. While water splitting provides a renewable means to store energy, the sluggish O-2 evolution half-reaction limits applications. Here, authors examine a silicon-incorporated strontium cobaltite perovskite and correlate lattice oxygen participation in O-2 evolution to the oxygen ion diffusivity.", + "Times Cited, WoS Core": 492, + "Times Cited, All Databases": 506, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000558820800020", + "Markdown": "# Direct evidence of boosted oxygen evolution over perovskite by enhanced lattice oxygen participation \n\nYangli Pan1,2,8, Xiaomin Xu 2,8, Yijun Zhong2, Lei Ge 1✉, Yubo Chen3, Jean-Pierre Marcel Veder4, Daqin Guan5, Ryan O’Hayre $\\textcircled{1}$ 6, Mengran Li $\\textcircled{1}$ 7, Guoxiong Wang7, Hao Wang1, Wei Zhou 5 & Zongping Shao2,5✉ \n\nThe development of oxygen evolution reaction (OER) electrocatalysts remains a major challenge that requires significant advances in both mechanistic understanding and material design. Recent studies show that oxygen from the perovskite oxide lattice could participate in the OER via a lattice oxygen-mediated mechanism, providing possibilities for the development of alternative electrocatalysts that could overcome the scaling relations-induced limitations found in conventional catalysts utilizing the adsorbate evolution mechanism. Here we distinguish the extent to which the participation of lattice oxygen can contribute to the OER through the rational design of a model system of silicon-incorporated strontium cobaltite perovskite electrocatalysts with similar surface transition metal properties yet different oxygen diffusion rates. The as-derived silicon-incorporated perovskite exhibits a 12.8-fold increase in oxygen diffusivity, which matches well with the 10-fold improvement of intrinsic OER activity, suggesting that the observed activity increase is dominantly a result of the enhanced lattice oxygen participation. \n\nn the societal pursuit of a sustainable energy future, the electrolysis of small molecules including water, dinitrogen and carbon dioxide is envisioned to play an important role, because it is central to the conversion of electrical energy, which can come from the vastly available renewable energies (e.g., solar and wind), into chemical energy stored in a range of fuels or chemicals such as hydrogen, ammonia and carbon monoxide1–3. While the kinetics for the reduction of these molecules determines the reaction rate, the overall electrical-to-chemical power conversion efficiency of these electrolytic processes is largely dependent on the anodic oxygen evolution reaction (OER), which provides electrons for the reduction reaction to occur but suffers from slow reaction kinetics associated with its four electron transfers. To date, iridium- and ruthenium-based materials are among the best-performing OER catalysts in aqueous solutions4. However, the scarcity and prohibitive cost of Ir and $\\mathtt{R u}$ pose major obstacles towards widespread use in electrolysis technologies. These concerns have encouraged tremendous research activities in finding efficient and low-cost alternatives, among which nonprecious transition metal oxides featuring a perovskite structure have been demonstrated excellent OER activities. Indeed, the best perovskites show performance comparable to (if not higher than) Ir-/Ru-based standards, especially in alkaline media5,6. Typical examples include single perovskite $\\mathrm{Ba}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{Co}_{0.8}\\mathrm{Fe}_{0.2}\\mathrm{O}_{3-\\delta}$ (BSCF) and double perovskite $\\mathrm{PrBaCo}_{2}\\mathrm{O}_{5+\\delta}$ (PBC), which have both been shown with exceptional intrinsic activity in alkaline electrolytes, in some cases several orders of magnitude higher than the $\\mathrm{IrO}_{2}$ benchmark7–13. \n\nOver the past years, our understanding of the OER mechanism has proven to be instrumental in developing better catalysts. Taking the OER on perovskite surfaces for an example, the conventional adsorbate evolution mechanism (AEM) proceeds via a sequence of concerted electron–proton transfers on the transition metal active centres7, whose binding to the adsorbed oxygen intermediates should be neither too strong nor too weak to achieve optimal activity according to the Sabatier’s principle14. This has initiated the exploration of electronic structure parameters that can serve as activity descriptors to help screen highly efficient catalyst candidates7,15–17. For instance, the filling of the 3d electron with an $e_{\\mathrm{g}}$ symmetry of surface transition metal cations has been successfully utilised to identify several state-of-the-art perovskite OER catalysts such as $\\mathrm{BSCF}^{7}$ , $\\mathrm{CaMnO}_{2.5}{}^{1}$ 8 and $\\mathrm{SrNb}_{0.1}\\mathrm{Co}_{0.7}\\mathrm{Fe}_{0.2}\\mathrm{O}_{3-\\delta}$ (SNCF)19. However, the performance of oxide electrocatalysts based on AEM is limited by the scaling relations between the oxygen intermediates, which, according to Man et al. $\\mathbf{\\bar{s}}^{20}$ density functional theory (DFT) calculations, can lead to a considerable overpotential for the OER. \n\nMore recently, a new mechanism based on the redox chemistry of lattice oxygen anions has been proposed. Often termed the lattice oxygen-mediated mechanism or lattice oxygen oxidation mechanism (LOM), this mechanism involves the direct participation of oxygen anions from the perovskite lattice as an active intermediate in the OER, which was supported by $^{18}\\mathrm{O}$ isotope detection of the reaction product as well as DFT calculations21–26. Of note, the LOM can also occur for other types of oxygencontaining OER catalysts, for example, Co–phosphate27, Co–Ni spinel oxide28 and $\\scriptstyle{\\dot{\\mathbf{C}}}0-{\\mathbf{Z}}{\\mathbf{n}}$ oxyhydroxide29. Importantly, it is expected that a catalyst utilizing the LOM can bypass the limitations inherent in AEM-based catalysts where scaling relations constrain performance20, thereby potentially offering much improved OER activity23. This possibility accentuates the need to develop novel catalyst candidates that operate via the LOM pathway. Even more importantly, the degree to which the lattice oxygen participation could promote the OER activity for perovskite oxides is still unclear and must be explored. \n\nIt is well known that the perovskite structure is highly flexible and can therefore accommodate a wide variety of elements in the periodic table. For this reason, elemental doping has been extensively applied to the development of perovskite oxides for diverse fields of research, including OER electrocatalysis. However, since many of the transition metals are active towards the OER30, their incorporation into the perovskite structure may mask the real contribution of lattice oxygen participation in enhancing the catalytic activity. In addition, synergy could be created between the dopant and the parent cation in the perovskite31, which causes additional difficulty in distinguishing the contribution of lattice oxygen participation to the OER activity. \n\nIt was reported that a minor amount of silicon (Si) doping can stabilise the oxygen vacancy disordered cubic perovskite structure, thus significantly improving the oxide ion conductivity/ oxygen ion diffusion rate as well as modifying the oxygen vacancy concentration32,33. Due to the much smaller size of $\\mathrm{Si^{4+}}$ $\\overset{\\cdot}{r}=\\operatorname{\\mathbb{\\Gamma}}$ $0.26\\mathring{\\mathrm{A}}$ with a preferable tetrahedral coordination) than most of the B-site cations34, the solubility of Si in ambient-pressure synthesised perovskites is usually quite low $(3-15\\%$ of the B-site), while the silicon-containing impurity phase is an insulator, which usually stays at the grain boundary and acts as an inhibitor for charge transfer35. By tailoring the amount of Si to be incorporated, materials with different oxygen vacancy concentrations and oxygen diffusion rates can be developed. Furthermore, Si by itself is inert towards electrocatalysis, hence the introduction of Si will not contribute additional catalysis towards the OER. Thus, Si incorporation may provide an excellent platform for investigating the role of lattice oxygen participation in the OER. \n\nStrontium cobaltite, i.e., $\\mathrm{SrCoO}_{3-\\delta}$ (SCO), is demonstrated both theoretically and experimentally with high OER activity, involving likely the operation of the LOM-type reaction mechanism20,23–25. In this study, we select silicon as a modifier for SCO to create several Si-incorporated SCO samples with different levels of oxygen diffusion rates and oxygen vacancy concentrations but similar surface transition metal properties, which are then applied as electrocatalysts to explore the role and degree of lattice oxygen participation in the OER process. pH-dependent OER kinetic studies and surface amorphization observations suggest that the LOM mechanism is operational during the OER on both SCO and Si-doped SCO. Notably, we achieve up to an order of magnitude higher OER intrinsic activity upon the inclusion of Si into the SCO lattice, approaching the activity of the benchmark BSCF, although the $e_{\\mathrm{g}}$ filling of the former is far from ideal based on the AEM. This activity improvement matches closely with the 12.8-fold enhancement in the oxygen mobility. We therefore can strongly support the important role of LOM in substantially contributing to the OER activity. Our work opens an avenue to develop lattice-oxygen-participated catalysts towards efficient water oxidation for potential electrolysis applications. \n\n# Results \n\nStructural characterisations. We first comparatively studied the pristine SCO and the Si-incorporated SCO with an intentional doping amount of $5\\%$ at the B-site (i.e., $y=0.05$ in $\\mathrm{SrCo}_{1-y}\\mathrm{Si}_{y}\\mathrm{O}_{3-\\delta},$ denoted as Si–SCO). Both samples were synthesised by a ballmilling-assisted solid-state reaction method (Methods section). X-ray diffraction (XRD) pattern as shown in Fig. 1a and the corresponding Rietveld refinement analysis (Supplementary Fig. 1a and Table 1) suggest that the parent SCO perovskite consists of a major $\\mathrm{Sr}_{6}\\mathrm{Co}_{5}\\mathrm{O}_{15}$ phase and a small quantity of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ impurity, in line with previously reported results36. Incorporating Si into the B-site gave rise to the formation of a tetragonal phase, which has a space group of $P4\\/$ mmm and lattice parameters of $a=a_{p}\\approx3.85917(\\bar{4})$ Å and $c\\approx2a_{p}=7.7270(1)$ Å ( $\\dot{\\b{a}}_{p}$ being the lattice parameter of an ideal cubic-phase single perovskite with space group of $P m\\overline{{3}}m)$ (Supplementary Fig. 1b). Two impurity phases, i.e., brownmillerite $\\mathrm{Sr}_{2}\\mathrm{Co}_{2}\\mathrm{O}_{5}$ and monoclinic $\\mathrm{Sr}_{2}\\mathrm{SiO}_{4},$ were also detected in the Si–SCO sample with only minor weight fractions (Supplementary Table 2), based on which the nominal bulk composition of the major tetragonal phase was approximated to be $\\bar{\\mathrm{Sr}}_{0.98}\\mathrm{Co}_{0.97}\\mathrm{Si}_{0.03}\\mathrm{O}_{3-\\delta},$ where presence of A-site $\\mathrm{sr}$ -deficiency may be possible. A schematic illustration of this tetragonal structure is given in Fig. 1b, in which layers of ${\\mathrm{ColO}}_{6}$ and $(\\mathrm{Co},\\mathrm{Si})2\\mathrm{O}_{6}$ octahedrons, both corner-shared, alternate with each other along the $\\boldsymbol{c}$ axis [here Co1 and $(\\mathrm{Co},\\mathrm{Si})2$ refer to two different crystallographic positions at the B-site]. This doubling of the perovskite unit cell along the $\\scriptstyle{c}$ -direction is characteristic of a double perovskite structure with B-site layered ordering37, resembling that of strontium cobaltites doped by main group VA elements such as phosphorus and antimony38,39. Figure 1c shows a high-resolution transmission electron microscopy (HR-TEM) image of Si–SCO, where lattice distances of 0.27 and $0.22\\mathrm{nm}$ are observed, consistent with those of (110) and (1\u000112) planes calculated from the XRD data. In addition, the corresponding fast Fourier transformed (FFT) pattern further reveals the presence of cation-ordering reflections (marked by a red circle in Fig. 1c inset). Figure 1d displays high-angle annular dark-field scanning TEM (HAADF-STEM) and energy-dispersive X-ray spectroscopy (EDS) mapping images, demonstrating a homogeneous distribution of all the constituent elements of Sr, Co, Si and O. This confirms the incorporation of Si within the perovskite lattice and suggests that the impurity phases were evenly dispersed inside the oxide powder rather than separated as large aggregates. The overall morphology of SCO and Si–SCO was studied by scanning electron microscopy (SEM), as presented in Supplementary Fig. 2. Both samples show a large particle size in the (sub)micrometre range with no noticeable difference, except that Si–SCO has somewhat larger and more sintered particles compared with SCO. This is also supported by the relatively lower Brunauer–Emmett–Teller (BET) surface area of Si–SCO, approximately a quarter that of SCO (0.44 vs. $1.74\\mathrm{m}^{2}\\mathrm{g}^{-1},$ ), as determined from multipoint Krypton $(\\mathrm{Kr})$ adsorption tests (Supplementary Table 3). \n\n![](images/f1a6af2805e5ae687d8aa0338dc3237c9c921da98e4de2743b04e7cdd849dbc9.jpg) \nFig. 1 Structural characterisations of Si-incorporated strontium cobaltites. a XRD patterns showing the formation of a tetragonal phase upon the incorporation of Si into SCO. b A schematic depicting the tetragonal crystal structure of Si–SCO. c HRTEM image of Si–SCO and the corresponding FFT pattern with zone axis of [11\u00011\u0001]. d HAADF-STEM image of Si–SCO and the corresponding EDS mapping images of Sr, Co, Si and O. Scale bar in c is $5\\mathsf{n m}$ and in d is $200\\mathsf{n m}$ . \n\nOxygen evolution activity. The electrocatalytic OER performance of SCO and Si–SCO was investigated using a rotating disk electrode (RDE) based three-electrode configuration under ambient conditions. To eliminate any contribution from the capacitive effect, cyclic voltammetry (CV) was performed in an $\\bar{\\mathrm{~O}_{2}^{\\bar{(}}}$ -saturated 0.1 M KOH aqueous electrolyte at a $10\\mathrm{mVs^{-1}}$ scan rate and at a $2000\\mathrm{rpm}$ rotation speed, which were averaged and $i R$ -corrected to obtain the OER kinetic currents (an example of this data processing can be found in Supplementary Fig. 3), as shown in Fig. 2a. As a common practice for evaluating perovskite oxide electrocatalysts (Supplementary Figs. 4 and 5, and Supplementary Note $\\dot{1})^{40}$ , the active materials were mixed at a mass ratio of 5:1 with conductive carbon, which facilitates electrical contact between catalyst particles as well as between the catalyst and the RDE while contributing negligibly to the OER currents (Fig. 2a). Compared with SCO, the kinetic current of Si–SCO markedly increases across the OER region, indicating a significantly enhanced OER activity. This is also the case when one compares the overpotential required to afford a geometric current density of $10\\mathrm{mA}\\mathrm{\\bar{c}m}^{-2}\\mathrm{geo}$ 2geo (η10, a metric associated with solar fuel production41). Specifically, Si–SCO exhibits a $\\eta_{10}$ value of $417\\mathrm{mV}$ , which is ${\\sim}70\\mathrm{mV}$ smaller than that of SCO $(488\\mathrm{mV})$ . \n\nThe catalyst surface area is known to influence the apparent OER activity observed on different catalysts. To assess this, we normalised the OER kinetic currents to the BET surface area of each perovskite catalyst (Supplementary Table 3), which allowed us to report the specific activity of the catalysts as a metric for comparing their intrinsic activity7. Figure 2a inset compares the specific activity at an applied potential of $1.60\\mathrm{V}$ vs. the reversible hydrogen electrode (RHE), from which it is obvious that Si–SCO is intrinsically more active than SCO, showing a one order of magnitude higher specific activity. In addition, steady-state Tafel data suggest that Si–SCO gives a Tafel slope of $66~\\mathrm{mV~dec^{-1}}$ , lower than that of SCO $\\bar{(}76\\mathrm{mV}\\mathrm{dec^{-1}},$ ) (Fig. 2b). This is a good indication of the improved OER kinetics on the perovskite catalyst incorporating silicon because catalysts having a smaller Tafel slope tend to deliver significantly increased currents at only moderate increments of overpotential. A detailed comparison with literature results, as tabulated in Supplementary Table 4, suggests that the Si-incorporated Si–SCO catalyst compares favourably to the state-of-the-art perovskite catalysts such as BSCF, PBC and SNCF, among many others7–13,18,19,31,42–47. \n\n![](images/3d10b1010eb5ac4d0eed85e063bd23c2a60a2bc060cefafcf3a56c04034d36bf.jpg) \nFig. 2 Electrocatalytic oxygen evolution performance of Si-incorporated strontium cobaltites. a OER kinetic currents (normalised to the geometric surface area of the electrode, in $\\mathsf{m A c m}^{-2}{}_{\\mathsf{g e o}})$ of SCO and Si–SCO collected in an $\\mathsf{O}_{2}$ -saturated 0.1 M KOH electrolyte under ambient conditions. The contribution from the conductive carbon as catalyst support is shown for reference. Inset shows the OER specific activity (normalised to the BET surface area of the oxide catalyst, in $\\mathsf{m A c m}^{-2}\\mathsf{_{o x i d e}})$ of SCO and Si–SCO at 1.60 V vs. RHE. Error bars are the standard deviations of triplicate measurements. b Steady-state Tafel data for SCO and Si–SCO. \n\nOxygen evolution mechanism. Previous $^{18}\\mathrm{O}$ -isotopic labelling experiments suggest that the OER on the pristine SCO can proceed via both the AEM and LOM pathways and that the LOM pathway plays an important role in delivering enhanced OER performance25. Specially, in alkaline electrolytes, the occurrence of LOM has been associated with the observation of pHdependent OER kinetics on the RHE scale25, which can be deducted from Eq. (1)48: \n\n$$\ni=\\theta\\cdot c_{\\mathrm{OH}}\\cdot\\mathrm{e}^{-\\Delta G/R T}\n$$ \n\nwhere $i$ is the OER current, $\\theta$ is the surface coverage of the adsorbed hydroxide or oxyhydroxide intermediates, $c_{\\mathrm{OH}}$ is the concentration of hydroxide ions, $\\Delta G$ is the reaction free energy, $R$ is the universal gas constant and $T$ is the temperature during the measurement. Raising the $\\mathrm{\\pH}$ can either modify the exponential term by altering the energy of the adsorbed intermediates or increase the pre-exponential term by increasing the surface coverage or the $\\mathrm{OH^{-}}$ concentration, thus leading to increased OER activity. Consistent with this model, our experimental studies confirm an increase in the OER activity for both SCO and Si–SCO samples with increasing $\\mathrm{\\pH}$ from 12.5 to 14 (Fig. 3a), indicative of $\\mathrm{\\pH}$ -dependence of the OER kinetics and hence LOM participation. Figure 3b further compares the specific activity of both SCO and Si–SCO electrocatalysts at $1.60\\mathrm{V}$ vs. RHE as a function of $\\mathrm{\\pH}$ , from which the proton reaction orders on the RHE scale were extracted from the slopes $[\\rho=(\\mathsf{{d}}\\mathsf{{l o g}}i/\\mathsf{{d}}\\mathsf{{p}}\\mathrm{{H}})_{E}]$ to be 0.58 and 0.70 for SCO and $\\mathsf{S i-S C O}$ , respectively, in accord with reported values for Co-based perovskite oxides25,48. These results strongly suggest that the LOM mechanism is likely at play during the OER on SCO and Si–SCO, agreeing well with the literature results concerning the lattice oxygen participation in the OER over $\\operatorname{SCO}^{25}$ . \n\nFurther evidence supporting the operation of the LOM mechanism can come from the observation of catalyst surface reconstruction during potential cycling, especially for the initial 50 cycles49,50. As shown in Fig. 3c, d, the pseudocapacitive and OER currents of SCO and Si–SCO were found to increase with the continuous CV cycling, indicative of the occurrence of surface amorphization, a phenomenon that was similarly observed for $\\mathrm{\\bar{B}S C F}^{26,51}$ . Of significance, this change appears to be more drastic for Si–SCO, which, in line with its higher proton reaction order, may suggest a higher tendency for its lattice oxygen to participate in the OER. The surface amorphization of Si–SCO was also confirmed by TEM investigations (Fig. 3e, f), in which an amorphous region of $\\approx5\\:\\mathrm{nm}$ was found on the cycled electrode in contrast to the largely crystalline surface of the as-prepared catalyst. These results further indicate the possible involvement of lattice oxygen redox during the OER on Si-incorporated Si–SCO, although it occurs at the expense of surface stability, which will be discussed later in more details. \n\nOrigin of the improved OER activity for Si–SCO. To understand the activity enhancement, we investigated the changes in physicochemical properties induced by Si-incorporation. As mentioned earlier, for Si-doping under ambient-pressure conditions, Si enters the perovskite framework with four-fold coordination to the oxygen (i.e., in the form of orthosilicate $\\mathrm{SiO}_{4}{}^{4-})^{32}$ . Therefore, the introduction of tetrahedral Si into the octahedral Co site can give rise to the generation of oxygen vacancies, which in turn results in a decrease in the bulk $\\scriptstyle{\\mathrm{Co}}$ oxidation state, as can be seen from the below defect equation (Kröger–Vink notation): \n\n$$\n\\mathrm{SiO}_{2}+2\\mathrm{Co}_{\\mathrm{Co}}^{\\times}\\longrightarrow\\mathrm{Si}_{\\mathrm{Co}}^{\\times}+2\\mathrm{Co}_{\\mathrm{Co}}^{\\prime}+\\mathrm{V}_{\\mathrm{O}}^{\\cdot}+1/2\\mathrm{O}_{2}+\\mathrm{O}_{\\mathrm{O}}^{\\times}\n$$ \n\nThis justifies the stabilisation of the Si-doped perovskite structure in which the effect of the smaller size of $\\mathrm{Si^{4+}}$ is balanced by that of the larger size of reduced $\\scriptstyle{\\mathrm{Co}}$ ions34. Indeed, results from iodometric titrations suggest that in the bulk of the ${\\mathrm{Si^{4+}}}$ -incorporated material an increase in the oxygen vacancy concentration occurred in concert with a reduction in the Co oxidation state (Supplementary Table 5). Specifically, $\\mathsf{S i-S C O}$ exhibits a higher level of oxygen deficiencies relative to SCO ( $\\overset{\\cdot}{\\delta}=$ 0.35 vs. 0.25), and concomitantly a lower average valence state of the bulk Co cations ( $^{3.32+}$ vs. $3.50+\\rangle$ . However, regarding the surface chemical state of Co, which is of greater relevance because the OER takes place on the catalyst surface, we observed no obvious difference using surface-sensitive techniques of $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) and near-edge X-ray absorption fine structure spectroscopy (NEXAFS), as shown in Fig. 4a, b. For example, only a very small shift toward lower photon energies was found at the Co $\\mathrm{L}_{3}$ -edge as $\\mathrm{Si^{4+}}$ is incorporated into SCO (Fig. 4b), indicative of an insignificant decline in the surface Co valence52. Considering the inertness of silicon towards electrocatalysis, the OER activity of SCO and Si–SCO based on the AEM pathway should be primarily determined by the valence of B-site surface cobalt ions7. The little change in surface Co state thus suggests that the contribution of AEM to the OER activity can be reasonably considered unchanged after Si incorporation. Based on peak deconvolution analysis following an earlier report53, we estimate the surface Co oxidation state to be $3.34+$ and $^{3.31+}$ for SCO and Si–SCO, respectively (Fig. 4a), which gives an approximate $e_{\\mathrm{g}}$ filling number of 0.7 assuming that the Co cations are in the intermediate spin state. This value diverges significantly from $e_{\\mathrm{g}}\\approx1.2$ , as predicted for highly active perovskite catalysts based on the AEM mechanism (e.g., BSCF)7. It thus suggests that other than AEM, the operation of LOM likely contributes significantly to the high overall OER activity observed on the Si–SCO catalyst. \n\n![](images/a2033a9074c094c5483b153e4eb46b4fb14d9cb49eb60db343cf72bfda5c9949.jpg) \nFig. 3 The oxygen evolution mechanism studies on Si-incorporated strontium cobaltites. a OER kinetic currents (in $\\mathrm{\\mA}\\mathsf{c m}^{-2}\\mathrm{\\Pi}_{\\mathrm{geo}})$ of SCO and Si–SCO in $\\mathsf{O}_{2}$ -saturated KOH electrolytes with varying pH. b OER specific activity (in $\\mathsf{m A c m}^{-2}\\mathsf{_{o x i d e}})$ of SCO and Si–SCO at $\\ensuremath{1.60\\vee}$ vs. RHE as a function of pH. c, d Select CV curves of c SCO and d Si–SCO in $\\mathsf{O}_{2}$ -saturated $0.1M$ KOH over 50 cycles at a $10\\mathrm{\\mV}\\mathsf{s}^{-1}$ scan rate. e, f HRTEM images and the corresponding FFT patterns of e as-prepared and f cycled (for 50 cycles) Si–SCO electrode. Scale bar in e and $\\pmb{\\uparrow}$ is $5\\mathsf{n m}$ . \n\nAs for the surface oxygen state, an increase in the oxygen vacancy concentration was observed, consistent with that in the bulk. As shown in Fig. 4c and Supplementary Table 6, XPS results of the $\\textsc{o}1s$ core level, which were fitted by four components assigned as adsorbed water $\\mathrm{(H}_{2}\\mathrm{O}$ at ${\\sim}532.4\\mathrm{eV})$ , hydroxide or carbonate $\\mathrm{(OH^{-}/C O_{3}^{2-}}$ at ${\\sim}531.0\\mathrm{eV})$ , oxidative oxygen $(\\mathrm{O}_{2}{}^{2-}/\\mathrm{O}^{-}$ at ${\\sim}529.4\\mathrm{eV})$ and lattice oxygen $(\\mathrm{O}^{2-}$ at ${\\sim}528.3\\mathrm{eV})$ , show a larger number of $\\mathrm{O}_{2}{}^{2-}/\\mathrm{O}^{-}$ species on Si–SCO than on SCO, suggesting a higher content of surface oxygen vacancies54. It is interesting to note that the large presence of surface hydroxide/carbonate is indicative of $\\operatorname{sr}$ segregation at the perovskite surface, a phenomenon commonly observed in $\\mathrm{sr}$ -containing perovskites prepared from conventional methods (e.g., solid-state reaction). However, the extent of $\\operatorname{sr}$ segregation does not vary significantly across different samples, and thus should not considerably affect the OER activity (Supplementary Fig. 6, Supplementary Tables 7 and 8, and Supplementary Note 2). To further corroborate the increased oxygen vacancy concentration through Si doping, the electrochemical oxygen intercalation in SCO and Si–SCO was probed through CV experiments conducted in an Arsaturated 6 M KOH solution. As depicted in Fig. 4d, redox peaks appear as oxygen ions are inserted into and extracted from the accessible lattice vacancy sites (with an occupancy fraction of $\\sigma$ ). This is associated with a pseudocapacitive-type intercalation process that can be represented by Eq. (3): \n\n$$\n\\mathrm{SrCo_{1-\\gamma}S i_{\\gamma}O_{3-\\delta}}+2\\sigma\\mathrm{OH^{-}}\\leftrightarrow\\mathrm{SrCo_{1-\\gamma}S i_{\\gamma}O_{3-\\delta+\\sigma}}+\\sigma\\mathrm{H}_{2}\\mathrm{O}+2\\sigma\\mathrm{e}^{-\\delta}\n$$ \n\nIt is interesting to note that this oxygen intercalation is accompanied by the oxidation of $\\scriptstyle{\\mathrm{Co}}$ when one considers the charge neutrality for $\\mathrm{SrCo}_{1-y}\\mathrm{Si}_{y}\\mathrm{O}_{3-\\delta}$ (before oxygen intercalation) and $\\mathrm{SrCo}_{1-y}\\mathrm{Si}_{y}\\mathrm{O}_{3-\\delta+\\sigma}$ (after oxygen intercalation). Of importance, Si–SCO, having more vacant oxygen sites, displayed a larger current density in the intercalation regime, thereby signifying a greater propensity for oxygen intercalation24. Moreover, the increase in oxygen vacancy content resulted in positively shifted intercalation redox peaks in Si–SCO with respect to SCO, as can be elucidated by the pseudocapacitive Nernst Equation55: \n\n$$\nE=E^{0}+(\\mathrm{RT}/n F)\\mathrm{ln}[\\sigma/(1-\\sigma)]\n$$ \n\nwhere $E$ and $E^{0}$ represent the measured and standard potential for oxygen intercalation, respectively, $n$ is the number of electrons transferred and $F$ is the Faraday constant. \n\nFollowing the oxygen intercalation measurements, the oxygen ion diffusion coefficients $(D_{\\mathrm{O}})$ of SCO and Si–SCO were determined using chronoamperometry with the results presented in the Fig. 4d inset, where current was plotted as a function of the inverse square root of time. By applying a bounded threedimensional diffusion model reported earlier24,56,57 (Methods section), the $D_{\\mathrm{O}}$ value of SCO at room temperature was calculated to be $0.94\\times10^{-11}\\mathrm{cm}^{2}s^{-1}$ , a value that agrees with literature results for strontium cobaltites58. Remarkably, Si–SCO had a diffusion coefficient of $D_{\\mathrm{O}}{=}12.04\\times10^{-11}\\ \\mathrm{\\dot{~cm}^{2}}\\ \\mathrm{s^{-1}}$ which is ${\\sim}12.8$ times faster than SCO, and correlates well with the 10-fold improvement in intrinsic OER activity. The accelerated oxygen ion diffusion is likely associated with the increased crystal lattice symmetry, i.e., from hexagonal symmetry for SCO to tetragonal symmetry for Si–SCO. Although the energy landscape through which the oxygen anions migrate remains quite complex, one general comment is that a higher symmetry could lead to faster oxygen anion transport59–61. Meanwhile, the fast oxygen ion diffusion in Si–SCO is believed to be related to its unique layered structure62, and the presence of partial A-site deficiency further facilitates the oxygen ion diffusion due to the increase in the oxygen vacancy concentration24,63. Given the unchanged contribution from the AEM process, the boosting in electrocatalytic activity through Si incorporation can instead be attributed to the enhanced lattice oxygen participation during the operation of the LOM mechanism. \n\n![](images/eb298aabd3063809760eebb6a2facbc7c91b5879df8145a48e5cc63fa69b7870.jpg) \nFig. 4 Chemical and electrochemical characterisations of Si-incorporated strontium cobaltites. a Co $2p$ core-level XPS spectra of SCO and Si–SCO, with peak fitting results based on multiple cobalt species. Here sat. denotes satellite peaks. b Co L-edge NEXAFS spectra of SCO and Si–SCO. Inset of b shows the Co $\\mathsf{L}_{3}$ -edge spectra in an expanded photon energy scale. c O 1s core-level XPS spectra of SCO and Si–SCO, with peak fitting results illustrated in the stacked columns. d CV curves of SCO and Si–SCO in $\\mathsf{A r}$ -saturated $6\\mathsf{M}\\mathsf{K O H},$ , where redox peaks indicate the electrochemical oxygen intercalation/deintercalation. Inset of d shows the chronoamperometry data $({\\boldsymbol{\\dot{\\mathbf{\\mathit{i}}}}}\\mathbf{\\mathit{\\Sigma}}$ vs. $\\mathrm{t}^{-1/2}$ ) used for the calculation of oxygen ion diffusion coefficients. \n\nImportant role of lattice oxygen participation. To further support the conclusion of lattice oxygen participation in enhancing the OER activity, we tested Si-incorporated samples with different intentional doping amounts (i.e., $y=0.03$ , 0.07 and 0.10 in $\\mathrm{SrCo}_{1-y}\\mathrm{Si}_{y}\\mathrm{O}_{3-\\delta})$ and evaluated the influence on oxygen diffusion properties and subsequent impact on the OER activity. Contrary to a previous report suggesting that Si can be incorporated up to $y=0.07^{64}$ , the actual Si solubility for all our samples was limited to around $3\\%$ and the extra amount of Si formed $\\mathrm{Sr}_{2}\\mathrm{SiO}_{4}$ instead according to Rietveld refinement of the XRD data (Supplementary Fig. 7 and Supplementary Table 2), which is likely due to the difference in synthesis conditions. For simplicity, we nonetheless mark these samples as SCSi0.03, SCSi0.07 and SCSi0.10. While the level of Si incorporated remains similar across these samples, the presence of A-site deficiency in the major perovskite phase associated with the formation of Srcontaining impurities contributed to an increase in oxygen vacancy concentrations with increasing intentional doping amount, both in the bulk and at the surface (Supplementary Tables 5 and 6, and Supplementary Fig. 8). This increase in oxygen vacancy content was also evidenced by the gradual positive shift of oxygen intercalation peaks (Supplementary Fig. 9). However, the oxygen ion diffusivity first experienced an increase to reach a maximum at $y=0.05$ and then decreased with further increasing $y$ to 0.10 (Supplementary Fig. 10 and Supplementary Table 9). This trend in $D_{\\mathrm{O}}$ can be understood from the inhibiting effect of the $\\mathrm{Sr}_{2}\\mathrm{SiO}_{4}$ impurity for charge transfer. $\\mathrm{Sr}_{2}\\mathrm{SiO}_{4},$ which is an insulator based on our electrical conductivity tests, shows negligible conductivity (Supplementary Table 10). Based on the EDS mapping (Supplementary Fig. 11), this impurity phase is highly distributed inside the sample, and thus causes a blocking effect for charge transfer across the grains. This hypothesis is supported by the electrical conductivity trend of the various Si-incorporated samples. The pristine SCO shows a conductivity of $\\bar{2}\\mathrm{{Scm}^{-1}}$ at room temperature, which accords with the literature result38. Incorporating Si into the perovskite lattice led to a substantial increase in conductivity by roughly two orders of magnitude for $y=0.05$ $\\mathrm{{(198\\thinspaceScm^{-1}})},$ ), beyond which a quick decrease in conductivity was observed for SCSi0.07 and SCSi0.10 (Supplementary Table 10). The change in the lattice structure is a main reason for the substantial increase in electrical conductivity at $y=0.05$ , while the counteracting influence of the $\\mathrm{Sr}_{2}\\mathrm{SiO}_{4}$ insulating phase leads to the conductivity decrease for $y>0.05$ . \n\n![](images/e9b0dafc5555ecac5134814590c589e01b3dd97fb666e0a46926b3fde11195e1.jpg) \nFig. 5 Activity correlations and lattice oxygen participation in the OER on Si-incorporated strontium cobaltites. a Correlation of intrinsic OER activity in 0.1 M KOH with the oxygen anion diffusion rate. b Correlation of intrinsic OER activity in 0.1 M KOH with the oxygen vacancy diffusion rate. c A schematic illustration of the AEM and LOM reaction pathways on Si-incorporated strontium cobaltites. The AEM occurs via concerted proton-coupled electrontransfer steps on the transition metal site, while the LOM operates via non-concerted proton–electron transfer steps involving the participation of lattice oxygen. The mobility of lattice oxygen is also illustrated to highlight its important role in enhancing lattice oxygen participation. \n\nFollowing the same electrochemical measurements, the OER activity of the various Si-incorporated samples was obtained (Supplementary Fig. 12). Decreased oxygen anion diffusion was found to lead to decreased OER activity for SCSi0.07 and SCSi0.10. Of significance, the intrinsic OER activity correlates strongly with the oxygen ion diffusion rate, as demonstrated in Fig. 5a. We note that the minor impurity phases of $\\mathrm{Sr}_{2}\\mathrm{Co}_{2}\\mathrm{O}_{5}{}^{65}$ and/or $\\mathrm{Sr}_{2}\\mathrm{SiO}_{4}$ (Supplementary Fig. 13) contribute negligibly to the observed OER activity. Meanwhile, any activity contribution from the variation of the AEM pathway can be ruled out given the almost identical chemical state of surface Co cations (Supplementary Figs. 14 and 15). It further confirms that the enhancement in OER activity for Si–SCO as compared to SCO is a result from the enhanced lattice oxygen participation, which is directly correlated to the oxygen ion diffusion rate. Since the diffusion of oxygen anions is physically equivalent to that of oxygen vacancies in the opposite direction, the oxygen vacancy diffusion coefficient $(D_{\\mathrm{V}})$ may be calculated using Eq. (5)66: \n\n$$\nD_{0}\\cdot c_{0}=D_{\\mathrm{V}}\\cdot c_{\\mathrm{V}}\n$$ \n\nwhere $c_{\\mathrm{O}}$ and $c_{\\mathrm{V}}$ are the concentrations for oxygen anions $(3-\\delta)$ and oxygen vacancies $(\\delta)$ , respectively. Applying this conversion, the oxygen vacancy diffusion rate is also found to correlate with the OER activity (Fig. 5b). \n\n# Discussion \n\nAs mentioned previously, two mechanisms are currently available for the OER over a perovskite electrocatalyst, i.e., AEM and LOM. The classical AEM mechanism focuses solely on the redox activity of the surface transition metal cations. In this scheme, oxygen products evolve from adsorbed water molecules following concerted proton-coupled electron-transfer steps through four intermediate states7 (M–OH, M–O, M–OOH and M–OO, where M denotes the transition metal active site), as shown in Fig. 5c. The binding strength of these intermediate states is found to be strongly correlated to one another20, thus imposing a theoretical minimum overpotential on the AEM-based catalysts that cannot be otherwise overcome. The LOM mechanism is different in that it considers the redox of lattice oxygen. As schematically illustrated in Fig. 5c, one possible LOM pathway25 involves the participation of five intermediate states, in the sequence of M–OH, M–O, M–OOH, M–OO and M–& (here O in bold denotes the oxygen active site and the square box denotes the oxygen vacancy). Despite the similarity in the form of these intermediates to those in the AEM, the LOM differs in the generation of a vacant oxygen site upon the evolution of a lattice oxygen-containing oxygen molecule, which is associated with the decoupling of a certain proton–electron transfer step, giving rise to the previously observed pH-dependent OER kinetics. The lattice oxygen evolved at the surface (which leaves behind a surface vacancy) will be quickly replenished by oxygen ions diffusing from the bulk of the electrocatalyst. The participation of the bulk in the catalysis process thus bypasses the scaling relations dictated in the AEM-based reaction process. Increasing the oxygen ion diffusion rate will facilitate the refilling of the surface lattice oxygen as it is consumed, consequently promoting the catalytic OER process. The participation of lattice oxygen in redox reactions is actually well demonstrated in the field of hightemperature solid oxide fuel cells, in which the introduction of oxygen-ion conductivity into the cathode effectively extends the active sites from the conventional electrolyte-electrode-air triple boundary to the whole electrode surface, thus greatly improving the cathode performance for the oxygen reduction reaction62,63,67. \n\nIt is also likely that hydroxide ions from the electrolyte can refill the generated oxygen vacancy25, which can either provide refreshed oxygen active sites or intercalate into the bulk to compensate for the charge imbalance caused by the previously mentioned oxygen diffusion from the bulk to the surface68. With oxygen being the active site, the importance of oxygen ion mobility can be further supported by the hypothesis that it offers the possibility for transporting inactive or less active oxygen to the active oxygen site, thereby allowing increased numbers of oxygen sites to take part in the reaction and consequently boosting the intrinsic catalytic activity. While determination and tracing of such active oxygen sites can be a formidable challenge, our experimental observation does suggest a link between the increase in the intrinsic OER activity and the extent to which the oxygen ion diffusivity is enhanced. \n\nThe above discussion thus points to the need for considering a dynamic catalyst surface that has strong interactions not only with the electrolyte but also with the bulk for electrocatalysts operating via the LOM mechanism. However, such dynamics can lead to an unstable surface region, especially in cases of high activity, where the rate of surface oxygen vacancy refilling cannot compete with that of surface vacancy formation (due to fast oxygen evolution), causing the formation of under-coordinated cation sites that become prone to dissolution49. This explains the surface amorphization of our Si–SCO catalyst despite its fast oxygen diffusivity associated with the unique A-site deficient layered structure. In fact, the surface reconstruction is recently claimed to be a general trend for perovskite OER catalysts using the LOM mechanism21,49. Constructing perovskite surfaces which allow fast enough kinetics for oxygen vacancy refilling appears to be one direct means to address this issue. In another likely solution, control over a constant dissolution/deposition process should be achieved to fulfil the stability requirement, as exemplified by the so-called self-healing mechanism on electrodeposited Co–phosphate catalyst27. \n\nIn summary, we have demonstrated a model system of Siincorporated strontium cobaltites, on which the OER occurs with the contribution of the LOM mechanism at different extents that strongly correlates to the oxygen ion diffusivity, a guiding parameter that can be facilely obtained through electrochemical experiments. Our findings not only provide new opportunities to design cost-effective, highly efficient materials for OER catalysis, but also deepen our understanding of the OER mechanisms by which they operate. The next step would be to design more stable perovskite surfaces to further drive advances in water oxidation electrocatalysts applicable for the electrolysis of water, dinitrogen and carbon dioxide. \n\n# Methods \n\nMaterials synthesis. Si-incorporated perovskite samples were prepared by a ballmilling-assisted solid-state reaction approach. Freshly dried chemicals of $\\mathrm{SrCO}_{3}$ , $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{SiO}_{2}$ (Sigma-Aldrich) were weighted according to the stoichiometric ratio of $\\mathrm{SrCo}_{1-y}\\mathrm{Si}_{y}\\mathrm{O}_{3-\\delta}$ ( $y=0.00$ , 0.03, 0.05, 0.07 and 0.10) with different intentional Si-doping levels. The precursory powders were then mixed in an acetone medium for 1 h using a high-energy ball mill (Planetary Mono Mill, Pulverisette 6, Fritisch) at a rotation of $400\\mathrm{rpm}$ . The as-obtained mixtures were dried, pressed into pellets and subjected to calcination in air under ambient pressure at $1000{-}1200^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ with intermediate grindings. The actual composition of each sample after calcination was analysed by XRD (Supplementary Tables 1 and 2). \n\nCharacterisations. XRD data were acquired over a 2θ range of $10{-}80^{\\circ}$ on a Bruker D8 Advance diffractometer with a copper tube. The phase structures were analysed by Rietveld refinement using the GSAS programme and EXPGUI interface69. HR-TEM, HAADF-STEM and EDS mapping were performed using a FEI Titan G2 80-200 TEM/STEM operating at $200\\mathrm{kV}$ . SEM was taken using a Zeiss Neon 40EsB instrument. XPS was conducted on a Kratos Axis Ultra DLD spectrometer with a monochromatic Al Kα irradiation source. The electron binding energy scale was calibrated to the C 1 s peak for adventitious carbon, set at $284.8\\mathrm{eV}$ . NEXAFS experiments were performed at the Soft X-ray (SXR) Beamline at the Australian Synchrotron70. Spectra were collected using a channeltron detector in partial electron yield mode at a $55^{\\circ}$ incident angle. Data were analysed using the QANT software package71. The photon energy was calibrated by applying the offset required to shift the concurrently measured reference spectra of Co foil (for Co L-edge) to its known energy position. The specific surface area was determined by multipoint Kr adsorption tests under liquid nitrogen temperature $(77.3\\mathrm{K})$ on a Micromeritics TriStar II Plus instrument. Approximately $3.0\\mathrm{g}$ of samples were degassed by heating in vacuum at $200^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ \n\nprior to each test. The surface area was calculated using the BET equation, assuming that the value for the cross-sectional area of a Kr molecule at liquid nitrogen temperature is $0.210\\mathrm{nm}^{2}$ . Electrical conductivity was measured in air at room temperature based on a four-probe DC configuration using a Keithley 2420 source metre. The average bulk $\\mathrm{Co}$ oxidation state and oxygen vacancy concentration were determined by iodometric titrations. \n\nElectrochemical measurements. Electrochemical measurements were carried out under ambient conditions using an RDE-based, three-electrode configuration (Pine Research Instrumentation). A catalyst-modified glassy carbon (GC) RDE $(0.196\\mathrm{cm}^{2})$ , a Pt wire, and a $\\mathrm{\\Ag/AgCl}$ (4 M KCl) (all from Pine Research Instrumentation) served as the working, counter and reference electrode, respectively. Prior to use, the GC electrode was polished using ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ slurries to give a mirror finish and then cleaned by ultrasonication in Milli-Q water $(18.2\\mathrm{M}\\Omega\\mathrm{cm}),$ . The working electrode was prepared by dropcasting ${5}\\upmu\\mathrm{L}$ of an ultra-sonically dispersed catalyst ink, which contains $10\\mathrm{mg}$ of perovskite oxide, $2\\mathrm{mg}$ of Super ${\\dot{\\mathrm{P}}}^{\\circledast}$ carbon black (Alfa Aesar), ${900\\upmu\\mathrm{L}}$ of absolute ethanol and $100\\upmu\\mathrm{L}$ of $5\\mathrm{wt\\%}$ Nafion® 117 solution (Sigma-Aldrich), onto the GC surface, yielding an approximate catalyst loading of $0.255~\\mathrm{mg}_{\\mathrm{oxide}}~\\mathrm{cm}^{-2}$ The electrolyte was prepared using Milli-Q water and KOH pellets $(99.99\\%$ , Sigma-Aldrich). $\\mathrm{~\\i~}_{\\mathrm{{O}}_{2}}$ saturation was maintained to ensure the $\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}$ equilibrium at $1.23\\mathrm{V}$ vs. RHE. The electrochemical data were collected on a CH Instruments CHI760E potentiostat. To make the catalyst electrochemically accessible, the working electrode, held stationary, was first subjected to CV cycling between $-0.6$ and $-0.2\\mathrm{V}$ vs. $\\mathrm{Ag/AgCl}$ at $100\\dot{\\mathrm{mVs^{-1}}}$ until a stable CV curve was obtained72. Afterwards, the electrocatalytic performance was evaluated by running CV scans at $10\\mathrm{mVs^{-1}}$ with the electrode rotated at $2000\\mathrm{rpm}$ to readily get rid of gaseous $\\mathrm{O}_{2}$ bubbles evolved at the catalyst surface. To compensate for capacitive effects, the anodic and cathodic scans were averaged. Ohmic losses were corrected by subtracting the ohmic voltage drop from the measured potential using an electrolyte resistance $(\\approx45\\Omega)$ determined by electrochemical impedance spectroscopy. All potentials were reported in the RHE scale, which was converted from the $\\mathrm{\\Ag/AgCl}$ reference electrode scale by applying the equation: $E_{\\mathrm{RHE}}=E_{\\mathrm{Ag/AgCl}}+0.199+0.0591\\times\\mathrm{pH}$ (V). The overpotential $(\\eta)$ , defined as the gap between the applied potential and the equilibrium potential, was calculated based on the equation: $\\eta=E_{\\mathrm{RHE}}-1.229$ (V). The geometric current density (in $\\mathrm{_{1}\\ m A\\ c m^{-2}}_{\\mathrm{geo}}\\mathrm{}_{\\mathrm{}}\\mathrm{}_{\\mathrm{}}\\mathrm{}_{\\mathrm{}}\\mathrm{}_{}$ and specific activity (in $\\mathrm{mAcm}^{-2}\\mathrm{\\overline{{{\\alpha}}}}_{\\mathrm{oxide}})$ were obtained by normalising the OER current to the geometric surface area of the GC electrode and the BET surface area of the perovskite oxide, respectively. The Tafel plot was constructed using steady-state currents collected from multistep chronoamperometry73 in a potential range of $0.6\\mathrm{-}0.7\\:\\mathrm{V}$ vs. $\\mathrm{\\Ag/AgCl}$ at a $10~\\mathrm{mV}$ increment, with the ohmic drop compensated for. \n\nOxygen intercalation and diffusion coefficient measurements. The electrochemical oxygen intercalation was performed at room temperature in an Arsaturated 6 M KOH solution using a catalyst-modified GC working electrode, a Pt wire counter electrode, and a $\\mathrm{\\hbar{Hg/Hg0}}$ reference electrode. CV was run at a $20\\ \\mathrm{mV}\\ s^{-1}$ scan rate with the working electrode being stationary. To measure the oxygen ion diffusion coefficient, chronoamperometry was performed on the same working electrode by applying a potential $50\\mathrm{mV}$ more anodic of the $E_{1/2}$ (defined as the potential halfway between the peak currents for oxygen insertion and extraction). During the chronoamperometry testing, the rotation rate was set at $2000\\mathrm{rpm}$ to remove any electrolyte-based mass-transfer effect. The chronoamperometry data were plotted as current versus the inverse square root of time (i vs. $t^{-1/2})$ , in which the linear portion was fitted to obtain the intercept with the $t^{-1/2}$ axis (at $i=0$ ). Using a bounded three-dimensional diffusion model24,56,57, this intercept was used to calculate the oxygen ion diffusion coefficient according to the equation $\\lambda=a(D_{\\mathrm{O}}t)^{-1/2}$ , where $\\lambda$ is a dimensionless shape factor, a is the radius of the particle and $D_{\\mathrm{O}}$ is the diffusion coefficient. Here, λ was assumed to be 2, which is representative of a rounded parallelepiped, halfway between the values for a sphere $(\\lambda=1.77$ ) and a cube $\\left(\\lambda=2.26\\right)$ . a was estimated using the relation of $S=6/(2a\\rho)$ based on a spherical geometry approximation, where $s$ is the surface area measured from the BET method and $\\rho$ is the theoretical density determined by Rietveld analysis. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 11 September 2019; Accepted: 27 March 2020; Published online: 24 April 2020 \n\n# References \n\n1. Roger, I., Shipman, M. A. & Symes, M. D. Earth-abundant catalysts for electrochemical and photoelectrochemical water splitting. Nat. Rev. Chem. 1, 0003 (2017). \n\n2. Suryanto, B. H. R. et al. Challenges and prospects in the catalysis of electroreduction of nitrogen to ammonia. Nat. Catal. 2, 290–296 (2019). \n3. Voiry, D., Shin, H. S., Loh, K. P. & Chhowalla, M. Low-dimensional catalysts for hydrogen evolution and $\\mathrm{CO}_{2}$ reduction. Nat. Rev. Chem. 2, 0105 (2018). \n4. Cherevko, S. et al. Oxygen and hydrogen evolution reactions on Ru, $\\mathrm{RuO}_{2}$ , Ir, and $\\mathrm{IrO}_{2}$ thin film electrodes in acidic and alkaline electrolytes: a comparative study on activity and stability. Catal. Today 262, 170–180 (2016). \n5. Hwang, J. et al. Perovskites in catalysis and electrocatalysis. Science 358, 751–756 (2017). \n6. Xu, X., Zhong, Y. & Shao, Z. Double perovskites in catalysis, electrocatalysis, and photo(electro)catalysis. Trends Chem. 1, 410–424 (2019). \n7. Suntivich, J., May, K. J., Gasteiger, H. A., Goodenough, J. B. & Shao-Horn, Y. A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles. Science 334, 1383–1385 (2011). \n8. Jung, J.-I. et al. Fabrication of $\\mathrm{Ba_{0.5}S r_{0.5}C o_{0.8}F e_{0.2}O_{3-\\delta}}$ catalysts with enhanced electrochemical performance by removing an inherent heterogeneous surface film layer. Adv. Mater. 27, 266–271 (2015). \n9. Yagi, S. et al. Covalency-reinforced oxygen evolution reaction catalyst. Nat. Commun. 6, 8249 (2015). \n10. Xu, X. et al. Toward enhanced oxygen evolution on perovskite oxides synthesized from different approaches: a case study of $\\mathrm{Ba}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{Co}_{0.8}\\mathrm{Fe}_{0.2}\\mathrm{O}_{3-\\delta}.$ Electrochim. Acta 219, 553–559 (2016). \n11. Grimaud, A. et al. Double perovskites as a family of highly active catalysts for oxygen evolution in alkaline solution. Nat. Commun. 4, 2439 (2013). \n12. Zhao, B. et al. A tailored double perovskite nanofiber catalyst enables ultrafast oxygen evolution. Nat. Commun. 8, 14586 (2017). \n13. Sun, H. et al. B-site cation ordered double perovskites as efficient and stable electrocatalysts for oxygen evolution reaction. Chem. Eur. J. 23, 5722–5728 (2017). \n14. Sabatier, P. Hydrogénations et déshydrogénations par catalyse. Ber. Dtsch. Chem. Ges. 44, 1984–2001 (1911). \n15. Trasatti, S. Electrocatalysis by oxides — attempt at a unifying approach. J. Electroanal. Chem. Interfacial Electrochem. 111, 125–131 (1980). \n16. Bockris, J. O. M. & Otagawa, T. The electrocatalysis of oxygen evolution on perovskites. J. Electrochem. Soc. 131, 290–302 (1984). \n17. Rossmeisl, J., Qu, Z.-W., Zhu, H., Kroes, G.-J. & Nørskov, J. K. Electrolysis of water on oxide surfaces. J. Electroanal. Chem. 607, 83–89 (2007). \n18. Kim, J., Yin, X., Tsao, K.-C., Fang, S. & Yang, H. $\\mathrm{Ca}_{2}\\mathrm{Mn}_{2}\\mathrm{O}_{5}$ as oxygendeficient perovskite electrocatalyst for oxygen evolution reaction. J. Am. Chem. Soc. 136, 14646–14649 (2014). \n19. Zhu, Y. et al. $\\mathrm{SrNb}_{0.1}\\mathrm{Co}_{0.7}\\mathrm{Fe}_{0.2}\\mathrm{O}_{3-\\delta}$ perovskite as a next-generation electrocatalyst for oxygen evolution in alkaline solution. Angew. Chem. Int. Ed. 54, 3897–3901 (2015). \n20. Man, I. C. et al. Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem 3, 1159–1165 (2011). \n21. Rong, X., Parolin, J. & Kolpak, A. M. A fundamental relationship between reaction mechanism and stability in metal oxide catalysts for oxygen evolution. ACS Catal. 6, 1153–1158 (2016). \n22. Yoo, J. S., Liu, Y., Rong, X. & Kolpak, A. M. Electronic origin and kinetic feasibility of the lattice oxygen participation during the oxygen evolution reaction on perovskites. J. Phys. Chem. Lett. 9, 1473–1479 (2018). \n23. Yoo, J. S., Rong, X., Liu, Y. & Kolpak, A. M. Role of lattice oxygen participation in understanding trends in the oxygen evolution reaction on perovskites. ACS Catal. 8, 4628–4636 (2018). \n24. Mefford, J. T. et al. Water electrolysis on $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-\\delta}$ perovskite electrocatalysts. Nat. Commun. 7, 11053 (2016). \n25. Grimaud, A. et al. Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution. Nat. Chem. 9, 457–465 (2017). \n26. Fabbri, E. et al. Dynamic surface self-reconstruction is the key of highly active perovskite nano-electrocatalysts for water splitting. Nat. Mater. 16, 925–931 (2017). \n27. Surendranath, Y., Kanan, M. W. & Nocera, D. G. Mechanistic studies of the oxygen evolution reaction by a cobalt-phosphate catalyst at neutral pH. J. Am. Chem. Soc. 132, 16501–16509 (2010). \n28. Hibbert, D. B. & Churchill, C. R. Kinetics of the electrochemical evolution of isotopically enriched gases. Part $2.-^{18}\\mathrm{O}^{16}\\mathrm{O}$ evolution on $\\mathrm{NiCo}_{2}\\mathrm{O}_{4}$ and $\\mathrm{Li}_{x}\\mathrm{Co}_{3-x}\\mathrm{O}_{4}$ in alkaline solution. J. Chem. Soc. Faraday Trans. 180, 1965–1975 (1984). \n29. Huang, Z.-F. et al. Chemical and structural origin of lattice oxygen oxidation in $\\scriptstyle\\mathbf{Co-Zn}$ oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). \n30. Kim, B.-J. et al. Functional role of Fe-doping in Co-based perovskite oxide catalysts for oxygen evolution reaction. J. Am. Chem. Soc. 141, 5231–5240 (2019). \n31. Xu, X. et al. Co-doping strategy for developing perovskite oxides as highly efficient electrocatalysts for oxygen evolution reaction. Adv. Sci. 3, 1500187 (2016). \n32. Shin, J. F., Apperley, D. C. & Slater, P. R. Silicon doping in $\\mathrm{Ba}_{2}\\mathrm{In}_{2}\\mathrm{O}_{5}$ : Example of a beneficial effect of silicon incorporation on oxide ion/proton conductivity. Chem. Mater. 22, 5945–5948 (2010). \n33. Xu, X. et al. Earth-abundant silicon for facilitating water oxidation over ironbased perovskite electrocatalyst. Adv. Mater. Interfaces 5, 1701693 (2018). \n34. Shannon, R. D. Revised effective ionic radii and systematic studies of interatomic distances in halides and chalcogenides. Acta Cryst. A 32, 751–767 (1976). \n35. Appel, C. C. & Bonanos, N. Structural and electrical characterisation of silicacontaining yttria-stabilised zirconia. J. Eur. Ceram. Soc. 19, 847–851 (1999). \n36. Harrison, W. T. A., Hegwood, S. L. & Jacobson, A. J. A powder neutron diffraction determination of the structure of $\\mathrm{Sr}_{6}\\mathrm{Co}_{5}\\mathrm{O}_{15}.$ formerly described as the low-temperature hexagonal form of $\\mathrm{SrCoO}_{3-x}.$ . J. Chem. Soc. Chem. Commun. 1953–1954 (1995). \n37. King, G. & Woodward, P. M. Cation ordering in perovskites. J. Mater. Chem. 20, 5785–5796 (2010). \n38. Xu, M. et al. An intrinsically conductive phosphorus-doped perovskite oxide as a new cathode for high-performance dye-sensitized solar cells by providing internal conducting pathways. Sol. RRL 3, 1900108 (2019). \n39. Aguadero, A. et al. $\\mathrm{SrCo}_{0.95}\\mathrm{Sb}_{0.05}\\mathrm{O}_{3-\\delta}$ as cathode material for high power density solid oxide fuel cells. Chem. Mater. 22, 789–798 (2010). \n40. Suntivich, J., Gasteiger, H. A., Yabuuchi, N. & Shao-Horn, Y. Electrocatalytic measurement methodology of oxide catalysts using a thin-film rotating disk electrode. J. Electrochem. Soc. 157, B1263–B1268 (2010). \n41. Gorlin, Y. & Jaramillo, T. F. A bifunctional nonprecious metal catalyst for oxygen reduction and water oxidation. J. Am. Chem. Soc. 132, 13612–13614 (2010). \n42. Yu, J. et al. Activity and stability of Ruddlesden–Popper-type $\\mathrm{La}_{n+1}\\mathrm{Ni}_{n}\\mathrm{O}_{3n+1}$ $\\scriptstyle{\\dot{n}}=1$ , 2, 3, and $\\infty$ ) electrocatalysts for oxygen reduction and evolution reactions in alkaline media. Chem. Eur. J. 22, 2719–2727 (2016). \n43. Yamada, I. et al. Systematic study of descriptors for oxygen evolution reaction catalysis in perovskite oxides. J. Phys. Chem. C 122, 27885–27892 (2018). \n44. Lee, D.-G. et al. Polypyrrole-assisted oxygen electrocatalysis on perovskite oxides. Energy Environ. Sci. 10, 523–527 (2017). \n45. Zhou, S. et al. Engineering electrocatalytic activity in nanosized perovskite cobaltite through surface spin-state transition. Nat. Commun. 7, 11510 (2016). \n46. Park, H. W. et al. Electrospun porous nanorod perovskite oxide/nitrogendoped graphene composite as a bi-functional catalyst for metal air batteries. Nano Energy 10, 192–200 (2014). \n47. Zhu, Y. et al. Enhancing electrocatalytic activity of perovskite oxides by tuning cation deficiency for oxygen reduction and evolution reactions. Chem. Mater. 28, 1691–1697 (2016). \n48. Yang, C. et al. Phosphate ion functionalization of perovskite surfaces for enhanced oxygen evolution reaction. J. Phys. Chem. Lett. 8, 3466–3472 (2017). \n49. Yang, C. & Grimaud, A. Factors controlling the redox activity of oxygen in perovskites: From theory to application for catalytic reactions. Catalysts 7, 149 (2017). \n50. Zhou, Y. et al. Enlarged Co–O covalency in octahedral sites leading to highly efficient spinel oxides for oxygen evolution reaction. Adv. Mater. 30, 1802912 (2018). \n51. May, K. J. et al. Influence of oxygen evolution during water oxidation on the surface of perovskite oxide catalysts. J. Phys. Chem. Lett. 3, 3264–3270 (2012). \n52. Guan, D. et al. Searching general sufficient-and-necessary conditions for ultrafast hydrogen-evolving electrocatalysis. Adv. Funct. Mater. 29, 1900704 (2019). \n53. Dupin, J. C., Gonbeau, D., Benqlilou-Moudden, H., Vinatier, P. & Levasseur, A. XPS analysis of new lithium cobalt oxide thin-films before and after lithium deintercalation. Thin Solid Films 384, 23–32 (2001). \n54. Merino, N. A., Barbero, B. P., Eloy, P. & Cadús, L. E. $\\mathrm{La}_{1-x}\\mathrm{Ca}_{x}\\mathrm{CoO}_{3}$ perovskite-type oxides: Identification of the surface oxygen species by XPS. Appl. Surf. Sci. 253, 1489–1493 (2006). \n55. Conway, B. E. Electrochemical Supercapacitors (Springer, Boston, 1999). \n56. Van Buren, F. R., Broers, G. H. J., Bouman, A. J. & Boesveld, C. An electrochemical method for the determination of oxygen ion diffusion coefficients in $\\mathrm{La}_{1-x}\\mathrm{Sr}_{x}\\mathrm{CoO}_{3-)}$ compounds: theoretical aspects. J. Electroanal. Chem. Interfacial Electrochem. 87, 389–394 (1978). \n57. Van Buren, F. R., Broers, G. H. J., Bouman, A. J. & Boesveld, C. The electrochemical determination of oxygen ion diffusion coefficients in $\\mathrm{La}_{0.50}\\mathrm{Sr}_{0.50}\\mathrm{CoO}_{3-y}$ : experimental results and related properties. J. Electroanal. Chem. Interfacial Electrochem. 88, 353–361 (1978). \n58. Takeda, Y. et al. Phase relation and oxygen-non-stoichiometry of perovskitelike compound $\\mathrm{SrCoO_{x}}$ $(2.29<\\mathbf{x}>2.80$ ). Z. Anorg. Allg. Chem. 540, 259–270 (1986). \n59. Ishihara, T., Matsuda, H. & Takita, Y. Effects of rare earth cations doped for La site on the oxide ionic conductivity of $\\mathrm{LaGaO}_{3}$ -based perovskite type oxide. Solid State Ion. 79, 147–151 (1995). \n60. Deng, Z. Q., Yang, W. S., Liu, W. & Chen, C. S. Relationship between transport properties and phase transformations in mixed-conducting oxides. J. Solid State Chem. 179, 362–369 (2006). \n61. Gouget, G. et al. Associating and tuning sodium and oxygen mixed-ion conduction in niobium-based perovskites. Adv. Funct. Mater. 30, 1909254 (2020). \n62. Kim, G. et al. Rapid oxygen ion diffusion and surface exchange kinetics in $\\mathrm{PrBaCo}_{2}\\mathrm{O}_{5+x}$ with a perovskite related structure and ordered A cations. J. Mater. Chem. 17, 2500–2505 (2007). \n63. Dong, F. et al. Structural and oxygen-transport studies of double perovskites $\\mathrm{PrBa}_{1-x}\\mathrm{Co}_{2}\\mathrm{O}_{5+\\delta}$ $\\stackrel{\\cdot}{x}=0.00$ , 0.05, and 0.10) toward their application as superior oxygen reduction electrodes. J. Mater. Chem. A 2, 20520–20529 (2014). \n64. Hancock, C. A. & Slater, P. R. Synthesis of silicon doped $\\mathrm{SrMO}_{3}$ $\\mathbf{M}=\\mathbf{M}\\mathbf{n}$ , Co): stabilization of the cubic perovskite and enhancement in conductivity. Dalton Trans. 40, 5599–5603 (2011). \n65. Wu, J. et al. Room-temperature ligancy engineering of perovskite electrocatalyst for enhanced electrochemical water oxidation. Nano Res. 12, 2296–2301 (2019). \n66. ten Elshof, J. E., Lankhorst, M. H. R. & Bouwmeester, H. J. M. Oxygen exchange and diffusion coefficients of strontium-doped lanthanum ferrites by electrical conductivity relaxation. J. Electrochem. Soc. 144, 1060–1067 (1997). \n67. Adler, S. B. Factors governing oxygen reduction in solid oxide fuel cell cathodes. Chem. Rev. 104, 4791–4844 (2004). \n68. Mefford, J. T., Hardin, W. G., Dai, S., Johnston, K. P. & Steveson, K. J. Anion charge storage through oxygen intercalation in $\\mathrm{LaMnO}_{3}$ perovskite pseudocapacitor electrodes. Nat. Mater. 13, 726–732 (2014). \n69. Toby, B. H. EXPGUI, a graphical user interface for GSAS. J. Appl. Crystallogr. 34, 210–213 (2001). \n70. Cowie, B. C. C., Tadich, A. & Thomsen, L. The current performance of the wide range $(90-2500\\mathrm{eV})$ soft $\\mathbf{x}$ -ray beamline at the Australian Synchrotron. AIP Conf. Proc. 1234, 307–310 (2010). \n71. Gann, E., McNeill, C. R., Tadich, A., Cowie, B. C., Thomsen, L. & Quick, A. S. NEXAFS Tool (QANT): a program for NEXAFS loading and analysis developed at the Australian Synchrotron. J. Synchrotron Radiat. 23, 374–380 (2016). \n72. Zhao, S. et al. Ultrathin metal–organic framework nanosheets for electrocatalytic oxygen evolution. Nat. Energy 1, 16184 (2016). \n73. Martin-Sabi, M. et al. Redox tuning the Weakley-type polyoxometalate archetype for the oxygen evolution reaction. Nat. Catal. 1, 208–213 (2018). \n\n# Acknowledgements \n\nThis work was supported by the Australian Research Council Discovery Projects (Grant Nos. DP150104365 and DP160104835) and Australian Research Council Linkage Projects (Grant No. ARC LP160101729). We are thankful for the facilities and scientific and technical assistance from the Curtin University X-ray Laboratory, the University of Western Australia Centre for Microscopy, Characterisation and Analysis, which were partially funded by the University, State, and Commonwealth Governments. We would also like to acknowledge the WA X-Ray Surface Analysis Facility, funded by an Australian Research Council LIEF grant (LE120100026). NEXAFS measurements were performed on the Soft X-ray (SXR) Beamline at the Australian Synchrotron, Victoria, Australia. We are grateful for the technical support from Lars Thomsen of the Australian Synchrotron. Y.P. and X.X. would like to acknowledge the contribution of an Australian \n\nGovernment Research Training Program Scholarship in supporting the research. R.O. \nacknowledges support from the 2019-2020 Fulbright Global Scholar Program. \n\n# Author contributions \n\nZ.S. and L.G. conceived and designed the research. Y.P. and X.X. conducted materials synthesis and electrochemical measurements. Y.P. and X.X. characterised the samples involving XRD, TEM, SEM, XPS and BET, assisted by Y.Z., J.-P.M.V., M.L., G.W. and H.W.; X.X., Y.Z. and J.-P.M.V. performed the NEXAFS experiments. D.G. performed iodometric titrations under the supervision of W.Z.; Y.C. performed XRD refinement analysis. Y.P. and X.X. analysed the data with the inputs from all the other authors. Y.P., X.X., L.G. and Z.S. co-wrote the manuscript, with modifications done by R.O. All authors commented on and contributed to the final version of the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-15873-x. \n\nCorrespondence and requests for materials should be addressed to L.G. or Z.S. \n\nPeer review information Nature Communications thanks Peter Slater and other, anonymous, reviewers for their contributions to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2020 " + }, + { + "id": "10.1038_s41467-021-23115-x", + "DOI": "10.1038/s41467-021-23115-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-23115-x", + "Relative Dir Path": "mds/10.1038_s41467-021-23115-x", + "Article Title": "Electrochemical ammonia synthesis via nitrate reduction on Fe single atom catalyst", + "Authors": "Wu, ZY; Karamad, M; Yong, X; Huang, QZ; Cullen, DA; Zhu, P; Xia, CA; Xiao, QF; Shakouri, M; Chen, FY; Kim, JY; Xia, Y; Heck, K; Hu, YF; Wong, MS; Li, QL; Gates, I; Siahrostami, S; Wang, HT", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electrochemically converting nitrate, a widespread water pollutant, back to valuable ammonia is a green and delocalized route for ammonia synthesis, and can be an appealing and supplementary alternative to the Haber-Bosch process. However, as there are other nitrate reduction pathways present, selectively guiding the reaction pathway towards ammonia is currently challenged by the lack of efficient catalysts. Here we report a selective and active nitrate reduction to ammonia on Fe single atom catalyst, with a maximal ammonia Faradaic efficiency of similar to 75% and a yield rate of up to similar to 20,000 mu gh(-1) mg(cat.)(-1) (0.46mmolh(-1) cm(-2)). Our Fe single atom catalyst can effectively prevent the N-N coupling step required for N-2 due to the lack of neighboring metal sites, promoting ammonia product selectivity. Density functional theory calculations reveal the reaction mechanisms and the potential limiting steps for nitrate reduction on atomically dispersed Fe sites.", + "Times Cited, WoS Core": 998, + "Times Cited, All Databases": 1023, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000658736000013", + "Markdown": "# Electrochemical ammonia synthesis via nitrate reduction on Fe single atom catalyst \n\nZhen-Yu Wu 1, Mohammadreza Karamad2, Xue Yong3, Qizheng Huang1, David A. Cullen $\\textcircled{6}$ 4, Peng Zhu $\\textcircled{6}$ 1, Chuan Xia1, Qunfeng Xiao5, Mohsen Shakouri $\\textcircled{1}$ 5, Feng-Yang Chen $\\textcircled{1}$ 1, Jung Yoon (Timothy) Kim1, Yang Xia1, Kimberly Heck1, Yongfeng Hu $\\textcircled{1}$ 5, Michael S. Wong $\\textcircled{1}$ 1, Qilin ${\\mathsf{L i}}^{6},$ Ian Gates $\\textcircled{1}$ 2, Samira Siahrostami $\\textcircled{1}$ 3✉ & Haotian Wang 1,7,8,9✉ \n\nElectrochemically converting nitrate, a widespread water pollutant, back to valuable ammonia is a green and delocalized route for ammonia synthesis, and can be an appealing and supplementary alternative to the Haber-Bosch process. However, as there are other nitrate reduction pathways present, selectively guiding the reaction pathway towards ammonia is currently challenged by the lack of efficient catalysts. Here we report a selective and active nitrate reduction to ammonia on Fe single atom catalyst, with a maximal ammonia Faradaic efficiency of \\~ $75\\%$ and a yield rate of up to $\\sim20,000\\upmu\\mathrm{g}\\mathsf{h}^{-1}\\mathsf{m g}_{\\mathsf{c a t.}}\\mathsf{\\ensuremath{\\tau}}^{-1}(0.46\\mathsf{m m o l}\\mathsf{h}^{-1}\\mathsf{c m}^{-2})$ . Our Fe single atom catalyst can effectively prevent the N-N coupling step required for ${\\sf N}_{2}$ due to the lack of neighboring metal sites, promoting ammonia product selectivity. Density functional theory calculations reveal the reaction mechanisms and the potential limiting steps for nitrate reduction on atomically dispersed Fe sites. \n\nmmonia $(\\mathrm{NH}_{3})$ is one of the most fundamental chemical ? feedstocks in thex world, as it is not only an indispensable chemical for fertilizer, pharmaceutical, dyes, etc., but also considered as an important energy storage medium and carbonfree energy carrier1–5. Currently, the industrial-scale ${\\mathrm{NH}}_{3}$ synthesis relies on the century-old Haber–Bosch process, which requires harsh operating conditions including high temperature $(400-500^{\\circ}\\mathrm{C})$ and high pressure $(150-300\\mathrm{atm})$ using heterogeneous iron-based catalysts $6{-}12$ . Due to its enormous annual production and energy-intensive processes, the ${\\mathrm{NH}}_{3}$ synthesis industry accounts for $1-2\\%$ of the world’s energy supply, and causes ca. 1% of total global energy-related CO2 emissions5,7,9,10. As an attractive alternative to the Haber–Bosch process, the electrochemical ${\\mathrm{NH}}_{3}$ synthesis route, with renewable electricity inputs such as solar or wind, has attracted tremendous interests over the past few years4,5,7,9,10,13–17. Nitrogen gas $(\\Nu_{2})$ from air was identified as one major nitrogen source for this renewable route via electrochemical nitrogen reduction reaction (NRR); however, due to the extremely stable ${\\mathrm{N}}\\equiv{\\mathrm{N}}$ triple bond (941 kJ $\\mathrm{mol^{-1}}.$ ) and its non-polarity, NRR suffers from low selectivity (referring to Faradaic efficiency in this work unless otherwise specified) and activity5,10,13,18–20. While exciting progresses in NRR catalyst development have been made, in many cases it is still challenging to firmly attribute the detected $\\mathrm{NH}_{3}$ to NRR process rather than contaminations due to the extremely low $\\bar{\\mathrm{NH}}_{3}$ production rate (mostly $<200\\upmu\\mathrm{g}\\mathrm{h}^{-1}\\mathrm{mg}_{\\mathrm{cat.}}-1)^{\\upxi,10,21}$ Therefore, using $\\Nu_{2}$ gas as the $_\\mathrm{N}$ source for electrochemical synthesis of $\\mathrm{NH}_{3}$ , as promising as it is, still has a long way to go to deliver considerable yields for practical applications. \n\nNitrate $\\left(\\mathrm{NO}_{3}{}^{-}\\right)$ ions as one of the world’s most widespread water pollutants become an attractive nitrogen source, alternative to the inert ${\\mathrm{N}}_{2},$ for electrochemical synthesis of ${\\mathrm{NH}}_{3}$ (refs. 22–27). Nitrate source mainly comes from industrial wastewater, liquid nuclear wastes, livestock excrements, and chemical fertilizers, with a wide range of concentrations up to ca. $2\\mathrm{M}^{23,28-34}$ . Using electrochemical methods to remove nitrate contaminants from industrial wastewater has been an important topic in environmental research field, and their targeted product of nitrate reduction is $\\Nu_{2}$ instead of ${\\mathrm{NH}}_{3}$ (refs. 29–31,35). A variety of metal catalysts (including Ru, Rh, Ir, Pd, Pt, Cu, Ag, and Au) and their alloys have been developed over the years to selectively convert ${\\mathrm{NO}}_{3}{}^{-}$ to $\\Nu_{2}$ , with ${\\mathrm{NH}}_{3}$ as the byproducts28,32,36. The development of high-performance electrocatalysts to selectively reduce nitrate wastes into value-added ${\\mathrm{NH}}_{3}$ will open up a different route of nitrate treatment, and impose both economic and environmental impacts on sustainable $\\mathrm{NH}_{3}$ synthesis. \n\nAs the ${\\mathrm{NO}}_{3}{}^{-}$ reduction to $\\mathrm{NH}_{3}$ involves $8e^{-}$ transfers and many possible reaction pathways $\\mathrm{(NO}_{2}$ , $\\mathrm{NO}_{2}{}^{-}$ , NO, ${\\mathrm{N}}_{2}{\\mathrm{O}}_{3}$ , $\\mathrm{N}_{2}$ , $\\mathrm{NH}_{2}\\mathrm{OH}$ , $\\mathrm{NH}_{3}$ , and $\\mathrm{NH}_{2}\\mathrm{\\dot{N}H}_{2})^{37-39}$ , an in-depth molecular level understanding of elementary steps can guide the rational design of selective catalysts for $\\mathrm{NH}_{3}$ . As an important competition, $\\mathrm{NO}_{3}^{-}$ reduction to $\\Nu_{2}$ pathway involves a $_{\\mathrm{N-N}}$ coupling step, where two neighboring active sites are possibly needed such as Rh- or $\\mathtt{C u}$ -based metal catalysts32,40. By dispersing transition metal (TM) atoms into isolated single atoms embedded in supports, the $_{\\mathrm{N-N}}$ coupling pathway towards $\\Nu_{2}$ gas could be prevented due to the lack of an active neighboring site. As a result, the selectivity towards ${\\mathrm{NH}}_{3}$ could be promoted. Due to this unique atomic structure and electronic property compared to bulk or nanosized TM catalysts, single-atom catalysts (SACs) have attracted tremendous research interests in catalysis field, presenting untraditional activity and selectivity in many catalytic reactions41–44. Nevertheless, TM SACs have never been reported for electrocatalytic ${\\mathrm{NO}}_{3}{}^{-}$ -to- $\\mathrm{\\cdotNH}_{3}$ conversion, to the best of our knowledge. More importantly, the well-defined atomic structure of single atomic sites can serve as a great platform to study nitrate reaction pathways, which are highly complex and poorly understood. \n\nInspired by the Fe active sites in both Haber–Bosch catalysts (Fe-based compounds) and nitrogenase enzymes (mainly containing Fe–Mo cofactor)5,10, here we report excellent activity and selectivity of Fe single atomic sites in reducing ${\\mathrm{NO}}_{3}{}^{-}$ towards $\\mathrm{NH}_{3}$ . Deposited on a standard glassy carbon electrode, our Fe SAC delivered a maximal ${\\mathrm{NH}}_{3}$ Faradaic efficiency (FE) of ${\\sim}75\\%$ at $-0.66\\mathrm{V}$ vs. reversible hydrogen electrode (RHE), with $\\mathrm{NH}_{3}$ partial current density of up to $\\sim100\\mathrm{mAcm}^{-2}$ at $-0.85\\mathrm{V}$ . This corresponds to an impressive $\\mathrm{NH}_{3}$ yield rate of ${\\sim}20,000\\upmu\\mathrm{gh}^{-1}$ $\\mathrm{mg_{cat.}}^{-1}$ . Importantly, the Fe SAC displayed a significantly improved $\\mathrm{NH}_{3}$ yield rate than that of Fe nanoparticle catalysts despite much lower Fe contents. We used density functional theory (DFT) calculations to elucidate reaction mechanism for ${\\mathrm{NO}}_{3}{}^{-}$ reduction to $\\mathrm{NH}_{3}$ on Fe single atomic site. In addition, we show that $\\mathrm{NO^{*}}$ reduction to $\\mathrm{HNO^{*}}$ and $\\mathrm{HNO^{*}}$ reduction to $\\mathrm{N^{*}}$ are the potential limiting steps. \n\n# Results \n\nSynthesis and characterizations of Fe SAC. The Fe SAC was synthesized by a TM-assisted carbonization method using $\\mathrm{SiO}_{2}$ powers as hard templates45,46. The strategy involves mixing precursors including $\\mathrm{FeCl}_{3}$ , $o$ -phenylenediamine with $\\mathrm{SiO}_{2}$ powder, followed by pyrolysis of the mixture, then NaOH and ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ etching and second pyrolysis (Fig. 1a; “Methods”). The lowmagnification transmission electron microscopy (TEM) image of Fe SAC indicates an interconnected vesicle-like structure with well-defined pores originating from $\\mathrm{SiO}_{2}$ hard templates (Fig. 1b and Supplementary Fig. 1). No nanoparticles can be found on the carbon frameworks. Isolated Fe single atoms dispersed on the porous carbon matrix can be clearly identified as bright dots by the aberration-corrected medium-angle annular dark-field scanning transmission electron microscopy (AC MAADF-STEM) image in Fig. 1c (“Methods”). No Fe clusters or nanoparticles are observed in many different areas of Fe SAC (Supplementary Fig. 2). The Fe metal loading is estimated to be $1.51~\\mathrm{wt\\%}$ based on inductively coupled plasma-optical emission spectroscopy (ICPOES) analysis. Energy-dispersive X-ray spectroscopy (EDS) mapping analysis confirms the existence of Fe, N, and C elements throughout the porous structure (Fig. 1d). A sophisticated point analysis of electron energy loss spectroscopy (EELS) on a single Fe atomic site, as shown in Fig. 1e, confirms the Fe–N–C coordination environment. Considering the angstrom resolution of the electron probe, the signals in EELS point spectrum comes from the Fe atom and its closest neighboring atoms47,48, suggesting a high possibility of Fe–N direct coordination in Fe SAC. Other point spectra acquired from different areas confirmed similar coordination environments (Supplementary Fig. 3). The X-ray diffraction (XRD) pattern of the Fe SAC exhibits two distinct characteristic peaks at ca. $26.2^{\\circ}$ and $43.7^{\\circ}$ , corresponding to the (002) and (101) planes of graphitic carbon (Fig. 1f). There are no characteristic peaks of Fe-based crystals, demonstrating that no large Fe-based crystalline nanoparticles exist in the catalyst. The graphitic carbon structures are also shown by high-resolution TEM as well as Raman spectroscopy (Supplementary Figs. 4 and 5). We used $\\Nu_{2}$ sorption method to analyze the pore structures of the Fe SAC (Fig. 1g), where a remarkable hysteresis loop of typeIV indicates the presence of highly mesoporous structures in Fe SAC. The mesopore size distribution is centered at $18.3\\mathrm{nm}$ (inset in Fig. 1g), and the Brunauer–Emmett–Teller (BET) surface area and pore volume are $285.8\\mathrm{m}^{2}\\mathrm{g}^{-1}$ and $0.80\\mathsf{c m}^{3}\\mathsf{g}^{-1}$ , respectively (Supplementary Table 1). \n\nWe further analyzed the chemical and atomic structure of our Fe SAC using X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS). In XPS results (Fig. 2a and Supplementary Fig. 6a), the high-resolution $\\mathrm{\\DeltaN}$ 1s spectrum contains four peaks at 398.5, 399.8, 401.0, and $402.6\\mathrm{eV}$ , which are assigned to pyridinic $\\mathrm{\\DeltaN,\\Omega}$ pyrrolic $\\mathrm{\\DeltaN_{:}}$ , graphitic $\\mathrm{N,}$ and oxidized N, respectively46,49. No obvious Si $2p$ XPS signal was found, indicating that $\\mathrm{SiO}_{2}$ templates have been completely removed (Supplementary Fig. 6b). The high-resolution Fe $2p$ spectrum with two relatively weak peaks centered at 711.1 eV (Fe $2p_{3/2})$ and $723.9\\mathrm{eV}$ (Fe $2p_{1/2}\\mathrm{,}$ ) suggests the positive oxidation states of Fe species in the Fe SAC (Supplementary Fig. 6c)50. This is consistent with our XAS analysis (Fig. 2b). The Fe K-edge Xray absorption near-edge structure (XANES) of Fe SAC presents a near-edge absorption energy between Fe metal foil and ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ references, indicating that the oxidation state of Fe single atoms sits between $\\mathrm{Fe}^{0}$ and $\\mathrm{Fe}^{3+}$ (Fig. 2b). The corresponding Fouriertransformed (FT) $\\mathrm{k}^{3}$ -weighted extended X-ray absorption fine structure (EXAFS) spectrum shows one dominant peak at around $1.6\\mathring\\mathrm{A}.$ , which can be assigned to the Fe–N coordination at the first shell $(\\mathrm{Fig.~}2\\mathsf{c})^{49-51}$ . No Fe–Fe interaction peak at $2.2\\mathring\\mathrm{A}$ can be observed, excluding the possibility of any Fe clusters or nanoparticles in our catalyst. These results conclude that the Fe atoms are atomically dispersed in the N-doped carbon (NC) matrix, consistent with our STEM observations. Owing to the powerful resolutions in both $\\mathbf{k}$ and R spaces, wavelet transform (WT) of Fe K-edge EXAFS oscillations was employed to further explore the atomic dispersion of Fe in Fe SAC. Only one intensity maximum is observed at ${\\sim}4.6\\mathring{\\mathrm{A}}^{-1}$ in the WT contour plots, which corresponds to the Fe–N coordination. No intensity maximum belonging to Fe–Fe contribution can be observed, compared with the WT plots of Fe foil and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ (Fig. 2d). To better understand the Fe coordination environment, we also conducted the EXAFS fitting to obtain the structural parameters and extract the quantitative chemical configuration of Fe atoms (Fig. 2e, f). Each Fe atom is coordinated by about 4N atoms in average, and the mean bond length is $1.{\\dot{9}}2{\\mathring{\\mathrm{A}}}$ (Supplementary Table 2). According to these fitting results, the proposed coordination structure of Fe SAC is ${\\mathrm{Fe-N}}_{4},$ which is shown as the inset in Fig. 2f. The EXAFS fitting results of Fe foil and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ are presented in Supplementary Fig. 7 and Supplementary Table 2. Additionally, only one peak at the $\\mathrm{L}_{3}$ -edge and no clear multiple structures are found in the Fe L-edge XANES spectrum of Fe SAC, which suggests a unique feature of delocalized Fe $3d$ electrons of Fe $\\mathrm{SAC^{49}}$ . The itinerant Fe $3d$ electrons of Fe SAC can be shared by the porphyrin-like structures (as analyzed by Fe K-edge EXAFS fitting) and enhance the electrical conductivity of the catalyst (Fig. $2\\mathrm{g})^{4\\bar{9}}$ . Other TM SACs including Co and Ni were also prepared using the same synthesis method, and characterized to confirm their atomic dispersion of TM atoms in NC support (Supplementary Figs. 8–21, Supplementary Tables 1and 2 and Supplementary Note 1). \n\n![](images/f233cb9df8a2c3d602a345212b6b8daad4c1c5d05fa590edf4ca1d128f73f647.jpg) \nFig. 1 Synthesis and characterization of Fe SAC. a Schematic illustration of the synthesis of Fe SAC. b TEM, c AC MAADF-STEM, and d EDS mapping images of Fe SAC. e EELS point spectrum from the Fe atomic site identified by the yellow arrow in the inserted AC MAADF-STEM image of Fe SAC. f XRD pattern and $\\pmb{\\mathsf{g}}\\mathsf{N}_{2}$ adsorption–desorption isotherms of Fe SAC. Inset in $\\pmb{\\mathrm{\\pmb{g}}}$ is pore-size distribution curve. Scale bars, b $200\\mathsf{n m}$ , $\\textsf{\\pmb{c}}2\\mathsf{n m}$ , and d $100\\mathsf{n m}$ . Note: a.u. means arbitrary units unless otherwise specified. \n\n![](images/fe46ed30785c0da7f47c99630282be6c4205bfaa9c077e62dea6589b7c37f471.jpg) \nFig. 2 Structural analysis of Fe SAC. a High-resolution N 1 s of the Fe SAC. b XANES spectra at the Fe K-edge of the Fe SAC, referenced Fe foil and $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ . c FT $k^{3}$ -weighted $\\chi(\\boldsymbol{k})$ -function of the EXAFS spectra at Fe K-edge. d WT of the Fe K-edge. Fitting results of the EXAFS spectra of Fe SAC at e k-space and f R space. Inset: Schematic model of Fe SAC: Fe (yellow), N (blue), and C (gray). $\\pmb{\\mathsf{g}}$ XANES spectrum at Fe L-edge of Fe SAC. \n\nElectrocatalytic nitrate reduction performance. Electrochemical nitrate reduction was conducted in a customized H-cell under ambient conditions. The Fe SAC was deposited onto a mirrorpolished glassy carbon electrode with a fixed catalyst mass loading of $0.4\\mathrm{mg}\\mathrm{cm}^{-2}$ . We first performed the linear sweep voltammetry (LSV) in ${\\mathrm{K}}_{2}{\\mathrm{SO}}_{4}$ electrolyte with and without ${\\mathrm{KNO}}_{3}$ to study the nitrate reduction catalytic activity of Fe SAC (Fig. 3a). The obviously enhanced current density under the same potential suggests that ${\\mathrm{NO}}_{3}{}^{-}$ ions can be effectively reduced by the Fe SAC. Product selectivity was performed in $\\mathrm{K_{2}S O_{4}/K N O_{3}}$ electrolyte by holding a certain potential each time for $0.5\\mathrm{h}$ , with generated $\\mathrm{NH}_{3}$ products quantified by ultraviolet-visible (UV–Vis) spectrophotometry (Supplementary Fig. 22; see “Methods”). As shown in Fig. 3b, c, our Fe SAC shows high selectivity and superior yield rate for electrocatalytic $N\\mathrm{O}_{3}\\mathrm{^-to}{\\mathrm{-N}\\mathrm{H}_{3}}$ conversion. At $-0.50\\mathrm{V}$ vs. RHE when the reaction starts to onset (an overall current density of $4.3\\mathrm{mA}\\mathrm{cm}^{-2},$ ), $\\mathrm{NH}_{3}$ product can be readily detected with an FE of $39\\%$ , representing a yield rate of $331\\upmu\\mathrm{{\\dot{g}}h^{-1}\\ m g_{\\mathrm{cat.}}}^{-1}$ (Fig. 3b, c). The ${\\mathrm{NH}}_{3}$ selectivity gradually increases to a maximal of ${\\sim}75\\%$ at $-0.66\\mathrm{V}$ under an overall current density of $35.3\\mathrm{mA}\\mathrm{cm}^{-2}$ , delivering a yield rate of $5245\\upmu\\mathrm{gh}^{-1}\\mathrm{m}{\\dot{\\mathrm{g}}_{\\mathrm{cat.}}}^{-1}$ . The $\\mathrm{NH}_{3}$ Faradaic efficiency does not change with time and keeps around $75\\%$ during $^{2\\mathrm{h}}$ (Supplementary Fig. 23). A large $\\mathrm{NH}_{3}$ partial current density of ${\\sim}100\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ is achieved at $-0.85\\mathrm{V}$ , corresponding to an impressive yield rate of ${\\sim}20,000\\upmu\\mathrm{gh^{-1}m g_{\\mathrm{cat.}}}^{-1}$ . The bare glassy carbon electrode shows a negligible nitrate reduction activity to ammonia (Supplementary Fig. 24). The FE and yield rate of ${\\mathrm{NO}}_{3}{}^{-}$ -to- ${\\mathrm{NH}}_{3}$ conversion on Fe SAC are orders of magnitude higher than reported ${\\mathrm{N}}_{2^{-}}{\\mathrm{to}}{\\mathrm{-N}}{\\mathrm{H}}_{3}$ conversions10,21, due to the dramatically different kinetic energy barriers to overcome39; more importantly, the ammonia activity per metal active site favorably compare with other nitrate reduction systems which typically used bulk or nanostructured transition metal catalysts (Supplementary Table 3)22–24,39,52–55. Different from $\\mathrm{N}_{2}$ reduction studies where the concentrations of generated $\\mathrm{NH}_{3}$ are typically much lower than $^1\\mathrm{H}$ nuclear magnetic resonance (NMR) detection limit, in our case the generated ${\\mathrm{NH}}_{3}$ has concentrations high enough to be accurately quantified by NMR test, which helps to independently confirm our UV–Vis test. We chose the maximal FE point to be validated by NMR (see “Methods”). As shown in Fig. 3d, three peaks corresponding to $^{14}\\mathrm{N}\\mathrm{H}_{4}{}^{+}$ are clearly observed in electrolytes after $0.{\\bar{5}}{\\cdot}\\mathrm{h}$ electrolysis under $-0.66\\mathrm{V}$ . Based on the averaged NMR peak areas of three independent electrolysis tests and the calibration curve of $^{14}\\mathrm{N}\\mathrm{H}_{4}{}^{+}$ (Supplementary Fig. 25), we obtained an FE of $\\mathrm{NH}_{3}$ at $\\sim76\\%$ (Fig. 3b), in good agreement with our UV–Vis spectrophotometry measurements. Additionally, we used NMR to confirm that the ${\\mathrm{NH}}_{3}$ produced actually came from ${\\mathrm{NO}}_{3}{}^{-}$ ions using $^{15}\\mathrm{N}$ -labeled ${\\mathrm{NO}}_{3}{}^{-}$ (Fig. 3e). Only two peaks of $^{15}\\mathrm{N}\\mathrm{H_{4}}^{+}$ appear in $^1\\mathrm{H}$ NMR spectra with their peak intensity increasing with the electrolysis time, confirming that the $\\mathrm{NH}_{3}$ generated is from electrochemical nitrate reduction rather than contaminations. Also, no ${\\mathrm{NH}}_{3}$ could be detected if ${\\mathrm{KNO}}_{3}$ was absent in the electrolyte during the electrolysis (Supplementary Fig. 26). \n\n![](images/57ccd7227fc88ba5c5ad31cfc5a189c8a6105c0545d0b99b06c790deda6ed6c0.jpg) \nFig. 3 Electrocatalytic nitrate reduction performance. a LSV curves of the Fe SAC in 0.25 M $K_{2}S O_{4}$ electrolyte and $0.50\\mathsf{M}$ $K N O_{3}/0.10$ M ${\\sf K}_{2}{\\sf S}{\\sf O}_{4}$ mixed electrolyte. b $N H_{3}$ FE of Fe SAC at each given potential. Red dot is FE estimated by three independent NMR tests. c $N H_{3}$ yield rate and partial current density of Fe SAC, FeNP/NC, and NC. d $^1\\mathsf{H}$ NMR spectra for the electrolytes after three independent nitrate reduction tests at $-0.66\\vee$ . e $^1\\mathsf{H}$ NMR spectra for electrolytes after $^{15}{\\mathsf{N O}}_{3}{}^{-}$ reduction tests at different time using $0.50\\mathsf{M}\\mathsf{K}^{15}\\mathsf{N O}_{3}/0.10\\mathsf{M}\\mathsf{K}_{2}\\mathsf{S O}_{4}$ mixed electrolyte. f $N H_{3}$ yield rate of Fe SAC, Co SAC, and Ni SAC based on metal content. $\\pmb{\\mathsf{g}}$ The cycling tests of Fe SAC for reduction tests at $-0.66\\vee$ . Catalyst loading for all of electrocatalytic nitrate reduction tests is $0.4\\mathsf{m g}\\mathsf{c m}^{-2}$ . \n\nThe main byproduct of nitrate reduction on Fe SAC is $\\mathrm{NO}_{2}^{-}$ , the simplest nitrate reduction product, as detected and quantified by UV–Vis (Supplementary Figs. 27 and 28). The FE of $\\mathrm{NO}_{2}^{-}$ starts from as high as $66\\%$ at the onset potential, followed by a gradual decease to a minimal of ${\\sim}9\\%$ . This trend correlates to the gradual increase of $\\mathrm{NH}_{3}$ selectivity, suggesting that $\\mathrm{NO}_{2}^{-}$ could be an intermediate product and can be further reduced to $\\mathrm{NH}_{3}$ under more negative potentials. This hypothesis was further validated by performing $\\mathrm{NO}_{2}^{-}$ reduction on Fe SAC, where more than $90\\%$ FE of ${\\mathrm{NH}}_{3}$ and higher production rates can be achieved under the studied potential window (Supplementary Fig. 29). Other possible minor products such as $\\mathrm{N}_{2}$ and $\\mathrm{H}_{2}$ were further quantified by gas chromatography, with FEs less than $1\\%$ . In fact, gas bubbles could hardly be observed on the working electrode during electrolysis until the potential is more negative than $-0.73\\mathrm{V}$ . \n\nAs various nitrate concentrations exist in different sources, we also evaluated the catalytic performance of Fe SAC at initial ${\\mathrm{KNO}}_{3}$ concentrations ranging from 0.05 to $1.0\\mathrm{M}$ . The maximal FEs of ${\\mathrm{NO}}_{3}{}^{-}$ -to- $\\cdot\\mathrm{NH}_{3}$ conversion were 74.3, 71.8, and $73.5\\%$ in \n\n0.05, 0.1, and $1\\mathrm{M}\\mathrm{KNO}_{3}$ , respectively, similar to the performance tested in 0.5 M ${\\mathrm{KNO}}_{3}$ solution (Supplementary Fig. 30). This suggests that the ${\\mathrm{NO}}_{3}{}^{-}$ concentration has no obvious impacts on Fe SAC’s ${\\mathrm{NH}}_{3}$ selectivity. In addition, we observed that the ${\\mathrm{NH}}_{3}$ yield rate was greatly enhanced by increasing the ${\\mathrm{KNO}}_{3}$ concentrations from 0.05 to $0.5{\\mathrm{M}}{}$ , but remained nearly unchanged with further increase to $1.0\\mathrm{M}$ . We found that this performance difference was not due to the mass diffusion limit or the concentration of $\\mathrm{K^{+}}$ (Supplementary Figs. 31 and 32). There could be a transition of rate-limiting step in the kinetic regime from positive to zero order in nitrate from 0.05 to $1.0\\mathrm{M}$ . For some practical applications, when the nitrate concentrations are much lower or higher in some sources, some strategies could be adopted, such as using mature industrial concentrating processes to concentrate those low-concentration nitrates, and diluting highly concentrated nitrates before conversion, as well as electrochemical cell engineering technology56,57. Besides, we found that the presence of $\\mathrm{\\DeltaNaCl}$ in the electrolyte did not affect the catalytic performance of Fe SAC for nitrate reduction (Supplementary Fig. 33). We also investigated nitrate reduction on Fe SAC at different $\\mathrm{\\tt{pH}}$ (Supplementary Fig. 34). The FE of ${\\mathrm{NO}}_{3}{}^{-}$ -to- $\\boldsymbol{\\cdot}\\mathrm{NH}_{3}$ conversion in the alkaline solution $(\\mathrm{pH}=13$ ) is similar to that at neutral $\\mathsf{p H}$ with significantly improved overpotentials, while the catalytic activity and selectivity are significantly lower in acidic solution $(\\mathsf{p H}=1$ ). In addition, the FE of ${\\mathrm{NO}}_{3}{}^{-}$ -to- $\\cdot\\mathrm{NH}_{3}$ conversion can be enhanced by further optimizing our catalysis system (Supplementary Fig. 35). An FE of $86\\%$ for ${\\mathrm{NO}}_{3}{}^{-}$ -to- ${\\cdot\\mathrm{NH}_{3}}$ conversion and ${\\mathrm{NH}}_{3}$ partial current of $60.7\\mathrm{mA}\\mathrm{cm}^{-2}$ were achieved at $-0.21\\mathrm{V}$ in $0.1\\mathrm{M}$ $\\mathrm{KNO}_{3}/1.0\\mathrm{M}$ KOH mixed electrolyte for 2-h electratalysis test (Supplementary Fig. 35 and Supplementary Table 3). \n\nTo explore the active sites in our Fe SAC, control experiments in NC and Fe nanoparticles supported on NC (FeNP/NC) were performed to compare with Fe SAC (Supplementary Figs. 36 and 37; see “Methods”). NC support exhibits much lower $\\mathrm{NH}_{3}$ activity compared to Fe SAC (Fig. 3c). Although FeNP catalyst shows similar $\\mathrm{NH}_{3}$ FE to Fe SAC (Supplementary Fig. 38b), the ${\\mathrm{NH}}_{3}$ yield rate of FeNP/NC was significantly lower than that of Fe SAC (Fig. 3c). Once normalized by metal contents, the ${\\mathrm{NH}}_{3}$ yield rate of Fe SAC per molar Fe is ${\\sim}20$ times higher than that of the NP counterparts, revealing the extraordinary activity on Fe single atomic site (Supplementary Fig. 39 and Supplementary Note 2). The double-layer capacitance $(C_{\\mathrm{dl}})$ which is proportional to the electrochemical surface area of Fe SAC and FeNP/NC are very close, further demonstrating the intrinsically higher activity of Fe SAC than FeNP/NC (Supplementary Fig. 40). Additionally, we found that the FeNP/NC catalyst was not stable during the nitrate reduction process $(-0.87\\mathrm{V}$ for $0.5\\mathrm{h}$ ); ${\\sim}20\\%$ of Fe contents were dissolved into the electrolyte solution. Such metal contamination from catalysts is problematic for many applications. As a sharp contrast, no Fe species were detected by ICP-OES in electrolytes after $0.5\\mathrm{-h}$ nitrate reduction on Fe SAC under $-0.5\\mathrm{~V~}$ and $-0.85\\mathrm{V}$ , suggesting the high stability of Fe single atoms. Also, Fe SAC exhibits much better performance than bulk Fe foil electrode (Supplementary Fig. 41). We also compared the Fe SAC with other TM SACs such as $\\scriptstyle{\\mathrm{Co}}$ and Ni prepared using the same synthesis method. While Co and Ni SACs showed only slightly lower ${\\mathrm{NH}}_{3}$ selectivity, their atomic site activities were around three (Co SAC) and four (Ni SAC) times lower than that of Fe (Fig. 3f, Supplementary 42 and Supplementary Note 3), suggesting the unique activity of Fe atom centers. However, Co and Ni SACs showed much higher activity than NC (Supplementary 43). The durability of Fe SAC in nitrate reduction was first evaluated by 20 consecutive electrolysis cycles in a H-cell reactor under the best $\\mathrm{NH}_{3}$ selectivity reaction condition (Fig. 3g; “Methods”). The $\\mathrm{NH}_{3}$ yield rate and FE in each cycle fluctuate but remain stable, suggesting the excellent stability of our catalyst. Importantly, the MAADF-STEM and AC MAADF-STEM images (Supplementary Fig. 44), EELS point spectra (Supplementary Fig. 45) and XAS tests (Supplementary Fig. 46) show that the structure of the Fe SAC is maintained well after the cycling test. Additionally, a 35-h continuous electrolysis was performed in a flow cell reactor under the similar operation current of $-35\\mathrm{mAcm}^{-2}$ (see “Methods”), showing negligible changes in working potential or $\\mathrm{NH}_{3}$ FE (Supplementary Fig. 47). \n\nDFT calculations. We performed DFT calculations to investigate the reaction mechanism and unravel the origin of Fe SAC’s high performance in nitrate reduction (Fig. 4; see “Methods”). Based on our characterization results, we used the $\\mathrm{Fe-N_{4}}$ motif with Fe atom as the active site in our model. We first investigated different possible reaction pathways for the formation of products such as $\\mathrm{NH}_{3}$ , NO, $\\mathrm{N}_{2}\\mathrm{O}$ , and $\\Nu_{2}$ (Supplementary Fig. 48). Supplementary Fig. 49 only displays pathways that result in $\\mathrm{NH}_{3}$ as the main product through nitrate reduction: \n\n$$\n\\mathrm{NO}_{3}^{-}+9\\mathrm{H}^{+}+8e^{-}\\rightarrow\\mathrm{NH}_{3}+3\\mathrm{H}_{2}\\mathrm{O}\\qquadE^{0}=0.88\\mathrm{V}\n$$ \n\nand eight electron transfers. The first step is protonation of ${\\mathrm{NO}}_{3}{}^{-}$ which is a solution-mediated proton transfer to form ${\\mathrm{HNO}}_{3}$ and does not require electron transfer. The intermediates and their energy profile across the reaction coordinate are displayed in the free energy diagram in Supplementary Fig. 50. Figure 4a (also the green arrows in Supplementary Fig. 49 and green line in Supplementary Fig. 50) indicate the minimum energy pathway (MEP) for nitrate reduction to ${\\mathrm{NH}}_{3}$ on Fe single atom site. We find that reduction of $\\mathrm{NO}_{2}^{-}$ to NO is downhill in free energy. This finding is in agreement with a previous computational report on Pd surface58. Nitrate reduction on polycrystalline and single crystals of transition metals have been studied in the past34,59–64. Liu et al.40 suggested that $\\mathrm{N^{*}}$ and ${{\\cal O}^{*}}$ binding energies can be used as descriptors for nitrate reduction performance on TMs. In addition, it has been shown that the main product of nitrate reduction reaction on all transition metals is nitrogen with low selectivity towards ammonia. The latter is due to the dominance of parasitic hydrogen evolution reaction. Moreover, $\\mathsf{N O}^{*}$ has been suggested as a key intermediate for nitrate reduction on metal surfaces such as $\\mathrm{\\Pt}$ where its reduction to $\\mathrm{HNO^{*}}$ or $\\mathrm{\\DeltaNOH^{*}}$ is a critical step for production of $\\mathrm{NH_{4}^{+}}$ . Our analysis on Fe SAC shows that ${\\mathrm{NO^{*}}}$ is a key intermediate for nitrate reduction reaction which is consistent with previous computational reports on Pt and $\\mathrm{Pd}^{58,65}$ . We would like to emphasize that while $\\mathrm{NO}_{2}^{-}$ is confirmed as an intermediate product in the experimental result, our DFT calculations show that the potential limiting steps are the $\\mathrm{NO^{*}}$ reduction to $\\mathrm{HNO^{*}}$ and ${\\bar{\\mathrm{HNO}}}^{*}$ reduction to $\\bar{\\mathbf{N}}^{*}$ in agreement with previous computational reports on transition metals such as $\\mathrm{\\Pt}$ and $\\mathrm{Pd}^{58,65}$ . Compared to the MEP at $U=0.0\\mathrm{V}$ vs. RHE (green line) in Fig. 4b, a limiting potential of $U=-0.30\\bar{\\mathrm{V}}$ (black line) is needed to make all steps downhill in free energy. Although not exactly the same, the calculated limiting potential $(-0.\\dot{3}0\\mathrm{V})$ is reasonably comparable with the observed experimental onset potential at ${\\sim}-0.\\bar{4}0\\mathrm{V}$ . The $0.10\\mathrm{V}$ difference can be attributed to the additional kinetic barriers that need to be overcome. We note here that due to the single atom nature of active sites in our catalyst, it is energetically unfavorable to make $_{\\mathrm{N-N}}$ coupling intermediates or products such as $\\mathrm{N}_{2}\\mathrm{O}$ or $\\Nu_{2}$ (Supplementary Fig. 50), which is why we did not observe any $\\mathrm{N}_{2}$ products from nitrate reduction on Fe SAC. In addition, our DFT calculations show that the MEP on Fe(110) is different from the one on Fe SAC and the potential limiting step is reduction of $\\mathrm{NH^{*}}$ to ${\\mathrm{NH}}_{2}{^{*}}$ (Supplementary Fig. 51). The DFT calculated limiting potential on $\\mathrm{Fe}(110)$ is $0.50\\mathrm{V}$ indicating that $\\mathrm{Fe}(110)$ exhibits lower catalytic activity than Fe SAC. We also calculated the free energy diagrams for $\\scriptstyle{\\mathrm{Co}}$ and Ni SACs (Supplementary Fig. 52). As it can be seen the potential limiting step is the reduction of $\\mathsf{N O}^{*}$ to $\\mathrm{HNO^{*}}$ on both Co and Ni SACs. The calculated limiting potentials for nitrate reduction on Co and Ni, and Fe SACs are 0.42, 0.39, and $0.3\\mathrm{V}$ , respectively, explaining why Fe SAC is more active than $C\\mathrm{{o}}$ and Ni SACs. Of note, the potential limiting steps on $\\scriptstyle{\\mathrm{Co}}$ and Ni SAC are highly close and within the range of DFT calculations error, indicating that they have very similar nitrate reduction activity, consistent with our experimental data (Fig. 3f). Combining experimental results and DFT calculations, the high $\\mathrm{NH}_{3}$ yield rate or activity of Fe SAC in this study can be attributed to the following two aspects. On the one hand, the Fe SAC has intrinsically high-efficiency active sites, i.e. $\\mathrm{Fe-N_{4}}$ centers, which exhibit much lower thermodynamic barriers, evidencing from smaller calculated limiting potentials than that of FeNP of FeNP/NC, $\\mathrm{Co-N_{4}}$ of Co SAC, and $\\mathrm{Ni-N_{4}}$ of Ni SAC. One the other hand, the optimized electrocatalytic conditions, including the concentration of ${\\mathrm{KNO}}_{3}$ , $\\mathsf{p H}$ of electrolyte, and applied potential, also play an important role in high $\\mathrm{NH}_{3}$ yield rate of Fe SAC. \n\n![](images/780fd9d709ae88d17ef12fe96ae78896d5f8d76ea2343f1684852a14ce045617.jpg) \nFig. 4 DFT calculations. a The minimum energy pathway that results in $N H_{3}$ as the main product. b Free energy diagram showing the minimum energy pathway at $U=0.0\\vee$ vs. RHE (green) and at the calculated limiting potential of $-0.30\\vee$ vs. RHE (black). \n\n# Discussion \n\nIn summary, we have demonstrated Fe SAC as an active and selective electrocatalyst to reduce nitrate to valuable ammonia. Our DFT simulations reveal the reaction pathways and potential limiting steps for nitrate reduction on Fe single atomic site. We believe this nitrate reduction to ammonia route could stimulate a different perspective towards how delocalized ammonia generation could be achieved. Future works should focus on further enhancing the catalytic selectivity, activity, and energy conversion efficiency in nitrate reduction to ammonia, testing the system in real wastewater system, and designing electrochemical reactors for more concentrated ammonia product generated from lowconcentration nitrate sources. \n\n# Methods \n\nSynthesis of Fe SAC. In a typical synthesis, $2.0\\ {\\mathrm{g}}\\ o$ -phenylenediamine, $0.58{\\mathrm{g}}$ ${\\mathrm{FeCl}}_{3}.$ and $2.0\\mathrm{~g~}\\mathrm{SiO}_{2}$ powder $\\mathrm{(10-20~nm}$ , Aldrich) were added into $240\\mathrm{mL}$ isopropyl alcohol and then vigorously stirred for ca. $12\\mathrm{h}$ . After drying the mixture by using a rotary evaporator, the obtained dried powder was subsequently carbonized under flowing Ar for $^{2\\mathrm{h}}$ at $800^{\\circ}\\mathrm{C}$ . Then, the product underwent alkaline $(2.0\\mathrm{M}$ $\\mathrm{\\DeltaNaOH_{\\mathrm{\\ell}}}$ and acidic $(2.0\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4},$ ) leaching successively to remove $\\mathrm{SiO}_{2}$ templates and unstable metallic species, respectively. Finally, the Fe SAC was obtained by second heat treatment at the same temperature (i.e. $800^{\\circ}\\mathrm{C})$ ) under flowing Ar for another $^{2\\mathrm{h}}$ . \n\nSynthesis of Co SAC and Ni SAC. The synthesis processes of Co SAC and Ni SAC are similar to that of Fe SAC, with the only difference being that $0.44\\mathrm{g}\\mathrm{CoCl}_{2}$ and $0.44\\mathrm{g}\\mathrm{NiCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ were used for synthesizing Co SAC and Ni SAC, respectively. \n\nSynthesis of NC catalyst. For comparison, the NC catalyst was also prepared. Typically, $2{\\mathrm{g}}o$ -phenylenediamine was firstly dissolved in $30\\mathrm{mL}1.0\\mathrm{M}$ HCl, and then $2.0\\mathrm{g}\\mathrm{SiO}_{2}$ powder was added into the above solution. After stirring for $0.5\\mathrm{h}$ , $24\\mathrm{mL}1.0\\mathrm{M}$ HCl solution containing $6.0\\:\\mathrm{g}$ ammonium peroxydisulfate, i.e., $(\\mathrm{NH}_{4})_{2}\\mathrm{S}_{2}\\mathrm{O}_{8}$ , was added dropwise with stirring. The polymerization process was carried out in an ice bath for ca. $24\\mathrm{h}$ . The mixture was dried by using a rotary evaporator, and then carbonized under flowing Ar for $^{2\\mathrm{h}}$ at $800^{\\circ}\\mathrm{C}$ . The $\\mathrm{SiO}_{2}$ templates were removed by $2.0\\mathrm{M}\\mathrm{NaOH}$ solution. Finally, the NC catalyst was obtained by second heat treatment at the same temperature $(800^{\\circ}\\mathrm{C})$ under flowing Ar for another $^{2\\mathrm{h}}$ . \n\nSynthesis of FeNP/NC catalyst. Firstly, $0.528\\mathrm{g}\\mathrm{FeSO_{4}{\\cdot}7H_{2}O}$ and $0.16\\mathrm{g}\\mathrm{NC}$ were added into $15\\mathrm{mL}$ deionized water and sonicated for $30\\mathrm{min}$ . Then, $10\\mathrm{mL}$ $\\mathrm{{NaBH_{4}}}$ (containing $0.284\\:\\mathrm{g}\\:\\mathrm{NaBH_{4}}.$ aqueous solution was added dropwise into the above solution with vigorous stirring. Then, the mixed solution was stirred for $^{3\\mathrm{h}}$ The sample was finally obtained by centrifugation collection, thoroughly washing with ethanol and deionized water and drying in an oven. The content of Fe in the FeNP/ NC catalyst was $22.2~\\mathrm{wt\\%}$ , which was determined by ICP-OES analysis. \n\nCharacterization. TEM observations and EDS elemental mapping were carried out on a Talos F200X transmission electron microscope at an accelerating voltage of $200\\mathrm{kV}$ equipped with an energy-dispersive detector. XPS was performed on an X-ray photoelectron spectrometer (ESCALab MKII) with an excitation source of Mg Kα radiation $(1253.6\\mathrm{eV})$ . XRD data were collected on a Rigaku D/Max Ultima II Powder X-ray diffractometer. $\\Nu_{2}$ adsorption–desorption isotherms were recorded on an ASAP 2020 accelerated surface area and porosimetry instrument \n\n(Micromeritics), equipped with automated surface area, at $77\\mathrm{K}$ using Barrett–Emmett–Teller calculations for the surface area. Raman scattering spectra were obtained by using a Renishaw System 2000 spectrometer using the $514.5\\mathrm{nm}$ line of an $\\mathrm{Ar^{+}}$ laser for excitation. Aberration-corrected MAADF-STEM images and EELS point spectra were captured in a Nion UltraSTEM U100 operated at 60 $\\mathrm{keV}$ and equipped with a Gatan Enfina electron energy loss spectrometer at Oak Ridge National Laboratory. Inductively coupled plasma-atomic emission spectrometry data were recorded on an Optima 7300 DV instrument. \n\nXAS measurement and data analysis. XAS spectra at the Fe, Co, and Ni K-edge were measured at the beamline 1W1B station of the Beijing Synchrotron Radiation Facility (BSRF), China. The Fe, Co, and Ni K-edge XANES data were recorded in a fluorescence mode. Fe, Co, and Ni foils and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ , $\\mathrm{Co}_{2}\\mathrm{O}_{3}$ , and NiO were used as the references. The storage ring was working at the energy of $2.5\\mathrm{GeV}$ with an average electron current of $250\\mathrm{mA}$ . The hard X-ray was monochromatized with Si (111) double crystals. The acquired EXAFS data were extracted and processed according to the standard procedures using the ATHENA module implemented in the IFEFFIT software packages. The $k^{3}$ -weighted EXAFS spectra were obtained by subtracting the post-edge background from the overall absorption and then normalizing with respect to the edge-jump step. Subsequently, $k^{3}.$ -weighted $\\chi(\\boldsymbol{k})$ data in the $k$ -space were Fourier transformed to real (R) space using a hanning windows to separate the EXAFS contributions from different coordination shells. To obtain the quantitative structural parameters around central atoms, least-squares curve parameter fitting was performed using the ARTEMIS module of IFEFFIT software packages. The X-ray absorption L-edge spectra of Fe, Co, and Ni were performed at the Catalysis and Surface Science Endstation at the BL11U beamline in the National Synchrotron Radiation Laboratory (NSRL) in Hefei, China. \n\nElectrocatalytic nitrate reduction. The electrochemical measurements were carried out in a customized H-type glass cell separated by Nafion 117 membrane (Fuel Cell Store) at room temperature. A BioLogic VMP3 workstation was used to record the electrochemical response. In a typical three-electrode system, a saturated calomel electrode (SCE, CH Instruments) and a platinum foil were used as the reference and counter electrode, respectively. All potentials in this study were measured against the SCE and converted to the RHE reference scale by $E(\\mathrm{V}$ vs. $\\mathrm{RHE})=E(\\bar{\\mathrm{V}}\\mathrm{vs.\\SCE})+0.0591\\times\\mathrm{pH}+0.241$ . The working electrode was prepared as follows: $10\\mathrm{mg}$ of catalyst powder, $2\\mathrm{ml}$ of isopropyl alcohol, and ${80\\upmu\\mathrm{l}}$ Nafion solution (Sigma Aldrich, $5\\mathrm{wt\\%}$ ) were mixed and sonicated for at least 2 h to form a homogeneous ink. Then, a certain volume of catalyst ink was drop-casted onto glassy carbon electrode with a loading of $0.4\\mathrm{mg}\\mathrm{cm}^{-2}$ . The area of glassy carbon electrode is $1\\times2\\mathrm{cm}^{2}$ and the practically immersing area in the electrolyte was $1\\times$ $\\textstyle1\\cos^{2}$ . For electrocatalytic ${\\mathrm{NO}}_{3}{}^{-}$ reduction, a solution with 0.1 M $\\mathrm{K}_{2}\\mathrm{SO}_{4}$ and $0.5{\\mathrm{M}}{}$ ${\\mathrm{KNO}}_{3}$ was used as the electrolyte unless otherwise specified and was evenly distributed to the cathode and anode compartment. The electrolyte volume in the two parts of H-cell was $25\\mathrm{mL}$ and was purged with high-purity Ar for $10\\mathrm{min}$ before the measurement. The LSV was performed at a rate of $\\bar{5}\\mathrm{mVs^{-1}}$ . The potentiostatic tests was conducted at constant potentials for $0.5\\mathrm{h}$ at a stirring rate of $500\\mathrm{r.p.m}$ . High-purity Ar was continuously fed into the cathodic compartment during the experiments. Solution resistance $(R_{s})$ was determined by potentiostatic electrochemical impedance spectroscopy (PEIS) at frequencies ranging from 0.1 to $200\\mathrm{kHz}$ . For consecutive recycling test, the potentiostatic tests were performed at $-0.66\\mathrm{V}$ for $0.5\\mathrm{h}$ at a stirring rate of $500~\\mathrm{r.p.m}$ . After electrolysis, the electrolyte was analyzed by UV–Vis spectrophotometry as mentioned below. Then, the potentiostatic tests were carried out at the same conditions using the fresh electrolyte for the next cycle. For electrochemical flow cell tests, typically $0.4\\mathrm{mg}\\mathrm{cm}^{-2}$ Fe SAC and $0.5\\mathrm{mg}\\dot{\\mathrm{cm}}^{-2}\\mathrm{Ir}\\mathrm{O}_{2}$ were air-brushed onto two Sigracet 39 BC GDL (Fuel Cell Store) electrodes as nitrate reduction cathode and oxygen evolution reaction anode, respectively. The two electrodes were placed on opposite sides of two $_{0.5\\mathrm{-}c\\mathrm{m}}$ -thick PTFE sheets with $0.5\\mathrm{cm}$ wide by $2.0\\mathrm{cm}$ long channels so that the catalyst layer interfaced with the flowing liquid electrolyte. A bipolar membrane (Fuel Cell Store) was used to separate the anode and cathode. The anode was circulated with $1.0\\mathbf{M}$ KOH electrolyte at $3\\mathrm{mL}\\mathrm{min}^{-1}$ flow rate while the flow rate of the $0.5\\mathrm{M}\\mathrm{KNO}_{3}/0.1\\mathrm{M}\\mathrm{K}_{2}\\mathrm{SO}_{4}$ in the middle flow channel is $1\\mathrm{mL}\\mathrm{min}^{-1}$ . A saturated calomel electrode was connected to cathode channel as the reference electrode. All of the measured potentials were manually $50\\%$ compensated. All of the current densities reported in this work are based on geometric surface area. \n\nCalculation of the FE and $M H_{3}$ yield rate. The FE of electrocatalytic ${\\mathrm{NO}}_{3}{}^{-}{-}{\\mathrm{NH}}_{3}$ conversion and ${\\mathrm{NO}}_{3}{\\mathrm{^-NO}}_{2}{^-$ conversion was calculated as follows: \n\n$$\n\\mathrm{FE}_{\\mathrm{NH}_{3}}=(8\\times F\\times C_{\\mathrm{NH}_{3}}\\times V)/(17\\times Q)\n$$ \n\n$$\n\\mathrm{FE}_{\\mathrm{NO}_{2^{-}}}=\\left(2\\times F\\times C_{\\mathrm{NO}_{2^{-}}}\\times V\\right)/(46\\times Q)\n$$ \n\nThe rate of ${\\mathrm{NH}}_{3}$ yield rate was calculated using the following equation: \n\n$$\nr_{\\mathrm{NH}_{3}}=(\\mathrm{C_{NH_{3}}}\\times V)/(t\\times m_{\\mathrm{cat}}.)\n$$ \n\nwhere $F$ is the Faraday constant $(96,485\\mathrm{C}\\mathrm{mol}^{-1},$ ), $C_{\\mathrm{NH3}}$ is the measured ${\\mathrm{NH}}_{3}$ concentration, $V$ is the volume of the cathodic electrolyte, $Q$ is the total charge passing the electrode, t is the reduction time, and $m_{\\mathrm{cat.}}$ is the loading mass of catalysts. \n\nDetermination of ammonia. The concentration of produced $\\mathrm{NH}_{3}$ was spectrophotometrically determined by the indophenol blue method with modification66. First, a certain amount of electrolyte was taken out from the electrolytic cell and diluted to the detection range. Then, $2\\mathrm{mL}$ of solution was removed from the diluted electrolyte. Subsequently, $2\\mathrm{mL}$ of a $1\\mathrm{M}\\mathrm{NaOH}$ solution containing $5\\mathrm{wt\\%}$ salicylic acid and $5\\mathrm{wt\\%}$ sodium citrate was added to the aforementioned solution, followed by the addition of $1\\mathrm{mL}$ of $0.05\\mathrm{M}\\mathrm{NaClO}$ and $0.2\\mathrm{mL}$ of $1.0~\\mathrm{wt\\%}$ ${\\mathrm{C}}_{5}{\\mathrm{FeN}}_{6}{\\mathrm{Na}}_{2}{\\mathrm{O}}$ (sodium nitroferricyanide) solution. After $^{2\\mathrm{h}}$ at room temperature, the absorption spectrum was measured by using a UV–vis spectrophotometer (UV2600). The formation of indophenol blue was determined using the absorbance at a wavelength of $655\\mathrm{nm}$ . The concentration–absorbance curve was made using a series of standard ammonium chloride solutions. \n\nDetermination of nitrite22. Firstly, $0.2\\:\\mathrm{g}$ of $N_{\\sun}$ -(1-naphthyl) ethylenediamine dihydrochloride, $_{4}\\mathrm{g}$ of $\\boldsymbol{p}$ -aminobenzenesulfonamide, and $10~\\mathrm{mL}$ of phosphoric acid $(\\rho\\dot{=}1.685\\mathrm{g}\\mathrm{mL}^{-1},$ ) were added into $50~\\mathrm{mL}$ of deionized water and mixed thoroughly as the color reagent. When testing the electrolyte from electrolytic cell, it should be diluted to the detection range. Then $5\\mathrm{mL}$ of the diluted electrolyte and $0.1\\mathrm{mL}$ of color reagent were mixed together. After $20\\mathrm{min}$ at room temperature, the absorption spectrum was measured by using a UV–vis spectrophotometer (UV2600), and the absorption intensity was recorded at a wavelength of $540\\mathrm{nm}$ . A series of standard potassium nitrite solutions were used to obtain the concentration–absorbance curve by the same processes. \n\nNMR determination of ammonia. The $\\mathrm{NH}_{3}$ concentration was also quantitatively determined by $^1\\mathrm{H}$ nuclear magnetic resonance (NMR, ${500}\\mathrm{MHz},\\$ ) with using DMSO- $\\cdot d_{6}$ as a solvent and maleic acid $\\mathrm{(C_{4}H_{4}O_{4})}$ as the internal standard. The calibration curve was made as follows. First, a series of ammonium chloride solutions with known concentration were prepared in 0.01 M HCl containing $0.5{\\bf M}$ $\\mathrm{KNO}_{3}$ as standards; second, $0.5\\mathrm{mL}$ of the standard solution was mixed with $0.1\\mathrm{mL}$ DMSO- $\\cdot d_{6}$ (with $0.04\\mathrm{wt\\%}$ $\\mathrm{C_{4}H_{4}O_{4};}$ 20 mg $\\mathrm{C_{4}H_{4}O_{4}}$ in $50\\mathrm{g}$ DMSO- $\\cdot d_{6})$ ; third, the mixture was tested by a 500 MHz SB Liquild Bruker Avance NMR spectrometer at room temperature; finally, the calibration curve was achieved using the peak area ratio between $\\mathrm{NH_{4}^{+}}$ and $\\mathrm{C_{4}H_{4}O_{4}}$ because the $\\mathrm{NH_{4}^{+}}$ concentration and the area ratio are positively correlated. For testing the produced $\\mathrm{NH_{4}^{+}}$ from $\\mathrm{NO}_{3}{}^{-}$ reduction, the pH of obtained electrolyte must be adjusted to 2.0 before the test. Then, the processes of testing produced $\\mathrm{NH_{4}^{+}}$ are the same to that for making the calibration curve. The amount of produced $\\mathrm{NH_{4}^{+}}$ can be calculated from the peak area using the calibration curve. \n\n$\\pmb{15}_{\\pmb{\\mathsf{M}}}$ isotope-labeling experiment. An isotope-labeling experiment using $0.10\\mathrm{M}$ $\\mathrm{K}_{2}\\mathrm{SO}_{4}/0.50\\mathrm{M}\\mathrm{K}^{15}\\mathrm{NO}_{3}$ ( $98~\\mathrm{atom}\\%~^{15}\\mathrm{N},$ mixed solution as the electrolyte was carried out to clarify the source of $\\mathrm{NH}_{3}$ . After $^{15}\\mathrm{NO}_{3}{}^{-}$ electroreduction for 0.5 to $^{2\\mathrm{h}}$ at $-0.66\\mathrm{V}$ (vs. RHE), the obtained $^{15}\\mathrm{N}\\mathrm{H_{4}}^{+}$ was tested by $^1\\mathrm{H}$ nuclear magnetic resonance (NMR, $500\\mathrm{MHz},\\$ . The NMR test method of $^{15}\\mathrm{N}\\dot{\\mathrm{H}_{4}}^{+}$ is the same to that of $^{14}\\mathrm{N}\\mathrm{H_{4}}^{+}$ . \n\nComputational details. Atomic simulation environment (ASE) was used to handle the simulation67. All electronic structure relaxations were performed using QUANTUM ESPRESSO code68. The electronic wavefunctions were expanded in plane waves with a cutoff energy of $500\\mathrm{eV}$ while 5000 grids were used for electronic density representation. To approximate the core electrons ultrasoft pseudopotentials were adapted69. Perdew–Burke–Ernzerhof (PBE) exchangecorrelation functional was used to calculate the adsorption energies70. A one-layer two-dimensional graphene structure was used with a $5\\times5$ super cell lateral size. The periodic images were separated by adding a vacuum of $18{\\bar{\\mathrm{A}}}$ . Additional layers of graphene have been shown to have negligible effect on the adsorption energies of the intermediates71. A $(4\\times4\\times1)$ Monkhorst–Pack $k$ -point was used to sample the Brillouin zone. We apply computational hydrogen electrode method to calculate the adsorption free energies, which assumes the chemical potential of an electron–proton pair is equal to that of $\\nu_{2}\\ \\mathrm{H}_{2}$ in the gas phase. The free energies of adsorption are then calculated as $\\Delta G=\\Delta E_{\\mathrm{DFT}}+\\Delta(\\mathrm{ZPE-TS}),$ where $\\Delta E_{\\mathrm{DFT}}$ , ZPE, $T,$ and S are adsorption enthalpy, zero-point energy, temperature, and entropy, respectively. The limiting potential is calculated by taking the negative of the maximum free energy difference between each two successive steps in the free energy diagram. \n\nAdsorption free energies are calculated using ${\\mathrm{HNO}}_{3}$ as a reference suggested by Calle-Vallejo et al.72. We applied $1.12\\mathrm{eV}$ correction to compensate for the DFT error of calculated formation energy of ${\\mathrm{HNO}}_{3}$ (ref. 72). We investigated the effect of solvation on the adsorption energies of the critical step $\\mathrm{NO^{*}}$ reduction to $\\mathrm{HNO^{*}}$ using an optimized explicit solvation model (Supplementary Fig. 53). This analysis showed a negligible change in the calculated limiting potential due to the solvent interaction. \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request. \n\nReceived: 18 September 2020; Accepted: 22 March 2021; Published online: 17 May 2021 \n\n# References \n\n1. Rosca, V., Duca, M., de Groot, M. T. & Koper, M. T. M. Nitrogen cycle electrocatalysis. Chem. Rev. 109, 2209–2244 (2009). \n2. Ashida, Y., Arashiba, K., Nakajima, K. & Nishibayashi, Y. Molybdenumcatalysed ammonia production with samarium diiodide and alcohols or water. Nature 568, 536–540 (2019). \n3. Service, R. F. New recipe produces ammonia from air, water, and sunlight. Science 345, 610–610 (2014). \n4. Foster, S. L. et al. Catalysts for nitrogen reduction to ammonia. Nat. Catal. 1, 490–500 (2018). \n5. Tang, C. & Qiao, S.-Z. How to explore ambient electrocatalytic nitrogen reduction reliably and insightfully. Chem. Soc. Rev. 48, 3166–3180 (2019). \n6. Kitano, M. et al. Ammonia synthesis using a stable electride as an electron donor and reversible hydrogen store. Nat. Chem. 4, 934–940 (2012). \n7. Suryanto, B. H. R. et al. Challenges and prospects in the catalysis of electroreduction of nitrogen to ammonia. Nat. Catal. 2, 290–296 (2019). \n8. Soloveichik, G. Electrochemical synthesis of ammonia as a potential alternative to the Haber–Bosch process. Nat. Catal. 2, 377–380 (2019). \n9. Guo, C., Ran, J., Vasileff, A. & Qiao, S.-Z. Rational design of electrocatalysts and photo(electro)catalysts for nitrogen reduction to ammonia $\\left(\\mathrm{NH}_{3}\\right)$ ) under ambient conditions. Energy Environ. Sci. 11, 45–56 (2018). \n10. Wan, Y., Xu, J. & Lv, R. Heterogeneous electrocatalysts design for nitrogen reduction reaction under ambient conditions. Mater. Today 27, 69–90 (2019). \n11. Honkala, K. et al. Ammonia synthesis from first-principles calculations. Science 307, 555–558 (2005). \n12. Hawtof, R. et al. Catalyst-free, highly selective synthesis of ammonia from nitrogen and water by a plasma electrolytic system. Sci. Adv. 5, eaat5778 (2019). \n13. Cui, X., Tang, C. & Zhang, Q. A review of electrocatalytic reduction of dinitrogen to ammonia under ambient conditions. Adv. Energy Mater. 8, 1800369 (2018). \n14. Wang, J. et al. Ambient ammonia synthesis via palladium-catalyzed electrohydrogenation of dinitrogen at low overpotential. Nat. Commun. 9, 1795 (2018). \n15. Chen, P. et al. Interfacial engineering of cobalt sulfide/graphene hybrids for highly efficient ammonia electrosynthesis. Proc. Natl Acad. Sci. USA 116, 6635–6640 (2019). \n16. Song, Y. et al. A physical catalyst for the electrolysis of nitrogen to ammonia. Sci. Adv. 4, e1700336 (2018). \n17. Chen, G.-F. et al. Ammonia electrosynthesis with high selectivity under ambient conditions via a $\\mathrm{Li^{+}}$ incorporation strategy. J. Am. Chem. Soc. 139, 9771–9774 (2017). \n18. Lv, C. et al. An amorphous noble-metal-free electrocatalyst that enables nitrogen fixation under ambient conditions. Angew. Chem. Int. Ed. 57, 6073–6076 (2018). \n19. Li, S.-J. et al. Amorphizing of Au nanoparticles by $\\mathrm{CeO_{x}}$ –RGO hybrid support towards highly efficient electrocatalyst for $\\Nu_{2}$ reduction under ambient conditions. Adv. Mater. 29, 1700001 (2017). \n20. Geng, Z. et al. Achieving a record-high yield rate of $120.9~{\\upmu\\mathrm{g}}_{\\mathrm{NH}3}~\\mathrm{mg}_{\\mathrm{cat.}}{}^{-1}~\\mathrm{h}^{-1}$ for $\\Nu_{2}$ electrochemical reduction over Ru single-atom catalysts. Adv. Mater. 30, 1803498 (2018). \n21. Andersen, S. Z. et al. A rigorous electrochemical ammonia synthesis protocol with quantitative isotope measurements. Nature 570, 504–508 (2019). \n22. Wang, Y., Yu, Y., Jia, R., Zhang, C. & Zhang, B. Electrochemical synthesis of nitric acid from air and ammonia through waste utilization. Natl Sci. Rev. 6, 730–738 (2019). \n23. Jia, R. et al. Boosting selective nitrate electroreduction to ammonium by constructing oxygen vacancies in $\\mathrm{TiO}_{2}$ . ACS Catal. 10, 3533–3540 (2020). \n24. Wang, Y. et al. Enhanced nitrate-to-ammonia activity on copper–nickel alloys via tuning of intermediate adsorption. J. Am. Chem. Soc. 142, 5702–5708 (2020). \n25. Taniguchi, I., Nakashima, N., Matsushita, K. & Yasukouchi, K. Electrocatalytic reduction of nitrate and nitrite to hydroxylamine and ammonia using metal cyclams. J. Electroanal. Chem. 224, 199–209 (1987). \n26. Chebotareva, N. & Nyokong, T. Metallophthalocyanine catalysed electroreduction of nitrate and nitrite ions in alkaline media. J. Appl. Electrochem. 27, 975–981 (1997). 27. Xu, exible, active macrocycle enables the electrocatalytic reduction of nitrate to ammonia by a cobalt complex. Chem. Sci. 9, 4950–4958 (2018). \n28. Martínez, J., Ortiz, A. & Ortiz, I. State-of-the-art and perspectives of the catalytic and electrocatalytic reduction of aqueous nitrates. Appl. Catal. B 207, 42–59 (2017). \n29. Chen, M. et al. Achieving high-performance nitrate electrocatalysis with PdCu nanoparticles confined in nitrogen-doped carbon coralline. Nanoscale 10, 19023–19030 (2018). \n30. Reyter, D., Bélanger, D. & Roué, L. Study of the electroreduction of nitrate on copper in alkaline solution. Electrochim. Acta 53, 5977–5984 (2008). \n31. Gao, J. et al. Non-precious $\\mathrm{Co_{3}O_{4}\\mathrm{-TiO_{2}/T i}}$ cathode based electrocatalytic nitrate reduction: preparation, performance and mechanism. Appl. Catal. B 254, 391–402 (2019). \n32. Garcia-Segura, S., Lanzarini-Lopes, M., Hristovski, K. & Westerhoff, P. Electrocatalytic reduction of nitrate: fundamentals to full-scale water treatment applications. Appl. Catal. B 236, 546–568 (2018). \n33. Katsounaros, I., Dortsiou, M. & Kyriacou, G. Electrochemical reduction of nitrate and nitrite in simulated liquid nuclear wastes. J. Hazard. Mater. 171, 323–327 (2009). \n34. Guo, S. et al. Insights into nitrate reduction over indium-decorated palladium nanoparticle catalysts. ACS Catal. 8, 503–515 (2018). \n35. Su, L. et al. Tailoring the assembly of iron nanoparticles in carbon microspheres toward high-performance electrocatalytic denitrification. Nano Lett. 19, 5423–5430 (2019). \n36. Hasnat, M. A., Karim, M. R. & Machida, M. Electrocatalytic ammonia synthesis: role of cathode materials and reactor configuration. Catal. Commun. 10, 1975–1979 (2009). \n37. Katsounaros, I., Ipsakis, D., Polatides, C. & Kyriacou, G. Efficient electrochemical reduction of nitrate to nitrogen on tin cathode at very high cathodic potentials. Electrochim. Acta 52, 1329–1338 (2006). \n38. Dortsiou, M. & Kyriacou, G. Electrochemical reduction of nitrate on bismuth cathodes. J. Electroanal. Chem. 630, 69–74 (2009). \n39. Chen, G.-F. et al. Electrochemical reduction of nitrate to ammonia via direct eight-electron transfer using a copper–molecular solid catalyst. Nat. Energy 5, 605–613 (2020). \n40. Liu, J.-X., Richards, D., Singh, N. & Goldsmith, B. R. Activity and selectivity trends in electrocatalytic nitrate reduction on transition metals. ACS Catal. 9, 7052–7064 (2019). \n41. Yang, X.-F. et al. Single-atom catalysts: a new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748 (2013). \n42. Wang, A., Li, J. & Zhang, T. Heterogeneous single-atom catalysis. Nat. Rev. Chem. 2, 65–81 (2018). \n43. Li, Z. et al. Well-defined materials for heterogeneous catalysis: from nanoparticles to isolated single-atom sites. Chem. Rev. 120, 623–682 (2020). \n44. Liu, L. & Corma, A. Metal catalysts for heterogeneous catalysis: from single atoms to nanoclusters and nanoparticles. Chem. Rev. 118, 4981–5079 (2018). \n45. Liang, H.-W. et al. Molecular metal– $\\mathbf{\\cdotN_{x}}$ centres in porous carbon for electrocatalytic hydrogen evolution. Nat. Commun. 6, 7992 (2015). \n46. Wu, Z.-Y. et al. Transition metal–assisted carbonization of small organic molecules toward functional carbon materials. Sci. Adv. 4, eaat0788 (2018). \n47. Li, J. et al. Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells. Nat. Catal. 1, 935–945 (2018). \n48. Chung, H. T. et al. Direct atomic-level insight into the active sites of a highperformance PGM-free ORR catalyst. Science 357, 479–484 (2017). 49. Chen, P. et al. Atomically dispersed iron–nitrogen species as electrocatalysts for bifunctional oxygen evolution and reduction reactions. Angew. Chem. Int. Ed. 56, 610–614 (2017). \n50. Jiao, L. et al. From metal–organic frameworks to single-atom Fe implanted Ndoped porous carbons: efficient oxygen reduction in both alkaline and acidic media. Angew. Chem. Int. Ed. 57, 8525–8529 (2018). \n51. Zhang, M. et al. Metal (hydr)oxides@polymer core-shell strategy to metal single-atom materials. J. Am. Chem. Soc. 139, 10976–10979 (2017). \n52. Su, J. F., Ruzybayev, I., Shah, I. & Huang, C. P. The electrochemical reduction of nitrate over micro-architectured metal electrodes with stainless steel scaffold. Appl. Catal. B 180, 199–209 (2016). \n53. Yin, D. et al. In situ growth of copper/reduced graphene oxide on graphite surfaces for the electrocatalytic reduction of nitrate. Electrochim. Acta 324, 134846 (2019). \n54. Wang, Y., Zhou, W., Jia, R., Yu, Y. & Zhang, B. Unveiling the activity origin of a copper-based electrocatalyst for selective nitrate reduction to ammonia. Angew. Chem. Int. Ed. 59, 5350–5354 (2020). \n55. Li, J. et al. Efficient ammonia electrosynthesis from nitrate on strained ruthenium nanoclusters. J. Am. Chem. Soc. 142, 7036–7046 (2020). \n56. Xia, C. et al. Continuous production of pure liquid fuel solutions via electrocatalytic $\\mathrm{CO}_{2}$ reduction using solid-electrolyte devices. Nat. Energy 4, 776–785 (2019). \n57. Xia, C., Xia, Y., Zhu, P., Fan, L. & Wang, H. Direct electrosynthesis of pure aqueous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solutions up to $20\\%$ by weight using a solid electrolyte. Science 366, 226–231 (2019). \n58. Shin, H., Jung, S., Bae, S., Lee, W. & Kim, H. Nitrite reduction mechanism on a Pd surface. Environ. Sci. Technol. 48, 12768–12774 (2014). \n59. Katsounaros, I., Figueiredo, M. C., Chen, X., Calle-Vallejo, F. & Koper, M. T. M. Structure- and coverage-sensitive mechanism of no reduction on platinum electrodes. ACS Catal. 7, 4660–4667 (2017). \n60. Clayborne, A., Chun, H.-J., Rankin, R. B. & Greeley, J. Elucidation of pathways for NO electroreduction on Pt(111) from first principles. Angew. Chem. Int. Ed. 54, 8255–8258 (2015). \n61. Bae, S.-E., Stewart, K. L. & Gewirth, A. A. Nitrate adsorption and reduction on $\\mathrm{{Cu}}(100)$ in acidic solution. J. Am. Chem. Soc. 129, 10171–10180 (2007). \n62. Dima, G. E., de Vooys, A. C. A. & Koper, M. T. M. Electrocatalytic reduction of nitrate at low concentration on coinage and transition-metal electrodes in acid solutions. J. Electroanal. Chem. 554–555, 15–23 (2003). \n63. Zeng, Y., Priest, C., Wang, G. & Wu, G. Restoring the nitrogen cycle by electrochemical reduction of nitrate: progress and prospects. Small Methods 4, 2000672 (2020). \n64. Hou, Y. et al. Atomically dispersed nickel–nitrogen–sulfur species anchored on porous carbon nanosheets for efficient water oxidation. Nat. Commun. 10, 1392 (2019). \n65. Chun, H.-J., Apaja, V., Clayborne, A., Honkala, K. & Greeley, J. Atomistic insights into nitrogen-cycle electrochemistry: a combined DFT and kinetic Monte Carlo analysis of NO electrochemical reduction on $\\mathrm{Pt}(100)$ . ACS Catal. 7, 3869–3882 (2017). \n66. Zhu, D., Zhang, L., Ruther, R. E. & Hamers, R. J. Photo-illuminated diamond as a solid-state source of solvated electrons in water for nitrogen reduction. Nat. Mater. 12, 836–841 (2013). \n67. Bahn, S. R. & Jacobsen, K. W. An object-oriented scripting interface to a legacy electronic structure code. Comput. Sci. Eng. 4, 56–66 (2002). \n68. Giannozzi, P. et al. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials. J. Phys. Condens. Matter 21, 395502 (2009). \n69. Ahmed Adllan, A. & Dal Corso, A. Ultrasoft pseudopotentials and projector augmented-wave data sets: application to diatomic molecules. J. Phys. Condens. Matter 23, 425501 (2011). \n70. Ernzerhof, M. & Scuseria, G. E. Assessment of the Perdew–Burke–Ernzerhof exchange-correlation functional. J. Chem. Phys. 110, 5029–5036 (1999). \n71. To, J. W. F. et al. High-performance oxygen reduction and evolution carbon catalysis: from mechanistic studies to device integration. Nano Res. 10, 1163–1177 (2017). \n72. Calle-Vallejo, F., Huang, M., Henry, J. B., Koper, M. T. M. & Bandarenka, A. S. Theoretical design and experimental implementation of Ag/Au electrodes for the electrochemical reduction of nitrate. Phys. Chem. Chem. Phys. 15, 3196–3202 (2013). \n\n# Acknowledgements \n\nThis work was supported by Rice University, the National Science Foundation Nanosystems Engineering Research Center for Nanotechnology Enabled Water Treatment (NEWT EEC 1449500), and the Welch Foundation Research Grant (C-2051-20200401). \n\nH.W. is a CIFAR Azrieli Global Scholar in the Bio-inspired Solar Energy Program. S.S. acknowledges the support from the University of Calgary’s Canada First Research Excellence Fund Program, the Global Research Initiative in Sustainable Low Carbon Unconventional Resources. Aberration-corrected STEM-EELS was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. The authors acknowledge Prof. H.W. Liang and M.X. Chen for XAS measurement and data analysis. \n\n# Author contributions \n\nZ.-Y.W. and H.W. conceptualized the project. H.W. and S.S. supervised the project. Z.-Y.W. developed and performed catalyst synthesis. Z.-Y.W., Q.H., F.-Y.C., and C.X. conducted the catalytic tests of catalysts and the related data processing. Z.-Y.W. performed materials characterization with the help of D.A.C., Q.X., M.S., J.Y.K., Y.X., K.H., and Y.H. $^1\\mathrm{H}$ NMR experiments and analysis was carried out by P.Z., Z.-Y.W., and Q.Z.H. S.S., M.K., X.Y., and I.G. performed the DFT simulation. Z.-Y.W., H.W., and S.S. wrote the manuscript. M.S.W. and Q.L. helped the revision of the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-23115-x. \n\nCorrespondence and requests for materials should be addressed to S.S. or H.W. \n\nPeer review information Nature Communications thanks Gang Fu and the other anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1126_sciadv.abb6772", + "DOI": "10.1126/sciadv.abb6772", + "DOI Link": "http://dx.doi.org/10.1126/sciadv.abb6772", + "Relative Dir Path": "mds/10.1126_sciadv.abb6772", + "Article Title": "Full-color fluorescent carbon quantum dots", + "Authors": "Wang, L; Li, WT; Yin, LQ; Liu, YJ; Guo, HZ; Lai, JW; Han, Y; Li, G; Li, M; Zhang, JH; Vajtai, R; Ajayan, PM; Wu, MH", + "Source Title": "SCIENCE ADVANCES", + "Abstract": "Quantum dots have innate advantages as the key component of optoelectronic devices. For white light-emitting diodes (WLEDs), the modulation of the spectrum and color of the device often involves various quantum dots of different emission wavelengths. Here, we fabricate a series of carbon quantum dots (CQDs) through a scalable acid reagent engineering strategy. The growing electron-withdrawing groups on the surface of CQDs that originated from acid reagents boost their photoluminescence wavelength red shift and raise their particle sizes, elucidating the quantum size effect. These CQDs emit bright and remarkably stable full-color fluorescence ranging from blue to red light and even white light. Full-color emissive polymer films and all types of high-color rendering index WLEDs are synthesized by mixing multiple kinds of CQDs in appropriate ratios. The universal electron-donating/withdrawing group engineering approach for synthesizing tunable emissive CQDs will facilitate the progress of carbon-based luminescent materials for manufacturing forward-looking films and devices.", + "Times Cited, WoS Core": 477, + "Times Cited, All Databases": 498, + "Publication Year": 2020, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000579157800027", + "Markdown": "# O P T I C S \n\n# Full-color fluorescent carbon quantum dots \n\nLiang Wang1,2\\*†, Weitao Li1\\*, Luqiao Yin3, Yijian Liu1, Huazhang Guo1, Jiawei Lai2, Yu Han1, Gao Li1, Ming Li1, Jianhua Zhang3, Robert Vajtai2, Pulickel M. Ajayan2, Minghong Wu1† \n\nQuantum dots have innate advantages as the key component of optoelectronic devices. For white light–emitting diodes (WLEDs), the modulation of the spectrum and color of the device often involves various quantum dots of different emission wavelengths. Here, we fabricate a series of carbon quantum dots (CQDs) through a scalable acid reagent engineering strategy. The growing electron-withdrawing groups on the surface of CQDs that originated from acid reagents boost their photoluminescence wavelength red shift and raise their particle sizes, elucidating the quantum size effect. These CQDs emit bright and remarkably stable full-color fluorescence ranging from blue to red light and even white light. Full-color emissive polymer films and all types of high–color rendering index WLEDs are synthesized by mixing multiple kinds of CQDs in appropriate ratios. The universal electron-­ donating/withdrawing group engineering approach for synthesizing tunable emissive CQDs will facilitate the progress of carbon-based luminescent materials for manufacturing forward-looking films and devices. \n\nCopyright $\\circledcirc$ 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). \n\n# INTRODUCTION \n\nWhite light–emitting diodes (WLEDs) hold great promise for the next generation of ideal lighting devices in terms of their high energy efficiency, long lifetime, fast response speed, and high reliability (1). Nowadays, a combination of a blue or ultraviolet (UV) LED chip and multicolor phosphors are commonly used to generate white light (2). Much remarkable effort has been devoted to optimizing the properties of phosphors for their potential applications in WLEDs. A considerable number of fluorescent materials have been researched for their applications in WLEDs, including proteins (3), semiconductor quantum dots (QDs) (4–6), perovskite QDs (7, 8), rare earth– based nanoparticles (9–11), polymers (12), metal complexes (13), and dyes (14). However, challenging synthesis, stability, and cytotoxicity of many materials still hinder their potential applications (4–8). \n\nNanoscale carbon QDs (CQDs) could fill this gap because of their biocompatibility, stability, and cost-effectiveness if these CQDs are made to fluoresce over a range of practically useful wavelengths (15–19). The inherent challenge in CQDs is the tunability of emission, as most of the CQDs are known to produce only blue, green, and yellow emissions (20–22). Supposing that the CQDs are capable of being prepared in a scalable fashion and their fluorescence is extended across the entire visible spectrum, the CQDs can work as excellent building blocks for all types of WLEDs. To this end, it is of paramount importance that optimum CQDs could be designed by choosing the right precursors and processing techniques. A few attempts have been achieved by using suitable precursors and complicated column chromatography postprocessing techniques in the past 5 years (17, 18, 23, 24). Although the improved optical properties of these CQDs offered advantages in device performance, we note that no study has yet been reported that uses previously unidentified synthesis techniques. In pursuit of high–color rendering index $\\mathrm{(CRI>80)}$ ) WLEDs, especially the warm WLEDs, the robust CQDs with tunable photoluminescence (PL) emission will inevitably require a feasible approach involving the practical synthesis techniques. \n\nHere, we report a novel one-step acid reagent engineering strategy to acquire highly luminescent CQDs, having remarkably tunable and stable fluorescence emission from blue to red and even white light by using $o$ -phenylenediamine (oPD) as the precursor. The relative PL quantum yields (QYs) of these CQDs reached $72\\%$ . Our detailed studies prove that by controlling the acid reagents in reactions, we can readily modulate the particle size and fluorescence wavelength of CQDs over a wide range. To gain fundamental insights into the engineering mechanism of acid reagents, we analyzed the trend of electron-withdrawing and electron-donating groups on the surface of CQDs, of which the PL wavelengths and particle sizes of the CQDs are positively related to their amount of electron-withdrawing groups. Furthermore, the quantum size effect is elucidated. This work is the typical demonstration of the preparation of high-performance multicolor emissive CQDs through an electron-donating/withdrawing group engineering pathway without any complicated postprocessing. Full-color emissive polymethyl methacrylate (PMMA) films are also achieved by adding one or more types of these CQDs to the colloid mixtures. By adding CQDs into silica gel, we fabricate all kinds of high-CRI WLEDs, including warm, standard, and cool WLEDs, paving a way to practically applicable WLEDs. Our finding establishes a versatile technique for desirable optical properties of carbon and related zero-dimensional materials by electron-donating/withdrawing group engineering. \n\n# RESULTS Synthetic strategy of full-color fluorescent CQDs \n\nWe demonstrated a one-step acid reagent engineering method for the synthesis of highly efficient full-color fluorescent CQDs by heating a mixture of oPD and selected acid reagents in ethanol solvent (Fig. 1A). Different acid reagents were chosen, and their fusion capability was evaluated in the preparation of CQDs under the same condition. The fluorescent properties of synthesized products were observed under UV light. Most of the as-prepared solutions only emitted blue and dim green fluorescence (fig. S1A) in that many acids are strong acids, which will easily cause excessive carbonization and defects during the reaction, resulting in weak optical properties of \n\n![](images/0c59656f3f0b6963a72bcb5ec26acb8df9cbb741ed2de1853a52181b2bd74c4d.jpg) \nFig. 1. Synthetic strategy of full-color fluorescent CQDs. (A) An acid reagent engineering strategy for the synthesis of full-color fluorescent CQDs using oPD as the precursor. (B) Fluorescence photographs of CQDs under UV light (excited at $365\\mathsf{n m}$ ). \n\nCQDs. Other than these acids for fabricating CQDs, a few mild acids were used to modulate the optical properties of CQDs by means of adjusting the mass ratio between oPD and specific acid reagents [4-aminobenzenesulfonic acid (4-ABSA), folic acid (FA), boric acid (BA), acetic acid (AA), terephthalic acid (TPA), and tartaric acid (TA)] in solvothermal reactions (Fig. 1A). To eliminate the selffluorescence impact of oPD or chosen acid to CQDs in the fusion step, subjecting pure oPD or acid reagents to the solvothermal reaction in ethanol just outputted blue-green fluorescence products (fig. S1B). When oPD met with an appropriate acid reagent, the synthesized CQDs emitted full-color fluorescence ranging from blue to red and even white light under UV light irradiation, manifesting tunable PL emission (Fig. 1B). The oPD constructs the structural skeleton of CQDs during the solvothermal treatment. In addition, the suitable acid is adopted to introduce different functional groups with various ratios into the structure of CQDs and to passivate the surface of CQDs, controlling particle sizes, reducing defects, and enhancing optical performance. When using different ideal acid reagents, six typical CQDs with blue, cyan, yellow-green, orange, red, and white fluorescence were created and labeled as b-CQDs, c-CQDs, yg-CQDs, o-CQDs, r-CQDs, and w-CQDs, respectively. \n\n# Structural and morphological characterizations \n\nThe compositions of the five typical CQDs (except w-CQDs) were analyzed by Fourier transform infrared (FTIR) spectra and x-ray photo­ electron spectroscopy (XPS). All these CQDs contain the same four stretching vibration bands in their FTIR spectra, such as OH/NH at 3300 to $3470~\\mathrm{cm}^{-1}$ , carboxylic $\\scriptstyle{\\mathrm{C=O}}$ at $\\mathrm{{1700~cm^{-1}}}$ , $\\mathsf{s p}^{2}\\mathsf{C}{=}\\mathsf{C}$ at $1462~\\mathrm{cm}^{-1}$ , and $\\mathrm{C-OH}$ at $122\\dot{4}\\mathrm{cm}^{-1}$ , evidencing that the five samples are always cofunctionalized by strong electron-donating groups (e.g., OH and $\\mathrm{NH}_{2}$ ) and weak electron-withdrawing COOH groups (fig. S2A), originating from ethanol/oPD and acid reagents, respectively. The stretching vibration band $\\mathrm{SO}_{3}$ at $1025~\\mathrm{{cm}^{-1}}$ is observed in the spectrum of b-CQDs, similar to surface-related B─O at $1344\\mathrm{{cm}^{-1}}$ and $_\\mathrm{B-C}$ at $1032\\mathrm{cm}^{-1}$ in the spectrum of yg-CQDs, confirming that the b-CQDs and yg-CQDs are additionally functionalized by medium electron-withdrawing $\\mathrm{SO}_{3}\\mathrm{H}$ and $_\\mathrm{B-O}$ related groups (25), respectively. Nuclear magnetic resonance (NMR) spectroscopy $^{\\cdot13}\\mathrm{C}$ and $\\mathrm{^{1}H}^{\\cdot}$ ) was used to distinguish functional groups on the surface of CQDs (fig. S2, B and C). In their $^{13}\\mathrm{C}$ NMR spectra, the observed signals in the range of 100 to 150 parts per million (ppm) are assigned to $\\mathsf{s p}^{2}\\mathsf{C}(\\bar{\\imath5},26)$ . The active $\\mathrm{~H~}$ signals from the $\\mathrm{NH}_{2}$ groups and aromatic hydrogen are detected in the range of 6 to 8 ppm in the $^1\\mathrm{H}$ NMR spectra, which further demonstrates the presence of electron-donating $\\mathrm{NH}_{2}$ groups on the surface of these CQDs. XPS findings were also carried out to investigate the surfaces of these samples (fig. S2, D to I) and to reconfirm the FTIR analysis results. All of the full spectra of five chosen samples show three typical peaks: C1s $(285\\mathrm{eV})$ , N1s $(399\\mathrm{eV})$ , and O1s $(532\\mathrm{eV})$ (27). Besides, the spectra of b-CQDs and yg-CQDs show the S2p and B1s peaks, respectively, further corroborating the conclusion of the FTIR data. All of the C1s band of CQDs can be deconvoluted into three peaks, relevant to $\\scriptstyle\\mathrm{C=C/C-C}$ $284.5\\ \\mathrm{eV},$ ), C─N/C─O $(286.1\\mathrm{eV})$ , and carboxylic O─ $\\scriptstyle\\cdot\\mathrm{C=O}$ $288.5\\mathrm{eV},$ ). Apart from that of yg-CQDs, there was a new peak (C─B, 283.4eV) (25). The whole N1s band displays the $\\mathrm{NH}_{2}$ groups $(399.2\\mathrm{eV})$ . All the O1s band of CQDs can be deconvoluted into two peaks of $\\scriptstyle\\mathrm{C=O}$ $(531.6~\\mathrm{eV})$ and $\\scriptstyle{\\mathrm{C-O}}$ $(533.2\\ \\mathrm{eV})$ , respectively (17). The S2p band of b-CQDs is decomposed into two peaks at 163.5 and $167.4\\mathrm{eV}$ , representing $\\mathrm{SO}_{3}/2\\mathrm{P}_{3/2}$ and $\\mathrm{SO}_{3}/2\\mathrm{P}_{1/2}$ , respectively (28). The B1s band of yg-CQDs is divided into two peaks, corresponding to B─C ( $191.9\\mathrm{eV})$ and B─O $\\cdot193.4\\mathrm{eV})$ . The atomic ratio of the electron-donating $\\mathrm{NH}_{2}$ groups and carbon element decreases from 0.26 to 0.12 as the electron-donating OH group content declines from b-CQDs to r-CQDs (table S1), which has a similar decreasing tendency of the atomic ratio of $\\mathrm{NH}_{2}$ and carbon in the elemental analysis (table S1). In contrast, the amount of electronwithdrawing COOH groups notable increase from $45.51\\%$ (b-CQDs) to $71.64\\%$ (r-CQDs), reflecting that the increasing electronwithdrawing groups, derived from acid reagents and grafted on the surface of these CQDs, can boost the PL wavelength red shift of the CQDs. Furthermore, increasing the ratio of the same acid reagent in the fusion process, such as 4-ABSA, FA, and TPA (Fig. 1B), also reveals the PL wavelength red shift phenomenon of the CQDs, illustrating the spectral engineering role of acid reagents in the solvothermal reaction. \n\nThe morphology of these samples was observed by transmission electron microscopy (TEM) and atomic force microscopy (AFM). The TEM images exhibit that these CQDs are uniform and monodispersed nanodots in Fig. 2 (A to E). Their average lateral sizes are about 1.71, 1.83, 1.95, 2.2, and $2.42\\mathrm{nm}$ for b-CQDs, c-CQDs, yg-CQDs, o-CQDs, and r-CQDs, respectively. The high-resolution TEM images illustrate the high crystallinity structure of CQDs with similar well-resolved lattice fringes. The crystal plane spacing of $0.21~\\mathrm{{nm}}$ corresponds to the (100) graphite plane (Fig. 2, F to J) (29). The average heights of the CQDs range from 0.48 to $0.66\\mathrm{nm}$ in Fig. 2 (K to O), elucidating that they consist of one to two layers of graphite (30). The $\\mathbf{x}$ -ray diffraction (XRD) patterns indicate a distinct peak at around $25.3^{\\circ}$ , signifying a nearly identical (002) layer spacing of the CQDs (fig. S2J) (31). Layer spacing $(3.78\\mathrm{\\AA})$ in the b-CQDs functionalized by $\\mathrm{SO}_{3}$ is substantially more extensive than that of other CQDs (3.31 to $3.57\\mathring\\mathrm{A}$ ), which is demonstrated in our previous work (28). Their graphitic structure is reflected in Raman spectra. The intensity ratios of the crystalline G band at $1520.8\\mathrm{cm}^{-1}$ and disordered D band at $1381.8~\\mathrm{cm}^{-1}$ $(I_{\\mathrm{G}}/I_{\\mathrm{D}})$ are 0.93, 1.04, 1.14, 1.17, and 1.38 from b-CQDs to r-CQDs, respectively (fig. S2K). The increasing ratio values imply the strengthened graphitization degree from b-CQDs to r-CQDs, indicating a gradual increase of the size of $\\mathsf{s p}^{2}$ domains (17, 32), which is consistent with the above TEM results. These consequents provide essential progress toward the understanding of the engineering role of acid reagents in the realization of highly efficient full-color CQDs. The acid reagents introduce electron-withdrawing groups on the surface of CQDs, which are performed to effectively modulate the degree of graphitization, and thereby construct their increasing particle size with red shift tunable emission. \n\n![](images/8c5a18a4d8f39664f01f4f20c5d8396a1f3bd733e3deb86710e4b9f5caa69807.jpg) \nFig. 2. Morphological characterizations of selected CQDs. (A to E) TEM images and corresponding lateral size distributions of b-CQDs (A), c-CQDs (B), yg-CQDs (C), o-CQDs (D), and r-CQDs (E). (F to J) High-resolution TEM images of b-CQDs (F), c-CQDs (G), yg-CQDs (H), o-CQDs (I), and r-CQDs (J) (inset: fast Fourier transform patterns). (K to O) AFM images and corresponding height profiles of b-CQDs (K), c-CQDs (L), yg-CQDs (M), o-CQDs (N), and r-CQDs (O). \n\n# Optical performance \n\nTo gain the optimal optical features of CQDs, we modulated their QYs by adjusting the acid reagent concentration and temperature of the reaction (fig. S3, A to J). The optimal QYs for the CQDs are deemed to range from 25 to $72\\%$ (table S2), overstepping majority CQDs reported to date (33–35). The yg-CQDs with the highest QYs among these CQDs demonstrate similar fluorescent properties with rhodamine 6G (a commonly used reference for measuring QYs) (fig. S3K). As shown in Fig. 3A, the absorption spectra of the CQDs exhibit strong excitonic absorption bands at 377, 428, 454, 571, and $628\\mathrm{nm}$ for b-CQDs, $c$ -CQDs, yg-CQDs, o-CQDs, and r-CQDs, respectively, which is similar to the absorption characteristics of traditional semiconductor QDs and unlike previously reported CQDs within the UV region (25, 26). The normalized PL spectra of CQDs also display PL peaks at about $450\\mathrm{nm}$ (b-CQDs), $490\\mathrm{nm}$ (c-CQDs), $540~\\mathrm{nm}$ (yg-CQDs), $600\\ \\mathrm{nm}$ (o-CQDs), and $665~\\mathrm{nm}$ (r-CQDs), respectively (Fig. 3B). We tested various solvents to investigate the solvation effect in the fabrication process of the CQDs. In comparison with the CQDs manufactured in ethanol, the excitonic absorption bands of most of these CQDs synthesized in water, $N,N^{\\prime}$ - dimethylformamide (DMF), and toluene are inhibited within $500\\mathrm{nm}$ (fig. S1, C to H) and do not show the wide spectral response characteristic like full-color CQDs. Meanwhile, the modulation of their PL peaks only ranges from 420 to $610~\\mathrm{{nm}}$ , which is limited compared with the optical properties of CQDs fabricated in ethanol. The optical phenomenon of CQDs produced in various solvents suggests that the reaction solution with high or low polarity led to a notable blue shift of optical properties of CQDs and illustrates that medium polarity ethanol is the most advisable solvent to synthesize CQDs with the desired optical properties. Notably, the CQDs demonstrate excitation-independent PL emissions (fig. S4, A to E) due to their highly ordered graphitic structure (fig. S2K) (27). The maximum PL excitation peak is centered at $355\\mathrm{nm}$ (b-CQDs), $410\\mathrm{nm}$ (c-CQDs), $440\\ \\mathrm{nm}$ (yg-CQDs), $535\\mathrm{nm}$ (o-CQDs), and $600\\ \\mathrm{nm}$ (r-CQDs), respectively (fig. S4F), which is consistent with the relevant excitonic absorption band (fig. S4G), revealing the band-edge emission properties of CQDs (15, 36). Meanwhile, the gradual increase of CQD size from 1.7 to $2.4~\\mathrm{nm}$ agrees with the corresponding PL wavelength and the first excitonic absorption band (Fig. 3C), elucidating the quantum size effect (15, 17, 27–29, 37). Moreover, the time-resolved PL spectra, illustrating the band-edge emission properties of CQDs, were further measured. A decreasing trend of monoexponential lifetimes of the CQDs from 10.91 ns (b-CQDs) to 2.49 ns (r-CQDs) (Fig. 3D and table S3) indicates that the CQDs’ lifetime decreases with their PL wavelength red shift (15). Furthermore, these CQDs retain the long-term photostability $_{>10}$ hours) under UV light irradiation and good temperature tolerance (fig. S4, H to Q), which is a benefit for long-term observation of the CQD-based technological devices. As a consequence, the QYs of these CQDs are markedly improved by optimizing reaction conditions. Besides, these CQDs have unique tunable fluorescence properties. Accompanied by the excellent photostability and thermal stability, these CQDs will generally be applicable for advanced WLEDs. \n\n![](images/da76ed6ea577d81db82f1b426815d739d2a161f7996ad9b8ac32245508dbd3a5.jpg) \nFig. 3. Optical performance of selected CQDs. (A) Absorption spectra of CQDs. (B) Normalized PL spectra of CQDs. (C) Dependence of the PL wavelength and first excitonic absorption band on the particle size of CQDs. (D) Time-resolved PL spectra of CQDs. (E) Dependence of the HOMO and LUMO energy levels concerning the particle size of CQDs. a.u., arbitrary units. \n\nBandgap energies of CQDs were calculated using the equation $E_{g}^{\\mathrm{\\scriptsize~opt}}=\\bar{1240}/\\lambda_{\\mathrm{edge}},$ where $\\lambda_{\\mathrm{edge}}$ is the wavelength of the maximum absorption edge. The calculated bandgap energies gradually decrease from 2.76 to $1.88~\\mathrm{eV}$ with the rising particle size of CQDs (table S3), further certifying the quantum size effect of CQDs. Meanwhile, the highest occupied molecular orbital (HOMO) energy level is determined by UV photoelectron spectroscopy, and the lowest unoccupied molecular orbital (LUMO) is gained on the basis of the optical bandgap energy and the HOMO energy level (fig. S5, A to E, and table S3). As seen from the energy diagram in Fig. 3E, there are similarly decreased trendies of HOMO and LUMO levels ranging from 5.22 to $3.83\\mathrm{eV}$ and from 2.46 to $1.95\\mathrm{eV}$ (the difference between energy gap and HOMO level), respectively, directly elucidating the interband transitions in the CQDs (fig. S5F and table S3) (18). \n\n# Unique w-CQDs \n\nThe w-CQDs have recently emerged as a candidate for innovative white luminescent materials for the replacement of present-day materials (38, 39). Note that anchoring the w-CQD phosphor on the UV chip can directly fabricate WLEDs without further proportional control. However, all of the reported w-CQDs were obtained by strong acid activation of bulk carbon materials, which broke their intrinsic $\\mathsf{s p}^{2}$ -hybridized structure, created massive defects, and resulted in their weak white fluorescence (39, 40). Thus, there is still a long way to get high-quality w-CQDs. Besides the multicolor CQDs, the highperformance w-CQDs were synthesized in an analogous route successfully. The w-CQDs emit bright white fluorescence when irradiated by UV light, obtaining the highest QY of $39\\%$ in all of the published w-CQDs (Fig. 4A) (38–40). The optical spectrum of w-CQDs demonstrates a broad PL ranging from 360 to about $800\\mathrm{nm}$ (Fig. 4B), covering the entire visible light region. The wide full width at half maximum of w-CQDs is $208~\\mathrm{nm}$ , which is broader than that of the reported w-CQDs (38–40). Besides, w-CQDs also maintain an excellent photostability for 10 hours and thermal stability (fig. S6, A and B). Furthermore, the w-CQDs exhibit a monoexponential fluorescence lifetime of 3.07 ns in Fig. 4C. A graphitic structure with a (002) layer spacing is shown in the XRD pattern (fig. S6C), which closely resembled that of other selected CQDs. The large G-to-D intensity ratio of 1.36 verifies the high-ordered graphitization structure (fig. S6D). As shown in the FTIR spectrum of w-CQDs (fig. S6E), there are four sharp peaks ascribed to the $\\mathrm{NH}_{2}$ , COOH, and OH groups on the surface of w-CQDs. The w-CQDs have the three-elemental composition (i.e., C, N, and O) in the XPS spectra (fig. S6, F to I). There is a $\\mathrm{C-N/C-O}$ signal at $286.1\\mathrm{eV}$ in the C1s spectrum and a strong signal of $\\mathrm{NH}_{2}$ to $399.2\\mathrm{eV}$ in the N1s spectrum, indicating the existence of $\\mathrm{NH}_{2}$ groups. Similarly, the O1s spectrum reveals the presence of $\\scriptstyle{\\mathrm{C=O}}$ at $531.6\\mathrm{eV}$ and $\\mathrm{C-O}$ at $533.2\\mathrm{eV}$ , while the $\\scriptstyle{\\mathrm{C=O}}$ signal at $288.6~\\mathrm{eV}$ is seen in the C1s spectrum. The XPS analysis further confirms the results of FTIR. The TEM image (Fig. 4D) reveals that the w-CQDs are well dispersed with an average lateral size of $3.01\\mathrm{nm}$ . The high-resolution TEM image of w-CQDs shows wellresolved lattice fringes that resemble other selected CQDs (Fig. 4E). An average thickness of w-CQDs characterized by AFM (Fig. 4F) is $0.64\\mathrm{nm}$ , also revealing an average layer number of ${\\sim}1$ to 2. There is no doubt that such superior w-CQDs are going to create highly efficient WLEDs soon. \n\n# Advanced WLED applications \n\nThe CQDs with unique optical properties could be used in several applications, such as full-color emissive films. The pure CQDs and mixtures with varying ratios of CQDs were applied to prepare fullcolor PMMA nanocomposite films (Fig. 5A and fig. S7A). All the obtained films are uniform and transparent (fig. S7A). These films indicate a broad range of PL emission colors under UV light at $365\\mathrm{nm}$ in Fig. 5A. Except for a white light emission film (xvi) using pure w-CQDs, it is noted that two white luminous films (xiv and xv) could also be achieved with varying ratios of CQDs. Next, all types of WLEDs were fabricated by using CQDs in silica gel in various concentrations and mixtures, including warm WLED (I), standard WLED (II), and cool WLED (III) [inset in Fig. 5 (B to D)]. The warm WLED with low correlated color temperature $(\\mathrm{CCT}<4000~\\mathrm{K})$ ) is strongly desired for indoor lighting because it makes our eyes relaxed and comfortable. However, it is difficult to improve its CRI over 80 because of a lack of efficient orange or red luminescent CQD-based phosphors (16). Here, the warm WLED made use of pure o-CQDs, as phosphor emits bright warm white light with CCT of 3913 K, Commission Internationale de L’Eclairage (CIE) color coordinate of (0.39, 0.38), and high CRI of 89.3 (Fig. 5B). When pure w-CQDs serve as the phosphor, a standard WLED with a CIE color coordinate of (0.33, 0.33) is acquired (Fig. 5C). The CCT and CRI of the WLED are 5994 K and as high as 86.7, respectively, and the emitted white light is very close to natural sunlight. By combining the b-CQDs, yg-CQDs, and r-CQDs with a weight ratio of 1:2:3, a cool WLED with the CIE color coordinate approaching (0.28, 0.29) and high-CRI (86.7) has also been achieved (Fig. 5D). The light-emitting spectrum of the WLEDs is shown in Fig. 5 (E to G), which also covers the whole visible light \n\n![](images/4ff27cba9675e99f01e0ec55fd5abe201a185edfdb59477f6ee3fb87874104a2.jpg) \nFig. 4. Optical and morphological characterizations of w-CQDs. (A) Photographs of w-CQDs under daylight (left) and UV light (right) (excited at $365\\mathsf{n m}$ ). (B) PL spectrum of w-CQDs. (C) Time-resolved PL spectrum of w-CQDs. (D) TEM image and corresponding lateral size distribution of w-CQDs. (E) High-resolution TEM image and fast Fourier transform pattern of w-CQDs. (F) AFM image and corresponding height profile of w-CQDs. \n\nWang et al., Sci. Adv. 2020; 6 : eabb6772 2 October 2020 region from 400 to $780\\mathrm{nm}$ . There are two visible PL peaks centered at about 475 and $620~\\mathrm{{nm}}$ in the light-emitting spectrum of warm WLED, whereas there is only a single PL peak near 600 and $550\\mathrm{nm}$ for standard and cool WLED, respectively. Wholly, the full-color phosphors based on CQDs are promising candidates for practical display and all types of high-CRI WLED applications. \n\n![](images/5784cf333ea60cb883ed929ba800610272e1ff85a400bd32b7a492b34fba7c61.jpg) \nFig. 5. Applications of full-color CQDs. (A) Fluorescence images of CQDs/PMMA composite films on glass substrates under UV light. (i) b-CQDs, (ii) c-CQDs, (iii) $\\mathsf{g-C O D s},$ (iv $)y{\\mathrm{-}}{\\mathsf{C O D s/g-C Q D s}}=1{:}1$ , (v) yg-CQDs, (vi) y-CQDs, (vii) $\\mathsf{g-C Q D s/o-C Q D s=}1{:}1,$ , (viii) o-CQDs, (ix) yg-CQDs/o-CQDs = 1:1, (x) r-CQDs/dr-CQDs $\\c=$ 1:1, (xi) dr-CQDs/b-CQDs = 1:1, (xii) r-CQDs, (xiii) dr-CQDs, (xiv) b-CQDs/yg-CQDs/dr-CQDs $\\mathbf{\\Sigma}=\\mathbf{\\Sigma}$ 1:2:3, (xv) $_{C-C Q D s/y-C Q D s/r-C Q D s}=1{:}2{:}1,$ , and (xvi) w-CQDs (all ratio scale w/w). (B and E) The CIE chromaticity coordinate and corresponding emission spectrum of the warm WLED (inset: the photograph and schematic of the warm WLED). (C and F) The CIE chromaticity coordinate and corresponding emission spectrum of the standard WLED (inset: the photograph and schematic of the standard WLED). (D and G) The CIE chromaticity coordinate and corresponding emission spectrum of the cool WLED (inset: the photograph and schematic of the cool WLED). \n\n# DISCUSSION \n\nAlthough CQDs have inherent advantages of tunable PL emission for WLEDs, the CQD-based devices have traditionally encountered from both relatively low CRI and unimplemented all types of ideal WLEDs. Exploiting the practical synthesis techniques of advanced full-color CQDs is the ultimate vital implication for further success in WLED applications. In summary, we have successfully demonstrated a facile acid reagent engineering approach to manipulate highly efficient full-color tunable fluorescent emission CQDs. More specifically, the QYs of these CQDs are remarkably improved up to $72\\%$ . The synthesis strategy relies on the introduced acid reagents in the fusion process, which markedly plays a role in modulating PL phenomena of as-produced CQDs. The fluorescence emission of these CQDs can be tuned from blue to red and even white light. The maximum PL excitation peaks are consistent with the relevant excitonic absorption bands, and the lifetimes of the CQDs decrease with their PL wavelength red shift, also revealing the band-edge emission properties of CQDs. Moreover, the linear behavior between the particle size of CQDs and the corresponding PL wavelength illustrates the quantum size effect of as-prepared CQDs. In this way, the superiorities of the CQDs in high QYs, optical tunability, remarkable photostability, and thermal stability are perfectly integrated to build advanced WLED architectures. Eventually, by adding one or more types of these CQDs in appropriate ratios to the colloid mixtures, we have succeeded in fabricating the full-color luminous films and all types of WLED devices, including warm, standard, and cool WLEDs. The values of their CIE color coordinate are precisely located on the white light trajectory, and these WLEDs also exhibit higher CRI than 80. Furthermore, the CQDs display an excellent cell imaging ability with a good biocompatibility (fig. S7, B to F), which opens a highly exciting scenario for the exploration of the advanced optoelectronic devices and future high-resolution bioimaging applications. \n\nTo elucidate the nature of the engineering role of acid reagents in the fusion process, we further pursued the functional groups on the surface of these CQDs via XPS and elemental analysis. With the illustration of XPS and elemental analysis evolutions, it reveals that introducing and increasing electron-withdrawing groups on the surface of CQDs mainly contribute to the rising particle sizes and PL wavelength red shift of the CQDs. Our approach discovered in this work constitutes a valuable proof of concept on the general electron-­donating/ withdrawing group engineering route for developing practical synthesis techniques of high-quality CQDs with tunable optical properties. The concept affirms killing three birds with one stone [i.e., (i) modulating particle size, (ii) tuning color emission, and (iii) realizing the advanced performance of CQD-based WLEDs]. Our findings may cause considerable repercussions to generate brand new envisages of processing techniques for advanced CQDs and other luminescent materials. We will attempt more systems to verify our discovery in the near future. \n\n# MATERIALS AND METHODS \n\n# Chemicals and materials \n\nReagent grades of oPD were purchased from Adamas. Ethanol, DMF, toluene, acids, and PMMA were provided by Sinopharm Chemical Reagent Co. Ltd. (Shanghai, China). All chemical reagents were used as received without further purification. Deionized water was used for all experiments. \n\n# Synthesis of full-color CQDs \n\nThe tunable fluorescent CQDs from blue to red and even white were prepared via a one-pot solvothermal process using acids and oPD as engineering reagents and the precursor. The CQDs from left to right in Fig. 1 were labeled as b-CQDs, $c$ -CQDs, $\\mathbf{g}$ -CQDs, yg-CQDs, y-CQDs, o-CQDs, r-CQDs, dr-CQDs, and w-CQDs, respectively. For b-CQDs and $\\mathbf{g}$ -CQDs, oPD $(0.1\\ \\mathrm{g})$ and 4-ABSA (0.1 and $0.2{\\mathrm{~g}}{\\mathrm{,}}$ ) were dissolved in $\\mathrm{10-ml}$ ethanol solution. Afterward, the solution was transferred into a $25\\mathrm{-ml}$ Teflon-lined stainless steel autoclave and heated at $180^{\\circ}\\mathrm{C}$ for 12 hours for b-CQDs and $\\mathbf{g}$ -CQDs, respectively. When the reaction temperature dropped to room temperature, the resulting solution was filtered with a $0.22\\mathrm{-}\\upmu\\mathrm{m}$ microporous membrane and then purified by dialysis in ethanol solvent. Last, the CQD powder could be obtained for further characterization after drying at $60^{\\circ}\\mathrm{C}$ . Other CQDs were prepared using a procedure similar to that described above for b-CQDs and $\\mathbf{g}$ -CQDs, except for the different acids with suitable amount. Generally, the 0.05- and $_{0.1-\\mathrm{g}}$ FA was used to react with oPD $(0.05~\\mathrm{g})$ for c-CQDs and y-CQDs, respectively. The $0.1\\mathrm{-g}$ BA was used to react with oPD $\\left(0.1\\ \\mathrm{g}\\right)$ for yg-CQDs. The $0.8–\\mathrm{ml}$ AA was used to react with oPD $\\left(0.1\\ \\mathrm{g}\\right)$ for o-CQDs. The 0.1- and $0.2\\mathrm{-g}$ TPA was used to react with oPD $(0.1\\mathrm{g})$ for r-CQDs and dr-CQDs, respectively. The $_{0.1-\\mathrm{g}}$ TA was used to react with oPD $(0.1\\ \\mathrm{g})$ for w-CQDs. \n\n# Preparation of full-color emissive films \n\nFor the blue/cyan/green/yellow-green/yellow/orange/magenta/red/ white fluorescent glass films, $2\\mathrm{ml}$ of the corresponding CQD solvent $(5~\\mathrm{mg}{\\cdot}\\mathrm{ml}^{-1}),$ ) was mixed with $10~\\mathrm{ml}$ of PMMA solvent $(10\\mathrm{mg}{\\cdot}\\mathrm{ml}^{-1})$ ), then dropped on a cleaned glass sheet using spin-coating method, and dried for 1 day under ambient conditions. Among them, the mixed glass films are obtained with the corresponding weight ratio: \n\n(i) b-CQDs, (ii) $\\mathfrak{c}$ -CQDs, (iii) $\\mathbf{g}$ -CQDs, (iv) $\\mathrm{\\gamma\\mathrm{y-CQDs/g-CQDs=1:1}}_{\\mathrm{z}}$ , (v) yg-CQDs, (vi) y-CQDs, (vii) $\\mathrm{\\Deltag{-}C Q D s/o{-}C Q D s=1:1,}$ (viii) o-CQDs, (ix) $\\mathrm{\\yg-CQDs/o-CQDs=1:1}$ , (x $\\mathrm{)r{-}C Q D s/d r{-}C Q D s=1:1}$ , (xi) dr-CQDs/ ${\\mathsf{b-C Q D s}}=1:1$ , (xii) $\\mathbf{r}$ -CQDs, (xiii) dr-CQDs, (xiv) b-CQDs/yg-CQDs/ dr $-\\mathrm{CQDs}=1{:}2{:}3$ , (xv) $\\mathsf{c.C Q D s/y-C Q D s/r-C Q D s=1:2:1}$ , and (xvi) w-CQDs (all ratio scale w/w). \n\n# Fabrication of WLEDs \n\nWarm WLED was fabricated with the o-CQDs and a blue LED chip. Standard and cool WLEDs were manipulated with the w-CQDs, mixed CQDs with the appropriate weight ratio $\\mathrm{(b{-}C Q D s/y g{-}C Q D s/}$ $\\mathrm{r{-CQDs}=1{:}2{:}1)}$ , and a UV LED chip, respectively. All types of WLEDs have a similar preparation process. The CQDs $(5\\mathrm{mg})$ were added to $1.6\\:\\mathrm{g}$ of ET-821A silica gel and $0.4\\ \\mathrm{g}$ of ET-821B silica gel. Then, the mixture was stirred for $15\\mathrm{min}$ $\\mathrm{50rpm})$ and added dropwise to a blue or UV LED chip, respectively. Then, the device was dried in an oven at $50^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . \n\n# Material characterization \n\nThe photographs were taken with a camera (Nikon D7000) under UV light excited at $365\\mathrm{nm}$ ${\\mathrm{\\'6000}}{\\mathrm{\\upmu}}{\\mathrm{W}}{\\cdot}{\\mathrm{cm}}^{-2}$ ; S4020-6K). AFM images were characterized using an SPM-9600 AFM. TEM observations were performed on aberration-corrected TEM (JEM-2100F) operating at $80\\mathrm{-kV}$ acceleration voltage. FTIR spectra of dried samples were recognized with a Bio-Rad FTIR spectrometer FTS165. XPS spectra were gathered using a Kratos Axis Ultra DLD $\\mathbf{x}$ -ray photoelectron spectrometer. Elemental analysis was performed on vario MICRO. $\\mathrm{^{1}\\dot{H}N M R}$ and $^{13}\\mathrm{C}$ NMR spectroscopy were carried out with JEOL resonance ECZ400S 400-MHz spectrometer using dimethyl sulfoxide–D6 as the solvent. XRD patterns were obtained with a Rigaku 18 KW D/max-2550 using Cu $\\mathrm{K}_{\\upalpha}$ radiation. Raman spectra were recorded on a Thermo Fisher Scientific DXRxi laser Raman spectrometer with $\\lambda_{\\mathrm{ex}}=633\\mathrm{nm}$ . Absorption and fluorescence spectra were registered at room temperature on a Hitachi 3010 spectrophotometer and a Hitachi 7000 fluorescence spectrophotometer. The time-resolved PL spectra were measured on an Edinburgh FS5 spectrofluorometer. The PL QY of CQD solutions was determined by comparing the integrated PL intensities and the absorbency values using rhodamine 6G in water (QY: $95\\%$ ) as the reference. The UV photoelectron spectroscopy was measured with a monochromatic He I light source $(21.22\\mathrm{eV}$ ; ESCALAB 250XI, Thermo Fisher Scientific) and a VG Scienta R4000 analyzer. A sample bias of $-5\\mathrm{V}$ was applied to observe the secondary electron cutoff. The work function () can be determined by the difference between the photon energy and the binding energy of the secondary cutoff edge. The CQD thin film was prepared from spin-coating on the indium tin oxide substrate for UV photoelectron spectroscopy measurement. The photoelectric properties, including the emission spectra, CCT, CRI, and CIE color coordinates of the WLEDs, were measured by using a high-accuracy array spectroradiometer (HAAS-2000, Everfine). \n\n# SUPPLEMENTARY MATERIALS \n\nSupplementary material for this article is available at http://advances.sciencemag.org/cgi/ content/full/6/40/eabb6772/DC1 \n\n# REFERENCES AND NOTES \n\n1.\t A. L. Chun, E. De Ranieri, A. Moscatelli, O. Vaughan, Our choice from the recent literature. Nat. Nanotechnol. 10, 568 (2015). \n2.\t G. Li, Y. Tian, Y. Zhao, J. Lin, Recent progress in luminescence tuning of $\\mathsf{C e}^{3+}$ and $\\mathsf{E u}^{2+}$ - activated phosphors for pc-WLEDs. Chem. Soc. Rev. 44, 8688–8713 (2015). \n3.\t M. D. Weber, L. Niklaus, M. Pröschel, P. B. Coto, U. Sonnewald, R. D. Costa, Bioinspired hybrid white light-emitting diodes. Adv. Mater. 27, 5493–5498 (2015). \n4.\t A. Lita, A. L. Washington II, L. van de Burgt, G. F. Strouse, A. E. Stiegman, Stable efficient solid-state white-light-emitting phosphor with a high scotopic/photopic ratio fabricated from fused CdSe-silica nanocomposites. Adv. Mater. 22, 3987–3991 (2010). \n5.\t E. Jang, S. Jun, H. Jang, J. Lim, B. Kim, Y. Kim, White-light-emitting diodes with quantum dot color converters for display backlights. Adv. Mater. 22, 3076–3080 (2010). \n6.\t B. Xie, H. Liu, R. Hu, C. Wang, J. Hao, K. Wang, X. Luo, Targeting cooling for quantum dots in white QDs-LEDs by hexagonal boron nitride platelets with electrostatic bonding. Adv. Funct. Mater. 28, 1801407 (2018). \n7.\t G. Li, H. Wang, T. Zhang, L. Mi, Y. Zhang, Z. Zhang, W. Zhang, Y. Jiang, Solvent-polarityengineered controllable synthesis of highly fluorescent cesium lead halide perovskite quantum dots and their use in white light-emitting diodes. Adv. Funct. Mater. 26, 8478–8486 (2016). \n8.\t C. Sun, Y. Zhang, C. Ruan, C. Yin, X. Wang, Y. Wang, W. W. Yu, Efficient and stable white LEDs with silica-coated inorganic perovskite quantum dots. Adv. Mater. 28, 10088–10094 (2016). \n9.\t H. Daicho, T. Iwasaki, K. Enomoto, Y. Sasaki, Y. Maeno, Y. Shinomiya, S. Aoyagi, E. Nishibori, M. Sakata, H. Sawa, S. Matsuishi, H. Hosono, A novel phosphor for glareless white light-emitting diodes. Nat. Commun. 3, 1132 (2012). \n10.\t W. B. Im, N. George, J. Kurzman, S. Brinkley, A. Mikhailovsky, J. Hu, B. F. Chmelka, S. P. DenBaars, R. Seshadri, Efficient and color-tunable oxyfluoride solid solution phosphors for solid-state white lighting. Adv. Mater. 23, 2300–2305 (2011). \n11.\t Y. H. Kim, P. Arunkumar, B. Y. Kim, S. Unithrattil, E. Kim, S.-H. Moon, J. Y. Hyun, K. H. Kim, D. Lee, J.-S. Lee, W. B. Im, A zero-thermal-quenching phosphor. Nat. Mater. 16, 543–550 (2017). \n12.\t H. Ding, J. Li, G. Xie, G. Lin, R. Chen, Z. Peng, C. Yang, B. Wang, J. Sun, C. Wang, An AIEgen-based 3D covalent organic framework for white light-emitting diodes. Nat. Commun. 9, 5234 (2018). \n13.\t C.-Y. Sun, X.-L. Wang, X. Zhang, C. Qin, P. Li, Z.-M. Su, D.-X. Zhu, G.-G. Shan, K.-Z. Shao, H. Wu, J. Li, Efficient and tunable white-light emission of metal-organic frameworks by iridium-complex encapsulation. Nat. Commun. 4, 2717 (2013). \n14.\t N. Hendler, B. Belgorodsky, E. D. Mentovich, M. Gozin, S. Richter, Efficient separation of dyes by mucin: Toward bioinspired white-luminescent devices. Adv. Mater. 23, 4261–4264 (2011). \n15.\t Z. Wang, F. Yuan, X. Li, Y. Li, H. Zhong, L. Fan, S. Yang, $53\\%$ efficient red emissive carbon quantum dots for high color rendering and stable warm white-light-emitting diodes. Adv. Mater. 29, 1702910 (2017). \n16. ${\\mathsf{S}}_{\\cdot}{\\mathsf{Q u}},$ D. Zhou, D. Li, W. Ji, P. Jing, D. Han, L. Liu, H. Zeng, D. Shen, Toward efficient orange emissive carbon nanodots through conjugated $\\mathsf{s p}^{2}.$ -domain controlling and surface charges engineering. Adv. Mater. 28, 3516–3521 (2016). \n17.\t H. Ding, S.-B. $\\mathsf{Y u,}$ J.-S. Wei, H.-M. Xiong, Full-color light-emitting carbon dots with a surface-state-controlled luminescence mechanism. ACS Nano 10, 484–491 (2016). \n18.\t Y. Yan, J. Chen, N. Li, J. Tian, K. Li, J. Jiang, J. Liu, Q. Tian, P. Chen, Systematic bandgap engineering of graphene quantum dots and applications for photocatalytic water splitting and $\\mathsf{C O}_{2}$ reduction. ACS Nano 12, 3523–3532 (2018). \n19.\t S. Yang, W. Li, C. Ye, G. Wang, H. Tian, C. Zhu, P. He, G. Ding, X. Xie, Y. Liu, Y. Lifshitz, S.-T. Lee, Z. Kang, M. Jiang, $C_{3}\\mathsf{N}$ —A 2D crystalline, hole-free, tunable-narrow-bandgap semiconductor with ferromagnetic properties. Adv. Mater. 29, 1605625 (2017). \n20.\t N. Gong, X. Ma, X. Ye, Q. Zhou, X. Chen, X. Tan, S. Yao, S. Huo, T. Zhang, S. Chen, X. Teng, X. Hu, J. Yu, Y. Gan, H. Jiang, J. Li, X.-J. Liang, Carbon-dot-supported atomically dispersed gold as a mitochondrial oxidative stress amplifier for cancer treatment. Nat. Nanotechnol. 14, 379–387 (2019). \n21.\t S. D. Pritzl, F. Pschunder, F. Ehrat, S. Bhattacharyya, T. Lohmüller, M. A. Huergo, J. Feldmann, Trans-membrane fluorescence enhancement by carbon dots: Ionic interactions and energy transfer. Nano Lett. 19, 3886–3891 (2019). \n22.\t P. Huang, J. Lin, X. Wang, Z. Wang, C. Zhang, M. He, K. Wang, F. Chen, Z. Li, G. Shen, D. Cui, X. Chen, Light-triggered theranostics based on photosensitizer-conjugated carbon dots for simultaneous enhanced-fluorescence imaging and photodynamic therapy. Adv. Mater. 24, 5104–5110 (2012). \n23.\t K. Holá, M. Sudolská, S. Kalytchuk, D. Nachtigallová, A. L. Rogach, M. Otyepka, R. Zbořil, Graphitic nitrogen triggers red fluorescence in carbon dots. ACS Nano 11, 12402–12410 (2017). \n24.\t X. Geng, Y. Sun, Z. Li, R. Yang, Y. Zhao, Y. Guo, $\\mathsf{J.}\\mathsf{X u,}$ F. Li, Y. Wang, S. Lu, L. Qu, Retrosynthesis of tunable fluorescent carbon dots for precise long-term mitochondrial tracking. Small 15, e1901517 (2019). \n25.\t W. Li, W. Zhou, Z. Zhou, H. Zhang, X. Zhang, J. Zhuang, Y. Liu, B. Lei, C. Hu, A universal strategy for activating the multicolor room-temperature afterglow of carbon dots in a boric acid matrix. Angew. Chem. Int. Ed. 58, 7278–7283 (2019). \n26.\t S. Zhu, Q. Meng, L. Wang, J. Zhang, Y. Song, H. Jin, K. Zhang, H. Sun, H. Wang, B. Yang, Highly photoluminescent carbon dots for multicolor patterning, sensors, and bioimaging. Angew. Chem. Int. Ed. 52, 3953–3957 (2013). \n27.\t K. Jiang, S. Sun, L. Zhang, Y. Lu, A. Wu, C. Cai, H. Lin, Red, green, and blue luminescence b carbon dots: Full-color emission tuning and multicolor cellular imaging. Angew. Chem. Int. Ed. 54, 5360–5363 (2015). \n28.\t L. Wang, B. Wu, W. Li, Z. Li, J. Zhan, B. Geng, S. Wang, D. Pan, M. Wu, Industrial production of ultra-stable sulfonated graphene quantum dots for Golgi apparatus imaging. J. Mater. Chem. B 5, 5355–5361 (2017). \n29.\t B. Zhang, Y. Liu, M. Ren, W. Li, X. Zhang, R. Vajtai, P. M. Ajayan, J. M. Tour, L. Wang, Sustainable synthesis of bright green fluorescent nitrogen-doped carbon quantum dots from alkali lignin. ChemSusChem 12, 4202–4210 (2019). \n30.\t Y. Han, M. Li, J. Lai, W. Li, Y. Liu, L. Yin, L. Yang, X. Xue, R. Vajtai, P. M. Ajayan, L. Wang, Rational design of oxygen-enriched carbon dots with efficient room-temperature phosphorescent properties and high-tech security protection application. ACS Sustain. Chem. Eng. 7, 19918–19924 (2019). \n31.\t X. Miao, D. Qu, D. Yang, B. Nie, Y. Zhao, H. Fan, Z. Sun, Synthesis of carbon dots with multiple color emission by controlled graphitization and surface functionalization. Adv. Mater. 30, 1704740 (2018). \n32.\t F. Yuan, T. Yuan, L. Sui, Z. Wang, Z. Xi, Y. Li, X. Li, L. Fan, Z. Tan, A. Chen, M. Jin, S. Yang, Engineering triangular carbon quantum dots with unprecedented narrow bandwidth emission for multicolored LEDs. Nat. Commun. 9, 2249 (2018). \n33.\t Z. Liu, H. Pei, L. Zhang, Y. Tian, Mitochondria-targeted DNA nanoprobe for real-time imaging and simultaneous quantification o $\\mathsf{C a}^{2+}$ and pH in neurons. ACS Nano 12, 12357–12368 (2018). \n34.\t J. Shao, S. Zhu, H. Liu, Y. Song, S. Tao, B. Yang, Full-color emission polymer carbon dots with quench-resistant solid-state fluorescence. Adv. Sci. 4, 1700395 (2017). \n35.\t Z. Tian, X. Zhang, D. Li, D. Zhou, P. Jing, D. Shen, S. Qu, R. Zboril, A. L. Rogach, Full-color inorganic carbon dot phosphors for white-light-emitting diodes. Adv. Opt. Mater. 5, 1700416 (2017). \n36.\t Y. Li, Y. Zhao, H. Cheng, Y. Hu, G. Shi, L. Dai, L. Qu, Nitrogen-doped graphene quantum dots with oxygen-rich functional groups. J. Am. Chem. Soc. 134, 15–18 (2012). \n37.\t L. Wang, Y. Wang, T. Xu, H. Liao, C. Yao, Y. Liu, Z. Li, Z. Chen, D. Pan, L. Sun, M. Wu, Gram-scale synthesis of single-crystalline graphene quantum dots with superior optical properties. Nat. Commun. 5, 5357 (2014). \n38.\t Z. Luo, G. Qi, K. Chen, M. Zou, L. Yuwen, X. Zhang, W. Huang, L. Wang, Microwave-assiste preparation of white fluorescent graphene quantum dots as a novel phosphor for enhanced white-light-emitting diodes. Adv. Funct. Mater. 26, 2739–2744 (2016). \n39.\t F. Arcudi, L. Đorđević, M. Prato, Rationally designed carbon nanodots towards pure white-light emission. Angew. Chem. Int. Ed. 56, 4170–4173 (2017). \n40.\t T. Meng, T. Yuan, X. Li, Y. Li, L. Fan, S. Yang, Ultrabroad-band, red sufficient, solid white emission from carbon quantum dot aggregation for single component warm white ligh emitting diodes with a 91 high color rendering index. Chem. Commun. 55, 6531–6534 (2019). \n\nAcknowledgments: We thank the Laboratory for Microstructures of Shanghai University. Funding: This work was supported by the National Natural Science Foundation of China (nos. 21671129, 21901154, 21671131, 51605272, 11875185, and 41430644), the Shanghai Sailing Program (no. 16YF1404400), and the Program for Changjiang Scholars and Innovative Research Team in University (no. IRT_17R71). Author contributions: L.W. and M.W. conceived the idea and supervised the project. P.M.A. and R.V. provided important suggestions, supervised parts of the project, and improved the manuscript. L.W. and W.L. conducted most of the experiments regarding the CQD fabrication and characterization. Y.L., H.G., J.L., Y.H., G.L., and M.L. supported the optical performance. L.Y. and J.Z. helped with WLED part experiment. L.W. wrote the manuscript. All authors analyzed and discussed the experimental data and drafted the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. \n\nSubmitted 11 March 2020 \nAccepted 19 August 2020 \nPublished 2 October 2020 \n10.1126/sciadv.abb6772 \n\nCitation: L. Wang, W. Li, L. Yin, Y. Liu, H. Guo, J. Lai, Y. Han, G. Li, M. Li, J. Zhang, R. Vajtai, P. M. Ajayan, M. Wu, Full-color fluorescent carbon quantum dots. Sci. Adv. 6, eabb6772 (2020). \n\n# ScienceAdvances \n\n# Full-color fluorescent carbon quantum dots \n\nLiang Wang, Weitao Li, Luqiao Yin, Yijian Liu, Huazhang Guo, Jiawei Lai, Yu Han, Gao Li, Ming Li, Jianhua Zhang, Robert Vajtai, Pulickel M. Ajayan and Minghong Wu \n\nSci Adv 6 (40), eabb6772. DOI: 10.1126/sciadv.abb6772 \n\nARTICLE TOOLS \n\nSUPPLEMENTARY MATERIALS \n\nREFERENCES \n\nThis article cites 40 articles, 0 of which you can access for free http://advances.sciencemag.org/content/6/40/eabb6772#BIBL \n\nPERMISSIONS \n\nUse of this article is subject to the Terms of Service " + }, + { + "id": "10.1038_s41586-021-03295-8", + "DOI": "10.1038/s41586-021-03295-8", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03295-8", + "Relative Dir Path": "mds/10.1038_s41586-021-03295-8", + "Article Title": "Large-area display textiles integrated with functional systems", + "Authors": "Shi, X; Zuo, Y; Zhai, P; Shen, JH; Yang, YYW; Gao, Z; Liao, M; Wu, JX; Wang, JW; Xu, XJ; Tong, Q; Zhang, B; Wang, BJ; Sun, XM; Zhang, LH; Pei, QB; Jin, DY; Chen, PN; Peng, HS", + "Source Title": "NATURE", + "Abstract": "Displays are basic building blocks of modern electronics(1,2). Integrating displays into textiles offers exciting opportunities for smart electronictextiles-the ultimate goal of wearable technology, poised to change the way in which we interact with electronic devices(3-6). Display textiles serve to bridge human-machine interactions(7-9), offering, for instance, a real-time communication tool for individuals with voice or speech difficulties. Electronictextiles capable of communicating(10), sensing(11,12) and supplying electricity(13,14) have been reported previously. However, textiles with functional, large-area displays have not yet been achieved, because it is challenging to obtain small illuminating unitsthat are both durable and easy to assemble over a wide area. Here we report a 6-metre-long, 25-centimetre-wide display textile containing 5 x10(5 )electroluminescent units spaced approximately 800 micrometres apart. Weaving conductive weft and luminescent warp fibres forms micrometre-scale electroluminescent units at the weft-warp contact points. The brightness between electroluminescent units deviates by less than 8 per cent and remains stable even when the textile is bent, stretched or pressed. Our display textile is flexible and breathable and withstands repeated machine-washing, making it suitable for practical applications. We showthat an integrated textile system consisting of display, keyboard and power supply can serve as a communication tool, demonstrating the system's potential within the Internet of things' in various areas, including healthcare. Our approach unifies the fabrication and function of electronic devices with textiles, and we expect that woven-fibre materials will shape the next generation of electronics.", + "Times Cited, WoS Core": 755, + "Times Cited, All Databases": 803, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000627422700011", + "Markdown": "# Article \n\n# Large-area display textiles integrated with functional systems \n\nhttps://doi.org/10.1038/s41586-021-03295-8 \n\nReceived: 9 August 2020 \n\nAccepted: 26 January 2021 \n\nPublished online: 10 March 2021 Check for updates \n\nXiang Shi1,2,3,11, Yong $\\scriptstyle\\pmb{Z}\\mathbf{uo}^{1,2,3,11}$ , Peng Zhai4,11, Jiahao Shen5, Yangyiwei Yang6, Zhen Gao1,2,3, Meng Liao1,2,3, Jingxia Wu1,2,3, Jiawei Wang1,2,3, Xiaojie $\\mathsf{X}\\mathsf{u}^{1,2,3}$ , Qi Tong5, Bo Zhang1,2,3, Bingjie Wang1,2,3, Xuemei Sun1,2,3, Lihua Zhang4,7, Qibing Pei8, Dayong Jin9,10, Peining Chen1,2,3 ✉ & Huisheng Peng1,2,3 ✉ \n\nDisplays are basic building blocks of modern electronics1,2. Integrating displays into textiles offers exciting opportunities for smart electronic textiles—the ultimate goal of wearable technology, poised to change the way in which we interact with electronic devices3–6. Display textiles serve to bridge human–machine interactions7–9, offering, for instance, a real-time communication tool for individuals with voice or speech difficulties. Electronic textiles capable of communicating10, sensing11,12 and supplying electricity13,14 have been reported previously. However, textiles with functional, large-area displays have not yet been achieved, because it is challenging to obtain small illuminating units that are both durable and easy to assemble over a wide area. Here we report a 6-metre-long, 25-centimetre-wide display textile containing $5\\times10^{5}$ electroluminescent units spaced approximately 800 micrometres apart. Weaving conductive weft and luminescent warp fibres forms micrometre-scale electroluminescent units at the weft–warp contact points. The brightness between electroluminescent units deviates by less than 8 per cent and remains stable even when the textile is bent, stretched or pressed. Our display textile is flexible and breathable and withstands repeated machine-washing, making it suitable for practical applications. We show that an integrated textile system consisting of display, keyboard and power supply can serve as a communication tool, demonstrating the system’s potential within the ‘internet of things’ in various areas, including healthcare. Our approach unifies the fabrication and function of electronic devices with textiles, and we expect that woven-fibre materials will shape the next generation of electronics. \n\nDisplay devices have evolved from rigid panels to flexible thin films15. However, the configuration and fabrication of electronic textiles are different from conventional film devices, such as organic light-emitting diodes (OLEDs) that are currently used to construct flexible displays. On one hand, textiles are woven from fibres, forming rough and porous structures that can deform and fit the contours of the human body16,17. OLEDs, on the other hand, are made by depositing multiple layers of semiconducting organic thin films between cathode and anode electrodes that are placed on planar substrates such as glass or plastic18. Therefore, when attached onto the rough and deformable surfaces of textiles, these film devices often perform poorly or fail over time19. Depositing organic thin films on fibres that are suitable for weaving into flexible display textiles is also very difficult because these thin films are too fragile to withstand the chafing during weaving. The evaporation method used to make OLEDs is not amenable to large-scale fabrication of fibre electrodes. More importantly, because light emission in OLEDs depends on carrier injection and transport between the anode and cathode20,21, weaving warps and wefts cannot provide sufficient high-quality ohmic contact between the electrodes and semiconducting layers for illumination. Although fibre light-emitting devices—such as optical fibres22, polymer light-emitting electrochemical cell fibres23 and a.c. electroluminescence fibres24–26 (Extended Data Table 1)—can be woven into lighting textiles, they generally show pre-designed patterns. The inability to dynamically control the pixels individually in real time according to input digital signals—as in standard display applications such as computers and mobile phones—is a considerable limitation. \n\nIn our study, we used electric field-driven devices based on ZnS phosphor to weave a display textile. Unlike OLED devices, ZnS phosphor dispersed in an insulating polymer matrix is activated by alternating an electric field across a polymer matrix27. Such electric field-driven devices require only spatial contacts between wefts and warps to illuminate28,29, making them intrinsically durable and suitable for large-scale production. We prepared transparent (over $90\\%$ transmittance) conductive weft fibres by melt-spinning ionic-liquid-doped polyurethane gel (Extended Data Fig. $\\mathbf{1}\\mathbf{a}-\\mathbf{c},$ ), and luminescent warp fibres by coating commercially available ZnS phosphor on silver-plated conductive yarn (Extended Data Fig. 1d–f). This solution-based coating is a simple way to obtain continuous lengths of luminescent warp fibres. We chose polyurethane as polymer matrix because it is durable to friction, compression and bending during weaving. To ensure uniform coating of ZnS, we dip-coated the conductive yarn in ZnS phosphor slurry and passed it through a home-made scraping micro-pinhole before drying (Extended Data Fig. 2a). The micro-pinhole smoothed the coating along the longitudinal and circumferential directions (Extended Data Fig. 2b, c). Different diameters of the micro-pinhole were used to tune the thickness of the $Z\\mathsf{n s}$ phosphor layer. We used an optimized thickness of approximately $70\\upmu\\mathrm{m}$ in our experiments unless specified otherwise. To evaluate the uniformity of the luminescent coating, we placed a $100\\cdot\\mathrm{{m}}$ -long luminescent warp into salt water and applied an alternating voltage between them (Extended Data Fig. 2d). The luminescence remained stable even when twisted (Extended Data Fig. 2e). For a $30\\cdot\\mathrm{{m}}$ -long fibre, the luminescence intensity varied by less than $10\\%$ (Extended Data Fig. 2f, g). The intensity along the circumference at different locations of the fibre was almost identical and was independent of observation angle (Extended Data Fig. 2h). Fibres with an uneven ZnS phosphor coating (Extended Data Fig. 2i) showed uneven brightness and failure in some electroluminescent units (EL units; Extended Data Fig. 2j, k), indicating that the light emission requires a uniform luminescent coating. \n\nWhen the conductive weft and luminescent warp fibres are woven with cotton yarn using an industrial rapier loom, each interlaced weft and warp forms an EL unit (Fig. 1a, Extended Data Fig. 1h, i). Synthetic fibre materials such as nylon and polyester fibres could also be co-woven with conductive weft and luminescent warp fibres for various applications (Extended Data Fig. 1j, k). Using this method, we produced a $6\\mathsf{m}\\times25\\mathsf{c m}$ (length $\\times$ width) large-area display textile containing approximately $5\\times10^{5}\\mathsf{E L}$ units (Fig. 1b, Supplementary Video 1). The relative deviations of emission intensity of the ${600}\\tt{E L}$ units varied by ${<}8\\%$ (Fig. 1c, d). Such small differences in intensity indicate that these fibres are well suited for making large-area display textiles at scale. After 1,000 cycles of bending (Fig. 1e), stretching (Fig. 1f) and pressing (Fig. 1g), the intensity for a vast majority of the EL units remained stable (with $<10\\%$ variation). Moreover, the intensity of the majority of the EL units varied by $<15\\%$ even after repeated folding along different directions (Extended Data Fig. 3a–h), and the intensity of the EL units at the folding line remained stable over 10,000 cycles of folding in each folding direction (Extended Data Fig. 3i–l), indicating superior durability over traditional film displays. We also obtained colourful textiles (Fig. 1h) with uniformly spaced EL units (Fig. 1i) by doping different elements such as copper and manganese into the ZnS phosphor30. Because the fibres are woven, the density of the EL units can be easily tuned by adjusting the weaving parameters to change the distance between the weft–warp contact points (Fig. 1j). The narrowest spacing we achieved here is approximately $800\\upmu\\mathrm{m}$ . Based on the project area of the textile, we obtained an average luminance of $122\\mathsf{c d m}^{-2}$ (Extended Data Fig. 4a), a value comparable to commercial planar displays $(100-300{\\mathrm{cd}}{\\mathrm{m}}^{-2},$ . \n\nTo turn on the EL units, we applied an alternating voltage to the luminescent warps and conductive wefts, generating a low, microampere current to power the units (Fig. 2a). Electric field-induced excitation of the luminescent centre and recombination of electron–hole pairs31 results in light emission from the ZnS phosphor at the weft–warp contact area. By varying the applied electricity, we could accurately tune the luminance of the EL unit. The luminance intensity increased with voltage and frequency (Extended Data Fig. 4b, c). A luminance of 115.1 cd $\\mathfrak{m}^{-2}$ was obtained at a voltage of $3.7\\mathrm{V}\\upmu\\mathrm{m}^{-1}$ and frequency of ${2,000}\\mathrm{Hz}$ , with a current density of $1.8\\mathsf{m A c m}^{-2}$ and power consumption of $363.1\\upmu\\mathrm{w}$ (Extended Data Fig. 4d, e). At such a low power consumption, heating was negligible (Extended Data Fig. 4g, h), which is crucial for large-area clothing applications. The driving voltage for the display textile could be reduced to less than 36 V by decreasing the thickness of the luminescent layer (Extended Data Fig. 4i). Coating the conductive wefts and luminescent warps with a layer of transparent insulating polymer can further ensure the safety of these devices. \n\nBecause light emission also depends on how uniform the electric field is at the curved contact area between the luminescent warp and conductive weft, we used a finite-element method to simulate the electric field distribution in the luminescent layer (Fig. 2b). We found that the distribution at the curved contact under an applied voltage was as uniform as a planar electroluminescent device (Fig. 2b, Extended Data Fig. 5a–f) and remained uniform even when the contact area was changed (Fig. 2c, Extended Data Fig. 5g). We attribute this electric field homogeneity to the elastic conductive weft that readily deforms to fit the curved and less elastic surface of the luminescent warp (Extended Data Fig. 1g, h). Light emission occurred even when the conductive weft was leaned, twisted and knotted with the luminescent warp (Fig. 2d, Supplementary Video 2). Electroluminescence mapping images show that electroluminescence intensities and EL unit areas remained nearly unchanged when the transparent conductive weft was moved along the luminescent warp (Fig. 2e), rotated around the contacting point (Fig. 2f), and bent with increasing bending angles (Fig. 2g). As the conductive weft slid along the luminescent warp in increments of $0.5\\mathsf{m m}$ , the luminance varied by less than $2.2\\%$ for a distance of up to $3\\mathsf{m m}$ (Fig. 2h). When the transparent weft rotated by $\\pm15^{\\circ}$ from the position perpendicular to the luminescent warp, the electroluminescence intensity fluctuated by less than $2.6\\%$ (Fig. 2i). Furthermore, owing to the elasticity of the transparent weft, the luminescence recovered instantly and remained stable over 100 cycles of pressing and releasing the EL unit (Fig. 2j). Bending the transparent weft or luminescent warp up to $1.8\\mathsf{m m}$ from its original state also resulted in fluctuations of less than $2.3\\%$ (Fig. 2k, l). Because the fibre is cylindrical, the EL intensity was well maintained when the transparent weft was rolled around its central axis (Extended Data Fig. 6a). The inert and non-volatile nature of the ionic liquid32 in the transparent conductive weft also contributed to the electrical and optical stability of the EL unit (Extended Data Fig. 6b, c). Leaving the textile in the open air for one month did not show any obvious decrease in luminance (Extended Data Fig. 6d). Further, the brightness of the EL units endured 100 cycles of accelerated washing and drying (Extended Data Fig. 6e–h). \n\nTo show our weaving strategy is general, we used it to produce other electronic functions within the textile (for example, keyboard and power supply). To create a textile keyboard that functions through dynamic contact, we wove low-resistance warp (silver-plated yarn) with high-resistance weft (carbon fibre) to form a $4\\times4$ keyboard (Extended Data Fig. 7a), where the intersections of the weft and warp form the keys (Extended Data Fig. 7b, c). For the power supply, we wove photoanode wefts with silver-plated conductive yarns to harvest solar energy (Extended Data Fig. 8a–f). The photoanode weft is a titanium (Ti) wire coated with a photoactive layer composed of titanium dioxide $\\left(\\mathrm{TiO}_{2}\\right)$ nanotubes as the electron transport layer, dye molecules as the sensitizer and copper iodide (CuI) as the solid electrolyte. Integrating these warps and wefts with battery fibres assembled from flexible $\\mathbf{MnO}_{2}$ -coated carbon nanotube fibre (cathode), zinc wire (anode) and $Z_{\\mathsf{n}}\\mathsf{s}0_{4}$ gel electrolyte, we realized both power generation and storage in the textile (Extended Data Fig. 8j–l). With a display, keyboard and power supply, we can design various multifunctional integrated textile systems for different applications (Fig. 3a, Extended Data Fig. 9). \n\nAs a proof-of-concept, we connected the woven display, keyboard and power supply to a display driver, microcontroller and Bluetooth module (Fig. 3b) and used the integrated textile system as an interactive navigation display (Fig. 3c). Through the Bluetooth module, the user’s real-time location in a T-junction, obtained from a smartphone, was transferred to the textile (Fig. 3d). To output the image on the display textile, electrical signals from the driver circuit are scanned row by row onto the array of EL units (Fig. 3e, Supplementary Video 3). \n\n![](images/9136b5c009b6e7f28aa559ba03f8ac84b6480fdc84036c9865606e92797c339e.jpg) \nFig. 1 | Structure and electroluminescence performance of the display textile. a, Schematic showing the weave diagram of the display textile. Each contacting luminescent warp and transparent conductive weft forms an EL unit (inset). An applied alternating voltage $(V_{\\mathrm{rms}})$ turns on the EL units. b, Photograph of a 6-m-long display textile consisting of approximately $5\\times10^{5}$ EL units. c, Statistical distribution showing the relative deviation in emission intensity for 600 EL units. The relative deviation is defined as the deviation of luminance for a single EL unit from the average value. d, Emission intensities of a $10\\times10$ EL unit array are uniform $\\mathrm{<10\\%}$ difference in intensity among the units). $\\mathbf{e}{\\boldsymbol{-}}\\mathbf{g}$ , Statistical distribution showing minor $(<10\\%)$ variations in \nluminance for 600 EL units after 1,000 cycles of bending (e), stretching (f) and pressing (g). Insets, photographs of tested samples. Scale bars, 1 cm. h, Photograph of a functional multicolour display textile under complex deformations, including bending and twisting. Blue and orange are achieved by doping ZnS with copper and manganese, respectively. Scale bar, 2 cm. i, Magnified photograph of the multicolour display textile from h shows that the EL units are uniformly spaced at a distance of ${\\sim}800\\upmu\\mathrm{m}$ . Scale bar, $2\\mathsf{m m}$ . j, Photographs of EL units spaced at different distances, obtained by changing the weave parameters. Scale bars, $2\\mathsf{m m}$ . a.u., arbitrary units. \n\nOur integrated textile system can also function as a communication tool, where information is input and displayed on the textile (Fig. 3f, Supplementary Video 3). We demonstrate this using the numbers 1, 2 and 3. Each number is assigned to a key and the microcontroller is programmed to output the number when the corresponding key is pushed (Fig. 3g). With the Bluetooth module, messages can also be \n\n![](images/8a236236600a058e09aa7135a3282588af157961b19b7642f4d3637595688742.jpg) \nFig. 2 | Characterization of EL units of the display textile. a, Schematic of an EL unit formed at the contact area between the luminescent warp and the transparent conductive weft. Light emission occurs when an alternating electric voltage is applied. b, c, Simulation using a finite-element method shows that the electric field distribution at the contact area in an EL unit is uniform (b) and does not change with increasing contact areas (c). d, Photographs show stable light emission as the transparent conductive weft is contacted, leaned, twisted and knotted with the luminescent warp (top to bottom). Scale bar, 2 mm. e–g, Electroluminescence maps show that the brightness of the EL units remains stable even when the transparent weft is slid \n(e), rotated (f) and bent $\\mathbf{\\sigma}(\\mathbf{g})$ along the luminescent warp. The colour bar indicates the relative electroluminescence intensity (see Methods section ‘Structure and performance characterization of the EL units’). Scale bars, 1 mm. $\\mathbf{h}{-}\\mathbf{l}$ The luminance varied minimally when the transparent weft is moved by $3\\mathrm{{mm}}$ along the luminescent warp (h) and rotated by different degrees $(\\mathbf{i};0^{\\circ}$ is when the weft is perpendicular to the warp), and when the EL unit is pressed and released for 100 cycles (j), bent along the weft length (k) and along the warp length (l) with increasing bending angles. $L_{0}$ and L correspond to the electroluminescence intensity before and after deformation, respectively. Error bars are standard deviations of the results from at least three samples. \n\n# Article \n\n![](images/e96b1a65106f4e6f029f2bb64b477717c585b66dd6dadf6e15b97f61a2efbcce.jpg) \nFig. 3 | Application scenarios of integrated textile systems. a, Photograph of an integrated textile system consisting of display, information input (keyboard) and power supply modules. Scale bar, 2 cm. b, System-level block diagram of the integrated textile system in a shows the modules connected to a microcontroller that is powered by solar-energy harvesting and electrical energy storage modules. c, Conceptual image illustrating the integrated textile as a smart node for the Internet of Things to offer location services during driving. Selective illumination on the display module is achieved by scanning electrical signals from the driver circuit row by row onto the array of EL units. d, e, The real-time location at a T-junction is displayed on a sleeve. The information is transferred through the Bluetooth and microcontroller modules, and is synchronized with the location map on a smartphone. Scale bars, 1 cm. f, Conceptual image shows \nthat textiles integrated with a display and keyboard can be used as a communication platform. g, Information is input onto the clothing by pressing the keys that are woven into the textile. Scale bars, 2 cm. h, Receiving and sending messages between the integrated textile system and a smartphone. i, j, Expressions of mental states by decoding representative electroencephalogram signals. The words ‘Relaxed’ (i) and ’Anxious’ (j) are displayed on clothes when the dominant brain waves are detected in the low-frequency region (0−10 Hz) and high-frequency region (10−40 Hz), respectively. Scale bars, 5 cm. k, Display textiles could in the future enable communication via clothing. l, Conceptual image of an assistive-technology device, showing brain waves being decoded into messages that are displayed on a shirt made from an integrated textile. \n\nsent, received and displayed between our integrated textile system and a smartphone (Fig. 3h). \n\nTo demonstrate the potential of display textiles in healthcare, we also fabricated a large display textile measuring $24\\mathsf{c m}\\times6\\mathsf{c m}$ (length $\\times$ width) (Extended Data Fig. 10). We collected electroencephalogram signals from volunteers playing a race car game and those who were meditating. The brain waves in relaxed volunteers were mostly low frequency (Fig. 3i), and those in anxious volunteers were mostly high frequency33 (Fig. 3j). We processed the signals on a computer and sent words corresponding to the mental state of the respective volunteers to the microcontroller through the Bluetooth module for display. In the future, together with ways to decode complicated brain waves, we envision display textiles such as ours to become effective assistive-technology communication tools34 (Fig. 3k, l). \n\nIn summary, we present a functional, large-area display textile by weaving conductive and luminescent fibres with cotton yarn to form EL units directly within the textile. Our method is simple and can be used to weave other electronic functions such as a keyboard and power supply into the textile to form a multifunctional integrated textile system for various applications. Because of the network of wefts and warps, each EL unit in our display textile can be uniquely identified and lit in a programmable way using a driver circuit. We show that such an electronic textile can be useful as a communication tool. With the integration of more functionality, we expect these ‘smart textiles’ to form the communication tools of the future. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03295-8. \n\n1. Larson, C. et al. Highly stretchable electroluminescent skin for optical signaling and tactile sensing. Science 351, 1071–1074 (2016). \n2. Tan, Y. J. et al. A transparent, self-healing and high- $-K$ dielectric for low-field-emission stretchable optoelectronics. Nat. Mater. 19, 182–188 (2020). \n3. Tian, X. et al. Wireless body sensor networks based on metamaterial textiles. Nat. Electron. 2, 243–251 (2019). \n4. Chen, G. R., Li, Y. Z., Bick, M. & Chen, J. Smart textiles for electricity generation. Chem. Rev. 120, 3668–3720 (2020). \n5. Weng, W., Chen, P. N., He, S. S., Sun, X. M. & Peng, H. S. Smart electronic textiles. Angew. Chem. Int. Ed. 55, 6140–6169 (2016). \n6. Carey, T. et al. Fully inkjet-printed two-dimensional material field-effect heterojunctions for wearable and textile electronics. Nat. Commun. 8, 1202 (2017). \n7. Kim, J. et al. Ultrathin quantum dot display integrated with wearable electronics. Adv. Mater. 29, 1700217 (2017). \n8. Son, D. et al. An integrated self-healable electronic skin system fabricated via dynamic reconstruction of a nanostructured conducting network. Nat. Nanotechnol. 13, 1057–1065 (2018). \n9. Yin, D. et al. Efficient and mechanically robust stretchable organic light-emitting devices by a laser-programmable buckling process. Nat. Commun. 7, 11573 (2016). \n10. Rein, M. et al. Diode fibres for fabric-based optical communications. Nature 560, 214–218 (2018). \n11. Leber, A. et al. Soft and stretchable liquid metal transmission lines as distributed probes of multimodal deformations. Nat. Electron. 3, 316–326 (2020). \n12. Yang, A. N. et al. Fabric organic electrochemical transistors for biosensors. Adv. Mater. 30, 1800051 (2018). \n13. Hatamvand, M. et al. Recent advances in fiber-shaped and planar-shaped textile solar cells. Nano Energy 71, 104609 (2020). \n14.\t Jinno, H. et al. Stretchable and waterproof elastomer-coated organic photovoltaics for washable electronic textile applications. Nat. Energy 2, 780–785 (2017). \n15. Koo, J. H., Kim, D. C., Shim, H. J., Kim, T. H. & Kim, D. H. Flexible and stretchable smart display: materials, fabrication, device design, and system integration. Adv. Funct. Mater. 28, 1801834 (2018). \n16.\t de Mulatier, S., Nasreldin, M., Delattre, R., Ramuz, M. & Djenizian, T. Electronic circuits integration in textiles for data processing in wearable technologies. Adv. Mater. Technol. 3, 1700320 (2018). \n17.\t Wang, B. H. & Facchetti, A. Mechanically flexible conductors for stretchable and wearable e‐skin and e‐textile devices. Adv. Mater. 31, 1901408 (2019). \n18.\t Prieto-Ruiz, J. P. et al. Enhancing light emission in interface engineered spin-OLEDs through spin-polarized injection at high voltages. Adv. Mater. 31, 1806817 (2019). \n19. Choi, S. et al. Highly flexible and efficient fabric-based organic light-emitting devices for clothing-shaped wearable displays. Sci. Rep. 7, 6424 (2017). \n20.\t Fukagawa, H. et al. Long-lived flexible displays employing efficient and stable inverted organic light-emitting diodes. Adv. Mater. 30, 1706768 (2018). \n21. Conaghan, P. J. et al. Highly efficient blue organic light-emitting diodes based on carbene-metal-amides. Nat. Commun. 11, 1758 (2020). \n22. Koncar, V. Optical fiber fabric displays. Opt. Photonics News 16, 40–44 (2005). \n23.\t Zhang, Z. T. et al. A colour-tunable, weavable fibre-shaped polymer light-emitting electrochemical cell. Nat. Photon. 9, 233–238 (2015). \n24.\t Dias, T. & Monaragala, R. Development and analysis of novel electroluminescent yarns and fabrics for localized automotive interior illumination. Text. Res. J. 82, 1164–1176 (2012). \n25.\t Liang, G. J. et al. Coaxial‐structured weavable and wearable electroluminescent fibers. Adv. Electron. Mater. 3, 1700401 (2017). \n26.\t Hu, D., Xu, X., Miao, J. S., Gidron, O. & Meng, H. A stretchable alternating current electroluminescent fiber. Materials 11, 184 (2018). \n27.\t Zhou, Y. et al. Bright stretchable electroluminescent devices based on silver nanowire electrodes and high-k thermoplastic elastomers. ACS Appl. Mater. Interfaces 10, 44760–44767 (2018). \n28.\t Li, S., Peele, B. N., Larson, C. M., Zhao, H. C. & Shepherd, R. F. A stretchable multicolor display and touch interface using photopatterning and transfer printing. Adv. Mater. 28, 9770–9775 (2016). \n29. Zhang, Z. T. et al. A stretchable and sensitive light-emitting fabric. J. Mater. Chem. C 5, 4139–4144 (2017). \n30.\t Yang, C. H., Chen, B. H., Zhou, J. X., Chen, Y. M. & Suo, Z. G. Electroluminescence of giant stretchability. Adv. Mater. 28, 4480–4484 (2016). \n31. Chen, F. & Xiang, Y. in Luminescent Materials and Applications (ed. Kitai, A.) Ch. 8 (John Wiley & Sons, 2008). \n32.\t Jin, M. L. et al. An ultrastable ionic chemiresistor skin with an intrinsically stretchable polymer electrolyte. Adv. Mater. 30, 1706851 (2018). \n33.\t Müller-Putz, G. R., Riedl, R. & Wriessnegger, S. C. Electroencephalography (EEG) as a research tool in the information systems discipline: foundations, measurement, and applications. Comm. Assoc. Inform. Syst. 37, 912–948 (2015). \n34.\t Voice, speech and language research https://www.nidcd.nih.gov/about/strategic-plan/ 2017-2021-nidcd-strategic-plan#sp22 (National Institute on Deafness and Other Communication Disorders, accessed 8 August 2020). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 \n\n# Article Methods \n\n# Preparation of the transparent conductive weft \n\nPolyurethane ionic gel fibre was spun from the transparent ionicliquid-doped polyurethane gel. Thermoplastic polyurethane (TPU) (Desmopan 2786A, Covestro) was first dissolved in N, N-dimethylformamide (DMF) (Sinopharm) with a weight ratio of 1/4 under mechanically stirring at $80^{\\circ}\\mathbf{C}$ for 2 h. Subsequently, 1-ethyl-3-methylimidazolium:bis (trifluoromethylsulfoyl) imide ([EMIM]+[TFSI]−) ionic liquid (Aladdin) was added to the above TPU–DMF solution for further stirring $(80^{\\circ}\\mathsf{C}$ for 1 h). The ionic gel flake was obtained by totally removing the solvent of DMF in an oven box at $80^{\\circ}\\mathsf{C}$ for $12\\mathsf{h}$ . Then, melt-spinning was carried out using a 3D printing system (3D Bio-Architect work station, Regenovo) with a $0.25\\cdot\\mathrm{mm}$ inner-diameter nozzle. The transparent conductive weft was extruded at a melting zone temperature of $180^{\\circ}\\mathsf{C}$ and cooled at room temperature. To achieve water resistance, a silicone protective layer (1-2577, Dow Corning) was further dip-coated on the transparent conductive wefts. \n\n# Preparation of the luminescent warp \n\nCommercially available ZnS phosphors (Shanghai Keyan Phosphor Technology Co.) were dispersed in waterborne polyurethane (U-9, Shanghai Sisheng Polymer Materials Co.) with a weight ratio of 3/1 by mechanical stirring for 20 min. After degassing in a vacuum oven, the as-prepared mixtures were loaded on the silver-plated nylon yarns (100D, Hengtong X-silver Speciality Textile Co.) on a continuous producing line. Silver-plated yarns were dipped into the ZnS phosphor dispersions and passed through the centre of a scraper ring in inner diameter of $0.32\\mathrm{mm}$ , followed by drying under $120^{\\circ}\\mathrm{C}$ in a $2-\\mathsf{m}$ -long air-dry oven. The movement speed of the yarns was $10\\mathsf{m}\\mathsf{m i n}^{-1}$ . A coating process was conducted three times to prepare the luminescent warp in a diameter of approximately $0.3\\mathsf{m m}$ . To achieve water resistance, a silicone protective layer (1-2577, Dow Corning) was further dip-coated on the luminescent warps. \n\n# Fabrication of the display textile \n\nThe weaving operation of the display textile was made on a rapier loom (Tong Yuan Textile Machinery Co.). The weave diagram is presented in Fig. 1a. Note that other fibre materials such as polyurethane-coated metal wire can be also co-woven inside. \n\n# Structure and performance characterization of the EL units \n\nThe cross-sectional image in Extended Data Fig. 1i of the single EL unit was obtained from scanning electron microscopy (S-4800, Hitachi) operated at 1 kV. The photographs of the textile were captured by a digital camera (D3400, Nikon) unless specified. The transparency of the ionic gel was characterized by an ultraviolet–visible spectrophotometer (UV-2550 Spectrometer, Shimazdu) to scan wavelengths from 450 to $700\\mathrm{nm}$ . The luminance of a single EL unit was detected by a spectrophotometer (Photoresearch PR-680) under an alternating voltage supplied by a function waveform generator (Keysight 33500B Series) connected with a high-voltage power amplifier (610 E, TREK). If not specified, the test parameters of the EL unit were $1.2\\mathsf{V}\\upmu\\mathrm{m}^{-1}$ and 2 kHz, and the intersection area in the EL unit projection was used as the effective device area. The voltage, current and power consumption were measured (34461A digital multimeter, Keysight) using a test circuit (see Extended Data Fig. 4e for details). The electroluminescence mappings of EL units under bending, sliding and rotating were obtained by mapping the photographs in Matlab. The relative electroluminescence intensity was defined according to the grey value. For the statistical analysis of the relative electroluminescence intensity of the units in the display textile (Fig. 1c–g, Extended Data Fig. 3), the grey values of the units were extracted from the photographs by ImageJ. The photographs were captured by a scientific camera (Photometrics Prime BSI) in a dark room. The calibration curve of grey values against actual luminance (detected by the photodetector) was made before statistical analysis (Extended Data Fig. 4f). The grey values were linearly correlated with the luminance of the unit, indicating that the statistical analysis of the emission variations based on the grey values was reliable. The uniformity of the EL unit array was evaluated according to the relative deviation, calculated by $\\mathsf{R D}=((L_{x}-\\bar{L})/\\bar{L})\\times100\\%,$ where $L_{x}$ was the electroluminescence intensity of a single EL unit, and $\\bar{L}$ was the average intensity of 600 units. The stability of the EL unit array was evaluated by counting the electroluminescence intensity variation (calculated as $L/L_{0}$ , where $L_{0}$ and L were the intensities before and after deforming, respectively) of 600 EL units. The temperature changes of the EL units were measured by an infrared camera (PI 640, Optris). \n\n# Washing test of the display textile \n\nAccelerated washing tests (approximately equal to five typical home launderings) were performed in a standard washing machine (SW-12E, Nantong Hongda Experimental Instrument Co.) (Extended Data Fig. 6e) following the ISO 105/C10:2006 and AATCC 61-2013 international standards for fabric washing. The load information includes: $_{\\mathsf{a}4\\mathsf{c m}\\times10\\mathsf{c m}}$ section of the display fabric, $200{\\mathrm{g}}$ of water, and $0.5\\mathrm{wt\\%}$ liquid detergent. We used a washing temperature of $60^{\\circ}\\mathsf C$ and the duration for each wash was $30\\mathrm{min}$ (Extended Data Fig. 6f). The stirring speed was 1,000 rpm. To evaluate the mechanical effects of washing, a total of 10 steel balls (6 mm in diameter) were added into the washing containers. After the washing test, the textiles were rinsed under flowing water and dried at $60^{\\circ}\\mathsf{C}$ for 1 h. The test parameters of the electroluminescence performance were $3\\mathsf{V}\\upmu\\mathrm{m}^{-1}$ and $2\\mathsf{k H z}$ . \n\n# Calculation of the power consumption of an EL unit \n\nThe voltage at certain positions (the root mean square at A, B, C and Ground; refer to Extended Data Fig. 4e) and the resistance of each resistor were first measured. The current across each resistor was calculated as $\\scriptstyle{I=V/R}$ . The current through resistors 2 and 3 was: \n\n$$\nI_{2}{=}\\frac{V_{\\mathrm{AB}}}{R_{2}}{=}I_{3}{.}\n$$ \n\nUsing equation (1), $V_{\\mathrm{AC}}$ was calculated (the voltage across the entire test circuit): \n\n$$\nV_{\\mathrm{AC}}=V_{\\mathrm{AB}}+V_{\\mathrm{BC}}=I_{2}R_{2}+I_{3}R_{3}.\n$$ \n\nThe current across resistor 1 was equal to the total current through the test circuit. On the basis of this equality, the power of the test circuit was: \n\n$$\nP_{\\mathrm{total}}{=}I_{1}V_{\\mathrm{AC}}{\\cos\\theta}.\n$$ \n\nwhere $\\theta$ represents the phase shift between the current and voltage waveforms across the test circuit. This phase shift was measured using an oscilloscope (TDS 2012C, Tektronix). Hence, the real power of the test circuit—which included energy used by the EL unit and the resistors—could be calculated according to: \n\n$$\nP_{\\mathrm{total}}{=}P_{\\mathrm{unit}}{+}P_{\\mathrm{resistor}}{.}\n$$ \n\nThe power consumption of the EL unit was obtained by subtracting the power consumption of the resistor. The power consumed by each resistor was calculated by $P=P R$ . \n\n# Electric field simulation of the EL unit using finite-element method \n\nThe EL unit was constructed in ABAQUS CAE with geometric characteristics given in Extended Data Fig. 1i. Eight-node linear reduced-integration hybrid brick elements (C3D8RH) were used to model the transparent conductive weft of hyperelastic materials. Through a mesh convergence study, 30,284 and 39,840 elements were generated for the luminescent warp and the transparent conductive weft, respectively. \n\nMechanical properties of the materials were defined by directly importing the uniaxial tensile test data (Extended Data Fig. 1). A linear elastic model was used for the luminescent warp. An Ogden hyperelastic model was used for the polyurethane ionic gel fibre with the strain energy potential function W: \n\n$$\nW=\\frac{2\\mu_{1}}{\\alpha_{1}^{2}}(\\overline{{{\\lambda}}}_{1}^{\\alpha_{1}}+\\overline{{{\\lambda}}}_{2}^{\\alpha_{1}}+\\overline{{{\\lambda}}}_{3}^{\\alpha_{1}}-3)+\\frac{1}{D_{1}}(J-1)^{2},\n$$ \n\nwhere $\\overline{{\\lambda}}_{i}$ is the deviatoric principal stretches, $\\overline{{\\lambda}}_{i}=J^{-1/3}\\lambda_{i}$ and $\\lambda_{i}$ is the principal stretches. This form can be degenerated into neo-Hookean form of potential energy when $\\alpha_{1}=2$ . \n\nAs mentioned above, periodic boundary conditions were imposed along the axial direction of the transparent conductive weft. The axial length of an EL unit was fixed, because the weft was kept tight during the weaving process. Contact between the transparent conductive weft and the luminescent warp was defined as default hard contact. The loads imposed on both ends of the transparent conductive weft were estimated by outputting the reaction force of the polyurethane ionic gel fibre under a displacement of $0.48\\mathsf{m m}$ . \n\nStatic electric analyses were then conducted on the deformed models to obtain the electric fields in the ZnS phosphor layer. The transparent conductive weft was grounded and 90 V electric potential was imposed on the core conductive yarn of luminescent warp. The dielectric constant of the luminescent layer was $3.621\\times10^{-11}\\mathrm{F~m^{-1}}$ . \n\n# Fabrication of the textile keyboard \n\nThe textile keyboard was based on a jacquard method by weaving carbon fibres (1K, TORAY), silver-plated yarns and cotton yarns according to the weave diagram in Extended Data Fig. 7a. Pressing a key activates it, and releasing turns it off (Extended Data Fig. 7d, e). The keyboard works by reading the voltage between the metallic and carbon fibres (sample voltage, $V_{s})$ ) under an applied voltage $(V_{\\mathrm{cc}})$ of ${5}\\mathrm{v}.$ Each key in the $4\\times4$ keyboard is distinguished by the different sample voltage recorded when the key is pressed (Extended Data Fig. 7f). \n\n# Fabrication of the energy harvesting and storing textile \n\nTi wire (diameter of $127\\upmu\\mathrm{m}.$ , Alfa Aesar) was used as the substrate of the photoanode. First, the Ti wire was sequentially cleaned by sonication in deionized water, acetone and isopropanol for 5 min each. Then $\\mathrm{TiO}_{2}$ nanotubes were grown on the Ti wire by an anodic oxidation in a water bath. A ${\\phantom{-}}_{1}0.3\\mathsf{w t}\\%{\\mathsf{N}}{\\mathsf{H}}_{4}{\\mathsf{F}}$ /ethylene glycol (Sinopharm) solution containing $8{\\sf w t\\%H_{2}O}$ was prepared as the electrolyte. The growth was operated in a two-electrode system with the Ti wire as the anode and a Pt plate as the cathode at 60 V for 2 h. The modified Ti wire was washed and annealed at $500^{\\circ}\\mathrm{C}$ for $60\\mathrm{{min}}$ . After cooled to $110^{\\circ}\\mathrm{C}$ in the furnace, the wire was immersed in Z907 (Shanghai MaterWin New Materials Co.) solution (a $0.3\\mathsf{m M}$ solvent mixture of dehydrated acetonitrile (Adamas) and tert-butanol (Sinopharm) with an equal volume ratio) for 16 h. Next, CuI was drop-coated onto the modified Ti wire in a glovebox at $110^{\\circ}\\mathsf{C}$ . A CuI solution was prepared by dissolving 0.16 M cuprous iodide (Aladdin), 1-methyl-3-ethylimidazolium thiocyanate (Lanzhou Greenchem ILs) and $0.2\\mathsf{m M}$ 4-tert-butylpyridine (Adamas) in acetonitrile. Owing to the close contact between the photoanode wefts and the conductive yarns, the electric outputs of the photovoltaic textile remained stable when it was bent from $0^{\\circ}$ to $180^{\\circ}$ (Extended Data Fig. 8g). Even after 10,000 cycles of bending, the electric output and structure of the photoanode fibre were well maintained (Extended Data Fig. 8h, i). The bending radius was $4\\mathsf{m m}$ . \n\nThe aqueous zinc-ion battery fibre was composed of a $\\ensuremath{\\mathsf{M n O}}_{2}$ coated carbon nanotube fibre cathode, a zinc wire anode, and gelatin $/Z_{\\mathrm{nSO_{4}}}$ water-based gel electrolyte35. A carbon nanotube fibre was first synthesized by the floating-catalyst method36. For the fibre cathode, $\\ensuremath{\\mathsf{M n O}}_{2}$ was electrodeposited onto the carbon nanotube fibre through a scalable electrodeposition method (pulse mode 1.5 V for 1 s and 0.7 V for 10 s) in electrolyte containing $\\mathrm{0.1MMn(Ac)_{2}{\\cdot}4H_{2}O}$ (Aladdin) and $0.1\\ensuremath{\\mathrm{M}}\\ensuremath{\\mathsf{N a}}_{2}\\ensuremath{\\mathsf{S}}\\ensuremath{\\mathbf{O}}_{4}$ (Sinopharm) with an $\\mathbf{Ag/AgCl}$ reference electrode and a Pt counter electrode. The $\\mathbf{MnO}_{2}$ loading mass was $0.5\\mathsf{m g c m}^{-1}$ for the cathode fibre. The zinc wire, with a diameter of $\\cdot0.5\\mathsf{m m}$ , was polished and rinsed before use. The cathode and anode wires were uniformly coated with gel electrolyte and then twisted together. The gel electrolyte was prepared by first dissolving $1.0{\\mathrm{g}}$ gelatin (Sinopharm) and ${\\bf0.1g N a_{2}B_{4}O_{7}}$ (Aladdin) in $10\\mathrm{ml}$ deionized water at $80^{\\circ}\\mathsf C$ Then 10 m $\\mathsf{\\iota M Z n S O_{4}{\\cdot}7H_{2}O}$ (Aladdin) and 1 m $\\mathsf{_{I M M n S O_{4}}{\\cdot}H_{2}O}$ (Aladdin) were added under stirring until a homogenous solution was formed. The as-fabricated battery was dried at room temperature. The gel electrolyte acted as both an electrolyte and separator. The battery, composed of the twisted cathode and anode wires, was put into a flexible poly(vinyl chloride) (PVC) tube (ranging from hundreds of micrometres to several millimetres in diameter) and sealed by resin adhesive at the terminals of the tube. The PVC-encapsulated battery fibre withstood bending and retained a capacity of $580\\%$ after 10,000 cycles of bending (Extended Data Fig. 8m, n). The bending radius was $4\\mathsf{m m}$ . \n\nSilver-plated nylon yarns were woven in the warp direction as the counter electrodes for the energy harvesting part and the electrical connections for the energy storage part. The cotton threads, modified photoanode fibres and zinc-ion battery fibres were then alternately woven in the weft direction. Current density–voltage curves of the energy harvesting part were recorded by a Keithley 2400 source meter under the illumination $(100\\mathrm{{mwcm}^{-2},}$ ) of simulated AM1.5 solar light from a solar simulator (Oriel-Sol3A 94023A, equipped with a 450 W Xe lamp and an AM1.5 filter). The area marked by the dashed line in Extended Data Fig. 8a was used to calculate the current density. Electrochemical measurements were performed on an electrochemical workstation (CHI 660a). \n\n# Fabrication of the integrated textile system \n\nDifferent electronic textiles were arranged on a piece of cloth by changing functional fibres during the weaving process, which were integrated on a jacket by hot-melt adhesive or sewing (Extended Data Fig. 9a–c). The microcontroller of textile electronics was STM32F103T8U6, an ARM 32-bit Cortex TM-M3 CPU with QFN36 package (DM14580). The single-bus detection of the keyboard was realized using an analogue-to-digital converter to sample the keyboard resistance. The driving circuit of the display textile was provided by Shanghai Mi Fang Electronics Co. The communication between the integrated textile system and the mobile phone was realized using a Bluetooth module (HC-05). The power supply of the integrated textile system was provided by battery fibres that stored energy from the photovoltaic textile module. For the integration circuit, the conductive wefts and luminescent warps of the display textile were connected to the display driver module by connecting lines named as column and line buses. The display driver module and microcontroller (integrated with reset and clock modules) were connected to the energy storage module (fibre batteries). The keyboard and Bluetooth modules were connected to the microcontroller. Display driver module, microcontroller and Bluetooth module were connected to form the external controlling device system, which was inserted in a pocket on the arm sleeve (Extended Data Fig. 9b). \n\nTo connect the circuits to the textile, flexible and thin conductive fibres serving as connecting lines were sewn into the textile using a digital sewing machine (Extended Data Fig. 9c). The conductive fibres were neatly arranged in the textile according to the designed sewing circuit patterns (Extended Data Fig. ${\\mathfrak{s d}}{\\mathfrak{-g}}{\\dot{}}$ ). Thereafter, the conductive fibres were carefully connected to the warp and weft electrodes of the display textile using mature welding equipment. \n\n# Article \n\nThe connecting points remained robust even when bent (Extended Data Fig. 9h, i). \n\n# Collection and decoding of electroencephalogram signals \n\nThe signals of volunteers were collected by a wearable recorder (MindWave Mobile 2, Neurosky). The volunteers were asked to play a car racing game to be in an anxious mental state and lay back in meditation to be in a relaxed mental state. The signals were recorded in real time and collected on a computer. After downsampling to $100{\\scriptstyle{\\mathsf{H z}}}$ , the signals were filtered by 4th-order IIR bandpass filters with bandwidth of $0.1{-}48\\mathsf{H z}$ . The time-domain signals were transferred to spectrogram by fast Fourier transform. \n\n# Data availability \n\nThe data that support the findings of this study are available from figshare at https://figshare.com/articles/dataset/Source_data_Display_textile_rar/13573205. Source data are provided with this paper. \n\n# Code availability \n\nThe codes used for the integrated textile system in this study are available at https://github.com/hnsyzjianghan/textiles_display. \n\n35.\t Wang, Z. F. et al. A flexible rechargeable zinc-ion wire-shaped battery with shape memory function. J. Mater. Chem. A 6, 8549–8557 (2018). \n36.\t Lee, J. et al. Direct spinning and densification method for high-performance carbon nanotube fibers. Nat. Commun. 10, 2962 (2019). \n\nAcknowledgements This work was supported by MOST (2016YFA0203302), NSFC (21634003, 22075050, 21805044), STCSM (20JC1414902, 18QA1400700, 19QA1400800) and SHMEC (2017-01-07-00-07-E00062). Part of the sample fabrication was performed at the Fudan Nano-fabrication Laboratory. We thank Shanghai Mi Fang Electronics Co., Ltd for technical support of the display driving circuits, Idea Optics Co., Ltd for offering test instruments, J. Zhao for assistance in textile weaving, and A. L. Chun of Science Storylab for critically reading and editing the manuscript. \n\nAuthor contributions H.P. and P.C. conceived and designed the research project. X. Shi., Y.Z. and P.Z. performed the experiments on the display textile, keyboard and integration systems. J.S., Y.Y. and Q.T. performed the simulation. Z.G. performed the experiments on photovoltaic textiles. M.L. and J. Wang performed the experiments on energy storage fibres. J. Wu and B.W. performed the durability test. X. Shi, Y.Z., P.Z. and X.X. analysed the data. B.Z., X. Sun., L.Z., Q.P., D.J. and all other authors discussed the data and wrote the paper. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-03295-8. Correspondence and requests for materials should be addressed to P.C. or H.P. Peer review information Nature thanks Tilak Dias, Xiaoming Tao and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\nExtended Data Fig. 1 | Mechanical characterization of transparent conductive weft, luminescent warp and their contact area. a, A photograph of transparent conductive wefts on a spool. Scale bar, 2 cm. b, Stress–strain curve of polyurethane ionic gel fibre. c, Transmittance of ionic gel film with thickness of $250{\\upmu\\mathrm{m}}$ . Inset, transparent conductive weft wound on a spool. Scale bar, 2 mm. d, Photograph of luminescent warps on a spool. Scale bar, 2 cm. e, Force–strain curve of silver-plated yarn. f, Stress–strain curve of ZnS \n\n![](images/5557d4345214b20b6c5702c350bade3a800f1d678e5338c476328f9848700a1c.jpg) \nphosphor layer. g, Comparison of mechanical properties of silver-plated yarn, ZnS phosphor layer and polyurethane ionic gel fibre. h, Deformation and stress simulation in an EL unit. i, Cross-sectional scanning electron microscope image of an EL unit after embedding in resin. Scale bar, $200\\upmu\\mathrm{m}$ . j, k, Photographs of display textiles co-woven with commercial nylon (PA) and polyester (PE) fibres, respectively. Scale bars, from left to right, 2 cm, 2 cm and 5 cm. \n\n![](images/56fbad50f542746dfbd7b823a4795b8af7147f24597fe1c18ef1d0edf6b48096.jpg) \n\nExtended Data Fig. 2 | Longitudinal and circumferential homogeneity of luminescent warp. a, Schematic illustration of continuous fabrication of luminescent warp. b, Optical image of luminescent warp. Scale bar, $1\\mathsf{m m}$ . c, Cross-sectional image of luminescent warp. Scale bar, $200\\upmu\\mathrm{m}$ . d, Photographs of \\~100-m-long luminescent warp arranged in parallel on a board in a salt water pool. Scale bar, $10\\mathrm{cm}$ . The luminescent warp was illuminated by applying an alternating voltage to the luminescent warp and salt water. The magnified area indicates the homogeneous luminescence along the fibre. Scale bar, $5\\mathsf{m m}$ . e, Multicolour luminescent warps wound on a glass stick and illuminated in salt water. Scale bars, $5\\mathsf{m m}$ . f, Schematic of longitudinal and circumferential direction of luminescent warp. g, Luminance distribution along the length of luminescent warp. Error bars represent the standard deviations of the results from three samples. h, Luminance distribution around the luminescent warp circumference. i, Uneven luminescent layer in the case without using the scraping micro-pinhole. Scale bars, 1 mm. j, Photograph of the display textile woven from luminescent warps with uneven coating. Scale bar, $5\\mathsf{m m}.\\mathbf{k}$ , Relative emission intensities of the $10\\times10$ EL unit array in j. \n\n![](images/aa6739633ebfac5058cd13912328c510cbac0a7f4bd8ae147eda1369e7b0afe2.jpg) \nExtended Data Fig. 3 | Durability and stability of the display textile upon folding. a–l, Photographs (a–d), statistical distribution of variations in luminance of EL units of a display textile containing 600 EL units (e–h), and variation of the relative luminescent intensity for the EL units at the folding lines (i–l) when the textile was successively folded along the vertical middle lin \n(a, e, i), horizontal middle line (b, f, j) and diagonal lines (c, g, k, d, h, l) for 10,000 cycles each. The bending radius was 1 mm. The majority of the EL units showed little change. Scale bars, $5c m$ . Error bars are standard deviations of the results from six samples. \n\n![](images/728543402cd0995dbc0f5372a9b7edca2e7baf035a13a1bcdff68ded9c5e8044.jpg) \n\nExtended Data Fig. 4 | Electroluminescence performance of the display textile and EL unit. a, Luminance–voltage curve of the display textile based on the projected area of the textile. b, c, Higher applied voltage (b) and frequency (c) increase the luminance of the EL unit. Frequency used in b was ${2,000}\\mathrm{Hz}$ . Voltage applied in c was $1.2\\mathsf{V}\\upmu\\mathrm{m}^{-1}$ . d, e, Current density–voltage (d) and power– luminance (e) characteristics of the EL unit. The inset of e shows the test circuit for measuring the power consumption of the EL unit. f, Calibration curve showing that the grey values extracted from photographs obtained from a \n\ncamera are linearly correlated with the actual luminance of the EL unit as detected by a photodetector. g, Thermal images of an EL unit illuminated for increasing durations (under a power of $-300\\upmu\\mathrm{W}$ ). The arrows indicate the position of the EL unit. Scale bar, $5\\mathsf{m m}$ . h, Local temperature variations of EL units under a power of $-300\\upmu\\mathrm{W}.$ i, Luminance–frequency curve of the EL unit working at $35\\mathrm{V}.$ . Thickness of the luminescent layer is ${\\sim}30\\upmu\\mathrm{m}$ . Error bars represent the standard deviations of the results from at least three samples. \n\n![](images/d3ef59dc1b7244ed9cdbde4781679accd5196b3cc079545ddc97cbbea23a5082.jpg) \n\nExtended Data Fig. 5 | Comparison of electric field distribution of curved and planar contact areas. Electric field distribution in woven EL unit (a–c) and traditional planar sandwiched electroluminescent devices (d–f). a, d, Electric field distribution. b, e, Statistics of the simulation elements on contact area \n\naccording to the electric field values. c, f, Visualization of the electric field values by the height of bars. g, Electric field distributions of EL unit along with increasing contact areas. \n\n# Article \n\n![](images/7e868045449cdf05a54f4f5a6c4ac82252e6facdc8d317cc8b6929a13a54ba78.jpg) \n\nExtended Data Fig. 6 | Durability of polyurethane ionic gel fibre and EL units. a, Luminance variations when the transparent conductive weft is rolled around its central axis. $L_{0}$ and L correspond to the electroluminescence intensity before and after deformation, respectively. b, c Variation of weight (b) and electrical resistance (c) for the polyurethane ionic gel fibre in open air at room temperature $(-25^{\\circ}\\mathsf{C})$ . Here $\\boldsymbol{w}_{0}$ and $w$ correspond to the weights before and after exposure to the air, respectively, and $R_{0}$ and $R$ correspond to the electrical resistances before and after exposure to the air, respectively. d, Electroluminescence performance of EL units stored in open air. $L_{0}$ and L correspond to the electroluminescence intensity before and after exposure to the air, respectively. e, Photograph of the standard washing machine used in the washing test. Scale bar, $20\\mathrm{cm.}$ f, Photographs of the washing container before and after washing. Scale bars, 5 cm. g, Photographs (top) and emission images (bottom) show that the luminescence of EL units after 100 cycles of washing (30 min per cycle) is similar to the original unwashed fabric. Scale bars, 1 mm. h, Quantitative measurement of the luminance of EL units. Little change is seen over 100 cycles of washing and drying. $L_{0}$ and L correspond to the electroluminescence intensities before and after washing, respectively. Error bars are standard deviations of the results from at least three samples. \n\n![](images/c1dae1f424378667c84a6dd149c93a88920047725dee0989e18268a1ba94d1f0.jpg) \n\nExtended Data Fig. 7 | Characterization of the textile keyboard. a, Weave diagram of the textile keyboard (yellow: Ag-plated fibre, black: carbon fibre, blue: cotton yarn, grey: cotton yarn). b, Photograph and electrical connection of a $4\\times4$ textile keyboard. The red squares indicate the positions of keys. Scale bar, $5\\mathsf{m m}$ . c, Equivalent circuit of a $4\\times4$ keyboard. This keyboard worked by reading the voltage between the metallic and carbon fibres (sample voltage, Vs) \n\nat an applied voltage $(V_{\\mathrm{cc}})$ of 5 V. d, Pressing responses of a key with resistance variations that were greater than four orders of magnitude. e, Working mechanism of the textile keyboard. f, Voltages $(V_{s})$ recorded by pressing individual keys one by one. The correspondence between the key position and its characteristic $V_{\\mathrm{s}}$ are indicated by the coordinates in b and f. \n\n![](images/74e24a1c3cee7a1d40eb603acd1ba84c1b7a244566b62527ca9585883625ad08.jpg) \n\nExtended Data Fig. 8 | Characterization of the textile power supply system. a, Schematic of a woven photovoltaic unit. b, Current density–voltage characteristics of the photovoltaic unit, exhibiting a short-circuit current density of $6.32\\mathsf{m A c m}^{-2}$ and an open-circuit voltage of 0.45 V. c, Schematic of the woven photovoltaic units connected in parallel. d, Current–voltage curve of the photovoltaic textile with increasing numbers of photoanode wefts connected in parallel. e, Schematic of the woven photovoltaic units connected in series. f, Current–voltage curve of the photovoltaic textile with increasing numbers of photoanode wefts connected in series. g, h, Photovoltaic performances at different bending angles $\\mathbf{\\sigma}(\\mathbf{g})$ and bending cycles at bending angle of $45^{\\circ}\\left(\\mathbf{h}\\right)$ show $<10\\%$ variation. $V_{\\mathrm{oc0}}$ and $V_{\\mathrm{oc}}$ represent the open-circuit voltage before and after bending, respectivel $\\prime;J_{\\mathrm{sc0}}\\mathbf{and}J_{\\mathrm{sc}}$ correspond to the photocurrent density before and after bending, respectively; and $\\eta_{\\mathrm{o}}$ and $\\eta$ \n\nrepresent the photon-to-electron conversion efficiency before and after bending, respectively. i, Scanning electron microscope images of the photoanode fibre before and after 10,000 cycles of bending appear similar. Scale bars, from left to right, ${50}\\upmu\\mathrm{m}$ and ${5}\\upmu\\mathrm{m}$ . j, Galvanostatic charge/discharge curves at $200\\mathsf{m A}\\mathsf{g}^{-1}$ (based on the active material of the cathode). The battery fibre exhibited a mass capacity of $176.9\\mathsf{m A h g^{-1}}$ . k, Schematic of the working mechanism of the energy harvesting and storage module. l, Photocharge and discharge curves of the battery fibre. Six photovoltaic units in series under illumination are used to charge zinc-ion battery fibres. The battery fibres are discharged to an external circuit at a current of $80\\upmu\\mathrm{A}$ . m, n, Capacity retention of the battery fibre after bending at different angles $\\mathbf{\\Pi}(\\mathbf{m})$ and over 10,000 cycles of bending at a fixed bending angle of $45^{\\circ}\\left(\\mathbf{n}\\right)$ . Error bars are standard deviations of the results from three samples. \n\n![](images/95d9711734d1cd488da56e972fb194f6e5f862f1cdfa318f37f45fb7032b2ea2.jpg) \n\nExtended Data Fig. 9 | Fabrication of the integrated textile system. a, Schematic of the circuit design for the integrated textile system. b, Photograph of an integrated textile system woven on a sleeve. Scale bar, 5 cm. c, Photograph shows conductive fibres serving as connecting lines are sewn into the textile using a digital sewing machine. Scale bar, $5\\mathsf{m m}$ . \n\nd, Photograph with outline showing the integrated circuit in the textile system. Scale bar, 5 cm. e–g, Magnified views of the connecting lines sewn into the textile. Scale bars, 2 cm. h, i, Photographs show that the folded connecting points remain sturdy. Scale bars, 1 cm. \n\n# Article \n\n![](images/f31ea6de15132bf21f38fb84fccce75e023a8173892755adaa27bb1aca448f79.jpg) \nExtended Data Fig. 10 | A large display textile measuring 24 cm $\\times$ 6 cm (length $\\times$ width). Scale bars, 10 cm. \n\n
Extended Data Table1| Comparison of the current electroluminescent textile technologies
EL textileThin film19Optical fibre22 Light sourceEL fibre23-26EL unit (this work)
MaterialPET substrate, cometaleeotrdenic semiconductorsPMMA or silicametal wire, light-emitig olimer ZnS phosphorzns hosphor conductive fibre
Fabricationvacum deapisition,hot drawingtwismntiof fere awft-warng
Working modepixel displaylimitation to lighting ofwovenpattern through extralight sourceslimitation to lighting of wovenpatternpixel display
Breathabilitylowhighhighhigh
Flexibilityfunctiondegradation under high bending curvatureintextilerigid, brittleflexibleflexible
Washing stabilityN/AN/AN/Astable
\n\n\\*PET, polyethylene terephthalate; PMMA, polymethyl methacrylate. Refs. 19,22–26. " + }, + { + "id": "10.1038_s41467-021-24511-z", + "DOI": "10.1038/s41467-021-24511-z", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-24511-z", + "Relative Dir Path": "mds/10.1038_s41467-021-24511-z", + "Article Title": "Interfacial chemical bond and internal electric field modulated Z-scheme Sv-ZnIn2S4/MoSe2 photocatalyst for efficient hydrogen evolution", + "Authors": "Wang, XH; Wang, XH; Huang, JF; Li, SX; Meng, A; Li, ZJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Construction of Z-scheme heterostructure is of great significance for realizing efficient photocatalytic water splitting. However, the conscious modulation of Z-scheme charge transfer is still a great challenge. Herein, interfacial Mo-S bond and internal electric field modulated Z-scheme heterostructure composed by sulfur vacancies-rich ZnIn2S4 and MoSe2 was rationally fabricated for efficient photocatalytic hydrogen evolution. Systematic investigations reveal that Mo-S bond and internal electric field induce the Z-scheme charge transfer mechanism as confirmed by the surface photovoltage spectra, DMPO spin-trapping electron paramagnetic resonullce spectra and density functional theory calculations. Under the intense synergy among the Mo-S bond, internal electric field and S-vacancies, the optimized photocatalyst exhibits high hydrogen evolution rate of 63.21mmol.g(-1)h(-1) with an apparent quantum yield of 76.48% at 420nm monochromatic light, which is about 18.8-fold of the pristine ZIS. This work affords a useful inspiration on consciously modulating Z-scheme charge transfer by atomic-level interface control and internal electric field to signally promote the photocatalytic performance. The construction of Z-scheme heterostructures is of great significance for realizing efficient photocatalytic water splitting. Here, the authors report an interfacial chemical bond and internal electric field modulated Z-Scheme S-v-ZnIn2S4/MoSe2 photocatalyst for efficient hydrogen evolution.", + "Times Cited, WoS Core": 714, + "Times Cited, All Databases": 722, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000672713100001", + "Markdown": "# Interfacial chemical bond and internal electric field modulated Z-scheme Sv-ZnIn2S4/MoSe2 photocatalyst for efficient hydrogen evolution \n\nXuehua Wang1, Xianghu Wang2, Jianfeng Huang3, Shaoxiang Li4, Alan Meng2✉ & Zhenjiang Li 1 ,4,5✉ \n\nConstruction of Z-scheme heterostructure is of great significance for realizing efficient photocatalytic water splitting. However, the conscious modulation of Z-scheme charge transfer is still a great challenge. Herein, interfacial Mo-S bond and internal electric field modulated Z-scheme heterostructure composed by sulfur vacancies-rich $Z n|{\\mathsf{n}}_{2}{\\mathsf{S}}_{4}$ and ${\\mathsf{M o S e}}_{2}$ was rationally fabricated for efficient photocatalytic hydrogen evolution. Systematic investigations reveal that Mo-S bond and internal electric field induce the Z-scheme charge transfer mechanism as confirmed by the surface photovoltage spectra, DMPO spin-trapping electron paramagnetic resonance spectra and density functional theory calculations. Under the intense synergy among the Mo-S bond, internal electric field and S-vacancies, the optimized photocatalyst exhibits high hydrogen evolution rate of $63.21\\mathsf{m m o l}\\cdot\\mathsf{g}^{-1}\\cdot\\mathsf{h}^{-1}$ with an apparent quantum yield of $76.48\\%$ at 420 nm monochromatic light, which is about 18.8-fold of the pristine ZIS. This work affords a useful inspiration on consciously modulating Z-scheme charge transfer by atomic-level interface control and internal electric field to signally promote the photocatalytic performance. \n\nW ith the rapid development of the industrial society, the energy crisis and environmental pollution issues are getting more and more serious. Therefore, finding an alternative energy source is of great significance for the long-term development of human society. Hydrogen $\\left(\\operatorname{H}_{2}\\right)$ has long been considered as an excellent candidate to substitute the fossil fuel, due to its advantages of clean, renewable, high energy density, and transportability1–3. However, at present, the low efficiency, high energy consumption, and environmentally hazardous $\\mathrm{H}_{2}$ production technology seriously restrict the commercial application of hydrogen energy. By comparison, photocatalytic water splitting can tactfully convert the sustainable solar energy to $\\mathrm{H}_{2}$ energy without discharging any pollutant during the whole process, thus has been considered as a sustainable and promising technique1,4,5. \n\nIn the past few years, metal chalcogenide semiconductor photocatalyst, such as $Z\\mathrm{nS}$ , CdS, PbS, $\\bar{Z_{\\mathrm{nIn}_{2}S_{4}}}$ , have absorbed extensively attention due to the favorable visible-light response ability6–8. $\\mathrm{\\ZnIn}_{2}\\mathrm{S}_{4}$ is a typical ternary layered metal chalcogenide semiconductor with adjustable band gap of $2.06{\\sim}2.85\\mathrm{eV}$ , besides, the conduction band is about $-1.21\\mathrm{eV}$ , suggesting the intense reducing capacity of the photogenerated electrons9. In addition to the suitable band structure, $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ also possess the prominent photo-stability, environmental and human friendliness in comparison to CdS and $\\mathrm{Pb}{\\mathsf{S}}^{10}$ . Whereas, the photocatalytic property of the single $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ is unsatisfying because of the serious carrier recombination. For pursuing the higher photocatalytic activity of $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}.$ , researchers have thrown tremendous efforts, including phase and morphology regulating, elements doping, cocatalystloading, defect engineering, and heterojunction constructing11–15. Among these strategies, defect engineering and heterojunction constructing are the two-effective means. In photocatalytic field, introducing anion vacancies in semiconductor can not only enhance the light absorption ability of the pristine semiconductor, but also introduce mid gap states in the band gap, which can serve as effective electron “traps” accelerating the separation efficiency of photocarriers16. Nevertheless, the excessive defects in photocatalyst can also act as the recombination sites of photocarriers, thus deteriorating the photocatalytic performance17. Therefore, regulating the defect in an appropriate concentration would ensure the high activity and stability of photocatalyst18. In addition, as known from the reported literatures, the only defect introduction is not enough for realizing efficient photocatalytic property. \n\nHeterojunction constructed by coupling different materials with diverse energy level structure is another effective means to improve photocatalytic performance19–23. In recent years, Z-scheme heterostructure, especially the direct Z-scheme heterostructure, has become one of the most effective strategy for obtaining high-efficient photocatalyst 22,23. For example, Huang et al. reported a $\\mathrm{HxMoO}_{3}@\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ direct Z-scheme photocatalyst for efficient hydrogen production. The results demonstrates that the $\\mathrm{H_{x}M o O_{3}}@\\mathrm{ZnIn}_{2}\\mathrm{S_{4}}$ presents a 10.5 times higher $\\mathrm{H}_{2}$ -production activity $(5.9\\mathrm{mmol{\\cdot}g^{-1}{\\cdot}h^{-1}})$ than pristine $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}{}^{24}$ . To fabricate the $Z$ -scheme heterostructure, the primary premise is the matching band structure, in which the conduction band of one semiconductor should locate as close to the valence band of another semiconductor as possible. It is reported that the conduction band potential of $\\mathrm{MoSe}_{2}$ (about $-\\bar{0.45}\\mathrm{eV}^{25})$ is lower than the conduction band of $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ , but very close to its valence band $(0.99\\ \\mathrm{eV}^{9})$ , which suggests that the photogenerated electrons in the conduction band of $\\mathrm{MoSe}_{2}$ are likely to recombine with the photogenerated holes in the valence band of $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ following Z-scheme pathway. However, as known from the current literatures, $\\mathrm{MoSe}_{2}$ can only play the role of cocatalyst in $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ instead of realizing Z-scheme charge transfer26,27. The question is that there is no direct and intimate interfacial connection between $\\mathrm{MoSe}_{2}$ and $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ . The poor interfacial contact is like erecting a “wall” between the two semiconductors, seriously preventing the trajection of charge flow. Therefore, the formation of intimate interface contact became the hinge to Z-scheme photocatalyst fabrication. \n\nRecently, defect-induced heterostructure construction have opened thought for assembling the heterostructure with specific atomic-level interfacial contact22. Its basic principle lies on that the defective sites with abundant coordinative unsaturation atoms and delocalize local electrons can act as the anchoring sites for other semiconductors to form a unique heterostructure contact interface with chemical bond connection28. The interfacial chemical bond can act as specific “bridge” accelerating charge transfer between semiconductors. In addition to the intimate interface combination, internal electric field also emerging as a viable strategy to promote Z-scheme charge transfer29. Under the effect of internal electric field, the photogenerated electrons in the conduction band of one semiconductor with lower Fermi level could directionally transfer to the valence band of another semiconductor with higher Fermi level, thus realizing the Z-scheme charge transfer30. Inspired by the above considerations, an efficient Z-scheme photocatalyst can be obtained through establishing intimate interfacial chemical bond connection between two semiconductors with specific band structure and Fermi level. Up to now, however, the interfacial bonding and internal electric field are always considered separately, the jointly modulation and their synergy effect on photocatalytic performance still remains a challenging task. \n\nHerein, taking S vacancies-rich $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ ( $\\mathrm{\\langleS_{v}-Z I S\\rangle}$ and $\\mathrm{MoSe}_{2}$ as model material, through a defect-induced heterostructure constructing strategy, an interfacial Mo-S bond and internal electric field modulated Z-scheme $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ photocatalyst was fabricated. The addition of hydrazine monohydrate $(\\mathrm{\\ddot{N}}_{2}\\mathrm{H}_{4}\\cdot\\mathrm{H}_{2}\\mathrm{O})$ provides pivotal prerequisite for the formation of S vacancies and coordinative unsaturation S atoms, where the S vacancies can enhance light absorption and facilitate photocarriers separation, while the abundant coordinative unsaturation S atoms can serve as anchoring sites for Mo atoms, thus contributing the formation of Mo-S bond and the in-situ growth of $\\mathrm{MoSe}_{2}$ on the surface of $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ (as showing in Fig. 1). During photocatalytic reaction, the internal electric field induced by the different work function between $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{IS}}$ and $\\mathrm{MoSe}_{2}$ provide intense driving force steering the photogenerated electrons on the conduction band of $\\mathrm{MoSe}_{2}$ transfer to the valence band of $S_{\\mathrm{v}^{-}}Z\\mathrm{IS}$ , that’s the Z-scheme mechanism. Meanwhile, the interfacial Mo-S bond afford the fast pathways for charge transfer from $\\mathrm{MoSe}_{2}$ to ${\\sf S}_{\\mathrm{v}^{-}}\\mathrm{ZIS},$ thus accelerating the Z-scheme charge transfer process. This work provides a constructive reference for atomic-level interfacial and internal electric field regulating Z-scheme heterostructure for efficient photocatalytic reaction. \n\n# Results and discussion \n\nCharacterizations of as-prepared photocatalysts. The morphology and microstructure of the as-synthesized ZIS, $\\mathrm{MoSe}_{2}$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ (the optimized sample) were analyzed by the SEM, TEM and HRTEM characterizations. As observed in Fig. 2a, the basic morphology of ZIS is flower-like hierarchical microsphere composed by plenty of intersecting nanoflakes, which benefits to the exposure of active surface. The TEM image in Fig. 2b further reveals the hierarchical microsphere of ZIS assembled by nanoflakes. Furtherly, as shown in the HRTEM image in Fig. 2c, the clear lattice stripes with interplanar spacing (d) of $0.32\\mathrm{nm}$ can be well indexed to the (102) lattice plane of hexagonal $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ (JCPDS:65-2023)9. Figures S1–S2 are the elements mapping and \n\n![](images/0411b0a16677cba4657d34ea5a1b5e3c24182638a6737aec7638dbce23dc69c5.jpg) \nFig. 1 Synthesis process. Schematic presentation of the synthetic route of $\\mathsf{S}_{\\mathsf{v}}–\\mathsf{Z n l n}_{2}\\mathsf{S}_{4}$ and $\\mathsf{S}_{\\mathrm{v}}{-}Z\\mathsf{n}|\\mathsf{n}_{2}\\mathsf{S}_{4}/\\mathsf{M}\\mathsf{o}\\mathsf{S}\\mathsf{e}_{2}$ heterostructure. \n\n![](images/d5192608200d14c758b0bfee6bb6fc333119af90788a397c814184ea3be232e2.jpg) \nFig. 2 Morphology and composition characterizations. a–c SEM, TEM, and HRTEM pictures of ZIS, d–f TEM and HRTEM images of ${\\sf M o S e}_{2},$ g–j SEM, TEM, and HRTEM images of $\\mathsf{S}_{\\mathrm{v}}{-}Z|\\mathsf{S}/\\mathsf{M}\\circ\\mathsf{S}\\mathrm{e}_{2}$ , k–p EDS and elements mapping of Zn, In, S, Mo, and Se in $\\mathsf{S}_{\\mathrm{v}}{-}Z|\\mathsf{S}/\\mathsf{M}\\circ\\mathsf{S}\\mathbf{e}_{2},$ $\\bullet\\times\\mathsf{R D}$ patterns of ZIS, $S_{\\mathrm{v}}{-}Z|S,$ ${\\mathsf{M o S e}}_{2}$ and $\\mathsf{S}_{\\mathrm{v}}{-}Z|\\mathsf{S}/\\mathsf{M}\\circ\\mathsf{S}\\mathsf{e}_{2},$ , r Raman spectra of $\\mathsf{S}_{\\mathsf{v}}$ -ZIS, ${\\mathsf{M o S e}}_{2}$ and $\\mathsf{S}_{\\mathrm{v}}{-}Z|\\mathsf{S}/\\mathsf{M o S e}_{2},$ and s EPR spectra of ZIS, $S_{\\mathrm{v}}{-}Z|S$ and $\\mathsf{S}_{\\mathrm{v}}{-}Z|\\mathsf{S}/\\mathsf{M}\\mathsf{o}\\mathsf{S}\\mathsf{e}_{2}$ . \n\nEDS spectrum of ZIS, it can be clearly seen the evenly distributed Zn, In and S elements, and the atomic ratio of $Z_{\\mathrm{{n}/I{n}/S}}$ can be calculated to be about $1.00/1.85/4.13$ (as listed in Table S1), very close to the stoichiometric ratio in $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ . Figure S3 presents the SEM, TEM and element mapping images of the $S_{\\mathrm{v}}$ -ZIS. It is found that the $S_{\\mathrm{v}}$ -ZIS appears the identical morphology and structure with ZIS, suggesting that the ${\\mathrm{N}}_{2}{\\mathrm{H}}_{4}\\cdot{\\mathrm{H}}_{2}{\\mathrm{O}}$ -assisted hydrothermal treatment cannot destroy the flower-like microsphere structure of ZIS. The atomic ratio of $Z_{\\mathrm{{n/In}/S}}$ in $S_{\\mathrm{v}}$ -ZIS sample is ${\\sim}1.00/1.92/$ 3.35 (as displayed in Table S2), the distinctly deficient of S atom compared to that in ZIS confirms the existence of abundant S vacancies in ZIS. Figure 2d is the TEM picture of $\\mathrm{MoSe}_{2}.$ , which manifests the nanosheet feature. The HRTEM image (Fig. 2e and f) present the d-spacing of 0.65 and $0.24\\mathrm{nm}$ , assigning to the (002) and (103) lattice planes of $2\\mathrm{H}{-}\\mathrm{MoSe}_{2}$ (JCPDS: 29-0914), respectively31. Figure $2\\mathrm{g}$ is the SEM image of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ , which exhibits almost the same morphology with ZIS, moreover, the ZIS and $\\mathrm{MoSe}_{2}$ in the $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ structure are undistinguishable, indicating that the $\\mathrm{MoSe}_{2}$ was grown on the surface of ZIS intimately to form a $2\\mathrm{D}/2\\mathrm{D}$ contact, and the introduction of $\\mathrm{MoSe}_{2}$ can hardly affect the hierarchical microsphere morphology of ZIS. The TEM image displaying in Fig. 2h and i further reveal the hierarchical flower-like microsphere structure of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ , which could lead to the enhanced light absorption by the multilevel reflection and scattering of the incident light32. Furthermore, the HRTEM picture displaying in Fig. 2j shows the different lattice stripes with d value of 0.32 and $0.24\\mathrm{nm}$ , respectively, which can be indexed to the (102) crystal face of hexagonal $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ (JCPDS:65-2023) and the (103) lattice planes of $2\\mathrm{H}{-}\\mathrm{MoSe}_{2}$ (JCPDS: 29-0914), respectively. The HRTEM results indicate that $\\mathrm{MoSe}_{2}$ are directly grown and attach on the ZIS nanosheets substrate. Figure $2\\mathrm{k-p}$ is the EDS spectra and element mapping of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ , as displayed, the distribution of $Z\\mathrm{n}$ , In, S elements are dense and uniform, meanwhile, the Mo and Se elements are relatively sparse but still evenly distributed. From the EDS spectrum, the mass ratio of $\\mathrm{MoSe}_{2}$ to ZIS can be calculated to be about $4.8\\%$ (as presented in Table S4), which is very close to the ratio of the added raw materials. What’s more, the atomic ratio of $Z_{\\mathrm{{n/In}/S}}$ in $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ was determined to be $1.00/1.83/3.25$ , indicating that there is still a mass of S vacancies inside $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ . \n\nThe ZIS, $\\begin{array}{r}{{\\mathsf{S}}_{\\mathrm{v}}–{\\mathsf{Z I S}}_{\\mathrm{i}}}\\end{array}$ , $\\mathrm{MoSe}_{2}$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ were further characterized by X-ray diffraction (XRD) to determine the phase composition. As displayed in Fig. 2q, the XRD pattern of $\\mathrm{MoSe}_{2}$ matches well with $2\\mathrm{\\bar{H}}{-}\\mathrm{\\iMoSe}_{2}$ $\\mathrm{\\DeltaJCPDS329-0914)^{31}}$ . Meanwhile, ZIS displays the distinct peaks at $21.6^{\\circ}$ , $27.7^{\\circ}$ , $30.4^{\\circ}$ , $39.8^{\\circ}$ , $47.2^{\\circ}$ , $52.4^{\\circ}$ , $55.6^{\\circ}$ and $76.4^{\\circ}$ , which can be severally indexed to the (006), (102), (104), (108), (110), (116), (022) and (213) crystal planes of hexagonal $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ $\\mathrm{^{\\prime}J C P D S:}65{-2023})^{9}$ . It is worth noting that the $S_{\\mathrm{v}^{-}}Z\\bar{\\mathrm{IS}}$ sample shows almost the same XRD pattern with ZIS, indicating that the introduction of S vacancies can hardly affect the size and crystal structure of ZIS. Moreover, in the XRD patterns of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}.$ , in addition to the peaks of hexagonal ZIS, a new peak at about $13.7^{\\circ}$ can be well assigned to the (002) crystal face of $\\mathrm{MoSe}_{2}$ , reconfirming the successful synthesis of $S_{\\mathrm{v}}{-}$ $\\mathrm{ZIS}/\\mathrm{MoSe}_{2}$ composite. \n\nTo further characterize the chemical structures of the assynthesized photocatalyst, the Raman spectra were carried out (shown in Fig. 2r). As observed in the Raman spectra of $\\mathrm{MoSe}_{2}$ , the peaks located at 235.4, 277.4 and $330.8\\mathrm{cm}^{-1}$ stem from the $A_{\\mathrm{{lg}}},~E_{2\\mathrm{{g}}}$ and $B_{2\\mathrm{g}}$ modes of $2\\mathrm{H}{-}\\mathrm{Mo}\\mathrm{Se}_{2}$ , respectively, while the peak at $142.1\\mathrm{cm}^{-1}$ is associated to the $E_{\\mathrm{1g}}$ mode of the in-plane bending of Se atoms in $2\\mathrm{H}\\mathrm{-}\\mathrm{MoSe}_{2}{}^{32}$ . For the Raman spectra of $\\ensuremath{\\mathrm{S}}_{\\mathrm{v}^{-}}\\ensuremath{\\mathrm{ZIS}}$ , the peaks located at 244.8 and $348.9\\mathrm{cm}^{-1}$ can be severally assigned to the $F_{2\\mathrm{g}}$ and $\\boldsymbol{A}_{1\\mathbf{g}}$ modes of $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ . Furtherly, as for the $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ (the red line), in addition to the $\\boldsymbol{E}_{\\mathrm{1g}}$ mode of $2\\mathrm{H}{-}\\mathrm{Mo}\\mathrm{Se}_{2}$ , and the $F_{2\\mathrm{g}}$ and $\\boldsymbol{A}_{1\\mathrm{g}}$ modes of $Z_{\\mathrm{{nIn}_{2}}}\\bar{S_{4}},$ a new emerging peak situated at about $\\stackrel{\\smile}{40}4.9\\thinspace c\\mathrm{m}^{-1}$ can be indexed to the Mo-S bonding state33, suggesting that the $\\ensuremath{\\mathrm{S_{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{IS}}$ and $\\mathrm{MoSe}_{2}$ were combined intimately by Mo-S bond. Additionally, it can be observed that all the peaks in $S_{\\mathrm{v}^{-}}Z\\mathrm{IS}/$ $\\mathrm{MoSe}_{2}$ exhibited evidently blue-shift compared to that in $S_{\\mathrm{v}}$ - ZIS, further revealing the intense chemical coupling effect between the $\\ensuremath{\\mathrm{S}}_{\\mathrm{v}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{\\mathrm{S}}$ and $\\mathrm{MoSe}_{2}{}^{34}$ . \n\nTo further testify the existence of S vacancies, the electron paramagnetic resonance (EPR) was carried out (Fig. 2s). For the original ZIS sample, the EPR intensity can hardly be observed, in comparison, the $S_{\\mathrm{v}}$ -ZIS sample shows the sharply increased EPR signal at a $\\mathbf{g}$ -factor of 2.009, confirming the abundant S-vacancies in $\\mathrm{S_{v}}–\\mathrm{ZIS}^{35,36}$ . In addition, it is interesting to observe that the EPR intensity of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ exhibits slightly decreased compared to that of $S_{\\mathrm{v}}$ -ZIS, which should be contributed to the bonding effect among Mo and unsaturated S in $S_{\\mathrm{v}}$ -ZIS, decreasing the number of unpaired electrons, but the S vacancies in ZIS have not been sewed up by compositing $\\mathrm{MoSe}_{2}{}^{37}$ . \n\nThe X-ray photoelectron spectroscopy (XPS) was applied to investigate the surface composition and chemical states of ZIS, $S_{\\mathrm{v}^{-}}$ ZIS and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}.$ and the results are showing in Fig. 3. As can be found from the survey spectrum (Fig. 3a), the $Z\\mathrm{n}.$ In and S peaks are coexisting in ZIS and $S_{\\mathrm{v}}$ -ZIS, in comparison, Mo and Se peaks can also be observed in the $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ , which is agree with the EDS test results. As observed in Fig. 3b, the S $2p_{3/2}$ and $2p_{1/2}$ of the original ZIS located at 161.72 and $162.97\\mathrm{eV}$ respectively, in accordance with the reported literature36. In comparison, the S $2p_{3/2}$ and $2p_{1/2}$ of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ presented evident negative-shift of about $0.14\\mathrm{eV}$ and $0.19\\mathrm{eV}$ , respectively, verifying the generation of S vacancies in ZIS. The S-vacancies can serve as strong electron-withdrawing group for facilitating the ZIS electrons transfer to S-vacancies, thus decreasing the equilibrium electron cloud density of S atoms inside ZIS, and further leading to the decreased binding energy38,39. Furtherly, it can be noted that the $\\mathrm{~S~}2p_{3/2}$ and $2p_{1/2}$ of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ exhibited a positiveshift of about 0.13 and $0.17\\mathrm{eV}$ compared to that of $S_{\\mathrm{v}}$ -ZIS, which should be caused by the strong interfacial interaction between $\\mathrm{MoSe}_{2}$ and $S_{\\mathrm{v}^{-}}Z\\mathrm{IS}^{34}$ . Besides, as shown in Fig. 3c and d, the $Z\\mathrm{n}2p$ and In $3d$ in $S_{\\mathrm{v}}$ -ZIS also exhibited a slightly negative-shift compared to that in ZIS, which could be explained that the generation of S vacancies leading to the decreased coordination number of $Z\\mathrm{n}$ and $\\mathrm{In}^{37}$ . After combining with $\\mathrm{MoSe}_{2}$ , the $Z\\mathrm{n}~2p$ and In $3d$ peaks re-shift to the high binding energy region, revealing that the bonding effect between Mo atoms in $\\mathrm{MoSe}_{2}$ and unsaturated coordination S in $S_{\\mathrm{v}}$ -ZIS contributing to the slightly increased electron cloud density around $Z\\mathrm{n}$ and In. Interestingly, it can also be observed that the binding energy variation of $Z\\mathfrak{n}\\ 2p$ in ZIS, $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ are more notable than that of In $3d.$ , revealing that the Mo were mainly bonded with the S around Zn sites37. What’s more, according to the XPS peak area, the actual atomic ratio of $Z_{\\mathrm{{n/In}/S}}$ in ZIS, $S_{\\mathrm{v}}$ ZIS and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ are $1.00/2.15/3.87$ , $1.00/2.20/3.29$ , and $1.00/2.14/3.36,$ respectively. The lower S atom ratio in $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ further confirm the presence of abundant S vacancies. As shown in Fig. 3e, the peaks at 228.05 and 230.5 $\\mathrm{^\\circv}$ can be attributed to Mo $3d_{5/2}$ and $3d_{3/2}$ of $\\mathrm{Mo^{4+}}$ in $\\mathrm{MoSe}_{2}$ meanwhile, the peak at $227.1\\mathrm{eV}$ verified the formation of Mo-S bond40. Figure 3f is the Mo $3p$ spectrum, as observed, four distinct XPS peaks can be distinguished, where the peaks at 400.55 and $390.3\\mathrm{eV}$ can be corresponded to the Se Auger peaks, and the peaks at 395 and $416\\mathrm{eV}$ can be assigned to the Mo $3p_{3/2}$ and $3p_{1/2}$ of $\\mathrm{Mo^{4+}}$ . The Se $3d$ spectrum presented in Fig. $3\\mathrm{g}$ shows two peaks at 54.4 and $55.35\\mathrm{eV}$ , which can be indexed to Se $3d_{5/2}$ and $3d_{3/2}$ of $\\mathsf{S e}^{2-}$ in $\\mathrm{MoSe}_{2}$ , respectively32. The XPS results further confirm the successful synthesis of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ with abundant S-vacancies, and the $\\mathrm{MoSe}_{2}$ is attached on the surface of $S_{\\mathrm{v}}$ -ZIS through Mo-S bond. \n\n![](images/b7f2594770413819205e59779a50ed2c0203836527f426383af44bdd32af52b4.jpg) \nFig. 3 XPS spectra. a survey, b S $2p$ , c Zn $2p.$ , $\\blacktriangleleft$ In 3d for ZIS, $S_{v}–Z1S$ and $\\mathsf{S}_{\\mathrm{v}}{-}Z{\\mathsf{I S}}/{M\\circ}\\mathsf{S e}_{2}$ , e Mo $3d$ and $\\textsf{S}2s,$ f Mo $3p$ and $\\pmb{\\mathrm{g}}\\mathsf{S e}3d$ of $\\mathsf{S}_{\\mathsf{v}}{-}Z{\\mathsf{l}}\\mathsf{S}/{\\mathsf{M}}\\mathsf{o}\\mathsf{S}{\\mathsf{e}}_{2}$ . \n\nPhotocatalytic $\\mathbf{H}_{2}$ evolution activity measurements. The photocatalytic $\\mathrm{H}_{2}$ evolution were evaluated under the visible light $(\\lambda>420\\mathrm{nm})$ ) irradiation, the corresponding test results are showing in Fig. 4. As shown in Fig. 4a and $\\mathbf{b}$ , all the tested samples exhibit $\\mathrm{H}_{2}$ production activity except for $\\mathrm{MoSe}_{2}$ . The pristine ZIS exhibits the poor $\\mathrm{H}_{2}$ production activity of about only $3.36\\mathrm{mmol{\\cdot}g^{-1}{\\cdot}h^{-1}}$ , in comparison, the $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ presents a slightly improved $\\mathrm{H}_{2}$ evolution rate of $4.77\\mathrm{mmol{\\cdot}\\bar{g}^{-1}{\\cdot}h^{-1}}$ . The improved photocatalytic performance of $S_{\\mathrm{v}}$ -ZIS should be ascribed to the accelerated photocarriers separation induced by S vacancies as the electrons trap. Furtherly, the introduction of $\\mathrm{MoSe}_{2}$ gave rise to the distinctly improved $\\mathrm{H}_{2}$ evolution activity, and the $\\mathrm{H}_{2}$ evolution rate of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ increased with the mass ratio of $\\mathrm{MoSe}_{2}$ to ZIS increasing. Until the mass ratio of $\\mathrm{MoSe}_{2}$ to ZIS reaches to $5.0\\%$ , the $\\mathrm{H}_{2}$ evolution rate reaches to the highest of $63.21\\mathrm{mmol{g}^{-1}{\\cdot}h^{-1}}$ , which is about 18.8 and 13.3 times higher than that of pristine ZIS and $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ , respectively, and superior to the recently reported $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ -based photocatalytic system (as listed in Table S6). It can also be observed that the $\\mathrm{S_{v}{-}Z I S{-}}5.0\\mathrm{MoSe}_{2}$ (synthesized by mixing $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ and $\\mathrm{MoSe}_{2}$ by ultrasound) performs obvious inferior $\\mathrm{H}_{2}$ evolution property compared to that of $\\mathrm{S_{v}{-}Z I S}/5.0\\mathrm{MoSe}_{2}.$ , indicating that the in-situ growth of $\\mathrm{MoSe}_{2}$ on $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ connecting by Mo-S bond plays critical influence on the photocatalytic performance of the ZIS$\\mathrm{MoSe}_{2}$ composite, which should be attributed to that the Mo-S bond could facilitate the charge transfer between $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{IS}}$ and $\\mathrm{MoSe}_{2}$ . Besides, Fig. S5 shows the wavelength dependent hydrogen evolution efficiency of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ , which was tested following the similar procedure of photocatalytic $\\mathrm{H}_{2}$ evolution, except that the band-pass filter was equipped to obtain monochromatic incident light $\\scriptstyle\\lambda=380$ , 420, 500 and $600\\mathrm{nm}$ ). The detailed test results and the light power of different monochromatic light are displaying in Table S5. Accordingly, the AQY of photocatalytic $\\mathrm{H}_{2}$ evolution over the $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ photocatalyst can be calculated (the detailed calculation process is shown in the Supporting Information) and the action spectrum was displayed in Fig. 4c. As observed, the action spectrum of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ matches well with the UV-vis absorption spectra, besides, the AQY values of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ are about $93.08\\%$ $380\\mathrm{nm},$ , $76.48\\%$ $(420\\mathrm{nm})$ , $29.7\\%$ $\\left(500\\mathrm{nm}\\right)$ and $0.15\\%$ $\\left(600\\mathrm{nm}\\right)$ , indicating the favorable optical absorption and utilization capacity of $S_{\\mathrm{v}^{-}}Z\\mathrm{IS}/$ $\\mathrm{MoSe}_{2}$ photocatalyst. Fig. S6 is the AQY of ZIS and $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{I\\boldsymbol{S}}$ it can be observed that under different monochromatic light wavelength, the AQY of $\\ensuremath{\\mathrm{S_{v}}}$ -ZIS are larger than that of ZIS, suggesting the more efficient photons to $\\mathrm{H}_{2}$ conversion ability of $S_{\\mathrm{v}^{-}}\\mathrm{ZIS,}$ which should be caused by the enhanced light absorption and the promoted photocarriers separation efficiency by introducing abundant S-vacancies in $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ . In addition to the excellent photocatalytic $\\mathrm{H}_{2}$ evolution efficiency, the recycling stability is also a pivotal factor for the practical application of photocatalyst. As discerned in Fig. 4d, the $\\mathrm{H}_{2}$ evolution amount of the optimized $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ photocatalyst remains about $90.5\\%$ after $20\\mathrm{h}$ of 5 cycles of photocatalytic tests, signifying the favorable photocatalytic stability of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ photocatalyst, which maybe contributed to the strong combination between ZIS and $\\mathrm{MoSe}_{2}$ through Mo-S bond. \n\n![](images/f242b9d1732e62fc93d9b127aec4303677b09fdb4fd456192d12da6a5888b094.jpg) \nFig. 4 Photocatalytic $\\Hat{\\boldsymbol{\\mathsf{H}}}_{2}$ evolution property. a ${\\sf H}_{2}$ evolution amount at different irradiation time and b ${\\sf H}_{2}$ evolution rate of different photocatalysts, c wavelength-dependent apparent quantum yield (AQY) and d cycling stability test of $\\mathsf{S}_{\\mathsf{v}}–\\mathsf{Z}|\\mathsf{S}/5.0\\mathsf{M}\\mathsf{o}\\mathsf{S}\\mathsf{e}_{2}$ . The vertical error bars indicate the maximum and minimum values obtained; the dot represents the average value. \n\n![](images/66256e369a30f000b9b27785c9afd1a9e3142f9d75e45f092dc8387917e0c02f.jpg) \nFig. 5 Photophysical and Electrochemical measurements. a UV-vis absorption spectrum, b photoluminescence spectra $(\\mathsf{P L},$ excited at $375{\\mathsf{n m}}$ c photocurrent response and d electrochemical impedance spectroscopy (EIS) of the as-prepared samples. \n\nPhotophysical and Electrochemical Properties. Figure 5a is the UV-vis absorption spectra of ZIS, $S_{\\mathrm{v}}$ -ZIS, $\\mathrm{MoSe}_{2}$ and $S_{\\mathrm{v}^{-}}Z\\mathrm{IS}/$ $\\mathrm{MoSe}_{2}$ . It is apparent that the $\\mathrm{MoSe}_{2}$ shows the intense light absorption in the whole UV-vis light range, which should be caused by its dark black color. Meanwhile, it can be observed that light absorption intensity of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ is higher than that of ZIS, indicating that the introduction of S vacancies can influence the band structure of ZIS. Furtherly, after combining with $\\mathrm{MoSe}_{2}$ , the light absorption of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ increased again compared to $S_{\\mathrm{v}^{-}}Z\\bar{\\mathrm{I}\\bar{\\mathrm{S}}}$ . The improved light absorption is in favor of the generation of photocarriers, and beneficial for the enhancement of photocatalytic performance9. Figure 5b is the PL spectroscopy. As displayed, under the $375\\mathrm{nm}$ excitation wavelength, the pristine ZIS displays a prominent emission peak, indicating the intense recombination of photogenerated carriers inside ZIS. In comparison to ZIS, the emission peak intensity of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ decreases lightly, which should be contributed to that S vacancies can act as electrons trap for facilitating the photocarriers separation. It is worth noting that the PL signal of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ sample is further quenched compared to that of $S_{\\mathrm{v}}$ -ZIS, revealing the positive effect of $\\mathrm{MoSe}_{2}$ for suppressing the recombination of photocarriers. Figure 5c is the photocurrent response. As observed, all the tested samples exhibit the light-response characteristic under the FX$300{\\mathrm{~\\bar{X}e}}$ lamp. Obviously, the photocurrent density is in the order of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}>S_{v}{-}Z I S>Z I S}$ The highest photocurrent density of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ reveals the most accelerated photocarriers separation and migration efficiency. Figure 5d is the electrochemical impedance spectroscopy (EIS). As compared, $\\mathrm{MoSe}_{2}$ express the smallest semicircle, meanwhile, the semicircle of ZIS is the largest. Obviously, the semicircle of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ is slightly lower than that of ZIS, and the semicircle of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ is significantly decreased than that of pristine ZIS and $S_{\\mathrm{v}}$ -ZIS, manifesting that the introduction of S vacancies and the combination with $\\mathrm{MoSe}_{2}$ can decrease the interfacial charge transfer resistance, which is in favor of photogenerated carriers transfer and separation, and finally facilitate the photocatalytic property. \n\nIn order to investigate the effects of the $\\mathrm{MoSe}_{2}$ to ZIS mass ratio on the photocatalytic performance of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ composites. The light absorption, photocarriers separation and photocurrent density of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ photocatalysts with different mass ratio of $\\mathrm{MoSe}_{2}$ to ZIS were also characterized by UV-vis absorption, steady-state PL spectroscopy and photocurrent response. As observed in Fig. S7, with increasing the mass ratio of $\\mathrm{MoSe}_{2}$ to ZIS, the light absorption intensity enhance gradually. It is worth mentioning that the $\\mathrm{S_{v}{-}Z I S}/7.0\\mathrm{MoSe}_{2}$ sample displays the strongest light absorption ability, but its photocatalytic $\\mathrm{H}_{2}$ production performance is not the best (as known from Fig. 4a), suggesting that the light absorption is not the only decisive factor for the photocatalytic activity. Fig. S8 is the PL spectra, it can be observed that the PL peak of $S_{\\mathrm{v}^{-}}Z\\mathrm{IS}/$ $5.0\\ensuremath{\\mathrm{MoSe}}_{2}$ is the lowermost, revealing the most effective photocarriers separation when the mass ratio of $\\mathrm{MoSe}_{2}$ to ZIS is $5\\%$ which directly explains why the $\\mathrm{S_{v}{-}Z I S}/5.0\\mathrm{MoSe}_{2}$ sample has the best photocatalytic performance. Figure S9 shows the photocurrent response. As displayed, the $\\mathrm{\\bar{S}_{v}{-}Z I S}/5.0\\mathrm{MoSe}_{2}$ shows the highest photocurrent density, which is the result of highefficiency separation and transfer of photogenerated electron and hole, further revealing the optimum photocatalytic performance of $\\mathrm{S_{v}{-}Z I S}/5.0\\mathrm{MoSe}_{2}$ . As known from the above results, the prominent photocatalytic performance requires the coordination among the efficient light absorption, photocarrier separation and transfer ability. \n\nMechanism analysis. Furtherly, the bandgap value $\\mathrm{(E_{g})}$ of the tested sample can be obtained from the Kubelka-Munk function vs. the energy of incident light plots41. As displayed in Fig. 6a, the $\\operatorname{E}_{\\mathrm{g}}$ of ZIS, $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ can be estimated to be 2.35, 2.28 and $2.19\\mathrm{eV}$ , respectively. The narrower $\\mathrm{E_{g}}$ is beneficial for the incident light absorption and photocarriers generation, thereby contributing to the photocatalytic property42. The MottSchottky (M-S) plot can be obtained by the following formula of $\\begin{array}{r}{C_{s c}^{-2}=\\frac{2}{\\varepsilon\\varepsilon_{0}e N_{D}}\\left(E-E_{f b}-\\frac{k_{B}T}{e}\\right)}\\end{array}$ , in which $\\mathbf{C}_{\\mathrm{SC}}$ represents space charge capacitance, ɛ represents the dielectric constant, $\\scriptstyle\\varepsilon_{0}$ represents the permittivity of vacuum, e represents the single electron charge, $\\mathrm{N_{D}}$ represents the charge carrier density, $\\mathrm{E_{fb}}$ represents the flat band potential, $\\bf k_{\\mathrm{B}}$ represents the Boltzmann constant, and T represents the temperature, E represents the electrode potential9. As displayed in Fig. 6b-d, the $\\mathrm{E_{fb}}$ of ZIS, $S_{\\mathrm{v}}$ - ZIS and $\\mathrm{MoSe}_{2}$ can be determined to be $-0.96$ , $-0.9$ and $-0.1\\mathrm{V}$ (vs. NHE), respectively, by extending the linear part of M-S plots. Besides, all the tested samples exhibit the positive slope of M-S plots, indicating the n-type semiconductor traits43. As known, the conduction band potential $\\mathrm{(E_{CB})}$ of $\\mathfrak{n}$ -type semiconductor is ${\\sim}0.2\\mathrm{eV}$ negative than the $\\mathrm{E_{fb}}^{44}$ , thus the $\\operatorname{E}_{\\mathrm{CB}}$ of ZIS, $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ and $\\mathrm{MoSe}_{2}$ can be discerned to $-1.16$ , $-1.1$ and $-0.3\\mathrm{V}$ (vs. NHE), respectively. According to the equation of $\\mathrm{E_{VB}=E_{C B}+E_{g}}$ ( $\\mathrm{\\DeltaE_{VB}}$ is the potential of valence band (VB)), the $\\mathrm{E_{VB}}$ of the ZIS and $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ can be estimated to 1.19 and $1.18\\mathrm{V}$ vs. NHE, respectively. According to the reported literature, the $\\mathrm{E_{g}}$ of $\\mathrm{MoSe}_{2}$ is about $1.89\\mathrm{eV}$ therefore, the $\\mathrm{E_{VB}}$ of $\\mathrm{MoSe}_{2}$ can be determined to be 1.59 eV25. \n\nThe work function $(\\Phi)$ is an important nature for reflecting the escaping ability of free electron from Fermi level $\\mathrm{(E_{f})}$ to vacuum level45. To investigate the mechanism for the excellent photocatalytic performance of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ , the ultraviolet photoelectron spectroscopy (UPS) with He I as the excitation source was conducted. As displayed in Fig. 6e, the secondary cutoff binding energy $(\\mathrm{E_{cutoff}})$ of $\\mathrm{\\partialS_{v}{-}Z I S}$ and $\\mathbf{MoSe}_{2}$ can be respectively determined as 17.65 and $16.87\\mathrm{eV}$ , by extrapolating the linear part to the base line of the UPS spectra. Based on the formula of $\\scriptstyle\\mathbf{\\bar{\\phi}}=\\mathbf{h}\\mathbf{v}-\\mathbf{E}_{\\mathrm{cutoff}},$ the $\\Phi$ of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{IS}}$ and $\\mathrm{MoSe}_{2}$ can be calculated as 3.57 and $4.35\\mathrm{eV}$ , respectively. Hence, the $\\mathrm{E_{f}}$ of $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ and $\\mathrm{MoSe}_{2}$ can be determined as $-0.93$ and $-0.15\\mathrm{V}$ (vs. NHE), respectively. Based on the above calculation and analysis results, the detailed band structure of $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ , $\\mathrm{MoSe}_{2}$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ were depicted in Fig. 6f. As observed, the $\\mathrm{E}_{\\mathrm{f}}$ of $\\mathrm{MoSe}_{2}$ is below that of $\\mathrm{\\bar{S}_{v}}–\\mathrm{ZIS}$ , hence, when $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ and $\\mathrm{MoSe}_{2}$ contact and form an intimate interface, the free electrons in $S_{\\mathrm{v}}$ -ZIS with high $\\mathrm{E}_{\\mathrm{f}}$ would spontaneously diffuse to $\\mathrm{MoSe}_{2}$ with low $\\mathrm{E}_{\\mathrm{f}},$ until a new equilibrium state $\\mathrm{E_{f}}$ fabricated. The electron drifting from $S_{\\mathrm{v}}$ -ZIS to $\\mathrm{MoSe}_{2}$ result in the charge redistribution on the interface between $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ and $\\mathrm{MoSe}_{2}$ , in which the interface near $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ side is positively charged, while negatively charged near the $\\mathrm{MoSe}_{2}$ side, as result, an internal electric field from $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ to $\\mathrm{MoSe}_{2}$ was built46. \n\nTo further reveal the photocatalytic reaction mechanism of $S_{\\mathrm{v}^{-}}$ $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ heterostructure, the density functional theory (DFT) calculations were conducted out. Figure 7(a) is the optimized structure of $\\mathrm{S_{v}{-}Z n I n}_{2}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ heterostructure, where the coordinative unsaturation S atoms was simulated by breaking two $Z\\mathrm{n-S}$ bonds in the surface of $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ . According to Population analysis and Hirshfeld analysis results, the population of $\\mathrm{Mo}_{001}{-}\\mathrm{S}_{018}$ is 0.34, and the transferred charge between $\\mathrm{MoSe}_{2}$ and $\\mathrm{S_{v}{-}Z n I n_{2}S_{4}}$ is $0.12\\left|\\textrm{e}\\right|$ . The above results directly demonstrate the intense bonding effect between the Mo atom in $\\mathrm{MoSe}_{2}$ and the coordinative unsaturation S atom in $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ . Figure 7(b) shows the side view of charge density difference of $\\mathrm{S_{v}{-}Z n I n_{2}S_{4}}/$ $\\mathrm{MoSe}_{2}$ , where the red and blue iso-surfaces denote the accumulation and depletion of electron density, respectively. As observed, the electron cloud density presents distinctly localized distribution between the Mo atom in $\\mathrm{MoSe}_{2}$ and the coordinative unsaturation S atoms in $\\mathrm{S_{v}–Z n I n}_{2}\\mathrm{S}_{4},$ which more intuitively manifests the intense bonding effect between Mo and S. In addition, it can be noted that the surface of $\\mathrm{MoSe}_{2}$ was dominantly covered by red color, while $\\mathrm{S_{v}{-}Z n I n_{2}S_{4}}$ was chiefly filled by blue color, suggesting that the electrons in $\\mathrm{S_{v}{-}Z n I n_{2}S_{4}}$ were transfer to $\\mathrm{MoSe}_{2}$ along the intimate heterointerface, which would subsequently induce the internal electric field in $S_{\\mathrm{v}^{-}}$ $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ heterostructure47. \n\nAccordingly, the photocatalytic reaction mechanism of $S_{\\mathrm{v}^{-}}Z\\mathrm{IS}/$ $\\mathrm{MoSe}_{2}$ can be elaborated in Fig. 7c. Under the irradiation of visible light, a mass of photoinduced electrons $\\left(\\mathrm{e^{-}}\\right)$ with enough energy would transfer from the VB of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{IS}}$ and ${\\mathrm{MoSe}}_{2}$ to the CB of $S_{\\mathrm{v}}$ -ZIS and $\\mathrm{MoSe}_{2}$ , respectively, while the holes $\\left(\\mathrm{h^{+}}\\right)$ be left on the VB of $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ and $\\mathrm{MoSe}_{2}$ , respectively. It should be mentioned that the abundant S vacancies inside ZIS could introduce new donor level in the band gap of ZIS, which can act as efficient electrons trap to suppress the photogenerated electron-hole pairs recombination48. Furtherly, under the driving effect of the internal electric field, the electrons on the CB of $\\mathrm{MoSe}_{2}$ would migrate to the VB of $\\ensuremath{\\mathrm{S_{v}}}\\mathrm{-}\\ensuremath{\\mathrm{ZIS}}$ to recombine with the holes. The Mo-S bond acting as atomic-level interfacial “bridge” can promote the photoexcited carriers migration between $S_{\\mathrm{v}}$ -ZIS and $\\mathrm{MoSe}_{2}$ , thus significantly accelerating the Z-scheme charge transfer. To validate the Z-scheme charge transfer mechanism, the SPV and EPR measurements were carried out. Figure 7d is the SPV spectra of ${\\sf S}_{\\mathrm{v}^{-}}\\mathrm{ZIS},$ $\\mathrm{MoSe}_{2}$ and $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ samples. It is noted that the pristine $\\mathrm{MoSe}_{2}$ presents no SPV signals in the whole wavelength, suggesting the poor photocarriers separation efficiency inside the $\\mathrm{MoSe}_{2}$ , that’s why $\\mathrm{MoSe}_{2}$ performed very poor hydrogen evolution. In comparison, a significant positive photovoltage response can be observed in the SPV spectra of $\\bar{\\mathsf{S}}_{\\mathrm{v}^{-}}\\mathsf{Z I S}$ , suggesting that the holes migrate to the surface of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{IS}}$ , which is the typical trait of n-type semiconductor49. Meanwhile, the SPV response of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ is significantly lower than that of $S_{\\mathrm{v}}$ -ZIS, which means that fewer photogenerated holes migrate to the surface of $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ . This phenomenon should be contributed to that the photogenerated electrons on the CB of $\\mathrm{MoSe}_{2}$ transfer to the VB of $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{IS}}$ and recombine with the photogenerated holes, that’s the Z-scheme mechanism50. EPR spin-trapping experiment with DMPO as spin-trapping reagent was further proceeded to support the Z-scheme charge transfer mechanism in $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ . As displayed in Fig. 7e, almost no DMPO- $\\cdot\\mathrm{O}_{2}^{-}$ signals can be observed under dark conditions. However, under visible light irradiation, the characteristic peaks of $\\mathrm{DMPO-\\cdotO_{2}\\mathrm{^{-}}}$ (1:1:1:1) can be monitored for the $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ methanol dispersion liquid, and the peak intensity increase with the time extending, suggesting that the $\\cdot\\mathrm{O}_{2}\\mathrm{^-}$ was generated in the reaction system51. In theory, the electrons on $\\mathrm{MoSe}_{2}$ cannot reduce $\\mathrm{O}_{2}$ to product $\\cdot\\mathrm{O}_{2}^{-}$ due to the lower CB potential of $\\mathrm{MoSe}_{2}$ $(-0.3\\:\\mathrm{V}$ vs. NHE) than the redox potential of $\\mathrm{O}_{2}/\\cdot\\mathrm{O}_{2}^{-}$ $\\left(-0.33\\mathrm{V}\\right.$ vs. NHE)52. Therefore, the $\\cdot\\mathrm{O}_{2}^{-}$ should be the reaction product between the photoinduced electrons on the CB of $\\mathsf{S}_{\\mathrm{v}}{-}\\mathsf{Z}\\mathrm{I}\\mathsf{S}$ and $\\mathrm{O}_{2}$ (the CB potential of $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ is about $-1.10\\mathrm{eV}$ , lager than the redox potential of $\\mathrm{O}_{2}/\\cdot\\mathrm{O}_{2}^{-})$ , indicating that a mass of photogenerated electrons were accumulated on the CB of $S_{\\mathrm{v}}$ -ZIS under irradiation of visible light, which should be contributed by the recombination between the electron on the CB of $\\mathrm{MoSe}_{2}$ and the hole on the VB of $\\ensuremath{\\mathrm{s}}_{\\mathrm{v}}$ -ZIS, thus verifying the direct Z-scheme charge migration mechanism. Above SPV and EPR spin-trapping technique provides the direct proof for the direct Z-scheme charge transfer mechanism inside the $\\mathrm{S_{v}{-}Z I S/M o S e_{2}}$ photocatalyst. \n\n![](images/a8a3859cc08df411d82648fe2748d77d01550b4794e5ca23037fb1312bcf6b7f.jpg) \nFig. 6 Band structure and the formation of internal electric field. a Kubelka-Munk function vs. the energy of incident light plots, b–d Mott-Schottky (M-S) plot, e UPS spectra of the as-prepared samples, and f band structure of $\\mathsf{S}_{\\mathsf{v}}$ -ZIS, ${\\mathsf{M o S e}}_{2}$ and $\\mathsf{S}_{\\mathsf{v}}{-}Z{\\mathsf{l}}\\mathsf{S}/{\\mathsf{M}}\\mathsf{o}\\mathsf{S}{\\mathsf{e}}_{2}$ . \n\nIn summary, we have successfully demonstrated an interfacial Mo-S bond and internal electric field modulated Z-scheme $S_{\\mathrm{v}}$ - $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ photocatalyst through a defect-induced heterostructure constructing strategy for boosting the photocatalytic $\\mathrm{H}_{2}$ evolution performance. The internal electric field provide the necessary driving force steering the photogenerated electrons on the conduction band of $\\mathrm{MoSe}_{2}$ transfer to the valence band of $S_{\\mathrm{v}^{-}}$ $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ following the Z-scheme mechanism, while the interfacial Mo-S bond creates direct charge transfer channels between $S_{\\mathrm{v}}$ - $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ and $\\mathrm{MoSe}_{2}$ , further accelerates the Z-scheme charge transfer process. What’s more, the abundant S-vacancies also contribute to the enhanced light absorption and accelerated photocarriers separation. The above factors together lead to the efficient photocatalytic performance of the $\\bar{\\mathrm{S_{v}}}{-}Z{\\mathrm{nIn}_{2}}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ . Specifically, the optimized photocatalyst exhibits a high AQY of $76.48\\%$ at $420\\mathrm{nm}$ , and an ultrahigh $\\mathrm{H}_{2}$ evolution rate of \n\n![](images/d83f2a2f99edeec8ad6a260059b7b289b3b04e1dfa91d9af0305f213d0992f25.jpg) \nFig. 7 Photocatalytic mechanism and verification. a The optimized structure and b the side view of charge density difference of $\\mathsf{S}_{\\mathrm{v}}{-}Z\\mathsf{n}|\\mathsf{n}_{2}\\mathsf{S}_{4}/\\mathsf{M}\\mathsf{o}\\mathsf{S}\\mathsf{e}_{2}$ heterostructure. c photocatalytic reaction mechanism of $\\mathsf{S}_{\\mathrm{v}}{-}Z|\\mathsf{S}/M\\mathsf{o}\\mathsf{S}\\mathsf{e}_{2}$ under light irradiation, d Surface photovoltage (SPV) measurement of $S_{\\mathrm{v}}{-}Z1S,$ $\\mathsf{M o S e}_{2}$ and $\\mathsf{S}_{\\mathsf{v}}{-}Z|\\mathsf{S}/\\mathsf{M o S e}_{2},$ and e DMPO spin-trapping electron paramagnetic resonance (EPR) spectra of DMPO- ∙ $\\mathsf{O}_{2}\\mathsf{^{-}}$ of $\\mathsf{S}_{\\mathrm{v}}{-}Z{\\mathsf{I S}}/{\\mathsf{M o S e}_{2}}$ in methanol solution. \n\n$63.21\\mathrm{mmol{\\cdot}g^{-1}\\cdot h^{-1}}$ under visible light $(\\lambda>420\\mathrm{nm})$ , which is about 18.8 times higher than that of pristine $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ . Besides, the $\\mathrm{S_{v}{-}Z n I n}_{2}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ also shows favorable recycling stability by remaining above $90\\%$ rate retention after $20\\mathrm{{h}}$ of 5 continuous photocatalytic tests. This work not only provides an efficient direct Z-scheme $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ -based heterostructure photocatalyst, but also affords a beneficial prototype for designing other $Z$ -scheme photocatalyst for efficient green energy conversion. \n\n# Methods \n\nMaterials. Analytical grade reagents were used directly without purification. Zinc acetate dihydrate $\\mathrm{(Zn(CH_{3}C O O)_{2}{\\cdot}2H_{2}O)}$ was bought from Tianjin guangcheng chemical reagent Co. LTD. Thioacetamide (TAA), Indium chloride $\\left(\\mathrm{InCl}_{3}\\right)$ , and Selenium power (Se, $299.99\\%$ metal basis) were bought from Shanghai Macklin biochemical technology Co. LTD. Ascorbic acid (AA) and hydrazine monohydrate $(\\mathrm{N}_{2}\\mathrm{H}_{4}{\\cdot}\\mathrm{H}_{2}\\mathrm{O},$ $85\\%$ ) were bought from Sinopharm Chemical Reagent Co., LTD. Sodium molybdate dihydrate $(\\mathrm{Na_{2}M o O_{4}{\\cdot}2H_{2}O)}$ was purchased from Tianjin Fengchuan Chemical Reagent Technology Co., LTD. Deionized water was obtained from local sources. \n\nSynthesis of $Z n\\ln_{2}S_{4}$ and $\\pmb{\\mathsf{S}}_{\\mathbf{v}}{-}\\pmb{\\mathrm{Znln}}_{2}\\pmb{\\mathsf{S}}_{4}$ . In a representative experiment, $\\mathrm{InCl}_{3}$ (1 mmol), $\\mathrm{Zn(CH_{3}C O O)_{2}\\cdot2H_{2}O}$ $0.5\\mathrm{mmol};$ , and TAA (4 mmol) were orderly dissolved into $50~\\mathrm{mL}$ deionized water, and then stirred at room temperature for $30\\mathrm{min}$ . Thereafter, the clear solution was poured into $100\\mathrm{mL}$ stainless steel \n\nautoclave, and maintained at $180^{\\circ}\\mathrm{C}$ oven for $18\\mathrm{h}$ . After cooling naturally to indoor temperature, the sediment was separated by centrifugation, followed by washing with deionized water and ethanol, and drying at $60^{\\circ}\\mathrm{C}$ for $^{10\\mathrm{h}}$ . The obtained yellow powder $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ were labeled as ZIS. $\\mathrm{S_{v}{-}Z n I n_{2}S_{4}}$ was prepared via a $\\mathrm{N}_{2}\\mathrm{H}_{4}{\\cdot}\\mathrm{H}_{2}\\mathrm{O}$ -assisted hydrothermal method. Typically, $100\\mathrm{mg}$ the as-synthesized ZIS was dispersed into $20~\\mathrm{mL}$ deionized water for $^{\\textrm{1h}}$ , then, 5 mL $\\mathrm{N}_{2}\\mathrm{H}_{4}{\\cdot}\\mathrm{H}_{2}\\mathrm{O}$ was added into the mixing solution and stirred for another $30\\mathrm{min}$ . After that, the mixture was transfer to $50~\\mathrm{mL}$ stainless steel autoclave, and maintained at $240^{\\circ}\\mathrm{C}$ oven for $^{5\\mathrm{h}}$ . Finally, the precipitate was separated by centrifugation, and washing with deionized water for several times, then drying at $60^{\\circ}\\mathrm{C}$ for $^{10\\mathrm{h}}$ . The obtained light-yellow powder was labeled as $S_{\\mathrm{v}^{-}}Z\\mathrm{I}S$ . \n\nSynthesis of $S_{v}–\\mathbf{Znln}_{2}S_{4}/\\mathbf{MoSe}_{2}$ heterostructure. The $\\mathrm{S_{v}{-}Z n I n}_{2}\\mathrm{S}_{4}/\\mathrm{MoSe}_{2}$ heterostructure were synthesized by the similar process with $\\mathrm{S_{v}{-}Z n I n_{2}S_{4}}$ except that $\\mathrm{Na}_{2}\\mathrm{MoO}_{4}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O}$ and Se powders were added into the mixture. The $\\mathrm{S_{v}{-}Z n I n_{2}S_{4}}/$ $\\mathrm{MoSe}_{2}$ with different mass ratio of $\\mathrm{MoSe}_{2}$ to $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ $0.5\\%$ $1.0\\%$ , $3.0\\%$ , $5.0\\%$ , and $7.0\\%$ ) were synthesized by adjusting the addition of $\\mathrm{Na}_{2}\\mathrm{MoO}_{4}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O}$ and Se, and the synthesized samples were labeled as $\\mathrm{S}_{\\mathrm{v}}–\\mathrm{ZIS}/0.5\\mathrm{MoSe}_{2}$ , $\\mathrm{S_{v}{-}Z I S}/1.0\\mathrm{MoSe}_{2}$ , $S_{\\mathrm{v}}{-}Z\\mathrm{I}S/$ $3.0\\mathrm{MoSe}_{2}.$ $\\mathrm{S_{v}{-}Z I S}/5.0\\mathrm{MoSe}_{2}$ , $\\mathrm{S_{v}{-}Z I S}/7.0\\mathrm{MoSe}_{2}.$ , respectively. For comparison, the pure $\\mathbf{MoSe}_{2}$ was prepared following the above steps without adding ZIS. Besides, the $\\mathrm{S_{v}{-}Z I S{-}}5.0\\mathrm{MoSe}_{2}$ mixture was also fabricated by ultrasonic mixing the $\\ensuremath{S_{\\mathrm{v}}}\\mathrm{-}Z\\ensuremath{\\mathrm{I}}\\ensuremath{S}$ with $\\mathrm{MoSe}_{2}$ for $^{\\textrm{1h}}$ . \n\nCharacterization. The morphology and microstructure were investigated by SU8010 scanning electron microscope (SEM) outfitted with an energy dispersive \n\nX-ray spectrometer (EDS), and JEM-2100 plus transmission electron microscope (TEM). The crystalline and phase information were characterized by Bruker D8 Advance X-ray diffraction (XRD). The chemical states were investigated by Thermo ESCALAB 250 XI X X-ray photoelectron spectroscopy (XPS, monochromatic Al Kα radiation), and the XPS data was calibrated by C 1 s spectrum (binding energy is $284.8\\mathrm{eV}$ ). The light absorption property was researched by the PerkinElmer Lambda 750 S UV-vis spectrophotometer using barium sulfate as standard reference. The recombination of photogenerated carriers was tested by F-4600 spectrofluorometer $375\\mathrm{nm}$ excitation wavelength). The secondary cutoff binding energy was measured by AXIS SUPRA X-ray photoelectron spectroscopy with He I as the excitation source. The surface photovoltage (SPV) measurement were carried out on the system consisting a 500 W Xe lamp source equipped with a monochromator, a lock-in amplifier with a light chopper, a photovoltaic cell, and a computer. The Raman spectra were conducted on LabRAM HR Evolution Raman spectrometer with $325\\mathrm{nm}$ excitation wavelength to analysis the composition. The electron paramagnetic resonance (EPR) measurement was conducted on JEOL JES-FA200 EPR spectrometer with a $9.054\\mathrm{GHz}$ magnetic field. The 5,5-dimethylpyrroline N-oxide (DMPO) was adopted as spin-trapping reagent and the $\\cdot\\mathrm{O}_{2}\\mathrm{^-}$ and ∙OH were tested in methanol and aqueous solution, respectively. \n\nPhotocatalytic water splitting for hydrogen evolution. The hydrogen production experiments were proceeded on Labsolar-6A (Beijing Perfectlight). Typically, photocatalyst $(50\\mathrm{mg})$ was ultrasonically suspended into $100~\\mathrm{mL}$ solution involving $0.1\\mathrm{M}$ ascorbic acid sacrificial agent. Prior to exerting light, the reaction system was degassed for $^{\\textrm{1h}}$ to thoroughly exclude the air and the dissolved oxygen in reaction system. Then the reaction was proceeded under PLS-SEX300D 300 W Xenon lamp (Beijing Perfectlight) with a $420\\mathrm{nm}$ cut-off filter. The light intensity was determined by PLMW2000 photoradiometer (Beijing Perfectlight) to be about $254\\mathrm{mW}/\\mathrm{cm}^{2}$ . The generated hydrogen was analyzed by GC 7900 gas chromatograph (Techcomp, $\\check{5}\\mathrm{\\AA}$ molecular sieve stainless steel packed column, Ar as carrier gas and TCD detector). \n\nPhotoelectrochemical and electrochemical measurements. All the electrochemical and photoelectrochemical measurements were conducted by a threeelectrode system on CHI-660E electrochemical workstation. In the typical threeelectrode system, the working electrode was a piece of nickel foam coating with the as-prepared photocatalyst, the reference electrode was $\\mathrm{Hg/HgO}$ , while the counter electrode was $\\mathrm{Pt}$ wire. The electrolyte was 0.5 M ${\\mathrm{Na}}_{2}{\\mathrm{SO}}_{4}$ aqueous solution. The electrochemical impedance spectroscopy (EIS) was conducted under open-circuit potential with 0.01 to $1{\\times}10^{5}\\mathrm{\\bar{Hz}}$ frequency range and $0.005\\mathrm{V}$ AC amplitude. The photocurrent response was tested under FX-300 Xe lamp. Mott-Schottky (M-S) plots were collected from $^{-1}$ to $-0.2\\mathrm{V}$ under $10\\mathrm{kHz}$ frequency and $0.01\\mathrm{V}$ amplitude. \n\nThe working electrode was fabricated as follows: a certain amount of photocatalyst, carbon black and polyvinylidene fluoride were weighted according to the mass ratio of 8:1:1, and then dispersed into N-methyl-2-pyrrolidone to gain a homogeneous paste. The paste was daubed on a piece of pre-cleaned $\\scriptstyle1\\times1\\ c m^{2}$ FTO collector, and then dried in $60~^{\\circ}\\mathrm{C}$ vacuum for $^{\\textrm{1h}}$ . \n\nTheoretical calculation. Density functional theory (DFT) calculations were performed utilizing the CASTEP module of Materials Studio $6.1^{53}$ , the Perdew-BurkeEmzerhof (PBE) functional54, and ultrasoft pseudopotential (USPP) method55,56. The cut-off kinetic energy of $400\\mathrm{eV}$ , a $3\\times3\\times3$ Monkhorst-pack k-point (Γ point) mesh sampled the Brillouin zone with a smearing broadening of $0.05\\mathrm{eV}$ were applied during the whole process. The convergence criteria of self-consistent field (SCF), total energy difference, maximum force, and maximum displacement are $2.0{\\times}10^{-6}$ eV/atom, $2.0{\\times}10^{-5}$ eV/atom, $5.0{\\times}10^{-2}\\mathrm{eV}/\\mathring{\\mathrm{A}}$ , and $2.0{\\times}10^{-3}\\mathrm{\\AA}$ , respectively. \n\n# Data availability \n\nThe experimental data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper. \n\nReceived: 4 February 2021; Accepted: 17 June 2021; Published online: 05 July 2021 \n\n# References \n\n1. Hisatomi, T. & Domen, K. Reaction systems for solar hydrogen production via water splitting with particulate semiconductor photocatalysts. Nat. Catal. 2, 387–399 (2019). \n2. Dai, B. Y. et al. Construction of infrared‐light‐responsive photoinduced carriers driver for enhanced photocatalytic hydrogen evolution. Adv. Mater. 32, 1906361 (2020). \n3. Yang, J. L. et al. Boosting photocatalytic hydrogen evolution reaction using dual plasmonic antennas. ACS Catal. 11, 5047–5053 (2021). \n5. Wang, Z. et al. Overall water splitting by Ta3N5 nanorod single crystals grown on the edges of KTaO3 particles. Nat. Catal. 1, 756–763 (2018). \n6. Kageshima, Y., et al, Photocatalytic and photoelectrochemical hydrogen evolution from water over Cu2SnxGe1-xS3 particles. J. Am. Chem. Soc. (2021). https://doi.org/10.1021/jacs.0c12140. \n7. Wang, S. B. et al. Supporting ultrathin ZnIn2S4 nanosheets on Co/N‐Doped graphitic carbon nanocages for efficient photocatalytic H2 generation. Adv. Mater. 31, 1903404 (2019). \n8. Kim, Y. et al. Efficient photocatalytic production of hydrogen by exploiting the polydopamine-semiconductor interface. Appl. Catal. B: Environ. 280, 119423 (2021). \n9. Li, Z. J. et al. CoNi bimetal cocatalyst modifying a hierarchical ZnIn2S4 nanosheet-based microsphere noble-Metal-Free photocatalyst for efficient visible-light-driven photocatalytic hydrogen production. ACS Sustain. Chem. Eng. 7, 20190–20201 (2019). \n10. Mohanty, B., Chattopadhyay, A. & Nayak, J. Band gap engineering and enhancement of electrical conductivity in hydrothermally synthesized CeO2- PbS nanocomposites for solar cell applications. J. Alloy. Compd. 850, 156735 (2021). \n11. Yu, H. et al. Enhanced photocatalytic tetracycline degradation using N-CQDs/ OV-BiOBr composites: Unraveling the complementary effects between NCQDs and oxygen vacancy. Chem. Eng. J. 402, 126187 (2020). \n12. Wang, J. et al. Cubic quantum dot/hexagonal microsphere ZnIn2S4 heterophase junctions for exceptional visible-light-driven photocatalytic H2 evolution. J. Mater. Chem. A. 5, 8451–8460 (2017). \n13. Gao, D. et al. Selenium-enriched amorphous NiSe1 $+\\mathbf{x}$ nanoclusters as a highly effcient cocatalyst for photocatalytic H2 evolution. Chem. Eng. J. 408, 127230 (2020). \n14. Rao, F. et al. Mirabbos Hojamberdieve. In-situ generation of oxygen vacancies and metallic bismuth from (BiO)2CO3 via N2-assisted thermal-treatment for efcient selective photocatalytic NO removal. Appl. Catal. B Environ. 281, 119481 (2021). \n15. Wang, Y. et al. Direct and indirect Z-scheme heterostructurecoupled photosystem enabling cooperation. of CO2 reduction and H2O oxidation. Nat. Commun. 11, 3043 (2020). \n16. Wu, Z. et al. Recent progress of vacancy engineering for electrochemical energy conversion related applications. Adv. Funct. Mater. 31, 2009070 (2020). \n17. Zhang, Y. et al. Structure-activity relationship of defective metal-based photocatalysts for water splitting: experimental and theoretical perspectives. Adv. Sci. 6, 1900053 (2019). \n18. Liu, J. et al. Defects engineering in photocatalytic water splitting materials. ChemCatChem 11, 6177–6189 (2019). \n19. Wang, J. Yang, L. & Zhang, L. Constructed 3D hierarchical micro-flowers CoWO4@Bi2WO6 Z-scheme heterojunction catalyzer: two-channel photocatalytic H2O2 production and anti‐biotics degradation. Chem. Eng. J. 127639 (2020) \n20. Gu, Y. et al. Two dimensional porous molybdenum phosphide/Nitride heterojunction nanosheets for pH-universal hydrogen evolution reaction. Angew. Chem. Int. Ed. 60, 6673–6681 (2020). \n21. Wu, J. et al. Piezotronic effect boosted photocatalytic performance of heterostructured BaTiO3/TiO2 nanofbers for degradation of organic pollutants. Nano Energy 77, 105122 (2020). \n22. Xu, H. et al. Metal-oxide-mediated subtractive manufacturing of twodimensional carbon nitride for high-efficiency and high-yield photocatalytic H2 evolution. ACS Nano. 13, 11294–11302 (2019). \n23. Chao, Y. et al. Ultrathin visible-light-driven Mo Incorporating In2O3- ZnIn2Se4 Z-Scheme Nanosheet Photocatalysts. Adv. Mater. 31, 1807226 (2019). \n24. Xing, F. S. et al. Tunable charge transfer efficiency in HxMoO3@ZnIn2S4 hierarchical direct Z-scheme heterojunction toward efficient visible-lightdriven hydrogen evolution. Appl. Catal. B Environ. 285, 119818 (2021). \n25. Kwon, I. S. et al. Se-rich MoSe2 nanosheets and their superior electrocatalytic performance for hydrogen evolution reaction. ACS Nano. 14, 6295–6304 (2020). \n26. Yang, M. Q. et al. Self-surface charge exfoliation and electrostatically coordinated 2D hetero-layered hybrids. Nat. Commun. 8, 14224 (2017). \n27. Zeng, D. et al. Hierarchical ZnIn2S4/MoSe2 nanoarchitectures for efficient noble-metal-free photocatalytic hydrogen evolution under visible Light. ChemSusChem 10, 4624–4631 (2017). \n28. Zhang, S. et al. Atomic-level and modulated interfaces of photocatalyst heterostructure constructed by external defect-induced strategy: a critical review. Small 17, 2004980 (2020). \n29. Tao, X. et al. Interfacial charge modulation: An efficient strategy for boosting spatial charge separation on semiconductor photocatalysts. Adv. Energy Mater. 9, 1803951 (2019). photogenerated charge separation and enhancing photoactivity. EcoMat. 1, (2019). \n31. Wang, Y. et al. Construction of Z-scheme MoSe2/CdSe hollow nanostructure with enhanced full spectrum photocatalytic activity. Appl. Catal. B Environ. 244, 76–86 (2019). \n32. Vikraman, D. et al. Engineering the novel MoSe2-Mo2C hybrid nanoarray electrodes for energy storage and water splitting applications. Appl. Catal. B Environ. 264, 118531 (2020). \n33. Li, F. et al. High-performance optoelectronic devices based on van der Waals vertical MoS2/MoSe2 heterostructures. Nano Res. 13, 1–7 (2020). \n34. Cheng, C. et al. Facile preparation of nanosized MoP as cocatalyst coupled with $\\mathbf{g}$ -C3N4 by surface bonding state for enhanced photocatalytic hydrogen production. Appl. Catal. B Environ. 265, 118620 (2020). \n35. Huang, X. et al. Recent advances of doped graphite carbon nitride for photocatalytic reduction of CO2: a review. Res. Chem. Intermed. 46, 5133–5164 (2020). \n36. Du, C. et al. Half-unit-cell ZnIn2S4 monolayer with sulfur vacancies for photocatalytic hydrogen evolution. Appl. Catal. B Environ. 248, 193–201 (2019). \n37. Zhang, S. et al. MoS2 Quantum dot growth induced by S vacancies in a ZnIn2S4 monolayer: atomic-level heterostructure for photocatalytic hydrogen production. ACS nano. 12, 751–758 (2018). \n38. Wang, Y. Z. et al. Hydrogenated ZnIn2S4 microspheres: boosting photocatalytic hydrogen evolution by sulfur vacancy engineering and mechanism insight. Phys. Chem. Chem. Phys. 21, 25484 (2019). \n39. Ma, Y. W. et al. Carbon inserted defect-rich MoS2-X nanosheets@CdS nanospheres for efficient photocatalytic hydrogen evolution under visible light irradiation. Colloid Interface Sci. 569, 89–100 (2020). \n40. Turner, N. H. & Singlet, A. M. Determination of peak positions and areas from wide-scan XPS spectra. Surf. Interface Anal. 15, 215–222 (1990). \n41. Xu, F. et al. Unique S-scheme heterojunctions in selfassembled TiO2/CsPbBr3 hybrids for CO2 photoreduction. Nat. Commun. 11, 4613 (2020). \n42. Li, P. S. et al. Visible-light-driven nitrogen fixation catalyzed by Bi5O7Br nanostructures: enhanced performance by oxygen vacancies. J. Am. Chem. Soc. 142, 12430–12439 (2020). \n43. Meng, A. L. et al. Molybdenum sulfide-modified metal-free graphitic carbon nitride/black phosphorus photocatalyst synthesized via high-energy ballmilling for efficient hydrogen evolution and hexavalent chromium reduction. J. Hazard. Mater. 413, 125400 (2021). \n44. Fan, L. L. et al. Controllable S-Vacancies of monolayered Mo-S nanocrystals for highly harvesting lithium storage. Nano energy 78, 105235 (2020). \n45. Xu, W. et al. Interfacial chemical bond-modulated Z-scheme charge transfer for efficient photoelectrochemical water splitting. Adv. Energy Mater. 11, 2003500 (2021). \n46. Shen, R. et al. Integrating 2D/2D CdS/α-Fe2O3 ultrathin bilayer Z-scheme heterojunction with metallic $\\upbeta$ -NiS nanosheet-based ohmic-junction for efficient photocatalytic H2 evolution. Appl. Catal. B Environ. 266, 118619 (2020). \n47. Du, C. Yan, Bo & Yang, G. W. Self-integrated effects of 2D ZnIn2S4 and amorphous Mo2C nanoparticles composite for promoting solar hydrogen generation. Nano Energy 76, 105031 (2020). \n48. Qiu, J., Li, M., Yang, L. & Yao Facile construction of three-dimensional netted ZnIn2S4 by cellulose nanofibrils for efficiently photocatalytic reduction of Cr (VI). J. Chem. Eng. J. 375, 121990 (2019). \n49. Lin, Y. et al. The evolution from a typical type-I CdS/ZnS to type-II and ZScheme hybrid structure for efficient and stable hydrogen production under visible light. ACS Sustain. Chem. Eng. 8, 4537–4546 (2020). \n50. Geng, Y. X. et al. Z-Scheme 2D/2D α-Fe2O3/g-C3N4 heterojunction for photocatalytic oxidation of nitric oxide. Appl. Catal. B Environ. 280, 119409 (2021). \n51. Zhao, Z. et al. Recycling of spent alkaline Zn-Mn batteries directly: Combination with TiO2 to construct a novel Z-scheme photocatalytic system. J. Hazard. Mater. 400, 123236 (2020). \n52. Zhu, Q. H. et al. Electron directed migration cooperated with thermodynamic regulation over bimetallic NiFeP $/\\mathrm{g}$ -C3N4 for enhanced photocatalytic hydrogen evolution. Appl. Catal. B Environ. 259, 118078 (2019). \n53. Segall, M. D. et al. First-principles simulation: ideas, illustrations and the CASTEP code. J. Phys.: Condens. Matter 14, 2717–2744 (2002). \n54. Perdew, J., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n55. Vanderbilt, D. Soft self-consistent pseudopotentials in a generalized eigenvalue formalism. Phys. Rev. B. 41, 7892–7895 (1990). \n56. Perdew, J., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple [Phys. Rev. Lett. 77, 3865 (1996)]. Phys. Rev. Lett. 78, 1396–1396 (1997). \n\n# Acknowledgements \n\nThe work reported here was supported by the National Natural Science Foundation of China under Grant No. 51672144, 51572137, 51702181, 52072196, 52002199, 52002200, Major Basic Research Program of Natural Science Foundation of Shandong Province under Grant No. ZR2020ZD09, Shandong Provincial Key Research and Development Program (SPKR&DP) under Grant No. 2019GGX102055, the Natural Science Foundation of Shandong Province under Grant No. ZR2019BEM042, the Innovation and Technology Program of Shandong Province under Grant No. 2020KJA004, Guangdong Basic and Applied Basic Research Foundation (Grant No. 2019A1515110933), China Postdoctoral Science Foundation (Grant No. 2020M683450) and the Taishan Scholars Program of Shandong Province under No. ts201511034. We express our grateful thanks to them for their financial support. \n\n# Author contributions \n\nX.W(1)., A.M., and Z.L. conceived the research. X.W(1). and X.W(2). prepared photocatalysts and conducted all the experiments. X.W(2). and J.H. performed the electrochemistry measurement. S.L. offered help to analyze the characterization experiment data. X.W(1)., X.W(2)., and Z.L. wrote and revised the manuscript. A.M., S.L., and J.H. gave suggestions on the experiment and writing. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-24511-z. \n\nCorrespondence and requests for materials should be addressed to A.M. or Z.L. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contributions to the peer review of this work. Peer review reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1016_j.cpc.2021.108033", + "DOI": "10.1016/j.cpc.2021.108033", + "DOI Link": "http://dx.doi.org/10.1016/j.cpc.2021.108033", + "Relative Dir Path": "mds/10.1016_j.cpc.2021.108033", + "Article Title": "VASPKIT: A user-friendly interface facilitating high-throughput computing and analysis using VASP code", + "Authors": "Wang, V; Xu, N; Liu, JC; Tang, G; Geng, WT", + "Source Title": "COMPUTER PHYSICS COMMUNICATIONS", + "Abstract": "We present the VASPKIT, a command-line program that aims at providing a robust and user-friendly interface to perform high-throughput analysis of a variety of material properties from the raw data produced by the VASP code. It consists of mainly the pre-and post-processing modules. The former module is designed to prepare and manipulate input files such as the necessary input files generation, symmetry analysis, supercell transformation, k-path generation for a given crystal structure. The latter module is designed to extract and analyze the raw data about elastic mechanics, electronic structure, charge density, electrostatic potential, linear optical coefficients, wave function plots in real space, etc. This program can run conveniently in either interactive user interface or command line mode. The command-line options allow the user to perform high-throughput calculations together with bash scripts. This article gives an overview of the program structure and presents illustrative examples for some of its usages. The program can run on Linux, macOS, and Windows platforms. The executable versions of VASPKIT and the related examples and tutorials are available on its official website vaspkit .com. Program summary Program title: VASPKIT CPC Library link to program files: https://doi.org/10.17632/v3bvcypg9v.1 Licensing provisions: GPLv3 Programming language: Fortran, Python Nature of problem: This program has the purpose of providing a powerful and user-friendly interface to perform high-throughput calculations together with the widely-used VASP code. Solution method: VASPKIT can extract, calculate and even plot the mechanical, electronic, optical and magnetic properties from density functional calculations together with bash and python scripts. It can run in either interactive user interface or command line mode. (C) 2021 Elsevier B.V. All rights reserved.", + "Times Cited, WoS Core": 3941, + "Times Cited, All Databases": 4028, + "Publication Year": 2021, + "Research Areas": "Computer Science; Physics", + "UT (Unique WOS ID)": "WOS:000678508900017", + "Markdown": "# VASPKIT: A user-friendly interface facilitating high-throughput computing and analysis using VASP code ✩,✩✩ \n\nVei Wang a,∗, Nan ${\\tt X}{\\tt u}^{\\mathrm{b}}$ , Jin-Cheng Liu c, Gang Tang d, Wen-Tong Geng e \n\na Department of Applied Physics, Xi’an University of Technology, Xi’an 710054, China \nb College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China \nc Department of Chemistry and Key Laboratory of Organic Optoelectronics & Molecular Engineering of Ministry of Education, Tsinghua University, Beijing 100084, \nChina \nd Theoretical Materials Physics, Q-MAT, CESAM, University of Liège, Liège B-4000, Belgium \ne School of Materials Science & Engineering, University of Science and Technology Beijing, Beijing 100083, China \n\n# a r t i c l e i n f o \n\n# a b s t r a c t \n\nArticle history: \nReceived 27 April 2020 \nReceived in revised form 28 April 2021 \nAccepted 5 May 2021 \nAvailable online 28 May 2021 \n\nKeywords: High-throughput Elastic mechanics Electronic properties Optical properties Molecular dynamics Wave-function \n\nWe present the VASPKIT, a command-line program that aims at providing a robust and user-friendly interface to perform high-throughput analysis of a variety of material properties from the raw data produced by the VASP code. It consists of mainly the pre- and post-processing modules. The former module is designed to prepare and manipulate input files such as the necessary input files generation, symmetry analysis, supercell transformation, $k$ -path generation for a given crystal structure. The latter module is designed to extract and analyze the raw data about elastic mechanics, electronic structure, charge density, electrostatic potential, linear optical coefficients, wave function plots in real space, etc. This program can run conveniently in either interactive user interface or command line mode. The command-line options allow the user to perform high-throughput calculations together with bash scripts. This article gives an overview of the program structure and presents illustrative examples for some of its usages. The program can run on Linux, macOS, and Windows platforms. The executable versions of VASPKIT and the related examples and tutorials are available on its official website vaspkit com. \n\n# Program summary \n\nCPC Library link to program files: https://doi org 10 17632 v3bvcypg9v.1 \nLicensing provisions: GPLv3 \nProgramming language: Fortran, Python \nNature of problem: This program has the purpose of providing a powerful and user-friendly interface to perform high-throughput calculations together with the widely-used VASP code. \nSolution method: VASPKIT can extract, calculate and even plot the mechanical, electronic, optical and magnetic properties from density functional calculations together with bash and python scripts. It can run in either interactive user interface or command line mode. \n\n$\\circledcirc$ 2021 Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nWith the rapid development of high-performance computations and computational algorithms, high-throughput computational analysis and discovery of materials has become an emerging research field because it promises to avoid time-consuming try and error experiments and explore the hidden potential behind thousands of potentially unknown materials within short timeframes that the real experiments might take a long time. Density functional theory (DFT) is one of the most popular methods that can treat both model systems and realistic materials in a quantum mechanical way [1–5]. It is not only used to understand the observed behavior of solids, including the structural, mechanical, electronic, magnetic and optical properties, but increasingly more to predict characteristics of compounds that have not yet been determined experimentally [6–12]. \n\nThe last two decades have witnessed tremendous progress in the methodology development for first-principles calculations of materials properties. Dozens of electronic-structure computation packages have been developed based on DFT so far, such as Abinit [13], CASTEP [14], VASP [15,16], Siesta [17], Quantum Espresso [18,19], Elk [20] and WIEN2k [21], with great success in exploring material properties. One of the common features for these packages is that post-processing is required to extract and/or plot into a human-readable format from the raw data. There are two popular commercial programs, Materials Studio [22] and QuantumATK [23], providing a graphical user interface (GUI) that allows the researchers to efficiently build, visualize, and review results and calculation setup up with a set of mouse actions. However, these GUI programs become less productive when the users want to perform batch processing operations. In contrast, several open-source post-processing packages, such as Python Materials Genomics (pymatgen) [24], Atomic Simulation Environment (ASE) [25], and PyProcar [26] provide powerful command-line interfaces to efficiently extract, plot and analyze the raw data in batch mode but require the users to be proficient in Python programming language. It is worth mentioning here that both lev00 [27] and qvasp [28] are two interactive menu-driven programs written in Fortran which mainly focus on the post-processing of electronic structure calculations using VASP and other codes. \n\nIn this article we will introduce a toolkit, referred to as VASPKIT which is developed to provide a robust and user-friendly integrated input/output environment to perform initial setup for calculations and post-processing analysis to derive various material properties from the raw data calculated using the VASP code. It is capable of calculating the elastic, electronic, optical and catalytic properties including equation of state, elastic constants, carrier effective masses, Fermi surfaces, band structure unfolding for supercell models, linear optical coefficients, joint density of states, transition dipole moment, wave functions plots in real space, thermal energy correction, etc. In addition, it also allows the users to perform high-throughput calculations with low barriers to entry. For example, we recently performed high-throughput calculations to screen hundreds of two-dimensional (2D) semiconductors from near 1000 monolayers using this program together with VASP [29]. The VASPKIT remains in development, with growing functionality, and is ready to be extended to work directly with outputs from other electronic structure packages. \n\nThe rest of this paper is organized as follows: In Section 2 the workflow and basic features of the pre-processing module as implemented into VASPKIT are described. Section 3 presents the computational algorithms and some examples illustrating the capabilities of post-processing module in the VASPKIT code. Finally, it ends with the Summary section. \n\n# 2. Capabilities of the pre-processing module \n\nThe workflow of the VASPKIT package is illustrated in Fig. 1. In the pre-processing module, the program first reads the POSCAR file and then prepares the rest three input files (INCAR, POTCAR and KPOINTS) to perform DFT calculations using VASP. It can also manipulate the structure file such as building supercell, generating the suggested $k$ -path for band structure calculation, determining the crystal symmetry information, or finding the conventional/primitive cell for a given lattice by employing the symmetry analysis library Spglib [30]. Furthermore, it can convert POSCAR to several widely-used structural formats, such as XCrysDen (.xsf) [31], Crystallographic Information Framework (.cif) [32] or Protein Data Bank (.pdb) formats [33]. \n\n![](images/fe5d1c2d80fd0f39b3adaad204cdc68d19135556247ec430d464b4fb2ef5c981.jpg) \nFig. 1. (Color online.) A structural overview of the VASPKIT package. \n\n# 2.1. Definitions and conversions of crystal structures \n\nThe crystal structures are often provided by basis vectors and point coordinates of labeled atoms. Lattice basis vectors A are represented by three row vectors \n\n$$\n\\mathbf{A}={\\left(\\begin{array}{l}{\\mathbf{a}}\\\\ {\\mathbf{b}}\\\\ {\\mathbf{c}}\\end{array}\\right)}=\\left({\\begin{array}{l l l}{a_{x}}&{a_{y}}&{a_{z}}\\\\ {b_{x}}&{b_{y}}&{b_{z}}\\\\ {c_{x}}&{c_{y}}&{c_{z}}\\end{array}}\\right).\n$$ \n\nThe position of an ion is represented by a row vector either in fractional coordinates $(x,\\ y,z)$ concerning basis vector lengths or in Cartesian coordinates $(X,Y,Z)$ . The relationship of these two coordinates is written as \n\n$$\n\\left(\\begin{array}{l}{\\boldsymbol{X}}\\\\ {\\boldsymbol{Y}}\\\\ {\\boldsymbol{Z}}\\end{array}\\right)=\\boldsymbol{\\mathsf{A}}^{T}\\left(\\begin{array}{l}{\\boldsymbol{x}}\\\\ {\\boldsymbol{y}}\\\\ {\\boldsymbol{z}}\\end{array}\\right)=\\left(\\begin{array}{l l l}{a_{x}}&{b_{x}}&{c_{x}}\\\\ {a_{y}}&{b_{y}}&{c_{y}}\\\\ {a_{z}}&{b_{z}}&{c_{z}}\\end{array}\\right)\\left(\\begin{array}{l}{\\boldsymbol{x}}\\\\ {\\boldsymbol{y}}\\\\ {\\boldsymbol{z}}\\end{array}\\right),\n$$ \n\nwhere $\\pmb{A}^{T}$ denotes the matrix transpose of lattice basis vectors A. \n\nThe conversion from one lattice basis $(\\mathbf{a},\\mathbf{b},\\mathbf{c})$ to another choice of lattice basis $(\\ensuremath{\\mathbf{a}}^{\\prime},\\ensuremath{\\mathbf{b}}^{\\prime},\\ensuremath{\\mathbf{c}}^{\\prime})$ is given by \n\n$$\n\\left(\\begin{array}{c}{\\mathbf{a}^{\\prime}}\\\\ {\\mathbf{b}^{\\prime}}\\\\ {\\mathbf{c}^{\\prime}}\\end{array}\\right)=\\mathbf{M}\\cdot\\left(\\begin{array}{c}{\\mathbf{a}}\\\\ {\\mathbf{b}}\\\\ {\\mathbf{c}}\\end{array}\\right),\n$$ \n\nwhere $\\mathbf{M}$ is the transformation matrix. Its determinant $|\\mathbf{M}|$ defines the ratio between the supercell and primitive cell volumes in the real space. Fig. 2 shows how to construct a supercell (SC) from the specified transformation matrix and the primitive cell (PC) lattice vectors. \n\n# 2.2. Generation of suggested $k$ -path \n\nIn order to plot a band structure, one needs to define a set of $k$ -points along with desired high-symmetry directions in the Brillouin zone (BZ). The $k$ -path utility automatically generates the suggested $k$ -path for a given 2D [29] or bulk [34] crystal structure. The flowchart of the algorithm to determine the suggested $k$ -path for a given crystal is shown in Fig. 3 (a). Specifically, VASPKIT first determines the space group number, crystal family and \n\n![](images/fe6711702cd5413ae7a59ab75edfda5d5b6a9d517a0b9ee4f5594e3f5bf6cec8.jpg) \nFig. 2. (Color online.) Schematic illustration of building a supercell from the lattice vectors of a primitive cell (PC) and the specified transformation matrix. The supercell and primitive cell are indicated by the yellow and red rhombuses. \n\nBravais lattice type from the input structure, typically read from the POSCAR file; a standardized conventional cell is then identified and constructed by idealizing the lattice vectors based on the axial lengths and the interaxial angles, aiming to eliminate the non-unique choices in the possible shapes of BZ in certain Bravais lattices [35,34]; then the standard primitive cell is determined by transforming the basis vectors of the standard conventional cell according to Eq. (4), \n\n$$\n\\left(\\begin{array}{c}{\\mathbf{a}_{p}}\\\\ {\\mathbf{b}_{p}}\\\\ {\\mathbf{c}_{p}}\\end{array}\\right)=\\mathbf{P}\\cdot\\left(\\begin{array}{c}{\\mathbf{a}_{c}}\\\\ {\\mathbf{b}_{c}}\\\\ {\\mathbf{c}_{c}}\\end{array}\\right),\n$$ \n\nwhere $(\\mathbf{a}_{p},\\mathbf{b}_{p},\\mathbf{c}_{p})$ and $(\\mathbf{a}_{c},\\mathbf{b}_{c},\\mathbf{c}_{c})$ are the basis vectors of primitive and conventional systems, respectively, $\\mathbf{p}$ is the transformation matrix from the standardized conventional cell to the primitive cell, as summarized in Table 3 in Ref. [34], and the subscripts $c$ and $p$ represent the primitive and conventional cells respectively. The atomic position of an ion in fractional coordinates transformed from the basis vectors of a conventional cell to those of primitive cell is written as below: \n\n$$\n\\left(\\begin{array}{c c c}{x_{p}}\\\\ {y_{p}}\\\\ {z_{p}}\\end{array}\\right)=\\mathbf P^{-1}\\left(\\begin{array}{c c c}{x_{c}}\\\\ {y_{c}}\\\\ {z_{c}}\\end{array}\\right).\n$$ \n\nIt should be noted that the number of atoms in the PC is generally less than that in SC. This means that the transformation from SC to PC leads to some duplicated atoms, which must be removed. \n\nIn the final step, the $k$ -path utility automatically saves the standard primitive cell and the suggested $k$ -path into the PRIMCELL.vasp and KPATH.in files respectively. In addition to the automatic generation of the suggested $k$ -path when a crystal structure is given as input, VASPKIT also provides the python script to visualize the specified $k$ -path in the first Brillouin zone using Matplotlib plotting library [36]. As illustrative examples, the recommended $k$ -paths of 2D-rectangular, 2D-oblique and face-centered cubic and hexagonal lattices are show in Fig. 3 (b)-(e) respectively. \n\n# 3. Capabilities of the post-processing module \n\nFig. 4 displays an overview of the post-processing features as implemented into the VASPKIT package. This module is designed to extract and analyze the raw data including elastic mechanics, electronic, charge density, electrostatic potential, optical wavefunction, catalysis and molecular dynamics related properties. We next present the computational algorithms and some examples to illustrate the capabilities of the post-processing module. \n\n# 3.1. Elastic mechanics \n\nThe second-order elastic constants (SOECs) play a crucial role in governing materials’ mechanical and dynamical properties, especially on the stability and stiffness. Within the linear elastic region, the stress $\\sigma=(\\sigma_{1},\\sigma_{2},\\sigma_{3},\\sigma_{4},\\sigma_{5},\\sigma_{6})$ response of solids to external loading strain $\\pmb{\\varepsilon}=(\\varepsilon_{1},\\varepsilon_{2},\\varepsilon_{3},\\varepsilon_{4},\\varepsilon_{5},\\varepsilon_{6})$ satisfies the generalized Hooke’s law and can be simplified in the Voigt notation [37], \n\n$$\n\\sigma_{i}=\\sum_{j=1}^{6}\\mathsf C_{i j}\\varepsilon_{j},\n$$ \n\nwhere strain $\\sigma_{i}$ and stress $\\varepsilon_{j}$ are represented as a vector with 6 independent components respectively, i.e., $1\\leq i,j\\leq6.\\ C_{i j}$ is the second-order elastic stiffness tensor expressed by a $6\\times6$ symmetric matrix in units of GPa. The elastic stiffness tensor ${\\mathsf{C}}_{i j}$ can be determined using the first-order derivative of the stress-strain curves proposed by Nielsen and Martin [38,39], as expressed in Eq. (6). The number of independent elastic constants depends on the symmetry of the crystal. The lower the symmetry means the more the independent elastic constants. For example, the cubic crystals have three but the triclinic ones have 21 independent elastic constants. The classification of the different crystal system with the corresponding number of independent elastic constants for bulk materials is summarized in Table 1 [40–42]. \n\nAn alternative theoretical approach to calculate elastic constants is based on the energy variation by applying minor strains to the equilibrium lattice configuration [43]. The elastic energy $\\Delta E(V,\\{\\varepsilon_{i}\\})$ of a solid under the harmonic approximation is \n\n![](images/68501c03c1829c09c4127aaa051297e6993377f4fa2e883d0da46e35a7c25986.jpg) \nFig. 3. (Color online.) (a) Workflow of the algorithm used in the $k$ -path utility. The first Brillouin zone, special high symmetry points, and recommended $k$ -paths for (a) 2D rectangular, (b) 2D oblique, (c) face-centered cubic and (d) hexagonal close-packed lattices respectively. \n\nTable 1 Classification of crystal systems, point group classes, and space-group numbers are provided with the number of independent second elastic constants for bulk materials. In the last column, several prototype materials are shown. \n\n\n
Crystal systemPoint groupsSpace-groupsNumber of independent SOECsMaterial prototypes
Trilinlinic1-25 213Zr02
Orthorhombic222, mm2, 22216-749TiS2
Tetragonal I, 422,4mm,42m,m89-1426MgF2
Tetragonal II 4.475-887CaMo04
Trigonal I32.3m,32149-1676α-Al03
Trigagal l 143-144
mmm75CaMg(CO3 )2
Cubic432.43m,3195-2303Diamond
\n\n![](images/b2aab9e7e03761a4db8183d8661a454d2d51ed07917c2893d9a123a568ccad69.jpg) \nFig. 4. (Color online.) A structural overview of the post-processing module implemented into the VASPKIT package. \n\ngiven by \n\n$$\n\\begin{array}{r}{\\Delta E\\left(V,\\{\\varepsilon_{i}\\}\\right)=E\\left(V,\\{\\varepsilon_{i}\\}\\right)-E\\left(V_{0},0\\right)}\\\\ {=\\displaystyle\\frac{V_{0}}{2}\\sum_{i,j=1}^{6}C_{i j}\\varepsilon_{j}\\varepsilon_{i},}\\end{array}\n$$ \n\nwhere $E\\left(V_{0},0\\right)$ and $E\\left(V,\\{\\varepsilon_{i}\\}\\right)$ are the total energies of the equilibrium and distorted lattice cells, with the volume of $V_{0}$ and $V$ , respectively. In the energy-strain method the elastic stiffness tensor is derived from the second-order derivative of the total energy versus strain curves [43]. In general, the stress-strain method requires higher computational precision to achieve the same accuracy as the energy-strain method. Nevertheless, it requires less distortion set than the latter [40,41,44,45,43]. Considering that the energy-strain relation has less stress sensitivity than the stressstrain one, the former method has been implemented into the VASPKIT package. Meanwhile, the determination of elastic stability criterion is also provided in the elastic utility based on the necessary and sufficient elastic stability conditions in the harmonic approximation [46] for various crystal systems proposed by Mouhat et al. [40,41,47]. \n\nWhen a crystal is deformed by applying strain $\\pmb\\varepsilon$ , the relation of lattice vectors between the distorted and equilibrium cells is given by \n\n$$\n\\left(\\begin{array}{l}{\\mathbf{a}^{\\prime}}\\\\ {\\mathbf{b}^{\\prime}}\\\\ {\\mathbf{c}^{\\prime}}\\end{array}\\right)=\\left(\\begin{array}{l}{\\mathbf{a}}\\\\ {\\mathbf{b}}\\\\ {\\mathbf{c}}\\end{array}\\right)\\cdot(\\mathbf{I}+\\mathbf{\\epsilon}),\n$$ \n\n![](images/651042cb82e35e40579741214e97c5f4bc9affd4b579bafb4fb4ea47e6cf3556.jpg) \nFig. 5. (Color online.) Workflow of the algorithm to determine the second-order elastic constants based on the energy-strain method used in the elastic utility. \n\nwhere I is the $3\\times3$ identity matrix. The strain tensor $\\epsilon$ is defined by \n\n$$\n\\begin{array}{r}{\\epsilon=\\left(\\begin{array}{l l l}{\\varepsilon_{1}}&{\\varepsilon_{6}/2}&{\\varepsilon_{5}/2}\\\\ {\\varepsilon_{6}/2}&{\\varepsilon_{2}}&{\\varepsilon_{4}/2}\\\\ {\\varepsilon_{5}/2}&{\\varepsilon_{4}/2}&{\\varepsilon_{3}}\\end{array}\\right).}\\end{array}\n$$ \n\nThe workflow of elastic utility is shown in Fig. 5. VASPKIT first reads the equilibrium structure from POSCAR in which both lattice parameters and atomic positions are fully relaxed. In addition, the dimensionality of material (either 2D or 3D) and the number of applied strain $\\pmb\\varepsilon$ need to be specified as input. For 2D materials, in order to avoid mirror interactions the periodic slabs are required to separate by sufficiently large vacuum layer in $c$ direction. In the second step, the space group number and the type of input structure are analyzed by using the Spglib code [30] to determine how many independent elastic constants need to be calculated. A classification of the different crystal system with the corresponding number of independent elastic constants is given in Table 1. Furthermore, a standard conventional cell needs to be adopted in the following calculations since the components of ${\\mathsf{C}}_{i j}$ are dependent on the choice of the coordinate system and lattice vectors. After that, based on the determined space group number, a series of distorted structures with specified values of strain around the equilibrium are generated via Eq. (8). Next, the elastic energies are calculated for each distorted structure by using VASP. Then, a polynomial fitting procedure is applied to calculate the second derivative at the equilibrium of the energy with respect to the strain. Finally, various mechanical properties such as bulk, shear modulus and Poisson’s ratio for polycrystalline materials are determined. \n\nWe take the cubic structure as an example to demonstrate how to calculate its independent elastic constants by using the energystrain method. For cubic system, the three independent elastic constants ${\\mathsf{C}}_{11},{\\mathsf{C}}_{12}$ and $\\mathsf{C}_{44}$ , are expressed in an elastic stiffness tensor matrix \n\n$$\nC_{i j}^{c u b i c}=\\left(\\begin{array}{c c c c c c}{C_{11}}&{C_{12}}&{C_{12}}&{0}&{0}&{0}\\\\ {C_{12}}&{C_{11}}&{C_{12}}&{0}&{0}&{0}\\\\ {C_{12}}&{C_{12}}&{C_{11}}&{0}&{0}&{0}\\\\ {0}&{0}&{0}&{C_{44}}&{0}&{0}\\\\ {0}&{0}&{0}&{0}&{C_{44}}&{0}\\\\ {0}&{0}&{0}&{0}&{0}&{C_{44}}\\end{array}\\right).\n$$ \n\nAfter substituting Eq. (10) into Eq. (7), the elastic energy is written as below: \n\n$$\n\\begin{array}{c}{\\displaystyle{\\frac{\\Delta E}{V}=\\frac{1}{2}(C_{11}\\varepsilon_{1}\\varepsilon_{1}+C_{11}\\varepsilon_{2}\\varepsilon_{2}+C_{11}\\varepsilon_{3}\\varepsilon_{3}+C_{12}\\varepsilon_{1}\\varepsilon_{2}}}\\\\ {\\displaystyle{+C_{12}\\varepsilon_{1}\\varepsilon_{3}+C_{12}\\varepsilon_{2}\\varepsilon_{1}+C_{12}\\varepsilon_{2}\\varepsilon_{3}+C_{12}\\varepsilon_{3}\\varepsilon_{1}}}\\\\ {\\displaystyle{+C_{12}\\varepsilon_{3}\\varepsilon_{2}+C_{44}\\varepsilon_{4}\\varepsilon_{4}+C_{44}\\varepsilon_{5}\\varepsilon_{5}+C_{44}\\varepsilon_{6}\\varepsilon_{6}).}}\\end{array}\n$$ \n\nWhen applied the tri-axial shear strain $ \\pmb{\\varepsilon}\\mathrm{=}(0,0,0,\\delta,\\delta,\\delta)$ , Eq. (10) becomes \n\n$$\n\\frac{\\Delta E}{V}=\\frac{3}{2}C_{44}\\delta^{2}.\n$$ \n\nSimilarly, $C_{11}{+}C_{12}$ can be obtained by using the strain $ \\varepsilon=(\\delta,\\delta,0,$ 0,0,0): \n\n$$\n\\frac{\\Delta E}{V}=\\left(C_{11}+C_{12}\\right)\\delta^{2}.\n$$ \n\nAlso, $C_{11}+2C_{12}$ is calculated using the strain $\\pmb{\\varepsilon}\\mathrm{=}(\\delta,\\delta,\\delta,0,0,0)$ : \n\n$$\n\\frac{\\Delta E}{V}=\\frac{3}{2}\\left(C_{11}+2C_{12}\\right)\\delta^{2}.\n$$ \n\nIn order to calculate the elastic stiffness constants given above, the elastic energies of a set of deformed configurations in the distortion range $-2\\%\\leq\\delta\\leq+2\\%$ with an increment of $0.5\\%$ are investigated using VASP. After that, the quadratic coefficients are determined by fitting the energy versus distortion relationship, and finally the second-order elastic constants $C_{i j}$ are determined by solving the equations (12)-(14) during the post-processing of elastic utility. The details of strain modes and the derived elastic constants for each crystal system based on the energy-strain approach are listed in Appendix A. \n\nThe crystallites are randomly oriented for polycrystalline materials, and such materials can be considered quasi-isotropic or isotropic in a statistical sense. Thus, the bulk modulus $K$ and shear modulus $G$ are generally obtained by averaging the singlecrystal elastic constants. Three of the most widely used averaging approaches have been implemented into the elastic utility: Voigt [37], Reuss [48], and Hill [49] schemes. Hill has shown that the Voigt and Reuss elastic moduli are the strict upper and lower bounds [49], respectively. The arithmetic mean of the Voigt and Reuss bounds termed the Voigt-as Reuss-Hill (VRH) average, is a better approximation to a polycrystalline material’s actual elastic behavior. \n\nThe Voigt bounds are given by the following equations: \n\n$$\n\\left\\{\\begin{array}{l l}{9K_{\\mathrm{V}}=(C_{11}+C_{22}+C_{33})+2(C_{12}+C_{23}+C_{31})}\\\\ {15G_{\\mathrm{V}}=(C_{11}+C_{22}+C_{33})-(C_{12}+C_{23}+C_{31})}\\\\ {\\quad+4(C_{44}+C_{55}+C_{66})}\\end{array}\\right.,\n$$ \n\nwhile the Reuss bounds are given by: \n\n$$\n\\left\\{\\begin{array}{l}{{1/K_{\\mathrm{R}}=(\\mathsf{S}_{11}+\\mathsf{S}_{22}+\\mathsf{S}_{33})+2(\\mathsf{S}_{12}+\\mathsf{S}_{23}+\\mathsf{S}_{31})}}\\\\ {{15/G_{\\mathrm{R}}=4(\\mathsf{S}_{11}+\\mathsf{S}_{22}+\\mathsf{S}_{33})-4(\\mathsf{S}_{12}+\\mathsf{S}_{23}+\\mathsf{S}_{31})}}\\\\ {{\\qquad+3(\\mathsf{S}_{44}+\\mathsf{S}_{55}+\\mathsf{S}_{66})}}\\end{array}\\right.,\n$$ \n\nwhere $S_{i j}$ are the components of compliance tensor, which correspond to the matrix elements of the inverse of the elastic tensor, namely, $\\left[S_{i j}\\right]=\\left[C_{i j}\\right]^{-1}$ . Based on the Voigt and Reuss bounds, Hill defined $K_{\\mathsf{V R H}}=1/2(K_{\\mathsf{V}}+K_{\\mathsf{R}})$ and $G_{\\mathsf{V R H}}=1/2(G_{\\mathsf{V}}+G_{\\mathsf{R}})$ , known as the Voigt-Reuss-Hill average [49]. Using the values of bulk modulus $K$ and shear modulus $G$ , the Young’s modulus $E$ and Poisson’s ratio $\\nu$ can be obtained by $\\begin{array}{r}{E=\\frac{9K G^{-}}{3K+G}}\\end{array}$ and $\\begin{array}{r}{\\nu=\\frac{3K-2G}{2(3K+G)}}\\end{array}$ , respectively. \n\nFor 2D materials, VASPKIT assumes the crystal plane in the xy plane. Then the relation between strain and stress can be written in the following form [40,50] \n\n$$\n\\left(\\begin{array}{l}{\\sigma_{1}}\\\\ {\\sigma_{2}}\\\\ {\\sigma_{6}}\\end{array}\\right)=\\left(\\begin{array}{l l l}{\\mathsf{C}_{11}}&{\\mathsf{C}_{12}}&{\\mathsf{C}_{16}}\\\\ {\\mathsf{C}_{21}}&{\\mathsf{C}_{22}}&{\\mathsf{C}_{26}}\\\\ {\\mathsf{C}_{61}}&{\\mathsf{C}_{62}}&{\\mathsf{C}_{66}}\\end{array}\\right)\\cdot\\left(\\begin{array}{l}{\\varepsilon_{1}}\\\\ {\\varepsilon_{2}}\\\\ {\\varepsilon_{6}}\\end{array}\\right),\n$$ \n\nwhere ${{C}_{i j}}$ $(i,j=1,2,6)$ is the in-plane stiffness tensor. The strain tensor $\\epsilon$ in Eq. (9) is simplified as \n\n$$\n\\epsilon^{2D}=\\left(\\begin{array}{l l l}{\\varepsilon_{1}}&{\\varepsilon_{6}/2}&{0}\\\\ {\\varepsilon_{6}/2}&{\\varepsilon_{2}}&{0}\\\\ {0}&{0}&{0}\\end{array}\\right).\n$$ \n\nThen the elastic strain energy per unit area based on the strainenergy method can be expressed as [51] \n\n$$\n\\begin{array}{r}{\\Delta E\\left({S},\\{\\varepsilon_{i}\\}\\right)=\\displaystyle\\frac{S_{0}}{2}(C_{11}\\varepsilon_{1}^{2}+C_{22}\\varepsilon_{2}^{2}+2C_{12}\\varepsilon_{1}\\varepsilon_{2}}\\\\ {+2C_{16}\\varepsilon_{1}\\varepsilon_{6}+2C_{26}\\varepsilon_{2}\\varepsilon_{6}+C_{66}\\varepsilon_{6}^{2}),}\\end{array}\n$$ \n\nwhere $S_{0}$ is the equilibrium area of the system. Clearly, the ${\\mathsf{C}}_{i j}$ is equal to the second partial derivative of strain energy $\\Delta E$ with respect to strain $\\varepsilon$ , namely, $\\mathsf{C}_{i j}=(1/S_{0})(\\partial^{2}\\Delta E/\\partial\\varepsilon_{i}\\partial\\varepsilon_{j})$ . Therefore, the unit of elastic stiffness tensor for 2D materials is force per unit length $\\left(\\mathsf{N}/\\mathsf{m}\\right)$ . The classification of the different crystal system with the corresponding number of independent elastic constants and elastic stability conditions for 2D materials are summarized in Table 2. The details of strain modes and the derived elastic constants for each 2D crystal system based on the energy-strain approach are listed in Appendix B. \n\nIn order to provide a benchmark for computational studies, we list the calculated second-order elastic constants for bulk and 2D prototype materials belonging to different crystal systems in Tables 3 and 4 respectively, together with other theoretical values [41,52–54] for comparison purposes. It is found that the results produced with different DFT codes are in good agreement with each other. \n\n# 3.2. Equations of state \n\nThermodynamic equations of state (EOS) for crystalline solids describe the relationships among the internal energy E, pressure $P$ , volume $V$ and temperature $T$ . It plays a crucial role in predicting the structural and thermodynamical properties of materials under high pressure and high temperature in condensed matter sciences [55], especially in extreme conditions such as earth or planetary interiors where the properties of materials are quite different from those found at ambient conditions [56]. Various EOS formulas have been proposed. One of the most widely used isothermal EOSs in solid-state physics is the Murnaghan EOS model assuming that the bulk modulus varies linearly with pressure [57]. The resulting energy–volume relationship is given as: \n\n$$\nE(\\nu)=E_{0}+\\frac{B V_{0}}{(C+1)}\\left(\\frac{\\nu^{-C}-1}{C}+\\nu-1\\right),\n$$ \n\nTable 2 Classification of crystal systems and independent elastic constants for 2D materials [50]. In the last column, several prototype materials are shown. \n\n\n
Crystal systemNumber of independent SOECsIndependent SOECsMaterial prototypes
Oblique6C11,C12,C22,C16,C26,C66
Rectangle4C11, C12, C22, C66Borophene
Square3C11,C12,C66SnO
Hexagonal2C11, C12Graphene, MoS2
\n\nTable 3 PBE-calculated elastic stiffness constants (in units of $\\mathbf{GPa}$ ) for $Z\\mathrm{r}0_{2}$ , $\\mathrm{TiS}_{2}$ , $\\mathrm{MgF}_{2}$ , $\\mathsf{C a M o O}_{4}$ , $\\alpha{\\mathrm{-}}{\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ , $\\mathsf{C a M g}(\\mathsf{C O}_{3})_{2}$ , Ti and Diamond. For comparison purposes, the available theoretical values from the literature are also shown [41]. \n\n\n
CijZr02TiS2MgF2CaMo04α-A03CaMg(CO3)2TiDiamond
Calc.Ref.Calc.Ref.Calc.Ref.Calc.Ref.Calc.Ref.Calc.Ref.Calc.Ref.Calc.Ref.
C1133433431431213413013012645245119219418418910511052
C1215515129288078535814915164678385127125
C13828278845955474610810854577874
C1420211718
C1526321312
C16 C223523563113061010
C231461422521
C24 C2552
C26263251404406192185112110455452107108197187
C33 C34
C35 C3627
C45 C44787173735261302913313237394641560559
C461515
C557071100106
C56 C6611311511811790833834
\n\nTable 4 PBE-calculated in-plane elastic stiffness constants (in units of $\\mathrm{{N/m}}{\\mathrm{{.}}}$ ). For comparison purposes, the available theoretical or experimental values from the previous literature are also shown. \n\n\n
SystemsC11C22C12C66
Our workLiteratureOur workLiteratureOur workLiteratureOur workLiterature
Graphene349.1358.1 [52]60.360.4 [52]
MoS2128.9131.4 [53]32.632.6 [53]
SnO48.1438.939.0
Phosphorene104.4105.2 [54]34.026.2 [54]21.618.4 [54]27.4
\n\nwhere $\\begin{array}{r}{\\nu=\\frac{V}{V_{0}}}\\end{array}$ , $V_{0}$ and $E_{0}$ are the volume and energy at zero pressure respectively. The values of bulk modulus $K$ and its pressure derivative $K^{\\prime}$ can be further deduced in terms of the fitting parameters $B$ and C. The bulk modulus $K$ is a measure of the resistance of a solid material to compression. It is defined as the proportion of volumetric stress related to the volumetric strain for any material, namely, \n\n$$\nK=-V\\left({\\frac{\\partial P}{\\partial V}}\\right)_{T}.\n$$ \n\nThe workflow of EOS utility is similar to that of the elastic constants presented in Fig. 5. In addition to the equilibrium volume and bulk modulus, pressure and energy as functions of volume are also provided in this utility. Very recently, Latimer et al. evaluated the quality of fit for the 8 widely-used EOS models listed in Table 5 across 87 elements and over 100 compounds [55]. They pointed out that it is hard to find a universal EOS model applicable to all types of solids and accurate over the whole range of pressure. Furthermore, their results reveal that the Birch-Euler [58], Tait [59], and Vinet [60] models give the best overall quality of fit to the calculated energy-volume curves among all the equations under examination. However, the inconsistencies among these investigated equations are not significant. As a benchmark test, the calculated energy and pressure of diamond as a function of volume using different EOS models are presented in Fig. 6. One can find that the agreement among these EOS fits is very satisfactory on the whole. The calculated bulk modulus ranges from 440 GPa to $442\\mathsf{G P a}$ , in good agreement with the experimental value of 443 GPa [61]. \n\n# 3.3. Band structure and density of states \n\nThe band structure is one of the essential concepts in solid-state physics. It provides the electronic levels in crystal structures, which are characterized by two quantum numbers, the band index n and the Bloch vector $\\mathbf{k},$ along with high symmetry directions in the BZ. Besides the band structure, the density of states (DOS) is another quantity that is defined as the number of states per interval of energy at each energy level that is available to be occupied by electrons. A high DOS at a specific energy level means that there are many states available for occupation and zero DOS means that no state can be occupied at that energy level. DOS can be used to calculate the density of free charge carriers in semiconductors, the electronic contribution to the heat capacity in metals. Moreover, it also provides an indirect description of magnetism, chemical bonding, optical absorption spectrum, etc. \n\nTable 5 The analytic formulae of energy-volume relation and bulk modulus $K$ for several widely used EOS models based on Table 1 of Ref. [55]. \n\n\n
ModelInternal energy EBulk modulus K (v =1)
Birch (Euler)[58]E=Eo+Bvo((v--1)²+(v-²-1)3)
Birch (Lagrange) [58]E=Eo+BVoC-Bvo(C-2)(1-v3)²+c(1-v)+C
Mie-Gruneisen [62]E=E+(B-9
Murnaghan [57]+-1) 3c(1-v E=Eo+(+)B
Pack-Evans-James [63]E=Eo+BVB
Poirier-Tarantola [64]E =Eo+BVo(In(v))2(3-C(In(V)))6B
Tait [59]E=Eo+B (v-1+(ec(-)1))B
Vinet [60]E=Eo+BV 1-(1+c(v-1))e-c(B-9
\n\n![](images/293ee32d2be126cf78f099e2d8d16c77009cbd3be033f659b2ac5746b77765bf.jpg) \nFig. 6. (Color online.) The equations of states of diamond using different EOS models as listed in Table 5. \n\nIn addition to the conventional plain band structure, VASPKIT can also deal with the projected band which provides insight into the atomic orbital contributions in each state. As illustrated examples, the projected band structures and density of states (DOS) of BiClO $\\left(P4/n m m\\right)$ and graphene monolayers are depicted in Fig. 7. To illustrate the band dispersion anisotropy of 2D materials, the 3D global band structures of the highest valence and lowest conduction bands for MoTe2 $(P\\overline{{6}}m2)$ and BiIO are shown in Fig. 8. \n\n# 3.4. Effective masses of carriers \n\nGenerally, the band dispersions close to conduction or valence band extrema can be approximated as parabolic for the semiconductors with low carrier concentrations. Consequently, the analytical expression of effective masses of carriers (EMC) $m^{*}$ for electrons and holes (in units of electron mass $m_{0}$ ) is given by \n\n$$\nm^{*}=\\hbar^{2}\\left[\\frac{\\partial^{2}E(k)}{\\partial^{2}k}\\right]^{-1},\n$$ \n\nwhere $E(k)$ are the energy dispersion relation functions described by band structures, and $\\hbar$ is the reduced Planck constant. Clearly, $m^{*}$ is inversely proportional to the curvature of the electronic dispersion in reciprocal space, implying that CB and VB edges with larger dispersions result in smaller effective masses. It is noteworthy that the above expression should not be used in non-parabolic band dispersion cases, for example, the linear dispersion in the band edges of graphene [65]. Similarly, the Fermi velocity represents the group velocity of electrons traveling in the material is defined as \n\n$$\n\\nu_{F}=\\frac{1}{\\hbar}\\frac{\\partial E}{\\partial k}.\n$$ \n\nFig. 9 (a) illustrates the determination of effective masses by fitting the band dispersion with a second-order polynomial schematically. The effective masses of carriers are calculated using an ultrafine $k$ -mesh of density uniformly distributed inside a circle of radius $k$ -cutoff. Haastrup et al. pointed out that the inclusion of third-order terms stabilizes the fitting procedure and yields the effective masses that are less sensitive to the details of the employed $k$ -mesh [53]. Thus, a third-order polynomial is also adopted to fit the band energy curvature in the EMC utility. In Table 6 we show the calculated effective masses for several typical 2D and bulk semiconductors with available effective mass data, including Phosphorene [53], $\\mathsf{M o S}_{2}$ [53], GaAs [66] and Diamond [67]. Overall, the agreement is excellent. In addition, the EMC utility can also calculate the orientation-dependent effective masses of charge carriers. Examples of this functionality are shown in Fig. 9 (b)-(e). One can find that the calculated effective masses of two investigated systems show strong anisotropy, especially for the case of bulk Si. \n\n# 3.5. Charge density and potential manipulation \n\nFor spin-polarized systems, the charge density $\\rho({\\bf r})$ and magnetization (spin) density $m(\\mathbf{r})$ are defined as \n\n$$\n\\begin{array}{r}{\\rho(\\mathbf{r})=\\rho_{\\uparrow}(\\mathbf{r})+\\rho_{\\downarrow}(\\mathbf{r})}\\\\ {m(\\mathbf{r})=\\rho_{\\uparrow}(\\mathbf{r})-\\rho_{\\downarrow}(\\mathbf{r})}\\end{array},\n$$ \n\nwhere $\\rho_{\\uparrow}({\\bf r})$ and $\\rho_{\\downarrow}(\\mathbf{r})$ are the spin-up and spin-down densities. Note that the $\\rho_{\\uparrow}({\\bf r})=\\rho_{\\downarrow}({\\bf r})$ in non-spin-polarized cases. The spin density $\\rho_{\\sigma}({\\bf r})$ is expressed as \n\n$$\n\\rho_{\\sigma}\\left(\\mathbf{r}\\right)=\\sum_{o c c}\\varphi_{i\\sigma}^{*}\\left(\\mathbf{r}\\right)\\varphi_{i\\sigma}\\left(\\mathbf{r}\\right),\n$$ \n\nwhere $\\sigma$ and $i$ are the spin- and band-index, respectively, $\\varphi_{i\\sigma}(\\mathbf{r})$ is the normalized single-particle wave-function. occ means that summation is over all occupied states. \n\nThe charge density difference $\\Delta\\rho({\\bf r})$ can track the charge transfer and gain information of the interaction between the two parts that constitute the system. The $\\Delta\\rho_{(}\\mathbf{r})$ can be obtained \n\n$$\n\\Delta\\rho({\\bf r})=\\rho_{\\mathrm{AB}}({\\bf r})-\\rho_{\\mathrm{A}}({\\bf r})-\\rho_{\\mathrm{B}}({\\bf r}),\n$$ \n\n![](images/d6c9a08b04b1cf6f6c5a78119f16f3193dd86e5b38b4be81ae8b390c2627ee19.jpg) \nFig. 7. (Color online.) Projected band structure (left panel) and density of states (right panel) of (a) BiClO $(P4/n m m^{\\cdot}$ ) and (b) graphene monolayers. The Fermi energy is set zero eV. \n\n![](images/39b616578dc982be782e31a4dd43631a51ac0ec79f04b01ac0e7763594abefd4.jpg) \nFig. 8. (Color online.) The global band structures of the highest valence and lowest conduction bands for (a) MoTe2 ( $P\\overline{{6}}m2)$ and (b) BiIO $\\left(P4/n m m\\right)$ monolayers. The Ferm energy is set to zero. \n\n![](images/cd4660ec748a44e9224494c3cf222b1ff4e26ff5c72623e8a9caba486bb8a8c6.jpg) \nFig. 9. (Color online.) (a) Schematic illustration of the determination of effective masses based on second-order polynomial fitting around the conduction and valence ban extrema. Orientation-dependent effective masses (in units of electron mass $m_{0}$ ) of (b, d) hole and (c, e) electron carriers for 2D BN monolayer (b, c) and bulk Si (d, e respectively. \n\nTable 6 The calculated effective masses of electron $m_{e}$ and hole $m_{h}$ carriers (in units of the electron mass ${\\mathfrak{m}}_{0}$ ) for typical semiconductors using PBE approach. The masses are labeled by the band extremum and the direction of the hight symmetry line along which the mass is calculated using a simple parabolic line fit. The labels of high-symmetry points are adopted from the Ref. [34]. \n\n\n
MaterialDirectionElectron mass (me)Hole mass (mh)
Our workLiteratureOur workLiterature
Phosphorene → X (zig-zag)1.231.24 [53]7.216.56 [53]
Phosphorene → Y (armchair)0.190.14 [53]0.170.13 [53]
MoS2 monolayerK→0.470.42 [53]0.560.53[53]
GaAs bulk→X0.060.07 [66]0.350.34 [66]
Diamond bulk→X0.320.29 [67]0.270.36 [67]
\n\n![](images/22100ab9aab39ae13265e8ee2ef90b60b912a4ee5ac6da994d66979ef73c02f2.jpg) \nFig. 10. (Color online.) Calculated (a) charge density difference, planar- (blue line) and macroscopic averages (red line) of (b) charge density difference, (c) electrostati potential of a GaAs/AlAs (100) heterojunction, and (d) electrostatic potential of a GaAs (110) slab. Ga atoms are shown in purple, As are blue, and Al are red. \n\nwhere $\\rho_{\\mathsf{A}}(\\mathbf{r})$ , $\\rho_{\\mathrm{B}}({\\bf r})$ and ${\\rho}_{\\mathsf{A B}}(\\mathbf{r})$ are the charge density of reactants A and B, and product C. VASPKIT can extract charge-density, spindensity, electrostatic potential as well as the difference of these quantities, and save them in VESTA (.vasp) [15,16,68], XCrysDen (.xsf) [31], or Gaussian (.cube) formats [69]. \n\nFrom the three-dimensional electronic charge density and electrostatic potential one can get the average one-dimensional charge density $\\overline{{n}}(z)$ and electrostatic potential $\\overline{{V}}(z)$ by calculating the planar average function $({\\overline{{f}}})$ [70]: \n\n$$\n\\overline{{f}}(z)=\\frac{1}{S}\\int V(\\mathbf{r})d x d y,\n$$ \n\nwhere S represents the area of a unit cell in the $x-y$ plane. Generally, this planar-averaged charge density and potential exhibit periodic oscillations along the $z$ axis due to the spatial distribution of the electrons and ionic cores. These oscillations can be removed using a macroscopic averaging procedure [70]: \n\n$$\n\\overline{{\\overline{{f}}}}(z)=\\frac{1}{L}\\int\\displaylimits_{-L/2}^{L/2}\\overline{{f}}(z)d z,\n$$ \n\nwhere $L$ is the length of the period of oscillation along $z$ . By definition, this macroscopic average would produce a constant value in the bulk. It is expected to reach a plateau value in the bulk-like regions of each layer in the superlattice. As an example, Fig. 10 shows the calculated planar and macroscopic averages of charge density difference and electrostatic potential for a (100)-oriented GaAs/AlAs heterojunction and a (110)-oriented GaAs slab, respectively. \n\n# 3.6. Fermi surface \n\nFermi surface is the surface in reciprocal space which separates occupied from unoccupied electron states at zero temperature [71]. It is defined to be the set of $k$ -points such that $E({\\bf k})=\\mu$ for any band index $n$ , where $\\mu$ is the Fermi energy. The shape of the Fermi surface is derived from the periodicity and symmetry of the crystalline lattice, and the occupation of electronic energy bands. The knowledge of the topology of the Fermi surface is vital for characterizing and predicting the thermal, electronic and magnetic properties. To calculate the Fermi surface, one first needs to use VASPKIT to determine the $k$ -mesh $N_{1}{\\times}N_{2}{\\times}N_{3}$ based on the specified $k$ -spacing value. The $k$ -spacing is defined as the smallest allowed spacing between the $k$ -points in BZ, that is, $N_{i}=\\operatorname*{max}\\left(1,\\left|\\mathbf{b}_{i}\\right|/k\\mathrm{spacing}\\right)$ , where $\\left|\\mathbf{b}_{i}\\right|$ is the length of the reciprocal lattice vector in the $i-t h$ direction. To reduce the computational cost, only the eigenvalues at the inequivalent $k$ -points in the irreducible Brillouin zone are calculated using VASP. Then these $k$ - points with the sum of the corresponding weight can be mapped to fill the entire BZ using symmetry operations without approximation during the post-processing. The resulting Fermi surface can be visualized using the XcrysDen [31] or FermiSurfser programs [72]. To illustrate the capabilities of this utility, the calculated Fermi surfaces of copper colored by the atomic orbital projected weights are shown in Fig. 11. \n\n![](images/2090da2b89c5db2c34e47b736dfba9c388d8754f3ac6cb78aab9629706591005.jpg) \nFig. 11. (Color online.) (a) Plain Fermi surface of Cu. Orbital-resolved Fermi surface of (b) Cu-s, (c) $\\mathtt{C u}{-}p$ and (d) Cu-d states respectively, visualized by the FermiSurfser ackage [72]. The color denotes the weight of the states. \n\n# 3.7. Wave-function visualization \n\nTo visualize wave functions, VASPKIT first reads the plane wave (PW) coefficients $\\psi_{n\\mathbf{k}}(\\mathbf{k})$ of the specified wave-vector $\\mathbf{k}$ -point and band-index $n$ from the WAVECAR file, and performs a fast Fourier transform (FFT) algorithm to convert the $\\psi_{n\\mathbf{k}}(\\mathbf{k})$ from the reciprocal space to the real space, as denoted by $\\psi_{n\\mathbf{k}}(\\mathbf{r})$ . The $\\psi_{n\\mathbf{k}}(\\mathbf{r})$ can thus be obtained \n\n$$\n\\psi_{n\\mathbf{k}}(\\mathbf{r})=\\sum_{\\mathbf{G}}C_{n\\mathbf{k}}(\\mathbf{k+G})\\mathrm{e}^{\\mathrm{i}(\\mathbf{k+G})\\cdot\\mathbf{r}},\n$$ \n\nwhere $\\textbf{\\^{G}}$ is the reciprocal lattice vector, and $C_{n\\mathbf{k}}(\\mathbf{k}+\\mathbf{G})$ is the PW coefficient of the wave vector $\\mathbf{k}+\\mathbf{G}$ and band-index $n$ in reciprocal space. Examples of the calculated wave function plots in real space are shown in Fig. 12. \n\n# 3.8. Band structure unfolding \n\nThe electronic structures of materials are perturbed by structural defects, impurities, fluctuations of the chemical composition, etc. In DFT calculations, these defects and incommensurate structures are usually investigated by using SC models. Nevertheless, it is difficult to compare the SC band structure directly with the PC band structure due to the folding of the bands into the smaller SC Brillouin zone (SBZ). Popescu and Zunger proposed the effective band structures (EBS) method which can unfold the SC band structures into the corresponding PC Brillouin zone (pbz) [73,74]. Such a delicate technique greatly simplifies the analysis of the results and enables direct comparisons with electronic structures of pristine materials. \n\n![](images/84c04eadd363be7125a206a84c68bc6c5d95d7e466b13f508af178b2a457c90a.jpg) \nFig. 12. (Color online.) Calculated isosurfaces of wave functions in real space for (a) CO molecule, (b) VBM and (c) CBM for graphene respectively, visualized by the VESTA package [68]. \n\nAs aforementioned, the SC and PC lattice vectors satisfy $\\pmb{A}=$ $\\mathbf{M}\\cdot\\mathbf{a}$ where A and a are the lattice vectors of SC and PC. The elements of transformation matrix $\\mathbf{M}$ are integers $\\left(m_{i j}\\in\\mathbb{Z}\\right)$ when building SC from PC. In the band unfolding utility, the transformation matrix is not required to be diagonal. In other words, the SC and PC lattice vectors do not need to be collinear. Following a general convention, capital and lower case letters indicate the quantities in the SC and PC, respectively, unless otherwise stated. A similar relation holds in reciprocal space: \n\n$$\n\\mathbf{B}=\\left(\\mathbf{M}^{-1}\\right)^{T}\\cdot\\mathbf{b},\n$$ \n\nwhere $\\textbf{B}$ and $\\mathbf{b}$ are the reciprocal lattice vectors of the SC and PC, respectively. The reciprocal lattice vectors ${\\bf g}_{n}({\\bf G}_{m})$ in the pbz (SBZ) are expressed as \n\n$$\n\\begin{array}{r l}&{\\mathbf{g}_{n}=\\sum_{i}n_{i}\\mathbf{b}_{i},\\quad n_{i}\\in\\mathbb{Z}}\\\\ &{\\mathbf{G}_{m}=\\sum_{i}m_{i}\\mathbf{B}_{i},\\quad m_{i}\\in\\mathbb{Z}}\\end{array},\n$$ \n\nwhere $\\{\\mathbf{g}_{n}\\}\\subset\\{\\mathbf{G}_{m}\\}$ , i.e., every reciprocal lattice vector of the pbz is also one of the SBZ. \n\nFor a given $\\mathbf{k}$ in pbz, there is a $\\textbf{K}$ in the SBZ, and the two vectors are related by a reciprocal lattice vector G in the SBZ: \n\n$$\n\\mathbf{k}=\\mathbf{K}+\\mathbf{G}_{i},i=1,\\ldots,N_{\\mathbf{K}},\n$$ \n\nwhere $N_{\\mathbf{K}}$ is the determinant $|M|$ that determines the multiplicity of the SC. When choosing plane waves as the basis functions, the projection of the SC eigenstates $|\\psi_{m\\bf{K}}^{\\mathrm{SC}}\\rangle$ on the PC eigenstates $|\\psi_{n\\bf{k}}^{\\mathrm{PC}}\\rangle$ is given by the spectra weight $P_{{\\bf K}m}$ [73,74]: \n\n![](images/1629f4cd4044b29f280f1db994081a337201ab9f83855f43b9204d5ce8e505d0.jpg) \nFig. 13. (Color online.) (a) Workflow of the algorithm used in the band unfolding utility. (b) Band structure of $3\\times3$ graphene SC along with the high-symmetry directions in pbz. The blue lines and red makers represent the band structure before and after applying the unfolding technique. The Fermi energy is set to zero. \n\n$$\n\\begin{array}{l}{{\\displaystyle P_{{\\bf K}m}\\left({\\bf k}_{i}\\right)=\\sum_{n}\\left|\\left\\langle\\psi_{m\\bf K}^{\\mathrm{SC}}\\mid\\psi_{n\\bf k}^{\\mathrm{PC}}\\right\\rangle\\right|^{2}=\\sum_{\\bf g}|C_{m\\bf K}\\left({\\bf g}+{\\bf k}_{i}-{\\bf K}\\right)|^{2}}\\ ~}\\\\ {{\\displaystyle~=\\sum_{\\bf g}|C_{m\\bf K}\\left({\\bf g}+{\\bf G}_{i}\\right)|^{2}},}\\end{array}\n$$ \n\nwhere $m$ and $n$ stand for band indices at vectors $\\textbf{K}$ and $\\mathbf{k}_{i}$ in the reciprocal space of the SC and $\\mathsf{P C}$ , respectively. $C_{m\\mathbf{K}}$ is the PW coefficients given by Eq. (29) that span the eigenstates of the SC. This implies that the required information about the PC is the reciprocal lattice vectors of the primitive cell $\\textbf{g}$ only, and the knowledge of the PC eigenstates is not necessary. All the filtered $C_{m\\mathbf{K}}\\left(\\mathbf{g}+\\mathbf{G}_{j}\\right)$ coefficients only contribute to the spectral function. The quantity $P_{{\\bf K}m}$ represents the amount of Bloch character $\\mathbf{k}_{i}$ preserved in $|\\psi_{n\\bf{k}}^{\\mathrm{PC}}\\rangle$ at the same energy $E_{n}=E_{m}$ . \n\nThe workflow of band unfolding utility is schematically shown in Fig. 13(a). Three input files including the information of SC structure, the transformation matrix M, and the selected $\\mathbf{k}_{i}$ vectors in pbz are required to provide respectively. To compare the unfolded band structure of SC with the band structure of PC directly, the $\\mathbf{k}_{i}$ vectors are generally sampled along with the highsymmetry directions in pbz and then translated in the SC reciprocal space by the transformation as described in Eq. (33) \n\n$$\n\\mathbf{K}=\\mathbf{M}\\cdot\\mathbf{k}_{i},\n$$ \n\nwhere $\\textbf{K}$ and $\\mathbf{k}_{i}$ are the scaled coordinates with respect to the SC and PC reciprocal basis vectors, respectively. After reading PW coefficients and eigenvalue of each state from the WAVECAR obtained by performing VASP calculation, the intricate supercell states can be unfolded back into the larger pbz by applying the unfolding technique via Eq. (32). Finally, the unfolded band can be visualized with the maker size proportional to the spectral weight $P_{{\\bf K}m}$ . From Fig. 13(b), it is clear that folding the bands into the smaller SBZ gives rise to quite a sophisticated band structure. In contrast, one can gain more straightforward analysis once the supercell states are unfolded into the pbz despite the equivalence between the PC and the SC descriptions of a perfectly periodic material. \n\nIt is well known that intrinsic defects (vacancies, self-interstitials, and antisites) and unintentional impurities have important effects on the properties of semiconductors. As a typical case, we take the $4\\times3~\\mathsf{M o S}_{2}$ monolayer SC with one neutral sulfur vacancy to demonstrate the role of intrinsic defect on the electronic structure of the pristine host. The calculated effective band structures of pristine and defective $\\mathsf{M o S}_{2}$ supercells in Fig. 14 (a) and (b), respectively. By comparing these two, one can find two nearly degenerated defect states existing in the fundamental band gap of $\\mathsf{M o S}_{2}$ . The orbital-resolved unfold band structures as shown in Figs. (c) and (d) further demonstrate that these two defect states are mainly derived from Mo- $\\cdot d$ and $S{-}p$ states respectively. Furthermore, the Bloch character close to the valence band edge is perturbed due to the presence of the sulfur vacancy. \n\n# 3.9. Linear optical properties \n\nThe linear optical properties of semiconductors can be obtained from the frequency-dependent complex dielectric function $\\varepsilon(\\omega)$ \n\n$$\n\\varepsilon(\\omega)=\\varepsilon_{1}(\\omega)+i\\varepsilon_{2}(\\omega),\n$$ \n\nwhere $\\varepsilon_{1}(\\omega)$ and $\\varepsilon_{2}(\\omega)$ are the real and imaginary parts of the dielectric function, and $\\omega$ is the photon frequency. Within the oneelectron picture, the imaginary part of the dielectric function $\\varepsilon_{2}(\\omega)$ is obtained from the following equation [75]: \n\n$$\n\\begin{array}{l}{{\\displaystyle\\varepsilon_{2}(\\omega)=\\frac{4\\pi^{2}e^{2}}{\\Omega}\\operatorname*{lim}_{q\\rightarrow0}\\frac{1}{q^{2}}}\\ ~}\\\\ {{\\displaystyle~\\times\\sum_{c,\\nu,\\mathbf{k}}2w_{\\mathbf{k}}\\delta\\left(E_{c}-E_{\\nu}-\\omega\\right)\\left\\vert\\left\\langle c\\middle\\vert\\mathbf{e}\\cdot\\mathbf{q}\\right\\vert\\nu\\right\\rangle\\right\\vert^{2}},}\\end{array}\n$$ \n\nwhere $\\langle c|\\mathbf{e}\\cdot\\mathbf{q}|\\nu\\rangle$ is the integrated optical transitions from the valence states $(\\nu)$ to the conduction states (c), e is the polarization direction of the photon and $\\mathbf{q}$ is the electron momentum operator. The integration over $\\mathbf{k}$ is performed by summation over special $k$ - points with a corresponding weighting factor $w_{k}$ . The real part of the dielectric function $\\varepsilon_{1}(\\omega)$ can be determined from the KramersKronig relation given by \n\n$$\n\\varepsilon_{1}(\\omega)=1+\\frac{2}{\\pi}P\\intop_{0}^{\\infty}\\frac{\\varepsilon_{2}\\left(\\omega^{\\prime}\\right)\\omega^{\\prime}}{\\omega^{\\prime2}-\\omega^{2}+i\\eta}d\\omega^{\\prime},\n$$ \n\nwhere $P$ denotes the principle value and $\\eta$ is the complex shift parameter. The frequency-dependent linear optical spectra, e.g., refractive index $n(\\omega)$ , extinction coefficient $\\kappa(\\omega)$ , absorption coefficient $\\alpha(\\omega)$ , energy-loss function $L(\\omega)$ , and reflectivity $R(\\omega)$ can be calculated from the real $\\varepsilon_{1}(\\omega)$ and the imaginary $\\varepsilon_{2}(\\omega)$ parts [76]: \n\n$$\n\\begin{array}{r l}&{\\pi(\\omega)=\\left(\\frac{\\sqrt{\\varepsilon_{1}^{2}+k_{2}^{2}}+\\varepsilon_{1}}{2}\\right)^{\\frac{1}{2}},}\\\\ &{k(\\omega)=\\left(\\frac{\\sqrt{\\varepsilon_{1}^{2}+k_{2}^{2}}-\\varepsilon_{1}}{2}\\right)^{\\frac{1}{2}},}\\\\ &{\\alpha(\\omega)=\\frac{\\sqrt{2}\\omega}{\\varepsilon}\\left(\\sqrt{\\varepsilon_{1}^{2}+k_{2}^{2}}-\\varepsilon_{1}\\right)^{\\frac{1}{2}},}\\\\ &{L(\\omega)=\\ln\\left(\\frac{-1}{\\varepsilon(\\omega)}\\right)=\\frac{\\varepsilon_{2}}{k_{2}^{2}+k_{2}^{2}},}\\\\ &{R(\\omega)=\\frac{(\\pi-1)^{2}+k_{2}^{2}}{(4\\pi+1)^{2}+k_{2}^{2}}.}\\end{array}\n$$ \n\nIn Fig. 15 we present the linear optical spectra of silicon as determined by solving the Bethe-Salpeter Equation (BSE) on the top of ${\\sf G}_{0}{\\sf W}_{0}$ approximation. One can find that the absorption coefficient becomes significant only after $3.0~\\mathrm{eV}$ . This is because silicon has an indirect band gap, resulting in a low absorption coefficient in the visible region. Since the GW approximation includes the exchange and correlation effects in a self-energy term dependent on the one-particle Green’s function G and the dynamically screened Coulomb interaction W, it can correct the one electron eigenvalues obtained from DFT within a many-body quasiparticle framework [77,78]. Furthermore, the errors originated from the lack of ladder diagrams in determining W can be included through the solution of the Bethe-Salpeter equation (BSE) [79]. It could be expected that the GW-BSE calculated optical properties yield better agreement with the experiment. In the single-shot ${\\sf G}_{0}{\\sf W}_{0}$ approximation, the one-electron Green’s function G is self-consistently updated within a single iteration, while the screened Coulomb interaction W is fixed at its initial value. \n\n![](images/5b9e3e370e86b0ee612e1eab7843d348c3a84519231d8a58af2c64c7e3b3bc68.jpg) \nFig. 14. (Color online.) Effective band structure of $4\\times3~\\mathrm{MoS}_{2}$ SC unfolded into the PC Brillouin zone through Eq. (32) (a) without and (b) with a S vacancy. Orbital-resolved effective band structure of (c) $S{-}p$ and (d) Mo-d states in the defective SC. The Fermi energy is set to zero. \n\n![](images/5c1dda4e7503baab94641cbbe6be4695ff5a0168f6185cd2f64b6c42a9c8242d.jpg) \nFig. 15. (Color online.) ${\\sf G}_{0}{\\sf W}_{0}$ -BSE calculated (a) absorption coefficient, (b) refractive index, (c) reflectivity and (d) extinction coefficient of silicon. Vertical color lines highlight the visible light region. \n\nIt should be pointed out that the Eqs. (37)-(41) are not welldefined for low-dimensional materials since the dielectric function is not straightforward and depends on the thickness of the vacuum layer when the low-dimensional systems are simulated using a periodic stack of layers with sufficiently large interlayer distance $L$ to avoid artificial interactions between the periodic images of the 2D sheet crystals in the standard DFT calculations [80,81]. To avoid the thickness problem, the optical conductivity $\\sigma_{2D}(\\omega)$ is used to characterize the optical properties of 2D sheets. Based on the Maxwell equation, the 3D optical conductivity can be expressed as [82] \n\n$$\n\\sigma_{3D}(\\omega)=i[1-\\varepsilon(\\omega)]\\varepsilon_{0}\\omega,\n$$ \n\nwhere $\\varepsilon(\\omega)$ is the frequency-dependent complex dielectric function given in (34), $\\scriptstyle{\\varepsilon_{0}}$ is the permittivity of vacuum and $\\omega$ is the frequency of the incident wave. The in-plane 2D optical conductivity is directly related to the corresponding $\\sigma_{3D}(\\omega)$ component through the equation [82,83] \n\n$$\n\\sigma_{2D}(\\omega)=L\\sigma_{3D}(\\omega),\n$$ \n\nwhere $L$ is the slab thickness in the simulation cell. The normalized reflectance $R(\\omega)$ , transmittance $T(\\omega)$ and absorbance $A(\\omega)$ are independent of the light polarization for a freestanding 2D crystal sheet when normal incidence is assumed [82,83], \n\n$$\n\\begin{array}{r}{{\\cal R}=\\left|\\displaystyle\\frac{\\tilde{\\sigma}/2}{1+\\tilde{\\sigma}/2}\\right|^{2},}\\\\ {{\\cal T}=\\displaystyle\\frac{1}{|1+\\tilde{\\sigma}/2|^{2}},}\\\\ {{\\cal A}=\\displaystyle\\frac{\\mathrm{Re}\\tilde{\\sigma}}{|1+\\tilde{\\sigma}/2|^{2}},}\\end{array}\n$$ \n\nwhere $\\tilde{\\sigma}(\\omega)=\\sigma_{2\\mathrm{D}}(\\omega)/\\varepsilon_{0}c$ is the normalized conductivity ( $c$ is the speed of light). Since the interband contribution is only considered, the formula (44) is valid for semiconducting and insulating 2D crystals with a restriction of $A+T+R=1$ . Generally, the reflectance of 2D sheets is extremely small, and the absorbance can be approximated by the real part of $\\tilde{\\sigma}(\\omega)$ , namely, $A(\\omega)=\\mathrm{Re}\\sigma_{2D}(\\omega)/\\varepsilon_{0}c$ . To demonstrate this functionality, the PBEcalculated linear optical spectra of freestanding graphene and phosphorene monolayers are displayed in Fig. 16. Our results are in good agreement with the available theoretical optical curves [82–84]. \n\n# 3.10. Joint density of states \n\nFor a semiconductor, the optical absorption in direct band-toband transitions is proportional to [85] \n\n$$\n\\frac{2\\pi}{\\hbar}\\intop_{\\mathbb{B Z}}\\left|\\left\\langle v\\left|\\mathcal{H^{\\prime}}\\right|c\\right\\rangle\\right|^{2}\\frac{2}{(2\\pi)^{3}}\\delta\\left(E_{c}(\\mathbf{k})-E_{\\nu}(\\mathbf{k})-\\hbar\\omega\\right)d^{3}k,\n$$ \n\nwhere $\\mathcal{H}^{\\prime}$ is the perturbation associated with the light wave and $\\left\\langle\\nu\\left|\\mathcal{H}^{\\prime}\\right|c\\right\\rangle$ is the transition matrix from states in the valence band (V\u0018B) t\u0018o states in the conduction band (CB); $\\delta$ is the Dirac delta function which switches on this contribution when a transition occurs from one state to another, i.e., $E_{c}(\\mathbf{k})-E_{\\nu}(\\mathbf{k})=\\hbar\\omega$ . Factor 2 stems from the spin degeneracy. The integration is over the entire BZ. The matrix elements vary little within the BZ. Therefore, we can pull these out in front of the integral and obtain \n\n![](images/b525400131ce45fa876b467ea1a984f9663788b1775d9582afa272321393bd94.jpg) \nFig. 16. (Color online.) Real (blue line) and imaginary (red line) parts of frequencydependent optical conductivity $\\sigma_{2D}(\\omega)$ for (a) graphene and (c) phosphorene [in units of $\\sigma_{0}=e^{2}/(4\\hbar)]$ . Absorption spectra $A(\\omega)$ of (b) graphene and (d) phosphorene. The incident light polarized along the armchair and zigzag directions of phosphorene are presented by solid and dashed lines respectively. Vertical color lines highlight the visible light region. \n\n$$\n\\frac{2\\pi}{\\Omega\\hbar}\\left|\\left\\langle v\\left|\\mathcal{H^{\\prime}}\\right|c\\right\\rangle\\right|^{2}\\cdot\\int\\frac{2\\Omega}{(2\\pi)^{3}}\\delta\\left(E_{c}(\\mathbf{k})-E_{\\nu}(\\mathbf{k})-\\hbar\\omega\\right)\\mathrm{d}^{3}k,\n$$ \n\nwhere $\\Omega$ is the volume of the lattice cell, and the factor $\\Omega/{(2\\pi)}^{3}$ normalizes the $\\mathbf{k}$ vector density within the Brillouin zone. The second term is the joint density of states (JDOS). After sum over all states within the first Brillouin zone and all possible transitions initiated by photons with a certain energy ¯hω between valence and conduction bands, we obtain \n\n$$\n\\begin{array}{r}{j(\\omega)=\\displaystyle\\sum_{\\nu,c}\\frac{\\Omega}{4\\pi^{3}}\\int\\delta(E_{c}(\\mathbf{k})-E_{\\nu}(\\mathbf{k})-\\hbar\\omega)d^{3}k}\\\\ {=2\\displaystyle\\sum_{\\nu,c,\\mathbf{k}}w_{\\mathbf{k}}\\delta\\left(E_{c}(\\mathbf{k})-E_{\\nu}(\\mathbf{k})-\\hbar\\omega\\right),}\\end{array}\n$$ \n\nwhere $c$ and $\\nu$ belong respectively to the valence and conduction bands, $E({\\bf k})$ are the eigenvalues of the Hamiltonian, and $w_{\\mathbf{k}}$ are weighting factors. The Dirac Delta function in Eq. (47) can be numerically approximated using a normalized Gaussian function: \n\n$$\nG(\\omega)=\\frac{1}{\\sigma\\sqrt{2\\pi}}e^{-\\left(E_{\\mathbf{k},n^{\\prime}}-E_{\\mathbf{k},n}-\\hbar\\omega\\right)^{2}/2\\sigma^{2}},\n$$ \n\nwhere $\\sigma$ is the broadening parameter. To demonstrate this functionality, we show the calculated total and partial JDOS for $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ and Si in Fig. 17. The calculated JDOS for $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ is in excellent agreement with previous data [86]. It should be pointed that the total JDOS includes all possible interband transitions from all the valence to all the conduction bands according to Eq. (47); while the partial JDOS considers only the interband transitions from the highest VB to the lowest CB. \n\n# 3.11. Transition dipole moment \n\nThe transition dipole moment (TDM) or dipole transition matrix elements ${\\mathsf{P}}_{a\\to b}$ , is the electric dipole moment associated with a transition between the initial state $a$ and the final state $b$ [87]: \n\n![](images/177710a12addcfd5bf64220d51920d1fbccfd5578798df4358a7d1fa05abd80f.jpg) \nFig. 17. (Color online.) Calculated joint density of states for (a) $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ and (b) Si. Blue and purple lines represent the total and partial joint density of states respectively. The visible light region is highlighted by vertical color lines. \n\n![](images/52f1899293984347e52314c3b80728313b9999aed78242fbf5dc849fbe8e1963.jpg) \nFig. 18. (Color online.) Calculated band structure (top panel) and transition dipole moment (bottom panel) for (a) $\\mathsf{C s}_{2}\\mathsf{A g I n C l}_{6}$ and (b) ${\\mathrm{C}}s_{2}{\\mathrm{InBiCl}}_{6}$ . \n\n$$\n\\mathrm{P}_{a\\to b}=\\langle\\psi_{b}|{\\bf r}|\\psi_{a}\\rangle={\\frac{i\\hbar}{(E_{b}-E_{a})m}}\\langle\\psi_{b}|{\\bf p}|\\psi_{a}\\rangle,\n$$ \n\nwhere $\\psi_{a}$ and $\\psi_{b}$ are energy eigenstates with energy $E_{a}$ and $E_{b};m$ is the mass of the electron. In general the TDM is a complex vector that includes the phase factors associated with the two states. Its direction gives the polarization of the transition, which determines how the system will interact with an electromagnetic wave of a given polarization, while the sum of the squares of TDM, $P^{2}$ , gives the transition probabilities between the two states. In Fig. 18 we provide some specific examples to illustrate its use. It is seen that the calculated TDM amplitude is zero for transition between the CBM and VBM at the $\\Gamma$ point in $\\mathsf{C s}_{2}\\mathsf{A g l n C l}_{6}$ , implying no optical absorption between these two states. On the other hand, the excellent optical absorption between CBM and VBM is predicted in ${\\mathrm{C}}s_{2}{\\mathrm{InBiCl}}_{6}$ when Bi substitues Ag atom. These findings are in good agreement with previous theoretical results [88]. \n\n# 3.12. $d$ -Band center \n\nThe $d$ -band center model of Hammer and Nørskov is widely used in understanding and predicting catalytic activity on transition metal surfaces. The main idea underlying the theory is that the binding energy of an adsorbate to a metal surface is largely dependent on the electronic structure of the surface itself. In this model, the $d$ -states band participating in the interaction is approximated by the center of the $d$ -band $\\textstyle{\\varepsilon_{d}}$ [89]: \n\n$$\n\\varepsilon_{\\mathrm{d}}=\\frac{\\int_{-\\infty}^{\\infty}n_{\\mathrm{d}}(\\varepsilon)\\varepsilon d\\varepsilon}{\\int_{-\\infty}^{\\infty}n_{\\mathrm{d}}(\\varepsilon)d\\varepsilon},\n$$ \n\nwhere $n_{\\mathrm{d}}$ and $\\varepsilon$ are projected-DOS and energy of transition metal $d$ -states. According to this model, the adsorption energy on the transition metal surface correlates with the upward shift of the dband center with respect to the Fermi energy. A more vital upward shift indicates the possibility of forming a more significant number of empty anti-bonding states, leading to a stronger binding energy [90,91,89]. It may be worth mentioning here that the $d$ -band center position linearly upshifts with increasing the number of empty states above the Fermi level. Therefore, one can specify the integral upper limit in Eq. (50) to calculate $d$ -band center by using VASPKIT. \n\n# 3.13. Thermo energy correction \n\nGibbs free energy plays a crucial role in catalysis reaction. The equations used to calculate thermochemical data for gases in VASPKIT are equivalent to those in the Gaussian program [92,93]. The Gibbs free energy $G$ is given by \n\n$$\nG=H-T S,\n$$ \n\nwhere $H,\\ T$ and S represent enthalpy, temperature and entropy, respectively. The enthalpy $H$ in Eq. (51) can be written as $H=$ $U+P V$ . Both internal thermal energy $U$ and entropy S have included the contributions from translational, electronic, rotational and vibrational motions and zero-point energy (ZPE) of molecules. Moreover, to calculate correctly when the number of moles (labeled $N$ ) of a gas changes during the course of a reaction, the Gibbs free energy has also included $\\Delta P V=\\Delta N R T$ , where $R$ is the molar gas constant. It is worth mentioning that only the modes with real vibrational frequencies are considered and the model with imaginary one are ignored during the calculations of the vibration contributions. Specifically, for linear (non-linear) molecules containing $n$ atoms, the degree of vibrational freedom is $3n-5$ (3n - 6). VASPKIT neglects the smallest 5 (6) frequencies. We take oxygen molecular as an example to calculate its free energy at 298.15 K using the corrected algorithm mentioned above. It is found that the calculated correction to free energy of $0_{2}$ molecule is -0.4467 eV, which is very close to the experimental data of -0.4468 eV at $298.15\\mathrm{~K~}$ and normal atmospheric pressure [94]. Moreover, the thermal correction result from VASPKIT is exactly the same with that from Gaussian program by setting the same molecular structure and frequencies. \n\nUnlike gas molecules, when the adsorbed molecules form chemical bonds with the substrate, their translational and rotational freedom will be constrained. Consequently, the contributions from translation and rotation to entropy and enthalpy are significantly reduced turn into vibrational modes. One standard method is to attribute the translational or rotational part of the contribution to vibration, that is, the $3n$ vibrations of the surface-adsorbing molecules (except the imaginary frequency) are all used to calculate the correction of the thermo energy [89]. Considering that a minor vibration mode makes a significant contribution to entropy. A minor vibration frequency will likely lead to abnormal entropy and free energy correction. Thus, VASPKIT allows specifying a threshold value which defines the lower limit of frequencies. For example, if a threshold value of $50~\\mathrm{cm}^{-1}$ is adopted, implying that the frequencies below $50~\\mathrm{cm}^{-1}$ are approximately equal to 50 $\\mathsf{c m}^{-1}$ during the calculations of the vibration contributions to the adsorbed molecular free energy correction. \n\n# 3.14. Molecular dynamics \n\nMolecular dynamics (MD) describes how the atoms in a material move as a function of time, and helps us to understand the structural, dynamical and thermodynamical properties of complex systems. It has been successfully applied to gases, liquids, and ordered and disordered solids. In addition to the equation of state, mean square displacement (MSD), velocity auto-correlation function (VACF), phonon vibrational density of states (VDOS) and pair correlation function (PCF) are the most critical quantities enabling us to determine various properties of interest in MD simulations. \n\nThe MSD is a measure of the deviation of the position of a particle with respect to a reference position over time. It can help to determine whether the ion is freely diffusing, transported, or bound. It is defined as \n\n$$\nM S D(m)=\\frac{1}{N_{\\mathrm{particles}}}\\sum_{i=1}^{N_{\\mathrm{particles}}}\\frac{1}{N-m}\\sum_{k=0}^{N-m-1}\\left({\\bf r}_{i}(k+m)-{\\bf r}_{i}(k)\\right)^{2},\n$$ \n\nwhere ${\\bf r}_{i}(t)$ is the position of atom i after $t$ time of simulation. $N.$ particles and $N$ are the total number of atoms and total frames respectively. According to this definition, the MSD is averaged over all windows of length $m$ and over all selected particles. An alternative method that can efficiently calculate MSD was proposed based on the Fast Fourier Transform (FFT) algorithm in Refs. [95,96] and references therein. If the system stays in the solid state, the MSD oscillates around a constant value. This means that all the atoms are confined to specific positions. However, for a liquid, atoms will move indefinitely and the MSD continues to increase linearly with time. This implies that sudden changes in the MSD with time indicate melting, solidification, phase transition, and so on. In addition, the calculation of MSD is the standard way to estimate the parameters of movement, such as the diffusion coefficients from MD simulations. \n\nThe VACF is another way of checking the movement type of atoms. It is a value that basically tells until when the particle remembers its previous movements. Like the MSD, it is a timeaveraged value, defined over a delay domain. The normalized VACF is defined as \n\n$$\nc(t)=\\frac{\\sum_{i=1}^{N}\\left\\langle\\mathbf{v}_{i}(t)\\cdot\\mathbf{v}_{i}(0)\\right\\rangle}{\\sum_{i=1}^{N}\\left(\\mathbf{v}_{i}(0)\\right)^{2}},\n$$ \n\nwhere ${\\bf v}_{i}(t)$ is the velocity of the i-th atom at time t. The bracket represents a time average over the history of the particle, i.e., all the values of t. The total velocity autocorrelation function C(t) is defined as the mass-weighted sum of the atom velocity autocorrelation functions [97] \n\n$$\nC(t)=\\sum_{j=1}^{N}m_{j}c_{j}(t),\n$$ \n\nwhere $c_{j}(t)$ is the velocity autocorrelation of atom $j$ . The optical and thermodynamical properties of materials depend on VDOS which can be obtained from the Fourier transform of the VACF under the harmonic approximation [98,97], \n\n$$\nf(\\omega)=\\mathcal{F}[\\gamma(t)]=\\frac{1}{k_{B}T}\\intop_{-\\infty}^{\\infty}\\gamma(t)e^{-i\\omega t}d t,\n$$ \n\nwhere $\\omega$ is the vibrational frequency, $\\mathcal{F}$ is the Fourier transform operator, $k_{B}$ is the Boltzmann constant and $T$ is the absolute temperature. \n\n![](images/9cef053a8d746a68dd0aebbbf438425c592f04a1b7b6057deb345cec1797e460.jpg) \nFig. 19. (Color online.) Calculated (a) MSD, (b) VACF, (c) VDOS and (d) PCF of liquid water at $400~\\mathrm{K}$ obtained from MD simulations. \n\nThe PCF $\\mathbf{g}(\\boldsymbol{r})$ describes how atoms are distributed in a thin shell at a radius $r$ from an arbitrary atom in the material. It is useful not only for studying the details of the system but also to obtain accurate values for the macroscopic quantities such as the potential energy and pressure. This quantity can be obtained by summing the number of atoms found at a given distance in all directions from a particular atom: \n\n$$\ng(r)=\\frac{d N/N}{d V/V}=\\frac{1}{4\\pi r^{2}}\\frac{1}{N\\rho}\\sum_{i=1}^{N}\\sum_{j\\neq i}^{N}\\left<\\delta\\left(r-\\left|\\mathbf{r}_{i}-\\mathbf{r}_{j}\\right|\\right)\\right>,\n$$ \n\nwhere $r$ is the radial distance. $\\rho$ is the average density of the entire material. The normalization via the density ensures that for large distances the radial distribution approaches unity. The partial radial distribution between two elements is calculated as \n\n$$\ng_{A B}(r)={\\frac{1}{4\\pi r^{2}}}{\\frac{N}{\\rho N_{A}N_{B}}}\\sum_{i\\in A}\\sum_{j\\in B,j\\neq i}^{N}\\left\\langle\\delta\\left(r-\\left|\\mathbf{r}_{i}-\\mathbf{r}_{j}\\right|\\right)\\right\\rangle.\n$$ \n\nAs an illustrated example, Fig. 19 shows the PBE-calculated MSD, VACF, VDOS and PCF for liquid water at $400\\mathrm{~K~}$ processed by the MD utility. Overall, our result is in good agreement with available experimental and theoretical results [99,100]. \n\n# 4. High-throughput capabilities \n\nVASPKIT also provides a light-weight high-throughput interface. As such it can advantageously be part of bash scripts, taking full advantage of bash capabilities (variables, loops, conditions, etc.) to batch performing pre- and post-processing. An easy-to-follow user manual is available at https://vaspkit com/tutorials html. The syntax is designed as simply as possible. For instance, to generate KPOINTS files in a series of subfolders, the syntax is \n\nfor d i r in $^*$ \ndo echo \\$dir cd \\$RootPath / \\$dir vaspkit task 102 kpr 0.04 \ndone \n\n# 5. Limitations and future capabilities \n\nCurrently, VASPKIT only deals with the raw data calculated using the VASP code. This program will be extended to support other \n\nab-initio packages in the future version. In addition, the data visualization and plotting utility based on Python and Matplotlib will be also implemented. \n\n# 6. Summary \n\nIn summary, VASPKIT is a user-friendly toolkit that can be easily employed to perform initial setup for calculations and postprocessing analysis to derive many material properties from the raw data generated by VASP code. We have demonstrated its capability through illustrative examples. VASPKIT provides a commandline interface to perform high-throughput calculations. It remains under development, and further functionality, including closer support for other codes, is readily to be implemented. With new features being added, we hope that VASPKIT will become an even more attractive toolkit contributing to efficient development and utilization of electronic structure theory. \n\n# Declaration of competing interest \n\nThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \n\n# Acknowledgements \n\nWe acknowledge other contributors (in no particular order) including Peng-Fei Liu, Xue-Fei Liu, Zhao-Fu Zhang, Tian Wang, DaoXiong Wu, Ya-Chao Liu, Jiang-Shan Zhao, Yue Qiu and Qiang Li. We gratefully acknowledge helpful discussions with Zhe-Yong Fan, QiJing Zheng and Ming-Qing Liao. We also thank various researchers worldwide for reporting bugs and suggesting features, which have led to significant improvements in the accuracy and robustness of the package. V.W. gratefully appreciates Yoshiyuki Kawazoe and Shigenobu Ogata for their invaluable support. V.W. also thanks The Youth Innovation Team of Shaanxi Universities. \n\n# Appendix A. Elastic stiffness tensor matrix and strain modes for bulk crystal systems \n\n# 1. Triclinic system (space group numbers: 1-2) \n\nThere are 21 independent elastic constants. C11, $C_{12}$ , C13, C14, C15, C16, C22, $C_{23}$ , $C_{24}$ , C25, C26, C33, C34, C35, C36, C44, C45, C46, $C_{55},C_{56}$ and $C_{66}$ . (See Table A.1.) \n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{C_{11}}&{C_{12}}&{C_{13}}&{C_{14}}&{C_{15}}&{C_{16}}\\\\ {C_{12}}&{C_{22}}&{C_{23}}&{C_{24}}&{C_{25}}&{C_{26}}\\\\ {C_{13}}&{C_{23}}&{C_{33}}&{C_{34}}&{C_{35}}&{C_{36}}\\\\ {C_{14}}&{C_{24}}&{C_{34}}&{C_{44}}&{C_{45}}&{C_{46}}\\\\ {C_{15}}&{C_{25}}&{C_{35}}&{C_{45}}&{C_{55}}&{C_{56}}\\\\ {C_{16}}&{C_{26}}&{C_{36}}&{C_{46}}&{C_{56}}&{C_{66}}\\end{array}\\right).\n$$ \n\n# 2. Monoclinic system (space group numbers: 3-15) \n\nThere are 13 independent elastic constants: $C_{11,~}C_{12},~C_{13},~C_{15}$ $C_{22},C_{23},C_{25},C_{33},C_{35},C_{44},C_{46},C_{55}$ and $C_{66}$ . (See Table A.2.) The elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{{C_{11}}}&{{C_{12}}}&{{C_{13}}}&{{0}}&{{C_{15}}}&{{0}}\\\\ {{C_{12}}}&{{C_{22}}}&{{C_{23}}}&{{0}}&{{C_{25}}}&{{0}}\\\\ {{C_{13}}}&{{C_{23}}}&{{C_{33}}}&{{0}}&{{C_{35}}}&{{0}}\\\\ {{0}}&{{0}}&{{0}}&{{C_{44}}}&{{0}}&{{C_{46}}}\\\\ {{C_{15}}}&{{C_{25}}}&{{C_{35}}}&{{0}}&{{C_{55}}}&{{0}}\\\\ {{0}}&{{0}}&{{0}}&{{0}}&{{C_{46}}}&{{C_{66}}}\\end{array}\\right).\n$$ \n\nTable A.1 List of strain modes and the derived elastic constants for triclinic system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy #
1(8, 0,0, 0,0, 0)C118²
2(0,8,0,0,0, 0)C2282
3(0, 0,8,0,0, 0)C3²
4(0, 0, 0,8,0,0)C4482
5(0, 0,0,0,8,0)#C552
6(0, 0, 0,0,0,8)C6682
7(8,8,0,0,0,0)++
8(8,0,8,0,0,0)+(1+
9(8,0,0,8,0,0)+C1+
10(8,0,0,0,8,0)+C15+
11(8,0,0,0,0,8)(+C1+
12(0,8,8,0,0,0)+C2+
13(0,8,0,8,0,0)+C+#
14(0,8,0,0,8,0)+C25+
15(0,8,0,0,0,8)(+
16(0,0,8,8,0,0)++
17(0,0,8,0,8,0)+C3+
18(0, 0,8,0,0,8)+C36+C
19(0,0,0,8,8,0)(+4+
20(0,0,0,8,0,8)(+C4+#
21(0,0,0,0,8,8)+C5
\n\nTable A.2 List of strain modes and the derived elastic constants for monoclinic system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy
1(8,0,0, 0, 0,0)C182
2(0,8,0,0,0, 0)##C2
3(0, 0, 8,0,0, 0)#C3²
4(0,0,0,8,0,0)C4482
5(0,0,0,0,8,0)C5582
6(0, 0, 0, 0,0, 8)C6682
7(8,8,0,0,0,0)++ # 82
8(8,0,8,0,0,0)(+ +
9(8,0,0,0,8,0)(+C1+
10(0,8,8,0,0,0)+C+
11(0,8,0,0,8,0)(+C28
12(0,0,8,0,8,0)
13(0,0,0,8,0,8)+C46+ 82
\n\n# 3. Orthorhombic system (space group numbers: 16-74) \n\nThere are 9 independent elastic constants: $C_{11},C_{12},C_{13},C_{22},$ $C_{23},C_{33},C_{44},C_{55}$ and $C_{66}$ . (See Table A.3.) \n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{C_{11}}&{C_{12}}&{C_{13}}&{0}&{0}&{0}\\\\ {C_{12}}&{C_{22}}&{C_{23}}&{0}&{0}&{0}\\\\ {C_{13}}&{C_{23}}&{C_{33}}&{0}&{0}&{0}\\\\ {0}&{0}&{0}&{C_{44}}&{0}&{0}\\\\ {0}&{0}&{0}&{0}&{C_{55}}&{0}\\\\ {0}&{0}&{0}&{0}&{0}&{C_{66}}\\end{array}\\right).\n$$ \n\n# 4. Tetragonal II system (space group numbers: 75-88) \n\nThere are 7 independent elastic constants: $C_{11},\\ C_{12},\\ C_{13},\\ C_{16},$ $C_{33},C_{44}$ and $C_{66}$ . (See Table A.4.) \n\nTable A.3 List of strain modes and the derived elastic constants for orthorhombic system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy
1(8,0,0, 0,0,0)C1182
2(0,8,0,0,0,0)#C282
3(0,0,8,0,0,0)#33
4(0,0,0,8,0,0)#C482
5(0,0,0,0,8,0)C552
6(0,0,0,0,0,8)#6682
7(8,8,0,0,0,0)1+
89(6. 0 6.0.0.0)
\n\nTable A.4 List of strain modes and the derived elastic constants for tetragonal I system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy F
1(8,8,0,0,0,0)(C11 +C12)82
23
(0. 0, 0. 0 0.0)#C
4(0,0,0,8,8,0)C4482
5(8,8,8,0,0,0)C11+C12+2C13+33 82
6(0,8,8,0,0,0)+C13+ 82
7(8,0,0,0,0,8)+C16+ 82
\n\nTable A.5 List of strain modes and the derived elastic constants for tetragonal system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy
1(8,8,0,0, 0, 0)(C11 +C12)82
2(0, 0, 0,0,0,8)C662
3(0, 0, 8,0, 0, 0)#C332
4(0,0,0,8,8,0)C4482
5(8,8,8,0,0,0)(C11 +C12 +2C13 +) 82
6(0,8,8,0,0,0)+C1+)8 2 2
\n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{C_{11}}&{C_{12}}&{C_{13}}&{0}&{0}&{C_{16}}\\\\ {C_{12}}&{C_{11}}&{C_{13}}&{0}&{0}&{-C_{16}}\\\\ {C_{13}}&{C_{13}}&{C_{33}}&{0}&{0}&{0}\\\\ {0}&{0}&{0}&{C_{44}}&{0}&{0}\\\\ {0}&{0}&{0}&{0}&{C_{44}}&{0}\\\\ {C_{16}}&{-C_{16}}&{0}&{0}&{0}&{C_{66}}\\end{array}\\right).\n$$ \n\n# 5. Tetragonal I system (space group numbers: 89-142) \n\nThere are 6 independent elastic constants: $C_{11},\\ C_{12},\\ C_{13},\\ C_{33},$ $C_{44}$ and $C_{66}$ . (See Table A.5.) \n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{C_{11}}&{C_{12}}&{C_{13}}&{0}&{0}&{0}\\\\ {C_{12}}&{C_{11}}&{C_{13}}&{0}&{0}&{0}\\\\ {C_{13}}&{C_{13}}&{C_{33}}&{0}&{0}&{0}\\\\ {0}&{0}&{0}&{C_{44}}&{0}&{0}\\\\ {0}&{0}&{0}&{0}&{C_{44}}&{0}\\\\ {0}&{0}&{0}&{0}&{0}&{C_{66}}\\end{array}\\right).\n$$ \n\n# 6. Trigonal II system (space group numbers: 143-148) \n\nThere are 7 independent elastic constants: $C_{11},C_{12},C_{13},C_{14}$ $C_{15},C_{33}$ and $C_{44}$ . (See Table A.6.) \n\nTable A.6 List of strain modes and the derived elastic constants for trigonal I system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector Elastic energy 令
1(8,8,0,0,0, 0)(C11 +C12)82
2(0,0,0,0,0,8)4(C11 - C12)82
3(0,0,8,0,0,0)#C32
4(0,0,0,8,8,0)C4482
5(8,8,8,0,0,0)(C11 + C12 +2C13 + 3 82
6(0,0,0,0,8,8)(-+C1+)²
7(0, 0,0,8,0,8)1+ 82 4 2
\n\nTable A.7 List of strain modes and the derived elastic constants for trigonal system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy
1(8,8, 0,0,0, 0)(C11 +C12)82
2(0, 0, 0,0,0,8)4(C11 -C12)82
3(0, 0, 8,0, 0, 0)C33²
4(0, 0,0,8,8,0)C4482
5(8,8,8,0,0,0)(C11 +C12 +2C13 + C3 82
6(0, 0, 0,0,8,8)-+C1+ 82
\n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{C_{11}}&{C_{12}}&{C_{13}}&{C_{14}}&{C_{15}}&{0}\\\\ {C_{12}}&{C_{11}}&{C_{13}}&{-C_{14}}&{-C_{15}}&{0}\\\\ {C_{13}}&{C_{13}}&{C_{33}}&{0}&{0}&{0}\\\\ {C_{14}}&{-C_{14}}&{0}&{C_{44}}&{0}&{-C_{15}}\\\\ {C_{15}}&{-C_{15}}&{0}&{0}&{C_{44}}&{C_{14}}\\\\ {0}&{0}&{0}&{-C_{15}}&{C_{14}}&{\\frac{C_{11}-C_{12}}{2}}\\end{array}\\right).\n$$ \n\n# 7. Trigonal I system (space group numbers: 149-167) \n\nThere are 6 independent elastic constants: $C_{11},\\ C_{12},\\ C_{13},\\ C_{14},$ $C_{33}$ and $C_{44}$ . (See Table A.7.) \n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{C_{11}}&{C_{12}}&{C_{13}}&{C_{14}}&{0}&{0}\\\\ {C_{12}}&{C_{11}}&{C_{13}}&{-C_{14}}&{0}&{0}\\\\ {C_{13}}&{C_{13}}&{C_{33}}&{0}&{0}&{0}\\\\ {C_{14}}&{-C_{14}}&{0}&{C_{44}}&{0}&{0}\\\\ {0}&{0}&{0}&{0}&{C_{44}}&{C_{14}}\\\\ {0}&{0}&{0}&{0}&{C_{14}}&{\\frac{C_{11}-C_{12}}{2}}\\end{array}\\right).\n$$ \n\n# 8. Hexagonal system (space group numbers: 168–194) \n\nThere are 5 independent elastic constants: $C_{11},\\ C_{12},\\ C_{13},\\ C_{33}$ and $C_{44}$ . (See Table A.8.) \n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c c}{C_{11}}&{C_{12}}&{C_{13}}&{0}&{0}&{0}\\\\ {C_{12}}&{C_{11}}&{C_{13}}&{0}&{0}&{0}\\\\ {C_{13}}&{C_{13}}&{C_{33}}&{0}&{0}&{0}\\\\ {0}&{0}&{0}&{C_{44}}&{0}&{0}\\\\ {0}&{0}&{0}&{0}&{C_{44}}&{0}\\\\ {0}&{0}&{0}&{0}&{0}&{\\frac{C_{11}-C_{12}}{2}}\\end{array}\\right).\n$$ \n\n# 9. Cubic system (space group numbers: 195–230) \n\nThere are 3 independent elastic constants: $C_{11},\\ C_{12}$ and $C_{44}$ . (See Table A.9.) \n\nTable A.8 List of strain modes and the derived elastic constants for hexagonal system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy 令
1(8,8,0,0,0,0)(C11 +C12)82
2(0,0, 0, 0,0,8)4(C11- C12)82
3(0, 0, 8,0, 0, 0)C33²
4(0,0,0,8,8,0)C4482
5(8,8,8,0,0,0)(C11 +C12 +2C13 +3 82
\n\nTable A.9 List of strain modes and the derived elastic constants for cubic system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy
1(0,0,0,8,8,8)CAA82
2(8,8,0,0,0,0)(C11 + C12)82
3(8,8,8,0,0,0)(C11 +2C12)82
\n\nThe elastic stiffness tensor matrix is expressed by \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c c c c}{{C_{11}}}&{{C_{12}}}&{{C_{12}}}&{{0}}&{{0}}&{{0}}\\\\ {{C_{12}}}&{{C_{11}}}&{{C_{12}}}&{{0}}&{{0}}&{{0}}\\\\ {{C_{12}}}&{{C_{12}}}&{{C_{11}}}&{{0}}&{{0}}&{{0}}\\\\ {{0}}&{{0}}&{{0}}&{{C_{44}}}&{{0}}&{{0}}\\\\ {{0}}&{{0}}&{{0}}&{{0}}&{{C_{44}}}&{{0}}\\\\ {{0}}&{{0}}&{{0}}&{{0}}&{{0}}&{{C_{44}}}\\end{array}\\right).\n$$ \n\n# Appendix B. Elastic stiffness tensor matrix and strain modes for 2D crystal systems \n\n# 1. 2D oblique system \n\nThere are 6 independent elastic constants: $C_{11,~}C_{12,~}C_{16,~}C_{22,~}$ $C_{26}$ and $C_{66}$ . (See Table B.1.) \n\n$$\nC_{i j}=\\left(\\begin{array}{l l l}{{C_{11}}}&{{C_{12}}}&{{C_{16}}}\\\\ {{C_{12}}}&{{C_{22}}}&{{C_{26}}}\\\\ {{C_{16}}}&{{C_{26}}}&{{C_{66}}}\\end{array}\\right)\n$$ \n\n# 2. 2D rectangular system \n\nThere are 4 independent elastic constants: $C_{11},C_{12},C_{22}$ and $C_{66}$ . (See Table B.2.) \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c}{{C_{11}}}&{{C_{12}}}&{{0}}\\\\ {{C_{12}}}&{{C_{22}}}&{{0}}\\\\ {{0}}&{{0}}&{{C_{66}}}\\end{array}\\right)\n$$ \n\n# 3. 2D square system \n\nTable B.1 List of strain modes and the derived elastic constants for 2D oblique system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy
1(8,0,0)C1182
2(0,8,0)##28
3(0,0,8)#C6682
4(8,8,0)+(1+)
5(8,0,8)(+ 1
6(0,8,8)+C26+ 8²
\n\nTable B.2 List of strain modes and the derived elastic constants for 2D rectangular system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy F
1(8,0,0)C112
2(0,8,0)C22²
3(0,0,8)C6682
4(8,8,0)+C1+)8
\n\nTable B.3 List of strain modes and the derived elastic constants for 2D square system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy
1(8,0,0)C1182
2(0,0,8)C6682
3(8,8,0)(C11 +C12)82
\n\nTable B.4 List of strain modes and the derived elastic constants for 2D hexagonal system used in VASPKIT based on energy-strain approach. \n\n\n
Strain indexStrain vector εElastic energy V
(8,0,0)C1182
2(8,8,0)(C11 +C12)82
\n\nThere are 3 independent elastic constants: $C_{11},\\ C_{12}$ and $C_{66}$ . (See Table B.3.) \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c}{{C_{11}}}&{{C_{12}}}&{{0}}\\\\ {{C_{12}}}&{{C_{11}}}&{{0}}\\\\ {{0}}&{{0}}&{{C_{66}}}\\end{array}\\right)\n$$ \n\n# 4. 2D hexagonal system \n\nThere are 2 independent elastic constants: $C_{11}$ and $C_{12}$ . (See Table B.4.) \n\n$$\nC_{i j}=\\left(\\begin{array}{c c c}{{C_{11}}}&{{C_{12}}}&{{0}}\\\\ {{C_{12}}}&{{C_{11}}}&{{0}}\\\\ {{0}}&{{0}}&{{\\frac{C_{11}-C_{12}}{2}}}\\end{array}\\right)\n$$ \n\n# References \n\n[1] P. Hohenberg, W. Kohn, Phys. Rev. 136 (1964) B864–B871, https://doi org 10. 1103 PhysRev.136 B864. \n[2] W. Kohn, L.J. Sham, Phys. Rev. 140 (1965) A1133–A1138, https://doi org 10. 1103 PhysRev.140 A1133. \n[3] M.C. Payne, M.P. Teter, D.C. Allan, T.A. Arias, J.D. Joannopoulos, Rev. Mod. Phys. 64 (1992) 1045–1097, https://doi org 10 1103 RevModPhys 64 1045. \n[4] R.O. Jones, O. Gunnarsson, Rev. Mod. Phys. 61 (1989) 689–746, https://doi org 10 1103 RevModPhys 61.689. \n[5] R.O. Jones, Rev. Mod. Phys. 87 (2015) 897–923, https://doi org 10 1103 RevModPhys 87.897. \n[6] K. Sato, L. Bergqvist, J. Kudrnovský, P.H. Dederichs, O. Eriksson, I. Turek, B. Sanyal, G. Bouzerar, H. Katayama-Yoshida, V.A. Dinh, T. Fukushima, H. Kizaki, R. Zeller, Rev. Mod. Phys. 82 (2010) 1633–1690, https://doi org 10 1103 RevModPhys 82 1633. \n[7] T. Dietl, H. Ohno, Rev. Mod. Phys. 86 (2014) 187–251, https://doi org 10 1103 RevModPhys 86 187. \n[8] A. Jain, Y. Shin, K.A. Persson, Nat. Rev. Mater. 1 (1) (2016) 15004, https:// doi org 10 1038 natrevmats 2015 4. \n[9] C. Freysoldt, B. Grabowski, T. Hickel, J. Neugebauer, G. Kresse, A. Janotti, C.G. Van de Walle, Rev. Mod. Phys. 86 (2014) 253–305, https://doi org 10 1103 RevModPhys 86 253. \n[10] J. Pokluda, M. Cˇern \\`y, M. Šob, Y. Umeno, Prog. Mater. Sci. 73 (2015) 127–158, https://doi org 10 1016 j pmatsci 2015 04 001. \n[11] L. Zhang, Y. Wang, J. Lv, Y. Ma, Nat. Rev. Mater. 2 (4) (2017) 17005, https:// doi org 10 1038 natrevmats 2017.5. \n[12] A.R. Oganov, C.J. Pickard, Q. Zhu, R.J. Needs, Nat. Rev. Mater. 4 (5) (2019) 331–348, https://doi org 10 1038 s41578 019 0101 8. \n[13] X. Gonze, F. Jollet, F.A. Araujo, D. Adams, B. Amadon, T. Applencourt, C. Audouze, J.-M. Beuken, J. Bieder, A. Bokhanchuk, et al., Comput. Phys. Commun. 205 (2016) 106–131, https://doi org 10 1016 j cpc 2016 04 003. \n[14] S.J. Clark, M.D. Segall, C.J. Pickard, P.J. Hasnip, M.I. Probert, K. Refson, M.C. Payne, Z. Kristallogr. 220 (5–6) (2005) 567–570, https://doi org 10 1524 zkri 220 5 567.65075. \n[15] G. Kresse, J. Furthmüller, Comput. Mater. Sci. 6 (1) (1996) 15–50, https://doi org 10 1016 0927 0256(96 00008 0. \n[16] G. Kresse, J. Furthmüller, Phys. Rev. B 54 (1996) 11169–11186, https://doi org 10 1103 PhysRevB 54 11169. \n[17] J.M. Soler, E. Artacho, J.D. Gale, A. García, J. Junquera, P. Ordejón, D. SánchezPortal, J. Phys. Condens. Matter 14 (11) (2002) 2745–2779, https://doi org 10 1088 0953 8984 14 11 302. \n[18] P. Giannozzi, S. Baroni, N. Bonini, M. Calandra, R. Car, C. Cavazzoni, D. Ceresoli, G.L. Chiarotti, M. Cococcioni, I. Dabo, A.D. Corso, S. de Gironcoli, S. Fabris, G. Fratesi, R. Gebauer, U. Gerstmann, C. Gougoussis, A. Kokalj, M. Lazzeri, L. Martin-Samos, N. Marzari, F. Mauri, R. Mazzarello, S. Paolini, A. Pasquarello, L. Paulatto, C. Sbraccia, S. Scandolo, G. Sclauzero, A.P. Seitsonen, A. Smogunov, P. Umari, R.M. Wentzcovitch, J. Phys. Condens. Matter 21 (39) (2009) 395502, https://doi org 10 1088 0953 8984 21 39 395502. \n[19] P. Giannozzi, O. Andreussi, T. Brumme, O. Bunau, M.B. Nardelli, M. Calandra, R. Car, C. Cavazzoni, D. Ceresoli, M. Cococcioni, et al., J. Phys. Condens. Matter 29 (46) (2017) 465901, https://doi org 10 1088 1361 648x aa8f79. \n[20] K. Dewhurst, S. Sharma, L. Nordstrom, F. Cricchio, F. Bultmark, H. Gross, C. Ambrosch-Draxl, C. Persson, C. Brouder, R. Armiento, et al., The elk fp-lapw code, http://elk.sourceforge net/. (Accessed 4 April 2020). \n[21] P. Blaha, K. Schwarz, F. Tran, R. Laskowski, G.K.H. Madsen, L.D. Marks, J. Chem. Phys. 152 (7) (2020) 074101, https://doi org 10 1063 1.5143061 \n[22] Dassault system\\` es biovia, materials studio, 7.0, dassault system\\` es, San Diego, https://www.3ds com products services biovia products molecular-modeling simulation biovia materials studio, 2017. (Accessed 4 April 2020). \n[23] S. Smidstrup, T. Markussen, P. Vancraeyveld, J. Wellendorff, J. Schneider, T. Gunst, B. Verstichel, D. Stradi, P.A. Khomyakov, U.G. Vej-Hansen, et al., J. Phys. Condens. Matter 32 (1) (2019) 015901, https://doi org 10 1088 1361 648x ab4007. \n[24] S.P. Ong, W.D. Richards, A. Jain, G. Hautier, M. Kocher, S. Cholia, D. Gunter, V.L. Chevrier, K.A. Persson, G. Ceder, Comput. Phys. Sci. 68 (2013) 314–319, https://doi org 10 1016 j commatsci 2012 10 028. \n[25] A.H. Larsen, J.J. Mortensen, J. Blomqvist, I.E. Castelli, R. Christensen, M. Dułak, J. Friis, M.N. Groves, B. Hammer, C. Hargus, et al., J. Phys. Condens. Matter 29 (27) (2017) 273002, https://doi org 10 1088 1361 648x aa680e. \n[26] U. Herath, P. Tavadze, X. He, E. Bousquet, S. Singh, F. Munoz, A.H. Romero, Comput. Phys. Commun. 251 (2020) 107080, https://doi org 10 1016 j cpc 2019 107080. \n[27] L.N. Kantorovich, Lev00 & tetr: user-friendly packages for dft codes vasp/siesta/quickstep/crystal/quantum espresso, https://nms kcl ac uk lev.kantorovitch des lev00 index html. (Accessed 4 April 2020). \n[28] W. Yi, G. Tang, X. Chen, B. Yang, X. Liu, Comput. Phys. Commun. 257 (2020) 107535, https://doi org 10 1016 j cpc 2020 107535. \n[29] V. Wang, Y. Liang, Y. Kawazoe, W. Geng, High-throughput computational screening of two-dimensional semiconductors, preprint, arXiv:1806 04285, 2018. \n[30] A. Togo, I. Tanaka, Spglib: a software library for crystal symmetry search, preprint, arXiv:1808 01590, 2018. \n[31] A. Kokalj, Comput. Mater. Sci. 28 (2) (2003) 155–168, https://doi org 10 1016 S0927 0256(03 00104 6. \n[32] S.R. Hall, F.H. Allen, I.D. Brown, Acta Crystallogr. A 47 (6) (1991) 655–685. \n[33] F.C. Bernstein, T.F. Koetzle, G.J. Williams, E.F. Meyer, M.D. Brice, J.R. Rodgers, O. Kennard, T. Shimanouchi, M. Tasumi, J. Mol. Biol. 112 (3) (1977) 535–542, https://doi org 10 1016 S0022 2836(77 80200 3. \n[34] Y. Hinuma, G. Pizzi, Y. Kumagai, F. Oba, I. Tanaka, Comput. Phys. Sci. 128 (2017) 140–184, https://doi org 10 1016 j commatsci 2016 10 015. \n[35] W. Setyawan, S. Curtarolo, Comput. Mater. Sci. 49 (2) (2010) 299–312, https:// doi org 10 1016 j commatsci 2010 05 010. \n[36] J.D. Hunter, Comput. Sci. Eng. 9 (3) (2007) 90–95, https://doi org 10 1109 MCSE 2007.55. \n[37] W. Voigt, et al., Lehrbuch der kristallphysik, vol. 962, Teubner, Leipzig, 1928. \n[38] O.H. Nielsen, R.M. Martin, Phys. Rev. Lett. 50 (1983) 697–700, https://doi org 10 1103 PhysRevLett 50 697. \n[39] O. Nielsen, R.M. Martin, Phys. Rev. B 32 (6) (1985) 3792, https://doi org 10 1103 PhysRevB 32 3792. \n[40] S. Zhang, R. Zhang, Comput. Phys. Commun. 220 (2017) 403–416, https://doi org 10 1016 j cpc 2017.07.020. \n[41] R. Golesorkhtabar, P. Pavone, J. Spitaler, P. Puschnig, C. Draxl, Comput. Phys. Commun. 184 (8) (2013) 1861–1873, https://doi org 10 1016 j cpc 2013 03 010. \n[42] J.F. Nye, et al., Physical Properties of Crystals: Their Representation by Tensors and Matrices, Oxford University Press, 1985. \n[43] Y. Le Page, P. Saxe, Phys. Rev. B 63 (17) (2001) 174103, https://doi org 10 1103 PhysRevB 63 174103. \n[44] R. Yu, J. Zhu, H. Ye, Comput. Phys. Commun. 181 (3) (2010) 671–675, https:// doi org 10 1016 j cpc 2009 11.017. \n[45] Y. Le Page, P. Saxe, Phys. Rev. B 65 (2002) 104104, https://doi org 10 1103 PhysRevB 65 104104. \n[46] Z. Hashin, S. Shtrikman, J. Mech. Phys. Solids 10 (4) (1962) 343–352, https:// doi org 10 1016 0022 5096(62 90005 4. \n[47] F. Mouhat, F.m.c.-X. Coudert, Phys. Rev. B 90 (2014) 224104, https://doi org 10 1103 PhysRevB 90 224104. \n[48] A. Reuss, Z. Angnew, Math. Meth. 9 (1929) 55, https://doi org 10 1007 BF00544497. \n[49] R. Hill, Proc. Phys. Soc. A 65 (5) (1952) 349–354, https://doi org 10 1088 0370- 1298 65 5 307. \n[50] M. Maz´dziarz, 2D Mater. 6 (4) (2019) 048001, https://doi org 10 1088 2053 1583 ab2ef3. \n[51] L.D. Landau, E.M. Lifshitz, Course of Theoretical Physics Vol 7: Theory and Elasticity, Pergamon Press, 1959. \n[52] X. Wei, B. Fragneaud, C.A. Marianetti, J.W. Kysar, Phys. Rev. B 80 (2009) 205407, https://doi org 10 1103 PhysRevB 80 205407. \n[53] S. Haastrup, M. Strange, M. Pandey, T. Deilmann, P.S. Schmidt, N.F. Hinsche, M.N. Gjerding, D. Torelli, P.M. Larsen, A.C. Riis-Jensen, et al., 2D Mater. 5 (4) (2018) 042002, https://doi org 10 1088 2053 1583 aacfc1. \n[54] L. Wang, A. Kutana, X. Zou, B.I. Yakobson, Nanoscale 7 (2015) 9746–9751, https://doi org 10 1039 C5NR00355E. \n[55] K. Latimer, S. Dwaraknath, K. Mathew, D. Winston, K.A. Persson, npj Comput. Mater. 4 (1) (2018) 40, https://doi org 10 1038 s41524 018 0091 x. \n[56] O.L. Anderson, O.L. Anderson, et al., Equations of State of Solids for Geophysics and Ceramic Science, vol. 31, Oxford University Press on Demand, 1995. \n[57] F.D. Murnaghan, Proc. Natl. Acad. Sci. USA 30 (9) (1944) 244–247, https:// doi org 10 1073 pnas 30 9 244. \n[58] F. Birch, Phys. Rev. 71 (1947) 809–824, https://doi org 10 1103 PhysRev.71.809. \n[59] J.H. Dymond, R. Malhotra, Int. J. Thermophys. 9 (6) (1988) 941–951, https:// doi org 10 1007 BF01133262. \n[60] P. Vinet, J. Ferrante, J.H. Rose, J.R. Smith, J. Geophys. Res. 92 (B9) (1987) 9319–9325, https://doi org 10 1029 JB092iB09p09319. \n[61] M. Hebbache, M. Zemzemi, Phys. Rev. B 70 (2004) 224107, https://doi org 10 1103 PhysRevB 70 224107. \n[62] P.B. Roy, S.B. Roy, J. Phys. Condens. Matter 17 (39) (2005) 6193–6216, https:// doi org 10 1088 0953 8984 17 39 007. \n[63] D.C. Pack, W.M. Evans, H.J. James, Proc. Phys. Soc. 60 (1) (1948) 1–8, https:// doi org 10 1088 0959 5309 60 1 302. \n[64] J.-P. Poirier, A. Tarantola, Phys. Earth Planet. Inter. 109 (1) (1998) 1–8, https:// doi org 10 1016 S0031 9201(98 00112 5. \n[65] L.D. Whalley, J.M. Frost, B.J. Morgan, A. Walsh, Phys. Rev. B 99 (2019) 085207, https://doi org 10 1103 PhysRevB 99 085207. \n[66] A.J. Williamson, L.W. Wang, A. Zunger, Phys. Rev. B 62 (2000) 12963–12977, https://doi org 10 1103 PhysRevB 62 12963. \n[67] N. Naka, K. Fukai, Y. Handa, I. Akimoto, Phys. Rev. B 88 (2013) 035205, https:// doi org 10 1103 PhysRevB 88 035205. \n[68] K. Momma, F. Izumi, J. Appl. Crystallogr. 44 (6) (2011) 1272–1276, https:// doi org 10 1107 S0021889811038970. \n[69] M. Frisch, G. Trucks, H.B. Schlegel, G. Scuseria, M. Robb, J. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G. Petersson, et al., Gaussian 09, Revision a. 02, vol. 200, Gaussian, Inc., Wallingford, CT, 2009, p. 28. \n[70] M. Peressi, N. Binggeli, A. Baldereschi, J. Phys. D, Appl. Phys. 31 (11) (1998) 1273–1299, https://doi org 10 1088 0022 3727 31 11 002. \n[71] S.B. Dugdale, Phys. Scr. 91 (5) (2016) 053009, https://doi org 10 1088 0031 8949 91 5 053009. \n[72] M. Kawamura, Comput. Phys. Commun. 239 (2019) 197–203, https://doi org 10 1016 j cpc 2019 01.017. \n[73] V. Popescu, A. Zunger, Phys. Rev. Lett. 104 (2010) 236403, https://doi org 10 1103 PhysRevLett 104 236403. \n[74] V. Popescu, A. Zunger, Phys. Rev. B 85 (2012) 085201, https://doi org 10 1103 PhysRevB 85 085201. \n[75] M. Gajdoš, K. Hummer, G. Kresse, J. Furthmüller, F. Bechstedt, Phys. Rev. B 73 (2006) 045112, https://doi org 10 1103 PhysRevB 73 045112. \n[76] M. Fox, Optical properties of solids, 2002. \n[77] L. Hedin, Phys. Rev. 139 (3A) (1965) A796, https://doi org 10 1103 PhysRev. 139 A796. \n[78] F. Fuchs, J. Furthmüller, F. Bechstedt, M. Shishkin, G. Kresse, Phys. Rev. B 76 (11) (2007) 115109, https://doi org 10 1103 PhysRevB 76 115109. \n[79] G. Onida, L. Reining, A. Rubio, Rev. Mod. Phys. 74 (2002) 601–659, https:// doi org 10 1103 RevModPhys 74 601. \n[80] F. Hüser, T. Olsen, K.S. Thygesen, Phys. Rev. B 88 (2013) 245309, https://doi org 10 1103 PhysRevB 88 245309. \n[81] P. Cudazzo, I.V. Tokatly, A. Rubio, Phys. Rev. B 84 (2011) 085406, https://doi org 10 1103 PhysRevB 84 085406. \n[82] L. Matthes, O. Pulci, F. Bechstedt, New J. Phys. 16 (10) (2014) 105007, https:// doi org 10 1088 1367 2630 16 10 105007. \n[83] L. Matthes, O. Pulci, F. Bechstedt, Phys. Rev. B 94 (2016) 205408, https://doi org 10 1103 PhysRevB 94 205408. \n[84] Z. Torbatian, R. Asgari, Phys. Rev. B 98 (2018) 205407, https://doi org 10 1103 PhysRevB 98 205407. \n[85] M.S. Dresselhaus, Solid state physics part ii optical properties of solids, 2001. \n[86] W.-J. Yin, T. Shi, Y. Yan, Adv. Mater. 26 (27) (2014) 4653–4658, https://doi org 10 1002 adma 201306281. \n[87] Transition dipole moment, https://en wikipedia org w index php?title= Transition_dipole_moment&oldid=902785194/. (Accessed 4 April 2020). \n[88] W. Meng, X. Wang, Z. Xiao, J. Wang, D.B. Mitzi, Y. Yan, J. Phys. Chem. Lett. 8 (13) (2017) 2999–3007, https://doi org 10 1021 acs pclett 7b01042. \n[89] J.K. Nørskov, F. Studt, F. Abild-Pedersen, T. Bligaard, Fundamental Concepts in Heterogeneous Catalysis, 1st edition, Wiley, 2014. \n[90] B. Hammer, J. Nørskov, Surf. Sci. 343 (3) (1995) 211–220, https://doi org 10 1016 0039 6028(96 80007 0. \n[91] B. Hammer, J. Nørskov, in: Impact of Surface Science on Catalysis, in: Advances in Catalysis, vol. 45, Academic Press, 2000, pp. 71–129. \n[92] D.A. McQuarrie, J.D. Simon, Molecular thermodynamics, 1999. \n[93] J.W. Ochterski, Thermochemistry in Gaussian, Gaussian Inc., 2000, pp. 1–19. \n[94] M. Chase, J. Phys. Chem. Ref. Data, Monogr. 9 (1998) 12. \n[95] G.R. Kneller, V. Keiner, M. Kneller, M. Schiller, Comput. Phys. Commun. 91 (1) (1995) 191–214, https://doi org 10 1016 0010 4655(95 00048 K. \n[96] T. Róg, K. Murzyn, K. Hinsen, G.R. Kneller, J. Comput. Chem. 24 (5) (2003) 657–667, https://doi org 10 1002 jcc 10243. \n[97] S.-T. Lin, M. Blanco, W.A. Goddard, J. Chem. Phys. 119 (22) (2003) 11792–11805, https://doi org 10 1063 1.1624057. \n[98] J.M. Dickey, A. Paskin, Phys. Rev. 188 (1969) 1407–1418, https://doi org 10. 1103 PhysRev.188 1407. \n[99] A.K. Soper, C.J. Benmore, Phys. Rev. Lett. 101 (2008) 065502, https://doi org 10 1103 PhysRevLett 101.065502. \n100] S. Imoto, S.S. Xantheas, S. Saito, J. Chem. Phys. 138 (5) (2013) 054506, https:// doi org 10 1063 1.4789951. " + }, + { + "id": "10.1038_s41467-021-21919-5", + "DOI": "10.1038/s41467-021-21919-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-21919-5", + "Relative Dir Path": "mds/10.1038_s41467-021-21919-5", + "Article Title": "Regulating Fe-spin state by atomically dispersed Mn-N in Fe-N-C catalysts with high oxygen reduction activity", + "Authors": "Yang, GG; Zhu, JW; Yuan, PF; Hu, YF; Qu, G; Lu, BA; Xue, XY; Yin, HB; Cheng, WZ; Cheng, JQ; Xu, WJ; Li, J; Hu, JS; Mu, SC; Zhang, JN", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "As low-cost electrocatalysts for oxygen reduction reaction applied to fuel cells and metal-air batteries, atomic-dispersed transition metal-nitrogen-carbon materials are emerging, but the genuine mechanism thereof is still arguable. Herein, by rational design and synthesis of dual-metal atomically dispersed Fe,Mn/N-C catalyst as model object, we unravel that the O-2 reduction preferentially takes place on Fe-III in the FeN4/C system with intermediate spin state which possesses one e(g) electron (t(2g)4e(g)1) readily penetrating the antibonding pi-orbital of oxygen. Both magnetic measurements and theoretical calculation reveal that the adjacent atomically dispersed Mn-N moieties can effectively activate the Fe-III sites by both spin-state transition and electronic modulation, rendering the excellent ORR performances of Fe, Mn/N-C in both alkaline and acidic media (halfwave positionals are 0.928 V in 0.1 M KOH, and 0.804 V in 0.1 M HClO4), and good durability, which outperforms and has almost the same activity of commercial Pt/C, respectively. In addition, it presents a superior power density of 160.8 mW cm(-2) and long-term durability in reversible zinc-air batteries. The work brings new insight into the oxygen reduction reaction process on the metal-nitrogen-carbon active sites, undoubtedly leading the exploration towards high effective low-cost non-precious catalysts.", + "Times Cited, WoS Core": 702, + "Times Cited, All Databases": 712, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000631927600019", + "Markdown": "# Regulating Fe-spin state by atomically dispersed Mn-N in Fe-N-C catalysts with high oxygen reduction activity \n\nGege Yang1, Jiawei Zhu2,3, Pengfei Yuan4, Yongfeng ${\\mathsf{H}}{\\mathsf{u}}^{5}$ , Gan ${\\sf Q}{\\sf u}^{1}$ , Bang-An Lu1, Xiaoyi Xue1, Hengbo Yin1, Wenzheng Cheng1, Junqi Cheng1, Wenjing $\\mathsf{X}\\mathsf{u}^{1}$ , Jin Li1, Jinsong Hu $\\textcircled{1}$ 6, Shichun $\\mathsf{M u}^{2,3\\boxtimes}$ & Jia-Nan Zhang1✉ \n\nAs low-cost electrocatalysts for oxygen reduction reaction applied to fuel cells and metal-air batteries, atomic-dispersed transition metal-nitrogen-carbon materials are emerging, but the genuine mechanism thereof is still arguable. Herein, by rational design and synthesis of dual-metal atomically dispersed Fe,Mn/N-C catalyst as model object, we unravel that the $\\mathsf{O}_{2}$ reduction preferentially takes place on $\\mathsf{F e}^{|||}$ in the $\\mathsf{F e N}_{4}/\\mathsf C$ system with intermediate spin state which possesses one $\\mathsf{e}_{\\mathrm{g}}$ electron $\\mathrm{(t_{2g}4e_{g}1)}$ readily penetrating the antibonding $\\pi$ -orbital of oxygen. Both magnetic measurements and theoretical calculation reveal that the adjacent atomically dispersed Mn-N moieties can effectively activate the $\\mathsf{F e}^{|||}$ sites by both spin-state transition and electronic modulation, rendering the excellent ORR performances of Fe, $M n/N-C$ in both alkaline and acidic media (halfwave positionals are $0.928\\mathrm{\\:V}$ in $0.1\\ M\\ K{\\mathsf{O H}}$ , and $0.804\\mathrm{~V~}$ in $0.1\\mathrm{~M~HClO_{4})}$ , and good durability, which outperforms and has almost the same activity of commercial $\\mathsf{P t/C},$ respectively. In addition, it presents a superior power density of $160.8~\\mathsf{m w}~\\mathsf{c m}^{-2}$ and long-term durability in reversible zinc–air batteries. The work brings new insight into the oxygen reduction reaction process on the metal-nitrogen-carbon active sites, undoubtedly leading the exploration towards high effective low-cost non-precious catalysts. \n\nT he oxygen reduction reaction (ORR), represents the cornerstone for regenerative energy conversion devices involving polymer electrolyte membrane fuel cell (PEMFC) and metal–air batteries1–7. Hitherto, the generally recognized state-of-the-art platinum $\\left(\\mathrm{Pt}\\right)$ -based catalysts possess the highest kinetic activity in catalyzing ORR under acid and alkaline media, however, the scarcity, price, and low methanol crossover tolerance of Pt alloys have motivated the search for cost-effective nonnoble-metal electrocatalysts8–13. Replacement of noble-metal materials with less expensive, highly active, and durable electrocatalysts for ORR is thereby increasingly attractive but arduous with great challenges ahead14–17. \n\nTransition metals $\\mathbf{\\dot{M}}=\\mathbf{M}\\mathbf{n}$ , Fe, Co, Ni, etc.) possessing the $3d$ unoccupied orbitals can accommodate foreign electrons to reduce the bonding strength between $\\mathrm{OOH^{*},O^{*}/O H^{*}}$ intermediates, allowing them with the potential to catalyze the $\\mathrm{O}_{2}$ reduction process18. During such a process, the activity of catalysts is mainly affected by its electronic structure, where the energy is released to form the $\\mathrm{M}^{\\mathrm{(m+1)+}}\\mathrm{-}\\mathrm{O}_{2}^{2-}$ bond on the surface of catalysts by breaking the $\\mathrm{M^{m+}{-}O H^{-}}$ bond, ensuring a fast displacement of $\\mathrm{O}^{2-}/\\mathrm{\\bar{O}H}^{-}$ and $\\mathrm{OH^{-}}$ regeneration19,20. Generally, $\\bf\\dot{F}e^{\\mathrm{III}}$ possesses multiple states due to the coordination environment, which can be classified to display different forms of spin (low spin $\\mathrm{t_{2g}5e_{g}0}$ , medium spin $\\mathrm{\\mathbf{t}_{2g}4\\:e_{g}1}$ , and high spin $\\mathfrak{t}_{2\\mathrm{g}}3\\:\\mathrm{e}_{\\mathrm{g}}2\\bar{)}^{21}$ . The low-spin electron configuration is $\\mathrm{d_{xy}}2\\ \\mathrm{\\d_{yz}}2\\ \\mathrm{\\d_{xz}}1$ , without electrons occupying anti-bond orbitals, resulting in strong ${\\bf{M}}^{\\mathrm{{m}}}$ $+/\\mathrm{O}_{2}$ interactions and stable $\\mathrm{M}^{\\mathrm{(m+1)+}}\\mathrm{-}\\mathrm{O}_{2}\\mathrm{^{2-}}$ bonds, and making it difficult for the $\\mathrm{M^{(m+1)+}{-}O_{2}{2}^{{2}-}/M^{m+}.}$ -OOH transition22. The electron configuration of high spin is $\\mathrm{d_{xy}1\\ d_{y z}1\\ d_{x z}1\\ d_{z}^{2}1\\ d_{x}^{2}–_{y}^{2}1}$ . Unfortunately, the high eg filling $(\\mathrm{d}_{\\mathrm{z}}{}^{2}\\mathrm{l}^{'}\\mathrm{d}_{\\mathrm{x}}{}^{2}{}^{2}\\mathrm{l})$ results in poor adsorption ability and bad performance. The medium spin electron configuration is $\\mathrm{d_{xy}2\\hat{\\ d}_{y z}1\\ d_{x z}1\\ d_{z}21}$ , while the single $\\mathrm{d}_{\\mathrm{z}}^{\\ 2}$ electron of the mediate spin state can readily penetrate the antibonding $\\pi$ -orbital of oxygen, rendering high ORR activity23. To date, a large amount of research has been devoted to the identification and geometric design of active sites to expose more active sites24. However, it is rarely reported to improve the activity of the catalyst by regulating the electronic structure. Therefore, modulating metal species with moderate spins is expected to increase ORR activity, but how to easily control the spin state is still very challenging25. \n\nThe family of metal-nitrogen complex carbon (M–N–C) materials has high conductivity and unique metal–ligand interaction, which have been regarded as the most promising alternatives to commercial $\\mathrm{Pt/C}$ because of their outstanding performance in activation of oxygen26–30. According to the latest research, due to the improvement in the structural stability of the active center and the modulation of the electron cloud, bimetallic particles show higher activity and stability when compared with monometallic atomic particles31–33. \n\nHerein, we first successfully implant $\\mathrm{{Mn-N}}$ moieties in the conventional $\\mathrm{Fe/N{\\mathrm{-}}C}$ system, by preparing a dual-metal atomically dispersed $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ electrocatalyst with the prepolymerization and pyrolysis processes, whereby dicyandiamide is used as C and $\\mathrm{~N~}$ sources, iron phthalocyanine (FePc) and manganese nitrate $(\\mathrm{Mn}(\\mathrm{NO}_{3})_{2})$ are selected as metal precursor. The dual-sites dispersion tagged in the N-doped defect carbon is probably originated from adsorption of Mn salts and their bonding with neighboring $\\mathrm{Fe-N_{4}}$ center (Iron phthalocyanine molecular) (Fig. 1a)15. The introduction of $\\mathrm{{Mn-N}}$ moieties causes $\\mathrm{Fe}^{\\mathrm{III}}$ electron delocalization and makes the spin state of $\\mathrm{Fe}^{\\mathrm{III}}$ transition from low spin $(\\mathrm{t}_{2\\mathrm{g}}5\\mathrm{e}_{\\mathrm{g}}0)$ to intermediate spin $(\\mathbf{t}_{2\\mathrm{g}}4~\\mathbf{e}_{\\mathrm{g}}1)$ , readily penetrating the antibonding $\\pi$ -orbital of oxygen, and thus allowing an excellent ORR activity in both $0.1\\mathrm{M}$ $\\mathrm{{HClO}_{4}}$ and $0.1\\mathrm{{M}}$ KOH solutions. DFT calculations reveal that $\\mathrm{Fe,Mn/N-C}$ can interact with oxygen moderately, with appropriate bond length and adsorption energy, beneficial to promote the kinetic process of ORR. \n\n# Results \n\nMaterial synthesis and characterization. The single metal atomically dispersed $\\mathrm{Fe/N{-}C}$ and $\\mathrm{Mn/N\\mathrm{-}C}$ catalysts with the sample loading using the same method were also synthesized as controlled experiments. As shown in Supplementary Fig. 1, the scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images of $\\mathrm{Fe,Mn/N-C}$ show a graphene-like carbon sheet morphology with a porous structure34. The aberration-corrected high-angle annular dark-filed scanning TEM (HAADF–STEM) was used to acquire the evidence of Fe and Mn distribution at atomic resolution. As displayed in Fig. 1b, a number of bright spots are clearly observed, in which Fe/Mn atomic pairs are randomly distributed on the surface of N-doped carbon as highlighted by red cycles, attributed to heavy Fe, Mn than light N, C atoms35. In order to make it clearer whether $\\mathrm{Mn-N_{4}}^{\\overline{{}}}$ is adjacent to $\\mathrm{Fe-N_{4}}.$ the atomic-resolution HAADFSTEM of Fe–N–C and $\\scriptstyle\\mathrm{Mn-N-C}$ catalysts have been additionally carried out. As displayed in Supplementary Figs. 2 and 3, isolated single Fe or Mn atoms can be distinctly observed on the carbon support, indicating that neither atomic Fe–Fe pairs nor atomic $\\mathbf{Mn-Mn}$ pairs form by our synthetic strategy. In contrast, when adding Mn and Fe sources stimulatingly in the synthetic system, a number of bright dual spot-pairs are clearly observed, further confirming that it forms the heterogeneous-metal- atoms pairs (Supplementary Fig. 4). The electron energy loss spectrum (EELS) (Fig. 1c) reals the coexistence of Fe and Mn elements in $\\mathrm{Fe,Mn/}$ N–C. As shown in Fig. 1d–e, a statistical analysis of more than 30 metal pairs has been conducted, which presents that the distance between the metal-pairs is $0.25\\pm0.02\\mathrm{nm}$ . The high-resolution TEM (HRTEM) images (Fig. 1f) demonstrates the lattice distortion defect characteristic, which might be attributed to the coordination of dual $\\mathrm{Fe/Mn}$ atoms with nitrogen. The energydispersive X-ray spectroscopic (EDS) elemental mapping analyses further manifest the homogeneous distribution of C, N, Fe, and Mn distribution over $\\mathrm{Fe,\\bar{M}n/N\\mathrm{-C}}$ (Fig. 1g). No characteristic crystal peaks of metal and metal oxides can be observed in the X-ray reduction patterns of carbonized samples, excluding the formation of large particles (Supplementary Fig. $6)^{36}$ . Taken together, such collective HAADF-STEM, EDS elemental mapping, EELS and the distance between the metal-pairs confirm the co-existence of Fe and Mn in a form of $\\mathrm{Fe/Mn}$ atomic pairs37. \n\nThe Raman spectrum of $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ shows that the intensity ratio of two main bands located at 1354 and $1591\\mathrm{cm}^{-1}$ $\\left({I_{\\mathrm{D}}}/{I_{\\mathrm{G}}}\\right)$ is 0.94, further confirming the defective structure of the carbon nanosheets38 (Supplementary Fig. 7, Supplementary Table 1). The specific surface area and pore volume of $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ , with rich microporous and mesoporous, are $245.33\\mathrm{m}^{2}\\mathrm{g}^{-1}$ and $0.3\\mathrm{m}^{3}\\mathrm{g}^{-1}$ , respectively (Supplementary Fig. 8). As reported, microporous can increase the density of active sites, and mesoporous are beneficial to the mass transfer, thus improving catalytic activity39. \n\nThe chemical composition of $\\mathrm{Fe,Mn/N-C}$ was further investigated using $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS). As depicted in Supplementary Table 3, after rational doping of $\\mathrm{M}\\dot{\\bf n}^{\\mathrm{III}}$ moieties, the content of graphitic N $(401.63\\mathrm{eV})$ increases compared with Fe–N/C sample, implying that Mn tends to catalyze the formation of highly ordered and less defective graphitic carbon, thereby improving the stability of nanocarbons40. As depicted in Supplementary Fig. 9a, the N 1s spectrum indicates five types of $\\mathrm{~N~}$ species existing in $\\mathrm{Fe,Mn/}$ $\\bar{\\bf N}{-}{\\bf C}$ . Especially, the $\\mathrm{Fe/\\dot{M}n{-}N_{x}}$ bond with the binding energy of $399.1\\mathrm{eV}$ , associated with the abundant atomically dispersed metal-nitrogen functional moieties in $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ . The content \n\n![](images/e8d8ae029075a869ef8688be6cec79d924a4c44bae5d270be5113876b1624413.jpg) \nFig. 1 Synthetic illustration and TEM characterizations of Fe,Mn/N–C catalyst. a Schematic illustration of synthesis procedure for Fe,Mn/N–C catalysts. b Aberration-corrected HAADF-STEM image and some of bimetallic Fe/Mn sites are highlighted by larger red circles. c Fe,Mn/N–C structure analyzed by EELS. d The intensity profiles obtained on two bimetallic Fe–Mn sites. e Statistical Fe–Mn distance in the observed diatomic pairs. f HR-TEM of Fe,Mn/N–C, in which some lattice distortions are highlighted by red circles. g HAADF-STEM image of Mn, Fe/N–C with mappings of individual elements (C, N, Fe, and Mn). \n\nof Fe and Mn detected by ICP analysis are 2.3 and 1.6 wt. $\\%$ \nrespectively. \n\nTo make it clear of the local structural information for Fe and Mn, X-ray absorption near-edge structure (XANES) and K-edge extended X-ray absorption fine structure (EXAFS) measurements were performed41. As shown in Fig. 2a, Fe K-edge XANES spectra show that the adsorption threshold position of $\\mathrm{Fe,Mn/N-\\bar{C}}$ and $\\mathrm{Fe/N{\\mathrm{-}}C}$ located between FeO and ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3},$ which indicated that the valance of Fe in $\\mathrm{Fe,Mn/N-C}$ and $\\mathrm{Fe/N{-}C}$ is situated between $+2$ and $+3^{42}$ . As shown in Fig. 2b, the Fourier transform (FT) $\\mathrm{k}^{3}$ - weighted EXAFS spectra of Fe K-edge show apparent the same peak of $\\mathrm{Fe,Mn/N{\\mathrm{-}}C}$ and $\\mathrm{Fe/N{\\mathrm{-}}C}$ at $\\mathrm{\\check{1}.4{-}\\mathring{A}}$ corresponding to the Fe–N coordination. The peak at $2.16\\mathrm{-}\\mathring{\\mathrm{A}}$ found in $\\mathrm{Fe,\\bar{M}n/N\\mathrm{-C}}$ represents the average nearest Fe-metal atoms distance but almost no such signal in $\\bar{\\mathrm{Fe/N\\mathrm{-}C}}$ at the same position. As shown in Fig. 2d, the Fourier transform (FT) $\\mathrm{k}^{3}$ -weighted EXAFS spectra of Mn K-edge demonstrate that $\\mathrm{Fe,Mn/N-C}$ not only shows a peak at $1.40\\mathring\\mathrm{A}$ indexing $\\mathrm{{Mn-N}}$ coordination, but also gives a peak at $2.34\\mathring\\mathrm{A}$ , demonstrating the next nearest Mn–metal atoms distance in $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ . Wavelet transform (WT) was also used to investigate the Fe K-edge EXAFS oscillations of $\\mathrm{Fe,Mn/N-C}$ and the references. As shown in Fig. 2e, the WT analysis of $\\mathrm{Fe,Mn/}$ N–C, Fe/N–C and $\\mathrm{Mn/N-C}$ shows only one intensity maximum at about $4.0\\mathring\\mathrm{A}^{-1}$ which is very close to that in the reference FePc $({\\sim}4.0\\mathring{\\mathrm{A}}^{-1})$ and $\\mathrm{MnPc}$ $({\\sim}4.0\\mathring\\mathrm{A}^{-1})$ (Supplementary Fig. 11a, c). In order to confirm the existence of $\\mathrm{Fe,Mn-N}_{6}{\\cdot}1$ moieties in $\\mathrm{Fe,Mn/}$ N–C, density functional theory (DFT) is firstly used to deduce the possible structure of $\\mathrm{Fe,Mn/N-C}$ (Supplementary Fig. 12a–e) and single atom $\\mathrm{Fe-N_{4}}$ (Supplementary Fig. 12f). Based on its simulated Fe K-edge spectra of XANES, the calculated architectural $\\mathrm{Fe,Mn-N}_{6^{-1}}$ model was in agreement with experimental spectra. Other structures could be excluded by the comparisons between the K-edge XANES experimental and theoretical spectra (Supplementary Fig. 12). Therefore, the $\\mathrm{Fe,Mn/N_{6}{-}1}$ model is suggested as the most possible structure for our catalyst. Furthermore, as calculated based on the fitting $\\mathbf{k}$ space curve in Supplementary Fig. 13 and listed in Supplementary Table 4, the coordination numbers of $\\mathrm{Fe-N_{1:}}$ $\\mathrm{Fe}{\\mathrm{-N}}_{2}$ and Fe–Mn are $1.8\\pm0.3$ , $2.0\\pm0.4$ , and $0.9\\pm0.2$ , respectively, and the coordination numbers of $\\mathrm{Mn-N_{1}}$ , $\\ensuremath{\\mathrm{Mn}}-\\ensuremath{\\mathrm{N}_{2}}$ , and $_\\mathrm{Mn-Fe}$ are $1.9\\pm0.3$ , $2.2\\pm0.4$ , and $1.1\\pm0.2$ , respectively. Compared with reported single metal centers in $_{\\mathrm{M-N-C}}$ structures, $\\mathrm{\\bar{Fe},M n/N{\\mathrm{-C}}}$ adopted a different dual-metal center, whereas the porphyrin-like structure was deformed. Thus, it is reasonable that the bond distances of $\\mathrm{Fe-N_{1:}}$ $\\mathrm{Fe}{\\mathrm{-N}}_{2}$ , $\\ensuremath{\\mathrm{Mn}}-\\ensuremath{\\mathrm{N}_{1}}$ and $\\ensuremath{\\mathrm{Mn}}-\\ensuremath{\\mathrm{N}_{2}}$ are different. Consequently, it can be inferred that the structure of $\\mathrm{Fe,Mn/N-C}$ is $\\mathrm{Fe,Mn/N_{6}{-}1}$ model. \n\nTo discriminate different Fe species, Mossbauer spectroscopy analysis was carried out43. As shown in Fig. 2f, for the Mossbauer spectra of $\\mathrm{Fe,Mn/N-C,}$ $\\mathrm{D}_{1}$ with relatively larger values of isomer shift (IS) and quadrupole splitting (QS), can be assigned to FePc-like $\\mathrm{Fe^{II}\\Sigma^{\\bullet}N_{4}}$ species44. $\\mathrm{D}_{3}$ can be attributed to the N- $\\mathrm{(Fe^{III}N_{4})}$ -N high-spin structure, the structure is so robust that it cannot be acted as the catalytically active site. $\\mathrm{D}_{4}$ can be assigned to the N $\\mathrm{[-(Fe^{III}N_{4})}$ medium-spin structure, and the unsaturated coordination structure of $\\mathrm{D}_{4}$ enables it to be catalytically active in chemical reactions. The IS(δ), descriptor of the valence state of the Mossbauer absorber atom, indicates that Fe exists mainly in the form of trivalent with high crystal field stabilization energy25. The quantitative analysis (Supplementary Table 5) reveals that the iron responsible for $\\mathrm{D}_{1}$ , ${\\bf D}_{3}$ , and $\\mathrm{D}_{4}$ makes up $13.5\\%$ , $27.1\\%$ , and $59.4\\%$ , respectively. This confirms that the $\\mathrm{\\dot{F}e^{I I I}}$ in $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ is predominantly present as $\\mathrm{Fe}^{\\mathrm{III}}$ with the medium-spin structure. \n\n![](images/4b2c841aa04cbfc989d8df9451e61268948284ca7ecef5de517b0af20c675d8f.jpg) \nFig. 2 XAS and 57Fe Mössbauer spectroscopy and Magnetic susceptibility of the catalysts. a Fe K-edge XANES and b Fourier-transform EXAFS spectra of $\\mathsf{F e,M n/N-C}$ and reference samples. c Mn K-edge XANES and d Fourier-transform EXAFS spectra of Fe,Mn/N–C and reference samples. e Wavelet transform of the $\\mathsf{k}^{3}$ -weighted EXAFS data of Fe,Mn/N–C, Fe/N–C, and Mn/N–C. f Room-temperature $^{57}\\mathsf{F e}$ Mossbauer spectrum of $\\mathsf{F e},M\\mathsf{n}/\\mathsf{N}-\\mathsf{C}$ . Magnetic susceptibility of $\\pmb{\\mathrm{g}}\\mathsf{F e},\\mathsf{M n/N-C},$ , h Fe/N–C (M.S. represents medium-spin, L.S. represents low-spin). \n\nTo further unravel the electron spin configuration of $\\mathrm{Fe,Mn/}$ ${\\mathrm{N-C}},$ the zero-field cooling (ZFC) temperature-dependent magnetic susceptibility was measured24. The calculated effective magnetic moment of $\\mathrm{Fe,Mn/N-C}$ and $\\mathrm{Fe/N{\\mathrm{-}}C}$ is $3.75\\mu_{\\mathrm{eff}}$ and $2.16\\mu_{\\mathrm{eff}},$ respectively (Fig. 2g, h). Besides, we further obtained the number of unpaired $d$ electron $(n)$ of $\\mathrm{Fe}^{\\mathrm{III}}$ ion via the following equation:22 \n\n$$\n\\mu_{\\mathrm{eff}}=\\sqrt{n(n+2)}\n$$ \n\nwhereby the number of unpaired d electron $(n)$ of $\\mathrm{Fe/N{\\mathrm{-}}C}$ is about 1.3, which means $\\mathrm{Fe}^{\\mathrm{III}}$ ions have a low-spin state without $\\boldsymbol{\\mathrm{e_{g}}}$ filling, so that no electron occupied in the $\\upsigma^{*}$ antibonding orbital of $\\mathrm{FeN_{4}}$ leads to a very strong $\\mathrm{Fe}^{\\mathrm{III}}/\\mathrm{O}_{2}$ interaction and a quite stable $\\mathrm{Fe^{4+}}{\\cdot}\\mathrm{O}_{2}{}^{2-}$ bond18. While the number of unpaired $d$ electron $(n)$ of $\\mathrm{Fe,Mn/N-C}$ is about 3, which has single $\\boldsymbol{\\mathrm{e_{g}}}$ filling21. Certainly, the unusual low-spin state of neighboring $\\mathrm{{Mn}^{I I}}$ moieties permits $\\mathrm{Fe}^{\\mathrm{III}}$ in $\\mathrm{FeN_{4}}$ to achieve the ideal $\\boldsymbol{\\mathrm{e_{g}}}$ filling. It is reckoned that this intrinsically optimal electronic configuration would endow the as-designed $\\mathrm{Fe,Mn/N-C}$ with a high catalytic activity. For verification, we measure the temperatureprogrammed desorption of $\\mathrm{O}_{2}$ $\\mathrm{\\mathrm{~\\small~\\leftmoon~}}_{2}$ -TPD) as shown in Supplementary Fig. 14. Owing to the electron affinity of oxygen, the electron can be transferred from catalyst to chemisorbed oxygen, so that it requires high temperature for desorption24. The amount and the $\\mathrm{O}_{2}$ desorption temperature obviously increase from Fe, $\\mathrm{Mn/N\\mathrm{-}C}$ $\\mathrm{\\mathrm{~\\sc~\\cdot~O~}}_{2}$ desorption temperature is $385.4^{\\circ}\\mathrm{C})$ to $\\mathrm{Fe/N\\mathrm{-}C}$ $\\mathrm{\\langleO}_{2}$ desorption temperature is $407.6^{\\circ}\\mathrm{C})$ , indicative of stronger bonding between the $\\mathrm{O}_{2}$ and the $\\mathrm{Fe/N{-}C}$ than that of $\\mathrm{Fe,Mn/}$ N–C, which is consistent with the ZFC results. \n\nTo probe the interaction between anchored Fe and Mn, the density of states (DOS) near the Fermi level, mainly originated from the $3d$ state, was investigated45. As shown in Supplementary Fig. 15, obviously, sharp peaks can be seen near the Fermi level for both Fe $\\left(\\mathrm{Fe-N_{4}}\\right)$ and Mn $\\mathrm{(Mn-N_{4})}$ , and the peaks for Fe are more sharply. These indicated that the interaction between Fe and the coming $\\mathrm{O}_{2}$ are stronger than that on Mn. For $\\mathrm{Fe,Mn/N}_{6}$ - 1, clearly differences can be seen, there are obvious overlapping between Fe $3d$ and Mn $3d$ which reflected the interaction by the neighboring atom. In addition, it is supposed that the antibonding state of $\\mathrm{Fe/N{\\mathrm{-}}C}$ possesses low electron energy giving low-spin state, while the higher antibonding electron energy of $\\mathrm{Fe,Mn/N-C}$ further confirming the medium-spin configuration of $\\mathrm{Fe}^{\\mathrm{III}}$ in Fe, $\\mathrm{Mn/N-C}$ . This probably owing to that $\\mathrm{{Mn}^{\\mathrm{{III}}}}$ with higher affinity to electrons can capture electrons from $\\mathrm{Fe^{III}}$ , thus leading to redistribution electrons of Fe $3d^{46}$ . In addition, the orbital hybridization of Fe $3d$ and Mn $3d$ causes obvious band gap narrowing and electron delocalization in $\\mathrm{Fe,Mn/N-C,}$ which increases the conduction band dispersion and reduces the large effective electron mass, thereby improving the electron transport. \n\n![](images/63d3db92af475a62ede73395c017772cbeae702f34bcf256886b1af48d47622a.jpg) \nFig. 3 ORR performances of $\\mathbb{F}e,M n/N-C$ in 0.1 M HClO4 and 0.1 M KOH. a LSV curves of Fe,Mn/N–C, Fe/N–C, Mn/N–C and $\\mathsf{P t/C}$ catalyst in $\\mathsf{O}_{2}$ - saturated 0.1 M ${\\mathsf{H C l O}}_{4}$ solution. b Corresponding Tafel plots obtained from the RDE polarization curves. c ${\\sf H}_{2}{\\sf O}_{2}$ yield and electron transfer number $(n)$ in $0.1M\\mathsf{H C l O}_{4}$ solution. d ORR polarization LSV and CV curves of $\\mathsf{F e},M\\mathsf{n}/\\mathsf{N}-\\mathsf{C}$ measurement before and after 8000 potential cycles at the scan rate of $50\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ with the rotation speed of 1600 rpm. e Comparison of the kinetic current density $(J_{\\boldsymbol{\\mathsf{k}}})$ and $\\mathsf{E}_{1/2}$ of Fe,Mn/N–C, Fe/N–C, Mn/N–C, and $\\mathsf{P t/C}$ catalysts. \n\nElectrochemical oxygen reduction performance. To verify the oxygen reactivity of $\\mathrm{Fe,Mn/N-C}$ with the medium-spin structure for $\\mathbf{\\widetilde{F}e}^{\\mathrm{III}}$ , the ORR electrocatalytic activity in $0.1\\ \\mathrm{HClO_{4}}$ aqueous solution of $\\mathrm{Fe,Mn/N-C}$ was first demonstrated by compared with $\\mathrm{Fe/N{\\mathrm{-}}C}$ and $\\mathrm{Mn/N-C}$ with Cyclic voltammetry (CV) and Linear scan voltammetry (LSV) measurements47. CV curve reveals a significant reduction peak at $0.804\\mathrm{V}$ for $\\mathrm{Fe,Mn/N-C}$ (Supplementary Fig. 16), suggesting a good ORR electrocatalytic activity. LSV curves in $\\mathrm{O}_{2}$ -saturated $0.\\dot{1}\\dot{\\mathrm{~M~HClO_{4}~}}$ with a loading amount of $0.1\\mathrm{mg}\\mathrm{cm}^{-2}$ was performed (Fig. 3a). $\\mathrm{Fe,Mn/N-C}$ obviously presents a high half-wave potential $\\left(\\operatorname{E}_{1/2}\\right)$ of $0.804\\mathrm{V}$ (Supplementary Table 6), which are similar to $\\mathrm{Pt/C}$ $\\mathrm{{'E}}_{1/2}=0.807\\mathrm{{V}})$ , and superior to $\\mathrm{Fe/N\\mathrm{-}C}$ $\\mathrm{(E_{1/2}}=0.702\\:\\mathrm{V},$ , $\\mathrm{Mn/N\\mathrm{-}C}$ $\\mathrm{(E_{1/2}}=0.73\\:\\mathrm{V}.$ ) and most of non-precious metal ORR electrocatalysts (Supplementary Table 7). The ORR kinetics was further probed by the Koutecky–Levich (K–L) method (Supplementary Fig. 17) and Tafel plot (Fig. 3b). The electron transfer number (n) of $\\mathrm{Fe,Mn/}$ $_{\\mathrm{N-C}}$ is 3.91, as evaluated according to the K-L equation12. The n and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield were further evaluated through rotating ring-disk electrode (RRDE, Fig. 3c), where the direct four-electron transfer mediated ORR process is confirmed (the n approaches 4 and the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield is below $4\\%$ ). \n\nAlso, $\\mathrm{Fe,Mn/N-C}$ exhibits excellent stability, as evidenced by a loss of only $18\\mathrm{mV}$ in $\\mathrm{E}_{1/2}$ after 8000 potential cycles in $\\mathrm{O}_{2}$ - saturated $0.1\\mathrm{M}\\mathrm{HClO_{4}}$ solution (Fig. 3d). The stability is largely enhanced over $\\mathrm{Fe/N{-}C}$ (loss $34\\mathrm{mV}$ after 8000 cycles), as well as the $\\mathrm{Mn/N\\mathrm{-}C}$ $21\\mathrm{mV}$ loss) (Supplementary Fig. 18). It can be attributed to the promotion of Mn to the formation of graphitized carbon and $\\mathrm{MnO}_{2}$ during the OER process, enhancing the stability of nano-carbon with reduced carbon corrosion48. In addition, $\\mathrm{Fe,Mn/N-C}$ displays a benchmark chronoamperometry response extended over ${40,000s}$ with retention of $96\\%$ of the initial current (Supplementary Fig. 19). Interestingly, $\\mathrm{Fe,Mn/N-C}$ exhibits more stable retention of current densities without a distinct recession after methanol crossover and CO, implying strong resistance to corrosion and poisoning in acidic electrolytes (Supplementary Fig. 20), better than $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%})$ ) catalyst and control samples $(\\mathrm{Fe/N\\mathrm{-}C}$ and $\\mathrm{Mn/N-C)^{49}}$ . Significantly, $\\mathrm{Fe,Mn/}$ $_{\\mathrm{N-C}}$ also presents outstanding ORR activity measured by CV, LSV, and Tafel plot in 0.1 M KOH (Supplementary Fig. 21–23a). It shows high ORR catalytic activity with $\\mathrm{E}_{1/2}$ of $0.928\\mathrm{V}$ (Fig. 4a, Supplementary Table 8 and 9), $97\\mathrm{mV}$ superior to that of $\\mathrm{Pt/C}$ $\\mathrm{(E_{1/2}}=0.831\\mathrm{V},$ . The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield for the $\\mathrm{Fe,Mn/N-C}$ remains below $3\\%$ over all potentials with $n\\approx4$ , comparable to $\\mathrm{Pt/C}$ (Supplementary Fig. 23b)49. What should be noted that $\\mathrm{Fe,Mn/}$ N–C exhibits excellent with almost no activity decay after $40,000~\\mathrm{CV}$ scanning cycles in $\\mathrm{O}_{2}$ -saturated $0.1\\mathbf{M}$ KOH solution (Supplementary Fig. 23c). In addition, $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ also exhibiting the strong tolerance to methanol with long-term current stability (Supplementary Fig. 23d, e)50. \n\nThe Zn–Air Batteries system analysis. The overall oxygen electrode activity can be evaluated by the difference of OER and ORR metrics51. \n\n$$\n\\Delta E=E_{\\mathrm{j}=10}-E_{1/2}\n$$ \n\n$\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ exhibits a $\\Delta\\mathrm{E}$ value of $0.692\\mathrm{V}$ , lower than ${\\mathrm{RuO}}_{2}$ and $\\mathrm{Pt/C}$ (Fig. 4b). Inspired by the excellent OER and ORR performance, we assembled liquid and flexible all-solid-state rechargeable ZABs for practical applications of $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ (Fig. 4c)52. As anticipated, it displays a high open-circuit voltage of up to $1.4\\mathrm{V}$ and a peak-power density as high as $160.8\\mathrm{mW}\\mathrm{cm}^{-2}$ (Fig. 4d), superior to commercial $\\mathrm{Pt/C}$ $(\\approx64\\:\\mathrm{mW}\\:\\mathrm{cm}^{-2})^{5}$ 3. Surprisingly, Fe, $\\mathrm{M}\\mathrm{\\bar{n}/N-C}$ has a specific capacity of 902 mAh $\\mathrm{\\bfg\\zn^{-\\bar{1}}}$ at the discharge current density of 5 mA $\\mathrm{cm}^{-2}$ with a corresponding energy density of $11\\dot{3}\\dot{6}.5\\mathrm{Wh\\kgzn^{-1}}$ (Supplementary Fig. 25). Its excellent stability is further illustrated by over $81\\mathrm{h}$ at $5.0\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ (Fig. 4e), where the voltage barely changes. A high OVC of $1.33\\mathrm{V}$ is obtained in Fig. 4f. The all-solid-state battery exhibited stable charge (1.94 V) and discharge $\\left(1.04\\mathrm{V}\\right)$ potentials at the current density of $1\\mathrm{mA}\\mathrm{cm}^{-2}$ for $^{6\\mathrm{h}}$ even when the device was bended to a large angle or folded back to front (Fig. $4\\mathrm{g})^{54}$ . \n\n![](images/a9f848527f6555a893b6057249f72b508b03d918b857c4aeb5705f92afb4f198.jpg) \nFig. 4 The performance of Zn–Air Batteries system of Fe,Mn/N–C catalyst. a LSV curves of Fe,Mn/N–C, Fe/N–C, Mn/N–C, and $\\mathsf{P t/C}$ catalyst in $\\mathsf{O}_{2}$ - saturated 0.1 M KOH solution. b LSV curves of Fe,Mn/N–C, commercial $\\mathsf{P t/C}$ and ${\\sf R u O}_{2}$ catalysts on an RDE in 0.10 M KOH, indicating the bifunctional activities toward both ORR and OER. c Schematic representation of the liquid rechargeable ZAB. d Polarization and power density curves of the primary Zn–air batteries of the Fe,Mn/N–C, Fe/N–C, Mn/N–C and $\\mathsf{P t/C}$ catalyst in $\\mathsf{O}_{2}$ -saturated 6 M KOH solution. e Charge−discharge cycling performance of rechargeable Zn−air batteries at a constant charge−discharge current density of $5\\mathsf{m A}\\mathsf{c m}^{-2}$ . f Photograph of all-solid-state zinc–air battery displaying a measured open-circuit voltage of ${\\sim}1.333\\lor$ . Photograph of a lighted LED powered (Left to right be green, red and blue) by three all-solid-state $Z n$ –air batteries. g Galvanostatic discharge–charge cycling curve at $1\\mathsf{m A}\\mathsf{c m}^{-2}$ for the all-solid-state rechargeable ZAB, applying bending strain (as depicted by the inset images) every $2\\mathsf{h}$ . \n\nAtomistic insight into the $\\mathbf{Fe,Mn/N{\\mathrm{-C}}}$ activities. To further shed light on the reason of the superior ORR activities of $\\mathrm{Fe,Mn/}$ $_{\\mathrm{N-C,}}$ density functional theory (DFT) calculations were conducted. Supplementary Figs. 26–28 and Supplementary Tables 10–12 show all possible active sites by optimized the structure via DFT calculations and their free energies for each elementary step was calculated by combining the enthalpy and the harmonic entropy. Considering $\\mathrm{Fe,Mn/N}_{6^{-1}}$ , is the nearest structure of our dual-metal atomically catalyst, we apply $\\mathrm{Fe,Mn/}$ $\\mathrm{N}_{6}{\\cdot}1$ , $\\mathrm{FeN}_{4},$ and $\\mathrm{MnN}_{4}$ graphene as the model reference to represent the difference of $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ , Fe/N–C, and $\\mathrm{Mn/N-C}$ (Supplementary Figs. 27 and 28). In the first step, the metal active site adsorbs oxygen molecules and forms a long $\\ensuremath{\\mathrm{Mn}}{-}\\ensuremath{\\mathrm{O}}_{2}$ bond $(2.209\\mathring{\\mathrm{A}})$ in $\\mathrm{M}\\mathrm{\\dot{n}/N-C}$ (Supplementary Fig. 30). Due to the large $\\mathrm{Mn^{III}}$ ion radius, the interaction with oxygen is so weak that the kinetic rate is limited because the process of proton-electron transfers to $^*\\mathrm{O}_{2}$ or splitting of the $^*\\mathrm{O}$ bind in $\\mathrm{O}_{2}$ (dissociative mechanism) demand extra energy. In addition, $\\mathrm{Mn^{III}}$ ions are unstable in solution and underwent a disproportionation reaction to form $\\mathrm{Mn^{II}}$ and $\\mathrm{Mn^{IV}}$ ions, which makes it very low ORR activities and low stability. The ${\\mathrm{Fe}}{\\mathrm{-}}\\mathrm{O}_{2}$ bond is $1.884\\mathring{\\mathrm{A}}$ in $\\mathrm{Fe/N{-}C}$ (Fig. 5a, b), which makes reaction site that bind oxygen too strongly and proton-electron transfer $^*\\mathrm{O}$ or $^{*}\\mathrm{{OH}}$ be circumscribed42. This promotes the formation of more peroxide intermediates and leads to poor ORR activity and stability. While oxygen is adsorbed by $\\mathrm{Fe/Mn}$ atom pair (Fig. 5c, d), it leads to proper bond length and suitable binding energy, which would reduce the dissociation energy barrier. In addition, it can effectively capture oxygen-containing intermediates and quickly break the bond between M–OH to ensure the regeneration of ${{\\mathrm{O}}^{*}}$ , $\\mathrm{OH^{*}}$ , making the ORR kinetics faster by effectively inhibiting the production of peroxides40. The calculated minimum free-energy path along the subtractions of the ORR is listed in Supplementary Fig. 26. For the $\\mathrm{Fe,Mn/N}_{6}$ -1 model at a potential $\\mathrm{U}{\\bar{=}}0\\mathrm{V}$ , all the reaction steps from $\\mathrm{O}_{2}$ to $\\mathrm{OH^{-}}$ are downhill, implying a facile reaction. At $\\mathrm{U}=0.72\\mathrm{V}$ , the subtraction step from ${{\\cal O}^{*}}$ to $\\mathrm{OH^{*}}$ takes place, while the other subtractions remain downhill. This potential is consequently called the thermodynamic limiting potential. The limiting potentials are determined to be $0.42\\mathrm{V}$ and $0.36\\mathrm{V}$ for $\\mathrm{Mn/N\\mathrm{-}C}$ and $\\mathrm{Fe/N{-}C_{:}}$ respectively. Therefore, it suggests that $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ with a highly reactive ORR process under this condition, consistent with our experimental results. In addition, as shown in Fig. 5e, f at a $\\mathrm{\\pH}$ different from 0, the acid-corrected one does not significantly change the free energy diagram, while the alkaline-corrected one does. However, the pHcorrected operation would not change the rate-determining step of oxygen reduction reaction with the same calculation model. Accordingly, despite the numerical change of overpotential, the theoretical ORR trend would not change for different models as well, as a result of the same pH-corrected value. That is to say, the effect of electrolyte would not change the current conclusion: the $\\mathrm{Fe,Mn/N_{6}{-}1}$ model possess the best theoretical ORR activity with the smallest overpotential among all models. In addition, Supplementary Fig. 31 and Supplementary Table 15 show all possible active sites and their free energies of OER, all the reaction steps from $\\mathrm{OH^{-}}$ to $\\mathrm{O}_{2}$ are downhill, implying a facile reaction. The Fe, $\\mathrm{Mn/N_{6}}–1$ structure is also the active site of OER. \n\n![](images/213ec2e9230ececfa3c88cddb827ed1950573956b5efb91e93fd953818b91ea9.jpg) \nFig. 5 DFT calculations of the ORR activity on Fe,Mn/N–C and Fe/N–C catalysts. The optimized structure of (a) Fe/N–C and (c) Fe,Mn/N–C. Optimized atomic structures for the main process of an ORR: b Fe/N–C and d $\\mathsf{F e},M\\mathsf{n}/\\mathsf{N}-\\mathsf{C}$ . e The pathways for $\\mathsf{F e},M\\mathsf{n}/\\mathsf{N}-\\mathsf{C}$ are summarized at $\\mathsf{U}=0$ V, $0.72\\vee,$ and $1.23\\vee,$ respectively. f pH-corrected free energy diagram of the $\\mathsf{F e},M\\mathsf{n}/\\mathsf{N}_{6}{-}1$ \n\n# Discussion \n\nIn summary, in order to take insight into the genuine mechanism of high effective atomic-dispersed M–N–C materials on ORR, dual-metal atomically dispersed $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ and the single-atom $\\mathrm{Fe/N\\mathrm{-}C}$ and $\\mathrm{Mn/N-\\dot{C}}$ catalyst were precisely design and prepared as model object, which uncover that the spin-state formation of $3d$ orbitals in transition metal ions is an important factor for optimizing the ORR activity. Both electron configuration features and theoretical calculation results demonstrate that the adjacent atomically dispersed $\\mathrm{{Mn-N}}$ moieties can effectively activate the $\\mathrm{Fe}^{\\mathrm{III}}$ sites and permits $\\mathrm{Fe}^{\\mathrm{III}}$ in $\\mathrm{FeN_{4}}$ to achieve the ideal one eg electron $(\\mathrm{t}_{2\\mathrm{g}}4\\mathrm{e}_{\\mathrm{g}}1)$ filling, which can penetrate the antibonding $\\pi-$ orbital of oxygen easily, allowing the excellent ORR performances of $\\mathrm{Fe,Mn/N-C}$ in both alkaline and acidic media $\\mathrm{(E}_{1/2}$ are $0.928\\mathrm{V}$ in $0.1\\mathrm{M}\\mathrm{\\KOH}$ , and $0.804\\mathrm{V}$ in $0.1\\mathrm{M}\\mathrm{\\HClO_{4}};$ . DFT theoretical calculations further confirms that the electronic structure-adjusted $\\mathrm{Fe,Mn/N-C}$ and the oxygen intermediate have proper bond length and binding energy, which improves the reaction kinetics of ORR. As practical applications, $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ was successfully incorporated as an effective air cathode for a rechargeable flexible $Z\\mathrm{n}$ –air battery device with long-term work stability. This work opens up new opportunities for optimizing noble-metal-free catalysts to achieve high-efficiency and stable catalysts towards fuel cells, metal–air batteries, and other renewable energy systems. \n\n# Method \n\nSynthesis of Fe,Mn/N–C. $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ was synthesized via a soft-template pyrolysis method. Typically, $_{5\\mathrm{g}}$ dicyandiamide, $2\\mathrm{mL}$ of phytic acid, $5\\mathrm{mg}$ Iron phthalocyanine, and $5\\upmu\\mathrm{L}50\\%$ Manganese nitrate water solution were dissolved in $40~\\mathrm{mL}$ of water under stirring and dried in an oven at $80^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . The obtained solid powder was placed in a tubular carbonization furnace and carbonized at $900^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ under Ar gas conditions at a heating rate of $10^{\\circ}\\mathrm{C}\\ \\operatorname*{min}^{-1}$ . The obtained sampled is named $\\mathrm{Fe,Mn/N{\\mathrm{-C}}}$ . \n\nSynthesis of Fe/N–C and Mn/N–C. Fe/N–C and $\\mathrm{Mn/N-C}$ were prepared using a similar process to that of $\\mathrm{Fe,Mn/N-C,}$ except for the use of Iron phthalocyanine and $50\\%$ Manganese nitrate water solution, respectively. \n\nCharacterizations. The morphology of the samples was characterized by transmission electron microscope (TEM, FEI Tecnai G220) with an accelerating voltage of $200\\mathrm{kV}$ and field-emission scanning electron microscope (FE-SEM, JEORJSM6700F). The HAADFSTEM images were obtained by JEOL JEM-ARM200F at an accelerating voltage of $200\\mathrm{kV}$ . The crystal phases present in each sample were identified using powder X-ray diffraction(XRD) patterns were recorded on a $\\mathrm{Y}$ - 2000X-ray Diffractometer with copper Kα radiation $(\\lambda=1.5406\\mathrm{\\AA})$ ) at $40\\mathrm{kV}$ , $40\\mathrm{mA}$ . The X-ray photoelectron spectroscopy (XPS) measurements were performed with an ESCA LAB 250 spectrometer on a focused monochromatic Al Kαline $\\mathrm{(1486.6eV)}$ ) X-ray beam with a diameter of $200\\upmu\\mathrm{m}$ . The Raman measurements were taken on a Renishaw spectrometer at $532\\mathrm{nm}$ on a Renishaw Microscope System RM2000. The $\\Nu_{2}$ adsorption/desorption curve was carried out by BET measurements using a Micromeritics ASAP 2020 surface area analyzer. The Fe and Mn K-edge X-ray absorption near edgestructure (XANES) and the extended X-ray absorption fine structure (EXAFS) were investigated at the SXRMB beamline at the Canadian Light Source. References, such as Fe and Mn foils, are used to calibrate the beamlie energy and for comparison to samples. Fluorescence detection was performed using a 7-element Si drift detector for samples and the total electron yield was used for measurement of samples with high concentration, such as references. The EXAFS raw data were then background-subtracted, normalized and Fourier transformed by the standard procedures with the IFEFFIT package. The Mössbauer measurements were performed using a conventional spectrometer (Germany, Wissel MS-500) in transmission geometry with constant acceleration mode. A 57Co(Rh) source with activity of $25\\mathrm{{mCi}}$ was used. The 5 velocity calibration was done with a room temperature α-Fe absorber. The spectra were fitted by the software Recoil using Lorentzian Site Analysis. \n\nThe Fe K-edge theoretical XANES calculations were carried out with the FDMNES code in the framework of real-space full multiple-scattering (FMS) scheme using Muffin-tin approximation for the potential. The energy-dependent exchange-correlation potential was calculated in the real Hedin–Lundqvist scheme, and then the spectra convoluted using a Lorentzian function with an energydependent width to account for the broadening due both to the core–hole width and to the final state width. \n\nElectrocatalytic measurement. Electrochemical experiments were conducted on a CHI760E electrochemical workstation (CH Instrument Co., USA). CV, RDE, and RRDE measurements (Pine Research Instrument, USA) were conducted using a standard three-electrode system. All the measurements were carried out at room temperature. For the preparation of working electrode, $2\\mathrm{mg}$ of catalyst was dispersed in $1\\mathrm{mL}$ mixture of ethanol and $5\\%$ Nafion $\\mathbf{\\dot{v}}\\mathbf{:v}=200{:}1\\$ ) under sonication for $^{\\textrm{1h}}$ to form a homogeneous catalyst ink. Then $10\\upmu\\mathrm{L}$ of this catalyst ink was loaded onto a glassy carbon rotating disk electrode with the diameter of $5\\mathrm{mm}$ , resulting in the catalyst loading of $\\bar{0.1}\\mathrm{mg}\\mathrm{cm}^{-2}$ , followed by drying at room temperature. \n\nFor the ORR at an RDE, the working electrode was scanned cathodically at a rate of $5\\mathrm{mV}\\mathrm{s}^{-1}$ with varying rotating speed from 400 to $2250\\mathrm{rpm}$ in $\\mathrm{O}_{2}$ -saturated $0.1\\mathrm{{M}}$ KOH aqueous solution. The electron transfer number per oxygen molecule for oxygen reduction can be determined on the basis of the Koutechy–Levich equation (ref): \n\n$$\n{\\frac{1}{J}}={\\frac{1}{J_{\\mathrm{L}}}}+{\\frac{1}{J_{\\mathrm{k}}}}={\\frac{1}{B\\omega^{0.5}}}+{\\frac{1}{J_{\\mathrm{k}}}}\n$$ \n\n$$\n\\mathrm{B}=0.62n F C_{0}(D_{0})^{2/3}\\nu^{-1/6}\n$$ \n\n$$\nJ_{\\mathrm{k}}=n F k C_{\\mathrm{0}}\n$$ \n\nWhere $J$ is the measured current density and is the electrode rotating rate $(\\mathrm{rad}s^{-1})$ . B is determined from the slope of the Koutechy–Levich (K-L) plot based on Levich equation. $J_{\\mathrm{L}}$ and $J_{\\mathrm{K}}$ are the diffusion- and kinetic-limiting current densities, $n$ is the transferred electron number, $F$ is the Faraday constant $(F\\mathrm{=}96485\\mathrm{Cmol^{-1}}$ ), $C_{0}$ is the $\\mathrm{O}_{2}$ concentration in the electrolyte $(C_{0}=1.\\dot{2}6\\times10^{-6}\\mathrm{~n~}$ ol $c\\mathrm{m}^{-3}$ ), $D_{0}$ is the diffusion coefficient of $\\mathrm{O}_{2}$ $(D_{0}{=}1.93\\times10^{-5}~\\mathrm{cm^{2}}~s^{-1})$ , and $\\nu$ is the kinetic viscosity $(\\nu=0.01009\\mathrm{cm}^{2}s^{-1}.$ ). The constant 0.62 is adopted when the rotation speed is expressed in rad $\\mathbf{s}^{-1}$ . \n\nFor the RRDE measurements, the disk electrode was scanned cathodically at a rate of $10\\mathrm{mV}\\ \\mathrm{s}^{-1}$ and the ring potential was kept at $1.5\\mathrm{V}$ versus RHE. The peroxide percentage and the electron transfer number (n) were determined by the following equations (ref): \n\n$$\n\\mathrm{HO}_{2}^{-}=200\\times\\frac{I_{\\mathrm{R}}/N}{I_{\\mathrm{D}}+I_{\\mathrm{R}}/N}\n$$ \n\n$$\n\\mathrm{n}=4\\times{\\frac{I_{\\mathrm{D}}}{I_{\\mathrm{D}}+I_{\\mathrm{R}}/N}}\n$$ \n\nwhere $I_{\\mathrm{d}}$ is disk current, Ir is ring current, and $N$ is current collection efficiency of the Pt ring. $N$ was determined to be 0.40. \n\n$_{A l l}$ -solid-state $Z n$ –air battery assembly. A polished zinc foil $\\cdot0.05\\mathrm{mm}$ thickness) was used as anode. The gel polymer electrolyte was prepared as follow: polyvinyl alcohol (PVA, ${5}\\mathrm{g})$ was dissolved in $50~\\mathrm{mL}$ was added 18 M KOH (5 mL) at $95^{\\circ}\\mathrm{C}$ to form a homogeneous viscous solution, followed by casting on a glass disk to form a thin polymer film (thickness about $2\\mathrm{mm}$ ). The film was then freezed in a freezer at $-20^{\\circ}\\mathrm{C}$ about $^{2\\mathrm{h}}$ , and then keep at $0^{\\circ}\\mathrm{C}$ temperature about $^{4\\mathrm{h}}$ . The film was thawed for $^{12\\mathrm{h}}$ before used. Then, the as-prepared $\\mathrm{Fe,Mn/N-C}$ film and zinc foil were placed on the two sides of PVA gel, followed by pressed Ni foam as current collector. The components were firmly pressed together by roll-pressing. No inert atmosphere or glove-box is required for the packaging. \n\nZinc–air battery tests. The catalyst ink recipe consists of $5.0\\mathrm{mg}$ catalyst dispersed in $480\\upmu\\mathrm{L}$ of DI water/isopropyl alcohol $(\\mathrm{v}/\\mathrm{v}{\\sim}3{:}7)/20\\upmu\\mathrm{L}$ Nafion $(5\\mathrm{wt.\\%})$ solution. For the Zn–air battery test, the air electrode was prepared by uniformly coating the asprepared catalyst ink onto carbon paper then drying it at $80^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . The mass loading was $0.{\\dot{5}}\\operatorname*{mg}{\\mathsf{c m}}^{-2}$ unless otherwise noted. A $\\dot{Z}\\mathrm{n}$ plate was used as the anode and catalysis loaded on carbon paper are used as cathodes. Both electrodes were assembled into a home-made $Z\\mathrm{n}$ –air battery, and $6\\mathrm{M}$ KOH aqueous solutions was used as the electrolyte28. All $Z\\mathrm{n}\\cdot$ –air batteries were evaluated under ambient \n\nconditions. The polarization curves were recorded by linear sweep voltammetry $\\zeta\\mathrm{m}\\mathrm{V}\\ s^{-1}$ , at room temperature) on a CHI 760D electrochemical platform. \n\nComputation methods. First-Principles calculations were carried out within the density functional theory framework. The projector-augmented wave (PAW) method and the generalized gradient approximation (GGA) for the exchangecorrelation energy functional, as implemented in the Vienna ab initio simulation package (VASP) were used. The GGA calculation was performed with the Perdew–Burke–Ernzerhof (PBE) exchange-correlation potential. A plane-wave cutoff energy of $400\\mathrm{eV}$ was used. All atoms were fully relaxed with a tolerance in total energy of $0.1\\mathrm{mV}$ , and the forces on each atom were less than $0.01\\mathrm{eV}/\\mathring{\\mathrm{A}}$ All calculations were spin-polarized. \n\nA 6x6 graphene supercell $(14.807\\mathrm{x}14.807\\mathring\\mathrm{A}$ ) with $12\\mathrm{\\AA}$ vacuum layer was first constructed, and then Fe (or Mn)-N4 structure was simulated based on this model. Fe and Mn co-doped structure was then constructed. Three co-doped type was considered. A $4\\times4~\\mathrm{K}$ -points was used in all these calculations. \n\nThe ORR performed on Fe or Mn site was calculated by the following theory. The four-electron pathway by which the ORR occurs under base condition are generally reported to proceed according to the following steps: \n\n$$\n\\mathrm{O}_{2}(\\mathbf{g})+\\mathrm{\\Omega}^{*}\\Rightarrow\\mathrm{O}_{2}^{*}\n$$ \n\n$$\n\\mathrm{O}_{2}^{*}+\\mathrm{H}_{2}\\mathrm{O}(l)+e^{-}\\Rightarrow\\mathrm{OOH}^{*}+\\mathrm{OH}^{-}\n$$ \n\n$$\n\\mathrm{OOH}^{*}+e^{-}\\Rightarrow\\mathrm{O}^{*}+\\mathrm{OH}^{-}\n$$ \n\n$$\n\\mathrm{O}^{*}+\\mathrm{H}_{2}\\mathrm{O}(l)+e^{-}\\Rightarrow\\mathrm{OH}^{*}+\\mathrm{OH}^{-}\n$$ \n\n$$\n\\mathrm{OH}^{*}+e^{-}\\Rightarrow\\mathrm{OH}^{-}+^{*}\n$$ \n\nwhere $*$ represents an active site on the corresponding surface. \n\nThe adsorption energy $(\\Delta\\mathrm{E_{ads}})$ for ORR was calculated as: \n\n$$\nE_{\\mathrm{ads}}=E_{\\mathrm{substrate+adsorbate}}-E_{\\mathrm{substrate}}-E_{\\mathrm{adsorbate}}\n$$ \n\nThe adsorption free energy $\\langle\\Delta G_{\\mathrm{ads}}\\rangle$ is obtained by \n\n$$\n\\Delta G_{\\mathrm{ads}}=\\Delta E+\\Delta Z P E-T\\Delta S+\\Delta G_{\\mathrm{U}}+\\Delta G_{\\mathrm{pH}}\n$$ \n\nwhere $\\Delta E$ is the energy difference of reactants and products, obtained from DFT calculations; ΔZPE and $\\Delta{\\sf S}$ are the contributions to the free energy from the zeropoint vibration energy and entropy, respectively. $T$ is the temperature (300 K). $\\Delta G_{U}=-e U$ here $U$ is the potential at the electrode and $e$ is the transferred charge. $\\Delta G_{\\mathrm{pH}}$ is the correction of the $\\mathrm{H^{+}}$ free energy. The free energy of $\\mathrm{H^{+}}$ ions has been corrected by the concentration dependence of the entropy: \n\n$$\nG(\\mathrm{pH})=-k T\\ln\\left[H^{+}\\right]=k T\\ln10^{*}\\mathrm{pH}\n$$ \n\n(0.059526 for 0.1 M HClO ; 0.773844 for 0.1 M KOH). \n\n# Data availability \n\nThe data underlying Figs. 1–5, Supplementary Figs. 2–10, 12–29 and 31 are provided as a Source Data file. The other data support the findings of this study are available from the corresponding author upon request. Source data are provided with this paper. \n\nReceived: 4 June 2020; Accepted: 5 February 2021; Published online: 19 March 2021 \n\n# References \n\n1. Li, J. Z. et al. Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells. Nat. Catal. 1, 935–945 (2018). \n2. Li, B. Q. et al. Framework-porphyrin-derived single-atom bifunctional oxygen electrocatalysts and their applications in $Z\\mathrm{n}$ -air batteries. Adv. Mater. 31, e1900592 (2019). \n3. Wan, X. et al. Fe–N–C electrocatalyst with dense active sites and efficient mass transport for high-performance proton exchange membrane fuel cells. Nat. Catal. 2, 259–268 (2019). \n4. Zhao, L. et al. Cascade anchoring strategy for general mass production of high-loading single-atomic metal-nitrogen catalysts. Nat. Commun. 10, 1278 (2019). \n5. Zhang, J. et al. Supported dual-atom catalysts: preparation, characterization, and potential applications. Chin. J. Catal. 41, 783–798 (2020). \n6. Tian, S. et al. Carbon nitride supported Fe2 cluster catalysts with superior performance for alkene epoxidation. Nat. Commun. 9, 2353 (2018). \n7. Zhang, N. et al. High-density planar-like Fe2N6 structure catalyzes efficient oxygen reduction. Matter 3, 509–521 (2020). \n8. Chen, Y. et al. Isolated single iron atoms anchored on N-doped porous carbon as an efficient electrocatalyst for the oxygen reduction reaction. Angew. Chem. Int. Ed. 56, 6937–6941 (2017). \n9. Cheng, Y. et al. Supported single atoms as new class of catalysts for electrochemical reduction of carbon dioxide. Small Methods 3, 1800440 (2019). \n10. Gupta, S. et al. Quaternary FeCoNiMn-based nanocarbon electrocatalysts for bifunctional oxygen reduction and evolution: promotional role of Mn doping in stabilizing carbon. ACS Catal. 7, 8386–8393 (2017). \n11. Jiang, J. X. et al. Freestanding single-atom-layer Pd-based catalysts: oriented splitting of energy bands for unique stability and activity. Chem 6, 431–447 (2020). \n12. Li, J. et al. Ultrahigh-loading zinc single-atom catalyst for highly efficient oxygen reduction in both acidic and alkaline media. Angew. Chem. Int. Ed. 58, \n7035–7039 (2019). \n13. Mu, C. et al. Rational design of spinel cobalt vanadate oxide Co2VO4 for superior electrocatalysis. Adv. Mater. 32, e1907168 (2020). \n14. Shen, H. et al. Synergistic effects between atomically dispersed Fe-N-C and CS-C for the oxygen reduction reaction in acidic media. Angew. Chem. Int. Ed. \n56, 13800–13804 (2017). \n15. Wang, J. et al. Design of N-coordinated dual-metal sites: a stable and active Ptfree catalyst for acidic oxygen reduction reaction. J. Am. Chem. Soc. 139, \n17281–17284 (2017). \n16. Wang, X. X. et al. Nitrogen-coordinated single cobalt atom catalysts for oxygen reduction in proton exchange membrane fuel cells. Adv. Mater. 30, \n1706758 (2018). \n17. Xiao, M. et al. A single-atom iridium heterogeneous catalyst in oxygen reduction reaction. Angew. Chem. Int. Ed. 131, 9742–9747 (2019). \n18. Wang, H. et al. Durable and efficient hollow porous oxide spinel microspheres for oxygen reduction. Cell Press. Chem. 2, 337–348 (2018). \n19. Chen, R. R. et al. Antiferromagnetic inverse spinel oxide LiCoVO4 with spinpolarized channels for water oxidation. Adv. Mater. 32, 1907976 (2020). \n20. Li, J. et al. Boosted oxygen evolution reactivity by igniting double exchange interaction in spinel oxides. J. Am. Chem. Soc. 142, 50–54 (2020). \n21. Li, Z. et al. The marriage of the FeN4 moiety and MXene boosts oxygen reduction catalysis: Fe 3d electron delocalization matters. Adv. Mater. 30, \n1803220 (2018). \n22. Wang, X. T. et al. Redox-Inert $\\mathrm{Fe}3+$ ions in octahedral sites of Co-Fe spinel oxides with enhanced oxygen catalytic activity for rechargeable zinc-air batteries. Angew. Chem. Int. Ed. 58, 13291–13296 (2019). \n23. Ouyang, T. et al. Coupling magnetic single-crystal Co2Mo3O8 with ultrathin nitrogen-rich carbon layer for oxygen evolution reaction. Angew. Chem. Int. Ed. 59, 11948–11957 (2020). \n24. Shen, G. et al. Regulating the spin state of Fe(III) by atomically anchoring on ultrathin titanium dioxide for efficient oxygen evolution electrocatalysis. Angew. Chem. Int. Ed. 59, 2313–2317 (2020). \n25. Cheng, W. et al. Boosting defective carbon by anchoring well-defined atomically dispersed metal-N4 sites for ORR, OER, and Zn-air batteries. Appl. Catal., B 260, 118198 (2020). \n26. Al-Zoubi, T. et al. Preparation of nonprecious metal electrocatalysts for the reduction of oxygen using a low-temperature sacrificial metal. J. Am. Chem. Soc. 142, 5477–5481 (2020). \n27. Chen, L. L. et al. Synergistic effect between atomically dispersed Fe and Co metal sites for enhanced oxygen reduction reaction. J. Mater. Chem. A 8, \n4369–4375 (2020). \n28. Guo, Y. et al. Carbon nanosheets containing discrete Co-Nx-By-C active sites for efficient oxygen electrocatalysis and rechargeable Zn-air batteries. ACS Nano 12, 1894–1901 (2018). \n29. Guo, Y. et al. Co2P–CoN double active centers confined in N-doped carbon nanotube: heterostructural engineering for trifunctional catalysis toward HER, ORR, OER, and Zn–Air batteries driven water splitting. Adv. Funct. Mater. 28, \n1805641 (2018). \n30. Chen, Z. H. et al. Holey graphene-based nanocomposites for efficient electrochemical energy storage. Nano Energy 73, 104762 (2020). \n31. Han, X. et al. Generation of nanoparticle, atomic‐cluster, and single-atom cobalt catalysts from zeolitic imidazole frameworks by spatial isolation and their use in zinc–air batteries. Angew. Chem. Int. Ed. 131, 5413–5418 (2019). \n32. Jiao, L. et al. From metal-organic frameworks to single-atom Fe implanted Ndoped porous carbons: efficient oxygen reduction in both alkaline and acidic media. Angew. Chem. Int. Ed. 57, 8525–8529 (2018). \n33. Jiao, W. et al. Hollow palladium-gold nanochains with periodic concave structures as superior ORR electrocatalysts and highly efficient SERS substrates. Adv. Energy Mater. 33, 1904072 (2020). \n34. Lu, Z. et al. An isolated zinc-cobalt atomic pair for highly active and durable oxygen reduction. Angew. Chem. Int. Ed. 58, 2622–2626 (2019). \n35. Moon, G. H. et al. Highly active cobalt-based electrocatalysts with facile incorporation of dopants for the oxygen evolution reaction. Angew. Chem. Int. Ed. 58, 3491–3495 (2019). \n36. Pan, Y. et al. A bimetallic $\\mathrm{Zn/Fe}$ polyphthalocyanine-derived single-atom FeN4 catalytic site: a superior trifunctional catalyst for overall water splitting and $Z\\mathrm{n}$ -Air batteries. Angew. Chem. Int. Ed. 57, 8614–8618 (2018). \n37. Qiao, M. et al. Ni–Co bimetallic coordination effect for long lifetime rechargeable Zn–air battery. J. Energy Chem. 47, 146–154 (2020). \n38. Qiao, Y. et al. Sulfuration of an Fe-N-C catalyst containing FexC/Fe species to enhance the catalysis of oxygen reduction in acidic media and for use in flexible $Z\\mathrm{n}$ -air batteries. Adv. Mater. 30, e1804504 (2018). \n39. Shinde, S. S. et al. Unveiling dual-linkage 3D hexaiminobenzene metal–organic frameworks towards long-lasting advanced reversible Zn–air batteries. Energy Environ. Sci. 12, 727–738 (2019). \n40. Sun, S. et al. Switch of the rate-determining step of water oxidation by spinselected electron transfer in spinel oxides. Chem. Mater. 31, 8106–8111 (2019). \n41. Wan, X. et al. Synthesis and active site identification of Fe−N−C single-atom catalysts for the oxygen reduction reaction. Chem. Electro Chem. 6, 304–315 (2019). \n42. Wang, Y. et al. Self-adjusting activity induced by intrinsic reaction intermediate in Fe-N-C single-atom catalysts. J. Am. Chem. Soc. 141, 14115–14119 (2019). \n43. Zhang, W. et al. Merging single-atom-dispersed iron and graphitic carbon nitride to a joint electronic system for high-efficiency photocatalytic hydrogen evolution. Small 15, e1905166 (2019). \n44. Xiong, Y. et al. Metal-organic-framework-derived Co-Fe bimetallic oxygen reduction electrocatalysts for alkaline fuel cells. J. Am. Chem. Soc. 141, 10744–10750 (2019). \n45. Wang, X. T. et al. Surface reorganization on electrochemically-induced Zn-NiCo spinel oxides for enhanced oxygen electrocatalysis. Angew. Chem. Int. Ed. 59, 6492–6499 (2020). \n46. Xiao, M. et al. Engineering energy level of metal center: Ru single-atom site for efficient and durable oxygen reduction catalysis. J. Am. Chem. Soc. 141, 19800–19806 (2019). \n47. Xiao, F. et al. Nitrogen-coordinated single iron atom catalysts derived from metal organic frameworks for oxygen reduction reaction. Nano Energy 61, 60–68 (2019). \n48. Xu, N. et al. High-performing rechargeable/flexible zinc-air batteries by coordinated hierarchical Bi-metallic electrocatalyst and heterostructure anion exchange membrane. Nano Energy 65, 104021 (2019). \n49. Yang, Y. et al. Golden palladium zinc ordered intermetallics as oxygen reduction electrocatalysts. ACS Nano 13, 5968–5974 (2019). \n50. Zhang, G. et al. A general route via formamide condensation to prepare atomically dispersed metal–nitrogen–carbon electrocatalysts for energy technologies. Energy Environ. Sci. 12, 1317–1325 (2019). \n51. Zhang, H. et al. High-performance fuel cell cathodes exclusively containing atomically dispersed iron active sites. Energy Environ. Sci. 12, 2548–2558 (2019). \n52. Zhang, H. et al. Single atomic iron catalysts for oxygen reduction in acidic media: particle size control and thermal activation. J. Am. Chem. Soc. 139, 14143–14149 (2017). \n53. Zhang, L. et al. Coordination of atomic Co-Pt coupling species at carbon defects as active sites for oxygen reduction reaction. J. Am. Chem. Soc. 140, 10757–10763 (2018). \n54. Zhang, S. L. et al. Co–Fe alloy/N-doped carbon hollow spheres derived from dual metal–organic frameworks for enhanced electrocatalytic oxygen reduction. Small 15, 1805324 (2019). \n\n# Acknowledgements \n\nThis work was the financial support from the National Natural Science Foundation of China (Nos. 21875221, U1604123), the Youth Talent Support Program of High-Level Talents Special Support Plan in Henan Province (ZYQR201810148), Creative talents in the Education Department of Henan Province (19HASTIT039), National Key Research and Development Program of China (2016YFB0101202) and the project supported by State Key Laboratory of Advanced Technology for Materials Synthesis and Processing (Wuhan University of Technology) (2019-KF-13) \n\n# Author contributions \n\nZ.J.N. and Y.G.G conceived the project and idea. Y.G.G. carried out the experiment and process data with the help of C.W.Z. Z.J.W. and Y.P.F. carried out DFT calculations. H.Y.F. performed NEXFAS experiments and data fitting with the discussion with Z. J. N. X.X.Y. carried out the HAADF–STEM. Z.J.N. and Y.G.G. created figures and table of content. Z.J.N., M.S.C., and Y.G.G. discussed the results and commented on the paper. All authors participated in the formulation of the paper. Z.J.N. supervised the project. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-21919-5. \n\nCorrespondence and requests for materials should be addressed to S.M. or J.-N.Z. \n\nPeer review information Nature Communications thanks anonymous reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41586-021-03192-0", + "DOI": "10.1038/s41586-021-03192-0", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03192-0", + "Relative Dir Path": "mds/10.1038_s41586-021-03192-0", + "Article Title": "Tunable strongly coupled superconductivity in magic-angle twisted trilayer graphene", + "Authors": "Park, JM; Cao, Y; Watanabe, K; Taniguchi, T; Jarillo-Herrero, P", + "Source Title": "NATURE", + "Abstract": "Moire superlattices(1,2) have recently emerged as a platform upon which correlated physics and superconductivity can be studied with unprecedented tunability(3-6). Although correlated effects have been observed in several other moire system(7-17), magic-angle twisted bilayergraphene remains the only one in which robust superconductivity has been reproducibly measured(4-6). Here we realize a moire superconductor in magic-angle twisted trilayer graphene (MATTG)(18), which has better tunability of its electronic structure and superconducting properties than magic-angle twisted bilayer graphene. Measurements ofthe Hall effect and quantum oscillations as a function of density and electric field enable us to determine the tunable phase boundaries of the system in the normal metallic state. Zero-magnetic-field resistivity measurements reveal that the existence of superconductivity is intimately connected to the broken-symmetry phase that emerges from two carriers per moire unit cell. We find that the superconducting phase is suppressed and bounded at the Van Hove singularities that partially surround the broken-symmetry phase, which is difficult to reconcile with weak-coupling Bardeen-Cooper-Schrieffer theory. Moreover, the extensive in situ tunability of our system allows us to reach the ultrastrong-coupling regime, characterized by a Ginzburg-Landau coherence length that reaches the average inter-particle distance, and very large T-BKT/F, values, in excess of 0.1 (where T-BKT and T-F are the Berezinskii-Kosterlitz-Thouless transition and Fermi temperatures, respectively). These observations suggest that MATTG can be electrically tuned close to the crossover to a two-dimensional Bose-Einstein condensate. Our results establish a family of tunable moire superconductors that have the potential to revolutionize our fundamental understanding of and the applications for strongly coupled superconductivity.", + "Times Cited, WoS Core": 613, + "Times Cited, All Databases": 673, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000613628300002", + "Markdown": "# Article \n\n# Tunable strongly coupled superconductivity in magic-angle twisted trilayer graphene \n\nhttps://doi.org/10.1038/s41586-021-03192-0 \n\nReceived: 26 October 2020 \n\nAccepted: 5 January 2021 \n\nPublished online: 1 February 2021 Check for updates \n\nJeong Min Park1,4, Yuan Cao1,4 ✉, Kenji Watanabe2, Takashi Taniguchi3 & Pablo Jarillo-Herrero1 ✉ \n\nMoiré superlattices1,2 have recently emerged as a platform upon which correlated physics and superconductivity can be studied with unprecedented tunability3–6. Although correlated effects have been observed in several other moiré systems7–17, magic-angle twisted bilayer graphene remains the only one in which robust superconductivity has been reproducibly measured4–6. Here we realize a moiré superconductor in magic-angle twisted trilayer graphene (MATTG)18, which has better tunability of its electronic structure and superconducting properties than magic-angle twisted bilayer graphene. Measurements of the Hall effect and quantum oscillations as a function of density and electric field enable us to determine the tunable phase boundaries of the system in the normal metallic state. Zero-magnetic-field resistivity measurements reveal that the existence of superconductivity is intimately connected to the broken-symmetry phase that emerges from two carriers per moiré unit cell. We find that the superconducting phase is suppressed and bounded at the Van Hove singularities that partially surround the broken-symmetry phase, which is difficult to reconcile with weak-coupling Bardeen– Cooper–Schrieffer theory. Moreover, the extensive in situ tunability of our system allows us to reach the ultrastrong-coupling regime, characterized by a Ginzburg– Landau coherence length that reaches the average inter-particle distance, and very large $T_{\\mathrm{BKT}}/T_{\\mathrm{F}}$ values, in excess of 0.1 (where $T_{\\mathrm{BKT}}$ and $T_{\\mathrm{{F}}}$ are the Berezinskii–Kosterlitz– Thouless transition and Fermi temperatures, respectively). These observations suggest that MATTG can be electrically tuned close to the crossover to a two-dimensional Bose–Einstein condensate. Our results establish a family of tunable moiré superconductors that have the potential to revolutionize our fundamental understanding of and the applications for strongly coupled superconductivity. \n\nWhen two or more layers of two-dimensional (2D) materials are stacked together, a moiré superlattice with reduced electronic bandwidth can arise from a small twist angle or lattice mismatch between the layers. In such flat-band systems, electronic interactions have a dominant role, which has led to the observation of various correlated and topological phases3–17,19–23. The case of magic-angle twisted bilayer graphene (MATBG) has attracted particular attention because of the intriguing superconducting phase it hosts4–6. Although signatures of superconductivity have also been reported in other systems8,9,11,13,17,22,23, definitive evidence of superconductivity—encompassing the observation of zero resistance, sharply switching voltage–current (V–I) characteristics, and Josephson phase coherence—has only been reproducibly demonstrated in MATBG so far. \n\nIn this Article, we report the realization of ultrastrong-coupling superconductivity in a magic-angle system that consists of three adjacent graphene layers sequentially twisted by $\\theta$ and $-\\theta$ (Fig. 1a)18. Here we consider ultrastrong coupling to exist where $T_{\\mathrm{c}}/T_{\\mathrm{F}}{\\gtrsim}0.1$ , where $T_{\\mathrm{c}}$ is the critical temperature and $T_{\\mathrm{F}}{=}\\uppi\\hbar n^{*}/(m^{*}k_{\\mathrm{B}})$ is the Fermi temperature $(k_{\\mathrm{B}},$ Boltzmann constant; $\\hbar$ , reduced Planck constant; $m^{*}$ , measured effective mass). This moiré superconductor—magic-angle twisted trilayer graphene (MATTG)—exhibits a rich phase diagram and greater electric field tunability than MATBG. The latter enables us to explore the interplay between correlated states and superconductivity beyond MATBG. Figure 1b, c shows the calculated bandstructures of MATTG without and with an electric displacement field, $D$ (Methods and Extended Data Fig. 1). At zero $D$ , MATTG has a set of flat bands, as well as gapless Dirac bands18,24–26. The flat bands in MATTG can be mathematically reduced to MATBG-like bands with an effective twist angle of $\\theta/\\sqrt{2}\\approx\\theta/1.4$ , and hybridization with the Dirac bands is prohibited by the mirror symmetry18,25,26. This reduction leads to a larger magic angle in MATTG, $\\ensuremath{\\theta_{\\mathrm{{MATTG}}}}^{\\smash{\\sim}}\\approx1.6^{\\circ}$ . When the mirror symmetry is broken by the application of $D$ , the flat bands can hybridize with the Dirac bands (Fig. 1c), enabling us to control the bandwidth and interaction strength in the flat bands. \n\n![](images/14e68c2420b780f82b6484fe7633abc89ac2345c9260290fa98a6d38e07924f1.jpg) \nFig. 1 | Electronic structure and robust superconductivity in mirrorsymmetric MATTG. a, MATTG consists of three graphene monolayers stacked in a symmetric arrangement (by rotating with angles θ and −θ sequentially between the layers). b, c, Calculated bandstructure of MATTG at zero (b) and finite (c) perpendicular electric displacement field $\\vert D/\\varepsilon_{0}=0.2\\mathsf{V}\\mathsf{n m}^{-1}$ for valley K (bands for valley K′ can be obtained by time-reversal symmetry), showing flat bands and Dirac bands near the charge-neutrality point. The colour represents the mirror-symmetry character of the eigenstates, which varies from purple (symmetric) to orange (antisymmetric; see Methods). Finite D lifts the mirror symmetry and hybridizes the flat bands and Dirac bands. d, e, Magnetotransport data (derivative of the Hall resistance $R_{x y}$ with respect to B) of MATTG at $D/\\varepsilon_{0}{=}0\\vee\\mathsf{n m}^{-1}$ and $D/\\varepsilon_{\\scriptscriptstyle0}=0.54\\mathrm{V}\\mathrm{nm}^{-1}$ , respectively. $\\mathbf{A}\\mathbf{t}D{=}0$ , we observe extra Landau levels, demonstrating the presence of coexisting Dirac bands, which are lifted by the displacement field. f, Longitudinal resistance $R_{x x}$ and Hall conductivity $\\sigma_{x y}$ as a function of inverse magnetic field $1/B$ , at moiré filling factor \n$\\nu{\\lesssim}4$ as marked by the purple arrow above d. The quantization of $\\dot{\\sigma}_{x y}$ at 2, 6, $10,...,e^{2}/h$ (h, Planck constant) indicates the presence of the massless Dirac bands. g, Estimated chemical potential as a function of ν, extracted from the evolution of Dirac band Landau levels (see Methods), showing a pinning behaviour at all integer fillings. h, i, $R_{x x}$ versus T and ν showing the superconducting regions near $\\scriptstyle\\nu=-2$ and $\\nu{=}{+}2$ , at $\\scriptstyle D/{\\varepsilon_{0}}=-0.44\\lor\\mathfrak{n}\\mathfrak{m}^{-1}i$ nd $D/\\varepsilon_{0}{=}0.74\\mathrm{V}\\mathrm{nm}^{-1}$ , respectively. j, $V_{x x}–I$ curves as a function of temperature at optimal doping in the $v{=}{-}2-\\delta$ dome. The top-left inset shows a fit of $\\cdot_{R_{x x}}$ –T data with the Halperin–Nelson formula30 $R\\propto\\exp[-b/(T-T_{\\mathrm{BKT}})^{1/2}]$ , where $b$ and $T_{\\mathrm{BKT}}$ are fitting parameters, which gives $T_{\\mathrm{BKT}}{\\approx}2.25\\mathsf{K}$ . The bottom-right inset shows the $V_{x x}$ –I curves on a log–log scale and sampled at finer temperature increments, again between 0 and 3.6 K, and the dashed line denotes where its slope is approximately 3 $(V_{x x}\\propto P^{3})$ , indicating $T_{\\mathrm{BKT}}{\\approx}2.1{\\sf K}$ . k, l, Critical current versus magnetic field at $\\nu{=}{-}2.4$ (k) and $\\nu{=}+2.22$ (l), both at $D/\\varepsilon_{\\scriptscriptstyle0}=-0.44\\mathrm{V}\\mathrm{nm}^{-1}$ . In k, the critical current shows a long tail up to $400\\mathrm{mT},$ whereas l shows a clear Josephson interference pattern. \n\n# Robust superconductivity in MATTG \n\nWe have fabricated three MATTG devices, all of which exhibit robust superconductivity (Methods and Extended Data Fig. 2, 3). Here we focus on the device with a twist angle $\\theta=1.57\\pm0.02^{\\circ}.$ —that is, particularly close to $\\theta_{\\mathrm{MATTG}}$ . The coexistence of Dirac bands and flat bands in MATTG can be directly observed in the transport data under a perpendicular magnetic field $B$ (Fig. 1d, e). Resistive states at integer fillings of the superlattice, $\\nu{=}4n/n_{s}{=}{+}1,\\pm{2},+3,\\pm{4}$ appear as vertical features, regardless of $D$ , where $n$ is the carrier density and $n_{s}=8\\theta^{2}/(\\sqrt{3}a^{2})$ is the superlattice density $(a=0.246\\mathsf{n m}$ is the graphene lattice constant). At zero $D$ , we find an extra set of quantum oscillations that emanates from the charge-neutrality point (Fig. 1d), which vanishes when a moderate $D$ is applied (Fig. 1e). These observations are consistent with a coexisting dispersive band tunable by $D$ , as predicted by calculations (Fig. 1b, c). We further confirm the Dirac character of the dispersive band by measuring its quantum Hall sequence (Fig. 1f). By tracking the Dirac Landau levels, we estimate the chemical potentia $\\mu$ in the flat bands as a function of $\\nu$ (Methods). We find ‘pinning’ of the chemical potential near each integer $\\nu$ (Fig. 1g), indicating a cascade of phase transitions similar to that observed in MATBG27–29. We estimate the many-body bandwidth of the flat bands to be around 100 meV (40 meV on the hole side and 60 meV on the electron side), relatively large compared to the approximately 40–60 meV many-body bandwidth in MATBG27,29. \n\n![](images/fbab4962e2563fdf15fdb1598b7b86f3834dbc64bb4b259650496306c34368ea.jpg) \nFig. 2 | MATTG phase diagrams. a, b, $R_{x x}$ at $B{=}0\\mathsf T$ (a) and normalized Hall density $\\nu_{\\mathrm{H}}{=}4n_{\\mathrm{H}}/n_{\\mathrm{s}}$ at $B{=}\\pm1.5\\operatorname{T}$ (b), versus ν and $D$ . Data are taken at $T=70\\mathrm{mK}$ . Superconductivity is represented by bright blue regions in a. c, Schematic sketches of the three types of feature found in the Hall density in b, and denoted by ‘gap/Dirac’ (red), ‘reset’ (yellow), and ‘VHS’ (dark blue). The blue regions in c denote the superconducting phase as determined in a. The branches near $v=-2+\\delta$ at large $D$ and the regions at smal $D$ , all denoted by light blue, correspond to very weak superconductivity. The behaviour of $\\dot{\\nu}_{\\mathrm{H}}$ versus ν for each of these features is shown in d–f. d, At a ‘gap/Dirac’ feature, $\\nu_{\\mathrm{H}}$ changes linearly with ν while crossing zero. e, At a ‘reset’ feature, $\\nu_{\\mathsf{H}}$ rapidly drops to zero \nbut without changing sign (here shown for $\\nu{>}0)$ ). f, At a ‘VHS’ feature, $\\nu_{\\mathsf{H}}$ diverges and changes sign at a Van Hove singularity. In d–f, the colour shading represents the expected colour in b across each type of feature. g, h, Plots of $\\cdot_{R_{x x}}$ (purple) and the BKT transition temperature $T_{\\mathrm{BKT}}$ (brown; g), and effective mass $m^{*}$ as function of $\\nu({\\bf h})$ , taken at the displacement field indicated by the yellow dashed line in a, $\\mathsf{b}{:}D/\\varepsilon_{0}{=}0.64\\mathsf{V}\\mathsf{n m}^{-1}$ . $T_{\\mathrm{BKT}}$ approaches zero and $m^{*}$ shows a peak around the VHS, which is represented by the pink region. $m_{\\mathrm{e}}$ is the electron mass. In h, the dashed guidelines correspond to a logarithmic divergence in the DOS at the VHS, and the error bars correspond to a confidence interval of 0.9. \n\nWhen MATTG is doped near $\\nu=\\pm2$ , we find robust superconducting phases. Figure 1h, i shows the superconducting domes in the hole-doped (near $v=-2$ ) and electron-doped (near $\\nu=+2$ ) sides at optimal displacement fields. We find strong superconductivity with a $T_{\\mathrm{c}}^{50\\%}$ (see Methods section $^{\\cdot}T_{\\mathrm{c}}$ and coherence-length analysis’) of approximately $2.9\\mathsf{K}$ and approximately 1.4 K for the regions $v{=}{-}2-\\delta$ and $V=+2+\\delta$ respectively $(0<\\delta<1)$ , and weaker superconductivity with $T_{\\mathrm{c}}^{50\\%}{<}1\\mathsf{K}$ for the $v=-2+\\delta$ and $v{=}{+}2-\\delta$ regions. Figure 1j shows the longitudinal voltage–current $(V_{x x}–I)$ characteristics in the $\\scriptstyle\\nu=-2-\\delta$ dome as a function of $T_{\\perp}$ exhibiting clear BKT-transition behaviour, from which we extracted $T_{\\mathrm{BKT}}{\\approx}2.1\\mathsf{K}$ . Alternatively, the Halperin–Nelson fit30 of the longitudinal resistance $R_{x x}$ versus T (Fig. 1j, top-left inset) gives a consistent value of $T_{\\mathrm{BKT}}{\\approx}2.25\\mathsf{K}$ . The $V_{x x}$ –I curve at the lowest temperature shows a zero resistance plateau up to a critical current $I_{\\mathrm{c}}{\\approx}600\\mathrm{nA}$ , above which the system switches sharply to a resistive state. The sharp transitions and associated hysteresis (Extended Data Fig.  4) are characteristic of robust superconducting behaviour, which cannot be accounted for by alternative mechanisms, such as Joule heating31. To further confirm the superconductivity, we measure the critical current in the $\\nu=+2+\\delta$ dome, near its boundary with the resistive feature, as a function of perpendicular magnetic field $B$ . We find a clear Fraunhofer-like oscillation pattern (Fig. 1l), which can be explained by the interference between superconducting percolation paths separated by normal regions due to charge inhomogeneity, and constitutes a direct demonstration of Josephson phase coherence in MATTG. On the other hand, the $B$ -dependence of $I_{\\mathrm{c}}$ at optimal doping, near $v{=}{-}2-\\delta.$ , does not show a visible oscillatory behaviour, probably owing to the lack of normal islands in this strong superconducting regime (Fig. 1k). Instead, we find a long superconducting ‘tail’ that remains up to $400\\mathrm{mT}$ , suggesting a high critical magnetic field $B_{{\\mathrm c}2}$ at this density. \n\n![](images/0370d128c23ecb13502ed7f7a7eb9894a4911e260a3e3ab2efa04eeb7e86d928.jpg) \nFig. 3 | Ultrastrong-coupling superconductivity and proximity to the BCS– BEC crossover. a, Three-dimensional map of the BKT transition temperature $T_{\\mathrm{BKT}}$ versus ν and $D_{\\cdot}$ . The optimal $(\\nu_{\\mathrm{opt}},D_{\\mathrm{opt}}/\\varepsilon_{0})$ point corresponding to the maximum $T_{\\mathrm{BKT}}$ is $(-2.4,-0.44\\mathrm{V}\\mathrm{nm}^{-1})$ . b, c, Line cuts of $T_{\\mathrm{BKT}}$ and the extracted Ginzburg–Landau coherence length $\\xi_{\\mathrm{GL}}$ versus $\\nu$ (b), and $D$ (c), while the other variable is kept at the optimal value (white dashed lines in a). The data points for $\\xi_{\\mathrm{GL}}$ were extracted using $T_{\\mathrm{c}}^{40\\%}$ , and the error bars show the values extracted with $T_{\\mathrm{c}}^{30\\%}$ (top) and $T_{\\mathrm{c}}^{50\\%}$ (bottom), respectively (see Methods for details). The red dashed lines show the expected interparticle distance $d_{\\mathrm{particle}}=\\lvert n^{*}\\rvert^{-1/2}$ for the carrier density $n^{*}$ , which starts counting from $\\scriptstyle\\nu=-2$ , $n^{*}=(\\left||\\mathbf{v}|-2\\right|)n_{s}/4$ . \nThe Ginzburg–Landau coherence length approaches the interparticle distance around the optimal point in the phase diagram where $T_{\\mathrm{BKT}}$ is the highest. The background colour plot shows $R_{x x}$ versus T and $\\nu.$ d, e, Effective mass $m^{*}$ in units of $m_{\\mathrm{e}}$ (upper panel) and the ratio $T_{\\mathrm{BKT}}/T_{\\mathrm{F}}$ (lower panel) as a function of $\\mathbf{\\dot{\\gamma}}_{\\nu}(\\mathbf{d})$ and $D$ (e; same line cuts as in b, c). The Fermi temperature is calculated from $T_{\\mathrm{F}}{=}\\uppi\\hbar^{2}n^{*}/(m^{*}k_{\\mathrm{B}})$ . Around optimal doping and displacement field, $T_{\\mathrm{BKT}}/T_{\\mathrm{F}}$ approaches the blue dashed line, which represents the upper bound of $T_{\\mathrm{{BKT}}}/T_{\\mathrm{F}}$ in the BCS–BEC crossover in two dimensions, the value of which is 0.125. The error bars in d, e correspond to a confidence interval of 0.9. \n\n# Tunable phase boundaries \n\nMATTG exhibits a rich phase diagram as a function of $\\nu,D_{\\cdot}$ , T and $B$ . In particular, the prominent $D$ dependence enables us to correlate the evolution of the superconducting phase boundaries with normal-state magnetotransport features, which can provide important insight into the nature of the superconductivity. Figure 2a shows $R_{x x}$ as a function of $\\nu$ and $D$ . Various resistive features can be seen, especially at $\\boldsymbol{\\nu}=+1$ , $\\pm2,+3,\\pm4$ , some of which have substantial $D$ dependence (Extended Data Fig. 5). In addition, there are zero resistance regions, shown in bright blue, denoting superconductivity. These superconducting regions are most prominent between $|\\nu|=2$ and $|\\nu|=3$ , though they can also extend into neighbouring regions. The extended regions at small $D$ could be due to the interplay with the Dirac bands. Figure 2b shows the normalized Hall density $\\nu_{\\mathrm{H}}{=}4n_{\\mathrm{H}}/n_{\\mathrm{s}},$ where $n_{\\mathrm{H}}{=}{-}[e(\\mathrm{d}R_{x y}/\\mathrm{d}B)]^{-1}$ (e, electron charge) and $R_{x y}$ is the Hall resistance (Extended Data Fig. 6). In MATTG, the Hall density exhibits three main types of behaviour, characterized by a different dependence on ν: ‘gap/Dirac’, ‘reset’ and ‘VHS’ (Van Hove singularity), as illustrated in Fig. 2d–f. The trajectories of these features are summarized in Fig. 2c, along with the phase boundaries of superconductivity. The first type, ‘gap/Dirac’, denotes a continuous zero crossing of $\\dot{\\nu}_{\\mathrm{H}}$ as ν is increased (Fig. 2d). This behaviour indicates that the Fermi level crosses a gap or Dirac-like point. The second type is a ‘reset’ to zero, that is, $\\nu_{\\mathrm{H}}$ drops/rises suddenly close to zero but it does not change sign, and it starts rising/dropping again in the same direction as it was before the ‘reset’ (see Fig. 2e for electron side). It is typically observed across certain integer filling factors in MATBG3,4, associated with the Coulomb-induced phase transitions27–29, and also occurs in MATTG near zero and small displacement fields. Both types of features occur only close to integer fillings $\\nu=0,\\pm1,\\pm2,$ … By contrast, the third type of feature exhibits a divergent $\\nu_{\\mathrm{H}}$ with a zero crossing (Fig. 2f), which is associated with saddle-points on the Fermi surface known as Van Hove singularities. At a VHS, $\\nu_{\\mathrm{H}}$ ceases to represent the number of carriers in the system, as the electrons no longer follow a closed semi-classical orbit. In two dimensions, the density of states (DOS) at a VHS diverges and, in general, there is no restriction on the density at which a VHS occurs. \n\n![](images/e4d0cef0ccfc185979344a738a1324c30dc14d3edc7f700c2758ed9b891fa99f.jpg) \nFig. 4 | Connection between superconductivity and carriers emerging from the $|\\pmb{\\nu}|=2$ phase. a, b, Landau fan diagrams $[R_{x x}$ versus ν and B, upper panel) and their Landau level designations (lower panel) in the hole-doped side $(\\nu<0)$ for large $D\\left(D/\\varepsilon_{0}=-0.64\\mathrm{V}\\mathrm{nm}^{-1}\\right)$ , and small ${\\sf O}(D/\\varepsilon_{0}=0{\\sf V}{\\sf n m}^{-1})$ , respectively (see Extended Data Fig. 9 for intermediate $D_{\\iota}^{\\dagger}$ . c–e, Schematic summaries of the carrier types and numbers corresponding to large, intermediate and small $D$ , respectively, with superconducting regions denoted by purple shades. f, g, Landau fan diagrams and designations in the electron-doped side $(\\nu{>}0)$ at $D/\\varepsilon_{0}{=}{-}0.77\\vee\\mathrm{nm^{-1}}(\\mathbf{f})$ and $D/\\varepsilon_{0}{=}0\\vee\\mathsf{n m}^{-1},$ (g; see Extended Data Fig. 9 for an intermediate $D$ ). The inset in f shows the derivative $\\mathrm{d}R_{x x}/\\mathrm{d}B$ of the region denoted by the pink dashed rectangle in the upper panel. These Landau fans indicate that at small $D$ , the carriers are always hole-like (electron-like) on the $-4<\\nu<0(0<\\nu<4)$ side, and ‘resets’ occur at $\\nu=+1,\\pm2,\\pm3$ , similar to previous \n\nWe find experimentally that they evolve and can merge with the other two types of features as $D$ is varied. \n\nWe find that superconductivity emanating from $\\nu=\\pm2$ is consistently suppressed upon reaching VHS—that is, the superconductivity is ‘bounded’ by the VHS contours, as well as at the ‘resets’ near $\\nu=\\pm3$ . Figure 2g shows $R_{x x}$ versus ν at $D/\\varepsilon_{0}{=}0.64\\mathrm{V}\\mathsf{n m}^{-1}(\\varepsilon_{0}$ , vacuum permittivity; yellow dashed line in Fig. 2a), and on the same plot $T_{\\mathrm{BKT}}$ versus ν. $T_{\\mathrm{BKT}}$ falls to 0 K, and $R_{x x}$ begins rising, as the VHS around $\\nu=-2.9$ (denoted by pink shading) is reached. To further confirm the occurrence of the VHS, we investigate the effective mass $m^{*}$ versus ν, measured through quantum oscillations, at the same $D$ (Methods and Extended Data Fig. 7). It exhibits a divergent trend near the VHS, as expected in a 2D system. We note that the Hall density signature of the VHS bounding the $\\nu{=}{-}2{+}\\delta$ superconducting dome appearing at large $D$ , which has a lower $T_{\\mathrm{c}}$ than in the $v{=}{-}2-\\delta$ dome, requires a smaller magnetic field of $B{\\approx}0.1\\ –0.3\\operatorname{T}$ to reveal it (Extended Data Fig. 6). \n\nThe observation that superconductivity vanishes right at the VHS is highly unusual. In Bardeen–Cooper–Schrieffer (BCS) superconductors, the order parameter and related quantities $\\langle T_{\\mathrm{c}},I_{\\mathrm{c}},$ and so on) are generally positively correlated with the DOS of the parent state at the Fermi level. This trend is directly seen in the weak-coupling BCS theory formula for $T_{\\mathrm{c}}\\propto\\exp(-1/\\lambda N)$ (where $N$ is the DOS at the Fermi level), regardless of whether the coupling λ originates from electron–phonon coupling, spin fluctuations, or other mechanisms. In particular, a divergent DOS at a VHS has been predicted to induce or enhance the superconducting order in various systems32–34. Our observation of the opposite trend therefore indicates that the superconductivity in studies in MATBG. On the other hand, at large $D$ , carriers with opposite polarity (that is, electron-like at $-4<\\nu<0$ or hole-like at $0<\\nu<4$ ) dominate near $\\nu{\\gtrsim}-4$ , $-2\\left(\\nu\\lesssim+2,+4\\right)$ . The VHSs are responsible for the transitions between carriers with different polarities. The ‘resets’ near $|\\nu|=3$ are no longer present, and the outward-facing Landau fans from $|\\nu|=2$ directly meet the inward-facing fans from $|\\nu|=4$ at VHSs. We find that superconductivity is only found in the regions where the carriers originate from the $\\nu=\\pm2$ states, that is, when the Landau fan at that density converges towards $\\nu=\\pm2$ . The large-ν regions in c and f are limited by the maximum gate value we can apply before leakage, but the trend of the carrier dynamics can be deduced from the Hall density map in Fig. 2b. (We note that at small $D$ there are slight shifts in ν, which may be attributed to interplay with the Dirac bands.). \n\nMATTG is unlikely to be consistent with conventional weak-coupling BCS theory. We emphasize that this clear demonstration of a separation between the strength of the superconductivity and the Fermi surface topology is accessible only in MATTG at large $D$ , where a VHS can be tuned near the vicinity of the superconducting region. This does not occur at small $D$ in MATTG, and this tunability is absent in MATBG. \n\n# Ultrastrong-coupling superconductivity \n\nThe wide tunability of the MATTG system enables us to investigate in detail the coupling strength of the superconducting state by measuring the Ginzburg–Landau coherence length $\\xi_{\\mathrm{GL}}$ as a function of various parameters. We first obtain a map of $T_{\\mathrm{BKT}}$ in the entire phase space of $\\dot{\\nu}$ and $D$ to understand the evolution of the superconductivity (Fig. 3a). The zero-temperature superconducting coherence length $\\xi_{\\mathrm{GL}}(0)$ can be determined by measuring the critical temperatures $T_{\\mathrm{c}}$ at different perpendicular magnetic fields $B$ (Methods and Extended Data Fig. 8). We perform this analysis as a function of either ν or $D$ , while the other parameter is kept fixed at the optimal point, and the extracted $\\xi_{\\mathrm{GL}}$ values are overlaid on the corresponding $T_{\\mathrm{BKT}}$ plots in Fig. 3b, c. We find that MATTG has an extremely short coherence length, reaching down to $\\xi_{\\mathrm{GL}}(0)\\approx12$ nm near the optimal point, which is comparable to the interparticle distance. For comparison, in Fig. 3b, c we show the expected mean interparticle distance $d_{\\mathrm{particle}}=\\vert n^{*}\\vert^{-1/2}$ , where $n^{*}=(||\\mathbf{v}|-2|)n_{s}/4$ is the carrier density counting from $\\nu=-2$ (as suggested by both quantum oscillations and Hall density measurements, see Fig. 4 and Extended Data Fig. 6). In the ‘underdoped’ region of the \n\n# Article \n\nsuperconducting dome $(-2.4<\\nu<-2.15)$ , we find that the coherence length is bounded by the interparticle distance. \n\nThese observations constitute a first indication that MATTG is a superconductor that can be tuned close to the BCS–BEC (Bose– Einstein condensate) crossover. The saturation of $\\cdot\\xi_{\\mathrm{GL}}$ at the interparticle distance suggests that a large fraction of the available carriers are condensed into Cooper pairs, that is, $n_{\\mathrm{sf}}/n^{*}\\lesssim1,$ where $n_{\\mathrm{sf}}$ is the superfluid density, in contrast to conventional superconductors where only a tiny fraction of electrons are condensed. This difference can be captured in the framework of the BCS–BEC crossover, as the system is tuned from the weak coupling regime $(T_{\\mathrm{c}}/T_{\\mathrm{F}}{\\ll}0.1)$ to the ultrastrong-coupling regime $(T_{\\mathrm{c}}/T_{\\mathrm{F}}{\\gtrsim}0.1)$ . To estimate how close MATTG near its optimal doping is to the BCS–BEC crossover, we measure the ratio $T_{\\mathrm{BKT}}/T_{\\mathrm{F}}$ as a function of ν and $D$ (Fig. 3d, e). As true long-range order does not exist in two dimensions, in both the BCS and BEC limits the superfluid undergoes a BKT transition at $^{35}T_{\\mathrm{{BKT}}}\\propto n_{\\mathrm{{sf}}}/m^{*}$ . We can therefore use the ratio $T_{\\mathrm{BKT}}/T_{\\mathrm{F}}$ to quantify the superfluid fraction $n_{\\mathrm{sf}}/n^{*}$ in both regimes. In the BCS–BEC crossover in two dimensions, $T_{\\mathrm{BKT}}/T_{\\mathrm{F}}$ has an upper bound of36 0.125. Our experimentally extracted $T_{\\mathrm{BKT}}/T_{\\mathrm{F}}$ reaches values in excess of 0.1, with maximum values close to 0.125. This indicates that the superconductivity in MATTG is probably of strong-coupling nature, and possibly close to the BCS–BEC crossover. For comparison with other strong 2D superconductors, $T_{\\mathrm{{BKT}}}/T_{\\mathrm{{F}}}{\\approx}0.05\\left(T_{\\mathrm{{c}}}/T_{\\mathrm{{F}}}{\\approx}0.08\\right)$ in MATBG4, and $T_{\\mathrm{c}}/T_{\\mathrm{F}}{\\approx}0.04$ in $\\mathsf{L i}_{x}\\mathsf{H f N C l}^{37}$ . Another strong 2D superconductor is monolayer FeSe grown on STO, for which very high $T_{\\mathrm{c}}/T_{\\mathrm{F}}$ values, of the order of approximately 0.1, have been reported38, though transport data show substantially broad $R{-}T$ transitions, which may indicate a lower $T_{\\mathrm{{BKT}}}/T_{\\mathrm{F}}$ value38. \n\n# Superconductivity emerges from the $|\\pmb{\\nu}|=2$ phase \n\nTo gain further insight into the MATTG superconducting phase diagram, we analyse the type of carriers involved in the superconductivity. Figure 4a, b shows quantum oscillations measurements in the $-4<\\nu<0$ range, at large and small displacement field, respectively. The corresponding data for electrons—that is, in the $0<\\nu<+4$ range—are shown in Fig. 4f, g. At small $D$ (including zero) there is a ‘reset’ at $|\\nu|=2$ , which manifests as an outward-facing (away from $\\scriptstyle{\\boldsymbol{v}}=0$ ) Landau fan originating from $|\\nu|=2$ (Fig. 4b, g). These fans end near $|\\nu|=3$ , where new outward fans start, consistent with the ‘resets’ occurring there (Fig. 2b, c), which indicates phase transitions to a different broken-symmetry-phase ground state27–29. At these small $D$ values, the superconductivity is restricted to the regions between $|\\nu|=2$ and $|\\nu|=3$ (Fig. 2a–c), a behaviour summarized in Fig. 4e. \n\nAt large $D$ , the phase diagram changes substantially (Fig. 2), where superconductivity is now bounded by VHSs in some regions, and extra superconducting branches appear, particularly strong for $\\scriptstyle\\nu=+2-\\delta$ (Fig. 3a). These features are correlated with inward-facing (towards charge neutrality) fans that start to develop at $|\\nu|=2$ (Fig. 4a, f), which meet the fans from $\\scriptstyle\\nu=0$ (hole side) or $\\scriptstyle\\nu=+1$ (electron side) at a VHS. This indicates that the states that result from the removal of electrons (holes) from $\\nu{=}{+}2\\left(\\nu{=}{-}2\\right)$ remain adiabatically connected to the ground state at $|\\nu|=2$ , until the VHS is reached. This is different from the small- $D$ case, where the system immediately goes through a phase transition across the ‘resets’. The data at intermediate $D$ are shown in Extended Data Fig. 9. The evolution between the ‘reset’-type features and ‘VHS’-type features might be related to a change in the bandwidth and band topology as the Dirac bands start to hybridize with the flat bands (Fig. 1b, c). As one possibility, it has been suggested that the positions of the VHSs in the single-particle flat bands help determine the occurrence of a flavour-symmetry-breaking phase transition, as well as the filling factor at which they occur39. When symmetry breaking occurs right at integer fillings, it appears as a ‘reset’; when it occurs slightly before the integer fillings, it appears as a ‘VHS’ feature in the Hall density at the phase transition, followed by a ‘gap/Dirac’ feature at the integer filling39. \n\nFor both cases, we find the superconductivity to be still bounded within the regions where the carriers are connected to the $|\\nu|=2$ ground state, as summarized in Fig. 4c, d. These observations indicate that the many-body ground state emerging from the broken-symmetry phase transition at $|\\nu|=2$ has an essential role in forming robust superconductivity, since superconductivity appears as carriers are added to or subtracted from that state, and it vanishes when the normal state of the system changes to a different phase, either through a ‘reset’ to the $|\\nu|=3$ broken-symmetry phase (at small $D$ ) or through a VHS to $\\scriptstyle\\nu=0$ , $\\nu=+1.$ or $|\\nu|=4$ phases at large $D$ . \n\nOur experiments point towards a strong coupling mechanism for superconductivity that is deeply tied to the ground state at $\\scriptstyle\\nu=\\pm2$ , and where the maximum $T_{\\mathrm{c}}$ is mostly determined by the carrier density instead of the precise structure of the DOS. At the same time, we also note that the presence of a VHS can affect the phase transitions that underlie the broken-symmetry phases. These observations should be taken into consideration in the development of theoretical models for moiré superconductors with ultrastrong coupling strength. It is noteworthy to determine what it is that makes MATBG and MATTG robust superconductors. One possibility is that they both have certain symmetry properties, in particular approximate $C_{2}$ symmetry40. Interestingly, this symmetry is absent in other graphene-based moiré systems. We hope future investigations on other $C_{2}$ -symmetric moiré systems will determine if this symmetry is indispensable for the formation of strong-coupling superconductivity in moiré flat bands. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03192-0. \n\n1. Suárez Morell, E., Correa, J. D., Vargas, P., Pacheco, M. & Barticevic, Z. Flat bands in slightly twisted bilayer graphene: tight-binding calculations. Phys. Rev. B 82, 121407 (2010). \n2. Bistritzer, R. & MacDonald, A. H. Moiré bands in twisted double-layer graphene. Proc. Natl Acad. Sci. USA 108, 12233–12237 (2011). \n3. Cao, Y. et al. Correlated insulator behaviour at half-filling in magic-angle graphene superlattices. Nature 556, 80–84 (2018). \n4. Cao, Y. et al. Unconventional superconductivity in magic-angle graphene superlattices. Nature 556, 43–50 (2018). \n5. Yankowitz, M. et al. Tuning superconductivity in twisted bilayer graphene. Science 363, 1059–1064 (2019). \n6. Lu, X. et al. Superconductors, orbital magnets and correlated states in magic-angle bilayer graphene. Nature 574, 653–657 (2019). \n7. Chen, G. et al. Evidence of a gate-tunable Mott insulator in a trilayer graphene moiré superlattice. Nat. Phys. 15, 237–241 (2019). \n8. Burg, G. W. et al. Correlated insulating states in twisted double bilayer graphene. Phys. Rev. Lett. 123, 197702 (2019). \n9. Shen, C. et al. Correlated states in twisted double bilayer graphene. Nat. Phys. 16, 520–525 (2020). \n10. Cao, Y. et al. Tunable correlated states and spin-polarized phases in twisted bilayer– bilayer graphene. Nature 583, 215–220 (2020). \n11. Liu, X. et al. Tunable spin-polarized correlated states in twisted double bilayer graphene. Nature 583, 221–225 (2020). \n12. Polshyn, H. et al. Electrical switching of magnetic order in an orbital Chern insulator. Nature 588, 66–70 (2020). \n13.\t Shi, Y. et al. Tunable Van Hove singularities and correlated states in twisted trilayer graphene. Preprint at https://arxiv.org/abs/2004.12414 (2020). \n14.\t Chen, S. et al. Electrically tunable correlated and topological states in twisted monolayer–bilayer graphene. Nat. Phys. https://doi.org/10.1038/s41567-020-01062-6 (2020). \n15.\t Regan, E. C. et al. Mott and generalized Wigner crystal states in ${\\sf W S e}_{2}/{\\sf W S}_{2}$ moiré superlattices. Nature 579, 359–363 (2020). \n16. Tang, Y. et al. Simulation of Hubbard model physics in ${\\sf W S e}_{2}/{\\sf W S}_{2}$ moiré superlattices. Nature 579, 353–358 (2020). \n17. Wang, L. et al. Correlated electronic phases in twisted bilayer transition metal dichalcogenides. Nat. Mater. 19, 861–866 (2020). \n18. Khalaf, E., Kruchkov, A. J., Tarnopolsky, G. & Vishwanath, A. Magic angle hierarchy in twisted graphene multilayers. Phys. Rev. B 100, 085109 (2019). \n19. Sharpe, A. L. et al. Emergent ferromagnetism near three-quarters filling in twisted bilayer graphene. Science 365, 605–608 (2019). \n20.\t Serlin, M. et al. Intrinsic quantized anomalous Hall effect in a moiré heterostructure. Science 367, 900–903 (2020). \n21.\t Chen, G. et al. Tunable correlated Chern insulator and ferromagnetism in a moiré superlattice. Nature 579, 56–61 (2020); correction 581, E3 (2020). \n22.\t Chen, G. et al. Signatures of tunable superconductivity in a trilayer graphene moiré superlattice. Nature 572, 215–219 (2019). \n23.\t Tsai, K.-T. et al. Correlated insulating states and transport signature of superconductivity in twisted trilayer graphene moiré of moiré superlattices. Preprint at https://arxiv.org/ abs/1912.03375 (2019). \n24.\t Mora, C., Regnault, N. & Bernevig, B. A. Flatbands and perfect metal in trilayer moiré graphene. Phys. Rev. Lett. 123, 026402 (2019). \n25.\t Carr, S. et al. Ultraheavy and ultrarelativistic Dirac quasiparticles in sandwiched graphenes. Nano Lett. 20, 3030–3038 (2020). \n26.\t Lei, C., Linhart, L., Qin, W., Libisch, F. & MacDonald, A. H. Mirror-symmetry breaking and stacking-shift dependence in twisted trilayer graphene. Preprint at https://arxiv.org/ abs/2010.05787 (2020). \n27.\t Park, J. M., Cao, Y., Watanabe, K., Taniguchi, T. & Jarillo-Herrero, P. Flavour Hund’s coupling, correlated Chern gaps, and diffusivity in moiré flat bands. Preprint at https:// arxiv.org/abs/2008.12296 (2020). \n28.\t Wong, D. et al. Cascade of electronic transitions in magic-angle twisted bilayer graphene. Nature 582, 198–202 (2020). \n29.\t Zondiner, U. et al. Cascade of phase transitions and Dirac revivals in magic-angle graphene. Nature 582, 203–208 (2020). \n30.\t Halperin, B. I. & Nelson, D. R. Resistive transition in superconducting films. J. Low Temp. Phys. 36, 599–616 (1979). \n31.\t He, M. et al. Symmetry breaking in twisted double bilayer graphene. Nat. Phys. 17, 26–30, (2021). \n32.\t Nandkishore, R., Levitov, L. S. & Chubukov, A. V. Chiral superconductivity from repulsive interactions in doped graphene. Nat. Phys. 8, 158–163 (2012). \n33.\t Dessau, D. S. et al. Key features in the measured band structure of $\\mathsf{B i}_{2}\\mathsf{S r}_{2}\\mathsf{C a C u}_{2}\\mathsf{O}_{8+\\bar{\\delta}}\\mathrm{:}$ flat bands at $E_{\\scriptscriptstyle\\mathsf{F}}$ and Fermi surface nesting. Phys. Rev. Lett. 71, 2781–2784 (1993). \n34.\t Yokoya, T. et al. Extended Van Hove singularity in a noncuprate layered superconductor $\\mathsf{S r}_{2}\\mathsf{R u O}_{4}$ Phys. Rev. Lett. 76, 3009–3012 (1996). \n35.\t Nelson, D. R. & Kosterlitz, J. M. Universal jump in the superfluid density of two-dimensional superfluids. Phys. Rev. Lett. 39, 1201–1205 (1977). \n36.\t Hazra, T., Verma, N. & Randeria, M. Bounds on the superconducting transition temperature: applications to twisted bilayer graphene and cold atoms. Phys. Rev. X 9, 031049 (2019). \n37.\t Nakagawa, Y. et al. Gate-controlled low carrier density superconductors: toward the two-dimensional BCS–BEC crossover. Phys. Rev. B 98, 064512 (2018). \n38.\t Wang, Z., Liu, C., Liu, Y. & Wang, J. High-temperature superconductivity in one-unit-cell FeSe films. J. Phys. Condens. Matter 29, 153001 (2017). \n39.\t Xie, M. & MacDonald, A. H. Weak-field Hall resistivity and spin/valley flavor symmetry breaking in MAtBG. Preprint at https://arxiv.org/abs/2010.07928 (2020). \n40.\t Khalaf, E., Chatterjee, S., Bultinck, N., Zaletel, M. P. & Vishwanath, A. Charged skyrmions and topological origin of superconductivity in magic-angle graphene. Preprint at https:// arxiv.org/abs/2004.00638 (2020). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 \n\n# Article Methods \n\n# Sample fabrication \n\nOur samples consist of three sheets of monolayer graphene, with twist angles $\\theta$ and $-\\theta$ for the top/middle and middle/bottom interfaces, respectively, which are then sandwiched between two hexagonal boron nitride (hBN) flakes approximately $30\\mathrm{-}80\\mathrm{nm}$ thick. We first exfoliate the hBN and graphene flakes on $\\mathsf{S i O}_{2}/\\mathsf{S i}$ substrates, and analyse these flakes with optical microscopy. The multilayer stack is fabricated using a dry pick-up technique, where a layer of poly(bisphenol A carbonate)/ polydimethylsiloxane (PC/PDMS) on a glass slide is used to pick up the flakes sequentially using a micro-positioning stage. To ensure the angle alignment between the graphene layers and to reduce strain, they are cut in situ from a single monolayer graphene flake using a focused laser beam27. The hBN flakes are picked up while heating the stage to $90^{\\circ}\\mathsf C$ , while the graphene layers are picked up at room temperature. The resulting structure is released on the prepared hBN on Pd/Au stack at $175^{\\circ}\\mathsf C$ . We define the Hall bar geometry with electron-beam lithography and reactive ion etching. The top gate and electrical contacts are thermally evaporated using Cr/Au. Schematics and optical picture of the finished devices are shown in Extended Data Fig. 2. \n\n# Measurement setup \n\nTransport data are measured in a dilution refrigerator with a base electronic temperature of $\\mathord{\\sim}70\\mathrm{mK}$ . Current through the sample and the four-probe voltage are first amplified by $10^{7}\\mathrm{VA^{-1}a n d1},000\\mathrm{VA^{-1}}$ , respectively, using current and voltage pre-amplifiers, and then measured with lock-in amplifiers (SR-830), synchronized at the same frequency between approximately 1 and $20{\\mathsf{H z}}$ . Current excitation of 1 nA or voltage excitation of $50\\upmu\\upnu$ to $100\\upmu\\upnu$ is used for resistance measurements. For d.c. bias measurements, we use a home-built digital–analogue converter (BabyDAC) passing through a 10-MΩ resistor to provide the d.c. bias current, and measure the d.c. voltage using a digital multimeter (Keysight 34461A) connected to the voltage pre-amplifier. \n\n# Bandstructure calculation \n\nThe bandstructures shown in Fig. 1b, c are calculated using the continuum model for twisted bilayer graphene2,41, extended with a third layer on the top that has the same twist angle as the bottommost layer18,25,26,42. For simplicity, we neglect the direct coupling from topmost and bottommost layers, and we use off-diagonal and diagonal interlayer hopping parameters $\\scriptstyle w=0.1$ eV and $\\scriptstyle w^{\\prime}=0.08\\mathrm{eV}.$ respectively, the latter value empirically accounting for a small relaxation of the lattice. We note that the Fermi velocity of the gapless Dirac bands using these parameters is the same as the value for monolayer graphene. \n\nThe colour of the curves in Fig. 1b, c represents the mirror symmetry character of the eigenstates, which we evaluate by projecting the wavefunction of the eigenstate in the topmost layer onto the bottommost layer and calculating its inner product with the wavefunction in the bottommost layer. This evaluates to 1 for a mirror symmetric eigenstate (coloured as orange) and $^{-1}$ for a mirror antisymmetric eigenstate (coloured as purple), and between $^{-1}$ and 1 for a nonsymmetric state. We find that at zero displacement field, the flat bands have symmetry character of 1 and the Dirac bands have $^{-1}$ . In other words, the flat bands in MATTG arise from mirror symmetric hopping from the outer layers onto the centre layer. Without a displacement field, the Dirac bands cannot couple to the flat bands, owing to this symmetry protection, though the electrons in the Dirac bands may still participate in the correlation-driven phenomena in the flat bands via Coulomb interactions. \n\nThe effect of displacement field is taken into account by imposing an interlayer potential difference $\\Delta V=d D/\\varepsilon_{0},$ , where $d{\\approx}0.3\\mathsf{n m}$ is the interlayer distance. Owing to the screening by the outer layers, the actual electric field between the layers will be less than the externally applied field. Although we can qualitatively capture the effect of the external displacement field in this calculation, a self-consistent treatment is required to accurately solve such a problem, which is beyond the scope of this mostly experimental paper. We note that these calculations do not take into account high-order and non-local interlayer coupling terms, which create a more pronounced particle–hole asymmetry than shown here25,26,39,42,43. \n\n# Stacking alignment \n\nTwisted trilayer graphene has an extra translation degree of freedom compared to twisted bilayer graphene. Although the topmost and bottommost layers are not twisted with respect to each other, their relative stacking order can have a notable effect on the single-particle bandstructure. Among the configurations, the ones with A-tw-A stacking and A-tw-B stacking (‘tw’ denotes the middle twisted layer) have the highest symmetry, as shown in Extended Data Fig. 1a, b. In particular, only A-tw-A stacking possesses a mirror symmetry; it was shown to have the lowest configuration energy among all possible stacking orders for a given twist angle25. Extended Data Fig. 1c–f shows the calculated bandstructures of the A-tw-A and A-tw-B configurations at zero and finite displacement fields. Furthermore, Extended Data Fig. 1g–j shows the calculated Landau level spectrum of the corresponding cases near charge neutrality44. In these calculations, we also included a small $C_{3}$ -symmetry-breaking term45 to reproduce the fourfold Landau level degeneracy observed in experiments $(\\beta=-0.01$ , following the convention of a previous work)45. We find that in the case of A-tw-A stacking, the Landau level sequence near charge neutrality is $\\pm2,\\pm6,\\pm10,...,$ regardless of whether a displacement field is applied, whereas in the case of A-tw-B stacking, the application of a displacement field leads to a complicated evolution of the Landau level that no longer follows the same sequence. The displacement field also induces a global bandgap in the A-tw-B configuration, while keeping A-tw-A gapless. \n\nFrom our experimental observations, our MATTG samples are more likely to possess A-tw-A stacking than other configurations, for the following reasons. First, unlike in MATBG, we do not find an insulating state at $\\scriptstyle\\nu=\\pm4$ at any displacement field, suggesting that the system does not have a global energy gap. Second, as shown in Extended Data Fig. 1k, l, the strongest Landau level sequence near the charge neutrality point is always $\\pm2,\\pm6,\\pm10,\\pm14,$ …, with or without displacement fields. Both of these findings are in agreement with the A-tw-A stacking case, as discussed above. We note that although it is difficult to achieve exactly identical top and bottom angles, from our experiments it seems that a minor difference might not qualitatively affect the role of mirror symmetry. \n\n# Chemical-potential estimate \n\nThe coexisting flat bands and Dirac bands share the same chemical potential, and so we can use the transport features of the Dirac bands as shown in Fig. 1d to determine the $n{-}\\mu$ relationship in the flat bands. Specifically, at a finite magnetic field $B$ and in the absence of $D$ , we assume that the flat bands host a charge density $n_{\\mathrm{f}}$ and the Dirac bands host a charge density $n_{\\mathrm{d}}$ such that $n{=}n_{\\mathrm{f}}{+}n_{\\mathrm{d}}$ . \n\nUnder finite $B$ , the Dirac bands are quantized into fourfold degenerate Landau levels labelled by an index $N{=}0,\\pm1,\\pm2,$ …. In the transport data, if we designate the centres of the $R_{x x}$ peaks (see for example, Fig. 1f) as the centre of the Nth Landau level (not the Landau level gaps), $n_{\\mathrm{d}}$ and $\\mu_{\\mathrm{d}}$ follow \n\n$$\n\\begin{array}{c}{{\\displaystyle n_{\\mathrm{d}}=\\frac{4N B}{\\phi_{\\mathrm{0}}},}}\\\\ {{\\displaystyle\\mu_{\\mathrm{d}}=\\nu_{\\mathrm{F}}\\sqrt{2e\\hbar N B}\\mathrm{sgn}(N),}}\\end{array}\n$$ \n\nwhere $\\phi_{0}=h/e$ is the flux quantum, the factor 4 accounts for spin and valley degeneracies, and $\\mathsf{s g n}(N)$ is the sign of $N$ . We use a Fermi velocity of $\\nu_{\\mathrm{{F}}}{=}10^{6}\\mathrm{{m}}s^{-1}$ for this estimation. Since $n_{\\mathrm{d}}$ and $\\mu_{\\mathrm{d}}$ are functions of \n\nNB only, they are known once we determine the Landau level index $N_{i}$ which is evident from the Hall conductivity in the gaps between them, $\\sigma_{x y}=4(N\\pm1/2)e^{2}/h$ (see Fig. 1f). Therefore, along the trajectory of the Nth Landau level in an $n{-}B$ map, we can determine the $n_{\\mathrm{f}}{-}\\mu_{\\mathrm{f}}$ relationship for the flat bands as \n\n$$\n\\begin{array}{c}{{\\displaystyle n_{\\mathrm{f}}=n-\\frac{4N B}{\\phi_{0}},}}\\\\ {{\\displaystyle\\mu_{\\mathrm{f}}=\\nu_{\\mathrm{F}}\\sqrt{2e\\hbar N B}\\mathrm{sgn}(N).}}\\end{array}\n$$ \n\nWe performed this extraction for $\\vert N\\vert=1,2,3,4$ and the results are consistent, as shown in Fig. 1f. The estimated many-body bandwidth of the flat bands from this extraction is around $100\\mathrm{meV},$ whereas that of MATBG is approximately $40{\\mathrm{-}}60\\mathrm{meV}$ (refs. $^{27,29,46},$ ). This many-body bandwidth includes the Coulomb interaction, which is, in principle, larger in MATTG than in MATBG, owing to the smaller unit cell. \n\n# Hall density analysis \n\nThe Hall density in Fig. 2b is calculated from $R_{x y}$ measured and anti-symmetrized at $B{=}1.5\\mathrm{T}$ . The reason for choosing this magnetic field is to fully suppress the superconductivity at $v{=}{-}2-\\delta$ , which has a critical magnetic field approaching 1 T, because of the short Ginzburg– Landau coherence length. Extended Data Fig. 6a–c shows representative linecuts in the maps of $\\cdot_{R_{x x},R_{x y}}$ and the Hall density $\\nu_{\\mathrm{H}}$ , with the Hall features (‘gap/Dirac’, ‘reset’ or ‘VHS’) and superconducting regions annotated. All major superconducting domes are bounded by the Hall features, although we notice a few exceptions of weak superconductivity that are not bounded. For example, at zero displacement field (Extended Data Fig. 6c), there is a weak signature of superconductivity beyond the reset around $\\scriptstyle\\nu=-3.2$ , which has a small but non-zero resistance. We also note that in Fig. 2b, there are some small regions, right before $\\scriptstyle\\nu=+1$ and $\\nu{=}{+}2$ in some ranges of $D$ , where there are signatures of a more complex behaviour in $\\nu_{\\mathrm{H}},$ with VHSs possibly very close to the ‘resets’. These regions need further investigation for a complete understanding. \n\nThe weak superconducting region at $\\nu=-2+\\delta$ at large $D$ is also seemingly not bounded by a VHS in the main Hall density plot taken at $B=\\pm1.5\\:\\mathrm{T}$ (see Fig. 2a, b). However, we find that signatures of a VHS boundary can be identified if we measure the Hall density using a smaller $B$ , as shown in Extended Data Fig. 6d. By comparing to $R_{x x}$ data shown in Extended Data Fig. 6e, we can see that although not perfectly matching, there is a clear correlation between the VHS and the superconductivity boundary. Furthermore, the Landau fans at finite $D$ (Fig. 4a, Extended Data Fig. 9a) show signatures of an inward-facing fan at $v=-2+\\delta$ , supporting the existence of carriers from $\\scriptstyle\\nu=-2$ . However, the inward fan, as well as the superconductivity in this region, appears to be extremely fragile, which might be related to why the VHS boundary is invisible when measured at higher $B$ . \n\n# $\\pmb{T}_{\\mathrm{c}}$ and coherence-length analysis \n\nThe mean-field $T_{\\mathrm{c}}$ is extracted by first fitting the high-temperature part of the data to a straight line $r(T)=A T+B$ , and then finding the intersection of ${\\bf\\nabla}\\cdot{\\cal R}_{x x}(T)$ with $p r(T)$ , where $p$ is the percentage of normal resistance (we use $50\\%$ unless otherwise specified). \n\nWe extract the Ginzburg–Landau coherence length from the $B$ -dependence of $T_{\\mathrm{c}},$ , using the Ginzburg–Landau relation $T_{\\mathrm{c}}/T_{\\mathrm{c0}}=1-(2\\uppi\\xi_{\\mathrm{GL}}^{2}/\\phi_{0})\\dot{B}_{\\perp}$ , where $\\scriptstyle\\phi_{0}=h/(2e)$ is the superconducting flux quantum and $T_{\\mathrm{c}0}$ is the mean-field critical temperature at zero magnetic field (slightly higher than $T_{\\mathrm{BKT}},$ . As shown in Extended Data Fig. 8, the mean-field $T_{\\mathrm{c}}$ at different $B$ is extracted at different percentages $p{=}30\\%$ , $40\\%$ and $50\\%$ of the normal resistance fit (shown as dashed lines). The insets show the extracted $T_{\\mathrm{c}}$ using different thresholds. The Ginzburg–Landau coherence length $\\xi_{\\mathrm{GL}}$ is then obtained from a linear fit of $T_{\\mathrm{c}}$ versus $B$ , the $x$ intercept of which is equal to $\\ensuremath{\\phi_{0}}/(2\\uppi\\ensuremath{\\xi_{\\mathrm{GL}}}^{2})$ . \n\nThe different thresholds yield slightly different but consistent coherence lengths, which we plot as the data points $(40\\%)$ and error bars $(50\\%,30\\%)$ in Fig. 3b, c. Note that in the presence of charge and/or twist angle disorder, values for $\\xi_{\\mathrm{GL}}$ , $T_{\\mathrm{c}}$ and $T_{\\mathrm{BKT}}$ should be interpreted as spatial averages of the corresponding local quantities. \n\n# Effective mass analysis \n\nThe effective mass of MATTG is extracted from the $T-$ -dependent quantum oscillations in a perpendicular magnetic field using the standard Lifshitz–Kosevich formula47. Extended Data Fig. 7a, b shows representative quantum oscillations at $\\pmb{\\nu}=-2.86$ and $\\nu=-2.5$ , respectively, at $D/\\varepsilon_{0}=-0.44\\mathrm{V}\\ \\mathrm{nm}^{-1}$ . Starting from raw resistance data $\\begin{array}{r}{R_{x x},}\\end{array}$ we first remove a smooth polynomial background in $B^{-1}$ and obtain $\\Delta R$ . We then select the most prominent peak/valley in $\\Delta R$ , and evaluate its change from the valley to the peak as a function of temperature, $\\delta R(T)$ . We notice that in some curves, such as those shown in Extended Data Fig. 7a, b, the high-field part of the oscillation is either split (Extended Data Fig. 7a) or has a higher periodicity (Extended Data Fig. 7b) than the fundamental frequency that corresponds to the carrier density, which we attribute to broken-symmetry states. We avoid using those peaks for extracting effective mass, as they tend to overestimate the effective mass $m^{*}$ and underestimate $T_{\\mathrm{F}}.\\delta R(T)$ is subsequently fitted with the Lifshitz–Kosevich formula \n\n$$\n\\delta R(T)=b\\frac{a T}{\\sinh(a T)},\n$$ \n\nwhere $a$ and $^{b}$ are fitting parameters. The effective mass $m^{*}$ is then extracted from \n\n$$\nm^{*}=\\frac{\\hbar e\\overline{{B}}}{2\\uppi^{2}k_{\\mathrm{B}}}a,\n$$ \n\nwhere $\\overline{{B}}$ is the average of the peak and valley positions. The fit is shown in the insets of Extended Data Fig. 7a, b, from which we obtain $m^{*}/m_{\\mathrm{e}}{=}1.25{\\pm}0.13$ and $m^{*}/m_{\\mathrm{e}}=0.95\\pm0.03$ , respectively. $T_{\\mathrm{BKT}}$ at these two points is 1.11 K and 2.09 K, respectively, and so the ratio $T_{\\mathrm{{BKT}}}/T_{\\mathrm{F}}$ is $0.041{\\scriptstyle\\pm0.004}$ and $0.100{\\scriptstyle\\pm0.003}$ , respectively. \n\nFor the effective-mass data in Fig. 2h and Fig. 3d, e, we performed the extraction with fewer points in temperature, as exemplified in Extended Data Fig. $7c-e$ . We manually select the peak/valley position (shown as triangles) for each density/displacement field, and the mass is obtained from the same fit as above, as shown in Extended Data Fig. 7f. We have checked that this extraction is consistent with the extraction using more data points in T for the representative curves shown (Extended Data Fig. 7a, b), which justifies the analysis with coarser data in $T$ . \n\n# Data availability The data that support the current study are available from the corresponding authors upon reasonable and well motivated request. \n\n41.\t Lopes dos Santos, J. M. B., Peres, N. M. R. & Castro Neto, A. H. Continuum model of the twisted graphene bilayer. Phys. Rev. B 86, 155449 (2012). \n42.\t Lopez-Bezanilla, A. & Lado, J. L. Electrical band flattening, valley flux, and superconductivity in twisted trilayer graphene. Phys. Rev. Res. 2, 033357 (2020). \n43.\t Carr, S., Fang, S., Zhu, Z. & Kaxiras, E. An exact continuum model for low-energy electronic states of twisted bilayer graphene. Phys. Rev. Res. 1, 013001 (2019). \n44.\t Bistritzer, R. & MacDonald, A. H. Moiré butterflies in twisted bilayer graphene. Phys. Rev. B \n84, 035440 (2011). \n45.\t Zhang, Y.-H., Po, H. C. & Senthil, T. Landau level degeneracy in twisted bilayer graphene: role of symmetry breaking. Phys. Rev. B 100, 125104 (2019). \n46.\t Tomarken, S. L. et al. Electronic compressibility of magic-angle graphene superlattices. Phys. Rev. Lett. 123, 046601 (2019). \n47.\t Shoenberg, D. Magnetic Oscillations in Metals (Cambridge Univ. Press, 1984). \n48.\t Giamarchi, T. & Bhattacharya, S. in High Magnetic Fields: Applications in Condensed Matter Physics and Spectroscopy (eds Berthier, C. et al.) 314–360 (2001). \n\n# Article \n\nAcknowledgements We thank S. Todadri, A. Vishwanath, S. Kivelson, M. Randeria, S. Ilani, L. Fu and A. Georges for discussions. This work has been primarily supported by the US Department of Energy (DOE), Office of Basic Energy Sciences (BES), Division of Materials Sciences and Engineering under award DE-SC0001819 (J.M.P.). Help with transport measurements and data analysis were supported by the National Science Foundation (DMR-1809802), and the STC Center for Integrated Quantum Materials (NSF grant number DMR-1231319; Y.C.). P.J.-H. acknowledges support from the Gordon and Betty Moore Foundation’s EPiQS Initiative through grant GBMF9643. P.J.-H. acknowledges partial support by the Fundación Ramon Areces. The development of new nanofabrication and characterization techniques enabling this work has been supported by the US DOE Office of Science, BES, under award DE‐SC0019300. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT, Japan, grant number JPMXP0112101001, JSPS KAKENHI grant numbers JP20H00354 and the CREST (JPMJCR15F3), JST. This work made use of the Materials Research Science and Engineering Center Shared Experimental Facilities supported by the National Science Foundation \n\n(DMR-0819762) and of Harvard’s Center for Nanoscale Systems, supported by the NSF (ECS-0335765). \n\nAuthor contributions J.M.P. and Y.C. fabricated the samples, and performed transport measurements and numerical simulations. K.W. and T.T. provided hBN samples. J.M.P., Y.C., and P.J-H. performed data analysis, discussed the results, and wrote the manuscript with input from all co-authors. \n\nCompeting interests The authors declare no competing interests. \n\nAdditional information \nCorrespondence and requests for materials should be addressed to Y.C. or P.J.-H. Peer review information Nature thanks Mathias Scheurer, Ke Wang and Guangyu Zhang for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/efdfba07c9a86d84c1e0dd3038e206a9551251f5181711b27c60d301248328f2.jpg) \nExtended Data Fig. 1 | Stacking order in MATTG. a, b, Illustrations of A-tw-A stacking (a) and A-tw-B stacking (b), where ‘tw’ denotes the middle twisted layer (L2, orange) and A/B represents the relative stacking order between the topmost (L3, green) and bottommost (L1, blue) layers. c–f, Continuum-model bandstructures of A-tw-A stacked (c, d) and A-tw-B stacked (e, f) MATTG at zero (c, e) and finite (d, f) displacement fields. The twist angle is $\\theta{=}1.57^{\\circ}$ for all plots. g–j, Calculated Landau level sequence corresponding to the bands in c–f. The size of the dots represents the size of the Landau level gaps in the Hofstadter spectrum. For A-tw-A stacking, the major sequence of filling factors near the \n\ncharge neutrality is $\\pm2,\\pm6,\\pm10,$ …, regardless of the displacement field, whereas for A-tw-B stacking the Landau levels evolve into a symmetry-broken sequence that has 0, $^{\\pm8}$ as the dominant filling factors with largest gaps in a finite displacement field. An anisotropy term of $\\beta=-0.01$ is included in all of the above calculations (see Methods). k, l, Experimentally measured Landau levels in MATTG near the charge neutrality. We find the strongest sequence of $\\pm2,\\pm6,$ $\\pm10,$ … at both $D=0$ and $D/\\varepsilon_{0}=0.77\\mathrm{V}\\mathrm{nm}^{-1}$ , consistent with the A-tw-A stacking scenario. \n\n# Article \n\n![](images/3f44e9cc768993646517eb57457fbb3e8223d923e47b068871782a09ef0b3aa0.jpg) \nExtended Data Fig. 2 | Device schematics and device optical picture. a, Our device consists of hBN-encapsulated MATTG etched into a Hall bar, $\\mathrm{Cr/Au}$ contacts on the edge, and top/bottom metallic gates. For transport measurements, we measure current I, longitudinal voltage $V_{x x},$ and transverse \n\nvoltage $V_{x y},$ while tuning the density ν and displacement field $D$ by applying top gate voltage $V_{\\mathrm{tg}}$ and bottom gate voltage $V_{\\mathrm{bg}}$ b, Optical picture of devices A and B. Device C is lithographically similar. \n\n![](images/2080ecc9bd90f9051f457bc02e602ff649e5bcca1b1fe7330ea5daffbf75bdc4.jpg) \nExtended Data Fig. 3 | Robust superconductivity in other MATTG devices (devices B and C). a, $R_{x x}$ –T curve. b, $V_{x x}$ –I and $\\mathrm{d}V_{x x}/\\mathrm{d}I^{.}$ –I curves. c, I–B map in device B with a smaller-than-magic-angle $\\theta{\\approx}1.44^{\\circ}$ . In this device, maximum $T_{\\mathrm{BKT}}{\\approx}0.73\\mathsf{K}$ . The choice of ν is to display the Fraunhofer-like Josephson \ninterference, which demonstrates the superconducting phase coherence. d–f, As in a–c, for device C, with a twist angle $\\theta{\\approx}1.4^{\\circ}$ . Device C has a maximum $T_{\\mathrm{BKT}}$ of $\\mathord{\\sim}0.68\\mathsf{K}$ . f shows a regular $B$ -suppression of $\\dot{I}_{\\mathrm{c}}$ with B. Both devices show sharp peaks in $\\mathbf{d}V_{x x}$ /dI at their critical currents. \n\n# Article \n\n![](images/b12262d317f07e1f847b7c50a3281ec72fc6c7a3db4d92ac0e5df2a32f029c04.jpg) \n\nExtended Data Fig. 4 $|\\pmb{V}_{x x}|$ –I curves and critical current $\\pmb{I_{\\mathrm{c}}}$ in MATTG. a, Forward (red) and backward (blue) sweeps of $V_{x x}$ –I curves for the optimal point $\\nu{=}{-}2.4$ and $D/\\varepsilon_{0}{=}{-}0.44\\mathsf{V}\\mathsf{n m}^{-1}$ . Inset, A clear hysteresis loop exists in the curve at $I{\\approx}550–600\\mathrm{nA}$ . b, Map of ${{\\mathbf{}}^{\\mathrm{{\\cdot}}}}{I_{\\mathrm{{c}}}}$ versus ν and $D$ in the major superconducting regions. c, Evolution of $\\dot{I}_{\\mathrm{c}}$ over $D$ at $\\nu{=}{-}2.4$ , showing that $I_{\\mathrm{c}}$ initially increases as finite $D$ is applied, and quickly decreases beyond local maxima near $|D|/\\varepsilon_{0}\\approx0.48\\mathrm{V}\\mathrm{nm}^{-1}$ . ${\\bf d},{\\cal I}_{\\mathrm{c}}$ versus $D$ at $\\nu=+2.26$ shows that the \n\nmaximum $I_{\\mathrm{c}}$ occurs near $|D|/\\varepsilon_{0}\\approx0.71\\mathrm{{V}n m^{-1}}$ , after which $I_{\\mathrm{c}}$ quickly decreases. The modulation of superconducting strength in $D$ may be due to change in the band flatness, as well as the interactions with the electrons in the Dirac bands. $\\mathbf{e}{\\boldsymbol{-}}\\mathbf{g}$ , $V_{x x}$ –I and $\\mathrm{d}V_{x x}/\\mathrm{d}I^{.}$ –I curves for certain points in superconducting domes near $\\nu{=}{-}2{+}\\delta$ (e), $\\nu{=}{+}2-\\delta(\\mathbf{f}$ ), and $\\pmb{\\nu}=+2+\\delta(\\mathbf{g})$ , all showing sharp peaks in $\\mathbf{d}V_{x x}$ /dI at the critical current. \n\n![](images/b7065bcdc8b46fafaded5e5201033d018aab81aebfecc6004cc1ab8f94ed1c8f.jpg) \nExtended Data Fig. 5 $|R_{x x}$ versus ν at $\\pmb{T}\\equiv7\\mathbf{0}\\mathbf{m}\\mathbf{K}$ , 5 K and 10 K. a–d, Measured a $\\cdot D/\\varepsilon_{0}=0.77\\vee\\mathsf{n m}^{-1}(\\mathbf{a}),D/\\varepsilon_{0}=0.52\\vee\\mathsf{n m}^{-1}(\\mathbf{b}),D/\\varepsilon_{0}=0.26\\vee\\mathsf{n m}^{-1}(\\mathbf{c})$ and $D/\\varepsilon_{0}{=}0\\vee\\mathsf{n m}^{-1}(\\mathbf{d})$ . \n\n# Article \n\n![](images/5d65af77c92b9f30ba37acfcf6f0af7c06ab29fc91651080a7d69a14eab51840.jpg) \nExtended Data Fig. 6 | Hall density analysis. a–c, Linecuts of $\\cdot_{R_{x x}},R_{x y}$ and $\\nu_{\\mathsf{H}}$ (right axis) versus ν at representative $D$ from high to zero, showing the bounding of major superconducting phases within the Hall density features. Vertical red, yellow, and dark blue bars denote ‘gap/Dirac’, ‘reset’ and ‘VHS’ features, respectively, and the light-blue regions denote superconductivity. Purple dashed lines show the expected Hall density. We note that there are some small regions right before $\\nu{=}{+}1$ and $\\nu=+2$ where for certain D values there are signatures of a more complex behaviour in $\\nu_{\\mathrm{H}}$ , with VHSs possibly very close \nto the ‘resets’, as shown in Fig. 2b. d, The Hall density $\\nu_{\\mathrm{H}}$ extracted from smaller magnetic fields of $\\ B{\\approx}0.1{-}0.3$ T reveals a VHS boundary close to the weak superconducting phase boundary near $\\nu=-2+\\delta_{\\cdot}$ which is absent in the Hall density shown in a–c and Fig. 2b extracted from a higher magnetic field of $B{\\approx}-1.5$ T to $1.5\\mathsf{T}.\\mathsf{e},R_{x x}$ in the same region as shown in d, where the superconducting boundary is close to the VHSs. All measurements are performed at the base temperature $T{\\approx}70\\mathrm{mK}$ . SC, superconducting. \n\n![](images/887a470c81f03f84ae8de573bcf68a6c0565a9dabd5f6016b5763a473e0f91d1.jpg) \nExtended Data Fig. 7 | Quantum oscillations and effective-mass analysis. All data shown here are measured at $D/\\varepsilon_{\\scriptscriptstyle0}=-0.44\\mathrm{V}\\mathrm{nm}^{-1}$ . a, b, Quantum oscillations at $\\nu{=}{-}2.86$ (a) and $\\nu{=}{-}2.5$ (b) at different $T.$ Grey dashed lines show the peaks used for analysis. Inset, Fit to the Lifshitz–Kosevich formula for the extraction of the effective mass, yielding $m^{*}/m_{\\mathrm{e}}{=}1.25{\\pm}0.13$ (a) and $m^{*}/m_{\\mathrm{e}}=0.95\\pm0.03$ (b). c, d, Quantum oscillations sampled at coarser points in T for the same ν as in \na, b. Extracted effective-mass values with these coarser data are $m^{*}/m_{\\mathrm{e}}{=}1.2{\\pm}0.2$ (c) and $m^{*}/m_{\\mathrm{e}}=0.96\\pm0.09$ (d), matching the values from a, b within the uncertainty. e, Quantum oscillations at $\\nu{=}{-}2.4$ (optimal doping). f, Lifshitz–Kosevich fits for the data shown in c–e, showing $\\delta R$ normalized with its value at the lowest temperature. The peaks chosen for extraction are marked with triangles in c–e. Amp., amplitude; a.u., arbitrary units. \n\n# Article \n\n![](images/096a317a35334521d613225305959a9499460304aa1e2e54fd45ce454294f119.jpg) \nExtended Data Fig. 8 | Analysis of the Ginzburg-Landau coherence length. a, b, Superconducting transitions at perpendicular magnetic fields from $B=0$ T to $B{=}0.2\\operatorname{T}$ ( $40\\mathrm{mT}$ between curves) for $\\nu{=}{-}2{-}\\delta(\\nu{=}{-}2.4;\\varepsilon$ ) and $\\nu{=}{-}2+\\delta\\left(\\nu{=}{-}1.84;\\mathbf{b}\\right.$ ), from which the Ginzburg–Landau coherence length $\\xi_{\\mathrm{cl}}$ is extracted. $D/\\varepsilon_{\\scriptscriptstyle0}=-0.44\\mathrm{V}\\mathrm{nm}^{-1}$ for both plots. Inset shows $T_{\\mathrm{c}}^{50\\%}$ , $T_{\\mathrm{c}}^{40\\%}$ and $T_{\\mathrm{c}}^{30\\%}$ as a \nfunction of $B$ , from which we extracted the coherence length $\\xi_{\\mathrm{GL}}$ as $9.4\\mathrm{nm}$ , $12.4\\ensuremath{\\mathrm{nm}}$ and $16.1\\ensuremath{\\mathrm{nm}}$ , respectively, for $\\begin{array}{r}{\\nu=-2-\\delta.}\\end{array}$ For $v=-2+\\delta$ , we obtained $38.0\\mathsf{n m}$ , 39.1 nm and $37.1\\ensuremath{\\mathrm{nm}}$ , respectively. We note that for $v=-2-\\delta$ the $R_{x x}{-}T$ curves develop an extra transition (‘knee’) below $T_{\\mathrm{c}}$ at finite $B$ , which is possibly related to the melting transition between a vortex solid and a vortex liquid48. \n\n![](images/914b0f92ec886b8249e65ad802df672646526ebc4cd6a8be7779878a25d27f21.jpg) \nExtended Data Fig. 9 | Landau fans for intermediate D. a, b, Landau fans on the hole-doped (a) and electron-doped sides (b). They show the evolution between small $D$ and large $D$ , which exhibits a hybridization of the features. In a, the Landau fan diagram at $D/\\varepsilon_{\\scriptscriptstyle0}=-0.34\\mathrm{V}\\mathrm{nm}^{-1}$ for the hole-doped side shows the fans emanating from all integer fillings. An inward-facing fan from $\\scriptstyle\\nu=-4$ starts developing, which meets the outward-facing fan from $\\scriptstyle\\nu=-3$ . Note also the appearance of an inward-facing fan from $\\scriptstyle\\nu=-2$ , which meets the outwardfacing fan from $\\scriptstyle\\nu=-1$ . These observations agree with the formation of VHSs around these two regions in the intermediate $|D|$ , where the electron-like \n\ncarriers become hole-like, as illustrated in Fig. 4d, and identified in Fig. 2b. A small region of superconductivity starts appearing at $\\nu{=}{-}2{+}\\delta$ while the carriers from $\\scriptstyle\\nu=-2$ are present, as shown in Fig. 2a. In b, the Landau fan diagram a $\\cdot D/\\varepsilon_{0}{=}-0.52\\vee\\mathrm{nm}^{-1}$ on the electron-doped side shows similar VHSs between $\\nu{\\approx}{+}1{-}2$ and $\\scriptstyle\\nu\\approx+3-4$ . Similar to the hole-doped side, an inward-facing fan from $\\nu=+2$ develops and meets with the outward-facing fan from $\\nu{=}{+}1$ . The density range of the inward-facing fan encompasses the appearance of a superconducting region at $\\nu{=}{-}2{+}\\delta$ at this $D$ . " + }, + { + "id": "10.1038_s41560-021-00820-x", + "DOI": "10.1038/s41560-021-00820-x", + "DOI Link": "http://dx.doi.org/10.1038/s41560-021-00820-x", + "Relative Dir Path": "mds/10.1038_s41560-021-00820-x", + "Article Title": "Non-fullerene acceptors with branched side chains and improved molecular packing to exceed 18% efficiency in organic solar cells", + "Authors": "Li, C; Zhou, JD; Song, JL; Xu, JQ; Zhang, HT; Zhang, XN; Guo, J; Zhu, L; Wei, DH; Han, GC; Min, J; Zhang, Y; Xie, ZQ; Yi, YP; Yan, H; Gao, F; Liu, F; Sun, YM", + "Source Title": "NATURE ENERGY", + "Abstract": "Molecular design of acceptor and donor molecules has enabled major progress in organic photovoltaics. Li et al. show that branched alkyl chains in non-fullerene acceptors allow favourable morphology in the active layer, enabling a certified device efficiency of 17.9%. Molecular design of non-fullerene acceptors is of vital importance for high-efficiency organic solar cells. The branched alkyl chain modification is often regarded as a counter-intuitive approach, as it may introduce an undesirable steric hindrance that reduces charge transport in non-fullerene acceptors. Here we show the design and synthesis of a highly efficient non-fullerene acceptor family by substituting the beta position of the thiophene unit on a Y6-based dithienothiophen[3,2-b]-pyrrolobenzothiadiazole core with branched alkyl chains. It was found that such a modification to a different alkyl chain length could completely change the molecular packing behaviour of non-fullerene acceptors, leading to improved structural order and charge transport in thin films. An unprecedented efficiency of 18.32% (certified value of 17.9%) with a fill factor of 81.5% is achieved for single-junction organic solar cells. This work reveals the importance of the branched alkyl chain topology in tuning the molecular packing and blend morphology, which leads to improved organic photovoltaic performance.", + "Times Cited, WoS Core": 1693, + "Times Cited, All Databases": 1745, + "Publication Year": 2021, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000648836900002", + "Markdown": "# Non-fullerene acceptors with branched side chains and improved molecular packing to exceed 18% efficiency in organic solar cells \n\nChao Li1,10, Jiadong Zhou2,10, Jiali Song1, Jinqiu $\\mathsf{X}\\mathsf{u}^{3}$ , Huotian Zhang   4, Xuning Zhang1, Jing Guo5, Lei Zhu $\\textcircled{10}3$ , Donghui Wei6, Guangchao Han7, Jie Min $\\textcircled{10}5$ , Yuan Zhang1, Zengqi Xie2, Yuanping Yi $\\textcircled{1}$ 7, He Yan $\\textcircled{10}8$ , Feng Gao $\\textcircled{10}4$ , Feng Liu $\\textcircled{10}3\\boxtimes$ and Yanming Sun   1,9 ✉ \n\nMolecular design of non-fullerene acceptors is of vital importance for high-efficiency organic solar cells. The branched alkyl chain modification is often regarded as a counter-intuitive approach, as it may introduce an undesirable steric hindrance that reduces charge transport in non-fullerene acceptors. Here we show the design and synthesis of a highly efficient non-fullerene acceptor family by substituting the beta position of the thiophene unit on a Y6-based dithienothiophen[3,2-b]-pyrrolobenzothiadiazole core with branched alkyl chains. It was found that such a modification to a different alkyl chain length could completely change the molecular packing behaviour of non-fullerene acceptors, leading to improved structural order and charge transport in thin films. An unprecedented efficiency of $18.32\\%$ (certified value of $17.9\\%$ ) with a fill factor of $81.5\\%$ is achieved for single-junction organic solar cells. This work reveals the importance of the branched alkyl chain topology in tuning the molecular packing and blend morphology, which leads to improved organic photovoltaic performance. \n\nS(olOuStiCosn)-hpraovceeessmeedrgebdu laks-haetperro jmuisnicntigoanlterorngaatinviec tos oilnaorrgcaenlilcs transparent and flexible1–3. The recent development of non-fullerene acceptors (NFAs) that can better harness the long-wavelength absorption and optimize electronic structure induces an elevated photocurrent density and voltage output, which significantly boosts the power conversion efficiency (PCE) of $\\mathrm{OSCs^{4,5}}$ . As a result, OSCs have surpassed $18\\%$ PCE using Y6-type acceptors6–11. However, comparing to inorganic and perovskite solar cells, OSCs show high energy loss $(E_{\\mathrm{loss}})$ and low fill factor (FF), which retards the device performance12–14. A systematic optimization to design the right materials is key to these issues15–17. \n\nThe rapid advances of NFAs bring in new opportunities in $\\mathrm{OSCS^{18-28}}$ . A reduced driving force in charge generation in NFAOSCs was effective in improving the open-circuit voltage $(V_{\\mathrm{oc}})$ , and the proper morphology and charge transport enable OSCs with high FFs of over $75\\%$ (refs. $29-32$ ). Such momentum should be carried on and extended to further manipulate material properties. The complexity in device $E_{\\mathrm{loss}}$ and FF lies in not only electronic structure but also morphology, in which the molecular ordering, phase separation and mixing are involved6,33–37. Thus, the paradigm of material construction is shifted to the manipulation of intermolecular interactions, from which we try to discover an avenue to control the intermolecular coupling and carrier transport to improve FF and suppress $E_{\\mathrm{loss}}$ . \n\nIn this contribution, we initiated a systematic effort to search for NFA materials with superior electronic properties in solids. We utilized the electronic structure of a Y6 backbone due to its high photovoltaic performance. Side-chain modification was taken as a design strategy that benefits from Y6 physical properties that can be retained and intermolecular packing that can be manipulated. Different aliphatic chains were introduced at various positions on the Y6 backbone to maximize the possibilities, shifting from the pyrrole site to the thiophene beta position. A series of NFAs, L8-R (with R being the alkyl chain), were developed. They showed blue-shifted light absorption, reduced bandgap and upshifted lowest unoccupied molecular orbital (LUMO) energy levels that hold the potential to improve device performance. Precise molecular packing was examined in single crystals, in which the backbone interaction showed systematic changes. And different crystallization behaviours in the crystal and thin film were recorded. Thus, the morphology can be effectively optimized through crystallization control. These areas of progress taken together deliver improved device performance, in which L8-BO (2-butyloctyl substitution) blended with polymer donor PM6 yielded a high PCE of $18.32\\%$ , with a low $E_{\\mathrm{loss}}$ of $0.55\\mathrm{eV}$ and a high FF of $81.5\\%$ . The high PCE and FF indicate that connecting morphology optimization with electronic-structure refinement is a plausible avenue towards $20\\%$ efficiency for solution-processed OSCs. \n\nOptoelectronic characterization and device performance The synthetic routes for L8-R are presented in Supplementary Fig. 1. L8-R and Y6 share the same synthetic procedures except for the synthesis of the 3-alkylthieno[3,2-b]thiophene unit. For Y6, the linear 3-alkylthieno[3,2-b]thiophene is synthesized through a four-step reaction from 3-bromothiophene. For L8-R, the branched 3-alkylthieno[3,2-b]thiophene is prepared in a two-step reaction from 3-bromothieno[3,2-b]thiophene. The design provides an effective route to synthesize 3-alkylthieno[3,2-b]thiophene with different alkyl chain topologies. The branched alkyl chain and extended alkyl chain length in L8-R enable better solubility than Y6 in common solvents. The decomposition temperatures (at $5\\%$ weight loss) of L8-R were over $320^{\\circ}\\mathrm{C}$ (Supplementary Fig. 3), indicating good thermal stability. From differential scanning calorimetry (DSC) measurements, the Y6, L8-BO, L8-HD (2-hexyldecyl substitution) and L8-OD (2-octyldodecyl substitution) exhibited exothermal peaks at 298.8, 319.6, 302.4 and $276.7^{\\circ}\\mathrm{C},$ respectively (Supplementary Fig. 4). The melting enthalpy $(\\Delta H_{\\mathrm{m}})$ of Y6, L8-BO, L8-HD and L8-OD were calculated to be 28.4, 38.5, 34.2 and $31.7\\mathrm{Jg}^{-1}$ , respectively. The results demonstrated that side-chain modification could control the L8-R molecular ordering, which, with a moderately branched alkyl chain, can be improved, compared to Y6. This property provides valuable input in the control of thin-film crystallization and morphology, which will be elaborated on in the following section on grazing-incidence wide-angle X-ray scattering (GIWAXS). \n\n![](images/38d8dd144927371796eea4d9c632769b09df7eb6aed1557cf2069e4b3d3bc5a1.jpg) \nFig. 1 | Molecular structures, photophysical properties and photovoltaic properties. a, Molecular structures of Y6 and L8-R. b, Normalized absorption spectra of Y6 and L8-R in thin films. c, Energy level diagrams of PM6, Y6 and L8-R. d J−V characteristics for optimized OSCs. e, Histogram of the efficiency measurements of Y6-based and L8-R-based OSCs, fitted with Gaussian distributions (solid lines). f, EQE spectra (solid lines) and integrated current densities (dashed lines) of the optimized OSCs. \n\nThe UV–visible absorption spectra of L8-R are shown in Fig. 1b and Supplementary Fig. 5. In dilute chloroform solution, the absorption spectra of Y6 and L8-R are nearly identical, with a maximum absorption peak located at $731\\mathrm{nm}$ . From solution to thin film, the absorption spectra of L8-R become broader and the maximum absorption peak red-shifts to $807\\mathrm{nm}$ , which is slightly shorter in wavelength compared to Y6 (Supplementary Table 1). Electronic-structure calculations are performed on L8-R and Y6 molecules. As shown in Supplementary Table 2, the calculated absorption maxima $\\lambda_{\\mathrm{max,ab}}$ of the four NFA dimers (geometry extracted from single crystals) are obviously bigger than those of the monomers, and the Y6 dimer has the biggest $\\lambda_{\\mathrm{max,ab}},$ which is consistent with the experimental results. Higher $\\pi{-}\\pi$ stacking overlaps exist in Y6 dimers along the molecular backbone compared to L8-R dimers. Thus Y6 dimers possess the stronger $\\pi{-}\\pi$ stacking interactions, as seen from the results of the non-covalent interaction and the transfer integral calculations using the dimer structures in crystals (Supplementary Figs. 6 and 7), which leads to a stronger electronic coupling of the monomers and a narrower energy gap between the highest occupied molecular orbital (HOMO) and the LUMO for the dimer. As shown in Supplementary Figs. 8 and 9, the HOMO and LUMO become highly symmetric and delocalized in the Y6 dimer, which accounts for the red-shift of absorption in the thin film. The optical bandgaps of L8-BO, L8-HD and L8-OD were determined to be 1.40, 1.43 and $1.42\\mathrm{eV},$ respectively, slightly larger than that of Y6 $(1.35\\mathrm{eV})$ . The electrochemical properties of L8-R and Y6 were studied by cyclic voltammetry (Supplementary Fig. 10). The energy level diagrams of PM6, Y6 and the L8-R series are displayed in Fig. 1c. The L8-R series exhibited similar HOMO energy levels, which are comparable to Y6. However, they showed upshifted LUMO energy levels compared to Y6, agreeing well with the simulated results (Supplementary Fig. 9). The photophysical properties of Y6 and L8-R are listed in Supplementary Table 1. \n\nTo study the influence of the alkyl chain topology on device performance, OSCs were fabricated. The optimized device conditions are described in the Supplementary Information (Supplementary Figs. 11–13, Supplementary Tables 3–5 and Table 1). As shown in Fig. 1d,e and Table 1, the Y6-based devices showed a PCE of $16.61\\%$ , with a $V_{\\mathrm{oc}}$ of $0.84\\mathrm{V},$ a short-circuit current density $(J_{s c})$ of $25.91\\mathrm{mAcm}^{-2}$ and a FF of $76.0\\%$ . In L8-R-based devices, increased $V_{\\mathrm{oc}}$ values were found, which was ascribed to the upshifted LUMO energy levels in L8-R. Among them, PM6:L8-BO devices showed the best photovoltaic performance, with a high PCE of $18.32\\%$ , with a $V_{\\mathrm{oc}}$ of $0.874\\mathrm{V}_{:}$ a $J_{s c}$ of $25.72\\mathrm{mAcm}^{-2}$ and a FF of $81.5\\%$ . To the best of our knowledge, such PCE and FF values are among the highest values for solution-processed OSCs thus far (Supplementary Table 6), indicating efficient charge transport and reduced charge recombination in L8-BO-based devices. As shown in Fig. 1f and Table 1, the calculated $J_{s c}$ values from external quantum efficiency (EQE) spectra are in good agreement with the $J_{\\mathrm{sc}}$ measured in current density–voltage $\\left(J-V\\right)$ curves. To confirm the reliability of device performance, the best PM6:L8-BO device was sent to the National Institute of Metrology, China, for certification. A certified efficiency of $17.9\\%$ was achieved (Supplementary Figs. 14 and 15). In addition, a PCE of $18.22\\%$ was independently verified by a third-party research group (Supplementary Fig. 16). It was noted that the PM6:L8-BO device exhibited excellent stability under a nitrogen atmosphere. After storage in a nitrogen-filled glove box for 60 days, the device maintained $98\\%$ of its initial PCE value (Supplementary Fig. 17). Moreover, inverted OSCs based on Y6 and L8-R acceptors have been also fabricated (Supplementary Fig. 18 and Table 1) and exhibited comparable PCEs to the devices with the conventional architecture. \n\n
Table 1 | Summary of device parameters of the optimized OSCs
Device structureActive layerV.. (V)Jsc (mA cm-2)FF (%)PCEa (%)
ConventionalPM6:Y60.84 (0.84 ± 0.01)25.91 (25.57± 0.37)76.0 (75.7 ± 0.9)16.61 (16.27 ± 0.17)
PM6:L8-BO0.87 (0.87± 0.01)25.72 (25.66±0.27)81.5 (80.5 ± 0.9)18.32 (17.97 ± 0.18)
PM6:L8-HD0.88 (0.88 ± 0.01)25.08 (24.87±0.29)78.8 (78.0 ±1.0)17.39 (17.09 ± 0.20)
PM6:L8-OD0.89 (0.89 ± 0.01)24.57 (24.61± 0.23)74.6 (73.9 ± 1.1)16.26 (15.93 ± 0.17)
PM6:L8-BO0.8725.3881.017.9b
PM6:Y60.85 (0.85 ± 0.01)25.52 (25.46±0.20)74.6 (74.3 ± 1.1)16.11 (15.95 ± 0.18)
InvertedPM6:L8-BO0.87 (0.87 ± 0.01)26.28 (25.99 ± 0.38)79.4 (78.9 ± 0.6)18.05 (17.89 ± 0.21)
PM6:L8-HD0.87 (0.88 ± 0.01)25.59 (25.38±0.26)77.9 (77.3 ± 0.7)17.32 (17.16 ± 0.18)
PM6:L8-OD0.88 (0.89 ± 0.01)25.28 (25.12±0.10)71.1 (70.1 ± 1.2)15.80 (15.62 ± 0.17)
\n\nThe error bars correspond to the standard deviation of multiple independent solar cells. aThe average parameters were calculated from 30 and 10 independent cells for conventional and inverted devices, respectively. bCertified by National Institute of Metrology, China. \n\nTo study the charge transport properties in OSCs, the hole/electron mobilities of the optimized PM6:NFA blended films were evaluated by using a space-charge-limited current method. As shown in Supplementary Fig. 19 and Supplementary Table 7, the hole/electron mobilities $(\\mu_{\\mathrm{h}}/\\mu_{\\mathrm{e}})$ of the PM6:Y6, PM6:L8-BO, PM6:L8-HD and PM6:L8-OD blended films were $1.82\\times10^{-4}/3.71\\times10^{-4}\\mathrm{~;~}$ , $3.58\\times10^{-4}/5.79\\times10^{-4}$ , $1.75\\times10^{-4}/4.62\\times10^{-4}$ and $1.61\\times10^{-4}/$ $2.31\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1};$ which correspond to $\\mu_{\\mathrm{h}}/\\mu_{\\mathrm{e}}$ ratios of 2.04, 1.62, 2.64 and 1.43, respectively. The high and balanced charge transport in the L8-BO-based blended film was conducive to prohibit charge accumulation and recombination, thus endowing the corresponding device with a higher FF of $81.5\\%$ . \n\nTo evaluate the charge generation and exciton dissociation in these OSCs, the dependence of the photocurrent density $(J_{\\mathrm{ph}})$ on the effective voltage $(V_{\\mathrm{eff}})$ was measured. The exciton dissociation probability $(P_{\\mathrm{diss}})$ , determined from $J_{\\mathrm{ph}}$ under the short-circuit condition divided by the saturated photocurrent density $(J_{\\mathrm{sat}})$ , was estimated to be $98.5\\%$ , $99.3\\%$ , $98.9\\%$ and $97.8\\%$ for the OSCs based on Y6, L8-BO, L8-HD and L8-OD, respectively (Supplementary Fig. 20a). To probe the charge recombination behaviour in the devices, the dependence of $V_{\\mathrm{oc}}$ on the light intensity $(P_{\\mathrm{light}})$ was examined (Supplementary Fig. 20b). When the slope of $\\bar{V}_{\\mathrm{oc}}$ versus the natural logarithm of $P_{\\mathrm{light}}$ is equal to $k T/q$ (where $k$ is the Boltzmann constant, $T$ is the Kelvin temperature and $q$ is the elementary charge), bimolecular recombination is the dominant recombination mechanism. The slope values from the Y6, L8-BO, L8-HD and L8-OD devices were determined to be 1.20, 1.09, 1.18 and $1.32k T/q$ , respectively. The slope value of L8-OD-based devices increases significantly, suggesting that trap-assisted recombination plays a major role. To confirm the recombination mechanism, we further performed transient photo-voltage measurements to examine the lifetime of photo-carriers in OSCs (Supplementary Fig. 21). The transient photo-voltage decay time can be correlated to the slope values in the $\\ln(P_{\\mathrm{light}})-\\bar{V}_{\\mathrm{oc}}$ plot. For the L8-OD based device, the shortest decay time was observed, indicating a reduction of carrier lifetime. This behaviour is caused by the higher trap density that accelerates recombination. By contrast, the L8-BO device exhibits the longest carrier lifetime, indicating suppressed recombination, which contributes to the enhanced FF and improved PCE in L8-BO-based OSCs. \n\n# Molecular packing in crystal and thin film \n\nSingle crystals of L8-BO, L8-HD and L8-OD were cultivated to investigate the chemical modification and its impact on intermolecular packing (Supplementary Table 8). Similar molecular conformations are seen regardless of the side-chain size. In a crystal, the molecules show a planar backbone due to the non-covalent S–O interaction that constrains the backbone planarity. The branched alkyl chains show a disordered arrangement, protruding out from the backbone plane to interact with adjacent side chains to condense (Fig. 2a and Supplementary Fig. 22). These molecules assemble via backbone stacking to form linear transport channels via $\\pi{-}\\pi$ stacking. Although similar in structure compared to Y6, L8-R packs differently in the solid state. As seen in Fig. 2b, L8-R forms a molecular arrangement with small ellipse-shaped voids from a tilted $a$ -axis projection, which is different from the Y6 packing that forms orthorhombic vacancies in the $c$ -axis projection. Such a change originates from the difference in the alkyl chain’s spacial arrangement and packing symmetry. As seen from Supplementary Fig. 22, the L8-R side chain in the single crystal tilts out of the conjugated plane, and interacts with adjacent chains at different heights to condense. The Y6 side chain is less crowded in density, and tilts out with a small angle and resides largely in-plane. The Y6 side chain interacts more favourably with in-plane molecules and thus forms large orthorhombic voids. In the molecular arrangement, Y6 molecules pack in mirror symmetry, and L8-R molecules pack in rotational symmetry to suit the side-chain interaction and backbone stacking (Supplementary Fig. 23). The combination of these factors leads to a different molecular packing motif in the crystal, which induces different electronic and transport properties in films. In addition, the difference in side-chain length gives rise to different void sizes. As seen from Fig. 2a,b, increasing the side-chain length reduces the marked lateral distances and increases the marked vertical distances. The packing coefficients for L8-BO, L8-HD and L8-OD are $64.1\\%$ , $64.2\\%$ and $63.7\\%$ , respectively, and this value is $54.5\\%$ for Y6 (Supplementary Table 9). Thus, a more condensed molecular assembly exists in L8-R molecules. \n\n![](images/f3e61709443e1aee8b09289d5ff415ce67fbb5361f458a3931fa68e3ea15f68e.jpg) \nFig. 2 | Single-crystal structures and molecular packing properties of NFAs. a, The main view of a molecular conformation sketch of L8-BO, L8-HD, L8-OD and Y6 according to single-crystal data. The dashed lines represent the side-chain self-assembly distance of NFAs. b, The main view of a molecular packing sketch of L8-BO, L8-HD, L8-OD and Y6. For L8-R, the horizontal value represents the (101) plane distance, and the vertical value represents the b axis parameter of the unit cell. For Y6, the horizontal and vertical values represent the $a$ axis and half of the b axis parameters of the unit cell, respectively. c, Two-dimensional GIWAXS diffraction patterns of L8-BO, L8-HD, L8-OD and Y6 neat films. The (021) and (11¯) diffraction peaks represent the intermolecular distance between the respective crystal miller index planes in the L8-R series, respectively, and the (110) and (11¯) diffraction peaks represent the lamellar distance and intermolecular distance between the respective crystal miller index planes in the Y6 film, respectively. The colour bar shows the scattering sign intensity from detectors in arbituary units. d,e, The $55^{\\circ}$ -tilted line-cut (L8-R, dashed lines), in-plane line-cut (Y6, dashed lines) and out-of-plane line-cut (solid lines) profiles of L8-BO, L8-HD, L8-OD and Y6 neat films (d) and the blend films (e). \n\nAnother feature of side-chain substitution is that the close molecular interaction can be modified. In this case, the average $\\pi{-}\\pi$ distances were seen changing from $3.19\\mathring\\mathrm{A}$ to $3.40\\mathring\\mathrm{A}$ with short- to long-branched side chains (Supplementary Fig. 24 and Supplementary Table 9), and such a value for Y6 is $3.2\\dot{0}\\mathring{\\mathrm{A}}$ . Moreover, we find that the Y6 single crystal exhibits two $\\pi{-}\\pi$ packing forms. By contrast, the L8-BO single crystal exhibits three $\\pi{-}\\pi$ packing motifs, which can provide more charge-hopping channels (Supplementary Fig. 7). Although the L8-BO dimers have smaller $\\pi{-}\\pi$ stacking overlaps, their electronic couplings are not much smaller than those of Y6 dimers due to the smaller average $\\pi{-}\\pi$ stacking distances. As a result, multiple charge-hopping pathways and a relatively strong electronic coupling enable a L8-BO with high electron mobilities in the thin film (Supplementary Table 7). These results reveal the success of substitution at the thiophene beta position in manipulating the molecular packing in the solid state. Thus, though L8-R and Y6 possess identical conjugated backbones, their solid-state characteristics differ significantly in packing position and distances, leading to absorption shifts and charge transport differences in thin films. \n\nThe success of the branched side-chain design strategy persuades us to explore other Y6-type NFAs. Several other materials and the corresponding device performances are shown in Supplementary Fig. 25 and Supplementary Table 10. Exciting results were observed, from which we note that this approach can be extended to NFAs with different atom decorations and different molecular symmetries. Thus, the branched side-chain design strategy is of general purpose in the design of NFAs with the Y6-type backbone. \n\nThe thin-film crystalline feature of L8-R neat films was studied using the GIWAXS technique. In a two-dimensional GIWAXS pattern (Fig. 2c), a strong scattering intensity along the out-of-plane $(q_{z})$ direction was seen in L8-R neat films, stronger than that in the Y6 neat film after signal normalization. In $55^{\\circ}$ -tilted line-cut profiles (Fig. 2d) and the two-dimensional diffraction pattern, all the L8-R neat films adopted a preferentially face-on orientation, as evidenced by the strong $\\pi{-}\\pi$ stacking diffraction peak in the out-of-plane direction and alkyl chain lamellar diffraction peak (11¯) in the in-plane $(q_{x y})$ direction. The appearance of a (021) diffraction peak off the major planes indicates the unit cell orientation on the substrate, by taking a tilted orientation with molecular end groups towards the substrate. From L8-BO, to L8-HD, to L8-OD neat films, the locations of the alkyl chain lamellar and $\\pi{-}\\pi$ stacking diffraction peaks were gradually shifted to lower $q$ values, corresponding to gradually increased lamellar and $\\pi{-}\\pi d$ spacings. The crystal coherence length estimated from the $\\pi{-}\\pi$ stacking diffraction peak decreased with increasing branched alkyl chain length (Supplementary Table 11). The L8-R in the single crystal showed closer $\\pi{-}\\pi$ stacking than in thin films, indicating the influence of processing on molecular self-assembly. Compared with Y6, the L8-BO neat thin film featured a broad $\\pi{-}\\pi$ stacking peak, with a smaller crystal coherence length, which can be caused by paracrystalline disorder in the $\\mathrm{film}^{38,39}$ . Although the Y6 neat thin film displayed a sharp stacking peak, it had an obvious diffraction signature located at $1.4\\mathrm{A}^{-1}$ , corresponding to the amorphous content in the thin film. The detailed structure information is summarized in Supplementary Fig. 26 and Supplementary Table 12. Based on these observations, it is obvious that the structural order of L8-BO is better than that of Y6. This result is in good accordance with the DSC measurement. A space-charge-limited current method was used to evaluate electron transport in the L8-R thin films. As shown in Supplementary Fig. 19c and Supplementary Table 7, the L8-BO neat film exhibited an electron mobility of $6.79\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1};$ , which is slightly higher than that in the Y6 neat film $\\left(4.49\\times10^{-4}{\\mathrm{cm}}^{2}\\mathrm{V}^{-1}{\\mathrm{s}}^{-1}\\right)$ , and the electron mobility of L8-R decreased in sequence with the increase of the branched alkyl chain lengths, from L8-BO to L8-OD. \n\n![](images/e49f118099bc787b45974b5faff1131d809eee2f84a7225cd9b03cb4a61eaa05.jpg) \nFig. 3 | Morphology characterization of blend films. a–h, AFM height and phase images of optimized PM6:Y6 (a and e), PM6:L8-BO (b and f), PM6:L8-HD (c and g) and PM6:L8-OD (d and h) films. The root-mean-square roughness values are 1.05, 1.11, 1.61 and $6.52\\mathsf{n m}$ for PM6:Y6, PM6:L8-BO, PM6:L8-HD and PM6:L8-OD films, respectively. \n\n# Morphology investigation \n\nGIWAXS, atomic force microscopy (AFM) and transmission electron microscopy (TEM) were performed to investigate the influence of branched alkyl chain substitution on the active layer morphology. As shown in Supplementary Fig. 27, all the blend films adopt a face-on orientation with an intense $\\pi{-}\\pi$ diffraction peak in the out-of-plane direction and pronounced lamellar diffraction peak in the in-plane direction. The overlapping of peaks at similar positions makes the quantitative analysis difficult. A strong diffraction peak located at $\\dot{0.32\\mathring\\mathrm{A}}$ is seen in all blended films in the in-plane direction, corresponding to a lamellar interchain $d$ spacing of $19.5\\mathring\\mathrm{A}$ , which comes from PM6 (100) diffraction in the L8-R blends and a combination of PM6 (100) and Y6 (110) diffraction in the Y6 blends (Fig. 2e and Supplementary Fig. 28). The Y6 blend film exhibited a sharper $\\pi{-}\\pi$ diffraction peak and an enlarged crystal coherence length of $24.7\\mathring\\mathrm{A}$ which was higher than those in the L8-R blend films (which ranged from $17.4\\mathring\\mathrm{A}$ to $18.4\\mathring\\mathrm{A}$ ; Supplementary Table 11). In the L8-R blend films, the $\\pi{-}\\pi$ stacking $d$ spacing was increased gradually when the branched alkyl chain length increased in sequence. Thus the L8-BO blended film had the tightest $\\pi{-}\\pi$ stacking of the L8-R blended thin films. The L8-BO in blends showed the most distinctive (021) diffraction peak compared to longer-side-chain analogues (a crystal coherence length of $4.3\\mathrm{nm}$ in blends compared to that of $2.8\\mathrm{nm}$ in the neat film). Thus, L8-BO is the most effective at preserving the packing structure as in the single crystal, which results from its high tendency to order, due to its short side chains. \n\nAFM measurements were used to investigate the surface morphology of bulk-heterojunction blends. As illustrated in Fig. 3, a fibrillar network morphology was seen in all blended films, which is favourable for charge transport30,40. The root-mean-square roughness increased from PM6:Y6 $(1.05\\mathrm{nm})$ to PM6:L8-R blends (PM6:L8-BO, 1.11 nm; PM6:L8-HD, $1.61\\mathrm{nm};$ ; and PM6:L8-OD, $6.52\\mathrm{nm}\\rangle$ . The increased roughness was ascribed to the L8-R crystallization that protrudes out of the surfaces. Meanwhile, the PM6:Y6 and PM6:L8-BO surfaces were quite homogeneous, as shown in phase images of fibril networks. PM6:L8-HD started to develop large NFA crystals, which was seen as a bright area in a height image. The NFA crystallization was so strong in the PM6:L8-OD blends that crystals of a hundred-nanometre size were probed. This feature originates from the readily crystallizable nature of the long-chain L8-R, from long-chain interactions. A thermal annealing treatment (Supplementary Figs. 29 and 30) was carried out to investigate NFA crystallization in blended thin films. No serious NFA crystallization was seen in the PM6:L8-BO blends, indicating good morphology stability. The PM6:L8-BO blends form small crystallites buried in between the fibril network, as evidenced by the tiny bright spots seen in the height image. Such details establish a multi-length scaled morphology, constructed by the PM6 fibril, the NFA crystallites and a mixing region background. In this sense, tuning the crystallization of acceptor materials is a useful approach in optimizing the blended thin-film morphology to suit light extraction and carrier transport purposes. \n\nThe surface morphology from AFM characterization was further supported by TEM characterization. As seen in Supplementary \n\n
Table 2 | Detailed energy loss of the OsCs based on PM6:NFA
Active layerEgap Voc (eV) (eV)Eloss (eV)vSb (V)△E (eV)Vrade (V)(eV) △E2△Ed (eV)
PM6:Y61.390.840.56 1.120.271.080.040.25
PM6:L8-BO1.420.87 0.551.160.271.110.050.24
PM6:L8-HD1.43 0.880.551.170.271.120.050.25
PM6:L8-OD1.420.89 0.531.160.271.110.050.22
\n\n${}^{\\mathsf{a}}E_{\\mathsf{a}\\mathsf{p}}$ is the optical bandgap of the film calculated on the basis of the intersections between the normalized absorption and EL spectra of films. $^\\mathrm{{b}}V_{\\mathrm{{oc}}}^{\\mathrm{{SQ}}}$ is the maximum $V_{\\infty}$ by the SQ limit. $^\\mathrm{c}V_{\\mathrm{oc}}^{\\mathrm{rad}}$ is the $V_{\\infty}$ when there is only radiative recombination. $^{\\mathrm{d}}\\Delta E_{3}$ is calculated from the $\\mathsf{E Q E}_{\\mathsf{E L}}$ measuredocby a silicon detector. \n\nFig. 31, Y6 and L8-BO blend films formed nanoscale phase separation and bicontinuous networks, while the L8-HD and L8-OD blended films showed large, black NFA crystals. The PM6:L8-BO film showed a large density of small black crystallites, commensurate in size with the fibre network characteristic length, and thus it is believed to have the best morphology in the L8-R material family. \n\n# Energy loss analysis \n\nTo investigate the impact of alkyl chain length and topology on $E_{\\mathrm{loss}},$ we measured the optical bandgap $(E_{\\mathrm{gap}})$ of blended films from the derivatives of the EQE spectra41. As presented in Supplementary Fig. 32, the $E_{\\mathrm{gap}}$ of the blend films based on Y6, L8-BO, L8-HD and L8-OD were 1.39, 1.42, 1.43 and $1.42\\mathrm{eV},$ respectively. We then calculated the total energy loss following the equation $E_{\\mathrm{loss}}{=}E_{\\mathrm{gap}}{-}q V_{\\mathrm{oc}}{.}$ As summarized in Table 2, Y6-based OSCs showed an $E_{\\mathrm{loss}}$ of $0.56\\mathrm{V},$ and L8-BO-based OSCs exhibited an $E_{\\mathrm{loss}}$ of $0.55\\mathrm{V},$ which is among the lowest $E_{\\mathrm{loss}}$ values for highly efficient $\\mathrm{OSC}s^{6,42}$ . \n\nWe then quantitatively analysed the detailed $E_{\\mathrm{loss}}$ components. According to the theory of detailed balance43, the $E_{\\mathrm{loss}}$ could be classified into three different constituents $(\\underbar{E}_{{\\mathrm{loss}}}=\\Delta E_{1}+\\Delta E_{2}+\\Delta E_{3})$ . The first constituent $(\\Delta E_{1}=E_{\\mathrm{gap}}-q V_{\\mathrm{oc}}^{\\mathrm{SQ}})$ ssis deΔfiEn1ed aΔsEt2he diΔffEe3rence between $E_{\\mathrm{gap}}$ andΔEth1e SEhgoacpkleyq–VQocueisser (SQ) limit output voltage $(V_{\\mathrm{oc}}^{\\mathrm{SQ}})$ , which is caused by the radiative recombination loss above theVbocandgap. For any types of solar cells, this $\\Delta E_{1}$ is unavoidable and is typically $0.25\\mathrm{V}$ or above. Here, the L8-R-based OSCs showed the same $\\Delta E_{1}$ value $(0.27\\mathrm{V})$ as that in Y6-based OSCs. The $\\ensuremath{V_{\\mathrm{oc}}^{\\mathrm{SQ}}}$ values were then calculated to be 1.12, 1.16, 1.17 and $1.16\\mathrm{V}$ fVorcthe OSCs based on Y6, L8-BO, L8-HD and L8-OD, respectively. The second constituent $(\\Delta E_{2}=q V_{\\mathrm{oc}}^{\\mathrm{SQ}}-q V_{\\mathrm{oc}}^{\\mathrm{rad}}=q\\Delta V_{\\mathrm{oc}}^{\\mathrm{ra\\dot{d}}})$ stems from radiative recombinatioΔnE2lossqbVeolcow tqhVeocbandqgaΔp,Vowc here the $V_{\\mathrm{oc}}^{\\mathrm{rad}}$ can be determined by realistic radiative recombination using a reciprocity relation between Fourier transform photocurrent spectroscopy-EQE (FTPS-EQE) and electroluminescence spectroscopy (EL). As shown in Fig. 4, the $V_{\\mathrm{oc}}^{\\mathrm{rad}}$ values of the OSCs based on Y6, L8-BO, L8-HD and L8-OD wVeorce calculated to be 1.08, 1.11, 1.12 and 1.11 V, respectively, which corresponded to $\\Delta E_{2}$ values of 0.04, 0.05, 0.05 and $0.05\\mathrm{eV},$ respectively. The third constituent $(\\Delta E_{3}=q V_{\\mathrm{oc}}^{\\mathrm{rad}}-q V_{\\mathrm{oc}}=q\\Delta V_{\\mathrm{oc}}^{\\mathrm{non-ra\\acute{d}}}=-\\dot{k}\\dot{T}\\mathrm{ln}(\\mathrm{EQE_{\\mathrm{EL}}}))$ originates frΔoEm noqn-VroacdiatiqvVe recoqmΔbiVnoaction loss, ckaTnl nbeEdQirEeEcLtly calculated from the EQE of EL $(\\mathrm{EQE_{\\mathrm{EL}}})$ ) and is the dominating and challenging factor among the three constituents14,44. It was found that the OSCs based on Y6 with an linear alkyl chain exhibited a small $\\Delta E_{3}$ value of $0.25\\mathrm{V}.$ In L8-R, as the branched alkyl chain length increased, the $\\Delta E_{3}$ value increased. When comparing with the Y6-based OSCs, all the L8-R-based OSCs showed reduced $\\Delta E_{3}$ values except L8-HD, indicating that the branched chain substitution at the thiophene beta position provides a useful mechanism to suppress the non-radiative recombination loss. The best-performing OSC, based on L8-BO, shows a slightly decreased $\\Delta E_{3}$ when compared with Y6-based OSCs. The OSCs based on L8-OD with the longest branched alkyl chain length exhibited an extremely low $\\Delta E_{3}$ value of $0.22\\mathrm{eV},$ close to that $_{(0.18\\mathrm{eV})}$ of crystalline silicon solar cells45. \n\n![](images/c507acc34e92e706af8248f92ec6de448470a98c85d009730bf7fa8dce0b66ff.jpg) \nFig. 4 | Energy loss analysis in PM6:NFA solar cells. a–d, Semilogarithmic plots of normalized EL and normalized FTPS-EQE (solid lines), and of reciprocally calculated EL and EQE (dotted and dashed lines, respectively) as a function of energy for OSCs based on PM6:NFA blends. The ratio of $\\phi_{\\mathtt{E L}}$ and $\\phi_{\\tt B B}$ was used to calculate the EQE while the product of FTPS-EQE and $\\phi_{\\tt B B}$ was used to calculate the EL, where $\\phi_{\\mathtt{E L}}$ and $\\phi_{\\tt B B}$ represent the emitted photon flux and the room-temperature black body photon flux, respectively. \n\n# Conclusions \n\nWe explored the alkyl chain chemistry in high-performance NFAs. Electronic structure, molecular ordering and intermolecular packing can be well tailored. The thiophene beta position is an interesting spot to consider since the major $\\pi{-}\\pi$ stacking occurs nearby, and introducing bulky branched substituents was considered. L8-BO with its 2-butyloctyl side chain shows better structural order that helps to build an optimized, multi-length-scale morphology, in which high carrier generation, low charge recombination and balanced charge transport are achieved. Such properties lead to high-performance OSCs with simultaneously reduced $E_{\\mathrm{loss}},$ high $J_{s c}$ and high FF, showing unprecedented efficiency. The L8-BO gives blue-shifted thin-film absorption and an upshifted LUMO energy level, which better matches with the PM6 donor that reduces the charge transfer driving force as well as non-radiative energy loss to improve $V_{\\mathrm{oc}}$ without serious sacrifice of $J_{s c}$ . The single-junction OSCs based on L8-BO afforded a remarkably high PCE of $18.32\\%$ , with a FF of $81.5\\%$ and an $E_{\\mathrm{loss}}$ of $0.55\\mathrm{V},$ which represents an advance in high-efficiency NFA development. We believe that such a strategy is useful, as shown by our initial efforts, and can be extended in material design, where material chemistry must be combined with the aspects of self-assembly and morphology to best explore the overall performance. \n\n# Methods \n\nMaterials. Polymer donor PM6 and NFA Y6 were purchased from Solar Materials. The 3-bromothieno[3,2-b]thiophene, 4,7-dibromo-5,6-dinitrobenzo[c] [1,2,5]thiadiazole and 2-(5,6-difluoro-3-oxo-2,3-dihydro-1H-inden-1-ylidene) malononitrile were purchased from Hyper. Diethyl ether $\\mathrm{(Et_{2}O)}$ was freshly distilled before use from sodium using benzophenone as the indicator. The other reagents and chemicals were purchased from commercial sources and used as received unless otherwise noted. The detailed synthetic procedures of L8-R, LC333 and LC301 and the corresponding structural characterizations can be found in the Supplementary Information (Supplementary Figs. 1, 2 and 34–81). \n\nSingle-crystal growth. Single crystals of L8-BO, L8-HD and L8-OD were grown by the liquid diffusion method at room temperature. A moderate amount of ethanol was transferred into concentrated toluene solution, and the crystals were formed on the inner glassy tube over time. The single-crystal diffraction was collected at $100{-}150\\mathrm{K}$ following a standard procedure to reduce X-ray radiation damage. Temperature-dependent X-ray diffraction measurements were carried out to study the temperature effect on lattice expansions. The same crystal structures were preserved for Y6 and L8-BO at different temperatures (Supplementary Fig. 33), and the lattice expansions were fairly small. Only the $\\pi{-}\\pi$ stacking region in Y6 showed noticeable changes. Thus, there was no major shifting in peak position or lattice structure changes within the temperature range $150{-}300\\mathrm{K}.$ The single-crystal growth of Y6 was reported in the literature46. The detailed crystal data are summarized in Supplementary Table 8. \n\nThermogravimetric analysis. Thermogravimetric analysis (TGA) measurements were recorded on a TGA Q50 instrument with a heating rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ under a nitrogen atmosphere. \n\nDSC. DSC measurements were performed on a PerkinElmer Diamond DSC instrument with a heating rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ under a nitrogen atmosphere. \n\nUV–visible absorption. UV–visible–near-infrared absorption spectra were recorded on a Shimadzu (model UV-3700) UV–visible–near-infrared spectrophotometer. \n\nCyclic voltammetry. Cyclic voltammetry measurements were carried out under a nitrogen atmosphere at a scan rate of $100\\mathrm{mVs^{-1}}$ using a Zahner IM6e Electrochemical workstation. A platinum plate coated with the sample film, a platinum wire and a saturated $\\mathrm{\\Ag/AgCl}$ electrode were employed as a working electrode, a counter electrode and a reference electrode, respectively. The supporting electrolyte was $0.1\\mathrm{M}$ tetra- $n$ -butylammonium hexafluorophosphate $\\left(\\mathrm{Bu}_{4}\\mathrm{NPF}_{6}\\right)$ in anhydrous acetonitrile solution, and the internal standard was ferrocene/ferrocenium $\\mathrm{(Fc/Fc^{+})}$ . The onset oxidation potential of the ferrocene external standard was measured to be $0.42\\mathrm{V}.$ Therefore, the HOMO and LUMO energy levels could be obtained from the following equations: ${\\mathrm{HOMO}}=$ – $-(E_{\\mathrm{ox}}+4.38)\\mathrm{eV}$ and $\\mathrm{LUMO}=-(E_{\\mathrm{red}}+4.38)\\mathrm{eV},$ where $E_{\\mathrm{ox}}$ and $E_{\\mathrm{red}}$ are the onset oxidation potential and onset reduction potential relative to $\\mathrm{Ag/AgCl}$ respectively. \n\nAFM. AFM measurements were performed using a Dimension Icon AFM instrument (Bruker) in the tapping mode. \n\nTEM. TEM measurements were carried out on a JEOL JEM-1400 transmission electron microscope. \n\nGIWAXS. GIWAXS measurements were carried out at beamline 7.3.3 at the Advanced Light Source, Lawrence Berkeley National Laboratory. \n\nFTPS. The FTPS-EQE measurements were performed with a modified Bruker Vertex 70 Fourier transform infrared spectrometer equipped with a tungsten lamp and a quartz beam-splitter, using the solar cell as the external detector. A current–voltage amplifier (SR570) was used to amplify the photocurrent produced from the solar cell. The output voltage of the current amplifier was fed back to the external input port of the Fourier transform infrared spectrometer for the Fourier transform. The FTPS spectra were calibrated by a standard silicon or germanium detector. \n\nEL. The EL spectra were measured using a Shamrock SR-303i spectrometer from Andor Tech with a Newton EM-CCD Si and an iDus InGaAs array detector at $-60^{\\circ}\\mathrm{C}$ . The bias of the EL measurement was applied on the devices using a Keithley 2400 SourceMeter. The emission spectrum of the OSCs was recorded at currents smaller or similar to the $J_{\\scriptscriptstyle\\mathrm{SC}}$ of the device at 1 sun illumination. \n\n$\\mathbf{EQE}_{\\mathrm{EL}}$ measurements. $\\mathrm{EQE_{\\mathrm{EL}}}$ values were obtained from an in-house-built system including a Hamamatsu silicon photodiode 1010B, a Keithley 2400 SourceMeter to provide voltage and injected current, and a Keithley 485 Picoammeter to measure the emitted light intensity. \n\nDetails of optical $E_{\\mathrm{gap}}$ determination. As reported in the previous literature41, an EQE is interpreted as a superposition of a distribution of step functions with a step at $E_{\\mathrm{gap}}$ having a certain probability distribution. This probability distribution can be obtained from the derivative dEQE/dE. The part where the probability is greater than half of the maximum is integrated to get an average bandgap. \n\nDevice development and testing. OSCs were fabricated with a conventional architecture of indium tin oxide (ITO)/poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS)/active-layer/poly[(9,9-bis( $3^{\\prime}$ -((N,N-dimethyl)- N-ethylammonium)propyl)-2,7-fluorene)-alt- $^{5,5^{\\prime}}$ -bis( $^{2,2^{\\prime}}$ -thiophene)- 2,6-naphthalene-1,4,5,8-tetracaboxylic-N,N′-di(2-ethylhexyl)imide]dibromide (PNDIT-F3N-Br)/Ag. The ITO-coated glass substrates were sequentially cleaned in detergent, deionized water, acetone and isopropyl alcohol for $15\\mathrm{min}$ each at room temperature. A $40\\mathrm{-nm}$ -thick PEDOT:PSS layer was first spin-cast on top of the ITO substrates at $4{,}000\\mathrm{r.p.m}$ . for 30 s and then annealed on a hotplate at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ under ambient conditions. The blend solutions were prepared by dissolving PM6 and NFAs in chloroform solvent with different weight ratios and 1,8-diiodooctane contents. The total concentration of all active layer solutions was maintained at $15.4\\mathrm{mg}\\mathrm{ml^{-1}}$ . The active layers were generated by spin-coating the blend solutions (the volume used per round is $17\\upmu\\mathrm{l})$ at a spin-coating rate of $_{3,000\\mathrm{r.p.m}}$ . for 30 s on the top of PEDOT:PSS with an optimal thickness of $130\\mathrm{nm}$ , and then were thermally annealed at $100^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ in a $\\Nu_{2}$ -filled glove box. A thin layer $(\\sim5\\mathrm{{nm})}$ of PNDIT-F3N-Br in trifluoroethanol with a concentration of $0.5\\mathrm{mg}\\mathrm{ml}^{-1}$ was spin-cast on the top of the active layer at a spin-coating rate of $_{3,000\\mathrm{r.p.m}}$ . for 30 s. Finally, a $150\\mathrm{-nm}$ -thick Ag electrode was thermally deposited under vacuum conditions of $2\\times10^{-4}\\mathrm{Pa}$ . The inverted OSCs were fabricated with a device structure of ITO/ZnO/active-layer $/\\mathrm{MoO}_{3}/\\mathrm{Ag}$ The $\\mathrm{znO}$ precursor was prepared by dissolving $_{1\\mathrm{g}}$ zinc acetate dihydrate and $280\\upmu\\mathrm{l}$ ethanolamine in $20\\mathrm{ml}$ of 2-methoxyethanol under stirring overnight for the hydrolysis reaction. The ZnO layer was formed by spin-coating the $Z\\mathrm{nO}$ precursor solution onto ITO substrates and then was annealed at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ under ambient conditions. The processing conditions of the active layers were the same as with the conventional OSCs. $\\mathbf{MoO}_{3}$ ( $\\mathrm{\\Delta}5\\mathrm{nm})$ and Ag ( $\\cdot120\\mathrm{nm})$ layers were prepared by vacuum evaporation deposition under vacuum conditions of $2\\times10^{-4}$ Pa. A photon mask with a well-defined aperture size was used in the cell measurement to reduce the light piping and internal-scattering-induced edge effect to access $J_{s c}$ more accurately47. The active area of the device was $5.12\\mathrm{mm}^{2}$ , and the mask area was $3.152\\mathrm{mm}^{2}$ ; thus the opening ratio was $61.6\\%$ . The series resistance in the L8-BO-based device was calculated to be $1.78\\Omega\\mathrm{cm}^{2}$ . Considering the relatively large aperture opening ratio and the low series resistance, the FF overestimation in the PM6:L8-BO device was only ${\\sim}1\\%$ , which validates the accuracy of the FF and efficiency measurements48. \n\nThe solar-cell performance test used an Air Mass 1.5 Global $\\mathrm{\\Omega}^{\\prime}\\mathrm{AM}\\mathrm{\\Omega}1.5\\mathrm{G})$ solar simulator (SS-F5-3A, Enlitech) with an irradiation intensity of $100\\mathrm{mW}\\mathrm{cm}^{-2}$ , which was measured by a calibrated silicon solar cell (SRC2020, Enlitech). The $J{-}V$ curves were measured along the forward scan direction from $-0.5$ to 1 V, with a scan step of $50\\mathrm{mV}$ and a dwell time of $10\\mathrm{ms}$ , using a Keithley 2400 Source Measure Unit. EQE spectra were measured by using a solar-cell spectral-response measurement system (QE-R3011, Enlitech). \n\nSpace-charge-limited current measurement. The charge transport properties of the neat film and blend film were investigated by a space-charge-limited current method. The hole-only devices were fabricated with a configuration of ITO/ PEDOT:PSS/PM6:NFA/Au, while the electron-only devices were fabricated with a structure of ITO/ZnO/PM6:NFA/PNDIT-F3N-Br/Ag. \n\nThe mobility was determined by fitting the dark current with the Mott– Gurney law described as $J{=}9\\varepsilon_{\\mathrm{0}}\\varepsilon_{\\mathrm{r}}\\mu V^{2}/8L^{3}$ , where $J$ is the current density, $\\scriptstyle{\\varepsilon_{0}}$ is the permittivity of free space, $\\varepsilon_{\\mathrm{r}}$ is the permittivity of the active layer, $\\mu$ is the hole mobility $(\\mu_{\\mathrm{h}})$ or electron mobility $(\\mu_{\\mathrm{e}})$ , $V$ is the effective voltage $(V=V_{\\mathrm{appl}}-V_{\\mathrm{bi}}-V_{\\mathrm{R}},$ where $V_{\\mathrm{appl}}$ is the applied voltage, $V_{\\mathrm{bi}}$ is the built-in potential and $V_{\\mathrm{{R}}}$ is the voltage loss on series resistance) and $L$ is the film thickness of the neat film or blend film. \n\nReporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nSource data are provided with this paper. All other data generated or analysed during this study are included in the published article and its Supplementary Information. The X-ray crystallographic coordinates for structures reported in this study have been deposited at the Cambridge Crystallographic Data Centre (CCDC), under deposition numbers 2005533–2005535. These data can be obtained free of charge from the Cambridge Crystallographic Data Centre via www.ccdc. cam.ac.uk/data_request/cif. \n\n# Received: 10 June 2020; Accepted: 18 March 2021; Published online: 10 May 2021 \n\n# References \n\n1.\t Zhang, J., Tan, H. S., Guo, X., Facchetti, A. & Yan, H. Material insights and challenges for non-fullerene organic solar cells based on small molecular acceptors. Nat. Energy 3, 720–731 (2018). \n2.\t Zhang, G. et al. Nonfullerene acceptor molecules for bulk heterojunction organic solar cells. Chem. Rev. 118, 3447–3507 (2018). \n3.\t Yan, C. et al. Non-fullerene acceptors for organic solar cells. Nat. Rev. Mater. \n3, 18003 (2018). \n4.\t Cheng, P., Li, G., Zhan, X. & Yang, Y. Next-generation organic photovoltaics based on non-fullerene acceptors. Nat. Photon. 12, 131–142 (2018). \n5.\t Wadsworth, A. et al. Critical review of the molecular design progress in non-fullerene electron acceptors towards commercially viable organic solar cells. Chem. Soc. Rev. 48, 1596–1625 (2019). \n6.\t Sun, C. et al. Achieving fast charge separation and low nonradiative recombination loss by rational fluorination for high-efficiency polymer solar cells. Adv. Mater. 31, 1905480 (2019). \n7.\t Yan, T. et al. $16.67\\%$ rigid and $14.06\\%$ flexible organic solar cells enabled by ternary heterojunction strategy. Adv. Mater. 31, 1902210 (2019). \n8.\t Sun, H. et al. A monothiophene unit incorporating both fluoro and ester substitution enabling high-performance donor polymers for non-fullerene solar cells with $16.4\\%$ efficiency. Energy Environ. Sci. 12, 3328–3337 (2019). \n9.\t Li, S., Li, C.-Z., Shi, M. & Chen, H. New phase for organic solar cell research: emergence of Y-series electron acceptors and their perspectives. ACS Energy Lett. 5, 1554–1567 (2020). \n10.\tLiu, L. et al. Graphdiyne derivative as multifunctional solid additive in binary organic solar cells with $17.3\\%$ efficiency and high reproductivity. Adv. Mater. \n32, 1907604 (2020). \n11.\t Liu, Q. et al. $18\\%$ efficiency organic solar cells. Sci. Bull. 65, 272–275 (2020). \n12.\tQian, D. et al. Design rules for minimizing voltage losses in high-efficiency organic solar cells. Nat. Mater. 17, 703–709 (2018). \n13.\tMenke, S. M., Ran, N. A., Bazan, G. C. & Friend, R. H. Understanding energy loss in organic solar cells: toward a new efficiency regime. Joule 2, \n25–35 (2018). \n14.\tHou, J., Inganäs, O., Friend, R. H. & Gao, F. Organic solar cells based on non-fullerene acceptors. Nat. Mater. 17, 119–128 (2018). \n15.\tKawashima, K., Tamai, Y., Ohkita, H., Osaka, I. & Takimiya, K. High-efficiency polymer solar cells with small photon energy loss. Nat. Commun. 6, 10085 (2015). \n16.\t Cui, Y. et al. Over $16\\%$ efficiency organic photovoltaic cells enabled by a chlorinated acceptor with increased open-circuit voltages. Nat. Commun. 10, \n2515 (2019). \n17.\t Liu, S. et al. High-efficiency organic solar cells with low non-radiative recombination loss and low energetic disorder. Nat. Photon. 14, 300–305 (2020). \n18.\tLin, Y. et al. An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174 (2015). \n19.\tLin, Y. et al. A facile planar fused-ring electron acceptor for as-cast polymer solar cells with $8.71\\%$ efficiency. J. Am. Chem. Soc. 138, 2973–2976 (2016). \n20.\tZhao, W. et al. Molecular optimization enables over $13\\%$ efficiency in organic solar cells. J. Am. Chem. Soc. 139, 7148–7151 (2017). \n21.\tMeng, L. et al. Organic and solution-processed tandem solar cells with $17.3\\%$ efficiency. Science 361, 1094–1098 (2018). \n22.\t Sun, J. et al. Dithieno $^{3,2-\\mathrm{b}:2^{\\prime},3^{\\prime}}$ -d]pyrrol fused nonfullerene acceptors enabling over $13\\%$ efficiency for organic solar cells. Adv. Mater. 30, 1707150 (2018). \n23.\tYuan, J. et al. Single-junction organic solar cell with over $15\\%$ efficiency using fused-ring acceptor with electron-deficient core. Joule 3, 1140–1151 (2019). \n24.\tJiang, K. et al. Alkyl chain tuning of small molecule acceptors for efficient organic solar cells. Joule 3, 25100–25107 (2019). \n25.\tLi, C., Fu, H., Xia, T. & Sun, Y. Asymmetric nonfullerene small molecule acceptors for organic solar cells. Adv. Energy Mater. 9, 1900999 (2019). \n26.\tYu, Z.-P. et al. Simple non-fused electron acceptors for efficient and stable organic solar cells. Nat. Commun. 10, 2152 (2019). \n27.\tLi, X. et al. Simplified synthetic routes for low cost and high photovoltaic performance $n$ -type organic semiconductor acceptors. Nat. Commun. 10, 519 (2019). \n28.\tHong, L. et al. Eco-compatible solvent-processed organic photovoltaic cells with over $16\\%$ efficiency. Adv. Mater. 31, 1903441 (2019). \n29.\tLiu, J. et al. Fast charge separation in a non-fullerene organic solar cell with a small driving force. Nat. Energy 1, 16089 (2016). \n30.\tLiu, T. et al. Optimized fibril network morphology by precise side-chain engineering to achieve high-performance bulk-heterojunction organic solar cells. Adv. Mater. 30, 1707353 (2018). \n31.\tYu, R. et al. Improved charge transport and reduced nonradiative energy loss enable over $16\\%$ efficiency in ternary polymer solar cells. Adv. Mater. 31, 1902302 (2019). \n32.\tZhou, Z. et al. Subtle molecular tailoring induces significant morphology optimization enabling over $16\\%$ efficiency organic solar cells with efficient charge generation. Adv. Mater. 32, 1906324 (2020). \n33.\tGao, W. et al. Asymmetrical ladder-type donor-induced polar small molecule acceptor to promote fill factors approaching $77\\%$ for high-performance nonfullerene polymer solar cells. Adv. Mater. 30, 1800052 (2018). \n34.\tZhou, Z. et al. High-efficiency small-molecule ternary solar cells with a hierarchical morphology enabled by synergizing fullerene and non-fullerene acceptors. Nat. Energy 3, 952–959 (2018). \n35.\tFei, Z. et al. An alkylated indacenodithieno[3,2-b]thiophene-based nonfullerene acceptor with high crystallinity exhibiting single junction solar cell efficiencies greater than $13\\%$ with low voltage losses. Adv. Mater. 30, 1705209 (2018). \n36.\tXu, X. et al. Single-junction polymer solar cells with $16.35\\%$ efficiency enabled by a platinum(II) complexation strategy. Adv. Mater. 31, 1901872 (2019). \n37.\tHuang, H. et al. Noncovalently fused-ring electron acceptors with near-infrared absorption for high-performance organic solar cells. Nat. Commun. 10, 3038 (2019). \n38.\tRivnay, J. et al. Quantitative analysis of lattice disorder and crystallite size in organic semiconductor thin films. Phys. Rev. B 84, 045203 (2011). \n39.\tNoriega, R. et al. A general relationship between disorder, aggregation and charge transport in conjugated polymers. Nat. Mater. 12, 1038–1044 (2013). \n40.\tXia, T., Cai, Y., Fu, H. & Sun, Y. Optimal bulk-heterojunction morphology enabled by fibril network strategy for high-performance organic solar cells. Sci. China. Chem. 62, 662–668 (2019). \n41.\tWang, Y. et al. Optical gaps of organic solar cells as a reference for comparing voltage losses. Adv. Energy Mater. 8, 1801352 (2018). \n42.\tSong, J. et al. Ternary organic solar cells with efficiency ${>}16.5\\%$ based on two compatible nonfullerene acceptors. Adv. Mater. 31, 1905645 (2019). \n43.\tShockley, W. & Queisser, H. J. Detailed balance limit of efficiency of $\\boldsymbol{p}$ -n junction solar cells. J. Appl. Phys. 32, 510–519 (1961). \n44.\tNikolis, V. C. et al. Reducing voltage losses in cascade organic solar cells while maintaining high external quantum efficiencies. Adv. Energy Mater. 7, 1700855 (2017). \n45.\tYao, J. et al. Quantifying losses in open-circuit voltage in solution-processable solar cells. Phys. Rev. Appl. 4, 014020 (2015). \n46.\tZhu, L. et al. Efficient organic solar cell with $16.88\\%$ efficiency enabled by refined acceptor crystallization and morphology with improved charge transfer and transport properties. Adv. Energy Mater. 10, 1904234 (2020). \n47.\tEmery, K. & Moriarty, T. Accurate measurement of organic solar cell efficiency. In Proc. Organic Photovoltaics IX (Eds. Kafafi, Z. H. & Lane, P. A.) 70520D (International Society for Optics and Photonics, 2008). \n48.\tKiermasch, D., Gil-Escrig, L., Bolink, H. J. & Tvingstedt, K. Effects of masking on open-circuit voltage and fill factor in solar cells. Joule 3, 16–26 (2019). \n\n# Acknowledgements \n\nThis work was financially supported by the National Natural Science Foundation of China (grant nos 51825301, 21734001, 51973110, 21734009, 21674007, 21733005 and 51761135101), the 111 Project (grant B14009) and Beijing National Laboratory for Molecular Sciences (BNLMS201902). F.G. acknowledges the Swedish Strategic Research Foundation through a Future Research Leader programme (FFL 18-0322). X-ray data were acquired at beamline 7.3.3 at the Advanced Light Source, Lawrence Berkeley National Laboratory, which is supported by the Director, Office of Science, Office of Basic Energy Sciences, of the US Department of Energy under contract no. DE-AC02-05CH11231. \n\n# Author contributions \n\nC.L. designed and synthesized the L8-R acceptors. J.Z. and Z.X. grew the single crystals, and solved and analysed the single-crystal structures of the L8-R acceptors. J.S. fabricated and characterized the devices. J.X., J.Z. and F.L. performed the morphology characterization and analysed the data. H.Z., F.G., J.G. and J.M. performed the EL and FTPS-EQE experiments and analysed the data. X.Z. and Y.Z. performed the space-charge-limited current method and the transient photo-voltage measurements. D.W., G.H. and Y.Y. performed the theoretical calculations of the Y6 and L8-R acceptors. \n\nH.Y. helped analyse the data and revise the manuscript. F.L. and Y.S. supervised and directed this project; C.L., F.L. and Y.S. wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41560-021-00820-x. \n\nCorrespondence and requests for materials should be addressed to F.L. or Y.S. \n\nPeer review information Nature Energy thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 \n\n# natureresearch \n\n# Solar Cells Reporting Summary \n\nNature Research wishes to improve the reproducibility of the work that we publish. This form is intended for publication with all accepted papers reporting the characterization of photovoltaic devices and provides structure for consistency and transparency in reporting. Some list items might not apply to an individual manuscript, but all fields must be completed for clarity. \n\nFor further information on Nature Research policies, including our data availability policy, see Authors & Referees. \n\n# Experimental design \n\n# Please check: are the following details reported in the manuscript? \n\n![](images/fc5e2c564fd2e74d5aceebf8df9aa3df7f1a5bd0585f76c274daee92d52a413f.jpg) \n\n![](images/d0ffaf39fb618d5374b05002e737a53f72c8e19d9151116b5f4e3eddbe8bd123.jpg) " + }, + { + "id": "10.1038_s41586-021-03212-z", + "DOI": "10.1038/s41586-021-03212-z", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03212-z", + "Relative Dir Path": "mds/10.1038_s41586-021-03212-z", + "Article Title": "Strong tough hydrogels via the synergy of freeze-casting and salting out", + "Authors": "Hua, MT; Wu, SW; Ma, YF; Zhao, YS; Chen, ZL; Frenkel, I; Strzalka, J; Zhou, H; Zhu, XY; He, XM", + "Source Title": "NATURE", + "Abstract": "Natural load-bearing materials such as tendons have a high water content of about 70 per cent but are still strong and tough, even when used for over one million cycles per year, owing to the hierarchical assembly of anisotropic structures across multiple length scales(1). Synthetic hydrogels have been created using methods such as electro-spinning(2), extrusion(3), compositing(4,5), freeze-casting(6,7), self-assembly(8) and mechanical stretching(9,10) for improved mechanical performance. However, in contrast to tendons, many hydrogels with the same high water content do not show high strength, toughness or fatigue resistance. Here we present a strategy to produce a multi-length-scale hierarchical hydrogel architecture using a freezing-assisted salting-out treatment. The produced poly(vinyl alcohol) hydrogels are highly anisotropic, comprising micrometre-scale honeycomb-like pore walls, which in turn comprise interconnected nullofibril meshes. These hydrogels have a water content of 70-95 per cent and properties that compare favourably to those of other tough hydrogels and even natural tendons; for example, an ultimate stress of 23.5 +/- 2.7 megapascals, strain levels of 2,900 +/- 450 per cent, toughness of 210 +/- 13 megajoules per cubic metre, fracture energy of 170 +/- 8 kilojoules per square metre and a fatigue threshold of 10.5 +/- 1.3 kilojoules per square metre. The presented strategy is generalizable to other polymers, and could expand the applicability of structural hydrogels to conditions involving more demanding mechanical loading. A strategy that combines freeze-casting and salting-out treatments produces strong, tough, stretchable and fatigue-resistant poly(vinyl alcohol) hydrogels.", + "Times Cited, WoS Core": 959, + "Times Cited, All Databases": 998, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000621583600011", + "Markdown": "# Article \n\n# Strong tough hydrogels via the synergy of freeze-casting and salting out \n\nhttps://doi.org/10.1038/s41586-021-03212-z \n\nReceived: 24 May 2020 \n\nAccepted: 8 January 2021 \n\nPublished online: 24 February 2021 Check for updates \n\nMutian Hua1,4, Shuwang Wu1,2,4, Yanfei Ma1, Yusen Zhao1, Zilin Chen1, Imri Frenkel1, Joseph Strzalka3, Hua Zhou3, Xinyuan Zhu2 & Ximin He1 ✉ \n\nNatural load-bearing materials such as tendons have a high water content of about 70 per cent but are still strong and tough, even when used for over one million cycles per year, owing to the hierarchical assembly of anisotropic structures across multiple length scales1. Synthetic hydrogels have been created using methods such as electro-spinning2, extrusion3, compositing4,5, freeze-casting6,7, self-assembly8 and mechanical stretching9,10 for improved mechanical performance. However, in contrast to tendons, many hydrogels with the same high water content do not show high strength, toughness or fatigue resistance. Here we present a strategy to produce a multi-length-scale hierarchical hydrogel architecture using a freezing-assisted salting-out treatment. The produced poly(vinyl alcohol) hydrogels are highly anisotropic, comprising micrometre-scale honeycomb-like pore walls, which in turn comprise interconnected nanofibril meshes. These hydrogels have a water content of 70–95 per cent and properties that compare favourably to those of other tough hydrogels and even natural tendons; for example, an ultimate stress of $23.5{\\pm}2.7\\ \\$ megapascals, strain levels of 2 $900\\pm450$ per cent, toughness of $210\\pm13$ megajoules per cubic metre, fracture energy of $170\\pm8$ kilojoules per square metre and a fatigue threshold of $10.5{\\pm}1.3\\$ kilojoules per square metre. The presented strategy is generalizable to other polymers, and could expand the applicability of structural hydrogels to conditions involving more demanding mechanical loading. \n\nWood is light and strong; nacres are hard and resilient; muscles and tendons are soft and tough. These natural materials show a combination of normally contradicting mechanical properties, which is attributed to their hierarchical structures across multiple length scales11. Compared with natural load-bearing materials, conventional hydrogels with loose crosslinking, low solid content and homogeneous structure are relatively weak and fragile for handling real-world applications, which often demand long service periods, high load or impact tolerance, and large deformation. Tremendous improvements have been made to strengthen and toughen hydrogels by introducing mechanisms for energy dissipation during loading, such as by forming a double network12,13, having dual crosslinking14,15, self-assembly8, inducing hydrophobic aggregation16 and creating nano-crystalline domains17,18. These methods primarily focus on composition and molecular engineering, involving limited structural changes within a narrow length scale (molecular or nanoscale) and relatively simple structures compared to their complex structured natural counterparts. \n\nOther advances take structural engineering approaches by creating anisotropic structures in hydrogels through freeze-casting6,7, mechanical stretching9,10,18,19 and compositing4,5. For example, directional freezing, or ice-templating, is widely used owing to its generic applicability to various polymers7. However, ice-templated hydrogels with micro-alignment have shown mechanical performance comparable to, or lower than, that of homogeneous tough hydrogels made by molecular engineering methods. Mechanical stretching has also been used to create anisotropic micro/nanostructures9,10,18,19. Alternatively, instead of in situ creating anisotropic structures within the hydrogel by ice-templating and mechanical stretching, compositing methods by addition of alien micro/nanoscale fibre reinforcements into hydrogel has also been explored5,20–22. The mechanically trained hydrogels and hydrogel composites have considerably improved strength and fracture toughness over homogeneous tough hydrogels, but also have limited stretchability or water content. These structural engineering approaches focus on optimizing the micro/nanostructures of existing hydrogels, yet it remains challenging to create simultaneously strong, tough, stretchable and fatigue-resistant hydrogels with more elaborate hierarchical structures across broader length scales, such as those observed in natural materials23,24, while using a generic and facile approach. \n\nRecently, an anisotropic composite of modulus-contrasting fibres and a matrix of similar composition has shown effectiveness for maintaining stretchability while improving strength, fracture toughness and fatigue resistance4,25. Therefore, forming a hierarchically anisotropic single-composition hydrogel containing strong and stretchable fibres of the same composition would be promising for making water-laden hydrogels with simultaneously high strength, toughness, stretchability and fatigue threshold. \n\n![](images/d64b149697c24dfb024dece48d1c1869ebc8084aabc432667a3aeef485f2085d.jpg) \nFig. 1 | Fabrication and hierarchical structures of HA-PVA hydrogels. a, Freezing-assisted salting-out fabrication procedure of the HA-PVA hydrogels. Structural formation and polymer chain concentration, assembly and aggregation during the freezing-assisted salting-out fabrication process. \nb, Macroscopic view of real tendon and of the HA-5PVA hydrogel. Scale bar, 5 mm. c–e, SEM images showing the microstructure (c) and nanostructure (d, e) of the HA-5PVA hydrogel. Scale bars, ${50\\upmu\\mathrm{m}}$ (c); 1 μm (d); ${500}\\mathrm{nm}$ (e). f, Molecular illustration of polymer chains aggregated into nanofibrils. \n\nThe alteration of polymer aggregation states could be realized by the simple addition of specific ions26; this is known as the Hofmeister effect27, in which different ions have distinct abilities to precipitate polymers. With the aid of specific ions, modulus-contrasting structures could be formed from the same polymer composition. Meanwhile, directional freezing could endow hydrogels with anisotropic structures at the larger (micrometre–millimetre) scales while promoting molecular concentration. Herein, we propose to make hydrogels using a combination of molecular and structural engineering approaches. By combining directional freeze-casting and a subsequent salting-out treatment, which synergistically create hydrogel structures on different length scales across the millimetre scale to the molecular level (Fig. 1), we have constructed strong, tough, stretchable and fatigue-resistant hydrogels with hierarchical and anisotropic structures (denoted as HA-PVA/gelatin/alginate hydrogels). \n\n# Formation of hierarchical structures \n\nUsing poly(vinyl alcohol) (PVA) as a model system, a PVA solution was first directionally frozen and then directly immersed in a kosmotropic salt solution (Fig. 1a). A honeycomb-like micro-network with aligned pore walls was created during the directional freezing process (Fig. 1a, b)6,7. Importantly, the concentration and closer packing of polymer during freezing prepared the polymer chains for subsequent strong aggregation and crystallization induced by salting out. For the choice of kosmotropic ions we tested various species, obtaining a broad tunable range of gel microstructures and mechanical properties. Of those, sodium citrate showed the best salting-out ability and produced PVA hydrogel with the highest modulus (Supplementary Fig. 3). Under the influence of kosmotropic ions, the preconcentrated PVA chains strongly self-coalesced and phase-separated from the original homogeneous phase, which in turn formed the mesh-like nanofibril network on the surface of the micrometre-scale aligned pore walls28 (Fig. 1d–f). The phase separation of PVA evolved over time until the elaborate structure and crystallinity developed and matured (Fig. 2c–e, Supplementary Fig. 4), and the non-phase-separated portion of PVA remained in between the nanofibrils as a continuous membrane that filled the nanofibril network (Fig. 1e). \n\nMechanistically, directional freezing concentrated PVA to form the aligned pore walls and increased the local concentration of PVA to higher values than the nominal concentration, whereas salting out strongly induced the aggregation and crystallization of PVA by phase separation to form the nanofibrils. To understand the synergistic effects of freezing and salting out in this combined method, we designed a series of gel preparation methods with one or several factors omitted for direct comparisons (Fig. 3, Extended Data Fig. 1). As control samples, the PVA hydrogels prepared by directional freezing alone (Fig. 3c, Extended Data Fig. 2a) or salting out alone (Extended Data Fig. 1f, Extended Data Fig. 2b) showed strength, toughness and stretchability that were all lower than those of HA-PVA hydrogels (Fig. 3a, \n\n![](images/44bfbd618394f4d2e2a52fdc410116dd47fe133f9f2a3336cf102114f1014ca6.jpg) \nFig. 2 | Mechanical properties and structural evolution of HA-PVA hydrogel. a, Tensile stress–strain curve of HA-5PVA hydrogel in the parallel (‖) and perpendicular (⊥) directions relative to the alignment direction. The image on the right shows the fibrotic fracture of the HA- $5\\mathsf{P V}\\mathsf{A}_{\\parallel}$ hydrogel. b, Tensile loading of a HA- $5\\mathsf{P V}\\mathsf{A}_{||}$ hydrogel with a pre-made crack. ε, strain. c, Confocal images showing the microstructures of HA- $5\\mathsf{P V}\\mathsf{A}_{\\parallel}$ hydrogels after different periods of salting out in 1.5 M sodium citrate. Scale bar, ${50}\\upmu\\mathrm{m}$ . d, SEM images showing the evolution of the nanofibril network within the microstructure during the salting-out process. Scale bar, ${5\\upmu\\mathrm{m}}$ . The insets show the \ncorresponding SAXS patterns of freeze-dried HA- $5\\mathsf{P V}\\mathsf{A}_{\\parallel}$ hydrogel; scale bar, $0.01\\mathring{\\mathsf{A}}^{-1}$ . e, Wide-angle X-ray scattering (WAXS) patterns of HA- $5\\mathsf{P V}\\mathsf{A}_{\\parallel}$ hydrogel (top) compared with a PVA hydrogel of the same polymer content prepared by repeated freeze–thaw cycles (bottom) and the corresponding integrated scattering intensity with scattering vector q with $q=0.5\\ –3\\mathring{\\mathbf{A}}^{-1}$ . The peak at $q{=}1.35\\mathring{\\mathsf{A}}^{-1}$ corresponds to the crystalline peak around a diffraction angle of $2\\theta=18^{\\circ}$ obtained using 8-keV X-ray diffraction. Scale bar, $0.5\\mathring{\\mathbf{A}}^{-1}$ ; a.u., arbitrary units. f, Stress–strain curve of HA-5PVA‖ hydrogels after different periods of salting out in 1.5 M sodium citrate. g, Toughening mechanisms at each length scale. \n\nExtended Data Fig. 2). Structure-wise, the directionally frozen PVA hydrogel without the subsequent salting out showed only aligned pore walls, without the mesh-like nanofibrils (Fig. 3c, Supplementary Fig. 5), which suggested weak aggregation of polymer chains in the absence of salting-out treatment. On the other hand, directly salting out the PVA without prior freezing did not yield a bulk hydrogel, and instead formed loosely and randomly entangled fibrils (Extended Data Fig. 1f), which suggested that pre-freezing the PVA solution provided the necessary confinement and preconcentration of PVA chains for effective phase separation during the subsequent salting out to form a strong bulk material. In short, such a freezing-assisted salting-out method presents a unique synergy that seamlessly integrates the advantages of the two techniques to boost the effect of aggregation, and is crucial for achieving simultaneously high strength, toughness, stretchability and structural hierarchy in the HA-PVA hydrogels. \n\n# Strengthening while toughening \n\nThe HA-PVA hydrogels showed distinct mechanical properties in the parallel and perpendicular direction relative to the alignment direction owing to the induced anisotropy (denoted as HA-xPVA for $x\\%$ PVA precursor). Notably, the HA-5PVA hydrogels demonstrated superior toughness of $\\mathrm{1}75{\\pm}9\\mathrm{M}\\mathrm{J}\\mathrm{m}^{-3}$ upon stretching in the direction parallel to the alignment, with an ultrahigh ultimate stress of $11.5{\\pm}1.4$ MPa and ultimate strain of $2,900\\pm450\\%$ after $24\\mathsf{h}$ of salting out (Fig. 2a). Even when stretched in the relatively weaker perpendicular direction, the HA-5PVA hydrogel was as tough as previously reported tough hydrogels14,16. The HA-5PVA hydrogel showed a gradual failure mode featuring stepwise fracture and pull-out of fibres, which are typical for highly anisotropic materials (Fig. 2a, right). There was no observable crack propagation perpendicular to the stretch direction during tensile loading of the hydrogel (Supplementary Video 1). Even with pre-existing cracks, the hydrogel showed a remarkable crack-blunting ability, and the initial crack did not advance into the material at high strains, indicating flaw-insensitivity18 (Fig. 2b, Supplementary Video 2). \n\n![](images/045b5ba4b5582acb40ef2a2a8bbe70033e459169ca9fd1fa09c5b7f37877f875.jpg) \nFig. 3 | Hydrogel structure and mechanical properties relationship. a–c, SEM images and mechanical properties of HA-5PVA hydrogel prepared by directional freezing and subsequent salting out (a), 5PVA hydrogel prepared by uniform freezing and subsequent salting out (b; non-directional, in contrast to a) and 5PVA hydrogel prepared by directional freezing and thawing for three cycles (c; no salting out, unlike a). Scale bars, ${50\\upmu\\mathrm{m}}$ (top row), $1\\upmu\\mathrm{m}$ (middle row, zoomed-in SEM images). d, SEM images (left) showing the deformation of the mesh-like nanofibril network during stretching and corresponding in situ SAXS patterns (right). Scale bars, $1\\upmu\\mathrm{m}$ (SEM images); $0.025\\mathring{\\mathsf{A}}^{-1}$ (SAXS images). \n\nThe unusual combination of high strength and high toughness was correlated with three structural aspects at the micrometre, nanometre and molecular levels that evolved during synthesis (Fig. 2c–e), which integrated multiple strengthening and toughening mechanisms. For instance, the densification of aligned micropore walls (Fig. 2c) and nanofibrils (Fig. 2d) strengthened the material by increasing the material density, and toughened it by increasing the energy dissipation during fracture. Additionally, the growing crystallinity during salting out (Fig. 2e, Supplementary Fig. 4; $40\\%$ crystallinity after 24 h) strengthened each nanofibril and improved material elasticity, owing to the crystalline domains acting as rigid, high-functionality crosslinkers24, and toughened the fibrils by virtue of their ability to delay the fracture of individual fibrils by crack-pinning (Fig. $2\\tt g)^{17}$ . In short, the strengthening mechanism was mainly structural densification due to hydrogen bonds and crystalline domains formation, and the toughening mechanisms were pull-out, bridging and energy dissipation by the fibrils (Fig. 2g, Supplementary Fig. 6). During the evolution of these structures across multiple length scales, the strength, stretchability and toughness of the HA-PVA hydrogel increased simultaneously (Fig. 2f). \n\n# Structure–property correlation \n\nThe three structural aspects at different length scales are intertwined in the present material. To identify their roles in the synergistic strengthening and toughening, we compared the mechanical performances (critical stress $\\sigma_{\\mathrm{c}},$ critical strain $\\varepsilon_{\\mathrm{c}}$ and fracture energy Γ) of a series of PVA hydrogels with different combinations of those three structural aspects (Fig. $3\\mathsf{a}-\\mathsf{c}$ , Extended Data Fig. 1, Supplementary Fig. 7) with a conventional chemically crosslinked PVA hydrogel in which none of these structures existed (Extended Data Fig. 1e). Forming only low-density crystalline domains (Extended Data Fig. 1d) or aligned pore walls (Fig. 3c) by the conventional freeze–thaw method did not show remarkable enhancement in mechanical performance, whereas the formation of nanofibril networks (Fig. 3b) led to a nearly two-orders-of-magnitude increase in strength and a four-orders-of-magnitude increase in toughness compared to the baseline. The addition of anisotropic microstructure (via directional freezing) further enhanced the strength and toughness, but the increase was less pronounced (Fig. 3a). We conclude that among the multiple aforementioned mechanisms, which all have important roles, the effect of the nanofibril network was particularly prominent for simultaneous high strength, toughness and stretchability (Supplementary Information section 3). \n\nThe formed nanofibrils were not rigid, but rather stretchable, and deformed along with the hydrogel during stretching, as depicted in the scanning electron microscope (SEM) images of Fig. 3d. The nanofibrils became increasingly aligned after stretching, as indicated by the stretch of the small-angle X-ray scattering (SAXS) pattern perpendicular to the loading direction (Fig. 3d). The average nanofibril spacing decreased from about $350\\mathsf{n m}$ to about $200\\mathsf{n m}$ (Fig. 3d, Supplementary Fig. 8) when the strain increased from $0\\%$ to $500\\%$ . These stretchable nanofibrils strengthen and toughen the hydrogel, in a similar way to rigid-fibre reinforcements used in composite hydrogels, yet they are stretchable to preserve the stretchability of the hydrogel, which is key to achieving high strength, toughness and stretchability4,25 simultaneously. From a fracture mechanics perspective (Supplementary Information section 4), first, the formation of a continuously connected network facilitates the stress transfer between individual fibrils and prevent inter-fibril sliding, and thus energy dissipation ahead of a crack tip is not confined to the vicinity of the crack tip but rather expands to the entire network (Supplementary Fig. 9). Equivalently, the connection of nanofibrils via a continuous network extends their length, and longer polymer fibres along the stress direction result in higher toughness4. Second, the fracture energy of amorphous hydrogel can be calculated as24,29 \n\n$$\n\\Gamma\\propto U_{\\mathrm{f}}N_{\\mathrm{f}},\n$$ \n\nwhere $U_{\\mathrm{f}}$ is the energy required to fracture a single polymer chain and $N_{\\mathrm{f}}$ is the number of polymer chains fractured. Owing to the strong aggregation and crystalline domains in the nanofibrils, the energy required to fracture the same number of crystalized polymer chains is much higher than that needed for non-packed amorphous chains30. The entire bulk hydrogel is a continuous micrometre-scale network comprising the above strong nanofibril networks, which largely account for its high strength, toughness and stretchability. \n\n![](images/c185e4602a8e636ddb64fba7bcb8202df97bf5fa5323caac59dca91eeea9c919.jpg) \nFig. 4 | Tunable mechanical properties and generality of hydrogels produced by ice-templating-assisted salting out. a, Stress–strain curves of HA-2PVA‖, $5\\mathsf{P V}\\mathsf{A}_{\\parallel}.$ , $\\mathrm{10PVA_{\\parallel}}$ and $20\\mathsf{P V}\\mathsf{A}_{\\parallel}$ hydrogels after $24\\mathsf{h}$ of salting out in $1.5\\mathsf{M}$ sodium citrate. b, Cyclic loading of HA- $5\\mathsf{P V}\\mathsf{A}_{||}$ hydrogel to $50\\%$ strain. c, Crack propagation per loading cycle, ${\\mathrm{d}}c/{\\mathrm{d}}N$ , under increasing energy release rate. The energy release rate was controlled by the corresponding maximum strain. d–f, Ashby diagrams of ultimate tensile strength versus ultimate tensile strain (d), toughness versus ultimate tensile strength (e) and toughness versus \nultimate tensile strain (f) of HA-PVA hydrogels, other reported tough hydrogels and other tough materials. The data used are summarized in Supplementary Table 3. g, Photograph of HA-2gelatin hydrogel prepared by the same method as HA-PVA (left) and stress–strain curves of HA-2gelatin and regular $2\\%$ gelatin hydrogel (right). Scale bar, $5\\mathsf{m m}$ . h, PPy-infiltrated HA-5PVA‖ hydrogel being stretched. Scale bar, $5\\mathsf{m m}$ . DN, double-network hydrogels; SMPU, shape-memory poly(urethane). \n\n# Tunability and fatigue resistance \n\nWe varied the densities of the aligned micropore walls and nanofibrils by changing the initial PVA concentration from $2\\%$ to $20\\%$ , and reached ultimate stresses of $23.5\\pm2.7\\mathsf{M P a}$ , ${\\bf16.1\\pm1.8}$ MPa and $11.5\\pm1.4$ MPa and corresponding ultimate strains of 1 $,400\\pm210\\%$ , $1,800\\pm330\\%$ and $2,900\\pm450\\%$ after 24 h of salting out (Fig. 4a, Supplementary Fig. 10). For hydrogels with sufficient structural density and PVA concentration above $5\\%$ , the ultimate stress increased with PVA concentration, whereas the ultimate strain decreased with increasing PVA concentration, and the overall toughness increased with PVA concentration. The fracture energy ranged from $131\\pm6\\mathrm{kJ}\\mathrm{m}^{-2}$ to $170\\pm8\\mathrm{kJ}\\mathrm{m}^{-2}$ (Extended Data Fig. 4b) as the PVA concentration increased from $5w t\\%$ to $20\\%$ , as measured with a pre-cut crack perpendicular to the fibres. It should be noted that crack redirection was observed for the HA-5PVA and HA-10PVA hydrogels during the fracture energy measurements (Supplementary Fig. 11), and the substantial blunting of crack size makes these hydrogels flaw-insensitive18. Therefore, the measured fracture energy becomes related to the sample size. For the same sample size, the fracture energy of HA-5PVA was 5 and 65 times higher than those of the hydrogel with nanofibrils only (Fig. 3b, Supplementary Video 4) and the hydrogel with aligned porous microstructure only (Fig. 3c), respectively, where the measured fracture energy is the true material property. \n\nWe further studied the reversibility and reusability of the HA-PVA hydrogels by conducting multiple loading–unloading tests (Fig. 4b, Supplementary Fig. 12). Mechanical hysteresis was observed for all samples tested (Fig. 4b), which indicated the presence of sacrificial bonds (primarily hydrogen bonds here) that broke during deformation. The maximum stress increased with the number of stretching cycles owing to improved alignment induced by stretching10,19. The hysteresis area did not show obvious decrease over ten cycles, which indicated that the sacrificial hydrogen bonds responsible for energy dissipation were mostly reversible. \n\nFatigue resistance is another important criterion for structural hydrogels, and its limit is usually much lower than the fracture energy. To provide an accurate measurement, we used the relatively rigid HA-20PVA, in which crack redirection was less likely to occur (Supplementary Video 3, Supplementary Information section 5). The HA-20PVA hydrogels showed excellent fatigue resistance with a fatigue threshold of $10.5{\\pm}1.3{\\mathrm{kJ}}{\\mathrm{m}}^{-2}$ (Fig. 4c, Extended Data Fig. 3), which is eight times higher than the highest reported value for existing tough hydrogels17,19. No crack propagation or redirection was observed for over 30,000 cycles with such a high energy release rate (Extended Data Fig. 3b). The highly fatigue-resistant HA-PVA hydrogels utilize the crystalline domains and networks of fibres as strong barriers to cracks such as those in tendons and other robust natural materials. \n\nOverall, the HA-PVA hydrogels showed high ultimate stress and strain that well surpassed the values seen in many reported tough hydrogels (Fig. 4d), with an overall toughness increased by 4 to $10^{3}$ times (Fig. 4e). The HA-PVA hydrogels demonstrated excellent toughness of $175{\\pm}9\\mathrm{M}\\mathrm{J}\\mathrm{m}^{-3}\\mathrm{to}210{\\pm}13\\mathrm{M}\\mathrm{J}\\mathrm{m}^{-3}$ in the absence of flaws, as the direct result of their combination of high strength and high ductility (Fig. 4e). At a water content of over $70\\%$ in these hydrogels (Extended Data Fig. 4a), these toughness values are well above those of water-free polymers such as polydimethylsiloxane (PDMS)31, Kevlar and synthetic rubber32, even surpassing the toughness of natural tendon1 and spider silk33 (Fig. 4f). \n\n# Generality and customizability \n\nUsing the freezing-assisted salting-out strategy, we also fabricated gelatin and alginate hydrogels with enhanced mechanical properties. Regular $2\\%$ gelatin hydrogels are weak and fragile, whereas the HA-2gelatin hydrogel could be stretched to 4 MPa and $550\\%$ strain, which led to an over 1,000-fold increase in toughness (from $0.0075{\\scriptstyle\\pm0.0006}\\mathrm{MJ}\\mathsf{m}^{-3}$ to $11.9\\pm1.7\\mathrm{MJ}\\ensuremath{\\mathrm{m}}^{-3})$ (Fig. 4g). Likewise, HA-5alginate, which is a pure alginate hydrogel without calcium crosslinking, showed an ultimate strength of $1.1\\pm0.2$ MPa and an over-20-fold increase in toughness compared to calcium-crosslinked alginate hydrogel (Extended Data Fig. 5). Building upon the combination of high strength, stretchability and fatigue resistance of these HA-PVA hydrogels, we demonstrated the facile customizability of additional properties (for example, electrical conductivity) for their application in other fields. Here, by infiltrating the HA-PVA hydrogel with a conducting polymer (for example, poly-pyrrole; PPy), the hydrogel was functionalized to have electrical conductivity, without affecting its strength nor toughness (Fig. 4h, Supplementary Fig. 13). \n\n# Conclusion \n\nIn this study, we developed hierarchically structured hydrogels that combine high strength, toughness, stretchability and fatigue resistance, using a freezing-assisted salting-out treatment. Considering that the Hofmeister effect exists for various polymers and solvent systems, we are convinced that the presented strategy is not restricted to the systems presented here. We foresee that with the help of the presented strategy, originally weak hydrogels could be applied in the medical, robotics, energy and additive manufacturing fields. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03212-z. \n\n4. Xiang, C. et al. Stretchable and fatigue-resistant materials. Mater. Today 34, 7–16 (2020). \n5. Huang, Y. et al. Energy-dissipative matrices enable synergistic toughening in fiber reinforced soft composites. Adv. Funct. Mater. 27, 1605350 (2017). \n6. Zhang, H. et al. Aligned two- and three-dimensional structures by directional freezing of polymers and nanoparticles. Nat. Mater. 4, 787–793 (2005). \n7. Zhang, H. Ice Templating and Freeze-Drying for Porous Materials and their Applications (Wiley-VCH, 2018). \n8. Qin, H., Zhang, T., Li, N., Cong, H. P. & Yu, S. H. Anisotropic and self-healing hydrogels with multi-responsive actuating capability. Nat. Commun. 10, 2202 (2019). \n9. Mredha, M. T. I. et al. Anisotropic tough multilayer hydrogels with programmable orientation. Mater. Horiz. 6, 1504–1511 (2019). \n10. Mredha, M. T. I. et al. A facile method to fabricate anisotropic hydrogels with perfectly aligned hierarchical fibrous structures. Adv. Mater. 30, 1704937 (2018). \n11. Wegst, U. G. K., Bai, H., Saiz, E., Tomsia, A. P. & Ritchie, R. O. Bioinspired structural materials. Nat. Mater. 14, 23–36 (2015). \n12. Sun, J.-Y. et al. Highly stretchable and tough hydrogels. Nature 489, 133–136 (2012). \n13. Gong, J. P., Katsuyama, Y., Kurokawa, T. & Osada, Y. Double-network hydrogels with extremely high mechanical strength. Adv. Mater. 15, 1155–1158 (2003). \n14. Hu, X., Vatankhah-Varnoosfaderani, M., Zhou, J., Li, Q. & Sheiko, S. S. Weak hydrogen bonding enables hard, strong, tough, and elastic hydrogels. Adv. Mater. 27, 6899–6905 (2015). \n15.\t Lin, P., Ma, S., Wang, X. & Zhou, F. Molecularly engineered dual-crosslinked hydrogel with ultrahigh mechanical strength, toughness, and good self-recovery. Adv. Mater. 27, 2054–2059 (2015). \n16.\t He, Q., Huang, Y. & Wang, S. Hofmeister effect-assisted one step fabrication of ductile and strong gelatin hydrogels. Adv. Funct. Mater. 28, 1705069 (2018). \n17. Lin, S. et al. Anti-fatigue-fracture hydrogels. Sci. Adv. 5, eaau8528 (2019). \n18. Bai, R., Yang, J., Morelle, X. P. & Suo, Z. Flaw-insensitive hydrogels under static and cyclic loads. Macromol. Rapid Commun. 40, 1800883 (2019). \n19. Lin, S., Liu, J., Liu, X. & Zhao, X. Muscle-like fatigue-resistant hydrogels by mechanical training. Proc. Natl Acad. Sci. USA 116, 10244–10249 (2019). \n20.\t Illeperuma, W. R. K., Sun, J. Y., Suo, Z. & Vlassak, J. J. Fiber-reinforced tough hydrogels. Extreme Mech. Lett. 1, 90–96 (2014). \n21. Lin, S. et al. Design of stiff, tough and stretchy hydrogel composites via nanoscale hybrid crosslinking and macroscale fiber reinforcement. Soft Matter 10, 7519–7527 (2014). \n22.\t King, D. R., Okumura, T., Takahashi, R., Kurokawa, T. & Gong, J. P. Macroscale double networks: design criteria for optimizing strength and toughness. ACS Appl. Mater. Interfaces 11, 35343–35353 (2019). \n23.\t Fan, H. & Gong, J. P. Fabrication of bioinspired hydrogels: challenges and opportunities. Macromolecules 53, 2769–2782 (2020). \n24. Zhao, X. Multi-scale multi-mechanism design of tough hydrogels: building dissipation into stretchy networks. Soft Matter 10, 672–687 (2014). \n25.\t Wang, Z. et al. Stretchable materials of high toughness and low hysteresis. Proc. Natl Acad. Sci. USA 116, 5967–5972 (2019). \n26.\t Iwaseya, M., Watanabe, M., Yamaura, K., Dai, L. X. & Noguchi, H. High performance films obtained from P $\\mathsf{V A}/\\mathsf{N a}_{2}\\mathsf{S O}_{4}/\\mathsf{H}_{2}\\mathsf{O}$ and $>\\Delta A/C H_{3}C O O N a/H_{2}O$ systems. J. Mater. Sci. 40, 5695–5698 (2005). \n27. Zhang, Y. & Cremer, P. S. Interactions between macromolecules and ions: the Hofmeister series. Curr. Opin. Chem. Biol. 10, 658–663 (2006). \n28.\t van de Witte, P., Dijkstra, P. J., Van Den Berg, J. W. A. & Feijen, J. Phase separation processes in polymer solutions in relation to membrane formation. J. Membr. Sci. 117, 1–31 (1996). \n29. Lake, G. J. & Thomas, A.G. The strength of highly elastic materials. Proc. R. Soc. A 300, 108–119 (1967). \n30.\t Kinloch, A. J. & Young, R. J. (eds) Fracture Behaviour of Polymers (Springer Science & Business Media, 1984). \n31.\t Johnston, I. D., McCluskey, D. K., Tan, C. K. L. & Tracey, M. C. Mechanical characterization of bulk Sylgard 184 for microfluidics and microengineering. J. Micromech. Microeng. 24, 035017 (2014). \n32.\t Wood, L. A. Uniaxial extension and compression in stress-strain relations of rubber. Rubber Chem. Technol. 51, 840–851 (1978). \n33. Ebrahimi, D. et al. Silk – its mysteries, how it is made, and how it is used. ACS Biomater. Sci. Eng. 1, 864–876 (2015). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Article Methods \n\n# Preparation of PVA solution \n\n$2\\mathbf{w}\\mathbf{t}\\%,5\\mathbf{w}\\mathbf{t}\\%,10\\mathbf{w}\\%$ and $20\\mathrm{wt\\%}$ PVA solutions were prepared by dissolving PVA powder in deionized water under vigorous stirring and heating $(70^{\\circ}\\mathrm{C})$ . After degassing by sonication for 1 h, a clear solution was obtained. \n\n# Preparation of salt solution \n\nA 1.5 M sodium citrate solution was prepared by dissolving anhydrous sodium citrate powder in deionized water. After sonication for $10\\mathrm{{min}}$ , a clear solution was obtained. \n\n# Fabrication of hydrogel \n\nAn ethanol bath at $\\scriptstyle-80^{\\circ}\\mathbf{C}$ was used as the immersion bath for icetemplating. The temperature was maintained using an EYELA-PSL1810 constant-temperature bath. For a typical fabrication of the hierarchically aligned PVA hydrogels, $2-20\\%$ PVA aqueous precursor is poured into an acrylic container with peripheral thermal insulation and a glass bottom for good thermal conduction. The container is lowered into the ethanol bath at an immersion rate of 1 mm min−1. The directionally frozen PVA solution is then immersed into a 1.5 M sodium salt solution for gelation for up to 4 days. \n\n# Tensile testing \n\nThe hydrogels were cut into dog-bone-shaped specimens with a gauge width of $2\\mathsf{m m}$ for regular tensile testing. The thickness of the individual specimens was measured with a calliper and was typically around $2\\mathsf{m m}$ . The HA- $x\\mathsf{P V}\\mathsf{A}_{\\parallel}$ specimens had a microstructure parallel to the loading direction and the HA- $x\\mathsf{P V}\\mathsf{A}_{\\perp}$ specimens had a microstructure perpendicular to the loading direction. The force–displacement data were obtained using a Cellscale Univert mechanical tester equipped with 50-N and 200-N loading cells. The stress–strain curves were obtained by dividing the measured force by the initial gauge cross-section area and dividing the measured displacement by the initial clamp distance. Five hydrogel specimens were tested for each condition. \n\n# Pure shear tests \n\nThe hydrogels were cut into rectangular specimens with a height of $40\\mathsf{m m}$ and a width of $20\\mathsf{m m}$ for the fracture tests. The thickness of individual specimens was measured with a calliper. An initial clamp distance of 1 mm or $2\\mathsf{m m}$ was used for every pair of specimens. All specimens had microstructure alignment parallel to the height direction. For pure shear tests, two identical samples (one notched, one unnotched) were loaded under the sample setup as a pair to obtain one fracture energy value12. Briefly, for the notched samples, an initial 8-mm-long straight cut was made from the middle of the long edge towards the centre of the hydrogel, and the specimen was loaded at a strain rate of $10\\%\\boldsymbol{\\mathsf{s}}^{-1}$ . The critical strain $(\\varepsilon_{\\mathrm{c}})$ for unstable propagation of the crack was obtained from the strain at maximum stress. The pairing unnotched specimens were subsequently loaded until $\\varepsilon=\\varepsilon_{\\mathrm{c}}$ . The fracture energy value was obtained by multiplying the area under the stress–strain curve of the unnotched specimens with the initial clamp distance $(H)$ a $\\displaystyle{\\mathsf{s}}{\\cal T}={\\cal H}{\\int_{0}^{\\varepsilon_{\\mathrm{c}}}}\\sigma\\mathrm{d}\\varepsilon$ . \n\n# Fatigue tests \n\nTo examine the fatigue resistance of our hydrogel, we adopted the single-notch method34. Fatigue testing was performed in a water bath to prevent dehydration of the hydrogel. Cyclic tensile tests were conducted using notched samples with initial crack length $(c_{0})$ smaller than 1/5 of the width $(L_{0})$ of the sample. The sample width $L_{0}$ was much smaller than the sample height $H_{0}$ . The cyclic force–displacement curves were obtained using a Cellscale Univert mechanical tester. A digital camera was used to monitor the crack propagation of the hydrogel. All stretch \n\n# cycles were conducted continuously without a relaxation time. The energy release rate $(G)$ was obtained using \n\n$$\nG=2k c W,\n$$ \n\nwhere $k$ is a function that varies with strain, which was empirically determined to be $k=3/\\sqrt{\\varepsilon+1}$ , $c$ is the crack length and W is the strain energy density of an unnotched sample with the same dimensions and stretched to the same strain ε. It should be noted that when repeatedly stretching to high strains, the stress–strain curve slowly deviates from the initial loading–unloading curve as a result of plastic deformation, and W is integrated from the loading part, where the loading–unloading curves become stable. \n\n# SEM characterization \n\nFor characterization of the micro- and nanostructure of the hierarchically aligned hydrogels, all hydrogel samples were immersed in deionized water for 24 h before freeze-drying using a Labconco FreeZone freeze-dryer. The freeze-dried hydrogels were cut along the aligned direction to expose their interior and sputtered with gold before carrying out imaging using a ZEISS Supra 40VP SEM. \n\n# Confocal characterization \n\nConfocal microscopy was carried out using a Leica DMi8 confocal microscope. 0.1 wt% fluorescein sodium salt was added to the PVA precursor as a fluorescent marker, and florescent HA-PVA hydrogels were made with the same fabrication procedures as regular HA-PVA hydrogels. The 488-nm laser channel was used to excite the fluorescent marker. The hydrogel was assigned a green pseudo-colour. \n\n# X-ray scattering characterization \n\nThe HA-PVA hydrogels were cut into $1\\times4\\mathrm{cm}^{2}$ rectangles and washed with deionized water before testing. The beamline station used was APS 8-ID-E (Argonne National Laboratory), which is equipped with the Pilatus 1M detector. A customized linear stretcher was used to hold the samples and stretch on demand for in situ X-ray scattering measurements. The MATLAB toolbox GIXSGUI was used for further editing and analysis of the scattering patterns35. \n\n# Water content measurement \n\nWe measured the water content of the HA-PVA hydrogels by comparing their weights before and after freeze-drying. Excess surface water was wiped from the hydrogel surface and the hydrogel specimens were instantly frozen using liquid nitrogen, followed by freeze-drying. The weight before $(m_{\\mathrm{w}})$ and after $(m_{\\mathrm{d}})$ freeze-drying was measured with a balance. The water content was obtained as $[(m_{\\mathrm{w}}-m_{\\mathrm{d}})/m_{\\mathrm{w}}]\\times100\\%$ . \n\n# Crystallinity content measurement \n\nBefore freeze-drying the hydrogels for differential scanning calorimetry (DSC) measurements, we first used excess chemical crosslinks induced by glutaraldehyde to fix the amorphous PVA polymer chains in order to minimize further formation of crystalline domains during the drying process following ref. 19. The water content of the hydrogel, $f_{\\mathrm{water}},$ was obtained by comparing the weight before and after freeze-drying. In a typical DSC measurement, we first measured the total mass of the freeze-dried sample, $m$ . The sample was subsequently placed in a Tzero pan and heated up from $50^{\\circ}\\mathrm{C}$ to $250^{\\circ}\\mathrm{C}$ at a rate of $20^{\\circ}\\mathrm{C}\\mathsf{m i n}^{-1}$ under a nitrogen atmosphere with a flow rate of $30\\mathsf{m l}\\mathsf{m i n}^{-1}$ . The curve of the heat flow shows another narrow peak ranging from $200^{\\circ}\\mathrm{C}$ to $250^{\\circ}\\mathrm{C}$ , which corresponds to the melting of the crystalline domains. The integration of the endothermic transition from $200^{\\circ}\\mathrm{C}$ to $250^{\\circ}\\mathrm{C}$ gives the enthalpy for the melting of the crystalline domains per unit mass of the dry samples. Therefore, the mass of the crystalline domains $m_{\\mathrm{crvstalline}}$ can be calculated as $m_{\\mathrm{crystalline}}=m H_{\\mathrm{crystalline}}/H_{\\mathrm{c}1}^{0}$ ystallin,e where $H_{\\mathrm{crystalline}}^{0}=138.6\\mathbf{J}\\mathbf{g}^{-1}$ is the enthalpy of the fusion of $100\\mathrm{wt\\%}$ crystalline PVA measured at the equilibrium melting point, $T_{\\mathfrak{m}}^{0}({\\mathfrak{r e f.}}^{36})$ . Therefore, the crystallinity in the dry sample, $X_{\\mathrm{dry}},$ can be calculated as $X_{\\mathrm{dry}}{=}m_{\\mathrm{crystalline}}/m$ . With the measured water content from freeze-drying, the crystallinity in the swollen state can be calculated as $\\chi_{\\mathrm{swollen}}=$ $X_{\\mathrm{dry}}(1-f_{\\mathrm{water}})$ . \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author on reasonable request. \n\n34.\t Long, R. & Hui, C. Y. Fracture toughness of hydrogels: measurement and interpretation. Soft Matter 12, 8069–8086 (2016). \n35.\t Jiang, Z. GIXSGUI: a MATLAB toolbox for grazing-incidence X-ray scattering data visualization and reduction, and indexing of buried three-dimensional periodic nanostructured films. J. Appl. Cryst. 48, 917–926 (2015). \n36.\t Peppas, N. A. & Merrill, E. W. Differential scanning calorimetry of crystallized PVA hydrogels. J. Appl. Polym. Sci. 20, 1457–1465 (1976). \n\nAcknowledgements This research was supported by NSF CAREER award 1724526, AFOSR awards FA9550-17-1-0311, FA9550-18-1-0449 and FA9550-20-1-0344, and ONR awards N000141712117 and N00014-18-1-2314. X.Z. acknowledges Shanghai Municipal Government 18JC1410800 and National Natural Science Foundation of China 51690151. This research used resources of the Advanced Photon Source, a US Department of Energy (DOE) Office of Science User Facility, operated for the DOE Office of Science by Argonne National Laboratory under contract number DE-AC02-06CH11357. \n\nAuthor contributions M.H., S.W. and X.H. conceived the concept. X.H. supervised the project. M.H., S.W., Z.C. and Y.Z. conducted the experiments. J.S. and H.Z. helped with the WAXS and SAXS measurements. M.H., S.W. and X.H. wrote the manuscript. All authors contributed to the analysis and discussion of the data. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-03212-z. Correspondence and requests for materials should be addressed to X.H. Peer review information Nature thanks Jiaxi Cui, Sylvain Deville and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n# Article \n\n![](images/ef831b1717543ebe17a23616aa9c33b98935d307f4a17f149b54a79e6cc582b3.jpg) \nDF + Salting out : HA-PVA \nDFT-3 cycle: Lacking nanofibrils \n\nFT-3cycle: Lacking microfiber &nanofibrils \n\nChemical Crosslinking: Lacking microfiber &nanofibrils & crystalline PVA \n\nSalting out: No gelation Only loose fibrils \n\nExtended Data Fig. 1 | Micro- and nanostructures and stress–strain curves of PVA hydrogels fabricated by different methods and their corresponding fracture energies and critical strains. a, ‘DF $^+$ Salting out’ denotes a hydrogel prepared by directional freezing of a $5\\%$ PVA solution and salting out in 1.5 M sodium citrate solution for 24 h. b, ‘F $^+$ Salting out’ represents a hydrogel prepared by non-directional freezing of a $5\\%$ PVA solution in the fridge and salting out in 1.5 M sodium citrate solution for $24\\mathsf{h}$ . c, ‘DFT-3 cycle’ denotes a hydrogel prepared by directional freezing and thawing of a $5\\%$ PVA solution for three cycles. d, ‘FT-3 cycle’ indicates a hydrogel prepared by non-directional freezing in the fridge and thawing of a $5\\%$ PVA solution for three cycles. e, ‘Chemical Crosslinking’ represents a hydrogel prepared by mixing $0.5\\%$ glutaraldehyde and $0.5\\%$ hydrochloric acid into a $5\\%$ PVA solution for gelation. f, Salting out resulted in non-gelation. Only weak globules of loose and random nanofibrils were made by directly adding a 1.5 M sodium citrate solution into a $5\\%$ PVA solution. Panels a–c are the same as Fig. $_{3\\mathsf{a-c}}$ . \n\n![](images/907e83db810bdb2757c4bad0f6d009e368e55b659144452acdaef7ad52639043.jpg) \nExtended Data Fig. 2 | Mechanical properties of HA-PVA hydrogel compared to those of PVA hydrogels prepared by ice-templating alone or salting out alone. a, b, The HA-PVA hydrogels are shown as red stars, and black \n\n![](images/cfb13184fcdc948b36babda9918555c6728fbb44b383ee430ae9ae815d2b6651.jpg) \nsquares correspond to the ice-templated PVA hydrogels (a) and the salting out PVA hydrogels (b). The data used are summarized in Supplementary Tables 1, 2. \n\n![](images/8173a39cef5e9d9eaa4295aab59e6732e143a18259f4d6891d456f8486604cbb.jpg) \nExtended Data Fig. 3 | Fatigue test of HA-20PVA hydrogels. a, Fatigue threshold of HA-20PVA. When loading above the threshold energy release rate $(\\varepsilon=400\\%$ ), the crack propagates slowly. N, number of cycles. b, Validation of \nfatigue threshold with an energy release rate slightly lower than the fatigue threshold. No crack propagation or failure was observed for 30,000 loading cycles. \n\n![](images/e938c2301142864acb05e86851f63db4dcc117777aba673a13b3320bc734261e.jpg) \nExtended Data Fig. 4 | Water content and fracture energy of the HA-PVA hydrogels. a, Water content of HA-xPVA hydrogels for $\\scriptstyle x=2,5,10$ and 20. The error bars (1 s.d. from five measured samples) were obtained from five measured samples with standard deviations of $1.72\\%$ , $2.29\\%$ , $2.69\\%$ and $2.43\\%$ \n\n![](images/c75b8425cb89ead146b331b5aeea58da8942d3b2b145567bfd4083de2d1ee0dd.jpg) \n\nfor $\\scriptstyle x=2,5,10$ and 20, respectively. b, Fracture energy of HA-xPVA hydrogels, $\\scriptstyle x=2,5,10$ and 20, measured by pure shear tests. The error bars (1 s.d. from five measured samples) were obtained from five measured samples with standard deviations of 0.16, 4.83, 5.44 and $5.62\\ensuremath{\\mathrm{kJ}}\\ensuremath{\\mathrm{m}}^{-2}$ for $\\scriptstyle x=2,5,10$ and 20, respectively. \n\n# Article \n\n![](images/4a8e4d4161b1c9b75f4d13eaa7bdfa5915a04291a2c23728f193cfd318dd057a.jpg) \n\nExtended Data Fig. 5 | HA-alginate hydrogels compared with calcium-alginate hydrogels. a, Photograph of HA-5alginate hydrogel. b, Tensile stress–strain urve of a HA-5alginate hydrogel compared to that of a regular calcium-alginate hydrogel. Scale bar, $5\\mathsf{m m}$ . " + }, + { + "id": "10.1038_s41586-021-03406-5", + "DOI": "10.1038/s41586-021-03406-5", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03406-5", + "Relative Dir Path": "mds/10.1038_s41586-021-03406-5", + "Article Title": "Pseudo-halide anion engineering for α-FAPbI3 perovskite solar cells", + "Authors": "Jeong, J; Kim, M; Seo, J; Lu, HZ; Ahlawat, P; Mishra, A; Yang, YG; Hope, MA; Eickemeyer, FT; Kim, M; Yoon, YJ; Choi, IW; Darwich, BP; Choi, SJ; Jo, Y; Lee, JH; Walker, B; Zakeeruddin, SM; Emsley, L; Rothlisberger, U; Hagfeldt, A; Kim, DS; Grätzel, M; Kim, JY", + "Source Title": "NATURE", + "Abstract": "Metal halide perovskites of the general formula ABX(3)-where A is a monovalent cation such as caesium, methylammonium or formamidinium; B is divalent lead, tin or germanium; and X is a halide anion-have shown great potential as light harvesters for thin-film photovoltaics(1-5). Among a large number of compositions investigated, the cubic a-phase of formamidinium lead triiodide (FAPbI(3)) hasemerged as the most promising semiconductor for highly efficient and stable perovskite solar cells(6-9), and maximizing the performance of this material in such devices is of vital importance for the perovskite researchcommunity. Here we introduce an anion engineering concept that uses the pseudo-halide anion formate (HCOO-) to suppress anion-vacancy defects that are present at grain boundaries and at the surface of the perovskite films and to augment the crystallinity of the films. Theresulting solar cell devices attain a power conversion efficiency of 25.6 per cent (certified 25.2 per cent), have long-term operational stability (450 hours) and show intense electroluminescence with external quantum efficiencies of more than 10 per cent. Our findings provide a direct route to eliminate the most abundant and deleterious lattice defects present in metal halide perovskites, providing a facile access to solution-processable films with improved optoelectronic performance.", + "Times Cited, WoS Core": 2467, + "Times Cited, All Databases": 2580, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000636947600001", + "Markdown": "# Article \n\n# Pseudo-halide anion engineering for α-FAPbI perovskite solar cells \n\nhttps://doi.org/10.1038/s41586-021-03406-5 \n\nReceived: 25 September 2020 \n\nAccepted: 1 March 2021 \n\nPublished online: 5 April 2021 Check for updates \n\nJaeki Jeong1,2,3,11, Minjin Kim4,11, Jongdeuk Seo1,11, Haizhou Lu2,3,11, Paramvir Ahlawat5, Aditya Mishra6, Yingguo Yang7, Michael A. Hope6, Felix T. Eickemeyer2, Maengsuk Kim1, Yung Jin Yoon1, In Woo Choi4, Barbara Primera Darwich8, Seung Ju Choi4, Yimhyun Jo4, Jun Hee Lee1, Bright Walker9, Shaik M. Zakeeruddin2, Lyndon Emsley6, Ursula Rothlisberger5, Anders Hagfeldt3,10 ✉, Dong Suk Kim4 ✉, Michael Grätzel2 ✉ & Jin Young Kim1 ✉ \n\nMetal halide perovskites of the general formula $\\mathbf{ABX}_{3}$ —where A is a monovalent cation such as caesium, methylammonium or formamidinium; B is divalent lead, tin or germanium; and X is a halide anion—have shown great potential as light harvesters for thin-film photovoltaics1–5. Among a large number of compositions investigated, the cubic $\\upalpha$ -phase of formamidinium lead triiodide $\\left(\\mathsf{F A P b l}_{3}\\right)$ ) has emerged as the most promising semiconductor for highly efficient and stable perovskite solar cells6–9, and maximizing the performance of this material in such devices is of vital importance for the perovskite research community. Here we introduce an anion engineering concept that uses the pseudo-halide anion formate (HCOO−) to suppress anion-vacancy defects that are present at grain boundaries and at the surface of the perovskite films and to augment the crystallinity of the films. The resulting solar cell devices attain a power conversion efficiency of 25.6 per cent (certified 25.2 per cent), have long-term operational stability (450 hours) and show intense electroluminescence with external quantum efficiencies of more than 10 per cent. Our findings provide a direct route to eliminate the most abundant and deleterious lattice defects present in metal halide perovskites, providing a facile access to solution-processable films with improved optoelectronic performance. \n\nPerovskite solar cells (PSCs) have attracted much attention since their first demonstration in $2009^{1-5}$ . The rapid expansion of research into PSCs has been driven by their low-cost solution processing and attractive optoelectronic properties, including a tunable bandgap6, high absorption coefficient10, low recombination rate11 and high mobility of charge carriers12. Within a decade, the power conversion efficiency (PCE) of single-junction PSCs progressed from $3\\%$ to a certified value of $25.5\\%^{13}$ , the highest value obtained for thin-film photovoltaics. Moreover, through the use of additive and interface engineering strategies, the long-term operational stability of PSCs now exceeds 1,000 hours in full sunlight14,15. PSCs therefore show great promise for deployment as the next generation of photovoltaics. \n\nCompositional engineering plays a key part in achieving highly efficient and stable PSCs. In particular, mixtures of methylammonium lead triiodide $\\left(\\mathbf{MAPbl}_{3}\\right)$ ) with formamidinium lead triiodide $\\left(\\mathrm{FAPbl}_{3}\\right)$ have been extensively studied5,7. Compared to $\\mathsf{M A P b l}_{3}$ , $\\mathsf{F A P b l}_{3}$ is thermally more stable and has a bandgap closer to the Shockley–Queisser limit6, rendering $\\mathsf{F A P b l}_{3}$ the most attractive perovskite layer for single-junction PSCs. \n\nUnfortunately, thin $\\mathsf{F A P b l}_{3}$ films undergo a phase transition from the black $\\mathfrak{a}$ -phase to a photoinactive yellow δ-phase below a temperature of $\\mathrm{150^{\\circ}C}$ . Previous approaches to overcome this problem have included mixing $\\mathsf{F A P b l}_{3}$ with a combination of methylammonium $(\\mathsf{M A}^{+})$ , caesium $(\\mathbf{C}\\mathbf{s}^{+})$ and bromide (Br−) ions; however, this comes at the cost of blue-shifted absorbance and phase segregation under operational conditions7–9,16. \n\nNevertheless, $\\mathsf{\\alpha}_{\\mathsf{d}\\mathsf{-}\\mathsf{F A P b l}_{3}}$ has recently emerged as the candidate of choice for highly efficient and stable $\\mathsf{P S C S}^{9,17,18}$ . We have previously prepared $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{\\mathrm{\\mathrm{\\alpha}}}\\mathbf{}\\mathrm{\\mathrm{\\mathrm{\\alpha}}}\\mathrm{\\mathrm{\\mathrm{\\alpha}}}\\mathrm{\\mathrm{\\mathrm}{\\mathrm}{\\mathrm\\mathrm{\\alpha}}}{\\mathrm{\\mathrm\\mathrm{\\alpha}}}{\\mathrm\\mathrm{\\mathrm}{\\mathrm}{\\mathrm\\mathrm{\\alpha}}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm}{\\mathrm\\mathrm{\\alpha}}}{\\mathrm\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm\\mathrm{\\mathrm\\mathrm}}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm\\mathrm}{\\mathrm}{\\mathrm\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm{\\mathrm}\\mathrm\\mathrm{}\\mathrm\\mathrm{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm} $ by spin-coating a precursor solution of $\\mathsf{F A P b l}_{3}$ mixed with excess methylammonium chloride (MACl), and achieved a certified efficiency of $23.48\\%$ for the resulting mesoporous $\\mathrm{FAPbl_{3}P S C^{\\mathrm{17}}}$ . By fully exploiting the absorption spectrum of $\\mathsf{\\Pi}_{\\mathsf{F A P b l}_{3}}$ together with proper light management, a certified efficiency of $23.73\\%$ was reported18—approaching the theoretical maximum—with a short-circuit current density $(\\boldsymbol{J}_{\\mathrm{sc}})$ of $26.7\\mathsf{m A c m}^{-2}$ . However, the open-circuit voltage $(V_{\\mathrm{oc}})$ of around 1.15 V for $\\mathsf{F A P b l}_{3}\\mathsf{P S C s}$ still lags behind the radiative limit9,18, which suggests that more work is needed to further reduce the density of defects in the $\\mathsf{F A P b l}_{3}$ perovskite films to suppress the non-radiative recombination of charge carriers. \n\n# Article \n\n![](images/7c6e8edc2fda30b788296fe38cfd65f3c9b7bb6e68c3b4e59460e2dacf31dc9f.jpg) \nFig. 1 | Characterization of the FAPbI films. a, UV–vis absorption and photoluminescence (PL) spectra of the FAPbI3 films. b, Time-resolved photoluminescence of the $\\mathsf{F A P b l}_{3}$ films. c, d, SEM images of the reference \n$\\mathsf{F A P b l}_{3}$ (c) and $2\\%$ Fo- $\\mathbf{\\cdotFAPbl}_{3}$ (d) films. The insets show cross-sectional SEM images. Scale bar, $2\\upmu\\mathrm{m}$ . e, f, Two-dimensional grazing-incidence XRD patterns of the reference (e) and $2\\%$ Fo-FAPbI3 (f) films. \n\nBromide, chloride (Cl−) and thiocyanate (SCN−) anions have commonly been used to improve the crystallinity and stability of perovskite films8,9,11,17–22. Another pseudo-halide anion, formate (HCOO−), has also been investigated in connection with $\\mathsf{M A P b l}_{3}\\mathsf{P S C S}^{23-26}$ . Two studies23,24 reported that MAHCOO improves the quality of $\\mathsf{\\mathbf{MAPbl}}_{3}$ films by controlling the growth of the perovskite crystals, while others25,26 reported that formic acid accelerates the crystallization of perovskites based on MA cations. Previous work has therefore mainly dealt with the effect of formate on the morphology, nucleation and growth of $\\mathsf{M A P b l}_{3}$ . There has also been a recent report of a highly fluorescent methylammonium lead bromide and formate mixture in water27. However, a fundamental understanding of the effects of formate on perovskite films has yet to be achieved. \n\nHere we uncover the key role of $\\mathsf{H C O O}^{-}$ anions in removing halide vacancies, which are the predominant lattice defects in $\\mathsf{F A P b l}_{3}$ perovskite films. This enables the PCE of the PSC to exceed $25\\%$ , combined with a high operational stability and external quantum efficiency (EQE) of electroluminescence $(\\mathsf{E Q E}_{\\mathtt{E L}})$ ) that exceeds $10\\%$ . Iodide vacancies are also the principal cause of the unwanted ionic conductivity of metal halide perovskites, which has deleterious effect on their operational stability. We provide insight into the mode of formate intervention. Formate is small enough to fit into the iodide vacancy22, thereby eliminating a prevalent and notorious defect in the metal halide perovskite that accelerates the non-radiative recombination of photogenerated charge carriers, in turn decreasing both the fill factor and the $V_{\\mathrm{oc}}$ of a solar cell. We generated $\\mathsf{F A P b l}_{3}$ perovskite films with improved crystallinity and larger grain size by introducing $2\\%$ formamidine formate (FAHCOO) into the precursor solution. The defect passivation and the improved crystallinity are essential to attain the levels of efficiency and stability that are demonstrated by our $\\mathsf{F A P b l}_{3}$ -based PSCs. \n\n# Characterization of the perovskite films \n\nThe reference $\\mathsf{F A P b l}_{3}$ film, hereafter denoted ‘reference’, was prepared as previously reported using a precursor solution containing a mixture of $\\mathsf{F A P b l}_{3}$ powder with $35\\mathrm{mol\\%}$ additional MACl17. For the formate-doped $\\mathsf{F A P b l}_{3}$ (Fo-FAPbI3) film, $x\\mathrm{mol\\%}\\left(x\\leq4\\right)$ FAHCOO was added to the reference precursor solution (for experimental details, see Supplementary Information). At a later stage in this work, we quantify the amount of MA in the resulting perovskite material to be $5\\%$ , but for simplicity we refer to this sample as $\\mathsf{F A P b l}_{3}$ . Figure 1a shows the ultraviolet–visible (UV–vis) absorption and photoluminescence spectra of the $\\mathsf{F A P b l}_{3}$ perovskite films $(x=0,2$ and 4). The absorption threshold and photoluminescence peak position were identical for all films; however, there was an obvious decrease in absorbance for the $4\\%\\mathsf{F o-F A P b l}_{3}$ film. We derived a bandgap of 1.53 eV for the films using the Tauc plot (Extended Data Fig. 1a). Fig. 1b shows the time-resolved photoluminescence of the $\\mathsf{F A P b l}_{3}$ perovskite films. The $2\\%$ $\\mathsf{F o-F A P b l}_{3}$ perovskite film showed a slower photoluminescence decay than the reference, which indicates a reduced non-radiative recombination rate due to a reduction in trap-mediated bulk or surface recombination. By contrast, the $4\\%\\mathsf{F o-F A P b l}_{3}$ perovskite film showed a faster photoluminescence decay than the reference. A full photoluminescence decay up to 4 μs is shown in Extended Data Fig. 1b. A quantitative analysis of the time-resolved photoluminescence is presented in Supplementary Note 1. \n\nScanning electron microscopy (SEM) measurements were performed to investigate the morphology of the perovskite film. Compared to the reference film (Fig. 1c), the $2\\%$ Fo-FAPbI3 film (Fig. 1d) had a slightly larger grain size of up to $2\\upmu\\mathrm{m}$ (Extended Data Fig. 1c). The insets of Fig. 1c, d show the cross-sectional SEM images of the corresponding perovskite films. Both the reference and $2\\%\\mathsf{F o-F A P b l_{3}}$ films showed monolithic grains from the top to the bottom. Extended Data Fig. 1d, e shows the irregular grain size of the $4\\%\\mathsf{F o-F A P b l}_{3}$ films. Atomic force microscopy measurements (Extended Data Fig. 1f, g) revealed a surface roughness of $41.66\\mathsf{n m}$ and $57.47\\mathrm{nm}$ for the reference and $2\\%\\mathsf{F o-F A P b l}_{3}$ films, respectively. The slightly increased surface roughness of the $2\\%\\mathsf{F o-F A P b l}_{3}$ film is probably due to the slightly increased grain size. \n\nX-ray diffraction (XRD) measurements (Extended Data Fig. 1h) showed identical peak positions at around $13.95^{\\circ}$ and $27.85^{\\circ}$ for both the reference and the $\\mathbf{Fo-FAPbl}_{3}$ perovskite films, corresponding to the $\\upalpha$ -phase of $\\mathsf{F A P b l}_{3}$ . However, the XRD pattern of the $4\\%\\mathsf{F o-F A P b l}_{3}$ film showed additional peaks, which are assigned to fluorine-doped tin oxide (FTO) substrates and different orientations of $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{}\\mathrm{\\mathrm{\\mathrm{\\alpha}}}\\mathbf{}\\mathrm{\\mathrm{\\alpha}}{\\mathrm{\\mathrm\\alpha}}{\\mathrm{\\mathrm}{\\mathrm\\mathrm{\\alpha}}}\\mathrm{}\\mathrm{\\mathrm{\\mathrm}{\\mathrm\\alpha}}{\\mathrm}{\\mathrm}\\mathrm{\\mathrm{\\mathrm}{\\mathrm\\mathrm{\\alpha}}}{\\mathrm\\mathrm{\\mathrm}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm}\\mathrm{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm}{\\mathrm\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm\\mathrm}{\\mathrm\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}\\mathrm{\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm}\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm\\mathrm{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm\\mathrm}\\mathrm{\\mathrm}{\\mathrm$ . The broader and lower-intensity diffraction peaks—resulting in a higher relative noise level—indicate a poor crystallinity, which is consistent with the poor optical measurements of the $4\\%\\mathsf{F o-F A P b l}_{3}$ film described above. Synchrotron-based two-dimensional grazing-incidence XRD measurements were also obtained for the $\\mathsf{F A P b l}_{3}$ films at a relative humidity of around $100\\%$ at $30^{\\circ}\\mathsf C$ in air. Figure 1e clearly shows the presence of the δ-phase in the reference, whereas this phase was absent in the $2\\%\\mathsf{F o-F A P b l}_{3}$ film (Fig. 1f). This provides strong evidence that FAHCOO stabilizes the $\\upalpha$ -phase of $\\mathsf{F A P b l}_{3}$ against humidity. In addition, the full-width at half-maximum of the $\\mathfrak{a}$ -phase peak was decreased for the $2\\%\\mathsf{F o-F A P b l_{3}}$ film, which is hereafter denoted as ‘target’. The integrated one-dimensional diffraction intensity is shown in Extended Data Fig. 1i. We infer from these data that including $2\\%$ FAHCOO in the synthesis of the $\\mathsf{F A P b l}_{3}$ films strongly enhances their crystallinity. \n\n![](images/94a4b0c33c6f40ff75e86bde4cda2826ce7771ef5d5b92abaae2fe842a2726e9.jpg) \nFig. 2 | Solid-state NMR spectra and molecular dynamics simulations. a, 207Pb solid-state NMR spectra (recorded at 298 K and a magic-angle spinning (MAS) rate of 15 kHz) of $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\mathbf{{c}}}}}\\mathbf{\\mathbf{{A}}}\\mathbf{\\mathbf{{P}}}\\mathbf{\\mathbf{{b}}}\\mathbf{\\mathbf{{l}}}_{3}}$ (1), $\\mathrm{\\alpha\\alpha\\mathrm{-}F A P b I_{3}}+5\\%$ FABr (2) and $\\mathrm{\\alpha\\alpha\\mathrm{-}F A P b I_{3}}+5\\%$ FAHCOO (3). In (1), a small amount of the δ-phase can be seen, but this is distinct from the shoulder seen in (2), and is not seen in (3). b, $^{13}{\\mathsf C}$ solid-state NMR spectra (recorded at $100\\mathsf{K}$ and 12 kHz MAS) of FAHCOO (1), ${\\delta\\mathrm{-}\\mathsf{F A P b I}_{3}(2)}$ , $\\mathsf{\\alpha}{\\mathsf{\\alpha}}{\\cdot}\\mathsf{F A P b l}_{3}(3)$ and $\\alpha{\\cdot}\\mathrm{FAPbI}_{3}{+}5\\%$ FAHCOO (4) (the top trace in (4) is an eightfold magnification). c, Calculated structure illustrating the passivation of an I− vacancy at the $\\mathsf{F A P b l}_{3}$ surface by a HCOO− anion. All chemical species are shown in ball-and-stick representation. $\\mathsf{P b}^{2+}$ , yellow; I−, pink; oxygen atoms, red; carbon, green; nitrogen, blue; hydrogen, white. d, The relative interaction strengths of different anions with the I− vacancy at the surface. \n\nWe obtained solid-state nuclear magnetic resonance (NMR) spectroscopy measurements in order to elucidate the molecular mechanisms that lead to the improvements afforded by the HCOO− anions. We prepared the samples by mixing formamidinium iodide and $\\mathsf{P b l}_{2}$ powders with 5 mol% excess FAHCOO using a mechano-synthesis method. Experimental details are provided in Methods. The $^{207}{\\sf P b}$ spectrum is sensitive to the nature of the anions that are coordinated to $\\mathsf{P b}^{2+}$ in the perovskite crystal28. Figure 2a shows the $^{207}\\mathrm{Pb}$ NMR spectrum of $\\left.\\mathbf{\\vec{\\alpha}}\\mathbf{\\cdot}\\mathbf{\\vec{F}A P b l_{3}}\\right.$ , in which the $^{207}\\mathrm{Pb}$ resonance appears at 1,543 ppm. The addition of $5\\%$ FABr results in a notable shoulder on the low-frequency side of the resonance, as shown in Fig. 2a (2). This shoulder corresponds to $^{207}\\mathrm{Pb}$ in a $[\\mathsf{P b B r l}_{5}]$ site, which resonates at lower frequency than in a $\\left[\\mathsf{P b l}_{6}\\right]$ site, because $^{207}\\mathrm{Pb}$ in a $\\left[\\mathsf{P b B r}_{6}\\right]$ site in $\\mathsf{F A P b B r}_{3}$ resonates at $510{\\mathsf{p p m}}^{28}$ . However, the $^{207}\\mathrm{Pb}$ resonance of $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\mathbf{{c}}}}}\\mathbf{{\\mathbf{{APbl}}}_{3}}}$ remained the same even when $5\\%$ FAHCOO was added during the synthesis, which is strong evidence that HCOO− does not substitute for iodide anions in the $\\mathsf{\\alpha}_{\\mathsf{d}}.\\mathsf{F A P b l}_{3}$ lattice. This is also supported by the density functional theory (DFT) calculations of the formation energy (Supplementary Note 2). \n\nTo explore the local environment of the HCOO− anions in the $\\mathsf{F o-F A P b l}_{3}$ perovskite, ${}^{1}\\mathsf{H}\\mathsf{-}^{13}\\mathsf{C}$ cross-polarization experiments 29 were performed at 100 K. Figure 2b (1) shows $^{13}\\mathrm{C}$ resonance signals at 167.8 ppm and 158.5 ppm for the HCOO− and $\\mathsf{F}\\mathsf{A}^{+}$ environments in FAHCOO, respectively. Figure 2b, (2) and (3) show the δ-FAPbI3 and $\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathrm{\\mathrm{\\alpha}}\\mathbf{\\mathrm{\\alpha}}\\mathrm{\\mathrm{\\alpha}}\\mathrm{\\mathrm{\\alpha}}\\mathrm{\\mathrm{\\alpha}\\mathrm{\\alpha}}\\mathrm{\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\mathrm}{\\alpha}\\mathrm{\\mathrm}\\mathrm{\\alpha}\\mathrm{\\alpha}\\mathrm{\\mathrm}\\mathrm{\\alpha}\\mathrm{\\mathrm}\\mathrm{\\alpha}\\mathrm{\\mathrm\\alpha}\\mathrm{\\mathrm}\\mathrm{\\alpha}\\mathrm{\\mathrm\\alpha}\\mathrm{\\mathrm}\\mathrm{\\mathrm\\alpha}\\mathrm{\\mathrm\\alpha}\\mathrm{\\mathrm\\mathrm}{\\mathrm\\alpha}\\mathrm{\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm}\\mathrm{\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm\\mathrm{\\alpha}\\mathrm\\mathrm{\\mathrm}\\mathrm\\mathrm{\\alpha\\mathrm\\alpha}\\mathrm\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm\\mathrm\\alpha\\mathrm{\\alpha\\alpha\\alpha}\\mathrm\\mathrm\\mathrm\\mathrm}\\mathrm{\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\mathrm}\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\alpha\\mathrm\\mathrm\\mathrm}\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\alpha\\mathrm\\mathrm}\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\mathrm\\mathrm\\mathrm\\mathrm}\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm}\\mathrm\\mathrm\\mathrm\\mathrm{\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm{\\alpha\\alpha\\alpha}$ and $^{13}\\mathsf{C}$ resonances at 157.6 ppm and 153.4 ppm, respectively. Upon mixing 5 mol% FAHCOO with $\\mathsf{F A P b l}_{3}$ , the $^{13}\\mathrm{C}$ signal of α-FAPbI3 remained unchanged at 153.4 ppm (Fig. 2b (4)); this further corroborates the lack of substitution of iodide by HCOO− inside the $\\mathsf{F A P b l}_{3}$ lattice, which would broaden the $^{13}\\mathrm{C}$ resonance of $\\mathsf{F A P b l}_{3}$ . The $\\mathsf{H C O O^{-}}$ peak, however, exhibited considerable broadening—indicative of a distribution of local environments—in contrast to the well-defined environment in crystalline FAHCOO. This is consistent with interaction of the HCOO− anion with undercoordinated $\\mathsf{P b}^{2+}$ to passivate iodide vacancies that are present at the surface or the grain boundaries of the perovskite, as predicted by molecular dynamics simulations (see below). For the spin-coated target thin films, the formate $^{13}{\\mathsf C}$ signal is less intense, appearing as a shoulder on the $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\tilde{{c}}}}\\mathbf{{APb}}\\mathbf{{l}}_{3}}$ peak (Extended Data Fig. 2a, b). This is due to a combination of the lower initial formate concentration and—because the exposed area is greater—the potentially greater evaporation of formate during annealing in the thin films compared to that in the powders; however, it should be noted that cross-polarization spectra are not quantitative. The presence of FAHCOO in the $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\alpha}}}\\mathbf{{\\mathrm\\mathrm{\\alpha}}}\\mathbf{{\\mathrm{\\mathrm\\alpha}}}\\mathbf{}\\mathrm{{\\mathrm\\mathrm{\\alpha}}}\\mathrm{}\\mathrm{\\mathrm{\\mathrm{\\alpha}}}\\mathrm{\\mathrm{\\mathrm}{\\mathrm}{\\mathrm\\mathrm{\\alpha}}}\\mathrm{\\mathrm{\\mathrm}{\\mathrm}{\\mathrm\\mathrm}{\\mathrm}{\\mathrm\\mathrm{\\alpha}}\\mathrm{}\\mathrm{\\mathrm}{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm}}{\\mathrm\\mathrm{\\mathrm}}\\mathrm{\\mathrm\\mathrm{\\mathrm}{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm}\\mathrm{\\mathrm\\mathrm}{\\mathrm\\mathrm{}\\mathrm{\\mathrm\\mathrm}{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm}\\mathrm{\\mathrm\\mathrm}{\\mathrm}\\mathrm{\\mathrm\\mathrm}{\\mathrm\\mathrm\\mathrm{}\\mathrm\\mathrm{\\mathrm}\\mathrm{\\mathrm}{\\mathrm\\mathrm\\mathrm}{\\mathrm\\mathrm}{\\mathrm\\mathrm}\\mathrm{\\mathrm\\mathrm{}\\mathrm\\mathrm\\mathrm{\\mathrm}\\mathrm}{\\mathrm{\\mathrm\\mathrm}\\mathrm{\\mathrm}{\\$ films is also supported by the time-of-flight secondary-ion mass spectrometry measurements (Extended Data Fig. 2c, d). We further quantified the composition of the spin-coated target films using directly detected $^{13}{\\mathsf C}$ NMR at 100 K (Extended Data Fig. 2e). Integration of the FA+ and $\\mathbf{MA}^{+}$ resonances in the quantitative $^{13}\\mathsf{C}$ spectrum yields a concentration of $\\mathbf{MA}^{+}$ in the final film of $5.1\\%$ (Supplementary Note 3). \n\n# Molecular dynamics simulations \n\nTo explore in more detail the unique role of $\\mathsf{H C O O}^{-}$ anions, we performed ab initio molecular dynamics simulations of a homogeneous mixture of different ions in the precursor solution (see Extended Data Fig. 3a, b and Supplementary Note 4)—comprising $\\mathsf{P b}^{2+}$ , I−, HCOO− and $\\mathsf{F}\\boldsymbol{\\mathsf{A}}^{+}$ —and found that HCOO− anions coordinate strongly with $\\mathsf{P b}^{2+}$ cations (Supplementary Video 1). This strong coordination might help to slow the growth process, resulting in larger stacked grains of the perovskite film; this is validated by the in situ images of the perovskite films without annealing (Supplementary Fig. 1). Compared to the reference film, the target film showed a slower colour change from brown to black. We also performed molecular dynamics simulations to understand the surface passivation effects of HCOO− anions. Extended Data Fig. 3c shows a super cell of a $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\mathbf{{c}}}}}\\mathbf{\\mathbf{{APbl}}}_{3}}$ perovskite slab, in which surface iodides are replaced by formate anions. We found that $\\mathsf{H C O O}^{-}$ anions can form a hydrogen-bonded network with $\\mathsf{F}\\boldsymbol{\\mathsf{A}}^{+}$ ions (Extended Data Fig. 3d, Supplementary Video 2), in agreement with the hydrogen bonding that is observed in FAHCOO crystal structures30. In addition, ${\\mathsf{H}}{\\mathsf{C}}{\\mathsf{O}}{\\mathsf{O}}^{-}$ anions can also form a bonding network on the $\\mathsf{P b}^{2+}$ ion-terminated surface, owing to their strong affinity towards lead (Extended Data Fig. 3e, Supplementary Video 3). Figure 2c shows a calculated structure that illustrates an HCOO− anion passivating an I− vacancy at the $\\mathsf{F A P b l}_{3}$ surface. I− vacancy defects are the most deleterious defects for halide perovskites. They act as electron traps—inducing the non-radiative recombination of charge carriers—and are responsible for the ionic conductivity of perovskites that causes operational instability. We estimated the relative binding affinities of different anions to I− vacancies at the surface (Extended Data Fig. 4).The energies shown in Fig. 2d reveal that $\\mathsf{H C O O}^{-}$ has the highest binding energy to I− vacant sites in comparison with Cl−, $\\mathsf{B r}^{-}$ , I− and $\\mathsf{B F}_{4}^{-}$ . Furthermore, we also calculated the bonding energies of $\\mathsf{F}\\boldsymbol{\\mathsf{A}}^{+}$ cations at the interface with HCOO− anions and with other anions (Extended Data Fig. 5, Supplementary Note 5). We found that $\\mathsf{F}\\mathsf{A}^{+}$ cations at the interface form stronger bonds with $\\mathsf{H C O O}^{-}$ than with the other anions. We therefore conclude that the $\\mathsf{H C O O}^{-}$ anion acts by eliminating anion-vacancy defects. \n\n# Photovoltaic performance of the PSCs \n\nWe further explored the photovoltaic performance of the PSCs. $\\mathsf{F A P b l}_{3}$ \nPSCs were fabricated using a configuration as illustrated in Fig. 3a. \n\n![](images/4a96a12af88e0d9753a5273925b4ed2e0e6031b535a1fbf72721f9d0fb098cce.jpg) \nFigure 3b shows current density (J)–voltage (V) curves of the reference and target PSCs under both forward and reverse scans. The reference cell had a maximum PCE of $23.92\\%$ with $\\mathsf{a}J_{\\mathrm{sc}}$ of $25.72\\mathsf{m A c m^{-2}}$ , a $V_{\\mathrm{oc}}$ of 1.153 V and a fill factor of $80.69\\%$ . The target PSC had a maximum PCE of $25.59\\%$ with $\\mathsf{a}J_{\\mathrm{sc}}$ of $26.35\\mathsf{m A c m^{-2}}$ , a $V_{\\mathrm{oc}}$ of 1.189 V and a fill factor of $81.7\\%$ . The detailed parameters are summarized in Extended Data Table 1. A statistical distribution of the measured PCE of the reference and target PSCs are shown in Fig. 3c. To verify the efficiency, we sent one of our best target PSCs to an accredited photovoltaic test laboratory (Newport, USA) for certification. Supplementary Fig. 2 represents a certified quasi-steady-state efficiency of $25.21\\%$ , with a $V_{\\mathrm{oc}}$ of 1.174 V, a $J_{\\mathrm{sc}}$ of $26.25\\mathsf{m A c m}^{-2}$ and a fill factor of $81.8\\%$ . \n\nEQE measurements (Fig. 3d) were performed to verify the measured $J_{\\mathrm{sc}}$ . The EQE of the target cell was higher than that of the reference cell over the whole visible-light absorption region. By integrating the EQE over the AM 1.5G standard spectrum, the projected $J_{\\mathrm{sc}}$ of the reference and target PSCs are $25.75\\mathsf{m A c m}^{-2}$ and $26.35\\mathsf{m A c m^{-2}}$ , respectively, which well match the measured $J_{\\mathrm{sc}}$ under the solar simulator. Figure 3e shows the $\\mathsf{E Q E}_{\\mathtt{E L}}$ of the PSCs. It is known that the photovoltage of a solar cell is directly related to the ability to extract its internal luminescence31. $\\mathsf{E Q E}_{\\mathtt{E L}}$ values have previously been successfully used to predict the $V_{\\mathrm{oc}}$ of $\\mathsf{P S C S}^{32}$ . In this case, the $\\mathsf{E Q E}_{\\mathtt{E L}}$ of the reference cell was $2.2\\%$ , whereas that of the target cell was $10.1\\%$ for injection current densities of $25.5\\mathsf{m A}$ $\\mathsf{c m}^{-2}$ and $26.5\\mathsf{m A c m}^{-2}$ (corresponding to the $J_{\\mathrm{sc}}$ measured under 1 sun illumination), respectively. Treatment with formate therefore results in a fivefold reduction in the non-radiative recombination rate. The $V_{\\mathrm{oc}}$ of 1.21 V that we obtained for the target cell (Extended Data Fig. 6a) is $96\\%$ of the Shockley–Queisser limit of $1.25\\mathsf{V}^{32,33}$ —to our knowledge, this is the highest value yet obtained. To further confirm the role of formate, we also measured the performance of devices fabricated using formamidinium acetate as an additive (Extended Data Fig. 6b); however, this additive had a negative effect on performance. For the devices fabricated without MACl additives or passivation layers, those that contained formate still showed an advantage (Extended Data Fig. 6c, d). \n\n![](images/7350ed686407a96581b26a73ed17800933287d44452d5d962b3dfe1cfa4da0c3.jpg) \nFig. 3 | Characterization of the photovoltaic performance of the FAPbI3 PSCs. a, The configuration of a typical $\\mathsf{F A P b l}_{3}$ PSC device. Spiro-OMeTAD, 2,2′,7,7′-tetrakis(N,N-di$p$ -methoxyphenylamine)9,9′-spirobifluorene. $\\mathbf{\\delta}_{\\mathbf{b},J}$ –V curves of the reference and target PSCs under both reverse and forward voltage scans. c, The distribution of the PCEs of the reference and target PSCs. d, EQE and the integrated $J_{\\mathrm{sc}}$ of the reference and target PSCs. e, $\\mathsf{E Q E}_{\\mathtt{E L}}$ measurements of the reference and target PSCs under current densities from $0.01\\mathsf{m A}\\mathsf{c m}^{-2}$ to $100\\mathsf{m A c m}^{-2}$ f, The relationship between the measured $V_{\\mathrm{oc}}$ and light intensity for the reference and target PSCs. \nFig. 4 | Stability of the FAPbI3 PSCs. a, The shelf-life stability of the reference and target PSCs. b, The heat stability of the reference and target PSCs. c, The operational stability of the reference and target PSCs, showing high performance. d, The long-term operational stability of the reference and target PSCs. \n\nSupplementary Fig. 3 shows a linear relationship (with a slope of approximately 0.95) between $J_{\\mathrm{sc}}$ and light intensity for both the reference and target PSCs—indicating good charge transport and negligible bimolecular recombination—and Fig. 3f shows a linear relationship between $V_{\\mathrm{oc}}$ and the logarithm of light intensity. We fitted the data points with a slope of $\\eta_{\\mathrm{id}}k_{\\mathrm{B}}T/q$ , where $\\eta_{\\mathrm{id}}$ is the ideality factor, $k_{\\mathrm{{B}}}$ is the Boltzmann constant, $T$ is temperature and $q$ is the electron charge. The reference cell had an $\\eta_{\\mathrm{id}}$ of 1.52, whereas that of the target cell was 1.18—lower than the previously reported value33 of 1.27. A summary of the detailed photovoltaic parameters can be found in Extended Data Table 2. The reduction in $\\eta_{\\mathrm{id}}$ as well as the space-charge-limited current measurements (Supplementary Fig. 4), further support our findings of a reduction in trap-assisted recombination34,35. Because the fill factor critically depends $^{36}\\mathbf{on}\\eta_{\\mathrm{id}},$ the reduction in $\\eta_{\\mathrm{id}}$ that we observe here also contributes to the increase in fill factor measured for the target PSCs. \n\n# Shelf-life and operational stability of the PSCs \n\nTo assess the stability of our PSCs, we measured first their shelf life by storing the unencapsulated devices in the dark at $25^{\\circ}\\mathrm{C}$ and $20\\%$ relative humidity. Figure 4a shows that the PCE of the reference cell decreased by about $35\\%$ after $1,000\\mathsf{h}$ aging, whereas the target cell showed a degradation of only $10\\%$ over this time. A heat-stability test was also performed by annealing the unencapsulated PSC devices at $60^{\\circ}\\mathsf{C}$ under $20\\%$ relative humidity. Figure 4b shows that the target cell retained around $80\\%$ of its initial efficiency after $1,000\\mathsf{h}$ aging, whereas the reference cell retained only about $40\\%$ . \n\nWe further investigated the operational stability of the PSCs by aging the unencapsulated devices under a nitrogen atmosphere, using maximum power point (MPP) tracking under a simulated 1-sun illumination. Figure 4c shows the PCE of the PSCs under continuous light soaking using a xenon lamp. The PCE of the target cell remained above $24\\%$ after 10-h MPP tracking, whereas that of the reference cell decreased to $22.8\\%$ . Figure 4d shows the long-term operational stability of the PSCs. The PCE of the reference cell decreased by about $30\\%$ , whereas the target cell only lost around $15\\%$ of its initial efficiency. Note that during this experiment the temperature of the PSCs was measured to be around $35^{\\circ}\\mathsf C,$ as we did not cool the cells during illumination. Compared to the target PSC, the reference cell showed a considerable decrease in $J_{\\mathrm{sc}}$ and fill factor over the 450-h MPP tracking test (Extended Data Fig. 7), which suggests that reference perovskite layer is less stable. We attribute the decline in fill factor to a de-doping of the hole conductor due to Li+ ion migration under illumination37. \n\nThe improvement in thermal and operational stability of the target cell compared with the reference cell is ascribed to the better crystallinity of the perovskite film and a reduced concentration of halide defects, because NMR experiments show that formate is not incorporated into the bulk of the perovskite. It is known that crystallinity is crucial for the stability of the perovskites, because the main degradation process starts from defects near the grain boundaries. The high crystallinity and large grain size of the formate-containing perovskite films—as validated by SEM and XRD measurements—will contribute to their greater stability and performance. Our simulations and calculations suggest that formate anions have the highest binding affinity among all halides and pseudo halides for iodide vacancy sites, and are therefore the best candidates to eliminate the most abundant and deleterious lattice defects present in halide perovskite films. This results in a marked reduction of trap-mediated non-radiative recombination, which we validated by $\\mathsf{E Q E}_{\\mathtt{E L}}$ , time-resolved photoluminescence, ${\\mathbf{}}\\cdot{{n}_{\\mathrm{id}}},$ and SCLC measurements. A low level of halide vacancies is beneficial for the stability of solar cells, because halide vacancies can lead to degradation as a result of photoinduced iodine loss, especially under light illumination. \n\nOverall, we demonstrate $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\mathbf{{\\alpha}}}}\\mathbf{{\\mathbf{\\alpha}}}\\mathbf{{\\mathbf{\\alpha}}}\\mathbf{{\\mathbf{\\alpha}}}}\\mathbf{\\alpha}\\mathbf{{\\mathrm{\\mathbf{{\\alpha}}}}\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\mathbf{{\\alpha}}}}\\mathbf{{\\alpha}}\\mathbf{{\\mathrm{\\mathbf{{\\alpha}}}}\\mathbf{{\\alpha}}}}}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}_{3}$ -based PSCs with a PCE of $25.6\\%$ (certified $25.2\\%$ and high stability, achieved through solution processing by introducing $2\\%$ formamidinium formate into the $\\mathsf{F A P b l}_{3}$ perovskite precursor solution. Our molecular dynamics simulations, together with solid-state NMR spectroscopy analysis and in-depth optoelectronic device characterization, provide an understanding of the role of HCOO− anions as passivating agents for $\\mathsf{F A P b l}_{3}$ perovskites. Our findings pave the way for facile access to high-performance PSCs approaching their theoretical efficiency limit. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03406-5. \n\n1. Kojima, A., Teshima, K., Shirai, Y. & Miyasaka, T. Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051 (2009). \n2. Grätzel, M. The light and shade of perovskite solar cells. Nat. Mater. 13, 838–842 (2014). \n3. Park, N.-G. et al. Towards stable and commercially available perovskite solar cells. Nat. Energy 1, 16152 (2016). \n4. Correa-Baena, J. P. et al. Promises and challenges of perovskite solar cells. Science 358, 739–744 (2017). \n5. Lu, H., Krishna, A., Zakeeruddin, S. M., Grätzel, M. & Hagfeldt, A. Compositional and interface engineering of organic-inorganic lead halide perovskite solar cells. iScience 23, 101359 (2020). \n6. Eperon, G. E. et al. Formamidinium lead trihalide: a broadly tunable perovskite for efficient planar heterojunction solar cells. Energy Environ. Sci. 7, 982–988 (2014). \n7. Pellet, N. et al. Mixed-organic-cation perovskite photovoltaics for enhanced solar-light harvesting. Angew. Chem. Int. Ed. 53, 3151–3157 (2014). \n8. Jeon, N. J. et al. Compositional engineering of perovskite materials for high-performance solar cells. Nature 517, 476–480 (2015). \n9. Lu, H. et al. Vapor-assisted deposition of highly efficient, stable black-phase $\\mathsf{F A P b l}_{3}$ perovskite solar cells. Science 370, eabb8985 (2020). \n10. De Wolf, S. et al. Organometallic halide perovskites: sharp optical absorption edge and its relation to photovoltaic performance. J. Phys. Chem. Lett. 5, 1035–1039 (2014). \n11. Stranks, S. D. et al. Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber. Science 342, 341–344 (2013). \n12. Herz, L. M. et al. Charge-carrier mobilities in metal halide perovskites: fundamental mechanisms and limits. ACS Energy Lett. 2, 1539–1548 (2017). \n13. NREL. Best Research-Cell Efficiency Chart https://www.nrel.gov/pv/cell-efficiency.html (accessed 17 March 2021). \n14. Zheng, X. et al. Managing grains and interfaces via ligand anchoring enables $22.3\\%$ -efficiency inverted perovskite solar cells. Nat. Energy 5, 131–140 (2020). \n15. Liu, Z. et al. A holistic approach to interface stabilization for efficient perovskite solar modules with over 2,000-hour operational stability. Nat. Energy 5, 596–604 (2020). \n16. Saliba, M. et al. Cesium-containing triple cation perovskite solar cells: improved stability, reproducibility and high efficiency. Energy Environ. Sci. 9, 1989–1997 (2016). \n17. Kim, M. et al. Methylammonium chloride induces intermediate phase stabilization for efficient perovskite solar cells. Joule 3, 2179–2192 (2019). \n18. Min, H. et al. Efficient, stable solar cells by using inherent bandgap of α-phase formamidinium lead iodide. Science 366, 749–753 (2019). \n19. Yang, S. et al. Thiocyanate assisted performance enhancement of formamidinium based planar perovskite solar cells through a single one-step solution process. J. Mater. Chem. A 4, 9430–9436 (2016). \n20. Kim, D. H. et al. Bimolecular additives improve wide-band-gap perovskites for efficient tandem solar cells with CIGS. Joule 3, 1734–1745 (2019). \n21. Kim, D. et al. Efficient, stable silicon tandem cells enabled by anion-engineered wide-bandgap perovskites. Science 368, 155–160 (2020). \n22. Walker, B., Kim, G. H. & Kim, J. Y. Pseudohalides in lead-based perovskite semiconductors. Adv. Mater. 31, 1807029 (2019). \n23. Moore, D. T. et al. Direct crystallization route to methylammonium lead iodide perovskite from an ionic liquid. Chem. Mater. 27, 3197–3199 (2015). \n24. Seo, J. et al. Ionic liquid control crystal growth to enhance planar perovskite solar cells efficiency. Adv. Energy Mater. 6, 1600767 (2016). \n25. Nayak, P. K. et al. Mechanism for rapid growth of organic–inorganic halide perovskite crystals. Nat. Commun. 7, 13303 (2016). \n26. Meng, L. et al. Improved perovskite solar cell efficiency by tuning the colloidal size and free ion concentration in precursor solution using formic acid additive. J. Energy Chem. 41, 43–51 (2020). \n27. Khan, Y. et al. Waterproof perovskites: high fluorescence quantum yield and stability from a methylammonium lead bromide/formate mixture in water. J. Mater. Chem. C 8, 5873– 5881 (2020). \n28. Askar, A. M. et al. Composition-tunable formamidinium lead mixed halide perovskites via solvent-free mechanochemical synthesis: decoding the Pb environments using solid-state NMR spectroscopy. J. Phys. Chem. Lett. 9, 2671–2677 (2018). \n29. Kubicki, D. J. et al. Cation dynamics in mixed-cation $(\\mathsf{M A})_{\\boldsymbol{x}}(\\mathsf{F A})_{1-\\boldsymbol{x}}\\mathsf{P b l}_{3}$ hybrid perovskites from solid-state NMR. J. Am. Chem. Soc. 139, 10055–10061 (2017). \n30. Zhou, Z. et al. Synthesis, microwave spectra, X-ray structure, and high-level theoretical calculations for formamidinium formate. $J.$ Chem. Phys. 150, 094305 (2019). \n31. Ross, R. et al. Some thermodynamics of photochemical systems. J. Chem. Phys. 46, 4590–4593 (1967). \n32. Tress, W. et al. Predicting the open-circuit voltage of $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ perovskite solar cells using electroluminescence and photovoltaic quantum efficiency spectra: the role of radiative and non-radiative recombination. Adv. Energy Mater. 5, 1400812 (2015). \n33. Jiang, Q. et al. Surface passivation of perovskite film for efficient solar cells. Nat. Photonics 13, 460–466 (2019). \n34. Yang, D. et al. Surface optimization to eliminate hysteresis for record efficiency planar perovskite solar cells. Energy Environ. Sci. 9, 3071–3078 (2016). \n35. Kuik, M., Koster, L. J., Wetzelaer, G. A. & Blom, P. W. Trap-assisted recombination in disordered organic semiconductors. Phys. Rev. Lett. 107, 256805 (2011). \n36. Green, M. Accuracy of analytical expressions for solar cell fill factors. Solar Cells 7, 337– 340 (1982). \n37. Wang, Y. et al. Stabilizing heterostructures of soft perovskite semiconductors. Science 365, 687–691 (2019). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Article Methods \n\n# Materials \n\nFormamidine acetate salt $(99\\%)$ , hydroiodic acid $(\\mathsf{H l},57\\mathsf{w t\\%}$ in water), titanium diisopropoxide bis(acetylacetonate), 2-propanol (anhydrous, $99.5\\%$ ), chlorobenzene (anhydrous, $99.8\\%$ ), $N,N\\cdot$ dimethylformamide (DMF, anhydrous $99.8\\%,$ ), dimethyl sulfoxide (DMSO, ${>}99.5\\%$ ), 2-methoxyethanol (anhydrous, $99.8\\%$ ) and formic acid were procured from Sigma-Aldrich and used as received. Methylamine hydrochloride (MACl, $98\\%$ ) was procured from Acros Organics. Fluorine-doped tin oxide on glass (FTO glass, $7\\Omega\\mathsf{s q}^{-1})$ was obtained from Asahi. Ethanol (absolute, $99.9\\%$ ) was procured from Changshu Yangyuan Chemicals. Diethyl ether (extra pure grade) was procured from Duksan. $\\mathrm{TiO}_{2}$ paste (SC-HT040) was procured from ShareChem. Lead iodide $(\\mathsf{P b l}_{2},\\mathsf{99.999}\\%$ ) was purchased from TCI. \n\n# Materials synthesis \n\nFormamidinium iodide (FAI) was synthesized as reported elsewhere8. In brief, $25\\mathrm{g}$ formamidine acetate was directly mixed with $50\\mathrm{ml}$ hydroiodic acid in a $500\\mathrm{ml}$ round-bottomed flask with vigorous stirring. A light-yellow powder was obtained by evaporating the solvent at $80^{\\circ}\\mathsf{C}$ for 1 h in a vacuum evaporator. The resulting powder was then dissolved in ethanol and precipitated using diethyl ether. This procedure was repeated three times until white powder was obtained, and the white powder was recrystallized from ethanol and diethyl ether in a refrigerator. After recrystallization, the resulting powders were collected and dried at $60^{\\circ}\\mathsf{C}$ for 24 h. As reported previously18, black $\\mathsf{F A P b l}_{3}$ powder was synthesized by mixing the synthesized FAI (0.8 M) with $\\mathsf{P b l}_{2}$ (1:1 molar ratio) in 30 ml of 2-methoxyethanol with stirring. The yellow mixed solution was heated with a stirring bar at $120^{\\circ}\\mathrm{C}$ and then recrystallized using the retrograde method. The resulting powder was filtered using a glass filter and baked at $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . Formamidine formate (FAHCOO) was synthesized by dissolving formamidine acetate in an excess of formic acid. The resulting solution was dried at $80^{\\circ}\\mathrm{C}$ by rotary evaporation to remove most of the formic acid and acetic acid. A wet formamidine formate powder was obtained. This wet powder was recrystallized with a small amount of ethanol. A transparent, plate-like crystal was formed after the recrystallization, which was consecutively dried in vacuum for 10 h to obtain the final formamidine formate. Bulk perovskite samples for solid-state NMR are prepared by grinding the reactant (FAI and $\\mathsf{P b l}_{2}$ with FABr or FAHCOO as appropriate) in an electric ball (Retsch Ball Mill MM-200) for 30 min at $25\\mathsf{H z}$ , before annealing at $150^{\\circ}\\mathrm{C}$ for $15\\mathrm{{min}}$ . \n\n# Substrate preparation \n\nAsahi FTO glass $(1.8\\mathrm{mm},7\\Omega\\mathsf{s q}^{-1})$ was used as the substrate for the devices. The substrates were cleaned using the RCA-2 $\\left(\\mathsf{H}_{2}\\mathbf{O}_{2}{\\cdot}\\mathsf{H C l}{\\cdot}\\mathsf{H}_{2}\\mathbf{O}\\right)$ 1 procedure for $15\\mathrm{{min}}$ to remove metal-ion impurities. Then, the substrates were cleaned sequentially with acetone, ethanol and isopropyl alcohol (IPA) in an ultrasonic system for $15\\mathrm{{min}}$ . To deposit the compact $\\mathsf{T i O}_{2}(\\mathsf{c}\\cdot\\mathsf{T i O}_{2})$ layer, $60\\mathrm{ml}$ of a titanium diisopropoxide bis(acetylacetonate)/ethanol (1:10 volume ratio) solution was applied using the spray-pyrolysis method. Prior to the spraying process, the FTO substrates were placed on a hot plate and the temperature was increased to $450^{\\circ}\\mathrm{C}$ rapidly. After the spray pyrolysis step, the substrates were stored at $450^{\\circ}\\mathrm{C}$ for 1 h and then slowly cooled to room temperature. On top of the $\\mathbf{c}{\\cdot}\\mathsf{T i O}_{2}$ layer, a mesoporous $\\mathbf{\\ddot{i}}0_{2}(\\mathbf{m}\\mathbf{-}\\mathbf{TiO}_{2})$ layer was deposited by spin-coating a $\\mathrm{TiO}_{2}$ paste dispersed in ethanol/terpineol $(78{:}22\\mathbf{w}/\\mathbf{w})$ . The $\\mathrm{TiO}_{2}$ nanoparticles have a diameter of approximately $50\\mathrm{nm}$ and were purchased from ShareChem. The FTO $/\\mathbf{c}{\\cdot}\\mathsf{T i O}_{2}$ substrates prepared with $\\scriptstyle\\mathbf{m}\\cdot\\mathbf{TiO}_{2}$ were heated at $500^{\\circ}\\mathrm{C}$ on a hot plate for 1 h to remove organic compounds first, and then slowly cooled to $200^{\\circ}\\mathrm{C}$ . \n\n# Device fabrication \n\nFor the fabrication of the perovskite layer, the whole process was carried out at controlled room temperature $(25^{\\circ}\\mathbf{C})$ and humidity $20\\%$ relative humidity). The reference perovskite precursor solution was prepared by mixing $1,139\\mathrm{mg}\\mathrm{FAPbl}_{3}$ and $35\\mathrm{mol\\%}$ MACl in a mixture of DMF and DMSO (4:1). For the $\\mathsf{F o-F A P b l}_{3}$ perovskite film, extra FAHCOO was added to the reference solution in the range of $1{-}4\\mathrm{mol\\%}$ . For each sample, $70\\upmu\\upmu\\upmu$ of the solution was spread over the $\\scriptstyle\\mathbf{m}\\cdot\\mathbf{TiO}_{2}$ layer at 6,000 rpm for 50 s with 0.1 s ramping. During the spin-coating, 1 ml diethyl ether was dripped after spinning for 10 s. The perovskite film was then dried on a hot plate at $150^{\\circ}\\mathrm{C}$ for 10 min immediately. See Supplementary Video 4 for details of the fabrication of perovskite films. After cooling the perovskite film on the bench, $15\\mathsf{m M}$ of octylammonium iodide dissolved in IPA was spin-coated on top of the perovskite film at 3,000 rpm for 30 s. The hole-transport layer was deposited by spin-coating a Spiro-OMeTAD (Lumtech) solution at 4,000 rpm for $30{\\mathsf{s}}.$ Details of the Spiro-OMeTAD solution was reported in the previous study18. Finally, a gold electrode was deposited on top of the Spiro-OMeTAD layer using a thermal evaporation system. The back and front contacts were formed with 100-nm-thick Au films deposited under a pressure of $10^{-6}$ Torr. \n\n# Characterization of the solar cells \n\nThe solar cells without encapsulation were measured with a solar simulator (McScience, K3000 Lab solar cell I-V measurement system, Class AAA) in a room with relative humidity below $25\\%$ at $25^{\\circ}\\mathrm{C}$ . An anti-reflecting coating layer was used for the devices. The light intensity was calibrated to AM 1.5G $\\mathrm{100mwcm^{-2}}.$ ) using a Si-reference cell certified by the National Renewable Energy Laboratory before performing measurements. No light soaking was applied before the potential I–V scans. All J–V curves were measured using a reverse scan (from 1.25 V to 0 V) and a forward scan (from $_{0\\vee}$ to 1.25 V) under a constant scan speed of $\\mathrm{100mVs^{-1}}$ . The stabilized power output was measured at the maximum power point using a xenon lamp light source. A non-reflective mask with an aperture area of $0.0804\\mathrm{cm}^{2}$ was used to cover the active area of the device to avoid the artefacts produced by the scattered light (the mask area is determined using a microscope). EQE measurements were obtained using a QEX7 system (PV Measurements). For the $\\mathsf{E Q E}_{\\mathtt{E L}}$ measurements, different bias voltages or currents were applied to the PSCs with a BioLogic SP300 potentiostat. The emitted photon flux from the PSCs was recorded using a calibrated, large-area $(1\\mathsf{c m}^{2})$ Si photodiode (Hamamatsu S1227-1010BQ). All measurements were performed in the ambient environment $40\\%$ relative humidity, $24^{\\circ}\\mathrm{C})$ . \n\n# Characterization of the device stability \n\nFor the stability tests, all PSCs were used without encapsulation. The shelf-life stability was assessed by measuring the photovoltaic performance of PSCs every tens of hours. The thermal stability test was performed by ageing the solar cells on a hot plate at $60^{\\circ}\\mathrm{C}$ at $20\\%$ relative humidity. The performance of the devices was periodically measured after cooling the devices to room temperature. The operational stability was performed with a BioLogic potentiostat under an LED or a lamp that was adjusted to AM 1.5G $(100\\mathsf{m w c m^{-2}})$ . The PSCs were masked and placed inside a homemade sample holder purged with continuous ${\\sf N}_{2}$ flow. The devices were aged with a maximum point power tracking routine under continuous illumination. The temperature-control system was not activated during the measurements. J–V curves with reverse voltage scans were recorded every $30\\mathrm{min}$ during the whole operational test. \n\n# Characterization of the perovskite film \n\nUV–vis absorption spectra of the perovskite films were recorded on a UV-1800 (Shimadzu) spectrophotometer. The SEM images of the perovskite films were taken with a field-emission scanning electron microscope (FE-SEM, S-4800, Hitachi). XRD patterns of the perovskite films were performed using a D8 Advance (Bruker) diffractometer equipped with Cu Kα radiation $(\\lambda=0.1542\\mathrm{nm})$ ) as the X-ray source. Steady-state photoluminescence and time-resolved photoluminescence measurements of the perovskite films were conducted using a \n\nPicoQuant FluoTime 300 (PicoQuant GmbH) equipped with a PDL 820 laser pulse driver. A pulsed laser diode $(\\lambda=375\\mathrm{nm}$ , pulse full-width at half-maximum $<70$ ps, repetition rate $200\\mathsf{k H z-40\\mathsf{M H z}}$ ) was used to excite the perovskite sample. Surface roughness was assessed using a Cypher S atomic force microscope from Asylum Research under ambient conditions $24^{\\circ}\\mathrm{C}$ , $50\\%$ relative humidity). An Olympus AC240-TS tip was used, and the system was operated under tapping mode. Two-dimensional grazing-incidence XRD of the perovskite films was performed at the BL14B1 beamline of the Shanghai Synchrotron Radiation Facility (SSRF) using X-rays with a wavelength of $0.6887\\mathring{\\mathbf{A}}$ . Two-dimensional grazing-incidence XRD patterns were acquired by a MarCCD mounted vertically at a distance of around $632\\mathsf{m m}$ from the sample with grazing-incidence angles of $0.4^{\\circ}$ and an exposure time of 30 s. For the time-of-flight secondary-ion mass spectrometry (TOF-SIMS) measurements, the reference and $2\\%\\mathsf{F o-F A P b l}_{3}$ films were coated on a glass substrate using anti-solvent methods. The samples were analysed by TOF-SIMS using a hybrid IONTOF TOF-SIMS instrument. Depth profiling was accomplished with a three-lens $25{\\cdot}\\mathrm{keV}$ BiMn primary ion gun and a ${\\mathbf B{\\mathbf i}_{3}}^{+}$ primary ion-beam cluster (1 pA pulsed beam current). Measurements used a caesium-ion beam for sputtering with an energy of $500\\mathrm{eV}$ (sputtering current 1–23 nA). Profiling was completed with a $100\\times100\\upmu\\mathrm{m}^{2}$ primary-beam area and a $300\\times300\\upmu\\mathrm{m}^{2}$ sputter-beam raster. Non-interlaced mode was used to limit beam damage from the primary ion-beam (1 frame, 2 s sputter, 2 s pause). \n\n# Solid-state NMR measurements \n\nLow-temperature (100 K) ${}^{1}\\mathsf{H}-{}^{13}\\mathsf{C}$ cross-polarization and directly detected $^{13}\\mathsf{C}$ ( $\\mathrm{125.8MHz)}$ NMR spectra, and room-temperature $^{207}\\mathrm{Pb}$ $(104.7\\mathrm{MHz})$ NMR spectra were recorded on a Bruker Avance III 11.7 T spectrometer equipped with a $3.2\\cdot\\mathrm{mm}$ low-temperature CPMAS probe. $^{207}\\mathrm{Pb}$ and $^{13}\\mathrm{C}$ spectra were referenced to $\\mathsf{P b}(\\mathsf{N O}_{3})_{2}$ at $^{-3,492}$ ppm and the $\\mathrm{CH}_{2}$ resonance of solid adamantane at 38.48 ppm, respectively, at room temperature. Room temperature $^{207}\\mathrm{Pb}$ spectra were recorded with a Hahn echo and an effective recycle delay of 17 ms. The low-temperature ${}^{1}\\mathsf{H}-{}^{13}\\mathsf{C}$ cross-polarization spectra of ${\\tt8-F A P b l}_{3}$ and $\\mathbf{\\alpha}_{\\mathbf{{\\alpha}}\\mathbf{{\\mathcal{{K}}}A P b l}_{3}}$ were recorded with 1 ms contact time, recycle delays of 1.5 s and 4 s, respectively, and $12\\mathsf{k H z}$ MAS. The low-temperature ${}^{1}\\mathsf{H}-{}^{13}\\mathsf{C}$ spectra of FAHCOO and $\\mathbf{Fo-FAPbl}_{3}$ were recorded with 2 ms contact time, 10 s recycle delay and 12 kHz MAS. The quantitative, directly detected $^{13}{\\mathsf C}$ experiment on a scraped $2\\%$ Fo-FAPbI3 film was performed with a single pulse experiment, $12\\mathsf{k H z}$ MAS and a 10 s recycle delay, which is more than 5 times the longitudinal relaxation time of $^{\\cdot13}\\mathsf{C}$ (1 s). All $^{13}{\\mathsf C}$ spectra were acquired with $100\\mathsf{k H z}^{\\mathrm{1}}\\mathsf{H}$ decoupling. The low-temperature ${}^{1}\\mathsf{H}\\mathsf{-}^{13}\\mathsf{C}$ cross-polarization spectrum of scraped $2\\%\\mathsf{F o-F A P b l}_{3}$ thin-film was measured with 2 ms contact time, 4 s recycle delay and 12 kHz MAS. NMR characterization was performed with $S\\%\\mathsf{F o-F A P b l}_{3}$ , because the greater amount of formate in the sample provides higher sensitivity compared to $2\\%$ Fo-FAPbI3. MACl was not included in the mechanosynthesized samples for NMR spectroscopy, because this would lead to broadening of the $^{13}\\mathsf{C}$ and $^{207}\\mathrm{Pb}$ resonances of FAPbI3 (ref. 29), owing to different local environments with slightly different chemical shifts that arise from MA+ substitution of nearest-neighbour—and more distant—A-site cations. This broadening would obscure the small changes in the $^{207}{\\sf P b}$ and $^{13}\\mathrm{C}$ resonances that arise from the incorporation of formate. However, given that the incorporation of $\\mathbf{MA}^{+}$ ions has a minimal effect on the lattice structure, these findings also apply to the $\\mathsf{M A}^{+}$ -doped composition studied here. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Code availability \n\nThe code used for this study is available from the corresponding author upon reasonable request. \n\nAcknowledgements We thank W. R. Tress for discussions, and the staff at beamlines BL17B1, BL14B1, BL11B, BL08U and BL01B1 of the SSRF for providing the beamline, and the Swiss National Supercomputing Centre (CSCS) and EPFL computing center (SCITAS) for their support. This research was supported by the Technology Development Program to Solve Climate Changes of the National Research Foundation (NRF) funded by the Ministry of Science, ICT & Future Planning (2020M1A2A2080746). This work was also supported by ‘The Research Project Funded by U-K Brand’ (1.200030.01) of Ulsan National Institute of Science & Technology (UNIST). D.S.K. acknowledges the Development Program of the Korea Institute of Energy Research (KIER) (C0-2401 and C0-2402). L.E. acknowledges support from the Swiss National Science Foundation, grant number 200020_178860. U.R. acknowledges funding from the Swiss National Science Foundation via individual grant number 200020_185092 and the NCCR MUST. A.H. acknowledges the Swiss National Science Foundation, project ‘Fundamental studies of dye-sensitized and perovskite solar cells’, project number 200020_185041. M.G. acknowledges financial support from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 881603, and the King Abdulaziz City for Science and Technology (KACST). \n\nAuthor contributions J.J., B.W. and J.Y.K. conceived the project. J.J., Minjin Kim and H.L. prepared the samples, performed the relevant photovoltaic measurements, analysed the data and wrote the manuscript. J.S. synthesised the FAHCOO material. Minjin Kim and D.S.K. certified the efficiency of the PSCs. Y.J.Y. carried out photoluminescence and UV–vis absorption spectroscopy. S.J.C. and I.W.C. performed the time-resolved photoluminescence, SEM and XRD measurements. Y.J. and H.L. collected the light-intensity-dependent J–V data. P.A. and U.R. designed and performed all the DFT calculations and molecular dynamics simulations. Maengsuk Kim and J.H.L contributed to the DFT calculations. A.M., M.A.H. and L.E. conducted the solid-state NMR measurements and analysis. B.P.D. performed the atomic force microscopy measurements. H.L. conducted the long-term operational stability measurements, $\\mathsf{E Q E}_{\\mathsf{E L}}$ measurements and analysed the data. Y.Y. performed the two-dimensional grazing-incidence XRD measurements. F.T.E contributed to the analysis of the time-resolved photoluminescence data. S.M.Z. coordinated the project. A.H. and M.G. proposed experiments and M.G. wrote the final version of the manuscript. A.H., D.S.K., M.G. and J.Y.K. directed the work. All authors analysed the data and contributed to the discussions. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-03406-5. \nCorrespondence and requests for materials should be addressed to A.H., D.S.K., M.G. or J.Y.K. Peer review information Nature thanks the anonymous reviewers for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/bf65c23485b31b808a9737257122568268e63b6f3acd1a49f3b8d96c4cbe9dcf.jpg) \n\nExtended Data Fig. 1 | Characterization of the perovskite films with and without FAFo. a, The Tauc plot of the $2\\%$ Fo-FAPbI3 perovskite film. b, A full photoluminescence decay of the reference, $2\\%$ Fo-FAPbI3 and $4\\%$ Fo- $\\mathbf{\\cdotFAPbl}_{3}$ perovskite films. c, The distribution of the grain sizes of the reference and $2\\%$ Fo-FAPbI3 films. The box $^+$ whisker plots show the distribution of the grain sizes for both reference and $2\\%$ Fo-FAPbI3 perovskite films. The distribution is based on 22 data points each. d, e, The top-view SEM image (d) and the cross-sectional \n\nSEM image (e) of the $4\\%$ Fo-FAPbI3 perovskite film. f, g, AFM images of the reference (f) and the $2\\%$ Fo- $\\cdot\\mathsf{F A P b l}_{3}$ (g) perovskite films. h, The XRD patterns of the reference, $2\\%$ Fo- $\\mathsf{F A P b l}_{3}$ and $4\\%$ Fo-FAPbI3 perovskite films. Peaks labelled with an asterisk are assigned to the FTO substrates, which can be seen for the $4\\%$ sample owing to the lower intensity of the perovskite reflections. i, Integrated one-dimensional grazing-incidence XRD pattern of the reference and $2\\%$ Fo-FAPbI3 films. \n\n![](images/2fa9c7ddb1c767d0049612e3446ccb4186b5b258c2bc7a4c039af0f5d4e8aaed.jpg) \nExtended Data Fig. 2 | The composition of the Fo- $\\mathbf{FAPbI_{3}}$ perovskite film. a, b, ${}^{1}\\mathsf{H}^{-13}\\mathsf{C}$ cross-polarization spectra of mechanosynthesized $\\mathsf{F A P b l}_{3}$ with $5\\%$ FAHCOO (a) and a scraped thin film of $2\\%$ Fo-FAPbI (b), recorded at 12 kHz MAS and 100 K. In b the formate signal can be seen as a minor shoulder on the $\\mathsf{F A P b l}_{3}$ \n\npeak. A minor signal arising from the PTFE that is used to seal the rotor is also visible. c, d, TOF-SIMS measurements of the reference (c) and the $2\\%\\mathsf{F o-F A P b l_{3}}$ (d) films. e, Quantitative, directly detected $^{13}\\mathrm{C}$ solid-state NMR measurement of $2\\%$ Fo-FAPbI3 scraped thin film at 12 kHz MAS and 100 K. \n\n# Article \n\n![](images/ecacfb29e55909f4fa1d4df5533db6b496295e9aa0df93aecfdb502ca2128c1b.jpg) \nExtended Data Fig. 3 | Ab initio molecular dynamics simulations. \n\na, Molecular dynamics snapshot showing the coordination of $\\mathsf{P b}^{2+}$ ions with HCOO− anions in the perovskite precursor solution. As a guide to the eye, we highlight only $\\mathsf{P b}^{2+}$ and $\\mathsf{H C O O^{-}}$ ions; the remaining ions and solvent molecules are shown as transparent. b, The radial distribution function g(r) between the oxygen atoms of HCOO− and $\\mathsf{P b}^{2+}$ over the full ab initio molecular dynamics trajectory of around 11 ps. c, Initial configuration of $\\mathsf{F A P b l}_{3}$ with surface iodide replaced by HCOO− anions. d, The top view of surface atoms on the $\\mathsf{F}\\boldsymbol{\\mathsf{A}}^{+}$ -terminated side. e, The top view of the surface atoms on the $\\mathsf{P b}^{2+}$ -terminated side. $\\mathsf{P b}^{2+}\\mathrm{-HCOO}^{-}$ and $\\mathsf{F}\\boldsymbol{\\mathsf{A}}^{+}$ –HCOO− bonding and hydrogen-bonding networks are illustrated with magenta dashed lines. All ions are shown in ball-and-stick representation. $\\mathsf{P b}^{2+}$ ions, yellow; iodide, light pink; oxygen, red; carbon, light blue; nitrogen, dark blue; sulfur, light yellow; hydrogen, white. \n\n![](images/4e91ae988a1381182627e9a9af9533395defce1efe1a49b1cecc3f878c1b1b7e.jpg) \nExtended Data Fig. 4 | DFT-relaxed slabs of FAPbI with different anions adsorbed at an iodide-vacancy site on the surface. a, Structure of a pure FAPbI slab with a Pb–I terminated surface on the top and an FA–I terminated surface on the bottom side. b–e, Front view of the Cl− (b), $\\mathbf{Br}^{-}(\\mathbf{c}),\\mathbf{BF}_{4}^{-}(\\mathbf{d})$ and HCOO− (e) passivated surface. f, An illustration of iodide-vacancy passivation by HCOO−. g, h, DFT-relaxed $\\mathsf{F A P b l}_{3}$ slab with HCOO− adsorbed at the \n\niodide-vacancy site on the Pb–I $\\mathbf{\\sigma}(\\mathbf{g})$ and the FA–I (h) terminated surface. All chemical species are shown in ball-and-stick representation. $\\mathsf{P b}^{2+}$ , grey; iodide, violet; oxygen, red; carbon, dark brown; nitrogen, light blue; bromide, red-brown; chloride, light green; boron atoms, dark green; fluoride, yellow; hydrogen atoms, white. \n\n# Article \n\n![](images/f663163bf999d44e800eaa3c684e7d56e7ac3f8b62f5d305f59d0bc94375f935.jpg) \n\nExtended Data Fig. 5 | Bonding between formamidinium and different anions on the surface of FA $\\mathbf{Pbl}_{3}$ . a, Structure of a pure $\\mathsf{F A P b l}_{3}$ slab with FA–I termination on the top and Pb–I termination on the bottom side. b, c, The front view (b) and the side view (c) of the $\\mathsf{H C O O}^{-}$ passivated surface. d–f, ${\\mathsf{C l}}^{-}$ (d), Br− (e) and $\\mathsf{B F}_{4}^{-}(\\mathbf{f})$ passivated surface. All chemical species are shown in \n\nball-and-stick representation. $\\mathsf{P b}^{2+}$ , grey; iodide, violet; oxygen, red; carbon, dark brown; nitrogen, light blue; bromide, red-brown; chloride, light green; boron atoms, dark green; fluoride, yellow; hydrogen, white. g, Relative desorption strength of FA+ cations on different passivated surfaces. \n\n![](images/5ae0a130f52eb74ec4d43ea2cac0739a4e9ef70f401f51991a3dd5f15a841c55.jpg) \nExtended Data Fig. 6 | Photovoltaic performance of the PSCs under different conditions. a, J–V curve of the target PSC measured without a metal mask. b, J–V curves of the reference PSC and the PSC with $2\\%$ formamidinium \nacetate. $^{\\mathbf{\\alpha}}\\mathbf{c}{\\mathcal{I}}^{\\mathbf{\\alpha}}$ –V curves of the reference and $2\\%$ Fo- $\\mathsf{F A P b l}_{3}$ PSCs without the MACl additive. ${\\bf d},J-$ –V curves of the reference and the $2\\%$ Fo-FAPbI3 PSCs without using octylammonium iodide passivation. FF, fill factor. \n\n![](images/d9e426c913871f3d45a5f20d3d6b96ffc1b800a859106e0b327577855beca34d.jpg) \nExtended Data Fig. 7 | J–V metrics of the reference and target PSCs during the operational stability test. a–c, The change $\\mathrm{in}J_{\\mathrm{sc}}$ (a), $V_{\\mathrm{oc}}$ (b) and fill factor (c) of the reference and target cells over the 450-h MPP tracking measurement. \n\nExtended Data Table 1 | Detailed J–V parameters of the reference and target PSCs under both reverse and forward voltage scans \n\n\n
ConditionJsc (mA/cm²)Voc (V)FF (%)PCE (%)
Reference_rev25.721.15380.6923.92
Reference_for25.311.15675.6922.13
Target_rev26.351.18981.7025.59
Target_for26.111.18579.0924.47
\n\n# Article \n\n
Extended Data Table2|DetailedJ-Vparametersofthereferenceandtarget PSCs under diferentlightintensities
Light intensity Jsc (mA/cm2) (mW/cm2)Voc (V)FF (%)PCE (%)
Reference10025.49 1.15177.122.62
5013.691.128 78.1
31.68.651.109 78.4
102.981.061 77.8
51.551.030 76.1
Target10025.601.174 83.425.06
5013.331.151 84.4
31.68.511.137 84.2
102.911.104 84.1
51.481.081 83.6
" + }, + { + "id": "10.1016_S1872-2067(20)63634-8", + "DOI": "10.1016/S1872-2067(20)63634-8", + "DOI Link": "http://dx.doi.org/10.1016/S1872-2067(20)63634-8", + "Relative Dir Path": "mds/10.1016_S1872-2067(20)63634-8", + "Article Title": "Sulfur-doped g-C3N4/TiO2 S-scheme heterojunction photocatalyst for Congo Red photodegradation", + "Authors": "Wang, J; Wang, GH; Cheng, B; Yu, JG; Fan, JJ", + "Source Title": "CHINESE JOURNAL OF CATALYSIS", + "Abstract": "Constructing step-scheme (S-scheme) heterojunctions has been confirmed as a promising strategy for enhancing the photocatalytic activity of composite materials. In this work, a series of sulfur-doped g-C3N4 (SCN)/TiO2 S-scheme photocatalysts were synthesized using electrospinning and calcination methods. The as-prepared SCN/TiO2 composites showed superior photocatalytic performance than pure TiO2 and SCN in the photocatalytic degradation of Congo Red (CR) aqueous solution. The significant enhancement in photocatalytic activity benefited not only from the 1D well-distributed nullostructure, but also from the S-scheme heterojunction. Furthermore, the XPS analyses and DFT calculations demonstrated that electrons were transferred from SCN to TiO2 across the interface of the SCN/TiO2 composites. The built-in electric field, band edge bending, and Coulomb interaction synergistically facilitated the recombination of relatively useless electrons and holes in hybrid when the interface was irradiated by simulated solar light. Therefore, the remaining electrons and holes with higher reducibility and oxidizability endowed the composite with supreme redox ability. These results were adequately verified by radical trapping experiments, ESR tests, and in situ XPS analyses, suggesting that the electron immigration in the photocatalyst followed the S-scheme heterojunction mechanism. This work can enrich our knowledge of the design and fabrication of novel S-scheme heterojunction photocatalysts and provide a promising strategy for solving environmental pollution in the future. (C) 2021, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.", + "Times Cited, WoS Core": 621, + "Times Cited, All Databases": 650, + "Publication Year": 2021, + "Research Areas": "Chemistry; Engineering", + "UT (Unique WOS ID)": "WOS:000582725100007", + "Markdown": "Article \n\n# Sulfur-doped $\\mathbf{g}–\\mathbf{C}_{3}\\mathbf{N}_{4}/\\mathbf{TiO}_{2}$ S-scheme heterojunction photocatalyst for Congo Red photodegradation \n\nJuan Wang a, Guohong Wang a,\\*, Bei Cheng b,#, Jiaguo Yu b, Jiajie Fan c \n\na Hubei Key Laboratory of Pollutant Analysis and Reuse Technology, College of Chemistry and Chemical Engineering, Institute for Advanced Materials, Hubei Normal University, Huangshi 435002, Hubei, China \nb State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan 430070, Hubei, China \nc Material Science and Engineering School, Zhengzhou University, Zhengzhou 450001, Henan, China \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nArticle history: Received 17 March 2020 Accepted 26 April 2020 Published 5 January 2021 \n\nKeywords: \n$\\mathrm{TiO}_{2}$ nanofiber \nSulfur-doped $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ \nStep-scheme heterojunction \nphotocatalysis \nIn situ XPS \nS-scheme mechanism \n\nConstructing step-scheme (S-scheme) heterojunctions has been confirmed as a promising strategy for enhancing the photocatalytic activity of composite materials. In this work, a series of sulfur-doped $\\mathrm{g{-}C_{3}N_{4}}$ (SCN)/ $\\mathrm{\\DeltaTiO_{2}}$ S-scheme photocatalysts were synthesized using electrospinning and calcination methods. The as-prepared $\\mathsf{S C N/T i O_{2}}$ composites showed superior photocatalytic performance than pure $\\mathrm{TiO}_{2}$ and SCN in the photocatalytic degradation of Congo Red (CR) aqueous solution. The significant enhancement in photocatalytic activity benefited not only from the 1D well-distributed nanostructure, but also from the S-scheme heterojunction. Furthermore, the XPS analyses and DFT calculations demonstrated that electrons were transferred from SCN to $\\mathrm{TiO}_{2}$ across the interface of the $\\mathsf{S C N/T i O_{2}}$ composites. The built-in electric field, band edge bending, and Coulomb interaction synergistically facilitated the recombination of relatively useless electrons and holes in hybrid when the interface was irradiated by simulated solar light. Therefore, the remaining electrons and holes with higher reducibility and oxidizability endowed the composite with supreme redox ability. These results were adequately verified by radical trapping experiments, ESR tests, and in situ XPS analyses, suggesting that the electron immigration in the photocatalyst followed the S-scheme heterojunction mechanism. This work can enrich our knowledge of the design and fabrication of novel S-scheme heterojunction photocatalysts and provide a promising strategy for solving environmental pollution in the future. \n\n$\\mathbb{C}2021$ , Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nThe treatment of industrial wastewater containing residual organics is still an immense challenge for humans in realizing sustainable development [1]. Congo Red (CR) is a widely used dye; however, its water-soluble and refractory characteristics make it difficult to purify in its aqueous solution [2]. Although several traditional technologies (adsorption, coagulation, etc.) have been applied to solve this problem, these processes cannot completely detoxify the contaminants and simultaneously bear high operating costs [3]. Fortunately, as an advanced oxidation and eco-friendly technology, photocatalysis has attracted increasing attention in organic wastewater treatment because of its mild reaction conditions and relatively low energy consumption [4–6]. Recently, many photocatalysts with different structures and shapes have been designed and synthesized. In particular, the metal-oxide semiconductor has received intensive attention for the photocatalytic degradation of organic wastewater due to its suitable band structure, physicochemical stability, non-toxicity, and so on [7–9]. Moreover, the one-dimensional (1D) nanostructure has been confirmed as a favorable structure for the photocatalytic degradation process, profiting from the enlarged specific surface area, short immigrating path of the ion, and unique 1D electron transfer trajectory [10–12]. For example, $\\mathrm{TiO}_{2}$ nanofibers were applied to the treatment of water pollutants and exhibited excellent photocatalytic performances under ultraviolet (UV) irradiation as a result of its hydrophilia, special morphology, and proper band position [13–16]. However, the wide band gap of $\\mathrm{TiO}_{2}$ $(\\sim3.2\\ \\mathrm{eV})$ , instinctive recombination of photoinduced carriers, and other defects result in its low solar quantum efficiency and restrict its practical utility [17,18]. Therefore, several strategies have been proposed to improve the photocatalytic activity, such as doping metallic or non-metallic elements, loading noble metals, and constructing heterojunctions [19,20]. \n\nThe heterojunction structure, which can efficiently facilitate the transfer and separation of photoinduced electrons, is commonly constructed by hybridizing two semiconductors with appropriate band alignments [21–23]. Presently, a novel step scheme (S-scheme) heterojunction has been proposed to elucidate the photocatalytic enhancement mechanism of heterojunction photocatalysts [24–26]. The S-scheme heterojunction not only efficiently separates photoinduced electrons and holes, but also reserves the promising redox abilities of semiconductors [27,28]. In a typical S-scheme heterojunction photocatalyst, the electrons flow from the conduction band (CB) of one semiconductor to the valance band (VB) of the other under the effect of the internal electric field (IEF), which usually exists at the interface of two semiconductors, exhibiting an S-scheme electron immigration route. Consequently, the electrons and holes with weak redox ability are transferred and consumed, whereas those electrons and holes with strong redox ability remain [29,30]. \n\nGraphitic carbon nitride $\\left(\\mathrm{g}{\\cdot}\\mathrm{C}_{3}\\mathrm{N}_{4}\\right)$ is a type of polymeric semiconductor. With its desirable band structure and high chemical stability, $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ has been considered as a promising photocatalytic material for water splitting and degradation of organic pollution, especially under visible light illumination [31–33]. Like other semiconductors, the immanent properties of $\\mathrm{g-C_{3}N_{4},}$ such as low electronic conductivity, quick recombination of photoinduced charge carriers, small surface area $_{<10}$ $\\mathbf{m}^{2}/\\mathbf{g})$ , and poor visible light absorption, inhibit its photocatalytic activity [34]. To overcome these flaws, numerous modification methods have been investigated, including doping metal or non–metal and hybridization with semiconductors [35–37]. In particular, the S-doped $\\mathrm{g-C_{3}N_{4}}$ (SCN), which was prepared through a sulfur doping process, was proven to have significantly stronger photocatalytic activity than pure $\\mathrm{g-C_{3}N_{4}}$ [38,39]. The introduction of the sulfur element to $\\mathrm{g-C_{3}N_{4}}$ can broaden its light absorption range, resulting in more photogenerated charge carriers. Furthermore, the extra surface impurities contribute to the trapping and separation of $\\mathbf{e}^{-}{\\mathrm{-}}\\mathbf{h}^{+}$ pairs [39,40]. Based on the above introduction, it will be an interesting and practical task to integrate the advantages of the 1D nanostructure, S-doping, and S-scheme heterojunctions to fabricate SCN/TiO2 photocatalysts. \n\nTo the best of our knowledge, the preparation of $\\mathsf{S C N/T i O_{2}}$ hybrid nanofibers and their application in photocatalytic degradation of organic pollutants have not been researched in detail. Herein, we report a facile method to prepare S-scheme $S C\\mathrm{N}/\\mathrm{Ti}0_{2}$ heterojunctions by a one-step calcination process. The obtained $S C N/\\mathrm{TiO}_{2}$ nanofibers possessed remarkably enhanced photocatalytic performances. The results of in situ X-ray photoelectron spectroscopy (XPS) and electron paramagnetic resonance (EPR) demonstrated that the S-scheme heterojunction constructed between $\\mathrm{TiO}_{2}$ and SCN played a crucial role in enhancing photocatalytic activity for the decomposition of Congo Red. \n\n# 2. Experimental \n\n# 2.1. Preparation of SCN/TiO2 heterostructures \n\nThe $\\mathrm{TiO}_{2}$ nanofibers were fabricated following a similar process to the literature [14]. The formation process of $S C\\mathrm{N}/\\mathrm{Ti}0_{2}$ was described as follows. Firstly, $6\\mathrm{g}$ of thiourea was dissolved in $50~\\mathrm{mL}$ of deionized water to form a transparent solution. Then, $_{0.2\\mathrm{~g~}}$ of $\\mathrm{TiO}_{2}$ nanofibers was added into the above solution and stirred to form the suspension. The suspensions were stirred for $^{2\\mathrm{~h~}}$ followed by evaporation at $100^{\\circ}\\mathrm{C}$ until dry. The resulting powders were annealed at $550^{\\circ}\\mathrm{C}$ for 2 h at a heating rate of $2\\ ^{\\circ}\\mathrm{C}/\\mathrm{min}$ to obtain the final $\\mathsf{S C N/T i O_{2}}$ hybrids. The products were named SCNT6. In order to discuss the role of SCN content on the photocatalytic activity of $\\mathsf{S C N/T i O_{2}}$ heterojunction photocatalysts, samples with different amounts of thiourea in the precursors (i.e., 5, 7, and $\\lfloor8\\ \\mathrm{g}\\right)$ were prepared under the same conditions. and the obtained samples were denoted as SCNTx $\\displaystyle\\langle{\\boldsymbol{x}}=5,$ 7, and 8). Figure 1 schematically illustrates the preparation of $\\mathsf{S C N/T i O_{2}}$ hybrid nanofibers. \n\n# 2.2. Characterization \n\nThe crystal phases of the samples were determined by X-ray diffractometry (XRD) with Cu $K_{\\alpha}$ radiation (D/max RB, Rigaku Co., Japan). The morphology was observed using a JSM 7500F field emission scanning electron microscope (FESEM). A Titan G2 60-300 electron microscope was used to take transmission electron microscopy (TEM) images and perform energy dispersive X-ray spectroscopy (EDX). The pore size distribution and specific surface area were obtained from nitrogen $\\left(\\mathsf{N}_{2}\\right)$ adsorption-desorption isotherms on a Micromeritics ASAP 3020 instrument. The UV-vis diffuse reflectance spectra (DRS) were recorded on a Shimadzu UV-2600 UV-visible spectrophotometer (Japan) using $\\mathsf{B a S O}_{4}$ as a reference. XPS was recorded with an ESCALAB 250Xi system. In situ XPS measurements were conducted under UV-visible light irradiation. Photoluminescence (PL) spectra were recorded using an LS55 fluorescence spectrophotometer at an excitation wavelength of ${320}\\mathrm{nm}$ . \n\n![](images/a3d03248f4c5677af13233fb051a76919ae78939c73e7686c049168ebee637fe.jpg) \nFig. 1. Schematic for the preparation of $\\mathsf{S C N/T i O_{2}}$ hybrid nanofibers. \n\n# 2.3. Photocatalytic activity \n\nThe photocatalytic activities of the as-prepared $\\mathsf{S C N/T i O_{2}}$ composites $\\left(20~\\mathrm{mg}\\right)$ were evaluated by degrading CR $[100~\\mathrm{mL},$ $50~\\mathrm{mg/L})$ under 300 W xenon lamp irradiation. Before light illumination, the solution was stirred in the dark for $^\\textrm{\\scriptsize1h}$ to reach the adsorption equilibrium. The concentration of dye was analyzed every $10~\\mathrm{min}$ using a UV-visible spectrophotometer (Shimadzu UV/Vis 1240, Japan). The photodegradation cycling tests were performed using the procedure of typical photocatalytic activity experiments. In addition, the used photocatalyst in the cycling tests was separated through a centrifuge and washed with deionized water prior to the next cycling test. \n\n# 2.4. Computational details \n\nThe density functional theory (DFT) calculations were carried out by using the CASTEP module in Materials Studio software. The exchange-correlation interaction was described by generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerhof (PBE) function. The energy cutoff was set as $500~\\mathrm{eV}$ . The Monkhorst-Pack k-point mesh was set as $3\\times3\\times1$ and $3\\times5\\times1$ for SCN and $\\mathrm{TiO}_{2}$ (1 0 1) models, respectively. Vacuum spaces of $15\\textup{\\AA}$ and $25\\textup{\\AA}$ were used in SCN and $\\mathrm{TiO}_{2}$ (1 0 1) models, respectively. The SCN model was built by replacing a two-coordinated N atom in a $2\\times2$ monolayer $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ model with an S atom. The $\\mathrm{TiO}_{2}$ (1 0 1) model was composed of $24~\\mathrm{Ti}$ and 48 O atoms. During the geometry optimization, the bottom third of Ti and O atoms were fixed, while other atoms were relaxed. \n\n# 3. Results and discussion \n\n# 3.1. Structure, surface chemical state, and morphology \n\nFigure 2(a) shows the XRD spectra of the $\\mathsf{g-C3N}_{4},$ SCN, $\\operatorname{scNT}x,$ and $\\mathrm{TiO}_{2}$ . The characteristic peaks of $\\mathrm{g-C_{3}N_{4}}$ at $13.1^{\\circ}$ and $27.5^{\\circ}$ belong to its (1 0 0) and (0 0 2) planes (JCPDS 87-1526) \n\n![](images/5127d9a23d074d80abd65ecbf2eb56b5e5c79da5fda836ab0e0811f9b368f05f.jpg) \nFig. 2. (a) XRD patterns of $\\mathrm{g-C_{3}N_{4},}$ SCN, ${\\mathrm{TiO}}_{2},$ and $\\mathsf{S C N/T i O_{2}}$ composites; (b) FT-IR spectra of SCN, ${\\mathrm{TiO}}_{2},$ and $\\mathsf{S C N/T i O_{2}}$ composites; (c) Nitrogen adsorption-desorption isotherms and pore size distribution curves (inset) of SCN, ${\\mathrm{TiO}}_{2},$ and $\\mathsf{S C N/T i O_{2}}$ composites; (d) TG curves for SCN, ${\\mathrm{TiO}}_{2},$ and $\\mathsf{S C N/T i O_{2}}$ composites. \n\n[41]. The peak at $13.1^{\\circ}$ can be ascribed to the in-planar structure of $\\mathrm{g-C_{3}N_{4},}$ but the peak at $27.5^{\\circ}$ is produced from the aromatic stacking structure. For the SCN sample, the location of the (0 0 2) peak negatively shifts to $27.3^{\\circ}\\mathrm{~}$ , suggesting that the $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ lattice is influenced by the S element, which has a larger atomic radius than C or N. On the other hand, the distinctly decreased peak intensity of the SCN sample can be attributed to the changed lattice structure of $\\mathrm{g-C_{3}N_{4},}$ which is affected by the inserted S atoms [42,43]. Compared with $\\underline{{\\mathbf{g}}}\\mathbf{-}\\mathbf{C}_{3}\\mathbf{N}_{4},$ the above characteristic variations in the XRD spectra of SCN confirm that the S element has been successfully incorporated into $\\mathrm{g-C_{3}N_{4}}$ . Additionally, the four typical diffraction peaks of $\\mathrm{TiO}_{2}$ located at $25.5^{\\circ},37.8^{\\circ},48.0^{\\circ},$ , and $53.8^{\\circ}$ demonstrate that only the anatase phase $\\mathrm{TiO}_{2}$ (JCPDS 21-1272) exists [44]. It is noteworthy that the peaks at $13.1^{\\circ}$ are not observed in the XRD spectra of the SCNTx samples. This can be ascribed to the inferior crystallization of SCN in the composites [45]. Interestingly, the intensities of the peaks at $27.3^{\\circ}$ for the SCNTx samples are enhanced monotonously with the increasing amount of SCN in the composites, and the intensities of the peaks at $25.5^{\\circ}$ are weakened accordingly. However, the intensities of the peaks $(27.3^{\\circ})$ belonging to SCN are always lower than those of the peaks (25.5°) belonging to $\\mathrm{TiO}_{2}$ . This phenomenon results from the instinctive difference in crystallinity between $\\mathrm{TiO}_{2}$ and SCN. In addition, no peak shifts are observed comparing the XRD spectra of SCNTx samples with those of SCN and ${\\mathrm{TiO}}_{2},$ demonstrating that the lattice structures of $\\mathrm{TiO}_{2}$ and SCN have not been changed in the SCNTx samples. \n\nFigure 2(b) shows the FT-IR spectra of SCNTx samples, SCN, and $\\mathrm{TiO}_{2}$ . In the spectrum of pristine ${\\mathrm{TiO}}_{2},$ the absorption band at ${\\sim}475~\\mathrm{cm^{-1}}$ arises from the stretching vibration modes of Ti-O-Ti and Ti-O in anatase crystals. For the SCN sample, the absorption peak located at $808~\\mathrm{cm}^{-1}$ is induced by the breathing vibration of the $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ triazine structure. Meanwhile, the wide absorption band in the range of 1200 to $1600~\\mathrm{cm}^{-1}$ is caused by the stretching vibration of $\\mathsf{C}{\\mathrm{-}}\\mathsf{N}$ and $\\mathsf{C}\\mathrm{=}\\mathsf{N}$ heterocycle unit of $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ . The other obvious typical peaks at ${\\sim}3200~\\mathrm{cm^{-1}}$ belong to the amino and surface hydroxyl groups [46,47]. Clearly, all typical peaks of the two components, $\\mathrm{TiO}_{2}$ and SCN, are observed in the FT-IR spectra of the SCNTx samples, implying that the two materials have been successfully incorporated into composites. The results are in conformity with the above XRD analyses. \n\nThe ${\\sf N}_{2}$ adsorption isotherms and pore size distributions of the samples are displayed in Fig. 2(c) and its inset, respectively. All the isotherms can be identified as type IV, demonstrating the existence of mesopores [48]. Furthermore, the hysteresis loop of the $\\mathrm{TiO}_{2}$ and SCNT5 samples can be classified as type H2, suggesting the formation of ink-bottle pores caused by the particle aggregation. Notably, the hysteresis loops of the SCNTx samples gradually display the characteristic of type H3 with the increasing amount of SCN in SCNTx. This phenomenon can be ascribed to the existence of narrow slit-shaped mesopores, which are produced by the random distribution of SCN on the $\\mathrm{TiO}_{2}$ nanofibers [49]. As shown in the inset of Fig. 2(c), the pore sizes of pristine $\\mathrm{TiO}_{2}$ and SCN samples both show bimodal distributions. The peaks $(\\sim3.5\\ \\mathrm{nm}$ and ${\\sim}30~\\mathrm{nm}\\$ ) of $\\mathrm{TiO}_{2}$ and the peaks ( $\\cdot\\mathord{\\sim}3.8\\ \\mathrm{nm}$ and $\\sim5\\ \\mathrm{nm}$ ) of SCN further confirm their mesoporous structures. Particularly, the pore size of $\\mathrm{TiO}_{2}$ is mainly centered at ${\\sim}30~\\mathrm{nm}$ , and that of SCN is mainly located at ${\\sim}3.8$ nm. The composites inherit the characteristics of the pores of $\\mathrm{TiO}_{2}$ and SCN. Moreover, the new ${\\sim}9\\mathrm{nm}$ pores are produced in the SCNT6 sample after hybridizing, which is the result of homogeneous mixing of $\\mathrm{TiO}_{2}$ and SCN at the microscopic level. Therefore, the SCNT6 shows a tri-modal pore size distribution. Table 1 shows the Brunauer-Emmett-Teller (BET) surface area, pore volume, and pore size of all samples. Compared with pure $\\mathrm{TiO}_{2}$ and SCN, the SCNTx samples possess an enlarged specific surface area. The specific surface area of $\\operatorname{scNT}x$ gradually increases with increasing content of thiourea in the precursors (from 5 to 6 g), then gradually decreases with further addition of thiourea (from 6 to $\\textrm{\\hphantom{-}8g}$ . The increased specific surface area of SCNTx could be attributed to the low content of thiourea in the precursor. Moreover, the highly scattered thiourea can produce lighter and smaller SCN particles, resulting in the increase in the specific surface area of the composite [39]. However, further increasing the content of thiourea may induce the self-aggregation of SCN in the hybridization process [50]. The composite with a larger specific surface area is believed to provide more sites for photocatalytic reaction and is thus considered to have enhanced photocatalytic activity. \n\nThe thermal stability and quantitative analysis were investigated through thermogravimetric analysis (TGA). The TG curves of the samples are shown in Fig. 2(d). The $\\mathrm{TiO}_{2}$ nanofibers exhibited an excellent thermal stability, and the slight weight loss could be ascribed to absorbed water on the $\\mathrm{TiO}_{2}$ surface. However, for pure SCN, there is weak thermal stability at higher temperatures in the oxygen atmosphere. The rapid decomposition of the SCN sample is observed from 500 to 640 oC. When the temperature is further increased from 640 to 800 $^{\\circ}\\mathsf{C},$ the residue of the SCN sample is close to zero, indicating the complete decomposition of SCN. As expected, the SCNTx samples have similar TG curves to those of the SCN sample. The rapid weight loss of the SCNTx samples can be detected, and finally the weight percentages of the residues achieve a constant value. However, the initial temperatures of the final plateaus in the TG curves of the SCNTx samples are different from that of the SCN sample. This is ascribed to the different amount of SCN in the as-prepared composites. Particularly, the TG curve of the SCNT5 sample displayed a very different characteristic, resulting from the relatively low content of SCN in the hybrid. In light of the above analyses, the final residues of the hybrids are a result of the $\\mathrm{TiO}_{2}$ . Therefore, the content of SCN in the hybrids can be estimated based on the TG curves, and the results are shown in Fig. 2(d). \n\nTable 1 Porosity and surface properties of the prepared samples. \n\n\n
SamplesSBET (m²/g)Pore volume (cm3/g)Pore size (nm)
TiO2160.0819.4
SCNT5290.1014.1
SCNT6510.1713.2
SCNT7330.1012.3
SCNT8280.1115.2
SCN200.0510.2
\n\nXPS analysis was conducted to investigate the surface chemical state of the as-prepared samples, and the results are shown in Fig. 3(a)−(f). In Fig. 3(a), all elements of the composing materials are detected in the corresponding samples. However, the extra element, O, is also observed in the pristine SCN, resulting from the adsorbed hydroxyl groups [51]. The element S was not detected in either the SCN or SCNT6 sample due to trace contents of sulfur. Moreover, the signal of C in the survey spectrum of pure $\\mathrm{TiO}_{2}$ is attributed to the adventitious contamination of hydrocarbons from the instrument. \n\nFigure 3(b) shows the high-resolution Ti $2p$ XPS spectra of $\\mathrm{TiO}_{2}$ and SCNT6. The typical peaks belonging to $\\mathrm{Ti^{4+}}$ in $\\mathrm{TiO}_{2}$ are observed at approximately 458.5 and $464.3\\ \\mathrm{eV}$ . Notably, compared with pure ${\\mathrm{TiO}}_{2},$ the binding energies of Ti $2p$ for SCNT6 in the absence of light illumination exhibit slightly negative shifts. The changes in binding energies signify that the electrons transfer from SCN to $\\mathrm{TiO}_{2}$ on account of the hybridization [52]. This result is also further confirmed by the O 1s XPS spectra (Fig. 3(c)). The peaks located at approximately 529.7 and $532.1\\mathrm{eV}$ are assigned to lattice O and $-0\\mathrm{H}$ , respectively. Due to the immigration of electrons, the binding energy of lattice O for SCNT6 without light illumination also displays a slightly negative shift in comparison with pure $\\mathrm{TiO}_{2}$ . To further verify the above conclusion, the high-resolution C 1s and N 1s XPS spectra of SCN and SCNT6 were also analyzed. In Fig. 3(d), all binding energies were calibrated by the C 1s peaks located at $284.6\\mathrm{eV}$ The peaks at approximately $288.2\\ \\mathrm{eV}$ belong to $s p^{3}$ carbon in the N-C-N backbone of SCN and the precursors [53]. In Fig. 3(e), the characteristic peak at $398.6\\mathrm{eV}$ is ascribed to $s p^{2}$ -hybridized pyridine nitrogen $\\scriptstyle\\sum=N-C)$ , and the peak at approximately $400.0\\ \\mathrm{{\\eV}}$ is a typical signal for tertiary nitrogen (N-C3) [54]. Compared to the C 1s and N 1s XPS spectra of SCN and SCNT6 without light illumination, the SCNT6 possesses slightly higher binding energies than SCN, confirming the electron transfer from SCN to $\\mathrm{TiO}_{2}$ and simultaneously agreeing with the opposite banding energy shifts of Ti and O. \n\nThe immigration of electrons between two different semiconductors after contact is commonly caused by the difference in Fermi level. As SCN has a higher Fermi level than TiO2 (see DFT calculation), the different Fermi level will drive electrons to migrate from SCN to $\\mathrm{TiO}_{2}$ until their Fermi levels are equalized [55–57]. Sequentially, an internal electric field will be created at the interface of the two materials. It is interesting that all the binding energies of elements in the SCNT6 under light irradiation show reverse shifting directions compared with those of the SCNT6 without light irradiation. These phenomena can be attributed to the generation of photoinduced charge carriers, and the detailed analyses of this issue are performed in Section 3.5. \n\nFigure 3(f) shows high-resolution $\\textsf{S}2p$ XPS spectra of SCN and SCNT6. No distinct signal is probed in the $\\textsf{S}2p$ XPS spectrum of SCNT6, due to its low content in the SCNT6 sample $\\cdot<$ $0.35\\%w/w$ of S). However, a typical peak at $165.8\\mathrm{eV}$ belonging to the C−S bond of SCN is detected, signifying that the sulfur is successfully substituted in the lattice nitrogen [40]. \n\nThe morphologies and structures of bare $\\mathrm{TiO}_{2}$ nanofibers and $\\mathsf{S C N/T i O_{2}}$ hybrid were characterized by SEM, TEM, and HRTEM. In Fig. 4(a), the as-prepared $\\mathrm{TiO}_{2}$ nanofibers with a regular surface are constructed by uniform $\\mathrm{TiO}_{2}$ nanoparticles, and the mean diameters and lengths of the fibers are estimated to be ${\\sim}150~\\mathrm{nm}$ and hundreds of micrometers, respectively. In Fig. 4(b), the $\\mathsf{S C N/T i O_{2}}$ composite fibers, which were synthesized by calcining the mixture of thiourea and $\\mathrm{TiO}_{2}$ nanofibers, still retain the morphologies of $\\mathrm{TiO}_{2}$ nanofibers. Interestingly, the thermal polymerization products of thiourea (SCN) appear in a veil-like fashion, closely and uniformly covered on the surface of the $\\mathrm{TiO}_{2}$ nanofibers. The unique structure benefits the immigration of charge carriers and the diffusion of species in aqueous solution. Figure 4(c) shows the typical TEM image of SCNT6. Clearly, SCN is still attached to the $\\mathrm{TiO}_{2}$ nanofibers in a veil-like fashion, even though the samples were treated by bath sonication for $5\\mathrm{min}$ before the TEM test. This further confirms the structural stability of the $\\mathsf{S C N/T i O_{2}}$ composite fibers. In addition, the crystalline structure of SCNT6 was probed by HRTEM (Fig. 4(d)), and the lattice spacing of $0.352~\\mathrm{{nm}}$ corresponds to the (1 0 1) plane of anatase phase $\\mathrm{TiO}_{2}$ . In Fig. 4(e), the elements of Ti, O, C, N, and S in SCNT6 are all confined to the same region, which is almost identical to the shape of the selected area of SCNT6. These results strongly demonstrate the even allocation of SCN and the successful hybridization of $\\mathrm{TiO}_{2}$ and SCN. \n\n![](images/58233a233b783e764529f86b4c6bb7a960ff4c45ee94e0ad9f6a5297f16a3cc5.jpg) \nFig. 3. (a) XPS survey spectra of ${\\mathrm{TiO}}_{2},$ SCN, and SCNT6 samples; High-resolution XPS spectra of Ti $2p$ (b), O 1s (c) in $\\mathrm{TiO}_{2}$ and SCNT6, C 1s (d), N 1s (e), and $;2p$ (f) in SCN and SCNT6. \n\n![](images/c8107dbba520236644732fe2334032deca725dd8986ead15d617bbe56078bf65.jpg) \nFig. 4. FESEM images of $\\mathrm{TiO}_{2}$ (a) and SCNT6 (b); insets on left bottom are the corresponding low-magnification SEM images; TEM (c) and HRTEM (d) images of SCNT6; (e) EDX elemental mappings of O, Ti, N, C and S. \n\n# 3.2. Optical absorption properties \n\nThe light absorption properties of the as-prepared samples were characterized by the UV-vis diffuse reflectance spectra (UV-vis DRS). As shown in Fig. 5(a), the typical absorption edges of SCN and $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ fall in the wavelength of approximately 510 and $460~\\mathrm{nm}$ , respectively, whereas the $\\mathrm{TiO}_{2}$ exhibits only UV light absorption characteristics, as previously reported. Interestingly, all the SCNTx samples present enhanced light absorption performances compared to TiO2. Even the SCNT5 sample with a low content of SCN displays an obviously enhanced light absorption property in the range of $400{-}600~\\mathrm{nm}$ . Moreover, all the hybrids except the SCNT5 sample show red shifts of the absorption edge in comparison with $\\mathrm{TiO}_{2}$ . Commonly, the band gap energy $\\left(E_{\\mathrm{g}}\\right)$ of a semiconductor can be estimated based on the Kubelka-Munk function [58]. Therefore, the $E_{\\mathrm{g}}$ values of $\\mathrm{TiO}_{2},$ SCN, and $\\mathrm{g-C_{3}N_{4}}$ were estimated to be 3.28, 2.43, and $2.67~\\mathrm{eV},$ respectively (Fig. 5(b)). Clearly, the $E_{\\mathrm{g}}$ value of SCN is smaller than that of pure $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ due to the introduction of the S atom into $\\mathrm{g-C_{3}N_{4}}$ . The SCN sample with a narrower band gap produces more photoinduced charge carriers in the photocatalytic process. Therefore, the SCNTx hybrids with better light absorption and a narrower band gap are expected to present an improved photocatalytic activity. \n\n![](images/368a25a8a1f9babd958b82c89486903b20279a39e01428d6291820428fd081c7.jpg) \nFig. 5. (a) UV-vis diffused reflectance of SCN, $\\mathrm{g-C_{3}N_{4},}$ ${\\mathrm{TiO}}_{2},$ and $\\mathsf{S C N/T i O_{2}}$ composites; (b) Tauc plots of SCN, $\\mathrm{g-C_{3}N_{4},}$ and $\\mathrm{TiO_{2}}$ \n\n# 3.3. Photocatalytic activity \n\nThe photocatalytic performances of the as-prepared catalysts were evaluated by the photodegradation of CR under Xe lamp irradiation. Fig. 6(a) presents the concentration variation of CR during the photocatalytic degradation processes with different as-prepared samples. Clearly, the $\\mathrm{TiO}_{2}$ and SCN samples show slower degradation rates of CR in comparison with SCNTx heterojunction photocatalysts. Furthermore, the enhancements of photocatalytic activity of the SCNTx composites are highly relevant to the amount of SCN. According to Fig. 6(a), the apparent reaction rate constant $(k)$ of all samples was calculated and shown in Fig. 6(b). The relatively low degradation rate $[28.6\\times10^{-3}\\mathrm{\\min^{-1}}]$ of bare $\\mathrm{TiO}_{2}$ can be ascribed to the restriction of the light absorption range. Only the UV light could be absorbed by the bare $\\mathrm{TiO}_{2}$ . Owing to the inherent recombination of photoinduced charge carriers, the SCN also displays a fairly low degradation rate $[11.7\\times10^{-3}\\mathrm{{\\min^{-1}}}]$ [34]. However, the composites of the two components present significantly enhanced photocatalytic activities. In particular, the SCNT6 sample with $36.5~\\mathrm{wt\\%}$ SCN exhibits the highest photocatalytic activity. Its apparent reaction rate constant is estimated to be $96.2\\times10^{-3}\\mathrm{min^{-1}}$ , which exceeds that of bare $\\mathrm{TiO}_{2}$ and SCN by a factor of 3.4 and 8.2, respectively. The enhancement in photocatalytic activity of the hybrid can be explained by the following facts. First, the broadened photoabsorption range (Fig. 5) induces more photoinduced carriers. Second, the high-quality interface between $\\mathrm{TiO}_{2}$ and SCN (Figs. 3 and 4) provides vast electron immigration paths, resulting in fast charge carrier separation and transportation [59]. Third, the large surface area plays a key role in the increment of the active site, resulting in an increasing degradation rate of SCNTx samples. It is noted that the content of SCN in the hybrid has an optimal value $(36.5~\\mathrm{wt\\%})$ . When the amount of SCN is further increased, the photocatalytic performance of composites is deteriorated. This can be ascribed to the fact that most of the photoinduced $\\mathrm{e^{-}{\\cdot}h^{+}}$ pairs from extra uncoupled SCN are recombined and do not participate in photocatalytic reactions due to the absence of heterojunction interfaces. These results further verify the effectiveness of the hybridization. \n\nFigure 6(c) shows the absorbance of CR aqueous solutions with the SCNT6 sample versus the exposure time to the xenon lamp. Particularly, the concentration of the CR solution containing the SCNT6 photocatalyst quickly declined to below $5\\%$ of the initial value after $60~\\mathrm{{min}}$ of illumination. Furthermore, the stability of the composite was verified by the photodegradation cycling tests using the SCNT6 sample. The variations in concentration of CR in every cycle are shown in Fig. 6(d). The results revealed that the photocatalytic activity of the composite was not weakened after 5 cycles. Moreover, the FT-IR spectra (Fig. 6(e)) of the used and fresh SCNT6 samples displayed identical typical features, indicating its excellent chemical stability. \n\n# 3.4. Charge separation and charge transfer \n\nPhotoluminescence spectroscopy was applied to analyze the separation efficiency of the photoinduced $\\mathrm{e^{-}{\\cdot}h^{+}}$ pairs. Figure \n\n![](images/72aae72e6a8b870787685f3d5ae4a7e39a61710d164fb018fd031b03605a2596.jpg) \nFig. 6. (a) Photocatalytic activity curves of SCN, ${\\mathrm{TiO}}_{2},$ and $\\mathrm{SCN}/\\mathrm{TiO}_{2}$ composites for the degradation of CR aqueous solution under xenon lamp irradiation; (b) Comparison of the apparent rate constants $k\\left(10^{-3}\\operatorname*{min}^{-1}\\right)$ ) of the SCN, ${\\mathrm{TiO}}_{2},$ and $\\mathsf{S C N/T i O_{2}}$ composites of the degradation of CR under xenon lamp irradiation; (c) Adsorption peaks of CR aqueous solution in the presence of the SCNT6 sample with increasing irradiation time under xenon lamp irradiation; (d) Circulating runs in the decomposition of CR for the SCNT6 sample under xenon lamp irradiation; (e) FT-IR patterns of the SCNT6 sample before and after 5 circulating runs. \n\n![](images/e227f65c59418d9d5e2ebf8120af4c8e840ec70f27f2c538cc6e9fa2d19f1983.jpg) \nFig. 7. (a) PL spectra of $\\mathrm{TiO}_{2},$ , SCN, and SCNT6 under ${320}\\mathrm{nm}$ excitation; (b) Time-resolved transient PL decay of SCN and SCNT6; (c) Transient photocurrent responses of ${\\mathrm{TiO}}_{2},$ SCN, and SCNT6 under xenon lamp irradiation; (d) EIS spectra of ${\\mathrm{TiO}}_{2},$ SCN, and SCNT6 under xenon lamp irradiation; (e) MS plots for $\\mathrm{TiO}_{2}$ and SCN; (f) MS plot for g $\\small-\\mathbf{C}_{3}\\mathbf{N}_{4}.$ . \n\n7(a) shows the PL spectra of the as-prepared SCN, ${\\mathrm{TiO}}_{2},$ and SCNTx samples under $320~\\mathrm{{nm}}$ light excitation. In accordance with the previous reports, no obvious emission peak was detected for pristine $\\mathrm{TiO}_{2}$ [60,61]. Although the SCN displayed the strongest PL intensity, the peak intensities of SCNTx hybrids were remarkably weakened after the SCN coupled with $\\mathrm{TiO}_{2}$ . The SCNT5 sample did not exhibit any obvious emission peak because of the low content of SCN in the composite. However, the other composites presented remarkable PL signals. Among the SCNTx $\\left(x=6,7\\right.$ , and 8) samples, the SCNT6 sample showed the lowest PL intensity, suggesting that the recombination of charge carriers in the composite was greatly restrained due to the construction of the heterojunction at the interface between SCN and $\\mathrm{TiO}_{2}$ . The extreme inhibition of the recombination of $\\mathrm{e^{-}{\\cdot}h^{+}}$ pairs could make the hybrid release more photoinduced carriers to activate the photocatalytic reaction. Thus, it can be inferred that the SCNT6 sample possesses the highest photocatalytic activity (Fig. 6(b)). In addition, the TRPL spectra of SCN and SCNT6 (Fig. 7(b)) further elucidate the difference in the recombination process of photoinduced carriers in intrinsic SCN and SCNT6 samples. The fitting parameters and average lifetimes are summarized in Fig. 7(b). Evidently, the SCNT6 sample presents an increased short $\\tau_{1}=3.04$ ns), long $(\\tau_{2}=$ 13.16 ns), and average ${\\tau_{\\mathrm{m}}}=10.93$ ns) emission lifetime in comparison with the intrinsic SCN $\\tau{1}=3.13$ ns, $\\tau{_{2}}=12.98~\\mathrm{ns}$ , $\\tau_{\\mathrm{m}}~=~10.62~\\mathrm{ns}]$ . The lengthened fluorescence lifetime of the SCNT6 sample further confirms the efficient separation of photoinduced $\\mathbf{e}^{-}{\\mathrm{-}}\\mathbf{h}^{+}$ pairs. \n\nMoreover, the transient photocurrent response and electrochemical impedance were measured on a photoelectrochemical test device with a Xe lamp to further verify the difference in carrier separation efficiency under light irradiation. The cyclic photocurrent curves of pure ${\\mathrm{TiO}}_{2},$ SCN, and SCNT6 are shown in Fig. 7(c). In these curves, the photocurrent intensities display sharp increases and drops when the light source was turned on and off, indicating the generation of photoinduced electrons under the light illumination. Particularly, the electrode coated with the SCNT6 sample exhibits significantly higher current intensities than that of bare $\\mathrm{TiO}_{2}$ or SCN. In general, the photocurrent intensity is positively related to the separation efficiency of the photoinduced electron-hole pair in the material, and the high separation efficiency enhances the photocatalytic activity [62,63]. Therefore, it is not difficult to understand that the SCNT6 sample with higher separation efficiency exhibits a higher photocatalytic activity than bare $\\mathrm{TiO}_{2}$ and SCN. Figure 7(d) shows the Nyquist plots of the pure ${\\mathrm{TiO}}_{2},$ SCN, and SCNT6. The electron-transfer resistance in a sample is equivalent to the semicircle diameter on an EIS plot. The smaller arc radius of SCNT6 suggests that the charge transfer resistance in the composite sample was lower than that of the $\\mathrm{TiO}_{2}$ and SCN samples. In other words, the migration and separation efficiencies of carriers in the SCNT6 sample are obviously enhanced because of the formation of the heterojunction. All of these results demonstrate the superiority of the SCNTx composites over the single component in the electron-hole transportation and separation. \n\nIt is critical to identify the band structures of the composite components to investigate the enhancement mechanism of photocatalytic activity. Figure 7(e) shows the Mott-Schottky curves of the $\\mathrm{TiO}_{2}$ nanofibers and SCN sample. Their positive slopes manifest that both $\\mathrm{TiO}_{2}$ nanofibers and SCN samples belong to the $\\mathfrak{n}$ -type semiconductor. Therefore, their CB positions can be estimated by the flat band potentials, which are ascertained according to the $x$ -intercepts of the linear regions of their Mott-Schottky curves [64]. Consequently, the extrapolated CB positions of $\\mathrm{TiO}_{2}$ nanofibers and SCN samples are $-0.88$ and $-1.36~\\mathrm{V},$ , respectively (vs Ag/AgCl, $\\mathrm{\\pH}=7\\mathrm{\\cdot}$ . These values correspond to $-0.25$ and $-0.73{\\mathrm{~V~}}$ (vs NHE, $\\mathrm{\\boldmath~\\pH~}=0\\dot{\\mathrm{\\boldmath~\\sigma~}}$ ). According to the band gaps of $\\mathrm{TiO}_{2}$ $\\ensuremath{\\left[3.28\\mathrm{\\eV}\\right]}$ and SCN (2.43 eV), their VB positions are calculated to be 3.03 and $1.7\\:\\mathrm{V}$ (vs NHE, $\\mathrm{\\boldmath~\\pH~}=0\\dot{\\mathrm{\\boldmath~\\sigma~}}$ ), respectively. Analogously, Fig. 7(f) shows that the CB position of pure $\\mathrm{g-C_{3}N_{4}}$ is $-0.65\\mathrm{\\DeltaV}$ (vs NHE, $\\mathrm{\\pH}=0\\mathrm{\\cdot}$ ). Clearly, the S-doped $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ with a stronger reductive performance than pure $\\mathrm{g-C_{3}N_{4}}$ will endow the composites with an enhanced photocatalytic activity [65,66]. \n\n# 3.5. Possible photocatalytic mechanism \n\nIn order to probe the exact active species and identify the electron transfer mechanism, radical trapping experiments were conducted for the degradation process of CR solution with SCNTx composites. ${\\tt N a}_{2}{\\tt C}_{2}0_{4},$ isopropanol (IPA), and benzoquinone (BQ) were adopted as the $\\ln^{+}$ scavenger, •OH quencher, and $\\bullet0_{2}\\cdot$ scavenger in the trapping experiments, respectively. As shown in Fig. 8(a), the BQ had the strongest negative effects on the degradation rate for CR. The IPA played a relatively weaker role in photocatalytic activity than BQ. However, the $\\mathsf{N a}_{2}\\mathsf{C}_{2}0_{4}$ had no influence on the degradation process. These results clearly demonstrate that both $\\bullet0_{2^{-}}$ and •OH species play an essential role in the CR photocatalytic degradation process, but the $\\ln^{+}$ play a minor role. To further confirm the above conclusions, the ESR analyses were performed using 5,5-dimethyl-1-pyrroline N-oxide (DMPO) as a spin-trapping agent. In Fig. 8(b), no signal of $\\bullet0_{2^{-}}$ was detected in the absence of light irradiation, but the 1:1:1:1 quadruple signals were observed after the sample had been illuminated by the simulated solar light. Moreover, the signal intensities gradually increased with the increase in the illumination time. For •OH (Fig. 8(c)), a similar phenomenon was observed; the gradually enhanced 1:2:2:1 characteristic signals were detected when the light was on. The results of the trapping experiments and ESR tests revealed that the $\\bullet0_{2}\\overline{{\\cdot}}$ and $\\bullet0\\mathrm{H}$ radicals, which were generated in the presence of the SCNT6 composite under the light irradiation, were the major active components in the photocatalytic degradation process. It is noteworthy that the $\\bullet0_{2^{-}}$ radical cannot be generated if the charge immigration in the composite follows the conventional type II heterojunction mechanism. Obviously, the previously introduced S-scheme heterojunction mechanism is a better candidate to explain the enhancement mechanism of photocatalytic degradation activity for SCNTx composite photocatalysts. \n\nFigure 9(a) shows that $\\mathrm{TiO}_{2}$ with a larger work function $\\left(6.58~\\mathrm{eV}\\right)$ is an oxidation-type photocatalyst. Conversely, pure $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ with a smaller work function $\\left(4.18\\ \\mathrm{~eV}\\right)$ is a reduction-type photocatalyst [67]. To clarify the influence of sulfur on the electrostatic potential of $\\underline{{\\mathbf{g}}}\\mathbf{-}\\mathbf{C}_{3}\\mathbf{N}_{4},$ the density functional theory (DFT) was used to calculate the work function of SCN. As shown in Fig. 9(b), the work function of SCN is $3.57~\\mathrm{eV}_{\\cdot}$ which is smaller than that of pure $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ and in agreement with the previous reports [68,69]. In general, the work function of a material is negatively related to its Fermi level. Compared with ${\\mathrm{TiO}}_{2},$ the SCN with a smaller work function possessed a higher Fermi level (vs. vacuum level). Therefore, once the two materials were contacted together, the electrons spontaneously immigrated from SCN to $\\mathrm{TiO}_{2}$ across their interface until their Fermi levels achieved equilibrium (Fig. 9(c)). The electron output from SCN was equivalent to the positive charging process, resulting in the upward bent band edge of SCN due to the loss of electrons. Contrarily, the electron input to $\\mathrm{TiO}_{2}$ was equivalent to the negative charging process, resulting in the downward bent band edge of $\\mathrm{TiO}_{2}$ due to the accumulation of electrons. Simultaneously, an internal electric field was formed at the interface of $\\mathrm{TiO}_{2}$ and SCN. Under light irradiation, the photons absorbed by $\\mathrm{TiO}_{2}$ and SCN excited the electrons from their respective VB to CB. Benefiting from the internal electric field, band edge bending, and Coulomb interaction, some electrons (CB of $\\mathrm{TiO}_{2}\\dot{.}$ ) were easily recombined with holes (VB of SCN), but the recombination of some SCN CB electrons and $\\mathrm{TiO}_{2}$ VB holes was restrained. Figure 9(c) shows the charge transfer mechanism of the S-scheme heterojunction between $\\mathrm{TiO}_{2}$ and SCN. The relatively useless $\\mathrm{TiO}_{2}$ CB electrons and SCN VB holes are quenched, but the SCN CB electrons and $\\mathrm{TiO}_{2}\\mathrm{VB}$ holes with the stronger redox abilities remain. Therefore, this electron transfer process endows the hybrid with a supreme redox capacity and has been confirmed by the radical trapping experiments and ESR tests. The in situ XPS spectra under light irradiation also provide strong evidence for the electron transfer route following the S-scheme heterojunction mechanism (Fig. 3). The binding energies of Ti $2p$ and O 1s for SCNT6 under light irradiation exhibit slightly positive shifts compared with the corresponding values without irradiation. Conversely, the binding energies of $\\texttt{C}1s$ and N 1s under light irradiation showed negative shifts. The converse changes in binding energy with and without irradiation unequivocally validate that the photoinduced electrons in $\\mathrm{TiO}_{2}$ transfer to SCN under the light illumination. Consequently, the S-scheme heterojunction mechanism is more suitable to elucidate the reason for enhanced photocatalytic activity in the photodegradation of CR. \n\n![](images/603b43a0d1ea7bff4ae829b1e83447850acbec3257256edc4ebff55a743b2c75.jpg) \nFig. 8. (a) Photocatalytic activities of the SCNT6 sample for CR degradation with disparate scavengers; ESR spectra of SCNT6 under dark and simulated solar light: DMPO $\\bullet0_{2}\\overline{{-}}$ (b) in methanol dispersions and DMPO •OH (c) in aqueous dispersions. \n\n![](images/f442af31d402b1bd5aa221d2896487a17a6039b71c15c1c96b4a811da2e13d0c.jpg) \nFig. 9. (a) Calculated electrostatic potentials for the (101) face of $\\mathrm{TiO}_{2}$ and (b) SCN. The blue and red dashed lines denote the Fermi level and vacuum energy level, respectively. In the geometric structures of $\\mathrm{TiO}_{2}$ and SCN, the cyan, red, blue, orange, and yellow spheres stand for Ti, O, C, N, and S atoms respectively. (c) Proposed step-scheme heterojunction photocatalytic mechanism for $\\mathrm{SCN/TiO_{2}}$ . \n\n# 4. Conclusions \n\nIn summary, a series of $\\mathsf{S C N/T i O_{2}}$ S-scheme photocatalysts were prepared by electrospinning and calcination. The as-prepared $\\mathsf{S C N/T i O_{2}}$ composite exhibited a remarkably improved photocatalytic activity in degradation of CR compared with the pure $\\mathrm{TiO}_{2}$ and SCN. The enhanced photocatalytic activity can be ascribed to the 1D structure, abundant reactive sites, and constructed heterojunction. The results of XPS, EPR, and DFT calculations prove that the S-scheme heterojunction mechanism is a rational theory to expound the electron immigration process in composites, especially under light irradiation. This work can enrich our knowledge of the design and fabrication of novel S-scheme heterojunction photocatalysts, and also provides an effective strategy for solving environmental pollution in the future. \n\n# References \n\n[1] P. Senthilkumar, D. A. Jency, T. Kavinkumar, D. Dhayanithi, S. Dhanuskodi, M. Umadevi, S. Manivannan, N. V. Giridharan, V. Thiagarajan, M. Sriramkumar, K. Jothivenkatachalam, ACS Sustainable Chem. Eng., 2019, 7, 12032–12043. \n[2] H. Chen, S. Wageh, A. A. Al-Ghamdi, H. Y. Wang, J. G. Yu, C. J. Jiang, J. Colloid Interface Sci., 2019, 537, 736–745. \n[3] Y. Q. Zheng, B. Cheng, W. You, J. G. Yu, W. K. Ho, J. Hazard. Mater., \n\n# Graphical Abstract \n\nChin. J. Catal., 2021, 42: 56–68 doi: 10.1016/S1872-2067(20)63634-8 \n\n# Sulfur-doped $\\mathbf{g}–\\mathbf{C}_{3}\\mathbf{N}_{4}/\\mathbf{TiO}_{2}$ S-scheme heterojunction photocatalyst for Congo Red photodegradation \n\nJuan Wang, Guohong Wang \\*, Bei Cheng \\*, Jiaguo Yu, Jiajie Fan Hubei Normal University; Wuhan University of Technology; Zhengzhou University \n\n![](images/af6250ea8be7ae4396822d4ef3d56b5c04428e60cbb91860299afb35b24ccca5.jpg) \nThe S-doped $\\mathrm{g}{\\mathrm{-}}\\mathrm{C}_{3}\\mathrm{N}_{4}$ (SCN) possesses a stronger reductive performance than pure $\\mathrm{g-C_{3}N_{4}}$ . The S-scheme heterojunction formed by SCN and $\\mathrm{TiO}_{2}$ can improve the separation efficiency of photoinduced electron-hole pairs as well as the photocatalytic activity. \n\n2019, 369, 214–225. [4] S. Y. Dong, L. F. Cui, W. Zhang, L. J. Xia, S. J. Zhou, C. K. Russellc, M. Fand, J. L. Feng, J. H. Sun, Chem. Eng. J., 2020, 384, 123279. [5] Y. Guo, W. X. Shi, Y. F. Zhu, Y. P. Xu, F. Y. Cui, Appl. Catal. B, 2020, 262, 118262. [6] Y. Y. Fan, W. G. Ma, D. X. Han, S. Y. Gan, X. D. Dong, L. Niu, Adv. Mater., 2015, 27, 3767–3773. [7] J. Wang, G. H. Wang, X. H. Wei, G. Liu, J. Li, Appl. Surf. Sci., 2018, 456, 666–675. [8] C. B. Bie, B. C. Zhu, F. Y. Xu, L. Y. Zhang, J. G. Yu, Adv. Mater., 2019, 31, 1902868. [9] Q. L. Xu, L. Y. Zhang, J. G. Yu, S. Wageh, A. A. Al-Ghamdi, M. Jaroniec, Mater. Today, 2018, 21, 1042–1063. \n[10] C. Han, Y. D. Wang, Y. P. Lei, B. Wang, N. Wu, Q. Shi, Q. Li, Nano Res., 2015, 8, 1199–1209. \n[11] P. Singh, K. Mondal, A. Sharma, J. Colloid Interface Sci., 2013, 394, 208–215. \n[12] G. D. Lim, J. H. Yoo, Y. I. Lee, J. Alloys Compd., 2019, 806, 1060–1067. \n[13] L. Wang, C. B. Zhang, F. Gao, G. Mailhot, G. Pan, Chem. Eng. J., 2017, 314, 622–630. \n[14] G. Liu, G. H. Wang, Z. H. Hu, Y. R. Su, L. Zhao, Appl. Surf. Sci., 2019, 465, 902–910. \n[15] R. Asahi, T. Morikawa, H. Irie, T. Ohwaki, Chem. Rev., 2014, 114, 9824–9852. \n[16] M. Pelaez, N. T. Nolan, S. C. Pillai, M. K. Seery, P. Falaras, A. G. Kontos, P. S. M. Dunlop, J. W. J. Hamilton, J. A. Byrne, K. O’Shea, M. H. Entezari, D. D. Dionysiou, Appl. Catal. B, 2012, 125, 331–349. \n[17] W. K. Jo, S. Kumar, M. A. Isaacs, A. F. Lee, S. Karthikeyan, Appl. Catal. B, 2017, 201, 159–168. \n[18] A. Y. Meng, L. Y. Zhang, B. Cheng, J. G. Yu, Adv. Mater., 2019, 31, 1807660. \n[19] J. Y. Park, K. I. Choi, J. H. Lee, C. H. Hwang, D. Y. Choi, J. W. Lee, Mater. Lett., 2013, 97, 64–66. \n[20] F. Y. Xu, L. Y. Zhang, B. Cheng, J. G. Yu, ACS Sustainable Chem. Eng., 2018, 6, 12291–12298. \n[21] Y. J. Sun, J. Z. Liao, F. Dong, S. J. Wu, L. D. Sun, Chin. J. Catal., 2019, 40, 362–370. \n[22] W. L. Yu, S. Zhang, J. X. Chen, P. F. Xia, M. H. Richter, L. F. Chen, W. Xu, J. P. Jin, S. L. Chen, T. Y. Peng, J. Mater. Chem. A, 2018, 6, 15668–15674. \n[23] J. X. Low, B. Z. Dai, T. Tong, C. J. Jiang, J. G. Yu, Adv. Mater., 2019, 31, 1802981. \n[24] C. Chen, J. L. Zhou, J. F. Geng, R. Y. Bao, Z. H. Wang, J. X. Xia, H. Li, Appl. Surf. Sci., 2020, 503, 144287. \n[25] F. F. Mei, K. Dai, J. F. Zhang, W. Y. Li, C. H. Liang, Appl. Surf. Sci., 2019, 488, 151–160. \n[26] J. Wang, Q. Zhang, F. Deng, X. B. Luo, D. D. Dionysiou, Chem. Eng. J., 2020, 379, 122264. \n[27] H. X. Fan, H. L. Zhou, W. J. Li, S. N. Gu, G. W. Zhou, Appl. Surf. Sci., 2020, 504, 144351. \n[28] X. B. Li, J. T. Huang, J. Xiong, Z. Chen, B. B. Kang, J. Y. Liu, H. Li, Z. J. Feng, X. M. Gao, J. Ma, J. Hazard. Mater., 2020, 387, 121690. \n[29] X. M. Jia, Q. F. Han, M. Y. Zheng, H. P. Bi, Appl. Surf. Sci., 2019, 489, 409–419. \n[30] H. N. Ge, F. Y. Xu, B. Cheng, J. G. Yu, W. K. Ho, ChemCatChem, 2019, 11, 6301–6309. \n[31] W. L. Yu, J. X. Chen, T. T. Shang, L. F. Chen, L. Gu, T. Y. Peng, Appl. Catal. B, 2017, 219, 693–704. \n[32] X. B. Li, J. Xiong, Y. Xu, Z. J. Feng, J. T. Huang, Chin. J. Catal., 2019, 40, 424–433. \n[33] F. F. Mei, Z. Li, K. Dai, J. F. Zhang, C. H. Liang, Chin. J. Catal., 2020, 41, 41–49. \n[34] Q. Xie, W. M. He, S. W. Liu, C. H. Li, J. F. Zhang, P. K. Wong, Chin. J. Catal., 2020, 41, 140–153. \n[35] Q. Yan, G. F. Huang, D. F. Li, M. Zhang, A. L. Pan, W. Q. Huang, J. Mater. Sci. Technol., 2018, 34, 2515–2520. \n[36] E. X. Han, Y. Y. Li, Q. H. Wang, W. Q. Huang, L. Luo, W. Y. Hu, G. F. Huang, J. Mater. Sci. Technol., 2019, 35, 2288–2296. \n[37] J. Wang, G. H. Wang, X. Wang, Y. Wu, Y. R. Su, H. Tang, Carbon, 2019, 149, 618–626. \n[38] L. Ke, P. F. Li, X. Wu, S. J. Jiang, M. B. Luo, Y. H. Liu, Z. G. Le, C. Z. Sun, S. Q. Song, Appl. Catal. B, 2017, 205, 319–326. \n[39] M. Jourshabani, Z. Shariatinia, A. Badiei, J. Mater. Sci. Technol., 2018, 34, 1511–1525. \n[40] Y. J. Ren, D. Q. Zeng, W. J. Ong, Chin. J. Catal., 2019, 40, 289–319. \n[41] Y. Xia, Z. H. Tian, T. Heil, A. Y. Meng, B. Cheng, S. W. Cao, J. G. Yu, M. Antonietti, Joule, 2019, 3, 2792–2805. \n[42] L. Tang, C. Y. Feng, Y. C. Deng, G. M. Zeng, J. J. Wang, Y. N. Liu, H. P. Feng, J. J. Wang, Appl. Catal. B, 2018, 230, 102–114. \n[43] S. B. Yang, Y. J. Gong, J. S. Zhang, L. Zhan, L. L. Ma, Z. Y. Fang, R. Vajtai, X. C. Wang, P. M. Ajayan, Adv. Mater., 2013, 25, 2452–2456. \n[44] M. E. Aguirre, R. X. Zhou, A. J. Eugene, M. I. Guzman, M. A. Grela, Appl. Catal. B, 2017, 217, 485–493. \n[45] R. R. Hao, G. H. Wang, H. Tang, L. L. Sun, C. Xu, D. Y. Han, Appl. Catal. B, 2016, 187, 47–58. \n[46] H. F. Qin, W. H. Lv, J. R. Bai, Y. Zhou, Y. P. Wen, Q. T. He, J. H. Tang, L. B. Wang, Q. F. Zhou, J. Mater. Sci., 2019, 54, 4811–4820. \n[47] S. Y. Tan, Z. P. Xing, J. Q. Zhang, Z. Z. Li, X. Y. Wu, J. Y. Cui, J. Y. Kuang, J. W. Yin, W. Zhou, Int. J. Hydrogen Energy, 2017, 42, 25969–25979. \n[48] K. S. W. Sing, D. H. Everett, R. A. W. Haul, L. Moscou, R. A. Pierotti, J. Rouquerol, T. Siemieniewska, Pure Appl. Chem., 1985, 57, 603–619. \n[49] F. Y. Xu, B. C. Zhu, B. Cheng, J. G. Yu, J. S. Xu, Adv. Optical Mater., 2018, 1800911. \n[50] F. Chang, J. Zhang, Y. C. Xie, J. Chen, C. L. Li, J. Wang, J. R. Luo, B. Q. Deng, X. F. Hu, Appl. Surf. Sci., 2014, 311, 574–581. \n[51] T. P. Hu, K. Dai, J. F. Zhang, G. P. Zhu, C. H. Liang, Mater. Lett., 2019, 257, 126740. \n[52] A. Y. Meng, B. C. Zhu, B. Zhong, L. Y. Zhang, B. Cheng, Appl. Surf. Sci., 2017, 422, 518–527. \n[53] J. H. Luo, Z. X. Lin, Y. Zhao, S. J. Jiang, S. Q. Song, Chin. J. Catal., 2020, 41, 122–130. \n[54] J. W. Fu, B. C. Zhu, C. J. Jiang, B. Cheng, W. You, J. G. Yu, Small, 2017, 13, 1603938. \n[55] H. P. Li, T. X. Hu, R. J. Zhang, J. Q. Liu, W. G. Hou, Appl. Catal. B, 2016, 188, 313–323. \n[56] P. F. Xia, S. W. Cao, B. C. Zhu, M. J. Liu, M. S. Shi, J. G. Yu, Y. F. Zhang, Angew. Chem. Int. Ed., 2020, 59, 5218–5225. \n[57] X. C. Hu, G. H. Wang, J. Wang, Z. F. Hu, Y. R. Su, Appl. Surf. Sci., 2020, 511, 145499. \n[58] J. Wang, G. H. Wang, J. Jiang, Z. Wan, Y. R. Su, H. Tang, J. Colloid Interface Sci., 2020, 564, 322–332. \n[59] J. Li, M. Zhang, Q. Y. Li, J. J. Yang, Appl. Surf. Sci., 2017, 391, 184–193. \n[60] Y. G. Tan, Z. Shu, J. Zhou, T. T. Li, W. B. Wang, Z. L. Zhao, Appl. Catal. B, 2018, 230, 260–268. \n[61] R. Wang, J. Shen, W. J. Zhang, Q. Q. Liu, M. Y. Zhang, Zulfiqar, H. Tang, Ceram. Int., 2020, 46, 23–30. \n[62] N. Nie, L. Y. Zhang, J. W. Fu, B. Cheng, J. G. Yu, Appl. Surf. Sci., 2018, 441, 12–22. \n[63] Y. P. Zhu, M. Li, Y. L. Liu, T. Z. Ren, Z. Y. Yuan, J. Phys. Chem. C, 2014, 118, 10963–10971. \n[64] F. He, A. Y. Meng, B. Cheng, W. K. Ho, J. G. Yu, Chin. J. Catal., 2020, 41, 9–20. \n[65] C. Z. Sun, H. Zhang, H. Liu, X. X. Zheng, W. X. Zou, L. Dong, L. Qi, Appl. Catal. B, 2018, 235, 66–74. \n[66] M. Jourshabani, Z. Shariatinia, G. Achari, C. H. Langfordc, A. Badiei, J. Mater. Chem. A, 2018, 6, 13448–13466. \n[67] J. W. Fu, Q. L. Xu, J. X. Low, C. J. Jiang, J. G. Yu, Appl. Catal. B, 2019, 243, 556–565. \n[68] Y. L. Wang, Y. Tian, L. K. Yan, Z. M. Su, J. Phys. Chem. C, 2018, 122, 7712–7719. \n[69] L. M. Hu, J. T. Yan, C. L. Wang, B. Chai, J. F. Li, Chin. J. Catal., 2019, 40, 458–469. \n\n# 光降解刚果红的S型硫掺杂 $\\mathbf{g}{\\mathbf{-}}\\mathbf{C}_{3}\\mathbf{N_{4}}/\\mathbf{TiO}_{2}$ 异质结光催化剂 \n\n王 娟a, 王国宏a,\\*, 程 蓓b,#, 余家国b, 范佳杰ca湖北师范大学化学化工学院, 湖北师范大学先进材料研究院, 污染物分析与资源化技术湖北省重点实验室, 湖北黄石435002b武汉理工大学材料复合新技术国家重点实验室, 湖北武汉430070郑州大学材料科学与工程学院, 河南郑州450001 \n\n摘要: 含有机物工业废水的处理仍然是人类实现可持续发展的重大挑战. 而光催化作为一种先进的氧化环保技术, 以其反应条件温和、能耗相对较低的优点在有机废水处理中受到越来越多的关注. 近年来, 人们设计和合成了许多不同结构和形状的光催化剂. 特别是金属氧化物半导体以其适宜的能带结构、稳定的物化性质、无毒性等特点已成为光催化降解有机废水的研究热点. 此外, 一维纳米结构(1D)已被证实有利于光催化降解过程, 其优势在于比表面积大, 离子的迁移路径短,以及独特的一维电子转移轨道. 尤其是 $\\mathrm{TiO}_{2}$ 纳米纤维由于其亲水性、特殊的形貌和合适的能带位置, 在污染物水溶液的处理中表现出优异的光催化性能. 然而, $\\mathrm{TiO}_{2}({\\sim}3.2\\ \\mathrm{eV})$ 的宽禁带、光生载流子的易复合等缺陷导致其光利用率较低, 限制了其实际应用. 因此, 人们提出了许多提高光催化活性的策略, 如掺杂金属或非金属元素、负载贵金属、构建异质结等. \n\n构建梯形(S型)异质结已被证实是提高复合材料光催化活性的一种有前途的策略. S型异质结不仅能有效地分离光生电子和空穴, 而且还原能力低的半导体CB上的电子和氧化能力低的半导体VB上的空穴复合, 而氧化还原能力较强的空穴和电子分别被保留. 因此, 这一电子转移过程赋予了复合物最大的氧化还原能力. 同时, 在 $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ 中引入硫元素可以拓宽其光吸收范围, 从而产生更多的光生载流子. 此外, 额外的表面杂质将有助于 $\\mathrm{{e^{-}}\\mathrm{{h^{+}}}}$ 对的分离, 其光催化活性明显高于单纯的 $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ . \n\n综合一维纳米结构、硫掺杂和S型异质结的优势, 本文采用静电纺丝和煅烧法制备了一系列硫掺杂的 $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ $\\mathrm{(SCN)/TiO}_{2}$ S型光催化剂. 制备的 $\\mathrm{SCN}/\\mathrm{TiO}_{2}$ 复合材料在光催化降解刚果红(CR)水溶液中表现出比纯 $\\mathrm{TiO}_{2}$ 和SCN更优越的光催化性能. 光催化活性的显著增强是由于一维分布的纳米结构和S型异质结. 此外, XPS分析和DFT计算表明, 电子从SCN通过 $\\mathrm{SCN}/\\mathrm{TiO}_{2}$ 复合材料的界面转移到 $\\mathrm{TiO}_{2}$ . 在模拟太阳光照射下, 界面内建电场、带边缘弯曲和库仑相互作用协同促进了复合物相对无用的电子和空穴的复合. 因此, 剩余的电子和空穴具有较高的还原性和氧化性, 使复合材料具有最高的氧化还原能力. 这些结果通过自由基捕获实验、ESR实验和XPS原位分析得到了充分的验证, 说明光催化剂中的电子迁移遵循S型异质结机理. 本文不仅可以丰富了新型S型异质结光催化剂的设计和制备方面的知识, 并为未来解决环境污染问题提供一个有前景的策略. \n\n关键词: $\\mathrm{TiO}_{2}$ 纳米纤维; 硫掺杂 $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ ; 梯形异质结光催化剂; 原位XPS; S型机理 \n\n收稿日期: 2020-03-17. 接受日期: 2020-04-26. 出版日期: 2021-01-05. \n\\*通讯联系人. 电话/传真: (0714)6515602; 电子邮箱: wanggh2003 $@$ 163.com \n#通讯联系人. 电话/传真: (027)87871029; 电子邮箱: chengbei2013 $@$ whut.edu.cn \n基金来源: 国家自然科学基金(51872220, 51932007, 51961135303, 21871217, U1905215, U1705251); 国家重点研发计划项目(2018YFB1502001); 中央高校基本科研基金(WUT: 2019IVB050). \n本文的电子版全文由Elsevier出版社在ScienceDirect上出版(http://www.sciencedirect.com/science/journal/18722067). " + }, + { + "id": "10.1002_anie.202016531", + "DOI": "10.1002/anie.202016531", + "DOI Link": "http://dx.doi.org/10.1002/anie.202016531", + "Relative Dir Path": "mds/10.1002_anie.202016531", + "Article Title": "Boosting Zinc Electrode Reversibility in Aqueous Electrolytes by Using Low-Cost Antisolvents", + "Authors": "Hao, JN; Yuan, LB; Ye, C; Chao, DL; Davey, K; Guo, ZP; Qiao, SZ", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "Antisolvent addition has been widely studied in crystallization in the pharmaceutical industries by breaking the solvation balance of the original solution. Here we report a similar antisolvent strategy to boost Zn reversibility via regulation of the electrolyte on a molecular level. By adding for example methanol into ZnSO4 electrolyte, the free water and coordinated water in Zn2+ solvation sheath gradually interact with the antisolvent, which minimizes water activity and weakens Zn2+ solvation. Concomitantly, dendrite-free Zn deposition occurs via change in the deposition orientation, as evidenced by in situ optical microscopy. Zn reversibility is significantly boosted in antisolvent electrolyte of 50 % methanol by volume (Anti-M-50 %) even under harsh environments of -20 degrees C and 60 degrees C. Additionally, the suppressed side reactions and dendrite-free Zn plating/stripping in Anti-M-50 % electrolyte significantly enhance performance of Zn/polyaniline coin and pouch cells. We demonstrate this low-cost strategy can be readily generalized to other solvents, indicating its practical universality. Results will be of immediate interest and benefit to a range of researchers in electrochemistry and energy storage.", + "Times Cited, WoS Core": 696, + "Times Cited, All Databases": 719, + "Publication Year": 2021, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000621048500001", + "Markdown": "# Boosting Zinc Electrode Reversibility in Aqueous Electrolytes by Using Low-Cost Antisolvents \n\nJunnan Hao+, Libei Yuan+, Chao Ye, Dongliang Chao, Kenneth Davey, Zaiping Guo,\\* and Shi-Zhang Qiao\\* \n\nAbstract: Antisolvent addition has been widely studied in crystallization in the pharmaceutical industries by breaking the solvation balance of the original solution. Here we report a similar antisolvent strategy to boost Zn reversibility via regulation of the electrolyte on a molecular level. By adding for example methanol into $Z n S O_{4}$ electrolyte, the free water and coordinated water in $Z n^{2+}$ solvation sheath gradually interact with the antisolvent, which minimizes water activity and weakens $Z n^{2+}$ solvation. Concomitantly, dendrite-free $Z n$ deposition occurs via change in the deposition orientation, as evidenced by in situ optical microscopy. Zn reversibility is significantly boosted in antisolvent electrolyte of $50\\%$ methanol by volume $(A n t i-M{-}50\\%)$ ) even under harsh environments of $-20^{\\circ}C$ and $60^{\\circ}C.$ Additionally, the suppressed side reactions and dendrite-free Zn plating/stripping in Anti-M$50\\%$ electrolyte significantly enhance performance of $Z n^{\\prime}$ polyaniline coin and pouch cells. We demonstrate this low-cost strategy can be readily generalized to other solvents, indicating its practical universality. Results will be of immediate interest and benefit to a range of researchers in electrochemistry and energy storage. \n\n# Introduction \n\nRechargeable aqueous $Z\\mathrm{n}$ -ion batteries are widely seen as practical alternatives to Li-ion batteries for applications in large-scale energy storage. This is because they are low cost, safe and environmentally benign, and require relatively facile manufacture.[1] However, at present they are unsatisfactory to meet market demands, since the metallic $Z\\mathrm{n}$ anode is intrinsically limited in reversibility in slightly acidic electrolyte.[2] $Z\\mathrm{n}$ dendrite growth is therefore a major drawback to developing highly reversible Zn electrodes. Zn dendrite growth compromises the Coulombic efficiency (CE) during battery cycling and shortens battery lifespan.[3] Although Zn metal has a high overpotential against hydrogen $\\left(\\mathrm{H}_{2}\\right)$ evolution, $\\mathrm{H}_{2}$ evolution inevitably occurs during both battery rest and battery operation. This significantly limits CE of the battery, and fluctuates hydroxyl ion $(\\mathrm{OH^{-}})$ concentration in local areas of the $Z\\mathrm{n}$ electrode.[4] Increased concentration of $\\mathrm{OH^{-}}$ drives the corrosion reaction of the $Z\\mathrm{n}$ electrode to form inactive $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ which becomes a barrier for ion/ electron diffusion, and negatively impacts $Z\\mathrm{n}$ reversibility.[5] Additionally, $Z\\mathrm{n}^{2+}$ forms a stable solvation structure with six water molecules in the electrolyte. This strong solvation results in a high energy barrier for $Z\\mathrm{n}^{2+}$ ions against desolvation and deposition.[6] Therefore, inhibition in the dendrite growth and side reactions as well as controlled regulation of the solvation structure are necessary for nextgeneration $Z\\mathrm{n}$ -based batteries in which reversibility of the $Z\\mathrm{n}$ anode is practically boosted. \n\nA number of approaches have been reported to enhance Zn electrode reversibility including, building artificial solid/ electrolyte interphases,[7] introducing an electrolyte additive,[8] modifying current collectors,[9] developing functional gel electrolyte,[10] and controlling $Z\\mathrm{n}$ deposition.[11] Highly concentrated $Z\\mathrm{n}$ -based electrolytes have recently been proposed for high-performance aqueous batteries.[6a,12] By decreasing the number of free water molecules in the electrolyte, the water-induced $\\mathrm{H}_{2}$ evolution and corrosion reaction were suppressed.[13] Additionally, the solvation sheath of $Z\\mathrm{n}^{2+}$ was modified and resulted in a meaningfully improved CE of the Zn electrode. However, costly electrolytes are a significant drawback to application to large-scale.[14] There is therefore widespread interest in finding a practical low-cost approach to improve $Z\\mathrm{n}$ reversibility. \n\nAntisolvent precipitation is based on integration of coordination chemistry and antisolvent effect, and is used for crystallization in drugs, polymers and perovskite.[15] A supercritical fluid is chosen as the antisolvent that is miscible with the original solvent, but which cannot dissolve the substrate in solution.[16] In antisolvent precipitation the original solvent gradually interacts with the antisolvent. This causes precipitation of the substrate by breaking the solvation balance in the original solution.[17] It was reckoned therefore that introducing an antisolvent into aqueous $Z\\mathrm{n}^{2+}$ -based electrolyte was likely to reduce the water activity and impact the $Z\\mathrm{n}^{2+}$ solvation sheath because of interaction between antisolvent and water, with the result to meaningfully boost $Z\\mathrm{n}$ battery performance. \n\nHere, we demonstrate a practical and low-cost antisolvent approach to regulate aqueous $\\mathrm{{\\calZ}n S O_{4}}$ electrolyte on the molecular level to boost Zn chemistry reversibility. Methanol as antisolvent was comprehensively investigated to show that the $Z\\mathrm{n}^{2+}$ solvation is weakened and $\\mathrm{H}_{2}$ evolution, together with $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ by-product are suppressed when the electrolyte contains $50\\mathrm{v}/\\mathrm{v}\\%$ methanol (volume ratio, denoted as Anti-M- $50\\%$ ). A video recorded via in situ optical microscopy confirmed $Z\\mathrm{n}$ dendrite-free deposition in the Anti-M- $50\\%$ . Consequently, the Zn electrode in Anti-M$50\\%$ electrolyte exhibited a meaningfully greater average CE than that in 2 M $\\mathrm{ZnSO_{4}}$ electrolyte of, respectively, $99.7\\%$ and $96.6\\%$ at $25^{\\circ}\\mathrm{C}.$ . Importantly, we show that this low-cost strategy can be used with other solvents, including ethanol and 1-propanol. This finding suggests generalizability and possible universal application of low-cost antisolvents to boost $Z\\mathrm{n}$ electrode reversibility. Additionally, Zn reversibility under harsh environments was investigated. Findings reveal the $Z\\mathrm{n}$ electrodes are shown to exhibit high plating/stripping CEs at both $-20^{\\circ}\\mathrm{C}$ and $60^{\\circ}\\mathrm{C}$ in Anti-M- $50\\%$ electrolyte. This low-cost antisolvent electrolyte also endowed the $Z\\mathrm{n}$ - based coin cells and pouch-cells with high reversible capacity and cycling stability. \n\n# Results and Discussion \n\nMany liquid alcohols are miscible with water through generating an H-bond, but are not readily soluble with $\\mathrm{{ZnSO_{4}}}$ salt. These are therefore regarded theoretically as antisolvents for aqueous $\\mathrm{ZnSO_{4}}$ electrolyte. In a logical and stepwise experimental approach, a series of common monohydric and polyhydric alcohols were studied as potential antisolvents in $2\\:\\mathrm{M}\\:Z_{\\mathrm{nSO_{4}}}$ electrolyte. As shown in Figure 1a, methanol forms a homogenous phase with aqueous $\\mathrm{ZnSO_{4}}$ electrolyte with addition of $33\\mathrm{v}/\\mathrm{v}\\%$ and $50\\mathrm{v}/\\mathrm{v}\\%$ (volume ratio), however, recrystallization of $\\mathrm{ZnSO_{4}}$ occurs with addition of $55\\%$ methanol. This finding suggests the stable solvation structure of $Z\\mathrm{n}^{2+}$ with water is damaged when excess antisolvent is added.[18] Ethanol is miscible with $\\mathrm{{ZnSO_{4}}}$ electrolyte in limited quantity, $25\\%$ (Figure 1b). An apparent delamination, instead of $\\mathrm{ZnSO_{4}}$ recrystallization, occurred in the electrolyte with addition of $30\\%$ ethanol. In behaviour similar to ethanol, delamination of antisolvent electrolyte occurred with addition of $12\\%$ 1-propanol (Figure S1, in the Supporting Information). However, no obvious delamination or recrystallization was observed following addition of polyhydric alcohols including, ethylene glycol and glycerol, with a relatively high ratio of $77\\%$ (Figure S2). This finding demonstrates that both solvents did not break the balance of $Z\\mathrm{n}^{2+}$ coordination in the electrolyte. To elucidate the underlying principles, the dielectric constant and molecular diameter of selected alcohols was compared in Figure 1 c. Polyhydric alcohols have a larger molecular size than monohydric alcohols. A consequence is that a high energy barrier is required for these to insert into the first (inner) $Z\\mathrm{n}^{2+}$ solvation sheath to break the solvation balance. Therefore, for the present work only monohydric alcohols were selected for comprehensive investigation. \n\nMethanol features the smallest molecular size at $4.3\\mathring\\mathrm{A}$ among the monohydric alcohols,[19] indicating that it more readily modifies $\\mathrm{ZnSO_{4}}$ electrolyte by replacing the water molecules in the $Z\\mathrm{n}^{2+}$ solvation sheath. Meanwhile, methanol has a dielectric constant of 37.2, a value significantly greater than for ethanol of 24.5 and 1-propanol of 20.1.[20] Benefiting from its small size and high dielectric constant, methanol can insert into the inner $Z\\mathrm{n}^{2+}$ solvation sheath and affect the $Z\\mathrm{n}^{2+}$ solvation balance by interacting with coordinated water. \n\nTo determine the impact of methanol on $\\mathrm{ZnSO_{4}}$ electrolyte and the coordination structure of $Z\\mathrm{n}^{2+}$ , various spectra were determined including, deuterium $^{2}\\mathrm{H}.$ , D) nuclear magnetic resonance (NMR), Raman spectra and Fourier transform infrared spectroscopy (FTIR). The $^2\\mathrm{H}$ peak in $2{\\bf M}$ $\\mathrm{ZnSO_{4}}$ electrolyte prepared with ${\\bf D}_{2}\\mathrm{O}$ is located at $\\approx4.705$ ppm in NMR spectra (Figure 1 d). Following introduction of methanol, the $^2\\mathrm{H}$ peak shifts higher and reaches $4.71\\mathrm{ppm}$ in Anti-M- $50\\%$ , indicating that the electron density of $^2\\mathrm{H}$ increases owing to the H-bond formation between $^2\\mathrm{H}$ in ${\\bf D}_{2}\\mathrm{O}$ with $\\mathrm{~o~}$ in methanol.[21] The H-bond formation in antisolvent electrolytes was confirmed by the Raman Spectra (Figure S3a). As the O-H stretching vibration of methanol overlaps that of the water molecule, the H-bond was investigated through the peak of C-O stretching and $\\mathrm{C-H}$ stretching vibration.[22] Compared with pure methanol, the CO stretching $\\mathrm{'}\\approx1033.4\\mathrm{cm}^{-1},$ ) gradually moves to lower wavenumber (blue shift) in antisolvent electrolyte (Figure 1 e). The C-O stretching reduces to, respectively, $\\approx1023.0\\mathrm{cm}^{-1}$ and $1018.5\\mathrm{cm}^{-1}$ in Anti-M- $50\\%$ and Anti-M- $33\\%$ . The reduction of C-O stretching vibration is mainly caused by the interaction between methanol and water.[23] As evidenced by the $\\mathrm{^{C-H}}$ stretching movement in Figure S3b, the H-bond also results in enhancement of $\\mathrm{C^{-}H}$ symmetric and asymmetric stretching vibration of methanol in antisolvent electrolyte. It is worth noting that compared with $2\\mathrm{M}\\mathrm{\\ZnSO_{4}}$ electrolyte, a shift of the $\\nu$ $(\\mathrm{SO_{4}}^{2-})$ vibration is seen in antisolvent electrolyte, which is due mainly to the formation of the contact ion pair $(Z\\mathrm{n}^{2+}\\mathrm{-OSO}_{3}^{2-})$ .[12b,24] This means that the $Z\\mathrm{n}^{2+}$ solvent structure was changed because the interaction of $Z\\mathrm{n}^{2+}$ with water molecules is weaker than the interaction between water and methanol. The coordinated water molecules in the first sheath are attracted by methanol, leading to a weakened solvation between water and $Z\\mathrm{n}^{2+}$ .[25] This phenomenon was evidenced by FTIR spectra (Figure S4). In addition to the shift of -OH stretching caused by the H-bond, the $\\nu$ $(\\mathrm{SO}_{4}^{2-})$ stretching located at $1073.2\\mathrm{cm}^{-1}$ in 2 M $\\mathrm{{ZnSO_{4}}}$ electrolyte shifts due to antisolvent methanol addition (Figure 1 f). The absorption peak of $\\nu$ $(\\mathrm{SO}_{4}^{2-})$ in Anti-M- $50\\%$ is seen to be $1088.5\\mathrm{cm}^{-1}$ . This value is relatively similar to that for $\\mathrm{ZnSO_{4}}$ powder of $\\approx1092.4~\\mathrm{cm}^{-1}$ and therefore confirms the modified $Z\\mathrm{n}^{2+}$ solvation sheath. The weakened $Z\\mathrm{n}^{2+}$ solvation affects the transference number $(t_{{Z}{\\mathrm{n}}^{2+}})$ in the electrolyte of Anti- $.M{-}50\\%$ .[26] As shown in Figure S5, $t_{{\\mathrm{Zn}}^{2+}}$ was computed to be 0.48, higher than that for aqueous $\\mathrm{{ZnSO_{4}}}$ electrolyte (0.34),[5,7a] which suggests a faster migration speed of $Z\\mathrm{n}^{2+}$ in Anti-M- $50\\%$ . \n\nSchematic Figure $1\\mathrm{g}$ illustrated the evolution of $Z\\mathrm{n}^{2+}$ solvation changes with methanol addition. Without methanol, $Z\\mathrm{n}^{2+}$ exhibits a stable double-layer solvated structure in aqueous $\\mathrm{{ZnSO_{4}}}$ electrolyte.[6a] Because of the H-bond formation, methanol molecules initially attract free water molecules out of the $Z\\mathrm{n}^{2+}$ solvation. These gradually insert into the outer and inner sheath of $Z\\mathrm{n}^{2+}$ , as the volume ratio of methanol increases. It significantly impacts $Z\\mathrm{n}^{2+}$ solvation, which ultimately disrupts the coordination balance of water and $Z\\mathrm{n}^{2+}$ in the inner sheath. $Z\\mathrm{n}^{2+}$ will be re-combined with ${\\mathrm{SO}}_{4}^{2-}$ and result in recrystallization. The $Z\\mathrm{n}^{2+}$ solvation structure can therefore be regulated by carefully controlling methanol addition. \n\n![](images/4292f9a7bf1875bf895e74ec6d0043f6ed42eae20847bfb813fcf662e66992e3.jpg) \nFigure 1. Antisolvent electrolyte preparation, and physical properties of various solutions. a) Preparation of methanol-based antisolvent electrolytes—inset shows recrystallization of $Z n S O_{4}$ in antisolvent electrolyte of $55\\%$ methanol. b) Preparation of ethanol-based antisolvent electrolytes—inset presents delamination of antisolvent electrolyte. c) Dielectric constant (green) and molecular diameter (yellow) of solvents. d) $^2{\\sf H}$ NMR spectra, e) Raman spectra, f) FTIR spectra. g) Schematic of changes in the $Z n^{2+}$ solvent sheath, together with methanol addition. \n\nThe sessile drop contact angle technique was employed to quantify the effects of antisolvent on wettability, since the wettability of $Z\\mathrm{n}$ foil will influence directly the energy barrier for $Z\\mathrm{n}$ nucleation formation and evolution. Because of its hydrophobic nature, $Z\\mathrm{n}$ metal exhibits a high contact angle of $86.5^{\\circ}$ in $\\mathrm{{ZnSO_{4}}}$ electrolyte (Figure 2 a). With methanol addition, however, the contact angle is highly significantly decreased (Figure 2 b, c). A low angle of $10.8^{\\circ}$ characterizes pure methanol (Figure 2d). These findings underscore a high wettability of $Z\\mathrm{n}$ metal in methanol. Therefore compared with water, methanol molecules are more likely to adsorb on $Z\\mathrm{n}$ metal surfaces in the antisolvent electrolyte to impact water-induced $\\mathrm{H}_{2}$ evolution and $Z\\mathrm{n}$ nucleation formation during $Z\\mathrm{n}$ deposition.[27] \n\nFigure S6 summarizes the impact of methanol addition on water-induced $\\mathrm{H}_{2}$ evolution. Compared with the watermethanol hybrid, pure water undergoes a significant $\\mathrm{H}_{2}$ evolution.[28] Similarly, the $\\mathrm{{\\calZ}n S O_{4}}$ electrolyte undergoes a significant current response at $-1.06\\mathrm{V}$ vs. $\\mathbf{Ag/AgCl}$ (Figure 2e). The suppressed $\\mathrm{H}_{2}$ evolution reactions by methanol addition also convinced by the digital images of electrolysis bath (Figure S7). Following negative scanning, numerous bubbles were generated on the $Z\\mathrm{n}$ electrode in the $\\mathrm{{ZnSO_{4}}}$ electrolyte, however, no bubbles were produced in Anti-M$50\\%$ . Except for the strong adsorption of methanol on the $Z\\mathrm{n}$ electrode surface, another reason for $\\mathrm{H}_{2}$ evolution inhibition should be related with the diminished water activity caused by the strong interaction between methanol and free water.[29] \n\n![](images/5c112e9fde31948e7e817432ec5b6af5adc5bc68bae349457a66ba9a80323695.jpg) \nFigure 2. Impact of methanol on $Z n S O_{4}$ electrolyte and Zn reversibility. Contact angle measurement on Zn electrode: a) with $Z n S O_{4}$ electrolyte, b) with Anti-M- $33\\%$ , c) with Anti-M- $50\\%$ , d) with methanol. e) LSV response curves for different electrolytes at $0.1\\mathrm{\\mV}\\mathsf{s}^{-1}$ . $\\mathsf{f})$ Coulombic efficiency (CE) measurements of $Z n/C u$ cells with different electrolytes. g) Charge/discharge voltage profiles of $Z n/C u$ cells at ${\\sf7}^{\\mathrm{st}}$ , $200^{\\mathrm{th}}$ , $400^{\\mathrm{th}}$ , and $600^{\\mathrm{{th}}}$ plating/stripping. \n\nReversibility of $Z\\mathrm{n}$ chemistry was investigated by conducting plating/stripping measurements on $Z_{\\mathrm{{n}/C u}}$ coin cells at $1\\mathrm{mAcm}^{-2}$ . As illustrated in Figure 2 f, an average CE of $96.6\\%$ was obtained in the first 180 cycles in the $Z_{\\mathrm{{n}/C u}}$ cell with $2\\:\\mathrm{M}\\:Z_{\\mathrm{nSO_{4}}}$ electrolyte. The value for CE fluctuated in the following cycles due to battery failure, which was caused mainly by dendritic deposition, $\\mathrm{H}_{2}$ evolution and $\\mathrm{{Zn_{4}S O_{4}}}.$ - $\\mathrm{(OH)}_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ by-product.[30] In contrast, $Z_{\\mathrm{{n}}}/\\mathrm{Cu}$ cells with the addition of antisolvent methanol displayed a significantly boosted CE. In Anti-M- $33\\%$ , the $Z_{\\mathrm{{n}/C u}}$ cell showed high CE in the initial 10 cycles and maintained stability after 900 cycles in which a high average value of $99.3\\%$ was obtained. Importantly, the $Z_{\\mathrm{{n}/C u}}$ cell with Anti-M- $50\\%$ exhibited a greater average CE of $\\approx99.7\\%$ , which probably benefits from the less active water molecular existence in such electrolyte compared to Anti-M- $33\\%$ . Figure $2\\mathrm{g}$ compares plating/stripping curves of $Z_{\\mathrm{{n}/C u}}$ cells with different electrolytes. The cell with Anti-M- $50\\%$ electrolyte displayed a higher voltage polarization of $\\approx0.2{\\:}\\mathrm{V}$ than that with $\\mathrm{ZnSO_{4}}$ electrolyte $(\\approx0.13{\\mathrm{V}})$ . This result is because the ionic conductivity of the electrolyte is decreased with the antisolvent addition. The reduction was from $5.69\\mathrm{Sm}^{-1}$ for $2\\mathrm{M}\\mathrm{\\ZnSO_{4}}$ to $1.68\\mathrm{Sm}^{-1}$ for Anti-M- $50\\%$ . The cell with Anti- $.M{-}50\\%$ exhibited an initial CE of $90.3\\%$ . This CE value is significantly greater than that for $\\mathrm{ZnSO_{4}}$ electrolyte of $83.2\\%$ . \n\nTo further investigate the impact of antisolvent electrolyte on $Z\\mathrm{n}$ reversibility, Cu and $Z\\mathrm{n}$ electrodes stripped from cells with different electrolytes were compared after the $50^{\\mathrm{th}}$ plating. The digital image of the $\\mathrm{cu}$ electrode (Figure S8a) showed inhomogeneous $Z\\mathrm{n}$ deposition in the $\\mathrm{ZnSO_{4}}$ electrolyte. However, significant corrosion on the $Z\\mathrm{n}$ electrode was found also (Figure S8b), which readily induces dendritic $Z\\mathrm{n}$ deposition. In contrast, the $Z\\mathrm{n}$ deposition on the Cu electrode in Anti-M- $50\\%$ electrolyte is uniform (Figure S8c). No obvious corrosion could be seen on the Zn electrode, suggesting good reversibility of $Z\\mathrm{n}$ plating/stripping in such electrolyte (Figure S8d). From the scanning electron microscopy (SEM) images, it was observed that $Z\\mathrm{n}$ deposition on $\\mathrm{cu}$ electrode is dendritic and porous in the $\\mathrm{ZnSO_{4}}$ electrolyte (Figure 3 a). This significantly affects the CE of $Z\\mathrm{n}$ plating/ stripping.[31] The surface of the $Z\\mathrm{n}$ electrode was damaged after repeated plating/stripping (Figure 3b). Dendritic $Z\\mathrm{n}$ deposition on the Cu electrode is aggravated during further cycling, as shown in Figure 3 c ( $100^{\\mathrm{th}}$ plating). Simultaneously, a degraded surface of the $Z\\mathrm{n}$ electrode was found (Figure 3d), leading to limited $Z\\mathrm{n}$ reversibility in $\\mathrm{{ZnSO_{4}}}$ electrolyte. In contrast, $Z\\mathrm{n}$ deposition on the Cu electrode was compact and homogeneous in Anti-M- $50\\%$ , as shown in Figure 3 e. Uniform spherical deposition without Zn dendrite growth facilitates high reversibility of $Z\\mathrm{n}$ chemistry. Moreover, the $Z\\mathrm{n}$ electrode shows an even surface in Anti-M- $50\\%$ . This finding confirms $Z\\mathrm{n}$ plating/stripping behaviour was changed in the antisolvent electrolyte (Figure 3 f). Uniform and dendrite-free $Z\\mathrm{n}$ deposition was found on the $\\mathrm{cu}$ and $Z\\mathrm{n}$ electrodes after the $100^{\\mathrm{th}}$ plating in Anti-M- $50\\%$ (Figure $^{3}\\mathrm{g,h}\\dot{}$ ). \n\n![](images/d48452d93472bbcfdfb729efbf6e63ea2d18af0e103e3f407b530bdaaba89e53.jpg) \nFigure 3. SEM and in situ optical microscopy studies on Zn plating behaviour. SEM images of $\\mathsf{C u}$ and Zn electrodes in $Z n S O_{4}$ electrolyte: a) $\\mathsf{C u}$ electrode after the $50^{\\mathrm{th}}$ plating; b) $Z n$ electrode after the $50^{\\mathrm{th}}$ plating; c) $\\mathsf{C u}$ electrode after the $100^{\\mathrm{th}}$ plating; d) $Z n$ electrode after the $100^{\\mathrm{th}}$ plating. SEM images of $\\mathsf{C u}$ and $Z n$ electrodes in Anti-M- $50\\%$ electrolyte: e) Cu electrode after the $50^{\\mathrm{th}}$ plating, f ) Zn electrode after the $50^{\\mathrm{th}}$ plating, g) Cu electrode after the ${100}^{\\mathrm{th}}$ plating, h) Zn electrode after the ${100}^{\\mathrm{th}}$ plating. In situ optical microscope images of $\\mathsf{C u}$ electrode during Zn plating/ stripping: i) in $Z n S O_{4}$ electrolyte; j) in Anti- $M-50\\%$ . k) XRD patterns of Zn electrode in $Z n S O_{4}$ and Anti-M- $50\\%$ electrolytes after the $50^{\\mathrm{th}}$ plating. l) Binding energy of (002) facets for $Z n$ metal with water or methanol solvent. \n\nTo confirm the inhibition of $Z\\mathrm{n}$ dendrite growth in antisolvent electrolyte, transparent home-made $\\mathrm{{Cu-Zn}}$ cells were assembled to monitor $Z\\mathrm{n}$ plating/stripping behaviour in situ using an optical microscope. This was equipped with a digital camera to take videos. $Z\\mathrm{n}$ plating/stripping was conducted under a high current density of $20\\mathrm{mAcm}^{-2}$ for $10\\mathrm{min}$ . As shown in Video S1, uneven $Z\\mathrm{n}$ plating with dendritic growth appears on the Cu electrode in the $\\mathrm{{ZnSO_{4}}}$ electrolyte. These dendrites remained in following stripping process. Figure 3 i illustrates the snapshots taken during the plating/stripping. Apparently, the $\\mathrm{cu}$ electrode displays a smooth and bright edge prior to $Z\\mathrm{n}$ plating. After $200\\mathrm{s}$ plating, an uneven $Z\\mathrm{n}$ deposition starts along the edge of the Cu electrode. After 400 s plating, deposited protrusions form. Some protrusions gradually turn into $Z\\mathrm{n}$ dendrites with further plating $(600\\mathrm{{s})}$ . In stripping, the deposited $Z\\mathrm{n}$ is gradually removed from the Cu electrode, however, obvious $Z\\mathrm{n}$ dendrites remained on the Cu electrode even if the $\\mathrm{cu}$ surface was oxidized after $600\\mathrm{~s~}$ stripping. This finding confirmed that the inhomogeneous $Z\\mathrm{n}$ deposit cannot be stripped completely in 2 M $\\mathrm{ZnSO_{4}}$ electrolyte. This dendritic growth therefore results in the $Z\\mathrm{n}$ electrode to exhibit poor reversibility in 2 M $\\mathrm{ZnSO_{4}}$ electrolyte. In comparison, the $Z\\mathrm{n}$ plating on Cu electrode is smooth and homogeneous in Anti$M\\mathrm{-}50\\%$ electrolyte, as shown in Video S2. No obvious $Z\\mathrm{n}$ dendrites were generated after 600 s plating, as evidenced in Figure 3j. After $600\\mathrm{s}$ stripping, the deposited $Z\\mathrm{n}$ was completely removed from the Cu electrode, which affirms the high reversibility of dendrite-free Zn plating/stripping in Anti-M- $50\\%$ electrolyte. \n\nX-Ray Diffraction (XRD) measurements were performed to investigate the corrosion on the $Z\\mathrm{n}$ electrode after cycling. In the $\\mathrm{{\\calZ}n S O_{4}}$ electrolyte, $Z\\mathrm{n}$ electrode showed a significant peak at about $9.8^{\\circ}$ (Figure 3k), indexing to the (002) plane of $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}(\\mathrm{OH})_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ by-product. This finding strongly confirms that significant corrosion occurred during battery cycling.[32] In contrast, a significantly reduced peak at about $9.8^{\\circ}$ appeared in the XRD pattern for $Z\\mathrm{n}$ electrode in Anti$M{-}50\\%$ electrolyte, Zn electrode corrosion is significantly suppressed. This suppressed corrosion contributes to boosting $Z\\mathrm{n}$ reversibility. Additionally, unlike the XRD pattern for metallic $Z\\mathrm{n}$ before cycling (Figure S9) and that after cycling in the $\\mathrm{ZnSO_{4}}$ electrolyte, the peak intensity of $Z\\mathrm{n}$ electrode changes significantly in Anti-M- $50\\%$ . The (002) peak shows strongest intensity, revealing that the orientation of $Z\\mathrm{n}$ deposition in Anti-M- $50\\%$ has been changed. This modified deposition orientation leads to a different morphology of $Z\\mathrm{n}$ deposition, which is actually consistent with the SEM results. Based on the wettability measurements, methanol is more likely to adsorb on the $Z\\mathrm{n}$ surface compared with water. This difference influences $Z\\mathrm{n}$ deposition. To better understand the deposition orientation in the antisolvent electrolyte, densityfunctional theory (DFT) computations were conducted to compare the binding energies of methanol and water on the Zn (002) surface at top, bridge and hollow sites. As shown in Figure 3l, the binding energy of a water molecule on the $Z\\mathrm{n}$ (002) facet is computed to be, respectively, $-0.245$ , $-0.167$ and $-0.161\\mathrm{eV}.$ These results show the water molecule has highest binding energy at the top site. When the water was replaced by methanol, the binding energy on $Z\\mathrm{n}$ (002) facet increased to $-0.397$ , $-0.281$ , and $-0.308\\mathrm{eV},$ respectively. Therefore, compared with water, methanol is more likely to induce $Z\\mathrm{n}$ deposition on the (002) facet, which modifies the deposition orientation of $Z\\mathrm{n}$ in the antisolvent electrolytes.[31] \n\nUsing the antisolvent strategy to improve $Z\\mathrm{n}$ reversibility through changing $Z\\mathrm{n}$ deposition and inhibiting $\\mathrm{H}_{2}$ and corrosion can be shown to be effective for other solvents, such as ethanol and 1-propanol. As shown in Figure S10, the average CE is $99.3\\%$ and $99.1\\%$ in Anti-E- $25\\%$ and Anti-P$10\\%$ , respectively. Although these values are lower than that in Anti- $.M{-}50\\%$ due to the existence of fewer water molecules in Anti-M- $50\\%$ , they are much higher than that in $\\mathrm{{ZnSO_{4}}}$ electrolyte. Furthermore, dendrite-free $Z\\mathrm{n}$ deposition and suppressed corrosion in antisolvent electrolytes of ethanol and 1-propanol were confirmed by SEM (Figure S11) and XRD measurements (Figure S12). Importantly, these findings demonstrate possible practical universality of cost-effective antisolvents to boost Zn electrode reversibility. \n\nLarge-scale practical application of aqueous batteries is severely limited under harsh environments because of poor performance.[33] To test the efficacy of antisolvent electrolyte under harsh conditions, the freezing tolerances of $\\mathrm{ZnSO_{4}}$ and Anti-M- $50\\%$ electrolytes were compared. At $-10^{\\circ}\\mathrm{C}$ , both electrolytes are transparent liquids (Figure 4a), however, $\\mathrm{{ZnSO}_{4}}$ electrolyte turns into ice at $-20^{\\circ}\\mathrm{C}$ (Figure 4 b). In comparison, the Anti-M- $50\\%$ maintains good liquidity despite temperatures as low as $-40^{\\circ}\\mathrm{C}$ (Figure 4 c). The freezing point of Anti-M- $50\\%$ was tested to be $-46^{\\circ}\\mathrm{C}$ (Figure S13), which highlights its freezing tolerance properties. To evaluate antisolvent applicability under harsh environments, the CE of $Z_{\\mathrm{{n}/C u}}$ cells in different electrolytes was compared at low and high temperatures. Despite the fact that $\\mathrm{{\\calZ}n S O_{4}}$ electrolyte maintains liquidity at $-10^{\\circ}\\mathrm{C},$ its CE is low with significant fluctuations (Figure 4 d). Performance is poor in comparison with Anti-M- $50\\%$ with an average CE of $99.5\\%$ , and that for Anti-M- $33\\%$ of $99.4\\%$ , Figure S14. At a harsh temperature of $-20^{\\circ}\\mathrm{C}$ the cell with Anti-M- $50\\%$ maintained a high initial CE of $92.4\\%$ and a high average value of $98.7\\%$ (Figure S15). Because of its frozen state no CE data were practically possible for $\\mathrm{ZnSO_{4}}$ electrolyte at $-20^{\\circ}\\mathrm{C}$ . The performance of the $Z_{\\mathrm{{n}}}/\\mathrm{Cu}$ cells was compared also at high temperature. This comparison is summarized in Figure 4 e. It is seen that at $60^{\\circ}\\mathrm{C}$ the cell with $\\mathrm{ZnSO_{4}}$ electrolyte exhibited a CE of $93.8\\%$ . Importantly, this is meaningfully lower than for antisolvent electrolytes of $98.1\\%$ in Anti-M- $50\\%$ and $96.8\\%$ in Anti-M$33\\%$ (Figure S16). \n\nCharge/discharge voltage profiles of $Z_{\\mathrm{{n}/C u}}$ cells under various temperature were compared in Figure S17. Apparently, the cells with both electrolytes at $60^{\\circ}\\mathrm{C}$ display lower polarization than these at low temperatures. Nevertheless, the CE in $\\mathrm{ZnSO_{4}}$ electrolyte at $60^{\\circ}\\mathrm{C}$ was significantly less than that at $25^{\\circ}\\mathrm{C}.$ . This trend is a similar finding to that for organic Li-based batteries.[34] This trend highlights the fact that achieving high reversibility of metallic $Z\\mathrm{n}$ electrode at high temperatures is practically more difficult than that at lower temperatures. A likely reason is that higher temperature is beneficial for competing reactions in $Z\\mathrm{n}$ plating/stripping, such as $\\mathrm{H}_{2}$ evolution and corrosion. Figure S18 presents digital images of the cells after CE tests at $60^{\\circ}\\mathrm{C}.$ The cell with $\\mathrm{{ZnSO_{4}}}$ electrolyte exhibited significant $\\mathrm{H}_{2}$ evolution during battery cycling. This led to the battery swelling noticeably. \n\nThe morphology of $\\mathrm{cu}$ and $Z\\mathrm{n}$ electrodes under various conditions was compared after the $50^{\\mathrm{th}}$ plating. Digital images showed that $Z\\mathrm{n}$ plating on $\\mathrm{cu}$ electrode in $\\mathrm{{ZnSO_{4}}}$ electrolyte is uneven at both high and low temperature (Figure S19). Significantly more corrosion occurred on $Z\\mathrm{n}$ electrode at $60^{\\circ}\\mathrm{C}$ than at $-10^{\\circ}\\mathrm{C}.$ This finding indicates poor $Z\\mathrm{n}$ reversibility at high temperature, as confirmed in the SEM images. Numerous $Z\\mathrm{n}$ plates perpendicular to $Z\\mathrm{n}$ surface can be observed at the high temperature (Figure S20a), however, $Z\\mathrm{n}$ plating/stripping is relatively homogenous at the low temperature (Figure S20b). Under the same condition, the $Z\\mathrm{n}$ plating on Cu electrode is more uniform in Anti-M- $50\\%$ electrolyte (Figure S21) than that in $\\mathrm{ZnSO_{4}}$ electrolyte. Compared with $\\mathrm{ZnSO_{4}}$ electrolyte, Zn electrode corrosion is suppressed to some extent in Anti-M- $50\\%$ . Nevertheless, severe corrosion of $Z\\mathrm{n}$ electrode is observed at the high temperature, which agrees with the previous CE results. Figure 4 f,g shows the XRD patterns for $Z\\mathrm{n}$ electrode cycles under different conditions. The peak intensity of the $\\mathrm{Zn}_{4}\\mathrm{SO}_{4}$ - $\\mathrm{(OH)}_{6}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ by-product was significantly reduced at both low and high temperature when the $\\mathrm{ZnSO_{4}}$ electrolyte was replaced by Anti-M- $50\\%$ . This finding suggests the corrosion reaction is significantly suppressed. Concomitantly, the (002) peak of the $Z\\mathrm{n}$ electrode in Anti-M- $50\\%$ shows the greatest intensity at both high and low temperature. This reveals the \n\n![](images/b668f37084068c6f442b2fcf9f95f2220e1ee1ea0f9d6a4863685dfa17ebe54f.jpg) \nFigure $_4$ . Zn reversibility under harsh environments. Freezing tolerance comparison of $Z n S O_{4}$ with Anti- $M-50\\%$ electrolyte: a) at $-10^{\\circ}\\mathsf C$ b) at $-20^{\\circ}\\mathsf{C},\\mathsf{c})$ at $\\angle40^{\\circ}\\mathsf C.$ . Zn reversibility comparison of $Z n/C u$ cells with $Z n S O_{4}$ and Anti- $M-50\\%$ electrolytes: d) at $-10^{\\circ}C$ ; e) at $60^{\\circ}\\mathsf{C}$ XRD patterns of $Z n$ electrodes with $Z n S O_{4}$ and Anti- $M-50\\%$ after the $50^{\\mathrm{th}}$ plating: f ) at $-10^{\\circ}\\mathsf C,$ g) at $60^{\\circ}\\mathsf{C}$ . \n\nZn deposition orientation was changed, as evidenced also in SEM images of $Z\\mathrm{n}$ plating (Figure S22).[35] \n\nTo investigate further the efficacy of antisolvent electrolytes, $Z\\mathrm{n}/$ /polyaniline (PANI) coin cells were assembled where the PANI was synthesized on carbon-cloth through in situ polymerization.[36] SEM images showed that the PANI, featuring a stamen-like nanostructure, was uniformly distributed on the carbon-cloth (Figure S23). In $\\mathrm{{\\calZ}n S O_{4}}$ electrolyte, the ${\\cal Z}\\mathrm{n/PANI}$ cell displayed a long discharge plateau at $\\approx1.1\\:\\mathrm{V}$ with a reversible capacity of $213.3\\mathrm{mAhg^{-1}}$ at current density of $100\\mathrm{mAg^{-1}}$ when tested at $25^{\\circ}\\mathrm{C}$ (Figure 5 a). In harsher environments, a capacity of $242.6\\ \\mathrm{mAhg^{-1}}$ was obtained at $60^{\\circ}\\mathrm{C}$ , whereas this was reduced to $166.9\\mathrm{mAhg^{-1}}$ at $-10^{\\circ}\\mathrm{C}.$ . With the same testing conditions, the Anti-M- $50\\%$ electrolyte clearly enhanced the reversible capacity of $Z\\mathrm{n}/$ PANI cell (Figure 5b), namely, the capacity increased to, respectively, 186.3, 219.1 and $249.7\\mathrm{mAhg^{-1}}$ at 10, 25 and $60^{\\circ}\\mathrm{C}.$ . The cycling stability of ${\\mathrm{Zn/PANI}}$ cells with $\\mathrm{ZnSO_{4}}$ and Anti-M- $50\\%$ electrolytes was evaluated at ${5\\mathrm{Ag}^{-1}}$ in various testing environments. At $25^{\\circ}\\mathrm{C}$ , the cell with Anti-M- $50\\%$ exhibited stable cycling capacity and high CE. After 2000 cycles (Figure 5c), a high capacity of $114.6\\mathrm{mAhg^{-1}}$ was maintained, corresponding to a capacity retention of $85.5\\%$ . This finding results from the inhibition of dendrite growth, $\\mathrm{H}_{2}$ evolution and side reactions during the battery cycling. The capacity of the cell with $\\mathrm{{ZnSO_{4}}}$ electrolyte, however, was gradually reduced. Just $48.3\\%$ of its initial capacity was maintained after 2000 cycles, underscoring its limited cycling stability in $\\mathrm{{ZnSO_{4}}}$ electrolyte at ambient temperature. At $-10^{\\circ}\\mathrm{C}.$ the capacity of the $\\mathrm{{\\calZ}n S O_{4}}$ based cell significantly decreased, with just $\\approx20.2\\:\\mathrm{mAhg^{-1}}$ maintained after a limited 1000 cycles (Figure 5 d). In contrast, the cell with anti-M- $50\\%$ exhibited significantly boosted cycling stability, together with a capacity retention of $89.3\\%$ after 2000 cycles. It is concluded that Anti-M- $50\\%$ electrolyte has significant potential therefore for practical application. \n\nThe successfully boosted performance of ${\\cal Z}\\mathrm{n/PANI}$ coin cells with Anti- $.M{-}50\\%$ has motivated us to further assess the performance in a soft-packed cell. These cells can be facilely assembled in ambient. Figure 5e presents a ${\\cal Z}\\mathrm{n}/\\mathrm{PNAI}$ pouch cell of size $5.0\\mathrm{cm}$ in length and $3.6\\mathrm{cm}$ in width. Under a high current of $100\\mathrm{mA}$ this pouch cell exhibited a high capacity of \n\n![](images/f6db1f3f967dceb9516f3bee5d01fb42f3e06a2d68e40233bfc6641e73c12867.jpg) \nFigure 5. Electrochemical characterization. a) Charge-discharge curves for $Z n/{\\mathsf{P A N I}}$ coin-cell with a) $Z n S O_{4}$ electrolyte or b) Anti-M- $50\\%$ electrolyte under a current density of $\\mathsf{100\\ m A g^{-1}}$ at different testing temperatures. Cycling stability of Zn/PANI coin cells at $5\\mathsf{A g}^{-1}$ with different electrolytes: c) at $25^{\\circ}\\mathsf{C}$ d) at $-10^{\\circ}\\mathsf C.$ e) Digital image of the $Z n/{\\mathsf{P A N I}}$ pouch cell. f) Charge-discharge curves for $Z n/{P A N}|$ pouch cell under the current of ${\\mathsf{l o o}}{\\mathsf{m A}}.$ g) Two pouch cells power nine red LEDs (left) and air fan (right). \n\n$100.8\\mathrm{mAhg^{-1}}$ (Figure 5 f). The efficacy of the pouch cell was demonstrated by using it to power nine red light-emitting diodes (LEDs, $2.0\\mathrm{V}$ ) and a fan, as shown in Figure $5\\mathrm{g}$ . The cycle life of the aqueous pouch cell was investigated (Figure S24), it exhibited good cycling stability under a high current of $100\\mathrm{mA}$ , together with a high capacity of $96.4\\mathrm{mAhg^{-1}}$ after 300 cycles with $\\approx95.6\\%$ capacity retention. \n\n# Conclusion \n\nThe use of cost-effective antisolvent is demonstrated to regulate aqueous $Z\\mathrm{n}$ chemistry reversibility on a molecular level. In methanol-based antisolvent electrolytes, water molecules interact with methanol, which diminishes activity of free water and weakens $Z\\mathrm{n}^{2+}$ solvation in the electrolyte. Therefore, the water-induced $\\mathrm{H}_{2}$ evolution and corrosion reaction are significantly suppressed, whilst the transference number of $Z\\mathrm{n}^{2+}$ is increased. In situ optical microscopy confirmed that a homogeneous and dendrite-free Zn deposition was achieved with methanol addition (Anti-M- $50\\%$ ). This resulted from changing the $Z\\mathrm{n}$ disposition orientation. Zn electrodes therefore exhibit a high reversibility in Anti-M$50\\%$ electrolyte. A significant average CE of, respectively, $98.7\\%$ and $98.1\\%$ was demonstrated with Anti-M- $50\\%$ in harsh environments of $-20^{\\circ}\\mathrm{C}$ and $60^{\\circ}\\mathrm{C}$ Importantly, this result is significantly greater than that for $\\mathrm{ZnSO_{4}}$ electrolyte (which did not function at $-20^{\\circ}\\mathrm{C}$ and exhibited a CE of $93.8\\%$ at $60^{\\circ}\\mathrm{C}$ ). Because of boosted $Z\\mathrm{n}$ reversibility, Anti-M$50\\%$ electrolyte resulted in ${\\cal Z}\\mathrm{n/PANI}$ batteries with excellent cycling stability, both with coin and pouch cells. It is concluded that antisolvent electrolytes are a low-cost strategy that can be generalized to a range of solvents including, methanol, ethanol and 1-propanol. This suggests a practical universality to boost development of $Z\\mathrm{n}$ batteries. \n\n# Acknowledgements \n\nFinancial support provided by the Australian Research Council (ARC) (FL170100154, DP200101862 and LP160101629) is gratefully acknowledged. DFT computations were undertaken with the assistance of resources and services from the National Computational Infrastructure (NCI) and Phoenix High Performance Computing, which are supported by the Australian Government and The University of Adelaide. \n\n# Conflict of interest \n\nThe authors declare no conflict of interest. \n\nKeywords: antisolvent · dendrite-free $\\cdot\\cdot$ methanol · Zn ion battery · $Z\\mathsf{n}^{2+}$ solvation \n\n[1] a) H. Pan, Y. Shao, P. Yan, Y. Cheng, K. S. Han, Z. Nie, C. Wang, J. Yang, X. Li, P. Bhattacharya, Nat. Energy 2016, 1, 16039; b) F. Wan, Z. Niu, Angew. Chem. Int. Ed. 2019, 58, 16358 – 16367; Angew. Chem. 2019, 131, 16508 – 16517; c) D. Chao, W. Zhou, F. Xie, C. Ye, H. Li, M. Jaroniec, S.-Z. Qiao, Sci. Adv. 2020, 6, eaba4098; d) C. Zhong, B. Liu, J. Ding, X. Liu, Y. Zhong, Y. Li, C. Sun, X. Han, Y. Deng, N. Zhao, W. Hu, Nat. Energy 2020, 5, 440 – 449. \n[2] a) B. Tang, L. Shan, S. Liang, J. Zhou, Energy Environ. Sci. 2019, 12, 3288 – 3304; b) M. Song, H. Tan, D. Chao, H. J. Fan, Adv. Funct. Mater. 2018, 28, 1802564; c) X. Zeng, J. Hao, Z. Wang, J. Mao, Z. Guo, Energy Storage Mater. 2019, 20, 410 – 437; d) Z. Liu, Y. Huang, Y. Huang, Q. Yang, X. Li, Z. Huang, C. Zhi, Chem. Soc. Rev. 2020, 49, 180 – 232; e) L. E. Blanc, D. Kundu, L. F. Nazar, Joule 2020, 4, 771 – 799. \n[3] a) Q. Zhang, J. Luan, Y. Tang, X. Ji, H. Wang, Angew. Chem. Int. Ed. 2020, 59, 13180 – 13191; Angew. Chem. 2020, 132, 13280 – 13291; b) L. Ma, M. A. Schroeder, O. Borodin, T. P. Pollard, M. S. Ding, C. Wang, K. Xu, Nat. Energy 2020, 5, 743 – 749; c) Q. Yang, G. Liang, Y. Guo, Z. Liu, B. Yan, D. Wang, Z. Huang, X. Li, J. Fan, C. Zhi, Adv. Mater. 2019, 31, 1903778. \n[4] a) J. Hao, X. Li, X. Zeng, D. Li, J. Mao, Z. Guo, Energy Environ. Sci. 2020, 13, 3917 – 3949; b) L. Ma, S. Chen, N. Li, Z. Liu, Z. Tang, J. A. Zapien, S. Chen, J. Fan, C. Zhi, Adv. Mater. 2020, 32, 1908121. \n[5] J. Hao, X. Li, S. Zhang, F. Yang, X. Zeng, S. Zhang, G. Bo, C. Wang, Z. Guo, Adv. Funct. Mater. 2020, 30, 2001263. \n[6] a) F. Wang, O. Borodin, T. Gao, X. Fan, W. Sun, F. Han, A. Faraone, J. A. Dura, K. Xu, C. Wang, Nat. Mater. 2018, 17, 543 – 549; b) W. Yang, X. Du, J. Zhao, Z. Chen, J. Li, J. Xie, Y. Zhang, Z. Cui, Q. Kong, Z. Zhao, Joule 2020, 4, 1557 – 1574. \n[7] a) Z. Zhao, J. Zhao, Z. Hu, J. Li, J. Li, Y. Zhang, C. Wang, G. Cui, Energy Environ. Sci. 2019, 12, 1938 – 1949; b) J. Hao, B. Li, X. Li, X. Zeng, S. Zhang, F. Yang, S. Liu, D. Li, C. Wu, Z. Guo, Adv. Mater. 2020, 32, 2003021; c) H. Qiu, X. Du, J. Zhao, Y. Wang, J. Ju, Z. Chen, Z. Hu, D. Yan, X. Zhou, G. Cui, Nat. Commun. 2019, 10, 1 – 12; d) L. Cao, D. Li, T. Deng, Q. Li, C. Wang, Angew. Chem. Int. Ed. 2020, 59, 19292 – 19296; Angew. Chem. 2020, 132, 19454 – 19458. \n[8] a) A. Bayaguud, X. Luo, Y. Fu, C. Zhu, ACS Energy Lett. 2020, 5, 3012 – 3020; b) J. Hao, J. Long, B. Li, X. Li, S. Zhang, F. Yang, X. Zeng, Z. Yang, W. K. Pang, Z. Guo, Adv. Funct. Mater. 2019, 29, 1903605; c) Y. Jin, K. S. Han, Y. Shao, M. L. Sushko, J. Xiao, H. Pan, J. Liu, Adv. Funct. Mater. 2020, 30, 2003932; d) W. Xu, K. Zhao, W. Huo, Y. Wang, G. Yao, X. Gu, H. Cheng, L. Mai, C. Hu, X. Wang, Nano Energy 2019, 62, 275 – 281. \n[9] a) Q. Zhang, J. Luan, L. Fu, S. Wu, Y. Tang, X. Ji, H. Wang, Angew. Chem. Int. Ed. 2019, 58, 15841 – 15847; Angew. Chem. 2019, 131, 15988 – 15994; b) S. B. Wang, Q. Ran, R. Q. Yao, H. Shi, Z. Wen, M. Zhao, X. Y. Lang, Q. Jiang, Nat. Commun. 2020, 11, 1634. \n[10] a) F. Mo, G. Liang, Q. Meng, Z. Liu, H. Li, J. Fan, C. Zhi, Energy Environ. Sci. 2019, 12, 706 – 715; b) J. Zhu, M. Yao, S. Huang, J. Tian, Z. Niu, Angew. Chem. Int. Ed. 2020, 59, 16480 – 16484; Angew. Chem. 2020, 132, 16622 – 16626; c) S. Huang, F. Wan, S. Bi, J. Zhu, Z. Niu, J. Chen, Angew. Chem. Int. Ed. 2019, 58, 4313 – 4317; Angew. Chem. 2019, 131, 4357 – 4361. \n[11] a) J. Zheng, Q. Zhao, T. Tang, J. Yin, C. D. Quilty, G. D. Renderos, X. Liu, Y. Deng, L. Wang, D. C. Bock, Science 2019, 366, 645 – 648; b) S. Higashi, S. W. Lee, J. S. Lee, K. Takechi, Y. Cui, Nat. Commun. 2016, 7, 11801; c) J. Lee, R. Kim, S. Kim, J. Heo, H. Kwon, J. Yang, H. Kim, Energy Environ. Sci. 2020, 13, 2839 – 2848. \n[12] a) L. Zhang, I. A. P8rez, H. Jiang, C. Zhang, D. Leonard, Q. Guo, W. Wang, S. Han, L. Wang, X. Ji, Adv. Funct. Mater. 2019, 29, 1902653; b) H. Yang, Z. Chang, Y. Qiao, H. Deng, X. Mu, P. He, H. Zhou, Angew. Chem. Int. Ed. 2020, 59, 9377 – 9381; Angew. Chem. 2020, 132, 9463 – 9467. \n[13] L. Suo, O. Borodin, T. Gao, M. Olguin, J. Ho, X. Fan, C. Luo, C. Wang, K. Xu, Science 2015, 350, 938 – 943. \n[14] J. Xie, Z. Liang, Y. Lu, Nat. Mater. 2020, 19, 1006 – 1011. \n[15] a) A. A. Thorat, S. V. Dalvi, Chem. Eng. J. 2012, 181, 1 – 34; b) Y. Y. Kim, T. Yang, R. Suhonen, A. Kemppainen, K. Hwang, N. J. Jeon, J. Seo, Nat. Commun. 2020, 11, 3581; c) W. Xu, Y. Gao, W. Ming, F. He, J. Li, X. H. Zhu, F. Kang, J. Li, G. Wei, Adv. Mater. 2020, 32, 2003965. \n[16] Y. Yun, F. Wang, H. Huang, Y. Fang, S. Liu, W. Huang, Z. Cheng, Y. Liu, Y. Cao, M. Gao, Adv. Mater. 2020, 32, 1907123. \n[17] T. Zhang, F. Wang, H. Chen, L. Ji, Y. Wang, C. Li, M. B. Raschke, S. Li, ACS Energy Lett. 2020, 5, 1619 – 1627. \n[18] a) H. Liu, K. L. Sale, B. A. Simmons, S. Singh, J. Phys. Chem. B 2011, 115, 10251 – 10258; b) T. C. Schutt, G. A. Hegde, V. S. Bharadwaj, A. J. Johns, C. M. Maupin, J. Phys. Chem. B 2017, 121, 843 – 853. \n[19] A. T. Aguayo, A. G. Gayubo, R. Vivanco, M. Olazar, J. Bilbao, Appl. Catal. A 2005, 283, 197 – 207. \n[20] M. Mohsen-Nia, H. Amiri, B. Jazi, J. Solution Chem. 2010, 39, 701 – 708. \n[21] H. Gottlieb, V. Kotlyar, A. Nudelman, J. Org. Chem. 1997, 62, 7512 – 7515. \n[22] Y. Yu, W. Fan, Y. Wang, X. Zhou, J. Sun, S. Liu, J. Phys. Chem. B 2017, 121, 8179 – 8187. \n[23] M. I. Sulaiman, S. Yang, A. M. Ellis, J. Phys. Chem. A 2017, 121, 771 – 776. \n[24] W. W. Rudolph, M. H. Brooker, P. Tremaine, Z. Phys. Chem. 1999, 209, 181 – 207. \n[25] J. Ming, Z. Cao, W. Wahyudi, M. Li, P. Kumar, Y. Wu, J. Hwang, M. N. Hedhili, L. Cavallo, Y. Sun, ACS Energy Lett. 2018, 3, 335 – 340. \n[26] Q. Zhang, Y. Ma, Y. Lu, L. Li, F. Wan, K. Zhang, J. Chen, Nat. Commun. 2020, 11, 4463. \n[27] N. Chang, T. Li, R. Li, S. Wang, Y. Yin, H. Zhang, X. Li, Energy Environ. Sci. 2020, 13, 3527 – 3535. \n[28] a) X. Zeng, J. Liu, J. Mao, J. Hao, Z. Wang, S. Zhou, C. D. Ling, Z. Guo, Adv. Energy Mater. 2020, 10, 1904163; b) D. Chao, W. Zhou, C. Ye, Q. Zhang, Y. Chen, L. Gu, K. Davey, S.-Z. Qiao, Angew. Chem. Int. Ed. 2019, 58, 7823 – 7828; Angew. Chem. 2019, 131, 7905 – 7910. \n[29] D. Chao, S.-Z. Qiao, Joule 2020, 4, 1846 – 1851. \n[30] C. Li, Z. Sun, T. Yang, L. Yu, N. Wei, Z. Tian, J. Cai, J. Lv, Y. Shao, M. H. Rgmmeli, Adv. Mater. 2020, 32, 2003425. \n[31] Q. Guan, Y. Li, X. Bi, J. Yang, J. Zhou, X. Li, J. Cheng, Z. Wang, B. Wang, J. Lu, Adv. Energy Mater. 2019, 9, 1901434. \n[32] T. Zhang, Y. Tang, G. Fang, C. Zhang, H. Zhang, X. Guo, X. Cao, J. Zhou, A. Pan, S. Liang, Adv. Funct. Mater. 2020, 30, 2002711. \n[33] Y. Suleymanov, Science 2019, 366, 321 – 322. \n[34] J. Wang, W. Huang, A. Pei, Y. Li, F. Shi, X. Yu, Y. Cui, Nat. Energy 2019, 4, 664 – 670. \n[35] a) Q. Zhang, J. Luan, X. Huang, Q. Wang, D. Sun, Y. Tang, X. Ji, H. Wang, Nat. Commun. 2020, 11, 3961; b) K. E. Sun, T. K. \n\nHoang, T. N. L. Doan, Y. Yu, X. Zhu, Y. Tian, P. Chen, ACS Appl. Mater. Interfaces 2017, 9, 9681 – 9687. [36] F. Wan, L. Zhang, X. Wang, S. Bi, Z. Niu, J. Chen, Adv. Funct. Mater. 2018, 28, 1804975. " + }, + { + "id": "10.1126_science.abd3230", + "DOI": "10.1126/science.abd3230", + "DOI Link": "http://dx.doi.org/10.1126/science.abd3230", + "Relative Dir Path": "mds/10.1126_science.abd3230", + "Article Title": "Stacking-engineered ferroelectricity in bilayer boron nitride", + "Authors": "Yasuda, K; Wang, XR; Watanabe, K; Taniguchi, T; Jarillo-Herrero, P", + "Source Title": "SCIENCE", + "Abstract": "Two-dimensional (2D) ferroelectrics with robust polarization down to atomic thicknesses provide building blocks for functional heterostructures. Experimental realization remains challenging because of the requirement of a layered polar crystal. Here, we demonstrate a rational design approach to engineering 2D ferroelectrics from a nonferroelectric parent compound by using van der Waals assembly. Parallel-stacked bilayer boron nitride exhibits out-of-plane electric polarization that reverses depending on the stacking order. The polarization switching is probed through the resistance of an adjacently stacked graphene sheet. Twisting the boron nitride sheets by a small angle changes the dynamics of switching because of the formation of moire ferroelectricity with staggered polarization. The ferroelectricity persists to room temperature while keeping the high mobility of graphene, paving the way for potential ultrathin nonvolatile memory applications.", + "Times Cited, WoS Core": 544, + "Times Cited, All Databases": 577, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000665860000051", + "Markdown": "# FERROELECTRICS \n\n# Stacking-engineered ferroelectricity in bilayer boron nitride \n\nKenji Yasuda1\\*, Xirui Wang1, Kenji Watanabe2, Takashi Taniguchi2, Pablo Jarillo-Herrero1\\* \n\nTwo-dimensional (2D) ferroelectrics with robust polarization down to atomic thicknesses provide building blocks for functional heterostructures. Experimental realization remains challenging because of the requirement of a layered polar crystal. Here, we demonstrate a rational design approach to engineering 2D ferroelectrics from a nonferroelectric parent compound by using van der Waals assembly. Parallel-stacked bilayer boron nitride exhibits out-of-plane electric polarization that reverses depending on the stacking order. The polarization switching is probed through the resistance of an adjacently stacked graphene sheet. Twisting the boron nitride sheets by a small angle changes the dynamics of switching because of the formation of moiré ferroelectricity with staggered polarization. The ferroelectricity persists to room temperature while keeping the high mobility of graphene, paving the way for potential ultrathin nonvolatile memory applications. \n\nalso makes them ideal as ferroelectric tunnel barriers for use in ferroelectric tunnel junctions (15). Despite the potential importance for application as a ferroelectric memory, only a few examples of 2D vertical ferroelectrics— $\\mathrm{CuInP_{2}S_{6}}$ , $\\mathrm{In_{2}S e_{3}},$ $\\mathbf{MoTe_{2}}$ , and $\\mathrm{WIe_{2}}$ —have been discovered so far (9–13); the candidate materials have been largely limited by the requirement of the polar space group in the original layered bulk crystal. \n\nF feirerlodeslewcitcrihcabmleatpeorliarliszawtiothn aofnferl eactwriidce- range of technological applications, such as nonvolatile memories, high-permittivity dielectrics, electromechanical actuators, and pyroelectric sensors $(I)$ . Thinning down vertical ferroelectrics is one of the essential steps for the implementation of ferroelectric nonvolatile memory as part of the quest for denser storage and lower power consumption (1). Room-temperature ferroelectricity down to atomic thicknesses was, however, difficult to access because of the depolarization effect until the recent development of three series of materials: epitaxial perovskites (2, 3), $\\mathrm{HfO_{2}}$ - based ferroelectrics (4), and low-dimensional van der Waals (vdW) ferroelectrics (5–13). Among them, 2D vdW ferroelectrics present opportunities to integrate high-mobility materials such as graphene into ferroelectric field-effect transistors while keeping their properties intact, attributable to the absence of dangling bonds (14). Their uniform atomic thickness \n\nThe development of vdW assembly enabled the engineering of heterostructures with physical properties beyond the sum of those of the individual layers (16). For example, the Dirac band structure of graphene is dramatically transformed when it is aligned with hexagonal boron nitride (hBN) or stacked with another slightly rotated graphene sheet. The modified band structures have led to the discovery of a variety of emergent phenomena related to electron correlations and topology beyond expectations from the original band structure (17–24). Here, we demonstrate that the vdW stacking modifies not only the electronic band structure but also the crystal symmetry, thereby enabling the design of ferroelectric materials out of nonferroelectric parent compounds. We use BN as an example, but the same procedure can be applied to other bipartite honeycomb 2D materials, such as 2H-type transition metal dichalcogenides (TMDs) (25). Bulk hBN crystals realize AA′ stacking, as shown in Fig. 1A. This $180^{\\circ}$ -rotated natural stacking order restores reconstruction. The reconstruction creates relatively large AB (green) and BA (yellow) domains, with small AA regions (white) and domain walls in between (black). The red circled dot and red circled X represent up and down polarization, respectively. (E and F) Vertical PFM phase and amplitude images of twisted bilayer BN. Scale bars are $100\\mathsf{n m}$ . The contrast at the domain wall, different from the AB and BA domain regions, likely originates from the flexoelectric effect (36, 42). \n\n![](images/373e8b9581970f07e346e522b20b036e7187822e4e370753f44983b143868490.jpg) \nFig. 1. Polarization in AB-stacked bilayer BN. (A) Illustration of the atomic arrangement for AA′ stacking, the bulk form of hBN. Nitrogen and boron atoms are shown in silver and green, respectively. (B and C) Illustration of the atomic arrangement for AB and BA stacking. The vertical alignment of nitrogen and boron atoms distorts the $2\\mathsf{p}_{z}$ orbital of nitrogen (light blue), creating an out-of-plane electric dipole. (D) Illustration of a small-angle twisted bilayer BN after the atomic \n\n![](images/34060d343964710a8bd473194dd7853ba440de208e09fbba3e6834a0bf1b9373.jpg) \nFig. 2. Ferroelectric switching in parallel-stacked bilayer BN. (A) Resistance $R_{x x}$ of graphene for device P1 as a function of $V_{\\top}/d_{\\top}$ , the top gate voltage $V_{\\intercal}$ divided by the thickness of top hBN dT. $V_{\\top}/d_{\\top}$ is scanned in the backward (forward) direction starting from $+0.36\\ V/\\mathsf{n m}$ $(-0.36\\lor/\\mathsf{n m})$ in the blue (red) curve. Note that we only show the relevant scan range around the resistance peak in the figure. The inset on the left shows the schematic device structure. The inset on the right shows an optical micrograph of the device. Gr, graphene. (B) Resistance $R_{x x}$ as a function of $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ , the bottom gate voltage $V_{\\textsf{B}}$ divided by the distance between graphene and bottom gate electrode $d_{\\mathsf{B}}$ . $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ is scanned in the backward (forward) direction starting from $+0.42$ V/nm $(-0.42\\lor/\\mathsf{n m})$ in the blue (red) curve. The inset shows the enlarged plot around $0.20\\:\\forall/\\mathrm{nm}$ . (C) Resistance $R_{x x,\\cup}$ measured with the upper voltage contacts of device P1 (as displayed in the inset on the lower left) as a function of $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ and $V_{\\top}/d_{\\top}$ . We repeatedly scanned $V_{\\top}/d_{\\top}$ (fast scan, solid arrow) in the backward direction while gradually changing $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ (slow scan, dashed arrow). $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ is changed in the backward direction starting from $+0.42$ V/nm. Note that we only show the relevant scan range in the figure. The insets on the upper left and lower right show the schematic domain configuration and the polarization direction (red circled dot and red circled X). \n\nThe red dashed lines represent the charge neutrality points. (D) The same as (C) with $V_{\\mathsf{B}}/d_{\\mathsf{B}}$ changed in the forward direction starting from $-0.42\\lor/\\mathsf{n m}$ . (E) The same as (D) for the resistance $R_{x x,\\mathrm{L}}$ measured with the lower voltage contacts. The inset on the right shows the line cuts at the fixed $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ locations indicated by the red triangles. Each curve is offset by 1.5 kilohms for clarity. The inset on the left shows the schematic domain configuration during the ferroelectric switching (fig. S15). (F) Hall carrier density $\\boldsymbol{\\eta_{\\mathsf{H}}}$ measured as a function of $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ . $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ is scanned in the backward (forward) direction starting from $+0.42$ V/nm $(-0.42\\lor/\\mathsf{n m})$ in the blue (red) curve. The inset shows the Hall resistance $R_{y x}$ as a function of $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ under magnetic field $(B)=0.5{\\:}\\mathsf{T}.$ (G) The difference of Hall carrier density in the backward and forward scan, $\\mathfrak{n_{H}}^{\\mathsf{B}}-\\mathfrak{n_{H}}^{\\mathsf{F}}$ . (H) Twice the induced carrier density by the polarization of P-BBN, $2\\Delta{n}_{\\mathsf{P}}$ , plotted against $d_{\\mathsf{B}}$ for four devices studied in this work. The $2\\Delta{n}_{\\mathrm{P}}$ of each device is shown with a different shape; square (P1), triangle (P2), inverse-triangle (T1), and circle (T2). The filled and hollow symbols represent $2\\Delta{n}_{\\mathsf{P}}$ estimated from the horizontal shift of the resistance peak and the Hall resistance, respectively. Note that two markers of device T2 almost overlap with each other. The black curve is the theoretical curve calculated from the polarization obtained from the Berry phase calculation, $P_{2\\mathrm{D,theory}}$ (25). \n\n![](images/7108f7fb528c02e48626903e2e04a031260d0a151ae29c7560e28e3d0d985da6.jpg) \nFig. 3. Ferroelectric switching in twisted bilayer BN. (A) Resistance $R_{x x}$ of device T1 as a function of $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ and $V_{\\top}/d_{\\top}$ . The insets show schematic illustrations of the domain configurations. We repeatedly scanned $V_{\\top}/d_{\\top}$ (fast scan, solid arrow) while gradually changing $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ (slow scan, dashed arrow). $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ is changed in the backward direction starting from $+0.42\\ V/\\mathsf{n m}$ . The size of the domain is not to scale. (B) Spatial average of polarization of bilayer BN, $\\langle P\\rangle$ , estimated from the two-peak fitting as a function of the applied electric field $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ for a twisted device, T1 (solid lines), and a nontwisted device, P1 (dashed lines). The blue and red curves are backward and forward scans, respectively. $\\langle P\\rangle$ of device P1 is estimated by taking \nthe average of the polarization measured with the upper voltage contacts and the lower voltage contacts. We expect that small, but finite, AB (BA) regions remain, even at $\\langle P\\rangle=1(-1)$ , in a twisted device as depicted in the insets of (A), although they are too small to be clearly detected with our resistance measurement scheme. \n\nthe inversion symmetry broken in the monolayer. However, if two BN monolayer sheets are stacked without rotation (parallel stacking, P), it has been theoretically (26, 27) and experimentally (28–31) shown that polar AB or BA stacking orders (Fig. 1, B and C, respectively) are formed. These configurations are local energy minima in a parallel-stacked form and are realized as metastable crystal structures (26, 27). In AB (BA) stacking, the B (N) atoms in the upper layer sit above the N (B) atoms in the lower layer while the N (B) atoms in the upper layer lay above the empty site at the center of the hexagon in the lower layer. The vertical alignment of the $\\mathrm{2p}_{z}$ orbitals of N and B distorts the orbital of N, creating an electric dipole moment (fig. S3). As a result, AB and BA stacking will exhibit out-of-plane polarization in the opposite directions (25). \n\nWe demonstrate the polarization of ABstacked bilayer BN by vertical piezoelectric force microscopy (PFM). We fabricated nearly $0^{\\circ}$ bilayer BN devices by using the “tear and stack” method, where half of a monolayer BN flake is picked up and stacked on top of the remaining half (32, 33). In twisted bilayer BN, lattice relaxation leads to the formation of a moiré pattern consisting of AB and BA lattice networks with topological defects (AA regions), as in the case of twisted bilayer graphene and TMDs (Fig. 1D) (34–36). However, unlike twisted bilayer graphene, the low crystalline symmetry of BN creates a distinctive moiré pattern with staggered polarization in the AB and BA domains (25). PFM measurements on a smallangle twisted bilayer BN show a triangular pattern with finite contrast between the adjacent triangles (Fig. 1, E and F), whereas no moiré pattern is observed in the topographic image (fig. S6). The different piezoresponse in the AB and BA domains evidences the opposite out-of-plane polarizations in these domains. In a larger area scan (figs. S7 and S8), the periodicity of the triangular pattern varies at wrinkles and bubbles as the rotational angle changes. The triangular contrast does not show up in the monolayer BN region, confirming the interlayer interaction origin of the polarization (figs. S7 and S8). The stacking order–dependent out-of-plane polarization presents the interesting possibility that the polarization can be switched by an in-plane interlayer shear motion of one-third of the unit cell (25), which is distinct from the switching mechanism of conventional ferroelectrics $(I)$ . \n\nTo study the change of the polarization under the electric field, we fabricated dualgated vdW heterostructure devices composed of metal top gate (Au/Cr)/hBN/graphene $'0^{\\circ}$ parallel stacked bilayer BN (P-BBN)/hBN/ metal bottom gate (PdAu) (e.g., device P1), as schematically shown in the inset of Fig. 2A. Zero-degree stacking of P-BBN allows the entire region to be a single domain of AB or BA stacking without forming the moiré pattern. Here, the graphene sensitively detects the extra charge carriers induced by the polarization of P-BBN. Figure 2A shows the resistance of the graphene sensor as a function of the top gate voltage, $V_{\\mathrm{T}}$ (for both forward and backward gate sweep directions), which exhibits a typical maximum without hysteresis. By contrast, the forward and backward scans of the resistance versus the bottom gate voltage, $V_{\\mathrm{B}}(\\mathrm{Fig.2B})$ shows hysteresis, exhibiting maxima at about 0.10 and $0.12\\mathrm{V}/\\mathrm{nm}$ for the backward and forward scans, respectively. In addition, we observe a resistance step at around $0.20\\mathrm{V/nm}$ in the forward scan, as displayed in the inset. As discussed later, this bistability is attributed to the polarization switching of P-BBN by the applied electric field. \n\nDual-gate scanning allows independent control of the carrier density of graphene and the electric field across the P-BBN, because the top gate primarily changes the former (figs. S10 and S11), whereas the bottom gate changes both. In a standard dual-gated graphene device, a measurement of the resistance versus the top and bottom gate voltages results in a single diagonal feature, a maximum resistance ridge, corresponding to the charge neutrality condition. The diagonal feature stems from the fact that the induced carrier density follows the equation $n=\\varepsilon_{\\mathrm{hBN}}(V_{\\mathrm{B}}/d_{\\mathrm{B}}+V_{\\mathrm{T}}/d_{\\mathrm{T}})/e$ , where $\\varepsilon_{\\mathrm{hBN}}$ is the dielectric constant of hBN, $d_{\\mathrm{B}}\\left(d_{\\mathrm{T}}\\right)$ is the distance between graphene and the bottom (top) gate electrode, and $e$ is the elemental charge. By contrast, two parallel-shifted diagonal lines are observed in a dual-gate scan for our P-BBN device (Fig. 2C). The shift reflects an abrupt change in the induced carrier density, $\\Delta n_{\\mathrm{P}}$ , caused by the switching of the electric polarization of P-BBN: As the polarization switches from up (BA stacking) to down (AB stacking) at $V_{\\mathrm{B}}/d_{\\mathrm{B}}=-0.06\\mathrm{V/nm}$ , the total induced carrier density changes from $\\varepsilon_{\\mathrm{hBN}}(V_{\\mathrm{B}}/ $ $d_{\\mathrm{B}}+V_{\\mathrm{T}}/d_{\\mathrm{T}})/e+\\Delta n_{\\mathrm{P}}$ to $\\mathfrak{\\varepsilon}_{\\mathrm{hBN}}(V_{\\mathrm{B}}/d_{\\mathrm{B}}+V_{\\mathrm{T}}/d_{\\mathrm{T}})/e-$ $\\Delta n_{\\mathrm{P}}$ , leading to the shift of the charge neutrality resistance peak. Similarly, the forward scan of the bottom gate shows the polarization switching from down to up at $V_{\\mathrm{B}}/d_{\\mathrm{B}}=$ $0.16\\mathrm{V/nm}$ (Fig. 2D). Notably, the resistance measured using the lower voltage contacts exhibits an intermediate, two-peak behavior during the switching (Fig. 2E). This indicates the coexistence of micrometer-scale AB and BA domains and provides a hint to the dynamics of polarization switching. Namely, the domain wall is pinned in the middle of the Hall bar at around $V_{\\mathrm{B}}/d_{\\mathrm{B}}=0.13\\:\\mathrm{V/nm}$ , followed by the depinning at around $V_{\\mathrm{B}}/d_{\\mathrm{B}}=0.16~\\mathrm{V/nm}$ . \n\nTo further investigate the ferroelectric properties of P-BBN, we measured the carrier density $n_{\\mathrm{H}}$ of graphene extracted from Hall resistance measurements (Fig. 2F). Hysteretic behavior with an abrupt jump in $n_{\\mathrm{H}}$ is observed when sweeping $V_{\\mathrm{{B}}}$ , which is attributed to the ferroelectric switching. The subtraction of the forward and backward sweeps gives a magnitude of $2\\Delta n_{\\mathrm{P}}$ , which equals $3.0\\times10^{11}\\mathrm{cm}^{-2}$ (Fig. 2G). This value is consistent with $2\\Delta n_{\\mathrm{P}}=2.6\\times$ $\\mathrm{{10^{11}c m^{-2}}}$ estimated from the horizontal shift of the charge neutrality resistance peak in the dual-gate scan (Fig. 2, C to E). $\\Delta n_{\\mathrm{P}}$ allows us to calculate the magnitude of the polarization of AB-stacked bilayer BN. According to a simple model calculation (see fig. S14 for details), the \n\n![](images/8c2dfc8086e86eacb00366c87042c6ca277a6768dbd946378ae5a89f344910bb.jpg) \nFig. 4. Room-temperature operation of a ferroelectric field-effect transistor. (A) Temperature dependence of the magnitude of the polarization $P_{\\mathrm{2D}}$ for device P1. The inset shows a zoom-in of the vertical axis. (B) Hysteresis of resistance at various temperatures. $V_{\\mathrm{B}}/d_{\\mathrm{B}}$ is scanned in the backward (forward) direction starting from $+0.42\\ V/\\mathsf{n m}$ $(-0.42\\lor/\\mathsf{n m})$ in the blue (red) curve. Each curve is offset for clarity. The offset values are shown as dotted lines. (C) Resistance (red curve) after the repeated application of a voltage pulse of $V_{\\mathrm{B}}=+1.8\\ V$ and $V_{\\mathrm{B}}=-1.2~\\ V$ (black curve), which corresponds to $V_{\\mathrm{B}}/d_{\\mathrm{B}}=+0.19$ and $-0.13\\ V/\\mathsf{n m}$ , respectively. The measurement is performed at $T=300~\\mathsf{K}$ and \n$V_{\\top}/d_{\\top}=0.07~\\mathsf{V/n m}.$ . (D) Stability of polarization at room temperature. $V_{\\top}/d_{\\top}$ is scanned in the forward direction. The dotted green (purple) curve is measured at $V_{\\mathrm{B}}=0$ V right after applying $V_{\\mathrm{B}}/d_{\\mathrm{B}}=+0.31\\lor/\\mathsf{n m}(-0.26\\lor/\\mathsf{n m})$ to induce polarization up (down). The solid green curve is measured after applying $V_{\\mathrm{B}}/d_{\\mathrm{B}}=$ $+0.31\\lor/\\mathsf{n m}$ to induce polarization up and then leaving the device at $V_{\\mathrm{B}}=0$ V and $T=300~\\mathsf{K}$ for 14 days. The solid purple curve is measured after applying $V_{\\mathrm{B}}/d_{\\mathrm{B}}=-0.26~\\mathsf{V/n m}$ to induce polarization down and then leaving the device at $V_{\\mathsf{B}}=0~\\mathsf{V}$ and $T=300~\\mathsf{K}$ for 31 days. Each of the two curves almost exactly overlap, showing the robustness of polarization direction for a long period. \n\n2D polarization follows $P_{\\mathrm{2D}}=e\\Delta n_{\\mathrm{P}}d_{\\mathrm{B}};$ namely, the electric dipole moment between the bottom gate and graphene is equal to the magnitude of the polarization of bilayer BN. Figure 2H shows our measurement of $2\\Delta n_{\\mathrm{P}}$ for four different devices studied in this work, which indeed exhibit an inverse proportional behavior with respect to $d_{\\mathrm{B}}$ . The magnitude of the polarization estimated from these data points is $P_{\\mathrm{2D}}=2.25(0.37)\\times10^{-12}{\\bf C}\\mathrm{m}^{-1}$ (corresponding to $P_{\\mathrm{3D}}=0.68~\\upmu\\mathrm{C}~\\mathrm{cm}^{-2},$ . This agrees well with the theoretically calculated magnitude of the polarization of AB-stacked bilayer BN from a Berry phase calculation, P2D,theory = $2.08\\times10^{-12}\\mathrm{C}\\mathrm{m}^{-1}(25,37)$ . \n\nHaving established the ferroelectric nature of P-BBN, we next studied how the moiré superlattice affects the ferroelectric switching in a small-angle twisted bilayer BN. Here, owing to the opposite polarization of AB and BA stacking regions (Fig. 1, D to F), each domain with staggered polarization is expected to expand or shrink, through domain wall motion, when a vertical electric field is applied. Figure 3A shows the dual-gate scan of the resistance of graphene for a $0.6^{\\circ}$ –rotation angle twisted bilayer BN (device T1). It exhibits two parallel diagonal peaks, each corresponding to the AB or BA domains, similar to Fig. 2C. However, rather than an abrupt transition between the two lines, a gradual shift in weight from one to the other takes place along the diagonal. Thus, the magnitude of each peak gives the relative proportion of AB and BA domain sizes, or the average polarization, as a function of the applied electric field (fig. S17). The electric field dependence of the polarization (Fig. 3B) highlights the difference between the twisted and nontwisted devices. First, the coercive field is much smaller for the twisted bilayer BN than for the nontwisted P-BBN. Secondly, the polarization switching occurs gradually, in contrast to the sharp switching of the nontwisted device. In a nontwisted device, a domain wall moves over the device scale during the switching, as shown in Fig. 2, C to E, and is likely to be pinned by strong pinning centers. By contrast, each domain wall in a twisted device moves only by a moiré length scale and will experience weaker pinning centers, leading to the small coercive field. In addition, the different pinning strength of each domain wall leads to the gradual switching. Thus, the global rotation of the two layers modifies the dynamics of the ferroelectric switching behavior. \n\nFinally, we studied the temperature dependence of the ferroelectricity in P-BBN. Notably, the polarization measured from $\\Delta n_{\\mathrm{P}}$ is almost independent of temperature (Fig. 4A and fig. S22) up to room temperature. The nearly temperature-independent ferroelectric polarization presumably reflects the distinctive coupling between the out-of-plane polarization and the in-plane shear motion in P-BBN. The strong intralayer covalent bonding inhibits the in-plane thermal vibration of atoms, making the polarization insensitive to temperature (38). Correspondingly, the ferroelectric hysteresis is observable up to room temperature despite the temperature-induced broadening of the resistance peak (Fig. 4B). Such hysteretic behavior allows us to deterministically write the polarization by a voltage pulse of only a few volts and read it in a nonvolatile way, as shown in Fig. 4C. We also checked the stability of the ferroelectric polarization by keeping the sample at $_{0}\\mathrm{v}$ at room temperature for an extended period after setting the polarization to up or down (Fig. 4D). The resistance remains almost the same after at least a month (the longest period measured); namely, P-BBN retains its polarization over a technologically relevant time scale. Hence, the present result points to the potential use of P-BBN/graphene as a ferroelectric field-effect transistor with an ultrahigh mobility of graphene of around $5\\times10^{4}\\mathrm{cm^{2}V^{-1}s^{-1}}$ at room temperature (figs. S19 to S21). \n\nThe designer approach for engineering vdW ferroelectrics and moiré ferroelectrics demonstrated in this study can be extended to other bipartite honeycomb 2D materials, such as semiconducting 2H-type TMDs like $\\mathbf{MoS}_{2}$ and $\\mathrm{WSe_{2}}.$ metallic and superconducting ones like $\\mathrm{NbS_{2}}$ and $\\mathrm{NbSe_{2}}$ , and group III chalcogenides like GaS, GaSe, and InSe (25). The inversion symmetry breaking of these synthetic ferroelectrics will be coupled to the electronic band structures in a tunable manner through polarization switching. In addition to interesting physics resulting from the modification of the intrinsic properties of each material, such engineered ferroelectrics and moiré systems may substantially expand the capabilities of 2D materials for electronic, spintronic, and optical applications (15, 39). \n\nWe note that (40) and a paper in the same issue (41) report related findings. \n\n# REFERENCES AND NOTES \n\n1. K. Uchino, Ferroelectric Devices (CRC Press, 2009). \n2. D. D. Fong et al., Science 304, 1650–1653 (2004). \n3. H. Wang et al., Nat. Commun. 9, 3319 (2018). \n4. U. Schröeder, C. S. Hwang, H. Funakubo, Ferroelectricity in \nDoped Hafnium Oxide: Materials, Properties and Devices \n(Woodhead Publishing, 2019). \n5. C. Cui, F. Xue, W.-J. Hu, L.-J. Li, npj 2D Mater. Appl. 2, 18 (2018). \n6. M. Wu, P. Jena, Wiley Interdiscip. Rev. Comput. Mol. Sci. 8, e1365 \n(2018). \n7. A. V. Bune et al., Nature 391, 874–877 (1998). \n8. K. Chang et al., Science 353, 274–278 (2016). \n9. F. Liu et al., Nat. Commun. 7, 12357 (2016). \n10. Y. Zhou et al., Nano Lett. 17, 5508–5513 (2017). \n11. C. Cui et al., Nano Lett. 18, 1253–1258 (2018). \n12. S. Yuan et al., Nat. Commun. 10, 1775 (2019). \n13. Z. Fei et al., Nature 560, 336–339 (2018). \n14. C. R. Dean et al., Nat. Nanotechnol. 5, 722–726 (2010) \n15. E. Y. Tsymbal, H. Kohlstedt, Science 313, 181–183 (2006). \n16. A. K. Geim, I. V. Grigorieva, Nature 499, 419–425 (2013). \n17. B. Hunt et al., Science 340, 1427–1430 (2013). \n18. C. R. Dean et al., Nature 497, 598–602 (2013). \n19. L. A. Ponomarenko et al., Nature 497, 594–597 (2013). \n20. R. V. Gorbachev et al., Science 346, 448–451 (2014). \n21. Y. Cao et al., Nature 556, 43–50 (2018). \n22. Y. Cao et al., Nature 556, 80–84 (2018). \n23. A. L. Sharpe et al., Science 365, 605–608 (2019). \n24. M. Serlin et al., Science 367, 900–903 (2020). \n25. L. Li, M. Wu, ACS Nano 11, 6382–6388 (2017). \n26. G. Constantinescu, A. Kuc, T. Heine, Phys. Rev. Lett. 111, 036104 \n(2013). \n27. S. Zhou, J. Han, S. Dai, J. Sun, D. J. Srolovitz, Phys. Rev. B 92, \n155438 (2015). \n28. J. H. Warner, M. H. Rümmeli, A. Bachmatiuk, B. Büchner, \nACS Nano 4, 1299–1304 (2010). \n29. C.-J. Kim et al., Nano Lett. 13, 5660–5665 (2013). \n30. S. M. Gilbert et al., 2D Mater. 6, 021006 (2019). \n31. H. J. Park et al., Sci. Adv. 6, eaay4958 (2020). \n32. K. Kim et al., Nano Lett. 16, 1989–1995 (2016). \n33. Y. Cao et al., Phys. Rev. Lett. 117, 116804 (2016). \n34. H. Yoo et al., Nat. Mater. 18, 448–453 (2019). \n35. A. Weston et al., Nat. Nanotechnol. 15, 592–597 (2020). \n36. L. J. McGilly et al., Nat. Nanotechnol. 15, 580–584 (2020). \n37. R. D. King-Smith, D. Vanderbilt, Phys. Rev. B Condens. Matter \n47, 1651–1654 (1993). \n38. Q. Yang, M. Wu, J. Li, J. Phys. Chem. Lett. 9, 7160–7164 (2018). \n39. J. Sung et al., Nat. Nanotechnol. 15, 750–754 (2020). \n40. C. R. Woods et al., Nat. Commun. 12, 347 (2021). \n41. M. Vizner Stern et al., Science 372, 1462–1466 (2021). \n42. See supplementary materials. \n43. K. Yasuda, X. Wang, K. Watanabe, T. Taniguchi, P. Jarillo-Herrero, \nReplication Data for: Stacking-engineered ferroelectricity in \nbilayer boron nitride. Harvard Dataverse (2021); \nhttps://doi.org/10.7910/DVN/JNXOIM. \n\n# ACKNOWLEDGMENTS \n\nWe thank S. de la Barrera, D. Bandurin, Z. Zheng, Q. Ma, Y. Zhang, L. Fu, and M. Wu for fruitful discussions and J. M. Park, E. Soriano, and \n\nJ. Tresback for experimental support. Funding: This research was partially supported by US Department of Energy (DOE) Basic Energy Sciences (BES) grant DE-SC0018935 (early characterization measurements and device nanofabrication); by the Center for the Advancement of Topological Semimetals, an Energy Frontier Research Center funded by the DOE Office of Science, through the Ames Laboratory under contract DE-AC02-07CH11358 (performance measurements and data analysis); the Army Research Office (early effort towards device nanofabrication) through grant no. W911NF1810316; and the Gordon and Betty Moore Foundation’s EPiQS Initiative through grant GBMF9643 to P.J.-H. This work made use of the Materials Research Science and Engineering Center Shared Experimental Facilities supported by the National Science Foundation (NSF) (grant no. DMR-0819762). This work was performed in part at the Harvard University Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Coordinated Infrastructure Network (NNCI), which is supported by the NSF under NSF ECCS award no. 1541959. K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT, Japan (grant no. JPMXP0112101001); JSPS KAKENHI (grant no. JP20H00354); and the CREST (JPMJCR15F3). K.Y. acknowledges partial support from JSPS Overseas Research Fellowships. Author contributions: K.Y. and P.J.-H. conceived the project. K.Y. and X.W. fabricated the devices and performed the measurements. K.W. and T.T. grew the hBN bulk crystals. K.Y., X.W., and P.J.-H. analyzed and interpreted the data and wrote the manuscript with contributions from all authors. Competing interests: The authors declare no competing interests. Data and materials availability: The data shown in the paper are available at Harvard Dataverse (43). \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/372/6549/1458/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S26 \nTable S1 \nReferences (44–54) \n19 June 2020; accepted 8 May 2021 \nPublished online 27 May 2021 \n10.1126/science.abd3230 " + }, + { + "id": "10.1021_acsnullo.0c08357", + "DOI": "10.1021/acsnullo.0c08357", + "DOI Link": "http://dx.doi.org/10.1021/acsnullo.0c08357", + "Relative Dir Path": "mds/10.1021_acsnullo.0c08357", + "Article Title": "Modified MAX Phase Synthesis for Environmentally Stable and Highly Conductive Ti3C2 MXene", + "Authors": "Mathis, TS; Maleski, K; Goad, A; Sarycheva, A; Anayee, M; Foucher, AC; Hantanasirisakul, K; Shuck, CE; Stach, EA; Gogotsi, Y", + "Source Title": "ACS nullO", + "Abstract": "One of the primary factors limiting further research and commercial use of the two-dimensional (2D) titanium carbide MXene Ti3C2, as well as MXenes in general, is the rate at which freshly made samples oxidize and degrade when stored as aqueous suspensions. Here, we show that including excess aluminum during synthesis of the Ti3AlC2 MAX phase precursor leads to Ti3AlC2 grains with improved crystallinity and carbon stoichiometry (termed Al-Ti3AlC2). MXene nullosheets (Al-Ti3C2) produced from this precursor are of higher quality, as evidenced by their increased resistance to oxidation and an increase in their electronic conductivity up to 20 000 S/cm. Aqueous suspensions of stoichiometric single-to few-layer Al-Ti3C2 flakes produced from the modified Al-Ti3AlC2 have a shelf life of over ten months, compared to 1 to 2 weeks for previously published Ti3C2, even when stored in ambient conditions. Freestanding films made from Al-Ti3C2 suspensions stored for ten months show minimal decreases in electrical conductivity and negligible oxidation. Furthermore, oxidation of the improved Al-Ti3C2 in air initiates at temperatures that are 100-150 degrees C higher than that of conventional Ti3C2. The observed improvements in both the shelf life and properties of Al-Ti3C2 will facilitate the widespread use of this material.", + "Times Cited, WoS Core": 589, + "Times Cited, All Databases": 624, + "Publication Year": 2021, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000645436800038", + "Markdown": "# Modified MAX Phase Synthesis for Environmentally Stable and Highly Conductive T $i_{3}C_{2}$ MXene \n\nTyler S. Mathis, Kathleen Maleski, Adam Goad, Asia Sarycheva, Mark Anayee, Alexandre C. Foucher, Kanit Hantanasirisakul, Christopher E. Shuck, Eric A. Stach, and Yury Gogotsi\\* \n\nCite This: ACS Nano 2021, 15, 6420−6429 \n\n# ACCESS \n\n山 Metrics & More \n\nArticle Recommendations \n\nSupporting Information \n\nABSTRACT: One of the primary factors limiting further research and commercial use of the two-dimensional (2D) titanium carbide MXene ${\\bf T i}_{3}{\\bf C}_{2},$ as well as MXenes in general, is the rate at which freshly made samples oxidize and degrade when stored as aqueous suspensions. Here, we show that including excess aluminum during synthesis of the $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ MAX phase precursor leads to $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ grains with improved crystallinity and carbon stoichiometry (termed $\\mathbf{Al-Ti_{3}A l C}_{2}^{\\mathbf{\\eta}},$ ). MXene nanosheets $\\left(\\mathbf{Al-Ti_{3}C}_{2}\\right)$ produced from this precursor are of higher quality, as evidenced by their increased resistance to oxidation and an increase in their electronic conductivity up to $20000\\ \\mathrm{S/cm}$ . Aqueous suspensions of stoichiometric singleto few-layer $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ flakes produced from the modified Al− $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ have a shelf life of over ten months, compared to 1 to 2 weeks for previously published ${\\bf T i}_{3}{\\bf C}_{2},$ even when stored in ambient conditions. Freestanding films made from $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ suspensions stored for ten months show minimal decreases in electrical conductivity and negligible oxidation. Furthermore, oxidation of the improved $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ in air initiates at temperatures that are $\\bf{100-150\\ ^{\\circ}C}$ higher than that of conventional $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ . The observed improvements in both the shelf life and properties of $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ will facilitate the widespread use of this material. \n\n![](images/43dfe5cc6138ec3556b9c7491478848822ed58a48f663209152c77422dbe70f0.jpg) \n\nKEYWORDS: MXene, $T i_{3}C_{2},$ long-term stability, oxidation resistance, electronic conductivity \n\n# INTRODUCTION \n\nExfoliation of layered materials into two-dimensional (2D) nanosheets can lead to properties that often differ significantly from their bulk analogs. This has provided the building blocks necessary for developing nanoscale devices, metamaterials, and composites to meet emerging technological needs.1 MXenes are a large family of 2D transition metal carbides, nitrides, and carbonitrides that have the general formula $\\mathbf{M}_{n+1}\\mathbf{X}_{n}\\mathbf{T}_{x},$ where M is an early transition metal, X is carbon and/or nitrogen, and $n$ is an integer from 1 to 4. The $\\mathrm{T}_{x}$ represents surface terminations $\\scriptstyle(=0,$ , −OH, and $-\\mathrm{F}$ ) that commonly result from the wet chemical etching methods used to produce MXenes from their MAX phase precursors (A is typically a group 13 or 14 element, e.g., aluminum). More than 30 stoichiometric MXene structures have been synthesized from the more than 100 predicted compositions, and there have also been reports on the synthesis of solid solution MXenes.2,3 MXenes have been utilized in various fields, including energy storage and conversion, electromagnetic interference shielding, nanocomposites, sensors, and biomedical applications.4,5 \n\nAs the scope of MXene research has expanded, so too have studies on improving the quality of MXenes by exploring new synthesis routes and processing methods in order to enhance their performance.6− MXenes have several significant advantages over graphene and many other conducting nanomaterials: MXenes form stable colloidal solutions without additives or surfactants and they can easily be processed using the cheapest and safest solvent−water. However, MXenes are quick to oxidize in aqueous solutions and generally last no more than a few weeks when stored in aqueous media.10−14 \n\n![](images/ffeb5bac91a74d42bba2fb4a1f771b0f467f03d41dc4ed2f6824313e3388b074.jpg) \n\n![](images/861d86e35c4c9d4c3c68aa68f5beff888652540f594c27fc0bb58ce445fe7d2e.jpg) \nFigure 1. (a) X-ray diffraction (XRD) patterns of Al− $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (blue) and conventional $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (green) after washing with hydrochloric acid. Both samples were mixed with Si powder to serve as an internal standard. (b) Polarized Raman spectra of Al− $\\mathbf{\\cdotTi_{3}A l C}_{2}$ (red, not acid washed) and conventional $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (black, not acid washed). (c) Scanning electron microscopy (SEM) image of a hexagonal grain of HCl washed Al− $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ . Lower magnification SEM images of HCl washed $\\mathbf{Al-Ti_{3}A l C}_{2}$ (d) and conventional $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (e). \n\nSome $\\mathbf{M}_{2}\\mathbf{C}$ MXenes will even degrade within a day.10,15 This has prompted many investigations into the mechanisms of MXene degradation in order to prolong their shelf life.10−14,16 \n\nRecent work has focused on modifying the synthesis of MAX phases, as this can profoundly affect the synthesis, quality, and properties of the resultant MXene.17 The common assumption is that phase-pure MAX should lead to the highest quality MXene, and most studies have utilized established MAX phase synthesis procedures that result in the incorporation of minimal amounts of impurities into the sintered product. We report here the surprising result that the phase purity of the assintered MAX does not necessarily determine the quality of the resultant MXene. \n\nIn this study, we included excess aluminum (A-element) during the high-temperature synthesis of the MAX phase ${\\mathrm{Ti}_{3}}\\mathrm{Al}{\\bar{\\mathrm{C}}_{2}}$ to create a liquid phase at an early stage of the synthesis process. The presence of excess of molten metal during synthesis enhances the diffusion of reactants, resulting in $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ grains with improved structural ordering and morphology, while also working to decrease oxygen activity, producing highly stoichiometric MAX phase. This MAX phase (which we will refer to as $\\mathrm{{Al-Ti}_{3}A l C}_{2}^{\\cdot}$ ) was then used for the synthesis of high-quality $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{x}$ nanosheets (subsequently denoted as $\\mathrm{\\DeltaAl-Ti}_{3}C_{2}$ for simplicity). We find that the aqueous $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ solutions produced from the Al− $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX have an exceptional shelf life ( ${\\mathrm{>}}10$ months at ambient temperature) with only minimal steps taken to protect the MXene. Freestanding films made from fresh $\\mathrm{{Al-Ti}}_{3}\\mathrm{{C}}_{2}$ solutions have electronic conductivities as high as $20000\\ {\\mathrm{S}}/$ cm. These results represent a significant improvement in the oxidation stability of MXenes and can be expected to significantly impact their incorporation into industrial applications, enhancing their commercial viability. \n\n# RESULTS AND DISCUSSION \n\n$\\mathrm{\\Al{-}T i_{3}A l C}_{2}$ MAX was produced by pressureless sintering of a nonstochiometric mixture of TiC, Ti, and Al powders that contained excess Al (see Experimental Methods section). The as-produced MAX contains intermetallic compoundsnamely in the form of $\\mathrm{TiAl}_{3}$ as seen in the X-ray diffraction (XRD) \n\npattern of $\\mathrm{\\calAl{-}T i_{3}A l C}_{2}$ (Supporting Information (SI) Figure S1, red). The intermetallic impurities cause the body of the block of MAX to have a lustrous, metallic sheen when the sintered block is milled, which is not the case for blocks of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ produced using conventional synthesis methods (SI Figure S2).9 Generally, the use of excess aluminum in the synthesis of MAX phases is known to introduce deleterious impurities into the final sintered product.18,19 However, XRD analysis shows that these intermetallic impurities can easily be removed by washing the milled $\\mathsf{A l{-}T i}_{3}\\mathsf{A l C}_{2}$ powder in hydrochloric acid (HCl) at room temperature (Figure 1a, blue). There were no intermetallic impurities or differences observed in the XRD patterns of conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ before (SI Figure S1, black) and after acid washing (Figure 1a, green). Comparison of the XRD patterns of the HCl washed conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and the HCl washed $\\mathrm{{Al-Ti}}_{3}\\mathrm{{AlC}}_{2}$ reveals that there are minor differences in the diffraction patterns based on the positions of the defining peaks of the two materials (Figure 1a and SI Table S2). The small differences in the positions of the (002) and (110) peaks of the $\\mathsf{A l{-}T i}_{3}\\mathsf{A l C}_{2}$ and conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX phases listed in SI Table S2 indicate that the $\\mathbf{\\Psi}_{c}$ and a lattice parameters vary slightly between the two MAX phases. To better understand how the excess aluminum affects the composition and bonding within the MAX, we further compared the $\\mathsf{A l{-}T i}_{3}\\mathsf{A l C}_{2}$ with conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ using Raman spectroscopy. The Raman spectra of $\\mathrm{\\Al{-}T i_{3}A l C}_{2}$ (red, not acid washed) and conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (black, not acid washed) show the presence of TiC in both samples, along with the MAX phase $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (Figure 1b). The vibrational spectrum of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ consists of seven modes: 3 $E_{\\mathrm{{2g}}}+2\\ E_{\\mathrm{{1g}}}+2\\ A_{\\mathrm{{1g}}},$ where the sharp peak at $201~\\mathrm{cm}^{-1}$ in the spectrum of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}^{\\mathrm{^{\\circ}}}$ (green) is assigned to the $E_{2\\mathrm{g}}$ vibration of Ti, Al, and C.20 This vibration has a larger full width at half-maximum and lower intensity for $\\mathsf{A l{-}T i}_{3}\\mathsf{A l C}_{2}$ (red). It is worth noting that this is the only observable vibration that involves Al atoms. The broadening and diminishing of this peak in $\\mathrm{\\bfAl{-}T i_{3}A l C}_{2}$ suggests some structural changes in the Al layer. The out-of-plane peaks $\\mathrm{A_{lg}}$ symmetric and asymmetricare present in both spectra. However, in the case of $\\mathrm{{Al-Ti}}_{3}\\mathrm{{AlC}}_{2},$ the symmetric peak shifted slightly from 270 to $274~\\mathrm{{cm}^{-1}}$ and the asymmetric peak shifted from 659 to $661~\\mathrm{{\\cm}^{-1}}$ . The positions of the corresponding peaks in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ are located at 200 and 723 $\\mathrm{cm}^{-1}$ , respectively.21 The $300{-}500~\\mathrm{cm^{-1}}$ region has previously been attributed to impurities, but the exact origin of these peaks has yet to be determined.20 There is also an additional peak at approximately $549~\\mathrm{{cm}^{-1}}$ which was not always reproducible when we performed further Raman spectroscopy measurements on numerous individual $\\mathsf{A l{-}T i}_{3}\\mathsf{A l C}_{2}$ grains, suggesting that this peak may be attributed to a localized impurity that is not easily detectable when the MAX phase is analyzed as a bulk sample (SI Figure S3). Raman mapping measurements also show that the intensity of individual vibrational modes vary across the surface and edges of the Al− $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ particles (SI Figure S4), which may also lead to the variations in the spectra of different grains of $\\mathrm{\\Al{-}T i_{3}A l C}_{2}$ . Further in-depth investigations into the root of the changes of the lattice parameters and bonding in the $\\mathrm{\\Al{-}T i}_{3}\\mathrm{AlC}_{2}$ MAX phase are ongoing, however, this is beyond the scope of the results presented in this study. The acid washed $\\mathsf{A l-T i}_{3}\\mathsf{A l C}_{2}$ MAX also has well-shaped, hexagonal grains. We believe this to be the result of enhanced diffusion of the reactants during the sintering process caused by the presence of excess molten aluminum (Figure 1c and SI Figure $S5a{-c}$ ). Comparing low magnification SEM images of the conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and the $\\mathrm{Al-Ti}_{3}\\mathrm{AlC}_{2}$ shows the differences in the overall morphology of the grains of the two MAX phases. The conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ is composed of irregular, globular particles (Figure 1d), whereas the $\\mathrm{\\Al{-}T i_{3}A l C}_{2}$ is predominately made up of hexagonal, platelet-like particles (Figure 1e). We etched the HCl washed $\\mathrm{\\bfAl{-}T i_{3}A l C}_{2}$ using a mixture of hydrofluoric and hydrochloric acids (HF/HCl etching) and then delaminated the MXene by stirring the etched $\\mathrm{\\Al{-}T i}_{3}\\mathrm{C}_{2}$ in an aqueous solution of LiCl. This procedure yields suspensions of delaminated $\\mathrm{\\DeltaAl{-}T i_{3}C_{2}}$ flakes that largely retain the shape of the starting Al−Ti ${}_{3}\\mathrm{AlC}_{2}$ MAX particles (SI Figure S5d). \n\n![](images/49f49807e525cfbae4e9bf5e7b3071c1a17d40007c36a30b2ac5122d9e9377d3.jpg) \nFigure 2. XRD patterns of (a) multilayer (ML) powders and (b) freestanding films produced via vacuum-assisted filtration of delaminated $\\mathbf{\\Pi}(\\mathbf{D})$ $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ and conventional $\\mathbf{Ti}_{3}\\mathbf{C}_{2}.$ . (c) Electronic conductivity of freestanding films of $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ suspensions at different stages of the delamination process. Black squares represent measurements performed on different samples. Blue circles represent average values. Thermogravimetric analysis (TGA) in air for (d) (ML) powder and (e) (D) $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ film samples produced from Al− $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ and conventional $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ . Both types of MAX were washed using HCl prior to etching. \n\nXRD patterns of the multilayer powders and freestanding films of both $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ and $\\mathbf{Al-T}_{3}\\mathbf{C}_{2}$ show that there are no impurities or secondary phases in the MXene samples, which were present in the MAX phases that could influence the MXene properties (Figure 2a,b). The XRD patterns of the multilayer samples also do not show the (014) peak of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ at ${\\sim}39^{\\circ}$ that is characteristic of multilayer MXene samples containing residual, unetched MAX phase. Both of the freestanding film samples only show (00l) peaks, as expected for delaminated MXene. The broadening of the (004) and (006) peaks of the $\\mathrm{\\Al{-}T i_{3}C}_{2}$ freestanding film versus the conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ film in Figure 2b can be explained by minor differences in the amount of water contained between the MXene layers and slight differences in the packing of the MXene flakes. These effects have been studied extensively in the literature.22−24 The differences observed for the XRD patterns of the MXene films in Figure 2b are not significant enough to warrant extensive analysis of the interlayer spacing. One characteristic property of MXenes, and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ in particular, is the high electronic conductivity of films produced from solutions of single- or few-layer MXene flakes. Freestanding films made by vacuum filtering $\\mathrm{\\calAl-Ti}_{3}\\mathrm{\\calC}_{2}$ solutions have conductivities ranging from slightly higher than $10000\\mathrm{{\\:}S/}$ cm up to values exceeding $20000~{\\cal S}/{\\mathrm{cm}}$ (Figure 2c). It is important to note that the electronic conductivity of a MXene film depends not only on the quality of the MXene, but also on the film structure and morphology. Features such as flake alignment, film roughness, and interflake distance influence the conductivity of MXene films. However, such features were controlled during our film fabrication process for a direct comparison of the influence of the MXene quality on their resulting films’ conductivity. The conductivities of the films produced in this study $\\left(>20000\\ \\mathrm{S/cm}\\right)$ exceed the values reported in recent years for $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ freestanding films and coatings (ranging from 8000 to 15 000 S/cm).9,25−27 \n\n![](images/a0a9b017ab54936c7176f97208201414dfc91a4b986c02f30a100c03b515bb28.jpg) \nFigure 3. UV−vis spectra for aqueous suspensions of (a) $\\mathbf{Al-Ti_{3}C}_{2}$ and (b) conventional $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ recorded immediately after synthesis (Day 1, solid lines) and after 30 days of storage in argon-filled vials under ambient conditions (Day 30, dashed lines). Both MXene suspensions had starting concentrations of approximately $\\mathbf{1.7\\mg/mL}$ . (c) Absorbance changes in the UV−vis spectra (relative to the initial absorbance at 264 nm) over the course of 30 days for the stored $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ and conventional $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ solutions. High-angle annular dark-field scanning transmission electron (STEM) microscopy images of $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ flake edges produced from conventional $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (d) and $\\mathbf{Al-Ti_{3}A l C}_{2}$ (e). Inset in (e) shows an atomic-resolution cross-sectional STEM image from an $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ flake. Both types of MAX were washed using HCl prior to etching. \n\nThe conductivity of the $\\mathrm{{Al-Ti}}_{3}\\mathrm{{C}}_{2}$ films varies slightly depending on the quantity of water used during the delamination process (Figure 2c). The morphology of the $\\mathrm{\\Al{-}T i_{3}C_{2}}$ films matches the morphology expected of films of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ produced via vacuum-assisted filtration (SI Figure S6), and since the concentration of the delaminated $\\mathrm{{Al-Ti}}_{3}\\mathrm{{C}}_{2}$ colloidal solutions is also dependent on the quantity of water used during delamination (SI Figure S7), it is likely that the highest quality single-layer flakes delaminate first, leading to the highest quality films. However, traces of LiCl present in the MXene solutions in the initial stages of delamination may also influence the properties of the final films. We find that, as the delamination process continues, the remaining LiCl is removed (SI Figure S8). \n\nThermogravimetric analysis (TGA) of delaminated film and multilayer powder $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ samples conducted in air shows that $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ has significantly improved oxidation stability versus $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ produced from conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ (Figure $\\mathbf{\\pi}_{2\\mathrm{d},\\mathbf{e}}^{\\cdot}$ ). During the initial stage of heating (below $200^{\\circ}\\mathrm{C}\\cdot$ ), each sample shows mass loss due to the removal of water that was intercalated between the layers or adsorbed on the surfaces of the MXene samples. Weight gain due to oxidation begins at ${\\sim}150~^{\\circ}\\mathrm{C}$ higher for the delaminated $\\mathrm{\\DeltaAl{-}T i_{3}C_{2}}$ versus the conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . Oxidation of the $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ multilayer powder, where the flake edges are exposed and no continuous protective oxide can form, occurs at a much slower rate than the conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . Indicating that the oxidation stability of solid films and powders of $\\mathrm{\\DeltaAl{-}T i_{3}C_{2}}$ is improved in air. Moreover, the high-temperature resistance of the delaminated $\\mathrm{\\Al{-}T i}_{3}\\mathrm{C}_{2}$ in air is improved by approximately $200~^{\\circ}\\mathrm{C}$ over literature reports, up to $450~^{\\circ}\\mathrm{C}$ .28 This can potentially expand the use of MXenes to applications requiring operation at elevated temperatures in air, such as sensors or electronics operating near hot engines or electrical components. \n\nWe performed UV−vis spectroscopy on suspensions of both $\\mathrm{\\DeltaAl{-}T i_{3}C_{2}}$ and conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ that were placed in argonfilled vials immediately after synthesis and monitored changes in their absorbance spectra over the course of 30 days (Figure 3a,b). The UV−vis spectra in Figure 3a for the $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ sample recorded after 30 days of storage under ambient is nearly identical to the Day 1 spectra, with only a slight red-shift in the peak at $768~\\mathrm{nm}$ . Red-shifts of this peak have been shown to be caused by changes in the oxidation state of the Ti in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ .29 However, the spectra in Figure 3b show there is a noticeable change in the shape of the spectrum and a decrease in the absorbance of the conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ sample after 30 days. Comparing changes in the absorbance of the $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ and conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ solutions relative to their initial absorbance at $264\\mathrm{nm}$ over the course of the 30 day test shows the absorbance of the conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ sample decreases by approximately $6\\%$ , whereas the $\\mathrm{{Al-Ti}}_{3}\\mathrm{{C}}_{2}$ sample remains unchanged. Comparing high-resolution scanning transmission electron microscopy (HRSTEM) images of the edges of fresh conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ (Figure 3d) and $\\mathrm{\\Al{-}T i_{3}C}_{2}$ (Figure 3e) flakes show that the edges of $\\mathrm{\\DeltaAl{-}T i_{3}C_{2}}$ are smoother, without any of the protuberances seen in the conventional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . \n\n![](images/e82ad5051ebb160609ef411db5dd3031656f895c26ef9a1cbb14f14a9fbd4080.jpg) \nFigure 4. (a) Absorbance changes over time (relative to the initial absorbance at $264~\\mathrm{{nm}}$ ) for the stored Al− $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ solution calculated from the UV−vis spectra in (b). The gray region corresponds to suspension concentrations of $\\mathbf{1.5{-}1.8\\ m g/m L}$ . (b) UV−vis spectra recorded over time for an aqueous $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ solution stored in ambient conditions. (c) Electronic conductivity of freestanding $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ films made from solutions stored for different periods of time. (d) Raman spectra of films made from solutions stored for different periods of time. TEM images of a fresh $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ flake (e) and an $\\mathbf{Al-Ti}_{3}\\mathbf{C}_{2}$ flake from a 10-month-old solution (f). The red circles mark all the observable pinholes in the flake. \n\nImages of the basal planes of both flakes look very similar, however (SI Figure S9). \n\nThe most notable property of the $\\mathrm{\\DeltaAl-Ti}_{3}C_{2}$ produced from HCl-washed $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX is its significantly improved shelf life as an aqueous colloidal suspension. To test the long-term stability of the $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ solutions, we took the minimum amount of precautions to protect the $\\mathrm{\\Al{-}T i_{3}C}_{2}$ flakes, as to simulate the most typical laboratory storage conditions. Delaminated $\\mathrm{\\Al{-}T i}_{3}\\mathrm{C}_{2}$ solutions were degassed by bubbling argon through the solutions at the as-produced concentration directly after centrifugation before the solutions were transferred to sealed, argon-filled vials and then stored away from light in a laboratory bench drawer at room temperature. This is a common way of preparing colloidal solutions for shipment or storage that requires no specialized equipment, deep refrigeration, or stabilizing additives. Changes in the suspension’s absorbance over time based on UV−vis measurements recorded periodically during the storage period show that the concentration of the suspension remains relatively unchanged (Figure 4a). Outside of small fluctuations in absorbance, no noticeable changes in the UV−vis spectra of the stored samples occurred until the 4-month mark (Figure 4b), where a slight red-shift of the $768~\\mathrm{nm}$ peak to $780~\\mathrm{nm}$ occurs. When a film was made from the solution that was stored for 4 months, the conductivity was still over $10000\\mathrm{~}\\mathrm{{S/}}$ cm, close to the range of measurements made from films directly after delamination (Figure 4c). After 6 months of storage, the UV−vis spectra of the $\\mathrm{\\DeltaAl-Ti}_{3}C_{2}$ solution still had only a slight red-shift in the ${\\sim}780\\ \\ \\mathrm{\\nm}$ peak, but the conductivity of the film made from the 6-month-old solution dropped to just over $6000~\\mathrm{{S/cm}}$ . The Raman spectra of the $\\mathrm{\\Al{-}T i_{3}C}_{2}$ films made from fresh, 4-month-old, and 6-monthold solutions are identical. No photoluminescent background is present, meaning there was no titanium oxide formation during storage (Figure 4d).21 Minor oxidation begins after approximately 4 months for these storage conditions, as determined by the decrease in electronic conductivity. Comparison of TEM images of fresh $\\mathrm{\\Al{-}T i_{3}C}_{2}$ flakes and $\\mathrm{\\DeltaAl{-}T i}_{3}C_{2}$ flakes stored for 10 months exhibit few pinholes (commonly observed in samples stored for extended periods13 (Figure 4e,f) and very few $\\mathrm{TiO}_{2}$ crystals after nearly a year of storage (SI Figure S10). From the core level $\\mathrm{x}$ -ray photoelectron spectra (XPS), there were negligible differences in the chemical environments of Ti, C, and Al (Figure ${\\mathfrak{S a}}{-}\\mathfrak{c},$ respectively) between the $\\mathrm{\\bfAl{-}T i}_{3}\\mathrm{\\bfAlC}_{2}$ and conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX phases. However, close inspection of the O 1s region reveals that there is less oxygen in $\\mathrm{{Al-Ti}}_{3}\\mathrm{{AlC}}_{2},$ whereas conventional MAX contains oxygen, potentially in the form of oxycarbides (SI Figure S11). The close to perfect stoichiometry and elimination of oxygen from the carbon sublattice may have contributed to the improved oxidation stability of the resulting $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ . The straight edges of the $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ flakes show no traces of oxides after being exposed to air for a few days prior to the TEM measurements, which is another sign that the $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ is highly stable. It is known the that oxidation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ starts from point defects and edges and it was proposed that stabilization of the edges of the flakes by adsorbed species can improve the oxidation stability of Ti3C2.30 \n\nConventionally, aqueous solutions of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ will be completely oxidized after just a few weeks of storage in ambient conditions.10,11,13 Therefore, if further steps were taken to optimize the storage conditions for $\\mathrm{\\Al{-}T i}_{3}\\mathrm{C}_{2}$ solutions, such as storing the samples at temperatures near or below freezing to slow oxidation or by concentrating the $\\mathrm{\\Al{-}T i}_{3}\\mathrm{C}_{2}$ solutions to concentrations of tens or even hundreds of $\\mathrm{{mg/mL}}$ by high speed centrifugation to reduce the total amount of water in the solutions, we speculate that the shelf life of $\\mathrm{\\DeltaAl{-}T i_{3}C_{2}}$ solutions would be increased to years. Recent results show that freezing $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ solutions allows for storage for multiple years, however, we can now achieve similar results under ambient conditions with $\\mathrm{\\Al{-}T i_{3}C}_{2}$ .31 Our current results suggest that the improved oxidation stability of $\\mathrm{Al-}$ $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ is most likely due to a reduction in the number of defects in the carbon sublattice of MAX synthesized with excess aluminum, which would then result in MXene flakes that are less defective and have improved Ti:C stoichiometry (SI Table S3). A recent computational study reported that Al monovacancies $(V_{\\mathrm{Al}})$ , Al divacancies $(2~V_{\\mathrm{Al-Al}})$ , and divacancies composed of Al and C atoms $(2~V_{\\mathrm{Al-C}})$ are the most easily formed vacancies in $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ .32 Therefore, the presence of excess aluminum could play a role in minimizing carbon vacancies and reduce the associated loss of Ti atoms near carbon vacancies after etching. Reducing the loss of Ti atoms from the surface of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ flakes would in turn minimize the locations for water hydrolysis to occur, thereby slowing the rate at which the flakes degrade.10 The only apparent degradation seen in the TEM images from the Al− $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ flakes stored for 10 months (Figure 3f, SI Figure S10) are pinholes and titania particles formed in the middle of the flakes. No degradation is visible along the edges of the flakes, meaning that the degradation of the flakes is occurring primarily in the middle of the flakes. The slow degradation rate of $\\mathrm{\\Al{-}T i}_{3}\\mathrm{C}_{2}$ indicates that the surfaces of the $\\mathrm{\\Al{-}T i_{3}C_{2}}$ flakes contain relatively few points for degradation to occur. However, more in-depth studies will be needed to determine the exact mechanism of how using excess aluminum, or other molten fluxes, during MAX phase synthesis affects the atomic structure, composition, and growth of MAX phases.33,34 However, even without a complete understanding of the exact origin of the dramatic improvement in the stability of $\\mathrm{\\DeltaAl-Ti}_{3}\\mathrm{C}_{2},$ the results presented in this study will allow the MXene community to begin utilizing highly stable MXenes. \n\n![](images/0b8568b803c07426260ecad5f06cf9e23ed8dc1470185b23c3fb7b6626072cf6.jpg) \nFigure 5. X-ray photoelectron spectroscopy (XPS) spectra of (a) $\\mathbf{Ti}2\\mathbf{p},$ (b) C 1s, and (c) Al ${\\bf2p}$ regions of Al− $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (left) and conventional $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ (right). Both the $\\mathbf{Al-Ti_{3}A l C}_{2}$ and conventional $\\mathbf{Ti}_{3}\\mathbf{AlC}_{2}$ were acid washed using HCl prior to performing XPS measurements for consistency. \n\nIn prior work, researchers selecting MAX phase precursors for MXene synthesis were solely concerned with the phase purity of the MAX. Our results show that the optimization of MAX phase synthesis should aim to improve the properties of the resulting MXenes. As of now, the crystallinity and M:X stoichiometric ratio of the MAX appear to be the main factors. Finding optimal precursor ratios and synthesis conditions for non- ${\\mathrm{.Ti}}_{3}{\\mathrm{AlC}}_{2}$ MAX phases that will not produce mixed compositions (i.e., mixed $\\mathbf{M}_{3}\\mathbf{AlC}_{2}$ and $\\mathbf{M}_{2}\\mathrm{AlC}$ phases) or introduce impurities that cannot be readily removed will be the key challenges moving forward. \n\n# CONCLUSIONS \n\nBy modifying the synthesis of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ to produce a more stoichiometric MAX phase that is closer to the ideal Ti:C ratio (3:2) with grains that are more homogeneous in structure and have a hexagonal morphology, we have significantly improved the quality of the resulting $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene flakes, thereby markedly improving the shelf life and stability of the MXene. Doing so significantly improves both the commercial viability of MXenes and the ease with which MXenes can be studied. Storage of the improved $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ in closed vials at room temperature for 10 months with minimal degradation has been demonstrated. Additionally, the improved flake quality resulted in MXene films with higher electronic conductivity, with some films exceeding $20000\\ {\\mathrm{S/cm}}.$ −the highest value reported for any solution processable 2D material reported thus far. The oxidation stability of the MXene in air was also significantly improved, increasing the onset of oxidation by ${\\sim}150~^{\\circ}\\mathrm{C}$ . We anticipate that this modified methodology will be used as a guide to improve the oxidation stability and electronic conductivity of a large variety of carbide MXenes. \n\n# EXPERIMENTAL METHODS \n\n$\\mathsf{A l-T i}_{3}\\mathsf{A l C}_{2}$ MAX Synthesis. TiC (Alfa Aesar, $99.5\\%$ , $2\\ \\mu\\mathrm{m}$ powder), Ti (Alfa Aesar, $99.5\\%$ , $325\\mathrm{\\mesh},$ ), and Al (Alfa Aesar, $99.5\\%$ , 325 mesh) powders were mixed in a 2:1.25:2.2 molar ratio and then ball milled using yttria stabilized zirconia milling media (Inframat Advanced Materials, $12~\\mathrm{\\mm}$ diameter) for $^{18\\mathrm{~h~}}$ continuously at $70~\\mathrm{rpm}$ in high density polyethylene bottles. A 2:1 mass ratio of zirconia milling media to precursor powder mixture was used. Upwards of $_{100\\mathrm{~g~}}$ of precursor powder was ball milled in 250 mL bottles, smaller bottles were used for smaller batches. The precursor powder was not sieved after being ball milled. The only observable differences in XRD patterns of the precursor mixtures for the standard aluminum content $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ and the high aluminum $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ following ball milling was an increased intensity of the peaks of the aluminum metal in the high Al content precursor mixture, no new phases or alloying was observed (SI Figure S12). The ball milled precursor powder was then packed into an alumina crucible and covered with graphite foil and placed into a tube furnace. The furnace was purged with argon for $30~\\mathrm{{min}}$ at room temperature. After purging, the precursor powders were heated to $1380^{\\circ}\\mathrm{C}$ and held for $^{2\\mathrm{h}}$ under a constant argon flow at ${\\sim}100$ sccm. The heating and cooling rates were both $3~{\\mathrm{{}^{\\circ}C/m i n}}$ . The sintered block of $\\mathrm{\\Al{-}T i}_{3}\\mathrm{AlC}_{2}$ was then milled using a TiN coated milling bit to produce MAX powder which was subsequently washed using $9\\mathrm{~M~HCl}$ (Fisher Scientific, U.S.). Typically, $500~\\mathrm{mL}$ of 9 M HCl is sufficient to wash upward of 50 to 60 $\\mathbf{g}$ of $\\mathrm{\\mathbf{Al-Ti_{3}A l C}}_{2}$ . The MAX was washed until the evolution of gas bubbles from the solution stopped. Four hours is the minimum washing time that has been tested so far. Acid washing of the Al− $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX results in ca. $20\\text{\\textperthousand}$ loss of mass (SI Table S1) which is primarily attributed to the removal of intermetallic impurities. The acid washed MAX was then neutralized by filtering the $\\mathrm{Al{-}T i_{3}A l C_{2}/}$ HCl mixture though a vacuum filtration unit followed by repeated filtration of DI water through the $\\mathrm{\\calAl{-}T i_{3}A l C}_{2}$ deposit. The pore size of the filter membrane used was $5\\ \\mu\\mathrm{m}$ . During neutralization of the acid washed $\\mathrm{{Al-Ti}}_{3}\\mathrm{{AlC}}_{2},$ the acidic supernatant has a deep purple color (SI Figure S2c). The neutralized MAX was then dried in a vacuum oven for at least $6\\mathrm{{h}}$ at $80~^{\\circ}\\mathrm{C}.$ . The dried $\\mathrm{\\bfAl{-}T i_{3}A l C}_{2}$ was then sieved through a 450-mesh $\\left(32\\mu\\mathrm{m}\\right)$ particle sieve. The washed, dried, and sieved $\\mathrm{\\bfAl{-}T i_{3}A l C}_{2}$ was then etched to produce MXene. \n\n$\\bar{\\mathsf{T i}}_{3}\\mathsf{A l C}_{2}$ MAX Synthesis. The conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ was prepared, synthesized, and acid washed using the same procedure as the Al− $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2};$ however, a 2:1:1 molar ratio of the TiC, Ti, and Al precursor powders was used. \n\nNote about Safety during Acid Washing of MAX Powder. During acid washing of metal-rich MAX powder $(\\mathrm{e.g.,Al{-}T i_{3}A l C_{2}}),$ it is important to note that during the initial stage of the reaction (the first $20\\ \\mathrm{min}$ ) significant amounts of gas will be produced as the intermetallic impurities are dissolved. In order to minimize the rate at which gas is produced and reduce the danger involved in this reaction we recommend taking the following precautions: (1) Perform the acid washing reaction in an ice bath. Once the reaction is no longer bubbling vigorously the ice bath can be removed or the ice can be allowed to melt. (2) Add MAX to the acid washing solution very slowly, at a rate of approximately $_\\textrm{1g}$ per minute. (3) After all MAX has been added to the acid washing solution, monitor the reaction closely for at least $30~\\mathrm{min}$ to ensure no sudden changes in the gas evolution rate occur. (4) At no point during the acid washing process should the reaction vessel be capped, the vessel could potentially pressurize rapidly, leading to an extremely dangerous situation. \n\nMXene Synthesis. Typically, $_{\\textrm{1g}}$ of $\\mathrm{\\bfAl{-}T i_{3}A l C}_{2}$ (or conventional $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2},$ ) was mixed with $20~\\mathrm{mL}$ of etchant and stirred at $400~\\mathrm{rpm}$ for $24\\mathrm{h}$ at $35~^{\\circ}\\mathrm{C}$ . The etchant was a 6:3:1 mixture (by volume) of $12\\mathrm{~M~}$ HCl, DI water, and 50 wt $\\%$ HF (Acros Organics, Fair Lawn, NJ). A loosely capped $60~\\mathrm{mL}$ high density polyethylene bottle was used as the etching container. The etched $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ was washed with DI water via repeated centrifugation and decantation cycles until the supernatant reached $\\mathrm{\\pH}\\sim\\bar{\\epsilon}$ using a $175~\\mathrm{mL}$ centrifuge tube. Once the MXene was neutralized, one more additional wash cycle was performed to ensure the washing process was complete. Five wash cycles using a single $175~\\mathrm{mL}$ centrifuge tube are typically enough for 1 $\\mathbf{g}$ of MAX etched using $20~\\mathrm{mL}$ of etchant. The etched multilayer MXene sediment was then dispersed in a $0.5\\mathrm{~M~}$ solution of LiCl (typically $50~\\mathrm{mL}$ solution per gram of starting MAX) to start the delamination process. The MXene/LiCl suspension was then stirred at $400~\\mathrm{rpm}$ for a minimum of $^{4\\mathrm{~h~}}$ at room temperature. The MXene/ LiCl suspension was then washed with DI water via repeated centrifugation and decantation of the supernatant using a $175~\\mathrm{mL}$ centrifuge tube. The first wash cycle always sediments completely after $3{\\mathrm{-}}5{\\mathrm{~min}}$ of centrifugation at $3500~\\mathrm{rpm}$ . The second wash cycle and onward were centrifuged for $^\\textrm{\\scriptsize1h}$ at $3500~\\mathrm{rpm}$ before the MXene supernatants were collected to ensure the MXene solutions were single flake. The quantity and concentration of the delaminated MXene suspensions produced during each cycle of the delamination process is dependent on the quantity of the MAX that was etched and on the size of the centrifuge tubes used during delamination (SI Figure $S7\\mathrm{a}$ ). The solution concentrations and yield reported in this study are typical for etching $_\\textrm{1g}$ of $_{\\mathrm{Al-Ti_{3}A l C_{2}}}$ in $20~\\mathrm{mL}$ of etchant and using $175\\ \\mathrm{mL}$ centrifuge tubes for delamination. Large, singlelayer $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ flakes ${\\bf\\zeta}>25\\ \\mu\\mathrm{m}$ in the largest dimension, SI Figure $s7\\mathrm{c}$ ) can be readily obtained using this method, but it must be noted that the flake sizes of the $\\mathrm{Al-Ti}_{3}\\mathrm{C}_{2}$ flakes produced are polydisperse, with average flake sizes of 1.3 to $1.6\\ \\mu\\mathrm{m}$ (SI Figure S7b). If a narrow flake size distribution range is desired, then separation of the MAX phase into fractions with narrow distributions of particle sizes and/or density gradient centrifugation of colloidal solutions of MXene can be employed to isolate flakes of the desired size.35 It is important to note that acid washing the $\\mathsf{A l{-}T i}_{3}\\mathsf{A l C}_{2}$ prior to etching is crucial for achieving high stability suspensions as any residual ions from the intermetallic impurities may cause the suspensions to flocculate (SI Figure S13). \n\nPhysical Characterization. Conductivity measurements were performed using a four-point probe with $1\\ \\mathrm{mm}$ probe separation (Jandel Engineering Ltd., Bedfordshire, UK) on freestanding MXene films made by vacuum-assisted filtration of delaminated single flake MXene solutions. The measured sheet resistances of the films were converted into conductivity by using the thickness of the films taken from SEM images of the film cross sections. UV−vis spectra were recorded using an Evolution 201 spectrometer (Thermo Scientific) with a $10~\\mathrm{mm}$ optical path length quartz cuvette and scanning from \n\n200 to $1000\\ \\mathrm{nm},$ , where the absorbance was measured for samples at $100\\times$ dilution. Particle size analysis was performed using a Malvern Panalytical Zetasizer Nano ZS in a polystyrene cuvette. Three measurements were recorded, and the average intensity distribution was reported. For the long-term storage tests, solutions from the third delamination cycle $(700~\\mathrm{mL})$ were used since any excess LiCl would have been removed by that cycle. The concentrations of the stored $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ samples were calculated by measuring the absorbance changes of the samples over time versus the absorbance of the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ samples at the initial time of storage, normalized at $264\\ \\mathrm{nm}$ . A Rigaku SmartLab X-ray diffractometer (Rigaku Corporation, JP) was used to perform XRD analysis on the MAX phase samples that were mixed with 20 wt $\\%$ Si powder (325 mesh, $99.9\\%$ purity, Beantown Chemical Company, NH). $\\mathrm{Cu-K}\\alpha$ radiation was used at $40\\mathrm{~kV}/30$ mA. Diffraction patterns were recorded from $3\\mathrm{-}80^{\\circ}$ with a step size of $0.02^{\\circ}$ with a step duration of $1.5s.$ A Rigaku Miniflex X-ray diffractometer (Rigaku Corporation, JP) was used to perform XRD analysis on the MXene samples. $\\mathrm{Cu-K}\\alpha$ radiation was used at $40\\ensuremath{\\mathrm{\\kV/}}$ $15\\ \\mathrm{mA}.$ Diffraction patterns were recorded from $3\\mathrm{-}80^{\\circ}$ with a step size of $0.02^{\\circ}$ with a step duration of $0.4\\ s.$ . Calculated diffraction patterns were obtained from the Materials Project.36 Raman spectra were recorded using a reflection mode Renishaw InVia dispersive spectrometer (Renishaw plc, Gloucestershire, UK) equipped with $20\\times$ $\\mathrm{^{\\prime}N A}\\ =\\ 0.4\\mathrm{^{\\prime}},$ ) and $63\\times$ $\\mathbf{\\tilde{NA}_{\\lambda}}\\ =\\ 0.7\\mathbf{\\tilde{\\Sigma}}.$ ) objectives and a roomtemperature CCD. For MAX phase analysis, we used an $\\mathbf{A}\\mathbf{r}^{+}$ laser (488 and ${514}~\\mathrm{nm}$ emissions) and an $1800~\\mathrm{line/mm}$ grating, and for analysis of MXene we used a diode $(785~\\mathrm{nm})$ laser with a $\\bar{1200}\\mathrm{line/}$ mm diffraction grating. The power of the lasers was within the ${\\sim}0.3-$ $1~\\mathrm{\\mW}$ range. Transmission electron microscopy and scanning transmission electron microscopy images were taken using a JEOL JEM2100 and JEOL NEOARM (JEOL Ltd., JP), respectively, at an operating voltage of $200~\\mathrm{\\kV}$ . The colloid solution containing delaminated $\\mathrm{\\calAl{-}T i}_{3}\\mathrm{\\calC}_{2}$ flakes was drop-cast onto lacey carbon films on copper TEM grids (Electron Microscopy Sciences, PA). Thermal analysis (TGA) measurements were conducted using an SDT 650 thermal analysis system (TA Instruments, New Castle, DE). Samples were heated at $10~\\mathrm{^{\\circ}C/m i n}$ from room temperature to $1500~^{\\circ}\\mathrm{C}$ under constant flow of compressed dry air at $100\\ \\mathrm{sccm}$ . Samples for thermal analysis were equilibrated overnight in vials exposed to ambient atmosphere. XPS spectra were collected on MAX powder using a PHI VersaProbe 5000 instrument (Physical Electronics, U.S.) with a 200 $\\mu\\mathrm{m}$ and ${50\\mathrm{~W~}}$ monochromatic $\\mathrm{Al-K}_{\\alpha}$ X-ray source. Samples were sputtered for $10~\\mathrm{{min}}$ at $2\\mathrm{kV}.$ , 2uA with $\\mathbf{A}\\mathbf{r}^{+}$ ion beam. Pass energy and step size were set at 23.5 and $0.05\\mathrm{eV}$ , respectively. Quantification and peak fitting were conducted using CasaXPS V2.3.19 Software. \n\n# ASSOCIATED CONTENT \n\n# $\\bullet$ Supporting Information \n\nThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsnano.0c08357. \n\nAdditional XRD patterns, Raman spectroscopy analysis, SEM and TEM images, UV−vis spectra, DLS data, and XPS spectra for the MAX and MXene samples presented in this study (PDF) \n\n# AUTHOR INFORMATION \n\nCorresponding Author Yury Gogotsi − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19143, United States; orcid.org/0000-0001-9423-4032; Email: gogotsi@ drexel.edu \n\n# Authors \n\nTyler S. Mathis − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel \n\nUniversity, Philadelphia, Pennsylvania 19143, United States; orcid.org/0000-0002-1814-0242 \nKathleen Maleski − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19143, United States; $\\circledcirc$ orcid.org/0000-0003-4032-7385 \nAdam Goad − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19143, United States; $\\circledcirc$ orcid.org/0000-0002-5390-6311 \nAsia Sarycheva − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19143, United States \nMark Anayee − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19143, United States; $\\circledcirc$ orcid.org/0000-0002-6691-920X \nAlexandre C. Foucher − Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19143, United States; orcid.org/0000- 0001-5042-4002 \nKanit Hantanasirisakul − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19143, United States; orcid.org/0000-0002-4890-1444 \nChristopher E. Shuck − A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, Pennsylvania 19143, United States; $\\circledcirc$ orcid.org/0000-0002-1274-8484 \nEric A. Stach − Department of Materials Science and Engineering and Laboratory for Research on the Structure of Matter, University of Pennsylvania, Philadelphia, Pennsylvania 19143, United States; $\\circledcirc$ orcid.org/0000- 0002-3366-2153 \n\nComplete contact information is available at: https://pubs.acs.org/10.1021/acsnano.0c08357 \n\n# Author Contributions \n\nT.S.M. conducted synthesis and SEM characterization, K.M. conducted optical characterization, A.G. and A.C.F. conducted TEM studies, A.S. performed Raman analysis, M.A. performed XPS, TGA, and XRD analysis, C.E.S. performed XRD analysis, K.H. performed XRD measurements and assisted in interpreting XPS and TGA results, E.A.S. oversaw TEM analysis and Y.G. supervised the entire study. The manuscript was written through contributions of all authors and all authors have given approval to the final version of the manuscript. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThe synthesis and characterization of MAX and MXene materials performed in this study was supported by the Fluid Interface Reactions, Structures & Transport (FIRST) Center, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences. M.A. was supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1646737. A.C.F. and E.A.S. acknowledge the Vagelos Institute for Energy Science and Technology at the University of Pennsylvania for a graduate fellowship. This work was performed in part at the Singh Center for Nanotechnology at the University of Pennsylvania, a member of the National Nanotechnology Coordinated Infrastructure (NNCI) network, which is supported by the National Science Foundation (Grant No. NNCI-1542153). Additional support for the electron microscopy facilities was provided by the supported by NSF through the University of Pennsylvania Materials Research Science and Engineering Center (MRSEC) (DMR-1720530). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. SEM, XRD, XPS, and TEM analysis were performed using instruments in the Materials Characterization Core at Drexel University. This manuscript was previously submitted to the preprint server ChemRxiv on August 14th, 2020. The preprint version can be found under the following: Mathis, Tyler; Maleski, Kathleen; Goad, Adam; Sarycheva, Asia; Anayee, Mark; Foucher, Alexandre C.; Hantanasirisakul, Kanit; Stach, Eric A.; Gogotsi, Yury. (2020): Modified MAX Phase Synthesis for Environmentally Stable and Highly Conductive $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene. ChemRxiv. Preprint. 10.26434/ chemrxiv.12805280.v1 \n\n# REFERENCES \n\n(1) Nicolosi, V.; Chhowalla, M.; Kanatzidis, M. G.; Strano, M. S.; \nColeman, J. N. Liquid Exfoliation of Layered Materials. Science 2013, \n340 (6139), 1226419. (2) Anasori, B.; Gogotsi, Y. 2D Metal Carbides and Nitrides \n(MXenes).; Springer International Publishing: Cham, Switzerland, \n2019. (3) Han, M.; Shuck, C. E.; Rakhmanov, R.; Parchment, D.; Anasori, \nB.; Koo, C. M.; Friedman, G.; Gogotsi, Y. Beyond $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ : MXenes \nfor Electromagnetic Interference Shielding. ACS Nano 2020, 14 (4), \n5008−5016. (4) Anasori, B.; Lukatskaya, M. R.; Gogotsi, Y. 2D Metal Carbides \nand Nitrides (MXenes) for Energy Storage. Nature Reviews Materials \n2017, 2 (2), 16098. \n(5) Gogotsi, Y.; Anasori, B. The Rise of MXenes. ACS Nano 2019, \n13 (8), 8491−8494. (6) Anayee, M.; Kurra, N.; Alhabeb, M.; Seredych, M.; Hedhili, M. \nN.; Emwas, A.-H.; Alshareef, H. N.; Anasori, B.; Gogotsi, Y. Role of \nAcid Mixtures Etching on the Surface Chemistry and Sodium Ion \nStorage in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene. Chem. Commun. 2020, 56, 6090−6093. (7) Hantanasirisakul, ${\\mathrm{K}}.{\\mathrm{}}$ Alhabeb, M.; Lipatov, A.; Maleski, K.; \nAnasori, B.; Salles, P.; Ieosakulrat, C.; Pakawatpanurut, P.; Sinitskii, \nA.; May, S. J.; Gogotsi, Y. Effects of Synthesis and Processing on \nOptoelectronic Properties of Titanium Carbonitride MXene. Chem. \nMater. 2019, 31 (8), 2941−2951. (8) Li, Y.; Shao, H.; Lin, Z.; Lu, J.; Liu, L.; Duployer, B.; Persson, P. \nO. Å.; Eklund, P.; Hultman, L.; Li, M.; Chen, K.; Zha, X.-H.; Du, S.; \nRozier, P.; Chai, Z.; Raymundo-Piñero, E.; Taberna, P.-L.; Simon, P.; \nHuang, $\\mathsf{Q}.$ A General Lewis Acidic Etching Route for Preparing \nMXenes with Enhanced Electrochemical Performance in Non \nAqueous Electrolyte. Nat. Mater. 2020, 19 (8), 894−899. (9) Alhabeb, M.; Maleski, ${\\mathrm{K}}.{\\mathrm{}}$ Anasori, B.; Lelyukh, P.; Clark, L.; Sin, \nS.; Gogotsi, Y. Guidelines for Synthesis and Processing of Two \nDimensional Titanium Carbide $\\mathrm{\\Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene). Chem. Mater. \n2017, 29 (18), 7633−7644. (10) Huang, S.; Mochalin, V. N. Hydrolysis of 2D Transition-Metal \nCarbides (MXenes) in Colloidal Solutions. Inorg. Chem. 2019, 58 (3), \n1958−1966. \n(11) Chae, Y.; Kim, S. J.; Cho, S.-Y.; Choi, J.; Maleski, K.; Lee, B.-J.; \nJung, H.-T.; Gogotsi, Y.; Lee, Y.; Ahn, C. W. An Investigation into the \nFactors Governing the Oxidation of Two-Dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene. \nNanoscale 2019, 11 (17), 8387−8393. (12) Lipatov, A.; Alhabeb, M.; Lukatskaya, M. R.; Boson, A.; \nGogotsi, Y.; Sinitskii, A. Effect of Synthesis on Quality, Electronic Properties and Environmental Stability of Individual Monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene Flakes. Advanced Electronic Materials 2016, 2 (12), 1600255. (13) Zhang, C. J.; Pinilla, S.; McEvoy, $\\mathrm{N}.\\mathrm{\\Omega}$ Cullen, C. P.; Anasori, B.; Long, E.; Park, S.-H.; Seral-Ascaso, A.; Shmeliov, A.; Krishnan, D.; Morant, C.; Liu, X.; Duesberg, G. S.; Gogotsi, Y.; Nicolosi, V. Oxidation Stability of Colloidal Two-Dimensional Titanium Carbides (MXenes). Chem. Mater. 2017, 29 (11), 4848−4856. \n(14) Zhao, X.; Vashisth, A.; Prehn, E.; Sun, W.; Shah, S. A.; Habib, T.; Chen, Y.; Tan, Z.; Lutkenhaus, J. L.; Radovic, M.; Green, M. J. Antioxidants Unlock Shelf-Stable $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ (MXene) Nanosheet Dispersions. Matter 2019, 1 (2), 513−526. \n(15) Huang, S.; Mochalin, V. N. Understanding Chemistry of TwoDimensional Transition Metal Carbides and Carbonitrides (MXenes) with Gas Analysis. ACS Nano 2020, 14 (8), 10251−10257. \n(16) Habib, T.; Zhao, X.; Shah, S. A.; Chen, Y.; Sun, W.; An, H.; Lutkenhaus, J. L.; Radovic, M.; Green, M. J. Oxidation Stability of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene Nanosheets in Solvents and Composite Films. npj 2D Materials and Applications 2019, 3 (1), 8. \n(17) Shuck, C. E.; Han, M.; Maleski, K.; Hantanasirisakul, ${\\mathrm{K}}.{\\mathrm{}}$ Kim, S. J.; Choi, J.; Reil, W. E. B.; Gogotsi, Y. Effect of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX Phase on Structure and Properties of Resultant ${\\mathrm{Ti}}_{3}{\\mathrm{C}}_{2}{\\mathrm{T}}_{x}$ MXene. ACS Applied Nano Materials 2019, 2 (6), 3368−3376. \n(18) Etzkorn, J.; Ade, M.; Hillebrecht, H. $\\mathrm{Ta}_{3}\\mathrm{AlC}_{2}$ and $\\mathrm{Ta}_{4}\\mathrm{AlC}_{3}$ - Single-Crystal Investigations of Two New Ternary Carbides of Tantalum Synthesized by the Molten Metal Technique. Inorg. Chem. 2007, 46 (4), 1410−1418. \n(19) Tzenov, N. V.; Barsoum, M. W. Synthesis and Characterization of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . J. Am. Ceram. Soc. 2000, 83 (4), 825−832. \n(20) Presser, V.; Naguib, M.; Chaput, L.; Togo, A.; Hug, G.; Barsoum, M. W. First-Order Raman Scattering of the MAX Phases: $\\mathrm{Ti}_{2}\\mathrm{AlN}.$ , $\\mathrm{Ti}_{2}\\mathrm{AlC}_{0.5}\\mathrm{N}_{0.5},$ ${\\mathrm{Ti}}_{2}{\\mathrm{AlC}},$ $(\\mathrm{Ti}_{0.5}\\mathrm{V}_{0.5})_{2}\\mathrm{AlC}$ , ${\\mathrm{V}}_{2}{\\mathrm{AlC}}_{3}$ ${\\mathrm{Ti}}_{3}{\\mathrm{AlC}}_{2},$ and $\\mathrm{Ti}_{3}\\mathrm{GeC}_{2}$ . J. Raman Spectrosc. 2012, 43 (1), 168−172. \n(21) Sarycheva, $\\mathrm{A}.;$ Gogotsi, Y. Raman Spectroscopy Analysis of the Structure and Surface Chemistry of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ MXene. Chem. Mater. 2020, 32 (8), 3480−3488. \n(22) Ghidiu, M.; Kota, S.; Drozd, V.; Barsoum, M. W. PressureInduced Shear and Interlayer Expansion in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene in the Presence of Water. Science Advances 2018, 4 (1), No. eaao6850. (23) Shekhirev, M.; Shuck, C. E.; Sarycheva, A.; Gogotsi, Y. Characterization of MXenes at Every Step, from Their Precursors to Single Flakes and Assembled Films. Prog. Mater. Sci. 2020, 100757. (24) Sun, Y.; Zhan, C.; Kent, P. R. C.; Naguib, M.; Gogotsi, Y.; Jiang, D.-e. Proton Redox and Transport in MXene-Confined Water. ACS Appl. Mater. Interfaces 2020, 12 (1), 763−770. \n(25) Zhang, C.; Anasori, B.; Seral-Ascaso, A.; Park, S.-H.; McEvoy, N.; Shmeliov, A.; Duesberg, G. S.; Coleman, J. N.; Gogotsi, Y.; Nicolosi, V. Transparent, Flexible, and Conductive 2D Titanium Carbide (MXene) Films with High Volumetric Capacitance. Adv. Mater. 2017, 29 (36), 1702678. \n(26) Zhang, J.; Kong, N.; Uzun, S.; Levitt, A.; Seyedin, S.; Lynch, P. A.; Qin, S.; Han, M.; Yang, W.; Liu, J.; Wang, X.; Gogotsi, Y.; Razal, J. M. Scalable Manufacturing of Free-Standing, Strong $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\it x}$ MXene Films with Outstanding Conductivity. Adv. Mater. 2020, 32 (23), 2001093. \n(27) Mirkhani, S. A.; Shayesteh Zeraati, A.; Aliabadian, E.; Naguib, M.; Sundararaj, U. High Dielectric Constant and Low Dielectric Loss via Poly(Vinyl Alcohol) $\\mathrm{\\mathop{Ti}}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene Nanocomposites. ACS Appl. Mater. Interfaces 2019, 11 (20), 18599−18608. \n(28) Li, Z.; Wang, L.; Sun, D.; Zhang, Y.; Liu, B.; Hu, Q.; Zhou, A. Synthesis and Thermal Stability of Two-Dimensional Carbide MXene $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ . Mater. Sci. Eng., B 2015, 191, 33−40. \n(29) Salles, P.; Pinto, D.; Hantanasirisakul, K.; Maleski, K.; Shuck, C. E.; Gogotsi, Y. Electrochromic Effect in Titanium Carbide MXene Thin Films Produced by Dip-Coating. Adv. Funct. Mater. 2019, 29 (17), 1809223. \n(30) Natu, V.; Sokol, M.; Verger, L.; Barsoum, M. W. Effect of Edge Charges on Stability and Aggregation of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{z}$ MXene Colloidal Suspensions. J. Phys. Chem. C 2018, 122 (48), 27745−27753. (31) Zhang, J.; Kong, N.; Hegh, D.; Usman, K. A. S.; Guan, G.; Qin, S.; Jurewicz, I.; Yang, W.; Razal, J. M. Freezing Titanium Carbide Aqueous Dispersions for Ultra-Long-Term Storage. ACS Appl. Mater. Interfaces 2020, 12 (30), 34032−34040. \n(32) Meng, Z.; Wang, C.; Liu, J.; Wang, Y.; Zhu, X.; Yang, L.; Huang, L. New Insight into the Interaction between Divacancy and H/He Impurity in $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ Using First-Principles Studies. Phys. Chem. Chem. Phys. 2020, 22 (32), 18040−18049. \n(33) Etzkorn, J.; Ade, M.; Hillebrecht, H. $\\mathrm{V}_{2}\\mathrm{AlC}$ , $\\mathrm{V}_{4}\\mathrm{AlC}_{3-x}$ $\\mathbf{\\Deltax}\\approx$ 0.31), and $\\mathrm{V}_{12}\\mathrm{Al}_{3}\\mathrm{C}_{8}$ : Synthesis, Crystal Growth, Structure, and Superstructure. Inorg. Chem. 2007, 46 (18), 7646−7653. \n(34) Wang, D.; Si, J.; Lin, S.; Zhang, R.; Huang, Y.; Yang, J.; Lu, W.; Zhu, X.; Sun, Y. Achieving Macroscopic $\\mathrm{V}_{4}\\mathrm{C}_{3}\\mathrm{T}_{x}$ MXene by Selectively Etching Al from $\\mathrm{V}_{4}\\mathrm{AlC}_{3}$ Single Crystals. Inorg. Chem. 2020, 59 (5), 3239−3248. \n(35) Maleski, K.; Ren, C. E.; Zhao, ${\\bf{M.}}{\\bf{Q.}};$ Anasori, B.; Gogotsi, Y. Size-Dependent Physical and Electrochemical Properties of TwoDimensional MXene Flakes. ACS Appl. Mater. Interfaces 2018, 10 (29), 24491−24498. \n(36) Jain, A.; Ong, S. P.; Hautier, G.; Chen, W.; Richards, W. D.; Dacek, S.; Cholia, S.; Gunter, D.; Skinner, D.; Ceder, G.; Persson, K. A. Commentary: The Materials Project: A Materials Genome Approach to Accelerating Materials Innovation. APL Mater. 2013, 1 (1), 011002. " + }, + { + "id": "10.1038_s41467-021-24828-9", + "DOI": "10.1038/s41467-021-24828-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-24828-9", + "Relative Dir Path": "mds/10.1038_s41467-021-24828-9", + "Article Title": "Engineering single-atomic ruthenium catalytic sites on defective nickel-iron layered double hydroxide for overall water splitting", + "Authors": "Zhai, PL; Xia, MY; Wu, YZ; Zhang, GH; Gao, JF; Zhang, B; Cao, SY; Zhang, YT; Li, ZW; Fan, ZZ; Wang, C; Zhang, XM; Miller, JT; Sun, LC; Hou, JG", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Rational design of single atom catalyst is critical for efficient sustainable energy conversion. However, the atomic-level control of active sites is essential for electrocatalytic materials in alkaline electrolyte. Moreover, well-defined surface structures lead to in-depth understanding of catalytic mechanisms. Herein, we report a single-atomic-site ruthenium stabilized on defective nickel-iron layered double hydroxide nullosheets (Ru-1/D-NiFe LDH). Under precise regulation of local coordination environments of catalytically active sites and the existence of the defects, Ru-1/D-NiFe LDH delivers an ultralow overpotential of 18mV at 10mAcm(-2) for hydrogen evolution reaction, surpassing the commercial Pt/C catalyst. Density functional theory calculations reveal that Ru-1/D-NiFe LDH optimizes the adsorption energies of intermediates for hydrogen evolution reaction and promotes the O-O coupling at a Ru-O active site for oxygen evolution reaction. The Ru-1/D-NiFe LDH as an ideal model reveals superior water splitting performance with potential for the development of promising water-alkali electrocatalysts. Rational design of single atom catalyst is critical for efficient sustainable energy conversion. Single-atomic-site ruthenium stabilized on defective nickel-iron layered double hydroxide nullosheets achieve superior HER and OER performance in alkaline media.", + "Times Cited, WoS Core": 577, + "Times Cited, All Databases": 597, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000680875400015", + "Markdown": "# Engineering single-atomic ruthenium catalytic sites on defective nickel-iron layered double hydroxide for overall water splitting \n\nPanlong Zhai1,6, Mingyue Xia2,6, Yunzhen Wu1,6, Guanghui Zhang $\\textcircled{1}$ 1, Junfeng Gao2, Bo Zhang1, Shuyan Cao1, Yanting Zhang1, Zhuwei Li1, Zhaozhong Fan1, Chen Wang1, Xiaomeng Zhang1, Jeffrey T. Miller3, Licheng Sun 1,4,5 & Jungang Hou 1✉ \n\nRational design of single atom catalyst is critical for efficient sustainable energy conversion. However, the atomic-level control of active sites is essential for electrocatalytic materials in alkaline electrolyte. Moreover, well-defined surface structures lead to in-depth understanding of catalytic mechanisms. Herein, we report a single-atomic-site ruthenium stabilized on defective nickel-iron layered double hydroxide nanosheets $.R u\\mathcal{N}D$ -NiFe LDH). Under precise regulation of local coordination environments of catalytically active sites and the existence of the defects, Ru1/D-NiFe LDH delivers an ultralow overpotential of $18\\mathsf{m V}$ at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ for hydrogen evolution reaction, surpassing the commercial Pt/C catalyst. Density functional theory calculations reveal that ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH optimizes the adsorption energies of intermediates for hydrogen evolution reaction and promotes the O–O coupling at a $\\mathsf{R u-O}$ active site for oxygen evolution reaction. The ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH as an ideal model reveals superior water splitting performance with potential for the development of promising water-alkali electrocatalysts. \n\nH ydidtriognealn aos ai fusetlasintaoblemietingeartgeyeinsviarnonalmterntatl vpe otob etrmasfrom greenhouse gases1,2. Electrochemical water-splitting has been developed as an effective way to generate hydrogen fuel by use of electrocatalysts. At present, $\\mathrm{Pt^{.}}$ and $\\mathrm{{Ir/Ru}}$ -oxide-based catalysts are the benchmark materials for hydrogen evolution reaction (HER) and oxygen evolution reaction $(\\mathrm{OER})^{3-6}$ . However, their high cost and poor stability limit large-scale utilization. Thus, it is crucial to fabricate highly efficient catalysts for electrocatalytic applications. \n\nAmong various materials, $3d$ transition-metal-based layered double hydroxides (LDHs) containing different metals (e.g., Co, Ni, Fe, etc.) are promising electrocatalysts due to the unique lamellar structure and abundant active sites7–9. For example, LDHs based on Fe, Co, Ni, Zn, and Mn have been widely investigated for $\\mathrm{OER^{10-16}}$ . NiFe, NiV, and CoFe LDHs give superior OER activities in our group17–19. To optimize the catalytic activity of LDHs, different strategies have been developed through the regulation of morphology, defect formation, charge transfer, etc.,20–23. With regard to defect engineering, it is an effective approach to modulate catalytic performance. For instance, oxygen vacancies in $\\mathrm{Co}_{3}\\mathrm{O}_{4},$ sulfur vacancies in $\\ensuremath{\\mathrm{MoS}}_{2}$ and Fe vacancies in $\\delta\\mathrm{-}\\mathrm{FeOOH}$ have been produced24–28, optimizing the electrocatalytic activity. However, it is still a challenge to control the structure of active sites in LDHs by defect engineering and develop a correlation between the defects and electrocatalytic performance. \n\nSingle atom catalysts (SACs) have emerged as a promising frontier to optimize the catalytic performance, sparking widespread interest by virtue of the appropriate coordination environment, intimate interactions of single atoms with proper supports, and quantum size effects5,6,29–32. Often, it is difficult to produce SACs due to facile aggregation of individual metal atoms. Interestingly, two-dimensional (2D) LDHs provide a favorable platform for the stabilization of SACs due to 2D flat facet, ultrathin thickness and high surface area29,30. In this regard, single atoms anchored 2D LDHs is an ideal model to maximize the OER activity, while simultaneously decreasing the content of single atoms on the support. These sites also offer a useful platform for in-depth understanding of the catalytic mechanism at an atomic level29–32. However, HER performance of various LDHs catalysts is rather poor owing to the large energy barrier and sluggish water dissociation kinetics in alkaline media30–32. Specifically, it is a challenge to stabilize single atoms on LDHs for water oxidation and reduction in the same alkaline electrolyte. Although various strategies, such as pyrolysis, wet chemistry, atomic layer deposition, etc., have been extensively explored to produce SACs with tailored requirements33–35, there is still no simple large-scale synthesis protocol to produce single atoms stabilized on the supports. There is a promising approach to boost the catalytic activity by the introduction of defects into the support, stabilizing single atoms due to the intimate interaction of the resulting structure36–38. Combining defect engineering and single atoms supported 2D LDHs, it is possible to rationally design the atomically dispersed, active single atoms stabilized on defective LDH supports for extraordinary overall water splitting performance in alkaline electrolyte. \n\n![](images/ccd4239d0c3a3ea46e285501fd9e46628b32ddb78de457d3df67eba81c483cab.jpg) \nFig. 1 Schematic representation of synthesis and morphological characterizations. a Synthesis illustration and b SEM image, d TEM image, e SAED pattern, and g aberration-corrected TEM image of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH (isolated Ru atoms are marked with yellow circles), (cf) elemental mapping of c HAADF-STEM and f aberration-corrected TEM images of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH. Scale bar, b $1\\upmu\\mathrm{m}$ , d $1200\\mathsf{n m}$ , and g 1 nm. \n\nIn this work, a single-atomic-site ruthenium catalyst stabilized on defective NiFe-LDH is synthesized by a simple electrodeposition and subsequent etching procedure as the straightforward and practical approach. The combined analysis of spherical aberration-corrected transmission electron microscope and X-ray absorption fine structure (XAFS) spectroscopy reveals the existence of Ru single atoms and in-depth local atomic structures of Ni, Fe, and Ru sites. Although Ru and NiFe-LDH have been regarded to be active OER catalysts29,30, as-synthesized $\\mathrm{{Ru}_{1}/D}$ - NiFe LDH achieves a current density of $\\mathrm{i}0\\mathrm{mA}\\mathrm{cm}^{-2}$ at an ultralow overpotential of $18\\mathrm{mV}$ and a high turnover frequency of $7.66\\ s^{-1}$ at an overpotential of $100\\mathrm{mV}$ (45 times higher than that of commercial $\\mathrm{Pt/C}$ catalyst) for HER. Inspired by the superior HER and OER performances, the assembled two-electrode cell by $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH reaches an industrial current density of 500 $\\operatorname{mA}\\thinspace{\\mathrm{cm}}^{-2}$ at a low cell voltage of $1.72\\mathrm{V}$ for overall water splitting in alkaline media. Density functional theory (DFT) calculations suggest that $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH optimizes the favorable regulation of H adsorption energies for HER, and promotes the $0{-}\\mathrm{\\bar{O}}$ coupling due to the existence of $\\mathrm{{Ru-O}}$ moieties. Moreover, the abundant number of active sites accelerate the water splitting kinetics, thus enhancing the intrinsic HER and OER activities. This work also establishes a promising platform for future fundamental studies into the role of isolated Ru single atoms on defective NiFe LDH nanosheets in promoting electrocatalytic performance. \n\n# Results \n\nSynthesis and characterization. A single-atomic-site ruthenium catalyst stabilized on defective NiFe LDH (denoted as $\\mathrm{{Ru}_{1}/D}$ - NiFe LDH) supported on three-dimensional (3D) skeleton of nickel foam was synthesized by a facile electrodeposition and subsequent etching approach as depicted schematically in Fig. 1a. Notably, the synthetic approach was completed at room temperature and atmospheric pressure without harsh operations. Ru single atoms stabilized on NiFeAl LDH nanosheets $\\mathrm{\\langleRu_{1}/N i F e A l}$ LDH) were deposited onto the 3D conductive substrate by a simple electrodeposition procedure. Then, as-synthesized $\\mathrm{Ru}_{\\mathrm{1}}/$ NiFeAl LDH nanosheets were etched in alkali media, removing Al from $\\mathrm{Ru_{1}/N i F e A l}$ precursor and thus resulting into the formation of Ru single atoms integrated with defective NiFe LDH nanosheets by the precise regulation of the etching time and the content of Ru single atoms. \n\nTo shed light on the crystalline structure, X-ray diffraction (XRD) patterns verify that only a set of interplanar angles located at $44.5^{\\circ}$ , $51.8^{\\circ}$ , and $76.4^{\\circ}$ (Supplementary Fig. 1), assigned to (111), (200), and (220) planes of metallic nickel (JCPDS 04-0850), respectively, indicating the amorphous nature of NiFe LDH and $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH nanosheets. \n\nTo identify the form of Ru single atoms dispersed on D-NiFe LDH supports, field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and spherical aberration-corrected atomic resolution HAADF-STEM were used. As shown in Fig. 1b, SEM image of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH shows uniform interconnected nanosheets with a smooth surface vertically grown on 3D foam. For comparison, NiFe LDH and $\\mathrm{Ru}_{1}$ /NiFeAl LDH nanosheets were synthesized by electrodeposition, while Ru-doped NiFe LDH (denoted as NiFeRu LDH) nanosheets were prepared by hydrothermal synthesis (Supplementary Fig. 2). Based on the electrodeposition and subsequent etching treatment for various times, the typical morphological nanostructures of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH are 2D nanosheets after $24\\mathrm{h}$ etching treatment (Supplementary Fig. 3). TEM image in Fig. 1d confirms 2D nanosheets structure of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH. The selected-area electron diffraction (SAED) pattern of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH is presented in Fig. 1e, indicating the amorphous nature with the halo-like diffraction pattern consistent with XRD. From spherical aberration corrected HAADF-STEM image, isolated Ru single atoms as bright spots are homogeneously distributed on the surface of $\\mathrm{Ru_{\\mathrm{1}}/}$ D-NiFe LDH nanosheets without any apparent nanoparticles or clusters, demonstrating the successful synthesis of single-atom electrocatalyst. The elemental mappings of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH are determined by HAADF-STEM and spherical aberration corrected TEM images (Fig. 1c, f), revealing the existence of Ni, Fe, Ru, and O elements and the homogeneous distribution of Ru single atoms on 2D nanosheets. SEM and TEM images, element mapping and energy-dispersive X-ray (EDX) analysis of different arrays were also conducted (Supplementary Figs. 3–10). The Ru content (1.2 $\\mathrm{{wt\\%}}$ ) of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH is determined by inductively coupled plasma optical emission spectrometry (ICP-OES) analysis. The atomic force microscopy (AFM) was performed to characterize the average thickness about $4.2\\mathrm{nm}$ for the nanosheets (Supplementary Fig. 11). These results demonstrate that Ru single atoms stabilized on defective NiFe LDH nanosheets have been synthesized by the facile electrodeposition and subsequent etching procedure. \n\nTo unravel the chemical composition and electronic properties of the electrocatalysts, X-ray photoelectron spectroscopy (XPS) was conducted (Supplementary Fig. 12). For $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, the peaks located at 856.2 and $874.0\\mathrm{eV}$ with two shakeup satellites are assigned to $\\mathrm{Ni}2p_{3/2}$ and Ni $2{p}_{1/2}$ , indicating the $\\mathrm{Ni}^{2\\dot{+}}$ oxidation state in $\\mathrm{{Ru}_{1}/D}$ -NiFe $\\mathrm{LDH}^{\\mathrm{11},2\\hat{3}}$ . The core-level Fe $2p$ XPS spectrum of $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH displays the typical peaks at 712.1 and $725.7\\mathrm{eV}$ , which can be indexed to Fe $2p_{3/2}$ and Fe $2p_{1/2}$ of $\\mathrm{Fe}^{3+9,21}$ . In comparison of NiFe LDH, there are the positive shifts of 0.5 and $0.3\\mathrm{eV}$ in $\\mathrm{\\DeltaNi}$ and Fe XPS of $\\mathrm{Ru_{1}/N i F e}$ LDH and $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, respectively, indicating the electronic coupling of Ru single atoms and D-NiFe $\\mathrm{LDH}^{3,1\\breve{3}}$ . In Ru $3p$ spectra, the peaks of Ru $3p_{3/2}$ and Ru $3p_{1/2}$ are located at 463.8 and $486.2\\:\\mathrm{eV}$ , intermediate between $\\mathtt{R u}$ (0) and Ru (IV)39. O 1s XPS core-level spectra can be divided into three spin–orbit peaks. The O 1s signals located at 530.3, 531.6, and $532.4\\mathrm{eV}$ are assigned to metal–oxygen bond (M–O), vacancy with low oxygen coordination and adsorbed hydroxy or $\\mathrm{H}_{2}\\mathrm{O}$ , respectively39. Moreover, a positive shift is observed in O 1s XPS of ${\\mathrm{Ru}_{1}}/{\\mathrm{NiFe}}$ LDH and $\\mathrm{Ru}_{1}/$ D-NiFe LDH in comparison of NiFe LDH (Supplementary Fig. 12), indicating that $\\mathtt{R u}$ atom coordinates with $\\mathrm{~O~}$ atoms through an intimate interaction between Ru single atoms and defective NiFe LDH support. \n\nTo determine the valance states and local coordination structures of $\\mathrm{{Ru_{1}}/\\mathrm{{D}}}$ -NiFe LDH at the atomic level, X-ray absorption near-edge structure (XANES) spectroscopy and extended X-ray absorption fine structure (EXAFS) spectroscopy were performed. The Ru K-edge XANES spectra of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH in Fig. 2a shows that the edge energy is between Ru foil and $\\mathrm{RuO}_{2}$ , demonstrating a cationic environment. In the Fouriertransform EXAFS (FT-EXAFS) spectra in Fig. 2d, $\\mathrm{{Ru_{\\mathrm{1}}}/\\mathrm{{D}}}$ -NiFe LDH has a first shell $\\mathrm{{Ru-O}}$ peak at $1.56\\mathring{\\mathrm{A}}$ (phase uncorrected distance) and a weak $\\operatorname{Ru-O-M}$ ( $\\mathbf{M}=\\mathbf{Ni}$ or Fe) in the higher shells. Compared to Ru foil and ${\\mathrm{RuO}}_{2}$ , there is no characteristic peak for Ru–Ru scattering in $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, which is consistent with the analysis of aberration-corrected TEM image of atomically dispersed Ru atoms on 2D LDH nanosheets29,40. The analysis of coordination configuration was conducted by model-based EXAFS fitting. The coordination number of $\\mathrm{{Ru-O}}$ in first coordination sphere of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe-LDH is estimated to be 3.7, implying the existence of coordinatively unsaturated $\\mathrm{RuO}_{4}$ sites (Supplementary Table 1 and Supplementary Figs. 13 and 14). XANES simulation on $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe-LDH presents that the white line and post-edge features are well reproduced in experimental and simulated spectra (Supplementary Fig. 15). All above results indicate that atomically dispersed Ru is successfully immobilized on D-NiFe LDH nanosheets by coordianting with O atoms. As shown in the Fe K-edge XANES spectra in Fig. 2b, a pre-edge energy of $7114.8\\mathrm{eV}$ for $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH, identical to that of ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3},$ suggests the presence of $\\mathrm{Fe}^{3+}$ , which is in agreement with the XPS analysis. A slightly higher pre-edge intensity than that of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ likely indicates a distorted octahedral coordination geometry of the $\\mathrm{Fe}^{3+}$ sites in $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe $\\mathrm{LDH^{41}}$ . The R-space shows two prominent coordination peaks at 1.44 and $2.{\\dot{5}}8{\\dot{\\mathrm{A}}}$ (phase uncorrected distance), which can be assigned to the Fe–O peak and Fe–Ni/Fe peak. Moreover, the average Fe–Ni/Fe distance in $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH is slightly shorter than that of NiFe LDH, indicating the presence of coordinatively unsaturated sites and structure distortion around Fe center40,41. As for Ni Kedge, the pre-edge peak of $\\mathrm{{Ru_{1}}/\\mathrm{{D}}}$ -NiFe LDH $(8333.4\\mathrm{eV})$ is similar to that of the NiO reference (Fig. 2), indicating the presense of $\\mathrm{Ni}^{2+}$ , which is in accordance with the analysis of XPS spectra. The similar change of Ni or Fe EXAFS was obtained with the precense of abundant metal defect sites in $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH nanosheets26,42,43. Based on the EXAFS analysis, the abundant number of defects in the LDH nanosheets could play an important role in stabilizing Ru atoms on LDH support. \n\n![](images/9af2fd0ac315df127bd9a6af6f594f96e661286c1cfaef883c5e21ba990bb022.jpg) \nFig. 2 X-ray absorption spectroscopy characterizations. a XANES spectra at Ru K-edge of ${\\sf R u}_{\\mathcal{V}}\\ D$ -NiFe LDH, Ru foil, and ${\\mathsf{R u O}}_{2}$ . b XANES spectra at Fe K-edge of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH, Fe foil, and $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ . c XANES spectra at Ni K-edge of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH, Ni foil, and NiO. d–f Fourier-transform EXAFS spectra from a–c. \n\nElectrocatalytic performance for HER. Owing to the kinetically sluggish electrocatalytic HER by NiFe LDH, it is important to optimize the HER activity. The electrocatalytic HER performance of all electrocatalysts by linear sweep voltammetry (LSV) was evaluated using a typical three-electrode system in nitrogensaturated $1\\mathrm{M}\\mathrm{KOH}$ electrolyte. As shown in Fig. 3a, b, $\\mathrm{{Ru}_{1}/D}$ - NiFe LDH with only $1.2\\mathrm{wt\\%}$ of Ru single atoms has the catalytically most active polarization curve with a near zero onset potential. $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH delivers the overpotentials of 18 and $61\\mathrm{mV}$ to reach the current densities of 10 and $100\\mathrm{mA}\\mathrm{cm}^{-2}$ which are lower than the benchmark catalysts, 33 and $90\\mathrm{mV}$ for $\\mathrm{Pt/C}$ catalyst, and 272 and $371\\mathrm{mV}$ for NiFe LDH, indicating that \n\nRu single atoms stabilized on D-NiFe LDH nanosheets can significantly improve the electrocatalytic performance. In comparison to $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, the HER electrocatalytic activities of $\\mathtt{R u}$ single atoms supported on NiFe LDH ( $\\mathrm{Ru_{1}}/\\mathrm{NiFe}$ LDH), NiFeAl LDH ( $\\mathrm{Ru}_{1}$ /NiFeAl LDH) and defective NiFe LDH (D-NiFe LDH) are low (Supplementary Fig. 16), highlighting the important role of the defects and Ru single atoms on NiFe LDH surface. The difference between $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH and ${\\mathrm{Ru_{1}}}/{\\mathrm{NiFe}}$ LDH suggests that defect-rich NiFe LDH has a stronger interaction with Ru single atoms than NiFe LDH, leading to a significant enhancement in the HER performance. By tuning the etching time and the amount of Ru single atoms in $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, the catalytic performance can be optimized (Supplementary Fig. 17). Tafel plots were derived from the polarization curves to capture deeper insight of the electrochemical reaction kinetics (Fig. 3c). The Tafel slope of $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH is as low as $29\\mathrm{mV}\\mathrm{{\\bar{dec}^{-1}}}$ , which is lower than those of $\\mathrm{Ru_{1}/N i F e}$ LDH $(36\\mathrm{mV}\\mathrm{dec}^{-1}),$ and NiFe LDH $(101\\mathrm{mV}\\mathrm{dec}^{-1},$ , indicating that the reaction pathways follow the Volmer–Tafel mechanism and the chemical recombination of adsorbed $\\mathrm{~H~}$ is the rate-determining step35. Moreover, the exchange current density $(j_{0})$ determined by extrapolating the Tafel plot of $\\mathrm{{Ru}_{1}/D}$ NiFe LDH is estimated at $2.{\\dot{6}}\\operatorname*{mA}\\operatorname{cm}^{-2}$ (Supplementary Fig. 18), which is better than those of other catalysts, revealing the excellent inherent electrocatalytic activity. With regard to low overpotential and Tafel slope, the apparent merits of $\\mathrm{{Ru_{\\mathrm{1}}}/\\mathrm{{D}}}$ -NiFe LDH are significantly better than those reported for commercial $\\mathrm{Pt/C}$ and most HER catalysts (Fig. 3d and Supplementary Table 2). Interestingly, an impressive mass activity, $\\mathrm{\\dot{1}4,650\\ A\\dot{g}_{m e t a l}}^{-1}$ of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH was achieved at the overpotential of $100\\mathrm{mV}$ , which is ${\\sim}7\\$ times higher than that of ${\\mathrm{Ru_{1}}}/{\\mathrm{NiFe}}$ LDH $(2420\\mathrm{Ag}_{\\mathrm{metal}}-1\\cdot$ ), and ${\\sim}45$ times higher than that of the $\\mathrm{Pt/C}$ catalyst $(32\\bar{0}\\mathrm{Ag_{metal}}^{-1}),$ ). The turnover frequency (TOF) was calculated (Fig. 3e), assuming all $\\mathtt{R u}$ are presented as active sites to quantify the catalytic efficiency. The TOF of ${\\mathrm{Ru}}_{1}/{\\mathrm{D}}.$ NiFe LDH is $\\bar{7.66~s^{-1}}$ at the overpotential of $100\\mathrm{mV}$ , which is ${\\sim}6$ times higher than that of ${\\mathrm{Ru_{1}}}/{\\mathrm{NiFe}}$ LDH $(1.27s^{-1})$ ), and ${\\sim}24$ times higher than that of $\\mathrm{Pt/C}$ catalyst $(0.32s^{-1})$ as well as higher than those of most reported catalysts (Supplementary Table 3), implying the highly efficient utilization of $\\mathtt{R u}$ single atoms on defective LDH support. To evaluate the active surface area of the electrocatalysts, the electrochemical surfaces areas (ECSA) were obtained by double-layer capacitance $(C_{\\mathrm{dl}})$ in non-Faradaic potential region22–35. $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH has the highest $C_{\\mathrm{dl}}$ value of $32.{\\overset{\\cdot}{6}}\\operatorname*{mF}{\\mathrm{cm}}^{-2}$ , which is 1.9- and 7.1-fold times higher than those of $\\mathtt{R u}$ /NiFe LDH and NiFe LDH, respectively (Fig. 3f and Supplementary Fig. 19). Especially, the current densities of NiFe LDH, $\\mathrm{Ru_{1}/N i F e}$ LDH, $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, and commercial $\\mathrm{Pt/C}$ were normalized to ECSA (Fig. $3\\mathrm{g}$ and Supplementary Figs. 20, 21), demonstrating the highest instrinsic activity of $\\mathrm{Ru}_{1}/$ D-NiFe LDH. Electrochemical impedance spectroscopy (EIS) measurement was performed to get insight into the kinetics of charge transfer. Based on Nyquist plots, the charge transfer resistance $(R_{\\mathrm{ct}})$ of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH is smaller than those of other electrocatalysts, demonstrating a facilitated HER charge transfer kinetics and a fast Faradaic reaction process at the interface between the catalyst and the electrolyte (Fig. 3h and Supplementary Fig. 22). Thus, the synergistic effect of the defects and Ru single atoms faciliates the charge transport and increases the number of active sites. To identify the durability of the catalyst, LSV curves before and after 2000 cycles tests show little change (Fig. 3i). The time-dependent current density curves of ${\\mathrm{Ru}}_{1}/{\\bar{\\mathrm{D}}}.$ NiFe LDH were recorded, delivering 10 and $100\\mathrm{mA}\\mathrm{cm}^{-2}$ at $-0.018$ and $-0.061\\mathrm{V}$ vs. RHE for $100\\mathrm{h}$ . Negligible change of current density is also observed in Fig. 3i, indicating the excellent cycling and long-term stability. The extraordinary stability is ascribed to the unique structures of Ru single atoms integrated NiFe LDH nanosheets with abundant defect sites, stabilizing Ru single atoms at atomic level and facilitating the charge transfer in $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH. Afterwards, hydrogen generation was analyzed (Supplementary Fig. 23), indicating that Faradaic efficiency (FE) of $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH is close to $100\\%$ for real water splitting. \n\n![](images/75cb9ac0e5a79a67a6b1a36db34fefe96a60744c9e281200bd1d7e8067480858.jpg) \nFig. 3 HER catalytic performance. a HER polarization curves, b overpotentials at typical current densities, c Tafel slopes of various LDHs, d comparison of merit with respect to both kinetics (Tafel slope) and activity (the overpotential at $10\\mathsf{m A}\\mathsf{c m}^{-2},$ , e TOF values of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH (blue dots), together with reported HER electrocatalysts at typical overpotentials, f double-layer capacitances $(C_{\\mathrm{d}|})$ , $\\pmb{\\mathsf{g}}$ polarization curves with the current normalized to ECSA of NiFe LDH, $\\mathsf{R u}_{1^{\\prime}}$ /NiFe LDH, and ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH, h electrochemical impedance spectroscopy, i time-dependent current density curves of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH at $-0.018$ and $-0.061\\vee$ vs. RHE. Inset is LSV curves before and after 2000 cycles. \n\nElectrocatalytic performance for OER. The OER performace of the electrocatalysts was also evaluated in oxygen-saturated $1\\mathrm{M}$ KOH solution. For $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, a sharp increase in the anodic current response was observed at an onset potential of $1.41\\mathrm{V}$ vs. RHE. Strikingly, $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH increases dramatically after the onset potential with small overpotentials of 189 and $220\\mathrm{mV}$ at 10 and $\\mathrm{\\bar{100}}\\mathrm{mA}\\mathrm{cm}^{-2}$ , which is lower than those of NiFe LDH (250 and $290\\mathrm{mV}$ ) and commericial $\\mathrm{IrO}_{2}$ $350\\mathrm{mV})$ in Fig. 4a, b, demonstrating remarkable OER activity. What is the most significant is that a high current density up to $300\\mathrm{mA}\\mathrm{cm}^{-2}$ can be achieved at $1.47\\mathrm{V}$ vs. RHE for $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH owing to efficient charge transfer, large electrochemical surface area and unique architecture as well as the synergistic effect of $\\mathtt{R u}$ single atoms and the defective support. In comparison of $\\mathrm{{Ru_{1}}/D}$ -NiFe LDH, ${\\mathrm{Ru}_{1}}/{\\mathrm{NiFe}}$ LDH, $\\mathrm{Ru}_{1}$ /NiFeAl LDH and D-NiFe LDH present the inferior OER electrocatalytic activities (Supplementary Fig. 24). Compared to Ru-doped NiFe (NiFeRu) LDH by hydrothermal process44,45, ${\\mathrm{Ru}_{1}}/{\\mathrm{NiFe}}$ LDH shows high OER activity (Supplementary Fig. 25), demonstrating this electrodeposition approach is a promising strategy to fabricate the integtration of single atoms and 2D nanomaterials. The superior $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH is achieved by regluating the etching time and the amount of Ru single atoms in $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH (Supplementary Fig. 25). With regard to the reproducibility, ten $\\mathrm{{Ru}_{1}/D}$ - NiFe LDH electrodes were synthesized by the same approach. There is no big change upon the potentials of 1.419, 1.448 and \n\n![](images/f4952114b8703546f65ddabf832de76f03f63b6a0e420229bfa635dc0f55a4d4.jpg) \nFig. 4 OER catalytic performance. a OER polarization curves, b overpotentials at typical current densities, c potentials at current densities of 10, 100, and $300\\mathsf{m A c m}^{-2}$ for ten ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH electrodes, d Tafel slopes of various LDHs, e comparison of merit with respect to both kinetics (Tafel slope) and activity (the overpotential at $10\\mathsf{m A}\\mathsf{c m}^{-2}.$ ), f electrochemical impedance spectroscopy, g double-layer capacitances $(C_{\\mathrm{d}|})$ of of NiFe LDH, $\\mathsf{R u}_{\\mathbb{\\nu}}$ /NiFe LDH, and ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH, h time-dependent current density curves of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH at 1.419 and $1.448\\vee$ vs. RHE. Inset is LSV curves before and after 2000 cycles. i The amount of gas theoretically calculated and experimentally measured vs. time by use of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH. \n\n1.469 V vs. RHE to deliver the current densities of 10, 100, and $300\\mathrm{mA}\\mathrm{cm}^{-2}$ , as shown in Fig. 4c, demonstrating the excellent reproducibility. In addition to the low overpotential and high current density, the Tafel plot in Fig. 4d shows that $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH has a small slope of $\\bar{31}\\mathrm{mV}\\mathrm{dec}^{-1}$ , which is lower than those of $\\mathrm{Ru_{1}/N i F e}$ LDH $(\\bar{4}1\\mathrm{mV}\\mathrm{dec^{-1}},$ ) and NiFe LDH $(99\\mathrm{mV}\\mathrm{dec}^{-1})_{,}$ , respectively, suggesting favorable OER kinetics in alkaline electrolyte. The combined merits of $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH including low overpotentials and Tafel slopes (Fig. 4e), are superior to commercial $\\mathrm{IrO}_{2}$ and most reported OER catalysts (Supplementary Table $4)^{15,46-54}$ . Particularly, the mass activity, $11,9\\bar{8}\\bar{0}\\mathrm{Ag_{metal}-\\bar{1}}$ of $\\mathrm{{Ru_{1}}/D}$ -NiFe LDH was obtained at the overpotential of $240\\mathrm{mV}$ suggesting that Ru single atoms supported on defective NiFe LDH nanosheets can dramatically maximize the OER activity. \n\nFrom Nyquist plots, $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH exhibits a smaller semicircle diameter than others, implying the faster charge transfer between the electrodes and the electrolyte (Fig. 4f). To investigate the origin of the enhancement of OER performance, a large $C_{\\mathrm{dl}}$ value, $32.3\\mathrm{mF}\\mathrm{cm}^{-2}$ was obtained for $\\mathrm{{Ru_{1}}/D}$ -NiFe LDH, which is higher than those of $\\mathrm{Ru_{1}/N i F e}$ LDH and NiFe LDH (Fig. $_{4\\mathrm{g}}$ and Supplementary Fig. 26), indicating an abundant number of active sites. $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH also has impressive durability in alkaline media (Fig. 4h). The amount of oxygen was measured in comparison of actual quantity against theoretical quantity at differernt reaction time (Fig. 4i), revealing that the FE of $\\mathrm{{Ru}_{\\mathrm{{l}}}\\mathrm{{/D}}}$ -NiFe LDH is $99.6\\%$ during OER process and the observed catalytic current originates exclusively from water oxidation. Accordingly, the intimate interaction between Ru single atoms and defective NiFe LDH nanosheets is beneficial to the OER enhancement of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH. \n\nElectrocatalytic performance for overall water splitting. Inspired by the superior hydrogen and oxygen evolution performance of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH, a two-electrode configuration electrolyzer ( $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH $\\|\\mathrm{Ru}_{1}/\\mathrm{D}$ -NiFe LDH) for overall water splitting (Fig. 5a) was assembled by $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH as both the anode and cathode. The polarization curves of as-prepared $\\mathrm{Ru}_{1}/$ D-NiFe $\\mathrm{LDH||Ru_{1}/D.}$ -NiFe LDH and $\\mathrm{Pt/C\\|IrO}_{2}$ as the benchmark catalysts are displayed in Fig. 5b. $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH only requires the low cell voltages of 1.44 and $1.54\\mathrm{V}$ to reach current densities of 10 and $100\\mathrm{\\dot{m}A}\\mathrm{cm}^{-2}$ , respectively, which is even better than $\\mathrm{Pt/C||IrO}_{2}$ and most reported bifunctional electrocatalysts (Fig. 5d and Supplementary Table 5). Particularly, $\\mathrm{Ru}_{1}/$ D-NiFe LDH as a quintessence drives the typical two-electrode cell to the industrially required current density as high as $500\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ at an ultralow cell voltage of $1.72\\mathrm{V}$ . The overpotential at $500\\mathrm{mA}\\mathrm{cm}^{-2}$ by $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH is lower than most of reported bifunctional catalysts $(175\\mathrm{mA}\\mathrm{cm}^{-2}$ at $1.8\\mathrm{V}$ for NiVIr$\\mathrm{L\\bar{D}H||N i V R u\\mathrm{-}L D H^{42}}$ , $50\\dot{0}\\mathrm{mA}\\mathrm{cm}^{-2}$ at $1.735\\mathrm{V}$ for $\\mathrm{NiMoN}||$ NiMoN $@$ NiFeN55, $190\\mathrm{mA}\\mathrm{cm}^{-2}$ at $1.7\\mathrm{V}$ for $\\mathrm{Rh/NiFeRh-LDH||}$ Rh/NiFeRh- $\\cdot\\mathrm{LDH}^{56}$ , $50\\mathrm{mA}\\mathrm{cm}^{-2}$ at $1.76\\mathrm{V}$ for $\\mathrm{P-}\\mathrm{Co}_{3}\\mathrm{O}_{4}||\\mathrm{P}$ - $\\mathrm{Co}_{3}\\mathrm{O}_{4}{}^{24}$ , etc.), indicating promising potential for industrial overall water splitting application. \n\nSignificantly, as-assembled $\\mathrm{{Ru}_{1}/D}$ -NiFe $\\mathrm{LDH||Ru_{1}/D}$ -NiFe LDH electrodes presented long-term stability by timedependent current density curves. There is no obvious degradation of the current densities of 10 and $100\\mathrm{mA}\\mathrm{cm}^{-2}$ at constant potentials of 1.44 and $1.54\\mathrm{V}$ over $\\boldsymbol{100}\\mathrm{h}$ , indicating the good durability. After long-term electrocatalysis, there is a positive shift of two peaks at 856.5 and $874.3\\dot{\\mathrm{eV}}$ for the Ni $2p$ XPS (Supplementary Fig. 27), confirming the formation of high valence state of $\\mathrm{Ni}^{3+}$ from the oxidation of $\\mathrm{Ni}^{2+23,57-61}$ . In addition, a new peak located at $869.1\\mathrm{eV}$ occured in the XPS of Ni $2p$ , demonstrating the existence of oxyhydroxides as the active sites after long-term OER. However, there is little change in the morphologies and components of $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH after HER and OER by use of SEM and element mappings (Supplementary Figs. 28–30). Additionally, the atomic dispersion of Ru single atoms in D-NiFe LDH after long-tern OER is maintained (Supplementary Fig. 31). The combined analysis of these results demonstrates the potential of $\\mathtt{R u}$ single atoms stabilized on defective NiFe-LDH as a promising candidate towards overall water splitting. \n\n![](images/24d3a0bffe7c0ae0df3309c0f340b58eacde79004a96c5631a9c8741f54804c8.jpg) \nFig. 5 Electrocatalytic performance for overall water splitting. a Schematic diagram of water splitting in a two-electrode configuration, (b) polarization curves by two-electrode system, c chronoamperometric test of ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH with current densities of 10 and $100\\mathsf{m A c m}^{-2}$ at 1.44 and $1.54\\lor,$ and d comparison of the cell voltages at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ for ${\\sf R u_{\\mathrm{\\ell}}}/{\\sf D}$ -NiFe LDH with reported bifunctional electrocatalysts. \n\nTo gain in-depth insights into the structure evolution and electrocatalytic mechanism during OER process, in-situ Raman spectra was used from open circuit voltage (OCV) to $1.7\\mathrm{V}$ vs. RHE in 1 M KOH. When the applied potential was higher than $1.4\\mathrm{V}$ vs. RHE, a pair of characteristic Raman peaks appeared at 447 and $557\\mathrm{cm}^{-1}$ , which can be assigned to the $\\mathrm{\\hat{Ni^{3+}}}$ –O $e_{\\mathrm{g}}$ bending and $\\boldsymbol{A}_{1\\mathrm{g}}$ stretching vibrations of $\\gamma{\\mathrm{-NiOOH}}$ (Supplementary Fig. 32a), indicating the pristine structure transformed to the oxyhydroxides under oxygen evolution potential $^{62-64}$ . Interestingly, when the potential decreases from 1.7 to $1.2\\mathrm{V}$ vs. RHE, the peak of $\\gamma{\\mathrm{-NiOOH}}$ disappeared, suggesting the oxyhydroxides transformed back to LDH (Supplementary Fig. 32b). In brief, these results reveal that the reversible transformation between LDH and the oxyhydroxides are the real active species. \n\nFirst-principles calculations. DFT calculations were performed to identify the active sites in $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH. The Gibbs free energy for each elementary reaction step in HER and OER were explored. The hydrogen absorption energy $(\\Delta G_{\\mathrm{H^{*}}})$ of adsorbed H is a key descriptor for evaluating the HER performance $^{3,29,65}$ . The adsorption structures of $\\mathrm{H}$ at Ni and Fe sites in NiFe LDH, and Ru site on $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDHs were modeled (Supplementary Fig. $33\\mathrm{a-c})$ . Compared with $\\Delta G_{\\mathrm{H^{*}}}$ of adsorbed H at Ni site (1.53 $\\mathrm{eV},$ and Fe site $(1.16\\mathrm{eV})$ in NiFe LDH (Supplementary Fig. 33d), $\\mathrm{H}$ adsorption at the Ru site on $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH has a lower $\\Delta G_{\\mathrm{H^{*}}}$ value of $0.25\\mathrm{eV}$ indicating that the Ru site has more favorable enthalpy of hydrogen adsorption and simultaneous decrease in the thermodynamic barriers for hydrogen production. The DFT results demonstrate the importance of the synergistic effect between the isolated Ru single atoms and defective LDH for high hydrogen evolution rates in alkaline medium. \n\n![](images/3c485ccfd822fef321fed1204fb2069e7caa5454fd2c963c1a9d2cad60259b10.jpg) \nFig. 6 DFT calculations. a, b Schematic illustration of the proposed OER mechanism and c, d Gibbs free energy diagram for a, c Ru and b, d $\\mathsf{R u-O}$ sites on ${\\sf R u}_{1}/{\\sf D}$ -NiFe LDH. The lavender box step is the rate-determining step. \n\nDFT modeling of the water oxidation mechanism involving four concerted proton–electron transfer steps was also analyzed in alkaline medium. As shown in Fig. 6, each elementary reaction step of Gibbs free energy was calculated. The edge sites of Ni and Fe in NiFe LDH were selected as the active site for OER. For NiFe LDH, the transition from ${{\\mathrm{O}}^{*}}$ to ${\\mathrm{OOH^{*}}}$ and the formation ${{\\cal O}^{*}}$ from ${\\mathrm{OH}}^{*}$ are the rate-determining steps for Fe sites and Ni sites, respectively (Supplementary Figs. 34, 35)5. The large Gibbs free energies of the rate-determining step for Fe and Ni sites lead to low $\\mathrm{O}_{2}$ rates, presenting the sluggish OER kinetics. The DFT results suggest that the rate-determining step for Ru site on $\\mathrm{Ru}_{1}/$ D-NiFe LDH is the transition ${|0^{*}}$ to $\\mathrm{\\Gamma_{OOH}*}$ , with the overpotential of $1.71\\mathrm{eV}$ (Fig. 6a). Surprisingly, the Gibbs free energy of Ru sites is higher than those of Fe and Ni sites in NiFe LDH, which is not in agreement with the electrocatalytic performance of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH. From previous reports, $_{\\mathrm{M-O}}$ $\\mathbf{M}=\\operatorname{Ir}$ , Ru) was shown as the likely reaction site during $\\mathrm{OER}^{5,30}$ . Herein, $\\mathrm{{Ru-O}}$ moiety on $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH (Fig. 6b) was proposed as the active site and modeled for the four elementary OER reaction steps. The rate-determining step for $\\mathrm{{Ru-O}}$ site on $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH is the formation of ${\\mathrm{O}}{\\bar{\\mathrm{H}}}^{*}$ . With this active site structure, the overpotential of the rate-determining step for $\\mathrm{{Ru-O}}$ site decreased to $0.38\\mathrm{eV}$ , which is even lower that those of Fe–O and Ni–O sites, expediting the OER kinetics. Thus, both experiment and theoretical simulation confirm that the synergetic effect between Ru single atoms and defective NiFe LDH is beneficial to accelerate the reaction kinetics and thus promote the enhancement of electrocatalytic performance of $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH. \n\n# Discussion \n\nIn summary, a simple and scalable electrocatalytic synthesis strategy is described for stabilization of large number of single atom ruthenium sites on defective NiFe LDH. Based on the precise regulation of local coordination environments of the active sites and the existence of the defects, $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH achieves superior HER and OER performance in alkaline media with low overpotential, high current density and long-term durability. The well-defined structures of the catalysts also allow for fundamental investigation into the reaction steps and kinetics of the HER and OER reactions. For example, DFT calculations reveal that $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH promotes the favorable regulation of H adsorption energies for HER, and facilitates the O–O coupling for OER. For the OER, the $\\mathrm{{Ru-O}}$ moiety is proposed as active site for high rates of $\\mathrm{O}_{2}$ formation. This work not only develops a simple and practical strategy for the synthesis of $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH, but also theoretically/experimentally confirms the pivotal roles of single atoms in unexpectedly optimizing electrocatalytic activity, opening up new opportunities for efficient and stable electrocatalysts with potential for the development of an improved commercial water splitting process. \n\n# Methods \n\nSynthesis of $\\tt R u_{\\tt N}$ -NiFe LDHs. The electrolyte was containing 0.12 M Ni $(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ , $0.12\\mathrm{M}$ $\\mathrm{Fe}(\\mathrm{NO}_{3})_{3}{\\cdot}9\\mathrm{H}_{2}\\mathrm{O}_{3}$ 0.001 M $\\mathrm{Al(NO}_{3})_{3}{\\cdot}9\\mathrm{H}_{2}\\mathrm{O}$ and $0.01{-}0.06\\mathrm{M}$ ${\\mathrm{RuCl}}_{3}{\\cdot}x{\\mathrm{H}}_{2}{\\mathrm{O}}$ . A constant potential electrodeposition was conducted at $-1.0\\mathrm{V}$ vs. $\\mathrm{Ag/AgCl}$ for a certain time. Ru single atoms stabilized NiFeAl LDH (denoted as Ru1/NiFeAl LDH) as the precursor was fabricated by electrodeposition approach. Then, $\\mathrm{Ru_{1}/N i F e A l}$ LDH supported on nickel foam was immersed in $5\\mathrm{M\\NaOH}$ solution under continuous stirring for various times (12, 24, and $36\\mathrm{h}$ ). After alkaline etching treatment, Ru single atoms integrated defective NiFe LDH (denoted as $\\mathrm{{Ru}_{\\mathrm{1}}/\\mathrm{D}}$ -NiFe LDH) nanosheets were obtained. In comparison, $\\mathrm{Ru}_{1}/$ \n\nNiFe LDH was synthesized by the same procedure of $\\mathrm{{Ru}_{1}/D}$ -NiFe LDH without alkaline etching, by use of $0.12\\mathrm{M}$ $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ , 0.12 M $\\mathrm{Fe}(\\mathrm{NO}_{3})_{3}{\\cdot}9\\mathrm{H}_{2}\\mathrm{O}$ , and $0.01{-}0.06\\mathrm{M}\\mathrm{RuCl}_{3}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ . NiFe LDH was fabricated by the same procedure of $\\mathrm{Ru}_{1}/$ D-NiFe LDH, without use of ${\\mathrm{RuCl}}_{3}{\\cdot}x{\\mathrm{H}}_{2}{\\mathrm{O}}$ and alkaline etching. \n\nStructural characterization. Powder XRD patterns were characterized using X-ray diffractometer (Japan Rigaku Rotaflex) by Cu $\\mathrm{K}_{\\mathrm{a}}$ radiation $(\\lambda=1.5418\\mathrm{\\AA}$ . SEM tests were recorded on Nova NanoSEM 450. TEM and HAADF-STEM images were performed on FEI TF30. Spherical aberration-corrected TEM images were characterized on a JEM ARM200F thermal-field emission microscope with a probe spherical aberration corrector. XPS data was tested by a model of ESCALAB250. Inductively coupled plasma-optical emission spectrometer (ICP-OES) was characterized on PerkinElmer AVIO 500. In-situ Raman experiments were conducted with a Raman spectrometer (Thermo Fisher, DXR Microscope) with a $\\times50$ visible objective. The wavenumber of the excitation light source was $532\\mathrm{nm}$ . Atomic force microscope (AFM, Bruck Dimension Icon) was utilized to analyze the thickness of the product. X-ray absorption fine structure spectra (XAFS) of Ni, Fe, and ${\\mathrm{Ru~K}}.$ - edge were collected at BL07A1 beamline of National Synchrotron Radiation Research Center (NSRRC). The data were collected in fluorescence mode using a Lytle detector. \n\nElectrochemical measurements. The electrochemical measurements were conducted by a standard three-electrode cell with the connection of an electrochemical workstation. As-synthesized LDH-based electrode was employed as the working electrode. A graphite rod was applied as the counter electrode. $\\mathrm{Hg/HgO}$ electrode was utilized as the reference electrode. The potentials were converted to RHE by the equation, $E_{\\mathrm{RHE}}=E_{\\mathrm{Hg/HgO}}+0.059\\:\\mathrm{pH}+0.098\\:\\mathrm{V}$ . The geometric surface area of the catalysts supported Ni foam is $\\textstyle{1\\:{\\mathrm{cm}}^{2}}$ , corresponding the mass loading of $\\mathrm{Ru}_{1}/$ D-NiFe LDHs $(2\\mathrm{mg}\\mathrm{cm}^{-2}),$ . In comparison, $20\\mathrm{wt\\%\\Pt/C}$ and $\\mathrm{IrO}_{2}$ inks were dropcast onto Ni foam, producing $\\mathrm{Pt/C}$ and $\\mathrm{IrO}_{2}$ electrodes for electrochemical tests. The HER and OER polarization curves were measured by a LSV approach with a sweeping rate of $1\\mathrm{mV}s^{-1}$ in nitrogen- and oxygen-saturated $1\\mathrm{M}\\mathrm{KOH}$ media at $25^{\\mathrm{{o}}}\\mathrm{{C}}$ . EIS was performed within the frequency range from $100~\\mathrm{kHz}$ to $0.1\\mathrm{Hz}$ . With regard to the measurement of FE, the gaseous products were conducted by gas chromatography (Shimadzu, GC-2014). For determination of FE, the efficiency of HER or OER catalysts is defined as the ratio of the amount of experimentally determined hydrogen or oxygen to that of the theoretically expected hydrogen or oxygen from the HER or OER reaction in 1 M KOH solution. The calculation of mass activity, TOF measurement and XANES simulation were presented (Supplementary Notes 1–3). \n\nFirst-principle calculations. All DFT calculations were performed by the Vienna ab initio simulation package $\\mathrm{(VASP)}^{66}$ . The projector augmented wave pseudopotentials and the generalized gradient approximation parameterized by Perdew–Burke–Ernzerhof (GGA-PBE) for exchange-correlation functional67. The core electrons were descripted by the Projector-augmented wave (PAW) technology. The Brillouin zones of the supercells were sampled by $1\\times2\\times3$ uniform $k$ point mesh66. With fixed cell parameters, the model structures were fully optimized using the convergence criteria of $10^{-5}\\mathrm{eV}$ for the electronic energy and $10^{-2}\\mathrm{eV}/\\mathring{\\mathrm{A}}$ for the forces on each atom and the plane wave cutoff was set to $400\\mathrm{eV}$ . The supercells dimension in $y$ and $z$ was 10.14 and $6.44\\mathring\\mathrm{A}$ , respectively. The vacuum region in the $z$ direction was adopted large than $20\\textup{\\AA}$ . Both spin-polarized and spin-unpolarized computations were performed. Considering the strong $d$ -electron correlation effects for Fe and Ni, $\\mathrm{DFT}+U$ method was used in this work with $U=$ $3.9\\mathrm{eV}$ and $\\boldsymbol{J=}0\\mathrm{eV}$ for Fe and $U=2.9\\mathrm{eV}$ and $\\boldsymbol{J=}0\\mathrm{eV}$ for Ni. and $U{=}3.4\\mathrm{eV}$ and $\\boldsymbol{J=}0\\mathrm{eV}$ for Ru. \n\nThe Gibbs free energy of the intermediates for HER and OER process, that is, $^*\\mathrm{H}$ , ${}^{*}\\mathrm{OH}$ , $^{*}\\mathrm{O}$ , and $^{*}\\mathrm{OOH}$ , can be calculated as \n\n$$\n\\Delta G=E_{\\mathrm{ads}}+\\Delta E_{\\mathrm{ZPE}}-T\\Delta S-\\Delta G(p H)+e U\n$$ \n\nHere $E_{\\mathrm{ads}}$ is the adsorption energy of intermediate, $\\Delta E_{\\mathrm{ZPE}}$ is the zero point energy difference between the adsorption state and gas state, $T$ is the temperature $(300~\\mathrm{\\AA})$ , ΔS is the entropy various between the adsorption and gas phase. \n\nThe intermediates adsorption energy $E_{\\mathrm{ads}}$ for $^*\\mathrm{H}$ , $^{*}\\mathrm{OH}$ , $^*\\mathrm{O}$ and $^{*}\\mathrm{OOH}$ can be used DFT ground state energy calculated $\\mathtt{a s}^{68}$ \n\n$$\n\\Delta E_{*_{M H}}=E(^{*}M H)-E(^{*})-1/2E(H_{2})\n$$ \n\n$$\n\\Delta E_{*_{O O H}}=E(^{*}O O H)-E(^{*})-(2E_{H_{2}O}-3/2E_{H_{2}})\n$$ \n\n$$\n\\Delta E_{*_{O}}=E(^{*}O)-E(^{*})-(E_{H_{2}O}-E_{H_{2}})\n$$ \n\n$$\n\\Delta E_{^*O H}=E(^{*}O H)-E(^{*})-(E_{H_{2}O}-1/2E_{H_{2}})\n$$ \n\nThe OER process usually summarized in four steps \n\n$$\n\\begin{array}{l}{{{\\mathrm{\\boldmath~*~}}+H_{2}O\\rightarrow{\\mathrm{\\boldmath~*}}O H+H^{+}+e^{-}\\mathrm{\\boldmath~.}}}\\\\ {{{\\mathrm{\\boldmath~*}}O H\\rightarrow{\\mathrm{\\boldmath~*}}O+H^{+}+e^{-}\\mathrm{\\boldmath~.}}}\\end{array}\n$$ \n\n$$\n\\begin{array}{l}{{{\\bf\\Pi}^{*}+H_{2}O\\rightarrow{}^{*}O O H+H^{+}+e^{-}.}}\\\\ {{{}}}\\\\ {{{\\bf\\Pi}^{*}O O H\\rightarrow O_{2}+H^{+}+e^{-}+{}^{*}}}\\end{array}\n$$ \n\nHere \\* denotes adsorption active site on the substrate. \n\n$$\n\\Delta G_{I}=\\Delta G_{^{\\ast}O H}\n$$ \n\n$$\n\\Delta G_{I I}=\\Delta G_{^{\\scriptstyle*}O}-\\Delta G_{^{\\scriptstyle*}O H}\n$$ \n\n$$\n\\Delta G_{I I I}=\\Delta G_{^{\\prime}O O H}-\\Delta G_{^{\\prime}O}\n$$ \n\n$$\n\\Delta G_{I V}=4.92-\\Delta G_{^{\\ast}O O H}\n$$ \n\nThe overpotential $(\\eta)$ is defined as below: \n\n$$\n\\eta=\\operatorname*{max}\\{\\Delta G_{I},\\Delta G_{I I},\\Delta G_{I I I},\\Delta G_{I V}\\}-1.23e V\n$$ \n\n# Data availability \n\nThe data that support the findings of this work are available from the corresponding author upon reasonable request. \n\nReceived: 30 November 2020; Accepted: 7 July 2021; Published online: 28 July 2021 \n\n# References \n\n1. Chu, S. & Majumdar, A. Opportunities and challenges for a sustainable energy future. Nature 488, 294–303 (2012). \n2. Zhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving scatalysts. Science 352, 333–337 (2016). \n3. Jiang, K. et al. Single platinum atoms embedded in nanoporous cobalt selenide as electrocatalyst for accelerating hydrogen evolution reaction. Nat. Commun. 10, 1743 (2019). \n4. Yu, F. Y. et al. Pt-O bond as an active site superior to $\\mathrm{Pt}(0)$ in hydrogen evolution reaction. Nat. Commun. 11, 490 (2020). \n5. Jiang, K. et al. Dynamic active-site generation of atomic iridium stabilized on nanoporous metal phosphides for water oxidation. Nat. Commun. 11, 2701 (2020). \n6. Kweon, D. H. et al. Ruthenium anchored on carbon nanotube electrocatalyst for hydrogen production with enhanced Faradaic efficiency. Nat. Commun. 11, 1278 (2020). \n7. Liu, Y. et al. Corrosion engineering towards efficient oxygen evolution electrodes with stable catalytic activity for over $6000\\mathrm{h}$ . Nat. Commun. 9, 2609 (2018). \n8. Yan, Z. et al. Anion insertion enhanced electrodeposition of robust metal hydroxide/oxide electrodes for oxygen evolution. Nat. Commun. 9, 2373 (2018). \n9. Lu, X. & Zhao, C. Electrodeposition of hierarchically structured threedimensional nickel-iron electrodes for efficient oxygen evolution at high current densities. Nat. Commun. 6, 6616 (2015). \n10. Lee, S., Bai, L. & Hu, X. Deciphering iron-dependent activity in oxygen evolution catalyzed by nickel-iron layered double hydroxide. Angew. Chem. Int. Ed. 59, 8072–8077 (2020). \n11. Dionigi, F. et al. In-situ structure and catalytic mechanism of NiFe and CoFe layered double hydroxides during oxygen evolution. Nat. Commun. 11, 2522 (2020). \n12. Jiang, J. et al. Atomic-level insight into super-efficient electrocatalytic oxygen evolution on iron and vanadium co-doped nickel (oxy)hydroxide. Nat. Commun. 9, 2885 (2018). \n13. Yan, J. et al. Single atom tungsten doped ultrathin $\\mathrm{\\Delta}{\\mathsf{a}}{-}\\mathrm{Ni}(\\mathrm{OH})_{2}$ for enhanced electrocatalytic water oxidation. Nat. Commun. 10, 2149 (2019). \n14. Wang, J., Tan, C. F., Zhu, T. & Ho, G. W. Topotactic consolidation of monocrystalline CoZn hydroxides for advanced oxygen evolution electrodes. Angew. Chem. Int. Ed. 55, 10326–10330 (2016). \n15. Song, F. & Hu, X. Ultrathin cobalt-manganese layered double hydroxide is an efficient oxygen evolution catalyst. J. Am. Chem. Soc. 136, 16481–16484 (2014). in $\\scriptstyle\\mathbf{Co-Zn}$ oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). \n17. Wu, X. et al. Hierarchically structured ${\\mathrm{FeNiO}}_{x}{\\mathrm{H}}_{y}$ electrocatalyst formed by in situ transformation of metal phosphate for efficient oxygen evolution reaction. ChemSusChem. 11, 1761–1767 (2018). \n18. Fan, K. et al. Nickel–vanadium monolayer double hydroxide for efficient electrochemical water oxidation. Nat. Commun. 7, 11981 (2016). \n19. Du, J. et al. Iron-salen complex and $\\mathrm{Co}^{2+}$ ion-derived cobalt–iron hydroxide/ carbon nanohybrid as an efficient oxygen evolution electrocatalyst. Adv. Sci. 6, 1900117 (2019). \n20. Hou, J. et al. Rational design of nanoarray architectures for electrocatalytic water splitting. Adv. Funct. Mater. 29, 1808367 (2019). \n21. Tang, Y. et al. Activating the hydrogen evolution and overall water splitting performance of NiFe LDH by cation doping and plasma reduction. Appl. Catal. B 266, 118627 (2020). \n22. Yan, D. et al. Defect chemistry of nonprecious-metal electrocatalysts for oxygen reactions. Adv. Mater. 29, 1606459 (2017). \n23. Gao, Z. W. et al. Engineering NiO/NiFe LDH intersection to bypass scaling relationship for oxygen evolution reaction via dynamic tridimensional adsorption of intermediates. Adv. Mater. 31, 1804769 (2019). \n24. Xiao, Z. et al. Filling the oxygen vacancies in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ with phosphorus: an ultra-efficient electrocatalyst for overall water splitting. Energy Environ. Sci. 10, 2563–2569 (2017). \n25. Yin, Y. et al. Contributions of phase, sulfur vacancies, and edges to the hydrogen evolution reaction catalytic activity of porous molybdenum disulfide nanosheets. J. Am. Chem. Soc. 138, 7965–7972 (2016). \n26. Liu, B. et al. Iron vacancies induced bifunctionality in ultrathin feroxyhyte nanosheets for overall water splitting. Adv. Mater. 30, 1803144 (2018). \n27. Chen, D. et al. Preferential cation vacancies in perovskite hydroxide for the oxygen evolution reaction. Angew. Chem. Int. Ed. 57, 8691–8696 (2018). \n28. Wang, Y. et al. Layered double hydroxide nanosheets with multiple vacancies obtained by dry exfoliation as highly efficient oxygen evolution electrocatalysts. Angew. Chem. Int. Ed. 56, 5867–5871 (2017). \n29. Li, P. et al. Boosting oxygen evolution of single-atomic ruthenium through electronic coupling with cobalt–iron layered double hydroxides. Nat. Commun. 10, 1711 (2019). \n30. Zhang, J. et al. Single-atom Au/NiFe layered double hydroxide electrocatalyst: probing the origin of activity for oxygen evolution reaction. J. Am. Chem. Soc. 140, 3876–3879 (2018). \n31. Lim, T. et al. Atomically dispersed $\\mathrm{Pt-N_{4}}$ sites as efficient and selective electrocatalysts for the chlorine evolution reaction. Nat. Commun. 11, 412 (2020). \n32. Liu, D. et al. Atomically dispersed platinum supported on curved carbon supports for efficient electrocatalytic hydrogen evolution. Nat. Energy 4, 512–518 (2019). \n33. Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}}/\\mathrm{FeO}_{x}.$ Nat. Chem. 3, 634–641 (2011). \n34. Qu, Y. et al. Direct transformation of bulk copper into copper single sites via emitting and trapping of atoms. Nat. Catal. 1, 781–786 (2018). \n35. Liu, D. et al. Atomically dispersed platinum supported on curved carbon supports for efficient electrocatalytic hydrogen evolution. Nat. Energy 4, 512–518 (2019). \n36. Bliem, R. et al. Subsurface cation vacancy stabilization of the magnetite (001). Surf. Sci. 346, 1215–1218 (2014). \n37. Zhang, J. et al. Cation vacancy stabilization of single-atomic-site $\\mathrm{Pt_{1}}/\\mathrm{Ni}(\\mathrm{OH})_{x}$ catalyst for diboration of alkynes and alkenes. Nat. Commun. 9, 1002 (2018). \n38. Wan, J. et al. Defect effects on $\\mathrm{TiO}_{2}$ nanosheets: stabilizing single atomic site Au and promoting catalytic properties. Adv. Mater. 30, 1705369 (2018). \n39. Asnavandi, M. et al. Promoting oxygen evolution reactions through introduction of oxygen vacancies to benchmark NiFe–OOH catalysts. ACS Energy Lett. 7, 1515–1520 (2018). \n40. Song, L. et al. Achieving efficient alkaline hydrogen evolution reaction over a $\\mathrm{Ni}_{5}\\mathrm{P}_{4}$ catalyst incorporating single-atomic Ru sites. Adv. Mater. 32, 1906972 (2020). \n41. Genovese, C. et al. Operando spectroscopy study of the carbon dioxide electro-reduction by iron species on nitrogen-doped carbon. Nat. Comm. 9, 935 (2018). \n42. Wang, Y., Qiao, M., Li, Y. & Wang, S. Tuning surface electronic configuration of NiFe LDHs nanosheets by introducing cation vacancies (Fe or Ni) as highly efficient electrocatalysts for oxygen evolution reaction. Small 14, 1800136 (2018). \n43. Han, X. et al. Ultrasensitive iron-triggered nanosized Fe–CoOOH integrated with graphene for highly efficient oxygen evolution. Adv. Energy Mater. 7, 1602148 (2017). 44. Wang, D. et al. modulation vanadium layered double hydroxide to accelerate water splitting kinetics. Nat. Commun. 10, 3899 (2019). \n45. Chen, G. et al. Accelerated hydrogen evolution kinetics on NiFe-layered double hydroxide electrocatalysts by tailoring water dissociation active sites. Adv. Mater. 30, 1706279 (2018). \n46. Ping, J. et al. Self-assembly of single-layer CoAl-layered double hydroxide nanosheets on 3D graphene network used as highly efficient electrocatalyst for oxygen evolution reaction. Adv. Mater. 28, 7640–7645 (2016). \n47. Qin, M. et al. Unprecedented synthesis of holey 2D layered double hydroxide nanomesh for enhanced oxygen evolution. Adv. Energy Mater. 9, 1803060 (2019). \n48. He, K. et al. Utilizing the space-charge region of the FeNi-LDH/CoP p–n junction to promote performance in oxygen evolution electrocatalysis. Angew. Chem. Int. Ed. 58, 11903–11909 (2019). \n49. Liu, R., Wang, Y., Liu, D., Zou, Y. & Wang, S. Water-plasma-enabled exfoliation of ultrathin layered double hydroxide nanosheets with multivacancies for water oxidation. Adv. Mater. 29, 1701546 (2017). \n50. Jia, Y. et al. A heterostructure coupling of exfoliated Ni–Fe hydroxide nanosheet and defective graphene as a bifunctional electrocatalyst for overall water splitting. Adv. Mater. 29, 1700017 (2017). \n51. Yin, S. et al. A highly efficient oxygen evolution catalyst consisting of interconnected nickel-iron-layered double hydroxide and carbon nanodomains. Adv. Mater. 30, 1705106 (2018). \n52. Zhang, X. et al. A simple synthetic strategy toward defect-rich rorous monolayer NiFe-layered double hydroxide nanosheets for efficient electrocatalytic water oxidation. Adv. Energy Mater. 9, 1900881 (2019). \n53. Long, X. et al. A strongly coupled graphene and FeNi double hydroxide hybrid as an excellent electrocatalyst for the oxygen evolution reaction. Angew. Chem. Int. Ed. 53, 7584–7588 (2014). \n54. Gong, M. et al. An advanced Ni–Fe layered double hydroxide electrocatalyst for water oxidation. J. Am. Chem. Soc. 135, 8452–8455 (2013). \n55. Yu, L. et al. Non-noble metal-nitride based electrocatalysts for highperformance alkaline seawater electrolysis. Nat. Commun. 10, 5106 (2019). \n56. Zhang, B. et al. Integrating Rh species with NiFe-layered double hydroxide for overall water splitting. Nano Lett. 20, 136–144 (2020). \n57. Cai, Z. et al. Introducing $\\mathrm{Fe}^{2+}$ into nickel–iron layered double hydroxide: local structure modulated water oxidation activity. Angew. Chem. Int. Ed. 57, 9392–9396 (2018). \n58. Dionigi, F. & Strasser, P. NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes. Adv. Energy Mater. 6, 1600621 (2016). \n59. Li, P. et al. Tuning electronic structure of NiFe layered double hydroxides with vanadium doping toward high efficient electrocatalytic water oxidation. Adv. Energy Mater. 8, 1703341 (2018). \n60. Chung, D. Y. et al. Dynamic stability of active sites in hydr(oxy) oxides for the oxygen evolution reaction. Nat. Energy 5, 222–230 (2020). \n61. Zhang, N. et al. Lattice oxygen activation enabled by high-valence metal sites for enhanced water oxidation. Nat. Commun. 11, 4066 (2020). \n62. Yeo, B. S. & Bell, A. T. In situ Raman study of nickel oxide and gold-supported nickel oxide catalysts for the electrochemical evolution of oxygen. J. Phys. Chem. C 116, 8394–8400 (2012). \n63. Trzesniewski, B. J. et al. In situ observation of active oxygen species in Fecontaining Ni-based oxygen evolution catalysts: the effect of pH on electrochemical activity. J. Am. Chem. Soc. 137, 15112–15121 (2015). \n64. Huang, J. et al. Identification of key reversible intermediates in selfreconstructed nickel-based hybrid electrocatalysts for oxygen evolution. Angew. Chem. Int. Ed. 58, 17458–17464 (2019). \n65. Nørskov, J. K. et al. Trends in the exchange current for hydrogen evolution. J. Electrochem. Soc. 152, 23–26 (2005). \n66. Kress, G. et al. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169 (1996). \n67. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865 (1996). \n68. Mathew, K., Sundararaman, R., Letchworth-Weaver, K., Arias, T. A. & Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 140, 084106 (2014). \n\n# Acknowledgements \n\nThis work was supported by National Natural Science Foundation of China (Nos. 21972015, 51672034, 12074053), Young top talents project of Liaoning Province (No. XLYC1907147, XLYC1907163), Joint Research Fund Liaoning-Shenyang National Laboratory for Materials Science (No. 2019JH3/30100003), the Fundamental Research Funds for the Central Universities (No. DUT20TD06) and the Liaoning Revitalization Talent Program (XLYC2008032). \n\n# Author contributions \n\nJ.H. supervised the research. J.H., P.Z. and Y.W. conceived the research. P.Z. and Y.W. carried out the experiments, collected and analyzed the experimental data. P.Z. and S.C. performed SEM and TEM characterizations. M.X. and J.G. conducted theoretical calculations. P.Z., G.Z. and J.T.M. carried out XAS measurements and analysis. B.Z., Y.Z., Z. L., Z.F., C.W., X.Z. and L.S. offered help to analyze and discuss the experiment data. J.T. M. and L.S. gave helpful advice on the manuscript preparation. P.Z. and J.H. wrote the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-24828-9. \n\nCorrespondence and requests for materials should be addressed to J.H. \n\nPeer review information Nature Communications thanks Rosalie Hocking, Marcus Lundberg, Xiaoming Sun and other, anonymous, reviewers for their contributions to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41467-021-23306-6", + "DOI": "10.1038/s41467-021-23306-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-23306-6", + "Relative Dir Path": "mds/10.1038_s41467-021-23306-6", + "Article Title": "Electronic metal-support interaction modulates single-atom platinum catalysis for hydrogen evolution reaction", + "Authors": "Shi, Y; Ma, ZR; Xiao, YY; Yin, YC; Huang, WM; Huang, ZC; Zheng, YZ; Mu, FY; Huang, R; Shi, GY; Sun, YY; Xia, XH; Chen, W", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Tuning metal-support interaction has been considered as an effective approach to modulate the electronic structure and catalytic activity of supported metal catalysts. At the atomic level, the understanding of the structure-activity relationship still remains obscure in heterogeneous catalysis, such as the conversion of water (alkaline) or hydronium ions (acid) to hydrogen (hydrogen evolution reaction, HER). Here, we reveal that the fine control over the oxidation states of single-atom Pt catalysts through electronic metal-support interaction significantly modulates the catalytic activities in either acidic or alkaline HER. Combined with detailed spectroscopic and electrochemical characterizations, the structure-activity relationship is established by correlating the acidic/alkaline HER activity with the average oxidation state of single-atom Pt and the Pt-H/Pt-OH interaction. This study sheds light on the atomic-level mechanistic understanding of acidic and alkaline HER, and further provides guidelines for the rational design of high-performance single-atom catalysts. Insights into the rational design of single-atom metal catalysts remains obscure in heterogeneous catalysis. Here, the authors establish the atomic-level structure-activity relationship for a wide-pH-range hydrogen evolution reaction through the electronic metal-support interaction modulation.", + "Times Cited, WoS Core": 608, + "Times Cited, All Databases": 619, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000658766200003", + "Markdown": "# Electronic metal–support interaction modulates single-atom platinum catalysis for hydrogen evolution reaction \n\nYi Shi 1,8✉, Zhi-Rui Ma1,8, Yi-Ying Xiao1, Yun-Chao Yin2, Wen-Mao Huang3, Zhi-Chao Huang3, Yun-Zhe Zheng4, Fang-Ya Mu5, Rong Huang4, Guo-Yue Shi5, Yi-Yang Sun6, Xing-Hua Xia 2✉ & Wei Chen 1,3,7✉ \n\nTuning metal–support interaction has been considered as an effective approach to modulate the electronic structure and catalytic activity of supported metal catalysts. At the atomic level, the understanding of the structure–activity relationship still remains obscure in heterogeneous catalysis, such as the conversion of water (alkaline) or hydronium ions (acid) to hydrogen (hydrogen evolution reaction, HER). Here, we reveal that the fine control over the oxidation states of single-atom Pt catalysts through electronic metal–support interaction significantly modulates the catalytic activities in either acidic or alkaline HER. Combined with detailed spectroscopic and electrochemical characterizations, the structure–activity relationship is established by correlating the acidic/alkaline HER activity with the average oxidation state of single-atom Pt and the Pt–H/Pt–OH interaction. This study sheds light on the atomic-level mechanistic understanding of acidic and alkaline HER, and further provides guidelines for the rational design of high-performance single-atom catalysts. \n\nydrogen has emerged as a green and sustainable fuel to 1 meet the demand for future global energy1–3. Nowadays the majority of hydrogen is still produced from steamreformed methane, which is derived from limited fossil resources and greatly increases $\\mathrm{CO}_{2}$ emission. Electrocatalytic hydrogen evolution reaction (HER) enabled by renewable electricity holds great promise as a safe, scalable, low-cost, and environmentalfriendly pathway for hydrogen production4–6. To date, noble metals (e.g., Pt, Pd, and Rh) are regarded as the most efficient materials to catalyze the conversion of $\\mathrm{H}_{3}\\mathrm{O}^{+}$ (acid) and $\\mathrm{H}_{2}\\mathrm{O}$ (alkaline) to $\\mathrm{H}_{2}{}^{7}$ . In order to maximize the utilization efficiency of noble metals, the rational design and controllable synthesis of catalysts based on the deep understanding of reaction mechanism and structure–activity relationship is crucial for cost-efficient HER catalytic process8,9. An effective approach for mechanistic study of the structure–activity relationship is to modulate the electronic structure of catalysts and unravel the factors that govern their catalytic activities8. \n\nSeveral strategies—multimetallic construction that integrates metal components with distinctive electronic properties, surface engineering of metal by organic modifiers, and metal–support interaction modulation—have been developed to tune the electronic structure of metal catalysts8,10–12. In industrial heterogeneous catalysis, metal nanoparticles are immobilized on a support and the electronic structure of the active sites on metal nanocatalysts can be effectively regulated through the strong metal–support interactions, which is rationalized as the electronic metal–support interaction (EMSI) proposed by Rodriguez and colleagues13,14. EMSI is associated with the orbital rehybridization and charge transfer across the metal–support interface, leading to the formation of new chemical bonds and the realignment of molecular energy levels15–17. The electron transfer modulates the $d$ -band structure of metal nanocatalysts, strengthens the adsorption of reaction intermediates, and hence lowers the energy barrier and facilitates the rate-limiting step. However, the rearrangement of electrons with considerable EMSI effect is only confined to a couple of atomic layers at the metal–support interface11. For the conventional supported metal nanocatalysts consisting of few atomic layers near the interface and non-uniform atomic coordination sites (e.g., vacancies, step edges, kinks and corner sites)18, it is difficult to correlate the overall catalytic activity with the EMSI effect on the electronic structure of active sites. \n\nSingle-atom metal catalyst (SAMC) minimizes the structure of metal components with the well-defined active sites, which are located at the metal–support interface and exposed to reactive species19,20. The homogeneous atomic coordination environment makes SAMC an ideal and simplified model system for the mechanistic investigation of catalytic reactions. Strong EMSI not only stabilizes the single-atom metals owing to the formation of thermodynamically favorable metal–support bonds, but also leads to the charge redistribution induced via electron transfer21–24. The net electron transfer from the single-atom metals to the electronegative atoms (e.g., C, N, O, S) on support positively charges the metal atoms with high oxidation state, and thus modulates the $d$ state of single-atom metals21–27. The $d$ -orbital electrons of transition metal atoms participate directly in the catalytic redox reactions, and thus have close relationship with the adsorption strength of the catalytic reaction intermediates20,28–31. Although SAMC has been widely used for catalyzing HER, comprehensive atomic-level insights into the structure–activity relationship of SAMC for a wide-pH-range HER are rarely reported. \n\nTransition metal dichalcogenides (TMDs) have been widely used as the supports for immobilizing SAMC in heterogeneous catalysis32–37. Compared with SAMC supported on carbon-based materials38–40, the electronic structure of single-atom metals supported on TMDs is usually adjusted by both the anchoring atom and the neighboring transition metal atoms with relatively high atomic number, which affords a more flexible and complex coordination environment to regulate the catalytic activity24,41. Owing to the various well-defined band structures of TMDs (e.g., $\\mathbf{MoS}_{2}$ , $\\mathrm{WS}_{2}$ , $\\mathrm{MoSe}_{2}$ , and ${\\mathrm{WSe}}_{2}$ , Fig. 1a)42, the core anchoring chalcogen (S, Se) and the neighboring transition metal (Mo, W) can synergistically regulate the electronic structure of SAMC through EMSI. The tuneable $d$ -orbital state of single-atom Pt changes the adsorption energy of reactants on metal atoms and thus influences the catalytic activity of HER (Fig. 1a). \n\nHerein, we used the previously reported site-specific electrodeposition technique43 to construct four kinds of single-atom Pt catalysts on different two-dimensional TMDs supports $(\\mathrm{MoS}_{2}$ , $\\mathrm{WS}_{2}.$ $\\mathbf{MoSe}_{2}$ , and $\\mathrm{WSe}_{2}$ ) as a model system. Detailed spectroscopic and electrochemical characterizations show that the fine tailoring of the oxidation state of single-atom Pt through EMSI activates the alkaline and acidic HER (mass activity) up to 73-fold $\\mathrm{(Pt{-}S A s/M o S e_{2})}$ ) and 43-fold $\\mathrm{(Pt-SAs/WS}_{2}$ ) higher than that of the commercial $\\mathrm{Pt/C,}$ respectively, revealing the universality of the single-atom Pt system for the wide-pH-range HER investigations. With the decrease in oxidation state of single-atom $\\mathrm{\\Pt}$ , the hydrogen binding energy decreases, and consequently the acidic HER activity increases to a record level. In the alkaline HER, the single-atom $\\mathrm{Pt}$ catalyst with optimal oxidation state $(c a.+2)-$ showing neither too strong catalyst–H interaction for hydrogen release, nor too weak catalyst–OH interaction for water dissociation—exhibits exceptional catalytic activity. \n\n# Results \n\nSynthesis and characterization of single-atom Pt catalysts. For the self-terminating growth of single-atom Pt on various TMDs supports (Fig. 1b), Cu atoms were first underpotentially deposited on the chemically exfoliated TMDs (ce-TMDs, Supplementary Figs. 1–3). The Cu atoms were then galvanically exchanged by $\\mathrm{Pt}$ (II) (Supplementary Figs. 4 and 5), forming TMDs-supported single-atom $\\mathrm{Pt}$ samples (denoted as Pt-SAs/TMDs: $\\mathrm{Pt}{-}\\mathrm{SA}\\bar{s}/\\mathrm{MoS}_{2}$ , $\\mathrm{Pt}{\\cdot}\\mathrm{\\bar{S}A s}/\\mathrm{W}S_{2}$ , $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ , and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{WSe}_{2},$ ). The surfacelimited underpotential deposition (UPD) technique enables the formation of energetically favorable metal–support bonds, and automatically terminates the sequential formation of metallic bonding, confirming the growth of single-atom $\\mathrm{Pt}^{43}$ . The Pt loadings on $_{c e-\\mathrm{MoS}_{2}}$ , ${\\mathsf{c e}}{\\mathrm{-}}{\\mathsf{W}}{\\mathsf{S}}_{2}$ , $_{\\mathrm{ce-MoSe}_{2}}$ , and ${\\mathsf{c e}}{\\mathrm{-}}{\\mathsf{W S e}}_{2}$ were 5.1, 4.1, 4.7, and $4.9\\ \\mathrm{wt\\%}$ , respectively, as revealed by inductively coupled plasma optical emission spectrometry. No $\\mathrm{\\Pt}$ -containing clusters/nanoparticles or crystalline Pt phases were observed on the ce-TMDs nanosheets (Supplementary Figs. 6, 7). Owing to the discrete distribution of $\\mathrm{Pt}$ atoms, electrochemical cyclic voltammograms of all the Pt-SAs/TMDs samples did not show characteristic peaks of Pt in the regions of $\\mathrm{Pt\\mathrm{-}H}$ adsorption/desorption (Supplementary Fig. 8). The similar Raman spectra of $\\mathrm{Pt}{-}S\\mathrm{A}s/$ TMDs samples with those of the pure ce-TMDs imply that the metallic 1T phase of TMDs well retained after single-atom Pt decoration (Supplementary Figs. 3, 9). The aberration-corrected high-angle annular dark-field-scanning TEM (HAADF-STEM) images confirmed the atomically dispersed Pt atoms (bright spots) on the ce-TMDs nanosheets (Fig. 1c–f). The STEMcoupled energy-dispersive spectroscopy element mapping showed the homogeneous dispersion of atomic Pt over the whole samples (Fig. 1c–f). \n\nElectronic and coordination structure. We then investigated the chemical configuration and local coordination of Pt-SAs/TMDs through the combination of X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS). As shown by XPS in Fig. 2a, compared to that of commercial $\\mathrm{Pt/C}$ located dominantly at $71.2\\mathrm{eV}$ , the binding energies of $\\mathrm{Pt}~4f_{7/2}$ of $\\mathrm{Pt}{-}S\\mathrm{A}s/$ TMDs increased with obvious peak shape changes, located at approximately $71.8\\mathrm{-}72.8\\ \\mathrm{~eV}$ . In order to better support the average oxidation states of Pt, the $\\mathrm{Pt^{4+}}$ and $\\mathrm{Pt}^{2+}$ references were also shown in Supplementary Fig. 10. These results demonstrated that the $\\mathrm{Pt}$ species in Pt-SAs/TMDs were partially oxidized with $_{0-+4}$ valence state $(\\mathrm{Pt}^{\\delta+})$ , owing to the mutual electronic interactions between $\\mathrm{Pt}$ atoms and ce-TMDs supports. Quantitative peak deconvolution and integration of XPS analysis showed that the average oxidation states of $\\mathrm{Pt}$ in $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{S}\\mathrm{As}/\\mathrm{W}\\mathrm{S}_{2}$ , $\\mathrm{Pt}{-}S\\mathrm{A}s/$ $\\mathrm{MoS}_{2}.$ , $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ , and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{WSe}_{2}$ were 1.24, 1.71, 2.11, and 2.61, respectively44 (Fig. 2a, and Supplementary Table 1). The binding energies of Mo 3d/W $4f$ and $\\bar{\\mathsf{S}}\\ 2p/\\mathsf{S e}\\ 3d$ of the supports decreased slightly (Supplementary Fig. 11) while the binding energy of Pt 4f increased, indicating that the electrons were transferred from $\\mathrm{Pt}$ to ce-TMDs supports. In X-ray absorption near-edge spectroscopy (XANES), the Pt $L_{3}$ -edge analysis (Fig. 2b) showed that the white-line intensity for $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoS}_{2}$ and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ were higher than that for $\\mathrm{Pt}$ foil, indicating more unoccupied $5d$ orbitals for single-atom Pt. The oxidation states of single-atom $\\mathrm{Pt}$ in $\\mathrm{Pt}{-}\\mathrm{SA}\\bar{\\mathrm{s}}/\\mathrm{MoS}_{2}$ and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ samples were 1.61 and 2.07 (Fig. 2c and Supplementary Fig. 12), respectively, in line with the XPS analysis. According to $\\mathrm{\\bar{Pt^{0}}}$ foil $(5\\dot{\\mathrm{d}}^{9}6s^{1})$ and $\\mathrm{Pt^{\\mathrm{{IV}}}O}_{2}$ $(5\\mathrm{d}^{6}6s^{0})$ standards, the number of $d$ -band hole for $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ was estimated to be 2.590, higher than that for $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoS}_{2}$ (2.205), indicative of the increased $d$ vacancy29 (Fig. 2d). Because of the interference of W $k$ -edge signal, the Pt $\\mathrm{L}_{3}$ edges of $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{S}\\mathrm{As}/\\mathrm{W}\\mathrm{S}_{2}$ and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{WSe}_{2}$ could not be well recorded45. \n\n![](images/a2ece9775e801914f58572cfcb9ed8f262c2d7acc269fa7005e388b309b50980.jpg) \nFig. 1 Rational design and construction of single-atom Pt catalysts. a Electronic metal–support interactions (EMSI) modulation of single-atom Pt for catalyzing HER. Left: schematic structure of single-atom Pt on TMDs material. The gray, purple, and green spheres represent the chalcogen (sulfur/ selenium), transition metal (molybdenum/tungsten), and platinum, respectively. The electronic structure of single-atom Pt was modulated by twodimensional TMDs through charge delocalization, enabling the single-atom Pt to take slightly positive charge $(\\mathsf{P t^{\\delta+}})$ . The structural unit of single-atom Pt was circled by the orange dashed line and further enlarged above. Top right: schematic diagram of the band edges of TMDs. The conduction band minimum (CBM)/valence-band maximum (VBM) band edges of TMDs (theoretical values) refer to ref. 42. The schematic band structure—showing the electron affinity and ionization potential of various TMDs—provides a guideline for rationalizing the EMSI modulation of single-atom Pt. Bottom right: schematic illustrating that the $d$ -state shift of single-atom Pt induced by EMSI regulates the catalytic performance of HER. b Fabrication of TMDs-supported single-atom Pt. The gray, purple, brown, and green spheres represent chalcogen (sulfur/selenium), transition metal (molybdenum/tungsten), copper, and platinum, respectively. After site-specific electrodeposition of Cu adatoms on the support, galvanic replacement of $\\mathsf{C u}$ adatoms with $\\mathsf{P t C l}_{4}2-$ is carried out to produce TMDs-supported single-atom Pt. Atomic-resolution HAADF-STEM images for (c) $\\mathsf{P t}{\\mathrm{-}}\\mathsf{S A s}/\\mathsf{M}\\mathsf{o S}_{2},$ (d) $\\mathsf{P t}{-}\\mathsf{S A s}/\\mathsf{M o S e}_{2},$ (e) $\\mathsf{P t}{-}\\mathsf{S}\\mathsf{A}\\mathsf{s}/\\mathsf{W}\\mathsf{S}_{2},$ $(\\pmb{\\uparrow})$ Pt${\\mathsf{S A s}}/{\\mathsf{W S e}}_{2}$ (scale bars: $5\\mathsf{n m}.$ ) and the corresponding elemental mappings (right side, scale bars: $100\\ \\mathsf{n m}.$ ). \n\n![](images/8839c834549199331e89548deb0e86dba349c0dab19e4f97726308ebbbdebcef.jpg) \nFig. 2 Structural characterizations of the catalysts. a Pt 4f XPS spectra of the Pt-SAs/TMDs samples and commercial $\\mathsf{P t/C}$ . b Normalized XANES spectra at the Pt $L_{3}$ -edge of Pt foil, $\\mathsf{P t O}_{2},$ , $\\mathsf{P t}{-}\\mathsf{S}\\mathsf{A}\\mathsf{s}/\\mathsf{M}\\mathsf{o}\\mathsf{S}_{2},$ and $\\mathsf{P t}{-}\\mathsf{S}\\mathsf{A}\\mathsf{s}/\\mathsf{M}\\mathsf{o}\\mathsf{S}\\mathsf{e}_{2}$ . The fitted average oxidation states (c) and $d$ -band hole counts (d) of Pt from XANES spectra. e First-shell fitting of EXAFS spectra of $\\mathsf{P t}$ foil, $\\mathsf{P t O}_{2},$ $\\mathsf{P t}{-}\\mathsf{S}\\mathsf{A}\\mathsf{s}/\\mathsf{M}\\mathsf{o}\\mathsf{S}_{2},$ and $\\mathsf{P t}{-}\\mathsf{S A s}/\\mathsf{M o S e}_{2}$ . f Top, side, and perspective views (up to bottom, respectively) of the geometric configurations of Pt-SAs/TMDs with the $\\mathsf{P t}$ atom on the Mo/W top site. The color code is the same as in Fig. 1a. \n\nTo further demonstrate the homogeneous coordination environment of the model system, we further evaluated the local atomic structure of single-atom Pt by extended X-ray absorption fine structure (EXAFS), density functional theory (DFT)- optimized structural models, as well as magnified HAADFSTEM images. The EXAFS spectra of $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoS}_{2}$ and $\\mathrm{Pt}{-}S\\mathrm{A}s/$ $\\mathrm{MoSe}_{2}$ showed a similar peak at approximately $2.3\\mathrm{\\AA}.$ ascribed to the $\\mathrm{Pt}{-}S$ and $\\mathrm{Pt-Se}$ bonds with coordination numbers of 3.2 and 3.5, respectively (Fig. 2e, Supplementary Figs. 13, 14, and fitting parameters shown in Supplementary Table 2)23,43. No appreciable $\\mathrm{Pt-Pt}$ bond $(2.8\\mathrm{~\\AA~})$ was detected in $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoS}_{2}$ and Pt$\\mathsf{S A s}/\\mathrm{MoSe}_{2}$ (Fig. 2e), further verifying the dominant existence of single-atom Pt. No observation of $\\mathrm{Pt-Mo}$ coordination ruled out the covalent attachment of $\\mathrm{Pt}$ atom on Mo edge site or S vacancy. Combined with the coordination numbers, the magnified HAADF-STEM images implied that Pt atoms, coordinating with three nearest neighboring S or Se, were straddled atop Mo (Supplementary Fig. 15). In line with these results, the theoretical Pt–S (2.22, 2.22, and $2.47\\mathrm{~\\AA~}$ ) and $\\mathrm{Pt-Se}$ distance (2.28, 2.28, and $2.56\\mathrm{~\\AA})$ obtained from the optimized Mo atop model (Supplementary Fig. 16) agreed well with the EXAFS analysis (average bond length 2.27 and $2.35\\mathrm{~\\AA~}$ for Pt–S and $\\mathrm{Pt-Se}$ , respectively), which further confirmed Pt attachment on the Mo top site (Fig. 2f). The high-energy barrier for Pt diffusion between the nearest adsorption sites demonstrated the structural stability of the single-atom catalysts (Supplementary Fig. 16). \n\nElectrochemical HER study. The structural characterizations have shown that the electronic structure of single-atom Pt could be finetuned by different TMDs supports through EMSI. We then attempted to demonstrate the effect of EMSI modulation on the catalytic performance of single-atom $\\mathrm{\\Pt}$ Considering the different HER reactants in alkaline $\\mathrm{(H}_{2}\\mathrm{O})$ and acidic $(\\mathrm{H}_{3}\\mathrm{O}^{+})$ media (detailed mechanisms shown in Supplementary Fig. 17)7, we investigated the electrocatalytic HER activity of Pt-SAs/TMDs using a typical threeelectrode configuration in wide-pH-range electrolytes, including 1.0 M KOH and 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solutions (Supplementary Fig. 18). \n\nIn the alkaline condition, all the Pt-SAs/TMDs samples showed much superior electrocatalytic HER activity with negligible overpotential, compared to the pristine ce-TMDs supports (Supplementary Fig. 19). It should be noted that these supported single-atom Pt samples exhibited various alkaline HER activities, with the order of $\\mathrm{Pt\\mathrm{-}S A s/M o S e_{2}>\\mathrm{Pt\\mathrm{-}S A s/M o S_{2}>\\mathrm{Pt\\mathrm{-}S A s/W S_{2}>\\mathrm{0}}}}$ $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{WSe}_{2}$ (Fig. 3a). Specifically, $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ displayed the overpotential value of approximately $29~\\mathrm{mV}$ at a current density of $1\\bar{0}\\mathrm{mA}\\mathrm{cm}^{-2}$ (left axis of Fig. 3b) and exceptional mass activity of $34.4\\mathrm{~A~mg^{-1}}$ under an overpotential of $100~\\mathrm{{mV}}$ (right axis of Fig. 3b, details of calculation shown in Supplementary Note 1), which was the best among all four samples. The electrocatalytic HER activity of $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ was remarkably 73.4-fold higher than that of commercial $\\mathrm{Pt/C},$ and exceeds most of the state-ofthe-art SAMCs or Pt-based electrocatalysts (Fig. 3b, Supplementary Fig. 20, and references shown in Supplementary Tables 3, 4). Gas chromatography analysis was applied to verify the catalytic production of $\\mathrm{H}_{2}$ (Supplementary Fig. 21). \n\nTo investigate the mechanistic insights into the alkaline HER activity of Pt-SAs/TMDs samples, we evaluated the catalysis kinetics from Tafel plots (Fig. 3c). Compared to the other $\\mathrm{Pt}{-}\\mathrm{SA}s/$ TMDs samples (50, 59, and ${\\bar{6}}5\\operatorname{mV}\\mathrm{dec}^{-{\\bar{1}}},$ , $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ exhibited the smallest Tafel slope of $41\\mathrm{mV}\\mathrm{dec}^{-1}$ , implying the fastest HER kinetics. Tafel slopes were much lower than $\\mathrm{\\dot{1}}2\\mathrm{\\dot{0}}\\mathrm{mV}\\mathrm{dec}^{-1}$ in all Pt-SAs/TMDs samples, suggesting that the prior sluggish Volmer reaction was greatly accelerated. The turnover frequency (TOF) value of the Pt sites on $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ was $6.21\\ s^{-1}$ (at $-50\\mathrm{mV}$ ; details of the calculation shown in Supplementary Note 2), which strikingly surpasses the other three Pt-SAs/TMDs samples (Fig. 3d) and previously reported single-atom electrocatalysts (references shown in Supplementary Table 3). The negligible degradation of Pt-SAs/TMDs after 1000 cycles stability tests demonstrated the high stability of the supported single-atom Pt (Supplementary Fig. 22), which is an essential prerequisite for mechanism investigation. The HAADF-STEM and XPS characterizations of Pt-SAs/TMDs after HER measurements suggested the unchanged morphology and valence state of single-atom Pt during HER, further confirming the stability of the Pt-SAs/TMDs catalysts (Supplementary Figs. 23, 24, and Supplementary Table 5). \n\nSimilarly, we also showed the various acidic HER activities on different supported single-atom Pt samples, which followed the order distinctive from that in alkaline HER: $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{WS}_{2}>\\mathrm{Pt}.$ $\\mathrm{SAs/MoS_{2}\\ >\\ P t-S A s/M o S e_{2}\\ >\\ P t-S A s/W S e_{2}}$ (Figs. 3e and 3f), consistent with the previously reported results43. For instance, compared to the other three samples, $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{S}\\mathrm{As}/\\mathrm{W}\\mathrm{S}_{2}$ displayed much lower overpotential value $32\\mathrm{mV}$ ; left axis of Fig. 3f) at a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ and exceptional mass activity of $130.2\\mathrm{A}\\mathrm{mg}^{-1}$ under an overpotential of $100\\mathrm{mV}$ (43.1-fold higher than commercial $\\mathrm{Pt/C_{:}}$ ; right axis of Fig. 3f, details of the calculation shown in Supplementary Note 1). The Tafel slope and TOF values of $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{S}\\mathrm{As}/\\mathrm{\\bar{W}S}_{2}$ were ${\\dot{2}}8\\operatorname{mV}\\mathrm{dec}^{-1}$ and $273{\\bar{\\mathsf{s}}}^{-1}$ (at $-200\\mathrm{mV}$ ; details of the calculation shown in Supplementary Note 2), respectively, much better than the other three $\\mathrm{Pt}{-}S\\mathrm{A}s/$ TMDs samples and most of the state-of-the-art SAMCs or Ptbased electrocatalysts (Figs. 3g, 3h, Supplementary Fig. 25, and references shown in Supplementary Tables 6, 7). \n\nWe further verified the active sites for HER and the negligible contribution of TMDs support to HER. The thiocyanate ions $(\\mathrm{SCN^{-}})$ poison experiment of the Pt-SAs/TMDs samples was conducted to efficiently block the Pt sites for acidic $\\dot{\\mathrm{HER}}^{34,43}$ . \n\nUpon the addition of $\\mathrm{{\\calS}C N^{-}}$ , the HER current of all the $\\mathrm{Pt}{-}S\\mathrm{A}s/$ TMDs samples decreased dramatically approaching near zero, confirming that HER activity dominantly derives from the singleatom $\\mathrm{Pt}$ and the catalytic performance enhancement is mainly attributed to the EMSI modulation of $\\mathrm{Pt}$ (Supplementary Fig. 26). This phenomenon is distinct from the Pt-doping case, where Pt atoms are incorporated into the TMD lattice and chalcogen atoms are reported as the active sites of $\\mathrm{HER}^{33}$ (Supplementary Note 3, and Supplementary Table 8). Additionally, the Tafel behavior of Pt-SAs/TMDs in acidic HER $(\\sim30\\mathrm{mV}\\mathrm{{\\dot{dec}^{-1}}}.$ ) resembles that of the commercial $\\mathrm{Pt,}$ indicating that the catalytic reaction on single-atom Pt contributed mostly to the HER. In contrast, it has been reported that $\\mathrm{\\Pt}$ -doped $\\ensuremath{\\mathrm{MoS}}_{2}$ showed a Tafel slope of $96\\mathrm{mV}\\mathrm{dec}^{-\\mathrm{i}}$ , close to that of pure $\\mathbf{MoS}_{2}$ $(\\sim100\\mathrm{mV}\\mathrm{dec}^{-1})^{3\\hat{3}}$ . \n\nStructure and activity relationship. To evaluate the EMSI effect on the hydrogen adsorption ability of different single-atom Pt catalysts, the highly surface-sensitive ultraviolet photoelectron spectroscopy (UPS) was conducted to probe the occupied electronic states of single $\\mathrm{Pt}$ atoms on different supports (Fig. 4a). For a free-state single-atom metal, no metallic bonding is formed and thus only the $d$ level exists. The $p{-}d$ orbital hybridization between single $\\mathrm{Pt}$ atom and coordinating atom (e.g., S and $\\mathsf{S e}$ ) on the support broadens the $d$ level of single-atom $\\mathrm{\\Pt}$ , leading to the formation of a narrower $d$ band around $0{-}4\\mathrm{eV}$ compared to that of bulk $\\mathrm{Pt}$ (Fig. 4a and Supplementary Fig. 27)46–49. The positions of $d$ -band center for $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{S}\\mathrm{As}/\\mathrm{W}\\mathrm{S}_{2}$ , $\\mathrm{Pt}{\\mathrm{-}}{\\mathrm{SAs}}/\\mathrm{MoS}_{2}$ , $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ , and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{WSe}_{2}$ were $-2.58\\mathrm{eV}$ , $-2.39\\mathrm{eV}$ , $-2.24\\mathrm{eV}$ , and $-2.06\\mathrm{eV}$ respectively (Fig. 4a), higher than that of Pt nanocrystal $\\mathrm{(-2.94~eV)^{48}}$ . Due to the EMSI modulation, various density of states patterns were obtained from the DFT calculation for the Pt$d$ orbitals of the four Pt-SAs/TMDs (Supplementary Fig. 28). The $d$ -band model developed by Norskov and colleagues has been widely used in relating adsorption properties of rate-limiting intermediates to the electronic structure of catalysts28,50. According to the $d$ -band theory, when the Pt d band experiences an upward shift, more antibonding states of hydrogen are pulled above the Fermi level, and hence strengthens the affinity of Pt towards hydrogen (Fig. 4b)28,50. On the basis of the experimental UPS valence-band spectra (VBS), the $\\mathrm{~H~}$ adsorption ability of these single-atom Pt samples can be proposed following the order: $\\mathrm{Pt{-}S A s/W S_{2}\\mathrm{~<~\\mathrm{Pt{-}}S A s/M o S_{2}\\mathrm{~<~\\mathrm{Pt{-}}S A s/M o S e_{2}\\mathrm{~<~\\mathrm{Pt{-}}S A s/M o S e_{2}\\mathrm{~<~\\mathrm{Pt{-}}S A s/M o S e_{2}\\mathrm{~<~\\mathrm{Pt{-}}S A s/M o S e_{2}\\mathrm{~<~\\mathrm{Pt{-}}S A s/M o S e_{2}\\mathrm{~>~\\mathrm{Pt{-}}S A s/M o S e_{2}\\mathrm{~\\eta_{2}\\ e t a_{2}\\ e t a_{2}\\ e t a_{2}\\ e t a_{2}\\ e t a_{3}\\ e t a_{3}\\ e t a_{2}\\ }}}}}}}}}$ ${\\mathrm{WSe}}_{2}$ . This trend predicted by the $d$ -band theory also agreed well with the Gibbs free energy of atomic hydrogen adsorption $(\\Delta\\mathrm{G_{H^{*}}}$ , Supplementary Fig. 29) obtained from the DFT simulation. \n\nThe correlation of electronic structure, hydrogen binding energy (HBE) and acidic HER activity is shown (Fig. 4c) with the average oxidation state of single-atom $\\mathrm{Pt}$ (determined by XPS and XANES) as $x\\cdot$ -axis while hydrogen adsorption ability (represented by the $d$ -band center from VBS) as left $y$ -axis and the overpotential required to achieve a current density of $10~\\mathrm{\\mA}$ $\\mathrm{cm}^{-\\frac{3}{2}}$ as the right $y$ -axis. With the increase of average oxidation state of single-atom Pt, the hydrogen adsorption ability also increased in a nearly linear relation (Fig. 4c), implying the EMSI modulation on the adsorption energy of $\\mathrm{H^{*}}$ intermediates during HER. We showed that the HER activity of the single-atom Pt catalyst decreased monotonically with the increase of average oxidation state and H adsorption ability (Fig. 4c), thus providing solid evidence supporting that HBE is the dominant descriptor in the acidic HER of single-atom Pt. The near ambient-pressure Xray photoelectron spectroscopy (NAP-XPS) further demonstrated that stronger hydrogen adsorption on single-atom Pt with higher valence state $(\\mathrm{Pt}{-}\\mathrm{S}\\bar{\\mathrm{A}}s/\\mathrm{W}{\\mathrm{S}}{\\mathrm{e}}_{2},$ ) leaded to active site poisoning and slow hydrogen desorption, greatly limiting the overall HER activity (Supplementary Figs. 30, 31). \n\n![](images/eef4224cc333e7e621c5ae0b2ee8a61404d79983496863b4bac5c5254adba843.jpg) \nFig. 3 Electrochemical analysis in 1.0 M KOH and 0.5 M ${\\bf H}_{2}\\thinspace{\\sf s o}_{4}$ . a, e HER polarization curves of various Pt-SAs/TMDs samples. b, f HER comparison of overpotentials required to achieve a current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ (black arrow, left axis) and mass activities (normalized by the Pt loading, red arrow, right axis) at $-100\\mathsf{m V}$ versus RHE for various Pt-SAs/TMDs samples. c, g Tafel plots derived from the early stage of the corresponding HER polarization curves. d, h Turnover frequency (TOF) curves of various Pt-SAs/TMDs samples and a comparison with the previously reported state-of-the-art values for single-atom HER catalysts. \n\n![](images/0b52c1b7625f2e2d27686f7b083cf60d050472e6435adde58ca429aa9008f347.jpg) \nFig. 4 Mechanistic investigations. a UPS valence-band spectra (VBS) of single-atom Pt relative to the Fermi level. The black dashed lines represent the position of the $d$ -band centers. The gray dashed lines represent the variation in the VBS of ce-TMDs induced by single-atom Pt attachment. b Schematic DOS diagrams illustrating the EMSI effect on the $d$ -band position of single-atom $\\mathsf{P t},$ and the interaction between Pt and chemisorbed atomic hydrogen. When H is adsorbed on single-atom Pt, the interaction of the adsorbed H $(H^{\\star})$ $s$ -orbital with the Pt $d$ -orbital will result in fully filled low-energy bonding states and partially filled high-energy antibonding states. c Relationship of average oxidation state, H adsorption ability and acidic HER activity of $\\mathsf{P t-S A s}/\\mathsf{\\Lambda}$ TMDs. The circle and triangle represent the average oxidation state of single-atom Pt obtained from XPS and XANES, respectively. The H adsorption ability is quantified by the position of the $d$ -band center. d CO stripping voltammetry of various single-atom Pt catalysts. The dashed lines represent the CO oxidation potentials obtained for catalysts. The scanning potential value for Pt-SAs/TMDs samples could only reach as high as $0.7\\:\\mathrm{V}$ , since higher potential resulted in the oxidation of ce-TMDs (Supplementary Fig. 36). e Relationship of average oxidation state, Pt–OH interaction and alkaline HER activity of PtSAs/TMDs. The circle and triangle are the average oxidation states of single-atom Pt obtained from XPS and XANES, respectively. The Pt–OH interaction is quantified by the CO oxidation potentials obtained from CO stripping voltammetry. \n\nIt is generally accepted that the HER process in acidic and alkaline conditions shares a similar reaction pathway, except for the generation of $\\mathrm{H^{*}}$ intermediates in alkaline HER through a water dissociation step (Supplementary Fig. 17). We correlated the hydrogen adsorption ability with the HER activity of four single-atom Pt catalysts in alkaline condition. We noted that with increased HBE, the alkaline HER activity of single-atom $\\mathrm{Pt}$ catalyst increased at low oxidation states $(<2.0)$ , which was opposite to that observed in acidic HER (Supplementary Fig. 32). These results partially demonstrate that HBE of single-atom Pt— although is one of the influential factors—is not critical for the single-atom catalytic activity in alkaline $\\mathrm{HER^{9}}$ . Considering the sluggish water dissociation in the Volmer and Heyrovsky steps $(\\mathrm{H}_{2}\\bar{\\mathrm{O}}+\\mathrm{e}^{-}\\to\\mathrm{H}^{*}+\\mathrm{OH}^{-}$ and $\\mathrm{H}^{*}+\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{e}^{-}\\rightarrow\\mathrm{\\dot{H}}_{2}+\\mathrm{OH}^{-}$ , \\* represents an adsorption site) during alkaline $\\mathrm{HER}^{38}$ , we then focused on the contribution of water dissociation. \n\nWe propose that such single-atom $\\mathrm{Pt}$ with high oxidation state is energetically favorable for the adsorption and activation of electron-rich $\\dot{\\mathrm{H}}_{2}\\mathrm{O}$ and adsorbed OH intermediates $(\\mathrm{OH^{*}})$ . The deuterated effect in alkaline HER indicated that water dissociation on single-atom $\\mathrm{Pt}$ was dominant, as evidenced by the inferior HER activities in $\\mathrm{D}_{2}\\mathrm{O}$ than $_\\mathrm{H}_{2}\\mathrm{O}$ (Supplementary Fig. 33)51,52, which was in good agreement with the Tafel slope analysis. It is well-known that the strong interaction between $\\bar{\\mathrm{OH^{*}}}$ species and surface of catalysts accelerates the water dissociation process53. Since $\\mathrm{OH^{*}}$ facilitates the removal of adsorbed CO intermediate53, we used CO stripping voltammetry tests to measure the ability of single-atom $\\mathrm{Pt}$ catalysts for the water dissociation (Fig. 4d). \n\nCompared to the commercial $\\mathrm{Pt/C}$ (0.53 V, Supplementary Fig. 34), electron-deficient single-atom $\\mathrm{\\Pt}$ catalysts showed much lower onset potential of CO oxidation (0.28–0.46 V), indicating stronger $\\mathrm{Pt-OH}$ interaction of single-atom $\\mathrm{Pt}$ and accelerated kinetics of water dissociation (Fig. 4d). On the other hand, singleatom Pt catalyst with higher oxidation state leaded to a smaller contribution of back-donation of $\\mathrm{Pt}~5d$ electrons to the $2\\pi^{*}$ orbitals of CO molecule10,54, thus weakening CO adsorption. The different CO oxidation potential also in turn reflects the variation in the electronic structure of different single-atom $\\mathrm{Pt}$ catalysts, in line with the XPS and XANES analysis. Additionally, the $d$ -band upshifts of the four Pt-SAs/TMDs samples (Fig. 4a and Supplementary Fig. 28) also imply an improved water dissociation ability due to the increased $\\mathrm{OH^{*}}$ binding energy55–57, consistent with the CO stripping measurement (Fig. 4d). With an increase of the average oxidation state of single-atom $\\mathrm{\\Pt}$ , the $\\mathrm{Pt-OH}$ interaction became stronger while the alkaline HER activity showed a volcano-type relationship (Fig. 4e). The singleatom Pt catalyst with the average oxidation state of approximately $+2$ (volcano’s top) exhibited exceptional alkaline HER activity. \n\n# Discussion \n\nIn this work, we demonstrate that EMSI modulation of singleatom Pt significantly regulates the HER activity over a wide-pH range, and systematically unravel the relationship between oxidation state and HER activity of single-atom Pt. The EMSI— acting as a bridge between electronic study and catalyst design— provides a detailed explanation of the enhanced properties of supported catalysts at the electronic scale. With the length scale of catalysts shrinking to the atomic level, the EMSI effect becomes stronger and can predominate the reaction rate24,41. The strong EMSI between the single-atom Pt and TMDs support redistributes the electron density around the metal center with the direct formation of metal–support bonds, facilitating the electron transfer from the active metal center to the reactant. The changes in the oxidation state of single-atom Pt can be the direct effect from EMSI, which acts as a useful approach to quantitatively determine the strength of EMSI. The technical characterizations (e.g., XPS, XAS; Fig. 2) of the oxidation state pave the way for revealing the underlying mechanism of the target reaction, which in turn enhances the comprehensive understanding of EMSI and electronic structures across the length scales. Apart from changes in the electronic structure of active sites, the stabilization effect is also a basic influence of EMSI, which suppresses the migration of single-atom metals even under operating conditions (Supplementary Figs. 23 and 24). \n\nFrom the structure–activity relationship, the fine control over the oxidation state of single-atom Pt catalysts enables to achieve the optimal catalytic activity in either acidic or alkaline HER. In acidic environment, the HER performance could be well optimized through properly decreasing the oxidation state of singleatom Pt (Fig. 5a), accelerating the hydrogen desorption process. Similar to our finding, Liang’s and Yao’s groups have recently reported that the electron-enriched or near-zero-valence atomically dispersed Pt species are more active than the high-valence single-atom Pt for catalyzing acidic HER29,30. In alkaline environment, as the oxidation state of single-atom $\\mathrm{Pt}$ increases, the HER activity also increases initially (left side of the volcano plot, Fig. 4e). Under the electrochemical condition, the charge of the metal plays a decisive role with regard to water dissociation58,59. Choi’s group reported the counterintuitive promoting effect of CO molecule on alkaline HER of single-atom $\\mathrm{Pt}^{25}$ , which could be also explained by our proposed model (Fig. 5b). After the coordination of CO (strong electron acceptor), metal-to-ligand charge transfer from Pt was increased, endowing the single-atom $\\mathrm{Pt}$ site with higher oxidation state (ca. $+2\\substack{-2.3}$ . Such single-atom Pt site was more electrophilic and favorable for the water dissociation, thus accelerating the alkaline HER. The opposite trends in acidic and alkaline HER (Fig. 4c, 4e) indicate the different mechanistic pathways of HER depending on the $\\mathrm{\\tt{pH}}$ conditions, consistent with the previously reported works25,60. \n\nWe further suggest that single-atom $\\mathrm{Pt}$ with optimal valence state is simultaneously favorable for water dissociation, adsorption/desorption of ${\\mathrm{OH}}^{*}$ and $\\boldsymbol{\\mathrm{H^{*}}}$ (Fig. 5b, and Supplementary Fig. 35). It should be noted that with the increased oxidation state of single-atom $\\mathrm{{Pt},}$ the adsorption of $\\mathrm{H^{*}}$ and $\\mathrm{OH^{*}}$ on the catalyst were both strengthened. Although single-atom Pt with high oxidation state energetically favors the adsorption of electron-rich $_\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{OH^{*}}$ , too strong hydrogen adsorption will also lead to the slow release of active sites and hence the sluggish HER kinetics. From a fundamental point of view, the present work reveals the atomic-level enhancement of HER thermodynamically and kinetically by optimizing the catalyst– $\\boldsymbol{\\cdot}\\mathrm{H}$ interaction and accelerating the water dissociation, respectively. The single-atom $\\mathrm{Pt}$ catalyst with optimal oxidation state $(\\sim+2)$ , showed neither too strong $\\mathrm{Pt\\mathrm{-}H}$ interaction to release hydrogen, nor too weak $\\mathrm{Pt-OH}$ interaction to dissociate water, which dramatically contributes to the overall alkaline HER. \n\n![](images/874d4b6952e842dcd0656c3a6133beded32551830de0d29adf734001f5d66931.jpg) \nFig. 5 EMSI modulation mechanism of electrocatalytic HER on the single-atom Pt. a Surface intermediate on single-atom Pt modified electrode in the acidic condition. $k$ represents the kinetics rate of ${\\sf H}_{2}$ desorption. With the increase in oxidation state of single-atom Pt, the kinetics rate of ${\\sf H}_{2}$ desorption $(k)$ decreases. b Surface intermediate on single-atom Pt modified electrode in the alkaline condition. $k_{\\u{\\tau}}$ and $k_{2}$ represent the kinetics rates of water dissociation and ${\\sf H}_{2}$ desorption, respectively. With the increase in oxidation state of single-atom $\\mathsf{P t},$ the kinetics rate of water dissociation $(k_{1})$ increases while the kinetics rate of ${\\sf H}_{2}$ desorption $(k_{2})$ decreases. EDL represents the electric double layer. \n\nTo date, three widely adopted theories have emerged to explain the alkaline HER mechanism: water dissociation theory (hydroxyl binding energy, OHBE), hydrogen binding energy (HBE) theory, or interface water and/or anion transfer theory9. It still remains unclear which descriptor governs the alkaline HER. At the atomic level, our results show that the two descriptors $\\mathrm{\\DeltaOH^{*}}$ and $\\mathrm{H^{*}}$ ) codetermined the rate of alkaline HER (Fig. 5b), which sheds light on the long-standing puzzle about HER mechanism. Although a quantitative contribution of the water dissociation and hydrogen desorption in alkaline HER is beyond the scope of the current work, the structure–activity relationship bridges a previously unconsidered link between oxidation state and wide-pH-range HER activity. Owing to the limitation of the EMSI-induced TMDs support modulation in the current work, the oxidation state of single-atom Pt was mostly restricted to a record level of ca. $+1\\mathrm{-}+2.6$ . Further, more researches about the structure–activity relationship could be extended to the nearzero-valence single-atom metal or even negatively charged ultrasmall metal clusters. Apart from the oxidation state of singleatom metals, many complicated factors (e.g., coordination environment, reactive interface, interfacial water orientation)44,53,58–62 could also be considered for the development of structure–activity relationship and the rational design of high-performance HER catalysts. \n\nIn summary, the EMSI-induced variation in oxidation state of single-atom Pt catalyst effectively modulates the acidic and alkaline HER. The improved HER arises from optimized thermodynamics of HER for hydrogen adsorption and accelerated reaction kinetics for water dissociation. The oxidation state of single-atom Pt controls the catalytic activity towards HER by virtue of modulating the $\\mathrm{Pt-H/Pt-\\dot{O}H}$ interactions. Such atomiclevel understanding of the structure–activity relationship helps to shed more insights into other single-atom electrocatalytic reduction reactions, which also involve water dissociation or hydrogen adsorption/desorption steps in carbon dioxide reductions and nitrogen reduction reactions. \n\n# Methods \n\nMaterials. Molybdenum(IV) sulfide $(\\ensuremath{\\mathrm{MoS}}_{2})$ powder, molybdenum(IV) selenide $(\\mathrm{MoSe}_{2})$ powder, tungsten(IV) sulfide $(\\mathrm{W}\\mathrm{S}_{2})$ powder, n-butyllithium in cyclohexane $(2.0\\ \\mathrm{M})$ , copper(II) sulfate pentahydrate $(\\mathrm{CuSO}_{4}{\\cdot}5\\mathrm{H}_{2}\\mathrm{O})$ , potassium platinum (II) chloride $\\mathrm{(K_{2}P t C l_{4})}$ , $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%})$ and Nafion perfluorinated resin solution ( $5\\mathrm{wt\\%}$ in a mixture of low aliphatic alcohols and water, contains $45\\%$ water) were purchased from Sigma-Aldrich (USA); tungsten(IV) selenide $(\\mathrm{WSe}_{2})$ powder was purchased from Aladdin Industrial Corporation (Shanghai, China). All aqueous solutions were prepared with Millipore water (resistivity of $18.2~\\mathrm{\\M\\Omega/cm}$ ). \n\nSynthesis of Pt-SAs/TMDs. The single-atom $\\mathrm{Pt}$ on different ce-TMDs nanosheets $(\\mathrm{Pt}{\\mathrm{-}}\\mathrm{SAs}/\\mathrm{TMDs})$ were synthesized through the site-specific electrodeposition method43. Details of the synthesis of ce-TMDs nanosheets are shown in Supplementary Methods. Briefly, a working electrode was made by drop-casting $5~{\\upmu\\mathrm{L}}$ of the well-dispersed ce-TMDs suspension ( ${\\mathsf{c e}}{\\mathrm{-MoS}}_{2}$ , ce- $\\mathrm{WS}_{2}.$ ce- $\\mathrm{.}\\mathrm{MoSe}_{2}\\mathrm{.}$ , or ${\\mathsf{c e}}{\\mathrm{-}}{\\mathrm{WSe}}_{2}.$ ) to cover a glassy carbon electrode (GCE, $3\\mathrm{mm}$ diameter). A Cu UPD process was first performed on the ce-TMDs-modified GCE by controlling the potential at $+0.10\\mathrm{~V~}$ (vs $\\mathrm{Ag/AgCl})$ in an Ar-saturated $0.1\\mathrm{~M~}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution containing $2~\\mathrm{mM}$ $\\mathrm{CuSO_{4}}$ . After the UPD process, the GCE was quickly transferred into an Arsaturated $0.05\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution containing 5 mM $\\mathrm{K_{2}P t C l_{4}}$ . The electrode was kept in this solution for more than $20~\\mathrm{min}$ at an open circuit potential to ensure a complete galvanic replacement of Cu by $\\mathrm{Pt}(\\mathrm{II})$ , forming atomically dispersed Pt decorated ce-TMDs nanohybrid (termed as Pt-SAs/TMDs). All the electrochemical measurements were carried out using a CHI 760E Instrument (Chenhua, China) at room temperature. \n\nPhysical characterization. Transmission electron microscopy (JEOL JEM-2100, Japan) and field emission electron microscopy (JEOL JEM-2800, Japan) were utilized to characterize the morphologies and elemental maps of catalysts. The atomic force microscopy (AFM) measurements were carried out using a \n\ncommercial AFM (Bruker, Dimension FastScan, Icon Scanner, USA). High-angle annular dark-field-scanning transmission electron microscopy (HAADF-STEM) characterizations were carried out on a FEI Titan $^3\\mathrm{G}260\\ –300^{\\cdot}$ equipped with double aberration correctors, which was operated at $200~\\mathrm{kV}$ . X-ray diffraction patterns (XRD, X’TRA, Switzerland) were collected to characterize the crystal structures of samples. Inductively coupled plasma optical emission spectrometry (ICP-OES) was used to determine the loading of single-atom Pt in $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{SAs}/\\mathrm{TMDs}$ on a CHN-ORapid (German). The samples for ICP analysis were treated with aqua regia in Teflon-lined autoclaves at $230^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{~h~}}$ . The $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy at the $\\mathrm{Pt}~\\mathrm{L}_{3}$ -edge was obtained at the 14W1 beam line of the Shanghai Synchrotron Radiation Facility, using a Si(111) double-crystal monochromator operated at 3.5 GeV in fluorescence mode. The oxidation states and formal $d$ -band hole counts of different single-atom Pt catalysts can be determined quantitatively by integrating the white-line area44. Specifically, the differential XANES (ΔXANES) spectra were obtained by subtracting the spectra of Pt-SAs/TMDs from that of Pt foil reference (Supplementary Fig. 12). Owing to the linear relationship between the white-line area and the oxidation states/formal $d$ -band hole counts, these two parameters of single-atom Pt can be fitted by correlating the ΔXANES area of the references (Pt foil and $\\mathrm{PtO}_{2}$ ) and the single-atom $\\mathrm{Pt}$ catalysts. For example, the formal $d$ -band hole count was calculated based on the slope of 1.166 unit area per $d$ -band hole obtained from $\\mathrm{Pt}^{0}$ foil $(5\\mathrm{d}^{9}6s^{1})$ and $\\mathrm{Pt}^{\\mathrm{IV}}\\mathrm{O}_{2}^{*}(5\\mathrm{d}^{6}6\\mathrm{s}^{0})$ standards29. X-ray photoelectron spectroscopy (XPS) spectra were obtained on a SPECS Phoibos 150 (Germany) with the calibration of binding energies based on the C 1s peak energy located at $284.6~\\mathrm{eV}$ . The near ambient-pressure XPS (NAP-XPS) experiments were performed by using a differentially pumped electron analyzer and an in situ ambient-pressure gas cell equipped with a twin anode X-ray source (SPECS XR50, Al Kα, $\\mathrm{h}\\upgamma=1486.6\\mathrm{eV}$ ; Mg Kα, $\\mathrm{h}\\upgamma=1253.6\\mathrm{eV}$ ) under a base pressure at 0.5 mbar. The precise leak valve let gas fill the gas cell via gas line to several millibar from ultra-high vacuum in $2~\\mathrm{min}$ . The sample was loaded near the nozzle $(300\\upmu\\mathrm{m})$ of the gas cell and illuminated to the X-ray through a $100\\mathrm{nm}\\mathrm{Si}_{3}\\mathrm{N}_{4}$ window. The high purity $\\mathrm{H}_{2}$ gas $(99.999\\%$ , CHEM-GAS) was introduced into the cell at room temperature and liquid nitrogen trap was used to eliminant the residual water contamination during the spectra collection. All the samples were first exposed to $\\mathrm{H}_{2}$ for $^{2\\mathrm{~h~}}$ before their XPS spectra were collected. The core-level spectra of W 4f, Mo 3d, S 2p, Se 3d, and Pt 4f were measured by using the Al $\\mathrm{Ka}$ source with the kinetic energies at around $1450~\\mathrm{eV}$ , $1258\\ \\mathrm{eV}$ , $1324{\\mathrm{~eV}}$ , $1432\\mathrm{eV}$ , and $1414~\\mathrm{eV}$ , respectively. The UPS measurements were carried out by using the UVS 10/35 UV source (SPECS) in He I $(21.2\\ \\mathrm{eV})$ . The UPS valence-band spectra of single-atom Pt were obtained by subtraction of the normalized ce-TMDs spectra from the $\\mathrm{Pt-SAs}/$ TMDs spectra (Supplementary Fig. 19). The pass energy was set at $40~\\mathrm{eV}$ for XPS measurements and $2\\mathrm{eV}$ for UPS measurements. \n\nElectrochemical measurements for HER. Linear sweep voltammetry (using CHI 760E instrument, Chenhua, China) with scan rate of $20\\mathrm{mVs^{-1}}$ was conducted in either 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ or $1.0\\mathrm{M}$ KOH solution using an $\\mathrm{Ag/AgCl}$ electrode (saturated KCl) as the reference, a graphite rod as the counter electrode, and a glassy carbon electrode (GCE) as the working electrode. The $\\mathrm{\\Ag/AgCl}$ (saturated KCl) electrode was calibrated with respect to the reversible hydrogen electrode (RHE). In $1.0\\ \\mathrm{M}$ KOH solution, the loading amount of $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoS}_{2}$ , $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ , $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{S}{\\mathrm{As}}/{\\mathrm{W}}\\mathrm{S}_{2}$ and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{WSe}_{2}$ on the GCE were $5\\upmu\\mathrm{g}.$ $,4.35\\upmu\\mathrm{g},5.6\\upmu\\mathrm{g}$ and $5\\upmu\\mathrm{g};$ respectively, $E$ $(\\mathrm{RHE})=E(\\mathrm{Ag/AgCl})+1.012\\:\\mathrm{V}$ ; in 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution, the loading amount of $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoS}_{2}$ , $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{MoSe}_{2}$ , $\\mathrm{Pt}{\\mathrm{-}}\\mathrm{SAs}/\\mathrm{W}\\mathrm{S}_{2},$ and $\\mathrm{Pt}{-}\\mathrm{SAs}/\\mathrm{W}\\mathrm{Se}_{2}$ on the GCE were $0.625{\\upmu\\mathrm{g}},0.55{\\upmu\\mathrm{g}},0.715{\\upmu\\mathrm{g}}$ and $0.65\\upmu\\mathrm{g},$ respectively, $E(\\mathrm{RHE})=E(\\mathrm{Ag}/\\mathrm{AgCl})+$ $0.222\\mathrm{~V~}$ (Supplementary Fig. 18). The commercial $\\mathrm{Pt/C}$ catalyst ink was prepared by ultrasonically mixing $2\\mathrm{mg}$ of the $12\\upmu\\mathrm{L}5\\%$ Nafion and $1\\mathrm{mL}$ water/ethanol (v:v, 1:9) suspension for $^\\textrm{\\scriptsize1h}$ . Geometric area of GCE is $0.07065\\mathrm{cm}^{2}$ . Then, ${5}\\upmu\\mathrm{L}$ of the ink was drop-cast onto the GCE and dried naturally in air. The loading amount of Pt was about $28.3\\upmu\\mathrm{g}_{\\mathrm{Pt}}\\mathrm{cm}^{-2}$ . Before each HER LSV measurement, the catalyst on the electrode was first activated by cyclic voltammetry scanning between $0.05\\mathrm{~V~}$ and $1.3{\\mathrm{~V~}}$ (vs RHE) for 20 cycles at a scan rate of $50\\mathrm{mVs^{-1}}$ in Ar-saturated electrolyte $(1.0\\mathrm{~M~KOH/0.5~M~H_{2}S O}.$ ). For CO stripping measurement, pure CO gas was first adsorbed on the working electrode at a fixed potential of $0.1\\mathrm{~V}_{\\mathrm{RHE}}$ in a CO-saturated $1.0\\ \\mathrm{M}$ KOH electrolyte for $10~\\mathrm{min}$ . All the cyclic voltammograms (CVs) of CO stripping were collected after purging with Ar gas at a scan rate of $20\\mathrm{mVs^{-1}}$ . \n\nThe reaction product of hydrogen was measured using a gas chromatograph (GC-2014, SHIMADZU) equipped with a separation column (MS-13X, 80/100 mesh, $3.2\\times2.1\\:\\mathrm{mm}\\times2.0\\:\\mathrm{m})$ and a thermal conductivity detector (TCD). Nitrogen was used as the carrier gas in the chromatograph. The parameters were set as follows: column temperature, $80~^{\\circ}\\mathrm{C};$ TCD temperature, $100^{\\circ}\\mathrm{C};$ and bridge current, $60\\mathrm{mA}$ . \n\nThe TOF of the catalysts was calculated according to the following equation: \n\n$$\n\\mathrm{TOF}=I/(2F\\times n)\n$$ \n\nwhere $I$ represents the measured current during linear sweep measurement, $F$ is the Faraday constant $(96,500\\mathrm{Cmol^{-1}},$ ) and $n$ is the mole amount of active $\\mathrm{\\Pt}$ site. The factor $1/2$ represents that two electrons are required to form one hydrogen molecule $(2\\bar{\\mathrm{H}}^{+}+2\\mathrm{e}^{-}\\rightarrow\\mathrm{H}_{2}^{-},$ Þ. \n\n# Data availability \n\nAll data supporting the findings in the article as well as the Supplementary Information files are available from the corresponding authors on reasonable request. \n\nReceived: 14 December 2020; Accepted: 14 April 2021; Published online: 21 May 2021 \n\n# References \n\n(2001). \n2. Turner, J. A. Sustainable hydrogen production. Science 305, 972–974 (2004). \n3. Xiao, S. et al. Microwave-induced metal dissolution synthesis of core–shell copper nanowires $/Z\\mathrm{nS}$ for visible light photocatalytic $\\mathrm{H}_{2}$ evolution. $A d\\nu$ . Energy Mater. 9, 1900775 (2019). 4. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: Insights into materials design. Science 355, eaad4998 (2017). \n5. Shi, Y. et al. Hot electron of Au nanorods activates the electrocatalysis of hydrogen evolution on $\\ensuremath{\\mathbf{MoS}}_{2}$ nanosheets. J. Am. Chem. Soc. 137, 7365–7370 (2015). \n6. Shi, Y. et al. Energy level engineering of $\\ensuremath{\\mathbf{MoS}}_{2}$ by transition-metal doping for accelerating hydrogen evolution reaction. J. Am. Chem. Soc. 139, 15479–15485 (2017). \n7. Zou, X. et al. Noble metal-free hydrogen evolution catalysts for water splitting. Chem. Soc. Rev. 44, 5148–5180 (2015). \n8. Luo, M. et al. Strain-controlled electrocatalysis on multimetallic nanomaterials. Nat. Rev. Mater. 2, 17059 (2017). 9. Wang, X. et al. Strategies for design of electrocatalysts for hydrogen evolution under alkaline conditions. Mater. Today 36, 125–138 (2020). \n10. Chen, G. et al. Interfacial electronic effects control the reaction selectivity of platinum catalysts. Nat. Mater. 15, 564–569 (2016). \n11. van Deelen, T. W. et al. Control of metal-support interactions in heterogeneous catalysts to enhance activity and selectivity. Nat. Catal. 2, 955–970 (2019). \n12. Sheng, T. et al. Structure design and performance tuning of nanomaterials for electrochemical energy conversion and storage. Acc. Chem. Res. 49, 2569–2577 (2016). \n13. Campbell, C. T. Electronic perturbations. Nat. Chem. 4, 597–598 (2012). \n14. Bruix, A. et al. A new type of strong metal–support interaction and the production of $\\mathrm{H}_{2}$ through the transformation of water on $\\mathrm{Pt/CeO}_{2}(111)$ and $\\mathrm{Pt}/\\mathrm{CeO_{x}}/\\mathrm{TiO}_{2}(110)$ catalysts. J. Am. Chem. Soc. 134, 8968–8974 (2012). \n15. Lykhach, Y. et al. Counting electrons on supported nanoparticles. Nat. Mater. 15, 284–288 (2016). \n16. Vayssilov, G. N. et al. Support nanostructure boosts oxygen transfer to catalytically active platinum nanoparticles. Nat. Mater. 10, 310–315 (2011). \n17. Shi, Y. et al. Electronic metal–support interaction to modulate $\\ensuremath{\\mathrm{MoS}}_{2}$ - supported Pd nanoparticles for the degradation of organic dyes. ACS Appl. Nano Mater. 2, 3385–3393 (2019). \n18. Liu, P. et al. Surface coordination chemistry of metal nanomaterials. J. Am. Chem. Soc. 139, 2122–2131 (2017). \n19. Wang, A. et al. Heterogeneous single-atom catalysis. Nat. Rev. Chem. 2, 65–81 (2018). \n20. Hu, P. et al. Electronic metal–support interactions in single-atom catalysts. Angew. Chem. Int. Ed. 53, 3418–3421 (2014). \n21. Chen, Y. et al. Discovering partially charged single-atom Pt for enhanced antiMarkovnikov alkene hydrosilylation. J. Am. Chem. Soc. 140, 7407–7410 (2018). \n22. Zu, X. et al. Efficient and robust carbon dioxide electroreduction enabled by atomically dispersed $\\sin^{\\delta+}$ sites. Adv. Mater. 31, 1808135 (2019). \n23. Jiang, K. et al. Single platinum atoms embedded in nanoporous cobalt selenide as electrocatalyst for accelerating hydrogen evolution reaction. Nat. Commun. 10, 1743 (2019). \n24. Yang, J. et al. Electronic metal–support interaction of single-atom catalysts and applications in electrocatalysis. Adv. Mater. 32, e2003300 (2020). \n25. Kwon, H. C. et al. Carbon monoxide as a promoter of atomically dispersed platinum catalyst in electrochemical hydrogen evolution reaction. J. Am. Chem. Soc. 140, 16198–16205 (2018). \n26. Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}/F e O_{x}}$ . Nat. Chem. 3, 634–641 (2011). \n27. Li, J. et al. Highly active and stable metal single-atom catalysts achieved by strong electronic metal–support interactions. J. Am. Chem. Soc. 141, 14515–14519 (2019). \n28. Nørskov, J. K. et al. Density functional theory in surface chemistry and catalysis. Proc. Natl Acad. Sci. USA 108, 937–943 (2011). \n29. Fang, S. et al. Uncovering near-free platinum single-atom dynamics during electrochemical hydrogen evolution reaction. Nat. Commun. 11, 1029 (2020). doped carbon support for electrocatalytic hydrogen evolution. Nat. Commun. 10, 4977 (2019). \n31. Jeong, H. et al. Controlling the oxidation state of Pt single atoms for maximizing catalytic activity. Angew. Chem. Int. Ed. 132, 20872–20877 (2020). \n32. Wang, Y. et al. Catalysis with two-dimensional materials confining single atoms: concept, design, and applications. Chem. Rev. 119, 1806–1854 (2019). \n33. Deng, J. et al. Triggering the electrocatalytic hydrogen evolution activity of the inert two-dimensional $\\ensuremath{\\mathbf{MoS}}_{2}$ surface via single-atom metal doping. Energ. Environ. Sci. 8, 1594–1601 (2015). \n34. Qi, K. et al. Single-atom cobalt array bound to distorted 1T $\\ensuremath{\\mathrm{MoS}}_{2}$ with ensemble effect for hydrogen evolution catalysis. Nat. Commun. 10, 5231 (2019). \n35. Li, J. et al. Accelerated dinitrogen electroreduction to ammonia via interfacial polarization triggered by single-atom protrusions. Chem 6, 885–901 (2020). \n36. Liu, G. et al. $\\mathbf{MoS}_{2}$ monolayer catalyst doped with isolated Co atoms for the hydrodeoxygenation reaction. Nat. Chem. 9, 810–816 (2017). \n37. Qin, R. et al. Surface coordination chemistry of atomically dispersed metal catalysts. Chem. Rev. 120, 11810–11899 (2020). \n38. Chen, Y. et al. Atomic-level modulation of electronic density at cobalt singleatom sites derived from metal–organic frameworks: enhanced oxygen reduction performance. Angew. Chem. Int. Ed. 60, 3212–3221 (2021). \n39. Wan, J. et al. In situ phosphatizing of triphenylphosphine encapsulated within metal–organic frameworks to design atomic $\\mathrm{Co}_{1}{-}\\mathrm{P}_{1}\\mathrm{N}_{3}$ interfacial structure for promoting catalytic performance. J. Am. Chem. Soc. 142, 8431–8439 (2020). \n40. Zhang, J. et al. Tuning the coordination environment in single-atom catalysts to achieve highly efficient oxygen reduction reactions. J. Am. Chem. Soc. 141, 20118–20126 (2019). \n41. Li, X. et al. Modulating the local coordination environment of single-atom catalysts for enhanced catalytic performance. Nano Res. 13, 1842–1855 (2020). \n42. Bertolazzi, S. et al. Molecular chemistry approaches for tuning the properties of two-dimensional transition metal dichalcogenides. Chem. Soc. Rev. 47, 6845–6888 (2018). \n43. Shi, Y. et al. Site-specific electrodeposition enables self-terminating growth of atomically dispersed metal catalysts. Nat. Commun. 11, 4558 (2020). \n44. Ren, Y. et al. Unraveling the coordination structure-performance relationship in $\\mathrm{Pt_{1}}/\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ single-atom catalyst. Nat. Commun. 10, 4500 (2019). \n45. Park, J. et al. Investigation of the support effect in atomically dispersed Pt on $\\mathrm{WO}_{3-\\mathbf{x}}$ for utilization of Pt in the hydrogen evolution reaction. Angew. Chem. Int. Ed. 58, 16038–16042 (2019). \n46. Hannagan, R. T. et al. Single-atom alloy catalysis. Chem. Rev. 120, 12044–12088 (2020). \n47. Duchesne, P. N. et al. Golden single-atomic-site platinum electrocatalysts. Nat. Mater. 17, 1033–1039 (2018). \n48. Hofmann, T. et al. Using photoelectron spectroscopy and quantum mechanics to determine $d$ -band energies of metals for catalytic applications. J. Phys. Chem. C. 116, 24016–24026 (2012). \n49. Greiner, M. T. et al. Free-atom-like $d$ states in single-atom alloy catalysts. Nat. Chem. 10, 1008–1015 (2018). \n50. Hammer, B. et al. Why gold is the noblest of all the metals. Nature 376, 238–240 (1995). \n51. Cai, Z. S. et al. Bioinspired engineering of cobalt-phosphonate nanosheets for robust hydrogen evolution reaction. ACS Catal. 8, 3895–3902 (2018). \n52. Tang, Q. et al. Mechanism of hydrogen evolution reaction on 1T- ${\\cdot\\mathrm{MoS}_{2}}$ from first principles. ACS Catal. 6, 4953–4961 (2016). \n53. Wang, X. et al. Anomalous hydrogen evolution behavior in high-pH environment induced by locally generated hydronium ions. Nat. Commun. 10, 4876 (2019). \n54. Su, S. et al. Tailoring the electron density of Pd nanoparticles through electronic metal-support interaction for accelerating electrocatalysis of formic acid. Electrochem. Commun. 107, 106540 (2019). \n55. Wang, X. et al. Rapid activation of platinum with black phosphorus for efficient hydrogen evolution. Angew. Chem. Int. Ed. 58, 19060–19066 (2019). \n56. Xue, S. et al. Enhancing the hydrogen evolution reaction activity of platinum electrodes in alkaline media using nickel–iron clusters. Angew. Chem. Int. Ed. 59, 10934–10938 (2020). \n57. Anniyev, T. et al. Complementarity between high-energy photoelectron and Ledge spectroscopy for probing the electronic structure of 5d transition metal catalysts. Phys. Chem. Chem. Phys. 12, 5694–5700 (2010). \n58. Ledezma-Yanez, I. et al. Interfacial water reorganization as a pH-dependent descriptor of the hydrogen evolution rate on platinum electrodes. Nat. Energy 2, 17031 (2017). \n59. Iwasita, T. & Xia, X. Adsorption of water at $\\mathrm{Pt}(111)$ electrode in $\\mathrm{{HClO}_{4}}$ solutions. The potential of zero charge. J. Electroanal. Chem. 411, 95–102 (1996). \n60. Staszak-Jirkovský, J. et al. Design of active and stable Co–Mo– $\\cdot S_{\\mathrm{x}}$ chalcogels as pH-universal catalysts for the hydrogen evolution reaction. Nat. Mater. 15, 197–203 (2016). \n\n61. Koper, M. T. M. A basic solution. Nat. Chem. 5, 255–256 (2013). 62. Shen, L. F. et al. Interfacial structure of water as a new descriptor of the hydrogen evolution reaction. Angew. Chem. Int. Ed. 59, 22397–22402 (2020). \n\n# Acknowledgements \n\nThe authors acknowledge the financial support from Singapore National Research Foundation under the grant of NRF2017NRF-NSFC001-007, NUS Flagship Green Energy Programme, the National Key Research and Development Program of China (2017YFA0206500), the National Natural Science Foundation of China (21902076, 21635004), and the Natural Science Foundation of the Jiangsu Province (BK20190289). The authors thank Prof. Li. Song, Prof. Shuang-Ming Chen, Dr. Yu Wang, and Wen-Jie Xu for assistance in structural analysis. The authors thank Dr. Xiao-Kun Huang and Dr. Yu Wang for his useful discussion on DFT simulations. The authors thank Dr. ZhangLiu Tian, Dr. Da-Feng Yan, Dr. Wen-Rui Dai, Ms. Yu-Min Da, and Ms. Meng Wang for assistance in the research work. The authors also gratefully thank the Shanghai Synchrotron Radiation Facility (14W1, SSRF). \n\n# Author contributions \n\nY.S., X.X. and W.C. conceived the project. Y.S., Z.M. and Y.X. carried out the synthesis of the catalysts, physical and electrochemical characterizations. Y.Y., W.H. and G.S. assisted in the data analysis. Z.H. and Y.-Y.S. performed the DFT calculations. Y.Z., F.M. and R.H. carried out and assisted in the morphology characterization. Y.S., X.X. and W.C. wrote the manuscript. All authors commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-23306-6. \n\nCorrespondence and requests for materials should be addressed to Y.S., X.-H.X. or W.C. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1007_s40820-021-00624-4", + "DOI": "10.1007/s40820-021-00624-4", + "DOI Link": "http://dx.doi.org/10.1007/s40820-021-00624-4", + "Relative Dir Path": "mds/10.1007_s40820-021-00624-4", + "Article Title": "Lightweight, Flexible Cellulose-Derived Carbon Aerogel@Reduced Graphene Oxide/PDMS Composites with Outstanding EMI Shielding Performances and Excellent Thermal Conductivities", + "Authors": "Song, P; Liu, B; Liang, CB; Ruan, KP; Qiu, H; Ma, ZL; Guo, YQ; Gu, JW", + "Source Title": "nullO-MICRO LETTERS", + "Abstract": "In order to ensure the operational reliability and information security of sophisticated electronic components and to protect human health, efficient electromagnetic interference (EMI) shielding materials are required to attenuate electromagnetic wave energy. In this work, the cellulose solution is obtained by dissolving cotton through hydrogen bond driving self-assembly using sodium hydroxide (NaOH)/urea solution, and cellulose aerogels (CA) are prepared by gelation and freeze-drying. Then, the cellulose carbon aerogel@reduced graphene oxide aerogels (CCA@rGO) are prepared by vacuum impregnation, freeze-drying followed by thermal annealing, and finally, the CCA@rGO/polydimethylsiloxane (PDMS) EMI shielding composites are prepared by backfilling with PDMS. Owing to skin-core structure of CCA@rGO, the complete three-dimensional (3D) double-layer conductive network can be successfully constructed. When the loading of CCA@rGO is 3.05 wt%, CCA@rGO/PDMS EMI shielding composites have an excellent EMI shielding effectiveness (EMI SE) of 51 dB, which is 3.9 times higher than that of the co-blended CCA/rGO/PDMS EMI shielding composites (13 dB) with the same loading of fillers. At this time, the CCA@rGO/PDMS EMI shielding composites have excellent thermal stability (T-HRI of 178.3 degrees C) and good thermal conductivity coefficient (lambda of 0.65 W m(-1) K-1). Excellent comprehensive performance makes CCA@rGO/PDMS EMI shielding composites great prospect for applications in lightweight, flexible EMI shielding composites.", + "Times Cited, WoS Core": 588, + "Times Cited, All Databases": 606, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000629787500001", + "Markdown": "# Lightweight, Flexible Cellulose‑Derived Carbon Aerogel $@$ Reduced Graphene Oxide/PDMS Composites with Outstanding EMI Shielding Performances and Excellent Thermal Conductivities \n\nReceived: 3 February 2021 \nAccepted: 16 February 2021 \n$\\circledcirc$ The Author(s) 2021 \n\nPing Song1, Bei Liu1,2, Chaobo Liang1, Kunpeng Ruan1, Hua Qiu1, Zhonglei $\\mathbf{M}\\mathrm{a}^{1}$ , Yongqiang Guo1, Junwei Gu1 \\* \n\n# HIGHLIGHTS \n\n•\t Cellulose aerogels were prepared by hydrogen bonding driven self-assembly, gelation and freeze-drying. \n\n•\t The skin-core structure of CCA $@\\mathrm{rGO}$ aerogels can form a perfect three-dimensional bilayer conductive network. \n\n•\t Outstanding EMI SE (51 dB) is achieved with $3.05\\mathrm{wt}\\%$ CCA@rGO, which is 3.9 times higher than that of the co-blended composites. \n\nABSTRACT  In order to ensure the operational reliability and information security of sophisticated electronic components and to protect human health, efficient electromagnetic interference (EMI) shielding materials are required to attenuate electromagnetic wave energy. In this work, the cellulose solution is obtained by dissolving cotton through hydrogen bond driving self-assembly using sodium hydroxide (NaOH)/ urea solution, and cellulose aerogels (CA) are prepared by gelation and freeze-drying. Then, the cellulose carbon aerogel $@$ reduced graphene oxide aerogels $\\operatorname{\\rho}_{\\mathrm{(CCA@rGO)}}$ are prepared by vacuum impregnation, freeze-drying followed by thermal annealing, and finally, the $\\mathrm{CCA@}$ rGO/polydimethylsiloxane (PDMS) EMI shielding composites are prepared by backfilling with PDMS. Owing to skin-core structure of $\\mathrm{CCA@rGO}$ , the complete three-dimensional (3D) double-layer conductive network can be successfully constructed. When the loading of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ is $3.05~\\mathrm{wt}\\%$ , CCA $@$ rGO/PDMS EMI shielding composites have an excellent EMI shielding effectiveness (EMI SE) of 51 dB, which is 3.9 times higher than that of the co-blended CCA/rGO/PDMS EMI shielding composites (13 dB) with the same loading of fillers. At this time, the CCA $@$ rGO/PDMS EMI shielding composites have excellent thermal stability $\\langle T_{H R I}$ of $178.3^{\\circ}\\mathrm{C})$ and good thermal conductivity coefficient $\\lambda$ of $0.65\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}.$ ). Excellent comprehensive performance makes CCA $@$ rGO/PDMS EMI shielding composites great prospect for applications in lightweight, flexible EMI shielding composites. \n\n![](images/210d608a9587ad1452089712f86d8b90232f29bf534759686c7dcf8a0b456c6b.jpg) \n\nKEYWORDS  Polydimethylsiloxane; Electromagnetic interference shielding; Cellulose carbon aerogel; Reduced graphene oxide \n\n# 1  Introduction \n\nWhile electronic and electrical equipment have brought great convenience to our lives, they have also caused increasingly serious electromagnetic pollution, such as electronic noise, electromagnetic interference and radio frequency interference [1–3]. Electromagnetic waves not only couple and interfere with the normal use of other electronic components, making it impossible for electronic equipment to function properly and posing serious threat to information security, but also affect human health. Studies have shown that when people are exposed to electromagnetic radiation for a long time, the risk of diseases such as cancer, heart disease, skin problems, headaches and other mild or acute diseases will increase. Therefore, the design and development of lightweight, economical and efficient EMI shielding materials are imperative to address the problems of electromagnetic pollution [4–6]. \n\nCompared with traditional metal-based EMI shielding composites, polymer-based EMI shielding composites have attracted much attention from the scientific and industrial communities due to their lightweight, high specific strength, easy molding and processing, excellent chemical stability, low cost and good sealing properties [7–9] Commonly used polymer matrixes are epoxy resin, phenolic resin, polyvinylidene fluoride (PVDF) and polydimethylsiloxane (PDMS). Among them, PDMS has good mechanical properties, high and low temperature resistance, excellent weather resistance, chemical stability and easy processing and molding characteristics, widely used in many fields such as aerospace, automotive industries and microelectronics [10–12]. In addition, PDMS has excellent flexibility compared to rigid matrixes such as epoxy resins and can meet the requirements of wearable electronic devices for flexibility in materials. In recent years, PDMS-based EMI shielding composites have made certain research progress, but to achieve the desired EMI shielding effectiveness (EMI SE) usually requires high filler loading, which seriously affects the cost, processability and mechanical properties, largely limiting the application of PDMS-based EMI shielding composites in the field of microelectronics, aircraft and spacecraft [13–15]. Therefore, the development of PDMS-based EMI shielding composites with excellent EMI shielding performances at low filler loading is a research hotspot. \n\nAs the abundant renewable bioenergy on the earth, biomass (such as straw, wood, sugarcane and cotton) is easy and fast to prepare from a wide variety of sources [16–19]. The preparation of biomass-based carbon aerogel/polymer composites by certain methods has a wide range of applications in the fields of flexible conductive materials, supercapacitors, energy storage materials and EMI shielding materials [20–22]. Shen et al. [23] prepared aerogel (Cs)/epoxy EMI shielding composites by carbonizing natural wood at 1200 $^{\\circ}\\mathrm{C}$ to obtain Cs and then backfilling with epoxy resin. The results showed that the electrical conductivity $(\\sigma)$ and EMI $S\\mathrm{E_{T}}$ of the Cs/epoxy EMI shielding composites reached $12.5~\\mathrm{S~m}^{-1}$ and $28~\\mathrm{dB}$ , respectively. Li et al. [24] prepared aerogel-like carbon (ALC)/PDMS EMI shielding composites by hydrothermal carbonization of sugarcane to obtain ALC, followed by backfilling with PDMS. The results showed that the EMI $\\mathrm{{\\calSE}_{T}}$ of ALC/PDMS EMI shielding composites reached 51 dB with the thickness of $10~\\mathrm{mm}$ . Ma et al. [25] obtained straw-derived carbon (SC) aerogel by carbonizing wheat straw at $1500^{\\circ}\\mathrm{C}$ and then prepared SC/epoxy EMI shielding composites by backfilling with epoxy resin. The results showed that the EMI $S\\mathrm{E_{T}}$ of SC/epoxy EMI shielding composites reached $58\\mathrm{dB}$ with the thickness of $3.3\\mathrm{mm}$ . \n\nIt has been shown that the EMI SE of biomass-based carbon aerogel/polymer EMI shielding composites can be further enhanced by compounding the carbon aerogel with highly conductive materials (such as silver wire, MXene and graphene) or magnetic materials (such as iron, cobalt, nickel and their oxides) [26, 27]. The introduction of reduced graphene oxide (rGO) into cellulose carbon aerogels (CCA) can further improve the 3D conductive network and significantly enhance the $\\sigma$ of biomass-based carbon aerogel/polymer EMI shielding composites, thus effectively improving their EMI SE [28]. Zeng et al. [29] prepared ultra-lightweight and highly elastic rGO/lignin-derived carbon (LDC) aerogel EMI shielding composites by freeze-drying. The results showed that the EMI $S\\mathrm{E_{T}}$ of the rGO/LDC aerogel EMI shielding composites reached $49\\ \\mathrm{dB}$ with the thickness of $2~\\mathrm{mm}$ . Wan et  al. [30] prepared ultra-lightweight cellulose fiber $({\\mathrm{CF}})/{\\mathrm{rGO}}$ aerogel EMI shielding composites by freeze-drying and carbonization. The results showed that the EMI $S\\mathrm{E_{T}}$ of the $\\mathrm{CF/rGO}$ aerogel EMI shielding composite reached $48~\\mathrm{dB}$ with the thickness of $5\\mathrm{mm}$ . In our previous research, Gu et al. [31] prepared annealed sugarcane (ACS) by hydrothermal method and annealing, followed by vacuum-assisted impregnation to prepare ASC/rGO aerogel EMI shielding composites. The results showed that the EMI $S\\mathrm{E_{T}}$ of $\\mathbf{ASC/rGO}$ aerogel EMI shielding composites reached $53\\mathrm{dB}$ with the thickness of $3\\mathrm{mm}$ . \n\nIn this paper, $\\mathrm{\\DeltaNaOH/}$ urea solution was used to dissolve cotton via hydrogen bond driving self-assembly to obtain cellulose solution and then CA was prepared by combining gelatinization, freeze-drying. The optimized CA was impregnated into GO solution, freeze-dried to produce $\\mathrm{CA}@$ GO aerogel with GO loaded on CA backbone, then carbonized at high temperature to produce $\\mathrm{CCA@rGO}$ aerogel with rGO loaded on CCA backbone and finally backfilled with PDMS to produce CCA $@$ rGO/PDMS EMI shielding composites. On this basis, the effects of CCA and rGO loading on the electrical conductivities, EMI SE, thermal conductivities, mechanical and thermal properties of $\\mathrm{CCA@rGO}/$ PDMS EMI shielding composites were investigated. \n\n# 2  \u0007Experimental \n\n# 2.1  \u0007Preparation of CA \n\nNaOH/urea solution was used to dissolve the cotton by hydrogen bond driving self-assembly to obtain the cellulose solution. The process was described below. The NaOH/urea solution (NaOH/urea/water $=7/12/81$ , wt/wt/wt) was first prepared and pre-cooled to $0~^{\\circ}\\mathrm{C}$ . An appropriate amount of dried cotton was then weighed and immersed in the precooled solution (cotton/pre-cooled solution $=1/99$ , 2/98, 3/97, 4/96 and 5/95, wt/wt) and mechanically stirred in an ice bath $(0^{\\circ}\\mathrm{C})$ for $48\\mathrm{h}$ to obtain the cellulose solution, and the corresponding solution concentrations were $1\\mathrm{wt}\\%$ , 2 $\\mathrm{wt}\\%$ , $3\\mathrm{\\wt}\\%$ , $4\\mathrm{wt}\\%$ and $5\\mathrm{wt}\\%$ , respectively. The cellulose hydrogel was obtained by adding a certain amount of cellulose solution to a three-necked flask equipped with a condensing unit and heating to $70~^{\\circ}\\mathrm{C}$ for $24\\mathrm{~h~}$ . The cellulose hydrogel was soaked in deionized water, changed at $12\\mathrm{~h~}$ intervals to $\\mathrm{pH}=7$ and frozen in liquid nitrogen $(-56^{\\circ}\\mathrm{C})$ and freeze-dried for $72\\mathrm{{h}}$ to obtain cellulose aerogel (CA). \n\n# 2.2  \u0007Preparation of CCA $@$ rGO/PDMS \n\nGO was prepared by modified Hummers method, and a range of GO solutions at different concentrations (2.5, 5, \n\n7.5 and $10~\\mathrm{{mg}~\\mathrm{{mL^{-1}}}}$ ) were configured. The $\\operatorname{CA@GO}$ was prepared by impregnating the pre-prepared CA into the above aqueous GO solution, evacuating until no air bubbles emerged, then freezing $(-56^{\\circ}\\mathrm{C})$ and freeze-drying for $^{72\\mathrm{~h~}}$ to obtain $\\operatorname{CA@GO}$ with GO loaded on the CA backbone. After carbonization at $1500^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ under nitrogen atmosphere, $\\operatorname{CCA@rGO}$ with rGO supported on the CCA framework was obtained. The prepared $\\operatorname{CCA}\\ @\\operatorname{rGO}$ foam has excellent flexibility and can withstand bending deformations up to $180^{\\circ}\\mathrm{C}$ (Fig. 1b). It also has excellent mechanical load-bearing performance and resilience. It can load $500~\\mathrm{g}$ weights, and the original shape can be restored immediately after the weights are removed (Fig. 1c-c’’). \n\nWeigh a certain amount of PDMS and n-hexane (PDMS/n-hexane ${\\it\\Omega}=1/2$ , vol/vol), and mechanically stir at room temperature for $30\\mathrm{min}$ to obtain the PDMS/n-hexane solution. The $\\mathrm{CCA@rGO}$ was placed in the mould and the portion of the PDMS/n-hexane solution was first poured into the mould and vacuum impregnated at room temperature until there were no bubbles. The PDMS/n-hexane solution was then poured into the mould and the vacuum impregnation was continued at room temperature until there were no bubbles. This was repeated until the $\\mathrm{PDMS/n}$ -hexane solution had completely submerged the $\\mathrm{CCA@rGO}$ and the temperature was raised to $65~^{\\circ}\\mathrm{C}$ for $^{4\\mathrm{h}}$ . The $\\mathrm{CCA@rGO/}$ PDMS EMI shielding composites were obtained by simple processing after natural cooling to room temperature. The schematic diagram is shown in Fig. 1a. \n\nAt the same time, $\\operatorname{CCA@rGO}$ was crushed to obtain $\\mathrm{P}(\\mathrm{CCA@rGO})$ . A series of $\\mathrm{P}(\\mathrm{CCA@rGO})/\\mathrm{PDMS}$ EMI shielding composites with the same amount of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ as the CCA@rGO/PDMS EMI shielding composites were prepared by controlling the amount of $\\mathrm{P}(\\mathrm{CCA@rGO})$ added. The prepared CA was carbonized at $1500~^{\\circ}\\mathrm{C}$ under nitrogen atmosphere for $^{2\\mathrm{~h~}}$ to obtain cellulose carbon aerogel (CCA). The same PDMS casting process was adopted to obtain CCA/PDMS EMI shielding composites \n\n# 3  \u0007Results and Discussion \n\n# 3.1  \u0007Characterization on CA, CCA, CA@GO and CCA@rGO \n\nFigure S1a illustrates the thermogravimetric analyses curves of CA and CCA. It can be seen that CA has a significant thermal weight loss process from 200 to $400~^{\\circ}\\mathrm{C}$ , and the residual carbon rate at $1000~^{\\circ}\\mathrm{C}$ is $5.4\\%$ , which is mainly attributed to the low thermal stability of CA due to the rich hydrogen and oxygen elements in the cellulose molecular chains inside CA. In contrast, CCA has no significant thermal weight loss, with a residual carbon percentage of $98.6\\%$ at $1000^{\\circ}\\mathrm{C}$ . This is mainly attributed to the fact that after carbonization at $1500^{\\circ}\\mathrm{C}$ , CCA removes most of the oxygencontaining functional groups and has a very high degree of carbonization. Figure S1b shows the Fourier transform infrared spectroscopy (FTIR) spectra of CA and CCA. It can be seen that in the FTIR spectra of CA, 3358, 2903, 1470\\~1320, 1450, 1173 and $1058\\mathrm{cm}^{-1}$ are the vibrational peaks of $\\mathrm{O-H}$ , C–H, C–H, $\\scriptstyle{\\mathrm{C=O}}$ , C–O–H and C–O–C, respectively. In contrast, in the FTIR spectra of CCA, the characteristic absorption peaks of the above functional groups almost all disappear, mainly attributed to the chemical inertness of CCA, which makes it show almost no characteristic absorption peaks. Figure S1c shows the X-ray diffraction (XRD) spectra of CA and CCA. We can see that the main diffraction peaks of CA appear at $14.7^{\\circ}$ (101), $16.7^{\\circ}$ (101) and $22.5^{\\circ}$ (002), which are characteristic diffraction peaks of type I cellulose [32]. The main diffraction peaks of CCA appear at $23.5^{\\circ}$ (002) and $43.8^{\\circ}$ (100), which are formed by the specific reflection of graphitic carbon on the (002) and (100) planes and are mainly attributed to the high-temperature carbonization of CA into CCA containing graphitic carbon. Figure S1d shows the Raman spectra of CA and CCA. The D peak (1340 $\\mathrm{cm}^{-1}$ ), G peak ( $1590\\mathrm{cm}^{-1},$ and 2D peak $(2500{\\sim}3000\\mathrm{cm}^{-1})$ correspond to the defective/disordered carbon, the tangential planar stretching vibration peak of $s p^{2}$ -hybridized carbon and the characteristic peak of graphitic carbon, respectively. The Raman spectrum of CA only has the G peak, which is attributed to the regularity of the cellulose network within CA. The Raman spectrum of CCA contains both D and G peaks, which is attributed to the production of irregular graphitic carbon in CCA during the high-temperature carbonization. In addition, the Raman spectrum of CCA also shows a 2D peak, which further evidence of the production of graphitic carbon. Figure S1e shows the X-ray photoelectron spectroscopy (XPS) spectrum of CA and CCA. Both CA and CCA have obvious C 1s $(284.0\\mathrm{eV})$ and O 1s $(530.0\\mathrm{eV})$ ) peaks. The C \n\n![](images/86c54481c8f4b733fef7c0ee31cf1f087ce0e969ca32415ef42b85e61f8d5dae.jpg) \nFig. 1   Schematic illustration of the fabrication procedure for CCA $@$ rGO/PDMS EMI shielding composites (a), illustration of the flexibility (b) and resilience $(\\mathbf{c-c}^{,9})$ of $\\operatorname{CCA@rGO}$ aerogel \n\n1s peak of CA is weaker and the O 1s peak is stronger, with a C/O ratio of 1.61. Compared to CA, the C 1s peak of CCA is more intense and the O 1s peak is less intense, with a corresponding increase in C/O ratio to 13.90. This is mainly due to the gradual removal of oxygen-containing functional groups and the carbonization of the cellulose molecular chains under high-temperature conditions. In addition, the three characteristic peaks in the high-resolution C 1s spectra of CA and CCA (Fig. S1e’) are $284.6\\mathrm{~eV}$ $(\\mathrm{sp}^{2}\\mathrm{C}\\mathrm{-sp}^{2}\\mathrm{C})$ , $285.6\\mathrm{eV}$ $(\\mathrm{sp}^{3}\\mathrm{C}\\mathrm{-}\\mathrm{sp}^{3}\\mathrm{C})$ and $287\\mathrm{eV}$ $\\scriptstyle(\\mathbf{=}\\mathbf{0})$ ), respectively. Compared to CA, the characteristic peaks of $\\mathrm{sp}^{2}\\mathrm{C}\\mathrm{-}\\mathrm{sp}^{2}\\mathrm{C}$ and $\\mathrm{sp}^{3}\\mathrm{C}\\mathrm{-}\\mathrm{sp}^{3}\\mathrm{C}$ of CCA are enhanced, while the characteristic peak of $\\scriptstyle{\\mathrm{C=O}}$ is weakened, mainly attributed to the high-temperature removal of most of the $\\scriptstyle{\\mathrm{C=O}}$ and conversion to graphitic carbon [33]. Figure S2 further supports the removal of oxygen-containing functional groups on CCA. \n\nFigure 2a shows the FTIR spectra of CA, $\\operatorname{CA@GO}$ and $\\mathrm{CCA@rGO}$ . In the FTIR spectra of CA, $3358~\\mathrm{cm^{-1}}$ is the stretching vibration peak of $\\mathrm{O-H}$ , $2903~\\mathrm{cm}^{-1}$ is the stretching vibration peak of $\\mathrm{C-H}$ in $\\mathrm{CH}_{2}$ , $1470{\\sim}1320\\ \\mathrm{cm}^{-1}$ is the bending vibration peak of $\\mathrm{C-H}$ , $1450~\\mathrm{cm}^{-1}$ is the stretching vibration peak of $\\scriptstyle{\\mathrm{C=O}}$ , $1173~\\mathrm{cm}^{-1}$ is the stretching vibration peak of $\\mathrm{C-O-H}$ , and $1058~\\mathrm{{cm}^{-1}}$ is the C–O–C stretching vibration peak. In the FTIR spectra of $\\operatorname{CA@GO}$ , in addition to the characteristic peaks mentioned above, a stretching vibration peak of $0-C=0$ at $1652~\\mathrm{cm}^{-1}$ appears, attributed to the introduction of GO [34]. In contrast, in the FTIR spectra of $\\mathrm{CCA@rGO}$ , these functional groups almost completely disappear, mainly due to the fact that $\\mathrm{CCA@rGO}$ is chemically inert so that it shows almost no characteristic absorption peaks. Figure 2b shows the Raman spectra of CA, CA@GO and CC $\\operatorname{\\mathrm{:A@rGO}}$ . Only the G peak is present in the Raman spectrum of CA, which is attributed to the regularity of the cellulose network within CA. A faint D peak starts to appear in the Raman spectrum of $\\operatorname{CA@GO}$ , which is attributed to the irregular graphitic carbon structure in $\\mathbf{CA@GO}$ due to the introduction of GO [28]. The Raman spectrum of $\\operatorname{CCA@rGO}$ contains D peaks, G peaks and 2D peaks, and the D peaks are stronger than the G peaks. This is mainly attributed to the irregular graphitic carbon produced by CCA during the carbonization. At the same time, GO is reduced to rGO by thermal annealing, resulting in a large amount of irregular graphitic carbon structure in $\\operatorname{CCA@}$ rGO. Figure 2c shows the XPS spectra of CA, $\\mathbf{CA@GO}$ and $\\mathrm{CCA@rGO}$ . The C 1s $(284.0\\mathrm{eV})$ and O 1s $(530.0\\mathrm{eV})$ peaks are evident in CA, $\\mathbf{CA@GO}$ and $\\operatorname{CCA}\\ @\\operatorname{r}\\mathrm{GO}$ . The C 1s peaks are weaker and the O 1s peaks are stronger in CA and CA@GO. Compared to CA and CA $\\iota\\ @\\mathbf{G}\\mathbf{O}$ , CCA@rGO has a significantly higher C 1s peak intensity and a significantly lower O 1s peak intensity, which is mainly attributed to the gradual removal of oxygen-containing functional groups, the carbonization of cellulose molecular chains and the reduction of GO to rGO under high-temperature conditions [35]. In addition, the high-resolution C 1s spectra of CA and $\\mathrm{CCA@rGO}$ (Fig. 2c’) have three characteristic peaks: 284.6 eV $(\\mathrm{sp}^{2}\\mathrm{C}\\mathrm{-sp}^{2}\\mathrm{C})$ , $285.6\\mathrm{eV}$ $(\\mathrm{sp}^{3}\\mathrm{C}\\mathrm{-}\\mathrm{sp}^{3}\\mathrm{C})$ and $287\\mathrm{eV}$ ( $\\scriptstyle(=0)$ , respectively. In contrast to CA, a new characteristic peak of $288.6\\mathrm{eV}$ appears in the high-resolution C 1s spectrum of $\\operatorname{CA@GO}$ , which is characteristic of $0-C=0$ in GO. Compared with $\\operatorname{CA@GO}$ , the characteristic peaks of $\\mathrm{sp}^{2}\\mathrm{C}\\mathrm{-}\\mathrm{sp}^{2}\\mathrm{C}$ and $\\mathrm{sp}^{3}\\mathrm{C}\\mathrm{-sp}^{3}\\mathrm{C}$ of $\\mathrm{CCA@rGO}$ are enhanced, the characteristic peak of $0{\\mathrm{-}}C{=}0$ disappears, and the characteristic peak of $\\scriptstyle{\\mathrm{C=O}}$ is very weak, which is mainly due to the removal of most of the $\\scriptstyle{\\mathrm{C=O}}$ by CCA and conversion to graphitic carbon and the reduction of GO to rGO [36]. \n\n![](images/9047ba1fbb412918a5c3963f33d13b33c9b7f3b93c1ef64714330c45cd309f7e.jpg) \nFig. 2   FTIR (a), Raman (b), XPS spectra (c) and high-resolution C 1s $(\\mathbf{c}^{\\dagger})$ of CA, CA@GO and CCA@rGO \n\n# 3.2  \u0007Morphologies of CA, CCA, CCA@rGO and CCA $@$ rGO/PDMS \n\nFigure 3 shows SEM images of the CA, CCA, CCA@rGO and CCA@rGO/PDMS EMI shielding composites. Figure 3a shows that the CA is a kind of 3D aerogel made of cellulose fibers entwined with each other, and the individual fibers have the relatively regular circular rodlike structure with the diameter of approximately $12\\upmu\\mathrm{m}$ . When the mass ratio of cotton to pre-cooled solution is 4:96, CCA is the 3D carbon aerogel formed by fibers lapping onto each other. But unlike CA, the single fibers of CCA have the twisted twist-like structure and are approximately $6~{\\upmu\\mathrm{m}}$ in diameter (Fig. 3b), which is mainly attributed to the removal of oxygen-containing functional groups and the carbonization of the cellulose. When the mass ratio of cotton to pre-cooled solution is 5:95, the tangling of fibers within the CCA is more severe (Fig. 3b’). This is due to the limited solubility of the NaOH/urea solution on the cotton, resulting in the tangling of fibers within the CCA. As shown in Fig. 3c, when the GO solution concentration is $7.5~\\mathrm{mg~mL^{-1}}$ , the $\\mathrm{CCA@}$ rGO is the homogeneous network structure, with the CCA forming the main framework of the C $\\mathrm{\\Sigma{TA@rGO}}$ and the rGO lamellae completely wrapping the fibers, forming the skincore structure similar to that of a cable. The $\\operatorname{rGO}$ is similar to the skin and is densely wrapped around the CCA fibers to provide sufficient structural stability for $\\mathrm{CCA@rGO}$ . The CCA is similar to the core and is wrapped by rGO sheets to provide attachment points and support for the rGO sheets. When the GO solution concentration is $10\\mathrm{{mg}\\mathrm{{mL}^{-1}}}$ , rGO is agglomerated in $\\mathrm{CCA@rGO}$ , CCA is not uniformly wrapped and C $\\operatorname{CA@rGO}$ has an uneven network structure (Fig. 3c’). This is due to the high viscosity of the GO solution, which limits its diffusion inside the CA and eventually leads to the agglomeration of rGO in the CCA. After backfilling with PDMS, the skin-core structure of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ is well preserved, and the 3D double-layer conductive network structure of $\\mathrm{CCA@rGO}$ is not significantly damaged (Fig. 3d), and PDMS is more uniformly dispersed in the gaps of the 3D conductive network of $\\mathrm{CCA@rGO}$ . At the same time, PDMS is uniformly dispersed in the gaps of the 3D conducting network of CCA $\\ @\\mathrm{rGO}$ . \n\n![](images/e6c962174ed5658e3d435366fb7f7eaf931287cc290432bf47003440ceece147.jpg) \nFig. 3   SEM images of CA (a), CCA (b-b’), CCA@rGO (c-c’) and the CCA $@$ rGO/PDMS EMI shielding composites (d) \n\n# 3.3  \u0007Electrical Conductivities and EMI Shielding Performances \n\nFigure 4a shows the $\\sigma$ of PCCA/PDMS and CCA/PDMS EMI shielding composites. It can be seen that the $\\sigma$ of PCCA/PDMS EMI shielding composites shows a gradual increase with the increase in the amount of PCCA. When the loading of PCCA is $2.80\\mathrm{wt}\\%$ , the $\\sigma$ of the PCCA/PDMS EMI shielding composites reaches $0.094~\\mathrm{S~cm^{-1}}$ . This is mainly due to the fact that the conductive network inside the PCCA/PDMS EMI shielding composites is gradually improved with the increase in PCCA. As the loading of CCA increases, the $\\sigma$ of the CCA/PDMS EMI shielding composites tends to increase and then decrease. When the loading of CCA is $2.24~\\mathrm{wt}\\%$ , the CCA/PDMS EMI shielding composites have the largest $\\sigma$ value $(0.47\\mathrm{S}\\mathrm{cm}^{-1},$ . This is mainly attributed to the gradual improvement of the CCA–CCA conductive network within the CCA/PDMS EMI shielding composites with increasing CCA loading [37]. However, the further increase in the amount of CCA causes the fibers within the CCA to twist into knots, which is detrimental to the formation of the complete conductive pathway and thus has negative impact on the $\\sigma_{\\cdot}$ . In addition, the $\\sigma$ of the $\\mathrm{CCA}/$ PDMS EMI shielding composites is consistently much larger than that of the PCCA/PDMS EMI shielding composites for the same amount of CCA or PCCA [38]. At a CCA loading of $2.24\\ \\mathrm{wt}\\%$ , $\\sigma$ for the CCA/PDMS EMI shielding composites $(0.47\\mathrm{S}\\mathrm{cm}^{-1}),$ ) is 6.3 times greater than that of the PCCA/ PDMS EMI shielding composites $(0.075\\mathrm{~S~cm^{-1}},$ ) with the same loading of PCCA. Mainly due to the random distribution of PCCA in the PCCA/PDMS EMI shielding composites, which is difficult to form the effective PCCA–PCCA conductive network. Within the CCA/PDMS EMI shielding composites, CCA has the more complete 3D conductive network structure, giving it an even better $\\sigma$ . \n\n![](images/c183d5663242c3cd16379a6dc3c31fc4beeeb11b58dc467ba7add035b1ed9a50.jpg) \nFig. 4 $\\sigma$ of the PCCA/PDMS and CCA/PDMS EMI shielding composites (a) and P(CCA@rGO)/PDMS and CCA@rGO/PDMS EMI shielding composites ${\\bf(b)}$ \n\nFigure 4b shows the $\\sigma$ comparison diagram of $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@$ rGO)/PDMS and CCA@rGO/PDMS EMI shielding composites. It can be seen that the $\\sigma$ of the $\\mathrm{P(CCA@rGO)/PDMS}$ EMI shielding composites tends to increase as the loading of $\\mathrm{P}(\\mathrm{CCA@rGO})$ increases. The $\\sigma$ of the $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})/$ PDMS EMI shielding composites reaches $0.117\\mathrm{~S~cm}^{-1}$ at a $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})$ loading of $3.32~\\mathrm{wt}\\%$ , mainly due to the gradual improvement of the conductive network inside the P(CCA@rGO)/PDMS EMI shielding composites with the increasing $\\mathrm{P}(\\mathrm{CCA@rGO})$ loading. With the increase in the loading of $\\mathrm{CCA@rGO}$ , the $\\sigma$ of the CCA@rGO/PDMS EMI shielding composites tends to increase and then decrease [39]. When the loaidng of $\\operatorname{CCA@rGO}$ is $3.05\\ \\mathrm{wt}\\%$ , the CCA $@$ rGO/PDMS EMI shielding composites have the largest $\\sigma$ value $(0.75\\mathrm{~S~cm}^{-1},$ ), which is $59.6\\%$ higher than the $\\sigma$ $(0.47\\mathrm{S}\\mathrm{cm}^{-1},$ ) of the CCA/PDMS EMI shielding composites $(2.24\\ \\mathrm{wt}\\%$ CCA). This is mainly due to the fact that the rGO wrapped around the CCA gradually forms the second conductive network as the amount of rGO increases based on the first conductive network $(2.24~\\mathrm{wt}\\%$ CCA). The synergy of the two conductive networks results in the gradual improvement of the internal conductive network of the $\\operatorname{CCA@}$ rGO/PDMS EMI shielding composites and the consequent increase in its $\\sigma$ [40]. However, as the amount of rGO increases further, the rGO is prone to agglomeration inside the CC $\\mathbf{A}@\\mathbf{rGO}$ and the CCA is not uniformly wrapped, resulting in an imperfect second conductive network, which has negative impact on the $\\sigma$ . It can also be seen that the $\\sigma$ of the CCA@rGO/PDMS EMI shielding composites is consistently much greater than that of the $\\mathrm{P}(\\mathrm{CCA}@\\mathrm{rGO})/\\mathrm{PDMS}$ EMI shielding composites for the same loading of $\\mathrm{CCA@}$ rGO and $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})$ . When the loading of $\\mathrm{CCA@rGO}$ is $3.05\\ \\mathrm{wt}\\%$ , the $\\sigma$ of the CCA@rGO/PDMS EMI shielding composites $(0.75\\mathrm{{Scm}^{-1})}$ ) is 7.1 times higher than that of the $\\mathrm{P}(\\mathrm{CCA@rGO})$ )/PDMS EMI shielding composites (0.106 S $\\mathrm{cm}^{-1}.$ ) with the same loading of $\\mathrm{P}(\\mathrm{CCA@rGO})$ . Mainly due to the random distribution of $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})$ in the $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@$ rGO)/PDMS EMI shielding composites, which makes it difficult to form an effective $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})$ - $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})$ conductive network through point–point laps [41]. In the CCA@rGO/PDMS EMI shielding composites, the $\\mathrm{CCA@}$ rGO has the more complete 3D conductive network. At the same time, the rGO sheet is wrapped around the CCA fibers to form the double-layer conductive network with the skin-core structure. The CCA–CCA (wire–wire), CCA–rGO (wire–surface) and rGO–rGO (surface–surface) laps form the very complete 3D double-layer conductive network, giving it an even better $\\sigma$ . \n\nFigure 5 shows the comparison graph of the EMI shielding effectiveness (EMI SE) results of PCCA/PDMS, CCA/ PDMS, $\\mathrm{P(CCA@rGO)/PDMS}$ and CCA@rGO/PDMS EMI shielding composites. As shown in Fig. 5a, the EMI $S\\mathrm{E_{T}}$ of the PCCA/PDMS EMI shielding composites tends to increase as the loading of PCCA increases. When the loading of PCCA is $2.80~\\mathrm{wt}\\%$ , the EMI $S\\mathrm{E_{T}}$ of the PCCA/ PDMS EMI shielding composites is 12 dB. This is mainly due to the PCCA–PCCA conductive network within the PCCA/PDMS EMI shielding composites gradually improving with increasing PCCA loading, resulting in an increased ability to reflect and absorb incident electromagnetic waves, which is reflected in the increase in EMI $S\\mathrm{E_{T}}$ value [42]. Figure 5b shows that as the loading of CCA increases, the EMI $S\\mathrm{E_{T}}$ of the CCA/PDMS EMI shielding composite material first increases and then decreases. When the loading of CCA is $2.24\\mathrm{wt}\\%$ , the CCA/PDMS EMI shielding composites have the best EMI $S\\mathrm{E_{T}}$ $(40\\mathrm{dB})$ , which is 20 times than that of pure PDMS (2 dB). This is because the density of the CCA–CCA conductive network within the CCA/PDMS EMI shielding composites increases as the amount of CCA increases [43]. At the same time, the two-phase interface with the PDMS matrix increases, resulting in enhanced conductive losses, impedance mismatch and interfacial polarization losses between the incident electromagnetic waves and the CCA–CCA conductive network, thus significantly improving the EMI $S\\mathrm{E_{T}}$ of the CCA/PDMS EMI shielding composite [44]. However, when the amount of CCA is too high, the fibers in CCA tend to twist into knots, which reduces the conductive network density of CCA and reduces the two-phase interface between CCA and PDMS substrate, thus reducing its EMI $S\\mathrm{E_{T}}$ . As shown in Fig. 5c, the EMI $\\mathrm{SE_{T}}$ of the $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})$ )/PDMS EMI shielding composites tends to increase gradually as the loading of $\\mathrm{P}(\\mathrm{CCA@rGO})$ increase. The EMI $S\\mathrm{E_{T}}$ of $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})/$ PDMS EMI shielding composites is $14~\\mathrm{dB}$ when the loading of $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@\\mathbf{r}\\mathbf{G}\\mathbf{O})$ is $3.32~\\mathrm{wt}\\%$ . This is mainly due to the gradual improvement of the conductive network inside the $\\mathrm{P}(\\mathrm{CCA@rGO})/\\mathrm{PDMS~}]$ EMI shielding composites with the increase in the loading of $\\mathrm{P}(\\mathrm{CCA}@\\mathrm{rGO})$ , which leads to the enhancement of its ability to reflect and absorb the incident electromagnetic waves, manifested in the increase in the EMI $S\\mathrm{E_{T}}$ [45, 46]. Figure 5d shows that the EMI $S\\mathrm{E_{T}}$ of CCA@rGO/PDMS EMI shielding composites tend to increase and then decrease as the loading of $\\mathrm{CCA@rGO}$ increase. When the loading of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ is $3.05\\ \\mathrm{wt}\\%$ , the CCA $@$ rGO/PDMS EMI shielding composites have the best EMI $S\\mathrm{E_{T}}$ (51 dB), which is $27.5\\%$ higher than the EMI $S\\mathrm{E_{T}}$ (40 dB) of the CCA/PDMS EMI shielding composites $(2.24\\ \\mathrm{wt}\\%$ CCA) and 25.5 times higher than that of the pure PDMS (2 dB). This is because as the amount of $\\mathrm{CCA@rGO}$ increases, the CCA (first conductive network) wrapped with rGO gradually forms the perfect second conductive network, and the skin-core structure of $\\operatorname{CCA@rGO}$ makes the two conductive networks work together to form the perfect 3D double-layer conductive network [47]. At the same time, the interfaces between rGO and CCA, rGO and $\\mathrm{rGO}$ , and $\\mathrm{CCA@rGO}$ and PDMS matrix are increased, so that the conductive loss, impedance mismatch and interface polarization loss between CCA@rGO/PDMS EMI shielding composite and incident electromagnetic waves are enhanced, which significantly improves the EMI $S\\mathrm{E_{T}}$ of CCA@rGO/PDMS EMI shielding composites. However, when the loading of $\\mathrm{rGO}$ is too high, rGO tends to agglomerate in $\\mathbf{CCA@rGO}$ , resulting in an imperfect second conductive network and reducing the conductive network density. At the same time, it reduces the two-phase interface between $\\mathrm{CCA@rGO}$ and PDMS matrix, which adversely affects the EMI $S\\mathrm{E_{T}}$ of CCA $@$ rGO/PDMS EMI shielding composites [48]. \n\n![](images/62c10d9367770dd1eec6a4c6b9bd0960737c70e4ab41541ef74e45ba566091d1.jpg) \nFig. 5   EMI $\\mathrm{SE_{T}}$ of the PCCA/PDMS EMI shielding composites (a), EMI $\\mathrm{SE_{T}}$ of the CCA/PDMS EMI shielding composites ${\\bf(b)}$ , EMI $\\mathrm{SE_{T}}$ of the $\\mathrm{P}(\\mathrm{CCA@rGO})$ )/PDMS EMI shielding composites (c), EMI $S\\mathrm{E_{T}}$ (d), EMI $S\\mathrm{E_{A}}$ and $S\\mathrm{E_{R}}$ $(\\mathbf{d}^{\\prime})$ of the CCA $@$ rGO/PDMS EMI shielding composites, schematic illustration of EMI shielding mechanism (e) \n\nCombining Fig. 5c, d also shows that the EMI $S\\mathrm{E_{T}}$ of CCA@rGO/PDMS EMI shielding composites is always better than that of $\\mathrm{P}(\\mathrm{CCA}@\\mathrm{rGO})/\\mathrm{PDMS}$ EMI shielding composites at the same $\\operatorname{CCA@rGO}$ and $\\mathrm{P}(\\mathrm{CCA@rGO})$ loading. When the amount of $\\operatorname{ccA@rGO}$ is $3.05\\ \\mathrm{wt}\\%$ , the EMI $S\\mathrm{E_{T}}$ of CCA $@$ rGO/PDMS EMI shielding composites is 51 dB, which is 3.9 times higher than that of $\\mathrm{P(CCA@rGO)/PDMS}$ EMI shielding composites $(13\\ \\mathrm{dB})$ with the same loading of filler. This is because the conductive fillers in $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@$ rGO)/PDMS EMI shielding composites are randomly distributed, and the efficiency of lap bonding through $\\operatorname{P}(\\mathbf{C}\\mathbf{C}\\mathbf{A}@$ rGO)-P $\\mathsf{\\Pi}^{\\prime}(\\mathrm{CCA@rGO})$ (point–point) is extremely low [49]. At the same time, $\\mathrm{P}(\\mathrm{CCA@rGO})$ has high surface energy and are prone to agglomeration within the PDMS matrix, which makes it difficult to form an effective conductive network, thus affecting the reflectivity and dissipation ability of the P(CCA@rGO)/PDMS EMI shielding composites for incident electromagnetic waves, and therefore, its EMI $S\\mathrm{E_{T}}$ enhancement effect is poor [50]. For the $\\mathrm{CCA@rGO/}$ PDMS EMI shielding composites, the skin-core structure allows $\\mathrm{CCA@rGO}$ to form the 3D double-layer conductive network structure with a high conductive network density, which enhances the conductive loss and impedance mismatch between the incident electromagnetic waves and the CCA@rGO/PDMS EMI shielding composites (Fig. 5e). Meanwhile, the introduction of rGO leads to more twophase interfaces between rGO and CCA, rGO and rGO, and $\\mathrm{CCA@rGO}$ and PDMS matrix, which significantly improves the interfacial polarization loss capability of $\\mathrm{CCA@rGO/}$ PDMS EMI shielding composites to incident electromagnetic waves [51]. The synergistic effect of the two aspects makes the $\\mathbf{CCA@rGO/PDMS~E}$ MI shielding composites have relatively stronger reflection, scattering and absorption of incident electromagnetic waves, so that their EMI $S\\mathrm{E_{T}}$ is consistently better than that of $\\mathrm{P(CCA@rGO)/PDMS}$ and CCA@rGO/PDMS EMI shielding composites [52]. \n\nFigure  5d’ shows that the EMI $S\\mathrm{E_{A}}$ and EMI $S\\mathrm{E_{R}}$ of CCA@rGO/PDMS EMI shielding composites also tend to increase and then decrease as the loading of $\\mathrm{CCA@rGO}$ increases. When the loading of $\\mathrm{CCA@rGO}$ is $3.05\\ \\mathrm{wt}\\%$ , the EMI $S\\mathrm{E_{R}}$ and EMI $\\mathrm{\\DeltaSE_{A}}$ of CCA $@$ rGO/PDMS EMI shielding composites reach the maximum values of $7~\\mathrm{dB}$ and 44 dB, respectively. This is because the continuous increase in $\\operatorname{CCA@rGO}$ provides more mobile charge, which enhances the impedance mismatch between the $\\mathrm{CCA}@\\mathrm{rGO/PDMS}$ EMI shielding composites and the incident electromagnetic wave, hence the EMI $S\\mathrm{E_{R}}$ increase [53]. Meanwhile, the $\\mathbf{CCA@rGO-CCA@rGO}$ double-layer conductive network is gradually improved with the increase in $\\mathrm{CCA@rGO}$ loading, which can provide more carriers for dissipating electromagnetic waves, so its EMI $S\\mathrm{E_{A}}$ is improved [54]. However, as the loading of $\\mathrm{CCA@rGO}$ increases further, rGO tends to agglomerate inside $\\operatorname{CCA}\\ @\\operatorname{rGO}$ and CCA is not uniformly wrapped, reducing the internal conductive network density of CCA@rGO/PDMS EMI shielding composites and decreasing the two-phase interface between $\\mathrm{CCA@rGO}$ and PDMS matrix [55]. This weakens the ability of the $\\mathrm{CCA@}$ rGO/PDMS EMI shielding composite to reflect, scatter and absorb incident electromagnetic waves, resulting in lower EMI $S\\mathrm{E_{R}}$ and EMI $S\\mathrm{E_{A}}$ . \n\n# 3.4  \u0007Thermal Conductivities \n\nFigure 6 shows the $\\lambda$ (a), thermal diffusivity $(\\alpha,\\mathfrak{b})$ , 3D infrared thermal images (c) and surface temperature curves vs heating time (d) of the CCA@rGO/PDMS EMI shielding composites. Figure 6a, b shows that $\\lambda$ and $\\alpha$ of $\\mathrm{CCA@}$ rGO/PDMS EMI shielding composites both tend to increase and then decrease as the amount of $\\operatorname{CCA}@\\operatorname{rGO}$ increases. When the loading of $\\operatorname{CCA@rGO}$ is $3.05~\\mathrm{wt}\\%$ , the $\\operatorname{CCA@}$ rGO/PDMS EMI shielding composites have the largest $\\lambda$ $(0.65\\mathrm{W}\\mathrm{mK}^{\\-1})$ and $\\alpha$ $(1.082\\mathrm{mm}^{2}\\mathrm{s}^{-1})$ , which are 3.3 and 3.4 times higher than $\\lambda(0.20\\mathrm{W}\\mathrm{mK}^{\\mathrm{-1}})$ and $\\alpha(0.3185\\mathrm{mm}^{2}\\mathrm{s}^{-1})$ of pure PDMS. This is because, as the loading of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ increases, rGO gradually wraps the CCA fibers to form the 3D double-layer thermal conductivity network with the skincore structure, which improves the thermal conductivities of CCA@rGO/PDMS EMI shielding composites. However, as the amount of $\\mathrm{CCA@rGO}$ increases further, the internal rGO of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ tends to agglomerate, which reduces the density of the thermal conductivity network inside the CCA@rGO/PDMS electromagnetic shielding composites [56, 57]. However, with the further increase in the loading of $\\mathrm{CCA@rGO}$ , the rGO inside $\\mathbf{CCA@rGO}$ tends to agglomerate, which decreases the density of the thermal conductivity network inside the CCA $@$ rGO/PDMS EMI shielding composites, thus adversely affecting the $\\lambda$ and $\\alpha$ of the CCA/ PDMS EMI shielding composites [58]. \n\nAs shown in Fig. 6c, the heat flow conduction rate is significantly higher inside the CCA@rGO/PDMS EMI shielding composites compared to the CCA/PDMS EMI shielding composites for the same temperature thermal stage and heating time, indicating their excellent thermal conductivities [59]. Meanwhile, with the increase in the amount of $\\mathrm{CCA@}$ rGO, the heat flow conduction rate inside the $\\mathrm{CCA@rGO}/$ PDMS EMI shielding composites becomes faster and then slower, indicating that the appropriate amount of $\\mathrm{CCA@}$ rGO $(3.05~\\mathrm{wt}\\%)$ is beneficial to further improving the thermal conductivities of the CCA@rGO/PDMS EMI shielding composites, which is consistent with the experimental results of Fig. 6a, b. In addition, the heat flow is uniformly conducted inside the $\\mathrm{CCA}@\\mathrm{rGO/PDMS~EMI}$ shielding composites, indicating the relatively uniform dispersion of CCA $@\\mathrm{rGO}$ in the CCA@rGO/PDMS EMI shielding composites (consistent with Fig. 3d). \n\n![](images/b3227bf79e79166bd922ed847e87a4211ffc8c20896674aed15b6959441e20b0.jpg) \nFig. 6   λ (a), $\\alpha$ (b), 3D infrared thermal images (c) and surface temperature curves vs heating time (d) of the CCA $@$ rGO/PDMS EMI shielding composites \n\nThe surface temperature change of the CCA@rGO/PDMS EMI shielding composites is divided into two stages as the heating time increases (Fig. 6d). The first stage is the 0 to 40 s heating time period, where the surface temperature of the CCA $@$ rGO/PDMS EMI shielding composite increases rapidly. This is mainly attributed to the low initial temperature of the CCA@rGO/PDMS EMI shielding composites, which causes the large temperature difference between them and the heat table, and therefore, the heat propagation rate is fast [60]. The second stage is the 40 to 80 s heating time period, where the surface temperature of the $\\mathrm{CCA@rGO}/$ PDMS EMI shielding composites increase slowly. This is mainly attributed to the fact that after 40 s of heating, the temperature of the CCA@rGO/PDMS EMI shielding composites start to increase and the temperature difference between them and the hot table are smaller, so the heat propagation rate become slower [61]. It is also observed that the heating rate of the surface temperature of the $\\mathbf{CCA@rGO}/$ PDMS EMI shielding composites tend to increase and then decrease in the first heating stage with the increase in the loading of $\\mathrm{CCA@rGO}$ . In the case of both heating times is $40\\mathrm{s}$ and the loading of $\\mathrm{CCA@rGO}$ is $3.05\\mathrm{wt}\\%$ , the surface temperature of $\\mathrm{CCA}@\\mathrm{rGO/PDMS}$ EMI shielding composites reach the maximum value of $89.2^{\\circ}\\mathrm{C}$ indicates that the appropriate $\\operatorname{CCA@rGO}$ $(3.05~\\mathrm{wt}\\%)$ is beneficial to efficiently enhance the thermal conductivities of $\\mathrm{CCA@rGO/}$ PDMS EMI shielding composites [62]. \n\n# 3.5  \u0007Mechanical Performances \n\nFigure 7 shows the stress–strain curves (a), tensile strength (b), elongation at break (c) and hardness (d) of the $\\mathrm{CCA@}$ rGO/PDMS EMI shielding composites. The tensile strength and elongation at break of the CCA $@$ rGO/PDMS EMI shielding composites show a decreasing trend with the increase in the loading of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ (Fig. 7a-c). When the loading of $\\mathrm{CCA@rGO}$ is $3.05\\ \\mathrm{wt}\\%$ , the tensile strength and elongation at break of CCA@rGO/PDMS EMI shielding composites are $4.1\\mathrm{MPa}$ and $77.3\\%$ , respectively, which are $36.9\\%$ and $35.6\\%$ lower than the tensile strength $(6.5\\mathrm{MPa})$ and elongation at break $(120\\%)$ of pure PDMS. It is mainly attributed to more two-phase interfaces (weak interfacial connections) between rGO and CCA, rGO and $\\operatorname{rGO}$ , and CCA $\\scriptstyle{\\mathcal{Q}}\\operatorname{rGO}$ and PDMS matrix with the increase in $\\mathrm{CCA@}$ rGO loading. It is easy to develop microcracks and voids inside the CCA@rGO/PDMS EMI shielding composites, resulting in the reduction of bond strength. When subjected to external forces, its internal defects will become stress concentration points and rapidly trigger the expansion and fracture of internal microcracks, thus reducing the tensile strength and elongation at break of CCA@rGO/PDMS EMI shielding composites. \n\n![](images/d354e31942d4f7ab08572d670e8c0ebdeb3ca2f807974ff9e6c1de6c71ec501b.jpg) \nFig. 7   Stress–strain curves (a), tensile strength ${\\bf(b)}$ , elongation at break (c) and hardness (d) of the CCA $@$ rGO/PDMS EMI shielding composites \n\nAs shown in Fig. 7d, the hardness of the $\\operatorname{CCA@rGO}/$ PDMS EMI shielding composites illustrates a gradual increase with the increase in the loading of $\\operatorname{CCA}\\ @\\operatorname{r}\\mathbf{GO}$ . When the loading of $\\operatorname{CCA@rGO}$ is $3.05\\ \\mathrm{wt}\\%$ , the hardness of CCA@rGO/PDMS EMI shielding composites reach 42 HA, which is $50\\%$ higher than that of pure PDMS $(28\\mathrm{HA})$ . This is mainly attributed to the fact that the network density of the rigid skeleton $\\operatorname{CCA@rGO}$ gradually increases with the loading of $\\operatorname{CCA}\\ @\\operatorname{rGO}$ , forming more hard twophase interfacial layers with the PDMS matrix, which effectively hinders the deformation of the CCA@rGO/PDMS \n\nEMI shielding composites under pressure, resulting in the increase in the hardness. \n\nFigure 8 shows the $\\sigma$ (a) and EMI $S\\mathrm{E_{T}}$ (b) results of $\\mathrm{CCA}@\\mathrm{rGO/PDMS~EM}$ I shielding composites after bending fatigue. The $\\sigma$ and EMI $S\\mathrm{E_{T}}$ of $\\mathrm{CCA}@\\mathrm{rGO/PDMS}$ EMI shielding composites show a slight decrease with the increase in the number of bending fatigues. When the bending fatigue reach 2000 times, the $\\sigma$ and EMI $S\\mathrm{E_{T}}$ of $\\mathrm{CCA@}$ rGO/PDMS EMI shielding composites are $0.745\\mathrm{Scm}^{-1}$ and 50 dB $(3.05\\mathrm{wt}\\%\\mathrm{CCA@rGO})$ , respectively, which were only $0.7\\%$ and $2.0\\%$ lower than the $\\sigma(0.75\\mathrm{Scm^{-1}})$ and EMI $S\\mathrm{E_{T}}$ (51 dB) of the $\\mathrm{CCA}@\\mathrm{rGO/PDMS}$ EMI shielding composites without bending fatigue, which indicates that the $\\mathrm{CCA@}$ rGO/PDMS EMI shielding composites have good bending fatigue resistance. \n\n# 3.6  \u0007Thermal Stabilities \n\nFigures 9a, b shows the DSC and TGA curves of the $\\mathrm{CCA@}$ rGO/PDMS EMI shielding composites, respectively, and Table 1 shows the corresponding thermal characteristic data. Figure 9a and Table 1 show that the $T_{g}$ of the $\\mathrm{CCA@}$ rGO/PDMS EMI shielding composites gradually increases with the increase in the loading of $\\mathrm{CCA@rGO}$ . When the loading of $\\mathbf{CCA@rGO}$ is $3.05~\\mathrm{wt}\\%$ , the $T_{g}$ of $\\mathrm{CCA@rGO}/$ PDMS EMI shielding composites is $-43.4^{\\circ}\\mathrm{C}$ , which is 5.7 $^{\\circ}\\mathrm{C}$ higher than that of pure PDMS. This is mainly attributed to the fact that the hard two-phase interfacial layer between $\\mathrm{CCA@rGO}$ and PDMS matrix increases with the increase in CCA $@$ rGO loading, which restricts the movement of PDMS molecular chains and makes $T_{g}$ increase [63]. As shown in \n\n![](images/268e24ba64659d1482f8de658318bfe02104a431d72ddd8e51820b66d7d76a28.jpg) \nFig. 8 $\\sigma$ (a) and EMI $S\\mathrm{E_{T}}$ (b) values of CCA $@$ rGO/PDMS EMI shielding composites after bending fatigue \n\n![](images/63b3d72e163c99aa30f3772fe09a6446cb4d2702784543fbceb176cc5ce4f861.jpg) \nFig. 9   DSC curves (a) and TGA curves ${\\bf(b)}$ of the CCA $@$ rGO/PDMS EMI shielding composites \n\nTable 1   Thermal characteristic data of the CCA@rGO/PDMS EMI shielding composites \n\n\n
SimplesT(C)Weight loss temperature (C) T5THRI* (C)
PDMS-49.1292.3362.5163.9
2.24 wt% CCA@rGO/ PDMS-46.3307.5381.3172.4
2.51wt%CCA@rGO/ PDMS-45.4310.2384.6173.9
2.78 wt% CCA@rGO/ PDMS-44.5313.4388.6175.7
3.05 wt% CCA@rGO/ PDMS-43.4318.1394.4178.3
3.32 wt% CCA@rGO/ PDMS-42.6321.6398.8180.3
\n\nThe sample’s heat resistance index is calculated by Eq. (1): $T_{H R I}=0.49\\ [T_{5}+0.6\\ (T_{30}-T_{5})]$ (Eq. (1)) $T_{5}$ and $T_{30}$ are corresponding decomposition temperature of $5\\%$ and $30\\%$ weight loss, respectively \n\nFig. 9b and Table 1, the $T_{5}$ , $T_{30}$ and the corresponding $T_{H R I}$ of the CCA@rGO/PDMS EMI shielding composites show a gradual increase with the increase in the C $\\mathrm{CA@rGO}$ loading. When the loading of CCA $@\\mathrm{rGO}$ is $3.05\\mathrm{wt}\\%$ , the $T_{5}$ , $T_{30}$ and the corresponding $T_{H R I}$ of the CCA $@$ rGO/PDMS EMI shielding composites are 318.1, 394.4 and $178.3^{\\circ}\\mathrm{C}$ , respectively. which are 25.8, 362.5 and $163.9^{\\circ}\\mathrm{C}$ higher than The $T_{5}$ , $T_{30}$ and $T_{H R I}$ of the pure PDMS (292.3, 362.5 and 163.9 ${}^{\\circ}\\mathbf{C}\\mathbf{\\Psi},$ ). It is mainly attributed to the fact that the introduction of rGO with excellent heat resistance can help improve the heat resistance of CCA@rGO/PDMS EMI shielding composites [64]. Meanwhile, the good interfacial compatibility between $\\mathrm{CCA@rGO}$ and PDMS matrix can effectively prevent the oxygen penetration and thermal degradation behavior of $\\operatorname{CCA}@\\operatorname{rGO}/\\operatorname{PDMS}\\ ]$ EMI shielding composites [65, 66]. The synergy of the two aspects leads to the significant improvement in the heat resistance of $\\mathrm{CCA}@\\mathrm{rGO/PDMS}$ EMI shielding composites compared to pure PDMS. \n\n# 4  \u0007Conclusions \n\nrGO was successfully wrapped on the surface of CCA to form $\\operatorname{CCA@rGO}$ with the 3D double-layer conductive network skin-core structure, and its 3D conductive network structure was not significantly damaged during backfilling with PDMS. When the loading of $\\mathrm{CCA@rGO}$ is 3.05 $\\mathrm{wt}\\%$ , CCA@rGO/PDMS EMI shielding composites have the best EMI $S\\mathrm{E_{T}}$ (51.0 dB). At this time, the $\\mathrm{CCA@rGO}/$ PDMS EMI shielding composites have outstanding thermal conductivities ( $\\lambda$ is $0.65\\mathrm{~W~mK^{-1}}.$ ), excellent mechanical properties (tensile strength and hardness are $4.1\\ \\mathrm{MPa}$ and $42\\mathrm{HA}$ , respectively) and excellent thermal stabilities $(T_{H R I}$ of $178.3\\ {^\\circ}\\mathrm{C}\\$ . Excellent EMI shielding performances and thermal stabilities, as well as good thermal conductivities, make CCA $@$ rGO/PDMS EMI shielding composites have great application prospects in lightweight, flexible electromagnetic shielding composites and portable and wearable electronic devices. \n\nAcknowledgments  This work is supported by the Foundation of National Natural Science Foundation of China (51773169 and 51973173); the Natural Science Basic Research Plan for Distinguished Young Scholars in Shaanxi Province of China (2019JC11); and the Natural Science Basic Research Plan in Shaanxi Province of China (2020JQ-164). Y.Q. Guo thanks the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (CX202055). This work is also financially supported by Polymer Electromagnetic Functional Materials Innovation Team of Shaanxi Sanqin Scholars. We would like to thank the Analytical & Testing Center of Northwestern Polytechnical University for Raman, XRD and SEM tests. \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\nSupplementary Information  The online version contains supplementary material available at https://​doi.​org/​10.​1007/ s40820-​021-​00624-4. \n\n# References \n\n1.\t B. Quan, W. Gu, J. Sheng, X. Lv, Y. Mao et  al., From intrinsic dielectric loss to geometry patterns: dual-principles strategy for ultrabroad band microwave absorption. Nano Res. 14, 1495–1501 (2021). https://​doi.​org/​10.​1007/ s12274-​020-​3208-8 \n2.\t H. Liu, S. Wu, C. You, N. Tian, Y. Li et  al., Recent progress in morphological engineering of carbon materials for electromagnetic interference shielding. Carbon 172, 569–596 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2020.​10.​067 \n3.\t Y. Wang, H. Wang, J. Ye, L. Shi, X. Feng, Magnetic CoFe alloy $@\\mathrm{C}$ nanocomposites derived from ZnCo-MOF for electromagnetic wave absorption. Chem. Eng. J. 383, 123096 (2020). https://​doi.​org/​10.​1016/j.​cej.​2019.​123096 \n4.\t J. Liu, Z. Liu, H.B. Zhang, W. Chen, Z. Zhao et al., Ultrastrong and highly conductive MXene-based films for high-performance electromagnetic interference shielding. Adv. Electron. Mater. 6(1), 1901094 (2019). https://​doi.​org/​10.​1002/​aelm. 20190​1094 \n5.\t K. Qian, H. Wu, J. Fang, Y. Yang, M. Miao et al., Yarn-ballshaped CNF/MWCNT microspheres intercalating $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene for electromagnetic interference shielding films. Carbohydr. Polym. 254, 117325 (2021). https://​doi.​org/​10. 1016/j.​carbp​ol.​2020.​117325 \n6.\t J. Zhang, Z. Yan, X. Liu, Y. Zhang, H. Zou et al., Conductive skeleton–heterostructure composites based on chrome shavings for enhanced electromagnetic interference shielding. ACS Appl. Mater. Interfaces 12(47), 53076–53087 (2020). https://​doi.​org/​10.​1021/​acsami.​0c143​00 \n7.\t G. Han, Z. Ma, B. Zhou, C. He, B. Wang et al., Cellulosebased Ni-decorated graphene magnetic film for electromagnetic interference shielding. J. Colloid Interface Sci. 583, 571–578 (2021). https://​doi.​org/​10.​1016/j.​jcis.​2020.​09.​072 \n8.\t Y. Jia, T.D. Ajayi, B.H. Wahls, K.R. Ramakrishnan, S. Ekkad et al., Multifunctional ceramic composite system for simultaneous thermal protection and electromagnetic interference shielding for carbon fiber-reinforced polymer composites. ACS Appl. Mater. Interfaces 12(52), 58005–58017 (2020). https://​doi.​org/​10.​1021/​acsami.​0c173​61 \n9.\t N. Yousefi, X. Sun, X. Lin, X. Shen, J. Jia et  al., Highly aligned graphene/polymer nanocomposites with excellent dielectric properties for high-performance electromagnetic interference shielding. Adv. Mater. 26(31), 5480–5487 (2014). https://​doi.​org/​10.​1002/​adma.​20130​5293 \n10.\t J. Ju, T. Kuang, X. Ke, M. Zeng, Z. Chen et al., Lightweight multifunctional polypropylene/carbon nanotubes/carbon black nanocomposite foams with segregated structure, ultralow percolation threshold and enhanced electromagnetic interference shielding performance. Compos. Sci. Technol. 193, 108116 (2020). https://​doi.​org/​10.​1016/j. comps​citech.​2020.​108116 \n11.\t W. He, M. Sohn, R. Ma, D.J. Kang, Flexible single-electrode triboelectric nanogenerators with MXene/PDMS composite film for biomechanical motion sensors. Nano Energy 78, 105383 (2020). https://​doi.​org/​10.​1016/j.​nanoen.​2020. 105383 \n12.\t X. Sun, J. Sun, T. Li, S. Zheng, C. Wang et al., Flexible tactile electronic skin sensor with 3D force detection based on porous CNTs/PDMS nanocomposites. Nano-Micro Lett. 11(1), 57 (2019). https://​doi.​org/​10.​1007/​s40820-​019-​0288-7 \n13.\t X. Wu, B. Han, H. Zhang, X. Xie, T. Tu et al., Compressible, durable and conductive polydimethylsiloxane-coated MXene foams for high-performance electromagnetic interference shielding. Chem. Eng. J. 381, 122622 (2020). https://​doi. org/​10.​1016/j.​cej.​2019.​122622 \n14.\t J.N. Ni, R.Y. Zhan, J. Qiu, J.C. Fan, B.B. Dong et al., Multiinterfaced graphene aerogel/polydimethylsiloxane metacomposites with tunable electrical conductivity for enhanced electromagnetic interference shielding. J. Mater. Chem. C 8(34), 11748–11759 (2020). https://​doi.​org/​10.​1039/​D0TC0​2278K \n15.\t V.-T. Nguyen, B.K. Min, Y. Yi, S.J. Kim, C.-G. Choi, MXene $\\mathrm{(Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{X}})$ /graphene/PDMS composites for multifunctional broadband electromagnetic interference shielding skins. Chem. Eng. J. 393, 124608 (2020). https://​doi.​org/​10. 1016/j.​cej.​2020.​124608 \n16.\t Y. Zhang, J. Mei, C. Yan, T. Liao, J. Bell et al., Bioinspired 2D nanomaterials for sustainable applications. Adv. Mater. 32(18), 1902806 (2020). https://​doi.​org/​10.​1002/​adma.​20190​ 2806 \n17.\t Y. Yuan, Y. Ding, C. Wang, F. Xu, Z. Lin et al., Multifunctional stiff carbon foam derived from bread. ACS Appl. Mater. Interfaces 8(26), 16852–16861 (2016). https://​doi.​org/​10. 1021/​acsami.​6b039​85 \n18.\t Y. Cheng, J.Z.Y. Seow, H. Zhao, Z.J. Xu, G. Ji, A flexible and lightweight biomass-reinforced microwave absorber. Nano-Micro Lett. 12(1), 125 (2020). https://​doi.​org/​10.​1007/​ s40820-​020-​00461-x \n19.\t Y. Lin, J. Chen, P. Jiang, X. Huang, Wood annual ring structured elastomer composites with high thermal conduction enhancement efficiency. Chem. Eng. J. 389, 123467 (2020). https://​doi.​org/​10.​1016/j.​cej.​2019.​123467 \n20.\t Z. Sun, T. Liao, W. Li, Y. Qiao, K. Ostrikov, Beyond Seashells: Bioinspired 2D Photonic and Photoelectronic Devices. Adv. Funct. Mater. 29(29), 1901460 (2019). https://​doi.​org/​10.​1002/ adfm.​20190​1460 \n21.\t Z.-H. Zhou, Y. Liang, H.-D. Huang, L. Li, B. Yang et  al., Structuring dense three-dimensional sheet-like skeleton networks in biomass-derived carbon aerogels for efficient electromagnetic interference shielding. Carbon 152, 316–324 (2019). https://​doi.​org/​10.​1016/j.​carbon.​2019.​06.​027 \n22.\t K. Qian, Q. Zhou, H. Wu, J. Fang, M. Miao et al., Carbonized cellulose microsphere $@$ void@MXene composite films with egg-box structure for electromagnetic interference shielding. Compos. Part A Appl. S 141, 106229 (2021). https://​doi.​org/​ 10.​1016/j.​compo​sitesa.​2020.​106229 \n23.\t Z. Shen, J. Feng, Preparation of thermally conductive polymer composites with good electromagnetic interference shielding efficiency based on natural wood-derived carbon scaffolds. ACS Sustain. Chem. Eng. 7(6), 6259–6266 (2019). https://​ doi.​org/​10.​1021/​acssu​schem​eng.​8b066​61 \n24.\t Y.-Q. Li, Y.A. Samad, K. Polychronopoulou, K. Liao, Lightweight and highly conductive aerogel-like carbon from sugarcane with superior mechanical and emi shielding properties. ACS Sustain. Chem. Eng. 3(7), 1419–1427 (2015). https://​doi. org/​10.​1021/​acssu​schem​eng.​5b003​40 \n25.\t X. Ma, B. Shen, L. Zhang, Z. Chen, Y. Liu et al., Novel strawderived carbon materials for electromagnetic interference shielding: a waste-to-wealth and sustainable initiative. ACS Sustain. Chem. Eng. 7(10), 9663–9670 (2019). https://​doi.​org/​ 10.​1021/​acssu​schem​eng.​9b012​88 \n26.\t J. Li, Y. Ding, N. Yu, Q. Gao, X. Fan et al., Lightweight and stiff carbon foams derived from rigid thermosetting polyimide foam with superior electromagnetic interference shielding performance. Carbon 158, 45–54 (2020). https://​doi.​org/​10. 1016/j.​carbon.​2019.​11.​075 \n27.\t S. Zhao, H.B. Zhang, J.Q. Luo, Q.W. Wang, B. Xu et al., Highly electrically conductive three-dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene/reduced graphene oxide hybrid aerogels with excellent electromagnetic interference shielding performances. ACS Nano 12(11), 11193–11202 (2018). https://​doi.​org/​10.​ 1021/​acsna​no.​8b057​39 \n28.\t H. Zhang, G. Zhang, Q. Gao, M. Tang, Z. Ma et al., Multifunctional microcellular PVDF/Ni-chains composite foams with enhanced electromagnetic interference shielding and superior thermal insulation performance. Chem. Eng. J. 379, 122304 (2020). https://​doi.​org/​10.​1016/j.​cej.​2019.​122304 \n29.\t Z. Zeng, C. Wang, Y. Zhang, P. Wang, S.I. Seyed Shahabadi et al., Ultralight and highly elastic graphene/lignin-derived carbon nanocomposite aerogels with ultrahigh electromagnetic interference shielding performance. ACS Appl. Mater. Interfaces 10(9), 8205–8213 (2018). https://​doi.​org/​10.​1021/​ acsami.​7b194​27 \n30.\t Y.-J. Wan, P.-L. Zhu, S.-H. Yu, R. Sun, C.-P. Wong et al., Ultralight, super-elastic and volume-preserving cellulose fiber/ graphene aerogel for high-performance electromagnetic interference shielding. Carbon 115, 629–639 (2017). https://​doi. org/​10.​1016/j.​carbon.​2017.​01.​054 \n31.\t L. Wang, X. Shi, J. Zhang, Y. Zhang, J. Gu, Lightweight and robust rGO/sugarcane derived hybrid carbon foams with outstanding EMI shielding performance. J. Mater. Sci. Technol. 52, 119–126 (2020). https://​doi.​org/​10.​1016/j.​jmst.​2020.​03. 029 \n32.\t Y. Huangfu, C. Liang, Y. Han, H. Qiu, P. Song et al., Fabrication and investigation on the $\\mathrm{Fe}_{3}\\mathrm{O}_{4}/$ thermally annealed graphene aerogel/epoxy electromagnetic interference shielding nanocomposites. Compos. Sci. Technol. 169(5), 70–75 (2019). https://​doi.​org/​10.​1016/j.​comps​citech.​2018.​11.​012 \n33.\t Y. Chen, Y. Wang, H.B. Zhang, X. Li, C.X. Gui et  al., Enhanced electromagnetic interference shielding efficiency of polystyrene/graphene composites with magnetic $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ nanoparticles. Carbon 82, 67–76 (2015). https://​doi.​org/​10. 1016/j.​carbon.​2014.​10.​031 \n34.\t D. Lai, X. Chen, Y. Wang, Controllable fabrication of elastomeric and porous graphene films with superior foldable behavior and excellent electromagnetic interference shielding performance. Carbon 158, 728–737 (2020). https://​doi.​org/​10.​ 1016/j.​carbon.​2019.​11.​047 \n35.\t H. Sun, D. Chen, C. Ye, X. Li, D. Dai et al., Large-area selfassembled reduced graphene oxide/electrochemically exfoliated graphene hybrid films for transparent electrothermal heaters. Appl. Surf. Sci. 435, 809–814 (2018). https://​doi.​org/​10. 1016/j.​apsusc.​2017.​11.​182 \n36.\t R. Yu, Y. Shi, D. Yang, Y. Liu, J. Qu et al., Graphene oxide/ chitosan aerogel microspheres with honeycomb-cobweb and radially oriented microchannel structures for broad-spectrum and rapid adsorption of water contaminants. ACS Appl. Mater. Interfaces 9(26), 21809–21819 (2017). https://​doi.​org/​10. 1021/​acsami.​7b046​55 \n37.\t C. Liang, P. Song, H. Qiu, Y. Zhang, X. Ma et al., Constructing interconnected spherical hollow conductive networks in silver platelets/reduced graphene oxide foam/epoxy nanocomposites for superior electromagnetic interference shielding effectiveness. Nanoscale 11(46), 22590–22598 (2019). https://​doi.​org/​ 10.​1039/​C9NR0​6022G \n38.\t Y. Sun, S. Luo, H. Sun, W. Zeng, C. Ling et al., Engineering closed-cell structure in lightweight and flexible carbon foam composite for high-efficient electromagnetic interference shielding. Carbon 136, 299–308 (2018). https://​doi.​org/​ 10.​1016/j.​carbon.​2018.​04.​084 \n39.\t X. Wang, J. Shu, W. Cao, M. Zhang, J. Yuan et  al., Ecomimetic nanoarchitecture for green EMI shielding. Chem. Eng. J. 369, 1068–1077 (2019). https://​doi.​org/​10.​1016/j.​cej. 2019.​03.​164 \n40.\t J.B. Xi, Y.L. Li, E.Z. Zhou, Y.J. Liu, W.W. Gao et al., Graphene aerogel films with expansion enhancement effect of high-performance electromagnetic interference shielding. Carbon 135, 44–51 (2018). https://​doi.​org/​10.​1016/j.​carbon. 2018.​04.​041 \n41.\t X.Z. Ye, J. Hu, B. Li, M. Hong, Y.F. Zhang, Graphene loaded with nano-Cu as a highly efficient foam interface material with excellent properties of thermal-electronic conduction, antipermeation and electromagnetic interference shielding. Chem. Eng. J. 361, 1110–1120 (2019). https://​doi.​org/​10.​1016/j.​cej. 2018.​12.​047 \n42.\t P. Song, B. Liu, H. Qiu, X. Shi, D. Cao et al., MXenes for polymer matrix electromagnetic interference shielding composites: a review. Compos. Commun. 24, 100653 (2021). https://​doi.​org/​10.​1016/j.​coco.​2021.​100653 \n43.\t A.K. Singh, A. Shishkin, T. Koppel, N. Gupta, A review of porous lightweight composite materials for electromagnetic interference shielding. Compos. Part B-Eng. 149, 188–197 (2018). https://​doi.​org/​10.​1016/j.​compo​sitesb.​2018.​05.​027 \n44.\t Y. Chen, Y. Li, M. Yip, N. Tai, Electromagnetic interference shielding efficiency of polyaniline composites filled with graphene decorated with metallic nanoparticles. Compos. Sci. Technol. 80, 80–86 (2013). https://​doi.​org/​10.​1016/j.​comps​ citech.​2013.​02.​024 \n45.\t S. Lu, J. Shao, K. Ma, D. Chen, X. Wang et  al., Flexible, mechanically resilient carbon nanotube composite films for high-efficiency electromagnetic interference shielding. Carbon 136, 387–394 (2018). https://​doi.​org/​10.​1016/j.​carbon.​2018. 04.​086 \n46.\t W. Cao, C. Ma, S. Tan, M. Ma, P. Wan et al., Ultrathin and flexible CNTs/MXene/cellulose nanofibrils composite paper for electromagnetic interference shielding. Nano-Micro Lett. 11(1), 72 (2019). https://​doi.​org/​10.​1007/​s40820-​019-​0304-y \n47.\t P. Song, H. Qiu, L. Wang, X. Liu, Y. Zhang et al., Honeycomb structural rGO-MXene/epoxy nanocomposites for superior electromagnetic interference shielding performance. Sustain. Mater. Technol. 24, e00153 (2020). https://​doi.​org/​10.​1016/j. susmat.​2020.​e00153 \n48.\t S. Zhao, Y. Yan, A. Gao, S. Zhao, J. Cui et al., Flexible polydimethylsilane nanocomposites enhanced with a three-dimensional graphene/carbon nanotube bicontinuous framework for high-performance electromagnetic interference shielding. ACS Appl. Mater. Interfaces 10(31), 26723–26732 (2018). https://​doi.​org/​10.​1021/​acsami.​8b092​75 \n49.\t S. Li, D. Liu, W. Li, G. Sui, Strong and heat-resistant SiCcoated carbonized natural loofah sponge for electromagnetic interference shielding. ACS Sustain. Chem. Eng. 8(1), 435– 444 (2020). https://​doi.​org/​10.​1021/​acssu​schem​eng.​9b057​23 \n50.\t C. Liang, H. Qiu, P. Song, X. Shi, J. Kong et al., Ultra-light MXene aerogel/wood-derived porous carbon composites with wall-like “mortar/brick” structures for electromagnetic interference shielding. Sci. Bull. 65(8), 616–622 (2020). https:// doi.​org/​10.​1016/j.​scib.​2020.​02.​009 \n51.\t Z. Chen, C. Xu, C. Ma, W. Ren, H. Cheng, Lightweight and flexible graphene foam composites for high-performance electromagnetic interference shielding. Adv. Mater. 25(9), 1296–1300 (2013). https://​doi.​org/​10.​1002/​adma.​20120​4196 \n52.\t G.P. Kar, S. Biswas, R. Rohini, S. Bose, Tailoring the dispersion of multiwall carbon nanotubes in co-continuous PVDF/ ABS blends to design materials with enhanced electromagnetic interference shielding. J. Mater. Chem. A 3(15), 7974– 7985 (2015). https://​doi.​org/​10.​1039/​C5TA0​1183C \n53.\t P. Song, C. Liang, L. Wang, H. Qiu, H. Gu et al., Obviously improved electromagnetic interference shielding performances for epoxy composites via constructing honeycomb structural reduced graphene oxide. Compos. Sci. Technol. 181(8), 107698 (2019). https://​doi.​org/​10.​1016/j.​comps​citech.​2019. 107698 \n54.\t H. Zhang, G. Zhang, M. Tang, L. Zhou, J. Li et al., Synergistic effect of carbon nanotube and graphene nanoplates on the mechanical, electrical and electromagnetic interference shielding properties of polymer composites and polymer composite foams. Chem. Eng. J. 353, 381–393 (2018). https://​doi.​org/​10. 1016/j.​cej.​2018.​07.​144 \n55.\t L. Jia, D. Yan, X. Liu, R. Ma, H. Wu et al., Highly efficient and reliable transparent electromagnetic interference shielding film. ACS Appl. Mater. Interfaces 10(14), 11941–11949 (2018). https://​doi.​org/​10.​1021/​acsami.​8b004​92 \n56.\t Y. Li, C. Gong, C. Li, K. Ruan, C. Liu et al., Liquid crystalline texture and hydrogen bond on the thermal conductivities of intrinsic thermal conductive polymer films. J. Mater. Sci. Technol. 82, 250–256 (2021). https://​doi.​org/​10.​1016/j.​jmst. 2021.​01.​017 \n57.\t X. Huang, C. Zhi, Y. Lin, H. Bao, G. Wu et al., Thermal conductivity of graphene-based polymer nanocomposites. Mat. Sci. Eng. R 142, 100577 (2020). https://​doi.​org/​10.​1016/j. mser.​2020.​100577 \n58.\t P. Liu, X. Li, P. Min, X. Chang, C. Shu et al., 3D lamellarstructured graphene aerogels for thermal interface composites with high through-plane thermal conductivity and fracture toughness. Nano-Micro Lett. 13(1), 22 (2020). https://​doi. org/​10.​1007/​s40820-​020-​00548-5 \n59.\t X. Yang, X. Zhong, J. Zhang, J. Gu, Intrinsic high thermal conductive liquid crystal epoxy film simultaneously combining with excellent intrinsic self-healing performance. J. Mater. Sci. Technol. 68, 209–215 (2021). https://​doi.​org/​10.​1016/j. jmst.​2020.​08.​027 \n60.\t H. Liao, S. Guo, Y. Liu, Q. Wang, Form-stable phase change composites with high thermal conductivity and adjustable thermal management capacity. Sol. Energy Mater. Sol. Cells 221, 110881 (2021). https://​doi.​org/​10.​1016/j.​solmat.​2020. 110881 \n61.\t S.-W. Xiong, P. Zhang, Q. Zou, Y. Xia, M.-Y. Jiang et al., High thermal conductivity and electrical insulation of liquid alloy/ceramic/epoxy composites through the construction of mutually independent structures. Compos. Sci. Technol. 202, 108596 (2021). https://​doi.​org/​10.​1016/j.​comps​citech.​2020. 108596 \n62.\t Y. Guo, K. Ruan, X. Shi, X. Yang, J. Gu, Factors affecting thermal conductivities of the polymers and polymer composites: a review. Compos. Sci. Technol. 193, 108134 (2020). https://​doi.​org/​10.​1016/j.​comps​citech.​2020.​108134 \n63.\t X. Shi, R. Zhang, K. Ruan, T. Ma, Y. Guo et al., Improvement of thermal conductivities and simulation model for glass fabrics reinforced epoxy laminated composites via introducing hetero-structured BNN-30@BNNS fillers. J. Mater. Sci. Technol. 82, 239–249 (2021). https://​doi.​org/​10.​1016/j.​jmst. 2021.​01.​018 \n64.\t J. Myalski, M. Godzierz, P. Olesik, Effect of carbon fillers on the wear resistance of pa6 thermoplastic composites. Polymers 12(10), 2264 (2020). https://​doi.​org/​10.​3390/​polym​12102​264 \n65.\t I.M. El Radaf, R.M. Abdelhameed, Surprising performance of graphene oxide/tin dioxide composite thin films. J. Alloys Compd. 765, 1174–1183 (2018). https://​doi.​org/​10.​1016/j.​jallc om.​2018.​06.​277 \n66.\t T. Ma, Y. Zhao, K. Ruan, X. Liu, J. Zhang et al., Highly thermal conductivities, excellent mechanical robustness and flexibility, and outstanding thermal stabilities of aramid nanofiber composite papers with nacre-mimetic layered structures. ACS Appl. Mater. Interfaces 12(1), 1677–1686 (2020). https://​doi. org/​10.​1021/​acsami.​9b198​44 " + }, + { + "id": "10.1038_s41467-020-20580-8", + "DOI": "10.1038/s41467-020-20580-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-20580-8", + "Relative Dir Path": "mds/10.1038_s41467-020-20580-8", + "Article Title": "Single-layered organic photovoltaics with double cascading charge transport pathways: 18% efficiencies", + "Authors": "Zhang, M; Zhu, L; Zhou, GQ; Hao, TY; Qiu, CQ; Zhao, Z; Hu, Q; Larson, BW; Zhu, HM; Ma, ZF; Tang, Z; Feng, W; Zhang, YM; Russell, TP; Liu, F", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "The chemical structure of donors and acceptors limit the power conversion efficiencies achievable with active layers of binary donor-acceptor mixtures. Here, using quaternary blends, double cascading energy level alignment in bulk heterojunction organic photovoltaic active layers are realized, enabling efficient carrier splitting and transport. Numerous avenues to optimize light absorption, carrier transport, and charge-transfer state energy levels are opened by the chemical constitution of the components. Record-breaking PCEs of 18.07% are achieved where, by electronic structure and morphology optimization, simultaneous improvements of the open-circuit voltage, short-circuit current and fill factor occur. The donor and acceptor chemical structures afford control over electronic structure and charge-transfer state energy levels, enabling manipulation of hole-transfer rates, carrier transport, and non-radiative recombination losses.", + "Times Cited, WoS Core": 596, + "Times Cited, All Databases": 633, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000662810100013", + "Markdown": "# Single-layered organic photovoltaics with double cascading charge transport pathways: 18% efficiencies \n\nMing Zhang1,7, Lei Zhu 1,7, Guanqing Zhou1,7, Tianyu Hao1, Chaoqun Qiu1, Zhe Zhao1, Qin Hu $\\textcircled{6}$ 2, Bryon W. Larson $\\textcircled{1}$ 3, Haiming Zhu $\\textcircled{1}$ 4, Zaifei $M a^{5},$ , Zheng Tang5, Wei Feng6, Yongming Zhang1,6, Thomas P. Russell2 & Feng Liu 1,6✉ \n\nThe chemical structure of donors and acceptors limit the power conversion efficiencies achievable with active layers of binary donor-acceptor mixtures. Here, using quaternary blends, double cascading energy level alignment in bulk heterojunction organic photovoltaic active layers are realized, enabling efficient carrier splitting and transport. Numerous avenues to optimize light absorption, carrier transport, and charge-transfer state energy levels are opened by the chemical constitution of the components. Record-breaking PCEs of $18.07\\%$ are achieved where, by electronic structure and morphology optimization, simultaneous improvements of the open-circuit voltage, short-circuit current and fill factor occur. The donor and acceptor chemical structures afford control over electronic structure and chargetransfer state energy levels, enabling manipulation of hole-transfer rates, carrier transport, and non-radiative recombination losses. \n\nA cihrocluiist cvosltraagte $(V_{\\mathrm{OC}})^{1-3}$ ,asnhsoirtm-uciltracnuietocuslryr inmt $\\mathrm{\\bar{(}}J_{\\mathrm{SC}})^{4,5}$ ,paendfill factor $(\\mathrm{FF})^{6-9}$ has been long sought in organic photovoltaics (OPVs) to maximize power conversion efficiency (PCE). Improving all characteristics simultaneously has been hard to achieve, due to morphological and electronic structure constraints, leading to performance trade-offs. The ideal OPV device simultaneously maximizes light absorption, enhances exciton splitting, and facilitates the carrier extraction. The carrier generation kinetics must shunt energy loss channels induced by low energy chargetransfer (CT) states to improve the $V_{\\mathrm{OC}}^{\\mathrm{~\\tiny~l0,11}}$ . Consequently, optimizing the electronic structure of photovoltaic blends along with optimizing morphology is essential12–14. Mixtures of the midbandgap donor PM6 and the low-bandgap acceptor Y6 have shown exceptional PCE $(\\sim16\\%)$ , high $J_{\\mathrm{SC}}$ $(\\sim25\\mathrm{mAc}\\mathrm{\\bar{m}}^{-2},$ ), and low energy loss $(E_{\\mathrm{loss}},\\ 0.5\\mathrm{-}0.6\\mathrm{eV})^{15-19}$ . Enhancement of the photovoltaic characteristics requires more efficient exciton splitting and carrier transport pathways in the active layer. \n\nHere, we use quaternary blends, comprised of existing donor–acceptor pairs mixed with additional donor and acceptor components to mediate deficiencies in electronic performance or morphology, to address this challenge. It is advantageous to establish a tiered energy level alignment, to form cascading charge hopping channels that mitigate the $J_{\\mathrm{SC}}$ loss by fine-tuning the charge splitting and allow manipulation of multiple chargetransfer energies to ensure a high $V_{\\mathrm{OC}}$ . This applies to both electron and hole transport pathways to maximize the energy gain. From the hole transport side, PM7, which has a chemical structure similar to PM6 but a deeper highest occupied molecular orbital (HOMO) energy level, can be used as an “added” donor20,21, since it is miscible with PM6, does not disrupt the morphology, and provides a tiered cascading energy level alignment. From the electron transport side, $\\mathrm{PC}_{71}\\mathrm{BM}$ , which is compatible with the base PM6:Y6 blends, is an acceptor with a slightly higher lowest unoccupied molecular orbital (LUMO) than Y6 that affords a cascading energy level alignment to improve electron transport and promote efficiency. Consequently, the quaternary blend strategy, where the composition can be fine-tuned to optimize device characteristics, represents a new strategy to improve PCEs. \n\nIn addition to reducing the charge splitting driving force, PM7 preferentially interacts with the Y6 acceptor, effectively regulating the crystallization of Y6 to better suit carrier transport. PM7 redirects the ultrafast hole transfer from Y6 to the donor phase, forming tiered cascading energy levels that improve $J_{\\mathrm{SC}}$ without further absorption gain. Adding $\\mathrm{PC}_{71}\\mathrm{BM}$ reduces the light absorption, yet not the current output. The higher LUMO level of $\\mathrm{PC}_{71}\\mathrm{BM}$ in the acceptor mixture improves the $V_{\\mathrm{OC}}$ and electron transport, and offsets the absorption loss, leading to an enhancement in device performance. The synergy between the components in the PM6:PM7: $\\mathrm{Y6{:}P C_{71}B M}$ quaternary devices result in a maximum PCE of $18.07\\%$ , the highest in single-layered OPV devices, with an excellent stability $81\\%$ PCE after $1000\\mathrm{h}$ illumination) that is ${\\sim}5\\%$ better than PM6:Y6 binary devices. The double cascading quaternary blend strategy is implemented in other material systems, which is reflected in similar behavior of device operation, demonstrating the novelty in the approach for OPV device fabrication. These results demonstrate the importance of manipulating the electronic structure in BHJ thin films, while simultaneously manipulating the morphology, opening a new route to higher efficiency OPV devices. \n\n# Results \n\nThe double cascading charge transport and device performance. Figure 1a, b shows the chemical structure and absorption profiles of the materials used in this study. The Y6 acceptor absorbs from 700 to $950\\mathrm{nm}$ , while PM6 and PM7 donors show complementary absorption from 400 to $700\\mathrm{nm}$ . $\\mathrm{PC}_{71}\\mathrm{BM}$ , with a much lower absorption in VIS-IR region, can mostly be considered a transport medium. The HOMO and LUMO are $-5.13\\mathrm{eV}/\\$ $-3.2\\bar{8}\\mathrm{eV}$ for PM6, $-5.24\\mathrm{eV}/-3.38\\mathrm{eV}$ for PM7, $-5.66\\:\\mathrm{eV}/-4.29$ $\\mathrm{eV}$ for Y6, and $-6.10\\:\\mathrm{eV}/-4.10\\:\\mathrm{eV}$ for $\\mathrm{PC}_{71}\\mathrm{BM}$ . The HOMO levels are accurately measured by ultraviolet photoelectron spectroscopy $(\\mathrm{UPS})^{22}$ , coupled with the optical band gaps to estimate the LUMO levels (Fig. 1c, d). Solar cells were prepared with a forward structure (ITO/PEDOT:PSS/active layer/PFNDI- $\\mathrm{\\cdotBr/Ag}$ ). The donor to acceptor ratio was fixed at 1:1.2 (optimized conditions for PM6:Y6) to avoid light-absorption-induced performance change, and $\\mathrm{PC}_{71}\\mathrm{BM}$ was added separately. The concentrations of PM7 and $\\mathrm{PC}_{71}\\mathrm{BM}$ were varied to determine the optimal composition. Detailed performances of the devices are shown in Supplementary Fig. 1, and Supplementary Tables 1 and 2. For the PM6:PM7:Y6 ternary blends, a mixing ratio of 0.8:0.2:1.2 $(D_{1}{:}D_{2}{:}A_{1})$ was found to be optimal, while for the $\\mathrm{PM6{:}P M7{:}Y6{:}P C_{71}B M}$ quaternary blends, a mixing ratio of 0.8:0.2:1.2:0.25 $(D_{1}{:}D_{2}{:}A_{1}{:}A_{2})$ yielded optimum performance. The current density–voltage $\\left(J-V\\right)$ curves are shown in Fig. 1e, with performance detailed in Supplementary Fig. 2 and Table 1. PM6:Y6 binary devices showed a maximum PCE of $16.52\\%$ , with a $V_{\\mathrm{OC}}$ of $0.842\\mathrm{V}$ , a $J_{\\mathrm{SC}}$ of $25.98\\mathrm{mAcm}^{-2}$ , and an FF of $75.52\\%$ . Ternary devices showed a maximum PCE of $17.02\\%$ , a $V_{\\mathrm{OC}}$ of $0.848\\mathrm{V}$ , a $J_{\\mathrm{SC}}$ of $26.17\\mathrm{mAcm}^{-2}$ , and an FF of $76.70\\%$ . Quaternary devices showed a maximum PCE of $18.07\\%$ , with a $V_{\\mathrm{OC}}$ of $0.859\\mathrm{V},$ a $J_{\\mathrm{SC}}$ of $26.55\\mathrm{mAcm}^{-2}$ , and an FF of $79.23\\%$ . The quaternary devices had a certified PCE of $17.35\\%$ , subject to the calibration procedures of the National Renewable Energy Laboratory, using a $0.032\\mathrm{cm}^{2}$ photon mask (Supplementary Fig. 3), which is the highest certified value reported for a single-layered BHJ device. In the ternary blends, the external quantum efficiency (EQE) improved slightly at ${\\sim}640\\mathrm{nm}$ in comparison to the PM6:Y6 binary blends, as shown in Supplementary Fig. 4. In the quaternary blends, the EQE spectra of $450{\\mathrm{-}}600{\\mathrm{nm}}$ and $650{-}800\\mathrm{nm}$ improved slightly. Therefore, enhanced electron transport aided in improving the light extraction from the acceptor materials. The enhanced performance results from better charge collection channels for both electrons and holes, i.e., double cascading carrier transport pathways, which will be discussed in detail in the following section. \n\n![](images/03a72206577a55af7cd905559a4e9232745d6b3246b9ef480e198c38f544d2c8.jpg) \nFig. 1 Molecular structure and photovoltaic performance of single-junction devices. a Chemical structures, b thin film absorption coefficients, and c UPS results of PM6 (red line), PM7 (yellow line), and Y6 (blue line). Fermi energy was determined by linear extrapolating the high binding energy portion of the spectrum, and HOMO energy level was referred to low binding energy onset. d Energy level alignment and double cascading transport pathways for quaternary system. e Current density–voltage characteristics and f histogram of PCE measurement for 40 devices on binary, ternary, and quaternary devices under constant incident light intensity (AM $1.5\\mathsf{G}$ , $100\\mathsf{m W}\\mathsf{c m}^{-2},$ . g Normalized PCE, $V_{\\mathrm{OC}},J_{\\mathsf{S C}},$ and FF (20 devices statistics) against aging time under illumination equivalent to ${\\sim}1$ sun for $1000\\mathsf{h}$ (red for binary and blue for quaternary, the error bar is from the deviation of twenty samples). \n\nThe stepwise-aligned energy levels lead to interesting device characteristics. The carrier recombination was determined from the dependence of the $J_{\\mathrm{SC}}$ and $V_{\\mathrm{OC}}$ on light intensity, as shown in Supplementary Fig. 5, Supplementary Fig. 8a, and Supplementary Table 3. A slope from $V_{\\mathrm{OC}}$ vs. $P_{\\mathrm{light}}$ of $2\\bar{k}T/q$ should be obtained if monomolecular or trap-assisted recombination dominate23,24. The recombination parameter $\\alpha$ , defined by $J_{\\mathrm{SC}}\\propto(P_{\\mathrm{light}})^{\\alpha};$ , is close to unity, suggesting minimal bimolecular recombination25. From the binary to ternary to quaternary blends, $\\alpha$ increased from ${\\sim}0.93$ to ${\\sim}0.94$ and to ${\\sim}0.96$ , and the slope of $V_{\\mathrm{OC}}$ vs. $P_{\\mathrm{light}}$ decreased from ${1.34k T}/{q}$ to $1.18~k T/q$ and $1.\\bar{1}0k T/q$ , respectively, consistent with the change in the FFs. These results indicate that the PM7 donor reduces trap-assisted recombination, due to a better HOMO level alignment, which will be discussed further in the following section. Adding $\\mathrm{PC}_{71}\\mathrm{BM}$ to the ternary blends leads to a further decrease from the electron transport side. Detailed hole and electron mobilities of the active layers with different thickness were determined using space-charge-limited current with log–log plot (Supplementary Figs. 6 and 7, and Supplementary Table 4). The space-charge-limited region was found with the slope of $(2\\pm0.1)$ , which was also fitted according to Mott–Gurney law to obtain mobility values, reflecting electron and hole transport properties26–28. It could be seen that higher mobilities correspond to better $J_{\\mathrm{SC}}$ and less recombination, which seems a common phenomenon29,30. To further understand the recombination mechanism, transient photovoltage and transient photocurrent were carried out, with details shown in experimental section. Lifetimes under different $V_{\\mathrm{OC}}$ conditions (tuned by changing the light intensity) could be obtained through biexponential fitting, as shown in Supplementary Fig. 9a. The lifetime of quaternary device shows a significant enhancement in the whole $V_{\\mathrm{OC}}$ regime, indicating optimized device condition. The charge density as a function of $V_{\\mathrm{OC}}$ for devices is calculated by differential capacitance method, with results shown in Supplementary Fig. 9b, which shows a clear exponential dependence on $V_{\\mathrm{OC}},$ following $n=n_{0}e^{\\gamma V_{\\mathrm{oc}}}$ , where $n_{0}$ is the average charge density in the active layer in dark condition. The value of $\\gamma$ (slope of $\\ln(n)-V_{\\mathrm{OC}}$ curve) for each blend was found to give similar results, in which for an ideal semiconductor, a $\\gamma$ of ${\\bar{e}}/2k T,$ , equal to $19.3\\mathrm{V}^{-1}$ at room temperature should be obtained. The deviation can be attributed to the existence of the exponential distribution of the tail states extending to the bandgap of the active layers. The improved charge density in quaternary devices echoes promoted transfer and transport properties, which offset the absorption loss. Derived charge lifetime in the devices as a function of charge density is shown in Supplementary Fig. 9c, following a power law dependence, indicating the nongeminate recombination is the dominating loss channel for carrier density under open-circuit condition. According to the above, nongeminate recombination rate coefficient can be determined, which is defined by $\\begin{array}{r}{k(n)=\\frac{1}{\\tau(n)n},}\\end{array}$ as shown in Supplementary Fig. 9d, and the recombination coefficient derived from Langevin theory $k_{L}=$ $\\begin{array}{r}{\\frac{q}{\\varepsilon_{r}\\varepsilon_{0}}\\left(\\mu_{n}+\\mu_{p}\\right)}\\end{array}$ is calculated for comparison31. Quaternary devices show the smallest recombination rate coefficient indicating significantly suppressed nongeminate recombination. All of the devices showed a decreased recombination rate coefficient, with two orders of magnitude smaller than the Langevin recombination coefficient. The Langevin recombination rate increases with charge mobility. However, on the basis of detail balanced theory, the charge transport process in photoactive layers is much more complicated at interface, where excitons can dissociate into electrons and holes, meanwhile electrons and holes can meet to generate excitons again or annihilate directly32. The much lower recombination coefficient rate compared with Langevin theory indicates a significantly reduced nongeminate recombination loss in devices, contributing to improved devices photoelectric properties. Time-resolved microwave conductivity (TRMC) measurements were performed to characterize the free-charge generation characteristics33–35. The $\\varphi\\Sigma\\mu$ value at the lowest absorbed flux, where we find excitation intensity-independent recombination dynamics, is used as an indicator of PV potential. As seen in Supplementary Fig. 10a, PM6:Y6 blends peak at a value of $2.3\\times\\dot{1}0^{-2}\\mathrm{cm}^{2}\\dot{s}^{-1}\\dot{\\mathrm{V}^{-1}}$ . The addition of PM7 and $\\mathrm{PC}_{71}\\mathrm{BM}$ , slightly increases this value to $2.4\\times10^{-2}\\mathrm{cm}^{2}s^{-1}\\mathrm{V}^{-1}$ for the ternary and $2.9\\times10^{-2}\\mathrm{cm}^{2}s^{-1}\\mathrm{V}^{-1}$ for the quaternary blends, indicating an increased charge generation yield. Shown in Supplementary Fig. 10b are the normalized photoconductivity transient spectra over 500 ns. PM7:Y6 shows the carrier lifetimes increase from 246 to 431 to $460\\mathrm{ns}$ in going from the binary to ternary to quaternary blends. From a local photo-physics perspective, these improved free carrier dynamics, especially in concert with high exciton-to-charge conversion, are consistent with increasingly efficient interfacial exciton dissociation and carrier extraction, which help to improve the long-term stability of the device36. \n\nThe average parameters were calculated from 40 devices, with the area of 0.032 cm2. Values outside the parentheses denote the best optimal results. \n\n\n
Table 1 Photovoltaics of BHJ solar cells under illumination of AM 1.5 G, 10O mW cm-2.
BlendVoc (V) Jsc (mA cm-2)FF (%)PCE (%)μe (cm² s-1v-1)μh (cm² s-1v-1)
PM6:Y60.842 (0.842±0.001)25.98 (25.67 ± 0.19)75.52 (74.91± 0.66)16.52 (16.30 ± 0.11)(4.42 ± 0.36) × 10-4(1.41± 0.49) ×10-3
PM6:PM7:Y60.848 (0.847±0.001)26.17 (25.72 ± 0.31)76.70 (75.91± 0.72)17.02 (16.69 ± 0.27)(4.69 ± 0.42) × 10-4(1.47 ± 0.57) × 10-3
PM6:PM7:Y6:PC7BM0.859 (0.859±0.001)26.55 (26.24± 0.43)79.23 (78.7 ± 0.32)18.07 (17.71± 0.23)(6.53 ± 0.64) ×10-4(1.73 ± 0.16) ×10-3
PM7:Y60.879 (0.879±0.001)24.89 (24.79 ± 0.34)69.10 (67.52 ± 1.25)15.12 (14.79 ± 0.32)(3.62 ± 0.56)×10-4(1.34 ± 0.22) × 10-3
\n\nStability tests were performed for $1000\\mathrm{h}$ under illumination equivalent to 1 sun, and the performance of quaternary devices maintains an $81.0\\%$ PCE, with $5.2\\%{V_{\\mathrm{OC}}}$ loss, $5\\%\\ J_{\\mathrm{SC}}$ loss, and $10.1\\%$ FF loss (Fig. 1g and Supplementary Fig. 11), which is superior than binary devices. Temperature and humidity during the test process are shown in Supplementary Fig. 12 (average $12.5\\%$ and $41.5^{\\circ}\\mathrm{C})$ . The storage stability for quaternary devices retain $97.2\\%$ PCE after $\\stackrel{\\cdot}{1}000\\mathrm{h}$ aging in dark conditions (Supplementary Fig. 13), underscoring the benefits of the double cascading quaternary blends in enhancing the morphology and operation stability for long-term use. Different cathode interlayers were also investigated during stability test, which yield large variations in performances, suggesting the necessity of cathode interlayer optimization in the future. \n\nUltrafast hole transfer and efficient carrier transport along double cascading pathways. It is essential to understand the carrier transfer dynamics within the framework of the morphology. Femto-second transient absorption (TA) spectroscopy was used to probe the photoinduced hole transfer dynamics in the multicomponent blends37–39. The results are shown in Fig. 2, with the corresponding hole transfer times summarized in Supplementary Table 5. The static absorption peaks for the $D$ and $A$ are spectrally well separated, so both the spectral and temporal characteristics of hole transfer dynamics can be determined. An excitation wavelength of $750\\mathrm{nm}$ was used to selectively excite Y6. The 2D color plot of TA spectra of PM6:Y6 blend film is shown in Fig. 2a, and a few representative TA spectra at the indicated delay times are shown in Fig. 2b. With the decay of the Y6 bleach peak at $770-860\\mathrm{nm}$ , a few clear bleach peaks at $560{-}600\\mathrm{nm}$ emerge in the TA spectra, matching well with the absorption features of PM6. The bleach decay process of the photoexcited Y6 agrees with the increase of the PM6 ground state bleach, confirming the ultrafast hole transfer from Y6 to PM6, as shown in Fig. 2c. We can extract the rising kinetic of PM6 bleach to represent the hole transfer process. Herein, the rising kinetic of PM6 bleach is not influenced by Y6 bleach due to well separating of static absorption peaks between PM6 and Y6, providing a clear hole transfer process. We fit the donor kinetics with a biexponential function. The hole transfer process in the four blends (PM6:Y6, PM6:PM7:Y6, $\\mathrm{\\Delta^{2}M6z P M7.Y65P C_{71}B M}$ , and PM7:Y6) show a fast component with $\\tau_{1}$ of $\\cdot{-0.25,}{\\sim}0.39,{\\sim}0.37$ , and ${\\sim}0.47$ ps, and a slow component $\\tau_{2}$ of 8.18, 10.28, 13.22, and 16.36 ps, respectively (Fig. 2d, e), and their relative contributions are shown in Supplementary Table 5. The former fast component $\\tau_{1}$ can be assigned to the ultrafast exciton dissociation of Y6 at the donor–acceptor interface and the latter to the diffusion of excitons in Y6 toward interface before dissociation40–42. The interfacial exciton separation is more than one order of magnitude faster in comparison to the exciton diffusion. The trend in the hole transfer lifetime and the hole transfer efficiency is consistent with the values of HOMO offsets or driving force (Supplementary Fig. 14), which points out the direction of device operating principle. The presence of PM7 in the BHJ blends reduces the driving force, aligning the cascading energy levels to ensure better transport and an increase in the $J_{\\mathrm{SC}},$ a trade-off with the hole transfer rate. $\\mathrm{PC}_{71}\\mathrm{BM}$ does not perturb the hole transfer process, suggesting close interactions between Y6 and PM6/PM7. Such results also agree well with the observation that no $\\mathrm{PM}6{:}\\mathrm{PC}_{71}\\mathrm{BM}$ CT emission is seen in quaternary blends. While most studies focus on increasing absorption with the addition of more components, our findings indicate that a detailed balance between the driving force and hole transfer rate is equally important to refine the carrier generation and extraction to generate high $J_{\\mathrm{SC}}$ in OSCs. We compared the polaron decay dynamics of the quaternary blend films at different pump fluences to probe the charge recombination mechanism (Supplementary Fig. 15). The difference in fluence dependence of recombination dynamics suggests that carriers recombine via the nongeminate recombination with small amount of geminate recombination $(1\\%)$ , indicating of small amount of CT states formation. Timeresolved photoluminescence (TRPL) measurements were further performed. To avoid the influence of Y6 fluorescence quenching, we only probed $550\\mathrm{-}650\\mathrm{nm}$ and pump at $515\\mathrm{nm}$ in TRPL measurement. As illustrated in Supplementary Fig. 16 and Supplementary Table 6, PM6:PM7 blended film presents much smaller fluorescence lifetime $\\mathit{\\'}\\tau=672.4\\pm9.3\\mathrm{ps})$ compared with PM6 $(1483.6\\pm11.7\\mathrm{ps})$ and PM7 $(1521.7\\pm13.1\\$ ps) neat films, indicating electron transfer channel between PM6 and PM7. After blending Y6, the fluorescence lifetime is significantly decreased with a time constant of $73.9\\pm1.23\\$ ps, indicating a highly efficient electron transfer in the PM6:PM7:Y6 heterojunction. From the above results, a picture of the mechanism emerges, as shown in Fig. 2f. The photon excitation first drives ultrafast and large amounts of free carriers accompanied with nongeminate recombination, biasing out the weak interfacially bound CT states (which are quite close in energies), along with a density-dependent recombination process (step 4). \n\n![](images/f1da944c56b58ebff895875f3bde1df43f642e4aade400f7cfa21d16956f0794.jpg) \nFig. 2 Ultrafast hole transfer and efficient carrier transport along double cascading pathways. a Color plot of fs transient absorption spectra of blended film at indicated delay times under $750\\mathsf{n m}$ excitation with a fluence $<10\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ . b Representative fs TA spectra of blended films at indicated delay times. c TA kinetics in blended films showing the hole transfer process. d The hole transfer process in PM6:Y6 (red line), PM6:PM7:Y6 (yellow line), PM6:PM7: $\\mathsf{Y6}\\colon\\mathsf{P C}_{71}\\mathsf{B}M$ (blue line), and PM7:Y6 (black line) blended films. e Charge-transfer time achieved through multi-exponential fitting for different blended films (the error bar is from the standard error of curve fitting). f Schematic of electronic states in an organic solar cell, and the excited state $(\\mathsf{S}_{1})$ can be directly separated (step 1) or form charge-transfer states (step 2), accompanied with recombination processes (steps 3 and 4). \n\nEnergy loss optimization induced by CT energy management. In solar cell devices, the $V_{\\mathrm{OC}}$ decreases in going from quaternary to ternary to binary blends. This results from the energy level management, driving force, and energy loss $(E_{\\mathrm{loss}})$ . Highly sensitive EQE (s-EQE), electroluminescence (EL), and electroluminescence quantum efficiency (EQE-EL) measurements were performed to investigate energy loss channels43–45. Two energy loss sectors, charge generation $(\\Delta E_{2}=E_{\\mathrm{g}}–E_{\\mathrm{CT}})$ and charge recombination losses $({\\bar{E}}_{\\mathrm{CT}^{-}}q V_{\\mathrm{OC}})$ were considered. The charge recombination loss could be further traced to radiative $(\\Delta E_{1})$ and non-radiative $(\\Delta E_{3})$ recombinations46. The $E_{\\mathrm{CT}}$ could be obtained by fitting the sub-gap absorption of the corresponding $s$ -EQE curve (Fig. 3b and Supplementary Fig. 17) following the Marcus theory $^{43,\\tilde{4}7}$ . The CT energy of the binary PM6:Y6 blend was $1.34\\mathrm{eV}$ , yielding a $\\Delta E_{2}=0.066\\mathrm{eV}$ . PM7:Y6 blend showed a CT energy of $1.37\\mathrm{eV}$ , with $\\Delta E_{2}=0.061\\mathrm{eV}$ . Ternary and quaternary blends showed the CT energies of 1.35 and $1.36\\mathrm{eV}$ , respectively. The lowest $\\Delta E_{2}$ of $0.048\\mathrm{eV}$ was obtained for quaternary films, resulting in a higher $V_{\\mathrm{OC}}$ . The deeper HOMO of PM7 leads to a reduced hole transfer driving force but smaller energy loss, providing one avenue for device optimization, with an optimized ternary blend composition of $20\\%$ PM7. The $\\mathrm{PM}6{\\mathrm{:}}\\mathrm{PC}_{71}\\mathrm{BM}$ mixture has a CT energy of $1.49\\mathrm{eV}$ , higher than the bandgap of Y6, and thus would not introduce a low level CT state to trap electrons. Consequently, adding $\\mathrm{PC}_{71}\\mathrm{BM}$ to the ternary blends redefines the acceptor LUMO at a higher level, which further improves $V_{\\mathrm{OC}}$ . \n\nFigure 3a shows the normalized EL spectra of devices based on the pure materials and the BHJ films. PM6:Y6 blends show a single EL emission peak at $924\\mathrm{nm}$ , similar to that of a Y6 film $(920\\mathrm{nm})$ . When the applied current was increased from 1 to 5 mA, no EL change was observed (Supplementary Fig. 19). Thus, the CT states, if present, have a very low density. $\\mathrm{PM}6{:}\\mathrm{PC}_{71}\\mathrm{BM}$ blends have a CT emission at $980\\mathrm{nm}$ , well below the emission in the binary mixtures. However, in the quaternary blends, the EL is dominated by Y6, eliminating the PM6: $\\mathrm{PC}_{71}\\mathrm{BM}$ CT states. Therefore, the BHJ blends can be viewed as simple OLED devices, with PM6/PM7 and $\\mathrm{PC}_{71}\\mathrm{BM}$ acting as hole and electron transporting layers, and emission happens at the Y6 acceptor or PM6:Y6 interfaces. Y6, then, functions as both a photovoltaic and EL material. The energy losses due to radiative recombination $(\\Delta E_{1})$ of charge carriers can be calculated using the fit parameters from the s-EQE spectra (Fig. 3b and Supplementary Fig. 17), and the losses due to the non-radiative recombination $(\\Delta E_{3})$ were quantified by measuring the EQE-EL48. As shown in Fig. 3c, the emission efficiency of PM7:Y6 blend was $1.33\\times10^{-20}\\%$ , much higher than that of PM6:Y6 blend $(5.05\\times10^{-3}\\%)$ . Thus, for ternary blends, the additional $20\\%$ PM7 actually reduced the energy loss caused by non-radiative recombination. The quaternary blends show a higher emission efficiency of $9.37\\times10^{-3}\\%$ in comparison to the ternary film, representing a decrease in $\\Delta E_{3}$ to $0.24\\bar{0}\\mathrm{eV}$ . Non-radiative recombination can be calculated from $\\Delta E_{3}=-k T\\mathrm{.ln(EQE_{EL})}$ . Consequently, it is important to maximize $\\mathrm{EQE_{EL}}$ to minimize $\\Delta E_{3}$ , and in the current case, the double cascading energy level alignment plays an important role. Different contributions to energy loss are shown in Fig. 3d and summarized in Supplementary Table 7. The quaternary blends showed the lowest total energy loss of $0.548\\mathrm{eV}$ , in comparison to the other blends $\\mathrm{\\phantom{-}}0.567\\mathrm{eV}$ for PM6:Y6, $0.553\\mathrm{eV}$ for PM7:Y6, and $0.568\\mathrm{eV}$ for ternary blends). We attribute the elevated $V_{\\mathrm{OC}}$ of the quaternary devices to the smallest $E_{\\mathrm{g}}{-}E_{\\mathrm{CT}}$ energy offset and the suppressed non-radiative recombination losses, due to the addition of PM7 and $\\mathrm{PC}_{71}\\mathrm{BM}$ . \n\n![](images/7da0e22d490702c8e062c2ca51256f4c59b7a169d25a3b1aeb115209a4afdff0.jpg) \nFig. 3 Energy loss analysis. a Electroluminescence spectra of devices based on the pristine and blended films. b s-EQE and c EQE-EL of the blende devices. d Energy loss histogram, including $\\Delta E_{1},$ $\\Delta E_{2},$ and $\\Delta E_{3}$ of blended devices. \n\nThin film morphology of double cascading blends. The structure of the neat and BHJ thin films were determined using grazing incidence wide-angle X-ray diffraction (GIWAXS), the results of which are shown in Fig. 4 and Supplementary Fig. 20. The PM6 donor assumed a dominant face-on orientation, with a broad (100) reflection in the in-plane (IP) direction at $0.28\\mathring{\\mathrm{A}}^{-1}$ and a $\\pi-$ π stacking peak in the out-of-plane (OOP) direction at $1.69\\mathring{\\mathrm{A}}^{-1}$ . The crystal coherence lengths (CCLs) for (100) and (010) were 5.27 and $1.56\\mathrm{nm}$ , respectively, as determined using the Scherrer analysis49,50. PM7 had a similar diffraction profile, with a (100) reflection in the IP direction at $0.29\\mathring{\\mathrm{A}}^{-1}$ and (010) reflection in the OOP direction at $1.66\\mathring{\\mathrm{A}}^{-1}$ with CCLs of 4.52 and $1.31\\mathrm{nm}$ , respectively. Y6 films showed a $\\pi{-}\\pi$ stacking peak at $1.75\\mathring{\\mathrm{A}}^{-1}$ in the OOP direction and a lamellar stacking peaks at $0.27\\mathring\\mathrm{A}^{-1}$ in the IP direction. However, the banana-shaped Y6 molecules pack in a unique manner so that they can overlap by end group $\\pi{-}\\pi$ stacking to form a polymer-like conjugated backbone, and the lamellae packing is assigned to the (110) lattice plane, which is shown in Fig. 4d and Supplementary Fig. 21. Thus, Y6 assumes a tilted molecular orientation where the polymer-like backbone is tilted normal to surface, which is more efficient for charge transport. \n\nA summary of the 2D and linecut GIWAXS profiles are shown in Fig. 4a, b, respectively. For the PM6:Y6 blends, Y6 showed well-defined IP (020) and (11-1) lattice reflections at 0.21 and $0.42\\mathring\\mathrm{A}^{-1}$ . PM7:Y6 blends show weak crystalline order, with the Y6 (11-1) and (020) diffraction peaks absent. Even though PM6 and PM7 have similar chemical structures, PM7 interacts differently with Y6 and retards Y6 crystallization, such that only the Y6 (110) stacking can be seen. In ternary blends, the intensities of the reflections at 0.23 and $0.42\\mathring{\\mathrm{A}}^{-1}$ decreased significantly. In the quaternary blends, the Y6 reflections at 0.23 and $0.42\\mathring{\\mathrm{A}}^{-1}$ were quite weak, indicating that $\\mathrm{PC}_{71}\\mathrm{BM}$ also disrupts the packing of Y6. The polymer lamellar and Y6 (110) reflections could not be separated, and they were used in sum to estimate the lamellar ordering of the BHJ thin film. The polymer and $\\Upsilon6\\pi\\ –\\pi$ reflections are summarized in Supplementary Table 8. Figure $_{4c}$ shows parameters derived from the lamellar and $\\pi{-}\\pi$ stacking peaks of the different BHJ thin films. The quaternary blend showed the largest CCL and peak area for both the lamellar and $\\pi{-}\\pi$ stacking peaks, indicating that the overall crystallinity and crystal quality are improved for the quaternary blends, which improves carrier transport pathways. The Y6 (020) peak showed a decrease in the peak area, but an increase in the CCL in going from the binary to ternary to quaternary blends, as shown in Supplementary Fig. 22 and Supplementary Table 9. Consequently, the crystallization behavior of Y6 changed in the blends. The loss of primary axis coherence and intensity in Y6, but improvement in the (110) and $\\pi{-}\\pi$ stacking reflect an extended polymer-like conjugated backbone by adopting a twisted or screw-like packing in the multicomponent blends, providing a pathway for electron transport. A schematic of the molecular packing in the blend films is illustrated in Fig. 4e. The intimate mixing of PM6 and PM7 (as indicated by the linear dependence of the $V_{\\mathrm{OC}}$ on concentration) results in the formation of a homogeneous polymer-rich phase embedded in a fibrillar network. The difference in the interactions of PM6 and PM7 with Y6 optimizing the crystallization of Y6. $\\mathrm{PC}_{71}\\mathrm{BM}$ addition does not perturb the morphological framework of PM6:Y6 and is distributed uniformly, as evidenced by the absence of any feature characteristic of $\\mathrm{P}\\dot{\\mathrm{C}}_{71}\\mathrm{BM}$ aggregation. Thus, the plasticizing nature of $\\mathrm{PC}_{71}\\mathrm{BM}$ aids in the overall ordering, improving both electron and hole mobility, and a higher FF. \n\nBHJ thin film phase separation was visualized using transmission electron microscopy (TEM). As shown in Supplementary Fig. 23, all the BHJ thin films showed evidence of phase separation on the tens of nanometers length scale. Resonant soft x-ray scattering (Supplementary Fig. 24) for PM6:Y6 and PM6: PM7:Y6 blends yielded an interference at a length scale of $\\sim60\\mathrm{nm}$ . The quaternary blends with different $\\mathrm{PC}_{71}\\mathrm{BM}$ loadings (Supplementary Fig. 24b) show a shoulder gradually developing into a well-defined interference at higher $\\mathrm{PC}_{71}\\mathrm{BM}$ loadings, suggesting that uniform distribution of $\\mathrm{PC}_{71}\\mathrm{BM}$ in the mixed region enhances the scattering contrast. The uniform distribution of $\\mathrm{PC}_{71}\\mathrm{BM}$ in the mixture indicates that the close interactions with the other amorphous components produces a unique electronic structure with improved electron transport channels, where excited electrons in the donors can transfer onto the “LUMO” of mixed domain that are rapidly extracted. Though the HOMO of $\\mathrm{PC}_{71}\\mathrm{BM}$ is much deeper than that of Y6, a homogeneous mixing provides good contacts with the donor materials making exciton harvesting by $\\mathrm{PC}_{71}\\mathrm{BM}$ and Y6 efficient. \n\n![](images/d4dadc89eba9183a97a1a4d62f53e6402970a721a0d59c7964352e9923842d9c.jpg) \nFig. 4 Morphology optimization of thin films. a 2D GIXD patterns of the binary, ternary and quaternary blends. b Out-of-plane (black) and in-plane (red) linecut profiles of the 2D GIXD data. c $D$ -spacing (red symbol), CCL (blue symbol) and peak area/volume fraction (black symbol) of pi–pi and lamellae diffraction peak for blended films with different composition. d Molecular packing sketch map of Y6 crystal. e The arrangement sketch of molecules in quaternary blended films. \n\n# Discussion \n\nThe results show the importance of achieving a detailed balance between morphology, energy loss reduction, and ultrafast charge transfer kinetics in double cascading quaternary blends. The double donor strategy yields a terraced HOMO energy level alignment that facilitates hole transport in the BHJ blends. \n\nAdding $\\mathrm{PC}_{71}\\mathrm{BM}$ that is uniformly mixed with Y6 produces a terraced LUMO energy level alignment, and in the HOMO levels, the longer exciton diffusion times, in comparison to the splitting times, lead to a high probability that a suitable donor/acceptor interface can be found to split excitons. The close contact between Y6 and PM7 provides an important channel where Y6 trapped exciton or hole carriers can be extracted. Such a unique double cascading energy level simultaneously improves the $V_{\\mathrm{OC}},J_{\\mathrm{SC}},$ and FF. A more thorough correlation between the structure, photon–electron processes, and device performances needs to be quantified to establish a solid structure–property relationship. Shown in Fig. 5a, b are the correlations between the structural and device characteristics, Fig. 5c–e shows relationships between charge transfer, transport, and performance, and Fig. 5f, the correlation between energy loss and $V_{\\mathrm{OC}}.$ A quantitative analysis was performed using the Pearson correlation method51,52, as shown in Fig. 5g, h in 3D and 2D. A correlation factor of 1, indicates a direct correlation, with decreasing values reflecting a loss in correlation. The Pearson correlation coefficient matrix is shown in Supplementary Table 10. It is seen that crystallization is the major factor that accounts for $J_{\\mathrm{SC}}$ and FF in photovoltaic devices, thus the quaternary blends reach the maximum value. Mobilities $\\cdot\\mu_{\\mathrm{h}}$ and $\\mu_{\\mathrm{e}})$ are highly dependent on thin film crystallinity. $1/\\tau_{1}$ shows a strong correlation with the driving force, indicating its strong influence on exciton separation, while the trend in driving force matches well with recombination parameters, suggesting an important mechanism correlating efficient charge transfer and extraction. $V_{\\mathrm{OC}}$ should show an inverted correlation with energy loss, and $\\Delta E_{3}$ , originating with nonradiative recombination, shows the most significant influence. Therefore, a detailed balance between morphology optimization, charge transfer efficiency, and energy loss channels controls the device output. These observations suggest a new strategy using double cascading quaternary blends for device optimization. The material properties and device performance parameters are highly interconnected, and optimizing only one parameter is not sufficient to optimize performance. Binary mixtures are effective for material screening, and ternary mixtures bring complementary absorption and energy level management into the device design, but quaternary mixtures enable a fine-tuning of both the morphology and electronic structure simultaneously. Fine-tuning such quaternary mixtures introduces a new strategy to achieve higher efficiency OPVs. We extended the double cascading quaternary mixture strategy to other well-studied NFA OPV systems (Supplementary Fig. 25 and Supplementary Table 11), with similar results been obtained as seen in $\\mathrm{PM6{:}P M7{:}Y6{:}P C_{71}B M}$ mixture, underscoring the generality of this approach. \n\n![](images/bd317a0f1e1f28ac10a4915565dea5a760305e375ba9ec68a15b42889a4b9296.jpg) \nFig. 5 Correlation of structure, photon-to-electron process, and device performance. a–f Multidimensional correlation analysis of structure–property relationships (the parameter units are following previous data). g, h Person correlation analysis of major device and structure parameters (color bar and height both represent person correlation coefficients, CCL is the abbreviation of crystal coherence length, DF is the abbreviation of driving force, HTE is the abbreviation of hole transfer efficiency, E1–E3 represent energy loss). \n\nHere, we designed multicomponents blends of polymer donors PM6 and PM7, a non-fullerene small-molecule acceptor Y6, and a fullerene acceptor $\\mathrm{PC}_{71}\\mathrm{BM}$ . An average PCE of $16.69\\%$ was obtained when $80\\%$ PM6 and $20\\%$ PM7 were blended with Y6. The addition of the fourth component $\\mathrm{PC}_{71}\\mathrm{BM}$ significantly increased the average efficiency output to $17.71\\%$ $(\\bar{\\mathrm{PCE}}_{\\operatorname*{max}}$ of $18.07\\%)$ , with a slightly improved $J_{\\mathrm{SC}}$ of $26.55\\mathrm{mAcm}^{-2}$ , which could be ascribed to a fine balance between light absorption and charge extraction. The elevated $V_{\\mathrm{OC}}\\left(0.859\\mathrm{V}\\right)$ of the quaternary device was attributed to the smallest $E_{\\mathrm{g}}{-}E_{\\mathrm{CT}}$ energy offset and the suppressed non-radiative recombination losses after the addition of PM7 and, especially, $\\mathrm{PC}_{71}\\mathrm{BM}$ . An FF of over 0.79 was obtained, since an optimized morphology formed with balanced crystallization features that ensured better charge transport, as shown in Supplementary Fig. 26 that summarizes the holistic strategy in OPV efficiency optimization. \n\n# Methods \n\nDevice fabrication. Organic solar cell devices with ITO/PEDOT:PSS/active layer/ PFNDI- $.{\\mathrm{Br/Ag}}$ regular structures were fabricated according to the following procedure. Patterned ITO glass substrates were sequential cleaned by ultrasonicating in acetone, detergent, deionized water, and isopropyl alcohol for $15\\mathrm{min}$ each and then dried under $80^{\\circ}\\mathrm{C}$ . The precleaned substrates were treated in an ultraviolet–ozone chamber for 15 min, then a ${\\sim}40\\mathrm{nm}$ thick PEDOT:PSS (Clevious P VP AI $\\boldsymbol{4083\\mathrm{H}}$ . C. Stark, Germany) thin film was deposited onto the ITO surface by spin-coating and baked at $150^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . The blend solution with different mixing ratio $(14\\mathrm{{mg}\\mathrm{{mL^{-1}}}}$ in total) in CF (with $0.5\\%$ CN solvent additive) was stirred at $25^{\\circ}\\mathrm{C}$ for $120\\mathrm{min}$ in advance, and then spin-coated on top of the PEDOT:PSS layer. The prepared films were treated with thermal annealing at $85^{\\circ}\\mathrm{C}$ for $6\\mathrm{{min}}$ . After cooling to room temperature, a $\\sim5\\mathrm{nm}$ thick of PFNDI-Br $(0.5\\mathrm{mg}\\mathrm{mL}^{-1}$ ) was spin-coated on the top of active layer. Then, those samples were brought into to an evaporate chamber and a $140\\mathrm{nm}$ thick silver layer was thermally evaporated on the PFNDI-Br layer at a base pressure of $1\\times10^{-6}$ mbar. The evaporation thickness was controlled by SQC-310C deposition controller (INFICON, Germany). Ten devices were fabricated on one substrate and the active area of each device was $0.032\\mathrm{cm}^{2}$ defined by a shadow mask. \n\nReporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nThe data that support the plots within this paper and other finding of this study are available from the corresponding authors upon reasonable request. \n\nReceived: 16 July 2020; Accepted: 2 December 2020; Published online: 12 January 2021 \n\n# References \n\n1. Chen, Y. et al. Tuning Voc for high performance organic ternary solar cells with non-fullerene acceptor alloys. J. Mater. Chem. A 5, 19697–19702 (2017). \n2. Liu, Y. et al. Exploiting noncovalently conformational locking as a design strategy for high performance fused-ring electron acceptor used in polymer solar cells. J. Am. Chem. Soc. 139, 3356–3359 (2017). \n3. Baran, D. et al. Reduced voltage losses yield $10\\%$ efficient fullerene free organic solar cells with ${>}1\\mathrm{~V~}$ open circuit voltages. Energy Environ. Sci. 9, 3783–3793 (2016). \n4. Ma, X. et al. Efficient ternary polymer solar cells with two well-compatible donors and one ultranarrow bandgap nonfullerene acceptor. Adv. Energy Mater. 8, 1702854 (2018). \n5. Zhan, L. et al. A near-infrared photoactive morphology modifier leads to significant current improvement and energy loss mitigation for ternary organic solar cells. Adv. Sci. 5, 1800755 (2018). \n6. Nian, L. et al. Ternary non-fullerene polymer solar cells with $13.51\\%$ efficiency and a record-high fill factor of $78.13\\%$ . Energy Environ. Sci. 11, 3392–3399 (2018). \n7. Zhou, Z. et al. High-efficiency small-molecule ternary solar cells with a hierarchical morphology enabled by synergizing fullerene and non-fullerene acceptors. Nat. Energy 3, 952–959 (2018). \n8. Zhang, M. et al. Efficient ternary non-fullerene polymer solar cells with PCE of $11.92\\%$ and FF of $76.5\\%$ . Energy Environ. Sci. 11, 841–849 (2018). \n9. Zheng, Z. et al. A highly efficient non-fullerene organic solar cell with a fill factor over 0.80 enabled by a fine-tuned hole-transporting layer. Adv. Mater. 30, 1801801 (2018). \n10. Qian, D. et al. Design rules for minimizing voltage losses in high-efficiency organic solar cells. Nat. Mater. 17, 703–709 (2018). \n11. Gao, K. et al. Deep absorbing porphyrin small molecule for high-performance organic solar cells with very low energy losses. J. Am. Chem. Soc. 137, 7282–7285 (2015). \n12. Zhu, L. et al. Aggregation-induced multilength scaled morphology enabling $11.76\\%$ efficiency in all-polymer solar cells using printing fabrication. Adv. Mater. 31, 1902899 (2019). \n13. Liu, F. et al. Characterization of the morphology of solution-processed bulk heterojunction organic photovoltaics. Prog. Polym. Sci. 38, 1990–2052 (2013). \n14. Chen, W., Nikiforov, M. P. & Darling, S. B. Morphology characterization in organic and hybrid solar cells. Energy Environ. Sci. 5, 8045–8074 (2012). \n15. Yuan, J. et al. Single-junction organic solar cell with over $15\\%$ efficiency using fused-ring acceptor with electron-deficient core. Joule 3, 1140–1151 (2019). \n16. Fan, B. et al. Achieving over $16\\%$ efficiency for single-junction organic solar cells. Sci. China Chem. 62, 746–752 (2019). \n17. Cui, Y. et al. Over $16\\%$ efficiency organic photovoltaic cells enabled by a chlorinated acceptor with increased open-circuit voltages. Nat. Commun. 10, 2515 (2019). \n18. Yu, R. et al. Improved charge transport and reduced nonradiative energy loss enable over $16\\%$ efficiency in ternary polymer solar cells. Adv. Mater. 31, 1902302 (2019). \n19. Zhu, L. et al. Efficient organic solar cell with $16.88\\%$ efficiency enabled by refined acceptor crystallization and morphology with improved charge transfer and transport properties. Adv. Energy Mater. 10, 1904234 (2020). \n20. Fan, Q. et al. Chlorine substituted 2D-conjugated polymer for highperformance polymer solar cells with $13.1\\%$ efficiency via toluene processing. Nano Energy 48, 413–420 (2018). \n21. Ma, L. et al. A ternary organic solar cell with $300~\\mathrm{{nm}}$ thick active layer shows over $14\\%$ efficiency. Sci. China Chem. 63, 21–27 (2020). \n22. Schlaf, R., Parkinson, B. A., Lee, P. A., Nebesny, K. W. & Armstrong, N. R. HOMO/LUMO alignment at PTCDA/ZnPc and PTCDA/ClInPc heterointerfaces determined by combined UPS and XPS measurements. J. Phys. Chem. B 103, 2984–2992 (1999). \n23. Koster, L. J. A., Mihailetchi, V. D., Ramaker, R. & Blom, P. W. M. Light intensity dependence of open-circuit voltage of polymer:fullerene solar cells. Appl. Phys. Lett. 86, 123509 (2005). \n24. Xiao, B. et al. High efficiency organic solar cells based on amorphous electrondonating polymer and modified fullerene acceptor. Nano Energy 39, 478–488 (2017). \n25. Schilinsky, P., Waldauf, C. & Brabec, C. J. Recombination and loss analysis in polythiophene based bulk heterojunction photodetectors. Appl. Phys. Lett. 81, 3885–3887 (2002). \n26. Carbone, A., Kotowska, B. K. & Kotowski, D. Space-charge-limited current fluctuations in organic semiconductors. Phys. Rev. Lett. 95, 236601 (2005). \n27. Blom, P. W. M., Tanase, C., de Leeuw, D. M. & Coehoorn, R. Thickness scaling of the space-charge-limited current in poly(p-phenylene vinylene). Appl. Phys. Lett. 86, 092105 (2005). \n28. Blom, P. W. M., Mihailetchi, V. D., Koster, L. J. A. & Markov, D. E. Device physics of polymer:fullerene bulk heterojunction solar cells. Adv. Mater. 19, 1551–1566 (2007). \n29. Fan, Q. et al. Synergistic effects of side-chain engineering and fluorination on small molecule acceptors to simultaneously broaden spectral response and minimize voltage loss for $13.8\\%$ efficiency organic solar cells. Sol. RRL 3, 1900169 (2019). \n30. Weng, K. et al. Ternary organic solar cells based on two compatible PDI-based acceptors with an enhanced power conversion efficiency. J. Mater. Chem. A 7, 3552–3557 (2019). \n31. Juška, G., Arlauskas, K., Stuchlik, J. & Österbacka, R. Non-Langevin bimolecular recombination in low-mobility materials. J. Non-Cryst. Solids 352, 1167–1171 (2006). \n32. Kirchartz, T., Mattheis, J. & Rau, U. Detailed balance theory of excitonic and bulk heterojunction solar cells. Phys. Rev. B 78, 235320 (2008). \n33. Ihly, R. et al. Tuning the driving force for exciton dissociation in single-walled carbon nanotube heterojunctions. Nat. Chem. 8, 603–609 (2016). \n34. Habisreutinger, S. N., Noel, N. K., Larson, B. W., Reid, O. G. & Blackburn, J. L. Rapid charge-transfer cascade through SWCNT composites enabling lowvoltage losses for perovskite solar cells. ACS Energy Lett. 4, 1872–1879 (2019). \n35. Larson, B. W. et al. Inter-fullerene electronic coupling controls the efficiency of photoinduced charge generation in organic bulk heterojunctions. Adv. Energy Mater. 6, 1601427 (2016). \n36. Burlingame, Q. et al. Intrinsically stable organic solar cells under highintensity illumination. Nature 573, 394–397 (2019). \n37. Bakulin, A. A. et al. The role of driving energy and delocalized states for charge separation in organic semiconductors. Science 335, 1340 (2012). \n38. Ziffer, M. E. et al. Long-lived, non-geminate, radiative recombination of photogenerated charges in a polymer/small-molecule acceptor photovoltaic blend. J. Am. Chem. Soc. 140, 9996–10008 (2018). \n39. Liu, Y., Zuo, L., Shi, X., Jen, A. K. Y. & Ginger, D. S. Unexpectedly slow yet efficient picosecond to nanosecond photoinduced hole-transfer occurs in a polymer/nonfullerene acceptor organic photovoltaic blend. ACS Energy Lett. 3, 2396–2403 (2018). \n40. Zhong, Y. et al. Molecular helices as electron acceptors in high-performance bulk heterojunction solar cells. Nat. Commun. 6, 8242 (2015). \n41. Li, K. et al. Influence of exciton diffusion and charge-transfer state dissociation efficiency on the short-circuit current densities in semi-random donor/ acceptor polymer:fullerene solar cells. J. Phys. Chem. C 117, 6940–6948 (2013). \n42. Kaake, L. G., Moses, D. & Heeger, A. J. Coherence and uncertainty in nanostructured organic photovoltaics. J. Phys. Chem. Lett. 4, 2264–2268 (2013). \n43. Vandewal, K., Tvingstedt, K., Gadisa, A., Inganäs, O. & Manca, J. V. Relating the open-circuit voltage to interface molecular properties of donor:acceptor bulk heterojunction solar cells. Phys. Rev. B 81, 125204 (2010). \n44. Tvingstedt, K. et al. Electroluminescence from charge transfer states in polymer solar cells. J. Am. Chem. Soc. 131, 11819–11824 (2009). \n45. Yao, J. et al. Quantifying losses in open-circuit voltage in solution-processable solar cells. Phys. Rev. Appl. 4, 014020 (2015). \n46. Eisner, F. D. et al. Hybridization of local exciton and charge-transfer states reduces nonradiative voltage losses in organic solar cells. J. Am. Chem. Soc. 141, 6362–6374 (2019). \n47. Marcus, R. A. Relation between charge transfer absorption and fluorescence spectra and the inverted region. J. Phys. Chem. 93, 3078–3086 (1989). \n48. Benduhn, J. et al. Intrinsic non-radiative voltage losses in fullerene-based organic solar cells. Nat. Energy 2, 17053 (2017). \n49. Song, J. et al. Morphology characterization of bulk heterojunction solar cells. Small Methods 2, 1700229 (2018). \n50. Zhang, M., Zhu, L., Qiu, C., Zhang, Y. & Liu, F. Printing and in situ morphology detection of organic thin film photovoltaic devices. Acta Polym. Sin. 50, 352–358 (2019). \n51. Li, J. & Ji, L. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 95, 221–227 (2005). \n52. Saad, Z. S. et al. A new method for improving functional-to-structural MRI alignment using local Pearson correlation. Neuroimage 44, 839–848 (2009). \n\n# Acknowledgements \n\nThis work was financially supported by the grant from the National Natural Science Foundation of China (Grant Nos. 51973110, 21734009, 21905102, and 61805138), Beijing National Laboratory for Molecular Sciences (BNLMS201902), the Center of Hydrogen Science, Shanghai Jiao Tong University, China. We thank Cheng Wang and Chenhui Zhu from Advanced Light Source for providing $\\mathbf{x}\\cdot\\mathbf{\\partial}$ -ray scattering tests, which were carried out at beamline 7.3.3 and 11.0.1.2 (a portion of this work) at the Advanced Light Source, Molecular Foundry, Lawrence Berkeley National Laboratory, supported by the DOE, Office of Science, and Office of Basic Energy Sciences. L.Z. acknowledge the funding supported by China Postdoctoral Science Foundation (Grant No. 2020M681278). Z.M. acknowledges the funding supported by the Natural Science Foundation of Shanghai (Grant No. 19ZR1401400). H.Z. acknowledges the funding supported by the National Key Research and Development Program of China (2017YFA0207700). T.P.R. and Q.H. were supported by the US Office of Naval Research under contract N00014-17-1-2244. A portion of this work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. B.W.L. acknowledges funding from the Solar Energy Technology Office (SETO), Office of Energy Efficiency and Renewable Energy, U.S. DOE, for microwave conductivity measurements. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. \n\n# Author contributions \n\nF.L. and T.P.R. conceived and directed the study. M.Z. fabricated the BHJ devices and did morphology optimization. L.Z. characterized the BHJ devices and conducted the certification. TA results and corresponding analysis were provided by G.Z. and H.Z. Energy loss test was performed by T.H., and assisted by Z.M. and Z.T. C.Q. and Y.Z. carried out recombination analysis. Z.Z. did correlation analysis. Q.H. assisted in scattering measurement and device performance certification. B.W.L. carried out TRMC test and W.F. provided TEM test. This manuscript was mainly prepared by F.L., M.Z., and L.Z., and all authors participated in the manuscript preparation and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-20580-8. \n\nCorrespondence and requests for materials should be addressed to F.L. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41467-021-24079-8", + "DOI": "10.1038/s41467-021-24079-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-24079-8", + "Relative Dir Path": "mds/10.1038_s41467-021-24079-8", + "Article Title": "Platinum single-atom catalyst coupled with transition metal/metal oxide heterostructure for accelerating alkaline hydrogen evolution reaction", + "Authors": "Zhou, KL; Wang, ZL; Han, CB; Ke, XX; Wang, CH; Jin, YH; Zhang, QQ; Liu, JB; Wang, H; Yan, H", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Single-atom catalysts provide an effective approach to reduce the amount of precious metals meanwhile maintain their catalytic activity. However, the sluggish activity of the catalysts for alkaline water dissociation has hampered advances in highly efficient hydrogen production. Herein, we develop a single-atom platinum immobilized NiO/Ni heterostructure (Pt-SA-NiO/Ni) as an alkaline hydrogen evolution catalyst. It is found that Pt single atom coupled with NiO/Ni heterostructure enables the tunable binding abilities of hydroxyl ions (OH*) and hydrogen (H*), which efficiently tailors the water dissociation energy and promotes the H* conversion for accelerating alkaline hydrogen evolution reaction. A further enhancement is achieved by constructing Pt-SA-NiO/Ni nullosheets on Ag nullowires to form a hierarchical three-dimensional morphology. Consequently, the fabricated Pt-SA-NiO/Ni catalyst displays high alkaline hydrogen evolution performances with a quite high mass activity of 20.6Amg(-1) for Pt at the overpotential of 100mV, significantly outperforming the reported catalysts. While H-2 evolution from water may represent a renewable energy source, there is a strong need to improve catalytic efficiencies while maximizing materials utilization. Here, authors examine single-atom Pt on nickel-based heterostructures as highly active electrocatalysts for alkaline H-2 evolution.", + "Times Cited, WoS Core": 549, + "Times Cited, All Databases": 561, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000665040300012", + "Markdown": "# Platinum single-atom catalyst coupled with transition metal/metal oxide heterostructure for accelerating alkaline hydrogen evolution reaction \n\nKai Ling Zhou1,2, Zelin Wang1,2, Chang Bao Han1✉, Xiaoxing ${\\mathsf{K e}}^{1\\boxtimes},$ Changhao Wang $\\textcircled{1}$ 1, Yuhong Jin1, Qianqian Zhang1, Jingbing Liu1, Hao Wang1✉ & Hui Yan1 \n\nSingle-atom catalysts provide an effective approach to reduce the amount of precious metals meanwhile maintain their catalytic activity. However, the sluggish activity of the catalysts for alkaline water dissociation has hampered advances in highly efficient hydrogen production. Herein, we develop a single-atom platinum immobilized NiO/Ni heterostructure $(P t_{S A}-N i O/$ Ni) as an alkaline hydrogen evolution catalyst. It is found that Pt single atom coupled with NiO/Ni heterostructure enables the tunable binding abilities of hydroxyl ions $(\\mathsf{O H}^{\\star})$ and hydrogen $(\\mathsf{H}^{\\star})$ , which efficiently tailors the water dissociation energy and promotes the $\\mathsf{H}^{\\star}$ conversion for accelerating alkaline hydrogen evolution reaction. A further enhancement is achieved by constructing $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ nanosheets on Ag nanowires to form a hierarchical three-dimensional morphology. Consequently, the fabricated PtSA-NiO/Ni catalyst displays high alkaline hydrogen evolution performances with a quite high mass activity of $20.6\\mathsf{A}\\mathsf{m}\\mathsf{g}^{-1}$ for Pt at the overpotential of $100\\mathsf{m V},$ , significantly outperforming the reported catalysts. \n\nydrogen $\\left(\\operatorname{H}_{2}\\right)$ has been regarded as the most promising energy carrier alternative to fossil fuels due to the environmental friendliness nature and high gravimetric energy density1,2. Electrocatalytic water splitting powered by wind energy or solar technologies for hydrogen generation is considered a sustainable strategy3. For an optimal electrocatalyst, minimizing the energy barrier and increasing the active sites are desirable for boosting the hydrogen evolution reaction $\\mathrm{(HER)}^{4-6}$ . Despite the significant progress that has been presented in nonprecious catalysts7,8, the platinum $\\left(\\mathrm{Pt}\\right)$ -based materials are still regarded as the most active catalysts for HER due to its optimal binding ability with hydrogen9–12. However, the high cost and scarcity of $\\mathrm{Pt}$ hamper its large-scale application in electrolyzers for $\\mathrm{H}_{2}$ production. Single-atom catalysts (SACs) provide an effective approach to reduce the amount of Pt meanwhile maintain its high intrinsic activity13–16. Recently, electrocatalytic HER in an alkaline condition has attracted more attention because catalyst systems are generally unstable in acidic media, resulting in safety and cost concerns in practice. Unfortunately, the alkaline HER activity of $\\mathrm{\\Pt}$ -based catalysts is approximately two orders of magnitude lower than that in the acidic condition caused by the high activation energy of the water dissociation step17–20. Alkaline HER process involves two electrochemical reaction steps: (step (i)) electron-coupled $\\mathrm{H}_{2}\\mathrm{O}$ dissociation to generate adsorbed hydrogen hydroxyl $(\\mathrm{OH^{*}})$ and hydrogen $(\\mathrm{H^{*}})$ (Volmer step), and (step (ii)) the concomitant interaction of dissociated $\\mathrm{H^{*}}$ into molecular $\\mathrm{H}_{2}$ (Heyrovsky or Tafel step)21,22. In particular, the additional energy in step (i) is required to overcome the barrier for splitting strong $\\mathrm{OH-H}$ bond, leading to a hamper of Pt SACs for alkaline HER application. Therefore, reducing the water dissociation energy in Volmer step (step (i)) for Pt SAC in alkaline media becomes vital for large-scale $\\mathrm{H}_{2}$ production of industrialization. \n\nSome strategies have been developed to improve Pt SACs HER activity. For instance, employing microenvironment engineering to immobilize single $\\mathrm{Pt}$ atoms in MXene nanosheets $(\\mathrm{Mo}_{2}\\mathrm{TiC}_{2}\\mathrm{T}_{x})$ and onion-like carbon nanospheres supports could greatly reduce the H adsorption energy $(\\Delta G_{\\mathrm{H}})$ and, thus, facilitates the release of $\\mathrm{H}_{2}$ molecular23,24. Besides, Pt single atoms anchored alloy catalysts $(\\mathrm{Pt/np–Co}_{0.85}\\mathrm{Se}$ SAC) were constructed as an efficient HER electrocatalyst25, in which np- $\\mathrm{Co}_{0.85}\\mathrm{Se}$ can largely optimize the adsorption/desorption energy of hydrogen on atomic $\\mathrm{Pt}$ sites, thus improving the HER kinetics. Furthermore, by utilizing the electronic interaction between the $\\mathrm{Pt}$ atoms and the supports, single-atom $\\mathrm{Pt}$ -anchored 2D $\\ensuremath{\\mathrm{MoS}}_{2}$ $(\\mathrm{Pt}_{\\mathrm{SA}^{-}}\\mathrm{MoS}_{2})^{26}$ , nitrogendoped graphene nanosheets $(\\mathrm{Pt}_{\\mathrm{SA}^{-}}\\mathrm{NGN}\\mathrm{s})^{27}$ , and porous carbon matrix $(\\mathrm{Pt}@\\mathrm{PCM})^{28}$ show enhanced electrocatalytic HER efficiency due to the higher $d$ -band occupation near Fermi level, which can provide more free electrons for boosting the $\\mathrm{H^{*}}$ conversion. Despite significant progress in Pt SACs, these methods are difficult to decrease the energy barrier of water dissociation in the Volmer step (step (i)). Generally, the $\\mathrm{H}_{2}\\mathrm{O}$ dissociation and $\\mathrm{H^{*}}$ conversion happen on different catalytic sites29. Especially, the HER activities of $\\mathrm{\\Pt}$ -based catalysts in alkaline conditions are governed by the binding ability of hydroxyl species $(\\mathrm{OH^{*}})^{18,30,31}$ , and the alkaline HER kinetics could be optimized by independently regulating the binding energy of reactants (OH and H\\*) on dual active sites32–34. Inspired by these findings, the energy barrier of $\\mathrm{Pt}$ SCAs for $\\mathrm{H}_{2}\\mathrm{O}$ dissociation in Volmer step (step (i)) in alkaline media could be decreased by incorporating or creating the dual active sites in the catalyst to independently modulate the binding energy of reactants ( $\\mathrm{\\DeltaOH^{*}}$ and $\\mathrm{H^{*}}$ ). \n\nIn this work, we developed a three-dimensional (3D) nanostructured electrocatalyst consisting of two-dimensional (2D) NiO/Ni heterostructure nanosheets supported single-atom Pt attached on one-dimensional $\\mathbf{A}\\mathbf{g}$ nanowires (Ag NWs) conductive network $\\left(\\mathrm{Pt}_{\\mathrm{SA}}–\\mathrm{NiO}/\\mathrm{Ni}\\right)$ . Density functional theory (DFT) calculations reveal that the dual active sites consisting of metallic Ni sites and O vacancies-modified NiO sites near the interfaces of NiO/Ni heterostructure in $\\mathrm{Pt_{SA}}{-}\\mathrm{NiO}/\\mathrm{Ni}$ show the preferred adsorption affinity toward ${\\mathrm{OH}}^{*}$ and $\\mathrm{H^{*}}$ , respectively, which efficiently facilitates water adsorption and reaching a barrier-free water dissociation step with a lower energy barrier of $0.31\\mathrm{eV}$ in Volmer step (step (i)) for $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ in the alkaline condition compared with that of $\\mathrm{Pt_{SA}\\mathrm{-}N i}$ $(0.47\\mathrm{eV})$ and $\\mathrm{Pt}_{\\mathrm{SA}^{-}}\\mathrm{NiO}$ $(1.42\\mathrm{eV})$ catalysts. In addition, anchoring $\\mathrm{Pt}$ single atoms at the interfaces of NiO/Ni heterostructure induces more free electrons on $\\mathrm{Pt}$ sites due to the elevated occupation of the $\\mathrm{Pt}~5d$ orbital at Fermi level and the more suitable H binding energy $(\\Delta G_{\\mathrm{H^{*}}},-0.07\\:\\mathrm{eV})$ than that of Pt atoms at the NiO ( $\\Delta G_{\\mathrm{H^{*}}}$ , $0.74\\mathrm{eV})$ and Ni $(\\Delta G_{\\mathrm{H^{*}}}$ , $-0.38\\mathrm{eV},$ , which efficiently promotes the $\\mathrm{H^{*}}$ conversion and $\\mathrm{H}_{2}$ desorption, thus accelerating overall alkaline HER (step (ii)). Furthermore, the Ag NWs-supported 3D morphology provides abundant active sites and accessible channels for charge transfer and mass transport. As a result, the fabricated $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ catalyst exhibits outstanding HER activity with a quite lower overpotential of $26\\mathrm{mV}$ at $\\mathbf{\\bar{l}}0\\mathbf{m}\\mathbf{A}\\mathbf{cm}^{-2}$ in 1-M KOH. The mass activity of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ is $20.6\\mathrm{A}\\mathrm{mg}^{-1}$ Pt at the overpotential of $100\\mathrm{mV}$ , which is 41 times greater than that of the commercial $\\mathrm{Pt}/\\$ C catalyst, significantly outperforming the reported catalysts. This work provides a design principle toward SAC systems for efficient alkaline HER. \n\n![](images/d6257e2371eb056ce981c8cde1dc35a5aa21f80535846132d5e5edd9ce5d2865.jpg) \nFig. 1 Schematic illustration of synthesis and water splitting mechanism of $P t_{S A}=N i O/N i$ . a The synthesis process of Pt single atom anchored NiO/Ni heterostructure nanosheets on $\\mathsf{A g}$ nanowires network. b The mechanism of $\\mathsf{P t}_{\\mathsf{S A}}$ -NiO/Ni network as an efficient catalyst toward large-scale water electrolysis in alkaline media. \n\nResults Synthesis and characterization of $\\mathbf{Pt_{SA}}\\mathbf{-NiO/Ni}$ catalyst. The fabrication process of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ on $\\mathrm{Ag}$ NWs is illustrated in Fig. 1. In brief, the synthesized Ag NWs by a typical hydrothermal method35 were first loaded on the flexible cloth to form a conductive network. The loading of Ag NWs leads to a brown film deposited on the surface of the white cloth fabric substrate (Fig. S1a, b), and the loading capacity of $\\mathrm{Ag}$ NWs was determined to be $\\sim0.47\\mathrm{mg}\\mathrm{cm}^{-2}$ . The surface of the cloth fabric was studied by scanning electron microscopy (SEM) as shown in Fig. S1d–f, and a large number of fibers is presented. The abundant interconnected pores consist of a rich number of seams in each fiber. After the loading of the Ag NWs, the cloth fabric fibers are covered, and the uniform Ag NWs layer forms on the surface of cloth fabric as shown in Fig. S1g–i. Then Ni/NiO composite is attached to the $\\mathbf{Ag}$ network by the facile electrodeposition process36. In detail, the Ag NWs network-loaded cloth is immersed in nickel acetate aqueous solution followed by an electrochemical process with $\\mathrm{~-}3.0\\mathrm{V}$ versus SCE (saturated calomel electrode) for $200s$ (Fig. S2), forming the uniformly distributed nanosheets on the Ag network (Fig. S3). Transmission electron microscopy (TEM, Fig. S4a, b) images, high-resolution TEM (HRTEM, Fig. S4c) image with corresponding fast Fourier transform (FFT pattern, Fig. S4d), and elemental mapping (Fig. S5) images clearly show that the metallic Ni is uniformly embedded in amorphous-like NiO nanosheets. Besides, the X-ray diffraction (XRD, Fig. S6) pattern shows that only metallic Ni signal without distinctive peaks of NiO can be detected, and $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS, Fig. S7) spectra suggest both metallic Ni and Ni oxide exists in Ni/NiO sample, further confirming the composition of metallic Ni on NiO. Interestingly, the deposited composition can be facilely controlled by performing various voltage in the nickel acetate aqueous solution36. Specifically, as above discussion, a high voltage of $-3\\mathrm{V}$ versus SCE will generate the Ni/NiO composite on Ag NWs (NiO/Ni), whereas a lower voltage of $-1\\mathrm{V}$ versus SCE could prepare the pure NiO on $\\mathrm{Ag}$ NWs (NiO, Figs. S8–10). Besides, the pure metallic Ni on $\\mathrm{Ag}$ network (Ni, Figs. S11–14) was fabricated by a traditional electrodeposition method with $1.2\\mathrm{V}$ for $200s$ in a mix solution containing 0.10-M $\\mathrm{NiCl}_{2}$ and 0.09-M $\\mathrm{H}_{3}\\mathrm{BO}_{3}$ . Afterward, the single-atom Pt-immobilized $\\mathrm{NiO/Ni}$ $\\left(\\mathrm{Pt}_{\\mathrm{SA}}{-}\\mathrm{Ni}\\mathrm{O}/\\mathrm{Ni}\\right)$ is obtained by sequentially electroreduction process with cyclic voltammetry in 1-M KOH solution containing low-concentration $\\mathrm{Pt}$ metallic salts. Abundant voids an cancy defects at the surfaceexposed interfaces of NiO/Ni heterostructure induced by crystallattice dislocation and phase transition3 9 will provide efficient sites for trapping Pt single atom. The electrodeposition of $\\mathrm{Pt_{SA}}$ - NiO/Ni leads to a black film deposited on the surface of $\\mathrm{Ag}$ NWs@cloth fabric (Fig. S1b, c). In addition, the Ag NWs@cloth fabric supported PtSA-NiO/Ni catalyst also shown high wettability (Fig. S15). The water dissociation of Volmer step in alkaline aqueous media is expected to be accelerated by O vacanciesmodified NiO near the interfaces interacted strongly with OH and metallic Ni interacted with H for $_\\mathrm{H-OH}$ bond destabilization (step (i)). Apart from the Volmer step, NiO/Ni heterostructure-supported single-atom Pt sites could show more suitable H binding ability for the conversion and deabsorption of dissociated H (step (ii)), further accelerating overall HER kinetics of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ in an alkaline condition. \n\nThe phase evolution of samples is investigated by XRD pattern as shown in Fig. 2a, in which no Pt characteristic peaks are detected, implying the absence of Pt cluster and particles in PtSANiO/Ni. The SEM (Fig. 2b, c) images show the well-distributed and open 3D nanosheets morphology for $\\mathrm{Pt_{SA}}{-}\\mathrm{NiO}/\\mathrm{Ni}$ . During the single-atom $\\mathrm{Pt}$ electroreduction process, some quantities of hydrogen bubbles are generated and released due to the high cathodic potential between 0 and $-0.50\\mathrm{V}$ versus reversible hydrogen electrode (RHE) in alkaline conditions40. In this case, the unchanged $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ nanosheets morphology on Ag NWs compared with the original NiO/Ni (Fig. S3) indicates the high structural stability of the catalyst for HER application, and the exposed NiO/Ni nanosheet could also provide more sites for Pt atoms immobilization and improve the HER performance. The TEM (Fig. S16) images suggest that the nanosheets consist of few NiO/Ni layers for $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ . The high-angle annular darkfield STEM (HAADF-STEM, Fig. 2d) image displays bright spots along with the interfaces of NiO/Ni heterostructure, corresponding to heavy constituent atoms species, which efficiently confirms the immobilization of atomically dispersed $\\mathrm{Pt}$ atoms in the NiO/ Ni nanosheets. The magnified HAADF-STEM image (Fig. 2e) suggests that the single $\\mathrm{Pt}$ atoms are mostly immobilized at the interfaces of the NiO/Ni heterostructure. Based on these findings, the atomic environment of $\\mathrm{Pt}$ atom was explored via the DFToptimized structure (Figs. 2f, $\\mathbf{g}$ and S17), and the result suggests that the $\\mathrm{Pt}$ atoms are fixed at the Ni positions by binding with O atom and Ni atoms near the interfaces of the NiO/Ni heterostructure. Here, it needs to note that the theoretical prediction is limited due to the use of the crystalline NiO model instead of amorphous-like NiO during DFT calculation. Further, the HRTEM shows one distinct lattice fringes of $0.18\\mathrm{nm}$ , matching well with metallic Ni (200) crystallographic planes (Fig. 2h). The FFT pattern (inset in Fig. 2h) shows four distinct rings: the red ring corresponds to the metallic Ni (200) plane41, and the yellow rings with the highly diffused halo are assigned to the NiO phase36,42. These results further confirm the formation of single-atom Pt-anchored NiO/Ni composition, and the interfacial coupling of $\\mathrm{\\Pt}$ single atom with NiO/Ni does not change the phase structure of NiO/Ni. Moreover, the elemental mapping, SEM image, and HAADF-STEM image (Figs. 2i–n and S18–20) show that Pt atoms are uniformly dispersed throughout NiO/Ni nanosheets. Besides, as a comparison, PtSANiO and $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ were fabricated under the same conditions as $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ but replacing NiO/Ni with NiO and $\\mathrm{Ni,}$ respectively. The corresponding HAADF-STEM images (Fig. S21) confirm the atomically dispersed Pt in the NiO and metallic Ni phase. \n\nThe electronic state evolution of the single Pt atoms in $\\mathrm{{NiO/Ni},}$ NiO, and Ni supports is explored by XPS as shown in Fig. 3a. The Pt $4f$ spectrums of $\\mathrm{Pt_{SA}}{-}\\mathrm{NiO}/\\mathrm{Ni}$ , $\\mathrm{Pt_{SA}}$ -NiO, and $\\mathrm{Pt_{SA}\\mathrm{-}N i}$ are close to $\\mathrm{\\dot{P}t^{0}}$ but show some positive shift with different extents compared with Pt foil, confirming the electrochemical reduction of $\\mathrm{PtCl}_{6}{}^{2-}$ and the electronic interaction by charge transfer from $\\mathrm{Pt}$ sites to the supports (NiO/Ni, NiO, and $\\mathrm{\\DeltaNi})^{43}$ . Specifically, the $\\mathrm{Pt}_{\\mathrm{SA}}–\\mathrm{NiO}$ shows the largest positive shift in Pt $4f$ spectrum, suggesting the maximum electron loss of Pt species44,45. Besides, the fitting curve of Pt XPS spectrums display $\\mathrm{Pt}(\\mathrm{IV})$ species in the samples, which derives from the adsorbed $\\mathrm{PtCl}_{6}{}^{2-}$ ions on the surface of the sample46,47. Further, the electronic state and atomic environment of $\\mathrm{Pt}$ atoms in NiO/Ni, NiO, and $\\mathrm{Ni}$ supports are further verified by performing X-ray absorption fine structure measurements. As shown in Fig. 3b, the evolutions of Pt $L_{3}$ -edge X-ray absorption near edge structure (XANES) spectra with different supports are distinguished, in which the intensity of white-line peaks corresponds to the transfer of the Pt $2p_{3/2}$ coreelectron to $5d$ states, and thus is used as an indicator of $\\mathrm{Pt}~5d.$ 一 band occupancy27,48. The overall white-line intensity gradually decreases as the change of support from NiO, NiO/Ni to metallic Ni, corresponding to the increase of $5d$ occupancy of Pt. Hence, higher $5d$ occupancy indicates the less charge loss of the singleatom Pt after coordinating with the supports, which is consistent with the results of XPS analysis in Fig. 3a. \n\n![](images/b4962f8f05e17c1cc333e81a1e4bd9ac6b18d34f99cda76816aa462077444dbf.jpg) \nFig. 2 Structural characterization of the fabricated $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ catalyst. a XRD patterns of $\\mathsf{P t}_{\\mathsf{S A}}$ -NiO/Ni, NiO/Ni, and $\\mathsf{A g}$ NWs. b, c SEM images of $\\mathsf{P t}_{\\mathsf{S A}}$ - NiO/Ni. d HAADF-STEM image of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ . e Magnified HAADF-STEM image of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ and $\\pmb{\\mathscr{f}},\\pmb{\\mathsf{g}}$ the illustrated interface structure by DFT calculation, showing the atomically dispersed Pt atoms at Ni position (circles in (e)). h HRTEM images of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ and the insert in ${\\bf\\Pi}({\\bf h})$ show the related FFT pattern of $\\mathsf{P t}_{\\mathsf{S A}}$ -NiO/Ni. i, j HAADF-STEM images of $\\mathsf{P t}_{\\mathsf{S A}}$ -NiO/Ni at different magnifications and $k=n$ the elemental mapping of the corresponding elementals. \n\nTo quantitate the structural information of the electronic state, the white-line peak evolution of Pt can be clearly described by the differential XANES spectra (ΔXANES, Fig. S22) by subtracting the spectra from that of Pt foil. The valence state of $\\mathrm{Pt}$ can be quantitatively examined by the integration of the white-line peak in \n\nΔXANES spectra. As shown in Fig. 3c, the average valence state of $\\mathrm{Pt}$ increase from $+0.29$ , $+0.73$ , to $+1.23$ for the $\\bar{\\mathrm{Pt}}_{\\mathrm{SA}^{-}}\\mathrm{Ni,Pt}_{\\mathrm{SA}^{-}}\\mathrm{NiO}/$ $\\mathrm{Ni,}$ and $\\mathrm{Pt_{SA}\\mathrm{-NiO}}$ catalysts, respectively. The evolution of the atomic coordination configuration of $\\mathrm{\\Pt}$ was further revealed by extended X-ray absorption fine structure spectroscopy (EXAFS, Fig. 3d), in which the typical $\\mathrm{Pt-Pt}$ contribution peak of Pt foil at about $2.7\\mathring\\mathrm{A}$ is absent for the fabricated $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ , $\\mathrm{Pt_{SA}\\mathrm{-NiO}}$ , and $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ catalysts, strongly confirming the single Pt atoms dispersion. Further, the first-shell EXAFS fitting of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ sample (Fig. 3e and Table S1) gives a coordination number (CN) of 1.3 for $\\mathrm{Pt-O}$ contribution and 5.8 for $\\mathrm{\\Pt{-}N i}$ contribution. For PtSANiO, the fitting results of EXAFS spectra suggested CN about 2.4 for $\\mathrm{Pt-O}$ contributions and 2.1 for CN for $\\mathrm{Pt-Ni}$ contributions. Whereas $\\mathrm{\\Pt{-}N i}$ contribution with 4.9 for CN and no $\\mathrm{Pt-O}$ contributions are found in the fitting of $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ EXAFS spectra. Combining the DFT-optimized structure (Fig. S23), the $\\mathrm{Pt}$ atoms are mainly immobilized at the interfacial Ni positions by coordinating with one $\\mathrm{~O~}$ atom and five Ni atoms in $\\mathrm{\\bar{Pt}_{S A}\\mathrm{-NiO/Ni}}$ . which is consistent with the conclusion of HAADF-STEM analysis (Fig. 2d–g). To more precisely clarify the atomic dispersion and coordination conditions of $\\mathrm{Pt,}$ the wavelet transform analysis was carried out due to its more efficient resolution ability in $K$ spaces and radial distance49,50, in which the atoms at similar coordination conditions and distances could be discriminated51,52. As shown in Fig. 3f, $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ displays a different intensity maximum with $\\mathrm{Pt}_{\\mathrm{SA}}–\\mathrm{NiO}$ and $\\mathrm{Pt_{SA}\\mathrm{-Ni,}}$ and especially, the intensity maximum at $7.6\\mathring\\mathrm{A}^{-1}$ for $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ is lower than that of $\\mathrm{Pt}_{\\mathrm{SA}}{\\cdot}\\mathrm{\\dot{NiO}}~(8.5\\mathrm{\\mathring{A}^{-1}})$ , but high than that of $\\mathrm{Pt_{SA}\\mathrm{-}N i}$ $(7.4\\mathring\\mathrm{A}^{-1})$ , further confirming the interfacial coordination conditions for $\\mathrm{Pt}$ atoms immobilized in NiO/Ni. Besides, the intensity maximum at $11.5\\mathring{\\mathrm{A}}^{-1}$ correspondings to $\\mathrm{Pt-Pt}$ coordination is absent in the fabricated catalysts; further confirming the successful loading of single $\\mathrm{Pt}$ atoms in $\\mathrm{Ni},$ $\\mathrm{{NiO/Ni}}$ , and NiO supports. \n\n![](images/dfbbe47f290f3e6b46525eaa32f83e3d40dead302b1235ba53f1b3e3e44f8299.jpg) \nFig. 3 Electronic state and atomic structure characterization. a Pt 4f spectra, b XANES spectra, and c calculated Pt oxidation states derived from ΔXANES spectra of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ , $\\mathsf{P t}_{\\mathsf{S A}}$ -NiO, and $\\mathsf{P t}_{\\mathsf{S A}}\\mathrm{-}\\mathsf{N i}$ , and Pt foil is given as a reference. d Corresponding FT-EXAFS curves of Fig. 3b. e EXAFS fitting curve of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ , $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O},$ and $\\mathsf{P t}_{\\mathsf{S A}}$ -Ni $R$ -space. f EXAFS wavelet transform plots of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ , $\\mathsf{P t}_{\\mathsf{S A}}$ -NiO, $\\mathsf{P t}_{\\mathsf{S A}}\\mathsf{-N i},$ and Pt foil. \n\nTheoretical investigations. Based on the above structure analysis, theoretical investigations were performed to disclose the influences of the evolved coordinate configurations of the Pt atom on the electronic structure and catalytic activity of the catalysts. According to the HAADF-STEM and EXAFS measurements, the models for $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ were shown in Fig. 4a. Based on the calculated charge density distributions, an increased charge density area along the interface of NiO/Ni heterostructure was induced (Fig. S24a, b). After coupling Pt single atom with NiO/Ni heterostructure, an electronic structure redistribution at the interfaces of the heterostructure is caused due to the different electronegativity of atoms (3.44 for O atom, 1.91 for Ni, and 2.28 for Pt). Especially, charge delocalizing from Pt to the bonded O atom and charge localizing from adjacent Ni atoms to Pt are displayed. Consequently, a locally enhanced electric field with a half-moon shape area around the \n\nPt site was generated (Fig. S24c, d), which is more intensive than that of $\\mathrm{Pt_{SA}}$ -NiO (Fig. 4b) and $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ (Fig. 4c), suggesting Pt single atom coupled with NiO/Ni heterostructure could possess the more free electrons to promote the adsorbed H conversion and $\\mathrm{H}_{2}$ evolution24,46. Moreover, the projected density of states (PDOS, Figs. 4d and S25) of the single-atom $\\mathrm{\\Pt}$ -immobilized NiO/Ni heterostructure shows higher occupation than that of the pure NiO/ Ni near the Fermi level, suggesting a promoted electron transfer and higher conductivity of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ The contrast between the PDOS of NiO/Ni and $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ reveals that the increased DOS of the $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ near the Fermi level mainly derives from the contribution of $\\operatorname*{Pt}d$ orbitals (Fig. 4d). These results suggest that the NiO/Ni heterostructure-coupled single-atom Pt can effectively enhance the total $d$ -electron domination of the catalyst near the Fermi level, which will benefit the activation of $\\mathrm{H}_{2}\\mathrm{O}$ and lead to energetically catalytic activity23,53. Moreover, the $d$ -band features of the Pt atom in NiO/Ni, NiO, and Ni coordinated configurations are investigated. The wider $5d$ band and higher density near the Fermi level for NiO/Ni-supported $\\mathrm{Pt}$ atom than that of $\\mathrm{Pt}_{\\mathrm{SA}}{-}\\mathrm{NiO}.$ and $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ (Figs. 4e and S26) suggest that the NiO/Ni-coupled $\\mathrm{\\Pt}$ atom can induce more free electrons near $\\mathrm{Pt}$ sites than $\\mathrm{Pt_{SA}\\mathrm{-NiO}}$ and $\\mathrm{Pt_{SA}\\mathrm{-Ni,}}$ which is more favorable for the H reactants adsorption and transfer. Besides, the $\\mathrm{Pt}\\ –5d$ band of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ also shows a substantially broad range for overlapping with H-1s and $_{\\mathrm{H}_{2}\\mathrm{O}-2p\\pi}$ orbitals (Fig. 4f). Therefore, the Pt site could play a protecting role for stabilizing the Ni valence state and a distributary role by binding OH and H species to low the deactivation of absorption sites in case of over-binding of intermediates on the active sites for NiO/Ni heterostructure-coupled single-atom $\\mathrm{Pt}^{54}$ . \n\n![](images/1c447523a559b5b1c80edcd174c2cb45babb819c8149ab14ae7317a0706f68b1.jpg) \nFig. 4 Theoretical investigations. Computational models and localized electric field distribution of a $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ b $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}.$ , and c $\\mathsf{P t}_{\\mathsf{S A}}$ -Ni. d Calculated PDOS of NiO/Ni and $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ , with aligned Fermi level. e Calculated Pt 5d band of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ , $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}$ and $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i}$ . f The orbital alignment of the surficial sites for $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ binding with $H_{2}O$ molecule. g Calculated $\\mathsf{O H}$ -binding energies $(\\Delta E_{\\mathrm{OH}})$ and H binding energies $(\\Delta E_{\\mathsf{H}})$ for Ni, pure NiO, and O vacancies-modified NiO surface. h Calculated energy barriers of water dissociation kinetic and i adsorption free energies of $\\mathsf{H}^{\\star}$ on the surface of the $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ , $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O},$ and $\\mathsf{P t}_{\\mathsf{S A}}$ -Ni catalysts, respectively. \n\nBased on the above finding, we further explore the reaction barrier of the fabricated catalysts for $_\\mathrm{H}_{2}\\mathrm{O}$ splitting in alkaline conditions, consisting of the dissociation of $_\\mathrm{H}_{2}\\mathrm{O}$ molecule of Volmer step and the subsequent conversion of $\\mathrm{~H~}$ to $\\mathrm{H}_{2}.$ , which mainly depends on how OH and H bond to the active sites on the surface of the catalysts55. We found that both $\\mathrm{~H~}$ and OH bind weakly to the pure NiO surface, and metallic Ni surface shows a preference for stabilizing H (Figs. $4\\mathrm{g}$ and S27). While O vacancies-modified NiO facilitates the adsorption of OH species (Figs. 4g and S28). For NiO/Ni composition, the O vacancies on the interfaces of the NiO/Ni heterostructure (Fig. S29) are induced by the crystal-lattice dislocation and phase transition37–39. As an integration, NiO/Ni-coupled single-atom $\\mathrm{Pt}$ catalyst demonstrates the strongest $_{\\mathrm{H}_{2}\\mathrm{O}}$ adsorption ability (Fig. S30) and largest energy release of $-0.09\\mathrm{eV}$ for water dissociation in Volmer step (Fig. 4h). Moreover, $\\mathrm{Pt_{SA}}{-}\\mathrm{NiO}/\\mathrm{Ni}$ hybrid catalyst only needs the minimum energy barriers $(0.31\\mathrm{eV})$ for the dissociation of $_\\mathrm{H}_{2}\\mathrm{O}$ into OH and $\\mathrm{~H~}$ under the assistance of NiO/Ni interfaces (Fig. S31) calculated by using the Ab Initio Cluster-Continuum Model, confirming the critical role of surface-exposed NiO/Ni interfaces for the $\\mathrm{H}_{2}\\mathrm{O}$ dissociation of Volmer step in alkaline media. In the subsequent step, the NiO/Ni-supported single-atom $\\mathrm{\\Pt}$ sites at the NiO/Ni interfaces act as the proton-acceptor for the recombination of the dissociated proton $(\\bar{\\mathrm{H}}^{*})$ and $\\mathrm{H}_{2}$ evolution due to its near-zero H binding energy $(-0.07\\mathrm{eV}$ , Figs. 4i and S32) and strong electron supply capacity deriving from locally enhanced charge distribution (Fig. 4a) and the higher occupation of $\\mathrm{Pt}5d$ band near Fermi lever (Fig. 4e). Consequently, the overall steps of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ hybrid catalyst for HER in alkaline media are significantly accelerated. Further, the effects of implicit solvation were considered by using VASPsol software as shown in Fig. S33, and NiO/Ni-coupled single-atom $\\mathrm{Pt}$ catalyst also demonstrates the minimum energy barriers for the dissociation of $\\mathrm{H}_{2}\\mathrm{O}$ into OH and H than that of NiO-coupled single-atom Pt and Ni-coupled single-atom Pt catalyst (Fig. S33a), confirming the critical role of surfaceexposed NiO/Ni interfaces for the $\\mathrm{H}_{2}\\mathrm{O}$ dissociation of Volmer step. Moreover, compared with $\\mathrm{Pt}_{\\mathrm{SA}}–\\mathrm{NiO}$ and $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ systems, the NiO/Ni-supported single-atom $\\mathrm{\\Pt}$ sites at the NiO/Ni interfaces also show near-zero H binding energy (Fig. S33b), which is consistent with the results of Fig. 4h, i. \n\nElectrocatalytic alkaline HER performances. Based on the structural characterizations and theoretical investigations, the Pt SAC-coupled with NiO/Ni heterostructure possesses the best intrinsic HER activity in alkaline media among the fabricated catalysts. Thus, the electrocatalytic activities of $\\mathrm{\\bar{Pt}_{S A}\\mathrm{-NiO/Ni}}$ for alkaline HER were measured in 1-M KOH solution. As a comparison, the HER performance of $\\mathrm{Pt_{SA}\\mathrm{-}N i O}$ , $\\mathrm{Pt_{SA}\\mathrm{-}N i},$ , $\\mathrm{NiO/Ni}$ , and $20\\%$ $\\mathrm{Pt/C}$ was also tested under the same conditions. As shown in Fig. 5, the $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ shows the highest HER performance among all catalysts, and only needs a quite low overpotential of 26 and $85\\mathrm{mV}$ to achieve the current density of 10 and $100\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively, significantly superior to the PtSANiO, $\\mathrm{Pt_{SA}\\mathrm{-Ni}}$ , $\\mathrm{NiO/Ni},$ and the $\\mathrm{Pt/C}$ catalyst (Fig. 5b). Moreover, the mass activity of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ normalized to the loaded $\\mathrm{\\Pt}$ mass $(1.14\\mathrm{wt\\%}$ , inductively coupled plasma-mass spectrometry) at an overpotential of $100\\mathrm{mV}$ is $20.{\\overset{\\cdot}{6}}\\operatorname{A}\\operatorname*{mg}^{-1}$ , which is 2.4, 2.3, and 41.2 times greater than that of $\\mathrm{Pt}_{\\mathrm{SA}}–\\mathrm{NiO}$ $(8.5\\mathrm{A}\\mathrm{mg}^{-1}\\mathrm{\\Omega},$ ), $\\mathrm{Pt_{SA}-}$ Ni $(9.0\\mathrm{A}\\mathrm{mg}^{-1}\\mathrm{\\dot{\\Omega}},$ , and the commercial $\\mathrm{Pt/C}$ catalyst $(0.5\\mathrm{A}\\mathrm{mg}^{-1}\\mathrm{\\Omega}.$ ), respectively. These results suggest that single $\\mathrm{Pt}$ atoms coupled with NiO/Ni can maximize the alkaline HER activity of $\\mathrm{\\Pt}$ -based catalysts, leading to a significant reduction in cost. In addition, the $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ exhibits a smaller Tafel slope of $27.07\\mathrm{mV}\\mathrm{dec}^{-1}$ than $\\mathrm{Pt}_{\\mathrm{SA}^{-}}\\mathrm{NiO}$ $(37.54\\mathrm{mV}\\mathrm{dec^{-1}}^{.}$ ), $\\mathrm{Pt_{SA}}{-}\\mathrm{\\bar{Ni}}$ $(37.32\\mathrm{mV}\\mathrm{dec}^{-1})$ , NiO/Ni $(58.67\\mathrm{mV}\\mathrm{dec}^{-1}),$ ), and $\\mathrm{Pt/C}$ catalyst $(41.69\\mathrm{mV}\\mathrm{dec}^{-1}),$ , which suggests a typical Volmer-Tafel mechanism for alkaline HER and implies that the rate-determining step of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ is the $\\mathrm{H}_{2}$ desorption (Tafel step) rather than the $_{\\mathrm{H}_{2}\\mathrm{O}}$ dissociation (Volmer step)34,56. Besides, $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ catalyst exhibits a 2.0, and 2.4-fold enhancement in the double-layer capacitance $(C_{\\mathrm{dl}})$ over $\\mathrm{Pt_{SA}\\mathrm{-NiO}}$ and $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ (Fig. S34), respectively, suggesting the favorable nanostructure with more sites for $\\mathrm{\\Pt}$ atoms immobilization and HER. Furthermore, the charge transfer resistance $(R_{\\mathrm{ct}})$ of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ (0.61 ohm, Fig. 5e) is low than that of $\\mathrm{Pt}_{\\mathrm{SA}^{-}}\\mathrm{NiO}.$ $\\mathrm{Pt_{SA}\\mathrm{-Ni_{:}}}$ and NiO/Ni catalysts, which mainly originates from the introduction of cloth fabric substrate and Ag NWs (Figs. S35 and 36) and the enhanced electronic structure of single Pt atoms coupled with NiO/Ni. \n\n![](images/11c65602d65b7c5161297f6b3883aac9350c0f5309f13435f28266bd2fde382f.jpg) \nFig. 5 Electrocatalytic alkaline HER performances of the catalysts in 1-M KOH electrolyte. a HER polarization curves of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ , ${\\mathsf{P t}}_{\\mathsf{S A}^{-}}{\\mathsf{N i O}},$ $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i},$ NiO/Ni, and Pt/C. b The comparison of overpotentials required to achieve 10 and $100\\mathsf{m A c m}^{-2}$ for various catalysts. c The mass activity of the Pt-based catalysts. d Corresponding Tafel slope originated from LSV curves. e EIS (Electrochemical Impedance Spectroscopy) Nyquist plots of the catalysts. f Stability test of $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ through cyclic potential scanning and chronoamperometry method (inset in f). g TOFs plots of the Pt-based electrocatalysts. h Comparison of the HER activity for $\\mathsf{P t}_{\\mathsf{S A}^{-}}\\mathsf{N i O}/\\mathsf{N i}$ with reported catalysts, originating from Table S3. \n\nFor real applications, HER catalyzing stability is another essential factor. As present in Fig. 5f, the $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ shows high durability in the alkaline electrolyte with negligible loss in HER performance for 5000 cycles or $30\\mathrm{h}$ . The characterizations of $\\mathrm{\\bar{Pt}_{S A}\\mathrm{-NiO/Ni}}$ after the stability test, including HAADF-STEM images, elemental mapping, and double-layer capacitance (Figs. S37–39), suggest the negligible structure changes and single-atom dispersion for $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ after long-term alkaline HER. Moreover, the turnover frequencies (TOFs) per Pt atom site are analyzed, and the TOFs of $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ (5.71 $\\begin{array}{r}{\\mathrm{H}_{2}\\ s^{-1},}\\end{array}$ are 2.02, 1.99, and 38.06 times higher than that of $\\mathrm{Pt_{SA}}$ -NiO, $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ , and $\\mathrm{Pt/C}$ catalyst, respectively (Fig. 5g). To our knowledge, the electrocatalytic HER performances of our $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ catalyst in the alkaline media are almost optimal among the reported SACs, and are comparable with the performances of catalysts in acid media (Fig. 5h and Table S3), confirming the advance by the constructing single Pt sites in NiO/Ni hybrid system. \n\nFurther, based on the highly intrinsic HER activity, the electrocatalytic HER performances of the catalysts in neutral electrolytes containing 1.0-M phosphate buffer solutions $\\mathrm{(pH=}$ 7.0) are investigated as shown in Fig. S40. $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ shows the highest HER performance among all catalysts in neutral electrolytes, and only needs a quite low overpotential of 27 and $159\\mathrm{mV}$ to achieve the current density of 10 and $100\\mathrm{mA}\\mathrm{cm}^{-2}$ , respectively, significantly superior to the $\\mathrm{Pt_{SA}}$ -NiO, PtSA-Ni, NiO/ Ni, and the $\\mathrm{Pt/C}$ catalyst (Fig. S40b). Moreover, Fig. S40c presents a small Tafel slope $(31.94\\mathrm{m}\\mathrm{\\bar{V}}\\mathrm{dec}^{-1})$ for $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni},}$ lower than that of $\\mathrm{Pt_{SA}\\mathrm{-Ni\\bar{O}}}$ $(47.26\\mathrm{mV}\\mathrm{dec}^{-1})$ , $\\mathrm{Pt_{SA}\\mathrm{-Ni}}$ $(40.68\\mathrm{mV}\\mathrm{dec}^{-1}),$ , and $\\mathrm{Pt/C}$ catalyst $(42.40\\mathrm{mV}\\mathrm{dec}^{-1}),$ ), revealing fast HER kinetics for NiO/Ni heterostructure-coupled $\\mathrm{Pt}$ single atoms. The above merits of the $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ , including low overpotential and Tafel slope, are superior to most previously reported catalysts in the neutral solution (Fig. S40d and Table S4), further confirming the advance by the constructing single $\\mathrm{Pt}$ sites in NiO/Ni hybrid system. \n\n# Discussion \n\nIn summary, we reported a single-atom Pt ( $\\mathrm{(Pt_{SA})}$ immobilized NiO/Ni heterostructure nanosheets on $\\mathrm{Ag}$ NWs network nanocomposite by the facile electrodeposition strategy, which serves as an efficient electrocatalyst for vigorous hydrogen production in alkaline media. Theoretical calculations revealed that the Pt SACs coupled with NiO/Ni heterostructure could efficiently tailoring water dissociation energy for accelerating alkaline HER. In particular, the dual active sites consisting of metallic Ni sites and O vacancies-modified NiO sites near the interfaces of $\\mathrm{{NiO/Ni}}$ have the preferred adsorption affinity toward both $\\mathrm{OH^{*}}$ and $\\mathrm{H^{*}}$ , which facilitates water adsorption and reaches a barrier-free water dissociation step with the lowest energy barrier of $0.31\\mathrm{eV}$ in Volmer step (step (i)) for $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ compared with that of $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ $(0.47\\mathrm{eV})$ and PtSA-NiO $(1.42\\mathrm{eV})$ catalysts. Besides, fixing Pt atoms at the NiO/Ni interfaces induce a higher occupation of the $\\mathrm{Pt}~5d$ band at the Fermi level and the more suitable H binding energy $(\\Delta G_{\\mathrm{H^{*}}},-0.07\\mathrm{eV})$ than that of $\\mathrm{Pt}$ atoms at the NiO $(\\Delta G_{\\mathrm{H^{*}}}$ $0.74\\mathrm{eV})$ and Ni $(\\Delta G_{\\mathrm{H^{*}}},-0.38\\mathrm{eV})$ , which efficiently promotes the $\\mathrm{H^{*}}$ conversion and $\\mathrm{H}_{2}$ desorption, thus accelerating overall alkaline HER. The further enhancement of alkaline HER performance was achieved by introducing the Ag NWs network into 2D $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ nanosheets to construct a seamlessly conductive 3D nanostructure. The unique nanostructural feature and highly conductive Ag NWs network provide abundant active sites and accessible channels for electron transfer and mass transport. Consequently, the 3D $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ catalyst shows outstanding HER performances in alkaline conditions with a quite low overpotential of $26\\mathrm{mV}$ at a current density of $10\\mathrm{mA}\\mathrm{\\bar{c}}\\mathrm{m}^{-2}$ and high mass activity of $20.6\\mathrm{A}\\mathrm{mg^{-1}\\ P t}$ in 1-M KOH, significantly outperforming the reported catalysts. This study opens an efficient avenue for the advance of SACs by introducing a water dissociation kinetic-oriented material system. \n\n# Methods \n\nSynthesis of ${\\pmb A}{\\pmb g}$ NWs. An oil bath method was used to synthesize Ag NWs according to our previous report57. Specifically, a mix solution consisting of ethylene glycol, $\\mathrm{FeCl}_{3}$ $(7.19\\mathrm{mM})$ , ${\\mathrm{AgNO}}_{3}$ (0.051 M), and polyvinylpyrrolidone (0.012 M) was heat and maintained under an oil bath pan with $110^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . After that, the generated precipitate was washed with acetone and alcohol to get the pure Ag NWs. Subsequently, the Ag NWs were uniformly dispersed on a flexible cloth fabric by spray coating technology to fabricate a conductive network. \n\nSynthesis of NiO/Ni on Ag NWs. Ni/NiO is grown on $\\mathrm{Ag}$ NWs network by a facile electrodeposition process in the aqueous electrolyte of $20\\mathrm{-mM}$ \n\n$\\mathrm{C_{4}H_{6}N i O_{4}{\\cdot}4H_{2}O}$ according to the recent report36. The electrodeposition process was performed by chronoamperometry method with $-3\\mathrm{V}$ versus SCE for $200\\mathrm{{s}}$ under a standard three-electrode system, in which graphite sheet acted as a counter electrode, SCE acted as a reference electrode, and the fabricated $\\mathbf{A}\\mathbf{g}$ NWs network loaded on the cloth was directly used as working electrode. The obtained samples were washed with deionized water and then dried at room temperature. \n\nSynthesis of NiO on ${\\pmb A}{\\pmb g}$ NWs. NiO is grown on Ag NWs network by the electrodeposition process with $-1\\mathrm{V}$ versus SCE for $600\\mathrm{s}$ in an aqueous electrolyte of $20\\mathrm{-}\\mathrm{mM}$ $\\mathrm{C_{4}H_{6}N i O_{4}{\\cdot}4H_{2}O}$ . The obtained samples were washed with deionized water and then dried at room temperature. \n\nSynthesis of Ni on ${\\pmb A}{\\pmb g}$ NWs. Metallic Ni is grown on Ag NWs network by the electrodeposition process in an aqueous solution consisting of $0.10{\\cdot}\\mathrm{M}\\mathrm{Ni}\\mathrm{Cl}_{2}$ , 0.09- M $\\mathrm{H}_{3}\\mathrm{BO}_{3}$ and a solvent containing ethanol and deionized water with 2:5 in volume ratio. The electrodeposition process was performed by chronoamperometry with $-1.2\\mathrm{V}$ versus SCE for $200\\mathrm{s}$ . The obtained samples were washed with deionized water and then dried at room temperature. \n\nSynthesis of $P t_{S A}-N i O/N i$ on ${\\pmb A}{\\pmb g}$ NWs. $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ on Ag NWs was fabricated by the electrochemical reduction process in the three-electrode system, in which the fabricated NiO/Ni on Ag NWs was performed as the working electrode, graphite sheet acted as a counter electrode, saturated calomel electrode acted as a reference electrode. The corresponding electrochemical process was carried out by multi-cycle cathode polarization in 1-M KOH solution containing 50- $\\upmu\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ with a scan rate of $\\bar{50}\\mathrm{mVs^{-1}}$ between 0 and $-0.50\\mathrm{V}$ versus RHE for 200 cycles. \n\nSynthesis of $P t_{S A}$ -NiO on $\\pmb{A}\\pmb{g}$ NWs. $\\mathrm{Pt_{SA}}$ -NiO on $\\mathrm{Ag}$ NWs was fabricated by multi-cycle cathode polarization in 1-M KOH solution containing $50{\\mathrm{-}}{\\upmu\\mathrm{M}}\\ \\mathrm{H}_{2}{\\mathrm{PtCl}}_{6}$ with a scan rate of $50\\mathrm{mV}s^{-1}$ between 0 and $-0.50\\mathrm{V}$ versus RHE for 200 cycles. \n\nSynthesis of $P t_{S A}=N i$ on ${\\pmb A}{\\pmb g}$ NWs. $\\mathrm{Pt_{SA}}{-}\\mathrm{Ni}$ on $\\mathrm{Ag}$ NWs was fabricated by multicycle cathode polarization in 1-M KOH solution containing 50-μM $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ with a scan rate of $5\\mathrm{{0}\\mathrm{{mVs^{-1}}}}$ between 0 and $-0.50\\mathrm{V}$ versus RHE for 200 cycles. \n\nCharacterizations. The morphology measurement of the synthesized catalysts was performed by SEM (GeminiSEM 300). HRTEM images, HAADF-STEM images, and STEM-EDS mapping images were obtained by an FEI Titan $\\mathrm{\\bfG}^{2}$ microscope equipped with an aberration corrector for probe-forming lens and a Bruker SuperX energy dispersive spectrometer operated at $300\\mathrm{kV}$ . The Pt contents in the catalysts were measured by inductively coupled plasma optical emission spectrometry. The XPS spectra of elementals were tested by a surface analysis system (ESCALAB250Xi). The phase and crystal information were obtained by Cu Kα radiation in an X-ray diffractometer (XRD, Bruker, D8 Advance Davinci). The EXAFS measurement of the $\\mathrm{Pt_{SA}\\mathrm{-NiO/Ni}}$ , $\\mathrm{Pt_{SA}}$ -NiO, and $\\mathrm{Pt_{SA}}{-}\\mathrm{NiO}/\\mathrm{Ni}$ at the Pt $L_{3}$ -edge was performed at 1W1B station at the Beijing Synchrotron Radiation Facility. Data analysis and fitting were performed with Athena and Artemis in the Demeter package. \n\nElectrochemical measurements. All electrochemical measurements were finished by an electrochemical workstation $\\mathrm{CHI}660\\mathrm{E})$ with a three-electrode configuration, in which fabricated catalysts were directly employed as the working electrode, graphite sheet acted as a counter electrode, saturated calomel electrode acted as a reference electrode. All the presented potential in this work was transferred to RHE according to an experimental method53. LSV with $95\\%$ iR-corrections were tested under the potential range from 0.05 to $-0.5\\mathrm{V}$ and the scan rate of $5\\mathrm{mVs^{-1}}$ . EIS was obtained by a frequency range from $100\\mathrm{k}$ to $0.1\\mathrm{Hz}$ with an overpotential of $230\\mathrm{mV}$ versus RHE. For the preparation of 3D $\\mathrm{Pt/C}\\ @\\mathrm{Ni}$ foam, $5\\mathrm{mg}20\\mathrm{-wt\\%}$ Pt/C was dispersed in $_{0.9-\\mathrm{mL}}$ alcohol containing $0.1\\mathrm{mL}5\\mathrm{-wt\\%}$ Nafion solution to form a homogeneous ink. Then, the obtained ink was coated on the Ni foam and dried in air to form a porous $\\mathrm{Pt/C@Ni}$ foam electrode. \n\nDFT theoretical calculations. All the structural optimizations, charge density difference analysis, Bader charge analysis, and energy calculations were carried out based on DFT as implemented in the Vienna Ab initio Simulation Package58–60. The projector-augmented wave method was implemented to calculate the interaction between the ionic cores and valence electrons61,62. The Perdew–Burke–Ernzerhof approach of spin-polarized generalized gradient approximation was used to describe the exchange-correlation energy63. Calculations were performed with the cutoff plane-wave kinetic energy of $500\\mathrm{eV}$ , and ${8\\times}$ $4\\times1$ $k$ -mesh grids were employed for the integration of the Brillouin zone. Electronic relaxation was undertaken to utilize the conjugate-gradient method64 with the total energy convergence criterion being $10^{-5}\\mathrm{eV}$ . Geometry optimization was employed by the quasi-Newton algorithm65,66 until all the residual forces on unconstrained atoms $<0.01\\ \\mathrm{eV}/\\mathrm{\\AA}$ . Climbing image nudge elastic band calculations67 were employed for finding transition barriers with the initial configuration of $_\\mathrm{H}_{2}\\mathrm{O}$ absorbed on the catalyst surface and final configuration of $\\mathrm{OH+}$ \n\nH absorbed on the catalyst surface. To ensure the initial configuration correctly, an $\\mathrm{H}_{2}\\mathrm{O}$ molecule was deposited on the catalyst surface and relaxed for calculating its local minimum total energy on different sites, and the last one is the initially stable configuration. The final configuration is also found by relaxing OH and H near the $_\\mathrm{H}_{2}\\mathrm{O}$ absorbed site of the initial configuration. Next, The equation for calculating adsorption enthalpy $\\Delta\\mathrm{E_{H^{*}}}$ as the following: \n\n$$\n\\Delta E_{\\mathrm{H^{*}}}=E_{\\mathrm{slab+H}}-E_{\\mathrm{slab}}-\\frac{1}{2}E_{\\mathrm{H_{2}}}\n$$ \n\nwhere the $E_{\\mathrm{slab+H}}$ is the total enthalpy of $\\mathrm{~H~}$ adsorbing on the catalysts, the enthalpy of the catalysts is $E_{\\mathrm{slab}},$ and the $\\mathrm{H}_{2}$ enthalpy is $E_{\\mathrm{H_{2}}}$ . \n\nThe $\\mathrm{~H~}$ and $\\mathrm{H}_{2}\\mathrm{O}$ absorbing on the slabs were investigated by comparing the formation energy of different sites. The equation for calculating adsorption enthalpy $\\Delta\\mathrm{E_{H^{*}}}$ as the following: \n\n$$\n\\Delta E_{\\mathrm{H^{*}}}=E_{\\mathrm{slab+H}}-E_{\\mathrm{slab}}-\\frac{1}{2}E_{\\mathrm{H_{2}}}\n$$ \n\nwhere the $E_{\\mathrm{slab+H}}$ is the total enthalpy of $\\mathrm{~H~}$ adsorbing on the catalysts, enthalpy of the catalysts is $E_{\\mathrm{slab}},$ the $\\mathrm{H}_{2}$ enthalpy is $E_{\\mathrm{H_{2}}}$ . As similar, the equation for calculating the $_\\mathrm{H_{2}O}$ adsorption enthalpy $\\Delta E_{\\mathrm{H_{2}O^{*}}}$ as the following: \n\n$$\n\\Delta E_{\\mathrm{H_{2}O^{*}}}=E_{\\mathrm{slab+H_{2}O}}-E_{\\mathrm{slab}}-E_{\\mathrm{H_{2}O^{*}}}\n$$ \n\nThe free energy of adsorbed $\\mathrm{~H~}$ and $_\\mathrm{H}_{2}\\mathrm{O}$ as follows: \n\n$$\n\\Delta G_{\\mathrm{H^{*}}}=\\Delta E_{\\mathrm{H^{*}}}+\\Delta E_{\\mathrm{ZPE}}-T\\Delta S\n$$ \n\n$$\n\\Delta G_{\\mathrm{H_{2}O^{*}}}=\\Delta E_{\\mathrm{H_{2}O^{*}}}+\\Delta E_{\\mathrm{ZPE}}-T\\Delta S\n$$ \n\nwhere $\\Delta E_{\\mathrm{H^{*}}}$ represent the $\\mathrm{~H~}$ adsorption energy and $\\Delta E_{\\mathrm{H_{2}O^{*}}}$ represent the $\\mathrm{H}_{2}\\mathrm{O}$ adsorption energy, and $\\Delta E_{\\mathrm{ZPE}}$ represents the difference related to the zero-point energy between the gas phase and the adsorbed state. \n\n# Data availability \n\nThe data that support the findings of this work are available from the corresponding author upon reasonable request. \n\nReceived: 25 January 2021; Accepted: 1 June 2021; Published online: 18 June 2021 \n\n# References \n\n1. Turner, J. A. Sustainable hydrogen production. Science 305, 972–974 (2004). \n2. Dresselhaus, M. et al. Alternative energy technologies. Nature 414, 332–337 (2001). \n3. Jiao, Y. et al. Design of electrocatalysts for oxygen-and hydrogen-involving energy conversion reactions. Chem. Soc. Rev. 44, 2060–2086 (2015). \n4. Wang, P. et al. Phase and interface engineering of platinum-nickel nanowires for efficient electrochemical hydrogen evolution. Angew. Chem. Int. Ed. 128, 13051–13055 (2016). \n5. Morales-Guio, C. G. et al. Nanostructured hydrotreating catalysts for electrochemical hydrogen evolution. Chem. Soc. Rev. 43, 6555–6569 (2014). \n6. Lv, H. et al. A new core/shell $\\mathrm{NiAu/Au}$ nanoparticle catalyst with Pt-like activity for hydrogen evolution reaction. J. Am. Chem. Soc. 137, 5859–5862 (2015). \n7. Laursen, A. et al. Nanocrystalline $\\mathrm{Ni}_{5}\\mathrm{P}_{4}$ : a hydrogen evolution electrocatalyst of exceptional efficiency in both alkaline and acidic media. Energy Environ. Sci. 8, 1027–1034 (2015). \n8. Laursen, A. B. et al. Climbing the volcano of electrocatalytic activity while avoiding catalyst corrosion: ${\\mathrm{Ni}}_{3}{\\mathrm{P}}$ , a hydrogen evolution electrocatalyst stable in both acid and alkali. ACS Cat. 8, 4408–4419 (2018). \n9. Lai, J. et al. Strongly coupled nickel-cobalt nitrides/carbon hybrid nanocages with pt-like activity for hydrogen evolution catalysis. Adv. Mater. 31, 1805541 (2019). \n10. Xie, X. et al. Electrocatalytic hydrogen evolution in neutral ph solutions: dualphase synergy. ACS Cat. 9, 8712–8718 (2019). \n11. Lv, F. et al. Ir-based alloy nanoflowers with optimized hydrogen binding energy as bifunctional electrocatalysts for overall water splitting. Small Methods 4, 1900129 (2020). \n12. Li, Y. et al. Ru nanoassembly catalysts for hydrogen evolution and oxidation reactions in electrolytes at various pH values. Appl. Catal. B. 258, 117952 (2019). \n13. Jones, J. et al. Thermally stable single-atom platinum-on-ceria catalysts via atom trapping. Science 353, 150–154 (2016). \n14. Li, H. et al. Synergetic interaction between neighbouring platinum monomers in $\\mathrm{CO}_{2}$ hydrogenation. Nat. Nanotech. 13, 411–417 (2018). \n15. Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}}/\\mathrm{FeO}_{x}.$ Nat. Chem. 3, 634–641 (2011). \n16. Li, X. et al. Single-atom Pt as co-catalyst for enhanced photocatalytic $\\mathrm{H}_{2}$ evolution. Adv. Mater. 28, 2427–2431 (2016). \n17. Ledezma-Yanez, I. et al. Interfacial water reorganization as a pH-dependent descriptor of the hydrogen evolution rate on platinum electrodes. Nat. Energy 2, 1–7 (2017). \n18. Subbaraman, R. et al. Enhancing hydrogen evolution activity in water splitting by tailoring $\\mathrm{Li^{+}{-}N i(O H)}_{2}$ -Pt interfaces. Science 334, 1256–1260 (2011). \n19. Stamenkovic, V. R. et al. Energy and fuels from electrochemical interfaces. Nat. Mater. 16, 57–69 (2017). \n20. Durst, J. et al. New insights into the electrochemical hydrogen oxidation and evolution reaction mechanism. Energy Environ. Sci. 7, 2255–2260 (2014). \n21. Wang, D. et al. Atomic and electronic modulation of self-supported nickelvanadium layered double hydroxide to accelerate water splitting kinetics. Nat. Commun. 10, 1–12 (2019). \n22. Zhang, J. et al. Efficient hydrogen production on $\\mathrm{MoNi_{4}}$ electrocatalysts with fast water dissociation kinetics. Nat. Commun. 8, 1–8 (2017). \n23. Zhang, J. et al. Single platinum atoms immobilized on an MXene as an efficient catalyst for the hydrogen evolution reaction. Nat. Catal. 1, 985–992 (2018). \n24. Liu, D. et al. Atomically dispersed platinum supported on curved carbon supports for efficient electrocatalytic hydrogen evolution. Nat. Energy 4, 512–518 (2019). \n25. Jiang, K. et al. Single platinum atoms embedded in nanoporous cobalt selenide as electrocatalyst for accelerating hydrogen evolution reaction. Nat. Commun. 10, 1743 (2019). \n26. Deng, J. et al. Triggering the electrocatalytic hydrogen evolution activity of inert two-dimensional $\\ensuremath{\\mathrm{MoS}}_{2}$ surface via single-atom metal doping. Energy Environ. Sci. 8, 1594–1601 (2015). \n27. Cheng, N. et al. Platinum single-atom and cluster catalysis of the hydrogen evolution reaction. Nat. Commun. 7, 13638 (2016). \n28. Huabin, Z. et al. Dynamic traction of lattice-confined platinum atoms into mesoporous carbon matrix for hydrogen evolution reaction. Sci. Adv. 4, eaao6657 (2018). \n29. Zhang, B. et al. Dual-descriptor tailoring: the hydroxyl adsorption energydependent hydrogen evolution kinetics of high-valance state doped $\\mathrm{Ni}_{3}\\mathrm{N}$ in alkaline media. ACS Cat. 9, 9332–9338 (2019). \n30. Subbaraman, R. et al. Trends in activity for the water electrolyser reactions on 3d $\\mathrm{M(Ni,Co,Fe,Mn)}$ hydr(oxy)oxide catalysts. Nat. Mater. 11, 550–557 (2012). \n31. Sheng, W. et al. Correlating hydrogen oxidation and evolution activity on platinum at different pH with measured hydrogen binding energy. Nat. Commun. 6, 5848 (2015). \n32. Chen, G. et al. Accelerated hydrogen evolution kinetics on NiFe-layered double hydroxide electrocatalysts by tailoring water dissociation active sites. Adv. Mater. 30, 1706279 (2018). \n33. Li, F. et al. Balancing hydrogen adsorption/desorption by orbital modulation for efficient hydrogen evolution catalysis. Nat. Commun. 10, 1–7 (2019). \n34. Huang, J. et al. Boosting hydrogen transfer during volmer reaction at oxides/ metal nanocomposites for efficient alkaline hydrogen evolution. ACS Energy Lett. 4, 3002–3010 (2019). \n35. Zhou, K. et al. A Setaria-inflorescence-structured catalyst based on nickelcobalt wrapped silver nanowire conductive networks for highly efficient hydrogen evolution. J. Mater. Chem. A 7, 26566–26573 (2019). \n36. Li, X. et al. Sequential electrodeposition of bifunctional catalytically active structures in $\\mathrm{MoO}_{3}/\\mathrm{Ni}$ -NiO composite electrocatalysts for selective hydrogen and oxygen evolution. Adv. Mater. 32, 2003414 (2020). \n37. Han, S.-K. et al. Precursor triggering synthesis of self-coupled sulfide polymorphs with enhanced photoelectrochemical properties. J. Am. Chem. Soc. 138, 12913–12919 (2016). \n38. Wu, X.-J. et al. Controlled growth of high-density CdS and CdSe nanorod arrays on selective facets of two-dimensional semiconductor nanoplates. Nat. Chem. 8, 470–475 (2016). \n39. Feng, Y. et al. Selectively anchoring $\\mathrm{\\Pt}$ single atoms at hetero-interfaces of γ- $\\mathrm{Al}_{2}\\mathrm{O}_{3}/\\mathrm{NiS}$ to promote the hydrogen evolution reaction. J. Mater. Chem. A 6, 11783–11789 (2018). \n40. Hsu, P.-C. et al. Hydrogen bubbles and the growth morphology of ramified zinc by electrodeposition. J. Electrochem. Soc. 155, D400 (2008). \n41. Xu, D. et al. Simple coordination complex-derived Ni NP anchored N-doped porous carbons with high performance for reduction of nitroarenes. CrystEngComm 19, 6612–6619 (2017). \n42. Xu, X. et al. The preparation of hierarchical tubular structures comprised of NiO nanosheets with enhanced supercapacitive performance. RSC Adv. 4, 3181–3187 (2014). \n43. Ye, S. et al. Highly stable single Pt atomic sites anchored on aniline-stacked graphene for hydrogen evolution reaction. Energy Environ. Sci. 12, 1000–1007 (2019). \n44. Hunt, S. T. et al. Activating earth-abundant electrocatalysts for efficient, low-cost hydrogen evolution/oxidation: sub-monolayer platinum coatings on titanium tungsten carbide nanoparticles. Energy Environ. Sci. 9, 3290–3301 (2016). \n45. Huang, X. et al. High-performance transition metal-doped $\\mathrm{Pt}_{3}\\mathrm{Ni}$ octahedra for oxygen reduction reaction. Science 348, 1230–1234 (2015). \n46. Zhou, K. et al. Seamlessly conductive ${\\mathrm{Co}}({\\mathrm{OH}})_{2}$ tailored atomically dispersed pt electrocatalyst in hierarchical nanostructure for efficient hydrogen evolution reaction. Energy Environ. Sci. 13, 3082–3092 (2020). \n47. Romanchenko, A. et al. X-ray photoelectron spectroscopy (XPS) study of the products formed on sulfide minerals upon the interaction with aqueous platinum (IV) chloride complexes. Minerals 8, 578 (2018). \n48. Cai, W. et al. Platinum-trimer decorated cobalt-palladium core-shell nanocatalyst with promising performance for oxygen reduction reaction. Nat. Commun. 10, 440 (2019). \n49. Fei, H. et al. Atomic cobalt on nitrogen-doped graphene for hydrogen generation. Nat. Commun. 6, 8668 (2015). \n50. Kwak, J. et al. Coordinatively unsaturated $\\mathrm{Al}^{3+}$ centers as binding sites for active catalyst phases of platinum on ${\\bf-A l_{2}O_{3}}$ . Science 325, 1670–1673 (2009). \n51. Savinelli, R. et al. Wavelet transform EXAFS analysis of mono- and dimolybdate model compounds and a Mo/HZSM-5 dehydroaromatization catalyst. Phys. Chem. Chem. Phys. 12, 5660–5667 (2010). \n52. Funke, H. et al. Wavelet analysis of extended $\\mathbf{x}$ -ray absorption fine structure data. Phys. Rev. B 71(9), 094110–094110.7 (2005). \n53. Fang, S. et al. Uncovering near-free platinum single-atom dynamics during electrochemical hydrogen evolution reaction. Nat. Commun. 11, 1029 (2020). \n54. Yin, J. et al. Iridium single atoms coupling with oxygen vacancies boosts oxygen evolution reaction in acid media. J. Am. Chem. Soc. 142, 18378–18386 (2020). \n55. Dinh, C. T. et al. Multi-site electrocatalysts for hydrogen evolution in neutral media by destabilization of water molecules. Nat. Energy 4, 107–114 (2019). \n56. Shi, Y. et al. Recent advances in transition metal phosphide nanomaterials: Synthesis and applications in hydrogen evolution reaction. Chem. Soc. Rev. 45, 1529–1541 (2016). \n57. Zhou, K. L. et al. Highly stable transparent conductive electrodes based on silver–platinum alloy-walled hollow nanowires for optoelectronic devices. ACS Appl. Mater. Interfaces 10, 36128–36135 (2018). \n58. Kresse, G. G. et al. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n59. Kresse, G. G. et al. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n60. Kresse, G. G. et al. Ab initio molecular-dynamics simulation of the liquidmetal-amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251–14269 (1994). \n61. Blöchl, P. et al. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n62. Kresse, G. G. et al. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n63. Perdew, J. P. et al. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n64. Payne, M. C. et al. Iterative minimization techniques for ab initio total-energy calculations: molecular dynamics and conjugate gradients. Rev. Mod. Phys. 64, 1045–1097 (1992). \n65. Methfessel, M. et al. High-precision sampling for Brillouin-zone integration in metals. Phys. Rev. B 40, 3616–3621 (1989). \n66. Pulay, P. Convergence acceleration of iterative sequences. The case of SCF iteration. Chem. Phys. Lett. 73, 393–398 (1980). \n\n67. Henkelman, G. et al. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000). \n\n# Acknowledgements \n\nThis work was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 52070006, 11804012, 12074017), the Scientific and Technological Development Project of the Beijing Education Committee (No. KZ201710005009), and the Beijing Municipal Education Commission (Grant No. KM201910005009), the Beijing municipal high level innovative team building program (IDHT20190503) and the National Natural Science Fund for Innovative Research Groups of China (51621003). \n\n# Author contributions \n\nH.W. and H.Y. supervised this study. K.L.Z. conceived the idea. K.L.Z., Z.W., C.W., and Y.J. planned and carried out the experiments, collected, and analyzed the experimental data. X.K. and Q.Z. performed SEM and TEM characterizations. C.W. and K.L.Z. conducted theoretical calculations. K.L.Z., J.L., and C.B.H. wrote the paper. All the authors have discussed the results and wrote the paper together. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-24079-8. \n\nCorrespondence and requests for materials should be addressed to C.B.H., X.K. or H.W \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contributions to the peer review of this work. Peer review reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41467-020-20646-7", + "DOI": "10.1038/s41467-020-20646-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-20646-7", + "Relative Dir Path": "mds/10.1038_s41467-020-20646-7", + "Article Title": "A structural polymer for highly efficient all-day passive radiative cooling", + "Authors": "Wang, T; Wu, Y; Shi, L; Hu, XH; Chen, M; Wu, LM", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "All-day passive radiative cooling has recently attracted tremendous interest by reflecting sunlight and radiating heat to the ultracold outer space. While some progress has been made, it still remains big challenge in fabricating highly efficient and low-cost radiative coolers for all-day and all-climates. Herein, we report a hierarchically structured polymethyl methacrylate (PMMA) film with a micropore array combined with random nullopores for highly efficient day- and nighttime passive radiative cooling. This hierarchically porous array PMMA film exhibits sufficiently high solar reflectance (0.95) and superior longwave infrared thermal emittance (0.98) and realizes subambient cooling of similar to 8.2 degrees C during the night and similar to 6.0 degrees C to similar to 8.9 degrees C during midday with an average cooling power of similar to 85W/m(2) under solar intensity of similar to 900W/m(2), and promisingly similar to 5.5 degrees C even under solar intensity of similar to 930W/m(2) and relative humidity of similar to 64% in hot and moist climate. The micropores and nullopores in the polymer film play crucial roles in enhancing the solar reflectance and thermal emittance. There still remains a big challenge in fabricating highly efficient and low-cost radiative coolers for all-day and all-climates. Here, the authors report a hierarchically structured polymethyl methacrylate film with a micropore array combined with random nullopores for highly efficient day- and nighttime passive radiative cooling.", + "Times Cited, WoS Core": 545, + "Times Cited, All Databases": 574, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000610677200001", + "Markdown": "# A structural polymer for highly efficient all-day passive radiative cooling \n\nTong Wang1, Yi Wu1, Lan Shi 1, Xinhua Hu 1, Min Chen 1 & Limin Wu 1✉ \n\nAll-day passive radiative cooling has recently attracted tremendous interest by reflecting sunlight and radiating heat to the ultracold outer space. While some progress has been made, it still remains big challenge in fabricating highly efficient and low-cost radiative coolers for all-day and all-climates. Herein, we report a hierarchically structured polymethyl methacrylate (PMMA) film with a micropore array combined with random nanopores for highly efficient day- and nighttime passive radiative cooling. This hierarchically porous array PMMA film exhibits sufficiently high solar reflectance (0.95) and superior longwave infrared thermal emittance (0.98) and realizes subambient cooling of ${\\sim}8.2^{\\circ}\\mathsf C$ during the night and ${\\sim}6.0^{\\circ}\\mathsf{C}$ to $\\cdot8.9^{\\circ}\\mathsf{C}$ during midday with an average cooling power of $\\sim85\\:\\mathsf{W}/\\mathsf{m}^{2}$ under solar intensity of ${\\、}900\\mathsf{W}/\\mathsf{m}^{2}$ , and promisingly ${\\sim}5.5^{\\circ}\\mathsf{C}$ even under solar intensity of ${\\sim}930\\ \\mathsf{W}/\\mathsf{m}^{2}$ and relative humidity of ${\\sim}64\\%$ in hot and moist climate. The micropores and nanopores in the polymer film play crucial roles in enhancing the solar reflectance and thermal emittance. \n\nlthough the climate-science community is attempting to find efficient solutions for the accelerating global warming and greenhouse gas emissions, few concrete actions have been taken to resolve climate change1–3. Conceptually, one of the most efficient strategies is to reduce the amount of solar irradiance absorbed by the Earth4, e.g., through solar radiation management (SRM), to slow or reverse global warming5–7. The basic idea behind SRM is to seed reflective particles into the Earth’s stratosphere to reduce solar absorption, which might cause potentially dangerous threats to the Earth’s basic climate operations8,9. One possibly alternative approach is passive radiative cooling—a sky-facing surface on the Earth spontaneously cools by radiating heat to the ultracold outer space through the atmosphere’s longwave infrared (LWIR) transparency window $(\\lambda\\stackrel{\\cdot}{\\sim}8-13\\upmu\\mathrm{m})^{1\\breve{0}-14}$ . However, passive daytime radiative cooling (PDRC) to a temperature below ambient under direct sunlight is a particular challenge because most of the naturally available thermal radiation materials also absorb incident solar irradiance and rapidly heat up under exposure to the $S u n^{15,16}$ . Accordingly, designing and fabricating efficient PDRC with sufficiently high solar reflectance $\\left(\\bar{\\rho}_{\\mathrm{solar}}\\right)$ $(\\bar{\\lambda_{\\mathrm{~\\sim~}}}0.3\\mathrm{-}2.5\\upmu\\mathrm{m})$ to minimize solar heat gain and simultaneously strong LWIR thermal emittance $\\left(\\Bar{\\varepsilon}_{\\mathrm{LWIR}}\\right)$ to maximize radiative heat loss is highly desirable17,18. When the incoming radiative heat from the Sun is balanced by the outgoing radiative heat emission, the temperature of the Earth can reach its steady state4,19. Thus, PDRC technology is very promising to considerably decrease the use of compression-based cooling systems (e.g., air conditioners) and has a significant impact on global energy consumption20–24. \n\nThe first theoretical design of a metal-dielectric photonic structure for PDRC was presented by Raman et al.25 in 2013 by tailoring the material spectrum responses for continuous daytime radiative cooling. Then, they first experimentally achieved PDRC via a precision-designed nanophotonic radiative cooler in $2014^{26}$ . This cooler, consisting of seven alternating dielectric layers deposited on top of a silver mirror, cooled to $4.{\\overset{\\circ}{9}}{}^{\\circ}\\mathrm{C}$ below ambient temperature by reflecting $97\\%$ of incident sunlight while strongly and selectively emitting in the atmospheric transparency window. Nonetheless, many photonic structures suffer from a high manufacturing cost and large-scale production limits23,26–28. Another pioneering strategy was recently developed by Yin et al.29, who created a glass-polymer hybrid metamaterial thin film consisting of silica $(\\mathrm{{SiO}}_{2})$ microspheres randomly distributed in the matrix material of polymethylpentene via the scalable-manufactured rollto-roll polymer extrusion process. With the assistance of a silver coating, the metamaterial was able to exhibit ${>}93\\%$ infrared emissivity and reflect ${\\sim}96\\%$ of solar irradiance, achieving a noontime radiative cooling power of $93\\mathrm{W}/\\mathrm{m}^{2}$ under direct sunshine. The introduction of polymer-based radiative cooling materials can greatly improve the scalability and applicability of PDRC systems in practical applications18,30–33. Very recently, instead of using a reflective metallic mirror, state-of-the-art PDRC designs, such as porous polymer coatings17,34,35, polymeric aerogels36, white structural wood37 and cooling paints38,39, have attracted considerable attention because of their high cooling performance, simplicity, applicability and economical efficiency. For example, Yu et al.17 made remarkable progress in the design of PDRC poly(vinylidene fluoride-co-hexafluoropropene) coatings with random micro-/nano-pores through a phase inversion-based method, demonstrating high solar reflectance $(0.96\\pm0.03)$ , as well as high longwave infrared emittance $(0.97\\pm0.02)$ that enabled cooling up to ${\\sim}6^{\\circ}\\mathrm{C}$ and ${\\sim}3^{\\circ}\\mathrm{C}$ below ambient temperature under direct sunlight in dry southwestern USA and south Asia, respectively. Nonetheless, almost all of the PDRC prototypes reported so far performed well in an arid atmosphere (e.g., total precipitable water (TPW) $<10\\mathrm{mm},$ ) and at relatively low environmental temperatures (e.g., below $25^{\\circ}\\mathrm{C})^{26,29,36,37}$ rather than in hot (e.g., $30{}^{\\circ}\\mathrm{{C}}$ or above) and humid (e.g., TPW å $20\\mathrm{mm},$ ) regions17,30. Theoretically, atmosphere humidity or TPW heavily influences the absorbed power density of atmospheric radiation and the magnitude of the cooling performance. In a dry environment, the atmospheric window is open not only in the 1st atmospheric transparency window $(8-13\\upmu\\mathrm{m})$ but also in the 2nd atmospheric transparency window $(16-25\\upmu\\mathrm{m})$ , making efficient thermal radiation possible23,30. However, in a hot and humid environment, the transmissivity of the atmosphere slightly decreases in the 1st atmospheric transparency window and dramatically drops in the 2nd atmospheric transparency window. Thus, the cooling performance naturally becomes lower and is even limited due to the increased downwelling atmospheric radiation induced by higher humidity and temperature40–42. Therefore, developing facile, scalable, and cost-effective PDRC for practical thermal radiation applications, including hot and humid regions, still remains a great challenge. \n\nInspired by these intelligent reports and above considerations, herein, we design and report a hierarchically porous array PMMA $(\\mathrm{PMMA_{HPA}},$ film with a close-packed micropore array on the surface combined with abundant random nanopores inside by a template method. The as-obtained $\\mathrm{PMMA_{HPA}}$ film demonstrates excellent $\\bar{\\rho}_{\\mathrm{solar}}$ (0.95) and $\\overline{{\\varepsilon}}_{\\mathrm{LWIR}}$ (0.98), with not only subambient cooling of as high as ${\\sim}8.2^{\\circ}\\mathrm{C}$ during the night and of ${\\sim}6.0^{\\circ}\\mathrm{C}$ to ${\\sim}8.9^{\\circ}\\mathrm{C}$ during midday with an average cooling power of ${\\sim}85\\mathrm{W/}$ $\\mathrm{m}^{2}$ under solar intensity of ${\\sim}900\\mathrm{W}/\\mathrm{m}^{2}$ , but also ${\\sim}5.5^{\\circ}\\mathrm{C}$ even under solar intensity of ${\\sim}930\\mathrm{W}/\\mathrm{m}^{2}$ and relative humidity of ${\\sim}64\\%$ in hot and moist subtropical marine monsoon climate, which was not reported previously. Both experimental evidence and theoretical calculations verify that both the dense micropore array on the surface and the random nanopores in the $\\mathrm{PMMA_{HPA}}$ film play crucial roles in enhancing the solar reflectance and thermal emittance, which provides deep insight into devising superb PDRC technologies. \n\n# Results and discussion \n\n$\\bar{\\bar{\\rho}}_{\\mathrm{solar}}$ and $\\overline{{\\mathfrak{E}}}_{\\mathrm{LWIR}}$ of the $\\mathbf{PMMA_{HPA}}$ film. Fig. 1a illustrates the fabrication process of $\\mathrm{PMMA_{HPA}}$ . In brief, a monolayer of a hexagonally close-packed $5\\upmu\\mathrm{m}\\ \\mathrm{SiO}_{2}$ array is fabricated using a facile unidirectional rubbing assembly method43,44, as shown in Fig. 1b, c. A dispersion of PMMA and $200\\mathrm{nm}\\ \\mathrm{SiO}_{2}$ nanospheres in acetone is then infiltrated into the $\\mathrm{SiO}_{2}$ monolayer template. After the rapid evaporation of acetone in air, the obtained $\\mathrm{PMMA}/\\mathrm{SiO}_{2}^{-}$ composite displays randomly distributed $\\mathrm{SiO}_{2}$ nanospheres and regularly distributed $\\mathrm{SiO}_{2}$ microspheres, as indicated by the micrograph and EDS elemental mappings (Fig. $\\mathrm{|d\\mathrm{-}\\dot{g})}$ . After removal of the $\\mathrm{SiO}_{2}$ nanospheres and the monolayer template by etching in hydrofluoric acid aqueous solution, a hierarchically porous array PMMA $(\\mathrm{PMMA_{HPA}})$ film with ordered symmetrical micropores $(\\sim4.6\\upmu\\mathrm{m}$ diameter) and randomized nanopores ${\\sim}250\\mathrm{nm}$ average diameter) can be obtained (Fig. 1h, i and Supplementary Figs. 1a–c). Fourier transform infrared (FTIR) spectra and thermogravimetric analysis (TGA) confirm that $\\mathrm{PMMA_{HPA}}$ is entirely composed of organic polymer without residual inorganic $\\mathrm{SiO}_{2}$ (Supplementary Figs. 1d and e), while the $49.4\\mathrm{wt\\%}$ of $\\mathrm{SiO}_{2}$ before etching indicates a high porosity of $\\mathrm{PMMA_{HPA}}$ (Supplementary Fig. 1f). \n\nFigure 2 demonstrates the spectral reflectance and emissivity of the $\\mathrm{PMMA_{HPA}}$ film with ${\\sim}160\\upmu\\mathrm{m}$ effective thickness according to the normalized ASTM G173 Global solar spectrum and the LWIR atmospheric transparency window. The $\\mathrm{PMMA_{HPA}}$ film with $\\sim60\\%$ porosity presents a high average solar reflectance $(\\bar{\\rho}_{\\mathrm{solar}}=$ 0.95, Fig. 2a and Supplementary Fig. 2a), which ensures excellent reflection of sunlight from all incidences and minimizes the solar heat gain. Meanwhile, the film also shows a high thermal emittance over a broad bandwidth in the mid-infrared and still emits a significant part of its thermal energy even at large emission angles $(\\overline{{\\varepsilon}}_{\\mathrm{{LWIR}}}=0.98\\$ , Fig. 2b and Supplementary Fig. 2b), which can enable strong emission of heat to the cold sink of outer space through the atmospheric transparency window at different angles in relation to the sky. One remarkable feature of our structural polymer is that the periodic ordered ${\\sim}4.6\\upmu\\mathrm{m}$ micropores can scatter sunlight of ultraviolet-visible-near-infrared (UV-Vis-NIR) wavelengths, and the abundant, random ${\\sim}250$ nm nanopores greatly reduce the mean scattering path and transmission through the material, which further enhances the scattering of shorter visible wavelengths45,46. The combination of PMMA with air voids, one of which has a high refractive index and the other has a low refractive index ðΔn ¼ nPMMA \u0002 nair ¼ $1.49-1=0.49\\$ , could provide a sharp refractive index transition across polymer-air boundaries and yield the efficient solar scattering and the required strong sky window absorptance without surface obstruction34. \n\n![](images/46f6f835147c8608c0b5e7a6b4e1d24a557075fb33e2ae173a0aa246b99de1da.jpg) \nFig. 1 Fabrication and characterization of the $P M M\\sim\\Delta_{H P A}$ film. a Schematic illustration of the fabrication of $P M M A_{H P A}$ with a hierarchically porous array. b, c SEM micrographs of hexagonally close-packed monolayer $\\mathsf{S i O}_{2}$ templates. d SEM micrograph of PMMA/ $\\mathsf{S i O}_{2}$ composite. e–g EDS elemental mappings of Si, O, and C in d, showing the randomly distributed $\\mathsf{S i O}_{2}$ nanospheres and regularly distributed $\\mathsf{S i O}_{2}$ microspheres of the composite. h, i SEM micrographs of $\\mathsf{P M M A}_{\\mathsf{H P A}}$ showing an ordered symmetrical micropores array made of hierarchical randomized nanopores. \n\n![](images/236792329f10855218825a879edb6ded1ae12396f36b931d46c308b3c76a548f.jpg) \nFig. 2 Spectroscopic response of the $P M M\\sim\\Delta G_{H P A}$ film. a, b Spectral reflectance and emissivity of the $P M M A_{H P A}$ film with ${\\sim}160\\upmu\\mathrm{m}$ effective thickness along with the normalized ASTM G173 Global solar spectrum and the LWIR atmospheric transparency window. c, d Spectral refractive index (n) and extinction coefficient $(\\upkappa)$ of PMMA, showing negligible absorptivity in the solar range and multiple extinction peaks in the LWIR wavelengths. e Absorbance spectrum of $P M M A_{H P A}$ measured with ATR-FTIR spectroscopy. f Schematic diagram showing the periodic re-entrant structure with nano/microscale pores is conducive to enhance the total scattering efficiency by multiple reflections. \n\nAs one of the most widely used and low-cost polymers, pristine PMMA film has ideal intrinsic properties to enable highperformance PDRC applications47. Figure 2c, d show that PMMA has negligible extinction coefficient in the solar wavelengths and multiple extinction peaks at the 8, 8.6, 10.3, 11.8, and $13.2\\upmu\\mathrm{m}$ within the LWIR window, which should result from the different vibrational modes of its molecular structure. These properties keep the heat gain from sunlight to a minimum and contribute to a large amount of infrared absorption/emission in the atmospheric transparency window, which is responsible for the superior PDRC. Furthermore, the absorbance spectrum measured with attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) exhibits strong infrared absorption due to $\\scriptstyle{\\mathrm{C-O-C}}$ stretching vibrations between 770 and $\\bar{1250}\\mathrm{cm}^{-1}$ $8-13\\upmu\\mathrm{m}$ , Fig. 2e), which coincidently lie in the atmospheric transparency window. Importantly, the periodic reentrant structure with hierarchical nano/microscale pores is conducive to enhance the total scattering efficiency and increase the probability of infrared absorption/emission through multiple diffuse reflection at various incident angles (Fig. 2f). All these features benefit the radiative heat exchange between the cooling structural polymer and the atmosphere, causing sufficiently high $\\bar{\\rho}_{\\mathrm{solar}}$ and $\\overline{{\\varepsilon}}_{\\mathrm{LWIR}}$ of our $\\mathrm{PMMA_{HPA}}$ film to achieve all-day passive radiative cooling. \n\nDifferent from transparent pristine PMMA, the $\\mathrm{PMMA}/\\mathrm{SiO}_{2}$ composite film is translucent due to the absorptance in the UV and visible regions, and the corresponding $\\mathrm{PMMA_{HPA}}$ film has negligible transmittance because its plenty of pores can efficiently scatter sunlight of all wavelengths (Supplementary Figs. 3a–d). The spectral transmittance of the $\\mathrm{PMMA_{HPA}}$ film decreases with increasing thickness (Supplementary Fig. 4). Accordingly, the solar reflectance appears to have a more pronounced increasing trend with thickness than the thermal emittance in the range of $8-13\\upmu\\mathrm{m}$ (Fig. 3a–c), which likely arises from the increased backscattering of light from the thicker, nonabsorptive, porous PMMA layer. Evidently, even the emittance of the only effectively ${\\sim}2\\upmu\\mathrm{m}$ thick $\\mathrm{PMMA_{HPA}}$ film can reach 0.85. This suggests that the porous structure is sufficient to augment the intrinsic emittance of $\\mathrm{PMMA_{HPA}}$ . Further, we experimentally and theoretically demonstrated the influence of pore sizes and porosity on the optical performance. As clearly seen in Supplementary Fig. 5a, the $\\mathrm{PMMA_{HPA}}$ with ${\\sim}500\\mathrm{nm}$ nanopores shows a high-level $\\bar{\\rho}_{\\mathrm{solar}}.$ but its scattering of short wavelength region is inferior to that of ${\\sim}200\\mathrm{nm}$ nanopores. The reflectance of $\\mathrm{PMMA_{HPA}}$ with ${\\sim}100\\mathrm{nm}$ nanopores drops gradually in the visible and NIR-to-SWIR ranges $(0.4\\mathrm{-}2.5\\upmu\\mathrm{m})$ , leading to a lower $\\bar{\\rho}_{\\mathrm{solar}}$ . Such results coincide with the finite-difference time-domain (FDTD) simulation data (Supplementary Fig. 6a), indicating nanopores ranging in diameter from 200 to ${300}\\mathrm{nm}$ are optimum to reinforce the scattering of UV and visible wavelength region. For the optimization of micropore sizes, we established a model of ordered monolayer micropore with different sizes in the range of 1 to $10\\upmu\\mathrm{m}$ . Given the simulation results, one could derive that micropores ranging from 5 to $7\\upmu\\mathrm{m}$ in diameter would highly contribute to the solar reflectance (Supplementary Fig. 6b). Thus, combining the optimized nanopore size of $200{-}300\\mathrm{nm}$ and micropore size of $5{\\mathrm{-}}7\\upmu\\mathrm{m}.$ , the maximum $\\bar{\\rho}_{\\mathrm{solar}}$ of our hierarchical porous PMMA film can be obtained (Supplementary Fig. 6c). Moreover, the solar reflectance of the $\\mathrm{PMMA_{HPA}}$ film increases with increasing porosity, while its thermal emittance does not significantly change (Supplementary Fig. 5b). FDTD simulation results also show that the nanopore density or porosity has a positive correlation with the reflectance (Supplementary Fig. 6d). However, too high porosity may reduce the mechanical strength. Based on the trade-off of the optical and mechanical properties, $\\sim$ $60\\%$ porosity was adopted in the experiment design and radiative cooling application. \n\n![](images/5ad10960a0ee7ddb751a710b3a5c5c7d88e3ac9bebc9d85160dbe577b0345751.jpg) \nFig. 3 Variation in $\\overline{{\\rho}}_{\\mathsf{s o l a r}}$ and $\\overline{{\\varepsilon}}_{\\lfloor\\mathbf{uw}\\mid\\mathsf{R}}$ of the $P M M\\sim\\Delta_{H P A}$ films with effective thickness and polarization angle. a Variation in $\\bar{\\rho}_{\\mathsf{s o l a r}}$ and $\\overline{{\\varepsilon}}_{\\lfloor\\mathrm{W\\rfloorR}}$ of the $\\mathsf{P M M A}_{\\mathsf{H P A}}$ films with effective thickness. The error bars represent the standard deviation. b, $\\blacktriangledown\\mathbf{c}$ Measured reflectance and emissivity spectra of the $P M M A_{H P A}$ films as a function of the film effective thickness. d Infrared emissivity spectra of a $\\mathsf{P M M A}_{\\mathsf{H P A}}$ film at different polarization angles (θ) from $10^{\\circ}$ to $80^{\\circ}$ . e Polar distribution of the average emissivity across the atmospheric window of the $P M M A_{H P A}$ film at different polarization angles (θ) from $10^{\\circ}$ to $80^{\\circ}$ . f Measured polarization-dependent infrared emissivity spectra of the $P M M A_{H P A}$ films. \n\n![](images/e8364780f8e586afc72fcc5bad2bcf5b14d19d248c98f4dd3e0e82ed3e3f290d.jpg) \nFig. 4 SEM micrographs and optical properties of different types of PMMA films. a–d SEM micrographs of the $\\mathsf{P M M A}_{\\mathsf{H P A}},$ ${\\mathsf{P M M A}}_{\\mathsf{N P}}$ , $\\mathsf{P M M A}_{\\boldsymbol{M}\\mathsf{P A}},$ and pristine PMMA films. e Reflectance spectra across the solar wavelengths of different types of PMMA films. f Infrared emissivity spectra of different types of PMMA films. \n\nFigure 3d–f demonstrate the emissivity spectra of the $\\mathrm{PMMA_{HPA}}$ film in the infrared range of $2.5\\mathrm{-}20\\upmu\\mathrm{m}$ at different polarization angles. $\\overline{{\\varepsilon}}_{\\mathrm{LWIR}}$ shows a regularly decreasing trend from $10^{\\circ}$ to $80^{\\circ}$ , mainly owing to the ordered periodic micropore array on the top surface of the $\\mathrm{PMMA_{HPA}}$ film. Excitingly, the average emissivity across the atmospheric window $\\left(\\Bar{\\varepsilon}_{\\mathrm{LWIR}}\\right)$ is greater than 0.95 over a wide polarization angle range from $10^{\\circ}$ to $80^{\\circ}$ , indicating a stable emitted heat flux through the atmospheric transparency window to the cold sink of outer space. \n\nTo investigate the influence of the hierarchical porous structure on the optical properties of the $\\mathrm{PMMA_{HPA}}$ film, we further compared it with three other types of PMMA films, nanopore $\\mathrm{PMMA_{NP}}$ , monolayer micropore array $\\mathrm{PMMA_{MPA}}$ and pristine PMMA, as shown by the SEM images in Fig. 4a–d. Figure 4e shows that the $\\mathrm{PMMA_{HPA}}$ film presents the highest average solar reflectance $\\langle\\bar{\\rho}_{\\mathrm{HPA}}=0.95\\rangle$ ) in UV-Vis-NIR wavelengths, while $\\mathrm{PMMA_{NP}}$ drops gradually to a lower average solar reflectance $(\\bar{\\rho}_{\\mathrm{NP}}=0.74),$ in the near-to-short wavelength infrared (NIR-toSWIR) range $(0.7-2.5\\upmu\\mathrm{m})$ because only these disordered nanopores are too small to effectively scatter such wavelengths. In contrast, PMMAMPA exhibits a low value at all wavelengths $(\\bar{\\rho}_{\\mathrm{MPA}}=0.23)$ because the scattering of uniform monolayer micropores is weak. Similar results can be observed for pristine PMMA $(\\bar{\\rho}_{\\mathrm{prestine}}=0.10)$ due to its high transparency. The emission spectra show that all four films have strong thermal emittances in the LWIR transparency window $(\\bar{\\varepsilon}_{\\mathrm{HPA}}=0.98$ , $\\overline{{\\varepsilon}}_{\\mathrm{NP}}=0.96$ , $\\bar{\\varepsilon}_{\\mathrm{MPA}}=0.95$ and $\\begin{array}{r}{\\bar{\\varepsilon}_{\\mathrm{prestine}}=0.92.}\\end{array}$ ), as shown in Fig. 4f. However, the emissivity of $\\mathrm{PMMA_{MPA}}$ and pristine PMMA substantially drops in the range of mid-IR wavelengths compared to the $\\mathrm{PMMA_{HPA}}$ and $\\mathrm{PMMA_{NP}}$ films. This probably because that the existence of abundant hierarchically porous structure reduces the effective refractive index and leads to a more gradual refractive index transition across the polymer-air interface than $\\mathrm{PMMA_{MPA}}$ and PMMA17. Thus, the impedance matching between the porous polymer and surrounding air is improved48, which reduces the surface reflectance and results in a consistently higher emissivity for $\\mathrm{PMMA_{HPA}}$ or $\\mathrm{PMMA_{NP}}$ film in the mid-IR wavelengths. Besides, as we mentioned above, the porous structure with high specific surface area might increase the probability of infrared absorption through multiple diffuse reflection and enhances the emissivity. \n\nThe experimental results of four types of PMMA films were also theoretically verified by FDTD simulations (Supplementary Fig. 7)49. The numerical simulation results further reveal that hierarchical porous structure containing dual-scale nano/micro cavities would significantly improve the broadband scattering performance contrast to uniform nanoscale porous structure, especially in the range of NIR-to-SWIR, while the LWIR thermal emissivity of the two kinds of structures has negligible changes. The theoretical model of $\\mathrm{PMMA_{MPA}}$ verifies that the ordered micropores monolayer does not have enough high scattering coefficient, which matches well with the experimental result. We also simulated the reflectance spectra across the solar wavelengths of the $\\mathrm{PMMA_{HPA}}$ film with thickness of ${\\sim}5$ $\\upmu\\mathrm{m}$ (effectively ${\\sim}2\\upmu\\mathrm{m}.$ Supplementary Fig. 8). Surprisingly, such thin film is sufficient to yield an efficient scattering $(\\bar{\\rho}_{\\mathrm{HPA-}2\\mu\\mathrm{m}}=0.35)$ which further evidences the enhancement effect of hierarchical porous surface on the solar reflectance. \n\nBesides, to verify the optical superiority of the periodic micropores array on the surface, we also investigated the optical properties of a hierarchically porous PMMA $\\mathrm{(PMMA_{HP})}$ ) film with loose-packed random micropores and nanopores (Supplementary Figs. 9a–c). The solar reflectance of the $\\mathrm{PMMA_{HP}}$ film drops $8\\%$ in the range of NIR-to-SWIR compared to $\\mathrm{PMMA_{HPA}}$ (Supplementary Fig. 9d), which contains about $5\\%$ of sunlight $(\\bar{\\rho}_{\\mathrm{HP}}=0.90)$ . This suggests that the close-packed periodic arrangement of the hierarchical nano/microscale pores on the surface of our $\\mathrm{PMMA_{HPA}}$ can maximize both the surface area and the amount of scatters per unit and increase the overall scattering efficiency, especially in NIR-to-SWIR range, although this distribution of micropores on the surface does not influence the infrared emissivity (Supplementary Fig. 9e). \n\nFurthermore, the $\\mathrm{PMMA_{HPA}}$ film was modified by fluorosilane to become superhydrophobic with a water contact angle (WCA) of ${\\sim}156^{\\circ}$ (Supplementary Fig. 10) for stable durability in various atmospheric humidity conditions. Both the solar reflectance and infrared emissivity are at high levels and vary negligibly after fluorosilane treatment (Supplementary Figs. 11a and b). Even after accelerated weathering treatment for $\\boldsymbol{480}\\mathrm{h}$ (each cycle including the UV irradiation at $310\\mathrm{nm}$ wavelength with intensity of $0.71\\mathrm{\\:W}/\\mathrm{m}^{2}$ at $60^{\\circ}\\mathrm{C}$ for $^{4\\mathrm{h}}$ , followed by condensation at $50^{\\circ}\\mathrm{C}$ for $\\mathtt{4h}$ with UV lamps off), the $\\mathrm{PMMA_{HPA}}$ films exhibit no blistering, peeling, cracking and color changing. The porous morphology of our $\\mathrm{PMMA_{HPA}}$ films basically remains the same (Supplementary Figs. 12a and b). The ATR-FTIR spectra further demonstrate that the surface-modified $\\mathrm{PMMA_{HPA}}$ films before and after weathering treatment all have obvious absorption peaks of $\\scriptstyle{\\mathrm{C=O}}$ at $1726\\mathrm{cm}^{-1}$ , $\\mathrm{C-F}$ at $1187\\mathrm{cm}^{-1}$ , $\\scriptstyle{\\mathrm{C-O-C}}$ at $1139\\mathrm{\\dot{c}m^{-1}}$ and $\\mathrm{{C-Cl}}$ at 779, 746, 700, and $651~\\mathrm{cm}^{-1}$ (Supplementary Fig. 12c), owing to the protection of fluorosilane molecules. Moreover, the constant WCAs in Supplementary Fig 12d after weathering treatment also indicate the excellent durability and potential applicability. The reflectance and emissivity spectra of the $\\mathrm{PMMA_{HPA}}$ films show slight fluctuations of solar reflectance $(\\bar{\\rho}_{\\mathrm{solar}}=0.95\\pm0.02)$ and negligible variations in emissivity $(\\bar{\\varepsilon}_{\\mathrm{LWIR}}=0.98\\pm0.01)\\$ with the accelerated weathering time (Supplementary Figs. 12e and f), which may be attributed to the inconspicuous yellowing effect in response to the UV irradiation. We also conducted the real outdoor exposure test for 40 days on a flat roof in Shanghai city and the results indicate the almost unchanged optical performance and WCAs (Supplementary Table S1). \n\nAll-day continuous passive radiative cooling measurements of the $\\mathbf{PMMA_{HPA}}$ film. The radiative cooling performances of the structural polymers $(\\sim160\\upmu\\mathrm{m}$ effective thickness and $100\\mathrm{mm}\\times$ $100\\mathrm{mm}$ in size) were measured from 20:00 on 09 Oct. to 20:00 on 10 Oct. 2019 using a $24\\mathrm{-h}$ uninterrupted thermal measurement on a flat roof of a five-story building under a clear sky in Shanghai, China. As shown in Fig. 5a, the strong optical scattering of sunlight gives our $\\mathrm{PMMA_{HPA}}$ surface a matte and white appearance, which can be further confirmed by the CIE chromaticity coordinate analysis (Fig. 5b). Under intense solar irradiance of ${\\sim}930\\mathrm{W}/$ $\\mathrm{m}^{2}$ and relative humidity of ${\\sim}40\\%$ at noon (Fig. 5c), the real-time temperature tracking of the air and four types of PMMA films are shown in Fig. 5d. Evidently, although the pristine PMMA and $\\mathrm{PMMA_{MPA}}$ films can exhibit decreases in temperature by ${\\sim}3.7\\ ^{\\circ}\\mathrm{C}$ and ${\\sim}4.9^{\\circ}\\mathrm{C}$ at night, respectively, their temperatures dramatically rise to ${\\sim}15.2^{\\circ}\\mathrm{C}$ and ${\\sim}14.1^{\\circ}\\mathrm{C}$ above the ambient temperature at noon due to their transparency and translucency, respectively (Fig. 5e). The $\\mathrm{PMMA_{NP}}$ film can achieve a subambient cooling of ${\\sim}6.5^{\\circ}\\mathrm{C}$ during the night but maintains almost the same temperature as the ambient environment during midday. In contrast, the $\\mathrm{PMMA_{HPA}}$ film exhibits fabulous passive radiative cooling during both night and daytime. The average below-ambient temperature of the $\\mathrm{PMMA_{HPA}}$ film is ${\\sim}8.2^{\\circ}\\mathrm{C}$ during the night (between $6\\mathrm{p.m}$ . and $6\\mathrm{a.m.}$ ) and ${\\sim}6.0^{\\circ}\\mathrm{C}$ during midday (between 11 a.m. and $2{\\mathrm{p.m.}}$ ). This cooling performance is on par with those in previous reports (Supplementary Table S2). \n\nSubambient PDRC performance in various geographical regions and climates. Radiative cooling performance in realworld applications is substantially affected by the geographical regions and climates. For instance, the net radiative cooling power of the cooler is limited by the increased solar irradiation, humidity, cloud cover, local wind speed and ambient temperature30,50. Here, we further performed a series of experiments to evaluate and compare the effects of climates from different cities on the radiative cooling performance of our $\\mathrm{PMMA_{HPA}}$ films. Three cities, Xiamen city (Southern China, Coastal), Shanghai city (Eastern China, Coastal) and Xuzhou city (Northern China, Inland), were chosen as typical test locations due to their different topographic and meteorological characteristics (Supplementary Fig. 13). The climate characteristics in Xuzhou, Shanghai and Xiamen are temperate monsoon climate, subtropical monsoon climate and subtropical marine monsoon climate, respectively, which provide a remarkable difference in humidity for our measurements. As shown in Fig. 6a–i, under clear skies with comparable solar intensity and wind speed but various humidity conditions ( $\\sim38\\%$ in Xuzhou, ${\\sim}47\\%$ in Shanghai, and ${\\sim}54\\%$ in \n\n![](images/67df9ec0810536200df3f538cafebc0cbb3f6fc915a5eb351d5399ebdb5b952a.jpg) \nFig. 5 Twenty-four-hour continuous passive radiative cooling performance measurements. a Photograph of the cooling $\\mathsf{P M M A}_{\\mathsf{H P A}}$ film showing its bright white appearance (inset, water contact angle image of $\\mathsf{P M M A}_{\\mathsf{H P A}}.$ ). b CIE chromaticity coordinates of the cooling ${\\mathsf{P M M A}}_{\\mathsf{H P A}}$ film. c Relative humidity tracking of the air and solar irradiance at $12\\mathsf{P}M$ on 10 Oct. 2019. d Temperature tracking of the air and PMMA films. e Temperature difference between the ambient and structural PMMA films. \n\n![](images/77bcb16833e58e1b110b2659bf8ea36352d97d35ce447d0c5037e7a34db3db3b.jpg) \nFig. 6 Passive daytime radiative cooling performance of the $P M M\\sim\\Delta G H P A$ film in different locations and weathers. a–c Solar irradiance, wind speed and relative humidity, and temperatures of the air and the $P M M A_{H P A}$ film in Xuzhou city. d–f Solar irradiance, wind speed and relative humidity, and temperatures of the air and the $P M M A_{H P A}$ film in Shanghai city. $\\pmb{\\mathrm{g}}\\pmb{-}\\pmb{\\mathrm{i}}$ Solar irradiance, wind speed and relative humidity, and temperatures of the air and the $P M M A_{H P A}$ film in Xiamen city. j–l Solar irradiance, wind speed and relative humidity, and temperatures of the air and the $P M M A_{H P A}$ film in Xiamen city. \n\nXiamen), the subambient cooling of ${\\sim}8.9^{\\circ}\\mathrm{C},$ ${\\sim}7.8^{\\circ}\\mathrm{C}$ and ${\\sim}8.6^{\\circ}\\mathrm{C}$ at noontime is observed, separately. Even in the same location (e.g., in Xiamen city), increasing solar intensity (from ${\\sim}890~\\mathrm{W/m}^{2}$ to ${\\sim}930\\mathrm{W}/\\mathrm{m}^{2},$ , wind speed (from ${\\sim}0.6\\mathrm{m}/s$ to ${\\sim}1.1\\mathrm{m}/s,$ and humidity (from ${\\sim}54\\%$ to ${\\sim}64\\%$ ), the $\\mathrm{PMMA_{HPA}}$ film still enables cooling up to ${\\sim}5.5^{\\circ}\\mathrm{C}$ below ambient temperature (Figs. 6g–l), which has not been reported previously40,41. Comparing Xuzhou and Xiamen city (Fig. 6a–c and $\\mathrm{j-l}_{\\cdot}^{\\cdot}$ ), we can conclude that increasing solar intensity (from ${\\sim}860\\mathrm{W}/\\mathrm{m}^{2}$ to ${\\sim}930\\mathrm{W}/\\mathrm{m}^{2}.$ ), wind speed (from ${\\sim}0.5\\mathrm{m}/s$ to ${\\sim}1.1\\mathrm{m}/s$ ) and humidity (from ${\\sim}38\\%$ to ${\\sim}64\\%$ ), the subambient cooling temperatures of $\\mathrm{PMMA_{HPA}}$ film are indeed influenced (decreasing from ${\\sim}8.9^{\\circ}\\mathrm{C}$ to ${\\sim}5.5^{\\circ}\\mathrm{C})$ . The primary driver of the good performance in various geographical regions and climates should be the synergistic result of visible white (high solar reflectance) and infrared black (high infrared emissivity in both the 1st and 2nd atmospheric transparency window) that greatly minimizes the absorbing solar irradiance and the thermal radiation emitted by the atmosphere. In addition, we investigated the effect of surface modification on the daytime radiative cooling performance of the $\\mathrm{PMMA_{HPA}}$ film. The results show that the $\\mathrm{PMMA_{HPA}}$ films with and without surface modification can achieve subambient cooling temperatures of ${\\sim}6.9^{\\circ}\\mathrm{C}$ and ${\\sim}6.5^{\\circ}\\mathrm{C},$ respectively (Supplementary Fig. 14). While the $\\mathrm{PMMA_{HPA}}$ film without surface modification also demonstrates excellent passive radiative cooling behavior, the fluorosilane treatment enables stable performance by restricting the effect of moisture and water under different levels of humidity. \n\nPassive radiative cooling power measurements of the $\\mathbf{PMMA_{HPA}}$ film. When used in a building roof or external siding, our $\\mathrm{PMMA_{HPA}}$ films can achieve all-day passive radiative cooling through reflecting sunlight and radiating heat to the cold outer space under a clear sky (Fig. 7a). Figure 7b schematically shows the direct thermal measurement system based on the net cooling equation. To further demonstrate the PDRC capability of the cooling $\\mathrm{\\PMMA_{HPA},}$ we adopted a feedback-controlled heating system to measure its radiative cooling power during the midday (Fig. 7c). This feedback-controlled heating system maintains the surface temperature of the $\\mathrm{PMMA_{HPA}}$ film at the measured ambient temperature to minimize the impact of conductive and convective heat losses (Fig. 7d). Promisingly, the $\\mathrm{PMMA_{HPA}}$ film attains an average cooling power of ${\\sim}85\\mathrm{W}/\\mathrm{m}^{2}$ under solar intensity of ${\\sim}900\\mathrm{\\overline{{W}}}/\\mathrm{m}^{2}$ in April in Shanghai (Fig. 7e). \n\nFigure 8a, b present the net cooling power during the nighttime and daytime calculated using the radiative cooling theoretical model, respectively. More details of this model are given in the “Methods” section. The power of solar radiation is set to approximately $1000\\mathrm{W}/\\mathrm{m}^{2}$ for simplicity, and the ambient temperature $T_{\\mathrm{amb}}$ is assumed to be $298.15\\mathrm{K}$ in both cases. A maximum cooling power of $124.40\\mathrm{W}/\\mathrm{m}^{2}$ can be achieved for nighttime operation. For daytime operation, the calculated maximum net cooling power is $7\\dot{4}.40\\mathrm{W}/\\mathrm{m}^{2}$ at thermal equilibrium, which is lower than the measured daytime cooling power due to the fluctuations in the ambient conditions, the uncertainty in the measurements and the theoretical model approximations. \n\n![](images/6f5457a447379d0aff8c88a8ff243ddfb4ba075fc3eab98728c5a2a8956874c1.jpg) \nFig. 7 Net cooling power of the $P M M\\sim\\Delta_{H P A}$ film during the midday. a Schematic of the basic principles of PDRC. When used in a building roof or external siding, the $\\mathsf{P M M A}_{\\mathsf{H P A}}$ film exhibits high solar reflectance and high infrared emissivity. b Two-dimensional schematic drawing of the thermal box apparatus with a feedback-controlled heater. The heater maintains the sample surface temperature at that of the ambient environment, minimizing convective and conductive heat losses. c Photo of the experimental apparatus on a rooftop in Shanghai, China. d Temperature tracking of the ambient and the $\\mathsf{P M M A}_{\\mathsf{H P A}}$ film under solar intensity of $\\sim900\\:\\mathsf{W}/\\mathsf{m}^{2}$ and relative humidity of \\~ $44\\%$ on April 23, 2020. e Continuous measurement of the radiative cooling power of the $\\mathsf{P M M A}_{\\mathsf{H P A}}$ film during the midday. \n\n![](images/c6d5e8b548b5fcf5b2c976e8cabb3bbbd039b9b3bf4a7ed82c555c1cc067b719.jpg) \nFig. 8 Calculated net cooling power with software MATLAB based on the theoretical simulation. a Calculated net cooling power during the nighttime. b Calculated net cooling power during the daytime. The variable $h_{c}$ is a combined nonradiative heat coefficient. Values of 0, 3, 6, 9, and 12 for $h_{c}$ are used in the calculations. For daytime calculations, $5\\%$ solar power absorption is considered. \n\nIn summary, we have demonstrated and fabricated a hierarchically structured PMMA film with a dense micropore monolayer array and randomly distributed nanopores for highly efficient all-day passive subambient radiative cooling in various geographical locations and climates. Our structural polymer film exhibits sufficiently high solar reflectance and thermal emittance owing to its abundant periodic scattering micropores embedded with random nanopores and ideal intrinsic properties. Without needing any silver or aluminum reflectors, our cooling structural \n\nPMMA film realizes an average below-ambient temperature ${\\sim}8.2^{\\circ}\\mathrm{C}$ during the night and ${\\sim}6.0^{\\circ}\\mathrm{C}$ to ${\\sim}8.9^{\\circ}\\mathrm{C}$ during midday, and promisingly ${\\sim}5.5^{\\circ}\\mathrm{C}$ even under solar intensity of ${\\sim}930\\mathrm{W}/\\mathrm{m}^{2}$ and relative humidity of ${\\sim}64\\%$ in hot and moist subtropical marine monsoon climate, which is really an all-day and allclimate PDRC system. And the superhydrophobized $\\mathrm{PMMA_{HPA}}$ film can ensure cooling performance durability by eliminating the effect of moisture and water under different levels of humidity. This study has revealed the effects of micropores, nanopores and their arrangement on optical performance, which may provide deep insight into the crucial roles of various pores and their array in solar reflectance and thermal emittance and help us design and fabricate more efficient all-day passive subambient radiative cooling materials and systems. \n\n# Methods \n\nFabrication of $\\mathsf{P M M A}_{\\mathsf{H P A}}$ . Monodisperse $5\\upmu\\mathrm{m}\\mathrm{SiO}_{2}$ microspheres were placed on top of a polydimethylsiloxane (PDMS)-coated glass sheet and rubbed with another \n\nPDMS substrate with slight palm pressure along a randomly chosen direction according to our reported method43,44. After being rubbed for $5s_{;}$ the $\\mathrm{SiO}_{2}$ microspheres had assembled into hexagonally close-packed monolayers on the PDMS surfaces. A $200\\mathrm{nm}\\ \\mathrm{SiO}_{2}$ nanosphere dispersion in acetone was added to PMMA to make a dispersion of $\\mathrm{SiO}_{2}$ -acetone-PMMA (1:10:1 mass ratio) under magnetic stirring at $50^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . This dispersion was then drop-cast onto the monolayer $\\mathrm{SiO}_{2}$ template. After the solvent was fully evaporated, a freestanding $\\mathrm{PMMA}/\\mathrm{SiO}_{2}$ composite film was obtained by peeling the coating off the smooth surface. After removal of the $\\mathrm{SiO}_{2}$ template and nanospheres with $2{\\cdot}5\\ \\mathrm{vol\\%}$ hydrofluoric acid aqueous solution, $\\mathrm{PMMA_{HPA}}$ films with various effective thicknesses of $2\\pm0.5\\upmu\\mathrm{m}$ to $160\\pm5{\\upmu\\mathrm{m}}$ were obtained by casting different amounts of solution. For comparison, $\\mathrm{PMMA_{NP}}$ film was fabricated by the same procedure above without using the monolayer $\\mathrm{SiO}_{2}$ template, $\\mathrm{PMMA_{MPA}}$ film was obtained without $\\mathrm{SiO}_{2}$ nanospheres, and the pristine non-porous PMMA film was prepared at an acetone-PMMA (10:1 mass ratio) without using $\\mathrm{SiO}_{2}$ particles. In addition, $\\mathrm{PMMA_{HP}}$ film was fabricated using random loose-packed monolayer $5\\upmu\\mathrm{m}\\ \\mathrm{SiO}_{2}$ templates and $200\\mathrm{nm}\\mathrm{SiO}_{2}$ nanosphere. All the films above have the same effective thickness by controlling the PMMA mass and film-forming substrate size. \n\n$P M M A_{H P A}$ surface modification. To make superhydrophobic $\\mathrm{PMMA_{HPA}}$ film, the sample was treated with 1H,1H,2H,2H-perfluorooctyltrichlorosilane (PFOTS) via a chemical vapor deposition (CVD) method. In detail, the $\\mathrm{PMMA_{HPA}}$ film and a vial containing $1\\%$ PFOTS/ethanol solution were placed in a sealed vacuum desiccator. The desiccator was immediately pumped to vacuum for $15\\mathrm{min}$ and placed at room temperature for $24\\mathrm{h}$ for fluorination. The modified $\\mathrm{PMMA_{HPA}}$ film was then baked in an oven at $80^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ to remove the excessive PFOTS. \n\n# Characterization \n\nOptical characterization of the cooling structural polymers. The spectral reflectance $\\left(\\rho\\left(\\lambda\\right)\\right)$ and transmittance $(\\uptau\\left(\\lambda\\right))$ in the ultraviolet, visible and near-infrared $(0.3\\mathrm{-}2.5\\upmu\\mathrm{m})$ wavelength ranges were separately determined in an UV-Vis-NIR spectrophotometer (Hitachi, U-4100, Japan) with a polytetrafluoroethylene integrating sphere. The $\\textsf{\\rho}(\\lambda)$ and τ (λ) in the mid-infrared wavelength ranges were characterized in an FTIR spectrometer (Nicolet 6700, Thermo Fisher Scientific, USA) equipped with a gold integrating sphere. We put one black substrate behind the samples during spectral reflectance measurement to eliminate the reflectance contribution of the substrate. The average value of more than five parallel measurements on different sites of the film was reported and the error bars represent the standard deviation. A polarizer was used in the FTIR spectrometer equipped with a smart diffuse reflectance accessory to measure the reflectance over a range of polarization angles (θ) from $10^{\\circ}$ to $80^{\\circ}$ . For any object at thermal equilibrium, the spectral absorptivity (α $(\\lambda)$ ) and emissivity (ε $\\mathbf{\\eta}^{(\\lambda)}$ ) must be equal according to Kirchhoff’s law; thus, ε (λ) was calculated as ε $\\mathbf{\\eta}(\\lambda)=1-\\mathbf{\\rho}(\\lambda)\\ –\\tau\\mathbf{\\eta}(\\lambda)^{51,52}$ . The angular reflectance spectra in the wavelength range of $0.4\\mathrm{-}1.1\\upmu\\mathrm{m}$ at different incidence angles were measured by an angle-resolved photonic spectral system (R1, Ideaoptics Technology Ltd., China). Refractive index and extinction coefficient measurements in the wavelength range of $0.2\\mathrm{-}14\\upmu\\mathrm{m}$ at ${60}^{\\circ}$ were taken for pristine PMMA films using a V-VASE and an IR-VASE ellipsometer (J. A. Woollam, USA). \n\nTheoretical model of the radiative cooling performance. When the structural polymer films are exposed to a clear sky, they are influenced by the solar irradiance and atmospheric downward thermal radiation. Meanwhile, heat can be transferred from the ambient surroundings to the polymers via conduction and convection due to the temperature difference between the cooling polymers and the ambient environment. To achieve PDRC, the device must satisfy very stringent constraints as dictated by the power balance equation. The net cooling power $P_{c o o l}$ of the structural polymers is expressed $\\mathsf{a s}^{26}$ : \n\n$$\nP_{\\mathrm{cool}}(T)=P_{\\mathrm{rad}}(T)-P_{\\mathrm{atm}}(T_{\\mathrm{amb}})-P_{\\mathrm{solar}}-P_{\\mathrm{cond+conv}}\n$$ \n\nwhere $T$ is the surface temperature of the structural polymers and $T_{\\mathrm{amb}}$ is the ambient temperature. $P_{\\mathrm{rad}}(T)$ is the power radiated by the structural polymers, and $P_{\\mathrm{atm}}(T_{\\mathrm{amb}})$ is the absorbed atmospheric thermal radiation at $T_{\\mathrm{amb}}.\\ P_{\\mathrm{solai}}$ is the incident solar irradiation absorbed by the structural polymers, and $P_{\\mathrm{cond+conv}}$ is the power lost due to convection and conduction. The net cooling power defined in Eq. (1) can reach a high value by increasing the radiative power of the structural polymers and reducing either the solar absorption or parasitic heat gain34. These parameters can be calculated by the following equations26,53–55: \n\n$$\nP_{\\mathrm{rad}}(T)=A\\int d\\Omega\\mathrm{cos}\\theta\\int_{0}^{\\infty}d\\lambda I_{\\mathrm{BB}}(T,\\lambda)\\varepsilon(\\lambda,\\theta)\n$$ \n\n$$\nP_{\\mathrm{atm}}(T_{\\mathrm{amb}})=A\\int d\\Omega\\cos\\theta\\int_{0}^{\\infty}d\\lambda I_{\\mathrm{BB}}(T_{\\mathrm{amb}},\\lambda)\\varepsilon(\\lambda,\\theta)\\varepsilon_{\\mathrm{atm}}(\\lambda,\\theta)\n$$ \n\n$$\nP_{\\mathrm{solar}}=A\\int_{0}^{\\infty}d\\lambda\\varepsilon(\\lambda,\\theta_{\\mathrm{solar}})I_{\\mathrm{AM1.5}}(\\lambda)\n$$ \n\n$$\nP_{\\mathrm{cond+conv}}(T,T_{\\mathrm{amb}})=A h_{c}(T_{\\mathrm{amb}}-T)\n$$ \n\nwhere $A$ is the surface area of the radiative cooler. $\\begin{array}{r}{\\int d\\Omega=2\\pi\\int_{0}^{\\pi/2}d\\theta\\sin\\theta}\\end{array}$ is the angular integral over a hemisphere. $\\begin{array}{r}{I_{\\mathrm{BB}}(T,\\lambda)=\\frac{2h c^{2}}{\\lambda^{5}}\\frac{1}{e^{h c/\\left(\\lambda\\kappa_{B}T\\right)}-1}}\\end{array}$ is the spectral radiance of a blackbody at temperature T. h is Planck’s constant, $\\kappa_{B}$ is the Boltzmann constant, and $\\scriptstyle{c}$ is the speed of light. $\\varepsilon(\\lambda,\\theta)$ is the directional emissivity of the surface at wavelength λ. $\\varepsilon_{\\mathrm{atm}}(\\lambda,\\theta)=1-\\tau(\\lambda)^{1/\\mathrm{con}\\theta}$ is the angle-dependent emissivity of the atmosphere; $\\tau(\\lambda)$ is the atmospheric transmittance in the zenith direction. $P_{\\mathrm{rad}}(T)$ and $P_{\\mathrm{atm}}\\big(T_{\\mathrm{amb}}\\big)$ are determined by both the spectral data of the structural polymers and the emissivity spectrum of the atmosphere according MODTRAN of Mid-Latitude Summer Atmosphere Model $^{36,56}$ . In Eq. (4), the solar illumination is represented by the AM1.5 spectrum $(I_{\\mathrm{AM}1.5}(\\lambda))$ . For our $\\mathrm{PMMA_{HPA}}$ film, approximately $95\\%$ of the input solar power can be reflected, and thus, the $5\\%$ absorption of the solar irradiance will reduce the net cooling power. In Eq. (5), $h_{c}=\\bar{h}_{\\mathrm{cond}}+h_{\\mathrm{conv}}$ is a combined nonradiative heat coefficient that captures the collective effect of conductive and convective heating, which can be limited to a range between 0 and $12\\mathrm{W/m}^{2}/\\mathrm{K}$ . \n\nThe average solar reflectance $(\\bar{\\rho}_{\\mathrm{solar}})$ is defined $\\mathbf{a}\\mathbf{s}^{17}$ : \n\n$$\n\\bar{\\rho}_{\\mathrm{solar}}=\\frac{\\int_{0.3\\mu\\mathrm{m}}^{2.5\\mu\\mathrm{m}}I_{\\mathrm{solar}}(\\lambda)\\cdot\\rho_{\\mathrm{solar}}(\\lambda,\\theta)d\\lambda}{\\int_{0.3\\mu\\mathrm{m}}^{2.5\\mu\\mathrm{m}}I_{\\mathrm{solar}}(\\lambda)\\mathrm{d}\\lambda}\n$$ \n\nwhere $\\lambda$ is the wavelength of incident light in the range of $0.3\\mathrm{-}2.5\\upmu\\mathrm{m},I_{\\mathrm{solar}}(\\lambda)$ is the normalized ASTM G173 Global solar intensity spectrum, and $\\rho_{\\mathrm{solar}}(\\lambda,\\theta)$ is the surface’s angular spectral reflectance. The average emittance $(\\overline{{\\varepsilon}}_{\\mathrm{LWIR}})$ in the LWIR atmospheric transmittance window is defined as: \n\n$$\n\\overline{{\\varepsilon}}_{\\mathrm{LWIR}}=\\frac{\\int_{8\\mu\\mathrm{m}}^{13\\mu\\mathrm{m}}I_{B B}(\\lambda)\\cdot\\varepsilon_{\\mathrm{LWIR}}(\\lambda,\\theta)d\\lambda}{\\int_{8\\mu\\mathrm{m}}^{13\\mu\\mathrm{m}}I_{\\mathrm{BB}}(\\lambda)\\mathrm{d}\\lambda}\n$$ \n\nwhere $I_{\\mathrm{BB}}(\\lambda)$ is the spectral intensity emitted by a blackbody and $\\varepsilon_{\\mathrm{LWIR}}(\\lambda,\\theta)$ is the surface’s angular spectral thermal emittance in the range of $8\\mathrm{-}13\\upmu\\mathrm{m}$ . \n\nThermal measurements of cooling temperature and cooling power with a feedbackcontrolled heater. We designed a feedback-controlled program to minimize both conductive and convective heat exchange to the structural polymers under strong solar irradiance based on Eq. $(1)^{29}$ . Our thermal box consisted of insulation foam covered by a layer of reflective foil. A $10\\mathrm{-}\\upmu\\mathrm{m}$ -thick transparent low-density polyethylene film was used to seal the thermal box and served as a wind shield. \n\nMoreover, a $\\mathrm{PMMA_{HPA}}$ film with a size of $100\\mathrm{mm}\\times100\\mathrm{mm}\\times160\\upmu\\mathrm{m}$ was placed on a $100\\mathrm{mm}\\times100\\mathrm{mm}\\times1\\mathrm{mm}$ thick copper plate attached to a $100\\mathrm{mm}\\times$ $100\\mathrm{mm}\\times0.2\\mathrm{mm}$ thick Kapton heater. The Kapton heater was feedback-controlled by an ambient temperature-responsive thermostat to maintain the $\\mathrm{PMMA_{HPA}}$ film at ambient temperature and accurately assess the cooling power. The apparatus was elevated 1.1 meters above the ground to avoid heat conduction from the ground to the thermal box. An adhesive resistant temperature detector was directly mounted on the back surface of the polymer film to detect real-time temperature of the sample, which was continuously recorded by a datalogging thermometer with an uncertainty of $\\pm0.1^{\\circ}\\mathrm{C}$ (CENTER309, CENTER corp, Taiwan, China). For comparison, a temperature detector was mounted outside the box to detect real-time temperature of the ambient. A relative humidity (RH) data logger with an accuracy of $\\pm0.1\\%$ RH (GSP-8, Elitech corp, China) was placed near the samples to measure the relative air humidity. The solar irradiation outside the box was simultaneously recorded using a datalogging solar radiometer with an accuracy of $\\pm5\\%$ (TES1333R, TES Electrical Electronic corp. Taiwan, China). It is worth mentioning that the sunlight our PMMA films received is ${\\sim}10\\%$ less than the pyranometer measured due to the polyethylene cover on the thermal box. The wind speed around our thermal boxes was measured using a digital anemometer with an accuracy of $\\pm2.5\\%$ (AS856, Smart Sensor corp, China). All weather data were automatically tracked every 10 s. The heater was switched on to test the radiative cooling power, but the heater and copper plate were removed to demonstrate the subambient cooling performance. As a control, we exposed the $\\mathrm{PMMA_{NP}}$ , $\\mathrm{PMMA_{MPA}}$ and pristine PMMA films to the sky while mounted in the same apparatus to compare the subambient cooling performances. Demonstrations of the cooling performance of different types of PMMA films during both day and night were carried out under a clear sky with a relative humidity of $\\sim40\\%$ at noon in on a flat roof of a five-story building at Fudan University, Shanghai, China on October 09, 2019. The daytime cooling performance of the $\\mathrm{PMMA_{HPA}}$ film in different locations and climates was conducted in April and May, 2020, such as Xiamen city (Southern China, Coastal, $24^{\\circ}26^{\\circ}57^{\\circ}\\mathrm{N}.$ , $118^{\\circ}3^{\\circ}$ $35^{\\mathrm{{*}}}\\mathrm{~E~}_{\\rightmoon}^{\\cdot}$ ), Shanghai city (Eastern China, Coastal, 31° 18’ $22^{\\mathfrak{w}}$ N, $121^{\\circ}30^{\\circ}17^{\\circ}$ E) and Xuzhou city (Northern China, Inland, $34^{\\circ}27^{\\circ}$ 55” N, $117^{\\circ}\\ 0^{\\circ}\\ 51^{\\circ}\\ \\mathrm{E}$ ). \n\n# Data availability \n\nAll data needed to evaluate the conclusions in the paper are presented in the paper and/ or the Supplementary information. Additional data related to this paper may be requested from the authors. \n\nReferences \n1. Walther, G. R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002). \n2. Oreskes, N. The scientific consensus on climate change. Science 306, 1686–1686 (2004). \n3. Xu, Y., Ramanathan, V. & Victor, D. G. Global warming will happen faster than we think. Nature 564, 30–32 (2018). \n4. Munday, J. N. Tackling climate change through radiative cooling. Joule 3, 2057–2060 (2019). \n5. Budyko, M. I. The earth’s climate: past and future. Vol. 20, 256–257 ((Academic Press, New york, 1983). \n6. Keith, D. W. Geoengineering the climate: history and prospect. Annu. Rev. Energ. Environ. 25, 245–284 (2000). \n7. Wigley, T. M. A combined mitigation/geoengineering approach to climate stabilization. Science 314, 452–454 (2006). \n8. Ricke, K. L., Morgan, M. G. & Allen, M. R. Regional climate response to solarradiation management. Nat. Geosci. 3, 537–541 (2010). \n9. Keith, D. W. & MacMartin, D. G. A temporary, moderate and responsive scenario for solar geoengineering. Nat. Clim. Change 5, 201–206 (2015). \n10. Catalanotti, S. et al. The radiative cooling of selective surfaces. Sol. Energy 17, 83–89 (1975). \n11. Orel, B., Gunde, M. K. & Krainer, A. Radiative cooling efficiency of white pigmented paints. Sol. Energy 50, 477–482 (1993). \n12. Shi, N. N. et al. Keeping cool: enhanced optical reflection and radiative heat dissipation in Saharan silver ants. Science 349, 298–301 (2015). \n13. Hsu, P. C. et al. Radiative human body cooling by nanoporous polyethylene textile. Science 353, 1019–1023 (2016). \n14. Baranov, D. G. et al. Nanophotonic engineering of far-field thermal emitters. Nat. Mater. 18, 920–930 (2019). \n15. Lim, X. The super-cool materials that send heat to space. Nature 577, 18–20 (2020). \n16. Zhang, X. Metamaterials for perpetual cooling at large scales. Science 355, 1023–1024 (2017). \n17. Mandal, J. et al. Hierarchically porous polymer coatings for highly efficient passive daytime radiative cooling. Science 362, 315–319 (2018). \n18. Yin, X., Yang, R., Tan, G. & Fan, S. Terrestrial radiative cooling: using the cold universe as a renewable and sustainable energy source. Science 370, 786–791 (2020). \n19. Stocker, T. F. et al. Climate Change 2013: The Physical Science Basis, Contribution of Working Group I To The Fifth Assessment Report Of The Intergovernmental Panel On Climate Change. (Cambridge University Press, Cambridge, 2013). \n20. Zhu, L., Raman, A., Wang, K. X., Anoma, M. A. & Fan, S. Radiative cooling of solar cells. Optica 1, 32–38 (2014). \n21. Bhatia, B. et al. Passive directional sub-ambient daytime radiative cooling. Nat. Commun. 9, 5001 (2018). \n22. Shi, Y., Li, W., Raman, A. & Fan, S. Optimization of multilayer optical films with a memetic algorithm and mixed integer programming. ACS Photon. 5, 684–691 (2017). \n23. Chen, Z., Zhu, L., Raman, A. & Fan, S. Radiative cooling to deep sub-freezing temperatures through a 24-h day-night cycle. Nat. Commun. 7, 13729 (2016). \n24. Lu, X., Xu, P., Wang, H., Yang, T. & Hou, J. Cooling potential and applications prospects of passive radiative cooling in buildings: the current state-of-the-art. Renew. Sust. Energ. Rev. 65, 1079–1097 (2016). \n25. Rephaeli, E., Raman, A. & Fan, S. Ultrabroadband photonic structures to achieve high-performance daytime radiative cooling. Nano lett. 13, 1457–1461 (2013). \n26. Raman, A. P., Anoma, M. A., Zhu, L., Rephaeli, E. & Fan, S. Passive radiative cooling below ambient air temperature under direct sunlight. Nature 515, 540–544 (2014). \n27. Hossain, M. M., Jia, B. & Gu, M. A metamaterial emitter for highly efficient radiative cooling. Adv. Opt. Mater. 3, 1047–1051 (2015). \n28. Zou, C. et al. Metal‐Loaded dielectric resonator metasurfaces for radiative cooling. Adv. Opt. Mater. 5, 1700460 (2017). \n29. Zhai, Y. et al. Scalable-manufactured randomized glass-polymer hybrid metamaterial for daytime radiative cooling. Science 355, 1062–1066 (2017). \n30. Zhao, D. et al. Subambient cooling of water: toward real-world applications of daytime radiative cooling. Joule 3, 111–123 (2019). \n31. Gentle, A. R. & Smith, G. B. A subambient open roof surface under the MidSummer sun. Adv. Sci. 2, 1500119 (2015). \n32. Zhou, L. et al. A polydimethylsiloxane-coated metal structure for all-day radiative cooling. Nat. Sustain 2, 718–724 (2019). \n33. Kou, J. L., Jurado, Z., Chen, Z., Fan, S. & Minnich, A. J. Daytime radiative cooling using near-black infrared emitters. ACS Photon. 4, 626–630 (2017). \n34. Mandal, J. et al. Porous polymers with switchable optical transmittance for optical and thermal regulation. Joule 3, 1–12 (2019). \n35. Wang, X. et al. Scalable flexible hybrid membranes with photonic structures for daytime radiative cooling. Adv. Funct. Mater. 30, 1907562 (2019). \n36. Leroy, A. et al. High-performance subambient radiative cooling enabled by optically selective and thermally insulating polyethylene aeroge. Sci. Adv. 5, eaat9480 (2019). \n37. Li, T. et al. A radiative cooling structural material. Science 364, 760–763 (2019). \n38. Mandal, J., Yang, Y., Yu, N. & Raman, A. P. Paints as a scalable and effective radiative cooling technology for buildings. Joule 4, 1350–1356 (2020). \n39. Xue, X. et al. Creating an eco-friendly building coating with smart subambient radiative cooling. Adv. Mater. 32, 1906751 (2020). \n40. Suichi, T., Ishikawa, A., Hayashi, Y. & Tsuruta, K. Performance limit of daytime radiative cooling in warm humid environment. AIP Adv. 8, 055124 (2018). \n41. Fan, J., Fu, C. & Fu, T. Yttria-stabilized zirconia coating for passive daytime radiative cooling in humid environment. Appl. Therm. Eng. 165, 114585 (2020). \n42. Amenu, G. G. & Kumar, P. NVAP and Reanalysis-2 global precipitable water products: Intercomparison and variability studies. B. Am. Meteorol. Soc. 86, \n245–256 (2005). \n43. Fan, W. et al. Iridescence-controlled and flexibly tunable retroreflective structural color film for smart displays. Sci. Adv. 5, eaaw8755 (2019). \n44. Wu, Y., Zeng, J., Si, Y., Chen, M. & Wu, L. Large-area preparation of robust and transparent superomniphobic polymer films. ACS nano 12, 10338–10346 (2018). \n45. Durian, D. J., Weitz, D. A. & Pine, D. J. Multiple light-scattering probes of foam structure and dynamics. Science 252, 686–688 (1991). \n46. Bizheva, K. K., Siegel, A. M. & Boas, D. A. Path-length-resolved dynamic light scattering in highly scattering random media: The transition to diffusing wave spectroscopy. Phys. Rev. E 58, 7664 (1998). \n47. Aili, A. et al. Selection of polymers with functional groups for daytime radiative cooling. Mater. Today Phys. 10, 100127 (2019). \n48. Liu, J., Zhou, Z., Zhang, J., Feng, W. & Zuo, J. Advances and challenges in commercializing radiative cooling. Mater. Today Phys. 11, 100161 (2019). \n49. Zhou, L. et al. Self-assembly of highly efficient, broadband plasmonic absorbers for solar steam generation. Sci. Adv. 2, e1501227 (2016). \n50. Harrison, A. W. Effect of atmospheric humidity on radiation cooling. Sol. Energy 26, 243–247 (1981). \n51. Zeyghami, M., Goswami, D. Y. & Stefanakos, E. A review of clear sky radiative cooling developments and applications in renewable power systems and passive building cooling. Sol. Energ. Mat. Sol. C. 178, 115–128 (2018). \n52. Howell, J. R., Menguc, M. P. & Siegel, R. Thermal Radiation Heat Transfer. (CRC Press, 2015). \n53. Mu, E. et al. A novel self-powering ultrathin TEG device based on micro/nano emitter for radiative cooling. Nano Energy 55, 494–500 (2019). \n54. Hossain, M. M. & Gu, M. Radiative cooling: principles, progress, and potentials. Adv. Sci. 3, 1500360 (2016). \n55. Zhao, B., Hu, M., Ao, X., Chen, N. & Pei, G. Radiative cooling: a review of fundamentals, materials, applications, and prospects. Appl. Energy 236, \n489–513 (2019). \n56. Berk, A. et al. MODTRAN6: a major upgrade of the MODTRAN radiative transfer code. Proceedings of SPIE, 9088, 90880H–90880H–7 (2014). \n\n# Acknowledgements \n\nWe appreciate the financial support provided for this research by the National Key Research and Development Program of China (2017YFA0204600 and 2020YFE0100300) and the National Natural Science Foundation of China (52033003 and 51721002). \n\n# Author contributions \n\nL.W., T.W., and M.C. conceived the concept and designed the research. T.W. and Y.W. \nconducted the experiments. T.W. and L.S. conducted the FDTD simulations. T.W. \ncreated the schematics. L.W. and T.W. wrote the manuscript. All authors including X.H. \ndiscussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-20646-7. \n\nCorrespondence and requests for materials should be addressed to L.W. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41586-021-03251-6", + "DOI": "10.1038/s41586-021-03251-6", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03251-6", + "Relative Dir Path": "mds/10.1038_s41586-021-03251-6", + "Article Title": "High-resolution X-ray luminescence extension imaging", + "Authors": "Ou, XY; Qin, X; Huang, BL; Zan, J; Wu, QX; Hong, ZZ; Xie, LL; Bian, HY; Yi, ZG; Chen, XF; Wu, YM; Song, XR; Li, J; Chen, QS; Yang, HH; Liu, XG", + "Source Title": "NATURE", + "Abstract": "Current X-ray imaging technologies involving flat-panel detectors have difficulty in imaging three-dimensional objects because fabrication of large-area, flexible, silicon-based photodetectors on highly curved surfaces remains a challenge(1-3). Here we demonstrate ultralong-lived X-ray trapping for flat-panel-free, high-resolution, three-dimensional imaging using a series of solution-processable, lanthanide-doped nulloscintillators. Corroborated by quantum mechanical simulations of defect formation and electronic structures, our experimental characterizations reveal that slow hopping of trapped electrons due to radiation-triggered anionic migration in host lattices can induce more than 30 days of persistent radioluminescence. We further demonstrate X-ray luminescence extension imaging with resolution greater than 20 line pairs per millimetre and optical memory longer than 15 days. These findings provide insight into mechanisms underlying X-ray energy conversion through enduring electron trapping and offer a paradigm to motivate future research in wearable X-ray detectors for patient-centred radiography and mammography, imaging-guided therapeutics, high-energy physics and deep learning in radiology. Using lanthanide-doped nullomaterials and flexible substrates, an approach that enables flat-panel-free, high-resolution, three-dimensional imaging is demonstrated and termed X-ray luminescence extension imaging.", + "Times Cited, WoS Core": 545, + "Times Cited, All Databases": 571, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000683860300003", + "Markdown": "# Article \n\n# High-resolution X-ray luminescence extension imaging \n\nhttps://doi.org/10.1038/s41586-021-03251-6 \n\nReceived: 1 August 2020 \n\nAccepted: 11 December 2020 \n\nPublished online: 17 February 2021 Check for updates \n\nXiangyu Ou1,8, Xian Qin2,8, Bolong Huang3,8, Jie Zan1, Qinxia Wu1, Zhongzhu Hong1, Lili Xie1, Hongyu Bian2, Zhigao Yi2, Xiaofeng Chen1, Yiming Wu2, Xiaorong Song1, Juan Li1, Qiushui Chen1,5 ✉, Huanghao Yang1,5 ✉ & Xiaogang Liu2,4,6,7 ✉ \n\nCurrent X-ray imaging technologies involving flat-panel detectors have difficulty in imaging three-dimensional objects because fabrication of large-area, flexible, silicon-based photodetectors on highly curved surfaces remains a challenge1–3. Here we demonstrate ultralong-lived X-ray trapping for flat-panel-free, high-resolution, three-dimensional imaging using a series of solution-processable, lanthanide-doped nanoscintillators. Corroborated by quantum mechanical simulations of defect formation and electronic structures, our experimental characterizations reveal that slow hopping of trapped electrons due to radiation-triggered anionic migration in host lattices can induce more than 30 days of persistent radioluminescence. We further demonstrate X-ray luminescence extension imaging with resolution greater than 20 line pairs per millimetre and optical memory longer than 15 days. These findings provide insight into mechanisms underlying X-ray energy conversion through enduring electron trapping and offer a paradigm to motivate future research in wearable X-ray detectors for patient-centred radiography and mammography, imaging-guided therapeutics, high-energy physics and deep learning in radiology. \n\nFlat-panel X-ray detectors with active readout mechanisms have found critical applications in medical diagnostics, security screening and industrial inspection4. Over recent decades, several types of X-ray detector—mainly based on direct conversion of X-ray energy into electrical charges or indirect conversion using a scintillating material—have been implemented5–8. Many X-ray detection technologies require integration of flat-panel detectors with thin-film transistors (TFTs) consisting of pixelated photodiode arrays deposited on glass substrates. Although TFT-integrated flat-panel detectors offer high sensitivity for X-ray detection and radiographic reconstruction, they present substantial challenges for high-resolution X-ray imaging. Moreover, flat-panel detectors are costly and not applicable to three-dimensional (3D) X-ray imaging of curved or irregularly shaped objects. Despite enormous efforts, flexible X-ray detectors have not been well developed due to stringent dual requirements of a flexible TFT substrate and a thin layer of scintillators conformably attached to the flexible substrate. \n\nPersistent luminescent phosphors can store excitation energy and slowly release the captured energy as light emission9–12, making it possible to develop flat-panel-free X-ray detectors. Although inorganic oxide phosphors, such a $\\mathrm{\\langleSrAl_{2}O_{4};E u^{2+}/D y^{3+}}$ and $Z_{\\mathrm{n}}\\mathrm{Ga}_{2}\\mathrm{O}_{4};\\mathrm{Cr}^{3+}$ (ZGO:Cr), have been used for in vivo optical imaging under X-ray irradiation13, these materials suffer from low X-ray sensitivity14. Moreover, their fabrication also requires complex crystal growth processes under harsh conditions $(>600^{\\circ}\\mathbf{C})$ to generate efficient electron-trapping states in host lattices15. Persistent luminescent microparticles can be prepared by mechanical grinding12. However, microparticles are difficult to disperse in solution for thin-film processing, a prerequisite for the fabrication of flexible devices. \n\nLanthanide-doped nanomaterials that exhibit unique luminescence properties16,17 have been widely used in X-ray scintillation3,18–20, optical imaging21,22, biosensing23 and optoelectronics24. Notably, high-energy irradiation at ambient conditions can displace small anions from their lattice to interstitial sites, creating vacancy and interstitial pairs25. Here we report a general approach for flat-panel-free X-ray imaging of 3D electronic objects using lanthanide-doped nanoscintillators that feature high-efficiency X-ray absorption and long-lived energy trapping. We name this imaging technique X-ray luminescence extension imaging (Xr-LEI) for its ability to perform radiography on highly curved 3D objects after the termination of X-rays, which is inaccessible by conventional flat-panel X-ray detectors or synchrotron-based X-ray microscopy. \n\nWe synthesized a series of terbium $(\\mathsf{T}\\mathsf{b}^{3+})$ -doped NaLuF $_{4}$ nanoscintillators by a co-precipitation method22 (Extended Data Figs. 1, 2). A representative transmission electron microscopy (TEM) micrograph of oleic acid-capped NaLu $\\mathsf{F}_{4}{:\\mathsf{T b}}(15\\mathsf{m o l}\\%)\\ @\\mathsf{N a Y F}_{4}$ core–shell nanoscintillators reveals a hexagonal shape with an average size of $27\\mathsf{n m}$ (Fig. 1a). The radioluminescence of NaLuF $\\mathsf{\\Pi}_{4}{:}\\mathsf{T b}@\\mathsf{N a Y F}_{4}$ nanoscintillators was measured under excitation with a 50-kV X-ray source (Fig. 1b). We observed a set of intense emission bands, corresponding to ${}^{5}\\mathrm{D}_{4}\\twoheadrightarrow{}^{7}\\mathrm{F}_{4}$ (584 nm), $^5\\mathrm{D}_{4}\\to^{7}\\mathrm{F}_{5}\\left(546\\mathrm{nm}\\right)$ and $^5\\mathrm{D}_{4}\\to^{7}\\mathrm{F}_{6}\\left(489\\mathrm{nm}\\right)$ optical transitions of $\\mathsf{T}\\mathsf{b}^{3+}$ . On switching off the X-ray source, we recorded prolonged radioluminescence decay of these nanoscintillators with gradually decreasing intensity (Fig. 1b, c, Extended Data Fig. 3, Supplementary Video 1), suggesting effective trapping of ionizing radiation. Intriguingly, the afterglow emission of NaLuF $\\mathbf{\\Sigma}_{4}$ ${\\therefore\\mathsf{T b}}(\\underline{{a}})\\mathsf{N a Y F}_{4}$ nanoscintillators lasted more than 30 days after the termination of X-rays (Fig. 1b, bottom). By comparison, the afterglow lifetime of previously reported $Z\\mathsf{n}\\mathsf{G a}_{2}\\mathsf{O}_{4}{\\mathsf{:C r}}^{3+}$ phosphors is approximately 15 days12. We also observed a gradual increase in the emission intensity of NaLuF $\\overset{\\cdot}{4}$ $:\\mathsf{T b}@\\mathsf{N a Y F}_{4}$ nanoscintillators on continuous X-ray irradiation, indicating a dynamic energy-charging process (Extended Data Fig. 3). Importantly, our nanomaterials cannot be activated by daylight, making them ideal for fabrication of X-ray memory devices. Notably, coating of a ${\\mathsf{N a Y F}}_{4}$ shell onto NaLuF $_4$ :Tb nanoparticles enhanced the radioluminescence intensity by 1.5-fold, whereas the afterglow luminescence intensity was increased by 6.5-fold (Fig. 1c). These results suggest that ${\\mathsf{N a Y F}}_{4}$ -shell passivation can effectively mitigate quenching of trapped X-ray energies on nanocrystal surfaces. \n\n![](images/54b7f84f694cd0bd4ab3b21116f956998cc639f3527d9495aa6516d62b25854b.jpg) \nFig. 1 | Characterization of lanthanide-doped persistent luminescent nanoscintillators. a, TEM micrograph of NaLu $\\mathrm{\\dot{4}}{\\cdot}\\mathsf{T b}(\\mathsf{15m o l%})\\textcircled{a}\\mathsf{N a Y F_{4}}$ nanocrystals. b, Radioluminescent emission spectra of the core–shell nanocrystals, recorded after cessation of X-rays $(50\\mathsf{k V})$ for 0.5–168 h or 30 days. c, Radioluminescent intensity of NaLuF4:Tb (15 mol%) and NaLuF $_4\\mathrm{:}\\mathrm{Tb}(15\\mathrm{mol}^{\\circ})@\\mathrm{NaYF_{4}}$ nanocrystals, monitored at $546\\mathsf{n m}$ as a function of time upon cessation of X-rays. d, Comparison of afterglow decay profiles of \nvarious phosphors after cessation of X-ray excitation $(50\\mathsf{k V})$ . NPs, nanoparticles. e, Afterglow photographs of NaLuF $\\dot{\\mathbf{\\rho}}_{4}{\\cdot}\\mathsf{T b}(15\\mathsf{m o l}\\%)\\ @\\mathsf{N a Y F}_{4}$ nanocrystals dispersed in 1 ml cyclohexane. X-ray operation was set at a voltage of $70\\up k\\upnu$ with a tube current of 1 mA. f, Radioluminescence and afterglow of NaLuF4 nanocrystals doped with various activators $(\\mathsf{N d}^{3+},\\mathsf{T m}^{3+},\\mathsf{D y}^{3+},\\mathsf{T b}^{3+},\\mathsf{E r}^{3+},$ ${\\mathsf{H o}}^{3+}$ , $\\mathsf{S}\\mathsf{m}^{3+}$ and $\\mathsf{P r}^{3+}$ ). a.u., arbitrary units. \n\nWe next benchmarked the radioluminescence of NaLuF $_4$ : $\\mathrm{Tb}({15}\\mathrm{mol}^{\\circ}\\%)@\\mathrm{Na}\\mathrm{YF}_{4}$ nanoscintillators with commercial plastic scintillators and conventional persistent phosphors, including $\\mathsf{S r A l}_{2}\\mathsf{O}_{4}{:}\\mathsf{E u}^{2+}/$ $\\mathsf{D}\\mathsf{y}^{3+}$ powder, $Z\\mathrm{nS}{:}\\mathrm{Cu}^{2+}/\\mathrm{Co}^{2+}$ powder, $\\mathrm{SrAl}_{2}\\mathrm{O}_{4}{:}\\mathrm{Eu}^{2+}/\\mathrm{Dy}^{3+}$ nanoparticles and $Z\\mathsf{n}\\mathsf{G a}_{2}\\mathsf{O}_{4}{\\mathsf{:C r}}^{3+}$ nanoparticles. Under X-ray irradiation at $50\\mathrm{kV},$ our core–shell nanoscintillators exhibited much stronger X-ray-induced emission and afterglow luminescence than commercial counterparts (Fig. 1d, Extended Data Fig. 4, Supplementary Fig. 1, Supplementary Table 1). Improvements in performance were attributed to the large X-ray stopping power and high X-ray trapping efficiency of NaLuF $_4$ : \n\n# Article \n\n![](images/b4c7dccea4547bcec00ccdc2ba86961a392373b25f9d33bd17f959a30ede4b43.jpg) \nFig. 2 | Photophysical studies of X-ray irradiation on lanthanide-doped nanoscintillators. a, Absorption spectra of $\\mathsf{N a Y F}_{4}$ NaGdF4 and NaLu ${\\dot{\\mathbf{\\up}}}_{4}$ as a function of X-ray energy. Attenuation coefficients were obtained from ref. 26. The inset shows a schematic of X-ray-induced photoionization. b, Room-temperature afterglow intensity of NaYF4:Tb (15 mol%), NaGdF $_4\\mathrm{:}$ :Tb $(15\\mathrm{mol\\%})$ and NaLuF4:Tb (15 mol%) nanocrystals as a function of time after cessation of X-rays. All samples were excited with X-rays at $50\\mathrm{kV.}$ \nc, Dependence of transient formation energy on the separation distance between the $\\mathsf{V}_{\\mathtt{F}}$ and ${\\sf I}_{\\sf F}$ subdefects. d, Decay curves of the NaLuF4:Tb $(15\\mathrm{mol\\%})$ nanocrystals when illuminated with different X-ray dosages at room temperature. e, EPR spectra of as-synthesized NaLuF4:Tb $(15\\mathrm{mol\\%})$ nanocrystals. Samples were measured at room temperature under the following conditions: before X-rays, during X-rays, 2, 4 and 8 h after cessation of X-rays, and after heating at $200^{\\circ}\\mathrm{C}$ , respectively. $H,$ magnetic field. \n\n$\\mathsf{T b}@\\mathsf{N a Y F}_{4}$ nanoscintillators. These oleic acid-capped nanoscintillators emit radioluminescence visible to the unaided eye upon switching off the X-ray source $(70\\mathrm{kV},1\\mathrm{mA})$ (Fig. 1e). Moreover, multicolour radioluminescence modulation from the ultraviolet–visible to the near-infrared can be achieved using hexagonal-phase NaLuF $_4$ nanocrystals as a host material for activator doping (for example, ${\\mathsf{N}}{\\mathsf{d}}^{3+}$ , $\\mathsf{T m}^{3+}$ , $\\mathsf{D}\\mathsf{y}^{3+}$ , $\\mathsf{T}\\mathsf{b}^{3+}$ , $\\mathsf{E r}^{3+}$ , ${\\mathsf{H o}}^{3+}$ , $\\mathsf{S}\\mathsf{m}^{3+}$ and $\\mathsf{P r}^{3+^{\\prime}}.$ ) (Fig. 1f, Extended Data Fig. 5). Notably, there is no detectable afterglow of $\\mathsf{E u}^{3+}$ -doped nanoparticles after X-ray charging (Extended Data Fig. 6). \n\nTo understand how large-momentum X-ray photons interact with lanthanide-doped nanoscintillators to produce lasting radioluminescence, we examined the X-ray photon-absorbing ability of the NaLuF $^4$ host26,27. The absorption coefficient of NaLuF $^4$ (atomic number $Z_{\\mathrm{max}}=71$ , $\\mathsf{K}\\upalpha=63.31\\upk\\mathrm{eV})$ is larger than that of ${\\mathsf{N a Y F}}_{4}$ $(Z_{\\mathrm{max}}=39$ , $\\mathsf{K}\\upalpha=17.05\\mathsf{k e V}.$ ) or NaGdF4 $(Z_{\\mathrm{max}}=64\\$ , $\\mathsf{K}\\upalpha=50.24\\mathrm{keV})$ (Fig. 2a). Indeed, the afterglow intensity of NaLuF $_4$ :Tb $(15\\mathrm{mol\\%}$ ) nanocrystals is threefold stronger than that of ${\\mathsf{N a Y F}}_{4}$ :Tb $(15\\mathrm{mol\\%})$ ) nanocrystals, suggesting a heavy-atom (for example, ${\\mathsf{L}}{\\mathsf{u}}^{3+}$ ) effect on X-ray absorption (Fig. 2b). The high-efficiency radioluminescence was also attributed to the low phonon energy of the hexagonal-phase NaLuF $\\overset{\\cdot}{4}$ crystal lattice $(<350\\mathrm{cm}^{-1})$ ) and reduced surface quenching. Moreover, at a low $\\mathbf{G}\\mathbf{d}^{3+}$ concentration, the excitation energy can be efficiently transferred from $\\mathbf{G}\\mathbf{d}^{3+}$ to $\\mathsf{T}\\mathsf{b}^{3+}$ activators. By comparison, at a high $\\mathbf{G}\\mathbf{d}^{3+}$ concentration, the excitation energy dissipates non-radiatively to quenching sites through energy migration, resulting in fast spontaneous emission of $\\mathsf{T}\\mathsf{b}^{3+}$ with low afterglow intensity (Extended Data Fig. 6). \n\nWe further investigated long-lived X-ray energy trapping by modelling the formation of anion Frenkel defects in a NaLuF $_4$ lattice. We speculated that a sufficient energy may dislocate fluoride anions (F−) to interstitial sites through elastic collisions with large-momentum X-ray photons25,28 (Extended Data Fig. 7). This leads to formation of fluoride vacancies $(\\mathsf{V}_{\\mathtt{F}})$ and interstitials $(\\mathsf{I}_{\\mathtt{F}})$ , accompanied by the production and trapping of many energetic electrons $(e^{-})$ in Frenkel defect-associated trap states. Using first-principles calculations based on density functional theory (DFT), we monitored the structural relaxation of anion Frenkel pairs at various distances. We found that interstitial fluoride ions gradually diffuse back to original vacancies when the proximity of these two subdefects is less than $3\\mathring{\\mathbf{A}}$ . For defect pairs with a larger separation (more than $3\\mathring{\\mathsf{A}}$ ), interstitial fluoride ions can be stabilized due to increased energy barriers, except under stimulation with heating or light exposure. Creation of such defect pairs requires formation energies from $2.78\\mathrm{eV}$ to 12 eV, suggesting a high probability of displacing fluoride ions upon X-ray irradiation (Fig. 2c). Moreover, DFT calculations revealed that for defect pairs with small separation distances, electron relaxation and atom diffusion have similar rates (Extended Data Fig. 7). With an increase in separation distance, the rate of electron relaxation decreases, owing to substitution-based anion diffusion, rather than direct relaxation. \n\n![](images/358c9766ca4018fcd68682fdb42b8c294386a16c99bd64f9047a9b4906c4a9c5.jpg) \nFig. 3 | Mechanistic investigations of X-ray energy trapping in lanthanide-doped nanoscintillators. a, Proposed mechanism of long-lived persistent radioluminescence of $\\mathsf{T b}^{3+}$ -doped NaLuF4 nanocrystals. Upon X-ray excitation, electrons at an inner electronic shell of lattice atoms are photoexcited to produce low-energy electrons, which are either transferred to activators for emission or partially stored at electronic trap states. Electrons in shallow traps release slowly for spontaneous long-lasting emission of $\\mathsf{T b}^{3+}$ . In contrast, electrons in deep traps populate to the conduction band (CB) under optical or thermal stimulation. VB, valence band. b, Energy diagram of lanthanide 4f levels (in red) with respect to host bands (in black). Solid and dotted lines represent occupied and empty orbitals, respectively. c, Thermally \nstimulated luminescence spectra of NaLuF4:Tb $(15\\mathrm{mol\\%}$ ) nanocrystals measured in the temperature range of 170 to $470\\mathsf K$ The sample was first irradiated by an X-ray source for 300 s. After cessation of the X-ray source for $10\\mathrm{{min}}$ , emission spectra were measured at a heating rate of $\\mathrm{TK}\\mathsf{s}^{-1}$ d, Optically stimulated luminescence (OSL) decay profiles of NaLuF :Tb/Gd (15/5 mol%) nanocrystals, recorded upon turning off X-rays and photostimulation at 480, 530, 620, 808, 980 and $\\scriptstyle1,064{\\mathsf{n m}}$ for 2 min, respectively. All measurements were performed at room temperature 1 h after luminescence afterglow of the samples faded. $\\lambda_{\\mathrm{Exc.}}$ , excitation wavelength. e, X-ray absorption near-edge structure (XANES) spectra of the $\\mathsf{T b}\\mathsf{L}_{\\mathsf{I I I}}.$ edge, recorded from NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ :Tb $(15\\mathrm{mol\\%})$ nanocrystals and $\\mathrm{Tb}_{4}\\mathrm{O}_{7}$ reference samples. \n\nWe next examined the transient dynamics of X-ray energy trapping at Frenkel defects by varying the X-ray dosage. Our experiments indicated that afterglow intensity can be enhanced with higher doses, most likely owing to an increased density of trap states available for X-ray storage (Fig. 2d). We further measured captured electrons at trap states by electronic paramagnetic resonance (EPR) spectroscopy. After cessation of X-ray excitation, we observed a gradual decrease in EPR signal intensity $\\scriptstyle(g=1.8743$ and $g=2$ .1163; where $g$ is a scaling factor accounting for the coupling between orbital and spin angular momentum), and the EPR signal completely disappeared upon heating at $200^{\\circ}\\mathsf{C}$ for $20\\mathrm{min}$ (Fig. 2e). These results confirm that it is possible to generate high-density trap states in lanthanide-doped nanoscintillators using high-momentum X-ray photons and subsequently to achieve long-lived photon trapping. \n\nIn light of experimental and computational results, we proposed the following mechanism underlying long-lived photon trapping in lanthanide-doped nanoscintillators (Fig. 3a). In a NaLuF $_{4}$ :Tb $(15\\mathrm{mol\\%})$ nanoscintillator, X-ray energies are primarily absorbed by lutetium atoms in the lattice to create many energetic electrons, largely due to photoelectric effects. Through elastic collisions of large-momentum X-ray photons with small fluoride ions, anion Frenkel defects form in the nanocrystal and trap thermalized low-energy electrons, enabling long-lived photon trapping. Specifically, fluoride vacancies and interstitials are created as electron traps (E-traps) and hole traps (H-traps). Displacements of fluoride ions at short and long distances form transient shallow and long-lived deep trap states, respectively. Electrons in shallow traps can spontaneously escape over time to the conduction band with a concurrent defect self-healing process, whereas electrons in deep traps require extra energy in the form of either optical or thermal stimulation to migrate to $\\mathsf{T}\\mathsf{b}^{3+}$ emitters. Trapped holes can also migrate towards $\\mathsf{T}\\mathsf{b}^{3+}$ emitters, forming hole–Tb3+ centres that radiatively recombine with captured electrons. Notably, we did not observe $\\mathsf{E u}^{3+}$ emission as hole– $\\boldsymbol{\\cdot}\\boldsymbol{\\mathrm{Eu}}^{3+}$ centres could not be formed in \n\n# Article \n\n![](images/40ef7a37ef7e21c0999671807ccffec631ffa1dabfb6811ebad4f0eb473c0ff2.jpg) \nFig. 4 | High-resolution Xr-LEI. a, Schematic showing 3D electronic imaging enabled by a nanoscintillator-integrated, flexible detector. First, the detector is inserted into a 3D electronic circuit board for conformal coating. Next, the image of the electronic board is projected onto the detector. After cessation of X-rays, the detector is transferred onto a hot substrate for thermal stimulation and subsequently luminescence imaging. b, Xr-LEI of a 3D electronic board using a prototype NaLuF4:Tb(15 mol%)@NaYF4-based detector (voltage, $50\\up k\\upnu.$ ; \nheating temperature, $80^{\\circ}\\mathrm{C},$ . c, Imaging of the same circuit board using a conventional flat-panel X-ray detector. d, Xr-LEI of integrated circuits of an iPhone 6 Plus smartphone (voltage, $50\\upkappa\\upnu$ ; scale bar, ${500}\\upmu\\mathrm{m}\\mathrm{\\cdot}$ ). The inset is the corresponding digital photograph of the circuits. e, Photograph of a stretchable, NaLuF $_4\\mathrm{:}\\mathsf{T b}(15\\mathsf{m o l}\\%)\\ @\\mathsf{N a Y F}_{4}$ -based X-ray detector. f, High-resolution Xr-LEI using the stretchable X-ray detector (voltage, 50 kV). \n\n${\\sf E u}^{3+}$ -doped NaLuF $_4$ compounds on the basis of electronic calculations (Fig. 3b). We measured thermally stimulated luminescence spectra of NaLuF $_4$ :Tb nanocrystals in the temperature range of 170 to $470\\mathsf K$ (Fig. 3c, Supplementary Fig. 2), and the energy distribution of electron trap states was calculated as 0.12–0.98 eV below the conduction band (Extended Data Fig. 8). By optically stimulating stored electrons to escape from deep traps, we confirmed that high-energy photons induce stronger persistent luminescence than low-energy photons (Fig. 3d). The local electronic structure of $\\mathsf{T}\\mathsf{b}^{3+}$ was examined by X-ray absorption near-edge spectroscopy, revealing that $\\mathsf{T}\\mathsf{b}^{3+}$ activators in NaLuF ${\\bf{\\bar{\\Psi}}_{4}}$ nanocrystals maintain a trivalent state (Fig. 3e, Supplementary Fig. 3). The core–shell nanoscintillators showed high recyclability and photostability under X-ray irradiation and heating at $80^{\\circ}\\mathrm{C}$ for 14 cycles (Extended Data Fig. 8, Supplementary Video 1). \n\nThe ability to trap X-ray energy in nanoscintillators for persistent radioluminescence prompted us to develop a flexible detector for Xr-LEI (Fig. 4a, Extended Data Fig. 9). This detector was fabricated by embedding NaLuF $_4$ : $\\mathrm{Tb}({15\\mathrm{mol}^{\\circ}}\\%)@\\mathrm{Na}\\mathrm{YF}_{4}$ nanoscintillators $(2\\mathsf{w t\\%})$ 1 into a polydimethylsiloxane (PDMS) substrate $(16\\mathsf{c m}\\times16\\mathsf{c m}\\times0.1\\mathsf{c m})$ . Internal structures of a highly curved electronic circuit board can be visualized using the as-fabricated X-ray detector and a digital camera or smartphone (Fig. 4b). High-resolution 3D Xr-LEI was achieved by combining afterglow luminescence and graphical simulations (Supplementary Video 2). For comparison, only overlapped imaging of the electronic circuit board was rendered using a typical flat-panel X-ray detector (Fig. 4c, Supplementary Fig. 4). Using thin films containing $2.5\\mathrm{wt\\%NaLuF_{4}\\mathrm{:Tb(15\\mathrm{mol\\%)\\textcircled{\\omega}N a Y F_{4}}}}$ nanoparticles, the X-ray exposure for digital radiography shortened to 1 s (Extended Data Fig. 10). \n\nWe further demonstrated high-resolution Xr-LEI using a highly stretchable detector comprising $\\mathtt{V a L u F_{4}}\\mathtt{T b(15m o l\\%)}\\ @\\mathtt{N a Y F_{4}}$ nanoscintillators and commercial silicone rubber (Fig. 4d, Extended Data Fig. 11, Supplementary Video 3). The stretchable X-ray detector enabled a spatial imaging resolution of more than 20 line pairs per millimetre $(<25\\upmu\\mathrm{m})$ , which is much higher than that achievable by conventional flat-panel X-ray detectors (typically less than 5.0 line pairs per millimetre) (Fig. 4e, f). \n\nThe invention of the Xr-LEI technique enhances our understanding of the microscopic mechanism governing long-lived trapping of X-rays in condensed-matter systems. Our experimental investigations on X-ray-induced generation of Frenkel defect-based trap states offer new opportunities to fabricate persistent luminescent nanocrystals, which are highly desirable for applications in optogenetics, low-dose radiotherapy, optoelectronics, expansion microscopy, and quantification of radioactive particles, such as α, $\\upbeta$ or high-energy γ particles29–32. When coupled with highly stretchable elastomers33, these optical nanomaterials may allow the development of next-generation X-ray imaging technologies with unprecedented spatial resolution and special imaging capability for 3D conformal electronics34. Such low-cost, smartphone-recordable, X-ray imaging techniques are particularly suitable for point-of-care radiography, screening mammography without breast compression and semiconductor non-destructive inspection. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, \n\n# acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03251-6. \n\n1. Rogers, J. A., Someya, T. & Huang, Y. Materials and mechanics for stretchable electronics. Science 327, 1603–1607 (2010). \n2. Wang, S. et al. Skin electronics from scalable fabrication of an intrinsically stretchable transistor array. Nature 555, 83–88 (2018). \n3. Blahuta, S., Bessiere, A., Gourier, D., Ouspenski, V. & Viana, B. Effect of the X-ray dose on the luminescence properties of Ce:LYSO and co-doped Ca,Ce:LYSO single crystals for scintillation applications. Opt. Mater. 35, 1865–1868 (2013). \n4. Chen, Q. et al. All-inorganic perovskite nanocrystal scintillators. Nature 561, 88–93 (2018). \n5. Yakunin, S. et al. Detection of X-ray photons by solution-processed organic–inorganic perovskites. Nat. Photon. 9, 444–449 (2015). \n6. Wei, H. et al. Sensitive X-ray detectors made of methylammonium lead tribromide perovskite single crystals. Nat. Photon. 10, 333–339 (2016). \n7. Wei, W. et al. Monolithic integration of hybrid perovskite single crystals with heterogenous substrate for highly sensitive X-ray imaging. Nat. Photon. 11, 315–321 (2017). \n8. Büchele, P. et al. X-ray imaging with scintillator-sensitized hybrid organic photodetectors. Nat. Photon. 9, 843–848 (2015). \n9. le Masne de Chermont, Q. et al. Nanoprobes with near-infrared persistent luminescence for in vivo imaging. Proc. Natl Acad. Sci. USA 104, 9266–9271 (2007). \n10.\t Maldiney, T. et al. The in vivo activation of persistent nanophosphors for optical imaging of vascularization, tumours and grafted cells. Nat. Mater. 13, 418–426 (2014). \n11. Matsuzawa, T., Aoki, Y., Takeuchi, N. & Murayama, Y. A new long phosphorescent phosphor with high brightness, $\\mathsf{S r A l_{2}O_{4}}\\colon\\mathsf{E u}^{2+},\\mathsf{D y}^{3+}$ . J. Electrochem. Soc. 143, 2670–2673 (1996). \n12. Pan, Z. et al. Sunlight-activated long-persistent luminescence in the near-infrared from ${\\mathsf{C r}}^{3+}$ -doped zinc gallogermanates. Nat. Mater. 11, 58–63 (2012). \n13.\t Xue, Z. et al. X-ray-activated near-infrared persistent luminescent probe for deep-tissue and renewable in vivo bioimaging. ACS Appl. Mater. Interfaces 9, 22132–22142 (2017). \n14.\t Song, L. et al. Low-dose X-ray activation of W(VI)-doped persistent luminescence nanoparticles for deep-tissue photodynamic therapy. Adv. Funct. Mater. 28, 1707496 (2018). \n15.\t Li, Y. et al. Long persistent phosphors-from fundamentals to applications. Chem. Soc. Rev. 45, 2090–2136 (2016). \n16.\t Shyichuk, A. et al. Energy transfer upconversion dynamics in $\\mathsf{Y V O}_{4}\\colon\\mathsf{Y b}^{3+},\\mathsf E\\mathsf{r}^{3+}$ . J. Lumin. 170, 560–570 (2016). \n17.\t Capobianco, J. A., Vetrone, F., Boyer, J. C., Speghini, A. & Bettinelli, M. Enhancement of red emission $(^{4}\\mathsf{F}_{9/2}\\to^{4}|_{15/2})$ via upconversion in bulk and nanocrystalline cubic $\\mathsf{Y}_{2}\\mathsf{O}_{3}{:}\\mathsf{E r}^{3+}$ . J. Phys. Chem. B 106, 1181–1187 (2002). \n18.\t Van der Heggen, D. et al. Optically stimulated nanodosimeters with high storage capacity. Nanomaterials 9, 1127 (2019). \n19. Hsu, C.-C., Lin, S.-L. & Chang, C. A. Lanthanide-doped core–shell–shell nanocomposite for dual photodynamic therapy and luminescence imaging by a single X-ray excitation source. ACS Appl. Mater. Interfaces 10, 7859–7870 (2018). \n20.\t Nikl, M. & Yoshikawa, A. Recent R&D trends in inorganic single-crystal scintillator materials for radiation detection. Adv. Opt. Mater. 3, 463–481 (2015). \n21. Liu, Y. et al. Amplified stimulated emission in upconversion nanoparticles for super-resolution nanoscopy. Nature 543, 229–233 (2017). \n22. Prigozhin, M. B. et al. Bright sub-20-nm cathodoluminescent nanoprobes for electron microscopy. Nat. Nanotechnol. 14, 420–425 (2019). \n23.\t Bünzli, J.-C. G. Lanthanide luminescence for biomedical analyses and imaging. Chem. Rev. 110, 2729–2755 (2010). \n24.\t Fernandez-Bravo, A. et al. Continuous-wave upconverting nanoparticle microlasers. Nat. Nanotechnol. 13, 572–577 (2018). \n25.\t Lushchik, C. B. Creation of Frenkel defect pairs by excitons in alkali halides. Mod. Probl. Condens. Matter Sci. 13, 473–525 (1986). \n26.\t Berger, M. J. et al. XCOM: Photon Cross Sections Database (NIST, 2013); https://www.nist. gov/pml/xcom-photon-cross-sections-database \n27.\t Cooper, D. R., Capobianco, J. A. & Seuntjens, J. Radioluminescence studies of colloidal oleate-capped beta- $\\mathsf{\\cdot N a}(\\mathsf{G d},\\mathsf{L u})\\mathsf{F}_{4}\\mathsf{:L n}^{3+}$ nanoparticles $\\angle n=C e$ , Eu, Tb). Nanoscale 10, 7821–7832 (2018). \n28.\t Kang, M. et al. Resolving the nature of electronic excitations in resonant inelastic X-ray scattering. Phys. Rev. B 99, 045105 (2019). \n29.\t Lu, K. et al. Low-dose X-ray radiotherapy–radiodynamic therapy via nanoscale metal– organic frameworks enhances checkpoint blockade immunotherapy. Nat. Biomed. Eng. 2, 600–610 (2018). \n30.\t Yang, Y. et al. X-ray-activated long persistent phosphors featuring strong UVC afterglow emissions. Light Sci. Appl. 7, 88 (2018). \n31. Chen, F., Tillberg, P. W. & Boyden, E. S. Expansion microscopy. Science 347, 543–548 (2015). \n32.\t All, A. H. et al. Expanding the toolbox of upconversion nanoparticles for in vivo optogenetics and neuromodulation. Adv. Mater. 31, 1803474 (2019). \n33.\t Sun, J. Y. et al. Highly stretchable and tough hydrogels. Nature 489, 133–136 (2012). \n34.\t Holler, M. et al. High-resolution non-destructive three-dimensional imaging of integrated circuits. Nature 543, 402–406 (2017). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 \n\n# Article Methods \n\n# Chemicals \n\nGadolinium (III) acetate hydrate $(\\mathbf{G}\\mathbf{d}(\\mathbf{C}\\mathbf{H}_{3}\\mathbf{C}\\mathbf{O}_{2})_{3}{\\bullet}x\\mathbf{H}_{2}\\mathbf{O}_{2}$ , $99.9\\%$ ), yttrium (III) acetate hydrate $(\\Upsilon(\\mathsf{C H}_{3}\\mathsf{C O}_{2})_{3}{\\bullet}\\Upsilon\\mathsf{H}_{2}\\mathbf{O}$ , $99.9\\%$ ), lutetium (III) acetate hydrate $\\mathrm{(Lu(CH_{3}C O_{2})_{3}}{\\bullet}x\\mathrm{H}_{2}\\mathrm{O}$ , $99.9\\%$ ), thulium (III) acetate hydrate $\\mathrm{\\langleTm(CH_{3}C O_{2})_{3}{\\bullet}\\mathrm{\\timesH_{2}O}}$ , $99.9\\%$ ), praseodymium (III) chloride hydrate $\\left(\\mathsf{P r C l}_{3}\\bullet x\\mathsf{H}_{2}\\mathbf{O}\\right.$ , $99.9\\%$ ), neodymium (III) acetate hydrate $\\begin{array}{r}{(\\mathbf{Nd}(\\mathbf{C}\\mathbf{H}_{3}\\mathbf{C}\\mathbf{O}_{2})_{3}{\\bullet}x\\mathbf{H}_{2}\\mathbf{O},}\\end{array}$ , $99.9\\%$ ), samarium (III) acetate hydrate $\\mathrm{(Sm(CH_{3}C O_{2})_{3}{\\bullet}{x}H_{2}O,99.9\\%}$ ), terbium (III) acetate hydrate $\\mathrm{(Tb(CH_{3}C O_{2})_{3}}\\bullet x\\mathrm{H}_{2}\\mathrm{O},$ $99.9\\%$ ), dysprosium (III) acetate hydrate $\\mathrm{(Dy(CH_{3}C O_{2})_{3}}{\\bullet}x\\mathrm{H}_{2}\\mathrm{O}_{\\cdot}$ , $99.9\\%$ ), holmium (III) acetate hydrate $({\\sf H o}({\\sf C}{\\sf H}_{3}{\\sf C}{\\sf O}_{2})_{3}{\\bullet}x{\\sf H}_{2}{\\sf O}$ , $99.9\\%$ ), erbium (III) acetate hydrate $\\left(\\mathrm{Er}(\\mathrm{CH}_{3}\\mathrm{CO}_{2})_{3}{\\bullet}x\\mathrm{H}_{2}\\mathrm{O},99.9\\%\\right)$ , zinc nitrate hexahydrate $\\mathrm{\\Gamma}(Z{\\mathsf{n}}({\\mathsf{N O}}_{3})_{2}{\\mathsf{\\bullet}}6{\\mathsf{H}}_{2}{\\mathsf{O}},$ $599\\%$ ), gallium (III) nitrate hydrate $\\left(\\mathrm{Ga}(\\mathrm{NO_{3}})_{3}{\\bullet}x\\mathrm{H}_{2}\\mathrm{O},99.9\\%\\right)$ , chromium (III) nitrate nonahydrate $\\mathrm{(Cr(NO_{3})_{3}{\\bullet}9H_{2}O}$ , $99\\%$ , sodium hydroxide $(\\mathsf{N a O H},{>}98\\%)$ , ammonium fluoride $(\\mathsf{N H}_{4}\\mathsf{F},{>}98\\%$ ), 1-octadecene (ODE, $90\\%$ ), oleic acid (OA, $90\\%$ ) and cyclohexane (chromatography grade, $99.7\\%$ were purchased from Sigma-Aldrich. SYLGARD 184 silicone elastomer kit was purchased from Dow Corning. Persistent phosphor powders of $\\mathrm{CaAl_{2}O_{4};E u^{2+}/N d^{3+}}$ , $\\mathrm{Sr}_{2}\\mathrm{MgSi}_{2}\\mathrm{O}_{7}\\mathrm{Eu}^{2+}/\\mathrm{Dy}^{3+}$ , $\\mathrm{SrAl}_{2}\\mathrm{O}_{4}\\mathrm{:Eu}^{2+}/\\mathrm{Dy}^{3+}$ and $Z\\mathrm{nS}{:}\\mathbf{C}\\mathbf{u}^{2+}/\\mathbf{C}\\mathbf{o}^{2+}$ were purchased from Xiucai Chemical. Type-38 and Type-74 line-pair charts were purchased from Hua Ruisen Technology Development. $\\mathrm{Tb}_{4}\\mathrm{O}_{7}$ powder was purchased from Aladdin Biochemical Technology. BC422 plastic scintillator was a mixture of poly(vinyltoluene) and small molecules of 2-(4-tert-butylphenl)- 5-(4-biphenylyl)-1,3,4-oxadiazole, obtained from Saint-Gobain. ST401 plastic scintillator was purchased from Zhonghelixin. Unless otherwise noted, all chemicals were used without further purification. \n\n# Synthesis of $\\mathsf{B}{\\cdot}\\mathsf{N a L u F}_{4}\\mathsf{L I n}/\\mathsf{G d}\\left(x/(20-x)\\mathsf{m o l}\\%\\right)$ nanocrystals \n\nOA-capped NaLuF :Ln/Gd $(x/(20-x)\\mathrm{mol\\%}$ ) $\\ensuremath{(\\mathrm{Ln}^{3+})}=\\ensuremath{\\mathsf{P r}}^{3+}$ , ${\\mathsf{N}}{\\mathsf{d}}^{3+}$ , $\\mathsf{S m}^{3+}$ , Tb3+, $\\ensuremath{\\mathbf Ḋ y Ḍ }^{3+}$ , ${\\mathsf{H o}}^{3+}$ , $\\mathsf{E r}^{3+}$ and $\\mathsf{T m}^{3+}$ ; $x=0.5$ –15) nanocrystals were synthesized using a coprecipitation method22. In a typical experiment, a mixture of Ln $(\\mathbf{CH}_{3}\\mathbf{CO}_{2})_{3}{\\bullet}\\mathbf{\\mathcal{X}H}_{2}\\mathbf{O}$ (0.5 mmol; $\\mathsf{L}\\mathsf{n}=\\mathsf{L}\\mathsf{u}$ , Gd, Tb, Nd, Sm, Dy, Ho, Er and Tm) or $\\mathsf{P r C l}_{3}\\bullet x\\mathsf{H}_{2}\\boldsymbol{0}$ in the desired ratio was added into a 50-ml two-neck round-bottom flask containing $5.0\\mathrm{ml}$ OA and $7.5\\mathsf{m l}$ ODE. The mixture was heated to $150^{\\circ}\\mathrm{C}$ under vacuum for 30 min. After cooling to room temperature, $10.0\\mathrm{ml}$ methanol containing 2.0 mmol ${\\mathsf{N H}}_{4}{\\mathsf{F}}$ and 1.25 mmol NaOH was added to the solution. The resulting solution was vigorously stirred at $50^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ , followed by heating at $100^{\\circ}\\mathsf{C}$ under vacuum for another 10 min. The reaction mixture was quickly heated to $300^{\\circ}\\mathrm{C}$ at a rate of $20^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ for 1 h under a nitrogen atmosphere with stirring. After cooling to room temperature, the resultant nanocrystals were precipitated by addition of ethanol, collected by 8,000 r.p.m. centrifugation for 5 min, washed with absolute ethanol, dispersed in $4.0\\mathrm{ml}$ cyclohexane and finally stored in a freezer at $4^{\\circ}\\mathsf C$ . \n\n# Synthesis of $\\mathbf{\\beta}\\mathbf{\\{-NaLuF_{4}:T b/G d\\left(15/\\alpha\\mathbf{\\{\\{\\psi}\\mathbf{\\{\\psi}}}\\mathbf{\\{\\psi}}\\mathbf{\\{\\psi}}\\mathbf{\\psi}\\right)}}}\\end{array}$ ) nanocrystals \n\nThe synthetic procedure for N $\\mathrm{aLuF}_{4}{:}\\mathrm{Tb}^{3+}/\\mathrm{Gd}^{3+}\\left(15/x\\mathrm{mol}^{\\gamma}\\mathrm{;}x=0{-}35\\right)$ nanocrystals was identical to the synthesis of NaLuF $_4$ $:\\mathsf{T b}^{3+}/\\mathsf{G d}^{3+}$ $(x/(20-x)\\mathrm{mol}\\%;x=2-20)$ nanocrystals. \n\n# Synthesis of $\\pmb{\\beta}$ -NaReF4:Tb $(15\\mathrm{mol\\%})$ ) nanocrystals \n\nThe synthetic procedure for NaReF $_4$ :Tb $(15\\mathrm{mol\\%})$ ( $\\mathbf{\\nabla}\\cdot\\mathbf{Re}=\\mathbf{Y}$ or Gd) nanocrystals was identical to the synthesis of NaLuF $\\cdot$ :Tb $15\\mathrm{mol\\%})$ nanocrystals except for heating temperature and heating duration. To a $50\\mathrm{-}\\mathsf{m l}$ round-bottom two-necks flask, $5.0\\mathrm{ml}$ OA and $7.5\\mathsf{m l}$ ODE were added with a total amount of 0.5 mmol Re $\\mathrm{:(CH_{3}C O_{2})bullet\\boldsymbol{x}H_{2}O\\ }$ $\\mathrm{Re}=\\Upsilon,$ Gd and Tb). The resulting solution was heated at $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ under stirring and then cooled to room temperature. Afterward, a methanol solution $(10.0\\mathrm{ml})$ containing ${\\mathsf{N H}}_{4}{\\mathsf{F}}$ $(2.0\\:\\mathrm{mmol};$ ) and NaOH $\\left(1.25\\mathrm{mmol}\\right)$ was added to the solution. This solution was heated at $50^{\\circ}\\mathrm{C}$ for 30 min under stirring. Upon removal of methanol by heating at $100^{\\circ}\\mathsf{C}$ for $10\\mathrm{{min}}$ , the resulting solution was kept at $295^{\\circ}\\mathrm{C}$ for $1.5\\mathsf{h}$ . \n\nProducts were precipitated with ethanol, collected by centrifugation at 8,000 r.p.m. for $10\\mathrm{{min}}$ , washed with absolute ethanol and finally dispersed in $4.0\\mathrm{ml}$ cyclohexane. \n\n# Synthesis of $\\pmb{\\beta}$ -NaLuF $\\overset{\\cdot}{\\mathbf{4}}$ :Tb@NaYF4 core–shell nanocrystals \n\nThe $\\upbeta$ -NaLuF $\\dot{\\mathbf{\\Omega}}_{4}{:}\\mathsf{T b}@\\mathsf{N a Y F}_{4}$ core–shell nanocrystals were prepared using an epitaxial growth method. In a typical experiment, $0.5\\mathrm{mmol}$ $\\Upsilon(\\mathrm{CH}_{3}\\mathrm{COO}){\\bullet}4\\mathrm{H}_{2}\\mathrm{O}$ in $4.0\\mathrm{ml}$ OA and $16\\mathrm{ml}$ ODE were heated to $150^{\\circ}\\mathrm{C}$ under vacuum for $30\\mathrm{min}$ and then cooled to room temperature. The temperature was then decreased to $50^{\\circ}\\mathbf{C}$ , and $4.0\\mathrm{ml}$ as-prepared core nanocrystals were added to the mixture and heated at $80^{\\circ}\\mathsf{C}$ for 10 min to evaporate cyclohexane. After cooling to room temperature, a solution of 2.0 mmol ${\\mathsf{N H}}_{4}{\\mathsf{F}}$ and 1.25 mmol NaOH dissolved in $10\\mathrm{ml}$ methanol was added. The resulting mixture was vigorously stirred at $50^{\\circ}\\mathsf{C}$ for 30 min and then heated at $100^{\\circ}\\mathsf{C}$ for $10\\mathrm{{min}}$ . The reaction mixture was then quickly heated to $295^{\\circ}\\mathrm{C}$ for $1.5\\mathsf{h}$ under a nitrogen atmosphere while stirring. After cooling to room temperature, the resulting core–shell nanocrystals were precipitated by addition of ethanol, collected by centrifugation, washed with absolute ethanol and dispersed in 4 ml cyclohexane. \n\nSynthesis of $\\mathbf{\\hat{\\beta}}{\\cdot}\\mathbf{NaGdF_{4}}{\\cdot}\\mathbf{Tb}\\ @\\mathbf{Na}\\mathbf{Y}\\mathbf{F}_{4}$ core–shell nanocrystals The synthetic procedure for NaGdF $_4$ :Tb@NaYF4 nanocrystals was identical to the synthesis of NaLuF $\\mathsf{\\Pi}_{4}{:}\\mathsf{T b}@\\mathsf{N a Y F}_{4}$ nanocrystals. \n\n# Synthesis of $\\pmb{\\beta}$ -NaGdF4:Eu nanocrystals \n\nThe synthetic procedure for NaGdF $^4$ :Eu $(15\\mathrm{mol\\%})$ nanocrystals was identical to the synthesis of NaGdF ${\\overset{\\cdot}{_{4}}}$ :Tb ( $15\\mathrm{mol\\%})$ nanocrystals. \n\n# Preparation of $\\mathbf{ZnGa}_{1.995}\\mathbf{O}_{4}\\mathbf{:Cr}_{0.005}$ persistent luminescent nanoparticles \n\nIn a typical procedure, persistent luminescence nanoparticles were prepared by a hydrothermal method, followed by sintering in an inert atmosphere. A solution of $Z_{\\mathsf{n}}(\\mathsf{N O}_{3})_{2}{\\bullet}6\\mathsf{H}_{2}\\mathsf{O}$ $(0.2668{\\bf g},0.897{\\bf m m o l})$ , $\\begin{array}{r}{\\mathbf{Ga}(\\mathbf{NO}_{3})_{3}{\\bullet}x\\mathbf{H}_{2}\\mathbf{O}\\left(0.4577\\mathbf{g},1.7895\\mathbf{mmol}\\right)}\\end{array}$ and $\\mathrm{Cr}(\\mathrm{NO}_{3})_{3}{\\bullet}9{\\sf H}_{2}\\mathrm{O}\\left(0.0018{\\bf g},\\right.$ $0.0045\\mathrm{mmol};$ ) was added to a round-bottom flask and vigorously stirred at room temperature. The total volume was adjusted to $16\\mathrm{ml}$ by adding ultrapure water. Then, ammonium hydroxide $(28\\mathrm{wt\\%})$ solution was quickly added to adjust the pH to about 6.5 while a white precipitate gradually formed. After stirring for $30\\mathrm{min}$ , the mixture was transferred to a Teflon-lined autoclave $(25\\mathsf{m l})$ . The autoclave was put in an oven at $220^{\\circ}\\mathsf C$ . After 12 h reaction, the system was cooled to room temperature. The resulting products were washed with deionized water three times to remove excess inorganic species and subsequently dried at $60^{\\circ}\\mathsf{C}$ overnight. The powder was further sintered in air at $950^{\\circ}\\mathrm{C}$ for $4\\mathfrak{h}$ . \n\n# Physical characterization \n\nTEM and high-resolution TEM images were taken on a Tecnai G2 F20 S-TWIN microscope (FEI Nano Ports) operated at an accelerating voltage of $200\\mathsf{k V}.$ Elemental mapping analysis was performed using a scanning transmission electron microscopy and energy-dispersive X-ray spectroscopy equipped with a Tecnai G2 F20 S-TWIN microscope at an accelerating voltage of $120\\mathsf{k V}.$ High-resolution scanning transmission electron microscopy characterization was done with an FEI aberration-corrected Titan Cubed S-Twin transmission electron microscope at an accelerating voltage of $60\\mathsf{k V}.$ Scanning electron microscope characterization was performed on a Verios G4 XHR electron microscope (Thermal Fisher Scientific). Radioluminescent spectra and persistent luminescence decay curves were measured using an Edinburgh FS5 fluorescence spectrophotometer (Edinburgh Instruments) equipped with a miniature X-ray source (Amptek). Thermally stimulated luminescence was measured using an Edinburgh FS5 spectrophotometer coupled with an HFS 600 heating/cooling stage (Linkam Scientific Instruments) and a customized optical fibre. X-ray diffraction patterns were obtained using an X-ray powder diffractometer (D/MAX-3C, Rigaku) over the angular range of $5{\\mathrm{-}}90^{\\circ}$ . Photographs of X-ray-induced luminescence and radioluminescence-based X-ray imaging were acquired with a digital camera (Nikon, D850 coupled with AF-S Micro-Nikkor $105\\mathrm{mm}2.8\\mathrm{G}$ or AF-S Micro-Nikkor $40\\:\\mathrm{mm}2.8\\mathrm{G},$ in an all-manual mode. EPR was carried out using a Bruker model A300 spectrometer recorded at 9.85 GHz. X-ray absorption fine-structure spectra were collected with a BL14W beamline at the Shanghai Synchrotron Radiation Facility. The storage rings of the Shanghai Synchrotron Radiation Facility were operated at $3.5\\mathsf{G e V}$ with a stable current of $200\\mathrm{{mA}}$ . Using a Si (111) double-crystal monochromator, data collection was carried out in fluorescence mode using a Lytle detector. All spectra were collected under ambient conditions. \n\n# Mechanical compression of persistent phosphors \n\nPersistent phosphors were poured into an open mould (diameter, $7\\mathsf{m m})$ ). A pressure of 2 tons was applied to compress the powder for 20 s. A round disk of the powder was removed from the open mould for further characterization. The open mould (PMK-YB) and the tablet machine (PC-12S) were purchased from Jingtuo Instrument and Technology. \n\n# Electronic trap depth of NaLuF $^4$ :Tb/Gd (15/x mol%; x = 0–35) nanocrystals \n\nThe depth of electronic traps was characterized by measuring temperature-dependent thermoluminescence spectra of the $\\mathrm{NaLuF_{4}};\\mathrm{Tb}/\\mathrm{Gd}\\left(15/x\\mathrm{mol}\\%;x=0-35\\right)$ nanocrystals using the initial rise analysis method35. In a typical procedure, materials were heated at a temperature of $550\\mathsf{K}$ to completely release their trapped carriers using a cooling/heating stage (Linkam Scientific Instruments, HSF 600). Next, these samples were excited by an X-ray source for 5 min at a set temperature. Afterward, samples were heated to 550 K at a rate of $1\\mathsf{K}\\mathsf{s}^{-1}$ . Light output was measured using an Edinburgh FS5 spectrometer coupled with an optical fibre. \n\n# Mechanical characterization \n\nThe stretchability of silicone rubber was measured with an electrical universal material testing machine (CMT4104, MTS Systems). Silicone rubber samples were cut into rectangles $50\\mathrm{mm}$ in length, $10\\mathrm{mm}$ in width and 1 mm in thickness. \n\n# Fabrication of a flexible X-ray detector \n\nIn a typical experiment, SYLGARD 184 silicone elastomer base was premixed with the curing agent (10:1 by mass). Platinum-catalysed rubber elastomer was prepared by casting the commercial Ecoflex 30 (Smooth-On) mixture (part A and part B in 1:1 weight ratio). A cyclohexane solution of NaLuF $_4$ : $\\mathrm{Tb}({\\bf15m o l\\%})@\\mathrm{NaYF_{4}}$ nanocrystals with various concentrations was added to the resultant solution while stirring vigorously. The mixture was poured into a square acrylic plate $(16\\times16\\thinspace{\\mathsf{c m}}^{2})$ as a mould for thin-film fabrication. The resulting composites were degassed in a vacuum container to remove air bubbles. The mixture was finally heated at $80^{\\circ}\\mathbf{C}$ for 4 h. After cooling to room temperature, the as-fabricated film (thickness, $\\mathbf{1}\\mathbf{m}\\mathbf{m})$ was peeled from the square acrylic template and used for X-ray imaging. \n\n# Experimental setup for X-ray luminescence extension imaging \n\nA charge-coupled device camera (Tucsen, FL-20BW) was coupled with AZURE-6515TH10M objective (AZURE Photonics) and fixed on a bracket (Olympus China) using a quasi-focus screw. A heating plate was placed under the flexible X-ray detector to stimulate radioluminescence afterglow after turning off X-rays. \n\n# Digital X-ray imaging \n\nIn a typical procedure for X-ray imaging, the flexible X-ray detector was inserted into an electronic board or placed on its surface. A beam of X-ray source (P357, VJ Technologies) or miniature X-ray source (Amptek) \n\nwas applied to the electronic board with different amounts of X-ray exposure. After X-ray exposure, the flexible X-ray detector was placed on a metal plate and heated to $80^{\\circ}\\mathbf{C}$ . Images were recorded using a digital camera (exposure time, 10 s) or a smartphone or an optical microscope. \n\n# Three-dimensional projection of acquired X-ray images \n\nA 3D model of a printed circuit board was constructed using Solidworks software. The recorded X-ray images were projected onto the surface of the 3D model. \n\n# Calculation of electronic trap depth using the initial rise analysis method \n\nThermally stimulated luminescence was performed to investigate the electronic trap depth in the as-synthesized persistent luminescent nanomaterials. Using the initial analysis method, temperature-dependent luminescence spectra under different excitation temperatures were measured to calculate the distribution of trap depth. The equation for the first, second and general order afterglow curve can be expressed as: \n\n$$\nI(T)=C{\\mathrm{exp}}\\biggl(-\\frac{E_{\\mathrm{t}}}{k T}\\biggr),\n$$ \n\nwhere I is the intensity of thermally stimulated luminescence, $c$ is a constant, $E_{\\mathrm{t}}$ is the defect energy level, $k$ is the Boltzmann constant and T is the temperature. When the equation was plotted in an Arrhenius kinetic process, the equation in (1) can be expressed as: \n\n$$\n\\mathsf{l n}I(T)=\\mathsf{l n}C-\\frac{E_{\\mathrm{t}}}{k T}.\n$$ \n\nHence, the trap depth can be determined by the slope of the straight section on the low-temperature side: \n\n$$\nE_{\\mathrm{t}}{=}{-}k\\times8.617{\\times}10^{-2}\\mathrm{eV}.\n$$ \n\nThe glow curves of equation (1) are integrated to obtain the density of trapped electrons. The distribution of trap depth can be obtained by calculating the difference between each energy level. \n\n# Density functional theory \n\nDFT calculations were performed to determine the formation energies of defects and the corresponding ground-state electronic properties of both intrinsic and defective NaLuF $_4$ lattice with $P6^{-}$ space group. To calculate the transient formation energy of the anion Frenkel defect, DFT $+\\mathsf{U}$ calculations were conducted using the CASTEP (Cambridge Serial Total Energy Package) source code36, and the on-site Coulomb energy of the spurious electron self-energy was corrected using self-consistent determined U parameters on the localized 4f orbitals of rare-earth elements. The norm-conserving pseudopotentials for Na, Tb, Lu and F atoms were generated using the OPIUM code in the Kleinman–Bylander projector form37. Note that nonlinear partial core correction and a scalar relativistic averaging scheme are used to treat the spin–orbital coupling effect. In particular, we treated the $(4f,5s,5p,5d,$ 6s) states as valence states of the Tb and Lu atoms. The time-dependent DFT calculation was performed with a two-electron-based Tamm– Dancoff approximation imported from our self-consistent corrected ground-state wave function. A full set of optical properties of systems was retrieved by calculating excitation energies and transition probabilities, revealing more precise locations of absorption peaks in the optical spectrum than Kohn–Sham excitation energies. \n\nConcurrently, to estimate the location of impurity levels with respect to the bands of the NaLuF $\\mathbf{\\Sigma}_{4}^{\\prime}$ host, the screened-exchange hybrid density functional HSE06 was used to calculate precise ground-state electronic structures with spin–orbit coupling effect38. Note that $12\\%$ of \n\n# Article \n\nthe GGA-PBE functional is replaced by the Hartree−Fock exchange. These electronic calculations were performed within the framework of DFT implemented in the Vienna ab initio simulation package with the projector augmented wave method39. \n\n# Finite element simulation \n\nTo investigate tensile strain (the first principal stress) on the silicone rubber film structure, the finite element simulations were performed using commercial FET software COMSOL (COMSOL LIC). Geometries were meshed using eight-node hexahedron elements. The Mooney– Rivlin model was used to capture the hyperelastic behaviour of the material. For the random point in elastomer, the equilibrium differential equation along the Cartesian axis $(x,y,z)$ can be expressed as: \n\n$$\n\\left\\{\\begin{array}{l}{\\displaystyle\\frac{\\partial\\sigma_{x}}{\\partial x}+\\frac{\\partial\\tau_{x y}}{\\partial y}+\\frac{\\partial\\sigma_{x z}}{\\partial z}+f_{x}=0}\\\\ {\\displaystyle\\frac{\\partial\\tau_{y x}}{\\partial x}+\\frac{\\partial\\sigma_{y}}{\\partial y}+\\frac{\\partial\\tau_{y z}}{\\partial z}+f_{y}=0,}\\\\ {\\displaystyle\\frac{\\partial\\tau_{z x}}{\\partial x}+\\frac{\\partial\\tau_{y z}}{\\partial y}+\\frac{\\partial\\sigma_{z}}{\\partial z}+f_{z}=0}\\end{array}\\right.\n$$ \n\nwhere $f_{x},f_{y}$ and $f_{z}$ are the components of the vector of the stress per unit volume in the $x$ , y and $z$ directions. $\\tau$ and $\\sigma$ denote normal and shear stress, respectively. When slight displacement and deformation occur, if higher-order and nonlinear terms of the displacement derivative are omitted, the geometric equation in the Cartesian coordinate system x, y, z can be expressed as: \n\n$$\n\\left\\{\\begin{array}{l l}{\\varepsilon_{x}{=}\\displaystyle{\\frac{\\partial u}{\\partial x}},\\gamma_{x y}{=}\\displaystyle{\\frac{\\partial u}{\\partial y}}+\\frac{\\partial v}{\\partial x}}\\\\ {\\varepsilon_{y}{=}\\displaystyle{\\frac{\\partial v}{\\partial y}},\\gamma_{y z}{=}\\displaystyle{\\frac{\\partial v}{\\partial z}}+\\frac{\\partial w}{\\partial y},}\\\\ {\\varepsilon_{z}{=}\\displaystyle{\\frac{\\partial w}{\\partial z}},\\gamma_{x z}{=}\\displaystyle{\\frac{\\partial u}{\\partial z}}+\\frac{\\partial w}{\\partial x}}\\end{array}\\right.\n$$ \n\nwhere u, v and $w$ represent displacement in the $x,y$ and $z$ directions, respectively. When large displacement and deformation occur, nonlinear terms of displacement derivatives are preserved, and the geometric equation in the Cartesian coordinate system x, y, z can be expressed as: \n\n$$\n\\left\\{\\begin{array}{l l}{\\varepsilon_{x}=\\displaystyle\\frac{\\partial u}{\\partial x}+\\frac{1}{2}\\Bigg[\\left(\\frac{\\partial u}{\\partial x}\\right)^{2}+\\left(\\frac{\\partial v}{\\partial x}\\right)^{2}\\Bigg],\\gamma_{x y}=\\displaystyle\\frac{\\partial v}{\\partial x}+\\frac{\\partial u}{\\partial y}+\\frac{\\partial u}{\\partial x}\\frac{\\partial u}{\\partial y}+\\frac{\\partial v}{\\partial x}\\frac{\\partial v}{\\partial y}}\\\\ {\\varepsilon_{y}=\\displaystyle\\frac{\\partial v}{\\partial y}+\\frac{1}{2}\\Bigg[\\left(\\frac{\\partial v}{\\partial y}\\right)^{2}+\\left(\\frac{\\partial w}{\\partial y}\\right)^{2}\\Bigg],\\gamma_{y z}=\\displaystyle\\frac{\\partial v}{\\partial z}+\\frac{\\partial w}{\\partial y}+\\frac{\\partial v}{\\partial y}\\frac{\\partial v}{\\partial z}+\\frac{\\partial w}{\\partial y}\\frac{\\partial w}{\\partial z}}\\\\ {\\varepsilon_{z}=\\displaystyle\\frac{\\partial w}{\\partial z}+\\frac{1}{2}\\Bigg[\\left(\\frac{\\partial w}{\\partial z}\\right)^{2}+\\left(\\frac{\\partial u}{\\partial z}\\right)^{2}\\Bigg],\\gamma_{x z}=\\displaystyle\\frac{\\partial u}{\\partial z}+\\frac{\\partial w}{\\partial x}+\\frac{\\partial w}{\\partial z}\\frac{\\partial w}{\\partial x}+\\frac{\\partial u}{\\partial z}\\frac{\\partial u}{\\partial x}}\\end{array}\\right..\n$$ \n\nThe physical equation can be expressed as: \n\n$$\n\\boldsymbol{\\sigma}=\\boldsymbol{K}^{T}\\boldsymbol{\\sigma}_{\\boldsymbol{\\mathrm{l}}}=\\boldsymbol{K}^{T}\\boldsymbol{D}_{\\boldsymbol{\\mathrm{l}}}\\boldsymbol{\\varepsilon}_{\\boldsymbol{\\mathrm{l}}}=\\boldsymbol{K}^{T}\\boldsymbol{D}_{\\boldsymbol{\\mathrm{l}}}\\boldsymbol{K}\\boldsymbol{\\varepsilon}=\\boldsymbol{D}\\boldsymbol{\\varepsilon},\n$$ \n\nwhere $D$ is the elastic matrix and $\\varepsilon$ is the strain matrix. $D_{\\mathfrak{l}},\\sigma_{\\mathfrak{l}}$ and $\\varepsilon_{\\mathrm{{l}}}$ refer to the element stiffness matrix, the element stress matrix and the element strain matrix, respectively. \n\nAssuming that the internal force per unit area of the elastic body on the boundary is $T_{x},T_{y},T_{z},$ and the area force acting on the unit area of the known elastomer on the boundary $S_{\\sigma}$ (force boundary) is $\\overline{{T}}_{\\mathrm{x}},\\overline{{T}}_{\\mathrm{y}},\\overline{{T}}_{\\mathrm{z}}.$ According to the plane conditions: \n\n$$\nT_{x}=\\overline{{T_{x}}},T_{y}=\\overline{{T_{y}}},T_{z}=\\overline{{T_{z}}}.\n$$ \n\nSupposing that the outer normal of the boundary is N and the cosine of its direction is $n_{x},n_{y},n_{z},$ the internal force of the elastomer on the boundary can be determined by the following formula: \n\n$$\n\\left\\{\\begin{array}{l l}{T_{x}=n_{x}\\sigma_{x}+n_{y}\\tau_{x y}+n_{z}\\tau_{x z}}\\\\ {\\qquad\\mathrm{~}}\\\\ {T_{y}=n_{x}\\tau_{x y}+n_{y}\\sigma_{y}+n_{z}\\tau_{y z}}\\\\ {T_{z}=n_{x}\\tau_{x z}+n_{y}\\tau_{y z}+n_{z}\\sigma_{z}}\\end{array}\\right.\n$$ \n\nor \n\n$$\n\\lbrace T\\rbrace=n\\lbrace\\sigma\\rbrace.\n$$ \n\nAmong them: \n\n$$\nn={\\left[\\begin{array}{l l l l l l}{n_{x}}&{0}&{0}&{n_{y}}&{0}&{n_{z}}\\\\ {0}&{n_{y}}&{0}&{n_{x}}&{n_{z}}&{0}\\\\ {0}&{0}&{n_{z}}&{0}&{n_{y}}&{n_{x}}\\end{array}\\right]}.\n$$ \n\nThe displacement of the elastomer on $S_{u}$ is $\\bar{u},\\bar{v},\\bar{w}$ , hence: \n\n$$\nu=\\bar{u},\\upsilon=\\bar{v},w=\\bar{w},\n$$ \n\nwhere $S_{u}$ is the boundary conditions of the displacement. \n\n# Data availability The data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\n35.\t Van den Eeckhout, K., Bos, A. J. J., Poelman, D. & Smet, P. F. Revealing trap depth distributions in persistent phosphors. Phys. Rev. B 87, 045126 (2013). \n36.\t Huang, B. Doping of RE ions in the 2D ZnO layered system to achieve low-dimensional upconverted persistent luminescence based on asymmetric doping in ZnO systems. Phys. Chem. Chem. Phys. 19, 12683–12711 (2017). \n37.\t Rappe, A. M., Rabe, K. M., Kaxiras, E. & Joannopoulos, J. D. Optimized pseudopotentials. Phys. Rev. B 41, 1227–1230 (1990). \n38.\t Heyd, J., Scuseria, G. E. & Ernzerhof, M. Hybrid functionals based on a screened Coulomb potential. J. Chem. Phys. 118, 8207–8215 (2003). \n39.\t Kresse, G. & Furthmuller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n\nAcknowledgements We thank L. Ma, Y. Huang, X. Wang and B. Hou for technical assistance. This work is supported by the National Key and Program of China (grant number 2018YFA0902600), the National Natural Science Foundation of China (grant numbers 21635002, 21771135, 21871071 and 21771156), the Early Career Scheme fund (grant number PolyU 253026/16P) from the Research Grant Council in Hong Kong, Research Institute for Smart Energy of the Hong Kong Polytechnic University, Agency for Science, Technology and Research (grant numbers A1883c0011 and A1983c0038), NUS NanoNash Programme (NUHSRO/2020/002/NanoNash/LOA and R143000B43114) and National Research Foundation, the Prime Minister’s Office of Singapore under its NRF Investigatorship Programme (award number NRF-NRFI05-2019-0003). \n\nAuthor contributions X.O. and H.Y. initiated the project. Q.C. and X.L. conceived the concept of X-ray luminescence extension imaging. X.L., H.Y. and Q.C. supervised the project and organized the collaboration. X.O., X.L., H.Y. and Q.C. designed the experiments. X.O., Q.W., X.C., Z.H. and J.Z. performed nanocrystal synthesis. X.O., Q.W., J.Z. and L.X. performed luminescence measurements and X-ray imaging. X.O., Z.Y. and H.B. performed flexible X-ray imaging. X.Q. and B.H. carried out theoretical calculations. J.L., H.B. and Y.W. fabricated PDMS moulds and measured low-temperature scintillation spectra. X.O., H.Y., Q.C. and X.L. wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-03251-6. Correspondence and requests for materials should be addressed to Q.C., H.Y. or X.L. Peer review information Nature thanks Christophe Dujardin, Oscar Malta and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/d171ab134f55bd5582fddd06802f19a0b6109399a37d1c4578e84c4752c3c309.jpg) \n\nExtended Data Fig. 1 | Synthesis and characterization of $\\mathbf{T}\\mathbf{b}^{3+}$ -doped nanocrystals. a, Schematic for the synthesis of NaLu $\\dot{\\iota}_{4}{\\cdot}\\mathsf{L n}/\\mathsf{G d}$ $\\mathbf{\\chi}_{\\mathbf{{L}}\\mathbf{{n}}=\\mathbf{{Pr}}^{3+}}$ , $\\mathsf{S m}^{3+}$ , ${\\mathsf{H o}}^{3+}$ , $\\mathsf{E r}^{3+}$ , $\\mathsf{T}\\mathsf{b}^{3+}$ , $\\ensuremath{\\mathbf Ḋ y Ḍ }^{3+}$ , $\\mathsf{T m}^{3+}$ and $\\mathsf{N}\\mathsf{d}^{3+}$ ) nanocrystals. In a typical procedure, lanthanide acetate salts $(\\mathrm{Ln}(\\mathrm{Ac})_{3}{\\bullet}x\\mathrm{H}_{2}\\mathrm{O})$ were added to a flask containing OA and ODE. The mixture was heated at $150^{\\circ}\\mathrm{C}$ to form lanthanide–oleate coordination complexes. Nucleation of NaLuF4:Ln/Gd nanocrystals was triggered by injecting a methanol solution of NaOH and ${\\mathsf{N H}}_{4}{\\mathsf{F}}$ . Subsequently, the reaction solution was heated at $300^{\\circ}\\mathsf{C}$ for 1 h. The final product was precipitated with ethanol. OA was used as a surface ligand to control the particle size and stabilize as-synthesized nanocrystals. b–f, Low-resolution TEM images of as-synthesized hexagonal-phase nanocrystals (top) and corresponding size \n\ndistributions (bottom). These samples are NaLuF $_{4}{\\cdot}\\mathsf{T b/G d}$ $(15/35\\mathrm{mol\\%})$ (b), NaLuF :Tb/Gd $(15/25\\mathrm{mol\\%})$ (c), NaLuF $_{4}{\\cdot}\\mathsf{T b/G d}$ $15/15\\mathrm{mol\\%}$ (d), NaLuF $\\dot{\\mathbf{\\rho}}_{4}{\\cdot}\\mathsf{T b/G d}$ $(15/5\\mathrm{mol\\%})$ (e) and NaLuF $\\dot{\\mathbf{\\zeta}}_{4}$ :Tb ( $15\\mathrm{mol\\%})$ (f). Scale bars, $200\\mathsf{n m}$ . g, Particle size as a function of the lutetium doping ratio. h, Powder X-ray diffraction patterns for NaLuF $_{4}$ :Tb/Gd $(15/x\\mathrm{mol\\%}$ ; $\\scriptstyle x=0-35$ ) nanocrystals. All peaks are consistent with the hexagonal-phase NaLuF4 structure (Joint Committee on Powder Diffraction Standards (PDF) file number 27-0726). i, Corresponding persistent radioluminescence decay curves of NaLuF4:Tb/Gd (15/x mol%; $\\scriptstyle x=0-35$ ) nanocrystals monitored at 546 nm as a function of time. Spectra were obtained after X-ray excitation at a power density of $278\\upmu\\mathrm{Gy}\\leq^{-1}$ for 5 min at room temperature (298 K). \n\n# Article \n\n![](images/08a282f7cca40167569d48db89249dc9679f3e3b7f8f65924adf51696fcfe91b.jpg) \nExtended Data Fig. 2 | Chemical composition analysis of Tb3+-doped fluoride nanocrystals. a, Energy-dispersive X-ray element mapping of as-prepared NaLuF4:Tb/Gd $(15/5\\mathrm{mol\\%})$ ) nanocrystals (Na, green; Lu, red; Gd, yellow; F, purple; Tb, green blue). b–f, EDX spectra of NaLuF $_{4}{\\cdot}\\mathsf{T b/G d}$ \n\n$(15/35\\mathrm{mol\\%})$ (b), NaLuF $\\dot{\\bar{\\cdot}}_{4}$ :Tb/Gd ( $15/25\\mathrm{mol\\%}$ (c), NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ :Tb/Gd (15/15 mol%) (d), NaLuF4:Tb/Gd $(15/5\\mathrm{mol\\%})$ (e) and NaLuF4:Tb (15 mol%) (f) nanocrystals. $\\mathbf{g}$ Corresponding stoichiometric composition of NaLuF $_{\\cdot_{4}}$ :Tb/Gd (15/x mol%; $\\scriptstyle x=0-35$ ) nanocrystals. \n\n![](images/e551471e3d197ebe17676fc78e2f4d0af9898a14ee4e1138f9ad628881d71093.jpg) \nExtended Data Fig. 3 | Afterglow characterizations of the $\\mathbf{T}\\mathbf{b}^{3+}$ -doped nanocrystals. a, Powder X-ray diffraction patterns of NaLuF $\\dot{\\iota}_{4}{\\cdot}\\mathsf{T b}/\\mathsf{G d}$ $(x/(20-x)$ $1\\mathrm{mol\\%}$ ; $\\scriptstyle x=2-20$ ) nanocrystals, showing that all peaks are consistent with hexagonal-phase NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ (Joint Committee on Powder Diffraction Standards file number 27-0726). b, Radioluminescence decay curves of NaLuF $\\mathbf{\\rho}_{4}{:}\\mathsf{T b}^{3+}/\\mathsf{G d}^{3+}$ $(x/(20-x)\\mathrm{mol}\\%;x=2{-}20)$ nanocrystals monitored at $546\\mathsf{n m}$ after cessation of X-rays (dose rate, $278\\upmu\\mathrm{Gy}\\leq^{-1}$ ; excitation time, $300{\\mathsf{s}}$ temperature, 298 K). \nc, Radioluminescence intensities, monitored at ${546}\\mathsf{n m}$ as a function of time, of as-synthesized NaLuF4:Tb ( $15\\mathrm{mol\\%}$ and NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ $\\therefore\\mathrm{Tb}(15\\mathrm{mol}^{\\circ})@\\mathrm{NaYF}_{4}$ nanocrystals upon continuous X-ray irradiation. d, Luminescent decay profiles of NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ $\\mathrm{:Tb(15mol^{\\circ})}@\\mathrm{NaYF_{4}}$ nanocrystals. The luminescence intensity was monitored at ${546}\\mathsf{n m}$ as a function of time, recorded upon turning off X-rays or ultraviolet–visible excitation at 273, 369, 487, 530, 620 and $750\\mathsf{n m}$ for $5\\mathrm{{min}}$ , respectively. All measurements were performed at room temperature. \n\n# Article \n\n![](images/40de93c32dc89bcf2de50ea57ab035e0937bf96d28da7409cb20aac71904c4fa.jpg) \nExtended Data Fig. 4 | Morphology and radioluminescent afterglow performance of various persistent phosphors upon X-ray excitation. a-d, Representative TEM images of $\\mathrm{\\bullet}\\mathrm{r}\\mathsf{A l}_{2}\\mathsf{O}_{4}\\mathrm{:Eu}^{2+}/\\mathsf{D}\\mathsf{y}^{3+}$ powder (a), mechanically grounded $\\mathrm{SrAl}_{2}\\mathrm{O}_{4}\\mathrm{:Eu}^{2+}/\\mathrm{Dy}^{3+}$ nanoparticles (b), $Z n\\mathrm{Ga}_{2}\\mathrm{O}_{4}\\mathrm{;Cr}^{3+}\\left(\\mathrm{ZGO}\\mathrm{;Cr}\\right)$ nanoparticles prepared by hydrothermal synthesis at $220^{\\circ}\\mathrm{C}$ (c) and ZGO:Cr nanoparticles calcinated at $950^{\\circ}\\mathrm{C}$ (d). e, Radioluminescence spectra of NaLuF $\\mathrm{:Tb(15mol^{\\circ})}@\\mathrm{NaYF_{4}}$ nanoparticles, $\\mathrm{SrAl}_{2}\\mathrm{O}_{4}\\mathrm{:Eu}^{2+}/\\mathrm{D}{\\mathrm{y}}^{3+}$ bulk powder, $\\scriptstyle{Z\\ n S:C\\mathbf{u}^{2+}/C\\mathbf{o}^{2+}}$ bulk powder, $\\mathrm{SrAl}_{2}\\mathrm{O}_{4}\\mathrm{:Eu}^{2+}/\\mathrm{D}{\\mathrm{y}}^{3+}$ nanoparticles (after grinding), $\\mathbf{ZnGa_{1.995}O_{4}};\\mathbf{Cr}_{0.005}$ (ZGO:Cr) nanoparticles (before and after calcination), \n\n$\\mathrm{CaAl}_{2}\\mathrm{O}_{4};\\mathrm{Eu}^{2+}/\\mathrm{N}\\mathrm{d}^{3+}$ nanoparticles (after grinding) and $\\mathbf{Sr}_{2}\\mathbf{MgSi}_{2}\\mathbf{O}_{7}{\\cdot}\\mathbf{Eu}^{2+}/\\mathbf{Nd}^{3+}$ nanoparticles (after grinding). Insets show corresponding photographs of the samples under X-ray excitation. f, Radioluminescence intensity profiles of various persistent luminescent materials upon continuous X-ray irradiation as a function of time (accelerating voltage, $50\\up k\\upnu$ ; temperature, 298 K). g, Comparison of afterglow intensities of various persistent phosphors. Afterglow intensities were recorded after cessation of X-rays, following 300 s of X-ray excitation. h, Corresponding SEM images of compressed samples. All samples were prepared by a tablet machine without the PDMS matrix. \n\n![](images/dea451e2506cbbbfb0da402108e3602cc6ace3fb9ae6b39cfa06165989335add.jpg) \n\nExtended Data Fig. 5 | Characterization of persistent luminescent nanocrystals doped with different lanthanide activators. a, TEM images of NaLuF $\\operatorname{\\Pi}_{4}{:}\\operatorname{Pr}/\\operatorname{Gd}$ $\\mathrm{\\primeGd}\\left(0.5/19.5\\mathrm{mol\\%}\\right)$ , NaLuF $_4$ :Sm/Gd $(0.5/19.5\\mathrm{mol\\%})$ ), NaLuF :Ho/Gd $(1/19\\mathrm{mol\\%}$ ), NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ :Er/Gd $(1/19\\mathrm{mol\\%})$ ), NaLuF :Tb/Gd (15 $5\\mathrm{mol\\%}$ ), NaLuF $\\dot{\\cdot}_{4}$ :Dy/ Gd $(0.5/19.5\\mathrm{mol\\%}$ ), NaLuF $_{\\cdot_{4}}$ :Tm/Gd (1/19 mol%) and NaLuF4:Nd/Gd (1/19 mol%) nanocrystals. b, Powder X-ray diffraction patterns of NaLuF4:Ln/Gd ( $\\mathbf{\\chi}_{\\mathbf{{L}}\\mathbf{{n}}=\\mathbf{{Pr}}^{3+}}$ , $\\mathsf{S m}^{3+}$ , ${\\mathsf{H o}}^{3+}$ , $\\mathsf{E r}^{3+}$ , $\\mathsf{T}\\mathsf{b}^{3+}$ , $\\mathsf{D}\\mathsf{y}^{3+}$ , $\\mathsf{T m}^{3+}$ and ${\\mathsf{N}}{\\mathsf{d}}^{3+}$ ) nanocrystals. All peaks are indexed in accordance with the hexagonal-phase NaLuF4 structure (Joint Committee on Powder Diffraction Standards file number 27-0726). c, Room-temperature afterglow spectra of NaLuF4:Pr/Gd (0.5/19.5 mol%), NaLuF4:Sm/Gd \n\n$(0.5/19.5\\mathrm{mol\\%})$ ), NaLuF $\\mathrm{\\Pi_{4}}{:}\\mathrm{Ho/Gd}$ $(1/19\\mathrm{mol\\%})$ , NaLuF $_4{:}\\mathrm{Er/Gd}\\left(1/19\\mathrm{mol\\%}\\right)$ , NaLuF $_{4}{\\cdot}\\mathrm{Tb/Gd}$ $(15/5\\mathrm{mol\\%})$ , NaLuF :Dy/Gd (0.5/19.5 mol%), NaLuF :Tm/Gd $(1/19\\mathrm{mol\\%})$ and NaLuF ${\\dot{\\mathbf{\\up}}}_{4}$ :Nd/Gd $(1/19\\mathrm{mol\\%})$ nanocrystals. All spectra were recorded after turning off X-rays (dose rate, $278\\upmu\\mathrm{Gy}\\leq^{-1}$ ; excitation time, 300 s). d, Corresponding commission Internationale de l’Eclairage chromaticity coordinates of persistent luminescence. e, Room-temperature afterglow decay curves of NaLuF4:Ln/Gd $\\mathbf{\\chi}_{\\mathbf{L}\\mathbf{n}=\\mathbf{Pr}^{3+}}$ , $\\mathsf{S m}^{3+}$ , ${\\mathsf{H o}}^{3+}$ , $\\mathsf{E r}^{3+}$ , $\\mathsf{D}\\mathsf{y}^{3+}$ , $\\mathsf{T m}^{3+}$ and $\\mathsf{N}\\mathsf{d}^{3+}$ ) nanocrystals monitored at 606, 594, 542, 543, 573, 453 and $385\\mathsf{n m}$ , respectively (dose rate, $278\\upmu\\mathrm{Gy}\\upepsilon^{-1}$ ; excitation time, 300 s). \n\n# Article \n\n![](images/f55f0e653e522f33f0e34184914c390ccd4211485480fda0bfb38ed918b10dd2.jpg) \nExtended Data Fig. 6 | Physical investigation of X-ray-induced luminescence on lanthanide-doped fluoride nanocrystals. a, Emission spectra of NaLuF $_4$ :Eu $15\\mathrm{mol\\%}$ ) nanocrystals with and without X-ray irradiation. b, Luminescence intensity of NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ :Eu and NaLuF4:Tb nanocrystals as a function of time upon switching on/off X-rays. c, X-ray absorption near-edge structure (XANES) spectra of $\\mathsf{T b L}_{\\mathsf{I I I}}.$ edge recorded for NaLuF $_{4}$ :Eu (15 mol%) nanocrystals and $\\mathsf{E u}_{2}\\mathsf{O}_{3}$ and $\\mathsf{E u T i O}_{3}$ references. d, Room-temperature emission spectra of $\\mathsf{N a Y F}_{4}$ :Tb $(15\\mathrm{mol\\%})$ ), NaGdF :Tb $(15\\mathrm{mol\\%})$ ), and NaLu $\\dot{\\mathbf{\\rho}}_{4}$ :Tb $(15\\mathrm{mol\\%})$ ) nanocrystals. e, X-ray-induced luminescence intensity of NaYF $_4$ :Tb $(15\\mathrm{mol\\%})$ , NaGdF :Tb (15 mol%) and NaLuF :Tb $15\\mathrm{mol\\%}$ ), monitored at 546 nm. All \n\nsamples were excited with X-ray irradiation at 50 kV (dose rate, $278\\upmu\\mathrm{Gy}\\leq^{-1}$ ; temperature, 298 K). f, Luminescence decay curves of NaLuF4:Er/Gd $(1/x\\mathrm{mol\\%}$ ; $\\scriptstyle x=0-49 $ ) nanocrystals after X-ray excitation is ceased. g, Emission spectra of NaLuF4:Tb/Gd $(15/5\\mathrm{mol\\%})$ ) nanocrystals with and without X-ray irradiation, showing energy migration from $\\mathbf{G}\\mathbf{d}^{3+}$ to $\\mathsf{T b}^{3+}$ . h, Luminescence decay curves of the NaGdF4:Tb $(15\\mathrm{mol\\%}$ ) core and $\\mathrm{NaGdF_{4};T b(15m o l\\%)\\textcircled{\\omega}N a Y F_{4}},$ core–shell nanoparticles after cessation of X-rays. i, Schematic of NaGdF4:Tb crystal lattice and the energy level diagram of $\\mathrm{\\DeltaGd^{3+}}$ and $\\mathsf{T}\\mathsf{b}^{3+}$ . The excitation energy dissipates non-radiatively to quenching sites through energy migration. \n\n![](images/a9be805171fa0363befdc5c9d661db877a56e95b5890b766ebc0a014877ed8a6.jpg) \nExtended Data Fig. 7 | Calculated electronic structures of NaLuF4-based systems. a, Schematic illustrating creation of Frenkel-related trap states in NaLuF4 crystal lattices upon high-energy X-ray irradiation. Small fluoride ions (F−) are then displaced from lattice to interstitial sites. This leads to many fluoride vacancies $(\\mathsf{V}_{\\mathtt{F}})$ and interstitials $(\\mathsf{I}_{\\mathtt{F}})$ , along with trapping of energetic electrons $(e^{-})$ at anion defects. b, Structural configuration of closely and distantly paired defects in the NaLuF $\\dot{\\mathbf{\\rho}}_{4}$ lattice. Fluorine atoms are ejected from their original lattice sites to interstitial sites upon X-ray irradiation, followed by either spontaneous or stimulated self-recovery. c, Calculated electron and \n\natom relaxation speed of defect pairs featuring different separation distances. d, Density of states of pristine $\\upbeta$ -NaLuF4 (top), $\\mathsf{V}_{\\mathtt{F}}{-}\\mathsf{I}_{\\mathtt{F}}$ -contained $\\upbeta$ -NaLuF4 (middle) and $\\mathsf{V}_{\\mathtt{F}}\\mathrm{-I}_{\\mathtt{F}}$ contained $\\upbeta$ -NaLuF4:Tb (bottom). Green dashed lines indicate the position of Fermi levels. Localized states due to F displacement are marked with arrows. Note that the values of the 4f-resolved density of states are scaled up (tenfold) for comparison purposes. e, The corresponding spatial distribution of partial charge densities of $\\mathbf{\\ddot{V}}_{\\mathrm{F}}.$ and ${\\bf l}_{\\mathrm{F}}$ -induced localized states within the bandgap. Light purple and orange iso-surfaces are used for occupied and unoccupied localized states, respectively. \n\n# Article \n\n![](images/e26365871d3f9a486b2b01eaa5d930361978877371d7ddabe6a024315b896693.jpg) \nExtended Data Fig. 8 | Characterization of electronic trap depth in NaLuF4:Tb/Gd $\\mathbf{(15/x}$ mol%; $\\begin{array}{r}{{\\pmb x}={\\pmb0}-{3}{\\pmb5}^{{\\d}},}\\end{array}$ ) nanocrystals. a–e, Density distribution of electronic trap depths in NaLuF $\\mathbf{\\rho}_{4}{\\cdot}\\mathbf{T}\\mathbf{b}^{3+}/\\mathbf{G}\\mathbf{d}^{3+}\\left(15/35\\mathbf{mol}\\%\\right)$ (a), NaLuF4:Tb/Gd $(15/25\\mathrm{mol\\%})$ ) (b), NaLuF4:Tb/Gd $(15/15\\mathrm{mol\\%})$ (c), NaLu $_{4}$ :Tb/Gd $(15/5\\mathrm{{mol\\%})}$ (d) and NaLu $\\dot{\\mathbf{\\rho}}_{4}{:}\\mathsf{T}\\mathbf{b}$ ( $15\\mathrm{mol\\%})$ (e) nanocrystals. f, Measured electronic trap depth of $\\mathsf{T b}^{3+}$ -doped nanocrystals as a function of the doping ratio of lutetium in the material host. Data were calculated from the measured results of a–e. g, Luminescence profile of NaLuF $_4\\mathrm{:}\\mathsf{T b}(\\mathsf{15m o l}^{\\circ})@\\mathsf{N a Y F}_{4}$ nanocrystals under \nX-ray and after cessation of excitation, followed by cycled near-infrared stimulation with a $980{\\cdot}\\mathsf{n m}$ laser. h, Radioluminescence intensity of nanocrystals under repeated X-ray irradiation and thermal stimulation. Samples were excited with an X-ray source at $50\\up k\\upnu$ for 300 s. Radioluminescent afterglow decays quickly upon heating. i, Recycling performance evaluation of $\\mathtt{V a L u F_{4}}\\mathrm{:Tb(15mol\\%)}\\ @\\mathsf{N a Y F_{4}}$ nanocrystals under X-ray irradiation and heating at $80^{\\circ}\\mathsf{C}$ for 14 cycles. \n\n![](images/8aec4897c3271c42a9ad3b66f338e1e4b234e1931640e7d63a89ef544627848f.jpg) \nExtended Data Fig. 9 | Xr-LEI based on persistent radioluminescent nanocrystals. a, Schematic showing the microscopy setup for X-ray imaging. b, c, Bright-field photos (top) and X-ray images (bottom) of an X-ray dosimeter (b) and a computer mouse (c). d–f, Bright-field photos (top) and X-ray images (bottom) of a 3D electronic circuit board, conforming and adhering to the X-ray \n\ndetector (d, e) or placed on the top of the X-ray detector as a control (f). g, Photograph (left) and corresponding X-ray images (right) of an encapsulated metallic spring, recorded with a digital camera at time intervals from 1 s to 15 days. The Xr-LEI was performed by heating the flexible detector at $80^{\\circ}\\mathsf{C}$ after cessation of X-rays (50 kV). \n\n![](images/fe23dce0c8290816b28bf16dae5faea06213a7f94cc9fd6c9c058f446a54f8a9.jpg) \nExtended Data Fig. 10 | X-ray imaging of an electronic circuit board using a PDMS thin film containing NaLuF4:Tb(15 mol%)@NaYF4 nanoparticles. \n\nhe X-ray exposure was controlled from 1 to 15 s, and the nanoparticle concentration in the PDMS film was controlled between 0.4 and $2.5\\mathsf{w t\\%}$ . \n\n![](images/249e39fa4b388b7d90b504ebfcb49500603faf83e0083dd558c0149c2aa629dd.jpg) \nExtended Data Fig. 11 | Characterization of the stretchable X-ray detector. a, Material parameters were obtained by fitting the stress–strain curve of the elastomer using the Mooney–Rivlin model. Experimental results and analysis derived a tensile elastic modulus $(E_{\\mathrm{t}})$ of 10 psi (0.0689 MPa), a tensile strength $(\\sigma_{\\mathrm{t}})$ of 200 psi (1.379 MPa), a Poisson ratio $(\\mu)$ of 0.35 and a bulk modulus $(D)$ of 0.0766 MPa $\\dot{C}_{10}=0.065\\mathrm{MPa}$ , $C_{01}{=}0.36\\mathsf{M P a}$ ). b, Stress–strain curve of the film \n\nin 10 cyclic stress-strain tests, with a sample width of $\\mathrm{{10}m m}$ , a thickness of 1 mm, a gauge length of $50\\mathsf{m m}$ and a loading rate of $100\\mathrm{{mmmin^{-1}}}$ . c, Finite element simulation of strain distribution over the stretchable X-ray detector as the local strain increases to $50\\%$ . d, Light intensity function of pixels (along the blue line below and the full-width at half-maximum taken as the resolution) and X-ray imaging of a line-pair mask. " + }, + { + "id": "10.1038_s41929-021-00605-1", + "DOI": "10.1038/s41929-021-00605-1", + "DOI Link": "http://dx.doi.org/10.1038/s41929-021-00605-1", + "Relative Dir Path": "mds/10.1038_s41929-021-00605-1", + "Article Title": "Atomically dispersed antimony on carbon nitride for the artificial photosynthesis of hydrogen peroxide", + "Authors": "Teng, ZY; Zhang, QT; Yang, HB; Kato, K; Yang, WJ; Lu, YR; Liu, SX; Wang, CY; Yamakata, A; Su, CL; Liu, B; Ohno, T", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Artificial photosynthesis offers a promising strategy to produce hydrogen peroxide (H2O2)-an environmentally friendly oxidant and a clean fuel. However, the low activity and selectivity of the two-electron oxygen reduction reaction (ORR) in the photocatalytic process greatly restricts the H2O2 production efficiency. Here we show a robust antimony single-atom photocatalyst (Sb-SAPC, single Sb atoms dispersed on carbon nitride) for the synthesis of H2O2 in a simple water and oxygen mixture under visible light irradiation. An apparent quantum yield of 17.6% at 420 nm together with a solar-to-chemical conversion efficiency of 0.61% for H2O2 synthesis was achieved. On the basis of time-dependent density function theory calculations, isotopic experiments and advanced spectroscopic characterizations, the photocatalytic performance is ascribed to the notably promoted two-electron ORR by forming mu-peroxide at the Sb sites and highly concentrated holes at the neighbouring N atoms. The in situ generated O-2 via water oxidation is rapidly consumed by ORR, leading to boosted overall reaction kinetics. Hydrogen peroxide is an interesting target for artificial photosynthesis, although its actual production via the two-electron oxygen reduction reaction remains limited. Now, a carbon nitride-supported antimony single atom photocatalyst has been developed with a superior performance for this process.", + "Times Cited, WoS Core": 545, + "Times Cited, All Databases": 557, + "Publication Year": 2021, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000653054400008", + "Markdown": "# Atomically dispersed antimony on carbon nitride for the artificial photosynthesis of hydrogen peroxide \n\nZhenyuan Teng1,2,8, Qitao Zhang3,8, Hongbin Yang4,8, Kosaku Kato $\\textcircled{10}5$ , Wenjuan Yang3, Ying-Rui Lu6, Sixiao Liu2,7, Chengyin Wang $\\textcircled{1}2,7$ , Akira Yamakata $\\oplus5$ , Chenliang Su   3 ✉, Bin Liu $\\oplus4\\boxtimes$ and Teruhisa Ohno   1,2 ✉ \n\nArtificial photosynthesis offers a promising strategy to produce hydrogen peroxide $(H_{2}O_{2})$ —an environmentally friendly oxidant and a clean fuel. However, the low activity and selectivity of the two-electron oxygen reduction reaction (ORR) in the photocatalytic process greatly restricts the ${\\bf H}_{2}\\bar{\\bf O}_{2}$ production efficiency. Here we show a robust antimony single-atom photocatalyst (Sb-SAPC, single Sb atoms dispersed on carbon nitride) for the synthesis of ${\\bf H}_{2}\\bar{\\bf O}_{2}$ in a simple water and oxygen mixture under visible light irradiation. An apparent quantum yield of $17.6\\%$ at $420n m$ together with a solar-to-chemical conversion efficiency of $0.61\\%$ for ${\\bf H}_{2}\\bar{\\bf O}_{2}$ synthesis was achieved. On the basis of time-dependent density function theory calculations, isotopic experiments and advanced spectroscopic characterizations, the photocatalytic performance is ascribed to the notably promoted two-electron ORR by forming $\\pmb{\\mu}$ -peroxide at the Sb sites and highly concentrated holes at the neighbouring N atoms. The in situ generated $\\bullet_{2}$ via water oxidation is rapidly consumed by ORR, leading to boosted overall reaction kinetics. \n\nydrogen peroxide $\\mathrm{(H}_{2}\\mathrm{O}_{2})$ is an important green oxidant1 widely used in a variety of industries and a promising clean fuel for jet car and rocket $\\mathrm{\\Large;}2\\mathrm{-}7$ $60\\mathrm{wt\\%}$ $\\mathrm{H}_{2}\\mathrm{O}_{2}$ has an energy density of 3.0 mega joules $(\\mathbf{M}\\mathbf{J})\\mathbf{l}^{-1}$ , higher than compressed $\\mathrm{H}_{2}$ gas at $35\\mathrm{MPa},2.8\\mathrm{MJ^{-1}},$ ). Currently, $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is manufactured by the energy-consuming, waste-intensive and indirect anthraquinone method8,9. Photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis on semiconductor materials from water and oxygen has emerged as a safe, environmentally friendly and energy-saving process10,11. To achieve high efficiency for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production, it is crucial to boost the $2\\mathrm{e^{-}}$ oxygen reduction reaction (ORR) (equation $(1))^{12}$ or the $2\\mathrm{e}^{-}$ water oxidation reaction (WOR) (equation (2))13. The light-driven $2\\mathrm{e^{-}}$ WOR pathway is not easy to achieve due to the uphill thermodynamics $\\mathrm{1.76V}$ versus normalized hydrogen electrode, NHE); that is, the as-synthesized $\\mathrm{H}_{2}\\mathrm{O}_{2}$ will decompose at this highly oxidative potential since $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is an excellent hole scavenger11,14,15. On the contrary, the $2\\mathrm{e}^{-}$ ORR pathway has been realized for artificial photosynthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in several particulate systems12,16–23. However, the highest apparent quantum yield $(\\Phi\\mathrm{AQY})$ for non-sacrificial $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production (equation (3)) is still smaller than $8\\%$ (at $\\lambda{=}420\\mathrm{nm})^{16{-}24}$ , much lower than the highest $\\Phi\\mathrm{AQY}$ values reached for overall water splitting (roughly $30\\%$ at $\\lambda{=}420\\mathrm{nm}$ )25. To boost the photocatalytic activity for the non-sacrificial $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production, both $2\\mathrm{e}^{-}$ ORR (equation (2)) and $4\\mathrm{e^{-}}$ WOR (equation (4)) should be promoted simultaneously. Unlike some other photocatalytic processes (for example, overall water splitting and $\\mathrm{N}_{2}$ fixation)25,26, these redox reactions cannot be separately considered as irrelevant half reactions, since \n\n$\\mathrm{O}_{2}$ is not only a product in the $4\\mathrm{e}^{-}$ WOR (equation (4)), but also a reactant in the $2\\mathrm{e^{-}}$ ORR (equation (1)). If the in situ generated $\\mathrm{~O}_{2}$ from WOR (equation (4)) can be consumed rapidly by ORR, it will kinetically facilitate the WOR. Therefore, introducing highly active and selective sites for the $2\\mathrm{e}^{-}$ ORR in the photocatalytic system to consume the $\\mathrm{O}_{2}$ generated from the WOR offers a promising strategy for breaking the bottleneck of photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis. \n\n$$\n\\mathrm{O}_{2}+2\\mathrm{H}^{+}+2\\mathrm{e}^{-}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}_{2}\\left(0.695\\mathrm{V}\\mathrm{versusNHE}\\right)\n$$ \n\n$$\n2\\mathrm{H}_{2}\\mathrm{O}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}_{2}+2\\mathrm{H}^{+}+2\\mathrm{e}^{-}\\left(1.76\\mathrm{V}\\mathrm{versusNHE}\\right)\n$$ \n\n$$\n2\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{O}_{2}\\to2\\mathrm{H}_{2}\\mathrm{O}_{2}\n$$ \n\n$$\n2\\mathrm{H}_{2}\\mathrm{O}+4\\mathrm{h}^{+}\\rightarrow\\mathrm{O}_{2}+4\\mathrm{H}^{+}\\left(1.23\\mathrm{V}\\mathrm{versusNHE}\\right)\n$$ \n\n$$\n\\mathrm{O}_{2}+4\\mathrm{H}^{+}+4\\mathrm{e}^{-}\\rightarrow2\\mathrm{H}_{2}\\mathrm{O}\\left(1.23\\mathrm{V}\\mathrm{versusNHE}\\right)\n$$ \n\nManipulating metallic sites can change both the activity and selectivity of $\\mathrm{ORR}^{27}$ . The $\\mathrm{O}_{2}$ molecular adsorption on metal surface can be generally classified into three types (Fig. 1a): Pauling-type (end-on), Griffiths-type (side-on) and Yeager-type (side-on)27,28. The end-on $\\mathrm{~O}_{2}$ adsorption configuration is able to minimize O–O bond breaking, leading to the suppression of $4\\mathrm{e}^{-}$ ORR (equation (5)) and thus, a highly selective $2\\mathrm{e^{-}}$ ORR. On metal particles, both end-on and side-on $\\mathrm{O}_{2}$ molecular adsorption exist, and thus $_{\\mathrm{O-O}}$ bond splitting on the metal particles’ surfaces is difficult to prevent29,30. Benefiting from the desirable features of the single atom catalyst (SAC), the adsorption of $\\mathrm{O}_{2}$ molecules on atomically isolated sites is usually the end-on type, and could therefore reduce the possibility of $_{\\mathrm{O-O}}$ bond breaking (Fig. 1b)31–34. For instance, SACs with $\\mathrm{Pt}^{2+}$ (ref. 35) and $\\mathrm{Co-N_{4}}$ (refs. $^{36,37}$ ) centres could electrochemically reduce $\\mathrm{~O}_{2}$ to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ via a $2\\mathrm{e}^{-}\\mathrm{ORR}$ pathway with ultrahigh selectivity $(>96\\%)$ ). However, $\\mathrm{Pt}^{2+}$ and $\\mathrm{Co-N_{4}}$ sites are difficult to couple in the photocatalytic system due to their high charge recombination characteristics, which originate from the intermediate band formed by the half-filled $d$ electrons. Constructing photocatalysts with atomically dispersed elements possessing the $d^{10}$ electronic configuration can eliminate the formation of the intermediate band in the band structure, which is favourable for efficient charge separation and formation of reactive centres with a high density of electrons/ holes15,38,39. This suggests that SACs with the $d^{10}$ electronic configuration would be ideal candidates for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis via the $2\\mathrm{e^{-}}$ ORR. \n\n![](images/a0acf78c45afbd81d13954eae755c0df82a19782bc8258956e861d587ded3208.jpg) \nFig. 1 | Photocatalytic performance of Sb-SAPC towards ${\\bf H}_{2}{\\bf O}_{2}$ production. a, Schematic structures of $\\mathsf{O}_{2}$ adsorption on metal surface. b, ORR on a metal particle (top) and an isolated atomic site (bottom). c, Action spectra of PCN, PCN_Na15 and Sb-SAPC15 towards ${\\sf H}_{2}{\\sf O}_{2}$ production in a phosphate buffer solution $\\langle\\mathsf{p H}=7.4\\rangle$ ). Error bars represent the standard deviations of three replicate measurements. d, Solar-to-chemical conversion efficiency of PCN, PCN_Na15 and Sb-SAPC15 under AM 1.5 illumination in a phosphate buffer solution. e, Selectivity comparison of Sb-SAPC15 and pristine PCN for different photoreduction reactions (reaction time 1 h). Left, comparison of hydrogen evolution activity of Sb-SAPC15 and PCN loaded with 1 wt% Pt in a $10\\%$ (v/v) 2-propanol aqueous solution. Right, comparison of activity for photocatalytic ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ production on pristine PCN, PCN_Na15 and Sb-SAPC15 in a phosphate buffer solution with or without $\\mathsf{O}_{2}$ . f, Amount of $\\mathsf{O}_{2}$ and ${\\sf H}_{2}{\\sf O}_{2}$ produced on Sb-SAPC15 in $N a l O_{3}$ (0.1 M, as the electron acceptor) solution. g, Photocatalytic ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ production with electron acceptor $(0.1\\mathsf{m}\\mathsf{M}\\mathsf{A}\\mathsf{g}^{+})$ under ${\\sf N}_{2}$ atmosphere. Irradiation conditions were $\\lambda>420\\mathsf{n m}$ $\\mathsf{\\Omega}_{\\mathsf{X e}}$ lamp, light intensity at 420– 500 nm, $30.3\\mathsf{W}\\mathsf{m}^{-2};$ at $298\\mathsf{K}.$ . ND (not detected) in Fig. 1e,g means that ${\\sf H}_{2}{\\sf O}_{2}$ cannot be detected in the photocatalytic system. \n\nHerein, we develop a Sb single atom photocatalyst (Sb-SAPC) for non-sacrificial photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis in a water and oxygen mixture under visible light irradiation, in which the oxidation state of Sb is regulated to $+3$ with a $4d^{10}5s^{2}$ electron configuration. Notably, an apparent quantum efficiency of $17.6\\%$ at $420\\mathrm{nm}$ and a solar-to-chemical conversion efficiency of $0.61\\%$ are achieved on the as-developed photocatalyst. Combining experimental and theoretical investigations, it is found that the adsorption of $\\mathrm{O}_{2}$ on isolated Sb atomic sites is end-on type, which promotes formation of $\\mathsf{S}\\mathsf{b}{-}\\mu$ -peroxide (Sb-OOH), leading to an efficient $2\\mathrm{e}^{-}$ ORR pathway for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. More importantly, the Sb sites also induce highly concentrated holes at the neighbouring melem units, promoting the $4\\mathrm{e}^{-}$ WOR. The concept of using SAC to simultaneously boost reduction and oxidation reactions shall provide a design guide to develop more advanced photocatalytic systems for extensive applications. \n\n# Results \n\nPhotocatalytic $\\mathbf{H}_{2}\\mathbf{O}_{2}$ production on Sb-SAPC. The Sb-SAPC was prepared by a wet chemical method using ${\\mathrm{NaSbF}}_{6}$ and melamine as the precursor (Supplementary Fig. 1). Control samples including pristine polymetric carbon nitride (PCN) and $\\mathrm{Na^{+}}$ incorporated PCNs, were also prepared as references. According to the amount of metal salt added $\\langle x{=}0.5$ , 1, 3, 5, 10, 15 or 20 mmol of NaF or $\\mathrm{NaSbF}_{6})$ into $_{4\\mathrm{g}}$ of melamine, the samples are denoted as PCN_Nax or Sb-SAPCx, respectively. The as-prepared Sb-SAPC reached a quantity of $100\\mathrm{g}$ in one batch, which is very promising for scalable production (Supplementary Fig. 2). \n\nThe photocatalytic performance of Sb-SAPC for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production was assessed in a water and oxygen mixture without presence of any sacrificial agents under visible light illumination. As shown in Supplementary Fig. 3, Sb-SAPC15 shows the highest $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate $(12.4\\mathrm{mgl^{-1}}$ in $120\\mathrm{min}$ ) among the samples, which is about 248 times higher than pristine PCN $(0.05\\mathrm{mgl^{-1}}$ in $120\\mathrm{min}$ ). The surface area of Sb-SAPC15 $(1.89\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , Supplementary Fig. 4) is only about $1/7.78$ of pristine PCN $\\left(14.7\\mathrm{m}^{2}\\mathrm{g}^{-1}\\right)$ , indicating that the activity per area enhancement induced by introducing Sb into PCN is increased by more than 1,900-fold as compared to pristine PCN. After we optimized the reaction conditions (Supplementary Figs. 5 and $6)^{19}$ , the action spectra (Fig. 1c) for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production were measured. The $\\Phi\\mathrm{AQY}$ of Sb-SAPC15 at $420\\mathrm{nm}$ was determined to be $17.6\\%$ , which is twice of the most efficient photocatalyst (RF-resin, Supplementary Table 1) for non-sacrificial $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production16. The solar-to-chemical conversion efficiency of Sb-SAPC15 reached as high as $0.61\\%$ (Fig. 1d), comparable with the most efficient water splitting photocatalyst (roughly $0.8\\%)^{25}$ . The Sb-SAPC15 displayed negligible photocatalytic activity for the hydrogen evolution reaction (Fig. 1e). Furthermore, by comparing the photocatalytic products at two different reaction conditions (with and without $\\mathbf{O}_{2})$ , the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is clearly produced via the $2\\mathrm{e^{-}}$ ORR (no $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was detected in the photocatalytic system without $\\mathrm{O}_{2},$ Fig. 1e). Besides activity, more than $95\\%$ of the initial activity (Sb-SAPC15) could be maintained after five consecutive photocatalytic runs indicating good stability (Supplementary Fig. 7a). Reproducibilities of Sb-SAPC15 (five different batches) were also excellent for AQY and solar-to-chemical conversion measurements (Supplementary Fig. $^{7{\\mathrm{b}},{\\mathrm{c}}^{\\cdot}}$ ). The long-term stability and potential for scalable photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production using the Sb-SAPC photocatalyst were demonstrated in a fixed bed reactor (Supplementary Fig. 8). \n\nTo study the overall reaction for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production, the half redox reactions on Sb-SAPC15 were separately investigated as follows: Sb-SAPC15 in a 2-propanol aqueous solution (2-propanol as an electron donor, $10\\%\\ \\mathrm{v/v}$ with saturated $\\mathrm{~O}_{2}$ (Supplementary Fig. 9) and in a $\\mathrm{NaIO}_{3}$ aqueous solution $\\left({\\mathrm{NaIO}}_{3}\\right.$ as an electron acceptor) with $\\mathrm{N}_{2}$ (Fig. 1f and Supplementary Fig. 10), respectively, under visible light irradiation, which confirm that the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is indeed produced via the ORR on Sb-SAPC15. Isotope experiments16 (Supplementary Fig. 11) were further performed to verify the $4\\mathrm{e}^{-}$ WOR mechanism, in which Sb-SAPC15 in $\\mathrm{H}_{2}^{16}\\mathrm{O}$ and $^{18}{\\bf O}_{2}$ gas was irradiated for 6, 24 and $72\\mathrm{h}$ . $\\mathrm{Fe}^{3+}$ and high concentration $\\mathrm{H^{+}}$ were added into the reaction system to decompose $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to release $\\mathrm{O}_{2},$ and the evolved gas was analysed by gas chromatography–mass spectrometry. The gaseous product obtained after $6\\mathrm{h}$ reaction exhibited a strong $^{18}\\mathrm{O}_{2}\\left(m/z\\right)$ peak $(94.5\\%)$ and a weak $^{16}\\mathrm{O}_{2}$ $(m/z)$ peak $(25.2\\%)$ , showing that $\\mathrm{H}_{2}^{18}\\mathrm{O}_{2}$ was produced by $\\mathrm{O}_{2}$ reduction at the initial stage of the reaction. The gaseous product obtained with the increasing reaction time showed a decreased intensity of the $^{18}\\mathrm{O}_{2}$ peak ( $24\\ensuremath{\\mathrm{h}}55.7\\%$ ; $72\\mathrm{h}$ $45.5\\%$ ) and an increased intensity of the $^{16}{\\bf O}_{2}$ peak (24 h $32.5\\%$ ; $72\\mathrm{h}~45.5\\%\\mathrm{,}$ ), indicating that the oxygen generated by WOR gradually participated in the ORR process16. \n\nTo quantitatively reveal the relationship between the WOR and ORR, a low-concentration electron acceptor $(0.1\\mathrm{mM\\Ag^{+}})$ was added into the PCN and Sb-SAPC system in the absence of $\\mathrm{O}_{2}$ . In this case, $\\mathrm{H}_{2}\\mathrm{O}_{2}$ can only be produced via the reduction of $\\mathrm{O}_{2}$ generated from water oxidation. PCN showed no photocatalytic activity in this condition, while Sb-SAPC gradually produced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in a certain time interval. After that, the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentration stayed constant at roughly $1.0\\mathrm{mgl^{-1}}$ no matter how much catalyst was used (Fig. 1g). The quantitative relationship between the amount of added $\\mathrm{Ag^{+}}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ produced from WOR is discussed in Supplementary Note 1. An isotope experiment using $\\mathrm{H}_{2}^{18}\\mathrm{O}$ was also conducted to confirm that the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generated in the system was indeed derived from the $\\mathrm{O}_{2}$ produced by the $4\\mathrm{e}^{-}$ WOR process (Supplementary Fig. 12). The intensity of the $^{18}{\\bf O}_{2}$ peak $(m/z=36)$ gradually increased with increasing reaction time, indicating that $\\mathrm{H}_{2}^{18}\\mathrm{O}_{2}$ originated from the $^{18}{\\bf O}_{2}$ generated by WOR. Therefore, the $\\mathrm{O}_{2}$ generated from WOR in the Sb-SAPC system was rapidly consumed by the $2\\mathrm{e^{-}}$ ORR process to produce $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . \n\nCharacterization of Sb-SAPC. To understand the superb photocatalytic performance of Sb-SAPC for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production, the catalyst synthesis process (Supplementary Figs. 13–17 and Supplementary Note 2) and the structural characteristics of the as-synthesized catalysts were carefully investigated. As revealed in the $\\zeta$ -potential measurements, negative surface charges appeared on the as-prepared Sb-SAPCs to neutralize the positive charges induced by the incorporated Na and Sb cations (Supplementary Fig. 18). The crystalline structures of Sb-SAPCx show no obvious changes compared to the pristine PCN, as evidenced in the X-ray diffraction patterns and high-resolution transmission electron microscopy (HRTEM) images (Supplementary Note 3 and Supplementary Figs. 19 and 20). As a powerful tool for visualizing individual heavy atoms, high-angle annular dark-field–scanning transmission electron microscopy (HAADF–STEM) was used to further examine the morphology and elemental distribution. The Sb-SAPC15 is composed of aggregated two-dimensional nanosheets, on which Sb and Na elements are homogeneously distributed (Supplementary Fig. 21). For Sb-SAPC0.5, 1, 3, 5, 10 and 15, Supplementary Fig. 22 and Fig. 2a show that the bright spots with high density were uniformly dispersed over the entire carbon nitride matrix. Electron energy loss spectroscopy (EELS) (Fig. 2b and Supplementary Fig. 23) measurement revealed the bright spots corresponding to Sb atoms. The size distribution as displayed in Fig. 2a shows that $99.6\\%$ of Sb species are less than $0.2\\mathrm{nm}$ , demonstrating that Sb exists exclusively as isolated single atoms40. The mass ratio of Sb species in Sb-SAPC15 $(10.9\\mathrm{wt\\%}$ , Supplementary Table 2) is considerably larger than that of the noble or transition metal single atom species in many reported SACs. \n\n![](images/7fe25d0c7892f8acfc78a2b8c177e84a16cc63e1466be399ed1236b3499d5dbe.jpg) \nFig. 2 | Characterization of Sb-SAPC. a, High-magnification HAADF–STEM image of Sb-SAPC15. The inset is the size distribution of the bright spots. Scale bar, $2{\\mathsf{n m}}$ . b, EELS spectrum of Sb-SAPC15. c–e, High-resolution C 1s (c) and N 1s XPS spectra $(\\blacktriangleleft)$ of PCN (up) and Sb-SAPC15 (down) and Sb 3d XPS spectrum (e) of Sb-SAPC15. f,g, Sb K-edge X-ray absorption near edge structure (f) and Fourier transform–EXAFS spectra $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ of the Sb foil, ${\\mathsf{S b}}_{2}{\\mathsf{O}}_{5}$ and Sb-SAPC15. h, Fitting of the EXAFS data of the Sb-SAPC15 based on the model obtained from DFT optimization. The insets show optimized molecular models based on DFT for EXAFS fitting. R indicates the radial distance in Å. \n\nTo investigate the interaction between the isolated Sb atoms and the PCN skeleton, Fourier transform–infrared and $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) measurements were conducted. \n\nThe spectra of PCN, PCN_Na15 and Sb-SAPC15 show no obvious difference in the wavenumber ranges of 700–900 and $^{1,200-}$ $1{,}600\\mathsf{c m}^{-1}$ (Supplementary Fig. 24), indicating that the skeleton of PCN hardly changed before and after incorporation of Na and Sb ions (Supplementary Table 3 and Supplementary Note 4). All fluoride elements have been removed during the calcination process (Supplementary Figs. 25 and 26). In the high-resolution C 1s spectrum of pristine PCN (Fig. 2c), the typical components at around 287.6 and $284.6\\mathrm{eV}$ can be indexed as the $\\mathrm{C}{=}\\mathrm{N}$ and adventitious carbon, respectively. It is important to note that a new nitrogen peak (N 1s) emerges at $398.1\\mathrm{eV}$ in the spectrum of Sb-SAPC15 (Fig. 2d), which can be assigned to the chemical bond of Sb-N. The binding energy of Sb 3d for Sb-SAPC15 (Sb $3d_{3/2}$ at $539.5\\mathrm{eV}$ and Sb $3d_{5/2}$ at $530.2\\mathrm{eV})$ is close to that for ${\\mathrm{Sb}}_{2}{\\mathrm{O}}_{3}$ (Sb $3d_{3/2}$ at $539.8\\mathrm{eV}$ and Sb $3d_{5/2}$ at $530.5\\mathrm{eV})^{41}$ , indicating that the oxidation state of Sb in Sb-SAPC15 is close to $+3$ (Fig. 2e). \n\nThe oxidation state of the Sb atoms in Sb-SAPC15 was further determined by the position of the absorption edge in the Sb K-edge X-ray absorption near edge structure (Fig. 2f). The absorption edge for Sb-SAPC15 is $2.2\\mathrm{eV}$ higher than that for the $\\mathsf{S}\\mathsf{b}^{\\mathrm{{0}}}$ foil, and $1.5\\mathrm{eV}$ lower than that for $S{\\mathrm{b}}^{+5}{}_{2}\\mathrm{O}_{5},$ , suggesting a valence state of around $+3$ for the Sb atoms in Sb-SAPC15. A Fourier transform– extended X-ray absorption fine structure (FT–EXAFS) spectrum (Fig. $2\\mathrm{g})$ ) obtained from $k^{3}$ -weighted $k$ -space (Supplementary Fig. 27) of Sb-SAPC15 shows only one peak at about $1.{\\overset{\\cdot}{5}}3{\\overset{\\circ}{\\mathrm{A}}},$ and no $\\mathrm{Sb-}$ Sb bond at $2.71\\mathring\\mathrm{A}$ can be detected, indicating that the Sb sites in Sb-SAPC15 are atomically dispersed. The coordination structure of the Sb atoms was estimated by fitting the EXAFS spectrum of Sb-SAPC15 using Artemis $(\\mathrm{v}.0.9.25)^{42}$ (Fig. 2h and Supplementary Table 4) based on the density functional theory (DFT) optimization result from the carbon nitride cluster with single Sb sites (Melem_ $3\\mathrm{Sb}3^{+}$ , Supplementary Fig. 28c). The best fitting result for the first shell shows that each Sb atom is coordinated with 3.3N atoms on average and can be fitted well with the optimized DFT model (Supplementary Fig. 28d), further indicating that the Sb species are atomically dispersed, consistent with the HAADF–STEM results (Fig. 2a and Supplementary Fig. 22). It is noteworthy that postcharacterizations of Sb-SAPC15 after continuous reaction for 5 days are almost the same as the fresh ones (Supplementary Fig. 29), confirming the excellent stability of Sb-SAPC (Supplementary Fig. 7 and Supplementary Note 5). \n\nProperties of Sb-SAPC and photocatalytic mechanism. The optical properties and the band diagram of Sb-SAPC were investigated. The introduction of Sb and Na species slightly narrowed the bandgap $(2.77\\mathrm{eV}$ for PCN and $2.63\\mathrm{eV}$ for Sb-SAPC15), and notably improved the light absorbance (Fig. 1c and Supplementary Fig. 30a,b). Confirmed by valence-band XPS and Mott–Schottky measurements, the introduction of Na and/or Sb species slightly shifted the conduction band minimum from roughly $-1.3\\mathrm{eV}$ (versus NHE) to roughly $-1.2\\mathrm{eV}$ while rarely influencing the valence band maximum (roughly $1.45\\mathrm{eV}\\cdotp$ ) (Supplementary Fig. $30\\mathrm{c-g}$ and Supplementary Note 6). \n\nThe charge separation and recombination process were monitored by steady-state photoluminescence emission spectroscopy (Supplementary Fig. 31a)43. The radiative recombination of excited charge pairs was clearly observed in pristine PCN while the photoluminescence intensity was markedly reduced with addition of Sb and/or Na, indicating that the radiative recombination was greatly retarded after addition of Sb and/or Na species. This phenomenon is consistent with the highest photocatalytic activity of Sb-SAPC15. In addition, the onset of photoluminescence wavelength gradually red-shifted, which is also consistent with the narrowed bandgap. The facilitated charge migration in Sb-SAPC15 could be further verified by the enhanced photocurrent density (Supplementary Fig. 31c) and decreased electrochemical impedance in the Nyquist plots (Supplementary Fig. $^{31\\mathrm{b},\\mathrm{c}},$ ). It is noteworthy that the substantially shortened lifetime of photoluminescence (Supplementary Fig. 31d) could be attributed to the generated deeply trapped sites, which have been proved to facilitate the ORR process43,44. \n\nTo further investigate whether the deeply trapped sites in Sb-SAPC15 could facilitate both ORR and oxygen evolution reaction (OER), time-resolved–infrared absorption spectroscopy was performed to monitor the charge carrier dynamics and the reactivities of Sb-SAPC15 for ORR and WOR on the microsecond time-scale43,45. To probe the charge-transfer dynamics from electron to $\\mathrm{O}_{2}$ and hole to ${\\mathrm{H}}_{2}\\mathrm{O};$ , the decay kinetics of deeply trapped electrons (at $5,000{\\mathsf{c m}}^{-1},$ ) of PCN, PCN_Na15 and Sb-SAPC15 were investigated (Supplementary Fig. 32 and Fig. 3a) and compared under ${\\mathrm{N}}_{2},$ $\\mathrm{~O}_{2}$ and $\\mathrm{H}_{2}\\mathrm{O}$ atmospheres (Fig. 3b). The decay of the deeply trapped electrons at $5,000{\\mathsf{c m}}^{-1}$ on pristine PCN accelerated very slightly (Fig. 3b) in $\\mathrm{O}_{2}$ compared to that in $\\mathrm{N}_{2}$ ( $\\mathrm{\\Delta}\\cdot\\mathrm{\\Delta}I_{\\mathrm{O_{2}}}/I_{\\mathrm{N_{2}}}{=}0.83\\$ . The decay on PCN_Na15 showed a little acceleratioInO2i/nI $\\mathrm{O}_{2}$ compared to that in $\\mathrm{N}_{2}$ $\\mathrm{\\prime}}_{I_{\\mathrm{O_{2}}}}/I_{\\mathrm{N_{2}}}{=}0.66)$ , indicating that introduction of Na could generate reactive sites for charge transfer of trapped electrons to $\\mathrm{~O}_{2}$ (refs. $^{43,44}$ ). When Sb was introduced into the catalyst, we observed notable decay of the deeply trapped electrons on Sb-SAPC15 in $\\mathrm{~O}_{2}$ as compared to that in $\\mathrm{N}_{2}$ ( $\\mathrm{\\Delta}I_{\\mathrm{O_{2}}}/I_{\\mathrm{N_{2}}}{=}0.46)$ . This indicates that the reactant $\\mathrm{O}_{2}$ would preferentiaIlOl2y/IreN2act with the deeply trapped electrons that were induced by the Sb sites. In the case of holes, the decay on pristine PCN and PCN_Na15 changed very little in $\\mathrm{H}_{2}\\mathrm{O}$ environment compared to that in $\\mathrm{N}_{2}$ $\\mathrm{'}I_{\\mathrm{H}_{2}\\mathrm{O}}/I_{\\mathrm{N}_{2}}{=}0.86$ for PCN and $I_{\\mathrm{H}_{2}\\mathrm{O}}/I_{\\mathrm{N}_{2}}{=}1.09$ for PCN_Na15), indicatIiHn2gOt/IhNa2t the photogenerated IhHo2leOs/Ib2arely transferred to $\\mathrm{H}_{2}\\mathrm{O}$ On the contrary, the decay on Sb-SAPC15 was substantially retarded in $\\mathrm{H}_{2}\\mathrm{O}$ compared to that in $\\mathrm{N}_{2}\\left(I_{\\mathrm{H}_{2}\\mathrm{O}}/I_{\\mathrm{N}_{2}}{=}1.92\\right)$ , suggesting that the photogenerated holes could readIilHy2 tOr/aInN2sfer to $\\mathrm{H}_{2}\\mathrm{O}$ molecules: hole-consuming reaction by $\\mathrm{H}_{2}\\mathrm{O}$ reduced the number of surviving holes in the catalyst and hence elongated the lifetime of electrons45. Additionally, an isotopic experiment (Supplementary Fig. 33) to simulate the real system (without ${\\mathrm{Ag}}^{+}$ or $\\mathrm{NaIO}_{3}.$ ) was conducted to verify the as-proposed mechanism of WOR by using $^{16}\\mathrm{O}_{2}$ (as an electron acceptor) and $\\mathrm{H}_{2}^{18}\\mathrm{O}$ (as an electron donor). As shown in Supplementary Fig. 33b, the signal of $^{18}{\\bf O}_{2}$ $(m/z=36)$ ) could be detected after photocatalytic reaction for $^\\mathrm{1h}$ , indicating that the OER indeed occurred in the real reaction system. It is important to note that this signal could not be detected in absence of Sb-SAPC15 or light irradiation, indicating that the photogenerated holes participated in the WOR to generate $^{18}{\\bf O}_{2}$ . The highly active holes for OER could also be confirmed by rotating ring disc electrode measurements (Supplementary Fig. 34). A clear signal of $\\mathrm{O}_{2}$ reduction to $\\mathrm{H}_{2}\\mathrm{O}$ was detected by the ring disc, verifying $\\mathrm{O}_{2}$ generation on the Sb-SAPC surface via WOR. These results confirm that the deeply trapped electrons and the corresponding holes in Sb-SAPC15 are the major contributors to the ORR and OER processes (Supplementary Note 7), respectively, leading to a notably promoted photocatalytic activity of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. \n\nThe DFT calculation also shows how the Sb and Na species promote the inner and interlayer charge transfer in Sb-SAPC (Supplementary Figs. 35 and 36). Four periodic models including graphitic carbon nitride (GCN), sodium incorporated graphitic carbon nitride (Na-GCN), antimony incorporated graphitic carbon nitride (Sb-GCN) and sodium and antimony co-incorporated graphitic carbon nitride (NaSb-GCN) were optimized, and the Bader charges of each layer in different models are presented in Supplementary Fig. 35 (refs. $^{43,46},$ . The Bader charge difference between each adjacent layers of pristine GCN is extremely small $(|\\Delta q|$ roughly $0.004\\mathrm{e}^{-})$ , suggesting very weak adiabatic coupling between interlayers in $\\mathrm{GCN^{45,46}}$ , leading to poor interlayer charge transfer. Both Na-GCN and Sb-GCN display a relatively large number of electrons accumulating on the second and fourth layer (roughly $0.1\\mathrm{e}^{-}$ of layer charge)46,47. As a result, the Na-GCN and Sb-GCN exhibit a high value of charge difference between the adjacent layers $(|\\Delta q|$ roughly $0.3\\mathrm{e}^{-}\\mathrm{\\check{\\}}$ ), indicating that adiabatic coupling has been notably boosted by introducing Na or Sb. The copresence of Na and Sb atoms makes the electron distribution more balanced between the layers (Supplementary Fig. 35l). In other words, when both Na and Sb are present in the carbon nitride structure, the Na- and Sb-induced electron density polarization can be counterbalanced to lower the $|\\Delta q|$ (roughly $0.05\\mathrm{e}^{-}\\dot{,}$ ) and at the same time the distance for adiabatic coupling is notably increased $(|\\Delta q|$ between the first and second layer and between the third and fourth layer are significantly increased). This indicates that the charge transfer between the interlayers in carbon nitride incorporated with Sb and Na atoms is better facilitated than in pristine $\\mathrm{GCN^{46,47}}$ . The deformation charge density near surface of NaSb-GCN (Supplementary Fig. 36) reveals a clear pathway from Na to Sb. The Sb on the surface of GCN with weak interlayer bridging shows a larger number of electrons accumulating on the first layer $(-0.0395\\mathrm{e}^{-}$ of layer charge) than the second layer $0.1345\\mathrm{e}^{-}$ of layer charge)46–50. Note that a clear electron accumulation region and an electron depletion region, respectively, are located at the first and second layer while the pristine CN layer (the third layer) can hardly be polarized, indicating that the inner layer charge transfer is substantially improved with incorporation of Sb and Na species48–50. These results show that the electron transfer can be notably promoted by the incorporation of Sb and Na species in GCN, which can explain the higher photocatalytic activities of Sb-SAPC15. \n\n![](images/861436d2b67c6bc4526e81a3e3fc782a5c71f6d41f2acc8c1c414eebe91add84.jpg) \nFig. 3 | Excitation properties and OER/ORR reactivities of Sb-SAPC15. a, The systematic diagram of transition absorption after excitation as the probe for OER/ORR (details for the pulse light $420\\mathsf{n m}$ , 6 ns, $5\\mathsf{m}\\mathsf{J}$ and $0.2H z$ ). b, The comparison of transient absorption decay among PCN, PCN_Na15 and Sb-SAPC15 at $5,000{\\mathsf{c m}}^{-1}$ under $\\ensuremath{\\mathsf{N}}_{2},\\ensuremath{\\mathsf{O}}_{2}$ and $H_{2}O$ atmosphere (20 torr). The absorption intensities at the time point of 1 ms was used as the benchmark for investigating how deeply trapped electrons/holes interact with $0_{2}/\\mathsf{H}_{2}\\mathsf{O}$ . c, Total density of states (TDOS), partial density of states (PDOS) and overlapped density of states (ODOS) of Melem_ $3563^{+}$ combined with the isosurface of LUMO (isovalue is 0.05). HOMO, highest occupied molecular orbital. d, Experimental Raman spectra recorded during photoreaction in a 2-propanol aqueous solution with saturated oxygen. Spectrum a–d, PCN, Sb-SAPC1, Sb-SAPC5 and Sb-SAPC15 in $10\\%$ (v/v) 2-propanol aqueous solution, respectively. Spectrum e, Sb-SAPC15 in pure water. CB and VB indicate the conduction band and valence band, respectively. \n\nThe excited properties of Sb-SAPC were further studied by time-dependent DFT (TDDFT) to understand the correlation between structure and photocatalytic activity using a monolayer cluster model51,52. The possible simulated excited states that contributed to photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production (corresponding to the spectra from 420 to $470\\mathrm{nm}$ ) were confirmed by comparing the action spectra (Fig. 1c and Supplementary Note 6) with the simulated ones (Supplementary Fig. 37a–c). On the basis of the action spectra and the photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production activities, the ES1-16 of Melem_3, the excited states 1–15 of Melem_ $3\\mathrm{Na^{+}}$ and the excited states 1–26 of Melem_ $3\\mathrm{Sb}3^{+}$ are highlighted in the distribution heatmap of photogenerated electrons and holes (Supplementary Fig. 37d–i)53. On the one hand, most of electrons accumulated at the Sb sites (excited states 1–26, Supplementary Table 5), a ligand-to-metal charge transfer from neighbouring melem units to Sb, in Melem_ $3\\mathrm{Sb}3^{+}$ with high density (roughly $20\\mathrm{-}80\\%$ ), while most of the states (excited states 1–16 for Melem_3, Supplementary Table 6; excited states 1–15 for Melem_ $3\\mathrm{Na^{+}};$ , Supplementary Table 7) show averagely distributed electrons at the C sites $(<10\\%)$ in Melem_3 and Melem_ $3\\mathrm{{Na}^{+}}$ (refs. $^{51-53^{\\cdot}}$ ). Note that the photogenerated electrons and holes barely locate at the Na atoms, indicating that the coordinated Na species on the catalyst’s surface could not serve as the active sites for the photocatalytic reaction. Additionally, a comprehensive investigation of charge separation and delocalization of holes and electrons were conducted by using Melem_6, Melem_ $6\\mathrm{Na^{+}}$ and Melem_ $65\\mathsf{b}3^{+}$ as models (Supplementary Figs. 38–40 and Supplementary Note 7). The substantially improved separation of electron–hole pairs and highly concentrated electrons/ holes may effectively promote both photocatalytic ORR and WOR in Sb-SAPC15 by introducing atomic Sb sites. \n\nThe influence of Sb single atoms on the photo-redox reactions was further studied by analysing the contributions of molecular orbital to holes and electrons from ES1 to ES26 of Melem_ $3\\S\\ensuremath{\\mathrm{b}}3^{+}$ (Supplementary Table 5). Several molecular orbitals, whose energetic levels are equal to or lower than the highest occupied molecular orbital, all contribute to holes (ranging from 0 to roughly $60\\%$ ), while almost all electrons are contributed by the lowest occupied molecular orbital (LUMO) (MO155) in most of transitions. This observation indicates that the electronic configuration of LUMO can almost represent the photogenerated electronic configuration. The result from partial DOS (PDOS) of Melem_ $3\\mathrm{Sb}3^{+}$ shows that a new molecular orbital mainly contributed by electrons from Sb forms the LUMO. It is important to note that this molecular orbital exhibits a slightly lower energetic level than the molecular orbital contributed by C and N, which is in accordance with the slightly shifted conduction band minimum of Sb-SAPC15 (ref. 22). Combined with the simulated results of charge separation, isosurface of LUMO of Melem_ $3\\mathrm{Sb}3^{+}$ reveals that most of the electrons $(>75\\%)$ are concentrated at the single Sb sites with ideal electronic configuration for adsorption of electrophilic oxygen (Fig. 3c). To study the ORR mechanism on Sb-SAPC, rotating disc electrode analysis was performed to investigate the number of electrons $(n)$ transferred in the ORR process (Supplementary Fig. 41). The estimated $n$ value is close to 2 for Sb-SAPC15 in both dark and light irradiation conditions. The preferred $2e^{-}$ ORR pathway on Sb-SAPC can be further supported by DFT calculation using the computational hydrogen electrode method. As shown in Supplementary Fig. 42a, the calculated $\\Delta G_{\\mathrm{{*_{OOH}}}}$ is $4.53\\mathrm{eV}$ $\\mathrm{{\\dot{U}}}=0\\mathrm{{V}}$ versus the reversible hydrogen electrode (RHE)), which is smaller than $4.59\\mathrm{eV}$ of $\\Delta G_{\\mathrm{*o}},$ a crucial intermediate in $4\\mathrm{e}^{-}\\mathrm{ORR}^{36}$ . The large energetic barrier towards forming $^*\\mathrm{O}$ would suppress the $4\\mathrm{e}^{-}$ ORR process. For a $2\\mathrm{e^{-}}$ ORR catalyst, the adsorption energy of $^{*}\\mathrm{OOH}$ should be larger than the thermoneutral value at the equilibrium potential $\\mathrm{\\Delta\\mathrm{U}=0.7V}$ versus RHE), corresponding to $\\Delta G_{\\mathrm{{*_{OOH}}}}$ of $3.52\\mathrm{eV.}$ The calculated $\\Delta G_{\\mathrm{{*_{OOH}}}}$ is $3.83\\mathrm{eV}$ 1 $\\mathrm{\\DeltaU=0.7V}$ versus RHE), suggesting that the ORR on single atom Sb may follow a $2\\mathrm{e^{-}}$ pathway (Supplementary Fig. 42b). This shows that the difference between $^{*}\\mathrm{OH}$ and $^{*}\\mathrm{O}$ is as high as $3.742\\mathrm{eV},$ indicating that a considerably large energetic barrier needs to be overcome for the $4\\mathrm{e}^{-}$ OER process. In this case, the Sb site should not function as an effective site to catalyse $4\\mathrm{e}^{-}$ OER. It is noteworthy that the calculated $\\Delta G_{\\mathrm{*_{H}}}$ on Sb-SAPC15 is substantially larger $(0.937\\mathrm{eV})$ than that on Pt (111) (Supplementary Fig. 43), suggesting that hydrogen evolution reaction on Sb-SAPC15 is energetically unfavourable, matching well with the experimental result (Fig. 1e). \n\nTo identify the intermediate in the photocatalytic process, Raman spectroscopy measurements (Fig. 3d) were performed under operando conditions. For PCN, after reaction with 2-propanol as an electron donor under visible light irradiation, a new band appears at $896\\mathrm{cm}^{-1}$ , which can be assigned to the $C{\\mathrm{-}}\\mathrm{O}$ vibration and O–O stretching on the melem12. While for Sb-SAPCs, a new absorption band at $855\\mathrm{cm}^{-1}$ increases with Sb content in the sample, which can be assigned to the $_{\\mathrm{O-O}}$ stretching mode of a Sb-OOH species with end-on adsorption configuration54,55. This relative chemical shift between $\\mathrm{O}_{2}$ end-on/side-on adsorption configuration has been also confirmed by DFT calculations (Supplementary Fig. 44 and Supplementary Note 8). It is noteworthy that Sb-OOH exists even without addition of electron donor, indicating that formation of Sb-OOH, rather than the side-on configuration, dominates in the photocatalytic process on Sb-SAPCs. The end-on adsorption shall notably suppress the $4\\mathrm{e}^{-}$ ORR, leading to a high selectivity of the $2e^{-}$ process29,30. Additionally, electron spin resonance signal of 5,5-dimethyl-1-pyrroline $N$ -oxide- $\\cdot\\mathrm{O}_{2}^{-}$ $(\\mathrm{DMPO–{\\cdot}O_{2}{'}})$ could be hardly observed in the Sb-SAPC system (Supplementary Fig. 45). Since $\\cdot\\mathrm{O_{2}}^{-}$ is an important intermediate in the stepwise $1\\mathrm{e}^{-}$ pathway (equation (6)) during formation of 1–4 endoperoxide, the invisible signal of $\\mathrm{DMPO{-}{\\cdot}O_{2}}^{-}$ in the Sb-SAPC system demonstrates rapid reduction of $\\mathrm{O}_{2}$ on Sb-SAPC to generate $\\mathrm{H}_{2}\\mathrm{O}_{2}$ via a $2\\mathrm{e^{-}}$ ORR pathway22,23,55. \n\n$$\n\\mathrm{O}_{2}+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\cdot\\mathrm{OOH}\\left(-0.046\\mathrm{V}\\mathrm{versusNHE}\\right)\n$$ \n\nOn the basis of the above characterizations and analyses, the reaction mechanism (Fig. 4) of Sb-SAPC for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production is proposed as follows: first, efficient charge separation occurred on Sb-SAPC under visible light irradiation, generating photoexcited electrons and holes for ORR and WOR, respectively. Then, water molecules were oxidized to evolve $\\mathrm{~O}_{2}$ by photogenerated holes localized at the $\\mathrm{\\DeltaN}$ atoms near the single Sb atoms. Simultaneously, $\\mathrm{~O}_{2}$ molecules dissolved in water and generated from the WOR both participated in the ORR process to produce $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . It is worth noting that the efficient charge separation, ideal single atomic sites for end-on type $\\mathrm{O}_{2}$ adsorption and close spatial distribution of active sites boost both the $2\\mathrm{e^{-}}$ ORR and $4\\mathrm{e}^{-}$ WOR for efficient $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. \n\n# Conclusions \n\nIn summary, we have reported a well-defined, highly active, selective and photochemically robust single Sb atom photocatalyst for non-sacrificial $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in a water and oxygen mixture under visible light irradiation. The single Sb sites are able to accumulate electrons, which act as the photoreduction sites for $\\mathrm{~O}_{2}$ via a $2e^{-}$ ORR pathway. Simultaneously, the accumulated holes at the $\\mathrm{\\DeltaN}$ atoms of the melem units neighbouring to the Sb sites accelerate the water oxidation kinetics. The collaborative effect between the single atom sites and the support shall open up a strategy for designing various SACs for a variety of photocatalytic reactions in energy conversion and environmental remediation. \n\n![](images/e71fe9480e79457904376863afe8390fca2be6df4348d06f493e26587c141617.jpg) \nFig. 4 | Mechanism of photocatalytic ${\\sf H}_{2}{\\sf O}_{2}$ production. The white, grey, blue, red and magenta spheres refer to hydrogen, carbon, nitrogen, oxygen and Sb atoms, respectively. After shining visible light, the photogenerated electrons are localized at the Sb sites (with a blue glow), while the photogenerated holes are localized at the N atoms at the melem units (with a red glow). Subsequently, the dissolved $\\mathsf{O}_{2}$ molecules are adsorbed (orange arrows) onto the Sb sites and then get reduced (blue arrows) via a $2\\mathsf{e}^{-}$ transfer pathway through forming an electron $\\mu$ -peroxide as the intermediate. Simultaneously, water molecules are oxidized (pink arrows) to generate $\\mathsf{O}_{2}$ by the highly concentrated holes on the melem units. \n\n# Methods \n\nPreparation of photocatalysts. Unless otherwise stated, the purities of all reagents for photocatalyst preparation and for photoelectrochemical measurements are above the analytical grade. The pristine PCN and PCN_Na15 were prepared according to the reported methods19. The Sb-SAPCs were prepared by a bottom-up method as follows: a certain amount of $\\mathrm{NaSbF}_{6}$ (HuNan HuaJing Powdery Material, $0.5\\mathrm{mmol}$ , 1 mmol, 3, 5, 10, 15 and $20\\mathrm{mmol}\\cdot$ was dissolved in $30\\mathrm{ml}$ of ethanol under sonication for $60\\mathrm{{min}}$ at $60^{\\circ}\\mathrm{C},$ followed by adding $_{4\\mathrm{g}}$ melamine (Wako Pure Chemical Industries). The solvent in the solution was removed by combination of rotatory evaporator and vacuum oven. The obtained white powder was transferred into a tube furnace. To ensure that oxygen was not present during thermal treatment, the tube furnace was first vacuumed to $^{<1}$ torr before switching on the $\\mathrm{N}_{2}$ gas flow. This process was repeated three times, and then $50\\mathrm{ml}\\mathrm{min}^{-1}\\mathrm{N}_{2}$ gas flow was maintained for $30\\mathrm{min}$ before heat treatment. During the synthesis process (including heating and cooling), the system was pressurized by $\\Nu_{2}$ flow so that oxygen could not influence the synthesis. The temperature of the furnace was increased from $25^{\\circ}\\mathrm{C}$ to $560^{\\circ}\\mathrm{C}$ at a ramp rate of $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ in $\\Nu_{2}$ atmosphere then kept at $560^{\\circ}\\mathrm{C}$ for 4 h. After heat treatment, the furnace was cooled down naturally to $25^{\\circ}\\mathrm{C}$ lasting for at least $^{8\\mathrm{h}}$ with continuous $\\Nu_{2}$ flowing. \n\nPhotocatalytic reaction towards $\\mathbf{H}_{2}\\mathbf{O}_{2}$ production. Here, $100\\mathrm{mg}$ of photocatalyst was added to $50\\mathrm{ml}$ of deionized water in a borosilicate glass bottle (maximum diameter, $\\varphi60\\mathrm{mm}$ ; capacity $\\mathrm{100ml}$ ), and the bottle was sealed with a rubber septum cap. The catalyst was dispersed by ultrasonication for $15\\mathrm{min}$ , and $\\mathrm{~O}_{2}$ was bubbled through the solution for $30\\mathrm{min}$ . The bottle was kept in a temperature-controlled air bath at $25\\pm0.5^{\\circ}\\mathrm{C}$ with wind flow and was irradiated at $\\lambda>420\\mathrm{nm}$ using a 300 W Xe lamp (PXE-500, USHIO Inc.) under magnetic stirring. To study the WOR, $50\\mathrm{mg}$ of photocatalyst was added into $\\mathrm{NaIO}_{3}$ (0.1 M, $50\\mathrm{ml}$ ) solution in a borosilicate glass bottle ( $\\operatorname{\\rho60}\\operatorname{mm};$ capacity $\\boldsymbol{100}\\mathrm{ml}$ ). After completely removing $\\mathrm{O}_{2}$ from the reaction system, the bottle was irradiated by a 300 W Xenon Lamp. The light intensity of visible light and infrared light $(I_{>400})$ after passing an ultraviolet (UV) cut filter $\\lambda>400\\mathrm{nm}$ was first measured. Then, a glass filter with $\\lambda>500\\mathrm{nm}$ was used to replace the UV cut filter for measuring the light intensity $(I_{>500})$ . The difference between $I_{>400}$ and $I_{>500}$ was used to calibrate the total light intensity. After a certain time interval, the gas was extracted from the bottle and examined by gas chromatography equipped with a thermal conductivity detector. To examine the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production from $\\mathrm{O}_{2}$ generated by WOR, a certain amount of photocatalyst (Sb-SAPC15 200, 100 and $50\\mathrm{mg}$ Pristine $\\operatorname{PCN}200\\operatorname{mg}$ was added into $50\\mathrm{ml}$ of $\\mathrm{NaNO}_{3}$ solution $(\\mathrm{pH7})$ with $\\mathrm{AgNO}_{3}$ ( $\\mathrm{{[0.1mM})}$ . Every hour, $1.5\\mathrm{ml}$ of solution was extracted to acquire the time-dependent $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production without the initial introduction of $\\mathrm{~O}_{2}$ . The amount of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in these experiments was determined by a colorimetric method using PACKTEST (WAK- $\\mathrm{.H}_{2}\\mathrm{O}_{2},$ Kyoritsu Chemical-Check Laboratory, Corp.) equipped with a digital PACKTEST spectrometer (ED723, GL Sciences Inc.). \n\nApparent quantum efficiency analysis. The photocatalytic reaction was carried out in pure deionized water $(30\\mathrm{ml})$ with photocatalyst $\\left(60\\mathrm{mg}\\right)$ and with or without addition of ethanol as an electron donor in a borosilicate glass bottle. After ultrasonication and $\\mathrm{O}_{2}$ bubbling, the bottle was irradiated by an $\\mathrm{Xe}$ lamp for 4 h with magnetic stirring. The incident light was monochromated by band-pass glass filters (Asahi Techno Glass Co.), where the full-width at half-maximum of the light was $11-16\\mathrm{nm}$ . The number of photons that enter the reaction vessel was determined by a 3684 optical power meter (Hioki E.E. Corp.). \n\nDetermination of solar-to-chemical conversion efficiency. Solar-to-chemical conversion efficiency was determined by a PEC-L01 solar simulator (Peccell Technologies, Inc.). The photoreaction was performed in pure deionized water $(100\\mathrm{ml})$ with photocatalyst $(500\\mathrm{mg})$ under an $\\mathrm{~O}_{2}$ atmosphere (1 atm) in a borosilicate glass bottle. A UV cut filter $\\begin{array}{r}{\\langle\\lambda>420\\mathrm{nm},}\\end{array}$ ) was used to avoid decomposition of the formed $\\mathrm{H}_{2}\\mathrm{O}_{2}$ by absorbing UV light12,16,23. The irradiance of the solar simulator was adjusted to the AM1.5 global spectrum12,16,23. The solar-to-chemical conversion efficiency $(\\eta)$ was calculated by equation (7): \n\n$$\n\\eta\\left(\\%\\right)=\\frac{\\Delta G_{\\mathrm{H_{2}O_{2}}}\\times n_{\\mathrm{H_{2}O_{2}}}}{t_{\\mathrm{ir}}\\times S_{\\mathrm{ir}}\\times I_{\\mathrm{AM}}}\\times100\\%.\n$$ \n\nwhere $\\Delta G_{\\mathrm{H_{2}O_{2}}}$ is the free energy for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generation $(117\\mathbf{k})\\mathbf{mol}^{-1},$ ), $n_{\\mathrm{H_{2}O_{2}}}$ is the amountΔoGf $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generated and $t_{\\mathrm{ir}}$ is the irradiation time (s). The overnall2 ir2radiation intensity $(I_{\\mathrm{AM}})$ of the AM1.5 global spectrum $(300-2,500\\mathrm{nm})$ is $1,000\\mathrm{W}\\mathrm{m}^{-2}$ and the irradiation area $(S_{\\mathrm{ir}})$ is $3.14\\times10^{-4}\\mathrm{m}^{2}$ . \n\nInstruments. HRTEM, HAADF–STEM, selected area electron diffraction and energy-dispersive X-ray spectroscopy were performed on a Titan Cubed Themis $G2300$ electron microscope with an accelerating voltage of $300\\mathrm{kV}.$ EELS was conducted using a Quantum ER/965 P detector. The crystalline phases were characterized by a powder X-ray diffraction instrument (MiniFlex II, Rigaku) with CuKα $\\overset{\\cdot}{\\lambda}=\\overset{\\cdot}{1}.5\\overset{\\cdot}{4}18\\overset{\\cdot}{\\mathrm{A}}^{\\cdot}$ ) radiation (cathode voltage $30\\mathrm{kV},$ current $15\\mathrm{mA}$ ). Absorption properties of the powder samples were determined using the diffuse reflection method on a UV-visible light near-infrared spectrometer (UV-2600, Shimadzu) attached to an integral sphere at room temperature. XPS measurements were performed on a Kratos AXIS Nova spectrometer (Shimazu) with a monochromatic Al Kα X-ray source. The binding energy was calibrated by taking the carbon (C) 1s peak of adventitious carbon at $284.6\\mathrm{eV.}$ Valence-band XPS was performed on an ESCALAB 250Xi (Thermo Scientific). The equilibration of Fermi level of the instrument was performed by measuring the VB-XPS of Au metal basis as the reference. The Fermi level of the instrument was equilibrated at $4.5\\mathrm{eV.}$ In this case, the numerical value of the binding energy in the calibrated VB-XPS spectrum is the same as the potential versus standard hydrogen electrode. Electron spin resonance signals of spin-trapped paramagnetic species with 5,5-diemthyl-1-pyrroline $N$ -oxide (DMPO, methanol solution) were recorded with an A300-10/12 spectrometer. Photoluminescence spectroscopy was performed on a FP-8500 spectrofluorometer (JASCO Corporation). The temperature for the photoluminescence measurements was about $25^{\\circ}\\mathrm{C}$ controlled by an air conditioner, which worked 24/7. Time-dependent photoluminescence spectroscopy was conducted on a FS5 fluorescence spectrometer (Edinburgh Instruments). Raman spectroscopy was performed on a Laser Microscopic Confocal Raman Spectrometer (Renishaw inVia) at $785\\mathrm{nm}$ . The pH value of the solution was measured by a pH meter (HORIBA pH meter D-51, Horiba). \n\nThe X-ray absorption spectroscopy for the Sb K-edge was measured at beamline BL01C at the National Synchrotron Radiation Research Center (NSRRC, Hsinchu, Taiwan). The data analysis for the X-ray absorption spectroscopy using IFEFFIT was conducted using the Demeter system. \n\nPhotoelectrochemical characterizations. Photoelectrochemical characterizations were conducted on a conventional three-electrode potentiostat setup connected to an electrochemical analyser (Model 604D, CH Instruments). The fluorine-doped tin oxide (FTO) glass of $1\\times2\\mathrm{cm}$ in size was covered with photocatalyst that was achieved by first mixing a catalyst $(100\\mathrm{mg})$ with ethyl cellulose binder $\\mathrm{(10mg)}$ in ethanol $(6\\mathrm{ml})$ for 1 h and then depositing the final viscous mixture by a doctor blade method, followed by drying at room temperature and further drying at $40^{\\circ}\\mathrm{C}$ overnight in a vacuum oven. The area of the photoelectrode was controlled to be $1\\mathrm{cm}^{2}$ . The photoelectrochemical system consisted of an FTO glass covered by the photocatalyst, a coiled Pt wire and a saturated $\\mathrm{Ag/AgCl/KCl}$ (saturated) electrode as the working, counter and reference electrode, respectively. The photocurrent was collected at $0.8\\mathrm{V}$ versus NHE ( $\\mathrm{.0.6V}$ versus $\\mathrm{Ag/AgCl})$ in a phosphate buffer solution (PBS, pH 7.4). The solution was saturated with $\\mathrm{O}_{2}$ by bubbling $\\mathrm{~O}_{2}$ for $15\\operatorname*{min}{(0.51\\operatorname*{min}^{-1})^{12,56,57}}$ . Electrochemical impedance spectroscopy analysis was performed at a d.c. voltage of $-0.6\\mathrm{V}$ versus $\\mathrm{Ag/AgCl}$ with an a.c. voltage amplitude of $5\\mathrm{mV}$ in a frequency range from $100\\mathrm{kHz}$ to $0.01\\mathrm{Hz}$ . For the Mott–Schottky measurements, similar strategy was performed on FTO glass $(1.5\\times3\\mathrm{cm})$ by the same doctor blade method. The area of the electrode for the Mott–Schottky measurements was controlled to be $0.50\\mathrm{cm}^{2}$ . Mott–Schottky measurements were performed at a potential range from $0.2\\mathrm{V}$ to $-0.6\\mathrm{V}$ versus NHE, with an a.c. voltage amplitude of $5\\mathrm{mV}$ and in a frequency range of $25\\mathrm{-}500\\mathrm{Hz}$ . Each increase of potential is $0.05\\mathrm{V}.$ The quiet time for each test is 2 s. \n\nIsotopic experiments with ${\\bf\\sqrt[18]{\\bf{0}}}_{2}$ and $\\mathbf{H}_{2}^{\\mathbf{\\lambda}16}\\mathbf{O}.$ . First, $60\\mathrm{mg}$ of Sb-SAPC15 was dispersed in $30\\mathrm{ml}$ of $\\mathrm{H}_{2}^{16}\\mathrm{O}$ via sonication for $15\\mathrm{min}$ . Subsequently, $10\\mathrm{ml}$ of $^{18}{\\mathrm{O}}_{2}$ gas $(\\geq98\\%~^{18}\\mathrm{O}$ ; Taiyo Nippon Sanso Corporation) was injected to the suspension. Then, the system was completely sealed and irradiated by visible light. After a certain time interval (6, 24 and 72 h), $\\mathrm{1ml}$ of suspension was extracted and injected into a glass test tube filled with $\\Nu_{2}$ and $0.1\\mathrm{g}$ of $\\mathrm{Fe}_{2}(\\mathrm{SO}_{4})_{3}$ dissolved in $\\mathrm{1ml}$ of ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}.$ After injection of suspension, the test tube was sealed and irradiated under UV light for $^{5\\mathrm{h}}$ . The gas $(0.1\\mathrm{ml})$ in the test tube was extracted by gas chromatography syringe and injected into a Shimadzu GC–MS system (GC–MS-QP2010). \n\nIsotopic experiments with $\\mathbf{H}_{2}^{\\mathbf{\\alpha18}}\\mathbf{O}$ . Here, $20\\mathrm{mg}$ of Sb-SAPC15 was dispersed in $10\\mathrm{g}$ of $\\mathrm{H}_{2}^{\\mathrm{~18}}\\mathrm{O}$ $(\\geq98\\%{}^{18}\\mathrm{O};$ Taiyo Nippon Sanso Corporation) containing $\\begin{array}{r}{{1}\\mathrm{m}\\mathrm{M}\\mathrm{Ag}\\mathrm{NO}_{3}}\\end{array}$ under sonication for $15\\mathrm{min}$ . Afterwards, $\\Nu_{2}$ was bubbled into the suspension for $2\\mathrm{h}$ at a flow rate of $0.51\\mathrm{{min}^{-1}}$ to ensure complete removal of the dissolved oxygen $\\left(^{16}\\mathrm{O}_{2}\\right)$ in the system16. Then, the system was completely sealed and irradiated by visible light. After a certain time interval (0.5, 1, 3, 5, 10 and 24 h), $\\mathrm{1ml}$ of suspension was extracted and injected into a glass test tube filled with $\\Nu_{2}$ and $0.1\\mathrm{g}$ $\\mathrm{Fe}_{2}(\\mathrm{SO}_{4})_{3}$ dissolved in $\\mathrm{1ml}$ of $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ . After injection of suspension, the test tube was sealed and irradiated under UV light for $5\\mathrm{h}$ The gas $\\left(0.1\\mathrm{ml}\\right)$ in the test tube was extracted by gas chromatography syringe and injected into a Shimadzu GC– MS system (GC–MS-QP2010). \n\nIsotopic experiments in real experimental conditions. A poly-tetrafluoroethylene gas bag was used for the isotopic experiment. First of all, $3\\mathrm{ml}$ ultrapure $\\mathrm{N}_{2}$ was injected into the bag, followed by injecting $\\mathrm{1ml}$ aqueous suspension of Sb-SAPC15 (concentration $1\\mathrm{mg}\\mathrm{ml}^{-1}$ ; $\\mathrm{1\\mg}$ of Sb-SAPC15 powder dissolved in $\\mathrm{1ml}$ of $\\mathrm{H}_{2}^{\\ 18}\\mathrm{O}_{\\it4}^{\\backslash}$ ). Subsequently, $100\\upmu\\mathrm{l}$ of $\\mathrm{O}_{2}$ gas was injected and the bag was properly sealed and put over an ultrasonicator. Additionally, control experiments in absence of Sb-SAPC15 or light irradiation were conducted for confirming the photo-induced oxygen generation reaction. Furthermore, GC–MS spectra of the gas extracted from the Sb-SAPC15 system with other electron acceptors $\\mathrm{(0.1MAg^{+}}$ or $0.1\\mathrm{MNaIO}_{3};$ ) or without addition of Sb-SAPC were also conducted for comparison. \n\n${\\bf{H}}_{2}{\\bf{O}}_{2}$ degradation study. Here, $50\\mathrm{ml}$ of deionized water in a borosilicate glass bottle ( $\\cdot\\varphi60\\mathrm{mm}$ ; capacity $\\mathrm{100ml}$ ) without addition of catalyst was bubbled with $\\mathrm{~O}_{2}$ for $30\\mathrm{min}$ . Then, a certain amount of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was added into the bottle, and the concentration of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was manipulated to be $1\\times10^{2}\\mathrm{mgl^{-1}}$ . Finally, the bottle was sealed with a rubber septum cap. To investigate the hole transfer to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ the following experiment was performed: $50\\mathrm{mg}$ of photocatalyst was added into $50\\mathrm{ml}$ of $\\mathrm{NaIO}_{3}$ (0.1 M) and $\\mathrm{H}_{2}\\mathrm{O}_{2}\\left(0.01\\mathrm{wt}\\%\\right)$ solution in a borosilicate glass bottle $\\overset{\\cdot}{\\varphi}$ $60\\mathrm{mm}$ ; capacity $\\mathrm{100ml}$ ). The same solution without addition of photocatalyst was also measured as a control. Additionally, the same experiment was also conducted in $50\\mathrm{ml}$ of $\\mathrm{NaIO}_{3}$ (0.1 M) phosphate buffer solution (0.1 M, pH 7.4). After completely removing $\\mathrm{O}_{2}$ from the reaction system, the bottle was irradiated by a 300 W Xenon lamp with a UV cut filter (light intensity $30.3\\mathrm{W}\\mathrm{m}^{-2}$ at $420{-}500\\mathrm{nm}$ ). \n\nDetails for TDDFT calculations. The optimization and frequency combined with vertical excitation properties were performed via TDDFT in the Gaussian 09 program S2, which was carried out by using the wb97xd/6-311g(d) level of theory for C, N and H elements and SDD for Sb element. Three monolayer cluster models were optimized to represent the major surface properties of CN sites in PCN, Na sites in PCN_Na15 and Sb sites in Sb-SAPC15 (refs. 50,58). The charges of monolayer cluster models were settled in consideration of the oxidation state of Sb and Na on the basis of the experimental results as follows: 0 for Melem_3; $+1$ for Melem $_{-}\\mathrm{Nal^{+}}$ and $+3$ for Melem ${}_{-}3\\mathrm{Sb}3^{+}$ . To give a comprehensive understanding of the relationships between the electronic configuration during excitation and the realistic experiment results, 50 excited states of these three cluster models were used to simulate UV absorption spectra50. Note that the absorption edges of simulated UV spectra are unusually large compared to those of experimental ones for two reasons: (1) to simulate the charge-transfer properties of the high-quality model, functions of $\\omega97x d,$ a function including a large amount of Hartree–Fock exchange, were used. These exchange functions usually overestimate the excitation energies, as well as the simulated highest to lowest highest occupied molecular orbital $\\mathrm{gap}^{51,52,58}$ , (2) In the solid state, p-conjugated molecules adjacent to the one carrying a charge become strongly polarized, an effect that stabilizes the cationic and anionic states (each generally by about one $\\boldsymbol{\\mathrm{{eV}}}$ in p-conjugated materials). In this case, the bandgap is typically considerably lower in energy than the molecular fundamental gap and the optical $\\mathrm{gap}^{52}$ . Since the evitable system error cannot be eliminated, the possible simulated excited states that contributed to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production (corresponding to spectra from $420{-}470\\mathrm{nm}$ ) were confirmed by comparing the experimental spectra and simulated ones. Then, the transition density of electron/holes were considered at all these excited states. \n\nFor analysis of the excitation and charge-transfer properties, Multiwfn v.3.6 (released on 21 May 2019)53 was performed. Visualization of hole, electron and transition density was also performed by Multiwfn; functions of $\\mathrm{IOp}(9/40{=}3)$ were set during the vertical excitation based on TDDFT calculation53. The electron distributions at these excited states were presented as heatmaps by combination of GaussView and Multiwfn $\\begin{array}{r}{53,59-62}\\\\ {.}\\end{array}$ . The isosurface of LUMO orbitals were presented by setting the isovalue at 0.05. \n\nDetails for the free energy diagram. The cluster model is more likely to predict the ORR process on the basis of our previous investigation36. The free energy diagram of Melem_ $3\\mathrm{Sb}3^{+}$ was calculated as follows: \n\nThe optimized structure of Melem ${}_{-}3\\mathrm{Sb}3^{+}$ was used as the initial structure for calculating the most stable adsorption configurations of $^{*}\\mathrm{OOH}$ , $^{*}\\mathrm{O}$ and $^{*}\\mathrm{OH}$ The ORR following the $2e^{-}$ and $4e^{-}$ pathway produces $\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2},$ respectively. The associative $4e^{-}$ ORR is composed of four elementary steps (equations (8)–(11)): \n\n$$\n\\mathrm{\\Omega}_{\\ast}+\\mathrm{O}_{2}\\left(\\mathrm{g}\\right)+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\ast\\mathrm{OOH}\n$$ \n\n$$\n\\mathrm{\\Omega_{\\astOOH}+H^{+}+e^{-}\\rightarrow\\ast O+H_{2}O\\left(l\\right)}\n$$ \n\n$$\n\\mathrm{*O+H^{+}+e^{-}\\rightarrow*O H}\n$$ \n\n$$\n\\mathrm{*OH+H^{+}+e^{-}\\rightarrow H_{2}O\\left(l\\right)+*}\n$$ \n\nThe $2e^{-}\\mathrm{ORR}$ comprises two elementary steps (equations (12) and (13)): \n\n$$\n\\mathrm{\\Omega}_{\\ast}+\\mathrm{O}_{2}\\left(\\mathrm{g}\\right)+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\mathrm{\\astOOH}\n$$ \n\n$$\n\\mathrm{\\sOOH+H^{+}+e^{-}\\to H_{2}O_{2}(l)+\\ast}\n$$ \n\nThe asterisk (\\*) denotes the active site of the catalyst. The free energy for each reaction intermediate is defined as: \n\n$$\nG=E_{\\mathrm{DFT}}+E_{\\mathrm{ZPE}}-T_{\\mathrm{S}}+E_{\\mathrm{sol}}\n$$ \n\nwhere $E_{\\mathrm{DFT}}$ is the electronic energy calculated by DFT, $E_{\\mathrm{ZPE}}$ denotes the zero point energy estimated within the harmonic approximation and $T_{\\mathrm{s}}$ is the entropy at 298.15 K ( $\\begin{array}{r}{T{=}298.15\\mathrm{K},}\\end{array}$ ). The $E_{\\mathrm{ZPE}}$ and $T_{\\mathrm{s}}$ of gas-phase $\\mathrm{H}_{2}$ and reaction intermediates are based on our previous work36. For the concerted proton–electron transfer, the free energy of a pair of proton and electron $\\mathrm{(H^{+}+e^{-})}$ was calculated as a function of applied potential relative to RHE (U versus RHE), that is, $\\mu(\\mathrm{H^{+}})+\\mu(\\mathrm{e^{-}})=1/2\\mu(\\mathrm{H}_{2})-\\mathrm{eU}_{:}$ according to the computational hydrogen electrode model proposed by Nørskov63. In addition, the solvent effect was reported to play an important role in ORR. In our calculations, the solvent corrections $(E_{\\mathrm{sol}})$ for $^{*}\\mathrm{OOH}$ and $^{*}\\mathrm{OH}$ are $0.45\\mathrm{eV}$ in accordance with previous studies64,65. We used the energies of $\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{H}_{2}$ molecules calculated by DFT together with experimental formation energy of $_\\mathrm{H_{2}O}$ (4.92 eV) to construct the free energy diagram. The free energies of $\\mathrm{O}_{2}$ , \\*OOH, $^{*}\\mathrm{O}$ and $^{*}\\mathrm{OH}$ at a given potential U relative to RHE are defined as: \n\n$$\n\\Delta G\\left(\\mathrm{O}_{2}\\right)=4.92-4\\mathrm{eU}\n$$ \n\n$$\n\\Delta G(\\mathrm{OOH})=G\\left(\\ast\\mathrm{OOH}\\right)+\\frac{3G\\left(\\mathrm{H}_{2}\\right)}{2}-G\\left(\\ast\\right)-2G\\left(\\mathrm{H}_{2}\\mathrm{O}\\right)-3\\mathrm{eU}\n$$ \n\n$$\n\\Delta G(\\mathrm{O})=G(\\ast\\mathrm{O})+G(\\mathrm{H}_{2})-G(\\ast)-G(\\mathrm{H}_{2}\\mathrm{O})-2\\mathrm{eU}\n$$ \n\n$$\n\\Delta G(\\mathrm{OH})=G(\\ast\\mathrm{OH})+\\frac{G(\\mathrm{H}_{2})}{2}-G(\\ast)-G(\\mathrm{H}_{2}\\mathrm{O})-\\mathrm{eU}\n$$ \n\nDetails for simulations of charge transfer. All theoretical calculations were performed based on DFT, implemented in the Vienna ab initio simulation package66,67. The electron exchange and correlation energy were treated within the generalized gradient approximation in the Perdew–Burke–Ernzerhof \n\nfunctional68,69. The valence orbitals were described by plane-wave basis sets with cutoff energies of $400\\mathrm{eV.}$ For the simulation of Na and Sb incorporated in bulk phase of $\\mathrm{g-C_{3}N_{4},}$ a $1\\times1\\times2$ supercell of pristine bulk $\\mathrm{g-C_{3}N_{4}}$ was adopted. And the $k$ -points were sampled in a $3\\times3\\times2$ Monkhorst–Pack grid. For the simulation of Na and Sb near the surface of g- $\\mathrm{C_{3}N_{4},}$ the $k$ -point sampling was obtained from the Monkhorst–Pack scheme with a $(2\\times2\\times1)$ mesh. The atomic coordinates are fully relaxed using the conjugate gradient method70. The convergence criteria for the electronic self-consistent iteration and force were set to $10^{-4}\\mathrm{eV}$ and $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ , respectively. The vacuum gap was set as $15\\mathrm{\\AA}$ . To quantitatively compare the degree of charge transfer, a Bader charge analysis has been carried out45. \n\n# Data availability \n\nSource data are provided with this paper. The data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 7 June 2020; Accepted: 16 March 2021; Published online: 21 May 2021 \n\n# References \n\n1.\t Bryliakov, K. P. Catalytic asymmetric oxygenations with the environmentally benign oxidants $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and $\\mathrm{~O}_{2}$ . Chem. Rev. 117, 11406–11459 (2017). \n2.\t Shaegh, S. A. M., Nguyen, N.-T., Ehteshamiab, S. M. M. & Chan, S. H. A membraneless hydrogen peroxide fuel cell using Prussian Blue as cathode material. Energy Environ. Sci. 5, 8225–8228 (2012). \n3.\t Gray, H. B. Powering the planet with solar fuel. Nat. Chem. 1, 7 (2009). \n4.\t Kim, D., Sakimoto, K. K., Hong, D. & Yang, P. Artificial photosynthesis for sustainable fuel and chemical production. Angew. Chem. Int. Ed. 54, 3259–3266 (2015). \n5.\t Xia, C., Xia, Y., Zhu, P., Fan, L. & Wang, H. Direct electrosynthesis of pure aqueous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solutions up to $20\\%$ by weight using a solid electrolyte. Science 366, 226–231 (2019). \n6.\t Edwards, J. K. et al. Direct synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ from $\\mathrm{H}_{2}$ and $\\mathrm{~O}_{2}$ over gold, palladium, and gold-palladium catalysts supported on acid-pretreated $\\mathrm{TiO}_{2}$ . Angew. Chem. Int. Ed. 48, 8512–8515 (2009). \n7. Freakley, S. J. et al. Palladium-tin catalysts for the direct synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ with high selectivity. Science 351, 965–968 (2016). \n8.\t Yang, S. et al. Toward the decentralized electrochemical production of $\\mathrm{H}_{2}\\mathrm{O}_{2};$ a focus on the catalysis. ACS Catal. 8, 4064–4081 (2018). \n9.\t Yi, Y., Wang, L., Li, G. & Guo, H. A review on research progress in the direct synthesis of hydrogen peroxide from hydrogen and oxygen: noble-metal catalytic method, fuel-cell method and plasma method. Catal. Sci. Technol. 6, 1593–1610 (2016). \n10.\tHou, H., Zeng, X. & Zhang, X. Production of hydrogen peroxide through photocatalytic process. Angew. Chem. Int. Ed. 59, 17356–17376 (2020). \n11.\tShi, X. et al. Understanding activity trends in electrochemical water oxidation to form hydrogen peroxide. Nat. Commun. 8, 701 (2017). \n12.\tShiraishi, Y. et al. Sunlight-driven hydrogen peroxide production from water and molecular oxygen by metal-free photocatalysts. Angew. Chem. 126, 13672–13677 (2014). \n13.\tFuku, K. & Sayama, K. Efficient oxidative hydrogen peroxide production and accumulation in photoelectrochemical water splitting using a tungsten trioxide/ bismuth vanadate photoanode. Chem. Commun. 52, 5406–5409 (2016). \n14.\tBaek, J. H. et al. Selective and efficient Gd-doped ${\\mathrm{BiVO}}_{4}$ photoanode for two-electron water oxidation to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . ACS Energy Lett. 4, 720–728 (2019). \n15.\tTeng, Z. et al. Photoexcited single metal atom catalysts for heterogeneous photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production: pragmatic guidelines for predicting charge separation. Appl. Catal. B Environ. 282, 119589 (2020). \n16.\tShiraishi, Y. et al. Resorcinol–formaldehyde resins as metal-free semiconductor photocatalysts for solar-to-hydrogen peroxide energy conversion. Nat. Mater. 18, 985–993 (2019). \n17.\tFan, W. et al. Efficient hydrogen peroxide synthesis by metal-free polyterthiophene via photoelectrocatalytic dioxygen reduction. Energy Environ. Sci. 13, 238–245 (2020). \n18.\t Kim, H., Choi, Y., Hu, S., Choi, W. & Kim, J.-H. Photocatalytic hydrogen peroxide production by anthraquinone-augmented polymeric carbon nitride. Appl. Catal. B Environ. 229, 121–129 (2018). \n19.\tMoon, G.-H. et al. Eco-friendly photochemical production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ through $\\mathrm{O}_{2}$ reduction over carbon nitride frameworks incorporated with multiple heteroelements. ACS Catal. 7, 2886–2895 (2017). \n20.\tChu, C. et al. Spatially separating redox centers on 2D carbon nitride with cobalt single atom for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Proc. Natl Acad. Sci. USA 117, 6376–6382 (2020). \n21.\tWei, Z. et al. Efficient visible-light-driven selective oxygen reduction to hydrogen peroxide by oxygen-enriched graphitic carbon nitride polymer. Energy Environ. Sci. 11, 2581–2589 (2018). \n22.\tKaynan, N., Berke, B. A., Hazut, O. & Yerushalmi, R. Sustainable photocatalytic production of hydrogen peroxide from water and molecular oxygen. J. Mater. Chem. A 2, 13822–13826 (2014). \n23.\tTeng, Z. et al. Bandgap engineering of polymetric carbon nitride copolymerized by 2,5,8-triamino-tri-s-triazine (melem) and barbituric acid for efficient nonsacrificial photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Appl. Catal. B. 271, 118917 (2020). \n24.\tZeng, X. et al. Simultaneously tuning charge separation and oxygen reduction pathway on graphitic carbon nitride by polyethylenimine for boosted photocatalytic hydrogen peroxide production. ACS Catal. 10, 3697–3706 (2020). \n25.\tWang, Q. & Domen, K. Particulate photocatalysts for light-driven water splitting: mechanisms, challenges, and design strategies. Chem. Rev. 120, 919–985 (2020). \n26.\tHirakawa, H., Hashimoto, M., Shiraishi, Y. & Hirai, T. Photocatalytic conversion of nitrogen to ammonia with water on surface oxygen vacancies of titanium dioxide photocatalytic conversion of nitrogen to ammonia with water on surface oxygen vacancies of titanium dioxide. J. Am. Chem. Soc. 139, 10929–10936 (2017). \n27.\tKulkarni, A., Siahrostami, S., Patel, A. & Nørskov, J. K. Understanding catalytic activity trends in the oxygen reduction reaction. Chem. Rev. 118, 2302–2312 (2018). \n28.\tWatanabe, E., Ushiyama, H. & Yamashita, K. Theoretical studies on the mechanism of oxygen reduction reaction on clean and O-substituted $\\mathrm{Ta}_{3}\\mathrm{N}_{5}(100)$ surfaces. Catal. Sci. Technol. 5, 2769–2776 (2015). \n29.\tChoi, C. H. et al. Hydrogen peroxide synthesis via enhanced two-electron oxygen reduction pathway on carbon-coated Pt surface. J. Phys. Chem. C 118, 30063–30070 (2014). \n30.\tChu, C. et al. Electronic tuning of metal nanoparticles for highly efficient photocatalytic hydrogen peroxide production. ACS Catal. 9, 626–631 (2019). \n31.\t Pegis, M. L., Wise, C. F., Martin, D. J. & Mayer, J. M. Oxygen reduction by homogeneous molecular catalysts and electrocatalysts. Chem. Rev. 118, 2340–2391 (2018). \n32.\t Yang, S., Kim, J., Tak, Y. J., Soon, A. & Lee, H. Single-atom catalyst of platinum supported on titanium nitride for selective electrochemical reactions. Angew. Chem. Int. Ed. 55, 2058–2062 (2016). \n33.\tMontemore, M. M., van Spronsen, M. A., Madix, R. J. & Friend, C. M. $\\mathrm{~O}_{2}$ activation by metal surfaces: implications for bonding and reactivity on heterogeneous catalysts. Chem. Rev. 118, 2816–2862 (2018). \n34.\tWang, A., Li, J. & Zhang, T. Heterogeneous single-atom catalysis. Nat. Rev. Chem. 2, 65–81 (2018). \n35.\tShen, R. et al. High-concentration single atomic Pt sites on hollow CuSx for selective $\\mathrm{O}_{2}$ reduction to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in acid solution. Chem 5, 2099–2110 (2019). \n36.\t Gao, J. et al. Enabling direct $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in acidic media through rational design of transition metal single atom catalyst. Chem 6, 1–17 (2020). \n37.\tJung, E. et al. Atomic-level tuning of Co-C-N catalyst for high performance electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Nat. Mater. 19, 436–442 (2020). \n38.\tNosaka, Y. & Nosaka, A. Introduction to Photocatalysis: From Basic Science to Applications (Royal Society of Chemistry, 2016). \n39.\tInoue, Y. Photocatalytic water splitting by $\\mathrm{RuO}_{2}$ -loaded metal oxides and nitrides with $\\mathbf{d}^{0}.$ - and $\\mathrm{d}^{10}$ -related electronic configurations. Energy Environ. Sci. 2, 364–386 (2009). \n40.\tLi, X. et al. Single-atom Pt as co-catalyst for enhanced photocatalytic $\\mathrm{H}_{2}$ evolution. Adv. Mater. 28, 2427–2431 (2016). \n41.\tNaumkin, A. V., Kraut-Vass, A., Gaarenstroom, S. W. & Powell, C. J. NIST X-Ray Photoelectron Spectroscopy Database figshare (NIST, 2012); https://doi.org/10.18434/T4T88K \n42.\tRavel, B. & Newville, M. ATHENA, ARTEMIS, HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT. $J.$ Synchrotron Radiat. 12, 537–541 (2005). \n43.\tZhang, P. et al. Heteroatom dopants promote two-electron $\\mathrm{O}_{2}$ reduction for photocatalytic production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ on polymeric carbon nitride. Angew. Chem. Int. Ed. 59, 16209–16217 (2020). \n44.\tKim, S. et al. Selective charge transfer to dioxygen on $\\mathrm{KPF}_{6}$ -modified carbon nitride for photocatalytic synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ under visible light. J. Catal. 357, 51–58 (2018). \n45.\tYamakata, A., Ishibashi, T. & Onishi, H. Water- and oxygen-induced decay kinetics of photogenerated electrons in $\\mathrm{TiO}_{2}$ and $\\mathrm{Pt/TiO}_{2}$ : a time-resolved infrared absorption study. J. Phys. Chem. B 105, 7258–7262 (2001). \n46.\tZhang, P. et al. Modified carbon nitride nanozyme as bifunctional glucose oxidase-peroxidase for metal-free bioinspired cascade photocatalysis. Nat. Commun. 10, 940 (2019). \n47.\tSanville, E., Kenny, S. D., Smith, R. & Henkelman, G. Improved grid based algorithm for Bader charge allocation. J. Comput. Chem. 28, 899–908 (2001). \n48.\tGao, H., Yan, S., Wang, J. & Zou, Z. Ion coordination significantly enhances the photocatalytic activity of graphitic-phase carbon nitride. Dalton Trans. 43, 8178–8183 (2014). \n49.\tXiong, T. et al. KCl-mediated dual electronic channels in layered $\\mathrm{g-C_{3}N_{4}}$ for enhanced visible light photocatalytic NO removal. Nanoscale 10, 8066–8074 (2018). \n50.\tXiong, T., Cen, W., Zhang, Y. & Dong, F. Bridging the $\\mathrm{g-C_{3}N_{4}}$ interlayers for enhanced photocatalysis. ACS Catal. 6, 2462–2472 (2016). \n51.\tGhuman, K. K. et al. Photoexcited surface frustrated Lewis pairs for heterogeneous photocatalytic $\\mathrm{CO}_{2}$ reduction. J. Am. Chem. Soc. 138, \n1206–1214 (2016). \n52.\tBredas, J.-L. Mind the gap! Mater. Horiz. 1, 17–19 (2014). \n53.\tLu, T. & Chen, F. Multiwfn: A multifunctional wavefunction analyzer. J. Comput. Chem. 33, 580–592 (2012). \n54.\tNakamura, R. & Nakato, Y. Primary intermediates of oxygen photoevolution reaction on $\\mathrm{TiO}_{2}$ (rutile) particles, revealed by in situ FTIR absorption and photoluminescence measurements. J. Am. Chem. Soc. 126, 1290–1298 (2004). \n55.\tJones, R., Summerville, D. & Basolo, F. Synthetic oxygen carriers related to biological systems. Chem. Rev. 79, 139–179 (1979). \n56.\t Li, S. et al. Effective photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production under visible light irradiation at $\\mathrm{g-C_{3}N_{4}}$ modulated by carbon vacancies. Appl. Catal. B 190, \n26–35 (2016). \n57.\tKofuji, Y. et al. Carbon nitride–aromatic diimide–graphene nanohybrids: metal-free photocatalysts for solar-to-hydrogen peroxide energy conversion with $0.2\\%$ efficiency. J. Am. Chem. Soc. 138, 10019–10025 (2016). \n58.\tGovind, N., Lopata, K., Rousseau, R., Andersen, A. & Kowalski, K. Visible light absorption of N-doped $\\mathrm{TiO}_{2}$ rutile using (LR/RT)-TDDFT and active space EOMCCSD calculations. J. Phys. Chem. Lett. 2, 2696–2701 (2011). \n59.\tBahers, T. L., Adamo, C. & Ciofini, I. A qualitative index of spatial extent in charge-transfer excitations. J. Chem. Theory Comput. 7, 2498–2506 (2011). \n60.\tKraner, S., Scholz, R., Plasser, F., Koerner, C. & Leo, K. Exciton size and binding energy limitations in one-dimensional organic materials. J. Chem. Phys. 143, 244905 (2015). \n61.\tKraner, S., Prampolini, O. & Cuniberti, G. Exciton binding energy in molecular triads. J. Phys. Chem. C 121, 17088–17095 (2017). \n62.\tKislitsyn, D. et al. Spatial mapping of sub-bandgap states induced by local nonstoichiometry in individual lead sulfide nanocrystals. J. Phys. Chem. Lett. \n5, 3701–3707 (2014). \n63.\tNørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004). \n64.\tCalle-Vallejo, F., Martı´nez, J. I. & Rossmeisl, J. Density functional studies of functionalized graphitic materials with late transition metals for oxygen reduction reactions. Phys. Chem. Chem. Phys. 13, 15639–15643 (2011). \n65.\tXu, H., Cheng, D., Cao, D. & Zeng, X. C. A universal principle for a rational design of single-atom electrocatalysts. Nat. Catal. 1, 339–348 (2018). \n66.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. J. Phys. Rev. B. 54, \n11169–11186 (1996). \n67.\tKresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. J. Comput. Mater. Sci. 6, 15–50 (1996). \n68.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n69.\tBlöchl, P. E. Projector augmented-wave method. Phys. Rev. B. 50, 17953–17979 (1994). \n70.\tPress, W. H., Teukolsky, S. A., Vetterling, W. T. & Flannery, B. P. Numerical Recipes (Cambridge Univ. Press, 2007). \n\n# Acknowledgements \n\nWe acknowledge the financial support from the Mitsubishi Chemical Corporation, Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Research (B, grant no. 20H02847), Grant-in-Aid for JSPS Fellows (DC2, grant no. 20J13064), Project National Natural Science Foundation of China (grant nos. 21805191, 21972094), the Guangdong Basic and Applied Basic Research Foundation (grant no. 2020A15150 10982), Shenzhen Pengcheng Scholar Program, Shenzhen Peacock Plan (grant nos. KQJSCX20170727100802505 and KQTD2016053112042971), the Singapore Ministry of Education (Tier 1: RG4/20 and Tier 2: MOET2EP10120-0002) and the Agency for Science, Technology and Research (A\\*Star IRG: A20E5c0080). We thank X. Huang from the Department of Physics, Southern University of Science and Technology for his help in theoretical calculation and N. Jian from the Electron Microscope Center of the Shenzhen University for his help in HRTEM measurement. \n\n# Author contributions \n\nZ.T., Q.Z. and T.O. conceptualized the project. T.O., C.S. and B.L. supervised the project. Z.T. synthesized the catalysts, conducted the catalytic tests and the related data processing, and performed materials characterization and analysis with the help of H.Y., Q.Z., Y.-R.L. and S.L. K.K. and A.Y. conducted transient absorption spectroscopy. Z.T., W.Y. and C.W. performed the theoretical study. Z.T., H.Y. and B.L. wrote the paper with support from all authors. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41929-021-00605-1. \n\nCorrespondence and requests for materials should be addressed to C.S., B.L. or T.O. \n\nPeer review information Nature Catalysis thanks Wei Lin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021, corrected publication 2021 " + }, + { + "id": "10.1038_s41586-021-03428-z", + "DOI": "10.1038/s41586-021-03428-z", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03428-z", + "Relative Dir Path": "mds/10.1038_s41586-021-03428-z", + "Article Title": "Direct observation of chemical short-range order in a medium-entropy alloy", + "Authors": "Chen, XF; Wang, Q; Cheng, ZY; Zhu, ML; Zhou, H; Jiang, P; Zhou, LL; Xue, QQ; Yuan, FP; Zhu, J; Wu, XL; Ma, E", + "Source Title": "NATURE", + "Abstract": "Direct experimental evidence of chemical short-range atomic-scale ordering (CSRO) in a VCoNi medium-entropy alloy is provided via diffraction and electron microscopy, analysed from specific crystallographic directions. Complex concentrated solutions of multiple principal elements are being widely investigated as high- or medium-entropy alloys (HEAs or MEAs)(1-11), often assuming that these materials have the high configurational entropy of an ideal solution. However, enthalpic interactions among constituent elements are also expected at normal temperatures, resulting in various degrees of local chemical order(12-22). Of the local chemical orders that can develop, chemical short-range order (CSRO) is arguably the most difficult to decipher and firm evidence of CSRO in these materials has been missing thus far(16,22). Here we discover that, using an appropriate zone axis, micro/nullobeam diffraction, together with atomic-resolution imaging and chemical mapping via transmission electron microscopy, can explicitly reveal CSRO in a face-centred-cubic VCoNi concentrated solution. Our complementary suite of tools provides concrete information about the degree/extent of CSRO, atomic packing configuration and preferential occupancy of neighbouring lattice planes/sites by chemical species. Modelling of the CSRO order parameters and pair correlations over the nearest atomic shells indicates that the CSRO originates from the nearest-neighbour preference towards unlike (V-Co and V-Ni) pairs and avoidance of V-V pairs. Our findings offer a way of identifying CSRO in concentrated solution alloys. We also use atomic strain mapping to demonstrate the dislocation interactions enhanced by the CSROs, clarifying the effects of these CSROs on plasticity mechanisms and mechanical properties upon deformation.", + "Times Cited, WoS Core": 496, + "Times Cited, All Databases": 516, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000645368900011", + "Markdown": "# Article \n\n# Direct observation of chemical short-range order in a medium-entropy alloy \n\nhttps://doi.org/10.1038/s41586-021-03428-z \n\nReceived: 27 September 2020 \n\nAccepted: 8 March 2021 \n\nPublished online: 28 April 2021 Check for updates \n\nXuefei Chen1,2,7, Qi Wang3,7, Zhiying Cheng4,7, Mingliu Zhu1, Hao Zhou5, Ping Jiang1, Lingling Zhou1,2, Qiqi Xue1,2, Fuping Yuan1,2, Jing Zhu4 ✉, Xiaolei Wu1,2 ✉ & En Ma6 ✉ \n\nComplex concentrated solutions of multiple principal elements are being widely investigated as high- or medium-entropy alloys (HEAs or MEAs)1–11, often assuming that these materials have the high configurational entropy of an ideal solution. However, enthalpic interactions among constituent elements are also expected at normal temperatures, resulting in various degrees of local chemical order12–22. Of the local chemical orders that can develop, chemical short-range order (CSRO) is arguably the most difficult to decipher and firm evidence of CSRO in these materials has been missing thus far16,22. Here we discover that, using an appropriate zone axis, micro/nanobeam diffraction, together with atomic-resolution imaging and chemical mapping via transmission electron microscopy, can explicitly reveal CSRO in a face-centred-cubic VCoNi concentrated solution. Our complementary suite of tools provides concrete information about the degree/extent of CSRO, atomic packing configuration and preferential occupancy of neighbouring lattice planes/sites by chemical species. Modelling of the CSRO order parameters and pair correlations over the nearest atomic shells indicates that the CSRO originates from the nearestneighbour preference towards unlike (V−Co and V−Ni) pairs and avoidance of V−V pairs. Our findings offer a way of identifying CSRO in concentrated solution alloys. We also use atomic strain mapping to demonstrate the dislocation interactions enhanced by the CSROs, clarifying the effects of these CSROs on plasticity mechanisms and mechanical properties upon deformation. \n\nWe selected V-Co-Ni as a model system, because the equilibrium V−Co, V−Ni and V−Co−Ni phase diagrams23,24 show binary and ternary intermetallic compounds over a range of temperatures and compositions. The VCoNi MEA, previously claimed to be a face-centred-cubic (fcc) random solid solution at room temperature23, is therefore a metastable phase with a high likelihood of partial chemical order. Specifically, we hypothesize that this single-phase fcc MEA has a preference for V−Co and V−Ni bonds accompanied by V−V avoidance. Such CSROs, however, are notoriously difficult to observe in a direct manner12–22. We therefore designed systematic and meticulous experiments to avoid the need for data fitting17 and/or multiple possible interpretations22. The complementary characterization tools we chose are described in the Methods. The transmission electron microscope (TEM) observations, as displayed in Fig. 1a, shows a dual-phase microstructure in the VCoNi MEA. The dominant phase is the fcc solution, at a volume fraction of about $80\\%$ . The minority phase, occupying about $20\\%$ of the sample volume, has a long-range chemically ordered $\\mathbf{L}\\mathbf{1}_{2}$ structure, residing as plates inside the fcc grains and containing a high density of faults. The fully recrystallized fcc solution (see Methods) is composed of equi-axed and dislocation-free grains, with an average size of $1.2\\upmu\\mathrm{m}$ . Its composition, from atom probe tomography data (not shown), is $\\mathsf{V}_{36}\\mathsf{C o}_{33}\\mathsf{N i}_{31},$ slightly shifted relative to the overall VCoNi composition, owing to the coexisting $\\mathbf{L}\\mathbf{l}_{2}$ , which contains a little more Co and Ni. From here on, we will focus on the fcc solution only, to locate and dissect the CSROs that emerge inside this single phase. Figure 1b presents the lattice image of this fcc phase. The selected-area electron diffraction pattern (EDP) (left inset, lower right corner in Fig. 1a) and nano beam EDP (right inset in Fig. 1a), together with the fast Fourier transform (FFT) pattern (inset in Fig. 1b), show no additional diffraction information beyond the normal fcc Bragg spots. No CSRO could be detected from these results under the [110] zone axis, which has been normally used in previous TEM work22. \n\nDramatic differences emerge when the [112] zone axis was adopted, as shown in Fig. 2 (for a sample after tensile pulling to $18\\%$ plastic strain, but the sample before deformation (Extended Data Fig. 1) gives very similar results). Figure 2a is the selected-area EDP of one fcc grain, showing the expected fcc spots. Interestingly, there are extra disks, which are highly diffuse but visible halfway in between the transmission spot (000) and the {311} spots; one example is highlighted using a yellow circle. These extra diffuse disks in reciprocal space, each with a diameter several times that of the normal Bragg spot, are definitive indications that there exists additional order in real space that must be very small in spatial extent25–28. To improve the signal-to-noise (background) ratio, we further carried out nano-beam (about $35\\mathsf{n m}$ in diameter) EDP, using the same [112] zone axis. This led to much better contrast (Fig. 2b): the extra reflections are easily discernible. These disks all line up at the positions corresponding to $\\scriptstyle{\\frac{1}{2}}\\{{\\bar{3}}11\\}$ , as marked using arrows, clearly indicating the presence of CSRO. To observe the locations and dimensions of coherently diffracting regions, Fig. 2c shows the dark-field TEM image (with a close-up view in the inset) taken using the extra reflections; the vast majority $(90\\%)$ of these CSRO regions that light up are less than 1 nm in size, with an average size $\\stackrel{-}{d}\\approx0.6\\boldsymbol{\\mathrm{nm}}$ ; see the size distribution in Fig. 2d (and Extended Data Fig. 1a-3). The CSRO regions take up around $25\\%$ of the total area in these images. \n\n![](images/36d23d55c23ca13502773deb6ecea696d4da386bb3963fbb200113fb3a0ac65e.jpg) \nFig. 1 | TEM microstructure of VCoNi MEA. Both images were taken with the [110] zone axis for the fcc phase. a, Bright-field TEM image showing the equi-axed, dislocation-free fcc grains, with faulted $\\mathbf{L}\\mathbf{1}_{2}$ plates inside, in the as-prepared microstructure after cold rolling followed by recrystallization annealing at 1,173 K. Left and right insets show the selected-area EDP and nano-beam EDP, respectively. b, Lattice image of the fcc solution and the corresponding FFT pattern (inset). \n\nFigure 2e is the high-angle annular dark-field (HAADF) lattice image of the fcc phase, and the inset is the corresponding FFT pattern ([112] zone axis. Extra diffuse reflections (one is circled in yellow) are again observed in addition to the fcc diffraction spots (blue circles). Using these, inverse FFT images are obtained: the CSRO regions light up inside the yellow circles in Fig. 2f, and the corresponding image for the normal fcc lattice is in Fig. 2g. Superimposing the two images leads to Fig. 2h, with details in the close-up view in the inset. In this overlapped image, the CSRO stands out even more clearly because it adds intensity onto the fcc columns . The red dashed rectangle gives the cell motif corresponding to the local CSRO configuration. Of special note is that the lattice planes (yellow dashed lines) characterizing the CSRO periodicity have an inter-planar spacing $(d_{\\tt C S R O})$ that is twice the inter-planar spacing $d_{\\mathrm{fcc}}$ of the {311} planes in the fcc phase (blue dashed lines), as illustrated in the inset in Fig. 2h. Such chemical order, doubling the $d_{\\mathrm{fcc}},$ explains why the superlattice reflections appear at the locations corresponding to $\\scriptstyle{\\frac{1}{2}}\\{{\\bar{3}}11\\}$ in Fig. 2a, b and e. \n\nWe next wished to determine what kind of CSRO is present and why; that is, the detailed arrangements of the three elemental species constituting the CSROs. To this end, we carried out energy-dispersive X-ray spectroscopy (EDS) mapping: see Fig. 3a and additional maps as shown in Extended Data Fig. 2, based on HAADF imaging with the [112] zone axis. In Fig. 3a, each spot corresponds to an atomic column along the thickness direction of the TEM foil. We mapped out each element, V (red), Co (green) and Ni (blue), one by one. The intensity (brightness) of the coloured spot depends on the make-up of the column, scaling with the content of the particular element being probed. We discover that the CSRO can be best described in terms of the V occupancy. Specifically, as seen in the EDS maps (two examples are shown, respectively, in the left and right columns in Fig. 3b), two V-enriched (311) planes (see the map for V, under dashed yellow lines, across the red spots) sandwich one V-depleted (311) plane (in either the V−Co or V−Ni map, under dashed blue line, across the intense green/blue spots but with faint or even vanishing red V). In other words, the V-enriched (311) planes alternate with those enriched in Co and/or Ni. This alternating [112] zone axis and the corresponding FFT pattern (inset). This pattern again displays the extra diffuse reflections (see, for example, inside the yellow circle) at ${\\frac{1}{2}}\\{\\bar{3}\\mathbf{1}\\mathbf{1}\\}$ positions, besides the sharper Braggs spots from the fcc phase (blue circles). f, g, Inverse FFT image showing the CSRO regions (several are circled), and the fcc lattice, respectively. These two images are superimposed in h, with a close-up view of a CSRO region in the inset. Overlapping in this way produces bright sites that highlight the extra CSRO lining up on {311} planes (yellow dashed lines). $d_{\\mathrm{fcc}}$ denotes the spacing of {311} planes in the normal fcc lattice, whereas $d_{\\tt C S R O}$ displays the spacing corresponding to the extra chemical order. The red dashed box outlines this unit period for the local CSRO configuration. All scale bars are $0.5\\mathsf{n m}$ except in c. \n\n![](images/b5911068b96c4df6fe3f51211b34b7240b21531ec63901ae99a165294537f793.jpg) \nFig. 2 | Evidence of CSRO in the fcc VCoNi. The sample was deformed in tension to $18\\%$ plastic strain. a, Selected-area EDP with the [112] zone axis. We note two arrays of extra and diffuse disks (indicated by arrows) appearing at ${\\frac{1}{2}}\\{{\\bar{3}}11\\}$ positions (one example is inside the yellow circle). b, Nano-beam EDP with the [112] zone axis. Arrays of superlattice reflections at $\\scriptstyle{\\frac{1}{2}}\\{{\\bar{3}}11\\}$ positions as indicated by arrows. c, Energy-filtered dark-field TEM image taken using the diffuse reflections, with the inset showing a close-up view of the dashed square area, highlighting some coherently diffracting clusters corresponding to the local CSROs. The size distribution of these CSRO regions is shown in d. The average size $\\bar{d}$ is $0.60\\mathrm{nm}$ and $0.65\\mathsf{n m}$ , based on the dark-field TEM image and the inverse FFT image, respectively. e, Lattice image of the fcc phase with the \n\n![](images/813d6e96df54e14e989d8c47d7cf9750e51b1b08fb9f0f2efd2d0afea823537f.jpg) \nFig. 3 | Chemical mapping indicating element-specific enrichment on alternating atomic planes. a, EDS maps showing element distribution, atomic column by atomic column, from the HAADF image with the [112] zone axis (Fig. 2e). b, Close-up maps of V, V-Co, and V-Ni, respectively, in two local regions in a (see Extended Data Fig. 2 for additional maps showing the distribution of Co, Ni and ${\\mathsf{C o}}{\\mathsf{+N i}}$ ). All dashed lines mark the (311) planes intersecting the (111¯) plane in plan view: yellow: V-enriched, blue: Co-/Nienriched. All scale bars are $0.5\\mathsf{n m}$ . c, Line scan profiles along the horizontal direction. Each line profile represents the distribution of an element in a (111) plane, column by column, projected along either the [110] or the [112] zone axis. d, Pair correlation coefficients, $C_{\\mathrm{A\\cdotB}}(r)$ , calculated from 17 experimental EDS line profiles, are plotted over a spatial distance on the short-to-medium range length scale to quantitatively gauge the CSRO. The correlation and anti-correlation of chemical species are obvious (see text), and similar before and after tensile straining. e, Evolution of the Warren–Cowley short-range order parameter $\\alpha_{\\mathrm{A-B}}^{1}$ indicates the development of V−V, V−Co and V−Ni CSRO (upper panel). The steadily reducing energy (lower panel) with increasing swap Monte Carlo steps underscores the origin of the CSRO. \n\nchemical occupancy extends across only a few (311) planes, that is, a distance of less than 1 nm, and can hence be rightfully classified as chemical short-to-medium range order. Again, the two V-enriched planes are separated by a distance twice the normal spacing of {311} planes in the fcc lattice, as there is one Co/Ni-enriched plane in between. As a result, extra reflections appear at the $\\scriptstyle{\\frac{1}{2}}\\{{\\bar{3}}11\\}$ positions in Fig. 2b, e. \n\nWe also monitored the spatial distribution of each individual element from column to column along the horizontal ([110])  direction in Fig. 3a. The atomic fraction, an average for each atomic column, is plotted in Fig. 3c. The atomic concentration (percentage) of V, Co and Ni varies from one atomic column to another, although on average the chemical composition from the local chemical maps is not far from the global fcc composition, $\\mathsf{V}_{36}\\mathsf{C o}_{33}\\mathsf{N i}_{31}$ . Although the EDS profile in Fig. 3c is useful for observing compositional fluctuation21, it is necessary to devise a powerful metric with which to quantify the spatial correlations of chemical species. To this end, we calculate a set of pair correlation coefficients, $C_{\\mathrm{A\\cdotB}}(r)$ (see definition, test and feature details in Supplementary Information sections 1 and 2), to gauge the strength of positive and negative self-correlation or cross-correlation of the species at $r$ over short-to-medium range in our one-dimensional line profiles. We monitored 17 independent EDS line profiles. Figure 3d shows the correlation coefficient for V−V, V−Co and V−Ni at various r values up to $1.0\\mathsf{n m}$ . We observe an obvious $C_{\\mathrm{A\\cdotB}}(r)$ peak/valley at $r^{*}$ (around $\\phantom{-}0.14\\mathsf{n m}\\rangle$ ); see Extended Data Fig. 3a for a schematic showing the direct correspondence between this $r^{\\ast}$ and the (1st) nearest neighbour CSRO. To be specific, while V−Co and V−Ni exhibit positive $C(r^{*})$ , preferring to be (1st) nearest neighbours, V−V tend to avoid each other, showing a negative $C(r^{*})$ . In fact, the strength of correlation indicated by the absolute $C(r^{*})$ values—that is, V−V being approximately two times V−Co and V−Ni whereas $\\scriptstyle\\mathsf{V}-\\mathbf{Co}$ is slightly larger than V−Ni—is also in agreement with the degree of CSRO in the upper panel of Fig. 3e, which is the theoretically predicted magnitude for the order parameter (see below). Meanwhile, negative and positive $C(r^{*})$ values alternate, persisting roughly (due to lattice-distortion-induced displacement/uncertainty especially at large separation distances) at 2, 3 and 4 times the distance r\\*. That is, the correlation (together with concurrent anti-correlation) suggests a repeating CSRO pattern across several neighbouring atomic columns: Co(Ni)-enriched, V-enriched, Co(Ni)-enriched, V-enriched and so on, both before (upper panel in Fig. 3d) and after (lower panel in Fig. 3d) tensile deformation. This alternating neighbouring-column chemical preference in the (111) planes indicates the same preference/ avoidance trend as our observations about the (311) type planes (Figs. 2h, 3b). The thermodynamic driving force leading to the CSRO is shown in the lower panel of Fig. 3e, which will be discussed later (and in Supplementary Information section 3). \n\nNext, in Extended Data Fig. 4 we use schematics to help visualize the local three-dimensional atomic configuration that corresponds to the CSRO identified above. The inverse FFT image (Fig. 2h and inset) and EDS mapping (Fig. 3b) suggest that V atoms have a tendency/preference to occupy the eight vertices of the unit cell, interspersed with Co/Ni-enriched positions along the [111] direction. This is idealized in the model in Extended Data Fig. 4a, viewed from the [112] zone axis. This simplified model captures the alternating {311} planes (red ball planes interspersed with blue ball planes)—the salient chemical enrichment repeatedly featured in figures such as Fig. 2h and its inset, as well as the peak/valley undulation along [110] scan direction in Fig. 3. An idealized three-dimensional local configuration that corresponds to the CSRO can thus be hypothesized in Extended Data Fig. 4b (to be analysed elsewhere). The EDP corresponding with the [112] zone axis in Extended Data Fig. 4c shows the extra diffuse disks at the ${\\frac{1}{2}}\\{{\\bar{3}}11\\}$ positions, in full agreement with direct experimental observations in Figs. 2a, b, e. Therefore, it is such an atomic configuration/arrangement that locally breaks the fcc symmetry to produce the extra reflections, while all V, Co and Ni atoms reside on the fcc lattice sites. \n\nIn the following discussion, we make four important points that are of interest to the HEA/MEA community. First, we carried out density functional theory (DFT)-based modelling to monitor the evolution of CSRO and understand the underlying energetics. See Methods for the methodology29–32 we adopted. The cohesive energy gradually and substantially decreases with ordering (Fig. 3e). This demonstrates the thermodynamic driving force responsible for the CSRO observed. Meanwhile, we track the CSRO using the Warren–Cowley order parameter $\\alpha_{\\mathrm{A-B}}^{s},$ where subscript ‘A-B’ indicates the pair consisting of element A and element B in the sth nearest-neighbour shell (Fig. 3e, see Methods). We see that VCoNi is not random $(\\alpha_{\\mathsf{A-B}}^{s}\\approx0)$ , but instead strongly disfavours V−V connection in the 1st-neighbour shell, as indicated by the positive $\\alpha_{\\mathsf{V}-\\mathsf{V}}^{1},$ and prefers V−Co and V−Ni (negative $\\alpha_{\\mathrm{V-Co}}^{1}\\mathrm{or}\\alpha_{\\mathrm{V-Ni}}^{1})$ . $\\alpha_{\\mathsf{V}-\\mathsf{V}}^{1}$ is about twice the magnitude of $\\alpha_{\\mathrm{V-Co}}^{1}\\mathrm{or}\\alpha_{\\mathrm{V-Ni}}^{1},$ and V−Co is slightly more favoured than V−Ni (Fig. 3e). These theoretical findings explain the experimentally observed CSRO reported above. \n\nSecond, we explain using a simplified model why the CSRO has been difficult to detect in HEAs and MEAs. A projection of the (111) plane along the [110] beam direction is shown in Extended Data Fig. 3b. Suppose that for a given atom (take the blue C as centre), its six (1st) nearest neighbours (and none of its 2nd nearest neighbours) residing in this plane are unlike species, and for simplicity we assume the 3rd and 4th nearest neighbours (grey spheres) have negligible effects. As illustrated, when projecting along the [110] direction (dashed lines in Fig. 3b), the centre is directly superimposed on two 1st neighbours, resulting in a mixed-species column that blurs the difference from other neighbouring columns and hence the contrast in the image and chemical mapping. Previous attempts used only the [100] and [110] zone axes21,22. As illustrated in Extended Data Fig. 3a, the alternating V-rich and Co (Ni)-rich columns are best visualized with the [112] beam direction. \n\n![](images/e49f26e50c2f5c0abe87d3fe91dd91e77dca9c66e6e4130d130e3dc61b4d058a.jpg) \nFig. 4 | Interaction between CSRO regions and dislocations. a, TEM microstructure after tensile deformation, showing stored dislocations. b, c, Lattice images showing dislocations, with the [110] and [112] zone axis. Insets are Burgers circuits encircling the dislocations (marked by ‘T’ symbols) identifying Burgers vector $\\scriptstyle\\mathbf{b}={\\frac{1}{2}}[110]$ and $\\scriptstyle\\mathbf{b}={\\frac{1}{3}}[111]$ , respectively. d, e, Strain ε mapping before and after tensile deformation calculated from lattice images in the fcc phase with the [110] zone axis. The yellow band of positive strain is induced by a V-enriched column in the CSRO (see inset in d). The inset in e is a close-up view showing the edge-dislocation-induced strain field: the two coterminous fine fibre-like areas with highly contrasting positive (red) and negative (blue) strain are due to the extra half atomic plane. The dislocation strains overlap with the strains (yellow) due to CSRO. f, Upon tensile deformation, the magnitude of the strain around the CSROs increases and its distribution widens. \n\nThird, we observe that the degree of CSRO is almost the same before and after tensile deformation. Before deformation, Extended Data Fig. 1 shows that $\\overline{{d}}=0.6\\left(0.62\\right)\\mathrm{nm}$ , the areal fraction of $\\mathrm{CSRO}f_{\\mathrm{areal}}{=}14\\%$ $(25\\%)$ , and out of all CSRO regions the fraction of CSRO less than 1 $\\mathsf{n m}{}=91\\%\\left(89\\%\\right)$ , based on the dark-field image (or inverse FFT image), which are all similar to those in Fig. 2d. It appears that the plastic strain experienced is insufficient to cause marked reduction of CSRO in this ordering-prone alloy. Dislocations may spread to many planes when there is work hardening. Even when repeated dislocation shear on a slip plane would destroy chemical order towards a random mixture20, CSROs remain intact on other planes. \n\nFourth, we address how local chemical order influences the mechanical behaviour of HEAs and MEAs20–22. Here we probe into one aspect of this issue: the CSROs are expected to interact with moving dislocations. We observed profuse dislocation tangles in the fcc phase, rather than planar slip; see Fig. 4a. The full dislocations (marked by ‘T’ symbols) exhibit a high density on the order of $\\cdot3.1\\times10^{12}\\mathrm{cm}^{2}$ ; see lattice image in Fig. 4b. Viewed from the [112] zone axis (Fig. 4c), the immobile Frank dislocations are also plentiful, with a high density of $6.2\\times10^{11}\\mathrm{cm}^{2}$ . Furthermore, we conducted geometric phase analysis33 to shed light on the interaction between the CSROs and dislocations (see Methods). Specifically, the geometric phase analysis compares the atomic strain field around the CSRO, to gauge the change incurred by interactions with the dislocations trying to pass by. Figure 4d is the strain map under the [110] zone axis. The dispersed yellow regions (example shown in inset of Fig. 4d) correspond to the CSROs, showing elastic strains due to the relatively large radius of V atoms mismatched with Co and Ni. More details are in Extended Data Fig. 5, showing tensile (positive) strain due to V and compressive (negative) strain nearby. After deformation, the strain map features many slender areas of contrasting local strains (Fig. 4e); the inset shows a typical edge-dislocation-induced strain field. The extra half atomic plane of edge dislocation causes tensile strain above the slip plane (area in red), and compressive strain (area in blue) below. We note that these strain contours around the dislocations frequently reside right on top of those (yellow bands) from the CSRO. This CSRO−dislocation coupling increases the local strain around CSROs (Fig. 4f). This interaction can be understood as follows. An extra force is needed on a moving dislocation when it encounters, and has to break, the energetically favoured CSROs. This entails a trapping effect on the moving dislocations. As a result, the dislocation line migrating through the field of CSRO heterogeneities slows down, and its forward progression has to proceed via local segments cutting through and de-trapping from the local CSROs. This wavy and sluggish process is expected to increase the opportunities for dislocations to interact with one another, leading to tangles and reactions. One would then expect the CSROs to increase strain hardening during tensile deformation. \n\nWe conclude that a nominally random multi-principal-element solid solution can contain partial chemical order, even though CSROs are difficult to detect. Our fcc VCoNi provides a dataset that conclusively demonstrates substantial CSRO in a single-phase MEA with a composition near the centre of the phase diagram. Existing engineering alloys typically make use of chemically ordered intermetallics; now, in concentrated solutions such as MEAs/HEAs, we have identified their equivalent—the local chemical orders and their CSRO building blocks. The CSRO can be the same as the chemical order in a known (equilibrium) second phase; it can also be a new metastable order, including a variant/extension of a previously observed order in a related alloy. We note that although CSROs are by definition limited to (sub)nanometre spatial extents, local chemical orders built upon the CSROs can develop to long-range in some of the three dimensions. We have yet to take full advantage of these chemical heterogeneities5, which provide an opportunity to tune properties in concentrated solutions. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03428-z. \n\n# Article \n\n15.\t Ma, Y. et al. Chemical short-range orders and the induced structural transition in high-entropy alloys. Scr. Mater. 144, 64–68 (2018). \n16.\t Yin, B. L., Yoshida, S. H., Tsuji, N. & Curtin, W. A. Yield strength and misfit volumes of NiCoCr and implications for short-range-order. Nat. Commun. 11, 2507 (2020). \n17. Zhang, F. X. et al. Local structure and short-range order in a NiCoCr solid solution alloy. Phys. Rev. Lett. 118, 205501 (2017). \n18. Oh, H. S. et al. Engineering atomic-level complexity in high-entropy and complex concentrated alloys. Nat. Commun. 10, 2090 (2019). \n19.\t Ding, J., Yu, Q., Asta, M. & Ritchie, R. O. Tunable stacking fault energies by tailoring local chemical order in CrCoNi medium-entropy alloys. Proc. Natl Acad. Sci. USA 115, 8919–8924 (2018). \n20.\t Li, Q. J. et al. Strengthening in multi-principal element alloys with local-chemical-order roughened dislocation pathways. Nat. Commun. 10, 3563 (2019). \n21.\t Ding, Q. et al. Tuning element distribution, structure and properties by composition in high-entropy alloys. Nature 574, 223–227 (2019). \n22.\t Zhang, R. et al. Short-range order and its impact on the CrCoNi medium-entropy alloy. Nature 581, 283–287 (2020). \n23.\t Sohn, S. S. et al. Ultrastrong medium-entropy single-phase alloys designed via severe lattice distortion. Adv. Mater. 31, 1807142 (2019). \n24.\t Sohn, S. S. et al. High-rate superplasticity in an equiatomic medium-entropy VCoNi alloy enabled through dynamic recrystallization of a duplex microstructure of ordered phase. Acta Mater. 194, 106–117 (2020). \n25.\t Williams, D. B. & Carter, C. B. Transmission Electron Microscopy, A Textbook for Materials Science (Springer, 2009). \n26.\t Kuwano, N. et al. In situ TEM observation of long range ordering via short range order in $\\mathsf{C u}_{3}\\mathsf{P t}$ . Bull. Mater. Sci. 22, 697–700 (1999). \n27.\t Van Tendeloo, G. & Amelinckx, S. The origin of diffuse intensity in electron diffraction patterns. Phase Transit. 67, 101–135 (1998). \n28.\t Van Tendeloo, G. & Amelinckx, S. On a simple method to determine the origin of diffuse scattering in electron diffraction patterns. Scr. Metall. 20, 335–339 (1986). \n29.\t Tibshirani, R. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. 58, 267–288 (1996). \n30.\t Zunger, A. First-principles statistical mechanics of semiconductor alloys and intermetallic compounds. In Statics and Dynamics of Alloy Phase Transformations (eds Turchi, P. E. A. & Gonis, A.) 361–419 (Springer, 1994). \n31.\t Tamm, A., Aabloo, A., Klintenberg, M., Stocks, M. & Caro, A. Atomic-scale properties of Ni-based FCC ternary and quaternary alloys. Acta Mater. 99, 307–312 (2015). \n32.\t Zunger, A., Wei, S., Ferreira, L. G. & Bernard, J. E. Special quasirandom structures. Phys. Rev. Lett. 65, 353–356 (1990). \n33.\t Hÿtch, M. Quantitative measurement of displacement and strain fields from HREM micrographs. Ultramicroscopy 74, 131–146 (1998). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Methods \n\n# Materials and sample preparation \n\nThe VCoNi MEA was produced by arc-melting pure vanadium, cobalt, and nickel (all ${>}99.9\\%$ purity) and subsequently casting into a $130\\cdot\\mathrm{{mm}}$ -diameter iron mould under an argon atmosphere. To ensure homogeneity, the ingot was re-melted three times and flipped multiple times. The ingot was then hot-forged at $^{1,423\\mathsf{K}}$ to the dimensions of $10\\times10\\times50\\mathrm{mm}^{3}$ , homogenization-treated in vacuum at 1,373 K for 2 h, followed by quenching in water. The ingot was cold rolled to $90\\%$ thickness reduction, and the final cold-rolled sheets with $1.0\\:\\mathrm{mm}$ thickness were annealed at 1,173 K for 150 s for recrystallization. Differential scanning calorimetry scan at a heating rate of about 10 K per minute (similar to that in our heating to 1,173 K) demonstrates that the heat release peaks corresponding to recovery and recrystallization of the fcc phase are both over when the temperature reaches 1,173 K. Tensile specimens were cut along the rolling direction, with a gauge cross-section of $4\\times1\\mathrm{mm}^{2}$ and $15\\mathsf{m m}$ in length. The uniaxial tensile testing was performed using MTS 793 machine at room temperature and a strain rate of 5 × 10−4 s–1. \n\n# TEM techniques \n\nThe foils for TEM observations were polished to ${50}\\upmu\\mathrm{m}$ , then punched to disks 3 mm in diameter. Perforation by twin-jet electro-polishing was carried out using a solution of $20\\%$ perchloric acid and $80\\mathrm{vol\\%}$ acetic acid, at $-15^{\\circ}\\mathsf{C}$ and $50\\mathrm{mA}$ . The thin regions in the TEM specimen used for TEM experiments are about 30 nm in thickness. Atomic-resolution TEM and HAADF scanning transmission electron microscope (STEM) experiments were performed on an aberration-corrected STEM (FEI Titan Cubed Themis G2 300) operated at $300\\mathsf{k V},$ equipped with a Super-X EDS with four windowless silicon-drift detectors. The experiments used the following aberration coefficients: $_{\\mathbf{A1}\\approx2.09\\mathsf{n m}}$ , ${\\bf A}2\\approx25.7{\\mathrm{nm}}$ , ${\\mathsf B}2\\approx25.3{\\mathsf{n m}}$ , ${\\mathsf C}3\\approx828{\\mathsf{n m}}$ , ${\\bf A}3\\approx490{\\mathrm{nm}}$ , $S3\\approx98.5\\ensuremath{\\mathrm{nm}}$ , ${\\bf A}4\\approx2.99{\\upmu\\mathrm{m}}$ , ${\\mathsf{B}}4\\approx6.85\\upmu\\mathrm{m}$ , ${\\mathsf{D}}4\\approx4.74\\upmu{\\mathsf{m}}$ , ${\\bf C}5\\approx-188\\upmu\\mathrm{m}$ and $65\\approx239\\upmu\\mathrm{m}$ , ensuring ${\\tt s}0.06{\\tt n m}$ resolution under normal conditions. The nano-beam electron diffraction was performed under the TEM microprobe mode, with the electron-beam spot diameter of $35\\mathsf{n m}$ . The image was obtained using a Flucam-Viewer camera with Sensitivity 6. Quantitative EDS mapping with atomic resolution was conducted on both the samples before and after tensile testing. The count rate was in the range of 180 to 500 counts per second when acquiring atomic-resolution EDS maps. The dwell time was ${5}{\\upmu}{\\upsigma}$ per pixel with a map size of $512\\times512$ pixels; each EDS mapping took roughly 1 h to reach a high signal-to-noise ratio. \n\n# CSRO parameter \n\nWe use the Warren−Cowley order parameter3 $^4\\alpha_{\\mathrm{A-B}}^{s}{=}1{-}p_{\\mathrm{A-B}}^{s}/c_{\\mathrm{B}}$ to quantify the CSRO in each specific nearest-neighbouring shell. $\\overset{\\cdot}{p}_{\\mathtt{A-B}}^{s}$ is the fraction of species B in the sth nearest-neighbouring shell around A, and $c_{\\scriptscriptstyle\\mathrm{B}}$ is the nominal concentration of B. Positive (negative) $\\alpha_{\\mathrm{{A}}}^{s}$ −B indicates disfavoured (favoured) A–B pairs in the sth-neighbouring shell. \n\n# DFT-based modelling \n\nModelling complements experiments to understand the energetics and monitor the evolution of the ordering in VCoNi. We started with \n\n400 108-atom randomly substituted VCoNi configurations and their DFT-calculated energies, and fitted a surrogate cluster expansion model29,30 via active learning (that is, adaptive learning; see details in Supplementary Information section 3). We use the model to guide the swap Monte Carlo simulations20,31 at 1,173 K to optimize a special quasi-random structure (SQS)32 with 2,592 atoms. With progressive swap Monte Carlo simulations, the energy substantially decreases, gradually evolving to a state about 120 meV per atom lower than the SQS configuration. \n\n# Geometric phase analysis \n\nGeometric phase analysis maps out the strain field from high-resolution TEM images, from the variation of the lattice fringes across the image. FFT was performed on the atomic-resolution images from a specific zone axis. In FFT patterns, the Bragg reflections are related to different crystal planes (hkl). A perfect crystal lattice gives rise to sharply peaked frequency components, while the broadening of Bragg reflections is due to the local lattice distortion. In the VCoNi MEA, the V, Co and Ni atoms are mixed. The atomic radii for V, Co and Ni are 1.35 Å, 1.26 Å and $1.24\\mathring{\\mathsf{A}}$ , respectively. The tensile and compressive strains in the normal direction of the close-packed (111) planes are caused by the enrichment of the larger V and the smaller Co/Ni atoms, respectively. In practice, we placed a circular Gaussian mask on the reflection of (111) to obtain the strain mapping of the close-packed planes. The resolution was set at $0.25\\mathrm{nm}$ to ensure the full display of lattice strain caused by the CSRO. \n\n# Data availability \n\n# The data generated during and/or analysed during the current study are available from the corresponding author upon reasonable request. \n\n34.\t Warren, B. E. X-Ray Diffraction (Dover Publications, 1990). \n\nAcknowledgements X.W., F.Y. and P.J. were supported by the National Key Research and Development Program of the Ministry of Science and Technology of China (grant numbers 2019YFA0209900 and 2017YFA0204402), the Basic Science Center Program (grant number 11988102), the Natural Science Foundation of China (grant numbers 11972350 and 11890680), and the Chinese Academy of Sciences (grant number XDB22040503). Z.C. and J.Z. were supported by the Basic Science Center Program (grant number 51788104), the National Key Research and Development Program of the Ministry of Science and Technology of China (2016YFB0700402). E.M. thanks Xi′an Jiaotong University for supporting his work at the Center for Alloy Innovation and Design. \n\nAuthor contributions X.W. and E.M. conceived the ideas and supervised the project together with J.Z. X.C. and H.Z. performed the TEM, FFT and geometric phase analysis work. Q.W. conducted the pair correlation analysis, DFT and Monte Carlo simulations. Z.C. designed and carried out the STEM experiments. P.J. prepared the materials, samples and heat treatments. P.J., L.Z., Q.X., M.Z. and F.Y. conducted tensile testing, electron backscatter diffraction observations, and mechanical behaviour analysis. All authors participated in the discussions. X.W. and E.M. wrote the paper. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-03428-z. Correspondence and requests for materials should be addressed to J.Z., X.W. or E.M. Peer review information Nature thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n# Article \n\n![](images/47d6fc1ef205f5854d1aea4acaf6a426cd150ec817bb13d19081495f301d4c1e.jpg) \n\nExtended Data Fig. 1 | Evidence of CSRO in the fcc phase of VCoNi MEA before tensile deformation. All results are similar to those after tensile straining shown in Fig. 2. a-1, Micro-area EDP with the [112] zone axis. Arrows point to the arrays of superlattice reflections at ${\\frac{1}{2}}\\{{\\overline{{3}}}11\\} $ positions. a-2, Energy-filtered dark-field TEM image taken using extra reflections. Inset, a close-up view of the area in the dashed-line enclosed square, highlighting an area with CSROs. a-3, Statistics showing the size distribution of CSROs, observed in the dark-field TEM images and inverse FFT images. b-1, FFT pattern of the fcc phase with the [112] zone axis. The yellow circle highlights a diffuse reflection at ${\\frac{1}{2}}\\{{\\bar{3}}11\\}$ positions. b-2, Inverse FFT image showing the CSROs (circled) that are superimposed on the fcc lattice image. b-3, Maps of V, V−Co and V−Ni, respectively, showing two CSROs in two arrays by EDS mapping from the HAADF image with the [112] zone axis in an aberration-corrected TEM. All dashed lines mark the (311) planes intersecting the (111) plane in plan view: yellow: V-enriched, blue: Co-/Ni-enriched. All scale bars are $0.5\\mathsf{n m}$ . \n\n![](images/1096767c70ef2e96d37131003e09d45f6064d6039445d61c304862edc7d6a0de.jpg) \nExtended Data Fig. 2 | EDS mapping of the VCoNi alloy with the [112] zone axis. These are additional maps not included in the main text, showing the distribution of Co, Ni and ${\\mathsf{C o}}{\\mathsf{+N i}}.$ . The dashed lines in each panel mark (Co,Ni)-enriched {311} planes (blue dashed in Fig. 3), which alternate with V-enriched ones. \n\n# Article \n\n![](images/92e1ece0c5d3100c32fd13458490e5d6e90ca880f605f47ecfce96626432cd5e.jpg) \n\nExtended Data Fig. 3 | Illustration of projecting a (111) plane along [112] and [110] beam directions. V−Co(Ni) as the nearest neighbour is assumed in this idealized model to be the prevailing CSRO. The numbers 1, 3 and 4 indicate the 1st, 3rd and 4th nearest neighbours, respectively, around a centre atom C. a, Plan view of a close-packed (111) plane, projected along the [112] beam direction. The distance between the nearest points in the [110] direction is $r^{*}$ (compare with Fig. 3d). b, Plan view of the same (111) plane, observed along the [110] beam direction. Unlike for the [112] beam direction, when projected along the [110] beam direction (for example, horizontal dashed lines) the centre atom will be directly superimposed onto two unlike 1st neighbours. This mixed column, when compared with the case in a (no overlapping of unlike species in the column) blurs the difference (and hence the contrast) from the neighbouring columns. [112] is therefore the preferred beam direction to see the CSRO of interest. \n\n![](images/67b961a8486650edc5a255e5e3dde691ab59752f6559754393ecf505d7265b7e.jpg) \n\nExtended Data Fig. 4 | Schematic of element occupancy that exemplifies the CSRO taking fcc lattice sites. a, Two-dimensional lattice structure of the CSRO, deduced from experimental evidence (the alternating pattern of {311} planes in Fig. 2h and of atomic columns in the {111} plane in Fig. 3d). Note that the red (blue) spheres are meant to represent V (Co,Ni)-enriched atom positions, respectively (i.e., red is not yet V only, but still contains some Co and Ni). The boxed region shows the minimum-sized configuration of the CSRO. b, The 3D configuration of the CSRO is based on the motif (left) deduced from observations under both the [112] and [110] z.a. (to be explained in a future publication), and embedded in the fcc matrix (right). Grey spheres indicate random atoms (V,Co,Ni) without chemical order in the fcc lattice. c, Simulated diffraction pattern for the sub-nanometre CSRO configuration embedded in the fcc lattice in b, with the [112] zone axis, showing the extra reflections at the ${\\frac{1}{2}}\\{{\\bar{3}}11\\}$ positions (purple diffuse disks). \n\n# Article \n\n![](images/a44d7a25df7f4422439bd39ec00db4b6d1834ccfc95b8f77dbd8b960a2ef210d.jpg) \n\nExtended Data Fig. 5 | Strain-field analysis around the CSRO before tensile deformation. a, Geometric phase analysis strain mapping, superimposed on the lattice image taken with the [110] zone axis. The yellow striped areas with positive strain correspond to the CSROs; two red atoms $\\mathbf{\\nabla}[\\mathbf{V}_{1}$ and $\\mathbf{V}_{2})$ are displayed to represent the V-enriched columns. b, Strain distribution between the two V atoms in a. We note that the spacing between the strain peaks of neighbouring V atoms is $0.28\\mathrm{nm}$ . This figure further illustrates the elastic strains observed in Fig. 4. The atomic radii of V, Co, and Ni are 1.35 Å, 1.26 Å and $1.24\\mathring{\\mathsf{A}}$ , respectively. The larger V atoms and the smaller Co/Ni atoms induce tensile and compressive strain, respectively, in the normal direction of close-packed {111} planes. The yellow striped bands correspond to the CSROs, with tensile (positive) strain induced by the V-enriched columns in the (111) plane. Two V atoms (red) are placed in the figure to mark such columns. The strain distribution between these neighbouring columns $(\\mathsf{V}_{1}$ and $\\mathbf{V}_{2})$ is shown in b. The spacing between the two strain peaks is $0.28\\ensuremath{\\mathrm{nm}}$ (the average value is $0.3\\mathsf{n m},$ ), quite close to the measured spacing between two atomic columns $(0.26\\mathsf{n m})$ based on TEM lattice image. This corroborates that the yellow regions of positive strain are due to the V-enriched columns associated with the CSRO. Nearby regions (blue) experience compressive strain (negative). " + }, + { + "id": "10.1038_s41563-020-0797-2", + "DOI": "10.1038/s41563-020-0797-2", + "DOI Link": "http://dx.doi.org/10.1038/s41563-020-0797-2", + "Relative Dir Path": "mds/10.1038_s41563-020-0797-2", + "Article Title": "Carbazole isomers induce ultralong organic phosphorescence", + "Authors": "Chen, CJ; Chi, ZG; Chong, KC; Batsanov, AS; Yang, Z; Mao, Z; Yang, ZY; Liu, B", + "Source Title": "NATURE MATERIALS", + "Abstract": "Commercial carbazole has been widely used to synthesize organic functional materials A carbazole isomer, typically present as an impurity in commercially produced carbazole batches, is shown to be responsible for the ultralong phosphorescence observed in these compounds and their derivatives.", + "Times Cited, WoS Core": 504, + "Times Cited, All Databases": 515, + "Publication Year": 2021, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000571692500007", + "Markdown": "# Carbazole isomers induce ultralong organic phosphorescence \n\nChengjian Chen $\\oplus1$ , Zhenguo Chi $\\textcircled{1}$ 2, Kok Chan Chong1, Andrei S. Batsanov3, Zhan Yang2, Zhu Mao2, Zhiyong Yang $\\oplus2$ and Bin Liu   1,4 ✉ \n\nCommercial carbazole has been widely used to synthesize organic functional materials that have led to recent breakthroughs in ultralong organic phosphorescence1, thermally activated delayed fluorescence2,3, organic luminescent radicals4 and organic semiconductor lasers5. However, the impact of low-concentration isomeric impurities present within commercial batches on the properties of the synthesized molecules requires further analysis. Here, we have synthesized highly pure carbazole and observed that its fluorescence is blueshifted by $54\\pi m$ with respect to commercial samples and its room-temperature ultralong phosphorescence almost disappears6. We discover that such differences are due to the presence of a carbazole isomeric impurity in commercial carbazole sources, with concentrations $<0.5\\mathrm{mol}\\%$ . Ten representative carbazole derivatives synthesized from the highly pure carbazole failed to show the ultralong phosphorescence reported in the literature1,7–15. However, the phosphorescence was recovered by adding $0.1m o l\\%$ isomers, which act as charge traps. Investigating the role of the isomers may therefore provide alternative insights into the mechanisms behind ultralong organic phosphorescence1,6–18. \n\nUltralong phosphorescence, also called afterglow, results from the storage of excitation energy and the slow release of luminescence mainly via triplet states19,20. The first scientifically documented afterglow material was Bologna Stone and its afterglow was caused by impurity doping21. Two decades ago, the research interest in inorganic afterglow increased following the doping of $\\mathrm{Dy}^{3+}$ into the $\\mathrm{SrAl}_{2}\\mathrm{O}_{4}{:}\\mathrm{Eu}^{2+}$ phosphor22. Inorganic afterglow is now extensively employed to produce, for example, luminous paints, dials and emergency signs19. Compared with their inorganic counterparts, organic materials show several advantages, such as flexibility, transparency, solubility and colour tunability20. Recently, organic afterglow materials, including carbazole, dibenzothiophene, dibenzofuran, fluorene and their derivatives, have been successfully developed14. However, their hypothesized impurities have been under debate since the early 20th century6,15,23, but no solid evidence for their existence has been provided. For example, it was proposed that small traces of impurities, even after sublimation and recrystallization, contribute to phosphorescence23, although the impurity effect was ruled out nearly 40 years later following the proposal of a crystal-quality effect6. Notably, the phosphorescence of many solid organic compounds has been attributed to very small traces of impurities15,23. Therefore, identifying the molecular structures of impurities is critical for building frameworks that efficiently exploit the triplet states of organic functional materials. \n\nMore than a century ago, carbazole $(\\mathrm{Cz})$ was successfully isolated from the anthracene fraction of coal tar24, which is the current commercial source of Cz. During the past 5 years, $\\mathrm{Cz}$ derivatives have attracted considerable research interest, and many of them have directly led to the recent breakthroughs in highly efficient delayed fluorescence emitters2,3, efficient organic luminescent radicals4 and organic semiconductor lasers5. In particular, commercial $C z$ derivatives are the current focus of single-component organic ultralong phosphorescence studies1,6–14,16–18. However, fundamental inconsistencies emerged when the same compounds were repeatedly reported by different research groups7–12,15, showing obvious differences in room-temperature phosphorescence lifetimes and quantum yields. We therefore examined commercial $\\mathrm{Cz}$ from Tokyo Chemical Industry (TCI), J&K, Sigma-Aldrich (Sigma) and Aladdin. All of them showed room-temperature ultralong phosphorescence after recrystallization6, but with varying intensities and durations. Moreover, we also tried to purify $\\mathrm{Cz}$ from TCI (TCI-Cz) by performing column chromatography three times using dichloromethane:hexane $(1{:}3,\\mathrm{v}/\\mathrm{v})$ , ethyl acetate:hexane $(5{:}95,\\mathrm{v/v})$ and dichloromethane:hexane $(1{:}2,\\upnu/\\upnu)$ as the eluents, respectively, followed by recrystallization from toluene. The obtained TCI- $C\\mathbf{z}$ still showed very bright room-temperature ultralong phosphorescence, clearly visible to the naked eye. \n\nWe then synthesized highly pure $C\\mathbf{z}$ (Lab-Cz) from 2-aminobiphenyl (for details, see the Methods). Surprisingly, the fluorescence of Lab- $C\\mathbf{z}$ is blueshifted by $54\\mathrm{nm}$ as compared with that for TCI-Cz in the same crystal state (Supplementary Fig. 1), and the well-known ultralong phosphorescence almost disappears (Fig. 1a)6,8. Notably, the room-temperature ultralong phosphorescence of Lab- $C z$ crystals could not be observed by the naked eye. However, as shown in Supplementary Fig. 2, very weak luminescence from Lab- $C\\mathbf{z}$ could be captured by a Sony camera $8.3\\mathrm{ms}$ after $365\\mathrm{nm}$ light illumination had ceased (irradiation OFF), and the signal disappeared after $83.3\\mathrm{ms}$ . Under the same camera setting, the photos of TCI-Cz were all overexposed with strong luminescent and background signals. This indicates that traces of impurities play a key role in the ultralong phosphorescence. \n\nMany methods had been tried to separate the impurities but without success until high-performance liquid chromatography (HPLC) was rationalized to monitor the onset absorption at ${346}\\mathrm{nm}$ . This wavelength was essential because, when monitored at $294\\mathrm{nm}$ (Fig. 1b), the signal of the impurity was covered by the maximum absorption of the dominant $C z$ (Supplementary Fig. 3). However, at the onset absorption of $346\\mathrm{nm}$ (Fig. 1c), the impurity peak was gradually revealed as the acetonitrile:water ratio of the eluent was optimized from 95:5 to 50:50 (v/v). After isolating $\\mathrm{\\sim}10\\mathrm{mg}$ of the impurity from commercial TCI- $C\\mathbf{z}$ (for details, see the Supplementary methods), X-ray crystallography revealed its structure to be an isomer of $\\mathrm{Cz}$ , namely 1H-benzo $[f]$ indole (Bd; Fig. 1c and Supplementary Fig. 4a). The isomer Bd itself does not show room-temperature ultralong phosphorescence even in the crystal state. We further identified the same impurity from $\\mathrm{Cz}$ supplied by J&K, Sigma and Aladdin, but with different contents (Figs. 1d and 2a and Supplementary Table 1). As the isomer Bd exhibits similar reactivity to $\\mathrm{Cz}$ , we speculate that this widely found isomer could affect a variety of organic materials derived from commercial $\\mathrm{Cz}$ . \n\n![](images/296e75ed7a0d8490f7e1710f3d63bdb8618002bad272ae5c7fb95e632773e2bb.jpg) \nFig. 1 | Paradox of the ultralong phosphorescence of carbazole. a, Photographs of TCI-Cz and Lab-Cz crystals in daylight and under $365\\mathsf{n m}$ irradiation ON/OFF, together with their single-crystal structures and unit cell parameters. b,c, HPLC spectra of TCI- $\\cdot{\\mathsf{C}}z$ crystals monitored at $294\\mathsf{n m}\\left(\\mathbf{b}\\right)$ and $346{\\mathsf{n m}}$ $\\mathbf{\\eta}(\\bullet)$ with acetonitrile:water as eluent in ratios of 95:5 to 50:50 (v/v) along with the chemical structures of $\\mathsf{C}z$ and Bd. d, Commercial sourcing of $\\mathsf{C}z$ (for example, TCI, J&K, Sigma and Aladdin), mixed with its isomer Bd. \n\nTaking CPhCz and DPhCzT (Fig. 2c,d) as examples1,7, the contribution of Bd to their reported ultralong phosphorescence was studied in detail. Considering the presence of Bd in commercial Cz (Fig. 2a), TCI-CPhCz (synthesized from TCI-Cz) was carefully purified by column chromatography three times before recrystallization (for details, see the Supplementary methods). In the same single-crystal state (Fig. 2d), the purified TCI-CPhCz showed room-temperature ultralong phosphorescence, in contrast to Lab-CPhCz (synthesized from Lab- $\\cdot\\mathrm{Cz}$ ). Meanwhile, the optimized HPLC trace of the recrystallized TCI-CPhCz revealed a small trace of impurity upon monitoring at the onset absorption of $354\\mathrm{nm}$ , which was later quantified to be $0.1\\mathrm{mol}\\%$ (Fig. 2b). After isolating ${\\sim}22\\mathrm{mg}$ of the impurity from TCI-CPhCz, X-ray crystallography identified its structure as CPhBd (Fig. 2c and Supplementary Fig. 4b). CPhBd itself does not show room-temperature ultralong phosphorescence in the crystal state. We further confirmed that the synthesis of CPhBd from Bd could be scaled up by using the same method as that used for the synthesis of CPhCz from $\\mathrm{Cz}$ (Supplementary Scheme 1)7. Similarly, following the procedure for the synthesis of DPhCzT from $C z$ (ref. 1), DPhBdT (Fig. 2c) was synthesized from Bd and no room-temperature ultralong phosphorescence was observed by the naked eye. \n\n![](images/3d99dfece3be8977aa5dfee31e7e357d73c5ea6bf61b13316fcbe40881426989.jpg) \nFig. 2 | Impurity effect on carbazole derivatives. a,b, HPLC spectra recorded at the onset absorption of $346{\\mathsf{n m}}$ for $\\mathsf{C}z$ (a) and $354\\mathsf{n m}$ for $\\mathsf{C P h C z}$ (b) obtained from commercial and laboratory-synthesized sources. Elapsed time aberrations caused by injections are shifted by setting Lab- $\\cdot{\\mathsf{C}}z$ and Lab-CPhCz as references, respectively. c, Chemical structures of CPhCz, CPhBd, DPhCzT and DPhBdT. d, Photographs of $\\mathsf{C P h C z}$ and $\\mathsf{D P h C z T}$ crystalline powders in daylight and under $365\\mathsf{n m}$ irradiation ON/OFF together with their single-crystal structures and unit cell parameters. TCI-CPhCz and TCI-DPhCzT were synthesized from TCI-Cz. Lab-CPhCz and Lab-DPhCzT were synthesized from Lab-Cz. \n\nTo explore the generality of the phenomenon, another eight representative $C z$ derivatives with reported ultralong phosphorescence were also investigated (Supplementary Fig. 5)1,7–15. It was found that their reported ultralong phosphorescence was only observed by the naked eye with the crystals synthesized from TCI- $C\\mathbf{z}$ , but not from Lab-Cz. Taking all these results together, we propose that the presence of isomer Bd in commercial $C\\mathbf{z}$ is responsible for their reported ultralong phosphorescence. This also indicates that the widespread presence of Bd should be taken into consideration in other organic semiconductors directly synthesized from commercial $\\mathrm{Cz}$ without proper exclusion of the isomer, especially those being used in optoelectronic applications2–5,25. Furthermore, ultralong phosphorescence could be observed in Bd/Lab-Cz even in the presence of $0.01\\mathrm{mol}\\%$ Bd (Supplementary Fig. 6b), implying that isomer doping is extremely effective. This ultralow content also explains why the impurity effect has largely been ignored so far1,6–14. \n\nTo understand how the isomer affects ultralong phosphorescence, the emission characteristics of Bd/Lab-Cz, CPhBd/ CPhCz and DPhBdT/DPhCzT were investigated with 0, 0.5, 1, 5, 10 and $100\\mathrm{mol\\%}$ isomer dopant in the crystalline state (Fig. 3 and Supplementary Fig. 7). The isomer-doping effect of ultralong phosphorescence was corroborated because each pair of $0.5\\mathrm{mol}\\%$ Bd/Lab-Cz and TCI- $C z$ (Fig. 3a), $0.5\\mathrm{mol}\\%$ CPhBd/CPhCz and TCI-CPhCz (Fig. 3b), and $0.5\\mathrm{mol}\\%$ DPhBdT/DPhCzT and TCI-DPhCzT (Fig. 3c) showed nearly identical prompt and delayed spectra. More importantly, even with $0.1\\mathrm{mol}\\%$ isomer doping, the above doped systems showed effective room-temperature ultralong phosphorescence (Supplementary Fig. 6). Meanwhile, the phosphorescent emission from the crystalline powders was stable in air (Supplementary Fig. 8) and their doped polymer films also showed room-temperature ultralong phosphorescence (Supplementary Fig. 9). \n\n![](images/211d52405df89d64d2a4d2a843aebfa258d59ea651c2f27c60f68e1b739c20bc.jpg) \nFig. 3 | Emission characteristics with different isomer doping concentrations. a–c, Photoluminescence (PL) spectra of crystalline powders resolved into prompt and delayed (8 ms) components for $0.5\\mathsf{m o l\\%}$ Bd/Lab- $\\cdot{\\mathsf{C}}z$ and TCI- $.C z$ (a), $0.5\\mathsf{m o l\\%}$ CPhBd/CPhCz and TCI-CPhCz (b), and $0.5\\mathrm{mol}\\%$ DPhBdT/ $\\mathsf{D P h C z T}$ and TCI-DPhCzT (c) at room temperature in air. $\\mathbf{d}{\\mathbf{-}}\\mathbf{f},$ Prompt components of the PL of crystalline powders with 0, 0.5, 1, 5, 10 and $100\\mathrm{mol}\\%$ isomer dopant in Bd/Lab-Cz (d), CPhBd/CPhCz (e) and DPhBdT/DPhCzT (f). g–i, Delayed $(8\\mathsf{m s})$ components of the PL after $365\\mathsf{n m}$ excitation OFF for crystalline powders with 0, 0.5, 1, 5, 10 and $100m o l\\%$ isomer dopant in Bd/Lab- $\\cdot{\\mathsf{C}}z\\left(\\mathbf{g}\\right)$ , CPhBd/CPhCz (h) and DPhBdT/DPhCzT (i). j–l, Photographs of crystalline powders with 0.5, 1, 5 and $10\\mathrm{mol}\\%$ isomer dopant in $\\mathsf{B d}/\\mathsf{C z}\\left(\\mathbf{j}\\right)$ , CPhBd/CPhCz (k) and DPhBdT/DPhCzT (l). Excitation at $310\\mathsf{n m}$ was used for the prompt spectra in a, c and d and excitation at $365\\mathsf{n m}$ for all other measurements. \n\nAs for the the prompt emission (Fig. 3d–f), the fluorescence of Bd/Lab-Cz, CPhBd/CPhCz and DPhBdT/DPhCzT is redshifted with increasing dopant content, implying that Lab-Cz could benefit the development of deep-blue emitters as compared with those based on commercial $\\mathrm{Cz}$ (ref. 25). Moreover, the distinct differences (solid lines in Fig. 3d–f) between the prompt emissions from each pair of isomers indicate that $\\mathrm{Cz}$ and Bd possess totally different electron-donating capabilities. In addition, the well-resolved fluorescence in Fig. 3d,f indicates that the emission is from the local-excited (LE) states, whereas the broad fluorescence in Fig. 3e is characteristic of charge-transfer (CT) emission18,26. \n\nFigure $3\\mathrm{g}$ shows the delayed LE emission of Bd/Lab-Cz, with one band at $364-543\\mathrm{nm}$ and another newly generated band at \n\n$544-836\\mathrm{nm}$ at $8\\mathrm{ms}$ delay after photoexcitation at room temperature. The short-wavelength band of the delayed component varies with dopant concentration, which is in agreement with the prompt emission (dashed lines in Fig. 3d), indicating that the fluorescence of Bd is involved in the delayed emission. The long-wavelength band shows the highest intensity of delayed emission at $1\\mathrm{mol\\%}$ doping. A similar phenomenon of LE delayed emission is observed for DPhBdT/DPhCzT (Fig. 3i). For CPhBd/CPhCz, presented in Fig. 3h, the negligible CT delayed emission and obvious LE delayed emission with a maximum at $5\\mathrm{mol\\%}$ should result from CT to LE intersystem crossing26,27. The delayed emission characteristics indicate that singlet and triplet excited states are simultaneously generated (Supplementary Fig. 10). Representative photographs of samples with isomer doping at varying concentrations are shown in Fig. 3j–l. \n\nRoom-temperature ultralong phosphorescence based on isomer doping differs from most design paradigms $\\cdot^{1,7-9,14,15,17,20,28}$ . The very similar molecular structure and size (Supplementary Fig. 11) allow the isomers to interact tightly28 and generate beneficial defects to store excitation energy. To explore the mechanism, transient absorption spectra were obtained by subtracting the absorbance spectrum recorded before photoexcitation from that recorded $8\\mathrm{ms}$ after photoexcitation20, so that the delayed emission (negative absorption) and transient absorption (positive absorption) spectra were synchronously recorded (Fig. 4a–c and Supplementary Fig. 12). The broad absorption bands with peaks located at \n\n![](images/11f710c3a0ab8dcb1775c44e4f9347623c3d8b6312a8c0333eec16538b8cd277.jpg) \nFig. 4 | Transient absorption, photoluminescence and ultralong phosphorescence mechanism. a–c, Photoinduced transient absorption (TA) spectra of crystalline powders with 0, 1, 5 and $10\\mathrm{mol}\\%$ isomer dopant in Bd/Lab- $.C z$ (a), CPhBd/CPhCz (b) and DPhBdT/DPhCzT (c). d, Prompt emission at 77 K and delayed emission at $8\\mathsf{m s}$ at room temperature for crystalline powders of Bd/CPhCz, Bd/DPhCzT, CPhBd/Cz and DPhBdT/Cz with $5m o l\\%$ cross-doping. e, Photographs of crystalline powders of Bd/CPhCz, Bd/DPhCzT, CPhBd/Cz and DPhBdT/Cz with 5 mol% cross-doping under $365\\mathsf{n m O N}$ , OFF, OFF $0.2\\mathsf{s}$ and OFF 1 s. f, Proposed mechanism of ultralong phosphorescence (Phos.) with $\\mathsf{B d}/\\mathsf{C}z$ as an example. Left: charge transfer during photoexcitation. Type I: electrons from the LUMO of Bd are transferred to the LUMO of Cz. Type II: electrons from the HOMO of Bd are transferred to the HOMO of Cz. Middle: charge-separated states are formed with $\\mathsf{C}z$ radical anions diffusing to neighbouring Cz, whereas Bd radical cations are trapped by defects. Note that intrinsic lattice defects may occur spontaneously during crystal growth. Right: singlets (for example, S1) and triplets (for example, ${\\sf T}_{1})$ are generated from charge recombination (CR) and intersystem crossing (ISC) of $\\mathsf{S}_{1}$ to $T_{\\scriptscriptstyle1}$ is enabled. \n\n$460{-}475\\mathrm{nm}$ were ascribed to radical ions20, which were generated by charge separation. In the absence of doping (black lines in Fig. 4a–c), the spectra showed only noise $8\\mathrm{ms}$ after photoexcitation had ceased, indicating that charge-separated states were not generated in the Lab-Cz, Lab-CPhCz and Lab-DPhCzT crystals. Therefore, their reported ultralong phosphorescence was not observed by the naked eye (Figs. 1a, 2d and $3\\mathrm{g-i})^{1,6,7}$ . By contrast, with doping (coloured lines in Fig. 4a–c), delayed emission and transient absorption of charge-separated states were simultaneously captured, indicating that ultralong phosphorescence results from charge-separated states20. Further, comparing $5\\mathrm{mol\\%}$ CPhBd/ CPhCz with CPhBd (Supplementary Fig. 13a), the transient absorption spectra recorded from $8\\mathrm{ms}$ to 1 s showed that the absorption and emission intensities decrease simultaneously with time, whereas the noise spectrum of CPhBd at $8\\mathrm{ms}$ delay after photoexcitation implies no charge-separated states in the CPhBd crystals. \n\nOwing to their different electron-donating capabilities, Cz and Bd moieties in close proximity could act as a microplanar heterojunction to generate photoinduced charge-separated states. To validate our hypothesis, we designed $5\\mathrm{mol\\%}$ cross-doping systems of Bd/CPhCz, Bd/DPhCzT, CPhBd $\\mathrm{\\DeltaCz}$ and DPhBdT/Cz. By comparing the prompt emission at $77\\mathrm{K}$ with the delayed emission at room temperature (Fig. 4d), the $5\\mathrm{mol\\%}$ cross-doping systems were found to emit ultralong phosphorescence with peaks located at $525\\mathrm{-}675\\mathrm{nm}$ , which were a result of the newly generated charge-separated states (Supplementary Fig. 13b). Photographs of their ultralong phosphorescence are shown in Fig. 4e. \n\nTo further elucidate the mechanism, we studied the simple Bd/ $\\mathrm{Cz}$ doping system as an example (Fig. 4f). The highest-occupied molecular orbital (HOMO) and lowest-unoccupied molecular orbital (LUMO) energy levels were calculated from the cyclic voltammetry and absorption data presented in Supplementary Fig. 14. During photoexcitation, two types of charge transfer could occur between Bd and $\\mathrm{Cz}$ , inducing the generation of $C\\mathbf{z}$ radical anions (Supplementary Fig. 15) and Bd radical cations20. The $\\mathrm{Cz}$ radical anions diffuse through the crystals and the Bd radical cations are trapped by defects, leading to the formation of charge-separated states. Consequently, ultralong phosphorescence results from gradual charge recombination of the charge-separated states in the trap/ detrap model of defects. \n\nIn summary, comparison between laboratory-synthesized and commercial sources of $\\mathrm{Cz}$ in combination with the optimization of HPLC separation offers a feasible solution to impurity conundrums that is applicable to other systems, such as commercial dibenzothiophene and dibenzofuran (Supplementary Fig. 16). Our studies reveal that the isomer Bd widely found in commercial $C z$ can be synchronously derivatized into many organic functional materials, forming isomer-doping systems that activate ultralong phosphorescence. The identification of the Bd molecular structure opens up completely different molecular design principles to manage triplet states in the development of organic functional materials. This discovery also has motivated us to design and study the isomer effect in various organic functional materials, and is an area of on-going research in our laboratory. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/ s41563-020-0797-2. \n\nReceived: 18 December 2019; Accepted: 10 August 2020; Published: xx xx xxxx \n\n# References \n\n1.\t An, Z. et al. Stabilizing triplet excited states for ultralong organic phosphorescence. Nat. Mater. 14, 685–690 (2015). \n2.\t Uoyama, H., Goushi, K., Shizu, K., Nomura, H. & Adachi, C. Highly efficient organic light-emitting diodes from delayed fluorescence. Nature 492, 234–238 (2012). \n3.\t Hamze, R. et al. Eliminating nonradiative decay in $\\mathtt{C u(I)}$ emitters: ${>}99\\%$ quantum efficiency and microsecond lifetime. Science 363, 601–606 (2019). \n4.\t Ai, X. et al. Efficient radical-based light-emitting diodes with doublet emission. Nature 563, 536–540 (2018). \n5.\t Sandanayaka, A. S. D. et al. Indication of current-injection lasing from an organic semiconductor. Appl. Phys. Express 12, 061010 (2019). \n6.\t Bilen, C. S., Harrison, N. & Morantz, D. J. Unusual room temperature afterglow in some crystalline organic compounds. Nature 271, \n235–237 (1978). \n7.\t Cai, S. et al. Visible-light-excited ultralong organic phosphorescence by manipulating intermolecular interactions. Adv. Mater. 29, 1701244 (2017). \n8.\t Xie, Y. et al. How the molecular packing affects the room temperature phosphorescence in pure organic compounds: ingenious molecular design, detailed crystal analysis, and rational theoretical calculations. Adv. Mater. 29, \n1606829 (2017). \n9.\t Xiong, Y. et al. Designing efficient and ultralong pure organic room-temperature phosphorescent materials by structural isomerism. Angew. Chem. Int. Ed. 57, 7997–8001 (2018). \n10.\tZhang, T. et al. Pure organic persistent room-temperature phosphorescence at both crystalline and amorphous states. ChemPhysChem 19, 2389–2396 (2018). \n11.\tGong, Y. et al. Achieving persistent room temperature phosphorescence and remarkable mechanochromism from pure organic luminogens. Adv. Mater. \n27, 6195–6201 (2015). \n12.\tYang, Z. et al. Intermolecular electronic coupling of organic units for efficient persistent room-temperature phosphorescence. Angew. Chem. Int. Ed. 55, \n2181–2185 (2016). \n13.\tFateminia, S. M. A. et al. Organic nanocrystals with bright red persistent room-temperature phosphorescence for biological applications. Angew. Chem. Int. Ed. 56, 12160–12164 (2017). \n14.\tKenry, Chen,C. & Liu, B. Enhancing the performance of pure organic room-temperature phosphorescent luminophores. Nat. Commun. 10, \n2111 (2019). \n15.\tXue, P. et al. Correction: Bright persistent luminescence from pure organic molecules through a moderate intermolecular heavy atom effect. Chem. Sci. \n8, 6691–6691 (2017). \n16.\tGu, L. et al. Dynamic ultralong organic phosphorescence by photoactivation. Angew. Chem. Int. Ed. 57, 8425–8431 (2018). \n17.\tZhao, W. et al. Boosting the efficiency of organic persistent room-temperature phosphorescence by intramolecular triplet-triplet energy transfer. Nat. Commun. 10, 1595 (2019). \n18.\tMao, Z. et al. Two-photon-excited ultralong organic room temperature phosphorescence by dual-channel triplet harvesting. Chem. Sci. 10, \n7352–7357 (2019). \n19.\tLi, Y., Gecevicius, M. & Qiu, J. Long persistent phosphors—from fundamentals to applications. Chem. Soc. Rev. 45, 2090–2136 (2016). \n20.\tKabe, R. & Adachi, C. Organic long persistent luminescence. Nature 550, \n384–387 (2017). \n21.\tLastusaari, M. et al. The Bologna Stone: history’s first persistent luminescent material. Eur. J. Miner. 24, 885–890 (2012). \n22.\tMatsuzawa, T., Aoki, Y., Takeuchi, N. & Murayama, Y. A new long phosphorescent phosphor with high brightness, $\\mathrm{SrAl}_{2}\\mathrm{O}_{4};\\mathrm{Eu}^{2+},\\mathrm{Dy}^{3+}.$ J. Electrochem. Soc. 143, 2670–2673 (1996). \n23.\tClapp, D. B. The phosphorescence of tetraphenylmethane and certain related substances. J. Am. Chem. Soc. 61, 523–524 (1939). \n24.\tGraebe, C. & Glaser, C. Ber. Dtsch. Chem. Ges. 5, 12 (1872). \n25.\tFeng, H. et al. Tuning molecular emission of organic emitters from fluorescence to phosphorescence through push-pull electronic effects. Nat. Commun. 11, 2617 (2020). \n26.\tChen, C. et al. Intramolecular charge transfer controls switching between room temperature phosphorescence and thermally activated delayed fluorescence. Angew. Chem. Int. Ed. 57, 16407–16411 (2018). \n27.\tNoda, H. et al. Critical role of intermediate electronic states for spin-flip processes in charge-transfer-type organic molecules with multiple donors and acceptors. Nat. Mater. 18, 1084–1090 (2019). \n28.\t Bolton, O., Lee, K., Kim, H.-J., Lin, K. Y. & Kim, J. Activating efficient phosphorescence from purely organic materials by crystal design. Nat. Chem. \n3, 205–210 (2011). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 \n\n# Methods \n\nThe syntheses, isolation of Bd from TCI-Cz, preparation of doping systems and polymer films, growth of single crystals, photographs and time-dependent density functional theory calculations are fully described in the Supplementary methods. \n\nMaterials. Commercial carbazoles were obtained from TCI (product of Japan, $\\mathrm{C}0032\\mathrm{-}100\\mathrm{g})$ , J&K (product of Beijing, 601413-250 g), Sigma-Aldrich (product of Germany, C5132-100 g) and Aladdin (product of Shanghai, C104875-100 g), and were further recrystallized from toluene before use. After customized synthesis by Arch Bioscience, Bd was further purified by column chromatography (ethyl acetate:hexane, 5:95, v/v) and then recrystallized from hexane. White sheet crystals were obtained $(\\sim5\\%$ , total purification yield) that have a different odour from Lab-Cz. Commercial dibenzothiophene was purchased from Sigma-Aldrich (product of Belgium, D32202-25 g), commercial dibenzofuran was purchased from TCI (product of Japan, D0147-25 g) and 2-aminobiphenyl was purchased from Combi-Blocks (product of USA, QS7870-25 g). Biphenyl-2-thiol was ordered from ChemCollect (product of Germany, ChemCol-DP000316-5 g). Tetrahydrofuran was distilled with sodium/benzophenone. All solvents were HPLC grade from Fisher Chemicals unless noted otherwise, and ultrapure water was produced by using SMART2PURE (ThermoFisher). All other chemicals were obtained from commercial sources and used as received unless noted otherwise. \n\nSynthesis of Lab-Cz. Lab- $C\\mathbf{z}$ was synthesized as described previously (Supplementary Scheme $1)^{29,30}$ . 2-Aminobiphenyl $(0.85\\mathrm{g},5.0\\mathrm{mmol}$ ) was dissolved in a degassed solution containing $6.0\\mathrm{ml}$ ultrapure water and $1.0\\mathrm{ml}$ concentrated sulfuric acid at $50^{\\circ}\\mathrm{C}$ . After stirring at $50^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ , the resulting solution was cooled to $0^{\\circ}\\mathrm{C}$ in an ice–water bath and a solution of $0.42\\mathrm{g}\\left(6.1\\mathrm{mmol}\\right)$ sodium nitrite in $4.7\\mathrm{ml}$ ultrapure water was added dropwise. The solution was stirred in the ice–water bath for $30\\mathrm{min}$ . A solution of $0.56\\mathrm{g}$ $8.6\\mathrm{mmol};$ sodium azide in $3.5\\mathrm{ml}$ ultrapure water was then added dropwise to the cold solution and the mixture stirred for a further 1 h. The mixture was then filtered and washed with $\\boldsymbol{100}\\mathrm{ml}$ of a $2\\mathbf{M}$ potassium carbonate solution three times and then with $300\\mathrm{ml}$ ultrapure water five times. Afterwards, the filtrate was dissolved in dichloromethane (DCM) and purified by column chromatography with DCM:hexane $(1{:}3,\\mathrm{v}/\\mathrm{v})$ ) as eluent to yield 2-azidobiphenyl as a light-yellow oil $\\mathbf{(0.94g}$ 4.8 mmol, $96\\%$ yield). The above procedure was repeated several times to produce a sufficient amount of 2-azidobiphenyl. \n\n2-Azidobiphenyl $(4.09,23.7\\mathrm{mmol}$ ) was then dissolved in $60\\mathrm{ml}$ acetone and added to a mixture of $\\boldsymbol{100}\\mathrm{ml}$ acetone and $\\boldsymbol{100}\\mathrm{ml}$ ultrapure water. Silica gel $(5.0\\mathrm{g})$ was subsequently added and the mixture stirred for $24\\mathrm{h}$ under the illumination of two HITACHI F6T5 6 W fluorescent lamps, which led to a change in the colour of the mixture from colourless to brown. The set-up for this photochemical step is shown in detail in Supplementary Fig. 17. Furthermore, the reaction solvent was maintained at $260\\mathrm{ml}$ by adding acetone every $^{8\\mathrm{h}}$ . Throughout the whole reaction, the mixture was covered with tin foil. After removing the solvent on a rotary evaporator, the mixture was purified by column chromatography using DCM:hexane $(1{:}3,\\mathrm{v}/\\mathrm{v})$ ) as the eluent to yield the product $\\mathrm{Cz}$ as a white powder. $C\\mathbf{z}$ was further purified by column chromatography two more times using ethyl acetate:hexane $(5{:}95,\\mathrm{v/v})$ and DCM:hexane $(1{:}2,\\mathbf{v}/\\mathbf{v})$ as eluents, respectively. After this column chromatographic purification procedure, the product was recrystallized from toluene to yield Lab- $C\\mathbf{z}$ $(1.2\\mathrm{g}$ , 7.2 mmol, $30\\%$ yield) as white sheet crystals. The melting point of Lab- $\\mathrm{Cz}$ was $246.9^{\\circ}\\mathrm{C},$ and this value is compared with those of commercial carbazole samples in Supplementary Fig. 18. \n\nGeneral. HPLC purifications were conducted using a Waters 2545 Binary Gradient Module, Waters 2707 Autosampler and Waters Fraction Collector III with an XBridge Prep C18 OBD ${5\\upmu\\mathrm{m}}$ ( $50\\mathrm{mm}\\times150\\mathrm{mm}$ ) column at a flow rate of $20.00\\mathrm{ml}\\mathrm{min}^{-1}$ . The injection volume for $\\mathrm{Cz}$ purification was $^{1,500\\upmu\\mathrm{l}}$ at $10.0\\mathrm{mg}\\mathrm{ml}^{-1}$ and the injection volume for CPhCz purification was $^{1,700\\upmu\\mathrm{l}}$ at $4.0\\mathrm{mg}\\mathrm{ml}^{-1}$ . DPhCzT was not sufficiently soluble in methanol or acetonitrile and hence no impurity peak was revealed by HPLC using the C18 column. Purifications by silica gel column chromatography were performed using DAVISIL silica LC60A $40{-}63\\upmu\\mathrm{m}$ purchased from GRACE and monitored using thin-layer chromatography silica gel plates with a coating thickness of $0.2\\mathrm{-}0.25\\mathrm{mm}$ from SANPONT. NMR spectra were recorded with a Bruker Avance-III 400 NanoBay HD NMR spectrometer at ambient temperature. High-resolution mass spectrometry was performed with a Bruker AmaZon X LC-MS spectrometer with electrospray ionization. The $\\mathrm{HOMOs^{26}}$ were determined by cyclic voltammetry data obtained using a BioLogic VMP-300 instrument in DCM $(99.9\\%$ , Super Dry, stabilized, J&K Seal) containing $5\\times10^{-4}\\mathrm{M}$ sample and 0.1 M $\\mathrm{Bu}_{4}\\mathrm{NPF}_{6}$ electrolyte with a glassy carbon working electrode, a platinum disk counter electrode and \n\na $\\mathrm{Ag/AgCl}$ reference electrode (calibrated against ferrocene) at $100\\mathrm{mVs^{-1}}$ . The LUMOs were determined from the ultraviolet-visible (UV-Vis) absorption spectra recorded using an Hitachi U-3900 spectrophotometer. Melting points were measured by differential scanning calorimetry (DSC) using a NETZSCH DSC $204~\\mathrm{F1}$ Phoenix instrument at a heating rate of $10\\mathrm{Kmin^{-1}}$ under the protection of nitrogen. The melting points were determined from the DSC curves from the second heating process. The onset values were considered the melting points, determined by ‘NETZSCH Proteus Thermal Analysis’ software. UV-Vis absorption spectra of solutions and solids were recorded on Shimadzu UV-1700 and UV3600 ultraviolet-visible-near-infrared (UV-Vis-NIR) spectrometers, respectively. X-ray diffraction experiments were carried out on a four-circle goniometer Kappa geometry Bruker D8 Venture diffractometer with a PHOTON 100 CMOS active pixel sensor detector. \n\nOptical measurements. The PL spectra of crystalline powders of $5\\mathrm{mol\\%}$ Bd/ Lab-Cz, $5\\mathrm{mol\\%}$ CPhBd/CPhCz and $5\\mathrm{mol\\%}$ DPhBdT/DPhCzT were measured in air and vacuum using an Edinburgh FLS980 instrument with an OXFORD Optistat DN cryostat as the sample holder. After vacuum-pumping for $30\\mathrm{min}$ , the emissions of the crystalline samples were measured in a vacuum. Transient decay spectra, temperature-dependent PL spectra and PL quantum yields (PLQYs) were measured using a Jobin-Yvon-Horiba FL-3 spectrofluorimeter equipped with a calibrated integrating sphere. Notably, the PLQYs of these doping systems were randomly fluctuant, which was probably caused by changes in the emission intensity upon prolonging the photoirradiation16, and hence the PLQYs are not reported here. Time-resolved PL spectra (room temperature and $77\\mathrm{K})^{18}$ and photoinduced TA spectra (ambient temperature)20 were obtained in air using an Ocean Optics QE65 Pro CCD with Ocean Optics LED-365 and LED-310 as excitation sources and an Ocean Optics DH-2000-BAL as UV-Vis-NIR light source, which were assembled as reported previously. \n\n# Data availability \n\nThe data that support the findings of this study are available from C.C. and L.B. upon reasonable request. The X-ray crystallographic data for the structures reported here have been deposited at the Cambridge Crystallographic Data Centre (CCDC) under deposition numbers CCDC 1953802–1953811 and 2019581–2019589. These data can be obtained free of charge from the Cambridge Crystallographic Data Centre at www.ccdc.cam.ac.uk/data_request/cif. Source data are provided with this paper. \n\n# References \n\n29.\tUllah, E., McNulty, J. & Robertson, A. Highly chemoselective mono-Suzuki arylation reactions on all three dichlorobenzene isomers and applications development. Eur. J. Org. Chem. 2012, 2127–2131 (2012). \n30.\tYang, L., Zhang, Y., Zou, X., Lu, H. & Li, G. Visible-light-promoted intramolecular C–H amination in aqueous solution: synthesis of carbazole. Green. Chem. 20, 1362–1366 (2018). \n\n# Acknowledgements \n\nThis study was supported by the Singapore National Research Foundation (NRF) Competitive Research Program (R279-000-483-281), the NRF Investigatorship (R279- 000-444-281) and the National University of Singapore (R279-000-482-133). \n\n# Author contributions \n\nC.C. and B.L. designed the experiments. C.C. optimized the HPLC and grew crystals. C.C., Z.C., Z.Y., Z.M. and Z.Y. contributed to the optical characterizations. C.C. and K.C.C. synthesized all compounds. A.S.B. and C.C. solved the crystal structures. C.C. and B.L. discussed the results and drafted the manuscript. B.L. supervised the project. All authors contributed to the proofreading of the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information Supplementary information is available for this paper at https://doi.org/10.1038/s41563-020-0797-2. Correspondence and requests for materials should be addressed to B.L. Reprints and permissions information is available at www.nature.com/reprints. " + }, + { + "id": "10.1038_s41929-020-00545-2", + "DOI": "10.1038/s41929-020-00545-2", + "DOI Link": "http://dx.doi.org/10.1038/s41929-020-00545-2", + "Relative Dir Path": "mds/10.1038_s41929-020-00545-2", + "Article Title": "Identification of durable and non-durable FeNx sites in Fe-N-C materials for proton exchange membrane fuel cells", + "Authors": "Li, JK; Sougrati, MT; Zitolo, A; Ablett, JM; Oguz, IC; Mineva, T; Matanovic, I; Atanassov, P; Huang, Y; Zenyuk, I; Di Cicco, A; Kumar, K; Dubau, L; Maillard, F; Drazic, G; Jaouen, F", + "Source Title": "NATURE CATALYSIS", + "Abstract": "While Fe-N-C materials are a promising alternative to platinum for catalysing the oxygen reduction reaction in acidic polymer fuel cells, limited understanding of their operando degradation restricts rational approaches towards improved durability. Here we show that Fe-N-C catalysts initially comprising two distinct FeNx sites (S1 and S2) degrade via the transformation of S1 into iron oxides while the structure and number of S2 were unmodified. Structure-activity correlations drawn from end-of-test Fe-57 Mossbauer spectroscopy reveal that both sites initially contribute to the oxygen reduction reaction activity but only S2 substantially contributes after 50 h of operation. From in situ Fe-57 Mossbauer spectroscopy in inert gas coupled to calculations of the Mossbauer signature of FeNx moieties in different electronic states, we identify S1 to be a high-spin FeN4C12 moiety and S2 a low- or intermediate-spin FeN4C10 moiety. These insights lay the groundwork for rational approaches towards Fe-N-C cathodes with improved durability in acidic fuel cells.", + "Times Cited, WoS Core": 491, + "Times Cited, All Databases": 511, + "Publication Year": 2021, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000599021700001", + "Markdown": "# Identification of durable and non-durable FeN sites in Fe–N–C materials for proton exchange membrane fuel cells \n\nJingkun Li1,9, Moulay Tahar Sougrati $\\oplus1$ , Andrea Zitolo $\\textcircled{10}2$ , James M. Ablett2, Ismail Can Oğuz   1, Tzonka Mineva $\\oplus1$ , Ivana Matanovic3,4, Plamen Atanassov $\\textcircled{10}5$ , Ying Huang $\\textcircled{10}5$ , Iryna Zenyuk $\\textcircled{10}$ 5, Andrea Di Cicco6, Kavita Kumar7, Laetitia Dubau7, Frédéric Maillard   7, Goran Dražić8 and Frédéric Jaouen   1 ✉ \n\nWhile Fe–N–C materials are a promising alternative to platinum for catalysing the oxygen reduction reaction in acidic polymer fuel cells, limited understanding of their operando degradation restricts rational approaches towards improved durability. Here we show that Fe–N–C catalysts initially comprising two distinct FeNx sites (S1 and S2) degrade via the transformation of S1 into iron oxides while the structure and number of S2 were unmodified. Structure–activity correlations drawn from end-of-test $57F e$ Mössbauer spectroscopy reveal that both sites initially contribute to the oxygen reduction reaction activity but only S2 substantially contributes after 50 h of operation. From in situ 57Fe Mössbauer spectroscopy in inert gas coupled to calculations of the Mössbauer signature of $\\pmb{\\mathbb{F}}\\pmb{\\mathrm{e}}\\pmb{\\mathbb{N}}_{\\pmb{x}}$ moieties in different electronic states, we identify S1 to be a high-spin $F e N_{4}C_{12}$ moiety and $\\$2a$ low- or intermediate-spin $F e N_{4}C_{10}$ moiety. These insights lay the groundwork for rational approaches towards Fe–N–C cathodes with improved durability in acidic fuel cells. \n\natalysis of the oxygen reduction reaction (ORR) is a cornerstone of industrially relevant electrochemical devices1 that convert chemical energy into electric power (metal–air batteries2,3, fuel cells $(\\mathrm{FCs})^{2,4,5},$ ) or electric power into high-added value products $\\mathrm{(H}_{2}\\mathrm{O}_{2},$ refs. 6–8, $\\mathrm{Cl}_{2}$ with oxygen-depolarized cathodes9–11). The $\\mathrm{\\pH}$ in those devices establishes the ground for selecting materials with promising ORR activity and durability. While proton exchange membrane FCs (PEMFCs) are appealing12, their acidic environment is challenging. Platinum-based catalysts now reach high activity and durability13,14, but catalysts free of Pt group metals remain topical for cost and sustainability reasons. Although metal–nitrogen–carbon (M–N–C) catalysts ${\\bf\\dot{M}}={\\bf F}{\\bf e}$ , Co) have demonstrated high ORR activity15–18, their durability in PEMFC is poor. Their most active sites are atomically dispersed $\\mathrm{MN}_{x}$ moieties15,16,18, and main degradation mechanisms in acidic medium are demetallation19–23, surface carbon oxidation via Fenton reactions24,25, bulk carbon corrosion21,26,27 and protonation of nitrogen groups followed by anion adsorption—a phenomenon particularly important for $\\mathrm{Fe-N-C}$ catalysts comprising highly basic N groups28. Exacerbated demetallation was recently reported in oxygenated acid medium for highly active $\\mathrm{NH}_{3}$ -pyrolysed Fe–N–C catalysts, explaining their poor durability in PEMFC22,29. The demetallation rate was measured online in acidic aqueous condition29, or indirectly assessed by 57Fe Mössbauer spectroscopy22. In contrast, high stability in acidic medium was reported by us for \n\ntwo catalysts exclusively comprising $\\mathrm{FeN}_{x}$ moieties, with only $25\\%$ activity decrease after 30,000 load cycles in Ar-saturated $0.1\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at $80^{\\circ}\\mathrm{C}$ (ref. 21). However, after 10,000 load cycles in the same conditions but in $\\mathrm{~O}_{2}$ -saturated electrolyte, the decrease in activity and number of $\\mathrm{FeN}_{x}$ moieties was 65 and $83\\%$ , respectively, forming iron oxide particles during cycling30. Carbon corrosion was observed from Raman spectroscopy after load cycles in $\\mathrm{~O}_{2}$ -saturated electrolyte30, while restricted changes in cyclic voltammetry (restricted carbon corrosion) was observed by Dodelet et al. for an $\\mathrm{NH}_{3}$ -pyrolysed Fe–N–C after a voltage hold of $6\\mathrm{h}$ at $0.6\\mathrm{V}$ in $\\mathrm{H}_{2}$ –air PEMFC at $80^{\\circ}\\mathrm{C}$ (ref. 22). \n\nTherefore, Fe–N–C catalysts comprising more of the durable $\\mathrm{FeN}_{x}$ sites and fewer of the non-durable ones should be targeted. Before the community can engage in this challenge, the identification of which $\\mathrm{FeN}_{x}$ sites are durable and which are not is required. It was revealed with ex situ 57Fe Mössbauer spectroscopy that Fe–N–C catalysts comprise two types of $\\mathrm{FeN}_{x}$ site, labelled D1 (doublet with quadrupole splitting (QS) values of $0.9{-}1.2\\operatorname*{mm}s^{-1},$ and D2 $\\mathrm{(QS=1.8–2.8mms^{-1}}.$ ), both having a similar isomer shift15,31,32. By bridging density functional theory (DFT) calculations on QS values with ex situ Mössbauer spectroscopy, we identified D1 to be a high-spin $\\mathrm{Fe}(\\mathrm{III})\\mathrm{N}_{x}$ site (iron site S1) and D2 a low- or medium-spin $\\mathrm{Fe}(\\mathrm{II})\\mathrm{N}_{x}$ site (iron site $S2)^{33}$ , in general agreement with two recent studies34,35. While these sites are ubiquitous in $\\mathrm{Fe-N-C}$ catalysts, their respective activity and durability are unknown. \n\n![](images/17bf1bb0c184f4d96805f5a065bcc1450ba5f912f45008d1609f20193e6a0ecd.jpg) \nFig. 1 | Initial activity and reversible spectral changes of Fe with PEMFC potential. a, PEMFC Tafel plots of $\\mathsf{F e}_{0.5}$ and $\\mathsf{F e}_{0.5}$ -950(10). Voltage corrected for the Ohmic drop, ‘IR-corrected’. b, Fe K-edge XANES spectra measured under operando conditions in PEMFC as a function of potential. c,d, In situ $^{57}\\mathsf{F e}$ Mössbauer spectra at $0.8\\mathsf{V}$ (c) and $0.2\\mathsf{V}$ (d) acquired during the fourth cycle. Exp., exprimental data. For a, the cell temperature was $80^{\\circ}\\mathsf{C}$ the flow rates of $\\mathsf{O}_{2}$ and ${\\sf H}_{2}$ were 60 sccm with $100\\%$ relative humidity, the gauge pressure was 1 bar and the cathode loading was $4\\mathsf{m g c m}^{-2}$ . For b, all the testing conditions were the same as a, except that no backpressure was applied. For c,d, the cell was at room temperature, the humidifiers were at $50^{\\circ}\\mathsf C_{\\iota}$ , Ar and ${\\sf H}_{2}$ gases were fed at the cathode and anode, respectively, and no backpressure was applied. Each Mössbauer spectrum was collected for 36 h. D1H is the Mössbauer signature of S1 sites at high potential while D1L is their signature at low potential. \n\nHere, we separately interrogate S1 and S2 with in situ, operando and end-of-test (EoT) spectroscopies (see self-consistent definitions in Supplementary Note 1). With in situ $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy in $\\mathrm{~O}_{2}$ -free PEMFC, we demonstrate that a fraction of S1 is stable, reversibly changing from high-spin ferric to high-spin ferrous state between 0.8 and $0.2\\mathrm{V},$ while the electronic state of S2 is potential independent, being ferrous low- or medium-spin. Ex situ $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy at 5 K after PEMFC potentiostatic operation reveals that S2 is durable while S1 is not, with corresponding Fe cations forming ferric oxide nanoparticles. We also provide evidence that S2 is the main contributor to ORR activity in PEMFC after short operation time. \n\n# Results \n\nEx situ characterization of pristine Fe–N–C catalysts. This study was conducted on two Fe–N–C catalysts, previously demonstrated to be free of iron clusters and containing only single-metal-atom $\\mathrm{FeN}_{x}$ sites, synthesized as previously reported (Methods)15 and labelled $\\mathrm{Fe}_{0.5}$ (pyrolysis in argon) and $\\mathrm{Fe}_{0.5}{-950(10)}$ (pyrolysis of $\\mathrm{Fe}_{0.5}$ in $\\mathrm{NH}_{3}$ at $950^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}\\dot{}$ ). Their ex situ structure and morphology are reported in Extended Data Fig. 1 and Supplementary Table 1, the main ex situ differences between them being the higher surface basicity and microporous area of $\\mathrm{Fe}_{0.5}–950$ (10). No Fe particles were observed by transmission electron microscopy (TEM) in both pristine powder catalysts, and the atomic dispersion of Fe in $\\mathrm{Fe}_{0.5}$ was further confirmed by scanning TEM (STEM) (Extended Data Fig. 1g–i). Their initial ORR activities in PEMFC (Fig. 1a) are similar to values reported in ref. 15 and representative for state-of-the-art Fe–N–C catalysts18,22,36. $\\mathrm{NH}_{3}$ pyrolysis introduces highly basic nitrogen groups, increasing the turnover frequency (TOF) of $\\mathrm{FeN}_{x}$ sites but leading to decreased durability in PEMFC15,17. This was recently explained by higher demetallation rates for $\\mathrm{NH}_{3}$ - versus Ar-treated $\\mathrm{Fe-N-C}$ catalysts in acid medium17,29, while demetallation rates were equally low in alkaline medium29. These results support the involvement of highly basic nitrogen groups in an important fraction of $\\mathrm{FeN}_{x}$ sites in $\\mathrm{Fe}_{0.5}{-950(10)}$ , leading to higher TOF but also fast protonation of $_\\mathrm{N}$ groups in acid medium, leading to demetallation of the most active sites. Due to its high stability in acid21, $\\mathrm{Fe}_{0.5}$ was selected for in situ $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy in PEMFC. The ex situ Mössbauer spectra at $300\\mathrm{K}$ of $\\mathrm{Fe}_{0.5}$ (powder) and $\\mathrm{Fe}_{0.5}$ -cathode are identical, identifying only D1 and D2 (Extended Data Fig. 2a,b). However, one cannot exclude the formation of superparamagnetic ferric oxide nanoparticles during cathode preparation, which would contribute with a doublet overlapping with D1 signal from S1 sites37. To unveil this degeneracy, the spectra were acquired at lower temperature (5 K), which increases the magnetization time constant of nano ferric oxides, contributing then with a sextet component38,39, while the signal of S1 remains a doublet40. At $5\\mathrm{K}$ , no sextet was visible for $\\mathrm{Fe}_{0.5}$ while a broad sextet representing only $9\\%$ of the absorption area, assigned to superparamagnetic ferric oxide, appeared for $\\mathrm{Fe}_{0.5}$ cathode (Extended Data Fig. 2c,d). Thus, the low-QS doublet (labelled D1) in the $\\mathrm{Fe}_{0.5}$ -cathode spectrum at $300\\mathrm{K}$ can mainly be assigned to S1 sites. \n\nOperando X-ray absorption spectroscopy of $\\mathbf{Fe}_{0.5}$ in PEMFC. Operando (extended) X-ray absorption near-edge and fine structure (XANES and EXAFS, respectively) was acquired at Fe K-edge with fast acquisition mode in PEMFC (cell 2, ref. 41, Supplementary \n\n![](images/35de95629d63962f5a76ac7d5822c128e3c8df88d84e72e3c2d77041b36b7e8b.jpg) \nFig. 2 | Effect of PEMFC potential on doublets from fitted in situ Mössbauer spectra. a–f, The spectral doublet D1 (a), D2 (c) and D3 (e) resulting from the fittings, and the corresponding isomer shift (IS) and QS values of D1 (b), D2 (d) and D3 (f) at $0.8\\mathsf{V}$ (2), $0.2\\mathsf{V}$ (2), $0.8\\mathsf{V}$ (4) and $0.2\\mathsf{V}$ (4). The number in parentheses represents the cycle number. In a, c and e, solid curve, 0.8 V (2); dashed curve, $0.2\\mathsf{V}$ (2); crosses, $0.8\\mathsf{V}$ (4); dots, 0.2 V (4). In b, d and f, squares, QS; coloured spots, IS. D1H is the Mössbauer signature of S1 sites at high potential while D1L is their signature at low potential. The experimental spectra and all fitted components from which a,c,e were made can be seen in Supplementary Fig. 6. \n\nFig. 1a and Supplementary Note 2). Reversible changes with electrochemical potential were revealed (Fig. 1b and Extended Data Fig. 3), confirming in PEMFC the in situ and/or operando XANES-EXAFS results previously measured in aqueous acidic electrolyte for $\\mathrm{Fe}_{0.5}$ and other catalysts comprising only or mostly $\\mathrm{FeN}_{x}$ sites2,16,42,43. Operando XANES spectra indicate a $\\mathrm{Fe({\\mathrm{III}})/F e({\\mathrm{II}})}$ redox transition and conformational changes of an important fraction of $\\mathrm{FeN}_{x}$ sites in the region $0.2\\mathrm{-}0.8\\mathrm{V}$ (Extended Data Fig. 3a), while operando EXAFS spectra indicate a change from an average $\\mathrm{O-Fe(III)N_{4}}$ to $\\mathrm{Fe(II)N_{4}}$ coordination as the potential is decreased (Extended Data Fig. 3b)42–44. The redox transition is also seen by cyclic voltammetry in acid electrolyte and in line with the decreased average oxidation state of Fe identified by the threshold energy of the XANES spectrum (Extended Data Fig. 3c). \n\nIn situ Mössbauer spectroscopy of $\\mathbf{Fe}_{0.5}$ in PEMFC. X-ray absorption spectroscopy (XAS), however, fails to provide separate information on S1 and S2. To this end, we resorted to in situ 57Fe Mössbauer spectroscopy with an in-house single-cell PEMFC (cell 3, Supplementary Fig. 1b and Supplementary Note 2), whose proper electrochemical response was verified (Supplementary Fig. 2). The transmitted $\\boldsymbol{\\upgamma}$ -ray signal was continuously acquired for $36\\mathrm{h}$ during each in situ potentiostatic experiments at room temperature, with humidified $\\mathrm{H}_{2}$ or argon at anode or cathode. Following the potentiostatic controls shown in Extended Data Fig. 4, we identified irreversible changes in the Mössbauer spectra of $\\mathrm{Fe}_{0.5}$ cathode (during the first two cycles, discussed later) and, thereafter, reversible changes triggered by the potential. Figure 1c,d shows reversible changes for in situ Mössbauer spectra measured at 0.8 and $0.2\\mathrm{V}$ during cycle 4, labelled $0.8\\mathrm{V}$ (4) and $0.2\\mathrm{V}$ (4). The hyperfine parameters isomer shift and QS of D1 (labelled D1H for in situ spectra, see later) and of D2 are similar at $0.8\\mathrm{V}$ (4) to those measured ex situ for the pristine $\\mathrm{Fe}_{0.5}$ cathode (Supplementary Table 2). In contrast, at $0.2\\mathrm{V}$ (4), both the isomer shift and QS values for D1 (labelled D1L, see later) substantially increased, while those for D2 were unmodified (Fig. 1d and Supplementary Table 2, row $\\mathrm{\\Delta}^{\\cdot}0.2\\mathrm{V}$ (4)’). After all potential holds (Extended Data Fig. 4), we verified with ex situ Mössbauer spectroscopy at 5 K that the low-QS doublet (labelled D1H and observed in situ at high potential in cycles 1–4) can still be assigned to S1 sites (Supplementary Fig. 3). D1H and D1L therefore represent the in situ Mössbauer signal of S1 sites at high and low potential, respectively. Figure 1c,d also identifies a third doublet D3, independent of potential and related to irreversible changes occurring to the $\\mathrm{Fe}_{0.5}$ cathode during cycle 1 (discussed later). \n\nWe now discuss trends for all in situ Mössbauer spectra acquired at various potentials. The spectrum $0.8\\mathrm{V}$ (1) shows the doublets D1–D2 (Supplementary Fig. 4a), with same isomer shift and QS values as those of the pristine $\\mathrm{Fe}_{0.5}$ cathode at $300\\mathrm{K}$ (Extended Data Fig. 2b). However, the ratio of D1 to D2 is lower in $0.8\\mathrm{V}$ (1) (Supplementary Table 2), indicating that some unstable S1 sites were lost during the 36-h long $0.8\\mathrm{V}$ (1) experiment. From $0.8\\mathrm{V}$ (1) to $0.2\\mathrm{V}$ (1), the spectral parameters and intensity of D2 remained unchanged (Supplementary Fig. 4a,b). This applies also to all subsequent potential holds (Supplementary Figs. 5–8). In contrast, the signal from S1 at high potential (D1H) in $0.8\\mathrm{V}$ (1) resulted in a much less intense central doublet in $0.2\\mathrm{V}$ (1) (grey doublet in Supplementary Fig. 4b). This indicates demetallation of an important fraction of sites S1 during the first hold at $0.2\\mathrm{V},$ in line with $15\\mathrm{-}40\\%$ activity loss after 10,000 load cycles in inert gas reported by us for two $\\mathrm{Fe-N-C}$ catalysts (almost) exclusively comprising $\\mathrm{FeN}_{x}$ sites21. Since the $0.2\\mathrm{V}$ (1) spectrum was acquired for $36\\mathrm{h}$ , it may be regarded as a time-averaged spectrum reflecting irreversible phenomena. A detailed analysis of the time dependence of $0.2\\mathrm{V}$ (1) spectrum clearly reveals this (Supplementary Fig. 9 and Supplementary Note 3). During cycles 2–4, however, the switch between D1H and D1L was triggered solely by the electrochemical potential, with distinct isomer shift and QS values (Fig. 2a,b and Supplementary Fig. 5b). Regarding doublet D3 (isomer shift of roughly $1.15\\mathrm{mms^{-1}}$ and QS of roughly $2.5\\mathrm{mms^{-1}},$ , it first appeared in $0.2\\mathrm{V}$ (1) (Supplementary Fig. 4b) and is unambiguously assigned to high-spin ${\\mathrm{Fe}}^{2+}$ species due to its high isomer shift45,46. The spectral parameters and intensity of D3 remained almost unchanged from $0.2\\mathrm{V}$ (1) and during all subsequent potential holds (Fig. 2e,f and Supplementary Figs. 5–8). From $0.8\\mathrm{V}$ (2) and afterwards, all spectral changes only reflect the reversible potential dependence of the Mössbauer signature from S1 sites (Fig. 2 and Supplementary Figs. 5–7). To gain understanding on D3, we performed EoT Mössbauer spectroscopy of the $\\mathrm{Fe}_{0.5}$ cathode at various temperatures, after completing all in situ measurements (Supplementary Figs. 3b, 10 and 11, Supplementary Table 3 and Supplementary Note 4). In summary, the in situ D3 component is assigned to high-spin $\\mathrm{Fe}^{2+}$ cations (possibly complexed with Nafion sulfonic acid groups), formed from the demetallation of a fraction of S1 sites during $0.2\\mathrm{V}$ (1) (scheme in Extended Data Fig. 5). When exposed to air, such cations form superparamagnetic ferric oxide nanoparticles, overlapping then with D1 at $300\\mathrm{K}$ (Supplementary Fig. 10a,b). At $T{\\le}80\\mathrm{K},$ they then, however, contribute with a sextet component with isomer shift and hyperfine magnetic field corresponding to ferric oxide (Supplementary Fig. 10b–f). A summary of the inter-relation between the Mössbauer components ex situ, in situ and EoT after in situ measurements is given in Supplementary Table 4. \n\n![](images/231360719911a9b0a052b91e860351f3d5baa5d6d9bfeec63d7fc54e2f8e0cc9.jpg) \nFig. 3 | Experimental and calculated values of hyperfine parameters versus potential. a,b, Reversible change of isomer shift (a) and QS values (b) of the spectral component D1 versus electrochemical potential. The error bars in a and b at 0.8 and $0.2\\mathsf{V}$ represent the standard deviation from three separate measurements on different cycles. c, The QS values calculated with the PBE/DZVP2 method for different $F e N_{4}C_{12}$ model structures in high spin, with or without oxygen adsorbate. The structures of 1e, 1f and 2e are given in Supplementary Fig. 13. QS values calculated for $F e N_{4}C_{10}$ model structures are given in Supplementary Table 5. \n\nReversibly changing in situ coordination of S1 with potential. We now discuss the structures and electronic states of S1 and S2. The in situ (absence of $\\mathrm{~O}_{2}$ ) Mössbauer signal of the fraction of S1 sites that survived $0.2\\mathrm{V}$ (1) reversibly switches between D1L at $0.2\\mathrm{V}$ and D1H at $0.8\\mathrm{V}$ (Fig. 2a,b). D1H is identical to D1 measured ex situ on pristine $\\mathrm{Fe}_{0.5}{\\mathrm{:}}$ , which we recently identified to be mainly $\\mathrm{Fe(III)N}_{4}\\mathrm{\\bar{C}}_{12}$ periodic or cluster structures in high-spin state, with axial oxygen adsorbates33,42. Due to its high isomer-shift value, the assignment of D1L to a high-spin ${\\mathrm{Fe}}(\\mathrm{II})$ species is straightforward45,46. Consequently, only a restricted change in the average iron spin is expected for an $\\mathrm{Fe}_{0.5}$ cathode between high and low potential. We used a three-electrode cell (cell 4, ref. 16, Supplementary Fig. 1c and Supplementary Note 2) to verify this with in situ Fe $\\mathrm{K}_{\\upbeta}$ X-ray emission spectroscopy (XES), a technique well suited to investigating the spin state of metal centres47. The overlapping in situ XES spectra at 0.2 and $0.8\\mathrm{V}$ support the idea that the sites S1 are in high spin at all potentials (Supplementary Fig. 12). The switch from D1H to D1L signal for S1 is thus the outcome of the reduction from $\\mathrm{Fe(III)N}_{4}\\mathrm{C}_{12}$ to $\\mathrm{Fe(II)N_{4}C_{12}},$ also triggering the removal of an axial OH adsorbate. To further support this, we applied our recently reported DFT methods33 to calculate the QS value of different high-spin $\\mathrm{OH-Fe(III)N_{4}C_{12}},$ $\\mathrm{OH-Fe(III)N_{4}C_{10},}$ $\\mathrm{Fe(II)N_{4}C_{12}}$ and $\\mathrm{Fe(II)N_{4}C_{10}}$ models (Supplementary Fig. 13, the atomic coordinates of the optimized models are provided in Supplementary Data 1). While high-spin $\\mathrm{OH-Fe(III)N_{4}C_{12}}$ and $\\mathrm{OH{-Fe}(I I I)N_{4}C_{10}}$ structures lead to QS values of $0.6{-}1.0\\mathrm{mm}s^{-1}$ , matching those of D1H, only the high-spin $\\mathrm{Fe(II)N}_{4}\\mathrm{C}_{12}$ structures lead to QS values of $1.7{-}2.0\\mathrm{mm}s^{-1}$ , matching those of D1L (Supplementary Table 5). The QS values of high-spin $\\mathrm{Fe(II)N_{4}C_{10}}$ structures are ${>}3.0\\mathrm{mms^{-1}}$ , notably higher than those of D1L (Supplementary Table 5). These results confirm our recent assignment of D1 to high-spin Fe(III) $\\mathrm{N}_{4}\\mathrm{C}_{12}$ structures with axial oxygen ligand33, and reveal their switch to high-spin $\\mathrm{Fe(II)N}_{4}\\mathrm{C}_{12}$ structures, without axial ligand, at low potential (D1L). Operando EXAFS spectra (Extended Data Fig. 3b) also support that the ${\\mathrm{Fe}}(\\mathrm{III})$ -to-Fe(II) reduction is accompanied by desorption of oxygen adsorbates42,48. This redox switch is in line with in situ or operando XAS on numerous Fe–N–C catalysts2,16,42,43 and with the notable presence of S1 in Fe–N–C catalysts15,31,32,42. Here, we show that S1 undergoes this redox transition, but not S2. We then analysed the potential dependence of the S1 hyperfine parameters. Figure $^{3\\mathrm{a},\\mathrm{b}}$ shows that they can be divided into those below $0.5\\mathrm{V}$ and those above (D1L and D1H, respectively). For comparison, Fig. 3c reports the DFT-calculated QS for high-spin OH–Fe(III)– $\\mathrm{N}_{4}\\mathrm{C}_{12}$ and high-spin $\\mathrm{Fe(II){-}N_{4}C_{12}}$ structures, demonstrating that our DFT method correctly reproduces the change in QS. Supplementary Table 4 summarizes the main findings on D1H and D1L and how they interrelate with the site S1. \n\nDifferent fates of sites S1 and S2 in an operating PEMFC. We then attempted to investigate the electronic states and durability of S1 and S2 with operando $\\left(\\mathrm{O}_{2}\\right)$ Mössbauer spectroscopy. However, this proved impossible for S1. After a single potential hold at $0.2\\mathrm{V}$ in $\\mathrm{O}_{2}$ no S1 sites were observed in the EoT Mössbauer spectrum at $5\\mathrm{K}$ while two sextets appeared, assigned to ferric oxide particles (Extended Data Fig. 6c). The relative number of sextets is much higher than in the pristine $\\mathrm{Fe}_{0.5}$ -cathode (Extended Data Fig. 6a), supporting the idea that the main fraction of S1 sites survived the membrane electrode assembly (MEA) preparation, but transformed to ferric oxides during fuel cell testing. The cathode was also characterized before and after the potential hold with TEM (Extended Data Fig. $\\mathrm{6b,d},$ ) and X-ray diffraction (XRD) (Extended Data Fig. 6e). Only TEM after operation identified Fe particles of around $5-15\\mathrm{nm}$ in size. The operando Mössbauer spectra were comparable at open circuit potential (OCP) and $0.2\\mathrm{V}$ (not shown) which, combined with the EoT spectrum at $5\\mathrm{K},$ suggests that the D1-like signal identified at $0.2\\mathrm{V}$ under operando conditions already originated from ferric oxides instead of S1 sites. The presence of ferric oxides at $0.2\\mathrm{V}$ in turn suggests those particles are not electronically connected to the cathode, but only in contact with Nafion phase. In contrast, the parameters and absolute intensity of D2 were unmodified before and after $0.2\\mathrm{V}$ hold in $\\mathrm{~O}_{2}$ (Supplementary Table 6). This indicates that the electronic state of S2 is potential independent in the range $0.2\\mathrm{-}0.9\\mathrm{V}$ and independent of the presence or absence of $\\mathrm{~O}_{2}$ . This in turn indicates that S2 is either not accessible to $\\mathrm{~O}_{2}$ or binds $\\mathrm{O}_{2}$ weakly, in line with our ex situ analysis33. The activity of $\\mathrm{Fe}_{0.5}$ cathode before and after operando measurements (cell 3) was measured in cell 1 at $80^{\\circ}\\mathrm{C}$ . A restricted ORR activity decrease from 23 to $15\\mathrm{mAcm}^{-2}$ is observed at $0.8\\mathrm{V}$ (Extended Data Fig. 6f). The remaining activity is much higher than that of the Fe-free N-doped carbon matrix $(\\mathrm{N-C})^{15}$ , indicating that either S2 or ferric oxides are active. To evaluate the ORR activity of the latter, we precipitated $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ nanoparticles on the same $_{\\mathrm{N-C}}$ support. The activity of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}/\\mathrm{N}{-}\\mathrm{C}$ above $0.7\\mathrm{V}$ is within reproducibility equal to that of $\\mathrm{N-C},$ , indicating no or negligible ORR activity of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ (Supplementary Fig. 14). \n\n![](images/7cbbd38214fd996dfab6023e5bbeca63664a201d6305da96bfa1e1aa7c677c28.jpg) \nFig. 4 | Characterization of $\\mathsf{F e}_{0.5}$ cathode after operation at $\\phantom{+}0.5\\mathsf{V}$ in PEMFC. a, Ex situ 57Fe Mössbauer spectrum at $5{\\sf K}$ of the pristine $\\mathsf{F e}_{0.5}$ cathode. Exp., experimental data. b,c, EoT Mössbauer spectra at $51$ of the $\\mathsf{F e}_{0.5}$ cathode after a hold at $0.5\\mathsf{V}$ for $5h$ (b) and $50\\mathsf{h}$ (c). d, The corresponding Tafel plots. Cell voltage corrected for the Ohmic drop, ‘IR-corrected’). The insets (bottom right in a, b and c) show the Tafel plot trace, the thicker curve corresponding to each spectrum. The cell temperature was $80^{\\circ}\\mathsf C_{\\iota}$ 60 sccm $\\mathsf{O}_{2}$ and ${\\sf H}_{2}$ gases with $100\\%$ relative humidity were fed at the cathode and anode, respectively, the gauge pressure was 1 bar, and the cathode loading was $4\\mathsf{m g c m}^{-2}$ . e, Volume-rendered $\\mathsf{F e O}_{x}$ particles (left) and $\\mathsf{F e O}_{x}$ particles superimposed onto the morphology of support material (right) of the $\\mathsf{F e}_{0.5}$ cathode after a hold at $0.5\\mathsf{V}$ for $50\\mathsf{h},$ obtained from $\\mathsf{X}$ -ray computed tomography with phase contrast for soft elements (mainly C and N) and absorption contrast for hard elements (that is, Fe). Scale bar, $10\\mathsf{u m}$ . \n\nTo follow spectral changes as a function of operating time, a series of cathodes was prepared from a same $\\mathrm{Fe}_{0.5}$ batch and operated at $0.5\\mathrm{V}$ in cell 1 for 5, 10, 25 or $50\\mathrm{h}$ . Polarization curves were recorded before and after each experiment. Each MEA was characterized with EoT $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy at $5\\mathrm{K}$ (Fig. 4a–c, Supplementary Fig. 15 and Supplementary Table 7). The fittings indicate unmodified spectral parameters and absolute intensity for D2 with operation time, continuously decreasing signal intensity for D1 and continuously increasing signal intensity for the two sextets, assigned to superparamagnetic ferric oxide (Fig. 4a–c and \n\n![](images/f5766a948357cc11150e3f2be3a2d88e5f6b5f0ea617d233982047685b12a425.jpg) \nFig. 5 | Correlations between $\\mathsf{F e N}_{x}$ site amount in $\\mathsf{F e}_{0.5}$ cathode and activity over time. a–d, Current density of the $\\mathsf{F e}_{0.5}$ cathode at $0.8\\mathsf{V}$ versus duration of operation at $0.5\\mathsf{V}$ in ${\\sf H}_{2}/\\sf{O}_{2}$ PEMFC (a), absolute absorption (Abs.) areas of D1 $(\\pmb{\\ b})$ , D2 $\\mathbf{\\eta}(\\bullet)$ and sextets $({\\pmb d})$ versus duration of operation at $0.5\\mathsf{V}$ in ${\\sf H}_{2}/{\\sf O}_{2}\\sf P{\\sf E}{\\sf M}{\\sf F}{\\sf C}$ . e, The current density of $\\mathsf{F e}_{0.5}$ -cathodes at $0.8\\mathsf{V}$ as a function of the absolute absorption area for D1 and $D1+{\\mathsf{D}}2$ . The absolute absorption area of a given spectral component is proportional to the number of corresponding sites in the cathode. \n\nSupplementary Fig. 15). EoT XANES reveals only minor changes (Supplementary Fig. 16a) while EXAFS spectra after $10{-}50\\mathrm{h}$ reveal a small increase in the Fe–Fe signal at roughly $2.7\\mathring\\mathrm{A}$ , matching the Fe–Fe distance in ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ (Supplementary Fig. 16b). X-ray computed tomography performed ex situ after $50\\mathrm{h}$ of operation at $0.5\\mathrm{V}$ shows the presence of Fe particles (Fig. 4e and Supplementary Fig. 17a). Most particles are present on or near the outer surface of the N–C matrix. Size distribution analysis (Supplementary Fig. 17b) reveals the presence of particles 5 to $60\\mathrm{nm}$ in size, with the most frequent sizes being between 5 and 10 nm $(47.5\\%)$ . The initial and final polarization curves indicate a sharp activity decrease after $^{5\\mathrm{h}}$ operation at $0.5\\mathrm{V}$ followed by a slow but steady activity decrease (Fig. 4d, Supplementary Fig. 18a). \n\nEvidence for ORR activity contributions from S1 and S2 sites. To identify structure–activity relationships, we plotted the absolute area of each spectral component and the current density at $0.8\\mathrm{V}$ as a function of time (Fig. 5a–d). The results indicate a trend of decreased activity with operation time, decreasing number of sites S1, increasing amount of ferric oxides (sextets) and unchanged number of sites S2. On the basis of this, we plotted in Fig. 5e the current density at $0.8\\mathrm{V}$ as a function of the absolute absorption area for either D1 or $(\\mathrm{D}1+\\mathrm{D}2),$ . Except for the initial activity measurements, the results reveal a linear correlation between the activity and either D1 or $(\\mathrm{D}1+\\mathrm{D}2)$ , demonstrating that S1 contributes to ORR activity. The data for the initial activity (star symbol) is an outlier and this can be explained by a higher TOF of Fe-based sites during the first polarization curve. This hypothesis is in line with our recent work that demonstrated decreased TOF of Fe-based sites by chemical reaction of $\\mathrm{Fe}_{0.5}$ with $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (ref. 25). The activity drop that occurred from 0 to $^{5\\mathrm{h}}$ of operation is thus assigned to both decreased TOF via mild surface oxidation of carbon (vertical arrows in Fig. 5e), and decreased number of S1 sites (arrows along the dashed lines in Fig. 5e). After $5\\mathrm{h}$ operation, the TOF of the Fe sites seems stabilized, leading to linear correlations between the overall activity and either D1 or $\\mathrm{D}1+\\mathrm{D}2$ . The extrapolation at $\\scriptstyle x=0$ of the plot of activity versus absolute area of D1 leads, however, to a positive y intercept, indicating that the $\\mathrm{Fe}_{0.5}$ cathode should have substantial ORR activity even in the absence of S1. This is supported by the results after operation at $0.2\\mathrm{V}$ in $\\mathrm{O}_{2}$ (Extended Data Fig. 6). In contrast, the extrapolation at $\\scriptstyle x=0$ of the plot of activity versus absolute area of $\\mathrm{D}1+\\mathrm{D}2$ is near zero, supporting the fact that both S1 and S2 are ORR active in acidic medium. A rigorous analysis shows that this near-zero $y$ intercept can be interpreted either as S2 sites being all located on the surface and having a similar TOF as S1, or only a fraction of S2 sites are on the surface and then indicating a higher TOF than S1 (Supplementary Note 5). From EoT Raman spectroscopy, no carbon corrosion was identified (Supplementary Fig. 18b). We verified that these trends also apply to the initially more active $\\mathrm{Fe}_{0.5}{-950(10)}$ catalyst (Extended Data Fig. 7, Supplementary Table 8 and Supplementary Note 6). The relative percentage area of D1 decreased from 32 to $6\\%$ during $50\\mathrm{h}$ at $0.5\\mathrm{V}$ for $\\mathrm{Fe}_{0.5}{-950(10)}$ and from 43 to $6\\%$ for $\\mathrm{Fe}_{0.5}$ . For D2, the relative percentage area decreased from 40 to $38\\%$ in $50\\mathrm{h}$ for $\\mathrm{Fe}_{0.5}{-950(10)}$ but slightly increased from 49 to $51\\%$ for $\\mathrm{Fe}_{0.5}$ . The variation of $\\pm2\\%$ in D2 is within the error, and D2 can be considered durable in both cathodes. Comparative STEM–energy dispersive $\\mathrm{\\DeltaX}$ -ray (EDX) analysis of $\\mathrm{Fe}_{0.5}{-950(10)}$ fresh and aged ( $50\\mathrm{h}$ at $0.5\\mathrm{V}$ ) cathodes identify few large Fe particles in the fresh cathode but numerous Fe nanoparticles after ageing (Supplementary Fig. 19). In addition, the correlation between Fe and F mapping in the aged cathode suggests that Fe clustering is linked to the presence of Nafion ionomer (Supplementary Fig. 20). \n\n# Conclusions \n\nIn conclusion, we identify with Mössbauer spectroscopy the high-spin S1 site and the low- or intermediate-spin S2 site, both assigned to $\\mathrm{FeN_{4}}$ moieties but embedded in different ways in the carbon matrix. Iron in the site S1 switches oxidation state III/II in the region $_{0-1\\mathrm{V}}$ while S2 does not, remaining ${\\mathrm{Fe}}(\\mathrm{II})$ . We also identify that both sites initially contribute to the ORR activity of $\\mathrm{Fe-N-C}$ in acidic medium. However, S1 is not durable in operating PEMFC, quickly transforming to ferric oxides (Fig. 6). In contrast, S2 is shown to be more durable, with no measurable decrease of the number of active sites after $50\\mathrm{h}$ operation at $0.5\\mathrm{V}.$ The lack of change of oxidation state for Fe in S2 in the region $_{0-1\\mathrm{V}}$ is not contradictory with catalysis. For example, we showed with in situ XAS that $\\mathrm{CoN}_{x}$ sites do not change oxidation state in acidic medium in the same region but catalyse ORR16,44. The degradation of S1 into ferric oxides may be a direct or indirect demetallation, the indirect pathway possibly triggered by localized carbon surface oxidation or protonation of highly basic nitrogens involved in S1. The stability of S2 may be due to a more graphitic local structure, lower amount of reactive oxygen species (ROS) produced during ORR in acid or its subsurface location activating the N-doped carbon top surface. These results and/or methods are of high interest to the improved understanding of Fe–N–C materials for application in PEMFC but also in anion-exchange membrane fuel cells and for $\\mathrm{CO}_{2}$ electro-reduction49,50. For PEMFC application, further efforts should be devoted to increasing the site density of S2 sites and/or stabilizing S1 in acidic and oxygenated environment. The former goal might be achieved by depositing a thin overlayer of N-doped carbon on top of Fe–N–C (possibly transforming S1 into S2 sites) and the latter goal by adding cocatalysts (to scavenge $\\mathrm{H}_{2}\\mathrm{O}_{2}$ or ROS formed during ORR in acid medium) or by integrating S1 sites in a more graphitic carbon support. In addition, the targeted removal of sites S1 before integrating Fe–N–C materials in PEMFC cathodes would avoid the formation of ferric oxides under operando conditions, in turn probably forming ROS in the presence of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . \n\n![](images/046ee4b9daf3b59a7447c5facc1ee9f6c3915c1e6f7883d95950b97e80d6440d.jpg) \nFig. 6 | Coordination or structural changes of the sites S1 and S2 under in situ or operando conditions. The site S1 is a high-spin $F e N_{4}C_{12}$ structure, undergoing reversible change of Fe oxidation state from III to II in situ (no $\\mathbf{O}_{2})$ for the most stable S1 sites fraction (D1H to D1L double-sided black arrow), while the less stable fraction of S1 sites irreversibly transforms in situ into high-spin $\\mathsf{F e}^{2+}$ (D1H to D3, single-sided black arrow). When exposed to ambient air for EoT measurement following the in situ measurement, high-spin $\\mathsf{F e}^{2+}$ transform into ferric oxides (D3 to ${\\mathsf{F e}}_{2}{\\mathsf{O}}_{3},$ single-side red arrow). S1 sites irreversibly transform into ferric oxides under operando conditions when catalysing the ORR (single-sided red arrow), most probably via a fast intermediate stage involving the leaching of $\\mathsf{F e}^{2+}$ cations (D3) before the oxide growth may start. S2 sites do not change oxidation state and are stable both in situ and operando (double-sided arrows). \n\n# Methods \n\nSynthesis. The synthesis of $\\mathrm{Fe}_{0.5}$ and $\\mathrm{Fe}_{0.5}{-950(10)}$ has been reported previously15. Catalyst precursors were prepared from a $Z\\mathrm{n}(\\mathrm{II})$ zeolitic imidazolate framework (Basolite Z1200 from BASF, labelled ZIF-8), ${\\mathrm{Fe}}(\\mathrm{II})$ acetate $({\\mathrm{Fe}}({\\mathrm{II}}){\\mathrm{Ac}})$ and 1,10-phenanthroline (Phen). $^{57}\\mathrm{Fe(II)Ac}$ was used as iron precursor for all Mössbauer studies. For operando XAS, natural $\\mathrm{Fe(II)Ac}$ was used. The catalyst $\\mathrm{Fe}_{0.5}$ was synthesized via the dry ball milling of ZIF-8 $\\mathrm{\\langle800mg\\rangle}$ , Phen $(200\\mathrm{mg})$ and ${\\mathrm{Fe}}(\\mathrm{II})\\mathrm{Ac}$ $\\left(16\\mathrm{mg}\\right)$ in a zirconium oxide crucible filled with 100 zirconium oxide balls $5\\mathrm{mm}$ diameter) at $400\\mathrm{r.p.m}$ . for $2\\mathrm{h}$ (Fritsch Pulverisette 7 Premium, Fritsch). The subscript in $\\mathrm{Fe}_{0.5}$ corresponds to the Fe content $(\\mathrm{wt\\%})$ in the entire catalyst precursor before pyrolysis. Then the mixed precursor was pyrolysed in flash mode in Ar at $1{,}050^{\\circ}\\mathrm{C}$ for 1 h. Owing to a mass loss of $65\\mathrm{-}70\\mathrm{wt\\%}$ during pyrolysis in Ar, caused by volatile products formed from ZIF-8 and Phen, the iron content in $\\mathrm{Fe}_{0.5}$ is about three times the iron content in the catalyst precursor. $\\mathrm{Fe}_{0.5}$ was subjected to a second flash pyrolysis for $10\\mathrm{min}$ at $950^{\\circ}\\mathrm{C}$ in ${\\mathrm{NH}}_{3},$ , yielding $\\mathrm{Fe}_{0.5}{-950(10)}$ . The mass loss of carbon during $\\mathrm{NH}_{3}$ pyrolysis was $25\\mathrm{-}31\\%$ , further increasing the iron content. \n\nTo synthesize $\\mathrm{Fe}_{2}\\mathrm{O}_{3}/\\mathrm{N}{-}\\mathrm{C},$ the Fe-free N–C was first synthesized identically with $\\mathrm{Fe}_{0.5}{-950}$ except for the first ball-milling step, where no $\\mathrm{Fe(II)Ac}$ was added. Then $15\\mathrm{mg}$ of $\\mathrm{FeCl}_{2}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ was dissolved in $7.5\\mathrm{ml}\\mathrm{H}_{2}\\mathrm{O}$ to ethanol solution (vol.:vol. $=24{:}1$ ). Then $300\\mathrm{mg}$ of $_{\\mathrm{N-C}}$ was added, and well-mixed via sonication for 1 h. The obtained slurry was stirred continuously for another $^{48\\mathrm{h},}$ , followed by filtration, washing with water and drying in an oven at about $50^{\\circ}\\mathrm{C}$ overnight. The $\\mathrm{Fe_{2}O_{3}/N\\mathrm{-C}}$ sample was obtained by a final heat treatment at $200^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ in Ar with a ramping rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ . The Fe content in $\\mathrm{Fe_{2}O_{3}/N\\mathrm{-C}}$ was found to be $1.3\\mathrm{wt\\%}$ by X-ray fluorescence (XRF) spectroscopy. \n\nXRF. The metal content in $\\mathrm{Fe_{2}O_{3}/N\\mathrm{-C}}$ was measured via X-ray XRF spectroscopy (Axios Max from PANanalytical). $\\mathrm{Fe_{2}O_{3}/N\\mathrm{-C}}$ powder was mixed with boric acid as a binder in a ratio of 1:3 by weight via ball milling at $400\\mathrm{r.p.m}$ . for $30\\mathrm{min}$ . Then $200\\mathrm{mg}$ of the mixture was pelletized as a disc of $13\\mathrm{mm}$ diameter for XRF measurements. The calibration curve was performed using 0.1, 0.2, 0.5, 1.0, 1.5 and $2.0\\mathrm{wt\\%}$ Fe in a mixture of $\\mathrm{Fe(II)Ac}$ and Vulcan XC72R. The Vulcan XC72R (mixed with ${\\mathrm{Fe}}(\\mathrm{II})\\mathrm{Ac})$ were mixed with boric acid in a ratio of 1:3 by weight via ball milling at $400\\mathrm{r.p.m}$ . for $30\\mathrm{min}$ , and then $200\\mathrm{mg}$ of the mixture was pelletized as a disc of $13\\mathrm{mm}$ in diameter. \n\nXRD. XRD patterns were recorded using a PANanalytical X’Pert Pro powder X-ray diffractometer with Cu Kα radiation. \n\nSTEM. Probe Cs-corrected scanning transmission electron microscope JEOL ARM 200F, equipped with a cold field emission electron source, was used for imaging atomically dispersed ${\\mathrm{FeN}}_{x}{\\mathrm{C}}_{y}$ moieties in $\\mathrm{Fe}_{0.5}$ pristine powder. To minimize the beam damage, $80\\mathrm{keV}$ and low beam current were used. High-angle annular dark-field images were obtained using 68–180 mrad collection half-angles at 24 mrad probe convergence semi-angle. Images were filtered with non-linear filter that is a combination of low-pass and Wiener filters. The presence of iron and nitrogen was confirmed with Gatan Quantum ER dual Electron Energy-loss spectroscopy system. \n\nTEM and STEM–EDX. A JEOL 2010 TEM operated at $200\\mathrm{kV}$ was used to examine Fe–N–C cathodes before testing or at EoT. The resolution was $0.19\\mathrm{nm}$ . Elemental mapping was performed on a fresh or aged Fe0.5-950(10) cathode using a $200\\mathrm{kV}$ JEOL 2100F microscope equipped with a retractable large angle Centurio Silicon Drift detector. The Fe K, C K and O K lines and the $K$ factors specified by the JEOL software were used for elemental quantification. \n\nRaman spectroscopy. Raman spectra were collected using a LabRAM ARAMIS Raman microscope with a 473-nm laser. \n\n$\\mathbf{N}_{2}$ sorption isotherms acquisition and analysis. $\\Nu_{2}$ adsorption/desorption was performed at liquid nitrogen temperature (77 K) with a Micromeritics ASAP 2020 instrument. Before the measurements, all samples were degassed at $200^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ in flowing nitrogen to remove guest molecules or moisture. The pore size distributions were calculated by fitting the full isotherm with the quench solid DFT model with slit pore geometry from NovaWin (Quantachrome Instruments). \n\nBasicity measurement of pristine Fe–N–C powders. The basicity measurement of $\\mathrm{Fe}_{0.5}$ and $\\mathrm{Fe}_{0.5}{-950(10)}$ has been reported elsewhere15. A solution with $\\mathrm{pH}6.0$ was first prepared by the titration of a $0.1\\mathrm{{M}}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution by $0.1\\mathrm{M}$ KOH. Then $40\\mathrm{mg}$ catalyst was dispersed into $20\\mathrm{ml}$ aqueous solution with an initial pH $\\mathrm{(pH_{i})}$ of 6.0. The solution was constantly saturated with $\\mathrm{N}_{2}$ to avoid acidification from air. The final pH $\\mathrm{(pH_{f})}$ after the dispersion of the catalyst was measured once the pH meter indicated a stable value. \n\nElectrochemical characterization. The ORR activities of $\\mathrm{Fe}_{0.5}$ and $\\mathrm{Fe}_{0.5}{-950}$ were investigated in a single-cell PEMFC (cell 1, Supplementary Note 2). For the MEA, cathode inks were prepared by sonicating for 1 h the mixture of $20\\mathrm{mg}$ of catalyst, $652\\upmu\\mathrm{l}$ of a $5\\mathrm{wt\\%}$ Nafion solution containing $15\\mathrm{-}20\\%$ water, $326\\upmu\\mathrm{l}$ of ethanol and $272\\upmu\\mathrm{l}$ of deionized water. Then, three aliquots of $405\\upmu\\mathrm{l}$ of the catalyst ink were successively deposited on the microporous layer of a $4.84\\mathrm{cm}^{2}$ gas diffusion layer (Sigracet S10-BC). The cathode was then placed at $60^{\\circ}\\mathrm{C}$ to dry for 2 h. The anode used for all PEMFC tests in cell 1 was $0.5\\mathrm{mg_{Pt}}\\mathrm{cm}^{-2}$ on Sigracet S24-BC. Nafion NRE-211 was used as membrane. No hot-pressing was applied to easily peel off the cathode for EoT characterization. PEMFC tests were performed with a single-cell fuel cell with serpentine flow field (Fuel Cell Technologies) using an in-house test bench and a Biologic potentiostat with a 50 A load and EC-Lab software. The fuel cell temperature was $80^{\\circ}\\mathrm{C},$ , the humidifiers were set at $85^{\\circ}\\mathrm{C}$ and the inlet pressures were set to 1-bar gauge for both anode and cathode sides. The flow rate for humidified $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ gases was 60 standard cubic centimetres per minute (sccm) downstream. No break-in was applied before recording the first polarization curve. Polarization curves were recorded by scanning the voltage at $1\\mathrm{mVs^{-1}}$ . \n\nEx situ and operando XAS. Fe K-edge X-ray absorption spectra were collected at room temperature at SAMBA beamline (Synchrotron SOLEIL). The beamline is equipped with a sagittally focusing Si 220 monochromator, and X-ray harmonics are removed by two Pd-coated mirrors. For ex situ measurements on pristine Fe–N–C catalysts, the powders were pelletized as discs of $10\\mathrm{mm}$ diameter with a thickness of $1\\mathrm{mm}$ , using Teflon powder ( $_{\\mathrm{1-\\upmu\\mathrm{m}}}$ particle size) as a binder and XAS measured in transmission mode. For ex situ measurements on Fe–N–C cathodes (before testing or at EoT), XAS was acquired in fluorescence mode. For operando XAS experiments, MEAs were prepared identically as for measurements in the commercial PEMFC (cell 1). The design of the PEMFC used for operando XAS study (cell 2, Supplementary Note 2) was reported in ref. 41. The cell temperature was $80^{\\circ}\\mathrm{C}$ 60 sccm. $\\mathrm{O}_{2}$ and $\\mathrm{H}_{2}$ with $100\\%$ relative humidity were fed at cathode and anode, respectively, and the cathode loading was $4\\mathrm{mg}\\mathrm{cm}^{-2}$ . No backpressure was applied. Operando measurements were performed by recording the $\\mathrm{K}\\upalpha$ XRF of Fe with a Canberra 35-elements monolithic planar Ge pixel array detector. \n\nEx situ and in situ Mössbauer spectroscopy. 57Fe-enriched ${\\mathrm{Fe}}({\\mathrm{II}}){\\mathrm{Ac}}$ was used as iron precursor for all Mössbauer studies. The $^{57}\\mathrm{Fe}$ Mössbauer spectrometer was operated in transmission mode with a $^{57}{\\mathrm{Co:Rh}}$ source. The velocity driver was operated in constant acceleration mode with a triangular velocity waveform. The velocity scale was calibrated with the magnetically split sextet of a high-purity $\\upalpha$ -Fe foil at room temperature. The spectra were fitted to appropriate combinations of Lorentzian profiles representing quadrupole doublets, sextets by least-squares methods. Isomer-shift values are reported relative to $\\upalpha$ -Fe at room temperature. Unless otherwise mentioned in the Supplementary Tables 2, 3 and 6–8, the fittings were performed with unconstrained parameters (relative area, isomer shift, QS, linewidth (LW), hyperfine field (H)) for each spectral component. For ex situ measurements on pristine Fe–N–C catalysts, powders $(20-30\\mathrm{mg})$ were mounted in a $2\\mathrm{-cm}^{2}$ holder. For ex situ measurements on Fe–N–C cathodes, before testing or at EoT, $5\\mathrm{-}\\mathrm{cm}^{2}$ electrodes were cut into four pieces and stacked on top of each other. Mössbauer measurements below $100\\mathrm{K}$ were performed in a helium flow cryostat (SHI-850 Series from Janis). For in situ Mössbauer experiments, MEAs were prepared as described for testing in the commercial PEMFC (cell 1), except that the anode was $0.1\\mathrm{mg}_{\\mathrm{Pt}}\\mathrm{cm}^{-2}$ to maximize $\\boldsymbol{\\upgamma}$ -ray transmission through the cell. The design of the PEMFC for in situ Mössbauer spectroscopy (cell 3; Supplementary Note 2) is shown in Supplementary Fig. 1b. The cell was at room temperature, the humidifiers were at $50^{\\circ}\\mathrm{C},$ Ar and $\\mathrm{H}_{2}$ gases were fed at the cathode and anode, respectively, and no backpressure was applied. The Mössbauer signal was continuously acquired for $36\\mathrm{h}$ at each cathode potential. \n\nIn situ XES. Fe $\\operatorname{K}_{\\mathfrak{p}}\\mathrm{X}$ -ray emission spectra were collected at room temperature using a $1\\mathrm{m}$ radius Germanium 620 analyser crystal at GALAXY inelastic scattering end-station (Synchrotron SOLEIL)51,52. The incident energy was $8{,}500\\mathrm{eV}$ (using a silicon double-crystal monochromator) and the focused beam size was 30 (vertical) $\\times90$ (horizontal) $\\upmu\\mathrm{m}^{2}$ . The sample, analyser crystal and silicon drift detector were all arranged in a vertical Rowland circle geometry and air \n\nabsorption was reduced by using helium flight paths. The electrochemical cell (Goodfellow catalogue no. C 000200/2) used for operando XES in liquid electrolyte with a three-electrode system is the same as the one previously for ion with ultrasounds. A 50-µl aliquot was then pipetted on a roughly $3\\mathrm{cm}^{2}$ circular area of a $100\\mathrm{-}\\upmu\\mathrm{m}$ -thick graphite foil, resulting in a catalyst loading of around $1\\mathrm{mg}\\mathrm{cm}^{-2}$ . The graphite foil with deposited catalyst then served as a working electrode, $\\mathrm{Ag/AgCl}$ and Pt were used as reference and counter electrodes, respectively. The cell was filled with $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and saturated with $\\Nu_{2}$ by continuously bubbling gas in the electrolyte. \n\nX-ray computed tomography. X-ray computed tomography imaging was performed at the Advanced Photon Sources (APS) at Argonne National Laboratory (ANL) using Beamline 32-ID, with $8\\mathrm{keV}$ energy and $0.4\\:s$ exposure time. Fresnel zone plates with grading of $44.6\\mathrm{nm}$ were used to achieve a resolution of $44.6\\mathrm{nm}$ . Zernike phase contrast was used to detect soft elements, whereas absorption contrast was used for imaging hard materials. Image phase retrieval and reconstructions were performed using TomoPy53. The volume-rendering structure and analysis were done in Dragonfly v.4.1 (ref. 54). The calculated volume-to-surface area ratio was considered as the sizes of the particles. The surface area was calculated by pixel-wise method. \n\nDFT computation. DFT spin-polarized calculations were carried out with the cluster and periodic approaches using respectively, deMon2k.6.0.2 developers version55,56 and the Vienna Ab Initio Simulation Package $(\\mathrm{VASP})^{57,58}$ computer programs on graphene sheets (with defects) integrating various moieties from the ferrous and ferric $\\mathrm{FeN}_{4}\\mathrm{C}_{10}$ and $\\mathrm{FeN}_{4}\\mathrm{C}_{12}$ subgroups. The considered cluster and periodic models are reported in Supplementary Fig. 13. The dangling bonds in all structures were saturated with hydrogen atoms. In the cluster calculations, the electrons of the C, H and N atoms are described by triple- $\\boldsymbol{\\xi}$ basis set and of Fe by double- $\\boldsymbol{\\xi}$ plus polarization $(\\mathrm{D}\\mathrm{}Z\\mathrm{}\\mathrm{V}\\mathrm{P}2)^{59}$ . Electronic exchange and correlation effects were described within the generalized gradient approximation (GGA) in the Perdew–Burke–Ernzerhof (PBE) parametrization60,61. No symmetry constraints were imposed. In deMon2k code, for all atoms, automatically generated auxiliary functions up to orbital quantum number, $l{=}3$ were used for fitting the density with the GGA functionals62. The GGA functionals were also coupled to an empirical dispersion $\\mathbf{\\mathrm{(}D)}\\operatorname{term}^{63}$ . A quasi-Newton method in internal redundant coordinates with analytical energy gradients was used for structure optimization of ferrous and ferric models in high-spin state. For the numerical integrations of the exchange-correlation energy and potential, we used an adaptive grid with tighten threshold $(10^{-8}\\mathrm{AU})^{64}$ . The convergence was based on the Cartesian gradient and displacement vectors with thresholds of $10^{-3}\\mathrm{AU}$ and the energy convergence was set to $10^{-7}$ AU. The DFT calculations with periodic boundary conditions, carried out with VASP code, used the models 2e and 2a to build the unit cells for periodic calculations. In the case of the cluster model 1e, the corresponding periodic structure 2e was modelled using a cell size $17.19\\times20.89\\mathring\\mathrm{A}$ . In the case of model 1a, the corresponding periodic structure 2a was constructed using cell size of $9.94\\times12.64\\mathring\\mathrm{A}$ . A vacuum region of $15\\mathrm{\\AA}$ was introduced in the $z$ direction to eliminate interactions between the graphene sheet and its periodic images. All the DFT calculations with periodic boundary conditions were performed using the PBE exchange-correlation functional and VASP 5.2 recommended projector augmented-wave pseudopotentials65,66. For the calculation of structural and electronic properties, standard projector augmented-wave potentials supplied with VASP were used, with four valence electrons for C $(2s^{2}2p^{2})$ , with five electrons for O $(2s2p^{3})$ , eight valence electrons for Fe $(4s^{2}3d^{6})$ and six valence electrons for O $(2s2p^{4})$ , respectively. Electric field gradients at the positions of the Fe nuclei were calculated using the method reported in ref. 67 as implemented in VASP. When calculating electric field gradient, we have used the corresponding Green’s wavefunction (GW) potentials (pseudopotentials optimized for $G W$ calculations, in which the self-energy operator is the product of the Green function $G$ and the screened Coulomb interaction $W$ ), which give a better description of high-energy unoccupied states. For Fe, GW pseudopotential that treats 3s and $3p$ states as valence states was used. Cut-off energy for the plane wave basis set of $800\\mathrm{eV}_{:}$ , break condition for electronic SC loop of $10^{-6}\\mathrm{eV}$ and $8\\times8\\times1$ gamma centred mesh for the model 2a, and $4\\times4\\times1$ mesh for the model 2e were found to lead to the converged electric field gradients. In all cases, the Fermi–Dirac smearing method with sigma set to 0.03 was used. In addition, all the calculations included support grid for the evaluation of the augmentation charges. \n\nThe Bader charge density analysis68 with the implementation of Henkelman and coworkers69 in VASP code was used to obtain the spin-charge density of the periodic structures. The charge-spin density of the cluster structures was obtained using the Mulliken population scheme. \n\nThe atomic spin densities were computed for all cluster and periodic models to verify the spin density at the ferric or ferrous Fe site. The Fe spin density in its high and intermediate spins was found to amount to roughly $4e^{-}$ and $2e^{-}$ , respectively. Note that, in high-spin models, spin polarization of C and N sites occurs before the increase of spin density on Fe. Therefore, the total spin of each cluster or unit cell model was increased until the spin density on Fe became approximately $4e^{-}$ , for which the QS energies were obtained (Supplementary Table 5). This approach differs from our previous study on high-spin ferric models33, where the spin state referred to the total spin of the clusters. \n\nThe QS energy is computed as the coupling between the nuclear quadrupole moment (Q) the non-spherical nucleus and the principle components $V_{i i}\\left(i=x,y,z\\right)$ of the electric filed gradient tensor at $^{57}\\mathrm{Fe}$ nucleus using the following equation: \n\n$$\n\\Delta E_{Q}=\\frac{1}{2}e Q V_{z z}\\sqrt{1+\\frac{\\eta^{2}}{3}}\n$$ \n\nwhere $e$ is the charge of the electron and the asymmetry parameter $\\eta$ is computed as $\\eta=\\left(V_{x x}-V_{y y}\\right)/\\bar{V}_{z z}$ , where $\\lvert V_{z z}\\rvert\\ge\\lvert V_{y y}\\rvert\\ge\\lvert V_{x x}\\rvert$ : The nuclear quadrupole moment, $Q,$ for the $J{=}3/2$ state is taken tIo be 0\u001f.16 b\u001farn. Computation of $\\Delta E_{\\mathrm{Q}}$ and $\\eta$ therefore becomes a question of computing the electric field gradient (EFG) tensor, which is readily obtained as an expectation value of the EFG operator, $\\begin{array}{r}{V_{i j}=\\Psi_{0}\\bigg|\\frac{3i j-r^{2}}{r^{5}}\\bigg|\\Psi_{0},}\\end{array}$ for the electronic ground state $\\psi_{\\scriptscriptstyle0}$ and ${i,j=x,y,z}$ being the componIents of \u001fthe electron radius vector $r$ . For a direct comparison to experimentally reported values, calculated values of $\\Delta E_{Q}$ are reported in units of $\\mathrm{mm}s^{-1}$ . \n\n# Data availability \n\nThe raw data that support the findings of this study are available from the corresponding authors upon request. In addition to being available upon request, the XAS raw data associated with this work is permanently stored at Synchrotron SOLEIL; the raw data related to electron microscopy images are permanently stored at LEPMI; the raw data related to $\\mathrm{\\DeltaX}$ -ray radiographs are permanently stored at the APS synchrotron; the $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy data and the raw and reconstructed tomography data are available at Institut Charles Gerhardt Montpellier. Source data are provided with this paper. \n\n# Code availability \n\nThe source code used for DFT calculation with deMon2k is available at http://www. demon-software.com/public_html/download.html, upon request for academic purposes. VASP is a proprietary software available for purchase at https://www. vasp.at/. \n\nReceived: 6 March 2020; Accepted: 28 October 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Katsounaros, I., Cherevko, S., Zeradjanin, A. R. & Mayrhofer, K. J. J. Oxygen electrochemistry as a cornerstone for sustainable energy conversion. Angew. Chem. Int. Ed. 53, 102–121 (2014). \n2.\t Chen, Y. et al. Enhanced oxygen reduction with single-atomic-site iron catalysts for a zinc-air battery and hydrogen-air fuel cell. Nat. Commun. 9, 5422 (2018). \n3.\t Jung, H.-G., Hassoun, J., Park, J.-B., Sun, Y.-K. & Scrosati, B. An improved high-performance lithium–air battery. Nat. Chem. 4, 579–582 (2012). \n4.\t Sharma, S. & Pollet, B. G. Support materials for PEMFC and DMFC electrocatalysts—a review. J. Power Sources 208, 96–119 (2012). \n5.\t Rahimnejad, M., Adhami, A., Darvari, S., Zirepour, A. & Oh, S.-E. Microbial fuel cell as new technology for bioelectricity generation: a review. Alex. Eng. J. 54, 745–756 (2015). \n6.\t Yin, X., Lin, L., Martinez, U. & Zelenay, P. $^{2,2^{\\prime}}$ -Dipyridylamine as heterogeneous organic molecular electrocatalyst for two-electron oxygen reduction reaction in acid media. ACS Appl. Energy Mater. 2, 7272–7278 (2019). \n7.\t Sun, Y. et al. Activity–selectivity trends in the electrochemical production of hydrogen peroxide over single-site metal–nitrogen–carbon catalysts. J. Am. Chem. Soc. 141, 12372–12381 (2019). \n8.\t Yang, S. et al. Toward the decentralized electrochemical production of $\\mathrm{H}_{2}\\mathrm{O}_{2}\\mathrm{:}$ a focus on the catalysis. ACS Catal. 8, 4064–4081 (2018). \n9.\t Moussallem, I., Pinnow, S., Wagner, N. & Turek, T. Development of high-performance silver-based gas-diffusion electrodes for chlor-alkali electrolysis with oxygen depolarized cathodes. Chem. Eng. Process. 52, 125–131 (2012). \n10.\tZiegelbauer, J. M. et al. Chalcogenide electrocatalysts for oxygen-depolarized aqueous hydrochloric acid electrolysis. Electrochim. Acta 52, 6282–6294 (2007). \n11.\t Li, J., Jia, Q., Ghoshal, S., Liang, W. & Mukerjee, S. Highly active and stable Fe–N–C catalyst for oxygen depolarized cathode applications. Langmuir 33, 9246–9253 (2017). \n12.\tWang, X. X., Swihart, M. T. & Wu, G. Achievements, challenges and perspectives on cathode catalysts in proton exchange membrane fuel cells for transportation. Nat. Catal. 2, 578–589 (2019). \n13.\tOtt, S. et al. Ionomer distribution control in porous carbon-supported catalyst layers for high-power and low Pt-loaded proton exchange membrane fuel cells. Nat. Mater. 19, 77–85 (2019). \n14.\tHuang, X. et al. High-performance transition metal–doped $\\mathrm{Pt}_{3}\\mathrm{Ni}$ octahedra for oxygen reduction reaction. Science 348, 1230–1234 (2015). \n15.\tZitolo, A. et al. Identification of catalytic sites for oxygen reduction in iron- and nitrogen-doped graphene materials. Nat. Mater. 14, 937–942 (2015). \n16.\tZitolo, A. et al. Identification of catalytic sites in cobalt–nitrogen–carbon materials for the oxygen reduction reaction. Nat. Commun. 8, 957 (2017). \n17.\tProietti, E. et al. Iron-based cathode catalyst with enhanced power density in polymer electrolyte membrane fuel cells. Nat. Commun. 2, 416 (2011). \n18.\t Chung, H. T. et al. Direct atomic-level insight into the active sites of a high-performance PGM-free ORR catalyst. Science 357, 479–484 (2017). \n19.\tChoi, C. H. et al. Minimizing operando demetallation of Fe–N–C electrocatalysts in acidic medium. ACS Catal. 6, 3136–3146 (2016). \n20.\tChoi, C. H. et al. Unraveling the nature of sites active toward hydrogen peroxide reduction in Fe‐N‐C catalysts. Angew. Chem. Int. Ed. 56, 8809–8812 (2017). \n21.\tKumar, K. et al. Physical and chemical considerations for improving catalytic activity and stability of non-precious-metal oxygen reduction reaction catalysts. ACS Catal. 8, 11264–11276 (2018). \n22.\tChenitz, R. et al. A specific demetalation of $\\mathrm{Fe-N_{4}}$ catalytic sites in the micropores of $\\mathrm{NC\\_Ar+NH_{3}}$ is at the origin of the initial activity loss of the highly active Fe/N/C catalyst used for the reduction of oxygen in PEM fuel cells. Energy Environ. Sci. 11, 365–382 (2018). \n23.\tFerrandon, M. et al. Stability of iron species in heat-treated polyaniline–iron– carbon polymer electrolyte fuel cell cathode catalysts. Electrochim. Acta 110, 282–29 (2013). \n24.\tLefèvre, M. & Dodelet, J.-P. Fe-based catalysts for the reduction of oxygen in polymer electrolyte membrane fuel cell conditions: determination of the amount of peroxide released during electroreduction and its influence on the stability of the catalysts. Electrochim. Acta 48, 2749–2760 (2003). \n25.\tChoi, C. H. et al. The achilles’ heel of iron-based catalysts during oxygen reduction in an acidic medium. Energy Environ. Sci. 11, 3176–3182 (2018). \n26.\tChoi, C. H. et al. Stability of Fe–N–C catalysts in acidic medium studied by operando spectroscopy. Angew. Chem. Int. Ed. 54, 12753–12757 (2015). \n27.\tGoellner, V. et al. Degradation of $\\mathrm{Fe/N/C}$ catalysts upon high polarization in acid medium. Phys. Chem. Chem. Phys. 16, 18454–18462 (2014). \n28.\tHerranz, J. et al. Unveiling N-protonation and anion-binding effects on Fe/N/C catalysts for $\\mathrm{O}_{2}$ reduction in proton-exchange-membrane fuel cells. J. Phys. Chem. C. 115, 16087–16097 (2011). \n29.\tSantori, P. G. et al. Effect of pyrolysis atmosphere and electrolyte pH on the oxygen reduction activity, stability and spectroscopic signature of $\\mathrm{FeN}_{x}$ moieties in Fe–N–C catalysts. J. Electrochem. Soc. 166, F3311–F3320 (2019). \n30.\tKumar, K. et al. On the influence of oxygen on the degradation of Fe–N–C catalysts. Angew. Chem. Int. Ed. 59, 3235–3243 (2020). \n31.\tKramm, U. I. et al. Structure of the catalytic sites in Fe/N/C-catalysts for $\\mathrm{~O}_{2}$ -reduction in PEM fuel cells. Phys. Chem. Chem. Phys. 14, 11673–11688 (2012). \n32.\tKramm, U. I., Lefèvre, M., Larouche, N., Schmeisser, D. & Dodelet, J.-P. Correlations between mass activity and physicochemical properties of Fe/N/C catalysts for the ORR in PEM fuel cell via $^{57}\\mathrm{Fe}$ Mossbauer spectroscopy and other techniques. J. Am. Chem. Soc. 136, 978–985 (2014). \n33.\tMineva, T. et al. Understanding active sites in pyrolyzed Fe–N–C catalysts for fuel cell cathodes by bridging density functional theory calculations and $^{57}\\mathrm{Fe}$ Mössbauer Spectroscopy. ACS Catal. 9, 9359–9371 (2019). \n34.\tWagner, S. et al. Elucidating the structural composition of a Fe–N–C catalyst by nuclear and electron resonance techniques. Angew. Chem. Int. Ed. 58, 10486–10492 (2019). \n35.\tZelenay, P. & Myers, D. J. Hydrogen and Fuel Cells Program: 2019 annual merit review and peer evaluation meeting—ElectroCat (Electrocatalysis Consortium) US Department of Energy https://www.hydrogen.energy.gov/ pdfs/review19/fc160_myers_zelenay_2019_o.pdf (2019). \n36.\tBanham, D. et al. Critical advancements in achieving high power and stable nonprecious metal catalyst–based MEAs for real-world proton exchange membrane fuel cell applications. Sci. Adv. 4, 7180 (2018). \n37.\tZboril, R., Mashlan, M. & Petridis, D. Iron(III) oxides from thermal processes—synthesis, structural and magnetic properties, Mössbauer spectroscopy characterization, and applications. Chem. Mater. 14, 969–982 (2002). \n38.\tKamali-M, S., Ericsson, T. & Wäppling, R. Characterization of iron oxide nanoparticles by Mössbauer spectroscopy. Thin Solid Films 515, 721–723 (2006). \n39.\tLyubutin, I. S. et al. Structural and magnetic properties of iron oxide nanoparticles in shells of hollow microcapsules designed for biomedical applications. Croat. Chem. Acta 88, 397–403 (2015). \n40.\tSougrati, M. T., Goellner, V., Schuppert, A. K., Stievano, L. & Jaouen, F. Probing active sites in iron-based catalysts for oxygen electro-reduction: a temperature-dependent 57Fe Mössbauer spectroscopy study. Catal. Today 262, 110–120 (2016). \n41.\tPrincipi, E., Di Cicco, A., Witkowska, A. & Marassi, R. Performance of a fuel cell optimized for in situ X-ray absorption experiments. J. Synchrotron Rad. 14, 276–281 (2007). \n42.\tLi, J. et al. Structural and mechanistic basis for the high activity of Fe–N– catalysts toward oxygen reduction. Energy Environ. Sci. 9, 2418–2432 (2016). \n43.\t Osmieri, L. et al. Elucidation of Fe–N–C electrocatalyst active site functionality via in-situ X-ray absorption and operando determination of oxygen reduction reaction kinetics in a PEFC. Appl. Catal. B. 257, 117929 (2019). \n44.\t Li, J., Alsudairi, A., Ma, Z.-F., Mukerjee, S. & Jia, Q. Asymmetric volcano trend in oxygen reduction activity of Pt and non-Pt catalysts: in situ identification of the site-blocking effect. J. Am. Chem. Soc. 139, 1384–1387 (2017). \n45.\tFultz, B. in Characterization of Materials 1–21 (E. N. Kaufmann, Wiley, 2002). \n46.\tBonomi, F. et al. Characterization, Properties and Applications (Walter de Gruyter, 2017). \n47.\tVankó, G. et al. Probing the 3d spin momentum with X-ray emission spectroscopy: the case of molecular-spin transitions. J. Phys. Chem. B. 110, 11647–11653 (2006). \n48.\tJia, Q. et al. Experimental observation of redox-induced Fe–N switching behavior as a determinant role for oxygen reduction activity. ACS Nano 9, 12496–12505 (2015). \n49.\tHossen, M. M., Artyushkova, K., Atanassov, P. & Serov, A. Synthesis and characterization of high performing Fe–N–C catalyst for oxygen reduction reaction (ORR) in alkaline exchange membrane fuel cells. J. Power Sources 375, 214–221 (2018). \n50.\tVarela, A. S. et al. pH effects on the selectivity of the electrocatalytic $\\mathrm{CO}_{2}$ reduction on graphene-embedded Fe–N–C motifs: bridging concepts between molecular homogeneous and solid-state heterogeneous catalysis. ACS Energy Lett. 3, 812–817 (2018). \n51.\tAblett, J. M. et al. The GALAXIES inelastic hard X-ray scattering end-station at Synchrotron SOLEIL. J. Synchrotron Radiat. 26, 263–271 (2019). \n52.\tRueff, J. P. et al. The GALAXIES beamline at the SOLEIL synchrotron: inelastic X-ray scattering and photoelectron spectroscopy in the hard X-ray range. J. Synchrotron Radiat. 22, 175–179 (2015). \n53.\tGürsoy, D., DeCarlo, F., Xiao, X. & Jacobsen, C. Tomopy: a framework for the analysis of synchrotron tomographic data. J. Synchrotron Radiat. 21, 1188–1193 (2014). \n54.\tDragonfly 4.1 (Object Research Systems (ORS) Inc., 2019); http://www. theobjects.com/dragonfly \n55.\tde la Lande, A. et al. Molecular Simulations with in-deMon2k QM/MM, a tutorial-review. Molecules 24, 1653 (2019). \n56.\tKoster, A. M. et al. deMon2k v.6 (The deMon developers, 2018). \n57.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B. 54, 11169–11186 (1996). \n58.\tKresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n59.\tGodbout, N., Salahub, D. R., Andzelm, J. & Wimmer, E. Optimization of Gaussian-type basis sets for local spin density functional calculations. Part I. Boron through neon, optimization technique and validation. Can. J. Chem. 70, 560 (1992). \n60.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n61.\tZhang, Y. & Yang, W. Comment on ‘Generalized Gradient Approximation Made Simple’. Phys. Rev. Lett. 80, 890–890 (1998). \n62.\tKöster, A. M., Reveles, J. U. & Del, J. C. Calculation of exchange-correlation potentials with auxiliary function densities. J. Chem. Phys. 121, 3417–3424 (2004). \n63.\tWu, Q. & Yang, W. Empirical correction to density functional theory for van der Waals interactions. J. Chem. Phys. 116, 515–524 (2001). \n64.\tKrack, M. & Köster, A. M. An adaptive numerical integrator for molecular integrals. J. Chem. Phys. 108, 3226–3234 (1998). \n65.\tBlöchl, P. E. Projector augmented-wave method. Phys. Rev. B. 50, 17953–17979 (1994). \n66.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B. 59, 1758–1775 (1999). \n67.\tPetrilli, H. M., Blöchl, P. E., Blaha, P. & Schwarz, K. Electric-field-gradient calculations using the projector augmented wave method. Phys. Rev. B. 57, 14690–14697 (1998). \n68.\tBader, R. F. W. Atoms in Molecules: A Quantum Theory (Oxford Univ. Press, 1994). \n69.\tTang, W., Sanville, E. & Henkelman, G. A grid-based Bader analysis algorithm without lattice bias. J. Phys. Condens. Matter 21, 084204 (2009). \n\n# Acknowledgements \n\nThe research leading to these results has received partial funding from the French National Research Agency under the CAT2CAT contract (no. ANR-16-CE05-0007), the FCH Joint Undertaking (CRESCENDO project, grant agreement no. 779366) and the Centre of Excellence of Multifunctional Architectured Materials ‘CEMAM’ (grant no. ANR-10-LABX-44-01). We acknowledge Synchrotron SOLEIL (Gif-sur Yvette, France) for provision of synchrotron radiation facilities at beamline GALAXIES (proposal no. 20170390) and at beamline SAMBA (proposal no. 99190122). I.Z. acknowledges the resources of the APS, a US Department of Energy (DOE) Office of Science User Facility operated for the US DOE Office of Science by the ANL under contract no. DE-AC02-06CH11357. I.M. gratefully acknowledges the computational resources of the National Energy Research Scientific Computing Center (NERSC), a US DOE Office of Science User Facility operated under contract no. DE-AC02-05CH11231. This paper has been assigned LA-UR-19-31453. The computational work of T.M and I.C.O. was granted access to the HPC resources of IDRIS/TGCC under the allocation no. 2019-A0050807369 made by the Grand équipement national de calcul intensif and supported by the LabExCheMISyst ANR-10-LABX-05-01. G.D. acknowledges the financial support from Slovenian Research Agency (P2-0393). \n\n# Author contributions \n\nJ.L. and F.J. designed and synthesized the materials, and conducted the electrochemical and physical characterizations. M.T.S. and J.L. designed and conducted the in situ and ex situ Mössbauer spectroscopy measurements. M.T.S. conducted Mössbauer data analysis. A.Z. and J.L. conducted the operando and ex situ XAS measurements. A.D.C. designed the operando fuel cell for XAS. F.J., A.Z., J.L. and J.M.A. conducted the in situ XES experiments. I.C.O., T.M., I.M. and P.A. conducted the DFT computation. K.K., L.D. and F.M. performed TEM and STEM–EDX analyses, G.D. performed atomic-scale STEM analyses, I.Z. and Y.H. performed tomography and TEM analyses. J.L., M.T.S. and F.J. wrote and edited the manuscript with input from all authors. F.J. supervised the project. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nExtended data is available for this paper at https://doi.org/10.1038/s41929-020-00545-2. \n\nSupplementary information is available for this paper at https://doi.org/10.1038/ s41929-020-00545-2. \n\nCorrespondence and requests for materials should be addressed to F.J. \n\nPeer review information Nature Catalysis thanks Esen Alp, Gang Wu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 \n\n![](images/027021433ace30f999bb66aa61ba5da28ac5b0818a772f83b5a6723ae12b9388.jpg) \nExtended Data Fig. 1 | Ex situ characterization of pristine powder catalysts. SEM images of a, $\\mathsf{F e}_{0.5}$ and b, $\\mathsf{F e}_{0.5}$ -950(10), TEM images of c, $\\mathsf{F e}_{0.5}$ and d, $\\mathsf{F e}_{0.5}$ - 950(10), XRD patterns of e, $\\mathsf{F e}_{0.5}$ and f, $\\mathsf{F e}_{0.5}{-950(10)}$ , STEM images of $\\mathsf{F e}_{0.5}$ in g, high-angle annular dark-field (HAADF) mode, h, fast Fourier transform filtered HAADF and i, annular bright field mode. $\\mathsf{F e}_{0.5}$ -950(10) powder was stored in glove box before any characterisation, to avoid formation of Fe particles in ambient conditions. $\\mathsf{F e}_{0.5}$ catalyst does not lead to the formation of Fe particles even after months of storage in ambient conditions. \n\n![](images/0b22b5f64845de7855a404111d634b413a7d8ba00898322f56a3ff95a7c5e5d0.jpg) \nExtended Data Fig. 2 | Ex situ 57Fe Mössbauer spectra of $\\mathsf{F e}_{0.5}.$ Acquired in ambient air at $300\\mathsf{K}$ for $\\mathsf{F e}_{0.5}$ powder a, at $300\\mathsf{K}$ for $\\mathsf{F e}_{0.5}$ -cathode b, at 5 K for $\\mathsf{F e}_{0.5}$ powder c, and at $5{\\sf K}$ for $\\mathsf{F e}_{0.5}$ -cathode d. \n\n![](images/237e1b1567f80dca7933e3ca2770a5614ae895cd3c966050bcb35a17f46e755e.jpg) \nExtended Data Fig. 3 | See next page for caption. \n\n# Articles \n\n# Nature Catalysis \n\nExtended Data Fig. 3 | Operando X-ray absorption spectroscopy of $\\mathsf{F e}_{0.5}$ . Operando Fe K-edge XANES a, and FT-EXAFS b, spectra of $\\mathsf{F e}_{0.5}$ -cathode as a function of electrochemical potential, c, position of redox peak in the CV of $\\mathsf{F e}_{0.5}$ compared to ΔE (right handside y-axis), the threshold energy of the XANES spectrum relative to a metallic Fe foil. The spectra were measured in a PEMFC (Cell 2). The cell temperature was $80^{\\circ}\\mathsf C$ , the flow rates for $\\mathsf{O}_{2}$ and ${\\sf H}_{2}$ gases were 60 sccm with $100\\%$ relative humidity, no backpressure. The cathode loading was $4\\mathsf{m g}_{\\mathsf{F e N C}}{\\cdot}\\mathsf{c m}^{-2}$ , the anode loading was $0.5\\mathsf{m g}_{\\mathsf{p t}}\\mathsf{\\cdot c m^{-2}}$ and the membrane was Nafion 211. The operando XAS acquisition duration was ca $4\\min$ at each potential. For c), the CV was measured with a rotating disk electrode (RDE) in ${\\mathsf N}_{2}$ -saturated 0.1 M ${\\mathsf{H C l O}}_{4}$ at $20\\mathsf{m}\\mathsf{V}{\\cdot}\\mathsf{s}^{-1}$ and the loading of $\\mathsf{F e}_{0.5}$ was $0.8\\mathsf{m g}{\\cdot}\\mathsf{c m}^{-2}$ . The reference and counter electrodes were a RHE and graphite rod. \n\n![](images/98e72fe7ae7da3d4db437ba3d9b51e31a7a4a61d1af93344deabc5b68059c0ed.jpg) \nExtended Data Fig. 4 | Potential holds applied vs. time for the in situ 57Fe Mössbauer spectroscopy study. The duration of each potential hold was 36 h, and each hold is labelled according to the potential value and the cycle number (the number in brackets). \n\n![](images/bc92fc262885dfae828295eb2117ef024d145fa079d431ea8a8607d0a3ba828e.jpg) \nExtended Data Fig. 5 | Scheme of the formation of iron oxides and the corresponding Mössbauer signal. A fraction of S1 sites demetallate during 0.2 V (1) a, leading to the formation of high-spin $\\mathsf{F e}^{2+}$ (possibly complexed with sulfonic acid groups in Nafion ionomer) with an associate D3 signal at room temperature b. Upon exposure to air ex situ, such high-spin $\\mathsf{F e}^{2+}$ is mainly transformed into ferric oxides, then contributing with a doublet component in EoT Mössbauer spectra at $300\\mathsf{K}\\thinspace\\mathbf{c},$ with IS and QS values similar to those of D1 (compare a and c). When the EoT Mössbauer spectra are recorded at low temperatures, the ferric oxide particles become magnetically ordered at ${\\mathsf{T}}\\leq80{\\mathsf{K}},$ then contributing with a sextet component d. \n\n![](images/49406e3d75ef5718039128f8fe5443ff6c12d29dbde299568281569b4f9374bb.jpg) \nExtended Data Fig. 6 | End-of-Test characterisation of $\\mathsf{F e}_{0.5}$ cathode after a durability test at $0.2{\\tt V}.$ Mössbauer spectrum at $5{\\sf K}$ of a, pristine $\\mathsf{F e}_{0.5}$ -cathode and c, $\\mathsf{F e}_{0.5}$ -cathode after $72\\mathsf{h}$ operation in cell 3 at $0.2\\mathsf{V}$ under $\\mathsf{O}_{2}$ at room temperature. TEM micrograph of b, pristine $\\mathsf{F e}_{0.5}$ -cathode and d, $\\mathsf{F e}_{0.5}$ -cathode corresponding to c. The low amount of Fe oxide in the pristine $\\mathsf{F e}_{0.5}$ -cathode identified in a) and/or non-uniform distribution of Fe oxide particles challenged their identification with TEM. e, $x_{R}\\mathsf{D}$ spectra of the $\\mathsf{F e}_{0.5}$ -cathode before and after $72\\mathsf{h}$ operation in cell 3 at $0.2\\mathsf{V}$ under $\\mathsf{O}_{2}$ at room temperature. The XRD pattern of graphite (00-041-1478) is shown as vertical lines. f, Tafel plots of $\\mathsf{F e}_{0.5}$ -cathode before and after $72\\mathsf{h}$ operation in cell 3 at $0.2\\mathsf{V}$ under $\\mathsf{O}_{2}$ at room temperature, measured at $80^{\\circ}\\mathsf{C}$ in the commercial PEMFC (Cell 1). An iron-free N-C cathode (synthesized identically as $\\mathsf{F e}_{0.5}$ except that no iron salt was added during ball-milling) is shown as a reference. For (d), the cell temperature was $80^{\\circ}C$ the flow rates for $\\mathsf{O}_{2}$ and ${\\sf H}_{2}$ gases were 60 sccm with $100\\%$ relative humidity, the gauge pressure was 1 bar and the cathode loading was $4\\mathsf{m g}{\\cdot}\\mathsf{c m}^{-2}$ . \n\n![](images/322840672ec6699dcc0b837baa5fea884e880005f265f7005e8723bec2e93fd6.jpg) \n\nExtended Data Fig. 7 | End-of-Test characterisation of $\\bar{\\mathsf{F e}}_{0.5}$ -950(10) cathode after durability test at $\\phantom{+}0.5\\mathsf{V}.$ Mössbauer spectra of $\\mathsf{F e}_{0.5}{-950(10)}$ cathode at $5{\\sf K}$ before a, and after b, potential hold at $0.5\\mathsf{V}$ in PEMFC for 50 hours. c, The corresponding Tafel plots of $\\mathsf{F e}_{0.5}{-950(10)}$ before and after the durability test. The cell temperature was $80^{\\circ}C$ , 60 sccm $\\mathsf{O}_{2}$ and ${\\sf H}_{2}$ gases with $100\\%$ relative humidity were fed at cathode and anode respectively, the gauge pressure was 1 bar, and the cathode loading was $4\\mathsf{m g}{\\cdot}\\mathsf{c m}^{-2}$ . TEM images of $\\mathsf{F e}_{0.5}{-950(10)}$ cathode before d, and after 50-hour durability test at $0.5\\mathsf{V}$ in PEMFC e,f. The durability tests were performed at $0.5\\mathsf{V}$ for $50\\mathsf{h}$ in the same conditions as described above. " + }, + { + "id": "10.1126_science.abi6323", + "DOI": "10.1126/science.abi6323", + "DOI Link": "http://dx.doi.org/10.1126/science.abi6323", + "Relative Dir Path": "mds/10.1126_science.abi6323", + "Article Title": "Stabilizing perovskite-substrate interfaces for high-performance perovskite modules", + "Authors": "Chen, SS; Dai, XZ; Xu, S; Jiao, HY; Zhao, L; Huang, JS", + "Source Title": "SCIENCE", + "Abstract": "The interfaces of perovskite solar cells (PSCs) are important in determining their efficiency and stability, but the morphology and stability of imbedded perovskite-substrate interfaces have received less attention than have top interfaces. We found that dimethyl sulfoxide (DMSO), which is a liquid additive broadly applied to enhance perovskite film morphology, was trapped during film formation and led to voids at perovskite-substrate interfaces that accelerated the film degradation under illumination. Partial replacement of DMSO with solid-state carbohydrazide reduces interfacial voids. A maximum stabilized power conversion efficiency (PCE) of 23.6% was realized for blade-coated p-type/intrinsic/n-type (p-i-n) structure PSCs with no efficiency loss after 550-hour operational stability tests at 60 degrees C. The perovskite mini-modules showed certified PCEs of 19.3 and 19.2%, with aperture areas of 18.1 and 50.0 square centimeters, respectively.", + "Times Cited, WoS Core": 597, + "Times Cited, All Databases": 626, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000686562400034", + "Markdown": "# SOLAR CELLS \n\n# Stabilizing perovskite-substrate interfaces for high-performance perovskite modules \n\nShangshang Chen, Xuezeng Dai, Shuang Xu, Haoyang Jiao, Liang Zhao, Jinsong Huang\\* \n\nThe interfaces of perovskite solar cells (PSCs) are important in determining their efficiency and stability, but the morphology and stability of imbedded perovskite-substrate interfaces have received less attention than have top interfaces. We found that dimethyl sulfoxide (DMSO), which is a liquid additive broadly applied to enhance perovskite film morphology, was trapped during film formation and led to voids at perovskite-substrate interfaces that accelerated the film degradation under illumination. Partial replacement of DMSO with solid-state carbohydrazide reduces interfacial voids. A maximum stabilized power conversion efficiency (PCE) of $23.6\\%$ was realized for blade-coated $\\boldsymbol{\\mathsf{p}}$ -type/intrinsic/n-type (p-i-n) structure PSCs with no efficiency loss after 550-hour operational stability tests at ${\\tt60^{\\circ}C}$ . The perovskite mini-modules showed certified PCEs of 19.3 and $19.2\\%$ , with aperture areas of 18.1 and 50.0 square centimeters, respectively. \n\nn (ePrtCifEise)dfopropwerovcsoknivtersoiloanr ecfeflilcs (ePnSciCess) have exceeded $25\\%$ for small-area singleU junction cells and $29\\%$ for perovskitesilicon tandem cells (1–3). However, degradation caused by various stimuli remains a critical challenge for PSC commercialization (4, 5). Degradation of PSCs starts from the interfaces, including both perovskite-metal electrodes and perovskites-substrates, where defects enrich (6–9). However, most research efforts have focused on stabilizing perovskitemetal electrode interface through surface passivation (10) or post-fabrication treatment $(I I)$ , whereas the imbedded perovskite-substrate interface has received less attention, in part because of difficulties in its study with morphology characterization methods such as scanning electron microscopy (SEM) or atomic force microscopy (AFM). Nevertheless, stabilizing the imbedded bottom interfaces is as important as that of top interface (12). Trap density profiling showed that the perovskite layers near the substrate side have an even higher defect concentration, particularly deep charge traps, than that of perovskite-metal electrode interfaces (6). High-resolution transmittance electron microscopy also revealed that perovskite at this interface contains amorphous regions or nanocrystals with large interface areas. Light is incident from the perovskitesubstrate interface and also makes it more vulnerable to degradation. \n\nhave intimate contact with the substrate. The morphology of the $\\mathrm{\\mathbf{MAPbI_{3}}}$ -substrate interface was investigated by first peeling off the bladecoated $\\mathbf{MAPbI_{3}}$ films from the ITO glass substrates with an epoxy encapsulant (Fig. 1A, scheme). After exposing the perovskite bottom surfaces next to the PTAA HTL layer, we discovered by use of SEM voids in the perovskite surface with sizes of tens to hundreds of nanometers (Fig. 1B). These voids were not caused by the breakdown of perovskite grains during the peeling-off process; otherwise, residual particles would have been left on the ITO substrates, and none was seen in SEM, AFM, and x-ray photoelectron spectroscopy (XPS) characterizations on the corresponding ITO substrates after their peeling off (fig. S1). \n\nthese voids was related to the entrapped nonvolatile dimethyl sulfoxide (DMSO) near the bottom of perovskite films. We replaced DMSO partially with a solid-state leadcoordinating additive of carbohydrazide (CBH), which reduced the formation of interfacial voids, yielding blade-coated p-type/intrinsic/ n-type (p-i-n) structure PSCs with a highest stabilized PCE of $23.6\\%$ and a module efficiency of $19.2\\%$ $50.0\\ \\mathrm{cm}^{2}$ ), certified by the National Renewable Energy Laboratory (NREL). In addition, the reduced interfacial voids and the CBH residuals in perovskite films stabilized the PSCs and improved the yield of highefficiency perovskite modules. \n\nThe PSCs were fabricated with a p-i-n structure of glass/indium tin oxide (ITO)/poly[bis (4- phenyl)(2,4,6-trimethylphenyl)amine (PTAA)/ perovskite/fullerene $\\mathrm{(C_{60})}$ )/bathocuproine (BCP)/ copper (Cu). Both the PTAA hole-transporting layer (HTL) and perovskite films were prepared with a room-temperature blade-coating method that we had developed previously (13). A mixed solvent composing of volatile and nonvolatile solvents, such as volatile 2-methoxyethanol (2-ME) mixed with nonvolatile DMSO, has been widely adopted to coat large-area perovskite films (14–16). During the blade-coating of perovskite films, the majority fraction, 2-ME, quickly evaporated to leave the “wet” films under $\\mathrm{{N}_{2}}$ blowing at room temperature. The small fraction of the nonvolatile DMSO retarded the crystallization to yield large grains as well as intimate contact with bottom substrates. \n\nIn this work, we discovered a high density of voids at the perovskite-substrate interfaces of the bladed and spun perovskite films with a variety of compositions by peeling them off from the substrates. The perovskites around these voids underwent faster degradation under light illumination. The formation of \n\nIn our previous study of blade-coating efficient methylammonium lead tri-iodide $\\mathrm{(MAPbI_{3})}$ minimodules, the addition of $13\\%$ DMSO [molar ratio to lead (Pb)] optimized the formation of a crystalline intermediate phase with methylammonium iodide (MAI) and lead iodide $\\mathrm{(PbI_{2})}$ (13), which then crystallized downward and converted into perovskite during thermal annealing $(I7)$ . A dense and mirror-like $\\mathbf{MAPbI_{3}}$ film was obtained and appeared visually to \n\nIn addition to $\\mathrm{\\mathbf{MAPbI_{3}}},$ other compositions, such as MAI-FAI (FAI, formamidinium iodide) mixed perovskites, showed similar amounts or even more voids at the perovskite-substrate interfaces. Replacing MAI partially or completely with FAI has been widely adopted in the perovskite photovoltaic community to enhance material stability and broaden the absorption spectrum (18, 19). We used $\\mathrm{MA_{0.6}F A_{0.4}P b I_{3}}$ as the perovskite composition, which remained in the black phase at room temperature. To bladecoat high-quality FAI-containing perovskite films, the percentage of DMSO had to be much higher than that for $\\mathrm{\\mathbf{MAPbI_{3}}}$ . It proved much harder to form the FAI- $\\mathrm{\\cdotPbI_{2}}$ -DMSO intermediate phase by using the same solvent system, and we had to add more DMSO to retard its crystallization. Previous reports found that pure $\\mathrm{FAPbI_{3}}$ films spun from DMSO-containing precursor solutions had no notable FAI-containing intermediate phase (20). \n\nWe studied the effect of DMSO on the perovskites near the HTL interface by changing the molar ratio of DMSO to $\\mathrm{Pb}$ in $\\mathrm{MA_{0.6}F A_{0.4}P b I_{3}}$ precursor solutions from 0 to $50\\%$ Using the same peeling technique, the bottom interface morphology (Fig. 1B) at a lower amount of DMSO $(<13\\%)$ was very poor. Insufficient DMSO was present, and rapid crystallization of the precursor solution rapidly created a porous film full of voids. Increasing the amount of DMSO to $\\mathrm{\\Pb}$ from 13 to $25\\%$ reduced both the density and size of voids at the perovskite bottom interface. The PCEs of the corresponding PSCs increased from 19.0 to $21.5\\%$ (fig. S2 and table S1). Further increasing the amount of DMSO to $38\\%$ yielded a maximum PCE of $22.0\\%$ (hereafter denoted as the control device), despite the density of interfacial voids increasing and the reappearance of some large voids. The presence of the interfacial voids was also confirmed with cross-sectional SEM (fig. S3) and focused ion beam (FIB)–SEM (fig. S4A) characterizations. Increasing the amount of DMSO to $50\\%$ created a film with much larger interfacial voids and a PCE of $16.4\\%$ . \n\n![](images/81440ddd9ba37e775f0c521e7795b1add749183a0e2203fe62682dab5931c65b.jpg) \nFig. 1. Investigate the morphology of perovskite-substrate interfaces by peeling off perovskite films from ITO glass substrates. \n(A) Schematic of peeling off perovskite films from ITO glass substrates with an epoxy encapsulant for SEM characterization. (Right) A peeled-off device from ITO glass substrate. (B) Top-view SEM images of the perovskite-substrate interfaces of the blade-coated perovskite films that were prepared from the precursor solutions with different amounts of DMSO and then peeled off from ITO glass substrates. Scale bars, $1\\upmu\\mathrm{m}$ . (C) Schematic shows how the voids are formed at the perovskitesubstrate interfaces. (D) Top-view SEM images of the peeled-off perovskite-substrate interfaces of the light-soaked $\\mathsf{M A}_{0.6}\\mathsf{F A}_{0.4}\\mathsf{P b}\\mathsf{l}_{3}$ films. Scale bars, $1\\upmu\\mathrm{m}$ . \n\nWe recently observed that the crystallization of perovskite films by using one-step solution deposition methods generally started at the film-air interface as the solvents evaporate from the film top surface, quickly forming a solid shell that temporarily traps “wet” films containing high–boiling point DMSO (17). The trapped DMSO solvent would eventually escape the films, particularly after further annealing, which left voids in the perovskite films near the perovskite-substrate interface because of the volume collapse (Fig. 1C). This phenomenon was more evident in the coated thick films that further delayed the escape of DMSO from the bottom side. We also examined perovskite films including $\\mathrm{\\mathbf{MAPbI_{3}}}$ , $\\mathrm{Cs_{0.05}F A_{0.81}M A_{0.14}P b I_{3}},$ and $\\mathrm{Cs_{0.4}F A_{0.6}P b I_{1.95}B r_{1.05}}$ spun from DMSO-containing precursor solutions. Voids were observed at all the perovskite-substrate interfaces (fig. S5), showing this phenomenon to be a general issue, despite almost all reported record performance devices fabricated with a solution process by using DMSO solutions (2, 20, 21). \n\n![](images/60f7a1af88fe3bc5e41dd818165907684a3c35eb61ed6bb3ea2b003b709b0a78.jpg) \nFig. 2. Characterization of perovskite films. (A) Chemical structures of DMSO and CBH. (B) FTIR spectra of DMSO, CBH, and the $\\mathsf{M A}_{0.6}\\mathsf{F A}_{0.4}\\mathsf{P b}\\mathsf{l}_{3}$ films with the addition of DMSO and CBH. (C) Top-view SEM image of the perovskitesubstrate interface of the target perovskite film peeled off from ITO glass \nsubstrate. Scale bar, $1\\upmu\\mathrm{m}$ . (D) XPS spectra of the (bottom) perovskite-substrate and (top) perovskite-air interfaces of an identical target $\\mathsf{M A}_{0.6}\\mathsf{F A}_{0.4}\\mathsf{P b}\\mathsf{I}_{3}$ film. (E) PL maps of the (left) control and (right) target perovskite films on thin glass excited from the glass side with a $485\\cdot\\mathsf{n m}$ laser. \n\nTo investigate the evaporation rate of DMSO in perovskite films during thermal annealing, we scraped the perovskite films off glass substrates and dissolved them in deuterium oxide $\\mathrm{(D_{2}O)}$ and then performed proton nuclear magnetic resonance $\\mathrm{\\cdot^{1}H}$ NMR) characterization of the solutions to determine how much DMSO was trapped in each stage of annealing. By comparing the integrated area of DMSO $^1\\mathrm{H}$ NMR peak and those of MAI and FAI (fig. S6), we were able to quantify the relative amount of DMSO to MAI or FAI, and then that of Pb in the perovskite films. As shown in fig. S7, the evaporation of DMSO occurred in two stages: a rapid evaporation in the first few seconds and a slow process from $5\\mathrm{~s~}$ to 1 min. The top solid shell also forms within a few seconds $(I7).$ , and the slow evaporation of DMSO in the second stage should be caused by the hinderance from the perovskite top shell. Because nearly $90\\%$ of DMSO in the perovskite solution evaporated in the first ${\\mathrm{~5~s,~}}$ about $10\\%$ of DMSO, or ${\\sim}2$ mole $\\%$ $(\\mathrm{mol\\\\%})$ ) relative to Pb, was trapped initially in the wet bottom layer. We estimate that it would cause a total void volume of $0.01\\upmu\\mathrm{m}^{3}$ per cubic micrometer of perovskites on the basis of the residual DMSO amount when the subsequent entrapped DMSO leaves the perovskite-substrate interface. This roughly agrees with the results $(1\\%$ volume ratio to perovskites) obtained by analyzing the relative ratio between the regions of perovskite grains and voids in the top-view SEM image (fig. S8) and the void depth of ${\\sim}100\\ \\mathrm{nm}.$ \n\nWe examined the effect of the interfacial voids on the stability of the perovskite films. Encapsulated $\\mathrm{MA_{0.6}F A_{0.4}P b I_{3}}$ control films were light-soaked under simulated 1-sun illumination at $60^{\\circ}\\mathrm{C}$ for different durations and then peeled off from ITO substrates for SEM characterization. Some small white regions started to appear around the voids after 4 hours of lightsoaking (Fig. 1D). These white regions are generally caused by a charging effect in electron-beam scanning, which is caused by less conductive decomposition products. After 8 hours, the white regions expanded, accompanied with the generation of more and larger ones, whereas the regions without voids showed barely any change. Thus, interfacial voids initialized film degradation at the perovskitesubstrate interface. \n\nSeveral perovskite degradation mechanisms could be triggered by interfacial voids. Photogenerated holes surrounding the voids could not be quickly extracted by the $\\scriptstyle{\\mathrm{HTL}}$ , which would lead to charge accumulation that accelerates perovskite degradation by increasing ion migration (22). The surface of the voids would be similar to perovskite top surfaces that are generally defective, and lack of passivation coatings would make them degrade more quickly. Voids can act as a reservoir for decomposition products such as iodine vapor, which is generated in perovskite films during light-soaking (23, 24) and can accelerate decomposition (25–27). Recent studies also show that passivating the perovskite film surfaces can effectively shift the reaction balance for iodide interstitials and thus prevent the iodide generation under illumination (23). \n\nTo address this issue, we replaced partial DMSO with a solid-state CBH additive (melting point $153^{\\circ}\\mathrm{C}$ , denoted as target films or PSCs) that can also coordinate with $\\mathrm{\\Pb}$ cations by means of its $\\scriptstyle\\mathrm{C=O}$ bond, similar to DMSO (Fig. 2A). CBH barely evaporated during thermal annealing and thus remained within the perovskite films (figs. S9 and S10). It avoids the volume collapse during annealing and thus reduces void formation. Moreover, CBH can reduce the detrimental $\\mathrm{I_{2}}$ generated in perovskite films. First, we confirmed the shifted Fourier-transform infrared spectroscopy (FTIR) peak of $\\scriptstyle\\mathrm{C=O}$ bond after introducing CBH into the $\\mathrm{MA_{0.6}F A_{0.4}P b I_{3}}$ films (Fig. 2B). Such an interaction was found to slow down the rapid crystallization and enhance crystallization of perovskite films (figs. S11 and S12). \n\n![](images/e798efea0a2564b662cb131a2f907962d8789a336d3e6be8d0e2cc8a1d31fe1d.jpg) \nFig. 3. Photovoltaic performance of PSCs. (A) $J-V$ curve of the champion of the peeled-off perovskite-substrate interface of the light-soaked (left) target PSC. (Inset) The stabilized power output of the champion target PSC control and (right) target PSCs after stability test. Scale bars, $1\\upmu\\mathrm{m}$ . fixed at a bias of $1.04\\:\\Vdash$ for $600{\\mathrm{~s}}.$ . (B) The efficiency distribution of 65 target (D) UV-vis absorption spectra of the toluene solutions in which control and PSCs. (C) Operational stability test results of the encapsulated control and target $\\mathsf{M A}_{0.6}\\mathsf{F A}_{0.4}\\mathsf{P b}\\mathsf{l}_{3}$ films were immersed under 1-sun illumination for target PSCs processed under 1-sun equivalent illumination in air. Neither 15 hours. (Inset) A picture of the vials in which each film (15 by $15~\\mathsf{m m}$ ) was cooling nor UV filters were used in this test. (Inset) The top-view SEM images immersed into $5~\\mathsf{m l}$ of toluene. \n\nBecause of the nonvolatility of CBH, voids were dramatically reduced with the CBH additive (Fig. 2C and figs. S4B and S13). Some amount of DMSO ( $\\sim25\\%$ to $\\mathrm{Pb}$ ) in the solution was needed to help the grain growth, but it was the entrapped $10\\%$ of DMSO that caused void formation. The quick top perovskite shell formation and later release of CBH molecules from the CBH-Pb coordinates should expel some CBH molecules toward HTL side because of the film-downward crystallization evidenced by the grazing incidence x-ray diffraction (GIXRD) results (fig. S14). XPS characterization of both perovskite-air and perovskite-HTL interfaces of the identical target perovskite films showed more CBH molecules at perovskite-HTL interface (Fig. 2D), whereas the control film only showed a single ammonium peak (fig. S15). In addition, we performed the photoluminescence (PL) mapping of the perovskite films excited from the thin cover glass side. The target perovskite film showed both more uniform PL emission (likely from fewer voids) and stronger PL emission (from passivation effects) than those of the control film (Fig. 2E). Both effects should reduce charge recombination and facilitate charge extraction. \n\nThe current density-voltage $\\left(J\\mathbf{-}V\\right)$ characteristics show that the target PSCs delivered a PCE of $23.8\\%$ (Fig. 3A), with an elevated opencircuit voltage $(V_{\\mathrm{OC}})$ of 1.17 V, a short-circuit current density $(J_{\\mathrm{SC}})$ of $24.1\\mathrm{mAcm^{-2}}$ , and a fill factor $(F F)$ of 0.842. The optical bandgap of the target PSCs determined from the absorption onset of the external quantum efficiency (EQE) spectra is 1.49 eV (fig. S16), which gave a small \n\n$V_{\\mathrm{OC}}$ deficit of 0.32 V. The champion PSC showed a stabilized PCE of $23.6\\%$ (Fig. 3A, inset). The PSCs also showed good reproducibility (Fig. 3B), where 50 and $88\\%$ of PSCs can realize PCEs of more than 22.5 and $22.0\\%,$ , respectively. \n\nWe tested the long-term stability of encapsulated perovskite devices under a plasma lamp with a light intensity equivalent to AM (air mass coefficient) 1.5 G (global) in air at a relative humidity of ${\\sim}40\\pm10\\%$ . No ultraviolet (UV) filter was used during the tests. All devices were connected to an automatic maximum power point (MPP) tracker so that the devices kept working under MPP conditions during light-soaking. The temperature of the devices was measured to be ${\\sim}60^{\\circ}\\mathrm{C}$ (the heating effect of light). The operational stability of control and CBH-incorporated PSCs is compared in Fig. 3C. The CBH-incorporated PSC shows negligible efficiency loss after 550 hours of light-soaking, whereas the control one was near zero-power output after $\\sim200$ hours of light-soaking. This good stability was realized without further post-treatments on the bladecoated perovskite films. \n\n![](images/9420112e85a2674c8e359f5abae2a8bb9f756fe02a0fd50f04b81c99e710998d.jpg) \nFig. 4. Photovoltaic performance of perovskite minimodules. (A) $J-V$ 112 minimodules. (Inset) The aperture efficiency distribution of 112 minimodules. characteristics of two perovskite minimodules with aperture areas of (D) Long-term operational stability results of five perovskite minimodules 17.9 and $50.1\\mathrm{cm}^{2}$ , respectively. (B) NREL certified stabilized current-voltage under simulated 1-sun illumination at $50^{\\circ}\\mathrm{C}$ . The abrupt PCE change at dots around the MPP point of the minimodules with aperture areas of $\\mathord{\\sim}400$ hours was caused by the replacement of the peeling-off PDMS 18.1 and $50.0~\\mathrm{cm}^{2}$ . (C) Average efficiencies versus aperture areas of antireflection layers. \n\nAfter the stability tests, we peeled off the light-soaked devices from ITO glass substrates and performed SEM characterization of the perovskite-substrate interfaces. The control device showed substantial degradation at its perovskite-substrate interface accompanied with the merging of the voids, whereas the CBH device did not show notable morphology changes at the bottom interface (Fig. 3C). The enhanced operational stability we attributed not only to the reduction in interfacial voids that accumulate charges and decomposition products but also to CBH being an effective reductant (fig. S17). The CBH residuals in perovskite films could further reduce the detrimental iodine formed in perovskites during the light-soaking back to I–. We immersed the target film into a vial filled with $5\\ \\mathrm{ml}$ of toluene and then illuminated it for 15 hours. The UV–visible (vis) absorption spectra of the toluene extractions show that the formation of iodine has been suppressed by the residual CBH (Fig. 3D). \n\nWe evaluated the compatibility of the CBH additive with upscaling processes by fabricating perovskite minimodules with aperture areas from 10.7 to $60.8\\mathrm{cm}^{2}$ by means of blade-coating. The minimodules with 5 and 14 subcells showed high aperture efficiencies of $20.1\\%$ $V_{\\mathrm{OC}}=1.17\\:\\mathrm{V}$ ; $J_{\\mathrm{SC}}=21.8~\\mathrm{mA~cm^{-2}}$ ; and $F F=0.786\\$ for each subcell) and $19.7\\%$ $V_{\\mathrm{OC}}=1.15\\:\\mathrm{V}$ ; $J_{\\mathrm{SC}}=21.5~\\mathrm{mA}$ ; $F F=0.798$ for each subcell) with aperture areas of 17.9 and $50.1~\\mathrm{cm}^{2}$ , respectively (Fig. 4A), derived from $J_{-}V$ scanning. The geometric fill factor (GFF) of the champion minimodules was $92\\%$ (fig. S18); thus, each subcell with an area of $3.6\\mathrm{cm}^{2}$ in the best minimodule has a $J_{\\mathrm{SC}}$ of $23.7~\\mathrm{mA~cm^{-2}}$ , $V_{\\mathrm{OC}}$ of 1.17 V, and an active area efficiency of $21.8\\%$ . \n\nWe sent our most effective minimodules to NREL for certification, and a highest stabilized aperture efficiency of 19.3 and $19.2\\%$ were reached for the minimodules with the certified aperture areas of 18.1 and $50.0~\\mathrm{cm}^{2}$ , respectively (Fig. 4B and figs. S19 and S20). Stabilizing photocurrent is needed to get the accurate efficiency for module measurement, and regular $J{-}V$ scanning generally overestimates the module efficiency by 0.5 to $1\\%$ regardless of scanning rates. The aperture efficiencies of 112 minimodules were further analyzed statistically, and their distribution is shown in Fig. 4C, inset, with their detailed photovoltaic parameters listed in table S2. More than $50\\%$ of minimodules showed aperture PCEs of ${>}19.0\\%$ , and $77\\%$ of them had efficiencies of ${>}18.5\\%$ indicating the good reproducibility of this method. We also plot efficiencies and aperture areas of the 112 minimodules in Fig. 4C. Module efficiencies were not sensitive to their aperture areas, and a high efficiency of $(18.3\\pm0.48)\\%$ was maintained with increasing aperture areas to $\\mathrm{>}60\\mathrm{cm}^{2}$ as a result of high film uniformity after introducing CBH. Furthermore, the long-term operational stability of the highly efficient perovskite minimodules was also tested with the statistical results (Fig. 4D). Five minimodules retained $85\\%$ of initial PCEs after 1000 hours of lightsoaking under simulated 1-sun illumination at $50^{\\circ}\\mathrm{C}$ . \n\n# REFERENCES AND NOTES \n\n1. NREL, Best Research-Cell Efficiency Chart (2021); \nwww.nrel.gov/pv/cell-efficiency.html. \n2. J. J. Yoo et al., Nature 590, 587–593 (2021). \n3. A. Al-Ashouri et al., Science 370, 1300–1309 (2020). \n4. Y. Rong et al., Science 361, eaat8235 (2018). \n5. J.-P. Correa-Baena et al., Science 358, 739–744 (2017). \n6. Z. Ni et al., Science 367, 1352–1358 (2020). \n7. S. Yang et al., Science 365, 473–478 (2019). \n8. F. Wang, S. Bai, W. Tress, A. Hagfeldt, F. Gao, npj Flexible \nElectronics 2, 22 (2018). \n\n9. S. P. Dunfield et al., Adv. Energy Mater. 10, 1904054 (2020). \n10. B. Chen, P. N. Rudd, S. Yang, Y. Yuan, J. Huang, Chem. Soc. Rev. 48, 3842–3867 (2019). \n11. J. Xue, R. Wang, Y. Yang, Nat. Rev. Mater. 5, 809–827 (2020). \n12. X. Yang et al., Adv. Mater. 33, e2006435 (2021). \n13. Y. Deng et al., Sci. Adv. 5, eaax7537 (2019). \n14. D.-K. Lee, D.-N. Jeong, T. K. Ahn, N.-G. Park, ACS Energy Lett. 4, 2393–2401 (2019). \n15. J. Li et al., Adv. Energy Mater. 11, 2003460 (2021). \n16. K. H. Hendriks et al., J. Mater. Chem. A Mater. Energy Sustain. 5, 2346–2354 (2017). \n17. S. Chen et al., Sci. Adv. 7, eabb2412 (2021). \n18. S.-H. Turren-Cruz, A. Hagfeldt, M. Saliba, Science 362, 449–453 (2018). \n19. Y. Deng, Q. Dong, C. Bi, Y. Yuan, J. Huang, Adv. Energy Mater. 6, 1600372 (2016). \n20. M. Kim et al., Joule 3, 2179–2192 (2019). \n21. H. Min et al., Science 366, 749–753 (2019). \n22. Y. Lin et al., Nat. Commun. 9, 4981 (2018). \n23. S. G. Motti et al., Nat. Photonics 13, 532–539 (2019). \n24. N. Aristidou et al., Angew. Chem. Int. Ed. 54, 8208–8212 (2015). \n25. F. Fu et al., Energy Environ. Sci. 12, 3074–3088 (2019). \n26. S. Wang, Y. Jiang, E. J. Juarez-Perez, L. K. Ono, Y. Qi, Nat. Energy 2, 16195 (2016). \n27. S. Chen, X. Xiao, H. Gu, J. Huang, Sci. Adv. 7, eabe8130 (2021). \n\n# ACKNOWLEDGMENTS \n\nFunding: The material and characterization research was supported by the Center for Hybrid Organic Inorganic \n\nSemiconductors for Energy (CHOISE), an Energy Frontier Research Center funded by the Office of Basic Energy Sciences, Office of Science within the US Department of Energy. The demonstration of modules and related stability studies were supported by Office of Naval Research (ONR) under award N6833520C0390. We thank the University of North Carolina’s Department of Chemistry NMR Core Laboratory for NMR spectrometers, and ONR award N00014-18-1-2239 for PL mapping. Author contributions: S.C. and J.H. conceived the idea. S.C. fabricated and characterized the perovskite films and devices. X.D. performed laser scribing. S.X. carried out PL measurement and prepared the film samples for GIXRD, FIB-SEM, and partial NMR characterizations. H.J. carried out FIB milling, and acquired the FIB-SEM images and partial NMR spectra. L.Z. performed GIXRD measurement. S.C. and J.H. wrote the manuscript, and all authors commented on the manuscript. Competing interests: J.H. has disclosed a financial interest with Perotech. J.H. and S.C. are inventors of an invention disclosure covering this work filed by University of North Carolina Chapel Hill. The other authors declared no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/373/6557/902/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S20 \nTables S1 and S2 \n22 March 2021; accepted 7 July 2021 \n10.1126/science.abi6323 " + }, + { + "id": "10.1126_science.abh1035", + "DOI": "10.1126/science.abh1035", + "DOI Link": "http://dx.doi.org/10.1126/science.abh1035", + "Relative Dir Path": "mds/10.1126_science.abh1035", + "Article Title": "Lead halide-templated crystallization of methylamine-free perovskite for efficient photovoltaic modules", + "Authors": "Bu, TL; Li, J; Li, HY; Tian, CC; Su, J; Tong, GQ; Ono, LK; Wang, C; Lin, ZP; Chai, NAY; Zhang, XL; Chang, JJ; Lu, JF; Zhong, J; Huang, WC; Qi, YB; Cheng, YB; Huang, FZ", + "Source Title": "SCIENCE", + "Abstract": "Upscaling efficient and stable perovskite layers is one of the most challenging issues in the commercialization of perovskite solar cells. Here, a lead halide-templated crystallization strategy is developed for printing formamidinium (FA)-cesium (Cs) lead triiodide perovskite films. High-quality large-area films are achieved through controlled nucleation and growth of a lead halide_N-methyl-2-pyrrolidone adduct that can react in situ with embedded FAI/CsI to directly form alpha-phase perovskite, sidestepping the phase transformation from delta-phase. A nonencapsulated device with 23% efficiency and excellent long-term thermal stability (at 85 degrees C) in ambient air (similar to 80% efficiency retention after 500 hours) is achieved with further addition of potassium hexafluorophosphate. The slot die-printed minimodules achieve champion efficiencies of 20.42% (certified efficiency 19.3%) and 19.54% with an active area of 17.1 and 65.0 square centimeters, respectively.", + "Times Cited, WoS Core": 487, + "Times Cited, All Databases": 510, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000665616000032", + "Markdown": "# SOLAR CELLS \n\n# Lead halide–templated crystallization of methylamine-free perovskite for efficient photovoltaic modules \n\nTongle $\\mathsf{B u}^{1,2,3}$ , Jing Li1, Hengyi Li1, Congcong Tian1, Jie $\\mathsf{\\pmb{s u}}^{4}$ , Guoqing Tong3, Luis K. Ono3, Chao Wang1, Zhipeng Lin1, Nianyao Chai1, Xiao-Li Zhang5, Jingjing Chang4, Jianfeng $\\mathsf{L u}^{2,6}$ , Jie Zhong1,2, Wenchao Huang1, Yabing ${\\mathfrak{Q}}{\\mathfrak{i}}^{3}.$ , Yi-Bing Cheng2, Fuzhi Huang1,2\\* \n\nUpscaling efficient and stable perovskite layers is one of the most challenging issues in the commercialization of perovskite solar cells. Here, a lead halide–templated crystallization strategy is developed for printing formamidinium (FA)–cesium (Cs) lead triiodide perovskite films. High-quality large-area films are achieved through controlled nucleation and growth of a lead halide•N-methyl-2-pyrrolidone adduct that can react in situ with embedded FAI/CsI to directly form $\\mathbf{a}$ -phase perovskite, sidestepping the phase transformation from d-phase. A nonencapsulated device with $23\\%$ efficiency and excellent long-term thermal stability (at $85^{\\circ}\\mathsf{C}$ ) in ambient air $(-80\\%$ efficiency retention after 500 hours) is achieved with further addition of potassium hexafluorophosphate. The slot die–printed minimodules achieve champion efficiencies of $20.42\\%$ (certified efficiency $19.3\\%$ ) and $19.54\\%$ with an active area of 17.1 and 65.0 square centimeters, respectively. \n\nybrid organic-inorganic metal halide perovskite solar cells (PSCs) have attracted intensive interest during the past H ? decade, with power conversion efficiencies (PCEs) now greater than $25\\%$ $(I)$ . Such a development is attributed to the intrinsically superior photoelectric properties of the perovskite materials that possess tunable bandgaps, high absorption coefficients, and long carrier diffusion lengths (2–4). In particular, the PSCs can be fabricated through a myriad of low-cost solution processes, which offers great promise for future commercialization. However, scalability and stability issues have impeded their industrialization. \n\nThe most important prerequisite for fabricating large-area PSCs is the deposition of high-quality perovskite thin films. The nucleation and crystal growth of the perovskite in solution are largely uncontrollable, often leading to a porous film that would greatly impair the device’s performance $(5,6)$ . The larger the area is, the harder it will be to achieve a uniform crystalline film. Various efforts have been devoted to controlling the nucleation and crystal growth for scaling up perovskite films. Many strategies—including antisolvent bathing $(7)_{:}$ , softcover coating (8), gas flow $(9)$ , vacuum (10) or thermal assisting $(I I)$ , and additive engineering (12)—have been successfully used to fabricate high-quality large-area perovskite films. For example, Hu and others used an air blade to quickly remove the solvent of the methylammonium lead triiodide $\\mathrm{(MAPbI_{3})}$ perovskite wet film to promote the concentration of the perovskite precursor and induce a higher nucleation rate, forming a dense perovskite film $(\\boldsymbol{{\\cal{I}}}\\boldsymbol{3})$ . Huang and others reported a thermally assisted blade-coated perovskite film with an efficiency of $14.6\\%$ on $57.2–\\mathrm{cm}^{2}$ perovskite solar modules (PSMs) using a surfactantadded $\\mathrm{MAPbI_{3-x}C l_{\\it x}}$ perovskite ink $(I I)$ . \n\nHowever, $\\mathrm{\\mathbf{MAPbI_{3}}}$ perovskites have shown poor stability at high temperatures or under light illumination $(I4,I5)$ . Instead, the MA-free perovskites such as formamidinium lead triiodide $\\mathrm{(FAPbI_{3})}$ or formamidinium-caesium lead triiodide $\\mathrm{[(FACs)PbI_{3}]}$ show promising thermal stability owing to their higher phasetransformation temperatures (16–18). In addition, the narrower optical bandgap of $\\mathrm{FAPbI_{3}}$ with respect to that of $\\mathrm{\\mathbf{MAPbI_{3}}}$ can contribute to higher efficiencies $(I9)$ . Recently, the FAbased PSCs without MA have attracted intensive attention, especially for large-area devices (20). Unfortunately, the nucleation and crystal growth of the FA-based perovskites are even harder to control. Alternatively, it might be feasible to control the nucleation of perovskite intermediates such as their solventcoordinated complexes (9, 21). However, the nucleation rate of solvent-coordinated FA-based perovskite complexes is still not high enough. Indeed, besides the one-step method, the twostep method is also widely used in fabricating small-area perovskite films. It is rather easy to achieve a dense $\\mathrm{PbI_{2}}$ film in the first step, but it is hard for the FAI deposited in the second step to diffuse into the bottom of the $\\mathrm{PbI_{2}}$ film to induce a complete reaction (22). In the perovskite precursor solution, if the FAI and $\\mathrm{PbI_{2}}$ species do not form perovskites or solventcoordinated perovskite complexes, the nucleation will be dominated by $\\mathrm{PbI_{2}}$ and therefore it will be easier to form a dense film. Because FAI is embedded during the formation of the $\\mathrm{PbI_{2}}$ film, it is easier to induce an in situ reaction between the $\\mathrm{PbI_{2}}$ and FAI by the subsequent thermal annealing, resulting in a dense perovskite film. Thus, the crystallization of the perovskite is templated by the $\\mathrm{PbI_{2}}$ -derived crystals. \n\nHere, we report a lead halide–templated crystallization strategy to prepare compact methylamine-free perovskite films for the fabrication of antisolvent–free and ambient air–printed high-performance PSMs. The key point to obtaining high-quality large-area FAbased perovskite films is to completely inhibit the formation of a solvent-coordinated perovskite intermediate complex via the formation of a stable $\\mathrm{PbI}_{2}{\\bullet}N.$ -methylpyrrolidone (NMP) adduct, which can react in situ with embedded FAI/CsI species. In addition, by using this process, we can lower the formation energy of $\\mathrm{\\Delta}\\mathrm{a}$ -phase perovskite, which is an unstable hightemperature phase, thus converting the $\\upalpha$ -phase FA-based perovskite film $\\mathrm{(FA_{0.83}C s_{0.17}P b I_{3})}$ even at room temperature. The resulting perovskite films are further passivated by a $\\mathrm{KPF}_{6}$ salt, which contributes to high-performance hysteresis-free PSCs with an efficiency of $23.35\\%$ and dramatically enhanced thermal and light stability. Eventually, a slot die– printed high-quality large-area perovskite film is realized using this strategy. The corresponding solar minimodules demonstrate efficiencies of $20.42\\%$ on $\\mathrm{17.1cm^{2}}$ and $19.54\\%$ on $65.0\\mathrm{cm}^{2}$ , respectively. \n\n$\\mathrm{FAPbI_{3}}$ has the narrowest bandgap (\\~1.48 eV) among the $\\mathrm{\\mathbf{Pb}}$ -based perovskites and much better thermal stability than MA-based perovskite. However, pure $\\mathbf{\\mathrm{\\mathbf{q}}{\\mathrm{-}}F\\mathbf{APbI}_{3}}$ is unstable, so Cs is normally introduced to stabilize the phase (23). Here, $\\mathrm{FA_{0.83}C s_{0.17}P b I_{3}}$ perovskite is used to study its nucleation and crystal growth kinetics. N,N-dimethylformamide (DMF) is a commonly used solvent for perovskite precursor ink because of its high solubility and volatility. We found that during the natural drying process, only a few nuclei form at the beginning (fig. S1i), then several flat, needle-shaped crystals grow, surrounding every nucleus. After drying completely, a scanning electron microscopy (SEM) image (Fig. 1Ai) shows a rough film with dendrites, large pores, and some densely packed large grains lying underneath the dendrites, clearly indicating that there are two types of structures. To trace the formation processes of such structures, in situ x-ray diffraction (XRD) was conducted to investigate phase change during the natural drying process. According to the density functional theory (DFT) fitting (fig. S2) and a comparison with the in situ XRD patterns from different components with additives (fig. S3), it can be inferred from Fig. 1Bi and fig. S4 that at the beginning, solvent-coordinated perovskite intermediate phases of $\\mathrm{Cs_{2}P b_{3}I_{8}\\bullet4D M F}$ and $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ form and then transform to d-(FACs)PbI3. Finally, $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ and $\\S{\\mathrm{-}}(\\mathrm{FACs)PbI_{3}}$ are mainly present in the film. Although perovskites in the DMF form intermediate solventcoordinated complexes, the nucleation rate is still too low during the natural drying process. To accelerate the nucleation rate, the precursor solution is spun at $3000\\ \\mathrm{rpm}$ to quickly remove the solvent. The morphology change is shown in Fig. 1Ci. There are some large-area dense zones that formed, with a few rods randomly distributed. So even with the assistance of solvent removal by spinning, the nucleation rate is not high enough, because there are still many large pores. This demonstrates that it is hard to change the nucleation kinetics of FA-based perovskites through the approach of forming intermediate solventcoordinated complexes. The XRD patterns (Fig. 1Di) show the presence of major d-(FACs) $\\mathrm{PbI_{3}}$ in the final film. \n\n![](images/7c924852fae785c3ec2a8e9957fa4d8566db7b85fdbd38de8dc1cf7138e8cf78.jpg) \nFig. 1. Nucleation and crystallization of MA-free perovskites. (A and B) Shown are (A) SEM and (B) in situ XRD patterns of $10\\mathrm{-}\\upmu|$ perovskite precursor inks (1.1 M) with or without different additives drying on the 1.5-cm–by–1.5-cm FTO/glass substrates: (i) $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b l}_{3}/\\mathsf{D M F}$ , (ii) $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}\\mathsf{l}_{3}\\mathsf{N M P/D M F},$ , and (iii) $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}|_{3}$ -NMP-10%PbCl2/DMF. $\\mathsf{C s}_{2}\\mathsf{P b}_{3}\\mathsf{I}_{8}$ •4DMF, solid blue triangle; $\\mathsf{F A}_{2}\\mathsf{P b}_{3}\\mathsf{I}_{8}$ •4DMF, purple circle; open triangle, $\\delta\\mathsf{-}(\\mathsf{F A C s})\\mathsf{P b}|_{3};$ solid green \ndiamond, $\\mathsf{P b l}_{2}$ •NMP; open diamond, $\\mathsf{P b}\\mathsf{X}_{2}\\bullet0.5\\mathsf{N M P}\\bullet0.5\\mathsf{D M F}.$ a.u., arbitrary units. (C) SEM images of the corresponding perovskite ink spun onto FTO/glass substrates at 3000 rpm. (D) The corresponding XRD patterns of spin-coated (at $3000~\\mathsf{r p m},$ ) perovskite films annealed at different temperatures for 10 min. (E) Schematic diagram of crystal growth with or without NMP. (F) Free-energy calculation for the formation of $\\mathsf{F A P b l}_{3}$ perovskites with or without NMP. \n\n![](images/5c5bb68a628662a25eb77f95282cb342c2f233f8a24b48e803226c4e09c92742.jpg) \nFig. 2. Photovoltaic performance of antisolvent– free coated PSCs with ${\\mathsf{K P F}}_{6}$ passivation. (A) Schematic of the PSC with the structure $\\mathsf{F T O}/\\mathsf{S n O}_{2}/3\\mathsf{D}$ -perovskite/ 2D-perovskite/spiro-OMeTAD/ Au. PVSK, perovskite. (B and C) Champion J-V curves of 3D/2D perovskite–based devices with or without ${\\mathsf{K P F}}_{6}$ additive tested using a metal mask with an aperture area of (B) $0.148\\mathsf{c m}^{2}$ and (C) $1.0(\\mathsf{c m}^{2}$ . (D) $J-V$ characteristics of the 3D/2D perovskite films with or without ${\\mathsf{K P F}}_{6}$ additive derived from the SCLC measurements with a structure of ITO/ perovskite/Au (ITO, indium tin oxide). $V_{\\mathsf{T F L}},$ trap-filled limited voltage. (E and F) Time-resolved confocal PL lifetime maps of (E) 3D/2D and (F) 3D/2D- ${\\mathsf{K P F}}_{6}$ perovskite films, respectively. \n\nIn our initial study, we found that NMP can form a strong $\\mathrm{PbI_{2}\\bullet N M P}$ adduct (fig. S3). As proposed, if $\\mathrm{PbI_{2}\\bullet N M P}$ can remain in the perovskite precursor solution, then the nucleation will be dominated by the $\\mathrm{PbI_{2}\\bullet N M P}$ adduct. After the formation of the film, the FAI/CsI species are also homogeneously distributed in the film. It is very easy to induce the reaction of $\\mathrm{PbI_{2}}$ and FAI/CsI in the film by thermal annealing. Thus, the film morphology will be well controlled. Then NMP with a molar ratio of 1:1 to $\\mathrm{PbI_{2}}$ is added into the $\\mathrm{FA_{0.83}C s_{0.17}P b I_{3}/D M F}$ solution. Similar studies are carried out, and we find that there are two types of nuclei (fig. S1ii). The nuclei that induce the growth of needle-shaped crystals have no obvious changes, but the length of the needle becomes a little shorter, indicating that the growth of the solventcoordinated perovskite complexes is suppressed. More importantly, a large number of the second type of nuclei form, growing into spherical particles. Through the in situ XRD (Fig. 1Bii), we find that the initial strong peaks of $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ become weaker and the later-appearing $\\mathrm{PbI_{2}\\bullet N M P}$ peaks become stronger, leaving the final film consisting of $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ and $\\mathrm{PbI_{2}\\bullet N M P}$ . The SEM image (Fig. 1Aii) also shows that there are two types of structures in the rough film: densely packed particles in the layered structure and some dendrite structures that originated from the $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ . When the film is prepared by spin-coating the precursor solution at $3000~\\mathrm{rpm}$ , the film becomes smoother and denser and has a light brown color (fig. S5), but it still has some small pores and several needles (Fig. 1Cii). XRD patterns (Fig. 1Dii) show the presence of an almost pure $\\mathrm{PbI_{2}\\bullet N M P}$ phase. Interestingly, we also find that minor $\\mathrm{\\Delta\\mathrm{a-(FACs)PbI_{3}}}$ emerges in the film. When we increase the spinning speed to $5000~\\mathrm{rpm}$ , the peak intensity of the $\\mathfrak{a}$ -phase becomes stronger (fig. S6). It is completely different from that of the film derived from the pure DMF solution. When the film is annealed at $70^{\\circ}\\mathrm{C}$ , an obvious $\\mathrm{\\Delta\\mathrm{a-(FACs)PbI_{3}}}$ phase appears (Fig. 1Dii), and the film becomes a black color (fig. S5). With a further increase in annealing temperature to $150^{\\circ}\\mathrm{C}$ , the peak of the $\\mathfrak{a}$ -phase becomes even stronger. For the DMF-derived film, when annealed at $70^{\\circ}\\mathrm{C}$ , the peak of the $\\delta\\mathrm{-(FACs)PbI_{3}}$ phase becomes stronger (Fig. 1Di) and the film still remains a yellow color (fig. S5). However, when further annealed at $\\mathrm{150^{\\circ}C},$ the d-phase is completely transformed into $\\mathbf{\\alpha}\\propto$ -phase (Fig. 1Di) and becomes a black color (fig. S5). According to the DFT calculation (Fig. 1F), because $\\mathrm{\\mathbf{q}{\\mathrm{-FAPbI}}_{3}}$ is a hightemperature phase, the conversion energy is high if it is from ${\\delta\\mathrm{-FAPbI_{3}}}$ , which is rapidly transformed from the DMF-coordinated complexes. However, when $\\mathrm{PbI_{2}\\bullet N M P}$ reacts with FAI to form perovskite, the $\\mathrm{\\Phi_{\\mathrm{{\\mathrm{d}}\\mathrm{{-}\\mathrm{{FAPbI}_{\\mathrm{{3}}}}}}}}$ formation energy is dramatically decreased. This is why the addition of NMP can induce an $\\upalpha$ -phase perovskite at room temperature with the incorporation of Cs. The study of pure $\\mathrm{FAPbI_{3}}$ films growing from 2-methoxyethanol (2-Me), an uncoordinated solvent, with or without corresponding coordination solvent additives further confirms the above findings, as shown in fig. S7. In short, the presence of the intermediate phases (the perovskite-DMF complexes) will result in porous d-phase perovskite films, whereas the existence of $\\mathrm{PbI_{2}\\mathrm{-NMP}}$ will directly produce dense $\\upalpha$ -phase perovskite films (fig. S4E). Therefore, an improved quality of perovskite film can be obtained by inhibiting the formation of the perovskite-DMF complexes. \n\nThus, it is more preferable if $\\mathrm{\\Gamma_{0.-(FACs)PbI_{3}}}$ is directly formed from the solution without a second phase transformation, which would suppress the formation of defects and traps during the $\\delta-$ to $\\mathfrak{a}$ -phase transition. From the above results, we can conclude that in the $\\mathrm{(FACs)PbI_{3}}$ perovskite DMF solution, solventcoordinated perovskite intermediate phases of $\\mathrm{Cs_{2}P b_{3}I_{8}\\bullet4D M F}$ and $\\mathrm{FA_{2}P b_{3}I_{8}}$ •4DMF that later convert to $\\delta\\mathrm{-}(\\mathrm{FACs)PbI_{3}}$ are likely to form and thus result in poor morphology, as depicted in Fig. 1E. When NMP is added, the intermediate phases of $\\mathrm{Cs_{2}P b_{3}I_{8}\\bullet4D M F}$ and $\\mathrm{FA_{2}P b_{3}I_{8}}$ •4DMF are restrained by the competition of $\\mathrm{PbI_{2}\\bullet N M P}$ , resulting in the formation of $\\mathrm{~\\bf~a~}$ $\\mathrm{\\Sigma_{\\cdot}(F A C s)P b I_{3}}$ . To further improve the film quality, the intermediate phase of $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ should be completely inhibited. By the further introduction of excess $\\mathrm{PbCl_{2}}$ to the precursor solution, we find that the growth of the $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ nuclei is further suppressed by the formation of an additional $\\mathrm{Pb}\\mathrm{X}_{2}{\\bullet}0.5\\mathrm{NMP}{\\bullet}0.5\\mathrm{DMF}$ adduct, as shown in fig. S1iii, and the film becomes much denser (Fig. 1Aiii), more transparent, and brown in color (fig. S5), indicating much faster nucleation of lead halide–NMP adducts and effective suppression of d-phase formation. Further evidence can be found from the in situ XRD patterns (Fig. 1Biii), which show the presence of a much lower peak of $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ , and the SEM image of the spin-coated film, which shows negligible pores (Fig. 1Ciii). The related XRD patterns (Fig. 1Diii) of the spin-coated film show the presence of $\\mathrm{PbI_{2}\\bullet N M P}$ and $\\mathrm{PbX_{2}}$ •NMP/DMF complexes without $\\mathrm{FA_{2}P b_{3}I_{8}\\bullet4D M F}$ . The XRD patterns (fig. S6) and SEM images (fig. S8) indicate that a relatively low volatilization rate of the precursor solution during the deposition (spin rate $>3000\\ \\mathrm{rpm}_{.}$ ) is sufficient to achieve dense perovskite films even without an antisolvent process. The annealing even at \n\n$70^{\\circ}\\mathrm{C}$ could induce a stronger peak of $\\upalpha$ -(FACs) $\\mathrm{PbI_{3}}$ phase. The additional peak belonging to $\\mathrm{PbI_{2}}$ at $150^{\\circ}\\mathrm{C}$ is due to the added excess $\\mathrm{PbX_{2}}$ . The excess $\\mathrm{PbI_{2}}$ is generally beneficial to the device because of the passivation effect (24). \n\nTo study the corresponding film’s device performance, we used a normal structure of FTO $\\mathrm{\\DeltaSnO_{2}}$ /perovskite/spiro-OMeTAD/Au [FTO, fluorine-doped tin dioxide; spiro-OMeTAD, 2,2′,7,7′-tetrakis(N,N-di- $p$ -methoxyphenyl-amine) 9,9′-spirobifluorene]. To facilitate industrial production, we adopted a two-step annealing process for perovskites, namely a $70^{\\circ}\\mathrm{C}$ annealing in the glovebox to dry the films followed by another $\\mathrm{150^{\\circ}C}$ annealing in air to promote crystal growth with the assistance of humidity. The champion current density–voltage $\\left(J{-}V\\right)$ \n\n![](images/63c2ab54f592e2fe62f8fd3755e8b7b9c718a07c60b04192fa0bb049820a9866.jpg) \nFig. 3. Thermal stability characterization. (A) Average PCE evolution of the unencapsulated devices measured over a 500-hour stability test at $85^{\\circ}\\mathrm{C}$ in ambient air (relative humidity ${\\sim}15\\pm5\\%\\dot{,}$ ). The shaded regions represent the variation range of the PCE obtained from eight cells. (B) TOF-SIMS of Pb, P, and F ions in the $\\mathsf{F A}_{0.83}\\mathsf{C s}_{0.17}\\mathsf{P b}\\mathsf{I}_{3-x}C I_{x}$ perovskite film with ${\\mathsf{K P F}}_{6}$ additive on a Si substrate (measurement area $80\\upmu\\mathrm{m}$ by $80\\upmu\\mathrm{m}$ ). (C and D) Cross-sectional SEM images of different devices: (C) fresh 3D/2D device before and after 360 hours of $85^{\\circ}\\mathrm{C}$ aging and (D) fresh 3D/2D-KPF $\\dot{6}$ device before and after 360 hours of $85^{\\circ}\\mathrm{C}$ aging. (E and F) TOF-SIMS spectra of (E) 3D/2D and (F) 3D/2D-KPF6 devices after 360 hours of $85^{\\circ}\\mathrm{C}$ aging. HTL, hole transport layer; ETL/FTO, electron transport layer/fluorine-doped tinoxide. \n\ncurves of PSCs are shown in fig. S9. The devices made from pure DMF-derived perovskite films exhibit a poor PCE of $7.64\\%,$ , whereas the NMP-engineered perovskite devices show a much higher efficiency of greater than $20\\%$ . We further modulated the addition of $\\mathrm{PbCl_{2}}$ and obtained mirror-like black films (fig. S5). The efficiencies are substantially improved when the amount of $\\mathrm{PbCl_{2}}$ is increased to no more than $10\\%$ while the hysteresis continues to decrease. A champion efficiency of $21.92\\%$ is achieved by the addition of $10\\%$ $\\mathrm{PbCl_{2}}$ (fig. S9). After further characterization of the crystal properties by XRD, UV-visible (UV-Vis) absorption spectroscopy, and SEM for perovskite films with different amounts of added $\\mathrm{PbCl_{2}}$ (fig. S10), we found that the intrinsic reasons for the improved performance by introducing $\\mathrm{PbCl_{2}}$ are the suppression of d-phase formation, the improvement of coverage with increased grain size, and the in situ formation of $\\mathrm{PbI_{2}}$ at the grain boundary as a passivator (fig. S10) due to the substitution of ${\\boldsymbol{\\mathrm{I}}}^{-}$ or ${\\boldsymbol{\\mathrm{I}}}^{-}$ vacancies by $\\mathrm{Cl}^{-}$ to form a $\\mathrm{FA_{0.83}C s_{0.17}P b I_{3-x}C l_{\\it x}}$ perovskite (25, 26). \n\nTo further improve performance, we introduced a posttreatment of bromide-based large cation salt (isobutylamine bromide, iBABr) on the as-fabricated $\\mathrm{FA_{0.83}C s_{0.17}P b I_{3-x}C l_{\\it x}}$ [labeled as three-dimensional (3D) perovskite] surface to form a 3D/2D structured perovskite layer according to previous reports (27, 28) (fig. S11), which would contribute to stability improvement and open-circuit voltage $(V_{\\mathrm{oc}})$ –loss reduction for the solar cells. The corresponding device structure is shown in Fig. 2A. An improved efficiency of $23.02\\%$ under reverse scan (RS) for the 3D/2D perovskite-based solar cells is achieved, with a $V_{\\mathrm{{oc}}}$ of 1.166 V, a short-circuit current density $(J_{\\mathrm{sc}})$ of $23.97\\mathrm{\\mA\\cm^{-2}}$ , and a fill factor (FF) of 0.824. A lower efficiency of $20.71\\%$ is achieved under forward scan (FS), with a $V_{\\mathrm{{oc}}}$ of 1.142 V, $J_{\\mathrm{sc}}$ of $24.01\\mathrm{mAcm^{-2}}$ , and a FF of 0.755, respectively (Fig. 2B and table S1). An obvious hysteresis with a hysteresis index (HI) of 0.10 is still present. \n\nHysteresis reflects the stability that is one of the major obstacles to the commercialization of PSCs (29). To eliminate the hysteresis and further improve the photovoltaic performance and stability, we used a potassium-based salt, $\\mathrm{KPF}_{6}$ , as an additive to the perovskite precursor solution. XRD, UV-Vis absorption spectroscopy, and SEM characterizations (fig. S12) confirm the incorporation of $\\mathrm{KPF}_{6}$ to perovskites. The corresponding photovoltaic characteristics are shown in fig. S13. With the addition of $\\mathrm{KPF}_{6}$ , the hysteresis continues to decrease and the HI reaches 0.00 at a $5\\%$ additive concentration. To accurately evaluate the real PCE, steady-state power output (SPO) measurements were conducted. With a lower HI, the PCE from SPO becomes closer to the PCE from J-V scans. When the concentration is above $0.5\\%$ , the hysteresis is actually almost negligible. A champion efficiency is obtained with the addition of $1.5\\mathrm{\\mol\\\\%}$ $\\mathrm{KPF}_{6}$ salts (labeled as $3\\mathrm{D}/2\\mathrm{D}{\\cdot}\\mathrm{KPF}_{6})$ , showing a higher $V_{\\mathrm{{oc}}}$ of 1.178 V, a $J_{\\mathrm{sc}}$ of $24.03\\mathrm{\\mA\\cm^{-2}}$ , a FF of 0.825, and a PCE of $23.35\\%$ under RS, and a $V_{\\mathrm{{oc}}}$ of 1.175 V, a $J_{\\mathrm{sc}}$ of $24.06\\mathrm{\\mA\\cm^{-2}}$ , a FF of 0.818, and a PCE of $23.13\\%$ under FS. The average PCE of $23.24\\%$ is very close to the PCE from SPO of $23.2\\%$ , which is much higher than the control device $(21.9\\%)$ (fig. S14A). It is not surprising to see that further addition of $\\mathrm{KPF}_{6}$ decreases the PCE, although there is no hysteresis, because too much $\\mathrm{KPF}_{6}$ will affect the nucleation behavior and lead to poorer film morphology (fig. S12C). The corresponding external quantum efficiency spectra show an integrated $J_{\\mathrm{sc}}$ of 23.70 and $23.78\\mathrm{mAcm^{-2}}$ for devices with and without $\\mathrm{KPF}_{6}$ , respectively (fig. S14B), which match well with the measured $J_{\\mathrm{sc}}$ In addition, PSCs that are $\\mathrm{1.0~cm^{2}}$ in size also exhibit substantial improvements in PCE, increasing from $21.92\\%$ (RS) and $19.31\\%$ (FS) to $22.53\\%$ (RS) and $22.27\\%$ (FS) with the addition of $\\mathrm{KPF}_{6}$ (Fig. 2C and table S2). The distribution of $J{-}V$ parameters for both small-area and $\\scriptstyle1.0\\mathrm{-cm^{2}}$ -sized cells proresulting in a small $V_{\\mathrm{{oc}}}$ loss of ${\\sim}0.37\\ \\mathrm{eV}$ (fig. S17). This passivation strategy would be beneficial to stability. \n\n![](images/30798f8bfc2c4ab655cc73ea60227ac4338a223a584056f1bd6cbe38b929a2ce.jpg) \nFig. 4. Photovoltaic performance characterization of large-area modules. (A) Schematic illustration for the slot-die printing of perovskite films with low-pressure dry air blowing. The inset shows a photo of a printed 20-cm–by–20-cm perovskite film. (B) Champion $J-V$ curves of the 5-cm–by–5-cm minimodules based on the antisolvent-free spin-coating method and slot-die printing method. The inset shows the schematic diagram of a six-subcell series-connected module. F, forward scan; R, reverse scan; P1, P2, and P3, three laser scribing steps. (C) Champion $J-V$ curves of the 10-cm–by–10-cm minimodule using the largescale perovskite film fabricated by the slot-die printing method. (D) Champion efficiencies of PSCs as a function of the area from this work and recent representative reports (9, 11, 20, 25, 34–36). \n\ncessed with or without $\\mathrm{KPF}_{6}$ additives are shown in fig. S15. Ultraviolet photoemission spectroscopy (UPS) and UV-Vis absorption spectroscopy (fig. S16) characterizations reveal the lifted conduction band minimum from $-4.14\\mathrm{eV}$ for 3D perovskite to $\\mathrm{-4.10~eV}$ for 3D/ 2D perovskite, and further to $-3.94\\ \\mathrm{eV}$ for 3D/ 2D- $\\mathrm{\\cdotKPF}_{6}$ perovskite, which contributes to the enhanced $V_{\\mathrm{{oc}}}$ of the modified devices. \n\nFigure 3A shows the thermal stability of widely researched CsFAMA triple-cation-based perovskite $\\mathrm{Cs_{0.05}(F A_{0.85}M A_{0.15})_{0.95}P b(I_{0.85}B r_{0.15})_{3}}$ and our MA-free perovskite $(\\mathrm{FA_{0.83}C s_{0.17}P b I_{3}})\\mathrm{-}$ – based solar cells measured at $85^{\\circ}\\mathrm{C}$ in ambient air $15\\pm5\\%$ relative humidity). The efficiency of CsFAMA devices quickly decreases to $2.9\\pm$ $3.1\\%$ within 360 hours. Obvious holes are observed from the cross-sectional SEM image because of the degradation of the CsFAMA device after aging at $85^{\\circ}\\mathrm{C}$ (fig. S18). Although the MA-free 3D/2D devices exhibit a considerable improvement and retain the black appearance, the devices still show a salient decrease after aging at $85^{\\circ}\\mathrm{C}$ for 500 hours, retaining less than $50\\%$ of the initial efficiency. However, this degradation can be substantially suppressed with the addition of $\\mathrm{KPF}_{6}$ . The $\\mathrm{3D/2D\\mathrm{-KPF}_{6}}$ devices exhibit ${\\sim}80\\%$ of the initial efficiency after aging at $85^{\\circ}\\mathrm{C}$ for 500 hours. The $J{-}V$ curves of different devices under the thermal stability measurements are plotted in fig. S19. There is a negligible change of FF in the device processed with $\\mathrm{KPF}_{6},$ indicating the undamaged interfaces of devices. \n\nWe further used the space charge–limited current (SCLC) measurements to characterize the trap density of these different films (30–32). The calculated defect density decreases from $6.17\\times10^{15}$ to $4.97\\times10^{15}\\ \\mathrm{cm^{-3}}$ , indicating the reduced defects of the perovskite film with the addition of $\\mathrm{KPF}_{6}$ (Fig. 2D). Time-resolved confocal photoluminescence (PL) microscopy measurements were also performed to characterize the charge carrier properties of these perovskite films in microsize ${\\mathrm{70~}}\\upmu\\mathrm{m}$ by $10\\upmu\\mathrm{m})$ (Fig. 2, E and F). The blue region with a short PL lifetime for the pristine 3D/2D perovskite transits to a green region with a much longer PL lifetime after the addition of $\\mathrm{KPF}_{6}$ . It indicates a reduced trap-induced or nonradiative recombination by the defect passivation due to the addition of $\\mathrm{KPF}_{6}.$ , thus \n\nThis substantial improvement in stability can be ascribed to the $\\mathrm{PF}_{6}^{-}$ -induced complex in perovskite films. The complex stays on the surface, passivating the grain boundaries, as seen from the SEM images (fig. S12C). In addition, to unravel the distribution of the $\\mathrm{PF}_{6}^{-}$ complex across the perovskite layer, we conducted time-of-flight secondary-ion mass spectrometry (TOF-SIMS) for $1.5\\:\\mathrm{mol}\\:\\%\\:\\mathrm{KPF}_{6^{-}}$ contained $\\mathrm{FA_{0.83}C s_{0.17}P b I_{3-x}C l_{\\it x}}$ perovskite film (Fig. 3B). A block-by-block distribution of the agglomerated $\\mathrm{PF}_{6}^{-}$ ions is shown in the 3D visualization images. The corresponding depth profiles of TOF-SIMS and x-ray photoelectron spectroscopy also show detected signals of K and F elements throughout the perovskite films (fig. S20, A to C). In addition, Fourier transform infrared spectra show that the N–H and P–F corresponding peaks shift to lower wave numbers with the increasing amount of $\\mathrm{KPF}_{6}$ additives, revealing the presence of the hydrogen bonding between perovskite and $\\mathrm{PF}_{6}^{-}$ (fig. S20, D to F). Thus, the $\\mathrm{PF}_{6}^{-}$ additives would greatly affect both the perovskite grain boundary and the interfacial properties of the devices, contributing to better performance by passivating the surface defects. \n\nThe corresponding cross-sectional SEM images of the thermally aged devices with or without $\\mathrm{KPF}_{6}$ additives are shown in Fig. 3, C and D. We found that there is no obvious change of the perovskite/spiro-OMeTAD interface with the $\\mathrm{KPF}_{6}$ additive, whereas the interface becomes intersected without the $\\mathrm{KPF}_{6}$ additive. We further used TOF-SIMS characterization to probe the thermally aged devices and fresh devices (Fig. 3, E and F, and fig. S21). \n\nIn the device without $\\mathrm{KPF}_{6}$ , Cs, $\\mathrm{Pb}$ , and I ions are shifted toward the spiro-OMeTAD layer. The Co ions that are a dopant in spiro-OMeTAD diffuse into the perovskite layer after thermal aging (Fig. 3E), matching well with the above SEM finding. With $\\mathrm{KPF}_{6}.$ the diffusion of ions is considerably suppressed (Fig. 3F). \n\nWe also measured the light illumination stability of the devices. The solar cells were continuously measured five times under 1 sun AM 1.5G solar illumination. A rapid degradation of $V_{\\mathrm{{oc}}}$ and FF for the $\\mathrm{1.0{-cm}^{2}3D/2D}$ PSC is observed, whereas the $\\mathrm{KPF}_{6}$ -modified device exhibits negligible degradation (fig. S22). The long-term light illumination stability was also characterized, as shown in fig. S23A. The champion device with $\\mathrm{KPF}_{6}$ additives exhibits a better photostability than the pristine device, retaining $82\\%$ of its initial efficiency after 500 hours under continuous 1 sun AM 1.5G solar illumination without a UV filter, at an open-circuit condition that is harsher than the operating condition (33). A more stable statistic PCE evolution of the devices with $\\mathrm{KPF}_{6}$ additive compared with the pristine devices is shown in fig. S23B. Therefore, the $\\mathrm{KPF}_{6}$ additive plays an important role in improving the stability of perovskite devices as well. \n\nJust as the dense perovskite films can be easily prepared by spin-coating with the developed ink at a relatively low speed, similarly a moderate dry-air gas can also promote nucleation (fig. S24A). Thus, a gas-assist slot-die printing technology toward the continuous deposition of large-area perovskite films is developed here, as demonstrated in Fig. 4A. With a low pressure of \\~0.3-MPa dry air blowing, the printed wet perovskite film quickly changes to a brown color with a mirror-like surface, as shown in movie S1. The inset in Fig. 4A shows a photograph of the printed large-area 20-cm–by–20-cm perovskite film. A pinhole-free high-quality perovskite layer with clear grain boundaries is shown in the SEM image (fig. S24B). \n\nThe 5-cm–by–5-cm PSMs are then fabricated, and the $J_{-}V$ curves are shown in Fig. 4B. The inset shows the schematic diagram of a sixsubcell series-connected 5-cm–by–5-cm module, and fig. S25 shows its photo. The slot die– printed PSM shows comparable performance to the spin-coated counterpart (Fig. 4B), with efficiencies greater than $20.4\\%$ (table S3). Certified efficiencies of 19.3 and $18.9\\%$ with a mask area of $\\mathrm{17.1~cm^{2}}$ are achieved, respectively, for the slot die–printed and spin-coated PSMs (figs. S26 and S27). The hysteresis-suppression effect of $\\mathrm{KPF}_{6}$ is also proven in large solar modules, which exhibit a very stable efficiency (fig. S28, A and B). We also achieved a champion FF of 0.806 for a 4-cm–by–4-cm solar module (mask area of $10.0~\\mathrm{cm}^{2},$ (fig. S28C), which is the highest FF recorded among the reported PSMs. Furthermore, the solar module also shows excellent performance under weak light illumination and continuous multiple testing (fig. S28D). Our results indicate that the very high uniformity of large-area perovskite films that is achieved from this lead halide–templated crystallization strategy contributes to high-performance solar modules. \n\nWe further scaled up the perovskite films to print a 10-cm–by–10-cm solar module with a series connection of 14 subcells and demonstrated a hysteresis-free solar module with high efficiency of $19.54\\%$ under RS and $19.22\\%$ under FS with a mask area of $65.0~\\mathrm{cm}^{2}$ (Fig. 4C). The module efficiencies from different upscaling methods with different areas that were achieved in the past several years are summarized in Fig. 4D. The antisolvent-free modulated high-quality perovskite films in this work exhibit the highest efficiencies among all the reported works, indicating the high processability for achieving large-area high-quality perovskite films. \n\n# REFERENCES AND NOTES \n\n1. National Renewable Energy Laboratory (NREL), Best research-cell efficiency chart (2021); www.nrel.gov/pv/ cell-efficiency.html. \n2. S. D. Stranks et al., Science 342, 341–344 (2013). \n3. D. Shi et al., Science 347, 519–522 (2015). \n4. Q. Dong et al., Science 347, 967–970 (2015). \n5. F. Huang et al., Nano Energy 10, 10–18 (2014). \n6. M. Xiao et al., Angew. Chem. Int. Ed. 53, 9898–9903 (2014). \n7. Y. Y. Kim et al., Nat. Commun. 11, 5146 (2020). \n8. H. Chen et al., Nature 550, 92–95 (2017). \n9. Y. Deng et al., Sci. Adv. 5, eaax7537 (2019). \n10. Z. Xu et al., J. Mater. Chem. A Mater. Energy Sustain. 7, 26849–26857 (2019). \n11. Y. Deng et al., Nat. Energy 3, 560–566 (2018). \n12. C. Li et al., J. Am. Chem. Soc. 141, 6345–6351 (2019). \n13. J. Ding et al., Joule 3, 402–416 (2019). \n14. B. Conings et al., Adv. Energy Mater. 5, 1500477 (2015). \n15. E. J. Juarez-Perez et al., J. Mater. Chem. A Mater. Energy Sustain. 6, 9604–9612 (2018). \n16. S.-H. Turren-Cruz, A. Hagfeldt, M. Saliba, Science 362, 449–453 (2018). \n\n17. Y.-H. Lin et al., Science 369, 96–102 (2020). \n18. X. X. Gao et al., Adv. Mater. 32, e1905502 (2020). \n19. M. Jeong et al., Science 369, 1615–1620 (2020). \n20. M. Du et al., Adv. Mater. 32, e2004979 (2020). \n21. N. Ahn et al., J. Am. Chem. Soc. 137, 8696–8699 (2015). \n22. F. Guo et al., Adv. Funct. Mater. 29, 1900964 (2019). \n23. M. Saliba et al., Energy Environ. Sci. 9, 1989–1997 (2016). \n24. Q. Jiang et al., Nat. Energy 2, 16177 (2016). \n25. A. Ren et al., Joule 4, 1263–1277 (2020). \n26. M. I. Saidaminov et al., Nat. Energy 3, 648–654 (2018). \n27. Y. Liu et al., Angew. Chem. Int. Ed. 59, 15688–15694 \n(2020). \n28. D. Luo et al., Science 360, 1442–1446 (2018). \n29. P. Liu, W. Wang, S. Liu, H. Yang, Z. Shao, Adv. Energy Mater. 9, \n1803017 (2019). \n30. Z. Liu et al., Nat. Commun. 9, 3880 (2018). \n31. E. A. Duijnstee et al., ACS Energy Lett. 5, 376–384 (2020). \n32. J. Chen, S.-G. Kim, N.-G. Park, Adv. Mater. 30, e1801948 \n(2018). \n33. K. Domanski, E. A. Alharbi, A. Hagfeldt, M. Grätzel, W. Tress, \nNat. Energy 3, 61–67 (2018). \n34. T. Bu et al., Solar RRL 4, 1900263 (2019). \n35. J. Li et al., Joule 4, 1035–1053 (2020). \n36. X. Dai et al., Adv. Energy Mater. 10, 1903108 (2019). \n\n# ACKNOWLEDGMENTS \n\nFunding: This work is financially supported by the National Key Research and Development Plan (2019YFE0107200 and 2017YFE0131900), the National Natural Science Foundation of China (91963209 and 21875178), the Technological Innovation Key Project of Hubei Province (2018AAA048), and the Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory (XHD2020-001 and XHT2020-005). The Analytical and Testing Centre of Wuhan University of Technology and Hubei Key Laboratory of Low Dimensional Optoelectronic Material and Devices, Hubei University of Arts and Science, are acknowledged for the XRD and SEM characterizations. G.T., L.K.O., and Y.Q. acknowledge funding support from the Energy Materials and Surface Sciences Unit of the Okinawa Institute of Science and Technology Graduate University. Author contributions: F.H. and T.B. conceived the ideas and designed the experiments. Y.-B.C. provided helpful advice on the work. T.B. conducted the corresponding device and module fabrication and basic characterization. J.L., H.L., and C.T. helped with the module fabrication and encapsulation. J.L. and C.W. helped with the efficiency certification of modules. T.B. and J.S. conducted the DFT calculations. G.T. and L.K.O. helped with the XPS, UPS characterization, and analyses. Z.L. and N.C. helped with the stability test. J.C., J.L., J.Z., X.-L.Z., W.H., Y.Q., and Y.-B.C. provided valuable suggestions for the manuscript. F.H. and T.B. participated in all of the data analyses. F.H. and T.B. wrote the paper, and all authors revised the paper. Competing interests: None declared. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/372/6548/1327/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S28 \nTables S1 to S4 \nReferences (37–43) \nMovie S1 \n16 February 2021; accepted 6 May 2021 \n10.1126/science.abh1035 " + }, + { + "id": "10.1002_adma.202007829", + "DOI": "10.1002/adma.202007829", + "DOI Link": "http://dx.doi.org/10.1002/adma.202007829", + "Relative Dir Path": "mds/10.1002_adma.202007829", + "Article Title": "Poly(vinyl alcohol) Hydrogels with Broad-Range Tunable Mechanical Properties via the Hofmeister Effect", + "Authors": "Wu, SW; Hua, MT; Alsaid, Y; Du, YJ; Ma, YF; Zhao, YS; Lo, CY; Wang, CR; Wu, D; Yao, BW; Strzalka, J; Zhou, H; Zhu, XY; He, XM", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "Hydrogels, exhibiting wide applications in soft robotics, tissue engineering, implantable electronics, etc., often require sophisticately tailoring of the hydrogel mechanical properties to meet specific demands. For examples, soft robotics necessitates tough hydrogels; stem cell culturing demands various tissue-matching modulus; and neuron probes desire dynamically tunable modulus. Herein, a strategy to broadly alter the mechanical properties of hydrogels reversibly via tuning the aggregation states of the polymer chains by ions based on the Hofmeister effect is reported. An ultratough poly(vinyl alcohol) (PVA) hydrogel as an exemplary material (toughness 150 +/- 20 MJ m(-3)), which surpasses synthetic polymers like poly(dimethylsiloxane), synthetic rubber, and natural spider silk is fabricated. With various ions, the hydrogel's various mechanical properties are continuously and reversibly in situ modulated over a large window: tensile strength from 50 +/- 9 kPa to 15 +/- 1 MPa, toughness from 0.0167 +/- 0.003 to 150 +/- 20 MJ m(-3), elongation from 300 +/- 100% to 2100 +/- 300%, and modulus from 24 +/- 2 to 2500 +/- 140 kPa. Importantly, the ions serve as gelation triggers and property modulators only, not necessarily required to remain in the gel, maintaining the high biocompatibility of PVA without excess ions. This strategy, enabling high mechanical performance and broad dynamic tunability, presents a universal platform for broad applications from biomedicine to wearable electronics.", + "Times Cited, WoS Core": 503, + "Times Cited, All Databases": 517, + "Publication Year": 2021, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000615816100001", + "Markdown": "# Poly(vinyl alcohol) Hydrogels with Broad-Range Tunable Mechanical Properties via the Hofmeister Effect \n\nShuwang Wu, Mutian Hua, Yousif Alsaid, Yingjie Du, Yanfei Ma, Yusen Zhao, Chiao-Yueh Lo, Canran Wang, Dong Wu, Bowen Yao, Joseph Strzalka, Hua Zhou, Xinyuan Zhu,\\* and Ximin He\\* \n\nHydrogels, exhibiting wide applications in soft robotics, tissue engineering, implantable electronics, etc., often require sophisticately tailoring of the hydrogel mechanical properties to meet specific demands. For examples, so ft robotics necessitates tough hydrogels; stem cell culturing demands various tissuematching modulus; and neuron probes desire dynamically tunable modulus. Herein, a strategy to broadly alter the mechanical properties of hydrogels reversibly via tuning the aggregation states of the polymer chains by ions based on the Hofmeister effect is reported. An ultratough poly(vinyl alcohol) (PVA) hydrogel as an exemplary material (toughness $150\\pm20\\mathrm{M}|\\mathrm{m}^{-3}|$ ), which surpasses synthetic polymers like poly(dimethylsiloxane), synthetic rubber, and natural spider silk is fabricated. With various ions, the hydrogel’s various mechanical properties are continuously and reversibly in situ modulated over a large window: tensile strength from $50\\pm9\\mathsf{k P a}$ to $15\\pm1$ MPa, toughness from $0.0167\\pm0.003$ to $150\\pm20\\mathrm{M}|\\mathrm{m}^{-3}$ , elongation from $300\\pm100\\%$ to $2100\\pm300\\%$ , and modulus from $24\\pm2$ to $2500\\pm140\\mathrm{kPa}$ . Importantly, the ions serve as gelation triggers and property modulators only, not necessarily required to remain in the gel, maintaining the high biocompatibility of PVA without excess ions. This strategy, enabling high mechanical performance and broad dynamic tunability, presents a universal platform for broad applications from biomedicine to wearable electronics. \n\nHydrogels are 3D crosslinked polymeric materials with high water content. They have been widely studied because of their potential applications in various fields, such as tissue \n\nengineering,[1] drug delivery,[2] implantable electronics,[3] energy storage devices,[4] coatings,[5] adhesives,[6] soft robotics,[7] etc. However, several issues persist and await solutions in bridging hydrogel researches and specific realworld applications. First, the high water content and loose crosslinking of hydrogels make them mechanically weak and often too fragile to handle practical tasks. Despite various advances in toughening hydrogels by forming double network,[8] adding nanofillers,[9] and mechanical training,[10] their mechanical performances are still less than satisfactory compared to waterless polymers.[11,12] Second, their resemblance to biological tissues make them the most ideal matetriuarlisnfgo,rtthisesueleasetnicginmeoerdiunlgu.[s13]oIfnhcyedllrocguel-l should be on the same order of magnitude as that of the cells to promote adhesion between cells and hydrogel,[14] and to better mimic physiological conditions. In stem cell studies, the modulus of hydrogels can also affect the differentiation,[15] proliferation,[16] mitigation,[17] and spreading[18] of stem cells. Therefore, tremendous effort has been spent on tuning the hydrogel modulus via testing the combinations of various composition,[19] concentration,[20] or curing conditions.[21] However, these approaches suffer from a narrow range of achievable modulus[22] or require sophisticated recipes.[19] Third, in some scenarios, dynamic or in situ tuning of the material between stiff and soft states is highly beneficial.[23,24] For instance, a neuron probe is desired to be initially rigid for easy insertion into brain tissue, but become soft subsequently to avoid causing damage or inflammation to adjacent neuron cells.[23,24] Some elastomers based on phase transition can exhibit a large range of tunable modulus, yet they are still not soft enough to match the modulus of neurons even at their softest states.[23] Compared to elastomers, hydrogels are more biocompatible. Additionally, water, ions, nutrition, and many other biologically relevant molecules can transport freely in the porous hydrogel matrix.[25] Despite these significant advantages, little research has focused on realizing dynamic in situ tuning of hydrogel mechanical properties, therefore limiting their applications in these important areas. \n\nDifferent salts exhibit distinguishable abilities to precipitate proteins from aqueous solutions, which is known as the Hofmeister effect or ion-specific effect.[26] Such ion-specific phenomena have also been observed in other fields such as ice nucleation and recrystallization,[27] colloidal assembly,[28] and surface tension.[29] Regarding the synthetic macromolecules, plenty of researchers have studied the interactions among the ions, water molecules and polymer chains at the molecular level;[30] some works discussed how different ions affect the solubility and swelling of polymers;[31] a few papers reported improving hydrogel mechanical performance by soaking in salt solutions after the hydrogel is synthesized.[32,33] The previous studies of the ion-specific effect on hydrophilic polymers revealed that the ion-specific effects arise from the impacts of different ions on the hydration water around the hydrophilic functional groups on the hydrophobic chains.[34] However, the effects of different ions on the mechanical properties of hydrogels and utilizing the ion-specific effect to fabricate a functional hydrogel with variable mechanical properties have not yet been systematically studied.[32,33,35–37] Here, we proposed a freeze-soak method, soaking the frozen polymer solutions in the salt solutions, to fabricate hydrogels with different mechanical properties by tuning the aggregation of the hydrophilic polymer chains at the molecular level via the Hofmeister effect, to address the urgent demands of aforementioned various areas. Poly(vinyl alcohol) (PVA) was used as a model system here, because of the simple molecular structure of the amphiphilic macromolecule composed of a hydrophobic $(\\mathrm{CH}_{2}\\mathrm{-CH}_{2})$ backbone and hydrophilic $(\\mathrm{-OH})$ side-groups. Besides, it has many other outstanding merits such as biodegradability, biocompatibility, and nontoxicity[13] which have been well studied and made as hydrogels with various methods, such as freezethaw, chemically crosslinking, and mechanical training.[10,13] These make PVA an ideal exemplary polymer for the systematic study of the effects of various anions and cations on hydrogel networks, and to develop hydrogels with widely tunable mechanical, structural, and physical properties. In this study, by gelation of PVA in various salt solutions, we have fabricated an ultratough hydrogel (strain $2100\\pm300\\%$ , stress $15\\pm1\\mathrm{{\\:MPa}}$ , toughness, $150\\pm20\\mathrm{~M~J~m}^{-3},$ ) which has larger strain and stress than the most tough hydrogels reported previously and is even tougher than the synthetic polymers like PDMS, synthetic rubber, and natural spider silk. Meanwhile we have realized the modulation of the hydrogel’s mechanical properties over large windows: tensile strength ranging from $50\\pm9\\mathrm{{kPa}}$ to $15\\pm1$ MPa, toughness from $0.0167\\pm0.003$ to $150\\pm20\\ \\mathrm{MJ\\m^{-3}}$ , elongation from $300\\pm100\\%$ to $2100\\pm300\\%$ , and modulus from $24\\pm2$ to $2500\\pm140\\mathrm{kPa}$ . It is important to note that, during gelation the ions used only served to induce the aggregation of polymer chains and the formation of nano/microstructures. Instead of remaining in the polymer networks, the ions can be washed out completely and leave a hydrogel composed of pure PVA, hence maintaining the biocompatibility of the produced hydrogels without excess ions. Such a simple hydrogel, entirely physically assembled from PVA, hold important potential in broad applications in implantable tissues, cell culturing, stem cell differentiation, and neuron probes. \n\nWe first evaluated the effects of various ions on the gelation of PVA in their respective sodium and chloride salt solutions with the freeze-soak assay (Figure S1, Supporting Information). The $5\\mathrm{wt\\%}$ PVA solution was first frozen at $-20{}^{\\circ}\\mathrm{C}$ , followed by the addition of $1.0\\mathrm{~m~}$ salt solutions or pure water, after which the ice was allowed to melt at room temperature (Figure S1, Supporting Information). With freezing, the PVA was fixed in a specific shape macroscopically (Figure S2, Supporting Information) and the polymer chains were prepacked microscopically to facilitate the subsequent aggregation by ions to form a bulk hydrogel. The freezing also ensured clear judgement of whether the gelation happened during the thawing process. As shown in Figure S3 (Supporting Information), instead of forming a dense bulk hydrogel, the aggregates of PVA (without prior freezing) dispersed in the solution, presented a cloudy dispersion, when the solution state PVA was directly added into a salt solution (1.0 m $\\mathrm{Na}_{2}\\mathrm{SO}_{4},$ . On the contrary, with freezing, a dense bulk hydrogel was formed (Figure S2, Supporting Information). This was attributed to the polymer chain prepacking, as they were squeezed between the growing ice crystals during the freezing process.[38] During the subsequent melting process, the gelation occurred in 1.0 m $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ solution, which resulted in an opaque PVA hydrogel as shown in Figure S4 (Supporting Information); however, the PVA remained as a liquid solution when pure water or $1.0\\mathrm{~m~}$ NaI solution was used (Figure S4, Supporting Information). \n\nGenerally, depending on the ion species, there are three kinds of possible interactions between the ions, the polymer chains, and the hydration water of polymer,[34,39] as illustrated by Figure 1a. First, some anions can polarize the hydration water molecules, which destabilizes the hydrogen bonds between the polymer and its hydration water molecules (Figure 1a1). Second, some ions can interfere with the hydrophobic hydration of the macromolecules by increasing the surface tension of the cavity surrounding the backbone (Figure $\\mathbf{1}\\mathbf{a}_{2}$ ). Third, other anions can bind directly and thus add extra charges to the PVA chains, which increase the solubility of the polymer (Figure $\\left|\\mathsf{a}_{3}\\right\\rangle$ . Specifically, ions such as $\\mathrm{SO_{4}}^{2-}$ and $\\mathrm{CO}_{3}{}^{2-}$ exhibit the first and second effects and could lead to the salting-out of polymers, thereby resulting in the collapse of polymer chains and forming small pores.[39] During the melting process of frozen samples in solutions of these ions, the water molecules were expelled from between the polymer chains, and the hydrogen bonds formed between the hydroxyl groups, which resulted in aggregation/ crystallization of the polymer chains (Figure  1b). By contrast, other ions like ${\\mathrm{NO}}_{3}{}^{-}$ and $\\mathrm{I}^{-}$ exhibit the third interaction and lead to the salting-in of polymers.[39] As a result, the hydrogen bonds were dissociated, and the solubility increased when the frozen samples were melted in solutions of these other ions (Figure 1c). \n\nTo systematically investigate the effect of each type of anions/ cations, series of sodium salts and chloride salts were chosen according to the Hofmeister series. As depicted in Figure  1d, when frozen samples were soaked in $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ solution, PVA gelation occurred, as long as the ion concentration was higher than $0.5\\textbf{M}$ . However, in NaI solution, the PVA reverted to solution, even when the ion concentration was as high as $3.0\\ \\mathrm{u}$ . The critical gelation concentration of ions was also influenced by the concentration and molecular weight of PVA (Figure S5, Supporting \n\n![](images/996049ce2ebb76c85087a643701b35143a97587a4aea4effe5e5c0fd84d035e4.jpg) \nFigure 1.  Schematics of the aggregation states of PVA polymer chains treated with different ions. a) The interactions among ions, polymer chains, and water molecules. b) Hydrogen bonds form between PVA polymer chains induced by ions due to salting-out effect. c) Hydrogen bonds break between PVA polymer chains induced by ions due to salting-in effect. d,e) Summary of the status of PVA gelation induced by different ions of different concentrations. The top-left region (blue) and the bottom-right region (yellow), respectively, represent the gelation and nongelation conditions. \n\nInformation). By comparing the critical gelation concentrations of $5\\mathrm{\\wt\\%}$ PVA in different anions, a typical Hofmeister series emerged following the sequence $\\mathrm{SO_{4}}^{2-}>\\mathrm{CO_{3}}^{2-}>\\mathrm{Ac^{-}}>\\mathrm{Cl^{-}}>$ ${\\ N O_{3}}^{-}>{\\ I^{-}}$ , with $\\mathrm{{Na^{+}}}$ as the constant counterion. The cations had similar specific effect on the gelation of PVA. However, the effect was less pronounced than that of anions, which was consistent with other phenomenon caused by the Hofmeister effect.[27] When $\\mathrm{Cl^{-}}$ was used as the constant counterion, the critical gelation concentration of cations was $1.5~\\mathrm{~M~}$ at a minimum, and the PVA could not be gelled by $\\mathrm{Li^{+}}$ , $\\mathrm{Ca}^{2+}$ , and $\\mathrm{Mg^{2+}}$ (Figure 1e). The cation sequence based on critical PVA gelation concentration followed $\\mathrm{K^{+}}>\\mathrm{Na^{+}}\\approx\\mathrm{Cs^{+}}>\\mathrm{Li^{+}}\\approx\\mathrm{Ca^{2+}}\\approx\\mathrm{Mg^{2+}},$ . With systematic experiments, a chart of concentration versus ions was obtained as shown in Figure  1d,e, respectively, for anions and cations. In the chart, the blue and yellow regions represent the corresponding ions and their concentrations for gelation or nongelation, respectively. \n\nThe gelation occurred because of the salting-out effect, during which the aggregation of PVA chains were rearranged by ions. Therefore, this effect could be applied to tune the mechanical properties of the PVA hydrogels. To confirm this, PVA hydrogels made with 3 freeze-thaw cycles, after which the PVA solution became a translucent hydrogel (Figure S6, Supporting Information). Then the obtained hydrogels were soaked in 1.5 m $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ for different times from 1 to $^{48\\mathrm{~h~}}$ (Figure S7, Supporting Information), which showed that after $24\\mathrm{h}$ soaking, the mechanical performance reached a plateau. Afterward, the mechanical properties of the PVA hydrogels soaked in different salt solutions for $24\\mathrm{~h~}$ at room temperature were characterized systematically. Figure 2a,b showed the typical stress– strain curves of PVA hydrogels treated with different sodium salts and chloride salts chosen based on the Hofmeister series. Among the anion series, PVA hydrogel immersed in solution of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ had the largest ultimate stress $(2.2\\ \\mathrm{MPa})$ and strain $(1400\\%)$ , while the PVA hydrogel immersed in $\\mathrm{I}^{-}$ had the smallest ultimate stress $(50\\mathrm{~kPa})$ and strain $(300\\%)$ (Figure 2d. Systematically, the strength and toughness of PVA hydrogels of various anions followed the order: $\\mathrm{SO}_{4}^{2-}>\\mathrm{CO}_{3}^{2-}>\\mathrm{Ac}^{-}>\\mathrm{Cl}^{-}>$ ${\\ N O}_{3}{}^{-}>{\\mathrm{I}}^{-}$ . Similar to the observations made with gelation process, the effects of cations were less pronounced than those of the anions. Here, the stress–strain curves of PVA hydrogels soaked in $3.0\\mathrm{~\\m~}$ chloride salts were measured. As shown in Figure  2b,d, the PVA hydrogel of KCl gives the largest stress $(1.1\\ \\mathrm{MPa})$ as the hydrogel was stretched to $700\\%$ . At the same time, the stress of PVA hydrogel immersed in LiCl was only $100~\\mathrm{{kPa}}$ as the hydrogel was stretched to $300\\%$ (Figure  2b,d). Note that the stress–strain curves of gels treated by $\\mathrm{Ca}^{2+}$ and $\\mathrm{Mg^{2+}}$ could not be measured because the PVA hydrogel almost dissolved in these salt solutions. By comparing the strength and toughness, a cation series was obtained: $\\mathrm{K^{+}>N a^{+}\\approx C s^{+}>L i^{+}>}$ $\\mathrm{Ca}^{2+}\\approx\\mathrm{Mg}^{2+}$ . To study the stability of the mechanical properties of PVA hydrogels in pure water for a long period of time, the salts were washed out with abundant pure water and the hydrogels were soaked in pure water for more than $^{48\\mathrm{~h~}}$ . As shown in Figure S8 (Supporting Information), their mechanical properties showed decreases, yet significantly higher than that of the untreated PVA hydrogel prepared by 3 cycles of freeze-thaw only, which was too soft to be measured. Particularly, the hydrogel made in the saturated $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ solution had a strength around $6.3\\ \\mathrm{MPa}$ with an elongation around $1900\\%$ after removing the salts in the hydrogel and soaking in pure water for $^{48\\mathrm{~h~}}$ . Additionally, the strength retention increased as the salt concentration decreased (Figure S8,e,f, Supporting Information). The images showed that the hydrogel remained unchanged even after immersion in water for three months (Figure S9, Supporting Information). This confirmed that during the salting-out process, the ions mainly induced the aggregation of the polymer chains, but did not serve as components in the aggregated hydrogel.[40] Moreover, the viscoelastic behaviors of the hydrogels were measured after washing out the salts. As shown in Figure S10 (Supporting Information), the storage moduli and loss moduli of hydrogels follow the same order of ions. The hydrogels showed mainly an elastic behavior, as the storage moduli were an order of magnitude higher than loss moduli. \n\n![](images/dc07b23f94ed99cdd595591fe74badd42d7f7572d282726484bb5a7b51c51fb2.jpg) \nFigure 2.  Tunable mechanical properties of PVA hydrogels by various ions. a–c) Representative stress–strain curves of PVA hydrogels soaked in 1 m sodium salts (a), $3M$ chloride salts (b), and ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ with concentration range from 0 m to saturated (c). ${\\mathsf{d}}{-}{\\mathsf{f}})$ Strengths (d), toughness (e), and moduli (f) of PVA hydrogels tuned by various anions (with ${\\mathsf{N a}}^{+}$ as the constant counterion); different cations (with $\\mathsf{C l}^{-}$ as the constant counterion); and ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ with concentrations ranging from $0\\mathrm{~m~}$ to saturated. g) Diagrams of ultimate strength versus ultimate strain $\\left({{\\bf{g}}_{1}}\\right)$ , and toughness versus ultimate strain $(\\mathsf{g}_{2})$ of the hydrogels treated with different ions compared with other tough hydrogels and polymers reported in references. h) The moduli ranges of soft tissues in the human body and the PVA hydrogels regulated by ions with different concentrations. The green circle in (h) refers to the moduli range of the asprepared PVA hydrogels. The blue shaded areas in $(\\mathsf{g}_{\\mathsf{l}})$ and $(\\mathsf{g}_{2})$ indicate the ranges of strength and toughness that can be tuned via the Hofmeister effect. \n\nFurthermore, the specific ion effect is usually concentration sensitive. Here, $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ was used as an example to study the influence of concentrations. As concentration of $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ increased from $0.5\\mathrm{~m~}$ to saturated $({\\approx}1.8\\ \\mathrm{m}$ at room temperature), the ultimate stress and maximum strain of the resulted hydrogel increased significantly from 1.0 to $15.0\\mathrm{MPa}$ and from $1500\\%$ to $2100\\%$ , respectively (Figure 2c). Toughness and modulus exhibited similar trends, which increased from 3.1 to 153.41 MJ $\\mathrm{m}^{-3}$ and from 24 to $2500~\\mathrm{kPa}$ , respectively (Figure 2d,e,f). Note that the hydrogel soaked with saturated $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ showed higher ultimate stress and strain that surpassed the values reported in previous works studying tough hydrogels (Figure $2\\mathrm{g}_{1})$ by 10 to $10^{3}$ fold,[41–43] and the corresponding toughness was larger than the water-free polymers like PDMS, synthetic rubber and natural spider silk (Figure $2\\mathrm{g}_{2})$ ). Furthermore, via changing the ions or concentrations, the modulus of PVA hydrogels can be easily tuned within a broad range, from near 24 to $2500\\ \\mathrm{kPa}$ , which covered all the moduli of soft tissues in the human body[38,44] as shown in Figure 2h With such a large range of moduli and biocompatibility, the PVA hydrogels can offer a very promising material platform for stem cells to differentiate into various functional cells, ranging from extremely soft brain cells to very rigid cartilage cells. This strategy was also applicable to other polymers such as gelatin (Figure S11, Supporting Information). Additionally, in contrast to traditional hydrogels with certain mechanical properties achieved by ionic crosslinking,[45,46] the ions used here, functioned as a gelation trigger rather than the components of the hydrogels, which was washed out with of DI water and left the final hydrogel structure ion-free without altering its properties or comprising the biocompatibility. \n\nAlong with the tunable mechanical properties over large ranges, the water contents remained high, with slight differences among the PVA hydrogels soaked in different ions solutions. As shown in Figure S12 (Supporting Information), the water contents of PVA hydrogels treated with various sodium salts followed the order: $\\mathrm{Na_{2}S O_{4}N a_{2}C O_{3}>}$ $\\mathrm{NaNO_{3}}\\approx\\mathrm{NaI}$ . Figure  3c,d; and Figure S15 (Supporting Information) showed the morphologies of $\\mathrm{PVA-SO_{4}}$ and $\\mathrm{PVA-NO}_{3}$ . The $\\mathrm{PVA-SO_{4}}$ hydrogel had the highest pore density and the smallest pore size of around $200\\ \\mathrm{nm}$ among all tested ions of the same concentration (Figure  3c; and Figure S15, Supporting Information). Its structure presented continuous networks of nanofibrils. By contrast, in $\\mathrm{PVA-NO}_{3}$ hydrogel, most pores were around $2\\upmu\\mathrm{m}$ in size, with a few smaller pores on the walls of the larger pores (Figure 3d). Such a significant difference in morphology between $\\mathrm{PVA-SO_{4}}$ and $\\mathrm{PVA-NO}_{3}$ was believed to originate from the aforementioned specific ion effect. Ions such as $\\mathrm{SO}_{4}{}^{2-}$ and $\\mathrm{CO}_{3}{}^{2+}$ triggered the salting-out of the polymers, thereby resulting in the spontaneous collapse of polymer chains and formation of the small pores. Ions like ${\\mathrm{NO}}_{3}{}^{-}$ and $\\mathrm{I}^{-}$ led to the salting-in of the polymer, which resulted in partial dissolution of the polymer, and has led to larger pores (Figures S15 and S16, Supporting Information). \n\n![](images/98758ad08a85074f5b40398efa1f8affb83806d9307c1115add5fbcad7920268.jpg) \nFigure 3.  Characterizations of PVA hydrogels soaked in 1 m ${\\mathsf N}{\\mathsf a}_{2}{\\mathsf S}{\\mathsf O}_{4}$ and ${\\mathsf{N a N O}}_{3}$ . a,b) XRD spectra of PVA hydrogels soaked with $\\mathsf{1.0~m}$ ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ and ${\\mathsf{N a N O}}_{3}$ . The inset shows the enlarged spectra to compere the crystalline information. c,d) SEM images of PVA– $S O_{4}$ and $P\\mathsf{V}A\\mathsf{-}N O_{3}$ . SEM scale bars $500\\ \\mathsf{n m}$ . e) SAXS patterns of $P V A\\mathrm{-}S O_{4}$ and PVA– ${\\mathsf{N O}}_{3}$ during tensile loading. SAXS scale bar $0.025\\mathring{\\mathsf{A}}^{-1}$ . f) The schematic structures of PVA– ${\\cdot}S O_{4}$ and PVA– ${\\cdot\\mathsf{N O}}_{3,}$ with different densities of nanofibrils and crystalline domains and thus different crack blunting and pinning effects. \n\nFor $\\mathrm{PVA-SO_{4}}$ during stretching, the nanofibril spacing decreased significantly as the network became partially aligned, as indicated by the stretch of SAXS pattern perpendicular to the stretching direction (Figure  3e1). The average nanofibril spacing decreased from ${\\approx}90$ to ${\\approx}30~\\mathrm{nm}$ (Figure S17, Supporting Information) when the strain increased from $0\\%$ to $500\\%$ . Such scattering difference was not observed for PVA– $\\mathrm{NO}_{3}$ , which had no structural features of the same length scale (Figure $3\\mathrm{e}_{2}$ ). From a fracture mechanics perspective, there were three reasons why the $\\mathrm{PVA-SO_{4}}$ was much tougher than the $\\mathrm{PVA-NO}_{3}$ . First, because of the two opposite effects, saltingout and salting-in, the density of polymer chains in $\\mathrm{PVA-SO_{4}}$ was higher than that in $\\mathrm{PVA-NO}_{3}$ (also verified by the different water contents in these two hydrogels as shown in Figure S12, Supporting Information). Second, during the salting-out process, abundant hydrogen bonds were formed which resulted in strong aggregation and partial crystallization of the polymer chains (Figures  1b and  3a), while $\\mathrm{PVA-NO}_{3}$ went through a reverse process of salting-in (Figures 1c and 3b) . Therefore, the density of crystalline domains in $\\mathrm{PVA-SO_{4}}$ was much higher than that in $\\mathrm{PVA-NO}_{3}$ . The structures and material elasticity were strengthened and improved by the crystalline domains which acted as rigid high functionality cross-linkers.[11] Meanwhile, the crystalline domains delayed the fracture of individual nanofibrils by crack pinning leading to the toughness enhancement[10] (Figure 3f). Third, compared to $\\mathrm{PVA-NO}_{3}$ which has no nanofibril features, when $\\mathrm{PVA-SO_{4}}$ was stretched, the decrease in interfibril spacing led to an increase in concentration of nanofibrils per unit cross-section, which in situ strengthened the material (Figure  3e). In short, $\\mathrm{PVA-SO_{4}}$ obtained extraordinary toughness and largest ranges of strength and moduli because of the densification enhancements on three levels: polymer chains, crystalline domains, and nanofibrils (Figure 3). \n\nThe mechanical properties of PVA hydrogel can be altered by different ions dynamically which means the tough gel made by some salting-out salts can be soften by some salting-in salts. As illustrated in Figure  4a after soaking in saturated $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ and washed with excess water, the PVA hydrogel became opaque and shrunk slightly. Subsequently, the opaque PVA hydrogel was soaked in 3 m $\\mathrm{CaCl}_{2}$ for $^{48\\mathrm{~h~}}$ , where it transformed into a translucent hydrogel that swelled back slightly. Meanwhile, the corresponding strength, toughness, and modulus were tuned dynamically from $15.53~\\mathrm{\\MPa}$ , 153.41  MJ $\\mathbf{m}^{-3}$ and $2500\\ \\mathrm{kPa}$ to 0.09  MPa, 2.48  MJ $\\mathbf{m}^{-3}$ , and $34~\\mathrm{kPa}$ , respectively. Many salting-out salts have been tested, such as $\\mathrm{LaCl}_{3}$ , $\\mathsf{A l}(\\mathsf{N O}_{3})_{3}$ and ${\\mathrm{Fe}}({\\mathrm{NO}}_{3})_{3}$ (Figure S18, Supporting Information), and $\\mathrm{Fe}(\\mathrm{NO}_{3})_{3}$ was found to have the strongest salting-in effect, which can soften the tough hydrogels rapidly. As shown in Movie S1 (Supporting Information), the hydrogel became transparent and soft in less than $10\\mathrm{min}$ in the $3\\mathrm{~M~Fe}(\\mathrm{NO}_{3})_{3}$ . It took 26 and $100\\mathrm{min}$ respectively, to soften the PVA hydrogel in 2 and $1\\textbf{M}$ solutions (Figure S19, Supporting Information). The effect of repeated soaking in salting-in and salting-out solutions on the mechanical performances were also studied. As shown in Figure S20 (Supporting Information), after the first cycle, the strength can be recovered to $72\\%$ and $48\\%$ for the second cycle. As the cycles increased further, the strength decreased at a slower rate. The decrease of mechanical property was mainly attributed to that polymers partially dissolved away from the bulk material during soaking in the salting-in solution. Such hydrogel with variable mechanics can be potentially used as neuron probes, which need to be rigid initially to easily insert into brain tissue, and as soon as after insertion, become softened subsequently to match the modulus of neuron cells[3] $({\\approx}10\\ \\mathrm{kPa})$ . Here, to mimic the brain tissue, a soft hydrogel made of polyacrylamide with a brain-tissue-matching modulus $({\\approx}10\\ \\mathrm{kPa})$ was utilized. When the PVA hydrogel probe was toughened by ${\\mathrm{Na}}_{2}{\\mathrm{SO}}_{4},$ it could penetrate the soft polyacrylamide hydrogel as shown in Figure $\\mathsf{4b}_{1},$ while the soft PVA hydrogel soaked in 1 m $\\mathrm{CaCl}_{2}$ could not (Figure $\\mathsf{4b}_{2};$ and Figure S21, Supporting Information). Furthermore, to demonstrate on-site stiffness tuning, i.e., the hydrogel can be softened after “implantation,” the hydrogel probe inserted in the brain-mimicking hydrogel was soaked in a $2\\textbf{M}$ $\\mathrm{Fe}(\\mathsf{N O}_{3})_{3}$ solution. As shown in Figure  4c the originally white hydrogel probe became translucent gradually over $220\\ \\mathrm{min}$ of soaking, indicating that the PVA hydrogel probe can be in situ softened by ions even, while constrained inside another matrix. This on-site stiffness tunability presents attractive advantages and opportunities for applications that require local tuning of material properties, unachievable with conventional materials whose properties are set once produced or can be tuned only with extreme conditions, such as high temperature.[23] \n\n![](images/4a983716b668635ea060a75ff2277d1d0b5bac8f3348fe5228c7a7adf616716b.jpg) \nFigure 4.  PVA hydrogel softened or toughened by ${\\mathsf N}{\\mathsf a}_{2}{\\mathsf S}{\\mathsf O}_{4}$ and $\\mathsf{C a C l}_{2}$ , respectively. a) Optical images of PVA hydrogel after soaking with solutions of saturated ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ and $3{\\mathsf{M}}{\\mathsf{C a C l}}_{2}$ . The PVA hydrogel was toughened by ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ and then softened by $\\mathsf{C a C l}_{2}$ , with the corresponding values of strength, toughness, and modulus listed. Scale ba $=1$ . $\\mathsf{b}_{\\rceil}$ ) A stiff PVA hydrogel toughened by 1 m ${\\mathsf N}{\\mathsf a}_{2}{\\mathsf S}{\\mathsf O}_{4}$ penetrating into a soft brain-tissue-mimicking hydrogel. $\\left\\lfloor\\right\\rceil_{2})$ ) A soft PVA hydrogel treated with 1 $\\mathsf{C a C l}_{2}$ ould n te the same brain-tissue-mimicking hydrogel. The hydrogel probes were dyed with Rhodamine B for visualization ) The hydrogel probe inserted in the brain-mimic hydrogel was soaked in a $2M$ ${\\sf F e}({\\sf N O}_{3})_{3}$ solution. Over $220\\mathrm{min}$ , the original white hydrogel probe gradually became translucent. Scale bars of (b) and (c) are 1 cm and $\\mathsf{l}\\mathsf{m}\\mathsf{m}$ , respectively. \n\nIn summary, with a freeze-soak method, it was discovered that ions have a specific effect on the gelation of PVA. The effects of different ions on the ion-facilitated gelation and the toughening of PVA followed such orders: $\\mathrm{SO_{4}}^{2-}>\\mathrm{CO_{3}}^{2-}>$ $\\mathrm{Ac^{-}>C l^{-}>N O_{3}^{-}>I^{-}}$ for anions and $\\mathrm{K^{+}>N a^{+}\\approx C s^{+}>L i^{+}\\approx}$ $\\mathrm{Ca}^{2+}\\approx\\mathrm{Mg}^{2+}$ for cations. The ion-specific gelation originated from the different interaction modes with PVA polymer chains that resulted in either salting-out or salting-in. The PVA hydrogels showed mechanical properties that followed the Hofmeister series after being treated with various salts solutions. In addition to the different types of ions used, higher salt concentration also enhanced their influence on the mechanical properties of the produced hydrogels. Therefore, by changing the types and concentrations of salts, the mechanical properties of PVA hydrogels could be tuned with a large window. Specifically, the tensile strength was tuned from $50\\pm9\\mathrm{{kPa}}$ to $15\\pm1~\\mathrm{MPa}$ , toughness was regulated from $0.0167\\pm0.003$ to $150\\pm20\\mathrm{~M~}$ J $\\mathbf{m}^{-3}$ , and the elongation varied from $300\\pm100\\%$ to $2100\\pm300\\%$ . Specially, the PVA hydrogel treated with saturated $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ solution showed the largest strength $(15\\pm1\\mathrm{{MPa}}_{\\beta}^{\\prime}$ ), toughness $(150\\pm20\\mathrm{~M~}$ J $\\mathbf{m}^{-3}$ ), and elongation $(2100\\pm300\\%$ ), which can be considered as an ultratough and highly-stretchable hydrogel. The hydrogel soaked with saturated $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ showed higher ultimate stress and strain surpassing the values reported in previous works of tough hydrogels by $\\scriptstyle10-10^{3}$ fold, and the toughness of hydrogels soaked with saturated $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ is higher than that of water-free polymers like PDMS, synthetic rubber and natural spider silk. The hydrogels treated with different salts showed significantly different mechanical properties, which resulted from the various degrees of aggregation of polymers chains because of the specific interactions among the ions, water molecules, and polymer chains at the molecular level. In this study, PVA was used as an exemplary polymer to demonstrate the regulation of mechanical properties by tuning the aggregation states of polymer chains. Since the classic Hofmeister effect is universal for hydrophilic polymers, the presented strategy can be extended to many other systems composed of hydrophilic polymers. \n\nFurthermore, the demonstration of onsite dynamically tunable stiffness presented a potentially new strategy to design hydrogel-based neuron probes with the stiffness tuned by ions. Although currently the salt concentration used in the proof of concept here is higher than that in human body, through optimization the hydrogel neuron probe may be further improved for practical applications. Additionally, the ions utilized for fabricating the hydrogels only induced the aggregation of polymer chains and the formation of structures, instead of serving as the components of hydrogels. Hence, after soaking treatment in ions solutions and subsequently washing out the ions completely, the final ion-free PVA hydrogels could well maintain their properties and the highly desirable biocompatibility without interferences from potentially hazardous ions used when making the hydrogels. With this facile method and the excellent in situ and broad-range tunability of mechanical properties, PVA hydrogels can be expanded to a broader-based platform to meet the needs of a variety of areas ranging from biomedicine to robotics and wearable electronics. \n\n# Experimental Section \n\nMaterials: Poly(vinyl alcohol) (PVA) (weight-average molecular weight $(M w)$ of $89-98~\\mathsf{k D a}$ ; degree of hydrolysis of $99\\%$ ; SigmaAldrich), glutaraldehyde $25\\ \\mathrm{~v\\%~}$ ; Sigma-Aldrich), hydrochloric acid (36.5–38  wt $\\%$ , Sigma-Aldrich), salts (analytical grade; Sigma-Aldrich) Rhodamine B, acrylamide (analytical grade; Sigma-Aldrich), $N,N^{\\prime}.$ methylenebisacrylamide, and 2-hydroxy-2-methylpropiophenone were used as received. \n\nPreparation of PVA and Salt Solutions: 2, 5, and $10\\mathrm{\\Omega}\\mathrm{wt\\%}$ PVA solutions were prepared by dissolving PVA powder in deionized (DI) water under vigorous stirring and heating $(95~^{\\circ}\\mathsf{C})$ . After degassing by sonication for $1\\ h$ , clear solutions were obtained. Various salt solutions of different concentrations were prepared by dissolving salts in DI water. After sonication for $10\\min$ , clear salt solutions were obtained. \n\nFabrication of Hydrogel: To judge if the PVA solutions can form hydrogels, $1.5~\\mathsf{m L}$ PVA solution of $5\\mathrm{\\wt\\%}$ was injected into a vial and was frozen at $-20^{\\circ}\\mathsf C$ . Then the frozen samples were transferred to room temperature and different salt solutions of $\\mathsf{l}.0\\mathrm{~m~}$ or DI water were added, where the ice melted over time. After $\\rceil\\mathfrak{h}$ , the vial was shaken to see if the solution became a hydrogel. To fabricate the hydrogels for measuring the mechanics, $20m L70~\\mathrm{wt\\%}$ PVA solution was poured into a Petri dish and freeze–thawed for 3 cycles, after which it became a hydrogel. The hydrogel was cut into strips of $5\\mathsf{m m}\\times3\\mathsf{c m}$ and soaked into different salt solutions with specific concentrations for $24\\mathrm{~h~}$ . To test the stability of hydrogels soaking in pure water for a long period of time, the hydrogels were first freeze–thawed for three cycles and then soaked in solutions of different concentrations from $0.5~\\mathsf{m}$ to saturate. Afterward, the samples were soaked in a large container (volume $=6000~\\mathrm{mL}$ ) for 2 days, during which the water was exchanged for 4 times. The mechanical properties of hydrogels were measured after the thorough washing and swelling. The PVA hydrogels with different shapes were obtained by freezing the PVA solutions in specific molds, followed by soaking in $\\mathsf{l}.5\\mathrm{~m~}\\mathsf{N a}_{2}\\mathsf{S O}_{4}$ . At last, the molds were removed. To make gelatin hydrogels, a solution of $70\\mathrm{\\ut\\%}$ gelatin was prepared by dissolving $\\rceil0\\mathrm{~g~}$ gelatin in $90~\\mathsf{m L}$ pure water at $50~^{\\circ}\\mathsf{C}$ with stirring. Afterward, the solution was poured in a petri dish and kept at room temperature overnight for gelation. At last, the gelatin hydrogels were soaked in various ${\\mathsf{1}}{\\mathsf{M}}$ salt solutions for $24\\mathsf{h}$ and characterized. \n\nTensile Testing: Hydrogels were cut into dog-bone shaped specimens with gauge width of $2\\ m\\ m$ for regular tensile testing. The thickness of each specimens was measured with a caliper. The force–displacement data were obtained using a Cellscale Univert mechanical tester with a 50N loading cell installed. The stress–strain curves were obtained by division of an initial gauge cross-section area and an initial clamp distance. \n\nSEM Characterization: For the characterization of the micro- and nanostructures of the hierarchically aligned hydrogels, all hydrogel samples were immersed in DI water for $24\\ h$ before freeze drying using a Labconco FreeZone freeze drier. The freeze-dried hydrogels were cut along the aligned direction to expose the inside and sputtered with gold before carrying out the imaging using a ZEISS Supra 40VP SEM. \n\nX-Ray Scattering Characterization: The hydrogels treated with different ions were cut into $1c m$ by $4c m$ rectangles and washed with plenty of DI water for before testing. The beamline station used was APS 8-ID-E (Argonne National Laboratory) equipped with Pilatus 1 m detector. A customized linear stretcher was used to hold the samples and stretch on demand for in situ X-ray scattering measurements. A MATLAB toolbox “GIXSGUI” was used for further line-cut analysis and space conversion of the obtained scattering pattern.[47] \n\nWater Content Measurement: The hydrogels were washed with plenty of pure water after soaking in different salt solutions for $24\\ h$ (concentration: $1.5~\\mathsf{m}$ ). The water contents of the PVA hydrogels were measured by comparing the weights before and after freeze-drying. Excess surface water was wiped away from the hydrogel surface before measuring the weight $(m_{\\mathrm{w}})$ . The hydrogel samples were instantly frozen in liquid nitrogen and freeze-dried with a Labconco FreeZone freeze drier. Weight before $(m_{\\mathrm{w}})$ and after freeze drying $(m_{\\mathrm{d}})$ were measured with a balance. The water content was calculated by $(m_{\\mathrm{w}}{-}m_{\\mathrm{d}})/m_{\\mathrm{w}}{\\mathrm{\\ddot{*}}}700\\%$ . \n\nMeasurement of Crystallinity: The crystallinities of $\\mathsf{P V A-S O}_{4}$ and $P\\mathsf{V}A\\mathsf{-}N O_{3}$ were measured by DSC (DSC-Q8000). The $P V A-S O_{4}$ and $P\\mathsf{V}A\\mathsf{-}N\\mathsf{O}_{3}$ were first soaked in the $700~\\mathsf{m L}$ solution consisting $20~\\mathsf{m L}$ of glutaraldehyde and $7m L$ of hydrochloric acid for $6\\mathrm{~h~}$ . During this process, the amorphous parts in the hydrogels were crosslinked and fixed by glutaraldehyde. Thereafter, the samples were immersed in DI water for $24\\ h$ to remove the unreacted glutaraldehyde and hydrochloric acid. The samples were further dried and measured with DSC.[48] \n\nMeasurements of the Reversibility: The PVA hydrogels were prepared with 3 cycles of freeze-thaw, followed by soaking in $\\mathsf{l}.5\\mathsf{m N a}_{2}\\mathsf{S O}_{4}$ for $24\\ h$ and in $2\\ M F e(N O_{3})_{3}$ for $100\\mathrm{\\min}$ , respectively. The soaking processes were repeated for different cycles and the mechanical properties were measured. \n\nDynamically Tuning PVA Hydrogel: The PVA hydrogel freeze-thawed for three cycles was first immersed in a 1 m $N a_{2}S O_{4}$ solution for $24\\ h$ ; then it was washed with plenty of water to remove the salts in the hydrogel. Afterward, the hydrogel was soaked in a $3{\\ensuremath{\\mathsf{\\Delta}}}{\\mathsf{M}}{\\mathsf{\\Sigma}}{\\mathsf{C a C l}}_{2}$ solution for $48\\mathrm{~h~}$ . During this soaking process, the images were taken with a camera. \n\nFabrication of Brain-Tissue-Mimicking Hydrogels and Softening of the Probe: To make a brain-tissue-mimicking hydrogel, $700~\\mathsf{m L}$ precursor solution was prepared containing $5g$ monomer acrylamide, $400~\\mathsf{m g}$ cross-linker $N,N^{\\prime}$ -methylenebisacrylamide, and $70~\\upmu\\upiota$ initiator 2-hydroxy2-methylpropiophenone. Then the precursor was cured in a cubic mold with UV illumination or printed. To observe the softening process of the probe, a brain-tissue-mimicking hydrogel was first soaked in $2\\mathsf{\\Omega}_{\\mathsf{M}}$ ${\\sf F e}({\\sf N O}_{3})_{3}$ to exchange the solution in the polymer matrix. Afterward, a hydrogel probe was inserted into the brain-tissue-mimicking hydrogel and they were immersed together in $2\\textsf{m}$ Fe $(N O_{3})_{3}$ . \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThis research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility, operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. This research was supported by NSF CAREER Award No. 1724526, AFOSR Award Nos. FA9550-17-1- 0311, FA9550-18-1-0449 and FA9550-20-1-0344, and ONR Award Nos. N000141712117 and N00014-18-1-2314. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Author Contributions \n\nS.W., M.H., and X.H. conceived the concept. X.Z. and X.H. supervised the project. S.W. and M.H., conducted the experiments. J.S. and H.Z. helped with the SAXS measurements. S.W., M.H., and X.H. wrote the manuscript. All authors contributed to the analysis and discussion of the data. S.W. and M.H. contributed equally to this work. \n\n# Data Availability Statement \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Keywords \n\nHofmeister effect, ions, poly(vinyl alcohol), tough hydrogels, tunable mechanical properties \n\nReceived: November 17, 2020 \nRevised: December 28, 2020 \nPublished online: February 8, 2021 \n\n[1]\t K. Y. Lee, D. J. Mooney, Chem. Rev. 2001, 101, 1869. \n[2]\t J. Li, D. J. Mooney, Nat. Rev. Mater. 2016, 1, 16071. \n[3]\t Y.  Liu, J.  Liu, S.  Chen, T.  Lei, Y.  Kim, S.  Niu, H.  Wang, X.  Wang, A. M. Foudeh, J. B. H. Tok, Z. Bao, Nat. Biomed. Eng. 2019, 3, 58. \n[4]\t Y.  Huang, M.  Zhong, F.  Shi, X.  Liu, Z.  Tang, Y.  Wang, Y.  Huang, H. Hou, X. Xie, C. Zhi, Angew. Chem., Int. Ed. 2017, 56, 9141. \n[5]\t X.  Yao, J.  Liu, C.  Yang, X.  Yang, J.  Wei, Y.  Xia, X.  Gong, Z.  Suo, Adv. Mater. 2019, 31, 1903062. \n[6]\t H.  Yuk, T.  Zhang, S.  Lin, G. A.  Parada, X.  Zhao, Nat. Mater. 2016, 15, 190. \n[7]\t H.  Yuk, S.  Lin, C.  Ma, M.  Takaffoli, N. X.  Fang, X.  Zhao, Nat. Commun. 2017, 8, 14230. \n[8]\t J. Y.  Sun, X.  Zhao, W. R. K.  Illeperuma, O.  Chaudhuri, K. H.  Oh, D. J. Mooney, J. J. Vlassak, Z. Suo, Nature 2012, 489, 133. \n[9]\t L.  Han, X.  Lu, K.  Liu, K.  Wang, L.  Fang, L. T.  Weng, H.  Zhang, Y. Tang, F. Ren, C. Zhao, G. Sun, R. Liang, Z. Li, ACS Nano 2017, 11, 2561. \n[10]\t S.  Lin, J.  Liu, X.  Liu, X.  Zhao, Proc. Natl. Acad. Sci. USA 2019, 116, 10244. \n[11]\t X. Zhao, Soft Matter 2014, 10, 672. \n[12]\t H. Fan, J. P. Gong, Macromolecules 2020, 53, 2769. \n[13]\t A. Kumar, S. S. Han, Int. J. Polym. Mater. Polym. Biomater. 2017, 66, 159. \n[14]\t O.  Chaudhuri, L.  Gu, D.  Klumpers, M.  Darnell, S. A.  Bencherif, J. C.  Weaver, N.  Huebsch, H. P.  Lee, E.  Lippens, G. N.  Duda, D. J. Mooney, Nat. Mater. 2016, 15, 326. \n[15]\t A. S. Mao, J. W. Shin, D. J. Mooney, Biomaterials 2016, 98, 184. \n[16]\t F. Trensz, F. Lucien, V. Couture, T. Söllrald, G. Drouin, A. J. Rouleau, M. Grandbois, G. Lacraz, G. Grenier, Skelet. Muscle 2015, 5, 31. \n[17]\t W. J. Hadden, J. L. Young, A. W. Holle, M. L. McFetridge, D. Y. Kim, P.  Wijesinghe, H.  Taylor-Weiner, J. H.  Wen, A. R.  Lee, K.  Bieback, B. N.  Vo, D. D.  Sampson, B. F.  Kennedy, J. P.  Spatz, A. J.  Engler, Y. S. Cho, Proc. Natl. Acad. Sci. USA 2017, 114, 5647. \n[18]\t J. Li, D. Han, Y. P. Zhao, Sci. Rep. 2014, 4, 3910. \n[19]\t J. Lee, O. Jeon, M. Kong, A. A. Abdeen, J. Shin, H. N. Lee, Y. Bin Lee, W.  Sun, P.  Bandaru, D. S.  Alt, K.  Lee, H.  Kim, S. J.  Lee, S.  Chaterji, S. R. Shin, 2020, 6, eaaz5913. \n[20]\t J.  Blacklock, A.  Vetter, A.  Lankenau, D.  Oupický, H.  Möhwald, Biomaterials 2010, 31, 7167. \n[21]\t I. Hopp, A. Michelmore, L. E. Smith, D. E. Robinson, A. Bachhuka, A. Mierczynska, K. Vasilev, Biomaterials 2013, 34, 5070. \n[22]\t S. K.  Seidlits, Z. Z.  Khaing, R. R.  Petersen, J. D.  Nickels, J. E. Vanscoy, J. B. Shear, C. E. Schmidt, Biomaterials 2010, 31, 3930. \n[23]\t J. R.  Capadona, K.  Shanmuganathan, D. J.  Tyler, S. J.  Rowan, C. Weder, Science 2008, 319, 1370. \n[24]\t Y.  Qiu, E.  Askounis, F.  Guan, Z.  Peng, W.  Xiao, Q.  Pei, ACS Appl. Polym. Mater. 2020, 2, 2008. \n[25]\t J. M. Korde, B. Kandasubramanian, Chem. Eng. J. 2020, 379, 122430. \n[26]\t P. Jungwirth, P. S. Cremer, Nat. Chem. 2014, 6, 261. \n[27]\t S.  Wu, C.  Zhu, Z.  He, H.  Xue, Q.  Fan, Y.  Song, J. S.  Francisco, X. C. Zeng, J. Wang, Nat. Commun. 2017, 8, 15154. \n[28]\t R.  Du, Y.  Hu, R.  Hübner, J. O.  Joswig, X.  Fan, K.  Schneider, A. Eychmüller, Sci. Adv. 2019, 5, eaaw4590. \n[29]\t L. M. Pegram, M. T. Record, J. Phys. Chem. B 2007, 111, 5411. \n[30]\t Y. Zhang, P. S. Cremer, Curr. Opin. Chem. Biol. 2006, 10, 658. \n[31]\t R. S.  Carnegie, C. L. D.  Gibb, B. C.  Gibb, Angew. Chem., Int. Ed. 2014, 53, 11498. \n[32]\t Y.  Yang, X.  Wang, F.  Yang, H.  Shen, D.  Wu, Adv. Mater. 2016, 28, 7178. \n[33]\t Q. He, Y. Huang, S. Wang, Adv. Funct. Mater. 2018, 28, 1705069. \n[34]\t Y. Zhang, S. Furyk, D. E. Bergbreiter, P. S. Cremer, J. Am. Chem. Soc. 2005, 127, 14505. \n[35]\t J. Wei, Q. Wang, Small Methods 2019, 3, 1900558. \n[36]\t M.  Jaspers, A. E.  Rowan, P. H. J.  Kouwer, Adv. Funct. Mater. 2015, 25, 6503. \n[37]\t J. Wang, M. Satoh, Polymer 2009, 50, 3680. \n[38]\t A. M.  Handorf, Y.  Zhou, M. A.  Halanski, W. J.  Li, Organogenesis 2015, 11, 1. \n[39]\t H. Muta, M. Miwa, M. Satoh, Polymer 2001, 42, 6313. \n[40]\t P. Lo Nostro, B. W. Ninham, Chem. Rev. 2012, 112, 2286. \n[41]\t M. T. I. Mredha, Y. Z. Guo, T. Nonoyama, T. Nakajima, T. Kurokawa, J. P. Gong, Adv. Mater. 2018, 30, 1704937. \n[42]\t G.  Qu, Y.  Li, Y.  Yu, Y.  Huang, W.  Zhang, H.  Zhang, Z.  Liu, T.  Kong, Angew. Chem. 2019, 131, 11067. \n[43]\t X. Hu, M. Vatankhah-Varnoosfaderani, J. Zhou, Q. Li, S. S. Sheiko, Adv. Mater. 2015, 27, 6899. \n[44]\t J.  Liu, H.  Zheng, P. S. P.  Poh, H. G.  Machens, A. F.  Schilling, Int. J. Mol. Sci. 2015, 16, 15997. \n[45]\t P. Lin, S. Ma, X. Wang, F. Zhou, Adv. Mater. 2015, 27, 2054. \n[46]\t P. Lin, T. Zhang, X. Wang, B. Yu, F. Zhou, Small 2016, 12, 4386. \n[47]\t Z. Jiang, J. Appl. Crystallogr. 2015, 48, 917. \n[48]\t S.  Lin, X.  Liu, J.  Liu, H.  Yuk, H.-C.  Loh, G. A.  Parada, C.  Settens, J.  Song, A.  Masic, G. H.  McKinley, Sci. Adv. 2019, 5, eaau8528. " + }, + { + "id": "10.1038_s41560-021-00783-z", + "DOI": "10.1038/s41560-021-00783-z", + "DOI Link": "http://dx.doi.org/10.1038/s41560-021-00783-z", + "Relative Dir Path": "mds/10.1038_s41560-021-00783-z", + "Article Title": "Tailoring electrolyte solvation for Li metal batteries cycled at ultra-low temperature", + "Authors": "Holoubek, J; Liu, HD; Wu, ZH; Yin, YJ; Xing, X; Cai, GR; Yu, SC; Zhou, HY; Pascal, TA; Chen, Z; Liu, P", + "Source Title": "NATURE ENERGY", + "Abstract": "Lithium metal batteries hold promise for pushing cell-level energy densities beyond 300 Wh kg(-1) while operating at ultra-low temperatures (below -30 degrees C). Batteries capable of both charging and discharging at these temperature extremes are highly desirable due to their inherent reduction in the need for external warming. Here we demonstrate that the local solvation structure of the electrolyte defines the charge-transfer behaviour at ultra-low temperature, which is crucial for achieving high Li metal Coulombic efficiency and avoiding dendritic growth. These insights were applied to Li metal full-cells, where a high-loading 3.5 mAh cm(-2) sulfurized polyacrylonitrile (SPAN) cathode was paired with a onefold excess Li metal anode. The cell retained 84% and 76% of its room temperature capacity when cycled at -40 and -60 degrees C, respectively, which presented stable performance over 50 cycles. This work provides design criteria for ultra-low-temperature lithium metal battery electrolytes, and represents a defining step for the performance of low-temperature batteries. Charging and discharging Li-metal batteries (LMBs) at low temperatures is problematic due to the sluggish charge-transfer process. Here the authors discuss the roles of solvation structures of Li-ions in the charge-transfer kinetics and design an electrolyte to enable low-temperature operations of LMBs.", + "Times Cited, WoS Core": 546, + "Times Cited, All Databases": 575, + "Publication Year": 2021, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000621706600001", + "Markdown": "# Tailoring electrolyte solvation for Li metal batteries cycled at ultra-low temperature \n\nJohn Holoubek $\\oplus1$ , Haodong Liu $\\textcircled{1}$ 1, Zhaohui Wu $\\textcircled{10}3$ , Yijie Yin2, Xing Xing2, Guorui Cai1, Sicen $\\forall u^{2}$ , Hongyao Zhou $\\oplus1$ , Tod A. Pascal   1,2,3,4 ✉, Zheng Chen $\\textcircled{12}1,2,3,4\\boxtimes$ and Ping Liu   1,2,3,4 ✉ \n\nLithium metal batteries hold promise for pushing cell-level energy densities beyond 300 Wh kg−1 while operating at ultra-low temperatures (below $-30^{\\circ}C)$ . Batteries capable of both charging and discharging at these temperature extremes are highly desirable due to their inherent reduction in the need for external warming. Here we demonstrate that the local solvation structure of the electrolyte defines the charge-transfer behaviour at ultra-low temperature, which is crucial for achieving high Li metal Coulombic efficiency and avoiding dendritic growth. These insights were applied to Li metal full-cells, where a high-loading $3.5\\mathsf{m A h c m}^{-2}$ sulfurized polyacrylonitrile (SPAN) cathode was paired with a onefold excess Li metal anode. The cell retained $84\\%$ and $76\\%$ of its room temperature capacity when cycled at −40 and $\\mathbf{-60^{\\circ}C_{i}}$ respectively, which presented stable performance over 50 cycles. This work provides design criteria for ultra-low-temperature lithium metal battery electrolytes, and represents a defining step for the performance of low-temperature batteries. \n\nhe deployment of rechargeable lithium-ion batteries (LIB) is crucial to the operation of modern portable electronics in extreme environments, where a reduction in cell energy density at ultra-low temperatures $.-30^{\\circ}\\mathrm{C}$ and below) has limited operations in electric vehicles, subsea, military and defence devices, and space exploration1–6. In principle, this can be accomplished by both increasing the baseline energy density of the battery, or mitigating the energy loss at low temperatures via improvement of the charge-transfer kinetics. Intuitively, ideal performance would be produced by a system inherently capable of doing both of these things simultaneously. \n\nTo address the former of these improvements, replacing the commonly applied graphite anode $(372\\mathrm{mAhg^{-1}})$ with Li metal $(3,860\\mathrm{mAhg^{-1}})$ ) has been noted as an effective step to push cell energy densities above $300\\mathrm{Whkg^{-1}}$ (ref. 7). However, Li metal anodes are known for poor cycling stability, where large volume change paired with the high reactivity of metallic Li inevitably yields low Coulombic efficiency (CE), limiting the cyclability of practical Li-metal batteries $(\\mathrm{LMBs})^{8-10}$ . On the other hand, both the capacity retention and operating voltage of LIBs and LMBs are known to suffer severely at temperatures below $-30^{\\circ}\\mathrm{C}$ . This performance decrease has been attributed to a number of factors, including increased impedance from bulk ion transport in the electrolyte and migration of $\\mathrm{Li^{+}}$ through the solid–electrolyte interphase (SEI). Most importantly, $\\mathrm{Li^{+}}$ desolvation is believed to be the dominant impedance contributor, and is correlated to the $\\mathrm{Li^{+}}$ /solvent binding energy at the interphase1,11–13. In general, these resistances have been minimized by employing low-melting-point and/or low-polarizability solvents1–6,13–21, novel salt additives21–23 and, most recently, surface functionalization, where Gao et al. demonstrated remarkable Li reversibility down to $-15^{\\circ}\\mathrm{C}$ (ref. 24). Though much progress has been made, methods for directly improving the desolvation kinetics are largely unknown. \n\nThis work aims to provide such a method, where the solvation structure of $\\mathrm{Li^{+}}$ in the electrolyte was found to be of great importance to the reversibility and plating behaviour of Li metal at low temperatures. These findings were demonstrated through the systematic comparison of a diethyl ether (DEE), and 1,3-dioxolane/1,2-dimethoxyethane-based (DOL/DME) control electrolyte. After experimental and theoretical investigation of their low-temperature Li plating behaviour, the investigated electrolytes were applied in LMB full-cells with practical electrode loadings, employing a SPAN cathode at a loading of $3.5\\operatorname{mAh}\\mathsf{c m}^{-2}$ paired with a limited Li anode (N/P capacity ratio $=1$ ). The cells employing the DEE electrolyte retained $76\\%$ of their capacity when charged and discharged at $-60^{\\circ}\\mathrm{C}$ , compared with only $2.8\\%$ in the DOL/DME control system. This study sets a performance standard for the operation of ultra-low-temperature batteries and reveals key electrolyte design strategies at the molecular level to do so. \n\n# Low-temperature system design \n\nLow-temperature performance loss of batteries can be mitigated by the addition of warming mechanisms. Recently, progress has been made in limiting the impact to total system mass25,26. Battery warming systems, however, consume non-negligible power, which inevitably reduces overall operating efficiency and energy density of low-temperature devices25,26. Hence, it is important to consider the operational conditions of low-temperature batteries during system design, which define the requirements of the warming components. In principle, these operation conditions fall under three schemes as shown in Fig. 1, where scheme 3 is required to reduce or eliminate the need for battery warming during continuous operation. Despite this, the low-temperature LIB and LMB communities have primarily focused on low-temperature discharge after charging under mild conditions (scheme 2)1–6,14,16,18–23. This focus is likely a result of the kinetic demands of scheme 3, particularly for LMBs due to the challenge of maintaining homogenous Li deposition at ultra-low temperatures, which is a notably difficult proposition even under benign temperatures8–10. \n\n![](images/2c80a54b4bab23a7efd2e7b42dad9c670daa68c8ff0d96031c973f1efee4a3a3.jpg) \nFig. 1 | Operational schemes of low-temperature LMBs and the significance of their electrolyte structure for ultra-low Li plating. Scheme 1, thermal management required during both charge and discharge processes. Scheme 2, low-temperature discharge capability with thermal management required during charge. Scheme 3, batteries capable of both charge and discharge at low temperature, free of thermal management. \n\nThough reversible LMBs have recently been demonstrated at $-15^{\\circ}\\mathrm{C}$ (ref. 24), there has been very few demonstrations of full-cell LMBs at temperatures below $-30^{\\circ}\\mathrm{C}$ (refs. 14–16), where only Dong et al. have provided low-temperature charge and discharge cycling15. This earlier work revealed the significant role of ionic solvation in extending the operational potential window while maintaining ionic conductivity at ultra-low temperature. This work also served to provide an LMB capable of cycling at ultra-low temperature, with a reported CE of $89\\%$ at $-40^{\\circ}\\mathrm{C}$ . Thus, design strategies for high Li CE at ultra-low temperatures are yet to be established, and the mechanistic understanding of Li plating dynamics at such temperature extremes are largely unknown. These factors had fundamentally limited the deployment of high-energy rechargeable LMBs in extreme environments. In this work, we observe that enabling LMBs at ultra-low temperatures is heavily dependent on optimization of the electrolyte solvation structure, which was found to define the interfacial ion desolvation mechanics and the corresponding Li deposition morphologies (Fig. 1). This evidence was shown by electrolytes based on DEE and DOL/DME solvents, which provided vastly divergent Li metal performance at $-40^{\\circ}\\mathrm{C}$ and below, owing to their differing solvation structures, without any correspondence to their SEI composition and ionic conductivity at low temperature. \n\n# Ultra-low-temperature Li metal performance \n\nElectrolytes utilizing lithium bis(fluorosulfonyl)imide (LiFSI) are well known to produce some of the highest reported CE values for Li metal anode cycling27–30. Hence, 1 M LiFSI was paired with the solvents of interest (Supplementary Table 1) in order to examine their Li metal performance at ultra-low temperature. 1 M LiFSI \n\nDOL/DME (1:1 volume) was selected as the control electrolyte due to the large volume of work previously conducted with similar formulations in the field, in addition to the low melting points of both DOL and DME (Supplementary Table $1)^{28,31-33}$ . These electrolytes were first applied to $\\mathrm{Li}||\\mathrm{Cu}$ cells, where the Li plating/stripping CE was determined via the method proposed by Adams et al.34 As shown in Fig. 2a, despite providing an efficiency of $98.9\\%$ at room temperature, the CE of the $1\\mathrm{M}$ LiFSI DOL/ DME system was found to sharply decrease to $45.4\\%$ and $27.5\\%$ at $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ , respectively. The 1 M LiFSI DEE system, however, was found to maintain CE values of $98.9\\%$ , $99.0\\%$ and $98.4\\%$ at $23^{\\circ}\\mathrm{C},$ $-40^{\\circ}\\mathrm{C}$ and $\\mathrm{-60^{\\circ}C,}$ respectively (Fig. 2b). Furthermore, it was found that the DEE system yielded smooth Li deposition/stripping profiles with stable voltage outputs, which was not shared by the DOL/DME system, indicative of soft-shorting events. Additional data demonstrating the superiority of the DEE electrolyte in terms of long term Li||Cu cycling efficiency, critical current density at different temperatures, and faster kinetics at low temperatures as measured by Tafel plots can be found in Supplementary Figs. 1–3. \n\nTo confirm the presence of shorting in the DOL/DME system and provide further characterization of the Li metal plated at ultra-low temperatures, high capacity deposition was conducted, where $5\\operatorname{mAh}\\operatorname{cm}^{-2}$ was deposited at $0.5\\mathrm{mAcm}^{-2}$ in both electrolytes at the temperatures of interest (Fig. $^{2\\mathrm{c},\\mathrm{d}},$ ). The cells were then disassembled to observe the morphology of the plated Li. The photographs taken of the Cu electrodes (Fig. 2e) clearly show that the observable amount of deposited Li in 1 M LiFSI DOL/ DME undergoes a severe reduction from $23^{\\circ}\\mathrm{C}$ to $-40^{\\circ}\\mathrm{C}$ where almost no deposits are visible at $-60^{\\circ}\\mathrm{C}$ . We believe this is a clear sign of soft shorting, in which the fast growth of dendritic Li serves to form a pathway for electrons in the circuit, rendering further $\\mathrm{Li^{+}}$ migration and conversion unnecessary to balance the charge in the electrochemical circuit. On the other hand, the DEE system yielded visibly uniform silver Li metal depositions down to $-60^{\\circ}\\mathrm{C}$ (Fig. 2d). The scanning electron microscopy (SEM) images of the DOL/DME system are shown in Fig. 2g, where the image of plated Li at $23^{\\circ}\\mathrm{C}$ reveals dense Li ‘chunks’ up to $10\\upmu\\mathrm{m}$ in size. The same images were also taken for the sparse Li plated at $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ of the red-boxed regions indicated in Fig. 2e, where extremely porous Li was observed at $-40^{\\circ}\\mathrm{C},$ and a single localized dendrite was observed at $-60^{\\circ}\\mathrm{C}$ . However, the Li plated at $23^{\\circ}\\mathrm{C},$ , $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ in 1 M LiFSI DEE shows the same dense, dendrite-free structure, whose chunk size was found to reduce from ${\\sim}10\\upmu\\mathrm{m}$ to ${\\sim}1\\upmu\\mathrm{m}$ from $23^{\\circ}\\mathrm{C}$ to $-60^{\\circ}\\mathrm{C}$ . \n\n![](images/799be3c9e5337bd9ae5781eed6e44faf48fe4c5576e0cf88030482e3650dc5ef.jpg) \nFig. 2 | Li metal performance and characterization at benign and ultra-low temperatures. a,b, Plating/stripping profiles for CE determination in 1 M LiFSI DOL/DME (a) and 1 M LiFSI DEE (b) at $0.5\\mathsf{m A c m^{-2}}$ with SEI formation steps omitted. c,d, Li deposition profiles for characterization in 1 M LiFSI DOL/ DME (c) and 1 M LiFSI DEE (d) at $0.5\\mathsf{m A c m}^{-2}$ . e,f, Optical photographs of Cu current collector after the corresponding deposition experiments in 1 M LiFSI DOL/DME (e) and 1 M LiFSI DEE (f). The significantly reduced amount of visible Li at $-40$ and $-60^{\\circ}\\mathsf C$ in DOL/DME were attributed to shorting. g,h, SEM images of Li plated in 1 M LiFSI DOL/DME $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ and 1 M LiFSI DEE (h). \n\n# Non-correlation between SEI or bulk transport and performance \n\nThough desolvation has been previously attributed to be the dictating step of charge transfer in intercalation-based LIBs, the SEI composition and ionic conductivity was first assessed to determine the presence of any correlations that may relate to the low-temperature performance deviation12. Through the application of X-ray photoelectron spectroscopy (XPS), it was found that there was little deviation between the interfacial chemistry of Li cycled 10 times in the DOL/DME and DEE systems, which were largely $\\mathrm{CO}_{3}$ , C–O, S–O, Li–O and Li–F, and is in close agreement to Li cycled in other DME/LiFSI-based systems28. The chemical similarity of the SEI produced in these two systems corroborates the identical CE at room temperature, and indicates the SEI composition is not likely related to the shorting behaviour found in the DOL/DME based system. (Fig. 3a–c). The SEI composition produced by the DEE system at varying temperatures is also provided in Supplementary Fig. 4. \n\n![](images/0be81b066cda155fa5ede83976898ad3708cf8fae1b9e558e76484fa221a0f75.jpg) \nFig. 3 | Lithium SEI and ionic conductivity study of electrolytes. a–c, $\\mathsf{E x}$ -situ XPS of Li anodes after 10 cycles for $1\\mathsf{m A h c m}^{-2}$ at $0.5\\mathsf{m A c m^{-2}}$ in 1 M LiFSI DOL/DME (top) and 1 M LiFSI DEE (bottom) at room temperature. C 1s (a), O 1s (b) and F 1s (c) spectra with assigned peaks from Gaussian/Lorentzian product peak fitting. d, Measured ionic conductivity of the investigated electrolytes at different temperatures. \n\nAdditionally, the salient deviation of Li metal performance at low temperatures between the DOL/DME and DEE electrolytes cannot be attributed to the reduction of bulk ion transfer in the electrolytes at reduced temperature, where the electrolytes both remain in a liquid state (Supplementary Fig. 5). As shown in Fig. 3d, the measured ionic conductivity of the 1 M LiFSI DOL/DME electrolyte was found to be consistently higher at all measured temperatures, still retaining a remarkable $3.41\\mathrm{mS}\\mathrm{cm}^{-1}$ at $-60^{\\circ}\\mathrm{C},$ compared with only $0.368\\mathrm{mScm^{-1}}$ in 1 M LiFSI DEE. It is noteworthy that there was also a deviation in the $\\mathrm{Li^{+}}$ transference number between the DOL/DME and DEE systems, which were measured to be 0.314 and 0.512, respectively (Supplementary Fig. 6). While this discrepancy is significant, the tenfold difference in ionic conductivities is expected to overwhelm the difference in transference number in the determination of $\\mathrm{Li^{+}}$ transport limitation, as shown in the calculated Sand’s capacity for the DEE and DOL/DME electrolytes in Supplementary Fig. 7 using the model proposed by Bai et al.35. As maintaining high ionic conductivity at low temperatures has been a historical and intuitively rooted focus of the low-temperature electrolyte field, this case study serves to challenge this trend. Hence, understanding the underlying electrolyte features that yield such salient deviation of Li metal performance in these two systems is vital not only to studying these systems, but to elucidate the molecular design requirements for the future of low-temperature LMBs. \n\n# Electrolyte solvation structure and performance impact \n\nGiven the non-correspondence of the ionic conductivity and SEI compositions, it is clear that both the improved CE and morphology provided by the DEE system in stark contrast to the catastrophic failure of the DOL/DME system are a result of charge-transfer reactions at the interphase. As previous studies have indicated that $\\mathrm{Li^{+}}$ desolvation dominates this process at low temperature, we hypothesize that the desolvation behaviour is a direct result of the inherent solvation structure of the electrolytes, which holds the key to describing the performance discrepancy between the DOL/DME and DEE systems11,12. These solvation structures were investigated using both computational and experimental methods. \n\nFirst, classical molecular dynamics (MD) simulations were conducted with the resulting data shown in Fig. 4a–d. Analysis of the RDF data revealed that 1 M LiFSI in DOL/DME displayed a characteristic solvent-separated ion pair (SSIP) structure, in which the $\\mathrm{Li^{+}}$ coordination is dominated by DME molecules, with an average coordination number of 4.6 DME oxygens per ${\\mathrm{Li^{+}}}$ . The SSIP structure is well known to persist in similar glyme $\\mathrm{^{\\prime}L i^{+}}$ electrolytes, and is characterized by solvation shells dominated by interactions between cation and solvent $(\\mathrm{Fig.4e})^{35-38}$ . By contrast, the 1 M LiFSI DEE solution was found to display a characteristic contact-ion pair (CIP) structure, in which the $\\mathrm{Li^{+}}$ solvation shell comprises both FSI− and DEE molecules, with average coordination numbers of 1.8 DEE oxygens and $2.0~\\mathrm{FSI^{-}}$ oxygens per ${\\mathrm{Li^{+}}}$ . This CIP structure is well known to exist in electrolytes with a high salt/solvating solvent ratio, and is balanced between both ion/solvent and cation/anion binding (Fig. $4\\mathrm{g})^{15,27-30,39}$ . The factors that dictate the formation of SSIP and \n\n![](images/3866114f681c5e5628c4a29833dbcc01428ff55dec23d2a8e907c642fd9ff4f9.jpg) \nFig. 4 | Theoretical and experimental analysis of electrolyte structure. a,b, Snapshot (a) and ${\\mathsf{L i}}^{+}$ radial distribution function (b) obtained from MD simulations of 1 M LiFSI DOL/DME. c,d, Snapshot $\\mathbf{\\eta}(\\bullet)$ and ${\\mathsf{L i}}^{+}$ radial distribution function (d) obtained from MD simulations of 1 M LiFSI DEE. e, Most probable solvation structure extracted from MD simulation of 1 M LiFSI DOL/DME. f, Raman spectra obtained from electrolytes of interest and their components. g, Most probable solvation structure extracted from MD simulations of 1 M LiFSI DEE. \n\nCIP structures have yet to be proposed quantitatively, however in thermodynamic terms, solubilities resulting in CIP structures are more entropically driven than the SSIP structures. An expanded discussion of these considerations is provided in Supplementary Note 1. \n\nExperimental evidence of these MD results was obtained from Raman spectra of the electrolytes and their components. These spectra are displayed in Fig. 4f, where the 1 M LiFSI DOL/DME and 1 M LiFSI DEE are compared to the individual LiFSI salt, and the DME, DOL and DEE solvents. It is well known that upon dissolution, the peaks associated with the anion of the $\\mathrm{Li^{+}}$ salt undergoes a significant red shift due to the reduced coordination between cation and anion and increased coordination between cation and solvent27,40. As seen in the LiFSI spectra, the S–N–S bending peak of the $\\mathrm{FSI^{-}}$ at $774\\mathrm{cm}^{-1}$ undergoes a significant shift to $720\\mathrm{cm}^{-1}$ when dissolved in the DOL/DME solvents, indicating a strong dissociation of the $\\mathrm{Li^{+}/F S I^{-}}$ interactions, in agreement with the MD SSIP solvation structure. Conversely, the FSI− S–N–S bending peak in $1\\mathrm{M}$ LiFSI DEE undergoes a much smaller shift, from $774\\mathrm{cm}^{-1}$ in the pure salt to only $748\\mathrm{cm}^{-1}$ in the electrolyte, indicative of much stronger $\\mathrm{Li^{+}/F S I^{-}}$ interactions that is characteristic of a CIP structure. The Fourier transform infra-red spectra (FT-IR) for these systems can also be found in Supplementary Fig. 8, where the $C{\\mathrm{-}}\\mathrm{O}{\\mathrm{-}}\\mathrm{C}$ peak of DEE $(1,130\\mathsf{c m}^{-1})$ was found to undergo a reduced shift compared with that of DME $\\cdot1,106\\mathrm{cm}^{-1},$ ) after the introduction of 1 M LiFSI. A further confirmation of the MD accuracy can be found through the calculated transference numbers, which are close to the experimental values for both systems (Supplementary Table 2). Additionally, it is noteworthy that the CIP solvation structure exhibited by the DEE system may be responsible for the improved oxidative stability shown in Supplementary Fig. 9. \n\nThe balance between cation/solvent and cation/anion binding in each solvation shell is of particular importance when considering $\\mathrm{Li^{+}/L i}$ charge-transfer mechanics at the anode interphase, where these structures can be expected to undergo different dynamics in the presence of an electric field. Specifically, it has been well documented that the significant negative polarization of the anode surface results in the repulsion of anions9,35,41, and $\\mathrm{Li^{+}/a n i o n^{-}}$ binding has frequently been neglected in the desolvation/solvation energy calculations of previous studies16,42. As represented in the proposed mechanisms shown in Fig. 5a,b, the binding energy of the remaining $\\mathrm{Li^{+}}(\\mathrm{solvent})_{n}$ complexes were assessed via quantum chemistry simulations, which yielded binding energies of $-414$ and $-280\\mathrm{kJ}\\mathrm{mol}^{-1}$ for the $\\mathrm{Li^{+}(D M E)}_{2.3}$ and $\\mathrm{Li^{+}(D E E)_{1.8}}$ complexes (average coordination numbers from MD), respectively. It is worthwhile to consider that $\\mathrm{Li^{+}}$ may undergo significant changes in its solvent coordination number at the interface after anion repulsion, however for the purposes of this study it was determined that the binding energy disparity between DME and DEE persists across comparable $\\mathrm{Li^{+}}(\\mathrm{DME})_{n}$ and ${\\mathrm{Li}}^{+}({\\mathrm{DEE}})_{n}$ complexes for $n=1-3$ as shown in Supplementary Fig. 10. Hence, the binding energies provided for $\\mathrm{Li^{+}(D M E)}_{2.3}$ and $\\mathrm{Li^{+}(D E E)_{1.8}}$ complexes are meant as a qualitative indication of their divergent desolvation barriers. As the charge-transfer impedance is known to be dominated by $\\mathrm{Li^{+}}$ desolvation at ultra-low temperatures11,12, we contend that this stark difference in binding energy leads to vastly increased local charge-transfer impedance in the DOL/DME system. Under such severe conditions, it is natural to expect that the Li deposition dynamics would proceed in a tip-driven manner, due to the increased driving force offered by the high-surface-area dendritic Li (Fig. 5a). Such growth would ultimately result in the rampant shorting observed in the 1 M LIFSI DOL/DME system at $-40$ and $\\scriptstyle-60^{\\circ}\\mathrm{C},$ whereas the weakly bound DEE system offers homogenous deposition behaviour at these ultra-low temperatures (Fig. 5b). \n\nFurther confirmation of the advantages provided by the CIP solvation structure was also observed in additional systems by changing the salt or the solvent. When the LiFSI salt was replaced by $\\mathrm{LiClO_{4}}$ in DOL/DME, evidence of a CIP structure was observed with MD, Raman, ionic conductivity and transference number measurements, and an improvement of low-temperature Li metal shorting behaviour was observed at $-20^{\\circ}\\mathrm{C}$ (Supplementary Fig. 12). LiFSI solutions with dipropyl ether (DPE) and dibutyl ether (DBE) are also expected to yield the CIP structure via MD. These electrolytes show similar improvements in performance at $-40^{\\circ}\\mathrm{C}$ with CEs of 97.3 and $98.2\\%$ , respectively (Supplementary Fig. 13). Additionally, the influence of bulk ion transport and interphasial kinetics on Li metal shorting was examined through the variation of LiFSI concentration in DOL/DME (Supplementary Fig. 14), and DEE (Supplementary Fig. 15). The critical short current of the DEE electrolytes was found to be highly dependent on salt concentration and weakly dependent on temperature due to their superior interphasial kinetics and relatively poor mass transport, while the DOL/DME series were found to display the opposite trend (Supplementary Fig. 16). All of these observations further confirm the advantage of the CIP structure in enabling low-temperature performance for Li metal anodes. A more detailed discussion of these experiments is provided in Supplementary Notes 2–4. \n\n![](images/413ffc8cf4f665f6935ed30d636d36babf20ee191ad3a56da6dfd6e1cfde8c66.jpg) \nFig. 5 | Proposed relationship between electrolyte structure and desolvation. a,b, Proposed desolvation mechanisms and corresponding Li+/solven binding energies obtained from quantum chemistry simulations in 1 M LiFSI DOL/DME (a) and 1 M LiFSI DEE (b). \n\n# Full-cell behaviour \n\nIn order to demonstrate the low-temperature performance of the 1 M LiFSI DEE system, a SPAN cathode was selected as the basis of eventual full-cell construction due to its high capacity, low cost and modest voltage, which satisfies the oxidative stability range of most ether electrolytes43–45. The full-cells comprised a SPAN cathode with the high mass loading of $3.5\\mathrm{mAh}\\mathrm{cm}^{-2}$ paired with a $40\\upmu\\mathrm{m}$ Li metal anode, which corresponds to onefold excess capacity (Fig. 6a). Due to the inherent solubility of lithium polysulfides in typical ether solvents, the SPAN cathode is generally discouraged from use44–47. However, as displayed in Fig. 6b, DEE does not display the same solubility for polysulfides as the DOL/DME mixture. This reduced dissolution feature is also apparent in the room-temperature voltage profiles found in Supplementary Fig. 17 and the cycling data of the full-cells (Fig. 6c), where the DEE system retained stable cycling performance in contrast to the low initial CE and immediate capacity fade of the DOL/DME system, which can be attributed to polysulfide shuttling45–47. Such polysulfide dissolution was also observed via ex-situ FT-IR (Supplementary Fig. 18) and XPS (Supplementary Fig. 19) conducted on delithiated SPAN electrodes after 10 cycles in the electrolytes of interest. In both FT-IR and XPS, clear Li–S signals were observed on the electrodes cycled in the DOL/DME system, which is attributed to residual polysulfides and is not found in the DEE cycled electrodes. It is also noteworthy that the formation of polysulfides in the DOL/DME electrolyte during cycling may also interfere with the production of a stable cathode–electrolyte interphase (CEI), as both C 1s signals and Li–F peaks were found to be diminished in the DOL/DME cycled electrode, whereas clear peaks were still visible in the DEE cycled electrodes, particularly for Li–F. \n\nA similar cycling trend was also observed in half cells, where the DEE system retained stable performance at both $0.5\\operatorname{mAh}{\\mathsf{c m}}^{-2}$ and $3.5\\operatorname{mAh}\\mathsf{c m}^{-2}$ cathode loadings, while the DOL/DME system’s poor cycling stability and low CE is clearly evident at $0.5\\mathrm{mAhcm}^{-2}$ loading and significantly exacerbated at $3.5\\mathrm{mAh}\\mathrm{cm}^{-2}$ (Supplementary Fig. 20). These cells were then subjected to cycling at $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ to satisfy the design requirements of operating scheme 3 as previously discussed. The voltage profiles for the DEE and DOL/ DME full-cells cycled at $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ and a $0.1\\mathrm{C}$ rate are shown in Fig. $\\textstyle6\\mathrm{d},\\mathrm{f},$ where it was found that the 1 M LiFSI DOL/DME electrolyte produced diminished output capacities of $236\\mathrm{mAhg^{-1}}$ and $13\\mathrm{mAh}\\mathrm{g}^{-1}$ , which correspond to $38.9\\%$ and $2.8\\%$ of the capacity produced at room temperature, respectively. On the other hand, the $1\\mathrm{M}$ LIFSI DEE system was found to produce improved capacities of $519\\mathrm{mAhg^{-1}}$ and $474\\mathrm{mAhg^{-1}}$ at the same conditions, which corresponds to room-temperature capacity retentions of $84\\%$ and $76\\%$ , respectively. The variance in cell performance was found to be primarily attributable to charge transfer at low temperature, which is shown via electrochemical impedance spectroscopy (EIS) in Supplementary Fig. 21. \n\nThe full-cells based on these two electrolytes were then cycled at $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ in order to provide the wholistic effect of both the Li metal anode and SPAN cathode performance at ultra-low temperatures. As shown in Fig. 6e, the $1\\times$ Li||SPAN full-cell utilizing 1 M LiFSI DOL/DME at $-40^{\\circ}\\mathrm{C}$ was found to undergo severe capacity fade after only two cycles of operation, where the low CE observed starting on the third cycle was taken to be clear evidence of the exhaustion of the onefold excess Li reserve. Furthermore, the same full cell utilizing 1 M LiFSI DOL/DME was found to provide no viable capacity output after 2 cycles at $-60^{\\circ}\\mathrm{C}$ (Fig. 6g). On the other hand, the $\\mathrm{i}\\times\\mathrm{Li}||$ SPAN full-cell was able to provide reliable cycling performance at both $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ (Fig. 6e,g). \n\n![](images/61b7aec43825c7dcea581f4f6d84f439a960bb29fb8cebd03137727f3bbdddf1.jpg) \nFig. 6 | $\\mathfrak{l}\\times$ Li||SPAN full-cell performance at benign and ultra-low temperature. a, Schematic of the demonstrated full cells. b, Dissolution photograph of $0.25\\mathsf{M}\\mathsf{L i}_{2}\\mathsf{S}_{6}$ obtained by stirring stoichiometric amounts of $\\mathsf{L i}_{2}\\mathsf{S}$ and S for $24\\mathsf{h}$ . c, Cycling performance of full cells in each electrolyte at $23^{\\circ}\\mathsf{C}$ and 0.333 C rate. d,e, 0.1 C charge/discharge profiles $(\\blacktriangleleft)$ and cycling performance (e) at $-40^{\\circ}\\mathsf C$ and 0.2 C. f,g, 0.1 C charge/discharge profiles $(\\pmb{\\uparrow})$ and cycling performance $\\mathbf{\\sigma}(\\mathbf{g})$ at $-60^{\\circ}\\mathsf C$ and $_{0.2\\mathsf{C}}$ . \n\n# Comparison with the state of the art \n\nTo put this work in a historical perspective, we calculated the energy density of previously published systems based on the 18,650 cell-level projection model proposed by Betz et al.48 with the details outlined in the experimental section. The fundamental appeal of LMBs is their ability to achieve higher energy densities than those of LIBs, however until very recently there had not been a practical demonstration of a rechargeable LMB exceeding the theoretical limit of a LIB 18,650 cylinder cell $({\\sim}250\\mathrm{Wh}\\mathrm{kg}^{-1})$ at the cell level projected using the above model29. Intuitively, state-of-the-art low-temperature LMBs are behind ambient temperature LMBs due to the inherently more difficult considerations of system design. For this reason, all of the cell demonstrations to date have employed Li metal anodes of excess capacity, often paired with cathodes of low mass loading14–16. Moreover, no LIB or LMB has ever demonstrated both charge and discharge at ultra-low temperatures with the notable exceptions of Cho et al.49 and Dong et al.15 It is also worth noting that while our previous work has demonstrated an LMB system with practical Li loading capable of ultra-low temperature discharge, the correspondingly high energy densities of this system are not expected to be sustained if the charging was carried out at low temperatures, particularly given the cell shorting considerations outlined above50. \n\nIn this regard, this work is a significant step both in diagnosing the challenge of plating Li at ultra-low temperatures and high CE, as well as providing the criteria required to overcome this challenge via solvation chemistry of the electrolyte. In doing so we have provided a route to practical LMB full-cells with cell-level energy densities of 218, 143 and $126\\mathrm{Whkg^{-1}}$ when charged and discharged at 23, $-40$ and $-60^{\\circ}\\mathrm{C}$ (Fig. 7a), respectively. This performance compares favourably with other LMB and LIB energy densities at the same temperatures, the majority of which were charged at room temperature before low-temperature discharge. A quantitative comparison of the practical considerations of low-temperature LMBs can be found in Fig. 7b corresponding to the metrics listed in Supplementary Table 3. \n\nIt is worth noting that depending on the application for a given system, safety should also be considered. To provide a first step in demonstrating the scalability and potential safety risks associated with LMBs at ultra-low temperature, we have assembled a $160\\mathrm{mAh}$ Li||SPAN pouch cell utilizing a further increased cathode loading of $6\\mathrm{mAh}\\ \\mathrm{cm}^{-2}$ (Supplementary Fig. 23a). This pouch cell was able to produce a capacity of $450\\mathrm{mAhg^{-1}}$ when charged and discharged at $-40^{\\circ}\\mathrm{C},$ which compares favourably to the coin-cell performance given the increased loading and overall cell size (Supplementary Fig. 23b). Furthermore, when put under soft-shorting conditions at $-40^{\\circ}\\mathrm{C},$ , the cell temperature was found to change negligibly, indicating that this process may not result in catastrophic outcomes at such operating temperatures (Supplementary Fig. 23c). \n\n![](images/e15db1e3f5dd9e10762b290584ba9a3948fc9c20ee3a0da07694fd1ee9214016.jpg) \nFig. 7 | The historical context of this work. a, Cell-level energy density of selected low-temperature batteries by publication year. Energy densities were calculated based on the 18,650 cylinder cell model proposed by Betz et al.48 using the assumptions outlined in the experimental details. b, Comparison of relevant low-temperature LMBs as quantified by Supplementary Table 3, where loading values are normalized to the highest reported values in literature and the capacity retention values are normalized to $100\\%$ . It is noteworthy that the ostensibly greater energy densities from previous works are not expected to be upheld under low-temperature charging. \n\n# Conclusions \n\nIn summary, we have demonstrated that electrolyte solvation structure is crucial to enable the reversible cycling of Li metal at ultra-low temperatures primarily through the comparative study of 1 M LiFSI DEE and 1 M LiFSI DOL/DME. These insights, as well as the performance metrics provided by the 1 M LiFSI DEE system were leveraged to produce a full-cell with practical electrode loadings that promise to enable LMBs cycled at $23^{\\circ}\\mathrm{C},$ $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}.$ This work represents a significant advancement in the design of low-temperature batteries, both in concept and demonstration, and sets a new performance standard that promises to yield systems that exceed previous energy density limitations while reducing or eliminating the need for battery warming systems due to their universal operating capabilities at ultra-low temperatures. \n\n# Methods \n\nMaterials. The electrolyte materials DOL and DME were purchased from Gotion and used as received. DEE was purchased from Sigma-Aldrich, and LiFSI was obtained from Capchem. The electrolytes were prepared by dissolving predetermined amounts of LiFSI salt into the solvents of interest and stirred. \n\nThe SPAN electrodes were prepared by hand milling polyacrylonitrile (Sigma-Aldrich, $\\ensuremath{M_{\\mathrm{w}}}=150,000)$ and elemental sulfur (Sigma-Aldrich) in a mortar with a mass ratio of 1:4 until a homogenous mixture was obtained. The mixed powders were heated in an argon-filled tube furnace at $450^{\\circ}\\mathrm{C}$ for 6 hours with a ramp rate of $2^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ , then cooled down to room temperature. The SPAN cathode was prepared by mixing the synthesized SPAN powder, Super-P and PVDF (KYNAR 2800) in a ratio of 80:10:10 in $N\\mathrm{.}$ methyl pyrrolidinone solvent, cast on carbon-coated Al foil and dried overnight in a vacuum oven at $60^{\\circ}\\mathrm{C}$ . \n\nFor electrochemical tests CR-2032-type coin cells were assembled with prepared cathodes and anodes separated by a $25\\upmu\\mathrm{m}$ Celgard membrane soaked with $75\\upmu\\mathrm{l}$ of electrolyte. It is noteworthy that the cells were first assembled dry and electrolyte injection was saved for the last step before crimping in order to minimize evaporation of the DEE solvent. For Li metal performance tests, $250\\upmu\\mathrm{m}$ Li metal chips were purchased from Xiamen TOB New Energy Technology and paired with Cu foil for Li||Cu cells, or an identical Li chip in Li||Li cells. The Li||SPAN half cells were assembled with a $250\\upmu\\mathrm{m}$ chip and the prepared SPAN cathodes. Linear scan voltammetry (LSV) stability tests were conducted with $250\\upmu\\mathrm{m}$ Li and a blocking working electrode made of Al foil. $1\\times$ Li||SPAN full-cells were assembled with a $3.5\\mathrm{mAhcm}^{-2}$ SPAN electrode and a thin Li electrode obtained from China Energy Lithium, which was determined via SEM to be $40\\upmu\\mathrm{m}$ thick. Two Celgard separators were employed in the full-cells in an attempt to mitigate shorting during cycling. \n\nCharacterization. The morphology of the deposited Li metal at various temperatures was characterized using an FEI Quanta 250 SEM. The samples were obtained from coin cells and washed with either DEE or DME before analysis. XPS (Kratos Analytical, Kratos AXIS Supra) was carried out using an Al anode source at $15\\mathrm{kV}$ and all the peaks were fitted based on the reference C–C bond at $284.6\\mathrm{eV}$ on both Li metal and SPAN samples. All XPS measurements were collected with a $300\\mathrm{mm}\\times700\\mathrm{mm}$ spot size during acquisition. Survey scans were collected with a $1.0\\mathrm{{eV}}$ step size, and were followed by high-resolution scans with a step size of $0.05\\mathrm{eV}$ for C 1s, O 1s, F 1s and $s_{2p}$ regions. All prepared samples were placed in a heat-sealed bag inside the glovebox before they were transferred to the XPS and SEM. SPAN electrodes before and after 10 cycles in 1 M LiFSI DEE and DOL/ DME were analysed by a Perkin Elmer FT-IR. The polysulfide dissolution tests were performed by immersing stoichiometric ratios of $\\mathrm{Li}_{2}S$ and S corresponding to $0.25\\mathrm{M}\\mathrm{Li}_{2}\\mathrm{S}_{6}$ in DEE and DOL/DME (1:1) solvents and stirring for $24\\mathrm{h}$ . \n\nThe ionic conductivity of the electrolyte was measured by a customized two-electrode cell, in which the two polished 316 stainless-steel electrodes were spaced symmetrically at a set distance. The cell constant is frequently calibrated by using OAKTON 0.447 to $80\\mathrm{m}\\mathrm{S}\\mathrm{cm}^{-1}$ standard conductivity solution. The electrolytic conductivity value was obtained with a floating AC signal at a frequency determined by the phase angle minima given by EIS using the following equation: \n\n$$\n\\sigma=\\frac{L}{A\\times R}\n$$ \n\nwhere $R$ is the resistance, and $A$ and $L$ are the area of and space between the electrodes, respectively. The data points from $40^{\\circ}\\mathrm{C}$ to $-60^{\\circ}\\mathrm{C}$ were measured by LabView Software, which was also used to control an ESPEC BTX-475 temperature chamber to maintain the cell at a set temperature for 30-minute intervals during measurement. \n\nSand’s capacity projections were calculated using the following equation35: \n\n$$\nC_{\\mathrm{Sand}}=\\pi{\\left(\\frac{m_{\\mathrm{Li^{+}}}D_{\\mathrm{FSI^{-}}}+m_{\\mathrm{FSI^{-}}}D_{\\mathrm{Li^{+}}}}{m_{\\mathrm{Li^{+}}}+m_{\\mathrm{FSI^{-}}}}\\right)}\\left(\\frac{C_{\\mathrm{Li^{+}}}^{\\mathrm{'}}e}{2j}{*\\frac{1}{(1-t_{\\mathrm{Li^{+}}})}}\\right)\n$$ \n\nWhere $m$ is the mobility and $D$ is the diffusion coefficient of ionic species, $C_{\\mathrm{Li^{+}}}^{*}$ is the bulk $\\mathrm{Li^{+}}$ concentration, $j$ is the areal current density, $e$ is the elementary Icharge and $t_{\\mathrm{Li^{+}}}$ is the $\\mathrm{Li^{+}}$ transference number. \n\nElectrochemical testing. All electrochemical data provided in this work were produced by CR-2032-type coin cells or heat-sealed pouch cells assembled in an Ar-filled glovebox kept at ${<}0.5\\mathrm{ppm}\\mathrm{O}_{2}$ and ${<0.1\\mathrm{ppmH}_{2}\\mathrm{O}}$ . All low-temperature data points were obtained from these cells inside SolidCold C4-76A and SolidCold C-186A ultra-low chest freezers for $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ tests, respectively. All galvanostatic testing was done on an Arbin LBT-10V5A system and all potentiostatic tests were carried out on a Biologic VSP-300 potentiostat. \n\nFor Li metal CE determinations, the accurate CE test popularized by Adams et al.34 was carried out on $\\mathrm{Li}||\\mathrm{Cu}$ cells. Prior to the test, a condition cycle was carried out on all the cells, where $4\\mathrm{mAhcm}^{-2}$ of Li was deposited onto the Cu foil at $0.5\\mathrm{mAcm}^{-2}$ , and then fully stripped to 1 V to form the SEI before CE testing. During testing $4\\mathrm{mAhcm}^{-2}$ was first deposited followed by 10 cycles of $1\\mathrm{mAhcm}^{-2}$ plating and stripping before finally stripping all Li to 1 V. The CE was calculated by dividing the total stripped capacity by the total plated capacity. The morphological Li studies at various temperatures were conducted on Cu working electrodes plated with $5\\mathrm{mAhcm}^{-2}$ at $0.5\\mathrm{mAcm^{-2}}$ at room temperature as well as $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ after resting for 2 hours to achieve temperature equilibration. \n\nEIS tests of Li||Li cells were carried out on a Biologic VSP-300 potentiostat with a $10\\mathrm{mV}$ perturbation in the frequency range of 1 MHz to $100\\mathrm{mHz}$ . In the case of biased EIS tests, $100\\mathrm{mV}$ was applied to the cell for 2 hours before taking the impedance spectra, and the same bias was applied during the EIS measurement. \n\nThe transference numbers of the electrolytes were determined via a commonly applied potentiostatic polarization technique on a Biologic VSP-300 potentiostat in which $5\\mathrm{mV}$ was applied for $2\\mathrm{h}$ to a Li||Li cell with five Celgard separators to obtain the initial current $I_{0},$ where the cation concentration is uniform and the current corresponds to both the cations and anions, and the steady state current $I_{s s},$ which is only attributed to the cations. EIS was applied before and after the polarization on a in order to obtain the cell impedance, where the transference number was then calculated using the following equation: \n\n$$\nt_{+}=\\frac{I_{\\mathrm{SS}}(\\Delta V-I_{0}R_{0})}{I_{0}(\\Delta V-I_{\\mathrm{SS}}R_{\\mathrm{SS}})}\n$$ \n\nwhere $\\Delta V$ is the applied bias, $R_{0}$ is the initial cell impedance and $R_{\\mathrm{ss}}$ is the steady state cell impedance. The oxidative stability of the electrolytes was determined via LSV of a Li||Al cell at $1\\mathrm{mVs^{-1}}$ . \n\nLi||SPAN cells were assembled and subjected to galvanostatic cycling at room temperature and $-40^{\\circ}\\mathrm{C}$ and $-60^{\\circ}\\mathrm{C}$ inside the respective chest freezers after resting for $2\\mathrm{h}$ to achieve temperature equilibration. Li||SPAN half cells utilized of $250\\upmu\\mathrm{m}$ Li counter electrodes with either $0.5\\mathrm{mAhcm}^{-2}$ or $3.5\\mathrm{mAhcm}^{-2}$ SPAN electrodes. Li||SPAN full cells consisted of $40\\upmu\\mathrm{m}$ Li anodes paired with $3.5\\mathrm{mAhcm^{-2}}$ SPAN cathodes, which corresponds to a onefold Li anode excess $\\mathrm{(N/P=1)}$ for the SPAN after lithiation. \n\nThree-electrode pouch cells consisted of a $12\\mathrm{mm}$ diameter SPAN or $15\\mathrm{mm}$ diameter Li working electrode, a $15\\mathrm{mm}$ diameter Li counter electrode and a Li reference electrode slightly outside the ionic path of the two electrodes sandwiched between two Celgard separators. Tabs were sealed to the pouch bag using an MTI MSK-140 compact heating sealer. The selected electrodes were attached to the tabs in the Ar-filled glovebox and were sealed using a table-top impulse heat sealer after electrolyte injection. The Li||Li||Li pouch cells were subjected to LSV measurements at room temperature and $-40^{\\circ}\\mathrm{C}$ at $1\\mathrm{mVs^{-1}}$ down to $-100\\mathrm{mV}$ versus Li. The SPAN||Li||Li pouch cells were subjected to EIS measurements (same conditions as above) at room temperature and $-40^{\\circ}\\mathrm{C}$ directly after discharging them to $50\\%$ SOC at the selected temperature to avoid encountering nucleation impedance on the anode side. The two-electrode SPAN||Li pouch cell was prepared using a $6\\operatorname{mAh}\\mathsf{c m}^{-2}$ SPAN cathode cut to $4.4\\times5.7\\mathrm{cm}$ using an MTI MSK-180 punch and a copper anode to which Li was rolled onto inside the glovebox. The sealing procedure matched the three-electrode pouch cells. The two-electrode pouch was subject to ${\\sim}100\\mathrm{kPa}$ of pressure using two parallel plates fastened together by screws. Temperature monitoring for the two-electrode pouch was conducted with a HOBO thermocouple attached directly to the outside of the pouch on the cathode side and recorded using the HOBO data logger software. \n\nMD simulations. MD simulations were performed in LAMMPS using the OPLS-AA forcefield51 with the FSI molecules description from Gaouveia et al.52 For electrolyte structure determination, simulation boxes containing 20 LiFSI molecules and 192 DEE, or $96\\mathrm{DME}+143$ DOL molecules corresponding to 1 M LiFSI DEE and 1 M LiFSI DOL/DME (1:1 volume) electrolytes, respectively. Similarly, 1 M $\\mathrm{LiClO_{4}}$ DOL/DME and 1 M LiFSI DPE simulations were carried out in boxes composed of 20 salt molecules and $96\\mathrm{\\DME}+143\\mathrm{\\DOL}$ , and 147 DPE molecules. In all cases, the charges of the $\\mathrm{Li^{+}}$ and FSI− molecules were scaled to the high-frequency dielectric properties of the solvents present in the system according to the method proposed by Park et al.36 For each system, an initial energy minimization at 0 K (energy and force tolerances of $10^{-4^{\\cdot}}$ ) was performed to obtain the ground-state structure. After this, the system was slowly heated from 0 K to room temperature at constant volume over 0.2 ns using a Langevin thermostat, with a damping parameter of $100\\mathrm{ps}$ . The system was then subjected to five cycles of quench-annealing dynamics, where the temperature was slowly cycled between $298\\mathrm{K}$ and $894\\mathrm{K}$ over $0.8\\mathrm{ns}$ in order to eliminate the persistence of any meta-stable states. After annealing, the system was equilibrated in the constant temperature (298 K), constant pressure (1 bar) (NpT ensemble) for 0.5 ns before finally being subjected to $5\\mathrm{ns}$ of constant volume, constant temperature dynamics. Radial distribution functions were obtained using the Visual Molecular Dynamics (VMD) software. Snapshots of the most probable solvation shells were also sampled from the simulation trajectory using VMD. Transference numbers were calculated from the MD trajectories through a mean-squared displacement analysis over the duration of the constant volume dynamics. \n\nQuantum chemistry calculations. Quantum chemistry simulations were performed using the Q-Chem 5.1 quantum chemistry package at the PBE/6– $31\\mathrm{G}\\mathrm{+}(\\mathrm{d},\\mathrm{p})$ level of theory, which has previously been shown to produce accurate binding energies42. Binding energies of the $\\mathrm{Li^{+}(S o l v e n t)}_{x}$ complexes were calculated after geometry optimizations, where the full complexes were optimized with and without $\\mathrm{Li^{+}}$ , representing their separation at infinite distance. The binding energy was calculated as: $\\begin{array}{r}{\\dot{E}_{\\mathrm{B}}=\\dot{E}_{\\mathrm{Li^{+}(s o l v e n t)}_{x}}-\\left(E_{\\mathrm{Li^{+}}}+E_{x(\\mathrm{solvent})}\\right)}\\end{array}$ . The fractional $\\mathrm{Li^{+}(D M E)}_{2.3}$ and $\\mathrm{Li^{+}(D E E)_{1.8}}$ binding energies were calculated via linear interpolation of the $\\mathrm{Li^{+}(D M E)_{3}}$ , $\\mathrm{Li^{+}(D M E)}_{2}$ and $\\mathrm{Li^{+}(D E E)_{1:}}$ , $\\mathrm{Li^{+}(D E E)}_{2}$ complex binding energies, respectively. \n\nCell-level energy density calculations. The cell-level energy densities for this and previous works were calculated via the 18,650 cylinder cell model proposed by Betz et al.48 previously. As the previous LIB works were generally conducted using commercially produced cells, it was assumed that the cathode loading was $2.5\\mathrm{mAhcm^{-2}}$ given the lower loadings generally applied from 2000–2010 with an $\\mathrm{N}/\\mathrm{P}$ cathode/anode capacity ratio of 1.1. For metal-oxide-based cathodes, the active loading was assumed to be $96\\%$ , while polymer-based electrodes were assumed to be $90\\%$ . The volume change during discharge was determined to be $20\\%$ for LIB chemistries and $-20\\%$ for the Li||SPAN full-cell, which are conservative estimates compared with the previous work, and align with the differences between LIBs and $\\mathrm{LMBs^{48}}$ . The macroscopic volume change of the previous LMBs were assumed to be $0\\%$ given the excess anode capacities of the previous LMB works. For all works, it was assumed that a $30\\%$ electrode porosity and an electrolyte loading of $2\\mathrm{gAh}^{-1}$ was achievable and were used in the calculation. For the LMB works, the electrode loadings provided in the original publications were used. \n\n# Data availability \n\nAll relevant data are included in the paper and its Supplementary Information. \n\nReceived: 16 April 2020; Accepted: 21 January 2021; Published online: 25 February 2021 \n\n# References \n\n1.\t Zhang, S. S., Xu, K. & Jow, T. R. The low temperature performance of Li-ion batteries. J. Power Sources 115, 137–140 (2003). \n2.\t Smart, M. C. et al. The use of lithium-ion batteries for JPL’s Mars missions. Electrochim. Acta 268, 27–40 (2018). \n3.\t Gupta, A. & Manthiram, A. Designing advanced lithium-based batteries for low-temperature conditions. Adv. Energy Mater. 10, 2001972 (2020). \n4.\t Huang, C.-K., Sakamoto, J. S., Wolfenstine, J. & Surampudi, S. The limits of low‐temperature performance of Li‐ion cells. J. Electrochem. Soc. 147, 2893–2896 (2000). \n5.\t Plichta, E. J. et al. Development of low temperature Li-ion electrolytes for NASA and DoD applications. J. Power Sources 94, 160–162 (2001). \n6.\t Li, Q. et al. Wide-temperature electrolytes for lithium-ion batteries. ACS Appl. Mater. Interfaces 9, 18826–18835 (2017). \n7.\t Liu, J. et al. Pathways for practical high-energy long-cycling lithium metal batteries. Nat. Energy 4, 180–186 (2019). \n8.\t Xu, W. et al. Lithium metal anodes for rechargeable batteries. Energy Environ. Sci. 7, 513–537 (2014). \n9.\t Li, S. et al. Developing high-performance lithium metal anode in liquid electrolytes: challenges and progress. Adv. Mater. 30, 1706375 (2018). \n10.\t Zhou, H., Yu, S., Liu, H. & Liu, P. Protective coatings for lithium metal anodes: recent progress and future perspectives. J. Power Sources 450, 227632 (2020). \n11.\tXu, K., von Cresce, A. & Lee, U. Differentiating contributions to “ion transfer” barrier from interphasial resistance and $\\mathrm{Li^{+}}$ desolvation at electrolyte/graphite interface. Langmuir 26, 11538–11543 (2010). \n12.\t Li, Q. et al. ${\\mathrm{Li^{+}}}$ -desolvation dictating lithium-ion battery’s low-temperature performances. ACS Appl. Mater. Interfaces 9, 42761–42768 (2017). \n13.\tHoloubek, J. et al. Exploiting mechanistic solvation kinetics for dual-graphite batteries with high power output at extremely low temperature. Angew. Chem. Int. Ed. 58, 18892–18897 (2019). \n14.\tRustomji, C. S. et al. Liquefied gas electrolytes for electrochemical energy storage devices. Science 356, eaal4263 (2017). \n15.\tDong, X. et al. High-energy rechargeable metallic lithium battery at $-70^{\\circ}\\mathrm{C}$ enabled by a cosolvent electrolyte. Angew. Chem. Int. Ed. 58, 5623–5627 (2019). \n16.\tFan, X. et al. All-temperature batteries enabled by fluorinated electrolytes with non-polar solvents. Nat. Energy 4, 882–890 (2019). \n17.\tDong, X., Guo, Z., Guo, Z., Wang, Y. & Xia, Y. Organic batteries operated at $-70^{\\circ}\\mathrm{C}$ . Joule 2, 902–913 (2018). \n18.\tSmart, M. C., Ratnakumar, B. V., Chin, K. B. & Whitcanack, L. D. Lithium-ion electrolytes containing ester cosolvents for improved low temperature performance. J. Electrochem. Soc. 157, A1361–A1374 (2010). \n19.\tSmart, M. C. et al. Gel polymer electrolyte lithium-ion cells with improved low temperature performance. J. Power Sources 165, 535–543 (2007). \n20.\tPlichta, E. J. & Behl, W. K. A low-temperature electrolyte for lithium and lithium-ion batteries. J. Power Sources 88, 192–196 (2000). \n21.\t Smart, M. C., Lucht, B. L., Dalavi, S., Krause, F. C. & Ratnakumar, B. V. The effect of additives upon the performance of $\\scriptstyle{\\mathrm{1CMB/LiNi_{\\boldsymbol{x}}C o_{1-{\\boldsymbol{x}}}O_{2}}}$ Li-ion cells containing methyl butyrate-based wide operating temperature range electrolytes. J. Electrochem. Soc. 159, A739–A751 (2012). \n22.\tZhang, S. S., Xu, K. & Jow, T. R. A new approach toward improved low temperature performance of Li-ion battery. Electrochem. Commun. 4, 928–932 (2002). \n23.\tLiao, B. et al. Designing low impedance interface films simultaneously on anode and cathode for high energy batteries. Adv. Energy Mater. 8, 1800802 (2018). \n24.\tGao, Y. et al. Low-temperature and high-rate-charging lithium metal batteries enabled by an electrochemically active monolayer-regulated interface. Nat. Energy 5, 534–542 (2020). \n25.\tWang, C.-Y. et al. Lithium-ion battery structure that self-heats at low temperatures. Nature 529, 515–518 (2016). \n26.\tJi, Y. & Wang, C. Y. Heating strategies for Li-ion batteries operated from subzero temperatures. Electrochim. Acta 107, 664–674 (2013). \n27.\tChen, S. et al. High-voltage lithium-metal batteries enabled by localized high-concentration electrolytes. Adv. Mater. 30, 1706102 (2018). \n28.\t Qian, J. et al. High rate and stable cycling of lithium metal anode. Nat. Commun. 6, 6362 (2015). \n29.\tNiu, C. et al. High-energy lithium metal pouch cells with limited anode swelling and long stable cycles. Nat. Energy 4, 551–559 (2019). \n30.\tRen, X. et al. Enabling high-voltage lithium-metal batteries under practical conditions. Joule 3, 1662–1676 (2019). \n31.\tZhang, X.-Q. et al. Regulating anions in the solvation sheath of lithium ions for stable lithium metal batteries. ACS Energy Lett. 4, 411–416 (2019). \n32.\tThenuwara, A. C., Shetty, P. P. & McDowell, M. T. Distinct nanoscale interphases and morphology of lithium metal electrodes operating at low temperatures. Nano Lett. 19, 8664–8672 (2019). \n33.\tWang, J. et al. Improving cyclability of Li metal batteries at elevated temperatures and its origin revealed by cryo-electron microscopy. Nat. Energy 4, 664–670 (2019). \n34.\tAdams, B. D., Zheng, J., Ren, X., Xu, W. & Zhang, J.-G. Accurate determination of Coulombic efficiency for lithium metal anodes and lithium metal batteries. Adv. Energy Mater. 8, 1702097 (2018). \n35.\t Bai, P., Li, J., R. Brushett, F. & Bazant, Z. M. Transition of lithium growth mechanisms in liquid electrolytes. Energy Environ. Sci. 9, 3221–3229 (2016). \n36.\tPark, C. et al. Molecular simulations of electrolyte structure and dynamics in lithium–sulfur battery solvents. J. Power Sources 373, 70–78 (2018). \n37.\tCallsen, M., Sodeyama, K., Futera, Z., Tateyama, Y. & Hamada, I. The solvation structure of lithium ions in an ether based electrolyte solution from first-principles molecular dynamics. J. Phys. Chem. B 121, 180–188 (2017). \n38.\tChaban, V. Solvation of lithium ion in dimethoxyethane and propylene carbonate. Chem. Phys. Lett. 631–632, 1–5 (2015). \n39.\tUeno, K. et al. Glyme–lithium salt equimolar molten mixtures: concentrated solutions or solvate ionic liquids? J. Phys. Chem. B 116, 11323–11331 (2012). \n40.\tSuo, L., Zheng, F., Hu, Y.-S. & Chen, L. FT-Raman spectroscopy study of solvent-in-salt electrolytes. Chin. Phys. B 25, 016101 (2016). \n41.\tSand, H. J. S. III On the concentration at the electrodes in a solution, with special reference to the liberation of hydrogen by electrolysis of a mixture of copper sulphate and sulphuric acid. Philos. Mag. 1, 45–79 (1901). \n42.\t Borodin, O. et al. Competitive lithium solvation of linear and cyclic carbonates from quantum chemistry. Phys. Chem. Chem. Phys. 18, 164–175 (2016). \n43.\tWei, S., Ma, L., Hendrickson, K. E., Tu, Z. & Archer, L. A. Metal–sulfur battery cathodes based on PAN–sulfur composites. J. Am. Chem. Soc. 137, 12143–12152 (2015). \n44.\tYang, H., Chen, J., Yang, J. & Wang, J. Prospect of sulfurized pyrolyzed poly(acrylonitrile) (S@pPAN) cathode materials for rechargeable lithium batteries. Angew. Chem. Int. Ed. 59, 7306–7318 (2019). \n45.\tXing, X. et al. Cathode electrolyte interface enabling stable Li–S batteries. Energy Storage Mater. 21, 474–480 (2019). \n46.\tChen, X. et al. Ether-compatible sulfurized polyacrylonitrile cathode with excellent performance enabled by fast kinetics via selenium doping. Nat. Commun. 10, 1021 (2019). \n47.\tZhou, J. et al. A new ether-based electrolyte for lithium sulfur batteries using a S@pPAN cathode. Chem. Commun. 54, 5478–5481 (2018). \n48.\tBetz, J. et al. Theoretical versus practical energy: a plea for more transparency in the energy calculation of different rechargeable battery systems. Adv. Energy Mater. 9, 1803170 (2019). \n49.\tCho, Y.-G., Kim, Y.-S., Sung, D.-G., Seo, M.-S. & Song, H.-K. Nitrile-assistant eutectic electrolytes for cryogenic operation of lithium ion batteries at fast charges and discharges. Energy Environ. Sci. 7, 1737–1743 (2014). \n50.\tHoloubek, J. et al. An all-fluorinated ester electrolyte for stable high-voltage Li metal batteries capable of ultra-low-temperature operation. ACS Energy Lett. 5, 1438–1447 (2020). \n51.\tKaminski, G. A., Friesner, R. A., Tirado-Rives, J. & Jorgensen, W. L. Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J. Phys. Chem. B 105, 6474–6487 (2001). \n52.\tGouveia, A. S. L. et al. Ionic liquids with anions based on fluorosulfonyl derivatives: from asymmetrical substitutions to a consistent force field model. Phys. Chem. Chem. Phys. 19, 29617–29624 (2017). \n53.\tTowns, J. et al. XSEDE: accelerating scientific discovery. Comput. Sci. Eng. 16, 62–74 (2014). \n\n# Acknowledgements \n\nThis work was supported by a NASA Space Technology Graduate Research Opportunity. This work was also partially supported by the Office of Vehicle Technologies of the US Department of Energy through the Advanced Battery Materials Research (BMR) Program (Battery500 Consortium) under contract no. DE-EE0007764 to P.L. This work was also partially supported by an Early Career Faculty grant from NASA’s Space Technology Research Grants Program (ECF 80NSSC18K1512) to Z.C. Part of the work used the UCSD-MTI Battery Fabrication Facility and the UCSD-Arbin Battery Testing Facility. Electron microscopic characterization was performed at the San Diego Nanotechnology Infrastructure (SDNI) of UCSD, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the National Science Foundation (grant ECCS-1542148). Computational support for this work was provided by the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility operated under contract no. DE-AC02-05CH11231. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE)53 on the Comet supercomputer at the San Diego \n\nSupercomputing Center, which is supported by National Science Foundation grant no. \nACI-1548562. \n\n# Author contributions \n\nJ.H. conceived the original idea. P.L. and Z.C. directed the project. J.H., H.L. and Z.W. \ncarried out the experiments. Z.W., X.X., S.Y., G.C. and Y.Y. assisted with characterization. \nT.A.P. directed the computational experiments. J.H., H.L., Z.C. and P.L. wrote the paper. \nAll authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41560-021-00783-z. \n\nCorrespondence and requests for materials should be addressed to T.A.P., Z.C. or P.L. \n\nPeer review information Nature Energy thanks Kevin Leung and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 " + }, + { + "id": "10.1038_s41467-021-26947-9", + "DOI": "10.1038/s41467-021-26947-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-26947-9", + "Relative Dir Path": "mds/10.1038_s41467-021-26947-9", + "Article Title": "Horizontally arranged zinc platelet electrodeposits modulated by fluorinated covalent organic framework film for high-rate and durable aqueous zinc ion batteries", + "Authors": "Zhao, ZD; Wang, R; Peng, CX; Chen, WJ; Wu, TQ; Hu, B; Weng, WJ; Yao, Y; Zeng, JX; Chen, ZH; Liu, PY; Liu, YC; Li, GS; Guo, J; Lu, HB; Guo, ZP", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Rechargeable aqueous zinc-ion batteries (RZIBs) provide a promising complementarity to the existing lithium-ion batteries due to their low cost, non-toxicity and intrinsic safety. However, Zn anodes suffer from zinc dendrite growth and electrolyte corrosion, resulting in poor reversibility. Here, we develop an ultrathin, fluorinated two-dimensional porous covalent organic framework (FCOF) film as a protective layer on the Zn surface. The strong interaction between fluorine (F) in FCOF and Zn reduces the surface energy of the Zn (002) crystal plane, enabling the preferred growth of (002) planes during the electrodeposition process. As a result, Zn deposits show horizontally arranged platelet morphology with (002) orientations preferred. Furthermore, F-containing nullochannels facilitate ion transport and prevent electrolyte penetration for improving corrosion resistance. The FCOF@Zn symmetric cells achieve stability for over 750 h at an ultrahigh current density of 40 mA cm(-2). The high-areal-capacity full cells demonstrate hundreds of cycles under high Zn utilization conditions. Rechargeable aqueous zinc-ion batteries are promising but the zinc anode suffers from dendrite growth and electrolyte corrosion. Here, the authors develop a fluorinated covalent organic framework film as a protective layer for aqueous zinc anode battery.", + "Times Cited, WoS Core": 485, + "Times Cited, All Databases": 495, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000719546000021", + "Markdown": "# Horizontally arranged zinc platelet electrodeposits modulated by fluorinated covalent organic framework film for high-rate and durable aqueous zinc ion batteries \n\nZedong Zhao1,6, Rong Wang1,6, Chengxin Peng2,3✉, Wuji Chen1, Tianqi Wu1, Bo Hu1, Weijun Weng 1, Ying Yao1, Jiaxi Zeng1, Zhihong Chen2, Peiying Liu1, Yicheng Liu1, Guisheng Li2, Jia Guo1✉, Hongbin Lu 1,4✉ & Zaiping Guo5✉ \n\nRechargeable aqueous zinc-ion batteries (RZIBs) provide a promising complementarity to the existing lithium-ion batteries due to their low cost, non-toxicity and intrinsic safety. However, Zn anodes suffer from zinc dendrite growth and electrolyte corrosion, resulting in poor reversibility. Here, we develop an ultrathin, fluorinated two-dimensional porous covalent organic framework (FCOF) film as a protective layer on the $Z n$ surface. The strong interaction between fluorine (F) in FCOF and Zn reduces the surface energy of the Zn (002) crystal plane, enabling the preferred growth of (002) planes during the electrodeposition process. As a result, Zn deposits show horizontally arranged platelet morphology with (002) orientations preferred. Furthermore, F-containing nanochannels facilitate ion transport and prevent electrolyte penetration for improving corrosion resistance. The ${\\mathsf{F C O F@Z r}}$ symmetric cells achieve stability for over $750\\mathsf{h}$ at an ultrahigh current density of $40\\mathsf{m A}\\mathsf{c m}^{-2}$ . The highareal-capacity full cells demonstrate hundreds of cycles under high Zn utilization conditions. \n\nZ $(Z\\boldsymbol{\\mathrm{n}})$ -sbtasoewdinagquteoouZsn roereatitcralctcianpgatcriteymendous intere ’s high the $(820\\mathrm{~mAh~g^{-1})}$ $(-0.\\dot{7}62\\mathrm{V}$ dard hydrogen electrodes), high natural abundance, low cost, and intrinsic non-flammable advantage over organic-based lithium batteries1–3. Unfortunately, previous $Z\\mathrm{n}$ anodes showed poor reversibility in aqueous electrolytes1,4,5. Issues including Zn dendrite formation, continuous parasitic hydrogen evolution reaction (HER), and irreversible by-products, resulting in low Coulombic efficiency (CE), and shortened battery $\\mathrm{life}^{6-9}$ . To stabilize the $Z\\mathrm{n}$ anode, various strategies including electrolyte optimization (additives10 and water-in-salt1/gel electrolytes11), surface coating materials (e.g., metal-organic frameworks12, polyamide8, and $\\mathrm{Zn\\bar{O}}$ networks6) and Zn bulk structure engineering (e.g., CNT frameworks13 or zinc–aluminum alloy14) have been proposed to achieve higher performance Zn anodes. However, there are still some unsolved issues with these strategies, which restricts them to subdued performance levels in Zn batteries. For instance, manipulating previous electrolyte compositions leads to an increase in overall costs15, sacrifices rate performance of the batteries owing to their slow ionic conductivity and the HER is only lowered, not eliminated2. Interfacial modification layers are effective for suppressing $\\mathrm{HER}^{8,16}$ , however, the huge volume change during repeated Zn plating/stripping can damage protective layers, even peeling them completely off the Zn matrix17. Employing conductive 3D hosts could help to realize high-rate Zn deposition13,18, but adds additional porosity and weight, thereby reducing the volumetric/gravimetric energy density of the batteries. Therefore, developing alternative techniques to achieve dendrite-free $Z\\mathrm{n}$ anodes while maintaining fast Zn deposition is urgently needed. \n\nThe crystallinity and morphology of Zn electrodeposits dominates the reversibility of Zn plating/stripping5,19,20, yet the linkage has often not been considered. Modulating irregularly-shaped Zn to planar Zn electrodeposits is desirable for high reversibility of Zn anodes5. The electrodeposition processes of $Z\\mathrm{n},$ which involve crystallization, exhibit a direct correlation to the morphology of deposits20. Upon plating, the influences of external factors often promote the preferred orientation of Zn grains along a specific crystal plane, thus leading to a specific morphological “texture“21–23. The morphology and texture of $Z\\mathrm{n}$ deposits have been proved to be closely related to additives22,24–26, initial substrate composition and texture5,27,28, and applied external fields19,29. Organic molecules and additives can adsorb on a Zn surface, guiding the Zn deposits to show specific preferred orientation of crystal planes $^{25,26,30}$ . For example, the polyethylene-glycolin electrolytes25 make the Zn deposits show a preferred orientation exposure of (002) and (103) planes, which mitigates dendrite formation and reduces the later corrosion rates. Substrate such as stainless steel modified with an aligned graphene layer5, shows good lattice matching with Zn, which induces epitaxial deposition of Zn along the (002) planes, achieving ultra-long cycling life. Recently, fields generated by rotating disc electrodes19 are reported to promote the crystallographic reorientation of $Z\\mathrm{n}$ to be grow parallel to the substrate, and the reversibility of $Z\\mathrm{n}$ deposition/ stripping is greatly increased. Therefore, correlating the crystallography and morphology to deeply understand and regulate the electrodeposition behavior of $Z\\mathrm{n}$ is of great significance for developing long-life $Z\\mathrm{n}$ batteries. However, there is an obvious lacks of fundamental elucidation of the mechanism controlling planar $Z\\mathrm{n}$ deposition. Furthermore, the surface stability of inorganic crystals has long been thought to be dominated by their surface energy31–33. From the perspective of crystal growth, controlling the surface energy of Zn crystal planes offers exciting opportunities to realize planar zinc deposition. \n\nHere, by using two-dimensional (2D) covalent organic frameworks (COF) as a multi-functional platform (Fig. 1a), we develop a mechanically strong, ultra-thin, porous, and fluorinated COF (FCOF) film as a protective layer on $Z\\mathrm{n}$ anode surfaces $({\\mathrm{FCOF@Zn}})$ . Compared with alterative protective layer materials, FCOF film is advantageous. This is because: i) From the perspective of regulation of the surface energy of Zn crystal, it introduces numerous F atoms into the FCOF film. The electronegative F atoms exhibit strong interaction with the underlying Zn atoms, leading to a lower surface energy for Zn (002) planes compared with that of conventional Zn (101) planes. Consequently, Zn deposits show platelet morphology with preferred orientation along the (002) plane, with the platelets arranged parallel to each other to give a planar Zn deposition morphology; ii) The FCOF film is continuous and dense, and has strong adhesion with $Z\\mathrm{n}$ , that remains intact on the surface of $Z\\mathrm{n}$ to provide durable protection; iii) The 2D stacking and covalent bonding makes the film excellent mechanical properties. The robust film possesses an elastic modulus ${>}30\\mathrm{GPa}$ , which buffers volume expansion of $Z\\mathrm{n}$ during cycling; and, iv) The FCOF film is ultra-light in mass, thin $(100\\mathrm{nm})$ and is precisely regulated on a nanometer-scale without impacting mass or volume energy density of $Z\\mathrm{n}$ anodes. As a result, the $\\operatorname{FCOF@Zn}$ anodes show prolonged cycle life and better reversibility in a large current density range $(5{-}80\\mathrm{mA}\\mathrm{cm}^{-2}),$ . The assembled full cells paired with manganese dioxide $\\mathrm{(MnO}_{2}^{\\cdot}$ ) cathodes show a stable cycle life for over 250 cycles under practical condition of lean electrolyte, high areal capacity cathode and limited $Z\\mathrm{n}$ excess. \n\n# Results \n\nSynthesis and characterization of the FCOF film. The iminelinked FCOF thin films are prepared through a solvothermal procedure (Fig. 2a). In a typical process, two monomers (2, 3, 5, 6-tetrafluoroterephthaldehyde (TFTA) and 1, 3, 5-tris (4-aminophenyl) benzene (TAPB)), are dissolved in a dioxane/mesitylene (D/M) mixture and condensed in a solvothermal tube, using acetic acid as the catalyst. As a new COF film material, the production cost of FCOF is comparable to those for reported microporous metal-organic frameworks (MOFs) or COF material (Supplementary Table 1). Optimization of the synthesis pathways and cost of COFs can be used to reduce overall cost for practical commercialization (details in Supplementary Table 1). To obtain a highly crystalline and continuous FCOF film, reaction conditions i.e., the proportion of solvent mixture, the concentration of catalyst and the reaction time needs to be controlled (Supplementary Figs. 1–4). When the ratio of D:M solvent in the mixtures is optimized to 9:1 (v/v) with $1.5\\mathrm{M}$ acetic acid catalyst, continuous bright orange FCOF films without any insoluble COF particulates are uniformly attached to the tube inner wall, indicating the FCOF films is successfully achieved (Supplementary Fig. 1). After soaking in pure water overnight, the free-standing FCOF films detach from the tube wall due to surface tension (Supplementary Fig. 5). The growth mechanism of FCOF film during solvothermal processes is mainly attributed to the fusion of numerous nanospheres that are formed during a co-condensation reaction (Supplementary Fig. 2), as revealed by the time-dependent morphology evolution (Supplementary Fig. 4). In addition, such uniform FCOF films can grow on various substrates such as copper $\\mathrm{(Cu)}$ , silicon, stainless steel foil/ grids, nickel, and titanium foils by placing the targeted substrates in the reaction solutions, as shown in Supplementary Fig. 6. This is beneficial for structural and property characterization after being transferred to various substrates during subsequent post-processing. \n\nThe crystal structure of the FCOF film is identified by twodimensional wide-angle X-ray scattering (2D WAXS) measurement (Fig. 2b). From the integrated WAXS curves, the peaks at $q=0.20$ , 0.35, 0.40, $0.53\\mathrm{A}^{-1}$ correspond to the planes (100), (110), (200) and (210), respectively, consistent with a previous report34, confirming the high degree of crystallinity of the asprepared film. Findings from theoretical simulation and Pawley refinement confirm that the 2D stacked structure in FCOF is an AA stacking mode (detailed analysis in Supplementary Fig. 7). High-resolution transmission electron microscopy (HRTEM) images clearly show the lattice fringes of the FCOF film at a spacing of ${\\sim}0.34\\ \\mathrm{nm}$ (Fig. 2c), which represents the $\\pi-\\pi$ stacking distance. Field emission scanning electron microscopy (FESEM) images show a smooth and defect-free film suspended on a copper grid (Fig. 2d), and the folds at the edges also reflect the flexibility of the film to a certain extent (Fig. 2e). Brunauer–Emmett–Teller (BET) measurement indicates the surface area of the film is as high as $723~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ , and the main pore size distribution is $2-3{\\mathrm{nm}}$ in diameter (Fig. 2f), which is well consistent with the WAXS result. The chemical structure of the FCOF film is further confirmed. The emerging peak at $1614~\\mathrm{{cm}^{-1}}$ in FTIR spectra (Fig. 2h) is assigned to the newly formed $\\mathrm{C}{=}\\mathrm{N}$ imine stretch vibrations. The peak intensity at $1705~\\mathrm{{cm}^{-1}}$ assigned to $\\scriptstyle{\\mathrm{C=O}}$ stretching weakens in FCOF film, indicating the consumption of the aldehyde groups of TFTA monomers34. High-resolution X-ray photoelectron spectroscopy (XPS) of the N1s spectra (Fig. 2g) shows that the weak peak at $399.89\\mathrm{eV}$ arises from the N–H bonds35, revealing the small amount of residues of the amino groups34, consistent with the FTIR result (N–H peak at ${\\sim}3400\\mathrm{cm}^{-1}$ ). The high intensity of the peak at $398.96\\mathrm{eV}$ in the N1s spectra (Fig. 2g) further confirm the formation of $\\mathrm{C}{=}\\mathrm{N}$ (imine) bonds in the FCOF $\\mathrm{{flm}}^{35}$ . \n\n![](images/d7aa338d1df0d90f89651f102145c8512a4e077cf29292bf83eada00d4dc9771.jpg) \nFig. 1 The FCOF structure design and stabilizing mechanism elucidation. a The physicochemical structure of the FCOF film, showing suppression of dendrites. b Mechanism comparison of the deposition processes for $F C O F@Z n$ and bare Zn surfaces. \n\nThe F atoms are the crucial elements within the FCOF films for achieving high-performance Zn anodes. The element mapping obtained from energy dispersive X-ray spectroscopy (EDX) indicates that F is evenly distributed in the film (Supplementary Fig. 8). The F content is estimated to be 8.25 atomic $\\%_{:}$ in according to the XPS result (Supplementary Fig. 9). In addition, the thickness of the film is adjustable by means of controlling the concentration of monomers. As determined by AFM analysis, the FCOF films have thicknesses of ${\\sim}100,~{\\sim}300$ , and ${\\sim}500\\mathrm{nm}$ (Supplementary Fig. 10). It is worth mentioning that due to the formation mechanism of the films, a minimum limitation of thickness exists for preparing the FCOF film (Supplementary Fig. 11). To suppress the side reactions and retard the Zn dendrites, a reliable film with a thickness of about $100\\mathrm{nm}$ is optimal to conduct the subsequent characterization. The $\\operatorname{FCOF@Zn}$ anode is fabricated via a pulling method in acetone solvent using Zn foil as substrate. After drying, the FCOF film tightly adheres the surface of the Zn foil and does not detach even under rolling, bending or unfolding of the $Z\\mathrm{n}$ (Fig. 2i, j). In addition, as determined by nano-indentation measurements (Fig. 2k), the high quality two-dimensional FCOF crystalline films show a remarkable elastic modulus exceeding $30\\mathrm{GPa}$ and an average hardness of over $1.2\\mathrm{GPa}$ , which is an order of magnitude higher than a recently reported $\\mathrm{TiO}_{2}$ and polyvinylidene difluoride (PVDF) hybrid matrix $(2.67\\mathrm{GPa})^{36}$ . The good mechanical strength is greatly beneficial to buffer volume expansion and retard dendrite propagation during the dissolution/ deposition of $Z\\mathrm{n}$ anodes. \n\n![](images/a021167030a123ae7c9e50340f839964add825b0ab06e49dfe210abe40e3f275.jpg) \nFig. 2 The morphology and structure characterization of the FCOF film. a Synthesis procedure of the FCOF film. b WAXS result and its integrated curve. c HRTEM image and measurement of $d$ -spacing. d, e FESEM images of the FCOF film. f BET measurement and pore size distribution. $\\pmb{\\mathsf{g}}\\times\\mathsf{P S}$ result for N1s in the FCOF film. i, j Pictures of typical FCOF $@Z_{n}$ and typical bare Zn. h FTIR result for the monomers and the FCOF film. k Nano-indentation measurement result for FCOF film. \n\nIon de-solvation promotion and transport acceleration in the FCOF film. Good $\\mathsf{\\bar{Z}n}^{2+}$ conductivity through a protective layer is highly desired for $Z\\mathrm{n}$ anodes. To experimentally determine the ion transport behavior of the FCOF films, the ionic conduction is calculated based on electrochemical impedance spectroscopy (EIS) results (Supplementary Figs. 12 and 13). As is shown in \n\nSupplementary Fig. 12, the FCOF films exhibits a greater $Z\\mathrm{n}^{2+}$ transference number ZTN of 0.75 compared with conventional glass fiber separators of 0.22. The ion conductivity of the ${\\sim}100\\mathrm{nm}$ FCOF film coated on glass fiber separator is computed to be $24.19\\mathrm{mScm^{-1}}$ , that is, 1.7 times greater than that for bare glass fiber separator of $14.12\\mathrm{mS}\\mathrm{cm}^{-\\widetilde{1}}$ . These results confirm that FCOF accelerates $Z\\mathrm{n}^{2+}$ transport and therefore boosts ionic conductivity37,38. According to the equivalent circuit fitting results (Supplementary Fig. 13), Zn anodes coated by the FCOF films with different thicknesses reveal lower charge transfer resistance $(R_{\\mathrm{ct}})$ than bare $Z\\mathrm{n}$ . In particular, the $R_{\\mathrm{{ct}}}$ of $Z\\mathrm{n}$ anodes coated by the $100\\mathrm{nm}$ thick FCOF film is lowest $(90~\\Omega)$ , about half that of bare Zn $\\left(180\\Omega\\right)$ . Apparently, the $Z\\mathrm{n}^{2+}$ transport is increased by the fluorinated 1D nanochannels. This is mainly due to the $\\mathrm{~F~}$ atoms surrounded within the nanopores that endow the film a strong hydrophobic effect. When hydrated $Z\\mathrm{n}^{2+}$ transport through fluorinated nanochannels is driven by electric field force, water molecules coordinated with $Z\\mathrm{n}^{2+}$ will be repelled because of the strong hydrophobicity of $\\mathrm{~F~}$ element in the FCOF film covering the Zn metal. Consequently, a large portion of water molecules is retarded and not able to penetrate the fluorinated nanochannels. The de-solvation effect of $Z\\mathrm{n}^{2+}$ is therefore significantly promoted by F element. To confirm the ability of FCOF film to promote de-solvation, a study of the activation energy $\\left(E_{\\mathrm{a}}\\right)$ is made, $E_{\\mathrm{a}}$ represents the de-solvation barrier to $Z\\mathrm{n}^{2+}$ transport. A computation for $E_{\\mathrm{a}}$ based on temperature-dependent EIS is performed (Supplementary Fig. 14). To determine $E_{\\mathrm{a}},$ temperature-dependent EIS curves for $\\operatorname{FCOF@Zn}$ and bare $Z\\mathrm{n}$ anodes are determined. The EIS are fitted with an equivalent circuit, and $R_{\\mathrm{{ct}}}$ at different temperatures is obtained. It is found that $R_{\\mathrm{{ct}}}$ for $\\operatorname{FCOF@Zn}$ is several orders of magnitude lower than that for bare $Z\\mathrm{n}$ when evolving at different temperatures (Supplementary Fig. 14a, $c$ ). According to the equation: \n\n$$\n\\ln(R_{\\mathrm{ct}}^{-1})=\\ln A-E_{\\mathrm{a}}/\\mathrm{RT},\n$$ \n\nwhere $R_{\\mathrm{ct}},A,E_{\\mathrm{a}},R,$ and $T$ represent the charge transfer resistance, pre-exponential factor, activation energy, molar gas constant, and absolute temperature. The computed activation energy $\\left(E_{\\mathrm{a}}\\right)$ for $\\operatorname{FCOF@Zn}$ is $14.5\\mathrm{kJ}\\mathrm{mol}^{-1}$ , whilst that for bare $Z\\mathrm{n}$ is significantly greater at $32.2\\mathrm{kJ}\\mathrm{mol}^{-1}$ . The lower activation energy for $\\operatorname{FCOF@Zn}$ over bare $Z\\mathrm{n}$ strongly suggests that the FCOF layer ensures fast de-solvation of $\\dot{Z}\\mathrm{n}^{2+}$ and facilitates fast iontransference. Studies have demonstrated that COFs are an excellent ionic conductor38,39. The inherent ordered structures provide regular ionic coordination sites to facilitate ions to hop along the 1D aligned nanochannels. This highly boosts ionic conductivity. To study $Z\\mathrm{n}^{2+}$ transport in FCOF, the transport sites for $\\scriptstyle{\\mathrm{Zn}}^{2+}$ on the COF skeleton are determined theoretically. The charge density distribution of the chemical structural unit in FCOF is computed. As is shown in Supplementary Fig. 15a, the significant number of $\\mathrm{~F~}$ atoms within FCOF film (four (4) F element per unit) exhibit a strong local, negative charge concentration distribution. The pore channels of COF with strong negative charge coordination sites have been confirmed to boost fast ion movement38,39. Because of electrostatic attraction, the positively charged $Z\\mathrm{n}^{2+}$ hops around the $\\mathrm{~F~}{}$ atom sites and transports along the 1D aligned channels during charge/discharge (Supplementary Fig. 15b, c). This shortens the transportation pathways, and $\\mathrm{Zn}^{2\\mp}$ transport is boosted. \n\nCorrosion resistance property of the FCOF film. The corrosion resistance of the FCOF film on the $Z\\mathrm{n}$ surface is investigated in aqueous electrolyte (2M $\\mathrm{ZnSO_{4}},$ . The impedance of the $\\operatorname{FCOF@Zn}$ symmetric cells increases from 180 to $600~\\Omega$ within $^{8\\mathrm{h}}$ (h) after cell assembly (Supplementary Fig. 16a). For bare $Z\\mathrm{n}$ symmetric cells, on the contrary, the impedance increases dramatically from 200 to over $10,000\\ \\Omega$ after $^{8\\mathrm{h}}$ (Supplementary Fig. 16b). The increase in impedance implies that the continuous corrosion of $Z\\mathrm{n}$ by the electrolyte results in large amounts of byproducts deposited on the surface. Time-dependent XRD patterns (Supplementary Fig. 16c) show a peak at around $8^{\\circ}$ appears, corresponding to the by-product species $\\mathrm{Zn_{4}S O_{4}(O H)}_{6}{\\cdot}5\\mathrm{H}_{2}\\mathrm{O}$ (JCPDS# 39-0688)11. When plain $Z\\mathrm{n}$ anodes are immersed in aqueous electrolyte for $48\\mathrm{h}$ , the peak intensity of by-products increases sharply. Much less irreversible by-product is accumulated on the surface of $\\operatorname{FCOF@Zn}$ anodes during the same time duration. To evaluate corrosion resistance of the FCOF film, potentiodynamic and open-circuit, tests are conducted using a home-made test apparatus (Supplementary Figs. 17 and 18). The time-dependent potentiodynamic curves for $\\operatorname{FCOF@Zn}$ and bare $Z\\mathrm{n}$ in $2\\mathrm{\\:M\\:ZnSO_{4}^{-}}$ electrolyte are shown in Supplementary Fig. 17. Following soaking in electrolyte for $2\\mathrm{h}$ , the $E_{\\mathrm{corr}}$ for $\\operatorname{FCOF@Zn}$ is $-1.057\\mathrm{V}$ , a value slightly greater than that for bare Zn of $-1.063\\mathrm{V}$ . Additionally, the corrosion rate is proportional to computed corrosion current. The corrosion current $(I_{\\mathrm{corr}})$ decreased from $2.5\\ \\times\\ 10^{-3}\\mathrm{Acm}^{-2}$ for bare $Z\\mathrm{n}$ to $4.1~\\times$ $10^{-5}\\mathrm{A}\\mathrm{cm}^{-2}$ for $\\operatorname{FCOF@Zn}$ . Despite 8 days of electrolyte immersion, $\\operatorname{FCOF@Zn}$ continued to exhibit a greater corrosion potential $(E_{\\mathrm{corr}})$ of $-1.063\\mathrm{V}$ and a lower corrosion current $(I_{\\mathrm{corr}})$ of $4.8\\times10^{-4}$ A $\\mathrm{cm}^{-2}$ , compared with bare $Z\\mathrm{n}$ of, respectively, $-1.068\\mathrm{V}$ and $1.2\\times10^{-3}\\mathrm{~\\AA~}\\mathrm{cm}^{-}$ −2. The open circuit potential (OCP) for both electrodes is shown in Supplementary Fig. 18. The corrosion potential for bare $Z\\mathrm{n}$ in 2 M $\\mathrm{ZnSO_{4}}$ remained stable at $\\sim-1.042\\mathrm{V}$ vs. SCE, whilst that for $\\operatorname{FCOF@Zn}$ is $\\sim-1.020\\mathrm{V}$ in the initial stage, and remained greater at $-1.032\\mathrm{V}$ than that for bare $Z\\mathrm{n}$ of $-1.041\\mathrm{V}$ , despite $5000s\\mathrm{,}$ . It is reliably concluded therefore that the corrosion resistance for $Z\\mathrm{n}$ anode is significantly improved by FCOF film surface protection. \n\nHorizontal parallel Zn platelet deposition enabled by the FCOF film. In addition to the fast ion conduction and suppression of side reactions features, the morphology and texture of $Z\\mathrm{n}$ deposits has been proven to have large impact on the cycling life of $Z\\mathrm{n}$ batteries. Attaining an even planar deposition can ensure the batteries running for a prolonged time without short circuiting. An electronic resistance property is important in $Z\\mathrm{n}$ deposition underneath the FCOF film. From the polarization I–V curve, the $100\\mathrm{nm}$ FCOF film exhibits an electronic resistance of $3\\times10^{4}\\Omega$ cm (Supplementary Fig. 29d). This is a value has been to be sufficient to enable Li deposition underneath the protective layer40. It is concluded the FCOF film therefore provides good electronic insulation on the surface of $Z\\mathrm{n}$ , and establishes the needed potential gradient across the film to drive $Z\\mathrm{n}^{2+}$ diffusion through the film. Additionally, the F-containing channels inside the film provide a rapid de-solvation environment and 1D ion diffusion pathways (Supplementary Fig. 19) that allow $Z\\mathrm{n}^{2+}$ to pass through the film and readily deposit on the $Z\\mathrm{n}$ surface. To investigate the deposition morphology of $Z\\mathrm{n}$ underneath the FCOF film, the $\\mathrm{Ti}/\\mathrm{\\bar{Z}n}$ or $\\mathrm{FCOF}@\\mathrm{Ti}$ cells are employed. As shown in Fig. 3a, b, the Zn deposits underneath the FCOF film exhibits platelet morphology and the platelets are stacked horizontally in response to a controlled capacity of $1\\ \\mathrm{mAh}\\ \\mathrm{cm}^{-2}$ . Meanwhile, for the bare Ti without FCOF film protection (Fig. 3c, d), disordered, distributed, and irregularly-shaped $Z\\mathrm{n}$ dendrites are observed on the surface. When further increasing the used capacity to $2\\ \\mathrm{mAh}$ $c\\mathrm{m}^{-2}$ , similar consistent morphological characteristics of the two samples are still maintained. A comparison of deposition morphology is shown in Supplementary Figs. 20 and 21. It can be seen that $Z\\mathrm{n}$ deposition on $Z\\mathrm{n}$ surface underneath the FCOF film exhibits horizontally arranged platelet morphology. SEM images with low magnification confirm platelet deposition morphology over a range of tens-of-microns (Supplementary Figs. 20–22). This confirms that platelet electrodeposition facilitated by FCOF film is ubiquitous, and, importantly, is therefore scalable for $Z\\mathrm{n}$ battery anodes. The XRD results reveal the intensity of (002) plane located at $2\\theta\\:=\\:36.3^{\\circ}$ is highest for the Zn deposits underneath FCOF films (Fig. 3e, f), while the bare Zn deposits show (101) planes dominating the peak intensities (Fig. 3g, h). This change in the dominant peaks implies that the FCOF films on $Z\\mathrm{n}$ anodes influence the preferred orientation of the $Z\\mathrm{n}$ deposits. It is noted that the XRD peaks located at $8.5^{\\circ}$ $16.8^{\\circ}$ , $20.6^{\\circ}$ , and $24.8^{\\circ}$ are observed for bare Zn deposits (Supplementary Fig. 23), and are attributed to $\\mathrm{Zn_{4}S O_{4}(O H)_{6}\\bullet5H_{2}O}$ (JCPDS NO: 39-0688) by-product. In contrast, these by-product signals are significantly weaker for $Z\\mathrm{n}$ deposits under the FCOF film, strongly evidencing that the FCOF film provides protection for $Z\\mathrm{n}$ , and inhibits accumulation of by-product. The orientation of the Zn deposits can also be quantified by calculating the texture coefficient41 ( $\\mathit{T_{c}},$ Supplementary Fig. 24). The $T_{c}$ (002) of $Z\\mathrm{n}$ deposits underneath the FCOF film is 19.2, much higher than that of the deposits on bare $Z\\mathrm{n}$ (11.5), verifying the preferential growth on the (002) plane of $Z\\mathrm{n}$ modulated by an FCOF film. XRD patterns for Zn deposits following the 30th and $80\\mathrm{th}$ cycles are shown in Supplementary Fig. 25. Results highlight that the Zn deposits underneath the FCOF film maintain preferred (002) plane orientation (Supplementary Fig. 25b), whilst bare Zn deposits have a (101) crystal-plane orientation (Supplementary Fig. 25a). Significantly, for the $\\operatorname{FCOF@Zn}$ electrode (Supplementary Fig. 25c), $T_{c}$ for the (002) plane is stable with increase in cycle number (1st cycle: 19.2; 30th cycle: 18.42; 80th cycle: 18.31), however is higher than that for bare $Z\\mathrm{n}$ (1st cycle: 11.5; 30th cycle: 11.12; 80th cycle: 10.34). These evidences validate that the preferred (002) plane orientation is maintained, despite long cycling. \n\n![](images/061c5db5a2c6c5527f845cb7331df30fc1ed7700b4e67b6bc0f27fa3b798f6ee.jpg) \nFig. 3 Morphology, crystallography and microstructure characterization of Zn electrodeposits. FESEM images of Zn deposits a, b underneath a FCOF film and c, d on bare Ti. XRD results for the Zn deposits e, f underneath the FCOF film and g, h on bare Ti. i Schematic illustration of preferred orientations of Zn crystal plane. (002) plane pole figures of the Zn deposits j on bare Ti and k underneath FCOF film. The WAXS results of $Z n$ deposits l, m underneath FCOF film and n, o on bare Ti. p–r HRTEM images and SAED patterns of the Zn platelet. s Theoretical atomic model of $Z n$ along the [001] direction. \n\nX-ray diffraction pole figures are used to further identify the texture information of $Z\\mathrm{n}$ deposits. The (002) pole figure (Fig. 3k) of Zn underneath FCOF films shows a sharp intensity concentration around $\\Psi=0{-}20^{\\circ};$ , indicating that the Zn platelets have a preferred textured based on (002) planes, and are nearly paralleled to the electrode substrate24,42 (Fig. 3i). In contrast, the random distributed of bare Zn deposits leads to a broad distribution of grain orientations, and the corresponding (002) pole figure (Fig. 3j) shows almost uniform distribution of diffraction intensity along the radial direction, indicating its random (non-preferential) texture. In addition, the 2D WAXS patterns of deposited Zn underneath FCOF film show some strong, discrete diffraction spots in the ring plane (Fig. 3l, m), while for bare Zn deposits, the WAXS results are continuous diffraction rings (Fig. 3n, o). This indicates that the bare Zn deposits are polycrystalline and randomly oriented, whereas the Zn grain size influenced by FCOF films is larger and more oriented5. The structure of the Zn platelets is characterized by \n\nHRTEM and selected area electron diffraction (SAED). As shown in Fig. 3p, q and Supplementary Fig. 26, the diffraction patterns of the SAED results can be indexed into diffraction spots of the [001] zone. The HRTEM image of Fig. 3r further shows two $d$ -spacings of 0.230 and $0.133\\mathrm{nm}$ with an interfacial angle of $90^{\\circ}$ , corresponding to the (100) and (1–20) planes, respectively. The HRTEM result is in accord with the indexed SAED diffraction spots. To further verify the indexing results, an atomic arrangement model of Zn along the (001) direction is simulated, as shown in Fig. 3s. Obviously, the indexed result matches well with the theoretical crystal model. According to the above results, we conclude that the exposed hexagonal planes of the $Z\\mathrm{n}$ platelet are predominately (002) planes. \n\nPerformance evaluation of the high-rate and long-life zinc anode. The planar $Z\\mathrm{n}$ deposition morphology, fast $Z\\mathrm{n}^{2+}$ transport, and corrosion resistance properties enabled by the FCOF film are expected to greatly improve the electrochemical performance of $Z\\mathrm{n}$ anodes. The reversibility of $Z\\mathrm{n}$ anodes can be measured by a procedure that wherein a specific amount of $Z\\mathrm{n}$ is plated on the substrate and then stripped away. Coulombic efficiency (CE) is an important index to evaluate such reversibility. The CE using the half cells in $\\mathrm{FCOF@Ti/Zn}$ and $\\mathrm{Ti}/\\mathrm{Zn}$ configurations is measured. At a moderate current density $(1\\mathrm{mAh}\\mathrm{cm}\\dot{^{-2}}$ , $5\\mathrm{mAcm}^{-2}$ , Supplementary Fig. $27\\mathrm{a-c})$ , the $\\operatorname{FCOF@Ti/Zn}$ cells produced CE values of ${\\sim}98.4\\%$ on average, with stability over 480 cycles. By contrast, the $\\mathrm{Ti}/\\mathrm{Zn}$ with no FCOF cells ran for only 30 cycles, and their CE is around ${\\sim}95.1\\%$ . When the current density is increased to an ultrahigh current density of $80\\mathrm{mA}\\mathrm{cm}^{-2}$ (Fig. 4a), the $\\mathrm{FCOF@Ti}/$ Zn cells still exhibit a high CE of approaching $97.2\\%$ on average within for 320 cycles, whereas the CE of the $\\mathrm{Ti}/\\mathrm{Zn}$ cells decreases rapidly after 95 cycles. When further increasing the capacity to 2 mAh $\\mathrm{im}^{-2}$ at a current density of $40\\mathrm{mA}\\mathrm{cm}^{-2}$ , the $\\mathrm{FCOF@Ti/Zn}$ cells show CE of $97.3\\%$ for over 250 cycles, much higher than that of the $\\mathrm{Ti}/\\mathrm{Zn}$ cells $_{\\sim35}$ cycles, $84.1\\%$ ). Remarkably, as evidenced from the AFM height and phase imaging (Fig. 3e, f and Supplementary Fig. 28a and c), the horizontally arranged platelet morphology of the Zn deposits underneath FCOF remains well after 100 cycles during Zn plating/stripping processes $(1\\ \\mathrm{mAh}\\ \\mathrm{cm}^{-2}$ , $5\\mathrm{mA}\\mathrm{{cm}}^{-2}$ ). The average height difference (along $X$ and Y axis) is only $170\\mathrm{nm}$ (Supplementary Fig. 28e), indicating the surface of the Zn deposits underneath FCOF is very flat and homogeneous. However, the Zn deposits on bare Ti after 100 cycles shows fluctuating and rough patterns with a much higher height difference of $710\\mathrm{nm}$ (Supplementary Fig. 28b, d, and f). During the $Z\\mathrm{n}$ plating/ stripping process, the $\\mathrm{\\dot{H}^{+}}$ from the decomposition of water will receive electrons and then evolve $\\mathrm{H}_{2},$ which could induce an increase of $\\mathrm{OH^{-}}$ . The generated $\\mathrm{OH^{-}}$ will react with $Z\\mathrm{n}^{2+}$ , $\\mathrm{SO}_{4}{}^{2-}$ , and $\\mathrm{H}_{2}\\mathrm{O}$ to form by-products such as $\\mathrm{Zn(OH)}_{2}$ or $\\mathrm{Zn_{4}S O_{4}(O H)_{6}}$ $\\mathrm{\\nH}_{2}\\mathrm{O}$ on $Z\\mathrm{n}$ surface16. Raman spectroscopy is carried out to reveal the components on $Z\\mathrm{n}$ deposits surfaces after cycling (100 cycles at $1\\ \\mathrm{mA}\\mathrm{\\bar{h}}\\ \\mathrm{cm}^{-2}$ , $5\\mathrm{mA}\\mathrm{cm}{\\dot{-}}^{2}$ ). Sharp peaks at 1152, 1110, 1011, and $967\\mathrm{cm}^{-1}$ are observed on the $Z\\mathrm{n}$ deposits on bare Ti (Supplementary Fig. 29a), which implies that the by-product should be the $\\mathrm{\\dot{Z}n_{4}S\\bar{O}_{4}(O H)}_{6}{\\cdot}5\\mathrm{H}_{2}\\mathrm{O}^{43}$ . In contrast, the peaks of the Zn deposits underneath FCOF are not obvious and their intensity is much lower (Supplementary Fig. 29b), indicating less by-product accumulation on its surface. Raman mapping $(8\\times10~\\upmu\\mathrm{m}$ area, Fig. 4g) of the dominated peak at $967\\mathrm{cm}^{-\\mathrm{\\bar{1}}}$ reveals that the counts variation for the $Z\\mathrm{n}$ deposits underneath FCOF is within 13–726, which is one to two orders of magnitude smaller than for Zn deposits on bare Ti (Fig. 4h, counts: 1200–8400). It has been reported that the Zn deposits with high percentage of (002) planes parallel to the substrate could provide higher corrosion resistance than other planes44. Combined with the $\\mathrm{~F~}$ endowed hydrophobic properties, the water-related side reactions could be largely suppressed in the $\\operatorname{FCOF}@^{\\prime}$ Ti cells. Moreover, the electrochemical stability of the FCOF film is evaluated using CV measurements (Supplementary Fig. 30). No excess decomposition current is apparent. It is concluded therefore that the FCOF film is stable and did not react with $Z\\mathrm{n}$ , or electrolyte, and is resistant to parasiticchemical reactions during cycling. In addition, the bare Ti is not adequate for regulating the zinc deposition behavior or suppressing by-products accumulation, causing elevated voltage hysteresis or short circuiting of the batteries, as evidenced by the voltage fluctuation in $\\mathrm{Ti}/\\mathrm{Zn}$ cells during cycling (Supplementary Fig. 27c–e). Whereas the voltage files of $\\mathrm{FCOF@Ti/Zn}$ remain stable at various levels of current density (Supplementary Fig. 27a and Fig. 4c, d). Meanwhile, $\\mathrm{FCOF@Ti/Zn}$ cells display long-term stability of the Zn plating/stripping process even at ultrahigh current density up to $\\bar{8}0\\mathrm{mAcm}^{-2}$ , larger than that of most previous studies (Supplementary Table 2). \n\nTo evaluate the stability of the Zn anodes, the $\\operatorname{FCOF@Zn}$ symmetric cells show prolonged cycle life for over $1700\\ \\mathrm{h}$ at 1 mAh $\\mathrm{cm}^{-2}$ and $5\\mathrm{m}\\mathrm{\\dot{A}}\\mathrm{cm}^{-\\sharp}$ which is nearly 13 times the performance of the bare Zn anodes (Fig. 4i). The $\\operatorname{FCOF@Zn}$ symmetric cells show lower voltage hysteresis $\\operatorname{FCOF@Zn}$ : $60\\mathrm{mV}$ vs. bare $\\mathrm{Zn}\\colon80\\mathrm{mV},$ , which we mainly attribute to the enhanced $Z\\mathrm{n}^{2+}$ transport within the 1D fluorinated nanochannels. Under elevated current densities of 8 and $40\\mathrm{mA}\\mathrm{cm}^{-2}$ (Supplementary Fig. 27e and Fig. 4j), the $\\operatorname{FCOF@Zn}$ symmetric cells could sustain repeated deposition/dissolution processes without obvious significant fluctuations in the voltage-time curves. However, the bare $Z\\mathrm{n}$ symmetric cells suffer short-circuits after a few limited cycles. The excellent performance of $\\operatorname{FCOF@Zn}$ symmetric cells at ultrahigh current density $(40\\mathrm{mA}\\mathrm{cm}^{-2})\\mathrm{.}$ ) is also far superior to most previous reported values (below $10\\mathrm{mA}\\mathrm{cm}^{-2}$ Supplementary Table 3). Under higher cycling capacity conditions (Supplementary Fig. 31), including $2\\ \\mathrm{\\mAh}\\ \\mathrm{\\cm}^{-2}$ , and 3 mAh $c\\bar{\\mathrm{m}}^{-2}$ , $\\operatorname{FCOF@Zn}$ maintains a more stable cycling performance than for bare $Z\\mathrm{n}$ . The highly stable electrochemical performance of the $\\operatorname{FCOF@Zn}$ anodes indicates that dendrite formation is largely suppressed. To identify the suppression of dendrite growth in $\\operatorname{FCOF@Zn}$ anode, transparent home-made $Z_{\\mathrm{{n}/Z_{\\mathrm{{n}}}}}$ symmetric cells with or without FCOF are assembled to realize in situ monitoring of the $Z\\mathrm{n}$ deposition process using an optical microscope. $Z\\mathrm{n}$ deposition is performed under a current density of $20\\mathrm{mA}\\mathrm{cm}^{-2}$ for $35\\mathrm{min}$ . As shown in Fig. 4k, after an initial 5 min of deposition, nonuniform Zn morphology with some protuberances appears on the bare Zn surfaces. These protuberances remain and grew into needle-like dendrites in the following deposition process. In contrast, the deposition on $\\operatorname{FCOF@}\\bar{Z}\\mathrm{n}$ is smooth as evidenced in Fig. 4l. No obvious Zn dendrites are observed, even after $35\\mathrm{min}$ deposition. The microscopic morphologies of the $Z\\mathrm{n}$ anodes after cycling at 1 mAh $\\mathrm{c}\\mathrm{\\dot{m}}^{-2}$ and $\\mathbf{\\bar{5}}\\ \\mathbf{mAcm}^{-2}$ , for $500\\mathrm{{h}}$ are also investigated. As shown in Supplementary Fig. 32, the $\\operatorname{FCOF@Zn}$ anodes show that dendrite-free morphology and parallel platelet-morphology is consistently maintained. In contrast, protuberant Zn dendrites are found randomly distributed on bare $Z\\mathrm{n}$ surfaces. Moreover, the HRTEM and FTIR results (Supplementary Fig. 33) show the FCOF films maintain good crystallinity and chemical structure stability after cycling. Consequently, it can be concluded that the multifunctional $\\mathrm{~F~}{}$ nanochannels greatly improve the $Z\\mathrm{n}^{2+}$ kinetics and deposition morphology, which results in highrate and long life $\\operatorname{FCOF@Zn}$ anodes. \n\nFull cell performance and flexible device demonstration. We next evaluate the electrochemical performance of full cells in which $\\operatorname{FCOF@Zn}$ or Zn anodes are paired with high mass-loading $(\\sim8\\mathrm{mg}\\mathrm{cm}^{-2},$ ) manganese dioxide $\\mathrm{(MnO}_{2}\\mathrm{)}$ cathodes. For the $\\mathrm{FCOF@Zn/MnO}_{2}\\mathrm{cells}.$ , cyclic voltammetry curve (CV) curves demonstrate a larger current density at $0.1\\dot{\\mathrm{~mV~}}s^{-1}$ and a smaller voltage gap between typical redox peaks than in $\\mathrm{Zn/MnO}_{2}$ cells (Supplementary Fig. 34a). This implies that the $\\mathrm{FCOF@Zn/MnO}_{2}$ cells possess higher specific capacity and better charge transfer capability6. EIS results further confirm that, the impedance of the $\\mathrm{FCOF@Zn/MnO}_{2}$ cells $\\left(\\sim100~\\Omega\\right)$ is lower than that of $\\mathrm{Zn}/\\mathrm{MnO}_{2}$ cells (Supplementary Fig. 34b). Theref ore, a a current density of ${}_{3\\mathrm{C}},$ the $\\mathrm{FCOF@Zn/MnO_{2}}$ reveal a high initial reversible specific capacity of $130\\ \\mathrm{mAh\\g^{-1}}$ while the $\\mathrm{Zn}/\\mathrm{MnO}_{2}$ cells attain only 120 mAh $\\mathbf{g}^{-1}$ (Sup 34c). The FCOF films clearly endow stable $Z\\mathrm{n}$ anodes, and retain a capacity of ${\\sim}92\\%$ and stable ge/discharge curves after 1000 cycles (Fig. 5a and Supp g. 34d, e). This is nearly four times higher than the $\\mathrm{Zn/MnO}_{2}$ cells (capacity retention: $20\\%$ ). Reducing the capacity ratio of the negative electrode to the positive electrode $(N/P)$ during full cell operation is a key parameter to achieve high energy density14,30,45. In previous studies, many systems chose to use thick zinc foil $(\\geq100~{\\upmu\\mathrm{m}})$ paired with low mass loading cathodes to assemble full cells, the $N/P$ reported in these studies is typically higher than 50, which is not beneficial for achieving high energy density. In our case, the excellent performance of the $\\operatorname{FCOF@Zn}$ anodes allows us to further evaluate the cycle performance of full cells under harsh conditions. Using thin FCOF film-protected $Z\\mathrm{n}$ plates as anodes (the thin $Z\\mathrm{n}$ plates is rolled to desired thickness to satisfy the required $N/P$ condition), $\\mathrm{FCOF@Zn/MnO}_{2}$ cells with $N/P\\stackrel{\\cdot}{=}10{:}1$ and $N/P=$ 5:1 show stable specific capacity at current density of $4\\mathrm{mA}\\mathrm{cm}^{-2}$ for over 300 and 200 cycles, respectively (Fig. 5b). The $Z\\mathrm{n}$ platelet morphology after cycling and stable charge–discharge curves indicate the FCOF films enable great performance improvements in $Z\\mathrm{n}$ anodes (Supplementary Fig. 35). To evaluate the electrochemical performance of the aqueous $Z\\mathrm{n}$ batteries for commercial applications under practical conditions, lean electrolyte addition and high areal capacity cathode is needed (inset of Fig. 5c). To understand the practicality of $\\operatorname{FCOF@Zn}$ anode, full cells with high mass loading $\\mathrm{MnO}_{2}$ cathode $(16\\mathrm{mg}\\mathrm{cm}^{-2})$ and controlled electrolyte-to-capacity ratio $(E/C,~12\\upmu\\mathrm{L}\\mathrm{\\mAh}^{-1})$ ) is assembled. When the mass loading of $\\mathrm{MnO}_{2}$ increases from 8 to $16\\mathrm{mg}\\mathrm{cm}^{-2}$ the charge and discharge curves for $\\mathrm{FCOF@Zn–MnO}_{2}$ full cell exhibit low polarization as shown in Supplementary Fig. 36a. The $\\mathrm{FCOF@Zn-MnO_{2}}$ full cell (cathode loading, $1\\dot{6}\\mathrm{mg}\\mathrm{cm}^{-2}$ , $N/P=2{:}1$ and electrolyte addition, $12\\upmu\\mathrm{L}\\ \\mathrm{mAh}^{-1},$ ) is cycled at a current density of $3\\mathrm{\\mA}\\mathrm{cm}^{-2}$ . The charge/discharge curves determined from different cycles almost overlap (Supplementary Fig. 36b), highlighting high cycle stability. Additionally, the assembled full cell exhibits a significant capacity of $0.5\\operatorname{mA}\\dot{\\mathrm{h}}\\mathrm{cm}^{-2}$ following 250 cycles. The gravimetric energy density of the cell is $130\\mathrm{Wh}\\mathrm{\\bar{k}g^{-1}}$ (based on the total mass of the $Z\\mathrm{n}$ anode and the $\\mathrm{MnO}_{2}$ cathode), which is significantly increased (by approx. 6.5 times) compared with many reported $\\mathrm{Zn/MnO}_{2}$ cells using low mass loading cathodes and thick $Z\\mathrm{n}$ foils30 (Fig. 5d). It should be noted that the cell still delivers an energy density of $55\\mathrm{Wh}\\mathrm{kg}^{-1}$ when including the electrolyte weight. Further optimization of other key components such as separator membrane and electrolyte may improve the energy density of the cell. \n\n![](images/b836b841e560a6ee4918914698ea19fdafe4ab08b04dc48b29aa5f0ff9e878e0.jpg) \nFig. 4 The electrochemical performance of Zn anodes. CE of Zn plating/stripping on FCOF film-coated Ti and bare Ti at a 1 mAh $\\mathsf{c m}^{-2}$ , $80\\mathsf{m A c m}^{-2}$ and b $2\\mathsf{m A h\\thinspace c m^{-2}},$ $40\\mathsf{m A}\\mathsf{c m}^{-2}$ . c, d The corresponding voltage profiles at various cycles on FCOF film-coated Ti. The insets are enlarged voltage profiles. AFM 3D height imaging and 2D Raman mapping on the surfaces of Zn deposits after 200 cycles plating/stripping $(1\\mathsf{m A h}\\mathsf{c m}^{-2}.$ , $5\\mathsf{m A}\\mathsf{c m}^{-2}.$ ), e, $\\pmb{\\mathsf{g}}$ on FCOF film-coated Ti and f, h bare Ti. Cycling performance of $Z n$ symmetric cells with or without FCOF film protection at i $1\\mathsf{m A h c m}^{-2}$ , $5\\mathsf{m A c m}^{-2}$ , and j 1 mAh $\\mathsf{c m}^{-2}$ , $40\\mathsf{m A}\\mathsf{c m}^{-2}$ . The insets are initial and selected voltage-time profiles. In situ optical microscopy studies on $Z n$ deposition behaviors. k Bare $Z n$ , $1F C O F@Z n$ . \n\nTo further demonstrate the application prospects of the $\\operatorname{FCOF@Zn}$ anodes for constructing realistic, smart, highperformance aqueous Zn batteries, we assemble a flexible transparent battery for device demonstration. Figure 5e and Supplementary Fig. 37 shows the structural schematic diagram of the transparent battery. The $\\mathrm{MnO}_{2}$ cathode and $\\operatorname{FCOF@Zn}$ anode are fixed to the flexible PVC substrate, and glass fiber is used as the separator. All layers are sandwiched and the battery is then assembled by thermal sealing. The cycling performance of the flexible battery under different bending conditions is shown in Fig. 5h–j. The EIS results (Supplementary Fig. 38) and the charge and discharge curves (insets of Fig. 5i, j) remain nearly unchanged at bending angles of $0^{\\circ}$ , $45^{\\circ}$ and $60^{\\circ}$ , respectively, indicating its good mechanical stability and flexibility. To create a more realistic scenario, a flexible $\\operatorname{FCOF}@$ $\\mathrm{Zn/MnO}_{2}$ battery is used to power a wearable bracelet for lighting a light emitting diode (LED) indicator (Fig. 5f, g), showing its promising application in portable wearable electronic devices. \n\n# Discussion \n\nThe excellent electrochemical performance of the $\\operatorname{FCOF@Zn}$ anodes can be mainly attributed to the planar deposition morphology, i.e., the predominantly parallel tessellated Zn platelets. This specific morphology seems to result from the tailored strongly-electronegative F atoms within the FCOF films, since the surface stability of inorganic crystals is largely governed by their surface chemistry. The preference of the exposed the crystal plane is closely related to the surface energy changes31–33. Previous studies indicated that the specific surface crystal planes in anatase surfaces are preferentially terminated by $\\mathrm{~F~}$ atoms, inducing the anatase to expose specific crystal planes. Such a result is attributed to the surface energy decreases after the interaction between F and these crystal planes31,46. The F terminated (FT) plane with lowest the surface energy tends to stay exposed instead of its intrinsic thermodynamically stable plane. In our case, the uniformly distributed F atoms within FCOF film have a strong binding interaction with the $Z\\mathrm{n}$ atoms, thereby regulating the relative surface energy value of the (101) and (002) planes and influencing the deposited morphology. To verify this, the surface energy and adsorption energy o f the two crystal planes terminated by $\\mathrm{~F~}$ atoms are studied by first-principles calculations (Fig. 6a). The calculated energy values clearly show that F atoms result in bonding to (002) planes that are more stable than (101) planes (Fig. 6b), and F atoms interact more strongly with the (002) planes (Fig. 6c), in accordance with the above XRD results. Moreover, with the formation of $Z\\mathrm{n-F}$ interactions, the equilibrium positions of the Zn atoms on the surface of the crystal surface are clearly and obviously moved outward from where they would be without the presence of F atoms (insets of Fig. 6b). To further elucidate the stability mechanisms associated with F atoms, the electronic structures of clean surfaces and FT surfaces are investigated. The PDOS of clean and fluorinated surfaces are shown in Fig. 6d, e. For the clean surfaces, electrons contributed by $\\mathrm{Zn~}4s$ delocalize in the range of the higher valence band (VB) and lower conduction band (CB). With the formation of $Z\\mathrm{n-F}$ interaction, however, localized states of $\\scriptstyle{\\Z n\\ \\4s}$ are observed, indicating that $\\mathrm{~F~}{}$ atoms are prone to stabilize $Z\\mathrm{n}$ atoms. To qualitatively determine the strength of the interaction between F atoms and $Z\\mathrm{n}$ atoms and its impact on different crystal planes, the electron states of the $Z n3d$ and F $2p$ are analyzed. Due to the strong electron-withdrawing property of F atoms, the $\\mathrm{~F~}2p$ could accept electrons from the Zn 4s. As a result, the $\\mathtt{Z n\\ 4s}$ planes would partially lose electrons, forming quasi-stable bonds with the $\\mathrm{~F~}$ species. Thereafter, the electrons from the $Z n\\ 3d$ may be excited toward the Fermi level. The displacement of $Z\\mathfrak{n}\\ 3d$ electrons from the FT-(002) planes is more energetically-favorable than from FT-(101) planes. On the other hand, compared with the F $2p$ electron states f the in FT-(101) planes, the F $2p$ electron distribution in a FT-(002) plane is more localized. These results clearly suggest that F atoms interact more strongly with the (002) planes than with the (101) plane. The XPS data for the F 1s and $Z\\mathrm{n}~2p$ at the FCOF-Zn interface also indicate the existence of strong $\\mathrm{F}{-}\\mathrm{Zn}$ interaction47–50 (Supplementary Fig. 39). Therefore, the FT-(002) planes are more stable and thus preferentially form the outer surfaces. It seems the (101) surfaces are preferentially eroded in a stepped fashion during electro-stripping so that the exposed surface, which remains and subsequently builds up Zn deposits is a (002) surface. \n\n![](images/bbb940e98a3427b806c1c664bc337fbabd64ee5fd9d590504653b1cf15a9a6de.jpg) \nFig. 5 The full cell performance and flexible device demonstration. a Cycling performance at current density of 3 C. b Cycling performance at $N{:}P$ capacity ratio conditions of 10:1 and 5:1. c Cycling performance at low $N{:}P$ capacity ratio of 2:1 with controlled electrolyte addition of $12\\upmu\\upmu\\upmu\\upmu\\upmu^{-1}$ d Dependence of cell-level energy density on $N/P$ ratio in $Z n/M n O_{2}$ full cell. The gravimetrical energy density is calculated based on the total mass of the $Z n$ anode and the $\\mathsf{M n O}_{2}$ cathode. e Assembly schematic illustration of the flexible transparent battery. f, g Pictures of the battery acting as a source of energy to power a LED. h–j Cycling performance of the flexible transparent battery under different bending angles. The insets are selected voltage-time profiles. \n\nTo experimentally clarify the formation mechanism of $Z\\mathrm{n}$ platelets, the evolution of the morphology and crystallography during the Zn deposition growth is systematically investigated. To compare growth behavior of $Z\\mathrm{n}$ both underneath FCOF film and on bare Ti, the deposition capacity is controlled by setting the cut-off deposition time, 40 s, 2, 6, and $12\\mathrm{min}$ , at a current density of $5\\mathrm{mA}\\mathrm{cm}^{-2}$ . Corresponding SEM images are shown as Supplementary Figs. 40 and 41. In contrast to Zn deposits on the Ti surface, in which the dendrites are randomly oriented (Supplementary Fig. 41), the Zn deposits underneath the FCOF film are in the form of platelets with parallel orientation (Supplementary Fig. 40). High-magnification SEM images of the different deposition stages reveal the evolution (Supplementary Fig. 40). At the initial heterogeneous nucleation stage (40 s), small-sized and horizontally-arranged Zn platelets are found to be evenly distributed underneath the FCOF film. With increased deposition capacity, the $Z\\mathrm{n}$ platelets gradually grow horizontally, and following the entire Ti surface being fully occupied, the deposition enters the next homogeneous growth stage $(6\\mathrm{min})$ ). Because the upper layer has been uniformly covered by F atoms, the newly deposited Zn continues to grow in the horizontal direction of the (002) crystal planes $(12\\mathrm{min})$ . The XRD results confirm this finding. From the initial heterogeneous nucleation stage to the final homogeneous growth stage, the XRD patterns underscore that the Zn deposits under the FCOF film maintain the strongest signal of the (002) planes (Supplementary Fig. 42a), whilst the bare Zn deposits shows the strongest (101) signal (Supplementary Fig. 42b). This confirms that the Zn deposits underneath the FCOF film grow along the preferred orientation of the (002) planes. Moreover, it is observed that the crystal plane signals in the WAXS spectra of the Zn deposits underneath the FCOF (Supplementary Fig. 43a) show discrete diffraction spots on the (002) ring, revealing the existence of (002)-textured single-crystal Zn deposits. The presence of the single-crystal signal underscores homogeneous deposition of Zn under the FCOF film. This means that the initial small-sized Zn platelets continue to grow in the direction of their initial orientation. In contrast, the WAXS spectra for the bare Zn deposits show a continuous, dispersive diffraction ring (Supplementary Fig. 43b), underscoring its polycrystalline and randomly oriented features. \n\n![](images/4ba105b7b17a7463e3bf32daa2fb9834cc3cec04525c370563488070a5d38f2c.jpg) \nFig. 6 Theoretical simulation of FT-Zn (002) and FT-Zn (101). a Calculations models of F atom adsorbed on $Z n$ (002) and $Z n$ (101). Calculated b free energies and $\\blacktriangledown\\mathbf{c}$ adsorption energies of F atom on $Z n$ (002) plane and $Z n$ (101) plane. d, e Calculated projected density of states (PDOS) for clean Zn and FT-Zn systems. \n\nThrough experimental and first-principles calculations, we have determined that the F atoms in the FCOF film demonstrate the strongest interaction with the (002) crystal planes of Zn. The growth of (002) planes is most stable during the deposition process, and anisotropic growth of Zn along other planes is done in such a way that a (002) plane is formed, resulting in plateletlike Zn deposits. Given that the F atoms bonded within the FCOF film are arranged in parallel along the surfaces of the current collectors, which induces each Zn platelet to also be arranged in parallel. Furthermore, the F-containing porous nano channels endow good hydrophobic effects on the film, which is beneficial for de-solvation and facilitates fast transport of hydrated $Z\\mathrm{n}^{2+}$ , as well as reducing the corrosion of $Z\\mathrm{n}$ by the aqueous electrolyte. The presence of F atoms and the “built-in nanochannels” in FCOF films seems to endow multiple advantages: the $\\operatorname{FCOF@Zn}$ anodes exhibit excellent fast charging properties and cycle stability. The $\\operatorname{FCOF@Zn}$ anodes can sustain over 320 cycles with excellent reversibility of ${\\sim}97.2\\%$ and the symmetric cells exhibit long cycle life up to $750\\mathrm{h}$ at an ultrahigh current density of $40\\mathrm{m}\\mathrm{\\AA}\\mathrm{cm}^{-2}$ . This work provides novel design concepts for the realization of planar deposition and thus dendrite-free $Z\\mathrm{n}$ anodes. The 2D COFs films are versatile platforms that show distinct advantages for constructing high-performance batteries, owing to their adjustable pore sizes, tailored functional groups, light weight, and structural stability through covalent bonding. The 2D COF rational design of the approach may also prove useful for other dendrite-free, longlife, and high-safety metal anode batteries, such as lithium, sodium, potassium, and magnesium. Importantly, the stabilizing mechanism proposed to suppress dendrite formation is not limited to FCOF, it might therefore reasonably lead to material designs for advanced separators and liquid/gel/solid electrolytes to achieve high energy density batteries. \n\n# Methods \n\nPreparation of FCOF films and $\\pmb{M}\\pmb{n}\\pmb{0}_{2}$ cathodes. For the typical synthesis of FCOF film, a pyrex tube is charged with $3.75\\mathrm{mg}$ (0.0182 mmol) $2,3,5$ , \n\n6-tetrafluoroterephthalaldehyde (TFA), $4.40\\mathrm{mg}$ $(0.0125\\mathrm{mmol}$ ) 1,3,5-Tris(4-aminophenyl) benzene (TAPB), $1.8\\mathrm{mL}$ dioxane (Dio) and 0.2 mL 1, 3, 5-trimethylbenzene (TMB). After sonication for 10 min, $0.1\\mathrm{mL}$ HOAc (1.5 M) solution is added. After this, the tube is frozen at $77\\mathrm{K}$ (liquid $\\Nu_{2}$ bath) and degassed by three freeze-pumpthaw cycles and finally sealed under vacuum conditions. The sealed tube is heated at $120^{\\circ}\\mathrm{C}$ for 3 days. For the postprocessing, the tube is opened, washed with acetone several times and then the tube is charged with deionized water overnight. The freestanding FCOF films easily detach from the tube wall by gently shaking the tube. The obtained FCOF films is immersed in acetone for 2 days to wash out any impurities. Finally, the as-prepared FCOF films is transferred to various substrates via a pulling method in acetone solvent. The thickness of the membrane/film can be also easily tuned by controlling the concentration of monomers. The $\\mathrm{MnO}_{2}$ cathodes are synthesized using an aging method according to a previous report51. First, $5.07\\mathrm{g}$ manganese sulfate monohydrate $(\\mathrm{MnSO}_{4}{\\cdot}\\mathrm{H}_{2}\\mathrm{O})$ is put in $100\\mathrm{mL}$ deionized water, followed by ultrasound and stir to ensure dissolution (named Solution 1). Then $4.32{\\mathrm{g}}$ sodium hydroxide $\\left(\\mathrm{NaOH}\\right)$ and $20~\\mathrm{mL}$ hydrogen peroxide $\\mathrm{(H}_{2}\\mathrm{O}_{2},30\\mathrm{wt}\\%\\mathrm{)}$ are dissolved in $180~\\mathrm{mL}$ deionized water (named Solution 2). Solution 2 is then dropwise added into Solution 1 under vigorous stirring conditions. The mixed solution is stirred for $^\\mathrm{1h}$ and aged at $25^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . The precipitated product is centrifuged for three times, washed with deionized water, and dried to obtain $\\mathrm{MnO}_{2}$ . \n\nStructural and chemical characterizations. Wide-angle X-ray scattering (WAXS) measurement is conducted on a XenocsXeuss2.0 with $8\\mathrm{KeV}$ Cu Kα radiation. X-ray diffraction (XRD) data is measured by a Bruker D8 Advance with $\\mathrm{{Cu-KaX}}.$ - ray radiation $(\\lambda=0.154056\\mathrm{nm})$ ), using an operating voltage of $40\\mathrm{kV}$ and a $40\\mathrm{mA}$ current. Fourier transform infrared (FTIR) spectra are collected on a ThermoFisher Nicolet 6700 spectrometer. $\\Nu_{2}$ adsorption–desorption isotherms are measured at $77\\mathrm{K}$ on a Micromeritics TriStar II 3020 volumetric adsorption analyzer after degassing in a vacuum at $120^{\\circ}\\mathrm{C}$ overnight. Atomic force microscope (AFM) is performed on a NT-MDT NTEGRA Spectra II microscope. Field-emission scanning electron microscopy (FESEM) images are acquired from a Zeiss Gemini SEM500, equipped with an Aztec X-Max Extreme energy dispersive spectrometer (EDS). High-resolution transmission electron microscope (HRTEM) images are collected from a JEM-2010F transmission electron microscope. XPS measurements are carried out with a Thermo Scientific K-Alpha $^{+}$ spectrometer under vacuum. Nano-indentation surface hardness measurements are conducted on a TI950, NHT. \n\nElectrochemical measurements. Cycling tests for symmetric cells and $Z\\mathrm{n/Ti}$ half cells of bare $Z\\mathrm{n}$ or $\\operatorname{FCOF@Zn}$ are conducted with 2 M $\\mathrm{ZnSO_{4}}$ aqueous electrolyte. For cathode fabrication, the high mass loading $\\mathrm{MnO}_{2}$ cathodes are prepared by mixing the active materials with carbon black and polytetrafluoroethylene (PTFE) in a mass ratio of 7:2:1. The mixture is compressed onto a Ti grid. The electrodes are dried at $80^{\\circ}\\mathrm{C}$ under vacuum for $^{12\\mathrm{h}}$ and then punched into disks. All the electrochemical properties are tested by assembling 2016-coin cells with glass fiber separators. All Galvanostatic charge-discharge measurements are carried out on a battery testing instrument (Land CT2001A, Wuhan China) at different current densities. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) are performed by a CHI 660E electrochemical workstation. CV curves of full cells are recorded over the voltage range of $1{-}1.85\\mathrm{V}$ . EIS is measured in a frequency range of $100\\mathrm{kHz}$ to $0.1\\mathrm{{Hz}}$ at open circuit potential and an amplitude of $5\\mathrm{mV}$ . The fitting parameters of the equivalent circuit are analyzed by ZSimpWin software. \n\nCalculation method. The DFT calculations are carried out using the Vienna Ab-initio Simulation Package (VASP) with the frozen-core all-electron projectoraugment-wave (PAW) method. The Perdew–Burke–Ernzerhof (PBE) form of the generalized gradient approximation (GGA) is adopted to describe the exchange and correlation potential. The cutoff energy for the plane-wave basis set is set to $500\\mathrm{eV}$ The Monkhorst-Pack k-point6 sampling is set to $3\\times3\\times1$ . The geometry optimizations are performed until the forces on each ion is reduced below $0.05\\mathrm{eV}/{\\dot{\\mathrm{A}}}.$ The vacuum slab models are used to calculate the adsorption of $\\mathrm{~F~}$ atom on $Z\\mathrm{n}$ (002) and (101) surfaces. These $Z\\mathrm{n}$ surface slabs comprise four layers of $Z\\mathrm{n}$ atoms, and a vacuum region of $20\\textup{\\AA}$ above them is used to ensure the decoupling between neighboring systems. For the geometry optimization, the atoms in the 2-bottom layers of slab are fixed to their bulk positions. \n\nThe adsorption energy, $E_{\\mathrm{ads}}$ , is calculated using the expression: \n\n$$\nE_{\\mathrm{ads}}=E_{\\mathrm{surface}}+16\\mathrm{E}_{\\mathrm{F}}-E_{\\mathrm{F+surface}}\n$$ \n\nwhere $E_{\\mathrm{surface}}$ is the energy of the clean $Z\\mathrm{n}$ surface, $E_{\\mathrm{{F}}}$ represents the energy of the F atom, and $E_{\\mathrm{F+surface}}$ represents the total energy of the adsorbed $\\mathrm{F}/\\mathrm{Zn}$ system. \n\nThe surface free energy $(\\gamma)$ , is calculated using the expression based on a previous study31: \n\n$$\n\\gamma=\\frac{E^{\\mathrm{slab}}-\\mathrm{NE_{Zn}^{b u l k}}-N_{\\mathrm{F}}E_{\\mathrm{F}}}{2\\mathrm{A}},\n$$ \n\nwhere, $E_{\\mathrm{Zn}}^{\\mathrm{bulk}}$ is the energy per unit of $\\mathrm{Zn},E^{\\mathrm{slab}}$ is the total energy of the slab, $N$ is the total number of unit $Z\\mathrm{n}$ contained in the slab model, $N_{\\mathrm{X}}$ is the number of adsorbed F atoms, $\\begin{array}{r}{E_{\\mathrm{F}}=\\frac{1}{2}E_{\\mathrm{F-F}}-}\\end{array}$ and $E_{\\mathrm{F-F}}$ indicates the total energy of dimer $\\mathrm{F}_{2}$ . \n\n# Data availability \n\nSource data are provided with this paper. Data supporting the findings of this study are available within the article and the associated Supplementary Information. The source data underlying Figs. 2–6 generated in this study is provided as a Source Data file. Additional data are available from the corresponding authors upon reasonable request. Source data are provided with this paper. \n\nReceived: 5 May 2021; Accepted: 20 October 2021; Published online: 16 November 2021 \n\n# References \n\n1. Wang, F. et al. Highly reversible zinc metal anode for aqueous batteries. Nat. Mater. 17, 543–549 (2018). \n2. Yi, Z., Chen, G., Hou, F., Wang, L. & Liang, J. Strategies for the stabilization of Zn metal anodes for Zn-ion batteries. Adv. Energy Mater. 11, 2003065 (2021). \n3. Tang, B., Shan, L., Liang, S. & Zhou, J. Issues and opportunities facing aqueous zinc-ion batteries. Energy Environ. Sci. 12, 3288–3334 (2019). \n4. Zhang, Q., Luan, J., Tang, Y., Ji, X. & Wang, H. Interfacial design of dendritefree zinc anodes for aqueous zinc-ion batteries. Angew. Chem. Int. Ed. 59, \n13180–13191 (2020). \n5. Zheng, J. et al. Reversible epitaxial electrodeposition of metals in battery anodes. Science 366, 645–648 (2019). \n6. Xie, X. et al. Manipulating the ion-transfer kinetics and interface stability for high-performance zinc metal anodes. Energy Environ. Sci. 13, 503–510 (2020). \n7. Hao, J. et al. An in-depth study of Zn metal surface chemistry for advanced aqueous Zn-ion batteries. Adv. Mater. 32, 2003021 (2020). by a multifunctional brightener-inspired interphase. Energy Environ. Sci. 12, 1938–1949 (2019). \n9. Yang, Q. et al. Hydrogen-substituted graphdiyne ion tunnels directing concentration redistribution for commercial-grade dendrite-free zinc anodes. Adv. Mater. 32, 2001755 (2020). \n10. Bayaguud, A., Luo, X., Fu, Y. & Zhu, C. Cationic surfactant-type electrolyte additive enables three-dimensional dendrite-free zinc anode for stable zincion batteries. ACS Energy Lett. 5, 3012–3020 (2020). \n11. Cong, J. et al. Ultra-stable and highly reversible aqueous zinc metal anodes with high preferred orientation deposition achieved by a polyanionic hydrogel electrolyte. Energy Storage Mater. 35, 586–594 (2021). \n12. Yang, H. et al. Constructing a super-saturated electrolyte front surface for stable rechargeable aqueous zinc batteries. Angew. Chem. Int. Ed. 59, 9377–9381 (2020). \n13. Zeng, Y. et al. Dendrite-free zinc deposition induced by multifunctional CNT frameworks for stable flexible Zn-ion batteries. Adv. Mater. 31, 1903675 (2019). \n14. Wang, S. et al. Lamella-nanostructured eutectic zinc-aluminum alloys as reversible and dendrite-free anodes for aqueous rechargeable batteries. Nat. Commun. 11, 1634 (2020). \n15. Zhang, H., Liu, X., Li, H., Hasa, I. & Passerini, S. Challenges and strategies for high-energy aqueous electrolyte rechargeable batteries. Angew. Chem. Int. Ed. 60, 598–616 (2021). \n16. Zhou, M. et al. Suppressing by-product via stratified adsorption effect to assist highly reversible zinc anode in aqueous electrolyte. J. Energy Chem. 55, 549–556 (2021). \n17. Du, W. et al. Challenges in the material and structural design of zinc anode towards high-performance aqueous zinc-ion batteries. Energy Environ. Sci. 13, 3330–3360 (2020). \n18. Wang, Z. et al. A metal-organic framework host for highly reversible dendritefree zinc metal anodes. Joule 3, 1289–1300 (2019). \n19. Zheng, J. et al. Spontaneous and field-induced crystallographic reorientation of metal electrodeposits at battery anodes. Sci. Adv. 6, b1122 (2020). \n20. Zheng, J. & Archer, L. A. Controlling electrochemical growth of metallic zinc electrodes: toward affordable rechargeable energy storage systems. Sci. Adv. 7, eabe0219 (2021). \n21. Majuste, D. et al. Effect of organic impurities on the morphology and crystallographic texture of zinc electrodeposits. Hydrometallurgy 169, 330–338 (2017). \n22. Nayana, K. O. & Venkatesha, T. V. Synergistic effects of additives on morphology, texture and discharge mechanism of zinc during electrodeposition. J. Electroanal. Chem. 663, 98–107 (2011). \n23. Raeissi, K., Saatchi, A., Golozar, M. A. & Szpunar, J. A. Texture and surface morphology in zinc electrodeposits. J. Appl. Electrochem. 34, 1249–1258 (2004). \n24. Yuan, D. et al. Anion texturing towards dendrite-free Zn anode for aqueous rechargeable batteries. Angew. Chem. Int. Ed. 133, 7289–7295 (2021). \n25. Sun, K. E. K. et al. Suppression of dendrite formation and corrosion on zinc anode of secondary aqueous batteries. ACS Appl. Mater. Interfaces 9, 9681–9687 (2017). \n26. Hao, J. et al. Boosting zinc electrode reversibility in aqueous electrolytes by using low-cost antisolvents. Angew. Chem. Int. Ed. 60, 7366–7375 (2021). \n27. Kubo, B. et al. Effect of surface textures of iron substrate on the crystal orientation relationship between electrodeposited zinc and iron. ISIJ Int. 59, 144–151 (2019). \n28. KAMEI, K. & OHMORI, Y. Hetero-epitaxial growth of zinc electrodeposits on low-carbon steel sheets. J. Appl. Electrochem. 17, 821–827 (1987). \n29. Monzon, L. M. A., Klodt, L. & Coey, J. M. D. Nucleation and electrochemical growth of zinc crystals on polyaniline films. J. Phys. Chem. C 116, 18308–18317 (2012). \n30. Hao, J. et al. Deeply understanding the $Z\\mathrm{n}$ anode behaviour and corresponding improvement strategies in different aqueous $Z\\mathrm{n}$ -based batteries. Energy Environ. Sci. 13, 3917–3949 (2020). \n31. Yang, H. G. et al. Anatase $\\mathrm{TiO}_{2}$ single crystals with a large percentage of reactive facets. Nature 453, 638–641 (2008). \n32. Maurer, F. et al. Preferred growth orientation of metallic fcc nanowires under direct and alternating electrodeposition conditions. Nanotechnology 18, 135709 (2007). \n33. Pan, H., Sun, H., Poh, C., Feng, Y. & Lin, J. Single-crystal growth of metallic nanowires with preferred orientation. Nanotechnology 16, 1559–1564 (2005). \n34. Liao, Q. et al. Catalyst-free and efficient fabrication of highly crystalline fluorinated covalent organic frameworks for selective guest adsorption. J. Mater. Chem. A 7, 18959–18970 (2019). \n35. Zhou, D., Tan, X., Wu, H., Tian, L. & Li, M. Synthesis of C−C bonded twodimensional conjugated covalent organic framework films by Suzuki polymerization on a liquid-liquid interface. Angew. Chem. Int. Ed. 58, 1376–1381 (2019). \n36. Zhao, R. et al. Redirected Zn electrodeposition by an anti-corrosion elastic constraint for highly reversible Zn anodes. Adv. Funct. Mater. 31, 2001867 (2021). \n37. Deng, C. et al. A sieve-functional and uniform-porous kaolin layer toward stable zinc metal anode. Adv. Funct. Mater. 30, 2000599 (2020). \n38. Zhao, Z. et al. Covalent organic framework-based ultrathin crystalline porous film: manipulating uniformity of fluoride distribution for stabilizing lithium metal anode. J. Mater. Chem. A 8, 3459–3467 (2020). \n39. Jeong, K. et al. Solvent-free, single lithium-ion conducting covalent organic frameworks. J. Am. Chem. Soc. 141, 5880–5885 (2019). \n40. Liang, X. et al. A facile surface chemistry route to a stabilized lithium metal anode. Nat. Energy 2, 17119 (2017). \n41. Li, N. et al. Reduced-graphene-oxide-guided directional growth of planar lithium layers. Adv. Mater. 32, 1907079 (2019). \n42. Shi, F. et al. Strong texturing of lithium metal in batteries. PNAS 114, 12138–12143 (2017). \n43. Kasperek, J. & Lenglet, M. Identification of thin films on zinc substrates by FTIR and Raman spectroscopies. Rev. Met. Paris 94, 713–719 (1997). \n44. Raeissi, K., Golozar, M. A., Saatchi, A. & Szpunar, J. A. The effect of texture on the corrosion resistance of zinc electrodeposits. T. I. Met. Finish. 83, 99–103 (2005). \n45. Liu, J. et al. Pathways for practical high-energy long-cycling lithium metal batteries. Nat. Energy 4, 180–186 (2019). \n46. Liu, S., Yu, J. & Jaroniec, M. Anatase $\\mathrm{TiO}_{2}$ with dominant high-energy {001} facets: synthesis, properties, and applications. Chem. Mater. 23, 4085–4093 (2011). \n47. Waware, U. S., Hamouda, A. M. S., Rashid, M. & Kasak, P. Binding energy, structural, and dielectric properties of thin film of poly(aniline-co-mfluoroaniline). Ionics 24, 3249–3257 (2018). \n48. Xu, H. Y. et al. Photoluminescence of F-passivated ZnO nanocrystalline films made from thermally oxidized $\\mathrm{ZnF}_{2}$ films. J. Phys. Condens. Matter 16, 5143–5150 (2004). \n49. Wang, H. et al. Synthesis and characterization of F-doped MgZnO films prepared by RF magnetron co-sputtering. Appl. Surf. Sci. 503, 144273 (2020). \n50. Ilican, S., Caglar, M., Aksoy, S. & Caglar, Y. XPS studies of electrodeposited grown F-Doped ZnO rods and electrical properties of p-Si/n-FZN heterojunctions. J. Nanomater. 2016, 1–9 (2016). \n51. Qiu, N., Chen, H., Yang, Z., Sun, S. & Wang, Y. Low-cost birnessite as a promising cathode for high-performance aqueous rechargeable batteries. Electrochim. Acta 272, 154–160 (2018). \n\n# Acknowledgements \n\nThe authors greatly appreciate the financial support from the 973 Project (2011CB605702), the National Science Foundation of China (22075048, 51173027, 21875141, 22179085), the Shanghai Key Basic Research Project (14JC1400600), Beijing National Laboratory for Condensed Matter Physics, Shanghai International Collaboration Research Project (19520713900). Thanks to the State Key Laboratory of Molecular Engineering of Polymers (Fudan University), Yiwu Research Institute of Fudan University and SHAANXI YANCHANG PETROLEUM (GROUP) CO., LTD. for funding and equipment support. \n\n# Author contributions \n\nH.L., J.G., C.P., and Z.G. conceived and designed the experiment and participated in writing and revising the paper. Z.Z. performed the electrochemical tests, analyzed the data, and wrote the manuscript. R.W., C.W., and Y.Y. synthesized the samples, performed the characterizations of COF. T.W. performed the WAXS measurements. B.H. performed the AFM measurements. J.Z. and Z.C. performed the Raman measurements. W.W., Y.L., G.L., and P.L. provided valuable advice on simulation results. All authors have read and approved the final paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-26947-9. \n\nCorrespondence and requests for materials should be addressed to Chengxin Peng, Jia Guo, Hongbin Lu or Zaiping Guo. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. \n\n# Reprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41563-021-01064-6", + "DOI": "10.1038/s41563-021-01064-6", + "DOI Link": "http://dx.doi.org/10.1038/s41563-021-01064-6", + "Relative Dir Path": "mds/10.1038_s41563-021-01064-6", + "Article Title": "Polycrystalline SnSe with a thermoelectric figure of merit greater than the single crystal", + "Authors": "Zhou, CJ; Lee, YK; Yu, Y; Byun, S; Luo, ZZ; Lee, H; Ge, BZ; Lee, YL; Chen, XQ; Lee, JY; Cojocaru-Mirédin, O; Chang, H; Im, J; Cho, SP; Wuttig, M; Dravid, VP; Kanatzidis, MG; Chung, I", + "Source Title": "NATURE MATERIALS", + "Abstract": "Thermoelectric materials generate electric energy from waste heat, with conversion efficiency governed by the dimensionless figure of merit, ZT. Single-crystal tin selenide (SnSe) was discovered to exhibit a high ZT of roughly 2.2-2.6 at 913 K, but more practical and deployable polycrystal versions of the same compound suffer from much poorer overall ZT, thereby thwarting prospects for cost-effective lead-free thermoelectrics. The poor polycrystal bulk performance is attributed to traces of tin oxides covering the surface of SnSe powders, which increases thermal conductivity, reduces electrical conductivity and thereby reduces ZT. Here, we report that hole-doped SnSe polycrystalline samples with reagents carefully purified and tin oxides removed exhibit an ZT of roughly 3.1 at 783 K. Its lattice thermal conductivity is ultralow at roughly 0.07 W m(-1) K-1 at 783 K, lower than the single crystals. The path to ultrahigh thermoelectric performance in polycrystalline samples is the proper removal of the deleterious thermally conductive oxides from the surface of SnSe grains. These results could open an era of high-performance practical thermoelectrics from this high-performance material. SnSe has a very high thermoelectric figure of merit ZT, but uncommonly polycrystalline samples have higher lattice thermal conductivity than single crystals. Here, by controlling Sn reagent purity and removing SnOx impurities, a lower thermal conductivity is achieved, enabling ZT of 3.1 at 783 K.", + "Times Cited, WoS Core": 480, + "Times Cited, All Databases": 491, + "Publication Year": 2021, + "Research Areas": "Chemistry; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000680338900002", + "Markdown": "# OPEN Polycrystalline SnSe with a thermoelectric figure of merit greater than the single crystal \n\nChongjian Zhou   1,10, Yong Kyu Lee1,10, Yuan Yu   2,10, Sejin Byun1,3, Zhong-Zhen Luo4, Hyungseok Lee   1,3, Bangzhi Ge1, Yea-Lee Lee5, Xinqi Chen6, Ji Yeong Lee7, Oana Cojocaru-Mirédin $\\oplus2$ , Hyunju Chang   5, Jino Im $\\textcircled{10}$ 5, Sung-Pyo Cho8, Matthias Wuttig $\\textcircled{10}2$ , Vinayak P. Dravid $\\textcircled{10}$ 9, Mercouri G. Kanatzidis4,9 ✉ and In Chung   1,3 ✉ \n\nThermoelectric materials generate electric energy from waste heat, with conversion efficiency governed by the dimensionless figure of merit, ZT. Single-crystal tin selenide (SnSe) was discovered to exhibit a high ZT of roughly 2.2–2.6 at 913 K, but more practical and deployable polycrystal versions of the same compound suffer from much poorer overall ZT, thereby thwarting prospects for cost-effective lead-free thermoelectrics. The poor polycrystal bulk performance is attributed to traces of tin oxides covering the surface of SnSe powders, which increases thermal conductivity, reduces electrical conductivity and thereby reduces ZT. Here, we report that hole-doped SnSe polycrystalline samples with reagents carefully purified and tin oxides removed exhibit an ZT of roughly 3.1 at $78316$ . Its lattice thermal conductivity is ultralow at roughly $\\mathbf{0.07wm^{-1}K^{-1}}$ at 783 K, lower than the single crystals. The path to ultrahigh thermoelectric performance in polycrystalline samples is the proper removal of the deleterious thermally conductive oxides from the surface of SnSe grains. These results could open an era of high-performance practical thermoelectrics from this high-performance material. \n\n$\\mathsf{M}$ ore than $65\\%$ of the globally produced energy is lost as waste heat1. Thermoelectric power generators are semiconductor-based electronic devices that can turn such waste heat into electricity through the Seebeck effect2. This conversion process is free of motion or moving parts, thus can be an eco-friendly solution to recovering and using enormous amounts of waste heat to create electricity. The efficiency of thermoelectric semiconductors is assessed by the dimensionless figure of merit $\\mathrm{ZT}{=}S^{2}\\sigma T/\\kappa_{\\mathrm{tot}}$ (refs. $^{2-4^{\\mathsf{V}}},$ ), where $s$ is the Seebeck coefficient, $\\sigma$ is the electrical conductivity, $T$ is the absolute temperature and $\\kappa_{\\mathrm{tot}}$ is the total thermal conductivity from the electrical $(\\kappa_{\\mathrm{ele}})$ and lattice vibration contribution $(\\kappa_{\\mathrm{lat}})^{3}$ . \n\nZT values have been substantially improved by developing various strategies for increasing power factor (the product $S^{2}\\sigma_{.}$ ) or suppressing $\\kappa_{\\mathrm{lat}}$ in the past decade. They have been individually or multiply applied to representative thermoelectric systems such as lead chalcogenides5, skutterudites6 and half-Heusler compounds7. For example, an unusually high ZT roughly 2.2–2.5 around $920\\mathrm{K}$ was achieved in PbTe–SrTe systems by applying multiple strategies of band engineering, endotaxial nanostructuring, hierarchical architecturing and non-equilibrium processing8. However, among the state-of-the-art thermoelectric systems, the most surprising and promising is the discovery of tin selenide (SnSe) as a top thermoelectric material9–11. This material combines two very desirable attributes: (1) highly effective inherent ultralow thermal conductivity and (2) very favourable electronic band structure with multiple bands contributing to the charge transport, thereby contributing to the ultrahigh power factor9–11. The innate strongly anisotropic and anharmonic crystal chemistry gives rise to intrinsically ultralow $\\kappa_{\\mathrm{lat}}$ of roughly $0.20\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ . As a result, its $\\boldsymbol{\\mathrm{\\tt~p~}}$ -type pristine crystals exhibit a ZT of 2.6 at $913\\mathrm{K}$ along the $b$ axis9, and the Br-doped $\\mathfrak{n}$ -type crystals show a ZT of 2.8 at $773\\mathrm{K}$ along the $^a$ axis11. \n\nHowever, these extraordinarily high thermoelectric properties have been only observable in single-crystal SnSe samples while the polycrystalline versions show much poorer figure of merit12–14. In fact, many research groups have observed much higher thermal conductivity $\\kappa_{\\mathrm{lat}}$ values in polycrystalline SnSe samples than those reported for the single-crystal samples, despite the expected presence of additional phonon scattering mechanism from the grain boundaries (GBs)15,16. Accordingly, ZT values of the polycrystalline SnSe materials have been much lower than those of the single crystals. This has led to controversy regarding the ultralow $\\kappa_{\\mathrm{lat}}$ of SnSe as an intrinsic property and whether the exceptional ZT values of the single-crystal SnSe can ever be achieved in polycrystalline SnSe samples15. Indeed, given the high cost, lengthy and labour-intensive production, poor mechanical brittleness and high cleavability of the single-crystal SnSe samples, it is the polycrystalline samples that have a realistic chance to achieve mass production and commercial applications. Consequently, it has been a huge challenge to realize comparable or even higher thermoelectric performance in polycrystalline SnSe samples. Indeed, matching single-crystal thermoelectric performance in polycrystalline SnSe would be a major development; not only because of both maximum and average ZT during operating temperature range, but also due to the relative abundance of Sn and Se (in comparison to Te) as well as the lead-free nature of the compound. \n\n![](images/8c22dcedc2549d7468b9bf173e3d00af25a3257129e64f6fb5ffb6e744ebdc51.jpg) \nFig. 1 | A schematic illustration of the process to remove surface tin oxides $(\\mathsf{S n O}_{x})$ in polycrystalline SnSe, and to reveal the intrinsic thermoelectric properties of the material. Our facile two-step process involves the successive purification of the tin starting reagent and the synthesized SnSe samples. The use of the purified samples minimizes the presence of $\\mathsf{S n O}_{x}$ in the SPS-processed dense pellets. As a result, the intrinsically ultralow thermal conductivity $(\\kappa_{\\mathrm{tot}})$ is finally uncovered in the purified sample (green squares on the right) in sharp contrast to the controversially high values in the untreated sample (red circles), leading to the record-high thermoelectric figure of merit, ZT, of roughly 3.1 among all bulk thermoelectric systems. \n\nRecently, we have revealed that this apparently higher $\\kappa_{\\mathrm{lat}}$ reported for polycrystalline SnSe samples is attributed to the presence of surface tin oxides $(\\mathrm{SnO}_{x})$ on SnSe powders12. $\\mathrm{SnO}_{2}$ has approximately 140 times higher $\\kappa_{\\mathrm{lat}}$ than $\\mathrm{SnSe}^{1\\bar{6}}$ . When the SnSe powders covered with $\\mathrm{SnO}_{x}$ thin films are compacted into dense pellets, high thermal conductivity $\\mathrm{SnO}_{x}$ present at GBs provides natural percolation pathway for heat transport. In this case, the thermal conductivity is greatly enhanced, contrary to the general expectation that polycrystalline samples should have lower thermal conductivity than that of their single-crystal counterpart due to expected extensive GB phonon scattering. In fact, high thermal conductivity $\\mathrm{SnO}_{x}$ phases can also easily grow on the surfaces of the single crystals, thereby often complicating the studies of the thermal transport properties. Further, the surface $\\mathrm{SnO}_{x}$ can strongly scatter charge carriers, consequentially affecting both thermal and charge transport properties adversely, and as a result severely curtailing the promise of a cost-effective, eco-friendly, widely deployable thermoelectric material such as SnSe. Indeed, polycrystalline SnSe with minimal GB and surface phase of $\\mathrm{SnO}_{x}$ would be a major advance in this context. \n\nTo initially mitigate this problem, we developed a postprocess of ball milling combined with chemical reduction for polycrystalline SnSe-based materials. This approach effectively removes $\\mathrm{SnO}_{x}$ phase from surfaces and subsequent interfaces to reveal the exceptionally low $\\kappa_{\\mathrm{lat}}$ of roughly $0.11\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ and near-single-crystal ZT of roughly 2.5 at $773\\mathrm{K}$ (ref. 12). However, despite this great progress these samples still show higher $\\kappa_{\\mathrm{lat}}$ of roughly $0.84{-}0.32\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ than the single-crystal SnSe with $0.47{-}0.24\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ in the nearly entire temperature range $300{-}673\\mathrm{K}$ suggesting the presence of persistent and pervasive presence of $\\mathrm{SnO}_{x}$ in the samples. This continues to obscure the intrinsic thermal and charge-carrier transport properties of SnSe and, as a result, the true thermoelectric properties of SnSe have hitherto not yet been realized in polycrystalline samples of SnSe. \n\nHerein, we report that the tin (Sn) metal starting reagent, despite its $99.999\\%$ purity, is the culprit behind the formation of surface $\\mathrm{SnO}_{x}$ in polycrystalline SnSe-based materials. To remedy this further, we have developed a facile and more efficient two-step process to remove the deleterious oxygen and minimize the presence of $\\mathrm{SnO}_{x}$ . Collectively, this further reduces the thermal conductivity and increases the power factor, thereby uncovering the extraordinarily high thermoelectric performance of polycrystalline SnSe, which reaches a ZT of roughly 3.1 at 783 K. A schematic illustration of this process is shown in Fig. 1. \n\n# Purification process for SnSe \n\nAs-received elemental tin (Sn) reagent must be purified before use. Note that we use $99.999\\%$ purity Sn chunks, showing a characteristic silvery lustre. This was chemically reduced by a $4\\%$ $\\mathrm{H}_{2}/\\mathrm{Ar}$ flow for $6\\mathrm{h}$ at $473\\mathrm{K}$ , near the melting point of $\\scriptstyle\\mathrm{Sn}$ , showing no visible change in surface colour and lustre afterwards. The metal was subsequently heated at $^{1,223\\mathrm{K}}$ in an evacuated ampule. This caused ash-like black residues to form at the top and entire surface of the resulting Sn ingot and it was unambiguously identified as $\\mathrm{SnO}_{x}$ by far-infrared spectroscopy17 and atom probe tomography (APT) (Supplementary Figs. 1–3). After removing these residues, the melting-purification process was repeated until the ash-like black $\\mathrm{SnO}_{x}$ residues were no more visible. The purified Sn reagent was confirmed to be nearly oxygen-free according to the APT analysis (Supplementary Fig. 3). We found that the purification of elemental selenium (Se) reagent had a negligible influence on thermoelectric properties of SnSe. After the purification of Sn, the synthesized SnSe samples were pulverized and further purified under a $4\\%\\mathrm{H}_{2}/96\\%$ Ar flow at $613\\mathrm{K}$ for $6\\mathrm{h}$ . For the sake of the discussion, samples prepared by this two-step purification process are referred to as ‘purified’, while those not prepared by this process are denoted as ‘untreated’. \n\nAnalysis of surface $\\mathbf{SnO}_{x}$ in untreated and purified SnSe. The facile formation of surface $\\mathrm{SnO}_{x}$ in polycrystalline SnSe samples is supported by our density functional theory (DFT) calculations (Supplementary Fig. 4 and Note). To probe the presence and distribution of surface $\\mathrm{SnO}_{x}$ in both the untreated and purified SnSe samples, we first performed time-of-flight–secondary ion mass spectrometry (TOF–SIMS). This is a highly surface-sensitive technique providing chemical mapping at spatial resolutions down to a submicrometre scale, thereby providing the broad-range distribution of surface $\\mathrm{SnO}_{x}$ at GBs. We mapped the $\\mathrm{\\DeltaSnOH^{+}}$ species to reliably display the spatial distribution of tin-bound oxygen. \n\nFigure 2a,b shows TOF–SIMS images of the untreated and purified spark plasma sintering (SPS) SnSe samples. Spread red spots correspond to the distribution of $\\mathrm{{\\calSnOH^{+}}}$ , which are much fainter and less dense in the purified SnSe sample. The analysed data show that it has a factor of 7.4 lower $\\mathrm{SnO}_{x}$ concentration than the untreated sample. After identifying the GBs in the corresponding optical images (Supplementary Fig. $^{5\\mathrm{a},\\mathrm{b}}$ ), the line-profile scan for the $\\mathrm{SnO}_{x}$ concentration was taken across them. It revealed that $\\mathrm{SnO}_{x}$ is more abundant in the GBs than in the interior regions of SnSe crystallites (Fig. 2c,d). This is not surprising in view of the compaction process of SnSe powders, which are surface-covered with $\\mathrm{SnO}_{x}$ . \n\n![](images/ae03c98c1b5814412aa620a67435d8800d6d52a1c2d875d5c234dff10c169643.jpg) \nFig. 2 | Distribution of $\\mathsf{S n O}_{x}$ in untreated and purified polycrystalline SnSe samples obtained by TOF–SIMS. The surface of both SPS-processed specimens was sputtered to generate $\\mathsf{S n O H^{+}}$ complex that is a relevant quantity to tin-bound oxygen. Accordingly, the $\\mathsf{S n O H^{+}}$ map clearly represents the distribution of surface $\\mathsf{S n O}_{x}$ on SnSe samples. a, The $\\mathsf{S n O H^{+}}$ image for the untreated SnSe sample. b, The $\\mathsf{S n O H^{+}}$ image for the purified SnSe sample. The red spots correspond to $\\mathsf{S n O}_{x}$ . The white dotted lines indicate GBs, which were defined with optical images taken on the corresponding regions. Scale bars are $10\\upmu\\mathrm{m}$ . c, The concentration of $\\mathsf{S n O}_{x}$ across the GB by a line profile (yellow solid line in a) for the untreated SnSe sample. d, The concentration of $\\mathsf{S n O}_{x}$ across the GB by a line profile (yellow solid line in b) for the purified SnSe sample. The width of a line profile is $3\\upmu\\mathrm{m},$ , in which the concentrations of $\\mathsf{S n O}_{x}$ were averaged. The substantial decrease in surface $\\mathsf{S n O}_{x}$ is clearly observed by our purification process. \n\nWe further investigated surface $\\mathrm{SnO}_{x}$ in GB regions in the untreated SnSe sample using a spherical aberration-corrected scann­ ing transmission electron microscope (STEM). A representative high-angle annular dark-field (HAADF)–STEM image shows the presence of abundant nanoscale precipitates, indicated by the white arrows, around the GB marked by the orange dashed line and arrow (Fig. 3a). The corresponding elemental map reveals that they are rich in oxygen and devoid of selenium with the negligible fluctuation in the tin concentration throughout the specimen, thereby being identified as $\\mathrm{SnO}_{x}$ (Fig. 3b–e). \n\nTo spatially determine the distribution and composition of surface $\\mathrm{SnO}_{x},$ we conducted APT analysis on the untreated SnSe sample. It quantitatively provides the three-dimensional distribution of constituent elements with equal sensitivity at a spatial resolution nearly down to the subatomic level, thereby serving as an effective tool to resolve secondary phases either in the matrix or trapped at ${\\bf G B S}^{18-20}$ . Figure 3f displays the three-dimensional reconstruction of the needle-shaped specimen from the untreated SnSe sample. The GB, marked by the orange arrow and dash line, is located by a much higher atomic counts due to the local magnification effect20. The high concentration O atoms are aggregated along the GB, coincident with our STEM observations. They also percolate into the grain forming $\\mathrm{SnO}_{x}$ layers as observed in the upper area in Fig. 3f. \n\nTo quantitatively resolve their content with the greater statistical accuracy, one-dimensional compositional profiles were recorded at the oxygen-rich region, namely both across the GB as enclosed by the blue cylinder (Fig. 3g) and across the oxygen-rich layer as marked by the green cylinder (Fig. 3h) in Fig. 3f. In these regions, the O concentration exceeds roughly $15\\mathrm{at\\%}$ with a maximum reaching roughly $30\\mathrm{at\\%}$ , whereas the Se concentration drops by greater than $20\\%$ . Outside these, the former rapidly decreases and a compositional ratio of $\\mathrm{{Sn}}$ to Se atom remains nearly constant at unity. The typical thickness of surface $\\mathrm{SnO}_{x}$ layer at GBs is about $15\\mathrm{nm}$ in the untreated SnSe sample according to both STEM and APT observations. Even nanoscale GB phases could considerably affect charge21 and thermal22 transport properties of materials, consequently inhibiting the observation of intrinsic values21,22. \n\nA typical HAADF–STEM image for the purified SnSe sample does not show the presence of $\\mathrm{SnO}_{x}$ at the GBs (Fig. 3i). The magnified image focusing on the GB shows that two adjacent crystalline grains form the tightly jointed interface without intervening secondary phases (Fig. 3j). The three-dimensional APT reconstruction (Fig. 3k) and one-dimensional compositional profile extracted across the GB (Fig. 3l) show that the distribution of Sn and Se atoms is nearly homogeneous at the same level over the specimen with a negligible discontinuity across the GB. No signal for the presence of O atoms is detected in the mass-to-charge ratio spectrum (Fig. 3m). The results confirm that our purification process effectively removes surface $\\mathrm{SnO}_{x}$ from SnSe-based materials. \n\nThe strong beneficial effect of our purification process is dramatically evident in the thermoelectric properties of polycrystalline SnSe. Because of the characteristic lamellar structure of SnSe (Fig. 4a), its thermoelectric properties are highly anisotropic9. Namely, polycrystalline and single-crystal samples exhibit the lowest thermal conductivity $(\\kappa)$ along the parallel direction of compaction (//) and along the crystallographic $\\mathbf{\\Delta}_{a}$ axis9, respectively. Along these directions, we compare $\\kappa$ of our polycrystalline SnSe-based samples with the reported values for the undoped single-crystal sample9. To obtain accurate $\\kappa$ , we directly recorded the temperature-dependent heat capacity $(C_{\\mathrm{p}})$ of the samples over the entire temperature range using differential scanning calorimetry (DSC). To ensure the credi­ bility of data, we ran measurements for more than 20 samples. The $C_{\\mathfrak{p}}$ values taken at the three different heating rates of 5, 7.5 and $10\\mathrm{{Kmin^{-1}}}$ , respectively, unambiguously confirm that they are nearly constant outside the phase transition temperature of the $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.965}\\mathrm{Se}$ sample regardless of the heating rate (Fig. 4b). We averaged the obtained $C_{\\mathrm{{p}}}$ values and then derived the $\\kappa$ The averaged experimental $C_{\\mathfrak{p}}$ is comparable to the modelled value derived from the previous report10 over the entire range of temperature. \n\nUltralow thermal conductivity. The purification process reduces lattice thermal conductivity $(\\kappa_{\\mathrm{lat}})$ for the polycrystalline SnSe sample and makes it comparable to that reported for single crystals over the entire temperature range (Fig. 4c). In contrast, when SnSe powder is treated only by the post $\\mathrm{H}_{2}$ -reduction without the Sn metal purification, the decrease in $\\kappa_{\\mathrm{lat}}$ is small. The $\\kappa_{\\mathrm{lat}}$ values for the untreated, $\\mathrm{H}_{2}$ -reduced and purified polycrystalline SnSe samples are roughly 1.03, 0.99 and $0.58\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at $300\\mathrm{K}$ and roughly 0.39, 0.38 and $0.23\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at $773\\mathrm{K}$ , respectively. This observation confirms that the application of a proper Sn purification procedure is essential to unveil the intrinsically ultralow $\\kappa_{\\mathrm{lat}}$ in SnSe-based thermoelectric materials. \n\nHole-doped $\\mathrm{Na}_{x}\\mathrm{Sn}_{0.995-x}\\mathrm{Se}$ $\\scriptstyle(x=0.01-0.03)$ ) purified samples exhibit even lower $\\kappa_{\\mathrm{lat}}$ than the undoped polycrystalline and single-crystal SnSe samples. Their $\\kappa_{\\mathrm{lat}}$ decreases with the higher Na concentration because of slightly softened phonon frequency (Fig. 4d and Supplementary Fig. 6). The lowest $\\kappa_{\\mathrm{lat}}$ is roughly 0.17 $\\scriptstyle\\left(x=0.01\\right)$ ), 0.12 $\\scriptstyle(x=0.02)$ and $0.07\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ $\\left(x=0.03\\right)$ ) at $783\\mathrm{K},$ in comparison with roughly $0.20\\mathrm{~W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at $973\\mathrm{K}$ for the single-crystal SnSe along the a axis9. The observed value is one of the lowest $\\kappa_{\\mathrm{lat}}$ reported for bulk crystalline solids. In comparison, bulk polycrystalline ${\\mathrm{CsAg}}_{5}{\\mathrm{Te}}_{3}$ exhibits roughly $0.18\\mathrm{{W}}\\mathrm{{m}}^{-1}\\mathrm{{K}}^{-1}$ at 727 K (ref. 23) and disordered thin films of lamellar $\\mathrm{WSe}_{2}$ , prepared by the vacuum deposition, give roughly $0.05\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at $300\\mathrm{K}$ (ref. 24). The $\\scriptstyle x=0.03$ sample shows the lowest total thermal conductivity $(\\kappa_{\\mathrm{tot}})$ among the series as the trend of $\\kappa_{\\mathrm{lat}}$ (Supplementary Fig. 7). Its $\\kappa_{\\mathrm{tot}}$ at $300\\mathrm{K}$ is higher at roughly 0.65 than $0.46\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ of the single-crystal SnSe sample. They show comparable $\\kappa_{\\mathrm{tot}}$ at the elevated temperatures, and the former exhibits a lower minimum of roughly $0.21\\mathrm{\\overline{{W}}m^{-1}K^{-1}}$ at $783\\mathrm{K}$ than roughly $0.23\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ at 773 K of the latter. \n\n![](images/0a5bd09642fc2ed7331d162ebfa290defc65c47436b170cc5a8a72a68e87080b.jpg) \nFig. 3 | Distribution and composition of $\\mathsf{s n O}_{x}$ in untreated and purified polycrystalline SnSe samples. a, HAADF–STEM image for the untreated polycrystalline SnSe sample, revealing $\\mathsf{S n O}_{x}$ precipitates around the GBs as indicated by the white arrows. Scale bar, $20\\mathsf{n m}$ . b, Elemental map recorded on the entire area of a by STEM–EDS. Scale bar, $50\\mathsf{n m}$ . c–e, A joint image by overlaying the EDS signals directly arising from O (c), Se (d) and Sn (e) atoms, respectively. f, Three-dimensional APT reconstruction of the untreated polycrystalline SnSe specimen, presenting the spatial distribution of Sn (green), Se (orange) and O (blue) atoms. Scale bar, $50\\mathsf{n m}$ . g,h, One-dimensional compositional profiles showing the content of Sn, Se and O atoms across the GB as enclosed by the blue cylinder $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ and across the oxygen-rich layer as marked by the green cylinder ${\\bf\\Pi}({\\bf h})$ in f, respectively. i, HAADF–STEM image for the purified SnSe sample, confirming the absence of $\\mathsf{S n O}_{x}$ around the GBs. Scale bar, $200\\mathsf{n m}$ . j, Magnified HAADF–STEM image focusing on the GB, showing two adjacent crystalline grains form the tightly jointed interface without intervening secondary phases. Scale bar, 1 nm. k, Three-dimensional APT reconstruction of the purified SnSe, representing the spatial distribution of Sn (green) and Se (orange) atoms. The O atoms are not detected, verifying the successful removal of $\\mathsf{S n O}_{x}$ by our two-step purification process. Scale bar, $50\\mathsf{n m}$ l, One-dimensional compositional profile extracted across the GB, demonstrating an $a t\\%$ ratio of Sn and Se atoms that is nearly constant at unity over the specimen. m, The mass-to-charge ratio spectrum for the purified sample, confirming the absence of signals from O atoms as indicated by the blue dashed lines. The orange arrows and dashed lines in a, f, i, j and $\\pmb{\\ k}$ indicate the GBs in the samples. \n\nThe ultralow $\\kappa$ of $\\mathrm{Na}_{x}\\mathrm{Sn}_{0.995-x}\\mathrm{Se}$ and SnSe samples up to $783\\mathrm{K}$ is present before the sharp endothermic thermal event occurs, thus the phase transition has a negligible effect on the ultralow value of $\\kappa$ . Figure 4e demonstrates that the temperature-dependent $\\kappa_{\\mathrm{tot}}$ calculated by our DSC $C_{\\mathfrak{p}}$ and modelled $C_{\\mathfrak{p}}$ derived from the previous report10 are comparable from 300 to $78\\Bar{3}\\mathrm{K}$ , confirming that $\\kappa$ is not underestimated by the modelled $C_{\\mathfrak{p}}$ in this temperature regime. \n\nWe prepared ten independent $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.965}\\mathrm{Se}$ specimens and cross-checked the reproducibility of the ultralow $\\kappa$ from two institutions, SNU and Northwestern University, and the manufacturer of Netzsch Instruments (Fig. 4f). The measurements on all specimens (four from SNU, three from Northwestern University and three from Netzsch) gave the uncertainty in $\\kappa_{\\mathrm{tot}}$ of less than roughly $10\\%$ in the temperature range $323\\mathrm{-}773\\mathrm{K}$ . \n\nCharge transport properties. The effect of the purification process is seemingly marginal on electrical conductivity $(\\sigma)$ for the undoped polycrystalline SnSe samples (Supplementary Fig. 8a) because such samples have a very low carrier concentration $(n_{\\mathrm{H}})$ , for example, roughly $2.5\\times10^{17}$ and $2.0\\times10^{17}\\mathrm{cm}^{-3}$ at $300\\mathrm{K}$ for the untreated and purified polycrystalline SnSe, respectively. In the doped $\\mathrm{Na}_{x}\\mathrm{Sn}_{0.995-x}\\mathrm{Se}$ samples with $n_{\\mathrm{H}}$ roughly $10^{19}\\mathrm{cm}^{-3}$ , however, the purification process that minimizes surface $\\mathrm{SnO}_{x}$ is key to achieving the enhanced Hall carrier mobility $(\\upmu_{\\mathrm{H}})$ (Supplementary Fig. 9) \n\n![](images/e4d7a01e57636a1cc106abd8c7e445b582b80ce7cd72623e836ccc2c527d8179.jpg) \nFig. 4 | SnSe crystal structure and lattice, $\\kappa_{\\vert\\mathsf{a t}},$ and total thermal conductivities, $\\kappa_{\\mathrm{tot}},$ as a function of temperature for the undoped and Na-doped polycrystalline SnSe samples before and after the purification process. a, Room temperature crystal structure (Pnma space group) viewed down the $b$ axis9: Sn atoms, blue; Se atoms, red. b, Temperature-dependent heat capacity $(C_{\\mathfrak{p}})$ measured by DSC for the purified $\\mathsf{N a}_{0.03}\\mathsf{S}\\mathsf{n}_{0.965}\\mathsf{S}\\mathsf{e}$ samples. Orange, green and purple solid lines denote the $C_{\\mathfrak{p}}$ recorded at the heating rate of 5, 7.5 and $10\\mathsf{K}\\mathsf{m i n}^{-1}.$ respectively. The averaged $C_{\\mathfrak{p}}$ values are represented by red circles, which are used to calculate the $\\kappa_{\\mathrm{tot}}$ . $C_{\\mathfrak{p}}$ values derived from the previous work are included for comparison (black circles)10. c, $\\kappa_{\\vert\\mathfrak{a}\\mathfrak{t}}$ for the untreated, ${\\sf H}_{2}$ -reduced without Sn purification and purified SnSe samples. d, $\\kappa_{\\vert\\mathrm{at}}$ for the $\\mathsf{N a}_{x}\\mathsf{S n}_{0.995-x}\\mathsf{S e}$ $\\scriptstyle(x=0.01$ , 0.02 and 0.03) samples in comparison with that for the untreated and purified SnSe samples. e, $\\kappa_{\\mathrm{tot}}$ of the $\\mathsf{N a}_{0.03}\\mathsf{S n}_{0.965}\\mathsf{S e}$ sample calculated using the $C_{\\mathfrak{p}}$ obtained by our DSC experiments (red circles) and derived from the previous works (black circles)10. f, The reproducibility of $\\kappa_{\\mathrm{tot}}$ for ten independently synthesized samples, cross-checked at SNU (samples 1–4), Netzsch Instruments (Netzsch, samples 5–7) and Northwestern University (NU, samples 8–10). $\\kappa_{\\vert a t}$ and $\\kappa_{\\mathrm{tot}}$ for a SnSe single crystal along the $a$ axis are given for comparison9 in c,d,f. Polycrystalline samples were measured parallel to the SPS direction. \n\nand $\\sigma$ over the full range of temperature (Fig. 5a). The $\\sigma$ markedly increases with the higher Na content in the temperature range $300-$ $523\\mathrm{K}$ . This leads to the enhanced thermoelectric performance of the samples in the low- to mid-temperature regime, a big improvement over previous polycrystalline SnSe thermoelectrics that suffer from low $\\sigma$ in that range, resulting in poor ZT values. The $\\scriptstyle x=0.03$ sample shows the $\\sigma$ of 140 and $118\\mathsf{S c m}^{-1}$ at 423 and $783\\mathrm{K}$ measured parallel to the SPS direction, and 181 and $132\\mathsf{S c m}^{-1}$ at the same temperatures perpendicular to the SPS direction. \n\nThe Seebeck coefficients (S) of the $\\mathrm{Na}_{x}\\mathrm{Sn}_{0.995-x}\\mathrm{Se}$ samples are nearly the same along the parallel and perpendicular direction of SPS (Supplementary Fig. 10). Because of the higher hole concentration, the S values are lower than in the undoped SnSe samples (Fig. 5b). S slightly increases with the higher Na concentration consistent with the multi-band nature of the valence band in this material, which enhances the effective hole mass with higher hole concentrations as the Fermi level lowers to cross several valence bands according to our theoretical calculations (Supplementary Fig. 11) and the previous report10. Their S is slightly increased by our purification process making the Na doping more effective. For example, the maximum S for the $\\scriptstyle x=0.03$ sample is $+322$ and $+342\\upmu\\mathrm{V}\\mathrm{K}^{-1}$ at $673\\mathrm{K}$ before and after the purification process, respectively. The high reproducibility of $\\sigma$ and S values were confirmed using numerous independently synthesized specimens (Supplementary Fig. 12). \n\nThe simultaneously increased $\\sigma$ and S of the purified $\\mathrm{Na}_{x}\\mathrm{Sn}_{0.995-x}\\mathrm{Se}$ samples result in the improved power factor (Fig. 5c) that trends higher with the rising Na concentration. The $\\scriptstyle x=0.03$ sample exhibits power factors near $\\mathsf{9\\upmu W\\mathsf{c m}^{-1}K^{-2}}$ in the wide range of temperature $473\\mathrm{-}783\\mathrm{K}$ with a maximum of roughly $9.62\\upmu\\mathrm{W}\\uptau\\mathrm{m}^{-1}\\mathrm{K}^{-2}$ at $498\\mathrm{K}$ parallel to the SPS direction. The maximum power factor is roughly $12.06\\upmu\\mathrm{W}\\mathrm{cm}^{-1}\\mathrm{K}^{-2}$ at $473\\mathrm{K}$ perpendicular to the SPS direction, which is the highest value reported for polycrystalline SnSe-based materials. \n\nThermoelectric figure of merit. The purification process concurrently enhances $\\sigma$ and $s,$ and decreases $\\kappa_{\\mathrm{tot}}$ for the $\\mathrm{Na}_{x}\\mathrm{Sn}_{0.995-x}\\mathrm{Se}$ samples, leading to an extraordinarily high thermoelectric figure of merit ZT. It increases with higher Na concentration. The $\\scriptstyle x=0.03$ sample exhibits the maximum ZT $(Z\\mathrm{T_{\\mathrm{max}}})$ roughly 3.1 at $783\\mathrm{K},$ which is the highest reported for any thermoelectric system. This ultrahigh thermoelectric performance is attained below the phase transition temperature as observed in our DSC results (Fig. 4b), affirming no overestimation of ZT by the phase transition. In comparison, p- and n-type SnSe single crystals exhibit a $\\mathrm{ZT_{\\mathrm{max}}}$ of roughly 2.6 at $923\\mathrm{K}$ (ref. 9) and 2.8 at $773\\mathrm{K}$ (ref. 11), respectively (Fig. 5d). Among the highest performance polycrystalline thermoelectric systems have been PbTe- $8\\%\\mathrm{SrTe}$ doped with $2\\%$ Na $\\mathrm{\\DeltaZT_{\\mathrm{max}}}$ roughly 2.5 at $923\\mathrm{K},$ ref. 8) and ball-milled and $\\mathrm{H}_{2}$ -reduced $\\mathrm{SnSe}{-}5\\%\\mathrm{PbSe}$ doped with $1\\%$ Na ( $\\mathrm{\\DeltaZT_{\\mathrm{max}}}$ roughly 2.5 at $773\\mathrm{K},$ ref. 12). ZT for $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.965}\\mathrm{Se}$ already exceeds unity above $473\\mathrm{K},$ at which temperature regime few materials show comparable performance. It exhibits a record-high average $Z\\mathrm{T}^{25}$ roughly 2.0 from 400 to $783\\mathrm{K}$ (Supplementary Fig. 13). The deviation in temperature-dependent ZT values on consecutive heating and cooling cycles is less than $10\\%$ , indicating the prospect of stable operation from 300 to $783\\mathrm{K}$ for thermoelectric power generation (Supplementary Figs. 14 and 15). \n\n![](images/4471bb73cbb6c8f7855655ba9a04ff60abee16c3e4e3e79d43fde57af9593bec.jpg) \nFig. 5 | Thermoelectric properties of $\\mathsf{N a}_{x}\\mathsf{S n}_{0.995-x}\\mathsf{S e}$ before and after the purification process. a, Electrical conductivity $(\\sigma)$ . b, Seebeck coefficient (S). c, Power factor (PF). d, ZT values of polycrystalline $\\mathsf{N a}_{x}\\mathsf{S n}_{0.995-x}\\mathsf{S e}$ developed in this work and current-state-of-the-art polycrystalline thermoelectrics, $2\\%N a$ -doped PbTe- $8\\%5r\\mathtt{F e}^{8}$ (filled pink) and ball-milled and ${\\sf H}_{2}$ -reduced SnSe- $.5\\%$ PbSe doped with $1\\%N a^{12}$ (filled green) and single-crystal SnSe, undoped (p-type, open orange)9, single-crystal $\\mathsf{N a}$ -doped $(\\mathsf{p}$ -type, open blue)10 and single-crystal $\\mathsf{B r}$ -doped $\\mathsf{S n S e}^{11}$ (open black). Polycrystalline samples were measured parallel to the SPS direction. The typical uncertainty of $10\\%$ for ZT estimates is given. \n\nWe conclude that a trace of $\\mathrm{SnO}_{x}$ in the starting tin metal reagent, used to prepare SnSe samples, has persistently concealed the intrinsic charge and thermal transport properties of SnSe and prevented the full thermoelectric performance from being realized. When properly purified and doped using the methods described above, polycrystalline SnSe exhibits an extraordinarily high ZT of roughly 3.1, outperforming any other bulk thermoelectric systems. The ultrahigh thermoelectric performance indeed originates from the intrinsic crystal chemistry of this simple yet remarkable binary compound SnSe, and this bodes well for the future development of this material to affect power generation applications from waste heat. This revelation has broader implications of how other systems need to be handled in the future and calls for the re-examination of synthesis and sample preparation processes for extensively studied thermoelectric systems, especially those containing tin. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of \n\nauthor contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/ s41563-021-01064-6. \n\nReceived: 3 February 2021; Accepted: 24 June 2021; Published: xx xx xxxx \n\n# References \n\n1.\t Gingerich, D. B. & Mauter, M. S. Quantity, quality, and availability of waste heat from United States thermal power generation. Environ. Sci. Technol. 49, 8297–8306 (2015). \n2.\t Jood, P., Ohta, M., Yamamoto, A. & Kanatzidis, M. G. Excessively doped PbTe with Ge-induced nanostructures enables high-efficiency thermoelectric modules. Joule 2, 1339–1355 (2018). \n3.\t Tan, G., Zhao, L.-D. & Kanatzidis, M. G. Rationally designing high-performance bulk thermoelectric materials. Chem. Rev. 116, 12123–12149 (2016). \n4.\t He, J. & Tritt, T. M. Advances in thermoelectric materials research: looking back and moving forward. Science 357, eaak9997 (2017). \n5.\t Biswas, K. et al. High-performance bulk thermoelectrics with all-scale hierarchical architectures. Nature 489, 414–418 (2012). \n6.\t Tang, Y. et al. Convergence of multi-valley bands as the electronic origin of high thermoelectric performance in $\\mathrm{CoSb}_{3}$ skutterudites. Nat. Mater. 14, 1223–1228 (2015). \n7.\t Hinterleitner, B. et al. Thermoelectric performance of a metastable thin-film Heusler alloy. Nature 576, 85–90 (2019). \n8.\t Tan, G. et al. Non-equilibrium processing leads to record high thermoelectric figure of merit in PbTe–SrTe. Nat. Commun. 7, 12167 (2016). \n9.\t Zhao, L.-D. et al. Ultralow thermal conductivity and high thermoelectric figure of merit in SnSe crystals. Nature 508, 373–377 (2014). \n10.\tZhao, L.-D. et al. Ultrahigh power factor and thermoelectric performance in hole-doped single-crystal SnSe. Science 351, 141–144 (2016). \n11.\tChang, C. et al. 3D charge and 2D phonon transports leading to high out-of-plane ZT in n-type SnSe crystals. Science 360, 778–783 (2018). \n12.\tLee, Y. K., Luo, Z., Cho, S. P., Kanatzidis, M. G. & Chung, I. Surface oxide removal for polycrystalline SnSe reveals near-single-crystal thermoelectric performance. Joule 3, 719–731 (2019). \n13.\tWei, W. et al. Achieving high thermoelectric figure of merit in polycrystalline SnSe via introducing Sn vacancies. J. Am. Chem. Soc. 140, 499–505 (2018). \n14.\tLee, Y. K. et al. Enhancing p-type thermoelectric performances of polycrystalline SnSe via tuning phase transition temperature. J. Am. Chem. Soc. 139, 10887–10896 (2017). \n15.\tWei, P. C. et al. The intrinsic thermal conductivity of SnSe. Nature 539, E1–E2 (2016). \n16.\tZhao, L.-D., Chang, C., Tan, G. & Kanatzidis, M. G. SnSe: a remarkable new thermoelectric material. Energy Environ. Sci. 9, 3044–3060 (2016). \n17.\tRoy, S., Joshi, A. G., Chatterjee, S. & Ghosh, A. K. Local symmetry breaking in $\\mathrm{SnO}_{2}$ nanocrystals with cobalt doping and its effect on optical properties. Nanoscale 10, 10664–10682 (2018). \n18.\tYu, Y. et al. Revealing nano-chemistry at lattice defects in thermoelectric materials using atom probe tomography. Mater. Today 32, 260–274 (2020). \n19.\tYe, X. et al. Magnetoelectric tuning of pinning-type permanent magnets through atomic-scale engineering of grain boundaries. Adv. Mater. 33, 2006853 (2021). \n20.\tGault, B., Moody, M. P., Cairney, J. M. & Ringer, S. P. Atom Probe Microscopy (Springer Science & Business Media, 2012). \n21.\tSlade, T. J. et al. Understanding the thermally activated charge transport in $\\mathrm{NaPb}_{m}\\mathrm{SbQ}_{m+2}$ ( $\\mathrm{Q}=\\mathrm{S},$ , Se, Te) thermoelectrics: weak dielectric screening leads to grain boundary dominated charge carrier scattering. Energy Environ. Sci. 13, 1509–1518 (2020). \n22.\t Kuo, J. J., Wood, M., Slade, T. J., Kanatzidis, M. G. & Snyder, G. J. Systematic over-estimation of lattice thermal conductivity in materials with electrically-resistive grain boundaries. Energy Environ. Sci. 13, 1250–1258 (2020). \n23.\t Lin, H. et al. Concerted rattling in $\\mathrm{CsAg_{5}T e_{3}}$ leading to ultralow thermal conductivity and high thermoelectric performance. Angew. Chem. Int. Ed. 55, 11431–11436 (2016). \n24.\tChiritescu, C. et al. Ultralow thermal conductivity in disordered, layered $\\mathrm{WSe}_{2}$ crystals. Science 315, 351–353 (2007). \n25.\tQin, B. et al. Ultrahigh average ZT realized in p-type SnSe crystalline thermoelectrics through producing extrinsic vacancies. J. Am. Chem. Soc. 142, 5901–5909 (2020). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons. org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 \n\n# Methods \n\nNote. All procedures for the synthesis and sample preparations were strictly carried out in an Ar-filled glovebox $(99.99\\%$ purity), in which the levels of moisture and oxygen are kept at 0 and less than 1 ppm, respectively, unless noted otherwise. When samples were transported from the glovebox for measurements and compaction processes, they were properly protected under a mobile Ar flowing system. \n\nReagents. The following starting reagents were used as received unless noted otherwise: Se shot $(99.999\\%$ , 5N Plus) and Na piece $(99.9\\%$ , Sigma-Aldrich). As-received Sn chunk $(99.999\\%$ , American Elements) was used to synthesize ‘untreated’ SnSe-based materials as control samples. It was purified by our melting-purification process as described below to eliminate surface tin oxides, and was used to synthesize ‘purified’ SnSe-based materials. \n\nPurification of Sn. As-received Sn chunks were apparently silvery. They were placed on a graphite sheet prewashed with ethanol, and were heated at $473\\mathrm{K}$ , which is near the melting point of $\\scriptstyle\\mathrm{Sn}$ at roughly $505\\mathrm{K},$ for $^{6\\mathrm{h}}$ under a $4\\%\\mathrm{H}_{2}/96\\%$ Ar with a flow rate of $200\\mathrm{ml}\\mathrm{min}^{-1}$ . A change in their surface colour and lustre was invisible. The resulting Sn chunks were loaded into a carbon-coated and evacuated fused-silica tube (roughly $10^{-4}\\mathrm{Torr}\\$ ). The tube was heated at $^{1,273\\mathrm{K}}$ for $6\\mathrm{h}$ , followed by cooling to room temperature. Ash-like black residues formed at the top and surface of the Sn ingot. They were identified as tin oxides by Fourier transformed far-infrared absorption spectroscopy. They were scraped out of the Sn ingot. The same melting-purification process was repeated three times at 873–723 K until the black residues were no longer observed. \n\nSynthesis. Purified and untreated materials with the nominal compositions $\\mathrm{Na}_{x}\\mathrm{Sn}_{0.995-x}\\mathrm{Se}$ $(x=0.01-0.03)$ and SnSe as a reference were synthesized by reacting stoichiometric mixtures of proper starting reagents. They were loaded in carbon-coated and evacuated fused-silica tubes (roughly $10^{-4}\\mathrm{Torr}^{\\cdot}$ , and were heated at $^{1,223\\mathrm{K}}$ for $12\\mathrm{h}$ , followed by quenching to ice water. The obtained ingots were further annealed at $773\\mathrm{K}$ for $48\\mathrm{h}$ and were cooled naturally to room temperature. The weight of typical ingots was approximately $13\\mathrm{g}$ They were pulverized by hand-grinding, and were subsequently purified at $613\\mathrm{K}$ for $6\\mathrm{h}$ under a $4\\%$ $\\mathrm{H}_{2}/96\\%$ Ar with a flow rate of $200\\mathrm{ml}\\mathrm{min}^{-1}$ . \n\nCompacting powders. The resulting powders were loaded in a BN-coated graphite die and were cold-pressed manually in an Ar-filled glovebox. To avoid any possible oxidation of a sample, the loaded die was tightly sealed in a plastic zipper bag and taken out of the glovebox. It was transported from the chamber of the glovebox to the adjacently placed SPS system (SPS-211Lx, Fuji Electronic Industrial Co.) under a mobile Ar $(99.99\\%)$ ) flowing system. Powder samples in the die were densified at roughly $783\\mathrm{K}$ for $5\\mathrm{{min}}$ under an axial pressure of $50\\mathrm{\\:MPa}$ in a vacuum of roughly $1.4\\times10^{-2}$ Torr using SPS. All SPS-processed samples show relative densities of roughly $96\\%$ . \n\nPowder X-ray diffraction. We carried out X-ray diffraction analysis on a SmartLab Rigaku X-ray diffractometer with Cu Kα $\\begin{array}{r}{\\dot{\\lambda}=1.\\dot{5}418\\mathring\\mathrm{A}\\dot{\\mathrm{A}},}\\end{array}$ graphite-monochromatized radiation operating at $40\\mathrm{kV}$ and $30\\mathrm{mA}$ at room temperature. The patterns measured parallel and perpendicular to the pressing direction of the SPS-processed ingots for purified and untreated SnSe and $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.965}\\mathrm{Se}$ samples are given in Supplementary Figs. 16 and 17. \n\nTOF–SIMS. TOF–SIMS experiments were carried out on a Physical Electronics TRIFT III spectrometer. The SPS-processed samples were polished with Buehler Ecomet III Tabletop Polisher/Grinder to prepare a smooth surface. Subsequently, they were sputtered with a $5\\mathrm{keV}$ Ar ion beam for $5\\mathrm{{min}}$ in SIMS chamber to expose the GB. During this process, omnipresent $\\mathrm{H}_{2}\\mathrm{O}$ even in an ultrahigh vacuum chamber was ionized to give $\\mathrm{H^{+}}$ , which then attached to surface tin oxides to form $\\mathrm{\\SnOH^{+}}$ . Accordingly, to examine the distribution of surface tin oxides, the $\\operatorname{SnOH^{+}}$ ion mapping images were collected for $10\\mathrm{min}$ . The primary ion source of SIMS is gallium beam with $25\\mathrm{keV}$ energy. The measurements were conducted in NUANCE-Keck-II centre of Northwestern University. \n\nHall measurements. The Hall coefficients $(R_{\\mathrm{H}})$ were obtained by the Van der Pauw method on a Lake Shore HMS8407 Hall effect measurement system in a magnetic field of $1.5\\mathrm{T}$ and $3\\mathrm{mA}$ excitation current. The hole carrier concentration $(n_{\\mathrm{H}})$ and hole mobility $(\\mu_{\\mathrm{H}})$ were accessed by the formulas, $n_{\\mathrm{H}}{=}1/(\\mathrm{e}R_{\\mathrm{H}})$ and $\\mu_{\\mathrm{{H}}}=R_{\\mathrm{{H}}}\\sigma,$ respectively. \n\nElectrical and thermal transport property measurements. The obtained SPS-processed pellets were cut and polished into a rectangular shape with a length of $13\\mathrm{mm}$ and thickness of roughly $2\\mathrm{mm}$ under a $\\Nu_{2}$ atmosphere $(99.99\\%$ purity) (Supplementary Fig. 18). The electrical conductivity and Seebeck coefficient were measured simultaneously under an Ar atmosphere from room temperature to $823\\mathrm{K}$ using a Netzsch SBA 458 Nemesis system. A Netzsch LFA 457 MicroFlash instrument was used to record the thermal diffusivity of the samples coated with graphite. The typical samples are disc shaped with a diameter of $8\\mathrm{mm}$ and thickness ranging from 1 to $2\\mathrm{mm}$ . To confirm the reproducibility of ultralow \n\nthermal conductivity of the $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.965}\\mathrm{Se}$ samples, the thermal diffusivity was cross-checked at Northwestern University and Netzsch Instruments (Korea) using LFA 457 and 467 instruments, respectively (Supplementary Figs. 19–21). The thermal conductivity was calculated from the formula $\\kappa_{\\mathrm{{tot}}}=D C_{\\mathrm{{p}}}\\rho$ where $D$ is the thermal diffusivity, $C_{\\mathfrak{p}}$ is the heat capacity, which was directly measured using the DSC technique, and $\\rho$ is the mass density of the specimens. The $\\rho$ value used was obtained by their geometrical dimensions and masses, which is nearly the same as that by the Archimedes method. The density values used are given in Supplementary Table 1. The total thermal conductivity $\\kappa_{\\mathrm{{tot}}}$ is the sum of the lattice $(\\kappa_{\\mathrm{lat}})$ and electronic thermal $(\\kappa_{\\mathrm{ele}})$ conductivities. $\\kappa_{\\mathrm{ele}}$ is proportional to the electrical conductivity $(\\sigma)$ according to the Wiedemann–Franz relation $(\\kappa_{\\mathrm{ele}}=L\\upsigma T)$ , where $L$ is the temperature-dependent Lorenz number and $T$ is the absolute temperature. The $\\kappa_{\\mathrm{lat}}$ value was calculated by subtracting the $\\kappa_{\\mathrm{ele}}$ from the $\\kappa_{\\mathrm{{tot}}}$ value by the relation $\\kappa_{\\mathrm{lat}}=\\kappa_{\\mathrm{tot}}-\\kappa_{\\mathrm{ele}}$ . Average ZT $(Z\\mathrm{T_{ave}})$ was calculated using the following equation25: \n\n$$\n\\mathrm{ZT_{ave}}=\\frac{\\int_{T_{\\mathrm{cold}}}^{T_{\\mathrm{hot}}}{\\mathrm{ZTd}T}}{T_{\\mathrm{hot}}-T_{\\mathrm{cold}}}\n$$ \n\nwhere $T_{\\mathrm{hot}}$ and $T_{\\mathrm{cold}}$ represent the temperature at the hot and cold sides, respectively. \n\nHeat capacity measurements. The temperature-dependent heat capacity $(C_{\\mathrm{p}})$ was experimentally recorded by differential scanning calorimeter (DSC Polyma 214, Netzsch). To minimize the error, samples were cut into a cube with dimensions of roughly $2\\times2\\times2\\operatorname*{mm}^{3}$ . Because $\\mathrm{{Na}}$ easily reacts with typical ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ or Al crucibles, Pt crucibles were used. Before the measurement, the blank crucible was heated to $823\\mathrm{K}$ at least twice under a high-purity argon $(99.999\\%$ ) flow to remove any possible residual water and physisorbed $\\mathrm{~O}_{2}$ . Afterwards, a standard sapphire disc with a diameter of $4\\mathrm{mm}$ and a thickness of $0.25\\mathrm{mm}$ was loaded into the crucible and measured up to $823\\mathrm{K}$ . Subsequently, the standard sapphire was taken out, and the $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.965}\\mathrm{Se}$ sample was placed in the same crucible. The loaded crucible was purged with a high-purity argon flow for $30\\mathrm{min}$ to ensure a dry and air-free atmosphere before the measurement. The $C_{\\mathfrak{p}}$ was extracted by comparing the signal difference between the reference sapphire and sample26. \n\nSTEM. STEM specimens were excised from the GB using a dual-beam scanning electron microscope/focused ion beam (Helio NanoLab 650, FEI) system using gallium ion milling. Before the ion milling, the surface of specimens was protected with carbon coating by sputtering. Structures and chemical compositions around GBs were analysed using a spherical aberration-corrected JEM ARM-200F microscope (Cold FEG Type, JEOL) equipped with an SDD type energy-dispersive X-ray spectroscopy (EDS) detector (Solid Angle 0.9-sr, X-MaxN 100TLE, Oxford) at $200\\mathrm{kV}$ installed at the National Centre for Inter-University Research Facilities in SNU. In HAADF–STEM images, the point-to-point resolution was approximately $80\\mathrm{pm}$ after correcting the spherical aberration, and the angular range of the annular detector used was from 68 to $280\\mathrm{{mrad}}$ . All STEM images were recorded using a high-resolution CCD detector with a $2,000\\times2,000$ -pixel device in the GIF-QuantumER imaging filter (Gatan). For STEM–EDS investigation, chemical maps were acquired with a probe size of $0.13\\mathrm{nm}$ and a probe current of $40\\mathrm{pA}$ . \n\nAPT. APT needle-shaped specimens were prepared using a dual-beam scanning electron microscope/focused ion beam (Helios NanoLab 650, FEI) following the site-specific ‘lift-out’ method27. The specimens were measured in a local electrode atom probe (LEAP $4000{\\mathrm{XSi}}$ , Cameca) with voltage- and laser-assisted evaporation modes for the Sn reagent and SnSe samples, respectively. For a voltage mode, a voltage pulse with a repetition rate of $200\\mathrm{kHz}$ and pulse fraction of $20\\%$ was used. The detection rate was five ions per 1,000 pulses $(0.5\\%)$ on average. The base temperature of specimen was $30\\mathrm{K}.$ For a laser mode, a 5 pJ ultraviolet (wavelength, $355\\mathrm{nm}$ ) laser with $10\\mathrm{ps}$ pulse and a $200\\mathrm{kHz}$ repetition rate was used. The detection rate was one ion per 100 pulses $(1\\%)$ on average. For both modes, the base temperature was $40\\mathrm{K}$ and the ion flight path was $160\\mathrm{mm}$ . The detection efficiency was limited to $50\\%$ due to the open area of the microchannel plate. The APT data were processed using the software package IVAS v.3.8.0 (ref. 18). \n\nCalculations for phonon band structure and Grüneisen parameters. Phonon band structure and Grüneisen parameters were calculated within quasi-harmonic approximations based on DFT calculations. They have been calculated for pristine SnSe previously9. In this work, we further calculated them for the optimally hole-doped system, namely, $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.97}\\mathrm{Se}$ . To obtain accurate force constant matrix, we used a $2\\times2\\times2$ supercell for $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.97}\\mathrm{Se}$ with 64 atoms, and accordingly the supercell accommodates 512 atoms in total. For better comparison, we also considered the same size of supercell for pristine SnSe. DFT force calculations were performed with a plane wave set of $350\\mathrm{eV}$ energy cutoff, gamma point $k$ -space sampling and PBEsol exchange functional28, and they were forced to converge until the largest component of atomic force becomes smaller than $10^{-8}\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . To evaluate the Grüneisen parameters defined by the relation $\\begin{array}{r}{\\gamma_{i}=-\\frac{V}{\\omega_{i}}\\frac{\\partial\\omega_{i}}{\\partial\\mathrm{V}},}\\end{array}$ where $V$ is the volume of unit cell and $\\omega_{i}$ is frequency of $i$ -th phononγ imode,ωwi e∂Vconsidered three sets of phonon dispersion relation with different volumes, namely, 0.99, 1.00 and 1.01 times the optimized volume of the unit cell. Calculation results are presented in Supplementary Fig. 6. \n\nCalculations for electronic band structure. To understand the enhanced Seebeck coefficient by Na doping, we obtained electronic band structures for hole-doped $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.97}\\mathrm{Se}$ and pristine $\\mathrm{SnSe}$ using DFT calculations with plane wave basis set with $350\\mathrm{eV}$ energy cutoff, $4\\times4\\times4k$ -space sampling, and $\\mathrm{SCAN+rVV10}$ functional29. We used a $2{\\sqrt{2}}\\times2{\\sqrt{2}}\\times1$ supercell, and the lattice parameters and internal coordinates wer2e fu2lly o2pti2mized. On Na doping, the lattice dimension decreases by about $0.5\\%$ along the $b$ and $c$ axes and increases by about $0.3\\%$ along the $a$ axis. \n\nIt should be noted that the recent investigation by angle-resolved photon emission spectroscopy (ARPES) for SnSe clearly shows the emergence of pudding mould-type bands near valence band maximum30, which is highly important for achieving high power factor within the band convergence strategy. However, many previous DFT studies for SnSe using semilocal exchange-correlation functional such as Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation could not reproduce band structures observed by the ARPES appropriately. In this work, we found that such band dispersions in SnSe seen by the ARPES experiments can be well reproduced by $\\mathrm{SCAN+rVV10}$ functional. Accordingly, we applied the same method to hole-doped $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.97}\\mathrm{Se}$ We considered a 64-atom-containing supercell for both SnSe and $\\mathrm{Na}_{0.03}\\mathrm{Sn}_{0.97}\\mathrm{Se}$ . Band structures are evaluated along a high-symmetric line in $k$ -space. For density of states, we used a denser $10\\times10\\times10$ regular mesh. Calculation results are given in Supplementary Fig. 11. \n\n# Data availability \n\nThe datasets for Figs. 1–5 are available in the source data section. Additional information is available from the authors on request. Source data are provided with this paper. \n\n# Code availability \n\nThe computer codes that support the findings of this study are available from the corresponding author on reasonable request. \n\n# References \n\n26.\tRudtsch, S. Uncertainty of heat capacity measurements with differential scanning calorimeters. Thermochim. Acta 382, 17–25 (2002). \n27.\tMiller, M. K. & Russell, K. F. Atom probe specimen preparation with a dual beam SEM/FIB miller. Ultramicroscopy 107, 761–766 (2007). \n28.\tPerdew, J. P. et al. Restoring the density-gradient expansion for exchange in solids and surfaces. Phys. Rev. Lett. 100, 136406 (2008). \n29.\tPeng, H., Yang, Z. H., Perdew, J. P. & Sun, J. Versatile van der Waals density functional based on a meta-generalized gradient approximation. Phys. Rev. X 6, 041005 (2016). \n\n30.\tPletikosić, I. et al. Band structure of the IV-VI black phosphorus analog and thermoelectric SnSe. Phys. Rev. Lett. 120, 156403 (2018). \n\n# Acknowledgements \n\nThe work at SNU was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (no. NRF-2020R1A2C2011111), Nano Material Technology Development Program through the NRF grant funded by the Korean Government (MSIP) (nos. NRF-2017M3A7B4049274 and NRF2017M3A7B4049273), the IBS (grant no. IBS-R009-G2) and LG Chem. The Northwestern personnel and research work were supported by the Department of Energy, Office of Science, Basic Energy Sciences under grant no. DE-SC0014520. The work at Northwestern was supported by the Department of Energy, Office of Science, Basic Energy Sciences under grant no. DE-SC0014520 (materials characterization and physical properties measurements). This work also made use of the EPIC and Keck facilities of Northwestern University’s NUANCE Centre, which has received support from the Soft and Hybrid Nanotechnology Experimental Resource (grant no. NSF ECCS1542205); the MRSEC program (grant no. NSF DMR-1720139) at the Materials Research Centre; the International Institute for Nanotechnology (IIN); the Keck Foundation and the State of Illinois, through the IIN. Parts of the text in this work have been reproduced from the thesis by Y.K.L., at SNU, and is accessible at https://s-space.snu.ac.kr/ bitstream/10371/169453/1/000000162714.pdf. \n\n# Author contributions \n\nM.G.K. and I.C. conceived and designed the experiments. C.Z., Y.K.L., S.B., H.L., B.G. and I.C. synthesized the samples and characterized their properties. Z.-Z.L. and M.G.K. cross-checked thermoelectric properties. X.C. and V.P.D. performed TOF–SIMS characterizations, and contributed to overall interpretation of data and their implications. Y.Y., J.Y.L., O.C.M. and M.W. collected APT data. Y.-L.L., H.C. and J.I. carried out theoretical calculations. S.-P.C. performed TEM characterizations. M.G.K. and I.C. wrote the manuscript with discussion and input from all authors. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41563-021-01064-6. Correspondence and requests for materials should be addressed to M.G.K. or I.C. Peer review information Nature Materials thanks Baptiste Gault and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at www.nature.com/reprints. " + }, + { + "id": "10.1016_j.joule.2021.06.020", + "DOI": "10.1016/j.joule.2021.06.020", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2021.06.020", + "Relative Dir Path": "mds/10.1016_j.joule.2021.06.020", + "Article Title": "Reduced non-radiative charge recombination enables organic photovoltaic cell approaching 19% efficiency", + "Authors": "Bi, PQ; Zhang, SQ; Chen, ZH; Xu, Y; Cui, Y; Zhang, T; Ren, JZ; Qin, JZ; Hong, L; Hao, XT; Hou, JH", + "Source Title": "JOULE", + "Abstract": "Reducing non-radiative charge recombination is of critical importance to achieving high- performance organic photovoltaic (OPV) cells. The correlation between the exciton behaviors and non-radiative charge recombination is rarely studied. In this work, we achieved an increase in the exciton diffusion length (L-D) in the acceptor phase via introducing HDO-4Cl to the PBDB-TF: eC9-based system. Compared with the eC9-based film, the exciton L-D in the HDO- 4Cl: eC9-based film is increased from 12.2 to 16.3 nm. The enlarged exciton L-D can obviously decrease the non- radiative charge recombination and increase the efficiency of photon utilization in the PBDB-TF: eC9-based OPV cell. Finally, we not only obtained an outstanding power conversion efficiency (PCE) of 18.86% but also demonstrated the correlations between the nonradiative energy loss and exciton behaviors. The results show that regulating the exciton behaviors is an effective way to reduce the non-radiative energy loss and realize high-efficiency OPV cells.", + "Times Cited, WoS Core": 479, + "Times Cited, All Databases": 494, + "Publication Year": 2021, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000696854300014", + "Markdown": "# Article Reduced non-radiative charge recombination enables organic photovoltaic cell approaching 19% efficiency \n\nPengqing Bi, Shaoqing Zhang, Zhihao Chen, ..., Ling Hong, Xiaotao Hao, Jianhui Hou \n\nshaoqingz@iccas.ac.cn (S.Z.) hjhzlz@iccas.ac.cn (J.H.) \n\n# Highlights \n\nCorrelations between nonradiative energy loss and exciton behaviors are revealed \n\n![](images/18c4bf5458149ac31214227f320b4c51ed2144ce1861dcc3056f5de5f706601a.jpg) \n\nThe exciton-diffusion length can be effectively enlarged through ternary strategy \n\nA high PCE approaching $19\\%$ is demonstrated \n\nSuppressing the non-radiative energy loss by optimizing the exciton behaviors in PBDB-TF:eC9-based organic photovoltaic (OPV) cells is demonstrated in this work. The exciton diffusion length and exciton lifetime in the active layer based on PBDBTF:eC9 are enhanced via introducing HDO-4Cl, resulting in the obvious reduction in the non-radiative charge recombination in the corresponding OPV cell. As a result, a high PCE of $18.86\\%$ is achieved in the single-junction OPV cell. \n\n# Article Reduced non-radiative charge recombination enables organic photovoltaic cell approaching 19% efficiency \n\nPengqing Bi,1 Shaoqing Zhang,2,\\* Zhihao Chen,3 Ye Xu,1,4 Yong Cui,1 Tao Zhang,1 Junzhen Ren,1 Jinzhao Qin,1,4 Ling Hong,1 Xiaotao Hao,3 and Jianhui Hou1,4,5,\\* \n\n# SUMMARY \n\nReducing non-radiative charge recombination is of critical importance to achieving high-performance organic photovoltaic (OPV) cells. The correlation between the exciton behaviors and non-radiative charge recombination is rarely studied. In this work, we achieved an increase in the exciton diffusion length $(L_{\\mathsf{D}})$ in the acceptor phase via introducing HDO-4Cl to the PBDB-TF:eC9-based system. Compared with the eC9-based film, the exciton $L_{\\mathsf{D}}$ in the HDO-4Cl:eC9-based film is increased from 12.2 to $16.3\\ \\mathsf{n m}$ . The enlarged exciton LD can obviously decrease the non-radiative charge recombination and increase the efficiency of photon utilization in the PBDB-TF:eC9-based OPV cell. Finally, we not only obtained an outstanding power conversion efficiency (PCE) of $18.86\\%$ but also demonstrated the correlations between the nonradiative energy loss and exciton behaviors. The results show that regulating the exciton behaviors is an effective way to reduce the non-radiative energy loss and realize high-efficiency OPV cells. \n\n# INTRODUCTION \n\nDesirable properties, such as being lightweight, having tunable absorption spectra and mechanical flexibility, etc., make organic photovoltaic (OPV) cells a promising clean energy technology.1–5 The innovations in device engineering, photophysics, and materials have greatly promoted the development of OPV cells.6–12 Up to date, the power conversion efficiencies (PCEs) of the state-of-the-art OPV cells have approached $18\\%$ .13–15 However, further improvement in PCE is still one of the focus areas in the development of OPV technology. In comparison with the inorganic counterparts, such as silicon-, perovskite-, and GaAs-based cells, the relatively large energy loss $\\langle E_{\\mathrm{loss}}\\rangle$ is one of the main factors that restricts the further improvement in PCE of OPV cells.16,17 \n\nIt has been recognized that the $\\boldsymbol{E}_{\\mathrm{loss}}$ in an OPV cell is originated in two parts, the energy losses caused by radiative and non-radiative charge recombination $(E_{\\mathrm{loss.}}$ rad and $\\boldsymbol{E}_{\\mathrm{loss}}$ , non-rad).18 At present, for some of the high-performance non-fullerene acceptors (NFAs)-based OPV cells, there is almost no room for further reducing the $E_{\\mathrm{loss.}}$ rad.19–21 In contrast, the relatively large $E_{\\mathrm{loss}}$ , non-rad plays a key role in determining the performance of OPV cells, and as for prediction, PCE over $21\\%$ could be achieved in OPV cells if the Eloss, non-rad could be decreased to ca. $0.13\\mathrm{eV}$ .22 Currently, synthesizing new types of materials and optimizing the nanomorphology of the active layers are two main strategies employed to suppress the Eloss, non-rad, which can be calculated by the equation of $E_{|\\mathrm{oss,~non-rad}}=-\\mathsf{k T}|\\mathsf{n}(E\\Omega E_{\\mathsf{E}\\mathsf{L}}),$ , \n\n# Context & scale \n\nOrganic photovoltaic (OPV) cells have recently emerged as costeffective and energy-efficient candidates of green energy sources. Further improvement in power conversion efficiency (PCE) is still needed for practical application. Compared with the inorganic photovoltaic cells, the non-radiative energy loss (Eloss, non-rad) in OPV cell is relatively large. Therefore, reducing the Eloss, non-rad is an effective way to achieve a breakthrough in the PCE of OPV cells. In addition to material synthesis and morphology optimization, optimizing exciton behaviors is also crucial to reduce the Eloss, non-rad and, thus, enhance the state-of-art high-performance OPV cells. In this work, the exciton diffusion length in PBDB-TF:eC9- based active layer is effectively enhanced through introducing a third component named HDO4Cl. As a result, we not only achieved an outstanding PCE of approaching $19\\%$ but also revealed the correlations between the Eloss, non-rad and exciton behaviors. \n\nwhere $E\\mathsf{O}\\mathsf{E}_{\\mathsf{E}^{\\mathsf{L}}}$ is the external quantum efficiency of the electroluminescence (EL) for an OPV cell, $k$ is the Boltzmann constant, and $\\tau$ is the absolute temperature.23 For example, the $E O\\mathsf{E}_{\\mathsf{E}}_{\\mathsf{L}}$ of fullerene-based OPV cells are typically below $10^{-6}$ , corresponding to the $E_{\\mathrm{loss.}}$ , non-rad values over $0.4\\ \\mathrm{eV},^{24}$ and the relatively large $E_{\\mathrm{loss}.}$ non-rad limit their PCEs to be lower than $12\\%$ .25 The OPV cells based on IT-4F, a derivative of the famous ITIC-family acceptors, exhibited a higher $E\\mathsf{O}\\mathsf{E}_{\\mathsf{E}^{\\mathsf{L}}}$ reaching the order of $10^{-4}$ , leading to a PCE of approximately $15\\%$ .26 More recently, the $E\\mathsf{O}\\mathsf{E}_{\\mathsf{E}^{\\mathsf{L}}}$ values over $10^{-3}$ were demonstrated in the Y6- and its derivative-based OPV cells, resulting in further improvement in PCEs.27 The ternary strategy, introducing the third components into the binary photoactive layers, could have also been employed to modulate the phase separation morphology and reduce the $\\boldsymbol{E}_{\\mathrm{loss}}$ , non-rad.28,29 Nowadays, although the methods to modulate the Eloss, non-rad have been established, the potential of the exiting photoactive materials may not have been fully explored and also the photophysics behind them have not been completely revealed. \n\nThe photogenerated excitons in organic molecules usually have relatively large binding energy values due to the low dielectric constants.30,31 As charge dissociation efficiency that occurs at the donor/acceptor interface determines photo-generated current densities of the OPV cells and the excitons cannot diffuse to the interface will annihilate; thus, the diffusion length $(L_{\\mathrm{D}})$ of the excitons plays a critical role in photoelectric conversion process. For instance, Holmes et al. reported that the PCE of an OPV cell increased by $30\\%$ when the $L_{\\mathsf{D}}$ was enlarged32; Adachi et al. demonstrated an almost linear correlation between the short-circuit current density $(J_{S C})$ and the $L_{\\mathsf{D}}$ .33 According to the reported works, the domain sizes in the NFA-based OPV cells are in the range of $20{-}50~\\mathsf{n m}$ , which may exceed variations of exciton LD.34,35 Therefore, a larger $L_{\\mathsf{D}}$ is desirable to restrain charge recombination in the state-of-the-art OPV cells so as to further improve their PCEs. \n\nIn this work, we suppressed the $\\boldsymbol{E}_{\\mathrm{loss}}$ , non-rad and significantly improved photovoltaic performance of a high-performance OPV cell by introducing a third component into its photoactive layer. We investigated phase separation morphologies of the photoactive layers and found that the third component, HDO-4Cl, prefers to form an alloylike acceptor phase with the acceptor, eC9, in the photoactive layer. By the ultrafast spectroscopy and photoelectrical measurements, we found that the addition of HDO-4Cl leads to a significantly enlarged exciton $L_{\\mathsf{D}}$ and obviously suppressed non-radiative charge recombination. As a result, the best ternary OPV cell demonstrated a PCE of $18.86\\%$ , which is not only much higher than the binary counterpart but also the highest value for the OPV cells reported so far. \n\n# RESULTS AND DISCUSSION \n\nThe molecular structures of PBDB-TF, HDO-4Cl, and eC9 are shown in Figure 1A. HDO-4Cl and eC9 have very similar molecular structures, including the same backbones and end-groups. The absorption spectra of the neat and blend films are shown in Figures 1B and S1A. The absorption peaks of HDO-4Cl and eC9 are located at 775 and $835{\\mathsf{n m}}$ , respectively. The HDO-4Cl:eC9 blend film with a weight ratio of 0.2:1, the optimal value used in the ternary photoactive layers, shows a blue shift of $20~\\mathsf{n m}$ compared with the neat film of eC9. In the PBDB-TF:HDO-4Cl and PBDBTF:eC9 blend films, the absorption peaks originated from the polymer donor and the NFAs can be clearly distinguished. Interestingly, the absorption spectrum of the PBDB-TF:HDO-4Cl:eC9 blend film is very similar to that of PBDB-TF:eC9 blend film, indicating that the blue shift observed in the HDO-4Cl:eC9 blend film almost \n\n![](images/3b9800d39c8faa081c9bdb6fa9cee29081423e0abbf7cc0bcc3364ce22409a79.jpg) \nFigure 1. Basic properties of the active layer materials used in this study \n\n(A) Chemical structures of PBDB-TF, HDO-4Cl, and eC9. \n(B) The absorption spectra of the neat and the HDO-4Cl:eC9 blend films. \n(C) The PL spectra of the neat and the HDO-4Cl:eC9 blend films. \n(D) Energy levels of PBDB-TF, HDO-4Cl, and eC9. \n(E) Contact angle images of water and glycerol droplets on the neat films of PBDB-TF, HDO-4Cl, and eC9. \n(F) XRD spectra of the eC9, HDO-4Cl:eC9, and HDO-4Cl films. \n\ndisappears. The PL spectra of neat and blend films are shown in Figures 1C and S1B. Whether PBDB-TF is used or not, the films with eC9 and HDO-4Cl:eC9 demonstrate very similar PL spectra. The cyclic voltammetry (CV) curves and the corresponding molecular energy levels of PBDB-TF, HDO-4Cl, and eC9 are shown in Figures 1D and S1C. The HOMO/LUMO levels of HDO-4Cl and eC9 are $-5.60/-3.81$ and $-5.66/-3.96\\mathrm{eV},$ respectively. \n\nThe distribution of the third component in the ternary blend is crucial for the ternary OPV cells.29,36 Herein, contact angle measurement was employed to evaluate the miscibility between PBDB-TF, HDO-4Cl, and eC9. The corresponding images of water and glycerol droplets on the neat films are shown in Figure 1E and the detailed calculations of interfacial tensions are exhibited in the supplemental information. The interfacial tension between HDO-4Cl and eC9 (gHDO-4Cl-eC9) is approximately $0.18~\\mathsf{m N}~\\mathsf{m}^{-1}$ , which is much smaller than that for PBDB-TF/eC9 (gPBDB-TF-eC9 $\\approx$ $1.52\\mathsf{m N}\\mathsf{m}^{-1})$ and PBDB-TF/HDO-4Cl $(\\gamma_{P B D B-T F-H D O-4C I}\\approx0.74\\boldsymbol{\\mathrm{m}}\\boldsymbol{\\mathrm{N}}\\boldsymbol{\\mathrm{m}}^{-1})$ . The results imply that HDO-4Cl and eC9 prefer to form an alloy-like phase in the ternary blend.37–39 X-ray diffraction (XRD) was used to gain more insight into the miscibility of eC9 and HDO-4Cl. As shown in Figure 1F, the neat films of eC9 and HDO-4Cl demonstrate characteristic diffraction peaks at around $28.8^{\\circ}$ and $33.2^{\\circ}$ . However, for the blend film of HDO-4Cl:eC9, the characteristic diffractions of HBO-4Cl disappear completely, whereas the diffractions of eC9 remain. The results indicate that only one crystallization pattern is formed in the HDO-4Cl:eC9-based film. Furthermore, we have measured the photoluminescence quantum yield (PLQY) of the acceptors in binary cell (eC9) and in ternary cell (HDO-4Cl:eC9), and the PLQY values of eC9 and HDO-4Cl:eC9 are $2.3\\%$ and $4.2\\%$ , respectively. The PLQY of \n\nTable 1. Summary of photovoltaic parameters of the binary and ternary cells \n\n\n
Voc (V) Jsc (mA cm-2) Cal. Jsc (mA cm-2) FF (%)PCEa (%)
PBDB-TF:eC9 Devices0.84626.5826.1078.5017.65 (17.40±0.25)
PBDB-TF:HDO-4CI:eC90.86627.0526.6180.5118.86 (18.54±0.18)
PBDB-TF:HDO-4Cl:eC9b 0.86426.6879.518.3
PBDB-TF:HDO-4CI0.95721.5220.2274.5815.36 (15.03±0.21)
\n\naAverage values with standard deviation are obtained from 10 devices. bCertified by National Institute of Metrology, China (NIM, China). \n\nHDO-4Cl:eC9 blend is obviously higher than the pristine eC9, indicating that the coplanar conjugate system should be formed in the HDO-4Cl:eC9 blend, confirming the formation of the alloy-like phase.36 \n\nThe OPV cells were fabricated to study the effect of HDO-4Cl on the photovoltaic performance. The device architecture and the detailed device fabrication procedures are provided as supplemental information. The current density versus voltage $(J-V)$ curves and the corresponding device parameters are shown in Figures 2A and S2A and Tables 1 and S1. Besides, the transmittance of ITO-glass used in this work is shown in Figure S2B. The binary reference cell based on PBDB-TF:eC9 demonstrates the best PCE of $17.65\\%$ , with an open-circuit voltage $(V_{\\mathrm{OC}})$ of $0.846\\ \\vee,$ a $J_{S C}$ of $26.58~\\mathsf{m A}$ $\\mathsf{c m}^{-2},$ , and a fill factor (FF) of $78.50\\%$ . The best cell based on PBDB- TF:HDO-4Cl shows a PCE of $15.36\\%$ , with a high $V_{\\mathrm{OC}}$ of $0.957\\:\\forall,$ a $J_{S C}$ of $21.52~\\mathsf{m A}~\\mathsf{c m}^{-2}$ , and an FF of $74.58\\%$ . As shown in Figure S2A and Table S1, the addition of HDO-4Cl has great impact on the photovoltaic properties of the binary cells. An outstanding PCE of $18.86\\%$ is recorded by adding 20 wt $\\%$ of HDO-4Cl. In detail, compared with the PBDB-TF:eC9-based binary cell, this ternary cell shows higher photovoltaic parameters, i.e., $V_{\\mathrm{OC}}=0.866\\:\\forall.$ , $J_{\\mathsf{S C}}=27.05\\mathsf{m A c m}^{-2}$ , and F $:F=80.51\\%$ . The external quantum efficiency (EQE) spectra of the best binary and ternary cells are shown in Figure 2B. Compared with the PBDB-TF:eC9-based device, obvious enhancement in EQE in the range from 650 to $850~\\mathsf{n m}$ is observed. Clearly, the significantly boosted $J_{S C}$ for the ternary cell is ascribed to the enhanced EQE. Besides, the integrated current densities from the EQE spectra match well with the values obtained from the J-V measurements, which confirm the good reliability of the $J_{-}V$ measurements. Furthermore, photovoltaic performance of the best cell is certified by National Institute of Metrology, China (NIM, China), and a certified PCE of $18.3\\%$ is recorded (see Figure S3 for the certification report and Figure 2C for the J-V curve). To the best of our knowledge, this is the highest value in the reported works. \n\nThe mobilities of the carriers in the three representative cells were measured through photo-induced charge-carrier extraction in linearly increasing voltage (Photo-CELIV), as shown in Figure 2D. The calculated charge mobilities of PBDB-TF:eC9-, PBDB-TF:HDO-4Cl:eC9-, and PBDB-TF:HDO-4Cl-based cells are $1.6\\times10^{-4}$ , $2.0\\times\\ 10^{-4}$ , and $1.3\\times10^{-4}c m^{2}\\bigvee^{-1}\\mathsf{s}^{-1}$ , respectively. The charge carrier lifetimes in these three cells were further studied by transient photocurrent (TPC) measurement. As shown in Figure 2E, the photocurrents of these cells reach their saturation values very sharply. By removal of the illumination, the photocurrent of the ternary cell decays faster than that in the PBDB-TF:eC9- and PBDB-TF:HDO4Cl-based cells. The results indicate the lower trap-state density in the ternary cell than in the other two cells. \n\nEloss has been regarded as a key factor limiting the photovoltaic performance.19,22,40 According to the charge-transfer state, accurate calculation methods of energy loss have been established.18,41,42 Herein, the $\\boldsymbol{E}_{\\mathrm{loss}}$ of the three OPV cells were investigated by a well-established method due to the unobvious CT states.19 The obtained optical bandgaps $(E_{\\mathfrak{g}}\\mathfrak{s})$ of PBDB-TF:eC9-, PBDB-TF:HDO-4Cl:eC9-, and PBDBTF:HDO-4Cl-based systems from the EL and EQE spectra are shown in Figures S4A–S4C. The high-sensitive EQE (HS-EQE) and EL spectra of the PBDB-TF:eC9-, PBDB-TF:HDO-4Cl:eC9-, and PBDB-TF:HDO-4Cl-based systems are shown in Figures S4D–S4F. The detailed $\\boldsymbol{E}_{\\mathrm{loss}}$ parameters are summarized in Table S2. The calculation processes of energy loss are described in supplemental information. The values of $\\Delta E_{1}$ are 0.26, 0.26, and $0.27\\ \\mathrm{eV}$ for the PBDB-TF:eC9-, PBDB-TF:HDO4Cl:eC9-, and PBDB-TF:HDO-4Cl-based cells, respectively. Besides, the $E_{\\mathrm{loss.}}$ , rad values are $0.08\\mathsf{e V}$ for PBDB-TF:eC9, $0.08\\mathsf{e V}$ for PBDB-TF:HDO-4Cl:eC9, and 0.09 $\\mathsf{e V}$ for PBDB-TF:HDO-4Cl. Furthermore, $\\mathsf{E O E}_{\\mathsf{E L S}}$ of the three cells were measured to calculate the Eloss, non-ra d.43 For the cells based on PBDB-TF:eC9 and PBDBTF:HDO-4Cl, the $E O E_{\\mathsf{E L S}}$ are ca. $2.80\\times10^{-4}$ and $1.10\\times10^{-4}$ , corresponding to Eloss, non-rad values of 0.21 and $0.24\\:\\mathrm{eV},$ respectively. However, for the ternary cell, the $E\\mathsf{O}\\mathsf{E}_{\\mathsf{E}^{\\mathsf{L}}}$ is ca. $5.30\\times10^{-4},$ , which shows a lower $\\boldsymbol{E}_{\\mathrm{loss}}$ , non-rad $\\mathsf{o f}0.19\\mathsf{e V}$ . Therefore, the relatively higher $V_{\\mathrm{OC}}$ of the PBDB-TF:HDO-4Cl:eC9-based cell can be attributed to the reduced non-radiative charge recombination.16,44,45 \n\n![](images/43c6b3dc75cfd199eb7abad0f7bbaa0ba22365e43e1aa6781297aff95ef1a3fa.jpg) \nigure 2. Performance and photoelectric characteristics of the OPV cells \n(A) J-V curves of the binary and the optimized ternary OPV cells under AM 1.5G, $100\\mathsf{m A}\\mathsf{c m}^{-2}$ . (B) EQE spectra of the binary and the optimized ternary OPV cells. (C) The certified results of the optimized ternary OPV cell measured by NIM, China. (D) Photo-CELIV curves of the cells for fast carrier mobility calculations. (E) TPC curves and the corresponding decay dynamics of the binary and the optimized ternary OPV cells. (F) $E\\cap E_{\\mathsf{E}\\mathsf{L}}\\mathsf{s}$ of the binary and optimized ternary OPV cells. \n\nFigure 3A shows the atomic force microscope (AFM) height and phase images of the blend films. The PBDB-TF:eC9- and PBDB-TF:HDO-4Cl:eC9-based films exhibit similar mean-square surface roughness $(R_{\\mathrm{q}})$ of 1.42 and $1.30\\mathsf{n m}$ , respectively, which are slightly smaller than that of the PBDB-TF:HDO-4Cl-based film $(R_{\\mathrm{q}}=1.80\\mathsf{n m})$ . The AFM phase images of the three blend films show obvious phase separation, which is beneficial to FFs of OPV cells. Transmission electron microscopy (TEM) was used to study the phase separation morphologies in the blend films. As shown in Figure 3B, the TEM images of the PBDB-TF:eC9 and PBDB-TF:HDO-4Cl:eC9 films also show similar aggregation characteristics, suggesting the compatibility of the two acceptors. Grazing incidence wide-angle X-ray scattering (GIWAXS) was used to investigate the molecular packing behaviors. The 2D GIWAXS patterns and corresponding 1D profiles in the in-plane (IP) and out-of-plane (OOP) directions are shown in Figures 3C and 3D. The blend films show obvious (010) peaks in the OOP direction but no (010) signal can be distinguished in the IP direction, indicating that the donor and acceptor molecules prefer the face-on dominated $\\pi-\\pi$ stacking.46 The $\\pi-\\pi$ stacking distance (d) and coherence length (CL) of the blend films were quantitatively calculated. For PBDB-TF:eC9, the d and $C L$ are 3.81 and $18.84\\mathring{\\mathsf{A}},$ respectively. After adding 20 wt $\\%$ of HDO-4Cl, the $d$ is slightly decreased to $3.71\\mathring{\\mathsf{A}}.$ , whereas the $C L$ is the same as that of PBDB-TF:eC9. Overall, the phase separation morphology and crystallinity of the ternary film are very similar to those of the two binary films, the obviously enhanced PCE should not be interpreted by the influence of morphology. \n\n![](images/9261b2221fc2b7a54241c08b25550150259e7d3ee7e1ddc6412d18f2c3868807.jpg) \nFigure 3. Morphology and crystallization characteristics of the active layers (A) AFM height and phase images of the binary and ternary films. (B) TEM images of the binary and ternary films. (C and D) (C) 2D GIWAXS patterns and (D) the corresponding IP and OOP profiles of the binary and ternary films. \n\nAccording to the previous reports, the non-radiative energy loss is directly related to the exciton behaviors.47 Therefore, we further investigated the $L_{\\mathsf{D}}\\mathsf{s}$ in both eC9 and HDO-4Cl:eC9 phases by the exciton-exciton annihilation (EEA) method through transient absorption spectroscopy (TAS).35 The EEA method considers that there are two main quenching channels for excitons, i.e., the radiative and non-radiative deactivations with an intrinsic exciton lifetime constant $(k)$ and the bimolecular EEA with a bimolecular decay rate coefficient $(\\gamma)$ .48 The values of $k$ and $\\gamma$ can be used to calculate the exciton diffusion coefficient (D). The broad ground-state bleaching (GSB) signals appear after photoexcitation of eC9 and HDO-4Cl:eC9 films at $800~\\mathsf{n m}$ , as shown in Figure S5. The decay profiles are shown in Figure 4. As expected, the decay of these signals is highly dependent on the excitation intensity. The decay half-times of eC9 are 173 ps at $0.2~{\\upmu\\mathsf{J}}~{\\mathsf{c m}}^{-2}$ and 31.0 ps at $10\\ensuremath{~\\upmu\\mathrm{J}\\mathrm{~cm}^{-2}}$ . For the HDO-4Cl:eC9 film, the decay half-times are 147 ps at $0.2~\\upmu\\mathsf{J}~\\mathsf{c m}^{-2}$ and 21.1 ps at $10~\\upmu\\mathsf{J}~\\mathsf{c m}^{-2}$ . The calculated D values of eC9 and HDO-4Cl:eC9 are $4.6\\times10^{-3}$ and $7.9\\times10^{-3}\\ \\mathsf{c m}^{2}\\ \\mathsf{s}^{-1}$ , respectively. The detailed calculation processes are demonstrated in SI and the related parameters are summarized in Table S3. According to the equation of $L_{\\mathsf{D}}=\\left(D\\tau\\right)^{1/2}$ , the calculated $L_{\\mathsf{D}}$ values are $12.2\\mathsf{n m}$ for eC9 and $16.3\\mathsf{n m}$ for HDO-4Cl:eC9. The difference between the exciton diffusion length is mainly due to the difference of the exciton diffusion coefficient, which corresponds to the diffusion rate.31 Therefore, the photo-induced exciton in the alloy acceptor phase can diffuse to a longer distance within the effective exciton lifetime, which can greatly reduce the exciton recombination, especially in the domain size that is larger than the exciton diffusion length in eC9 neat phase. Thus, the enlarged $L_{\\mathsf{D}}$ should be helpful to restrain the charge recombination and, hence, improve the current density of the corresponding OPV cells. \n\n![](images/c80be743ab5866bbc1561b772e8d3c816f70478a87c84edc78123386e4488c73.jpg) \nFigure 4. Singlet exciton decay dynamics with different excitation fluenc (A) The decay dynamics of the singlet excitons in eC9 film under the excitation of $800~\\mathsf{n m}$ , 0.2 and $10\\upmu\\mathsf{J}\\mathsf{c m}^{-2}$ . (B) The decay dynamics of the singlet excitons in HDO-4Cl:eC9 film under the excitation of $800\\mathsf{n m}$ , 0.2 and $10\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ . \n\nThe charge generation and recombination processes were further studied by TAS. A beam of 400 nm excitation light was used to primarily excite PBDB-TF. The TA images and the corresponding spectra with the various decay times are presented in Figure S6. The negative signals in the range from 500 to $680~\\mathsf{n m}$ are assigned to the GSB of PBDB-TF. The decay dynamics of the $630\\mathsf{n m}\\mathsf{G S B}$ signals of PBDB-TF:eC9- and PBDB-TF:HDO-4Cl:eC9-based films are displayed in Figure S7, which represent the electron transfer processes. The GSB profiles of $630~\\mathsf{n m}$ at the early stage are fitted by using the biexponential functions. The PBDB-TF:eC9- and PBDB-TF:HDO4Cl:eC9-based films show the fast components $(\\uptau_{1})$ of 1.53 and 0.1 ps and the slow components $(\\tau_{2})$ of 129 and 38 ps, respectively. $\\boldsymbol{\\uptau}_{1}$ can be assigned to the ultrafast exciton dissociation at the donor-acceptor interface and $\\tau_{2}$ represents the diffusion of excitons in the donor phase toward interface before dissociation.49 The results show that the ternary cell has a faster electron transfer rate than the binary counterpart, which is benefiting to charge generation in the corresponding cell. \n\nAs the absorption spectra of the donor and acceptors can be well separated, the hole transfer dynamics can be clearly detected.50 Here, 900 nm excitation light was used to solely excite the acceptor to obtain the hole transfer signals in visible (vis) region and 800 nm excitation light was used to collect the photo-induced absorption signals in the near-infrared (NIR) region. The TA images in the vis and NIR regions of PBDBTF:eC9- and PBDB-TF:HDO-4Cl:eC9-based films are shown in Figures 5A and 5B, and the representative TA spectra at the various delay times are shown in Figure S8. The decay traces at the various wavelengths representing the different photophysical processes are shown in Figures 5D and 5E. Among them, the traces at 740 and $800\\mathsf{n m}$ represent the GSB signals of the acceptor. The signal at $885\\mathsf{n m}$ is the photo-induced absorption of singlet excitons of the acceptor. Those at 585 and $630\\mathsf{n m}$ are assigned to the GSB signals of PBDB-TF. With the decay of the signals at 740 and $885\\mathsf{n m}$ , the bleach signals at 585 and 630 nm emerge in the TA spectra. The GSB decay process of the photoexcited acceptor agrees well with the rise of PBDB-TF GSB, confirming the hole transfer process from the acceptor to the donor.51 However, the absorption peak of $630\\mathsf{n m}$ has a similar rising edge to that of acceptor GSB, so it should be a superposition of the GSB of the acceptor and the signal of hole transfer. Therefore, the trace at $585\\mathsf{n m}$ is selected as a characteristic signal of the hole transfer. The TA images and spectrum of neat PBDB-TF under 900 nm excitation were also measured to prove that these signals were generated by the hole transfer processes. As shown in Figures S8A and S8B, the TA image and spectrum only exhibit the background signals, which indicates that all of the GSB signal at $585~\\mathsf{n m}$ is contributed to the hole transfer from the acceptor to donor. The hole transfer processes in both the binary and ternary films are separately compared. As shown in Figure 5G, the ternary film takes a longer time to reach its saturation value compared with the PBDB-TF:eC9- based film, which may be due to the smaller HOMO level offset between the donor and acceptor.52 The GSB values, which have positive correlations with exciton densities, at $585\\mathsf{n m}$ of the ternary film are prominent than that of the binary film, which can be attributed to the enlarged exciton LD. In addition, an 800 nm excitation light, which can simultaneously excite the HDO-4Cl and eC9, was further used to investigate the hole transfer process. The corresponding TA images, spectra, and TA traces are shown in Figures 5C, 5F, and S8E. As shown in Figure S10A, the decay traces at $585~\\mathsf{n m}$ under the 800 and $900~\\mathsf{n m}$ excitations in the ternary film show very similar characteristics, which confirms the formation of the alloy-like acceptor phase between HDO-4Cl:eC9. We also probed the TA traces of PBDB-TF:eC9- and PBDBTF:HDO-4Cl:eC9-based films at $885\\mathsf{n m}$ , which represents the absorption of singlet excitons in the acceptor phase. As shown in Figure 5H, the singlet exciton lifetimes in the binary and ternary films are 3 and 6 ps, respectively, indicating the hole transfer in the ternary film is slower than that in the binary counterpart. A 600-nm excitation light was used to excite both the donor and acceptor in the blend films of PBDB-TF:eC9 and PBDB-TF:HDO-4Cl:eC9. As shown in Figures S10B–S10D, a new absorption signal peaking at $960~\\mathsf{n m}$ originating from the absorption of polarons appears, as the absorption peak of exciton in acceptor phase at $885~\\mathsf{n m}$ gradually decreased. As shown in Figure 5I for the decays of the above two signals, the polaron lifetime in the ternary film is much longer than that in the binary film, suggesting a suppressed bimolecular recombination probability in the former.53 \n\n![](images/f7de2b2693f200479175ad39ee0944b6230d89f3645e6edc8fb16d7070f890f9.jpg) \nFigure 5. TA images and the corresponding decay dynamics \n(A–C) TA images of the binary and ternary blend films under various excitation with a fluence below $10\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ . (D–F) Decay dynamics probed at different wavelengths from the PBDB-TF:eC9 and PBDB-TF:HDO-4Cl:eC9 blend films. (G) The hole transfer processes in PBDB-TF:eC9 and PBDB-TF:HDO-4Cl:eC9 systems. (H) The decay dynamics probed at $885~\\mathsf{n m}$ in PBDB-TF:eC9 and PBDB-TF:HDO-4Cl:eC9 systems with an excitation of $800~\\mathsf{n m}$ . (I) Exciton decay dynamics probed at $960~\\mathsf{n m}$ in PBDB-TF:eC9 and PBDB-TF:HDO-4Cl:eC9 systems under $600~\\mathsf{n m}$ excitation. \n\n# Conclusions \n\nIn summary, an efficient ternary OPV cell was prepared by introducing HDO-4Cl into the PBDB-TF:eC9-based photoactive layer. We confirmed that an alloy-like HDO4Cl:eC9 phase is formed in the ternary cell and the three key photovoltaic parameters including $V_{\\mathrm{OC}},J_{\\mathsf{S C}},$ and FF of the ternary cell are all higher than those of the binary counterpart, resulting in a significantly improved PCE. The results obtained from the ultrafast spectroscopy measurement reveal that the exciton $L_{\\mathsf{D}}$ is improved from 12.2 to $16.3\\mathsf{n m}$ by adding HDO-4Cl into the PBDB-TF:eC9-based film, which contributes to the reduced charge recombination and interprets the higher photovoltaic performance of the ternary cell. For the best ternary cell based on a composition of PBDB-TF:HDO-4Cl:eC9 (1:0.2:1 for weight ratio), a PCE of $18.86\\%$ with a $V_{\\mathrm{OC}}$ of $0.866\\mathsf{V}.$ , a $J_{S C}$ of $27.05\\mathsf{m A c m}^{-2}$ , and an FF of $80.51\\%$ was achieved. Overall, this work not only reports an outstanding PCE but also demonstrates that to optimize the behaviors of excitons will be an effective pathway to further improve photovoltaic performance of the highly efficient OPV cells. \n\n# EXPERIMENTAL PROCEDURES \n\n# Resource availability \n\nLead contact \n\nFurther information and requests for resources and materials should be directed to and will be fulfilled by the lead contact, Jianhui Hou (hjhzlz@iccas.ac.cn). \n\n# Materials availability \n\nThis study did not generate new unique materials. \n\n# Data and code availability \n\nAll data are present in the paper and supplementary materials. Other data are available from the lead contact or corresponding author. \n\nFull details of experimental procedures can be found in the supplemental information. \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental information can be found online at https://doi.org/10.1016/j.joule. \n2021.06.020. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the financial support from National Natural Science Foundation of China (21835006 and 21734008), the National Key Research and Development Program of China (2019YFE0116700), China Postdoctoral Science Foundation (2019M660799), and Beijing National Laboratory for Molecular Sciences (2019BMS20005). \n\n# AUTHOR CONTRIBUTIONS \n\nP.B., S.Z., and J.H. conceived the idea. P.B., Y.C., T.Z., and L.H. carried out the device fabrication and characterizations. Y.X. synthesized the HDO-4Cl. J.R. and J.Q. conducted the TEM and AFM characterizations. Z.C. and X.H. conducted the TA characterizations. All authors discussed and commented on the key scientific issues in the work. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: April 13, 2021 \nRevised: May 24, 2021 \nAccepted: June 25, 2021 \nPublished: July 23, 2021 \n\n# REFERENCES \n\n1. Yu, G., Gao, J., Hummelen, J.C., Wudl, F., and Heeger, A.J. (1995). Polymer photovoltaic cells: enhanced efficiencies via a network of internal donor-acceptor heterojunctions. Science 270, 1789–1791. \n2. Meng, L., Zhang, Y., Wan, X., Li, C., Zhang, X., Wang, Y., Ke, X., Xiao, Z., Ding, L., Xia, R., et al. (2018). Organic and solution-processed tandem solar cells with $17.3\\%$ efficiency. Science 361, 1094–1098. \n3. Yan, C., Barlow, S., Wang, Z., Yan, H., Jen, A.K.-Y., Marder, S.R., and Zhan, X. (2018). Nonfullerene acceptors for organic solar cells. Nat. Rev. Mater. 3, 18003. \n4. Nayak, P.K., Mahesh, S., Snaith, H.J., and Cahen, D. (2019). Photovoltaic solar cell technologies: analysing the state of the art. Nat. Rev. Mater. 4, 269–285. \n5. Zhang, J., Tan, H.S., Guo, X., Facchetti, A., and Yan, H. (2018). Material insights and challenges for non-fullerene organic solar cells based on small molecular acceptors. Nat. Energy 3, 720–731. \n6. Lin, Y., Wang, J., Zhang, Z.G., Bai, H., Li, Y., Zhu, D., and Zhan, X. (2015). An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174. \n7. Yuan, J., Zhang, Y., Zhou, L., Zhang, G., Yip, H.-L., Lau, T.-K., Lu, X., Zhu, C., Peng, H., Johnson, P.A., et al. (2019). Single-junction organic solar cell with over $15\\%$ efficiency using fused-ring acceptor with electron-deficient core. Joule 3, 1140–1151. \n8. Ma, Y., Cai, D., Wan, S., Wang, P., Wang, J., and Zheng, Q. (2020). Ladder-type heteroheptacenes with different heterocycles for nonfullerene acceptors. Angew. Chem. Int. Ed. Engl. 59, 21627–21633. \n9. Chen, Y.N., Li, ${\\mathsf{M}}_{\\cdot,\\cdot}$ Wang, Y., Wang, J., Zhang, M., Zhou, Y., Yang, J., Liu, $\\Upsilon_{\\cdot,\\cdot}$ Liu, F., Tang, Z. et al. (2020). A fully non-fused ring acceptor with planar backbone and near-ir absorption for high performance polymer solar cells. Angew. Chem. Int. Ed. Engl. 59, 22714–22720. \n10. Liu, S., Yuan, J., Deng, W., Luo, M., Xie, Y., Liang, Q., Zou, Y., He, Z., Wu, H., and Cao, Y. (2020). High-efficiency organic solar cells with low non-radiative recombination loss and low energetic disorder. Nat. Photonics 14, 300–305. \n11. Xia, R., Brabec, C.J., Yip, H.-L., and Cao, Y (2019). High-throughput optical screening for efficient semitransparent organic solar cells. Joule 3, 2241–2254. \n12. Du, X., Heumueller, T., Gruber, W., Classen, A., Unruh, T., Li, N., and Brabec, C.J. (2019). Efficient polymer solar cells based on nonfullerene acceptors with potential device lifetime approaching 10 years. Joule 3, 215–226. \n13. Zhang, M., Zhu, L., Zhou, G., Hao, T., Qiu, C., Zhao, Z., Hu, $\\Omega.,$ Larson, B.W., Zhu, H., Ma, Z., et al. (2021). Single-layered organic photovoltaics with double cascading charge transport pathways: $18\\%$ efficiencies. Nat. Commun. 12, 309. \n14. Zhan, L., Li, S., Xia, X., Li, Y., Lu, X., Zuo, L., Shi, ${\\mathsf{M}}_{\\cdot,\\prime}$ and Chen, H. (2021). Layer-by-layer processed ternary organic photovoltaics with efficiency over $18\\%$ . Adv. Mater. 33, e2007231. \n15. Liu, $\\Omega.,$ Jiang, Y., Jin, $\\mathsf{K}_{\\cdot,\\prime}$ Qin, J., Xu, J., Li, W., Xiong, J., Liu, J., Xiao, Z., Sun, K., et al. (2020). $18\\%$ efficiency organic solar cells. Science Bulletin 65, 272–275. \n16. Menke, S.M., Ran, N.A., Bazan, G.C., and Friend, R.H. (2018). Understanding energy loss in organic solar cells: toward a new efficiency regime. Joule 2, 25–35. \n17. Green, M.A. (2012). Radiative efficiency of state-of-the-art photovoltaic cells. Prog. Photovolt: Res. Appl. 20, 472–476. \n18. Eisner, F.D., Azzouzi, M., Fei, Z., Hou, X., Anthopoulos, T.D., Dennis, T.J.S., Heeney, M., and Nelson, J. (2019). Hybridization of local exciton and charge-transfer states reduces nonradiative voltage losses in organic solar cells. J. Am. Chem. Soc. 141, 6362–6374. \n19. Liu, J., Chen, S., Qian, D., Gautam, B., Yang, G., Zhao, J., Bergqvist, J., Zhang, F., Ma, W., Ade, H., et al. (2016). Fast charge separation in a non-fullerene organic solar cell with a small driving force. Nat. Energy 1, 16089. \n20. Vandewal, K., Tvingstedt, K., Gadisa, A., Ingana¨ s, O., and Manca, J.V. (2009). On the origin of the open-circuit voltage of polymerfullerene solar cells. Nat. Mater. 8, 904–909. \n21. Vandewal, K., Albrecht, S., Hoke, E.T., Graham, K.R., Widmer, J., Douglas, J.D., Schubert, M., Mateker, W.R., Bloking, J.T., Burkhard, G.F., et al. (2014). Efficient charge generation by relaxed charge-transfer states at organic interfaces. Nat. Mater. 13, 63–68. \n22. Hou, J., Ingana¨ s, O., Friend, R.H., and Gao, F. (2018). Organic solar cells based on nonfullerene acceptors. Nat. Mater. 17, 119–128. \n23. Vandewal, K., Benduhn, J., and Nikolis, V.C. (2018). How to determine optical gaps and voltage losses in organic photovoltaic materials. Sustainable Energy Fuels 2, 538–544. \n24. Benduhn, J., Tvingstedt, $\\mathsf{K}_{\\cdot,\\cdot}$ Piersimoni, F., Ullbrich, S., Fan, Y., Tropiano, M., McGarry, K.A., Zeika, O., Riede, M.K., Douglas, C.J., et al. (2017). Intrinsic non-radiative voltage losses in fullerene-based organic solar cells. Nat. Energy 2, 17053. \n25. Zhao, J., Li, $\\mathsf{Y}_{\\cdot,\\prime}$ Yang, G., Jiang, K., Lin, H., Ade, H., Ma, W., and Yan, H. (2016). Efficient organic solar cells processed from hydrocarbon solvents. Nat. Energy 1, 15027. \n26. Wang, J., and Zhan, $x.$ (2021). Fused-ring electron acceptors for photovoltaics and beyond. Acc. Chem. Res. 54, 132–143. \n27. Li, S., Li, C.-Z., Shi, M., and Chen, H. (2020). New phase for organic solar cell research: emergence of y-series electron acceptors and their perspectives. ACS Energy Lett 5, 1554– 1567. \n28. An, Q., Wang, J., Ma, X., Gao, J., Hu, Z., Liu, B., Sun, H., Guo, X., Zhang, X., and Zhang, F. (2020). Two compatible polymer donors contribute synergistically for ternary organic solar cells with $1\\bar{7}.53\\%$ efficiency. Energy Environ. Sci. 13, 5039–5047. \n29. Gasparini, N., Salleo, A., McCulloch, I., and Baran, D. (2019). The role of the third component in ternary organic solar cells. Nat. Rev. Mater. 4, 229–242. \n30. Sajjad, M.T., Ruseckas, A., Jagadamma, L.K., Zhang, Y., and Samuel, I.D.W. (2020). Longrange exciton diffusion in non-fullerene acceptors and coarse bulk heterojunctions enable highly efficient organic photovoltaics. J. Mater. Chem. A 8, 15687–15694. \n31. Mikhnenko, O.V., Blom, P.W.M., and Nguyen, T.-Q. (2015). Exciton diffusion in organic semiconductors. Energy Environ. Sci. 8, 1867– 1888. \n32. Menke, S.M., Luhman, W.A., and Holmes, R.J. (2013). Tailored exciton diffusion in organic photovoltaic cells for enhanced power conversion efficiency. Nat. Mater. 12, 152–157. \n33. Terao, Y., Sasabe, H., and Adachi, C. (2007). Correlation of hole mobility, exciton diffusion length, and solar cell characteristics in phthalocyanine/fullerene organic solar cells. Appl. Phys. Lett. 90, 103515. \n34. Schwartz, G., Reineke, S., Rosenow, T.C., Walzer, $\\mathsf{K}_{\\cdot,\\prime}$ and Leo, K. (2009). Triplet harvesting in hybrid white organic light-emitting diodes. Adv. Funct. Mater. 19, 1319–1333. \n35. Firdaus, Y., Le Corre, V.M., Karuthedath, S., Liu, W., Markina, A., Huang, W., Chattopadhyay, S., Nahid, M.M., Nugraha, M.I., Lin, Y., et al. (2020). Long-range exciton diffusion in molecular nonfullerene acceptors. Nat. Commun. 11, 5220. \n36. Zhang, J., Zhang, Y., Fang, J., Lu, $\\mathsf{K}_{\\cdot,\\cdot}$ Wang, Z., Ma, W., and Wei, Z. (2015). Conjugated polymer–small molecule alloy leads to high efficient ternary organic solar cells. J. Am. Chem. Soc. 137, 8176–8183. \n37. Jiang, K., Zhang, G.Y., Yang, G.F., Zhang, J.Q., Li, Z.K., Ma, T.X., Hu, H.W., Ma, W., Ade, H., and Yan, H. (2018). Multiple cases of efficient nonfullerene ternary organic solar cells enabled by an effective morphology control method. Adv. Energy Mater. 8, 1701370. \n38. Song, J.L., Li, C., Zhu, L., Guo, J., Xu, J.Q., Zhang, X.N., Weng, K.K., Zhang, K.N., Min, J., Hao, X.T., et al. (2019). Ternary organic solar cells with efficiency $>16.5\\%$ based on two compatible nonfullerene acceptors. Adv. Mater. 31, e1905645. \n39. Ye, L., Hu, H., Ghasemi, M., Wang, T., Collins, B.A., Kim, J.H., Jiang, K., Carpenter, J.H., Li, H., Li, Z., et al. (2018). Quantitative relations between interaction parameter, miscibility and function in organic solar cells. Nat. Mater. ${17},$ 253–260. \n40. Qin, Y., Zhang, S., Xu, Y., Ye, L., Wu, Y., Kong, J., Xu, B., Yao, H., Ade, H., and Hou, J. (2019). Reduced nonradiative energy loss caused by aggregation of nonfullerene acceptor in organic solar cells. Adv. Energy Mater. 9, 1901823. \n41. Chen, X.K., Coropceanu, V., and Br ´edas, J.L. (2018). Assessing the nature of the chargetransfer electronic states in organic solar cells. Nat. Commun. 9, 5295. \n42. Azzouzi, M., Yan, J., Kirchartz, T., Liu, $\\mathsf{K}_{\\cdot,\\prime}$ Wang, J., Wu, H., and Nelson, J. (2018). Nonradiative energy losses in bulk-heterojunction organic photovoltaics. Phys. Rev. $\\times\\dot{8},$ 031055. \n43. Liu, X., Du, X., Wang, J., Duan, $\\mathsf{C}_{\\cdot,\\prime}$ Tang, X., Heumueller, $\\intercal_{\\cdot,\\prime}$ Liu, $\\mathsf{G}_{\\cdot,\\prime}$ Li, $\\mathsf{Y}_{\\cdot,\\prime}$ Wang, Z., Wang, J., et al. (2018). Efficient organic solar cells with extremely high open-circuit voltages and low voltage losses by suppressing nonradiative recombination losses. Adv. Energy Mater. 8, 1801699. \n44. Wu, J., Fan, Q., Xiong, M., Wang, Q., Chen, K., Liu, H., Gao, M., Ye, L., Guo, X., Fang, J., et al. (2021). Carboxylate substituted pyrazine: a simple and low-cost building block for novel wide bandgap polymer donor enables $15.3\\%$ efficiency in organic solar cells. Nano Energy 82, 105679. \n45. Lai, H., Zhao, Q., Chen, Z., Chen, H., Chao, P., Zhu, Y., Lang, Y., Zhen, N., Mo, D., Zhang, Y., and He, F. (2020). Trifluoromethylation enables a 3d interpenetrated low-band-gap acceptor for efficient organic solar cells. Joule 4, 688–700. \n46. Zhou, Z., Liu, W., Zhou, G., Zhang, M., Qian, D., Zhang, J., Chen, S., Xu, S., Yang, C., Gao, F., et al. (2020). Subtle molecular tailoring induces significant morphology optimization enabling over $16\\%$ efficiency organic solar cells with efficient charge generation. Adv. Mater. 32, e1906324. \n47. Classen, A., Chochos, C.L., Lu¨ er, L., Gregoriou, V.G., Wortmann, J., Osvet, A., Forberich, K., McCulloch, I., Heumu¨ ller, $\\intercal_{\\cdot,\\prime}$ and Brabec, C.J. (2020). The role of exciton lifetime for charge generation in organic solar cells at negligible energy-level offsets. Nat. Energy 5, 711–719. \n48. Cha, H., Wheeler, S., Holliday, S., Dimitrov, S.D., Wadsworth, A., Lee, H.H., Baran, D., McCulloch, I., and Durrant, J.R. (2018). Influence of blend morphology and energetics on charge separation and recombination dynamics in organic solar cells incorporating a nonfullerene acceptor. Adv. Funct. Mater. 28, 1704389. \n49. Zhang, M., Zhu, L., Hao, T., Zhou, G., Qiu, C., Zhao, Z., Hartmann, N., Xiao, B., Zou, Y., Feng, W., et al. (2021). High-efficiency organic photovoltaics using eutectic acceptor fibrils to achieve current amplification. Adv. Mater. 33, e2007177. \n50. Wang, R., Zhang, C., Li, $\\Omega.,$ Zhang, Z., Wang, X., and Xiao, M. (2020). Charge separation from an intra-moiety intermediate state in the highperformance pm6:y6 organic photovoltaic blend. J. Am. Chem. Soc. 142, 12751–12759. \n51. Chen, S., Lee, S.M., Xu, J., Lee, J., Lee, K.C., Hou, T., Yang, Y., Jeong, M., Lee, B., Cho, Y., et al. (2018). Ultrafast channel ii process induced by a 3-d texture with enhanced acceptor order ranges for high-performance non-fullerene polymer solar cells. Energy Environ. Sci. 11, 2569–2580. \n\n52. Eastham, N.D., Logsdon, J.L., Manley, E.F., Aldrich, T.J., Leonardi, M.J., Wang, G., PowersRiggs, N.E., Young, R.M., Chen, L.X., Wasielewski, M.R., et al. (2018). Hole-transfer dependence on blend morphology and energy level alignment in polymer: ITIC photovoltaic materials. Adv. Mater. 30, 1704263. \n\n53. Sun, C., Qin, S., Wang, R., Chen, S., Pan, F., Qiu, B., Shang, $Z.,$ Meng, L., Zhang, C., Xiao, M., et al. (2020). High efficiency polymer solar cells with efficient hole transfer at zero highest occupied molecular orbital offset between methylated polymer donor and brominated acceptor. J. Am. Chem. Soc. 142, 1465–1474. " + }, + { + "id": "10.1016_j.nulloen.2020.105716", + "DOI": "10.1016/j.nulloen.2020.105716", + "DOI Link": "http://dx.doi.org/10.1016/j.nulloen.2020.105716", + "Relative Dir Path": "mds/10.1016_j.nulloen.2020.105716", + "Article Title": "Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles", + "Authors": "Mortazavi, B; Javvaji, B; Shojaei, F; Rabczuk, T; Shapeev, A; Zhuang, XY", + "Source Title": "nullO ENERGY", + "Abstract": "Chemical vapor deposition has been most recently employed to fabricate centimeter-scale high-quality singlelayer MoSi2N4 (Science; 2020;369; 670). Motivated by this exciting experimental advance, herein we conduct extensive first-principles based simulations to explore the stability, mechanical properties, lattice thermal conductivity, piezoelectric and flexoelectric response, and photocatalytic and electronic features of MA(2)Z(4) (M = Cr, Mo, W; A = Si, Ge; Z = N, P) monolayers. The considered nullosheets are found to exhibit dynamical stability and remarkably high mechanical properties. Moreover, they show diverse electronic properties from antiferromagnetic metal to half metal and to semiconductors with band gaps ranging from 0.31 to 2.57 eV. Among the studied nullosheets, the MoSi2N4 and WSi2N4 monolayers yield appropriate band edge positions, high electron and hole mobilities, and strong visible light absorption, highly promising for applications in optoelectronics and photocatalytic water splitting. The MoSi2N4 and WSi2N4 monolayers are also predicted to show outstandingly high lattice thermal conductivity of 440 and 500 W/mK, respectively. For the first time we show that machine learning interatomic potentials trained over small supercells can be employed to examine the flexoelectric and piezoelectric properties of complex structures. As the most exciting finding, WSi2N4, CrSi2N4 and MoSi2N4 are found to exhibit the highest piezoelectric coefficients, outperforming all other-known 2D materials. Our results highlight that MA(2)Z(4) nullosheets not only undoubtedly outperform the transition metal dichalcogenides family but also can compete with graphene for applications in nulloelectronics, optoelectronic, energy storage/conversion and thermal management systems.", + "Times Cited, WoS Core": 460, + "Times Cited, All Databases": 467, + "Publication Year": 2021, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000634235000004", + "Markdown": "# Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional $\\mathrm{MoSi}_{2}\\mathrm{N}_{4}$ family confirmed by first-principles \n\nBohayra Mortazavi b,c,\\*, Brahmanandam Javvaji b,1, Fazel Shojaei d,1, Timon Rabczuk a, Alexander V. Shapeev e, Xiaoying Zhuang a,b,c,\\* \n\na College of Civil Engineering, Department of Geotechnical Engineering, Tongji University, 1239 Siping Road Shanghai, China \nb Chair of Computational Science and Simulation Technology, Institute of Photonics, Department of Mathematics and Physics, Leibniz Universit¨at Hannover, Appelstraße \n11, 30157 Hannover, Germany \nc Cluster of Excellence PhoenixD (Photonics, Optics, and Engineering–Innovation Across Disciplines), Gottfried Wilhelm Leibniz Universita¨t Hannover, Hannover, \nGermany \nd Department of Chemistry, Faculty of Sciences, Persian Gulf University, Bushehr 75169, Iran \ne Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Nobel St. 3, Moscow 143026, Russia \n\n# A R T I C L E I N F O \n\nKeywords: \n2D Materials \n$\\mathrm{MoSi_{2}N_{4}}$ \nPiezoelectric \nMechanical \nThermal conductivity \nElectronic \n\n# A B S T R A C T \n\nChemical vapor deposition has been most recently employed to fabricate centimeter-scale high-quality singlelayer $\\mathtt{M o S i_{2}N_{4}}$ (Science; 2020;369; 670). Motivated by this exciting experimental advance, herein we conduct extensive first-principles based simulations to explore the stability, mechanical properties, lattice thermal con­ ductivity, piezoelectric and flexoelectric response, and photocatalytic and electronic features of $M A_{2}Z_{4}$ $\\mathbf{\\hat{M}}=\\mathbf{Cr}$ , Mo, W; $\\mathbf{A}=S\\mathbf{i}$ , Ge; $\\boldsymbol Z=\\boldsymbol{\\mathrm{N}}$ , P) monolayers. The considered nanosheets are found to exhibit dynamical stability and remarkably high mechanical properties. Moreover, they show diverse electronic properties from antiferromag­ netic metal to half metal and to semiconductors with band gaps ranging from 0.31 to $2.57\\mathrm{eV}$ . Among the studied nanosheets, the $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathsf{W S i}_{2}\\mathrm{N}_{4}$ monolayers yield appropriate band edge positions, high electron and hole mobilities, and strong visible light absorption, highly promising for applications in optoelectronics and photo­ catalytic water splitting. The $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathsf{W S i}_{2}\\mathrm{N}_{4}$ monolayers are also predicted to show outstandingly high lattice thermal conductivity of 440 and $500\\ \\mathrm{W/mK}$ respectively. For the first time we show that machine learning interatomic potentials trained over small supercells can be employed to examine the flexoelectric and piezoelectric properties of complex structures. As the most exciting finding, $\\mathsf{W S i_{2}N_{4}}$ , $\\mathrm{CrSi_{2}N_{4}}$ and $\\mathrm{MoSi_{2}N_{4}}$ are found to exhibit the highest piezoelectric coefficients, outperforming all other-known 2D materials. Our results highlight that $M A_{2}Z_{4}$ nanosheets not only undoubtedly outperform the transition metal dichalcogenides family but also can compete with graphene for applications in nanoelectronics, optoelectronic, energy storage/con­ version and thermal management systems. \n\n# 1. Introduction \n\nGraphene’s first experimental realization in 2004 [1–3] and confir­ mation of its ultrahigh thermal conductivity [4,5], mechanical strength [6] and carrier mobility [7] along with outstanding electronic and op­ tical properties [8–11], initiated extending and continuous interests toward two-dimensional (2D) materials. The pristine graphene with full- $\\cdot\\mathsf{s p}^{2}$ carbon atoms does not however exhibit an electronic band gap. The semimetal electronic nature of defect-free graphene limits its application in nanoelectronics and nano-optics. In fact, having a proper electronic band gap is a critical requirement for the majority of rapidly growing technologies. During the last decade numerous techniques have been proposed for the band gap opening in graphene, like the formation of point defects [12–16], patterned cuts [17,18], stretching [19–23], and doping [24–28]. Nonetheless all the aforementioned techniques require additional processing after the fabrication of graphene and thus result in increased complexity and production cost as well. This way, for practical applications it is more recommended to fabricate an intrinsic 2D semiconductor rather than to engineer the graphene’s electronic structure. This issue motivated the design and fabrication of novel 2D semiconductors, such as the transition metal dichalcogenides [29,30], indium selenide [31] and phosphorene [32,33]. In comparison with graphene, the majority of 2D semiconductors exhibit distinctly lower mechanical strength and thermal conductivity. In fact, one of the most appealing features of graphene is its superior thermal conductivity that outperforms all other materials and propose it as unique candidate for the thermal management systems [34–37]. This way, a 2D semi­ conductor with high thermal conductivity is greatly appealing to tackle the common overheating concern in nanoelectronics. Moreover, the application of novel nanomaterials in energy storage/conversion sys­ tems is another very active and attractive field of research [38–43]. In this regard, piezoelectricity and flexoelectricity are currently playing critical roles in many advanced technologies [44–48]. Therefore, the design of novel 2D materials with appealing piezoelectricity and flex­ oelectricity are highly appealing to expand the practical application of 2D materials. \n\nIn line of continuous expansion of 2D semiconductors, in a latest study by Hong and coworkers [49], they succeeded in the first experi­ mental realization of large-area $\\mathrm{MoSi_{2}N_{4}}$ monolayer by incorporating silicon during chemical vapor deposition growth of molybdenum nitride. This novel 2D system was found to be a semiconductor with remarkable tensile strength and high carrier mobility as well [49]. As an exciting fact, this latest accomplishment paves the path for the experi­ mental realization of an extensive family of $M A_{2}Z_{4}$ nanosheets, in which M is an early transition metal (Mo, W, V, Nb, Ta, Ti, Zr, Hf or Cr), A is either Si or Ge and Z can be N, P or As [50]. Their unique sandwich structure with the possibility of altering the different layers’ composi­ tion create vast opportunities to reach diverse properties [50]. \n\nMotivated by this latest experimental accomplishment by Hong et al. [49], in this study our objective is to examine the stability, mechanical response, lattice thermal conductivity, piezoelectricity and flexoelec­ tricity and electronic features of twelve different $M A_{2}Z_{4}$ $\\mathbf{\\tilde{M}}=\\mathbf{Cr}$ , Mo, W; $\\mathbf{A}=\\mathbf{S}\\mathbf{i}$ , Ge; $\\begin{array}{r}{Z=\\mathbf{N}.}\\end{array}$ , P) monolayers. For every composition we consider two different structures and evaluate their energetic and dynamical stability. The considered representative lattices in this work can establish a comprehensive vision on the intrinsic properties of $M A_{2}Z_{4}$ nanosheets. We explored the intrinsic properties by conducting density functional theory (DFT) based calculations. For the most stable configurations the acquired results reveal semiconducting electronic nature with band gaps ranging from 0.8 to 2.6 eV. Our first-principles results confirm remarkably good mechanical properties and thermal conductivity of this novel class of 2D materials. In particular, the $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathsf{W S i_{2}N_{4}}$ monolayers are predicted to show outstandingly high lattice thermal conductivity of 440 and $500\\mathrm{W/mK},$ and elastic modulus of 487 and 506 GPa, respectively. These aforementioned monolayers are also found to exhibit appropriate band edge positions, high electron and hole mobil­ ities, and strong visible light absorption, highly promising for the ap­ plications in optoelectronics and photocatalytic water splitting. As the first study, we show that machine learning interatomic potentials can be effectively employed to evaluate piezoelectric and flexoelectric re­ sponses of 2D systems. Notably, we predict that the $\\mathrm{WSi}_{2}\\mathrm{N}_{4}$ , $\\mathrm{CrSi_{2}N_{4}}$ and $\\mathrm{MoSi_{2}N_{4}}$ monolayers exhibit the highest piezoelectric coefficients, out­ performing all other-known 2D materials. The presented first-principles results provide a comprehensive vision on the critical properties of $\\mathrm{MA_{2}Z_{4}2D}$ materials family and highlight their very attractive properties for the design of novel nanoelectronics, optoelectronics, thermal man­ agement and energy conversion/storage systems. \n\n# 2. Computational methods \n\nDensity functional theory (DFT) simulations in this work are con­ ducted using the Vienna $_{A b}$ -initio Simulation Package (VASP) [51–53] with generalized gradient approximation (GGA) and Per­ dew−Burke−Ernzerhof (PBE) [54] functional considering an energy cutoff of $500~\\mathrm{eV}$ for the plane waves. Energy minimization is achieved with the conjugate gradient approach with the convergence criteria of $10^{-6}$ eV and $\\bar{0.002}\\mathrm{eV}/\\mathring{\\mathrm{A}}$ for the energy and forces, respectively, employing a $14\\times14\\times1$ Monkhorst-Pack[55] $\\mathbf{k}$ -point grid. Spin polarized calculations are conducted to examine the possibility of magnetism in these structures. Mechanical properties are examined by conducting uniaxial tensile simulations. Density functional perturbation theory (DFPT) simulations over $4\\times4\\times1$ supercells are carried out to acquire the force constants. Phonon dispersion relations are then ac­ quired employing the PHONOPY code [56] with the DFPT results as inputs. For the analysis of electronic and optical features we consider the convergence criterion of $10^{-5}\\mathrm{eV}$ for the electronic self-consistent-loop and use a finer $\\mathbf{k}$ -point grid of $12\\times12\\times1$ . Since PBE/GGA un­ derestimates the position of conduction band maximums and system­ atically underestimate the band gap, the screened hybrid functional of HSE06 [57] is employed to provide more accurate estimations for the electronic and optical properties. \n\nCharge carrier mobilities are calculated from the deformation po­ tential approximation [58] via: $e\\hbar^{3}C_{2D}/K T m_{e}^{*}m_{d}{(E_{l}^{i})}^{2}.$ , in which $\\hbar$ is the reduced Planck constant, $K$ is the Boltzmann constant, $C_{2D}$ and $m^{*}$ are the elastic modulus and the effective mass of the carrier along the transport direction, respectively, $m_{d}$ is the average effective mass along both planar directions and $E_{l}^{i}\\operatorname*{mimics}$ the deformation energy constant of the carrier due to phonons for the i-th edge band along the transport direction. We examine the light absorption properties of the two systems by calculating their frequency-dependent dielectric matrix, neglecting the local field effects. The imaginary part $(\\varepsilon_{2})$ of the frequency-dependent dielectric matrix is using the following equation [59]: \n\n$$\n\\begin{array}{l}{{\\displaystyle\\varepsilon_{\\alpha\\beta}{}^{2}(\\omega)=\\frac{4\\pi^{2}e^{2}}{\\varOmega}\\mathrm{lim}_{q\\rightarrow0}\\frac{1}{q^{2}}\\sum_{c,\\nu,\\mathbf{k}}2w_{k}\\delta(\\varepsilon_{c\\mathbf{k}}-\\varepsilon_{\\nu\\mathbf{k}}-\\omega)}}\\\\ {{^{*}}}\\end{array}\n$$ \n\nwhere indices c and $\\nu$ refer to conduction and valence band states, respectively; $w_{k}$ is the weight of the $\\pmb{k}$ -point; and $u_{c{\\pmb k}}$ is the cell periodic part of the orbitals at the $\\pmb{k}$ -point. The real part $(\\varepsilon_{1})$ of the tensor is obtained from the Kramers–Kronig relation [59]. The absorption coef­ ficient is calculated from the following: \n\n$$\n\\alpha(\\omega)=~\\sqrt{2}\\omega~\\left[\\frac{\\sqrt{\\varepsilon_{1}^{2}+\\varepsilon_{2}^{2}}-\\varepsilon_{1}}{2}\\right]^{1/2}\n$$ \n\nIn this work, machine-learning interatomic potentials are developed to evaluate the phononic properties, lattice thermal conductivity, piezoelectric and flexoelectric responses of $M A_{2}Z_{4}$ monolayers. As the first study, in this work we extend the application of machine-learning interatomic potentials for the modeling of piezoelectricity and flex­ oelectricity. To this aim we train moment tensor potentials (MTPs)[60], which have been proven as accurate and computationally efficient models for describing the atomic interactions [61–63]. The training sets are prepared by conducting ab-initio molecular dynamics (AIMD) sim­ ulations over $4\\times3\\times1$ supercells with $2\\times2\\times1$ k-point grids. AIMD simulations are carried out at 50 and $600~\\mathrm{K},$ each for 1000 time steps. Half of the AIMD trajectories are selected to create the training sets. MTPs are then trained passively with the same procedure explained in our earlier studies [64,65] using the MLIP package [66]. The PHONOPY code [56] is employed to obtain phonon dispersion relations and har­ monic force constants over $5\\times5\\times1$ supercells using the trained MTPs for the force calculations [64,65]. Anharmonic interatomic force constants are calculated using the trained MTPs over $5\\times5\\times1$ super­ cells with taking into account the interactions with eights nearest neighbors. Lattice thermal conductivity is acquired by conducting the full iterative solutions of the Boltzmann transport equation using the ShengBTE [67] package, with harmonic and anharmonic interatomic force constants as inputs. Isotope scattering is considered in the Boltz­ mann transport solution in order to estimate the thermal conductivity of naturally occurring structures. For every structure the convergence with respect to the $q$ -grid is tested and depending on the structure between $61\\times61\\times1-101\\times101\\times1$ $q$ -grids are employed. Complete computa­ tional details for the MTP/ShengBTE coupling can be found in our earlier study [65]. \n\nIn order to calculate the electrical polarization due to mechanical deformation, we use a combination of short-range bonding interactions with long-range charge-dipole (CD) interactions. In this work trained MTPs are used to describe short-range interactions. In the CD model [68, 69], each atom is assumed to carry a charge $q$ and dipole moment $p$ . The estimation of $q$ and $p$ variables for each atom requires the parameter $R$ (related to polarizability) and $\\chi$ (electron affinity). $\\chi$ values for atom types N, Cr, P, Mo, W, Ge and Si are 0.07 [70], 0.676 [71], 0.746 [72], 0.747 [71], 0.816 [73], 1.233 [74] and 1.389 [75], respectively. To quantify R value for each atom type in $\\mathrm{MA}_{2}\\mathrm{Z}_{4}$ , we perform DFT simu­ lations for different sized atomic systems and the isotropic polarizability values from DFT $(\\alpha_{\\mathrm{DFT}})$ are evaluated. With these atomic configurations and assuming $R$ varies between 0.1 to $1.6\\mathring{A}$ for each atom type, the total polarizability $(\\alpha_{\\mathrm{CAL}})$ from the CD model can be estimated. After that, establishing a close match between $\\alpha_{\\mathrm{DFT}}$ and $\\alpha_{\\mathrm{CAL}}$ results the parameter R for each atom type in $\\mathrm{MA_{2}Z_{4}}$ monolayer. The GAUSSIAN software [76] is utilized to perform the DFT simulations for measuring $\\alpha_{\\mathrm{CAL}}$ . The calculation procedure of CD parameters and the implementation of the CD model incorporating into the atomic configuration under mechanical deformation are discussed in the earlier works in details [77,78]. \n\nWe evaluate the in-plane piezoelectric coefficients and out-of-plane bending coefficients for a square sheet of $\\mathrm{MA_{2}Z_{4}}$ monolayers of di­ mensions of nearly $80\\times80\\bar{\\mathring{\\mathsf{A}}}^{2}$ . Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [79] package is employed. To determine the in-plane piezoelectric coefficient, the following displacement field of $u_{y}=K_{t}y$ is used to the atomic system, where $y$ represents the atomic coordinate in the $y$ direction and $K_{t}$ represents the given in-plane strain. For the bending deformation, we apply displacement field $\\left(u_{z}\\right)$ of $u_{z}=$ $\\scriptstyle{\\frac{1}{2}}K_{b}y^{2}$ where $\\textstyle{\\frac{1}{2}}K_{b}$ represents the given strain gradient to the bending plane. Fig. 1 illustrates the schematics of loading schemes for both tensile and bending deformations. The axes in Fig. 1 show that sheet’s center is not having a displacement. The blue to red color gradient in the upper right inset represents the application of displacement $u_{y}$ according to the displacement field. The symmetrical color gradient from center to edges along the $y$ direction indicates the applied displacement $u_{z}$ . Here the diamond and hexagonal markers indicate the variation of strain components $\\epsilon_{y y}$ (tensile) and $\\epsilon_{z y}$ (bending). During deformation, the numerical values of these components for each atom are calculated ac­ cording to previous references [80,81]. Once the deformation is pre­ scribed, the boundary atoms are kept fixed whereas the interior atoms are allowed to relax using the constant temperature simulations (NVT ensemble). After that, the point charges and dipole moments are found for each atom by the CD model. The total polarization of the atomic system is calculated $\\begin{array}{r}{\\mathbf{P}=\\frac{\\sum_{i=1}^{n}\\mathbf{p}_{i}}{A};}\\end{array}$ where $A$ is the area and $n$ is the total number of atoms in the interior (excluding the atoms near the edges) atomic system. This polarization has contributions from both piezo­ electric and flexoelectric effects, which is \n\n![](images/4ddb26155a6cd17b50dee6413c191bc271d0fbade48ccc37d92b5fb1f110a90e.jpg) \nFig. 1. The distribution of strain along y direction for the $\\mathrm{MoSi_{2}P_{4}}$ sheet in both tensile $(\\mathrm{Kt}=0.002)$ and bending $(\\mathbf{K}\\mathbf{b}=0.0005\\textup{\\AA}^{-1})$ deformations. The upper right and lower left corner insets depict the schematic for the tensile and loading schemes, respectively. The color coding indicates the range for the displacements uy and uz associated with the deformation. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n$$\nP_{\\alpha}=d_{\\alpha\\beta\\gamma}\\epsilon_{\\beta\\gamma}+\\mu_{\\alpha\\beta\\gamma\\delta}\\frac{\\partial\\epsilon_{\\beta\\gamma}}{\\partial r_{\\delta}}\n$$ \n\nwhere $d_{\\alpha\\beta\\gamma}$ and $\\mu_{\\alpha\\beta\\gamma\\delta}$ are the piezoelectric and flexoelectric coefficients, respectively. Term $\\frac{\\partial\\epsilon_{\\beta\\gamma}}{\\partial r_{\\delta}}$ represents the strain gradient to the atomic sys­ tem. From the variation between polarization to strain and polarization to strain gradient, we estimate the piezo and flexoelectric coefficients, respectively. \n\n# 3. Results and discussions \n\nWe first introduce the structural features of $M A_{2}Z_{4}$ 1 $\\mathbf{\\boldsymbol{M}}=\\mathbf{\\boldsymbol{C}}\\mathbf{\\boldsymbol{r}}$ , Mo, W; $\\mathbf{A}={\\mathbf{\\mathit{S}}}\\mathbf{\\mathbf{\\mathit{i}}}$ , Ge; $Z=\\Nu$ , P) monolayers investigated in this work. In accor­ dance with TMD structures, two different lattices are considered for each composition, namely, 2H and 1T phases, in which M atom has trigonal prismatic and octahedral coordination, respectively. As illustrated in Fig. 2, each monolayer can be viewed as a 2H/1T-MoS2-like $\\ensuremath{\\mathbf{M}}\\ensuremath{\\mathrm{Z}_{2}}$ ( $\\mathrm{MoN}_{2}$ , taking $\\mathrm{MoSi_{2}N_{4}}$ as a demonstrator) monolayer sandwiched in-between two buckled honeycomb AZ (SiN) layers. The three layers are stacked on each other in a way that for 2H phase, M atom is located at the center of a trigonal prism building block with six A atoms, and the $\\mathbf{MZ}_{2}\\left(\\mathbf{MoN}_{2}\\right)$ layer is bonded to AZ (SiN) layers via vertically aligned A–Z (Si–N) bonds. The same holds for 1T phase with a difference that M atom can be thought of at the center of center of by $60^{\\circ}$ twisted trigonal prism building block with six A atoms. 2H- and $\\scriptstyle1\\mathrm{T}-M A_{2}Z_{4}$ compounds have a hexagonal primitive unitcell with space groups of $\\scriptstyle\\mathbf{P-}6\\mathbf{m}2$ (No. 187) and P3m1 (No. 156), respectively. Table 1 lists the structural, energetic, electronic, and magnetic properties of 2H- and $\\scriptstyle1\\mathrm{T}-M A_{2}Z_{4}$ compounds. The geometry optimized structures and their corresponding PAW po­ tentials in VASP native format are included in the data availability section. We first examine the dynamical stability by considering the calculated phonon dispersion relations, as illustrated in Fig. 3 and Fig. S1 for 2H and 1T phases, respectively. It is clear that for all considered $2\\mathrm{H}{\\cdot}M A_{2}Z_{4}$ monolayers the phonon dispersion relations are free of any imaginary frequency, confirming the dynamical stability. On the other side as illustrated in Fig. S1, except for the case of $1\\mathrm{T}\\mathrm{-}\\mathrm{Cr}\\mathrm{Ge}_{2}\\mathrm{N}_{4}.$ , for all other considered 1T $M A_{2}Z_{4}$ lattices two of the acoustic modes show imaginary frequencies, questioning their dynamical stability. Before we discuss the relative energetic stabilities of 2H and 1T phases of each of $M A_{2}Z_{4}$ compounds, their possible magnetic ground is carefully examined. To study possible magnetism in $M A_{2}Z_{4}$ monolayers, we investigate three competing states, namely, nonmagnetic (NM), ferro­ magnetic (FM), and antiferromagnetic (AF). Because there is only one M atom in the unit cell of $M A_{2}Z_{4}$ monolayers, we constructed a rectangular cell with two M atoms for each one to accommodate the AF spin order. The calculated total energies show that all $M o A_{2}Z_{4}$ and ${\\tt W}A_{2}Z_{4}$ mono­ layers possess a NM ground state. $\\mathrm{Cr}A_{2}Z_{4}$ monolayers however exhibit diverse magnetic characteristics. According to our results summarized in Table 1, $\\scriptstyle2\\mathrm{H-CrSi_{2}N_{4}}$ , $2\\mathrm{H-CrSi_{2}P_{4}}.$ , and $\\scriptstyle2\\mathrm{H-CrGe}_{2}\\mathrm{N}_{4}$ are found to have a NM ground state, $1\\mathrm{T}\\mathrm{-}\\mathrm{Cr}G e_{2}N_{4}$ favors a FM spin order and it carries a net moment of $2\\upmu_{\\mathrm{B}}/\\upepsilon\\mathrm{ell}$ , however, for the four rest monolayers of 1T$\\mathrm{Cr}S i_{2}N_{4},$ $1\\mathrm{T-Cr}S i_{2}P_{4},$ and 1T- $\\mathrm{Cr}G e_{2}P_{4}$ and $\\mathrm{\\backslashH-CrGe_{2}P_{4}}$ AF spin order with net $0\\upmu_{\\mathrm{B}}/\\mathrm{cell}$ is favored. We found that in all cases with FM and AF spin order, local magnetic moment is almost entirely located on the Cr. Previous theoretical studies have indicated that 2H-phase of single layer pristine $\\mathbf{MX}_{2}$ , where $\\mathbf{M}=\\mathbf{Cr}$ , Mo, W and $\\mathbf{X}=0$ , S, Se, Te is energetically more favorable than other configurations [82,83]. An almost similar stability trend is observed for 2H- and $\\begin{array}{r}{1\\mathrm{T}\\mathrm{-}\\mathbf{M}\\mathbf{A}_{2}\\mathbf{Z}_{4}}\\end{array}$ , with one exception in which FM $\\scriptstyle1\\mathrm{T}\\cdot\\mathrm{CrGe}_{2}\\mathrm{N}_{4}$ is more stable than its corresponding NM 2H phase by $0.007\\mathrm{eV}/$ atom. Small relative energies $(\\mathrm{E_{rel}})$ (0.032 eV/atom) are also found for $\\mathrm{CrSi_{2}P_{4}}$ and $\\mathrm{CrGe_{2}P_{4}}$ . The calculated relative energy differences in $M A_{2}Z_{4}$ compounds are appreciably smaller than that re­ ported for the single-layer $\\mathbf{MoS}_{2}$ (0.27 eV/atom) [83]. This may result in the coexistence of the two phases in experimentally fabricated samples. The $\\mathrm{{\\bfE}}_{\\mathrm{rel}}$ values for $\\mathrm{MA_{2}P_{4}}$ monolayers are generally smaller by half than those of $\\mathrm{{MA}_{2}N_{4}}$ . This could be due to the facts that the stability of octahedral coordination increases with increasing the radius of anion. \n\n![](images/1d571b8764252ccfc66f8cb68ef52919aabdd1778cede3daebc32442e0dcd975.jpg) \nFig. 2. Top and side views of $\\mathrm{MA_{2}Z_{4}}$ monolayers with (a and c) 2H and (b and d) 1T phases. The hexagonal primitive lattice is shown with the dashed lines. The monolayer thickness $(h)$ is defined as the normal distance between two boundary Z atoms plus their Van der Waals radiuses $(r_{\\nu d W})$ . $\\mathbf{M}\\mathbf{Z}_{2}$ motif for (e) 2H and (f) 1T phases are also shown. In this figure light blue and purple colors represent Z (N or P) atoms, wine color M (Cr or Mo or W) atoms, and orange color A (Si or Ge) atoms. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\nWe next investigate the electronic properties of $\\mathrm{MA_{2}Z_{4}}$ monolayer in 2H and 1T phases via calculating their electronic band structures along the high symmetry direction of the Brillouin zone. The HSE06 and PBE band structures of $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{Z}_{4}$ monolayers are depicted in Fig. 3 and those for the corresponding 1T phases are shown in Fig. S2. The pre­ dicted band gap values, nature of band gaps, and HSE06 transition kpoints are also listed in Table 1. It is conspicuous that this family exhibits diverse electronic properties and depending on their chemical compo­ sitions they show metallic to moderate band gap semiconducting nature. Several observations can be concluded from the band structure results, as follows: (1) All 2H monolayers are semiconducting except for 2H$\\mathrm{CrGe_{2}P_{4}}_{\\mathrm{:}}$ , which is found to be a AF metal. The predicted band gap values range from 0.31 eV for $\\scriptstyle2\\mathrm{H-CrGe}_{2}\\mathrm{N}_{4}$ to 2.57 eV for $2\\mathrm{H}{\\cdot}\\mathrm{WSi}_{2}\\mathrm{N}_{4}$ . (2) The valence band maximum (VBM) in 2H- ${\\cdot}\\mathrm{MA}_{2}\\mathrm{N}_{4}$ and $\\scriptstyle2\\mathrm{H-MA_{2}P_{4}}$ is located at Г and K points, respectively, while conduction band minimum (CBM) for all 2H semiconductors always occurs at K point. As a consequence, 2H$\\mathrm{MA}_{2}\\mathrm{N}_{4}$ are indirect band gap materials $(\\Gamma{\\to}\\mathrm{K})$ , while $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{P}_{4}$ are direct $\\mathrm{(K\\toK)})$ ) gap semiconductors. Predicted band gap values and transition $k$ -points for the experimentally synthesized $\\scriptstyle2\\mathrm{H-CrSi_{2}N_{4}}$ $(2.23\\mathrm{eV}$ , $\\Gamma{\\to}\\mathrm{K})$ are in very good agreement with those (2.297 eV, $\\Gamma{\\to}\\mathbb{K})$ reported in the original study [49]. Interestingly, for $2\\mathrm{H-CrSi_{2}N_{4}}$ and $2\\mathrm{H}{\\cdot}\\mathrm{MoSi}_{2}\\mathrm{N}_{4}$ the gap at point K is only $0.06\\mathrm{eV}$ larger than the indirect gap, indicating that these two monolayers can be considered as quasi-direct gap semiconductors. These observations are highly prom­ ising for potential applications in electronic and optoelectronic devices. (3) $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{N}_{4}$ show greater band gaps than corresponding $\\mathrm{MA_{2}P_{4}}$ counterparts. (4) Generally 1T monolayers exhibit appreciably smaller band gaps than their corresponding 2H lattices. More precisely, most of 1T monolayers even exhibit metallic character. In this regard the only dynamically stable lattice of $\\scriptstyle1\\mathrm{T-CrGe}_{2}\\mathrm{N}_{4},$ , is a half metal, and the others are semiconductors with band gaps smaller than $0.33\\mathrm{eV}$ (find Table 1 and Fig. S2). A very similar band gap trend is also observed for 1T and 2H phases of single layer transition metal dichalcogenides [84]. \n\nTable 1 Calculated structural, energetic, and electronic properties of $M A_{2}Z_{4}$ nanosheets in 2H- and 1T-phase. \n\n\n
LatticeLc (A)ah(A)bErel (eV/atom)cElectronic structuredTransition k-pointseμ(μB)f
8.073
1.80
1T3.4212.8280.032BE=OeV(M)e()0(AF)
28330323435634303634283634363535
...8.9f.8.8.
222
\n\nLc, h, $\\mathbf{E_{g}}$ and Erel are, respectively, hexagonal lattice constant, thickness, band gap and relative energy. Hexagonal lattice constants. b Effective thickness of a $\\mathrm{MA_{2}Z_{4}}$ monolayer is defined as the sum of normal distance between boundary atoms plus the Van der Waals diameter of Z atoms. c Relative stability of 2H- and 1T-phases of each compound defined as $\\mathrm{E_{rel}=E_{t o t}(2H{-}M A_{2}Z_{4})-E_{t o t}(1T{-}M A_{2}Z_{4})}$ . d PBE and HSE06 calculated band gaps. Abbreviations $\"\\mathrm{T}\"$ and $\"\\mathbf{D}\"$ indicate indirect and direct gap semiconducting character, respectively, and $\"\\mathbf{M}\"$ indicate metallic character. e Band gap transition k-points of HSE06 results. f Total magnetic moment per rectangular unitcell (two M atoms). Abbreviations \"NM\", \"FM\", and \"AF\" indicate nonmagnetic, ferromagnetic, and antiferromagnetic ground states spin order in $\\mathrm{MA}_{2}\\mathrm{Z}_{4}$ nanosheets, respectively. \n\n![](images/20992b9dbacbe4d2788b67df0fa1b820d78bf5f84d19f9152876836380108c94.jpg) \nFig. 3. Phonon dispersion relation of $2\\mathrm{H}{-}M A_{2}Z_{4}$ monolayer acquired using the MTP method. For several cases the DFPT results are also plotted using the dotted lines. \n\nTo better understand the nature of band edge states and also to rationalize some of the observed trends, we calculated the charge den­ sity distribution at VB(Г), VB(K) and CB(K) of each $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}Z_{4}$ mono­ layer, shown in Fig. S3. Our charge density analysis reveals that for all monolayers, VB(Г) is mainly constructed by $\\mathbf{M}{-}d_{z^{2}}$ orbital with minor contribution by $\\mathsf{Z}\\mathrm{-p_{z}}$ and $\\mathsf{A}{\\cdot}\\mathsf{p}_{\\mathrm{z}}$ orbitals, representing a ${\\upsigma}(\\mathbf{M}\\mathbf{-}\\mathbf{M})$ state hy­ bridized with ${\\mathfrak{o}}({\\mathsf{A}}{-}{\\mathsf{Z}})$ states. However, VB(K) is predominantly distrib­ uted over $\\mathbf{M}\\mathbf{Z}_{2}$ layer and it represents ${\\upsigma}(\\mathbf{M}{\\cdot}\\mathbf{M})$ state hybridized with ${\\mathfrak{o}}(\\mathbf{M}-\\mathbf{Z})$ states derived from M- $(d_{x^{2}-y^{2}},d_{x y})$ and Z- $(\\mathsf{p_{x}},\\mathsf{p_{y}},\\mathsf{p_{z}})$ orbitals. The CB(K) is solely derived from M- $(s,d_{z^{2}}$ ) orbitals. Our analysis indicates the key role of metal-metal interaction in constructing band edge states of these materials. Owing to the strong interaction between d orbitals of M atoms, the VB and CB are both highly dispersed, implying small effective masses and high charge carrier mobilities. From Fig. 4, it is evident that $\\mathrm{2H{-}M A_{2}N_{4}}$ monolayers exhibit greater VB and CB dispersions and consequently smaller electron and hole effective masses than those of ${2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{P}_{4}}$ monolayers. This observation is due to the smaller lattice constants of $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{N}_{4}$ monolayers which results in more effective metal-metal interaction (See Fig. S3) and consequently higher band dispersion. Here, we recall our observation above that $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{N}_{4}$ are indirect gap semiconductors $(\\Gamma{\\to}\\mathrm{K})$ , whereas $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{P}_{4}$ monolayer are direct gap semiconductors $\\mathrm{(K\\toK)}$ . By moving from ${2\\mathrm{H}{-}\\mathbf{M}\\mathbf{A}_{2}\\mathbf{P}_{4}}$ to 2H$\\mathrm{MA}_{2}\\mathrm{N}_{4}$ both VB(Г) and VB(K) are stabilized due to the stronger metalmetal interaction in $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{N}_{4}$ . However, because the planar $d_{x^{2}-y^{2}},d_{x y}$ orbitals in VB(K), higher d-d orbital overlap occur as compared to the $d_{z^{2}}$ orbitals in VB(Г), and VB(K) state becomes more deeply stabilized than VB(Г) state and the material turns into an indirect band gap semiconductor. \n\nAfter examining the stability and electronic features, we now explore the photocatalytic activity of $M A_{2}Z_{4}$ monolayers for water splitting reaction from a thermodynamic point of view. In order to achieve photocatalytic water splitting using a single semiconductor, a material must possess a band gap in the range of 1.23–3 eV to be able to harvest visible light. According to Table 1, only four of $M A_{2}Z_{4}$ monolayers satisfy this criterion, namely, 2H$\\mathrm{MoSi_{2}N_{4}},$ 2 $\\mathrm{R}{\\cdot}\\mathrm{MoGe}_{2}\\mathrm{N}_{4}.$ , $2\\mathrm{H}{\\cdot}\\mathrm{WSi}_{2}\\mathrm{N}_{4},$ , and $2\\mathrm{H}\\mathrm{-}\\mathsf{W G e}_{2}\\mathrm{N}_{4}$ with band gap values of 2.23, 1.27, 2.57, and $1.51\\mathrm{eV}$ , respectively. We recall that $2\\mathrm{H-MoSi_{2}N_{4}}$ is a quasi-direct gap material and the other three lattices are indirect gap semi­ conductors. In Fig. 5, the band edge position of these four monolayer calculated using HSE06 are shown with respect to the vacuum level. The standard potentials for the two half reactions of decomposition of water $\\mathrm{(2H^{+}(a q)+2e^{-}\\rightarrow H_{2}(g)}$ , $\\mathrm{H}_{2}\\mathrm{O}\\rightarrow2\\mathrm{H}^{+}+1/2\\mathrm{O}_{2})$ are also drawn at $\\mathbf{p}\\mathrm{H}=0$ and 7. For hydrogen evolution reaction (HER), the standard reduction po­ tential at $\\boldsymbol{\\mathrm{pH}}=0$ is $\\it-4.44\\:\\mathrm{eV}$ , while that of the oxygen evolution reaction (OER) is by $1.23\\mathrm{eV}$ lower than the HER level $\\left(-\\ 5.67\\ \\mathrm{eV}\\right)$ . In addition, the standard potential of both HER and OER sensitively vary with pH according to the Nernst equations of $\\mathbf{E^{red}(H^{+}/H_{2})}=-\\mathbf{\\nabla}4.44\\mathrm{{eV+pH}\\times0.059\\mathrm{{eV}}}$ and $\\mathrm{E^{ox}(H_{2}O/O_{2})=-5.67~e V+p H\\times0.059~e V}$ . Besides having a large band gap $\\left(>1.23\\mathrm{eV}\\right)$ , the band edge positions of a photocatalyst candidate must straddle the standard redox potentials of water (SRPW). In Fig. 5a, it can be clearly seen that band edge positions of $2\\mathrm{H-MoSi_{2}N_{4}}$ straddle the SRPW in both highly acidic $\\mathrm{(pH}=0)$ and neutral $(\\mathrm{pH}=7)$ conditions. However, those of $2\\mathrm{H}\\mathrm{-}\\mathsf{W}\\mathsf{S}\\mathrm{i}_{2}$ and $2\\mathrm{H}\\mathrm{-}\\mathsf{W G e}_{2}\\mathrm{N}_{4}$ straddle the SRPW only in highly acidic and neutral conditions, respectively. We predicted that the CBM of 2H$\\mathrm{MoGe}_{2}\\mathrm{N}_{4}$ occurs at appreciably lower energies than standard potential of OER reaction in acidic condition and therefore it cannot function as photo­ catalyst for water splitting. This was expectable due to a relatively small band gap in $2\\mathrm{H}{\\cdot}\\mathrm{MoGe}_{2}\\mathrm{N}_{4}$ monolayer. \n\n![](images/b8b14a357f598c45ce33f1f49cdecfec695132edf5074dfa8376392d4019c5cc.jpg) \nFig. 4. HSE06 and PBE band structures for $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}Z_{4}$ monolayers in their magnetic ground states. Black solid and blue dotted lines represent HSE06 and PBE band structures, respectively. The Fermi level is set to $0\\:\\mathrm{eV}$ . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) \n\n![](images/a4b8973ef5eb67ca12dfffa78825613a236911080a3583dbd70545b077798c49.jpg) \nFig. 5. (a) Band edge positions with respect to the vacuum level for those $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}Z_{4}$ mono­ layers with band gap larger than $1.23\\mathrm{eV}$ . For comparison, the potential of the two halfreactions of HER $\\mathrm{(H^{+}/H_{2})}$ and OER $\\mathrm{(H_{2}O/O_{2})}$ are also shown at $\\boldsymbol{\\mathrm{pH}}=0$ (solid horizontal lines) and $\\mathbf{p}\\mathbf{H}=7$ (dotted horizontal lines). (b) Optical absorption coefficient obtained using HSE06 functional for $2\\mathrm{H}\\mathrm{-}\\mathsf{W G e}_{2}\\mathrm{N}_{4}.$ , $\\mathsf{W S i_{2}N_{4}}$ $\\mathrm{MoGe_{2}N_{4}}$ and $\\mathrm{MoSi_{2}N_{4}}$ monolayers. The light incident is along the out-of-plane direction and isotropically polarized along the in-plane di­ rections. The energy range of visible light spectrum is also shown. \n\nIn addition to the two criteria investigated above, a photocatalyst material should also yield high electron and hole mobilities, so that the photogenerated electron and holes can participate in charge transfer process before they recombine. We estimated the electron and hole mobilities of the four monolayers along armchair and zigzag directions using the deformation potential theory (DPT) in combination with the effective mass approximation. It is found that both electron and hole mobilities are almost isotropic along armchair and zigzag directions. Our predicted electron and hole mobilities are, respectively, 200 and $1100\\ c m^{2}\\ \\mathrm{V}^{-1}\\ s^{-1}$ for $2\\mathrm{H}{\\cdot}\\mathrm{MoSi}_{2}\\mathrm{N}_{4}$ , 490 and $2190\\ c m^{2}\\mathrm{\\bfV}^{-1}\\mathrm{\\bfs}^{-1}$ for 2H$\\mathrm{MoGe_{2}N_{4}}.$ 320 and $2026\\thinspace{\\mathrm{cm}}^{2}{\\mathrm{V}}^{-1}{\\mathrm{s}}^{-1}$ for $2\\mathrm{H}{\\cdot}\\mathrm{WSi}_{2}\\mathrm{N}_{4}$ , 690 and $2490~\\mathrm{cm}^{2}$ $\\nabla^{-1}\\mathsf{s}^{-1}$ for 2H- $\\mathrm{WGe_{2}N_{4}}$ . Our calculated mobilities for 2 $\\mathrm{\\cdotH-MoSi_{2}N_{4}}$ are in very good agreement with those reported in a previous work ${\\cdot}\\mathrm{\\sim}270$ and $12\\dot{0}0\\dot{\\mathrm{cm}}^{2}\\dot{\\mathrm{V}}^{-1}\\mathrm{s}^{-1}$ for electron and hole mobilities, respectively) [49]. The calculated mobilities are much larger than those theoretically esti­ mated for $\\mathbf{MoS}_{2}$ monolayer (72.16 and $\\mathbf{\\bar{200.52\\cm^{2}V^{-1}}}s^{-1}$ for electron and hole mobilities, respectively) [85]. In all cases, the electron mobility is found to be a few times larger than the hole mobility. The large dif­ ference between electron and hole mobilities may enhance electron-hole separation efficiency and photocatalytic activity. A photocatalyst is also required to exhibit absorption in visible light. We thus examine the optical absorption of these monolayers by computing their dielectric functions and absorption coefficients $\\left(\\upalpha(\\upomega)\\right)$ using the HSE06 functional. Fig. 5b depicts absorption spectrum in response to the light incident along the out-of-plane direction and polarized along the in-plane di­ rections (find Fig. S4 for more details). Considered monolayers are all found to exhibit isotropic absorption, due to their highly symmetrical lattice. Although $2\\mathrm{H}{\\cdot}\\mathrm{MoSi}_{2}\\mathrm{N}_{4}$ is a quasi-direct gap semiconductor and the three others are indirect gap, it is evident that the four monolayers absorb light in the visible range. The calculated absorption coefficients $(10^{5}\\thinspace\\mathrm{cm}^{-1})$ are comparable to those of perovskites, which are known to be highly efficient for solar cells. \n\nWe next examine the mechanical responses of $2\\mathrm{H}{\\cdot}M A_{2}Z_{4}$ monolayers according to the uniaxial stress-strain curves. In these simulations the stresses along the two perpendicular directions of the loading are ensured to stay small. Along the normal direction of the monolayers this objective is automatically achieved upon the geometry optimization due to the contact with vacuum. For the other planar direction, the stress is reached to a negligible value by altering the periodic box size [86]. Mechanical responses are evaluated along the armchair and zigzag (as shown in Fig. 2) directions to assess the anisotropy. The acquired stress-strain relations of $M A_{2}Z_{4}$ monolayers for the loading along the armchair and zigzag directions are illustrated in Fig. 6. The key me­ chanical properties including the elastic modulus and tensile strengths are also summarized in Table 2. As it is clear, for all the considered monolayers loaded along the armchair and zigzag directions, the initial linear parts of the stress-strain relation coincide, confirming the isotropic elasticity. Moreover, by increasing the strain level and devi­ ating from the initial linear response, the samples loaded along the armchair direction start to exhibit higher stresses than those along the zigzag direction. \n\nAcquired results suggest that depending on the terminating elements of N or P atoms, $M A_{2}Z_{4}$ nanosheets show different behaviors. For the $\\mathrm{MA}_{2}\\mathrm{N}_{4}$ monolayers loaded along the armchair direction, the maximum tensile strengths happen at lower strains than the zigzag direction. For these structures, while the structures show higher stretchability along the zigzag direction, the tensile strengths along the both loading di­ rections are close. In $\\mathrm{MA_{2}P_{4}}$ nanosheets, the maximum tensile strengths however occur at closer strain levels for the loading along armchair and zigzag. This way, $\\mathrm{MA_{2}P_{4}}$ nanosheets show noticeably higher tensile strengths along the armchair than the zigzag direction. It is found that by increasing the atomic weight of the core atoms in $M A_{2}Z_{4}$ nanosheets, the elastic modulus increases slightly. The elastic modulus of $\\mathrm{MoSi_{2}N_{4}}$ is found to be $487\\mathrm{GPa}$ , showing an excellent agreement with experi­ mentally measured value of $491.4\\pm139.1\\$ GPa [49]. For the tensile strength, ${\\tt W A}_{2}Z_{4}$ nanosheets exhibit higher values than $\\mathbf{MoA}_{2}\\mathbf{Z}_{4}$ and $\\mathrm{CrA_{2}Z_{4}}$ counterparts. The tensile strength of $\\mathrm{MoSi_{2}N_{4}}$ is predicted to be $55.4\\substack{-57.8\\mathrm{GPa}}$ , which is within the range of experimentally reported value of $65.8\\pm18.3$ GPa [49]. From the acquired results it is clear that the mechanical properties are mainly affected by the type of terminating atoms, and such that lattices composed of N atoms show substantially higher mechanical characteristics than those terminated with P atoms. It is conspicuous that while the core atoms slightly affect the mechanical properties, the increasing of the atomic weight of A and Z atoms in $M A_{2}Z_{4}$ nanosheets remarkably suppress the both elastic modulus and tensile strength. From the structural point of view, in $M A_{2}Z_{4}$ nanosheets only M–Z and A–Z bonds are partially oriented along the loading di­ rection. These bonds are thus directly involved in the deformation and can result in a dominant effect on the overall mechanical properties. From the general chemistry we know that chemical bonds formed with N atoms are appreciably stronger than those made with P atoms and moreover Si–N bond is stronger than Ge-N one, resulting in the maximal elastic modulus for $\\mathrm{MSi_{2}N_{4}}$ monolayers. It is also noticeable that the $\\mathrm{MSi_{2}N_{4}}$ lattices normally exhibit higher maximal stretchability. It can be thus concluded that in order to reach maximal mechanical characteris­ tics, $\\mathrm{MSi_{2}N_{4}}$ nanosheets show superiority and the type of M core atom is not expected to result in substantial changes. \n\n![](images/393efa43967ccad913d4d70eca2d1bfe6bc134a1c7b74e959a9ade162583061b.jpg) \nFig. 6. Uniaxial stress-strain responses of $2\\mathrm{H}{\\cdot}M A_{2}Z_{4}$ monolayers for the loading along the armchair and zigzag directions. \n\nTable 2 Summarized elastic modulus (E) and tensile strength (TS) of $2\\mathrm{H}{-}M A_{2}Z_{4}$ monolayers along the armchair (Arm.) and zigzag (Zig.) directions. \n\n\n
LatticeE (GPa)TsZig. (GPa)TSArm. (GPa)K (W/mK)Contribution
ZATALAOptical
CrSi2N446857.855.43320.240.280.190.29
MoSi2N448756.753.34390.210.260.320.21
WSi2N450659.255.55030.250.220.320.21
CrGe2N434038.738.11980.210.260.330.20
MoGe2N436240.342.12860.190.260.320.24
WGeN438442.644.53220.240.210.230.32
CrSi2P415418.521.21200.230.250.320.20
MoSiP415917.521.21220.230.200.330.24
WSi2P416718.822.01290.220.220.310.25
CrGe2P413515.217.7630.210.250.330.21
MoGe2P413915.318.4630.170.200.370.26
WGe2P414516.519.3640.170.200.290.34
\n\nRoom temperature lattice thermal conductivity (K) and contribution of ZA, TA and LA acoustic and optical modes on the overall conductivity. \n\nWe next evaluate the lattice thermal conductivity of $2\\mathrm{H}{\\cdot}M A_{2}Z_{4}$ monolayers at the room temperature using the full iterative solutions of the Boltzmann transport equation. For the solution of lattice thermal conductivity, the anharmonic interatomic force constants for every composition is obtained by computing the interatomic forces for 784 systems, each one consisting of 175 atoms. In Fig. 3 the phonon dispersion relations of $2\\mathrm{H}{\\cdot}M A_{2}Z_{4}$ monolayers are depicted. For few cases the MTP-based results are compared with those by DFPT method, which show excellent agreements, in accordance with our earlier study results [64]. In principle, exhibiting a wider or narrower dispersion for a particular band, particularly for the acoustic modes, reveal faster or slower group velocity, respectively. Moreover, the phonon bands with narrow dispersions crossing each other may increase scattering and result in lower thermal conductivity. By considering the range of fre­ quencies for the phonons, it is clear that the type of the core atom shows marginal effects. In contrast, by changing the type of terminating atom the phonon dispersions and the maximum range of frequencies change considerably. In general, $\\mathrm{\\Delta\\mathbf{MA}_{2}N_{4}}$ monolayers show higher frequencies than $\\mathrm{MA_{2}P_{4}}$ counterparts. Similarly, $\\mathrm{MSi_{2}Z_{4}}$ lattices show wider phonon dispersions than $\\mathrm{MGe_{2}Z_{4}}$ lattices. As mentioned earlier, the compression of phonon bands may result in lower group velocity and higher scattering and subsequently lower thermal conductivity. Therefore, it is expected that the lattice thermal conductivity decreases by going from $\\mathrm{MSi_{2}N_{4}}$ to $\\mathrm{MGe_{2}N_{4}}$ , $\\mathrm{MSi_{2}P_{4}}$ and $\\mathtt{M G e_{2}P_{4}}$ . In Table 2 we also summarized the values of room temperature lattice thermal conductivity for 2H $\\mathrm{MA_{2}Z_{4}}$ monolayers, which confirms this trend. Worthy to mention that the studied monolayers are all found to show isotropic lattice thermal conductivity. In Fig. S5, we compare the phonons group velocity of $\\mathrm{MoSi_{2}N_{4}}$ , $\\mathrm{MoGe_{2}N_{4}}$ , $\\mathrm{MoSi_{2}P_{4}}$ and ${\\bf M o G e}_{2}{\\bf P}_{4}$ monolayers, respectively, which reveal noticeable suppressions of phonon group velocities and thus explaining the observed decreasing trend in thermal conductivity. \n\nAs we discussed earlier, by increasing the weight of the core atom the elastic modulus of $M A_{2}Z_{4}$ nanosheets increases. Acquired results reveal that by increasing the atomic weight of the core atom the thermal conductivity of $M A_{2}Z_{4}$ monolayers increases, which is consistent with the classical theory that expects a higher thermal conductivity for stiffer systems. The higher thermal conductivity of ${\\tt W A}_{2}Z_{4}$ than $\\mathbf{MoA}_{2}\\mathbf{Z}_{4}$ is also consistent with the reported trend for the $\\mathsf{W S}_{2}$ and $\\mathbf{MoS}_{2}$ monolayers [87]. In Table 2, we also compare the contribution of acoustic and op­ tical modes on the overall lattice thermal conductivity. It is conspicuous that the acoustic modes are the main heat carriers in the studied systems, by average yielding $75\\%$ of the total phononic thermal conductivity. As an example, in Fig. S6 we compare the phonon lifetime of $\\mathsf{W S i_{2}N_{4}}$ and $\\mathrm{MoSi_{2}N_{4}}$ monolayers. Our results generally show noticeably higher lifetimes for the acoustic modes (low range of frequencies) in $\\mathsf{W S i_{2}N_{4}}$ in comparison with the $\\mathrm{MoSi_{2}N_{4}}$ counterpart. Since the acoustic modes are the main heat carriers in these systems, it can be concluded that the higher scattering rates of acoustic modes in $\\mathrm{MoSi_{2}N_{4}}$ monolayer decrease the phonons’ lifetime and result in a lower thermal conduc­ tivity than $\\mathsf{W S i}_{2}\\mathrm{N}_{4}$ counterpart. In Fig. S7 we also compare the cumu­ lative thermal conductivity as a function of phonons mean free path, which reveals that the lattice thermal conductivity usually converges for the lengths between 20 and $100~{\\upmu\\mathrm{m}}$ . Our results reveal a consistent trend for the elastic modulus and lattice thermal conductivity, such that a $M A_{2}Z_{4}$ monolayer with a higher elastic modulus shows a higher thermal conductivity as well. It can be thus suggested that in order to reach a noticeably high thermal conductivity, W core atom is more favorable than Mo and Cr counterparts. The thermal conductivity of $\\mathrm{WSi_{2}N_{4}}$ and $\\mathrm{MoSi_{2}N_{4}}$ monolayers are found to be 503 and $439\\mathrm{{W/mK}}$ which are by several folds higher than $\\boldsymbol{\\mathsf{W S}}_{2}$ and $\\mathbf{MoS}_{2}$ monolayers [87]. The remark­ ably high thermal conductivity of $\\mathrm{{MSi_{2}N_{4}}}$ nanosheets is highly prom­ ising for the thermal management systems. Worth noting that while the thermal conductivity of these novel 2D systems are yet by around 8 folds lower than that of the graphene, but their semiconducting electronic nature is more appealing for the thermal management in nano­ electronics and Li-ion batteries than the semimetal character of graphene. \n\nFinally, we explore the piezoelectric and flexoelectric responses of this novel class of 2D materials. Fig. 7a and b show the variation of polarization $P_{y}$ with strain $\\epsilon_{y y}$ in $\\mathrm{MA_{2}Z_{4}}$ monolayers. We first consider $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathrm{MoSi_{2}P_{4}}$ monolayers for exploring the variation in polar­ ization with deformation. As it is clear, a linear variation between $P_{y}$ and $\\epsilon_{y y}$ exists. The atomic deformations using the displacement filed $u_{y}$ helps to dismiss the flexoelectric part of polarization from Eq. (3). In the case of tensile deformation, Fig. 7 shows nearly constant variation for strain component $\\epsilon_{y y}$ along the y direction. This confirms that strain gradient is zero and removes the flexoelectric contribution during the tensile deformation $\\biggl(\\mu_{\\alpha\\beta\\gamma\\delta}\\frac{\\partial\\epsilon_{\\beta\\gamma}}{\\partial r_{\\delta}}=0\\biggr)$ βγδ∂ϵrβγ = 0). Note that the strain values represented in Fig. 7 are the averaged values of the atomic strain over 23 equally spaced bins along the y direction. The wavy nature of the strain variation is due to the uncontrollable out-of-plane thermal fluctuations. The slope of variation between $P_{y}$ and $\\epsilon_{y y}$ is the piezoelectric coefficient $d_{y y y}.$ , which is $2.293~\\mathrm{nC/m}$ for $\\mathrm{MoSi_{2}N_{4}}$ and $0.890~\\mathrm{nC/m}$ for $\\mathrm{MoSi_{2}P_{4}}$ . In general, the dipole moment of an atom depends on the effective atomic polarizability and total electric filed induced by the charges and dipoles. The unit cell polarizability of $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathbf{MoSi_{2}P_{4}}$ are 36.372 and $80.274\\hat{\\cal A}^{3}$ , respectively. Fig. 8a and b show the atomic configuration for $\\mathrm{MoSi_{2}N_{4}}$ system at zero strain (stress-free) and at a strain of 0.01, respectively. The total electric field difference $\\Delta\\left(E_{y}^{q}+E_{y}^{p}\\right)$ between these configurations is $182.721\\mathrm{V}/\\tilde{A}$ in $\\mathrm{MoSi_{2}N_{4}}$ and $37.212\\mathrm{V}/\\tilde{A}$ in $\\mathrm{MoSi_{2}P_{4}}$ monolayers. The ratio of polarizability $\\Delta\\left(E_{y}^{q}+E_{y}^{p}\\right)$ between $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathrm{MoSi_{2}P_{4}}$ is about 2.225, which is in a close match with the ratio of piezoelectric coefficients. \n\nFig. 8c shows the dipolar distribution for $\\mathrm{MoSi_{2}N_{4}}$ nanosheets under the deformed configuration. The dipole moment $\\left(p_{y}\\right)$ is nearly zero for all the N (B, D, F, G, I and K labels) atoms and 0.012 for Mo atom (label A). Whereas the Si atoms (C and J labels) left to Mo atom exhibit \n\n$00.224~e\\hat{A}$ as $p_{y}$ and right (E and H labels) to Mo atom show $0.125~e\\mathring{A}$ . The change in dipole moment between Si atoms is due to the differences in the elongation in the bond $\\mathtt{C-D}$ and $\\tt D-E$ . For undeformed $\\mathrm{MoSi_{2}N_{4}}$ (Fig. 8a), C–D and D-–E bond lengths are about $1.755\\:\\mathring{A}.$ . The symmetric bond lengths induce equal and opposite local electric fields, which does not help to generate the dipole moment. Because of the tensile defor­ mation, the C–D bond stretches to 1.794 $\\hat{A}$ and D–E bond compresses to $1.696\\mathring{A}$ . This difference in bond lengths breaks the electric field sym­ metry and induce dipole moments according to the local electric field strength. Similarly, the changes in bond lengths connected to Mo atom helps to induce the observed smaller dipole moment. The changes in electric fields implies the importance of $\\pi-\\sigma$ and $\\sigma-\\sigma$ interactions originated across the valence and bonding electrons in generating the dipole moments. The electron affinity of N is higher compared to Mo and Si atoms, which means N atoms are reluctant to change their charge state. The difference in charge state for atom labels B, D and F between strained and unstrained configurations is about $0.002e$ . The smaller change in charge represent that there exists a weak transfer of charge to atom N. This reduce the $\\pi-\\sigma$ or $\\sigma-\\sigma$ interactions in $\\mathsf{N}$ and induce low dipole moments. Whereas, for atom label C the difference in charge is about 0.0426e, which shows an easy transfer of charge to Si atom and thus resulting in high dipole moment via enhanced $\\pi$ and $\\sigma$ interactions. The change in charge state for atom label E is about 0.01e, which results into a low dipole moment. We note the similar observations for atoms below the Mo atom in Fig. 8c. Finally, the total dipole moment of $\\mathrm{MoSi_{2}N_{4}}$ is predominantly from the Si atoms. The sum over these dipole moments across all the unitcells leads to the observed high dipole moment and polarization for $\\mathrm{MoSi_{2}N_{4}}$ . We consider $\\mathrm{MoSi_{2}P_{4}}$ atomic configuration at the same strain state (as shown in Fig. 8c). Here, there is an improvement of the dipole moment of $\\mathrm{~\\bf~P~}$ atoms over $\\mathsf{N}$ atoms in $\\mathrm{MoSi_{2}N_{4}}$ . The low electron affinity of $\\mathbf{P}$ over N helps to change their charge state easily and allow for increasing the $\\pi-\\sigma$ and $\\sigma-\\sigma$ in­ teractions, which helps in the form of increasing the $E_{y}^{q}$ and $E_{y}^{p}$ parts of the total electric field. However, the total dipole moment or polarization of $\\mathrm{MoSi_{2}P_{4}}$ is much lower than $\\mathrm{MoSi_{2}N_{4}}$ due to the oppositely induced dipole moments of Si and P atoms. Besides, Mo atoms also reduce the total dipole moment due to the increased electric field effect from the P atoms. It can be thus concluded that due to the chemical nature of N and P atoms, $\\mathrm{MoSi_{2}N_{4}}$ exhibits a large dipole moment compared to $\\mathrm{MoSi_{2}P_{4}}$ under tensile deformation. \n\n![](images/67e71bae8edbf26242dbd9a10f92b16fbf9303073c6845e2a2530a044ac92174.jpg) \nFig. 7. The variation of polarization of $P_{y}$ with strain $\\epsilon_{y y}$ for (a) $\\mathrm{MSi_{2}Z_{4}}$ and (b) $\\mathrm{MGe_{2}Z_{4}}$ systems. The bending induced polarization $P_{z}$ with strain gradient ∂ϵzy for (c) $\\mathrm{MSi_{2}Z_{4}}$ and (d) $\\mathrm{{MGe}_{2}Z_{4}}$ systems. The solid lines indicate the linear fitting to the respective simulation data. \n\n![](images/6446cde4328b64879e379d1404048b1aa742fdcbd51229c856c629d1ebe376cc.jpg) \nFig. 8. Atomic configuration for $\\mathrm{MoSi_{2}N_{4}}$ system at (a) undeformed state and (b) tensile deformed state with strain 0.01. (e) represents the atomic configuration during the bending deformation at strain gradient of $0.3\\mathring\\mathrm{A}^{-1}$ . (c) and (d) shows the selected unitcell atoms in the tensile and bending deformed configurations. The arrows indicate the respective dipole moments. $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathrm{MoSi_{2}P_{4}}$ unitcells are included in (c) and (d) panels, respectively. \n\n$\\mathrm{CrSi_{2}Z_{4}}$ and $\\mathrm{{WSi_{2}Z_{4}}}$ nanosheets also follow the above observations during the comparison between N and P substitution. The piezo coeffi­ cient for $\\mathrm{CrSi_{2}N_{4}}$ and $\\mathsf{W S i_{2}N_{4}}$ are 3.687 and $3.760~\\mathrm{nC/m}$ , respectively and $d_{y y y}$ for $\\mathrm{CrSi_{2}N_{4}}$ is by a factor of 1.6 higher than that of the $\\mathrm{MoSi_{2}N_{4}}$ \n\nIn $\\mathrm{CrSi_{2}N_{4}}$ , the ratio of polarizability (from Table 3) times $\\Delta\\left(E_{y}^{q}+E_{y}^{p}\\right)$ \n\nTable 3 Total polarizability estimated by DFT $(\\alpha_{D F T})$ and the present CD model $(\\alpha_{C A L})$ Atomic polarizability $(R)$ in $2\\mathrm{H}{\\cdot}\\mathrm{MA}_{2}\\mathrm{Z}_{4},$ , $d_{y y y}$ and $\\mu_{y z y z}$ are the tensile piezoelectric coefficient and out-of-plane bending flexoelectric coefficient, respectively. \n\n\n
LatticeαDFT (A3)αCAL (A3)RM (A)Ra (A)Rz (A)dyy (nC/ m)(nC/ m) Myzyz
MoSi2N436.37235.9681.0061.3860.5052.2930.007
MoSi2P480.27476.5191.2551.4401.0220.8900.041
MoGe2N441.02340.9131.2231.4430.5201.7750.004
MoGe2P460.16656.4861.2011.4280.9370.2680.021
CrSi2N435.45235.0631.0971.4090.6503.6870.009
CrSi2P477.09177.1111.2421.4431.0230.8240.033
CrGe2N433.28232.7271.2241.4700.6933.1630.004
CrGe2P481.12381.8091.2891.5650.7700.1910.007
WSi2N439.51937.9651.1711.4500.6583.7600.001
WSi2P494.22688.0791.3161.7460.6680.3670.017
WGe2N445.00142.0981.1141.4020.7162.0770.047
WGe2P491.19486.7451.2821.7630.7500.3020.008
\n\nover $\\mathrm{MoSi_{2}N_{4}}$ is about 1.345, which is nearer to the observed increase in piezoelectric coefficients. Here Si atoms left to Cr obtain a dipole moment of 0.595 and right to Cr show 0.367 and these values are higher than those observed in $\\mathrm{MoSi_{2}N_{4}}$ . Cr and N atoms show further lower dipole moments than in $\\mathrm{MoSi_{2}N_{4}}$ due to their high electron affinities. Thus the given mechanical deformation is efficiently used only by the Si atoms to change their charge state and induce larger $\\pi-\\sigma$ and $\\sigma-\\sigma$ in­ teractions, which enhances the local electric fields and results in higher dipole moments. For the case of $\\mathrm{{WSi_{2}N_{4}}}$ , W gets a dipole moment of $0.031\\mathrm{e}\\hat{A}$ , which is by 2.58 times higher than the dipole moment of atom Mo in $\\mathrm{MoSi_{2}N_{4}}$ . The lower electron affinity of atom W helps to raise its dipole moment over Mo and $\\mathrm{cr}$ . The low electron affinity helps to change the charge state easily and develop required interactions to induce dipole moment. The Si atoms left to W have $0.216\\mathrm{e}\\mathring{A}$ and right atoms show $0.114\\mathrm{e}\\mathring{A}$ as dipole moments, which are reduced by a small amount when compared to Si in $\\mathrm{MoSi_{2}N_{4}}$ . The increased contribution from W helps to increase the total polarization of the $\\mathrm{{WSi_{2}N_{4}}}$ system. In total, the ratio of polarizability times the change in electric field across configurations of $\\mathsf{W S i}_{2}\\mathrm{N}_{4}$ and $\\mathrm{MoSi_{2}N_{4}}$ is about 1.640. This ratio is in close agreement with the proportion between their piezoelectric co­ efficients. Identical observations appear in enhancing the piezoelectric coefficients for materials involved with Ge (find Fig. 7b). \n\nFig. 7c shows the variation of polarization $P_{z}$ due to the bending deformation by increasing the strain gradients. The values of $P_{z}$ are calculated similar to $P_{y}$ and divided with thickness mentioned in Table 1 to match with the units of flexoelectric coefficients. Here also, Fig. 1 also confirms the linear variation for the strain component $\\epsilon_{z y}$ with respect to bins in y-direction during the bending deformation. The linear variation further cancels the total strain $\\epsilon_{z y}$ and maintains the piezoelectric contribution $d_{\\alpha\\beta\\gamma}\\epsilon_{\\beta\\gamma}$ as zero for bending deformation. However, the slope of the $\\epsilon_{z y}$ component is highly in match with the given strain gradient $\\scriptstyle{\\frac{1}{2}}K_{b}$ at the given load step. $\\mathrm{MoSi_{2}N_{4}}$ atomic configuration in Fig. 8e is at $\\scriptstyle{\\frac{1}{2}}K_{b}$ or $\\frac{\\partial\\epsilon_{z y}}{\\partial y}$ equal to $0.3\\mathring{\\mathrm{~A~}}^{-1}$ . Note that the training dataset used to generate MTP does not contain any information related to bending deformation. However, the developed MTP can predict the bending deformation. The atomic configuration in Fig. 8e deformed uniformly in the left and right parts of the sheet. We consider the same unitcell used in tensile deformation for dipole moment analysis in bending case. For $\\mathrm{MoSi_{2}N_{4}}.$ , the N atoms have low dipole moments due to the weak $\\pi-\\sigma$ interactions. Here top and bottom Si atoms are having dipole moments opposite to each other. The asymmetry in bond and angle values asso­ ciated with Si atoms leads to change in the dipole moments via the local electric fields. During bending, the bond C–D compressed to $1.726\\mathring{A}$ and D–E stretched to $1.771\\mathring{A}.$ , respectively. However, the change in bond angle $\\angle B C D$ is higher than bond angle ∠FED. Since the angle change induces a shift in buckling height between successive atoms, which helps to achieve a different hybridization state via the $\\pi-\\sigma$ interactions. These changes in bond length and angles lead to the higher dipole moment for the C labeled-atom than the E one. For the case of tensile deformation atom labels, C and J have identical dipole moments. In contrast to tensile case, the dipole moments for atom label J is lower than dipole moment of atom C because of the changes in local atomic configuration in response to the upward bending deformation. Between atom labels H and E also similar changes in the dipole moments are observed. In total, these changes in dipole moments added up, to produce polarization. The linear variation between $P_{z}$ and strain gradient for $\\mathrm{MoSi_{2}N_{4}}$ gives a flexoelectric coefficient of $0.007\\mathrm{nC/m}$ . In case of $\\mathbf{MoSi_{2}P_{4}},$ Si atoms are performing in the similar manner as $\\mathrm{MoSi_{2}N_{4}}$ . P atoms (B, F, G and K) produce dipole moments in the direction of nearest bonded Si atoms. Interestingly, atoms D and I (type P) produce significant contribution to the total dipole moment because of the differences in angle and bond lengths, which induce different local electric fields for these atoms and producing non vanishing dipole moments. This helps to increase the total dipole moment of $\\mathrm{MoSi_{2}P_{4}}$ unitcell to 6.87 times higher than $\\mathrm{MoSi_{2}P_{4}}$ counterpart. The rise in dipole moment reflected in the increased flexoelectric coefficient for $\\mathrm{MoSi_{2}P_{4}}$ , which is $0.041~\\mathrm{{nC/m}}$ Considering $\\mathrm{CrSi_{2}P_{4}}$ material, which shows a flexoelectric coefficient of $0.033\\mathrm{nC/m}$ and it is a little smaller as compared to $\\mathrm{MoSi_{2}P_{4}}$ . Here also, we observed that Si atoms are producing similar dipole moments as in the case of $\\mathrm{MoSi_{2}N_{4}}$ . The dipole moments from P atoms left and right to the $\\mathrm{cr}$ atom is cancelling out. Whereas, the top and bottom $\\mathrm{~\\bf~P~}$ atoms produce a difference of $0.0182{\\mathrm e}\\mathring{A}$ , which is about 0.86 times lower than that produced in $\\mathrm{MoSi_{2}P_{4}}$ . This ratio is nearly identical to the flexo­ electric coefficient ratio between $\\mathrm{CrSi_{2}P_{4}}$ and $\\mathrm{MoSi_{2}P_{4}}$ . For the $\\mathsf{W S i_{2}P_{4}}.$ the flexoelectric coefficient is only $0.017~\\mathrm{nC/m}$ . In addition to the similar observations made from $\\mathrm{MoSi_{2}P_{4}}$ and $\\mathrm{CrSi_{2}P_{4}}.$ W core atom ac­ quires higher $p_{z}$ compared Mo and Cr. Nonetheless, its direction is opposite to the resultant dipole moment from other atoms. This makes the total dipole moment of these system lower compared to others. \n\nAmong all studied $\\mathrm{MA_{2}Z_{4}}$ monolayers, $\\mathrm{WGe_{2}N_{4}}$ shows $0.047~\\mathrm{{nC/m}}$ flexo coefficient (find Table 3), which is by around 1.5 times higher than $\\mathbf{MoS}_{2}$ [78]. Here also W acquires a higher dipole moment $p_{z}$ due to the lower electron affinity. This dipole moment is in the direction of Ge dipole moment, similar to the case of $\\mathrm{MoSi_{2}N_{4}}$ shown in Fig. 8d. As a result, the total dipole moment variation is higher compared to other Ge based monolayers shown in Fig. 7d. An interesting point to note is, nanosheets terminated with N atoms exhibit high piezoelectric proper­ ties. The current asymmetry in upper and lower portions of the M core atom in the unitcell is not sufficient to further enhance the flexoelectric coefficient. But it appears that Janus type of $\\mathrm{MA_{2}Z_{4}}$ (like upper and bottom parts contain N, Si and P, Ge, respectively) may substantially enhance the flexo coefficient over Janus TMDs, which requires future examinations. When comparing the piezo coefficient of $\\mathrm{MA_{2}Z_{4}}$ , they show superior piezoelectric coefficient over existing materials like $\\mathbf{MoS}_{2}$ [78,88,89], XTeI [90] and Janus TMDs [91,92]. A recent DFT study predicted that SnOSe Janus structure has the highest piezo coefficient of $1.12\\mathrm{nC/m}$ [93] among the known 2D materials. Notably, our result for the piezo coefficient of $\\mathrm{MoSi_{2}N_{4}}$ is already by around 2 times higher than that of the SnOSe. More importantly, $\\mathrm{CrSi_{2}N_{4}}$ and $\\mathrm{WSi_{2}N_{4}}$ nanosheets even outperform $\\mathrm{MoSi_{2}N_{4}}$ (find Table 3). It can thus be concluded that $\\mathrm{MSi_{2}N_{4}}$ nanosheets record the highest piezoelectric coefficient among the all 2D materials. Nonetheless they show moderate flexoelectricity which can be very possibly enhanced by considering the Janus lattices. \n\n# 4. Concluding remarks \n\nMotivated by the latest experimental advance in the fabrication of centimeter-scale high-quality single-layer $\\mathrm{MoSi_{2}N_{4}}$ , in this work we conduct extensive first-principles simulations to explore the mechanical properties, lattice thermal conductivity, piezoelectric response and photocatalytic and electronic features of $M A_{2}Z_{4}$ $[\\mathbf{M}=\\mathbf{C}\\mathbf{r}$ , Mo, W; $\\mathbf{A}=S\\mathbf{i}$ , Ge; $\\begin{array}{r}{Z=\\mathrm{N}.}\\end{array}$ , P) monolayers. We show that depending on the atomic configuration and compositions, the studied nanomembranes show diverse electronic features from antiferromagnetic metal to half metal and to semiconductors with band gaps ranging from 0.31 to $2.57\\mathrm{eV}$ . Interestingly, $\\mathrm{MoSi_{2}N_{4}}$ , $\\mathsf{W G e}_{2}\\mathrm{N}_{4}$ and $\\mathsf{W S i}_{2}\\mathrm{N}_{4}$ nanosheets are found to exhibit appropriate band edge positions, excellent carrier mobilities and decent absorption of visible light and thus can be considered as prom­ ising candidates for the photocatalytic water splitting. The obtained results confirm remarkably high mechanical properties of studied nanosheets, in particular for the cases of $\\mathrm{{MSi_{2}N_{4}}}$ lattices. Notably, our results suggest outstanding thermal conductivities for the $\\mathrm{MSi_{2}N_{4}}$ nanosheets, reaching to around 440 and $500\\mathrm{W/mK}$ for the $\\mathrm{MoSi_{2}N_{4}}$ and $\\mathsf{W S i_{2}N_{4}}$ monolayers, respectively, appealing for the thermal manage­ ment systems. For the first time we show that machine learning inter­ atomic potentials trained using 2000 time-step long AIMD trajectories over small $4\\times3\\times1$ supercells enable the examination of flexoelectric and piezoelectric properties of complex structures. As the most exciting finding, $\\mathrm{WSi_{2}N_{4}}$ , $\\mathrm{CrSi_{2}N_{4}}$ and $\\mathrm{MoSi_{2}N_{4}}$ are found to, respectively, record the highest piezoelectric coefficients, outperforming all other-known 2D materials. Our extensive results clearly reveal the outstanding properties of $\\mathrm{MSi_{2}N_{4}}$ compositions. Therefore, in order to find the structure with the maximal mechanical, thermal conduction and piezoelectric prop­ erties, $\\mathrm{MSi}_{2}\\mathrm{N}_{4}$ $(\\mathbf{M}=\\mathbf{M}\\mathbf{o}$ , W, V, Nb, Ta, Ti, Zr, Hf or Cr) nanosheets should be further examined. Extensive results by this study highlight the exceptional physical properties of $\\mathrm{MA_{2}Z_{4}}$ nanomembranes, highly promising for the design of strong and robust nanoelectronics, opto­ electronics, thermal management and energy conversion nanosystems. It is evident that this novel class of 2D materials not only outperforms the transition metal dichalcogenides group but can also compete with graphene for many advanced applications. \n\n# CRediT authorship contribution statement \n\nBohayra Mortazavi: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing - review & editing. Brahmanandam Javvaji: Data curation, Formal analysis, Investigation, Software, Validation, Visualization, Writing - original draft. Fazel Shojaei: Data curation, Formal analysis, Investi­ gation, Software, Validation, Visualization, Writing - original draft. Timon Rabczuk: Supervision, Resources. Alexander V. Shapeev: Software, Methodology, Supervision, Writing - review & editing. Xiaoying Zhuang: Resources, Funding acquisition. \n\n# Declaration of Competing Interest \n\nThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \n\n# Acknowledgment \n\nB.M. and X.Z. appreciate the funding by the Deutsche For­ schungsgemeinschaft, Germany (DFG, German Research Foundation) \n\nunder Germany’s Excellence Strategy within the Cluster of Excellence PhoenixD (EXC 2122, Project ID 390833453). B.J. and X.Z. gratefully acknowledge the sponsorship from the ERC, Germany Starting Grant COTOFLEXI (No. 802205). Authors also acknowledge the support of the cluster system team at the Leibniz Universit¨at of Hannover, Germany. B. M and T. R. are greatly thankful to the VEGAS cluster at Bauhaus Uni­ versity of Weimar for providing the computational resources. A.V.S. is supported by RFBR, Russia grant number 20-53-12012. F.S. thanks the Persian Gulf University Research Council, Iran for support of this study. \n\n# Appendix A. Supporting information \n\nSupplementary data associated with this article can be found in the online version at doi:10.1016/j.nanoen.2020.105716. \n\n# References \n\n[1] K.S. Novoselov, A.K. Geim, S.V. Morozov, D. Jiang, Y. Zhang, S.V. Dubonos, I. V. Grigorieva, A.A. Firsov, Electric field effect in atomically thin carbon films, Science 306 (2004) 666–669, https://doi.org/10.1126/science.1102896. \n[2] A.K. Geim, K.S. Novoselov, The rise of graphene, Nat. Mater. 6 (2007) 183–191, https://doi.org/10.1038/nmat1849. \n[3] A.H. Castro Neto, N.M.R. Peres, K.S. Novoselov, A.K. Geim, F. Guinea, The electronic properties of graphene, Rev. Mod. Phys. 81 (2009) 109–162, https://doi. org/10.1103/RevModPhys.81.109. \n[4] S. Ghosh, I. Calizo, D. Teweldebrhan, E.P. Pokatilov, D.L. Nika, A.A. Balandin, W. Bao, F. Miao, C.N. Lau, Extremely high thermal conductivity of graphene: Prospects for thermal management applications in nanoelectronic circuits, Appl. Phys. Lett. 92 (2008), 151911, https://doi.org/10.1063/1.2907977. \n[5] A.A. Balandin, S. Ghosh, W. Bao, I. Calizo, D. Teweldebrhan, F. Miao, C.N. Lau, Superior thermal conductivity of single-layer graphene, Nano Lett. 8 (2008) 902–907, https://doi.org/10.1021/nl0731872. [6] C. Lee, X. Wei, J.W. Kysar, J. Hone, Measurement of the elastic properties and intrinsic strength of monolayer graphene, Science 321 (2008) 385–388, https:// doi.org/10.1126/science.1157996. [7] L. Banszerus, M. Schmitz, S. Engels, J. Dauber, M. Oellers, F. Haupt, K. Watanabe, T. Taniguchi, B. Beschoten, C. Stampfer, Ultrahigh-mobility graphene devices from chemical vapor deposition on reusable copper, Sci. Adv. 1 (2015), e1500222, https://doi.org/10.1126/sciadv.1500222. [8] C. Berger, Z. Song, T. Li, X. Li, A.Y. Ogbazghi, R. Feng, Z. Dai, A.N. Marchenkov, E. H. Conrad, P.N. First, W. a de Heer, Ultrathin epitaxial graphite: 2D electron gas properties and a route toward graphene-based nanoelectronics, J. Phys. Chem. B 108 (2004) 19912–19916, https://doi.org/10.1021/jp040650f. \n[9] M. Liu, X. Yin, E. Ulin-Avila, B. Geng, T. Zentgraf, L. Ju, F. Wang, X. Zhang, A graphene-based broadband optical modulator, Nature 474 (2011) 64–67, https://doi.org/10.1038/nature10067. \n[10] F. Withers, M. Dubois, A.K. Savchenko, Electron properties of fluorinated singlelayer graphene transistors, Phys. Rev. B 82 (2010), 073403, https://doi.org/ 10.1103/PhysRevB.82.073403. \n[11] B. Liu, K. Zhou, Recent progress on graphene-analogous 2D nanomaterials: properties, modeling and applications, Prog. Mater. Sci. 100 (2019) 99–169, https://doi.org/10.1016/J.PMATSCI.2018.09.004. \n[12] A. Lherbier, S.M.-M. Dubois, X. Declerck, Y.-M. Niquet, S. Roche, J.-C. Charlier, Transport properties of graphene containing structural defects, Phys. Rev. B 86 (2012), 075402, https://doi.org/10.1103/PhysRevB.86.075402. \n[13] A.W. Cummings, D.L. Duong, V.L. Nguyen, D. Van Tuan, J. Kotakoski, J.E. Barrios Vargas, Y.H. Lee, S. Roche, Charge transport in polycrystalline graphene: challenges and opportunities, Adv. Mater. 26 (2014) 5079–5094, https://doi.org/ 10.1002/adma.201401389. \n[14] A. Cresti, N. Nemec, B. Biel, G. Niebler, F. Triozon, G. Cuniberti, S. Roche, Charge transport in disordered graphene-based low dimensional materials, Nano Res. 1 (2008) 361–394, https://doi.org/10.1007/s12274-008-8043-2. \n[15] S. Bazrafshan, A. Rajabpour, Thermal transport engineering in amorphous graphene: non-equilibrium molecular dynamics study, Int. J. Heat Mass Transf. 112 (2017) 379–386, https://doi.org/10.1016/j.ijheatmasstransfer.2017.04.127. \n[16] S. Bazrafshan, A. Rajabpour, Engineering of thermal transport in graphene using grain size, strain, nitrogen and boron doping; a multiscale modeling, Int. J. Heat Mass Transf. 123 (2018) 534–543, https://doi.org/10.1016/j. ijheatmasstransfer.2018.02.107. \n[17] M.K. Blees, A.W. Barnard, P. a Rose, S.P. Roberts, K.L. McGill, P.Y. Huang, A. R. Ruyack, J.W. Kevek, B. Kobrin, D. a Muller, P.L. McEuen, Graphene kirigami, Nature 524 (2015) 204–207, https://doi.org/10.1038/nature14588. \n[18] J. Bai, X. Zhong, S. Jiang, Y. Huang, X. Duan, Graphene nanomesh, Nat. Nanotechnol. 5 (2010) 190–194, https://doi.org/10.1038/nnano.2010.8. \n[19] F. Guinea, Strain engineering in graphene, Solid State Commun. 152 (2012) 1437–1441, https://doi.org/10.1016/j.ssc.2012.04.019. \n[20] C. Metzger, S. Re´mi, M. Liu, S.V. Kusminskiy, A.H. Castro Neto, A.K. Swan, B. B. Goldberg, Biaxial strain in graphene adhered to shallow depressions, Nano Lett. 10 (2010) 6–10, https://doi.org/10.1021/nl901625v. \n[21] V.M. Pereira, A.H. Castro, Strain engineering of graphene’s electronic structure, Phys. Rev. Lett. 103 (2009), 046801, https://doi.org/10.1103/ PhysRevLett.103.046801. \n[22] S. Barraza-Lopez, A.A.P. Sanjuan, Z. Wang, M. Vanevi´c, Strain-engineering of graphene’s electronic structure beyond continuum elasticity, Solid State Commun. 166 (2013) 70–75, https://doi.org/10.1016/j.ssc.2013.05.002. \n[23] F. Guinea, M.I. Katsnelson, A.K. Geim, Energy gaps and a zero-field quantum Hall effect in graphene by strain engineering, Nat. Phys. 6 (2010) 30–33, https://doi. org/10.1038/nphys1420. \n[24] T.O. Wehling, K.S. Novoselov, S.V. Morozov, E.E. Vdovin, M.I. Katsnelson, A. K. Geim, A.I. Lichtenstein, Molecular doping of graphene, Nano Lett. 8 (2008) 173–177, https://doi.org/10.1021/nl072364w. \n[25] X. Miao, S. Tongay, M.K. Petterson, K. Berke, A.G. Rinzler, B.R. Appleton, A. F. Hebard, High efficiency graphene solar cells by chemical doping, Nano Lett. 12 (2012) 2745–2750, https://doi.org/10.1021/nl204414u. \n[26] X. Wang, L. Zhi, K. Müllen, Transparent, conductive graphene electrodes for dyesensitized solar cells, Nano Lett. 8 (2008) 323–327, https://doi.org/10.1021/ nl072838r. \n[27] F. Schedin, a K. Geim, S.V. Morozov, E.W. Hill, P. Blake, M.I. Katsnelson, K. S. Novoselov, S.V.M.E.W.H.P.B.M.I.K, K.S.N.F. Schedin, A.K. Geim, Detection of individual gas molecules adsorbed on graphene, Nat. Mater. 6 (2007) 652–655, https://doi.org/10.1038/nmat1967. \n[28] D. Soriano, D. Van Tuan, S.M.-M. Dubois, M. Gmitra, A.W. Cummings, D. Kochan, F. Ortmann, J.-C. Charlier, J. Fabian, S. Roche, Spin transport in hydrogenated graphene, 2D Mater. 2 (2015), 022002, https://doi.org/10.1088/2053-1583/2/2/ 022002. \n[29] Y. Wang, Y. Ding, Strain-induced self-doping in silicene and germanene from firstprinciples, Solid State Commun. 155 (2013) 6–11, https://doi.org/10.1016/j. c.2012.10.044. \n[30] B. Radisavljevic, A. Radenovic, J. Brivio, V. Giacometti, A. Kis, Single-layer $\\mathbf{MoS}_{2}$ transistors, Nat. Nanotechnol. 6 (2011) 147–150, https://doi.org/10.1038/ nnano.2010.279. \n[31] D.A. Bandurin, A.V. Tyurnina, G.L. Yu, A. Mishchenko, V. Z´olyomi, S.V. Morozov, R.K. Kumar, R.V. Gorbachev, Z.R. Kudrynskyi, S. Pezzini, Z.D. Kovalyuk, U. Zeitler, K.S. Novoselov, A. Patan\\`e, L. Eaves, I.V. Grigorieva, V.I. Fal’ko, A.K. Geim, Y. Cao, High electron mobility, quantum Hall effect and anomalous optical response in atomically thin InSe, Nat. Nanotechnol. (2016) 1–18, https://doi.org/10.1038/ nnano.2016.242. \n[32] S. Das, M. Demarteau, A. Roelofs, Ambipolar phosphorene field effect transistor, ACS Nano 8 (2014) 11730–11738, https://doi.org/10.1021/nn505868h. \n[33] L. Li, Y. Yu, G.J. Ye, Q. Ge, X. Ou, H. Wu, D. Feng, X.H. Chen, Y. Zhang, Black phosphorus field-effect transistors, Nat. Nanotechnol. 9 (2014) 372–377, https:// doi.org/10.1038/nnano.2014.35. \n[34] K.M.F. Shahil, A.A. Balandin, Thermal properties of graphene and multilayer graphene: applications in thermal interface materials, Solid State Commun. 152 (2012) 1331–1340, https://doi.org/10.1016/j.ssc.2012.04.034. \n[35] K.M.F. Shahil, A.A. Balandin, Graphene-multilayer graphene nanocomposites as highly efficient thermal interface materials, Nano Lett. 12 (2012) 861–867, https://doi.org/10.1021/nl203906r. \n[36] J. Renteria, D. Nika, A. Balandin, Graphene thermal properties: applications in thermal management and energy storage, Appl. Sci. 4 (2014) 525–547, https://doi. org/10.3390/app4040525. \n[37] P. Goli, S. Legedza, A. Dhar, R. Salgado, J. Renteria, A.A. Balandin, Grapheneenhanced hybrid phase change materials for thermal management of Li-ion batteries, J. Power Sources 248 (2014) 37–43, https://doi.org/10.1016/j. jpowsour.2013.08.135. \n[38] D. Tan, M. Willatzen, Z.L. Wang, Electron transfer in the contact-electrification between corrugated 2D materials: a first-principles study, Nano Energy 79 (2021), 105386, https://doi.org/10.1016/j.nanoen.2020.105386. \n[39] S. Deng, R. Xu, M. Li, L. Li, Z.L. Wang, Q. Zhang, Influences of surface charges and gap width between p-type and n-type semiconductors on charge pumping, Nano Energy 78 (2020), 105287, https://doi.org/10.1016/j.nanoen.2020.105287. \n[40] J. Chen, K. Han, J. Luo, L. Xu, W. Tang, Z.L. Wang, Soft robots with self-powered configurational sensing, Nano Energy 77 (2020), 105171, https://doi.org/ 10.1016/j.nanoen.2020.105171. \n[41] L. Shuai, Z.H. Guo, P. Zhang, J. Wan, X. Pu, Z.L. Wang, Stretchable, self-healing, conductive hydrogel fibers for strain sensing and triboelectric energy-harvesting smart textiles, Nano Energy 78 (2020), 105389, https://doi.org/10.1016/j. nanoen.2020.105389. \n[42] M. Tabatabaeichehr, H. Mortazavi, The effectiveness of aromatherapy in the management of labor pain and anxiety, Ethiop. J. Health Sci. 30 (2020) 449–458. 〈https://www.ajol.info/index.php/ejhs/article/view/195867〉. \n[43] S.M. Hatam-Lee, A. Rajabpour, S. Volz, Thermal conductivity of graphene polymorphs and compounds: from $\\mathbf{C}_{3}\\mathbf{N}$ to graphdiyne lattices, Carbon N. Y. 161 (2020) 816–826, https://doi.org/10.1016/j.carbon.2020.02.007. \n[44] F. Lan, Y. Chen, J. Zhu, Q. Lu, C. Jiang, S. Hao, X. Cao, N. Wang, Z.L. Wang, Piezotronically enhanced detection of protein kinases at ZnO micro/nanowire heterojunctions, Nano Energy 69 (2020), 104330, https://doi.org/10.1016/j. n.2019.104330. \n[45] W. Ma, J. Lu, B. Wan, D. Peng, Q. Xu, G. Hu, Y. Peng, C. Pan, Z.L. Wang, Piezoelectricity in multilayer black phosphorus for piezotronics and nanogenerators, Adv. Mater. 32 (2020), 1905795, https://doi.org/10.1002/ adma.201905795. \n[46] L. Pan, S. Sun, Y. Chen, P. Wang, J. Wang, X. Zhang, J.-J. Zou, Z.L. Wang, Advances in Piezo-phototronic effect enhanced photocatalysis and photoelectrocatalysis, Adv. Energy Mater. 10 (2020), 2000214, https://doi.org/10.1002/ enm.202000214. \n[47] Q. Hua, J. Sun, H. Liu, X. Cui, K. Ji, W. Guo, C. Pan, W. Hu, Z.L. Wang, Flexible GaN microwire-based piezotronic sensory memory device, Nano Energy 78 (2020), 105312, https://doi.org/10.1016/j.nanoen.2020.105312. \n[48] T. Liu, D. Li, H. Hu, X. Huang, Z. Zhao, W. Sha, C. Jiang, C. Du, M. Liu, X. Pu, B. Ma, W. Hu, Z.L. Wang, Piezo-phototronic effect in InGaN/GaN semi-floating micro-disk LED arrays, Nano Energy 67 (2020), 104218, https://doi.org/10.1016/j. oen.2019.104218. \n[49] Y.-L. Hong, Z. Liu, L. Wang, T. Zhou, W. Ma, C. Xu, S. Feng, L. Chen, M.-L. Chen, D.- M. Sun, X.-Q. Chen, H.-M. Cheng, W. Ren, Chemical vapor deposition of layered two-dimensional $\\mathbf{MoSi_{2}N_{4}}$ materials, Science 369 (2020) 670–674, https://doi.org/ 10.1126/scienc e.abb7023. \n[50] K.S. Novoselov, Discovery of 2D van der Waals layered $\\mathrm{MoSi}_{2}\\mathrm{N}_{4}$ family, Natl. Sci. Rev. 7 (2020) 1842–1844, https://doi.org/10.1093/nsr/nwaa190. \n[51] G. Kresse, J. Furthmüller, Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set, Comput. Mater. Sci. 6 (1996) 15–50, https://doi.org/10.1016/0927-0256(96)00008-0. \n[52] G. Kresse, J. Furthmüller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set, Phys. Rev. B 54 (1996) 11169–11186, https://doi.org/10.1103/PhysRevB.54.11169. \n[53] G. Kresse, From ultrasoft pseudopotentials to the projector augmented-wave method, Phys. Rev. B 59 (1999) 1758–1775, https://doi.org/10.1103/ PhysRevB.59.1758. \n[54] J. Perdew, K. Burke, M. Ernzerhof, Generalized gradient approximation made simple, Phys. Rev. Lett. 77 (1996) 3865–3868, https://doi.org/10.1103/ PhysRevLett.77.3865. \n[55] H. Monkhorst, J. Pack, Special points for Brillouin zone integrations, Phys. Rev. B 13 (1976) 5188–5192, https://doi.org/10.1103/PhysRevB.13.5188. \n[56] A. Togo, I. Tanaka, First principles phonon calculations in materials science, Scr. Mater. 108 (2015) 1–5, https://doi.org/10.1016/j.scriptamat.2015.07.021. \n[57] G.E. Krukau, A.V. Vydrov, O.A. Izmaylov, A.F. Scuseria, Influence of the exchange screening parameter on the performance of screened hybrid functionals, J. Chem. Phys. 125 (2006), 224106, https://doi.org/10.1063/1.2404663. \n[58] J. Bardeen, W. Shockley, Deformation potentials and mobilities in non-polar crystals, Phys. Rev. 80 (1950) 72–80, https://doi.org/10.1103/PhysRev.80.72. \n[59] M. Gajdoˇs, K. Hummer, G. Kresse, J. Furthmüller, F. Bechstedt, Linear optical properties in the projector-augmented wave methodology, Phys. Rev. B 73 (2006), 045112, https://doi.org/10.1103/PhysRevB.73.045112. \n[60] A.V. Shapeev, Moment tensor potentials: a class of systematically improvable interatomic potentials, Multiscale Model. Simul. 14 (2016) 1153–1173, https:// doi.org/10.1137/15M1054183. \n[61] K. Schutt, P.-J. Kindermans, H.E.S. Felix, S. Chmiela, A. Tkatchenko, K.-R. Muller, Schnet A continuous-filter convolutional neural network for modeling quantum interactions, in: Adv. Neural Inf. Process. Syst., (2017), pp. 991–1001. \n[62] V. Botu, R. Batra, J. Chapman, R. Ramprasad, Machine learning force fields: construction, validation, and outlook, J. Phys. Chem. C 121 (2017) 511–522, https://doi.org/10.1021/acs.jpcc.6b10908. \n[63] Y. Zuo, C. Chen, X. Li, Z. Deng, Y. Chen, J. Behler, G. Cs´anyi, A.V. Shapeev, A. P. Thompson, M.A. Wood, S.P. Ong, Performance and cost assessment of machine learning interatomic potentials, J. Phys. Chem. A 124 (2020) 731–745, https://doi. org/10.1021/acs.jpca.9b08723. \n[64] B. Mortazavi, I.S. Novikov, E.V. Podryabinkin, S. Roche, T. Rabczuk, A.V. Shapeev, X. Zhuang, Exploring phononic properties of two-dimensional materials using machine learning interatomic potentials, Appl. Mater. Today 20 (2020), 100685, https://doi.org/10.1016/j.apmt.2020.100685. \n[65] B. Mortazavi, E.V. Podryabinkin, I.S. Novikov, T. Rabczuk, X. Zhuang, A. V. Shapeev, Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: a MTP/ShengBTE solution, Comput. Phys. Commun. 258 (2021), 107583, https://doi.org/10.1016/j.cpc.2020.107583. \n[66] I.S.N, K.G, E.P, A.V. Shapeev, The MLIP package: moment tensor potentials with MPI and active learning, Mach. Learn. Sci. Technol. (2020) http://iopscience.iop. org/article/10.1088/2632-2153/abc9fe. \n[67] W. Li, J. Carrete, N.A. Katcho, N. Mingo, ShengBTE: a solver of the Boltzmann transport equation for phonons, Comput. Phys. Commun. 185 (2014) 1747–1758, https://doi.org/10.1016/j.cpc.2014.02.015. \n[68] A. Mayer, P. Lambin, R. Langlet, Charge-dipole model to compute the polarization of fullerenes, Appl. Phys. Lett. 89 (2006), 063117, https://doi.org/10.1063/ 1.2337524. \n[69] A. Mayer, Formulation in terms of normalized propagators of a charge-dipole model enabling the calculation of the polarization properties of fullerenes and carbon nanotubes, Phys. Rev. B 75 (2007), 045407, https://doi.org/10.1103/ PhysRevB.75.045407. \n[70] S.G. Bratsch, J.J. Lagowski, Predicted stabilities of monatomic anions in water and liquid ammonia at 298.15 K, Polyhedron 5 (1986) 1763–1770, https://doi.org/ transition metal negative ions: studies on, $\\mathrm{Cr}^{-}$ , $\\mathbf{Mo}^{-}$ , ${\\mathsf{C u}}^{-}$ and $\\mathsf{A g}^{-}$ , J. Phys. B Mol. Opt. Phys. 31 (1998) 3885–3891, https://doi.org/10.1088/0953-4075/31/17/ 013. \n[72] R.J. Pel´aez, C. Blondel, M. Vandevraye, C. Drag, C. Delsart, Photodetachment microscopy to an excited spectral term and the electron affinity of phosphorus, J. Phys. B Mol. Opt. Phys. 44 (2011), 195009, https://doi.org/10.1088/0953- 4075/44/19/195009. \n[73] A.O. Lindahl, P. Andersson, C. Diehl, O. Forstner, P. Klason, D. Hanstorp, The electron affinity of tungsten, Eur. Phys. J. D 60 (2010) 219–222, https://doi.org/ 10.1140/epjd/e2010-00199-y. \n[74] D. Bresteau, C. Drag, C. Blondel, Isotope shift of the electron affinity of carbon measured by photodetachment microscopy, Phys. Rev. A Mol. Opt. Phys. 93 (2016) 1–8, https://doi.org/10.1103/PhysRevA.93.013414. \n[75] W. Chaibi, R.J. Pela´ez, C. Blondel, C. Drag, C. Delsart, Effect of a magnetic field in photodetachment microscopy, Eur. Phys. J. D 58 (2010) 29–37, https://doi.org/ 10.1140/epjd/e2010-00086-7. \n[76] M.J. Frisch, G.W. Trucks, H.E. Schlegel, G.E. Scuseria, M.A. Robb, J.R. Cheeseman, G. Scalmani, V. Barone, G.A. Petersson, F. O, J.B. Foresman, J.D. Fox. Gaussian 16, Gaussian, Inc.,, Wallingford CT, 2016. \n[77] B. Javvaji, B. He, X. Zhuang, The generation of piezoelectricity and flexoelectricity in graphene by breaking the materials symmetries, Nanotechnology 29 (2018), 225702, https://doi.org/10.1088/1361-6528/aab5ad. \n[78] X. Zhuang, B. He, B. Javvaji, H.S. Park, Intrinsic bending flexoelectric constants in two-dimensional materials, Phys. Rev. B 99 (2019), 054105, https://doi.org/ 10.1103/PhysRevB.99.054105. \n[79] S. Plimpton, Fast parallel algorithms for short-range molecular dynamics, J. Comput. Phys. 117 (1995) 1–19, https://doi.org/10.1006/jcph.1995.1039. \n[80] B. Javvaji, S. Bhamy Maithry, D.R. Mahapatra, A. Ravikumar, G.M. Hegde, M. R. Rizwan, Stable configurations of graphene on silicon, Appl. Surf. Sci. 414 (2017) 25–33. \n[81] F. Shimizu, S. Ogata, J. Li, Theory of Shear Banding in metallic glasses and molecular dynamics calculations, Mater. Trans. 48 (2007) 2923–2927, https://doi. org/10.2320/matertrans.MJ200769. \n[82] C. Ataca, H. ¸Sahin, S. Ciraci, Stable, single-layer $\\mathbf{MX}_{2}$ transition-metal oxides and dichalcogenides in a honeycomb-like structure, J. Phys. Chem. C 116 (2012) 8983–8999, https://doi.org/10.1021/jp212558p. \n[83] M. Calandra, Chemically exfoliated single-layer $\\mathbf{MoS}_{2}$ : stability, lattice dynamics, and catalytic adsorption from first principles, Phys. Rev. B 88 (2013), 245428, https://doi.org/10.1103/PhysRevB.88.245428. \n[84] Y.-L. Hong, Z. Liu, L. Wang, T. Zhou, W. Ma, C. Xu, S. Feng, L. Chen, M.-L. Chen, D.- M. Sun, X.-Q. Chen, H.-M. Cheng, W. Ren, Chemical vapor deposition of layered two-dimensional $\\mathrm{MoSi}_{2}\\mathrm{N}_{4}$ materials, Science 369 (2020) 670–674, https://doi.org/ 10.1126/science.abb7023. \n[85] Y. Cai, G. Zhang, Y.-W. Zhang, Polarity-reversed robust carrier mobility in monolayer $\\mathbf{MoS}_{2}$ nanoribbons, J. Am. Chem. Soc. 136 (2014) 6269–6275, https:// doi.org/10.1021/ja4109787. \n[86] B. Mortazavi, M. Shahrokhi, M. Makaremi, G. Cuniberti, T. Rabczuk, Firstprinciples investigation of Ag-, Co-, Cr-, Cu-, Fe-, Mn-, Ni-, Pd- and Rhhexaaminobenzene 2D metal-organic frameworks, Mater. Today Energy 10 (2018) 336–342, https://doi.org/10.1016/J.MTENER.2018.10.007. \n[87] X. Gu, R. Yang, Phonon transport in single-layer transition metal dichalcogenides: a first-principles study, Appl. Phys. Lett. 105 (2014), 131903, https://doi.org/ 10.1063/1.4896685. \n[88] H. Zhu, Y. Wang, J. Xiao, M. Liu, S. Xiong, Z.J. Wong, Z. Ye, Y. Ye, X. Yin, X. Zhang, Observation of piezoelectricity in free-standing monolayer $\\mathbf{MoS}_{2}.$ Nat. Nanotechnol. 10 (2015) 151–155, https://doi.org/10.1038/nnano.2014.309. \n[89] M.N. Blonsky, H.L. Zhuang, A.K. Singh, R.G. Hennig, Ab initio prediction of piezoelectricity in two-dimensional materials, ACS Nano 9 (2015) 9885–9891, https://doi.org/10.1021/acsnano.5b03394. \n[90] S.D. Guo, X.S. Guo, Z.Y. Liu, Y.N. Quan, Large piezoelectric coefficients combined with high electron mobilities in Janus monolayer XTeI $(\\mathrm{X}=\\mathrm{S}\\mathrm{b}$ and Bi): a firstprinciples study, J. Appl. Phys. 127 (2020), 064302, https://doi.org/10.1063/ 1.5134960. \n[91] B. Javvaji, B. He, X. Zhuang, H.S. Park, High flexoelectric constants in Janus transition-metal dichalcogenides, Phys. Rev. Mater. 3 (2019), 125402, https://doi. org/10.1103/PhysRevMaterials.3.125402. \n[92] L. Dong, J. Lou, V.B. Shenoy, Large in-plane and vertical piezoelectricity in Janus transition metal dichalchogenides, ACS Nano 11 (2017) 8242–8248, https://doi. org/10.1021/acsnano.7b03313. \n[93] X. Zhang, Y. Cui, L. Sun, M. Li, J. Du, Y. Huang, Stabilities, and electronic and piezoelectric properties of two-dimensional tin dichalcogenide derived Janus monolayers, J. Mater. Chem. C 7 (2019) 13203–13210, https://doi.org/10.1039/ c9tc04461b. " + }, + { + "id": "10.1126_science.abj8114", + "DOI": "10.1126/science.abj8114", + "DOI Link": "http://dx.doi.org/10.1126/science.abj8114", + "Relative Dir Path": "mds/10.1126_science.abj8114", + "Article Title": "Gradient cell-structured high-entropy alloy with exceptional strength and ductility", + "Authors": "Pan, QS; Zhang, LX; Feng, R; Lu, QH; An, K; Chuang, AC; Poplawsky, JD; Liaw, PK; Lu, L", + "Source Title": "SCIENCE", + "Abstract": "Similar to conventional materials, most multicomponent high-entropy alloys (HEAs) lose ductility as they gain strength. In this study, we controllably introduced gradient nulloscaled dislocation cell structures in a stable single-phase HEA with face-centered cubic structure, thus resulting in enhanced strength without apparent loss of ductility. Upon application of strain, the sample-level structural gradient induces progressive formation of a high density of tiny stacking faults (SFs) and twins, nucleating from abundant low-angle dislocation cells. Furthermore, the SF-induced plasticity and the resultant refined structures, coupled with intensively accumulated dislocations, contribute to plasticity, increased strength, and work hardening. These findings offer a promising paradigm for tailoring properties with gradient dislocation cells at the nulloscale and advance our fundamental understanding of the intrinsic deformation behavior of HEAs.", + "Times Cited, WoS Core": 470, + "Times Cited, All Databases": 479, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000720789200034", + "Markdown": "# METALLURGY \n\n# Gradient cell–structured high-entropy alloy with exceptional strength and ductility \n\nQingsong Pan1†, Liangxue Zhang1,2†, Rui Feng3†, Qiuhong ${\\mathbf{L}}{\\mathbf{u}}^{1}$ , Ke $\\mathsf{\\pmb{A}}\\mathsf{\\pmb{n}}^{3}$ , Andrew Chihpin Chuang4, Jonathan D. Poplawsky5, Peter K. Liaw6, Lei ${{\\mathbf{L}}{\\mathbf{u}}^{1*}}$ \n\nSimilar to conventional materials, most multicomponent high-entropy alloys (HEAs) lose ductility as they gain strength. In this study, we controllably introduced gradient nanoscaled dislocation cell structures in a stable single-phase HEA with face-centered cubic structure, thus resulting in enhanced strength without apparent loss of ductility. Upon application of strain, the sample-level structural gradient induces progressive formation of a high density of tiny stacking faults (SFs) and twins, nucleating from abundant lowangle dislocation cells. Furthermore, the SF-induced plasticity and the resultant refined structures, coupled with intensively accumulated dislocations, contribute to plasticity, increased strength, and work hardening. These findings offer a promising paradigm for tailoring properties with gradient dislocation cells at the nanoscale and advance our fundamental understanding of the intrinsic deformation behavior of HEAs. \n\nigh-entropy alloys (HEAs), or alloys with multiple principal elements, have a nearinfinite multicomponent phase space that can lead to unusual mechanical properties (1, 2). Good strength and ductility, high work hardening, and exceptional damage tolerance have been achieved in some single-phase HEAs that have inherent concentration inhomogeneity created through tailoring of their chemical complexity (3–6). Moreover, engineering a spatial heterogeneous microstructure that consists of graded grain sizes, nanoclusters, multiphases, and so forth could also allow HEAs to achieve superior properties (7–9), similar to those that have been achieved in traditional heterostructured metallic materials (10–12). However, the longlasting strength-ductility paradox for conventional metallic materials still exists for most HEAs (7, 8, 13). \n\nThe trade-off between strength and ductility for HEAs exists because the fundamental plastic-deformation features and mechanisms of HEAs reported so far are similar to those of conventional metals (13, 14). Elementary line defects that carry plasticity—i.e., full dislocations and related interactions with different structural defects, such as high-angle grain boundaries (HAGBs) or twin boundaries (TBs)—are well understood in traditional metals (15–18). Notably, some unusual dislocation behaviors have been identified in HEAs with highly concentrated solid solutions, owing to local inhomogeneity with chemical short-range order (SRO) and spatially variable stacking fault energy (SFE) at the atomic scale $(I4)$ . For example, the changing dislocation slip modes $(6,74,79-21)$ , as well as the enhanced friction resistance to motion or accumulation of dislocations (5, 22, 23), enabled by increasing local concentration fluctuations or local SRO at the nanoscale (generally ${<}3\\mathrm{nm}\\dot{}$ ) $(5,6,24);$ , are believed to contribute to the improved mechanical properties. \n\nWe propose a heterogeneous gradient dislocation cell structure (GDS) in a stable singlephase face-centered–cubic (fcc) $\\mathrm{Al_{0.1}C o C r F e N i}$ HEA that contains randomly oriented, equiaxed fine grains (FGs) with an average diameter of $\\sim46~\\upmu\\mathrm{m}$ . This alloy is a well-studied model material with a locally varied SFE of 6 to $21\\mathrm{mJ/m^{2}}$ (25). We found an unexpected and extremely high density of tiny stacking faults (SFs), twin nucleation, and accumulationdominated plastic deformation in our GDS HEA upon initial application of tensile strain. This feature resulted in attractive strength and ductility properties compared with those of other HEAs (10, 26, 27). \n\nTo process HEA dog-bone–shaped bar specimens with a gauge diameter of $4.5\\mathrm{mm}$ and a gauge length of $12~\\mathrm{mm}$ , we used a cyclic torsion (CT) treatment without surface tooling to form a sample-level multiscaled hierarchical dislocation structure under the imposed spatially gradient plastic strains from the surface to the core (28) (fig. S1). By controllably tuning CT parameters (i.e., torsion angle amplitudes of $20^{\\circ}$ and ${6^{\\circ}}.$ ), we prepared two different GDS samples with a constant torsion number of 200 cycles. We refer to these samples as GDS-H (Fig. 1; $20^{\\circ}.$ ) and GDS-L (fig. S2; ${6^{\\circ}}$ ) on the basis of the imposed high $\\mathrm{(H)}$ and low (L) accumulated torsion plastic strains (18.4 and 5.2, respectively, in the topmost layer; fig. S1E). \n\nWe focus on the GDS-H sample to illustrate the salient microstructural feature of a samplelevel hierarchical dislocation structure. Grains from the surface to the core of the GDS-H sample are still homogeneously distributed, with characters of faceted grain morphologies, unchanged grain size, and random crystallographic orientations (Fig. 1, A and G), as evidenced by electron backscatter diffraction (EBSD) experiments with scanning electron microscopy (SEM). The same observations were made before CT (fig. S1C). The noticeably unchanged grain features after CT processing are in sharp contrast to those of traditional homogeneous or gradient nanostructures with severely refined grain sizes and higher densities of HAGBs that are produced by employing conventional severe plastic deformation strategies (29, 30). Most grains in the sample core have the typical planar single-slip dislocation configuration in a relatively low dislocation density (fig. S3C), like that reported in the same HEA after tension strain (25). Well-developed singleslip–induced dislocation walls with low-angle boundaries (LABs) were occasionally observed in several grains (Fig. 1H and fig. S3D). Specifically, massive LABs with misorientations $<15^{\\circ}$ were introduced in the topmost grain interior and spatially distributed such that they became smaller in volume fraction and larger in size with increasing the depth from the top surface (Fig. 1B; also schematically illustrated in Fig. 1C). \n\nWe randomly selected one grain separated by HAGBs in the topmost layer ${\\bf\\omega}_{\\bf{\\omega}}\\mathrm{\\sim}100\\upmu\\mathrm{m}$ from the surface) of the GDS-H sample and used transmission electron microscopy (TEM) to investigate its dislocation structure. Figure 1D shows an example of the numerous equiaxed dislocation cells and cell walls with a small misorientation ranging from $0.7^{\\circ}$ to $4.8^{\\circ},$ corresponding to massive LABs in Fig. 1B. We observed a misorientation gradient in the grain interior along the radial direction (white arrow in Fig. 1D), as a result of the imposed macrolevel plastic-strain gradient upon the CT treatment (Fig. 1F) (31). We measured the cell diameter to be ${\\sim}200\\ \\mathrm{nm}$ in the top surface, which gradually increases to $\\sim450\\ \\mathrm{nm}$ for the dislocation wall structure in the core (fig. S3). Each cell wall $\\cdot{\\cdot}40~\\mathrm{nm}$ thickness on average) is decorated with a high density of dislocations $({\\sim}1.7\\times10^{15}\\mathrm{~m}^{-2};$ (28), but the cell interior has relatively fewer dislocations with curved morphologies (Fig. 1E and fig. S3). We achieved a similar dislocation structure in the GDS-L sample at a low cumulative plastic strain, exhibiting undeveloped dislocation cells with a larger average size of $\\sim450\\ \\mathrm{nm}$ in the topmost surface (figs. S1 and S2). The dislocation cells in the GDS HEA sample are primarily caused by intensive multislip full dislocation interactions under a complex gradient stressstrain state (32) after a high cumulative torsion strain (fig. S1). We observed no visible SFs or deformation twins in the bulk GDS sample (Fig. 1 and figs. S2 and S3), indicating dislocationcontrolled plastic deformation during the CT process, analogous to that observed in numerous HEAs with low SFEs (13, 25, 33, 34). \n\n![](images/7e5febe032887adfde0b968aacbbf6429d687591bb82d4f91f0ac488fe8fe2a9.jpg) \nFig. 1. Typical microstructure and structural gradient of a gradient dislocation structure. (A and B) Crosssectional EBSD images of the GDS-H $\\mathsf{A l}_{0.1}\\mathsf{C o C r F e N i}$ HEA processed by cyclic torsion (CT) processing at a torsion angle amplitude of $20^{\\circ}$ , showing the distributions of a grain-scaled morphology, orientation (A), and three types of boundaries (HAGB, LAB, and TB) with different misorientation angles (B) within a depth of ${\\sim}1.2\\ \\mathsf{m m}$ from the surface. (G and H) Same as (A) and (B) but for the core. (C) Schematic of GDS with a gradiently distributed lowangle dislocation structure. (D) Corresponding bright-field TEM image of dislocation structures at the topmost surface of the treated sample [indicated in (A) and (C)]. The misorientation angle of each cell wall, measured by means of an electron procession diffraction technique (28) in TEM, is indicated. The upper left inset is the corresponding SAED pattern. (E) A closer view of a typical dislocation cell structure. (F) Plots of misorientation-angle variation, measured with respect to the origin, across multiple cells at the topmost surface of the GDS-H HEA, along the direction of the white arrow in (D). Scale bars in (A), (B), and (G): $100\\upmu\\mathrm{m}$ . \n\nSynchrotron x-ray diffraction (SXRD) scanning on the as-prepared GDS-H samples from the topmost surface to the core showed a spatial gradient–distributed dislocation density— up to $8.8\\times10^{14}\\mathrm{{m^{-2}}}$ in the topmost ${\\sim}200\\upmu\\mathrm{m}$ of depth (fig. S4). The GDS-H sample still exhibits a stable single-phase fcc structure, as evidenced by EBSD, TEM, and SXRD or neutrondiffraction results (Fig. 1 and figs. S5 and S8). Quantitative compositional analysis at the atomic scale by means of three-dimensional atom probe tomography (3D-APT) shows that the GDS structure is compositionally homogeneous without detectable elemental segregation at the cell wall (fig. S6). \n\nThe hierarchical dislocation cell structure results in substantially improved tensile properties (Fig. 2A). Tensile tests of both GDS samples show higher yield strengths $(\\upsigma_{\\mathrm{y}};0.2\\%$ offset) of $362\\pm2$ and $539\\pm26$ MPa, about two to three times as strong as those of the FG and coarse-grained (CG) counterparts $\\mathbf{785\\pm}$ \n\n5 MPa and $138\\pm3$ MPa, respectively) (25). In addition, we measured a high uniform elongation $(\\delta_{\\mathrm{u}})$ up to $42.6\\pm0.2\\%$ for GDS-H, which is slightly reduced relative to that of FG counterparts without GDS $(55.4\\pm3.4\\%)$ . This behavior differs from the strength gain at the expense of ductility in most conventional metals and HEAs (7, 10). Specifically, the GDS-H sample shows steady strain hardening with a slightly decreased work-hardening rate $\\left(\\Theta\\right)-$ from 1.28 GPa at a $3\\%$ strain to 0.99 GPa before necking—which is distinct from the trend of notably reduced $\\Theta$ upon straining in its FG counterpart and the concave $\\Theta$ shape of the CG counterpart (Fig. 2B) dominated by deformation twinning (35). \n\nlocation architecture in the whole cross-section, we identified a distinct, gradiently distributed $H_{\\mathrm{V}}\\mathrm{from3.7GPa}$ at the topmost surface to $2.2\\mathrm{GPa}$ in the central region in GDS-H. These values are much higher than those of GDS-L (from 2.3 to 1.7 GPa). Compared to the uniform increase in $H_{\\mathrm{V}}$ for the FG sample after tensile straining, the hardening was particularly continuous in both tensioned GDS samples from the top surface to the core. This hardening feature is quite different from the deformation-induced continuous softening in conventional metals with gradient nanograins (10, 36). \n\nThe GDS structure that we introduced leads to unexpected deformation-induced continuous hardening behavior that we found by measuring the microhardness [i.e., Vickers hardness $(H_{\\mathrm{V}})]$ along the depth from the surface to the cores of GDS and FG samples before and after application of tension (Fig. 2C). Owing to the presence of the sample-level gradient dis \n\nWe attributed the pronounced increase in yield strengths to the nanoscaled dislocation cell unit with LABs (Fig. 1). Specifically, the contribution of LABs to strength has been demonstrated to be comparable with that of conventional HAGBs, and an ultrahigh hardness was observed in a nanolaminated Ni with LABs (18, 37). For the topmost GDS surface layer of the GDS-H sample, the ultrahigh $H_{\\mathrm{V}}$ that we measured indicates that the massive low-angle dislocation cells are effective in resisting dislocation motion. This trend results from their structural features, including nanoscaled size and high density of dislocations. We argue that this feature, together with the obvious continuous hardening in the topmost GDS surface and the unusual work-hardening response of the whole GDS samples, indicates an enhanced-strengthening and ductilizing mechanism in gradient dislocation structures upon straining. \n\nWe further characterized the microstructural evolution at the top surface of GDS-H at strains of $3\\%$ (onset stage of steady work hardening) and $40\\%$ (later stage of plasticity) to unravel the intrinsic deformation mechanism of the gradient dislocation cell–structured HEA. At a strain of $3\\%$ , we found almost no detectable changes to the grain-level characteristics, including grain shape, size, and orientation (Fig. 3, A and H). However, the density of LABs was notably reduced in both the subsurface layer and the core. The presence of these dislocation patterns is attributable to a poorly developed or unstable state at relatively low cumulative plastic strains (38, 39), whereas the pattern remains almost unchanged for the topmost grains (Fig. 3, B and I). Specifically, a widespread class of long, parallel lamellae bundles (average spacing of $\\mathrm{\\sim}1.7\\upmu\\mathrm{m}\\mathrm{\\rangle}$ ) was detected in the majority of the topmost grain, which decreases in number density as depth increases (Fig. 3, C and D, and fig. S7). The main components of these lamellae bundles are SFs, with a few TBs, as can be observed in selected-area electron diffraction (SAED) (Fig. 3E) and high-resolution TEM (Fig. 3F) images. We detected most parallel SFs and TBs (i.e., the dashed lines) across a dislocation wall (i.e., a white contrast region) (Fig. 3F). Closeup atomic-resolution TEM views show that more easily at an early deformation stage in GDS samples. Ex situ SXRD measurements further reveal that the enhanced probability of SFs and twins primarily stems from the contribution of GDS (fig. S8), consistent with our ex situ SEM and TEM observations (Figs. 3 and 4). By contrast, both SFs and deformation twins are rarely observed in FGs or at the core of GDS samples, even at a $40\\%$ strain, as confirmed by results in fig. S9 and in agreement with those reported in numerous single-phase fcc HEAs deformed at ambient temperature (4, 9, 13, 40–42). \n\nOn the basis of the above results, we rationalize that the extremely high density of SFs and the TBs that mediate plastic deformation are primarily responsible for the superior mechanical properties of the gradient dislocation cell– structured HEA. As for the dominance of such dense SFs and TBs, which are not achievable in conventional metallic materials or most singlephase fcc HEAs in the early deformation stage at ambient temperature (8, 13, 25, 42), we mainly attribute it to the chemical features of the HEA, nanoscaled dislocation cells with LABs, and their spatial gradient distribution. \n\n![](images/bcb9cd5b1a06d60a9faed6c2c0100b3b87b0834f342a14737b3016b5c83fc574.jpg) \nFig. 2. Mechanical properties of the GDS $\\pmb{\\Delta}\\pmb{\\mathrm{I}_{0.1}}\\pmb{\\mathrm{CoC}}$ rFeNi HEA. (A) Tensile engineering stress-strain relations of GDS, CG, and FG samples. (B) Work-hardening rate and true strain relations of GDS samples compared with their homogeneous components. (C) Variations of measured microhardness along the distance from the top surface to the interior of GDS samples after CT processing. Measured values after application of a $40\\%$ tensile strain (e) are also indicated. Error bars indicate SDs from 10 independent hardness measurements. (D) The product of strength and ductility versus yield strength normalized by the Young’s modulus of the GDS $\\mathsf{A l}_{0.1}\\mathsf{C o C r F e N i}$ HEA, compared with those of homogenous and gradient-grained structures and other metals and alloys with gradiently distributed nanograins and nanotwins reported in the literature (10, 36, 52–55). In (D), error bars represent SDs from more than three independent tensile tests. GNG and GNT denote the gradient nanograin and nanotwin, respectively; TWIP denotes twinning-induced plasticity; 316 SS denotes 316 stainless steel. \n\neach individual long lamellae interface is essentially composed of numerous nanoscaled SFs or twin segments, ranging from several to tens of nanometers in length (Fig. 3G). Measurements of the thickness between adjacent SFs or TBs produce a much smaller value ${\\mathrm{2.9~nm}}$ on average), corresponding to a very high volume density $({\\sim}4.14\\times10^{8}~\\mathrm{m^{2}/m^{3}})$ in the bundle. Moreover, the dislocation cells remain almost unchanged in shape and size. By contrast, the plastic deformation of most grains in the core of GDS-H is still dominated by intensive parallel full dislocations along {111} primarily slip planes (Fig. 3, J and K). \n\nWith the tensile strain increased to $40\\%$ before necking, the density of planar SF interfaces increases in volume fraction, prevailing in the grain interior (Fig. 4, A and B). Additional ultrafine nanotwins are also detected (Fig. 4C). The average spacing between adjacent SFs or TBs is small: ${\\sim}4.4~\\mathrm{nm}$ (Fig. 4C). \n\nAccording to conventional wisdom, generation of both SFs and deformation twins is associated with the emission and slip of partial dislocations from GBs (16)—in this case, most likely from dislocation cell walls instead. Additionally, numerous short SFs along the other inclined {111} slip plane are widely detected in between neighboring SFs and TBs, thereby forming an unusual 3D SF-twin structure network (Fig. 4C). \n\nWe conducted in situ neutron-diffraction tensile experiments to confirm that the formation of SFs with detectable splitting of (111) and (222) planes happens at a very low tensile strain of ${\\sim}5\\%$ for GDS-H samples, whereas it sets in at a high strain of $\\sim30\\%$ for the FG counterpart (Fig. 4D). Our analysis of the neutron-diffraction results yields for the GDS-H sample a higher value of the SF probability than that of the FG counterpart upon straining (Fig. 4E), which indicates that SFs form \n\nPlastic deformation of conventional polycrystalline fcc metals is known to be mainly carried by the full dislocation slip and the intensive interactions within individual grains (16). As traditionally alternative ductilizing strategies of high-strength metals and alloys, twinning or phase transformation usually come into play, mostly through either tuning compositions to reduce the SFEs or lowering the deformation temperature (16, 43). Under such circumstances, deformation twinning or phase transformation becomes prevalent, primarily owing to the ready partial dislocation glide on consecutive (or every other) {111} atomic planes in fcc metals (16, 43). By contrast, for most single-phase fcc HEAs (3, 13, 44), neither twinning nor phase transformation dominates. Instead, the planar full dislocations usually dominate the plastic deformation, as detected in FGs (fig. S9) and the core of the GDS (Fig. 3K) after tension. Specifically, the SF dissociation distance of full dislocations in the deformed HEA is wider than in conventional metals—it can be as wide as $34\\mathrm{nm}$ under tension tests at room temperature (25). We argue that the larger probability for partial dislocations and SF nucleation, rather than twinning or phase transformation, is closely related to the intrinsically spatially variable low SFE associated with the saliently rugged local atomic environments (14, 22, 23, 25) and chemical SRO $(5,6,24);$ , inherent to HEAs, although we do not have direct evidence. The SF is a planar defect with energy relative to the lattice energy level where it forms. In particular, the increase in the lattice-distortion energy induced by high-density dislocations in the GDS can more readily adjust the local atomic positions to further decrease the SFE $(45)$ , potentially increasing the SF width between partial dislocations. \n\n![](images/ecec324a7733ccf2cb4b98925041e7be435601c7941332d94e1487a8ad2f1b45.jpg) \nFig. 3. Deformation microstructure of the GDS-H $\\pmb{\\Delta\\mathrm{l}_{0.1}}\\pmb{\\mathrm{coc}}$ rFeNi HEA at a tensile strain of $3\\%.$ . (A and B) Cross-sectional EBSD images showing the distributions of the grain-scaled morphology, orientation (A), and three types of boundaries with different misorientation angles (B) within a depth of ${\\sim}1.2\\ \\mathsf{m m}$ from the surface. (H and I) Same as (A) and (B) but for the core after tension. (C to E) Corresponding SEM [(C) and (D)] and bright-field TEM (E) images, which indicate the widespread occurrence of dense SF bundles (tens of micrometers in length), indicated by the white arrows, that cut through multiple dislocation cell structures. The inset in (E) is the corresponding SAED pattern that contains parallel streaks (along the [111] direction, denoted by the white arrow) from SFs. The two-headed arrow in (C) denotes the loading axis (LA). The two-headed arrow in (D) denotes the spacing of adjacent SF bundles. (F) Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) image taken from bundles in the vicinity of dislocation cell walls with a relatively low dislocation density, revealing an ultrahigh density of SFs and TBs. (G) Close-up HAADFSTEM image exhibiting numerous nanoscaled SFs or twin segments. The solid and dashed lines in (F) and (G) denote SFs or TBs and the (111) plane, respectively. (J and K) Corresponding SEM (J) and TEM (K) images at the sample core, indicating planar-slip–induced parallel dislocation morphologies. \n\nIn addition to the atomic-scaled compositional effect, the activity of the dislocationdominated plastic deformation usually exhibits a strong (grain or cell) size dependence (46). As the characteristic size $(d)$ decreases, the full dislocation activity is gradually inhibited, whereas the partial dislocation activity becomes more favorable. In terms of the classical Orowan relation (15, 47), the critical stress required for initiating the full dislocation $(\\uptau_{\\mathrm{F}})$ and partial dislocation $(\\uptau_{\\mathrm{P}})$ as a function of cell size $(d)$ can be expressed as \n\n$$\n\\uptau_{\\mathrm{F}}(d)=\\uptau_{0}+\\frac{2\\upalpha\\upmu b}{d}\n$$ \n\n$$\n\\uptau_{\\mathrm{P}}(d)=\\frac{\\upgamma}{b_{\\mathrm{p}}}+\\frac{2\\upalpha\\upmu b_{\\mathrm{p}}}{d}\n$$ \n\nwhere $\\tau_{0}$ and $\\boldsymbol{\\upgamma}$ are the lattice friction stress (57 MPa) and SFE (6 to $21\\mathrm{mJ/m^{2}},$ ) (25); $\\mathbf{\\ensuremath{a}}$ is a parameter that reflects the characteristic of dislocations (0.5 for an edge dislocation; 1.5 for a screw dislocation); $\\upmu$ is the shear modulus $(80\\mathrm{GPa})$ ; and $b$ and $b_{\\mathrm{p}}$ are the Burgers vectors of full and partial dislocations (0.253 and $0.146\\mathrm{nm}\\dot{},$ ), respectively (28). With a maximum SFE of $\\mathrm{21mJ/m^{2}}$ and ${\\mathfrak{a}}=1$ [roughly assuming that the dislocations in cell interiors have curved morphologies (Fig. 1D and fig. S2) belonging to a mixed type], the estimated critical size for the transition from full to partial dislocation activity is ${\\sim}140~\\mathrm{nm}$ (fig. S10), which tends to become larger as the SFE decreases, evidently being comparable to the cell size in the topmost GDS layer (Fig. 1 and fig. S3). In essence, both the chemical and nanoscaled cell structural characters render partial dislocations highly favorable to full dislocations at ambient temperature (Fig. 3, F and G). \n\nThe sample-level gradient structure, with length scales spanning six orders of magnitude from the millimeter scale to the nanoscale [i.e., compositional fluctuation inhomogeneity or SRO, like those reported in the similar Al-CoCr-Fe-Ni systems (5, 48)], plays a pivotal role in enabling activation of partial dislocations in our alloy. First, the built-in gradient distribution of dislocation cells causes progressive plastic deformation from the core to the topmost surface (fig. S11), effectively suppressing the overall strain localization. All nanoscaled dislocation cells jointly mediate plastic deformation, providing the spatial “playground” for activating partial dislocations and the resultant formation of SFs to undergo plastic deformation. Second, gradient plastic deformation in the multiscaled architecture is accompanied by a complex stress-strain state with the sample-level stress partition and the presence of the back stress, especially at the early stage of plastic deformation (32). By conducting tensile load-unload-reload tests, we determined the back stress of the GDS-H sample at a strain of $0.6\\%$ (close to $0.2\\%$ offset) to be as high as $260\\mathrm{MPa}$ , which is $\\sim50\\%$ of the yield strength and much higher than that of the FG counterpart, as expected. Consequently, such obvious enhanced strengthening originates from back-stress hardening associated with gradient plastic deformation of GDS, effectively contributing to a higher yield strength than that of the FG counterpart. Microscopically, the nanoscaled cells with a higher dislocation density at the walls tend to induce a stronger local stress field (than the measured samplescaled macro-back stress), coupled with that caused by the local atomic distortions, thus endowing the internal driving force for partial dislocations slipping away from the equilibrium separation (13, 38), with dense SFs stably left behind (Figs. 3, E to G, and 4). \n\nMoreover, the ultrahigh density of dislocations at the cell boundaries naturally serves as an abundant, sustainable source for nucleating partial dislocations. Both large numbers and orientation-independence features of topmost grains that contain SFs (fig. S7) indicate that nucleation of SFs is not solely determined by the axial tensile stress state but is mostly controlled by complex multiaxial stress states in GDS upon straining. \n\nThrough engineering hierarchical nanoscaled GDS in a stable HEA, the deformation mechanism associated with extensive SFs and twins occurs even after a low tensile strain and is responsible for the steady work hardening and large tensile ductility. Such a high density of extremely fine SFs and TBs $({\\sim}4.14\\times10^{8}\\mathrm{m}^{2}/\\mathrm{m}^{3})$ not only effectively mediates plastic strains, exhibiting SF-induced plasticity, but also substantially helps delocalize plastic deformation, coupled with gradient-induced strain delocalization. First, the penetrations of more and more dense SF and TB bundles across dislocation walls progressively subdivide stable modulus of the corresponding material. When plotted this way, we found that the GDS HEA achieves the best combination of uniform tensile elongation and strength. It is not surprising that conventional gradient nanograined metals and alloys with a high density of HAGBs suffer from structural coarsening, such as GB migration with concomitant coarsening (contributing to plasticity) and resultant softening, although these materials must sacrifice strength and stability to a certain extent (10). By contrast, monotonic strengthening with high, steady work hardening was achieved in the stable single-phase fcc GDS HEA with spatially gradient LABs, contributed by the aforementioned SF and twin behavior, with gradual structural refinement. \n\nIn summary, our observations show that engineering gradient LAB structures on a single-phase fcc $\\mathrm{{Al}_{0.1}\\mathrm{{CoCrFeNi}}}$ HEA can help readily activate a mechanism to strengthen SF-induced plasticity, leading to exceptional strength and ductility. The discovery of such SF and twin behavior in the GDS HEA is essential for acquiring the common deformation features inherent to HEAs. It is also widely applicable to other HEA systems, particularly toward the achievement of better performance with superior properties, which are of fundamental and applied importance for advanced engineering applications such as automobiles, power stations, and aeronautic systems. \n\n![](images/afc7be8d1aae24a2296393a6aed7d4b87028b5c06dfc61b72759df6d0b2eb316.jpg) \nFig. 4. Deformation features at $40\\%$ tensile strain and in situ neutron-diffraction measurements during uniaxial tension of the GDS-H $\\pmb{\\Delta|}_{0.1}\\pmb{\\ C0}\\pmb{\\ C}$ rFeNi HEA. (A and B) SEM (A) and TEM (B) images of a high density of SF bundles (indicated by white arrows) in the whole grain interior. The inset in (B) is the corresponding SAED pattern. (C) Typical atomic-resolution HAADF-STEM image showing an ultrahigh density of SFs and TBs with inclined short SFs. The solid and dashed lines in (C) denote SFs or TBs and the (111) plane, respectively. (D) Evolution of lattice strains for (111)//LA and (222)//LA grains in both GDS-H and FG samples versus engineering strain measured by in situ neutron-diffraction experiments. The error bars are obtained from the uncertainties of the single-peak fitting on hkl diffraction peaks (hkl denotes Miller indices). Black arrows indicate the occurrence of (111) and (222) splitting events. (E) Variation of the calculated SF probability (SFP) as a function of engineering strain in both GDS-H and FG samples. \n\n# REFERENCES AND NOTES \n\ndislocation structures and build in 3D bundlecell networks (coupled with inherent, spatial local chemical fluctuations) that act as strong obstacles to dislocation slip (Fig. 3, C to G). In this case, intensive interactions among SFs or TBs and dislocations are promoted to induce considerable strengthening and work hardening, thus greatly counteracting the hastily reduced $\\Theta$ trend of the GDS structure associated with rapid recovery of preexisting full dislocations and relatively limited capacity of dislocation multiplications at a low strain (Fig. 2B). \n\nIn addition, the progressively refined 3D SF-cell networks also act as sustainable sources for high-density full dislocation storage during uniaxial tension. The newly accumulated density of full dislocations in the GDS-H sample is substantially higher than that in the FG counterparts at the same tensile strain (fig. S4), still consequently offering a progressive and steady work-hardening response of GDS (Fig. 2B). Benefiting from the roles of such unexpected high-density linear and planar defects, bulk GDS exhibits better strain compatibility without strain localization and visible cracks in the grain interior or along GBs, thus resulting in high tensile plasticity comparable to that of the FG counterparts, at higher stress levels (Fig. 2A). We compared yield strengths and the product of strength and ductility for GDS samples with the same compositional HEA (40, 41, 49–51) and other existing high-performance metals and alloys with gradient structures (10, 36, 52–55). The strength was normalized by the Young’s \n\n1. J. W. Yeh et al., Adv. Eng. Mater. 6, 299–303 (2004). \n2. B. Cantor, I. T. H. Chang, P. Knight, A. J. B. Vincent, Mater. Sci. Eng. A 375–377, 213–218 (2004). \n3. Y. Zhang et al., Prog. Mater. Sci. 61, 1–93 (2014). \n4. B. Gludovatz et al., Science 345, 1153–1158 (2014). \n5. Q. Ding et al., Nature 574, 223–227 (2019). \n6. R. Zhang et al., Nature 581, 283–287 (2020). \n7. E. Ma, X. Wu, Nat. Commun. 10, 5623 (2019). \n8. P. Sathiyamoorthi, H. S. Kim, Prog. Mater. Sci. 10.1016/ j.pmatsci.2020.100709 (2020). \n9. T. Yang et al., Science 362, 933–937 (2018). \n10. T. H. Fang, W. L. Li, N. R. Tao, K. Lu, Science 331, 1587–1590 (2011). \n11. X. Wu et al., Proc. Natl. Acad. Sci. U.S.A. 112, 14501–14505 (2015). \n12. Y. M. Wang et al., Nat. Mater. 17, 63–71 (2018). \n13. W. Li et al., Prog. Mater. Sci. 118, 100777 (2021). \n14. E. Ma, Scr. Mater. 181, 127–133 (2020). \n15. J. P. Hirth, J. Lothe, Theory of Dislocations (Wiley, ed. 2, 1982). \n16. M. A. Meyers, K. K. Chawla, Mechanical Behavior of Materials (Cambridge Univ. Press, ed. 2, 2009). \n17. K. Lu, L. Lu, S. Suresh, Science 324, 349–352 (2009). \n18. K. Lu, Nat. Rev. Mater. 1, 16019 (2016). \n19. C. Lee, J. Brechtl, P. K. Liaw, Metall. Mater. Trans. A 52, 2033–2093 (2021). \n20. F. Wang et al., Science 370, 95–101 (2020). \n21. C. Lee et al., Sci. Adv. 6, eaaz4748 (2020). \n22. J. Ding, Q. Yu, M. Asta, R. O. Ritchie, Proc. Natl. Acad. Sci. U.S.A. 115, 8919–8924 (2018). \n23. Q. J. Li, H. Sheng, E. Ma, Nat. Commun. 10, 3563 (2019). \n24. X. Chen et al., Nature 592, 712–716 (2021). \n25. X. D. Xu et al., Acta Mater. 144, 107–115 (2018). \n26. K. S. Kumar, H. Van Swygenhoven, S. Suresh, Acta Mater. 51, 5743–5774 (2003). \n27. B. B. He et al., Science 357, 1029–1032 (2017). \n28. Materials and methods are available as supplementary materials. \n29. M. A. Meyers, A. Mishra, D. J. Benson, Prog. Mater. Sci. 51, 427–556 (2006). \n30. W. Guo et al., Acta Mater. 170, 176–186 (2019). \n31. M. F. Ashby, Philos. Mag. 21, 399–424 (1970). \n32. Y. T. Zhu et al., Mater. Res. Lett. 9, 1–31 (2020). \n33. Z. Li, K. G. Pradeep, Y. Deng, D. Raabe, C. C. Tasan, Nature 534, 227–230 (2016). \n34. F. Otto et al., Acta Mater. 61, 5743–5755 (2013). \n35. S. W. Wu et al., Mater. Res. Lett. 5, 276–283 (2017). \n36. Y. Lin, J. Pan, H. F. Zhou, H. J. Gao, Y. Li, Acta Mater. 153, 279–289 (2018). \n37. X. C. Liu, H. W. Zhang, K. Lu, Science 342, 337–340 (2013). \n38. H. Mughrabi, Acta Metall. 31, 1367–1379 (1983). \n39. P. Peralta, C. Laird, in Physical Metallurgy, D. E. Laughlin, K. Hono, Eds. (Elsevier, ed. 5, 2014), pp. 1765–1880. \n40. M. Komarasamy, N. Kumar, Z. Tang, R. S. Mishra, P. K. Liaw, Mater. Res. Lett. 3, 30–34 (2015). \n41. D. Choudhuri, M. Komarasamy, V. Ageh, R. S. Mishra, Mater. Chem. Phys. 217, 308–314 (2018). \n42. M. Naeem et al., Sci. Adv. 6, eaax4002 (2020). \n43. B. C. De Cooman, Y. Estrin, S. K. Kim, Acta Mater. 142, 283–362 (2018). \n44. E. P. George, D. Raabe, R. O. Ritchie, Nat. Rev. Mater. 4, 515–534 (2019). \n45. J.-W. Yeh, in High-Entropy Alloys Fundamentals and Applications, M. C. Gao, J.-W. Yeh, P. K. Liaw, Y. Zhang, Eds. (Springer, 2016), pp. 51–113. \n46. R. J. Asaro, P. Krysl, B. Kad, Philos. Mag. Lett. 83, 733–743 (2003). \n47. E. Orowan, in Symposium on Internal Stresses in Metals and Alloys (Institute of Metals, 1948), p. 451. \n48. L. J. Santodonato, P. K. Liaw, R. R. Unocic, H. Bei, J. R. Morris, Nat. Commun. 9, 4520 (2018). \n\n49. G. Chen et al., Scr. Mater. 167, 95–100 (2019). \n50. N. Kumar et al., JOM 67, 1007–1013 (2015). \n51. J. Yang et al., J. Alloys Compd. 795, 269–274 (2019). \n52. H. W. Huang, Z. B. Wang, J. Lu, K. Lu, Acta Mater. 87, 150–160 (2015). \n53. J. Z. Long et al., Acta Mater. 166, 56–66 (2019). \n54. H. T. Wang, N. R. Tao, K. Lu, Scr. Mater. 68, 22–27 (2013). \n55. J. J. Wang, N. R. Tao, K. Lu, Acta Mater. 180, 231–242 (2019). \n\n# ACKNOWLEDGMENTS \n\nWe thank S. Y. He for performing HAADF-STEM experiments, M. X. Yang for measuring the back stress, J. Xu for analyzing EBSD results, C. J. Zhang and L. F. Cheng for performing raw sample forging treatment, and J. Burns for performing APT experiments. Funding: Q.P. and L.L. acknowledge financial support from the National Science Foundation of China (NSFC; grants 51931010, 92163202, 52122104, and 52071321), the Key Research Program of Frontier Science and International partnership program (GJHZ2029), Youth Innovation Promotion Association (2019196), the Chinese Academy of Sciences (CAS), and LiaoNing Revitalization Talents Program (XLYC1802026). P.K.L. appreciates support from the National Science Foundation (DMR-1611180 and 1809640) and the US Army Research Office (W911NF-13-1-0438 and W911NF-19-2-0049). This study used resources at the Spallation Neutron Source (SNS), a US Department of Energy (DOE) Office of Science User Facility operated by the Oak Ridge National Laboratory (ORNL). Synchrotron diffraction was conducted at the Advanced Photon Source (APS), a US DOE Office of Science User Facility operated for the DOE Office of Science by the Argonne National Laboratory under contract DE-AC02- 06CH11357. APT was conducted at ORNL’s Center for Nanophase Materials Sciences (CNMS), which is a US DOE Office of Science User Facility. R.F. is grateful for support from Material Engineering Initiative (MEI) at SNS, ORNL. Author contributions: L.L. and P.K.L. initiated the project. L.L. supervised the project. Q.P. and L.Z. prepared the sample and performed the experimental tests. Q.L. conducted TEM observations. R.F., K.A., and A.C.C. performed the neutron and synchrotron diffraction experiments. R.F. carried out the diffraction line profile analysis. J.D.P. and R.F. performed the APT experiments and analysis. Q.P. and L.L. drafted the manuscript. All authors contributed to the discussions and revised the manuscript. Competing interests: A Chinese patent (grant number ZL201911044516.5) on the CT processing has been granted. Data and materials availability: All data generated or analyzed during this study are included in this article and its supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abj8114 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S11 \nReferences (56–83) \n3 June 2021; accepted 1 September 2021 \nPublished online 23 September 2021 \n10.1126/science.abj8114 " + }, + { + "id": "10.1038_s41557-021-00734-x", + "DOI": "10.1038/s41557-021-00734-x", + "DOI Link": "http://dx.doi.org/10.1038/s41557-021-00734-x", + "Relative Dir Path": "mds/10.1038_s41557-021-00734-x", + "Article Title": "General synthesis of single-atom catalysts with high metal loading using graphene quantum dots", + "Authors": "Xia, C; Qiu, YR; Xia, Y; Zhu, P; King, G; Zhang, X; Wu, ZY; Kim, JY; Cullen, DA; Zheng, DX; Li, P; Shakouri, M; Heredia, E; Cui, PX; Alshareef, HN; Hu, YF; Wang, HT", + "Source Title": "NATURE CHEMISTRY", + "Abstract": "Transition-metal single-atom catalysts present extraordinary activity per metal atomic site, but suffer from low metal-atom densities (typically less than 5 wt% or 1 at.%), which limits their overall catalytic performance. Here we report a general method for the synthesis of single-atom catalysts with high transition-metal-atom loadings of up to 40 wt% or 3.8 at.%, representing several-fold improvements compared to benchmarks in the literature. Graphene quantum dots, later interweaved into a carbon matrix, were used as a support, providing numerous anchoring sites and thus facilitating the generation of high densities of transition-metal atoms with sufficient spacing between the metal atoms to avoid aggregation. A significant increase in activity in electrochemical CO2 reduction (used as a representative reaction) was demonstrated on a Ni single-atom catalyst with increased Ni loading.", + "Times Cited, WoS Core": 460, + "Times Cited, All Databases": 471, + "Publication Year": 2021, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000665817700002", + "Markdown": "# General synthesis of single-atom catalysts with high metal loading using graphene quantum dots \n\nChuan Xia $\\begin{array}{r}{\\textcircled{10}1,2,3\\boxtimes}\\end{array}$ , Yunrui Qiu1, Yang Xia1, Peng Zhu $\\oplus1$ , Graham King $\\textcircled{\\bullet}4$ , Xiao Zhang1, Zhenyu Wu $\\textcircled{10}$ 1, Jung Yoon (Timothy) Kim $\\oplus1$ , David A. Cullen $\\textcircled{10}5$ , Dongxing Zheng6, Peng $\\mathsf{L i}^{6}$ , Mohsen Shakouri ${\\textcircled{15}}4$ , Emilio Heredia4, Peixin Cui $\\textcircled{10}$ 7, Husam N. Alshareef $\\textcircled{10}6$ , Yongfeng Hu   4 ✉ and Haotian Wang   1,8,9,10 ✉ \n\nTransition-metal single-atom catalysts present extraordinary activity per metal atomic site, but suffer from low metal-atom densities (typically less than 5 wt% or 1 at. $\\%$ ), which limits their overall catalytic performance. Here we report a general method for the synthesis of single-atom catalysts with high transition-metal-atom loadings of up to $40\\times1\\%$ or $3.8\\approx1.\\%,$ representing several-fold improvements compared to benchmarks in the literature. Graphene quantum dots, later interweaved into a carbon matrix, were used as a support, providing numerous anchoring sites and thus facilitating the generation of high densities of transition-metal atoms with sufficient spacing between the metal atoms to avoid aggregation. A significant increase in activity in electrochemical $\\mathbf{co}_{2}$ reduction (used as a representative reaction) was demonstrated on a Ni single-atom catalyst with increased Ni loading. \n\nike the transformative changes brought to the catalysis field by making bulk metal materials into nanosized particles, further shrinking the size all the way down to isolated single atoms, embedded in a supporting matrix, is reshaping both the design of catalysts and the understanding of reaction mechanisms1–5. Due to their unique atomic structures and electronic properties, atomically dispersed transition-metal (TM) catalysts have been demonstrated to (1) maximize the atom utilization, particularly for high-cost noble metals1,2,5–8, and (2) more importantly present unconventional catalytic activities compared to their bulk or nanosized counterparts9–15. These exciting features have sparked the development of general synthesis methods of single-atom catalysts for different applications. Strong interactions between metal atoms and the solid support are critical to confine those isolated atoms and prevent aggregation16,17, especially under high-temperature conditions. The most commonly used support matrix is carbon, mainly due to its strong affinity with TM atoms by forming stable chemical bonds, as well as its high tunability in allowing different dopants, high stability and good electrical conductivity18,19. A few general synthesis strategies have been reported to obtain various single-atom coordinations on carbon supports2,20–26, with a general form of TM–X–C ( $\\mathrm{TM}=\\mathrm{Fe}$ , Ni, Ir, Pt and so on; ${\\mathrm{X}}{=}{\\mathrm{N}}_{\\mathrm{i}}$ , S, P and so on). However, their metal-atom loadings, especially for noble metals, are typically limited within one atomic percent $\\left(\\mathrm{at.\\%}\\right)$ or a few weight percent $(\\mathrm{wt\\%})$ , which are significantly lower than commercial benchmark catalysts (for example, $20\\mathrm{wt\\%\\Ir/C}$ or $\\mathrm{Pt/C},$ ) and thus result in limited overall catalytic activity. Therefore, a general synthesis strategy to dramatically improve the metal-atom densities in single-atom catalysts, with metal loadings close to or even beyond their commercial benchmark counterparts, will play a critical role in this field, but still remains as an open challenge. \n\nThere are two general strategies, ‘top down’ (Fig. 1a) and ‘bottom up’ (Fig. 1b), that have been widely reported in synthesizing TM single atoms on carbon supports4,5. The ‘top-down’ synthesis strategies typically start with existing carbon supports such as graphene sheets or carbon nanotubes, followed by creating carbon vacancies to allow physical confinement of TM atoms27,28. However, as the size of carbon vacancies cannot be uniformly controlled and could range from one to tens of atoms, the total number of vacant sites is dramatically limited. As a result, clusters will be easily formed in large vacancies under a high metal loading (Fig. 1a). On the other hand, the ‘bottom-up’ strategies start with metal and organic precursors13,21, such as metal–organic frameworks, metal–porphyrin molecules or small organic molecules, followed by a high-temperature carbonization process to form the carbon matrix with metal atoms embedded (Fig. 1b). However, due to the excessive number of metal atoms and the lack of spacing between them, they tend to aggregate into clusters or nanoparticles during the annealing process, resulting in significantly decreased single-atom metal loadings. A strategy with a different synthesis mechanism is needed to overcome these metal loading limitations in single-atom catalysts. \n\nHere we report a general synthesis of single-atom catalysts with high TM-atom densities of up to $41.6\\mathrm{wt\\%}$ or $3.84\\mathrm{at.}\\%$ (in the case of iridium, Ir), representing a several-fold improvement compared to benchmarks in the literature (Table 1). Multi-scale characterization evidence ranging from subnanometres to millimetres was integrated to exclude the existence of clusters or nanoparticles. Other noble or non-noble TM single-atom catalysts with similarly high loadings were also obtained, suggesting the generality of our strategy. We first use Ir as the representative metal centre, confined in N-doped carbon, which has been most widely used to stabilize TM single atoms29–31, to demonstrate our synthetic strategy. In contrast with traditional ‘top-down’ or ‘bottom-up’ methods, our strategy (Fig. 1c) starts from surface-functionalized graphene quantum dots (GQDs) based on the following motivations: (1) GQDs are small enough, compared to the carbon supports in ‘top-down’ methods, to supply numerous surface anchoring sites for large loadings of isolated metal atoms. (2) On the other hand, compared to the organic precursors in ‘bottom-up’ methods, GQDs as the intermediate carbon support do not undergo significant structural evolution during pyrolysis, providing a stable and large spacing between TM atoms to avoid aggregation. Specifically, when functionalized with amine groups $\\bigl(\\mathrm{GQDs}{\\mathrm{-NH}}_{2}\\bigr)$ ) and mixed with TM salts in solutions, GQDs can stably and uniformly spread and confine TM cations on their surfaces (Fig. 1c) due to the strong chelation/complexation effect between metal cations and amine groups32. This strong interaction helped the quantum dots to interconnect with each other and self-assemble into a layered bulk structure during the freeze-drying process of the $\\mathrm{Ir^{3+}/G Q D s{\\mathrm{-}}N H_{2}}$ mixture33. Followed by a pyrolysis process under an ammonia-rich atmosphere, a dense Ir single-atom catalyst can be obtained. \n\n![](images/8977f555ff2f60e2203b8d308d2e61cafd3816daa23bd325dd1351ca5eaa15a6.jpg) \nFig. 1 | Schematic illustration of the synthesis process of single-atom catalysts using different strategies. a, The ‘top-down’ synthesis strategy, which typically starts with existing carbon supports such as graphene sheets or carbon nanotubes, followed by creating carbon vacancies to trap TM atoms. b, The ‘bottom-up’ approach, which starts with metal and organic precursors. c, The proposed method, which is based on the crosslinking and self-assembly of GQDs. \n\n# Results and discussion \n\nSynthesis of functionalized GQDs. A modified molecular fusion route was employed to synthesize well-crystallized GQDs– $\\mathrm{NH}_{2}$ (Methods)34. Photoluminescence (PL) emission studies (Supplementary Fig. 1) of the as-prepared carbon suspension presents an excitation-dependent PL, confirming the successful preparation of $\\mathrm{GQD}s^{33}$ . Transmission electron microscopy (TEM) images and X-ray diffraction suggest that the GQDs are well crystallized, with a uniform size of ${\\sim}6{-}8\\mathrm{nm}$ (Fig. 2b and Supplementary Figs. 2 and 3). Obviously, the GQDs with different particle sizes and functional groups could affect the metal loading of single-atom catalysts (details in Supplementary Figs. 2 and 4). With the decreasing of the size of GQDs, the concentration of the surface functional group will be increased due to its enhanced surface/volume ratio and thus lead to a higher concentration of anchored single metal atoms. So, theoretically, the smaller it is, the better. However, if the size of GQDs is too small, effective steric hindrance cannot be provided to prevent the agglomeration of metal sites between different GQDs. The optimized size of the GQDs is within ${\\sim}5\\mathrm{-}10\\mathrm{nm}$ in our case. The X-ray photoelectron spectroscopy (XPS) analysis of the as-prepared GQDs shows a high nitrogen content of $10.8\\mathrm{at.}\\%$ (Supplementary Fig. 5). Further deconvolution of the high-resolution N 1s spectrum (Supplementary Fig. 5) shows the contribution of the $\\mathrm{-NH}_{2}$ group, $_{\\mathrm{N-C}}$ bond and a trace amount of residual $-\\mathrm{NO}_{2}$ group at $399.2\\mathrm{eV},$ $400.3\\mathrm{eV}$ and $405.4\\mathrm{eV},$ respectively34,35. The small size of the GQDs with high contents of surface and edge $\\mathrm{-NH}_{2}$ functional groups ensure the fixation of high metal-atom loadings. \n\nSynthesis of Ir single-atom catalyst. We then use the as-obtained $\\mathrm{GQDs-NH}_{2}$ solution to synthesize the $\\mathrm{Ir{-}N{-}C}$ catalyst with varied iridium loadings (Fig. 2a). Specifically, different volumes of ${\\mathrm{IrCl}}_{3}$ stock solution (5 milligrams per millilitre) were first added into 30 millilitres of $\\mathrm{GQDs-NH}_{2}$ solution (1 milligram per millilitre), henceforth referred to as $\\scriptstyle\\mathrm{Ir-N-C-}x$ where $x$ represents the ${\\mathrm{IrCl}}_{3}$ volume in millilitres, followed by freeze drying and pyrolysis. \n\n
Table1| Composition summary of as-prepared TM single-atom catalysts
CatalystCarbon precursorMetal content (wt%) Metal content (at.%) Dopant content (at.%)
Ir-N-C (this work)GQDs-NH241.6 ± 2.5a 37.6b 44.5℃3.84b27.8b nitrogen
Ni-N-C (this work)GQDs-NH215.3 ± 1.4a 14.8b 15.4±0.4d3.61b20.3b nitrogen
Ir/meso_S-C (ref.17)Mesoporous bulk carbon~10b~0.77b~6.6b sulfur
f-IrNC (ref. 44) Formamide3.06bN/AN/A
Ir-SAC (ref. 39)ZIF-80.2dN/AN/A
Ni-NC ref. 22)Glucose5.9aN/AN/A
Ni-N-C (ref. 45) Ni(phen) complex6.55c 7.5d1.48c11.3c nitrogen
A-Ni-NSG (ref. 41)Melamine/L-alanine(L-cysteine)2.5b 2.8d0.47b9.2b nitrogen
\n\nRecently reported representative carbon-supported single-atom catalysts with high metal loading are included for comparison. Note that all of the included reports presented at least EXAFS and STEM characterizations to confirm their single-atom dispersion. SAC, single-atom catalyst; A–Ni–NSG, sulfur and nitrogen co-doped carbon-supported Ni single-atom catalyst, where A is the amino acid that is the carbon source of the catalyst; N/A indicates that the related information was not provoided in the literature. aEstimated by TGA. bEstimated by XPS. cEstimated by EDS. dEstimated by inductively coupled plasma \n\nFigure 2c and Supplementary Fig. 6 show the scanning electron microscope (SEM) images of the $\\mathrm{GQDs-NH}_{2}$ with 7 millilitres of $\\mathrm{IrCl}_{3}$ solution after freeze drying, indicating a crosslinking and self-assembly process from well-dispersed $\\mathrm{GQDs-NH}_{2}$ to layered bulk carbon structures, which agrees with previous reports33,36. This layered morphology was maintained after pyrolysis at $500^{\\circ}\\mathrm{C}$ in argon, resulting in the Ir–N–C-7 final product (Methods, Fig. 2d and Supplementary Fig. 7). Cl ligands were completely removed during this pyrolysis step as confirmed by XPS (Supplementary Fig. 8). The X-ray diffraction patterns of $\\mathrm{Ir-N-C}$ catalysts with different iridium loadings show similar features of two broad peaks at approximately $19^{\\circ}$ and $38^{\\circ}$ (Fig. 2e), suggesting the formation of amorphous bulk carbon from GQD assembly after pyrolysis. No metallic iridium peaks were observed in $\\mathrm{Ir{-}N{-}C}$ catalysts until ${\\sim}60\\mathrm{wt\\%}$ iridium loading (Ir–N–C-15), implying that high-loading atomically dispersed iridium catalyst could be obtained. Iridium quantification from XPS (Fig. 2f) reveals a quasi-linear increasing of iridium content from Ir–N–C-1 to Ir–N–C-7, followed by a nonlinear change of iridium content from Ir–N–C-8 to Ir–N–C-15 catalyst, which implies that uniform atomically dispersed iridium might be formed until the nominal iridium loading (Methods) of ${\\sim}41\\mathrm{wt\\%}$ (iridium content in Ir–N–C-7). This observation is consistent with the deconvolution of the high-resolution iridium $4f$ spectrum (Fig. 2g). Only an oxidized iridium specie in the form of $\\mathrm{Ir}^{\\delta+}$ (iridium $4f_{7/2}$ peak at $61.9\\mathrm{eV}\\cdot$ ) was detected until the Ir–N–C-7 catalyst, followed by the arising of metallic iridium (iridium $4f_{7/2}$ peak at $60.8\\mathrm{eV},$ from $I\\mathrm{r-N\\mathrm{-}C-}8$ to $I\\mathrm{r-N-C-}15$ (ref. 37). It is worthwhile to note that the oxidation state of iridium in Ir–N–C-7 catalyst is very close to that of $\\mathrm{IrO}_{2}\\left(+4\\right)$ , where the iridium $4f_{7/2}$ peak of $\\mathrm{IrO}_{2}$ is located at $61.6\\mathrm{eV}$ (ref. 38). According to the XPS results, our Ir–N–C-7 catalyst has an iridium loading of $37.6\\mathrm{wt\\%}$ $(3.84\\mathrm{at.\\%})$ and nitrogen content of $27.8\\mathrm{at.\\%}$ , consistent with the nominal iridium loading of ${\\sim}41\\mathrm{wt\\%}$ . \n\nAberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) was performed to investigate the distribution of iridium species at the atomic scale in $\\bar{\\mathrm{Ir}}{-}\\mathrm{N}{-}\\mathrm{C}{-}7$ catalyst. As illustrated in Fig. 3a–d, densely while atomically dispersed iridium atoms on a highly porous carbon support were observed in $\\mathrm{Ir-N\\mathrm{-}C\\mathrm{-}7}$ catalyst, with no clusters observed. The homogeneously dispersed bright spots are ${\\sim}0.2\\mathrm{nm}$ in size, matching with the theoretical size of metal atoms. The simultaneous acquisition of electron energy loss spectroscopy (EELS) and energy-dispersive X-ray spectroscopy (EDS) results with the beam positioned on a bright atom, shown in Supplementary Fig. 9, revealed Ir, N and C and suggested possible coordination of Ir–N–C. EDS mapping analysis further demonstrates the homogeneous distribution of iridium, nitrogen and carbon (Supplementary Fig. 10) and gives an iridium content of $44.5\\mathrm{wt\\%}$ . More importantly, a wide-range HAADF-STEM screening was performed to confirm that there are no iridium clusters or nanoparticles in high-loading $\\scriptstyle{\\mathrm{Ir-N-C}}$ samples (Supplementary Figs. 11 and 12). However, nanoparticles were observed when the iridium loading was further increased to Ir–N–C-8 (Supplementary Fig. 13), agreeing well with the XPS analysis. Considering the limited solubility of iridium in corrosive aqua regia solution, we employed thermogravimetric analysis (TGA) to accurately obtain the iridium loading in $\\mathrm{Ir{-}N{-}C{-}7}$ catalyst of $41.6{\\pm}2.5\\mathrm{wt\\%}$ (Supplementary Fig. 14). This result is consistent with the estimations by XPS $(37.6\\mathrm{wt\\%})$ and EDS $(44.5\\mathrm{wt\\%})$ and the nominal calculation $(\\sim41.5\\mathrm{wt\\%})$ . \n\nWith the confirmation of the atomic distribution of Ir down to the subnanometre scale by STEM characterization, we next employed $\\mathrm{\\DeltaX}$ -ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) to study the electronic and coordination structures of iridium in high-loading Ir single-atom catalysts, such as the Ir–N–C-7 sample, at the micrometre scale. As shown in the Ir $\\mathrm{L}_{3}$ -edge XANES spectra (Supplementary Fig. 15), the spectrum of $\\mathrm{Ir{-}N{-}C{-}7}$ was different from that of Ir foil and very similar to that of $\\mathrm{IrO}_{2}$ , indicating a higher oxidation state of iridium in Ir–N–C-7. The EXAFS spectra of Ir–N–C-7 catalyst (Fig. 3e) presents a prominent peak at $\\mathrm{\\sim}\\mathrm{\\bar{1}}.58\\mathrm{\\AA}$ , which can be ascribed to the iridium–nitrogen/carbon coordination39. No high-order peaks, such as the iridium–iridium interaction in Ir foil $({\\sim}2.6\\mathrm{\\AA})$ and Ir–O– Ir in $\\mathrm{IrO}_{2}$ , were observed, confirming that the iridium species in Ir–N–C-7 were dispersed as isolated single atoms. Further EXAFS fitting, as shown in Supplementary Fig. 16 and Supplementary Table 1, suggested a possible relative uniform $\\mathrm{Ir-N_{4}}$ configuration for the Ir sites of Ir–N–C-7 catalyst. Synchrotron-based pair distribution function (PDF) analysis was performed to further demonstrate the homogeneity of Ir–N–C-7 catalyst in the millimetre-scale range. The Ir–N–C-7 powders were loaded into 0.9-millilitre-inner-diameter Kapton capillaries for PDF measurement using an X-ray radiation of wavelength $0.21062\\mathring{\\mathrm{A}}$ . Figure 3f and Supplementary Fig. 17 show the PDF spectra of Ir–N–C-7, suggesting a highly amorphous material with a structural correlation up to only $7\\ddot{\\mathrm{A}}$ . The peaks located at 1.35 and $2.02\\mathring\\mathrm{A}$ represent the C–C/N bonds and the Ir–C/N bonds, respectively. No iridium–iridium interaction, which is expected at $2.7\\mathring\\mathrm{A}$ , was observed in Ir–N–C-7 catalyst, indicating the atomic dispersion of iridium across the whole range of Ir–N–C-7 single-atom catalyst. The above discussed multi-scale characterization results, taken together, lead to a solid conclusion that Ir single-atom catalyst with a high loading of up to ${\\sim}40\\mathrm{wt\\%}$ was successfully synthesized. \n\n![](images/0a8802b357fbb00dd36d29c6e1134f1e3113171fe4c915ace856afe4bc9566b9.jpg) \nFig. 2 | Synthesis and characterization of atomically dispersed iridium catalyst with iridium content of approximately $41w t\\%$ and 3.84 at.%. a, Digital photo of (from left to right) GQD precursor (Pre-GQDs), $G Q D s\\mathrm{-}N H_{2}$ solution, freeze-dried $\\mathsf{I r/G Q D S–N H_{2}}$ assembly and Ir–N–C-7 catalyst. b, Typical TEM image of $G Q D s\\mathrm{-}N H_{2},$ , showing its uniform lateral size of $\\mathord{\\sim}6\\mathrm{-}8\\mathsf{n m}$ . c,d, SEM images of freeze-dried $\\mathsf{I r/G Q D S–N H_{2}}$ assembly (c) and Ir–N–C-7 catalyst (d). Scale bars: $5\\mathsf{n m}$ (b), $300\\mathsf{n m}$ (c) and $500\\mathsf{n m}$ $({\\pmb d})$ . e, X-ray diffraction patterns of as-prepared iridium-anchored carbon catalysts with different iridium loadings, demonstrating that no metallic iridium peaks could be detected until ${\\sim}60\\mathrm{{wt\\%}}$ iridium was loaded. $2\\theta$ represents the diffraction angle. f, Preliminary quantification of iridium loading using $\\mathsf{X P S}$ analysis. The plot shows a quasi-linear iridium increase from the Ir–N–C-1 sample to the Ir–N–C-7 sample, implying the formation of uniformly dispersed iridium species onto the carbon support within these samples. The vertical dotted line represents the starting point of formation of Ir clusters/particles. Errors have not been estimated because multiple tests were not deemed necessary for the whole range. We repeated the XPS measurements on the Ir–N–C-7 sample and observed loadings of $37.6\\mathrm{wt\\%}$ (Table 1) and, on a different batch sample, $39.8\\mathrm{wt\\%}$ . g, Deconvolution of the high-resolution iridium $4f$ spectra for Ir–N–C-6, Ir–N–C-7, Ir–N–C-8, Ir–N–C-10, Ir–N–C-12 and Ir–N–C-15 catalysts. The panel shows that metallic iridium clusters and/or nanoparticles become visible in XPS when iridium content is higher than that in Ir–N–C-7 (approximately $41w t\\%$ and $3.84\\sf{a t.\\%}^{\\cdot}$ ). B.E., binding energy. \n\nTo monitor the synthesis transition of the $\\mathrm{GQDs}{\\mathrm{-NH}_{2}}/\\mathrm{Ir}^{3+}$ mixture to the single-atom $\\mathrm{Ir{-}N{-}C{-}7}$ catalyst, we first examined the sample using ex-situ $\\mathrm{\\DeltaX}$ -ray diffraction under different temperatures, which represent different synthesis phases. As shown in Supplementary Fig. 18, the GQDs started to get fused at $300^{\\circ}\\mathrm{C}$ to form an amorphous bulk carbon, indicated by the emerging of a broad peak at around $19^{\\circ}$ as well as the decreasing of the intensity of the GQD (002) peak. The amorphization transition might be due to the heavy incorporation of nitrogen and iridium atoms into the GQD lattice under high temperature. With the temperature further increased, the (002) peak of the GQDs completely disappeared, and two broad peaks at approximately $19^{\\circ}$ and $38^{\\circ}$ (Supplementary Fig. 18) emerged, suggesting the full formation of amorphous bulk carbon from GQD assembly after pyrolysis. No metallic iridium peaks were observed in Ir–N–C-7 catalysts. Ex-situ XPS study (Supplementary Fig. 18) reveals that the oxidation state of Ir gradually increases from $300^{\\circ}\\mathrm{C}$ to $500^{\\circ}\\mathrm{C},$ which also implies that the $\\mathrm{Ir}^{3+}$ stabilized by the amine functional group in the $\\mathrm{\\GQDs{-}N H{_{2}}/}$ $\\mathrm{Ir}^{3+}$ mixture gradually coordinated with the lattice nitrogen and carbon to form more stable Ir– ${\\mathrm{-N}}_{a}{\\mathrm{-C}}$ motif. A scheme (Supplementary Fig. 18) was employed to illustrate the synthesis of high-loading $\\mathrm{Ir{-}N{-}C{-}7}$ catalyst. Initially, the $\\mathrm{Ir}^{3+}$ atoms were stably absorbed on the $\\mathrm{GQDs-NH}_{2}$ surface by the strong chelation/complexation effect between metal cations and amine groups. With the temperature continuing to increase, the small GQDs started to interconnect and then to form a three-dimensional bulk carbon that can be directly used for practical applications. Simultaneously, the surface nitrogen will be in-situ doped into the GQD lattice under high temperature, and thus help to trap the isolated Ir atoms to form the Ir– $\\scriptstyle\\cdot\\mathrm{N}_{a}-\\mathrm{C}$ coordination. As a result, the oxidation state of Ir will increase after the formation of the $\\mathrm{Ir}{-}\\mathrm{N}_{a}$ –C motif. The thermal stability of the GQDs is the key point to avoid the formation of Ir nanoclusters or particles. While the heavy incorporation of nitrogen and iridium atoms leads to less lattice periodicity of GQDs, they do not undergo a complete deconstruction during pyrolysis, which was demonstrated by the TEM study under different temperatures (Supplementary Fig. 18). Thus, it can provide a stable and large spacing between TM atoms to avoid aggregation. \n\n![](images/663fb910a63d70707c2975d20dfd1c54d46bba4b9501e77a5d260dea1f147107.jpg) \nFig. 3 | Characterization of atomically dispersed iridium catalyst with iridium content of \\~41 wt%. a–d, Aberration-corrected HAADF-STEM images of Ir–N–C-7 catalyst. Scale bars, $100\\mathsf{n m}$ (a), 5 nm (b), $2{\\mathsf{n m}}$ (c) and 1 nm (d). e, The EXAFS spectra of the Ir–N–C-7 sample. The data for commercial iridium foil and $\\mathsf{I r O}_{2}$ powder were included for comparison. f, Pair distribution function for Ir–N–C-7 catalyst. The simulated PDF for bulk iridium metal was used for comparison. The $\\mathsf{X}$ -ray absorption spectroscopy and pair distribution function demonstrated that there is no iridium–iridium contribution in Ir–N–C-7 catalyst in the micrometre-scale and millimetre-scale ranges, respectively, confirming the formation of fully isolated iridium species in this sample. \n\nWe further demonstrated that another carbon substrate with similar high nitrogen dopants cannot deliver the same products. Specifically, we first synthesized nitrogen-doped graphene using graphene oxide (GO) as the starting material (Supplementary Fig. 19). The as-synthesized nitrogen-doped carbon $\\scriptstyle\\left(\\mathrm{GO-NH}_{2}\\right)$ shows a very high nitrogen content of ${\\sim}20\\mathrm{at.}\\%$ (Supplementary Fig. 19). The ${\\mathrm{GO}}{\\mathrm{-NH}}_{2}$ was used as the support to synthesize the Ir single-atom catalyst, following the same process as for Ir–N–C-7 synthesis. However, we found that even if the loading of Ir is less than $10\\mathrm{wt\\%}$ , nanoparticles will be formed (Supplementary Fig. 19), showing obvious metallic Ir $\\mathrm{\\DeltaX}$ -ray diffraction peaks. This observation reveals that a high-loading Ir single-atom catalyst could not be obtained using the carbon support with only a high level of nitrogen dopant, demonstrating the unique role of the GQDs. While ${\\mathrm{GO}}{\\mathrm{-NH}}_{2}$ is as stable as GQDs during pyrolysis, it shows a very low surface-to-volume ratio, providing limited anchor sites. As the intermediate carbon support, GQDs are unique since they can supply numerous surface anchoring sites for large loadings of isolated metal atoms, and they are stable enough during pyrolysis to prevent the isolated atom aggregation. \n\nSynthesis of other single-atom catalysts. To validate if our GQD-assisted synthesis method can be extended to synthesize other TM single-atom catalysts with high metal loadings, we first replaced the iridium precursor with platinum to prepare $\\mathrm{Pt-N-C}$ single-atom catalysts. Figure $\\mathtt{4a}$ and Supplementary Fig. 20 exhibit the HAADF-STEM images of Pt–N–C-6 catalyst with a nominal platinum content of ${\\sim}32.3\\mathrm{wt\\%}$ (Methods). Densely dispersed Pt single atoms were observed without any nanoclusters or particles, suggesting the successful extension from iridium to different noble metal centres. The EDS elemental mapping shows the uniform distribution of platinum, nitrogen and carbon in Pt–N–C-6 (Supplementary Fig. 21). The EELS and EDS scans on a single platinum site (Supplementary Fig. 22) further reveal the expected platinum, nitrogen and carbon signals in $\\mathrm{Pt}{-}\\mathrm{N}{-}\\mathrm{C}{-}6$ . The deconvolution of platinum $4f$ spectra (Supplementary Fig. 20) demonstrates that the isolated platinum in $\\mathrm{Pt}{-}\\mathrm{N}{-}\\mathrm{C}{-}6$ catalyst is in the oxidized valence state, with the Pt $4f_{7/2}$ peak located at $72.5\\mathrm{eV},$ which is higher than that of metallic Pt $4f_{7/2}$ at $71.1\\mathrm{eV})^{40}$ . No metallic platinum signal was detected by XPS. \n\nOther TM centres beyond noble metals, represented by nickel, were also prepared via the same synthesis method. As shown in Fig. 4b, the as-synthesized Ni–N–C-3 catalyst presents atomically dispersed nickel without observable nickel clusters. The colocation of nickel and nitrogen on the carbon support was also demonstrated by the STEM–EELS point spectrum (Fig. 4c). The highest nickel single-atom loading we can obtain is approximately $15\\mathrm{wt\\%}$ $(3.6\\mathrm{at.\\%}$ ; Supplementary Fig. 23) in $N_{1-}\\mathrm{N}_{-}\\mathrm{C}_{-}3$ , which is at least twofold higher than previously reported Ni single-atom catalysts (Table 1). As the nickel species can be readily dissolved in aqua regia solution, we then used inductively coupled plasma optical emission spectrometry to double confirm the nickel atom loading. \n\n![](images/6e64b53eaa31fbe855d376c1cfa4c146ede6c52a48503d4d657a63d1192d8aa0.jpg) \n\nAs a result, the inductively coupled plasma gives a nickel content of $15.4\\pm0.4\\mathrm{wt\\%}$ for Ni–N–C-3, which is in good agreement with XPS and TGA estimations, confirming the high accuracy of the XPS and TGA methods for single-atom loading quantification. The Ni K-edge XANES spectra in Fig. 4d show that the oxidation state of Ni in as-prepared Ni–N–C is located between 0 and $+2$ , which is consistent with XPS analysis (Supplementary Fig. 24). The EXAFS \n\nFig. 4 | Generality of the GQD-assisted strategy for synthesizing atomically dispersed TM catalysts with high metal content. a, Aberration-corrected HAADF-STEM image of Pt–N–C-6 catalyst with a nominal platinum content of ${\\sim}32.3\\mathrm{wt\\%}$ , demonstrating the formation of isolated platinum species on a nitrogen-doped carbon support. Scale bar, 2 nm. b, Aberration-corrected HAADF-STEM image of Ni–N–C-3 catalyst with ${\\sim}15\\mathrm{wt\\%}$ Ni, demonstrating that isolated nickel atoms were uniformly immobilized onto the carbon support. Scale bar, 1 nm. c, STEM–EELS point spectrum of isolated nickel site (circled in red in the inset), suggesting the colocation of nickel and nitrogen on the carbon support. c.p.s., counts per second. d,e, Normalized XANES (d) and EXAFS (e) spectra for the Ni–N–C-3 sample. The data for commercial nickel foil and NiO powder were included for comparison. f, Pair distribution function for Ni– N–C-3 catalyst. The simulated PDF spectra for bulk nickel metal was included for comparison. The peak at \\~1.41 Å is due to the C–C bonds in graphite. Two overlapped peaks at approximately 1.8 to $2.0\\mathring{\\mathsf{A}}$ can be ascribed to the Ni–N and Ni–C contributions. Another prominent peak at ${\\sim}2.5\\tt{\\AA}$ originates from the second nearest neighbour C–C distances. The PDF clearly demonstrates that the nickel species are in isolated environments and coordinate with nitrogen in as-prepared 15 wt% Ni–N–C catalyst. $\\scriptstyle{\\pmb{\\mathsf{g}}},$ The steady-state current densities $(j)$ and the corresponding Faradaic efficiencies of CO $(\\mathsf{F E}_{\\mathsf{C O}})$ of ${\\sim}7.5\\mathrm{wt}\\%$ Ni–N–C and \\~15 wt% Ni–N–C catalyst in an anion membrane electrode assembly (MEA). The intrinsic ${\\mathsf{C O}}_{2}$ reduction reaction performance of Ni–N–C catalysts were performed and repeated in a standard three-electrode flow cell (Supplementary Fig. 26). h, The corresponding CO partial current densities $(j_{\\scriptscriptstyle{\\subset\\circ}})$ of ${\\sim}7.5\\mathrm{wt\\%}$ Ni–N–C and \\~15 wt% Ni–N–C catalyst at different applied voltages. \n\nof $15\\mathrm{wt\\%}$ Ni–N–C catalyst (Fig. 4e) presented a notable Ni–N/C coordination peak at ${\\sim}1.\\dot{3}5\\mathring\\mathrm{A}$ , without any observable Ni–Ni interactions at ${\\sim}2.{\\dot{1}}8{\\dot{\\mathrm{A}}}$ (Ni foil) and Ni–O–Ni (NiO). Synchrotron-based PDF (Fig. 4f and Supplementary Fig. 25) further confirms the nickel single-atom dispersion across the whole sample region. The above results confirm that tuning the metal active site is routinely achievable, demonstrating the generality of our synthetic strategy for high-loading TM single-atom catalysts. \n\nElectrochemical $\\mathbf{CO}_{2}$ reduction on Ni single-atom catalyst. Ni single-atom catalysts have shown high selectivity in electrochemical $\\mathrm{CO}_{2}$ reduction to CO, but limited activity due to the low Ni density14,41–43. As a representative case study, we compare the $\\mathrm{CO}_{2}$ reduction performances on as-prepared Ni–N–C-1.5 $\\mathrm{({\\sim}7.5w t\\%N i)}$ ) and Ni–N–C-3 $\\left({\\sim}15\\mathrm{wt\\%\\Ni}\\right)$ catalysts with the same catalyst mass loading but different nickel atom loadings. To overcome the $\\mathrm{CO}_{2}$ diffusion limitation in the H-cell reactor and the flooding issue of the gas diffusion electrode in the flow cell reactor, we utilized an anion-exchange membrane electrode assembly (Methods) to investigate the impact of Ni single-atom loading on $\\mathrm{CO}_{2}$ reduction performance14. As shown in Fig. $4\\mathrm{g}$ and Supplementary Fig. 26, while both ${\\sim}7.5\\mathrm{wt\\%}$ Ni–N–C-1.5 and ${\\sim}15\\mathrm{wt\\%}$ Ni–N–C-3 show an outstanding CO selectivity of over $90\\%$ , their activities differ dramatically. Specifically, under a cell voltage of ${\\sim}2.55\\mathrm{V},{\\sim}15\\mathrm{wt}\\%\\mathrm{Ni}–\\mathrm{N}–\\mathrm{C}–3$ catalyst can deliver a CO partial current of $122\\mathrm{mAcm}^{-2}$ , which represents a 2.5-fold improvement from ${\\sim}7.5\\mathrm{wt\\%}$ Ni–N–C-1.5 (Fig. 4h). In addition, we performed HADDF-STEM analysis on the postcatalysed Ni–N–C-3 catalyst (Supplementary Fig. 27). We did not observe any agglomeration during the $\\mathrm{CO}_{2}$ reduction reaction, demonstrating the good stability of our high-loading single-atom catalysts. This result clearly demonstrates the advantage of high single-atom loadings in improving single-atom catalysis. \n\nPushing the metal loading in single-atom catalysts to the limit will play a critical role in the catalysts’ practical applications. Our GQD-assisted synthesis strategy sets up a limit of TM single-atom density before the formation of clusters or nanoparticles. Fine tuning of the quantum dot functional group, TM coordination environment and TM centre will be future directions to further increase the single-atom loading and improve the catalytic performances of single-atom catalysts in different reaction applications. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/ s41557-021-00734-x. \n\n# References \n\n1.\t Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}}/\\mathrm{FeO}_{x}.$ Nat. Chem. 3, 634–641 (2011). \n2.\t Sun, X. et al. Facile synthesis of precious-metal single-site catalysts using organic solvents. Nat. Chem. 12, 560–567 (2020). \n3.\t Zhang, L., Ren, Y., Liu, W., Wang, A. & Zhang, T. Single-atom catalyst: a rising star for green synthesis of fine chemicals. Natl Sci. Rev. 5, 653–672 (2018). \n4.\t Ji, S. et al. Chemical synthesis of single atomic site catalysts. Chem. Rev. 120, 11900–11955 (2020). \n5.\t Chen, Y. et al. Single-atom catalysts: synthetic strategies and electrochemical applications. Joule 2, 1242–1264 (2018). \n6.\t Liu, P. et al. Photochemical route for synthesizing atomically dispersed palladium catalysts. Science 352, 797–800 (2016). \n7.\t Lu, Y. et al. Identification of the active complex for CO oxidation over single-atom Ir-on- $\\mathbf{\\cdot}\\mathbf{Mg}\\mathbf{Al}_{2}\\mathbf{O}_{4}$ catalysts. Nat. Catal. 2, 149–156 (2019). \n8.\t Jones, J. et al. Thermally stable single-atom platinum-on-ceria catalysts via atom trapping. Science 353, 150–154 (2016). \n9.\t Back, S., Lim, J., Kim, N.-Y., Kim, Y.-H. & Jung, Y. Single-atom catalysts for $\\mathrm{CO}_{2}$ electroreduction with significant activity and selectivity improvements. Chem. Sci. 8, 1090–1096 (2017). \n10.\tDarby, M. T., Stamatakis, M., Michaelides, A. & Sykes, E. C. H. Lonely atoms with special gifts: breaking linear scaling relationships in heterogeneous catalysis with single-atom alloys. J. Phys. Chem. Lett. 9, 5636–5646 (2018). \n11.\tGani, T. Z. & Kulik, H. J. Understanding and breaking scaling relations in single-site catalysis: methane to methanol conversion by $\\mathrm{Fe^{\\mathrm{IV}}=}\\mathrm{O}$ . ACS Catal. 8, 975–986 (2018). \n12.\t Gu, J., Hsu, C.-S., Bai, L., Chen, H. M. & Hu, X. Atomically dispersed $\\mathrm{Fe}^{3+}$ sites catalyze efficient $\\mathrm{CO}_{2}$ electroreduction to CO. Science 364, 1091–1094 (2019). \n13.\tXiong, Y. et al. Single-atom Rh/N-doped carbon electrocatalyst for formic acid oxidation. Nat. Nanotechnol. 15, 390–397 (2020). \n14.\tZheng, T. et al. Large-scale and highly selective $\\mathrm{CO}_{2}$ electrocatalytic reduction on nickel single-atom catalyst. Joule 3, 265–278 (2019). \n15.\tMalta, G. et al. Identification of single-site gold catalysis in acetylene hydrochlorination. Science 355, 1399–1403 (2017). \n16.\tWu, J., Xiong, L., Zhao, B., Liu, M. & Huang, L. Densely populated single atom catalysts. Small Methods 4, 1900540 (2019). \n17.\tWang, L. et al. A sulfur-tethering synthesis strategy toward high-loading atomically dispersed noble metal catalysts. Sci. Adv. 5, eaax6322 (2019). \n18.\tGawande, M. B., Fornasiero, P. & Zbořil, R. Carbon-based single-atom catalysts for advanced applications. ACS Catal. 10, 2231–2259 (2020). \n19.\tBakandritsos, A. et al. Mixed-valence single-atom catalyst derived from functionalized graphene. Adv. Mater. 31, 1900323 (2019). \n20.\tZhang, Z. et al. Electrochemical deposition as a universal route for fabricating single-atom catalysts. Nat. Commun. 11, 1215 (2020). \n21.\tHe, X. et al. A versatile route to fabricate single atom catalysts with high chemoselectivity and regioselectivity in hydrogenation. Nat. Commun. 10, 3663 (2019). \n22.\tZhao, L. et al. Cascade anchoring strategy for general mass production of high-loading single-atomic metal-nitrogen catalysts. Nat. Commun. 10, 1278 (2019). \n23.\tFei, H. et al. General synthesis and definitive structural identification of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n24.\tQu, Y. et al. Ambient synthesis of single-atom catalysts from bulk metal via trapping of atoms by surface dangling bonds. Adv. Mater. 31, 1904496 (2019). \n25.\tLiu, K. et al. Strong metal-support interaction promoted scalable production of thermally stable single-atom catalysts. Nat. Commun. 11, 1263 (2020). \n26.\tZhu, Y. et al. A cocoon silk chemistry strategy to ultrathin N-doped carbon nanosheet with metal single-site catalysts. Nat. Commun. 9, 3861 (2018). \n27.\tJiang, K. et al. Highly selective oxygen reduction to hydrogen peroxide on transition metal single atom coordination. Nat. Commun. 10, 3997 (2019). \n28.\tDu, Z. et al. Cobalt in nitrogen-doped graphene as single-atom catalyst for high-sulfur content lithium–sulfur batteries. J. Am. Chem. Soc. 141, 3977–3985 (2019). \n29.\t Deng, D. et al. A single iron site confined in a graphene matrix for the catalytic oxidation of benzene at room temperature. Sci. Adv. 1, e1500462 (2015). \n30.\tJung, E. et al. Atomic-level tuning of Co–N–C catalyst for high-performance electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Nat. Mater. 19, 436–442 (2020). \n31.\tLiu, W. et al. Single-atom dispersed $\\scriptstyle\\mathrm{Co-N-C}$ catalyst: structure identification and performance for hydrogenative coupling of nitroarenes. Chem. Sci. 7, 5758–5764 (2016). \n32.\tWang, J. et al. Amino-functionalized $\\mathrm{Fe}_{3}\\mathrm{O}_{4}@{\\mathrm{SiO}}_{2}$ core-shell magnetic nanomaterial as a novel adsorbent for aqueous heavy metals removal. J. Colloid Interface Sci. 349, 293–299 (2010). \n33.\tChen, G. et al. Assembling carbon quantum dots to a layered carbon for high-density supercapacitor electrodes. Sci. Rep. 6, 19028 (2016). \n34.\tWang, L. et al. Gram-scale synthesis of single-crystalline graphene quantum dots with superior optical properties. Nat. Commun. 5, 5357 (2014). \n35.\tKumar, G. S. et al. Amino-functionalized graphene quantum dots: origin of tunable heterogeneous photoluminescence. Nanoscale 6, 3384–3391 (2014). \n36.\tAllahbakhsh, A. & Bahramian, A. R. Self-assembly of graphene quantum dots into hydrogels and cryogels: dynamic light scattering, UV–Vis spectroscopy and structural investigations. J. Mol. Liq. 265, 172–180 (2018). \n37.\tGelfond, N. et al. An XPS study of the composition of iridium films obtained by MO CVD. Surf. Sci. 275, 323–331 (1992). \n38.\tWang, G. et al. Selective growth of $\\mathrm{IrO}_{2}$ nanorods using metalorganic chemical vapor deposition. J. Mater. Chem. 16, 780–786 (2006). \n39.\tXiao, M. et al. A single-atom iridium heterogeneous catalyst in oxygen reduction reaction. Angew. Chem. Int. Ed. 131, 9742–9747 (2019). \n40.\tHall, S. C., Subramanian, V., Teeter, G. & Rambabu, B. Influence of metal–support interaction in $\\mathrm{Pt/C}$ on CO and methanol oxidation reactions. Solid State Ion. 175, 809–813 (2004). \n41.\tYang, H. B. et al. Atomically dispersed $\\mathrm{{Ni}(I)}$ as the active site for electrochemical $\\mathrm{CO}_{2}$ reduction. Nat. Energy 3, 140–147 (2018). \n42.\tJiang, K. et al. Transition-metal single atoms in a graphene shell as active centers for highly efficient artificial photosynthesis. Chem 3, 950–960 (2017). \n43.\tKoshy, D. et al. Understanding the origin of highly selective $\\mathrm{CO}_{2}$ electroreduction to CO on Ni,N-doped carbon catalysts. Angew. Chem. Int. Ed. 59, 4043–4050 (2020). \n44.\tZhang, G. et al. A general route via formamide condensation to prepare atomically dispersed metal–nitrogen–carbon electrocatalysts for energy technologies. Energy Environ. Sci. 12, 1317–1325 (2019). \n45.\tLiu, W. et al. A durable nickel single-atom catalyst for hydrogenation reactions and cellulose valorization under harsh conditions. Angew. Chem. Int. Ed. 130, 7189–7193 (2018). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. $\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 \n\n# Methods \n\nGQDs– $\\cdot\\mathbf{NH}_{2}$ synthesis. A modified molecular fusion route was employed to synthesize well-crystallized $\\mathrm{GQDs}{\\mathrm{-NH}_{2}}^{34}$ . Typically, 8 grams of pyrene (Sigma, purity ${>}98\\%$ ) was nitrated into trinitropyrene in 640 millilitres of concentrated ${\\mathrm{HNO}}_{3}$ ( $70\\%$ , Sigma) at $80^{\\circ}\\mathrm{C}$ under refluxing and stirring for $12\\mathrm{h}$ . After cooling to room temperature, the mixture was washed to neutral pH using deionized (DI) water $(18.2\\mathrm{M}\\Omega)$ by centrifuging. The resultant yellow 1,3,6-trinitropyrene was then dried under vacuum at room temperature. Next, 1.2 grams of dried 1,3,6-trinitropyrene powder were dispersed into a solution containing 220 millilitres of DI water and 20 millilitres of concentrated ammonia solution $30\\%$ , Sigma). The above mixture was ultrasonicated in ice water using a batch sonicator for 4 h. Sixty millilitres of the homogeneous suspension were transferred into a Teflon-lined autoclave (100 millilitres). The four autoclaves (total 240 millilitres mixture solution) were heated at $200^{\\circ}\\mathrm{C}$ for $10\\mathrm{{h}}$ . After natural cooling to room temperature, all the product-containing solution was filtered through a $0.22\\upmu\\mathrm{m}$ microporous membrane to remove insoluble carbon product and further concentrated to ${\\sim}90$ millilitres by rotation drying. The concentrated solution was dialysed in a dialysis bag (retained molecular weight, ${\\sim}12{\\mathrm{-}}14\\mathrm{kDa}$ , Innovating Science) for two days to remove contamination and unfused small molecules. The concentration of purified $\\mathrm{GQDs{-}N H_{2}}$ solution was ${\\sim}1$ milligram per millilitre. \n\nIr–N–C- $\\mathbf{\\sigma}\\cdot\\mathbf{{\\boldsymbol{x}}}$ synthesis. First, 1 gram of $\\mathrm{IrCl}_{3}{\\bullet}x\\mathrm{H}_{2}\\mathrm{O}$ (Alfa Aesar) was dissolved into 200 millilitres of DI water to prepare the $\\mathrm{IrCl}_{3}$ stock solution with a concentration of ${\\sim}5$ milligrams per millilitre. For the Ir–N–C-7 sample, 7 millilitres of $\\mathrm{IrCl}_{3}$ stock solution were added to ${\\sim}30$ millilitres of purified $\\mathrm{GQDs-NH}_{2}$ solution ( $_{\\sim30}$ milligrams of GQDs– $\\cdot\\mathrm{NH}_{2}$ ). Then, the mixture solution was sonicated in ice water for $15\\mathrm{min}$ , followed by being quickly frozen in liquid nitrogen. After freeze drying, the as-prepared aerogel-like powder was mixed with urea (VWR) with a mass ratio of 1 to 10 and further heated in a tube furnace to $500^{\\circ}\\mathrm{C}$ under a gas flow of $100\\mathrm{{sccm}}$ Ar (UHP, Airgas) within $^\\mathrm{1h}$ , and kept at the same temperature for another 2 h before cooling to room temperature. Finally, the Ir–N–C-7 powder was collected for further characterizations. For other Ir–N–C- $x$ catalyst syntheses, only the volume of $\\mathrm{IrCl}_{3}$ stock solution was changed; for example 1 millilitre of $\\mathrm{IrCl}_{3}$ stock solution was used to prepared $\\mathrm{Ir{-}N{-}C{-}1}$ catalyst. The nominal Ir loading was defined using following equation: M−ass(added)−+Ir (mg) ( ) × 100%, where Massadded–Ir and MassGQDs are the masses of the added Ir and the GQDs, respectively. \n\n$\\mathbf{Ir}\\mathbf{-GO-NH}_{2}\\mathbf{-}\\mathbf{\\mathcal{x}}$ synthesis. First, to prepare the nitrogen-doped graphene support $\\mathrm{(GO-NH_{2})}$ ), GO (purchased from CYG and used as received) was mixed with urea (VWR) with a mass ratio of 1 to 10, and further heated in a tube furnace to $500^{\\circ}\\mathrm{C}$ under a gas flow of 100 sccm Ar (UHP, Airgas) within $\\operatorname{1h}.$ , and then kept at the same temperature for another 2 h before cooling to room temperature. Then, Ir– ${\\mathrm{GO-NH}}_{2}{\\cdot}x$ was synthesized by following the same process as for Ir–N–C- $x$ catalyst using the GO– $\\mathrm{NH}_{2}$ as the support instead of $\\mathrm{GQDs{-}N H_{2}}$ . \n\nPt–N–C-6 synthesis. First, 1 gram of $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ (Sigma) was dissolved into 200 millilitres of DI water to prepare the $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ stock solution with a concentration of 5 milligrams per millilitre. Then, 6 millilitres of $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ stock solution was added to ${\\sim}30$ millilitres of purified $\\mathrm{GQDs{-}N H_{2}}$ solution $_{\\sim30}$ milligrams of $\\mathrm{GQDs-NH}_{2})$ ), followed by sonication in ice water for $15\\mathrm{min}$ . The above solution was freeze dried and mixed with urea (VWR) with a mass ratio of 1 to 10, and further heated in a tube furnace to $500^{\\circ}\\mathrm{C}$ under a gas flow of $100\\mathrm{{sccm}}$ Ar (UHP, Airgas) within $2\\mathrm{h}$ , and then kept at the same temperature for another 1 h before cooling to room temperature. Finally, the Pt–N–C-6 powder was collected for further characterization. The nominal $\\mathrm{Pt}$ loading was defined using the fmolalsoswoifntgheqaudadtieodn:P $\\frac{\\mathrm{Mass}_{\\mathrm{added-pt}}\\ (\\mathrm{mg})}{\\mathrm{Mass}_{\\mathrm{added-pt}}(\\mathrm{mg})+\\mathrm{Mass}_{\\mathrm{GQDs}}\\ (\\mathrm{mg})}\\ \\times\\ 100\\%$ , where $\\mathrm{Mass}_{\\mathrm{added-Pt}}$ is \n\nNi–N–C-x synthesis. First, 1 gram of $\\mathrm{Ni(NO_{3})_{2}{\\bullet}6H_{2}O}$ (Sigma) was dissolved into 200 millilitres of DI water to prepare the $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}$ stock solution with a concentration of ${\\sim}5$ milligrams per millilitre. Then, for the Ni–N–C sample with $15\\mathrm{wt\\%}$ nickel, 3 millilitres of $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}$ stock solution was added to ${\\sim}30$ millilitres of purified GQDs– $\\cdot\\mathrm{NH}_{2}$ solution $_{\\sim30}$ milligrams of $\\mathrm{GQDs-NH}_{2};$ ), followed by sonication in ice water for $15\\mathrm{min}$ . The above solution was freeze dried and mixed with urea (VWR) with a mass ratio of 1 to 10 and further heated in a tube furnace to $750^{\\circ}\\mathrm{C}$ under a gas flow of $100\\mathrm{sccm}$ Ar (UHP, Airgas) within $\\ensuremath{1\\mathrm{h}}$ and then kept at the same temperature for another 1 h before cooling to room temperature. Finally, the as-prepared powder was collected for further characterization. To synthesize the Ni–N–C- $x$ catalysts for the electrochemical $\\mathrm{CO}_{2}$ reduction test, only 30 milligrams of GQDs– $\\cdot\\mathrm{NH}_{2}$ was replaced using 30 milligrams of GQDs–OH. To prepare GQDs– OH, all the processes are the same as in the preparation of $\\mathrm{GQDs}{\\mathrm{-NH}}_{2}$ except 240 millilitres of $0.2\\mathrm{MNaOH}$ solution was used to replace the previous ammonia solution (220 millilitres of DI plus 20 millilitres of concentrated ammonia). This is because the heavily nitrogen-doped carbon matrix will also promote the hydrogen evolution reaction. The as-prepared Ni–N–C-1.5 $\\left({\\sim}7.5\\mathrm{wt\\%\\Ni}\\right)$ ) and Ni–N–C-3 $\\left({\\sim}15\\mathrm{wt\\%\\Ni}\\right.$ ) single-atom catalysts from GQDs–OH were also verified using STEM. \n\nCharacterization. XPS was obtained with a PHI Quantera spectrometer, using a monochromatic Al Kα radiation $(1,486.6\\mathrm{eV})$ and a low-energy flood gun as neutralizer. All XPS spectra were calibrated by shifting the detected carbon C 1s peak to $284.6\\mathrm{eV}.$ X-ray diffraction was performed on a Rigaku SmartLab X-ray diffraction platform. Absorption and PL spectra were measured with Agilent Cary-60 ultraviolet–visible spectrometer and Cary Eclipse fluorometer, respectively. TGA was performed on a Q-600 Simultaneous TGA/DSC from TA Instruments. SEM was performed on an FEI Helios NanoLab 660 DualBeam system and an FEI Quanta 400 field emission scanning electron microscope. Inductively coupled plasma atomic emission spectroscopy results were collected using an Optima 8300 spectrometer. The images of the GQDs were taken on a JEOL 2100F TEM instrument. HAADF-STEM images and EELS point spectra of the Ni–N–C samples were acquired on a Nion Ultra STEM U100 operated at $60\\mathrm{keV}$ and equipped with a Gatan Enfina spectrometer. Simultaneous EELS and EDS point spectra of $\\mathrm{Pt-N-C}$ and Ir–N–C were acquired on a JEOL NEOARM operated at $60\\mathrm{kV}$ and equipped with dual $\\scriptstyle100\\mathrm{mm}^{2}$ silicon drift detectors and a Gatan Quantum spectrometer. X-ray absorption spectroscopy spectra, including XANES and EXAFS of the $\\mathrm{NiK}$ edge and Ir $\\mathrm{L}_{3}$ edge, were acquired at the Soft X-ray Microcharacterization Beamline and BioXAS-Spectroscopy Beamline at Canadian Light Source. Total scattering data were collected at the Brockhouse High Energy Wiggler Beamline of the Canadian Light Source using wavelength $\\lambda{=}0.21062\\bar{\\mathrm{A}}$ radiation. The samples were loaded into $0.9\\mathrm{mm}$ Kapton capillaries. An empty Kapton tube was measured for background subtraction. Pair distribution functions were generated with GSAS-II software using a $Q_{\\mathrm{max}}$ of $21\\mathring{\\mathrm{A}}^{-1}$ , where $Q_{\\mathrm{max}}=4\\pi\\mathrm{sin}(\\theta)/\\lambda)$ . \n\nElectrochemical test. All the electrochemical measurements were run at $25^{\\circ}\\mathrm{C}$ A BioLogic VMP3 workstation was employed to record the electrochemical response. Typically, $32\\mathrm{mg}$ of as-prepared Ni–N–C-3 (or Ni–N–C-1.5) powder and $8\\mathrm{mg}$ of carbon black (Vulcan XC-72, Fuel Cell Store) were mixed with $4\\mathrm{ml}$ of isopropanol and $160\\upmu\\mathrm{l}$ of alkaline ionomer binder solution (Dioxide Materials, $5\\%$ ) and sonicated for $10\\mathrm{min}$ to obtain a homogeneous ink. Then, all the ink was air-brushed onto the $5\\times5\\mathrm{cm}^{2}$ Sigracet 35 BC (Fuel Cell Store) gas diffusion layer electrode. Then $4\\mathrm{cm}^{2}$ of the catalyst-coated gas diffusion layer electrode was cut to be used as a $\\mathrm{CO}_{2}$ reduction reaction cathode with a catalyst loading of $\\sim0.5\\mathrm{mgcm}^{-2}$ . An $\\mathrm{IrO}_{2}$ electrode (Dioxide Materials) was used as an oxygen evolution reaction anode. A polystyrene methyl methylimidazolium chloride anion-exchange membrane (PSMIM, Dioxide Materials) was sandwiched by the two gas diffusion layer electrodes to separate the chambers. On the cathode side, a titanium gas flow channel supplied $30\\mathrm{sccm}$ humidified $\\mathrm{CO}_{2}$ while the anode was circulated with $0.5\\mathrm{M}$ KOH electrolyte at $3\\mathrm{ml}\\mathrm{min}^{-1}$ flow rate. The cell voltages in Fig. $4\\mathrm{g}$ and H were recorded with $85\\%$ iR-correction (current $\\times$ resistance compensation). \n\nIn order to quantify the gas products during electrolysis, $\\mathrm{CO}_{2}$ gas (Airgas, $99.995\\%$ ) was delivered into the cathodic compartment at a rate of $30.0\\mathrm{sccm}$ and vented into a gas chromatograph (Shimadzu GC-2014) equipped with a combination of molecular sieve 5A, HayeSep $\\scriptstyle\\mathrm{Q},$ HayeSep T and HayeSep N columns. A thermal conductivity detector was mainly used to quantify $\\mathrm{H}_{2}$ concentration, and a flame ionization detector with a methanizer was used to quantitatively analyse CO content and/or any other alkane species. The partial current density for a given product was calculated as follows: \n\n$$\nj_{i}=x_{i}\\times\\nu\\times\\frac{n_{i}F p_{\\mathrm{o}}}{R T}\\times(\\mathrm{electrodearea})^{-1}\n$$ \n\nwhere $x_{i}$ is the volume fraction of a certain product determined by online gas chromatograph referenced to calibration curves from the standard gas sample (Airgas), $\\nu$ is the flow rate of $30.0\\mathrm{sccm}$ , $n_{i}$ is the number of electrons involved, $p_{\\mathrm{{o}}}{=}101.3\\mathrm{{kPa}}$ , $F$ is the Faradaic constant, the temperature $\\scriptstyle{T=298\\mathrm{K}}$ and $R$ is the gas constant. The corresponding Faradaic efficiency at each potential is calculated by $\\begin{array}{r}{\\mathrm{FE}=\\frac{j_{i}}{j_{\\mathrm{total}}}\\times100\\%}\\end{array}$ where $j_{\\mathrm{total}}$ is the total current density. \n\n# Data availability \n\nThe authors declare that all of the data supporting the findings of this study are available within the paper and the Supplementary Information, and also from the corresponding authors upon reasonable request. Source data are provided with this paper. \n\n# Acknowledgements \n\nThis work was supported by Rice University and the Welch Foundation Research Grant C-2051-20200401. H.W. is a CIFAR Azrieli Global Scholar in the Bio-inspired Solar Energy Program. C.X. acknowledges support from a J. Evans Attwell-Welch Postdoctoral Fellowship. C.X. acknowledges the University of Electronic Science and Technology of China for startup funding (A1098531023601264). This work was performed in part at the Shared Equipment Authority at Rice University. H.N.A. acknowledges support from King Abdullah University of Science and Technology. XAS and PDF measurements were conducted at the Canadian Light Source, which is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), National Research Council Canada (NRC) and University of Saskatchewan. Electron microscopy was conducted at the \n\nCenter for Nanophase Materials Sciences, which is a U.S. Department of Energy Office of Science User Facility. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Author contributions \n\nThe project was conceptualized by C.X. and H.W. and supervised by H.W. and Y.H. Catalysts were synthesized by C.X. with the help of Y.Q.; C.X., Y.Q. and P.Z. conducted the catalytic tests and the related data processing. Materials characterization and analysis were performed by C.X. with the help of P.Z., Y.X., X.Z., Z.W., D.Z., P.L., D.A.C. and J.Y.K. The XAS test and analysis was performed by M.S., E.H., P.C. and Y.H. PDF was performed by G.K.; H.N.A provided suggestions for this study. C.X. and H.W. wrote the manuscript with input from all the authors. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41557-021-00734-x. Correspondence and requests for materials should be addressed to C.X., Y.H. or H.W. Peer review information Nature Chemistry thanks Aiqin Wang, Yuen Wu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at www.nature.com/reprints. " + }, + { + "id": "10.1038_s41586-021-03264-1", + "DOI": "10.1038/s41586-021-03264-1", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03264-1", + "Relative Dir Path": "mds/10.1038_s41586-021-03264-1", + "Article Title": "Thermal-expansion offset for high-performance fuel cell cathodes", + "Authors": "Zhang, Y; Chen, B; Guan, DQ; Xu, MG; Ran, R; Ni, M; Zhou, W; O'Hayre, R; Shao, ZP", + "Source Title": "NATURE", + "Abstract": "One challenge for the commercial development of solid oxide fuel cells as efficient energy-conversion devices isthermo-mechanical instability. Large internal-strain gradients caused by the mismatch in thermal expansion behaviour between different fuel cell components are the main cause of this instability, which can lead to cell degradation, delamination or fracture(1-4). Here we demonstrate an approach to realizing full thermo-mechanical compatibility between the cathode and other cell components by introducing a thermal-expansion offset. We use reactive sintering to combine a cobalt-based perovskite with high electrochemical activity and large thermal-expansion coefficient with a negative-thermal-expansion material, thus forming a composite electrode with a thermal-expansion behaviour that is well matched to that of the electrolyte. A new interphase is formed because of the limited reaction between the two materials in the composite during the calcination process, which also creates A-site deficiencies in the perovskite. As a result, the composite shows both high activity and excellent stability. The introduction of reactive negative-thermal-expansion components may provide a general strategy for the development of fully compatible and highly active electrodes for solid oxide fuel cells.", + "Times Cited, WoS Core": 436, + "Times Cited, All Databases": 460, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000627422700012", + "Markdown": "# Article \n\n# Thermal-expansion offset for high-performance fuel cell cathodes \n\nhttps://doi.org/10.1038/s41586-021-03264-1 \n\nReceived: 28 March 2020 \n\nAccepted: 19 January 2021 \n\nPublished online: 10 March 2021 Check for updates \n\nYuan Zhang1, Bin Chen2,3, Daqin Guan1, Meigui Xu1, Ran Ran1, Meng Ni2, Wei Zhou1 ✉, Ryan O’Hayre4 & Zongping Shao1,5 ✉ \n\nOne challenge for the commercial development of solid oxide fuel cells as efficient energy-conversion devices is thermo-mechanical instability. Large internal-strain gradients caused by the mismatch in thermal expansion behaviour between different fuel cell components are the main cause of this instability, which can lead to cell degradation, delamination or fracture1–4. Here we demonstrate an approach to realizing full thermo-mechanical compatibility between the cathode and other cell components by introducing a thermal-expansion offset. We use reactive sintering to combine a cobalt-based perovskite with high electrochemical activity and large thermal-expansion coefficient with a negative-thermal-expansion material, thus forming a composite electrode with a thermal-expansion behaviour that is well matched to that of the electrolyte. A new interphase is formed because of the limited reaction between the two materials in the composite during the calcination process, which also creates A-site deficiencies in the perovskite. As a result, the composite shows both high activity and excellent stability. The introduction of reactive negative-thermal-expansion components may provide a general strategy for the development of fully compatible and highly active electrodes for solid oxide fuel cells. \n\nThe most popular cathode materials for intermediate-temperature solid oxide fuel cells (SOFCs) are cobalt-containing perovskites5,6, including $\\mathsf{S m}_{0.5}\\mathsf{S r}_{0.5}\\mathsf{C o O}_{3-\\delta}$ (ref. 7), $(\\mathsf{L a},\\mathsf{S r})(\\mathsf{C o},\\mathsf{F e})\\mathsf{O}_{3-\\delta}$ (refs. 8,9), $\\mathsf{B a}_{0.5}\\mathsf{S r}_{0.5}\\mathsf{C o}_{0.8}\\mathsf{F e}_{0.2}\\mathsf{O}_{3-\\delta}(\\mathsf{B S C F})^{1,10}$ and $\\mathsf{S r N b}_{0.1}\\mathsf{C o}_{0.9}\\mathsf{O}_{3-\\delta}(\\mathsf{S N C})^{11,12}$ , owing to their superior oxygen-reduction activity and high conductivity. However, their thermal-expansion coefficients (TECs) are very high (typically in the range $20{-}25\\times10^{-6}\\mathsf{K}^{-1})^{13-16}$ , which can be generally ascribed to the thermal reduction of cobalt ions, the associated phase transitions and the thermally activated transition in the spin state of the $\\mathbf{Co}d$ -orbital electrons17. Most critically, these TECs are considerably larger than that of common SOFC electrolytes, such as samaria-doped ceria (SDC) and yttria-stabilized zirconia (YSZ) $(11.2–12.3\\times10^{-6}\\mathsf{K}^{-1})^{18,19}$ . \n\nTo reduce the TEC value of cobalt-based electrodes, considerable efforts have been made, such as lattice doping with transition metals containing $d^{0}$ orbitals20, compositing the perovskite electrode material with electrolyte material21, introducing A-site deficiency into the perovskite13 or pursuing in situ formation of a thermal-expansion-inhibiting phase22. However, most of these strategies can reduce the TEC value of cobalt-based electrodes to a very modest extent, not fully matching that of the electrolyte, and may cause negative side-effects on oxygen-reduction reaction (ORR) activity17. It is imperative to search for a strategy that provide substantial reduction in thermal expansion (by a level of about $10^{-6}\\mathsf{K}^{-1},$ ) without imposing negative effects, or even introducing positive effects, on ORR activity. \n\nHere, we demonstrate how compositing a high-TEC cobalt-based perovskite with an appropriately chosen negative-thermal-expansion (NTE) material makes it possible to use their offsetting behaviours to tune the overall TEC of the composite electrode and to mediate, or even fully eliminate, the TEC mismatch with the electrolyte. Several solid-state NTE materials are also known to demonstrate contraction behaviour upon heating over a certain range of temperatures23–25. We choose $\\mathsf{Y}_{2}\\mathsf{W}_{3}\\mathsf{O}_{12}$ oxide (YWO; TEC of about $-7\\times10^{-6}\\mathsf{K}^{-1}$ from room temperature to $1{,}100^{\\circ}\\mathrm{C})$ as the NTE candidate to composite with an SNC electrode as the positive thermal expansion candidate (TEC of $19{-}24\\times10^{-6}\\mathrm{K^{-1}}$ from room temperature to $800^{\\circ}\\mathrm{C})$ to demonstrate this TEC offset strategy17,26–29. We further harness a reactive compositing concept to ensure strong interaction between these two phases to strengthen the thermal-expansion offset effect. Specifically, a beneficial interfacial phase reaction between SNC and YWO is induced, resulting in the exsolution of strontium from the bulk phase of the perovskite, with the consequent formation of a $\\mathsf{S r W O}_{4}$ (SWO) interphase. This process creates also A-site cation deficiencies in the perovskite phase (that is, formation of A-site-deficient $\\mathsf{S r}_{x}(\\Upsilon_{y}(\\mathsf{N b}_{0.1}\\mathsf{C o}_{0.9})_{1-y})\\d\\mathbf{O}_{3-\\delta};$ SYNC). As a result, the as-obtained SYNC composite (c-SYNC) electrode shows good SOFC electrochemical performance and outstanding thermo-mechanical stability. The synergetic effects of the reduced TEC, perovskite phase optimization and thermo-mechanical stability collaboratively contribute to the excellent electrochemical performance of this SOFC composite cathode and demonstrate a new pathway for future SOFC electrode design. \n\n![](images/5fffb3ed552ccdc43778390367397bcbe24d0dc65785d638556369bb4f45640b.jpg) \nFig. 1 | Properties and formation mechanism of c-SYNC. a, Rietveld refinement of XRD plot of reacted c-SYNC composite powder with measured data (black dots), simulated (red line; Ycalc, calculated profile) and difference curves (green line). b, Schematic illustration of the formation mechanism of $c$ -SYNC. c, The XPS spectra of the Sr 3d orbital for c-SYNC and ‘pristine’ SNC/YWO before calcination. d, HRTEM images of the c-SYNC electrode. \ne–g, HRTEM images of interfaces of the YWO, SWO and SYNC phases. h, SEAD pattern of the [110] zone axis of the SYNC phase in f. i, STEM-HAADF of c-SYNC, with each phase marked by dashed lines. j, Corresponding element mapping of Sr, W (top) and Co (bottom) for i. k, l, STEM ${\\bf\\Pi}({\\bf k})$ and corresponding FFT (l) images of the SWO phase in i. a.u., arbitrary units. \n\n# Results \n\n# Evolution of structure and properties \n\nOwing to the large difference in TEC between YWO and SNC, delamination between the two phases occurs easily during thermal cycling if they are connected by a weak physical contact. A chemical reaction between the two oxides will build a strong connection between the different phases, ensuring sound mechanical integrity. The phase reaction behaviour between YWO and SNC is examined by a solid-state reaction in powder form. The X-ray diffraction (XRD) patterns of pure SNC, pure YWO and an SNC/YWO composite $20\\mathrm{wt\\%}$ YWO) after thermal treatment at $800^{\\circ}\\mathrm{C}$ in air for $2\\mathfrak{h}$ are shown in Fig. 1a and Supplementary Fig. 1. After the calcination, a secondary phase of SWO (JCPDF#85-0587) is detected. This finding suggests that Sr is exsolved from SNC, reacts with the W in YWO to form SWO, and creates A-site cation deficiencies in the SNC perovskite oxide lattice. Previous studies have shown that the in situ exsolution phase has advantages such as promoting catalytic activity and increasing the effective catalytic area30,31. The (110) peak in the XRD pattern of samples (Supplementary Fig. 2) also supports this claim by showing a shift to lower angles, which is consistent with lattice volume expansion due to the creation of A-site cation deficiency32,33. Although no characteristic peak of YWO remains, we confirm the persistence of the YWO phase by other means, as described in the following section. Meanwhile, the presence of B-site Y in the SNC phase after the calcination (in other words, the formation of SYNC) is supported by the refinement results (Fig. 1a, with details in Supplementary Information section 1 and Supplementary Tables 1–5). In summary, we find that after the calcination of the YWO/SNC physical mixture, the as-obtained $c$ -SYNC is a composite of newly formed interfacial SWO, along with YWO and SYNC. The combination of A-site cation deficiency and low-valence $(\\Upsilon^{3+})$ doping of the SNC is expected to introduce additional oxygen vacancies, thus benefiting the ORR reactivity34. \n\nTo elucidate the chemical state of B-site elements in the perovskite after the Y doping, the valence states of Co and Nb in the c-SYNC sample are studied by X-ray photoelectron spectroscopy (XPS) analysis. As shown in Supplementary Fig. 3a, $\\mathbf{b}^{35}$ , identical peak profiles of Co 2p and Nb 3d are observed for both the raw SNC/YWO composite and $c$ -SYNC, indicating scarcely changed chemical states for both Co and Nb. In other words, the substitution of $\\Upsilon^{3+}$ appears to have little effect on the Co and Nb cation valance states. By contrast, considerable differences in the Sr 3d peak profiles are observed between SNC/YWO and c-SYNC (Fig. 1b), from which we differentiate the Sr $3d_{5/2}$ and $3d_{3/2}$ peaks to two different species of Sr, namely, $\\mathsf{S r}_{\\mathsf{l a t t i c e}}$ (low binding energy) and Srsurface (high binding energy)36. The ratio of $\\mathsf{S r}_{\\mathsf{s u r f a c e}}$ to $\\mathsf{S r}_{\\mathsf{l a t t i c e}}$ clearly increases after the calcination of SNC with YWO. We attribute this increase to the formation of SWO, which is consistent with the XRD results. The Sr cation from the A-site of SNC reacts with YWO to form SWO at the interface between YWO and SNC. Meanwhile, Y diffuses into the B-site of the SNC to form a stable SYNC perovskite structure with a residual YWO phase (as well as the SWO) retained in the final $c$ -SYNC composite system, as illustrated in Fig. 1c. \n\nThe morphology and phase structure of the $c$ -SYNC composite electrode—prepared by focused ion beam milling in a scanning electron \n\n# Article \n\nmicroscope (FIB-SEM), as shown in Supplementary Fig. 4a–d—are also verified by high-resolution transmission electron microscopy (HRTEM), shown in Fig. 1d–h and Supplementary Fig. 4e. The co-existence of YWO, SWO and SYNC phases can be clearly observed in a lattice spacing measurement (Fig. 1e–g) from a selected region of Fig. 1d. Specifically, the presence of the SYNC perovskite phase is well supported by the observed $d(101)=3.43{\\mathring{\\mathrm{A}}}$ in Fig. 1e and $\\overset{\\cdot}{d}(110)=2.71\\overset{\\circ}{\\mathrm{A}}$ in Fig. 1f, of which the corresponding selected-area electron diffraction pattern is shown in Fig. 1h, demonstrating the superlattice structure of the SYNC phase from the [110] axis, which is in accordance with the XRD refinement results. \n\nTo confirm the morphology, we further transferred a pellet sample of c-SYNC to a spherical-aberration-corrected scanning transmission electron microscope high-angle annular dark-field (STEM-HAADF) for higher-resolution imaging (as shown in Fig. 1i). Using the corresponding element mapping images (Fig. 1j), the phase distribution is identified (dashed lines in Fig. 1i). In addition, we can clearly observe the formation of an intergranular SWO phase at the boundaries of YWO and SYNC, which is verified by the lattice spacing $d(101)=4.82\\mathring{\\mathrm{A}}$ of SWO (Fig. 1k) and the corresponding fast Fourier transform (FFT; Fig. 1l). More morphology images are shown in Supplementary Fig. 4b, c. By comparing the SEM images of the SNC and $c$ -SYNC particles/electrodes (Supplementary Fig. 5), it can be found that the particle size of c-SYNC is much smaller than that of SNC, consistent with the Brunauer–Emmett–Teller specific surface area measurements of the c-SYNC composite and SNC $(2.8\\mathsf{m}^{2}\\mathsf{g}^{-1}$ versus $\\mathbf{1.6\\:m^{2}\\:g^{-1}}$ ; Supplementary Fig. 6), as well as the crystallite sizes estimated by the Scherrer equation (41 nm versus $63\\mathsf{n m}$ ). \n\nIn addition, we deconvolute the O 1s XPS spectra of SNC and c-SYNC and compare their thermogravimetric analysis profiles (Supplementary Information section 2.2, Supplementary Figs. 7, 8, Supplementary Table 6), finding that SYNC has more weight loss than SNC, and thus more oxygen vacancies37. This could be seen as an indication of good ORR activity of the SYNC phase, and thus of the overall $c$ -SYNC. \n\nGood chemical and thermo-mechanical compatibility are also of great importance to SOFC operation34. The structural stability of $c$ -SYNC powder is certified by in situ high-temperature XRD characterization from room temperature to $750^{\\circ}\\mathrm{C}$ in ambient air (Supplementary Fig. 9a). Supplementary Fig. 9b shows the reaction and phase transformation behaviour of the SNC/YWO composite, confirming the formation of the SWO phase at $800^{\\circ}\\mathrm{C}$ , with subsequent formation of cubic $\\mathsf{S r}_{2}\\mathsf{C o W O}_{6}$ (JCPDF#74-2470) above $1,000^{\\circ}\\mathsf{C}$ . Considering that the cathode layer should be fired onto the electrolyte surface at increased temperature to ensure sufficient mechanical strength and adhesion, the phase reaction between them at high temperature needs to be evaluated. The XRD patterns of a powder mixture of SDC and SNC (weight ratio 3:7) treated at $800^{\\circ}\\mathrm{C}$ are presented in Supplementary Fig. 10. The small additional peaks observed indicate the phase reaction (generally Sr segregation from SNC)38. However, there are no additional peaks observed in the SDC/c-SYNC counterpart. The improved chemical stability could further enhance the durability of $c$ -SYNC as a cathode material for SDC electrolyte-based cells. \n\nRegarding the thermo-mechanical compatibility between the cathode and the electrolyte, a low TEC mismatch reduces the delamination risk of the cathode during fabrication and also upon subsequent device operation, especially during thermal cycling. However, simply doping certain elements or compositing with the electrolyte phase cannot sufficiently reduce the TEC of classical Co-based perovskite cathodes13,39. Thus, compositing with an NTE material can be more effective. \n\nTo verify this, the thermal expansion behaviour of both pure SNC and the c-SYNC composite is measured via dilatometry at $100{-}800^{\\circ}\\mathrm{C}$ (Fig. 2a) using dense, sintered, column-shaped specimens prepared by spark plasma sintering. At the temperature range $100{-}800^{\\circ}\\mathrm{C}$ , the overall average TEC of c-SYNC $(12.9\\times10^{-6}\\mathsf{K}^{-1})$ closely matches that of the SDC electrolyte (about $12.3\\times10^{-6}\\mathsf{K}^{-1})$ and is much smaller than that of pure SNC (about $20.5\\times10^{-6}\\mathsf{K}^{-1})$ and other cobalt-containing perovskites (Supplementary Table 7). Moreover, the TEC of the c-SYNC composite shows much less temperature-dependent variability. At higher temperatures $(550-800^{\\circ}\\mathrm{C})$ , the TEC of SNC increases substantially to $-28.1\\times10^{-6}\\mathsf{K}^{-1}$ , whereas the TEC of $\\dot{\\boldsymbol{c}}$ -SYNC increases slightly (to about $14.8\\times10^{-6}\\mathsf{K}^{-1})$ . We can conclude that $c$ -SYNC is therefore a good candidate for a durable cathode material because of its low and stable TEC behaviour in the working temperature range. \n\nTo unveil the role of exsolution and two-phase composting in improving the thermal stability, we design a control group with varied ratios of SWO (or YWO) to SNC to study the contributory effects of SWO (TEC of $9.2\\times10^{-6}\\mathsf{K}^{-1})$ and YWO on reducing the TEC. From Fig. 2b and Supplementary Fig. 11a, b, it is clear that the addition of SWO does not reduce the TECs of the SWO-SNC composite markedly (that is, it cannot fully match the TEC of SDC, about $12.3\\times10^{-6}\\mathsf{K}^{-1},$ . Likewise, the TEC of the SYNC phase (Fig. 2b, Supplementary Fig. 11c) is also very close to that of pristine SNC, so no mitigation effect can be expected. Therefore, it is clear that the mitigated TEC of the composition is mainly caused by the YWO phase, rather than the SWO exsolution or the newly formed SYNC. \n\nAdditionally, the thermal expansion behaviour of SNC/YWO composites with different YWO mass ratios is investigated and compared with values predicted from several theoretical models, as shown in Fig. 2c (model formulations in Supplementary Information section 3, Supplementary Table 8). The measured TECs are lower than the values predicted by either a simple first-order rule-of-mixtures model (ROM) or by the well established Turner and Kerner models40. The discrepancies between the experimental data and the model predictions indicate the existence of unaccounted reinforcement factors that may decrease the TEC of c-SYNC, given that the theoretical models generally assume perfectly dense samples, isolated YWO particles and no interfacial mechanical interactions. Although the discrepancy is small for the ROM model, we conjecture that the mechanical linking effect due to the in situ generated interfacial phase SWO could create additional constraints, forming interconnections that mitigate the expansion of the composite. In addition, the residual porosity could also serve to release thermal strain during heating, thereby reducing the measured value of TEC41,42. \n\n# Electrochemical evaluation of the c-SYNC composite \n\nTo evaluate the activity and effectiveness of the $c$ -SYNC composite as an oxygen-reduction electrode (ORE), electrochemical impedance spectroscopy (EIS) measurements of c-SYNC|SDC $|c\\rrangle$ -SYNC symmetrical cells are performed under open-circuit conditions from 500 to $700^{\\circ}\\mathrm{C}$ in air. Figure 2d summarizes the Arrhenius plots of the area-specific resistance (ASR; noted as $R_{\\mathfrak{p}}^{\\mathrm{~\\cdot~}}$ ) for the $c$ -SYNC electrodes fired at 800, 900 and $1{,}000^{\\circ}\\mathsf{C}$ . The electrode fired at $800^{\\circ}\\mathrm{C}$ demonstrates much lower $R_{\\mathfrak{p}}$ than the others owing to less electrode coarsening and phase transformations, as previously revealed by our XRD investigations. Therefore, the $800^{\\circ}\\mathrm{C}$ firing temperature is used for all subsequent $c$ -SYNC and SNC electrode investigations. \n\nThe c-SYNC electrode also demonstrates consistently lower polarization resistance at all temperatures (as shown in Fig. 2e and Supplementary Fig. 12a), and its ORR activity is rate-determined by the surface oxygen transport according to the change of ASR at varied oxygen partial pressure (Supplementary Information section 2.3, Supplementary Figs. 12b, c, 13). For example, the $R_{\\mathfrak{p}}$ value of the $c$ -SYNC electrode is only $0.063\\Omega\\mathrm{cm}^{2}$ at $600^{\\circ}\\mathrm{C}$ , which is appreciably lower than that of most well known OREs, as shown in Fig. 2f, which summarizes the $R_{\\mathfrak{p}}$ values of $\\boldsymbol{c}$ -SYNC (at $600^{\\circ}\\mathrm{C},$ ) versus the TEC values of popular perovskite-based OREs for SOFCs (see Supplementary Information section 4 for references). The $c$ -SYNC electrode demonstrates outstanding ORR activity and the lowest TEC value reported so far. Considering the substantial amounts of YWO and SWO present in the composite, which have limited oxygen vacancy content, as shown by thermogravimetric and XPS investigations, we conjecture that the high ORR activity of c-SYNC can be associated with the A-site deficiency of the SYNC phase and the resulting high oxygen vacancy concentration present in this phase. In addition, we test the ${\\mathsf{C O}}_{2}$ -tolerance of the electrodes; the results in Supplementary Information section 2.4 (including Supplementary Fig. 14) indicate that $c$ -SYNC shows higher $\\mathbf{CO}_{2}$ tolerance, which could be attributed to the high acidity of the YWO additive and the presence of the SWO surface phase. \n\n![](images/5d0e240942d5a0f4eedcda8f65a575bec782d2932098bb2033c0d05bc218ce80.jpg) \nFig. 2 | Thermal-expansion behaviour of c-SYNC and electrochemical performance. a, Thermal-expansion curves of dense c-SYNC and SNC bar specimens from 100 to $800^{\\circ}\\mathrm{C}$ in air. b, Measured TECs of SNC, SYNC, $x w t\\%$ SWO-SNC and x wt% YWO-SNC composition, with mass percentage x varied from 0 to 100. c, Measured TECs of c-SYNC with varied weight fractions of YWO from 0 to $50\\mathrm{wt\\%}$ versus theoretical predictions based on the rule of mixtures, Turner and Kerner models. d, Arrhenius plots of polarization resistance for $c$ -SYNC electrodes fired at 800, 900 and $\\scriptstyle\\lfloor,000^{\\circ}\\mathsf C$ . e, Impedance spectroscopy of c-SYNC electrodes (fired at $800^{\\circ}\\mathbf{C},$ ) measured at 500, 600 and $650^{\\circ}\\mathrm{C}$ . f, Summary diagram for $R_{\\mathfrak{p}}$ versus TEC for various outstanding ORE materials at \n$600^{\\circ}\\mathrm{C}$ . The error bars are defined as the diversity in the impedance results obtained from different sources; see Supplementary Information section 4 for references. g, ASR values for $c$ -SYNC- and SNC-based symmetric cells as a function of electrode thickness, measured in air at $600^{\\circ}\\mathrm{C}$ . The error bars are defined as the deviation of the results obtained with different test equipment and fabrication processes. h, $R_{\\mathfrak{p}}$ of $40{\\cdot}{\\upmu}{\\m}$ -thick $c$ -SYNC and SNC symmetric cells measured for $200\\mathsf{h}$ in air at $600^{\\circ}\\mathrm{C}.\\mathbf{i},$ , EIS plots of c-SYNC and SNC electrodes before and after the durability test. $E_{\\mathrm{a}}$ is the activation energy; $Z^{\\prime}$ and $Z^{\\prime\\prime}$ denote the real and imaginary part of the impedance, respectively. \n\n# Thermo-mechanical compatibility \n\nNext, we assess the thermo-mechanical stability of the $c$ -SYNC electrode, which ought to outperform the singe-phase SNC electrode owing to its better-matched TEC with the electrolyte. One advantage of improved thermo-mechanical compatibility is that thicker (that is, up to the optimal thickness of $40\\upmu\\mathrm{m}$ suggested by a detailed analysis43), higher-performing SOFC cathodes can be successfully fabricated, thus providing more ORR catalytic sites and a higher tolerance to cathode poisoning. \n\nTo study this effect, the electrode thickness (individual side) of SNC and $c$ -SYNC symmetric cells is varied from 5 to $40\\upmu\\mathrm{m}$ in increments of ${5}\\upmu\\mathrm{m}$ in the coating process. As shown in Fig. 2g and Supplementary Fig. 15, we find that the optimal ASR value is $0.041\\Omega\\mathrm{cm}^{2}(600^{\\circ}\\mathrm{C})$ at a thickness of $35\\upmu\\mathrm{m}$ , a reduction of about $60\\%$ compared to the initial $0.104\\Omega\\mathrm{cm}^{2}$ at ${5}\\upmu\\mathrm{m}$ . This clearly proves the effectiveness of increasing electrode thickness to further enhance performance when the TECs of the ORE and electrolyte are well matched. By contrast, the ASR values for the SNC-based cells increase from 0.059 to $0.24\\Omega\\mathrm{cm}^{2}\\mathrm{a}$ s the electrode thickness increase from 5 to $40\\upmu\\mathrm{m}$ , indicating that thermo-mechanical problems, such as delamination, and/or destruction of the charge percolation network could be causing issues in this electrode. Therefore, enhancing cathodic performance simply by increasing cathode thickness may not be feasible for high-TEC cathode systems. \n\nAs additional evidence of these issues, we note remarkable stability for the $40{\\cdot}{\\upmu}{\\m}$ -thick $c$ -SYNC ORE during a 200-h test of $R_{\\mathfrak{p}}$ at $600^{\\circ}\\mathrm{C}$ , whereas the SNC electrode shows considerable performance deterioration (Fig. 2h, i). The symmetrical cells are subjected to a harsh thermal cycling procedure (Fig. 3a). After 40 cycles, the $R_{\\mathfrak{p}}$ value of the $c$ -SYNC electrode is only slightly increased from 0.075 to $0.081\\Omega\\mathrm{cm}^{2}$ ( $8\\%$ increase) despite its greater thickness, while the $R_{\\mathfrak{p}}$ value of the SNC electrode increases more, from 0.095 to $0.13\\Omega\\mathrm{cm}^{2}$ ( $19\\%$ increase). An evaluation of representative EIS Nyquist plots during the thermal cycling of the SNC and $c$ -SYNC electrodes confirms the better durability of the $c$ -SYNC electrode (Fig. 3b, c). In addition to the appreciable increase in $R_{\\mathfrak{p}}$ , it can be seen that the area-specific Ohmic resistance $(R_{\\mathrm{ohm}})$ also increases substantially for the cell with the SNC electrode, which may be a sign of degradation and/or the onset of delamination at the electrode–electrolyte interface due to the repeated thermal cycling. We observe post-mortem cross-sectional micrographs of the two electrodes after the thermal cycling, as shown in Fig. 3d, Supplementary Figs. 16, 17. Whereas the SNC electrode has developed obvious cracks both at the electrode– electrolyte interface and across the electrode, no cracks are observed in the $c$ -SYNC electrode. \n\n![](images/485998832bd13bde6f24249b260b85870cf2ead51e682263de3273501762ad96.jpg) \nFig. 3 | Thermal cycling and mechanism schematic. a, The ASR $(R_{\\mathrm{p}})$ response of SNC- and $c$ -SYNC-based symmetric cell electrodes during 40 thermal cycles between $600^{\\circ}\\mathrm{C}$ and $300^{\\circ}\\mathsf C$ (at a heating rate of $30^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ and passive cooling at about $7.5^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ , 90 h total cumulative testing). We note that a $40{\\cdot}{\\upmu}{\\m}$ -thick electrode is used for the c-SYNC cell, whereas a 10-μm-thick electrode is used for the SNC cell because thicker SNC electrodes are prone to rapid failure. b, c, Representative EIS Nyquist plots for the SNC (b) and $c$ -SYNC (c) symmetric cell after cycling. d, Cross-sectional photographs of cells after cycling: SNC-based symmetric cell with cracks inside the electrode bulk (marked by C1) \nand at electrode–electrolyte interface (C2) (top images); $c$ -SYNC-based electrode (bottom images). The dashed rectangles indicate the areas magnified in the middle and right images. e, The I–V and I–P (I, current density; V, voltage; P, power density) curves of an anode-supported H2/air SOFC with a $40{\\cdot}{\\upmu}{\\m}$ -thick c-SYNC cathode. f, Proposed mechanism for thermo-mechanical enhancement by TEC offset in c-SYNC composite electrode with zoomed view of particle interaction and analysis of forces, contrasting the behaviour of SNC versus c-SYNC. \n\nTo fully demonstrate the concept of TEC matching, the electrochemical performances of thickness-optimized $c$ -SYNC and SNC electrodes are further assessed in YSZ-Ni cermet anode-supported single cells with a YSZ $(8\\upmu\\mathrm{m})/\\mathrm{SDC}\\left(5\\upmu\\mathrm{m}\\right)$ double-layered electrolyte. The maximum power density of the cell using the $40{\\cdot}{\\upmu}{\\m}$ -thick $c$ -SYNC cathode reaches 1,690, 1,139 and $817\\mathsf{m}\\mathsf{w}\\mathsf{c m}^{-2}$ at 750, 700 and $650^{\\circ}\\mathrm{C}$ , respectively, greatly exceeding the SNC cathode counterparts (Fig. 3e, Supplementary Fig. 18a). The durability of the $c$ -SYNC-based single cell is also better than that of the SNC-based cell (Supplementary Fig. 18b). Post-mortem cross-sectional images are shown in Supplementary Fig. 19. The larger surface area observed in the $c$ -SYNC electrode microstructure may increase the active sites for the ORR and enhance thermo-mechanical stability. \n\n# Discussion of thermo-mechanical stability \n\nAlthough it is difficult to directly elucidate the nanoscale mechanisms contributing to the thermo-mechanical stability enhancement in the TEC-offset $c$ -SYNC electrode, for the purposes of speculative discussion, we consider a contact scenario of SDC and $c$ -SYNC particles in the vicinity of an electrode–electrolyte interface (Fig. 3f) which represents a simplified model of the actual c-SYNC composite particle network revealed by TEM imaging (Fig. 1, Supplementary Fig. 4). When heated, the YWO particles will shrink, which, we hypothesize, reduces the expansion of adjoining SYNC particles owing to the constraint enforced by the interlinking SWO interphase. The contact structure of SYNC–SWO–YWO would therefore be expected to self-reconstruct to adapt with the expansion of the underlying SDC electrolyte substrate, for example, via pore-filling, contact angle adjustment or even topology change (for example, introduction of extra contact between SYNC particles). Consequently, the TEC of the c-SYNC is somewhat self-regulated to match that of SDC, and the delamination risk is greatly reduced. A simplified mechanical analysis posits the development of shear $(\\tau_{\\theta})$ and tensile $(\\sigma_{\\theta})$ stresses on the main SYNC particle owing to shrinkage of adjoining YWO particles. If no detachment occurs between YWO and SYNC (thanks to the reinforcement of SWO), the $x$ -axis component of $\\tau_{\\theta}$ and $\\sigma_{\\theta}$ will reduce the shear stress $(\\tau_{x})$ at the contact between SDC and SYNC to fulfil the force balance with $\\sigma_{x}$ . Given that shear stress is usually responsible for Model II delamination failure44, compositing YWO is therefore effective in reducing the risk of delamination between SYNC and SDC. By contrast, the mismatched expansion at the SDC–SNC interface can cause delamination failure upon thermal cycling. Cracks are also likely to spread throughout the whole cathode owing to a similar mechanism. \n\n# Conclusions \n\nIn this work, a composite electrode design approach is proposed that uses the thermal-expansion offset provided by an NTE component to greatly enhance long-term electrode durability and ORR activity. As a practical demonstration of this approach, we synthesized a highly active and durable composite cathode system formed from the high-TEC cobalt-containing perovskite SNC with the NTE oxide YWO. Calcination of the composite electrode at $800^{\\circ}\\mathrm{C}$ results in the in situ formation of uniformly distributed $c$ -SYNC particles with a high ORR activity and a fine size that also ensure strong thermo-mechanical reliability. The $c$ -SYNC composite (TEC of $12.9\\times10^{-6}\\mathsf{K}^{-1})$ achieves thermal expansion closely matching the electrolyte, in marked contrast to the unacceptably high TEC of the single-phase SNC electrode material. The $c$ -SYNC composite electrode demonstrates promising ORR activity with an ASR value of $0.041\\Omega\\mathrm{cm}^{2}$ for a thickness of $35\\upmu\\mathrm{m}$ at $600^{\\circ}\\mathrm{C}$ ; the peak power density from an SOFC button cell employing the $c$ -SYNC cathode reaches $1{,}690\\mathsf{m}\\mathsf{w c m}^{-2}$ at $750^{\\circ}\\mathrm{C}$ . In summary, the proposed strategy of compositing YWO as an NTE component with limited phase reaction to offset the high TEC of a cobalt-containing perovskite cathode is proved to be a promising and effective approach to developing durable, high-performance SOFCs. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03264-1. \n\n15. Chen, Y., Shen, J., Yang, G., Zhou, W. & Shao, Z. A single-/double-perovskite composite with an overwhelming single-perovskite phase for the oxygen reduction reaction at intermediate temperatures. J. Mater. Chem. A 5, 24842–24849 (2017). \n16. Baek, S. W., Kim, J. H. & Bae, J. Characteristics of $A B O_{3}$ and $\\mathsf{A}_{2}\\mathsf{B O}_{4}$ ( $A=5m$ , Sr; $B=C O$ , Fe, Ni) samarium oxide system as cathode materials for intermediate temperature-operating solid oxide fuel cell. Solid State Ion. 179, 1570–1574 (2008). \n17. Wang, F., Zhou, Q., He, T., Li, G. & Ding, H. Novel $\\mathsf{S r C o}_{1-y}\\mathsf{N b}_{y}\\mathsf{O}_{3-\\bar{\\delta}}$ cathodes for intermediate-temperature solid oxide fuel cells. J. Power Sources 195, 3772–3778 (2010). \n18.\t Hrovat, M., Holc, J. & Kolar, D. Thick film ruthenium oxide/yttria-stabilized zirconia-based cathode material for solid oxide fuel cells. Solid State Ion. 68, 99–103 (1994). \n19.\t Zhou, Q., Wang, F., Shen, Y. & He, T. Performances of $\\mathsf{L n B a C o}_{2}\\mathsf{O}_{5+x}\\mathrm{-Ce}_{0.8}\\mathsf{S m}_{0.2}\\mathsf{O}_{1.9}$ composite cathodes for intermediate-temperature solid oxide fuel cells. J. Power Sources 195, 2174–2181 (2010). \n20.\t Zhou, W., Shao, Z., Ran, R. & Cai, R. Novel $\\mathsf{S r S c}_{0.2}\\mathsf{C o}_{0.8}\\mathsf{O}_{3.\\delta}$ as a cathode material for low temperature solid-oxide fuel cell. Electrochem. Commun. 10, 1647–1651 (2008). \n21. Ding, X., Cui, C. & Guo, L. Thermal expansion and electrochemical performance of $\\mathsf{L a}_{0.7}\\mathsf{S r}_{0.3}\\mathsf{C u O}_{3-\\delta}\\mathsf{-S m}_{0.2}\\mathsf{C e}_{0.8}\\mathsf{O}_{2-\\delta}$ composite cathode for IT-SOFCs. J. Alloys Compd. 481, 845–850 (2009). \n22.\t Song, Y. et al. A cobalt-free multi-phase nanocomposite as near-ideal cathode of intermediate-temperature solid oxide fuel cells developed by smart self-assembly. Adv. Mater. 32, 1906979 (2020). \n23.\t Mary, T. A., Evans, J. S., Vogt, T. & Sleight, A. W. Negative thermal expansion from 0.3 to 1050 Kelvin in $Z r W_{2}O_{8}.$ Science 272, 90–92 (1996). \n24. Chen, J. et al. Zero thermal expansion in PbTiO $_{3}$ -based perovskites. J. Am. Chem. Soc. 130, 1144–1145 (2008). \n25. Goodwin, A. L. & Kepert, C. J. Negative thermal expansion and low-frequency modes in cyanide-bridged framework materials. Phys. Rev. B 71, 140301 (2005). \n26. Forster, P. M. & Sleight, A. W. Negative thermal expansion in $\\mathsf{Y}_{2}\\mathsf{W}_{3}\\mathsf{O}_{12}$ Int. J. Inorg. Mater. 1, 123–127 (1999). \n27. Sumithra, S., Waghmare, U. V. & Umarji, A. M. Anomalous dynamical charges, phonons, and the origin of negative thermal expansion in $\\mathsf{Y}_{2}\\mathsf{W}_{3}\\mathsf{O}_{12}$ . Phys. Rev. B 76, 024307 (2007). \n28.\t Khaliullin, S. M., Khaliullina, A. S. & Neiman, A. Y. High-temperature conductivity and structure of $\\mathsf{Y}_{2}(\\mathsf{W O}_{4})_{3}$ ceramics. Russ. J. Phys. Chem. B 10, 62–68 (2016). \n29.\t Zhou, W., Jin, W., Zhu, Z. & Shao, Z. Structural, electrical and electrochemical characterizations of $\\mathsf{S r N b}_{0.1}\\mathsf{C o}_{0.9}\\mathsf{O}_{3-\\delta}$ as a cathode of solid oxide fuel cells operating below $600^{\\circ}\\mathsf{C}$ Int. J. Hydrogen Energy 35, 1356–1366 (2010). \n30. Rosen, B. A. Progress and opportunities for exsolution in electrochemistry. Electrochem 1, 32–43 (2020). \n31. Han, H. et al. Lattice strain-enhanced exsolution of nanoparticles in thin films. Nat. Commun. 10, 1471 (2019); author correction 10, 2083 (2019). \n32. Zhu, Y. et al. An A-site-deficient perovskite offers high activity and stability for low-temperature solid-oxide fuel cells. ChemSusChem 6, 2249–2254 (2013). \n33.\t Zhu, Y. et al. Influence of crystal structure on the electrochemical performance of A-sitedeficient $\\mathsf{S r}_{1\\cdot s}\\mathsf{N b}_{0.1}\\mathsf{C o}_{0.9}\\mathsf{O}_{3\\cdot\\bar{\\delta}}$ perovskite cathodes. RSC Advances 4, 40865–40872 (2014). \n34.\t Duan, C., Hook, D., Chen, Y., Tong, J. & O’Hayre, R. Zr and Y co-doped perovskite as a stable, high performance cathode for solid oxide fuel cells operating below $500^{\\circ}\\mathsf{C}$ Energy Environ. Sci. 10, 176–182 (2017). \n35.\t Biesinger, M. C. et al. Resolving surface chemical states in XPS analysis of first row transition metals, oxides and hydroxides: Cr, Mn, Fe, Co and Ni. Appl. Surf. Sci. 257, 2717–2730 (2011). \n36. Lu, Q., Chen, Y., Bluhm, H. & Yildiz, B. Electronic structure evolution of $\\mathsf{S r C o O}_{x}$ during electrochemically driven phase transition probed by in situ X-ray spectroscopy. J. Phys. Chem. C 120, 24148–24157 (2016). \n37.\t Li, M., Zhou, W., Peterson, V. K., Zhao, M. & Zhu, Z. A comparative study of $\\mathsf{S r C o}_{0.8}\\mathsf{N b}_{0.2}\\mathsf{O}_{3-\\bar{\\delta}}$ and $\\mathsf{S r C o}_{0.8}\\mathsf{T a}_{0.2}\\mathsf{O}_{3-\\bar{\\delta}}$ as low-temperature solid oxide fuel cell cathodes: effect of non-geometry factors on the oxygen reduction reaction. J. Mater. Chem. A 3, 24064– 24070 (2015). \n38.\t Koo, B. et al. Sr segregation in perovskite oxides: why it happens and how it exists. Joule 2, 1476–1499 (2018). \n39. Lee, K. T. & Manthiram, A. Comparison of $\\mathsf{L n}_{0.6}\\mathsf{S r}_{0.4}\\mathsf{C o O}_{3-\\bar{\\delta}}$ (Ln=La, Pr, Nd, Sm, and Gd) as cathode materials for intermediate temperature solid oxide fuel cells. J. Electrochem. Soc. 153, A794–A798 (2006). \n40. Das, S., Das, S. & Das, K. Synthesis and thermal behavior of $\\mathsf{C u}/\\mathsf{Y}_{2}\\mathsf{W}_{3}\\mathsf{O}_{12}$ composite. Ceram. Int. G. 40, 6465–6472 (2014). \n41. Ganesh, V. V. & Gupta, M. Effect of the extent of reinforcement interconnectivity on the properties of an aluminum alloy. Scr. Mater. 44, 305–310 (2001). \n42.\t Uju, W. A. & Oguocha, I. N. A. A study of thermal expansion of Al–Mg alloy composites containing fly ash. Mater. Des. 33, 503–509 (2012). \n43.\t Barbucci, A. et al. Influence of electrode thickness on the performance of composite electrodes for SOFC. J. Appl. Electrochem. 38, 939–945 (2008). \n44.\t Liu, L., Kim, G. Y. & Chandra, A. Modeling of thermal stresses and lifetime prediction of planar solid oxide fuel cell under thermal cycling conditions. J. Power Sources 195, 2310–2318 (2010). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n# Article Methods \n\n# Synthesis of materials \n\nSNC powder was synthesized by a combined EDTA-citrate complexing process45, using stoichiometric $\\mathsf{S r}(\\mathsf{N O}_{3})_{2},$ , $\\mathbf{C_{\\mathrm{10}}H_{5}N b O_{20}}$ and $\\mathbf{Co}(\\mathsf{N O}_{3})_{2}{\\cdot}6\\mathsf{H}_{2}\\mathbf{O}$ (Sinopharm Chemical, analytical grade). The solid precursor for SNC was calcined at $1{,}000^{\\circ}\\mathsf{C}$ for $5\\mathsf{h}$ in air to obtain the final product. The SDC electrolyte powder was synthesized by a similar process as in our previous works45. $\\Upsilon_{2}0_{3}$ and ${\\mathsf{W O}}_{3}$ powders were used as raw materials to prepare YWO by co-milling (Fritsch, Pulverisette 6) at 400 rpm for 1 h in alcohol and then dried. Next, the mixture was calcined at $1,100^{\\circ}\\mathsf C$ for $5\\mathsf{h}$ in air to obtain YWO powder. The $c$ SYNC powder was composited by calcinating appropriate amounts of YWO and SNC at $800^{\\circ}\\mathrm{C}$ for $2\\mathfrak{h}$ in air. \n\n# Fabrication of symmetrical and single cells \n\nThe electrode powder $\\dot{}c$ -SYNC or SNC) was ball-milled for 30 min with isopropanol, glycol and glycerol to form the electrode slurry, and then the slurry was sprayed onto both sides of an SDC compact disk, followed by heating at $800^{\\circ}\\mathrm{C}$ for 2 h to obtain symmetrical cells. The thicknesses of the electrodes were controlled by adjusting the spraying time. \n\nTo fabricate single cells, anode-supported half-cells (NiO+YSZ/YSZ/ SDC) were first prepared via a tape-casting process45. Then, the c-SYNC (or SNC) cathode slurry was sprayed over the centre of the SDC surface (with a circular area of $0.45\\mathrm{cm}^{2}.$ ), followed by sintering at $800^{\\circ}\\mathrm{C}$ for 2 h in air. \n\n# Basic characterizations \n\nRoom-temperature powder XRD was performed to determine the crystal structure of the powders (Bruker D8 Advance). The high-temperature XRD characterization was performed with a high-temperature attachment (Rigaku D/max 2500 V) at a heating rate of $10^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ and was held for $2\\mathfrak{h}$ at each target temperature. The morphologies of composite powders and cells were examined using a STEM-HAADF (FEI, Titan Cubed Themis G201), HRTEM (JEOL JEM-2100F) and SEM (FEI QUANTA-2000, ZEISS SUPRA-55 and Hitachi S4800). The pellet samples for STEM-HAADF and HRTEM were prepared by FIB-SEM (FEI Scios 2). The thermogravimetric analysis was performed by a thermobalance (STA 449 F3 Jupiter, NETZSCH). All TEC tests were performed using a Netzsch DIL 402C/3/G dilatometer in air with a heating rate of $5^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ . Dense column-shaped samples for thermal expansion tests were fabricated using a spark plasma sintering system (LABOX-110H, Sinter Land) at $600^{\\circ}\\mathrm{C}$ under 50 MPa at a heating rate of $100^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ in Ar. The XPS test was performed by a Physical Electronics PHI 5600 multi-technique system using Al monochromatic X-rays at a power of $350\\mathsf{W}$ . \n\n# Electrochemical testing \n\nEIS measurements of the symmetrical cells were carried out using an electrochemical workstation (Solartron $1287\\substack{+1260\\mathbf{A}},$ from $100\\mathsf{k H z}$ to 0.01 Hz with a signal amplitude of $10\\mathrm{mV}$ under open circuit. The ${\\mathsf{C O}}_{2}$ exposure test was performed in air containing $\\mathrm{\\cdot10\\vol\\%00_{2}}$ at $600^{\\circ}\\mathrm{C}$ . The ZView program was used for the equivalent circuit fitting, and the distribution of relaxation time analysis was performed using an open-source MATLAB code46. \n\nThe I–V and $I{-}P$ polarization curves were collected using a source meter (Keithley 2420) in an in-house fuel cell test station. During the test, dry ${\\sf H}_{2}$ was fed into the anode side as fuel at a flow rate of $\\mathbf{\\delta}80\\mathbf{m}\\mathbf{l}\\mathbf{m}\\mathbf{i}\\mathbf{n}^{-1}$ (STP), while the cathode side was fed with ambient air at a flow rate of $100\\mathrm{ml}\\mathrm{min}^{-1}$ (STP). \n\n# Data availability \n\n# The data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\n45.\t Zhang, Y. et al. Significantly improving the durability of single-chamber solid oxide fuel cells: a highly active $\\mathsf{C O}_{2}$ -resistant perovskite cathode. ACS Appl. Energy Mater. 1, 1337– 1343 (2018). \n46.\t Wan, T. H., Saccoccio, M., Chen, C. & Ciucci, F. Influence of the discretization methods on the distribution of relaxation times deconvolution: implementing radial basis functions with DRT tools. Electrochim. Acta 184, 483–499 (2015). \n\nAcknowledgements This work was financially supported by the National Natural Science Foundation of China (21576135, 21878158, 21828801 and 52006150), Jiangsu Natural Science Foundation for Distinguished Young Scholars (BK20170043), the Priority Academic Program Development of Jiangsu Higher Education Institutions, and State Key Laboratory of Materials-Oriented Chemical Engineering. R.O. acknowledges support from the Fulbright Foundation Global Scholars Program and the US Army Research Office under grant number W911NF-17-540 1-0051. M.N. acknowledges a Research Grant Council University Grants Committee Hong Kong SAR Grant, reference number PolyU 152064/18E. The authors also acknowledge the assistance on HRTEM observation received from the Electron Microscope Center of Shenzhen University. \n\nAuthor contributions W.Z., R.O. and Z.S. conceived and designed the project. Y.Z. and B.C. performed the characterizations and experiments. Y.Z., B.C. and D.G. analysed the data. M.X., R.R. and M.N. contributed the laboratory apparatus and experiment sites. Y.Z., B.C., W.Z., R.O. and Z.S. drafted the article and revised it critically. All authors reviewed the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-03264-1. Correspondence and requests for materials should be addressed to W.Z. or Z.S. Peer review information Nature thanks Yanhai Du, Anke Hagen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. " + }, + { + "id": "10.1002_advs.202003627", + "DOI": "10.1002/advs.202003627", + "DOI Link": "http://dx.doi.org/10.1002/advs.202003627", + "Relative Dir Path": "mds/10.1002_advs.202003627", + "Article Title": "Highly Stretchable, Adhesive, Biocompatible, and Antibacterial Hydrogel Dressings for Wound Healing", + "Authors": "Yang, ZF; Huang, RK; Zheng, BN; Guo, WT; Li, CK; He, WY; Wei, YG; Du, Y; Wang, HM; Wu, DC; Wang, H", + "Source Title": "ADVANCED SCIENCE", + "Abstract": "Treatment of wounds in special areas is challenging due to inevitable movements and difficult fixation. Common cotton gauze suffers from incomplete joint surface coverage, confinement of joint movement, lack of antibacterial function, and frequent replacements. Hydrogels have been considered as good candidates for wound dressing because of their good flexibility and biocompatibility. Nevertheless, the adhesive, mechanical, and antibacterial properties of conventional hydrogels are not satisfactory. Herein, cationic polyelectrolyte brushes grafted from bacterial cellulose (BC) nullofibers are introduced into polydopamine/polyacrylamide hydrogels. The 1D polymer brushes have rigid BC backbones to enhance mechanical property of hydrogels, realizing high tensile strength (21-51 kPa), large tensile strain (899-1047%), and ideal compressive property. Positively charged quaternary ammonium groups of tethered polymer brushes provide long-lasting antibacterial property to hydrogels and promote crawling and proliferation of negatively charged epidermis cells. Moreover, the hydrogels are rich in catechol groups and capable of adhering to various surfaces, meeting adhesive demand of large movement for special areas. With the above merits, the hydrogels demonstrate less inflammatory response and faster healing speed for in vivo wound healing on rats. Therefore, the multifunctional hydrogels show stable covering, little displacement, long-lasting antibacteria, and fast wound healing, demonstrating promise in wound dressing.", + "Times Cited, WoS Core": 439, + "Times Cited, All Databases": 452, + "Publication Year": 2021, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000625411600001", + "Markdown": "# Highly Stretchable, Adhesive, Biocompatible, and Antibacterial Hydrogel Dressings for Wound Healing \n\nZifeng Yang, Rongkang Huang, Bingna Zheng,\\* Wentai Guo, Chuangkun Li, Wenyi He, Yingqi Wei, Yang Du, Huaiming Wang, Dingcai Wu,\\* and Hui Wang\\* \n\nTreatment of wounds in special areas is challenging due to inevitable movements and difficult fixation. Common cotton gauze suffers from incomplete joint surface coverage, confinement of joint movement, lack of antibacterial function, and frequent replacements. Hydrogels have been considered as good candidates for wound dressing because of their good flexibility and biocompatibility. Nevertheless, the adhesive, mechanical, and antibacterial properties of conventional hydrogels are not satisfactory. Herein, cationic polyelectrolyte brushes grafted from bacterial cellulose (BC) nanofibers are introduced into polydopamine/polyacrylamide hydrogels. The 1D polymer brushes have rigid BC backbones to enhance mechanical property of hydrogels, realizing high tensile strength (21–51 kPa), large tensile strain $(899-7047\\%)$ , and ideal compressive property. Positively charged quaternary ammonium groups of tethered polymer brushes provide long-lasting antibacterial property to hydrogels and promote crawling and proliferation of negatively charged epidermis cells. Moreover, the hydrogels are rich in catechol groups and capable of adhering to various surfaces, meeting adhesive demand of large movement for special areas. With the above merits, the hydrogels demonstrate less inflammatory response and faster healing speed for in vivo wound healing on rats. Therefore, the multifunctional hydrogels show stable covering, little displacement, long-lasting antibacteria, and fast wound healing, demonstrating promise in wound dressing. \n\nThe ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/advs.202003627 \n\n$\\textcircled{\\odot}2021$ The Authors. Advanced Science published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. \n\nDOI: 10.1002/advs.202003627 \n\n# 1. Introduction \n\nWound dressing has been an important branch of biomedical materials research.[1] Skin damage caused by abrasion after falling and clinical incision after surgery are the most common wounds in real life.[2] Compared with the wounds at flat areas of human body, it is still challenging to treat the wounds at special areas such as joints, popliteal fossae, axillae, and muscle folds. Poor adhesive performance, difficult fixation, and incomplete coverage are the main reasons. Moreover, in clinic, most wounds are sterilized with $75\\%$ alcohol or iodine, followed by covering with cotton gauzes. Therefore, regular disinfection and dressing replacement are necessary due to lack of antibacterial property of cotton gauze. In addition, fixed cotton gauze dressing needs to be taped, and sometimes, the skin is allergic to tape material. To this end, designing a stretchable, adhesive, antibacterial, and biocompatible dressing is of great clinical significance. \n\nHydrogels are a class of 3D network gels formed by chemical and/or physical crosslinking.[3] Because of their superior biocompatibility, controllable physical properties, natural drug-loading structure, and abundant functional groups, hydrogels have gradually become a hotspot of medical wound dressing. To date, hydrogels have been successfully applied to treat skin defects,[4] infected wounds,[5] burn wounds,[6] diabetic feet,[7] and wet wounds inside the body.[8] Based on the healing requirements of different wounds, one or more functions such as good tissue adhesion, excellent mechanical property, antibacterial capability, cell crawling promotion, physical contraction, local immune regulation, and antitumor property have been implanted in the hydrogel dressings, such as Cur-QCS/PF,[5] QCSP/PEGS-FA[9] , OSA-DA-PAM,[3] PDA@AgNPs/CPHs,[10] NPs-P-PAA,[11] and STP[12] hydrogels. However, the existing hydrogel dressings were difficult to achieve a satisfactory balance among the multiple functions. For example, due to the presence of quaternary ammonium salt, both Cur-QCS/PF[5] and QCSP/PEGS-FA[9] hydrogels showed excellent antibacterial property, but their tensile strain (below $100\\%$ ) and adhesion strength (less than 8 kPa) were not satisfactory. OSA-DA-PAM[3] and STP[12] hydrogel dressings had good adhesion and stretching performances, but no antibacterial property. With the catechol structure and nanosilver, PDA@AgNPs/CPHs[10] and NPs-P-PAA[11] hydrogels exhibited excellent tissue adhesion and antibacterial properties, but use of silver-functionalized biomedical materials could give rise to cumulative toxic effect of heavy metal in organisms.[13] Therefore, it is still highly challenging in preparing a hydrogel dressing with ideal tissue adhesion, good stretchability, broad-band antibacterial capability, cell crawling promotion, and bio-compatibility by a facile and efficient material design. \n\nHerein, a new class of highly stretchable, adhesive, biocompatible, and antibacterial hydrogel dressings is designed and prepared by introducing poly(diallyl dimethyl ammonium chloride) (pDADMAC) brushes grafted from bacterial cellulose (BC) nanofibers (BC-g-pDADMAC, BCD) into polydopamine/polyacrylamide (PDA/PAM) hydrogels. For the asprepared multifunctional BCD/PDA/PAM hydrogels, the PAM component has good biocompatibility and stable crosslinking structure, and is thus used as the hydrogel scaffold.[3] Inspired by the biological adhesion of dopamine from mussel,[14] the PDA component has abundant catechol groups and thus can adhere to various surfaces, especially special areas needing large movements. More importantly, the BCD component not only has rigid BC backbones to enhance the mechanical property of hydrogels, but also has pDADMAC brushes with broad spectrum and low toxic positively charged quaternary ammonium groups for providing high-efficiency and long-lasting antibacterial performance. Moreover, the positively charged pDADMAC brushes could help attract negatively charged epidermis cells and thus promote cell crawling and proliferation.[15] Therefore, our BCD/PDA/PAM hydrogels have superior mechanical behaviors with high tensile strength $(21\\mathrm{-}51\\mathrm{kPa})$ , large tensile strain (899– $1047\\%$ and ideal compressive performance, and demonstrate stable covering, little displacement, long-lasting antibacteria and fast wound healing. \n\n# 2. Results and Discussion \n\n# 2.1. Structure Characterizations \n\nBC has a natural nanofiber network structure with good hydrophilicity, mechanical property, and biocompatibility, which has a broad application prospect in biomedical dressings.[16] Surface-initiated atom transfer radical polymerization (SI-ATRP) is a highly efficient active/controllable polymerization system and can be used in surface functionalization of BC with abundant hydroxyl groups.[17] pDADMAC chains were grafted from nanofibers of BC via SI-ATRP, leading to formation of BCD (Figure 1a).The original smooth and fine nanofibers of BC became rough after grafting pDADMAC (Figure 2a–c). Element mapping showed the presence of chlorine on the surface of BCD, confirming the successful polymeric modification of BC (Figure 2b, inset). The X-ray photoelectron spectroscopy (XPS) spectrum of BC showed $\\mathrm{\\DeltaO_{1s}}$ $(533.1\\ \\mathrm{eV})$ and $\\mathrm{C_{1s}}$ (287.1 eV) peaks (Figure S1a, Supporting Information); peaks at 287.9, 286.3, and $284.7\\mathrm{eV}$ of the deconvoluted high resolution $\\mathrm{C_{1s}}$ spectrum were mainly attributed to bonds of O–C–O, C–O, and $\\mathrm{C-C/C-H}$ of BC, respectively (Figure S1b, Supporting Information).[17c,18] After grafting pDADMAC, new peaks appeared at 197.1, 268.0, and \n\n$402.1\\ \\mathrm{eV},$ which were assigned to $\\mathrm{Cl}_{2\\mathrm{p}}$ , $\\mathrm{Cl}_{2\\mathrm{s}}$ , and $\\mathrm{N_{1s}}$ , respectively (Figure S1c, Supporting Information); peak at $286.2\\ \\mathrm{eV}$ was mainly attributed to $\\mathrm{C-N/C-O}$ bonds of BCD (Figure S1d, Supporting Information).[19] Fourier transform infrared (FT-IR) was also used to study the structure evolution of BC, initiatorfunctionalized BC (BC-Br) and BCD (Figure S2, Supporting Information). Compared to BC, a new peak appeared at $1735\\mathrm{cm}^{-1}$ for BC-Br, which was attributed to carbonyl $\\scriptstyle{(\\mathsf{C}=\\mathsf{O})}$ stretching vibration;[20] new peaks at 848 and $1479~\\mathrm{cm}^{-1}$ for BCD were ascribed to the characteristic bands of $\\displaystyle{\\mathrm{C}}{\\mathrm{-}}{\\mathrm{N}}$ and methyl $\\left(\\mathrm{-CH}_{3}\\right)$ groups of quaternized ammonium,[17c,21] indicating pDADMAC was successfully grafted. \n\nThe preparation of BCD/PDA/PAM hydrogels was achieved by incorporating BCD into PDA/PAM hydrogel network. For the traditional PDA/PAM hydrogel, prepolymerization of dopamine was usually carried out in a weak alkaline $\\mathrm{(pH=}$ 8) environment,[22] which could affect the stability of acidic reactants. Here, BCD was firstly dispersed in the aqueous dopamine solution. Considering dopamine could prepolymerize under the action of oxidants,[23] ammonium persulfate (APS) was used for prepolymerization of dopamine in our study (Figure 1b, Step 2), which can avoid use of conventional alkaline condition and ice bath. It took $25\\ \\mathrm{min}$ for the color of the solution to gradually change from white to brown in room temperature with a high-speed stirring (Figure S3, Supporting Information). Subsequently, acrylamide and crosslinking agent were added into the reaction system (Figure 1b, Step 3). The remaining APS was directly used as initiator for synthesis of BCD/PDA/PAM hydrogels (e.g., 10‰BCD/PDA/PAM hydrogel, Figure 1c). With a reaction in a $60~^{\\circ}\\mathrm{C}$ chamber for $^{3\\mathrm{h}}$ , the gelation was completed (Figure S4, Supporting Information). Compared with other studies,[14a] the whole process of our hydrogel preparation was simple and mild, which was free of $\\mathsf{p H}$ control and ice bath. The as-obtained $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel showed stretchable and adhesive properties (Figure 1d,e,g). The rich catechol groups from PDA component of the hydrogel product could enhance cell affinity, tissue adhesion, and cell proliferation (Figure 1h, S5a, Supporting Information), which has been applied to many biomedical hydrogels.[24] Addition of BCD component could improve the mechanical strength and cell affinity of hydrogel.[16a,25] BCD is a kind of cationic polyelectrolyte brush and can form porous networks by the interconnection of nanofibers, which is conducive to cell adhesion and crawling. Meanwhile, the positively charged quaternary ammonium salts of BCD facilitate attraction of negatively charged normal cells by electrostatic interaction;[26] the increase of surface charge for biomaterials could enhance the number of biologically available surface-attached proteins, leading to an increased cell spreading area after adhesion.[27] Therefore, the incorporation of PDA and BCD components can enhance the cell affinity of $10\\%\\mathrm{{8CD/PDA/PAM}}$ hydrogel (Figure S5b, Supporting Information). Due to presence of positively charges, the zeta potential of BCD/PDA/PAM hydrogel was measured to be $1.42{-}3.78\\ \\mathrm{mV}$ $\\mathrm{(pH=6.5\\}$ ) or $1.64{-}3.35\\ \\mathrm{mV}$ $(\\mathrm{pH}=7.2)$ ), and became higher with increasing the BCD content (Figure S6, Supporting Information). The positive charges would endow the hydrogel with antibacterial performance (Figure 1f) and promotion of cell crawling and proliferation (Figure S5, Supporting Information).[26b,28] \n\n![](images/20a7a0dd1acd93fbb8ede1d59f59aa910d9117fdac3333ecb51193dc202a5749.jpg) \nFigure 1. Schematic of the stretchable, adhesive, and antibacterial hydrogel. a) Preparation of BCD by using SI-ATRP to graft pDADMAC from BC. b) Formation of BCD/PDA/PAM hydrogel. c–e) Different shapes of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel. f) Quaternary ammonium salts of BCD provide the antibacterial property to BCD/PDA/PAM hydrogel. g) Stretchable BCD/PDA/PAM hydrogel covers the elbow joint completely. h) Catechol groups of PDA component promote tissue adhesion of hydrogel. \n\n$10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel was transparent light brown (Figure 2d), which was different from transparent and colorless BC/PAM hydrogel (Figure S7a, inset, Supporting Information) and brown PDA/PAM hydrogel (Figure S7b, inset, Supporting Information). After lyophilization, $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel showed a porous network with a pore diameter of $3-$ $5\\upmu\\mathrm{m}$ (Figure 2e). For BC/PAM and PDA/PAM hydrogels, their pore diameters were ${\\approx}5{\\mathrm{-}}20{\\upmu}{\\mathrm{m}}$ (Figure S7, Supporting Information). As shown in FT-IR spectrum of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel (Figure 2f), the peak at $1668~\\mathrm{{cm}^{-1}}$ was ascribed to $\\scriptstyle{\\mathrm{C=O}}$ stretching of PAM; the peak at $1620~\\mathrm{{cm}^{-1}}$ was the $_\\mathrm{N-H}$ deformation peak for primary amine deriving from PDA, demonstrating the successful polymerization of dopamine in the system; the $\\displaystyle{\\mathrm{C}}{\\mathrm{-}}{\\mathrm{N}}$ stretching peak at $1402~\\mathrm{cm}^{-1}$ was from primary amide of both PDA and PAM in the hydrogel; the $\\mathrm{-NH}_{2}$ in-plane rocking peak at $1124~\\mathrm{{cm}^{-1}}$ mainly derived from PAM; the characteristic peak of BC at $619\\mathrm{cm}^{-1}$ in the fingerprint region proved the existence of BCD.[22e] \n\n![](images/8ad95a1eb2fb507f077e76ffe4ee6f888678c60d4549b1b686427a6385a352ae.jpg) \nFigure 2. SEM images of a) BC and b,c) BCD; the inset of (b) is the element mapping of Cl. d) Digital photo and e) SEM image of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel. f) FT-IR spectra of dopamine, acrylamide, BCD and $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel. \n\n# 2.2. Mechanical and Adhesive Properties \n\nThe network of BCD/PDA/PAM hydrogels was maintained by both noncovalent bonding (e.g., hydrogen bonding, van der Waals force, and electrostatic interaction) and covalent bonding of crosslinked polymers. Due to the existence of noncovalent bonds, $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel showed a valuable selfhealing performance (Figure S8, Supporting Information).[22b,29] The cut $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel was healed within $30\\mathrm{min}$ and could be stretched without cracking after $^{2\\mathrm{~h~}}$ healing (Figure S8a,b, Supporting Information). Meanwhile, the sample with $30\\mathrm{min}$ healing showed a good healing effect and no re-fracture was observed when attached to the left index finger with the movement of joints (Figure S8c, Supporting Information). As a result, the self-healed hydrogel would be enough to meet the requirements of dressing. \n\nWith a network system of physical and chemical crosslinking, BCD/PDA/PAM hydrogels have good elasticity and toughness. Under compressive loading, $10\\%\\mathrm{{BCD/PDA/PAM}}$ hydrogel could withstand $60\\%$ of compressive strain under a stress of $45\\mathrm{\\kPa}$ and recover to its original shape after removal of the load (Figure 3a; Figure S9, Supporting Information). After 5 cycles of loading-unloading test, the loops were similar to that of the first cycle (Figure 3c). Therefore, the hydrogel had stable elasticity and toughness, compared to the reported pure PAM hydrogel.[22a] The good resilience to withstand large deformation and high compressive strength made it qualified to meet the demand of toughness as hydrogel dressing. \n\n![](images/dfd1f8f6d4da95a5fc44e415a6904406c285ff5b4a80669fd5a44b4a3fcc5c79.jpg) \nFigure 3. a) $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel was compressed up to the strain of $60\\%$ and recovered to its original shape after it was released. b) Digital photos of the tensile test of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel, showing its high stretchability. c) Cyclic compressive loading–unloading test of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel. d) Tensile stress–strain curves of BCD/PDA/PAM hydrogels with different BCD contents and PDA/PAM hydrogel. e) Cyclic tensile test of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel under a tension of $400\\%$ . f) Digital photo of lap shear test using porcine skin. g) Adhesion strengths of BCD/PDA/PAM and PDA/PAM hydrogels. The error bars showed standard deviation $(n=3)$ ). h) Changes of adhesion strength with different adhesion cycles for BCD/PDA/PAM hydrogels. The error bars showed standard deviation $(n=3)$ ). i) Digital photos of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel adhered to the body’s frequently moving joints. \n\nAs shown in Figure 3b, $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel could be stretched to about 10 times of its initial length. Tensile strains of BCD/PDA/PAM hydrogels with different BCD ratios ranged from $89\\%$ to $1047\\%$ (Figure 3d), better than the other hydrogel wound dressing (normally lower than $100\\%$ ).[5,24a,30] Addition of BCD enhanced the degree of crosslinking, which slightly decreased the strain compared with PDA/PAM hydrogel $(1207\\%)$ , but improved the toughness of hydrogel. The tensile strength of BCD/PDA/PAM hydrogels increased with an increase of BCD content, indicating that BCD had a reinforcing effect. The fracture tensile strength greatly increased from 21 to $51\\mathrm{\\kPa}$ as an increase of the BCD ratio from $5\\text{\\textperthousand}$ to $15\\text{\\textperthousand}$ , compared with PDA/PAM hydrogel $(11\\mathrm{kPa})$ . During cyclic tensile tests, a small degree of stress reduction was observed after the first cycle, which was attributed to the toughness of BCD network (Figure 3e). In the later cycles, the stress kept almost the same value, indicating a small energy dissipation. \n\nBCD/PDA/PAM hydrogels showed excellent adhesion to various substrates. For example, $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel could be directly adhered to the surfaces of plastic, glass, porcine skin, and human skin with different bearing weights (Figure S10a, Supporting Information). The tissue adhesive mechanism of our hydrogels was attributed to catechol groups of PDA component that had high binding affinity to amines, thiols, and imidazoles in peptides and proteins of tissue (Figure 1h).[24c,31] As $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel was peeled from the porcine and human skins, visible sticky fibrils (indicated by red arrows) formed at the hydrogel-skin interfaces, indicating strong bonding (Figure S10b, Supporting Information).[29] Although sticky fibrils formed during the separation, no residual hydrogel remained on the skin and no allergy was observed after a $24\\mathrm{~h~}$ adhesion (Figure S10c, Supporting Information), indicating that $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel had good biocompatibility.[24c] To evaluate the potential utilization of BCD/PDA/PAM hydrogels as medical adhesives, in vitro lap shear testing was performed using porcine skin (Figure 3f).[8,32] The adhesion strength was maintained between 15 and $20~\\mathrm{\\kPa}$ (Figure 3g), higher than the commercial fibrin glue and other hydrogel dressings (normally $7.3\\mathrm{-}15.38\\mathrm{kPa}$ , Figure S11, Supporting Information).[5,12,29] The bonding of BCD and PDA in BCD/PDA/PAM hydrogels might consume a small part of hydroxyl groups of catechol groups. In addition, introduction of BCD improved the stiffness of BCD/PDA/PAM hydrogels, which would affect the polymer flexibility and then reduce the co-adhesion of the interface. These might be the reasons for the reduction of adhesion strength of BCD/PDA/PAM hydrogels as compared with PDA/PAM hydrogel (Figure 3g).[14a,31b] To further verify the repeatability of adhesion, 9-cycle peeling-off testing was performed on porcine skin (Figure 3h). The adhesion strength of BCD/PDA/PAM hydrogels decreased slightly with an increase of cycling numbers, but still could meet the adhesive requirements for hydrogel dressing. Furthermore, in order to test the stability of hydrogels by repeated stretching, $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel was fixed on the dynamic skin surfaces, including elbow, wrist, and interphalangeal joints. It was found that the position of the hydrogel was fixed without any retraction or rupture during this test process (Figure 3i; Figure S12, Supporting Information). These above good mechanical properties and excellent adhesion performances allowed BCD/PDA/PAM hydrogels to meet the demands of repeating stretching and good tissue adhesion for hydrogel dressing in real use. \n\n# 2.3. Antibacterial Property \n\nBacteria tend to adhere to traditional adhesive hydrogels and lead to wound infections.[5] Advantages of quaternary ammonium salt antibacterial agents lie in low bactericidal concentration, low toxicity, low irritation, broad-spectrum, and long-lasting effects. The principle of sterilization is mainly from the positive charges, which could adsorb the negatively charged bacteria by electrostatic force, and accumulate on their bacterial walls, thus causing growth inhibition and death of bacteria.[4–5,33] In this study, highly positive charged pDADMAC brushes of BCD were introduced to provide BCD/PDA/PAM hydrogels with antibacterial property (Figure 1f).[17c,34] \n\nContact sterilization experiments were performed by immersing BCD/PDA/PAM hydrogels into Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) culture solutions to assess antibacterial property. The experimental groups were BCD/PDA/PAM hydrogels with different BCD ratios immersed in culture solutions containing bacteria, while the control group was only a culture solution containing bacteria. Optical density $(\\mathrm{OD}_{600})$ values of bacteria cultured at different times were measured. As shown in Figure 4a, the $\\mathrm{\\DeltaOD}_{600}$ values of S. aureus and E. coli in the control group increased significantly at the ${8^{\\mathrm{{th}}}}$ and $6^{\\mathrm{th}}$ hours, respectively, and reached a peak at the $12^{\\mathrm{th}}$ hour. In the experimental groups, the $\\mathrm{\\DeltaOD}_{600}$ values of S. aureus and E. coli for $10\\text{\\textperthousand}$ BCD/PDA/PAM and $15\\%_{0}\\mathrm{BCD/PDA/PAM}$ hydrogels did not increase within measurement time of 96 h, indicating that the bacteria were completely killed. For $5\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel, the $\\mathrm{\\DeltaOD}_{600}$ value of S. aureus began to increase after $24\\mathrm{h}$ and reached a peak value at the $48^{\\mathrm{th}}$ hour, and the $\\mathrm{\\OD}_{600}$ value of E. coli started to increase after $^{12\\mathrm{~h~}}$ and also reached a peak value after $48\\mathrm{h}$ . This showed that the higher the BCD ratio, the better the antibacterial performance, and the longer was the antibacterial duration. The degree of turbidity of bacterial culture solutions was related to the number of bacteria.[11] It was observed that the culture solutions of $10\\text{\\textperthousand}$ BCD/PDA/PAM and $15\\text{\\textperthousand}$ BCD/PDA/PAM hydrogels were clear after $^{48\\mathrm{~h~}}$ , while the culture solutions of $5\\%o\\mathrm{BCD}/$ PDA/PAM hydrogel and the control group were still cloudy after $^{48\\mathrm{h}}$ , which was consistent with the bacterial growth curves (Figure 4b). \n\nA small amount of bacterial solutions was also extracted for live/dead bacteria experiments (Figure 4c) and agar plate experiments (Figure 4c, inset) after $24\\mathrm{h}$ . All bacteria in the group of $15\\%_{o o}\\mathrm{BCD/PDA/PAM}$ hydrogel were basically killed. The group of $10\\%\\mathrm{{BCD/PDA/PAM}}$ hydrogel was scattered with a small amount of bacteria. The group of $5\\%o\\mathrm{BCD/PDA/PAM}$ hydrogel had a moderate amount of bacteria, while the control group contained a large amount of bacteria. The results clearly indicated when the BCD content exceeded $10\\text{\\textperthousand}$ , BCD/PDA/PAM hydrogels showed a highly effective and long-lasting antibacterial effect. \n\n![](images/6b8d592bd4e2420465bb864cc9647b19adbc0f36b654b0f8ee05c06a57f9abc1.jpg) \nFigure 4. a) Growth curves of S. aureus and E. coli as a function of culture time in the groups of $5\\text{\\textperthousand}$ BCD/PDA/PAM, $10\\text{\\textperthousand}$ BCD/PDA/PAM, and $15\\text{\\textperthousand}$ BCD/PDA/PAM hydrogels, and the control group (culture solution). The error bars showed standard deviation $(n=3)$ ). b) Digital photos of the S. aureus ( $10^{5}$ per CFU, 4 mL) and E. coli ( $\\mathsf{10^{5}}$ per CFU, $4m L$ ) solutions cocultured with the hydrogels after $48\\mathrm{~h~}$ . c) Live/dead staining of S. aureus and E. coli after cocultured with the hydrogels for $24\\mathsf{h}$ . The inset digital photos showed the bacterial colonies of S. aureus and E. coli on agar plates for $24\\mathsf{h}$ . \n\n# 2.4. Biocompatibility \n\nGood biocompatibility is another prerequisite for hydrogels used in wound healing.[5,30b] Presence of PDA and positively charged BCD could enhance the cell adhesion, colonization, and proliferation.[26b,28c,d] To examine their cytocompatibility, BCD/PDA/PAM hydrogels with different BCD ratios were exposed to mouse bone marrow-derived mesenchymal stem cells (BMSCs), and presence of viable cells was assessed by cell counting kit-8 reagent (CCK-8) assay.[12,22a] BMSCs were planted on hydrogels and co-cultured for 5 days. $\\mathrm{OD}_{450}$ values showed that the proliferation activity of BMSCs on the experimental groups of BCD/PDA/PAM hydrogels and the control group increased gradually with increasing the cultural time (Figure 5a). More importantly, on day 5, $\\mathrm{OD}_{450}$ values of BCD/PDA/PAM hydrogels were higher than the control group $(p<0.05)$ (Figure 5a). The cell viability of all samples reached almost above $90\\%$ within the testing time, confirming the nontoxic nature of BCD/PDA/PAM hydrogels. On the other hand, the cell viability of all BCD/PDA/PAM hydrogels was above $100\\%$ on day 5 (Figure 5b). The results about $\\mathrm{OD}_{450}$ values and cell activity confirmed that BCD/PDA/PAM hydrogels not only had good cytocompatibility, but also could further promote cell proliferation. This might be because BCD/PDA/PAM hydrogels had celladhesive PDA, electrostatically attractive BCD and biomimetic porous structure, and could facilitate attachment, spreading and growth of cells. To visualize the cell viability more intuitively, the immunofluorescence staining of cultured BMSCs on the hydrogels was used by DAPI and Actin-Tracker Green.[11] BMSCs displayed normal cytoskeleton (green) and cell nuclei (blue) morphologies on all the hydrogels. For the hydrogels, the cells were distributed in a spindle-like shape and formed a higher density of homogeneous cell layer, demonstrating better cell attachment, spreading and retention performances than the control group (Figure 5c). This result was also supported by the live/dead cell assay (Figure S13, Supporting Information). In all groups of BCD/PDA/PAM hydrogels, BMSCs, with a spindle-like morphology, were green and almost no dead cells were seen after incubation on days 1, 3, and 5. In the control group, the majority of BMSCs were also green, although several dead cells were observed. Therefore, the good biocompatibility made BCD/PDA/PAM hydrogels safe candidate materials for hydrogel dressings. \n\n# 2.5. In Vivo Wound Healing \n\nThe ideal wound dressing should have the advantages of promoting healing, anti-infection, and less irritation.[5,11,30b] As shown in Figure S14 (Supporting Information), we evaluated the healingpromoting property of BCD/PDA/PAM hydrogel in a rat’s infected wound model and further evaluated the in-vivo biocompatibility. $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel and BC/PDA/PAM hydrogel were chosen as the experimental groups, while the control group received no hydrogel dressing treatment. Considering the wound in normal rats recovered in 2 weeks,[11,22e,24c] the wound healing was evaluated on day 0, 5, 10, and 15. After hydrogel implantation, wounds covered by hydrogels were observed to heal faster than wound in the control group, and redness and swelling of new tissues became less (Figure 6a). \n\nThis was mainly because of good biocompatibility and cell adhesion derived from catechol groups.[22a,e,28b,31b] Moreover, the multiple network structure constructed with addition of BCD or BC was also beneficial to cell crawling and colonization.[35] In order to visualize the change of wound area during wound healing, wound trace figures were drawn by ImageJ and PowerPoint softwares (Figure 6b). The wound area ratio, which was defined as the ratio of wound healing area to initial defect area, was used to quantitatively evaluate the wound healing rate of different hydrogel-treated wound groups (Figure 6c; Table S2, Supporting Information). $[11,22\\mathrm{e},24\\mathrm{a},\\mathrm{c}]$ The wound healing of experimental groups was significantly better than that of the control group. For example, on day 5, wound treated by $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel showed the smallest wound area ratio among all groups. It was worthy to note that $10\\%\\mathrm{{BCD/PDA/PAM}}$ hydrogel had ${\\approx}15\\%$ and $50\\%$ advantages compared with BC/PDA/PAM hydrogel and the control group $(p<0.001)$ , respectively, indicating a faster healing ratio of wounds treated by $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel. On day 10, $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel remained ${\\approx}13\\%$ (BC/PDA/PAM hydrogel) and $30\\%$ (the control group) advantages in wound area ratio $(p<0.001)$ . Furthermore, on day 15, wound treated by 10‰BCD/PDA/PAM hydrogel showed a complete closure, but BC/PDA/PAM hydrogel group and the control group still had wound area ratios of ${\\approx}8\\%$ and $14\\%$ $(p~<~0.01)$ , respectively. These results clearly indicated that $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel had much better wound healing effect than BC/PDA/PAM hydrogel and the control group. The reason was that the $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel had abundant positive charge, which killed the bacteria in time and reduced the inflammatory response.[4–5,17c,33] In addition, under the continuous stimulation of positive charges, it could promote crawling and proliferation of fibroblastic cells.[28a,c] \n\n# 2.6. Histological Analysis \n\nInfected wound healing is a complex process that involves infiltration of inflammatory cells, accumulation of new capillaries, crawling of fibroblasts and deposition of collagen.[5,11,22e,24c] Histological analysis was used to assess the quality of the regenerated epidermis in defects for the experimental groups of $10\\text{\\textperthousand}$ BCD/PDA/PAM and BC/PDA/PAM hydrogels and the control group without hydrogel dressing treatment on days 5, 10, and 15 (Figure 6d). Inflammatory reaction and cell proliferation were estimated from hematoxylin–eosin (HE) staining. On day 5 of HE staining, inflammatory response was observed in all three groups with inflammatory exudation, new capillary formation, and fibroblast proliferation. The inflammatory response of the control group was the most serious; its connective tissue was loose, and local hemorrhagic focus could be seen. On day 10, the control group still showed a severe inflammatory response, showing a large number of inflammatory cells and new capillary. In the group of BC/PDA/PAM hydrogel, inflammation subsided and inflammatory cells decreased. In sharp contrast, the group of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel had the lightest inflammatory response. On the other hand, although neonatal epidermis could be observed in all three groups, the neonatal epidermis for $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel was thicker and had a longer migration distance. Moreover, for $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel, the boundary between the neonatal epidermis and the surrounding normal epidermis was not obvious, indicating that its healing effect was better. On day 15, the complete epidermal healing was achieved for $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel; a large number of tightly-connected connective tissues including fibroblasts were observed under the skin. On the contrary, in the control group, a large number of inflammatory cells still existed on day 15, demonstrating that the epidermis was not fully healed. In the group of BC/PDA/PAM hydrogel, presence of moderate inflammatory cells was observed on day 15, indicating the healing was insufficient, but its epidermal healing speed was faster than that of the control group. \n\n![](images/2883fc87156fa3e333d2d79021cce3e12025bf856886fc625084def70c3e8b8e.jpg) \nFigure 5. a) CCK-8 assays of BMSCs and b) cell viability for BCD/PDA/PAM hydrogels after 1, 3, and 5 days of culture. The error bars showed standar deviation $(n=3)$ , $^{\\ast}p<0.05$ (one-way ANOVA followed by Bonferroni’s multiple comparison test). c) Fluorescence microscope of BMSCs on the group of BCD/PDA/PAM hydrogels and the control group (culture solution) after 3 days of culture. Scale bar: $200\\upmu\\mathrm{m}$ . \n\n![](images/66bd070577611253cf3512706afa2d94e1d0ded8f7dfb935ab07b6bf96570bc5.jpg) \nFigure 6. a) Representative digital photos of wounds in the groups of BC/PDA/PAM and 10‰BCD/PDA/PAM hydrogels, and the control group without hydrogel dressing treatment from day 0 to day 15. Scale bar: $10\\:\\mathsf{m m}$ . b) Wound traces at different periods. c) Evolution of wound area ratio at different days for each group. The error bars showed standard deviation $(n=3)$ ), $\\because\\mu<0.01$ or $^{***}p<0.001$ (one-way ANOVA followed by Bonferroni’s multiple comparison test). d) HE staining and e) Masson staining on day 5, 10, and 15 of the newly regenerated skin tissues for each group. Scale bar: $100\\upmu\\mathrm{m}$ . \n\nMasson staining was performed to assess the formation and deposition of collagen.[22e,24c] On day 5, the deposition of collagen in the experimental and control groups distributed sparsely. On day 10 and 15, the group of $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogel showed denser granulation tissue deposition and better collagen bundles, as indicated by blue staining in full thickness dermal wounds (Figure 6e). In contrast, both the group of BC/PDA/PAM hydrogel and the control group had poorly-developed shattered collagen bundles and small blue dyeing areas. \n\nThe above results showed that BCD/PDA/PAM hydrogels can play a key role in the healing of infected wound. Adhesion and positive charge enrichment of the hydrogels could promote the crawling, adhesion and reproduction of fibroblasts. The hydrogels also facilitated the production and deposition of collagen. On the other hand, the hydrogels had an antibacterial ability to kill the adhesive bacteria, and thus greatly reduced the inflammatory response and accelerated the healing of wounds. \n\n# 3. Conclusions \n\nWe have successfully fabricated a kind of multifunctional hydrogel dressings with stretchable, adhesive, and antibacterial properties for wound healing. The synthetic steps were optimized to operate at room temperature and avoid use of weak alkaline buffering solution. The mechanical property, antibacterial ability and biocompatibility of BCD/PDA/PAM hydrogels were greatly enhanced because of the introduction of BCD. The well-organized hydrogel systems were gifted with good stretchability, toughness and adhesion. In vitro antibacterial experiments showed that BCD/PDA/PAM hydrogels had high-efficiency and long-lasting antibacterial property. In vitro cytotoxicity indicated that BCD/PDA/PAM hydrogels were nontoxic and promoted cell growth and proliferation. In vivo wound healing on rats for 15 days treated by $10\\%\\mathrm{{BCD/PDA/PAM}}$ hydrogels showed faster tissue regeneration. Collagen deposition was also enhanced with almost no scar formation at the end of 15 days. In conclusion, our BCD/PDA/PAM hydrogels showed high potential in novel wound dressing, especially for the wounds from dynamic active areas, semi-contaminated incisions, infected surgical wounds, and other wounds that require frequent replacement of dressings. \n\n# 4. Experimental Section \n\nPreparation of $B C\\cdot B r$ : The water in BC water-dispersion was fully replaced by dimethylformamide (DMF) by centrifugation. BC solution $\\cdot520~\\mathsf{m g}$ in $60~\\mathsf{m L}$ DMF) was purged with nitrogen $(\\mathsf{N}_{2})$ for $30~\\mathrm{min}$ , followed by addition of $3.2~\\mathrm{mL}$ triethylamine. The mixture was stirred in an ice bath, and $4~\\mathrm{mL}$ 2-bromisobutyryl bromide was added in drops within $30~\\mathrm{min}$ . The mixture was further kept at $0^{\\circ}\\mathsf C$ for $15\\mathrm{\\min}$ and then stirred at room temperature for $24\\ h$ . The targeted BC-Br was obtained by washing thoroughly with ethanol and deionized (DI) water to remove residual reactants. The final BC-Br was stored in a $4^{\\circ}C$ refrigerator for later use. \n\nPreparation of BCD: According to the literature,[17c,36] BC-Br $(750\\mathrm{mg})$ and DADMAC $(70m L)$ were dissolved in water–methanol mixtures $(50{:}50~\\mathrm{\\v/v},~40~\\mathrm{\\mL})$ ) in a Schlenk flask. The solution was purged with $\\mathsf{N}_{2}$ for 30 min and then CuBr $(20.2~\\mathsf{m g})$ and $N,N,N,N,N.$ pentamethyldiethylenetriamine $(62\\upmu\\up L)$ were added immediately. The mixture was still stirred with protection of ${\\sf N}_{2}$ for another 10 min and the reaction was carried out at $60^{\\circ}C$ for $24\\ h$ with stirring. The final BCD was obtained by washing thoroughly with DI water and ethanol, and then stored in a $4^{\\circ}C$ refrigerator for later use. \n\nPreparation of Hydrogels: The BCD/PDA/PAM hydrogels were prepared via a two-step process: 1) BCD was firstly dispersed in the aqueous dopamine solution. Then, APS was added into the solution to initiate prepolymerization of dopamine. The mixture was stirred at room temperature for 25 min as the BCD/PDA solution turns brown. 2) Acrylamide, N,Nmethylene bisacrylamide and tetramethylethylenediamine were added to BCD/PDA solution under stirring for $\\mathsf{10}\\mathsf{m i n}$ . The final mixture was poured into a mold and kept at $60^{\\circ}C$ for $3h$ to form hydrogel. Finally, the obtained hydrogel was soaked in DI water and $75\\%$ ethanol to remove the excess monomers and dried at room temperature for later use. The weight percentages of all chemicals for various BCD/PDA/PAM hydrogels were listed in Table S1 (Supporting Information). \n\nCharacterization: FT-IR spectra were obtained by an FT-IR spectrometer (TENSOR 27, BRUKER, Germany). Zeta potential of hydrogels was measured by using a Zetasizer Nano-ZS PN3702 system (Malvern Instruments, Worcestershire, England). Surface morphology, internal structure, and element mapping of hydrogels were analyzed by using a field emission scanning electron microscope (FE-SEM, Hitachi S-4800) after lyophilization. XPS (Thermo-VG Scientific ESCALAB 250Xi) with a standard Al Ka X-ray source (1486.8 eV) was used to analyze the chemical structure. Selfhealing test was done by using a simple cut-link model. Compressive, tensile, and adhesive tests were performed on a universal mechanical testing machine (WD-5A, Guangzhou Experimental Instrument Factory, China). The adhesion performance of BCD/PDA/PAM hydrogels were proven by covering on human skin. The cell compatibility of the hydrogels was confirmed before the experiments. These experiments were carried out with the full, informed consent from human subjects. \n\nAntibacterial Property: To investigate the antibacterial activity of BCD/PDA/PAM hydrogels, S. aureus and E. coli were used for the tests. Bacterial growth curve, colonies forming units (CFU) test and live/dead bacteria assay were evaluated. Details were provided in the Supporting Information. \n\nIn Vitro Cytotoxicity: The BMSCs (SCSP-405) were used to evaluate the cytotoxicity and cell attachment of BCD/PDA/PAM hydrogels. Details were provided in the Supporting Information. \n\nIn Vivo Wound Healing: The BC/PDA/PAM and $10\\text{\\textperthousand}$ BCD/PDA/PAM hydrogels were implanted into full-thickness wounds of a rat model to evaluate their wound healing performances. Details were provided in the Supporting Information. \n\nHistological Analysis: On $5^{\\mathrm{th}}$ , $\\mathsf{70^{t h}}$ , and $\\mathsf{75^{t h}}$ day postsurgery, the wounds with surrounding tissue were collected carefully, fixed in $10\\%$ paraformaldehyde solution, and embedded in paraffin for routine histological processing. According to the standard protocols, tissues with $5\\:\\mathsf{m m}$ thickness were prepared. HE staining was used to assess the morphology and tissue regeneration. Masson staining was used to assess collagen deposition. \n\nStatistical Analysis: Statistical analysis was performed using SPSS software (version 22.0 for Windows; SPSS, Chicago, IL, USA). Data was expressed as mean $\\pm$ standard deviation (SD). Statistical differences were determined using one-way analysis of variance (ANOVA) followed by a Bonferroni post hoc test for multiple comparisons. The levels of significance were labeled with $\\because p<0.05$ , $\\ddot{\\cdots}\\dot{p}<0.01$ , and $\\because1<\\ast<\\vert1<0.00\\vert$ . \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nZ.Y. and R.H. contributed equally to this work. This work was supported by Science and Technology Program of Guangzhou (202002020041), National Natural Science Foundation of China (51925308, U1601206, 51872336, 51703254). All rats were treated strictly according to the Laboratory Animal Care and Use Guidelines. All rat experiments were approved by the Animal Ethics Committee of South China Agricultural University. Ethical approval for this study was received from the Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, P. R. China. This study was performed in accordance with the Ethical Standards of the World Medical Association Declaration of Helsinki. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Keywords \n\nadhesive, antibacterial dressings, hydrogel dressings, stretchable materials, wound healing \n\nReceived: September 23, 2020 \nRevised: November 24, 2020 \nPublished online: March 5, 2021 \n\n[1] a) L. Shi, X. Liu, W. Wang, L. Jiang, S. Wang, Adv. Mater. 2019, 31, 1804187; b) Z. Xu, S. Han, Z. Gu, J. Wu, Adv. Healthcare Mater. 2020, 9, 1901502. \n[2] a) D. A. Sleet, K. D. Liller, K. Hopkins, D. D. White, Am. J. Health. Behav. 2004, 7, S6; b) K. L. LaPlante, A. R. Caffrey, K. Gupta, N. Engl. J. Med. 2010, 362, 1540. [3] T. Chen, Y. Chen, H. U. Rehman, Z. Chen, Z. Yang, M. Wang, H. Li, H. Liu, ACS Appl. Mater. Interfaces 2018, 10, 33523. \n[4] X. Zhao, B. Guo, H. Wu, Y. Liang, P. X. Ma, Nat. Commun. 2018, 9, 2784. [5] J. Qu, X. Zhao, Y. Liang, T. Zhang, P. X. Ma, B. Guo, Biomaterials 2018, 183, 185. [6] M. D. Konieczynska, J. C. Villa-Camacho, C. Ghobril, M. Perez-Viloria, K. M. Tevis, W. A. Blessing, A. Nazarian, E. K. Rodriguez, M. W. Grinstaff, Angew. Chem., Int. Ed. 2016, 55, 9984. \n[7] Y. Zhu, Z. Cankova, M. Iwanaszko, S. Lichtor, M. Mrksich, G. A. Ameer, Proc. Natl. Acad. Sci. USA 2018, 115, 6816. \n[8] H. Yuk, C. E. Varela, C. S. Nabzdyk, X. Mao, R. F. Padera, E. T. Roche, X. Zhao, Nature 2019, 575, 169. \n[9] X. Zhao, H. Wu, B. Guo, R. Dong, Y. Qiu, P. X. Ma, Biomaterials 2017, 122, 34. \n[10] Y. Zhao, Z. Li, S. Song, K. Yang, H. Liu, Z. Yang, J. Wang, B. Yang, Q. Lin, Adv. Funct. Mater. 2019, 29, 1901474. \n[11] D. Gan, W. Xing, L. Jiang, J. Fang, C. Zhao, F. Ren, L. Fang, K. Wang, X. Lu, Nat. Commun. 2019, 10, 1487. \n[12] H. Qiao, P. Qi, X. Zhang, L. Wang, Y. Tan, Z. Luan, Y. Xia, Y. Li, K. Sui, ACS Appl. Mater. Interfaces 2019, 11, 7755. \n[13] a) P. V. AshaRani, G. Low Kah Mun, M. P. Hande, S. Valiyaveettil, ACS Nano 2009, 3, 279;. b) Y. H. Lee, F. Y. Cheng, H. W. Chiu, J. C. Tsai, C. Y. Fang, C. W. Chen, Y. J. Wang, Biomaterials 2014, 35, 4706. \n[14] a) B. P. Lee, P. B. Messersmith, J. N. Israelachvili, J. H. Waite, Annu. Rev. Mater. Res. 2011, 41, 99;. b) Y. Fu, P. Ren, F. Wang, M. Liang, W. Hu, N. Zhou, Z. Lu, T. Zhang, J. Mater. Chem. B 2020, 8, 2148. \n[15] P. L. Farber, B. Hochman, F. Furtado, L. M. Ferreira, Med. Hypotheses 2014, 82, 199. \n[16] a) G. F. Picheth, C. L. Pirich, M. R. Sierakowski, M. A. Woehl, C. N. Sakakibara, C. F. de Souza, A. A. Martin, R. da Silva, R. A. de Freitas, Int. J. Biol. Macromol. 2017, 104, 97;. b) M. Ul-Islam, T. Khan, J. K. Park, Carbohydr. Polym. 2012, 89, 1189. \n[17] a) P. S. Lacerda, A. M. Barros-Timmons, C. S. Freire, A. J. Silvestre, C. P. Neto, Biomacromolecules 2013, 14, 2063;. b) X. Liu, Y. Li, Z. Chu, Y. Fang, H. Zheng, J. Appl. Biomater. Funct. Mater. 2018, 16, 163; c) S. Lu, Z. Tang, W. Li, X. Ouyang, S. Cao, L. Chen, L. Huang, H. Wu, Y. Ni, Cellulose 2018, 25, 7261. \n[18] P. S. Zhong, N. Widjojo, T.-S. Chung, M. Weber, C. Maletzko, J. Membr. Sci. 2012, 417–418, 52. \n[19] P. S. Liu, Q. Chen, X. Liu, B. Yuan, S. S. Wu, J. Shen, S. C. Lin, Biomacromolecules 2009, 10, 2809. \n[20] a) H. S. Kim, Y. J. Son, W. Mao, K. W. Leong, H. S. Yoo, Nano Lett. 2018, 18, 314;. b) B. Xu, C. Feng, X. Huang, Nat. Commun. 2017, 8, 333. \n[21] a) N. Li, Q. Yue, B. Gao, X. Xu, Y. Kan, P. Zhao, J. Taiwan Inst. Chem. E 2018, 91, 499; b) S. H. Park, S. Wei, B. Mizaikoff, A. E. Taylor, C. Favero, C. H. Huang, Environ. Sci. Technol. 2009, 43, 1360. \n[22] a) L. Han, M. Wang, P. Li, D. Gan, L. Yan, J. Xu, K. Wang, L. Fang, C. W. Chan, H. Zhang, H. Yuan, X. Lu, ACS Appl. Mater. Interfaces 2018, 10, 28015; b) L. Han, X. Lu, M. Wang, D. Gan, W. Deng, K. Wang, L. Fang, K. Liu, C. W. Chan, Y. Tang, L. T. Weng, H. Yuan, Small 2017, 13, 1601916; c) J. Miao, H. Liu, W. Li, X. Zhang, Langmuir 2016, 32, 5365;. d) W. Cheng, X. Zeng, H. Chen, Z. Li, W. Zeng, L. Mei, Y. Zhao, ACS Nano 2019, 13, 8537;. e) L. Han, L. Yan, K. Wang, L. Fang, H. Zhang, Y. Tang, Y. Ding, L.-T. Weng, J. Xu, J. Weng, Y. Liu, F. Ren, X. Lu, NPG Asia Mater. 2017, 9, e372. \n[23] T. Liu, B. Lee, B. G. Kim, M. J. Lee, J. Park, S. W. Lee, Small 2018, 14, 1801236. \n[24] a) D. Gan, T. Xu, W. Xing, X. Ge, L. Fang, K. Wang, F. Ren, X. Lu, Adv. Funct. Mater. 2019, 29, 1805964; b) S. Liang, Y. Zhang, H. Wang, Z. Xu, J. Chen, R. Bao, B. Tan, Y. Cui, G. Fan, W. Wang, W. Wang, W. Liu, Adv. Mater. 2018, 30, 1704235; c) L. Han, X. Lu, K. Liu, K. Wang, L. Fang, L. T. Weng, H. Zhang, Y. Tang, F. Ren, C. Zhao, G. Sun, R. Liang, Z. Li, ACS Nano 2017, 11, 2561. \n[25] L. Huang, X. Du, S. Fan, G. Yang, H. Shao, D. Li, C. Cao, Y. Zhu, M. Zhu, Y. Zhang, Carbohydr. Polym. 2019, 221, 146. \n[26] a) G. B. Schneider, A. English, M. Abraham, R. Zaharias, C. Stanford, J. Keller, Biomaterials 2004, 25, 3023;. b) M. Dadsetan, A. M. Knight, L. Lu, A. J. Windebank, M. J. Yaszemski, Biomaterials 2009, 30, 3874;. c) O. V. Bondar, D. V. Saifullina, Shakhmaeva, II, Mavlyutova, II, T. I. Abdullin, Acta Nat. 2012, 4, 78;. d) H. Zheng, M. Gao, Y. Ren, R. Lou, H. Xie, W. Yu, X. Liu, X. Ma, ACS Appl. Mater. Interfaces 2016, 8, 19333. \n[27] A. Schulz, A. Katsen-Globa, E. J. Huber, S. C. Mueller, A. Kreiner, N. Putz, M. M. Gepp, B. Fischer, F. Stracke, H. von Briesen, J. C. Neubauer, H. Zimmermann, J. Mater. Sci. Mater. Med. 2018, 29, 105. \n[28] a) S. S. Behera, U. Das, A. Kumar, A. Bissoyi, A. K. Singh, Int. J. Biol. Macromol. 2017, 98, 329;. b) S. Staehlke, J. Lehnfeld, A. Schneider, J. B. Nebe, R. Muller, Mater. Sci. Eng., C 2019, 101, 190;. c) S. Hattori, J. D. Andrade, J. B. Hibbs, D. E. Gregonis, R. N. King, J. Colloid Interface Sci. 1985, 104, 72; d) P. C. Câmara, R. Balaban, M. Hedayati, K. Popat, A. Martins, M. Kipper, RSC Adv. 2019, 9, 25836. \n[29] X. Jing, H. Y. Mi, Y. J. Lin, E. Enriquez, X. F. Peng, L. S. Turng, ACS Appl. Mater. Interfaces 2018, 10, 20897. \n[30] a) L. Han, P. Li, P. Tang, X. Wang, T. Zhou, K. Wang, F. Ren, T. Guo, X. Lu, Nanoscale 2019, 11, 15846;. b) G. Chen, Y. Yu, X. Wu, G. Wang, J. Ren, Y. Zhao, Adv. Funct. Mater. 2018, 28, 1801386. \n[31] a) B. K. Ahn, S. Das, R. Linstadt, Y. Kaufman, N. R. MartinezRodriguez, R. Mirshafian, E. Kesselman, Y. Talmon, B. H. Lipshutz, J. N. Israelachvili, J. H. Waite, Nat. Commun. 2015, 6, 8663;. b) Q. Guo, J. Chen, J. Wang, H. Zeng, J. Yu, Nanoscale 2020, 12, 1307. \n[32] B. J. Kim, D. X. Oh, S. Kim, J. H. Seo, D. S. Hwang, A. Masic, D. K. Han, H. J. Cha, Biomacromolecules 2014, 15, 1579. \n[33] C. Wang, H. Niu, X. Ma, H. Hong, Y. Yuan, C. Liu, ACS Appl. Mater. Interfaces 2019, 11, 34595. \n[34] P. Pal, A. Banerjee, U. Halder, J. P. Pandey, G. Sen, R. Bandopadhyay, J. Polym. Environ. 2018, 26, 3272. \n[35] H. Ullah, M. Badshah, A. Correia, F. Wahid, H. A. Santos, T. Khan, Curr. Pharm. Des. 2019, 25, 3692. \n[36] F. Gu, H. Dong, Y. Li, Z. Sun, F. Yan, Macromolecules 2014, 47, 6740. " + }, + { + "id": "10.1007_s40820-021-00635-1", + "DOI": "10.1007/s40820-021-00635-1", + "DOI Link": "http://dx.doi.org/10.1007/s40820-021-00635-1", + "Relative Dir Path": "mds/10.1007_s40820-021-00635-1", + "Article Title": "Environmentally Friendly and Multifunctional Shaddock Peel-Based Carbon Aerogel for Thermal-Insulation and Microwave Absorption", + "Authors": "Gu, WH; Sheng, JQ; Huang, QQ; Wang, GH; Chen, JB; Ji, GB", + "Source Title": "nullO-MICRO LETTERS", + "Abstract": "HighlightsThe eco-friendly shaddock peel-derived carbon aerogels were prepared by a freeze-drying method.Multiple functions such as thermal insulation, compression resistance and microwave absorption can be integrated into one material-carbon aerogel.Novel computer simulation technology strategy was selected to simulate significant radar cross-sectional reduction values under real far field condition..AbstractEco-friendly electromagnetic wave absorbing materials with excellent thermal infrared stealth property, heat-insulating ability and compression resistance are highly attractive in practical applications. Meeting the aforesaid requirements simultaneously is a formidable challenge. Herein, ultra-light carbon aerogels were fabricated via fresh shaddock peel by facile freeze-drying method and calcination process, forming porous network architecture. With the heating platform temperature of 70 degrees C, the upper surface temperatures of the as-prepared carbon aerogel present a slow upward trend. The color of the sample surface in thermal infrared images is similar to that of the surroundings. With the maximum compressive stress of 2.435 kPa, the carbon aerogels can provide favorable endurance. The shaddock peel-based carbon aerogels possess the minimum reflection loss value (RLmin) of - 29.50 dB in X band. Meanwhile, the effective absorption bandwidth covers 5.80 GHz at a relatively thin thickness of only 1.7 mm. With the detection theta of 0 degrees, the maximum radar cross-sectional (RCS) reduction values of 16.28 dB m(2) can be achieved. Theoretical simulations of RCS have aroused extensive interest owing to their ingenious design and time-saving feature. This work paves the way for preparing multi-functional microwave absorbers derived from biomass raw materials under the guidance of RCS simulations.", + "Times Cited, WoS Core": 431, + "Times Cited, All Databases": 449, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000637357900001", + "Markdown": "# Environmentally Friendly and Multifunctional Shaddock Peel‑Based Carbon Aerogel for Thermal‑Insulation and Microwave Absorption \n\nReceived: 30 January 2021 \nAccepted: 26 February 2021 \n$\\circledcirc$ The Author(s) 2021 \n\nWeihua $\\mathbf{Gu}^{1}$ , Jiaqi Sheng2, Qianqian Huang1, Gehuan Wang1, Jiabin Chen1, Guangbin Ji1 \\* \n\n# HIGHLIGHTS \n\n•\t The eco-friendly shaddock peel-derived carbon aerogels were prepared by a freeze-drying method. \n•\t Multiple functions such as thermal insulation, compression resistance and microwave absorption can be integrated into one materialcarbon aerogel. \n•\t Novel computer simulation technology strategy was selected to simulate significant radar cross-sectional reduction values under real far field condition. \n\nABSTRACT  Eco-friendly electromagnetic wave absorbing materials with excellent thermal infrared stealth property, heat-insulating ability and compression resistance are highly attractive in practical applications. Meeting the aforesaid requirements simultaneously is a formidable challenge. Herein, ultra-light carbon aerogels were fabricated via fresh shaddock peel by facile freeze-drying method and calcination process, forming porous network architecture. With the heating platform temperature of $70^{\\circ}\\mathrm{C}$ , the upper surface temperatures of the as-prepared carbon aerogel present a slow upward trend. The color of \n\n![](images/1f432802a2ecb6c15153db221b8f6c7b337ca6756943828063664d9d2f61ea15.jpg) \n\nthe sample surface in thermal infrared images is similar to that of the surroundings. With the maximum compressive stress of $2.435\\mathrm{kPa}$ , the carbon aerogels can provide favorable endurance. The shaddock peel-based carbon aerogels possess the minimum reflection loss value $(R L_{\\mathrm{min}})$ of $-29.50\\mathrm{dB}$ in X band. Meanwhile, the effective absorption bandwidth covers $5.80\\mathrm{GHz}$ at a relatively thin thickness of only $1.7\\mathrm{mm}$ . With the detection theta of $0^{\\circ}$ , the maximum radar cross-sectional (RCS) reduction values of $16.28\\mathrm{dB}\\mathrm{m}^{2}$ can be achieved. Theoretical simulations of RCS have aroused extensive interest owing to their ingenious design and time-saving feature. This work paves the way for preparing multi-functional microwave absorbers derived from biomass raw materials under the guidance of RCS simulations. \n\nKEYWORDS  Microwave absorption; Thermal insulation; Carbon aerogel; Radar cross-sectional simulation; Multi-function \n\n# 1  Introduction \n\nRecently, various materials to solve the problem of severe electromagnetic pollution have been widely researched in depth [1, 2]. Generally speaking, these materials can be broadly divided into two categories: magnetic absorbing materials and dielectric absorbers. Due to unsatisfied high density, magnetic absorbers cannot meet lightweight requirements [3, 4]. Besides, permeability usually decreases a lot with the increase of frequency because of Snoek limit, which impairs microwave attenuation ability [5, 6]. Thus, dielectric absorbing materials are ideal choices for the purpose of light weight. \n\nDespite a variety of dielectric microwave absorbing materials and electromagnetic interference (EMI) shielding materials such as graphene [7, 8], MXene [9, 10], and carbon nanotubes [11, 12] have been investigated by academicians. However, most of the works merely focus on expanding bandwidth and improving reflection loss intensity, instead of quickly adapting complex practical environment and preliminarily designing nano/micro/macro-structure as well as predictably simulating radar cross section (RCS) [13]. For instance, Cu nanowire $@$ graphene core–shell aerogels synthesized by Wu et al. exhibit enhanced mechanical property, including robustness, strength and modulus [14]. This kind of stable material with three-dimensional (3D) network structures has outstanding durability, which can be potential applicants for industrial manufacture. Liu et al. prepared MXene/polyimide aerogels with splendid thermal insulation and resistance performance, which can be used as ideal candidates in high-temperature working environment [15]. In addition, our group previously fabricated three-dimensional ZIF-67-coated melamine foams with excellent thermal infrared stealth property, effectively preventing targets from being detected [16]. More importantly, Chen and his co-workers synthesized mesoporous carbon fibers and used computer simulation technology (CST) to simulate important radar cross-sectional (RCS) reduction data, this greatly contributes to the pre-design of macrostructure and pre-choice of materials [17]. Therefore, multifunctional applications and elaborate design as well as numerical simulation have promising prospects for the microwave absorbing materials. \n\nUnsatisfactorily, poisonous, harmful reagents and ingredients are often utilized to prepare microwave absorbers and EMI shielding materials [18]. Thanks to low toxicity and adequate sources, green biomass materials and their derivatives have attracted extensive attention of the researchers. For example, Wang et al. fabricated annealed sugarcane/rGO hybrid foams with superior EMI shielding effectiveness of $53~\\mathrm{dB}$ [19]. Qiu and his co-workers successfully prepared walnut shell-derived porous carbon microwave absorbing materials with a strong intensity of $\\mathbf{-42.4dB}$ at the matching thickness of $2~\\mathrm{mm}$ [20]. Interestingly, Dong et al. synthesized wood-based microwaving absorbers with the optimum absorption frequency range of $5.26\\:\\mathrm{GHz}$ [21]. Besides, our group also carried out deepgoing study about biomass-based microwave absorbing materials like wheat flour [22] and cotton [23]. Taking environment protection and sustainable development into consideration, we employed eco-friendly shaddock peel as origin of carbon in this work. Since shaddock peel is renewable and low-cost, this kind of biological waste can be made full use of. Benefiting from the threedimensional porous network structure and dielectric component, fresh shaddock peel derived conductive carbon aerogels inherit unexceptional advantages, including efficient dielectric loss capacity, superb light weight characteristic and superior thermal insulation property [24]. In addition, high resistance to compression is in favor of reusing, which make biomass-based carbon aerogels can afford the high requirement of ideal microwave absorbers. \n\nIn this work, we reported shaddock peel-derived carbon aerogel via freeze-drying method and subsequent annealing procedure. As a rule, facile freeze-drying method guarantees the integral 3D skeleton architecture with excellent electrical conductivity, contributing to strong dielectric loss ability [25]. On one hand, abundant holes left by sublimation of water in raw shaddock peel can enhance the number of dipoles as well as dipole polarization, on the other hand, the high porosity can give rise to light feature in weight [26]. Therefore, the as-synthesized sample achieves the effective bandwidth of $5.80\\:\\mathrm{GHz}$ at only $1.7\\ \\mathrm{mm}$ . Furthermore, multiple functions, such as outstanding thermal stealth, heat insulation and compression resistance, make it possible for microwave absorbing materials to be efficiently applied in a variety of complex situation. Similar colors can be seen from the sample surface and the surroundings in thermal infrared images, indicating excellent thermal stealth property of the carbon aerogel. When setting $70^{\\circ}\\mathrm{C}$ of the heating platform, the surface temperatures of the biomass-based carbon aerogel show a slow upward trend of 31.8, 33.7, and $35.3~^{\\circ}\\mathrm{C}$ within $3\\mathrm{min}$ , which can be attributed to effective thermal insulation performance. With regard to mechanical property, the shaddock peel-based aerogels can provide the maximum compressive stress of $2.435\\mathrm{kPa}$ at a strain of $80\\%$ . In addition, the optimum RCS reduction values of the carbon aerogel can be obtained as $16.28\\mathrm{dB}\\mathrm{m}^{2}$ when setting the detection theta as $0^{\\circ}$ . Last but not least, CST simulation strategy can not only give design train of thought of microwave absorbers, but also save the experiment time of actual operation. \n\n# 2  \u0007Experimental \n\n# 2.1  \u0007Preparation of Shaddock Peel‑Based Aerogel \n\nFresh shaddock purchased from school fruit store. Firstly, the entire grapefruit outer skin was peeled off and cleaned by a certain amount of deionized water and then gently wiped with non-crumb paper towels. Figure 1a exhibits the facile experiment process, which can be summarized in two steps. Step I: the prepared pomelo peel was immediately put into freeze-drying machine with a pre-freezing process for $6\\textup{h}$ and a subsequent drying procedure for $^{48\\mathrm{~h~}}$ . Step II: the as-made grapefruit precursor was transferred into corundum porcelain boat and then annealed at 700, 800, and $900^{\\circ}\\mathrm{C}$ for $2\\mathfrak{h}$ under Ar atmosphere with a heating rate of $2{\\mathrm{~}}^{\\circ}{\\bf C}{\\mathrm{~min}}^{-1}$ , which can be labeled as G700, G800, and G900, respectively. \n\n![](images/40177ea6120cff97f607599a459f2b1b830dccd9348d7b0e120784caaed82d57.jpg) \nFig. 1   a Schematic of the formation process of shaddock peel-based aerogel. b, c SEM images of the 3D lightweight precursor. d Digital photograph of G800 sample on petals. e–j SEM images of G700, G800, and G900 \n\n# 2.2  \u0007Materials Characterization \n\nThe microstructures of the samples were achieved by field emission scanning electron microscopy (FE-SEM, Hitachi S4800). The composition and phase of the 3D porous specimens were carried out by a Bruker D8 ADVANCE X-ray diffractometer (XRD) equipped with $\\mathrm{Cu}~\\mathrm{K}\\alpha$ radiation $(\\lambda=1.5604\\mathrm{~\\AA~}$ ). A confocal Renishaw inVia Raman microscope was used to characterize the degree of carbonization of the as-prepared 3D porous aerogels. Electrochemical impedance spectroscopy (EIS) test of the samples was implemented by a CHI 660D electrochemical workstation to investigate the electron transport characteristics. Selfassembly tesla wireless transmission device was adopted to indirectly observe the electrical conductivity of the shaddock peel-derived carbon aerogels. The information of the pore volume, porosity and pore diameter of the samples can be obtained via mercury intrusion method using a MicroActive AutoPore V 9600 2.03.00 machine. The digital images of thermal insulation performance of the lightweight biomass-based aerogels were photographed by a thermal infrared imaging device (TVS-2000MK). The compression resistance of the shaddock peel-based 3D porous aerogel $(2\\times2\\times0.5\\mathrm{cm}^{3})$ was tested by an electronic universal testing machine (CMT5105, XinSanSi Enterprise Development Co. Ltd., China). During the frequency range of $2{\\mathrm{-}}18\\operatorname{GHz}$ , electromagnetic parameters of complex permeability and permittivity were recorded by an Agilent PNA N5244A vector network analyzer using coaxial-line method at room temperature. In this test, the toroidal rings were prepared by mixing $20~\\mathrm{wt}\\%$ intact shaddocks peel-based aerogel with $80\\mathrm{\\wt\\\\%}$ paraffin in a precise mold $\\left(\\varphi_{\\mathrm{out}};7.00\\:\\mathrm{mm}\\right.$ , $\\varphi_{\\mathrm{in}}$ : $3.04\\mathrm{mm}$ ). \n\n# 2.3  \u0007RCS Simulation \n\nTake actual far-field response of the shaddock peel-based aerogel materials into consideration, CST Studio Suite 2019 was used for simulating the RCS of the microwave absorber. According to widely accepted metal back model, the simulation model of the specimens was established as a square $(20\\times20~\\mathrm{cm}^{2},$ ) with dual layers. In detail, the upper set as $1.7\\ \\mathrm{mm}$ signifies the absorbing layer and the bottom set as $1.0\\ \\mathrm{mm}$ is the perfect conductive layer (PEC). The shaddock peel-based aerogel-PEC model plate is placed on the $X$ -O-Y plane, and linear polarized plane electromagnetic waves incident from the positive direction of the $Z$ axis to the negative direction of the Z-axis. Meanwhile, the direction of electric polarization propagation is along the $X$ -axis. With the open boundary conditions setting in all directions, the chosen field monitor frequency was $12\\mathrm{GHz}$ . It is generally accepted that the scattering directions can be determined by theta and phi in spherical coordinates. The RCS values can be described as follows[27]: \n\n$$\n\\sigma\\left(\\mathrm{d}{\\bf B}\\mathrm{m}^{2}\\right)=10\\mathrm{log}\\big(\\big(4\\pi S/\\lambda^{2}\\big)|E_{s}/E_{i}|\\big)^{2}\n$$ \n\nHerein, $S,\\lambda,E_{s}$ and $E_{i}$ represent the area of the target object simulation model, the wavelength of electromagnetic wave, the electric field intensity of scattered wave and the incident wave, respectively. \n\n# 3  \u0007Results and Discussion \n\n# 3.1  \u0007Characterization of Shaddock Peel‑Derived Carbon Aerogel \n\nAs depicted in Fig. 1b, c, the fresh shaddock peel-based precursor shows integrated three-dimensional porous micro-structures without any skeleton fracture, which can be ascribed to the superiority of freeze-drying method. After high temperature pyrolysis, the shaddock peel derived specimen with density of only $0.09\\mathrm{gcm}^{-3}$ can rest quietly on the fragile flower petals (Fig. 1d), indicating the lightweight feature of the as-prepared aerogel. Compared with precursors, the size of 3D porous architecture shrinks to some extent, which can be seen from Fig. 1e–j. Fortunately, the threedimensional network can still exist even after calcination process, further revealing the advantage of freeze-drying method on the formation of 3D porous network structure. In addition, this interconnected structure can bring abundant electron-transport channels and plenty of pores between nodes and ligaments, which can provide more space for microwave multiple scatter propagation. \n\nXRD patterns of G700/G800/G900 samples are provided in Fig. 2a. Obviously, two broad peaks lie in $24.5^{\\circ}$ and $43.4^{\\circ}$ can be well-indexed to the (002) and (100) planes of graphitized carbon. Raman spectra in Fig. 2b further demonstrate the graphitization degree of all shaddock peel-based aerogel products. The prominent peaks at 1350 and $1580~\\mathrm{cm}^{-1}$ correspond to D-band and G-band, which are related to disordered carbon and $s p^{2}$ -bonded carbon, respectively [28]. As for all products, the $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ values (intensity ratio of D-band to G-band) are 1.01, 1.00, and 1.01, indicating the same high graphitization degree [29]. That is to say, calcination treatment with different high temperatures has little influence on the bonding state and conductivity of shaddock peel-based carbon aerogel. In order to further investigating electrical conductivity, the electronic impedance of $\\mathrm{G700/G800/G900}$ has been measured. As can be seen from the Nyquist plots in Fig. 2c, the size of the semicircles has a descending trend from G700 to G800 and G900, revealing the order of electronic transfer resistance is $\\mathbf{G}700>\\mathbf{G}800>\\mathbf{G}900$ [30]. Namely, the order of electrical conductivity is $\\mathrm{G900>G800>G700}$ . In addition, circuit connection and Tesla wireless transmission experiments demonstrate the steady electrical conductivity of the G800 sample, which are shown in Fig. 2d–f. Obviously, two conductive clips with G800 specimen are directly connected in series to a light-emitting diode (LED) and two small AA-size batteries (Fig. 2d), this LED lamp can keep a stable green brightness. With respect to the Tesla coil (Fig. 2e, f), it is a boosting transformer. By boosting the voltage of the transformer, the primary coil passes a changing current and creates a high voltage in the secondary coil. Essentially, Tesla wireless transmission is a mode of energy transmission via magnetic resonance rather than direct physical contact between the power supply object and electricity demand object [31]. The corresponding principle is that the electrical energy sender and receiver coils constitute a combined magnetic resonance system. When the frequency of the oscillating magnetic field generated by the sending end is consistent with the natural frequency of the receiving end, the receiving end resonates, thus realizing the energy transmission. In a high voltage electric field, neon gas in a neon bubble gives off light by glow discharge. Thus, the neon bulb in Fig. 2e can present an orange light because of strong glow effect. However, if an electric conductor is placed between the power supply and demand objects, the resonance balance will be destroyed and then the electric energy transmission will be blocked. Namely, the neon bulb can not apply glow effect under this circumstance. As depicted in Fig. 2f, due to the excellent electrical conductivity, the shaddock peel derived G800 carbon aerogel can hinder power transfer, which may lead to more dielectric loss. In addition, the unique three-dimensional microcellular structure of the asprepared carbon aerogels can be further found in Fig. 2g–i. The relevant mercury intrusion and extrusion curves of the as-prepared carbon aerogels exhibit that the total pore volume of $\\mathrm{G700/G800/G900}$ samples are 3.07, 4.01, and $4.12~\\mathrm{{mL}~g^{-1}}$ , respectively. Meanwhile, for $\\mathrm{G700/G800/}$ G900 specimens, their porosities are $78.70\\%$ , $83.53\\%$ , and $83.22\\%$ , separately, indicating the cellular structure and lightweight feature of the shaddock peel-based carbon aerogels. As illustrated in the pore size distribution curves in Fig. $2\\mathrm{g-i}$ , the pore diameters of the as-obtained specimens mainly distribute from nanoscale to microscale, further revealing the 3D porous architecture and lightweight characteristic of the carbon aerogel. \n\n![](images/64347c853a0ae9dc179eb794d566b2a401f75b4c23ceb2c35888b116ae460a5c.jpg) \nFig. 2   a XRD patterns of the obtained samples. b Raman spectra of G700/G800/G900. c Nyquist plots of the samples. d–f Digital images of circuit connection and Tesla wireless transmission experiments. g–i Mercury intrusion and extrusion curves of the as-prepared carbon aerogels with the insert of pore size distributions \n\n# 3.2  \u0007Thermal Insulation Performance \n\nTraditional microwave absorbing powders lack multifunctional features, such as thermal infrared stealth property, heat insulation function, and mechanical performance. Fortunately, due to the superiority of the 3D porous skeleton structure, the shaddock peel-derived carbon aerogels are highly desired for complex application environment. As shown in Fig. 3a–c, taking one piece of each sample and placing them on the platform with the set heating temperature of $70^{\\circ}\\mathrm{C}$ separately. Evidently, the upper surface of all products appears dark, which is similar to the color of surrounding environment. This unique phenomenon reveals the outstanding thermal infrared stealth function of the 3D porous network. The thermal infrared images recorded the temperature variation of the sample top surface for $3\\mathrm{min}$ . \n\n![](images/7aff40a17f67b148c6003424ca563db8b51870e8c8583681b97f6dc58fc17134.jpg) \nFig. $\\textbf{3}\\mathbf{a}-\\mathbf{c}$ Thermal infrared images of G700/G800/G900 samples captured at $1/2/3\\ \\mathrm{min}$ , respectively. d Heating time versus sample temperature line charts of the biomass-based aerogels. e Schematic illustration of the heat transfer mechanism of the 3D porous network. f Representative compression stress–strain $\\left(\\sigma\\mathrm{-}\\varepsilon\\right)$ curves of G700/G800/G900 aerogels upon $80\\%$ strain \n\nThe detected temperatures are 30.3, 32.1, and $35.1\\ ^{\\circ}\\mathrm{C}$ for G700; 31.8, 33.7, and $35.3~^{\\circ}\\mathrm{C}$ for G800; 31.7, 34.4, and $35.7^{\\circ}\\mathrm{C}$ for G900, respectively. As illustrated in Fig. 3d, the slow upward trends directly demonstrate that the shaddock peel-based aerogel possess excellent thermal insulating property. Figure 3e shows the possible heat transfer mechanism of the biomass-based carbon aerogel, including three main types: (1) thermal conduction of solid phase or gas phase, (2) thermal convection of gas in pores and (3) thermal radiation between hole walls and pores [32, 33]. Due to abundant air with lower thermal conductivity take the place of solid phase with higher thermal conductivity, the biomass-based aerogels exhibit superb thermal insulation performance. Satisfactory mechanical property also contributes to wide applications in industrial field [34]. The stress–strain curves have been captured with a strain of $80\\%$ at a strain rate of $0.5\\mathrm{mm}\\mathrm{min}^{-1}$ . As depicted in Fig. 3f, the maximum compressive stresses of $\\mathrm{G700/G800/G900}$ are 2.815, 2.435, and $3.639\\mathrm{kPa}$ , indicating the favorable mechanical property of the shaddock peel-based aerogels. \n\n# 3.3  \u0007Microwave Absorption Property \n\nTaking nonmagnetic ingredient of shaddock peel derived aerogel into account, it can be deduced that dielectric loss plays a leading role in electromagnetic absorbing behaviors. Hence, complex permittivity, including real part $(\\varepsilon^{\\prime})$ and imaginary part $(\\varepsilon^{\\prime\\prime})$ , were measured in the frequency region from 2 to18 GHz. Figure 4a exhibits that the average $\\varepsilon^{\\prime}$ value of G700 is 7.14, the $\\varepsilon^{\\prime}$ value of G800 decreases from 16.35 to 9.94 and the $\\varepsilon^{\\prime}$ value of G900 specimen declines from 20.87 to 11.08. Meanwhile, Fig. 4b displays the average imaginary part permittivity $\\varepsilon^{\\prime\\prime}$ values for $\\mathrm{G700/G800/}$ G900 are 1.85, 5.11, and 7.97, respectively. There is no doubt that the storage $(\\varepsilon^{\\prime})$ and dissipation $(\\varepsilon^{\\prime\\prime})$ capacity show an upward trend with increasing temperature. Obviously, as the frequency increases, the dielectric response $\\cdot\\varepsilon^{\\prime}$ and $\\varepsilon^{\\prime\\prime}$ values) gradually decreases for G800 and G900, which can be ascribed to frequency dispersion effect. However, as for G700 sample, the real $(\\varepsilon^{\\prime})$ and imaginary $(\\varepsilon^{\\prime\\prime})$ permittivity values keep smooth with the same constant, indicating frequency dispersion effect plays a minor role in microwave absorbing performance. In addition, the $\\varepsilon_{r}-f$ curve exhibits several fierce fluctuations in the $\\mathrm{\\Delta}\\mathrm{X}$ and $\\mathtt{K u}$ band for G800 and G900 specimens, which may be explained by multiple dipole polarization relaxation behaviors and splendid dielectric attenuation ability of the carbon aerogel [35]. Dielectric loss tangents $(\\mathrm{tan}\\delta_{\\varepsilon}{=}\\varepsilon^{\\prime\\prime}/\\varepsilon^{\\prime})$ values of all aerogel samples are 0.26521, 0.43381, and 0.5999, respectively, which can be seen from Fig. 4c [36]. In addition, the top-left inserts signify the frequency dependence of $\\tan\\delta_{\\varepsilon}$ . Based on the above analysis, G900 sample possesses the strongest dielectric dissipation capacity among all samples. According to the Debye theory, the relationship between real part and imaginary part of permittivity can be described as the following equation [37]: \n\n![](images/4a733c795572d5d126acea5314fb6a6ed7f5e922414dd7775d01cdc63d0976c4.jpg) \nFig. 4   a, b Frequency-dependent value curves of real part of permittivity $(\\varepsilon^{\\prime})$ and imaginary part of permittivity $(\\varepsilon^{\\prime\\prime})$ of all products. c A bar chart of average dielectric loss tangents of each sample. Insert is the line chart of frequency dependent dielectric loss tangents. d–f Cole–Cole plots of G700, G800, and G900 \n\n$$\n(\\varepsilon^{\\prime}-(\\varepsilon_{s}+\\varepsilon_{\\infty})/2)^{2}+(\\varepsilon^{\\prime\\prime})^{2}=((\\varepsilon_{s}-\\varepsilon_{\\infty})/2)^{2}\n$$ \n\nHerein, $\\varepsilon_{s}$ signifies the static permittivity and $\\varepsilon_{\\infty}$ represents the relative dielectric permittivity at limiting high frequency. As a rule, if the $\\varepsilon^{\\prime}-\\varepsilon^{\\prime\\prime}$ curves present semicircles, which are defined as Cole–Cole semicircles, there will appear Debye relaxation processes [38]. For comparison, the $\\varepsilon^{\\prime}-\\varepsilon^{\\prime\\prime}$ curves of shaddock peel-derived carbon aerogel have been drawn in Fig. 4d–f. Obviously, there are 4, 6, and 3 distorted semicircles in the curves of $\\mathrm{G700/G800/G900}$ samples, illustrating that G800 specimen experiences more Debye relaxation processes than the other two specimens, which may be caused by graphitized carbon and abundant defects [39]. Due to the existence of three-dimensional interconnected conductive network, conduction loss plays a significant role in dielectric loss. As can be seen from Fig. 4d, the G700 sample presents shorter dash dot line than the other two, manifesting that G800 and G900 samples exhibit more migrating and hopping electrons within the 3D interconnected network. Namely, G800 and G900 samples exhibit enlarged conduction loss ability, which is consistent with increased annealing temperature. Comprehensively considering dual factors of both dipole polarization processes and conduction loss capacity, it can be deduced that G800 specimen shows best microwave absorbing ability. \n\nIt is indispensible to verify the aforementioned speculation is correct or not. Thus, on the basis of transmission line theory, the reflection loss $(R L)$ values of as-prepared samples have been evaluated to intuitively examine and weigh microwave absorbing performance. Within the whole testing frequency range, $R L$ peaks at relatively thin thicknesses and 2D representation of RL values for all shaddock peel-based aerogel samples are summarized in Fig. 5a–f. As is known to all, RL values can be obtained using the following formulas [40–42]: \n\n$$\n\\mathrm{RL}=20\\log\\left|\\left(Z_{\\mathrm{in}}-Z_{0}\\right)/(Z_{\\mathrm{in}}+Z_{0})\\right|\n$$ \n\n$$\nZ_{\\mathrm{in}}=Z_{0}{\\left(\\mu_{r}/\\varepsilon_{r}\\right)}^{1/2}\\operatorname{tanh}\\left[j(2\\pi f d/c){\\left(\\mu_{r}\\varepsilon_{r}\\right)}^{1/2}\\right]\n$$ \n\nHerein, $Z_{i n}$ represents the input impedance value of the microwave absorbing materials and $Z_{\\theta}$ signifies the impedance value of air. Besides, $\\mu_{r}$ stands for complex permeability, $\\varepsilon_{r}$ is complex permittivity, $f$ represents the full measuring frequency, $d$ means the thickness of absorber, and $c$ signifies the velocity of light, respectively. Thanks to the efficient microwave absorbing performance $(R L<-10~\\mathrm{dB}$ , $90\\%$ microwave can be effectively absorbed), all of the 3D porous aerogel samples in this work can be used in practical applications at proper thicknesses. With the thickness increasing from 1.5 to $2.7~\\mathrm{mm}$ (Fig. 5a–c), the reflection loss peaks of the as-obtained samples gradually shift to low frequency region. This phenomenon may be related to the quarter wavelength theory [43]: $f_{m}{=}n c/4t_{m}(\\varepsilon_{r}\\mu_{\\mathrm{r}})^{1/2}$ , where $t_{m}$ represents the thickness and $f_{m}$ is the peak frequency. With regard to specific microwave absorbing properties, G700 sample shows the minimum reflection loss value of only − 12.74 dB and a narrow bandwidth of only $3.24\\:\\mathrm{GHz}$ , which is unsatisfied. As for G800, the optimum reflection loss value $(R L_{\\mathrm{min}})$ attains − 29.50 dB at the thickness of merely $2.3\\mathrm{mm}$ in X band, and the effective frequency range $(f_{E})$ reaches $5.80\\mathrm{GHz}$ (from 11.08 to $16.88\\mathrm{GHz}\\backslash$ at a relatively thin thickness of $1.7\\ \\mathrm{mm}$ in $\\mathtt{K u}$ band. Unfortunately, G900 specimen exhibits $R L_{\\mathrm{min}}$ of only − 13.50 dB with an effective bandwidth of $4.00\\:\\mathrm{GHz}$ at high frequency. Additionally, Fig. 5d–f presents the 2D color fill contour plots of reflection loss values. It should be noted that G800 sample can acquire the maximum area marked out by black bold lines, where the RL values are less than − 10 dB. Besides, Fig. 5g provides direct comparison of the bandwidth information for all products, suggesting that G800 owns the widest bandwidth at thin thicknesses among all shaddock peelbased aerogel samples. Therefore, in this case, G800 sample possesses optimum microwave-absorbing performance, which can be attributed to favorable impedance matching property and extremely high attenuation ability [44]. Speaking of impedance matching, it can be given on the basis of the following equations [45]: \n\n$$\nZ=\\:\\vert Z_{\\mathrm{in}}/Z_{0}\\vert\n$$ \n\n$$\nZ_{\\mathrm{in}}=\\left(\\mu_{r}/\\varepsilon_{r}\\right)^{1/2}Z_{0}\n$$ \n\nIt is generally accepted that if there exhibit almost none reflection between air and the upper surface of the microwave absorbing materials, the value of impedance matching $(Z)$ should be close to 1 [46]. If so, it will help electromagnetic wave enter into the internal of the as-obtained material as much as possible. When the thickness is 1.7 and $2.3~\\mathrm{mm}$ , $Z$ values of 0.75–1.25 occupy the frequency range from $7.52~\\mathrm{GHz}$ to $18~\\mathrm{{GHz}}$ (Fig.  5h). Herein, the order of suitable impedance matching performance should be $\\mathbf{G}700>\\mathbf{G}800>\\mathbf{G}900$ . Apart from the above factor, the integral attenuation capacity of the microwave absorber (attenuation constant $\\alpha$ ) can be expressed as [47]: \n\n![](images/c56b1f43a5a823e0069c34c016c7797ad0b732bfea5bc2af23d231572bd5b1da.jpg) \nFig. 5   a–c Reflection loss peaks at relatively thin thicknesses of all shaddock peel-based aerogel samples. d–f 2D representation of RL values for G700, G800, and G900 samples in the full tested frequency region. g Effective bandwidth of all samples. h Comparison of impedance matching $\\lvert Z_{i n}/Z_{\\theta}\\rvert$ values at $1.7\\mathrm{mm}$ and $2.3\\mathrm{mm}$ of G700, G800, and G900. i Attenuation constants of G700/G800/G900 \n\n$$\n\\alpha=\\frac{\\sqrt{2}\\pi f}{c}\\times\\sqrt{(\\mu^{\\prime\\prime}\\varepsilon^{\\prime\\prime}-\\mu^{\\prime}\\varepsilon^{\\prime})+\\sqrt{(\\mu^{\\prime\\prime}\\varepsilon^{\\prime\\prime}-\\mu^{\\prime}\\varepsilon^{\\prime})^{2}+(\\mu^{\\prime}\\varepsilon^{\\prime\\prime}+\\mu^{\\prime\\prime}\\varepsilon^{\\prime})^{2}}}\n$$ \n\nAs shown in Fig. 5i, the order of splendid attenuation characteristic should be $\\mathrm{G900>G800>G700}$ . To sum up, both the synergistic effect of suitable impedance matching characteristic and outstanding attenuation property contribute to microwave absorbing performance, explaining why G800 shows optimum electromagnetic absorption among all aerogel samples. \n\nBased on the metal back model, a possible microwave absorption mechanism of the 3D shaddock peel-derived carbon aerogel has been given in Fig. 6. Thanks to the interlinked network structure of the as-prepared porous carbon aerogel, several points can be beneficial for improving microwave absorption performance. First of all, strong dipole polarization mechanisms and relaxation mechanisms, induced by the incompatibility of dipoles migrating and external electric field, are useful for enhancing dielectric loss ability [48]. Moreover, the aforementioned Cole–Cole curves of the assynthesized 3D carbon aerogels (Fig. 4d–f) can confirm the existence of dipole polarization process and Debye relaxation process. Besides, the conductive routes of the biomassbased carbon network can bring active migrating electrons and hopping electrons, which can be available for conduction loss property [49]. Owing to the unique three-dimensional skeleton architectures with high porosity, multiple scattering propagation paths of microwave can be obtained by the shaddock peel-derived carbon aerogel [50]. In addition, sufficient internal absorbing behaviors can increase the exhaustion of microwave energy in the carbon aerogel. Furthermore, proper impedance matching has a significant effect on absorption efficiency of electromagnetic wave. \n\n![](images/57ee050796e4d6fae823d5149c00eba5058c1b3db29fce328cf485c1972dfeb6.jpg) \nFig. 6   Schematic illustration of microwave absorption mechanisms for 3D shaddock peel-derived carbon aerogel \n\n# 3.4  \u0007RCS Simulation Results \n\nCST simulation results of the perfect conductive layer (PEC) and the PEC layer covered by G700, G800, and G900 samples are shown in Fig. 7a–d, which can reflect the real far field condition of microwave absorbing performance of the as-prepared aerogels. In this simulation model, the positive $Z$ axis is selected to be the direction of incidence and theta is defined as the detection angle. With the angle variation range from $-60^{\\circ}$ to $60^{\\circ}$ at $12\\mathrm{GHz}$ , the pristine PEC layer and all as-synthesized samples display three-dimensional radar wave scattering signals of different intensities. Evidently, PEC plate exhibits the maximum scattering signal, which can be observed from Fig. 7a. The simulated appearance result of the square flat plate covered by G800 sample is much less than PEC and other objects, manifesting the minimum radar cross-sectional (RCS) value of G800 sample. As a validation, 2D curves of RCS values have been depicted in Fig. 7e. When microwave incident perpendicularly to the model plane, the reflected electromagnetic wave can occupy a larger proportion, which can be seen from Fig. 7e. With the deviation of detection angle, the RCS values gradually decrease from $0^{\\circ}$ to $\\pm60^{\\mathrm{o}}$ with several fluctuations. As compared to PEC, G700 and G900, there is no doubt that G800 exhibits the lowest RCS values over the angle range of $-60^{\\circ}$ to $60^{\\circ}$ at $12\\mathrm{GHz}$ in X band. The RCS values of G800 specimen are less than − 10 dB ${\\mathrm{m}}^{2}$ over the range of $-60^{\\circ}<\\mathrm{theta}<-6^{\\circ}$ and $6^{\\circ}<\\mathrm{theta}<60^{\\circ}$ at the coating thickness of $1.7~\\mathrm{mm}$ . This simulated result corresponds well with the outstanding microwave absorbing property in Fig. 5. In order to further testifying the above description, the relevant bar charts of comparing the RCS reduction values (the RCS values of PEC minus that of samples) are presented in Fig. 7f. When theta arrives at $0^{\\circ}$ , the maximum RCS reduction values can reach $16.28~\\mathrm{dB}~\\mathrm{m}^{2}$ for G800 sample. That is to say, the obtained aerogel possesses fabulous radar wave attenuation property, which can suppress the scattering and reflecting electromagnetic waves from the surface of PEC. Therefore, this kind of shaddock peel-based carbon aerogel can be appropriate for practical applications. \n\n![](images/f9af74ea5bd8877fef4bd971a0370cd41b380db61fdfd86c6a38efb58aaaa853.jpg) \nFig. 7   CST simulation results of the samples: a perfect conductive layer (PEC), b–d the perfect conductive layer covered with G700, G800, and G900 samples. e RCS simulated curves of PEC and all shaddock peel-derived carbon aerogel products under different scanning angles. f Comparison of RCS reduction values of G700/G800/G900 samples \n\n# 4  \u0007Conclusion \n\nIn conclusion, a series of shaddock peel-based carbon aerogels were prepared via a facile freeze-drying method and a subsequent high temperature treatment. Thanks to the interlinked conductive network with plenty of pore structures, the as-synthesized specimens show multi-functions as the following. Firstly, wonderful thermal infrared stealth property and heat insulation performance can not only protect the object from detection but also ensure availability of devices in high temperature environment. Then, promising mechanical performance allows equipments to reuse in daily routine. Except that, superb electrical conductivity of the as-obtained aerogels can be helpful to efficient dielectric loss ability, which may be beneficial for microwave absorbing performance. In detail, the obtained sample reaches an effective bandwidth (the RL values below $-10\\mathrm{dB}),$ ) of $5.80\\:\\mathrm{GHz}$ in X and $\\mathtt{K u}$ band at a relatively thin thickness of $1.7\\mathrm{mm}$ . Also, this work provides CST simulation data for the biomass-based carbon aerogels, which can be an intelligent design strategy for microwave absorption. Since the G800 sample covered model possesses smaller RCS values than PEC model, demonstrating the splendid microwave absorption performance. Therefore, this work provides lightweight shaddock peel derived microwave absorbing aerogels with multiple functions and brings novel RCS simulation method for predicting microwave absorption in practical application situation, which can of great significance for many fields in the future. \n\nAcknowledgements  We are thankful for the financial support from National Nature Science Foundation of China (No. 51971111) and Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX20_0190). \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\n# References \n\n1.\t Q. Liu, Q. Cao, H. Bi, C. Liang, K. Yuan et al., $\\mathrm{CoNi}@\\mathrm{SiO}_{2}@$ $\\mathrm{TiO}_{2}$ and $\\mathrm{CoNi@Air@TiO_{2}}$ microspheres with strong wideband microwave absorption. Adv. Mater. 28, 486–490 (2016). https://​doi.​org/​10.​1002/​adma.​20150​3149 \n2.\t X.X. Wang, W.Q. Cao, M.S. Cao, J. Yuan, Assembling nanomicroarchitecture for electromagnetic absorbers and smart devices. Adv. Mater. 32, 2002112 (2020). https://​doi.​org/​10. 1002/​adma.​20200​2112 \n3.\t M.A. Poothanari, J. Abraham, N. Kalarikkal, S. Thomas, Excellent electromagnetic interference shielding and high electrical conductivity of compatibilized polycarbonate/polypropylene carbon nanotube blend nanocomposites. Ind. Eng. Chem. Res. 57, 4287–4297 (2018). https://​doi.​org/​10.​1021/ acs.​iecr.​7b054​06 \n4.\t Y.P. Wang, B. Suo, Y. Shi, H.R. Yuan, C.L. Zhu et al., General fabrication of 3D hierarchically structured bamboo-like nitrogen-doped carbon nanotubes arrays on 1D nitrogen-doped carbon skeletons for highly efficient electromagnetic wave energy attenuation. ACS Appl. Mater. Interfaces 12, 40692–40701 (2020). https://​doi.​org/​10.​1021/​acsami.​0c124​13 \n5.\t X.H. Liang, Z.M. Man, B. Quan, J. Zheng, W.H. Gu et al., Environment-stable $\\mathrm{Co_{x}N i_{y}}$ encapsulation in stacked porous carbon nanosheets for enhanced microwave absorption. Nano-Micro Lett. 12, 102 (2020). https://​doi.​org/​10.​1007/ s40820-​020-​00432-2 \n6.\t R.C. Che, L. Peng, X. Duan, Q. Chen, X. Liang, Microwave absorption enhancement and complex permittivity and permeability of Fe encapsulated within carbon nanotubes. Adv. Mater. 16, 401–405 (2004). https://​doi.​org/​10.​1002/​adma. 20030​6460 \n7.\t J.X. Ma, W.H. Li, Y.C. Fan, J.Y. Yang, Q.K. Yang et  al., Ultrathin and light-weight graphene aerogel with precisely tunable density for highly efficient microwave absorbing. ACS Appl. Mater. Interfaces 11, 46386–46396 (2019). https://​doi. org/​10.​1021/​acsami.​9b178​49 \n8.\t J. Xu, X. Zhang, H.R. Yuan, S. Zhang, C.L. Zhu et  al., N-doped reduced graphene oxide aerogels containing pod-like N-doped carbon nanotubes and FeNi nanoparticles for electromagnetic wave absorption. Carbon 159, 357–365 (2020). https://​doi.​org/​10.​1016/j.​carbon.​2019.​12.​020 \n9.\t P. Song, B. Liu, H. Qiu, X.T. Shi, D.P. Cao et al., MXenes for polymer matrix electromagnetic interference shielding composites: a review. Compos. Commun. 24, 100653 (2021). https://​doi.​org/​10.​1016/j.​coco.​2021.​100653 \n10.\t Y.L. Zhang, K.P. Ruan, X.T. Shi, H. Qiu, Y. Pan et  al., $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}/\\mathrm{rGO}$ porous composite films with superior electromagnetic interference shielding performances. Carbon 175, 271–280 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2020.​12.​084 \n11.\t X.C. Zhang, X. Zhang, H.R. Yuan, K.Y. Li, Q.Y. Ouyang et al., CoNi nanoparticles encapsulated by nitrogen-doped carbon nanotube arrays on reduced graphene oxide sheets for electromagnetic wave absorption. Chem. Eng. J. 383, 123208 (2020). https://​doi.​org/​10.​1016/j.​cej.​2019.​123208 \n12.\t J. Zhao, J.L. Zhang, L. Wang, J.K. Li, T. Feng et al., Superior wave-absorbing performances of silicone rubber composites via introducing covalently bonded $\\mathrm{SnO}_{2}@\\mathrm{MWCNT}$ absorbent with encapsulation structure. Compos. Commun. 22, 100486 (2020). https://​doi.​org/​10.​1016/j.​coco.​2020.​100486 \n13.\t J.Q. Sheng, Y. Zhang, L. Liu, B. Quan, N. Zhang et al., Optimizing electromagnetic wave absorption performance: Design from microscopic bamboo carbon nanotubes to macroscopic patterns. J. Alloys Compd. 809, 151866 (2019). https://​doi.​ org/​10.​1016/j.​jallc​om.​2019.​151866 \n14.\t S.T. Wu, M.C. Zou, Z.C. Li, D.Q. Chen, H. Zhang et  al., Robust and stable Cu nanowire $@$ graphene core-shell aerogels for ultraeffective electromagnetic interference shielding. Small 14, 1800634 (2018). https://​doi.​org/​10.​1002/​smll.​20180​0634 \n15.\t J. Liu, H.B. Zhang, X. Xie, R. Yang, Z.S. Liu et  al., Multifunctional, superelastic, and lightweight MXene/polyimide aerogels. Small 14, 1802479 (2018). https://​doi.​org/​10.​1002/ smll.​20180​2479 \n16.\t W.H. Gu, J.W. Tan, J.B. Chen, Z. Zhang, Y. Zhao et al., Multifunctional bulk hybrid foam for infrared stealth, thermal insulation, and microwave absorption. ACS Appl. Mater. Interfaces 12, 28727–28737 (2020). https://​doi.​org/​10.​1021/ acsami.​0c092​02 \n17.\t J.B. Chen, X.H. Liang, J. Zheng, W.H. Gu, C.C. Pei et al., Modulating dielectric loss of mesoporouscarbon fibers with radar cross section reduction performance via computer simulation technology. Inorg. Chem. Front. 8, 758–765 (2020). https://​doi.​org/​10.​1039/​d0qi0​1237h \n18.\t H.Q. Zhao, Y. Cheng, W. Liu, L.J. Yang, B.S. Zhang et al., Biomass-derived porous carbon-based nanostructures for microwave absorption. Nano-Micro Lett. 11, 24 (2019). https://​doi.​org/​10.​1007/​s40820-​019-​0255-3 \n19.\t L. Wang, X.T. Shi, J.L. Zhang, Y.L. Zhang, J.W. Gu, Lightweight and robust rGO/sugarcane derived hybrid carbon foams with outstanding EMI shielding performance. J. Mater. Sci. Technol. 52, 119–126 (2020). https://​doi.​org/​10.​1016/j.​jmst. 2020.​03.​029 \n20.\t X. Qiu, L. Wang, H. Zhu, Y. Guan, Q. Zhang, Lightweight and efficient microwave absorbing materials based on walnut shellderived nanoporous carbon. Nanoscale 9, 7408–7418 (2017). https://​doi.​org/​10.​1039/​c7nr0​2628e \n21.\t S. Dong, P.T. Hu, X.T. Li, C.Q. Hong, X.H. Zhang et  al., $\\mathrm{NiCo}_{2}\\mathrm{S}_{4}$ nanosheets on 3D wood-derived carbon for microwave absorption. Chem. Eng. J. 398, 123817 (2020). https://​ doi.​org/​10.​1016/j.​cej.​2020.​125588 \n22.\t Y. Cheng, J.Z.Y. Seow, H.Q. Zhao, Z.C.J. Xu, G.B. Ji, A flexible and lightweight biomass-reinforced microwave absorber. Nano-Micro Lett. 12, 125 (2020). https://​doi.​org/​10.​1007/​ s40820-​020-​00461-x \n23.\t H.Q. Zhao, Y. Cheng, H.L. Lv, G.B. Ji, Y.W. Du, A novel hierarchically porous magnetic carbon derived from biomass for strong lightweight microwave absorption. Carbon 142, 245–253 (2019). https://​doi.​org/​10.​1016/j.​carbon.​2018.​10.​027 \n24.\t Z.C. Wang, R.B. Wei, J.W. Gu, H. Liu, C.T. Liu et al., Ultralight, highly compressible and fire-retardant graphene aerogel with self-adjustable electromagnetic wave absorption. Carbon 139, 1126–1135 (2018). https://​doi.​org/​10.​1016/j.​carbon. 2018.​08.​014 \n25.\t Y. Qin, Q. Peng, Y. Ding, Z. Lin, C. Wang et al., Lightweight, superelastic, and mechanically flexible graphene/polyimide nanocomposite foam for strain sensor application. ACS Nano 9, 8933–8941 (2015). https://​doi.​org/​10.​1021/​acsna​no.​5b027 81 \n26.\t X. Zhang, X. Zhao, T. Xue, F. Yang, W. Fan et al., Bidirectional anisotropic polyimide/bacterial cellulose aerogels by freeze-drying for super-thermal insulation. Chem. Eng. J. 385, 123963 (2020). https://​doi.​org/​10.​1016/j.​cej.​2019.​ 123963 \n27.\t J.B. Chen, J. Zheng, F. Wang, Q.Q. Huang, G.B. Ji, Carbon fibers embedded with $\\mathrm{Fe}^{\\mathrm{III}}.$ -MOF-5-derived composites for enhanced microwave absorption. Carbon 174, 509–517 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2020.​12.​077 \n28.\t S. Lee, D. Suh, W. Kim, C. Xu, T. Kim et al., Carbon nanotube covalent bonding mediates extraordinary electron and phonon transports in soft epoxy matrix interface materials. Carbon 157, 12–21 (2020). https://​doi.​org/​10.​1016/j.​carbon. 2019.​10.​013 \n29.\t P.B. Liu, S. Gao, Y. Wang, Y. Huang, W.J. He et al., Carbon nanocages with N-doped carbon inner shell and Co/N-doped carbon outer shell as electromagnetic wave absorption materials. Chem. Eng. J. 381, 122653 (2020). https://​doi.​org/​10. 1016/j.​cej.​2019.​122653 \n30.\t B.A. Mei, O. Munteshari, J. Lau, B. Dunn, L. Pilon, Physical interpretations of Nyquist plots for EDLC electrodes and devices. J. Phys. Chem. C 122, 194–206 (2018). https://​doi.​ org/​10.​1021/​acs.​jpcc.​7b105​82 \n31.\t B. Zhou, M.J. Su, D.Z. Yang, G.J. Han, Y.Z. Feng et  al., Flexible MXene/silver nanowire-based transparent conductive film with electromagnetic interference shielding and electro-photo-thermal performance. ACS Appl. Mater. Interfaces 12, 40859–40869 (2020). https://​doi.​org/​10.​1021/​ acsami.​0c090​20 \n32.\t Y. Li, X.F. Liu, X.Y. Nie, W.W. Yang, Y.D. Wang et  al., Multifunctional organic-inorganic hybrid aerogel for selfcleaning, heat-insulating, and highly efficient microwave absorbing material. Adv. Funct. Mater. 29, 1807624 (2019). https://​doi.​org/​10.​1002/​adfm.​20180​7624 \n33.\t A.A. Gunay, H. Kim, N. Nagarajan, M. Lopez, R. Kantharaj et al., Optically transparent thermally insulating silica aerogels for solar thermal insulation. ACS Appl. Mater. Interfaces 10, 12603–12611 (2018). https://​doi.​org/​10.​1021/​ acsami.​7b188​56 \n34.\t M. Stanzione, M. Oliviero, M. Cocca, M. Errico, G. Gentile et al., Tuning of polyurethane foam mechanical and thermal properties using ball-milled cellulose. Carbohydr. Polym. 231, 115772 (2020). https://​doi.​org/​10.​1016/j.​carbp​ol.​2019. 115772 \n35.\t R.Y. Tan, J.T. Zhou, Z.J. Yao, B. Wei, Z. Li, A low-cost lightweight microwave absorber: silicon carbide synthesized from tissue. Ceram. Int. 47, 2077–2085 (2021). https://​doi.​ org/​10.​1016/j.​ceram​int.​2020.​09.​040 \n36.\t R. Guo, Y.C. Fan, L.J. Wang, W. Jiang, Core-rim structured carbide MXene $\\mathrm{'SiO}_{2}$ nanoplates as an ultrathin microwave absorber. Carbon 169, 214–224 (2020). https://​doi.​org/​10. 1016/j.​carbon.​2020.​07.​054 \n37.\t C. Wu, Z.F. Chen, M.L. Wang, X. Cao, Y. Zhang et al., Confining tiny $\\mathbf{MoO}_{2}$ clusters into reduced graphene oxide for highly efficient low frequency microwave absorption. Small 16, 2001686 (2020). https://​doi.​org/​10.​1002/​smll.​20200 1686 \n38.\t S. Dong, X.H. Zhang, X.T. Li, J.M. Chen, P. Hu et al., SiC whiskers-reduced graphene oxide composites decorated with MnO nanoparticles for tunable microwave absorption. Chem. Eng. J. 392, 123817 (2020). https://​doi.​org/​10.​1016/j. cej.​2019.​123817 \n39.\t B. Quan, W.H. Shi, S.J. Hoong Ong, X.C. Lu, P.L. Wang et al., Defect engineering in two common types of dielectric materials for electromagnetic absorption applications. Adv. Funct. Mater. 29, 1901236 (2019). https://​doi.​org/​10.​1002/​ adfm.​20190​1236 \n40.\t B. Quan, W.H. Gu, J.Q. Sheng, X.F. Lv, Y.Y. Mao et  al., From intrinsic dielectric loss to geometry patterns: dualprinciples strategy for ultrabroad band microwave absorption. Nano Res. 14, 1495–1501 (2020). https://​doi.​org/​10. 1007/​s12274-​020-​3208-8 \n41.\t J.C. Liu, Z.H. Yang, L.J. Yang, Y.T. Zhu, T. Xue et  al., Rational design of yolk-shell $\\mathrm{NiCo}_{2}\\mathrm{O}_{4}@$ void $\\ @{\\mathrm{NiCo}_{2}}\\mathrm{S}_{4}$ nanospheres for effective enhancement in microwave absorption. J. Alloys Compd. 853, 157403 (2021). https://​doi.​org/ 10.​1016/j.​jallc​om.​2020.​157403 \n42.\t G.H. Wang, S.J.H. Ong, Y. Zhao, Z.C.J. Xu, G.B. Ji, Integrated multifunctional macrostructures for electromagnetic wave absorption and shielding. J. Mater. Chem. A 8, 24368 (2020). https://​doi.​org/​10.​1039/​d0ta0​8515d \n43.\t J. Singh, C. Singh, D. Kaur, S.B. Narang, R.B. Jotania et al., Development of doped BaeSr hexagonal ferrites for microwave absorber applications: Structural characterization, tunable thickness, absorption peaks and electromagnetic parameters. J. Alloys Compd. 855, 157242 (2021). https://​ doi.​org/​10.​1016/j.​jallc​om.​2020.​157242 \n44.\t Y.L. Lian, B.H. Han, D.W. Liu, Y.H. Wang, H.H. Zhao et al., Solvent-free synthesis of ultrafine tungsten carbide nanoparticles-decorated carbon nanosheets for microwave absorption. Nano-Micro Lett. 12, 153 (2020). https://​doi. org/​10.​1007/​s40820-​020-​00491-5 \n45.\t Y.M. Mao, Z.J. Yao, J.T. Zhou, B. Wei, L. Lei et al., Fabrication and investigations on BMI/OMMT nanocomposites with superior high-temperature wave-transparent performance. J. Mater. Sci. Mater. Electron. 31, 16073–16086 (2020). https://​doi.​org/​10.​1007/​s10854-​020-​04172-2 \n46.\t M. Javid, X.H. Qu, F.R. Huang, X.Y. Li, A. Farid et al., Insitu synthesis of SiC/Fe nanowires coated with thin amorphous carbon layers for excellent electromagnetic wave absorption in GHz range. Carbon 171, 785–797 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2020.​09.​066 \n47.\t L. Su, J.X. Ma, F.Z. Zhang, Y.C. Fan, W. Luo et  al., Achieving effective broadband microwave absorption with $\\mathrm{Fe}_{3}\\mathrm{O}_{4}@{\\mathrm{C}}$ supraparticles. J. Materiomics 7, 80–88 (2021). https://​doi.​org/​10.​1016/j.​jmat.​2020.​07.​011 \n48.\t Y.L. Duan, Y. Li, D. Wang, R.Q. Wang, Y.L. Wang et al., Transverse size effect on electromagnetic wave absorption performance of exfoliated thin-layered flake graphite. Carbon 153, 682–690 (2019). https://​doi.​org/​10.​1016/j.​carbon. 2019.​07.​078 \n49.\t B. Wen, M.S. Cao, M.M. Lu, W.Q. Cao, H.L. Shi et  al., Reduced graphene oxides: light-weight and high-efficiency electromagnetic interference shielding at elevated temperatures. Adv. Mater. 26, 3484–3489 (2014). https://​doi.​org/​10. 1002/​adma.​20140​0108 \n50.\t J.C. Shu, M.S. Cao, M. Zhang, X. Wang, W.Q. Cao et al., Molecular patching engineering to drive energy conversion as efficient and environment-friendly cell toward wireless power transmission. Adv. Funct. Mater. 30, 1908299 (2020). https:// doi.​org/​10.​1002/​adfm.​20190​8299 " + }, + { + "id": "10.1038_s41893-020-00635-w", + "DOI": "10.1038/s41893-020-00635-w", + "DOI Link": "http://dx.doi.org/10.1038/s41893-020-00635-w", + "Relative Dir Path": "mds/10.1038_s41893-020-00635-w", + "Article Title": "Organic wastewater treatment by a single-atom catalyst and electrolytically produced H2O2", + "Authors": "Xu, JW; Zheng, XL; Feng, ZP; Lu, ZY; Zhang, ZW; Huang, W; Li, YB; Vuckovic, D; Li, YQ; Dai, S; Chen, GX; Wang, KC; Wang, HS; Chen, JK; Mitch, W; Cui, Y", + "Source Title": "NATURE SUSTAINABILITY", + "Abstract": "The presence of organic contaminullts in wastewater poses considerable risks to the health of both humans and ecosystems. Although advanced oxidation processes that rely on highly reactive radicals to destroy organic contaminullts are appealing treatment options, substantial energy and chemical inputs limit their practical applications. Here we demonstrate that Cu single atoms incorporated in graphitic carbon nitride can catalytically activate H2O2 to generate hydroxyl radicals at pH 7.0 without energy input, and show robust stability within a filtration device. We further design an electrolysis reactor for the on-site generation of H2O2 from air, water and renewable energy. Coupling the single-atom catalytic filter and the H2O2 electrolytic generator in tandem delivers a wastewater treatment system. These findings provide a promising path toward reducing the energy and chemical demands of advanced oxidation processes, as well as enabling their implementation in remote areas and isolated communities. Here the authors design an electrolysis reactor to generate H2O2 which could be further catalytically activated by Cu single atoms to yield hydroxyl radicals. Combining the two reactions enables a system that could treat organic wastewater, providing a path toward sustainable advanced oxidation processes.", + "Times Cited, WoS Core": 479, + "Times Cited, All Databases": 494, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics; Environmental Sciences & Ecology", + "UT (Unique WOS ID)": "WOS:000588002700001", + "Markdown": "# Organic wastewater treatment by a single-atom catalyst and electrolytically produced H $\\phantom{}_{2}\\mathbf{O}_{2}$ \n\nJinwei $\\mathsf{\\pmb{X}}\\mathsf{\\pmb{u}}^{1}$ , Xueli Zheng   1, Zhiping Feng2, Zhiyi $\\mathbf{Lu}^{1}$ , Zewen Zhang1, William Huang $\\mathfrak{P}^{1}$ , Yanbin Li1, Djordje Vuckovic3, Yuanqing $\\mathsf{L i}^{3}$ , Sheng Dai4, Guangxu Chen1, Kecheng Wang1, Hansen Wang1, James K. Chen2,5, William Mitch3 and Yi Cui   1,6 ✉ \n\nThe presence of organic contaminants in wastewater poses considerable risks to the health of both humans and ecosystems. Although advanced oxidation processes that rely on highly reactive radicals to destroy organic contaminants are appealing treatment options, substantial energy and chemical inputs limit their practical applications. Here we demonstrate that Cu single atoms incorporated in graphitic carbon nitride can catalytically activate ${\\bf H}_{2}\\bar{\\bf O}_{2}$ to generate hydroxyl radicals at $\\yen123$ without energy input, and show robust stability within a filtration device. We further design an electrolysis reactor for the on-site generation of ${\\bf H}_{2}\\bar{\\bf O}_{2}$ from air, water and renewable energy. Coupling the single-atom catalytic filter and the ${\\bf H}_{2}\\bar{\\bf O}_{2}$ electrolytic generator in tandem delivers a wastewater treatment system. These findings provide a promising path toward reducing the energy and chemical demands of advanced oxidation processes, as well as enabling their implementation in remote areas and isolated communities. \n\ndvanced oxidation processes (AOPs), which produce highly reactive radicals (OH•, Cl• and so on) from soluble oxidants $\\mathrm{(H}_{2}\\mathrm{O}_{2},$ , $\\mathrm{~O}_{3},$ HOCl and so on), are state-of-the-art water treatment technologies used for the removal of organic contaminants1–3. Radicals react rapidly and non-selectively with organic contaminants and ultimately mineralize them into harmless small molecules $(\\mathrm{CO}_{2},$ $\\mathrm{H}_{2}\\mathrm{O}$ and so on). However, despite the substantial development of AOPs since the concept was formally defined in 1987 by Glaze et al.4, two fundamental challenges have thus far limited their practical use. \n\nThe first challenge in regard to AOPs is the efficient activation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Ultraviolet (UV) light is widely used in commercialized AOPs to cleave the O-O bond of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to generate $\\mathrm{OH^{\\bullet}}$ , yet this process is highly energy intensive5. Therefore, finding a catalyst to activate $\\mathrm{H}_{2}\\mathrm{O}_{2}$ without energy input is the crux of next-generation AOPs. Homogeneous catalysts, such as Fenton’s reagent6 (equations $(1,2))$ , suffer from drawbacks including the requirement of low pH, the recyclability of $\\mathrm{Fe}^{2+}$ and the accumulation of iron-containing sludge. Heterogeneous Fenton reaction is a promising alternative7 (equations (3, 4)). Previous studies have mainly focused on activation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ through the one-electron redox cycle of exposed transition-metal atoms (Fe (ref. 8), Cu (ref. 9), Mn (ref. 10) and so on) on various supports (magnetite11, zeolites12, activated carbon13 and so on). However, few of these catalysts exhibit good activity at $\\mathrm{pH}7.0$ , which is often attributed to three factors: (1) the quenching of OH• by adjacent transition-metal atoms8 (equations (3, 5)); (2) the disproportionation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ proceeding via a two-electron redox cycle14 (equations $(6,7))$ ; and (3) the slow kinetics of equation (4) retarding the full catalytic cycle15. \n\n$$\n\\mathrm{Fe}^{2+}+\\mathrm{H}_{2}\\mathrm{O}_{2}\\rightarrow\\mathrm{Fe}^{3+}+\\mathrm{OH}^{\\bullet}+\\mathrm{OH}^{-}\n$$ \n\n$$\n\\mathrm{Fe}^{3+}+\\mathrm{H}_{2}\\mathrm{O}_{2}\\rightarrow\\mathrm{Fe}^{2+}+\\mathrm{OOH}^{\\bullet}+\\mathrm{H}^{+}\n$$ \n\n$$\nM_{\\mathrm{surface}}^{n+}+\\mathrm{H}_{2}\\mathrm{O}_{2}\\longrightarrow M_{\\mathrm{surface}}^{(n+1)+}+\\mathrm{OH}^{\\bullet}+\\mathrm{OH}^{-}\n$$ \n\n$$\nM_{\\mathrm{surface}}^{(n+1)+}+\\mathrm{H}_{2}\\mathrm{O}_{2}\\longrightarrow M_{\\mathrm{surface}}^{n+}+\\mathrm{OOH}^{\\bullet}+\\mathrm{H}^{+}\n$$ \n\n$$\nM_{\\mathrm{surface}}^{n+}+\\mathrm{OH}^{\\bullet}\\rightarrow M_{\\mathrm{surface}}^{(n+1)+}+\\mathrm{OH}^{-}\n$$ \n\n$$\nM_{\\mathrm{surface}}^{n+}+\\mathrm{H}_{2}\\mathrm{O}_{2}\\rightarrow M_{\\mathrm{surface}}^{(n+2)+}+2\\mathrm{OH}^{-}\n$$ \n\n$$\nM_{\\mathrm{surface}}^{(n+2)+}+\\mathrm{H}_{2}\\mathrm{O}_{2}\\rightarrow M_{\\mathrm{surface}}^{n+}+\\mathrm{O}_{2}+2\\mathrm{H}^{+}\n$$ \n\nNote that $M_{\\mathrm{surface}}$ denotes surface transition-metal atoms. The second challenge with AOPs is the sustainable production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . The current industrial anthraquinone process requires complex infrastructure and is not feasible for small-scale operations16. Besides, the hazards associated with the transportation and storage of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ further hinder the implementation of AOPs in remote areas and isolated communities. A promising alternative route is the on-site generation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ via the two-electron reduction of $\\mathrm{O}_{2}$ (2e-ORR) (equation (8)). This process can be coupled with the oxygen evolution reaction (OER) (equation (9)) to produce $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in an electrolysis device from air, water and renewable energy (equation (10)). Substantial efforts have been invested in catalyst development and mechanistic studies for $2\\mathrm{e}{\\mathrm{-}}\\mathrm{ORR}^{17-20}$ , yet few device-level demonstrations have shown its practical utility21–24. \n\n$$\n\\mathrm{O}_{2}+2\\mathrm{e}^{-}+2\\mathrm{H}^{+}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}_{2}E_{\\mathrm{red}}=0.695\\mathrm{V}\\mathrm{versusRHE}\n$$ \n\n$$\n2\\mathrm{H}_{2}\\mathrm{O}\\rightarrow\\mathrm{O}_{2}+4\\mathrm{H}^{+}+4\\mathrm{e}^{-}E_{\\mathrm{red}}=1.229\\mathrm{V}\\mathrm{versusRHE}\n$$ \n\n$$\n\\mathrm{O}_{2}+2\\mathrm{H}_{2}\\mathrm{O}\\stackrel{0.534\\mathrm{V}}{\\longrightarrow}2\\mathrm{H}_{2}\\mathrm{O}_{2}\n$$ \n\nNote that $\\mathrm{e^{-}}$ denotes electrons and $E_{\\mathrm{red}}$ denotes reduction potential. Here we present a wastewater treatment system that successfully tackles the two aforementioned scientific challenges in regard to current AOPs. This system is enabled by two key innovations: first, we report that Cu single atoms incorporated in graphitic carbon nitride $\\mathrm{(C_{3}N_{4})}$ solve all three challenges in regard to current heterogeneous Fenton catalysts and show superb activity in activation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to generate $\\mathrm{OH^{\\bullet}}$ at $\\mathrm{pH}7.0$ . We further demonstrate the immobilization of the catalyst in a Fenton filter, which bypasses the redundancy of catalyst recovery. Second, we report the design of an electrolysis device that produces $10\\mathrm{gl}^{-1}\\mathrm{H}_{2}\\mathrm{O}_{2}^{-}$ at a total cost of $\\mathrm{US}\\$4.66\\mathrm{\\perm}^{3}$ by consuming air, electricity and 0.1 M ${\\mathrm{Na}}_{2}{\\mathrm{SO}}_{4}$ electrolyte. This device is based on (1) a novel gas diffusion electrode (GDE) to provide sufficient three-phase catalytic interfaces, (2) a three-chamber design for operation within a continuous flow reactor, (3) a carbon-based material recently reported17 to catalyse 2e-ORR, (4) anodically electrodeposited $\\mathrm{IrO}_{2}$ to catalyse OER and (5) careful selection of the electrolyte used. The Fenton filter and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser work in tandem to deliver the wastewater treatment system. We further demonstrate a $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ -carbon filter that quenches residual $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and renders the effluent safe for discharge into the environment. Small-scale pilot studies have demonstrated the feasibility of the whole system. \n\n# Results \n\nThe schematic of our wastewater treatment system is shown in Fig. 1, and includes five steps: (1) $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolysers generate $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in a 0.1 M ${\\mathrm{Na}}_{2}{\\mathrm{SO}}_{4}$ solution by consuming electricity and air; (2) the resultant $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution is added to the wastewater and mixed thoroughly; (3) the mixed solution flows through a Fenton filter where organic contaminants are oxidized; (4) the solution further flows through a $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ -carbon filter where the residual $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is quenched; and (5) the treated effluent is discharged into the environment. The Fenton filter and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser are at the heart of this system and solve the activation and production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , respectively. In the following sections we first discuss the design considerations and performance of the two components in parallel with correlation of the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentration (applied or generated), and in the final section we demonstrate the feasibility of the entire system in regard to treatment of synthetic wastewater. \n\nSingle-atom catalyst and design considerations. Concerning heterogeneous Fenton reaction, the most desirable feature provided by single-atom catalysts is the uniform dispersion of active sites in loose proximity to one another, which restrains the catalyst itself from quenching OH• (equation (5)). Therefore, we synthesized Cu-incorporated $\\mathrm{C}_{3}\\mathrm{N}_{4}$ $\\mathrm{(Cu-C_{3}N_{4})}$ (Fig. 2a) via a simple one-pot method (Methods), with $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}$ and cyanamide (mole ratio 1:20) serving as the precursor. The Cu content in $\\mathrm{Cu-C_{3}N_{4}}$ can be readily tailored by altering the mole ratio of $\\mathrm{{Cu:C}}$ in the precursor. The morphology of $\\mathrm{Cu-C_{3}N_{4}}$ was characterized by aberration-corrected high-resolution transmission electron microscopy (HR-TEM). As seen in Fig. 2b, the catalyst material consists of a homogeneous amorphous structure without the presence of Cu or $\\mathtt{C u O}$ nanoparticles. Elemental mapping (Supplementary Fig. 1) by energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) suggests the existence and uniform concentration of Cu over the $\\mathrm{C}_{3}\\mathrm{N}_{4}$ matrix. Closer observation, using aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), revealed the sole presence of isolated Cu atoms (circled in Fig. 2c). We subsequently employed Cu K-edge extended X-ray absorption fine structure spectroscopy (EXAFS) to confirm the coordination environment of $\\mathrm{Cu}$ atoms. Unlike Cu, $\\mathrm{Cu}_{2}\\mathrm{O}$ and $\\mathrm{CuO,}$ our $\\mathrm{Cu-C_{3}N_{4}}$ shows negligible $\\mathrm{{Cu-Cu}}$ interaction based on analysis of its Fourier-transformed EXAFS spectra (Fig. 2d), which is required to avoid the radical-quenching problem mentioned above. A further comparison between $\\mathrm{Cu-C_{3}N_{4}}$ and Cu-TMCPP (structural formula shown in Supplementary Fig. 2) on their EXAFS spectra shows that they share the same main peak centred around $\\mathrm{i}.\\mathrm{\\r{s}}\\mathrm{\\AA},$ corresponding to $\\mathrm{{Cu-N}}$ coordination. \n\n![](images/13807de692a4b96ce1185d55782825a069123fe2573fdc1f00c218b597e21976.jpg) \nFig. 1 | Schematic drawing of our wastewater treatment system. The system includes the ${\\sf H}_{2}{\\sf O}_{2}$ electrolyser, the Fenton filter and the $\\mathsf{F e}_{3}\\mathsf{O}_{4}$ -carbon filter. \n\nThe reason for choosing Cu and $\\mathrm{C}_{3}\\mathrm{N}_{4}$ as the active centre and hosting matrix, respectively, is that this combination provides redox sites with single-electron capacity, which favours the radical mechanism (equation (3)) over the non-radical mechanism (equation (6)) during decomposition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . In order to support this hypothesis, we probed the electronic properties of $\\mathrm{Cu-C_{3}N_{4}}$ by X-ray photoelectron spectroscopy (XPS) (Fig. 2e). As expected, the Cu LMM Auger spectrum confirmed the absence of metallic $\\operatorname{Cu}(0)$ , and the two peaks at 932.4 and $934.6\\mathrm{eV}$ in the $\\mathtt{C u2p}$ spectrum can be assigned to $\\mathtt{C u(I)}$ and $\\mathrm{{Cu}(I I)}$ , respectively, indicating that Cu single atoms can act as the desired redox sites with single-electron capacity. We further compared the N 1s and C 1s spectra of $\\mathrm{Cu-C_{3}N_{4}}$ with those of undoped $\\mathrm{C}_{3}\\mathrm{N}_{4}$ (Supplementary Fig. 3) and found negligible differences, which indicates that the introduction of Cu into the precursor does not affect the formation of $\\mathrm{C_{3}N_{4}}$ . Fourier-transformed infrared spectroscopy (FTIR) was also introduced to ascertain the local structure (Fig. 2f). In particular, the band at $1{,}314\\mathrm{cm}^{-1}$ , corresponding to the vibration of $\\scriptstyle{\\mathrm{C=N-C}}$ (ring N), is less pronounced in the spectrum of $\\mathrm{Cu-C_{3}N_{4}}$ while that at $1{,}228\\mathsf{c m}^{-1}$ , corresponding to the vibration of $\\Nu{-}(\\mathrm{C})_{3}$ (tertiary N), shows similar intensity in the two spectra25,26. These results support the EXAFS spectra, suggesting coordination of Cu atoms by $\\mathrm{C_{3}N_{4}}$ via the ring N sites. In summary, isolated Cu atoms with single-electron redox capacity were successfully incorporated into the N-coordinating cavities of $\\mathrm{C}_{3}\\mathrm{N}_{4}$ . \n\n$\\mathbf{H}_{2}\\mathbf{O}_{2}$ activation by $\\mathbf{Cu-C_{3}N_{4}}$ . To evaluate the activity of $\\mathrm{Cu-C_{3}N_{4}}$ as a heterogeneous Fenton catalyst, we used the oxidative degradation of rhodamine B (RhB) as a model reaction. As shown in Fig. 3a, degradation of RhB in the $\\mathrm{Cu-C_{3}N_{4}/H_{2}O_{2}}$ suspension reached $99.97\\%$ in only $5\\mathrm{{min}}$ while ${<}40\\%$ of RhB was removed when using conventional Cu-containing catalysts such as $\\mathrm{Cu}_{2}\\mathrm{O}$ or $\\mathtt{C u O}$ . In addition, dissolved ${\\mathrm{Cu}}^{2+}$ showed negligible homogeneous catalytic activity at $\\mathrm{pH}7.0$ . Further insights into catalytic activity were obtained by assessing the influence of $\\mathrm{Cu}$ content in $\\mathrm{Cu-C_{3}N_{4}}$ . As shown in Supplementary Fig. 4a, reducing Cu content reduced catalytic activity, suggesting that $\\mathrm{Cu}$ is the active site. On the other hand, excessive Cu in the precursor adversely affected catalyst performance due to the formation of CuO nanoparticles (Supplementary Fig. 4b). This observation supports our catalyst design considerations, that isolated single atoms are preferable to metal oxide nanoparticles when activating $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to generate OH•. \n\n![](images/d90a6acdd20757588ac0e4808f70b2595678112edc3c835848264902b2e7daa1.jpg) \nFig. 2 | Characterization of $C u-C_{3}N_{4}$ . a, Structural illustration of $C u-C_{3}N_{4}$ . b, Aberration-corrected HR-TEM image of $C u-C_{3}N_{4}$ showing the absence of crystalline structure. The darker area in the top-left corner is due to the lacey carbon of the TEM grid. Scale bar, $20\\mathsf{n m}$ . c, Aberration-corrected HAADF-STEM image of $C u-C_{3}N_{4}$ . Circles indicate single $\\mathsf{C u}$ atoms. Scale bar, $2{\\mathsf{n m}}$ . d, Normalized $k^{2}$ -weighted Fourier transform (FT) of the EXAFS spectra of $C u-C_{3}N_{4}$ and other reference materials within radial distance. e, ${\\mathsf{X P S}}\\mathsf{C u2p}$ spectrum and $\\mathsf{C u}$ LMM Auger spectrum (inset) of $C u-C_{3}N_{4}$ . The black lines denote the raw data while the coloured lines correspond to the deconvoluted components. f, FTIR spectra of $C u-C_{3}N_{4}$ and undoped $C_{3}N_{4}$ . a.u., arbitrary units. \n\nTo highlight the exceptional stability of $\\mathrm{Cu-C_{3}N_{4},}$ the RhB degradation tests were repeated for ten cycles (Supplementary Fig. 5a). Its pseudo-first-order reaction rate decreased from 1.64 to $1.08\\mathrm{{min}^{-1}}$ over the first five cycles but stabilized thereafter. XPS analysis (Supplementary Fig. 5b) revealed that the relative ratio of $\\mathrm{{Cu(I)}\\mathrm{{:Cu(II)}}}$ in the used catalyst differed from that in fresh $\\mathrm{Cu-C_{3}N_{4},}$ which supports our hypothesis that the $\\mathrm{{Cu(I)/Cu(II)}}$ redox is involved in the catalytic process. Comparison of EXAFS spectra (Supplementary Fig. 5c) between used and fresh catalysts confirmed the preservation of the single-atomic dispersion after cycles of reaction. \n\nTo identify the degradation products of RhB, we applied liquid chromatography-mass spectrometry (LC–MS). Figure 3b presents the chromatograms of a $10\\mathrm{-}\\upmu\\mathrm{M}$ RhB solution at different degradation times. The notable peaks are labelled with the corresponding $m/z$ values as measured by mass spectrometry. The peak with $m/z=443$ at retention time $4.4\\mathrm{{min}}$ relates to RhB, which decayed with increasing degradation time and finally disappeared after $5\\mathrm{{min}}$ . This observation is consistent with the results shown in Fig. 3a. A probable degradation pathway (Supplementary Fig. 6) is proposed based on the analysis of other major peaks in LC–MS chromatograms27,28. All peaks disappeared after $\\ensuremath{1\\mathrm{h}}$ of degradation, indicating that all intermediate products were mineralized to $\\mathrm{CO}_{2}$ The $\\mathrm{\\pH}$ of the solution decreased from 7.0 to 5.4 after the 1-h experiment, which also implies the production of $\\mathrm{CO}_{2}$ . \n\nTo further confirm the degree of mineralization, we measured the removal of total organic carbon (TOC) during the degradation. Due to the TOC detection limit $(0.1\\mathrm{ppm})$ , we increased the initial RhB concentration from 10 to $50\\upmu\\mathrm{M}$ , with the concentrations of $\\mathrm{Cu-C_{3}N_{4}}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ still kept at $1\\mathrm{gl^{-1}}$ . As shown in Fig. 3c, $73\\%$ of TOC remained after $25\\mathrm{min}$ when all RhB had been completely degraded. Then, the removal rate of TOC gradually increased and a mineralization degree of $95\\%$ was reached after $^\\mathrm{1h}$ . The increasing TOC removal rate agrees with the proposed degradation pathway, indicating that mineralization undergoes two different stages29: (1) scission of RhB molecules and (2) subsequent oxidation of fragments. We also analysed the inorganic nitrogen species produced during degradation (Supplementary Fig. 7) and found that nearly $90\\%$ of the amine groups in RhB were converted into inorganic species after $^{\\mathrm{1h,}}$ with $\\mathrm{NH_{4}^{+}}$ as the main mineralization end product. \n\nFenton filter. The high catalytic activity of $\\mathrm{Cu-C_{3}N_{4}}$ encouraged us to further explore its scope at the device level. Figure 4a shows an image taken of a proof-of-concept Fenton filter. Specifically, a square tube of cross-sectional area $1\\mathrm{cm}^{2}$ and length $5c\\mathrm{m}$ was filled with carbon felt, which is a porous structure composed of carbon fibres. $\\mathrm{Cu-C_{3}N_{4}}$ was coated on the surface of each carbon fibre, as shown in the scanning electron microscopy (SEM) image in Fig. 4b. A mixed solution of $10\\mathrm{ppm}$ RhB and $1\\mathrm{g}\\mathrm{l}^{-1}$ $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was passed through the Fenton filter at a flow rate of $\\mathrm{10mlh^{-1}}$ . As shown in Fig. 4c, the Fenton filter maintained $100\\%$ dye removal efficiency after $200\\mathrm{h}$ of operation (2 l of wastewater was filtered). The TOC in the effluent was below the detection limit $(0.1\\mathrm{ppm})$ throughout the course of the experiment, confirming the complete oxidation of the dye molecules. At $100\\mathrm{h}$ , we changed the pollutant from $10\\mathrm{ppm}$ RhB to $10\\mathrm{ppm}$ methylene blue (MB) to demonstrate the versatility of our Fenton filter for different pollutant molecules. A video of the filtration process is shown in Supplementary Video. \n\n![](images/8514310975b9b98237f802257904591f76b7fbc16895e1be1e8adc73a85260ea.jpg) \nFig. 3 | Catalytic activity and degradation product. a, Degradation of ${10\\upmu\\mathsf{M}}$ RhB in the presence of ${\\bar{1}}_{\\bar{8}}|^{-1}\\mathsf{H}_{2}{\\mathsf{O}}_{2}$ and selected catalysts. Reaction conditions were $10\\mathsf{m l}$ of aqueous solution, $1\\mathrm{g}\\vert^{-1}$ catalyst (if present), ${\\mathsf{p H7}}.0$ (adjusted to 7.0 at the beginning of the reaction without buffer control). b, LC–MS chromatograms of the reaction solution at different degradation time intervals. The reaction conditions are the same as those in a, with $C u-C_{3}N_{4}$ as the catalyst. c, TOC removal during the degradation of $50\\upmu\\up M$ RhB in the presence of ${\\boldsymbol{1}}_{\\mathbf{\\mathcal{E}}}|^{-1}\\mathsf{H}_{2}\\mathsf{O}_{2}$ and $\\bar{1}\\bar{8}^{|-1}\\mathsf{C u}-\\mathsf{C}_{3}\\mathsf{N}_{4}$ . Reaction conditions were $100\\mathsf{m l}$ of aqueous solution, ${\\mathsf{p H7}}.0$ . \n\nA major advantage of using $\\mathrm{Cu-C_{3}N_{4}}$ lies in its leaching resistance. Inductively coupled plasma mass spectrometry was carried out to measure the concentration of leached Cu in the effluent. As illustrated by the blue curve in Fig. 4c, the Cu concentration in the effluent finally reached a steady state of $0.1\\mathrm{ppm}$ , which is well below the goal of maximum contamination for drinking water $(1.3\\mathrm{ppm})$ set by the US Environmental Protection Agency. Because the relatively high concentration of Cu in the initial effluent can be attributed to unreacted precursors, washing the filter with water after synthesis would help reduce this leaching. Further insights into the treatment capacity of the Fenton filter were obtained by varying the flow rate and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ dosage (see further details in Supplementary Fig. 8). \n\nUp to this point we had successfully developed a Fenton filter that can remove organic contaminants from a mixed solution of wastewater and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and with no energy input—the only chemical input is $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . To further eliminate the dependence of the treatment system on $\\mathrm{H}_{2}\\mathrm{O}_{2},$ , we developed a $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser for the on-site generation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ from air, water and renewable energy. The following two sections are devoted to discussion of this electrolyser. \n\nElectrodes and electrolytes of the $\\mathbf{H}_{2}\\mathbf{O}_{2}$ electrolyser. The major challenge in developing a $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser regards the cathode for 2e-ORR. Because the ratio of $\\mathrm{~O}_{2}$ to $\\mathrm{H}_{2}\\mathrm{O}$ molecules in an aqueous solution under atmosphere is only ${\\sim}1{:}200{,}000$ , it is very easy for a conventional cathode immersed in electrolyte to reach the diffusion limit and build up a high concentration over-potential. The schematic in Fig. 5a shows our design of a GDE developed to solve this problem by directly delivering the gas reactant to the catalyst surface. We fabricated the GDE by mixing melted polyethylene (PE) and paraffin oil, then melt-pressing the composite mixture with a carbon paper and finally extracting the paraffin oil with methylene chloride. Oxidized Super P carbon black (O-SP) was drop-cast on the carbon paper side of the GDE with a loading of $0.5\\mathrm{mg}\\mathrm{cm}^{-2}$ . In this configuration, the carbon paper acts as the current collector, the porous PE functions as the hydrophobic gas diffusion layer, and the O-SP is the catalyst for 2e-ORR. $\\mathrm{~O}_{2}$ is supplied from the porous PE side and reacts at the gas–catalyst–electrolyte interface. The cross-sectional SEM image in Fig. 5b shows that our GDE has a hierarchical structure. The larger pores $(\\sim50\\upmu\\mathrm{m})$ in the carbon paper (Supplementary Fig. 9a) facilitate mass transport in the liquid phase while the smaller pores $({\\sim}2\\upmu\\mathrm{m})$ in porous PE (Fig. 5c and Supplementary Fig. 9a) provide the gas diffusion pathway and prevent flooding. \n\n![](images/4d1d14ec1a4ab0f48315e3b89df448fbdb45ecdf0ffddccc4e716c76579eb3a2.jpg) \nFig. 4 | Fenton filter. a, Image of a proof-of-concept Fenton filter: cross-sectional area, $1\\mathsf{c m}^{2}.$ ; length, $5c m$ . Scale bar, 5 cm. b, SEM image of the filter medium. Scale bar, $100\\upmu\\mathrm{m}$ Inset, magnified SEM image showing the $C u-C_{3}N_{4}$ catalyst coated on the surface of a carbon fibre. Scale bar, $5\\upmu\\mathrm{m}$ . c, Dye removal and $\\mathsf{C u}$ concentration in effluent as functions of filtration time. Flow rate, $10\\mathsf{m}|\\mathsf{h}^{-1}$ ; contact time, $30\\mathrm{min}$ ; ${\\sf H}_{2}{\\sf O}_{2}$ dosage, $1\\mathrm{g}\\lvert^{-1}$ . Pollutant, 10 ppm RhB for the first $\\mathsf{100h}$ then 10 ppm MB for the second $100\\mathsf{h}$ . \n\nThe performance of the GDE was characterized using a three-electrode configuration in a custom H-type cell (Supplementary Fig. 10). We compare our GDE with an immersed carbon paper electrode using Tafel plots (Fig. 5d), which are converted from the linear sweep voltammetry (LSV) data shown in Supplementary Fig. 9c. For the immersed electrode with pure $\\mathrm{~O}_{2}$ directly bubbled into the electrolyte, the Tafel plot drops from linearity at $0.3\\mathrm{mAcm}^{-2}$ , indicating depletion of $\\mathrm{~O}_{2}$ adjacent to the electrode. In contrast, for our GDE with pure $\\mathrm{O}_{2}$ supplied from the porous PE side, the Tafel plot remains linear up to $30\\mathrm{mAcm}^{-2}$ confirming the sufficient delivery of $\\mathrm{O}_{2}$ to the catalyst. We further substituted air for pure $\\mathrm{O}_{2}$ to determine whether our GDE can operate without a supply of pure $\\mathrm{O}_{2}$ . Although the Tafel plot deviates from linearity at high current density, $30\\mathrm{mAcm}^{-2}$ is still accessible at a reasonable over-potential. The overall potential shift of $43\\mathrm{mV}$ marked in Fig. 5d is due to the lower partial pressure of $\\mathrm{~O}_{2}$ in air, which is expected according to the Nernst equation. Another important attribute of the cathode is $2\\mathrm{e}$ -ORR selectivity relative to the four-electron reduction of $\\mathrm{O}_{2}$ to $\\mathrm{H}_{2}\\mathrm{O}.$ . As shown in Supplementary Fig. 9d, our GDE has a high 2e-ORR selectivity no matter whether $\\mathrm{O}_{2}$ is supplied in its pure state or in the form of air. \n\n![](images/23fe57766ab7fbac1be045abc3b3c7fa957404b17de15a57e5f2808ad8314572.jpg) \nFig. 5 | Electrodes and electrolytes of ${\\sf H}_{2}{\\sf O}_{2}$ electrolyser. a, Schematic drawing of the GDE for 2e-ORR. $\\mathsf{O}_{2}$ diffuses in the gas phase through the porous PE to the gas–catalyst–electrolyte interface and is then reduced by electrons transported from the carbon paper. b, Cross-sectional SEM image of the GDE, with dashed lines denoting the boundaries between components. The top surface is visible because the sample is slightly tilted. Scale bar, $50\\upmu\\mathrm{m}$ . $\\bullet,$ Magnified SEM image of the porous PE showing interconnected micron-sized pores, which provide the gas diffusion pathway and prevent flooding. Scale bar, $2\\upmu\\mathrm{m}$ . d, Comparison of the Tafel plots of a GDE supplied with pure $\\mathrm{O}_{2},$ a GDE supplied with atmospheric air and a carbon paper electrode immersed in electrolyte. All the electrodes were loaded with the same amount of catalyst $(0.5\\mathsf{m g c m^{-2}},$ . Electrolyte, 0.1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ . e, LSV curves of the ${\\mathsf{I r O}}_{2}$ anode before and after 200 cycles of continuous CV scanning in 0.1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ . Inset, image of the ${\\mathsf{I r O}}_{2}$ anode. Scale bar, $5\\mathsf{m m}$ . f, Cost estimate for producing $10\\mathrm{g}^{\\mathrm{|-1}}\\left(\\mathbb{1}\\mathrm{wt.}\\%\\right)\\mathsf{H}_{2}\\mathsf{C}$ solution using different electrolytes $(0.1M)$ , based on the condition that both electrodes are operated at $20\\mathsf{m A c m}^{-2}$ . The market price shown here is $2\\%$ of that for 50 wt.% ${\\sf H}_{2}{\\sf O}_{2}$ . \n\nIn addition to the cathode design, the anode must also be active and stable for OER. Here, we fabricated the anode by anodically electrodepositing $\\mathrm{IrO}_{2}$ on a titanium screen mesh in an oxalate-based deposition solution30. The inset of Fig. 5e shows a photo of the anode; the black colour of its lower part indicates the $\\mathrm{IrO}_{2}$ coating. The OER activity of our anode is confirmed by the LSV curve as shown in Fig. 5e. Moreover, the LSV curve after 200 cycles of continuous cyclic voltammetry (CV) scanning shows negligible difference from the initial one. To further confirm the stability of our cathode and anode, we conducted successive chronopotentiometry tests at 10, 20 and $30\\mathrm{mAcm}^{-2}$ (Supplementary Fig. 11). Both electrodes were very stable and showed no performance decay after $15\\mathrm{h}$ of operation. \n\nAs stated above, the targeted $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentration in the mixed solution flowing through the Fenton filter is $1\\mathrm{gl^{-1}}$ . Considering that a tenfold dilution is reasonable when mixing the electrolytically produced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution into wastewater, the electrolyser needs to generate $\\mathrm{H}_{2}\\mathrm{O}_{2}$ at a concentration of $10\\mathrm{gl^{-1}}$ . According to the potential of both electrodes at $20\\mathrm{mAcm}^{-2}$ and the selectivity of the cathode, we have an initial estimate of the electricity cost: $\\mathrm{\\i}\\mathrm{US}\\$2.03$ per m3. Compared with the market price of $10\\mathrm{gl}^{-1}\\mathrm{\\dot{H}}_{2}\\mathrm{O}_{2}$ 1 $\\mathrm{\\US\\$9.00}$ per m3, which is $2\\%$ of the market price of $50\\mathrm{wt.}\\%\\mathrm{H}_{2}\\mathrm{O}_{2})$ , this electricity cost is very promising. However, a considerable additional cost comes from the electrolyte, which is a key component of an electrolyser yet is often neglected. Figure 5f summarizes the total cost for producing $10\\mathrm{gl}^{-1}\\mathrm{H}_{2}\\bar{\\mathrm{O}}_{2}$ solution using different electrolytes (0.1 M). Although alkaline electrolyte provides a more stable condition for both OER and 2e-ORR, the cost of KOH and $\\mathrm{\\DeltapH}$ control suggests the need to sacrifice the activity of the catalysts for overall cost efficiency. In regard to $\\mathsf{p H}$ -neutral electrolytes, phosphate-buffered saline (PBS) is too expensive, NaCl can be oxidized to chlorine at the anode and ${\\mathrm{NaNO}}_{3}$ is a concern regarding discharge to the environment. Therefore, we chose $0.1\\mathrm{M}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ as the electrolyte, with an estimated total cost of only $\\operatorname{US}\\$2.93\\operatorname{perm}^{3}$ . \n\nReactor design and performance of the $\\mathbf{H}_{2}\\mathbf{O}_{2}$ electrolyser. \nThe $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser is composed of three chambers (Fig. 6a). \n\n![](images/51ac3cb4065c1a72b8c9f20ea027dc25cd9232e8772ec0046277aed6b2bde0a8.jpg) \nFig. 6 | Reactor design and performance of the ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ electrolyser. a, Schematic drawing of the ${\\sf H}_{2}{\\sf O}_{2}$ electrolyser. b, Front-view image (the same view direction as the schematic). Scale bar, 1 cm. c, Side-view image (from the OER chamber side). Scale bar, 1 cm. d, Operation of the electrolyser by controlling the working current and electrolyte flow rate. Air flow was maintained at $10\\mathsf{m l}\\mathsf{m i n}^{-1}$ . A $10\\mathrm{g}|^{-1}\\mathsf{H}_{2}\\mathsf{O}_{2}$ solution was produced at a total cost of $\\cup5\\$4.66$ per ${\\mathfrak{m}}^{3}$ when the working current and electrolyte flow rate were $100\\mathsf{m A}$ and $5\\mathsf{m}|\\mathsf{h}^{-1}$ , respectively. \n\nAn $\\mathrm{IrO}_{2}$ -coated titanium mesh is immersed in the electrolyte in the OER chamber as the anode. The OER chamber is separated from the ORR chamber by a Nafion film, which allows proton migration and obstructs $\\mathrm{H}_{2}\\mathrm{O}_{2}$ diffusion. A GDE seals the other side of the ORR chamber, separating it from the gas chamber. A gas tube connects the tops of the OER and gas chambers. Atmospheric air is blown into the OER chamber, carrying the generated oxygen, and then flows through the gas chamber. $\\mathrm{O}_{2}$ diffuses through the GDE as stated above and is reduced to $\\mathrm{H}_{2}\\mathrm{O}_{2};0.1\\mathrm{M}\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ electrolyte then flows through the ORR chamber and carries out the resultant $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Figure $^{\\mathrm{6b,c}}$ provides front view (the same view direction as the schematic) and side view (from the OER chamber side) images, respectively, of the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser. The cathode and anode are both $1.5\\times3.0\\mathrm{cm}^{2}$ . \n\nWe ran the electrolyser by controlling both working current and electrolyte flow rate (Fig. 6d), and the steady potential confirmed its stable operation. A $\\bar{10}\\mathrm{gl}^{-1}\\mathrm{~H}_{2}\\mathrm{O}_{2}$ solution was produced when the working current and electrolyte flow rate were maintained at $\\mathrm{{100mA}}$ and $5\\mathrm{mlh^{-1}}$ , respectively. The total cost (electricity plus electrolyte) of producing this $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution was $\\mathrm{USS4.66}$ per $\\mathbf{m}^{3}$ , which is higher than the previous estimate because of impedance loss and the self-decomposition of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Nevertheless, this value is still lower than the market price and on-site generation further eliminates the cost associated with the transportation and storage of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . \n\nOrganic wastewater treatment system. We combine the two aforementioned inventions, the Fenton filter and the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser, to present an organic wastewater treatment system. In order to quench residual $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and thus render the effluent safe for discharge to the environment, we fabricated a $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ -carbon filter via a process similar to that used to create the Fenton filter. It has the same exterior appearance as the Fenton filter yet is loaded with a different catalyst (Supplementary Fig. 12a,b). Specifically, $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ nanoparticles embedded in amorphous carbon (Supplementary Fig. 12c,d) were synthesized and immobilized on the filter medium to catalyse the disproportionation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . To characterize the performance of the filter in removal of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , we passed a $\\mathrm{1gl^{-1}H_{2}O_{2}}$ solution through the filter at a flow rate of $3\\mathrm{mlh}^{-1}$ and recorded the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentration in the effluent. The $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ -carbon filter demonstrated a very high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ removal efficiency $(>99.9\\%)$ over $\\boldsymbol{100}\\mathrm{h}$ of operation (Supplementary Fig. 12e). \n\nWe investigated the feasibility of the whole system to treat synthetic wastewater containing a mixture of $10\\mathrm{ppm}$ triclosan (antiseptic), $10\\mathrm{ppm\\17\\upalpha}$ -ethinyl oestradiol (oestrogenic birth control medication) and $10\\mathrm{ppm}$ cefazolin sodium (antibiotic). A $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser was operated at a working current of $100\\mathrm{mA}$ and electrolyte flow rate of $5\\mathrm{mlh^{-1}}$ , generating ${\\sim}10\\mathrm{gl}^{-1}\\ \\mathrm{H}_{2}\\mathrm{O}_{2}$ in a $0.1\\mathrm{M}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ solution. This solution was mixed with synthetic wastewater at a volume ratio of 1:9. The mixed solution was flowed through a Fenton filter at a flow rate of $3\\mathrm{mlh^{-1}}$ and then through a $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ -carbon filter at a flow rate of $3\\mathrm{mlh^{-1}}$ . We ran the system for $100\\mathrm{h}$ continuously, treating $270\\mathrm{ml}$ of synthetic wastewater and generating $300\\mathrm{ml}$ of effluent. We measured the TOC in the effluent and found that all three organic contaminants were completely oxidized to $\\mathrm{CO}_{2}$ . The residual $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in the effluent was also confirmed to be below the detection limit $(0.05\\mathrm{ppm})$ . We further conducted a zebrafish embryo teratogenicity analysis (Supplementary Fig. 13) to corroborate that our treatment system did not generate obviously toxic by-products. \n\n# Discussion \n\nIn this article we present strategies to address the two fundamental challenges of AOPs: the activation and production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . First, we carried out a comprehensive study to highlight the technological potential of single atoms stabilized in appropriate hosts for heterogeneous Fenton reaction. The uniform dispersion of active sites in loose proximity to one another restrains the single-atom catalyst per se from quenching OH•, which is the key problem in regard to conventional heterogeneous Fenton catalysts. We identified $\\mathrm{Cu-C_{3}N_{4}}$ as a good catalyst at $\\mathrm{pH}7.0$ and further demonstrated a Fenton filter by immobilizing the catalyst on a porous substrate, which eliminates the redundancy of catalyst recovery. Second, we fabricated a $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser that can continuously produce a $\\mathsf{p H}$ -neutral $10\\mathrm{gl}^{-1}\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution at a total cost of $\\mathrm{US}\\$4.66$ per $\\mathbf{m}^{3}$ , by consuming only air, electricity and $0.1\\mathrm{{M}}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ electrolyte, which makes it practical for on-site production and a broad array of decentralized applications. The high level of performance is attributed to the intrinsic activities of the catalysts, the novel GDE and the three-chamber flow reactor design. Finally, we coupled the Fenton filter and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ electrolyser in tandem and demonstrated a system for organic wastewater treatment. We note that additional efforts are needed to scale up the whole process; until then, we can assess its full potential by quantitatively benchmarking it with established industrial technologies. In Supplementary Discussion we identify the existing limitations of the wastewater treatment system (for example, the high $\\mathrm{H_{2}O_{2}/T O C}$ ratio, the expensive OER catalyst, the sulfate remaining in the effluent and so on), which we hope will motivate further technological advancements in the future. \n\n# Methods \n\nSynthesis of $\\mathbf{Cu-C_{3}N_{4}}$ . Typically, $2\\mathrm{g}$ of $50\\mathrm{wt.\\%}$ cyanamide aqueous solution (Alfa-Aesar) and $0.287{\\mathrm{g}}$ of $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ (Sigma-Aldrich) were added to a $\\mathrm{10{-}m l}$ glass vial. The mouth of the vial was covered by a piece of aluminum foil with four fine holes poked in it. The vial was then placed in a muffle furnace, heated to $550^{\\circ}\\mathrm{C}$ over $40\\mathrm{min}$ and maintained at this temperature for 1 h. The Cu content in Cu- $\\mathrm{C_{3}N_{4}}$ can be tailored by altering the mole ratio of Cu:C in the precursor. \n\nFabrication of the Fenton filter. A precursor solution was first prepared by dissolving $1.436\\mathrm{g}$ of $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ (Sigma-Aldrich) into $10\\mathrm{g}$ of $50\\mathrm{wt.\\%}$ cyanamide aqueous solution (Alfa-Aesar). A piece of carbon felt (Alfa-Aesar) of cross-sectional area $1\\mathrm{cm}^{2}$ and length $5c\\mathrm{m}$ was treated by $\\mathrm{O}_{2}$ plasma for 5 min and then dipped in the precursor solution; $4.5\\mathrm{g}$ of the precursor solution was absorbed by the carbon felt and excess solution was gently squeezed out. The carbon felt was wrapped in a piece of aluminum foil without drying and then placed in a tube furnace, heated to $550^{\\circ}\\mathrm{C}$ for $40\\mathrm{min}$ under 1-atm Ar and maintained at this temperature for 1 h. The side faces of the carbon felt were then sealed by epoxy (Devcon 5 Minute Epoxy) and wrapped in a piece of duct tape (3 M). \n\nSynthesis of Cu-TMCPP. $\\mathrm{cu}$ -TMCPP was synthesized according to a previous report31, with minor modification: $3.0\\mathrm{g}$ of Pyrrole (ACROS Organics) and $6.9\\mathrm{g}$ of methyl p-formylbenzoate (ACROS Organics) were added to $\\boldsymbol{100}\\mathrm{ml}$ of refluxed propionic acid (Fisher Chemical) and the solution was refluxed for $12\\mathrm{h}$ with a stirring bar. Crystals were then collected by suction-filtration to afford purple crystals (TMCPP, $1.9\\mathrm{g},21.3\\%$ yield). Next, $0.854\\mathrm{g}$ of TMCPP and $2.2\\mathrm{g}$ of $\\mathrm{CuCl}_{2}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O}$ (Sigma-Aldrich) were dissolved in $\\boldsymbol{100}\\mathrm{ml}$ of dimethylformamide (Fisher Chemical) and the solution was refluxed for 6 h. After the mixture was cooled, $150\\mathrm{ml}$ of deionized water was added. The precipitate thus obtained was filtered and repeatedly washed with deionized water and methanol. The solid was dissolved in $\\mathrm{CHCl}_{3},$ , followed by washing three times with deionized water. The organic layer was dried over anhydrous magnesium sulfate (Sigma-Aldrich) and evaporated to afford dark red crystals (Cu-TMCPP). \n\nSynthesis of O-SP. O-SP was synthesized according to our previous report17, with minor modification: $0.2\\mathrm{g}$ of Super P carbon black (Alfa-Aesar) and $200\\mathrm{ml}$ of $12\\mathrm{M}$ nitric acid (Sigma-Aldrich) were added to a three-necked, round-bottomed glass flask connected to a reflux condenser. The reaction flask, a magnetic stirrer and a thermometer were mounted in a preheated water bath. The temperature was maintained at $80^{\\circ}\\mathrm{C}$ for $48\\mathrm{h}$ . Next, the slurry was removed, cooled, centrifuged and washed with deionized water and ethanol several times until the $\\mathrm{\\DeltapH}$ was neutral. Finally, the sample was dried at $60^{\\circ}\\mathrm{C}$ in a vacuum oven overnight. \n\nFabrication of GDE. High-density PE (Sigma-Aldrich) was mixed with ultra-high-molecular-weight PE (Alfa-Aesar) at a weight ratio of 4:1 in paraffin oil (light; Fisher Chemical) at a temperature of ${\\sim}200^{\\circ}\\mathrm{C}$ . The volume of paraffin oil was five times the weight of PE. The composite mixture was melt-pressed into a thin film at $80^{\\circ}\\mathrm{C}$ . A piece of carbon paper (AvCarb MGL190) was then laminated with the film by melt-pressing again. Finally, the paraffin oil was extracted from the film using methylene chloride (Fisher Chemical). \n\nFabrication of the $\\mathbf{IrO}_{2}$ anode. $\\mathrm{IrO}_{2}$ was anodically electrodeposited on a titanium screen mesh according to a previous report30, with minor modification. To prepare the electrodeposition solution, $0.15\\mathrm{g}$ of $\\mathrm{IrCl}_{4}{\\cdot}\\mathrm{H}_{2}\\mathrm{O}$ (Sigma-Aldrich) was dissolved in $\\mathrm{100ml}$ of deionized water. Then, $0.5\\mathrm{g}$ of oxalic acid (Sigma-Aldrich) and $\\mathrm{1ml}$ of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ aqueous solution $(30\\mathrm{wt.\\%}$ , Sigma-Aldrich) were added. After $10\\mathrm{min}$ of stirring, the pH was slowly raised to 10.5 by stepwise addition of $\\mathrm{K}_{2}\\mathrm{CO}_{3}$ (Sigma-Aldrich). After preparation, the solution was heated to $90^{\\circ}\\mathrm{C}$ for $15\\mathrm{min}$ and subsequently cooled down to room temperature. Electrodeposition of $\\mathrm{IrO}_{2}$ was carried out by application of a constant current $(0.16\\mathrm{mAcm^{-2}}^{\\cdot}$ on a titanium mesh (Fuel Cell Store) in a two-electrode cell for $15\\mathrm{min}$ , with a graphite rod (Sigma-Aldrich) as the counter-electrode. \n\nFabrication of the $\\mathbf{Fe}_{3}\\mathbf{O}_{4}$ -carbon filter. A precursor solution was first prepared by dissolving $_{4\\mathrm{g}}$ of $\\mathrm{Fe(NO_{3})_{3}}{\\cdot}9\\mathrm{H}_{2}\\mathrm{O}$ (Sigma-Aldrich) and $0.4\\mathrm{g}$ of polyvinyl polypyrrolidone (Sigma-Aldrich) in $5.6\\mathrm{ml}$ of deionized water. A piece of carbon felt (Alfa-Aesar) of cross-sectional area $\\scriptstyle1\\cos^{2}$ and length $5c\\mathrm{m}$ was treated by $\\mathrm{~O}_{2}$ plasma for $5\\mathrm{{min}}$ and dipped in the precursor solution, then $4.5\\mathrm{g}$ of the precursor solution was absorbed by the carbon felt. Excess solution was gently squeezed out. The carbon felt was dried at $60^{\\circ}\\mathrm{C}$ in a vacuum oven overnight. After drying, the carbon felt was placed in a tube furnace and heated to $500^{\\circ}\\mathrm{C}$ for 1 h under 1 atm Ar and maintained at this temperature for $1.5\\mathrm{h}$ . The side faces of the carbon felt were then sealed by epoxy (Devcon 5 Minute Epoxy) and wrapped in a piece of duct tape (3 M). \n\nElectron microscopy. The SEM images were taken using an FEI XL30 Sirion SEM with an acceleration voltage of $5\\mathrm{kV.}$ The HR-TEM images and EDS mapping were taken by a FEI Titan 80–300 environmental (scanning) TEM operated at $300\\mathrm{keV.}$ The HAADF-STEM images were taken on a TEAM 0.5 microscope operated at $300\\mathrm{kV}.$ The samples were prepared by dropping catalyst powder dispersed in ethanol onto carbon-coated copper (or gold) TEM grids (Ted Pella) using micropipettes and were dried under ambient conditions. For imaging and EDS, copper and gold TEM grids, respectively, were used. \n\nSpectroscopy. The Cu K-edge EXAFS spectra were collected at Beamline 4-3 of Stanford Synchrotron Radiation Lightsource. We ran $\\mathrm{CuK}$ -edge in the range $8.878\\mathrm{-}9.778\\mathrm{keV}$ in fluorescence mode with a step size of $0.25\\mathrm{eV}$ at the near edge. The XPS spectra were collected using a PHI VersaProbe Scanning XPS Microprobe with an Al $(\\operatorname{K}\\upalpha)$ source. The FTIR spectra were measured using a Nicolet $\\mathrm{i}\\mathrm{S}50\\mathrm{FT}/$ IR spectrometer in attenuated total reflectance mode. \n\nMeasurement of the catalytic activity of $\\mathbf{Cu-C_{3}N_{4}}$ . All experiments were conducted under conditions of darkness, to eliminate the effect of photocatalysis. In a typical vial experiment, $1\\mathrm{gl^{-1}}$ prepared catalyst powder was dispersed in $10\\mathrm{ml}$ of $10\\upmu\\mathrm{M}$ RhB aqueous solution. The pH was then adjusted to 7.0 using a 1 M aqueous solution of either $\\mathrm{\\DeltaNaOH}$ or $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ . After establishment of adsorption/ desorption equilibrium $\\ensuremath{\\mathrm{:10}}\\ensuremath{\\mathrm{min}})$ , $\\mathrm{1gl^{-1}H_{2}O_{2}}$ was added to the pollutant suspension under stirring throughout the experiment. At time intervals, $\\mathrm{1ml}$ of the suspension was collected and centrifuged at $10,000{\\mathrm{r.p.m}}$ . for 30 s, then $400\\upmu\\mathrm{l}$ of the supernatant was sampled and analysed immediately. \n\nQuantification of organic contaminants. The pollutant concentration was measured by high-performance liquid chromatography (HPLC; Agilent 1260) equipped with a UV detector and a Zorbax Eclipse SB-C18 column $(2.7\\upmu\\mathrm{m}$ , $3.0\\times50\\mathrm{mm}^{2}$ ). The sample injection volume was $50\\upmu\\mathrm{l}$ . The isocratic mobile phase contained $40\\%$ 5 mM $\\mathrm{H}_{2}S\\mathrm{O}_{4}/60\\%$ methanol (v:v) at a flow rate of $0.7\\mathrm{ml}\\mathrm{min}^{-1}$ . The detector wavelength was set at $554\\mathrm{nm}$ for measurement of RhB, and at $665\\mathrm{nm}$ for MB. The degradation products of RhB were analysed by LC–MS (Agilent 6460 Triple Quad LC–MS equipped with an Agilent 1260 LC front end). The sample injection volume was $50\\upmu\\mathrm{l}$ . Samples were chromatographically separated using a Zorbax Eclipse SB-C18 column at a flow rate of $0.2\\mathrm{ml}\\mathrm{min}^{-1}$ . The mobile phase contained $5\\mathrm{mM}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and methanol. The vol. $\\%$ of methanol was decreased from 80 to 50 within $9\\mathrm{{min}}$ . Electrospray ionization–mass spectrometry analysis was performed in positive mode. TOC was determined using a Shimadzu TOC-L analyser with high-temperature combustion. The concentration of ${\\mathrm{Cu}}^{2+}$ was measured using inductively coupled plasma mass spectrometry on a Thermo Scientific XSeries II. \n\nElectrochemical measurements. The electrochemical experiments were conducted at $25^{\\circ}\\mathrm{C}$ in an H-type electrochemical cell separated by a Nafion 117 membrane (Chemours). A Pt plate was used as the counter-electrode when testing the 2e-ORR electrode; a graphite rod (Sigma-Aldrich) was used as the counter-electrode when testing the OER electrode. Both the working and reference electrode were laid to one side of the H-type cell. A computercontrolled Bio-Logic VSP Potentiostat was used for all electrochemical experiments. CV and LSV tests were performed by sweeping the working electrode potential from open circuit potential at a scan rate of $10\\mathrm{mVs^{-1}}$ . All the potentials were measured against a saturated calomel reference electrode (SCE) and converted to the reversible hydrogen electrode (RHE) reference: $E$ (versus $\\mathrm{RHE})=E$ (versus $\\mathrm{SCE})+0.240\\mathrm{V}+0.0591\\mathrm{V}\\times\\mathrm{pH}.$ . The potentials were also iR corrected to compensate for ohmic electrolyte resistance using the $E-i R$ relation, where $i$ is current and $R$ is electrolyte resistance measured via high-frequency AC impedance. \n\nQuantification of $\\mathbf{H}_{2}\\mathbf{O}_{2}.$ The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentration was measured by a traditional $\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ titration method based on the principle that a yellow solution of ${\\mathrm{Ce^{4+}}}$ will be reduced by $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to colourless $C e^{3+}$ . $\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ solution $(1\\mathrm{mM})$ was prepared by dissolving $33.2\\mathrm{mg}$ of $\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ in $100\\mathrm{ml}$ of $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution. To obtain the calibration curve, $\\mathrm{H}_{2}\\mathrm{O}_{2}$ of known concentration was added to the $\\mathrm{Ce}(\\mathrm{SO}_{4})_{2}$ solution and measured using an Agilent Cary 6000i UV/Vis/NIR Spectrometer at $316\\mathrm{nm}$ . Based on the linear relationship between signal intensity and $\\mathrm{Ce^{4+}}$ concentration, $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentrations of the samples could be obtained. \n\nTeratogenicity studies in zebrafish embryos. All animal procedures were performed according to National Institutes of Health (NIH) guidelines and were approved by the Committee on Administrative Panel on Laboratory Animal Care at Stanford University. Three fish culture media were prepared by adding the synthetic polluted water, the treated effluent or deionized water (blank control) to standard E3 medium at a volume ratio of 1:2. E3 medium contains $5\\mathrm{mM}$ NaCl, 0.17 mM KCl, $0.33\\mathrm{mMCaCl_{2}}$ and $0.33\\mathrm{mMMgSO_{4}}$ . Zebrafish zygotes were obtained from wild-type adults and cultured in standard E3 medium at $28^{\\circ}\\mathrm{C}$ . Dead and unfertilized eggs were discarded at 4 h post fertilization (hpf), while fertilized embryos were transferred into three $_{10\\mathrm{-cm}}$ culture dishes at about 120 embryos per dish. The medium was carefully removed from each dish and the embryos were then rinsed twice with $3\\mathrm{ml}$ of medium containing either synthetic polluted water, treated effluent or deionized water. Each dish was then filled with $39\\mathrm{ml}$ of the corresponding medium and the embryos were gently transferred to 96-well plates (one embryo in $300\\upmu\\mathrm{l}$ of medium per well) and cultured at $28^{\\circ}\\mathrm{C}$ . Embryo development was monitored, and representative images were acquired at 24, 48, 72, 96, 120 and 144 hpf. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon request. \n\nReceived: 17 July 2019; Accepted: 6 October 2020; Published: xx xx xxxx \n\n# References \n\n1.\t Miklos, D. B. et al. Evaluation of advanced oxidation processes for water and wastewater treatment—a critical review. Water Res. 139, 118–131 (2018). \n2.\t Chuang, Y.-H., Chen, S., Chinn, C. J. & Mitch, W. A. Comparing the UV/ monochloramine and UV/free chlorine advanced oxidation processes (AOPs) to the UV/hydrogen peroxide AOP under scenarios relevant to potable reuse. Environ. Sci. Technol. 51, 13859–13868 (2017). \n3.\t Hodges, B. C., Cates, E. L. & Kim, J.-H. Challenges and prospects of advanced oxidation water treatment processes using catalytic nanomaterials. Nat. Nanotechnol. 13, 642–650 (2018). \n4.\t Glaze, W. H., Kang, J.-W. & Chapin, D. H. The chemistry of water treatment processes involving ozone, hydrogen peroxide and ultraviolet radiation. Ozone Sci. Eng. 9, 335–352 (1987). \n5.\t Katsoyiannis, I. A., Canonica, S. & von Gunten, U. Efficiency and energy requirements for the transformation of organic micropollutants by ozone, $\\mathrm{O_{3}/H_{2}O_{2}}$ and $\\mathrm{UV/H_{2}O_{2}}$ . Water Res. 45, 3811–3822 (2011). \n6.\t Neyens, E. & Baeyens, J. A review of classic Fenton’s peroxidation as an advanced oxidation technique. J. Hazard. Mater. 98, 33–50 (2003). \n7.\t Nidheesh, P. V. Heterogeneous Fenton catalysts for the abatement of organic pollutants from aqueous solution: a review. RSC Adv. 5, 40552–40577 (2015). \n8.\t Pham, A. L.-T., Lee, C., Doyle, F. M. & Sedlak, D. L. A silica-supported iron oxide catalyst capable of activating hydrogen peroxide at neutral pH values. Environ. Sci. Technol. 43, 8930–8935 (2009). \n9.\t Lyu, L., Zhang, L., Wang, Q., Nie, Y. & Hu, C. Enhanced Fenton catalytic efficiency of $\\gamma\\mathrm{-Cu\\mathrm{-}A l_{2}O_{3}}$ by $\\upsigma\\mathrm{-}\\mathrm{Cu}^{2+}.$ –ligand complexes from aromatic pollutant degradation. Environ. Sci. Technol. 49, 8639–8647 (2015). \n10.\tCosta, R. C. C. et al. Novel active heterogeneous Fenton system based on $\\mathrm{Fe}_{3-\\mathrm{x}}\\mathrm{M}_{\\mathrm{x}}\\mathrm{O}_{4}$ (Fe, Co, Mn, Ni): the role of $\\mathbf{M}^{2+}$ species on the reactivity towards $\\mathrm{{H}}_{2}\\mathrm{{O}}_{2}$ reactions. J. Hazard. Mater. 129, 171–178 (2006). \n11.\tGao, L. et al. Intrinsic peroxidase-like activity of ferromagnetic nanoparticles. Nat. Nanotechnol. 2, 577–583 (2007). \n12.\tNavalon, S., Alvaro, M. & Garcia, H. Heterogeneous Fenton catalysts based on clays, silicas and zeolites. Appl. Catal. B 99, 1–26 (2010). \n13.\tNavalon, S., Dhakshinamoorthy, A., Alvaro, M. & Garcia, H. Heterogeneous fenton catalysts based on activated carbon and related materials. ChemSusChem 4, 1712–1730 (2011). \n14.\tBataineh, H., Pestovsky, O. & Bakac, A. pH-induced mechanistic changeover from hydroxyl radicals to iron(IV) in the Fenton reaction. Chem. Sci. 3, \n1594–1599 (2012). \n15.\tLin, S.-S. & Gurol, M. D. Catalytic decomposition of hydrogen peroxide on iron oxide: kinetics, mechanism, and implications. Environ. Sci. Technol. 32, \n1417–1423 (1998). \n16.\tCampos-Martin, J. M., Blanco-Brieva, G. & Fierro, J. L. G. Hydrogen peroxide synthesis: an outlook beyond the anthraquinone process. Angew. Chem. Int. Ed. Engl. 45, 6962–6984 (2006). \n17.\tLu, Z. et al. High-efficiency oxygen reduction to hydrogen peroxide catalysed by oxidized carbon materials. Nat. Catal. 1, 156–162 (2018). \n18.\tKim, H. W. et al. Efficient hydrogen peroxide generation using reduced graphene oxide-based oxygen reduction electrocatalysts. Nat. Catal. 1, \n282–290 (2018). \n19.\tSiahrostami, S. et al. Enabling direct $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production through rational electrocatalyst design. Nat. Mater. 12, 1137–1143 (2013). \n20.\tChoi, C. H. et al. Tuning selectivity of electrochemical reactions by atomically dispersed platinum catalyst. Nat. Commun. 7, 10922 (2016). \n21.\tXia, C., Xia, Y., Zhu, P., Fan, L. & Wang, H. Direct electrosynthesis of pure aqueous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solutions up to $20\\%$ by weight using a solid electrolyte. Science \n366, 226–231 (2019). \n22.\tChen, Z. et al. Development of a reactor with carbon catalysts for modular-scale, low-cost electrochemical generation of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . React. Chem. Eng. 2, 239–245 (2017). \n23.\tMurayama, T. & Yamanaka, I. Electrosynthesis of neutral $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution from $\\mathrm{O}_{2}$ and water at a mixed carbon cathode using an exposed solid-polymerelectrolyte electrolysis cell. J. Phys. Chem. C. 115, 5792–5799 (2011). \n24.\tYamanaka, I. & Murayama, T. Neutral $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis by electrolysis of water and $\\mathrm{~O}_{2}$ . Angew. Chem. Int. Ed. Engl. 47, 1900–1902 (2008). \n25.\t Bojdys, M. J., Müller, J.-O., Antonietti, M. & Thomas, A. Ionothermal synthesis of crystalline, condensed, graphitic carbon nitride. Chemistry 14, \n8177–8182 (2008). \n26.\tLiu, J., Zhang, T., Wang, Z., Dawson, G. & Chen, W. Simple pyrolysis of urea into graphitic carbon nitride with recyclable adsorption and photocatalytic activity. J. Mater. Chem. 21, 14398–14401 (2011). \n27.\tNatarajan, T. S., Thomas, M., Natarajan, K., Bajaj, H. C. & Tayade, R. J. Study on UV-LED $\\mathrm{\\DeltaTiO}_{2}$ process for degradation of rhodamine B dye. Chem. Eng. J. \n169, 126–134 (2011). \n28.\tHe, Z. et al. Photocatalytic degradation of rhodamine B by ${\\mathrm{Bi}}_{2}{\\mathrm{WO}}_{6}$ with electron accepting agent under microwave irradiation: mechanism and pathway. J. Hazard. Mater. 162, 1477–1486 (2009). \n29.\t Fu, H., Pan, C., Yao, W. & Zhu, Y. Visible-light-induced degradation of rhodamine B by nanosized ${\\mathrm{Bi}}_{2}{\\mathrm{WO}}_{6}.$ J. Phys. Chem. B 109, 22432–22439 (2005). \n30.\tYamanaka, K. Anodically electrodeposited iridium oxide films (AEIROF) from alkaline solutions for electrochromic display devices. Jpn. J. Appl. Phys. \n28, 632 (1989). \n31.\tFeng, D. et al. Zirconium-metalloporphyrin PCN-222: mesoporous metal–organic frameworks with ultrahigh stability as biomimetic catalysts. Angew. Chem. Int. Ed. Engl. 51, 10307–10310 (2012). \n\n# Acknowledgements \n\nPart of this work was performed at the Stanford Nano Shared Facilities, supported by the National Science Foundation under award no. ECCS-1542152. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under contract no. DE-AC02-76SF00515. Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the US Department of Energy under contract no. DE-AC02-05CH11231. The teratogenicity experiment was supported by NIH grant no. R35 GM127030. \n\n# Author contributions \n\nJ.X. and Y.C. conceived the idea. J.X. performed the experiments. X.Z. performed the EXAFS and STEM characterizations. Z.F. performed the teratogenicity studies. Z.L. synthesized the O-SP. W.H., Y.L. and Z.Z. performed the HR-TEM and EDS characterizations. D.V. and Y.L. helped with the HPLC and LC–MS measurements. S.D. helped with the STEM characterizations. K.W. synthesized Cu-TMCPP. Z.L. and G.C. helped with quantification of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ H.W. and Z.Z. helped with electrochemistry experiments. J.X. and Y.C. wrote the manuscript with input from all co-authors. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\nAdditional information \nSupplementary information is available for this paper at https://doi.org/10.1038/ s41893-020-00635-w. \n\nCorrespondence and requests for materials should be addressed to Y.C. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. $\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2020 " + }, + { + "id": "10.1038_s41467-021-21595-5", + "DOI": "10.1038/s41467-021-21595-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-21595-5", + "Relative Dir Path": "mds/10.1038_s41467-021-21595-5", + "Article Title": "Modulating electronic structure of metal-organic frameworks by introducing atomically dispersed Ru for efficient hydrogen evolution", + "Authors": "Sun, YM; Xue, ZQ; Liu, QL; Jia, YL; Li, YL; Liu, K; Lin, YY; Liu, M; Li, GQ; Su, CY", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Developing high-performance electrocatalysts toward hydrogen evolution reaction is important for clean and sustainable hydrogen energy, yet still challenging. Herein, we report a single-atom strategy to construct excellent metal-organic frameworks (MOFs) hydrogen evolution reaction electrocatalyst (NiRu0.13-BDC) by introducing atomically dispersed Ru. Significantly, the obtained NiRu0.13-BDC exhibits outstanding hydrogen evolution activity in all pH, especially with a low overpotential of 36mV at a current density of 10mAcm(-2) in 1M phosphate buffered saline solution, which is comparable to commercial Pt/C. X-ray absorption fine structures and the density functional theory calculations reveal that introducing Ru single-atom can modulate electronic structure of metal center in the MOF, leading to the optimization of binding strength for H2O and H*, and the enhancement of HER performance. This work establishes single-atom strategy as an efficient approach to modulate electronic structure of MOFs for catalyst design. Developing high-performance, neutral-media H-2-evolution electrocatalysts is important for clean and sustainable hydrogen energy, yet rare, expensive elements are most active. Here, authors show that metal-organic frameworks modified with single ruthenium atoms as high-performances catalysts.", + "Times Cited, WoS Core": 489, + "Times Cited, All Databases": 498, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000626168500025", + "Markdown": "# Modulating electronic structure of metal-organic frameworks by introducing atomically dispersed Ru for efficient hydrogen evolution \n\nYamei Sun1,3, Ziqian Xue1,3, Qinglin Liu1, Yaling Jia1, Yinle Li1, Kang Liu2, Yiyang Lin2, Min Liu $\\textcircled{1}$ 2, Guangqin Li1✉ & Cheng-Yong Su 1 \n\nDeveloping high-performance electrocatalysts toward hydrogen evolution reaction is important for clean and sustainable hydrogen energy, yet still challenging. Herein, we report a single-atom strategy to construct excellent metal-organic frameworks (MOFs) hydrogen evolution reaction electrocatalyst $(\\mathsf{N i R u}_{0.13}–\\mathsf{B D C})$ by introducing atomically dispersed Ru. Significantly, the obtained $\\mathsf{N i R u}_{0.13}$ -BDC exhibits outstanding hydrogen evolution activity in all pH, especially with a low overpotential of $36\\mathsf{m V}$ at a current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ in 1 M phosphate buffered saline solution, which is comparable to commercial Pt/C. X-ray absorption fine structures and the density functional theory calculations reveal that introducing Ru single-atom can modulate electronic structure of metal center in the MOF, leading to the optimization of binding strength for $H_{2}O$ and $\\mathsf{H}^{\\star}.$ , and the enhancement of HER performance. This work establishes single-atom strategy as an efficient approach to modulate electronic structure of MOFs for catalyst design. \n\nT ohf ilinvcirnega iengvicronsmuemnpt dornivoe fpoesosipl fe etlos enxdp odreet einorviartion- mental friendly and sustainable energy sources as alternatives for the traditional fossil fuels1–4. Among them, hydrogen is considered as the most promising substitute because of its high gravimetric energy density as well as zero $\\mathrm{CO}_{2}$ emission5–8. Recently, electrochemical water splitting, generally including two half-reactions, hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), has aroused increasing interests9–12. HER, producing low-cost and high purity hydrogen gas, is the hot spot in energy-conversion technologies and arouses increasing interests. Up to now, Pt is recognized as the high-performance electrocatalyst due to its fast dynamics and low overpotential13–16. Despite of the high efficiency, the high cost and scarcity impede its large-scale application and drive people to pursue more cheap and efficient electrocatalysts17–21. \n\nMetal-organic frameworks (MOFs) are a class of emerging porous crystalline materials22–25 composed of variety organic ligands and metal centers with various applications, such as water splitting26–29, gas storage30–32 and metal–air batteries33–37. Benefitting from flexible tunability and well-defined structure of MOFs, their performance can be optimized using fundamental molecular chemistry principles38. This makes MOFs as promising model catalysts for investigating the design of catalysts at the molecular level. Though, some approaches including metal node engineering39, missing-linker $\\mathbf{MOF^{40}}$ and lattice-strained $\\mathrm{MOF^{41}}$ have been reported to design advanced OER electrocatalysts. Developing efficient strategies to regulate electrocatalytic performance of MOFs for HER is challenging. \n\nCurrently, single-atom catalysts (SACs) have intrigued new interests in heterogenous electrocatalysis because of their outstanding activity and maximum atom utilization efficiency42,43. The impressive catalytic activity of SACs greatly results from the distinctive electronic structure of single metal atoms and the interaction between single metal atoms and supports44–47. So, beyond serving as active sites, incorporating single-atom metals into catalysts can also lead to the local electronic structure modulation of initial catalysts48, owning to the electronic interaction between them. Moreover, the incorporation of atomically dispersed single-atom can preserve the structural feature of original materials. All of these aspects provide promising opportunity to introduce single-atom to enhance the electrocatalytic performance of MOFs. \n\nHerein, we propose a single-atom strategy to tailor HER performance of the MOF Ni-BDC $(\\mathrm{Ni}_{2}(\\mathrm{OH})_{2}(\\bar{\\mathrm{C}}_{8}^{\\cdot}\\mathrm{H}_{4}\\mathrm{O}_{4})^{49,50}$ , $\\mathrm{H}_{2}\\mathrm{BDC};$ terephthalic acid) by introducing atomically dispersed Ru (named as $\\mathrm{NiRu}_{0.13}$ -BDC). Remarkably, the as-synthesized catalyst performs enhanced activity toward HER in all $\\mathsf{p H}$ . The optimized $\\mathrm{NiRu}_{0.13}$ -BDC catalyst exhibits high HER performance with a low overpotential of $36\\mathrm{mV}$ at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ and a Tafel slope of $32\\mathrm{m}\\mathrm{\\bar{V}}\\mathrm{dec}^{-1}$ , which are much improved compared with pure NiBDC in $1\\mathrm{M}$ phosphate buffered saline (PBS) solution. More importantly, combining with calculation results, the electronic structure of $\\mathrm{\\DeltaNi}$ can be regulated by the construction of Ru singleatom into Ni-BDC, thus optimizing the adsorption strength for $_\\mathrm{H}_{2}\\mathrm{O}$ and $\\mathrm{H^{*}}$ and contributing to the enhanced performance. \n\n# Results \n\nSynthesis and characterization of $\\mathbf{NiRu}_{0.13}$ -BDC. First, a pristine MOF nanosheet array supported on Ni foam was prepared by a hydrothermal method. Furthermore, the structure of initial MOF material was introduced as “Ni-BDC” with layered-pillared structure constructed by the coordinated octahedrally divalent Ni and terephthalic acid $(\\mathrm{H}_{2}\\mathrm{BDC})$ , where the terephthalates are coordinated and pillared directly to the Ni hydroxide layers and form a three-dimensional framework (Supplementary Fig. 1)50. Ru single-atom catalyst supported on Ni-BDC growing on nickel foam was synthesized by replacing part of Ni atoms through an ion-exchange method (Fig. 1a, Supplementary Fig. 1b and details in the Method section). Through varying the amount of ${\\mathrm{RuCl}}_{3}.$ a series of catalysts with different loading amount of Ru were synthesized. The content of Ru was determined by inductively coupled plasma mass spectrometry (ICP-MS) (Supplementary Table 1). The structures of these materials were firstly studied by powder X-ray diffraction (XRD). As revealed in Supplementary Fig. 4, $\\mathrm{NiRu}_{0.09}$ -BDC and $\\mathrm{NiRu}_{0.13}$ -BDC have the similar diffraction patterns as Ni-BDC, the diffraction peak appeared at 8.9 was identified to the characteristic (2,0,0) facet of the $\\mathrm{\\hat{N}i-B D C^{49,50}}$ , indicating the similar crystal structure. When the loading amount is higher than $13\\%$ , the structure of the MOF was destroyed, as shown in Supplementary Figs. 2 and 4. To further certify the structure of $\\mathrm{NiRu}_{0.13}$ -BDC, $\\mathrm{NiRu}_{0.13}$ -BDC powder sample was also synthesized via the same method excepting for the addition of nickel foam. As shown in Supplementary Fig. 5, the $\\mathrm{NiRu}_{0.13}$ -BDC powder exhibited the similar diffraction peaks as Ni-BDC. \n\nThe morphologies and microstructures of these catalysts were deeply investigated by scanning electron microscope (SEM) and transmission electron microscope (TEM). As disclosed in Fig. 1b, c and Supplementary Fig. 2, $\\mathrm{NiRu}_{0.13}$ -BDC, $\\mathrm{NiRu}_{0.09}$ -BDC, and Ni-BDC showed uniform nanosheets morphology assembling on nickel foam. High-resolution TEM images in Supplementary Fig. 3 revealed the lattice fringe spacing of $1.04\\mathrm{nm}$ , corresponding to the (200) plane of Ni-BDC. After introducing Ru, the lattice fringe spacing kept unchanged and no obvious nanoparticles exhibited. When the loading amount of $\\mathtt{R u}$ increased to $21\\%$ , the structure of $\\mathrm{NiRu}_{0.21}$ -BDC was completely destroyed, only aggregated bulk formed. The energy dispersive spectroscopy (EDS) of $\\mathrm{NiRu}_{0.13}$ -BDC in Fig. 1d further demonstrated the elements of C, O, Ni, and $\\mathtt{R u}$ distribute uniformly. In addition, ICP-MS analysis was also collected to determine the elements content, showing coexistence of Ni and Ru with a molar ratio of 0.13 $\\left(\\mathrm{{Ru}/\\mathrm{{Ni}}}\\right)$ , further confirming the successful doping of Ru. \n\nTo further investigate the chemical composition and electronic structure of the $\\mathrm{NiRu}_{0.13}$ -BDC, $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) was conducted. From Fig. 2a and Supplementary Fig. 6, the XPS spectra of the $\\mathrm{NiRu}_{0.13}$ -BDC demonstrated the coexistence of Ni, Ru, O, and C elements. Compared with Ni-BDC, after introducing Ru atoms, the $\\mathrm{Ru}~3p$ spectra (Fig. 2b) can be clearly detected in $\\mathrm{{NiRu}}_{0.13}–\\mathrm{{BDC}},$ further proving the successful doping of Ru. In addition, the $\\mathrm{Ru}~3p$ peaks located at 462.9 and $485.5\\mathrm{eV}$ were assigned to $\\mathrm{Ru}^{3+}3p_{3/2}$ and ${\\mathrm{Ru}}^{3+}$ $3p_{1/2},$ conforming the oxided state of $\\mathtt{R u}$ rather than metallic51–56. Meanwhile, there is a pair of peaks with an energy of 281.9 and $286.4\\:\\mathrm{eV}$ , which can be assigned to Ru $3d_{5/2}$ and Ru $3d_{3/2}$ in the C 1s and $\\ensuremath{\\mathrm{Ru}}3d$ spectra (Supplementary Fig. 6) in comparision with Ni-BDC51–56, indicating the valance state of ${\\mathrm{Ru}}^{3+}$ and the successful incorporation of Ru single-atom into Ni-BDC. The remaining three peaks can be contributed to $\\scriptstyle{\\mathrm{C}}={\\mathrm{C}}$ bond at $284.8\\mathrm{eV}$ , C–O bond at $285.8\\mathrm{eV}$ and $0{-}C{=}0$ bond at $288.8\\mathsf{e V}^{57}$ , in conformity with that of Ni-BDC. For $\\mathrm{NiRu}_{0.09}$ -BDC (Supplementary Fig. 6b), the $\\mathrm{Ru}~3p$ peaks with binding energy of 463.4 and $485.8\\:\\mathrm{eV}$ were also result from the oxidized Ru. While, from $\\mathrm{Ru}~3p$ of $\\mathrm{NiRu}_{0.21}\\mathrm{-}$ BDC, the peaks located at 461.7 and $484.3\\mathrm{eV}$ for Ru $3p_{3/2}$ and $3p_{1/2}$ are assigned to metallic $\\begin{array}{r}{\\mathrm{{Ru}},}\\end{array}$ indicating the formation of $\\mathtt{R u}$ nanoparticles51–56. The $\\mathrm{Ni}~2p$ spectra (Fig. 2c) of Ni-BDC show two characteristic peaks at 855.9 and $873.2\\mathrm{eV}$ , identified as Ni $2p_{3/2}$ and Ni $2p_{1/2}$ severally, which were the characteristic peaks of the $\\mathrm{Ni}^{2+57,58}$ . The Ni $2p$ binding energy of $\\mathrm{NiRu}_{0.13}$ -BDC is higher than that of Ni-BDC, suggesting strong electron interaction between Ni and Ru atoms and electron depletion on Ni. The O 1s spectra in Fig. 2d, can be deconvoluted into three peaks with their binding energies at 531.3, 532.0 and $532.9\\mathrm{eV}.$ assigned to the Ni $(\\mathrm{Ru}){-}\\bar{\\mathrm{O}}$ , $0{-}C{=}0$ , and absorbed water species respectively57. \n\n![](images/79442d285e8a979289c911338a93ed0087fc2677545b3b51b1fb4666084e40b4.jpg) \nFig. 1 Schematic of sample preparation and physical characterization of $\\mathsf{N i R u}_{0.13}$ -BDC. a Schematic illustration for the preparation of $\\mathsf{N i R u}_{0.13}$ -BDC catalyst. b SEM; c TEM images of $\\mathsf{N i R u}_{0.13}$ -BDC. d HAADF-STEM image and the corresponding STEM-EDS mappings of $\\mathsf{N i R u}_{0.13^{-B D C}}$ \n\nThe local electronic structure and coordination environment of $\\mathtt{R u}$ in $\\mathrm{NiRu}_{0.13}$ -BDC were further investigated by X-ray absorption measurements. Figure 3a and Supplementary Fig. 7 show the X-ray absorption near-edge structure (XANES) of ${\\mathrm{RuO}}_{2}$ , Ru foil and $\\mathrm{{NiRu}}_{0.13}{\\cdot}\\mathrm{{BDC}},$ it can be observed that the threshold value $(E_{0})$ of the $\\mathrm{NiRu}_{0.13}$ -BDC $(22129.17\\mathrm{eV})$ is between $\\mathrm{RuO}_{2}$ $(22130.25\\mathrm{eV})$ and Ru foil $(22127.02\\mathrm{eV})$ , indicating the valence state of $\\mathtt{R u}$ is between 0 and $+4.$ . In order to further estimate the valance state of the Ru atoms in $\\mathrm{NiRu}_{0.13}$ -BDC, we performed the $\\Delta\\mathrm{E}_{0}$ as a function of oxidation state of Ru atoms in these materials59. Hence, the average valance state of Ru atoms in $\\mathrm{NiRu}_{0.13}$ -BDC is $+2.67$ , as shown in Fig. 3b. The extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) of $\\mathrm{NiRu}_{0.13}$ -BDC shows only a primary peak at $1.5\\mathring\\mathrm{A}$ , which is assigned to $\\mathrm{Ru-O}$ bond (Fig. 3c). Compared with Ru foil and ${\\mathrm{RuO}}_{2}$ , there are no obvious characteristic peaks can be identified to $\\mathrm{{Ru-Ru}}$ metallic bond at $2.50\\mathrm{\\AA}$ in Ru foil and $\\mathrm{{Ru-Ru}}$ bond at $3.25\\mathrm{\\AA}$ in $\\mathrm{RuO}_{2}^{53}$ , revealing the Ru single-atom successfully dispersed in the Ni-BDC. In order to further confirm the structure of $\\mathtt{R u}$ in $\\mathrm{NiRu}_{0.13}$ -BDC, we fitted the Fourier transform XAFS in $R$ -space of $\\mathrm{Ru}\\ k$ -edge using the structure model of replacing Ni atoms in Ni-BDC by Ru atoms. As can be seen from Supplementary Fig. 7c and Table 2, the fitting spectrum is well consistent with as measured, further confirming Ru single-atom replaced part of Ni in Ni-BDC. Taking account into XPS spectra and XRD pattern, Ru was atomically anchored in the MOF Ni-BDC. Furthermore, as shown in Fig. 3d and Supplementary Fig. 8, the energy of Ni positively shifted to higher in comparison with Ni-BDC, verifying the electron interaction between Ni and Ru atoms, which is in agreement with XPS analysis. \n\nElectrocatalytic performance toward HER. The electrocatalytic performances of these catalysts were firstly measured in 1 M PBS solution with a three-electrode cell system under room temperature. And the loading mass of Ni-BDC, $\\mathrm{NiRu}_{0.09}$ -BDC, $\\mathrm{{NiRu}}_{0.13}{\\cdot}\\mathrm{{BDC}},$ and $\\mathrm{NiRu}_{0.21}–\\mathrm{BDC}$ was about $2.5\\mathrm{mg}\\mathrm{cm}^{-2}$ . To evaluate the HER activity of these materials, commercial $\\mathrm{Pt/C}$ and $\\mathrm{Ru/C}$ were utilized as benchmarks with the same loading. As exhibited in Fig. 4a, NiBDC performed poor electrocatalytic activity with an overpotential of $389\\mathrm{mV}$ to reach a current density of $10\\mathrm{\\mA}\\mathrm{cm}^{-2}$ . In contrast, after introducing Ru single-atom into Ni-BDC, the catalysts exhibited enhanced electrocatalytic performance toward HER. Remarkably, the $\\mathrm{NiRu}_{0.13}$ -BDC displayed high HER activity with a low overpotential of $36\\mathrm{mV}$ at $10\\mathrm{\\dot{m}V}\\mathrm{cm}^{-\\tilde{2}}$ in 1 M PBS solution, which is much lower than that of $\\mathrm{Ru/C}$ $\\mathrm{115}\\mathrm{mV})$ and even comparable to the commercial $\\mathrm{Pt/C}$ $(22\\mathrm{mV})$ ). Furthermore, $\\mathrm{NiRu}_{0.13^{-}}$ BDC only needed an overpotential of $132\\mathrm{mV}$ to reach a high current density of $100\\mathrm{mA}\\mathrm{cm}^{-2}$ , which was lower than that of $\\mathrm{Pt/C}$ $(139\\mathrm{mV})$ (Fig. 4a and Supplementary Fig. 9). The remarkable electroctatalytic performance of $\\mathrm{NiRu}_{0.13^{-}}\\mathrm{BDC}$ also outperformed other previously reported HER electrocatalysts (Supplementary Table 3). Moreover, $\\mathrm{NiRu}_{0.21}$ -BDC with higher Ru content, displayed worse activity than $\\mathrm{NiRu}_{0.13}$ -BDC, further suggesting the superiority of single-atom $\\mathrm{NiRu}_{0.13}$ -BDC electrocatalyst. The Tafel slope (Fig. 4b) of $\\mathrm{NiRu}_{0.13}$ -BDC is $32\\mathrm{mV}\\mathrm{dec}^{-1}$ , lower than that of \n\n![](images/3fca7eb020c687342acc598a93ff3065422196ad4750c2282b1a190f6b8996b0.jpg) \nFig. 2 X-ray photoelectron spectroscopic studies. a full range XPS spectra, b Ru $3p,$ c Ni $2p$ and d O 1s spectra of Ni-BDC and $\\mathsf{N i R u}_{0.13}$ -BDC. \n\n![](images/98d2b5e3c35309ad7892950b89059ff7f6907cd0b3e7659c56e85ffc7940e1e8.jpg) \nFig. 3 Electronic structure characterization of $\\mathsf{N i R u}_{0.13}\\mathrm{=BDC}$ a Ru $K\\cdot$ -edge XANES spectra of $\\mathsf{N i R u}_{0.13}$ -BDC, Ru foil and ${\\sf R u O}_{2}$ . b Relationship between $\\mathsf{R u}K\\cdot$ - edge threshold value $(E_{0})$ and oxidation state for $\\mathsf{N i R u}_{0.13^{-B D C}}$ and two reference materials. c Fourier transformed EXAFS spectra of $\\mathsf{R u}$ foil, ${\\sf R u O}_{2}$ and $\\mathsf{N i R u}_{0.13}$ -BDC. d Ni $K$ -edge XANES spectra of Ni-BDC and $\\mathsf{N i R u}_{0.13}$ -BDC. \n\nNi-BDC $(219\\mathrm{mV~dec^{-1}}),$ , $\\mathrm{{NiRu}}_{0.09}$ -BDC $(54\\mathrm{mV~dec^{-1}}).$ ) and $\\mathrm{NiRu}_{0.21}$ -BDC $(60\\mathrm{mV}\\mathrm{dec}^{-1})_{,}$ , which is comparable to $\\mathrm{Pt/C,}$ indicating that the $\\mathrm{NiRu}_{0.13^{-}}\\mathrm{BDC}$ performed as the best catalyst of the series. The electrocatalytic performances were also tested in $1\\mathrm{M}$ KOH and $^{1\\mathrm{M}}$ HCl. $\\mathrm{NiRu}_{0.13}$ -BDC also exhibited the best HER activity among these catalysts with an overpotential of 34 and $13\\mathrm{mV}$ at a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ in $1\\mathrm{M}\\mathrm{KOH}$ and $1\\mathrm{M}$ HCl, respectively, in Fig. 4c and Supplementary Fig. 9. The Tafel slope curves (Fig. 4d) also revealed $\\mathrm{NiRu}_{0.13}$ -BDC possessing smaller Tafel slope $(32\\mathrm{mV}\\mathrm{dec}^{-1})_{,}$ ) with accelerated HER kinetics in alkaline solution. The TOFs (Supplementary Fig. 10) of Ni-BDC, $\\mathrm{NiRu}_{0.09}$ -BDC, $\\mathrm{NiRu}_{0.13^{-}}\\mathrm{BDC},$ and $\\mathrm{NiRu}_{0.21}–\\mathrm{BDC}$ are 0.000048, 0.0032, 0.0091, and $0.0035s^{-1}$ , respectively. As can be seen from Supplementary Fig. 10, $\\mathrm{NiRu}_{0.13}$ -BDC has higher TOF value, indicating higher intrinsic activity. In addition, from the Supplementary Fig. 11, the faradic efficiency of $\\mathrm{NiRu}_{0.13}$ -BDC catalyst for HER is estimated to be close to $100\\%$ , indicating that almost all electrons are utilized for producing hydrogen. \n\n![](images/a6136f3ca54536145a8117566fb32c86637c8d64fb15ce21441534fdba4068e8.jpg) \nFig. 4 Electrochemical measurements. a LSV curves toward HER and b Tafel plots of Ni-BDC, $\\mathsf{N i R u}_{0.09}$ -BDC, $\\mathsf{N i R u}_{0.13}$ -BDC, $N i R u_{0.21}$ -BDC in 1 M PBS. c LSV curves toward HER and d Tafel plots of Ni-BDC, NiRu0.09-BDC, NiRu0.13-BDC, NiRu0.21-BDC in 1 M KOH. \n\nTo figure out the origin of the enhanced activity of the $\\mathrm{NiRu}_{0.13^{-}}\\mathrm{BDC}$ electrocatalyst, the double-layer capacitances $\\mathrm{(C_{dl})}$ measurements were carried out to evaluate the electrochemical active surface areas (Supplementary Fig. 12). $\\mathrm{NiRu}_{0.13}$ -BDC had higher $C_{\\mathrm{dl}}$ $(1.39\\mathrm{F}\\mathrm{cm}^{-2})^{60}$ than that of NiBDC $(0.0021\\mathrm{F}\\mathsf{c m}^{-2}.$ ), $\\mathrm{\\DeltaNiRu\\phantom{}_{0.09}–B D C}$ $(0.2797\\mathrm{F}\\mathrm{cm}^{-2},$ ) and $\\mathrm{NiRu}_{0.21}$ -BDC $(0.7572\\mathrm{F}\\mathrm{cm}^{-2}),$ ), indicating more electroactive surface exposed in $\\mathrm{NiRu}_{0.13^{-}}\\mathrm{BDC}$ compared with pure Ni-BDC. The electrochemical impedance spectroscopy (EIS) was performed to deeply study the charge-transfer mechanism and the resulted Nyquist plots were shown in Supplementary Fig. 13 and Table 4. Apparently, the $\\mathrm{NiRu}_{0.13}$ -BDC presented a smaller $R_{\\mathrm{{ct}}}$ value than other electrocatalysts, implying faster charge transfer. The long endurable stability was measured by chronoamperometry with an overpotential of $50\\mathrm{mV}$ (vs RHE) in $\\mathrm{~\\bar{~}1~M~}$ PBS solution. $\\mathrm{NiRu}_{0.13}$ -BDC exhibited good stability with a negligible current decrease after $30\\mathrm{h}$ test (Supplementary Fig. 13). After stability test for $^{10\\mathrm{h}}$ , the nanosheets morphology maintained well (Supplementary Fig. 14). The main phases are $\\mathrm{NiRu}_{0.13}$ -BDC, indicating that the crystal structure of MOF catalyst showed limited changes (Supplementary Fig. 15). The XPS spectra of $\\mathrm{NiRu}_{0.13}$ -BDC after electrocatalysis exhibited that the peak of $\\mathrm{Ru}~3p$ also showed limited changes (Supplementary Fig. 16), indicating the main component is still $\\mathrm{NiRu}_{0.13}$ -BDC MOF catalyst. The limited changes in crystal structure and chemical environment of $\\mathrm{NiRu}_{0.13^{-}}\\mathrm{\\bar{B}D C}$ after $^{10\\mathrm{h}}$ HER stability test indicated the MOF had good stability. \n\nDensity functional theory (DFT) calculations. To understand the effect of Ru single-atom in HER performance, we conducted DFT calculations. Supplementary Fig. 17 shows structure models of Ni-BDC and $\\mathrm{NiRu}_{0.13}$ -BDC (details in “Computation method”). For investigating the electronic structure of $\\mathrm{NiRu}_{0.13^{-}}$ BDC, the charge density difference was firstly simulated. From Fig. 5a, there is overt charge accumulation around Ru and charge depletion around Ni, revealing charge interaction between Ni and Ru, which is in agreement with the above-mentioned XPS and XANES results. It further confirmed after introducing of Ru single-atom, the electronic structure of metal center was modulated. In order to further elucidate the origin of the improved HER activity of $\\mathrm{NiRu}_{0.13}$ -BDC after introducing Ru single-atom, the density of states (DOS) was also calculated to deeply investigate the changes of electronic structure of the catalyst. According to the partial and total DOS calculations (Fig. 5b and Supplementary Figs. 18, 19), with the formation of Ru singleatom in the MOF, the electronic structure of $\\mathrm{NiRu}_{0.13^{-}}\\mathrm{B}\\mathrm{\\bar{D}C}$ changed. It should be noted that the d-band center of Ni shifted to lower energy (Fig. 5b), corresponding to a weaker $\\mathrm{H^{*}}$ adsorption on catalyst61. To elucidate the inherent relationship between the electronic structure and the enhanced electrocatalytic HER performance of $\\mathrm{NiRu}_{0.13}$ -BDC, the adsorption free energy of the HER intermediates was also calculated. Generally, there are two steps involved in neutral $\\mathrm{pH~HER},$ including $_{\\mathrm{H}_{2}\\mathrm{O}}$ adsorption/activation and H recombination on the surface of the catalyst62; so, a strong bonding of $_{\\mathrm{H}_{2}\\mathrm{O}}$ and neither too strong nor too weak bonding of H to the surface are desired63,64. As displayed in Fig. 5c, Ru in $\\mathrm{NiRu}_{0.13}$ -BDC shows much lower adsorption energy of $\\mathrm{\\tilde{H}}_{2}\\mathrm{O}$ $\\left(\\Delta{\\cal G}_{\\mathrm{H}2\\mathrm{O}^{*}}\\right)$ compared with $\\mathrm{\\DeltaNi}$ in Ni-BDC and $\\mathrm{NiRu}_{0.13^{-}}$ BDC, indicating the strongest water adsorption, which benefits for the following step to generate adsorbed $\\mathrm{~H~}$ atoms65,66. In addition, the calculated $\\Delta G_{\\mathrm{H^{*}}}$ for adsorbed $\\mathrm{~H~}$ atom forming molecular $\\mathrm{H}_{2}$ is the key descriptor to predict and evaluate the activity for HER on catalyst surface67. While, Ru in $\\mathrm{NiRu}_{0.13}$ -BDC and Ni in Ni-BDC possess a more negative value of $\\Delta\\mathrm{G}_{\\mathrm{H}^{*}}$ , indicating excessive strong adsorption of $\\mathrm{~H~}$ and adverse for $\\mathrm{~H~}$ desorption and $\\mathrm{H}_{2}$ release. By contrast, the $\\Delta\\mathrm{G}_{\\mathrm{H}^{*}}$ of $\\mathrm{\\DeltaNi}$ in $\\mathrm{NiRu}_{0.13}$ -BDC (Fig. 5d) is closer to the optimal value of $\\Delta G_{\\mathrm{H^{*}}}=$ $0\\mathrm{eV_{:}}$ , supporting high HER activity. For the $\\mathrm{NiRu}_{0.13}$ -BDC catalyst, with both Ni and Ru atoms in the crystal structure, it showcases a preferential HER activity. From the above results, it can be found that constructing Ru single-atom into the MOF can regulate the electronic states of Ni and Ru, and d-band center of Ni, resulting in an enhanced $\\Delta G_{\\mathrm{H2O^{*}}}$ and a more thermoneutral $\\Delta G_{\\mathrm{H^{*}}}$ , thus devoting to improved HER performance. \n\n![](images/59a78ae489acc91ac66c4a59352519a9d2cec32b3246c5b8cf5f8f24cc149090.jpg) \nFig. 5 DFT calculations. a The charge density difference between Ni-BDC and $\\mathsf{N i R u}_{0.13}$ -BDC. The yellow and blue color represent charge accumulation and depletion, respectively. b Calculated DOS of Ni in Ni-BDC and $\\mathsf{N i R u}_{0.13}$ -BDC. c The calculated adsorption free energy of water on Ni-BDC and $\\mathsf{N i R u}_{0.13}$ -BDC. d Calculated free energy diagram of the HER. \n\n# Discussion \n\nIn conclusion, we have synthesized the HER catalyst with significantly improved performance by introducing Ru single-atom into the MOF Ni-BDC. Impressingly, the as-sythesized $\\mathrm{NiRu}_{0.13^{-}}$ BDC exhibits enhanced activity toward HER in all $\\mathsf{p H}$ , comparable with commercial $\\mathrm{Pt/\\bar{C}}$ , especially delivering a low overpotential of $36\\mathrm{mV}$ at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ with a Tafel slope of $32\\mathrm{mV}$ dec−1 in $1\\mathrm{M}$ PBS solution. More improtantly, after introducing $\\begin{array}{r}{\\mathrm{{Ru},}}\\end{array}$ there is strong electron interaction between Ni and Ru atoms and electron depletion on Ni in the MOF from XPS results, also confirmed by EXAFS and XANES. DFT calculations disclose that the introduction of atomically dispersed Ru can promote the adsorption of $_{\\mathrm{H}_{2}\\mathrm{O}}$ and optimize good thermoneutral $\\Delta\\mathrm{G}_{\\mathrm{H}^{*}}$ to facilitate $\\mathrm{H}_{2}$ release on Ni site of the MOF by regulating electronic structure, thus effciently enhancing the HER activity. This work paves a way of designing efficient MOFs electrocatalysts via single-atom strategy to modulate electronic structure and intermediates asorption. \n\n# Methods \n\nChemicals. $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ , ${\\mathrm{RuCl}}_{3}$ , $\\mathrm{Pt/C}$ $(20\\%)$ , $\\mathrm{Ru/C}$ $(5\\%)$ , N,N-Dimethylformami (DMF), ethanol, and terephthalic acid $(\\mathrm{H}_{2}\\mathrm{BDC})$ were purchased from Aladdin (Shanghai, China). All the reagents were used without any further purification. \n\nSynthesis of Ni-BDC. The Ni-BDC was synthesized through a solvothermal method as following. First, the nickel foam was washed with 3 M HCl and water in the size of $1.5\\times3\\mathrm{cm}^{2}$ . Second, the as-processed nickel foam was immersed into a solution containing $4.5\\mathrm{mL}$ DMF and 1 mmol $\\mathrm{Ni}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ in a Teflon-lined autoclave. Afterwords, a solution composed of $7.5\\mathrm{ml}$ DMF, 1 mmol BDC and $\\mathrm{1ml}$ $0.4\\mathrm{M}\\mathrm{NaOH}$ was poured into the autoclave and subsequently heated at $100^{\\circ}\\mathrm{C}$ for $15\\mathrm{h}$ . \n\nSynthesis of $\\mathsf{N i R u}_{\\mathbf{x}}$ -BDC. The obtained Ni-BDC was immersed into an ethanol solution containing $50\\mathrm{mg}\\mathrm{RuCl}_{3}$ in Teflon-lined autoclave and then heated at $80^{\\circ}\\mathrm{C}$ for $12\\mathrm{{h}}$ . Other samples were prepared in the similar way with an addition of ${\\mathrm{RuCl}}_{3}$ of 20, 75 mg, respectively. And the as-obtained samples were named as $\\mathrm{NiRu}_{x}$ -BDC $_x$ represents the molar ratio of $\\mathrm{{Ru:Ni}}^{\\cdot}$ . The $\\mathrm{NiRu}_{0.13}$ -BDC powder sample was synthesized without addition of nickel foam with the same method. \n\nCharacterization. Powder X-ray diffraction was conducted on Rigaku SmartLab diffractometer equipped with Cu Kα X-ray source $(\\lambda=1.540598\\bar{\\mathrm{\\AA}}$ ). SEM measurements were operated on a Hitachi SU8010 system. TEM images were carried out on a JEM-1400Plus apparatus. Scanning transmission electron microscopy (STEM) and corresponding EDS mapping images were obtained from a JEOL JEMARM 200F equipped with energy dispersive X-ray spectrometer. X-ray photoelectron spectra were obtained from a Thermo fisher Scientific K-Alpha+ instrument. Inductively coupled plasma mass spectrometry (ICP-MS) was measured on Thermo Scientific iCAP RQ. \n\nElectrochemical measurements. The electrochemical measurements were evaluated in a standard three-electrode cell system by using a CHI 760D (Shanghai, China) instrument. The catalysts were cut into $0.5\\times1{\\mathrm{cm}}^{2}$ pieces utilizing as the working electrodes. An $\\mathrm{\\Ag/AgCl}$ (3 M KCl) electrode and carbon rod were used as the reference and counter electrode, respectively. The measured potential was converted relative to RHE according to the following equation: $E$ (vs $\\mathrm{RHE})=$ $E_{\\mathrm{Ag/AgCl}}+0.21+0.059\\times\\mathrm{pH}$ . The Linear sweep voltammetry (LSV) was conducted at a scan rate of $2\\mathrm{m}\\mathrm{V}\\mathrm{s}^{-\\bar{1}}$ with the potential corrected for iR loss. The CV tests were studied in the potential range from 0.386 to $0.486\\mathrm{V}$ (vs RHE) at different scan rates. By plotting the difference of current density (j) at $0.436\\mathrm{V}$ (vs. RHE) against the scan rate, we gained a line where the slope is equal to the geometric doublelayer capacitance $\\left(C_{\\mathrm{dl}}\\right)$ . EIS was evaluated with $5\\mathrm{mV}$ amplitude in a frequency range from 0.01 to $10,000\\mathrm{Hz}$ at $-1.036\\mathrm{V}$ (vs. $\\mathrm{Ag/AgCl}{\\mathrm{,}}$ ). The turnover frequency $(\\mathsf{s}^{-\\bar{1}})$ can be estimated with the following equation: $T O F=I/2n F;$ where $I$ is the current (A) during LSV, $F$ is the Faraday constant ( $96485.3\\mathrm{C}\\mathrm{mol}^{-1}$ ), $n$ is the number of active sites (mol). The factor 1/2 is based on the assumption that two electrons are necessary to form a hydrogen molecule. Faradic efficiency was evaluated in a H-type cell with an anion exchange membrane as the separator and a gas chromatography (SHIMADZU GC-2014) for the hydrogen gas detection. \n\nComputation method. All the calculations are performed in the framework of the density functional theory with the projector augmented plane-wave method, as implemented in the Vienna ab initio simulation package68. The generalized \n\ngradient approximation proposed by Perdew, Burke, and Ernzerhof is selected for the exchange-correlation potential69. The Ni-BDC crystal structure has been modeled using a single periodic slab with a $(4\\times2)$ supercell based on the previously reported $\\mathrm{MOF}^{50}$ , and the (200) facet was investigated which was dominant facet according to the XRD patterns. The benzene ring was passivated with hydrogen. And the $\\mathrm{NiRu}_{0.13}$ -BDC structure was derived by replacing one Ni atom with Ru atom. The reasonable vacuum layers were set to $20\\textup{\\AA}$ , in order to avoid the interaction between periodic structures. Furthermore, when a $30\\textup{\\AA}$ vacuum layer was set, the energy deviation yields to be 0.1 meV/atom compared with that of $20\\textup{\\AA}$ , for further calculations we chose the $20\\textup{\\AA}$ vacuum layer. The cut-off energy for plane wave is set to $400\\mathrm{eV}$ . The energy criterion is set to $10^{-5}\\mathrm{eV}$ in iterative solution of the Kohn–Sham equation. The Brillouin zone integration is performed using a $1\\times2\\times2$ k-mesh, for the DOS calculations the $1\\times5\\times5$ k-mesh was applied. The slab contains four layers with two layers are fixed. All the structures are relaxed until the residual forces on the atoms have declined to less than $0.05\\mathrm{eV}/\\mathrm{\\AA}$ . The free energies are calculated by the formula: $\\Delta G=\\Delta E_{\\mathrm{tot}}+\\Delta E_{\\mathrm{ZPE}}-$ TΔS, where $\\Delta E_{\\mathrm{tot}},$ $\\Delta E_{\\mathrm{ZPE}},$ and $\\Delta S$ are the changes in total energy of the system, vibrational zero-point energy, entropy during the reaction, respectively; while $T$ represents temperature70. \n\n# Data availability \n\nFull data supporting the findings of this study are available within the article and its Supplementary Information, as well as from the corresponding author upon reasonable request. \n\nReceived: 29 June 2020; Accepted: 2 February 2021; Published online: 01 March 2021 \n\n# References \n\n1. Dresselhaus, M. S. & Thomas, I. L. Alternative energy technologies. Nature 414, 332–337 (2001). \n2. Gray, H. B. Powering the planet with solar fuel. Nat. Chem. 1, 7–8 (2009). \n3. Cai, P., Li, Y., Wang, G. & Wen, Z. Alkaline-acid $Z\\mathrm{n-H}_{2}\\mathrm{O}$ fuel cell for the simultaneous generation of hydrogen and electricity. Angew. Chem. Int. Ed. 57, 3910–3915 (2018). \n4. Lu, X. F., Yu, L., Zhang, J. & Lou, X. W. Ultrafine dual-phased carbide nanocrystals confined in porous nitrogen-doped carbon dodecahedrons for efficient hydrogen evolution reaction. Adv. Mater. 31, 1900699 (2019). \n5. Meng, X. et al. Distance synergy of $\\ensuremath{\\mathrm{MoS}}_{2}$ -confined rhodium atoms for highly efficient hydrogen. Evol. Angew. Chem. Int. Ed. 59, 10502–10507 (2020). \n6. Jeon, K. J. et al. Air-stable magnesium nanocomposites provide rapid and high-capacity hydrogen storage without using heavy-metal catalysts. Nat. Mater. 10, 286–290 (2011). \n7. Wang, J. et al. Recent progress in cobalt-based heterogeneous catalysts for electrochemical water splitting. Adv. Mater. 28, 215–230 (2016). \n8. Liu, B. et al. Nickel-cobalt diselenide 3D mesoporous nanosheet networks supported on Ni foam: an all-pH highly efficient integrated electrocatalyst for hydrogen evolution. Adv. Mater. 29, 1606521 (2017). \n9. Cui, X. et al. Robust interface Ru centers for high-performance acidic oxygen evolution. Adv. Mater. 32, 1908126 (2020). \n10. Liu, Z. et al. Optimal geometrical configuration of cobalt cations in spinel oxides to promote oxygen evolution reaction. Angew. Chem. Int. Ed. 59, 4736–4742 (2019). \n11. Wu, T. et al. Iron-facilitated dynamic active-site generation on spinel $\\mathrm{CoAl}_{2}\\mathrm{O}_{4}$ with self-termination of surface reconstruction for water oxidation. Nat. Catal. 2, 763–772 (2019). \n12. Wei, Y.-S. et al. A single-crystal open-capsule metal-organic framework. J. Am. Chem. Soc. 141, 7906–7916 (2019). \n13. Zhang, Z. et al. Crystal phase and architecture engineering of lotus-thalamusshaped Pt-Ni anisotropic superstructures for highly efficient electrochemical hydrogen evolution. Adv. Mater. 30, 1801741 (2018). \n14. Wang, S., Wang, Y., Zhang, S. L., Zang, S.-Q. & Lou, X. W. Supporting ultrathin $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ nanosheets on Co/N-doped graphitic carbon nanocages for efficient photocatalytic H-2 generation. Adv. Mater. 31, 11903404 (2019). \n15. Huang, L. et al. Zirconium-regulation-induced bifunctionality in 3D cobaltiron oxide nanosheets for overall water splitting. Adv. Mater. 31, 1901439 (2019). \n16. Zhao, J.-Q. et al. Heptanuclear brucite disk with cyanide bridges in a cocrystal and tracking its pyrolysis to an efficient oxygen evolution electrode. Sci. Bull. 64, 1667–1674 (2019). \n17. Roger, I., Shipman, M. A. & Symes, M. D. Earth-abundant catalysts for electrochemical and photoelectrochemical water splitting. Nat. Rev. Chem. 1, 0003 (2017). \n18. Zhu, C. et al. Hierarchically porous M-N-C ( $\\mathbf{\\dot{M}}=\\mathbf{Co}$ and Fe) single-atom electrocatalysts with robust MNx active moieties enable enhanced ORR performance. Adv. Energy Mater. 8, 1801956 (2018). \n19. Liu, Y. et al. A general route to prepare low-ruthenium-content bimetallic electrocatalysts for pH-universal hydrogen evolution reaction by using carbon quantum dots. Angew. Chem. Int. Ed. 59, 1718–1726 (2020). \n20. Chen, L. et al. Mo-based ultrasmall nanoparticles on hierarchical carbon nanosheets for superior lithium ion storage and hydrogen generation catalysis. Adv. Energy Mater. 7, 1602782 (2017). \n21. Li, Y. et al. Fe vacancies induced surface ${\\mathrm{FeO}}_{6}$ in nanoarchitectures of Ndoped graphene protected beta-FeOOH: effective active sites for pH-universal electrocatalytic oxygen reduction. Adv. Funct. Mater. 28, 1803330 (2018). \n22. Gong, Y. N. et al. Regulating the coordination environment of MOFtemplated single-atom nickel electrocatalysts for boosting $\\mathrm{CO}_{2}$ reduction. Angew. Chem. Int. Ed. 59, 2705–2709 (2020). \n23. Qin, J.-S. et al. Creating well-defined hexabenzocoronene in zirconium metalorganic framework by postsynthetic annulation. J. Am. Chem. Soc. 141, 2054–2060 (2019). \n24. Lal, G. et al. Mechanical properties of a metal-organic framework formed by covalent cross-linking of metal-organic polyhedra. J. Am. Chem. Soc. 141, 1045–1053 (2019). \n25. Ghalei, B. et al. Rational tuning of zirconium metal-organic framework membranes for hydrogen purification. Angew. Chem. Int. Ed. 58, 19034–19040 (2019). \n26. Shen, J. Q. et al. Modular and stepwise synthesis of a hybrid metal-organic framework for efficient electrocatalytic oxygen evolution. J. Am. Chem. Soc. 139, 1778–1781 (2017). \n27. Zhao, M. et al. Metal-organic frameworks as selectivity regulators for hydrogenation reactions. Nature 539, 76–80 (2016). \n28. Zhao, R. et al. Puffing up energetic metal-organic frameworks to large carbon networks with hierarchical porosity and atomically dispersed metal sites. Angew. Chem. Int. Ed. 58, 1975–1979 (2019). \n29. Liao, C.-H. et al. From a layered iridium(III)-cobalt(II) organophosphonate to an efficient oxygen-evolution-reaction electrocatalyst. Chem. Commun. 55, 13920–13923 (2019). \n30. Han, N. et al. Nitrogen-doped tungsten carbide nanoarray as an efficient bifunctional electrocatalyst for water splitting in acid. Nat. Commun. 9, 924 (2018). \n31. Chao, D. et al. An electrolytic $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ battery for high-voltage and scalable energy storage. Angew. Chem. Int. Ed. 58, 7823–7828 (2019). \n32. Fang, R., Dhakshinamoorthy, A., Li, Y. & Garcia, H. Metal organic frameworks for biomass conversion. Chem. Soc. Rev. 49, 3638–3687 (2020). \n33. Wang, H. F., Tang, C., Wang, B., Li, B. Q. & Zhang, Q. Bifunctional transition metal hydroxysulfides: room-temperature sulfurization and their applications in $Z\\mathrm{n}$ -Air batteries. Adv. Mater. 29, 1702327 (2017). \n34. Lai, Z. et al. Preparation of $\\boldsymbol{1}\\mathrm{T}^{\\prime}$ -Phase $\\mathrm{ReS}_{2\\mathrm{x}}\\mathrm{Se}_{2(1-\\mathrm{~\\bf~x})}$ $({\\bf x}=0.1\\$ ) nanodots for highly efficient electrocatalytic hydrogen evolution reaction. J. Am. Chem. Soc. 140, 8563–8568 (2018). \n35. Hu, X. et al. Fast redox kinetics in Bi-heteroatom doped 3D porous carbon nanosheets for high-performance hybrid potassium-ion battery capacitors. Adv. Energy Mater. 9, 1901533 (2019). \n36. Su, C.-Y. et al. Atomic modulation of FeCo-nitrogen-carbon bifunctional oxygen electrodes for rechargeable and flexible all-solid-state zinc-air battery. Adv. Energy Mater. 7, 1602460 (2017). \n37. Chao, D. & Fan, H. J. Intercalation pseudocapacitive behavior powers aqueous. Batteries. Chem. 5, 1357–1370 (2019). \n38. Chen, D., Chen, C., Baiyee, Z. M., Shao, Z. & Ciucci, F. Nonstoichiometric oxides as low-cost and highly-efficient oxygen reduction/evolution catalysts for low-temperature electrochemical devices. Chem. Rev. 115, 9869–9921 (2015). \n39. Li, F. L., Shao, Q., Huang, X. & Lang, J. P. Nanoscale trimetallic metal-organic frameworks enable efficient oxygen evolution electrocatalysis. Angew. Chem. Int. Ed. 57, 1888–1892 (2018). \n40. Xue, Z. et al. Missing-linker metal-organic frameworks for oxygen evolution reaction. Nat. Commun. 10, 5048 (2019). \n41. Cheng, W. et al. Lattice-strained metal-organic-framework arrays for bifunctional oxygen electrocatalysis. Nat. Energy 4, 115–122 (2019). \n42. Zhang, E. et al. Bismuth single atoms resulting from transformation of metalorganic frameworks and their use as electrocatalysts for $\\mathrm{CO}_{2}$ reduction. J. Am. Chem. Soc. 141, 16569–16573 (2019). \n43. Rogge, S. M. J. et al. Metal-organic and covalent organic frameworks as singlesite catalysts. Chem. Soc. Rev. 46, 3134–3184 (2017). \n44. Wang, A., Li, J. & Zhang, T. Heterogeneous single-atom catalysis. Nat. Rev. Chem. 2, 65–81 (2018). \n45. Gao, G., Jiao, Y., Waclawik, E. R. & Du, A. Single atom (Pd/Pt) supported on graphitic carbon nitride as an efficient photocatalyst for visible-light reduction of carbon dioxide. J. Am. Chem. Soc. 138, 6292–6297 (2016). \n46. Cui, X., Li, W., Ryabchuk, P., Junge, K. & Beller, M. Bridging homogeneous and heterogeneous catalysis by heterogeneous single-metal-site catalysts. Nat. Catal. 1, 385–397 (2018). \n47. Ji, S. et al. Chemical synthesis of single atomic site catalysts. Chem. Rev. 120, 11900–11955 (2020). \n48. Zhu, C., Fu, S., Shi, Q., Du, D. & Lin, Y. Single-atom electrocatalysts. Angew. Chem. Int. Ed. 56, 13944–13960 (2017). \n49. Mesbah, A. et al. From hydrated $\\mathrm{Ni_{3}(O H)_{2}(C_{8}H_{4}O_{4})_{2}(H_{2}O)_{4}}$ to anhydrous Ni2(OH)(2)(C8H4O4): impact of structural transformations on magnetic properties. Inorg. Chem. 53, 872–881 (2014). \n50. Zhao, S. et al. Ultrathin metal-organic framework nanosheets for electrocatalytic oxygen evolution. Nat. Energy 1, 16184 (2016). \n51. Chen, G. et al. Accelerated hydrogen evolution kinetics on NiFe-layered double hydroxide electrocatalysts by tailoring water dissociation active sites. Adv. Mater. 30, 1706279 (2018). \n52. Peng, Y. et al. Hydrogen evolution reaction catalyzed by ruthenium ioncomplexed graphitic carbon nitride nanosheets. J. Mater. Chem. A. 5, 18261–18269 (2017). \n53. Geng, Z. et al. Achieving a record-high yield rate of $120.9~\\mathrm{ug_{NH3}\\ m g_{c a t-1}}.$ . $\\mathbf{h}^{-1}$ for $\\Nu_{2}$ electrochemical reduction over Ru single-atom catalysts. Adv. Mater. 30, 1803498 (2018). \n54. Lu, B. et al. Ruthenium atomically dispersed in carbon outperforms platinum toward hydrogen evolution in alkaline media. Nat. Commun. 10, 631 (2019). \n55. Zhang, L.-N. et al. Cable-like ${\\mathrm{Ru/WNO}}{\\textcircled{a}}C$ nanowires for simultaneous highefficiency hydrogen evolution and low-energy consumption chlor-alkali electrolysis. Energy Environ. Sci. 12, 2569–2580 (2019). \n56. Wang, Z. L. et al. Spatially confined assembly of monodisperse ruthenium nanoclusters in a hierarchically ordered carbon electrode for efficient hydrogen. Evol. Angew. Chem. Int. Ed. 57, 5848–5852 (2018). \n57. Sun, F. et al. NiFe-based metal-organic framework nanosheets directly supported on nickel foam acting as robust electrodes for electrochemical oxygen evolution reaction. Adv. Energy Mater. 8, 1800584 (2018). \n58. Xue, Z. et al. Interfacial electronic structure modulation of NiTe nanoarrays with NiS nanodots facilitates electrocatalytic oxygen evolution. Adv. Mater. 31, 1900430 (2019). \n59. Kim, J. et al. High-performance pyrochlore-type yttrium ruthenate electrocatalyst for oxygen evolution reaction in acidic media. J. Am. Chem. Soc. 139, 12076–12083 (2017). \n60. Ma, T. Y., Dai, S., Jaroniec, M. & Qiao, S. Z. Metal-organic framework derived hybrid $\\mathrm{Co}_{3}\\mathrm{O}_{4}.$ -carbon porous nanowire arrays as reversible oxygen evolution electrodes. J. Am. Chem. Soc. 136, 13925–13931 (2014). \n61. Zheng, Y., Jiao, Y., Jaroniec, M. & Qiao, S. Z. Advancing the electrochemistry of the hydrogen-evolution reaction through combining experiment and theory. Angew. Chem. Int. Ed. 54, 52–65 (2015). \n62. Xie, X. et al. Electrocatalytic hydrogen evolution in neutral pH solutions: dualphase synergy. Acs. Catal. 9, 8712–8718 (2019). \n63. Balat, H. & Kirtay, E. Hydrogen from biomass-present scenario and future prospects. Int. J. Hydrog. Energy 35, 7416–7426 (2010). \n64. Zhang, J. et al. Efficient hydrogen production on $\\mathrm{{MoNi}_{4}}$ electrocatalysts with fast water dissociation kinetics. Nat. Commun. 8, 15437 (2017). \n65. You, B., Zhang, Y., Jiao, Y., Davey, K. & Qiao, S. Z. Negative charging of transition-metal phosphides via strong electronic coupling for destabilization of alkaline water. Angew. Chem. Int. Ed. 58, 11796–11800 (2019). \n66. Liu, T. et al. CoP-doped MOF-based electrocatalyst for pH-universal hydrogen evolution reaction. Angew. Chem. Int. Ed. 58, 4679–4684 (2019). \n67. Zheng, Y., Jiao, Y., Vasileff, A. & Qiao, S. Z. The hydrogen evolution reaction in alkaline solution: from theory, single crystal models, to practical electrocatalysts. Angew. Chem. Int. Ed. 57, 7568–7579 (2018). \n68. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n69. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1999). \n70. Tang, Q. & Jiang, D.-E. Mechanism of hydrogen evolution reaction on 1T$\\ensuremath{\\mathbf{MoS}}_{2}$ from first principles. Acs Catal. 6, 4953–4961 (2016). \n\n# Acknowledgements \n\nThis work was supported by National Key R&D Program of China (2018YFA0108300), International S&T Cooperation Program of China (2017YFE0127800), the Overseas High-level Talents Plan of China and Guangdong Province, the Fundamental Research Funds for the Central Universities, the Hunan Provincial Science and Technology Program (No. 2017XK2026), The 100 Talents Plan Foundation of Sun Yat-Sen University, the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2017ZT07C069), the NSFC Projects (21872174, 21821003, 21890380, 22075321, and U1932148). We thank Dr. Ting-Shan Chan and Dr. Ying-Rui Lu for their helps during synchrotron measurements at Taiwan Light Source (BL01C). \n\n# Author contributions \n\nG.L., Y.S., and Z.X. conceived and designed the project. Y.S. carried out the syntheses and electrochemical measurements. Z.X. performed the DFT calculations. Q.L. performed the TEM characterizations. M.L., K.L., and Y.L. performed and analyzed the XANES and EXAFS results. Y.L. and Y.J. assisted with XPS characterizations. Y.S., Z.X., M.L., C.Y.S. and G.L. discussed and prepared the manuscript. All authors participated in the discussion of experimental and calculations results. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-21595-5. \n\nCorrespondence and requests for materials should be addressed to G.L. \n\nPeer review information Nature Communications thanks Yuan Ping and the other, anonymous, reviewer(s) for their contributions to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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" + }, + { + "id": "10.1126_science.abe8177", + "DOI": "10.1126/science.abe8177", + "DOI Link": "http://dx.doi.org/10.1126/science.abe8177", + "Relative Dir Path": "mds/10.1126_science.abe8177", + "Article Title": "Interfacial ferroelectricity by van der Waals sliding", + "Authors": "Stern, MV; Waschitz, Y; Cao, W; Nevo, ; Watanabe, K; Taniguchi, T; Sela, E; Urbakh, M; Hod, O; Ben Shalom, M", + "Source Title": "SCIENCE", + "Abstract": "Despite their partial ionic nature, many-layered diatomic crystals avoid internal electric polarization by forming a centrosymmetric lattice at their optimal van der Waals stacking. Here, we report a stable ferroelectric order emerging at the interface between two naturally grown flakes of hexagonal boron nitride, which are stacked together in a metastable non-centrosymmetric parallel orientation. We observe alternating domains of inverted normal polarization, caused by a lateral shift of one lattice site between the domains. Reversible polarization switching coupled to lateral sliding is achieved by scanning a biased tip above the surface. Our calculations trace the origin of the phenomenon to a subtle interplay between charge redistribution and ionic displacement and provide intuitive insights to explore the interfacial polarization and its distinctive slidetronics switching mechanism.", + "Times Cited, WoS Core": 447, + "Times Cited, All Databases": 459, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000665860000052", + "Markdown": "# FERROELECTRICS Interfacial ferroelectricity by van der Waals sliding \n\nM. Vizner Stern1, Y. Waschitz1, W. Cao2, I. Nevo1, K. Watanabe3, T. Taniguchi3, E. Sela1, M. Urbakh2, O. Hod2, M. Ben Shalom1\\* \n\nDespite their partial ionic nature, many-layered diatomic crystals avoid internal electric polarization by forming a centrosymmetric lattice at their optimal van der Waals stacking. Here, we report a stable ferroelectric order emerging at the interface between two naturally grown flakes of hexagonal boron nitride, which are stacked together in a metastable non-centrosymmetric parallel orientation. We observe alternating domains of inverted normal polarization, caused by a lateral shift of one lattice site between the domains. Reversible polarization switching coupled to lateral sliding is achieved by scanning a biased tip above the surface. Our calculations trace the origin of the phenomenon to a subtle interplay between charge redistribution and ionic displacement and provide intuitive insights to explore the interfacial polarization and its distinctive “slidetronics” switching mechanism. \n\nhe ability to locally switch a confined electrical polarization is a key functionality in modern technologies, where storing and retrieving a large volume of information is vital $(I)$ . The need to re \nduce the dimensions of individually polarized \ndomains, from the ${\\sim}100{\\cdot}\\mathrm{nm}^{2}$ scale $(2,3)$ toward \nthe atomic scale, is rising $\\left(4\\right)$ . The main chal \nlenges involve long-range dipole interactions, \nwhich tend to couple the individual domain \npolarization orientations (5). Likewise, surface \neffects and external strains that are difficult to \ncontrol become dominant once the surface-to \n\nFig. 1. High-symmetry interlayer stacking configurations. (A) Top view illustration of two layers. For clarity, atoms of the top layer are represented by smaller circles. Within each group of parallel or antiparallel twist orientations, a relative lateral shift by one lattice spacing results in a cyclic switching between three high-symmetry stacking configurations. (B) Calculated local-registry index (LRI) map of the atomic overlaps $(\\boldsymbol{{17}})$ in a rigid structure made of two hBN layers stacked with a twist angle of $0.5^{\\circ}.$ Blue regions correspond to AA stacking, whereas AB/BA stacking appears in orange $\\mathrm{\\underline{{\\cdot}}}|\\mathsf{R}|=0.86\\mathrm{\\overline{{\\rho}}},$ . (C) Calculated LRI map after geometry relaxation of the structure presented in (B). Large domains of uniform untwisted AB/BA stacking appear, at the expense of the preoptimized AA regions. The twist is accumulated in smaller AA-like regions volume ratio increases (6). To overcome these challenges, one can consider layered materials, such as hexagonal boron nitride $\\mathit{h}$ -BN) and transition-metal dichalcogenides (TMDs), where the bulk volume can be reduced to the ultimate atomic-thickness limit, whereas the crystalline surface remains intact (7). However, it is rare to find a spontaneous net electric polarization in two dimensions (2D) that is sufficiently large to read and write under ambient conditions (8–10). Furthermore, in naturally grown $h$ -BN and TMD crystals, polarization is eliminated by the formation of a centrosymmetric van der Waals (vdW) structure that is lower in energy than other metastable stacking configurations. Here, we break this symmetry by controlling the twist angle between two $h$ -BN flakes and find an array of permanent and switchable polarization domains at their interface. The polarization is oriented normal to the plane, and its amplitude is in good agreement with previous first-principle predictions for a twolayered system $(I I)$ and with our detailed multilayer calculations. \n\nTo identify which stacking modes can carry polarization, we present in Fig. 1A six different high-symmetry configurations of bilayer $h$ -BN. The stacking configurations are divided into two groups termed “parallel” and “antiparallel” twist orientations $(I2)$ ; within each group, a relative lateral shift by one interatomic distance switches the stacking configuration in a cyclic manner. Typically, the crystal grows in the optimal antiparallel (AA') configuration with full overlap between nitrogen (boron) atoms of one layer and boron (nitrogen) atoms of the adjacent layer (13). In the parallel twist orientation, however, the fully eclipsed configuration (AA) is unstable because it forces pairs of bulky nitrogen atoms atop each other, resulting in increased steric repulsion (14). Instead, a lateral interlayer shift occurs to a metastable AB stacking with only half of the atoms overlapping, whereas the other half are aligned with the empty centers of the hexagons in the adjacent layer $(75,76)$ . The AB and BA stacking form equivalent lattice structures (only flipped), and all depicted antiparallel configurations (AA', AB1', AB2') are symmetric under spatial inversion. \n\nTo explore these different configurations, we artificially stamped two exfoliated $h$ -BN flakes on top of each other, each consisting of a few AA' stacked layers, with a minute twist angle between the otherwise parallel interfacial layers $(I7)$ . The small twist imposes interlayer translations that evolve continuously and form a moiré pattern owing to the underlying crystal periodicity (Fig. 1B). In this rigid lattice picture, the three nearly commensurate stacking configurations (AB, BA, AA) appear at adjacent positions in space. Notably, this picture breaks for a sufficiently small twist angle as a result of structural relaxation processes, as shown by our molecular dynamics calculation based on dedicated interlayer potentials (Fig. 1C) $(I7,I8)$ . Instead, the system divides into large domains of reconstructed commensurate AB and BA stackings separated by sharp incommensurate domain walls that accommodate the global twist (fig. S3, A and B) (19–22). Notably, near the center of the extended commensurate domains, perfectly aligned configurations are obtained with no interlayer twist. In the experiments, we also introduce a topographic step at the interface between the flakes. A step thickness of an odd number of layers guarantees antiparallel stacking (AA', AB1', or AB2') on one side and parallel stacking (AA, AB, or BA) on its other side (Fig. 1D). Thus, one can compare all possible configurations at adjacent locations in space. \n\n![](images/05789207621f2dd3b18b5a6611005b6a75fc3d1990bdc76183715d339a9863e7.jpg) \nand in the \\~10-nm-wide incommensurate domain walls (bright lines); see fig. S3 and $(\\boldsymbol{{17}})$ for further discussion. (D) Cross-sectional illustration of two few-layered flakes (blue and light blue regions mark the top and bottom flakes, respectively) of naturally grown $h$ -BN (AA’), which are stacked with no twist. Plus (minus) signs mark boron (nitrogen) sites. A topographical step of a single-layer switches between parallel and antiparallel stacking orientations at the interface between the two flakes. Vertical charge displacements in eclipsed/hollow pairs (vertical/diagonal ellipses) and the resulting net polarization $\\mathsf{P}_{z}$ are marked by arrows. \n\n![](images/f9d357440543542b7e4460b8b2d52a94d7850f84045171b6a745d0524fedd61e.jpg) \nFig. 2. Direct measurement of interfacial polarization. (A) Illustration of the experimental setup. An atomic force microscope is operated in Kelvin-probe mode to measure the local potential modulation, $V_{\\mathsf{K P}}$ , at the surface of two $3-\\mathsf{n m}$ -thick $h$ -BN flakes, which are stacked with a very small twist angle. (B) $V_{\\mathsf{K P}}$ map showing oppositely polarized domains of AB/BA stacking (black and white), ranging in area between ${\\sim}0.01$ and $1\\upmu\\mathrm{m}^{2}$ and separated by sharp domain walls. (C) Surface potential measured along the purple line marked in (B) by first-harmonic KPFM. (D) DFT calculations of the polarization, $P_{z}$ , per unit area obtained for finite $h$ -BN bilayer flakes of different lateral dimensions (1:1 and $2.9\\ \\mathsf{n m}^{2}$ , black triangles) and for laterally periodic stacks made of 2 to 10 layers (marked as PBC, green square). The red star marks the polarization value evaluated from the measured $\\Delta V_{\\mathsf{K P}}$ data. (E) Calculated polarization for different interlayer shifts. \n\nTo measure variations in the electrical potential, $V_{\\mathrm{KP:}}$ , at surface regions of different stacking configurations, we place the $h$ -BN sandwich on a conducting substrate $\\mathrm{(Si/SiO_{2}}$ , graphite, or gold) and scan an atomic force microscope (AFM) operated in a Kelvin probe mode (KPFM) (Fig. 2A) (17). The potential map above the various stacking configurations is $\\Delta V_{\\mathrm{KP}}$ values ranging between 210 and $230\\mathrm{mV}$ for both closed-loop scans and local open-loop measurements (fig. S1). Similar values are measured for several samples with different substrate identities and various thicknesses of the top $h$ -BN flake (for flakes thicker than $\\mathbf{l}\\:\\mathrm{nm}\\dot{}$ ), and when using different AFM tips. These findings confirm that $\\Delta V_{\\mathrm{KP}}$ is an independent measure of the intrinsic polarization of the system that, in turn, is confined within a few interfacial layers. \n\nshown in Fig. 2B. We find clear domains (black and white) of constant $V_{\\mathrm{KP}}$ , extending over areas of several square micrometers, which are separated by narrow domain walls. Dark gray areas of average potential are observed above (i) positions where only one $h$ -BN flake exists (outside the dashed yellow line); (ii) above two flakes but beyond the topographic step marked by dashed red lines in Fig. 2B (and topography map fig. S2), as expected; and (iii) beyond topographic folds that can further modify the interlayer twist angle (dashed green lines). These findings confirm that white and black domains correspond to AB and BA interfacial stacking that host a permanent out-of-plane electric polarization. Such polarization is not observed at the other side of the step, where centrosymmetric AA', AB1', AB2' configurations are obtained, or at the AA configuration expected at domain-wall crossings (blue dots in Fig. 1C). Sufficiently far from the domain walls (toward the center of each domain), a constant potential is observed with a clear difference $\\Delta V_{\\mathrm{KP}}$ between the AB and BA domains, as shown in Fig. 2C. Whereas KPFM measurement nullifying the tip response at the electric bias frequency gives an underestimated potential difference of $\\Delta V_{\\mathrm{KP}}{\\sim}100~\\mathrm{mV}$ because of averaging contributions from the tip’s cantilever (17), more quantitative measurements obtained through sideband tip excitations yield \n\nAlthough our force field calculations for slightly twisted bilayer $h$ -BN show a uniform triangular lattice of alternating AB and BA stacked domains (Fig. 1C), in the experiment we observe large variations in their lateral dimensions and shape. This indicates minute deviations in the local twist, which are unavoidable in the case of small twist angles (19–22). Specifically, the ${\\sim}1{\\cdot}\\upmu\\mathrm{m}^{2}$ domains in the left part of Fig. 2B correspond to a global twist of less than $0.01^{\\circ}$ (23). In addition, any external perturbation to the structure, caused either by transferring it to a polymer, heating, or directly pressing it with the AFM tip, usually resulted in a further increase in domain size. In a few cases, high-temperature annealing resulted in a global reorientation to a single domain flake, many micrometers in dimensions. This behavior confirms the metastable nature of the AB/BA stacking mode, as well as the possible superlubric nature of the interface (24, 25). At the other extreme, much smaller domains are observed in the top righthand section of Fig. 2B. The smallest triangle edge that we could identify over many similar flakes was $60\\mathrm{nm}$ in length, which corresponds to a twist angle of $0.24^{\\circ}$ . We therefore conclude that, below this angle, atomic reconstruction to create untwisted domains is energetically favored. Naturally, this constitutes a lower bound on the maximal angle for domain formation as smaller domains below our experimental resolution may form at larger twist angles. \n\nTo trace the microscopic origin of the measured polarization, we performed a set of density functional theory (DFT) calculations on finite bilayer and quad-layer $h$ -BN flakes. For the finite bilayer calculations, we constructed two model systems, where hydrogen passivated $h$ -BN flakes of either 1 or $\\mathrm{3nm^{2}}$ surface area are stacked in the AB stacking mode (fig. S4). The calculated polarizations per unit area, $P_{z}/A$ , of these systems were 0.55 and 0.45 Debye $\\mathrm{{'nm^{2}}}$ , respectively (black triangles in Fig. 2D), pointing perpendicular to the interface only (table S1). Because edge effects may influence the results of such finite system calculations (17) (fig. S4), we performed complementary laterally periodic system calculations at various thicknesses. The detailed methods used for these calculations are discussed in (17). For the AB stacked periodic bilayer, we find a polarization of $P_{z}/A=$ 0:33 Debye= $\\mathrm{nm^{2}}$ , changing by only $10\\%$ when including additional two and eight AA' stacked layers above and below the AB stacked interface (see Fig. 2D and fig. S7). Adding more AB-stacked layers, however, reveals a linear increase of the calculated polarization with the number of added interfaces (fig. S9). The latter is a highly appealing control mechanism to engineer the magnitude of the polarization in future 2D systems, independent of external effects such as surface chemistry and local strains. Lateral shifts of the periodic bilayer system show a gradual evolution of the polarization when shifting between the AA, AB, and BA stacking modes, from zero to $+0.33$ and −0.33 Debye= $\\mathrm{nm^{2}}$ , respectively (Fig. 2E). This is crucial when considering the complex response at domain walls, where lattice deformations induce additional flexo (26) and piezo (27) responses. In fig. S8, we present also the charge density redistribution in the periodic bilayer system owing to interlayer coupling. The corresponding interlayer potential difference at the experimental configuration is calculated to be $\\begin{array}{r}{\\frac{1}{2}\\Delta V_{\\mathrm{KP}}=120\\mathrm{mV}}\\end{array}$ (fig. S7), in excellent agreement with the side-band measurements (red star in Fig. 2D). Similar results were reported in recent computational studies $(I I)$ . However, to obtain quantitative agreement with the experimental measurements, the results should be carefully converged with respect to the various calculation parameters (figs. S5 and S7). By further applying an electric field of $0.1\\mathrm{V/nm}$ normal to the plane, we find, from our calculations, a minute piezo-electric deformation of $0.1\\mathrm{pm}$ and a $5\\%$ variation in the polarization magnitude (fig. S10). \n\n![](images/5fd02bd35b4d5954c45e9176a955652ec234c56bc6d546dca7b19901e0d977aa.jpg) \nFig. 3. Dynamic flipping of polarization orientation by domain-wall sliding. Kelvinprobe maps measured consecutively from left to right above a particular flake location showing domains of up (white) and down (black) polarizations. The middle image was taken after \nbiasing the tip by a fixed DC voltage of $-20\\mathrm{\\V}$ and scanning it above the blue square region shown on the left-hand image. Then the tip was biased by $10\\mathrm{~V~}$ and scanned again over the same region before taking the right-hand image. Consecutive domain-wall positions are marked by dashed red, green, and yellow lines. Larger white (black) domains appear after positive (negative) bias scans as a result of domain-wall motion beyond the scan area. Note that the number of domain walls is apparently not altered. \n\nIt is instructive to further translate the measured potential difference into intralayer displacements in a simplistic point-like charges model ( $\\Delta d$ in Fig. 1D), where each atom is allowed to displace from its layer’s basal plane in the vertical direction. With the lattice site density of $n=37\\mathrm{{nm}^{-2}}$ and the on-site charge value, $q\\sim e/2$ , for single-layered $h$ -BN (28, 29), our measured $\\Delta V_{K P}$ gives out-of-plane atomic displacement of the order of $\\Delta d=\\Delta V_{\\mathrm{KP}}\\varepsilon_{0}/$ \n\n$4n q\\sim1\\times10^{-3}\\mathrm{{\\AA}}$ $(\\varepsilon_{0}$ is vacuum permittivity), which is much smaller than the intralayer $(\\mathrm{1.44\\AA})$ and interlayer $(3.30\\mathrm{\\AA})$ spacings. This implies that the polarization is determined by a delicate competition between the various interlayer interaction components and charge redistribution. Intuitively, we expect the vdW attraction to vertically compress the nonoverlapping interfacial sites (diagonal dashed ellipse in Fig. 1D) closer together than the overlapping sites (vertical dashed ellipse in Fig. 1D), which are more prone to Pauli repulsion. This direction of motion, for example, reduces the average interlayer separation and favors Bernal (AB like) stacking in graphite over the AA configuration (30). In $h$ -BN, however, the partial ionic nature of the two lattice sites (12, 31, 32) makes the fully eclipsed AA' stacking more stable (13). Hence, imposing a polar AB interface, as in our case, may favor overlapping sites of opposite charges to come closer together than the nonoverlapping pairs and the polarization to point in the opposite direction. \n\nTo quantify these arguments, we present a reduced classical bilayer model that captures the intricate balance between Pauli, vdW, and Coulomb interatomic interactions at different stacking modes. In our model $(I7)$ , the interfacial energy $\\begin{array}{r}{E=\\frac{1}{2}\\sum_{i,j}\\bigg[4\\upvarepsilon\\bigg(\\bigg(\\frac{\\upsigma}{r_{i j}}\\bigg)^{12}-\\bigg(\\frac{\\upsigma}{r_{i j}}\\bigg)^{6}\\bigg)+\\frac{q_{i}q_{j}}{r_{i j}}\\bigg]}\\end{array}$ includes a Lennard-Jones (LJ) potential characterized by the cohesive energy, e, and the interlayer spacing scale, $\\mathbf{\\sigma}_{\\mathbf{{\\sigma}}}$ and Coulomb interactions between the dimensionless partial atomic charges on the boron and nitrogen sites $q=\\pm q_{i}/e$ . Although neglecting any charge transfer processes between the layers that are explicitly taken into account in our DFT calculations, this model captures both the magnitude and orientation of the polarization by adjusting the ratio between e and Coulomb scales $\\propto\\varepsilon/q^{2}$ (fig. S11). Our detailed DFT calculations indicate that in bilayer $h$ -BN, the net polarization is oriented as marked by the arrows in Fig. 1D. \n\nThe permanent polarization observed in separated domains, whose dimensions can be tuned by the twist angle, each exhibiting a distinct and stable potential, may be useful in applications. To that end, however, one should identify additional ways to control the local orientation beyond the twisting mechanism. Reversible switching between AB and BA configurations, accompanied by polarization inversion, can be achieved through relative lateral translation by one atomic spacing (1.44 Å), as illustrated in Fig. 1A. Similar sliding between different stacking configurations was recently demonstrated in multilayered graphene. It was shown that both mechanical (33) and electric perturbations (34) can push domain walls, practically modifying the local stacking. In the present $h$ -BN interface, however, the polar switching calls for a preferred up or down orientation that can be predetermined by the user. To obtain such a spatially resolved control, we scanned a biased tip above an individual domain to induce a local electric field normal to the interface. The polarization images before and after the biased scans are presented in Fig. 3. We observe a redistribution of domain walls to orient the local polarization with the electric field under the biased tip. For example, after scanning a negatively biased tip above the region marked by the blue square, we observed a large white domain due to the motion of the walls marked by dashed red (green) line before (after) the scan. A successive scan by a positively biased tip resulted in practically complete domain polarization flipping. Hence, by applying negative or positive bias to the tip, it is possible to determine the polarization orientation of the underlying domain. Similar switching behavior was attained above different domains within the same interface and for several measured structures (fig. S12). We note that domain-wall motion is observed for electric field values exceeding ${\\sim}0.3\\ \\mathrm{V/nm}$ and when operating the biased scan in a pin-point mode $(I7)$ . \n\nOur results therefore demonstrate that the broken symmetry at the interface of parallelstacked $h$ -BN flakes gives rise to an out-ofplane two-dimensional polarization confined within a few interfacial layers that can be locally detected and controlled. Although the $h$ -BN system, with only two different light atoms, offers a convenient experimental and computational testbed and allows for intuitive interpretations, first-principle analysis (11) predicts similar phenomena to occur in other, more complex biatomic vdW crystals, such as various TMDs (35, 36). Notably, the origin of the polarization and the sliding inversion mechanism presented herein are fundamentally different from the minute deformations of tightly bonded atoms in common non-centrosymmetric 3D bulk crystals. The “slidetronics” switching involves lateral motion by a full lattice spacing in a weakly coupled interface under ambient conditions. The associated sliding order parameter reveals vortices patterns around the AA points (Figs. 1C and 2B) with topological aspects resembling the hexagonal manganite system (37). Unlike the 3D manganites, the present 2D structure allow relaxation processes through the delamination and formation of bubbles, or the annealing of walls at the open edges (fig. S12). In the present study, however, we focus on the physics away for the domain wall and toward the domain center, where no twist, moiré pattern, or strain are considered. The sensitivity of the system to the delicate interplay between vdW attraction, Pauli repulsion, Coulomb interactions, and charge redistribution implies that external stimuli such as pressure, temperature, and/ or electric fields may be used to control the polarization, thus offering many opportunities for future research. \n\nWe note that a paper in the same issue (38) reports similar findings. During the review process of this manuscript, similar experimental findings were also reported in (39), and a ferroelectric response in aligned bilayer graphene was reported in (40). \n\n# REFERENCES AND NOTES \n\n1. M. Lines, A. Glass, Principles and Applications of Ferroelectrics and Related Materials (Oxford Univ. Press, 2001). \n\n2. N. Setter et al., J. Appl. Phys. 100, 051606 (2006). \n3. J. F. Scott, Ferroelectrics 314, 207–222 (2005). \n4. J. F. Scott, ISRN Mater. Sci. 2013, 1–24 (2013). \n5. M. Dawber, K. M. Rabe, J. F. Scott, Rev. Mod. Phys. 77, 1083–1130 (2005). \n6. J. Müller, P. Polakowski, S. Mueller, T. Mikolajick, ECS J. Solid State Sci. Technol. 4, N30 (2015). \n7. Y. Cao et al., Nano Lett. 15, 4914–4921 (2015). \n8. D. D. Fong et al., Science 304, 1650–1653 (2004). \n9. S. S. Cheema et al., Nature 580, 478–482 (2020). \n10. F. Liu et al., Nat. Commun. 7, 1–6 (2016). \n11. L. Li, M. Wu, ACS Nano 11, 6382–6388 (2017). \n12. G. Constantinescu, A. Kuc, T. Heine, Phys. Rev. Lett. 111, 036104 (2013). \n13. R. S. Pease, Nature 165, 722–723 (1950). \n14. S. Zhou, J. Han, S. Dai, J. Sun, D. J. Srolovitz, Phys. Rev. B Condens. Matter Mater. Phys. 92, 155438 (2015). \n15. S. M. Gilbert et al., 2D Mater. 6, 021006 (2019). \n16. J. H. Warner, M. H. Rümmeli, A. Bachmatiuk, B. Büchner, ACS Nano 4, 1299–1304 (2010). \n17. Materials, methods, and additional information are available as supplementary materials. \n18. T. Maaravi, I. Leven, I. Azuri, L. Kronik, O. Hod, J. Phys. Chem. C 121, 22826–22835 (2017). \n19. J. S. Alden et al., Proc. Natl. Acad. Sci. U.S.A. 110, 11256–11260 (2013). \n20. M. R. Rosenberger et al., ACS Nano 14, 4550–4558 (2020). \n21. A. Weston et al., Nat. Nanotechnol. 15, 592–597 (2020). \n22. H. Yoo et al., Nat. Mater. 18, 448–453 (2019). \n23. T. A. Green, J. Weigle, Helv. Phys. Acta 21, 217 (1948). \n24. C. R. Woods et al., Nat. Phys. 10, 451–456 (2014). \n25. O. Hod, E. Meyer, Q. Zheng, M. Urbakh, Nature 563, 485–492 (2018). \n26. L. J. McGilly et al., Nat. Nanotechnol. 15, 580–584 (2020). \n27. P. Ares et al., Adv. Mater. 32, e1905504 (2020). \n28. W. M. Lomer, K. W. Morton, Proc. Phys. Soc. A 66, 772–773 (1953). \n29. Y.-N. Xu, W. Y. Ching, Phys. Rev. B Condens. Matter 44, 7787–7798 (1991). \n30. J.-C. Charlier, X. Gonze, J.-P. Michenaud, Europhys. Lett. 28, 403–408 (1994). \n31. N. Marom et al., Phys. Rev. Lett. 105, 046801 (2010). \n32. O. Hod, J. Chem. Theory Comput. 8, 1360–1369 (2012). \n33. L. Jiang et al., Nat. Nanotechnol. 13, 204–208 (2018). \n34. M. Yankowitz et al., Nat. Mater. 13, 786–789 (2014). \n35. J. Sung et al., Nat. Nanotechnol. 15, 750–754 (2020). \n36. T. I. Andersen et al., https://arxiv.org/abs/1912.06955 arXiv [cond-mat.mes-hall] (2019). \n37. S. Artyukhin, K. T. Delaney, N. A. Spaldin, M. Mostovoy, Nat. Mater. 13, 42–49 (2014). \n38. K. Yasuda, X. Wang, K. Watanabe, T. Taniguchi, P. Jarillo-Herrero, Science 372, 1458–1462 (2021). \n39. C. R. Woods et al., Nat. Commun. 12, 347 (2021). \n40. Z. Zheng et al., Nature 588, 71–76 (2020). \n41. M. Vizner Stern et al., Replication Data for: Interfacial Ferroelectricity by van der Waals Sliding, Zenodo (2021). \n\n# ACKNOWLEDGMENTS \n\nWe thank Y. Lahini for useful discussions, A. Cerreta (Park Systems) for AFM support, and N. Ravid for laboratory support. We further thank J. E. Peralta for helpful discussions regarding the DFT calculations. Funding: W.C. acknowledges the financial support of the IASH and the Sackler Center for Computational Molecular and Materials Science at Tel Aviv University. Growth of hBN was supported by the Elemental Strategy Initiative conducted by the MEXT, Japan (grant JPMXP 0112101001), JSPS KAKENHI (grant JP20H00354), and the CREST (JPMJCR15F3), JST. E.S. acknowledges support from ARO (W911NF-20-1-0013), the Israel Science Foundation (grant 154/19, and US-Israel Binational Science Foundation (grant 2016255). M.U. acknowledges financial support of the Israel Science Foundation (grant 1141/18) and the ISFNSFC (joint grant 3191/19). O.H. is grateful for the generous financial support of the Israel Science Foundation under grant 1586/17, the Naomi Foundation for generous financial support via the 2017 Kadar Award, and the Ministry of Science and Technology of Israel under project number 3-16244. M.B.S. acknowledges funding by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no.852925), the Israel Science Foundation (grant 1652/18), and the Israel Ministry of Science and Technology project no. 3-15619 (Meta-Materials). O.H. and M.B.S. acknowledge the Center for Nanoscience and Nanotechnology of TelAviv University. Author contributions: M.V.S. and Y.W. performed the experiments, supported by I.N. and supervised by M.B.S.; W.C. performed the DFT calculations supervised by M.U. and O.H.; K.W. and T.T. grew the hBN crystals; E.S. devised the adhesion model. All authors contributed to the writing of the manuscript. Competing interests: Ramot at Tel Aviv University Ltd. has applied for a patent (US application no. 63/083,947) on some of the technology and materials discussed here, on which M.V.S., Y.W., and M.B.S. are listed as co-inventors. Data and materials availability: All data needed to evaluate the conclusions in the study are present in the main text or the supplementary materials. The data have also been uploaded to Zenodo (41). \n\n# SUPPLEMENTARY MATERIALS \n\nscience.sciencemag.org/content/372/6549/1462/suppl/DC1 \nMaterials and Methods \nFigs. S1 to S12 \nTable S1 \nReferences (42–59) \n16 September 2020; accepted 10 May 2021 \nPublished online 10 June 2021 \n10.1126/science.abe8177 " + }, + { + "id": "10.1093_nsr_nwaa178", + "DOI": "10.1093/nsr/nwaa178", + "DOI Link": "http://dx.doi.org/10.1093/nsr/nwaa178", + "Relative Dir Path": "mds/10.1093_nsr_nwaa178", + "Article Title": "Molecular grafting towards high-fraction active nullodots implanted in N-doped carbon for sodium dual-ion batteries", + "Authors": "Mu, SN; Liu, QR; Kidkhunthod, P; Zhou, XL; Wang, WL; Tang, YB", + "Source Title": "NATIONAL SCIENCE REVIEW", + "Abstract": "Sodium-based dual-ion batteries (Na-DIBs) show a promising potential for large-scale energy storage applications due to the merits of environmental friendliness and low cost. However, Na-DIBs are generally subject to poor rate capability and cycling stability for the lack of suitable anodes to accommodate large Na+ ions. Herein, we propose a molecular grafting strategy to in situ synthesize tin pyrophosphate nullodots implanted in N-doped carbon matrix (SnP2O7@N-C), which exhibits a high fraction of active SnP2O7 up to 95.6 wt% and a low content of N-doped carbon (4.4 wt%) as the conductive framework. As a result, this anode delivers a high specific capacity similar to 400 mAh g(-1) at 0.1Ag(-1), excellent rate capability up to 5.0Ag(-1) and excellent cycling stability with a capacity retention of 92% after 1200 cycles under a current density of 1.5Ag(-1). Further, pairing this anode with an environmentally friendly KS6 graphite cathode yields a SnP2O7@N-C||KS6 Na-DIB, exhibiting an excellent rate capability up to 30 C, good fast-charge/slow-discharge performance and long-term cycling life with a capacity retention of similar to 96% after 1000 cycles at 20 C. This study provides a feasible strategy to develop high-performance anodes with high-fraction active materials for Na-based energy storage applications.", + "Times Cited, WoS Core": 464, + "Times Cited, All Databases": 468, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000697170300004", + "Markdown": "# RESEARCH ARTICLE \n\n# MATERIALS SCIENCE \n\n# Molecular grafting towards high-fraction active nanodots implanted in N-doped carbon for sodium dual-ion batteries \n\nSainan $\\mathrm{\\Mu^{a,b,\\dagger}}$ , Qirong Liua,†, Pinit Kidkhunthodc, Xiaolong Zhoua, Wenlou Wangb, Yongbing Tanga,\\* \n\naFunctional Thin Films Research Center, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China \n\nbNano Science and Technology Institute, University of Science and Technology of China, Suzhou 215123, China \n\ncSynchrotron Light Research Institute, Nakhon Ratchasima 30000, Thailand \n\n†Equally contributed to this work. \n\n\\*Corresponding authors. E-mail: tangyb@siat.ac.cn \n\n# ABSTRACT \n\nSodium-based dual-ion batteries (Na-DIBs) show a promising potential for large-scale energy storage applications due to the merits of environmental friendliness and low cost. However, Na-DIBs are generally subject to poor rate capability and cycling stability for the lack of suitable anodes to accommodate large $\\mathrm{{Na}^{+}}$ ions. Herein, we propose a molecular grafting strategy to in-situ synthesize tin pyrophosphate nanodots implanted in N-doped carbon matrix $\\mathrm{\\cdotSnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}})$ , which exhibits a high fraction of active $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ up to $95.6~\\mathrm{wt\\%}$ and a low content of N-doped carbon $(4.4~\\mathrm{wt\\%})$ as the conductive framework. As a result, this anode delivers a high specific capacity ${\\sim}400\\ \\mathrm{mAh}\\ \\mathrm{g}^{-}$ at 0.1 A $\\mathbf{g}^{-1}$ , excellent rate capability up to 5.0 A $\\mathbf{g}^{-1}$ , and excellent cycling stability with a capacity retention of $92\\%$ after 1200 cycles under a current density of $1.5\\mathrm{Ag}^{-1}$ . Further, pairing this anode with an environmentally friendly KS6 graphite cathode yields a $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}\\mathrm{-}\\mathrm{C}||\\mathrm{KS}6\\mathrm{\\Na}\\mathrm{-}\\mathrm{DI}$ B, exhibiting an excellent rate capability up to $30~\\mathrm{C}$ , good fast-charge/slow-discharge performance, and long-term cycling life with a capacity retention of ${\\sim}96\\%$ after 1000 cycles at $20~\\mathrm{C}$ . This study provides a feasible strategy to develop high-performance anodes with high-fraction active materials for Na-based energy storage applications. \n\nKeywords: molecular grafting, high-fraction active material, tin pyrophosphate, N-doped carbon, sodium-based dual-ion batteries \n\n# INTRODUCTION \n\nThe limited reserve and uneven distribution of lithium resource promote the development of lithium-free energy storage systems based on abundant alkali and alkaline cations such as Na+ [1-9], $\\operatorname{K}^{+}$ [10-15], $\\mathrm{Mg}^{2+}$ [16-18], $\\mathrm{Ca}^{2+}$ [19,20], $Z\\mathrm{n}^{2+}$ [21-25], Al3+ [26-28], etc. Among them, owing to the high natural abundance of sodium resources and the similar electrochemical properties of $\\mathrm{{Na}^{+}}$ to ${\\mathrm{Li}}^{+}$ , sodium-ion batteries (SIBs) are a potential alternative to lithium-ion batteries (LIBs) for large-scale power grids and intermittent energy storage systems [29-36]. On the other hand, dual-ion batteries (DIBs) have also attracted considerable attention due to their advantages of high working voltages, environmental benignity, and low cost [37-42]. \n\nIn this cell configuration, graphite materials are generally applied as both anode and cathode, cations and anions participate in the electrochemical redox reactions on anode and cathode, respectively [43-47]. Therefore, if the advantages of both SIBs and DIBs are combined, it is possible to develop high efficient, low-cost, and environmentally friendly sodium-based DIBs (Na-DIBs) for large-scale energy storage applications. \n\nHowever, unlike ${\\mathrm{Li}}^{+}$ and $\\mathrm{K}^{+}$ ions, traditional graphite materials are difficult to act as the anode for the intercalation of $\\mathrm{{Na}^{+}}$ ions [48,49]. Further, the large ionic radius of $\\mathrm{{Na}^{+}}$ (1.02 Å vs. 0.76 Å for ${\\mathrm{Li}}^{+}$ ) results in sluggish reaction kinetics and large volume changes of the anode materials such as Sn [50,51], $\\ensuremath{\\mathrm{MoS}}_{2}$ [52-54], TiO2 [55], and $\\mathrm{FePO}_{4}$ [56], and thus leads to poor rate capability and unsatisfied cycling stability [57-59]. Several approaches have been applied to improve the electrochemical performance of these anodes, including nanoscale modification and carbon-based composite construction [60-65], for example, carbon-based tin pyrophosphate $\\mathrm{(SnP_{2}O_{7})}$ ) composite with a high carbon content $(16.8\\%)$ has been demonstrated to exhibit enhanced cycling stability for ${\\mathrm{Na}}^{+}.$ -ion storage [66]. Although the carbon matrix can improve the electronic conductivity and provide a buffer framework for alleviating the volume expansion of these anodes, the excessive carbon content (commonly 15 wt%) would decrease the fraction of active material and thus reduce the energy density of batteries. Therefore, it is necessary to increase the fraction of active materials as high as possible and reduce the content of inactive carbon without compromising the conductivity of composite anodes, so that anodes can effectively \n\ndeliver their specific capacities. \n\nHerein, we propose a molecular grafting strategy to in-situ implant $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ nanostructure in N-doped carbon $(\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{-}\\mathrm{C})$ as the anode for Na-DIBs. Such a strategy enables high-fraction $(95.6~\\mathrm{wt\\%})$ ) active materials to uniformly embed in the carbon matrix and to effectively prevent the exfoliation of active materials, while the N doping leads to high conductivity even at a low C content. It exhibits a high specific capacity of $400\\ \\mathrm{mAh\\g^{-1}}$ at $0.1\\mathrm{~A~g^{-1}}$ and excellent cycling stability with a capacity retention of $92\\%$ after 1200 cycles under $1.5\\mathrm{Ag}^{-1}$ . Consequently, pairing this anode with an environmentally friendly graphite cathode yields a SnP2O7@N-C||KS6 Na-DIB, which shows excellent rate performance up to 30 C, good fast-charge/slow-discharge ability, and long-term cycling life with a capacity retention of $96.3\\%$ after 1000 cycles, showing a promising potential for Na-based energy storage devices. \n\n# RESULTS AND DISCUSSION \n\nFigure 1 schematically illustrates the synthesis procedure of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N-C}$ via the molecular grafting method. Owing to the complexing interaction between radical groups (e.g. phosphate groups) and metal cations (e.g. tin ions) and the hydrogen bond between organic precursors, many precursor agents can molecularly graft into precursor composite with a three-dimensional framework, accompanying with a fully mixing procedure. In this case, we choose phytic acid as the phosphorous source to strengthen the adhesion between active nanodots and carbon matrix due to sufficient \n\nO-C bonds and strong complexing ability of phosphate groups to tin cations. Simultaneously, the low atomic ratio of C to $\\mathrm{\\bfP}$ can avoid residual carbon content in the formed composite. Besides, we choose the melamine as the N doping source because its high atomic ratio of $\\mathrm{\\DeltaN}$ to C can result in a high concentration of nitrogen in the carbon matrix. After the filtration and dry processes, composite precursor nanoparticles were achieved. Finally, the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}/\\mathrm{N}{-}\\mathrm{C}$ nanoparticles were synthesized via calcining the precursor composite under an Ar atmosphere. \n\nIn order to investigate the molecular grafting process, Fourier transform infrared spectra (FTIR) measurements of precursors and their composites were carried out. The characteristic absorption peaks originating from phosphate radical (980 and 1140 $\\mathrm{cm}^{-1}.$ ), phosphate hydrogen radical $(1631~\\mathrm{cm}^{-1}\\cdot$ ), and stretching vibration of O-H (3329 $\\mathrm{cm}^{-1})$ ) are observed in the FTIR spectrum of the phytic acid solution (Supplementary Fig. S1a). To confirm the complexing interaction between phosphate groups and tin cations, phytic acid and $\\mathrm{SnCl}_{2}$ were applied to synthesize a precursor composite without the addition of melamine. Compared with that of phytic acid, the FTIR spectrum of the composite (Supplementary Fig. S1b) presents an obvious peak shift of phosphate to 1035 cm-1, which should be ascribed to the complexing interaction between phosphate groups and tin cations. For the pure melamine, some characteristic absorption peaks involving the out-of-plane ring bending vibration of triazine ring (810 cm-1), stretching vibration of C-N $(1431~\\mathrm{cm}^{-1}\\cdot$ ), stretching vibrations of triazine ring $1526\\mathrm{cm}^{-1},$ ), scissoring vibration of $\\mathrm{NH}_{2}$ ( $\\cdot1626\\mathrm{cm}^{-1})$ ), and stretching vibrations of $\\mathrm{NH}_{2}$ $(3100-3500~\\mathrm{cm}^{-1},\\$ ) were observed in its FTIR spectrum (Supplementary Fig. S1c). \n\nOnce the addition of melamine, its three typical absorption peaks at 773, 1440, and $1529~\\mathrm{{cm}^{-1}}$ were detected in the FTIR spectrum of the precursor composite (Supplementary Fig. S1d). The obvious peak shift of melamine at $810~\\mathrm{{cm}^{-1}}$ to $773~\\mathrm{{cm}^{-1}}$ should be attributed to the formation of intermolecular hydrogen bonds between melamine and phosphate groups [67]. \n\nCompared with the precursor composite (Supplementary Fig. S2), the synthesized SnP2O7@N-C composite features a stable morphology without structural collapse after calcination treatment (Fig. 2a and Supplementary Fig. S3a-c), and is comprised of nanoparticles with an average size of $200\\mathrm{nm}$ . The selected area electron diffraction (SAED) pattern (Supplementary Fig. S3d) indicates that the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}_{-}\\mathrm{C}$ sample has a well-crystallized structure. Further characterizations via high-resolution transmission electron microscopy (HRTEM) images (Fig. 2b) detect that several crystalline nanodots are uniformly implanted in the amorphous carbon matrix. Figure 2c and Supplementary Fig. S3e show obvious lattice fringes with an interplanar spacing of $0.40\\mathrm{nm}$ , matching well with the (200) plane of cubic-phase $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ . XRD pattern and Raman spectrum were carried out to provide more structural information. As observed in Fig. 2d, all sharp diffraction peaks can be indexed to cubic-phase $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ (JCPDS Card No. 29-1352), in accordance with the HRTEM observations. In contrast, those samples calcined at $500^{\\circ}\\mathrm{C}$ and $700^{\\circ}\\mathrm{C}$ (Supplementary Fig. S4) do not present similar characteristic diffraction peaks of $\\operatorname{SnP}_{2}\\mathrm{O}_{7}$ . Note that a bump peak located at ${\\sim}26^{\\circ}$ should originate from the amorphous carbon matrix. Its amorphous feature is also confirmed by the Raman spectrum (Fig. 2e), where two characteristic peaks of carbon situated at ${\\sim}1360~\\mathrm{cm^{-1}}$ and ${\\sim}1585~\\mathrm{cm}^{-1}$ can be observed. Both peaks are individually attributed to D band of disordered carbon and G band of graphitic carbon. The ratio of $\\boldsymbol{I_{\\mathrm{D}}}$ to $I_{\\mathrm{G}}$ approximates 1.0, implying the carbon matrix’s dominant defective and disordered nature. Further thermogravimetric analysis (TGA) measurement (Fig. 2f) indicates that the fractions of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ nanodots and N-doped carbon are $95.6~\\mathrm{wt\\%}$ and $4.4~\\mathrm{wt\\%}$ , respectively, which is the highest fraction of active material among previously reported Sn-based compound/carbon composites [66,68-70]. Both the XRD pattern (Supplementary Fig. S5a) and the Raman spectrum (Supplementary Fig. S5b) after the TGA test show the absence of carbon characteristic peaks, indicating the complete decomposition of the carbon component in the TGA test. Similarly, the TGA analysis of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{C}$ (Supplementary Fig. S6) shows that the carbon content of the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{C}$ composite is ${\\sim}3.7\\%$ , close to that of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ $(\\sim4.4\\%)$ , which suggests that the addition of melamine slightly increases the carbon content, ascribable to its high atomic ratio of $\\mathrm{\\DeltaN}$ to C. The nitrogen adsorption/desorption isotherm of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ (Supplementary Fig. S7) reveals that its Brunauer-Emmert-Teller (BET) specific surface area is ${\\sim}9.0\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}$ . \n\nThe chemical components of the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{-}\\mathrm{C}$ sample were analyzed by $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS). As shown in Supplementary Fig. S8a, the survey XPS spectrum suggests the existence of O, P, Sn, C, and N elements in the sample, consistent with the EDX elemental mappings where these elements uniformly distribute in the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ composite (Supplementary Fig. S9). High-resolution Sn 3d XPS spectrum (Fig. 2g) presents a pair of characteristic peaks at 495.4 and \n\n487.0 eV, corresponding to Sn $3\\mathrm{d}_{3/2}$ and Sn $3\\mathrm{d}_{5/2}$ of $\\mathrm{Sn}^{4+}$ in $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ , respectively. Besides, only one peak at $134.0~\\mathrm{eV}$ referring to the $\\textsf{P}2\\mathsf{p}$ can be observed (Fig. 2h), indicating a complete transformation of $\\mathrm{\\bfP}$ source to $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ without $\\mathrm{\\bfP}$ doping. The deconvoluted O 1s spectrum (Supplementary Fig. S8b) includes two peaks. The dominant peak is assigned to the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ , and another involves O-C bonding. Moreover, the high-resolution C 1s spectrum (Supplementary Fig. S8c) can be fitted into three peaks at 284.6, 285.5, and $286.5\\mathrm{eV},$ , individually originating from C-C, C-N, and C-O, exhibiting that the carbon matrix is doped with dominant nitrogen and slight oxygen [54]. The high-resolution $\\mathrm{\\DeltaN}$ 1s spectrum (Fig. 2i) shows the existence of pyridinic N (398.5 eV), pyrrolic N (400.0 eV), and quaternary N (401.1 eV) [71]. Such structural and chemical features confirm the homogeneous implantation of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ nanodots in the N-doped carbon matrix, which is expected to optimize its charge transfer kinetics and electrochemical stability for SIBs. \n\nWe firstly carried out the cyclic voltammogram (CV) measurement to investigate the $\\mathrm{{Na}^{+}}$ -storage behavior of the SnP2O7@N-C anode. Figure 3a exhibits the first three CV curves at 0.1 mV s-1 in the potential range of 0.01-3.0 V. In the first sodiation process, there are multiple peaks situated at 1.55, 1.10, 0.58, 0.39, and 0.07 V. According to previous reports, the Na-Sn alloying reactions occurred at potentials below $0.9\\mathrm{V}[70,72]$ . Thus, the first two peaks should involve the conversion process of $\\displaystyle\\mathbf{S}\\mathbf{n}\\mathbf{P}_{2}\\mathbf{O}_{7}$ to metallic Sn, and the others stem from the Na–Sn alloying reactions [70,71]. In the following cycles, only a broad and strong peak at $1.18{\\mathrm{~V~}}$ is observed for the conversion reaction. However, the desodiation processes in different cycles always exhibit five peaks at 0.23, 0.69, 0.86, 1.38, and 1.84 V. Such behavior suggests the conversion reaction probably refers to a two-step reduction/oxidation reactions of $\\mathrm{Sn}^{4+}/\\mathrm{Sn}^{2+}$ and $\\mathrm{Sn}^{2+}/\\mathrm{Sn}^{0}$ , and the Na–Sn alloying/dealloying reaction is also associated with a multi-step reaction process. \n\nTo further get insight into its $\\mathrm{{Na}^{+}}$ -ion storage mechanism, the sodiation/desodiation process of the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ anode was detected with synchrotron X-ray absorption near edge structure (XANES) spectra of the Sn $\\mathrm{L}_{3}$ -edge (Fig. 3b-c) at different charging/discharging states (Supplementary Fig. S10), where two peaks are assigned to the $2\\mathrm{p}_{3/2}\\mathrm{-}5\\mathrm{s}_{1/2}$ transition [73]. As observed in Fig. 3b, the intensities of the characteristic peaks decrease as the discharging process proceeds, associated with the transformation of $\\mathrm{Sn}^{4+}$ to $\\mathrm{Sn}^{0}$ [73,74]. A reverse evolution of the peak intensities is obviously observed during the charging process (Fig. 3c), demonstrating the good reversibility of Sn state during cycling. Note that the slight difference of Sn $\\mathrm{L}_{3}$ -edge XANES spectra at 0.01 V and $1.2\\mathrm{~V~}$ should be ascribed to the de-alloying reactions of the sample without obvious variation in the valence state of Sn element. \n\nFurther, HRTEM characterizations at different charging/discharging states were performed to verify its sodiation/desodiation mechanism. For the pristine sample, an interplanar spacing of $0.398~\\mathrm{nm}$ is clearly distinguished (Supplementary Fig. S11a), which corresponds to (200) plane of the $\\operatorname{SnP}_{2}\\mathrm{O}_{7}$ . When the sodiation process proceeds until 0.55 V, there are some lattice fringes with lattice spacing of 0.248 and $0.217{\\mathrm{nm}}$ (Fig. 3d), which match well with (131) plane of $\\mathrm{Sn}_{2}\\mathrm{P}_{2}\\mathrm{O}_{7}$ (ICSD No. 170846) and (208) \n\nplane of $\\mathrm{{NagSn_{4}}}$ (PDF No. 31-1326), respectively. And the fully sodiation state clearly contains ${\\bf N a}_{4}{\\bf P}_{2}{\\bf O}_{7}$ and $\\mathrm{Na}_{15}\\mathrm{Sn}_{4}$ two crystal phases (Fig. 3e), further confirming that the sodiation process of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ anode involves both conversion and alloying reactions. Conversely, as the desodiation process is conducted to $1.2~\\mathrm{V},$ the presence of metallic Sn is verified by the HRTEM image in Fig. 3f. The completed desodiation process at $3.0\\mathrm{~V~}$ accompanies with the formation of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ (Fig. 3g), indicating a good sodiation/desodiation reversibility of $\\operatorname{SnP}_{2}\\mathrm{O}_{7}$ . It is also noteworthy that, different from the reported results [66], there are some lattice fringes with an interplanar spacing of $0.304{\\mathrm{nm}}$ (Supplementary Fig. S11b), corresponding to the (-131) plane of P-1 $\\mathrm{Sn}_{2}\\mathrm{P}_{2}\\mathrm{O}_{7}$ (ICSD No. 170846), which implies the presence of Sn2P2O7 during desodiation process. Therefore, the HRTEM result is greatly consistent with the analyses of CV result during sodiation/desodiation processes. \n\nThe electrochemical properties of the $\\mathrm{SnP_{2}O}_{7}@\\mathrm{N}.\\mathrm{C}$ anode were evaluated in a coin-type half-cell. As observed in Fig. 4a, an abnormal shape of the galvanostatic charge-discharge profile at the first cycle is attributed to the incompletely reversible sodiation process of SnP2O7 and the formation of solid-electrolyte interphase (SEI) layer [54,75]. Although a pulverization phenomenon of $\\operatorname{SnP}_{2}\\mathrm{O}_{7}$ is observed after the first sodiation/desodiation process (Supplementary Fig. S12), there is a stable shape of galvanostatic charge-discharge profiles after the first cycle. It shows a specific discharge capacity of ${\\sim}400\\ \\mathrm{mAh\\g^{-1}}$ at $0.1\\mathrm{~A~g~}^{-1}$ with a Coulombic efficiency of ${\\sim}100\\%$ (Fig. 4b), indicating a good stability during the following sodiation/desodiation processes. Further, the EDX mappings of the anode at fully discharged state (Supplementary Fig. S13) verify uniform distributions of O, P, Sn, Na, C, and N elements, implying a homogeneous sodiation reaction during discharging process. Such robust charging/discharging behavior was also confirmed by the electrochemical impedance spectroscopy (EIS, Fig. 4c). No obvious variation in its EIS spectra is observed before and after 100 cycles, ascribable to the strong adhesion between $\\operatorname{SnP}_{2}\\mathrm{O}_{7}$ nanodots and N-doped carbon matrix. \n\nFigure 4d and e present the rate performance of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ anode at current densities from 0.1 to $5.0\\mathrm{~A~g}^{-1}$ . It exhibits specific capacities of 400, 381, 354, 335, 305, 295, 261, and $210\\ \\mathrm{mAh\\g^{-1}}$ at current densities of 0.1, 0.2, 0.3, 0.5, 1.0, 1.5, 3.0, and 5.0 A $\\mathbf{g}^{-1}$ , respectively. The specific capacities are recoverable as the current density is returned to $0.1\\mathrm{~A~g^{-1}}$ . It should be noted that the rate capability of the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ anode is much better than that of pure SnP2O7 (58 mAh $\\mathbf{g}^{-1}$ at $1.5\\mathrm{Ag}^{-1})$ , $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{C}$ without N doping (176 mAh g-1 at 1.5 A g-1) (Supplementary Fig. S14) and previously reported $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ composite with $16.8~\\mathrm{wt\\%}$ carbon nanosheets [66]. The excellent rate capability can be attributed to that $\\mathrm{~\\bf~N~}$ doping enhances the conductivity of carbon framework and facilitates diffusion kinetics of $\\mathrm{{Na}^{+}}$ ions [71,76], and the active nanodots shorten the diffusion path of $\\mathrm{{Na}^{+}}$ ions [77,78]. Figure 4f and Supplementary Fig. S15 show the composite anode’s cycling performance under a current density of $1.5\\mathrm{~A~g~}^{-1}$ , exhibiting excellent cycling stability with a capacity retention ${\\sim}92\\%$ after 1200 cycles and the corresponding Coulombic efficiency close to $100\\%$ . In contrast, much lower capacity retentions of $\\sim79\\%$ and ${\\sim}49\\%$ are obtained for $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{C}$ and pure $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ after 400 cycles (Supplementary \n\nFig. S16), respectively. Among the reported Sn-based compound/carbon composite anodes for SIBs (Supplementary Table S1), the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ with the lowest carbon content delivers a competitive specific capacity and superior cycling performance. \n\nConsequently, we paired this anode with an environmentally friendly KS6 graphite cathode to construct a proof-of-concept Na-DIB to further explore its practical sodium storage capability in the full cell. Figure 5a schematically illustrates its working mechanism, where $\\mathrm{{Na}^{+}}$ cations and $\\mathrm{PF}_{6}^{-}$ anions separately move to the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}-($ C anode and KS6 graphite cathode during the charging process, while both cations and anions return back to the electrolyte from the anode and cathode during discharging process, respectively. Its typical galvanostatic charge-discharge profile (Fig. 5b) in the voltage range of 1.0 to $4.0\\mathrm{V}$ at 3 C (1 C = 100 mA g-1) exhibits several voltage plateaus, corresponding to the different intercalation/de-intercalation stages of $\\mathrm{PF}_{6}^{-}$ anions. According to the dQ/dV differential curve (Fig. 5c), the charging process (Fig. 5b) can be roughly separated into three voltage regions of 2.6-3.25 V (stage I), 3.25-3.55 V (stage II), and 3.55-4.0 V (stage III), corresponding to three different stages of anion intercalation into KS6 graphite cathode [50,52,53]. In order to get insight into the electrochemical process of the SnP2O7@N-C//KS6 Na-DIB during the charging process, the galvanostatic charge-discharge profile of Na//KS6 half-cell and corresponding dQ/dV differential curve (Supplementary Fig. S17) were provided. The dQ/dV differential curve also present three different stages, indicating the dominant role of anion intercalation into KS6 graphite cathode. Conversely, a reverse evolution accompanies with the discharging process, where different de-intercalation stages occur in voltage ranges of 4.0-2.6 V (stage III’), 2.6-2.06 V (stage II’), and 2.06-1.30 V (stage I’) in the discharging process (Fig. 5c and Supplementary Fig. S17). Such intercalation/de-intercalation behavior of $\\mathrm{PF}_{6}^{-}$ anions was further confirmed by the in-situ XRD measurements during the charging/discharging process (Fig. 5d). The original XRD pattern presents a characteristic (002) peak of KS6 graphite cathode at $26.7^{\\mathrm{{o}}}$ . In the charging process, the characteristic peak becomes weak and splits into two peaks individually shifting towards lower (main peak) and higher 2θ degrees, corresponding to the stage I of anion intercalation into KS6 graphite cathode. The stage II involves the formation of a stable intercalation phase at $23.6^{\\circ}$ . Then, the stage III relates to a sharp transition of diffraction peaks and the formation of another stable phase at 22.1o. Such peak evolution is ascribable to the successful intercalation of PF6− anions into graphite cathode [79,80]. A reverse evolution occurs in the discharging process, and the two peaks gradually merge into the initial peak at $26.7^{\\mathrm{o}}$ at the end of the discharging, indicating excellent reversibility of the intercalation/de-intercalation process of $\\mathrm{PF}_{6}^{-}$ anions into/from KS6 graphite cathode. \n\nFigure 6a presents the rate capability of the $\\mathrm{SnP_{2}O_{7}@N-C||K S6_{\\Delta}N a-D I B_{\\Delta}}$ , which delivers a reversible discharge capacity of $78\\mathrm{mAh\\g^{-1}}$ at $3\\mathrm{C}$ . Even at $30\\mathrm{C}$ , a specific capacity of 65 mAh $\\mathbf{g}^{-1}$ can be obtained $83.3\\%$ capacity retention) with $\\sim100\\%$ Coulombic efficiency. The galvanostatic charge-discharge profiles at different current densities show similar shapes and a slight shift of voltage plateaus, indicating negligible electrochemical polarization (Fig. 6b). Besides, it can be rapidly charged at \n\n30 C and slowly discharged down to 3 C (Fig. 6c-d). The discharge profiles exhibit a slight variation, and the corresponding specific capacity can be stably delivered even at different current densities, exhibiting a good fast-charge/slow-discharge ability. Moreover, the Na-DIB shows an excellent cycling performance with a capacity retention of $\\sim96\\%$ and a Coulombic efficiency of ${\\sim}100\\%$ after 1000 cycles under a high rate of $20\\mathrm{C}$ (Fig. 6e). The galvanostatic charge-discharge profiles at $20^{\\mathrm{th}}$ , ${100}^{\\mathrm{th}}$ , $500^{\\mathrm{th}}$ and $1000^{\\mathrm{th}}$ cycles have the same shape and voltage plateaus (Fig. 6f), further verifying its stable cycling ability. As shown in Supplementary Table S2, the SnP2O7@N-C||KS6 Na-DIB presents superior cycling performance, rate capability, and Coulombic efficiency to previously reported Na-DIBs based on different anode materials [50,52-56,75,80-86]. \n\n# CONCLUSION \n\nIn summary, high-fraction (up to 95.6 wt%) SnP2O7 active anode material was successfully in-situ implanted in the N-doped carbon matrix via a molecular grafting strategy. Such a synthesis strategy effectively enhanced the adhesion between active materials and carbon matrix, while the N doping led to high conductivity even at low C content. As a result, the anode showed a high specific capacity of ${\\sim}400\\ \\mathrm{mAh\\g^{-1}}$ at 0.1 A g-1, good rate performance up to $5.0\\mathrm{Ag}^{-1}$ , and excellent cycling stability with a capacity retention of $92\\%$ after 1200 cycles at $1.5\\mathrm{Ag}^{-1}$ . Furthermore, this anode was paired with an environmentally friendly KS6 graphite cathode to yield a proof-of-concept Na-DIB, showing a superior rate capability with a capacity retention of ${\\sim}83\\%$ even at a high current density of $30~\\mathrm{C}$ , good fast-charge/slow-discharge ability, and long-term cycling life with a capacity retention of $\\sim96\\%$ after 1000 cycles at $20~\\mathrm{C}$ , exhibiting a great potential for high-performance Na-based energy storage devices. \n\n# METHODS \n\n# Synthesis of $\\mathbf{SnP}_{2}\\mathbf{O}_{7}@\\mathbf{N-C}$ \n\n$\\mathrm{SnCl}_{2}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O}$ powder was dissolved in deionized water under stirring, and then phytic acid solution and melamine powder were sequentially added into the above solution and subsequently stirred vigorously. Then, the mixture was transferred to a two-necked flask, and absolute ethanol was added, and refluxed under stirring. Next, the obtained reaction product was collected by centrifugation, successively washed with deionized water and ethanol several times and dried under vacuum. Finally, the powder product was calcined in an Ar atmosphere to obtain $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}-1$ C sample. \n\n# Materials characterization \n\nThe morphological and elemental features were characterized using field-emission scanning electron microscope (FE-SEM). The FEI Tecnai G2 F30 was applied to acquire the transmission electron microscope (TEM) images, elemental mappings and selected area electron diffraction (SAED) pattern. X-ray diffraction (XRD) analyses were implemented on a Rigaku D MiniFlex 600 diffractometer. Raman spectra were collected on Horiba LabRAM HR800. $\\Nu_{2}$ physical adsorption-desorption analysis was carried out on ASAP 2020M. The chemical composition of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}/\\mathrm{N}{-}\\mathrm{C}$ sample was determined using X-ray photoelectron spectroscopy (XPS) with monochromatic aluminum Kα radiation. Thermogravimetric analysis (TGA) were conducted from 100 $^{\\mathrm{{o}}}\\mathrm{{C}}$ to $700~^{\\circ}\\mathrm{C}$ . Fourier transform infrared spectra (FTIR) of precursors and their composites were acquired using on a PerkinElmer Frontier FTIR spectrophotometer. Tests about X-ray absorption near-edge spectra (XANES) were carried out at Synchrotron Light Research Institute (SLRI), Thailand. \n\n# Electrochemical measurement \n\nThe electrochemical performance of the half-cells and dual-ion battery (DIB) were carried out using CR2032 coin-type cells. The SnP2O7@N-C electrode was prepared by coating mixture slurry of the $\\mathrm{\\bfSnP_{2}O_{2}}$ 7@N-C, Ketjenblack and carboxy methyl cellulose with a weight ratio of 70:20:10. For the half cells, the electrodes were pressed and punched into circular sheets with $10\\mathrm{\\mm}$ in diameter. The KS6 graphite cathode was prepared by mixing 80 wt% KS6 graphite, $10\\ \\mathrm{wt\\%}$ conductive carbon black, and $10\\mathrm{wt\\%}$ polyvinylidene fluoride (PVDF) to form a homogeneous slurry. In order to boost the full utilization of cathode material, the cathode sheet was punched into circular sheets with 10 mm in diameter. The mass loading ratio of active anode/cathode materials for Na-DIB was ${\\sim}1{:}1$ and the corresponding size of anode sheet was 12 mm in diameter. Glass fabric was used as the separator, and $1\\mathrm{MNaClO_{4}}$ in propylene carbonate (PC) with $5\\mathrm{wt\\%}$ fluoroethylene carbonate (FEC) was used as the electrolyte for half cells. The electrolyte for the SnP2O7@N-C||KS6 DIB was 1 M NaPF6 dissolved in a mixture of ethylene carbonate (EC)/dimethyl carbonate (DMC)/ethyl methyl carbonate (EMC) (4:3:2 in volume). Cells were assembled in a glove box with water and oxygen content below 0.1 ppm and tested at room temperature. Galvanostatic charge-discharge tests and rate tests were conducted with a battery test system. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were performed on an Autolab electrochemical workstation. All chemical reagents were used as received without any further purification. The capacity is calculated based on the mass of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{-}\\mathrm{C}$ for half cells. The mass of KS6 is used to calculate the specific capacity of the DIB. More detailed materials are available in supplementary data. \n\n# SUPPLEMENTARY DATA \n\nSupplemtary data are available at NSR online. \n\n# FUNDING \n\nThis work was supported by the Key-Area Research and Development Program of Guangdong Province (2019B090914003), the National Natural Science Foundation of China (51822210, 51972329 and 11904379), the Shenzhen Science and Technology Planning Project (JCYJ20190807171803813), the China Postdoctoral Science Foundation (2018M643235), and the Natural Science Foundation of Guangdong Province (2019A1515011902). \n\n# AUTHOR CONTRIBUTIONS \n\nY.T. conceived and designed the study. S.M. and Q.L. carried out the synthesis, most of the structural characterizations and electrochemical tests. P.K. and X.Z. carried out XANES measurement. S.M., Q.L. and Y.T. co-wrote the manuscript. S.M., Q.L., P.K., X.Z., W.W. and Y.T. discussed the results and participated in analyzing the experimental results. \n\n# Conflict of interest statement. None declared. \n\n# REFERENCES \n\n1. Zhang Y, Su Q and Xu W et al. A confined replacement synthesis of bismuth nanodots in MOF derived carbon arrays as binder-free anodes for sodium-ion batteries. Adv Sci 2019; 6: 1900162. \n\n2. Li YQ, Lu YX and Meng QS et al. Regulating pore structure of hierarchical porous waste cork-derived hard carbon anode for enhanced Na storage performance. Adv Energy Mater 2019; 9: 1902852. \n\n3. Jin T, Han Q and Jiao L. Binder-free electrodes for advanced sodium-ion batteries. \nAdv Mater 2019; 32: 1806304. \n\n4. Yao Y, Chen M and Xu R et al. CNT interwoven nitrogen and oxygen dual-doped porous carbon nanosheets as free-standing electrodes for high-performance Na-Se and K-Se flexible batteries. Adv Mater 2018; 30: 1805234. \n\n5. Huang Y, Wang Z and Jiang Y et al. Hierarchical porous Co0.85Se@reduced graphene oxide ultrathin nanosheets with vacancy-enhanced kinetics as superior anodes for sodium-ion batteries. Nano Energy 2018; 53: 524-35. \n\n6. Xie D, Xia X and Zhong Y et al. Exploring advanced sandwiched arrays by vertical \n\ngraphene and N-doped carbon for enhanced sodium storage. Adv Energy Mater 2017; \n7: 1601804. \n\n7. Song TY, Yao WJ and Kidkhunthod P et al. A low-cost and environmentally friendly mixed polyanionic cathode for sodium-ion storage. Angew Chem Int Ed 2020; 59: 740-5. \n\n8. Zhao RZ, Qian Z and Liu ZY et al. Molecular-level heterostructures assembled from layered black phosphorene and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene as superior anodes for high-performance sodium ion batteries. Nano Energy 2019; 65: 104037. \n\n9. Dong SH, Li CX and Li ZQ et al. Synergistic effect of porous phosphosulfide and antimony nanospheres anchored on 3D carbon foam for enhanced long-life sodium storage performance. Energy Storage Mater 2019; 20: 446-54. \n\n10. Kraychyk KV, Bhauriyal P and Piveteau L et al. High-energy-density dual-ion battery for stationary storage of electricity using concentrated potassium fluorosulfonylimide. Nat Commun 2018; 9: 4469. \n\n11. Zhang M, Shoaib M and Fei H et al. Hierarchically porous N-doped carbon fibers as a free-standing anode for high-capacity potassium-based dual-ion battery. Adv Energy Mater 2019; 9: 1901663. \n\n12. Ji B, Yao W and Zheng Y et al. A fluoroxalate cathode material for potassium-ion batteries with ultra-long cyclability. Nat Commun 2020; 11: 1225. \n\n13. Zhao RZ, Di HX and Hui XB et al. Self-assembled $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene and N-rich porous carbon hybrids as superior anodes for high-performance potassium-ion batteries. Energy Environ Sci 2020; 13: 246-57. \n\n14. Li L, Liu LJ and Hu Z et al. Understanding high-rate $\\mathrm{K}^{+}$ -solvent co-intercalation in natural graphite for potassium-ion batteries. Angew Chem Int Ed 2020; doi: 10.1002/anie.202001966. \n\n15. Liu QN, Hu Z and Liang YR et al. Facile synthesis of hierarchical hollow CoP@C composites with superior performance for sodium and potassium storage. Angew Chem Int Ed 2020; doi: 10.1002/anie.201913683. \n\n16. Luo J, Xia Y and Zhang J et al. Enabling Mg metal anodes rechargeable in conventional electrolytes by fast ionic transport interphase. Natl Sci Rev 2020; 7: 333-41. \n\n17. Zhou LM, Liu Q and Zhang ZH et al. Interlayer-spacing-regulated VOPO4 nanosheets with fast kinetics for high-capacity and durable rechargeable magnesium batteries. Adv Mater 2018; 30: 1801984. \n\n18. Wang W, Liu L and Wang PF et al. A novel bismuth-based anode material with a stable alloying process by the space confinement of an in situ conversion reaction for a rechargeable magnesium ion battery. Chem Commun 2018; 54: 1714-7. \n\n19. Wang M, Jiang C and Zhang S et al. Reversible calcium alloying enables a practical room-temperature rechargeable calcium-ion battery with a high discharge voltage. Nat Chem 2018; 10: 667–672. \n\n20. Wu N, Yao W and Song X et al. A calcium-ion hybrid energy storage device with high capacity and long cycling life under room temperature. Adv Energy Mater 2019; 9: 1803865. \n\n21. Yang W, Dong L and Yang W et al. 3D oxygen-defective potassium vanadate/carbon nanoribbon networks as high-performance cathodes for aqueous zinc-ion batteries. Small Methods 2020; 4: 1900670. \n\n22. Wu Z-S, Bao X and Sun C et al. Scalable fabrication of printed $\\mathrm{Zn}/{\\mathrm{MnO}_{2}}$ planar micro-batteries with high volumetric energy density and exceptional safety. Natl Sci Rev 2020; 7: 64-72. \n\n23. Hao J, Long J and Li B et al. Toward high-performance hybrid Zn-based batteries via deeply understanding their mechanism and using electrolyte additive. Adv Funct Mater 2019; 29: 1903605. \n\n24. Wang H, Wang M and Tang Y. A novel zinc-ion hybrid supercapacitor for long-life and low-cost energy storage applications. Energy Storage Mater 2018; 13: 1-7. \n\n25. Li N, Li GQ and Li CJ et al. Bi-cation electrolyte for a 1.7 V aqueous Zn ion battery. ACS Appl Mater Interfaces 2020; 12: 13790-6. \n\n26. Zhang Y, Liu SQ and Ji YJ et al. Emerging nonaqueous aluminum-ion batteries: challenges, status, and perspectives. Adv Mater 2018; 30: 1706310. \n\n27. Yang HC, Li HC and Li J et al. The rechargeable aluminum battery: opportunities and challenges. Angew Chem Int Ed 2019; 58: 11978-96. \n\n28. Zhang X, Zhang G and Wang S et al. Porous CuO microsphere architectures as high-performance cathode materials for aluminum-ion batteries. J Mater Chem A 2018; 6: 3084-90. \n\n29. Niu YB, Yin YX and Guo YG. Nonaqueous sodium-ion full cells: status, strategies, and prospects. Small 2019; 15: 1900233. \n\n30. Hou HS, Qiu XQ and Wei WF et al. Carbon anode materials for advanced sodium-ion batteries. Adv Energy Mater 2017; 7: 1602898. \n\n31. Zhao C, Liu L and Qi X et al. Solid-state sodium batteries. Adv Energy Mater \n2018; 8: 1703012. \n\n32. Lim E, Jo C and Kim MS et al. High-performance sodium-ion hybrid supercapacitor based on ${\\mathrm{Nb}}_{2}{\\mathrm{O}}_{5}@\\$ carbon core–shell nanoparticles and reduced graphene oxide nanocomposites. Adv Funct Mater 2016; 26: 3711-9. \n\n33. Huang Y, Zhao L and Li L et al. Electrolytes and electrolyte/electrode interfaces in sodium-ion batteries: from scientific research to practical application. Adv Mater 2019; 31: 1808393. \n\n34. Chen M, Xiao J and Hua W et al. Strategy of cation and anion dual doping for potential elevating of titanium redox for high-power sodium-ion batteries. Angew Chem Int Ed 2020; doi: 10.1002/anie.202003275. \n\n35. Jiang C, Fang Y and Zhang W et al. A multi-ion strategy towards rechargeable sodium-ion full batteries with high working voltage and rate capability. Angew Chem Int Ed 2018; 57: 16370. \n\n36. Wang WL, Gang Y and Hu Z et al. Reversible structural evolution of sodium-rich rhombohedral Prussian blue for sodium-ion batteries. Nat Commun. 2020; 11: 980 \n\n37. Xu X, Lin K, Zhou D, et al. Quasi-solid-state dual-ion sodium metal batteries for low-cost energy storage. Chem 2020; 6: 902-18. \n\n38. Sui YM, Liu CF and Masse RC et al. Dual-ion batteries: the emerging alternative rechargeable batteries. Energy Storage Mater 2020; 25: 1-32. \n\n39. Zhou X, Liu Q and Jiang C et al. Strategies towards low-cost dual-ion batteries with high performance. Angew Chem Int Ed 2019; 59: 3802-3832. \n\n40. Kravchyk KV and Kovalenko MV. Rechargeable dual-ion batteries with graphite as a cathode: key challenges and opportunities. Adv Energy Mater 2019; 9: 1901749. \n\n41. Hao J, Li X and Song X et al. Recent progress and perspectives on dual-ion batteries. EnergyChem 2019; 1: 100004. \n\n42. Han X, Xu G and Zhang Z et al. An in situ interface reinforcement strategy achieving long cycle performance of dual-ion batteries. Adv Energy Mater 2019; 9: 1804022. \n\n43. Ji B, Zhang F and Wu N et al. A dual-carbon battery based on potassium-ion electrolyte. Adv Energy Mater 2017; 7: 1700920. \n\n44. Wu S, Zhang F and Tang Y. A novel calcium-ion battery based on dual-carbon configuration with high working voltage and long cycling life. Adv Sci 2018; 5: 1701082. \n\n45. Fan L, Liu Q and Chen S et al. Potassium-based dual ion battery with dual-graphite electrode. Small 2017; 13: 1701011. \n\n46. Zhu JJ, Li YL and Yang BJ et al. A dual carbon-based potassium dual ion battery with robust comprehensive performance. Small 2018; 14: 1801836. \n\n47. Rodríguez-Pérez IA and Ji X. Anion hosting cathodes in dual-ion batteries. ACS Energy Lett 2017; 2: 1762-70. \n\n48. Liu M, Xing L and Xu K et al. Deciphering the paradox between the co-intercalation of sodium-solvent into graphite and its irreversible capacity. Energy Storage Mater 2020; 26: 32-9. \n\n49. Xu ZL, Yoon G and Park KY et al. Tailoring sodium intercalation in graphite for high energy and power sodium ion batteries. Nat Commun 2019; 10: 2598. \n\n50. Sheng M, Zhang F and Ji B et al. A novel tin-graphite dual-ion battery based on sodium-ion electrolyte with high energy density. Adv Energy Mater 2017; 7: 1601963. \n\n51. Xie D, Zhang M and Wu Y et al. A flexible dual-ion battery based on sodium-ion quasi-solid-state electrolyte with long cycling life. Adv Funct Mater 2020; 30: 1906770. \n\n52. Zhu H, Zhang F and Li J et al. Penne-like MoS2/carbon nanocomposite as anode for sodium-ion-based dual-ion battery. Small 2018; 14: 1703951. \n\n53. Li ZY, Yang LW and Xu GB et al. Hierarchical MoS2@N-doped carbon hollow spheres with enhanced performance in sodium dual-ion batteries. ChemElectroChem 2019; 6: 661-7. \n\n54. Liu Y, Hu X and Zhong G et al. Layer-by-layer stacked nanohybrids of N,S-co-doped carbon film modified atomic MoS2 nanosheets for advanced sodium dual-ion batteries. J Mater Chem A 2019; 7: 24271-80. \n\n55. Wang X, Qi L and Wang H. Anatase $\\mathrm{TiO}_{2}$ as a ${\\mathrm{Na}}^{+}.$ -storage anode active material for dual-ion batteries. ACS Appl Mater Interfaces 2019; 11: 30453-9. \n\n56. Li C, Wang X and Li J et al. $\\mathrm{FePO_{4}}$ as an anode material to obtain high-performance sodium-based dual-ion batteries. Chem Commun 2018; 54: 4349-52. \n\n57. Zhao D, Zhao R and Dong S et al. Alkali-induced 3D crinkled porous $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene architectures coupled with NiCoP bimetallic phosphide nanoparticles as anodes for high-performance sodium-ion batteries. Energy Environ Sci 2019; 12: 2422-32. \n\n58. Li W, Yao Z and Zhong Y et al. Enhancement of the advanced Na storage performance of $\\mathrm{Na}_{3}\\mathrm{V}_{2}(\\mathrm{PO}_{4})_{3}$ in a symmetric sodium full cell via a dual strategy design. J Mater Chem A 2019; 7: 10231-8. \n\n59. Ge P, Li S and Xu L et al. Hierarchical hollow-microsphere metal– selenide@carbon composites with rational surface engineering for advanced sodium storage. Adv Energy Mater 2019; 9: 1803035. \n\n60. Zhang SW, Lv W and Qiu D et al. An ion-conducting $\\mathrm{SnS-SnS}_{2}$ hybrid coating for commercial activated carbons enabling their use as high performance anodes for sodium-ion batteries. J Mater Chem A 2019; 7: 10761-8. \n\n61. Wang MY, Wang XL and Yao ZJ et al. $\\mathrm{SnO}_{2}^{\\prime}$ nanoflake arrays coated with polypyrrole on a carbon cloth as flexible anodes for sodium-ion batteries. ACS Appl Mater Interfaces 2019; 11: 24198-204. \n\n62. Wang Y, Zhang Y and Shi J et al. Tin sulfide nanoparticles embedded in sulfur and nitrogen dual-doped mesoporous carbon fibers as high-performance anodes with battery-capacitive sodium storage. Energy Storage Mater 2019; 18: 366-74. \n\n63. Zhao J, Wang G and Hu R et al. Ultrasmall-sized SnS nanosheets vertically aligned on carbon microtubes for sodium-ion capacitors with high energy density. $J$ Mater Chem A 2019; 7: 4047-54. \n\n64. Xia J, Liu L and Jamil S et al. Free-standing $\\mathrm{\\SnS/C}$ nanofiber anodes for ultralong cycle-life lithium-ion batteries and sodium-ion batteries. Energy Storage Mater 2019; \n\n17: 1-11. \n\n65. Li ZQ, Ge XL and Li CX et al. Rational microstructure design on metal–organic framework composites for better electrochemical performances: design principle, synthetic strategy, and promotion mechanism. Small Methods 2020; 4: 1900756. \n\n66. Pan J, Chen S and Zhang D et al. $\\mathrm{SnP}_{2}\\mathrm{O}_{7}$ covered carbon nanosheets as a long-life and high-rate anode material for sodium-ion batteries. Adv Funct Mater 2018; 28: 1804672. \n\n67. Wang ZZ, Lv P and Hu Y et al. Thermal degradation study of intumescent flame retardants by TG and FTIR: melamine phosphate and its mixture with pentaerythritol. J Anal Appl Pyrolysis 2009; 86: 207-14. \n\n68. Li Q, Li Z and Zhang Z et al. Low-temperature solution-based phosphorization reaction route to $\\mathrm{Sn}_{4}\\mathrm{P}_{3} $ /reduced graphene oxide nanohybrids as anodes for sodium ion batteries. Adv Energy Mater 2016; 6: 1600376. \n\n69. Sha M, Zhang H and Nie YT et al. Sn nanoparticles@nitrogen-doped carbon nanofiber composites as high-performance anodes for sodium-ion batteries. J Mater Chem A 2017; 5: 6277-83. \n\n70. Yang X, Zhang R-Y and Zhao J et al. Amorphous tin-based composite oxide: a high-rate and ultralong-life sodium-ion-storage material. Adv Energy Mater 2018; 8: 1701827. \n\n71. Liu Y, Zhang N and Jiao L et al. Tin nanodots encapsulated in porous nitrogen-doped carbon nanofibers as a free-standing anode for advanced sodium-ion batteries. Adv Mater 2015; 27: 6702-7. \n\n72. Guo WY, Ding K and Mei SX et al. Hollow spheres consisting of SnS nanosheets conformally coated with S-doped carbon for advanced lithium-/sodium-ion battery anodes. ChemElectroChem 2020; 7: 914–21. \n\n73. Liu Z, Handa K and Kaibuchi K et al. Comparison of the Sn L edge X-ray absorption spectra and the corresponding electronic structure in Sn, SnO, and $\\mathrm{SnO}_{2}$ . J Electron Spectrosc 2004; 135: 155-8. \n\n74. Pelliccione CJ, Timofeeva EV and Segre CU. Potential-resolved in situ X-ray absorption spectroscopy study of Sn and $\\mathrm{SnO}_{2}$ nanomaterial anodes for lithium-ion batteries. J Phys Chem $C$ 2016; 120: 5331-9. \n\n75. Dong S, Li Z and Rodríguez-Pérez IA et al. A novel coronene//Na2Ti3O7 dual-ion battery. Nano Energy 2017; 40: 233-9. \n\n76. Li BQ, Liu Y and Jin X et al. Designed formation of hybrid nanobox composed of carbon sheathed $\\mathrm{CoSe}_{2}$ anchored on nitrogen-doped carbon skeleton as ultrastable anode for sodium-ion batteries. Small 2019; 15: 1902881. \n\n77. Bai YL, Xarapatgvl R and Wu XY et al. Core-shell anatase anode materials for sodium-ion batteries: the impact of oxygen vacancies and nitrogen-doped carbon coating. Nanoscale 2019; 11: 17860-8. \n\n78. Ying HJ, Zhang SL and Meng Z et al. Ultrasmall Sn nanodots embedded inside N-doped carbon microcages as high-performance lithium and sodium ion battery anodes. J Mater Chem A 2017; 5: 8334-42. \n\n79. Li N, Zhang F and Tang YB. Hierarchical $\\mathrm{T}{\\cdot}\\mathrm{Nb}_{2}\\mathrm{O}_{5}$ nanostructure with hybrid mechanisms of intercalation and pseudocapacitance for potassium storage and high-performance potassium dual-ion batteries. J Mater Chem A 2018; 6: 17889-95. \n\n80. Hu Z, Liu Q and Zhang K et al. All carbon dual ion batteries. ACS Appl Mater Interfaces 2018; 10: 35978-83. \n\n81. Yao X, Ke Y and Ren W et al. Defect-rich soft carbon porous nanosheets for fast and high-capacity sodium-ion storage. Adv Energy Mater 2018; 9: 1803260. \n\n82. Ma R, Fan L and Chen S et al. Offset initial sodium loss to improve coulombic efficiency and stability of sodium dual-ion batteries. ACS Appl Mater Interfaces 2018; 10: 15751-9. \n\n83. Wang X, Zheng C and Qi L et al. Carbon derived from pine needles as a $\\mathrm{{Na}^{+}}$ -storage electrode material in dual-ion batteries. Global Challenges 2017; 1: 1700055. \n\n84. Fan L, Liu Q and Chen S et al. Soft carbon as anode for high-performance sodium-based dual ion full battery. Adv Energy Mater 2017; 7: 1602778. \n\n85. Aubrey ML and Long JR. A dual-ion battery cathode via oxidative insertion of anions in a metal-organic framework. J Am Chem Soc 2015; 137: 13594-602. \n\n86. Fan J, Fang Y and Xiao Q et al. A dual-ion battery with a ferric ferricyanide anode enabling reversible Na intercalation. Energy Technol 2019; 7: 1800978. \n\n![](images/95c6888f4d648a39dfb8faad1966a156616763d9dc66045849ccc843acb79d96.jpg) \n\n![](images/011f0e84bc342c19e2cd7019bf3c8467a117ed557aea0ca249753beb273def78.jpg) \nFigure 1. Schematic synthesis process of the SnP2O7@N-C composite. \n\n![](images/f61f7866ef014630da8c26199dcfe779f59e833c71129bcf7fff090d79ef6f8d.jpg) \nFigure 2. Morphology, microstructure, and chemical components of as-synthesized \n\n$\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ . (a) SEM image, (b-c) HRTEM images, (d) XRD pattern, (e) Raman spectrum and (f) TGA analysis of as-synthesized $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}.\\mathrm{C}$ . High-resolution XPS spectra of Sn 3d (g), P 2p (h) and N 1s (i). \n\n![](images/8c2f18fe4db97bdf42ffbeff7f1279457e9bac2d5122abf4ef5a7a1eef63ba92.jpg) \n\nFigure 3. Studies on the working mechanism of SnP2O7@N-C in the sodium-based half-cell. (a) First three CV curves at a sweep rate of $\\mathrm{\\overline{{0.1}}~m V~s^{-1}}$ . (b-c) Sn $\\mathrm{L}_{3}$ -edge XANES spectra of the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ anode during discharging (b) and charging (c) processes. (d-g) HRTEM images of $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N-C}$ anode at different discharging states of (d) $0.55\\mathrm{~V~}$ and (e) 0.01 V, and different charging states of (f) $1.2\\mathrm{V}$ and (g) \n\n3.0 V. Scale bars: 5 nm. \n\n![](images/387108b81b5d132058c0f1f85e5259ca067d6bf31d8fab21a221c77426620355.jpg) \nFigure 4. Electrochemical performances of the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}.\\mathrm{C}$ anode in sodium-based \n\nhalf-cells. (a) Galvanostatic charge-discharge profiles and (b) the corresponding cycling performance at a current density of 0.1 A $\\mathbf{g}^{-1}$ . (c) Nyquist plots of the SnP2O7@N-C anode before and after 100 cycles. (d) Galvanostatic charge-discharge profiles measured at different current densities and (e) the corresponding rate capability. (f) Long-term cycling stability at $1.5\\mathrm{Ag}^{-1}$ . \n\n![](images/13ab62ab0d114ad72ab812c47fac4fdde5f9574a45a2107956f532234bfe588a.jpg) \nFigure 5. (a) Schematic illustration of the proof-of-concept Na-DIB configuration \n\nassembled with the $\\mathrm{SnP}_{2}\\mathrm{O}_{7}@\\mathrm{N}{\\mathrm{-C}}$ anode and KS6 graphite cathode. (b) Galvanostatic charge–discharge profile of the Na-DIB in the voltage range of 1.0–4.0 V at 3 C, corresponding dQ/dV differential curves (c), and in-situ XRD contour during charging/discharging process (d). \n\n![](images/55def7aa56255381c5ad32659aa58a0698f6f5ebd915f62c2f6b5c8b996d5066.jpg) \nFigure 6. Electrochemical energy-storage performances of the proof-of-concept \n\nNa-DIB. (a) Rate capability and (b) corresponding galvanostatic charge–discharge profiles at different current densities. Charge–discharge profiles at a constant charging current density of $30~\\overline{{\\mathrm{C}}}$ and different discharging rates (c) and the corresponding fast-charge/slow-discharge performance (d). (e) Long-term cycling stability and (f) the corresponding galvanostatic charge–discharge profiles at different cycles. " + }, + { + "id": "10.1038_s41467-021-23390-8", + "DOI": "10.1038/s41467-021-23390-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-23390-8", + "Relative Dir Path": "mds/10.1038_s41467-021-23390-8", + "Article Title": "Modifying redox properties and local bonding of Co3O4 by CeO2 enhances oxygen evolution catalysis in acid", + "Authors": "Huang, JZ; Sheng, HY; Ross, RD; Han, JC; Wang, XJ; Song, B; Jin, S", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Developing efficient and stable earth-abundant electrocatalysts for acidic oxygen evolution reaction is the bottleneck for water splitting using proton exchange membrane electrolyzers. Here, we show that nullocrystalline CeO2 in a Co3O4/CeO2 nullocomposite can modify the redox properties of Co3O4 and enhances its intrinsic oxygen evolution reaction activity, and combine electrochemical and structural characterizations including kinetic isotope effect, pH- and temperature-dependence, in situ Raman and ex situ X-ray absorption spectroscopy analyses to understand the origin. The local bonding environment of Co3O4 can be modified after the introduction of nullocrystalline CeO2, which allows the Co-III species to be easily oxidized into catalytically active Co-IV species, bypassing the potential-determining surface reconstruction process. Co3O4/CeO2 displays a comparable stability to Co3O4 thus breaks the activity/stability tradeoff. This work not only establishes an efficient earth-abundant catalysts for acidic oxygen evolution reaction, but also provides strategies for designing more active catalysts for other reactions. Developing efficient and stable earth-abundant electrocatalysts for acidic oxygen evolution reaction is challenging. Here, the authors modify the local bonding environment of Co3O4 by CeO2 nullocrystallites to regulate the redox properties, thus enhance the catalytic activity.", + "Times Cited, WoS Core": 457, + "Times Cited, All Databases": 466, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000658769300005", + "Markdown": "# Modifying redox properties and local bonding of Co3O4 by ${\\mathsf{C e O}}_{2}$ enhances oxygen evolution catalysis in acid \n\nJinzhen Huang1,2, Hongyuan Sheng 1, R. Dominic Ross1, Jiecai Han2, Xianjie Wang3, Bo Song2✉ & Song Jin 1✉ \n\nDeveloping efficient and stable earth-abundant electrocatalysts for acidic oxygen evolution reaction is the bottleneck for water splitting using proton exchange membrane electrolyzers. Here, we show that nanocrystalline ${\\mathsf{C e O}}_{2}$ in a $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ nanocomposite can modify the redox properties of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ and enhances its intrinsic oxygen evolution reaction activity, and combine electrochemical and structural characterizations including kinetic isotope effect, pHand temperature-dependence, in situ Raman and ex situ $\\mathsf{X}$ -ray absorption spectroscopy analyses to understand the origin. The local bonding environment of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ can be modified after the introduction of nanocrystalline ${\\mathsf{C e O}}_{2},$ which allows the ${\\mathsf{C o}}^{\\parallel\\parallel}$ species to be easily oxidized into catalytically active ${\\mathsf{C o}}^{\\mathsf{N}}$ species, bypassing the potential-determining surface reconstruction process. $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ displays a comparable stability to $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ thus breaks the activity/stability tradeoff. This work not only establishes an efficient earth-abundant catalysts for acidic oxygen evolution reaction, but also provides strategies for designing more active catalysts for other reactions. \n\nTehnfefeufctarts ddefeumpealsen iduosnsinuosgfarfieonsasebilwlefubsletelr etalengcidtersincitctory a.p iEonldgeucgtcreo canatrhabloyoutnsiecwater splitting has been considered a promising approach to generate hydrogen as a clean and renewable energy carrier2. Proton exchange membrane (PEM) electrolyzers operated in acidic media have shown great promises for large-scale applications3–5. Despite substantial recent advances in the discovery of robust and active earth-abundant electrocatalysts for acidic hydrogen evolution reaction $(\\mathrm{HER})^{1,6-8}$ , the development of high-performance yet cost-effective electrocatalysts for the sluggish four-electron oxygen evolution reaction (OER) is challenging9–11 especially in acidic media, which contributes to a major energy loss in the overall water splitting process and is a bottleneck for realizing practical PEM electrolyzers3,12. Most OER catalysts show inferior activities in acidic media compared to in alkaline media and require higher overpotentials to achieve comparable catalytic current densities. Moreover, the stability issues are more severe in acidic OER, and even noble metal-based catalysts (such as $\\mathrm{RuO}_{2}$ and ${\\mathrm{IrO}}_{2}^{\\cdot}$ ) experience dissolution and degradation13,14. Furthermore, the often observed tradeoff between activity and stability in acidic OER catalysts13–16 complicates the catalyst design. As a result, there have been very limited choices of earth-abundant OER catalysts that are both active and stable in acidic media17–20. Cobalt $\\scriptstyle(\\mathbf{Co})$ -based catalysts such as $\\mathrm{Ba}[\\mathrm{Co-POM}]^{17}$ , hetero-N-coordinated Co single atom catalyst21, $\\mathrm{CoFePbO}_{x}{}^{18}$ , $\\mathrm{Co}_{2}\\mathrm{TiO}_{4}{}^{22}$ , and $\\mathrm{Co}_{3}\\mathrm{O}_{4}{}^{23-25}$ are promising for acidic OER; however, the mechanistic details have rarely been studied for these emerging OER catalysts in acidic media. \n\nThe active site structures and catalytic mechanisms of cobalt oxide OER catalysts have been primarily investigated in alkaline and neutral media26–31, little is known about these catalysts in acidic media. The exact configuration of the active sites responsible for the O-O bond formation still remains debatable, but the generation of high-valence-state ${\\mathrm{Co}}^{\\mathrm{IV}}$ is accepted to be involved in the pre-OER redox processes of different types of cobalt oxide OER catalysts since they share the common active sites26,31,32. The further oxidation of the neighboring Co redox centers to form dimeric $\\mathrm{Co^{IV}C o^{I V}}$ takes place at high potentials33,34, and thus causes a large energy loss to bypass this potentialdetermining process for the catalytic $\\mathrm{OER}^{\\dot{3}\\hat{1}}$ . Besides, these prominent pre-OER redox features also suggest that the $\\mathrm{Co^{IV}\\dot{C}o^{I V}}$ intermediates are stabilized and could suffer from a slow catalytic turnover process for $\\mathrm{OER}^{35,36}$ . Therefore, a better understanding of the relationships between redox properties and catalytic activity is the key to design more efficient (Co-based) OER catalysts and to enhance catalytic activity by regulating redox properties, which remains elusive and largely underexplored especially in acidic media. \n\nIn this work, we enhance the intrinsic catalytic activity of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ by introducing nanocrystalline $\\mathrm{CeO}_{2}$ to form a heterogeneous $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ nanocomposite and establish $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ nanocomposite as an active acidic OER catalyst. $\\mathrm{CeO}_{2}$ has been well documented as (co-)catalyst in thermal catalysis due to its excellent redox properties and oxygen storage capacity37. Although $\\mathrm{CeO}_{2}$ has been introduced into a number of electrocatalyst systems to enhance the overall performance for various electrocatalytic reactions38 including the alkaline $\\mathrm{OER}^{39-41}$ , how it impacts the catalytic activity remains controversial and its contribution to the redox properties of the electrocatalysts has not yet been discussed. Now we show that the introduction of $\\mathrm{CeO}_{2}$ (meaning phase-pure $\\mathrm{CeO}_{2}$ nanocrystallites are interdispersed among phase-pure $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ crystallites in the two-component nanocomposite without phase mixing) substantially suppresses the pre-OER redox features of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ in acidic media, indicating the destabilization of the dimeric $\\mathrm{Co^{IV}C o^{I V}}$ intermediate. \n\nIn-depth electrochemical characterizations combined with rigorous structural characterizations, including kinetic isotope effect (KIE), pH- and temperature-dependence studies, in situ Raman, and ex situ X-ray absorption spectroscopy (XAS) analyses, reveal that the catalytic enhancement in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ is due to the altered electronic structures and local bonding environment in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ . Chronopotentiometry test together with inductively coupled plasma mass spectrometry (ICP-MS) analysis shows that the more active $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ exhibits a comparable acidic OER stability to $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and a better open circuit stability, thus breaks the activity/stability tradeoff. \n\nResults and discussion \nSynthesis and structural characterization of $\\mathbf{Co_{3}O_{4}}/\\mathbf{CeO_{2}}$ nanocomposites. $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanostructures and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ nanocomposites were synthesized directly on fluorine-doped tin oxide (FTO) electrodes by electrodeposition of the corresponding metal hydroxide precursors (Supplementary Fig. 1) followed by annealing in air (see Methods for details). The prototypical ${\\mathrm{Co}}(\\mathrm{OH})_{2}$ precursor displayed the morphology of interconnected nanosheets, while the introduction of Ce precursor led to more aggregations and wrinkles (Supplementary Fig. 2). After annealing in air at $400^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ , the resultant $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ samples preserved the nanosheet morphology (Supplementary Fig. 3). High-resolution transmission electron microscopy (HRTEM) further revealed the nanocrystalline domains in both $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (Fig. 1a, c and Supplementary Fig. 4a, b) and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ (Fig. 1b, d and Supplementary Fig. 4c, d) samples. Because the spinel oxide $\\mathrm{Co}_{3}\\mathrm{O}_{4}^{\\overline{{}}}$ and cubic $\\mathrm{CeO}_{2}$ structures (Supplementary Fig. 9a) cannot form mixed solutions, phase segregation is expected42, which is further proved by the powder $\\mathrm{\\DeltaX}$ -ray diffraction (PXRD) pattern of $\\mathrm{Co}_{3}\\mathrm{O}_{4}/\\mathrm{CeO}_{2}$ (Fig. 1e). Selected area electron diffraction patterns of both samples displayed similar diffraction rings due to the polycrystalline nature (insets of Fig. 1a, b). The inner to outer diffraction rings can be indexed to the (111), (220), (311), (400), (511), (440) planes of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (JCPDS 43-1003), consistent with the PXRD patterns (Fig. 1e) and the spinel oxide crystal structure of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (Fig. $\\mathrm{1f)^{43}}$ . The introduction of $\\mathrm{CeO}_{2}$ decreased the crystallinity of $\\mathrm{Co}_{3}\\mathrm{O}_{4}.$ as the average crystalline domain sizes of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ estimated from the widths of the (311) diffraction peaks using the Scherrer equation were 13.9 and $9.7\\mathrm{nm}$ , respectively (Supplementary Fig. 5). From the HRTEM images (Fig. 1c, d), the lattice spacings of 0.243 and $0.467\\mathrm{nm}$ were assigned to the (311) and (111) planes of $\\mathrm{Co}_{3}\\mathrm{O}_{4},$ respectively, and that of $0.312\\mathrm{nm}$ was attributed to the (111) plane of $\\mathrm{CeO}_{2}$ . Nanoscale crystallites of $\\mathrm{CeO}_{2}$ exhibit an average domain size of ${\\sim}5\\mathrm{nm}$ based on the Scherrer analysis of the PXRD peak (Supplementary Fig. 6) and are evenly dispersed among phase-pure $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ crystallites with numerous interfacial contact regions. Elemental mappings further confirmed the successful introduction of $\\mathrm{Ce}$ in $\\mathrm{\\bar{C}o_{3}\\mathrm{\\bar{O}_{4}/C e O_{2}}}$ (Fig. 1g). The bulk and surface Ce metal contents in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ [defined as $\\mathrm{Ce}/(\\mathrm{Ce}+\\mathrm{Co})\\times100\\%]$ were determined as 9.1 and 6.6 atomic percent $(\\mathrm{at\\%})$ using energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) and $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS), respectively (Supplementary Table 1). \n\nElectrocatalytic properties of $\\mathbf{Co_{3}O_{4}}/\\mathbf{CeO_{2}}$ nanocomposites. The substantial differences in the redox properties and acidic OER catalytic performances between the $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalysts on FTO electrodes are shown by cyclic voltammetry (CV) recorded in 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution (Fig. 2a). Three sets of pre-OER redox features are observed in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (the corresponding cathodic peaks are denoted as C1, C2, and C3 in the order of increasing potential, see Fig. 2b), which can be ascribed to the following equilibria involving dimeric Co redox centers26,31,33: $\\mathrm{Co}^{\\mathrm{H}}\\mathrm{Co}^{\\mathrm{I}\\mathrm{II}}\\leftrightarrow\\mathrm{Co}^{\\mathrm{III}}\\mathrm{Co}^{\\mathrm{III}}\\leftrightarrow\\mathrm{Co}^{\\mathrm{IV}}\\mathrm{Co}^{\\mathrm{III}}\\leftrightarrow\\mathrm{Co}^{\\mathrm{IV}}\\mathrm{Co}^{\\mathrm{IV}}$ (see proposed detailed structural motifs in Supplementary Fig. 7). In contrast, $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ displayed no obvious pre-OER redox features and a much lower onset potential for acidic OER (Fig. 2a and Supplementary Fig. 8b), suggesting the redox properties of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ can be effectively regulated by the introduction of $\\mathrm{CeO}_{2}$ . Note that $\\mathrm{CeO}_{2}$ itself shows no redox feature and very poor activity toward OER in acid (Supplementary Fig. 9). The $\\mathrm{Co}_{3}\\mathrm{O}_{4}/\\$ $\\mathrm{CeO}_{2}$ catalyst prepared by introducing a nominal $10\\mathrm{at\\%}$ Ce metal content during the electrodeposition process exhibited the highest acidic OER catalytic performance (Supplementary Fig. 10) and was therefore studied in the rest of this work. The overpotentials required for $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ $(10\\ \\mathrm{at\\%}\\ \\mathrm{Ce})$ to reach a geometric catalytic current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ on FTO electrodes were $507\\pm5$ and $423\\pm8\\mathrm{mV}$ , respectively, showing a substantial improvement of ${\\sim}84\\mathrm{mV}$ after the introduction of $\\mathrm{CeO}_{2}$ (Fig. 2a inset). The Tafel slopes of the acidic OER on $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ were 110.8 and $88.1\\mathrm{mV~dec^{-1}}$ , respectively (Fig. 2c). Both are in the range of $60-120\\mathrm{mV~dec^{-1}}$ , indicating a mixed kinetic control mechanism44. A second linear Tafel region was observed in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (in the overpotential range of $350{-}425\\mathrm{mV}$ shaded in pink), which originates from the chargeaccumulation process due to the oxidation of dimeric ${\\mathrm{Co}}^{\\mathrm{IV}}{\\mathrm{Co}}^{\\mathrm{{\\smile}I I I}}$ to ${\\mathrm{Co}}^{\\mathrm{IV}}{\\mathrm{Co}}^{\\mathrm{IV}}$ . In contrast, $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ only exhibits a single linear Tafel region with a smaller slope of $88.1\\mathrm{mV~dec^{-1}}$ , which suggests that the OER catalytic onset takes place at a much lower overpotential of ${\\sim}300\\mathrm{mV}$ without noticeable charge accumulation of dimeric Co redox centers. \n\n![](images/3b4b91db183ea94ddc7ea117f85b524f856a32bf96dc1c4c20cf4624d6e2d5ad.jpg) \nFig. 1 Structural characterizations of $\\cos_{4}$ nanostructures and $\\mathsf{c o}_{3}\\mathsf{o}_{4}/\\mathsf{c e o}_{2}$ nanocomposites. TEM images of a $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ and b $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ nanosheets, the insets show the corresponding SAED patterns. HRTEM images of c $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ and d $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ samples. The ${\\mathsf{C e O}}_{2}$ domain is highlighted with a yellow dashed circle. e PXRD patterns of the samples on FTO substrates in comparison with the standard PXRD patterns of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ (JCPDS 43-1003) and ${\\mathsf{C e O}}_{2}$ (JCPDS 43-1002). f Crystal structures of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ and ${\\mathsf{C e O}}_{2}$ . g Dark-field TEM image and the corresponding elemental mappings of Co, Ce, and O in the $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ sample. \n\nThe intrinsic acidic OER catalytic activities of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalysts on FTO electrodes were further extracted based on double-layer capacitance $(C_{\\mathrm{dl}})$ measurements and electrochemically active surface area (ECSA) normalization. The $C_{\\mathrm{dl}}$ values of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ $(7.31\\mathrm{mF}\\mathrm{cm}^{-2},$ ) and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ $23.26\\mathrm{mF}$ $\\mathrm{cm}^{-2}$ ) (Supplementary Fig. 11) showed that the introduction of ${\\mathrm{CeO}}_{2}$ substantially increased the ECSA. Nevertheless, after normalizing the geometric catalytic current density by the ECSA derived from $C_{\\mathrm{dl}}$ (see Methods for details)45, $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ still displayed a much lower OER catalytic onset potential than $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and a much higher ECSA-normalized catalytic current density of $23.7\\upmu\\mathrm{A}\\mathrm{cm}^{-2}$ at the overpotential of $450\\mathrm{mV}$ , which doubled that of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ at the same overpotential (Fig. 2d). These results confirm that $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ features enhanced intrinsic OER catalytic activity compared to $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ in acidic media. \n\nWe further examined the electron transfer kinetics of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalysts on FTO electrodes using electrochemical impedance spectroscopy (EIS) at different potentials and extracted the charge transfer resistance $(R_{\\mathrm{ct}})$ of the catalytic OER from EIS fitting using the Voigt circuit model (Supplementary Fig. 12 and Supplementary Table 2)46. At the potentials between 1.566 and $1.616\\mathrm{V}$ vs. reversible hydrogen electrode (RHE), the charge accumulation process due to the oxidation of dimeric Co redox centers dominated on the $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ catalyst, whereas the catalytic OER already took place on the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalyst. As a result, the $R_{\\mathrm{{ct}}}$ values of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ were one order of magnitude higher than those of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ (Supplementary Table 2). Once OER dominated on $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ after the oxidation of dimeric $\\mathrm{Co^{IV}C o^{I I I}}$ to $\\mathrm{Co^{IV}C o^{I V}}$ at the higher potential of $1.716\\mathrm{V}$ vs. RHE, its $R_{\\mathrm{{ct}}}$ substantially decreased to be on the same order of magnitude as that of $\\mathrm{\\dot{C}o_{3}O_{4}/C e O_{2}}$ (Supplementary Table 2). These EIS results suggest that the catalytic OER on $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ takes place efficiently only after overcoming the sluggish kinetic step associated with the charge accumulation process to form dimeric $\\mathrm{Co^{IV}C o^{I V}}$ , and the introduction of ${\\mathrm{CeO}}_{2}$ effectively regulates the redox properties of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and substantially enhances the electron transfer kinetics of the catalytic OER at a much lower overpotential. \n\nWe further verified that the enhanced catalytic activity of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ could not be attributed to the decreased crystallinity of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ due to the introduction of ${\\mathrm{CeO}}_{2}$ (see earlier discussions of Fig. 1e and Supplementary Fig. 5). By varying the annealing temperature, a series of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ samples with different degrees of crystallinity were prepared (Supplementary Fig. 13). The pre-OER redox features were consistently present in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and absent in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ regardless of different annealing temperatures, suggesting the redox properties of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ are unaffected by the degree of crystallinity (Supplementary Fig. 14a). Moreover, in contrast to $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ that appeared to be more active when less crystalline, the OER activity of $\\mathrm{Co}_{3}\\mathrm{O}_{4}/$ $\\mathrm{CeO}_{2}$ remained nearly constant regardless of the different sample crystallinity (Supplementary Fig. 14c, d), indicating the catalytic activity enhancement in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ originates from the regulated redox properties rather than sample crystallinity. \n\n![](images/36a7874d26cbc9cd1712a230a57de922b5cccd23aad99acf5491364d85b1f408.jpg) \nFig. 2 Electrochemical characterizations of $\\scriptstyle\\mathbf{Co_{3}O_{4}}$ and $\\mathsf{c o}_{3}\\mathsf{o}_{4}/\\mathsf{c e o}_{2}$ (prepared with 10 at% Ce) catalysts on FTO electrodes in 0.5 M ${\\bf H}_{2}\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\large=\\thinspace\\qquad\\large=\\frac{\\Omega}{4}$ solution. a $i R$ -corrected CV curves of both catalysts, the inset shows the overpotential (with error bar) required for each catalyst to reach a geometric catalytic current density of $10\\mathsf{m A c m}^{-2}$ based on the averages of three individual electrodes. b Magnified CV curve of the $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ catalyst that highlights the three pre-OER redox features and the corresponding C1, C2, and C3 cathodic peaks. c The corresponding Tafel plots of both catalysts. d ECSA-normalized CV curves of both catalysts, the inset shows the ECSA-normalized catalytic current density (JECSA-normalized) of each catalyst at the overpotential of $450\\mathsf{m V}$ . \n\nTo shed light on the pre-OER redox mechanisms of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and understand their relationships to the catalytic activity, we conducted $\\mathrm{\\tt{pH}}$ -dependence analysis of the C3 peak on the $\\dot{\\mathrm{Co}}_{3}\\mathrm{O}_{4}$ catalyst in ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution in the $\\mathrm{\\pH}$ range of 0.48–1.24 (Fig. 3a and Supplementary Fig. 15a). The peak potential vs. standard hydrogen electrode was plotted against the solution $\\mathrm{\\ttpH}$ (Fig. 3a inset). The slope of $95.9\\pm4.8\\:\\mathrm{mV}$ per $\\mathrm{\\ttpH}$ unit suggests a $2\\mathrm{e}^{-}/3$ $\\mathrm{H^{+}}$ coupled redox process47, which is different from the 59 or $120\\mathrm{mV}$ per $\\mathrm{\\DeltapH}$ unit expected for a $1~\\mathrm{e}^{-}/1~\\mathrm{H}^{+}$ or $1~\\mathrm{e}^{-}/2~\\mathrm{H}^{+}$ process, respectively48. In addition, CV curves of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ recorded at different scan rates in $0.5{\\mathrm{M}}{}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution (Fig. 3b and Supplementary Fig. 16) reveal the first-order power law relationship between the three cathodic peak current densities and the scan rate (Fig. 3b inset), suggesting that the C3 peak is associated with a surface capacitive process49,50. Thus, this crucial third redox feature of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ corresponds to a $2~\\mathrm{e}^{-}/3~\\mathrm{H}^{+}$ surface capacitive process of $\\mathrm{Co^{IV}C o^{I I I}\\leftrightarrow^{\\bullet}\\Gamma^{I V}C o^{I V}}$ , consistent with the proposed structural motifs in Supplementary Fig. 7. Moreover, this prominent $2\\mathrm{e}^{-}/3\\mathrm{H}^{+}$ redox feature of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ also indicates that the dimeric $\\mathrm{Co^{IV}C o^{I V}}$ intermediate is partially stabilized and therefore cannot undergo a rapid catalytic turnover process to produce $\\mathrm{O}_{2}$ and return to the lower valence resting states34,51, thus resulting in an increased overpotential to drive the catalytic reaction35,36. In contrast, the absence of this pre-OER redox feature in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ suggests that the introduction of $\\mathrm{CeO}_{2}$ effectively destabilizes the dimeric $\\mathrm{Co^{IV}C o^{I V}}$ intermediate and accelerates the catalytic turnover process, which leads to the enhanced acidic OER activity of the nanocomposite catalyst. \n\nSince the oxygen source for acidic OER is $_\\mathrm{H}_{2}\\mathrm{O}$ , the cleavage of HO-H bond and the proton transfer properties are important factors that could affect the catalytic activity, similar to the case of alkaline $\\mathrm{HER}^{52}$ . Therefore, we collected the CV curves of both $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalysts on FTO electrodes in the protonic (0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ in $\\mathrm{H}_{2}\\mathrm{O}\\dot{}$ ) vs. deuteric (0.5 M $\\mathrm{D}_{2}\\mathrm{SO}_{4}$ in $\\mathrm{D}_{2}\\mathrm{O})$ solution to investigate the KIE of acidic OER (Fig. 3c and Supplementary Fig. 17). Substituting proton with deuterium affects both the thermodynamics and the kinetics of reactions involving protons34. The shift of $33\\mathrm{mV}$ in the standard equilibrium potential of the OER when proton is exchanged with deuterium $[1.229\\mathrm{V}$ vs. RHE for $\\mathrm{O}_{2}/\\mathrm{H}_{2}\\mathrm{O}$ as opposed to $1.262\\mathrm{V}$ vs. reversible deuterium electrode (RDE) for $\\bar{\\mathrm{O}_{2}}/\\mathrm{D}_{2}\\mathrm{O}]$ is attributed to the change in the reaction thermodynamics (Fig. 3c)34,53. To separate the KIE from the reaction thermodynamics, linear sweep voltammetry curves were presented on the overpotential scale, and the KIE value was calculated based on the catalytic current density in the protonic vs. deuteric solution at the same overpotential (Fig. 3d, also see Methods for details). For both catalysts, the KIE values in OER potential regions fluctuated around the upper limit of secondary KIE $(\\sim1.5)$ with the absence of primary KIE, indicating that proton transfer is not rate-limiting for the acidic OER on both catalysts34,53. In addition, the pH-dependence analysis of the catalytic current densities at fixed overpotentials showed that the reaction order with respect to $\\mathrm{\\pH}$ is close to zero on the RHE scale for acidic OER on both catalysts (Supplementary Fig. 15), indicating the catalytic reaction is less dependent on the proton concentration in the electrolyte for both catalysts. These results suggest that the enhanced acidic OER activity of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ is unrelated to the proton transfer properties of the nanocomposite. \n\nWe further conducted temperature-dependent kinetic analysis of both $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalysts to extract the apparent activation energy $(E_{\\mathrm{app}})$ and pre-exponential factor $(A_{\\mathrm{app}})$ of the acidic OER and to examine how the introduction of $\\mathrm{CeO}_{2}$ affects the catalytic mechanism. CV curves of both catalysts on FTO electrodes were recorded in $0.5{\\bf M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution in the temperature range of $25\\mathrm{-}65^{\\circ}\\mathrm{C}$ (Supplementary Fig. 18). As expected, the catalytic performances of both catalysts increased at elevated temperatures (Fig. 3e and Supplementary Fig. 18). The $E_{\\mathrm{app}}$ values of both catalysts at fixed overpotentials were calculated from the Arrhenius equation (Fig. 3f and \n\n![](images/61a3bfd5b28974b56a04cc08f1b8de116821ee83aa81a39af1fb904fdf313e06.jpg) \nFig. 3 The pH-dependence, kinetic isotope effect (KIE) and apparent activation energy $(E_{\\mathrm{app}})$ analyses of the acidic OER on $\\cos O_{4}$ and $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{c e o}_{2}$ catalysts on FTO electrodes. a CV curves of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ recorded in ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solutions with different pH values, the inset shows the C3 peak potential vs. SHE plotted against the solution pH. b CV curves of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ recorded at different scan rates in $0.5{\\ensuremath{\\mathsf{M}}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solution, the inset shows the logarithm of cathodic peak current density $(j_{\\mathrm{c}})$ plotted against the logarithm of scan rate $(\\nu)$ . c CV curves of both catalysts recorded in 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ in $H_{2}O$ solution on the RHE scale (solid) vs. in $0.5{\\ensuremath{\\mathsf{M}}}$ ${\\sf D}_{2}{\\sf S}{\\sf O}_{4}$ in $\\mathsf{D}_{2}\\mathsf{O}$ solution on the RDE scale (dashed). d The KIE curves plotted with the LSV curves adapted from (c) but presented on the overpotential scale. e CV curves of both catalysts recorded in $0.5{\\ensuremath{\\mathsf{M}}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ solution at 25 vs. $65^{\\circ}\\mathsf{C}$ . f The corresponding $E_{\\mathsf{a p p}}$ data point and error bar are calculated from CV curves recorded at different temperatures (see Supplementary Fig. 18 for details). \n\nSupplementary Fig. 19, also see Methods for details)54,55. To completely capture the potential-dependent evolution of $E_{\\mathrm{app}}$ , the analysis was performed both below and above the catalytic onset potential. On both catalysts, the $E_{\\mathrm{app}}$ value reached its maximum around the respective catalytic OER onset potential (Fig. 3f), consistent with the fact that $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ requires a lower overpotential than $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ to catalyze the OER. Interestingly, the $E_{\\mathrm{app}}$ values on both catalysts were very similar after the catalytic onsets (Fig. 3f), while more obvious differences are observed in the $A_{\\mathrm{app}}$ (Supplementary Fig. 20). The similar $E_{\\mathrm{app}}$ suggests that the introduction of ${\\mathrm{CeO}}_{2}$ does not alter the rate-determining step and the kinetic barrier for the formation of reaction intermediates, but rather enhances the intrinsic activity of the same type of catalytic active site in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ by modifying the entropy of activation (i.e., the number of active intermediates that enter the rate-determining step) and the interfacial concentration of active sites, as higher $\\smash{\\ensuremath{A_{\\mathrm{app}}}}$ is extracted for $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ at the same overpotential56–58. Therefore, these KIE, $\\mathrm{pH}-$ and temperaturedependence analyses exclude several other factors, so we attribute the enhanced acidic OER activity to the regulation of the redox properties in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ resulted from the modified local bonding environment, as explained below. \n\n![](images/22b52ac474d7f578e988fe29ce909604a96181455021d1458a0fe0bf464fe360.jpg) \nFig. 4 XAS characterizations of $\\pmb{\\mathrm{Co}_{3}}\\pmb{0}_{4}$ and $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{c e o}_{2}$ catalysts before and after OER testing in 0.5 M ${\\bf H}_{2}\\thinspace\\thinspace{\\sf s o}_{4}$ solution to reveal the structural and oxidation state differences between the two catalysts. a Co ${\\sf K}$ edge XANES spectra, the inset shows the upshift in the absorption edge energy after OER testing. b The average Co oxidation states and the intensity ratios of ${\\mathsf{C o}}{\\mathsf{-C o}}_{\\mathsf{o c t}}$ and ${\\mathsf{C o}}{\\mathsf{-C o}}_{\\mathsf{t e t}}$ scattering paths $(\\boldsymbol{\\mathrm{I}}_{\\mathrm{oct}}/\\boldsymbol{\\mathrm{I}}_{\\mathrm{tet}})$ of both catalysts. For each catalyst, the left and right columns represent the values before and after OER testing, respectively. c Fourier transforms (FT) of $\\mathsf{k}^{3}$ -weighted Co K-edge EXAFS spectra for both catalysts before and after OER testing. d Schematic illustrations of the local bonding environment changes in $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ before and after OER testing and the hypothesized electronic modifications in $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ . \n\nSpectroscopic characterization of the structural evolution in $\\mathbf{Co_{3}O_{4}}/\\mathbf{CeO_{2}}$ . We performed ex situ XAS on $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co}_{3}\\mathrm{O}_{4}/$ $\\mathrm{CeO}_{2}$ catalysts before and after OER testing in $0.5{\\bf M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution to understand the their structural evolution. Scanning electron microscopy (SEM)-EDS and XPS analyses confirmed that the elemental compositions of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ were mostly preserved after OER testing (Supplementary Figs. 21 and 22 and Supplementary Table 1). The surface-sensitive XPS revealed no obvious shift in the binding energies of the Co $2p$ signals after the introduction of $\\mathrm{CeO}_{2}$ (Supplementary Fig. 22a, d). Ultraviolet photoelectron spectroscopy (UPS) (Supplementary Fig. 23) showed larger work function in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ than pure $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , suggesting the electronic structure in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ was slightly modified due to possible electronic interactions between $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and ${\\mathrm{CeO}}_{2}$ . XAS is more sensitive to subtle changes in the oxidation states and the local bonding environments throughout the nanocomposite samples. According to the relative absorption edge positions in the Co K-edge X-ray absorption near-edge spectra (Fig. 4a), the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ exhibited a slightly higher Co oxidation state than the as-synthesized $\\mathrm{Co}_{3}\\mathrm{O}_{4},$ and the $\\scriptstyle{\\mathrm{Co}}$ oxidation states in both catalysts increased and became similar after OER testing (inset of Fig. 4a). The absorption edge energies were further determined by an integral method59 and the average Co valence states were calculated (see Methods for details)34,60. The average Co oxidation states in the as-synthesized $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ were 2.43 and 2.54, respectively; but after OER testing, both were raised to comparable higher values of 2.63 and 2.64 (upper panel of Fig. 4b). Therefore, although the introduction of ${\\mathrm{CeO}}_{2}$ slightly increased the Co oxidation state in the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalyst, such difference did not persist after OER testing and therefore might not directly account for the distinct electrochemical properties of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ vs. $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ . Moreover, a comparison of various $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ samples annealed at different temperatures also suggests that a higher $\\mathrm{Co}$ oxidation state before OER testing (Supplementary Fig. 24) does not necessarily result in changes in the pre-OER redox features (Supplementary Fig. 14a). \n\nBesides the higher Co oxidation state, the changes in local bonding environment of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ induced by $\\mathrm{CeO}_{2}$ were also observed, as revealed by extended X-ray absorption fine structure (EXAFS) (Fig. 4c and Supplementary Fig. 25). Fourier transforms of $\\mathrm{k}^{3}$ -weighted Co K-edge EXAFS spectra of both $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalysts displayed three major signals associated with the Co-O, ${\\mathrm{Co-Co}}_{\\mathrm{oct}}$ (octahedral site), and $\\scriptstyle\\mathrm{Co-Co}_{\\mathrm{tet}}$ (tetrahedral site) scattering paths (Fig. 4c). Compared to the assynthesized $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ (Fig. 4c red trace), a shorter Co-O bond distance was observed in the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ (Fig. 4c blue trace) due to the higher positive charge density at the Co centers61 after the electron redistribution from $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ to $\\mathrm{CeO}_{2}.$ as illustrated in the bottom scheme in Fig. 4d. More importantly, the bond distances in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ remained the same after OER testing (Fig. 4c light blue trace), and the crystal structure barely changed, as shown by the identical intensity ratio of $_{\\mathrm{Co-Co}_{\\mathrm{oct}}}$ and $\\scriptstyle\\mathrm{Co-Co}_{\\mathrm{tet}}$ scattering paths $\\mathrm{(I_{oct}/I_{t e t})}$ before and after OER testing (lower panel of Fig. 4b). In contrast, there were distinct changes in the bonding distances in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ after OER reaction (Fig. 4c light red curve), namely the shortening of both Co-O and $\\mathrm{Co-Co_{\\mathrm{tet}}}$ bonds and the elongation of ${\\mathrm{Co-Co}}_{\\mathrm{oct}}$ bond, as illustrated in the top scheme in Fig. 4d. Moreover, the $\\mathrm{I_{oct}/I_{t e t}}$ ratio in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ displayed an obvious increase from 1.44 to 1.52 after OER testing (lower panel of Fig. 4b), suggesting the crystal structure of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ underwent dynamic changes during OER reaction, as revealed by the prominent three sets of pre-OER redox features, which might be similar to the formation of active structure motifs during OER reactions in alkaline or neutral media26,29. \n\n![](images/9ae3f6b42e9eb42b7ef4ea6f7238a81ef83f7d4b0347034a1360620e76fc3ede.jpg) \nFig. 5 In situ Raman characterizations of $\\pmb{\\mathrm{Co}_{3}}\\pmb{0}_{4}$ and $\\mathsf{c o}_{3}\\mathsf{o}_{4}/\\mathsf{c e o}_{2}$ catalysts on carbon paper electrodes during OER testing in 0.5 M ${\\bf H}_{2}\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\large=\\thinspace\\qquad\\large=\\thinspace\\large=\\thinspace\\frac{1}{2}$ solution to reveal the structural evolution of catalysts. a The in situ Raman spectra of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ (left panel) and $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ (right panel) at various constant potentials (vs. RHE) without $i R$ correction (increased from 1.22 to $1.87\\mathrm{V}$ and then back to $1.22\\vee{}$ . The Raman spectra of the dry samples were also presented at the bottom for comparisons. b The Raman $\\mathsf{A}_{1\\mathrm{g}}$ peaks of $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ (top) and $\\mathsf{C o}_{3}\\mathsf{O}_{4}/\\mathsf{C e O}_{2}$ (bottom) were fitted with Lorentzian function to extract the peak positions, intensity, and FWHM (dash lines: raw spectra; dots: fitting results). c The Raman $\\mathsf{A}_{1\\mathrm{g}}$ peak positions (upper panel) and intensity ratio with respect to the initial intensity at $1.22\\vee$ (lower panel) plotted against the applied potential. The open symbols represent the data collected at $1.22\\vee$ at the end after applying the higher potential sequence. The error bar represents the error from fitting. \n\nIn situ Raman studies of the OER reaction mechanisms. To further unveil the relationships between the catalytic activity enhancement, redox-mediated surface reconstruction, and the modified local bonding environment in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ nanocomposites, we conducted in situ Raman experiments on both catalysts in 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution under OER conditions (Supplementary Fig. 26). Both dry samples of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{3}O_{4}/C e0_{2}}$ display four characteristic Raman peaks corresponding to the $\\mathrm{E_{g}}$ $({\\sim}480\\ \\mathrm{cm^{-1}})$ , $\\mathrm{F}_{2\\mathrm{g}}$ $(\\sim520\\ c m^{-1})$ , $\\mathrm{\\DeltaF_{2g}}$ $({\\sim}620\\ \\mathrm{\\bar{c}m^{-1}})$ , and $\\mathbf{A}_{1\\mathbf{g}}$ $(\\sim690\\ c m^{-1})$ phonon modes of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ spinel oxides (Fig. 5a)62. After the samples were immersed in the electrolyte, another Raman signal emerged at ${\\sim}600\\ c m^{-1}$ at the applied potential of $1.22\\mathrm{V}$ (vs. RHE), which was attributed to the formation of CoOOH species at the surface31. This CoOOH species was less clearly detected at high potentials and started to disappear from the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ and $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ surfaces at 1.52 and $1.62{\\bar{\\mathrm{V}}}$ vs. RHE, respectively, which coincided with their respective OER onset potentials (Supplementary Fig. 26), as well as the two pre-OER redox features of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ associated with $\\mathrm{Co^{III}C o^{I I I}\\leftrightarrow\\dot{C}o^{I I I}C o^{I V}}$ $(\\sim1.50\\mathrm{V}$ vs. RHE) and $\\mathrm{Co}^{\\mathrm{III}}\\mathrm{Co}^{\\mathrm{IV}}\\leftrightarrow\\mathrm{Co}^{\\mathrm{IV}}\\mathrm{Co}^{\\mathrm{IV}}$ $_{\\sim1.63\\mathrm{V}}$ vs. RHE) transitions (Fig. 2b). Clearly, this CoOOH species is not the actual active phase for acidic OER and needs to be further oxidized into ${\\cal C}\\mathrm{o}^{\\mathrm{IV}}$ species. The disappearance of this CoOOH species from $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ at a lower potential indicates that it is easier to oxidize the active $\\mathrm{Co}$ sites in the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalyst into OERactive ${\\cal C}\\mathrm{o}^{\\mathrm{IV}}$ species compared to those Co sites in the pure $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ . The intensities of all Raman peaks at higher applied potentials decrease substantially (Fig. 5b, c lower panel), which was usually accompanied with the increase in average valence state of $\\scriptstyle{\\mathrm{Co}}$ atoms63. When the applied potential was finally switched back from 1.87 to $1.22\\mathrm{V}$ vs. RHE, the peak intensities partially recovered (lower panel in Fig. 5c) and the CoOOH species was clearly detected again. \n\nTo understand the evolution of the local bonding environments at the catalyst surface during the OER process, the peak position, intensity, and full width at half maximum (FWHM) of the Raman $\\mathbf{A}_{1\\mathbf{g}}$ peak $({\\sim}690\\ c m^{-1}),$ were extracted by fitting with Lorentzian function (Fig. 5b, c). The shift in the peak position as a function of applied potential can be interpreted as either the change in crystallinity (e.g., red-shift with broadening in FWHM happens when the crystallinity decreases dramatically), or the generation of strain/stress (i.e., lattice contraction/extension)64,65. Since the marginal variations in the peak FWHM suggested the crystalline domain sizes of both samples remain relatively constant during the OER process (Supplementary Fig. 27), the observed peak position shift should result from the lattice contraction/extension and surface reconstruction due to the changing local bonding environments. More importantly, the peak positions shift in opposite directions on these two catalysts as the potential goes over the OER catalytic onsets (Fig. 5c upper panel). $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ showed a redshift in the $\\mathbf{A}_{1\\mathbf{g}}$ peak position after the onset of OER at $1.52\\mathrm{V}$ vs. RHE. Red-shifts in Raman signals are commonly observed in OER catalysts $(\\mathrm{CoO}_{x}^{63,66}$ , $\\mathrm{NiOOH}^{\\mathrm{\\bar{6}7}}$ , NiFe, and CoFe oxyhydroxides68) at OER operating potentials, and they generally reflect the characteristic vibration for local bonding environment at the outer layer of catalysts with oxidized active site during OER. Thus, the generation of active ${\\mathrm{Co}}^{\\mathrm{IV}}$ species that can participate in a fast and efficient OER process should lead to the observed red-shift of the Raman signals. In contrast, blue-shifts in Raman signals usually suggest lattice contraction and charge redistribution64,69. Unlike the more active $\\mathrm{Co_{3}O_{4}/C e O_{2}}.$ the pure $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ catalyst would go through substantial charge-accumulation surface reconstruction $(\\mathrm{Co}^{\\mathrm{III}}\\mathrm{Co}^{\\mathrm{IV}}\\leftrightarrow\\mathrm{Co}^{\\mathrm{IV}}\\mathrm{Co}^{\\mathrm{IV}})$ at ${\\sim}1.62\\mathrm{V}$ around the onset for OER. The $\\mathrm{Co^{IV}}$ species generated during this process are stabilized and cannot participate in fast OER turnover since the reduction peak could be still observed when the potential was scanned backwards, thus they lead to a blue-shift in the Raman signals (Fig. 5c). Another interesting difference is that the peak position of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ at $1.22\\mathrm{V}$ vs. RHE remains almost unchanged before and after applying the higher potential sequence, suggesting the flexibility in the local bonding environment of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ in the composite catalyst. However, the peak position of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ cannot fully recover after the same potential cycle, with the final peak at ${\\sim}1\\mathrm{cm^{-1}}$ higher in wavenumber accordingly (Fig. 5c upper panel and Supplementary Fig. 28), which is consistent with the positive charge accumulated at the Co center with shorter $_{\\mathrm{Co-O}}$ bond in the $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ sample after OER (Fig. 4a–c). Together with the ex situ XAS results, the in situ Raman results clearly demonstrate that the bonding environment surrounding $\\scriptstyle\\mathrm{Co}$ centers is modified in the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalyst, which allows the active $\\scriptstyle\\mathrm{Co}$ sites to be more readily oxidized and avoid the substantial potential-determining surface reconstruction that would otherwise form stabilized dimeric ${\\mathrm{Co}}^{\\mathrm{IV}}{\\mathrm{Co}}^{\\mathrm{IV}}$ with charge accumulation and lattice contraction. As ${\\cal C}\\mathrm{o}^{\\mathrm{IV}}$ is the key intermediate to start OER process, the more facile formation of ${\\mathrm{Co}}^{\\mathrm{IV}}$ species and destabilization of $\\mathrm{Co^{IV}C o^{I V}}$ in $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ would allow faster OER kinetics thus enhance the catalytic activity. \n\nElectrode performance and stability of $\\mathbf{Co_{3}O_{4}}/\\mathbf{CeO_{2}}$ nanocomposites. We further optimized the overall electrode performance by replacing the FTO substrate with high-surface-area three-dimensional carbon paper substrate that facilitates electron and ion transport and gas bubble release. To reach a geometric catalytic current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ in 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}^{-}$ solution, $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ on carbon paper electrode only required an overpotential as low as $347\\mathrm{mV}$ , which is only $46\\mathrm{mV}$ higher than that needed for the benchmark ${\\mathrm{RuO}}_{2}$ catalyst on carbon paper electrode (Supplementary Fig. 29). A comprehensive comparison shows that $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ is an efficient earth-abundant metal oxide-based electrocatalysts reported to date for the acidic OER (Supplementary Table 3). \n\nLastly, we examined the acidic OER stability of the $\\mathrm{Co}_{3}\\mathrm{O}_{4}/$ $\\mathrm{CeO}_{2}$ catalyst, since the tradeoff between activity and stability has usually been observed in acidic OER catalysts15,16. As discussed earlier, the apparent elemental compositions of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ changed little after the OER test (Supplementary Figs. 21 and 22). Since it is known that $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ dissolves very slowly under acidic OER conditions based on detection of metal leaching23, we used ICP-MS to monitor the catalyst dissolution rate of the highperformance $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ on carbon paper electrode during long-term chronopotentiometry tests at $\\mathrm{i}0\\mathrm{mA}\\mathrm{cm}^{-2}$ in $0.5\\dot{\\mathrm{M}}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solutions (Supplementary Fig. 30). $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ displayed essentially the same rate of potential increase over time as $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ in 0.5 or 0.05 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution over 50 or $\\boldsymbol{100}\\mathrm{h}$ continuous operation, respectively (Supplementary Fig. 30a, c). The cobalt dissolution rate of $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ also coincided with that of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ in $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution (Supplementary Fig. 30b). The metal dissolution rates of both catalysts were also investigated under open circuit condition without an applied bias (Supplementary Fig. 31). Both catalysts showed inferior stability under open circuit condition compared to their respective stability under anodically biased OER condition, suggesting that the applied bias is important for the long-term stability of earth-abundant Co oxides during acidic OER operation70. It is noteworthy that $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ displayed no obvious Ce dissolution and much slower Co dissolution than pure $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ under open circuit condition. Thus, the more active $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ exhibits a comparable OER stability but an enhanced open circuit stability compared to the less active $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ , and therefore breaks the activity/stability tradeoff. \n\n# Discussion \n\nIn conclusion, $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ nanocomposite is established as an active earth-abundant OER electrocatalyst in acidic media. The overpotentials required for $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ to achieve a geometric catalytic current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ on FTO and carbon paper electrodes are ${\\sim}423$ and $347\\mathrm{mV}$ , respectively, making it an efficient earth-abundant electrocatalysts for acidic OER. In-depth electrochemical characterizations using the KIE, pH-, and temperature-dependence analyses, together with in situ Raman and ex situ XAS structural characterizations of the $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalyst before and after OER testing, consistently reveal the microstructural states of the catalysts and their changes through the OER processes. The introduction of nanocrystalline $\\mathrm{CeO}_{2}$ modifies the electronic structures and creates a more favorable local bonding environment in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ that allows the ${\\mathrm{Co}}^{\\mathrm{III}}$ surface species to be easily oxidized into OER-active ${\\mathrm{Co}}^{\\mathrm{IV}}$ species and suppresses the charge accumulation of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ under electrochemical conditions, which are the keys to bypassing the potential-determining redox step in $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ that result in substantial surface reconstruction and thus enhancing the acidic OER activity. Interestingly, $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ also breaks the activity/ stability tradeoff by featuring enhanced activity but comparable acidic OER stability and better open circuit stability in comparison with $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ . We hope these findings could stimulate future studies to further elucidate the active site structures and the catalytic mechanisms of nanocomposite OER catalysts using other in situ and/or operando techniques. This work not only establishes an active earth-abundant nanocomposite catalyst $(\\mathrm{Co}_{3}\\mathrm{O}_{4}/\\mathrm{CeO}_{2})$ for OER in acidic media, but also stimulates mechanistic understandings and provides an effective strategy to design more efficient and stable nanocomposite electrocatalysts for acidic OER or other reactions in the future. \n\n# Methods \n\nChemicals. All chemicals were purchased from Sigma-Aldrich and used as received without further purification, unless noted otherwise. Deionized nanopure water $(18.2~\\mathrm{M}\\Omega\\cdot\\mathrm{cm})$ from a Thermo Scientific Barnstead water purification system was used for all experiments. \n\nSynthesis of $\\pmb{\\mathrm{co}_{3}}\\pmb{0}_{4}$ and $\\mathsf{c o}_{3}\\mathsf{o}_{4}/\\mathsf{c e o}_{2}$ on FTO or carbon paper. The corresponding metal hydroxide precursors were first synthesized on the substrates by electrodeposition from a solution of the corresponding metal nitrate(s) with a total concentration of 0.1 molar (mol). For synthesizing the $C e$ -doped ${\\mathrm{Co}}(\\mathrm{OH})_{2}$ precursor, $10\\mathrm{mol}$ percent $(\\mathrm{mol\\%})$ of $\\mathrm{Co}(\\mathrm{NO}_{3})_{2}$ in the solution was replaced with Ce $(\\mathrm{NO}_{3})_{3}$ . Note that the as-received carbon paper substrate (Fuel Cell Earth, TGP-H060) was Teflon-coated; therefore, it was first treated with oxygen plasma at $300\\mathrm{W}$ power for $15\\mathrm{min}$ for each side and then annealed in air at $700^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ to make the surface hydrophilic. Prior to the electrodeposition, the FTO and carbon paper substrates were successively washed with acetone, ethanol, and nanopure water. During the electrodeposition, an $\\mathrm{\\Ag/AgCl}$ reference electrode and a $\\mathrm{Pt}$ mesh counter electrode were used, and a constant potential of $-1.0\\mathrm{V}$ vs. $\\mathrm{Ag/AgCl}$ was applied on the substrates for 3 and $10\\mathrm{min}$ in the case of FTO and carbon paper, respectively. During the electrodeposition, the reduction of nitrate generated OH– and a local alkaline environment near the substrate, and subsequently metal hydroxides were formed on the substrate71: \n\n$$\n\\mathrm{NO}_{3}^{-}+7\\mathrm{H}_{2}\\mathrm{O}+8\\mathrm{e}^{-}\\rightarrow\\mathrm{NH}_{4}^{+}+10\\mathrm{OH}^{-}\n$$ \n\n$$\n\\mathrm{Co}^{2+}+2\\mathrm{OH}^{-}\\rightarrow\\mathrm{Co}(\\mathrm{OH})_{2}\n$$ \n\nAfter the electrodeposition, the metal hydroxide precursors were dried at $80~^{\\circ}\\mathrm{C}$ for $6\\mathrm{h}$ , and then annealed in air at $400^{\\circ}\\mathrm{C}$ (or 300 or $500^{\\circ}\\mathrm{C}$ as specifically discussed) for $^{2\\mathrm{h}}$ in a muffle furnace to transform into oxides. \n\nStructural characterizations. SEM and EDS were conducted on a Zeiss Supra 55VP field emission SEM equipped with a Thermo Fisher Scientific UltraDry EDS detector. The accelerating voltage for SEM and EDS were 3 and $15\\mathrm{kV}$ , respectively. Transmission electron spectroscopy images and elemental mappings were collected using a JEM-2100F microscope equipped with an Oxford energy-dispersive X-ray analysis system, with the accelerating voltage of $200\\mathrm{kV}$ . PXRD was performed on a Bruker D8 Advance powder X-ray diffractometer using Cu Kα radiation. XPS was performed on a Thermo Scientific K-Alpha XPS system with an Al Kα X-ray source. UPS was collected on a Thermo ESCALAB 250Xi XPS system with a He I source gun. The Raman spectra were collected on a Thermo Fisher Scientific DXRxi Raman imaging microscope with a $532\\mathrm{nm}$ laser. The ICP-MS analysis was carried out on a Shimadzu ICPMS-2030 spectrometer. The XAS were collected in the transmission mode at the Advanced Photon Source Beamline 10-BM-B at the Argonne National laboratory. To collect the Co K-edge in the energy window from 7.450 to $8.650\\mathrm{keV}$ , a $71/29~\\mathrm{N}_{2}/\\mathrm{He}$ gas mixture was used in the $\\mathrm{I}_{0}$ ion chamber to achieve $10\\%$ absorption, while a $68/32~\\mathrm{N}_{2}/\\mathrm{Ar}$ gas mixture was used in the $\\mathrm{I_{t}}$ ion chamber to achieve $70\\%$ absorption (calculated using Hephaestus at an energy of $7.709\\mathrm{keV},$ ). The Co foil standard was used for the energy calibration. \n\nElectrochemical measurements. All electrochemical measurements were conducted in a conventional three-electrode setup using a Bio-Logic SP-200 potentiostat. The $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ or $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ catalyst grown on FTO or carbon paper was directly used as the working electrode, along with an $\\mathrm{Ag/AgCl}$ reference electrode and a Pt mesh counter electrode in $0.5\\:\\mathrm{M}\\:\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution. CV was performed at the scan rate of $5\\mathrm{mVs^{-1}}$ . EIS was collected in the frequency range from $100\\mathrm{kHz}$ to $50\\mathrm{mHz}$ . All CV curves were manually $i R$ -corrected based on EIS results. To extract the double-layer capacitance $\\left(C_{\\mathrm{dl}}\\right)$ , CV was collected in pre-OER potential region at various scan rates from 10 to $60\\mathrm{mVs^{-1}}$ . The relationship between ECSA $(\\mathrm{cm}^{2})$ and $C_{\\mathrm{dl}}$ (mF) is shown in Eq. (3): \n\n$$\n\\mathrm{ECSA}=C_{\\mathrm{dl}}/C_{s}\n$$ \n\nwhere $C_{\\mathrm{s}}$ is general specific capacitance, which is a constant of $0.035\\mathrm{mF}\\mathrm{cm}^{-2}$ in the literature45. \n\nAll potentials were reported versus the RHE using Eq. (4): \n\n$$\n\\mathrm{E(RHE)}=\\mathrm{E(Ag/AgCl)}+0.059\\mathrm{pH}+0.197\n$$ \n\nThe operational stability of the catalyst was tested by running chronopotentiometry tests at a constant geometric catalytic current density of $10\\mathrm{mA}\\mathrm{\\bar{c}}\\mathrm{m}^{-2}$ in 0.5 (or 0.05) M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution for 50 (or 100) h. \n\nReaction order with respect to ${\\mathsf{p H}}$ . To extract the reaction order with respect to $\\mathrm{\\tt{pH}}$ for the acidic OER, the electrochemical measurements of the catalysts were conducted in $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solutions with different $\\mathsf{p H}$ values. The reaction order with respect to $\\mathrm{\\DeltapH}$ was calculated using Eq. $(5)^{27,\\dot{7}2}$ : \n\n$$\n\\mathrm{Reactionorder}=\\left|{\\frac{\\partial(\\log_{10}j)}{\\partial{\\mathrm{pH}}}}\\right|_{\\eta}\n$$ \n\nwhere $j$ is the catalytic current density at a fixed overpotential $\\eta$ \n\nKinetic isotope effect (KIE). To evaluate the KIE, the electrochemical measurements of the catalysts were conducted in both protonic $\\mathrm{(}0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4}$ in $\\mathrm{H}_{2}\\mathrm{O}$ ) and deuteric $0.5\\mathrm{M}\\mathrm{~D}_{2}\\mathrm{SO}_{4}$ in $\\mathrm{D}_{2}\\mathrm{O}_{\\cdot}^{\\cdot}$ solutions. The pD value of the deuteric solution was determined by 0.41 plus the measured $\\mathrm{\\tt{pH}}$ value using a glass membrane $\\mathrm{\\tt{pH}}$ electrode connected to a $\\mathrm{\\ttpH}$ meter73. The potential on RDE scale was calculated using Eq. (6): \n\n$$\n\\mathrm{E(RDE)}=\\mathrm{E(Ag/AgCl)}+0.059\\mathrm{pD}+0.197+0.013\n$$ \n\nwhere the term of $+0.013$ originates from the difference in the standard equilibrium potentials of the deuterium couple $\\mathrm{(D_{2}/D^{+})}$ and the proton couple $(\\bar{\\mathrm{H}}_{2}/\\mathrm{H}^{+})^{53}$ . \n\nThe overpotentials of the OER in the protonic and deuteric solution were determined by Eqs. (7) and (8), respectively53: \n\n$$\n\\eta=\\mathrm{E}(\\mathrm{RHE})-1.229\\mathrm{V}\n$$ \n\n$$\n\\eta=\\mathrm{E(RDE)}-1.262\\mathrm{V}\n$$ \n\nThe KIE was calculated using Eq. (9): \n\n$$\n\\mathrm{KIE}=\\left|\\frac{j_{\\mathrm{H_{2}O}}}{j_{\\mathrm{D_{2}O}}}\\right|_{\\eta}\n$$ \n\nwhere $j_{\\mathrm{H_{2}O}}$ and $j_{\\mathrm{D_{2}O}}$ are the catalytic current density in the protonic and deuteric solution, respectively, at the same overpotential $(\\eta)^{72}$ . \n\nApparent activation energy. To extract the apparent activation energy $(E_{\\mathrm{app}})$ for the acidic OER, the electrochemical measurements of the catalysts were conducted in $0.5\\mathrm{M}\\mathrm{~H}_{2}\\mathrm{SO}_{4}$ solution at different temperatures. For heterogeneous electrocatalytic reaction, the current density can be expressed from apparent activation energy $(E_{\\mathrm{app}})$ in the Arrhenius Eq. $(10)^{56,57}$ : \n\n$$\nj=A_{\\mathrm{app}}\\exp\\left({-\\frac{E_{\\mathrm{app}}}{R T}}\\right)\n$$ \n\nwhere $A_{\\mathrm{app}}$ is the apparent pre-exponential factor, $R$ is the ideal gas constant (8.314 J $\\mathrm{K}^{\\mathrm{\\dot{-}1}}\\mathrm{mol}^{-1}.$ ), $T$ is the temperature in Kelvin (K). Therefore, $E_{\\mathrm{app}}$ can be \n\nfurther calculated from fitting the slope of the Arrhenius plot using Eq. $(11)^{54,56}$ : \n\n$$\n\\left|\\frac{\\partial(\\log_{10}j)}{\\partial(1/T)}\\right|_{\\eta}=-\\frac{E_{\\mathrm{app}}}{2.303\\mathrm{R}}\n$$ \n\nwhile the intercept of $\\log_{10}j$ vs. $1/T$ plot is the logarithm of $A_{a p p}{}^{57}$ . \n\nAverage Co valence state. The absorption edge energies of the XAS spectra were first determined by an integral method shown in Eq. $\\bar{(12)}^{59}$ : \n\n$$\nE_{\\mathrm{edge}}={\\frac{1}{\\mu_{2}-\\mu_{1}}}\\int_{\\mu_{1}}^{\\mu_{2}}E(\\mu)\\mathrm{d}\\mu\n$$ \n\nwhere $\\mu_{1}=0.15$ and $\\mu_{2}=1$ are the lower and upper limit, respectively, of the normalized absorption intensity that are used for the integral. The average Co valence states were then calculated by fitting the absorption edge energies determined earlier into an experimental equation developed by Dau et al.34,60: \n\n$$\n{\\mathrm{Oxidation~state}}={\\frac{1}{2.29}}(E_{\\mathrm{edge}}-7714.1{\\mathrm{~eV}})\n$$ \n\n# Data availability \n\nThe data that support the findings in the paper can be found in the Source Data. Additional data presented in the Supplementary Information are available from the corresponding author upon reasonable request. Source Data are provided with this paper. \n\nReceived: 4 October 2020; Accepted: 27 April 2021; Published online: 24 May 2021 \n\n# References \n\n1. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: Insights into materials design. Science 355, eaad4998 (2017). \n2. Stamenkovic, V. R., Strmcnik, D., Lopes, P. P. & Markovic, N. M. Energy and fuels from electrochemical interfaces. Nat. Mater. 16, 57–69 (2017). \n3. Reier, T., Nong, H. N., Teschner, D., Schlögl, R. & Strasser, P. Electrocatalytic oxygen evolution reaction in acidic environments—reaction mechanisms and catalysts. Adv. Energy Mater. 7, 1601275 (2017). \n4. Carmo, M., Fritz, D. L., Mergel, J. & Stolten, D. A comprehensive review on PEM water electrolysis. Int. J. Hydrog. Energy 38, 4901–4934 (2013). \n5. Ayers, K. The potential of proton exchange membrane–based electrolysis technology. Curr. Opin. Electrochem. 18, 9–15 (2019). \n6. Liu, Y. et al. Self-optimizing, highly surface-active layered metal dichalcogenide catalysts for hydrogen evolution. Nat. Energy 2, 17127 (2017). \n7. Cabán-Acevedo, M. et al. Efficient hydrogen evolution catalysis using ternary pyrite-type cobalt phosphosulphide. Nat. Mater. 14, 1245–1251 (2015). \n8. Lukowski, M. A. et al. Enhanced hydrogen evolution catalysis from chemically exfoliated metallic MoS2 nanosheets. J. Am. Chem. Soc. 135, 10274–10277 (2013). \n9. Sun, Y. et al. Covalency competition dominates the water oxidation structure–activity relationship on spinel oxides. Nat. Catal. 3, 554–563 (2020). \n10. Huang, Z.-F. et al. Strategies to break the scaling relation toward enhanced oxygen electrocatalysis. Matter 1, 1494–1518 (2019). \n11. Busch, M. et al. Beyond the top of the volcano?—a unified approach to electrocatalytic oxygen reduction and oxygen evolution. Nano Energy 29, 126–135 (2016). \n12. Shan, J., Zheng, Y., Shi, B., Davey, K. & Qiao, S.-Z. Regulating electrocatalysts via surface and interface engineering for acidic water electrooxidation. ACS Energy Lett. 4, 2719–2730 (2019). \n13. Danilovic, N. et al. Activity–stability trends for the oxygen evolution reaction on monometallic oxides in acidic environments. J. Phys. Chem. Lett. 5, 2474–2478 (2014). \n14. Povia, M. et al. Operando X-ray characterization of high surface area iridium oxides to decouple their activity losses for the oxygen evolution reaction. Energy Environ. Sci. 12, 3038–3052 (2019). \n15. Spöri, C., Kwan, J. T. H., Bonakdarpour, A., Wilkinson, D. P. & Strasser, P. The stability challenges of oxygen evolving catalysts: towards a common fundamental understanding and mitigation of catalyst degradation. Angew. Chem. Int. Ed. 56, 5994–6021 (2017). \n16. Yang, C. et al. Cation insertion to break the activity/stability relationship for highly active oxygen evolution reaction catalyst. Nat. Commun. 11, 1378 (2020). \n17. Blasco-Ahicart, M., Soriano-López, J., Carbó, J. J., Poblet, J. M. & GalanMascaros, J. R. Polyoxometalate electrocatalysts based on earth-abundant metals for efficient water oxidation in acidic media. Nat. Chem. 10, 24–30 (2018). \n18. Chatti, M. et al. Intrinsically stable in situ generated electrocatalyst for longterm oxidation of acidic water at up to $80^{\\circ}\\mathrm{C}$ . Nat. Catal. 2, 457–465 (2019). \n19. Li, A. et al. Stable potential windows for long-term electrocatalysis by manganese oxides under acidic conditions. Angew. Chem. Int. Ed. 58, 5054–5058 (2019). \n20. Moreno-Hernandez, I. A. et al. Crystalline nickel manganese antimonate as a stable water-oxidation catalyst in aqueous 1.0 M H2SO4. Energy Environ. Sci. 10, 2103–2108 (2017). \n21. Su, H. et al. Hetero-N-coordinated Co single sites with high turnover frequency for efficient electrocatalytic oxygen evolution in an acidic medium. ACS Energy Lett. 4, 1816–1822 (2019). \n22. Anantharaj, S., Karthick, K. & Kundu, S. Spinel cobalt titanium binary oxide as an all-non-precious water oxidation electrocatalyst in acid. Inorg. Chem. 58, 8570–8576 (2019). \n23. Mondschein, J. S. et al. Crystalline cobalt oxide films for sustained electrocatalytic oxygen evolution under strongly acidic conditions. Chem. Mater. 29, 950–957 (2017). \n24. Yang, X. et al. Highly acid-durable carbon coated $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanoarrays as efficient oxygen evolution electrocatalysts. Nano Energy 25, 42–50 (2016). \n25. Yan, K.-L. et al. Probing the active sites of $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ for the acidic oxygen evolution reaction by modulating the $\\mathrm{Co}^{2+}/\\mathrm{Co}^{3+}$ ratio. J. Mater. Chem. A 6, 5678–5686 (2018). \n26. Bergmann, A. et al. Unified structural motifs of the catalytically active state of Co(oxyhydr)oxides during the electrochemical oxygen evolution reaction. Nat. Catal. 1, 711–719 (2018). \n27. Huang, Z.-F. et al. Chemical and structural origin of lattice oxygen oxidation in $\\mathrm{Co-Zn}$ oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). \n28. Surendranath, Y., Kanan, M. W. & Nocera, D. G. Mechanistic studies of the oxygen evolution reaction by a cobalt-phosphate catalyst at neutral pH. J. Am. Chem. Soc. 132, 16501–16509 (2010). \n29. Tung, C.-W. et al. Reversible adapting layer produces robust single-crystal electrocatalyst for oxygen evolution. Nat. Commun. 6, 8106 (2015). \n30. Bergmann, A. et al. Reversible amorphization and the catalytically active state of crystalline $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ during oxygen evolution. Nat. Commun. 6, 8625 (2015). \n31. Moysiadou, A., Lee, S., Hsu, C.-S., Chen, H. M. & Hu, X. Mechanism of oxygen evolution catalyzed by cobalt oxyhydroxide: cobalt superoxide species as a key intermediate and dioxygen release as a rate-determining step. J. Am. Chem. Soc. 142, 11901–11914 (2020). \n32. Zhang, M., de Respinis, M. & Frei, H. Time-resolved observations of water oxidation intermediates on a cobalt oxide nanoparticle catalyst. Nat. Chem. 6, 362–367 (2014). \n33. Costentin, C., Porter, T. R. & Savéant, J.-M. Conduction and reactivity in heterogeneous-molecular catalysis: new insights in water oxidation catalysis by phosphate cobalt oxide films. J. Am. Chem. Soc. 138, 5615–5622 (2016). \n34. Pasquini, C. et al. H/D isotope effects reveal factors controlling catalytic activity in Co-based oxides for water oxidation. J. Am. Chem. Soc. 141, 2938–2948 (2019). \n35. Campbell, C. T. The degree of rate control: a powerful tool for catalysis research. ACS Catal. 7, 2770–2779 (2017). \n36. Liu, L., Liu, Y. & Liu, C. Enhancing the understanding of hydrogen evolution and oxidation reactions on $\\mathrm{Pt}(111)$ through Ab initio simulation of electrode/ electrolyte kinetics. J. Am. Chem. Soc. 142, 4985–4989 (2020). \n37. Montini, T., Melchionna, M., Monai, M. & Fornasiero, P. Fundamentals and catalytic applications of $\\mathrm{CeO}_{2}$ -based materials. Chem. Rev. 116, 5987–6041 (2016). \n38. Wang, J. et al. The application of $\\mathrm{CeO}_{2}$ -based materials in electrocatalysis. J. Mater. Chem. A 7, 17675–17702 (2019). \n39. Liu, Y. et al. 2D electron gas and oxygen vacancy induced high oxygen evolution performances for advanced $\\mathrm{Co_{3}O_{4}/C e O_{2}}$ nanohybrids. Adv. Mater. 31, 1900062 (2019). \n40. Qiu, B. et al. $\\mathrm{CeO}_{2}$ -induced interfacial $C o^{2+}$ octahedral sites and oxygen vacancies for water oxidation. ACS Catal. 9, 6484–6490 (2019). \n41. Kim, J.-H. et al. Enhanced activity promoted by CeOx on a CoOx electrocatalyst for the oxygen evolution reaction. ACS Catal. 8, 4257–4265 (2018). \n42. Chen, M., Hallstedt, B., Grundy, A. N. & Gauckler, L. J. $\\mathrm{CeO}_{2}\\mathrm{-CoO}$ phase diagram. J. Am. Ceram. Soc. 86, 1567–1570 (2003). \n43. Zhao, Q., Yan, Z., Chen, C. & Chen, J. Spinels: controlled preparation, oxygen reduction/evolution reaction application, and beyond. Chem. Rev. 117, 10121–10211 (2017). \n44. Tsuji, E., Imanishi, A., Fukui, K.-I. & Nakato, Y. Electrocatalytic activity of amorphous $\\mathrm{RuO}_{2}$ electrode for oxygen evolution in an aqueous solution. Electrochim. Acta 56, 2009–2016 (2011). \n45. McCrory, C. C. L., Jung, S., Peters, J. C. & Jaramillo, T. F. Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 135, 16977–16987 (2013). \n46. Huang, J. et al. Improving electrocatalysts for oxygen evolution using $\\mathrm{NixFe}_{3}–\\mathrm{xO}_{4}/\\mathrm{Ni}$ hybrid nanostructures formed by solvothermal synthesis. ACS Energy Lett. 3, 1698–1707 (2018). \n47. Dincă, M., Surendranath, Y. & Nocera, D. G. Nickel-borate oxygen-evolving catalyst that functions under benign conditions. Proc. Natl Acad. Sci. USA. 107, 10337–10341 (2010). \n48. Görlin, M. et al. Tracking catalyst redox states and reaction dynamics in Ni–Fe oxyhydroxide oxygen evolution reaction electrocatalysts: the role of catalyst support and electrolyte pH. J. Am. Chem. Soc. 139, 2070–2082 (2017). \n49. Brezesinski, T., Wang, J., Polleux, J., Dunn, B. & Tolbert, S. H. Templated nanocrystal-based porous TiO2 films for next-generation electrochemical capacitors. J. Am. Chem. Soc. 131, 1802–1809 (2009). \n50. Xiao, J. et al. Rational design of a P2-type spherical layered oxide cathode for high-performance sodium-ion batteries. ACS Cent. Sci. 5, 1937–1945 (2019). \n51. Weinberg, D. R. et al. Proton-coupled electron transfer. Chem. Rev. 112, 4016–4093 (2012). \n52. Subbaraman, R. et al. Enhancing hydrogen evolution activity in water splitting by tailoring $\\mathrm{Li^{+}{-N i(O H)2\\mathrm{-}P t}}$ interfaces. Science 334, 1256–1260 (2011). \n53. Malko, D. & Kucernak, A. Kinetic isotope effect in the oxygen reduction reaction (ORR) over Fe-N/C catalysts under acidic and alkaline conditions. Electrochem. Commun. 83, 67–71 (2017). \n54. Suermann, M., Schmidt, T. J. & Büchi, F. N. Comparing the kinetic activation energy of the oxygen evolution and reduction reactions. Electrochim. Acta 281, 466–471 (2018). \n55. Shinagawa, T., Ng, M. T.-K. & Takanabe, K. Boosting the performance of the nickel anode in the oxygen evolution reaction by simple electrochemical activation. Angew. Chem. Int. Ed. 56, 5061–5065 (2017). \n56. Anderson, A. B. et al. Activation energies for oxygen reduction on platinum alloys: theory and experiment. J. Phys. Chem., B 109, 1198–1203 (2005). \n57. Duan, Y. et al. Revealing the impact of electrolyte composition for Co-based water oxidation catalysts by the study of reaction kinetics parameters. ACS Catal. 10, 4160–4170 (2020). \n58. Shinagawa, T. & Takanabe, K. New insight into the hydrogen evolution reaction under buffered near-neutral pH conditions: enthalpy and entropy of activation. J. Phys. Chem. C. 120, 24187–24196 (2016). \n59. Dau, H., Liebisch, P. & Haumann, M. X-ray absorption spectroscopy to analyze nuclear geometry and electronic structure of biological metal centers —potential and questions examined with special focus on the tetra-nuclear manganese complex of oxygenic photosynthesis. Anal. Bioanal. Chem. 376, 562–583 (2003). \n60. Risch, M. et al. Water oxidation by amorphous cobalt-based oxides: in situ tracking of redox transitions and mode of catalysis. Energy Environ. Sci. 8, 661–674 (2015). \n61. Wang, H.-Y. et al. In situ spectroscopic identification of $\\upmu{-}\\mathrm{OO}$ bridging on spinel $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ water oxidation electrocatalyst. J. Phys. Chem. Lett. 7, 4847–4853 (2016). \n62. Xiao, Z. et al. Operando identification of the dynamic behavior of oxygen vacancy-rich $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ for oxygen evolution reaction. J. Am. Chem. Soc. 142, 12087–12095 (2020). \n63. Pasquini, C., D’Amario, L., Zaharieva, I. & Dau, H. Operando Raman spectroscopy tracks oxidation-state changes in an amorphous Co oxide material for electrocatalysis of the oxygen evolution reaction. J. Chem. Phys. 152, 194202 (2020). \n64. Xu, C. Y., Zhang, P. X. & Yan, L. Blue shift of Raman peak from coated TiO2 nanoparticles. J. Raman Spectrosc. 32, 862–865 (2001). \n65. Scamarcio, G., Lugará, M. & Manno, D. Size-dependent lattice contraction in CdS1-xSex nanocrystals embedded in glass observed by Raman scattering. Phys. Rev. B 45, 13792–13795 (1992). \n66. Yeo, B. S. & Bell, A. T. Enhanced activity of gold-supported cobalt oxide for the electrochemical evolution of oxygen. J. Am. Chem. Soc. 133, 5587–5593 (2011). \n67. Garcia, A. C., Touzalin, T., Nieuwland, C., Perini, N. & Koper, M. T. M. Enhancement of oxygen evolution activity of nickel oxyhydroxide by electrolyte alkali cations. Angew. Chem. Int. Ed. 58, 12999–13003 (2019). \n68. Bo, X., Li, Y., Chen, X. & Zhao, C. Operando Raman spectroscopy reveals Crinduced-phase reconstruction of NiFe and CoFe oxyhydroxides for enhanced electrocatalytic water oxidation. Chem. Mater. 32, 4303–4311 (2020). \n69. Iqbal, M. W., Shahzad, K., Akbar, R. & Hussain, G. A review on Raman finger prints of doping and strain effect in TMDCs. Microelectron. Eng. 219, 111152 (2020). \n70. Bloor, L. G., Molina, P. I., Symes, M. D. & Cronin, L. Low pH electrolytic water splitting using earth-abundant metastable catalysts that self-assemble in situ. J. Am. Chem. Soc. 136, 3304–3311 (2014). \n71. Wang, X.-F., You, Z. & Ruan, D.-B. A hybrid metal oxide supercapacitor in aqueous KOH electrolyte. Chin. J. Chem. 24, 1126–1132 (2006). \n72. Li, W. et al. A bio-inspired coordination polymer as outstanding water oxidation catalyst via second coordination sphere engineering. Nat. Commun. 10, 5074 (2019). \n\n73. Covington, A. K., Paabo, M., Robinson, R. A. & Bates, R. G. Use of the glass electrode in deuterium oxide and the relation between the standardized pD (paD) scale and the operational $\\mathrm{\\tt{pH}}$ in heavy water. Anal. Chem. 40, 700–706 (1968). \n\n# Acknowledgements \n\nThis work is partially supported by University of Wisconsin–Madison UW2020 Initiative and King Abdullah University of Science and Technology (KAUST) OSR-2017-CRG6- 3453.02. J. Z. H. thanks the China Scholarship Council (CSC) for fellowship support. B. S. thanks Natural Science Foundation of China (NSFC) Grant No. 51672057, 52072085, and 51722205 for support. H. S., R. D. R., and S. J. also thank the support from US NSF CHE-1955074. This research used resources of the Advanced Photon Source (APS), a US Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. The XAS experiments were performed at the APS Beamline 10-BM-B. The authors acknowledge use of facilities and instrumentation at the UW-Madison Wisconsin Centers for Nanoscale Technology partially supported by the NSF through the University of Wisconsin Materials Research Science and Engineering Center (DMR-1720415). \n\n# Author contributions \n\nJ. Z. H., B. S., and S. J. designed the experiments. J. Z. H. carried out the synthesis of catalysts, morphological and structural characterizations, and electrochemical measurements. H. S. collected the XPS spectra. J. Z. H. and H. S. collected the in situ Raman data. J. Z. H., H. S., and R. D. R. collected the ex situ XAS data at Advanced Photon Source in Argonne National Laboratory. J. Z. H. and S. J. wrote the manuscript. H. S., R. D. R., J. C. H., X. W., and B. S. performed the analysis and revised the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-23390-8. \n\nCorrespondence and requests for materials should be addressed to B.S. or S.J. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contributions to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41586-021-03217-8", + "DOI": "10.1038/s41586-021-03217-8", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03217-8", + "Relative Dir Path": "mds/10.1038_s41586-021-03217-8", + "Article Title": "Ligand-engineered bandgap stability in mixed-halide perovskite LEDs", + "Authors": "Hassan, Y; Park, JH; Crawford, ML; Sadhanala, A; Lee, J; Sadighian, JC; Mosconi, E; Shivanna, R; Radicchi, E; Jeong, M; Yang, C; Choi, H; Park, SH; Song, MH; De Angelis, F; Wong, CY; Friend, RH; Lee, BR; Snaith, HJ", + "Source Title": "NATURE", + "Abstract": "Lead halide perovskites are promising semiconductors for light-emitting applications because they exhibit bright, bandgap-tunable luminescence with high colour purity(1,2). Photoluminescence quantum yields close to unity have been achieved for perovskite nullocrystals across a broad range of emission colours, and light-emitting diodes with external quantum efficiencies exceeding 20 per cent-approaching those of commercial organic light-emitting diodes-have been demonstrated in both the infrared and the green emission channels(1,3,4). However, owing to the formation of lower-bandgap iodide-rich domains, efficient and colour-stable red electroluminescence from mixed-halide perovskites has not yet been realized(5,6). Here we report the treatment of mixed-halide perovskite nullocrystals with multidentate ligands to suppress halide segregation under electroluminescent operation. We demonstrate colour-stable, red emission centred at 620 nullometres, with an electroluminescence external quantum efficiency of 20.3 per cent. We show that a key function of the ligand treatment is to 'clean' the nullocrystal surface through the removal of lead atoms. Density functional theory calculations reveal that the binding between the ligands and the nullocrystal surface suppresses the formation of iodine Frenkel defects, which in turn inhibits halide segregation. Our work exemplifies how the functionality of metal halide perovskites is extremely sensitive to the nature of the (nullo)crystalline surface and presents a route through which to control the formation and migration of surface defects. This is critical to achieve bandgap stability for light emission and could also have a broader impact on other optoelectronic applications-such as photovoltaics-for which bandgap stability is required.", + "Times Cited, WoS Core": 421, + "Times Cited, All Databases": 439, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000626921700012", + "Markdown": "# Article \n\n# Ligand-engineered bandgap stability in mixed-halide perovskite LEDs \n\nYasser Hassan1,15 ✉, Jong Hyun Park2,15, Michael L. Crawford3, Aditya Sadhanala1,4,5, Jeongjae Lee6, James C. Sadighian3, Edoardo Mosconi7, Ravichandran Shivanna5, Eros Radicchi7,8, Mingyu Jeong9, Changduk Yang9, Hyosung Choi10, Sung Heum Park11, Myoung Hoon Song2, Filippo De Angelis7,8,12, Cathy Y. Wong3,13,14 ✉, Richard H. Friend5, Bo Ram Lee11 ✉ & Henry J. Snaith1 ✉ \n\nCheck for updates \n\nLead halide perovskites are promising semiconductors for light-emitting applications because they exhibit bright, bandgap-tunable luminescence with high colour purity1,2. Photoluminescence quantum yields close to unity have been achieved for perovskite nanocrystals across a broad range of emission colours, and light-emitting diodes with external quantum efficiencies exceeding 20 per cent—approaching those of commercial organic light-emitting diodes—have been demonstrated in both the infrared and the green emission channels1,3,4. However, owing to the formation of lower-bandgap iodide-rich domains, efficient and colour-stable red electroluminescence from mixed-halide perovskites has not yet been realized5,6. Here we report the treatment of mixed-halide perovskite nanocrystals with multidentate ligands to suppress halide segregation under electroluminescent operation. We demonstrate colour-stable, red emission centred at 620 nanometres, with an electroluminescence external quantum efficiency of 20.3 per cent. We show that a key function of the ligand treatment is to ‘clean’ the nanocrystal surface through the removal of lead atoms. Density functional theory calculations reveal that the binding between the ligands and the nanocrystal surface suppresses the formation of iodine Frenkel defects, which in turn inhibits halide segregation. Our work exemplifies how the functionality of metal halide perovskites is extremely sensitive to the nature of the (nano)crystalline surface and presents a route through which to control the formation and migration of surface defects. This is critical to achieve bandgap stability for light emission and could also have a broader impact on other optoelectronic applications—such as photovoltaics— for which bandgap stability is required. \n\nThe bandgap of metal halide perovskites can be tuned by several means, such as quantum confinement7–10 in nanocrystals5,6 and in two-dimensional perovskites11–14, or by varying the halide composition in the $\\mathbf{ABX}_{3}$ perovskite stoichiometry, where A is an organic ammonium or alkali metal cation, B is a group 14 metal cation (typically lead) and ${\\sf X}_{3}$ are halide anions5,6,15–17. Using a mixture of iodide and bromide ions, nanocrystals with red emission between $615\\mathsf{n m}$ and ${\\mathsf{640n m}}-\\mathbf{\\mathsf{as}}$ required for displays—can be obtained with a photoluminescence quantum yield (PLQY) approaching unity5,6,15,16. However, these nanocrystals are susceptible to halide segregation on photoexcitation and on the application of electrical bias5,18–20. Despite much effort, colour-stable red electroluminescence from mixed-halide perovskite nanocrystals has not yet been realized5,11–15,17,21–28. \n\nRecent investigations have suggested that halide segregation occurs through the diffusion of vacancy and interstitial defects18,19. In mixed-halide perovskite films measured experimentally and in pure iodide systems studied computationally, halide defects seem to migrate to grain boundaries or to crystal surfaces29–34. For polycrystalline films, improvements in bandgap stability and device efficiency have been achieved by passivating grain boundaries with alkali-metal halides or with larger organic ammonium cations7,8,11,17,27,35. For nanocrystals, interfacial passivation is of particular importance because of the high surface-area-to-volume ratio of nanocrystals and reports that halide segregation can occur both within (intra) and between (inter) nanocrystals20,36. One approach to resolving the issue of halide segregation in nanocrystals could involve a surface treatment that removes or immobilizes surface defects5,15. \n\n![](images/0a16ffdcf90dd12ef5b12e5f07717898774baf859f064bef0a6a621b36595baa.jpg) \nFig. 1 | Nanocrystal synthesis. a, Synthesis and ligand treatment steps: the dissolution of perovskite precursors in acetonitrile and methylamine; nanocrystal synthesis using a modified ligand-assisted re-precipitation method; and post-synthetic ligand treatment. b, Chemical structures of the ligands used. \n\nHere we synthesized MAPb $\\mathrm{\\DeltaI}_{x}\\mathrm{Br}_{1-x}\\mathrm{\\partial}\\mathbf{\\x}\\mathrm{\\partial}$ nanocrystals (where MA is methylammonium) using a modified ligand-assisted re-precipitation method5. After purification, we treated the nanocrystals with the ligands ethylenediaminetetraacetic acid (EDTA) and reduced l-glutathione (Fig. 1). These molecules bind strongly to lead in biological systems37–40. To assess the effect of the ligand treatment, we analysed time-resolved photoluminescence spectroscopy, PLQY, attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS) and $\\mathsf{x}$ -ray diffraction (XRD) measurements (Fig. 2, Extended Data Fig. 1). \n\n![](images/32f0a592fdde4b85badd661553030743fab05e7f60873213cdd521bc7057b537.jpg) \nFig. 2 | Effect of ligand treatment on the solution photoluminescence and the structural properties of the nanocrystals. a, Absorption and \n\nAs-synthesized MAPb $\\mathrm{\\Delta}[\\mathrm{\\mathbf{\\Omega}}_{x}\\mathrm{Br}_{1-x}]_{3}$ nanocrystals in toluene exhibit photoluminescence centred at $642\\mathsf{n m}$ (Fig. 2a). After treatment with glutathione, we observed an increase in intensity of the photoluminescence peak and a blueshift to $625\\mathrm{nm}$ (Fig. 2b). With EDTA, an increase in photoluminescence intensity was accompanied by a slight blueshift to $635\\mathsf{n m}$ . Using an equimolar mixture of EDTA and glutathione, hereafter denoted $\\mathbf{E}{+}\\mathbf{G}$ , we observed emission at $630\\mathrm{nm}$ and an increase in photoluminescence intensity, PLQY and decay lifetime (Fig. 2b, c, photoluminescence spectra of as-synthesized $\\begin{array}{r}{\\mathbf{MAPb}(\\mathbf{I}_{1-x}\\mathbf{Br}_{x})_{3}}\\end{array}$ nanocrystals in solution. b, Photoluminescence spectra of nanocrystal films before and after post-synthetic treatment with glutathione, EDTA and ${\\mathsf{E}}{+}{\\mathsf{G}}.{\\mathsf{c}}$ , Dependence of PLQY of the nanocrystal thin films on excitation fluence before and after ligand treatment, measured in an integrating sphere. d, e, HR-TEM images of neat nanocrystals (d) and nanocrystals after treatment with $\\mathbb{E}{+}\\mathbb{G}$ (e). f, XRD spectra of the nanocrystal films before and after ligand treatment. g, h, DADS from a global fit of TAS measurements of neat (g) and $\\mathbf{E}{+}\\mathbf{G}$ -capped (h) nanocrystals. Solid and dashed lines are spectra before and after 30 s exposure to a 7.1 W $\\mathrm{'cm}^{-2}405\\mathrm{nm}$ continuous-wave laser, respectively. Blue, green and red traces correspond to decay components with time constants of approximately 400 fs, 14 ps and 280 ps, respectively. Red arrows indicate the red edge of the spectra, where changes in the bandgap of the material would result in changes to the bleaching of the sample due to band filling. a.u., arbitrary units. \n\n# Article \n\n![](images/895f50b436fc66b6f7536c2a90b1485981e9d0555c71593ded808ed379f66abb.jpg) \n\nFig. 3 | Characterization of mixed-halide MA $\\mathbf{\\nabla}\\mathbf{\\cdot}\\mathbf{b}(\\mathbf{I}_{1-x}\\mathbf{Br}_{x})_{3}\\mathbf{NC}$ -LED devices. a, Schematic of the MAPb $(\\mathsf{I}_{1-x}\\mathsf{B r}_{x})_{3}$ NC-LED architecture and an SEM image showing the cross-section of a device. The thicknesses of each layer, as confirmed by SEM, are as follows: PEDOT:PSS/poly-TPD/TFB hole-transporting layer (HTL) $(30\\mathsf{n m})$ , perovskite nanocrystal emission layer $(20\\mathsf{n m})$ , TPBi electron-transporting layer $(70\\mathsf{n m})$ , LiF/Al electrode $\\left(80\\mathsf{n m}\\right)$ ). ITO, indium tin oxide; PEDOT:PSS, poly(3,4-ethylenedioxythiophene): poly( $\\dot{}p$ -styrene sulfonate; TBPi, $2,2^{\\prime},2^{\\prime\\prime}\\cdot$ (1,3,5- benzinetriyl)-tris(1-phenyl-1H-benzimidazole; poly-TPD; poly( $\\mathbf{\\dot{\\xi}}N,N^{\\prime}$ –bis(4-butylphenyl)-N,N′- bisphenylbenzidine); TFB, poly((9,9-dioctylfluorenyl-2, 7-diyl)-co-(4,4′-(N-(4-s-butylphenyl)diphenylamine)). b, Energy band diagram of the materials used in these LEDs, showing bandgap values (in eV from vacuum) from refs. 47–49. c–e, Operational characteristics for LEDs incorporating neat and $\\mathbf{E}{+}\\mathbf{G}$ -treated nanocrystal layers. c, Current density– voltage $(J-V)$ and luminance–voltage (L–V) curves; d, EQE–current density curves; e, device performance parameters of best-performing LEDs. LE, luminous efficiency. f, Electroluminescence spectra at different time intervals of LEDs held at a constant current density of $\\mathsf{i}.5\\mathsf{m A c m}^{-2}$ . g, Electroluminescence spectra at different current densities $\\mathsf{\\Lambda}(\\mathsf{m A c m}^{-2})$ . \n\nExtended Data Fig. 1); this is consistent with ligand treatment resulting in a decrease in the total number of active defects. These data suggest that, of the ligand treatments we tested, $_{\\mathsf{E}+\\mathsf{G}}$ is the most favourable for suppressing non-radiative recombination. High-resolution transmission electron microscopy (HR-TEM) images show that $_{\\mathsf{E}+\\mathsf{G}}$ -treated nanocrystals are smaller than untreated, ‘neat’ nanocrystals (average cubic dimensions of $12{\\pm}1.7$ nm and $16.3\\pm2\\mathrm{nm}$ , respectively; Fig. 2d, e, Extended Data Fig. 2). For weakly confined excitons, the exciton energy is linearly dependent on the inverse square of the nanocrystal width. A blueshift in emission, consistent with quantum confinement and lattice relaxation, has been measured for perovskite nanoparticles within this size range41. Furthermore, we have previously observed a blueshift in emission of up to $80\\mathsf{n m}$ due to quantum confinement effects in similarly sized $\\mathsf{M A P b l}_{3}$ nanocrystals5. We therefore expect the reduction in nanocrystal size as a result of ligand treatment to increase quantum confinement, contributing to the observed blueshift in emission41. \n\nUsing XPS (Extended Data Fig. 1), we find that the I:Br ratio decreases from 2:1 in the precursor solution to approximately 2:3 in the synthesized nanocrystals. For this composition, we would expect a bulk emission at 647–655 nm. After ligand treatment, we observed a minor enrichment in bromide content, which would account for the up to 8 nm blueshift in emission of the $_{\\mathsf{E}+\\mathsf{G}}$ -treated sample42. On the basis of experiments in which the halide composition of polycrystalline $\\mathsf{M A P b}(\\mathsf{I}_{1-x}\\mathsf{B r}_{x})_{3}$ films was varied42, we would also expect a change in lattice constant of approximately 0.019 Å per 10 nm shift in the position of the photoluminescence peak; however, XRD measurements revealed a cubic lattice constant of $\\mathbf{\\bar{6.05\\mathring{A}}}$ for the nanocrystal films both before and after ligand treatment (Fig. 2f). Collectively, these results suggest that both compositional changes and confinement effects influence the position of the emission peak. \n\nTo assess whether ligand treatment suppresses halide segregation and improves bandgap stability, we performed transient absorption spectroscopy (TAS) (Extended Data Fig. 3). We measured neat and $_{\\mathsf{E}+\\mathsf{G}}$ -treated nanocrystal films, as-prepared and after exposure to a $405\\cdot\\mathsf{n m}$ laser. A global fit of the signal yields decay-associated difference spectra (DADS) (Fig. 2g, h). The sub-ps decay measured using TAS arises from bandgap renormalization, Auger recombination and carrier cooling43. Carriers accumulate near the band edge, causing optical bleaching at these energies. The longest decay measured by TAS originates from carrier recombination. After irradiation for 30 s, spectra of the neat sample displayed a new low-energy bleach, which was visible in the longest DADS component. By contrast, the DADS line-shape for the $_{\\mathsf{E}+\\mathsf{G}}$ -treated sample remained approximately unchanged after irradiation. The emergence of the low-energy bleach in the neat sample is consistent with the emergence of lower-bandgap iodide-rich minority phases, from which charge carriers recombine; this is suppressed in the $_{\\mathsf{E}+\\mathsf{G}}$ treated sample. \n\nFig. 4 | Characterization of interactions between the ligands and the nanocrystal surface using NMR spectroscopy. a, The structures of EDTA and glutathione. a and b label ${\\mathrm{CH}}_{2}$ groups of EDTA whereas α, $\\upbeta$ and γ label ${\\mathrm{CH}}_{2}$ groups in glutathione; see c for their corresponding NMR peaks. b, $^{13}{\\mathsf C}$ solid-state NMR spectra of neat and ligand (glutathione, EDTA, $\\mathbf{E}{+}\\mathbf{G}^{\\prime}$ )-treated \n\nHalide segregation between nanocrystals would result in the formation of Br-rich and I-rich nanocrystals. This has been observed in other perovskite nanocrystals and can result in a second, higher-energy photoluminescence emission in addition to the redshifted photoluminescence20,36. In Extended Data Fig. 4 we show that, even at very low nanocrystal concentrations in a polymer matrix, we observe redshifted emission with no growth of a high-energy peak nor broadening of the high-energy emission shoulder after irradiation. Confocal photoluminescence measurements on such films reveal a redshifted emission under illumination, which seems to arise from single nanocrystals. The lack of a high-energy feature in the transient absorption spectra of illuminated neat nanocrystals also indicates that Br-rich nanocrystals are not forming, suggesting that segregation can occur within individual nanocrystals. \n\n![](images/aca3425f4d07804de6760adddd431d2143197019505c61c6816715397de0e7da.jpg) \nnanocrystals. The insets show the structures of the ligands. c, Solution 1H NMR spectra of $\\mathbf{\\tilde{E}{+}G}$ with and without $\\mathsf{P b l}_{2}$ in $d_{6}$ -DMSO solution. d, The proposed molecular interactions of glutathione and EDTA with $\\mathsf{P b}^{2+}$ atoms on the nanocrystal surface. \n\nWe next assess the effect of ligand treatment on light-emitting diodes fabricated from these nanocrystals (NC-LEDs). We find that both EDTA and glutathione considerably suppress the halide segregation and improve bandgap stability, but EDTA-treated NC-LEDs exhibit a small broadening in the emission spectra during operation. Conversely, glutathione-treated NC-LEDs show the most stable emission spectra but a lower device efficiency. Efficient and colour-stable NC-LEDs were achieved with $_{\\mathsf{E}+\\mathsf{G}}$ treatment (Extended Data Fig. 5). To better understand the role of each ligand, we performed a second ligand-treatment step using the soft Lewis base 1-adamantanecarboxylic acid (ADAC). EDTA-, glutathione- and $_{\\mathsf{E}+\\mathsf{G}}$ -treated NC-LEDs show a negligible peak shift and small spectral broadening during operation. After subsequent treatment with ADAC, the EDTA- and $\\mathbf{E}{+}\\mathbf{G}.$ -treated nanocrystals exhibit more substantial peak shifting and broadening. By contrast, glutathione-treated \n\nNC-LEDs show stable electroluminescence, even after treatment with ADAC. These observations indicate that glutathione is more strongly bound to the nanocrystal surface than is EDTA; however, EDTA seems to be important for achieving the highest device efficiencies. \n\nWhen choosing charge-injection layers and optimizing the performance of the LEDs, we found that maximizing the PLQY of half-constructed devices resulted in an effective selection of materials (Extended Data Figs. 6, 7). A schematic of our final device stack and a scanning electron microscopy (SEM) cross-sectional image are shown in Fig. 3a, b. We observed higher current densities in $\\mathsf{E}{+}\\mathsf{G}$ -treated NC-LEDs compared to those treated with other ligands, and considerably improved external quantum efficiencies (EQEs) (Fig. 3c, d). We measured a maximum EQE of $20.3\\%$ at a current density of around $0.1\\mathsf{m A}\\mathsf{c m}^{-2}$ and an emission wavelength of approximately $620\\mathrm{nm}$ , placing these red perovskite LEDs in the same quantum efficiency range as commercial organic light-emitting diodes. Considering the PLQY of isolated perovskite nanocrystal films on glass, the refractive index of the perovskite layer, optical outcoupling and photon recycling, we estimate an internal PLQY of 0.88 (see Methods44). The effect of photon recycling and optical outcoupling in complete perovskite LEDs has previously been quantified, showing that EQEs of more than $20\\%$ are feasible for perovskite emission layers with high internal PLQY45. \n\nThe most pressing challenge in the fabrication of red-emitting metal halide perovskites is achieving bandgap stability. In Fig. 3f, g we show the emission spectra of LEDs operating at a fixed current density over time and over a range of current densities, respectively. For the neat NC-LEDs held at a constant current density of $1.5\\mathsf{m A}\\mathsf{c m}^{-2}$ measured \n\n# Article \n\nover 20 min, we observed a broadening of the emission peak and the emergence of a shoulder at around $680\\mathrm{nm}$ . Similar results were obtained during measurements at current densities of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ (Extended Data Fig. 8). These observations are consistent with halide segregation driven by electrical biasing and/or current injection during LED operation and resulting in lower-energy emission from iodide-enriched regions. By contrast, the emission spectrum for the $\\mathbf{E}{+}\\mathbf{G}$ -treated NC-LEDs is stable at ${620}\\mathrm{nm}$ under the same operating conditions and duration. We note, however, that the absolute electroluminescence intensity decays over time. Extended Data Fig. 8 shows the luminance as a function of time for $_{\\mathsf{E}+\\mathsf{G}}$ -treated NC-LEDs held at current densities of 0.1, 1 and $10\\mathrm{mA}^{-2}$ . The time taken for the luminance to decay to $50\\%$ of its initial value $(T_{50})$ decreased from 340 to 130 to 16 min, respectively, with increasing current density. These findings indicate that, although we have achieved colour-stable red emission, the challenge to deliver long-term stability in terms of absolute brightness and efficiency remains. \n\nTo understand the origin of the improvement in device performance when using ligand-treated nanocrystals, we needed to identify the key ligand–perovskite interactions that stabilize the nanocrystal surface. To this end, we performed solid-state $^{13}\\mathsf{C}$ nuclear magnetic resonance (NMR) studies on the nanocrystals both before and after treatment with $\\mathbf{E}{+}\\mathbf{G}$ . The resulting data (Fig. 4a, b) show a clear peak at $130.2\\mathsf{p p m}$ , which arises from the double-bonded carbons in the oleic acid and oleylamine molecules. This peak, alongside the aliphatic $\\mathbf{-CH}_{2}-$ peaks (30–27 ppm), clearly indicates the presence of oleic acid and oleylamine on the nanocrystal surface even after treatment with EDTA, glutathione or $_{\\mathsf{E}+\\mathsf{G}}$ ; the nonpolar chains of these remaining oleic acid and oleylamine molecules probably ensure the solubility of the nanocrystals in toluene after the ligand treatment. The absence of EDTA peaks in the EDTA-treated sample shows that the amount of EDTA on the nanocrystal surface is below the NMR detection limit; however, clear peaks arising from the carbonyl and $\\mathfrak{a}$ -carbonyl groups of glutathione confirm its presence in the glutathione-treated sample. The peak at 38 ppm suggests the presence of oxidized glutathione; this could indicate that the reduction of some species on the perovskite surface could form part of the active role of glutathione, although this remains speculative. A key function of glutathione and EDTA ligands can be inferred from their $\\mathsf{P b}$ -binding ability: both ligands are known to bind strongly to Pb, as shown by solution-state NMR studies (Fig. 4c, Extended Data Fig. 9, Methods). \n\nFigure 4d shows the proposed molecular interactions of EDTA and glutathione with $\\mathsf{P b}^{2+}$ on the nanocrystal surface. We postulate that part of the role of these ligands is to remove undercoordinated lead from the nanocrystal surface, resulting in an electronically ‘cleaner’ surface with fewer defects. This ‘stripping’ action is consistent with the reduction in nanocrystal size upon ligand treatment, the existence of Pb–EDTA and Pb–glutathione complexes in solution, and the large binding energy of EDTA and glutathione to Pb (Extended Data Fig. 10). Some of the excess ligands could then bind to the remaining Pb on the ‘cleaned’ perovskite surface, further decreasing the concentration of defects. \n\nTo gain further understanding of ligand binding, we modelled the interaction of glutathione and EDTA with the $\\mathsf{M A P b l}_{3}$ surface using density functional theory (DFT) (Fig. 5). We consider a $\\mathsf{P b l}_{2}$ -terminated surface as representative of an unpassivated perovskite surface with exposed, undercoordinated Pb atoms. We decomposed glutathione and EDTA into their possible binding moieties and calculated the binding energy of each ligand to the perovskite surface (Extended Data Fig. 10). The binding energy is defined as Eb = Eligand@surface $-E_{\\mathrm{ligand}}-E_{\\mathrm{surface.}}$ , where the latter three terms are the energy of the surface and bound ligand, the energy of the isolated ligand, and the energy of the bare surface, respectively. Our calculated binding energy for glutathione, at $-1.85\\mathrm{eV,}$ is large compared to the calculated values for acetic acid $\\left(-0.58\\mathrm{eV}\\right)$ or for methylamine $(-0.84\\mathrm{eV})$ , which are representative of the carboxylic acid and primary amine binding moieties of glutathione. We deduce that the large binding energy is a result of contributions from multiple binding moieties. The binding energy determined for EDTA was also large $(-1.60\\mathrm{eV})$ , although slightly less than that of glutathione, with steric hindrance limiting binding through the tertiary amine group; this is also consistent with the observation of only glutathione in the $^{13}{\\bf C}$ solid-state NMR spectra of $\\mathbf{\\bar{E}}{+}\\mathbf{G}$ -treated nanocrystals (Fig. 4a). \n\n![](images/bf9bfb174f1d4dad3084d9812c0550569435269d5f33a5dcb0d91e5010dae055.jpg) \nFig. 5 | Optimized structures of interacting surface-adsorbed ligands. a–c, Optimized structures of glutathione (a), EDTA (b) and one glutathione and one EDTA molecule (c) on the perovskite surface along with calculated total binding energies $(E_{\\mathrm{{b}}})$ and their intermolecular contribution $(\\Delta E_{\\mathrm{inter}})$ in eV calculated with respect to the isolated surface-adsorbed molecules ( $\\cdot E_{\\mathrm{b}}{=}1.85$ eV and 1.60 eV for glutathione and EDTA, respectively). d, Optimized structure of an iodine Frenkel defect pair (defective sites highlighted by red and blue circles) in the presence of adsorbed EDTA and glutathione. The value shown is the increase in defect formation energy compared to the unpassivated surface $(\\Delta E_{\\mathrm{Frenkel}})$ . \n\nWe further evaluate the binding energy of two interacting glutathione molecules, two interacting EDTA molecules, and an interacting $\\mathbf{E}{+}\\mathbf{G}$ pair on the perovskite surface (Fig. 5, Extended Data Fig. 10). The $\\mathbf{E}{+}\\mathbf{G}$ pair has the largest binding energy, enhanced by a synergistic effect between glutathione and EDTA; intermolecular hydrogen bonding between the carboxylic groups of glutathione and EDTA provides extra stabilization to these surface-adsorbed molecules, leading to a binding energy of −4.45 eV (Extended Data Fig. 10). \n\nOur calculations confirm that this specific pairing of ligands has a strong affinity with the perovskite surface. We now assess how this influences the migration of halide species. Iodine Frenkel defects, which are iodide interstitial-vacancy pairs, are the most energetically probable defects at the $\\mathsf{P b l}_{2}$ -terminated perovskite surface owing to their low formation energy (0.03 eV). We calculate the formation energy of an iodine Frenkel defect at the $\\mathsf{P b l}_{2}$ -terminated perovskite surface in the presence of glutathione, $_{\\mathsf{E}+\\mathsf{G}}$ , or without passivating molecules (Methods). We find that passivation of the surface with glutathione raises the formation energy of the iodine Frenkel defects to $0.15\\mathrm{eV},$ whereas with $_{\\mathsf{E}+\\mathsf{G}}$ it is further increased to 0.18 eV. This is substantially higher than the calculated values for other passivating agents. For example, in the presence of polyethylene oxide, the formation of an interstitial iodine defect becomes less favourable by 0.08 eV compared to the bare perovskite surface32. To summarize, the large calculated binding energy, coupled with the substantial increase in formation energy of iodide Frenkel defects, suggests that glutathione and the combination of EDTA and glutathione markedly inhibit undercoordinated Pb atoms from stabilizing these Frenkel defects46. Because halide Frenkel defects are expected to be the ionic species responsible for halide segregation under illumination or during device operation, our results are consistent with reduced defect formation suppressing halide segregation in $_{\\mathsf{E}+\\mathsf{G}}$ -treated nanocrystals. \n\nIn conclusion, we have demonstrated that treatment with a lead-complexing multidentate ligand leads to bandgap-stable red electroluminescence from mixed-halide perovskite NC-LEDs, with a maximum EQE at $620\\mathrm{nm}$ of greater than $20\\%$ . We have found that stripping the nanocrystal surface of defects is an active role of these ligands. Furthermore, we have shown that both ligand–ligand and ligand–surface interactions are important to achieve a stable ligand shell on the nanocrystal surface, and that interactions of the multidentate ligand with the surface markedly suppress the formation of surface defects. Beyond light emission, this work is likely to be broadly applicable to stabilizing the bandgap of mixed-ion metal halide perovskites for a range of applications, such as multi-junction photovoltaics, and should help to expand the development of perovskites as versatile and tunable semiconductors. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03217-8. \n\n1. Lin, K. et al. Perovskite light-emitting diodes with external quantum efficiency exceeding 20 per cent. Nature 562, 245–248 (2018). \n2. Xiao, Z. et al. Efficient perovskite light-emitting diodes featuring nanometre-sized crystallites. Nat. Photonics 11, 108–115 (2017). \n3. Zhao, X. & Tan, Z.-K. Large-area near-infrared perovskite light-emitting diodes. Nat. Photonics 14, 215–218 (2020). \n4. Zhao, B. et al. High-efficiency perovskite–polymer bulk heterostructure light-emitting diodes. Nat. Photonics 12, 783–789 (2018). \n5. Hassan, Y. et al. Facile synthesis of stable and highly luminescent methylammonium lead halide nanocrystals for efficient light emitting devices. J. Am. Chem. Soc. 141, 1269–1279 (2019). \n6. Draguta, S. et al. Rationalizing the light-induced phase separation of mixed halide organic–inorganic perovskites. Nat. Commun. 8, 200 (2017). \n7. Tian, Y. et al. Highly efficient spectrally stable red perovskite light-emitting diodes. Adv. Mater. 30, 1707093 (2018). \n8. Chang, J. et al. Enhanced performance of red perovskite light-emitting diodes through the dimensional tailoring of perovskite multiple quantum wells. J. Phys. Chem. Lett. 9, 881–886 (2018). \n9. Hassan, Y. et al. Structure-tuned lead halide perovskite nanocrystals. Adv. Mater. 28, 566–573 (2016). \n10.\t Burlakov, V. M., Hassan, Y., Danaie, M., Snaith, H. J. & Goriely, A. Competitive nucleation mechanism for $\\mathsf{C s P b B r}_{3}$ perovskite nanoplatelet growth. J. Phys. Chem. Lett. 11, 6535–6543 (2020). \n11. Wang, Z. et al. Efficient ambient-air-stable solar cells with 2D–3D heterostructured butylammonium-caesium-formamidinium lead halide perovskites. Nat. Energy 2, 17135 (2017). \n12.\t Zhou, Y. et al. Benzylamine-treated wide-bandgap perovskite with high thermalphotostability and photovoltaic performance. Adv. Energy Mater. 7, 1701048 (2017). \n13.\t Yan, J., Qiu, W., Wu, G., Heremans, P. & Chen, H. Recent progress in 2D/quasi-2D layered metal halide perovskites for solar cells. J. Mater. Chem. A 6, 11063–11077 (2018). \n14.\t Lee, D. S. et al. Passivation of grain boundaries by phenethylammonium in formamidinium–methylammonium lead halide perovskite solar cells. ACS Energy Lett. 3, 647–654 (2018). \n15.\t Zhang, X. et al. Bright perovskite nanocrystal films for efficient light-emitting devices. J. Phys. Chem. Lett. 7, 4602–4610 (2016). \n16.\t Chiba, T. et al. Anion-exchange red perovskite quantum dots with ammonium iodine salts for highly efficient light-emitting devices. Nat. Photonics 12, 681–687 (2018). \n17. Xiao, Z. et al. Mixed-halide perovskites with stabilized bandgaps. Nano Lett. 17, 6863–6869 (2017). \n18. Barker, A. J. et al. Defect-assisted photoinduced halide segregation in mixed-halide perovskite thin films. ACS Energy Lett. 2, 1416–1424 (2017). \n19. Meggiolaro, D., Mosconi, E. & De Angelis, F. Formation of surface defects dominates ion migration in lead-halide perovskites. ACS Energy Lett. 4, 779–785 (2019). \n20. Vashishtha, P. & Halpert, J. E. Field-driven ion migration and color instability in red-emitting mixed halide perovskite nanocrystal light-emitting diodes. Chem. Mater. 29, 5965–5973 (2017). \n21. Yang, Z. et al. Stabilized wide bandgap perovskite solar cells by tin substitution. Nano Lett. 16, 7739–7747 (2016). \n22. Bush, K. A. et al. Compositional engineering for efficient wide band gap perovskites with improved stability to photoinduced phase segregation. ACS Energy Lett. 3, 428–435 (2018). \n23. Yi, C. et al. Entropic stabilization of mixed A-cation $\\mathsf{A B X}_{3}$ metal halide perovskites for high performance perovskite solar cells. Energy Environ. Sci. 9, 656–662 (2016). \n24. Hu, M., Bi, C., Yuan, Y., Bai, Y. & Huang, J. Stabilized wide bandgap $\\mathsf{M A P b B r}_{x}|_{3-x}$ perovskite by enhanced grain size and improved crystallinity. Adv. Sci. 3, 1500301 (2016). \n25. Gualdrón-Reyes, A. F. et al. Controlling the phase segregation in mixed halide perovskites through nanocrystal size. ACS Energy Lett. 4, 54–62 (2019). \n26.\t Zhou, Y. et al. Composition-tuned wide bandgap perovskites: from grain engineering to stability and performance improvement. Adv. Funct. Mater. 28, 1803130 (2018). \n27. Abdi-Jalebi, M. et al. Maximizing and stabilizing luminescence from halide perovskites with potassium passivation. Nature 555, 497–501 (2018). \n28. Belisle, R. A. et al. Impact of surfaces on photoinduced halide segregation in mixed-halide perovskites. ACS Energy Lett. 3, 2694–2700 (2018). \n29.\t Zhang, L. & Sit, P. H. L. Ab initio study of the dynamics of electron trapping and detrapping processes in the $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ perovskite. J. Mater. Chem. A 7, 2135–2147 (2019). \n30.\t Li, W., Liu, J., Bai, F.-Q., Zhang, H.-X. & Prezhdo, O. V. Hole trapping by iodine interstitial defects decreases free carrier losses in perovskite solar cells: a time-domain ab initio study. ACS Energy Lett. 2, 1270–1278 (2017). \n31. Meggiolaro, D. et al. Iodine chemistry determines the defect tolerance of lead-halide perovskites. Energy Environ. Sci. 11, 702–713 (2018). \n32.\t Motti, S. G. et al. Controlling competing photochemical reactions stabilizes perovskite solar cells. Nat. Photonics 13, 532–539 (2019). \n33. Shao, Y. et al. Grain boundary dominated ion migration in polycrystalline organic– inorganic halide perovskite films. Energy Environ. Sci. 9, 1752–1759 (2016). \n34. Bischak, C. G. et al. Origin of reversible photoinduced phase separation in hybrid perovskites. Nano Lett. 17, 1028–1033 (2017). \n35. Wu, T. et al. High-performance perovskite light-emitting diode with enhanced operational stability using lithium halide passivation. Angew. Chem. Int. Ed. 59, 4099–4105 (2020). \n36. Zhang, H. et al. Phase segregation due to ion migration in all-inorganic mixed-halide perovskite nanocrystals. Nat. Commun. 10, 1088 (2019). \n37. Flora, S. J. S. & Pachauri, V. Chelation in metal intoxication. Int. J. Environ. Res. Public Health 7, 2745–2788 (2010). \n38. Ferrero, M. E. Rationale for the successful management of EDTA chelation therapy in human burden by toxic metals. BioMed Res. Int. 2016, 8274504 (2016). \n39. Mah, V. & Jalilehvand, F. Lead(II) complex formation with glutathione. Inorg. Chem. 51, 6285–6298 (2012). \n40. Hayes, J. D. & Pulford, D. J. The glutathione S-transferase supergene family: regulation of GST and the contribution of the isoenzymes to cancer chemoprotection and drug resistance part I. Crit. Rev. Biochem. Mol. Biol. 30, 445–520 (1995). \n41. Zhao, Q. et al. Size-dependent lattice structure and confinement properties in $\\mathsf{C s P b l}_{3}$ perovskite nanocrystals: negative surface energy for stabilization. ACS Energy Lett. 5, 238–247 (2020). \n42. Noh, J. H., Im, S. H., Heo, J. H., Mandal, T. N. & Seok, S. I. Chemical management for colorful, efficient, and stable inorganic–organic hybrid nanostructured solar cells. Nano Lett. 13, 1764–1769 (2013). \n43. Richter, J. M. et al. Ultrafast carrier thermalization in lead iodide perovskite probed with two-dimensional electronic spectroscopy. Nat. Commun. 8, 376 (2017). \n44.\t Richter, J. M. et al. Enhancing photoluminescence yields in lead halide perovskites by photon recycling and light out-coupling. Nat. Commun. 7, 13941 (2016). \n45. Cho, C. et al. The role of photon recycling in perovskite light-emitting diodes. Nat. Commun. 11, 611 (2020). \n46. Bodnarchuk, M. I. et al. Rationalizing and controlling the surface structure and electronic passivation of cesium lead halide nanocrystals. ACS Energy Lett. 4, 63–74 (2019). \n47. Sun, Q. et al. Bright, multicoloured light-emitting diodes based on quantum dots. Nat. Photonics 1, 717–722 (2007). \n48. Auer-Berger, M. et al. All-solution-processed multilayer polymer/dendrimer light emitting diodes. Org. Electron. 35, 164–170 (2016). \n49. Yan, F. et al. Highly efficient visible colloidal lead-halide perovskite nanocrystal light-emitting diodes. Nano Lett. 18, 3157–3164 (2018). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 \n\n# Article Methods \n\nAll nanocrystal syntheses were carried out under ambient conditions in a fume hood. \n\n# Materials \n\nAll chemicals were used as received without further purification. Lead iodide $(\\mathsf{P b l}_{2})$ $(99.99\\%)$ was purchased from TCI Chemicals; methylammonium iodide and methylammonium bromide from Dyesol; and oleic acid $(99.0\\%)$ , oleylamine $(70\\%)$ , methylamine (MA) solution $33\\%$ in absolute ethanol), EDTA (anhydrous, $299\\%$ ), and reduced l-glutathione $(\\geq98.0\\%)$ from Sigma-Aldrich. All solvents, such as toluene, acetonitrile, and methyl acetate, were anhydrous and were purchased from Sigma-Aldrich. PEDOT:PSS (AI 4083), poly-TPD, and TPBi were purchased from OSM. TFB was purchased from Ossila. \n\n# Preparation of lead mixed-halide perovskite precursor \n\nTypically, a perovskite precursor solution was prepared according to our recent work (ref. 5), in which $922{\\mathrm{mg}}$ of $\\mathsf{P b l}_{2}$ and $223\\mathrm{mg}$ of methylammonium bromide were mixed with $4\\mathrm{ml}$ of acetonitrile (ACN) and shaken to form a green–black suspension. Dry methylamine gas was bubbled through the suspension to form a compound solvent, referred to as ACN/MA, as detailed elsewhere (ref. 5). \n\n# Synthesis of MAPb $(\\mathbf{I}_{1-x}\\mathbf{B}\\mathbf{r}_{x})_{3}$ perovskite nanocrystals for red emission \n\nThe synthesis of the $\\mathsf{M A P b}(\\mathsf{I}_{1-x}\\mathsf{B r}_{x})_{3}$ nanocrystals was carried out by injecting $0.2{\\ensuremath{\\mathrm{ml}}}$ of perovskite precursor dissolved in ACN/MA into toluene at $60^{\\circ}\\mathsf{C}$ containing $2\\mathsf{m l}$ of oleic acid and $0.2\\mathrm{ml}$ oleylamine. The nanocrystals immediately nucleated, turning the suspension red. The reaction was continued for 1–2 min to allow for crystal growth before the nanocrystal suspension was immersed into an ice bath. We synthesized six batches of nanocrystals simultaneously, collected them into three centrifuge tubes (each containing $10\\mathrm{ml}$ of nanocrystals), and the nanocrystals were iteratively precipitated by adding $20\\mathsf{m l}$ of anhydrous methyl acetate. The nanocrystals were separated from excess unreacted ligands and precursors and purified by centrifugation at $8{,}500g$ for $10\\mathrm{{min}}$ , then re-dispersed into $5\\mathrm{ml}$ toluene. Methyl acetate $\\left(10\\mathsf{m l}\\right)$ was added to each tube and the purification process was repeated before the nanocrystals were re-dissolved in toluene to a concentration of $40\\mathrm{mg}\\mathrm{ml}^{-1}$ for further characterization. These purified nanocrystals, capped with oleic acid and oleylamine, are denoted as ‘neat nanocrystals’. These neat nanocrystals exhibit photoluminescence at $630\\mathrm{nm}$ , and their cubic phase was confirmed by powder XRD (Fig. 2f). \n\n# Ligand treatment of MAPb $(\\mathbf{I}_{1-x}\\mathbf{B}\\mathbf{r}_{x})_{3}$ perovskite nanocrystals \n\nThe nanocrystals underwent two washing cycles with a methyl acetate mixture, as described in the previous section. Each nanocrystal batch was dispersed in 2 ml of toluene after the washing process. Six batches of washed nanocrystals were combined to make a $12\\mathsf{m l}$ ( $40\\mathrm{{mg}\\mathrm{{ml}^{-1})}}$ stock solution. This solution was centrifuged once more at $3{,}500g$ for 5 min to remove aggregates and large particles. The collected supernatant was divided into two portions: one was used as the control neat sample and the other was treated with a new ligand. Typically, 2 mmol ligand was added to 3 ml nanocrystals in toluene and stirred overnight (around 12 h) at room temperature. The unreacted ligand powder was separated from the nanocrystals after ligand treatment by centrifugation at $8{,}500g$ for $10\\mathrm{{min}}$ . The collected supernatant was filtered using a PTFE syringe filter (Whatman, $0.2\\upmu\\mathrm{m})$ and stored for further characterization and device preparation. \n\n# MAPb $(\\mathbf{I}_{1-x}\\mathbf{B}\\mathbf{r}_{x})_{3}$ nanocrystals characterization \n\nUV−vis absorption spectra for nanocrystal solutions were recorded using a commercial Varian Cary 60 in a cuvette with a path length of 1 cm. Steady-state photoluminescence measurement of solutions was carried out with a spectrofluorometer (Fluorolog, Horiba Jobin Yvon), with a 450-W xenon lamp excitation source and a photomultiplier tube detector with an excitation wavelength of $450\\mathrm{nm}$ . The absorbance spectra of MAPb $(\\mathsf{I}_{1-x}\\mathsf{B r}_{x})_{3}$ nanocrystals films were measured using a UV–vis–near infrared spectrometer (Cary 5000, Agilent Technology). Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) spectrums were obtained using FTIR spectroscopy (Cary 670, Agilent Technology). The HR-TEM images were captured using JEM-2100F (JEOL). For the TEM sample, diluted nanocrystals solutions were dropped on the copper grid with 300-mesh carbon film. The XPS results were obtained using a spectrometer (ESCALAB 250Xi, Thermo Fisher Scientific) with a monochromatic Al–Kα X-ray source. The confocal photoluminescence images and spectra were obtained using a laser scanning confocal microscope (LSM 780 NLO, Zeiss). The ultraviolet photoemission spectra were carried out using an AXIS Nova (Kratos Analytical) with a He (21.2 eV) ultraviolet source. \n\n# Transient absorption spectroscopy of MAPb $(\\mathbf{I}_{1-x}\\mathbf{B}\\mathbf{r}_{x})_{3}$ nanocrystals \n\nA Ti:sapphire laser (Coherent Astrella) operating at 1 kHz pumped an optical parametric amplifier (Light Conversion, Topas Prime Plus) to generate ${520}{\\cdot}\\mathrm{nm}$ pump pulses. The $800-\\mathsf{n m}$ fundamental was used to generate white light probe pulses in a sapphire plate. The pump pulse energy in TAS was $106\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ . The broadband probe pulse energies were $124\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ and $146\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ for the $\\mathbf{E}{+}\\mathbf{G}$ -treated and neat nanocrystal films, respectively. Transient absorption spectra were collected using an instrument constructed in-house, with 100-fs time resolution and pump–probe time delays of up to 800 ps. The TAS signal at alternate time delays was collected in ascending order, and the signal at the remaining time delays in descending order, to ensure that any changes in the sample during the scan were not systematically encoded into the transient. Each scan required 50 s. For each film, 72 TAS spectra were measured before 30 s of exposure to a 405-nm continuous-wave laser with the power density set at $7.09\\mathsf{W}\\mathsf{c m}^{-2}$ . The $405\\cdot\\mathrm{{nm}}$ laser also acted as the excitation source for the measurement of fluorescence spectra. Fluorescence was collected through a fibre optic cable (Thorlabs M53L01) by a portable spectrometer (Ocean Optics, Flame-T). After completing the exposure, the TAS instrument was initialized, a process that requires $40{\\mathsf{s}}.$ . TAS scans were then collected, with a few seconds of exposure to the 405-nm continuous-wave laser before and after each scan to compensate for the recovery of the halide migration during the TAS scan. This procedure was repeated for 60 TAS scans (Extended Data Fig. 3). \n\nAbsorbance, fluorescence and TAS measurements were performed on oleic acid/oleylamine-capped and $\\mathbf{E}{+}\\mathbf{G}$ -capped nanocrystals in spin-cast encapsulated films. The average wavelength of the fluorescence immediately before and after each TAS scan was used to estimate the average fluorescence wavelength during the scan. This estimates the average amount of halide segregation over 60 TAS scans. The duration of exposure to the $405\\cdot\\mathrm{{nm}}$ light after each scan was set to minimize the change in the average fluorescence wavelength during the 60 TAS scans, shown in Extended Data Fig. 3. TAS measurements were performed on different spots on each film using different durations of 405-nm exposure between TAS scans until a small standard deviation in the average fluorescence wavelength was achieved. This indicated that, with this additional irradiation, the nanocrystals did not undergo further halide segregation nor recovery of segregation during the 60 TAS scans. \n\n# Time-resolved photoluminescence spectra measurement \n\nThe time-resolved photoluminescence spectra of the MAPb $(\\mathsf{I}_{1-x}\\mathsf{B r}_{x})_{3}$ nanocrystals were measured using a fluorescence lifetime spectrometer (Fluo Time 300, PicoQuant). The samples were photoexcited using a 450-nm diode laser head (LDH-D-C-450, PicoQuant) coupled to a PDL 820 laser drive. The photons emitted from the nanocrystals were collected using a PicoHarp TCSPC module with a photomultiplier detector and monochromator (PMA-C 182-N-M). \n\n# Estimation of the EQE limit \n\nOur observed EQE of greater than $20\\%$ seems to be the limit of what is feasible when considering optical outcoupling efficiencies from perovskite thin films in LED device structures4. However, the precise outcoupling efficiency depends strongly upon the refractive index of the emission layer, and furthermore, photon recycling can contribute to enabling waveguided light to be reabsorbed and externally emitted from the device. To quantify this in more detail, we first estimated the refractive index of our nanocrystal films using spectroscopic ellipsometry as $n{\\approx}1.82$ at ${620}\\mathrm{nm}$ . Considering a thin film on glass, with $n{=}1.82$ , and accounting for emission from both the perovskite–air and perovskite–glass interfaces, we determine an outcoupling efficiency of $32.4\\%$ . Our observations of a PLQY of $70\\%$ for such films is clearly in excess of this, but can be understood by accounting for photon recycling, following the procedure in ref. 44. For our films, with an outcoupling efficiency of $32.4\\%$ and an external PLQY of $70\\%$ , we estimate an internal PLQY of $87.8\\%$ (further details are shown in the calculation below). For the LEDs, this calculation is slightly more complicated because there are a larger number of material layers, there is a reflective rear electrode, and parasitic absorption can occur in the charge-injection layers and in the electrode materials45. However, detailed calculations have been made for organic light-emitting diodes with very similar device stacks and refractive indices of the materials used, including the emission layer at $n{\\approx}1.8$ . Putting our internal PLQY of $87.8\\%$ into the average calculated escape cone efficiencies in ref. 50 results in an estimated EQE for electroluminescence of $27\\%$ . Therefore, our measured EQE of $20\\%$ is entirely feasible. \n\n# Details of the internal PLQY calculation \n\nSee also ref. 44. The PLQY of a perovskite film coated upon a glass slide is measured in an integrated sphere. The light is isotopically emitted within the perovskite film, and a certain fraction emitted within a specific solid angle will escape from the front and back surface of the film, with a considerable fraction of the light totally internally reflected and reabsorbed in the plane of the film. Because the overlap of emission and absorption spectra is considerable for these perovskite materials, we estimate that within a few tens of micrometres, more than $90\\%$ of the waveguided light will be reabsorbed and therefore very little light will be emitted from the edges of perovskite film coated on the $2\\times2$ cm glass slides. The analysis that we set out below, which includes realistic parameters, determines the relationship between measured PLQY and internal PLQY. The probability for a photon that is isotopically emitted from within one medium to be transmitted through an interface between the medium within which it was emitted and the adjacent medium, with refractive indices $n_{1}$ and $n_{2}^{\\mathrm{~~}}$ , respectively, can be estimated as \n\n$$\nn_{\\mathrm{trans}}=\\frac{\\Omega_{\\mathrm{esc}}}{4\\uppi}T\\approx\\frac{n_{2}^{3}}{n_{1}(n_{1}+n_{2})^{2}}\n$$ \n\nwhere $\\varOmega_{\\mathrm{esc}}$ is the escape solid angle and $T$ is the transmittance. Ellipsometry measurements estimate the refractive index of perovskite nanocrystal films to be around 1.82 at ${620}\\mathsf{n m}$ . Taking the refractive indices of air, glass and the perovskite nanocrystal film to be 1, 1.5 and 1.82, respectively, using the above equation we estimate the probability for a photon to be transmitted through the perovskite–air interface to be $6.9\\%$ and through the perovskite–glass interface to be $16.8\\%$ . \n\nWe assume the optical density of the nanocrystal films to be 0.02 at the photoluminescence emission wavelength of $620\\ensuremath{\\mathrm{nm}}$ (or 2 eV). Before reaching an interface, photons will, on average, have travelled through an optical density of 0.01. Of the total photons emitted, $16.8\\%$ of the photons will be travelling towards the perovskite–glass interface within the escape cone, and $6.9\\%$ of the photons will be travelling towards the perovskite–air interface within the escape cone. The photons emitted towards the perovskite–air interface, but within the solid angle in between the perovskite–air and the perovskite–glass escape cones (which accounts for $16.8-6.9\\%=9.9\\%$ of the photons), will be reflected off the perovskite–air interface, and will then escape out of the perovskite–glass interface. Therefore, accounting for the small attenuation due to self-absorption, the total escape probability for the perovskite nanocrystal films is estimated to be: \n\n$$\n\\eta_{\\mathrm{esc}}=10^{-0.01}\\times(16.8\\%+6.9\\%+10^{-0.02}\\times(16.8\\%-6.9\\%))=32.4\\%\n$$ \n\nFollowing equation 3 in ref. 44, the relation between the internal PLQY $(\\eta)$ and the measured PLQY $(\\eta_{\\mathrm{ext}})$ is given by: \n\n$$\n\\eta_{\\mathrm{ext}}={\\frac{(\\eta\\times\\eta_{\\mathrm{esc}})}{1-\\eta+(\\eta\\times\\eta_{\\mathrm{esc}})}}\n$$ \n\nSubstituting the measured external PLQY of $70\\%(\\eta_{\\mathrm{ext}}=0.70)$ and the total escape probability of $32.4\\%$ , $(\\eta_{\\mathrm{esc}}=0.324)$ , we obtain an internal PLQY $\\eta$ of 0.878 or $87.8\\%$ . We note that this expression accounts for the photon recycling and illustrates that the external measured PLQY can deviate considerably from the internal PLQY. \n\n# ICP-MS analysis \n\nTo provide evidence of the ‘stripped’ $\\mathsf{P b}$ –ligand complex (where the ligand is EDTA or glutathione) in the sediment, we analysed the resulting precipitates (which includes the potential $\\mathsf{P b}$ –ligand complex and undissolved ligand) by inductively coupled plasma mass spectrometry (ICP-MS) after repeated washing with toluene (10 times). As both EDTA and glutathione have very low solubility in toluene, this process effectively disperses and removes the remaining nanocrystals while retaining the Pb–ligand complexes in the residue. To rule out the lead content arising from any remaining nanocrystals, the toluene supernatant from the final washing step was also subjected to ICP-MS analysis. The results show lead is present in the precipitate at the following concentrations: glutathione-treated samples $(518\\upmu\\mathrm{g}\\mathsf{m}\\mathbf{g}^{-1})>\\mathsf{E}+\\mathbf{G}\\cdot$ treated samples $(428\\upmu\\mathrm{g}\\mathsf{m}\\mathbf{g}^{-1})>$ EDTA-treated samples $(354\\upmu\\mathrm{g}\\mathsf{m g}^{-1})$ compared with a concentration of nearly $0\\mathrm{ugmg^{-1}}$ in the final supernatant. To estimate whether EDTA and glutathione have different $\\mathsf{P b}^{2+}$ -complexation abilities, we calculated the binding energy between the two ligands and a $\\mathsf{P b}^{2+}$ ion (Extended Data Fig. 10). The complexes have a hemidirected coordination geometry, and EDTA has a considerably greater binding energy (by $0.80\\mathrm{eV})$ to $\\mathsf{P b}^{2+}$ than does glutathione. \n\n# Fabrication and characterization of MAPb $(\\mathbf{I}_{1-x}\\mathbf{B}\\mathbf{r}_{x})_{3}$ NC-LEDs \n\nOur final device stack, for which a schematic and an SEM cross-sectional image are shown in Fig. 3a, b, includes a ‘triple-layer’ hole-injection layer, comprising PEDOT:PSS, poly-TPD and the deep work-function polymer (TFB), followed by a thin dense layer of the perovskite nanocrystals (around $30\\mathsf{n m},$ ), capped with the electron transport layer of TBPi and a lithium fluoride/aluminium cathode. Typically, ITO-coated glass substrates were cleaned by an ultra-sonification process in deionized water, acetone and isopropanol for 10 min. PEDOT:PSS was spin-coated onto an ITO substrate at 5,000 rpm for 40 s. The coated substrates were transferred to an ${\\sf N}_{2}$ -filled glove box and annealed at $140^{\\circ}\\mathrm{C}$ for $10\\mathrm{{min}}$ . Poly-TPD solution $(15\\mathrm{{mg}\\mathrm{{ml}^{-1})}}$ in chlorobenzene and TFB solution $(20\\mathrm{mg}\\mathrm{ml^{-1}})$ in $p$ -xylene were sequentially spin-coated onto the substrates at 4,000 rpm for $40s$ . Each layer was annealed at $140^{\\circ}\\mathsf{C}$ for $30\\mathrm{min}$ . The $\\mathsf{M A P b}(\\mathsf{I}_{1-x}\\mathsf{B r}_{x})_{3}$ nanocrystals were spin-coated onto the substrates at 2,000 rpm for 40 s. A layer of TPBi $(70\\mathsf{n m})$ , LiF (1 nm) and Al $(80\\mathsf{n m})$ were sequentially deposited using a thermal evaporation system. The fabricated NC-LEDs were characterized using Keithley 2400 source measurement unit and a Minolta CS 2000 spectroradiometer. NC-LEDs were encapsulated with glass and measured under ambient conditions. The cross-sectional images of NC-LEDs were obtained using SEM (SU8220 FE-SEM, Hitachi) with an accelerating voltage of $10\\mathsf{k V}.$ \n\n# Article \n\n# Solid-state $^{13}\\mathbf{C}$ NMR \n\nSolid-state $^{13}\\mathrm{C}$ magic-angle spinning NMR was performed at 9.4 T (KBSI Western Seoul Center) using a $4\\mathsf{m m}$ Bruker triple resonance probe. The prepared nanocrystals were packed into reduced-volume zirconia rotors under a nitrogen atmosphere and were spun at $8\\mathsf{k H z}$ . $^{13}{\\mathsf C}$ data were acquired using a ${}^{1}\\mathsf{H}\\mathsf{-}^{13}\\mathsf{C}$ Hartmann–Hahn cross-polarization sequence with $100\\mathsf{k H z}$ SPINAL64 $\\mathsf{\\Pi}^{\\mathrm{1}}\\mathsf{H}$ decoupling. \n\n# Solution 1H NMR \n\nTo assess the interaction between the ligands and $\\mathsf{P b}^{2+}$ , we measured $\\mathrm{^1H}$ NMR spectra of the ligands mixed with $\\mathsf{P b l}_{2}$ . Figure 4a shows annotated structural diagrams of the ligands, indicating the different moieties responsible for the NMR resonances and the different binding units present in glutathione, namely glutamine (Glu), cysteine (Cys) and glycine (Gly). In Fig. 4c and Extended Data Fig. 9, we show that both $\\mathsf{\\Pi}^{\\mathrm{1}}\\mathsf{H}$ signals from EDTA shift downfield and broaden, indicating multidentate complexation of EDTA to $\\mathsf{P b}^{2+}$ . We mixed glutathione and $\\mathsf{P b l}_{2}$ in $d_{6}$ -DMSO and observed two changes: considerable broadening and increased chemical shifts of the cysteinyl $\\upbeta_{\\mathrm{cys}}$ resonance; and decreased chemical shifts of the amide $\\mathsf{N H}_{\\mathrm{cys}}$ resonances. The first change indicates that $\\mathsf{P b}^{2+}$ binds to cysteinyl sulfur39,51. The shift of amide $\\mathsf{N H}_{\\mathrm{cys}}$ resonances is probably caused by the proximity of the amide NH to the $\\mathsf{P b}^{2+}$ , as is seen when the chemically similar $\\mathbf{C}\\mathbf{d}^{2+}$ binds to glutathione52. We also observe a weakening of the geminal 2J coupling of the glutamine beta protons $(\\beta_{\\mathrm{glu}})$ , indicating that the COOH is also bound to $\\mathsf{P b}^{2+}$ . The alpha proton of glycine $(\\upalpha_{\\mathrm{gly}})$ displayed no observable shift upon the addition of $\\left.\\mathsf{P b l}_{2},\\right.$ in agreement with previous work showing that the $\\mathbf{COO^{-}}$ group of glycine does not bind to $\\mathsf{P b}^{2+}$ (ref. 53). In Extended Data Fig. 9 we show the $^1\\mathsf{H}$ NMR spectra when both ligands $\\left(\\mathbf{E}{+}\\mathbf{G}\\right)$ are mixed with $\\mathsf{P b l}_{2}$ . We observe that all of the changes associated with interactions that are present in the solutions containing the individual ligands are also present in the solution of the combined ligands, indicating that when both ligands are combined in the $\\mathbf{E}{+}\\mathbf{G}$ mixture they maintain their individual interactions with $\\mathsf{P b l}_{2}$ . We show the proposed molecular interactions of the $\\mathbf{E}{+}\\mathbf{G}$ ligands with $\\mathsf{P b}^{2+}$ on the nanocrystal surface in Fig. 4d. We conclude that, in this system, EDTA and glutathione can coordinate with $\\mathsf{P b}^{2+}$ via the aforementioned binding groups. \n\n# DFT approach \n\nWe modelled the interaction of glutathione and EDTA on perovskite surfaces using the state-of-the-art DFT calculations, including dispersion interactions, to mimic the surface chemistry of perovskite nanocrystals. Owing to the uncertain nature of surfaces and their terminations in mixed-halide perovskites, we focus here on $\\mathsf{M A P b l}_{3,}$ for which we have a reliable surface picture. We evaluate in due course the possible effect on the results of considering a single halide in place of a mixed halide. All our results are obtained considering a $\\mathsf{P b l}_{2}$ -terminated surface, which is representative of the extreme situation of a fully unpassivated perovskite surface exposing undercoordinated surface Pb. \n\nThe calculations were run with the following assumptions. First, halide demixing is triggered by defect formation and/or migration. Second, most defects and migration channels are on surfaces, so surface passivation blocks defect formation, ion migration and demixing. Third, surface passivation molecules should bind effectively to the perovskite surface and pack tightly, thus being an effective migration blocker. We considered the adsorption of single glutathione and EDTA molecules, and then considered glutathione–glutathione, EDTA–EDTA and glutathione–EDTA coadsorption. \n\nBecause glutathione is quite a complex molecule, we initially investigated which chemical fragment within glutathione interacts most strongly with the perovskite surface. Thus, we decomposed glutathione and EDTA into their possible binding moieties and calculated the binding energy of the fragments with the perovskite (Extended Data Fig. 10). The binding energy is defined as $E_{\\mathrm{b}}=E_{\\mathrm{r}}$ molecule@surface $-E_{\\mathrm{molecule}}-E_{\\mathrm{surface}}$ . \n\nThe results show that the amidic fragment of glutathione is the most strongly binding one; see Extended Data Fig. 10. Typically, the calculated binding energy of glutathione is large (−1.85 eV), arising from a partial sum of all binding moieties. EDTA shows a reduced binding energy to perovskite compared with glutathione (−1.60 versus −1.85 eV), with EDTA mainly binding through carboxylic groups. Although the tertiary aminic groups may show a greater binding energy to Pb than does COOH (Extended Data Fig. 10), steric hindrance prevents EDTA from exploiting such interactions. \n\nTo evaluate the energetics of forming a compact monolayer on the perovskite surface, thus effectively blocking all possible undercoordinated Pb atoms acting as defect-nucleating centres, we next evaluated the binding energies of two interacting glutathiones, two interacting EDTA molecules, and an interacting $\\cdot\\mathbf{E}{+}\\mathbf{G}$ pair on the perovskite surface. In the case of two or more interacting molecules, the binding energy includes both surface–molecule and molecule–molecule interactions. The $\\mathbf{E}{+}\\mathbf{G}$ pair was found to have the greatest binding energy, enhanced by a synergistic effect between glutathione and EDTA. Intermolecular hydrogen bonding between carboxylic groups of the glutathione and EDTA provides extra stabilization to these surface-adsorbed molecules, leading to a binding energy of $-4.45\\mathrm{eV}$ (Extended Data Fig. 10). \n\nTo connect the calculated binding energies to the defect-blocking properties of the respective surface-adsorbed molecules, we considered the energetics of formation of an iodine Frenkel defect pair (that is, iodine vacancy/interstitial iodine) at the surface. These defects are the energetically most probable defects at the $\\mathsf{P b l}_{2}$ -terminated perovskite surface; thus, they constitute a case study to evaluate the effect of surface-adsorbed molecules on defect formation energies. We thus calculated the formation energy of an iodine Frenkel defect pair at the $\\mathsf{P b l}_{2}$ -terminated perovskite surface without passivating molecules and in the presence of glutathione and $_{\\mathsf{E}+\\mathsf{G}}$ . \n\nFormation of an iodine Frenkel defect on the $\\mathsf{P b l}_{2}$ -terminated perovskite surface has very low formation energy (0.03 eV), in line with the instability of the unpassivated surface (complete surface passivation by methylammonium iodide raises the formation energy to 0.84 eV). Surface passivation by glutathione raises the formation energy to $0.15\\mathrm{eV,}$ with passivation by $\\mathbf{E}{+}\\mathbf{G}$ further raising it to $0.18\\mathrm{eV}.$ This clearly demonstrates the blocking of surface defects by glutathione and the synergistic effect of $\\mathbf{\\tilde{E}}{+}\\mathbf{G}.$ . To put this value into context, when modelling the interaction of polyethylene oxide (PEO) with the same perovskite surface, we calculated an increase in defect-formation energy of $0.08\\mathrm{eV}$ for a complete monolayer of ${\\mathrm{CH}}_{3}{\\mathrm{OCH}}_{3}$ (mimicking PEO). The values obtained here for glutathione and $_{\\mathsf{E}+\\mathsf{G}}$ are therefore to be considered as very high. \n\nTo sum up, we have evaluated the binding of glutathione, EDTA and $\\mathbf{E}{+}\\mathbf{G}$ on the perovskite surface and evaluated their ability to block Frenkel defects. The results show a synergistic effect of $_{\\mathsf{E}+\\mathsf{G}}$ , to deliver the highest surface binding energy and the highest defect-blocking activity. The key to efficient surface passivation is the concurrent action of strong molecule–surface and molecule–molecule interactions. \n\nAll simulations were carried out with the Quantum Espresso program package53. DFT calculations were carried out on the (001) $\\mathbf{MAPbl}_{3}$ surface within the supercell approach by the Perdew–Burke–Ernzerhof (PBE)54 functional using ultrasoft pseudopotentials (shells explicitly included in calculations: I 5s, $5p$ ; N, C 2s, $2p$ ; O 2s, $2p$ ; H 1s; Pb 6s, $6p$ , 5d; S 3s, $3p$ ) and a cutoff on the wavefunctions of 25 Ryd (200 Ryd on the charge density). DFT-D3 dispersion interactions were included in the calculation54. \n\nSlab models were built starting from the tetragonal phase of $\\mathsf{M A P b l}_{3}$ (ref. 55) by fixing cell parameters to the experimental values and generating a $2\\times2$ supercell in the a and $b$ directions. Along the non-periodic direction perpendicular to the slabs, $10\\mathring{\\mathbf{A}}$ of vacuum was added in all cases. A symmetric disposition of the organic cations on the external layers of the slabs was adopted in all cases, leading to supercells with zero average dipole moments. Such an arrangement of organic cations provided a flat electrostatic potential in the vacuum region of the supercells for all modelled slabs. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\n# Code availability Computational codes used in this work are available from the corresponding authors upon reasonable request. \n\n50.\t Salehi, A., Chen, Y., Fu, X., Peng, C. & So, F. Manipulating refractive index in organic light-emitting diodes. ACS Appl. Mater. Interfaces 10, 9595–9601 (2018). \n51.\t Sisombath, N. S. & Jalilehvand, F. Similarities between N-acetylcysteine and glutathione in binding to lead(II) ions. Chem. Res. Toxicol. 28, 2313–2324 (2015). \n52.\t Delalande, O. et al. Cadmium–glutathione solution structures provide new insights into heavy metal detoxification. FEBS J. 277, 5086–5096 (2010). \n53.\t Giannozzi, P. et al. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials. J. Phys. Condens. Matter 21, 395502 (2009). \n54.\t Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n55.\t Poglitsch, A. & Weber, D. Dynamic disorder in methylammoniumtrihalogenoplumbates(II) observed by millimeter‐wave spectroscopy. J. Chem. Phys. 87, 6373–6378 (1987). \n\nAcknowledgements This work was partially funded by the Engineering and Physical Sciences Research Council (EPSRC) UK through grants EP/M005143/1 and EP/M015254/2. This work is part of the PEROCUBE project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 861985. Y.H., A.S., R.S., H.J.S. and R.H.F. acknowledge funding and support from the SUNRISE project (EP/P032591/1), funded by the EPSRC. A.S. and R.H.F. acknowledge support from the UKIERI project. A.S. acknowledges funding and support from DST, Pratiksha Trust, IISc and MHRD. R.S. acknowledges a Newton International Fellowship from The Royal Society. M.L.C. acknowledges financial support from the Achievement Rewards for College Scientists (ARCS) Foundation, Oregon Chapter. This study was partially supported by the National Research \n\nFoundation of the Republic of Korea (NRF-2018R1C1B6005778, 2018R1A2B2006198, 2020R1A4A1018163 and 2019R1A6A1A10073437) and the Materials Innovation Project (NRF2020M3H4A3081793) funded by the National Research Foundation of Korea. NMR data were acquired on a 400-MHz solid-state NMR spectrometer (AVANCE III HD, Bruker) at KBSI Western Seoul Center. The HR-TEM, XPS, NMR, confocal photoluminescence and SEM experiments were supported by UNIST Central Research Facilities (UCRF). J.H.P. thanks A. Lee for assistance with TEM. Y.H. thanks M. Danie for assistance with TEM; S. M. Rabea, T. S. Ibrahim, A. M. Ali and T. Janes for assistance with NMR analysis; and M. N. Ahmed for advice on Fig. 1. We thank B. Wenger for discussions concerning the use of EDTA as a ligand in perovskite nanocrystals. Y.H. thanks A. Marshall and J. Sahmsi for discussions concerning the FTIR and N. Sakai for discussing XRD results. We thank V. Burlakov and S. Mahesh for discussions concerning the halide-segregation mechanism. Y.H. acknowledges funding and support from Linguistix Tank Inc. (LXT AI), Canada. \n\nAuthor contributions Y.H. initiated the project, synthesized the nanocrystals, conceived the multidentate-ligand approach, developed and performed the ligand treatment process and, with J.H.P., performed the TEM, UV–vis absorption, photoluminescence and XRD measurements. Y.H., A.S. and H.J.S. planned the experiments and overall project targets. Y.H. coordinated the collaboration efforts and was assisted by A.S. J.H.P. fabricated LED devices. A.S. assisted with the synthesis of the nanocrystals and performed the PLQY and photothermal deflection spectroscopy measurements. R.S. assisted with the PLQY and photothermal deflection spectroscopy measurements. Y.H., M.L.C., M.J., C.Y. and J.L. performed the NMR experiments and analysed the data. J.H.P. performed STEM experiments and Y.H. analysed the data. J.H.P. and B.R.L. assisted with the characterization of the materials and the LEDs. M.H.S., H.C., S.H.P. and B.R.L. provided support for the characterization of the materials and devices. J.H.P. and B.R.L. carried out the device-stability tests. M.L.C. and J.C.S. designed and executed the TAS experiments and M.L.C. performed data analysis. E.M., E.R. and F.D.A. conducted the computational simulations. C.Y.W., B.R.L., R.H.F. and H.J.S. supervised the work undertaken in their laboratories. Y.H. drafted the first version of the manuscript, with assistance from J.C.S., C.Y.W. and H.J.S. All authors have read and commented upon, or contributed to the writing of, the manuscript. \n\nCompeting interests H.J.S. is a co-founder of Oxford PV, which is commercializing perovskite-based photovoltaics. H.J.S. and R.H.F. are co-founders of Helio Display Materials, which is commercializing perovskite materials for light-emitting applications. \n\n# Additional information \n\nCorrespondence and requests for materials should be addressed to Y.H., C.Y.W., B.R.L. or H.J.S. Peer review information Nature thanks Chih-Jen Shih and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/34195d1c391836f6acf2555f30cfda2ba66b9d9635d332c70e151b89f8bc1e98.jpg) \n\n
SampleNeatEDTAGLEDTA+GL
lodine: PP At. % [halide ratio]3.37 [41.3%]3.56 [39.9%]3.71 [40.5%]3.59 [38.1%]
Bromine: PP At. % [halide ratio]4.79 [58.7%]5.36 [60.1%]5.44 [59.5%]5.83 [61.9%]
Lead (Pb): PP At. %1.421.551.531.51
\n\nExtended Data Fig. 1 | Characteristics of neat nanocrystals and nanocrystals with ligand treatment. a, Photothermal deflection spectra of neat perovskite nanocrystal films and $_{\\mathsf{E}+\\mathsf{G}}$ -treated nanocrystal films deposited on quartz substrates. The inset shows the calculation of the average Urbach energy for these two samples. b, c, Time-resolved photoluminescence decay of neat nanocrystals and $\\mathbf{E}{+}\\mathbf{G}$ -treated nanocrystals, as a solution dispersed in toluene (b) and as films (c). d, The corresponding time-resolved \n\nphotoluminescence lifetimes of the neat nanocrystals and the $_{\\mathsf{E}+\\mathsf{G}}$ -treated nanocrystals. e, FTIR spectra of drop-cast films from nanocrystals synthesized in oleic acid. neat and after treatment with EDTA, glutathione or $\\mathbf{E}{\\mathrm{+}}\\mathbf{G}.$ f, XPS of nanocrystals before and after ligand treatment, showing that the ligand-treated nanocrystals approximately correspond to MAPb $(\\mathsf{I}_{0.4}\\mathsf{B r}_{0.6})_{3},$ whereas the neat nanocrystals were synthesized using the composition of MAP $\\mathsf{b}(\\mathsf{I}_{0.67}\\mathsf{B r}_{0.33})_{3}$ . \n\n![](images/f07cc62e586fd8719023b665696b68ce0f4a2ecd4654a047a20fe8fbcbcc74c3.jpg) \nExtended Data Fig. 2 | HR-TEM images of nanocrystals. a, b, HR-TEM images of neat nanocrystals at different magnifications. c, Fast Fourier transformation of the selected region in b, in which the interplanar lattice spacing of the cubic phase is 0.60 and $0.42\\mathrm{nm}$ for the {001} and {110} family of planes. d, e, HR-TEM \nimages of $=\\pm\\mathbf{G}$ -treated nanocrystals at different magnifications. f, Fast Fourier transformation of the selected region in e showing a similar cubic structure to neat nanocrystals. \n\n![](images/59bdcbd154fff63c4a8554ac7bd1f2f171045196229cf3ac5f0b0fdc55295a08.jpg) \n\n# Extended Data Fig. 3 | Effect of ligands on nanocrystal excited-state \n\ndynamics. a, Schematic of TAS procedure. Coloured circles represent photoluminescence measurements before (black) and after (red) illumination with a 405-nm laser. Periodic re-exposure of the sample to the 405-nm laser maintained a stable photoluminescence wavelength during TAS scans without causing additional segregation. The duration of the re-exposure, T, was 10 s and 3 s for neat and $\\mathbf{E}{+}\\mathbf{G}$ treated nanocrystals, respectively. For neat nanocrystals, the photoluminescence wavelength was initially $649\\mathrm{nm}$ and was $669\\pm1\\mathrm{nm}$ after exposure; the photoluminescence of $\\mathbf{\\tilde{E}{+}G}$ -treated nanocrystals was initially $628\\mathsf{n m}$ and was $632\\pm1\\mathrm{nm}$ after exposure. b–e, TAS of neat (b, c) and \n\n$_{\\mathsf{E+G}}$ -treated (d, e) nanocrystals before (b, d) and after (c, e) illumination. f–m, Transients of neat (f–i) and $\\mathbf{E}{+}\\mathbf{G}$ -treated $(\\mathbf{j}-\\mathbf{m})$ nanocrystals before (f, g, j, k) and after (h, i, l, m) illumination. Traces are average signal in wavelength ranges chosen to highlight wavelength-dependent dynamics. Blue, green, yellow and red traces for the neat nanocrystals and the $_{\\mathsf{E}+\\mathsf{G}}$ -treated nanocrystals correspond to 560–600 and 550–580 nm, 600–640 and 580–610 nm, 640–680 and 610–640 nm, 680–720 and $640{-}670\\mathrm{nm}$ , respectively. Black dashed lines are a global fit to a tri-exponential function. n, Time constants before (after) illumination of each nanocrystal sample, found by a global fit of transient absorption spectra. Colours refer to those in Fig. 2g, h. \n\n![](images/f3b8131f80b478b676483e8406f9f3bb5e6ce48870f51df1ae98694121bbd9cf.jpg) \n\nExtended Data Fig. 4 | Halide segregation in diluted neat nanocrystals. a, b, Normalized photoluminescence spectra of spin-cast films of neat nanocrystals and polymethyl methacrylate (PMMA), in a nanocrystal:PMMA mass ratio of 1.03 (a) and 0.006 (b). A 405-nm continuous-wave laser was used as an excitation source and caused halide segregation, with the duration of irradiation indicated in the legend. The redshifted shoulder that developed during irradiation is ascribed to the recombination from within an iodideenriched minority phase with a smaller bandgap. This shoulder showed no dependence on the nanocrystal concentration in the film, indicating that \n\nsegregation can occur in isolated nanocrystals. c, d, Confocal photoluminescence images (c) and normalized photoluminescence spectra (d) of spin-cast films of neat nanocrystals over time under constant excitation with a 405-nm continuous-wave laser. The photoluminescence spectra were obtained from the highlighted region of c. e, f, Confocal photoluminescence images (e) and normalized photoluminescence spectra (f) of spin-cast films of neat nanocrystals and PMMA, in a nanocrystal:PMMA mass ratio of 0.001 over time under constant excitation with a 405-nm diode laser. The photoluminescence spectrum was obtained from the highlighted region of e. \n\n# Article \n\n![](images/8d87ec31bc2b1fd63bfc44b87a83547032f1ac1b2a7db135ba7f7a62b2b5a44b.jpg) \nExtended Data Fig. 5 | Stability of the electroluminescence spectra of the mixed-halide MAPb $\\mathbf{\\Delta}[\\mathbf{\\mathbf{{1}}}_{x}\\mathbf{\\mathbf{{B}}}\\mathbf{\\mathbf{{r}}}_{1-x}]_{3}$ NC-LEDs with different ligand treatments. a–c, Current density–voltage $(J-V)$ curves (a), luminance–voltage (L–V) curves (b) and EQE–current density curves (c) of NC-LEDs with different ligands treatment. d–f, Electroluminescence spectra of EDTA-treated (d), glutathione-treated (e) and $\\mathbf{E}{+}\\mathbf{G}$ -treated (f) NC-LEDs at different bias \nvoltages. g–i, Electroluminescence spectra of EDTA-treated $\\mathbf{\\sigma}(\\mathbf{g})$ , glutathione-treated ${\\bf\\Pi}({\\bf h})$ and $_{\\mathsf{E+G}}$ -treated (i) NC-LEDs over time at a constant current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ . j–l, Electroluminescence spectra after treatment of the EDTA-treated (j), glutathione-treated (k) and $\\mathbf{E}{+}\\mathbf{G}$ -treated (l) NC-LEDs with 1-adamantanecarboxylic acid (ADAC), measured over time at a constant current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ . \n\nExtended Data Fig. 6 | Characteristics of nanocrystal films with different charge-transporting layers. a, Time-resolved photoluminescence decays of $\\mathbf{E}{+}\\mathbf{G}$ -treated nanocrystal films with various charge-transporting layers (excitation at $450\\mathsf{n m},$ ). PNCs, perovskite NCs; PD, PEDOT:PSS; P-TPD, poly-TPD. b, Photoluminescence intensities of $E{+}\\mathbf{G}$ -treated nanocrystal films with various charge-transporting layers (excitation at $350\\mathsf{n m}$ ). Photoluminescence decays considerably faster, and photoluminescence intensity is reduced, in the presence of a poly-TPD HTL, whereas little change is observed with a TPBi ETL. This shows that exciton quenching markedly affects the interface between poly-TPD and the nanocrystals, resulting in a deterioration of device efficiency. \n\n![](images/c15f614250f310ae43dda385412da1c57316b374c4893cfb36fa9c60f13fa9f6.jpg) \nc, Time-resolved photoluminescence decays of $\\mathbf{E}{+}\\mathbf{G}$ -treated nanocrystal films with various HTLs (excitation at $450\\mathsf{n m}$ ). d, Photoluminescence intensities of $\\mathbf{E}{+}\\mathbf{G}$ -treated nanocrystal films with various HTLs (excitation at $450\\mathsf{n m},$ ). TFB HTLs have longer photoluminescence decays and larger photoluminescence intensity compared to the poly-TPD HTLs, indicating that there is less exciton quenching at the interface between the nanocrystals and the TFB HTLs. e, f, Photoemission cutoff energy (e) and the valence-band region (f) of neat and $\\mathbf{E}{+}\\mathbf{G}$ -treated nanocrystals from ultraviolet photoemission spectra. g, h, Optical bandgaps of neat nanocrystals $\\mathbf{\\sigma}(\\mathbf{g})$ and $_{\\mathsf{E}+\\mathsf{G}}$ treated nanocrystals (h). \n\n![](images/f3656c1dc5961237a07343c61bb3c628fc16b1652ef51fa44ed2cf547f1491fd.jpg) \nExtended Data Fig. 7 | Device characteristics and stability of the electroluminescence spectra of the mixed-halide MAPb $[\\mathbf{I}_{x}\\mathbf{B}\\mathbf{r}_{1-x})_{3}\\mathbf{N}\\mathbf{C}$ -LEDs. a, Schematic illustrations of the NC-LED configuration showing the device architecture: ITO/PEDOT:PSS/poly-TPD/MAPb $(\\mathsf{I}_{1-x}\\mathsf{B r}_{x})_{3}$ nanocrystals/TPBi/LiF/ Al. b, Current density–voltage (J–V) and luminance–voltage $(L{-}V)$ curves of NC-LEDs. c, Luminous efficiency plotted against current density for NC-LEDs. d, EQE–current density curves of NC-LEDs. e, f, Electroluminescence spectra of neat (e) and $\\mathsf{E}{+}\\mathsf{G}$ -treated (f) NC-LEDs at different bias voltages. g, Peak \nwavelength of electroluminescence of neat and $_{\\mathsf{E}+\\mathsf{G}}$ -treated NC-LEDs at different current densities. h, i, Peak wavelength of electroluminescence of neat (h) and $\\mathbb{E}{+}\\mathbb{G}$ -treated (i) NC-LEDs at a constant current of $0.5\\mathsf{m A c m}^{-2}$ for one hour, followed by measurements of the same device after resting in the glove box for the indicated times. The electroluminescence peak shifts under the constant current density of $0.5\\mathsf{m A c m}^{-2}$ but recovers to its initial position after resting in the glove box for 5 h, indicating the reversibility of halide segregation. \n\n![](images/789adcf65191685c6a0d4ce26f37b7eec870aa160f345a74d6b55ef1954c8e80.jpg) \nExtended Data Fig. 8 | Histogram of maximum EQE values and operating stability of mixed-halide MAPb $\\mathbf{\\Delta}\\mathbf{{I}}_{x}\\mathbf{\\mathbf{B}}\\mathbf{r}_{1-x}\\mathbf{\\mathbf{)}}_{3}$ NC-LEDs. a, Histogram of maximum EQE values for $\\mathbf{E}{+}\\mathbf{G}$ -treated NC-LEDs, collected from 25 devices. b, Operational stability of $\\Xi{+}\\mathbf{G}$ -treated NC-LEDs measured in air at a constant current of \n$0.1\\mathsf{m A c m}^{-2}$ (initial luminance $(L_{0})=22\\mathsf{c d m}^{-2})$ , $1\\mathsf{m A c m}^{-2}(L_{0}=141\\mathsf{c d}\\mathsf{m}^{-2})$ and 10 mA cm−2 $\\left(L_{0}=585{\\mathrm{cd}}{\\mathrm{m}}^{-2}\\right)$ . c–f, Electroluminescence spectra of NCs-LEDs with neat (c, e) and $\\boldsymbol{\\Xi}+{\\bf G}$ ligand-treated (d, f) nanocrystal layers at a different lifetimes and with constant current densities of 1 mA cm−2 (c, d) and $10\\mathsf{m A c m^{-2}}(\\mathbf{e},\\mathbf{f}$ ). \n\n# Article \n\n![](images/3b28d7aef021762b217bc22b7445a6d04eeb831acd5cfab9d0e4389bb66e3fea.jpg) \nExtended Data Fig. 9 | 1H NMR spectra of solutions. a, MAPb $\\mathbf{\\widetilde{I}}_{x}\\mathbf{Br}_{1-x}\\mathbf{)}_{3}$ nanocrystals before and after treatment with $\\mathsf{E}{+}\\mathsf{G}$ mixture in $d_{\\mathrm{{s}}}$ -toluene. b, Magnification of the circled region of the $\\mathrm{^1{H}}$ NMR spectra in a (between 5.4 and $5.6\\mathsf{p p m}\\rangle$ ), showing details of the proton bound to $\\scriptstyle\\mathbf{C}=\\mathbf{C}$ of oleic acid/ oleylamine. Fine structure can be seen on top of the broad resonance after ligand treatment, which is indicative of free oleic acid and oleylamine ligands. c, Systematic addition of $_{\\mathsf{E}+\\mathsf{G}}$ to $\\mathsf{P b l}_{2}$ in $d_{6}$ -DMSO solutions. d, e, EDTA, \n\nglutathione and $_{\\mathsf{E}+\\mathsf{G}}$ in $d_{6}$ -DMSO (d) and ${\\sf D}_{2}0$ (e). When both ligands are combined in the $_{\\mathsf{E}+\\mathsf{G}}$ mixture, the individual peak positions are retained, indicating that there is no chemical interaction between the two ligands. f, Glutathione in $d_{6}$ -DMSO and in a mixture of $d_{6}$ -DMSO with ${\\bf D}_{2}0$ showing the disappearance of the amide NH peaks (corresponding to exchangeable protons) in the presence of ${\\bf D}_{2}0$ . g, h, Systematic addition of EDTA $\\mathbf{\\sigma}(\\mathbf{g})$ and glutathione (h) to $\\mathsf{P b l}_{2}$ in $d_{6}$ -DMSO solutions. \n\n![](images/bd71b87d5bcf0f3aa6af05101361dc872dea9342e51e80326336cd3f60567d05.jpg) \n\n
MoleculeBE (eV)MoleculeBE(eV)
CHCOOH-0.58GL-1.85
CHSH-0.52EDTA-1.60
CHCONHCH3-1.022EDTA-4.02 (-2.01)
CHNH2-0.842GL-4.33 (-2.17)
(CH3)N-0.83GL+EDTA-4.45 (-2.23)
\n\nExtended Data Fig. 10 | DFT-optimized structures of surface-adsorbed ligands. a, Structure of glutathione (left) and EDTA (right), with fragments that were used to study their interaction with the perovskite highlighted. b–f, DFT-optimized structures of surface-absorbed glutathione (b), EDTA (c) one glutathione molecule and one EDTA molecule (d), two EDTA molecules (e) and two glutathione molecules (f). g–i, The optimized structure of an iodine Frenkel defect pair (defective iodine atoms in yellow) on the bare $\\mathsf{P b l}_{2}$ -terminated perovskite surface (g), in the presence of adsorbed \n\n![](images/6466b12df2e88a6bd58d428c709621d291b02a404409041e285fbab980223a87.jpg) \n\nglutathione (h) and in the presence of adsorbed $_{\\mathsf{E}+\\mathsf{G}}$ (i). The iodine vacancy is highlighted with a dashed circle. j, Binding energies of fragments and complete molecules to the $\\mathsf{P b l}_{2}$ terminated perovskite surface. Data in parenthesis is the value per adsorbed molecule. k, DFT-optimized structures of the $\\mathsf{P b}^{2+}$ complexes with EDTA and with glutathione. The relative binding energies showing that EDTA binds more strongly to $\\mathsf{P b}^{2+}$ than does glutathione by $0.80\\mathrm{eV}.$ . " + }, + { + "id": "10.1126_science.abg7217", + "DOI": "10.1126/science.abg7217", + "DOI Link": "http://dx.doi.org/10.1126/science.abg7217", + "Relative Dir Path": "mds/10.1126_science.abg7217", + "Article Title": "Carbon-free high-loading silicon anodes enabled by sulfide solid electrolytes", + "Authors": "Tan, DHS; Chen, YT; Yang, HD; Bao, W; Sreenarayanull, B; Doux, JM; Li, WK; Lu, BY; Ham, SY; Sayahpour, B; Scharf, J; Wu, EA; Deysher, G; Han, HE; Hah, HJ; Jeong, H; Lee, JB; Chen, Z; Meng, YS", + "Source Title": "SCIENCE", + "Abstract": "The development of silicon anodes for lithium-ion batteries has been largely impeded by poor interfacial stability against liquid electrolytes. Here, we enabled the stable operation of a 99.9 weight % microsilicon anode by using the interface passivating properties of sulfide solid electrolytes. Bulk and surface characterization, and quantification of interfacial components, showed that such an approach eliminates continuous interfacial growth and irreversible lithium losses. Microsilicon full cells were assembled and found to achieve high areal current density, wide operating temperature range, and high areal loadings for the different cells. The promising performance can be attributed to both the desirable interfacial property between microsilicon and sulfide electrolytes and the distinctive chemomechanical behavior of the lithium-silicon alloy.", + "Times Cited, WoS Core": 592, + "Times Cited, All Databases": 632, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000698977800047", + "Markdown": "# BATTERIES \n\n# Carbon-free high-loading silicon anodes enabled by sulfide solid electrolytes \n\nDarren H. S. Tan1, Yu-Ting Chen1, Hedi Yang1, Wurigumula Bao1, Bhagath Sreenarayanan1, Jean-Marie Doux1, Weikang Li1, Bingyu Lu1, So-Yeon Ham1, Baharak Sayahpour1, Jonathan Scharf1, Erik A. Wu1, Grayson Deysher1, Hyea Eun Han2, Hoe Jin Hah2, Hyeri Jeong2, Jeong Beom Lee2, Zheng Chen1,3,4,5\\*, Ying Shirley Meng1,4,5\\* \n\nThe development of silicon anodes for lithium-ion batteries has been largely impeded by poor interfacial stability against liquid electrolytes. Here, we enabled the stable operation of a 99.9 weight $\\%$ microsilicon anode by using the interface passivating properties of sulfide solid electrolytes. Bulk and surface characterization, and quantification of interfacial components, showed that such an approach eliminates continuous interfacial growth and irreversible lithium losses. Microsilicon full cells were assembled and found to achieve high areal current density, wide operating temperature range, and high areal loadings for the different cells. The promising performance can be attributed to both the desirable interfacial property between microsilicon and sulfide electrolytes and the distinctive chemomechanical behavior of the lithium-silicon alloy. \n\nS ilicon (Si), which has a specific capacity exceeding $3500\\ \\mathrm{mAh\\g^{-1}}$ , has emerged as a promising alternative to graphitebased anodes (with a specific capacity of ${\\sim}370~\\mathrm{mAh~g^{-1}},$ ) to increase the energy densities of lithium-ion batteries (LIBs), for various energy-storage applications such as electric vehicles and portable devices $(\\boldsymbol{I},\\boldsymbol{2})$ . In addition to being the second most abundant element in Earth’s crust, Si is also environmentally benign and exhibits electrochemical potentials close to that of graphite $\\mathrm{\\Delta}\\mathrm{\\Omega}_{0.3}\\mathrm{v}$ versus $\\mathrm{Li/Li^{+}}$ ) (2). However, commercialization of Si anodes is hindered by its poor cycling and shelf life resulting from continuous solid electrolyte interphase (SEI) growth between the highly reactive Li-Si alloy and organic liquid electrolytes used in LIBs. These deficiencies are exacerbated by the large volumetric expansion $(>300\\%)$ ) of Si during lithiation and by the loss of $\\mathrm{Li^{+}}$ inventory due to SEI growth and irreversibly trapped Li-Si alloy enclosed within (3). \n\nCurrent efforts to mitigate capacity fade include the use of sophisticated Si nanostructures in combination with carbon composites and robust binder matrix to mitigate pulverization $(\\boldsymbol{I},\\boldsymbol{3-6})$ . Liquid electrolyte modifications, including the use of cyclic ethers, fluorinated additives, or other ionic liquids additives that stabilize the SEI, have also been explored $(5,7)$ . Improvements have been reported in numerous half-cell studies, but the varied amounts of lithium excess make it challenging to evaluate the effectiveness of each strategy. Among reports that demonstrated stable cycling in full cells (5, 8–20), most are limited to 100 cycles, apart from a few that demonstrated longer cycle life using various prelithiation strategies to compensate for $\\mathrm{Li^{+}}$ inventory losses $(9,14,18)$ . Although prelithiation can be effective to extend cycle life, the ideal Si anode should be composed of pristine microsilicon $\\mathrm{(\\upmu{Si})}$ particles that do not require further treatment, reaping the benefits of low costs, ambient air stability, and environmentally benign properties. To realize this potential, two key challenges should be addressed: (i) stabilizing the Li-Si | electrolyte interface to prevent continuous SEI growth and trapped Li-Si accumulation, and (ii) mitigating growth of new interfaces induced by volume expansion that results in $\\mathrm{Li^{+}}$ consumption. \n\nSi stability problems arise mainly from the interface with liquid electrolytes. The use of solid-state electrolytes (SSEs) in an all solidstate battery (ASSB) is a promising alternative approach, owing to its ability to form a stable and passivating SEI (21). Previous studies have reported the use of thin (submicrometer)–film type Si in ASSBs (11, 22, 23). Most ASSB reports have focused on the use of metallic Li, in an effort to maximize cell energy densities (24, 25). However, small critical current densities of metallic Li anodes often dictate the need for operation under elevated temperatures, especially during cell charging. In this work, a $\\upmu\\mathrm{{Si}}$ electrode consisting of 99.9 wt $\\%\\upmu\\mathrm{{Si}}$ is used in $|\\upmu\\mathrm{Si}|$ |SSE||lithium nickel cobalt manganese oxide (NCM811) cells to overcome both the interfacial stability challenges of $\\upmu\\mathrm{Si}$ and the current density limitations of ASSBs. \n\nUnlike conventional liquid-cell architectures, the SSE does not permeate through the porous $\\upmu\\mathrm{Si}$ electrode (Fig. 1), and the interfacial contact area between the SSE and the $\\upmu\\mathrm{{Si}}$ electrode is reduced to a two-dimensional (2D) plane. After lithiation of $\\upmu\\mathrm{Si}$ , the 2D plane is retained despite volume expansion, preventing the generation of new interfaces. Bulk $\\upmu\\mathrm{{Si}}$ exhibits an electronic conductivity of $\\sim3\\times10^{-5}\\mathrm{S}\\mathrm{cm}^{-1}$ (fig. S1), comparable to that of most common cathode materials $\\left(\\sim\\mathrm{10}^{-6}\\right.$ to \n\n![](images/c8397df284046f8bf52c7d2d0fb5cba8a57c8671d8c3c320213d01d09b0339ae.jpg) \nFig. 1. Schematic of 99.9 wt $\\%\\upmu\\up S\\dot{\\mathbf{l}}$ electrode in an ASSB full cell. During lithiation, a passivating SEI is formed between the $\\upmu\\mathrm{Si}$ and the SSE, followed by lithiation of $\\upmu\\mathrm{Si}$ particles near the interface. The highly reactive Li-Si then reacts with Si particles within its vicinity. The reaction propagates throughout the electrode, forming a densified Li-Si layer. \n\n$10^{-4}\\mathrm{{Scm}^{-1},}$ ) (26–28), so additional carbon additives are not necessary. Moreover, carbon is well known to be detrimental to the stability of sulfide SSEs, as it promotes SSE decomposition (29, 30). Although certain types of carbon have been found to be compatible with anode-free ASSBs (24, 31), eliminating carbon entirely in the $\\upmu\\mathrm{Si}$ ASSB system is preferable. During lithiation of ${\\upmu}\\mathrm{{Si}}$ , Li-Si formation can propagate throughout the electrode, benefiting from the direct ionic and electronic contact between Li-Si and $\\upmu\\mathrm{{Si}}$ particles (Fig. 1). This process was found to be highly reversible without the need for any lithium excess. Separate full-cell experiments were performed, achieving current densities up to $5\\mathrm{\\mA\\cm^{-2}}$ , operation between $-20^{\\circ}$ and $80^{\\circ}\\mathrm{C}$ , and areal capacities of up to 11 mAh $\\mathrm{cm}^{-2}(2890\\mathrm{mAhg}^{-1})$ for the different cells. Subsequent cycling of the $\\upmu\\mathrm{Si}$ -NCM811 full cell at $5\\ \\mathrm{mA\\cm^{-2}}$ was found to deliver a capacity retention of $80\\%$ after 500 cycles, demonstrating the overall robustness of $\\upmu\\mathrm{Si}$ enabled by ASSBs. \n\n# Results \n\n# Interface characterization \n\nTo demonstrate the importance of eliminating carbon in the anode, as well as the passivating nature of the Si-SSE interface, we characterized and quantified the SEI products from SSE decomposition with and without the presence of carbon additives. As most literature reports adopt Si composites containing between 20 and 40 wt $\\%$ carbon additives $(5,8–20)$ , this was used as a basis for comparison against carbonfree $\\upmu\\mathrm{{Si}}$ . Although Li metal is typically used as the counterelectrode in liquid electrolyte studies, its low critical current density in ASSBs make it unsuitable for studying our system (32, 33). Likewise, limited kinetics in lithium indium alloys also make them inappropriate (fig. S2). Thus, NCM811, which is protected by a boron-based coating (34), was instead chosen as the counterelectrode, allowing direct evaluation of $\\upmu\\mathrm{Si}$ in a full cell configuration without lithium excess. To prepare the samples, we used two composite Si-SSE anodes (with and without 20 wt $\\%$ carbon additives). Composite anodes with SSEs were used to exaggerate any interfacial reactions for characterization. Figure 2A shows the voltage profiles of both cells during the first lithiation. The cell without carbon shows an initial voltage plateau around $3.5\\mathrm{V}$ , typical of a $\\lvert\\upmu\\mathrm{Si}\\rvert$ |NCM811 full cell. However, the cell with $20\\mathrm{wt}\\%$ carbon shows a stark difference, with a lower initial plateau at $2.5\\mathrm{V}_{:}$ , indicating extensive SSE electrochemical decomposition before reaching the lithiation potential above $3.5\\mathrm{V}.$ Figure 2B compares the diffraction patterns of the pristine Si-SSE, lithiated Si-SSE, and lithiated Si-SSE-carbon composites. The lithiated Si-SSE sample retained the crystalline structure of the SSE as well as that of the unreacted Si, with some signals of amorphous Li-Si manifesting as a hump at around $20^{\\circ}.$ Although some SEI is expected, the low amount formed at the interface is most likely not detectable with this bulk technique. However, in the cell where carbon is used, most of the pristine SSE’s diffraction signals are no longer present, indicating severe electrolyte decomposition. During this process, nanocrystalline $\\mathrm{Li}_{2}\\mathrm{S}$ forms as a major decomposition product and is observed as broad peaks appearing at 2q angles of around $26^{\\circ},45^{\\circ},$ and $52^{\\circ}.$ . \n\n![](images/83b96188887023e776a2d13f961eaa772ccdc138a383888170d71f52fdf5b499.jpg) \nFig. 2. Carbon effects on SSE decomposition. (A) Voltage profiles of $\\upmu{\\sf S i}\\ \\big|\\big|$ SSE $||$ NCM811 cells with and without carbon additives (20 wt $\\%$ ). Inset shows a lower initial plateau indicating SSE decomposition. (B) XRD patterns, and (C to E) XPS spectra of the (C) S 2p, (D) Li 1s, and (E) Si 2p core regions. \n\n![](images/6d88746657059cfd1c37dc4f5bb9ac03ecf6fa94471ce6531e922a9a0659f68f.jpg) \nFig. 3. Quantifying effects of SEI growth. (A) Voltage profiles of full cells used in titration gas chromatography. (B) Li-Si and SEI amounts relative to cell capacity. (C) Voltage profile of a Li-Si symmetric cell used for EIS, and (D) Nyquist plots. \n\nThese observations agree with the $\\mathbf{\\boldsymbol{x}}$ -ray photoelectron spectroscopy (XPS) analysis in Fig. 2C, where the presence of carbon results in a greater extent of SSE decomposition, as seen by the formation of $\\mathrm{Li}_{2}\\mathrm{S}$ (161 eV) in the S 2p region. Consequently, a larger decrease in peak intensities for the $\\mathrm{PS_{4}}^{3-}$ thiophosphate unit signals is observed for the electrode containing carbon (Fig. 2C, bottom) compared to the electrode without carbon (Fig. 2C middle). Although the Li 1s region (Fig. 2D) is difficult to deconvolute owing to the presence of multiple $\\mathrm{Li^{+}}$ species, a shift toward lower binding energies is observed as a result of reduction of $\\mathrm{Li^{+}}$ from the pristine SSE. Although a smaller shift is observed in the sample without carbon (Fig. 2D middle), the peak position for the sample containing carbon is dominated by the $\\mathrm{Li}_{2}\\mathrm{S}$ signals at about $55.6\\mathrm{eV}$ (Fig. 2D bottom), reaffirming the previous observation using x-ray diffraction (XRD). In the Si 2p region, a native oxide layer is detected near the surface of the Si particles (Fig. 2E, top). Upon lithiation, this signal shifts to a lower binding energy. A peak with a binding energy consistent with that of Li-Si is found in the sample without carbon, whereas Si appears to remain unreacted in the sample with carbon. This is likely due to formation of the $\\mathrm{Li^{+}}$ consuming SEI products, severely limiting the lithiation of the $\\upmu\\mathrm{Si}$ electrode itself. The vast disparities in the extent of SEI formation highlight the critical role of carbon in promoting decomposition as a result of its high specific area and electronic conductivity compared with Si. Previous studies also showed that the extent of SSE decomposition was highly dependent on the type of carbon material used, with the least decomposition observed when no carbon was used (31). For reduction to occur between solid-solid interfaces, sufficient contact with electronically conductive surfaces is needed. As such, carbon-free electrodes would substantially reduce SSE decomposition, resulting in improved first-cycle Coulombic efficiency $(\\mathrm{CE\\%})$ and rate capability compared with conventional carbon-containing electrodes (fig. S3, A and B). \n\n# Quantification of SEI components \n\n$\\mathrm{Li}_{6}\\mathrm{PS}_{5}\\mathrm{Cl}$ is reduced to form $\\mathrm{Li}_{2}\\mathrm{S}$ , $\\mathrm{Li_{3}P}$ , and LiCl (29), products that are highly passivating in nature (table S1). As such, SEI formation is expected to stabilize after the first cycle. Although capacity losses during cycling can be detected as a function of $\\mathrm{CE\\%}$ , it is difficult to accurately deconvolute contributions from the SEI or trapped Li-Si, respectively. Titration gas chromatography (TGC) has been effectively used to quantify SEI and dead Li growth in Li metal batteries (35). In this study, TGC is similarly applied to quantify SEI growth and ascertain its passivating and stable nature. Five $\\lvert\\upmu\\mathrm{Si}\\rvert$ ||SSE||NCM811 full cells were assembled and cycled from one to five cycles, respectively (Fig. 3A). First-cycle $\\mathrm{CE\\%}$ of $\\sim76\\%$ was measured across all cells, which quickly rose to ${>}99\\%$ from the second cycle. After cycling, the TGC method detailed in fig. S4 was applied to all five cells, where the difference between $\\mathrm{CE\\%}$ losses and active $\\mathrm{Li^{+}}$ allows derivation of the SEI formed. The amounts of SEI accumulated, active $\\mathrm{Li^{+}}$ from Li-Si, sum of cumulative losses, and total cumulative capacities are plotted in Fig. 3B and summarized with error values in table S2. After the first cycle, the total amount of SEI formed was found to be $11.7\\%$ of the cell’s capacity, and this amount increased slightly to $12.4\\%$ in the second cycle. In the subsequent cycles, both the accumulated SEI and the active $\\mathrm{Li}^{+}$ were found to remain stable and relatively unchanged, indicating interface passivation that prevents unwanted continuous reaction between Li-Si and the electrolyte. To evaluate the SEI stability over extended cycling, we fabricated and cycled a Li-Si symmetric cell at $5\\mathrm{\\mA\\cm^{-2}}$ using a capacity of $2\\mathrm{mAh\\cm^{-2}}$ per cycle (Fig. 3C). Electrochemical impedance spectroscopy (EIS) measurements found that the impedance remained stable over 200 cycles (Fig. 3D), confirming that the SEI is passivating in nature. Enlarged voltage profiles are shown in fig. S5. Conversely, impedance growth was observed in the NCM811 symmetric cell under similar conditions (fig. S5). Table S3 details the equivalent circuits’ fitted values. The stable SEI formed at the Li-Si||SSE interface may also address self-discharge challenges faced by Si anodes, especially under increased temperature where unwanted parasitic reactions are aggravated. To illustrate this, we assembled and cycled solid and liquid electrolytebased cells for five cycles at room temperature and at $55^{\\circ}\\mathrm{C}$ (fig. S6). Compared to the liquid cell, the solid cell was able to retain its charge $(\\sim99\\%)$ , even at $55^{\\circ}\\mathrm{C}.$ . Subsequent self-discharge tests, with 0 to 3 days of rest time at the charged state, also showed reduced loss of charge $3\\%$ versus $28\\%$ ) in the solid cell, with limited voltage decay during resting (fig. S7). \n\n# Morphological evolution \n\nAs illustrated in Fig. 1, the $\\upmu\\mathrm{Si}$ particles in the SSE cell remain in direct ionic $(\\mathrm{Li^{+}})$ and electronic $(\\mathrm{e^{-}})$ contact with each other. This allows for fast diffusion of $\\mathrm{Li^{+}}$ and transport of $\\mathrm{e}^{-}$ throughout the electrode, unhindered by any electronically insulative components such as SEI or electrolyte. Galvanostatic intermittent titration technique experiments were performed, and average $\\mathrm{Li^{+}}$ diffusion coefficients in the range of $\\mathrm{\\sim}10^{-9}\\mathrm{cm^{2}\\ s^{-1}}$ were obtained (fig. S8). These are one to two orders higher than values reported on nano-Si or Si thin films in conventional liquid electrolytes (36–38), which have been limited by the interfacial stability challenges and extra impedance caused by thick SEI. To visualize the morphological evolution of Li-Si, we prepared cross-section scanning electron microscopy (SEM) images of three separate $\\upmu\\mathrm{{Si}}$ electrodes by focused ion beam at the pristine, lithiated, and delithiated states. \n\nAt the pristine state (Fig. 4A), discreet $\\upmu\\mathrm{Si}$ particles (2 to $5\\upmu\\mathrm{m}\\mathrm{\\check{\\Omega}}$ ) were observed, with an electrode porosity of $40\\%$ after calendering. After lithiation (Fig. 4B), the electrode becomes densified, with most pores disappearing between the pristine $\\upmu\\mathrm{{Si}}$ particles. Moreover, the boundaries between separate $\\upmu\\mathrm{Si}$ particles have entirely vanished. An enlarged view of the more porous region shows that the entire electrode has become an interconnected densified Li-Si alloy. After delithiation (Fig. 4C), the $\\upmu\\mathrm{Si}$ electrode did not revert to its original discreet microparticle structure but instead formed large particles with voids between them. It is noted that a lower loading was used to image the entire void’s depth at the delithiated state. Energy-dispersive x-ray (EDS) imaging confirms that the pores are indeed voids, with no evidence of SEI or SSE present between each delithiated particle. The morphological behavior observed is in stark contrast to morphological changes of $\\upmu\\mathrm{Si}$ particles in liquid electrolyte systems (fig. S9, A and B), where lithiated $\\upmu\\mathrm{Si}$ particles do not merge and remain separate as a result of SEI formed throughout the electrode. This chemomechanical behavior of the Li-Si alloy has been previously reported in studies on porous Si thin-film ASSBs using sulfide SSEs as well, where initial porosity incorporated into the pristine Si thinfilm electrode was found to decrease during lithiation (11, 23). \n\nTo quantify thickness growth and porosity changes during cycling, we prepared $\\upmu\\mathrm{Si}$ electrodes with similar mass loadings of ${\\sim}3.8~\\mathrm{mg}$ $\\mathrm{cm^{-2}}$ and measured their thicknesses during charge and discharge states. At the pristine state, a thickness of $\\sim27~{\\upmu\\mathrm{m}}$ was measured (fig. S10A), and after lithiation to $\\mathrm{Li_{3.35}S i}$ , the thickness increased to ${\\sim}55\\ \\upmu\\mathrm{m}$ (fig. S10B). This increase falls short of the expected ${>}300\\%$ growth $(I)$ , indicating that a substantial decrease in initial $40\\%$ porosity must occur. To rationalize this, we calculated expected thicknesses versus porosities in table S4, which shows a low resulting porosity $(<10\\%)$ of the ${\\sim}55{\\cdot}{\\upmu}{\\mathrm{m}}{\\ }{\\upmu}{\\mathrm{Si}}$ electrode after lithiation. This agrees with the qualitative observations made in Fig. 4, where considerable densification is observed compared to the pristine state. After delithiation (fig. S10C), a thickness of ${\\sim}40~\\upmu\\mathrm{m}$ was measured, with a porosity of $\\sim30\\%$ calculated. The lower porosity at the delithiated state compared to the pristine $40\\%$ is expected, as some $\\mathrm{Li^{+}}$ remains in the anode (Fig. 3B). Despite the relatively large thickness and porosity changes, similar morphologies and thicknesses were observed after multiple cycles (fig. S11). This suggests that the mechanical properties of the Li-Si and SSE have a crucial role in maintaining the integrity of the interfaces as well as retaining contact with the anode along the 2D interfacial plane. \n\n![](images/b3deafec768d2fb9c10be8ed2b8393efa669e22061077240fa76f3486b54d6c0.jpg) \nFig. 4. Visualizing lithiation and delithiation of 99.9 wt $\\%$ Si. (A) Pristine porous microstructure of $\\upmu\\mathrm{Si}$ electrode. (B) Charged state with densified interconnected Li-Si structure. (C) Discharged state with void formation between large dense Si particles. Yellow dotted box represents enlarged porous regions of interest for each sample. \n\nAlthough contact losses are less likely during lithiation, where volume expansion occurs, it is an important consideration during delithiation. However, good contact is still maintained between the SSE layer and the porous structure of the delithiated Li-Si (Fig. 4C). This indicates that some degree of Li-Si deformation occurred during cell cycling under a uniaxial applied stack pressure of $50\\mathrm{{MPa}}$ with a homemade pressure rig (39). Although pristine $\\upmu\\mathrm{Si}$ did not deform under calendering pressures of $370\\ensuremath{\\mathrm{MPa}}$ , existing reports found that hardness of Li-Si alloys decreases substantially as a function of lithiation, with values reaching as high as 10.0 to 11.6 GPa for pristine Si (40, 41), to as low as 1.3 to 1.5 GPa for fully lithiated $\\mathrm{Li}_{3.75}\\mathrm{Si}$ (40, 42). This trend agrees with our previous observations, where lithiated Li-Si with lower hardness could undergo sufficient deformation to form a dense alloy with low porosity (Fig. 4B), whereas delithiated Li-Si with higher hardness could not be fully deformed, evident from the large interparticle voids observed (Fig. 4C). Although the stack pressure of $50\\ \\mathrm{MPa}$ applied in this study is lower than the range of Li-Si hardness values reported in the literature, absolute conclusions on its deformability cannot be drawn from the hardness values alone. As an example, sulfide glasses, such as ${\\mathrm{Li}}_{2}{\\mathrm{S}}{\\mathrm{-P}}_{2}{\\mathrm{S}}_{5}$ , were previously found to exhibit a hardness value of $1.9\\mathrm{GPa}$ , yet they can be readily deformed at compaction pressures of $360\\ \\mathrm{MPa}$ (43). Likewise, crystalline $\\mathrm{Li}_{6}\\mathrm{PS}_{5}\\mathrm{Cl}$ , which is expected to exhibit higher hardness than glassy $\\mathrm{Li_{2}S\\ –P_{2}S_{5}},$ , can also be deformed into a pellet for cell cycling at 50 MPa (44). Additionally, most mechanical studies conducted on Li-Si alloys have so far been limited to nano-indentation– based experiments on Si thin films, which can exhibit appreciably different mechanical properties compared with the $\\upmu\\mathrm{{Si}}$ used in this work. As such, it is plausible for the lithiated $\\upmu\\mathrm{{Si}}$ to undergo some degree of plastic deformation, especially at higher states of lithiation. To verify this, we lithiated a 99.9 wt $\\%\\upmu\\mathrm{{Si}}$ electrode up to 0.01 V versus $\\mathrm{Li/Li^{+}}$ without pressure in a liquid electrolyte–based coin cell. Subsequently, we imaged the Li-Si electrode before and after pressing at 50 MPa. We observed that some degree of deformation in the lithiated Li-Si alloy was induced, along with a reduction in electrode porosity (fig. S9C). This deformation is necessary to maintain a good contact with the SSE, enabling high reversibility. \n\n# Electrochemical performance \n\nTo test the 99.9 wt $\\%\\upmu\\mathrm{{Si}}$ in full cells, we prepared NCM811 cathode composites using a dry electrode process (fig. S12), with polytetrafluoroethylene (PTFE) as a binder to achieve thick electrodes. These electrodes were characterized by x-ray computed tomography (fig. \n\n![](images/dbf560eeaaa26d417f9f694292375adbeb20fa5a44cf3df82c7e85b31d47e6f2.jpg) \nig. 5. mSi||SSE||NCM811 performance. (A) High current density test. (B) Wide temperature range test. (C) High areal capacity test. (D) Cycle life at room temperature. All cells were tested under similar charge and discharge conditions between 2.0 and $4.3~\\forall.$ The first cycle voltage profile of each respective cell is plotted in black. \n\nS13) and found to achieve improved electrode homogeneity and higher packing density compared with slurry casted electrodes. The dry processed cathode composites were then paired against the $\\upmu\\mathrm{{Si}}$ anodes with an $\\mathrm{{N/P}}$ ratio of 1.1 in full cells. Although higher ${\\mathrm{N}}/{\\mathrm{P}}$ ratios reduce the likelihood of Li plating and cell shorting, they were found to deliver lower average $\\mathrm{CE\\%}$ (fig. S14), likely as a result of higher states of charge reached by the NCM811 cathode for the same voltage cutoff, inducing undesirable impedance growth and contact losses. \n\nFigure 5A shows the room-temperature galvanostatic cycling, where current is gradually increased from $0.2\\mathrm{\\mA\\cm^{-2}}$ at the 1st cycle to $5\\mathrm{\\mA\\cm^{-2}}$ at the 10th cycle. No evidence of a cell shorting occurs up to $5\\mathrm{\\mA\\cm^{-2}}$ at room temperature, which is substantially higher than the typical room-temperature critical current density of Li metal ASSBs (32, 33). In Fig. 5B, another full cell was cycled with a temperature range between $-20^{\\circ}$ and $80^{\\circ}\\mathrm{C}$ using a moderate current density of $0.3\\ \\mathrm{mA}$ $\\mathrm{cm}^{-2}$ . A lower current density is used to overcome the high bulk impedance of the SSE at low temperatures (45). Nonetheless, the cell does not exhibit shorting behavior despite charging at $-20^{\\circ}\\mathrm{C}$ . To evaluate high areal loadings of $\\upmu\\mathrm{Si}$ , we fabricated a full cell with a cathode sized to 12 mAh $\\mathrm{cm}^{-2}$ (fig. S15). To overcome bulk impedance of the thick cathode electrode, we operated the full cell at $60^{\\circ}\\mathrm{C}$ to enhance $\\mathrm{Li^{+}}$ diffusion kinetics (fig. S16), a temperature commonly used in ASSB reports (24). By cycling at $1.2\\mathrm{mA}\\mathrm{cm}^{-2}$ , the $\\upmu\\mathrm{Si}$ anode was found to deliver reversible capacities of more than 11 mAh $\\mathrm{cm}^{-2}(>2890\\mathrm{mAh}\\mathrm{g}^{-1})$ (Fig. 5C). Under continuous cycling at $\\mathrm{12\\mA\\cm^{-2}}$ , the $\\upmu\\mathrm{Si}$ anode delivers stable reversible capacity of more than 5 mAh $\\mathrm{cm}^{-2}$ $\\mathrm{^{\\prime}{>}1250\\ m A h\\ g^{-1})}$ (fig. S12). As room-temperature charge and discharge remains the ideal condition for ASSB operation, cycle life of the full cell was evaluated by maintaining a current density of $5\\mathrm{mAcm^{-2}}$ at room temperature (Fig. 5D). The cell was found to achieve a capacity retention of $80\\%$ after 500 cycles and an average $\\mathrm{CE\\%}$ of ${>}99.9\\%$ . This capacity fade likely occurs as a result of cathode-SSE contact losses and cathode impedance growth (fig. S5). As the cell’s capacity utilization at $5\\mathrm{mAcm^{-2}}$ is arguably low, lower current cycling was also performed (fig. S17), where average $\\mathrm{CE\\%}$ was found to also reach ${\\sim}99.9\\%$ . Additionally, cell cycling at lower stack pressures is also presented in fig. S18. Battery performance described here still represents single-layered pelletized cells with thick SSE separators. The $\\upmu\\mathrm{Si}$ anode’s potential for high energy densities $(>900\\mathrm{~Wh~liter^{-1}},$ can only be realized if SSE thickness can be reduced, in combination with multilayer form factors (table S5). Nonetheless, the electrochemical results shown above reaffirm the effectiveness of sulfide SSEs in enabling 99.9 wt $\\%\\upmu\\mathrm{{Si}}$ anodes, capable of operating with high current densities, over a wide temperature range, and using high areal loadings, as well as achieving a long cycle and calender life. Overall, this approach presents substantial advantages to advance both the silicon anode and ASSB community, offering a pathway to address some of the fundamental interfacial and performance challenges of $\\upmu\\mathrm{Si}$ anodes. \n\n# REFERENCES AND NOTES \n\n1. Y. Jin, B. Zhu, Z. Lu, N. Liu, J. Zhu, Adv. Energy Mater. 7, 1700715 (2017). \n2. A. Franco Gonzalez, N.-H. Yang, R.-S. Liu, J. Phys. Chem. C 121, 27775–27787 (2017). \n3. Y. Yang et al., Sustain. Energy Fuels 4, 1577–1594 (2020). \n4. C. Wang et al., Nat. Chem. 5, 1042–1048 (2013). \n5. J. Chen et al., Nat. Energy 5, 386–397 (2020). \n6. P. Parikh et al., Chem. Mater. 31, 2535–2544 (2019). \n7. H. Shobukawa, J. Shin, J. Alvarado, C. S. Rustomji, Y. S. Meng, J. Mater. Chem. A Mater. Energy Sustain. 4, 15117–15125 (2016). \n8. H. J. Kwon et al., Nano Lett. 20, 625–635 (2020). \n9. Q. Ma et al., ACS Appl. Energy Mater. 3, 268–278 (2019). \n10. A. Baasner et al., J. Electrochem. Soc. 167, 020516 (2020). \n11. S. Cangaz et al., Adv. Energy Mater. 10, 2001320 (2020). \n12. G. Huang et al., ACS Nano 14, 4374–4382 (2020). \n13. Y. Wang et al., Sci. Rep. 10, 3208 (2020). \n14. W. An et al., Nat. Commun. 10, 1447 (2019). \n15. Y. Li et al., Nat. Energy 1, 15029 (2016). \n16. S. Choi, T. W. Kwon, A. Coskun, J. W. Choi, Science 357, 279–283 (2017). \n17. Z. Xu et al., Joule 2, 950–961 (2018). \n18. X. Gao, F. Wang, C. Sam, S. Gollon, C. Yuan, J. Electrochem. Energy Convers. Storage 16, 011009 (2019). \n19. J.-G. Ren et al., Energy Technol. (Weinheim) 1, 77–84 (2013). \n20. J.-K. Kim et al., Solid State Ion. 268, 256–260 (2014). \n21. A. Banerjee, X. Wang, C. Fang, E. A. Wu, Y. S. Meng, Chem. Rev. 120, 6878–6933 (2020). \n22. W. Ping et al., Energy Storage Mater. 21, 246–252 (2019). \n23. J. Sakabe, N. Ohta, T. Ohnishi, K. Mitsuishi, K. Takada, Commun. Chem. 1, 24 (2018). \n24. Y.-G. Lee et al., Nat. Energy 5, 299–308 (2020). \n25. R. Xu et al., ACS Energy Lett. 4, 1073–1079 (2019). \n26. S. Burkhardt et al., ACS Energy Lett. 4, 2117–2123 (2019). \n27. X. Y. Qiu et al., Phys. Chem. Chem. Phys. 14, 2617–2630 (2012). \n28. Z. Chen et al., Adv. Energy Mater. 5, 1401826 (2015). \n29. D. H. S. Tan et al., ACS Energy Lett. 4, 2418–2427 (2019). \n30. T. K. A. Schwietert et al., Nat. Mater. 19, 428–435 (2020). \n31. W. Zhang et al., ACS Appl. Mater. Interfaces 9, 35888–35896 (2017). \n32. S. Randau et al., Nat. Energy 5, 259–270 (2020). \n33. J. Kasemchainan et al., Nat. Mater. 18, 1105–1111 (2019). \n34. E. A. Wu et al., J. Electrochem. Soc. 167, 130516 (2020). \n35. C. Fang et al., Nature 572, 511–515 (2019). \n36. K. Pan, F. Zou, M. Canova, Y. Zhu, J.-H. Kim, J. Power Sources 413, 20–28 (2019). \n37. N. Ding et al., Solid State Ion. 180, 222–225 (2009). \n38. K. Yoshimura, J. Suzuki, K. Sekine, T. Takamura, J. Power Sources 174, 653–657 (2007). \n39. J. M. Doux et al., Adv. Energy Mater. 10, 1903253 (2019). \n40. L. A. Berla, S. W. Lee, Y. Cui, W. D. Nix, J. Power Sources 273, 41–51 (2015). \n41. V. Kulikovsky et al., Thin Solid Films 516, 5368–5375 (2008). \n42. B. Hertzberg, J. Benson, G. Yushin, Electrochem. Commun. 13, 818–821 (2011). \n43. F. P. McGrogan et al., Adv. Energy Mater. 7, 1602011 (2017). \n44. J.-M. Doux et al., J. Mater. Chem. A Mater. Energy Sustain. 8, 5049–5055 (2020). \n45. C. Yu et al., ACS Appl. Mater. Interfaces 10, 33296–33306 (2018). \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge the UCSD Crystallography Facility. This work was performed in part at the San Diego Nanotechnology Infrastructure (SDNI) of UCSD, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the National Science Foundation (grant ECCS-1542148). TGC measurement is made possible by the support of the Office of Vehicle Technologies of the US Department of Energy through Battery500 Consortium (grant DE-EE0007764). Characterization work was performed in part at the UC Irvine Materials Research Institute (IMRI) using instrumentation funded in part by the National Science Foundation Major Research Instrumentation Program under grant no. CHE1338173. Y.S.M. thanks M. H. Kim and S. Bang from LG Energy Solutions for insightful discussions. Funding: This study was financially supported by LG Energy Solution through the Battery Innovation Contest (BIC) program. Z.C. acknowledges \n\nfunding from the start-up fund support from the Jacob School of Engineering at University of California San Diego. Y.S.M. acknowledges funding support from the Zable Endowed Chair Fund. Author contributions: D.H.S.T. and Y.S.M. conceived the ideas for the study. D.H.S.T. and H.Y. designed the experiments and cell configuration. Y.-T.C., W.B., B.S., W.L., B.L., S.-Y.H., B.S., and J.S., performed the XRD, XPS, TGC, FIB-SEM, and CT experiments. Z.C., J.-M.D., E.A.W., G.D., H.E.H., H.J.H., H.J., and J.B.L. participated in the scientific discussion and data analysis. D.H.S.T. wrote the manuscript. All authors discussed the results and commented on the manuscript. All authors have approved the final manuscript. Competing interests: A joint patent application on this work has been filed (US 63/157,012) between UC San Diego’s Office of Innovation and Commercialization as well as LG Energy Solution, Ltd, and licensed by UNIGRID L.L.C. Data and materials availability: All data are available in the manuscript or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nhttps://science.org/doi/10.1126/science.abg7217 \nMaterials and Methods \nFigs. S1 to S18 \nTables S1 to S5 \n\n23 January 2021; resubmitted 6 March 2021 \nAccepted 17 August 2021 \n10.1126/science.abg7217 " + }, + { + "id": "10.1002_anie.202012005", + "DOI": "10.1002/anie.202012005", + "DOI Link": "http://dx.doi.org/10.1002/anie.202012005", + "Relative Dir Path": "mds/10.1002_anie.202012005", + "Article Title": "An Inorganic-Rich Solid Electrolyte Interphase for Advanced Lithium-Metal Batteries in Carbonate Electrolytes", + "Authors": "Liu, SF; Ji, X; Piao, N; Chen, J; Eidson, N; Xu, JJ; Wang, PF; Chen, L; Zhang, JX; Deng, T; Hou, S; Jin, T; Wan, HL; Li, JR; Tu, JP; Wang, CS", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "In carbonate electrolytes, the organic-inorganic solid electrolyte interphase (SEI) formed on the Li-metal anode surface is strongly bonded to Li and experiences the same volume change as Li, thus it undergoes continuous cracking/reformation during plating/stripping cycles. Here, an inorganic-rich SEI is designed on a Li-metal surface to reduce its bonding energy with Li metal by dissolving 4m concentrated LiNO3 in dimethyl sulfoxide (DMSO) as an additive for a fluoroethylene-carbonate (FEC)-based electrolyte. Due to the aggregate structure of NO3- ions and their participation in the primary Li+ solvation sheath, abundant Li2O, Li3N, and LiNxOy grains are formed in the resulting SEI, in addition to the uniform LiF distribution from the reduction of PF6- ions. The weak bonding of the SEI (high interface energy) to Li can effectively promote Li diffusion along the SEI/Li interface and prevent Li dendrite penetration into the SEI. As a result, our designed carbonate electrolyte enables a Li anode to achieve a high Li plating/stripping Coulombic efficiency of 99.55 % (1 mA cm(-2), 1.0 mAh cm(-2)) and the electrolyte also enables a Li||LiNi0.8Co0.1Mn0.1O2 (NMC811) full cell (2.5 mAh cm(-2)) to retain 75 % of its initial capacity after 200 cycles with an outstanding CE of 99.83 %.", + "Times Cited, WoS Core": 403, + "Times Cited, All Databases": 420, + "Publication Year": 2021, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000599074500001", + "Markdown": "# A A Jnournal ogf the Gesellschafwt Deutschaer Chemniker dte International Edition Chemie \n\nwww.angewandte.org \n\n# Accepted Article \n\nTitle: Inorganic-rich Solid Electrolyte Interphase for Advanced Lithium Metal Batteries in Carbonate Electrolytes \n\nAuthors: Sufu Liu, Xiao Ji, Nan Piao, Ji Chen, Nico Eidson, Jijian Xu, Pengfei Wang, Long Chen, Jiaxun Zhang, Tao Deng, Singyuk Hou, Ting Jin, Hongli Wan, Jingru Li, Jiangping Tu, and Chunsheng Wang \n\nThis manuscript has been accepted after peer review and appears as an Accepted Article online prior to editing, proofing, and formal publication of the final Version of Record (VoR). This work is currently citable by using the Digital Object Identifier (DOI) given below. The VoR will be published online in Early View as soon as possible and may be different to this Accepted Article as a result of editing. Readers should obtain the VoR from the journal website shown below when it is published to ensure accuracy of information. The authors are responsible for the content of this Accepted Article. \n\nTo be cited as: Angew. Chem. Int. Ed. 10.1002/anie.202012005 \n\nLink to VoR: https://doi.org/10.1002/anie.202012005 \n\n# Inorganic-rich Solid Electrolyte Interphase for Advanced Lithium Metal Batteries in Carbonate Electrolytes \n\nSufu Liu,[a], $^+$ Xiao Ji,[a],+ Nan Piao,[a],+ Ji Chen,[a] Nico Eidson,[a] Jijian Xu,[a] Pengfei Wang,[a] Long Chen,[a] Jiaxun Zhang,[a] Tao Deng,[a] Singyuk Hou,[a] Ting Jin,[a] Hongli Wan,[a] Jingru Li,[b] Jiangping Tu,[b] Chunsheng Wang [a],\\* \n\n[a] Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, 20740, United States \n[b] State Key Laboratory of Silicon Materials, Key Laboratory of Advanced Materials and Applications for Batteries of Zhejiang Province, and School of Materials Science& Engineering, Zhejiang University, Hangzhou, 310027, China \n\\* Corresponding Author: cswang@umd.edu \n+ These authors contribute equally to this work. \n\nAbstract: In carbonate electrolytes, the organic-inorganic solid electrolyte interphase (SEI) formed on the lithium (Li) metal anode surface is strongly bonded to Li and experiences the same volume change as Li, thus it undergoes continuous cracking/reformation during plating/stripping cycles. Here, an inorganic-rich SEI is designed on a Li metal surface to reduce its bonding energy with Li metal by dissolving $4M$ concentrated $\\mathsf{L i N O}_{3}$ in dimethyl sulfoxide (DMSO) as an additive for a fluoroethylene carbonate (FEC) based electrolyte. Due to the aggregate structure of $N O_{3}^{-}$ ions and its participation in the primary Li+ solvation sheath, abundant $\\mathsf{L i}_{2}\\mathsf{O}$ , Li3N, and $\\mathsf{L i N}_{\\mathsf{x}}\\mathsf{O}_{\\mathsf{y}}$ grains are formed in the resulting SEI, in addition to the uniform LiF distribution from the reduction of $\\mathsf{P F}_{6}^{\\mathsf{^{-}}}$ ions. The inorganic-rich SEI’s weak bonding (high interface energy) to Li can effectively promote Li diffusion along the SEI/Li interface and prevent Li dendrite penetration into the SEI. As a result, our designed carbonate electrolyte enables a Li anode to achieve a high Li plating/stripping CE of $99.55\\%$ (1 mA $\\mathsf{c m}^{-2}$ , 1.0 mAh $\\mathsf{c m}^{-2}$ ) and the electrolyte also enables a Li| $\\mathsf{L i N i}_{0.8}\\mathsf{C o}_{0.1}\\mathsf{M n}_{0.1}\\mathsf{O}_{2}$ (NMC811) full cell (2.5 mAh cm-2) to retain $75\\%$ of its initial capacity after 200 cycles with an outstanding CE of $99.83\\%$ The concentrated additive strategy presented here provides a drop-in practical solution to further optimize carbonate electrolytes for beyond Li-ion batteries. \n\n# Introduction \n\nThe ever-increasing demand for electric vehicles and portable electronics has revitalized the long-term pursuit of Li-ion batteries with higher energy density.[1-4] Due to having the most electronegative potential (-3.04 V vs. standard hydrogen electrode) and ${>}10$ times higher capacity $(3860\\ \\mathrm{mAh}\\ 9^{-1})$ than graphite anodes, Li metal anode batteries can potentially deliver a higher power and energy density, especially when it is coupled with the high-voltage and high-specific-capacity nickel-rich $L i N i_{x}C o_{y}M n_{1-x-y}O_{2}$ (Ni-rich NMC, $N i\\geq60\\%$ ) cathode [5-6]. However, the highly active Li metal reacts with electrolytes and often forms dendrites, resulting in a low Coulombic efficiency (CE) and fast capacity decay. The Li dendrite growth also raises safety hazards with short-circuit concerns, which severely limit the practical applications of rechargeable Li metal batteries (LMBs).[7-10] \n\nAlmost all organic electrolytes will be reduced on metallic Li. Once the Li metal is immersed in carbonate electrolytes, unavoidable reactions occur instantaneously [11-12], forming an organic-inorganic solid electrolyte interphase (SEI) [13-14] to prevent further reaction. However, the nonuniform organicinorgansic SEI cannot dynamically bear the huge volume change during Li plating/stripping cycles, leading to the continuous SEI cracking/reformation, and even Li dendrite formation.[15-17] Therefore, a robust artificial SEI which can accommodate the large volume change of Li is necessary for high-performance LMBs. \n\nTo avoid the fracturing of the SEI, most researches focus on increasing the mechanical flexibility of the SEI to accommodate the infinite volume change during Li plating/stripping by increasing the organic-content in the SEI, and even forming a pure polymer SEI.[18-19] However, the strong bonding (lithiophilicity) between the organic SEI and Li metal also causes the SEI to suffer the same volume change as Li during Li plating/stripping [20-21], and the organic SEI cannot withstand the infinite volume change of the plated Li without breaking. Therefore, the cracking of the organic SEI is unavoidable, as evidenced by the reported low CE. Besides, the strong bonding of the organic SEI with Li also restricts the Li diffusion along the SEI/Li interface and promotes vertical Li penetration into the SEI to form Li dendrites. This dendritic growth is due to the lithiophlic nature and low interfacial energy of the SEI. Since inorganic lithium compounds (such as LiF, $\\mathsf{L i}_{2}\\mathsf{O}$ Li3N, etc.) have weak bonding (lithiophobicity) with a high interfacial energy with Li metal [22-24], these ceramic SEIs can boost the Li lateral diffusion along the SEI/Li interface and suppress metallic Li from penetrating into the inorganic SEI. Meanwhile, the ceramic SEI with a high Young’s modulus is also mechanically strong for better suppression of dendritic growth and penetration of the interface. Therefore, a uniform inorganic SEI with a lithiophobic property is desirable for an advanced Li metal anode, or at least an inorganicrich layer closely attached to metallic Li is highly required. \n\nThe chemical composition of the SEI can be manipulated by tailoring the electrolyte composition, which can alter the interfacial electrolyte environment on electrodes. Among all organic electrolytes, carbonate electrolytes have been extensively used in commercial Li-ion batteries because the flexible organicinorganic SEIs are strongly bonded to graphite and effectively accommodate the small volume change $(\\sim13\\%)$ of graphite during Li intercalation/deintercalation.[25] However, organic-inorganic SEIs cannot accommodate the volume change of a Li metal anode. A large number of additives have been explored in carbonate electrolytes to change the SEI composition. Among the additives, fluoroethylene carbonate (FEC) [26-27] and vinylene carbonate (VC) [28-29] are the most effective additives for carbonate electrolytes because they promote the formation of inorganic LiF and $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ components in the SEI. When used for Li/S batteries, the protective layer formed by FEC in carbonate-based electrolyte is also found to suppress the polysulfide attack against the metal Li anode.[30] However, the reduction of FEC and VC also produces organic compounds, which weaken the effectiveness of FEC and VC for Li-dendrite-suppression.[31-32] Adding more inorganic salts (such as $\\mathsf{L i P F}_{6}$ and $\\mathsf{L i N O}_{3}\\mathrm{.}$ into the electrolyte can increase the contact ion pair and aggregate solvates but it can also reduce the solvation separated ion pair, which will promote reduction of inorganic salts to form an inorganic-rich SEI. $\\mathsf{L i N O}_{3}$ has been regarded as one of the most successful SEI precursor in etherbased electrolytes especially for Li/S batteries, which can react with metallic Li to form a passivation layer and hence suppress redox shuttles of lithium polysulfide.[33-34] However, its poor solubility in both acyclic and cyclic carbonate solvents has long restrained its application in carbonate electrolytes. One method is to maintain $\\mathsf{L i N O}_{3}$ in carbonate solvents by implanting $\\mathsf{L i N O}_{3}$ particles into porous PVDF-HFP [31] or glass fiber [35] as separators or coating layers on Li metal anode surfaces, which will be continuously dissolved into the electrolyte when the trace amount of dissolved $\\mathsf{L i N O}_{3}$ in the electrolyte is consumed. Another method is to add $\\mathsf{L i N O}_{3}$ solubilizers such as copper fluoride [36], $\\gamma-$ butyrolactone [37], and Tin trifluoromethanesulfonate [38], tris(pentafluorophenyl)borane [39] into carbonate electrolytes to improve the solubility of $\\mathsf{L i N O}_{3}$ . However, these $\\mathsf{L i N O}_{3}$ solubilizer additives also destabilize the SEI, as evidenced by a lower Li plating/stripping CE of ${<99\\%}$ than that $(99.3\\%)$ [40] of highly concentrated or all-fluorinated LiFSI (or $\\mathsf{L i P F}_{6})$ single-salt carbonate electrolytes [41]. Therefore, $\\mathsf{L i N O}_{3}$ solubilizers that do not jeopardize the SEI in carbonate electrolytes should be further explored. \n\nHere, we used the solvent dimethyl sulfoxide (DMSO) as a $\\mathsf{L i N O}_{3}$ solubilizer to form an additive solution of $4.0\\mathrm{~M~LiNO}_{3}$ in DMSO, and added it into 0.8 M $\\mathsf{L i P F}_{6}$ FEC/DMC (1:4 by vol.) at 5 $w t\\%$ to form the $\\mathsf{L i N O}_{3}$ saturated electrolyte (denote as $L i N O_{3}{-}S$ ). In the $\\mathsf{L i N O}_{3^{-}}$ S electrolyte, $N O_{3}^{-}$ participates in the primary Li+ solvation sheath at high concentration, enabling $N O_{3}^{-}$ ions to form the aggregates structure. The aggregates solvation structure promotes the preferential reduction of $N O_{3}{}^{-}$ to form an inorganicrich SEI, which can effectively suppress Li dendrite formation and increases the Li plating/stripping CE to a recorded high value of $99.55\\%$ at a current of $1.0\\mathsf{m A c m^{-2}}$ and a capacity of $1.0\\:\\mathrm{mAh}$ cm2. The $99.55\\%$ CE for Li plating/stripping in $\\mathsf{L i N O}_{3}$ -S carbonate electrolytes is the highest CE in all reported carbonate electrolytes, and is even comparable to the recorded value $(99.5\\%)$ of local high-concentrated ether electrolytes [42]. By leveraging the high anodic stability of carbonate electrolytes, $\\mathsf{L i N i}_{0.8}\\mathsf{M n}_{0.1}\\mathsf{C o}_{0.1}\\mathsf{O}_{2}$ (NCM811)||Li full cells with a high areal capacity of 2.5 mAh $\\mathsf{c m}^{-2}$ and a limited Li excess anode $(50\\upmu\\mathrm{m})$ was also evaluated in the designed electrolytes and demonstrated a $75\\%$ capacity retention after 200 cycles (with nearly tripled the cycling lifespan), which is extremely appreciable in carbonate electrolytes. \n\n# Results and Discussion \n\n# Solvation structure and properties of the carbonate electrolyte with $\\pm\\mathsf{i N O}_{3}$ additive \n\nThe solubility of $\\mathsf{L i N O}_{3}$ in both EC/DMC and FEC/DMC electrolytes is very low, as evidenced by $\\textsf{a}$ distinct $\\mathsf{L i N O}_{3}$ sediments at the bottom of both solutions after only $1.0\\mathsf{w t}\\%\\mathsf{L i N O}_{3}$ was added. (Figure S1a, b). The donor number (DN) chemistry [43] has been used to predict the ability to dissociate salts with ion pairs, and a parameter to describe the Lewis basicity of solvents. Basically, the larger the DN value, the better the solvent solubilizes salts. As shown in Figure S2, the DN of EC (16), DMC (17) and FEC (9) are much lower than that of $N{\\mathsf{O}}_{3}{}^{-}$ (22) [43-46]. Therefore, the solubility of $\\mathsf{L i N O}_{3}$ in carbonate solvents is very low. DMSO has a much higher DN number (30) [47] and the $\\mathsf{L i N O}_{3}$ solubility in DMSO is at least two orders of magnitude higher (more than $4000\\mathsf{m M}$ at $25^{\\circ}\\mathsf{C}$ ) than that for carbonate electrolytes. \n\nIn the high-concentrated $4.0\\mathsf{M}\\mathsf{L i N O}_{3}$ -DMSO nitrate solution, free DMSO molecules are far fewer than in dilute solution $(<1.0~\\mathsf{M})$ , and the interionic attractions are pronounced. The unique solvation structure of high-concentrated nitrate electrolytes also increases the viscosity of the bulk electrolyte and changes the SEI compositions on the anodes, as demonstrated in the “water-insalt” aqueous electrolytes [48-49] as well as highly concentrated organic electrolytes [40, 50]. Therefore, antisolvents need to be added into these highly concentrated organic electrolytes in order to reduce their viscosities [41, 51]. In this work, we added a small amount of $4.0\\mathrm{~M~}$ LiN $|\\boldsymbol{\\mathrm{O}}_{3}\\cdot\\boldsymbol{\\mathrm{\\Omega}}|$ -DMSO solution into dilute carbonate electrolytes to leverage merits of both electrolytes while minimizing their weaknesses. To our best knowledge, using a solvent-in-salt solution as an additive to manipulate the SEI composition in dilute electrolytes for LMBs has remained unexplored, which provides a new opportunity to design electrolytes. \n\n![](images/1cbf74a10d3396f773516791f279591fd732b76183d094efb80cf5134be2d9af.jpg) \nFigure 1. MD Simulation and decomposition potential for the $\\mathsf{L i N O}_{3}$ -S electrolyte. (a) The snapshot of the MD simulated box. Li+ ion and coordinated molecules (within $3.5\\mathring{\\mathsf{A}}$ of ${\\mathsf{L i}}^{+}$ ions) are depicted by a ball-and-stick model, while the wireframes stand for the free solvents; (b) Representative Li-solvation structure with $N O_{3}^{-}$ involved and (c) radial distribution function (g(r), solid lines) and coordination numbers (n(r), dashed lines) of $\\mathsf{L i N O}_{3}$ -S electrolyte; (d) Typical CV curves of Li||Cu half cells scanned between $0V-2.5V$ at $0.1\\mathrm{\\mV}\\mathrm{\\mathsf{s}}^{-1}$ in different electrolyte; (e) Optimized ${\\mathsf{L i}}^{+}$ -solvent, $(\\mathsf{L i N O}_{3})_{2},$ and $(\\mathsf{L i P F}_{6})_{2}$ complexes from M052X calculations using SMD $(\\varepsilon{=}20)$ implicit solvation model. Calculated reduction potential vs. Li/Li+ are listed next to each complex). \n\nThe 1.0 M LiPF6 in FEC/DMC (1:4 by vol.) solution was chosen as the base electrolyte (denoted as $\\mathsf{L i N O}_{3}$ -free electrolyte) because it is one of the best carbonate electrolytes for lithium ion batteries [52-53]. For comparison, $\\mathsf{L i N O}_{3}$ -DMSO solutions with varying $\\mathsf{L i N O}_{3}$ salt concentrations were added to $\\mathsf{L i P F}_{6}$ FEC/DMC electrolytes. Due to the “common-ion effect”, the $\\mathsf{L i P F}_{6}$ concentration was reduced to $0.8{\\sf M}$ in order to promote the better $\\mathsf{L i N O}_{3}$ compatibility. As shown in Figure S1c, no precipitation is observed in the electrolyte, even when $5\\mathrm{wt\\%}$ of $4\\M\\sqcup\\ M\\odot_{3}$ -DMSO was added to the $0.8\\mathrm{~M~}$ LiPF6 FEC/DMC electrolyte, suggesting the excellent solvating power of DMSO for $\\mathsf{L i N O}_{3}$ . Here, M represents mole of salt dissolved in a liter of solvent. \n\nClassic molecular dynamic (MD) simulations were performed to understand the solvation structures of these electrolytes. For the $\\mathsf{L i N O}_{3}$ -free electrolyte (Figure S3), the carbonate molecules, including FEC and DMC, are the major component in the primary ${\\mathsf{L i}}^{+}$ solvation sheath. In such carbonate electrolytes, reduction of solvents is preferred with much higher potentials than that of Li metal deposition, resulting in a highly organic-rich SEI with strong lithiophilicity. However, in $\\mathsf{L i N O}_{3}$ -S electrolyte (0.8 M ${\\mathsf{L i P F}}_{6}$ FEC/DMC with $5\\mathrm{\\wt\\%}$ (4 M LiNO3-DMSO)), ions are distributed uniformly throughout the electrolyte as evidenced by the representative snapshot of the $\\mathsf{L i N O}_{3}$ -S electrolyte (Figure 1a). The representative Li solvation structures in Figure 1b & Figure S4 indicate that distinct $N O_{3}^{-}$ ions are involved in the solvation sheath while small amount of DMSO molecules are found. The radial distribution functions show apparent peaks around $1.8\\mathring{\\mathsf{A}}$ , indicating the primary ${\\mathsf{L}}{\\mathsf{i}}^{+}$ solvation sheath with $N O_{3}^{-}$ anion participation (Figure 1c). The coordination numbers for $\\mathsf{P F}_{6}\\bar{\\mathsf{\\Pi}}$ , $N O_{3}\\cdot$ , DMC, DMSO and FEC were found to be 0.24, 0.50, 2.43, 0.66, and 0.40, respectively. Although the $99.7\\%$ of the DMSO are in the Li first solvation shell, the low concentration of DMSO in the mixed electrolyte limits its ratio in the solvation structure. Interestingly, each $N O_{3}^{-}$ anion is found to solvate with an average of $2.63\\ \\mathsf{L i^{+}}$ ion (Figure S5), indicating the successful formation of the aggregates structure, which is similar to the aggregates structure in the pure 4 M $\\mathsf{L i N O}_{3}$ -DMSO (Figure S6). Meanwhile, the Raman spectra of the DMSO solution and carbonate electrolytes with different $\\mathsf{L i N O}_{3}$ concentrations were further studied in Figure S7. As shown in Figure S7a, the pure DMSO displays two typical peaks at $672c m^{-1}$ and $703\\mathsf{c m}^{-1}$ , which correspond to the C-S$\\mathsf{C}$ symmetric asymmetric stretching of DMSO. When $\\mathsf{L i N O}_{3}$ is dissolved in DMSO solvent, the two peaks are maintained in the spectrogram but shift to the higher value, which reaches $678\\mathsf{c m}^{-1}$ and $710~\\mathsf{c m}^{-1}$ in the 4M $\\mathsf{L i N O}_{3}$ -DMSO solution. This is mainly because increasing the $\\mathsf{L i N O}_{3}$ concentration can promote Li+-solvated DMSO structure as well as the association of ${\\mathsf{L}}{\\mathsf{i}}^{+}$ ions with $N O_{3}^{-}$ ions, thus reducing the free DMSO.[54] The similar trend is also find in the FECbased carbonate electrolyte with various concentrated $\\mathsf{L i N O}_{3}$ -DMSO additive (Figure S7b), which further confirms the participation of $N O_{3}^{-}$ ions in the ${\\mathsf{L}}{\\mathsf{i}}^{+}$ solvation structure and the enhanced the coordination strength under improved concentration. The MD simulations and experimental results indicate that the aggregates structure in the $4M$ $\\mathsf{L i N O}_{3}$ -DMSO can be well maintained when it is dissolved into the 0.8 ${\\mathsf{M}}{\\mathsf{L i P F}}_{6}$ in FEC/DMC electrolyte. \n\nThe reduction potentials of $\\mathsf{L i N O}_{3}$ -S and $\\mathsf{L i N O}_{3}$ -free electrolytes were also evaluated using cyclic voltammetry (CV) at a scanning rate of $0.1\\mathrm{\\mV}\\mathsf{s}^{-1}$ in a potential range from $2.5\\mathrm{V}$ to $0.0\\vee$ to avoid Li metal deposition during redox of $\\mathsf{L i N O}_{3}$ . As shown in Figure 1d, the $\\mathsf{L i N O}_{3}$ -S electrolyte shows a distinct reduction slope from 1.65 V to $1.0\\vee$ during the cathodic scan, which is similar to the pure 4 $M L i N O_{3}$ -DMSO solution (Figure S8). The reduction slop between $1.65\\mathrm{V}$ to $\\boldsymbol{\\mathsf{1.0\\vee}}$ is attributed to a cathodic reduction of $\\mathsf{L i N O}_{3}$ [55]. Therefore, the $\\mathsf{L i N O}_{3}$ is reduced in the first discharge process forming the SEI and preventing further reduction of $\\mathsf{L i N O}_{3}$ in the following cycles. Meanwhile, the cathodic peak around $0.6\\vee$ for $\\mathsf{L i N O}_{3}$ -free electrolytes is attributed to the reduction of the carbonate solvent [12, 56], which disappears in the $\\mathsf{L i N O}_{3}$ -S electrolyte, indicating that the SEI formation from reduction of $\\mathsf{L i N O}_{3}$ suppress carbonate reduction at $0.6\\mathsf{V}$ The small peak around $2.1~\\lor$ for both electrolytes can be assigned to the reduction of the inevitable copper oxide on Cu electrode surfaces [57]. \n\nTo further uncover the mechanism, the reduction of the Lisolvent, $\\mathsf{L i N O}_{3}$ , and LiPF6 were studied using quantum chemistry (QC) calculations. Figure 1e shows the optimized structures of solvents and salts before and after reduction and the corresponding reduction potentials. FEC and $\\mathsf{L i P F}_{6}$ ion pairs thermodynamically defluorinate at $\\boldsymbol{\\mathrm{1.93V}}$ and $1.12\\vee,$ respectively, forming LiF, which is in consistent with previous work [58]. However, the FEC ring deformation kinetically prefers a one electron transfer around $0.33~\\mathsf{V}$ before ${\\mathsf{L i}}^{+}$ (or Li metal) coordinates with the fluorine atom of FEC and reduces into LiF [59]. Therefore, the inorganic LiF in the inner SEI primarily results from $\\mathsf{L i P F}_{6}$ reduction. Since the reduction potential of the $\\mathsf{L i N O}_{3}$ dimer (1.23 V) is higher than that of the $\\mathsf{L i P F}_{6}$ dimer (1.12V), $\\mathsf{L i N O}_{3}$ will be reduced first during potential decrease, as confirmed by the CV scan (Figure 1d). The reduction potentials of other Li-solvent complexes are much lower than ${\\mathrm{}}i.0\\ \\vee.$ In summary, $N O_{3}{^-}$ has participated in the primary solvation sheath of ${\\mathsf{L}}{\\mathsf{i}}^{+}$ forming the aggregates solvation structures when the $\\mathsf{L i N O}_{3}$ -DMSO additive is combined with the carbonate electrolyte. The preferential reduction of $\\mathsf{L i N O}_{3}$ and $\\mathsf{L i P F}_{6}$ salts enables the formation of an inorganic LiF, $\\mathsf{L i}_{2}\\mathsf{O}$ , $\\mathsf{L i}_{3}\\mathsf{N}$ , and other nitrides inner SEI layer with an organic outer SEI layer from later solvent reduction. \n\n# Li plating/stripping in LiNO3-S and LiNO3-free electrolytes \n\nThe Li plating/stripping CE on a bare Cu substrate in the electrolytes with various concentrations of $\\mathsf{L i N O}_{3}$ additive was evaluated by a galvanostatic Li plating/stripping test. To mimic the Li plating/stripping cycles of a Li excess anode and minimize the impact of the Cu substrate, a special CE measurement protocol [60] was used here. Prior to cycling, Cu substrate was conditioned by plating 3 mAh $\\mathsf{c m}^{-2}$ of Li metal on the Cu substrate and then the plated Li was fully stripped to $0.5~\\mathsf{V}.$ Afterwards, a total capacity of the Li reservoir $\\prime Q_{\\intercal}=3\\mathsf{m A h c m^{-2}}$ ) was deposited back on the stabilized Cu substrate again at a current of $1.0\\mathsf{m A c m^{-2}}$ . After that, one third of plated Li ( $\\scriptstyle Q_{\\mathrm{C}}=$ 1 mAh cm-2) was stripped/plated in each cycle at the same current density of 1.0 mA cm-2. Finally, the Li remaining after 10 Li plating/stripping cycles was completely stripped to $0.5\\mathsf{V}$ at $1.0\\mathsf{m A c m^{-2}}$ to calculate the cycling CE. As shown in Figure 2a the Li nucleation overpotential is reduced and the CE is increased with increasing $\\mathsf{L i N O}_{3}$ concentration in DMSO. The peak overpotential (inset in Figure 2a) represents the nucleation overpotential to overcome the heterogeneous nucleation barrier of metallic Li on Cu surfaces. With the addition of $\\mathsf{L i N O}_{3}$ , the nucleation potential decreases from $140~\\mathsf{m V}$ to $75\\mathrm{~}\\mathsf{m V},$ suggesting that the $\\mathsf{L i N O}_{3}$ additive promotes the formation of a highly Li-ion conductive SEI. Meanwhile, the Li plating/stripping CE increases with the $\\mathsf{L i N O}_{3}$ concentration and the $\\mathsf{L i N O}_{3}$ -S electrolyte has the highest CE of $99.55\\%$ at a current of $1.0\\mathsf{m A c m^{-2}}$ and a capacity of 1.0 mAh cm2, which is one of the best value reported for LMBs in all carbonate electrolyte systems at similar currents and capacities (Table S1). In addition, we also tested the electrochemical performance of $\\mathsf{L i N O}_{3}$ -S electrolyte by one-solution route, namely all the solvent and salt compounds are mixed together at once. Its CE can also reach a high value of $99.34\\%$ (Figure S9) but is a little lower than that of $\\mathsf{L i N O}_{3}$ -S electrolyte by two-solution route $(99.55\\%)$ . It is possible that the heating process in one-solution route promotes the side reaction between FEC and $\\mathsf{L i P F}_{6}$ in $\\mathsf{L i N O}_{3}$ -S electrolyte, thus generating more impurities in the electrolyte.[61] Meanwhile, experimental error may also cause this subtle difference. Therefore, our two-solution strategy is more convenient in minimizing the errors during electrolyte preparation. The gaseous product of $\\mathsf{L i}||\\mathsf{C u}$ cell in $\\mathsf{L i N O}_{3}$ -S electrolyte after the cycling was also studied by mass spectrometer (MS), which confirms there is almost no N-contained gas generated and thus no serious gas concern in our designed electrolyte (Figure S10). It is possible that $\\mathsf{L i N O}_{3}$ is directly reduced to $\\mathsf{L i}_{2}\\mathsf{O}$ and $\\mathsf{L i}_{\\mathsf{x}}\\mathsf{N O}_{\\mathsf{y}}$ to form the SEI on Li metal surface or the resulted ${\\sf N}_{2}$ and N-O gas further react with metallic Li to create Li3N and $\\mathsf{L i}_{\\mathsf{x}}\\mathsf{N O}_{\\mathsf{y}}$ ,[34, 62] thus almost no Ncontained gas has been tested in our electrolyte. The specific SEI components will be discussed by the next part in detail. \n\nThe cycling stability of Li anodes highly depends on the CE and Li utilization in each cycle. In practical LMBs, Li metal normally is not fully removed from the current collector and there are always excess Li remained on the anode [63]. The theoretical capacity retention $(Q_{\\mathsf{R}})$ at a certain CE and Li utilization $(\\mathsf{Q c}/\\mathsf{Q}_{\\top})$ can be calculated using the followed equation: $Q_{R}=Q_{T}-n(1-C E)Q_{C}$ If the Li metal utilization is $33.3\\%$ $(Q_{\\mathsf{C}}/Q_{\\mathsf{T}})$ , the calculated capacity drops with Li plating/stripping cycles as shown in Figure S11, which clearly demonstrates the importance of CE for long-term cycling stability. Figure 2b shows that Li anodes in the $\\mathsf{L i N O}_{3}$ -free electrolyte can only survive for 41 cycles even at a low Li utilization of $33\\%$ due to a CE of $97\\%$ . By contrast, the Li anodes in the $\\mathsf{L i N O}_{3}$ -S electrolyte exhibits a stable cycling profile for 100 cycles without any obvious voltage polarization increase. The Li CE after 100 cycles is still maintained as high as $99.42\\%$ . At a high capacity of $2\\mathsf{m A h}\\mathsf{c m}^{-2}$ , the Li CE in the $\\mathsf{L i N O}_{3}$ -S electrolyte still maintained a high value of $99.16\\%$ while it dropped to $96.31\\%$ in the $\\mathsf{L i N O}_{3}$ -free counterpart (Figure S12). Li deposition kinetics were further investigated in a Li||Cu half-cell using CV in the potential range of $-0.3V{-}0.6V$ (Figure 2c). The Li plating/stripping currents in the $\\mathsf{L i N O}_{3}$ -S electrolyte are much larger than in the $\\mathsf{L i N O}_{3}$ -free electrolyte, demonstrating fast reaction kinetics. Moreover, the nucleation onset potential in the $\\mathsf{L i N O}_{3}$ -S electrolyte is decreased by $44~\\mathsf{m V}$ compared to that in the $\\mathsf{L i N O}_{3}$ -free electrolyte, further confirming the high reaction kinetics for Li deposition in the $\\mathsf{L i N O}_{3}$ -S electrolyte. \n\n![](images/5208dcf5c1de3f5ef3b66c8dd248d10ab78872080f591339af02ba3795968190.jpg) \nFigure 2. Li plating/stripping performance in various electrolytes. (a) Li plating/stripping CE in Li||Cu cells in electrolytes with different concentrations of $\\mathsf{L i N O}_{3}$ at a current density of $1\\mathsf{m A c m^{-}}$ 2 and a capacity of $1\\mathsf{m A h c m^{-2}}$ . The insets are magnified view of the Li nucleation potential and final stripping capacity in various electrolytes. (b) The Li plating/stripping voltage during long-term cycling; (c) CV curves for Li plating/stripping between $-0.3V{-}0.6V$ at a scan rate of $2~\\mathsf{m}\\mathsf{V}~\\mathsf{s}^{-1}$ ; (d) Polarization comparison of Li plating/stripping in $L i N O_{3}{-}S$ and $\\mathsf{L i N O}_{3}$ -free electrolytes at different current densities. \n\nThe electrochemical impedance spectroscopy (EIS) evolution in the Li||Li symmetrical cell can also be utilized to evaluate the interfacial dynamics of the Li metal anode. It is generally accepted that the semicircle in the high-frequency region is attributed to the \n\nLi-ion diffusion through the SEI $(\\mathsf{R}_{\\mathsf{S E l}})$ . As displayed by the Nyquist plots in Figure S13a, the $\\mathsf{R}_{\\mathsf{S E I}}$ in the $\\mathsf{L i N O}_{3}$ -free electrolyte has an initial impedance of around $\\boldsymbol{125\\ \\Omega}$ , and this value increases to nearly $175\\Omega$ after a $15\\mathsf{h}$ rest due to growth of the SEI. A similar impedance increase is found in the $\\mathsf{L i N O}_{3}$ -S electrolyte (Figure S13b). By contract, the SEI resistance of Li is very small and stable in the $\\mathsf{L i N O}_{3}$ -S electrolyte with only a minor increase from $20~\\Omega$ to $26\\ \\Omega$ (nearly one seventh of the $\\mathsf{L i N O}_{3}.$ -free electrolyte) after the same resting step, which further proves that the LiNO3 additive forms a thin and dense SEI with a higher Li-ion conductivity. Such a stable SEI in the $L i N O_{3}{-}S$ electrolyte with a low interfacial resistance is beneficial for promoting the uniform Li deposition and suppressing the dead Li formation during cycling. Specifically, the rate performance under a capacity of 1.0 mAh cm2 in symmetrical Li cells in two electrolytes were also compared in Figure S14a. Generally, the voltage hysteresis in both electrolytes increased with current density owing to the increased dynamics resistances, but the overpotential of Li plating/stripping in the $\\mathsf{L i N O}_{3}$ -S electrolyte was much less than that observed in the $\\mathsf{L i N O}_{3}$ -free electrolyte. The enlarged view of the overpotential vs. capacity during the entire cycling process is also plotted (Figure S14b, c), and the more visualized evolution of the average overpotential between Li plating/stripping at different current densities is presented in Figure 2d. Impressively, a much smoother voltage plateau (Figure S14b) with small polarizations of 26, 42, 108, and $210~\\mathsf{m V}$ at 0.5, 1.0, 3.0, and $5.0\\ m A\\ \\mathsf{c m^{-2}}$ , respectively, were observed in the $\\mathsf{L i N O}_{3}$ -S electrolyte, which are all far below the values of the $\\mathsf{L i N O}_{3}$ -free electrolyte. Such a great stability enhancement is definitely stemmed from a more stable SEI with reduced impedance for the uniform Li plating/stripping and improved charge transfer kinetics. By contrast, the cell overpotential in the $\\mathsf{L i N O}_{3}$ -free electrolyte shows irregular voltage hysteresis fluctuations with a large overpotential peak at the initial and end of the plating/stripping process (Figure S14c). The strong bonding between Li and the organic-rich SEI is responsible for the high initial overpotential. This becomes smaller after SEI cracking occurs due to the huge volume expansion occurring during Li plating, while the reformation/growth of SEI at the end of Li deposition increases the overpotential again. As a result, the repeated breaking/reformation of the SEI increase its thickness with higher ionic resistance, which is further confirmed by the larger impedance of cycled Li||Li cells in the $\\mathsf{L i N O}_{3}$ -free electrolyte than tin $\\mathsf{L i N O}_{3}$ -S electrolyte (Figure S15). The morphology of deposited Li metal was also evaluated by scanning electron microscopy (SEM). After plating 3 mAh $\\mathsf{c m}^{-2}$ of Li on Cu substrates at $1\\mathsf{m A}\\mathsf{c m}^{-2}$ , coin cells were disassembled for microscopic analysis. The typical diagrams for Li morphologies in $\\mathsf{L i N O}_{3}$ -free and $\\mathsf{L i N O}_{3}$ -S electrolytes have been displayed in Figures 3a and 3d, respectively. As revealed in Figure 3b, nodule-like Li, rather than whiskers, is found on top of plated Li in the $\\mathsf{L i N O}_{3}$ -free electrolyte, which is in agreement with previous reports that the FEC-rich electrolyte can generate a LiFcontained SEI enabling blocky Li growth $[64-65]$ . However, the plated Li is separated and stacked with each other, forming porous Li, and thus reducing CE under continuous cycling. The deposited Li in the $\\mathsf{L i N O}_{3}$ -free electrolyte also manifests as a loosely packed structure, resulting in a ${\\sim}19.5~{\\upmu}{\\sf m}$ -thick Li layer from the cross-section image (Figure 3c). In stark contrast, the top-view image of the deposited Li in the $\\mathsf{L i N O}_{3}$ -S electrolyte shows a dense surface with rounded edges tightly connected as a dense layer under the protective layer (Figure 3e), which displays a smaller thickness of $\\sim14.8~{\\upmu\\mathrm{m}}$ due to its compact structure (Figure 3f). The inserted optical pictures in Figures 3b and 3e also clearly demonstrate that the electrodeposited of Li in the $\\mathsf{L i N O}_{3}$ -S electrolyte has a silver-white color, closer to the pristine Li metal, indicating that the derived SEI is more stable at preventing side reactions with Li metal. In contrast, the electrodeposited Li in the $\\mathsf{L i N O}_{3}$ -free electrolyte is darker. More vivid evolution of the morphology with the increased areal capacity was further revealed by additional SEM images (Figure S16). It is shown that the deposited Li gradually grows into the intimate aggregates without porosity in the $\\mathsf{L i N O}_{3}$ -S electrolyte while the loose Li structure with smaller particles is shown in the $\\mathsf{L i N O}_{3}$ -free electrolyte. It was reported that a high CE can be achieved when chunky Li is deposited with low tortuosity and intimate connection to maintain the bulk integrity.[21] Since the side reactions between the deposited Li and the $\\mathsf{L i N O}_{3}.$ -S electrolyte have been greatly reduced, an outstanding CE with a Li metal anode has been achieved. \n\n![](images/9f40f06d3c09cf328d0290a50b9aa3503dc72d6ed483bdbd433ff48c787ce28c.jpg) \nFigure 3. Schematic diagrams and typical SEM images of the plated Li morphology. Metallic Li is electrochemically deposited $\\mathop{:}1\\mathop{\\:\\mathsf{m A c m^{-2}}}$ , 3 mAh cm-2) on the bare Cu substrate in the (a-c) $\\mathsf{L i N O}_{3}$ -free electrolyte and (d-f) $\\mathsf{L i N O}_{3}$ -S electrolyte. \n\n# Characterization of the inorganic-rich SEI \n\nThe SEI compositions formed in the $\\mathsf{L i N O}_{3}$ -S electrolyte and the $\\mathsf{L i N O}_{3}$ -free electrolyte were characterized by in-depth $\\mathsf{X}$ -ray photoelectron spectroscopy (XPS) with continuous Ar-ion sputtering from the surface to the bottom (closer to the Li metal). Figures 4a-d display the SEI composition on the Li anodes after 20 plating/stripping cycles $\\mathsf{1\\ m A\\ c m^{-2}}$ , $1\\ m A\\mathsf h\\ c m^{-2})$ in $\\mathsf{L i N O}_{3}$ -S and $\\mathsf{L i N O}_{3}$ -free electrolytes. The cycled Li was transferred under an inert Ar atmosphere to avoid any contamination by air or moisture. For the indicative C 1s spectrum, the organic components derived from carbonate solvents exist in both SEI layers. The top surface of the SEI formed in the $\\mathsf{L i N O}_{3}$ -free electrolyte has a much stronger C-O peak, initially around 286.5 eV, and the C-H/C-C (284.6 eV) intensity persists without distinct attenuation during the whole 600 s sputtering (Figure $\\pmb{4}\\overrightarrow{a}$ , indicating organic compounds are enriched from the surface to the inner part. Clear organic species are also found in the upper SEI formed in the $\\mathsf{L i N O}_{3}$ -S electrolyte, such as - $-\\mathsf{C O}_{3}.$ - and C-O groups, which may serve as the connectors of SEI to withstand the volume change during cycling.[66] However, all these C 1s signals, especially C-C/C-H and - $\\cdot{\\mathsf{C O}}_{3}.$ - peaks, drop sharply after 300 s of etching (Figure 4c), which demonstrates much less organic reduction species in the inert part of the SEI. For the F 1s spectrum, the specific LiF and $\\mathsf{L i}_{\\mathsf{x}}\\mathsf{P F}_{\\mathsf{y}}$ signals are also observed in both electrolytes, which results from the decomposition of $\\mathsf{L i P F}_{6}$ salt and FEC solvent [52]. LiF has been well-known as an excellent SEI component for its high interfacial energy with Li metal and high mechanical strength, thus it is effective at suppressing dendrite growth and enabling uniform Li deposition. Therefore, FEC-based carbonate electrolytes usually exhibit better Li metal performance than EC-based ones. For the SEI in the $\\mathsf{L i N O}_{3}$ -S electrolyte, the inorganic $\\mathsf{L i N O}_{2}$ , $\\mathsf{L i N}_{\\mathsf{x}}\\mathsf{O}_{\\mathsf{y}},$ Li3N, and $\\mathsf{L i}_{\\mathsf{x}}\\mathsf{N}_{\\mathsf{y}}$ species are present, suggesting that $\\mathsf{L i N O}_{3}$ has been reduced to form the resulting SEI. Besides, Li3N is a lithium super ionic conductor [67], which can help enhance the ion transport property of the SEI. More importantly, the $\\mathsf{L i}_{2}\\mathsf{O}$ content from the O 1s spectrum is significantly improved especially after deeper etching, which reveals that the decomposition of $\\mathsf{L i N O}_{3}$ also helps to promote more inorganic $\\mathsf{L i}_{2}\\mathsf{O}$ grains in the resulting SEI. As we discussed early for the solvation structure of the $\\mathsf{L i N O}_{3}$ -S electrolyte, $\\mathsf{L i N O}_{3}$ is prone to being reduced at a higher potential, and thus contributes more inorganic ceramics to the inert SEI close to Li metal when compared with the carbonate solvent. Meanwhile, no clear S signal is found in the $\\mathsf{S2p}$ spectrum (Figure S17), clearly demonstrating no detectable side reaction of DMSO due to the effective stabilization of Li metal anode by $\\mathsf{L i N O}_{3}$ additive in the $\\mathsf{L i N O}_{3}$ -S electrolyte, which is in good agreement with solvation structure analysis. However, we cannot completely exclude the decomposition of DMSO. \n\nFigures 4b and 4d compare the atomic composition ratios in the SEI at different etching times. As shown in Figure 4b, the C atomic signature, as an indicator for organic components, is the highest among all elements on the SEI surface. Therefore, more organic species were observed in the outer layer of the SEI after cycling in the reference $\\mathsf{L i N O}_{3}$ -free electrolyte. With the etching, the organic species gradually decreased, but still maintained a high percentage of $15.6\\%$ after 600s of sputtering, indicating polymer is still enriched in the entire SEI. In sharp contrast to Figure 4d, the C ratio is sharply decreased to only $5.2\\%$ while the total of the Li and O ratios reached an ultrahigh value of $81.6\\%$ after 600s of sputtering, confirming that a highly inorganic-rich inner SEI layer on Li is obtained in the $\\mathsf{L i N O}_{3}$ -S electrolyte. It needs to mention that the outer organic component may be reduced by the electron leakage due to the defects in the inner SEI layer such as radicals[68], interstitials[69], and polarons[70]. But nonetheless, much more inorganic species are still concentrated in the SEI layer formed in the $\\mathsf{L i N O}_{3}.$ S electrolyte, both on the surface as well as in the bulk. Specifically, inorganic species, taking Li and O elements as the indicators, always occupy the major components of the outer SEI layer. Meanwhile, the atomic ratios of F and N elements exhibit no huge fluctuation during the entire sputtering, indicating the relatively homogeneous fluoride and nitride distribution in the resulting SEI at different depths. \n\nThe more detailed morphology and structure of the SEI formed in the $\\mathsf{L i N O}_{3}$ -S electrolyte was further characterized by time-offlight secondary ion mass spectroscopy (ToF-SIMS). As shown in Figures 4e and 4f, the edge surface of the crater presents an explicit etching layer of around $130\\mathsf{n m}$ thickness after sputtering with an $\\mathsf{G a}^{+}$ ion beam $(20\\upmu\\mathrm{m}\\times20\\upmu\\mathrm{m}$ area). In the negative mode, obvious O, F and NO signals were found within the top $10\\ \\mathsf{n m}$ surface layer (Figure ${\\pmb q}_{\\pmb q}.$ ), which reveals that the thickness of the formed SEI is estimated to be around 10 nm.The O signal aggregates with a distinct distribution because $\\mathsf{L i N O}_{3}$ in the $\\mathsf{L i N O}_{3}$ -S electrolyte is preferentially reduced to form $\\mathsf{L i}_{2}\\mathsf{O}$ and suppresses the reduction of the carbonate solvent molecules (forming polycarbonate). The structural information of the SEI components were further detected by high-revolution transmission electron microscopy (HTEM) using a cryogenic temperature stage owing to the fragile property of the electrode interphase. Li metal was directly deposited on a Cu TEM grid for a convenient cryotransfer protocol. Abundant polycrystalline inorganics with various lattice spacings, mainly matching the planes of $\\mathsf{L i}_{2}\\mathsf{O}$ and $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ , can be clearly identified as well as the existing amorphous structure. Specifically, the $\\mathsf{L i}_{2}\\mathsf{O}$ species are more distributed on the inner side of the SEI, forming large amounts of heterogeneous grain boundaries spatially (Figure S18a). Although no fluoride or nitride crystalline phases was observed by HTEM, the existence of crystalline LiF, $\\mathsf{L i}_{2}\\mathsf{O}$ and $\\mathsf{L i}_{3}\\mathsf{N}$ in SEI was confirmed by the electron patterned diffraction (Figure S18b). Meanwhile, the elements O, F and N have been captured over the entire region via an elemental mapping with an energy dispersion spectrum (Figure S19). \n\n![](images/14c5ef37a3f5a45f7777a471011b0c8eb40da03819da74cf49a96d227438a8d8.jpg) \nFigure 4. The in-depth structure characterization of the SEI on the Li metal surface. (a-d) The typical elemental spectra and the atomic composition ratios by XPS measurement of the SEI layer formed in (a, b) $\\mathsf{L i N O}_{3}$ -free and (c, d) $\\mathsf{L i N O}_{3}$ -S electrolyte. The binding energy was calibrated with C 1s at $284.6\\mathsf{e V}$ and a Shirley BG type was used for background subtraction. Both peak deconvolution and assignments in C1s, O1s, N1s, and F1s spectra are presented. (e-g) The interface analysis of the deposited Li metal in the $\\mathsf{L i N O}_{3}$ -S electrolyte by ToFSIMS: (e,f) The crater with a magnified image of around $130~\\mathsf{n m}$ sputtered by a $\\mathsf{G a}^{+}$ ion beam and (g) the corresponding O, F, N, and NO distributions in the sputtered cross section. (h) The structure schematic of the inorganic-rich SEI formed in the $L i N O_{3}{-}S$ electrolyte for uniform Li deposition. \n\nBased on the discussion above, we can infer that the $\\mathsf{L i N O}_{3}$ additive has effectively altered the spatial distribution of inorganics as well as its components in the SEI in the FEC-based carbonate electrolyte. Despite traces of solvent molecules inevitably participating in the SEI formation, the addition of $\\mathsf{L i N O}_{3}$ promotes the generation of much more $\\mathsf{L i}_{2}\\mathsf{O}$ and N-containing components in the interface with bulk Li metal. The SEI mainly consists of stacked inorganic compounds as shown in Figure 4h, where inorganic nanocrystallites are dispersed throughout the amorphous matrix. It mainly displays an abundant distribution of inorganic particles, in which $\\mathsf{L i}_{2}\\mathsf{O}$ , $\\mathsf{L i}_{3}\\mathsf{N}$ , and LiF are more enriched at the metallic Li interface, with more $\\mathsf{L i}_{2}\\mathsf{C O}_{3}$ , $\\mathsf{L i N}_{\\mathsf{x}}\\mathsf{O}_{\\mathsf{y}}$ , and LiF next to it, and an organic layer on the electrolyte side of the SEI. Moreover, the highly ordered crystals with directional layout and large grain boundaries can significantly affect the Li-ions’ diffusion through the SEI, and what needs to be mentioned is that the amorphous area may also be composed of inorganic components (with trace organic polymer based on the ultralow C content). As a result, those inorganic components (including LiF, $\\mathsf{L i}_{2}\\mathsf{O}$ , ${\\mathsf{L i N}}_{\\mathsf{x}}{\\mathsf{O}}_{\\mathsf{y}},$ and $\\mathsf{L i}_{3}\\mathsf{N}_{.}^{\\prime}$ ) dominate the main constituents of the interphase layer, and thus, enable the advanced and inorganic-rich SEI to display high interfacial energy, outstanding mechanical properties, and ion-transport capabilities. \n\n# Performance of Li||NMC811 full cells \n\nThe Li||NMC811full-cell performance with $\\mathsf{L i N O}_{3}$ -S and $\\mathsf{L i N O}_{3}$ - free electrolytes was also compared using a $\\mathord{\\sim}50~\\upmu\\mathrm{m}$ Li metal anode and NMC811 cathode at an areal capacity of $2.5~\\mathsf{m A h}$ cm2. The electrochemical oxidation window of the electrolytes was firstly evaluated on stainless steel electrodes using a linear sweep voltammetry (LSV). As shown in Figure S20, the LiNiO3-S electrolyte shows an oxidative stability potential of $>4.5~\\mathsf{V}.$ Moreover, the CV curve of Li||NMC811 cells in the $\\mathsf{L i N O}_{3}$ -S electrolyte exhibit three charactistic peaks (Figure S21), representing the typical phase transitions for the NMC cathode. Therefore, the $\\mathsf{L i N O}_{3}.$ -S electrolyte is compatible with the highvoltage nickel-rich cathode. The long-term cycling stability of Li||NMC811 cells was investigated at $0.5\\mathrm{~C~}$ after two formation cycles at $0.1\\mathrm{~C~}$ (Figure 5a). The Li||NMC811 cell with the $\\mathsf{L i N O}_{3}.$ - free carbonate electrolyte showed continuous capacity decay during the charge/discharge cycles with an abrupt drop in both capacity and CE around the $80^{\\mathrm{th}}-85^{\\mathrm{th}}$ cycles. In contrast, an improved cycling performance with almost triple the lifespan was achieved using the $\\mathsf{L i N O}_{3}$ -S electrolyte with a high capacity retention of $75\\%$ after 200 cycles and an outstanding CE of $99.83\\%$ with no sign of any dramatic change. The voltage-capacity profiles in Figures 5b and 5c show that the cell discharging capacity in the $\\mathsf{L i N O}_{3}$ -free electrolyte dropped to $1.22m{\\mathsf{A}}{\\mathsf{h}}\\ {\\mathsf{c m}}^{-2}$ after 100 cycles, while the Li-NMC811 cell with the $\\mathsf{L i N O}_{3}$ -S electrolyte maintains a capacity of $2.15\\mathsf{m A h c m^{-2}}$ . In addition, cell discharge voltage in the $\\mathsf{L i N O}_{3}$ -free electrolyte also decreased faster than that in the $\\mathsf{L i N O}_{3}$ -S electrolyte, indicating that the sustainability of the SEI is greatly enhanced by the $\\mathsf{L i N O}_{3}$ additive. \n\nIt needs to emphasize that the inorganic-rich SEI formed in $\\mathsf{L i N O}_{3}$ -S electrolyte is well maintained on the surface of Li metal anode at different cycles (Figure S22 and Figure S23). Although SEI cracks may happen during cycling, the preferential reduction of $\\mathsf{L i N O}_{3}$ and $\\mathsf{L i P F}_{6}$ can promote more inorganic components in the SEI and further effectively supress the crack deterioration because of its low bonding with metallic Li. Due to the high interfacial energy, outstanding mechanical property and iontransport capability, the inorganic-rich SEI effectively suppresses the dendrite formation and improves the Li CE, thus enabling the excellent performance of Li||NCM811 cell with limited Li excess. By comparison, a much more organic-rich SEI is formed on Li metal surface of Li||NCM811 cell after cycling in $\\mathsf{L i N O}_{3}$ -free electrolyte (Figure S24), similar to the XPS results in Li symmetric cells (Figure 4a, b). To further uncover the kinetic features of the electrode interface, EIS of the Li||NCM811 cells after various cycles were also carried out (Figure S25). The Nyquist plots of the cells always contain one semicircle at high frequencies, which are connected with Li+ transfer through the interface and its specific resistance can be measured by the radius value. Generally, the interfacial resistance increased from the initial to the later cycles in both $\\mathsf{L i N O}_{3}$ -free and $\\mathsf{L i N O}_{3}$ -S electrolyte, which is mainly due to the accumulated thickness of SEI. But compared with the cell in $\\mathsf{L i N O}_{3}$ -free electrolyte, the Li||NCM811 cell in $\\mathsf{L i N O}_{3}$ -S electrolyte always exhibits a smaller total interfacial resistance with the slower growth rate during the cycling, which can be attributed to the formation of a more stable SEI with faster kinetics. \n\n![](images/f02302d6dd541c4bdeeae3491adfdf98c623d60be50dc868ee6637b2f6d5d50f.jpg) \nFigure 5. Performances of Li||NCM811 full cell in $\\mathsf{L i N O}_{3}$ -S and $\\mathsf{L i N O}_{3}$ -free electrolytes. (a) Cycling performance of Li||NCM811 cells with $50~{\\upmu\\mathrm{m}}$ Li at $0.5\\mathrm{~C~}$ . (b, c) Corresponding charging/discharging profiles of Li||NCM811 batteries after 4, 50, and 100 cycles with (b) $\\mathsf{L i N O}_{3}$ -free and (c) $\\mathsf{L i N O}_{3}$ -S electrolytes. (d) The capacity loss of 10.4 mAh $\\mathsf{c m}^{-2}$ Li after 50 cycles in different electrolytes. Only $1.1\\mathsf{m A h\\ c m^{-2}}$ of Li was lost in the $\\mathsf{L i N O}_{3}$ -S electrolyte, while a large amount of $6.47\\ m A{\\mathsf h}\\mathsf c{m}^{-2}$ of Li was lost in $\\mathsf{L i N O}_{3}$ -free electrolyte after 50 cycles. \n\nFigure S26 shows the morphology of Li metal anodes in Li||NCM811 cells after 50 cycles in both electrolytes. The electrode surface in the $\\mathsf{L i N O}_{3}$ -free electrolyte (Figure S26 a, b) has been covered with Li filaments and dendrites, resulting in a quick capacity decay. Meanwhile, the plated Li in the $\\mathsf{L i N O}_{3}$ -S electrolyte shows a much more uniform and dense morphology with a large granular structure (Figure S26 c, d). To determine the exact amount of Li loss, a Li||NMC811 cell was disassembled after 50 cycles and then the residual Li in the cycled Li anode was completely stripped to $-0.5\\mathsf{V}$ in a reassembled $\\mathsf{L i}||\\mathsf{C u}$ cell. As shown in Figure 5d, the fresh Li disk delivers a pristine capacity of $10.4\\ m A\\mathsf{h}\\ c m^{-2}$ (black line). The areal Li loss after 50 cycles in the $\\mathsf{L i N O}_{3}$ -S electrolyte is only 11 mAh $\\mathsf{c m}^{-2}$ , which is calculated by dividing the capacity difference by the area $(1.27\\ c m^{-2})$ . However, as high as 6.47 mAh cm-2 of Li is lost after 50 cycles in the $\\mathsf{L i N O}_{3}$ -free electrolyte, which is more than 5 times of active Li consumed by the corrosive carbonate electrolyte under the same cycling conditions. Such a stark difference further demonstrates the importance of high Li metal CE for capacity retention and reveals the great potential of the $\\mathsf{L i N O}_{3}$ additive in improving the lifespan of rechargeable LMBs. \n\nThe electrochemical performance of LMBs is significantly improved simply by incorporating the $\\mathsf{L i N O}_{3}$ -DMSO additive in currently used carbonate electrolytes, which is of vital importance to match the high-voltage cathode for higher energy density. Compared with the reported highly concentrated electrolytes, the 4 M LiNO3-DMSO additive is only added by $5\\mathrm{\\Delta}w t\\%$ in the dilute FEC-based electrolyte and thus our designed electrolyte has greater superiorities in lower viscosity, better wettability to electrodes and separator, and lower cost, which is promising for high-energy Li metal batteries. To avoid trial-and-error strategies, the electrolyte design principle of forming an inorganic SEI and on Li anodes and a CEI on high voltage cathodes is highly recommended to facilitate the screening process, especially for selecting less-soluble additives. The electrolytes for Li batteries have to satisfy the following requirements: (i) Since an inorganic SEI has a high interfacial energy with metallic Li, high mechanical stiffness, and rapid ionic diffusion along grain boundaries, the electrolytes should be able to form an inorganic-rich SEI, with at least an inorganic-rich layer is desirable in the inner side which is compactly attached to Li metal anode. (ii) To facilitate the formation of an inorganic SEI, lithium salts with inorganic anions (like nitrate, nitrite, borate, fluoroborate, etc.) without organic hydrocarbon groups are suggested as the additive, of which the oxidation potential also needs to be higher than the carbonate solvents. (iii) For additive salts with extremely low solubility in carbonate electrolytes, cosolvents with higher polarity and donor number can be used to promote dissociation. However, to restrain the side reaction of the co-solvent with metallic Li, the concentration of additive salts in the co-solvent should be as high as possible, which can help to increase the lowest unoccupied molecular orbital of the co-solvent for better stability. Besides, such a “concentrated additive” design also favors the anion of the additive to bond more ${\\mathsf{L i}}^{+}$ , promoting the formation of anion aggregates structure with easier decomposition. (iv) Multifunctional additives or the synergistic effect of multiple additives (wide temperature range and low flammability) should also be considered for rechargeable LMBs, especially for larger cells. \n\n# Conclusion \n\nIn summary, an inorganic-rich SEI was constructed on Li metal anodes by adding small amounts of $\\mathsf{L i N O}_{3}$ saturated DMSO into FEC-based carbonate electrolytes. The ${\\mathsf{L}}{\\mathsf{i}}^{+}$ coordination structure with $N O_{3}^{-}$ and $\\mathsf{P F}_{6}{\\mathrm{^{-}}}$ favored the formation of $\\mathsf{L i}_{2}\\mathsf{O}$ , $\\mathsf{L i}_{3}\\mathsf{N}$ , $\\mathsf{L i N}_{\\mathsf{x}}\\mathsf{O}_{\\mathsf{y}}$ , and LiF abundant SEI layers, which increased the interfacial energy and improved the ionic diffusion as well as the mechanical property of the SEI. The lithiophobic inorganic-rich SEI can effectively suppress the Li dendrite formation and regulate Li deposition as demonstrated by the theoretical analysis and experimental results. Consequently, we increased the Li plating/stripping CE on the $\\mathtt{C u}$ substrate up to $99.55\\%$ at $1.0\\mathsf{m A}$ $\\mathsf{c m}^{-2}$ of $1.0\\mathsf{m A h c m^{-2}}$ , which is the highest value ever reported for carbonate electrolytes. The electrolyte can support a high-voltage NCM811 cathode, and $50~\\upmu\\mathrm{m}~\\mathsf{L}$ i||NMC811 cells achieved an outstanding CE of $99.83\\%$ over 200 cycles at a practical areal capacity of 2.5 mAh $\\mathsf{c m}^{-2}$ . The concentrated $\\mathsf{L i N O}_{3}$ additive strategy reported here could also provide new guidelines on the development of future advanced high-voltage LMBs in carbonate electrolytes. \n\n# Acknowledgements \n\nThis work was supported the Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) through Battery500 Consortium under contract No. DE-EE0008202. We acknowledge the University of Maryland supercomputing resources (http://hpcc.umd.edu) made available for conducting \n\nDFT computations in this paper. We also thank the Maryland NanoCenter and its AIMLab for support. \n\n# Conflict of interest \n\nThe authors declare no competing financial interest. \n\nKeywords: lithium metal batteries • carbonate electrolyte• lithium nitrate • electrode interphase • dendrite-free \n\n# REFERENCES \n\n[1] G. G. E. Heng Zhang, Xabier Judez, Chunmei Li, Lide M. Rodriguez-Mart&nez, and Michel Armand, Angew. Chem. Int. Ed. 2018, 57, 15002 – 15027. \n[2] J. B. Goodenough, K. S. Park, J. Am. Chem. Soc. 2013, 135, 1167-1176. \n[3] X.-B. Cheng, C. Yan, X.-Q. Zhang, H. Liu, Q. Zhang, ACS Energy Lett. 2018, 3, 1564-1570. \n[4] X.-Y. Yue, X.-L. Li, W.-W. Wang, D. Chen, Q.-Q. Qiu, Q.-C. Wang, X.-J. Wu, Z.-W. Fu, Z. Shadike, X.-Q. Yang, Y.-N. Zhou, Nano Energy 2019, 60, 257-266. \n[5] W. Xu, J. Wang, F. Ding, X. Chen, E. Nasybulin, Y. Zhang, J.-G. Zhang, Energy Environ. Sci. 2014, 7, 513- 537. \n[6] X. B. Cheng, R. Zhang, C. Z. Zhao, Q. Zhang, Chem. Rev. 2017, 117, 10403-10473. \n[7] K. N. Wood, M. Noked, N. P. Dasgupta, ACS Energy Lett. 2017, 2, 664-672. \n[8] M. D. Tikekar, S. Choudhury, Z. Tu, L. A. Archer, Nat. Energy 2016, 1, 16114. \n[9] H. Yu, J. Zhao, L. Ben, Y. Zhan, Y. Wu, X. Huang, ACS Energy Lett. 2017, 2, 1296-1302. \n[10] X.-Y. Yue, W.-W. Wang, Q.-C. Wang, J.-K. Meng, X.-X. Wang, Y. Song, Z.-W. Fu, X.-J. Wu, Y.-N. Zhou, Energy Storage Mater. 2019, 21, 180-189. \n[11] K. Xu, Chem. Rev. 2004, 104, 4303−4417. \n[12] K. Xu, Chem. Rev. 2014, 114, 11503-11618. \n[13] E. Peled, J. Electrochem. Soc. 1979, 126, 2047-2051. \n[14] J. Zheng, J. Yin, D. Zhang, G. Li, D. C. Bock, T. Tang, Q. Zhao, X. Liu, A. Warren, Y. Deng, S. Jin, A. C. Marschilok, E. S. Takeuchi, K. J. Takeuchi, C. D. Rahn, L. A. Archer, Sci. Adv. 2020, 6, eabb1122. X. Shen, R. Zhang, X. Chen, X. B. Cheng, X. Li, Q. Zhang, Adv. Energy Mater. 2020. E. Peled, S. Menkin, J. Electrochem. Soc. 2017, 164, A1703-A1719. A. Wang, S. Kadam, H. Li, S. Shi, Y. Qi, npj Computational Materials 2018, 4, 15. B. Zhu, Y. Jin, X. Hu, Q. Zheng, S. Zhang, Q. Wang, J. Zhu, Adv. Mater. 2016, 29, 1603755. A. A. Assegie, J. H. Cheng, L. M. Kuo, W. N. Su, B. J. Hwang, Nanoscale 2018, 10, 6125-6138. L. Suo, Y.-S. Hu, H. Li, M. Armand, L. Chen, Nat. Commun. 2013, 4, 1481. C. Fang, J. Li, M. Zhang, Y. Zhang, F. Yang, J. Z. Lee, M. H. Lee, J. Alvarado, M. A. Schroeder, Y. Yang, B. Lu, N. Williams, M. Ceja, L. Yang, M. Cai, J. Gu, K. Xu, X. Wang, Y. S. Meng, Nature 2019, 572, 511-515. \n[22] J. Chen, Q. Li, T. P. Pollard, X. Fan, O. Borodin, C. Wang, Materials Today 2020, 39, 118-126. \n[23] X. Fan, X. Ji, F. Han, J. Yue, J. Chen, L. Chen, T. Deng, J. Jiang, C. Wang, Sci. Adv. 2018, 4, eaau9245. S. Liu, X. Ji, J. Yue, S. Hou, P. Wang, C. Cui, J. Chen, B. Shao, J. Li, F. Han, J. Tu, C. Wang, J. Am. Chem. Soc. 2020, 142, 2438-2447. \nS. Schweidler, L. de Biasi, A. Schiele, P. Hartmann, T. Brezesinski, J. Janek, J. Phys. Chem. C 2018, 122, 8829-8835. \nX. Q. Zhang, X. B. Cheng, X. Chen, C. Yan, Q. Zhang, Adv. Funct. Mater. 2017, 27, 1605989. \nX. Q. Zhang, X. Chen, X. B. Cheng, B. Q. Li, X. Shen, C. Yan, J. Q. Huang, Q. Zhang, Angew. Chem. Int. Ed. 2018, 57, 5301-5305. \nH. Ota, Y. Sakata, Y. Otake, K. Shima, M. Ue, J.-i. Yamaki, J. Electrochem. Soc. 2004, 151, A1778-A1788. X. Ren, Y. Zhang, M. H. Engelhard, Q. Li, J.-G. Zhang, W. Xu, ACS Energy Lett. 2017, 3, 14-19. \nX. Li, M. Banis, A. Lushington, X. Yang, Q. Sun, Y. Zhao, C. Liu, Q. Li, B. Wang, W. Xiao, C. Wang, M. Li, J. Liang, R. Li, Y. Hu, L. Goncharova, H. Zhang, T. K. Sham, X. Sun, Nat. Commun. 2018, 9, 4509. \nY. Liu, D. Lin, Y. Li, G. Chen, A. Pei, O. Nix, Y. Li, Y. Cui, Nat. Commun. 2018, 9, 3656. \nH. Shin, J. Park, A. M. Sastry, W. Lu, J. Electrochem. Soc. 2015, 162, A1683-A1692. \nR. Elazari, G. Salitra, G. Gershinsky, A. Garsuch, A. Panchenko, D. Aurbach, Electrochem. Commun. 2012, 14, 21-24. \nD. Aurbach, E. Pollak, R. Elazari, G. Salitra, C. S. Kelley, J. Affinito, J. Electrochem. Soc. 2009, 156, A694. \nQ. Shi, Y. Zhong, M. Wu, H. Wang, H. Wang, Proc. Natl. Acad. Sci. U. S. A. 2018, 115, 5676-5680. \nC. Yan, Y. X. Yao, X. Chen, X. B. Cheng, X. Q. Zhang, J. Q. Huang, Q. Zhang, Angew. Chem. Int. Ed. 2018, 57, 14055-14059. \nY. Jie, X. Liu, Z. Lei, S. Wang, Y. Chen, F. Huang, R. Cao, G. Zhang, S. Jiao, Angew. Chem. Int. Ed. 2020, 59, 3505-3510. \nW. Zhang, Q. Wu, J. Huang, L. Fan, Z. Shen, Y. He, Q. Feng, G. Zhu, Y. Lu, Adv. Mater. 2020, e2001740. S. Li, W. Zhang, Q. Wu, L. Fan, X. Wang, X. Wang, Z. Shen, Y. He, Y. Lu, Angew. Chem. Int. Ed. 2020, 59, 14935-14941. \nX. Fan, L. Chen, X. Ji, T. Deng, S. Hou, J. Chen, J. Zheng, F. Wang, J. Jiang, K. Xu, C. Wang, Chem 2018, 4, 174-185. \nX. Fan, X. Ji, L. Chen, J. Chen, T. Deng, F. Han, J. Yue, N. Piao, R. Wang, X. Zhou, X. Xiao, L. Chen, C. Wang, Nat. Energy 2019, 4, 882-890. \nX. Cao, X. Ren, L. Zou, M. H. Engelhard, W. Huang, H. Wang, B. E. Matthews, H. Lee, C. Niu, B. W. Arey, Y. Cui, C. Wang, J. Xiao, J. Liu, W. Xu, J.-G. Zhang, Nat. Energy 2019, 4, 796-805. \nS. Sekhon, Solid State Ionics 2003, 160, 301-307. \nN. Nambu, R. Takahashi, M. Takehara, M. Ue, Y. Sasaki, Electrochemistry 2013, 81, 817-819. \nC. M. Burke, V. Pande, A. Khetan, V. Viswanathan, B. D. McCloskey, Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 9293-9298. \nM. I. Gorobets, M. B. Ataev, M. M. Gafurov, S. A. Kirillov, Journal of Spectroscopy 2016, 2016, 6978560. \nH. Pan, J. Chen, R. Cao, V. Murugesan, N. N. Rajput, K. S. Han, K. Persson, L. Estevez, M. H. Engelhard, J.- G. Zhang, $\\kappa.$ T. Mueller, Y. Cui, Y. Shao, J. Liu, Nat. Energy 2017, 2, 813-820. \nL. Suo, O. Borodin, T. Gao, M. Olguin, J. Ho, X. Fan, C. Luo, C. Wang, K. Xu, Science 2015, 350, 938-943. C. Yang, J. Chen, X. Ji, T. P. Pollard, X. Lu, C. J. Sun, S. Hou, Q. Liu, C. Liu, T. Qing, Y. Wang, O. Borodin, Y. Ren, K. Xu, C. Wang, Nature 2019, 569, 245-250. J. Qian, W. A. Henderson, W. Xu, P. Bhattacharya, M. Engelhard, O. Borodin, J. G. Zhang, Nat. Commun. 2015, 6, 6362. \nN. Piao, X. Ji, H. Xu, X. Fan, L. Chen, S. Liu, M. N. Garaga, S. G. Greenbaum, L. Wang, C. Wang, X. He, Adv. Energy Mater. 2020, 10, 1903568. \nE. Markevich, G. Salitra, F. Chesneau, M. Schmidt, D. Aurbach, ACS Energy Lett. 2017, 2, 1321-1326. \nE. Markevich, G. Salitra, K. Fridman, R. Sharabi, G. Gershinsky, A. Garsuch, G. Semrau, M. A. Schmidt, D. Aurbach, Langmuir 2014, 30, 7414-7424. \nN. Togasaki, T. Momma, T. Osaka, J. Power Sources 2016, 307, 98-104. \nS. S. Zhang, J. A. Read, J. Power Sources 2012, 200, 77-82. \nD. Aurbach, H. Gottlieb, Electrochim. Acta 1989, 34, 141-156. \nN. Bellakhal, K. Draou, J. L. Brisset, J. Appl. Electrochem. 1997, 27, 414-421. \nX. Fan, L. Chen, O. Borodin, X. Ji, J. Chen, S. Hou, T. Deng, J. Zheng, C. Yang, S. C. Liou, K. Amine, K. Xu, C. Wang, Nat. Nanotechnol. 2018, 13, 715-722. \nZ. Yang, A. A. Gewirth, L. Trahey, ACS Appl. Mater. Interfaces 2015, 7, 6557-6566. \nB. D. Adams, J. Zheng, X. Ren, W. Xu, J.-G. Zhang, Adv. Energy Mater. 2017, 8, 1702097. \nC. Xu, G. Hernández, S. Abbrent, L. Kobera, R. Konefal, J. Brus, K. Edström, D. Brandell, J. Mindemark, ACS Appl. Energy Mater. 2019, 2, 4925-4935. \nA. Jozwiuk, B. B. Berkes, T. Weiß, H. Sommer, J. Janek, T. Brezesinski, Energy Environ. Sci. 2016, 9, 2603- 2608. \nS. Chen, C. Niu, H. Lee, Q. Li, L. Yu, W. Xu, J.-G. Zhang, E. J. Dufek, M. S. Whittingham, S. Meng, J. Xiao, J. Liu, Joule 2019, 3, 1094-1105. \nS. Lin, J. Zhao, ACS Appl. Mater. Interfaces 2020, 12, 8316-8323. \nJ. Zhao, L. Liao, F. Shi, T. Lei, G. Chen, A. Pei, J. Sun, K. Yan, G. Zhou, J. Xie, C. Liu, Y. Li, Z. Liang, Z. Bao, Y. Cui, J. Am. Chem. Soc. 2017, 139, 11550-11558. A. L. Michan, B. S. Parimalam, M. Leskes, R. N. Kerber, T. Yoon, C. P. Grey, B. L. Lucht, Chem. Mater. 2016, 28, 8149-8159. \nU. v. Alpen, J. Solid State Chem. 1979, 29, 379-392. F. A. Soto, Y. Ma, J. M. Martinez de la Hoz, J. M. Seminario, P. B. Balbuena, Chem. Mater. 2015, 27, 7990-8000. \nS. Shi, Y. Qi, H. Li, L. G. Hector, J. Phys. Chem. C 2013, 117, 8579-8593. \nJ. M. Garcia-Lastra, J. S. G. Myrdal, R. Christensen, K. S. Thygesen, T. Vegge, J. Phys. Chem. C 2013, 117, 5568-5577. \n\n# Entry for the Table of Contents \n\n![](images/2551757933f3fc4cc559988c7ebcd4996e601fab055cc579b314243c645d084d.jpg) \n\nBased on density functional theory (DFT) calculation and experimental results, the inorganic-rich SEI has been constructed on Li metal to promote dense Li growth with a recorded Coulombic efficiency (CE) of $99.55\\%$ in the carbonate electrolyte. Such an outstanding SEI is in-situ synthesized on the surface of Li metal anode through using concentrated $\\mathsf{L i N O}_{3}$ in dimethyl sulfoxide (DMSO) as electrolyte additive in the FEC-based electrolyte, which has participated in the primary ${\\mathsf{L i}}^{+}$ solvation sheath with the aggregates structure and thus promote the preferential reduction of $N O_{3}^{-}$ ions to form the inorganic-rich SEI. \n\n![](images/4488e4b65b526c583cb1bab4451587e3bbcef58f3a51badb356c873555fd23f9.jpg) " + }, + { + "id": "10.1038_s41467-020-20397-5", + "DOI": "10.1038/s41467-020-20397-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-20397-5", + "Relative Dir Path": "mds/10.1038_s41467-020-20397-5", + "Article Title": "Enhancing carbon dioxide gas-diffusion electrolysis by creating a hydrophobic catalyst microenvironment", + "Authors": "Xing, Z; Hu, L; Ripatti, DS; Hu, X; Feng, XF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electroreduction of carbon dioxide (CO2) over copper-based catalysts provides an attractive approach for sustainable fuel production. While efforts are focused on developing catalytic materials, it is also critical to understand and control the microenvironment around catalytic sites, which can mediate the transport of reaction species and influence reaction pathways. Here, we show that a hydrophobic microenvironment can significantly enhance CO2 gas-diffusion electrolysis. For proof-of-concept, we use commercial copper nulloparticles and disperse hydrophobic polytetrafluoroethylene (PTFE) nulloparticles inside the catalyst layer. Consequently, the PTFE-added electrode achieves a greatly improved activity and Faradaic efficiency for CO2 reduction, with a partial current density >250 mA cm(-2) and a single-pass conversion of 14% at moderate potentials, which are around twice that of a regular electrode without added PTFE. The improvement is attributed to a balanced gas/liquid microenvironment that reduces the diffusion layer thickness, accelerates CO2 mass transport, and increases CO2 local concentration for the electrolysis.", + "Times Cited, WoS Core": 420, + "Times Cited, All Databases": 435, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000626604800005", + "Markdown": "# Enhancing carbon dioxide gas-diffusion electrolysis by creating a hydrophobic catalyst microenvironment \n\nZhuo Xing 1,2, Lin ${\\mathsf{H}}{\\mathsf{u}}^{3}.$ , Donald S. Ripatti4, Xun Hu 1✉ & Xiaofeng Feng 2,3,5✉ \n\nElectroreduction of carbon dioxide $(\\mathsf{C O}_{2})$ ) over copper-based catalysts provides an attractive approach for sustainable fuel production. While efforts are focused on developing catalytic materials, it is also critical to understand and control the microenvironment around catalytic sites, which can mediate the transport of reaction species and influence reaction pathways. Here, we show that a hydrophobic microenvironment can significantly enhance ${\\mathsf{C O}}_{2}$ gasdiffusion electrolysis. For proof-of-concept, we use commercial copper nanoparticles and disperse hydrophobic polytetrafluoroethylene (PTFE) nanoparticles inside the catalyst layer. Consequently, the PTFE-added electrode achieves a greatly improved activity and Faradaic efficiency for ${\\mathsf{C O}}_{2}$ reduction, with a partial current density $>250\\ m A\\ c m^{-2}$ and a single-pass conversion of $14\\%$ at moderate potentials, which are around twice that of a regular electrode without added PTFE. The improvement is attributed to a balanced gas/liquid microenvironment that reduces the diffusion layer thickness, accelerates ${\\mathsf{C O}}_{2}$ mass transport, and increases ${\\mathsf{C O}}_{2}$ local concentration for the electrolysis. \n\nBedceamuasendo ftohrerleinmeiwteadb re seenrevregsyotfefcohsnsiol fougeiles, thaetreciasnareridsiuncge pogenic climate change1. A promising approach is to power the synthesis of fuels and chemicals from naturally abundant resources using renewable electricity2. Such electrosynthesis processes are compatible with the intermittent supply of electricity from renewable resources, such as solar or wind, and can enable sustainable production of fuels and chemicals3. Accordingly, numerous efforts have been made to develop efficient electrocatalysts for the conversion of $\\mathrm{CO}_{2}.$ , CO, $\\Nu_{2}$ , and $_\\mathrm{H}_{2}\\mathrm{O}$ to valuable chemicals, such as hydrocarbons, oxygenates, and ammonia4–12. In particular, the electrochemical reduction of $\\mathrm{CO}_{2}$ over Cu-based catalysts has received considerable interest, because Cu exhibits appreciable activity for $C{\\mathrm{-}}C$ coupling to form multicarbon products, including ethylene, ethanol, and propanol13,14. While efforts are focused on developing catalytic materials, it is also critical to understand other factors beyond catalytic materials, such as the local environment of the catalysts15, which can mediate the transport and local concentration of reaction species and influence reaction pathways16. \n\nElectrochemical $\\mathrm{CO}_{2}$ reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ has been typically evaluated using $\\mathrm{~H~}$ -type cells (H-cells)6–8, where the electrode is immersed in liquid electrolyte, and $\\mathrm{CO}_{2}$ molecules dissolve in the electrolyte and diffuse down a concentration gradient to the catalyst surface for reactions9, as schematically shown in Fig. 1a. While this cell configuration works well for evaluating $\\mathrm{CO}_{2}\\mathrm{RR}$ at low current densities $_{\\cdot^{6-10}}$ , the low solubility and slow diffusion of $\\mathrm{CO}_{2}$ in the electrolyte will cause a mass transport limitation at high current densities. The limiting current density for $\\mathrm{CO}_{2}\\mathrm{RR}$ on a planar electrode can be estimated by: $j_{\\mathrm{lim}}=n F D_{0}C_{0}/\\delta_{\\mathrm{r}}$ , where $n$ is the number of electrons transferred in the reaction, $F$ is the Faraday constant, $D_{0}$ and $C_{0}$ are the diffusion coefficient and solubility of $\\mathrm{CO}_{2}$ in the electrolyte, and $\\delta$ is the diffusion layer thickness. The diffusion layer is a virtual layer of the $\\mathrm{CO}_{2}$ concentration gradient interval17, which extends from the electrode surface to the point where the concentration of $\\mathrm{CO}_{2}$ reaches the bulk concentration, as illustrated in Supplementary Fig. 1. Typically, the diffusion layer thickness is of the order of magnitude of $100\\upmu\\mathrm{m}$ for $\\mathrm{CO}_{2}\\mathrm{RR}$ in $\\mathrm{\\Delta~H-cell^{18}~}$ , resulting in a limiting current density of the order of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , as indicated by the estimation in Supplementary Fig. 1. \n\nTo alleviate the limitations of mass transport, flow cells with gas-diffusion electrodes (GDEs) have been developed and used to investigate electrochemical $\\mathrm{CO}_{2}$ or CO reduction19–28. A GDE typically consists of a carbon fiber paper (CFP), a microporous layer (MPL), and a catalyst layer20. The catalyst side of a GDE is in contact with the electrolyte and the other side is exposed to flowing reactant gas, which diffuses through the pores in the CFP to reach the catalyst, as schematically illustrated in Fig. 1b. The MPL is composed of carbon powder and polytetrafluoroethylene (PTFE) particles, which can maintain the separation of the liquid and gas phases to prevent flooding of the pores in the $\\mathrm{CFP}^{20}$ . The catalyst particles in a GDE are often wetted by electrolyte due to their lack of hydrophobicity, as a result the reaction occurs primarily in aqueous phase via dissolved $\\mathrm{CO}_{2}$ (refs. 29–31). In this cell configuration, reactant molecules diffuse through a relatively thin layer of electrolyte to reach the catalyst29,30, which greatly reduces the diffusion layer thickness and enables high-rate $\\mathrm{CO}_{2}$ electrolysis at current densities ${>}200\\ \\mathrm{mAcm}^{-2}$ , as indicated by the plot in Supplementary Fig. 1. Nevertheless, the catalyst layer typically has a thickness of at least a few micrometers18, so the ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ may still be limited by $\\mathrm{CO}_{2}$ mass transport inside the three-dimensional catalyst layer32. \n\nFurthermore, the greatly improved $\\mathrm{CO}_{2}\\mathrm{RR}$ performance in GDE cells was also attributed to local gaseous environment and three-phase interfaces between solid catalyst, liquid electrolyte, and gaseous $\\mathrm{CO}_{2}$ in some studies21,22. However, such argument remains under debate, that is, whether the $\\mathrm{CO}_{2}\\mathrm{RR}$ in a GDE cell can occur at a solid–liquid–gas interface via gaseous $\\mathrm{CO}_{2}$ , in contrast to the conventional electrode–electrolyte interface29. Recently, a few studies explored the three-phase interfaces for $\\mathrm{CO}_{2}$ or CO reduction in H-cells33–38, typically using a hydrophobic substrate for the electrode. Although the electrode was immersed in liquid electrolyte in an H-cell, the hydrophobic substrate might trap gaseous reactant near the catalyst layer to change the local environment and form solid–liquid–gas interfaces, which could improve the activity and selectivity for $\\mathrm{CO}_{2}$ or \n\n![](images/369eb4b1e169ed9c6ffb66d6848136303714aab9a140d9faf00b2c7fcea4f616.jpg) \nFig. 1 Schematic illustration of different catalyst microenvironments and reaction interfaces. a Solid–liquid interface in an H-cell. b Solid–liquid interface in a regular GDE cell. c Proposed hydrophobic microenvironment with solid–liquid–gas interfaces that can be constructed in a GDE cell by dispersing PTFE nanoparticles inside the catalyst layer. \n\nCO reduction34–36. These studies revealed the significant impact of the local gas/liquid environment of the catalysts in gasinvolving electrochemical reactions38. However, much remains to be understood regarding the catalyst microenvironment and reaction interfaces, such as how to create an optimal microenvironment with solid–liquid–gas interfaces, and how such an environment affects the mass transport and kinetics of electrocatalytic reactions. \n\nHere, we present a study of a hydrophobic microenvironment with solid–liquid–gas interfaces for gas-involving electrocatalysis, particularly $\\mathrm{CO}_{2}$ reduction on Cu catalyst. As a proof-of-concept, we select commercially available Cu nanoparticles as the catalyst, so that the conclusions do not rely on any specially designed catalyst and can be generally applicable. We first show that using a hydrophobic substrate for the electrode improves the activity and selectivity for $\\mathrm{CO}_{2}\\mathrm{RR}$ in H-cell, validating the impact of the local environment. Then we design a GDE with a hydrophobic catalyst microenvironment for $\\mathrm{CO}_{2}$ gas-diffusion electrolysis by dispersing PTFE nanoparticles in the catalyst layer, where the hydrophobic PTFE can repel liquid electrolyte and maintain gaseous reactant near the catalyst particles, as schematically shown in Fig. 1c. As a result, this electrode shows a significant improvement in the activity and Faradaic efficiency for $\\mathrm{\\bar{CO}}_{2}\\mathrm{RR}$ as compared to regular GDEs without added PTFE. The improved catalytic performance is attributed to a balanced gas/liquid microenvironment that reduces the diffusion layer thickness, and enhances the mass transport and kinetics of $\\mathrm{CO}_{2}$ electrolysis, providing a general approach to improve gas-involving electrocatalysis. \n\n# Results \n\nCharacterization of Cu nanocatalyst. Commercial Cu nanoparticles (see Supplementary Note 1) were used as the electrocatalyst for $\\mathrm{CO}_{2}\\mathrm{RR}$ in this study. The Cu catalyst is less active than those specially designed $\\mathrm{Cu}$ catalysts19–22, but it is widely available and often used as a reference sample in $\\mathrm{CO}_{2}\\mathrm{RR}$ studies19,21. The nanoparticles were characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) to examine their size and composition, as presented in Supplementary Fig. 2. The TEM images and derived particle size distribution revealed an average size of $47.9\\pm$ $16.8\\mathrm{nm}$ of the Cu nanoparticles. XRD pattern showed diffraction peaks of Cu and a small fraction of $\\mathrm{Cu}_{2}\\mathrm{O}_{\\mathrm{i}}$ of which the latter was due to oxidation by air. XPS survey spectrum showed mainly $\\mathrm{cu}$ and O peaks, where the O was attributed to the $\\mathrm{Cu}_{2}\\mathrm{O}$ component. To further identify the chemical state of the Cu catalyst during ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ operando X-ray absorption spectroscopy (XAS) characterization was performed, as shown in Supplementary Fig. 3, and the acquired Cu K-edge XAS spectra indicated that the catalyst was reduced to metallic Cu state under $\\mathrm{CO}_{2}\\mathrm{RR}$ conditions39. \n\nMicroenvironment for $\\mathbf{CO}_{2}\\mathbf{RR}$ in H-cell. We first examined the microenvironment for $\\mathrm{CO}_{2}\\mathrm{RR}$ on the Cu catalyst in H-cell, where a simple model of solid–liquid interface can be used to describe the reaction interface (Fig. 1a). To probe the effect of substrate hydrophobicity on the electrode performance, two substrates purchased from the Fuel Cell Store were used for comparison: AvCarb MGL370 CFP, and AvCarb GDS2230 consisting of CFP and a hydrophobic MPL coating. Contact angle measurements on them (Supplementary Fig. 4) revealed superior hydrophobicity of the AvCarb GDS2230 $(151.7^{\\circ})$ relative to the MGL370 $(119.0^{\\circ})$ . Electrodes were prepared by depositing the catalyst ink (a mixture of Cu nanoparticles and carbon black) on the two substrates, and their configurations are schematically shown in Fig. 2a. Scanning electron microscopy (SEM) images suggested that the morphology of the catalyst layers on the two substrates was very similar (Supplementary Fig. 5). $\\mathrm{CO}_{2}\\mathrm{RR}$ tests were performed in an H-cell with $\\mathrm{CO}_{2}$ gas bubbling into the cathodic compartment (Supplementary Fig. 6). The $\\mathrm{CO}_{2}\\mathrm{RR}$ performance was evaluated by controlled potential electrolysis in $1\\mathrm{M}\\mathrm{\\KHCO}_{3}$ electrolyte. All potentials were reported with respect to the reversible hydrogen electrode (RHE) in this study. Gas-phase products were quantified by periodic gas chromatography, and solution-phase products were analyzed at the end of each electrolysis by nuclear magnetic resonance (NMR) spectroscopy (Supplementary Fig. 7). \n\n$\\bar{\\mathrm{CO}}_{2}\\mathrm{RR}$ was first evaluated at various potentials ranging from $-0.5$ to $-1.0\\mathrm{V}$ vs RHE for both electrodes, and representative chronoamperometric curves are shown in Supplementary Fig. 8. As expected, the partial current density for $\\mathrm{\\bar{CO}}_{2}\\mathrm{RR}$ increased exponentially with the overpotential for both electrodes (Fig. 2b). Interestingly, the $\\mathrm{CO}_{2}\\mathrm{RR}$ current densities on the GDS2230 electrode were generally higher than that on the MGL370 electrode, particularly at higher overpotentials. For example, a $\\mathrm{CO}_{2}\\mathrm{RR}$ current density of ${\\sim}23\\mathrm{mAcm}^{-2}$ was reached at $-1.0\\mathrm{V}$ on the GDS2230 electrode, which is about four times that on the MGL370 electrode $(\\sim6\\mathrm{mA}\\mathrm{cm}^{-2},$ . As there was no major difference between the two electrodes regarding the morphology (Supplementary Fig. 5) or the conductivity (as revealed by the electrochemical impedance spectra (EIS) in Supplementary Fig. 9), their difference in $\\mathrm{CO}_{2}\\mathrm{RR}$ performance is attributed to the substrate hydrophobicity, most likely because the hydrophobic MPL can repel liquid electrolyte and trap gas bubbles40,41. \n\nTo verify the liquid repelling effect of the MPL, we measured the contact angles of the AvCarb MGL370 and GDS2230 substrates (no catalyst loading) after electrochemical treatment at $-1.0\\mathrm{V}$ in the electrolyte. As shown in Supplementary Fig. 4, the contact angle of the MGL370 substrate dropped significantly from $119.0^{\\circ}$ to $22.5^{\\circ}$ due to electrochemical modifications. In contrast, the GDS2230 substrate remained similarly hydrophobic with a contact angle of ${\\sim}150^{\\circ}$ after the treatment, so the MPL cannot be wetted or flooded by the electrolyte and gas bubbles can be maintained in the pores of the MPL. When the GDS2230 electrode is tested for $\\mathsf{\\bar{C}O}_{2}\\mathrm{RR},$ the gas bubbles trapped inside the MPL can serve as an intermediate reservoir of gaseous $\\mathrm{CO}_{2}$ for the reaction. Thus, the diffusion layer thickness decreases to the distance between the gas bubbles in the MPL and the catalyst particles42, which improves $\\mathrm{CO}_{2}$ mass transport to the catalyst layer and increases the $\\bar{\\mathrm{CO}}_{2}\\mathrm{RR}$ limiting current density. This is also supported by the potentialdependent difference in the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance between the two electrodes: the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density was similar at $-0.5\\mathrm{V}$ , but the difference was enlarged to 4-fold at $-1.0\\mathrm{V}$ where the $\\mathrm{CO}_{2}\\mathrm{RR}$ became limited by mass transport (Fig. 2b), confirming that $\\mathrm{CO}_{2}$ mass transport in the GDS2230 electrode is improved by the MPL. This mechanism can also explain the enhanced performance for CO reduction on hydrophobic electrodes35,36. \n\nHow is gaseous $\\mathrm{CO}_{2}$ formed in the MPL? It can be formed directly by trapping the purged $\\mathrm{CO}_{2}$ gas bubbles34, or indirectly from the dissolved $\\mathrm{CO}_{2}$ molecules in the electrolyte43. If it is the former case, the gas bubbling rate will affect the trapping of gaseous $\\mathrm{CO}_{2}$ and the $\\mathrm{CO}_{2}\\mathrm{RR}$ rate34; otherwise the $\\mathrm{CO}_{2}\\mathrm{RR}$ rate should not depend on the gas bubbling rate in the latter case, as long as the electrolyte remains saturated with $\\mathrm{CO}_{2}$ . In the H-cell, the electrode is positioned ${\\sim}1\\mathrm{cm}$ away from the gas inlet (Supplementary Fig. 6), so it is less likely to directly trap gas bubbles. We varied the $\\mathrm{CO}_{2}$ gas bubbling rate to examine the gas trapping by the MPL. Figure 2c shows the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density measured on the two electrodes at $-1.0\\mathrm{V}$ with various $\\mathrm{CO}_{2}$ gas bubbling rates, ranging from 2 to 6 standard cubic centimeters per minute (sccm). Both current densities remained largely unchanged with the bubbling rate, indicating that the $\\mathrm{CO}_{2}\\mathrm{RR}$ mainly relied on the dissolved $\\mathrm{CO}_{2}$ molecules for both electrodes. We postulate that the hydrophobic MPL can facilitate the nucleation and formation of $\\mathrm{CO}_{2}$ gas bubbles from the $\\mathrm{CO}_{2}$ - saturated electrolyte44. Similarly, the Faradaic efficiency for $\\mathrm{CO}_{2}\\mathrm{RR}$ also showed a weak dependence on the gas flow rate (Fig. 2d). The total Faradaic efficiency for $\\mathrm{CO}_{2}^{-}\\mathrm{RR}$ on the GDS2230 and MGL370 electrodes was ${\\sim}30\\%$ and $13\\%$ , respectively. We attribute the difference to a higher local concentration of $\\dot{\\mathrm{CO}_{2}}$ due to the improved mass transport by the $\\mathrm{MPL}^{34}$ . The difference in the $\\mathrm{CO}_{2}\\mathrm{RR}$ selectivity confirmed the impact of the electrode hydrophobicity and corresponding local environment on the $\\mathrm{CO}_{2}\\mathrm{RR}$ . \n\n![](images/7299356a96add183bb32c6689a6dbc1f5bcd19f45901c895c287beab547a8019.jpg) \nFig. 2 Effect of hydrophobic substrate on the $C O_{2}R R$ in H-cell. a Configurations of the two electrodes prepared with AvCarb MGL370 and GDS2230 substrates. b Partial current densities for ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ on the two electrodes at various potentials with a ${\\mathsf{C O}}_{2}$ gas flow rate of 4 sccm. c Partial current densities and d Faradaic efficiencies for ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ on the two electrodes at $-1.0\\vee$ with various ${\\mathsf{C O}}_{2}$ flow rates. In d, the left column with dashed line frame at each flow rate is for the AvCarb $\\mathsf{M G L370+C u/C}$ electrode, and the right column with solid line frame is for the AvCarb $\\mathsf{G D S}2230+\\mathsf{C u}/\\mathsf{C}$ electrode. The error bars represent the standard deviation of three independent measurements. \n\nHydrophobic microenvironment for $\\mathbf{CO}_{2}\\mathbf{RR}$ in GDE cell. It was shown above that a hydrophobic substrate can change the local gas/liquid environment and improve the mass transport for $\\mathrm{CO}_{2}\\mathrm{RR}$ in an H-cell. In a GDE cell, the catalyst layer typically has a thickness of at least a few micrometers18,32, so the MPL is unlikely to influence the microenvironment deep inside the catalyst layer. Therefore, we designed an electrode with local hydrophobic centers by dispersing PTFE particles inside the catalyst layer, where the PTFE can repel liquid electrolyte and maintain gas bubbles in neighboring pores, as schematically shown in Fig. 1c. In particular, PTFE nanoparticles of $30{-}40~\\mathrm{nm}$ in size (Nanoshel LLC) were used, which have a similar size as the \n\nCu nanoparticles and can enable a uniform mixing, as verified by the energy-dispersive X-ray spectroscopy (EDS) elemental mapping in Supplementary Fig. 10. Thus, the PTFE nanoparticles can trap numerous gas bubbles in the catalyst layer and enforce a high surface area gas–liquid interface near the catalyst particles during ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ \n\nTo understand the effect of the hydrophobic microenvironment, two electrodes were prepared for comparison: one using the original catalyst ink (Cu nanoparticles and carbon black), and the other using PTFE-dispersed catalyst ink with a $50\\%$ mass ratio of PTFE, both deposited on the AvCarb GDS2230 substrate. The two electrodes have the same loading of Cu nanoparticles, and they are referred as $\\mathrm{Cu/C}$ and $\\mathrm{Cu/C/PTFE}$ electrodes, respectively. SEM images indicated that the morphology of the catalyst layers of the two electrodes was very similar (Supplementary Fig. 11). $\\mathrm{CO}_{2}$ gas-diffusion electrolysis was tested using a home-built GDE flow cell (Supplementary Fig. 12) with circulating 1 M KOH electrolyte (Supplementary Fig. 13). The electrodes were first evaluated at various potentials, ranging from $-0.5$ to $-1.0\\mathrm{~V~}$ . As shown in Fig. 3a, the partial current density for $\\mathrm{CO}_{2}\\mathrm{RR}$ on the $\\mathrm{Cu/C}$ electrode increased from $39\\mathrm{mA}\\mathrm{cm}^{-2}$ at $-0.5\\mathrm{V}$ to $138\\mathrm{mAcm}^{-2}$ at $-1.0\\mathrm{V}$ , much higher than that measured for the same electrode in the H-cell (Fig. 2b). The $\\mathrm{Cu/}$ C/PTFE electrode showed an even higher $\\mathrm{CO}_{2}\\mathrm{RR}$ current density than the $\\mathrm{Cu/C}$ electrode at each potential. Particularly, a partial current density of $\\sim250\\mathrm{mAcm}^{-2}$ was reached for $\\mathrm{CO}_{2}\\mathrm{RR}$ on the $\\mathrm{Cu/C/PTFE}$ electrode at $-1.0\\mathrm{V}$ , which was almost twice that of the $\\mathrm{Cu/C}$ electrode. We postulate that the dispersed PTFE nanoparticles in the catalyst layer form hydrophobic gas channels, which reduce the electrolyte layer thickness that $\\mathrm{CO}_{2}$ must diffuse from the point of dissolution to the catalyst surface. This greatly decreases the diffusion layer thickness for the catalyst particles inside the catalyst layer, thus improving the $\\mathrm{CO}_{2}$ mass transport and $\\mathrm{CO}_{2}\\mathrm{RR}$ performance. \n\n![](images/a643cd8aa6da894d466a95b75948f5153ec5694186a8d6ef5e9184a29c4413e9.jpg) \nFig. 3 Effect of hydrophobic microenvironment on the $C O_{2}R R$ in GDE cell. a Partial current densities for $C O_{2}R R$ on the $\\mathsf{C u/C}$ and $\\mathsf{C u/C/P T F E}$ electrodes at various potentials with a ${\\mathsf{C O}}_{2}$ gas flow rate of 4 sccm. b Partial current densities and c Faradaic efficiencies for $C O_{2}R R$ on the two electrodes at $-1.0\\vee$ with various ${\\mathsf{C O}}_{2}$ flow rates. In c, the left column with dashed line frame at each flow rate is for the $\\mathsf{C u/C}$ electrode and the right column with solid line frame is for the $\\mathsf{C u/C/P T F E}$ electrode. d Double-layer charging current plotted against the CV scan rate for the two electrodes. e, f Photographs of contact angle measurements on the e $\\mathsf{C u/C}$ electrode and f Cu/C/PTFE electrode before and after ${\\mathsf{C O}}_{2}$ electrolysis at $-1.0\\vee$ for $2\\mathsf{h}$ . The error bars represent the standard deviation of three independent measurements. \n\nTo distinguish if the $\\mathrm{CO}_{2}$ transport inside the catalyst layer was mainly mediated by gas-phase or aqueous-phase diffusion, we compared the $\\mathrm{CO}_{2}\\mathrm{RR}$ activity on the two electrodes with various $\\mathrm{CO}_{2}$ gas flow rates. As presented in Fig. 3b, the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density on the $\\mathrm{Cu/C}$ electrode at $-1.0\\mathrm{V}$ showed a weak dependence on the flow rate, which increased from 104 to $13{\\mathrm{\\dot{8}}}\\mathrm{mA}\\mathrm{cm}^{-2}$ as the flow rate increased from 2 to $4\\operatorname{sccm}$ , but declined to $122\\mathrm{mA}\\mathrm{cm}^{-2}$ at a flow rate of 6 sccm. In contrast, the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density on the Cu/C/PTFE electrode showed a distinct trend, which increased almost linearly from 140 to $250\\mathrm{mA}\\mathrm{cm}^{-2}$ as the flow rate increased from 2 to 4 sccm and then continued to increase mildly at higher flow rates. As a result, a maximum single-pass conversion rate of $14\\%$ was reached for $\\mathrm{CO}_{2}\\mathrm{RR}$ on the Cu/C/PTFE electrode at $4\\mathrm{sccm}$ , which is about twice that of the $\\mathrm{Cu/C}$ electrode $(7.3\\%)$ at the same flow rate (Supplementary Fig. 14). As previously discussed, if the $\\mathrm{CO}_{2}\\mathrm{RR}$ is only mediated by aqueous-phase transport of dissolved $\\mathrm{CO}_{2}$ molecules to the catalyst, the reaction rate should not be affected by the $\\mathrm{CO}_{2}$ gas flow rate (Fig. 2c). Here, the strong dependence of the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density on the flow rate for the $\\mathrm{\\bar{C}u/C/}$ PTFE electrode indicated a gas-phase transport of $\\mathrm{CO}_{2}$ in the catalyst layer via hydrophobic channels. In addition, the $\\mathrm{CO}_{2}\\mathrm{RR}$ selectivity was different between the two electrodes, as presented in Fig. 3c. The total Faradaic efficiency for $\\mathrm{CO}_{2}\\mathrm{RR}$ on the $\\mathrm{Cu/C}$ electrode ranged between 35 and $50\\%$ at various flow rates, while the total Faradaic efficiency on the $\\mathrm{Cu/C/PTFE}$ electrode was higher, ranging between 68 and $76\\%$ . The Faradic efficiency for $\\mathrm{C}_{2+}$ products was also higher on the $\\mathrm{Cu/C/}$ PTFE electrode, suggesting that the electrode increased the local concentration of the intermediate product CO and consequently enhanced the $C{\\mathrm{-}}C$ coupling process16,45. \n\nIt is noted that the added PTFE will increase the catalyst layer thickness of the $\\mathrm{Cu/C/PTFE}$ electrode, which can influence the diffusion of $\\mathrm{CO}_{2}$ and $\\mathrm{CO}_{2}\\mathrm{RR}$ activity. As revealed by the SEM images in Supplementary Fig. 15, the catalyst layer thickness was estimated to be $23.5\\pm2.1$ and $39.3\\pm2.6\\upmu\\mathrm{m}$ for the $\\mathrm{Cu/C}$ and $\\mathrm{Cu}/$ C/PTFE electrodes, respectively. To evaluate the influence of the catalyst layer thickness, an additional $\\mathrm{Cu/C}$ electrode with extra carbon black loading was prepared (referred as $\\mathrm{Cu/C}$ -extra electrode), of which the catalyst layer thickness $(40.6\\pm1.8\\upmu\\mathrm{m})$ is close to that of the $\\mathrm{Cu/C/}$ PTFE electrode. A comparison of their $\\mathrm{CO}_{2}\\mathrm{RR}$ performance was shown in Supplementary Fig. 15d: the partial current density and total Faradaic efficiency for $\\mathrm{\\bar{CO}}_{2}\\mathrm{RR}$ on the $\\mathrm{Cu/C}$ -extra electrode was similar to that of the $\\mathrm{Cu/C}$ electrode, but the Faradaic efficiency for $\\mathrm{C}_{2+}$ products was lower on the $\\mathrm{Cu/C}$ -extra electrode, which was attributed to the relatively lower concentration of $\\mathrm{CO}_{2}$ inside the catalyst layer16. This is reasonable as $\\mathrm{CO}_{2}$ needs to diffuse over a longer distance on average to reach the catalyst particles in a thicker catalyst layer. Interestingly, the $\\mathrm{Cu/C/}$ PTFE electrode had a similarly thicker catalyst layer, but its ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ current density and $\\mathrm{C}_{2+}$ Faradaic efficiency were both much higher than that of the $\\mathrm{Cu/C}$ and $\\mathrm{Cu}/$ C-extra electrodes, confirming the improvement of $\\mathrm{CO}_{2}$ mass transport and $\\mathrm{CO}_{2}\\mathrm{RR}$ performance by the hydrophobic microenvironment, despite a thicker catalyst layer. \n\nTo further verify the presence of gaseous reactant inside the catalyst layer, we compared the electrochemically active surface area (ECSA) of the two electrodes. ECSA represents the area of an electrode that is wetted and accessible to the electrolyte. We postulate that the increased volume of gas within the catalyst layer will reduce its ECSA due to less contact with the electrolyte. The ECSA is proportional to the electrochemical double-layer capacitance, which can be measured by cyclic voltammetry (CV) in a potential window where only double-layer charging and discharging occur46, as illustrated in Supplementary Fig. 16. The double-layer charging current was plotted against the scan rate, and the slope of the linear regression gives the double-layer capacitance. As shown in Fig. 3d, the capacitance of the $\\mathrm{Cu}\\dot{/}\\mathrm{C}I$ PTFE electrode $(\\sim12.4\\:\\mathrm{mF})$ was around half that of the $\\mathrm{Cu/C}$ electrode $\\mathrm{\\left({\\sim}26.1~m F\\right)}$ , despite the same loading of Cu and carbon black. This confirmed the presence of gas bubbles in the catalyst layer and the formation of solid–liquid–gas interfaces. \n\nA balance between gas and liquid in a GDE may be broken during electrolysis, as the electrode often becomes hydrophilic due to electrochemical modifications so that the pores in the catalyst layer are flooded by the electrolyte30,31, which will suppress the mass transport and lead to a decline of the reaction rate. For example, as shown in Fig. 3e, the catalyst side of the $\\mathrm{Cu/}$ C electrode exhibited a contact angle of $144.2^{\\circ}$ initially, which however dropped significantly to $55.4^{\\circ}$ after $\\mathrm{CO}_{2}\\mathrm{RR}$ at $-1.0\\mathrm{V}$ for $^{2\\mathrm{h}}$ , indicating an evolution of the electrode’s hydrophobicity and flooding of the electrode31. In contrast, the $\\mathrm{Cu}/\\mathrm{C}/$ PTFE electrode exhibited a contact angle of $150.8^{\\circ}$ and $144.7^{\\circ}$ before and after electrolysis (Fig. 3f), suggesting that the added PTFE particles preserved the hydrophobicity and prevented the catalyst layer from flooding, so that a balanced gas/liquid microenvironment was maintained in the catalyst layer to form durable solid–liquid–gas interfaces for $\\mathrm{CO}_{2}$ electrolysis. \n\nEffects of PTFE loading and size on the microenvironment. The gas/liquid microenvironment inside the catalyst layer depends on the added PTFE particles, particularly their loading and size. To elucidate their effects, we first varied the loading of the PTFE nanoparticles with otherwise the same amount of Cu nanoparticles and carbon black. Figure 4a shows the partial current densities for $\\mathrm{CO}_{2}\\mathrm{RR}$ on the $\\mathrm{\\bar{Cu}/C/P T F E}$ electrodes with different PTFE mass ratios in the catalyst layer. As the mass ratio increased from 0, the $\\mathrm{CO}_{2}\\mathrm{RR}$ activity increased until a maximum value was reached at a $50\\%$ mass ratio of PTFE, while an even higher ratio caused a decline of the activity. The total Faradaic efficiency for $\\mathrm{CO}_{2}\\mathrm{RR}$ exhibited a similar dependence on the PTFE mass ratio from 0 to $50\\%$ , but it did not drop at a higher ratio of $70\\%$ (Fig. 4b). Thus, a moderate amount of PTFE can create a hydrophobic microenvironment to enhance the $\\mathrm{CO}_{2}\\mathrm{RR}$ activity and Faradaic efficiency, but excessive PTFE will over suppress the availability of electrolyte and protons for $\\mathrm{CO}_{2}\\mathrm{RR}.$ An optimal balance between gas and liquid in the catalyst layer is needed for efficient $\\mathrm{CO}_{2}$ electrolysis. To directly build a relationship between the electrode hydrophobicity and $\\mathrm{CO}_{2}\\mathrm{RR}$ performance, we measured the contact angles of these electrodes and plotted the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density versus the contact angles, as shown in Supplementary Fig. 17. The contact angles before $\\mathrm{CO}_{2}\\mathrm{RR}$ were close, ranging from $144.2^{\\circ}$ ( $0\\%$ PTFE) to $155.1^{\\circ}$ ( $70\\%$ PTFE), but the contact angles after $\\mathrm{CO}_{2}\\mathrm{RR}$ decreased to various degrees: the more the PTFE loading was, the larger the contact angle remained. Therefore, only the contact angle measured after electrolysis reflects an electrode’s capability of repelling liquid and stabilizing gas/liquid microenvironment in the catalyst layer for ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ \n\nThe gas–liquid balance in the catalyst layer also depends on the size of hydrophobic pores, which is correlated with the PTFE particle size. The capillary pressure difference sustained across the interface between liquid and gas is determined by the Young–Laplace equation: $P_{\\mathrm{liquid}}-P_{\\mathrm{gas}}=2\\sigma/R,$ where $\\sigma$ is the surface tension of 1 M KOH electrolyte $(74.4\\mathrm{mN}\\mathrm{m}^{-1})^{47}$ , and $R$ is the radius of curvature of the interface. In addition, as illustrated in Fig. 4c, $R=r/\\sin(\\theta_{\\mathrm{a}}-90^{\\circ})$ , where $r$ is the pore radius and $\\theta_{\\mathrm{a}}$ is the advancing contact angle of the electrolyte on the electrode $(\\sim150.8^{\\circ})$ . Based on the equation, a smaller pore requires a higher critical burst-through pressure for liquid to enter the pore33, as plotted in Fig. 4c. Thus, the catalyst layer with smaller PTFE particles should form smaller hydrophobic pores that are more effective in repelling liquid and maintaining gas in the pores. \n\nTo verify the effect of PTFE particle size, two $\\mathrm{Cu/C/PTFE}$ electrodes were prepared with different PTFE particles: one is of $30{-}40\\mathrm{nm}$ in size (Nanoshel LLC), and the other is of ${\\sim}1\\upmu\\mathrm{m}$ in size (Sigma Aldrich), both with a $50\\%$ mass ratio in the catalyst layer. They are referred as $\\mathrm{Cu}/\\mathrm{C}/\\mathrm{PTFE}(\\mathrm{S})$ and $\\mathrm{{Cu}/\\mathrm{{C}/\\mathrm{{PTFE}(L)}}}$ , respectively. The two electrodes were evaluated for $\\mathrm{CO}_{2}\\mathrm{RR}$ in the GDE cell with various $\\mathrm{CO}_{2}$ flow rates. As shown in Fig. 4d, the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density on the $\\mathrm{{Cu}/\\mathrm{{C}/\\mathrm{{PTFE}(L)}}}$ electrode similarly increased with the flow rate, but it was generally lower than that on the $\\mathrm{Cu/C/}$ PTFE(S) electrode due to the larger hydrophobic pores with a weaker repelling of liquid electrolyte. Similar difference was observed in the total Faradaic efficiency for $\\mathrm{CO}_{2}\\mathrm{RR}$ on the two electrodes, as well as the Faradic efficiency for $\\mathrm{C}_{2+}$ products, as shown in Fig. 4e. The effect of PTFE particle size on the formed microenvironment can be further examined by double-layer capacitance that reflects the area wetted by the electrolyte. The linear fit in Fig. 4f revealed a capacitance of $21.2\\mathrm{mF}$ of the $\\mathrm{Cu/C/}$ PTFE(L) electrode, which is larger than that of the Cu/C/PTFE(S) electrode $(\\sim12.4\\:\\mathrm{mF})$ , but still smaller than that of the $\\mathrm{Cu/C}$ electrode $\\mathrm{\\hbar}^{\\prime}{\\sim}26.1\\mathrm{mF})$ ), validating the effect of PTFE particle size in creating a gas/liquid microenvironment inside the catalyst layer. \n\n![](images/95d2120cb36e83886bd4efedbd51d07f21f1a495e5b42e9406f1a39b6131e886.jpg) \nFig. 4 Effects of PTFE loading and size on the microenvironment for $C O_{2}R R$ in GDE cell. a Partial current densities and b Faradaic efficiencies for ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ at $-1.0\\vee$ on Cu/C/PTFE electrodes with different mass ratios of PTFE in the catalyst layer. c Pressure difference sustained across the liquid–gas interface in nano-sized pores as a function of the pore radius. Inset: schematic of the interface advancing inside a pore. d Partial current densities and e Faradaic efficiencies for $C O_{2}R R$ on two $\\mathsf{C u/C/P T F E}$ electrodes with different PTFE particle sizes. In e, the left column with dashed line frame at each flow rate is for the $\\mathsf{C u/C/P T F E(L)}$ electrode and the right column with solid line frame is for the Cu/C/PTFE(S) electrode. f Double-layer charging current plotted against the CV scan rate for the electrodes. The error bars represent the standard deviation of three independent measurements. \n\n![](images/36d90adf89407cd8e0671880427c9f665e78298d1c3ec81465f52c391d64d99e.jpg) \nFig. 5 Effect of gas-diffusion channels on the $C O_{2}R R$ in GDE cell. a Schematic illustration of the gas flow fields generated by the interdigitated and serpentine channels. b Partial current densities for ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ on the Cu/C/PTFE electrode (with a $50\\%$ PTFE mass ratio) with two different channels at $-1.0\\vee$ with various ${\\mathsf{C O}}_{2}$ gas flow rates. The error bars represent the standard deviation of three independent measurements. \n\nEffect of gas-diffusion channels. As the $\\mathrm{CO}_{2}\\mathrm{RR}$ activity of the Cu/C/PTFE electrode depends on the $\\mathrm{CO}_{2}$ gas flow rate, the gas flow field in the GDE can be engineered to enhance the $\\mathrm{CO}_{2}$ transport via the design of gas-diffusion channels, such as interdigitated and serpentine channels (Fig. 5a). Recent studies of $\\mathrm{CO}_{2}\\mathrm{RR}$ in GDE cells often used serpentine channels21,24, where the neighboring channels are connected so that gas diffuses along the channels from inlet to outlet. In this design, the vertical diffusion of gas into the electrode and catalyst layer is driven by pressure gradient. In contrast, in the interdigitated design the inlet and outlet rows are aligned alternately and separately by walls, so the inlet gas is forced to diffuse vertically into the electrode and then exit to the outlet channels48. Such a flow field is more effective in driving the mass transport of $\\mathrm{CO}_{2}$ into the catalyst layer. Thus, we compared $\\mathrm{CO}_{2}\\mathrm{RR}$ on the $\\mathrm{Cu/C}_{I}$ PTFE electrode in GDE cells with interdigitated and serpentine flow fields. As shown in Fig. 5b, the $\\mathrm{CO}_{2}\\mathrm{RR}$ current density increased with the gas flow rate for both designs, but the one with interdigitated channels showed a higher $\\mathrm{CO}_{2}\\mathrm{RR}$ current density, as well as a sharper increase with the flow rate, indicating a more efficient transport of gaseous $\\mathrm{CO}_{2}$ to the catalyst with the interdigitated flow field. \n\n# Discussion \n\nThe above results confirmed the formation of a balanced gas/ liquid microenvironment inside the catalyst layer of the $\\mathrm{Cu/C/}$ PTFE electrode for $\\mathrm{CO}_{2}$ electrolysis. Compared to regular GDEs, the added PTFE particles create hydrophobic pores for gas-phase $\\mathrm{CO}_{2}$ transport inside the catalyst layer, which greatly reduces the diffusion layer thickness as compared to a regular catalyst layer that is wetted by electrolyte29. To quantify the effect, we obtained the EIS of the electrodes under $\\bar{\\mathrm{CO}}_{2}\\mathrm{RR}$ conditions and model them to estimate the diffusion layer thickness. EIS is an effective and noninvasive method to investigate Nernst diffusion process in a multilayer system49, which can be described by an equivalent impedance $Z_{\\mathrm{d}}$ in circuit modeling. Supplementary Fig. 18 shows the circuit model and its equivalent ladder circuit to describe the impedances in a porous carbon electrode50, as well as the EIS measured for the ${\\mathrm{Cu/C}},$ Cu/C/PTFE(S), and $\\mathrm{{Cu}/\\mathrm{{C}/\\mathrm{{PTFE}(L)}}}$ electrodes under $\\mathrm{CO}_{2}\\mathrm{RR}$ conditions in the GDE cell. The feature in the low frequency region of the EIS is attributed to the impedance of the diffusion layer49. The finite diffusion layer thickness $\\delta$ in our system can be theoretically derived from $Z_{\\mathrm{d}}$ (ref. 51), and the diffusion layer thickness was estimated to be $20.2\\pm3.1$ , $3.2\\pm0.9$ , and $7.3\\pm0.8\\upmu\\mathrm{m}$ for the ${\\mathrm{Cu/C}},$ Cu/C/PTFE (S), and $\\mathrm{{Cu}/\\mathrm{{C}/\\mathrm{{PTFE}(L)}}}$ electrodes, respectively. The data further quantitatively confirmed our conclusion: the diffusion layer thickness greatly reduced from 20.2 to $3.2\\upmu\\mathrm{m}$ after dispersing PTFE particles in the catalyst layer, because the PTFE can enable gas-phase transport of $\\mathrm{CO}_{2}$ in the catalyst layer and reduce the thickness of liquid electrolyte that $\\mathrm{CO}_{2}$ must diffuse through to reach the catalyst. The estimated diffusion layer thickness for the Cu/C/PTFE(L) electrode is also consistent with our expectation and the measured $\\mathrm{CO}_{2}\\mathrm{RR}$ performance. \n\nThe reduced diffusion layer thickness accelerates the transport of $\\mathrm{CO}_{2}$ to the catalyst, resulting in an increased steady concentration of $\\mathrm{CO}_{2}$ near the catalyst29, as shown in Supplementary Fig. 19. At equilibrium, the surface coverage of $^*\\bar{\\mathrm{CO}}_{2}$ $(\\theta_{\\mathrm{CO}_{2}})$ adsorbed on the catalyst is proportional to the local concentration of $\\mathrm{CO}_{2}$ as follows16: $\\dot{\\theta}_{\\mathrm{CO}_{2}}=\\dot{\\theta}^{\\ast}\\mathrm{\\cdot}[\\mathrm{CO}_{2}]\\cdot\\mathrm{exp}(-E_{\\mathrm{CO}_{2}}/R T)$ , where $\\theta^{*}$ is the coverage of available surface sites, $[\\mathrm{CO}_{2}]$ is the $\\mathrm{CO}_{2}$ local concentration, $E_{\\mathrm{CO}_{2}}$ is the adsorption energy of $\\mathrm{CO}_{2}$ on the catalyst, $R$ is the ideal gas constant, and $T$ is the temperature. Therefore, we propose that the hydrophobic microenvironment in the $\\mathrm{Cu/C/PTFE}$ electrode enhances the mass transport and adsorption of $\\mathrm{CO}_{2}.$ , resulting in an increased coverage of $^*\\mathrm{CO}_{2}$ on the catalyst surface for reactions18,32. This will increase the $\\mathrm{CO}_{2}\\mathrm{RR}$ rate, as well as the produced CO for $\\scriptstyle\\mathrm{C-C}$ coupling, thus improving the Faradaic efficiency for $\\mathrm{C}_{2+}$ products. The hydrophobic microenvironment may also trap the produced CO inside the catalyst layer, which can increase the local concentration of CO to enhance $C{\\mathrm{-}}C$ coupling toward $\\mathrm{C}_{2+}$ products16,45. \n\nFurthermore, the ECSA of the $\\mathrm{Cu/C/PTFE}$ electrode is around half that of the $\\mathrm{Cu/C}$ electrode (Fig. 3d), so half of the Cu nanoparticles are not in contact with the electrolyte and the surfaces of these catalyst particles are inactive for $\\mathrm{CO}_{2}\\mathrm{RR}$ due to the lack of protons and ionic conductivity. On the other hand, some catalyst particles may be located at the boundary between gas and liquid, so they are accessible to both gaseous $\\mathrm{CO}_{2}$ molecules and liquid electrolyte. Thus, $\\mathrm{CO}_{2}$ molecules from the gas side, and protons or water molecules from the liquid side can promote ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ at the three-phase boundary sites of the catalyst surface, as schematically shown in Supplementary Fig. 20. Such three-phase boundary sites can be highly active for ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ due to the direct and fast gas-phase adsorption of $\\mathrm{CO}_{2}$ on the catalyst surface without the influence of electric double layer and solvated ions52–54. This can explain the dependence of the $\\mathrm{CO}_{2}\\mathrm{RR}$ activity on the gas flow rate for the $\\mathrm{Cu/C\\bar{/}}$ PTFE electrode due to the gasphase transport and adsorption of $\\mathrm{CO}_{2}$ . \n\nAs a proof-of-concept study, we used commercial Cu nanoparticles for simplicity, which are intrinsically less active than those optimized Cu catalysts19–22. As a result, the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance here may not be as high as that in some reports, but the significance of our study lies in the new understanding and a general approach to control the catalyst microenvironment for gas-involving electrochemical reactions. Our work differs from some prior studies that tuned the composition of the $\\mathrm{\\Delta}\\mathrm{MPL}^{20}$ or added PTFE suspensions in the catalyst layer55, where the PTFE particles were coated by surfactant that could weaken the hydrophobicity. In addition, some studies used $\\mathrm{CO}_{2}$ flow rates as high as 50 or $100\\mathrm{sccm}^{21,24}$ , which may create a high local pressure in the gas side of the $\\mathrm{GDE}^{56}$ and enhance the $\\mathrm{CO}_{2}$ mass transport to improve ${\\mathrm{CO}}_{2}{\\mathrm{RR}}$ performance57. Our study achieved a high activity and selectivity for $\\mathrm{CO}_{2}\\mathrm{RR}$ with a much lower $\\mathrm{CO}_{2}$ flow rate $(4\\mathrm{sccm})$ ), resulting in a high single-pass conversion rate of $\\mathrm{CO}_{2}$ of ${\\sim}14\\%$ (Supplementary Fig. 14), benefiting from the catalyst microenvironment. Our method of controlling local gas/ liquid microenvironment can be generally applied to improve other gas-involving electrocatalysis, when gaseous reactant has a low solubility and slow diffusion in the electrolyte, such as the electrochemical reduction of $\\Nu_{2}$ (ref. 58). \n\nIn summary, we developed a GDE with a hydrophobic microenvironment for $\\mathrm{CO}_{2}$ electrolysis by dispersing PTFE nanoparticles in the catalyst layer, where the PTFE can repel liquid electrolyte and maintain gaseous reactant near the catalyst particles. The $\\mathrm{Cu/C/}$ PTFE electrode showed a significant improvement in the activity, Faradaic efficiency, and $\\mathrm{C}_{2+}$ product selectivity for $\\mathrm{CO}_{2}\\mathrm{RR}$ as compared to a regular $\\mathrm{Cu/C}$ electrode without added PTFE. Furthermore, the $\\mathrm{CO}_{2}^{\\circ}\\mathrm{RR}$ current density on the $\\mathrm{Cu/C/}$ PTFE electrode increased with the $\\mathrm{CO}_{2}$ gas flow rate, indicating a gas-phase transport of $\\mathrm{CO}_{2}$ in the catalyst layer. The improved performance is attributed to the reduced diffusion layer thickness that accelerates $\\mathrm{CO}_{2}$ mass transport, increases the local concentration of $\\mathrm{CO}_{2}$ near the catalyst surface, and enhances $\\mathrm{CO}_{2}$ adsorption for the reaction. Compared to regular GDEs, the electrode with added PTFE particles creates a balanced gas/liquid microenvironment and solid– liquid–gas interfaces inside the catalyst layer, which can enhance the mass transport and kinetics of $\\mathrm{CO}_{2}$ electrolysis, providing a general approach to improve gas-involving electrocatalysis. \n\n# Methods \n\nMaterials characterization. TEM images were acquired using a FEI Tecnai F30 transmission electron microscope with a field emission gun operated at $200\\mathrm{kV}$ . SEM images and EDS elemental mapping were acquired using a ZEISS Ultra-55 FEG scanning electron microscope. XRD pattern was collected using a PANalytical Empyrean diffractometer with a $1.8\\mathrm{KW}$ copper X-ray tube. XPS data were acquired by a Thermo Scientific ESCALAB $\\mathrm{XI^{+}}$ X-ray Photoelectron Spectrometer with an Al Kα X-ray source $(1486.67\\mathrm{eV})$ . Operando XAS was performed at Beamline 2-2 of the Stanford Synchrotron Radiation Lightsource at the SLAC National Accelerator Laboratory using a modified two-compartment H-cell and a Lytle fluorescence detector (Supplementary Fig. 3). The XAS data were processed using the ATHENA software59. Contact angle measurements were carried out using an L2004A1 Ossila Contact Angle Goniometer (Ossila Ltd, UK). \n\nPreparation of electrodes for $C O_{2}R R$ in H-cell. First, $6\\mathrm{mg}$ of commercial Cu nanoparticles (US1828, US Research Nanomaterials) and 6 mg of Vulcan XC 72 carbon black (Fuel Cell Store) were each dispersed in $2\\mathrm{mL}$ isopropanol, \n\nrespectively. After sonication for $\\mathrm{{1h}}.$ the two dispersions were mixed with $200\\upmu\\mathrm{L}$ Nafion solution $(5\\mathrm{wt\\%})$ and sonicated for another $^{\\textrm{1h}}$ . The mixture was used as the catalyst ink and sprayed on electrode substrates by a homemade XY plotter equipped with an airbrush. Two types of substrates with an area of $1\\bar{\\times}1\\mathrm{cm}^{2}$ were used: AvCarb MGL370 and AvCarb GDS2230 (Fuel Cell Store). After deposition, the electrodes were dried overnight at room temperature, with a Cu catalyst loading of $0.65\\pm0.05\\mathrm{mg}\\mathrm{cm}^{-2}$ . \n\nPreparation of electrodes for $C O_{2}R R$ in GDE cell. The same catalyst ink in the H-cell studies was used as $0\\%$ PTFE-catalyst ink here. The PTFE-dispersed catalyst layer was prepared as follows. First, $6\\mathrm{mg}$ of commercial Cu nanoparticles (US1828, US Research Nanomaterials) and $6\\mathrm{mg}$ of Vulcan XC 72 carbon black (Fuel Cell Store) were each dispersed in $1\\mathrm{mL}$ isopropanol, respectively. Then, 2.2, 8.7, 20, 30, and $46.7\\mathrm{mg}$ PTFE nanopowder ( $\\mathrm{APS}30{-}40\\mathrm{nm}$ , Nanoshel LLC) were dispersed in $2\\mathrm{mL}$ isopropanol, respectively. After sonication for $^{\\textrm{1h}}$ , Cu nanoparticle dispersion, carbon black dispersion, corresponding PTFE dispersion, and $200\\upmu\\mathrm{L}$ Nafion solution $(5~\\mathrm{wt\\%}$ , containing $\\mathrm{\\sim}8\\mathrm{mg}$ Nafion) were mixed and sonicated for another $^{\\mathrm{~1\\h,~}}$ which were used as $10\\%$ , $30\\%$ , $50\\%$ , $60\\%,$ and $70\\%$ PTFE-catalyst inks, respectively. Each catalyst ink was sprayed on an AvCarb GDS2230 substrate with a Cu catalyst loading of $\\dot{0}.65\\pm0.05\\mathrm{m}\\mathbf{\\bar{g}}\\mathrm{cm}^{-2}$ . After drying overnight, $1\\mathrm{mL}$ of diluted Teflon PTFE DISP 30 solution $0.12~\\mathrm{wt\\%}$ , Fuel Cell Store) was further sprayed on top of all electrodes except the $0\\%$ PTFE one. All the samples were dried in air for at least $^{5\\mathrm{h}}$ before testing. \n\nElectrochemical measurements. Electrochemical tests were performed using a Gamry Interface 1000 Potentiostat or a CH Instruments 760E Potentiostat with an H-cell or a home-built GDE flow cell. The H-cell experiments were carried out in a gas-tight two-compartment H-cell separated by a Nafion 1110 membrane under ambient conditions (Supplementary Fig. 6). A platinum gauze and an $\\mathrm{\\Ag/AgCl}$ electrode with saturated KCl solution (BASi MF-2056) were used as the counter electrode and the reference electrode, respectively. Electrodes prepared with AvCarb MGL370 or GDS2230 substrate were used as the working electrode. $\\mathrm{CO}_{2}$ - saturated 1 M ${\\mathrm{KHCO}}_{3}$ solution was used as the electrolyte, which was stirred at a rate of 600 r.p.m. during electrolysis. GDE-cell studies were performed using a home-built GDE flow cell (Supplementary Fig. 12), including a Ti current collector with interdigitated gas-diffusion channels, a cathodic GDE with catalyst layer on AvCarb GDS2230 substrate, a 3D-printed chamber with ports for electrolyte flow and reference electrode, and an Fe–Ni foam inserted in a pocket of Ti current collector as the anode28. The gas-diffusion channels have a depth of $0.2\\mathrm{mm}$ and a density of 50 channels $c\\mathrm{m}^{-1}$ . A Nafion 1110 or FAA-3-PK-130 membrane was used to separate the cathode and anode chambers. A leak-free $\\mathrm{\\Ag/AgCl}$ electrode (Warner Instruments) was used as the reference electrode. The above prepared electrodes were used as working electrodes with an effective area of $0.66\\mathrm{cm}^{2}$ . The catholyte and the anolyte were each $20~\\mathrm{mL}$ of $^\\textrm{\\scriptsize1M}$ KOH solution circulated using peristaltic pumps at a flow rate ranging from $0.6{-}2.2\\ \\mathrm{mL\\min^{-1}}$ . For both H-cell and GDE-cell studies, $\\mathrm{CO}_{2}$ gas flow was controlled by an Alicat mass flow controller at a specified flow rate ranging from $2{\\mathrm{-}}6\\operatorname{sccm}$ , and the applied potentials were iR-compensated and converted to the RHE scale. The reported partial current densities for $\\mathrm{CO}_{2}\\mathrm{RR}$ were normalized to geometric surface areas. The EIS data were fit with a circuit model50 using the EIS Spectrum Analyser60. \n\nDuring electrolysis, gas-phase products from the H-cell or GDE cell were quantified by a gas chromatograph (SRI Multiple Gas Analyzer $\\#5$ ) equipped with molecular sieve 5A and HayeSep D columns with Ar as the carrier gas. Solutionphase products were analyzed using a Bruker AVIII ${500}\\ \\mathrm{MHz}$ NMR spectrometer. Typically, $500\\upmu\\mathrm{L}$ of the post-electrolysis catholyte was mixed with $100\\upmu\\mathrm{L}$ of $\\mathrm{D}_{2}\\mathrm{O}$ containing 100 p.p.m. dimethyl sulfoxide as the internal standard. $^1\\mathrm{H}$ NMR spectra were acquired using water suppression mode. \n\nElectrochemically active surface area measurement. The ECSA of an electrode was quantified by measuring the double-layer capacitance. CV was performed in the GDE flow cell at different scan rates in a potential window where only doublelayer charging and discharging occur (no Faradaic process). The double-layer charging current was then plotted versus the CV scan rate, and the slope of the linear regression gave the double-layer capacitance. A representative set of the CV scans is exhibited in Supplementary Fig. 16. \n\nCalculation of $C O_{2}R R$ current density and Faradaic efficiency. The gas-phase products were quantified by comparison of the peak integrals to standard calibration gases to determine the molar flow rate of a product (V). The Faradaic efficiency (FE) for each gas-phase product was calculated using the following equation: \n\n$$\n\\mathrm{FE}=\\frac{n F V}{I_{\\mathrm{total}}}\\times100\\%,\n$$ \n\nwhere $n$ is the number of electrons transferred for the product, $F$ is the Faraday constant, $V$ is the molar flow rate of the product, and $I_{\\mathrm{total}}$ is the total current of the electrolysis. The molar quantities of solution-phase products were quantified by NMR spectroscopy and then converted to Coulombs by multiplying by $n F_{;}$ , where $F$ is Faraday’s constant and $n=2$ , 8, 12, and 18 for formate $(\\mathrm{HCOO^{-}},$ , acetate $(\\mathrm{AcO^{-}})$ , ethanol (EtOH), and $n$ -propanol $(\\mathrm{PrOH})$ , respectively. The charges corresponding to each product were then compared to the integrated electrolysis charge to determine the Faradaic efficiency. \n\nThe partial current density for $\\mathrm{CO}_{2}\\mathrm{RR}$ $(j_{\\mathrm{CO_{2}R R}})$ was calculated using the following equation: \n\n$$\nj_{\\mathrm{CO_{2}R R}}=\\frac{\\sum_{\\mathrm{CO_{2}R R}\\mathrm{products}}\\left(I_{\\mathrm{total}}\\times\\mathrm{FE}\\right)}{\\mathrm{Electrodearea}},\n$$ \n\nwhere FE is the Faradaic efficiency of each product, and electrode area is the effective geometrical area of the working electrode. \n\nThe single-pass conversion rate (CR) of $\\mathrm{CO}_{2}$ was calculated using the following equation: \n\n$$\n\\mathrm{CR}=\\frac{\\sum_{\\mathrm{CO_{2}R R p r o d u c t s}}\\left(\\frac{I_{\\mathrm{total}}\\times\\mathrm{FE}}{n F}\\times N_{\\mathrm{C}}\\times\\frac{R T}{P}\\right)}{\\mathrm{CO_{2}f l o w r a t e}},\n$$ \n\nwhere $N_{\\mathrm{C}}$ is the number of carbon atoms in each product molecule (for example, $N_{\\mathrm{C}}=2$ for $\\mathrm{C}_{2}\\mathrm{H}_{4},$ ), $R$ is the ideal gas constant, and $T$ and $P$ are the absolute temperature and pressure of the $\\mathrm{CO}_{2}$ gas. \n\nThe reported $\\mathrm{CO}_{2}\\mathrm{RR}$ current densities, Faradaic efficiencies, conversion rates, and their error bars were determined based on the measurements of three separately prepared samples under the same conditions. \n\n# Data availability \n\nThe data that support the findings of this study are available in the article and its Supplementary Information file or from the corresponding authors upon reasonable request. \n\nReceived: 22 May 2020; Accepted: 23 November 2020; Published online: 08 January 2021 \n\n# References \n\n1. Chu, S. & Majumdar, A. Opportunities and challenges for a sustainable energy future. Nature 488, 294–303 (2012). \n2. Weber, R. S. Effective use of renewable electricity for making renewable fuels and chemicals. ACS Catal. 9, 946–950 (2018). \n3. De Luna, P. et al. What would it take for renewably powered electrosynthesis to displace petrochemical processes? Science 364, eaav3506 (2019). \n4. Hori, Y. in Modern Aspects of Electrochemistry, Vol. 42 (Vayenas, C. G., White, R. E. & Gamboa-Aldeco, M. E. eds) 89−189 (Springer, New York, 2008). \n5. Whipple, D. T. & Kenis, P. J. Prospects of $\\mathrm{CO}_{2}$ utilization via direct heterogeneous electrochemical reduction. J. Phys. Chem. Lett. 1, 3451–3458 (2010). \n6. Li, C. W. & Kanan, M. W. $\\mathrm{CO}_{2}$ reduction at low overpotential on Cu electrodes resulting from the reduction of thick $\\mathrm{Cu}_{2}\\mathrm{O}$ films. J. Am. Chem. Soc. 134, 7231–7234 (2012). \n7. Lu, Q. et al. A selective and efficient electrocatalyst for carbon dioxide reduction. Nat. Commun. 5, 3242 (2014). \n8. Wu, Y., Jiang, Z., Lu, X., Liang, Y. & Wang, H. Domino electroreduction of $\\mathrm{CO}_{2}$ to methanol on a molecular catalyst. Nature 575, 639–642 (2019). \n9. Ross, M. B. et al. Designing materials for electrochemical carbon dioxide recycling. Nat. Catal. 2, 648–658 (2019). \n10. Li, C. W., Ciston, J. & Kanan, M. W. Electroreduction of carbon monoxide to liquid fuel on oxide-derived nanocrystalline copper. Nature 508, 504–507 (2014). \n11. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science 355, eaad4998 (2017). \n12. Wang, J. et al. Ambient ammonia synthesis via palladium-catalyzed electrohydrogenation of dinitrogen at low overpotential. Nat. Commun. 9, 1795 (2018). \n13. Montoya, J. H., Peterson, A. A. & Nørskov, J. K. Insights into $\\scriptstyle{\\mathrm{C-C}}$ Coupling in $\\mathrm{CO}_{2}$ electroreduction on copper electrodes. ChemCatChem 5, 737–742 (2013). \n14. Garza, A. J., Bell, A. T. & Head-Gordon, M. Mechanism of $\\mathrm{CO}_{2}$ reduction at copper surfaces: pathways to $\\mathrm{C}_{2}$ products. ACS Catal. 8, 1490–1499 (2018). \n15. Garg, S. et al. Advances and challenges in electrochemical $\\mathrm{CO}_{2}$ reduction processes: an engineering and design perspective looking beyond new catalyst materials. J. Mater. Chem. A 8, 1511–1544 (2020). \n16. Tan, Y. C., Lee, K. B., Song, H. & Oh, J. Modulating local $\\mathrm{CO}_{2}$ concentration as a general strategy for enhancing C−C coupling in $\\mathrm{CO}_{2}$ electroreduction. Joule 4, 1104–1120 (2020). \n17. Bard, A. J. & Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications 2nd edn, 30 (Wiley, New York, NY, 2001). \n18. Zhang, B. A., Ozel, T., Elias, J. S., Costentin, C. & Nocera, D. G. Interplay of homogeneous reactions, mass transport, and kinetics in determining selectivity of the reduction of $\\mathrm{CO}_{2}$ on Gold electrodes. ACS Cent. Sci. 5, 1097–1105 (2019). \n19. Ma, S. et al. One-step electrosynthesis of ethylene and ethanol from $\\mathrm{CO}_{2}$ in an alkaline electrolyzer. J. Power Sources 301, 219–228 (2016). \n20. Kim, B., Hillman, F., Ariyoshi, M., Fujikawa, S. & Kenis, P. J. Effects of composition of the micro porous layer and the substrate on performance in the electrochemical reduction of $\\mathrm{CO}_{2}$ to CO. J. Power Sources 312, 192–198 (2016). \n21. Dinh, C. T. et al. $\\mathrm{CO}_{2}$ electroreduction to ethylene via hydroxide-mediated copper catalysis at an abrupt interface. Science 360, 783–787 (2018). \n22. De Arquer, F. P. G. et al. $\\mathrm{CO}_{2}$ electrolysis to multicarbon products at activities greater than 1 A $c\\mathrm{m}^{-2}$ . Science 367, 661–666 (2020). \n23. Higgins, D., Hahn, C., Xiang, C., Jaramillo, T. F. & Weber, A. Z. Gas-diffusion electrodes for carbon dioxide reduction: A new paradigm. ACS Energy Lett. 4, 317–324 (2019). \n24. Ren, S. et al. Molecular electrocatalysts can mediate fast, selective $\\mathrm{CO}_{2}$ reduction in a flow cell. Science 365, 367–369 (2019). \n25. Zheng, T. et al. Large-scale and highly selective $\\mathrm{CO}_{2}$ electrocatalytic reduction on nickel single-atom catalyst. Joule 3, 265–278 (2019). \n26. Han, L., Zhou, W. & Xiang, C. High-rate electrochemical reduction of carbon monoxide to ethylene using Cu-nanoparticle-based gas diffusion electrodes. ACS Energy Lett. 3, 855–860 (2018). \n27. Jouny, M., Luc, W. & Jiao, F. High-rate electroreduction of carbon monoxide to multi-carbon products. Nat. Catal. 1, 748–755 (2018). \n28. Ripatti, D. S., Veltman, T. R. & Kanan, M. W. Carbon monoxide gas diffusion electrolysis that produces concentrated $\\mathbf{C}_{2}$ products with high single-pass conversion. Joule 3, 240–256 (2019). \n29. Burdyny, T. & Smith, W. A. $\\mathrm{CO}_{2}$ reduction on gas-diffusion electrodes and why catalytic performance must be assessed at commercially-relevant conditions. Energy Environ. Sci. 12, 1442–1453 (2019). \n30. Weng, L. C., Bell, A. T. & Weber, A. Z. Modeling gas-diffusion electrodes for $\\mathrm{CO}_{2}$ reduction. Phys. Chem. Chem. Phys. 20, 16973–16984 (2018). \n31. Leonard, M. E., Clarke, L. E., Forner‐Cuenca, A., Brown, S. M. & Brushett, F. R. Investigating electrode flooding in a flowing electrolyte, gas‐fed carbon dioxide electrolyzer. ChemSusChem 13, 400–411 (2020). \n32. Kas, R. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction on nanostructured metal electrodes: fact or defect? Chem. Sci. 11, 1738–1749 (2020). \n33. Li, J. et al. Efficient electrocatalytic $\\mathrm{CO}_{2}$ reduction on a three-phase interface. Nat. Catal. 1, 592–600 (2018). \n34. Wakerley, D. et al. Bio-inspired hydrophobicity promotes $\\mathrm{CO}_{2}$ reduction on a Cu surface. Nat. Mater. 18, 1222–1227 (2019). \n35. Li, J. et al. Effectively increased efficiency for electroreduction of carbon monoxide using supported polycrystalline copper powder electrocatalysts. ACS Catal. 9, 4709–4718 (2019). \n36. Chen, R. et al. Highly selective production of ethylene by the electroreduction of carbon monoxide. Angew. Chem. Int. Ed. 59, 154–160 (2020). \n37. Cai, Z. et al. Selectivity regulation of $\\mathrm{CO}_{2}$ electroreduction through contact interface engineering on superwetting Cu nanoarray electrodes. Nano Res. 12, 345–349 (2019). \n38. Wang, Y. et al. Rational design of three-phase interfaces for electrocatalysis. Nano Res. 12, 2055–2066 (2019). \n39. Eilert, A., Roberts, F. S., Friebel, D. & Nilsson, A. Formation of copper catalysts for $\\mathrm{CO}_{2}$ reduction with high ethylene/methane product ratio investigated with in situ X-ray absorption spectroscopy. J. Phys. Chem. Lett. 7, 1466–1470 (2016). \n40. Steitz, R. et al. Nanobubbles and their precursor layer at the interface of water against a hydrophobic substrate. Langmuir 19, 2409–2418 (2003). \n41. Zhang, X. H., Quinn, A. & Ducker, W. A. Nanobubbles at the interface between water and a hydrophobic solid. Langmuir 24, 4756–4764 (2008). \n42. Burdyny, T. et al. Nanomorphology-enhanced gas-evolution intensifies $\\mathrm{CO}_{2}$ reduction electrochemistry. ACS Sustain. Chem. Eng. 5, 4031–4040 (2017). \n43. Zhao, X., Ren, H. & Luo, L. Gas bubbles in electrochemical gas evolution reactions. Langmuir 35, 5392–5408 (2019). \n44. Perez Sirkin, Y. A., Gadea, E. D., Scherlis, D. A. & Molinero, V. Mechanisms of nucleation and stationary states of electrochemically generated nanobubbles. J. Am. Chem. Soc. 141, 10801–10811 (2019). \n45. Liu, X. et al. pH effects on the electrochemical reduction of $\\mathrm{CO}_{2}$ towards $\\mathbf{C}_{2}$ products on stepped copper. Nat. Commun. 10, 32 (2019). \n46. Waszczuk, P., Zelenay, P. & Sobkowski, J. Surface interaction of benzoic acid with a copper electrode. Electrochim. Acta 40, 1717–1721 (1995). \n47. O’Brien, T. F., Bommaraju, T. V. & Hine, F. Handbook of Chlor-Alkali Technology Vol. 1 (Springer, Boston, MA, 2005). \n48. Kreutzer, H., Yarlagadda, V. & Van Nguyen, T. Performance evaluation of a regenerative hydrogen-bromine fuel cell. J. Electrochem. Soc. 159, F331–F337 (2012). \n49. Bisquert, J., Garcia-Belmonte, G., Fabregat-Santiago, F. & Bueno, P. R. Theoretical models for ac impedance of finite diffusion layers exhibiting low frequency dispersion. J. Electroanal. Chem. 475, 152–163 (1999). \n50. Kwon, W., Kim, J. M. & Rhee, S. W. A new equivalent circuit model for porous carbon electrodes in charge transfer reaction of iodide/triiodide redox couples. Electrochim. Acta 68, 110–113 (2012). \n51. Zhang, W. et al. Investigations on the interfacial capacitance and the diffusion boundary layer thickness of ion exchange membrane using electrochemical impedance spectroscopy. J. Membr. Sci. 502, 37–47 (2016). \n52. Ringe, S. et al. Double layer charging driven carbon dioxide adsorption limits the rate of electrochemical carbon dioxide reduction on Gold. Nat. Commun. 11, 33 (2020). \n53. Resasco, J. et al. Promoter effects of alkali metal cations on the electrochemical reduction of carbon dioxide. J. Am. Chem. Soc. 139, 11277–11287 (2017). \n54. Dunwell, M., Yan, Y. & Xu, B. Understanding the influence of the electrochemical double-layer on heterogeneous electrochemical reactions. Curr. Opin. Chem. Eng. 20, 151–158 (2018). \n55. Wang, Q., Dong, H., Yu, H. & Yu, H. Enhanced performance of gas diffusion electrode for electrochemical reduction of carbon dioxide to formate by adding polytetrafluoroethylene into catalyst layer. J. Power Sources 279, 1–5 (2015). \n56. Inoue, G., Matsukuma, Y. & Minemoto, M. Effect of gas channel depth on current density distribution of polymer electrolyte fuel cell by numerical analysis including gas flow through gas diffusion layer. J. Power Sources 157, 136–152 (2006). \n57. Clark, E. L. et al. Standards and protocols for data acquisition and reporting for studies of the electrochemical reduction of carbon dioxide. ACS Catal. 8, 6560–6570 (2018). \n58. Hu, L., Xing, Z. & Feng, X. Understanding the electrocatalytic interface for ambient ammonia synthesis. ACS Energy Lett. 5, 430–436 (2020). \n59. Ravel, B. & Newville, M. ATHENA, ARTEMIS, HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 12, 537–541 (2005). \n60. Bondarenko, A. S. & Ragoisha, G. A. in Progress in Chemometrics Research (ed. Pomerantsev, A. L.) 89−102 (Nova Science Publishers, New York, NY, 2005). \n\n# Acknowledgements \n\nThis work was supported by a startup fund from the University of Central Florida and a Sloan Research Fellowship from the Alfred P. Sloan Foundation (Grant Number: FG2019-11694). The authors acknowledge the use of an XPS instrument supported by the NSF MRI: ECCS: 1726636. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. \n\n# Author contributions \n\nZ.X. and X.F. designed the experiments. Z.X. prepared the GDE cell, performed the experiments, and analyzed the data. L.H. assisted in the experimental work. D.S.R. provided the design of the GDE cell and helpful discussions. X.F., Z.X., and X.H. cowrote the manuscript. X.F. and X.H. supervised the work. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-20397-5. \n\nCorrespondence and requests for materials should be addressed to X.H. or X.F. \n\nPeer review information Nature Communications thanks Tierui Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1016_j.soilbio.2021.108211", + "DOI": "10.1016/j.soilbio.2021.108211", + "DOI Link": "http://dx.doi.org/10.1016/j.soilbio.2021.108211", + "Relative Dir Path": "mds/10.1016_j.soilbio.2021.108211", + "Article Title": "The microplastisphere: Biodegradable microplastics addition alters soil microbial community structure and function", + "Authors": "Zhou, J; Gui, H; Banfield, CC; Wen, Y; Zang, HD; Dippold, MA; Charlton, A; Jones, DL", + "Source Title": "SOIL BIOLOGY & BIOCHEMISTRY", + "Abstract": "Plastics accumulating in the environment, especially microplastics (defined as particles <5 mm), can lead to a range of problems and potential loss of ecosystem services. Polyhydroxyalkanoates (PHAs) are biodegradable plastics used in mulch films, and in packaging material to minimize plastic waste and to reduce soil pollution. Little is known, however, about the effect of microbioplastics on soil-plant interactions, especially soil microbial community structure and functioning in agroecosystems. For the first time, we combined zymography (to localize enzyme activity hotspots) with substrate-induced growth respiration to investigate the effect of PHAs addition on soil microbial community structure, growth, and exoenzyme kinetics in the microplastisphere (i.e. interface between soil and microplastic particles) compared to the rhizosphere and bulk soil. We used a common PHAs biopolymer, poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and showed that PHBV was readily used by the microbial community as a source of carbon (C) resulting in an increased specific microbial growth rate and a more active microbial biomass in the microplastisphere in comparison to the bulk soil. Higher ss-glucosidase and leucine aminopeptidase activities (0.6-5.0 times higher Vmax) and lower enzyme affinities (1.5-2.0 times higher Km) were also detected in the microplastisphere relative to the rhizosphere. Furthermore, the PHBV addition changed the soil bacterial community at different taxonomical levels and increased the alpha diversity, as well as the relative abundance of Acidobacteria and Verrucomicrobia phyla, compared to the untreated soils. Overall, PHBV addition created soil hotspots where C and nutrient turnover is greatly enhanced, mainly driven by the accelerated microbial biomass and activity. In conclusion, microbioplastics have the potential to alter soil ecological functioning and biogeochemical cycling (e.g., SOM decomposition).", + "Times Cited, WoS Core": 371, + "Times Cited, All Databases": 412, + "Publication Year": 2021, + "Research Areas": "Agriculture", + "UT (Unique WOS ID)": "WOS:000640189100034", + "Markdown": "# The microplastisphere: Biodegradable microplastics addition alters soil microbial community structure and function \n\nJie Zhou a,b,1, Heng Gui c,d,1, Callum C. Banfield b, Yuan Wen a, Huadong Zang a,\\*, Michaela A. Dippold b, Adam Charlton e, Davey L. Jones f,g \n\na College of Agronomy and Biotechnology, China Agricultural University, Beijing, China \nb Biogeochemistry of Agroecosystems, Department of Crop Sciences, University of Goettingen, Goettingen, Germany \nc CAS Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Science, Kunming, China \nd Centre for Mountain Futures (CMF), Kunming Institute of Botany, Chinese Academy of Science, Kunming, Yunnan, China \ne BioComposites Centre, Bangor University, Bangor, Gwynedd, LL57 2UW, UK \nf School of Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2UW, UK \ng Soils West, UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA 6009, Australia \n\n# A R T I C L E I N F O \n\nKeywords: \nEnzyme activity \nMicrobial growth \nMicroplastic pollution \nSoil organic matter \nC turnover \nSequencing \n\n# A B S T R A C T \n\nPlastics accumulating in the environment, especially microplastics (defined as particles $<5~\\mathrm{{mm}}$ ), can lead to a range of problems and potential loss of ecosystem services. Polyhydroxyalkanoates (PHAs) are biodegradable plastics used in mulch films, and in packaging material to minimize plastic waste and to reduce soil pollution. Little is known, however, about the effect of microbioplastics on soil-plant interactions, especially soil microbial community structure and functioning in agroecosystems. For the first time, we combined zymography (to localize enzyme activity hotspots) with substrate-induced growth respiration to investigate the effect of PHAs addition on soil microbial community structure, growth, and exoenzyme kinetics in the microplastisphere (i.e. interface between soil and microplastic particles) compared to the rhizosphere and bulk soil. We used a common PHAs biopolymer, poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and showed that PHBV was readily used by the microbial community as a source of carbon (C) resulting in an increased specific microbial growth rate and a more active microbial biomass in the microplastisphere in comparison to the bulk soil. Higher $\\upbeta$ -glucosidase and leucine aminopeptidase activities (0.6–5.0 times higher $V_{\\mathrm{max}})$ and lower enzyme affinities (1.5–2.0 times higher $K_{m})$ were also detected in the microplastisphere relative to the rhizosphere. Furthermore, the PHBV addition changed the soil bacterial community at different taxonomical levels and increased the alpha diversity, as well as the relative abundance of Acidobacteria and Verrucomicrobia phyla, compared to the un­ treated soils. Overall, PHBV addition created soil hotspots where C and nutrient turnover is greatly enhanced, mainly driven by the accelerated microbial biomass and activity. In conclusion, microbioplastics have the po­ tential to alter soil ecological functioning and biogeochemical cycling (e.g., SOM decomposition). \n\n# 1. Introduction \n\nSynthetic polymers are widely used in our daily lives, and more than 280 million tons of plastics are produced annually (Duis and Coors, 2016; Sintim and Flury, 2017). Despite the remarkable benefits of plastics to society, there are increasing concerns associated with the vast amount of plastic entering our environment and its resistance to degradation (Rochman, 2018). These concerns are supported by esti­ mates that ${>}30\\%$ of the world’s plastic waste is disposed of inappropriately, with most of it ultimately ending up in soil (Jambeck et al., 2015; Weithmann et al., 2018). In soil, larger plastic debris often becomes fragmented into smaller pieces by biota and physical distur­ bance known as microplastics (mean diameter $<5~\\mathrm{mm},$ . They have received increased attention globally due to their potential to cause environmental damage (Rillig, 2012; de Souza Machado et al., 2019). A promising approach to overcome the accumulation of microplastics in soil is to replace traditional petroleum-based plastics with biodegrad­ able bioplastics like polyhydroxyalkanoates (PHAs; Gross and Kalra, \n\n2002; Volova et al., 2017). PHAs account for $5.6\\%$ of the global pro­ duction capacity for biodegradable polymers, and represent the second fastest growing group in the market sector since 2014 (Haider et al., 2019). Even though PHAs are used in an attempt to decrease micro­ plastic residues in terrestrial ecosystems, and praised as promising al­ ternatives for a diverse range of applications (e.g., mulch films for agriculture), the potential environmental consequences of PHAs have not yet been thoroughly studied. \n\nUnlike petroleum-based microplastics, which biodegrade extremely slowly, PHAs can be broken down by a range of organisms and are not thought to produce any harmful by-products (Volova et al., 2017; Haider et al., 2019; Sander et al., 2019). Given their biological origin, they are considered C neutral (Garrison et al., 2016), although this assumes that they do not induce positive priming of soil organic matter (SOM). Furthermore, they are thought to not enhance $\\mathrm{N}_{2}\\mathrm{O}$ and $\\mathrm{CH}_{4}$ emissions which might offset these benefits. Given that PHAs are C-rich but nutrient-poor (i.e. no N and P; Gross and Kalra, 2002; Volova et al., 2017), they may alter microbial community composition and func­ tioning during degradation. Since the decomposition of C-rich residues is associated with N and P immobilization, subsequent plant growth may also be affected due to the increased competition between plants and soil microorganisms for nutrients (Qi et al., 2018, 2020b; Song et al., 2020; Zang et al., 2020). In response to the additional C supplied from PHAs breakdown, the turnover of native SOM may be stimulated due to the altered metabolic status of the microbial community (Kuzyakov, 2010; Zang et al., 2017), and thus influence soil C and nutrient cycling. PHAs are also naturally present in soil being produced as storage compounds by the bacterial community (Mason-Jones et al., 2019). Given that bacteria are more sensitive to environmental changes (e.g. increased labile C) compared to fungi (Barnard et al., 2012), soil bacteria may have a stronger response due to the increased C availability through PHAs breakdown. This will lead to significant long-term impacts on a range of soil ecosystem services (e.g., C storage, nutrient cycling, and pollutant attenuation; Zang et al., 2018). Although recent studies revealed that microplastics may have divergent influences on soil mi­ crobial communities and enzyme activities, e.g., activation (Liu et al., 2017; de Souza Machado et al., 2019), suppression (Fei et al., 2020), or remaining unchanged (Zang et al., 2020), the effect of microbioplastics on soil microorganisms remains poorly understood. Therefore, it is vital to investigate how biodegradable microplastics affect microbial func­ tions and below-ground C processes (Zang et al., 2019, 2020; Qi et al., 2020a). \n\nSimilar to plant-soil interactions in the rhizosphere, the main pro­ cesses affected by microplastic input may occur at the soil-plastic interface (here defined as the microplastisphere). We hypothesize that these interactions are stimulated by the input of bioavailable C present in microbioplastics (i.e. increased microbial activity, attract or favor specific bacterial taxa, and interfere with belowground plantmicroorganisms interactions) leading to the formation of microbial hotspots in soil, similar to those seen in the rhizosphere (Kuzyakov and Blagodatskaya, 2015; Zang et al., 2016; Zhou et al., 2020b). Following PHAs addition, we predict that changes in the soil physico-chemical properties will only occur close to the microplastic particles, with changes in the (non-hotspot) bulk soil likely to be minor (Zettler et al., 2013; Huang et al., 2019). The specific niches of the microorganisms in the microplastisphere are of ecological relevance, given that most agricultural soils are contaminated by microplastics (Steinmetz et al., 2016; Qi et al., 2020a). However, it still remains unclear how PHAs affect soil microbial communities in hotspots and, thus, alters soil C and nutrient cycling. \n\nHere, for the first time, we coupled zymography, a method to accurately locate microbial hotspots (Hoang et al., 2020; Zhang et al., 2020), the kinetics of exoenzyme activities involved in C, N, and P cycling, microbial growth, and bacterial community structure to evaluate microbial functions, as well as soil process in hotspots (rhizosphere and microplastisphere) and bulk soil. Poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) represents a commercially available copolymer used for mulch film production. Compared to PHB, it has higher flexibility, thermal stability, and processibility due to the monomeric composition, which makes it a promising example of PHAs (Table S1; Jiang et al., 2009; Bugnicourt et al., 2014). Therefore, we aimed to 1) identify microbial hotspots in situ in soil treated with PHBV; 2) investigate the effect of biodegradable microplastics on microbial growth and enzyme kinetics; 3) evaluate changes in the bacterial community structure and function in the microplastisphere and rhizosphere. We hypothesized that: 1) the labile C in PHBV will greatly alter soil bacterial community structure and functioning compared to the rhizosphere and bulk soil, and 2) the microplastisphere contains microorganisms with a high growth rate and enzyme activity in comparison to rhizosphere and bulk soil. \n\n# 2. Materials and methods \n\n# 2.1. Site description and sampling \n\nSoil samples were taken from the Ap horizon $\\mathrm{(0{-}20~c m)}$ of an experimental field at the Reinshof Research Station of the Georg-August University of G¨ottingen, Germany $(28^{\\circ}33^{\\prime}26^{\\prime\\prime}\\mathrm{N}$ , $113^{\\circ}20^{\\prime}8^{\\prime\\prime}\\mathrm{E})$ . This experimental site was established more than 40 years ago and the farming history is well documented. No plastic mulch has ever been applied, and no plastic pollution has been recorded for the site. The soil was air-dried, sieved $(<2~\\mathrm{mm})$ ), and mixed to achieve a high degree of homogeneity and to reduce the variability among replicates. Fine roots and visible plant residues were carefully removed prior to use. The soil contained $1.3\\%$ total C, $0.14\\%$ total N, and had a pH of 6.8 (Zhou et al., 2020b). Ten percent (w/w) of the soil dry weight was added as poly (3-hydroxybutyrate-co-3-hydroxyvalerate) $\\mathrm{\\langle[COCH_{2}C H(C H_{3})O]m}$ $\\mathrm{\\small{[COCH_{2}C H(C_{2}H_{5})O]_{n})}}$ (PHBV). PHBV was obtained in a pelletized form from the Tianan Biologic Materials Company Ltd., Beilun, Ningbo, China. PHBV represents one of the most widespread and best charac­ terized members of the PHA family (Bugnicourt et al., 2014). It is a $100\\%$ biobased thermoplastic linear aliphatic (co-)polyester obtained from the copolymerization of 3-hydroxybutanoic acid and 3-hydroxy­ pentanoic acid which are produced through the bacterial fermentation of sugars and lipids (Zinn et al., 2001). Most of the PHBV is composed of hydroxybutyrate, however, a small fraction of hydroxyvalerate is pre­ sent in its polymeric backbone (Rivera-Briso and Serrano-Aroca, 2018). This type and amount of highly crystalline plastic were chosen to simulate the localized disposal of bioplastics in agricultural soils (e.g., ploughing in of mulch film residues at the end of the field season) and was based on field investigations and a review of the literature (Fuller and Gautam, 2016; Qi et al., 2020a). We added very high amounts of microplastic to reflect soil hotspots with higher contamination levels $(1-20\\%)$ . \n\n# 2.2. Experimental design \n\nA mesocosm experiment with a completely randomized design and four replicates was set up in a climate-controlled room. For the PHBV addition treatment, $_{400\\mathrm{~g~}}$ soil and PHBV were mixed homogeneously and then put in a rhizobox ${10\\times10\\times4}$ cm; Qiangsheng Co., Ltd. Heibei, China). The control treatment contained soil $(400~\\mathrm{g})$ without PHBV, but with a comparable soil disturbance. The soil bulk density was main­ tained at $1.2\\ {\\mathrm{g}}\\ {\\mathrm{cm}}^{-3}$ for all rhizoboxes. Prior to use, the soil was preincubated under field-moist $(25\\%\\ \\mathrm{v/v})$ conditions in a greenhouse for one week to allow the soil to equilibrate. Before planting, wheat (Triti­ cum aestivum L.) seeds were sterilized in $10\\%$ $\\mathrm{H}_{2}\\mathrm{O}_{2}$ for $10\\ \\mathrm{min}$ , then rinsed with deionized water and germinated on wet filter paper. Five days after germination, seedlings were transplanted in all rhizoboxes (one seedling per rhizobox), and then moved to the climate-controlled chamber (day/night regime of $14{\\mathrm{~h~}}/24{\\mathrm{~}}^{\\circ}{\\mathrm{C}}$ and $10\\mathrm{~h~}/14^{\\mathrm{~\\circ~C~}}$ respec­ tively). The relative humidity in the chamber was kept at $40\\%$ and the plants received $800\\upmu\\mathrm{mol}\\mathrm{m}^{-2}s^{-1}$ photosynthetic active radiation (PAR) at canopy height (Zhou et al., 2020b). Plants were watered every three days and the soil moisture was maintained at a gravimetric water con­ tent of $25\\%$ throughout the experiment by weighing the rhizoboxes. \n\n# 2.3. Hotspot identification \n\nAt 24 days after transplanting, zymography was used to visualize the spatial distribution of three hydrolytic enzymes (Razavi et al., 2016). B-glucosidase, acid phosphatase, and leucine-aminopeptidase play major roles in cellulose, organic phosphate, and protein degradation (Lopez-Hernandez et al., 1993; Lammirato et al., 2010). They reflect key enzymes related to soil C, P and N cycle, respectively (German et al., 2011). Polyamide membrane ${\\mathrm{7}}0.45{\\upmu\\mathrm{m}}$ mesh size, Tao yuan, China) were saturated with 4-methylumbelliferyl (MUF) or 7-amido-4-methylcou­ marin (AMC) based substrate to visualize the specific enzymes. Each substrate was separately dissolved in $10\\mathrm{mM}$ MES and TRIZMA buffer for MUF and AMC, respectively. The saturated membranes were placed on soil surfaces and covered with aluminum foil to avoid evaporation and moisture changes during the incubation period (Hoang et al., 2020). After incubation for $^\\textrm{\\scriptsize1h}$ , the membranes were carefully peeled off the soil surface and any attached soil particles were gently removed with tweezers and a soft brush (Razavi et al., 2016). Enzyme detection se­ quences followed as: $\\upbeta$ -glucosidase, acid phosphatase, leucine-aminopeptidase activity, with $^\\textrm{\\scriptsize1h}$ interval after each zymog­ raphy. The gray scale values transferred to the enzyme activities was calibrated using membranes $(2\\times2~\\mathrm{cm})$ saturated with a range of con­ centrations of corresponding products, i.e. MUF and AMC (0, 0.01, 0.2, \n\n# 0.5, 1, 2, 5 mM). \n\nThe zymograms were transferred into a 16-bit gray scale by ImageJ with a correction for environmental variations and camera noise (Razavi et al., 2016). The calibration equation obtained for each enzyme was used to convert gray values of each zymography pixel into enzyme ac­ tivities (Hoang et al., 2020). Enzyme activities exceeding $25\\%$ of mean corresponding activity of the whole soil were defined as hotspots (Zhang et al., 2020). Specifically, soil with a high color intensities (shown here in dark red) represent microbial hotspots, while low intensities (shown here in dark blue) indicate (non-hotspot) bulk soil on the zymograms (Fig. 1; Hoang et al., 2020). Given the hotspots in the control and PHBV-treated soil were detected at a distance of $1.5{-}2~\\mathrm{mm}$ from the roots and microplastics, the hotspots in the control and PHBV-treated soil were identical to the rhizosphere and microplastisphere zones, respectively (Fig. 1). After collecting soil from hotspots and bulk soil, a total of 16 samples [2 treatments (without and with $\\mathbf{PHBV}\\times2$ micro­ sites from each treatment (hotspots and bulk soil) $\\times4$ replicates] were obtained. \n\n# 2.4. Plant and soil sampling \n\nAt 25 days after transplanting, the shoots were cut off at the base of the stem and the roots were collected separately. For precise localized sampling, soil particles were carefully collected using needles (tip 1.5 mm) directly from the hotspots (rhizosphere and microplastisphere) identified by zymography (Fig. 1). Bulk soil was collected in a similar way. Once collected, soil samples (hotspots and bulk soil) were sepa­ rated into two sub-samples. One sub-sample was stored at $-80~^{\\circ}\\mathrm{C}$ to analyze the bacterial community structure, while the other sub-sample was used to measure enzyme kinetics and the kinetics of substrateinduced growth respiration directly. After removal of the hotspot sam­ ples and bulk soil, the remaining soil in the rhizobox was mixed and then stored at $4^{\\circ}\\mathbf{C}$ to measure microbial biomass N, dissolved organic C and N. Shoots and roots were oven-dried ( $60^{\\circ}\\mathrm{C}$ , 5 days) and then weighed. \n\n![](images/a3a3a04fc32c877668787fbfff5b0af6f458199397fe2e2f0749244aede0b322.jpg) \nFig. 1. Zymograms and hotspots of $\\upbeta$ -glucosidase (BG), acid phosphatase (ACP) and leucine aminopeptidase (LAP) in untreated soil (Control) and soil to which the bioplastic poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) was added. The color intensity is proportional to the respective enzyme activity (nmol $\\mathrm{cm}^{-2}\\mathrm{h}^{-1},$ ). The zymograms are representative of 4 independent replicates. The corresponding area of hotspots relative to the total area of the rhizobox for each enzyme is shown in the right-hand panel. Values are means $(\\pm S\\mathbf{E})$ of four replicates. Different letters show significant differences between treatments $(p<0.05)$ . Here, 1, 2, 3 indicate rhizosphere, microplastisphere, and bulk soil. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) \n\nSoil microbial biomass N (MBN) was extracted with $\\mathrm{K_{2}S O_{4}}$ $32~\\mathrm{mL}$ , $0.05~\\mathrm{M})$ ), and calculated with a corresponding ${\\mathrm{K}}_{\\mathrm{EN}}$ factor of 0.45 ac­ cording to Wen et al. (2020). Briefly, the fresh soil was homogenized and $_{8\\mathrm{~g~}}$ sub-sample of the soil were extracted with $32\\mathrm{\\mL}0.05\\mathrm{\\M\\K_{2}S O_{4}}.$ . Another $_{8\\mathrm{~g~}}$ sub-sample of the soil was fumigated with chloroform for $24\\mathrm{h}$ and then extracted in the same way. Total C and N in extracts were measured on a $2100~\\mathrm{N/C}$ analyzer (Analytik Jena GmbH, Jena, Ger­ many). The non-fumigated extractions were used as a measure for dis­ solved organic C (DOC) and N (DON). \n\n# 2.5. Enzyme kinetics \n\nThe activity of the exoenzymes $\\upbeta$ -1,4-glucosidase (BG) (EC 2.2.1.21), leucine aminopeptidase (LAP) (EC 3.4.11.1), and acid phosphatase (ACP) (EC 3.1.3.2) were determined by the 4-methylumbelliferyl (MUF)-based and 7-amido-4-methylcoumarin (AMC)-based artificial substrates (Marx et al., 2001; Wen et al., 2019). Briefly, $_{0.5~g}$ soil was mixed with $50\\mathrm{mL}$ sterile water and then shaking for $30\\mathrm{min}$ . After $2\\mathrm{min}$ low-energy sonication $(40\\mathrm{~J~}s^{-1})$ by ultrasonic disaggregation, $50~\\upmu\\mathrm{l}$ of the soil suspension, $50\\upmu\\mathrm{l}$ of corresponding buffer (MES or TRIZMA) and $100\\upmu\\mathrm{l}$ of the corresponding substrates at concentrations of 2, 5, 10, 20, 50, 100 and $200\\upmu\\mathrm{mol}1^{-1}$ were pipetted into 96-well black microplates (Brand $\\textsuperscript{\\textregistered}$ plates pureGrade, Sigma-Aldrich, Germany). The Victor 1420-050 Multi label Counter (PerkinElmer, USA) was used to measure the fluorescence at an excitation wavelength of $355\\mathrm{nm}$ and an emission wavelength of $460\\mathrm{nm}$ . Enzyme activities were taken at four times (0, 30 min, $^\\textrm{\\scriptsize1h}$ and $2~\\mathrm{h}\\mathrm{\\prime}$ ), and was expressed as nmol ${\\bf g}^{-1}$ soil $\\ensuremath{\\mathbf{h}}^{-1}$ . \n\nTo calculate key parameters describing the enzyme kinetics, we fitted a Michaelis-Menten equation to the experimental data (Marx et al., 2001): \n\n$$\nV=\\frac{V_{\\mathrm{max}}\\times[S]}{K_{m}+[S]}\n$$ \n\nwhere $V$ is the enzymatically mediated rate of reaction, $V_{\\mathrm{max}}$ is the maximal rate of reaction, $K_{\\mathrm{m}}$ (Michaelis constant) is the substrate con­ centration at $\\%V_{\\mathrm{max}}$ and $s$ is substrate concentration. The substrate turnover time ( $\\cdot\\mathbf{\\nabla}T_{\\mathrm{t}})$ was calculated according to the following equation: $T_{\\mathrm{t}}$ (hours) $=(K_{\\mathrm{m}}+S)/V_{\\mathrm{max}},$ where S is the substrate concentration (200 $\\upmu\\mathrm{mol}\\mathrm{l}^{-1}\\big)$ . The catalytic efficiency of enzymes $\\left(K_{\\mathrm{a}}\\right)$ was calculated by the ratio of $V_{\\mathrm{max}}$ and $K_{\\mathrm{m}}$ (Hoang et al., 2020). The microbial metabolic limitation was quantified by calculating the vector lengths and angles of enzymatic activity for all data based on untransformed proportional activities (e.g. (BG): $(\\mathrm{BG}+\\mathrm{LAP})$ , (BG): $(\\mathbf{BG}+\\mathbf{ACP}).$ ) (Moorhead et al., 2016). \n\n# 2.6. Kinetics of substrate-induced growth respiration \n\nThe substrate-induced growth respiration (SIGR) approach was used to distinguish total and active biomass fractions, as well as microbial specific growth rate and lag-time before growth (Zhang et al., 2020; Zhou et al., 2020a). It should be noted that although C substrate addition is required for the SIGR approach, all kinetic parameters analyzed by SIGR represent the intrinsic features of dominating microbial pop­ ulations before substrate addition (Blagodatskaya et al., 2010). \n\nOne gram of fresh soil was amended with a mixture containing 10 $\\mathrm{mg}\\ \\mathbf{g}^{-1}$ glucose, $1.9\\mathrm{mg}\\mathrm{g}^{-1}$ $(\\mathrm{NH}_{4})_{2}S O_{4}.$ , $2.25\\mathrm{\\mg\\g^{-1}\\ K_{2}H P O_{4}};$ and 3.8 $\\ensuremath{\\mathbf{m}}\\ensuremath{\\mathbf{g}}\\ensuremath{\\mathrm{~\\boldmath~\\pmb{g}~}}^{-1}$ $\\mathrm{MgSO_{4}^{2}7H_{2}O}$ , and placed in a Rapid Automated Bacterial Impedance Technique bioanalyzer (RABIT; Microbiology International Ltd, Frederick, MD, USA), for measuring $\\mathsf{C O}_{2}$ production at room temperature $(22^{\\circ}\\mathrm{C})$ . Firstly, we pre-incubated 16 samples from hotspots and bulk soil with and without PHBV amendment for 2 days at $45\\%$ water holding capacity (WHC) to minimize the effect of sampling disturbance. To measure substrate-induced respiration, a mixture of glucose and nutrients was added and the samples were further incubated for 5 day at $75\\%$ WHC (Blagodatskaya et al., 2010; Zhou et al., 2020a). The evolving $\\mathsf{C O}_{2}$ was trapped in a KOH solution where the impedance of the solution was continuously measured. The average value of $\\mathsf{C O}_{2}$ emission during the $^{3\\mathrm{h}}$ before and after adding substrates were taken as basal respiration (BR), and substrate-induced growth respiration (SIGR). \n\nMicrobial respiration in glucose amended soil was used to calculate the following kinetic parameters: the microbial maximal specific growth rate $(\\mu)$ , the growing microbial biomass (GMB) that capable for imme­ diate growth on glucose, the total microbial biomass (TMB) responding by respiration to glucose addition, and the lag period $(T_{\\mathrm{lag}})$ . \n\nMicrobial maximal specific growth rate $\\mu$ was used as an intrinsic property of the microbial population to estimate the prevailing growth strategy of the microbial community. According to Blagodatskaya et al. (2010), higher $\\mu$ reflects relative domination or shift towards fast-growing $r$ -strategists, while lower $\\mu$ values show relative domina­ tion or shift towards slow-growing $K$ -strategists. \n\nConsidering that PHBV is partially soluble in chloroform at $30~^{\\circ}\\mathrm{C}$ (Jacquel et al., 2007), the microbial biomass we measured by chloroform-fumigation extraction might contain a minor contribution from PHBV degradation during fumigation. Therefore, microbial biomass C (MBC) was determined using the initial rate of substrate-induced respiration after substrate addition according to the equation of Blagodatskaya et al. (2010): \n\n$$\n\\beth(\\upmu\\mathrm{g}\\mathrm{~\\underline{{{g}}}^{-1}\\ s o i l)=(\\upmu l\\ C O_{2}\\underline{{{g}}}^{-1}\\ s o i l\\ h^{-1})\\times40.04}\n$$ \n\n# 2.7. Soil bacterial community structure \n\n# 2.7.1. Soil genomic DNA extraction, PCR amplification and illumina sequencing \n\nTotal DNA was extracted from $_{0.5g}$ soil for each treatment using the Mo Bio PowerSoil DNA isolation kit (Qiagen Inc., Carlsbad, CA, USA) according to the manufacturer’s instructions. After extraction, the quality and concentration of DNA were tested using a NanoDrop ND 200 spectrophotometer (Thermo Scientific, USA). According to the concen­ tration, all DNA samples were diluted to $1~\\mathrm{{ng}}~\\upmu\\mathrm{{l}}^{-1}$ before PCR amplifi­ cation. We note that the DNA extracted from control hotspots leaked out during shipping for sequencing analysis, causing the DNA concentration to drop under the detection threshold. Therefore, the samples from this treatment could not be determined. \n\nThe V4 and V5 variable region of the bacterial 16S rRNA gene were amplified using the primers 515F ( $5^{\\prime}$ -CCATCTCATCCCTGCGTGTCTCC­ GAC- $3^{\\prime}$ ) and 907R $5^{\\prime}$ -CCTATCCCCTGTGTGCCTTGGCAGTC-3′). The polymerase chain reaction (PCR) amplification mixture was prepared with $1~\\upmu\\mathrm{l}$ purified DNA template $(10~\\mathrm{ng})$ , $5\\ \\upmu\\mathrm{l}\\ 10\\times\\mathrm{PCR}$ buffer, 2.25 mmol $1^{-1}~\\mathrm{MgCl_{2}}$ , 0.8 mmol $1^{-1}$ deoxyribonucleotide triphosphate (dNTP), $0.5~\\upmu\\mathrm{mol}~\\mathrm{l}^{-1}$ of each primer, $2.5\\mathrm{~U~}$ Taq DNA polymerase, and sterile filtered ultraclean water to a final volume of $50~\\upmu\\mathrm{l}$ . All the re­ actions were carried out in a PTC-200 thermal cycler (MJ Research Co., NY, USA). The PCR cycles included a $4\\mathrm{min}$ initial denaturation at $94^{\\circ}\\mathrm{C},$ followed by 30 cycles of denaturation at $94^{\\circ}\\mathrm{C}$ for $1~\\mathrm{min}$ , annealing at $53^{\\circ}\\mathrm{C}$ for $30~\\mathsf{s}_{:}$ , extension at $72^{\\circ}\\mathrm{C}$ for $1\\mathrm{min}$ , and a 5-min final elongation step at $72^{\\circ}\\mathrm{C}$ . The PCR products were quality-screened and purified by Qiagen Gel Extraction kit (Qiagen, Hilden, Germany). Next, all the amplicons were sequenced on the Illumina Miseq PE250 platform at Novogene Biotech Co., Ltd., Beijing, China. All the sequences have been submitted to NCBI SRA data repository under the Accession No. PRJNA648785. \n\n# 2.7.2. 16S gene sequences processing \n\nBriefly, de-noising and chimera analysis conducted with the Ampli­ conNoise and UCHIME algorithms were used to reduce sequence errors (Vargas-Gastelum et al., 2015). Furthermore, quality trimming was conducted to remove unwanted sequences shorter than 200 bp and reads containing ambiguous bases and with homopolymers longer than eight bases. The remaining sequences were used to identify the unique se­ quences by aligning with the SILVA reference database (v.128) (Quast et al., 2013). Within unique sequences, the UCHIME tool was applied to remove chimeras. Then, “Chloroplast”, “Mitochondria”, or “unknown” were identified and removed from the dataset. Subsequently, after calculating the pairwise distance and generating the distance matrix, a $97\\%$ identity threshold was used to cluster sequences into Operational Taxonomic Units (OTUs) according to the UCLUST algorithm (Edgar et al., 2011). The most abundant sequence in each OTU was picked as the representative sequence. For each representative sequence, the SILVA reference database (v.128) was applied to annotate the taxo­ nomic information using RDP classifier algorithm (Wang et al., 2007). \n\n# 2.8. Statistical analysis \n\nThe experiment was carried out with four replicates for each parameter. All values presented in the figures are means $\\pm$ standard errors of the means $(\\mathrm{mean}\\pm\\mathrm{SE})$ ). The enzyme kinetic parameters $\\boldsymbol{\\mathrm{{V}}_{\\mathrm{{max}}}}$ and $\\ensuremath{K_{\\mathrm{m}}})$ ) were fitted via the non-linear regression routine of SigmaPlot (version 12.5; Systat Software, Inc., San Jose, CA, USA). The DNA data were rarefied to an equal depth within the minimum observed sample size across all the samples. The following six parameters, namely Rich­ ness, Pielou, Chao1, Shannon, Simpson, and abundance-based coverage (ACE), were calculated to describe the alpha diversity of the soil bac­ terial community based on OTU abundance. The calculation was con­ ducted in QIIME 2 and the illustration was performed by R software (Ver. 3.2) using the packages “ggplot2” and “metacoder”. \n\nPrior to the analysis of variance (ANOVA), the data were tested for normality (Shapiro-Wilk, $p>0.05\\$ and homogeneity of variance (Lev­ ene-test, $p>0.05\\$ ). Any dataset that was not normally distributed was root square or $\\log_{10}$ -transformed to conform with the assumption of normality before further statistical analysis. For alpha diversity indices that did not conform to the assumption of normality, the nonparametric Kruskal-Wallis H-Test was applied to determine whether there were significant differences in alpha diversity among different treatments. \n\n# 3. Results \n\n# 3.1. Effect of PHBV on plant and soil properties \n\nThe mean plant biomass was $0.24\\ g\\ \\mathrm{pot}^{-1}$ without microplastics addition (Table 1). However, PHBV addition ultimately resulted in plant death after 25 days. PHBV addition greatly increased the soil microbial biomass and dissolved organic C content $(p<0.05$ , Table 1). MBC and DOC were 12 and 54 times higher in the PHBV-treated than in the control soil, respectively. Additionally, MBN was $45\\%$ higher in the PHBV-treatment in comparison to the control, whereas DON decreased by $66\\%$ compared to the control soil. \n\nTable 1 Plant biomass, microbial biomass carbon (MBC) and nitrogen (MBN), and dis­ solved organic carbon (DOC) and nitrogen (DON) in untreated soil (Control) and soil to which the bioplastic poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) was added. Values are means $(\\pm S\\mathbf{E})$ of four replicates. Letters show significant differences between treatments $(p<0.05)$ . MBC was calculated by substrate-induced growth respiration (according to Eq. (2)), MBN was measured by chloroform-fumigation extraction, DOC and DON were determined by nonfumigated extractions. \n\n\n
TreatmentPlant biomass (g DM pot-1)MBC (mg kg-1)MBN (mg kg-1)DOC (mg kg-1)DON (mg kg-1)
Control0.24 ± 0.02131 ± 23b20.6 ± 3.4b163 ± 20b93.9 ± 5.5a
PHBVn.d.1723 ± 625a30.4 ± 5.6a9049 ± 889a32.3 ± 5.2b
\n\nn.d.: no data due to plant death. \n\n# 3.2. Effect of PHBV on soil enzyme activities \n\nThe maximum potential enzyme activities $(V_{\\mathrm{max}})$ were $60\\%$ and 5- folds higher for $\\upbeta$ -glucosidase and leucine aminopeptidase in the microplastisphere than in the rhizosphere, respectively $(p<0.05$ , Fig. 2a and b). Similarly, the substrate affinities $(K_{m})$ of $\\upbeta$ -glucosidase and leucine aminopeptidase in the microplastisphere were 1.5–2 times higher in the rhizosphere, respectively $(p<0.05$ , Fig. 2b, d). The $V_{\\mathrm{max}}$ and $K_{m}$ of $\\upbeta$ -glucosidase and leucine aminopeptidase in microplasti­ sphere were significantly higher compared to those in the PHBV-treated bulk soil $(p<0.05$ , Fig. 2). In the bulk soil, however, none of the tested enzymes were affected by PHBV addition $(p>0.05$ , Fig. 2). Further­ more, the $V_{\\mathrm{max}}$ of $\\upbeta$ -glucosidase was positively correlated with active microbial biomass $(\\mathrm{R}^{2}=0.7,p<0.05$ , Fig. S4). The catalytic efficiency $(V_{\\mathrm{max}}/K_{m})$ of leucine aminopeptidase was higher in the microplasti­ sphere than in the rhizosphere $(p<0.05$ , Fig. S2c), and the turnover time was approximately 5 times shorter in the microplastisphere than in the rhizosphere soil (Fig. S2d). However, no changes in the catalytic efficiency and turnover time for all the enzymes were found in the bulk soil between the PHBV-treated and control soil $(p>0.05$ Fig. S2). Further, the vector angle was lowest in the microplastisphere compared to other soil samples $(p<0.05$ , Fig. S7d), indicating that microbial metabolisms may be N limited. \n\n![](images/c976c5c91abe05158cf3404ee95302ec2b259cf90ae1257d25d643dc0efd42f0.jpg) \nFig. 2. Potential enzyme activities $(V_{\\mathrm{max}})$ and substrate affinities $(K_{\\mathrm{m}})$ of $\\upbeta$ -glucosidase (BG), leucine aminopeptidase (LAP), and acid phosphatase (ACP) in bulk and hotspots in untreated soil (Control) and soil to which the bioplastic poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) was added. Values are means $(\\pm S\\mathbf{E})$ of four replicates. Different letters show significant differences between treatments $(p<0.05)$ . \n\n# 3.3. Effect of PHBV on soil microbial growth rate \n\nDifferent microbial growth patterns in response to substrate addition were observed among hotspots (microplastisphere and rhizosphere) and the bulk soil with and without PHBV addition (Fig. S3). The basal respiration (BR, $45{\\upmu}\\mathrm{g}\\mathrm{~C~g}^{-1}\\mathrm{~h}^{-1})$ and substrate-induced growth respi­ ration (SIGR, $58~{\\upmu\\mathrm{g}}\\subset{\\up g}^{-1}~{\\up h}^{-1})$ in the microplastisphere were 10 times and 12 times higher relative to the rhizosphere soil, respectively (Fig. 3a and b). However, the BR and SIGR in the bulk soil were not affected by PHBV addition compared to the control. \n\nSoil respiration showed a clear response to PHBV addition both in the hotspots and in bulk soil (Fig. S3). PHBV addition decreased the maximum specific growth rate $\\mathbf{\\mu}(\\mu)$ by $22\\%$ in the microplastisphere compared to the bulk soil $(p<0.05$ ; Fig. 3c), whereas there was no difference in $\\mu$ between the microplastisphere and the PHBV-treated bulk soil $(p>0.05)$ . Despite a slower specific growth rate, a 6-fold in­ crease in the fraction of active microbial biomass, and a four times shorter lag period was observed in the microplastisphere vs. rhizosphere soil (Fig. 3d,e,f). \n\n# 3.4. Effect of PHBV on soil bacterial community composition and diversity \n\nThe dominant bacteria phyla were Actinobacteria, Proteobacteria, Acidobacteria, Firmicutes, Bacteroidetes, Chloroflexi, Thaumarchaeota, and Gemmatimonadetes in all treatment soils (Fig. 4A), which together encompassed ca. $96\\mathrm{-}98\\%$ of the bacterial reads. Although the dominant phyla in all soils were consistent, changes in the relative abundances of the dominant taxa were observed across the treatments. There was a higher abundance of Proteobacteria and Acidobacteria and a lower abundance of Firmicutes in soils with PHBV addition comparing with control treatment $(p<0.05$ , Fig. 4A). In the family level, the fraction of these 20 dominant families with highest relative abundance decreased after PHBV addition (Fig. 4B). Specifically, the addition of PHBV induced the decrease of Planococcaceae, Xanthomonadaceae, Bacillaceae and the increase of Chitinophagaceae, Comamonadaceae and Oxalo­ bacteraceae (Fig. 4B). The detailed family level changes of bulk and hotspot soil bacterial community induced by PHBV addition were also given in Fig. 5C. Of the 3800 OTUs detected across all samples, the major numbers of OTUs $(n=3622)$ ) were shared by control-bulk, PHBV-bulk, and PHBV-hotspots soils, while 54 OTUs were unique to PHBV-hotspots soil and 16 OTUs were unique to the PHBV-bulk soil (Fig. 5A). \n\nThe mean values for ACE, Chao1, Richness, and Shannon indices in the PHBV-treated bulk soil increased by $10\\%$ , $11\\%$ , $16\\%$ , and $18\\%$ relative to the control soil, respectively (Fig. S5), while there were no differences between the microplastisphere and bulk soil after PHBV addition $(p>0.05)$ . \n\n# 4. Discussion \n\n# 4.1. Effect of PHBV on plant growth \n\nIntact PHBV and its decomposition products are thought to be of very low cytotoxicity (Napathorn, 2014). In all the rhizoboxes amended with PHBV, however, all the plants eventually died during the 4-week experiment. This is consistent with previous reports showing that degradation of conventional and bio-based microplastics might nega­ tively affect plant growth when present in high quantities (Qi et al., 2018, 2020b; Zang et al., 2020). Given that bioplastic polymers are solely composed of C, O and H, it is likely that PHBV addition to soil induced microbial immobilization of essential nutrients (e.g., N, P) leading to increased plant stress (Volova et al., 2017; Boots et al., 2019). Such an N immobilization was further confirmed by the decreased DON but increased MBN in PHBV-added soil compared to the unamended control treatment (Table 1). This is consistent with Sander (2019) who found that microorganisms on the surface of microplastics need to ac­ quire N from the surrounding soil to fuel growth. It also suggests that PHBV may have stimulated opportunistic plant pathogens (Matavulj et al., 1992), however, more work is required to confirm this. An alternative explanation might be that PHBV induced phytotoxicity due to acidification of the soil because of the release of high quantities of 3-hydroxybutyric acid during PHBV degradation. However, this would normally affect root growth rather than shoot growth (Lucas et al., 2008). Further, based on the degradation of other biopolymers (e.g. cellulose, proteins), it is unlikely that an accumulation of the monomer will occur due to rapid microbial consumption (Jan et al., 2009). This is quite likely as it is a monomer which is naturally present as a microbial storage compound (Mason-Jones et al., 2019). However, it is possible that undisclosed additives or contaminants in the polymer might also have induced phytotoxicity (Zimmermann et al., 2019). Lastly, we cannot disregard other general changes in soil properties and microbial communities following PHBV addition which may also have inhibited plant growth, contributing to plant death (Saarma et al., 2003; Wen et al., 2020). We conclude, that contrary to expectation, commercially sourced PHBV was deleterious to plant growth, at least under higher contents of PHBV in the short term, as indicated by the lower seed germination over 7-days germination (Fig. S6). Further experiments are therefore needed to determine the mechanistic basis of this response. \n\n![](images/d067317003264e844a274a03a1772c0aaa92201d95ee3cdf2d48d7bcf37acb1f.jpg) \nFig. 3. Basal respiration (BR), substrate-induced growth respiration (SIGR), specific growth rate $\\mathbf{\\Pi}(\\mu)$ , total microbial biomass (TMB), the fraction of growing microbial biomass to total microbial biomass (GMB/TMB), and their lag time in bulk and hotspots in untreated soil (Control) and soil to which the bioplastic poly(3-hydroxybutyrate-co-3- hydroxyvalerate) (PHBV) was added. Values are means $(\\pm S\\mathbf{E})$ of four replicates. Letters show sig­ nificant differences between treatments $(p<0.05)$ . \n\n![](images/251a6f1aebf040aca2b5085c3a34657303f5629bc2f021030935f47b7fd6bb38.jpg) \nFig. 4. Stacked bar chart of the top 10 bacterial phyla with the largest mean relative abundance in untreated soil (Control-bulk), and bulk (PHBV-bulk) and hotspots (PHBV-hotspots) soils with the bioplastic poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) addition (A). Stacked bar plot of the 20 families with largest mean relative abundance in all soil samples (B). \n\n# 4.2. Effect of PHBV on soil microbial and enzymatic functional traits \n\nSoil enzyme production is sensitive to both energy and nutrient availability (Allison et al., 2011). This notion was supported in our study where the input of bioavailable C (i.e. degradation products of PHBV) increased enzyme activities in hotspots by up to 2 times compared to the bulk soil. This increase in microbial activity is unsurprising given that poly-3-hydroxybutyrate is a common storage compound produced by a wide range of taxonomically different groups of microorganisms, particularly in response to N deficiency and cold stress (Obruca et al., 2016). Consequently, the ability to use PHBV-C is expected to be a widespread trait within the microbial community. For C- and N-degrading enzymes, the activity difference between hotspots and the bulk soil was 2–10 times larger when PHBV was added (Fig. 2a, c), demonstrating that bioplastic incorporation into the soil directly in­ fluences C and N cycling. The higher $V_{\\mathrm{max}}$ of $\\upbeta$ -glucosidase in the microplastisphere versus rhizosphere soil can be attributed to the faster growing biomass after PHBV addition (Fig. 3e). This is supported by the positive correlation between our measurement of the active microbial biomass and the $V_{\\mathrm{max}}$ of $\\upbeta$ -glucosidase $(\\mathrm{R}^{2}=0.7;$ Fig. S4). The increase in $\\upbeta$ -glucosidase also suggests that PHBV is stimulating the breakdown of other common soil polymers (i.e. cellulose). Further, PHBV could be broken down by depolymerases releasing hydroxybutyric acid mono­ mers which fuel the production of energetically expensive exoenzymes (i.e. leucine aminopeptidase; Fig. 2c) capable of degrading SOM to ac­ quire N for growth (i.e. positive priming; Zang et al., 2016; Zhou et al., 2020a, b). This was supported by a higher BR and SIGR in the micro­ plastisphere relative to the bulk soil (Fig. 3a and b), as well as the wider ratio of DOC and DON in the PHBV-treated soil (294) than in the control soil (1.77) (Table 1). In accordance with previous studies, N limitation also induced an increase in the catalytic properties $\\left(K_{\\mathrm{a}}\\right)$ of leucine aminopeptidase (Song et al., 2020). In line with this, the much shorter turnover time of substrates and higher $K_{\\mathrm{a}}$ of leucine aminopeptidase in the microplastisphere was observed compared to the rhizosphere (Figs. S2c and d), which suggests that the community was more limited by N than P in the microplastisphere. This could be supported by lower proportional activity of C- to N-cycling enzymes but higher proportional activity of C- to P-cycling enzymes in the microplastisphere versus the rhizosphere (Fig. S7). The lower vector angle in the microplastisphere further confirmed the microbial metabolisms were likely limited by soil N. We therefore hypothesize that due to N limitation the microbial community either (i) changed the intrinsic properties of their hydrolytic enzymes to adapt to the presence of the C-rich bioplastic, and/or (ii) that PHBV induced a shift in the soil microbial community and thus the types of enzymes being produced (Kujur and Patel, 2013). Overall, we conclude that N limitation is connected to microbial N immobilization due to stimulated microbial growth after C supply from PHBV. The C input stemming from the catabolism of PHBV will increase microbial biomass and intensify the N limitation. This was supported by the increased MBC and enzyme activities (especially N related), as well as the shift in enzymatic stoichiometric ratio and bacterial community. \n\n![](images/f79538e996d9ec8c94afa7e86032678c39e19ff6a829637d7307a10c4229505d.jpg) \nFig. 5. Venn diagram shows shared number of OTUs by untreated soil (Control-bulk), and bulk (PHBV-bulk) and hotspots (PHBV-hotspots) soils with the bioplastic poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) addition (A). The taxonomical information for each node was given in an individual enlarged heatmap (B). Metacoder heatmap to family level across different treatment. Each node from the center (Kingdom) to outward (Family) represents different taxonomical levels (C). The map is weighted and colored-coded based on read abundance. \n\nThis contrasts with C hotpots in the rhizosphere, where the supply of C is probably less and where N is also lost from root epidermal cells in the form of amino acids providing a more balanced nutrient supply to the microbial community (Jones et al., 2009). \n\nHere we speculate that PHBV breakdown was initially limited by the availability of polyhydroxybutyrate depolymerase (Jendrossek et al., 1993). The abundance and level of expression of this enzyme in soil remains unknown, however, an NCBI search revealed its presence in a wide range of microbial taxa. Although PHB depolymerase may be internally targeted (i.e. to break down internal storage C), there is also an evidence that it can be externally targeted (i.e. be an exoenzyme; Jendrossek and Handrick, 2002), probably to degrade microbial nec­ romass (Handrick et al., 2004). Our data support the view that PHBV can be used as a sole C substrate by the bacterial community when supplied exogenously (Martinez-Tobon et al., 2018). However, we also observed a significant decrease $(22\\%)$ in microbial specific growth rate $\\mu$ in the microplastisphere compared to the rhizosphere, indicating the potential dominance of $K$ -strategy microorganisms. $K$ -strategists typically store more C in their cells and consume it slower (Nguyen and Guckert, 2001), lowering respiration rates. We therefore hypothesize that PHBV de­ graders break down PHBV exogenously into monomeric units which can then be subsequently transported into the cell where re-polymerization into PHB occurs (Shen et al., 2015). Consequently, microbial community structure in the microplastisphere shifted toward species with a lower affinity to oligosaccharides and peptides indicated by a higher $K_{\\mathrm{m}}$ of $\\upbeta$ -glucosidase and leucine aminopeptidase. \n\n# 4.3. Effect of PHBV on soil bacterial community structure \n\nPHBV addition was associated with an increase in the relative abundance of Acidobacteria, Proteobacteria and Chloroflexi, and a decrease in the relative abundance of Firmicutes, The latter have previ­ ously been described as fast-growing copiotrophs that thrive in envi­ ronments of high C availability (Cleveland et al., 2007; Jenkins et al., 2010). In contrast, Acidobacteria and Chloroflexi tend to dominate in oligotrophic environments where N availability is low (Ho et al., 2017). As mentioned, the release of high quantities of 3-hydroxybutyric acid during PHBV degradation may have also reduced the pH, thus favoring the growth of Acidobacteria. Nitrospirae are nitrite-oxidizing bacteria that are ubiquitous in terrestrial environments and that play a major role in biological N cycling and nitrification in agricultural soils (Xia et al., 2011). The higher abundance of Nitrospirae after PHBV addition indi­ cated a change in N cycling (Zecchin et al., 2018), which was attributed to greater nutrient limitation in the microplastisphere than in the bulk soil (as indicated by $V_{\\mathrm{max}}$ ratio of C-to-N cycling enzymes; 5.1 vs. 8.6) (Table S1). The relative proportion of Bacteroidetes also increased in the PHBV treatments. These largely copiotrophic organisms are widely distributed in soils, and are considered to be specialized in degrading complex organic matter (Huang et al., 2019). Thus, DOM pools increased in the PHBV-treated soil compared with bulk soil due to the release of monomeric compounds from PHBV degradation (Table 1). Although only bacterial communities were investigated in this study, it is likely that fungi and mesofauna populations are also greatly affected by PHBV addition and involved in its degradation. Further studies are required to gain a better insight into the complex interactions between these groups. Overall, our results highlight the potential of PHBV to trigger metabolic changes in soil microorganisms (Fig. 6), and thus potentially impact their functional role in soil (Huang et al., 2019). In addition to the microplastisphere, PHBV addition also changed the mi­ crobial community in the bulk soil, suggesting that these changes are not only confined to hotspots in the soil. \n\n![](images/dcb1cbcc042a9e5fdc2b53645ba014d5e1fbd8eeedfaea8926cd7749e81329c5.jpg) \nFig. 6. Conceptual diagram showing changes of microbial activities and functions in the hotspots as affected by poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) addition. Vertical and horizontal red arrows indicate either an increase or no change of microbial exoenzyme kinetics and functions in the hotspots compared to the bulk soil, respectively. The red and orange gradient between the panels indicates the decreasing trend in enzyme activity $\\mathrm{(V_{max})}$ and substrate affinity $\\mathrm{(K_{m})}$ , respectively between the microplastisphere and the rhizosphere. The blue gradient indicates the increasing trend in microbial specific growth rate $(\\mu)$ . (For inter­ pretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) \n\n# 5. Conclusion \n\nMicrobial activity in agricultural soil is typically C-limited, such that even small C inputs can induce metabolic changes in the soil microbial community. Here we clearly showed that PHBV addition increased mi­ crobial activity, growth, and exoenzyme activity. This most likely leads to the enhanced mineralization of native SOM by co-metabolism, i.e. microorganisms degrade SOM by using degradable polymers as an en­ ergy source. Remarkably, greater enzyme activity and microbial biomass, and lower affinity for the substrate were observed in the microplastisphere compared to the rhizosphere, indicating a stronger and faster C and nutrient turnover with PHBV addition in hotspots. Taken together, the unique environment may benefit microbial survival in PHBV-treated soil compared with the rhizosphere, possibly altering the soil ecological functions and biogeochemical processes, which may result in a stimulation of soil C and nutrients cycling. Although bio­ plastics have been heralded as a solution to petroleum-based plastics, our research indicates that it is also important to consider the potential drawbacks of bioplastics, e.g., for plant growth and health. This is exemplified in the use of plastic microbeads in cosmetics and plastic mulch films in agriculture where the negative environmental conse­ quences were only realized decades after their introduction (Sintim and Flurt, 2017; Qi et al., 2020b). Our research was designed to understand the short-term impact of a localized PHBV hotspot in soil. It is clear, however, that longer-term field-scale studies are also required. In-field testing of biodegradation of PHBV under different scenarios (e.g., soil types, agricultural practice, climate changes) as well as using a realistic mixture of polymers over longer periods is therefore required, with particular attention to plant-soil-microbial interactions. \n\n# Declaration of competing interest \n\nThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \n\n# Acknowledgements \n\nThis work was supported by the China Agriculture Research System (CARS07-B-5) and the UKRI Global Challenges Research Fund (GCRF) project awarded to Bangor University (NE/V005871/1). We also would like to thank the UK-China Virtual Joint Center for Agricultural Nitrogen (CINAg, BB/N013468/1), which is jointly supported by the Newton Fund, via UK Biotechnology and Biological Sciences Research Council and Natural Environment Research Council, and the Chinese Ministry of Science and Technology. Jie Zhou would like to thank the support from the China Scholarship Council (CSC). Heng Gui would like to thank the National Natural Science Foundation of China (NSFC Grant 32001296) and Yunnan Fundamental Research Projects (Grant No. 2019FB063). The authors would like to thank Karin Schmidt for her laboratory assistance. The authors also thank the editor and two anonymous re­ viewers for their insightful comments. \n\n# Appendix A. Supplementary data \n\nSupplementary data to this article can be found online at https://doi. org/10.1016/j.soilbio.2021.108211. \n\n# References \n\nAllison, S.D., Weintraub, M.N., Gartner, T.B., Waldrop, M.P., 2011. Evolutionary economic principles as regulators of soil enzyme production and ecosystem function. In: Shukla, G., Varma, A. (Eds.), Soil Enzymology. Springer, Berlin, pp. 229–244. \n\nBarnard, R.L., Osborne, C.A., Firestone, M.K., 2013. Responses of soil bacterial and fungal communities to extreme desiccation and rewetting. The ISME Journal 7, 2229–2241. \nBlagodatskaya, E., Blagodatsky, S., Dorodnikov, M., Kuzyakov, Y., 2010. Elevated atmospheric $\\mathrm{CO}_{2}$ increases microbial growth rates in soil: results of three $\\mathrm{CO}_{2}$ enrichment experiments. Global Change Biology 16, 836–848. \nBoots, B., Russell, C.W., Green, D.S., 2019. Effects of microplastics in soil ecosystems: above and below ground. Environmental Science and Technology 53, 11496–11506. \nBugnicourt, E., Cinelli, P., Lazzeri, A., Alvarez, V., 2014. Polyhydroxyalkanoate (PHA): review of synthesis, characteristics, processing and potential applications in packaging. Express Polymer Letters 8, 791–808. \nCleveland, C.C., Nemergut, D.R., Schmidt, S.K., Townsend, A.R., 2007. Increases in soil respiration following labile carbon additions linked to rapid shifts in soil microbial community composition. Biogeochemistry 82, 229–240. \nde Souza Machado, A.A., Lau, C.W., Kloas, W., Bergmann, J., Bachelier, J.B., Faltin, E., Becker, R., G¨orlich, A.S., Rillig, M.C., 2019. Microplastics can change soil properties and affect plant performance. Environmental Science and Technology 53, 6044–6052. \nDuis, K., Coors, A., 2016. Microplastics in the aquatic and terrestrial environment: sources (with a specific focus on personal care products), fate and effects. Environmental Sciences Europe 28, 2–8. \nEdgar, R.C., Haas, B.J., Clemente, J.C., Quince, C., Knight, R., 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200. \nFei, Y., Huang, S., Zhang, H., Tong, Y., Wen, D., Xia, X., Wang, H., Luo, Y., Barcel´o, D., 2020. Response of soil enzyme activities and bacterial communities to the accumulation of microplastics in an acid cropped soil. The Science of the Total Environment 707, 135634. \nFuller, S., Gautam, A., 2016. Procedure for measuring microplastics using pressurized fluid extraction. Environmental Science and Technology 50, 5774–5780. \nGarrison, T.F., Murawski, A., Quirino, R.L., 2016. Bio-based polymers with potential for biodegradability. Polymers 8, 262. \nGerman, D., Weintraub, M., Grandy, A., Lauber, C., Rinkes, Z., Allison, S., 2011. Optimization of hydrolytic and oxidative enzyme methods for ecosystem studies. Soil Biology and Biochemistry 43, 1387–1397. \nGross, R.A., Kalra, B., 2002. Biodegradable polymers for the environment. Science 297, 803–807. \nHaider, T.P., Vo¨lker, C., Kramm, J., Landfester, K., Wurm, F.R., 2019. Plastics of the Future? The impact of biodegradable polymers on the environment and on society. Angewandte Chemie 58, 50–62. \nHandrick, R., Reinhardt, S., Kimmig, P., Jendrossek, D., 2004. The “intracellular” poly(3- hydroxybutyrate) (PHB) depolymerase of Rhodospirillum rubrum is a periplasmlocated protein with specificity for native PHB and with structural similarity to extracellular PHB depolymerases. Journal of Bacteriology 186, 7243–7253. \nHo, A., Di Lonardo, D.P., Bodelier, P.L.E, 2017. Revisiting life strategy concepts in environmental microbial ecology. FEMS Microbiology Ecology 93, fix006. \nHoang, D.T., Maranguit, D., Kuzyakov, Y., Razavi, B.S., 2020. Accelerated microbial activity, turnover and efficiency in the drilosphere is depth dependent. Soil Biology and Biochemistry 147, 107852. \nHuang, ${\\mathrm{Y}}_{\\cdot,\\cdot}$ Zhao, $\\mathrm{Y.,}$ Wang, J., Zhang, M., Jia, W., Qin, X., 2019. LDPE microplastics films alter microbial community composition and enzymatic activities in soil. Environmental Pollution 254, 112983. \nJacquel, N., Lo, C.W., Wu, H.S., Wei, Y.H., Wang, S.S., 2007. Solubility of polyhydroxyalkanoates by experiment and thermodynamic correlations. AIChE Journal 53, 2704–2714. \nJambeck, J.R., Geyer, R., Wilcox, C., Siegler, T.R., Perryman, M., Andrady, A., Narayan, R., Law, K.L., 2015. Plastic waste inputs from land into the ocean. Science 347, 768–771. \nJan, M.T., Roberts, P., Tonheim, S.K., Jones, D.L., 2009. Protein breakdown represents a major bottleneck in nitrogen cycling in grassland soils. Soil Biology and Biochemistry 41, 2272–2282. \nJendrossek, D., Handrick, R., 2002. Microbial degradation of polyhydroxyalkanoates. Annual Review of Microbiology 56, 403–432. \nJendrossek, D., Knoke, I., Habibian, R.B., Steinbüchel, A., Schlegel, H.G., 1993. Degradation of poly(3-hydroxybutyrate), PHB, by bacteria and purification of a novel PHB depolymerase from Comamonas sp. Journal of Environmental Polymer Degradation 1, 53–63. \nJenkins, S.N., Rushton, S.P., Lanyon, C.V., Whiteley, A.S., Waite, I.S., Brookes, P.C., Kemmitt, S., Evershed, R.P., O’Donnell, A.G., 2010. Taxon-specific responses of soil bacteria to the addition of low level C inputs. Soil Biology and Biochemistry 42, 1624–163. \nJiang, Y., Chen, Y., Zheng, X., 2009. Efficient polyhydroxyalkanoates production from a waste-activated sludge alkaline fermentation liquid by activated sludge submitted to the aerobic feeding and discharge process. Environmental Science and Technology 43, 7734–7741. \nJones, D.L., Nguyen, C., Finlay, R.D., 2009. Carbon flow in the rhizosphere: carbon trading at the soil-root interface. Plant and Soil 32, 5–33. \nKujur, M., Patel, A.K., 2013. Kinetics of soil enzyme activities under different ecosystems: an index of soil quality. Chilean Journal of Agricultural Research 74, 96–104. \nKuzyakov, Y., 2010. Priming effects: interactions between living and dead organic matter. Soil Biology and Biochemistry 42, 1363–1371. \nKuzyakov, Y., Blagodatskaya, E., 2015. Microbial hotspots and hot moments in soil: concept & review. Soil Biology and Biochemistry 83, 184–199. \nLammirato, C., Miltner, A., Wick, L.Y., Ka¨stner, M., 2010. Hydrolysis of cellobiose by β-glucosidase in the presence of soil minerals - interactions at solid - liquid interfaces and effects on enzyme activity levels. Soil Biology and Biochemistry 42, 2203–2210. \nLiu, S., Razavi, B.S., Su, X., Maharjan, M., Zarebanadkouki, M., Blagodatskaya, E., Kuzyakov, Y., 2017. Spatio-temporal patterns of enzyme activities after manure application reflect mechanisms of niche differentiation between plants and microorganisms. Soil Biology and Biochemistry 112, 100–109. \nLucas, N., Bienaime, C., Belloy, C., Queneudec, M., Silvestre, F., Nava-Saucedo, J., 2008. Polymer biodegradation: mechanisms and estimation techniques. Chemosphere 73, 429–442. \nLopez-Hernandez, D., Lavelle, P., Nin˜o, M., 1993. Phosphorus transformations in two Psorption contrasting tropical soils during transit through Pontoscolex corethrurus (Glossoscolecidae: Oligochaeta). Soil Biology and Biochemistry 25, 789–792. \nMason-Jones, K., Banfield, C.C., Dippold, M.A., 2019. Compound-specific $^{13}\\mathrm{C}$ stable isotope probing confirms synthesis of polyhydroxybutyrate by soil bacteria. Rapid Communications in Mass Spectrometry 33, 795–802. \nMartinez-Tobon, D.I., Gul, M., Elias, A.L., Sauvageau, D., 2018. Polyhydroxybutyrate (PHB) biodegradation using bacterial strains with demonstrated and predicted PHB depolymerase activity. Applied Microbiology and Biotechnology 102, 8049–8067. \nMatavulj, M., Molitoris, H.P., 1992. Fungal degradation of polyhydroxyalkanoates and a semiquantitative assay for screening their degradation by terrestrial fungi. FEMS Microbiology Letters 103, 323–331. \nMarx, M., Wood, M., Jarvis, S., 2001. A fluorimetric assay for the study of enzyme diversity in soils. Soil Biology and Biochemistry 33, 1633–1640. \nMoorhead, D.L., Sinsabaugh, R.L., Hill, B.H., Weintraub, M.N., 2016. Vector analysis of ecoenzyme activities reveal constraints on coupled C, N and P dynamics. Soil Biology and Biochemistry 93, 1–7. \nNapathorn, S.C., 2014. Biocompatibilities and biodegradation of poly(3- hydroxybutyrate-co-3-hydroxyvalerate)s produced by a model metabolic reactionbased system. BMC Microbiology 14, 285. \nNguyen, C., Guckert, A., 2001. Short-term utilisation of $^{14}\\mathrm{C}$ -glucose by soil microorganisms in relation to carbon availability. Soil Biology and Biochemistry 33, 53–60. \nObruca, S., Sedlacek, P., Krzyzanek, V., Mravec, F., Hrubanova, K., Samek, O., Kucera, D., Benesova, P., Marova, I., 2016. Accumulation of poly(3- hydroxybutyrate) helps bacterial cells to survive freezing. PloS One 11, e0157778. \nQi, R., Jones, D.L., Li, Z., Liu, Q., Yan, C., 2020a. Behavior of microplastics and plastic film residues in the soil environment: a critical review. The Science of the Total Environment 703, 134722. \nQi, Y.L., Yang, X.M., Pelaez, A.M., Lwanga, E.H., Beriot, N., Gertsen, H., Garbeva, P., Geissen, $\\mathrm{V.,}$ 2018. Macro- and micro- plastics in soil-plant system: effects of plastic mulch film residues on wheat (Triticum aestivum) growth. The Science of the Total Environment 645, 1048–1056. \nQi, Y., Ossowicki, A., Yang, X., Huerta Lwanga, E., Dini-Andreote, F., Geissen, V., Garbeva, P., 2020b. Effects of plastic mulch film residues on wheat rhizosphere and soil properties. Journal of Hazardous Materials 387, 121711. \nQuast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., Gl¨ockner, F.O., 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research 41, 590–596. \nRazavi, B.S., Zarebanadkouki, M., Blagodatskaya, E., Kuzyakov, Y., 2016. Rhizosphere shape of lentil and maize: spatial distribution of enzyme activities. Soil Biology and Biochemistry 96, 229–237. \nRillig, M.C., 2012. Microplastic in terrestrial ecosystems and the soil? Environmental Science and Technology 46, 6453–6454. \nRivera-Briso, A.L., Serrano-Aroca, ´A., 2018. Poly(3-hydroxybutyrate-co-3- hydroxyvalerate): enhancement strategies for advanced applications. Polymers 10, 732. \nRochman, C.M., 2018. Microplastics research-from sink to source. Science 360, 28–29. \nSaarma, K., Tarkka, M.T., Itavaara, M., Fagerstedt, K.V., 2003. Heat shock protein synthesis is induced by diethyl phthalate but not by di(2-ethylhexyl) phthalate in radish (Raphanus sativus). Journal of Plant Physiology 160, 1001–1010. \nSander, M., 2019. Biodegradation of polymeric mulch films in agricultural soils: concepts, knowledge gaps, and future research directions. Environmental Science and Technology 53, 2304–2315. \nShen, Y.C., Shaw, G.C., 2015. A membrane transporter required for 3-hydroxybutyrate uptake during the early sporulation stage in Bacillus subtilis. FEMS Microbiology Letters 362. UNSP fnv165. \nSintim, H.Y., Flury, M., 2017. Is biodegradable plastic mulch the solution to agriculture’s plastic problem? Environmental Science and Technology 51, 1068–1069. \nSong, X., Razavi, B., Ludwig, B., Zamanian, K., Zang, H., Kuzyakov, Y., Dippold, M., Gunina, A., 2020. Combined biochar and nitrogen application stimulates enzyme activity and root plasticity. The Science of the Total Environment 735, 139393. \nSteinmetz, Z., Wollmann, C., Schaefer, M., Buchmann, C., David, J., Troger, J., Munoz, K., Fror, O., Schaumann, G.E., 2016. Plastic mulching in agriculture. Trading short-term agronomic benefits for -term soil degradation? The Science of the Total Environment 550, 690–705. \nVargas-Gastelum, L., Romero-Olivares, A.L., Escalante, A.E., Rocha-Olivares, A., Brizuela, C., Riquelme, M., 2015. Impact of seasonal changes on fungal diversity of a semi-arid ecosystem revealed by 454 pyrosequencing. FEMS Microbiology Ecology 91 fiv044. \nVolova, T.G., Prudnikova, S.V., Vinogradova, O.N., Syrvacheva, D.A., Shishatskaya, E.I., 2017. Microbial degradation of polyhydroxyalkanoates with different chemical compositions and their biodegradability. Microbial Ecology 73, 353–367. \nWang, Q., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology 73, 5261–5267. \nWeithmann, N., Mo¨ller, J.N., Lo¨der, M.G., Piehl, S., Laforsch, C., Freitag, R., 2018. Organic fertilizer as a vehicle for the entry of microplastic into the environment. Science Advances 4, 8060. \nWen, Y., Zang, H., Ma, Q., Evans, C.D., Chadwick, D.R., Jones, D.L., 2019. Is the ‘enzyme latch’ or ‘iron gate’ the key to protecting soil organic carbon in peatlands? Geoderma 349, 107–113. \nWen, Y., Freeman, B., Ma, Q., Evans, C., Chadwick, D., Zang, H., Jones, D., 2020. Raising the groundwater table in the non-growing season can reduce greenhouse gas emissions and maintain crop productivity in cultivated fen peats. Journal of Cleaner Production 262, 121179. \nXia, W., Zhang, C., Zeng, X., Feng, Y., Weng, J., Lin, X., 2011. Autotrophic growth of nitrifying community in an agricultural soil. The ISME Journal 5, 1226–1236. \nZang, H.D., Blagodatskaya, E., Wang, J.Y., Xu, X.L., Kuzyakov, Y., 2017. Nitrogen fertilization increases rhizodeposit incorporation into microbial biomass and reduces soil organic matter losses. Biology and Fertility of Soils 53, 419–429. \nZang, H., Blagodatskaya, E., Wen, Y., Xu, X., Kuzyakov, Y., 2018. Carbon sequestration and turnover in soil under the energy crop Miscanthus: repeated $^{13}\\mathrm{C}$ natural abundance approach and literature synthesis. Global Change Biology Bioenergy 10, 262–271. \nZang, H., Wang, J., Kuzyakov, Y., 2016. N fertilization decreases soil organic matter decomposition in the rhizosphere. Applied Soil Ecology 108, 47–53. \nZang, H., Xiao, M., Wang, Y., Ling, N., Wu, J., Ge, T., Kuzyakov, Y., 2019. Allocation of assimilated carbon in paddies depending on rice age, chase period and N fertilization: experiment with $^{13}\\mathrm{CO}_{2}$ labelling and literature synthesis. Plant and Soil 445, 113–123. \nZang, H., Zhou, J., Marshall, M.R., Chadwick, D.R., Wen, Y., Jones, D.L., 2020. Microplastics in the agroecosystem: are they an emerging threat to the plant-soil system? Soil Biology and Biochemistry 148, 107926. \nZecchin, S., Mueller, R.C., Seifert, J., Stingl, U., Anantharaman, K., von Bergen, M., Cavalca, L., Pester, M., 2018. Rice paddy Nitrospirae carry and express genes related to sulfate respiration: proposal of the new genus “Candidatus Sulfobium”. Applied and Environmental Microbiology 84 e02224-17. \nZettler, E.R., Mincer, T.J., Amaral-Zettler, L.A., 2013. Life in the “plastisphere”: microbial communities on plastic marine debris. Environmental Science and Technology 47, 7137–7146. \nZhang, X., Kuzyakov, Y., Zang, H., Dippold, M.A., Shi, L., Spielvogel, S., Razavi, B.S., 2020. Rhizosphere hotspots: root hairs and warming control microbial efficiency, carbon utilization and energy production. Soil Biology and Biochemistry 107872. \nZimmermann, L., Dierkes, G., Ternes, T.A., Volker, C., Wagner, M., 2019. Benchmarking the in vitro toxicity and chemical composition of plastic consumer products. Environmental Science and Technology 53, 11467–11477. \nZhou, J., Wen, Y., Shi, L.L., Marshall, M.R., Kuzyakov, Y., Blagodatskaya, E., Zang, H.D., 2020a. Strong priming of soil organic matter induced by frequent input of labile carbon. Soil Biology and Biochemistry 152, 108069. \nZhou, J., Zang, H., Loeppmann, S., Gube, M., Kuzyakov, Y., Pausch, J., 2020b. Arbuscular mycorrhiza enhances rhizodeposition and reduces the rhizosphere priming effect on the decomposition of soil organic matter. Soil Biology and Biochemistry 140, 107641. \nZinn, M., Witholt, B., Egli, T., 2001. Occurrence, synthesis and medical application of bacterial polyhydroxyalkanoate. Advanced Drug Delivery Reviews 253, 5–21. " + }, + { + "id": "10.1038_s41467-020-20582-6", + "DOI": "10.1038/s41467-020-20582-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-020-20582-6", + "Relative Dir Path": "mds/10.1038_s41467-020-20582-6", + "Article Title": "Mixed halide perovskites for spectrally stable and high-efficiency blue light-emitting diodes", + "Authors": "Karlsson, M; Yi, ZY; Reichert, S; Luo, XY; Lin, WH; Zhang, ZY; Bao, CX; Zhang, R; Bai, S; Zheng, GHJ; Teng, PP; Duan, L; Lu, Y; Zheng, KB; Pullerits, T; Deibel, C; Xu, WD; Friend, R; Gao, F", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Bright and efficient blue emission is key to further development of metal halide perovskite light-emitting diodes. Although modifying bromide/chloride composition is straightforward to achieve blue emission, practical implementation of this strategy has been challenging due to poor colour stability and severe photoluminescence quenching. Both detrimental effects become increasingly prominent in perovskites with the high chloride content needed to produce blue emission. Here, we solve these critical challenges in mixed halide perovskites and demonstrate spectrally stable blue perovskite light-emitting diodes over a wide range of emission wavelengths from 490 to 451 nullometres. The emission colour is directly tuned by modifying the halide composition. Particularly, our blue and deep-blue light-emitting diodes based on three-dimensional perovskites show high EQE values of 11.0% and 5.5% with emission peaks at 477 and 467nm, respectively. These achievements are enabled by a vapour-assisted crystallization technique, which largely mitigates local compositional heterogeneity and ion migration. Achieving bright and efficient blue emission in metal halide perovskite light-emitting diodes has proven to be challenging. Here, the authors demonstrate high EQE and spectrally stable blue light-emitting diodes based on mixed halide perovskites, with emission from 490 to 451nm by using a vapour-assisted crystallization technique.", + "Times Cited, WoS Core": 386, + "Times Cited, All Databases": 409, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000609611000001", + "Markdown": "# Mixed halide perovskites for spectrally stable and high-efficiency blue light-emitting diodes \n\nMax Karlsson $\\textcircled{1}$ 1,8, Ziyue Yi1,2,8, Sebastian Reichert 3, Xiyu Luo1,4, Weihua Lin5, Zeyu Zhang6, Chunxiong Bao $\\textcircled{1}$ 1, Rui Zhang1, Sai Bai 1, Guanhaojie Zheng1, Pengpeng Teng1, Lian Duan4, Yue Lu6, Kaibo Zheng5,7, Tönu Pullerits $\\textcircled{1}$ 5, Carsten Deibel $\\textcircled{1}$ 3, Weidong Xu 1,9✉, Richard Friend 2 & Feng Gao 1,9✉ \n\nBright and efficient blue emission is key to further development of metal halide perovskite light-emitting diodes. Although modifying bromide/chloride composition is straightforward to achieve blue emission, practical implementation of this strategy has been challenging due to poor colour stability and severe photoluminescence quenching. Both detrimental effects become increasingly prominent in perovskites with the high chloride content needed to produce blue emission. Here, we solve these critical challenges in mixed halide perovskites and demonstrate spectrally stable blue perovskite light-emitting diodes over a wide range of emission wavelengths from 490 to 451 nanometres. The emission colour is directly tuned by modifying the halide composition. Particularly, our blue and deep-blue light-emitting diodes based on three-dimensional perovskites show high EQE values of $11.0\\%$ and $5.5\\%$ with emission peaks at 477 and $467\\mathsf{n m}$ , respectively. These achievements are enabled by a vapour-assisted crystallization technique, which largely mitigates local compositional heterogeneity and ion migration. \n\nnati irage ( olingahlte dme tlt’iEncgl CIwEi)th tchoe Cdionmatme svsailoune Ibnetleorw$\\stackrel{\\bigcup}{\\longrightarrow}0.15$ $(x+y)$ importance for display and energy-saving lighting applications1. Similar to preceding light-emitting technologies, achieving efficient blue emission in metal halide perovskite light-emitting diodes (PeLEDs) has proven to be very challenging, with performance lagging far behind their green, red and near-infrared counterparts2–7. Current efforts in blue PeLEDs largely take advantage of quantum confinement effects for bandgap engineering, i.e. using mixed dimensional perovskites or colloidal perovskite nanocrystals8–10. Although impressive progress has been achieved in developing skyblue PeLEDs (with $\\mathrm{CIEy}>0.15)$ (Supplementary Table 1)11, there are increasing difficulties to realize blue emission using these strategies. For example, state-of-the-art blue perovskite emitters achieved by strong quantum confinement commonly suffer from deteriorated electronic properties due to an excess of large-size organic cations and/or over-capped ligands. These issues lead to problematic charge injection and hence low brightness, as well as a big gap between photoluminescence quantum yields (PLQYs) of thin films and external quantum efficiencies (EQEs) of devices12–14. \n\nCompared with enhancing quantum confinement, modulating the halide anions is a more straightforward way to tune the bandgap of perovskites15. However, implementation of this facile approach in blue PeLEDs is largely hindered by poor colour stability of the resultant blue perovskite emitters (mixed bromide/chloride perovskites), due to anion segregation under electric bias16–18. In addition, it has been widely observed that the PLQYs decrease with increasing chloride content since chloride perovskites are less defect-tolerant compared to their bromide and iodide counterparts19,20. Both issues are particularly pronounced in perovskites with the high chloride content that is desired for producing blue and deep-blue emssion19–22. Very recently, strategies on mitigating photoinduced phase segregation in perovskite solar cells (e.g. defect passivation) have been borrowed to improve the spectral stability of mixed bromide/chloride blue $\\mathrm{PeLEDs}^{2\\dot{3},24}$ . These strategies were so far demonstrated to be feasible only in the cases where the chloride content is low $(<30\\%)^{22,25}$ . Unfortunately, even by combining the strategies of mixed bromide/ chloride perovskites with the advantages of enhanced quantum confinement, device performance of spectrally stable blue PeLEDs is still far from practical applications (Supplementary Table 2)11,14,20,25. \n\nHere, we demonstrate that blue PeLEDs based on mixed halide perovskites can be highly efficient and their colour instability issues can be substantially eliminated across a large range of the blue spectral region spanning $490{\\scriptstyle-451}\\mathrm{nm}$ (with a high chloride content ranging from $30\\%$ to $57\\%$ ), without any assistance from enhanced quantum confinement. We show that not only halide ion migration, but also compositional heterogeneity, is critical for triggering phase segregation. Both factors can be remarkably suppressed through depositing the perovskite films via a vapour-assisted crystallization (VAC) technique. As a result, we demonstrate spectrally stable blue PeLEDs presenting a high EQE value of $11.0\\%$ and a peak brightness of $2180{\\mathrm{cd}}{\\mathrm{m}}^{-2}$ , with an emission peak at $477\\mathrm{nm}$ and CIE coordinates of (0.107, 0.115). In addition, we fabricate a PeLED exhibiting ideal deep-blue emission at $467\\mathrm{nm}$ and a decent EQE of $5.5\\%$ , which is the highest efficiency with an emission peak below $470\\mathrm{nm}$ . The CIE coordinates of our deepblue PeLEDs are (0.130, 0.059), approaching that of Rec. 2020 specified primary blue. \n\n# Results and discussion \n\nDevice fabrication and spectral stability. We prepare perovskites from precursors with a stoichiometry of ${\\mathsf{C}}s^{+}$ : $\\mathrm{F\\bar{A}^{+}}$ : $\\mathrm{P\\hat{b}}^{2+}$ : $[\\mathrm{Br}_{1-\\mathrm{x}}+\\mathrm{Cl_{x}}]^{-}=1.2\\$ : 0.3: 1: 3.5 $\\begin{array}{r}{\\mathrm{'}_{\\mathbf{X}}=30\\%-57\\%\\mathrm{'}}\\end{array}$ ), where $\\mathrm{FA^{+}}$ is formamidinium. In the cases of $\\mathbf{x}$ below $20\\%$ , we do not observe any colour instability issues (Supplementary Fig. 1). We focus our discussions on the perovskites from a precursor solution with $\\mathbf{x}=$ $40\\%$ , which is the most representative case due to its high chloride content, decent device performance and emission within the blue region. The chloride content in this film accounts for $42\\%$ of total halide anions as determined by X-ray photoelectron spectroscopy (XPS) (Supplementary Fig. 2). We introduce 4,7,10-trioxa-1,13- tridecanediamin (TTDDA) into the perovskite precursors as a passivating agent to reduce defects5. \n\nWe show an illustration of the VAC-treatment for preparation of perovskite films in Fig. 1a. In brief, the as-casted films are directly moved into a petri-dish with a dimethylformamide (DMF) atmosphere, followed by a typical thermal annealing process. Control samples, annealed directly after spin-coating, are prepared for comparison. The different film processing techniques result in distinct variations of the film morphology, i.e. a discontinuous network of large grains for the VAC-treated films and full coverage of small nano-grains for the control ones, as shown in scanning electron microscope (SEM) images (Supplementary Fig. 3). We observe no change in the 3D crystal structure but a more preferential crystal orientation along the (110) direction and slight enhancement of crystallinity with VACtreatment, as demonstrated by grazing-incidence wide-angle Xray scattering (GIWAXS) and X-ray diffraction (XRD) measurements (Supplementary Fig. 4). \n\nWe fabricate the PeLEDs based on a device structure of indium tin oxide (ITO)/nickel oxide $(\\mathrm{NiO_{x},10\\ n m})/$ poly(9-vinylcarbazole) (PVK): polyvinylpyridine (PVP) $(10\\mathrm{nm})/$ perovskite/ $2,2^{\\prime},2^{\\prime\\prime}.$ -(1,3,5- benzinetriyl)tris(1-phenyl-1H-benzimidazole) (TPBi)/ lithium fluoride $(1\\mathrm{nm})$ /aluminium ( $\\cdot100\\mathrm{nm})$ (Fig. 1b). The employment of $\\mathrm{NiO_{x}/P V K}$ bilayer facilitates hole injection due to a cascade energy level alignment26, which contributes to improved PeLED performance (Supplementary Figs. 5 and 6). The PVP layer is used to improve the wettability of the precursor solution on the PVK surface, as demonstrated by the reduced water contact angle after PVP deposition (Supplementary Fig. 7). The high-angle annular dark-field scanning transmission electron microscope (HAADFSTEM) and energy-dispersive X-ray spectroscopy (EDX) device cross-sectional images indicate higher TPBi layer thickness $(\\sim50$ nm) on the bottom hole injection layer with respect to that on perovskite grains $(\\sim35\\mathrm{nm})$ (Fig. 1b and Supplementary Fig. 8 (carbon distribution)), leading to enhanced local resistance at the TPBi/PVK:PVP interface. Combined with the large injection barrier caused by the energy level mismatch between TPBi and PVK, the discontinuous morphology in VAC-treated devices does not necessarily lead to strong electrical shunts under normal PeLED operational conditions3,5 (Supplementary Fig. 9). Notably, the VACtreated devices with varying chloride content $(30-40\\%)$ show considerable enhancement of EQE values compared to the respective control samples (Fig. 1c). We show the characteristics of the representative devices in Supplementary Fig. 10. We notice that, as expected, our device performance also benefits from the efficient defect passivation ability of TTDDA (Supplementary Fig. 11). \n\nThe VAC-treated devices show stable electroluminescence (EL) with a negligible shift of the CIE coordinates up to $\\sim$ $400\\mathrm{mA}\\mathrm{cm}^{-2}$ $(\\bar{6}{-}\\bar{6}.5\\mathrm{V})$ , which is far above maximum light output $(L_{\\mathrm{max}})$ conditions at $100\\mathrm{mA}\\mathrm{cm}^{-2}/5.0\\mathrm{V}$ (Fig. 1d). The EL spectrum obtained at a high voltage (or current density) of $6\\mathrm{V}$ $(\\mathsf{\\tilde{\\Gamma}}400\\mathrm{mAcm}^{-2}.$ ) is only slightly broader than that at $3.5\\mathrm{V}$ $({\\sim}3\\operatorname*{mA}{\\mathsf{c m}}^{-2},$ ) (Fig. 1e). We attribute this slight EL broadening to charge carrier/phonon interaction due to Joule heating27, as similar behaviour is observed in pure-bromide PeLEDs (Supplementary Fig. 12). In contrast, the control devices undergo distinct emission colour changes starting at very low bias and current density of around $3.\\mathrm{\\i}0{-3.5}\\mathrm{V}$ and $1{-}5\\operatorname{mA}\\operatorname{cm}^{-2}$ (Fig. 1d, e), analogous to previous reports on spectrally unstable mixed bromide/chloride PeLEDs16,21. Under harsh operational conditions, that is, with a bias larger than $6.5\\mathrm{V}_{:}$ , distinct colour change is observable even in VAC-treated devices. We emphasize that in this case, the current density is over $400\\mathrm{mA}\\mathrm{cm}^{-2}$ , which is far above normal working conditions of reported blue PeLEDs11,14,20,25. Notably, we observe abnormal plateau-like $J{-}V$ characteristics during the voltage sweep at $6{-}6.5\\mathrm{V}$ and severe PL quenching after the operation (Supplementary Fig. 13), indicating severe device damage due to perovskite and/or interfacial degradation. Given the high current density, Joule heating could be a critical reason28. \n\n![](images/ae0c0c86195cd43870a03fc6c91c46dde6a1d7985f8b4f9dc0c3d7d2b2d46d35.jpg) \nFig. 1 Device fabrication and characteristics. a An illustration of the VAC-treatment. b Schematic of the PeLED structure and the HAADF cross-sectional device image. The scale bar is $100\\mathsf{n m}$ . c Histograms of peak EQEs extracted from control (top) and VAC-treated devices (bottom) with varying chloride contents $30\\%$ , $35\\%$ and $40\\%$ ). d–f Spectral stability for control and VAC-treated devices with $40\\%$ Cl loading. The representative plots of $\\mathsf{C l E}_{\\mathsf{y}}$ versus applied voltages (top) and current densities (bottom) (d); EL spectra at low and high voltage/current density for control (left) and VAC-treated devices (right) (e); EL spectra of VAC-treated devices with varying chloride content $(30-57\\%)$ at maximum luminance $(\\pmb{\\uparrow})$ . The points labelled as $L_{\\mathrm{max}}$ in (d) represent the operational condition for peak luminance. \n\nWith VAC-treatment, we demonstrate spectrally stable PeLEDs with emission colours from sky-blue to deep-blue (emission peaks at $490{\\mathrm{-}}451\\ \\mathrm{nm},$ ) by simply varying the chloride content $(30\\%-57\\%)$ (Fig. 1f and Supplementary Fig. 14). We also examine the spectral stability of our devices at a constant current density of $5\\operatorname{micm}^{-2}$ (with initial luminance ranging from ${\\sim}200$ to ${\\sim}600\\ c\\mathrm{d}\\ \\mathrm{m}^{-2}$ for different devices). Although the operational lifetime is no better than those in previously reported blue PeLEDs (with $\\mathrm{T}_{50}$ around $1-2\\operatorname*{min}\\bigr)^{\\hat{8},11,12,20}$ , we observe no spectral shift even after $10\\mathrm{min}$ of operation (Supplementary Fig. 15). Previous reports on photo-induced phase segregation in mixed halide perovskites indicate that it is only triggered when the excitation density is above a certain threshold, below which little to no effects are present29,30. Our results are consistent with these observations, indicating that employing mixed halide anions is a feasible approach for blue PeLEDs as long as we can control the phase segregation threshold to be far above working conditions. \n\nThe origin of improved spectral stability. Although the underlying reason for phase segregation is complicated, previous investigations on perovskite solar cells propose that three factors may be collectively contributing to this phenomenon. These three factors include a polaron induced strain effect31, a thermodynamic process as driven by free energy differences associated with composition and band offsets32, and field-dependent anion motion33. We carry out a series of characterizations to understand the origin of the spectral stability of PeLEDs based on VAC-treated perovskite films. \n\n![](images/0c7b501fa191bf80e436f703275270e1720c2d78b15f22ad27ab141426f1dd75.jpg) \nFig. 2 Understanding superior spectral stability of VAC-treated devices. a–d Photophysical characterizations for control and VAC-treated perovskite films: Fluence-dependent PLQYs (a); PL decay measured by TCSPC (b). PL spectra (c); Transient absorption of control (top) and VAC-treated films (bottom) after excitation at $400\\mathsf{n m}$ (d). e, f Derivatives of temperature-dependent capacitance versus frequency plots for control (e) and VAC-treated $(\\pmb{\\uparrow})$ devices. The blue arrows indicate temperature change from $3501\\mathrm{K}$ to $200\\mathsf{K}$ . Here, two mobile ions marked as $\\upbeta$ and ε are visible. \n\nWe first measure PL properties of our perovskite films. We observe obviously enhanced PLQYs in the VAC-treated films across a wide range of excitation fluences, with a peak PLQY of $12\\%$ compared to $3\\%$ for the control sample (Fig. 2a). Time correlated single photon counting (TCSPC) measurements demonstrate a prolonged PL lifetime for VAC-treated samples compared to the control one (Fig. 2b). These results suggest fewer defects and much suppressed non-radiative recombination in the VAC-treated films, consistent with the higher EQEs of the devices. We believe that the enhanced spectral stability in our PeLEDs is partially ascribed to the reduced defects, as defects are generally believed to act as channels for anion hopping and hence facilitate phase segregation34. \n\nIn addition to the reduced defect density, we also observe significantly improved local compositional homogeneity in the VAC-treated films compared to the control sample. It is first evidenced by a steeper edge of the absorption spectrum (Supplementary Fig. 16a) and a much-narrowed PL linewidth (with full-width at half-maximum (FWHM) of ${\\sim}18\\mathrm{nm}$ ) of VACtreated films compared to that of control samples (FWHM of $\\sim25\\mathrm{nm}\\dot{$ ) (Fig. 2c). To gain further understanding of electronic states in the films, we conducted transient absorption (TA) spectroscopy measurements. The control film displays a broad photobleaching peak that shifts from $455\\mathrm{nm}$ to $465\\mathrm{nm}$ (Fig. 2d and Supplementary Figs. 16b, c), which is consistent with the coexistence of different phases. As there is no sign of lowdimensional phases from GIWAXS and XRD patterns, we assign the compositional heterogeneity in the control films to a nonuniform distribution of halide anions, which has been widely reported in bromide/iodide mixed perovskites35,36. In contrast, the VAC-treated film shows a single narrow ground state photobleaching situated at $473\\mathrm{nm}$ , indicating a high compositional homogeneity. According to current polaronic and thermodynamic models for rationalizing phase segregation in perovskite solar cells, a high compositional heterogeneity can contribute to the phase segregation31,32,37–39. In specific, fluctuations in halide compositions can yield heterogeneous regions in the perovskites where polarons tend to localize at lower bandgap areas, leading to enhanced local lattice strain which drives demixing of halide anions31,38,39. A system with initially high free energy due to severe compositional disorder might be energetically unfavourable for phase stability as indicated by the thermodynamic model37. Lattice mismatch and discrepancy of band offsets between different phases are also believed to be the driving forces for phase segregation32,37. Our observations are in line with these previous investigations, demonstrating the critical role of high homogeneity in improving phase stability of VACtreated devices. \n\nAssured about the reduced defects and improved compositional homogeneity in VAC-treated films, we then evaluate fielddependent ion migration in our devices. We perform temperature-dependent admittance spectroscopy, from which we can determine ion migration activation energy $(E_{\\mathrm{A}})$ , ion diffusion coefficient $(D)$ , and concentration of mobile ions $(N_{\\mathrm{i}})^{40}$ . The capacitance (C) response of mobile ionic species can be probed by varying the frequency (ω) of an applied alternating voltage and the temperature. We show the admittance spectra in Supplementary Fig. 17 and the plots of derivatives $(-\\infty100)$ versus $\\upomega$ ) in Fig. 2e, f. Two distinct signatures from mobile ionic species are visible, which are labelled ε and $\\upbeta$ We confirm that the charge transport layers are not responsible for these signatures by characterizing devices with only charge transport layers (Supplementary Fig. 18)41. In particular, we observe that the response peaks at the low-frequency region (ε) in the VAC-treated devices are much less prominent than those in the control devices, suggesting a much lower mobile ion concentration. We show the deduced Arrhenius plots in Supplementary Fig. 19 and summarize all the obtained parameters $(E_{\\mathrm{A}},\\ D,$ and $N_{\\mathrm{i}}$ ) in Supplementary Table 3. The $E_{\\mathrm{A}}$ values of ion diffusion for both ε and $\\upbeta$ are very close in the two samples, implying that the mode of ion migration is not significantly altered. Both the concentration of mobile ions and ion diffusion coefficient are reduced in VAC-treated devices compared to the control devices. The most striking difference occurs to $N_{\\mathrm{i}}(\\varepsilon)$ , which is decreased from $5.4\\times10^{16}\\mathrm{cm}^{-3}$ to $1.6\\times10^{16}\\mathrm{cm}^{-3}$ . Considering the small $E_{\\mathrm{A}}$ of ε $({\\sim}0.2\\mathrm{eV})$ , we assign them to mobile halide anions33,40. The mitigated halide migration can be a result of reduced ionic defects, as confirmed by PLQYs and TCSPC results34. \n\nBased on the analysis above, we conclude that the excellent spectral stability in VAC-treated devices originates from a synergistic effect of less ionic defects, mitigated ion migration and a higher compositional homogeneity. \n\nUnderstanding the effect of the VAC-treatment process. Having understood the origin of high colour stability and excellent device performance, the question that remains is how the VAC-treatment brings about these effects. We conduct SEM measurements to track the grain growth and morphological evolution of the films during the VAC treatment. We clearly observe two stages. The first stage happens within the first minute of vapour treatment, showing a crystal growth from initially formed small grains into large ones, accompanied by the morphological evolution from dense films into a discontinuous network (Supplementary Fig. 20). Considering the presence of crystalline perovskites within the pristine films and the diffusive vapour atmosphere, we assign the process of grain growth to Ostwald ripening. The wet films preserved by DMF vapour can be regarded as a sol system, with the solvent as the dispersing medium and perovskites as the dispersed phases. The ripening process occurs because large grains are more energetically favoured to smaller grains, leading to reduced grain boundaries and hence fewer defects. The second stage happens during the prolonged duration of treatment, which only has a slight impact on the morphology. \n\nWe also employ in-situ PL and transmittance measurements to monitor the crystal growth with and without DMF vapour. The measurement setups are illustrated in Supplementary Fig. 21. Initially, both films show broad emission bands with the main peak at the low-energy region and a distinguishable shoulder at the high-energy region, which are labelled as P1 and P2, respectively (Fig. 3a, b). We speculate that the high-energy emission originates from initially formed Cl-rich perovskite phases due to their fast nucleation and crystallization, as governed by their poor solubility compared to Br-rich counterparts. By following the PL spectral evolution with time, we observe a gradual disappearance of P2 and a continuous red-shift of P1 in VAC-treated samples, leading to a narrow and single-emission peak eventually (Fig. 3b). To further clarify the spectral evolution of VAC-treated films in different time scales, we show the changes of emission bandwidth as well as the proportion of P2 $(\\mathrm{A}_{\\mathrm{P}2})$ to a total area of emission band (A) with time in Fig. 3c. We find that the most striking changes occur within the first five minutes of treatment, the while prolonged duration of up to 20 min results in only a small difference (Fig. 3c). This PL evolution is consistent with the results of in-situ transmittance measurements, i.e. a red-shift of absorption onset and steeper absorption edge after VAC-treatment (Supplementary Fig. 22a). In contrast, keeping the pristine films in the glovebox atmosphere does not change the PL (Fig. 3a) and transmittance (Supplementary Fig. 22b) spectra to any significant degree over time. \n\nBased on the in-situ spectroscopic measurement results, we can now rationalize the effect of the VAC-treatment. It provides a favourable diffusive environment for halide rearrangement within the films (Fig. 3d), which undergo an equilibrating crystallization process that homogenises local chemical composition and reduces disorder. Initially, the as-casted films are composed of various Clrich solid phases and Br-rich components in liquid phases due to nonequilibrium grain growth during spin-casting. For the films with no vapour atmosphere, quick solvent evaporation and following fast crystallization result in immediate freezing of the perovskite composition. The post-annealing could mitigate phase heterogeneity to some extent, as indicated by the weakened emission shoulder at short wavelength (P2) after annealing (Fig. 2c). However, the initially formed heterogeneous phases are still partially preserved in the resulting films. In contrast, with the presence of DMF vapour, the liquid phase can be preserved for a long duration. This facilitates and prolongs the following halide exchange process as driven and modulated by the chemical potential difference between solid (Cl-rich) and liquid phases (Brrich), resulting in a rearranged composition that gradually approaches chemical equilibrium and homogeneous distribution of constituents. The following annealing procedure has little impact on the PL spectra of VAC-treated films, further confirming that the high homogeneous composition has already been achieved during the VAC-treatment. \n\nWe then tune the duration of the DMF vapour treatment to assess the impact on spectral stability and device efficiency in different timescale (Fig. 3e, f), further supporting our understanding of this technique. We observe distinct batch to batch variations in EL spectra and dispersion of CIE coordinates in control devices (Fig. 3e and Supplementary Fig. 23a), ascribed to nonequilibrium crystal growth and hence uncontrollable local film composition. In contrast, EL spectra and CIE coordinates of VAC-treated devices are highly reproducible between batches, resulting from self-moderated halide rearrangement during the VAC-treatment (Fig. 3e and Supplementary Fig. 23b). When comparing the devices processed with different duration of VAC treatment, we observe a remarkable EQE enhancement in one minute of treatment, that is, with averaged peak EQE values improving from ${\\sim}0.6\\%$ to ${\\sim}3.8\\%$ (Fig. 3f), which well corresponds to the dramatical morphological variations in the same time scale from SEM results (Supplementary Fig. 20). We believe that perovskite re-crystallization, enlarged grain size and improved local homogeneity collectively help to reduce the defect density and hence reduce nonradiative recombination. In addition, the isolated nanostructures may also contribute to the efficiency improvement due to enhanced light-out coupling3. With increasing the processing duration, the EQE values gradually approach saturation. We assign this to a slow diffusion-mediated defect healing process from the gradually improved homogeneity that reduces local lattice mismatch and strain-induced interfacial defects42,43. Notably, one minute of VAC-treatment is sufficient for improving the efficiency but not the spectral stability (Fig. 3e), indicating that the discontinuous morphology has little impact on improving phase stability. In other words, a large perovskite grain with size scale of hundreds of nanometres in our samples can hardly be the reason for the suppression of phase segregation within the grain, as probed in previous reports showing that the phase segregated domain can be as small as $\\sim8\\mathrm{nm}^{\\breve{3}0,32}$ . We also notice that the devices with fiveminute treatment show comparable colour stability to those with twenty-minute treatment (Fig. 3e), corresponding well to the time scale of the disappearance of high-energy phases as observed in Fig. 3c. It further confirms the critical role of high compositional homogeneity in improving phase stability. \n\n![](images/e300095136e263b38d024006e2bdeb0e8f868aebf0cdedd521ab3379494438dc.jpg) \nFig. 3 Understanding the halide redistribution during VAC-process. a, b PL evolution of the precursor films kept in the glovebox atmosphere (a) and DMF atmosphere (b) with time. c the evolution of emission linewidth and the proportion of P2 $(\\mathsf{A}_{\\mathsf{P}2})$ to the respective total area of the emission band (A) in VAC-treated films with time. d Schematic illustration of the proposed mechanism for halide redistribution. Here, the purple $\\mathsf{P b}(\\mathsf{B r/C l})_{6}4-$ octahedra represent chloride-rich phases in respect to that with stoichiometric bromide/chloride distribution (blue octahedra). The khaki represents the liquid phase within the films and the blue arrows represent ion exchange process. The excessive ions within the dried films are not illustrated for clarity. e, f The evolution of CIE coordinates upon bias (e) and peak EQEs of the devices with varying duration of VAC-treatment (0, 1, 2, 5, 20 min). f The error bars present the standard deviation extracted from 4 to 6 devices. \n\nGiven the critical role of the diffusive environment on retarding crystallization for halide rearrangement, a proper solubility of perovskite precursors in the solvent vapour might be the key to achieving high compositional homogeneity. We thus perform additional experiments using dimethyl sulfoxide (DMSO) and chloroform as the alternative vapours to further understand the VAC treatment. DMSO is another commonly used solvent for perovskite precursors, while chloroform is a wellknown “anti-solvent” that is widely used to accelerate perovskite crystallization44. Considering that the vapour residues in the glovebox may affect the results, we also prepare the samples without introducing any vapour on purpose, that is, leaving the as-casted films in the glovebox for the same duration. As shown in Supplementary Fig. 24, the introduction of chloroform vapour has no positive effect on either device efficiency or spectral stability, which can be attributed to the poor solubility of perovskite precursors in chloroform, leading to a fast crystallization and freezing of the composition, and hence resulting in high heterogeneity. In contrast, DMSO treatment gives comparable improvement as DMF vapour, further rationalising our understanding of the effect of the vapour treatment. \n\nThe general applicability of VAC-treatment and device optimization. We proceed to explore the VAC-treatment in other material systems, aiming to further improve the device performance and validate the general applicability. We incorporate a small amount of rubidium ions $(\\mathrm{R\\bar{b}^{+}})$ in our perovskites, that is, using a precursor composition of $\\mathrm{Rb^{+}}$ : ${\\mathrm{C}}s^{+}$ : $\\mathrm{F}\\mathrm{\\bar{A}}^{+}$ : $\\mathrm{Pb}^{2+}$ : $[\\mathrm{Br}_{0.6}+$ $\\mathrm{Cl}_{0.4}\\bar{]}^{-}\\bar{=}0.1$ : 1.2: 0.2: 1: 3.5. Consistent with the previous reports in perovskite solar cells45,46, the incorporation of $\\mathrm{Rb^{+}}$ effectively suppresses non-radiative recombination as indicated by a considerable enhancement of peak external PLQY $(25\\%)$ and a prolonged PL lifetime (Supplementary Figs. 25a, b). The small amount of $\\mathrm{{Rb^{+}}}$ addition has little impact on the film morphology (Supplementary Fig. 25c). \n\n![](images/2373ea496d583985034ab1a2c821b102bed68147c72f1fa8acd5adf9a7a8182c.jpg) \nFig. 4 The device performance of Rb-passivated perovskites with $40\\%$ and $45\\%$ Cl contents. a EQE-current density $(J)$ curves (J-EQE). b Current density–voltage–luminance $(J-V-L)$ characteristics. c EL spectra and CIE colour coordinates. The square and pentagram in the CIE 1931 $(\\mathsf{x},\\mathsf{y})$ chromaticity diagram represent the colour coordinates of primary blue specified in the National Television System Committee (NTSC) and recommendation bt.2020 (Rec.2020), respectively. d Histograms of the peak EQEs extracted from 40 devices for each case. \n\nWe show the characteristics of the best-performing VACtreated Rb-device using $40\\%$ Cl content in Fig. 4. The device exhibits blue emission peaking at $477\\mathrm{nm}$ with FWHM of $18\\mathrm{nm}$ . The corresponding CIE coordinates are (0.107, 0.115), approaching the primary blue (0.14, 0.08) specified by the National Television System Committee (NTSC). Compared to the device without using VAC-treatment (Supplementary Fig. 26), the treated device shows a significant enhancement of EQE value up to $11.0\\%$ . The luminance rises rapidly after the device turns on at a low voltage of $2.6\\mathrm{V}$ , reaching a peak value of $\\displaystyle{2,180\\ c d\\ c m^{-2}}$ at $5.0\\mathrm{V}$ $(10\\bar{6}\\mathrm{mAcm}^{-2}.$ ). The low turn-on voltage and high brightness indicate efficient charge injection, which is usually very challenging in strongly confined perovskites14. We observe no peak shift during voltage scans until reaching a high bias at $6.0\\mathrm{V}$ $\\left(\\sim300\\mathrm{mA}\\mathrm{cm}^{-2}\\right)$ (Supplementary Fig. 27a), analogous to the device without $\\mathrm{Rb^{+}}$ incorporation, further indicating that phase segregation in VAC-treated devices is mainly mediated by the device damage at harsh operating conditions. In addition, we demonstrate that no EL shift can be observed even after $75\\mathrm{{min}}$ of operation at $3\\mathrm{V}$ $\\left(\\sim0.1\\ \\mathrm{mA}\\ c m^{-2}\\right.$ , with initial luminance of ${\\sim}10$ cd $\\mathbf{\\dot{m}}^{2},$ ) (Supplementary Fig. 27b). Although $\\mathrm{Rb^{+}}$ addition significantly improves the device efficiency, we have not observed any distinct effect on operational stability $\\cdot{\\sim}3\\mathrm{min}$ , Supplementary Fig. 27c, d). The short operational lifetime could be a result of Joule heating and ion-migration induced material and/or interfacial degradation under the bias9,28, as well as Al diffusion and relevant redox reaction between $\\mathrm{Pb}^{2+}$ and $\\mathrm{Al}^{047}$ . An EQE histogram for 40 devices shows an average peak EQE of $9.3\\%$ with a low standard deviation of $0.67\\%$ , indicating high reproducibility of the VAC-treatment. \n\nFurther increasing Cl content to $45\\%$ results in deep-blue emission, whose device characteristics are also summarized in Fig. 4. The corresponding CIE coordinates are (0.130, 0.059), very close to Rec. 2020 specified blue standards (0.131, 0.046). The deep-blue PeLEDs achieves a peak EQE of $5.5\\%$ and an average peak EQE of $3.9\\%$ with a standard deviation of $0.76\\%$ , which are among the best for PeLEDs with ideal deep-blue emission. \n\nWe demonstrate that the VAC-treatment is also applicable for improving the colour stability and device performance of low-dimensional perovskites with mixed bromide/chloride anions, e.g. the typical phenethylammonium $(\\mathrm{PEA^{+}})$ -modified $\\mathrm{Cs}\\mathrm{Pb}(\\mathrm{Br}_{0.7}\\mathrm{\\bar{Cl}}_{0.3})_{3}$ (Supplementary Fig. 28). These results indicate that the wavelength of the previously reported high-performance sky-blue PeLEDs based on quasi-2D perovskites could be pushed to a bluer region without any negative impacts on their colour stability and device efficiency. \n\nIn summary, we have demonstrated that the notorious colour instability issues in mixed halide blue PeLEDs can be substantially mitigated across a wide range of emission colours from sky blue to deep blue region $(490-451\\mathrm{nm})$ ). The excellent phase stability is mainly achieved by the development of a vapour-assisted crystallization technique that effectively suppresses the ion migration and compositional heterogeneity. Particularly, for the first time, we show high-efficiency and spectrally stable blue and deep-blue PeLEDs based on mixed halide 3D perovskites, with respective peak EQEs of $11.0\\%$ and $5.5\\%$ , presenting two of the most efficient blue PeLEDs to date. Our findings are also applicable to the prevailing low-dimensional blue perovskite emitters, indicating a bright future for further improvement of blue PeLEDs by combining these two strategies. Our research thus provides a broad avenue for future development of blue perovskite emitters, representing another milestone towards practical implementation of perovskite light-emitting diodes in full-colour displays and lighting applications. Beyond that, stabilized mixed halide perovskites are also of great interest for a wide range of perovskite applications where the bandgap needs to be finely controlled, for instance, lasing and tandem solar cells. \n\n# Methods \n\nMaterials. Caesium bromide (CsBr, $99.999\\%$ ), lead bromide $\\mathrm{(PbBr_{2}}$ , $99.999\\%$ ), lead chloride $({\\mathrm{Pb}}{\\mathrm{Cl}}_{2},$ $99.999\\%$ ) was purchased from Alfa Aesar. Formamidinium bromide (FABr) and phenethylammonium bromide (PEABr) were purchased from Greatcell Solar. Rubidium bromide (RbBr, $99.99\\%$ ), polyvinylpyridine (PVP, average Mw \\~55,000), 4,7,10-trioxa-1,13-tridecanediamin (TTDDA), poly(9- vinylcarbazole) (PVK, average Mn 25,000–50,000) were purchased from Sigma Aldrich. The $\\mathrm{NiO_{x}}$ nano-crystals were purchased from Avantama AG and were used without additional treatment. 1,3,5-tris(1-phenyl-1H-benzimidazol-2-yl)benzene (TPBi) was purchased from Luminescence Technology corp. Other materials for device fabrication were all purchased from Sigma-Aldrich. \n\nPreparation of the perovskite solution. Perovskite precursors (CsBr: FABr: $\\mathrm{Pb}\\mathrm{Br}_{2}$ : $\\mathrm{PbCl}_{2}$ : TTDDA) with a molar ratio of 1.2: 0.3: x: y: 0.1 (where $\\mathbf{x}+\\mathbf{y}=1$ ) were mixed and dissolved in dimethyl sulfoxide (DMSO). The precursor concentration as determined by $\\mathrm{Pb}^{2+}$ is $0.15\\mathbf{M}$ for $30\\mathrm{-}40\\%$ Cl, $0.13\\mathrm{M}$ for $45\\%$ Cl, 0.11 M for $50\\%$ Cl, and $0.09{\\mathrm{M}}{}$ for $57\\%$ Cl, respectively. The precursor solutions were stirred at $80~^{\\circ}\\mathrm{C}$ for 4 h before use. For the low-dimensional perovskites, precursors (PEABr: CsBr $\\mathrm{Pb}\\mathbf{B}\\mathbf{r}_{2}$ : ${\\mathrm{Pb}}{\\mathrm{Cl}}_{2}.$ ) with a molar ratio of 0.9:1.1:0.4:0.6 mixed and dissolved in DMSO to make a solution with $30\\%$ Cl-content. The precursor concentration determined by $\\mathrm{Pb}^{2+}$ is $0.15\\mathrm{M}$ . \n\nPeLED fabrication. Glass substrates with patterned Indium tin oxide (ITO) were sequentially cleaned by detergent and TL-1 (a mixture of water, ammonia $(25\\%)$ and hydrogen peroxide $(28\\%)$ (5:1:1 by volume)). The clean substrates were then treated by ultraviolet-ozone for $10\\mathrm{min}$ . $\\mathrm{NiO_{x}}$ was spin-coated in air at $4000{\\mathrm{r.p.m}}$ . for $30\\mathrm{{s}}$ , followed by baking at $150^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ in air. The substrates were then transferred into a nitrogen-filled glovebox $_{<0.1}$ ppm $\\mathrm{H}_{2}\\mathrm{O},<0.1\\mathrm{ppm}\\mathrm{O}_{2};$ . PVK (4 $\\mathrm{mg}\\mathrm{mL}^{-1}$ in chlorobenzene) was deposited at $3000{\\mathrm{r.p.m}}$ . followed by thermal annealing at $150^{\\circ}\\mathrm{C}$ for $10\\mathrm{min}$ . Next, a thin layer of PVP $(2.0\\mathrm{mg}\\mathrm{mL}^{-1}$ in isopropyl alcohol (IPA)) was deposited at $3000{\\mathrm{r.p.m}}$ . and baked at $100^{\\circ}\\mathrm{C}$ for $5\\mathrm{min}$ . After cooling down to room temperature, the perovskite solutions with varying bromide/chloride ratios were deposited at $3000{\\mathrm{r.p.m}}$ . Directly after spin-coating, the films were put in an unsealed $\\boldsymbol{\\infty}60\\mathrm{mm}$ petri-dish (with lid) at room temperature, where $20\\upmu\\mathrm{l}$ of dimethylformamide had been dropped $10\\mathrm{min}$ prior to the film placement. After $20\\mathrm{min}$ of vapour assisted crystallisation (VAC) treatment, the films were annealed at $80^{\\circ}\\mathrm{C}$ for $8\\mathrm{{min}}$ . For low-dimensional perovskite films with mixed halides, the treatment duration is $10\\mathrm{min}$ and the annealing condition is $80^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ . Finally, the electron transport layer TPBi and top contacts LiF/Al $\\mathrm{{.1nm/100nm}}$ ) were deposited by thermal evaporation through shadow masks at a base pressure of ${\\sim}10^{-7}$ torr. The device structure for single hole devices in Supplementary Fig. 6 is $\\mathrm{ITO/NiO_{x}}$ or not/PVK/molybdenum oxide $(\\mathrm{MoO}_{3})$ (7 $\\mathrm{{nm})/\\mathrm{{Au}}}$ . The device area was $7.25\\:\\mathrm{mm}^{-2}$ . \n\nPeLED characterization. All PeLED device characterizations were performed at room temperature in a nitrogen-filled glovebox without encapsulation. A Keithley 2400 source-meter and a fibre integration sphere (FOIS-1) coupled with a QE Pro spectrometer (Ocean Optics) were utilized. The absolute radiance was calibrated by a standard Vis–NIR light source (HL-3P-INT-CAL plus, Ocean Optics). The PeLED devices were measured on top of the integration sphere and only forward light emission can be collected. The devices were swept from zero bias to forward bias with a step voltage of $0.05\\mathrm{V}$ , lasting for $100\\mathrm{ms}$ at each voltage step for stabilisation. The sweep duration from 1 to $7\\mathrm{V}$ is $70\\mathrm{sec}$ (with a scan rate of $86\\mathrm{mV}$ $S^{-1}$ ). The EQE and spectral evolution with time was measured using the same system. \n\nPerovskite film characterization. Top-view scanning electron microscope (SEM) images were tested by LEO 1550 Gemini. Steady-state PL spectra of the perovskite films were recorded by a fluorescent spectrophotometer (F-4600, HITACHI) with a 200 W Xe lamp as an excitation source. UV–Vis absorbance spectra were collected using a PerkinElmer model Lambda 900. X-ray diffraction patterns were measured using a Panalytical X’Pert Pro with an X-ray tube (Cu Kα, $\\lambda=1.5406\\mathrm{\\AA}$ ). \n\nX-ray photoelectron spectroscopy (XPS) tests were performed by a Scienta ESCA 200 spectrometer in ultrahigh vacuum $(\\sim1\\times10^{-10}\\mathrm{mbar})$ with a monochromatic Al (Kɑ) X-ray source providing photons with $1,486.6\\mathrm{eV}$ The experimental was set so that the full-width at half-maximum of clean Au 4f 7/2 line (at the binding energy of $84.00\\mathrm{eV},$ was $0.65\\mathrm{eV}$ . All spectra were characterized at a photoelectron take-off angle of $0^{\\circ}$ . Ultraviolet photoelectron spectroscopy (UPS) was carried out using a Kratos AXIS Supra on perovskite samples spun-cast on $\\mathrm{ITO/NiO_{x}/P V K/P V P}$ . He I $(21.22\\mathrm{eV})$ radiation was generated from a helium discharge lamp. Samples were biased at $9.1\\mathrm{V}$ . \n\nIn-situ PL of the crystallisation process was collected using the integrating sphere and the QE Pro spectrometer as described above, and a $365\\mathrm{nm}$ UV laser as excitation source. In-situ transmittance tests were performed using the same spectrometer but with a solar simulator (AM 1.5G) as the light source. A ND filter was used to decrease the light intensity. The systems were illustrated in Supplementary Fig. 21. \n\nTime-correlated single photon counting (TCSPC) measurements were carried out by using an Edinburgh Instruments FL1000 with a $405\\mathrm{nm}$ pulsed picosecond laser (EPL-405). Fluence-dependent PLQY was measured using a $405\\mathrm{nm}$ continuous wave laser, an integrating sphere and the same spectrometer. The perovskite films were deposited on $\\mathrm{ITO/NiO_{x}/P V K/P V P}$ substrates under identical conditions as for the PeLEDs, and encapsulated using glass slides and UVcurable resin. \n\nGrazing-incidence wide-angle X-ray scattering (GIWAXS) was recorded in Shanghai Synchrotron Radiation Facility. The diffraction patterns were collected by two dimensional MarCCD 225 detector with $234\\mathrm{mm}$ from samples to the detector. All the samples were protected with $\\Nu_{2}$ gas during the measurements. To assure the diffraction intensity, an exposure time of 15 s was adopted with an incidence angle of $0.5^{\\circ}$ , and the wavelength of the X-ray was $1.24\\mathring{\\mathrm{A}}$ $\\mathrm{10~KeV})$ . For all these tests, the perovskite films were deposited on ITO/NiO $_\\mathrm{x}/$ PVK/PVP substrates under identical conditions as device fabrication. \n\nScanning transmission electron microscopy (STEM) and energy-dispersive Xray spectroscopy (EDX). The STEM samples were fabricated by using the FEI Focused Ion Beam (FIB) system (Helios Nanolab 600i). A FEI Titan-G2 Cs-corrected transmission electron microscope with $300\\mathrm{KV}$ accelerating voltage was used to get the high angle angular dark field (HAADF) images of the samples. The STEM elemental mapping images were collected by four silicon drift windowless detectors (Super-EDX) in the FEI Titan-G2 Cs-corrected transmission electron microscope. The energy resolution of the Super-EDX was $137\\mathrm{eV}$ \n\nTransient absorption. A femtosecond oscillator (Mai Tai, Spectra Physics) is used as a seed laser for a regenerative amplifier (Spitfire XP Pro, Spectra Physics) which generates well collimated beam of femtosecond pulses ( $800\\mathrm{nm}$ , 80 fs pulse duration, $1\\mathrm{kHz}$ repetition rate). The second harmonic generated by a BBO crystal was used as pump $\\mathrm{400nm}$ ). White light continuum (WLC) as the probe was produced by focusing the ${800}\\mathrm{nm}$ fs pulse on a thin $\\mathrm{CaF}_{2}$ plate. Polarization between the pump and probe was set to the magic angle $(54.7^{\\circ})$ . Both pump and probe pulses are monitored to compensate for the laser fluctuations during the measurements. \n\nAdmittance spectroscopy. For the defect studies, we used a setup consisting of a Zurich Instruments MFLI lock-in amplifier with MF-IA and MF-MD options, a Keysight Technologies 33600A function generator and a cryo probe station Janis ST500 with a Lakeshore 336 temperature controller. For determining the ion signature using admittance spectroscopy, we varied the sample temperature from 200 K to $350\\mathrm{K}$ in 5 K steps, controlled accurately within $0.01\\mathrm{K}$ and using liquid nitrogen for cooling. The capacitance in term of a $\\mathbf{C}\\parallel\\mathbf{R}$ equivalence model was measured by applying an ac voltage with amplitude of $V_{\\mathrm{ac}}=20\\:\\mathrm{mV}$ and varying the angular frequency from $0.6\\mathrm{Hz}$ to $3.2\\mathrm{MHz}$ . The rates $e_{\\mathrm{t}}$ are obtained from the peak maxima of the derivative of the capacitance. These rates are linked to the diffusion coefficient $D$ in terms of the underlying hopping process of the mobile ions48,49, \n\n$$\ne_{\\mathrm{t}}=\\frac{e^{2}N_{\\mathrm{eff}}D}{k_{\\mathrm{B}}T\\varepsilon_{0}\\varepsilon_{\\mathrm{R}}},\n$$ \n\nwhere $N_{\\mathrm{eff}}$ refers to the effective doping density, $e$ is the elementary charge, $k_{\\mathrm{B}}$ is the Boltzmann constant, $T$ the temperature, $\\scriptstyle{\\varepsilon_{0}}$ the dielectric constant and $\\varepsilon_{\\mathrm{R}}$ the relative permittivity. For the calculation of $D_{300\\mathrm{K}},$ we used a dielectric permittivity of $19.2^{5\\dot{0}}$ . Since ion migration is a thermally activated process, the diffusion coefficient depends on the temperature, \n\n$$\nD=D_{0}e x p\\Bigg(-\\frac{E_{A}}{k_{B}T}\\Bigg)\n$$ \n\nwith the activation energy for ion migration $E_{\\mathrm{A}}$ and the diffusion coefficient at infinite temperatures $D_{0}$ . Subsequently, $E_{\\mathrm{A}}$ and $D_{0}$ can be extracted from the slope and the cross section with the emission rate axis using Eqs. (1) and (2). By taking into account the surface polarization caused by the accumulation of mobile ions at the interfaces of the perovskite layer, the ion concentration $N_{\\mathrm{i}}$ is determined $\\mathsf{a s}^{51}$ , \n\n$$\nN_{\\mathrm{i}}={\\frac{k_{\\mathrm{B}}T\\Delta C^{2}}{e^{2}\\varepsilon_{0}\\varepsilon_{\\mathrm{R}}}}\n$$ \n\nHere, ΔC refers to the capacitance step in the admittance spectra of the contributing ions. \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. \n\nReceived: 14 October 2020; Accepted: 9 December 2020; Published online: 13 January 2021 \n\n# References \n\n1. Zhu, M. & Yang, C. Blue fluorescent emitters: design tactics and applications in organic light-emitting diodes. Chem. Soc. Rev. 42, 4963–4976 (2013). \n2. Tan, Z. K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n3. Cao, Y. et al. Perovskite light-emitting diodes based on spontaneously formed submicrometre-scale structures. Nature 562, 249–253 (2018). \n4. Lin, K. et al. Perovskite light-emitting diodes with external quantum efficiency exceeding 20 per cent. Nature 562, 245–248 (2018). \n5. Xu, W. et al. Rational molecular passivation for high-performance perovskite light-emitting diodes. Nat. Photon. 13, 418–424 (2019). \n6. Chiba, T. et al. Anion-exchange red perovskite quantum dots with ammonium iodine salts for highly efficient light-emitting devices. Nat. Photon. 12, 681–687 (2018). \n7. Zhao, B. et al. High-efficiency perovskite–polymer bulk heterostructure lightemitting diodes. Nat. Photon. 12, 783–789 (2018). \n8. Yuan, S. et al. Optimization of low-dimensional components of quasi-2D perovskite films for deep-blue light-emitting diodes. Adv. Mater. 31, 1904319 (2019). \n9. Lu, M. et al. Metal halide perovskite light‐emitting devices: Promising technology for next‐generation displays. Adv. Funct. Mater. 29, 1902008 (2019). \n10. Liu, X. et al. Metal halide perovskites for light-emitting diodes. Nat. Mater. 20, 10–21 (2021). \n11. Liu, Y. et al. Efficient blue light-emitting diodes based on quantum-confined bromide perovskite nanostructures. Nat. Photon. 13, 760–764 (2019). \n12. Jiang, Y. et al. Spectra stable blue perovskite light-emitting diodes. Nat. Commun. 10, 1868 (2019). \n13. Xing, J. et al. Color-stable highly luminescent sky-blue perovskite lightemitting diodes. Nat. Commun. 9, 3541 (2018). \n14. Dong, Y. et al. Bipolar-shell resurfacing for blue leds based on strongly confined perovskite quantum dots. Nat. Nanotechnol. 15, 668–674 (2020). \n15. Protesescu, L. et al. Nanocrystals of cesium lead halide perovskites $(\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3},$ $\\mathrm{X=Cl}.$ , Br, and I): novel optoelectronic materials showing bright emission with wide color gamut. Nano Lett. 15, 3692–3696 (2015). \n16. Li, G. et al. Highly efficient perovskite nanocrystal light-emitting diodes enabled by a universal crosslinking method. Adv. Mater. 28, 3528–3534 (2016). \n17. Xiao, Z. et al. Mixed-halide perovskites with stabilized bandgaps. Nano Lett. 17, 6863–6869 (2017). \n18. Hoke, E. T. et al. Reversible photo-induced trap formation in mixed-halide hybrid perovskites for photovoltaics. Chem. Sci. 6, 613–617 (2015). \n19. Nenon, D. P. et al. Design principles for trap-free $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{X}}_{3}$ nanocrystals: enumerating and eliminating surface halide vacancies with softer lewis bases. J. Am. Chem. Soc. 140, 17760–17772 (2018). \n20. Zheng, X. et al. Chlorine vacancy passivation in mixed halide perovskite quantum dots by organic pseudohalides enables efficient Rec. 2020 blue lightemitting diodes. ACS Energy Lett. 5, 793–798 (2020). \n21. Li, Z. et al. Modulation of recombination zone position for quasi-twodimensional blue perovskite light-emitting diodes with efficiency exceeding $5\\%$ . Nat. Commun. 10, 1027 (2019). \n22. Vashishtha, P., Ng, M., Shivarudraiah, S. B. & Halpert, J. E. High efficiency blue and green light-emitting diodes using ruddlesden–popper inorganic mixed halide perovskites with butylammonium interlayers. Chem. Mater. 31, 83–89 (2018). \n23. Abdi-Jalebi, M. et al. Maximizing and stabilizing luminescence from halide perovskites with potassium passivation. Nature 555, 497–501 (2018). \n24. Braly, I. L. et al. Hybrid perovskite films approaching the radiative limit with over $90\\%$ photoluminescence quantum efficiency. Nat. Photon. 12, 355–361 (2018). \n25. Wang, Q. et al. Efficient sky-blue perovskite light-emitting diodes via photoluminescence enhancement. Nat. Commun. 10, 5633 (2019). \n26. Niu, Y. H. et al. Thermally crosslinked hole-transporting layers for cascade hole-injection and effective electron-blocking/exciton-confinement in phosphorescent polymer light-emitting diodes. Appl. Phys. Lett. 88, 093505 (2006). \n27. Wright, A. D. et al. Electron-phonon coupling in hybrid lead halide perovskites. Nat. Commun. 7, 11755 (2016). \n28. Zhao, L. et al. Thermal management enables bright and stable perovskite lightemitting diodes. Adv. Mater. 32, 2000752 (2020). \n29. Braly, I. L. et al. Current-induced phase segregation in mixed halide hybrid perovskites and its impact on two-terminal tandem solar cell design. ACS Energy Lett. 2, 1841–1847 (2017). \n30. Kuno, M. & Brennan, M. C. What exactly causes light-induced halide segregation in mixed-halide perovskites? Matter 2, 21–23 (2020). \n31. Bischak, C. G. et al. Origin of reversible photoinduced phase separation in hybrid perovskites. Nano Lett. 17, 1028–1033 (2017). \n32. Draguta, S. et al. Rationalizing the light-induced phase separation of mixed halide organic-inorganic perovskites. Nat. Commun. 8, 200 (2017). \n33. Brennan, M. C., Draguta, S., Kamat, P. V. & Kuno, M. Light-induced anion phase segregation in mixed halide perovskites. ACS Energy Lett. 3, 204–213 (2017). \n34. Barker, A. J. et al. Defect-assisted photoinduced halide segregation in mixedhalide perovskite thin films. ACS Energy Lett. 2, 1416–1424 (2017). \n35. Gratia, P. et al. Intrinsic halide segregation at nanometer scale determines the high efficiency of mixed cation/mixed halide perovskite solar cells. J. Am. Chem. Soc. 138, 15821–15824 (2016). \n36. Tennyson, E. M., Doherty, T. A. S. & Stranks, S. D. Heterogeneity at multiple length scales in halide perovskite semiconductors. Nat. Rev. Mater. 4, 573–587 (2019). \n37. Brivio, F., Caetano, C. & Walsh, A. Thermodynamic origin of photoinstability in the $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Pb}(\\mathrm{I}_{1-\\mathrm{x}}\\mathrm{Br}_{\\mathrm{x}})_{3}$ hybrid halide perovskite alloy. J. Phys. Chem. Lett. 7, 1083–1087 (2016). \n38. Zhu, C. et al. Strain engineering in perovskite solar cells and its impacts on carrier dynamics. Nat. Commun. 10, 815 (2019). \n39. Wang, X. et al. Suppressed phase separation of mixed-halide perovskites confined in endotaxial matrices. Nat. Commun. 10, 695 (2019). \n40. Reichert, S. et al. Ionic-defect distribution revealed by improved evaluation of deep-level transient spectroscopy on perovskite solar cells. Phys. Rev. Appl. 13, 034018 (2020). \n41. Awni, R. A. et al. Influence of charge transport layers on capacitance measured in halide perovskite solar cells. Joule 4, 644–657 (2020). \n42. Doherty, T. A. S. et al. Performance-limiting nanoscale trap clusters at grain junctions in halide perovskites. Nature 580, 360–366 (2020). \n43. Jariwala, S. et al. Local crystal misorientation influences non-radiative recombination in halide perovskites. Joule 3, 3048–3060 (2019). \n44. Wu, C. et al. Improved performance and stability of all-inorganic perovskite light-emitting diodes by antisolvent vapour treatment. Adv. Funct. Mater. 27, 1700338 (2017). \n45. Saliba, M. et al. Incorporation of rubidium cations into perovskite solar cells improves photovoltaic performance. Science 354, 206–209 (2016). \n46. Abdi-Jalebi, M. et al. Potassium- and rubidium-passivated alloyed perovskite films: Optoelectronic properties and moisture stability. ACS Energy Lett. 3, 2671–2678 (2018). \n47. Zhao, L. et al. Redox chemistry dominates the degradation and decomposition of metal halide perovskite optoelectronic devices. ACS Energy Lett. 1, 595–602 (2016). \n48. Heiser, T. & Mesli, A. Determination of the copper diffusion coefficient in silicon from transient ion-drift. Appl. Phys. A 57, 325–328 (1993). \n49. Futscher, M. H. et al. Quantification of ion migration in $\\mathrm{CH_{3}N H_{3}P b I_{3}}$ perovskite solar cells by transient capacitance measurements. Mater. Horiz. 6, 1497–1503 (2019). \n50. Schlaus, A. P. et al. How lasing happens in $\\mathrm{Cs}\\mathrm{Pb}{\\mathrm{Br}}_{3}$ perovskite nanowires. Nat. Commun. 10, 265 (2019). \n51. Almora, O. et al. Capacitive dark currents, hysteresis, and electrode polarization in lead halide perovskite solar cells. J. Phys. Chem. Lett. 6, 1645–1652 (2015). \n\n# Acknowledgements \n\nWe thank D. Egger, X. Zhu, C. Yin, H. Tian and J. Li for valuable discussions, and X. Liu for help with the XPS measurements. We acknowledge the support from the ERC Starting Grant (No. 717026), the Swedish Energy Agency Energimyndigheten (No. 48758-1 and 44651-1), Swedish Research Council VR, NanoLund and the Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linköping University (Faculty Grant SFO-Mat-LiU No. 2009-00971). C.D. and S.R. acknowledge financial support by the Bundesministerium für Bildung und Forschung (BMBF Hyper project, contract no. 03SF0514C) and the DFG (no. DE 830/22-1) within the framework of SPP 2196 programme. Y. L. acknowledge financial support from the National Key Research and Development Program of China (2016YFB0700700), the National Natural Science Foundation of China (11704015, 51621003, 12074016), the Scientific Research Key Program of Beijing Municipal Commission of Education, China (KZ201310005002), and the Beijing Innovation Team Building Program, China (IDHT20190503). F.G. is a Wallenberg Academy Fellow. \n\n# Author contributions \n\nF.G. and W.X. conceived the idea and supervised the project; M.K. performed the experiments and analysed the data; Z.Y. developed Rb-doped devices and lowdimensional perovskite-based devices; S.R. performed admittance spectroscopy and analysed the data under the supervision of C.D.; X.L. and P.T. contributed to device fabrication and measurements; W.L. performed transient absorption under the supervision of K.Z. and T.P.; Z.Z. performed transmission electron microscopy under the supervision of Y.L.; R.Z. and G.Z. performed GIWAXS measurements and analysed the data; C.B., S.B., L.D. and R.F. contributed the interpretation of results; M.K., W.X. and F. G. wrote the manuscript; S.B. provided revisions to the manuscript; all authors discussed the results and commented on the manuscript. \n\n# Funding \n\nOpen Access funding provided by Linköping University Library. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information is available for this paper at https://doi.org/10.1038/s41467- 020-20582-6. \n\nCorrespondence and requests for materials should be addressed to W.X. or F.G. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41467-021-21527-3", + "DOI": "10.1038/s41467-021-21527-3", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-21527-3", + "Relative Dir Path": "mds/10.1038_s41467-021-21527-3", + "Article Title": "Rational design of isostructural 2D porphyrin-based covalent organic frameworks for tunable photocatalytic hydrogen evolution", + "Authors": "Chen, RF; Wang, Y; Ma, Y; Mal, A; Gao, XY; Gao, L; Qiao, LJ; Li, XB; Wu, LZ; Wang, C", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Covalent organic frameworks have recently gained increasing attention in photocatalytic hydrogen generation from water. However, their structure-property-activity relationship, which should be beneficial for the structural design, is still far-away explored. Herein, we report the designed synthesis of four isostructural porphyrinic two-dimensional covalent organic frameworks (MPor-DETH-COF, M=H-2, Co, Ni, Zn) and their photocatalytic activity in hydrogen generation. Our results clearly show that all four covalent organic frameworks adopt AA stacking structures, with high crystallinity and large surface area. Interestingly, the incorporation of different transition metals into the porphyrin rings can rationally tune the photocatalytic hydrogen evolution rate of corresponding covalent organic frameworks, with the order of CoPor-DETH-COF", + "Times Cited, WoS Core": 395, + "Times Cited, All Databases": 403, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000626168500010", + "Markdown": "# Rational design of isostructural 2D porphyrin-based covalent organic frameworks for tunable photocatalytic hydrogen evolution \n\nRufan Chen1,5, Yang Wang2,3,5, Yuan Ma $\\textcircled{1}$ 4,5, Arindam Mal $\\textcircled{1}$ 1, Xiao-Ya Gao2,3, Lei Gao 4, Lijie Qiao4, Xu-Bing $\\mathsf{L i}^{2,3\\boxtimes},$ Li-Zhu Wu $\\textcircled{1}$ 2,3✉ & Cheng Wang 1✉ \n\nCovalent organic frameworks have recently gained increasing attention in photocatalytic hydrogen generation from water. However, their structure-property-activity relationship, which should be beneficial for the structural design, is still far-away explored. Herein, we report the designed synthesis of four isostructural porphyrinic two-dimensional covalent organic frameworks (MPor-DETH-COF, ${\\sf M}={\\sf H}_{2},{\\sf C o},{\\sf N i},{\\sf Z n})$ and their photocatalytic activity in hydrogen generation. Our results clearly show that all four covalent organic frameworks adopt AA stacking structures, with high crystallinity and large surface area. Interestingly, the incorporation of different transition metals into the porphyrin rings can rationally tune the photocatalytic hydrogen evolution rate of corresponding covalent organic frameworks, with the order of CoPor-DETH-COF < H2Por-DETH-COF $\\angle$ NiPor-DETH-COF $<$ ZnPor-DETH-COF. Based on the detailed experiments and calculations, this tunable performance can be mainly explained by their tailored charge-carrier dynamics via molecular engineering. This study not only represents a simple and effective way for efficient tuning of the photocatalytic hydrogen evolution activities of covalent organic frameworks at molecular level, but also provides valuable insight on the structure design of covalent organic frameworks for better photocatalysis. \n\novalent organic frameworks (COFs) are a novel class of porous crystalline polymer that enables the precise integration of molecular building blocks into extended twodimensional or three-dimensional (2D or 3D) structures through covalent bonds1–5. Owing to their low density, high porosity, structural periodicity, and modular functionality, COFs have gained intensive attention and found promising applications in gas adsorption and separation6–10, catalysis11–14, sensing15–18, optoelectronics19–22, and energy storage23–26. From the structural viewpoint, the most important feature of 2D COFs differing from their 3D analogues and most organic systems is that they can offer a unique platform for constructing periodic columnar π arrays27. Accordingly, 2D COFs possess unique preorganized transport of long-lived photoexcited states and show high charge carrier mobility, which will allow them to work as effective heterogeneous photocatalysts. In addition, the crystalline nature of 2D COFs can facilitate the establishment of structure–property–activity relationship and thus providing insights into photocatalytic processes. Therefore, 2D COFs have received growing interests in photocatalysis over the past few years, ranging from chemical transformation28–33 to solar fuel production34–48. \n\nAmong all these tested systems, photocatalytic hydrogen evolution reaction (HER) from water is regarded as one of the most attractive ways to meet the increasing demands of clean and sustainable energy49. In 2014, Lotsch and co-workers reported the first example of utilizing 2D COF to produce $\\mathrm{H}_{2}$ in the presence of metallic platinum under visible light irradiation34. Since this pioneer work, several 2D COFs bearing different photoelectric units have been successfully constructed and found interesting potential in photocatalytic hydrogen evolution34–43. However, although continuing efforts are going on developing new 2D COFs for photocatalytic HER, the rational tuning of their structures and photophysical properties for maximizing the hydrogen evolution efficiency still needs to be further clarified. In an initial study, Lotsch et al. reported several 2D COFs with different numbers of nitrogen atoms in the central phenyl $\\mathrm{ring}^{35}$ , which showed controllable photocatalytic hydrogen evolution efficiencies. Unfortunately, as the tailoring of their photocatalytic performance lies on a multitude of variables (e.g., crystallinity, optoelectronic factors, etc.), it is very difficult to determine the individual contribution that is required for further modification. Therefore, it is highly demanded to construct isostructural 2D COFs with tunable optoelectronic properties and further explore their structure–property–activity relationship in photocatalytic HER from a molecular level. \n\nPorphyrin and its derivatives, a kind of conjugated $\\pi$ -electron macrocycles with unique photophysical and redox properties50,51, have been used to construct 2D COFs for heterogeneous photocatalysis28,29,46–48. In principle, the incorporation of different metal ions into porphyrin units may rationally tune their photophysical and electronic properties, which can thus affect the photocatalytic activity of corresponding COFs. With this consideration in mind, we report herein the synthesis and characterization of four isostructural hydrazone-linked 2D porphyrinic COFs (Fig. 1), named as MPor-DETH-COF ${\\mathrm{(M}}={\\mathrm{H}}_{2} $ , Co, Ni, Zn). Our results clearly demonstrate that these four COFs have high crystallinity and surface area, and the incorporation of different transition metal ions into porphyrin rings apparently influences the charge-carrier dynamics properties of corresponding COFs. When irradiated with visible light in the presence of $\\bar{\\mathrm{H}}_{2}\\mathrm{PtCl}_{6}$ and triethanolamine (TEOA), all MPor-DETH-COFs can continually produce hydrogen from water while retaining the framework. More importantly, these four COFs show rationally tunable activity toward photocatalytic hydrogen evolution with the order of CoPor-DETH-COF $25\\upmu\\mathrm{mol}$ $\\dot{\\mathrm{\\bf~g}}^{-1}\\dot{\\mathrm{\\bf~h}}^{-1})<\\mathrm{\\bf~H}_{2}\\mathrm{\\bfPor}$ -DETH-COF $(80\\mathrm{\\textmumol\\mathrm{\\g}^{-1}\\ h^{-1}})$ $\\angle{\\angle}$ NiPor \n\nDETH-COF $(211\\mathrm{\\{\\mumol\\g^{-1}\\ h^{-1}})$ NiPor-DETH$\\mathrm{COF}>\\mathrm{H}_{2}\\mathrm{Por}$ -DETH-COF $>$ CoPor-DETH-COF. Accordingly, ZnPor-DETH-COF has the most favorable excited-state charge separation, which may in turn be good for the utilization of excited electrons and holes in corresponding photoredox reactions. We further conducted photocurrent tests for all \n\nMPor-DETH-COFs to evaluate their photoelectric responses, by coating them on indium-tin oxide (ITO) substrates under same conditions (i.e., same amount, identical electrode area, etc.). The chopped photocurrent–time (I–t) curves of these COFs based photoelectrodes were presented in Fig. 3d, and their photocurrent responses also showed an order of ZnPor-DETH-COF $>$ NiPorDETH- ${\\mathrm{.COF}}>{\\mathrm{H}}_{2}{\\mathrm{P}}{\\mathrm{c}}$ r-DETH-COF $>$ CoPor-DETH-COF. This result is consistent with the trend of emission decays, which confirms again the most efficient charge carrier transport in ZnPor-DETH-COF. Therefore, the incorporation of different metal ions into porphyrin precursors can influence the chargecarrier dynamics of the resulting COFs. \n\nPhotocatalytic hydrogen evolution. Encouraging by above results, we then evaluated the photocatalytic performance of all MPor-DETH-COFs toward hydrogen evolution from water under visible light irradiation (Xe-lamp 300 W, $\\lambda>400\\mathrm{nm},$ ) in the presence of $\\mathrm{H}_{2}\\mathrm{\\bar{P}t C l}_{6}$ and triethanolamine (TEOA), where $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ was employed as the precursor of co-catalysts and TEOA worked as the sacrificial reagent. Control experiments confirmed that visible light, TEOA, $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ , and MPor-DETH-COFs were indispensable for effective hydrogen generation (Supplementary Fig. 27a–d). Moreover, $\\mathrm{H}_{2}$ Por-DETH-COF could not produce hydrogen gas when the incident wavelength was above $500\\mathrm{nm}$ (Supplementary Fig. $27\\mathrm{e}$ ), indicating that B-band absorption of porphyrin ring mainly contributes to the photoredox reactions. Notably, all four COFs could constantly evolve hydrogen gas during $10\\mathrm{{h}}$ light irradiation (Fig. 4a and Supplementary Fig. 28). The average rates of hydrogen evolution were quantified as 80 μmol $\\mathrm{~g^{-1}~h^{-1}}$ , $25~{\\upmu\\mathrm{mol}}~\\mathrm{g}^{-1}~\\mathrm{h}^{-1}$ , $211\\ \\upmu{\\mathrm{mol}}\\ \\mathrm{g}^{-1}\\ \\mathrm{h}^{-1}$ , and 413 $\\mathrm{\\dot{\\upmumol}{\\mathrm{\\Large~\\bf~g^{-1}~}}h^{-1}}$ for $\\mathrm{H}_{2}\\mathrm{Por}$ -DETH-COF, CoPor-DETH-COF, \n\n![](images/a928fbbabe41eaca5acf6d70d8229e135831e09e8dab75c50fb74c515797d733.jpg) \nFig. 4 Hydrogen production rate. a Time dependent ${\\sf H}_{2}$ photogeneration using visible light for ${\\sf H}_{2}{\\sf P}\\circ{\\sf r}$ -DETH-COF, CoPor-DETH-COF, NiPor-DETH-COF and ZnPor-DETH-COF $2.5\\mathsf{m g}$ catalyst in $5\\mathsf{m L}$ phosphate buffer solution, $2.5\\upmu\\up L$ (8 wt% ${\\sf H}_{2}{\\sf P t C l}_{6})$ , $50\\upmu\\upiota$ TEOA, $\\lambda>400\\mathsf{n m}300$ W Xe lamp). b Long-term ${\\sf H}_{2}$ production using visible light for ZnPor-DETH-COF for $120{\\mathsf{h}}$ (recycled every $40\\mathsf{h}$ for three times). \n\nNiPor-DETH-COF and ZnPor-DETH-COF, respectively. It should be emphasized that, this trend of hydrogen evolution efficiency matches well with the transient emission decays and chopped photocurrent tests of the four COFs, indicating the important factor of charge-carrier dynamics. The apparent quantum efficiency (AQE) of ZnPor-DETH-COF towards photocatalytic hydrogen evolution was measured as $0.063\\%$ at 450 nm by taking TEOA as the sacrificial reagent (see details in Supplementary Fig. 29). By optimizing the $\\mathrm{Pt}$ content and the type of sacrificial reagent, the hydrogen evolution amount of ZnPor-DETH-COF could be further improved (Supplementary Fig. 30), and AQE was determined to be $0.32\\%$ . \n\nFrom TEM characterization, Pt nanoparticles (NPs) with similar morphology that identified by the characteristic crystal spacing $(2.2{\\overset{\\cdot}{\\mathrm{A}}})$ for (111) lattice plane were formed in situ on four COFs with an average size of $3.5\\mathrm{nm}$ under light irradiation (Supplementary Figs. 32 and 33), further confirming the varied HER activity was a result of the different photosensitization effect of the four COFs. From PXRD experiments, the crystal structures of all four COFs were well-retained after photocatalytic HER (Supplementary Figs. 34−37). In addition, these COFs showed excellent durability of photocatalytic hydrogen evolution. For example, the hydrogen production rate of ZnPor-DETH-COF is preserved even after $120\\mathrm{h}$ irradiation (Fig. 4b). \n\nIn order to confirm the durability of electronic and chemical structures for the metal ion centers in photocatalysis process, we then performed $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy (XAS) measurement of three metalloporphyrin-based COFs (CoPor-DETHCOF, NiPor-DETH-COF, and ZnPor-DETH-COF) before and after hydrogen evolution. In the E-space curves, the M K-edge absorption of these three COFs remained unchanged during the reaction (Supplementary Fig. 38), confirming the invariability of the electronic configuration of metal centers. From Fourier transform $R$ -space spectra (Fig. 5a–c), these three COFs still showed two main coordinated peaks after photocatalysis, which could be attributed to the unaltered primary $\\mathbf{M}{-}\\mathbf{N}$ bond and secondary $\\scriptstyle{\\mathrm{{M-C}}}$ coordination layer. In addition, their coordination numbers (CNs) of $\\mathbf{M}{-}\\mathbf{N}$ and $\\scriptstyle{\\mathrm{{M-C}}}$ were determined as ${\\sim}4$ and $^{\\sim8}$ (see fitting details in Supplementary Table 7), strongly indicating the retained metalloporphyrin structures. Moreover, continuous Cauchy wavelet transform (CCWT) analysis displayed two intensity maximums, which were totally different from the standard $\\mathrm{Co},\\mathrm{Ni},$ and $Z\\mathrm{n}$ foils (Fig. 5d–l). Based on XAS $R$ -space and CCWT analysis, we believe the single-atom characteristic of metal ion centers in all of these three COFs are well retained, which can clearly rule out the formation of metal clusters that might serve as catalytic center in the process of hydrogen photogeneration. \n\nKinetic analysis of photocatalytic processes. As the hydrogen evolution was performed in alkaline condition, the reductive halfreaction occurs via following reaction: $2\\mathrm{H}_{2}\\mathrm{O}+2\\mathrm{e}^{-}\\rightarrow2\\mathrm{OH}^{-}+$ $\\mathrm{H}_{2}$ . We calculated the interaction between $_{\\mathrm{H}_{2}\\mathrm{O}}$ and metalloporphyrin-based COFs (CoPor-DETH-COF, NiPorDETH-COF, and ZnPor-DETH-COF) by density functional theory (DFT) (see models in Supplementary Fig. 41). Accordingly, the $\\mathrm{H}_{2}\\mathrm{O}$ absorption energy change $(\\Delta E)$ at CoPor-DETHCOF, NiPor-DETH-COF, and ZnPor-DETH-COF is 0.554, 0.847, and $0.659\\mathrm{eV}$ , respectively (Supplementary Fig. 42). The enormously positive values strongly indicate the adsorption and activation of $_\\mathrm{H}_{2}\\mathrm{O}$ molecules at the metal centers is unfavorable56, which matches well with the negligible hydrogen production activity in the absence of $\\mathrm{Pt}$ -cocatalysts (Supplementary Fig. 27). Therefore, it can be concluded that these COFs are light absorbers and can be photoexcited to produce electron-hole pairs, and the electrons migrate to the photo-deposited Pt NPs for hydrogen evolution while holes are consumed by sacrificial reagents. The concrete changes in the excited state and the whole catalytic processes can be found in Supplementary Figs. 39 and 40. \n\nThen, the different photocalytical $\\mathrm{H}_{2}$ generation efficiency of MPor-DETH-COFs was studied by DFT calculations. As shown in Fig. 6 and Supplementary Figs. 43 and 44, the electron density is trapped within the porphyrin cores, thus lowering the in-plane charge transport. In consideration of their AA stacking structures, the out-of-plane charge carrier migration of these four COFs might become the main pathway. To validate this point, the projected density of states (PDOS) for their monolayer and bilayer structures are calculated (Supplementary Fig. 45). Compared with monolayer structures, the band gaps of bilayer counterparties are narrowed ${\\sim}0.2\\mathrm{-}0.4\\mathrm{eV}$ due to the interlayer $\\pi-$ $\\pi$ interaction (Supplementary Table 8), indicating the favored interlayer charge carrier migration57. \n\nIn principle, considering the AA stacking structures of MPorDETH-COFs, the macrocycle-on-macrocycle and metal-on-metal channels within porphyrin columns would play vital roles in the kinetics of charge-carrier separation and migration21. Usually, upon light excitation of the porphyrin $\\pi$ -ring, the photogenerated electron migration relies on metal-on-metal channel $[\\mathrm{M_{n}}^{2\\mathrm{n+}}+\\mathrm{e}^{-}\\rightarrow\\mathrm{M_{n}}^{\\mathrm{\\tilde{(}2n-1)+}}$ ( $(n>>1$ , M represents the metal ion)] rather than localized on a specific metal center, while photogenerated holes mainly transfer through macrocycle-onmacrocycle pathway. For $\\mathrm{H}_{2}\\mathrm{P}$ or-DETH-COF, as no metal exists, both electron and hole migration proceed via macrocycle-onmacrocycle pathway (Fig. 6a), which will increase the possibility of charge recombination and thus lead to a short emission lifetime. However, for CoPor-DETH-COF and NiPor-DETH-COF, ligandto-metal charge transfer (LMCT) process can be taken into consideration, since it significantly restrains the hole migration via macrocycle-on-macrocycle channel. Specifically, for CoPor-DETHCOF, LMCT process is preeminent owing to the $3d^{7}$ configuration of $C o^{2+}$ , which suppresses holes migration (Fig. 6 and Supplementary Figs. 43 and 44). As a result, CoPor-DETH-COF showed the worst activity of hydrogen evolution. With the increase of $d$ -electrons $3d^{8}$ for $\\dot{\\mathrm{Ni}}^{2+}$ ), the LMCT process is partially suppressed, and hole transfer ability through macrocycle-onmacrocycle channel will be improved. Finally, in the case of $Z\\mathrm{n}^{2+}$ ion with $3d^{I O}$ configuration, the LMCT process is strictly forbidden (the variation of center metal electrons density from $\\mathrm{Co}^{\\dot{2}+}$ to $Z\\mathrm{n}^{2+}$ can be clearly seen in Fig. 6). Therefore, the holes of ZnPor-DETHCOF can freely migrate via macrocycle-on-macrocycle channel to the surface and the electrons transfer via $Z\\mathrm{n}{\\cdots}Z\\mathrm{n}$ chain, which will result in the long-time charge-separation state. Accordingly, ZnPorDETH-COF demonstrates the highest activity toward photocatalytic hydrogen evolution under the identical conditions. \n\n![](images/59cc3b5476bc658e7459e4566c5cc481278244d8aa28c92fc66766aaee38d96b.jpg) \nFig. 5 XAS analysis. XAS Fourier transform R-space curves of a CoPor-DETH-COF, b NiPor-DETH-COF and c ZnPor-DETH-COF before and after light reaction; CCWT plots of d CoPor-DETH-COF, e NiPor-DETH-COF, and f ZnPor-DETH-COF before reaction; CCWT plots of corresponded metal foil: ${\\pmb g}\\subset{\\joinrel\\subsetneq},$ h Ni, and i $Z\\mathsf{n};$ CCWT plots of corresponded COFs after light reaction: j CoPor-DETH-COF, k NiPor-DETH-COF, and l ZnPor-DETH-COF. \n\n# Discussion \n\nIn summary, in order to explore the structure–property–activity relationship in photocatalytic HER from a molecular level, we have reported the designed synthesis and characterization of four isostructural porphyrinic 2D COFs, which have high crystallinity and large pore surface. Interestingly, by incorporating different transition metals into the porphyrin rings, the photophysical and electronic properties of the porphyrinic COFs are adjusted. More importantly, these COFs showed tunable photocatalytic hydrogen production rate, mainly ascribed to their tailored charge-carrier dynamics via molecular engineering. Consequently, we believe the charge-carrier dynamics of COFs play a very important role in the photocatalytic HER from water. This study not only represents a simple example to efficiently tune the photocatalytic hydrogen evolution activities of COFs at molecular level, but also provides valuable insight on the structure design COFs for better photocatalytic performance in future. The construction of efficient COF-based photocatalysts (e.g., $\\mathrm{CO}_{2}$ reduction46) is undergoing in the lab. \n\n# Methods \n\nSynthesis of ${\\bf H}_{2}\\mathsf{P o r}$ -DETH-COF. A pyrex tube was charged with $\\boldsymbol{p}$ -Por-CHO (16 mg, $0.022\\mathrm{mmol}\\mathrm{\\Omega}$ , DETH $(13.04\\mathrm{mg},0.044\\mathrm{mmol})$ , 1,2-dichlorobenzene $(0.5\\mathrm{mL})$ , butanol $(0.5\\mathrm{mL})$ ) and aqueous acetic acid $(0.5\\mathrm{mL},12\\mathrm{M})$ . After being degassed through three freeze-pump-thaw cycles and then sealed under vacuum, the tube was heated at $120~^{\\circ}\\mathrm{C}$ for 3 days. The resulting precipitate was collected by centrifugation, exhaustively washed by Soxhlet extractions with THF and DCM for $24\\mathrm{h}$ , dried under vacuum at $80~^{\\circ}\\mathrm{C}$ . The $\\mathrm{H}_{2}\\mathrm{Por}$ -DETH-COF was isolated as brown powders in $88\\%$ yield. Elemental analysis: calculated C $(70.92\\%)$ , H $(4.79\\%)$ , N $(13.78\\%)$ and observed C $(69.14\\%)$ ), H $(4.73\\%)$ , N $(13.24\\%)$ . \n\nSynthesis of CoPor-DETH-COF. A pyrex tube was charged with $\\boldsymbol{p}$ -CoPor-CHO (17.23 mg, $0.022\\mathrm{mmol}\\mathrm{\\cdot}$ , DETH $(13.04\\mathrm{mg},0.044\\mathrm{mmol})$ , 1,2-dichlorobenzene $\\mathrm{(0.8~mL)}$ , butanol $\\ensuremath{\\mathrm{\\Delta}}_{:0.2\\ensuremath{\\mathrm{mL}}},$ and aqueous acetic acid $(0.1\\mathrm{mL},3\\mathrm{M}$ ). After being degassed through three freeze-pump-thaw cycles and then sealed under vacuum, the tube was heated at $120^{\\circ}\\mathrm{C}$ for 7 days. The resulting precipitate was collected by centrifugation, exhaustively washed by Soxhlet extractions with THF and DCM for $24\\mathrm{h}$ , dried under vacuum at $80~^{\\circ}\\mathrm{C}.$ . The CoPor-DETH-COF was isolated as dark red powders in $85\\%$ yield. Elemental analysis: calculated C $(67.76\\%)$ ), H $(4.42\\%)$ , N $(13.17\\%)$ and observed C $(66.69\\%)$ ), H $(4.30\\%)$ , N $(12.37\\%)$ . \n\n![](images/f7ecfdab6b1ffce88c7659a8fea3afe5df2f5492f11c6bc930965cea17f83700.jpg) \nFig. 6 LMCT mechanism indicated by DFT calculations. The isosurface of the electron orbitals of blue VBM and magenta CBM (upper panel) and schematic illustrations of the hole-electron transport processes (lower panel) in MPor-DETH-COFs: a ${\\sf H}_{2}{\\sf P}\\circ{\\sf r}$ -DETH-COF; b CoPor-DETH-COF; c NiPorDETH-COF, and d ZnPor-DETH-COF. The balls in different colors represent different atoms: H, white; C, grey; N, blue; Co, olive green; Ni, light blue; Zn, orange. \n\nSynthesis of NiPor-DETH-COF. A pyrex tube was charged with $p$ -NiPor-CHO (17.22 mg, 0.022 mmol), DETH (13.04 mg, $0.044\\mathrm{mmol}$ ), 1,2-dichlorobenzene $(0.5\\mathrm{mL})$ , butanol $(0.5\\mathrm{mL})$ and aqueous acetic acid $(0.1\\mathrm{mL},6\\mathrm{M}^{\\cdot}$ ). After being degassed through three freeze-pump-thaw cycles and then sealed under vacuum, the tube was heated at $120^{\\circ}\\mathrm{C}$ for 7 days. The resulting precipitate was collected by centrifugation, exhaustively washed by Soxhlet extractions with THF and DCM for $24\\mathrm{h}$ , dried under vacuum at $80~^{\\circ}\\mathrm{C}$ . The NiPor-DETH-COF was isolated as red powders in $86\\%$ yield. Elemental analysis: calculated C $(67.77\\%)$ ), H $(4.42\\%)$ , N $(13.17\\%)$ ) and observed C $(66.02\\%)$ ), H $(4.41\\%)$ , N $(12.62\\%)$ ). \n\nSynthesis of ZnPor-DETH-COF. A pyrex tube was charged with $p$ -ZnPor-CHO $\\mathrm{17.38\\mg}$ , $0.022\\mathrm{mmol}$ ), DETH $(13.04\\mathrm{mg},0.044\\mathrm{mmol})$ ), 1,2-dichlorobenzene $\\mathrm{{(0.8~mL)}}$ , butanol $(0.2\\mathrm{mL})$ , and aqueous acetic acid (0.5 mL, 12 M). After being degassed through three freeze-pump-thaw cycles and then sealed under vacuum, the tube was heated at $120^{\\circ}\\mathrm{C}$ for 7 days. The resulting precipitate was collected by centrifugation, exhaustively washed by Soxhlet extractions with THF and DCM for $24\\mathrm{h}$ , dried under vacuum at $80~^{\\circ}\\mathrm{C}$ . The ZnPor-DETH-COF was isolated as green powders in $85\\%$ yield. Elemental analysis: calculated C $(67.42\\%)$ , H $(4.\\dot{4}0\\%)$ , N $(13.10\\%)$ and observed C $(64.96\\%)$ , H $(4.38\\%)$ , N $(12.16\\%)$ ). \n\nPhotocatalysis experiment. The $\\mathrm{H}_{2}$ photogeneration test was performed with a $20~\\mathrm{mL}$ pyrex tube holding MPor-DETH-COF $(2.5\\mathrm{mg})$ , $5\\mathrm{mL}$ phosphate buffer solution $(0.1\\mathrm{M},\\mathrm{pH}=7.0)$ . The suspension was ultrasonicated for $30\\mathrm{min}$ before adding $2.5\\upmu\\mathrm{L}\\ 8\\up w\\upnu\\%\\ \\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ and $50\\upmu\\mathrm{L}$ triethanolamine (TEOA), and then degassing by Ar bubbling for $30\\mathrm{min}$ . Six hundred microliter of $\\mathrm{CH}_{4}$ was injected into the system and functioned as the internal standard for quantitative analysis. Xe lamps $(300\\mathrm{W})$ as light source for testing $\\mathrm{H}_{2}$ evolution performance, and using air fan to keep room temperature of the sample. The generated $\\mathrm{H}_{2}$ gas in the \n\nheadspace of reactor was taken with a gas-tight syringe and measured by using a gas chromatograph (Shimadzu GC2014CAFC/APC) equipped with a thermal conductivity detector and a $5\\textup{\\AA}$ molecular sieves GC column. Ar was used as a carrier gas. \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding author on request. \n\nReceived: 16 June 2020; Accepted: 27 January 2021; Published online: 01 March 2021 \n\n# References \n\n1. Lyle, S. J., Waller, P. J. & Yaghi, O. M. Covalent organic frameworks: organic chemistry extended into two and three dimensions. Trends Chem. 1, 172–184 (2019). \n2. Geng, K. et al. Covalent organic frameworks: design, synthesis, and functions. Chem. Rev. 120, 8814 (2020). \n3. Lohse, M. S. & Bein, T. Covalent organic frameworks: structures, synthesis, and applications. Adv. Funct. Mater. 28, 1705553 (2018). \n4. Segura, J. L., Mancheño, M. J. & Zamora, F. Covalent organic frameworks based on Schiff-base chemistry: synthesis, properties and potential applications. Chem. Soc. Rev. 45, 5635–5671 (2016). \n5. Ding, S.-Y. & Wang, W. Covalent organic frameworks (COFs): from design to applications. Chem. Soc. Rev. 42, 548–568 (2013). \n6. Gao, C. et al. Isostructural three-dimensional covalent organic frameworks. Angew. Chem. Int. Ed. 58, 9770–9775 (2019). \n7. Fan, H. et al. Covalent organic framework-covalent organic framework bilayer membranes for highly selective gas separation. J. Am. Chem. Soc. 140, 10094–10098 (2018). \n8. Jiang, L. et al. A crystalline polyimide porous organic framework for selective adsorption of acetylene over ethylene. J. Am. Chem. Soc. 140, 15724–15730 (2018). \n9. Nguyen, H. L. et al. A porous covalent organic framework with voided square grid topology for atmospheric water harvesting. J. Am. Chem. Soc. 142, 2218–2221 (2020). \n10. Zeng, Y., Zou, R. & Zhao, Y. Covalent organic frameworks for $\\mathrm{CO}_{2}$ capture. Adv. Mater. 28, 2855–2873 (2016). \n11. Li, L. H. et al. Salen-based covalent organic framework. J. Am. Chem. Soc. 139, 6042–6045 (2017). \n12. Yan, S. et al. Three-dimensional salphen-based covalent–organic frameworks as catalytic antioxidants. J. Am. Chem. Soc. 141, 2920–2924 (2019). \n13. Han, X. et al. Chiral covalent organic frameworks with high chemical stability for heterogeneous asymmetric catalysis. J. Am. Chem. Soc. 139, 8693–8697 (2017). \n14. Haug, W. K., Wolfson, E. R., Morman, B. T., Thomas, C. M. & McGrier, P. L. A nickel-doped dehydrobenzoannulene-based two-dimensional covalent organic framework for the reductive cleavage of inert aryl C–S bonds. J. Am. Chem. Soc. 142, 5521–5525 (2020). \n15. Lin, G., Ding, H., Yuan, D., Wang, B. & Wang, C. A pyrene-based, fluorescent three-dimensional covalent organic framework. J. Am. Chem. Soc. 138, 3302–3305 (2016). \n16. Wang, P. et al. Ultrathin two-dimensional covalent organic framework nanoprobe for interference-resistant two-photon fluorescence bioimaging. Chem. Sci. 9, 8402–8408 (2018). \n17. Gao, Q. et al. Highly photoluminescent two-dimensional imine-based covalent organic frameworks for chemical sensing. Chem. Commun. 54, 2349–2352 (2018). \n18. Das, G. et al. Chemical sensing in two dimensional porous covalent organic nanosheets. Chem. Sci. 6, 3931–3939 (2015). \n19. Ding, H. et al. An AIEgen-based 3D covalent organic framework for white light-emitting diodes. Nat. Commun. 9, 5234 (2018). \n20. Bessinger, D., Ascherl, L., Auras, F. & Bein, T. Spectrally switchable photodetection with near-infrared-absorbing covalent organic frameworks. J. Am. Chem. Soc. 139, 12035–12042 (2017). \n21. Feng, X. et al. High-rate charge-carrier transport in porphyrin covalent organic frameworks: switching from hole to electron to ambipolar conduction. Angew. Chem. Int. Ed. 51, 2618–2622 (2012). \n22. Thomas, S. et al. Electronic structure of two-dimensional π-conjugated covalent organic frameworks. Chem. Mater. 31, 3051–3065 (2019). \n23. Wang, S. et al. Exfoliation of covalent organic frameworks into few-layer redox-active nanosheets as cathode materials for lithium-ion batteries. J. Am. Chem. Soc. 139, 4258–4261 (2017). \n24. Du, Y. et al. Ionic covalent organic frameworks with spiroborate linkage. Angew. Chem. Int. Ed. 55, 1737–1741 (2016). \n25. Mulzer, C. R. et al. Superior charge storage and power density of a conducting polymer-modified covalent organic framework. ACS Cent. Sci. 2, 667–673 (2016). \n26. Halder, A. et al. Interlayer hydrogen-bonded covalent organic frameworks as high-performance supercapacitors. J. Am. Chem. Soc. 140, 10941–10945 (2018). \n27. Jin, Y., Hu, Y. & Zhang, W. Tessellated multiporous two-dimensional covalent organic frameworks. Nat. Rev. Chem. 1, 0056 (2017). \n28. Meng, Y. et al. 2D and 3D porphyrinic covalent organic frameworks: the influence of dimensionality on functionality. Angew. Chem. Int. Ed. 59, 3624–3629 (2020). \n29. Chen, R. et al. Designed synthesis of a 2D porphyrin-based $\\mathsf{s p}^{2}$ carbonconjugated covalent organic framework for heterogeneous photocatalysis. Angew. Chem. Int. Ed. 58, 6430–6434 (2019). \n30. Zhi, Y. et al. Covalent organic frameworks as metal-free heterogeneous photocatalysts for organic transformations. J. Mater. Chem. A 5, 22933–22938 (2017). \n31. Wei, P. F. et al. Benzoxazole-linked ultrastable covalent organic frameworks for photocatalysis. J. Am. Chem. Soc. 140, 4623–4631 (2018). \n32. Wang, S. et al. Programming covalent organic frameworks for photocatalysis: Investigation of chemical and structural variations. Matter 2, 416–427 (2020). \n33. Zhao, Y. et al. Fully conjugated two-dimensional $\\mathsf{s p}^{2}$ -carbon covalent organic frameworks as artificial photosystem I with high efficiency. Angew. Chem. Int. Ed. 58, 5376–5381 (2019). \n34. Stegbauer, L., Schwinghammer, K. & Lotsch, B. V. A hydrazone-based covalent organic framework for photocatalytic hydrogen production. Chem. Sci. 5, 2789–2793 (2014). \n35. Vyas, V. S. et al. A tunable azine covalent organic framework platform for visible light-induced hydrogen generation. Nat. Commun. 6, 8508 (2015). \n36. Banerjee, T., Gottschling, K., Savasci, G., Ochsenfeld, C. & Lotsch, B. V. $\\mathrm{H}_{2}$ Evolution with covalent organic framework photocatalysts. ACS Energy Lett. 3, 400–409 (2018). \n37. Pachfule, P. et al. Diacetylene functionalized covalent organic framework (COF) for photocatalytic hydrogen generation. J. Am. Chem. Soc. 140, 1423–1427 (2018). \n38. Biswal, B. P. et al. Sustained solar $\\mathrm{H}_{2}$ evolution from a thiazolo[5,4-d]thiazolebridged covalent organic framework and nickel-thiolate cluster in water. J. Am. Chem. Soc. 141, 11082–11092 (2019). \n39. Wei, S. et al. Semiconducting 2D triazine-cored covalent organic frameworks with unsubstituted olefin linkages. J. Am. Chem. Soc. 141, 14272–14279 (2019). \n40. Wang, J. et al. Cobalt-containing covalent organic frameworks for visible light-driven hydrogen evolution. Sci. China Chem. 63, 192–197 (2020). \n41. Jin, E. et al. 2D $\\mathsf{s p}^{\\bar{2}}$ carbon-conjugated covalent organic frameworks for photocatalytic hydrogen production from water. Chem 5, 1632–1647 (2019). \n42. Wang, X. et al. Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water. Nat. Chem. 10, 1180–1189 (2018). \n43. Zhang, S. et al. Strong-base-assisted synthesis of a crystalline covalent triazine framework with high hydrophilicity via benzylamine monomer for photocatalytic water splitting. Angew. Chem. Int. Ed. 59, 6007–6014 (2020). \n44. Zhong, W. et al. A Covalent organic framework bearing single Ni sites as a synergistic photocatalyst for selective photoreduction of $\\mathrm{CO}_{2}$ to CO. J. Am. Chem. Soc. 141, 7615–7621 (2019). \n45. Lu, M. et al. Rational design of crystalline covalent organic frameworks for efficient $\\mathrm{CO}_{2}$ photoreduction with $\\mathrm{H}_{2}\\mathrm{O}$ . Angew. Chem. Int. Ed. 58, 12392–12397 (2019). \n46. Lu, W. et al. A scalable general synthetic approach toward ultrathin iminelinked two-dimensional covalent organic framework nanosheets for photocatalytic $\\mathrm{CO}_{2}$ reduction. J. Am. Chem. Soc. 141, 17431–17440 (2019). \n47. Yang, S. et al. 2D Covalent organic frameworks as intrinsic photocatalysts for visible light-driven $\\mathrm{CO}_{2}$ reduction. J. Am. Chem. Soc. 140, 14614–14618 (2018). \n48. Bi, S. et al. Two-dimensional semiconducting covalent organic frameworks via condensation at arylmethyl carbon atoms. Nat. Commun. 10, 2467 (2019). \n49. Lubitz, W. & Tumas, W. Hydrogen: an overview. Chem. Rev. 107, 3900–3903 (2007). \n50. Ding, Y., Zhu, W.-H. & Xie, Y. Development of ion chemosensors based on porphyrin analogues. Chem. Rev. 117, 2203–2256 (2017). \n51. Lee, C. Y. et al. Light-harvesting metal-organic frameworks (MOFs): efficient strut-to-strut energy transfer in bodipy and porphyrin-based MOFs. J. Am. Chem. Soc. 133, 15858–15861 (2011). \n52. Uribe-Romo, F. J., Doonan, C. J., Furukawa, H., Oisaki, K. & Yaghi, O. M. Crystalline covalent organic frameworks with hydrazone linkages. J. Am. Chem. Soc. 133, 11478–11481 (2011). \n53. Gao, Y. & Peng, X. Photogenerated excitons in plain core CdSe nanocrystals with unity radiative decay in single channel: the effects of surface and ligands. J. Am. Chem. Soc. 137, 4230–4235 (2015). \n54. Gouterman, M. Spectra of porphyrins. J. Mol. Spectrosc. 6, 138–163 (1961). \n55. Loppnow, G. R., Melamed, D., Leheny, A. R., Hamilton, A. D. & Spiro, T. G. Excited-state photophysics of donor-appended cobalt(II) porphyrins from picosecond transient absorption spectroscopy. J. Phys. Chem. 97, 8969–8975 (1993). \n56. Wang, Y. et al. Unveiling catalytic sites in a typical hydrogen photogeneration system consisting of semiconductor quantum dots and 3d-metal ions. J. Am. Chem. Soc. 142, 4680–4689 (2020). \n57. Wang, M. et al. Unveiling electronic properties in metal–phthalocyaninebased pyrazine-linked conjugated two-dimensional covalent organic frameworks. J. Am. Chem. Soc. 141, 16810–16816 (2019). \n\n# Acknowledgements \n\nC.W. gratefully acknowledges financial support from the National Natural Science Foundation of China (21572170, 21772149 and 21975188) and the Fundamental Research Funds for Central Universities (2042020kf0213). L.-Z.W. and X.-B.L. are grateful for the financial support from the National Natural Science Foundation of China (21971251) and the National Key Research and Development Program of China (2017YFA0206903). L.G. and L.J.Q. thank financial support from the National Key Research and Development Program of China (2017YFB0702100). We also thank the Beijing Synchrotron Radiation Facility (BSRF, Beamline 1W1B) for providing beam time for the XAS measurements. \n\n# Author contributions \n\nR.C. performed the synthesis and characterization of COFs, including NMR, PXRD, FT-IR and gas absorption. Y.W. carried out $\\mathrm{H}_{2}$ evolution test, XAS data analysis and charge dynamics investigation. Y.M. did the structure stimulations and DFT calculations. X.-Y.G. helped with the $\\mathrm{H}_{2}$ evolution test and data analysis. L.G. and L.J.Q. guided the relevant calculation work. C.W., X.-B.L., and L.-Z.W. designed and supervised the project. R.C., Y.W., Y.M., A.M., X.-B.L., L.-Z.W., and C.W. analyzed the data and wrote the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-21527-3. \n\nCorrespondence and requests for materials should be addressed to X.-B.L., L.-Z.W. or C.W. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contributions to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41560-021-00782-0", + "DOI": "10.1038/s41560-021-00782-0", + "DOI Link": "http://dx.doi.org/10.1038/s41560-021-00782-0", + "Relative Dir Path": "mds/10.1038_s41560-021-00782-0", + "Article Title": "Reactive boride infusion stabilizes Ni-rich cathodes for lithium-ion batteries", + "Authors": "Yoon, M; Dong, YH; Hwang, J; Sung, J; Cha, H; Ahn, K; Huang, YM; Kang, SJ; Li, J; Cho, J", + "Source Title": "NATURE ENERGY", + "Abstract": "Engineered polycrystalline electrodes are critical to the cycling stability and safety of lithium-ion batteries, yet it is challenging to construct high-quality coatings at both the primary- and secondary-particle levels. Here we present a room-temperature synthesis route to achieve a full surface coverage of secondary particles and facile infusion into grain boundaries, and thus offer a complete 'coating-plus-infusion' strategy. Cobalt boride metallic glass was successfully applied to a Ni-rich layered cathode LiNi0.8Co0.1Mn0.1O2. It dramatically improved the rate capability and cycling stability, including under high-discharge-rate and elevated-temperature conditions and in pouch full-cells. The superior performance originates from a simultaneous suppression of the microstructural degradation of the intergranular cracking and of side reactions with the electrolyte. Atomistic simulations identified the critical role of strong selective interfacial bonding, which offers not only a large chemical driving force to ensure uniform reactive wetting and facile infusion, but also lowers the surface/interface oxygen activity, which contributes to the exceptional mechanical and electrochemical stabilities of the infused electrode. Coating is commonly used to improve electrode performance in batteries, but it is challenging to achieve and maintain complete coverage of electrode particles during cycling. Here the authors present a coating-and-infusion approach on Ni-rich cathodes that effectively retards stress corrosion cracking.", + "Times Cited, WoS Core": 383, + "Times Cited, All Databases": 407, + "Publication Year": 2021, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000623725900003", + "Markdown": "# Reactive boride infusion stabilizes Ni-rich cathodes for lithium-ion batteries \n\nMoonsu Yoon $\\textcircled{12}1,4$ , Yanhao Dong $\\textcircled{10}2,4$ , Jaeseong Hwang1, Jaekyung Sung1, Hyungyeon Cha1, Kihong Ahn1, Yimeng Huang3, Seok Ju Kang $\\oplus1$ , Ju Li $\\textcircled{10}2,3\\boxtimes$ and Jaephil Cho   1 ✉ \n\nEngineered polycrystalline electrodes are critical to the cycling stability and safety of lithium-ion batteries, yet it is challenging to construct high-quality coatings at both the primary- and secondary-particle levels. Here we present a room-temperature synthesis route to achieve a full surface coverage of secondary particles and facile infusion into grain boundaries, and thus offer a complete ‘coating-plus-infusion’ strategy. Cobalt boride metallic glass was successfully applied to a Ni-rich layered cathode $\\mathbf{LiNi}_{0.8}\\mathsf{C o}_{0.1}\\mathbf{M}\\mathsf{n}_{0.1}\\mathsf{O}_{2},$ . It dramatically improved the rate capability and cycling stability, including under high-discharge-rate and elevated-temperature conditions and in pouch full-cells. The superior performance originates from a simultaneous suppression of the microstructural degradation of the intergranular cracking and of side reactions with the electrolyte. Atomistic simulations identified the critical role of strong selective interfacial bonding, which offers not only a large chemical driving force to ensure uniform reactive wetting and facile infusion, but also lowers the surface/interface oxygen activity, which contributes to the exceptional mechanical and electrochemical stabilities of the infused electrode. \n\nfuture energy infrastructure needs advanced cathode active terials for lithium-ion batteries (LIBs) with a higher energy and power density, longer cycle life and better safety than now available1–3, but high-voltage and high-rate cycling often triggers accelerated degradation, premature failure and safety issues4,5. Much effort has been spent on exploring new cathode chemistry, introducing dopants into the bulk and at the surface, and designing nano-, micro- and/or heterostructures6–9. Coating is a widely exercised method to improve cathode stability, which can work synergistically with other cathode modifications10–12. Although a thin coating with a high stability and catalytic inertness is helpful, it is often difficult to achieve a $100\\%$ coverage in the synthesis due to a solid-on-solid wetting problem and the need to remain conformal during electrochemical cycling. These challenges set the motivation for the present work, which utilized a simple liquid–solution method to construct a high-quality cathode coating by reactive wetting with the oxide active material. \n\nWe chose a Ni-rich layered cathode $\\mathrm{LiNi_{0.8}C o_{0.1}M n_{0.1}O_{2}}$ (NCM) of great industrial interest as a model system to demonstrate our coating strategy. During the electrochemical cycling of NCM, a series of detrimental processes take place, which include phase transformation in the bulk and at the surface13, intergranular cracking of the secondary particles along grain boundaries $(\\mathrm{GB}\\mathsf{s})^{14,15}$ , the formation and growth of cathode electrolyte interphases (CEIs)16 and side reactions that consume precious liquid organic electrolytes, generate gases and cause transition metal (TM) dissolution (which may later migrate and precipitate at the anode side and affect the anode stability)17–19. The above processes result in a continuous impedance growth and degrade the full-cell performance, especially under high-rate conditions. One key issue is the stability of surface oxygen, which becomes labile at high voltages and easily escapes. Such oxygen loss not only oxidizes organic electrolytes and evolves gases, but also leads to cation reduction and/or densification20 and phase transformations21,22, which may in turn initiate other degradation processes in a chain-reaction manner23–25. In this sense, it is beneficial to construct a coating that binds strongly with the surface oxygen to address the root cause of the high-voltage instability. \n\nWe selected a cobalt boride $(\\mathbf{Co}_{x}\\mathbf{B})$ coating with the following considerations: \n\n1. $\\mathrm{Co}_{x}\\mathrm{B}$ is a metallic compound that has no direct tie-lines with oxygen26 and thermodynamically it would react with oxygen to form stable compounds, such as ${\\bf B}_{2}{\\bf O}_{3},$ $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ and $\\mathrm{Co_{4}B_{6}O_{13}},$ which implies strong reactivity between $\\mathrm{Co}_{x}\\mathrm{B}$ and the surface oxygen of NCM. \n2. $\\mathrm{Co}_{x}\\mathrm{B}$ has an exceptional oxidation resistance even at elevated temperatures $(850-950^{\\circ}\\mathrm{C})$ (ref. 27). This means that, even though $\\mathrm{Co}_{x}\\mathrm{B}$ likes to react with oxygen, the reaction is kinetically self-limiting, probably due to the glass-forming ability of the ${\\bf B}_{2}\\mathrm{O}_{3}$ -like product at the interface that forms a compact self-healing passivation layer28,29. Thus, although the reactive wetting ensures a complete coverage and tight adhesion between the $\\mathrm{Co}_{x}\\mathrm{B}$ and NCM, it does not consume much oxygen from the NCM lattice and will probably maintain a metallic glass nature30,31. The passivation would kinetically suppress oxygen penetration and/or loss through this coating layer, and the interfacial polyanionic borate glass also incorporates the Li alkali metal that comes with NCM, which makes itself a mixed ionic and electronic conductor. \n3.\t A $\\mathrm{Co}_{x}\\mathrm{B}$ coating can be synthesized at room temperature32,33, which eliminates the necessity of follow-up high-temperature treatments that may introduce additional complexity to the heavily optimized synthesis route of NCM. \n4. $\\mathbf{Co}_{x}\\mathbf{B}$ has been used to coat metal parts to improve their corrosion and wear resistance, and thus its mechanical properties should be good in the sense that it must not easily chip or fracture at the nanoscale. \n\n![](images/5aeb37dc16fe928430f27167eb4c3e1a9d6fc4bdc3d134c2657d5b49698b0b71.jpg) \nFig. 1 | ‘Coating-plus-infusion’ microstructure for $\\mathsf{C o}_{\\boldsymbol{x}}\\mathsf{B}$ -infused NCM. Schematic coating-plus-infusion microstructure in which ${\\mathsf{C o}}_{x}\\mathsf{B}$ uniformly coats the surface of NCM secondary particle and infuses into GBs between the NCM primary particles. \n\nRemarkably, we show that the as-synthesized $\\mathrm{Co}_{x}\\mathrm{B}$ coating not only completely covered the surface of the NCM secondary particles, but also infused into the GBs between primary particles with a zero equilibrium wetting angle, which we abbreviate as ‘infusion’ to distinguish it from a typical surface coating. This is similar to the complete wetting of GBs by liquid metal (for example, liquid Ga in aluminium GBs), and intergranular amorphous nanofilms in ceramics. The infused microstructure (Fig. 1) dramatically improved the rate capability and cycling stability of NCM, including under high-discharge rate (up to $1{,}540\\mathrm{mAg^{-1}}$ ) and high-temperature $(45^{\\circ}\\mathrm{C})$ conditions, as it greatly suppressed intergranular cracking, side reactions and impedance growth. \n\n# $\\mathsf{C o}_{x}\\mathsf{B}$ fully covers NCM surface and infuses into GBs \n\nPristine NCM was synthesized by a co-precipitation technique, followed by calcination with lithium hydroxide in a flowing oxygen atmosphere. To obtain $\\mathrm{Co}_{x}\\mathrm{B}$ –infused NCM $\\mathrm{'Co}_{x}\\mathrm{B-NCM)}$ , pristine NCM was added into the ethanol solution of $\\mathrm{Co}(\\mathrm{NO}_{3})_{2},$ followed by the addition of an ethanol solution of $\\mathrm{NaBH_{4}}$ at room temperature under argon protection. $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ was then washed, collected and dried (Methods and Supplementary Fig. 1). Using inductive coupled plasma optical emission spectrometry (ICP-OES; Supplementary Table 1), we confirmed that the infused $\\mathrm{Co}_{x}\\mathrm{B}$ has a composition close to $\\mathbf{Co}_{2.2}\\mathbf{B}$ . Both pristine NCM and $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ have a layered structure as shown by the X-ray diffraction (XRD) data in Supplementary Fig. 2, with minimum Ni/Li cation mixing 1 $1.2\\%$ for pristine NCM and $1.1\\%$ for $_{\\mathrm{Co_{\\itx}B-N C M}}$ ; Rietveld refinement data in Supplementary Table 2). \n\nThe synthesized NCM has a typical polycrystalline microstructure with spherical secondary particles (median diameter $D_{50}{=}12\\upmu\\mathrm{m}$ ; Supplementary Table 3), which consist of fine-grained primary particles (Fig. 2a). Such a microstructure is well maintained in $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ (Fig. 2b), in which a continuous uniform coating with a nanoscale fuzzy morphology was found at the surface under both scanning electron microscope (SEM, Fig. 2b; more examples in Supplementary Fig. 3) and transmission electron microscope (TEM, Fig. $2c,\\mathrm{d};$ ; the fuzzy morphology has a mesoporous structure, as confirmed by the pore size distribution in Supplementary Fig. 4). We found that the coating layer at the surface of the crystalline NCM was amorphous and of thickness $\\sim5\\mathrm{nm}$ (Fig. 2c; coating layer identified by the contrast, as shown in Supplementary Fig. 5). From energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS) mapping, it was enriched in Co and B and depleted in Ni and O compared with the \n\nNCM lattice (Fig. 2e), consistent with the targeted $\\mathrm{Co}_{x}\\mathrm{B}$ composition. Remarkably, despite the room-temperature synthesis route and the lack of high-temperature annealing, $\\mathrm{Co}_{x}\\mathrm{B}$ infused into the GBs between the NCM primary particles, as shown by the EDS mapping in Fig. 2f, and it completely wetted the GBs with an equivalent contact angle of zero degree. More examples of TEM-EDS mapping in Supplementary Figs. 6–8 confirmed the uniform surface coverage and infusion into the GBs deep inside the secondary particles up to ${>}2\\mathrm{-}3{\\upmu\\mathrm{m}}$ , which gave an unusually large room-temperature diffusivity of $1.4\\times10^{-16}$ to $3.1\\times10^{-16}\\mathrm{{m}}^{2}\\mathrm{{s}}^{-1}$ for the $\\mathbf{Co}_{x}\\mathbf{B}$ species as estimated with a two-dimensional (2D) random walk model. This thus indicates a huge driving force for 2D diffusion and/or penetration and supports a reactive wetting process, in which the coating layer spreads over the surface and GBs of the matrix driven by chemical reactions at the interface. \n\nBenefiting from such reactive wetting, we found that $\\mathrm{Co}_{x}\\mathrm{B}$ completely covered the surface of NCM, as supported by the $\\mathrm{\\DeltaX}$ -ray photon spectroscopy (XPS) data in Fig. $2\\mathrm{g-n}$ (fitting details in Supplementary Table 4): compared to pristine NCM, $_{\\mathrm{Co_{\\scriptscriptstylex}B-N C M}}$ showed not only a strong B 1s signal around $187.8\\mathrm{eV}$ (Fig. ${2\\mathrm{g}},$ absent in pristine NCM in Fig. 2k)32,34 and a negatively shifted Co $2p_{3/2}$ signal around $778.5\\mathrm{eV}$ (Fig. 2h, versus $780.2\\mathrm{eV}$ for the ${\\mathrm{Co}}^{3+}$ $2p_{3/2}$ signal in pristine NCM in Fig. 2l; unlike ${\\mathrm{Co}}^{3+}$ in NCM, $\\mathrm{Co}_{x}\\mathrm{B}$ is metallic with Co peaks that shift towards a lower binding energy)35, but also hugely suppressed $\\mathrm{Ni}2p$ and $\\mathrm{Mn}~2p$ signals (Fig. 2i,j, versus strong signals in pristine NCM in Fig. $2\\mathrm{m},\\mathrm{n})^{36}$ . As XPS is a surface-sensitive technique, the absence of Ni and Mn signals suggests a complete coverage of the $\\mathbf{Co}_{x}\\mathbf{B}$ coating layer at the surface of NCM particles (so that the XPS signals were mainly contributed by the coating layer), with much better statistics than typical TEM characterizations. \n\n# Enhanced rate capability and cycling stability \n\nWe next investigated the electrochemical performance of pristine NCM and $\\mathrm{Co}_{x}\\mathrm{B}{\\mathrm{-NCM}}$ as LIB cathodes in coin-type half cells under a high loading $(10.5{\\pm}0.2\\mathrm{mg}\\mathrm{cm}^{-2}$ , which corresponds to an areal capacity of ${\\sim}2.05\\mathrm{mAhcm^{-2}},$ and a high electrode density $(3.20\\pm0.03\\mathrm{g}\\mathrm{cm}^{-3}.\\$ ). When first charged/discharged at $0.1C$ (1C defined as $220\\mathrm{mAg^{-1}}$ ) between 3.0 and $4.4\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ at $25^{\\circ}\\mathrm{C},$ pristine NCM and $\\mathrm{Co}_{x}\\mathrm{B}-$ NCM showed similar charge–discharge curves, a discharge capacity around 215 mAh $\\mathbf{g}^{-1}$ and first-cycle Coulombic efficiency around $91.5\\%$ , and their redox behaviours were similar, as shown by a $\\mathsf{d}Q/\\mathsf{d}V$ analysis (Supplementary Fig. 9a,b). However, $_{\\mathrm{Co_{\\scriptscriptstylex}B-N C M}}$ had a better rate capability (Fig. $^{3\\mathrm{a},\\mathrm{b}^{\\cdot}}$ ) and cycling stability (shown by the 1C cycling data performed after the rate tests in Fig. 3a and the $0.5\\mathrm{C}$ cycling data in Supplementary Fig. 10). To gain a better understanding of the improved rate capability and cycling stability, we conducted a galvanostatic intermittent titration technique (GITT) measurements with a titration current of $0.5C$ after the first (41st cycle in the total number of cycling) and last (140th cycle in the total number of cycling) cycles of 1C cycling (Fig. 3a). As shown by the discharge profiles in Fig. 3c, a more severe polarization developed in cycled pristine NCM than in cycled $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ and the average voltage loss is 3.75 times larger in the former. The more detailed GITT analysis in Supplementary Fig. 11 demonstrates a minimum impedance growth in cycled $_{\\mathrm{Co_{\\scriptscriptstylex}B-N C M}}$ and a huge impedance growth in pristine NCM, mostly in the form of ohmic loss (which indicates degraded electron transport at the electrode level, which is consistent with observed intergranular cracking discussed below); this is further supported by electrochemical impedance spectroscopy (EIS) measurements (Supplementary Fig. 12). \n\n![](images/e20a59113fc3eed099dc2bae34eb820b632f126d83dff1801ebeada2b598d471.jpg) \nFig. 2 | Uniform amorphous $\\mathsf{C o}_{\\boldsymbol{x}}\\mathsf{B}$ infusion at the NCM surface and GBs. a,b, SEM images of pristine NCM (a) and ${\\mathsf{C o}}_{x}\\mathsf{B}$ –NCM (b). Insets: lower-magnification SEM images showing the morphology of the NCM secondary particles. c,d, TEM images of cross-sectioned ${\\mathsf{C o}}_{{\\boldsymbol{x}}}{\\mathsf{B-N C M}}$ near the surface. Insets of panel c: fast Fourier transform patterns showing crystalline NCM (bottom left) and amorphous ${\\mathsf{C o}}_{x}\\mathsf{B}$ (top right). e, EDS mapping of site A in d. f, EDS mapping of site B in d. Scale bars, $1\\upmu\\mathrm{m}$ (a,b), $5\\upmu\\mathrm{m}$ (a,b insets), $20\\mathsf{n m}$ (c,e,f), $50\\mathsf{n m}$ (d). g–j, XPS spectra of B 1s $\\mathbf{\\sigma}(\\mathbf{g})$ , Co $2p$ $(\\boldsymbol{\\mathsf{h}})$ , ${\\mathsf{N i}}2p$ (i) and Mn $2p$ (i) for ${\\mathsf C}_{0_{x}\\mathsf B}$ –NCM. k–n, XPS spectra of $\\textsf{B}$ 1s ${\\bf\\Pi}({\\bf k})$ , Co $2p$ (l), Ni $2p$ $(\\pmb{\\mathsf{m}})$ and Mn $2p$ ${\\bf\\Pi}({\\bf n})$ for pristine NCM. Details for the $\\mathsf{X P S}$ data analysis are listed in Supplementary Table 4. a.u., arbitrary units. \n\nTo highlight the exceptional performance offered by $\\mathrm{Co}_{x}\\mathrm{B}$ infusion, we tested under harsher conditions with a 7C discharge rate at $45^{\\circ}\\mathrm{C}$ (note the cells were charged at $0.5C$ because the lithium metal anode (LMA) cannot afford such a fast charging rate). Although pristine NCM rapidly faded within 60 cycles, $_{\\mathrm{Co_{\\scriptscriptstylex}B-N C M}}$ could be stably cycled up to 200 cycles with a capacity retention of $82.2\\%$ , high Coulombic efficiency (Fig. 3d), high energy efficiency and stable average discharge voltage (Supplementary Fig. 13a–d). The rapid failure of pristine NCM in 7C discharge cycling is due to the kinetic reason of impedance overgrowth instead of a thermodynamic transformation, as the intermittent recovery step (conducted after every 100 cycles with a slow charge/discharge rate of 0.2C) can recover most of the capacity, as shown in Fig. 3d. The conclusion is further supported by EIS data measured after different 7C discharge cycles (Supplementary Fig. 14), which show a dramatic impedance growth of pristine NCM on cycling. Additional experiments were conducted with a 5C discharge rate at $45^{\\circ}\\mathrm{C}$ (Supplementary Fig. 15), which again demonstrates the superior performance of $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ Lastly, we tested pristine NCM and $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ in $400\\mathrm{mAh}$ -pouch-type full-cells using a spherical graphite $(\\mathrm{Gr})$ anode and conducted long-term cycling in the range of $2.8\\mathrm{-}4.3\\mathrm{V}$ at $25^{\\circ}\\mathrm{C}$ . As shown in Fig. 3e, $_{\\mathrm{Co_{\\scriptscriptstylex}B-N C M}}$ has an impressive capacity retention of $95.0\\%$ (versus $79.2\\%$ for pristine \n\n![](images/1938b99554e1a4f345a1fc22b4834c5cda199a874b05124fc1097de4ceb433d8.jpg) \nFig. 3 | Superior electrochemical performance of $\\mathsf{C o}_{x}\\mathsf{B}$ –NCM over pristine NCM. a, Rate tests and 1C cycling of ${\\mathsf{C o}}_{x}{\\mathsf{B}}$ –NCM and pristine NCM in the range of $3.0{-}4.4\\lor$ versus $\\mathsf{L i}/\\mathsf{L i^{+}}$ at $25^{\\circ}\\mathsf{C}$ . The shading shows the standard deviations calculated from five cells. b, Discharge curves at different rates for ${\\mathsf{C o}}_{x}\\mathsf{B}$ – NCM (top) and pristine NCM (bottom). c, Discharge curves of the GITT measurements conducted after the 140th cycle in a. Inset: average voltage loss and its standard deviation (raw data available in Supplementary Fig. 11) over different GITT steps. d, 7C discharge cycling tests in the range of 3.0−4.4 V versus $\\mathsf{L i}/\\mathsf{L i^{+}}$ at $45^{\\circ}\\mathsf C.$ , with 6 intermittent cycles with 0.2C charge/discharges conducted after every 100 cycles. e, Cycling performance of CoxB–NCM/Gr and pristine NCM/Gr full-cells at 1.0C in the range of $2.8\\mathrm{-}4.3\\mathrm{V}$ at $25^{\\circ}\\mathsf{C}$ . Inset: photo of an assembled pouch cell. \n\n![](images/bd7124a387c1cd23b57b77cac5e4a48400de10366ebebcacc68044cac885b8ce.jpg) \nFig. 4 | $\\mathsf{C o}_{x}\\mathsf{B}$ infusion simultaneously suppresses microstructural degradation and side reactions. a, TEM image and EDS mapping (inset) of pristine NCM after 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathsf{C}$ . b,c, High-resolution transmission electron microscopy (HR-TEM) at a fresh surface generated by intergranular cracking (b) and an EELS line scan at a secondary-particle surface in cycled pristine NCM (c). d, TEM image and EDS mapping (inset) of ${\\mathsf{C o}}_{\\boldsymbol{x}}{\\mathsf{B-N C M}}$ after 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathsf{C}$ e,f, HR-TEM (e) and EELS line scan (f) at a secondary-particle surface in cycled ${\\mathsf{C o}}_{x}{\\mathsf{B}}-$ NCM. Scale bars, $2\\upmu\\mathrm{m}$ (a,d), $2{\\mathsf{n m}}$ (b,e). g–k, $\\mathsf{X P S}$ spectra of C 1s $\\mathbf{\\sigma}(\\mathbf{g})$ , F 1s $(\\mathbf{h})$ , Ni $2p$ (i), $\\mathsf{C o}2\\mathsf{p}$ (j) and B 1s ${\\bf\\Pi}({\\bf k})$ for ${\\mathsf{C o}}_{x}{\\mathsf{B-N C M}}$ (top) and pristine NCM (bottom) after 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathsf{C}$ . PEC, poly(ethylene carbonate); PVDF, poly(vinylidene fluoride). l, In situ DEMS data of pristine NCM (top) and ${\\mathsf{C o}}_{x}{\\mathsf{B}}$ –NCM (bottom) during first charge at $0.2C$ in the voltage range 3.0–4.4 V versus $\\mathsf{L i}/\\mathsf{L i^{+}}$ at $25^{\\circ}\\mathsf{C}$ . m, Dissolved Ni, Co and Mn in the electrolytes measured by ICP-OES after 100 and 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathsf{C}$ (electrolytes from three different cells were measured to obtain the averages and standard deviations for each data point). \n\nNCM) and a high Coulombic efficiency at $1.0C/1.0C$ charge/discharge for 500 cycles (more detailed electrochemical performances are given in Supplementary Fig. 16). Therefore, $\\mathrm{Co}_{x}\\mathrm{B}$ infusion can greatly enhance the rate capability and cycling stability of NCM with a suppressed impedance growth and voltage loss, especially under high-rate and high-temperature conditions. \n\n# Mitigating microstructural degradation and side reactions \n\nPristine NCM and $_{\\mathrm{Co_{\\itx}B-N C M}}$ show dramatically different microstructures after cycling. After 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathrm{C},$ we observed severe intergranular cracking in pristine NCM, as shown by TEM (Fig. 4a) and SEM (Supplementary Fig. $^{17\\mathrm{a,b}}$ ), which created more electrolyte-exposing fresh surfaces and led to extensive CEI formation, as indicated by the EDS mapping of F and C both at the surface and inside the secondary particle (insets of Fig. 4a). In comparison, the secondary particles of $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ remained intact without cracking, as confirmed by TEM (Fig. 4d) and SEM (Supplementary Fig. 17c,d), and the F and C signals were weaker (insets of Fig. 4d), which suggests less electrolyte infiltration and CEI formation37. Similarly, suppressed cracking by $\\mathrm{Co}_{x}\\mathrm{B}$ infusion was also observed in the initially charged cathodes as well as in those after 500 cycles in pouch cells (Supplementary Figs. 18 and 19). The contrasting cracking behaviours are interesting because intergranular cracking of Ni-rich cathodes is typically attributed to anisotropic lattice expansion and/or shrinkage and heterogeneous charge/discharge kinetics during electrochemical cycling38,39, which can hardly be removed by cathode coating. Indeed, as shown by in situ XRD during electrochemical cycling (Supplementary Figs. 20 and 21), pristine NCM and $_{\\mathrm{Co_{\\itx}B-N C M}}$ undergo the same bulk phase transformation and lattice expansion and/or shrinkage (Supplementary Fig. 22). Similar observations were also recently reported in the literature, in which the appropriate cathode coatings and electrolyte compositions can efficiently reduce intergranular cracking11,40,41. Therefore, large-scale cracking cannot be solely driven by mechanical stress and/or strain alone; instead, it should also involve chemical side reactions at the GBs, in other words, a stress corrosion cracking (SCC) problem. \n\nThe hypothesis is supported by simultaneously suppressed side reactions and surface phase transformations by $\\mathrm{Co}_{x}\\mathrm{B}$ infusion. To demonstrate the correlation, we first characterized the fresh surface generated by intergranular cracking in cycled pristine NCM under TEM (Fig. 4b), which showed a thick $(\\sim13\\mathrm{nm})$ cation-mixed rock-salt phase (which originated from surface oxygen loss followed by surface cation densification). From electron energy loss spectroscopy (EELS) measurements in Fig. $\\mathtt{4c}$ and Supplementary Fig. $23\\mathrm{a}.$ , we found severe TM reduction ( ${\\mathrm{Ni}}^{3+}$ reduced to $\\mathrm{Ni^{2+}}$ shown by the $\\mathrm{Ni}\\mathrm{L}_{3}$ edge) and defects in the oxygen sublattice (shown by the O K edge) near the surface of cycled pristine $\\mathrm{NCM^{42,43}}$ . In comparison, for cycled $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ , we found a thinner transformed cation-mixed rock-salt phase ( $\\cdot\\mathrm{\\sim}2\\mathrm{nm}$ , Fig. 4e) even at the surface of the secondary particles and much less Ni reduction and oxygen defects (Fig. 4f). The suppressed surface cation reduction, cation densification and surface phase transformation apparently benefit from $\\mathrm{Co}_{x}\\mathrm{B}$ infusion, as the morphology and chemistry remained unchanged at both surfaces and GBs, confirmed by TEM (Supplementary Figs. 23b, 24 and 25a) and EDS (Supplementary Figs. 24d and 25b). \n\nSecond, the surfaces of cycled samples were characterized by XPS, in which the signals of C 1s (contributed by organic CEI components, such as polycarbonates and semicarbonates)41,44,45, F 1s (contributed by CEI components of metal fluorides, such as $\\mathrm{NiF}_{2}$ and LiF) and $\\mathrm{Ni}2p$ signals (contributed by Ni-containing CEI components, such as $\\mathrm{NiF}_{2}^{\\cdot},$ ) (ref. 46) were observed in cycled pristine NCM were stronger than those in cycled $_{\\mathrm{Co_{\\itx}B-N C M}}$ (Fig. 4g–i; see detailed discussions in Supplementary Table 5). Meanwhile, strong Co $2p$ and B 1s signals were observed in cycled $_{\\mathrm{Co_{\\itx}B-N C M}}$ , which indicates the $\\mathrm{Co}_{x}\\mathrm{B}$ surface coating was not covered by thick CEIs, even after prolonged cycling. Both observations above suggest a suppressed CEI growth in $\\mathrm{Co}_{x}\\mathrm{B-NCM}$ (Fig. 4j,k). \n\nThird, by in situ differential electrochemical mass spectrometry (DEMS) measurements (Fig. 4l), we found much less gas evolution $\\mathrm{CO}_{2}$ and $\\mathrm{O}_{2}^{\\cdot}$ ) during the first charge cycle of $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ than during that of pristine NCM. This suggests that $\\mathrm{Co}_{x}\\mathrm{B}$ infusion effectively lowered the surface and GB oxygen activity and suppressed the electrolyte oxidation (the $\\mathrm{Co}_{x}\\mathrm{B}$ infusion may also work by physically separating the electrolyte from cathode surface). Meanwhile, from ICP-OES measurements of the electrolytes in cycled cells (Fig. 4m and Supplementary Table 6), we found less TM dissolution (Ni, Co and Mn) in cycled $_{\\mathrm{Co}_{x}\\mathrm{B-NCM}}$ than in pristine NCM. Therefore, we conclude that our coating efficiently mitigated the side reactions between the cathode and electrolyte, as well as side-reaction products in the solid (CEIs), gas $\\mathrm{CO}_{2}$ and $|\\mathrm{O}_{2})$ and soluble (dissolved Ni, Co and Mn) forms, and the suppressed side reaction correlated well with the eliminated microstructural degradation, which supports the proposed mechanism of SCC retardation. \n\nLastly, the boride infusion treatment improved safety, as demonstrated by differential scanning calorimetry (Supplementary Fig. 26). The exothermal reaction in $_{\\mathrm{Co_{\\itx}B-N C M}}$ charged at $4.4\\mathrm{V}$ (versus $\\mathrm{Li/Li^{\\cdot}}$ ) took place at a higher temperature of $269.5^{\\circ}\\mathrm{C}$ with a lower heat generation of $487.9\\mathrm{Jg^{-1}}$ compared with $250.9^{\\circ}\\mathrm{C}$ and $786.3\\mathrm{Jg^{-1}}$ , respectively, for 4.4-V-charged pristine NCM. This is strong proof of the chemical passivation kinetics we postulated, as oxygen release during cathode thermal decomposition is an important step in the exothermic reaction chain, and by reducing oxygen release, $\\mathrm{Co}_{x}\\mathrm{B-NCM}$ is able to delay the thermal runaway and reduce the total heat released47. \n\n# Crossover effect on LMA \n\nHigh-energy-density lithium metal batteries are currently under development48 and we found that the dissolved TMs from the NCM cathode greatly affected the morphology and electrochemical performance of the LMA during the 7C discharge cycling at $45^{\\circ}\\mathrm{C}$ . After 200 cycles, we found that the surface of the LMA paired with pristine NCM became rough (Fig. 5a) with a porous layer that consisted of mossy lithium and solid–electrolyte interphases (SEIs), as shown in Fig. 5b. EDS mapping of the porous layer in Fig. 5c identified not only non-uniform C and F distributions, but also strong Ni signals enriched at the SEI/LMA interface, from the crossover effect of Ni dissolution, migration and deposition on the anode10,19. In comparison, the LMA paired with $\\mathrm{Co}_{x}\\mathrm{B}{\\mathrm{-NCM}}$ had a smooth surface and a dense SEI layer (Fig. 5d,e). The contrasting morphology was closely related to the composition and stability of the SEI, and by XPS measurements (Fig. 5f) we confirmed the SEI of the LMAs paired with $\\mathrm{Co}_{x}\\mathrm{B-NCM}$ indeed had much weaker Ni signals than those paired with pristine NCM. (Note that Mn and Co were undetectable, as shown by the XPS in Supplementary Fig. 27 for cycled LMAs paired with both pristine NCM and $_{\\mathrm{Co_{\\itx}B-N C M}}$ , probably due to lower dissolved concentrations in the electrolytes.) Electrochemically, the deposited Ni-induced morphological instability would degrade the performance of the LMA, which was proved by the cycling experiments of Li/Li symmetric cells (Supplementary Fig. 28). Therefore, the suppressed TM dissolution by our coating conveyed an additional benefit by removing the crossover effect on the LMA and improved the full-cell cycling stability (Supplementary Fig. 29). \n\n# Selective interfacial bonding and suppressed oxygen activity \n\nFor the atomistic details, first-principles calculations were conducted on the (104) surface of $\\mathrm{LiNiO}_{2}$ and on the interface between the $\\mathrm{LiNiO}_{2}$ (104) surface and amorphous $\\mathrm{Co}_{x}\\mathrm{B}$ . As shown by the relaxed atomic structure of a $\\mathrm{LiNiO}_{2}$ slab with the top and bottom (104) surfaces in Supplementary Fig. 30a, the $\\mathrm{LiO}_{6}$ (grey) and $\\mathrm{NiO}_{6}$ (purple) octahedra were truncated at the surfaces, which created underbonded surface oxygen with two kinds of local structures: type I coordinated by two Ni and three Li, and type II coordinated by three Ni and two Li. Note that in the bulk of $\\mathrm{LiNiO}_{2}\\mathrm{.}$ the lattice oxygen was always coordinated by three Ni and three Li (inset of Supplementary Fig. 30b), which promoted a strong hybridization between the $\\mathrm{Ni}3d$ and O $2p$ orbitals (with three Ni–O–Li local configurations) and lowered the energy level of the occupied O $2p$ states (Supplementary Fig. 30b). However, the type I surface oxygen had one nil–O–Li configuration (in addition to two Ni–O–Li configurations; inset of Supplementary Fig. 30c), which indicates a weaker Ni $3d\\mathrm{-O}2p$ hybridization, and creates more high-energy O $2p$ states close to the Fermi level $E_{\\mathrm{{F}}}$ (Supplementary Fig. 30c). This is the origin of the surface oxygen instability, which is prone to lose electrons at high voltages and subsequently evolves oxygen gas. Indeed, similar analyses were put forward for Li-rich cathode materials49,50, in which the Li–O–Li local configuration raises the electronic energy of O $2p$ states and is responsible for the observed oxygen redox. \n\nAt the interface between $\\mathrm{LiNiO}_{2}(104)$ surface and amorphous $\\mathrm{Co}_{x}\\mathrm{B}$ (Fig. 6a), Co and B preferentially bond with the surface O of $\\mathrm{LiNiO}_{2};$ but not with Li or Ni. The interfacial $_{\\mathrm{Co-O}}$ and B–O bonds are stronger than the lattice Ni–O bond, as indicated by the stronger electron cloud sharing for the former in the charge density plot (Fig. $\\mathrm{6b,c)}$ . Note that in Fig. 6c, the $_{\\mathrm{B-O}}$ bond has a short bond distance $(1.33\\mathring{\\mathrm{A}})$ and the electron cloud of O polarizes towards B, which suggests a covalent bonding nature. Considering the local structure, the type I ‘surface’ O (now becoming an interfacial O) is coordinated either by one $\\begin{array}{r}{\\mathbf{\\Co},}\\end{array}$ two Ni and three Li atoms (inset of Fig. 6e) or by one B, two Ni and three Li atoms (inset of Fig. 6f; the strong B–O bond pulls O away from the centre of the original ‘octahedral’ site and the polyhedron becomes similar to a distorted square pyramid). Even though the O coordination (Fig. 6e) is similar to that in the lattice (by three Ni and three Li atoms, inset of Fig. 6d), the strong $\\mathrm{Co-O}$ bond effectively lowers the energy of the O $2p$ states (Fig. 6e), which have less high-energy states close to $E_{\\mathrm{{F}}}$ than that of the lattice O (Fig. 6d). A more dramatic energy-level lowering is achieved by the strong covalent B–O bond, as shown in Fig. 6f, which greatly stabilizes the interface O. We further verified that such an analysis approach on local structures is robust, as the same conclusion can be drawn from the amorphous $\\mathrm{Co}_{x}\\mathrm{B}$ GB phases with different atomic structures (Supplementary Fig. 31). The above results clearly demonstrate that the chemical nature of reactive wetting is the selective $\\mathrm{Co-O}$ and B–O bonds formed at $\\mathrm{Co}_{{x}}\\mathrm{B}/\\mathrm{NCM}$ interface, and the superior stability has an electronic-structure origin that effectively suppresses interface oxygen activity. This rationalizes the design of a reactive-wetting metal–metalloid glass30,31 coating materials with selective bonding, which ensures not only a uniform complete coverage but also stabilizes the surface oxygen. \n\n![](images/31e31833405562be219af65a70d588c8f0c959aaa361991f2fafc0f73bd7c939.jpg) \nFig. 5 | Morphology and chemical characteristics of cycled LMA. a–c, Top-view (a) and cross-sectional (b) SEM images, and EDS mapping (c) of LMA paired with pristine NCM after 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathsf{C}$ . d,e, Top-view (d) and cross-sectional (e) SEM images of LMA paired with CoxB–NCM after 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathsf{C}$ . Scale bars, $20\\upmu\\mathrm{m}$ (a,d), $5\\upmu\\mathrm{m}$ (b,c,e). f, XPS spectra of Ni $2p$ for ${\\mathsf{C o}}_{x}{\\mathsf{B}}$ –NCM (top) and pristine NCM (bottom) after 200 cycles under a 7C discharge rate at $45^{\\circ}\\mathsf{C}$ . \n\n![](images/299f75bd7586c4dc17442f2ba1e112a146d65030f884de7800c57177619aa9c0.jpg) \nFig. 6 | Strong interfacial bonding suppresses oxygen activity. $\\mathsf{a-c}$ Atomic structure (a) and 2D slices of the charge density distribution of a simulated interface between the LiNiO2(104) surface and amorphous $\\mathsf{C o}_{x}\\mathsf{B}$ across $4\\mathsf{C o-O}$ bonds $(\\pmb{\\ b})$ and $3\\mathsf{C o-O}$ and 1 B–O bond $\\mathbf{\\eta}(\\bullet)$ (dashed lines denote the ${\\mathsf C o}_{x}{\\mathsf B}/$ $\\mathsf{L i N i O}_{2}$ interface). d–f, Projected density of states (DOS) and schematic local environment (d–f insets) of lattice oxygen coordinated by three ${\\mathsf{N i}}$ and three Li atoms $(\\pmb{\\mathsf{d}})_{}$ , interface oxygen coordinated by one Co, two Ni and three Li atoms (e) and interface oxygen coordinated by one B, two Ni and two Ni atoms $(\\pmb{\\mathsf{f}})$ . \n\nRegarding the improved mechanical stability, although $\\mathrm{Co}_{x}\\mathrm{B}$ infusion mitigates SCC by stabilizing surface oxygen and suppressing the side reactions, it also benefits from a mechanical perspective, as less cracking was found even at the end of the first charge (Supplementary Fig. 18) when the chemical effect should be less conspicuous. Consistent with the strong interfacial bonds and reactive wetting, we found a 4.6 times higher ‘opening’ strength $\\mathrm{(41GPa}$ ; Supplementary Fig. 32) in first-principles cohesive zone calculations at the $\\mathbf{Co}_{x}\\mathbf{B}/$ $\\mathrm{LiNiO}_{2}$ interface compared with that of bulk $\\mathrm{LiNiO}_{2}$ $(9\\mathrm{GPa})$ , which would help to suppress a Mode I crack. For Mode II and III cracks, we suspect that the metallic glass $\\mathrm{Co}_{x}\\mathrm{B}$ phase is shear weak and can assist inelastic grain-boundary sliding via bond switching that preserves the coordination number. This could be an effective way to release strain energy and avoid stress concentration at the GBs, and thus benefit the long-term mechanical integrity (Supplementary Fig. 19). The above picture allows us to propose design principles for reactive coating/infusion. For oxide cathodes that are synthesized under an oxidizing atmosphere, a reducing agent (an electron donor) has a strong affinity to surface oxygen. This applies to metallic compounds, especially borides, phosphides, silicides and so on, which can form strong covalent bonds with surface oxygen, in other words, create interfacial polyanion groups that stabilize the labile surface oxygen. The latter concept applied to the 3D lattice is exactly the one that led to the invention of polyanion LIB cathodes (for example, $\\mathrm{LiFePO}_{4}.$ ) that have excellent stability and safety. Meanwhile, for the reactive wetting process to happen, such covalent bonds should be formed in situ at the interface and not pre-exist in the coating materials so that a large driving force can be derived from the interfacial chemical reactions. This means that borides reactively wet oxide particles, but borates cannot51. Regarding the synthesis route of the coating material, this may require a highly reducing condition, as in the work presented here in which $\\mathrm{\\DeltaNaBH_{4}}$ was used. To minimize the TM reduction at the interface (when NCM is treated with $\\mathrm{{NaBH_{4}}.}$ , a slight reduction of Ni but not of Co and Mn may occur at the surface, as shown in Supplementary Fig. 33), a low synthesis temperature is thus preferable, such as room temperature. Such a TM reduction definitely must not happen in the bulk. \n\n# Conclusions \n\nTo summarize, we have demonstrated a simple method to construct a high-quality $\\mathrm{Co}_{x}\\mathrm{B}$ metallic glass infusion (beyond that of typical surface coating) of NCM secondary particles by reactive wetting. Under the strong driving force of an interfacial chemical reaction, nanoscale $\\mathrm{Co}_{x}\\mathrm{B}$ metallic glass not only completely wraps around the secondary particle surfaces, but also infuses into the GBs between primary particles. This is extraordinary given that it happens at room temperature, and the secondary particle does not alter the crystalline bulk, but produces drastic changes in the GBs as they are infiltrated by reactive wetting. Consequently, it offers a superior electrochemical performance (especially a high-rate cycling stability at 7C, a high-temperature cycling at $45^{\\circ}\\mathrm{C}$ and an impressive $95.0\\%$ capacity retention over 500 cycles in practical pouch-type full-cells) and better safety by mitigating the entwined cathode-side intergranular SCC, microstructural degradation and side reactions, as well as the TM crossover effect to the anode. Mechanistically, our atomistic simulations revealed a strong, selective interfacial bonding between $\\mathrm{Co}_{x}\\mathrm{B}$ and NCM, which provides a consistent explanation of the reactive wetting and suppressed oxygen activity observed experimentally. The reactive infusion of oxides by other TM boride, phosphide and/or silicide metallic glasses, to produce ‘functional cermets’, should be a generic modification strategy for many electrodes used in advanced energy storage and conversion. \n\n# Methods \n\nSynthesis. Hydroxide precursors of NCM were synthesized by a co-precipitation method. An aqueous solution that contained $3.2\\mathrm{M}\\mathrm{Ni}^{2+}$ , $0.4\\mathrm{M}\\mathrm{Co}^{2+}$ and $0.4\\mathrm{M}$ $\\ensuremath{\\mathrm{Mn}}^{2+}$ was prepared by dissolving $\\mathrm{NiSO}_{4}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O},$ $\\mathrm{CoSO_{4}{\\cdot}7H_{2}O}$ and $\\mathrm{MnSO_{4}{\\cdot}6H_{2}O}$ with a molar ratio of 8:1:1. It was continuously fed into a stirred tank reactor (capacity of 4 l) with $4.0\\mathrm{MNaOH}$ and 0.4 M $\\mathrm{NH_{4}O H}$ solutions under feeding rates of 300, 300 and $40\\mathrm{mlh^{-1}}$ , respectively. A reaction temperature of $50^{\\circ}\\mathrm{C}$ was stably maintained by external water circulator for $20\\mathrm{h}$ , after which the hydroxide precursors were washed, collected and dried at $110^{\\circ}\\mathrm{C}$ for $^{\\mathrm{12h}}$ . NCM was then synthesized by mixing the hydroxide precursors (composition treated as $\\mathrm{(Ni_{0.8}C o_{0.1}M n_{0.1})(O H)_{2}},$ ) with $\\mathrm{LiOH\\cdotH_{2}O}$ in a molar ratio of 1:1.025, followed by a heat treatment at $450^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ and then at $800^{\\circ}\\mathrm{C}$ for $\\mathrm{10h}$ in flowing oxygen. To coat and infuse NCM with the $\\mathrm{Co}_{x}\\mathrm{B}$ compound, $\\boldsymbol{100}\\mathrm{ml}$ of anhydrous ethanol solution that contained 0.009 M $\\mathrm{Co}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ was first prepared under vacuum with a Schlenk line to remove the dissolved oxygen. NCM powders $(5.0\\mathrm{g})$ were next added under vigorous stirring and under argon protection. Subsequently, $2\\mathrm{ml}$ of ethanol solution that contained $0.078\\mathrm{MNaBH_{4}}$ was gradually added and maintained for 2 h under vigorous stirring and under argon protection. The samples were then washed with anhydrous ethanol, collected by vacuum filtration and dried at $120^{\\circ}\\mathrm{C}$ under vacuum overnight. \n\nMaterial characterizations. The chemical compositions of the cathode material and electrolyte were determined by an ICP-OES (Varian 700-ES, Varian, Inc.). Phases and crystallographic structures were characterized by XRD using a parallel-beam XRD instrument (Smartlab, Rigaku, with Cu Kα of wavelength $\\mathrm{\\dot{1}}.542\\mathrm{\\AA})$ ). Specific surface areas were measured by a surface area and porosity analyser (TriStar II, Micromeritics) based on Brunauer–Emmett–Teller theory. The water content was measured three times for each sample using Karl-Fischer coulometric titration (Metrohm 831 KF Coulometer) and are listed in Supplementary Table 7. Impurity content (LiOH and $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ ) amounts were measured by an acid-based titration method52 (Mettler Toledo Titrator) and are listed in Supplementary Table 8. Briefly, $10\\mathrm{g}$ of cathode powders were soaked into $100\\mathrm{ml}$ of deionized water. After stirring for $15\\mathrm{min}$ , $40\\mathrm{ml}$ of clear solution was separated by vacuum filtering and additional $\\mathrm{100ml}$ of deionized water was added. A flow of $0.1\\mathrm{{M}}$ HCl was added to the solution under stirring, while the $\\mathrm{\\pH}$ of the solution was recorded. The experiments were considered finished when the pH of the solution reached 4.0. In situ XRD measurements were conducted on cathodes assembled with a battery cell kit (Rigaku) in a glove box. After installing the assembled battery cell kit on an XRD stage, the cells were first cycled at 0.1C between 3.0 and $4.4\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ as a formation step, after which in situ XRD measurements were performed with Cu Kα radiation (Smartlab, Rigaku) during the charge process at a rate of $\\phantom{-}0.05C$ between $3.0{\\sim}4.4\\mathrm{V}$ versus $\\mathrm{Li/Li^{+}}$ . Cross-sections of the cathodes and LMAs were cut by ion milling (IM-40000, Hitachi) and characterized under a SEM (Verios 460, FEI) equipped with an EDS (XFlash 6130, Bruker) detector. The morphologies and chemical compositions of the prepared cathode powders and electrodes were also characterized by SEM and EDS. The surface chemistry was analysed by XPS (Thermo Scientific Kα spectrometer). Before the XPS measurements, all the samples were rinsed by a dimethyl carbonate (DMC) solvent to remove the residual electrolyte salt and by-products. In situ DEMS measurements were conducted on Swagelok type cells between 3.0 and 4.4 V (versus $\\mathrm{Li/Li^{\\circ}},$ ; the details are described elsewhere53. For the TEM analysis, samples were prepared by dual-beam focused ion beam (FIB, Helios 450HP, FEI) using a $2{-}30\\mathrm{kV}$ Ga ion beam. Prior to the analysis in the FIB workstation, epoxy soaking and carbon deposition were conducted to avoid damage to the Ga ion beam and preserve the sample morphology in subsequent lift-out and thinning processes. After lift-out, the prepared TEM samples were thinned to $200\\mathrm{nm}$ using a $30\\mathrm{kV}$ Ga ion beam. The thinned samples were next polished to remove surface contamination using an Ar-ion milling system (Model 1040 Nanomill, Fischione) and immediately transferred and inspected under TEM. HR-TEM (ARM300, JEOL) was conducted at 150 and $300\\mathrm{keV}$ to collect scanning transmission electron microscopy images for the atomic and structural analysis. For the elemental and spectrum analysis, EELS and EDS were conducted by HR-TEM (Aztec, Oxford Instruments). The thermal stability of charged cathodes was evaluated by differential scanning calorimeter (STAR 1, Mettler Toledo). The cathodes were first charged to $4.4\\mathrm{V}$ (versus Li/Li+) at $0.1C$ and then held at $4.4\\mathrm{V}$ for an additional 2 h. The cathode materials were next collected from disassembled cells, rinsed with DMC to remove residual electrolytes and dried. Charged cathode powders $\\left(5.0\\mathrm{mg}\\right)$ were placed in a hermetic aluminium pan with $3\\upmu\\mathrm{l}$ of electrolyte. During the differential scanning calorimetry measurements, the temperature was increased from the ambient condition to $400^{\\circ}\\mathrm{C}$ at a constant heating rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ . \n\nElectrochemical measurements. Composite cathodes were prepared by mixing $90\\mathrm{wt\\%}$ active material, $5\\mathrm{wt\\%}$ Super-P (as the conductive agent) and $5\\mathrm{wt\\%}$ poly(vinylidene fluoride) (as the binder) in $N$ -methyl-2-pyrrolidone. The slurry obtained was coated onto aluminium foil and dried at $120^{\\circ}\\mathrm{C}$ for 2 h. All the cathodes for the coin-type half cells were controlled with a loading level of $10.5{\\pm}0.2\\mathrm{mg}\\mathrm{cm}^{-2}$ (measured over five punched electrodes) and an electrode density of $3.20{\\pm}0.03\\mathrm{g}\\mathrm{cm}^{-3}$ (measured over five punched electrodes). Lithium metal batteries were assembled using $2032\\mathrm{R}$ coin-type cells in an argon glove box, with the cathodes (diameter $14\\mathrm{mm}$ ) and lithium metal foils (diameter $15\\mathrm{mm}^{\\prime}$ ) as the counter and reference electrode, respectively, and $1.15\\mathrm{M}\\mathrm{LiPF}_{6}$ in ethylene carbonate (EC)/ethyl methyl carbonate (EMC)/DMC with $5\\mathrm{wt\\%}$ fluoroethylene carbonate (EC:EMC:DM $\\mathit{\\Delta}=3/4/3\\mathrm{vol}\\%$ ; Panax Starlyte) as the electrolyte $\\cdot0.2\\mathrm{g}$ added to each coin cell). All the coin cells were evaluated in a constant current–constant voltage mode between 3.0 and $4.4\\mathrm{V}$ (versus $\\mathrm{Li/Li^{\\circ}}$ at 25 and $45^{\\circ}\\mathrm{C}$ . For all the coin cells, the first charge–discharge cycle was conducted at 0.1C. Here 1.0C is defined as $220\\mathrm{mAg^{-1}}$ . To evaluate the rate capability, the cells were charged at 0.5C and discharged at rates of 0.5, 1.0, 2.0, 3.0, 5.0, 7.0 and 10.0C. After the rate testing, the cells were charged/discharged at 1.0 C in the constant current‒constant voltage $_{(0.05\\mathrm{C}}$ cutoff) mode for another 100 cycles (41st to 140th cycles in the total number of cycles) to evaluate the cycling stability between 3.0 and $4.4\\mathrm{V}$ (versus $\\mathrm{Li/Li^{+}}$ ) at $25^{\\circ}\\mathrm{C}$ . GITT measurements were then conducted after the first and last cycles (41st and 140th cycle in the total number of cycles, respectively) of 1.0C cycling between 3.0 and $4.4\\mathrm{V}$ (versus $\\mathrm{Li}/$ Li+) with a titration step at $0.5C$ of $8\\mathrm{{min}}$ and a relaxation step of 1 h. To evaluate the high-rate cycling stability, the cells were charged at 0.5C and discharged at $5.0/7.0C.$ After every 100 cycles, an intermittent recovery step with charge/ discharge rate of $0.2C$ was conducted for six cycles. EIS measurements were conducted on cells charged to $4.4\\mathrm{V}$ (versus $\\mathrm{Li/Li^{+}}$ ) from 1 to ${\\bf\\ l{0}M H z}$ and with an a.c. voltage amplitude of $10\\mathrm{mV}$ using a VMP-300 potentiostat (Bio-logic). Nickel-containing electrolytes were prepared by dissolving 0, 200 and $600\\mathrm{ppm}$ $\\mathrm{Ni(TFSI)}_{2}$ (TFSI, trifluoromethylsulfonimide) in the base electrolyte $\\mathrm{1.15MLiPF_{6}}$ in EC:EMC:DM $\\mathrm{C}=3/4/3\\mathrm{vol\\%}$ ). Li/Li symmetric cells were assembled in the glove box with $80\\upmu\\mathrm{l}$ of the prepared electrolyte for each cell. Galvanostatic cycling was performed on a symmetric $\\mathrm{Li/Li}$ cell at a Li plating/stripping current density of 1.0 or $2.0\\mathrm{mAcm^{-2}}$ with a cycling capacity of $2.0\\mathrm{mAhcm}^{-2}$ $2\\mathrm{h}$ for each step). For full-cell tests, pristine NCM and $\\mathbf{Co}_{x}\\mathbf{B}$ –NCM cathodes and Gr anodes were utilized to assemble 400-mAh-scale pouch-type full-cells. The ratio of negative to positive electrode capacity (N/P ratio) was fixed at $1.11\\pm0.01$ . The cathode loading level was $13.5\\mathrm{mgcm}^{-2}$ on each side of the double-side coated Al foil. The anode loading level was $8.2\\mathrm{mg}\\mathrm{cm}^{-2}$ on each side of the double-side coated Cu foil. The graphite electrode density was $1.44\\mathrm{gcm}^{-3}$ and the cathode density was $3.35\\mathrm{gcm}^{-3}$ . The pouch-type full-cells were assembled in a dry room with a humidity of less than $1\\%$ . The separator and liquid electrolytes were the same as those used in coin cells. The weight of the electrolyte used in full-cells was $1.0{\\mathrm{g}},$ which corresponded to $2.5\\mathrm{gAh^{-1}}$ . The cycling voltage window was at $2.8\\mathrm{-}4.3\\mathrm{V},$ and a two-formation cycle was conducted at $0.1C$ before long-term cycling of 500 cycles at 1C. Details for full-cell specifications are also listed in Supplementary Table 9. All the electrochemical tests (except for EIS) were carried out using a TOSCAT-3100 battery cycler (TOYO SYSTEM). \n\nSimulations. Spin-polarized first-principles calculations were conducted using the Vienna ab initio simulation package based on density functional theory (DFT) using the projector augmented-wave method with the Perdew–Burke–Ernzerhof generalized gradient approximation54–56. The projector augmented-wave potentials with the $2s^{1}$ electron for Li, $3d^{8}4s^{2}$ electrons for Ni, $2s^{2}2p^{4}$ electrons for O, $3d^{7}4s^{2}$ electrons for Co and $2s^{2}2p^{1}$ electrons for B were used. $\\mathrm{DFT}+U$ was applied for the $3d$ orbitals of Ni $U{=}6.0\\mathrm{eV}$ and $\\scriptstyle J=0\\mathrm{eV}$ ) and Co $U{=}3.4\\mathrm{eV}$ and $\\scriptstyle J=0\\mathrm{eV}$ ) (refs. $^{57,58\\ '}$ ). The plane-wave cutoff energy was set to be $520\\mathrm{eV}$ and convergence was considered as reached when the residue atomic forces were less than $0.05\\mathrm{{\\'eV}\\AA^{-1}}$ . The (104) surface of the layered $\\mathrm{LiNiO}_{2}$ was simulated by a supercell that contained 20 Li, 20 Ni and 40 O atoms, with two surfaces separated by a $\\mathrm{{\\bar{10A}}}$ vacuum layer. The Brillouin zone was sampled using a Monkhorst–Pack scheme with a $3\\times3\\times3$ $\\mathbf{k}$ -point mesh. Amorphous $\\mathrm{Co}_{x}\\mathrm{B}$ was simulated by a supercell that contained 70 Co and $32\\mathrm{~B~}$ atoms (corresponding to a composition close to the experimentally measured $\\mathrm{Co}_{2.2}\\mathrm{B}_{,}^{\\prime}$ ) and prepared by first-principles molecular dynamics at $2{,}500\\mathrm{K}$ for $3.0\\mathrm{ps}$ followed by quenching and relaxation at $0\\mathrm{K}.$ The Brillouin zone was sampled using Monkhorst–Pack scheme with a $1\\times1\\times11$ k-point mesh. To simulate the $\\mathrm{Co}_{x}\\mathrm{B}/\\mathrm{LiNiO}_{2}$ interface, an amorphous $\\mathrm{Co}_{x}\\mathrm{B}$ slab that contained $35\\mathrm{Co}$ and $16\\mathrm{~B~}$ atoms were inserted between two (104) surfaces of a $\\mathrm{LiNiO}_{2}$ slab that contained 20 Li, $20\\ensuremath{\\mathrm{Ni}}$ and $40\\mathrm{O}$ atoms. Their relative positions were adjusted so that the $\\mathrm{Co}_{35}\\mathrm{B}_{16}$ slab has a density is similar to that of the individually simulated amorphous $\\mathrm{Co}_{x}\\mathrm{B}$ . The supercell was then heated to $2{,}500\\mathrm{K}$ for $3.0\\mathrm{ps}$ or $12.0\\mathrm{ps}$ by first-principles molecular dynamics (here the positions 20 Li, $20\\ensuremath{\\mathrm{Ni}}$ and $^{400}$ were fixed to avoid the melting of $\\mathrm{LiNiO}_{2}^{\\cdot}$ ), followed by quenching and relaxation at 0 K. In all the first-principles molecular dynamics calculations, the supercell size and shape were fixed and a time step of 1.5 fs was used. The Brillouin zone was sampled using Monkhorst–Pack scheme with a $1\\times1\\times1\\mathbf{k}$ -point mesh for first-principles molecular dynamics and a $2\\times3\\times2\\mathbf{k}$ -point mesh for $0\\mathrm{K}$ relaxation. The atomic structures were visualized and plotted using $\\mathrm{VESTA}^{59}$ . The projected DOS of the O $2p$ orbitals were summed over $P_{x},P_{y}$ and $p_{z},$ including both spin-up and spin-down states. \n\n# Data availability \n\nData generated and analysed in this study are included in the manuscript and its Supplementary Information. \n\nReceived: 10 June 2020; Accepted: 18 January 2021; Published online: 1 March 2021 \n\n# References \n\n1. Nitta, N., Wu, F., Lee, J. T. & Yushin, G. Li-ion battery materials: present and future. Mater. Today 18, 252–264 (2015). \n2. Kim, J. et al. Prospect and reality of Ni‐rich cathode for commercialization. Adv. Energy Mater. 8, 1702028 (2018). \n3. Li, W., Erickson, E. M. & Manthiram, A. High-nickel layered oxide cathodes for lithium-based automotive batteries. Nat. Energy 5, 26–34 (2020). \n4. Edström, K., Gustafsson, T. & Thomas, J. O. The cathode–electrolyte interface in the Li-ion battery. Electrochim. Acta 50, 397–403 (2004). \n5. Sharifi-Asl, S., Lu, J., Amine, K. & Shahbazian-Yassar, R. Oxygen release degradation in Li-ion battery cathode materials: mechanisms and mitigating approaches. Adv. Energy Mater. 9, 1900551 (2019). \n6.\t Xie, Q., Li, W. & Manthiram, A. A Mg-doped high-nickel layered oxide cathode enabling safer, high-energy-density Li-ion batteries. Chem. Mater. 31, \n938–946 (2019). \n7.\t Schipper, F. et al. From surface $\\mathrm{ZrO}_{2}$ coating to bulk $Z\\mathrm{r}$ doping by high temperature annealing of nickel-rich lithiated oxides and their enhanced electrochemical performance in lithium ion batteries. Adv. Energy Mater. 8, \n1701682 (2018). \n8.\t Xu, X. et al. Radially oriented single-crystal primary nanosheets enable ultrahigh rate and cycling properties of $\\mathrm{LiNi_{0.8}C o_{0.1}M n_{0.1}O_{2}}$ cathode material for lithium-ion batteries. Adv. Energy Mater. 9, 1803963 (2019). \n9.\t Ofer, D., Pullen, A. W. & Sriramulu, S. Polycrystalline metal oxide, methods of manufacture thereof, and articles comprising the same. US patent \n9,391,317 (2016). \n10.\tKim, J. et al. A highly stabilized nickel-rich cathode material by nanoscale epitaxy control for high-energy lithium-ion batteries. Energy Environ. Sci. 11, \n1449–1459 (2018). \n11.\tYan, P. et al. Tailoring grain boundary structures and chemistry of Ni-rich layered cathodes for enhanced cycle stability of lithium-ion batteries. Nat. Energy 3, 600–605 (2018). \n12.\tXu, G.-L. et al. Building ultraconformal protective layers on both secondary and primary particles of layered lithium transition metal oxide cathodes. Nat. Energy 4, 484–494 (2019). \n13.\tLi, L. et al. Hidden subsurface reconstruction and its atomic origins in layered oxide cathodes. Nano Lett. 20, 2756–2762 (2020). \n14.\tLiu, H. et al. Intergranular cracking as a major cause of long-term capacity fading of layered cathodes. Nano Lett. 17, 3452–3457 (2017). \n15.\tYan, P. et al. Coupling of electrochemically triggered thermal and mechanical effects to aggravate failure in a layered cathode. Nat. Commun. 9, \n2437 (2018). \n16.\tWatanabe, S., Kinoshita, M., Hosokawa, T., Morigaki, K. & Nakura, K. Capacity fade of $\\mathrm{LiAl}_{\\mathrm{y}}\\mathrm{Ni}_{1-x-y}\\mathrm{Co}_{x}\\mathrm{O}_{2}$ cathode for lithium-ion batteries during accelerated calendar and cycle life tests (surface analysis of Li $\\mathrm{Al}_{y}\\mathrm{Ni}_{1-x-y}\\mathrm{Co}_{x}\\mathrm{O}_{2}$ cathode after cycle tests in restricted depth of discharge ranges). J. Power Sources 258, 210–217 (2014). \n17.\tJung, R., Metzger, M., Maglia, F., Stinner, C. & Gasteiger, H. A. Chemical versus electrochemical electrolyte oxidation on NMC111, NMC622, NMC811, LNMO, and conductive carbon. J. Phys. Chem. Lett. 8, 4820–4825 (2017). \n18.\t Freiberg, A. T. S., Roos, M. K., Wandt, J., de Vivie-Riedle, R. & Gasteiger, H. A. Singlet oxygen reactivity with carbonate solvents used for Li-ion battery electrolytes. J. Phys. Chem. A 122, 8828–8839 (2018). \n19.\tZhan, C., Wu, T., Lu, J. & Amine, K. Dissolution, migration, and deposition of transition metal ions in Li-ion batteries exemplified by Mn-based cathodes—a critical review. Energy Environ. Sci. 11, 243–257 (2018). \n20.\tHuang, Y. et al. Lithium manganese spinel cathodes for lithium-ion batteries. Adv. Energy Mater. 11, 2000997 (2021). \n21.\tZhu, Z. et al. Gradient Li-rich oxide cathode particles immunized against oxygen release by a molten salt treatment. Nat. Energy 4, 1049–1058 (2019). \n22.\tYan, P. et al. Injection of oxygen vacancies in the bulk lattice of layered cathodes. Nat. Nanotechnol. 14, 602–608 (2019). \n23.\tArmstrong, A. R. et al. Demonstrating oxygen loss and associated structural reorganization in the lithium battery cathode $\\mathrm{Li}[\\mathrm{Ni}_{0.2}\\mathrm{Li}_{0.2}\\mathrm{Mn}_{0.6}]\\mathrm{O}_{2}$ . J. Am. Chem. Soc. 128, 8694–8698 (2006). \n24.\tHouse, R. A. et al. What triggers oxygen loss in oxygen redox cathode materials? Chem. Mater. 31, 3293–3300 (2019). \n25.\tYoon, M. et al. Unveiling nickel chemistry in stabilizing high-voltage cobalt-rich cathodes for lithium-ion batteries. Adv. Funct. Mater. 30, \n1907903 (2020). \n26.\tJain, A. et al. Commentary: The Materials Project: a materials genome approach to accelerating materials innovation. APL Mater. 1, 011002 (2013). \n27.\tMu, D. & Yang, C. Shen, B.-l. & Jiang, H. Oxidation resistance of borided pure cobalt. J. Alloy. Compd 479, 629–633 (2009). \n28.\t Yang, Y., Kushima, A., Han, W., Xin, H. & Li, J. Liquid-like, self-healing aluminum oxide during deformation at room temperature. Nano Lett. 18, \n2492–2497 (2018). \n29.\tLi, J., Lenosky, T. J., Först, C. J. & Yip, S. Thermochemical and mechanical stabilities of the oxide scale of $\\mathrm{ZrB}_{2}{+}\\mathrm{SiC}$ and oxygen transport mechanisms. J. Am. Ceram. Soc. 91, 1475–1480 (2008). \n30.\tHasegawa, R. & Ray, R. Iron–boron metallic glasses. J. Appl. Phys. 49, 4174–4179 (1978). \n31.\tGaskell, P. H. A new structural model for amorphous transition metal silicides, borides, phosphides and carbides. J. Non-Cryst. Solids 32, 207–224 (1979). \n32.\tMasa, J. et al. Amorphous cobalt boride $\\left(\\mathbf{Co}_{2}\\mathbf{B}\\right)$ as a highly efficient nonprecious catalyst for electrochemical water splitting: oxygen and hydrogen evolution. Adv. Energy Mater. 6, 1502313 (2016). \n33.\tDeng, J. et al. Co–B nanoflakes as multifunctional bridges in $\\mathrm{ZnCo_{2}O_{4}}$ micro-/nanospheres for superior lithium storage with boosted kinetics and stability. Adv. Energy Mater. 9, 1803612 (2019). \n34.\tJiang, B. et al. A mesoporous non-precious metal boride system: synthesis of mesoporous cobalt boride by strictly controlled chemical reduction. Chem. Sci. 11, 791–796 (2020). \n35.\tChen, Z. et al. Study of cobalt boride-derived electrocatalysts for overall water splitting. Int. J. Hydrog. Energy 43, 6076–6087 (2018). \n36.\tZhang, C. et al. Revealing the role of $\\mathrm{NH_{4}V O_{3}}$ treatment in Ni-rich cathode materials with improved electrochemical performance for rechargeable lithium-ion batteries. Nanoscale 10, 8820–8831 (2018). \n37.\t Yu, Y. et al. Optimal annealing of Al foil anode for prelithiation and full-cell cycling in Li-ion battery: the role of grain boundaries in lithiation/ delithiation ductility. Nano Energy 67, 104274 (2020). \n38.\t Miller, D. J., Proff, C., Wen, J. G., Abraham, D. P. & Bareño, J. Observation of microstructural evolution in Li battery cathode oxide particles by in situ electron microscopy. Adv. Energy Mater. 3, 1098–1103 (2013). \n39.\tKondrakov, A. O. et al. Anisotropic lattice strain and mechanical degradation of high- and low-nickel NCM cathode materials for Li-ion batteries. J. Phys. Chem. C. 121, 3286–3294 (2017). \n40.\tKim, J. et al. Controllable solid electrolyte interphase in nickel‐rich cathodes by an electrochemical rearrangement for stable lithium‐ion batteries. Adv. Mater. 30, 1704309 (2018). \n41.\tZhao, W. et al. High voltage operation of Ni‐rich NMC cathodes enabled by stable electrode/electrolyte interphases. Adv. Energy Mater. 8, 1800297 (2018). \n42.\tYoon, W.-S. et al. Investigation of the charge compensation mechanism on the electrochemically Li-ion deintercalated $\\mathrm{Li}_{1-x}\\mathrm{Co}_{1/3}\\mathrm{Ni}_{1/3}\\mathrm{Mn}_{1/3}\\mathrm{O}_{2}$ electrode system by combination of soft and hard X-ray absorption spectroscopy. J. Am. Chem. Soc. 127, 17479–17487 (2005). \n43.\tLin, F. et al. Profiling the nanoscale gradient in stoichiometric layered cathode particles for lithium-ion batteries. Energy Environ. Sci. 7, 3077–3085 (2014). \n44.\tYang, L., Ravdel, B. & Lucht, B. L. Electrolyte reactions with the surface of high voltage $\\mathrm{LiNi_{0.5}M n_{1.5}O_{4}}$ cathodes for lithium-ion batteries. Electrochem. Solid-State Lett. 13, A95–A97 (2010). \n45.\tZheng, J. et al. Highly stable operation of lithium metal batteries enabled by the formation of a transient high-concentration electrolyte layer. Adv. Energy Mater. 6, 1502151 (2016). \n46.\tLi, W. et al. Dynamic behaviour of interphases and its implication on high-energy-density cathode materials in lithium-ion batteries. Nat. Commun. 8, 14589 (2017). \n47.\tNguyen, T. T. D. et al. Understanding the thermal runaway of Ni-rich lithium-ion batteries. World Electr. Veh. J. 10, 79 (2019). \n48.\tLin, D., Liu, Y. & Cui, Y. Reviving the lithium metal anode for high-energy batteries. Nat. Nanotechnol. 12, 194–206 (2017). \n49.\tSeo, D.-H. et al. The structural and chemical origin of the oxygen redox activity in layered and cation-disordered Li-excess cathode materials. Nat. Chem. 8, 692–697 (2016). \n50.\tLuo, K. et al. Charge-compensation in $3d$ -transition-metal-oxide intercalation cathodes through the generation of localized electron holes on oxygen. Nat. Chem. 8, 684–691 (2016). \n51.\tHashigami, S. et al. Improvement of cycleability and rate-capability of $\\mathrm{LiNi}_{0.5}\\mathrm{Co}_{0.2}\\mathrm{Mn}_{0.3}\\mathrm{O}_{2}$ cathode materials coated with lithium boron oxide by an antisolvent precipitation method. Chem. Sel. 4, 8676–8681 (2019). \n52.\tPark, J.-H. et al. Effect of residual lithium rearrangement on Ni-rich layered oxide cathodes for lithium-ion batteries. Energy Technol. 6, 1361–1369 (2018). \n53.\t Kang, S. J., Mori, T., Narizuka, S., Wilcke, W. & Kim, H.-C. Deactivation of carbon electrode for elimination of carbon dioxide evolution from rechargeable lithium–oxygen cells. Nat. Commun. 5, 3937 (2014). \n54.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B: Condens. Matter Mater. Phys. 59, \n1758 (1999). \n55.\tKresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n56.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n57.\tDudarev, S. L., Botton, G. A., Savrasov, S. Y., Humphreys, C. J. & Sutton, A. P. Electron-energy-loss spectra and the structural stability of nickel oxide: an $\\mathrm{LSDA}+U$ study. Phys. Rev. B 57, 1505–1509 (1998). \n58.\tJain, A. et al. Formation enthalpies by mixing GGA and GGA $+\\ U$ calculations. Phys. Rev. B 84, 045115 (2011). \n59.\tMomma, K. & Izumi, F. VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J. Appl. Crystallogr. 44, \n1272–1276 (2011). \n\n# Acknowledgements \n\nThis work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (no. 20172410100140). 2020 Research Funds (1.200029.1) of the Ulsan National Institute of Science and Technology (UNIST) is also acknowledged. Y.D. and J.L. acknowledge support from the Department of Energy, Basic Energy Sciences, under award no. DE-SC0002633 (Chemomechanics of Far-From-Equilibrium Interfaces). \n\n# Author contributions \n\nM.Y., Y.D., J.L. and J.C. conceived the project. M.Y. synthesized the materials and conducted the electrochemical testing. Y.D. conducted the simulations and theoretical analysis. M.Y. and J.H. conducted ex situ and in situ XRD measurements and analysis. H.C. and J.S. conducted the focused ion beam, TEM, SEM and XPS measurements. S.J.K. provided equipment for the DEMS measurements. M.Y. and K.A. assembled and tested the pouch-type full-cells. M.Y. and Y.D. analysed the data. M.Y., Y.D., J.L. and J.C. wrote the paper. All the authors discussed and contributed to the writing. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41560-021-00782-0. \n\nCorrespondence and requests for materials should be addressed to J.L. or J.C. \n\nPeer review information Nature Energy thanks Payam Kaghazchi, David Wood III and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021, corrected publication 2021 " + }, + { + "id": "10.1038_s41560-021-00789-7", + "DOI": "10.1038/s41560-021-00789-7", + "DOI Link": "http://dx.doi.org/10.1038/s41560-021-00789-7", + "Relative Dir Path": "mds/10.1038_s41560-021-00789-7", + "Article Title": "Rejuvenating dead lithium supply in lithium metal anodes by iodine redox", + "Authors": "Jin, CB; Liu, TF; Sheng, OW; Li, M; Liu, TC; Yuan, YF; Nai, JW; Ju, ZJ; Zhang, WK; Liu, YJ; Wang, Y; Lin, Z; Lu, J; Tao, XY", + "Source Title": "NATURE ENERGY", + "Abstract": "Inactive lithium (more frequently called dead lithium) in the forms of solid-electrolyte interphase and electrically isolated metallic lithium is principally responsible for the performance decay commonly observed in lithium metal batteries. A fundamental solution of recovering dead lithium is urgently needed to stabilize lithium metal batteries. Here we quantify the solid-electrolyte interphase components, and determine their relation with the formation of electrically isolated dead lithium metal. We present a lithium restoration method based on a series of iodine redox reactions mainly involving I-3(-)/I-. Using a biochar capsule host for iodine, we show that the I-3(-)/I- redox takes place spontaneously, effectively rejuvenating dead lithium to compensate the lithium loss. Through this design, a full-cell using a very limited lithium metal anode exhibits an excellent lifespan of 1,000 cycles with a high Coulombic efficiency of 99.9%. We also demonstrate the design with a commercial cathode in pouch cells. Cycling lithium batteries often results in inactive lithium that no longer participates in redox reactions, leading to performance deterioration. Here the authors use an iodic species to react with inactive lithium, bringing it back to life and thus making batteries last longer.", + "Times Cited, WoS Core": 373, + "Times Cited, All Databases": 400, + "Publication Year": 2021, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000627674900001", + "Markdown": "# Rejuvenating dead lithium supply in lithium metal anodes by iodine redox \n\nChengbin Jin $\\textcircled{12}1,4$ , Tiefeng Liu $\\textcircled{10}1,4$ , Ouwei Sheng1, Matthew Li $\\oplus2$ , Tongchao Liu2, Yifei Yuan $\\textcircled{1}$ 2, Jianwei Nai $\\oplus1$ , Zhijin $\\mathbf{J}\\mathbf{u}^{1}$ , Wenkui Zhang $\\mathbb{O}^{1}$ , Yujing Liu $\\oplus1$ , Yao Wang $\\mathbb{O}^{1}$ , Zhan Lin $\\textcircled{10}3$ , Jun Lu $\\textcircled{1}2\\boxtimes$ and Xinyong Tao   1 ✉ \n\nInactive lithium (more frequently called dead lithium) in the forms of solid–electrolyte interphase and electrically isolated metallic lithium is principally responsible for the performance decay commonly observed in lithium metal batteries. A fundamental solution of recovering dead lithium is urgently needed to stabilize lithium metal batteries. Here we quantify the solid–electrolyte interphase components, and determine their relation with the formation of electrically isolated dead lithium metal. We present a lithium restoration method based on a series of iodine redox reactions mainly involving $\\pmb{\\mathrm{I}}_{3}^{-}/\\pmb{\\mathrm{I}}^{-}$ . Using a biochar capsule host for iodine, we show that the $\\pmb{\\mathrm{I}}_{3}^{-}/\\pmb{\\mathrm{I}}^{-}$ redox takes place spontaneously, effectively rejuvenating dead lithium to compensate the lithium loss. Through this design, a full-cell using a very limited lithium metal anode exhibits an excellent lifespan of 1,000 cycles with a high Coulombic efficiency of $99.9\\%$ . We also demonstrate the design with a commercial cathode in pouch cells. \n\nithium (Li) is the charge carrier in both conventional Li-ion batteries and emerging Li metal batteries1. It acts as an indispensable medium to ensure battery operation. However, improvements to battery energy, lifespan and safety are all urgently needed in various applications such as electric vehicles and grid energy storage2. Presently, the inactive Li supply (more frequently called dead Li) in the form of solid–electrolyte interphase (SEI) and electrically isolated metallic Li has been identified as the main origin of the capacity decay and insufficient lifespan3–5. Moreover, it has recently been recognized that dead Li, probably preceding dendrites, accounts for thermal runaway5. These adverse obstacles of Li chemistries are critically dependent on the properties of the SEI on anode surfaces. \n\nIn a typical Li-ion cell with the classic graphite anode, it is well accepted that the SEI components mainly include LiF, together with certain amounts of $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ , alkyl carbonate and so on, and that they arise from the reduction of organic electrolytes in the very first cycles6,7. The shift from graphite to a much higher energy Li metal anode, however, substantially complicates the SEI formation, because the SEI chemical components highly depend not only on the types of electrolytes, but also on the reactivity of the anode8. Very recent studies have provided strong evidence that $\\mathrm{Li}_{2}\\mathrm{O}$ instead of LiF is the dominant component in the SEI layer formed on Li metal9–14. Moreover, the inherent volume variation of the Li plating/ stripping compromises the mechanical integrity and corresponding passivation functionality of the $\\mathrm{Li}_{2}\\mathrm O$ -dominated SEI4, and thus leads to the formation of dead Li. Some state-of-the-art artificial SEI structures15–19 and SEI-regulated electrolyte additives (for example, caesium hexafluorophosphate, fluoroethylene carbonate, $\\mathrm{LiNO}_{3},$ LiF, LiI)20–25 have been proposed to improve the performance of Li metal. However, the SEI breaks due to the volume variation of Li, and fresh Li is again exposed to the electrolyte, forming a new SEI. Such repeated breakage–repair of the SEI makes these strategies non-durable in long-term cycling. Further, the underlying relationship between the dead SEI and isolated Li metal debris is still unclear. A compelling demonstration of inhibiting dead Li to prevent battery failure would be even more difficult to clarify. \n\nIn this work, built on the recent recognition that $\\mathrm{Li}_{2}\\mathrm{O}$ dominates the dead SEI on Li metal anodes, we quantified the $\\mathrm{Li}_{2}\\mathrm{O}$ content in the SEI layer. More importantly, we unravelled the roles of the dead SEI in producing electrically isolated dead Li metal and showed that both Li loss in the SEI and dead Li debris are principally responsible for the performance decay commonly observed in Li metal batteries. Such a discovery guided us to design a Li restoration method based on an iodine redox chemistry that can effectively rejuvenate electrochemically inactive Li in both the dead SEI and electrically isolated Li metal debris (Fig. 1). The proposed $\\mathrm{Li}_{2}\\mathrm{O}$ transport from the dead SEI to a/the newly exposed Li surface not only efficiently eradicates the dead SEI and Li debris accumulation during the Li plating/stripping cycles, but also notably suppresses the highly active metal-induced electrolyte decomposition commonly occurring in Li cells. Meanwhile, a cathode with a discharging voltage over the iodine redox $(2.89\\mathrm{V})$ enables reversible iodine shuttling that is capable of recovering inactive Li back to the cathode (Fig. 1). The resultant Li metal anode in a half-cell delivers a high Coulombic efficiency (CE; $99.5\\%$ for 1,000 cycles) and ultralong lifespan $(\\sim2,000\\mathrm{h})$ . When coupled with commercial cathodes like $\\mathrm{LiFePO_{4}}$ (LFP) and $\\mathrm{LiNi_{0.8}C o_{0.1}M n_{0.1}O_{2}}$ (NCM811) for both coin and pouch cells, the cells exhibit very encouraging cyclability and high efficiency. We believe that the proposed strategy could open up a different window to relieve the inactive-Li-supply-induced capacity decay of Li metal batteries and improve their cycling lifetimes towards practical application. \n\n# Atomic identification of the dead SEI \n\nOperation of a carbon-free copper $\\mathrm{(Cu)}$ grid as the host of Li metal allows the surface of the Li metal to be directly detected by cryogenic transmission electron microscopy (cryo-TEM)26–28. The SEI formation on the metallic Li surface is accompanied by the initial Li deposition onto the Cu grid in an ether-based electrolyte. Once the deposited Li is stripped, this SEI appears to collapse towards the Cu grid (Supplementary Fig. 1). In subsequent Li deposition, corresponding Li metal microspheres use a newly formed SEI rather than the collapsed SEI residue on the Cu grid (Fig. 2a). Obviously, the collapsed SEI has no ability in hosting and protecting the replated fresh $\\mathrm{Li}^{29}$ . These specific SEI residues are what we call dead SEI as they no longer function as a SEI and instead trap the Li source. \n\n![](images/ff05045d37df5a6c27fa1ae25f65ad92c00bf8a977cd7259c75b59e611b04cda.jpg) \nFig. 1 | Li restoration based on iodine redox shuttling. The inactive Li sources in a dead SEI are spontaneously removed by ${\\bigl\\vert}_{3}^{~-}$ additive to form soluble LiI and ${|\\mathsf{O}_{3}}^{-}$ species. Meanwhile, $\\mathsf{L i l O}_{3}$ can be reduced by Li metal to $\\mathsf{L i}_{2}\\mathsf{O}$ and LiI so that $\\mathsf{L i}_{2}\\mathsf{O}$ is still deposited onto the anode and forms part of the healthy SEI. The oxygen of $\\mathsf{L i}_{2}\\mathsf{O}$ in the dead SEI is transferred to refresh the SEI on the Li anode through a soluble $\\mathsf{L i l O}_{3}$ -based oxygen transport vehicle. In addition, the ${\\mathfrak{l}}_{3}^{-}$ additive also reacts with the Li debris to give LiI. All Li released from the dead SEI or dead Li is in the form of soluble LiI species and transferred to cathodes through a LiI-based lithium transport vehicle, eventually returning back to the anode with a subsequent charge process. At the cathode side, the transferred LiI can react with delithiated LFP to regenerate ${\\mathsf{I}}_{3}^{-}$ , which subsequently diffuses back to the anode to continue the rejuvenation of the dead SEI or dead Li. \n\nHigh-resolution cryo-TEM further revealed that the SEI was dominated by a massive crystal of $\\mathrm{Li}_{2}\\mathrm{O}$ (coloured green), which was confirmed by a lattice space matching the {111} planes30,31 and corresponding fast Fourier transform (Fig. 2b)13,14. By using high-angle annular dark-field scanning transmission electron microscopy combined with energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy mapping, we also detected a strong oxygen signal (Supplementary Fig. 2). The mass content ratio between oxygen and carbon $\\scriptstyle(\\mathrm{O}/\\mathrm{C})$ was calculated to be as high as 10.2 (Fig. 2c). The identification of $\\mathrm{Li}_{2}\\mathrm{O}$ in the SEI was also reconfirmed by Raman and X-ray photoelectron spectroscopy (XPS) measurements (Supplementary Figs. 3 and 4). Quantifying the $\\mathrm{Li}_{2}\\mathrm{O}$ content over $60\\%$ in the external SEI according to the depth-profile XPS, we have demonstrated that $\\mathrm{Li}_{2}\\mathrm{O}$ was indeed the major component in the SEI. The other components of Li loss in the dead SEI are tentatively ascribed to LiF, ROLi (R is the alkyl group), LiOH and so $\\mathrm{{on^{8}}}$ . Therefore, when the first cycle is completed, a majority of the dead Li occurs in the form of the $\\mathrm{Li}_{2}\\mathrm O$ -dominated $\\mathrm{SEI^{9,29}}$ . \n\nAs long as the Li plating–stripping is continually performed, abundant metallic Li debris surrounded by the porous and broken SEI can be observed on the Cu grid (Supplementary Fig. 5). The overall thickness of the dead SEI and isolated Li debris repeatedly formed on the Cu grid gradually increases with the cycle number (Supplementary Fig. 6). Unfortunately, the metallic Li debris encapsulated by the insulated dead SEI loses its electrical contact with the Cu substrate, eventually forming an inactive Li supply (known as dead metallic Li debris)4. Herein, combining cryo-TEM with XPS and Raman measurements, it is clear that most of the Li loss in Li metal batteries can be traced down to two main components: $\\mathrm{Li}_{2}\\mathrm{O}$ in the dead SEI and dead metallic Li debris. More importantly, the identification of the major Li mass sinks provides the opportunity of developing a comprehensive strategy to retrieve and rejuvenate these Li atoms back into the circulation of the battery. \n\n# Design concept to remove dead Li \n\nAs both forms of dead Li are physically disconnected from the circuit, we designed a method in which a soluble redox active species can chemically rejuvenate the dead Li from the two major Li mass sinks. From a thermodynamic viewpoint, the triiodide ion $\\bigl(\\mathrm{I}_{3}^{~-}$ ; the dominant form of iodine in a polar solvent32,33) has immense potential. The reaction of ${\\mathrm{I}}_{3}^{-}$ with $\\mathrm{Li}_{2}\\mathrm{O}$ is thermodynamically spontaneous (Supplementary Fig. 7), according to the free energy calculated in equation (1). Typically, cycled Li metal anodes appear to be dark due to massive dead SEI stacking on the surface (Supplementary Fig. 8a). When soaked in iodine-containing electrolyte, such an electrode immediately brightens, with the tarnish stemming from the dead SEI quickly dissolving into the electrolyte (Supplementary Fig. 8b). XPS analysis further verified a $\\mathrm{Li}_{2}\\mathrm{O}$ content of less than $50\\%$ in the external SEI (Supplementary Fig. 9), which was much lower than that in iodine-free electrolyte (Supplementary Fig. 4). These experiments conclusively point to the fact that iodine can remove the dead SEI in quite an efficient manner. \n\n![](images/8b9b87b3d2f84fd84b0d7899df20b55fc20142860c18b773ea585fa8cb1bedb5.jpg) \nFig. 2 | Microstructures and components of different SEIs. a, Cryo-TEM image of plated Li and SEI on a Cu grid after one cycle in LiTFSI–DOL–DME. b, High-resolution cryo-TEM image of the SEI layer on plated Li in LiTFSI–DOL–DME. Inset is the corresponding fast Fourier transform pattern. Regions outlined with green are $\\mathsf{L i}_{2}\\mathsf{O}.$ . c, Mass content of C, N, O, F and S in the plated Li and SEI in LiTFSI–DOL–DME. d, High-resolution cryo-TEM image of the SEI layer on plated Li in $\\mathsf{L i P F}_{6}$ –EC–EMC–DEC. Inset is the corresponding fast Fourier transform pattern. Regions outlined with green are $\\mathsf{L i}_{2}\\mathsf{O}$ . e, Cryo-TEM image of plated Li and SEI on a Cu grid after one cycle in iodine-containing LiTFSI–DOL–DME. f, High-resolution cryo-TEM image of the SEI layer on plated Li in iodine-containing LiTFSI–DOL–DME. Inset is the corresponding fast Fourier transform pattern. Regions outlined with green are $\\mathsf{L i}_{2}\\mathsf{O}$ . g, Mass content of C, N, O, F, S and I in the plated Li and SEI in iodine-containing LiTFSI–DOL–DME. h, High-resolution cryo-TEM image of the SEI layer on plated Li in iodine-containing LiPF $\\overline{{6}}^{\\prime}$ –EC–EMC–DEC. Inset is the corresponding fast Fourier transform pattern. Regions outlined with green are $\\mathsf{L i}_{2}\\mathsf{O}$ . \n\n$$\n3\\mathrm{Li}_{2}\\mathrm{O}+3\\mathrm{I}_{3}^{-}=6\\mathrm{Li}^{+}+\\mathrm{IO}_{3}^{-}+8\\mathrm{I}^{-}\n$$ \n\nAn atomic analysis of the corresponding Li metal morphology by cryo-TEM provides more details on the effectiveness of iodine introduced into the electrolyte. After one cycle, neat Li metal microspheres without a dead SEI and isolated Li debris grew on the Cu grid, and a smooth and dense SEI tightly covered the Li metal surface (Fig. 2e). This SEI is still composed of a crystalline $\\mathrm{Li}_{2}\\mathrm{O}$ component (Fig. 2f). Chemical analysis from energy dispersive X-ray spectroscopy reveals the $_{\\mathrm{O/C}}$ mass ratio of 5.5 (Fig. $2\\mathrm{g}$ and Supplementary Fig. 10), which is much lower than that of the case using iodine-free electrolyte (Fig. 2c). Such a variation in the $_{\\mathrm{O/C}}$ ratio is also consistent with the XPS results. Additionally, in ester-based electrolyte, the positive role of iodine chemistries in reducing $\\mathrm{Li}_{2}\\mathrm O$ in the SEI was also observed by comparing the samples with or without iodine (Fig. 2d,h). After various cycles, no obvious dead SEI and Li debris accumulation were observed on the Cu grid (Supplementary Fig. 11). Along with the removal of $\\mathrm{Li}_{2}\\mathrm{O}$ in the dead SEI and dead Li debris, residual components (Supplementary Fig. 12) mainly including LiF, ROLi, LiOH and so on are also observed on the Cu grid. Meanwhile, no obvious crystal lattices for LiI or $\\mathrm{LiIO}_{3}$ were detected. \n\n# Iodine redox to restore Li and preserve electrolyte \n\nWhen the iodine is introduced into the electrolyte, the subsequently formed ${\\mathrm{I}_{3}}^{-}$ will attack the $\\mathrm{Li}_{2}\\mathrm{O}$ in the dead SEI on the Li metal surface according to equation (1), supported by the arrival of $\\mathrm{IO}_{3}^{-}$ , which appears in the ultraviolet spectra (Fig. 3a). Meanwhile, a spontaneous reaction as described by equation (2) cannot be overlooked due to the existence of Li metal (Supplementary Fig. 7). The first step of this process helps the removal of the Li debris from the anode surface. The second step is $\\mathrm{Li}_{2}\\mathrm{O}$ transport from the dead SEI to the surface of the bulk Li metal anode to enable a new, healthy SEI. \n\n$$\n6\\mathrm{Li}+\\mathrm{IO}_{3}^{-}=\\mathrm{I}^{-}+3\\mathrm{Li}_{2}\\mathrm{O}\n$$ \n\nTo elucidate the $\\mathrm{Li}_{2}\\mathrm{O}$ transfer process, we used isotope tracing characterization of elemental $^{18}\\mathrm{O}$ . The $\\mathrm{Li}_{2}^{18}\\mathrm{O}$ , which was synthesized and confirmed by $\\mathrm{\\DeltaX}$ -ray powder diffraction measurement (Supplementary Fig. 13a), acted as the prototype of $\\mathrm{Li}_{2}\\mathrm{O}$ in the dead SEI. The Li foil and $\\mathrm{Li}_{2}^{18}\\mathrm{O}$ powders were put into the electrolyte container separated by a polypropylene membrane that we used to avoid contamination between the samples (Fig. $^{3\\mathrm{b},\\mathrm{c}}$ ). According to equations (1) and (2), this test is an emulation of the $\\mathrm{Li}_{2}\\mathrm{O}$ transfer process during cycling through a soluble $\\mathrm{LiIO}_{3}$ -based oxygen transport vehicle. As expected, the Li foil using iodine-containing electrolyte was identified as having strong signals of elemental $^{18}\\mathrm{O}$ (Fig. 3d). No such signals were detected in the Li foil using iodine-free electrolyte. This demonstration of the $\\mathrm{Li}_{2}\\mathrm{O}$ transfer was also confirmed in the predesigned coin cell using an iodine-containing electrolyte, indicating the role of iodine for $\\mathrm{Li}_{2}\\mathrm O$ transfer in the real cell scenario (Supplementary Fig. 13b). Therefore, an exquisite combination of equations (1) and (2) naturally drives $\\mathrm{Li}_{2}\\mathrm{O}$ transfer from dead SEIs to a newly exposed Li surface. Furthermore, as $\\mathrm{LiIO}_{3}$ reduction to $\\mathrm{Li}_{2}\\mathrm{O}$ and LiI is thermodynamically favourable, newly exposed or plated Li will always have recycled $\\mathrm{Li}_{2}\\mathrm O$ deposited on it. \n\n![](images/554ed7d064b6a7c4baa21c105c7ff3eae038feaa1100b1ff4350c7bf445f88c1.jpg) \nFig. 3 | The underlying functions of iodine species. a, Ultraviolet spectra of $\\mid_{2}$ in DOL, $\\mathsf{L i}_{2}\\mathsf{O}$ in DOL and $\\mathsf{L i}_{2}\\mathsf{O}-\\mathsf{I}_{2}$ in DOL. b, The design of the container using a polypropylene membrane to test $\\mathsf{L i}_{2}\\mathsf{O}$ transfer. c, The Li foil is soaked in the electrolyte containing iodine and $\\mathsf{L i}_{2}^{18}\\mathsf{O}$ d, The isotope tracing analysis for elemental ${}^{18}\\mathrm{O}.8{}^{18}\\mathrm{O},$ isotope-ratio deviation $({}^{18}\\mathrm{O}/{}^{16}\\mathrm{O})$ between testing samples and reference material; VPDB, ‘Vienna Pee Dee Belemnite’ scale—a standard reference for isotopic measurements. e, X-ray powder diffraction patterns of LFP, fully charged LFP $(\\mathsf{F e P O}_{4})$ and ${\\mathsf{F e P O}}_{4}$ soaked in the LiI-containing solution. PDF, powder diffraction file database. f, A digital photo of LiI solution and LiI solution with added $\\mathsf{F e P O}_{4}$ . The colour of the LiI solution after adding ${\\mathsf{F e P O}}_{4}$ changed to pale yellow. \n\nNoting that equation (3) also allows the removal of dead Li debris by ${\\mathrm{I}_{3}}^{-}$ , most of the product from equations (1) and (3) is soluble LiI. Considering that the vast majority of cathodes have a working voltage $(>3.0\\mathrm{V})$ over the oxidation potential (2.89 V) of $\\mathrm{I}^{-}$ to ${\\mathrm{I}_{3}}^{-}$ (ref. 32), we further design this procedure of rejuvenating Li sources, releasing Li back to the battery cycling. \n\n$$\n2\\mathrm{Li}+\\mathrm{I}_{3}^{-}=2\\mathrm{Li}^{+}+3\\mathrm{I}^{-}\n$$ \n\nTypically, it is well accepted that the stable LFP cathode offers a discharge platform at $3.4\\mathrm{V}^{34,35}$ , resulting in a spontaneous reaction as in equation (4), driving the recycling of the Li source into the cathode36. As evidence, both the peaks of ${\\mathrm{I}}_{3}^{-}$ (refs. $^{32,37}$ ) in the ultraviolet spectra and the phase transition of LFP in $\\mathrm{\\DeltaX}$ -ray powder diffraction measurement, as well as the colour evolution of LiI solution when adding ${\\mathrm{FePO}}_{4},$ confirm the above chemical redox reaction (Fig. 3e,f and Supplementary Fig. 14). \n\n$$\n2\\mathrm{Li^{+}}+3\\mathrm{I^{-}}+2\\mathrm{FePO_{4}}=2\\mathrm{LiFePO_{4}}+\\mathrm{I_{3}}^{-}\n$$ \n\nSimilarly, this demonstration in Li reuse is also confirmed in the predesigned cell using in situ Raman spectroscopy combined with cyclic voltammetry (Supplementary Fig. 15a). At a high scanning rate of $1\\mathrm{mVs}^{-1}$ , the cathodic/anodic peaks at ${\\sim}3.68/3.25\\mathrm{V}$ clearly belong to the LFP (Supplementary Fig. $^{15\\mathrm{b,c}}$ ). In addition, the sloping charging–discharging profiles of the cathode also indicate the electrochemical contributions of iodine oxidation (Supplementary Fig. 15b). When the voltage of the cathode was over $3.0\\mathrm{V}$ in the first charge–discharge process, the conversion from $\\mathrm{I^{-}}$ to ${\\mathrm{I}}_{3}^{-}$ occurred due to concerted chemical and electrochemical oxidations (Supplementary Fig. 16). The second charge process with the voltage over $3.0\\mathrm{V}$ drives a similar reversible iodine conversion. The resulting ${\\mathrm{I}}_{3}^{-}$ species enriched on the cathode side will gradually diffuse back to the anode, and will continue to attack the dead SEI and Li debris. \n\nNote that in the presence of iodine species, quantitative elemental analysis further verified that all the elements in the SEI have only a slight content fluctuation after cycling (Fig. 4a). Similarly, the amount of organic gas molecules (hydrocarbon) obviously decreased (Fig. 4b), indicating that the amount of electrolyte consumed decreased in both ester and ether systems. According to frontier molecular orbital theory (Fig. 4c), the redox reaction activities of the electrolyte are highly dependent on the energy levels of the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO). All the iodic species have a relatively low LUMO energy level $(-2.63\\mathrm{eV}$ for $\\mathrm{LiIO}_{3}$ and $-3.62\\mathrm{eV}$ for ${\\boldsymbol{\\mathrm{I}}}_{3}{\\mathrm{,}}$ , that is, a higher electron affinity, and are easy to reduce during the SEI formation. In other words, all the iodic species react with Li metal more easily compared with other solutes and solvents, thus suppressing the electrolyte decomposition. \n\n![](images/50cede1456e2628878e954eafe7653a994ace8abbe0ba330a4845938df82c123.jpg) \nFig. 4 | The inhibition of the electrolyte exhaustion by iodine species. a, Element contents in the SEI formed in an iodine-containing electrolyte at the Li plating state after various cycles. b, Contents of hydrocarbon from the LiFe $\\mathsf{P O}_{4}$ full-cells with or without iodine in ester or ether electrolyte. NA means the targeted content of the sample is beyond the detection limit. c, LUMO–HOMO energy level diagram of solutes and solvents. The blue and yellow surfaces represent the orbital wavefunction with opposite directions. FEC, fluoroethylene carbonate. \n\n# Design and characterization of iodine-storing carbon host \n\nConsidering the iodine chemistries applied in Li metal batteries, finding an appropriate host for both Li deposition and iodine loading is of great importance. It is widely accepted that the use of low-cost and environmentally friendly porous carbon as the host for Li storage allows a more uniform Li deposition, compared with naked Cu foils38,39. Furthermore, porous carbon with heteroatom doping has been reported as a preferred host for the iodine cathode in Li–iodine batteries. Among the heteroatom candidates for doped carbon, N-doped carbon is frequently reported37. According to density functional theory calculation, N-doped carbon exhibits a stronger adsorption for iodine species (including $\\mathrm{I^{-}}$ , ${\\mathrm{I}_{3}}^{-}$ and $\\mathrm{IO}_{3}^{-}$ ) compared with pristine carbon (Fig. 5a,b and Supplementary Fig. 17). Therefore, N-doped porous carbon is critically predesigned to enable the enrichment of iodine species in the anode. \n\nIn this context, different carbon powders, including carbonized porous conidial powder (CPC, a naturally N-doped carbon), commercial activated carbon (Carbot VXC-72R, VC; Ketjenblack EC-300J, KEC) and their N-doped carbon versions (NVC and NKEC), were investigated for iodine absorption (Fig. 5c,d and Supplementary Fig. 18a,b). The iodine absorption capacity of the various carbons was first investigated. Among them, the biomass-based CPC exhibits the best adsorption for iodine after $24\\mathrm{h}$ (Fig. 5e,f). Further analysing the data, including the specific surface area, pore size and N-doping content of the different carbon powders as summarized in Supplementary Fig. 18c–e, leads us to believe that the adsorption and sustained release of iodine species is associated with the appropriate pore size $(2.7\\mathrm{nm})$ . The iodine–CPC composite (ICPC) was fabricated by a facile and simple solution adsorption method. The ICPC allows a uniform adsorption of iodine (Fig. 5g). Notably, various iodine–carbon samples were prepared by simply changing the mass ratios between iodine and carbon. \n\n# Electrochemical effects of iodine species on cell evaluation \n\nThe ICPC has dual functions as the Li metal host and iodine source. An in situ Raman test of ICPC–Li half-cells using a transparent battery proved that the peaks of ${\\mathrm{I}}_{3}^{-}$ gradually decreased in the Li plating process, but barely increased in the subsequent Li stripping process (Supplementary Fig. 19), which is attributed to there being no obvious reversible reactions of ${\\mathrm{I}_{3}}^{-}$ during the Li plating–stripping operation. However, the peak of ${\\mathrm{I}}_{3}^{-}$ can be detected during the Li stripping, indicating the slow release of the iodine stored in ICPC. Different iodine-modified carbon hosts for Li storage were first evaluated by a Li–Cu half-cell test. Notably, it is very necessary for the cells to implement an initial activation for a better electrochemical assessment (Supplementary Fig. $20)^{40}$ . \n\nThe capacity of Li plating–stripping is fixed at $1\\mathrm{mAhcm}^{-2}$ with different current densities (Fig. 6a–c and Supplementary Fig. 21). Both a high CE and a long lifetime of different iodine-modified carbon hosts indicate their feasibility in Li storage. The ICPC electrode in the half-cell maintains a high average CE over $99.5\\%$ for 1,000 cycles $2,000\\mathrm{h}$ operation time) at $1\\mathrm{mAcm}^{-2}$ , which is better than that of the other samples. Even at an increased current density of 3 or $5\\operatorname{mA}\\mathrm{cm}^{-2}$ , the ICPC electrode still exhibits the best electrochemical behaviours, including a high average CE of $98.1\\%$ for 400 cycles and $97.8\\%$ for 300 cycles. Moreover, the ICPC electrode also delivers a high CE at various cycling capacities from 1 to $20\\mathrm{mAhcm}^{-2}$ (Fig. 6d and Supplementary Fig. 22). The ICPC electrode in symmetric cell tests has reduced Li plating–stripping overpotentials at various current densities, a low voltage hysteresis of $20\\mathrm{mV}$ for ${\\sim}700$ cycles (except the first 70 cycles) and an ultralong lifespan of $\\mathord{\\sim}1,500\\mathrm{h}$ (Fig. 6e and Supplementary Fig. 23). Such data verify the effectiveness of ICPC in stabilizing the Li metal anode. Therefore, more evaluations are implemented for the ICPC electrode. After a series of controlled studies (Supplementary Figs. 24–26), the optimized mass ratio between iodine and carbon is confirmed as 1:2. The reality is that the dominant component in a dead SEI on a Li metal anode as well as the contributions of iodine species to the dead SEI and Li debris has not yet been subjected to the electrolyte systems (Supplementary Fig. 27). \n\n![](images/9914f6571d2b9dc22ea9b4e42b5f6a45c1e946040e781c8d7b9643043c77b55e.jpg) \nFig. 5 | Fabrication and characterization of ICPC. a, Side views of differential charge density distributions of absorbed $\\mathsf{I}^{-},\\mathsf{I}_{3}^{-}$ and $10_{3}^{-}$ on N-doped carbon. b, Adsorption energy for I−, ${\\mathfrak{l}}_{3}^{-}$ and ${|\\mathsf{O}_{3}}^{-}$ upon pristine and N-doped carbon. c, SEM image of CPC before carbonization. d, SEM image of CPC after carbonization. e, Optical images of adsorbing ability of various carbon types for iodine. f, Iodine adsorption capacity with various carbon types after $24\\mathsf{h}$ . g, TEM image and elemental mappings of ICPC particles. \n\nThe good performance of the ICPC electrode prompted us to carry out a full-cell evaluation in a pair with a LFP cathode $(2\\operatorname*{mAh}\\mathrm{{hcm}^{-2})}$ ). The full-cell with $\\mathrm{Li@ICPC}$ anode (Li-metal-plated ICPC anode, with preplating of $2\\operatorname*{mA}\\mathrm{hcm}^{-2}.$ ) at a low ratio of the areal capacity of negative to positive electrodes $(N/P)$ of two was fabricated41. Generally, a conventional full-cell inherently suffers from a fast decay of battery performance due to insufficient $\\mathrm{CE}^{34,42,43}$ . Such a decay is only seen in a full-cell, not in a half-cell with its extremely excessive Li sources44. Conversely, the full-cell has an excellent cyclability of 300 times at 1 C $\\mathrm{^{\\prime1C=170mAhg^{-1}}}$ ) with a capacity retention ratio of $90\\%$ and a CE of $99.9\\%$ (Fig. 7a,b). The maintenance of available Li ions at an extremely low $N/P$ ratio is achieved, suggesting the sustainable operation of an ICPC in a practical cell setting. \n\nIn further confirmation of a prolonged cycling test, $\\mathrm{Li@CPC}$ (Li-metal-plated CPC), $\\mathrm{Li@Cu}$ (Li-metal-plated Cu foil) and $\\operatorname{Li@}$ ICPC anodes with a Li capacity of $3\\mathrm{mAhcm}^{-2}$ were fabricated based on the $N/P$ ratio of 2.5. At pristine states without iodine, the capacity of cells using $\\mathrm{Li@CPC}$ and $\\operatorname{Li@Cu}$ anodes as expected decayed quickly, within 1,000 cycles, to only 82 and $35\\mathrm{mAhg^{-1}}$ , respectively, with a low capacity retention of $56\\%$ and $22\\%$ (Fig. 7c), respectively. These results illustrate that the capacity design of the Li metal anode at an $N/P$ ratio of 2.5 barely offsets the Li loss for a stable cycling lifespan. By contrast, the cell with the $\\mathrm{Li@ICPC}$ anode showed a reversible specific capacity of $120\\mathrm{mAhg^{-1}}$ at 1 C with a stable cycling lifespan of 1,000 times. Both a high capacity retention of ${\\sim}80\\%$ and the CE of $99.9\\%$ were also readily achieved. Moreover, this Li@ICPC anode in rate measurements (Supplementary Fig. 28) delivered a better performance of specific capability and cycling stability than did the $\\operatorname{Li@CPC}$ and $\\mathrm{Li@Cu}$ anodes. Additionally, when the $N/P$ ratios were further reduced to 1.5 and 1 with the increase of the charge cut-off voltage from 3.8 to $4.2\\mathrm{V},$ the LFP full-cells using the $\\mathrm{Li@ICPC}$ anodes still delivered a remarkable electrochemical performance (Supplementary Fig. 29). The potential real application of iodine was further verified using the pouch cells $(0.5\\mathrm{Ah}$ level, Fig. 7d). In the absence of iodine, the LFP/Li@Cu and LFP/ $\\mathrm{Li@CPC}$ pouch cells suffer rapid capacity decay towards battery failure (Fig. 7e). By contrast, the LFP/Li@ICPC pouch cell exhibits better stability in the cycling lifetime (Fig. 7e). The success in both the coin-type and pouch cells of such iodine chemistries can also be translated into Li metal batteries with other cathodes like NCM811 (Supplementary Fig. 30). \n\n![](images/8167e4cf8984f90882b6121ac83dd710a73e79d90c4c41c59af90428c6dcd16e.jpg) \nFig. 6 | Electrochemical performance in the half-cells. a, CE of CPC and ICPC samples at $1\\mathsf{m A c m}^{-2}$ . b, CE of CPC and ICPC samples at $3\\mathsf{m A c m}^{-2}$ . c, CE of CPC and ICPC samples at $5\\mathsf{m A c m}^{-2}$ . d, The CE results of the ICPC electrode at various cycling capacities from 1 to $20\\mathsf{m A}\\mathsf{h c m}^{-2}$ . e, The voltage profiles of ICPC and CPC electrodes in symmetric cells at various current densities $(j)$ . \n\nDespite this success in relieving the issue of an inactive Li supply, limitations exist. This self-restoration of dead Li is powered by cell energy, which indicates a trade-off between the energy exhausted and enhanced performance. In addition, the effectiveness of this strategy is limited to the $\\mathrm{Li}_{2}\\mathrm O$ and Li debris, which are the major contribution to Li loss. Along with electrolyte decomposition, small amounts of other components (for example, LiF and ROLi) inevitably accumulate after prolonged cycling. This is inferred from the energy dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy analysis for the cycled SEI with different cycles (Fig. 4a). A further proof is the residual components observed by cryo-TEM (Supplementary Fig. 12), illustrating the accommodation of other components in the dead SEI after the effective elimination of iodine to $\\mathrm{Li}_{2}\\mathrm O$ . \n\n# Conclusions \n\nIn this work, we have demonstrated an effective strategy of rejuvenating the dead Li of Li metal batteries via iodine redox chemistry, which differs from the electrolyte additives that are widely used for regulating the SEI component (Supplementary Table 1). The inactive Li in the $\\mathrm{Li}_{2}\\mathrm{O}$ of a dead SEI and dead Li metal debris are transferred to the high-voltage cathode and subsequently recovered to compensate for the Li loss, leading to a remarkably improved cyclability of Li metal cells. Moreover, potential real-world application has been demonstrated in the test of commercially comparable pouch cells assembled with a $\\mathrm{Li@ICPC}$ anode and LFP cathode. In addition, this strategy may be developed into other anode materials that are challenged by a dead SEI, such as silicon, tin, alloys and so on, for large-scale application. \n\n# Methods \n\nPretreatment of conidial powder. Conidial powder (CP, average diameter of $4{\\mathrm{-}}5{\\upmu\\mathrm{m}})$ was purchased and employed as the raw material, without breaking the wall. The CP was composed of a tender core (containing genetic material like proteins and nucleic acids) and a porous exine (mainly cellulose and hemicellulose). In order to remove undesired chemical substances from the CP, it was first treated with $50\\mathrm{ml}$ ethanol under ultrasound for 1 h, followed by washing with deionized water several times. After that, the CP surface was cleaned and the core substances were dissolved out. Then, the CP was treated with a $50\\mathrm{ml}$ mixed solution of ethanol and formaldehyde $\\begin{array}{r}{\\mathrm{(v/v=1:1)},}\\end{array}$ ) to fix the natural morphology of the CP. The fixed CP was obtained via centrifugation with deionized water. Finally, a precarbonization process was carried out to further stabilize the morphology of the CP, which was achieved in $12\\mathrm{M}$ sulfuric acid at $80^{\\circ}\\mathrm{C}$ for 4 h. The pretreated CP was collected after washing to neutralize it and was freeze dried. \n\nSynthesis of N-doped carbon hosts. The pretreated CP was heated at $300^{\\circ}\\mathrm{C}$ for 4 h under an atmosphere of argon gas, and then carbonized at $700^{\\circ}\\mathrm{C}$ for 2 h with a heating rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ . After that, the CPC was obtained. As for commercial KEC and VC, they were blended with melamine, which was selected as the nitrogen source, with certain mass ratios. Then the mixtures were stabilized at $300^{\\circ}\\mathrm{C}$ in argon for $\\boldsymbol{4\\mathrm{h}}$ and then heated to $700^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ to collect the NKEC and NVC samples. \n\nSynthesis of iodine–carbon composite. The ICPC was synthesized via a simple solution method. First, a specific amount of iodine was dissolved in $20\\mathrm{ml}$ of ethanol, obtaining an orange–red solution. Then CPC was added and it was mixed with iodine $\\mathrm{\\bar{I}}_{2}/\\mathrm{CPC}=0{:}1$ , 1:1, 1:2, 1:3 and 1:4, $\\mathrm{m}/\\mathrm{m}$ ) under continuous stirring for 2 h. Finally, deionized water was added to make the iodine particles separate out and deposit on the CPC. After filtration and drying, various ICPC samples were collected and named CPC, ICPC-1, ICPC-2, ICPC-3 and ICPC-4, respectively. Based on the mass before and after loading the iodine, the mass content of iodine in the ICPC-1, ICPC-2, ICPC-3 and ICPC-4 samples was calculated to be close to the designed values. Other types of carbon, including KEC, NKEC, VC and NVC, were loaded with iodine by the same method, and these iodine–carbon composites were defined as IKEC, INKEC, IVC and INVC, respectively. \n\nCharacterization. The crystalline structure and phase information was confirmed via X-ray powder diffraction using an X’Pert Pro diffractometer with Cu Kα \n\n![](images/6d4b8c48128f493d240854a9e34ee06b7555f9d89df481337db89946ec61bfb9.jpg) \nFig. 7 | Electrochemical performance in the full-cells. a, The charge–discharge curves of the LFP coin-type cells with different anodes at 0.1 C. b, Cycling performance of $\\mathsf{i}@\\mathsf{l C P C}$ with a limited capacity of $2\\mathsf{m A h c m^{-2}}$ and a low $N/P$ ratio of 2. c, Cycling performance of L $\\mathsf{i}@\\mathsf{l C P C}$ , L $\\mathsf{i}@{\\mathsf{C P C}}$ and L $@{\\mathsf{C u}}$ anodes with a limited capacity of $3\\mathsf{m A h c m}^{-2}$ and a low $N/P$ ratio of 2.5 in LFP full-cells at 1 C, solid and hollow circles represent capacity and coulombic efficiency, respectively. d, Charge–discharge curves of LFP/L $@$ ICPC pouch cell with a designed capacity of $0.5\\mathsf{A h}$ . e, Cycling performance of the LFP pouch cells using different anodes with a designed capacity of $0.5\\mathsf{A h}$ . The inset shows a digital photo of a pouch cell coupled with the $\\mathsf{L i@}\\mathsf{l C P C}$ anode and LFP cathode. \n\nradiation (wavelength, $\\lambda{=}0.15418\\mathrm{nm}$ ). Raman spectroscopy was conducted on a Renishaw InVia Raman spectrometer under a backscattering geometry $\\left(532\\mathrm{nm}\\right)$ to characterize the structural disorder degree of the samples. The morphology, microstructure and elemental component of various powder samples as well as the electrodes were observed by field emission scanning electron microscopy (SEM; FEI, Nova NanoSEM 450) and TEM (FEI, Talos-S), which were equipped with an energy dispersive spectroscopy detector. The chemical bond and elemental information was characterized via XPS using an Al Kα monochromatic $\\mathrm{\\DeltaX}$ -ray source $(1,486.6\\mathrm{eV},$ Axis Ultra DLD, Kratos). Notably, XPS on Li foil after prolonged cycles in electrolyte with/without iodine was conducted at different depths via Ar ion sputtering. A gentle sputtering with a power of $3.8\\mathrm{kV}\\times20\\mathrm{mA}$ on a $3\\mathrm{mm}\\times3\\mathrm{mm}$ surface was applied, with a sputtering rate on $\\mathrm{Ta}_{2}\\mathrm{O}_{5}$ calibrated to be $1\\mathrm{nmmin^{-1}}$ . We used a vacuum transfer vessel to move the samples directly into the vacuum transfer chamber of the XPS system without any exposure to air. Ultraviolet spectrophotometry (Caryl 100 Conc) was used to record the signal of ${\\mathrm{I}}_{3}^{-},{\\mathrm{I}}^{-}$ and $\\mathrm{IO}_{3}{}^{-}$ . Isotope tracing was tested with an isotope ratio mass spectrometer (DELTA V Advantage). The $\\mathrm{Li}_{2}^{18}\\mathrm{O}$ was prepared by reacting $\\mathrm{H}_{2}^{18}\\mathrm{O}$ with Li in a dry room (dew-point temperature of $-60^{\\circ}\\mathrm{C})$ ), after which the product was heated in a furnace filled with argon and decomposed into $\\mathrm{Li}_{2}^{18}\\mathrm{O}$ . A gas chromatograph was used to detect the gas evolution in the cycled pouch cells; $\\mathrm{CH}_{4},$ $\\mathrm{C}_{2}\\mathrm{H}_{2},$ $\\mathrm{C_{2}H_{4}}$ and $\\mathrm{C}_{2}\\mathrm{H}_{6}$ were detected by a GC-2014 gas chromatograph (Shimadzu) with a flame ionization detector and a carbon molecular sieve column (TDX-01, Shimadzu) by employing nitrogen as the carrier gas. \n\nDead SEI dissolving experiment. To confirm the positive effect of iodine species in treating a dead SEI, a simple visible experiment was carried out. Electrolyte \n\ncontaining iodine was prepared by adding iodine into $5\\mathrm{ml}$ of a solution of 1 M lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in an electrolyte of 1,3-dioxolane (DOL) and dimethoxy ethane (DME) solvents $\\mathrm{{'v/v}=1:1}$ ) with 0.1 M $\\mathrm{LiNO}_{3}$ . After several hours, the clear solution was taken out and used to soak cycled Li foil. Then the treated Li foil was removed and washed with DOL solvent before studying it with digital photos and SEM observation. \n\nSEI and Li observation in Li–Cu grid half-cells via cryo-TEM and SEM. To better observe the SEI after the Li was stripped, we designed a Li–Cu grid half-cell. The typical Cu grid used in TEM characterization was employed as the electrode to grow the Li and SEI. During this test, the Cu grid was coupled with the Li foil and electrolytes with and without the iodine additive, to assemble the cells. Then, these cells were cycled at $1\\mathrm{mAcm}^{-2}$ with a Li stripping–plating capacity of $1\\mathrm{mAhcm}^{-2}$ . After operation for different numbers of cycles, they were stopped with the Li plated on or stripped from the Cu grids. The Cu grids were then obtained and washed with DOL or DEC solvent, and were ready for SEM observation. As for the cryo-TEM test, the Cu grid was directly mounted to the holder (Gatan 698, cryo-transfer holder) and stabilized at a low temperature of $-170^{\\circ}\\mathrm{C}$ . All TEM characterizations were carried out using an FEI Talos-S transmission electron microscope operated at $200\\mathrm{kV}$ rather than a specialized, expensive cryo-transmission electron microscope. \n\nBattery fabrication and electrochemistry. Electrochemical studies were performed using 2032-type coin cells, which were fabricated in an argon-gas-filled glove box $\\mathrm{(H}_{2}O<0.1$ ppm, $\\mathrm{O}_{2}{<}0.1\\mathrm{ppm}$ . The half-cells for evaluating CE were composed of lithium foil, a Celgard 2400 separator and an iodine–carbon \n\ncomposite electrode (active materials/polyvinylidene difluoride (PVDF) binder, $4{:}1\\mathrm{m/m}$ ). Galvanostatic experiments were conducted on a Neware multichannel battery cycler. The batteries were first cycled three times from $0.01{-}1.0\\mathrm{V}$ at $0.05\\mathrm{mA}$ , stabilizing the SEI on and removing contamination from the electrode. Then, Li was plated within the iodine/carbon-based anode at $1\\mathrm{mAhcm}^{-2}$ , followed by charging the battery to $1.5\\mathrm{V}$ to strip the deposited Li. CE tests with different current densities and Li plating–stripping capacities were also investigated. Symmetric Li cells were assembled with two Li-plated iodine–carbon anodes, prepared by electrochemical plating of Li into iodine–carbon electrodes at $5\\mathrm{mAhcm}^{-2}$ . The symmetric Li cells were cycled at various current densities (1, 2, 3, 5, 3, 2, $1\\mathrm{mAcm}^{-2}$ ). The electrolyte for all the half-cells contained 1 M LiTFSI in DOL/DME $\\mathbf{\\bar{y}}/\\mathbf{v}=1{:}1$ ) with $0.1\\mathrm{M}\\mathrm{LiNO}_{3}$ or 1 M $\\mathrm{LiPF}_{6}$ in ethylene carbonate (EC)/ethyl methyl carbonate (EMC)/diethyl carbonate (DEC; $\\mathbf{v}/\\mathbf{v}/\\mathbf{v}=1{:}1{:}1\\mathbf{\\dot{\\Gamma}}$ ). \n\nThe full-cells employing Li@Cu, Li@CPC and Li@ICPC anodes containing 0, 0.5, 2 or $3\\mathrm{mAhcm}^{-2}$ metallic Li, paired with commercial cathode materials (LFP or NCM811) were assembled in 2032-type coins. The LFP cathode (areal capacity, 2 and $2.3\\mathrm{mAhcm^{-2}}$ ) was prepared via blending $80\\mathrm{wt\\%}$ LFP, $10\\mathrm{{wt\\%}}$ PVDF binder and $10\\mathrm{wt\\%}$ Super P. The NCM811 cathode was prepared via blending $90\\mathrm{wt\\%}$ NCM811, $5\\mathrm{wt\\%}$ PVDF binder and $5\\mathrm{wt\\%}$ Super P. The LFP full-cells with low $N/P$ ratios of 1, 1.5, 2 and 2.5 were cycled from 2.5 to $3.8\\mathrm{V}$ or 2.5 to $4.2\\mathrm{V}$ at various rates ranging from 0.1 to 10 C. The NCM811 full-cells were cycled from 2.9 to $4.3\\mathrm{V}$ at 40 and $200\\mathrm{mAg^{-1}}$ . The pouch cells were assembled by pairing $4\\mathrm{cm}\\times5\\mathrm{cm}$ double-sided NCM811 $\\mathrm{'}6\\mathrm{mAhcm^{-2}}$ on each side) or LFP $(2.3\\operatorname{mAh}\\operatorname{cm}^{-2}$ on each side) cathodes with $4\\mathsf{c m}\\times5\\mathsf{c m}\\times50\\upmu\\mathrm{m}$ double-sided lithium foil copper inlay, using the $5\\mathrm{cm}\\times6\\mathrm{cm}$ separators and 1 M $\\mathrm{LiPF}_{6}$ in EC/EMC/DEC $(\\mathrm{v/v/v}=\\mathrm{1}{:}1{:}1)\\$ electrolyte. \n\nIn situ Raman test. To perform the in situ Raman test, a transparent battery was designed. LFP and ICPC were cast onto porous stainless foil. For the half-cell test, ICPC can directly be used to assemble a transport battery sealed with a polyethylene bag. Particularly, instead of a battery coin, two pieces of glass were applied to stabilize the battery, and Al wires were used to connect the battery with the electrochemical work station. A Li stripping–plating process similar to the CE test setting was carried out. The signal was collected from cycling half-cells with 0, 0.1, 0.3, 0.5 and $1\\mathrm{mAhcm}^{-2}$ Li plated, and 0, 0.5, 0.7, 0.9 and $\\mathrm{1mAhcm^{-2}}$ Li stripped, respectively. As for the full-cell in situ Raman test, Li metal was deposited within the ICPC-based electrode to obtain a $\\mathrm{Li@ICPC}$ composite anode. Then, the composite anode was coupled with the LFP cathode with a relatively low mass loading, fabricating the full-cell. A cyclic voltammetry test within the voltage range from 2.5 to $4.2\\mathrm{V}$ was performed, and the scanning speed was fixed at $1\\mathrm{mVs^{-1}}$ . The Raman test was conducted to collect signals within $50{-}460\\mathrm{cm}^{-1}$ , with a step of $0.1\\mathrm{V}$ in voltage change. \n\nFree energy calculation. The free energy for the reactions among $\\mathrm{Li}_{2}\\mathrm{O}$ and the various materials were calculated by HSC chemistry software (HSC version 6.0, Outokumpu Research Oy) at room temperature (298 K). \n\nSimulation method. All the calculations were carried out with the Vienna Ab-initio Simulation Package based on density functional theory. The projected augmented wave pseudopotential within the generalized gradient approximation with Perdew–Burke–Ernzerhof was employed to describe the exchange–correlation functionals. A kinetic cut-off energy of $500\\mathrm{eV}$ was used for the plane-wave expansion. The electronic configurations of C, N, O and I were depicted by projected augmented wave potentials containing 4 $(2s^{2}2p^{2})$ , 5 $(2s^{2}2p^{3})$ , 6 $(2s^{2}2p^{4})$ and 7 $(5s^{2}5p^{5})$ valence electrons, respectively. A $5\\times5$ graphene supercell was constructed to represent the carbon surface. The vacuum region was $15\\mathrm{\\AA}$ to avoid interactions between neighbouring images. The density functional theory D3 method was adopted to control the correction of the van der Waals interaction between the carbon host and iodinated adsorbates. Monkhorst–Pack k point sampling was utilized for Brillouin zone integration: $3\\times3\\times1$ for structure optimization and $9\\times9\\times1$ for electronic configuration calculation. The convergence tolerance for the electronic self-consistent field calculations was set at $10^{-5}\\mathrm{eV},$ while the Hellman–Feynman force for geometry relaxation was converged to $10^{-2}\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . Charge transfer behaviour was characterized by the Bader charge algorithm simulation as well as differential charge density distributions. \n\nThe adsorption energy $(E_{\\mathrm{ad}})$ was defined as follows: $E_{\\mathrm{ad}}{=}E_{\\mathrm{adsorbates/}}$ ${\\mathrm{graphene}}^{-}\\left(E_{\\mathrm{graphene}}+E_{\\mathrm{adsorbates}}\\right)$ , where $E_{\\mathrm{adsorbates/graphene}}$ is the total energy of adsorbates on the graphene surface, $E_{\\mathrm{graphene}}$ is the total energy of pristine or doped graphene and $E_{\\mathrm{adsorbates}}$ is the total energy of iodinated adsorbates. \n\n# Data availability \n\nAll data supporting the findings of this study are available in the article and its Supplementary Information. \n\nReceived: 23 July 2020; Accepted: 29 January 2021; Published online: 11 March 2021 \n\n# References \n\n1.\t Choi, J. W. & Aurbach, D. Promise and reality of post-lithium-ion batteries with high energy densities. Nat. Rev. Mater. 1, 16013 (2016). \n2. Liu, J. et al. Pathways for practical high-energy long-cycling lithium metal batteries. Nat. Energy 4, 180–186 (2019). \n3. Peled, E. & Menkin, S. Review—SEI: past, present and future. J. Electrochem. Soc. 164, A1703–A1719 (2017). \n4. Fang, C. et al. Quantifying inactive lithium in lithium metal batteries. Nature 572, 511–515 (2019). \n5. Zhang, S. S. Challenges and strategies for fast charge of Li-ion batteries. ChemElectroChem 7, 3569–3577 (2020). \n6. Verma, P., Maire, P. & Novák, P. A review of the features and analyses of the solid electrolyte interphase in Li-ion batteries. Electrochim. Acta 55, 6332–6341 (2010). \n7. Cai, W. et al. A review on energy chemistry of fast-charging anodes. Chem. Soc. Rev. 49, 3806–3833 (2020). \n8.\t Liu, T. et al. In situ quantification of interphasial chemistry in Li-ion battery. Nat. Nanotechnol. 14, 50–56 (2019). \n9.\t Li, Y. et al. Atomic structure of sensitive battery materials and interfaces revealed by cryo–electron microscopy. Science 358, 506–510 (2017). \n10.\tZachman, M. J., Tu, Z., Choudhury, S., Archer, L. A. & Kourkoutis, L. F. Cryo-STEM mapping of solid–liquid interfaces and dendrites in lithium-metal batteries. Nature 560, 345–349 (2018). \n11.\tLin, D. et al. Fast galvanic lithium corrosion involving a Kirkendall-type mechanism. Nat. Chem. 11, 382–389 (2019). \n12.\tWang, X. et al. Glassy Li metal anode for high-performance rechargeable Li batteries. Nat. Mater. 19, 1339–1345 (2020). \n13.\tXu, Y. et al. Atomic to nanoscale origin of vinylene carbonate enhanced cycling stability of lithium metal anode revealed by cryo-transmission electron microscopy. Nano Lett. 20, 418–425 (2020). \n14.\tHuang, W., Wang, H., Boyle, D. T., Li, Y. & Cui, Y. Resolving nanoscopic and mesoscopic heterogeneity of fluorinated species in battery solid-electrolyte interphases by cryogenic electron microscopy. ACS Energy Lett. 5, 1128–1135 (2020). \n15.\t Li, N.-W., Yin, Y.-X., Yang, C.-P. & Guo, Y.-G. An artificial solid electrolyte interphase layer for stable lithium metal anodes. Adv. Mater. 28, 1853–1858 (2016). \n16.\tLiu, Y. et al. An artificial solid electrolyte interphase with high Li-ion conductivity, mechanical strength, and flexibility for stable lithium metal anodes. Adv. Mater. 29, 1605531 (2017). \n17.\tCao, X. et al. Monolithic solid–electrolyte interphases formed in fluorinated orthoformate-based electrolytes minimize Li depletion and pulverization. Nat. Energy 4, 796–805 (2019). \n18.\tGao, Y. et al. Polymer–inorganic solid–electrolyte interphase for stable lithium metal batteries under lean electrolyte conditions. Nat. Mater. 18, 384–389 (2019). \n19.\t Cha, E. et al. 2D $\\mathbf{MoS}_{2}$ as an efficient protective layer for lithium metal anodes in high-performance Li–S batteries. Nat. Nanotechnol. 13, 337–344 (2018). \n20.\tDing, F. et al. Dendrite-free lithium deposition via self-healing electrostatic shield mechanism. J. Am. Chem. Soc. 135, 4450–4456 (2013). \n21.\tWang, G. et al. Suppressing dendrite growth by a functional electrolyte additive for robust Li metal anodes. Energy Storage Mater. 23, 701–706 (2019). \n22.\tZhang, X.-Q., Cheng, X.-B., Chen, X., Yan, C. & Zhang, Q. Fluoroethylene carbonate additives to render uniform Li deposits in lithium metal batteries. Adv. Funct. Mater. 27, 1605989 (2017). \n23.\tLiu, Y. et al. Solubility-mediated sustained release enabling nitrate additive in carbonate electrolytes for stable lithium metal anode. Nat. Commun. 9, 3656 (2018). \n24.\tChoudhury, S. & Archer, L. A. Lithium fluoride additives for stable cycling of lithium batteries at high current densities. Adv. Electron. Mater. 2, 1500246 (2016). \n25.\tWu, F. et al. Lithium iodide as a promising electrolyte additive for lithium– sulfur batteries: mechanisms of performance enhancement. Adv. Mater. 27, 101–108 (2015). \n26.\tJu, Z. et al. Biomacromolecules enabled dendrite-free lithium metal battery and its origin revealed by cryo-electron microscopy. Nat. Commun. 11, 488 (2020). \n27.\tYuan, H. et al. An ultrastable lithium metal anode enabled by designed metal fluoride spansules. Sci. Adv. 6, eaaz3112 (2020). \n28.\tSheng, O. et al. In situ construction of LiF-enriched interface for stable all-solid-state batteries and its origin revealed by cryo-TEM. Adv. Mater. 32, 2000223 (2020). \n29.\tLi, Y. et al. Correlating structure and function of battery interphases at atomic resolution using cryoelectron microscopy. Joule 2, 2167–2177 (2018). \n30.\tGao, Y. et al. Low-temperature and high-rate-charging lithium metal batteries enabled by an electrochemically active monolayer-regulated interface. Nat. Energy 5, 534–542 (2020). \n31.\tWang, J. et al. Improving cyclability of Li metal batteries at elevated temperatures and its origin revealed by cryo-electron microscopy. Nat. Energy 4, 664–670 (2019). \n32.\tZhao, Q., Lu, Y., Zhu, Z., Tao, Z. & Chen, J. Rechargeable lithium-iodine batteries with iodine/nanoporous carbon cathode. Nano Lett. 15, 5982–5987 (2015). \n33.\t Tułodziecki, M. et al. The role of iodide in the formation of lithium hydroxide in lithium–oxygen batteries. Energy Environ. Sci. 10, 1828–1842 (2017). \n34.\tKim, J.-H. et al. Capacity fading mechanism of LiFePO4-based lithium secondary batteries for stationary energy storage. J. Power Sources 229, 190–197 (2013). \n35.\tWang, B. et al. A hierarchical porous C@LiFePO4/carbon nanotubes microsphere composite for high-rate lithium-ion batteries: combined experimental and theoretical study. Adv. Energy Mater. 6, 1600426 (2016). \n36.\t Huang, Q., Yang, J., Ng, C. B., Jia, C. & Wang, Q. A redox flow lithium battery based on the redox targeting reactions between LiFePO4 and iodide. Energy Environ. Sci. 9, 917–921 (2016). \n37.\tLu, K. et al. A rechargeable iodine–carbon battery that exploits ion intercalation and iodine redox chemistry. Nat. Commun. 8, 527 (2017). \n38.\tJin, S., Jiang, Y., Ji, H. & Yu, Y. Advanced 3D current collectors for lithium-based batteries. Adv. Mater. 30, 1802014 (2018). \n39.\tJin, C. et al. 3D lithium metal embedded within lithiophilic porous matrix for stable lithium metal batteries. Nano Energy 37, 177–186 (2017). \n40.\tZheng, G. et al. Interconnected hollow carbon nanospheres for stable lithium metal anodes. Nat. Nanotechnol. 9, 618–623 (2014). \n41.\tKim, M. S. et al. Langmuir–Blodgett artificial solid–electrolyte interphases for practical lithium metal batteries. Nat. Energy 3, 889–898 (2018). \n42.\tNiu, C. et al. High-energy lithium metal pouch cells with limited anode swelling and long stable cycles. Nat. Energy 4, 551–559 (2019). \n43.\tLin, Z., Liu, T., Ai, X. & Liang, C. Aligning academia and industry for unified battery performance metrics. Nat. Commun. 9, 5262 (2018). \n44.\tXiao, J. et al. Understanding and applying Coulombic efficiency in lithium metal batteries. Nat. Energy 5, 561–568 (2020). \n\n# Acknowledgements \n\nWe acknowledge financial support by the National Natural Science Foundation of China (grant nos 51722210, 51972285, U1802254, 21902144 and 52071295), the \n\nNatural Science Foundation of Zhejiang Province (grant nos LY17E020010 and LD18E020003) and the Foundation of Zhejiang Institute of Advanced Materials for Science and Innovation (KYY-HX-20190265), and high-performance computational resources (TianHe-2) provided by LvLiang Cloud Computing Center of China. This work was also supported by the US Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office under the US–China Clean Energy Research Centre (CERC-CVC2) programme. Argonne National Laboratory is operated for the US Department of Energy, Office of Science by UChicago Argonne, LLC, under contract number DE-AC02-06CH11357. We thank S. Song for assistance with the gas chromatography experiments. \n\n# Author contributions \n\nC.J., Tiefeng Liu, J.L. and X.T. conceived the concept and designed the experiments. C.J. and M.L. performed the material synthesis and electrochemical measurements. O.S., C.J., Tongchao Liu, Y.Y. and Z.J. participated in material characterization. C.J., X.T., Y.L, Z.L. and W.Z. interpreted the results. Y.W. performed the density functional theory calculations. C.J., Tiefeng Liu, J.N., J.L. and X.T. cowrote the paper. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41560-021-00789-7. \nCorrespondence and requests for materials should be addressed to J.L. or X.T. Peer review information Nature Energy thanks the anonymous reviewers for their contribution to the peer review of this work. \nReprints and permissions information is available at www.nature.com/reprints. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 " + }, + { + "id": "10.1021_acsenergylett.0c02599", + "DOI": "10.1021/acsenergylett.0c02599", + "DOI Link": "http://dx.doi.org/10.1021/acsenergylett.0c02599", + "Relative Dir Path": "mds/10.1021_acsenergylett.0c02599", + "Article Title": "Revealing Charge Carrier Mobility and Defect Densities in Metal Halide Perovskites via Space-Charge-Limited Current Measurements", + "Authors": "Le Corre, VM; Duijnstee, EA; El Tambouli, O; Ball, JM; Snaith, HJ; Lim, J; Koster, LJA", + "Source Title": "ACS ENERGY LETTERS", + "Abstract": "Space-charge-limited current (SCLC) measurements have been widely used to study the charge carrier mobility and trap density in semiconductors. However, their applicability to metal halide perovskites is not straightforward, due to the mixed ionic and electronic nature of these materials. Here, we discuss the pitfalls of SCLC for perovskite semiconductors, and especially the effect of mobile ions. We show, using driftdiffusion (DD) simulations, that the ions strongly affect the measurement and that the usual analysis and interpretation of SCLC need to be refined. We highlight that the trap density and mobility cannot be directly quantified using classical methods. We discuss the advantages of pulsed SCLC for obtaining reliable data with minimal influence of the ionic motion. We then show that fitting the pulsed SCLC with DD modeling is a reliable method for extracting mobility, trap, and ion densities simultaneously. As a proof of concept, we obtain a trap density of 1.3 x 10(13) cm(-3), an ion density of 1.1 x 10(13) cm(-3), and a mobility of 13 cm(2) V-1 s(-1) for a MAPbBr(3) single crystal.", + "Times Cited, WoS Core": 405, + "Times Cited, All Databases": 409, + "Publication Year": 2021, + "Research Areas": "Chemistry; Electrochemistry; Energy & Fuels; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000629230800029", + "Markdown": "# Revealing Charge Carrier Mobility and Defect Densities in Metal Halide Perovskites via Space-Charge-Limited Current Measurements \n\nVincent M. Le Corre,\\* Elisabeth A. Duijnstee, Omar El Tambouli, James M. Ball, Henry J. Snaith, Jongchul Lim, and L. Jan Anton Koster\\* \n\nCite This: ACS Energy Lett. 2021, 6, 1087−1094 \n\n# ACCESS \n\n山 Metrics & More \n\nArticle Recommendations \n\nSupporting Information \n\nABSTRACT: Space-charge-limited current (SCLC) measurements have been widely used to study the charge carrier mobility and trap density in semiconductors. However, their applicability to metal halide perovskites is not straightforward, due to the mixed ionic and electronic nature of these materials. Here, we discuss the pitfalls of SCLC for perovskite semiconductors, and especially the effect of mobile ions. We show, using driftdiffusion (DD) simulations, that the ions strongly affect the measurement and that the usual analysis and interpretation of SCLC need to be refined. We highlight that the trap density and mobility cannot be directly quantified using classical methods. We discuss the advantages of pulsed SCLC for obtaining reliable data with minimal influence of the ionic motion. We then show that fitting the pulsed SCLC with DD modeling is a reliable method for extracting mobility, trap, and ion densities simultaneously. As a proof of concept, we obtain a trap density of $\\mathbf{1.3\\times10^{13}}$ $\\mathbf{cm}^{-3}$ , an ion density of $\\mathbf{1.i}\\times\\mathbf{10^{13}\\ c m^{-3}}$ , and a mobility of $\\mathrm{i}3\\ \\mathrm{cm}^{2}\\ \\mathrm{\\hat{V}}^{-1}\\ \\mathrm{s}^{-1}$ for a $\\mathbf{MAPbBr}_{3}$ single crystal. \n\n![](images/12732be0030ff2bf2e9138d586ae6ee712536b84cbc9159818f3e41ec51360bb.jpg) \n\nne of the most common techniques for investigating the intrinsic transport properties as well as the trap density of a semiconductor is the so-called spacecharge-limited current (SCLC) measurement. Due to the apparent simplicity of the measurement, it has been used extensively in the literature to study organic semiconductors and inorganic and hybrid organic−inorganic metal halide perovskites.1−13 In fact, the measurement consists of measuring “only” a dark current−voltage (JV) characteristic of a single-carrier device, i.e., a device in which the contacts on both sides of a semiconductor are aligned with the conduction (valence) band in such a way that only electrons (holes) are injected. One of the main advantages of this technique versus other techniques such as charge carrier extraction by linearly increasing voltage, optical pump terahertz probe photoconductivity, and microwave conductivity, lies in the fact that the electron and hole mobility and trap density can be probed independently.14,15 In addition, the device configuration is similar to that used in solar cells and other “sandwich structure” optoelectronic devices, where the vertical transport is probed, as opposed to the lateral transport that can be measured using field effect transistor measurements.15 \n\nThe widespread use of SCLC measurements in the field of organic semiconductors likely contributed to its rapid adoption by the perovskite community. As a result, a large number of very influential publications have used this technique to quantify the transport and trapping properties in both single crystals and thin films.4−13 However, the analysis of SCLC measurement data is sometimes oversimplified because the assumptions required to extract reliable values are often overlooked and not fully met, which leads to an over- or underestimation of the extracted values. \n\nIn this paper, we investigate the applicability of SCLC measurement for perovskites using drift-diffusion (DD) modeling. We show that the classical SCLC measurement procedure and analysis is not suitable to extract accurate values of the mobility and trap density of perovskites. Instead, pulsed SCLC measurements, as introduced by Duijnstee et al.,16,17 need to be used. Using simulations, we show how we can correctly interpret and extract important parameters from pulsed SCLC. To the best of our knowledge, this is the first report of extraction of both the ion and trap density from \n\n![](images/306b5e3c4eddcb6ea57e00931e8006767e7dedd6441c0f15d9d74bb83b9ac660.jpg) \nFigure 1. (a) Ideal device structure for SCLC measurement with symmetric ohmic contact and no injection barrier. (b) Simulated JV curve of an electron-only device with a ${\\bf100}\\mu{\\bf m}$ thick perovskite between two perfect electrodes as in panel a with various trap densities. The dashed lines correspond to the different tangents with slopes of 1, 2, and $^{>2}$ , and the red, blue, and magenta points correspond to construction of $V_{1},V_{\\mathrm{inf}}$ and $V_{2},$ respectively. (c) Evolution of the slopes of the $\\mathbf{\\Delta}\\mathbf{\\mathbf{{F}}}$ curves with voltage. (d) Evaluation of the accuracy of the trap density estimation depending on the voltage point taken as $V_{\\mathrm{tfl}}$ . The parameters used in the simulations are listed in Table S1. \n\nSCLC measurements, in addition to accurately determining the charge carrier mobility. \n\nTypical Pitfalls of SCLC Analysis. Ideally, SCLC measurements consist of a dark $\\mathrm{\\Delta}\\mathrm{J}\\mathrm{V}$ curve measurement of a singlecarrier device with symmetric ohmic contacts on either side of a semiconductor, as depicted in Figure 1a. When the JV curve is plotted on a log−log scale, several regimes can be identified: first a low-voltage regime with a slope $\\left[\\frac{\\mathrm{d}\\log(J)}{\\mathrm{d}\\log(V)}\\right]$ of 1, followed by a regime with a high slope $(>2)$ dueÇÅ to trapÖÑfilling (if any), and, finally, at high voltage, the so-called SCLC regime with a slope of 2. These three regimes are shown in panels b and c of Figure 1. Note that the space-charge effect also influences the trap-filled-limited (TFL) regime. \n\nSeveral pitfalls of SCLC measurements have already arisen from the simple characterization of these regimes, which have been reported in the literature. (i) The use of non-ohmic and/ or asymmetric contacts can lead to regimes with slopes of $^{>2}$ and needs to be accounted for while performing the SCLC analysis; studies by Blakesley1 and $\\mathrm{R}\\mathrm{\\ddot{o}h r}^{\\mathrm{18}}$ present methods on how to account for asymmetric contact. (ii) The interpretation of the low-voltage regime varies depending on several factors such as diffusion and intrinsic, trap, or dopant densities.19−22 (iii) The fitting and accuracy of the Mott−Gurney equation23,24 were used for the quadratic regime at high voltages. (iv) Fitting the Mark−Helfrich equation is used for the interpretation of the TFL regime.19,25−27 In addition to these issues, perovskite materials, good electronic and ionic conductors, bring some new challenges of their own as the contributions of electronic and ionic species influence the current. \n\nBefore discussing the influence of ions on SCLC measurements, we first discuss the ideal case in which no ions are present as it is not always clear in the literature what values can be extracted and how. \n\nSCLC measurements are some of the most common approaches for extracting the mobility and trap density values of semiconductors and have been widely used in the perovskite literature. $^{6-11,28}$ As discussed in numerous papers,19 ,23,24 the mobility value is typically extracted from the quadratic regime of the $\\mathrm{\\Delta}\\mathrm{\\mathcal{N}}$ curve by fitting the Mott−Gurney equation: \n\n$$\nJ={\\frac{9}{8}}\\varepsilon\\mu{\\frac{(V-V_{\\mathrm{BI}})^{2}}{L^{3}}}\n$$ \n\nwhere $J$ is the current density, $V$ and $V_{\\mathrm{BI}}$ are the applied and built-in voltage, respectively, $\\varepsilon$ is the dielectric constant, $L$ is the thickness, and $\\mu$ is the mobility. While some slightly different formulas were proposed to account for the presence of trapping,19 eq 1 remains the most commonly used formula in the literature. \n\nAs previously mentioned, the trap density can be extracted from the plot of the $\\mathrm{~\\textit~{~\\textbf~{~~}~}~}\\operatorname{\\textbf{{N}}}$ curve on a log−log scale. The most common approach is to calculate the trap density from the socalled trap-filled-limit voltage:19 \n\n$$\nV_{\\mathrm{tfl}}=\\frac{q n_{\\mathrm{t}}L^{2}}{2\\varepsilon}\n$$ \n\nwhere $q$ is the elementary charge and $n_{\\mathrm{t}}$ the trap density. Even though this formula can be easily derived under the assumption that the amount of traps is larger than the number of free charges, which point of the $\\mathrm{\\Delta}\\mathrm{J}\\mathrm{V}$ curve that should be chosen as $V_{\\mathrm{tfl}}$ has not yet been clarified. Most reports choose the voltage of the crossing point between the low-voltage tangent with a slope of 1 and the trap-filled-limited regime tangent with a slope of ${>}2$ , as shown in Figure 1b, which we call $V_{1}$ . However, others use the crossing point between the tangent space-charge-limited regime at high voltages and the trap-filled-limited regime, which we call $\\bar{V_{2}}$ .29 Lastly, one may consider the inflection point $\\cdot\\:V_{\\mathrm{inf}})$ as a viable option for the $V_{\\mathrm{{tfl}}}$ value. \n\n![](images/4139d5a80e373eb35927d83a30e8445665d36991f6d32a60bbe4d8a6e0eaa60e.jpg) \nFigure 2. (a) Forward and backward JV scan of a $\\mathbf{MAPbBr}_{3}$ perovskite single crystal taken from ref 16 showing strong hysteresis. (b) Simulated JV curves for forward, backward, and steady-state scans demonstrating the influence of ion migration on the JV curve. The vertical line indicates the $V_{\\mathrm{tfl}}$ as calculated from eq 2. (c) Cation density distribution calculated for steady-state conditions at different bias voltages where it can be seen that the cations slowly migrate toward the electrode (the anion distribution can be found in Figures S1−S3). (d) Effect of the injection barrier next to the injecting electrode that saturates the current at high voltages. The parameters used in the simulation are listed in Table S1. \n\nTo assess which voltage $(V_{1},\\ V_{2},$ or $V_{\\mathrm{inf}})$ yields the most accurate estimate of the trap density, we simulated $\\mathrm{~\\textit~{~\\textbf~{~~}~}~}\\operatorname{\\textbf{{N}}}$ curves by varying the trap densities for a fixed thickness of $100\\ \\mu\\mathrm{{m}}$ and extracted the values of $V_{1},$ $V_{\\mathrm{inf}}$ and $V_{2}$ and calculated the corresponding trap densities using eq 2. Figure 1d shows that using $V_{1}$ to calculate $V_{\\mathrm{tfl}}$ gives the worst estimation of trap density and can lead to errors of almost 1 order of magnitude in the estimated trap density. The error is largest when the trap density is low and the transition between the two regimes is shallow, i.e., when the slope of the TFL regime is low. As shown, $V_{2}$ gives the most accurate value for the trap density and should be used instead. This is not so surprising as the transition from the TFL to the SCLC regime happens when all traps are filled and the free charge carrier density becomes larger than the number of traps (see Figures S1−S3). \n\nWe also note that, for a given thickness, trap densities can be resolved by SCLC measurements only if the density of traps exceeds a certain threshold. In fact, the TFL regime appears only if $n_{\\mathrm{t}}~>~n$ at a low voltage. Hence, the minimum trap density leading to a TFL regime is given by the charge density $n_{\\mathrm{diff}}$ at a low voltage (where the current is dominated by diffusion) in the absence of traps and dopants.21,22 The minimum density of traps that is noticeable is thus given by \n\n$$\nn_{\\mathrm{t,min}}=n_{\\mathrm{diff}}=4\\pi^{2}{\\frac{k T}{q^{2}}}{\\frac{\\varepsilon}{L^{2}}}\n$$ \n\nAssuming that the relative dielectric constant of perovskites is typically 25 and that the experiment is performed at $295\\ \\mathrm{K},$ eq 3 implies that to resolve a trap density of $10^{11}~\\mathrm{cm}^{-3}$ the thickness of the perovskite layer needs to be at least $100\\ \\mu\\mathrm{{m}}$ . For a trap density of $10^{16}\\mathrm{cm}^{\\dot{-}3}$ , $400\\ \\mathrm{nm}$ is sufficient to resolve the TFL regime. Thus, to observe a TFL regime, high-quality perovskites require a very thick film in the SCLC experiment. However, because $V_{\\mathrm{tfl}}$ is inversely proportional to $L^{2}$ , it is possible to encounter difficulties as we have to measure at high voltages to reach the quadratic SCLC regime if the perovskite thickness is increased. \n\nThese important findings question the way SCLC measurements are reported in the literature. In the absence of a TFL regime, we should only note that the trap density is lower than $n_{\\mathrm{t,min}}^{},$ depending on the thickness of the measured sample, rather than claiming the absence of traps. \n\nInfluence of Ions on SCLC Measurements: Classic SCLC Measurement. One of the peculiar properties inherent to perovskite materials is the fact that they are both electronic and ionic conductors. Typically, the halide anions are identified as being primarily responsible for the ionic motion in metal halide perovskites with a higher diffusion coefficient, a lower activation energy, and higher densities compared to those of other ionic species.30−32 However, recent studies also suggest that the influence of A site cations such as ${\\mathrm{C}}s^{+}{\\mathrm{.}}$ , $\\mathrm{CH}_{3}\\mathrm{NH}_{3}^{+}$ , and $\\left(\\mathrm{NH}_{2}\\right)_{2}\\mathrm{CH}^{+}$ or even $\\mathrm{H^{+}}$ should not be neglected.33,34 Overall, it is difficult to find one responsible for the ionic motion in perovskite as it largely depends on the system being studied. Nevertheless, it is clear that mobile ions are present in a large majority of metal halide perovskites and need to be accounted for. \n\nLike the issue of identifying the main source of mobile ions, investigating the nature and origin of the traps is also a big challenge, and while many reports use first-principles calculation to calculate the trap depth regardless of whether there are more acceptor or donor types, there is still a large spread in the obtained values and no consensus as to the nature of the traps.31,35 It has been widely reported in the perovskite solar cell literature that the movement of ions can have a dramatic impact on the JV curves of perovskite solar cells and cause hysteresis.36−39 Surprisingly, the influence of ions on the JV curves of SCLC measurements has been largely overlooked, and there are, to the best of our knowledge, few reports of the difference between forward (FW) and backward (BW) scans for SCLC measurements. The FW (BW) scan is a measurement of a $\\mathrm{\\Delta}\\mathrm{\\mathrm{~\\textit~{~~}~}}\\mathrm{\\operatorname{~J}}^{\\mathrm{\\Delta}}$ curve from low $\\left(\\mathrm{{high}}\\right)$ to high (low) voltages. Recent exceptions are the papers by Duijnstee et al.16 and Sajedi Alvar et al.40 The $\\mathrm{\\Delta}\\mathrm{\\mathrm{~\\textit~{~J~V~}~}}$ curve from the SCLC measurement of a $\\mathbf{MAPbBr}_{3}$ single crystal, taken from ref 16, is shown in Figure 2a and shows large hysteresis between the FW and BW scans. This indicates that the movement of the ions has a strong effect on the current and, hence, needs to be considered in the SCLC analysis when studying perovskites. \n\n![](images/0c3ddf945ac550aca71267cd8d46a7ef76da4d1ff427ed68e80fd57507f7112c.jpg) \nFigure 3. (a) Schematic representation of the construction of the pulsed SCLC JV curve from the measurement of the current during a voltage pulse. (b) Pulsed SCLC measurement JV curves with a small hysteresis for a $\\mathbf{160}\\mu\\mathbf{m}$ thick $\\mathbf{MAPbBr}_{3}$ perovskite single crystal and the corresponding drift-diffusion fit. (c) Evolution of the pulsed SCLC $\\mathbf{\\Delta}\\mathbf{\\mathbf{{F}}}$ curves depending on the ion density for a fixed trap density of ${\\bf1}\\times{\\bf\\Sigma}$ $10^{13}~\\mathrm{cm}^{-3}$ . (d) Input vs calculated net-charge density using eq 4. The black solid line is a guide to the eye corresponding to the input net charge, and the dashed line corresponds to the input trap density. The parameters used in the simulation are listed in Tables S1 and S2. \n\nTo gain insight into how the ions affect the current, we simulated a $100\\ \\mu\\mathrm{{m}}$ thick perovskite single crystal, including trapping and mobile ions, as shown in Figure 2b and Table S1. First, we simulated a steady-state (or stabilized) scan in which ions have time to redistribute at every voltage step followed by a simulation of the extreme cases of an infinitely fast FW and BW scan prebiased at 0 and $200~\\mathrm{V},$ , respectively. For these scans, the ion distributions throughout the device are calculated at the prebias (here the first applied voltage) and kept fixed for all of the other voltage steps. While there is no significant difference between the FW and steady-state scans, there is a dramatic hysteresis feature between the FW and BW sweeps. The fact that the steady-state and FW scans are similar is not so surprising as the cations mostly stay in the bulk at low voltages because the perovskite layer is so thick (see Figure 2c). Therefore, the current at low voltages is hardly affected, as depicted Figure 2b. Even though the cations will accumulate at the electrode at high voltages, as shown in Figure 2c, it still has a negligible effect as the electric field is high enough not to be affected. During the BW scan, the current is mostly affected at intermediate voltages as the ions are confined near the electrode, effectively dedoping the bulk of the perovskite. \n\nThe vertical line in Figure 2b indicates the $V_{\\mathrm{tfl}}$ as calculated from eq 2. We can note that $V_{2}$ of the BW scan is much closer to $V_{\\mathrm{{tfl}}}$ than that from the FW or steady-state scan. This tends to indicate that using a BW scan leads to a better estimate of the trap density. However, for this to be true the scan rate should be sufficiently high to ensure than ions do not have time to move throughout the JV measurement, which is difficult when scanning over a large voltage range. Additionally, we will later discuss other effects that may influence the BW scan, and can cause experimental difficulties. \n\nIn summary, the ions have a strong influence on the SCLC $\\mathrm{\\Delta}\\mathrm{\\mathcal{N}}$ curves but more importantly the values of trap density extracted from this measurement are largely dependent on the ions, making it impossible to extract reliable trap density values using Vtfl. \n\nWhile there is a clear effect of the ionic distribution on the simulated JV curves, we do not see such a drastic decrease and saturation in the current density in the BW scan compared to the FW scan as in the experiment depicted in Figure 2a. This effect could potentially be explained by the creation of an injection barrier next to the electrode when the applied bias is too strong. This barrier could originate from the degradation of the perovskite materials next to the electrode. Too many ions at the interface can result in the formation of a thin layer with a different bandgap. The simulation with a small injection $({\\approx}0.2{-}0.3~\\mathrm{eV})$ barrier (see Figure 2d) in the layer next to the injecting electrode indeed shows a saturation of the current at high voltages and therefore makes this a probable scenario for explaining the shape of the hysteresis in the experimental JV curve. In addition, it has been shown in the literature that the reaction of the perovskite with the electrode or ionic migration could create different phases like $\\mathrm{PbI}_{2}$ next to the electrode,41 which could create such a barrier. Unfortunately, such a degradation complicates the use of the BW scan to gain a better estimate of the trap density. \n\nPulsed SCLC Measurement. To tackle the problem of hysteresis and fixing the position of the ions within the perovskite, Duijnstee et al. proposed a pulsed SCLC method for obtaining reliable JV curves with suppressed hysteresis.16 This method consists of a short voltage pulse $\\left(20~\\mathrm{ms}\\right)$ from 0 V to the wanted applied voltage (see Figure 3a) and measuring the current after the displacement pic and before the ions have the time to move significantly. In the Supporting Information, we show by simulating the pulsed measurement using transient drift diffusion that this approach is fully justified (for both single crystals and thin films) and that ions indeed do not move significantly and have little to no influence on the current at a such time scale and at such an electric field. \n\nUsing this pulsed method presents several advantages; on one hand, it allows the measurement of hysteresis free curves where the ions are effectively fixed to their position at $0\\mathrm{v}$ and do not move throughout the JV sweep, and on the other hand, it avoids unwanted degradation and phase changes next to the electrodes that saturate the current at high voltages. \n\nIn the remainder of this paper, we will discuss the pulsed SCLC as this measurement is more reliable.16 To simulate the pulsed SCLC, we first calculate the ion distribution at $0\\mathrm{v}$ and then keep it fixed for the voltage sweep, making it equivalent to the infinitely fast scan described previously. Similar to the fast FW scan, the pulsed SCLC and the steady-state scan give similar JV curves, as shown in Figure 2b. This similarity arises from the fact that the injected electron density and the filling of the traps are not as much affected by the movement ions, and especially cations. Figures S1 and S2 show that the cations mostly remain within the bulk of the perovskite and that the electron injection is not different for the three methods, which lead to completely filled traps at the same voltage. However, the situation is different for a fast BW scan prebiased at $200\\mathrm{V}$ . Figure S3 shows that in this case, the cations accumulate at the injecting electrode, which slows the injection of electrons, and thereby the filling of the traps. Hence, $V_{\\mathrm{tfl}}$ shifts to higher voltages. \n\nFigure 3b shows the measured pulsed SCLC JV curves for a $160~\\mu\\mathrm{m}$ thick $\\mathbf{MAPbBr}_{3}$ single crystal. More details about the measurement can be found in ref 16. Figure S4 shows the measurement performed on three different crystals with different thicknesses. The absence of hysteresis for all three crystals implies that the ions are indeed fixed around their $0\\mathrm{v}$ positions. Additionally, there is no sign of degradation in the BW scan, which confirms the hypothesis that the accumulation of ions at high voltages creates a barrier for the injection that limits the current. \n\nOn top of the hysteresis, the ions significantly influence the actual shape of the JV curve. We show in Figure 3c that as the ion density approaches the trap density, here at $1\\times10^{13}\\mathrm{cm}^{-3}.$ , the TFL regime disappears. In addition, $V_{1},V_{\\mathrm{inf}}$ and $V_{2}$ are all affected by the ion density. This is due to the fact that ions are shielding the charge from the traps, and thereby reducing the net charge. If the ion and trap densities are within the same order of magnitude, eq 2 does not apply and needs to be rewritten in terms of net charges in the bulk such as \n\n$$\nV_{\\mathrm{net}}=\\frac{q n_{\\mathrm{net}}L^{2}}{2\\varepsilon}=\\frac{q(n_{\\mathrm{t}}-n_{\\mathrm{ion}})L^{2}}{2\\varepsilon}\n$$ \n\nThe derivation of eq 4 is provided in the Supporting Information. Similarly, eq 3 can be expressed in terms of the net charge in the bulk. Equivalently, this equation still holds when other types of charges, such as dopants, are added, as shown in Figure S5. One should also note that in eq $4\\ n_{\\mathrm{t}}$ refers only to charged traps that are sufficiently deep within the bandgap; in our simulations for an electron-only device, only negatively charged traps (i.e., acceptor type) can be probed as shown in Figure S6. Realistically, if more than one type of trap is considered with both some donor and some acceptor, for example, $n_{\\mathrm{t}}$ would correspond to the net charge of all of the traps. \n\nThis is a crucial point for the interpretation of SCLC measurement for perovskites as it shows that we measure $V_{\\mathrm{net}}$ and the net charge in the bulk of the perovskite, rather than the $V_{\\mathrm{tfl}}$ and the trap density. This is well illustrated by Figure 3d, in which we show that as the ion density increases, i.e., the net charge decreases, the measured density deviates more from the actual trap density. This figure also shows that $V_{1},$ which is the most commonly used point for $V_{\\mathrm{tfl}},$ not only can be 1 order of magnitude off in predicting the net charge but also underestimates the trap density by almost 2 orders of magnitude. Hence, previously reported trap density values from SCLC measurement showing a small slope for the TFL regime, probably indicating an ion density close to the trap density, cannot be trusted. \n\nGiven the potential pitfalls of SCLC measurements when applying simplified equations such as the Mott−Gurney law or the expression for $V_{\\mathrm{tfl}},$ it appears to be more reasonable to fit drift-diffusion simulations to the measurement data. By doing so, we can relax a few assumptions and obtain values for trap and ion densities instead of only the net charge when using eq 4. If necessary, the built-in voltage can also be accounted for by fitting both positive and negative voltage $\\mathrm{\\Delta}\\mathrm{J}\\mathrm{V}$ curves, when different electrodes are used (which is not the case here). For this purpose, we use SIMsalabim, an open-source drift-diffusion simulation program, in the hope that it will enable researchers to fit their SCLC measurement to obtain more reliable values. More details about the simulation can be found in the Supporting Information and refs 39, 42, and 43, and the code is available on GitHub.44 \n\nIf we extract values from the $160\\ \\mu\\mathrm{{m}}$ single-crystal JV curve using the “classical” method, i.e., taking the $V_{\\mathrm{tfl}}$ as $V_{1},$ from the FW scan in Figure 2a and from the pulsed measurement in Figure $^{3\\mathrm{b},}$ we obtain trap densities of ${\\approx}2\\times10^{11}$ and ${\\approx}4.5\\times$ $10^{\\cdot12}\\mathrm{cm}^{-3}$ , respectively. However, when the pulsed JV curve is fitted using the drift-diffusion simulation, as shown in Figure 3a and Table S2, the simulation shows that trap and ion densities are indeed very similar, approximately $1.3\\times10^{13}$ and $1.1\\times$ $10^{13}\\mathrm{~cm}^{-3}$ , respectively, giving a net charge in the bulk of $2\\times$ $10^{12}\\mathrm{cm}^{-3}$ . The trap density was underestimated by $_{1-2}$ orders of magnitude when using the “classical” method. \n\nEven the values extracted by using the crossing points of the tangents from the pulsed measurement do not yield the correct values of either the net charge or the trap density. $V_{1;}$ , $V_{\\mathrm{inf}}$ and $V_{2}$ give values of $4.5\\times10^{12}$ , $9.4\\times10^{12}$ , and $1.2\\times10^{13}~\\mathrm{cm}^{-3}$ , respectively. The TFL regime is not very pronounced, so the net charge is overestimated, as in Figure 3d when $V_{\\mathrm{net}}$ is small. Clearly, under such conditions, fitting a drift-diffusion simulation becomes necessary to extract a value for the trap density. It also allows for an estimation of the mobility value, which would not have been accessible using the “classical” method and fitting the Mott−Gurney law becaise the SCLC regime is not reached even at $200{\\mathrm{V}}.$ . Here, we find a mobility of approximately $13\\ \\mathrm{cm}^{2}\\ \\mathrm{V}^{-1}\\ \\mathrm{s}^{-1}$ . \n\nWe show that SCLC measurements have to be treated carefully when performed upon mixed ionic and electronic conductors, such as metal halide perovskites. We present some of the common pitfalls for SCLC analysis and show that to obtain a reasonable estimate of the $V_{\\mathrm{tfl}}$ and trap density, one needs to consider $V_{2}$ rather than $V_{1}$ . \n\nWe then present a detailed analysis of the effect of mobile ions on the interpretation of SCLC measurement. Both simulations and experiments suggest that performing pulsed SCLC measurement is necessary to minimize ion migration during the measurement. In this way, we obtain reliable and reproducible $\\mathrm{\\Delta}\\mathrm{\\mathrm{~\\textit~{~J~V~}~}}$ curves and avoid any degradation of the perovskite under large applied voltages. We show that even though we can extract the net charge in the perovskite bulk from the SCLC measurement, we cannot directly extract the trap density. This calls into question previous reports in the literature that may have underestimated the trap density by several orders of magnitude. \n\nFinally, we show how we can accurately reproduce pulsed SCLC experiments using drift-diffusion modeling, which enables us to quantify not only the net charge but also the actual mobility and trap and ion densities. We propose a wider use of drift-diffusion simulations to fit pulsed SCLC to extract meaningful values for the trap and ion densities, and mobility in the case of perovskites, and we provide an open-source solution to fit these measurements. We strongly encourage others to follow this approach and no longer perform analytical fits to JV data. \n\n# ASSOCIATED CONTENT \n\n# Supporting Information \n\nThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsenergylett.0c02599. \n\nSimulation parameters (Tables S1 and S2), charge carrier density profiles (Figures S1−S3), pulsed SCLC of single crystals of different thicknesses (Figure S4), effect of doping on pulsed SCLC (Figure S5), effect of defect type and trap depth on pulsed SCLC (Figure S6), simulated transient for pulsed SCLC (Figure S7), comparison between full transient and steady-state simulations of pulsed SCLC for a single-crystal-like perovskite (Figure S8), time evolution of the ionic distribution during the voltage pulse (Figures S9−S11), comparison between full transient and steady-state simulations of pulsed SCLC for a thin-film perovskite (Figure S12), illustration of the synthesis process of the perovskite single crystal (Figure S13), drift-diffusion model details, pulsed SCLC with ions really fixed during the voltage pulse, derivation of eq 4, and experimental procedures (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\nVincent M. Le Corre − Zernike Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands; $\\circledcirc$ orcid.org/0000-0001-6365-179X; Email: v.m.le.corre@rug.nl \nL. Jan Anton Koster − Zernike Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands; orcid.org/0000-0002-6558-5295; Email: l.j.a.koster@rug.nl \n\n# Authors \n\nElisabeth A. Duijnstee − Zernike Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The \n\nNetherlands; Clarendon Laboratory, University of Oxford, Oxford OX1 3PU, United Kingdom; $\\circledcirc$ orcid.org/0000- 0002-7002-1523 \nOmar El Tambouli − Zernike Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands \nJames M. Ball − Clarendon Laboratory, University of Oxford, Oxford OX1 3PU, United Kingdom; $\\circledcirc$ orcid.org/0000- 0003-1730-5217 \nHenry J. Snaith − Clarendon Laboratory, University of Oxford, Oxford OX1 3PU, United Kingdom; $\\circledcirc$ orcid.org/ 0000-0001-8511-790X \nJongchul Lim − Clarendon Laboratory, University of Oxford, Oxford OX1 3PU, United Kingdom; $\\circledcirc$ orcid.org/0000- 0001-8609-8747 \n\nComplete contact information is available at: https://pubs.acs.org/10.1021/acsenergylett.0c02599 \n\n# Author Contributions \n\nV.M.L.C. wrote the manuscript. V.M.L.C. and O.E.T. performed the numerical simulations. E.A.D. and J.L. fabricated the devices and performed the pulsed SCLC experiments. J.M.B. wrote the control software and assisted with the experimental setup and measurements. All authors discussed the results and reviewed the manuscript. J.L., H.J.S., and L.J.A.K. guided and supervised the overall project. \n\n# Notes \n\nThe authors declare the following competing financial interest(s): H.J.S. is co-founder and CSO of Oxford PV Ltd., a company commercializing perovskite PV technology. \n\n# ACKNOWLEDGMENTS \n\nThe work by V.M.L.C. is supported by a grant from STW/ NWO (VIDI 13476). This is a publication by the FOM Focus Group “Next Generation Organic Photovoltaics”, participating in the Dutch Institute for Fundamental Energy Research (DIFFER). The work by E.A.D. was supported by the Engineering and Physical Sciences Research Council (EPSRC), Grants EP/M005143/1 and EP/P006329/1. E.A.D. thanks the EPSRC for funding via the Centre for Doctoral Training in New and Sustainable Photovoltaics. \n\n# REFERENCES \n\n(1) Blakesley, J. C.; Castro, F. A.; Kylberg, W.; Dibb, G. F.; Arantes, C.; Valaski, R.; Cremona, M.; Kim, J. S.; Kim, J. S. Towards reliable charge-mobility benchmark measurements for organic semiconductors. Org. Electron. 2014, 15, 1263−1272. \n(2) Zuo, G.; Linares, M.; Upreti, T.; Kemerink, M. General rule for the energy of water-induced traps in organic semiconductors. Nat. Mater. 2019, 18, 588−593. \n(3) Le Corre, V. M. V. V. M.; Chatri, A. A. R.; Doumon, N. Y. N.; Koster, L. J. A. Charge Carrier Extraction in Organic Solar Cells Governed by Steady-State Mobilities. Adv. Energy Mater. 2017, 7, 1701138. \n(4) Shi, D.; et al. Low trap-state density and long carrier diffusion in organolead trihalide perovskite single crystals. Science 2015, 347, 519−522. \n(5) Saidaminov, M. I.; Abdelhady, A. L.; Murali, B.; Alarousu, E.; Burlakov, V. M.; Peng, W.; Dursun, I.; Wang, L.; He, Y.; Maculan, G.; Goriely, A.; Wu, T.; Mohammed, O. F.; Bakr, O. M. High-quality bulk hybrid perovskite single crystals within minutes by inverse temperature crystallization. Nat. Commun. 2015, 6, 7586. \n(6) Liu, Y.; Sun, J.; Yang, Z.; Yang, D.; Ren, X.; Xu, H.; Yang, Z.; Liu, S. F. 20-mm-Large Single-Crystalline Formamidinium-Perovskite Wafer for Mass Production of Integrated Photodetectors. Adv. Opt. Mater. 2016, 4, 1829−1837. \n(7) Zhumekenov, A. A.; Saidaminov, M. I.; Haque, M. A.; Alarousu, E.; Sarmah, S. P.; Murali, B.; Dursun, I.; Miao, X.-H.; Abdelhady, A. L.; Wu, T.; Mohammed, O. F.; Bakr, O. M. Formamidinium Lead Halide Perovskite Crystals with Unprecedented Long Carrier Dynamics and Diffusion Length. ACS Energy Lett. 2016, 1, 32−37. (8) Han, $\\mathrm{Q.;}$ Bae, S.-H.; Sun, P.; Hsieh, Y.-T.; Yang, Y. M.; Rim, Y. S.; Zhao, H.; Chen, $\\mathrm{Q.;}$ Shi, W.; Li, G.; Yang, Y. Single Crystal Formamidinium Lead Iodide $\\left(\\mathrm{FAPbI}_{3}\\right)$ ): Insight into the Structural, Optical, and Electrical Properties. Adv. Mater. 2016, 28, 2253−2258. (9) Zhang, F.; Yang, B.; Mao, X.; Yang, $\\mathrm{R}.,$ Jiang, L.; Li, Y.; Xiong, J.; Yang, Y.; He, R.; Deng, W.; Han, K. Perovskite $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{PbI}_{3-x}\\mathrm{Br}_{x}$ Single Crystals with Charge-Carrier Lifetimes Exceeding 260 μs. ACS Appl. Mater. Interfaces 2017, 9, 14827−14832. \n(10) Murali, B.; Yengel, E.; Yang, C.; Peng, W.; Alarousu, E.; Bakr, O. M.; Mohammed, O. F. The Surface of Hybrid Perovskite Crystals: A Boon or Bane. ACS Energy Letters 2017, 2, 846−856. \n(11) Gu, Z.; Huang, Z.; Li, C.; Li, M.; Song, Y. A general printing approach for scalable growth of perovskite single-crystal films. Sci. Adv. 2018, 4, 2390. \n(12) Ju, D.; Dang, Y.; Zhu, Z.; Liu, H.; Chueh, C. C.; Li, X.; Wang, L.; Hu, X.; Jen, A. K.; Tao, X. Tunable Band Gap and Long Carrier Recombination Lifetime of Stable Mixed $\\mathrm{CH}_{3}\\mathrm{NH}_{3}\\mathrm{Pb}_{x}\\mathrm{Sn}_{1-x}\\mathrm{Br}_{3}$ Single Crystals. Chem. Mater. 2018, 30, 1556−1565. \n(13) Chen, Z.; Dong, $\\mathrm{Q.;}$ Liu, Y.; Bao, C.; Fang, Y.; Lin, Y.; Tang, S.; Wang, $\\mathrm{Q.;}$ Xiao, X.; Bai, Y.; Deng, Y.; Huang, J. Thin single crystal perovskite solar cells to harvest below-bandgap light absorption. Nat. Commun. 2017, 8, 1890. \n(14) Herz, L. M. Charge-Carrier Mobilities in Metal Halide Perovskites: Fundamental Mechanisms and Limits. ACS Energy Letters 2017, 2, 1539−1548. \n(15) Peng, J.; Chen, Y.; Zheng, K.; Pullerits, T.; Liang, Z. Insights into charge carrier dynamics in organo-metal halide perovskites: From neat films to solar cells. Chem. Soc. Rev. 2017, 46, 5714−5729. (16) Duijnstee, E. A.; Ball, J. M.; Le Corre, V. M.; Koster, L. J. A.; Snaith, H. J.; Lim, J. Toward Understanding Space-Charge Limited Current Measurements on Metal Halide Perovskites. ACS Energy Letters 2020, 5, 376−384. \n(17) Duijnstee, E. A.; Le Corre, V. M.; Johnston, M. B.; Koster, L. J. A.; Lim, J.; Snaith, H. J. Understanding Dark Current-Voltage Characteristics in Metal-Halide Perovskite Single Crystals. Phys. Rev. Appl. 2021, 15, 014006. \n(18) Röhr, J. A. Direct Determination of Built-in Voltages in Asymmetric Single-Carrier Devices. Phys. Rev. Appl. 2019, 11, 054079. (19) Lampert, M. A.; Mark, P. Current injection in solids; Academic Press: New York, 1970. \n(20) Kirchartz, T. Influence of diffusion on space-charge-limited current measurements in organic semiconductors. Beilstein J. Nanotechnol. 2013, 4, 180−188. \n(21) Wetzelaer, G. A. H.; Blom, P. W. M. Ohmic current in organic metal-insulator-metal diodes revisited. Phys. Rev. B: Condens. Matter Mater. Phys. 2014, 89, 241201. \n(22) Röhr, J. A.; Kirchartz, T.; Nelson, J. On the correct interpretation of the low voltage regime in intrinsic single-carrier devices. J. Phys.: Condens. Matter 2017, 29, 205901. \n(23) Mott, N. F.; Gurney, R. W. Electronic Processes in Ionic Crystals; Oxford University Press, 1940. \n(24) Röhr, J. A.; Moia, D.; Haque, S. A.; Kirchartz, T.; Nelson, J. Exploring the validity and limitations of the Mott-Gurney law for charge-carrier mobility determination of semiconducting thin-films. J. Phys.: Condens. Matter 2018, 30, 105901. \n(25) Mark, P.; Helfrich, W. Space-charge-limited currents in organic crystals. J. Appl. Phys. 1962, 33, 205−215. \n(26) Fischer, J.; Tress, W.; Kleemann, H.; Widmer, J.; Leo, K.; Riede, M. Exploiting diffusion currents at Ohmic contacts for trap characterization in organic semiconductors. Org. Electron. 2014, 15, 2428−2432. (27) Röhr, J. A.; Shi, X.; Haque, S. A.; Kirchartz, T.; Nelson, J. Charge Transport in Spiro-OMeTAD Investigated through SpaceCharge-Limited Current Measurements. Phys. Rev. Appl. 2018, 9, 044017. \n(28) Chen, Y.-X.; Ge, $\\mathsf{Q.^{-}Q.}\\mathsf{j}$ Shi, Y.; Liu, J.; Xue, D.-J.; Ma, J.-Y.; Ding, J.; Yan, H.-J.; Hu, J.-S.; Wan, L.-J. General Space-Confined OnSubstrate Fabrication of Thickness-Adjustable Hybrid Perovskite Single-Crystalline Thin Films. J. Am. Chem. Soc. 2016, 138, 16196− 16199. \n(29) Cai, F.; Yang, L.; Yan, Y.; Zhang, J.; Qin, F.; Liu, D.; Cheng, Y.- B.; Zhou, Y.; Wang, T. Eliminated hysteresis and stabilized power output over $20\\%$ in planar heterojunction perovskite solar cells by compositional and surface modifications to the low-temperatureprocessed $\\mathrm{TiO}_{2}$ layer. J. Mater. Chem. A 2017, 5, 9402−9411. \n(30) Frost, J. M.; Walsh, A. What Is Moving in Hybrid Halide Perovskite Solar Cells? Acc. Chem. Res. 2016, 49, 528−535. \n(31) Futscher, M. H.; Lee, J. M.; McGovern, L.; Muscarella, L. A.; Wang, T.; Haider, M. I.; Fakharuddin, A.; Schmidt-Mende, L.; Ehrler, B. Quantification of ion migration in CH3NH3PbI3 perovskite solar cells by transient capacitance measurements. Mater. Horiz. 2019, 6, 1497−1503. \n(32) Zhou, Y.; Sternlicht, H.; Padture, N. P. Transmission Electron Microscopy of Halide Perovskite Materials and Devices. Joule 2019, 3, 641−661. \n(33) Pavlovetc, I. M.; Brennan, M. C.; Draguta, S.; Ruth, A.; Moot, T.; Christians, J. A.; Aleshire, K.; Harvey, S. P.; Toso, S.; Nanayakkara, S. U.; Messinger, J.; Luther, J. M.; Kuno, M. Suppressing cation migration in triple-cation lead halide perovskites. ACS Energy Letters 2020, 5, 2802−2810. \n(34) Ceratti, D. R.; Zohar, A.; Kozlov, R.; Dong, H.; Uraltsev, G.; Girshevitz, O.; Pinkas, I.; Avram, L.; Hodes, G.; Cahen, D. Eppur si Muove: Proton Diffusion in Halide Perovskite Single Crystals. Adv. Mater. 2020, 32, 2002467. \n(35) Jin, H.; Debroye, E.; Keshavarz, M.; Scheblykin, I. G.; Roeffaers, M. B.; Hofkens, J.; Steele, J. A. It’s a trap! on the nature of localised states and charge trapping in lead halide perovskites. Mater. Horiz. 2020, 7, 397−410. \n(36) Snaith, H. J.; Abate, A.; Ball, J. M.; Eperon, G. E.; Leijtens, T.; Noel, N. K.; Stranks, S. D.; Wang, J. T. W.; Wojciechowski, K.; Zhang, W. Anomalous hysteresis in perovskite solar cells. J. Phys. Chem. Lett. 2014, 5, 1511−1515. \n(37) Weber, S. A.; Hermes, I. M.; Turren-Cruz, S. H.; Gort, C.; Bergmann, V. W.; Gilson, L.; Hagfeldt, A.; Graetzel, M.; Tress, W.; Berger, R. How the formation of interfacial charge causes hysteresis in perovskite solar cells. Energy Environ. Sci. 2018, 11, 2404−2413. (38) Van Reenen, S.; Kemerink, M.; Snaith, H. J. Modeling Anomalous Hysteresis in Perovskite Solar Cells. J. Phys. Chem. Lett. 2015, 6, 3808−3814. \n(39) Sherkar, T. S.; Momblona, C.; Gil-Escrig, L.; Á vila, J.; Sessolo, M.; Bolink, H. J.; Koster, L. J. A. Recombination in Perovskite Solar Cells: Significance of Grain Boundaries, Interface Traps, and Defect Ions. ACS Energy Letters 2017, 2, 1214−1222. \n(40) Sajedi Alvar, M.; Blom, P. W.; Wetzelaer, G. J. A. Space-chargelimited electron and hole currents in hybrid organic-inorganic perovskites. Nat. Commun. 2020, 11, 4023. \n(41) Kerner, R. A.; Schulz, P.; Christians, J. A.; Dunfield, S. P.; Dou, B.; Zhao, L.; Teeter, G.; Berry, J. J.; Rand, B. P. Reactions at noble metal contacts with methylammonium lead triiodide perovskites: Role of underpotential deposition and electrochemistry. APL Mater. 2019, 7, 041103. \n(42) Koster, L. J. A.; Smits, E. C. P.; Mihailetchi, V. D.; Blom, P. W. M. Device model for the operation of polymer/fullerene bulk heterojunction solar cells. Phys. Rev. B: Condens. Matter Mater. Phys. 2005, 72, 85205. \n(43) Sherkar, T. S.; Momblona, C.; Gil-Escrig, L.; Bolink, H. J.; Koster, L. J. A. Improving Perovskite Solar Cells: Insights From a Validated Device Model. Adv. Energy Mater. 2017, 7, 1602432. (44) Sherkar, T. S.; Le Corre, V. M.; Koopmans, M.; Wobben, F.; \nKoster, L. J. A. SIMsalabim GitHub repository. 2020 (https://github. \ncom/kostergroup/SIMsalabim) (accessed December 2020). " + }, + { + "id": "10.1038_s41467-021-22030-5", + "DOI": "10.1038/s41467-021-22030-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-22030-5", + "Relative Dir Path": "mds/10.1038_s41467-021-22030-5", + "Article Title": "New material platform for superconducting transmon qubits with coherence times exceeding 0.3 milliseconds", + "Authors": "Place, APM; Rodgers, LVH; Mundada, P; Smitham, BM; Fitzpatrick, M; Leng, ZQ; Premkumar, A; Bryon, J; Vrajitoarea, A; Sussman, S; Cheng, GM; Madhavan, T; Babla, HK; Le, XH; Gang, YQ; Jäck, B; Gyenis, A; Yao, N; Cava, RJ; de Leon, NP; Houck, AA", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "The superconducting transmon qubit is a leading platform for quantum computing and quantum science. Building large, useful quantum systems based on transmon qubits will require significant improvements in qubit relaxation and coherence times, which are orders of magnitude shorter than limits imposed by bulk properties of the constituent materials. This indicates that relaxation likely originates from uncontrolled surfaces, interfaces, and contaminullts. Previous efforts to improve qubit lifetimes have focused primarily on designs that minimize contributions from surfaces. However, significant improvements in the lifetime of two-dimensional transmon qubits have remained elusive for several years. Here, we fabricate two-dimensional transmon qubits that have both lifetimes and coherence times with dynamical decoupling exceeding 0.3 milliseconds by replacing niobium with tantalum in the device. We have observed increased lifetimes for seventeen devices, indicating that these material improvements are robust, paving the way for higher gate fidelities in multi-qubit processors. Quantum computers based on superconducting transmon qubits are limited by single qubit lifetimes and coherence times, which are orders of magnitude shorter than limits imposed by bulk material properties. Here, the authors fabricate two-dimensional transmon qubits with both lifetimes and coherence times longer than 0.3 milliseconds by replacing niobium with tantalum in the device.", + "Times Cited, WoS Core": 331, + "Times Cited, All Databases": 400, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000631934100011", + "Markdown": "# New material platform for superconducting transmon qubits with coherence times exceeding 0.3 milliseconds \n\nAlexander P. M. Place1,5, Lila V. H. Rodgers1,5, Pranav Mundada1, Basil M. Smitham1, Mattias Fitzpatrick1, Zhaoqi Leng2, Anjali Premkumar1, Jacob Bryon1, Andrei Vrajitoarea1, Sara Sussman2, Guangming Cheng3, Trisha Madhavan1, Harshvardhan K. Babla1, Xuan Hoang Le1, Youqi Gang1, Berthold Jäck 2, András Gyenis $\\textcircled{1}$ 1, Nan Yao $\\textcircled{1}$ 3, Robert J. Cava4, Nathalie P. de Leon 1 & Andrew A. Houck 1✉ \n\nThe superconducting transmon qubit is a leading platform for quantum computing and quantum science. Building large, useful quantum systems based on transmon qubits will require significant improvements in qubit relaxation and coherence times, which are orders of magnitude shorter than limits imposed by bulk properties of the constituent materials. This indicates that relaxation likely originates from uncontrolled surfaces, interfaces, and contaminants. Previous efforts to improve qubit lifetimes have focused primarily on designs that minimize contributions from surfaces. However, significant improvements in the lifetime of two-dimensional transmon qubits have remained elusive for several years. Here, we fabricate two-dimensional transmon qubits that have both lifetimes and coherence times with dynamical decoupling exceeding 0.3 milliseconds by replacing niobium with tantalum in the device. We have observed increased lifetimes for seventeen devices, indicating that these material improvements are robust, paving the way for higher gate fidelities in multi-qubit processors. \n\nStceoandy tpirnog rqeussb isn iermtphreovlianstg goatdeeca1d–e3lsithieas fnoar seudpkerycorrection4–6, and quantum supremacy7. These demonstrations have relied on either improving coherence through microwave engineering to avoid losses associated with surfaces and interfaces8–10 and to minimize the effects of thermal noise and quasiparticles11–14, or by realizing fast gates using tunable coupling15,16. By contrast, little progress has been made in addressing the microscopic source of loss and noise in the constituent materials. Specifically, the lifetime $(T_{1})$ of the twodimensional (2D) transmon qubit has not reliably improved beyond $100\\upmu\\mathrm{s}$ since $2012^{17,18}$ , and to date the longest published $T_{1}$ is $114\\upmu\\mathrm{s}^{\\mathrm{{l}}\\dot{9}}$ , consistent with other recent literature reports20–22. \n\nThe lifetimes of current 2D transmons are believed to be limited by microwave dielectric losses23–25. However, the expected loss tangent of the bulk constituent materials should allow for significantly longer lifetimes. For example, if the only source of loss is high-purity bulk sapphire with loss tangent $<1\\dot{0}^{-926,27}$ , $T_{1}$ would exceed $30\\mathrm{m}s$ . Although it is notoriously difficult to pinpoint microscopic loss mechanisms, this suggests that losses are dominated by uncontrolled defects at surfaces and interfaces, by material contaminants, or by quasiparticles trapped at the surface28. Here we demonstrate that a significant improvement over the state of the art in 2D transmon qubits can be achieved by using tantalum as the superconductor in the capacitor and microwave resonators, replacing the more commonly used niobium. We hypothesize that the complicated stoichiometry of oxides at the niobium surface can include non-insulating species29–31 that leads to additional microwave loss, and that the insulating oxide of tantalum32,33 reduces microwave loss in the device. We observe a time-averaged $T_{1}$ exceeding $0.3\\mathrm{ms}$ in our best device and an average $T_{1}$ of $0.23\\mathrm{ms}$ averaged across all devices, a significant improvement over the state of the art. \n\n# Results \n\nTransmon fabrication and measurement. To fabricate qubits (see “Methods”), tantalum is commercially deposited on sapphire substrates by sputtering while heating the substrate to around $500^{\\circ}\\mathrm{C}$ to ensure growth of the BCC $\\alpha$ phase34,35. We then use photolithography and a wet chemical etch to define the capacitor and resonator of the device, followed by electron beam lithography and an in situ ion etch before electron beam evaporation of an aluminum and aluminum oxide Josephson junction (Fig. 1a). Between most key steps of the fabrication process, we use solvent and piranha cleaning to reduce contamination introduced during fabrication. The transmon is capacitively coupled to a lithographically defined resonator (Fig. 1b), allowing us to dispersively measure the state of the qubit36. To determine $T_{1},$ we excite the qubit with a $\\pi$ -pulse and measure its decay over time at a temperature between 9 and $20~\\mathrm{mK}$ . In our best device, our highest $T_{1}$ measurement is $0.36\\pm0.01$ ms (Fig. 1c). We verify that the deposited tantalum film is in the $\\alpha$ phase by measuring resistance as a function of temperature. The observed superconducting critical temperature $\\Bar{(T_{c})}$ is around $4.3\\mathrm{K},$ which is consistent with the intended phase (Fig. 1d) rather than the tetragonal $\\beta$ phase, which has a $T_{c}$ below $\\mathrm{1\\K^{37,38}}$ . \n\nWe observe reproducible, robust enhancement of $T_{1}$ across all devices fabricated with this process. The lifetime of a given qubit fluctuates over time, with a standard deviation of around $7\\%$ of the mean (Fig. 2a). Results for eight devices are presented in Fig. 2b, with the time-averaged $T_{1}$ ranging from 0.15 to $0.30\\mathrm{ms},$ and an average $T_{1}$ of $0.23\\mathrm{ms}$ across all devices, qualitatively exceeding the $T_{1}$ of prior 2D transmon devices. We note that the highest observed $T_{1}$ and $T_{2}$ are achieved in a device with a thinner aluminum layer (Device 18, see “Methods”). The time-averaged coherence time, $T_{2,\\mathrm{Echo}},$ in our best device is $0.20\\pm0.03\\mathrm{ms}$ (a trace is shown in Fig. 2c). We can extend the coherence time using a Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence39 (Fig. 2d), and we achieve a time-averaged $T_{2,\\mathrm{CPMG}}$ of $0.38\\pm0.11$ ms in our best device (Fig. 2a). The spectral noise density extracted from dynamical decoupling measurements is consistent with $1/f$ noise (Supplementary Fig. 11) suggesting that this noise can be mitigated with a Floquet drive40. We note that there are small variations in processing and packaging between these eight devices, which are outlined in “Methods” and Supplementary Table 1. \n\n![](images/8fa8162c6b76edec2784ef2e84d03e048276dff4ec322c3f39a4646061b97403.jpg) \nFig. 1 Tantalum-based transmon superconducting qubit. a False-colored optical microscope image of a transmon qubit. The transmon consists of a Josephson junction shunted by two large capacitor islands made of tantalum (blue) on sapphire (gray). b Device layout image and corresponding circuit diagram of the transmon qubit coupled to the resonator via a coupling capacitor. c $T_{1}$ measurement of Device 18, showing the excited state population $P_{e}$ as a function of delay time $\\Delta t$ . Line represents a single exponential fit with a characteristic $T_{1}$ time of $0.36\\pm$ $0.01\\mathrm{ms}$ . d Four-probe resistance measurement of the tantalum film showing $T_{c}=4.38\\pm0.02\\mathsf{K}$ consistent with the critical temperature of $\\alpha$ -tantalum. \n\n![](images/786b821afb44717b3eab40dc403f32256e3245045fb5a5a13ecb84113f4886d2.jpg) \nFig. 2 Lifetime and decoherence measurements. a Lifetime $(T_{1})$ and coherence time with dynamical decoupling $(T_{2,C P M G})$ of Device 18 over time. b Summary of $T_{1}$ time series measurements of all devices fabricated with a wet etch and piranha cleaning steps. Details about the specific processing steps for each device are given in Supplementary Table 1 and “Methods.” The yellow line shows the median, while the box spans the middle two quartiles of the data. The whiskers show the extremal measurements. Data for Devices 13, 14, and 17 are the average of 19, 14, and 7 individual $T_{1}$ measurements, respectively, while the rest are the average of at least 32 measurements. Each device was measured over a period of hours to days, and Devices 11 and 13 include data from multiple dilution refrigerator cycles. c $T_{2,\\mathsf{E c h o}}$ measurement of Device 18, showing the excited state population $P_{e}$ as a function of delay time Δt. Solid blue line shows a stretched exponential fit to the data. The fit gives $T_{2,\\mathsf{E c h o}}=249\\pm$ $4\\upmu\\up s$ . d $T_{2,\\mathsf{C P M G}}$ of Device 11 as a function of the number of gates in a CPMG pulse sequence. The error bars denote one standard deviation in the data. \n\nDevice iterations. In addition to the eight qubits presented in Fig. 2, we present data on a total of 21 transmon qubits that were fabricated using different geometries, materials, and fabrication processes in Supplementary Table 1. We note that switching from niobium to tantalum alone increased the average $T_{1}$ for a Purcellfiltered qubit to $150\\upmu\\mathrm{s}$ (Device 2), already a significant improvement over the best published 2D transmon lifetime. To study the impact of heating the substrate during deposition, we made a device from niobium sputtered at $500^{\\circ}\\dot{\\mathrm{C}}$ (Device Nb2). This resulted in a $T_{1}$ of $79\\pm1~\\upmu s$ , an improvement over our previous niobium devices, but qualitatively lower than tantalumbased devices. This indicates that thermal cleaning of the substrate may play a role in enhancing $T_{1},$ but does not completely explain our improved coherence. \n\nIterative improvements to processing, including the use of wet etching to pattern the tantalum layer and the introduction of additional cleaning steps, further improved qubit lifetimes to the levels reported in Fig. 2 (Devices 11–18). Specifically, a piranha cleaning process (see “Methods”) was introduced to clean particulates and contaminants from the substrate and metal surfaces. Removal of particulates was verified using atomic force microscopy (AFM), and the signal due to adventitious carbon measured by $\\mathbf{x}$ -ray photoelectron spectroscopy (XPS) is attenuated after cleaning (Supplementary Fig. 3). In addition, we find that the introduction of an optimized wet etch process to pattern the tantalum resulted in improved edge morphology compared with reactive-ion etching (Supplementary Fig. 2). Of the ten devices measured prior to the optimized wet etch, none had a $T_{1}$ in excess of $200\\upmu\\mathrm{s};$ of the eight patterned with the optimized wet etch and fabricated with our cleaning procedure, six had a \n\n$T_{1}>200\\upmu s$ . These observations imply that residue and poor edge and surface morphology may limit qubit lifetimes for our tantalum devices. \n\nCharacterization of tantalum films. Because thin film structure has been observed to affect qubit performance for niobium-based qubits31, and because the crystal structure of thin tantalum films sensitively depends on deposition parameters34,37, we present detailed characterization of the deposited tantalum films. Scanning transmission electron microscopy (STEM) of a film cross section reveals a columnar structure, with the growth direction oriented along the [110] axis (Fig. 3a) and these observations are corroborated by probing a larger area with $\\mathbf{x}$ -ray diffraction measurements (Supplementary Fig. 7). Atomic-resolution STEM confirms the BCC structure of the film and reveals that the individual columnar grains are single-crystal, with the front growth face perpendicular to either the $\\left\\langle100\\right\\rangle$ or 111 directions (Fig. 3b). The different orientations result from the underlying three-fold symmetry of the sapphire crystal structure about its caxis41. A top-down plane view cross-sectional STEM shows that the grains range in size from around $5{-}50\\mathrm{nm}$ (Fig. 3c). We study the tantalum oxide on our devices using XPS, which shows two sets of spin-orbit split doublet peaks with binding energy between 20 and $30\\mathrm{eV}$ associated with $4f$ core ionization of Ta metal (lower binding energy) and ${\\mathrm{Ta}}_{2}{\\mathrm{O}}_{5}$ (higher binding energy) (Fig. 3d)42,43. The relative intensity of the metal and oxide peaks indicates that the oxide is ${\\sim}2\\ –\\mathrm{nm}$ thick (see Supplementary Information), consistent with angle-resolved XPS and high-resolution STEM measurements (Supplementary Fig. 9). Last, we directly image the interface between the sapphire surface and the sputtered tantalum using integrated differential phase contrast imaging under STEM (Fig. 3e). The interface shows an atomically sharp boundary with clear evidence of epitaxial growth, in which the tantalum atomic layer is directly grown on top of the oxygen atomic layer in the sapphire. \n\n# Discussion \n\nWe have demonstrated that tantalum 2D transmon qubits exhibit longer $T_{1}$ and $T_{2}$ than the previous state of the art with remarkable consistency. Building on these relatively simple materials improvements, there are several areas of future research. First, $T_{2,\\mathrm{Echo}}$ is shorter than $T_{1}$ for all tantalum devices measured. Better shielding44 and filtering45 of tantalum transmons may enable measurements with unprecedentedly long $T_{2}$ , allowing for the exploration of microscopic mechanisms of relaxation and decoherence. In addition, much can be learned from more systematic characterization of the effects of specific material properties on microwave losses. In particular, there are many open questions about the relative importance of oxide properties on device performance. An exciting avenue is to explore the detailed scaling of $T_{1}$ with surface participation by measuring tantalum qubits with different geometries. In addition, we are exploring the impact of tantalum grain size and heteroepitaxial growth interface quality on $T_{1}$ and $T_{2}$ . Furthermore, it has been well-established that multi-qubit devices suffer from significant variation between qubits21, as well as variation over time in the same qubit46. An interesting question is how particular material choices quantitatively affect these variations, and whether judicious material choice can narrow the distribution of device properties. Finally, we note that while we have not made a direct comparison to allaluminum qubits in this paper, the average $T_{1}$ achieved here is better than twice as long as the best published all-aluminum 2D transmon22,47. Further, our process produces a higher and more consistent average $T_{1}$ than the reported state of the art in 3D all-aluminum transmons48–50. The feasibility of eliminating aluminum by making all-tantalum qubits has yet to be explored. \n\n![](images/4b718e1773632eedd3e369a9cc6739a23733d36817c4bc1265bbd546dd833f11.jpg) \nFig. 3 Microscopy and spectroscopy of tantalum films. a STEM image of the tantalum film, showing single-crystal columns with the growth direction oriented along the [110] axis. b Atomic-resolution STEM image of an interface between two columns, viewed from $\\langle\\bar{11}\\bar{1}\\rangle$ and 001i zone axes, respectively. Fourier transforms (insets) of the image show that the columns are oriented with the image plane perpendicular to the 111i or $\\left\\langle100\\right\\rangle$ directions. c STEM image of a horizontal device cross section, showing grain boundaries. Image contrast at grain boundaries results from diffraction contrast caused by interfacial defects. d XPS spectrum of a device, exhibiting peaks from tantalum metal and $\\mathsf{T a}_{2}\\mathsf{O}_{5}$ . Other oxidation states of tantalum are expected to have binding energies between 22.2 and $23.8\\mathsf{e V}^{42,}$ 43. e High-resolution STEM with integrated differential phase contrast imaging of the interface between the sapphire and tantalum showing epitaxial growth. \n\nMore broadly, our results demonstrate that systematic material improvements are a powerful approach for rapid progress in improving quantum devices. We have recently employed similar targeted material techniques to improve spin coherence of shallow nitrogen vacancy centers in diamond51, and we note that many other quantum platforms are also limited by noise and loss at surfaces and interfaces, including trapped ions52,53, shallow donors54,55, and semiconductor quantum dots56. Our general approach of modifying and characterizing the constituent materials may allow for directed, rational improvements in these broad classes of systems as well. \n\n# Methods \n\nTantalum deposition and lithography. The 2D transmon qubits are fabricated on c-plane sapphire substrates (Crystec GmbH) that are $0.53\\mathrm{-mm}$ thick and doubleside polished (Supplementary Fig. 1). Prior to deposition, the wafer is cleaned by the commercial deposition company, Star Cryoelectronics, by dipping in a piranha solution $\\mathrm{(H}_{2}\\mathrm{SO}_{4}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2}\\mathrm{,}$ then cleaning with an oxygen plasma (Technics PE-IIA System) immediately before loading into the sputterer. \n\nTantalum is deposited on the sapphire substrate at high temperature (Star Cryoelectronics, alpha tantalum, $500^{\\circ}\\mathrm{C}$ deposition, $200\\mathrm{-nm}$ thickness, no seed layer, sapphire preclean with piranha and oxygen plasma). Before photolithography, the tantalum-coated substrates are placed in a 2:1 mixture of ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ for $20\\mathrm{min}$ (hereafter “piranha” refers to this specific chemical ratio and time duration) then heated on a hotplate for $5\\mathrm{{min}}$ at $140^{\\circ}\\mathrm{C}$ before AZ 1518 resist is spun (Merck KGaA). The resist is patterned using a direct-write process $2\\mathrm{mm}$ write head on a Heidelberg DWL $^{66+}$ Laser Writer). After developing (85 s in AZ 300MIF developer from Merck KGaA), the resist is hardbaked for $2\\mathrm{min}$ at $115^{\\circ}\\mathrm{C}$ . Unwanted residual resist is removed using a gentle oxygen descum (2 min in 30-mTorr $\\mathrm{O}_{2}$ with 20 W/200 W RF/ICP coil power in a Plasma-Therm Apex SLR). Next, the tantalum is etched in a 1:1:1 ratio of HF: ${\\mathrm{HNO}}_{3}{:}\\mathrm{H}_{2}\\mathrm{O}$ (Tantalum Etchant 111 from Transene Company, Inc.) for $21{\\mathfrak{s}}.$ . After stripping resist, the device is solvent-cleaned by sonicating in sequential baths of toluene, acetone, methanol, and isopropyl alcohol for ${\\sim}2\\ \\mathrm{{min}}$ each (\"TAMIcleaned”) then piranha-cleaned. The patterned tantalum is prepared for electron beam lithography to define Josephson junctions (resists MMA 8.5 MAA and 950 PMMA, with a $40\\mathrm{-nm}$ layer of evaporated aluminum to dissipate charge), then the chips are diced into $7\\times7$ -mm squares. \n\nLiftoff patterns for Manhattan junctions57 with overlap areas of ${\\sim}0.03\\upmu\\mathrm{m}^{2}$ are then exposed (Elionix ELS-F125). The anticharge layer is removed through a 4-min bath in MF 319 (Rohm and Haas Electronic Materials LLC) followed by a 50-s bath in a 1:3 mixture of methyl isobutyl ketone to isopropyl alcohol. Next, the device is loaded into a Plassys MEB 550S electron beam evaporator and ion-milled $(400\\mathrm{V}$ \n\n$30\\mathrm{{s}}$ along each trench of the junction). Immediately after, $15\\mathrm{nm}$ of aluminum is deposited at $0.4\\mathrm{nm}/\\mathrm{s}$ at a pressure of ${\\sim}10^{-7}$ mBar, followed by a $15\\mathrm{-min}$ , 200-mBar oxidation period. Finally, $54\\mathrm{nm}$ of aluminum is deposited to form the second layer of the junction, with the same evaporation parameters (for Device 18, 15 and $19\\mathrm{nm}$ of aluminum are deposited, respectively). The resist is then removed by soaking the sample in Remover PG (Kayaku Advanced Materials, Inc.) for ${\\sim}3\\mathrm{h}$ at $80^{\\circ}\\mathrm{C}$ , briefly sonicating in hot Remover PG, then swirling in isopropyl alcohol. \n\nDevice packaging. The completed devices are first mounted to a printed circuit board (PCB). The edge of the tantalum ground plane is firmly pressed against the PCB’s copper backside, sandwiched between the PCB and a piece of aluminumcoated oxygen-free copper (Supplementary Fig. 5b). The device is then wirebonded (Supplementary Fig. 5a, d). An aluminum-coated oxygen-free copper lid is sometimes placed above the qubit (Supplementary Table 1 column “Enclosure Lid Removed”), forming a superconducting enclosure partially surrounding the qubit. The device is mounted in a dilution refrigerator with a base temperature of ${\\sim}9{-}20~\\mathrm{mK}$ . The qubit and PCB are wrapped in several layers of aluminized mylar sheeting and suspended by an oxygen-free copper rod in the middle of an aluminum cylinder coated with microwave-attenuating epoxy or sheeting (Laird Performance Materials Eccosorb Cr or Loctite Stycast). This cylinder is enclosed in a mu-metal can to reduce the penetration of ambient magnetic fields into the aluminum during the superconducting transition. Both cans are then wrapped in several layers of mylar sheeting. \n\nWe note that all of the double-pad transmons presented in this text are positioned ${\\sim}2\\mathrm{mm}$ away from the copper traces on the PCB (Supplementary Fig. 5a), which could result in loss due to parasitic coupling of the qubit to the resistive traces. In order to reduce this possible source of loss, devices fabricated with the single-pad geometry were moved close to the center of the sapphire chip (Supplementary Fig. 5d). \n\nMeasurement setup. Each transmon is capacitively coupled to a microwave resonator, allowing the state of the qubit to be measured dispersively36. The transmon frequencies range from 3.1 to $5.5\\mathrm{GHz}$ while the resonators range in frequency from 6.8 to $7.3\\:\\mathrm{GHz}$ . An overview of the setup used to measure a majority of the devices is given in Supplementary Fig. 6. An Agilent E8267D vector signal generator, Holzworth HS9004A RF synthesizer, and Keysight M9330A arbitrary waveform generator are used to synthesize the excitation and measurement pulses. The input signals are combined into a single line and then attenuated on each plate of the dilution refrigerator. An additional filter made of Eccosorb CR110 epoxy is placed in the aluminum can to attenuate high-frequency radiation. Measured in reflection, the output signal is sent through a circulator (Raditek RADC-4-8-cryo-0.01-4K-S23-1WR-ss-Cu-b), two isolators (Quinstar QCI -075900XM00), superconducting wires, and then a high-electron-mobility transistor amplifier (Low Noise Factory LNF-LNC4_8C) at $4\\mathrm{K}$ . After the signal is amplified at room temperature (through two MITEQ AFS4-00101200 18-10P-4 amplifiers), it is measured in a homodyne setup by first mixing it with a local oscillator (Holzworth HS9004A), further amplifying (Stanford Research Systems SR445a), and then digitizing (Acqiris U1084A). \n\nTantalum etch. Initially we etched tantalum using a reactive-ion etch (8:3:2 $\\mathrm{CHF}_{3}$ : ${\\mathrm{SF}}_{6}$ :Ar chemistry at 50 mTorr, RF/ICP power of 100/100 W). However, scanning electron microscopy (SEM) images showed that reactive-ion etches can produce rough edges as well as small pillars and boulders near the sidewalls, likely due to micromasking (Supplementary Fig. 2a, b). The anomalous objects in Supplementary Fig. 2b remained after the device was cleaned in piranha solution and treated in an oxygen plasma. In order to avoid these fabrication problems, we employed a wet etch composed of 1:1:1 $\\mathrm{HF}{:}\\mathrm{HNO}_{3}{:}\\mathrm{H}_{2}\\mathrm{O}$ . We found that several resists delaminated before the tantalum was etched through, leaving the sidewalls and nearby tantalum visibly rough in SEM (Supplementary Fig. 2c). This problem was circumvented by using thick AZ 1518 resist $(\\sim2\\ –\\upmu\\mathrm{m}$ tall), which left cleaner sidewalls (Supplementary Fig. 2d). Comparing Devices 4–10 with Devices 11–18 in Supplementary Table 1, we note that the optimized wet etch likely improved $T_{1}$ . \n\nSapphire preparation. During recipe development, we aggressively cleaned and etched some wafers before tantalum was deposited. After dicing the resist-covered sapphire wafers, stripping the resist, and sonicating in solvents we found surface contamination. In particular, AFM revealed an abundance of particulates (Supplementary Fig. 3a) which were removed by cleaning in piranha solution (Supplementary Fig. 3b). The etched and piranha-cleaned surface was smooth $\\mathrm{{R}}_{a}$ of 80 pm) and did not show any signs of roughening (Supplementary Fig. 3b). In addition, the carbon signal in XPS was attenuated by a factor of 5 after piranha cleaning, illustrating a reduction in carbon contamination (Supplementary Fig. 3c). XPS also revealed zinc contamination that persisted through a piranha clean, but was removed by etching the sapphire substrate in heated sulfuric acid (Supplementary Fig. 3d). We note that sapphire wafers that had not been diced, stripped of resist, and sonicated in solvents displayed few particulates in AFM, and XPS showed a minimal carbon signal and no detectable zinc signal. \n\nWe prepare the sapphire surface using this sulfuric acid etch in Devices 9–14 and 17. In these devices, the wafers are covered with a protective layer of photoresist and then diced into 1 inch squares. After removing resist, the squares are TAMI-cleaned and piranha-cleaned. Next, the sapphire is placed into a quartz beaker filled with $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ sitting on a room temperature hotplate. The hotplate is set to $150^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ , followed by a $10\\mathrm{-min}$ cooldown period before removing the device. We estimate that $<1\\mathrm{nm}$ of the surface is removed through this procedure58. To avoid residue from the etch, the device is piranha-cleaned again. The device is then packaged, shipped, and loaded into a sputterer without further cleaning. \n\nCalibrating the time and temperature of the sapphire etch is critical to maintaining a smooth surface morphology while still removing zinc. In particular, polycrystalline aluminum sulfates form on the sapphire surface after heating in sulfuric acid for too long and at too high of a temperature (Supplementary Fig. 4a)58. We developed our sapphire etch recipe by (1) looking for crystal formation in an optical microscope, (2) ensuring that zinc was removed in XPS, and (3) checking that we preserved smooth surface morphology in AFM. We note that the zinc appeared to be inhomogeneously distributed on the surface and so we routinely checked multiple spots in XPS. After adjusting the time and temperature to the optimum procedure outlined above, we did not detect any crystal formation. \n\nIn addition, we observed surface contamination with AFM from etching sapphire in borosilicate glassware. An example of surface particulate contamination is shown in Supplementary Fig. 4b. Switching to a quartz beaker solved this issue. \n\nWe note that Devices 16 and 18 were not processed using the sapphire etch, and they exhibited $T_{1}$ over $0.2\\mathrm{ms}$ . In the future, we are interested in studying the impact of sapphire material properties on device performance. We plan to fabricate devices on higher-purity sapphire, remove polishing-induced strain by etching more of the substrate, and anneal to form an atomically smooth surface58. \n\nFabrication and packaging procedure iterations. Supplementary Table 1 summarizes different iterations of the fabrication procedure. Initially we made a tantalum transmon using our standard niobium processing techniques (reactive-ion etching, no acid cleaning). This material switch alone improved the coherence time by more than a factor of four compared to the control sample (Supplementary Table 1, Devices 1a and Nb1). We then began to iterate our packaging and fabrication techniques to explore the new dominant loss mechanisms. \n\nFirst we minimized losses unrelated to the qubit materials and interfaces. We reduced the density of photonic states at the qubit frequency by means of a Purcell filter (Device 2a and all subsequent devices)59. We also deposited aluminum shielding on a majority of the copper enclosure immediately surrounding the device to reduce dissipative currents induced by the qubit in the surrounding metal. At the same time, we introduced a mylar sheet wrapped around the PCB as an extra layer of shielding. Both added layers give additional protection from highenergy radiation (Device 2b and all subsequent devices). \n\nNext we focused on reducing material contaminants. XPS measurements revealed significant carbon residue that persisted after solvent-based cleaning. Accordingly, we reduced carbon contamination by adding a piranha clean before spinning e-beam resist (Device 4 and all subsequent devices). As mentioned above, we also cleaned the sapphire substrate prior to tantalum deposition. For Devices 1–8, 15–16, and 18 as well as Nb1 and Nb2, the sapphire substrate was dipped in a piranha solution and cleaned with an oxygen plasma (Technics PE-IIA System) immediately before loading into the sputterer. For the rest of the sapphire devices, we cleaned the substrate with the sapphire etch described above (Supplementary Note 2), packaged and shipped the samples, then deposited the tantalum. \n\nWe then focused on the tantalum etch, described in more detail above. Devices 1–6, Nb1–2, and Si1 were all fabricated with reactive-ion etching. Devices 7–10 were made using initial versions of the wet etch (using different resists, etch times, and acid concentrations), where the etch clearly roughened the sidewalls (Supplementary Fig. 2c). Devices 11–18 were made using the optimized wet etch. \n\n# Data availability \n\nThe data are available upon reasonable request. \n\n# Code availability \n\nThe codes are available upon reasonable request. \n\nReceived: 23 July 2020; Accepted: 24 February 2021; Published online: 19 March 2021 \n\n# References \n\n1. Montanaro, A. Quantum algorithms: an overview. npj Quantum Inf. 2, 15023 (2016). \n2. Kandala, A. et al. Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets. Nature 549, 242–246 (2017). \n3. O’Malley, P. J. et al. Scalable quantum simulation of molecular energies. Phys. Rev. X 6, 031007 (2016). \n4. Ofek, N. et al. Extending the lifetime of a quantum bit with error correction in superconducting circuits. Nature 536, 441–445 (2016). \n5. Hu, L. et al. Quantum error correction and universal gate set operation on abinomial bosonic logical qubit. Nat. Phys. 15, 503–508 (2019). \n6. Reed, M. D. et al. Realization of three-qubit quantum error correction with superconducting circuits. Nature 482, 382–385 (2012). \n7. Arute, F. et al. Quantum supremacy using a programmable superconducting processor. Nature 574, 505–510 (2019). \n8. Paik, H. et al. Observation of high coherence in Josephson junction qubits measured in a three-dimensional circuit QED architecture. Phys. Rev. Lett. 107, 240501 (2011). \n9. Oliver, W. D. & Welander, P. B. Materials in superconducting quantum bits. MRS Bull. 38, 816–825 (2013). \n10. Gambetta, J. M. et al. Investigating surface loss effects in superconducting transmon qubits. IEEE Trans. Appl. Superconductivity 27, 1–5 (2016). \n11. Corcoles, A. D. et al. Protecting superconducting qubits from radiation. Appl. Phys. Lett. 99, 181906 (2011). \n12. Serniak, K. et al. Hot nonequilibrium quasiparticles in transmon qubits. Phys. Rev. Lett. 121, 157701 (2018). \n13. Gustavsson, S. et al. Suppressing relaxation in superconducting qubits by quasiparticle pumping. Science 354, 1573–1577 (2016). \n14. Wang, C. et al. Measurement and control of quasiparticle dynamics in a superconducting qubit. Nat. Commun. 5, 5836 (2014). \n15. Chen, Y. et al. Qubit architecture with high coherence and fast tunable coupling. Phys. Rev. Lett. 113, 220502 (2014). \n16. Mundada, P., Zhang, G., Hazard, T. & Houck, A. Suppression of qubit crosstalk in a tunable coupling superconducting circuit. Phys. Rev. Appl. 12, 054023 (2019). \n17. Kjaergaard, M. et al. Superconducting Qubits: current state of play. https:// arxiv.org/abs/1905.13641 (2019). \n18. Devoret, M. H. & Schoelkopf, R. J. Superconducting circuits for quantum information:an outlook. Science 339, 1169–1174 (2013). \n19. Nersisyan, A. et al. Manufacturing low dissipation superconducting quantum processors. https://arxiv.org/abs/1901.08042 (2019). \n20. Barends, R. et al. Superconducting quantum circuits at the surface code threshold for fault tolerance. Nature 508, 500–503 (2014). \n21. Wei, K. X. et al. Verifying multipartite entangled GHZ states via multiple quantum coherences. https://arxiv.org/abs/1905.05720 (2019). \n22. Dunsworth, A. et al. Characterization and reduction of capacitive loss induced by sub-micron Josephson junction fabrication in superconducting qubits. Appl. Phys. Lett. 111, 022601 (2017). \n23. Kamal, A. et al. Improved superconducting qubit coherence with hightemperature substrate annealing. https://arxiv.org/abs/1606.09262 (2016). \n24. Lisenfeld, J. et al. Electric field spectroscopy of material defects in transmon qubits. npj Quantum Inf. 5, 1–6 (2019). \n25. Wang, C. et al. Surface participation and dielectric loss in superconducting qubits. Appl. Phys. Lett. 107, 162601 (2015). \n26. Braginsky, V., Ilchenko, V. & Bagdassarov, K. S. Experimental observation of fundamental microwave absorption in high-quality dielectric crystals. Phys. Lett. A 120, 300–305 (1987). \n27. Luiten, A., Mann, A. & Blair, D. Ultrahigh Q-factor cryogenic sapphire resonator. Electron. Lett. 29, 879–881 (1993). \n28. De Graaf, S. et al. Two-level systems in superconducting quantum devices due to trapped quasiparticles. https://arxiv.org/abs/2004.02485 (2020). \n29. Cava, R. J. et al. Electrical and magnetic properties of Nb 2 O 5- δ crystallographic shear structures. Phys. Rev. B 44, 6973–6981 (1991). \n30. Nico, C., Monteiro, T. & Graca, M. P. Niobium oxides and niobates physical properties:Review and prospects. Prog. Mater. Sci. 80, 1–37 (2016). \n31. Premkumar, A. et al. Microscopic relaxation channels in materials for superconducting Qubits. https://arxiv.org/abs/2004.02908 (2020). \n32. Face, D. & Prober, D. Nucleation of body-centered-cubic tantalum films with a thin niobium underlayer. J. Vac. Sci. Technol. A: Vac.,Surf., Films 5, 3408–3411 (1987). \n33. Face, D., Prober, D., McGrath, W. & Richards, P. High quality tantalum superconducting tunnel junctions for microwave mixing in the quantum limit. Appl. Phys. Lett. 48, 1098–1100 (1986). \n34. Gladczuk, L., Patel, A., Paur, C. S. & Sosnowski, M. Tantalum films for protective coatings of steel. Thin Solid Films 467, 150–157 (2004). \n35. Reese, M. Superconducting Hot Electron Bolometers for Terahertz Sensing. PhD thesis. Yale (2006). \n36. Wallraff, A. et al. Approaching unit visibility for control of a superconducting qubit with dispersive readout. Phys. Rev. Lett. 95, 060501 (2005). \n37. Face, D. & Prober, D. Nucleation of body-centered-cubic tantalum films with a thin niobium underlayer. J. Vac. Sci. Technol. A: Vac.,Surf., Films 5, 3408–3411 (1987). \n38. Read, M. H. & Altman, C. A new structure in tantalum thin films. Appl. Phys. Lett. 7, 51–52 (1965). \n39. Bylander, J. et al. Noise spectroscopy through dynamical decoupling with a superconducting flux qubit. Nat. Phys. 7, 565–570 (2011). \n40. Huang, Z. et al. Engineering dynamical sweet spots to protect Qubits from 1/f noise. https://arxiv.org/abs/2004.12458 (2020). \n41. Kronberg, M. Plastic deformation of single crystals of sapphire: basal slip and twinning. Acta Metall. 5, 507–524 (1957). \n42. McGuire, G., Schweitzer, G. K. & Carlson, T. A. Core electron binding energies in some Group IIIA, VB, and VIB compounds. Inorg. Chem. 12, 2450–2453 (1973). \n43. Himpsel, F., Morar, J., McFeely, F., Pollak, R. & Hollinger, G. Core-level shifts and oxidation states of Ta and W: Electron spectroscopy for chemical analysis applied to surfaces. Phys. Rev. B 30, 7236 (1984). \n44. Kreikebaum, J. M., Dove, A., Livingston, W., Kim, E. & Siddiqi, I. Optimization of infrared and magnetic shielding of superconducting TiN and Al coplanar microwave resonators. Supercond. Sci. Technol. 29, 104002 (2016). \n45. Wang, Z. et al. Cavity attenuators for superconducting qubits. Phys. Rev. Appl. 11, 014031 (2019). \n46. Klimov, P. et al. Fluctuations of energy-relaxation times in superconducting qubits. Phys. Rev. Lett. 121, 090502 (2018). \n47. Kelly, J. et al. State preservation by repetitive error detection in a superconducting quantum circuit. Nature 519, 66–69 (2015). \n48. Serniak, K. et al. Direct dispersive monitoring of charge parity in offsetcharge-sensitive transmons. Phys. Rev. Appl. 12, 014052 (2019). \n49. Dial, O. et al. Bulk and surface loss in superconducting transmon qubits. Superconductor Sci. Technol. 29, 044001 (2016). \n50. Touzard, S. et al. Gated conditional displacement readout of superconducting qubits. Phys. Rev. Lett. 122, 080502 (2019). \n51. Sangtawesin, S. et al. Origins of diamond surface noise probed by correlating single-spin measurements with surface spectroscopy. Phys. Rev. X 9, 031052 (2019). \n52. Stick, D. et al. Ion trap in a semiconductor chip. Nat. Phys. 2, 36–39 (2006). \n53. Hite, D. et al. Surface science for improved ion traps. MRS Bull. 38, 826–833 (2013). \n54. Schenkel, T. et al. Electrical activation and electron spin coherence of ultra low dose antimony implants in silicon. Appl. Phys. Lett. 88, 112101 (2006). \n55. Paik, S.-Y., Lee, S.-Y., Baker, W., McCamey, D. & Boehme, C. T1 and T2 spin relaxation time limitations of phosphorous donor electrons near crystalline silicon to silicon dioxide interface defects. Phys. Rev. B 81, 075214 (2010). \n56. Yoneda, J. et al. A quantum-dot spin qubit with coherence limited by charge noise and fidelity higher than $99.9\\%$ . Nat. Nanotechnol. 13, 102–106 (2018). \n57. Potts, A., Parker, G., Baumberg, J. & de Groot, P. CMOS compatible fabrication methods for submicron Josephson junction qubits. IEE Proc.-Sci., Meas. Technol. 148, 225–228 (2001). \n58. Dwikusuma, F., Saulys, D. & Kuech, T. Study on sapphire surface preparation for III-nitride heteroepitaxial growth by chemical treatments. J. Electrochem. Soc. 149, G603–G608 (2002). \n59. Reed, M. D. et al. Fast reset and suppressing spontaneous emission of a superconducting qubit. Appl. Phys. Lett. 96, 203110 (2010). \n\n# Acknowledgements \n\nWe thank Paul Cole, Eric Mills, Roman Akhmechet, Bert Harrop, and Joe Palmer for useful discussions relating to fabrication. We also acknowledge help from Daniel Gregory, John Schrieber, and Austin Ferrenti regarding materials characterization. We thank Jeff Thompson for helpful discussions. Devices were fabricated in the Princeton Micro/ Nano Fabrication Laboratory and the Quantum Device Nanofabrication Laboratory. Microscopy and analysis were performed at the Princeton Imaging and Analysis Center. This work was supported by the Army Research Office (HIPS W911NF1910016), the National Science Foundation (MRSEC DMR-1420541 and RAISE DMR-1839199), and the Air Force Office of Scientific Research (FA9550-18-1-0334). A.P.M.P. and L.V.H.R. were supported by the National Defense Science and Engineering Graduate Fellowship. M.F. was supported by an appointment to the Intelligence Community Postdoctoral Research Fellowship Program at Princeton University by the Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between the U.S. Department of Energy and the Office of the Director of National Intelligence (ODNI). A.P. acknowledges support from the National Science Foundation Graduate Research Fellowship Program. B.J. acknowledges support from a postdoctoral fellowship through the Alexander-von-Humboldt foundation. \n\n# Author contributions \n\nA.A.H., N.P.d.L., and R.J.C. designed and oversaw all experiments. A.P.M.P., L.V.H.R., B.M.S., M.F., A.P., J.B., A.V., S.S., T.M., H.K.B., B.J., and A.G. contributed to process development and fabricated the devices. A.P.M.P., P.M., B.M.S., and Z.L. performed device measurements. Materials characterization was performed by L.V.H.R., M.F., G.C., and T.M. with supervision from N.Y., R.J.C, and N.P.d.L. X.H.L., Y.G., and A.P.M.P implemented simulations. \n\n# Competing interests \n\nA.P.M.P., L.V.H.R., B.M.S., M.F., S.S., R.J.C., N.P.d.L., and A.A.H. filed for a provisional patent (62/933,758) that relates to this work. The other authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-22030-5. \n\nCorrespondence and requests for materials should be addressed to A.A.H. \n\nPeer review information Nature Communications thanks John Martinis, Kater Murch and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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" + }, + { + "id": "10.1103_PhysRevMaterials.5.034801", + "DOI": "10.1103/PhysRevMaterials.5.034801", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevMaterials.5.034801", + "Relative Dir Path": "mds/10.1103_PhysRevMaterials.5.034801", + "Article Title": "Superconductivity in the Z2 kagome metal KV3Sb5", + "Authors": "Ortiz, BR; Sarte, PM; Kenney, EM; Graf, MJ; Teicher, SML; Seshadri, R; Wilson, SD", + "Source Title": "PHYSICAL REVIEW MATERIALS", + "Abstract": "Here we report the observation of bulk superconductivity in single crystals of the two-dimensional kagome metal KV3Sb5. Magnetic susceptibility, resistivity, and heat capacity measurements reveal superconductivity below T-c = 0.93 K, and density functional theory (DFT) calculations further characterize the normal state as a Z(2) topological metal. Our results demonstrate that the recent observation of superconductivity within the related kagome metal CsV3Sb5 is likely a common feature across the AV(3)Sb(5) (A: K, Rb, Cs) family of compounds and establishes them as a rich arena for studying the interplay between bulk superconductivity, topological surface states, and likely electronic density wave order in an exfoliable kagome lattice.", + "Times Cited, WoS Core": 380, + "Times Cited, All Databases": 412, + "Publication Year": 2021, + "Research Areas": "Materials Science", + "UT (Unique WOS ID)": "WOS:000627741900001", + "Markdown": "# Superconductivity in the $\\mathbb{Z}_{2}$ kagome metal $\\mathbf{KV}_{3}\\mathbf{S}\\mathbf{b}_{5}$ \n\nBrenden R. Ortiz\\* and Paul M. Sarte Materials Department and California Nanosystems Institute, University of California Santa Barbara, Santa Barbara, California 93106, USA \n\nEric M. Kenney $\\circledcirc$ and Michael J. Graf Physics Department, Boston College, Chestnut Hill, Massachusetts 02467, USA \n\nSamuel M. L. Teicher $\\circledcirc$ , Ram Seshadri, and Stephen D. Wilson † Materials Department, University of California Santa Barbara, Santa Barbara, California 93106, USA (Received 16 December 2020; accepted 26 January 2021; published 2 March 2021) \n\nHere we report the observation of bulk superconductivity in single crystals of the two-dimensional kagome metal $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ . Magnetic susceptibility, resistivity, and heat capacity measurements reveal superconductivity below $T_{c}=0.93\\mathrm{~K~}$ , and density functional theory (DFT) calculations further characterize the normal state as a $\\mathbb{Z}_{2}$ topological metal. Our results demonstrate that the recent observation of superconductivity within the related kagome metal $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ is likely a common feature across the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ (A: K, Rb, Cs) family of compounds and establishes them as a rich arena for studying the interplay between bulk superconductivity, topological surface states, and likely electronic density wave order in an exfoliable kagome lattice. \n\nDOI: 10.1103/PhysRevMaterials.5.034801 \n\n# I. INTRODUCTION \n\nThe kagome lattice broadly supports an array of electronic phenomena and ground states of interest that span multiple fields within condensed matter physics. At the localized limit, the geometric frustration inherent to magnetic kagome lattices is the impetus for much of the historical work on these materials. Insulating kagome lattices, for example, are of interest as potential hosts of a quantum spin liquid state [e.g., Herbertsmithite, $\\mathrm{ZnCu_{3}(O H)C l_{2}]}$ [1–5]. At the itinerant limit, kagome metals have also recently come into focus due to their potential to host novel correlated and topological electronic states. Even absent magnetic ordering, the kagome motif naturally gives rise to electronic structures with Dirac cones, flat bands, and the potential for topologically nontrivial surface states. Between these two extremes, kagome metals are predicted to support a wide array of instabilities, ranging from bond density wave order [6,7], charge fractionalization [8,9], spin liquid states [10], charge density waves [11], and superconductivity [6,12]. \n\nThe $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ (A: K, Rb, Cs) compounds are a new model family of quasi two-dimensional kagome metals that were recently discovered [13]. These materials crystallize as layered materials in the $P6$ /mmm space group, forming layers of ideal kagome nets of V ions coordinated by Sb. The layers are separated by alkali metal ions, forming a highly two-dimensional, exfoliable structure. Figure 1 shows the structure of ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ in top-down and isometric views. \n\nSince their discovery, $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ compounds have shown an array of interesting phenomena. Single crystals of ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ were reported to exhibit an unusually large, unconventional anomalous Hall effect [14]. Both $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ and $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ have also been investigated by angle-resolved photoemission spectroscopy (ARPES) and density-functional theory (DFT), demonstrating multiple Dirac points near the Fermi level [13–15]. The normal state of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ can be described as a nonmagnetic, $\\mathbb{Z}_{2}$ topological metal [15], and topologically-protected surface states have been identified close to the Fermi level. \n\nOne widely sought electronic instability on a twodimensional kagome lattice is the formation of superconductivity. Layered kagome metals that superconduct are rare, and the interplay between the nontrivial band topology and the formation of a superconducting ground state makes this a particularly appealing space for realizing unconventional quasiparticles. In the localized electron limit, superconductivity competes with a variety of other electronic instabilities at different fillings [16,17]. In the itinerant limit, unconventional superconductivity is also predicted to emerge via nesting-driven interactions [18]. This mechanism, analogous to theories for doped graphene (which shares the hexagonal symmetry of the kagome lattice) [19,20], relies upon scattering between saddle points of a band at the M points of the two-dimensional Brillouin zone. \n\n$\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ was recently proposed as the first material potentially hosting a nesting-driven superconducting state, following the observation of bulk superconductivity below $T_{c}=2.5\\:\\mathrm{K}$ in both single crystals and powders [15]. However, the presence of superconductivity in the remaining compounds in the ${A V_{3}S b_{5}}$ class of materials, which share nearly identical electronic structures, remains an open question. Although superconductivity was not initially observed in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ or $\\mathrm{Rb}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ above $1.8\\mathrm{~K~}$ , the impact of sample quality (particularly with regards to A-site occupancy) and of insufficiently low temperature measurements remain unaddressed. \n\nIn this work, we report the discovery of bulk superconductivity in single crystals of ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ below $T_{c}=0.93\\mathrm{~K~}$ . We characterize the superconducting state using a combination of low temperature susceptibility, heat capacity, and electrical resistivity measurements on stoichiometric samples where K vacancies have been minimized. Consistent with prior work on $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ [15], we also present density-functional theory (DFT) results showing that the normal state of ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ is also characterized as a $\\mathbb{Z}_{2}$ topological metal. Our data demonstrate that $\\mathbb{Z}_{2}$ topology and superconducting ground states are common properties of the new class of $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ kagome metals. \n\n# II. METHODS \n\n# A. Synthesis \n\nSingle crystals of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ were synthesized from K (solid, Alfa $99.95\\%$ , $\\mathrm{\\DeltaV}$ (powder, Sigma $99.9\\%$ ), and Sb (shot, Alfa $99.999\\%$ ). As-received vanadium powder was purified using EtOH and concentrated HCl to remove residual oxides. Powder preparation was performed within an argon glove box with oxygen and moisture levels ${<}0.5\\ \\mathrm{ppm}$ . Single crystals of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ were then synthesized using a self-flux method using an eutectic mixture of $\\ensuremath{\\mathrm{KS}}\\ensuremath{\\mathbf{b}}_{2}$ and KSb [21], mixed with $\\mathrm{VSb}_{2}$ . Elemental reagents were initially milled in a sealed, pre-seasoned tungsten carbide vial to form the precursor composition, which is approximately $50~\\mathrm{at.}\\%~\\mathrm{K_{\\itx}S b_{\\it y}}$ eutectic and approximately $50\\mathrm{at.}\\%\\mathrm{VSb}_{2}$ . The precursor powder was subsequently loaded into alumina crucibles and sealed within stainless steel jackets. The samples were heated to $1000^{\\circ}\\mathrm{C}$ at $250^{\\circ}\\mathrm{C/hr}$ and soaked there for $24\\mathrm{~h~}$ . The mixture was subsequently cooled to $900^{\\circ}\\mathrm{C}$ at $100^{\\circ}\\mathrm{C/hr}$ and then further to $400^{\\circ}\\mathrm{C}$ at $2^{\\circ}\\mathrm{C/hr}$ . Once cooled, the flux boule is crushed, and crystals were extracted mechanically. \n\nReaction in nonpermeable steel tubes, mechanical extraction, and elimination of aqueous solvents during crystal extraction appear essential to recovering fully occupation of the potassium site. This differentiates the crystals reported here from earlier reports on K-deficient crystals [13]. Crystals are hexagonal flakes with brilliant metallic luster. Samples are routinely $1{-}3~\\mathrm{mm}$ in side length and $0.1\\mathrm{-}0.5~\\mathrm{mm}$ thick. Crystals are naturally exfoliable and readily cleave along the $\\scriptstyle a-b$ plane, consistent with the layered structure. Elemental composition of the crystals was assessed using energy dispersive $\\mathbf{\\boldsymbol{x}}$ -ray spectroscopy (EDX) using a APREO C scanning electron microscope. \n\n# B. Susceptibility, electrical transport, and heat capacity measurements \n\nMagnetometry data between $300\\mathrm{K}$ and $2\\mathrm{K}$ were collected using a Quantum Design Squid Magnetometer (MPMS3) in vibrating-sample measurement mode (VSM). Samples were mounted on a quartz paddle using GE varnish with crystals aligned with the $c$ axis perpendicular to the field. Alternating current (AC) magnetic susceptibility measurements between $3.5\\mathrm{K}$ and $300\\mathrm{mK}$ were performed in a $^3\\mathrm{He}$ refrigerator using a custom susceptometer consisting of a pair of astatically wound pickup coils inside a drive coil. Samples were mounted on a sapphire rod with silver paint and thermally anchored to the refrigerator via a gold wire. For the AC measurements, the $\\scriptstyle{c}$ axis was aligned parallel to the field, and data were collected at a frequency of $711.4~\\mathrm{Hz}$ . The susceptometer response was calibrated against standard samples measured in a Quantum Design AC susceptometer. Due to the orientation of the crystals, a correction for demagnetization was applied in the quantitative analysis of the superconducting volume fraction. The crystals (hexagonal platelets) were approximated as cylindrical volumes, though calibrations were also performed using similarly sized samples of Ta to accurately correct for any systematic offsets in the data. \n\nHeat capacity and electrical resistivity measurements were performed using a Quantum Design $14\\mathrm{T}$ Dynacool physical property measurement system (PPMS) with a $^{3}\\mathrm{He}/{^{4}\\mathrm{He}}$ dilution refrigerator insert option. Apezion $\\mathbf{N}$ grease was used to ensure thermal and mechanical contact with heat capacity stage. Crystals were mounted such that the $c$ axis was parallel to the applied magnetic field. Electrical contacts were made in a standard four-point geometry using gold wire and silver paint. Thermal contact and electrical isolation was ensured using layers of GE varnish and cigarette paper. Samples were again mounted such that the $c$ axis was parallel to the field (flat plates mounted flush on resistivity stage). This method for making contact to the crystals generates a relatively high contact resistance and amplified noise due to the low intrinsic resistivity of the sample. To compensate, a large alternating current of $1.25\\mathrm{mA}$ and $12.2\\mathrm{Hz}$ was driven in the ab plane. \n\n# C. Band structure calculations \n\nStructure visualization was performed with the VESTA software package [22], and the electronic structure was calculated in VASP $\\phantom{+}v5.4.4$ [23–25] using projector-augmented wave (PAW) potentials [26,27]. In order to address potential orbital localization (particularly $\\textsf{V}d_{\\cdot}^{\\cdot}$ and the van der Waals forces that play a role in $c$ -layer stacking in this compound, we performed simulations using the SCAN functional [28] and D2/D3 [29,30] dispersion corrections as well as the more standard PBE functional [31]. Calculations described in the text employed PBE with D3 corrections as this functional choice and gave relaxed lattice parameters with excellent matching to the room temperature experimental values for $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ (see Supplemental Material Fig. 1). Irrep assignments (see Supplemental Material Fig. 2) for the $\\mathbb{Z}_{2}$ topological invariant calculation were performed using the IRVSP program in conjunction with VASP [32,33]. \n\n# III. EXPERIMENTAL RESULTS \n\n# A. Structure and composition \n\nThe $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ family of kagome metals are layered, exfoliable materials consisting of $\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ slabs intercalated by alkali metal cations. As shown in Fig. 1(a), the kagome network of vanadium is immediately obvious, as is the layered nature of the crystal structure (all bonds ${<}3\\mathrm{\\AA}$ are shown in isometric perspective). For a conceptual interpretation of the $\\mathrm{\\DeltaV_{3}S b_{5}}$ network, we can decompose the structure further into the individual sublattices. Figure 1(b) shows the $\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ slab decomposed into the sublattices formed by the V1, Sb1, and Sb2 atomic sites. The V1 sublattice forms the kagome lattice and is interpenetrated with the Sb1 sublattice. The Sb2 sublattice encapsulates the kagome layer with a graphitelike (antimonene) layer of antimony. The alkali metals fill the natural space left between the antimonene layers. We note that the V-V bond distances are short, $2.74\\mathrm{\\AA}$ , in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ . \n\n![](images/f8c574fdcf119b756c0e54bb8510cfb77fea6c82ceb494c3af9ee97f30acd34f.jpg) \nFIG. 1. Crystal structure of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , the prototype structure for the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ family of kagome metals. (a) The kagome lattice of vanadium is immediately apparent from the top-down view of the structure. Bond lengths ${<}3\\bar{\\mathrm{~\\AA~}}$ are drawn in the isometric perspective to highlight the layered nature of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ . (b) Intuitive decomposition of the structure highlights the kagome lattice and graphitelike (antimonene) layers. \n\nWhile ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ is nearly identical to $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ in structure, the alkali K layer is more easily deintercalated from the lattice and the material has a tendency to form a variety of substoichiometric compositions. In our prior report, as-grown crystals were slightly deintercalated (approximately $\\mathrm{K_{0.9}V_{3}S b_{5}})$ [13]. We ascribe the potassium loss to the flux removal process in that report. To highlight the ease with which potassium is lost, we explored a variety of post-growth treatments (e.g., hydrothermal, mineral acid etches, vapor transport). We estimate that the as-grown crystals can be processed to remove approximately $25\\mathrm{-}30\\%$ of the potassium. For instance, crystals with compositions of $\\mathrm{K}_{0.7}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ have been formed by sealing as-grown crystals with small quantities of $\\mathrm{PtCl}_{2}$ and allowing the halogen to react with the potassium at elevated temperatures. A “reverse hydrothermal” method was also explored, by sealing crystals in glass tubes with purified water and heating to $150^{\\circ}\\mathrm{C}$ . This method also reduces the potassium content to $\\mathrm{K}_{0.7}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ . Beyond this limit, however, the material begins to decompose into $\\mathrm{VSb}_{2}$ Even within the allowable range of deintercalation, crystals of $\\mathrm{K}_{1-x}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ become progressively more brittle as potassium removal progresses. \n\nWhile the tunability of the potassium site is an interesting degree of freedom when studying transport in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , the focus in this paper is on stoichiometric crystals with fully occupied K1 sites. The discovery of superconductivity in stoichiometric crystals of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ highlights the need to control the alkali-metal occupancy. Stoichiometric crystals $(\\sim11.1$ at. $\\%$ K as measured by energy dispersive spectroscopy) were produced following the new methods outlined above with the main consideration being avoiding all contact with water. Mild solvents like isopropyl alcohol do not seem to affect the potassium content of the crystals. \n\n# B. Normal state transport, susceptibility, and heat capacity results \n\nFigure 2 presents a suite of magnetization, electrical resistivity, and heat capacity measurements of single crystals of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ . Panels (a)–(c) present data characterizing the normal state of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ above $2\\mathrm{~K~}$ . In all three measurements, data reveal an anomaly at $T^{*}=78\\mathrm{~K~}$ , consistent with prior work [13]. This $T^{*}$ feature is shared across the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ family, though the onset temperature varies: $78\\mathrm{-}80\\mathrm{~K~}$ in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , $93\\mathrm{K}$ in $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ , $110\\mathrm{K}$ in $\\mathrm{Rb}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ . \n\nSpecifically, normal state magnetization data [Fig. 2(a)] indicate temperature-independent Pauli paramagnetism above $T^{*}$ . Below $T^{*}$ , there is an abrupt steplike decrease in susceptibility, suggestive of a partial gapping of the Fermi surface. The same $T^{*}$ transition also appears as a weak inflection in resistivity data presented in Fig. 2(b) and as a weak $\\lambda$ -like anomaly in heat capacity data in Fig. 2(c). The influence of the anomaly in both heat capacity and resistivity is weaker than in previous single crystal studies of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ [15], and this distinction is also present in prior measurements on powders [13,15]. \n\nRecent studies of $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ further observed the onset of weak structural superlattice peaks below $T^{*}$ , suggesting that a structural transition onsets as a secondary response to a primary electronic order parameter [15]. This mechanism and the presence of a charge density wavelike instability is the likely source of the $T^{*}$ anomaly throughout the $\\mathrm{AV}_{3}\\mathrm{Sb}_{5}$ family of materials. Recently, scanning tunneling microscopy (STM) has confirmed the presence of the charge density wave in ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ [34]. \n\n# C. Low-temperature transport, susceptibility, and heat capacity measurements \n\nPanels (d)–(f) in the bottom row of Fig. 2 present data characterizing $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ single crystals below $2\\mathrm{~K~}$ . All probes reveal that $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ crystals are bulk superconductors with $T_{c}\\approx0.93\\mathrm{\\K}$ . Figure 2(d) presents the real and imaginary components of the AC magnetic susceptibility, showing bulk superconductivity with a well-defined Meissner state and a superconducting volume fraction of $4\\pi\\chi_{v}\\approx-1.1$ . We estimate the error in $\\chi_{v}$ is on the order of $10{-}15\\%$ due to the approximations used when correcting for the sample’s demagnetization. The imaginary component $\\chi^{\\prime\\prime}$ is shown in arbitrary units to highlight the onset of the transition. \n\n![](images/e6de8e91ab639904f26942db8ca9d7e276fcefb01d5f2322f0cdb7c3523ad22c.jpg) \nFIG. 2. (a)–(c) Susceptibility, electrical resistivity, and heat capacity showing behavior of stoichiometric single crystals above $2\\mathrm{~K~}$ . All measurements show an anomaly at $^{78\\mathrm{~K~}}$ , coinciding with emergence of a charge density wave. Magnetization results indicate that $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ is a Pauli paramagnet at high temperatures. As shown previously, the weak Curie tail at low temperature can be fit with a small concentration of impurity spins. Resistivity is low, indicating a high mobility metal. The $\\lambda$ -like anomaly in the heat capacity is shown, magnified, with a spline interpolation used to isolate the transition. (d)–(f) Susceptibility, electrical resistivity, and heat capacity measurements below $2\\mathrm{~K~}$ highlight the onset of bulk superconductivity in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ . A well-defined Meissner state is observed in susceptibility, which coincides with the zero-resistivity state and a sharp heat-capacity anomaly. \n\nFigure 2(e) presents low-temperature resistivity measurements similarly exhibiting a sharp superconducting phase transition into a zero-resistivity state. The superconducting state is quenched quickly by the application of a $c$ -axis aligned magnetic field, and the zero-resistivity condition is suppressed by $\\mu_{0}H=300$ Oe. Crystals of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ have inherently low resistivity in the normal state ${\\mathrm{\\Omega}}^{\\prime}{\\approx}0.3\\ {\\mu}\\Omega$ -cm at $2\\mathrm{~K~},$ ), comparable to measurements of stoichiometric $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ [15]. To ensure good noise-to-signal ratio, a relatively large $({\\sim}1\\ \\mathrm{mA})$ AC current was used. \n\nLow-temperature heat capacity measurements shown in Fig. 2(f) also indicate a well-defined entropy anomaly at $T_{c}$ . Combined with the magnetization and resistivity measurements, stoichiometric ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ can be unambiguously classified as a bulk superconductor. We note that heat capacity measurements also indicate the presence of a nuclear Schottky anomaly at the lowest temperatures measured. The anomaly matches known contributions from $^{51}\\mathrm{V}$ nuclei observed in other vanadium-containing compounds [35]. \n\nThe normal state heat capacity data $(T>T_{c.}$ ) fits to the form $C_{p}=\\gamma_{n}T+A T^{3}$ [33], allowing $\\gamma_{n}=$ \n\n$22.8~\\mathrm{mJ}\\mathrm{mol}^{-1}~\\mathrm{K}^{-2}$ to be determined. From $A$ , we estimate that the Debye temperature for $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ is approximately $\\theta_{D}=141\\mathrm{K}$ . Both values are consistent with prior high temperature $C_{p}$ data published on powders [13]. Removing the lattice contribution to the heat capacity allows us to examine the electronic specific heat $(\\boldsymbol{C}_{e s}^{\\top}=\\dot{\\boldsymbol{C}}_{p,0T}-\\boldsymbol{A}\\boldsymbol{T}^{3})$ in detail. Further, we can isolate the superconducting transition $(\\Delta C_{e s}=C_{p,0T}-C_{p,3T})$ by removing the normal state specific heat collected under a $3\\mathrm{T}$ field. \n\nFigure 3(a) shows the heat capacity associated with the onset of superconductivity as $\\Delta C_{e s}/T$ . The lattice component was verified from the normal state data collected under a $3\\mathrm{~T~}$ field. The red curve is a fit to the empirical, exponential approximation of the BCS formalism, using the form $C_{e s}/T\\approx$ $\\dot{a}e^{\\dot{b}/T}$ or $\\Delta C_{e s}/T\\approx a e^{b/T}-\\gamma_{n}$ . This curve is used to help determine $\\Delta C_{e s}/\\gamma_{n}T_{c}$ and $T_{c}=0.93\\mathrm{~K~}$ , where the dimensionless specific jump at $T_{c}$ is estimated to be $\\Delta C_{e s}/\\gamma_{n}T_{c}=1.03$ and the crossover point in $\\Delta C_{e s}$ occurs at $0.44T_{c}$ . Both values are quite small relative to the BCS weak coupling limit $\\Delta C_{e s}/\\gamma_{n}T_{c}\\approx1.43$ and $0.6T_{c}$ , respectively. \n\nFrom Fig. 3, the data below $T_{c}$ vanishes exponentially with temperature. Figure 3(b) shows the experimental data below $T_{c}$ , modeled with $C_{e s}/\\gamma_{n}T_{c}=a e^{-b(T_{c}/\\hat{T})}$ . Again, the fit value of $b=0.56$ is substantially smaller than the expectations of BCS theory $(b_{\\mathrm{BCS}}=1.44)$ ) suggesting a deviation from the traditional weak-coupling theory with an isotropic gap. Unfortunately, interference from the Schottky anomaly at low temperature precludes a more exhaustive examination of the superconducting gap and the field dependence of $\\gamma_{n}$ from the present $C_{p}$ data. \n\n![](images/f32355bbbcb5525f21bdfac34cbdfc6805af866e44ac9d073fff68b8defe001f.jpg) \nFIG. 3. (a) The specific heat capacity difference $\\Delta C_{e s}$ between the superconducting and normal states $(\\Delta C_{e s}=C_{p,0T}-C_{p,3T})$ shows a sharp transition at $T_{c}=0.93\\:\\mathrm{K}$ . Here, $\\gamma_{n}=22.8~\\mathrm{mJ}\\mathrm{mol}^{-1}\\mathrm{K}^{-1}$ and $\\theta_{D}=141~\\mathrm{K}$ have been modeled from the $3\\mathrm{~T~}$ data set. (b) The electronic heat capacity $C_{e s}=C_{p,0T}-A T^{3}$ below the transition (and above the Schottky anomaly) vanishes exponentially with temperature. Red lines show the exponential fits to the data as described in the text. \n\n# D. $\\mathbb{Z}_{2}$ evaluation \n\nIn this section, we determine whether $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ shares the same topological classification as its isostructural variant $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ . Unlike many of the more heavily studied kagome lattices (e.g., $\\mathrm{Fe}_{3}\\mathrm{Sn}_{2}$ [36,37], $\\mathbf{Mn}_{3}\\mathbf{Ge}$ [38,39], $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ [40–42], etc.), $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ compounds possess both time-reversal and inversion symmetry. The $\\mathbb{Z}_{2}$ topological invariant between each pair of bands near the Fermi level can be calculated by simply analyzing the parity of the wave function at the TRIM (time-reversal invariant momentum) points [43]. \n\n![](images/5680696d3c9cd9525b3c1447f88ea8056e00b69e80d6d0419052ca801a9f84af.jpg) \nFIG. 4. DFT electronic band structure for $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ near the Fermi level. The continuous gap (shaded) is noted, with band indices and parity products given. Note that surface states at the $\\overline{{M}}$ are expected to be topologically protected, in analogy to $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ . \n\nFigure 4 shows the calculated electronic structure of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ . The symmetry-enforced direct gap between the bands near $E_{F}$ has been highlighted. As with $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ , topologically nontrivial surface state crossings at the $\\overline{{M}}$ TRIM point (between bands 71 and 73) are expected. The combination of topologically nontrivial surface states near $E_{F}$ , combined with the continuous direct gap, allow us to classify ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ as a $\\mathbb{Z}_{2}$ topological metal. \n\n# IV. DISCUSSION \n\nThe observation of superconductivity in both $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ and $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ suggests that the known members of the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ (A: K, Rb, Cs) kagome metals may all be $\\mathbb{Z}_{2}$ topological metals with superconducting ground states. All compounds also exhibit very similar $T^{*}$ anomalies, which are suggestive of appreciable electronic interactions driving an accompanying charge or bond density wave order. Based on our observations in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , the emergence of superconductivity may depend strongly on the alkali-metal site occupancy. \n\nLong-range magnetic ordering is not observed in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ from previous neutron diffraction measurements [13], and more recent muon spin resonance $(\\mu\\mathbf{S}\\mathbf{R})$ measurements performed on near-stoichiometric polycrystalline powders of ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ observe no signature of localized, electronic magnetic moments [44]. Nevertheless, recent reports have shown unconventional transport phenomena in substoichiometric $\\mathrm{K}_{1-x}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ crystals attributed to the presence of local, disordered magnetic moments [14,45]. Direct experimental detection of the proposed magnetic defects in $\\mathrm{K}_{1-x}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ , however, remains an open challenge. \n\nHeat capacity measurements suggest a superconducting state that deviates from the BCS expectations of singleband, weak coupling $s$ -wave superconductivity. The small $\\Delta C_{e s}/\\gamma_{n}T_{c}=1.03$ value potentially indicates a nonuniform gap structure in momentum space or alternatively the possibility of a multiband gap structure [46]. Single band $d$ -wave superconductivity nominally has a value of $\\Delta C_{e s}/\\gamma_{n}T_{c}=0.95$ , which is not far from the observed value. The low temperature Schottcky anomaly, however, currently precludes canonical measurements of the field dependence of $\\gamma_{n}$ to assess the presence of nodes within the gap structure. Future measurements via low-temperature scanning tunneling microscopy or angle-resolved photoemission measurements exploring this possibility are highly desired. \n\nIn comparison to prior results on $\\mathrm{K}_{0.92}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ and $\\mathrm{K}_{0.85}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ crystals [13], the electrical resistivity collected from stoichiometric ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ [Fig. 2(a)] shows marked changes. Stoichiometric samples exhibit significantly reduced resistivity values, with the residual resistivity at $2\\mathrm{~K~}(\\rho_{0})$ dropping nearly two orders of magnitude from ${\\bf K}_{0.85}$ $\\approx$ $300\\:\\mu\\Omega\\mathrm{-cm)}$ , ${\\bf K}_{0.92}$ $\\approx10~\\mu\\Omega\\mathrm{-cm})$ , and ${\\sf K}_{1.0}$ ${\\approx}1~\\mu\\Omega{\\mathrm{-cm}},$ . At the stoichiometric limit, $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ is an astonishingly good metal, considering the relatively complex crystal structure. \n\nThe strong influence of stoichiometry and disorder on the normal state electrical transport of ${\\bf K V}_{3}{\\bf S}{\\bf b}_{5}$ is also reflected in the stability of its superconducting state. The lack of superconductivity in powders of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ reported previously [13] is most reasonably attributed to the offstoichiometry of potassium. Concurrent studies on potassium deficient $\\mathrm{K_{0.7}V_{3}S b_{5}}$ crystals have shown they are not natively superconducting, although the possibility for proximitized superconductivity remains [45]. Investigating the underlying connection between potassium occupancy and superconductivity in $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ as well as the connection between $T^{*}$ and $T_{c}$ across the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ family are interesting avenues for future study. \n\n[1] D. E. Freedman, T. H. Han, A. Prodi, P. Müller, Q.-Z. Huang, Y.-S. Chen, S. M. Webb, Y. S. Lee, T. M. McQueen, and D. G. Nocera, Site specific $\\mathbf{x}$ -ray anomalous dispersion of the geometrically frustrated kagome magnet, herbertsmithite, $\\mathrm{ZnCu_{3}(O H)_{6}C l_{2}}$ , J. Am. Chem. Soc. 132, 16185 (2010). \n[2] D. Wulferding, P. Lemmens, P. Scheib, J. Röder, P. Mendels, S. Chu, T. Han, and Y. S. Lee, Interplay of thermal and quantum spin fluctuations in the kagome lattice compound herbertsmithite, Phys. Rev. B 82, 144412 (2010). \n[3] T. Han, S. Chu, and Y. S. Lee, Refining the Spin Hamiltonian in the Spin-1 2 Kagome Lattice Antiferromagnet $\\mathrm{ZnCu_{3}(O H)_{6}C l_{2}}$ using Single Crystals, Phys. Rev. Lett. 108, 157202 (2012). \n[4] M. Fu, T. Imai, T.-H. Han, and Y. S. Lee, Evidence for a gapped spin-liquid ground state in a kagome Heisenberg antiferromagnet, Science 350, 655 (2015). \n[5] T.-H. Han, J. S. Helton, S. Chu, D. G. Nocera, J. A. RodriguezRivera, C. Broholm, and Y. S. Lee, Fractionalized excitations in the spin-liquid state of a kagome-lattice antiferromagnet, Nature (London) 492, 406 (2012). \n[6] W.-S. Wang, Z.-Z. Li, Y.-Y. Xiang, and Q.-H. Wang, Competing electronic orders on kagome lattices at van Hove filling, Phys. Rev. B 87, 115135 (2013). \n[7] S. V. Isakov, S. Wessel, R. G. Melko, K. Sengupta, and Y. B. Kim, Hard-Core Bosons on the Kagome Lattice: Valence-Bond Solids and their Quantum Melting, Phys. Rev. Lett. 97, 147202 (2006). \n\n# V. CONCLUSION \n\nOur results have demonstrated the synthesis of high-purity, stoichiometric single crystals of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ . Stoichiometric crystals exhibit bulk superconductivity with $T_{c}=0.93\\mathrm{~K~}$ and have a substantially reduced normal state residual resistivity. Similar to $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ , DFT results demonstrate that $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ can be classified as a $\\mathbb{Z}_{2}$ topological metal with a number of nontrivial surface crossings near the Fermi level. Our results suggest that superconductivity is common across the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ family of quasi two-dimensional kagome metals. They further motivate the continued exploration of $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ as materials supporting a rich interplay between superconductivity, nontrivial band topology, and potential correlation physics. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the National Science Foundation (NSF) through Enabling Quantum Leap: Convergent Accelerated Discovery Foundries for Quantum Materials Science, Engineering and Information (Q-AMASE-i): Quantum Foundry at UC Santa Barbara (DMR-1906325). The research made use of the shared facilities of the NSF Materials Research Science and Engineering Center at UC Santa Barbara (DMR- 1720256). The UC Santa Barbara MRSEC is a member of the Materials Research Facilities Network [47]. B.R.O. and P.M.S. also acknowledge support from the California NanoSystems Institute through the Elings Fellowship program. S.M.L.T has been supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1650114. \n\n[8] A. O’Brien, F. Pollmann, and P. Fulde, Strongly correlated fermions on a kagome lattice, Phys. Rev. B 81, 235115 (2010). \n[9] A. Rüegg and G. A. Fiete, Fractionally charged topological point defects on the kagome lattice, Phys. Rev. B 83, 165118 (2011). \n[10] S. Yan, D. A. Huse, and S. R. White, Spin-liquid ground state of the $\\mathrm{s}{=}1/2$ kagome Heisenberg antiferromagnet, Science 332, 1173 (2011). \n[11] H.-M. Guo and M. Franz, Topological insulator on the kagome lattice, Phys. Rev. B 80, 113102 (2009). \n[12] W.-H. Ko, P. A. Lee, and X.-G. Wen, Doped kagome system as exotic superconductor, Phys. Rev. B 79, 214502 (2009). \n[13] B. R. Ortiz, L. C. Gomes, J. R. Morey, M. Winiarski, M. Bordelon, J. S. Mangum, I. W. H. Oswald, J. A. RodriguezRivera, J. R. Neilson, S. D. Wilson, E. Ertekin, T. M. McQueen, and E. S. Toberer, New kagome prototype materials: Discovery of $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , $\\mathrm{RbV}_{3}\\mathrm{Sb}_{5}$ , and $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ , Phys. Rev. Materials 3, 094407 (2019). \n[14] S.-Y. Yang, Y. Wang, B. R. Ortiz, D. Liu, J. Gayles, E. Derunova, R. Gonzalez-Hernandez, L. Smejkal, Y. Chen, S. S. Parkin et al., Giant, unconventional anomalous Hall effect in the metallic frustrated magnet candidate, $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , Sci. Adv. 6, eabb6003 (2020). \n[15] B. R. Ortiz, S. M. L. Teicher, Y. Hu, J. L. Zuo, P. M. Sarte, E. C. Schueller, A. M. M. Abeykoon, M. J. Krogstad, S. Rosenkranz, R. Osborn, R. Seshadri, L. Balents, J. He, and S. D. Wilson, $\\mathrm{Cs}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ : A $\\mathbb{Z}_{2}$ Topological Kagome Metal with A Superconducting Ground State, Phys. Rev. Lett. 125, 247002 (2020). \n[16] M. L. Kiesel, C. Platt, and R. Thomale, Unconventional Fermi Surface Instabilities in the Kagome Hubbard Model, Phys. Rev. Lett. 110, 126405 (2013). \n[17] J. Wen, A. Rüegg, C.-C. J. Wang, and G. A. Fiete, Interaction-driven topological insulators on the kagome and the decorated honeycomb lattices, Phys. Rev. B 82, 075125 (2010). \n[18] S.-L. Yu and J.-X. Li, Chiral superconducting phase and chiral spin-density-wave phase in a Hubbard model on the kagome lattice, Phys. Rev. B 85, 144402 (2012). \n[19] R. Nandkishore and A. V. Chubukov, Interplay of superconductivity and spin-density-wave order in doped graphene, Phys. Rev. B 86, 115426 (2012). \n[20] R. Nandkishore, L. Levitov, and A. Chubukov, Chiral superconductivity from repulsive interactions in doped graphene, Nat. Phys. 8, 158 (2012). \n[21] J. Sangster and A. Pelton, The K-Sb (potassium-antimony) system, J. Phase Equilib. 14, 510 (1993). \n[22] K. Momma and F. Izumi, VESTA3 for three-dimensional visualization of crystal, volumetric and morphology data, J. Appl. Crystallogr. 44, 1272 (2011). \n[23] G. Kresse and J. Hafner, Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium, Phys. Rev. B 49, 14251 (1994). \n[24] G. Kresse and J. Furthmüller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set, Phys. Rev. B 54, 11169 (1996). \n[25] G. Kresse and J. Furthmüller, Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set, Comput. Mater. Sci. 6, 15 (1996). \n[26] P. E. Blöchl, Projector augmented-wave method, Phys. Rev. B 50, 17953 (1994). \n[27] G. Kresse and D. Joubert, From ultrasoft pseudopotentials to the projector augmented-wave method, Phys. Rev. B 59, 1758 (1999). \n[28] J. Sun, A. Ruzsinszky, and J. P. Perdew, Strongly Constrained and Appropriately Normed Semilocal Density Functional, Phys. Rev. Lett. 115, 036402 (2015). \n[29] S. Grimme, Semiempirical GGA-type density functional constructed with a long-range dispersion correction, J. Comput. Chem. 27, 1787 (2006). \n[30] S. Grimme, S. Ehrlich, and L. Goerigk, Effect of the damping function in dispersion corrected density functional theory, J. Comput. Chem. 32, 1456 (2011). \n[31] J. P. Perdew, K. Burke, and M. Ernzerhof, Generalized Gradient Approximation Made Simple, Phys. Rev. Lett. 77, 3865 (1996). \n[32] J. Gao, Q. Wu, C. Persson, and Z. Wang, Irvsp: To obtain irreducible representations of electronic states in the vasp, Comput. Phys. Comm. 261, 107760 (2021). \n[33] See Supplemental Material at http://link.aps.org/supplemental/ 10.1103/PhysRevMaterials.5.034801 for further details. \n[34] Yu-Xiao Jiang, Jia-Xin Yin, M. Michael Denner, Nana Shumiya, Brenden R. Ortiz, Junyi He, Xiaoxiong Liu, Songtian S. Zhang, Guoqing Chang, Ilya Belopolski et al., Discovery of topological charge order in kagome superconductor $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ , arXiv:2012.15709. \n[35] K. Andres, Observation of nuclear specific heat in $\\mathrm{\\bfV}_{2}\\mathrm{\\bfO}_{3}$ , Phys. Rev. B 2, 3768 (1969). \n[36] L. Ye, M. Kang, J. Liu, F. Von Cube, C. R. Wicker, T. Suzuki, C. Jozwiak, A. Bostwick, E. Rotenberg, D. C. Bell et al., Massive Dirac fermions in a ferromagnetic kagome metal, Nature (London) 555, 638 (2018). \n[37] Q. Wang, Q. Yin, and H. Lei, Giant topological Hall effect of ferromagnetic kagome metal $\\mathrm{Fe}_{3}\\mathrm{Sn}_{2}$ , Chin. Phys. B 29, 017101 (2020). \n[38] A. K. Nayak, J. E. Fischer, Y. Sun, B. Yan, J. Karel, A. C. Komarek, C. Shekhar, N. Kumar, W. Schnelle, J. Kübler et al., Large anomalous Hall effect driven by a nonvanishing Berry curvature in the noncolinear antiferromagnet $\\mathrm{{Mn}}_{3}\\mathrm{{Ge}}$ , Sci. Adv. 2, e1501870 (2016). \n[39] N. Kiyohara, T. Tomita, and S. Nakatsuji, Giant Anomalous Hall Effect in the Chiral Antiferromagnet $\\mathbf{M}\\mathbf{n}_{3}\\mathbf{Ge}$ , Phys. Rev. Appl. 5, 064009 (2016). \n[40] P. Vaqueiro and G. G. Sobany, A powder neutron diffraction study of the metallic ferromagnet $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ , Solid State Sci. 11, 513 (2009). \n[41] G. Xu, B. Lian, P. Tang, X.-L. Qi, and S.-C. Zhang, Topological Superconductivity on the Surface of Fe-based Superconductors, Phys. Rev. Lett. 117, 047001 (2016). \n[42] N. Morali, R. Batabyal, P. K. Nag, E. Liu, Q. Xu, Y. Sun, B. Yan, C. Felser, N. Avraham, and H. Beidenkopf, Fermi-arc diversity on surface terminations of the magnetic Weyl semimetal $\\mathrm{Co}_{3}\\mathrm{Sn}_{2}\\mathrm{S}_{2}$ , Science 365, 1286 (2019). \n[43] L. Fu and C. L. Kane, Topological insulators with inversion symmetry, Phys. Rev. B 76, 045302 (2007). \n[44] E. M. Kenney, B. R. Ortiz, C. Wang, S. D. Wilson, and M. J. Graf, Absence of local moments in the kagome metal $\\mathrm{KV}_{3}\\mathrm{Sb}_{5}$ as determined my muon spin spectroscopy, arXiv:2012.04737. \n[45] Y. Wang, S. Yang, P. K. Sivakumar, B. R. Ortiz, S. M. Teicher, H. Wu, A. K. Sirvastava, C. Garg, D. Liu, S. S. Parkin, E. Toberer, T. McQueen, S. D. Wilson, and M. N. Ali, Proximityinduced spin-triplet superconductivity and edge supercurrent in the topological Kagome metal, $\\mathrm{K}_{1-x}\\mathrm{V}_{3}\\mathrm{Sb}_{5}$ , arXiv:2012.05898. \n[46] D. C. Johnston, Elaboration of the $\\alpha$ -model derived from the bcs theory of superconductivity, Supercond. Sci. Technol. 26, 115011 (2013). \n[47] www.mrfn.org. " + }, + { + "id": "10.1002_advs.202100309", + "DOI": "10.1002/advs.202100309", + "DOI Link": "http://dx.doi.org/10.1002/advs.202100309", + "Relative Dir Path": "mds/10.1002_advs.202100309", + "Article Title": "An Artificial Polyacrylonitrile Coating Layer Confining Zinc Dendrite Growth for Highly Reversible Aqueous Zinc-Based Batteries", + "Authors": "Chen, P; Yuan, XH; Xia, YB; Zhang, Y; Fu, LJ; Liu, LL; Yu, NF; Huang, QH; Wang, B; Hu, XW; Wu, YP; van Ree, T", + "Source Title": "ADVANCED SCIENCE", + "Abstract": "Aqueous rechargeable zinc-metal-based batteries are an attractive alternative to lithium-ion batteries for grid-scale energy-storage systems because of their high specific capacity, low cost, eco-friendliness, and nonflammability. However, uncontrollable zinc dendrite growth limits the cycle life by piercing the separator, resulting in low zinc utilization in both alkaline and mild/neutral electrolytes. Herein, a polyacrylonitrile coating layer on a zinc anode produced by a simple drop coating approach to address the dendrite issue is reported. The coating layer not only improves the hydrophilicity of the zinc anode but also regulates zinc-ion transport, consequently facilitating the uniform deposition of zinc ions to avoid dendrite formation. A symmetrical cell with the polymer-coating-layer-modified Zn anode displays dendrite-free plating/stripping with a long cycle lifespan (>1100 h), much better than that of the bare Zn anode. The modified zinc anode coupled with a Mn-doped V2O5 cathode forms a stable rechargeable full battery. This method is a facile and feasible way to solve the zinc dendrite problem for rechargeable aqueous zinc-metal batteries, providing a solid basis for application of aqueous rechargeable Zn batteries.", + "Times Cited, WoS Core": 382, + "Times Cited, All Databases": 395, + "Publication Year": 2021, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000634747100001", + "Markdown": "# An Artificial Polyacrylonitrile Coating Layer Confining Zinc Dendrite Growth for Highly Reversible Aqueous Zinc-Based Batteries \n\nPeng Chen, Xinhai Yuan, Yingbin Xia, Yi Zhang, Lijun Fu,\\* Lili Liu, Nengfei Yu, Qinghong Huang, Bin Wang, Xianwei Hu,\\* Yuping Wu,\\* and Teunis van Ree \n\nAqueous rechargeable zinc-metal-based batteries are an attractive alternative to lithium-ion batteries for grid-scale energy-storage systems because of their high specific capacity, low cost, eco-friendliness, and nonflammability. However, uncontrollable zinc dendrite growth limits the cycle life by piercing the separator, resulting in low zinc utilization in both alkaline and mild/neutral electrolytes. Herein, a polyacrylonitrile coating layer on a zinc anode produced by a simple drop coating approach to address the dendrite issue is reported. The coating layer not only improves the hydrophilicity of the zinc anode but also regulates zinc-ion transport, consequently facilitating the uniform deposition of zinc ions to avoid dendrite formation. A symmetrical cell with the polymer-coating-layer-modified Zn anode displays dendrite-free plating/stripping with a long cycle lifespan $(>1100\\ h)$ , much better than that of the bare Zn anode. The modified zinc anode coupled with a Mn-doped $\\mathsf{v}_{2}\\mathsf{o}_{5}$ cathode forms a stable rechargeable full battery. This method is a facile and feasible way to solve the zinc dendrite problem for rechargeable aqueous zinc-metal batteries, providing a solid basis for application of aqueous rechargeable Zn batteries. \n\n# 1. Introduction \n\nThe dwindling resources of fossil fuel and accelerating climate change are leading to urgent renewable energy demands. Harvesting sustainable energy from wind, sunlight, tides, and waves offers a great opportunity to overcome the energy shortage and catastrophic climate change. Collection and storage of the energy from these intermittent renewable resources is an intractable problem.[1] Lithium-based batteries (e.g., LIBs), which are among the most successful energy storage systems (EESs) in portable electronic devices such as laptops, smartphones, and wearable devices, have reached a bottleneck in aspect of large-scale grids and electric vehicles due to the exhaustion of lithium resources (high cost) and the use of inherently flammable liquid organic electrolytes.[2] Low cost, long life, and high safety are crucial factors for the successful application of the EESs.[3] Aqueous batteries (ABs), as one of the most promising candidates for large-scale EESs, have attracted the attention of researchers because of their low cost, environmental benignity, and safety.[4–6] Because zinc metal has the highest theoretical specific capacity $(820~\\mathrm{Ah~kg^{-1}}$ ) among multivalent ABs and the abundant zinc supply (costeffective), aqueous rechargeable zinc-ion batteries (ARZIBs) have been extensively investigated in recent years.[7–13] However, dendrite growth on the zinc anode seriously impacts their reliability and limits their life-span.[14] Uneven zinc deposition during cycling is the main culprit, leading to the uncontrollable dendrite growth on the zinc anode’s surface.[15,16] Therefore, homogenizing zinc deposition is the key technology to accelerate the large-scale practical application of ARZIBs. \n\nConsiderable efforts in the realms of zinc electrode construction, electrolytes, and anode surface modification have been made to suppress dendrite growth. Porous 3D zinc foam is the classical electrode design for suppressing zinc dendrite.[17–20] Zn-metal alloys were introduced as potential candidates for dendrite-free zinc anodes.[21,22] Benefitting from rich deposition sites, multidimensional zinc hosts, such as 3D copper,[23,24] carbon nanotube (CNT) frameworks,[25] carbon fiber mats,[26] polyarylimide covalent organic frameworks (PICOFs),[27] and porous carbonized metal–organic frameworks (MOFs),[28,29] have also been employed as current collectors to obtain dendrite-free zinc anodes. Electrolyte engineering (electrolyte additives,[30–33] water-starved electrolytes,[34–38] deep eutectic solvent electrolytes,[39,40] (quasi-) solid-state electrolytes,[41–45] alkaline-mild hybrid electrolytes,[46,47] etc.) has also been shown to be an excellent way to introduce practical application of ARZIBs. Moreover, coating functional layers on zinc anode has been extensively developed to control the dendrite formation.[48] \n\nCoating nanoscale electric materials on zinc surfaces is an effective method to evenly distribute charge, such as epitaxial graphene,[49] metal nanoparticles,[50–53] and carbon/reduced graphene oxide (rGO)/CNT/graphite coating.[37,54–57] Indeed, zinc deposition on these conductive coatings is more uniform and the dendrite growth is retarded to a certain degree, but dendrite formation might still be inevitable because of the uncontrollable electrochemical deposition. For this reason, some insulating materials, for example oxides (or sulfides)[58–62] and MOFs[63] have been coated on zinc surfaces to suppress dendrite formation by regulating the ion flux. Unfortunately, the brittle nature of these films restricts their application in large-scale EESs. \n\nTo overcome the shortcomings of inorganic coating layers, researchers recently developed inorganic/MOF-organic composites as coating layers to suppress dendrite growth, in which poly(vinylidene fluoride) (PVDF), the most popular organic binder, was used as coating preparation to strengthen the flexibility of blended films, such as PVDF–TiO2,[16,64] PVDF– $\\mathsf{\\mathrm{.CaCO}}_{3}$ ,[65] $\\mathrm{PVDF-ZrO}_{2}$ ,[66] PVDF–kaolin,[67] PVDF–MOFs,[68,69] etc. The inorganic/MOF–organic coating not only regulates ion transport, but also resists dendrite growth. Nonetheless, the high cost of nanoscale particles/ligands and the complicated preparation methods of MOFs will be obstacles to the commercialization of ARZIBs in large-scale EESs. Moreover, the gap between binder and solid-state particles probably makes the efforts to sift MOFs with precise $Z\\mathrm{n}^{2+}$ transportation channels in vain. \n\nPorous polymer coatings, a reasonable candidate to circumvent the abovementioned shortcomings, have rarely been reported because they are hydrophobic or water-insoluble. Therefore, constructing hydrophobic polymer coating films with hydrophilic ion transit channels may be a useful solution to direct uniform deposition and control dendrite growth. Polyacrylonitrile (PAN), a widely used polymer, is used extensively as polymer matrix in LIB gel electrolytes, because of its chemical stability, excellent thermal stability, and high tensile strength and tensile modulus.[70–72] By adapting to the volume change during metal plating/stripping, the PAN film’s mechanical flexibility further confines uncontrollable zinc deposition.[73] The polar nitrile group (-CN), which is a linear structure, provides coordination sites to bridge ${\\mathrm{Li}^{+}}$ , ${\\mathrm{Cu}}^{2+}$ , and $\\mathrm{Zn}^{2+}$ ions.[74–76] However, the application of PAN in ARZIBs has not been investigated widely, probably because of the hydrophobicity of PAN membranes. Therefore, partly hydrophilic modification of the PAN coating layer would be a worthwhile way to address the dendrite issue on the surfaces of zinc anodes. \n\nIn this work, we investigate a polymer coating layer for a dendrite-free zinc anode, which is prepared by dropping a PAN solution containing zinc trifluoromethanesulfonate $(Z\\mathrm{n}(\\mathrm{TfO})_{2})$ onto zinc foil $({\\mathrm{PANZ}}({\\overline{{a}}}){\\mathrm{Zn}})$ . Due to the addition of $\\mathrm{Zn(TfO)}_{2}$ , the PAN coating layer combined with a zinc salt (PANZ) has excellent hydrophilicity, which dramatically reduces the interfacial resistance of the Zn anode. With microchannels in the polymer network and the complexation effect between $\\scriptstyle{\\mathrm{Zn}}^{2+}$ and the cyano groups (–CN), the PANZ coating layer does not only facilitate the uniform transport of dissolved $\\scriptstyle{\\mathrm{Zn}}^{2+}$ in the PANZ membrane but also drives the uniform electrodeposition of zinc metal. A symmetric battery with a PANZ $@Z\\mathbf{n}$ anode displays stable cyclability for more than $1140\\mathrm{h}$ with a fixed capacity of $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ . The full battery coupled with Mn-doped ${\\bf V}_{2}{\\bf O}_{5}$ $(\\mathrm{MnVO})$ exhibits better electrochemical performance than that of the bare $Z\\mathrm{n}$ anode, even when ultrathin zinc foil $(20~\\upmu\\mathrm{m})$ was employed in the full batteries. \n\n# 2. Results and Discussion \n\nFigure 1 shows the morphologies, hydrophilicity, and electrochemical impendence spectroscopy (EIS) of different zinc anodes. In order to remove the zinc oxide passivation layer, the bare zinc metal was polished with sandpaper before use (Figure 1A). As shown in Figure 1B, the surface of the zinc anode coating PAN layer without salt (aliased as $\\operatorname{PAN}@\\operatorname{Zn})$ looks smooth and dense, and is a little different from the surface of PANZ $@Z\\mathrm{n}$ because of the microchannels formed in the film of PANZ $@Z\\mathrm{n}$ (Figure 1C; and Figure S1, Supporting Information). The cross-section scanning electron microscopy (SEM) images of bare Zn, $\\operatorname{PAN}@\\operatorname{Zn}$ and $\\mathtt{P A N Z@Z n}$ shown in Figure S1 (Supporting Information) show that the pure PAN coating layer is a pore-free dense layer, and some micropores can be found in the PANZ layer containing zinc salt after the $\\mathrm{Zn(TfO)}_{2}$ salt was partially removed by soaking in water for a few minutes. The energy-dispersive X-ray spectroscopy (EDS) of the Zn, C, N, S, and F elements confirms that the zinc salt in the PANZ coating layer is uniformly distributed (Figure 1D). \n\nSince the uneven wetting of electrolyte on the zinc anode is the crucial factor that triggers the nonuniform distribution of charge and the nonhomogeneous electrodeposition on the solidelectrolyte interface, the hydrophilicity of these zinc anodes in relation to electrolyte $(2\\mathrm{~M~}\\mathrm{Zn}(\\mathrm{TfO})_{2})$ was investigated by measuring dynamic contact angles in the ambient environment. The initial contact angle of uncoated zinc was ${\\approx}87^{\\circ}$ , it was reduced to $77.9^{\\circ}$ in the following $4\\mathrm{min}$ and then remained unchanged even after $20~\\mathrm{min}$ (Figure 1E; and Figure S2A, Supporting Information). In contrast, as illustrated in Figure 1F,G; and Figure S2B,C (Supporting Information), the contact angles of $\\operatorname{PAN}@\\operatorname{Zn}$ and PANZ $@Z\\mathbf{n}$ electrodes were reduced from ${\\approx}62.3^{\\circ}$ and ${\\approx}36.4^{\\circ}$ to $47.6^{\\circ}$ and $26.3^{\\circ}$ over 4 min, respectively. The distinct hydrophilicity improvement of $\\mathtt{P A N Z}@\\mathsf{Z n}$ is attributed to the microchannels formed by the introduction of $\\mathrm{Zn(TfO)}_{2}$ . It should be noted that the smaller contact angle of $\\operatorname{PAN}@\\operatorname{Zn}$ than that of the bare $Z\\mathrm{n}$ can be ascribed to the spreading of water on the PAN membrane.[77] The PANZ membrane exhibits a high ionic conductivity $(2.4~\\mathrm{mS~cm^{-1}}$ , Figure S2D, Supporting Information), which is similar to the previously reported,[78] indicating the fast $\\scriptstyle{\\mathrm{Zn}}^{2+}$ transport through the PANZ layer. The better wettability facilitates the even distribution of zinc-ion flux on the zinc’s surface during cycling, which reduces the ions’ motion resistance and promotes uniform zinc electrodeposition. The Nyquist curves of the impedance spectra of the different anodes before cycling reveal that the PANZ interfacial coating film significantly reduced the interfacial impedance of the zinc anode (Figure 1H). As shown in Figure S3A (Supporting Information), the highest resistance among the three anodes, displayed by $\\operatorname{PAN}@\\operatorname{Zn}$ , substantially confirms that the pure PAN membrane without any additives is pore-free and ion-blocking in aqueous systems. \n\n![](images/ecd56e16d7e516da465931f68475b7b05bf4296742c592c68cc9650c35b1611b.jpg) \nFigure 1. Morphologies, contact angles and EISs of different zinc anodes. A–C) Top-view SEM images of bare $Z n$ , $P A N\\ @Z n$ , and $P A N Z@Z n$ anodes. D) Cross-section SEM image and EDS element mapping analysis of PANZ $@2n$ . E–G) Optical images of contact angles between different zinc anodes and electrolyte. H) Electrochemical impedance spectra (EIS) of symmetric cells with bare Zn and $P A N Z@Z n$ anodes. I) SEM image of flake-shaped dendrites on bare Zn after 5 cycles at $\\mathsf{I m A c m}^{-2}$ with $\\mathsf{1\\ m A h\\ c m^{-2}}$ . J,K) SEM image of dendrite clusters on bare $Z n$ after 15 cycles at $\\mathsf{1\\ m A\\ c m^{-2}}$ with $\\mathsf{1\\ m A h\\ c m^{-2}}$ . L) Top-view SEM images of PANZ $@Z n$ after 15 cycles at $\\mathsf{i}\\mathsf{m A c m}^{-2}$ for $\\textsf{l h}$ . \n\nBare zinc suffers from dendrite formation during cycling, usually after just a few cycles. In a study of the morphologies of the different zinc anodes before and after cycling, an in-depth analysis shows how the PANZ coating layer tackles the dendrite problem. After five cycles at a current density of 1 mA $\\mathrm{cm}^{-2}$ with a capacity of $1\\mathrm{mAhcm}^{-2}$ , many dendrites were found on the surface of the Zn anode (Figure 1I), and the dendrites had grown considerably and gradually gathered to form dendrite clusters after 15 cycles (Figure 1J). Many glass fibers embedded in the dendrites indicate that the dendrites penetrated the glass fiber membrane (Figure 1J,K). \n\nThe cycling performance of a symmetrical cell with the $\\operatorname{PAN}@Z\\mathrm{n}$ anode is shown in Figure S3B (Supporting Information). The battery failed after working only $^{17\\mathrm{~h~}}$ because of an internal short circuit, with a bigger polarization than that of the bare $Z\\mathrm{n}$ and $\\mathtt{P A N Z@Z n}$ . The zinc anode and separator of the failed $\\operatorname{PAN}@Z\\mathrm{n}$ cell was disassembled for further investigation. Dendrites are evident on the edge of the zinc disk, which pierced into the glass fiber membrane and triggered the internal short circuit (Figure S3C–K, Supporting Information). In contrast, the $\\operatorname{PANZ}{\\widehat{\\mathbb{Q}}}\\operatorname Z\\mathrm{n}$ anode showed a smooth surface without dendrite formation after 15 cycles (Figure 1L), showing that the addition of $\\boldsymbol{Z}\\mathrm{n}(\\mathrm{TfO})_{2},$ not only improves the hydrophilicity of a zinc anode with PAN coating layer but also improves the conductivity of ${\\mathrm{Zn}}^{2+}$ in a PAN membrane, which boosts the uniform deposition of $Z\\mathrm{n}^{2+}$ on the zinc electrode surface, consequently inhibiting dendrite formation. \n\nTo further accurately study the dendrite suppression effect of the PANZ coating layer on the $Z\\mathrm{n}$ anode, we tested a symmetrical cell consisting of bare $Z\\mathrm{n}$ and $\\operatorname{PANZ}{\\widehat{\\mathbb{Q}}}\\operatorname{Zn}$ electrodes at the current density of $1\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ with a capacity of 1 mAh $\\mathrm{cm}^{-2}$ for 100 cycles. Aside from the synergistic effect between the two electrodes, we also investigated the morphology change and the electrochemical performance of these two electrodes, which suffered almost identical plating/stripping electrochemical processes (Figure 2). Many glass fibers can be seen adhering to the surface of cycled bare zinc because of the formation of dendrites piercing the separator (Figure 2A). Figure 2B–D shows the spikeshaped dendrites and many corrosion pits on the bare Zn anode surface, suggesting that the electrodeposition and stripping processes occur at preferred prereaction positions to minimize the free energy of the microsystem.[15,21,78] In contrast, the surface of PANZ $@Z\\mathrm{n}$ remained flat, and the PANZ film stayed intact and tightly adhering to the zinc surface (Figure 2E,F). \n\nThe PANZ coating layer on PANZ $@$ Zn was peeled off to reveal the morphology change of the zinc metal, and the SEM image shows a smooth surface without dendrite (Figure 2G). The magnified SEM image in Figure 2H shows that zinc was deposited orderly on the surface, indicating that the deposition behavior of $Z\\mathrm{n}$ on the PANZ $@Z\\mathrm{n}$ anode is different from that on its bare counterpart. The coating layer on the cycled PANZ $@Z\\mathrm{n}$ anode was peeled off and then the “bare zinc” (denoted as $\\operatorname{PANZ}@Z\\operatorname{n}.$ - 2) was reassembled into a coin cell with fresh bare Zn and continuously cycled for another five cycles to further verify the function of the PANZ coating layer. The digital picture displays glass fiber sticking to the surface of the $\\mathtt{P A N Z@Z n-2}$ anode (Figure S4, Supporting Information), and in the magnified SEM images (Figure 2I,J) many protruding dendrites can be seen on the surface. We also evaluated the anticorrosion capability of the PANZcoated zinc anode. The Tafel curves measured in 2 $\\cdot\\ \\mathrm{{M}}\\ Z\\mathrm{{n}(\\mathrm{{TfO})_{2}}}$ at a scan rate of $2\\mathrm{mVs^{-1}}$ show the more negative corrosion potential of PANZ $@Z\\mathbf{n}$ (Figure S5, Supporting Information), which implies that the PANZ coating layer can alleviate the hydrogen evolution reaction. \n\nThese results confirm that the PANZ coating layer can improve the surface wettability of the zinc electrode, reduce the interfacial impedance, relieve the corrosion of zinc, and confine the zinc ion flux to inhibit the growth of zinc dendrite.[79] Based on the above results, we can depict schematically the zinc stripping/plating behavior on the surface of bare $Z\\mathrm{n}$ and $\\operatorname{PANZ}{\\widehat{\\underline{{{a}}}}}\\operatorname{Zn}$ (Figure 2K). The poor cycling performance of the bare zinc electrode is mainly due to its severe interfacial reaction with water or dissolved $\\mathbf{O}_{2}$ and the random deposition/stripping positions and the accumulation effect of zinc dendrite.[80] In contrast, benefiting from excellent flexibility and hydrophilicity, the PANZ coating layer can not only adapt to the volume changes during the processes of zinc deposition/stripping and contain dendrite formation, but also facilitates uniform electrodeposition. \n\nTo evaluate the plating/stripping stability of the bare Zn and $\\mathtt{P A N Z@Z n}$ anodes, we investigated the long-term galvanostatic cycling performance of symmetrical cells at a current density of $1\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ with fixed capacity of $1\\ \\mathrm{mAh}\\ \\mathrm{cm}^{-2}$ . As illustrated in Figure 2L,M, the voltage hysteresis of the $Z\\mathrm{n}||Z\\mathrm{n}$ cell exceeds $100~\\mathrm{{mV},}$ and internal short-circuit signals (sudden voltage drops) were already observed after about $410\\mathrm{h}$ . In contrast, the $\\mathrm{PANZ@Zn||PANZ@Zn}$ cell has a stable voltage profile for $1145\\mathrm{h}$ with only $75~\\mathrm{mV}$ voltage hysteresis. The performance of $\\operatorname{PANZ}{\\widehat{\\mathbb{Q}}}\\operatorname{Zn}$ anode is superior to the most previous works. As summarized in Table S1 (Supporting Information), some of previous zinc anodes presented excellent cycling stability under high current density, but the capacity of per cycle they delivered is too low to satisfy the practical application.[81,82] On the other hand, although some of anodes worked at higher current density, they could only deliver limited number of cycles.[83] \n\nWe also coated a PANZ coating layer on copper foil $({\\mathrm{PANZ}}@{\\mathrm{Cu}})$ and tested two half cells (bare $\\lvert\\mathrm{zn}\\rvert\\rvert$ bare Cu and $\\mathtt{P A N Z@Z n}||\\mathtt{P A N Z@C u})$ to investigate the effect of the PAN coating layer on the Coulombic efficiency (CE) of the zinc stripping/plating process and on the morphology of the deposited zinc (Figure 3). The test was carried out by plating zinc (fixed areal capacity: $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ ) onto the Cu or $\\mathtt{P A N Z}@\\mathsf{C u}$ substrate and then stripping to 1 V. The nucleation overpotential of PANZ@Cu $36~\\mathrm{mV},$ Figure 3A) is much lower than that of bare C $\\boldsymbol{\\mathscr{x}}\\left(51\\mathrm{mV}\\right)$ , which is due to the considerably increased number of active nucleation sites on PANZ $@$ Cu. As displayed in Figure 3B,C, the $\\mathtt{Z n}||\\mathsf{P A N Z@C u}$ cell presents a very stable coulombic efficiency (CE) over 770 cycles $(1440\\ \\mathrm{h})$ , with the average CE as high as $99.8\\%$ after the initial activation cycles. However, the voltage of the $\\mathrm{\\Delta}Z\\mathrm{n}||\\mathrm{Cu}$ cell showed sharp fluctuations after only 90 cycles $\\left(180\\ \\mathrm{h}\\right)$ because of the internal short circuit in the cell caused by Zn dendrite formation. \n\nTo further reveal the effect of the PANZ coating layer on the deposition of zinc ions on the metal substrate, we investigated the morphology changes of the $Z\\mathrm{n}$ deposited on Cu and PANZ@Cu, respectively. A phenomenon similar to that occurring on zinc foil was observed: the zinc was not uniformly deposited on the copper foil, and glass fibers adhered to the copper foil (Figure 3D). Many large-sized nuclei and individual dendrites were observed after $^{1\\mathrm{h}}$ (Figure 3E), and the size and quantity of dendrites significantly increased after $^{2\\mathrm{h}}$ deposition (Figure 3F,G). However, the deposition on PANZ@Cu is very uniform, and the PANZ coating remains intact (Figure 3H,I). After uncovering the PANZ coating, a flat and dendrite-free surface was observed (Figure 3J; and Figure S6A, Supporting Information), confirming that the PANZ coating does regulate the deposition of zinc metal. The cross-section images of original PANZ $@\\mathrm{Cu}$ (Figure S6B, Supporting Information) and zinc deposited $\\mathrm{PANZ}@\\mathrm{Cu}$ (Figure 3K) show that the zinc deposition layer is uniform and dense, and the PANZ coating film remains intact. The EDS mapping further confirms the uniform deposition of zinc on PANZ@Cu (Figure S6C, Supporting Information). Furthermore, the X-ray diffraction (XRD) results also show that the zinc deposit between the PANZ layer and Cu foil is a dense layer (Figure S7, Supporting Information). \n\n$\\mathsf{M n V O}$ cathodes were investigated to further evaluate the impact of the PANZ coating layer on the electrochemical performance of full batteries consisting of bare $\\mathrm{Zn}||\\mathrm{Mn}\\mathrm{VO}$ and $\\mathrm{PANZ@Zn||MnVO}$ cells (Figure 4). MnVO was employed as cathode material to assemble a full battery due to the excellent reversibility, good electronic conductivity, and high specific capacity. The MnVO cathode material was synthesized by the hydrothermal method. The SEM image (Figure S8A, Supporting \n\n![](images/eaa9968980871afc452a44fc21b2f79706eeb641187e844702c212f1951fc0cd.jpg) \nFigure 2. Morphologies of $Z n$ anodes disassembled from $P A N Z@Z n|$ |bare Zn symmetric cell stopped after the 100th cycle, and long-term cycling stability of symmetric cells. A) Digital picture of bare Zn anode side. B–D) SEM images of bare Zn anode; bump-like zinc dendrite in the red dasheddotted region; corrosion pits in the bright yellow square. C) Magnification of SEM image of glass fiber embedded into the bump-like zinc dendrite. D) Erosion pits on the bare Zn anode. E) Digital picture of PANZ $@2n$ side. F) Top-view SEM image of PANZ@Zn. G) SEM image of $P A N Z@Z n$ anode peeled off the PANZ coating layer. H) Magnified SEM image of $P A N Z@Z n$ anode peeled off PAN the coating layer. I,J) SEM images of bulk-shaped dendrites on $\\mathsf{P A N Z@Z n.2}$ anode. K) Schematic illustration of dendrite formation process on bare $Z n$ and PANZ@Zn-2 electrodes. L,M) Voltage–time curves of bare Zn||bare $Z n$ and $\\mathsf{P A N Z@Z n||P A N Z@Z n}$ symmetric cells at $\\mathsf{1\\ m A\\ c m^{-2}}$ with a fixed capacity of 1 mAh $\\mathsf{c m}^{-2}$ . \n\nInformation) and the XRD pattern are consistent with the reported MnVO literature, and show that this cathode can provide a proper interlayer distance for zinc ion intercalation/ deintercalation.[84] \n\nThe CV curves of the two batteries were recorded between 0.2 and $1.8\\mathrm{V}$ versus $Z\\mathrm{n}/Z\\mathrm{n}^{2+}$ at a scan rate of $0.3\\mathrm{~mV~s^{-1}}$ . The two batteries, respectively, present two pairs of cathodic/anodic peaks located at $1.16/0.73$ and $0.80/0.40\\mathrm{~V~}$ (Figure 4A), corresponding to the zinc-ion intercalation and deintercalation processes, respectively.[84,85] The CV curves of the MnVO cathode recorded at multiple scan rates (Figure S9, Supporting Information) show that the cathodic peaks are shifted toward more negative values with increasing scan rate, and the anodic peaks are shifted more positively, which can be ascribed to polarization.[86] \n\n![](images/415e2ae05fb3b448a7b0b0db943d7723c286e9f3ed5fbf3691c81c7fd333f9db.jpg) \nFigure 3. Overpotentials, Coulombic efficiencies, voltage–time curves and morphology analysis of $P A N Z@C u$ and bare Cu electrodes. A) Nucleation overpotentials of Zn deposition on the $\\mathsf{P A N Z@C u}$ and bare $\\mathsf{C u}$ in asymmetric cells (vs Zn electrode). B) CE of Zn plating/stripping in the $Z n{\\mathrm{-}}C\\upmu$ and $\\mathsf{P A N Z@Z n.P A N Z@C u}$ half-cells. C) Typical GCD profiles of $Z n\\mathrm{-Cu}$ and PANZ@Zn-PANZ@Cu half-cells; morphology and zinc plating/stripping efficiency on a copper current collector; current density: $\\mathsf{1\\ m A c m^{-2}}$ . D) Digital picture of current copper collector after plating for $2\\mathfrak{h}$ . E,F) SEM images of bare copper deposited zinc for 1 and $2h$ , respectively. G) Magnified SEM image of zinc dendrite. H) Digital picture of copper current collector after plating for $2h$ . I) SEM image of ${\\mathsf{P A N Q C u}}$ after depositing Zn for $2h$ . J) Peeled-off PAN membrane. K) Cross-section view SEM image of $P A N@C\\upmu$ after depositing Zn. \n\nThe rate performance of the $\\mathrm{Zn}||\\mathrm{Mn}\\mathrm{VO}$ and $\\operatorname{PANZ}@Z\\mathrm{n}|$ $\\mathsf{\\Pi}\\mathsf{M n V O}$ batteries were also tested at various current densities ranging from 0.5 to $5\\mathrm{Ag^{-1}}$ . As shown in Figure 4B, the rate performance of $\\mathrm{\\cdotPANZ@Zn||MnVO}$ is better than that of $\\mathrm{Zn}\\vert\\vert\\mathrm{MnVO}$ . The full battery $\\mathrm{PANZ@Zn||MnVO}$ delivers a high specific capacity of 373 mAh $\\mathsf{g}^{-1}$ , 379, 340, 290, 254, and 220 mAh $\\mathsf{g}^{-1}$ at current densities of 0.5, 1, 2, 3, and $4\\mathrm{~A~g^{-1}}$ , respectively. Even at a very high current density of $5\\mathrm{~A~g^{-1}}$ , the $\\mathtt{P A N Z@Z n}$ still displays a high discharge specific capacity of $170\\ \\mathrm{mAh\\g^{-1}}$ , reaching ${\\approx}45\\%$ capacity utilization. However, the discharge specific capacity of the $\\mathrm{Zn}\\Vert\\mathrm{Mn}\\mathrm{VO}$ battery is lower than that of the $\\mathrm{PANZ@Zn||MnVO}$ battery when the current density is over $1\\mathrm{Ag^{-1}}$ . The charge–discharge curves in Figure 4C reveal that the $\\mathrm{PANZ@Zn||MnVO}$ presents a smaller voltage hysteresis than $\\mathrm{Zn}||\\mathrm{Mn}\\mathrm{VO}$ , which can be attributed to the reduced interfacial impedance due to the improved wettability provided by introducing the PANZ coating layer. \n\nThe long-term cycling stability of the full batteries was tested at $500\\mathrm{mAg^{-1}}$ (Figure 4D). The battery with a bare $Z\\mathrm{n}$ anode presented rapid capacity decay, and internal short circuit occurred at the $260\\mathrm{{th}}$ cycle (Figure S10A, Supporting Information). The fast decaying cycling performance can be attributed to the continuous corrosion of the unprotected $Z\\mathrm{n}$ anode and the continuous growth of dendrites.[87] \n\nBy comparison, the cycling stability and lifespan of the $\\mathrm{PANZ@Zn||MnVO}$ battery is enhanced significantly, with high capacity retention $(255\\mathrm{~mAh~g^{-1}},$ after 500 cycles and a longer lifespan of over 1000 cycles, even with the $20\\upmu\\mathrm{m}$ thickness zinc foil used here. The dynamic EIS analysis of full batteries with $\\mathrm{PANZ@Zn||MnVO}$ and $\\mathrm{Zn}||\\mathrm{Mn}\\mathrm{VO}$ (Figure S10B,C, Supporting Information) reveals that the battery with a $\\operatorname{PANZ}{\\widehat{\\mathbb{Q}}}\\operatorname{Zn}$ anode has a slightly lower resistance than the $\\mathrm{Zn}\\Vert\\mathrm{MnVO}$ battery, which can be attributed to the improvement of the wettability of $Z\\mathrm{n}$ , thus reducing the interfacial impedance. The increase in impedance of $\\mathrm{Zn}||\\mathrm{Mn}\\mathrm{VO}$ with cycling confirms that the PANZ coating layer plays the key role of an artificial solid electrolyte interphase (SEI) to maintain impedance stability during battery cycling. \n\n![](images/17014701dc1bb8cb2df58b67d87d62e5cb3b441225eca2f34113b5247ead7151.jpg) \nFigure 4. Electrochemical performance of full batteries with bare $Z n||\\mathsf{M n V O}$ and PANZ $@Z n\\parallel$ MnVO. A) Cyclic voltammetry of full batteries, scan rate $0.{\\overset{-}{3}}{\\underset{\\mathrm{mV}}{\\leq}}{\\mathrm{-}}^{1}$ . B) Rate performance of full batteries from 0.5 to $5\\mathsf{A}\\mathsf{g}^{-1}$ based on the mass of $\\mathsf{M n V O}$ . C) Capacity versus voltage curves at different current densities. D) Long-term cycling performance of full batteries. \n\n# 3. Conclusion \n\nWe have developed a PANZ coating layer consisting of PAN polymer and zinc salt on a $Z\\mathrm{n}$ anode $({\\mathrm{PANZ}}({\\overline{{a}}}){\\mathrm{Zn}})$ to suppress dendrite formation in ARZIBs. The zinc-ion transport channels in the PANZ coating layer serve as a zinc-ion flux regulator and enhance the uniform deposition of zinc ions on the zinc substrate. As a result, the PANZ coating layer reduces the interfacial impedance, resists dendrite formation, and alleviates side reactions on the zinc anode. Consequently, the $\\mathtt{P A N Z}@\\mathsf{Z n}$ anode in the symmetric batteries shows a dendrite-free surface, and the symmetric cell has a longer lifespan than that of the uncoated bare zinc anode. Moreover, studies of the morphology and the reversibility on copper foil further affirm that the PANZ coating layer can promote the even electrodeposition of zinc ions and maintain high plating/stripping reversibility. The full battery with a $\\operatorname{PANZ}{\\widehat{\\mathbb{Q}}}\\operatorname{Zn}$ anode has an excellent rate performance and a good cycling performance. The method proposed and the in-depth understanding of the mechanism in the current work could represent a big step forward for zinc dendrite suppression and stimulate further efforts on zinc-metal anodes and other aqueous metal-ion batteries. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nP.C. and X.Y. contributed equally to this work. The authors gratefully acknowledge the financial support from the National Key R & D Program of China (No. 2018YFB0104300), National Natural Science Foundation of China (Grant Nos. 51425301, U1601214, and 51974081), Natural Science Foundation of Jiangsu Province (No. BK20200696), State Key Lab Research Foundation (No. ZK201805, ZK201717), the Jiangsu Provincial Innovation Foundation for Postgraduate (Grant No. KYCX20_1072), and the Natural Science Foundation of Liaoning Province, China (Grant No. 2019-MS-129). \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Data Availability Statement \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Keywords \n\ndendrite suppression, polyacrylonitrile coating, zinc anodes, zinc-ion batteries \n\n[1] B. Obama, Science 2017, 355, 126. \n[2] E. Fan, L. Li, Z. Wang, J. Lin, Y. Huang, Y. Yao, R. Chen, F. Wu, Chem. Rev. 2020, 120, 7020. \n[3] B. Dunn, H. Kamath, J.-M. Tarascon, Science 2011, 334, 928. \n[4] N. Zhang, F. Cheng, J. Liu, L. Wang, X. Long, X. Liu, F. Li, J. Chen, Nat. Commun. 2017, 8, 405. \n[5] X. Yuan, F. Ma, L. Zuo, J. Wang, N. Yu, Y. Chen, Y. Zhu, Q. Huang, R. Holze, Y. Wu, T. van Ree, Electrochem. Energy Rev. 2021, 4, 1. \n[6] F. Wang, J. Tseng, Z. Liu, P. Zhang, G. Wang, G. Chen, W. Wu, M. Yu, Y. Wu, X. Feng, Adv. Mater. 2020, 32, 2000287. \n[7] H. Jia, Z. Wang, B. Tawiah, Y. Wang, C.-Y. Chan, B. Fei, F. Pan, Nano Energy 2020, 70, 104523. \n[8] J. Yi, P. Liang, X. Liu, K. Wu, Y. Liu, Y. Wang, Y. Xia, J. Zhang, Energy Environ. Sci. 2018, 11, 3075. \n[9] J. Shin, J. Lee, Y. Park, J. W. Choi, Chem. Sci. 2020, 11, 2028. \n[10] X. Wang, F. Wang, L. Wang, M. Li, Y. Wang, B. Chen, Y. Zhu, L. Fu, L. Zha, L. Zhang, Y. Wu, W. Huang, Adv. Mater. 2016, 28, 4904. \n[11] L. Wang, Z. Wu, M. Jiang, J. Lu, Q. Huang, Y. Zhang, L. Fu, M. Wu, Y. Wu, J. Mater. Chem. A 2020, 8, 9313. \n[12] F. Ma, X. Yuan, T. Xu, S. Zhou, X. Xiong, Q. Zhou, N. Yu, J. Ye, Y. Wu, T. van Ree, Energy Fuels 2020, 34, 13104. \n[13] X. Yuan, J. Mo, J. Huang, J. Liu, C. Liu, X. Zeng, W. Zhou, J. Yue, X. Wu, Y. Wu, ChemElectroChem 2020, 7, 1531. \n[14] L. E. Blanc, D. Kundu, L. F. Nazar, Joule 2020, 4, 771. \n[15] V. Yufit, F. Tariq, D. S. Eastwood, M. Biton, B. Wu, P. D. Lee, N. P. Brandon, Joule 2019, 3, 485. \n[16] Q. Zhang, J. Luan, X. Huang, Q. Wang, D. Sun, Y. Tang, X. Ji, H. Wang, Nat. Commun. 2020, 11, 3961. \n[17] M. Chamoun, B. J. Hertzberg, T. Gupta, D. Davies, S. Bhadra, B. van Tassell, C. Erdonmez, D. A. Steingart, NPG Asia Mater. 2015, 7, e178. \n[18] J. F. Parker, C. N. Chervin, I. R. Pala, M. Machler, M. F. Burz, J. W. Long, D. R. Rolison, Science 2017, 356, 415. \n[19] B. Bozzini, C. Mele, A. Veneziano, N. Sodini, G. Lanzafame, A. Taurino, L. Mancini, ACS Appl. Energy Mater. 2020, 3, 4931. \n[20] C. Wang, G. Zhu, P. Liu, Q. Chen, ACS Nano 2020, 14, 2404. \n[21] S. Wang, Q. Ran, R. Yao, H. Shi, Z. Wen, M. Zhao, X. Lang, Q. Jiang, Nat. Commun. 2020, 11, 1634. \n[22] B. Liu, S. Wang, Z. Wang, H. Lei, Z. Chen, W. Mai, Small 2020, 16, 2001323. \n[23] Q. Zhang, J. Luan, L. Fu, S. Wu, Y. Tang, X. Ji, H. Wang, Angew. Chem., Int. Ed. 2019, 58, 15841. \n[24] Z. Kang, C. Wu, L. Dong, W. Liu, J. Mou, J. Zhang, Z. Chang, B. Jiang, G. Wang, F. Kang, C. Xu, ACS Sustainable Chem. Eng. 2019, 7, 3364. \n[25] Y. Zeng, X. Zhang, R. Qin, X. Liu, P. Fang, D. Zheng, Y. Tong, X. Lu, Adv. Mater. 2019, 31, 1903675. \n[26] Z. Wu, X. Yuan, M. Jiang, L. Wang, Q. Huang, L. Fu, Y. Wu, Energy Fuels 2020, 34, 13118. \n[27] M. Yu, N. Chandrasekhar, R. K. M. Raghupathy, K. H. Ly, H. Zhang, E. Dmitrieva, C. Liang, X. Lu, T. D. Kühne, H. Mirhosseini, I. M. Weidinger, X. Feng, J. Am. Chem. Soc. 2020, 142, 19570. \n[28] X. Zeng, Z. Yang, J. Meng, L. Chen, H. Chen, H. Qin, J. Power Sources 2019, 438, 226986. \n[29] Z. Wang, J. Huang, Z. Guo, X. Dong, Y. Liu, Y. Wang, Y. Xia, Joule 2019, 3, 1289. \n[30] L. Cao, D. Li, E. Hu, J. Xu, T. Deng, L. Ma, Y. Wang, X. Yang, C. Wang, J. Am. Chem. Soc. 2020, 142, 21404. \n[31] A. Naveed, H. Yang, J. Yang, Y. Nuli, J. Wang, Angew. Chem., Int. Ed. 2019, 58, 2760. \n[32] K. E. K. Sun, T. K. A. Hoang, T. N. L. Doan, Y. Yu, X. Zhu, Y. Tian, P. Chen, ACS Appl. Mater. Interfaces 2017, 9, 9681. \n[33] X. Guo, Z. Zhang, J. Li, N. Luo, G. Chai, T. S. Miller, F. Lai, P. Shearing, D. J. L. Brett, D. Han, Z. Weng, G. He, I. P. Parkin, ACS Energy Lett. 2021, 6, 395. \n[34] L. Zhang, I. A. Rodríguez-Pérez, H. Jiang, C. Zhang, D. P. Leonard, Q. Guo, W. Wang, S. Han, L. Wang, X. Ji, Adv. Funct. Mater. 2019, 29, 1902653. \n[35] C. Zhang, J. Holoubek, X. Wu, A. Daniyar, L. Zhu, C. Chen, D. P. Leonard, I. A. Rodríguez-Pérez, J. Jiang, C. Fang, X. Ji, Chem. Commun. 2018, 54, 14097. \n[36] F. Wang, O. Borodin, T. Gao, X. Fan, W. Sun, F. Han, A. Faraone, J. A. Dura, K. Xu, C. Wang, Nat. Mater. 2018, 17, 543. \n[37] W. Li, K. Wang, M. Zhou, H. Zhan, S. Cheng, K. Jiang, ACS Appl. Mater. Interfaces 2018, 10, 22059. \n[38] S. Chen, R. Lan, J. Humphreys, S. Tao, Energy Storage Mater. 2020, 28, 205. \n[39] J. Zhao, J. Zhang, W. Yang, B. Chen, Z. Zhao, H. Qiu, S. Dong, X. Zhou, G. Cui, L. Chen, Nano Energy 2019, 57, 625. \n[40] E. L. Smith, A. P. Abbott, K. S. Ryder, Chem. Rev. 2014, 114, 11060. \n[41] C. Wang, Z. Pei, Q. Meng, C. Zhang, X. Sui, Z. Yuan, S. Wang, Y. Chen, Angew. Chem., Int. Ed. 2021, 60, 990. \n[42] Y. Tang, C. Liu, H. Zhu, X. Xie, J. Gao, C. Deng, M. Han, S. Liang, J. Zhou, Energy Storage Mater. 2020, 27, 109. \n[43] L. Ma, S. Chen, N. Li, Z. Liu, Z. Tang, J. A. Zapien, S. Chen, J. Fan, C. Zhi, Adv. Mater. 2020, 32, 1908121. \n[44] H. Li, C. Han, Y. Huang, Y. Huang, M. Zhu, Z. Pei, Q. Xue, Z. Wang, Z. Liu, Z. Tang, Y. Wang, F. Kang, B. Li, C. Zhi, Energy Environ. Sci. 2018, 11, 941. \n[45] D. Chao, C. R. Zhu, M. Song, P. Liang, X. Zhang, N. H. Tiep, H. Zhao, J. Wang, R. Wang, H. Zhang, H. J. Fan, Adv. Mater. 2018, 30, 1803181. \n[46] X. Yuan, X. Wu, X.-X. Zeng, F. Wang, J. Wang, Y. Zhu, L. Fu, Y. Wu, X. Duan, Adv. Energy Mater. 2020, 10, 2001583. \n[47] W. Fan, F. Liu, Y. Liu, Z. Wu, L. Wang, Y. Zhang, Q. Huang, L. Fu, Y. Wu, ChemComm 2020, 56, 2039. \n[48] Q. Zhang, J. Luan, Y. Tang, X. Ji, H. Wang, Angew. Chem., Int. Ed. 2020, 59, 13180. \n[49] J. Zheng, Q. Zhao, T. Tang, J. Yin, C. D. Quilty, G. D. Renderos, X. Liu, Y. Deng, L. Wang, D. C. Bock, C. Jaye, D. Zhang, E. S. Takeuchi, K. J. Takeuchi, A. C. Marschilok, L. A. Archer, Science 2019, 366, 645. \n[50] M. Cui, Y. Xiao, L. Kang, W. Du, Y. Gao, X. Sun, Y. Zhou, X. Li, H. Li, F. Jiang, C. Zhi, ACS Appl. Energy Mater. 2019, 2, 6490. \n[51] K. Hu, X. Guan, R. Lv, G. Li, Z. Hu, L. Ren, A. Wang, X. Liu, J. Luo, Chem. Eng. J. 2020, 396, 125363. \n[52] D. Han, S. Wu, S. Zhang, Y. Deng, C. Cui, L. Zhang, Y. Long, H. Li, Y. Tao, Z. Weng, Q.-H. Yang, F. Kang, Small 2020, 16, 2001736. \n[53] Z. Cai, Y. Ou, J. Wang, R. Xiao, L. Fu, Z. Yuan, R. Zhan, Y. Sun, Energy Storage Mater. 2020, 27, 205. \n[54] R. Yuksel, O. Buyukcakir, W. K. Seong, R. S. Ruoff, Adv. Energy Mater. 2020, 10, 1904215. \n[55] C. Shen, X. Li, N. Li, K. Xie, J.-G. Wang, X. Liu, B. Wei, ACS Appl. Mater. Interfaces 2018, 10, 25446. \n[56] M. Li, Q. He, Z. Li, Q. Li, Y. Zhang, J. Meng, X. Liu, S. Li, B. Wu, L. Chen, Z. Liu, W. Luo, C. Han, L. Mai, Adv. Energy Mater. 2019, 9, 1901469. \n[57] Z. Li, L. Wu, S. Dong, T. Xu, S. Li, Y. An, J. Jiang, X. Zhang, Adv. Funct. Mater. 2021, 31, 2006495. \n[58] K. Zhao, C. Wang, Y. Yu, M. Yan, Q. Wei, P. He, Y. Dong, Z. Zhang, X. Wang, L. Mai, Adv. Mater. Interfaces 2018, 5, 1800848. \n[59] Y. Yu, Y. Zuo, Z. Zhang, L. Wu, C. Ning, C. Zuo, Coatings 2019, 9, 692. \n[60] H. He, H. Tong, X. Song, X. Song, J. Liu, J. Mater. Chem. A 2020, 8, 7836. \n[61] J. Hao, B. Li, X. Li, X. Zeng, S. Zhang, F. Yang, S. Liu, D. Li, C. Wu, Z. Guo, Adv. Mater. 2020, 32, 2003021. \n[62] S. Bhoyate, S. Mhin, J. Jeon, K. Park, J. Kim, W. Choi, ACS Appl. Mater. Interfaces 2020, 12, 27249. \n[63] L. Cao, D. Li, T. Deng, Q. Li, C. Wang, Angew. Chem., Int. Ed. 2020, 59, 19292. \n[64] R. Zhao, Y. Yang, G. Liu, R. Zhu, J. Huang, Z. Chen, Z. Gao, X. Chen, L. Qie, Adv. Funct. Mater. 2021, 31, 2001867. \n[65] L. Kang, M. Cui, F. Jiang, Y. Gao, H. Luo, J. Liu, W. Liang, C. Zhi, Adv. Energy Mater. 2018, 8, 1801090. \n[66] P. Liang, J. Yi, X. Liu, K. Wu, Z. Wang, J. Cui, Y. Liu, Y. Wang, Y. Xia, J. Zhang, Adv. Funct. Mater. 2020, 30, 1908528. \n[67] C. Deng, X. Xie, J. Han, Y. Tang, J. Gao, C. Liu, X. Shi, J. Zhou, S. Liang, Adv. Funct. Mater. 2020, 30, 2000599. \n[68] M. Liu, L. Yang, H. Liu, A. Amine, Q. Zhao, Y. Song, J. Yang, K. Wang, F. Pan, ACS Appl. Mater. Interfaces 2019, 11, 32046. \n[69] H. Yang, Z. Chang, Y. Qiao, H. Deng, X. Mu, P. He, H. Zhou, Angew. Chem., Int. Ed. 2020, 59, 9377. \n[70] W. Liu, S. W. Lee, D. Lin, F. Shi, S. Wang, A. D. Sendek, Y. Cui, Nat. Energy 2017, 2, 17035. \n[71] A. Manuel Stephan, Eur. Polym. J. 2006, 42, 21. \n[72] W. Liu, N. Liu, J. Sun, P. Hsu, Y. Li, H. Lee, Y. Cui, Nano Lett. 2015, 15, 2740. \n[73] S. Choudhury, D. Vu, A. Warren, M. D. Tikekar, Z. Tu, L. A. Archer, Proc. Natl. Acad. Sci. USA 2018, 115, 6620. \n[74] H. G. M. Edwards, A. R. Hoskins, A. F. Johnson, I. R. Lewis, Polym. Int. 1993, 30, 25. \n[75] A. Ferry, L. Edman, M. Forsyth, D. R. MacFarlane, J. Sun, Electrochim. Acta 2000, 45, 1237. \n[76] K. Perera, M. Dissanayake, P. Bandaranayake, Electrochim. Acta 2000, 45, 1361. \n[77] Q. Liu, L. Li, Z. Pan, Q. Dong, N. Xu, T. Wang, J. Appl. Polym. Sci. 2019, 136, 47902. \n[78] Z. Zhao, J. Zhao, Z. Hu, J. Li, J. Li, Y. Zhang, C. Wang, G. Cui, Energy Environ. Sci. 2019, 12, 1938. \n[79] Y. Nie, F. Wang, H. Zhang, D. Wei, S. Zhong, L. Wang, G. Zhang, H. Duan, R. Cao, Appl. Surf. Sci. 2020, 517, 146079. \n[80] Q. Yang, Q. Li, Z. Liu, D. Wang, Y. Guo, X. Li, Y. Tang, H. Li, B. Dong, C. Zhi, Adv. Mater. 2020, 32, 2001854. \n[81] Q. Yang, Y. Guo, B. Yan, C. Wang, Z. Liu, Z. Huang, Y. Wang, Y. Li, H. Li, L. Song, J. Fan, C. Zhi, Adv. Mater. 2020, 32, 2001755. \n[82] H. Qiu, X. Du, J. Zhao, Y. Wang, J. Ju, Z. Chen, Z. Hu, D. Yan, X. Zhou, G. Cui, Nat. Commun. 2019, 10, 5374. \n[83] X. Xie, S. Liang, J. Gao, S. Guo, J. Guo, C. Wang, G. Xu, X. Wu, G. Chen, J. Zhou, Energy Environ. Sci. 2020, 13, 503. \n[84] C. Liu, Z. Neale, J. Zheng, X. Jia, J. Huang, M. Yan, M. Tian, M. Wang, J. Yang, G. Cao, Energy Environ. Sci. 2019, 12, 2273. \n[85] H. Zeng, D. Liu, Y. Zhang, K. A. See, Y.-S. Jun, G. Wu, J. A. Gerbec, X. Ji, G. D. Stucky, Chem. Mater. 2015, 27, 7331. \n[86] J. Ding, Z. Du, L. Gu, B. Li, L. Wang, S. Wang, Y. Gong, S. Yang, Adv. Mater. 2018, 30, 1800762. \n[87] Y. Cui, Q. Zhao, X. Wu, Z. Wang, R. Qin, Y. Wang, M. Liu, Y. Song, G. Qian, Z. Song, L. Yang, F. Pan, Energy Storage Mater. 2020, 27, 1. " + }, + { + "id": "10.1002_adfm.202101632", + "DOI": "10.1002/adfm.202101632", + "DOI Link": "http://dx.doi.org/10.1002/adfm.202101632", + "Relative Dir Path": "mds/10.1002_adfm.202101632", + "Article Title": "Advanced High Entropy Perovskite Oxide Electrocatalyst for Oxygen Evolution Reaction", + "Authors": "Nguyen, TX; Liao, YC; Lin, CC; Su, YH; Ting, JM", + "Source Title": "ADVANCED FUNCTIONAL MATERIALS", + "Abstract": "A new type of lanthanum-based high entropy perovskite oxide (HEPO) electrocatalyst for the oxygen evolution reaction is reported. The B-site lattices in the HEPO consist of five consecutive first-row transition metals, including Cr, Mn, Fe, Co, and Ni. Equimolar and five non-equimolar HEPO electrocatalysts are studied for their OER electrocatalytic performance. In the five non-equimolar HEPOs, the concentration of one of the five transition metals is doubled in individual samples. The performances of all the HEPOs outperform the single perovskite oxides. The optimized La(CrMnFeCo2Ni)O-3 HEPO exhibits an outstanding OER overpotential of 325 mV at a current density of 10 mA cm(-2) and excellent electrochemical stability after 50 h of testing.", + "Times Cited, WoS Core": 384, + "Times Cited, All Databases": 391, + "Publication Year": 2021, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000646958100001", + "Markdown": "# Advanced High Entropy Perovskite Oxide Electrocatalyst for Oxygen Evolution Reaction \n\nThi Xuyen Nguyen, Yi-Cheng Liao, Chia-Chun Lin, Yen-Hsun Su, and Jyh-Ming Ting\\* \n\nA new type of lanthanum-based high entropy perovskite oxide (HEPO) electrocatalyst for the oxygen evolution reaction is reported. The B-site lattices in the HEPO consist of five consecutive first-row transition metals, including Cr, Mn, Fe, Co, and Ni. Equimolar and five non-equimolar HEPO electrocatalysts are studied for their OER electrocatalytic performance. In the five non-equimolar HEPOs, the concentration of one of the five transition metals is doubled in individual samples. The performances of all the HEPOs outperform the single perovskite oxides. The optimized $\\mathsf{L a}(\\mathsf{C r M n F e C o}_{2}\\mathsf{N i})\\mathsf{O}_{3}$ HEPO exhibits an outstanding OER overpotential of $325~\\mathsf{m V}$ at a current density of $\\mathsf{10m A c m^{-2}}$ and excellent electrochemical stability after $50\\textmd h$ of testing. \n\n# 1. Introduction \n\nHydrogen energy represents one of the most important clean and renewable energies. Hydrogen can be produced by either steam reforming or electrochemical water splitting. In electrochemical water splitting, there are a two-electron transfer hydrogen evolution reaction (HER) and four-electron transfer oxygen evolution reaction (OER), the latter of which thus controls the water splitting efficiency. Due to the high cost and scarcity of most active ruthenium oxide $(\\mathrm{RuO}_{2})$ and iridium oxide $(\\mathrm{Ir}\\mathsf{O}_{2})$ catalysts, alternatives based on transition metals are being intensively investigated. They include various oxides,[1,2] oxy(hydroxides),[3–5] sulfides,[6,7] phosphides,[8,9] and nitrides.[10,11] Among these compounds, perovskite oxide $(\\mathrm{ABO}_{3})$ exhibits unique physical and chemical properties. Typically, the A site accommodates rare earth, alkaline, or alkaline-earth cations coordinated with oxygen, and the B site represents a transition metal cation such as Fe, Ni, Mn, Co, etc. As an electrocatalyst, the favorable non-stoichiometric chemistry and unique structure of perovskite oxide allow the formation of cation and oxygen defects, and tunable electronic structure to boost the OER process.[12–14] \n\nLanthanum-based perovskite oxides, such as $\\mathrm{LaCrO}_{3}$ , $\\mathrm{LaMnO}_{3}$ , $\\mathrm{LaFeO}_{3}$ , $\\mathrm{LaCoO}_{3}$ , and ${\\mathrm{LaNiO}}_{3}$ , have been widely studied for various applications.[15–17] For example, Hardin et  al. reported phasepure nanocrystal ${\\mathrm{LaNiO}}_{3}$ perovskite catalyst that shows high OER and ORR bifunctional performance.[18] To reach the benchmark current density of $10\\ \\mathrm{mA}$ $\\mathrm{cm}^{-2}$ , $\\mathrm{LaNiO}_{3}/$ nitrogen-doped carbon requires only an overpotential of $0.4\\mathrm{~V~}$ in $0.1\\mathrm{{u}}$ KOH electrolyte. The ORR activity of the $\\mathrm{LaNiO}_{3}/\\mathrm{NC}$ at $-3\\mathrm{mA}\\mathrm{cm}^{-2}$ is $0.64\\mathrm{V}.$ To improve the OER activity, the synthesis of nanoporous-structured or improving the intrinsic activity is considered.[19] Porous materials with high surface areas provide more accessible active sites, facilitating the electron transfer. Hollow nanospheres $\\mathrm{LaCoO}_{3}$ synthesized via a hydrothermal route shows an amorphous surface structure and a lower onset potential, and a 6-time higher current density at $1.6\\mathrm{~V~}$ than that of bulk $\\mathrm{LaCoO}_{3}$ .[20] On other hand, doping the A or B site lattices tunes the electronic and chemical characteristics to improve the catalytic activity. For example, Co doping into the B-site lattices in $\\mathrm{LaMnO}_{3}$ has shown to improve the OER performance due to the increased $\\mathrm{Mn}^{4+}/\\mathrm{Mn}^{3+}$ ratio, which facilitates the chemical disproportionation of $\\mathrm{{\\Gamma_{OOH^{-}}}}$ to form $\\mathrm{O}_{2}$ .[21] Another study also shows that $25\\%$ Co doping in $\\mathrm{LaMnO}_{3}$ to form $\\mathrm{LaMn}_{0.75}\\mathrm{Co}_{0.25}\\mathrm{O}_{3}$ gives 27.5 times higher OER performance than that of the pristine $\\mathrm{LaMnO}_{3}$ and the $\\mathrm{LaMn}_{0.75}\\mathrm{Co}_{0.25}\\mathrm{O}_{3}$ is comparable to commercial $\\mathrm{RuO}_{2}$ catalyst. Moreover, $\\mathrm{LaMn}_{0.75}\\mathrm{Co}_{0.25}\\mathrm{O}_{3}$ also shows excellent stability due to its novel structure, abundant higher oxidation state metal ions, and plentiful oxygen vacancies.[22] Fe-doping in Co-based perovskite oxide results in as high as a 10-time increase in the current density.[23] The Fe was also found to enlarge the potential range of thermodynamic metastability, giving structural stability of the perovskite to enable the growth of a surface oxy(hydroxide) layer during OER. A-site excess $(\\mathrm{La}_{0.8}\\mathrm{Sr}_{0.2})_{1+x}\\mathrm{MnO}_{3}$ $\\ (x=0$ , 0.05, and 0.1) bifunctional electrocatalyst exhibits an $87\\%$ higher OER current density at $0.8\\mathrm{~V~}$ versus $\\mathrm{\\sfAg/AgCl}$ than $\\mathrm{LaMnO}_{3}$ in $0.1\\textbf{M}$ KOH due to the formation of oxygen vacancies.[24] Therefore, doping with a metal at either the A or B site lattices in a perovskite oxide apparently enhances the catalyst performance. \n\nRecently, high entropy materials have been shown to exhibit superior activity and excellent stability in catalysis due to the inherent synergistic and high entropy effects of the combined catalytically active metals.[25] In addition, the tunability of composition and the surface electronic structure due to multiple elements involved provide a vast number of possible atomic configurations on the surface of a high entropy material. This also leads to the use of density function theory (DFT) to explain the resulting OER activity. In DFT calculation, descriptors such as $e_{\\mathrm{g}}$ occupancy,[26] charge-transfer energy,[2] $\\mathrm{{\\tt~p}}$ -band center of oxygen,[27] and d-band theory,[28] are commonly used. The use of descriptor provides information on whether a reaction is prone to occur or not. Equally important is the stability of an intermediate $\\mathrm{\\Delta^{*}O}$ or $^{*}{\\mathrm{OOH}}$ ) during the OER. Also noted is that both the adsorbate evolution mechanism (AEM) and lattice oxygen mechanism (LOM) have been considered for perovskite oxides.[29] Nevertheless, at this early stage, there are only very limited reports investigating high entropy oxide (HEO) electrocatalysts. Solvothermally-synthesized high entropy spinel oxide, (Co, Cu, Fe, Mn, $\\mathrm{Ni})_{3}\\mathrm{O}_{4},$ nanoparticles were investigated.[30] It appears that the OER performance is limited and relies on the addition of hydrophilic multi-walled carbon nanotubes (MWCNT). High entropy rock salt oxide, $\\mathrm{(CoNiMnZnFe)_{3}O_{3.2}},$ , has also been reported.[31] Due to the use of a mechanochemical technique, the resulting particles are micro-sized. The $\\mathrm{(CoNiMnZnFe)_{3}O_{3.2}}$ electrocatalyst exhibits a low overpotential of $336~\\mathrm{mV}$ at $10\\mathrm{\\mA\\cm^{-2}}$ , low Tafel slope of $47.5\\mathrm{mV}\\mathrm{dec}^{-1}$ , and stable OER activity for $20\\mathrm{{h}}$ in 1 m KOH electrolyte. The performance is attributed to the synergetic effect and a core-shell structure formed after activation. Perovskite oxide-halide solid solution with transition metals of Cr, Mn, Fe, Co, and Ni has been investigated for use as OER electrocatalyst.[32] In this study, the effect of adding perovskite halide to perovskite oxide is addressed. However, the real enhancement comes from the addition of quaternary Ba-Sr-Co-Fe oxide and the resulting current density is very low $(\\approx39\\mathrm{\\mA\\cm^{-2}})$ . Furthermore, such an enhancement is based on the comparison to the baseline of perovskite oxide that exhibits extremely low OER performance. Therefore, it appears that there is no study focusing on single-phased high entropy perovskite oxide and examining the effect of its composition. HEM catalyst is of great interest due to its large composition space, which is different from the conventional materials in a way that the unparalleled composition complexity brings desired electronic modification. Here, we not only focus on single-phased perovskite oxides with varying compositions but also demonstrate much better performance of the perovskite oxide as an OER electrocatalyst. \n\nIn this study, the B-site lattices in the high entropy perovskite oxides (HEPOs) consist of 5 consecutive first-row transition metals, including Cr, Mn, Fe, Co, and Ni, which have quite similar ionic radii. Both equimolar and non-equimolar HEPO nanoparticles (NPs) have been obtained and their OER electrocatalytic performance have been evaluated. A facile co-precipitation method is used for the synthesis of the perovskite oxides. The resulting HEPOs are uniform nanoparticles with an average particles size of ${\\approx}100\\ \\mathrm{nm}$ , which is much smaller than the aforementioned high entropy oxides (HEOs) prepared using a mechanochemical method. The nanoparticles contribute to improve the catalytic activity by giving higher active surface areas. The optimized HEPO exhibits an outstanding OER activity with an overpotential of $325~\\mathrm{mV}$ at a current density of $10\\mathrm{mAcm}^{-2}$ , low Tafel slope of $51.2~\\mathrm{mV~dec^{-1}}$ , and excellent $50\\mathrm{~h~}$ electrochemical stability. The performance HEPOs outperforms the single perovskite oxides. \n\n# 2. Results and Discussion \n\nFigure 1a shows the X-ray diffractometry (XRD) patterns of the obtained HEPOs samples. All the samples show a singlephased orthorhombic perovskite structure (Pbnm) (JCPDS#50- 0297) without any impurity phase. The crystalline structures of single-metal perovskite oxides were also examined and are shown in Figure S1, Supporting information. $\\mathrm{LaCrO}_{3}$ , $\\mathrm{LaMnO}_{3}$ , $\\mathrm{LaFeO}_{3}$ , and $\\mathrm{LaCoO}_{3}$ all exhibit single-phased orthorhombic perovskite oxide except that the $\\mathrm{LaCrO}_{3}$ contains a minor impurity phase, as marked by asterisks. The XRD pattern of $\\mathrm{LaNiO}_{3}$ corresponds to rhombohedral perovskite oxide (R-3c) (JCPDS#33-0711). The Fourier transform infrared spectro­ metry (FTIR) spectra of HEPOs and single-metal perovskite oxides are shown in Figure  1b and Figure S2, Supporting Information, respectively. All the HEPOs show identical IR spectra. Strong vibration bands at 555 and $600~\\mathrm{cm^{-1}}$ belong to the $\\mathrm{O{-}M{-}O{/}M{-}O{-}M}$ bending in $\\mathrm{\\DeltaMO_{6}}$ octahedral, and symmetric $\\mathrm{M}{-}\\mathrm{O}$ stretching vibrations, respectively.[33] The broaden IR bands at around $625~\\mathrm{cm}^{-1}$ correspond to asymmetric $\\mathrm{\\Delta\\times-}\\mathrm{\\Delta}$ stretching vibrations. The broadening and asymmetric of the vibration bands in all the FTIR spectra are attributed to $\\mathrm{\\DeltaMO_{6}}$ group asymmetry. The reason might be the existence of multitransition metals in different oxidation states, causing the Jahn–Teller distortion along with polarization of $\\mathrm{\\Delta\\times-o}$ bonds arising due to local distortion of crystalline structure with lower symmetry.[34,35] The morphologies of perovskite oxides are shown in Figure 1c–h. All the HEPOs consist of nanoparticles (NPs) having uniform diameters less than $100~\\mathrm{{nm}}$ , except that apparent particle agglomeration is seen in L5M2Cr. The singlemetal perovskite oxides also exhibit NP morphology, as shown in Figure S3, Supporting Information; however, the $\\mathrm{LaCrO}_{3}$ and $\\mathrm{LaNiO}_{3}$ have larger particle sizes, followed by the $\\mathrm{LaCoO}_{3}$ $\\mathrm{LaMnO}_{3}$ , and $\\mathrm{LaFeO}_{3}$ . The L5M2Co HEPO was further examined using transmission electron microscopy (TEM), as shown in Figure 2a. High resolution TEM (HRTEM) image (Figure 2b) shows a lattice spacing of 0.393 and $0.274\\ \\mathrm{nm}$ , which corresponds to the (110) and (202) crystal planes of orthorhombic perovskite oxide, respectively. The selected area electron diffraction (SAED) pattern (Figure  2c) further confirms that the L5M2Co is a single-phased perovskite oxide, consistent with the XRD data. The scanning transmission electron microscopy (STEM) mappings (Figure 2d) demonstrate the uniform distributions of metal elements in the sample. The elemental concentrations of the samples were determined using inductively coupled plasma-mass spectrometry (ICP-MS) analysis. Table 1 displays the atomic compositions of all the samples. Overall speaking, the compositions are consistent with that of the precursor compositions, except that the $\\mathrm{Cr}$ concentration is a little smaller than its precursor concentration. The surface chemistry of all the samples was studied using X-ray photoelectron spectroscopy (XPS). Figure 3 shows the high resolution XPS spectra of elements in L5M2Co. The La 3d spectrum shows a couple of spin orbital peaks of La $3\\mathrm{d}_{5/2}$ at $834.4\\mathrm{eV}$ and La $3\\mathrm{d}_{3/2}$ at $851.2\\mathrm{eV}.$ The peak at binding energy of $838.2\\ \\mathrm{eV}$ is the satellite peak of $3\\mathrm{d}_{5/2}$ ; while the peak locates at $855.1\\mathrm{eV}$ is the satellite peak of $3\\mathrm{d}_{3/2}$ and Ni $2\\mathrm{p}_{3/2}$ due to the complex structures of two components.[36] The Cr $2\\mathrm{p}_{3/2}$ was deconvoluted into two peaks, namely, ${\\mathrm{Cr}}^{3+}$ at $575.7\\mathrm{eV}$ and ${\\mathrm{Cr}}^{6+}$ at $578.7\\mathrm{eV}.$ .[37,38] with concentrations of $93.7\\%$ and $6.3\\%$ , respectively, giving a $\\mathrm{Cr}^{6+}/\\mathrm{Cr}^{3+}$ ratio of 0.82. The $\\mathrm{Cr}2\\mathrm{p}_{1/2}$ is located at $587.8\\ \\mathrm{eV}.$ Two satellite peaks of Cr $2\\mathrm{p}_{3/2}$ and Cr $2\\mathrm{p}_{1/2}$ were found at 587.8 and $596.3\\ \\mathrm{eV},$ respectively.[39] The Mn $2\\mathrm{p}_{3/2}$ and Mn $2\\mathrm{p}_{1/2}$ orbital peaks are seen at 642.7 and \n\n![](images/746ddaa0eb5ed0a8e5e8fe721012fa56462681d470e6941c9685be1a8e18abc9.jpg) \nFigure 1.  a) XRD diffraction patterns and b) FTIR spectra of HEPOs. SEM images of c) L5M, d) L5M2Cr, e) L5M2Mn, f) L5M2Fe, g) L5M2Co, an h) L2M2Ni. \n\n![](images/ff4b1ee928c1f69d59b34d9e8af89edfddceee12029628b1f9f7a141d04a3156.jpg) \nFigure 2.  a) TEM and b) HRTEM images, c) SAED pattern, and d) STEM mappings of L5M2Co. \n\nTable 1.  Chemical composition of HEPOs. \n\n\n
IDLa [%]Cr [%]Mn [%]Fe [%]Co [%]Ni [%]
L5M150.557.459.8511.110.6610.4
L5M2Cr48.4412.699.649.829.559.86
L5M2Mn42.376.822010.0610.3810.37
L5M2Fe44.37.489.7119.129.799.6
L5M2Co44.636.39.599.54209.94
L5M2Ni44.886.199.339.6910.219.71
\n\n$654.4\\ \\mathrm{eV},$ respectively.[40] Mn $2\\mathrm{p}_{3/2}$ peak was deconvoluted into $\\ensuremath{\\mathrm{Mn}}^{3+}$ and $\\mathrm{Mn^{4+}}$ with an $\\mathrm{Mn}^{4+}/\\mathrm{Mn}^{3+}$ ratio of $42.4/57.6=0.74.$ In Figure  3d, two peaks at 710.6 and $723.4\\ \\mathrm{eV}$ belong to the two spin orbital peaks of Fe $2\\mathrm{p}_{3/2}$ and Fe $2{\\mathrm{p}}_{1/2},$ , respectively.[41] Two oxidation states of Fe ions, that is, $\\mathrm{Fe}^{2+}$ and $\\mathrm{Fe}^{3+}$ , were found in Fe $2\\mathrm{p}_{3/2}$ . The $\\mathrm{Fe}^{3+}/\\mathrm{Fe}^{2+}$ ratio is $41.4/58.6=0.71$ . The doublet peaks at 715.4 and $718.5\\ \\mathrm{eV}$ are attributed to the satellite peaks of $\\mathrm{Fe}^{2+}$ (Fe $\\boldsymbol{2}\\mathrm{p}_{3/2})$ and $\\mathrm{Fe}^{3+}$ (Fe $2\\mathrm{p}_{3/2})$ , respectively. The high resolution XPS spectrum of Co shows two main peaks at 779.3 and $794.7\\mathrm{eV},$ , corresponding to Co $2\\mathrm{p}_{3/2}$ and Co $2\\mathrm{p}_{1/2}$ , respectively.[42] Two satellite peaks are seen at 788.5 and $802.{\\dot{7}}~\\mathrm{eV}.^{[43]}$ Deconvolution of Co $2\\mathrm{p}_{3/2}$ shows the existence of ${\\mathrm{Co}}^{3+}$ and ${\\mathrm{Co}}^{2+}$ , giving a $\\mathrm{Co}^{3+}/\\mathrm{Co}^{2+}$ ratio of $73.8/26.2=2.81$ . In the Ni 2p spectrum, only $\\mathrm{Ni^{2+}}$ was found. The strong peak locates at $851~\\mathrm{eV}$ belongs to the La $3\\mathrm{d}_{3/2}$ .[44] The satellite peak of Ni $2\\mathrm{p}_{3/2}$ is seen at $862.8\\ \\mathrm{eV}.$ . The O 1s spectrum was deconvoluted into four components of lattice oxygen $(O_{\\mathrm{I}})$ at $528.5\\ \\mathrm{eV},$ oxygen vacancy $(O_{\\mathrm{II}})$ at $529.8\\mathrm{eV},$ surface-adsorbed oxygen/hydroxyl group $(O_{\\mathrm{III}})$ at $531\\ \\mathrm{eV},$ and surface adsorbed water $(O_{\\mathrm{IV}})$ at 532.6 and $(O_{\\mathrm{V}})$ $_{/)}\\ 534.5\\ \\mathrm{eV}.^{[45]}$ The XPS data of rest samples were also analyzed and are shown in Figures S4–S9 and Tables S2 and S3, Supporting Information. \n\nThe obtained HEPOs were evaluated as OER electrocatalysts using a standard three electrode system in a $1\\mathrm{~m~}$ KOH electrolyte. For comparison, all five single-metal perovskite oxides, including $\\mathrm{LaCrO}_{3}$ , $\\mathrm{LaMnO}_{3}$ , $\\mathrm{LaFeO}_{3}$ , $\\mathrm{LaCoO}_{3}$ , and $\\mathrm{LaNiO}_{3}$ , were also used as electrocatalysts. The electrochemical test results of single-metal perovskite oxides are shown in Figure S10, Supporting Information. It can be seen that $\\mathrm{LaCoO}_{3}$ and $\\mathrm{LaNiO}_{3}$ have a higher catalytic activity with the lowest overpotential of 380 at current density of $10\\mathrm{\\mA\\cm^{-2}}$ ( $\\eta_{10}=380\\ \\mathrm{mV})$ , followed by $\\mathrm{LaCrO}_{3}$ $\\eta_{10}=420\\:\\mathrm{mV})$ ), $\\mathrm{LaFeO}_{3}$ $\\mathit{\\Omega}_{\\mathit{\\Pi}_{10}}=437\\:\\mathrm{mV})$ ), and $\\mathrm{LaMnO}_{3}$ with the worst performance of $\\eta_{10}=460\\ \\mathrm{mV}.$ Tafel slopes show the similar trend. The resulting polarization linear sweep voltammetry (LSV) curves of HEPOs are shown in Figure 4a. L5M has $\\eta_{10}=359\\mathrm{mV},$ which outperforms all single perovskite oxides. With the concentration of an element doubled, the OER performance improves, as compared to the equimolar HEPO of L5M. The overpotential at a current density of $10\\ \\mathrm{mA\\cm^{-2}}$ and the calculated turn over frequency (TOF) at overpotential of $400~\\mathrm{mV}$ are used to evaluate the catalytic activity toward OER, as shown in Figure 4b. The L5M2Co shows the best OER performance with the lowest $\\eta_{10}$ of $325~\\mathrm{mV}.$ L5M2Ni shows the second-best performance with $\\eta_{10}=335\\mathrm{~mV},$ followed by L5M2Cr and L5M2Fe $(\\eta_{10}=343~\\mathrm{mV}_{\\cdot}$ , and then L5M2Mn $\\eta_{10}=$ $353~\\mathrm{mV}$ ). This order echoes that of the single-metal perovskite oxides. TOF demonstrates the same order. L5M2Co has the highest TOF value of $0.0267{\\mathrm{s}}^{-1}$ . To investigate the kinetics, Tafel slopes were derived from the LSV curves, as shown in Figure 4c. The kinetic activity of HEPOs based on the Tafel slope follows the order: L5M2Co $(51.2\\ \\mathrm{mV\\dec^{-1})>L5M{2F e}}$ $(54~\\mathrm{mV}~\\mathrm{dec^{-1}})$ $>\\mathrm{L}5\\mathrm{M}2\\mathrm{Ni}$ $(55.1\\mathrm{~mV~dec^{-1}})>\\mathrm{L5M2Cr~(56~mV~dec^{-1})>L5M2M n}$ $(66.3\\ \\mathrm{mV}\\ \\mathrm{dec}^{-1})>\\mathrm{L}5\\mathrm{M}$ $(78.6~\\mathrm{mV~dec^{-1}})$ . As a comparison, $\\mathrm{RuO}_{2}$ shows a lower $\\eta_{10}$ than the HEPOs; however, its overpotential becomes the worst after the current density exceeds $15\\mathrm{mAcm}^{-2}$ , hence giving the highest Tafel slope of $109.6~\\mathrm{mV~dec^{-1}}$ and the lowest value of TOF. The electrochemical surface areas (ECSAs) of all samples were estimated from the double layer capacitance $(C_{\\mathrm{dl}})$ . The recorded cyclic voltammetry (CV) curves at different scan rates are shown in Figure S11, Supporting Information. $\\mathrm{(/{a}}^{\\phantom{}}-\\ensuremath{J_{\\mathrm{c}}})/2$ versus the scan rate for all the samples are shown in Figure 4d. ECSA values were calculate from the slopes or $C_{\\mathrm{dl}}$ and are shown in Table S4, Supporting Information. L5M2Fe gives largest ECSA, while L5M2Cr has the lowest $C_{\\mathrm{dl}}$ or ECSA due to agglomerated morphology. LSV curves were then normalized to the ECSA to evaluate the intrinsic activity, as shown in Figure  4e. L5M2Co shows the highest intrinsic catalytic activity or the lowest overpotential of $400~\\mathrm{mV}$ at $10\\mathrm{\\mA\\cm^{-2}}$ $(\\eta_{10,\\mathrm{ECSA}})$ . The intrinsic catalytic activities of the samples follow the order: L $5\\mathrm{M}2\\mathrm{Co}>\\mathrm{L}5\\mathrm{M}2\\mathrm{Ni}\\sim\\mathrm{L}5\\mathrm{M}2\\mathrm{Cr}>\\mathrm{L}5\\mathrm{M}2\\mathrm{Fe}>\\mathrm{L}5\\mathrm{M}2\\mathrm{Mn}$ $>\\mathrm{L}5\\mathrm{M}$ . L5M2Co remains as the best electrocatalyst. Electrochemical impedance spectroscopy (EIS) analysis was performed to understand the effect of electrical conductivity on the OER performance. The resulting Nyquist plots measured at an overpotential of $285~\\mathrm{mV}$ are given in Figure  4f. An equivalent circuit consisting of the electrolyte resistance $\\left(R_{\\mathrm{s}}\\right)$ , charge transfer resistance $(R_{\\mathrm{ct}})$ , and constant phase element (CPE) is shown in the figure inset. The order of the charge transfer resistance for HEPOs samples is: L5M2Co (17.7 $\\Omega_{-}^{-}$ ), L5M2Ni $(18.2\\Omega)$ , L5M2Fe $(21.2\\ \\Omega)$ , L5M2Cr $(23.3\\ \\Omega)$ , L5M2Mn $(33.8\\ \\Omega)$ , and L5M $(48.5~\\Omega)$ , coincides with the order of the OER activity. L5M2Co exhibits the smallest charge transfer resistance during the OER, thereby achieving faster and more efficient charge transfer for OER electrocatalysis. \n\nTo gain the insight of the intrinsic activity of HEPOs, the surface chemistry is discussed. The valent states of each metal obtained from the above XPS spectra are shown in Table S2, Supporting Information. The surface metals exhibit a variety of oxidation states. Ni shows only $\\mathrm{Ni}^{2+}$ , except that the L5M2Ni sample has both $\\mathrm{Ni^{3+}}$ and $\\mathrm{Ni}^{2+}$ . The ${\\mathrm{Co}}^{3+}/{\\mathrm{Co}}^{2+}$ ratio is the highest in each of the HEPO samples. Both $\\mathrm{Cr}$ and Mn have higher oxidation states of ${\\mathrm{Cr}}^{6+}$ and $\\mathrm{Mn^{4+}}$ , respectively. Such valent state variations cannot be explained by simply considering the electronegativity but involves complex electronic structure modifications (Figure S12, Supporting Information). However, a catalyst having high oxidation states is often favorable for the electrocatalytic activity. Of note here is that the variations of the oxidation state ratios in all the HESO samples remarkably follow the same trend, as shown in Figure S13, Supporting Information, except the L5M2Ni. Therefore, we first consider the L5M, L5M2Mn, L5M2Fe, L5M2Cr, and L5M2Co samples. In general, the catalytic activity increases with the amount the high oxidation states. L5M2Co, exhibiting the best OER activity, has the largest amounts of ${\\mathrm{Cr}}^{6+}$ , $\\mathrm{Mn^{4+}}$ , $\\mathrm{Fe}^{3+}$ , and ${\\mathsf{C o}}^{3+}$ . The presence of Cr has been shown to increase OER activity in various materials.[46–48] A partial oxidation of ${\\mathrm{Cr}}^{3+}$ to $\\mathrm{Cr^{6+}}$ improves the OER activity.[49,50] Also, $\\ensuremath{\\mathrm{Mn}}^{3+}$ cations are often regarded as the active species, with the existence of $\\mathrm{Mn^{4+}}$ critically affecting the catalytic activity in a manner that a synergistic effect of $\\mathrm{Mn}^{3+}$ and $\\mathrm{Mn^{4+}}$ ions was found to enhance the electrocatalytic performance in OER reactions.[51–55] Studies have reported that $\\mathrm{Mn^{4+}}$ serves as a secondary supply of the catalytically active $\\mathrm{Mn}^{3+}$ .[56,57] The presence of Fe provides charge stability to prevent the formation of a side oxide phase, which inhibits the formation of active sites, leading to a lower OER activity.[23] Moreover, the adjacent ${\\mathrm{Co}}^{3+}$ ions can be effectively activated by $\\mathrm{Fe}^{3+}$ due to both the spin and charge effect, resulting in increased intrinsic catalytic activity.[58] With regard to Co, Cobased perovskite oxides exhibit terrific OER performance due to the ${\\mathrm{CoO}}_{6}$ octahedron.[23,33,59–61] High oxidation states were found to be favorable for better catalytic activity.[62] A metal with high oxidation states is more likely to accept an electron from $\\mathrm{H}_{2}\\mathrm{O}$ . As a result, bearing in mind that $\\mathrm{Co}^{3+}/\\mathrm{Co}^{2+}$ ratio is the highest in each of the 5 samples (Table S2, Supporting \n\n![](images/16945f65ee077c24017ea080f0ec928d3cd817e8989c06cdeb947736d6729494.jpg) \nFigure 3.  a) La 3d, b) Cr 2p, c) Mn 2p, d) Fe 2p, e) Co 2p, f) Ni 2p, and g) O1s XPS spectra of L5M2Co. \n\n![](images/4faa28fef0e764b46a167a519d5f0be3c195844c9fd9f9f4b14ac89bd7ab5b1f.jpg) \nFigure 4.  a) Polarization LSV curves, b) overpotentials at a current density of $\\mathsf{10\\ m A\\ c m^{-2}}$ and TOF values, c) Tafel slopes, d) charging currents at 1.0518 V (versus RHE) as a function of the scan rate, e) LSV curves normalized to the ECSA, and f) Nyquist plots. \n\nInformation), Figure 5a shows that, for these 5 HEPO samples, the overpotential decreases with the $\\mathrm{Co}^{3+}/\\mathrm{Co}^{2+}$ ratio. In other words, Co dominates the catalytic activity. DFT calculation indicates that Co-doping can lower the OER overpotential with the ${\\mathsf{C o}}^{3+}$ sites being more effective than Ni and Fe cations.[63] However, while Co dominates the activity, the interplays with other factors cannot be ignored, especially, the existence of $\\mathrm{Mn^{4+}}$ and oxygen vacancy $(V_{\\mathrm{{o}}})$ . Of note here is that the $\\mathrm{Co}^{3+}/\\mathrm{Co}^{2+}$ ratio is low in L5M2Ni; however, following the argument for the other 5 HEPO samples, it shows a higher than expected overpotential (Figure  5a). The existence of $\\mathrm{Mn^{4+}}$ and $V_{\\mathrm{o}}$ is therefore considered. As mentioned above, $\\mathrm{Mn^{4+}}$ serves as a secondary supply of the catalytically active $\\mathrm{Mn}^{3+}$ . It has been shown that OER overpotential progressively decreases with $\\mathrm{Mn^{4+}}$ .[57] In-situ analysis even suggests $\\mathrm{Mn^{4+}}$ dictates OER activity.[56] Thus, the lowest OER overpotential was reported to be often in between $\\mathrm{Mn}^{3.5+}$ and $\\mathrm{Mn}^{3.7+}$ .[51–53,64] In this study, the L5M2Ni sample has a $\\mathrm{Mn}^{4+}/\\mathrm{Mn}^{3+}$ ratio of 1.55 (Table S2, Supporting Information), giving an oxidation state of $\\mathrm{Mn}^{3.61+}$ , that is, in between the optimal range of $\\mathrm{Mn}^{3.5+}$ and $\\mathrm{Mn}^{3.7+}$ . Table S2, Supporting Information, also shows that the L5M2Ni sample has the highest amount of $V_{\\circ}$ . Oxygen vacancies have been found to tune the electronic structure, providing a significant catalytic performance improvement for perovskite oxide electrocatalysts. Abundant oxygen vacancies promote the adsorption of adsorbates, thus considerably accelerating the OER kinetics.[65–68] With the a distinct $\\mathrm{Mn}^{4+}/\\mathrm{Mn}^{3+}$ ratio of 1.55 and the highest amount of $V_{\\mathrm{{o}}}\\mathrm{{}}$ the OER activity of L5M2Ni shown in Figure 5a is explained. In fact, considering the effects of $\\mathrm{Co}^{3+}/\\mathrm{Co}^{2+}$ , $\\mathrm{Mn^{4+}}/$ $\\ensuremath{\\mathrm{Mn}}^{3+}$ , and $V_{\\mathrm{o}}$ , the OER activity is justified since the overpotential of all the HEPOs follows the same trend (Figure S14, Supporting Information). To further explain the OER catalytic activity, DFT calculations were performed. We first found that $^{*}\\mathrm{O}$ is stable but $\\mathrm{\\\"{oo}}$ is unstable. In other words, it is the AEM that dominates the OER but not the lattice oxygen mechanism (LOM). Based on the AEM, the reaction of $_{\\mathrm{M-O^{*}+}}$ $\\mathrm{{OH^{-}\\rightarrow}}$ $\\mathrm{M-OOH^{*}+e^{-}}$ is take to be the rate determining step. In the calculation, Mn was taken as the active site (Figure S15a,b, Supporting Information). The optimized structures having $^{*}\\mathrm{O}$ and $\\mathrm{\\\"{ooH}}$ absorbed on the surface-active sites are shown in Figure S15c, Supporting Information. The calculated overpotentials as a function of the free energy of the rate-determining step are shown in Figure  5b. The OER activity estimated by the DFT calculation is in a good agreement with the experimental data. Both theory and experiment indicate that L5M2Co exhibits the best OER activity. Moreover, as mentioned above, the controlling factor is the ${\\mathrm{Co}}^{3+}/{\\mathrm{Co}}^{2+}$ ratio. This is also supported by the DFT calculation, as shown in Figure 5b. \n\n![](images/ee8be1a037da7e86bfc9a03ca5f886d89613229753882bc7e973b5036fd057bb.jpg) \nFigure 5.  a) The dependence of ECSA normalized overpotential at a current density of $\\mathsf{10\\ m A\\ c m^{-2}}$ on the ${\\mathsf{C o}}^{3+}/{\\mathsf{C o}}^{2+}$ ratio in various HEPOs. b) Over potential as a function of the free energy of the rate-determining step in OER. \n\nThe stability of the best L5M2Co catalyst was examined using the chronopotentiometric method under a constant current density of $10\\mathrm{\\mA\\cm^{-2}}$ . The sample shows excellent electrochemical stability without apparent change after $50\\mathrm{~h~}$ continuous electrolysis, as shown in Figure 6a. The polarization LSV curves (Figure  6b) were recorded initially and after $50\\mathrm{~h~}$ of electrolysis. After $50\\mathrm{~h~}$ , the activity is even slightly higher than in the beginning, indicating the stable catalytic performance. The stability of L5M2Co was further supported by post-characterization of the used catalyst. Scanning electron microscopy (SEM) and TEM were preformed after the OER test. As shown in Figure 7, there is no noticeable change in morphology of La5M2Co after OER process. The thin layer forming and surrounding the particles may be the metal hydroxides layer formed during the reaction.[23,45] The HRTEM and SAED show a single phase crystalline perovskite structure of the sample after OER, indicating the structural stability of the HEPO. STEM-mapping shows the uniform distribution of all elements. \n\n![](images/d3750df6fbc94963627b139bb8bfb3fea3c7ca7c81e0c12eeb92118b12f83cd1.jpg) \nFigure 6.  a) Durability test of L5M2n for $50\\mathrm{~h~}$ . b) Polarization curves before and after $50\\textmd{h}$ stability test. \n\n![](images/3878e524225a6a8720f7b7d263d0fe75968d8737d98d4652a24e07de7321ef2f.jpg) \nFigure 7.  a) SEM image, b) TEM image, c) HRTEM, d) SAED, and e) STEM-mapping of L5M2Co after OER test. \n\n# 3. Conclusion \n\nA series of new single-phased high entropy perovskite nanoparticle oxides have been synthesized using a precipitation method followed by post annealing. A total of five different metals, including Cr, Mn, Fe, Co, and Ni are in the B-site lattices to make the perovskites become high entropy materials. Both equimolar and non-equimolar high entropy nanoparticles were obtained and studied for their OER electrocatalytic performances. We first show that the HEPOs outperform the single perovskite oxides. The activity contribution of each metal in the B-site lattices was then investigated by doubling its concentration. Doubling the Co was shown to be most effective, giving an excellent overpotential of $325~\\mathrm{mV}$ at $10\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ , a low Tafel slope of $51.2~\\mathrm{mV~dec^{-1}}$ , and excellent durability for $50\\mathrm{~h~}$ . This study also opens a window of synthesizing advanced high entropy materials for various potential applications. \n\n# 4. Experimental Section \n\nChemicals: Lanthanum nitrate hexahydrate $(\\mathsf{L a}(\\mathsf{N O}_{3})_{3}{\\cdot}6\\mathsf{H}_{2}\\mathsf{O}$ , $99.9\\%$ , nickel (II) sulfate hexahydrate $(N i S O_{4}{\\cdot}6H_{2}O$ , $299\\%$ ), chromium (III) sulfate hydrate $(\\mathsf{C r}_{2}(\\mathsf{S O}_{4})_{3}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ , $99\\%$ , and iron (II) sulfate heptahydrate $(\\mathsf{F e S O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ , $299\\%$ ) were purchased from Acros. Manganese (II) sulfate monohydrate $(M n S O_{4}{\\cdot}H_{2}O$ , $299\\%$ was purchased from Sigma-Aldrich. Cobalt (II) sulfate monohydrate $(\\mathsf{C o S O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ , $299\\%$ ) was purchased from Vetec. Potassium hydroxide (KOH, $285\\%$ ) was purchased from Honeywell. Sodium hydroxide pellets (NaOH, $298\\%$ ) and ${\\sf R u O}_{2}$ $(99.9\\%)$ \n\nwere purchased from Alfa Aesar. Lemon juice (LJ) having a $\\mathsf{p H}$ value of 3 was extracted from natural lemon. \n\nLanthanum nitrate hexahydrate and metal sulfate hydrates of Mn, Cr, Fe, Co, and Ni were used as the precursors. In a typical process, 2 mmol of $\\mathsf{L a}(\\mathsf{N O}_{3})_{3}{\\cdot}6\\mathsf{H}_{2}\\mathsf{O}$ was dissolved in $20~\\mathsf{m l}$ de-ionized (DI) water. Transition metal sulfates having desired elements and concentrations (2 mmol in total) were dissolved in $20~\\mathsf{m l}$ DI water. The two precursor solutions were mixing in a beaker with the addition of citric acid $(3.5~\\mathsf{m L}$ lemon juice) under stirring for $15\\mathrm{\\min}$ . After that, $20\\ m\\ 0.6\\ \\bowtie\\ \\mathsf{N a O H}$ was also added into the resulting solution under stirring. The stirring lasted for $3\\ h$ to allow the formation of precipitates. The resulting precipitates were centrifuged and washed using DI water and ethanol several times, and then dried for $24\\mathrm{~h~}$ at $60~^{\\circ}\\mathsf{C}$ in a vacuum oven. The collected powders were milled and heat-treated in $750^{\\circ}\\mathsf C$ for ${\\mathsf{1}}2{\\mathsf{h}}$ . The sample having equimolar transition metal sulfates is designated as L5M. The concentration of each transition metal sulfate was doubled to obtain samples L5M2Ni, L5M2Co, L5M2Fe, L5M2Mn, and L5M2Cr, where 2M $[M=\\mathsf{N i}$ , Co, Fe, Mn, and Co) depicts the metal whose sulfate concentration was doubled. Single perovskite oxides including, $\\mathsf{L a C r O}_{3}$ $\\mathsf{L a M n O}_{3}$ , $\\mathsf{L a F e O}_{3}$ , $\\mathsf{L a C o O}_{3}$ and $\\mathsf{L a N i O}_{3}$ were synthesized using the same protocol for comparison. \n\nCrystalline structure was examined using XRD (Bruker D8 Discover). Morphology was examined using SEM (JEOL 6701F) and TEM (JEOL JEM-2100F). Microstructure was studied using HRTEM and SAED analyses. Dark field STEM coupled with energy-dispersive X-ray spectroscopy (EDS) was used for elements mapping. Chemical composition was examined using ICP-MS (ICP-MS, Thermo-Element XR). XPS (Versa Probe PHI 5000) was used for analyzing the surface chemistry. \n\nElectrochemical properties were evaluated using a Metrohm Autolab instrument in a 3-electrode cell at room temperature. Ni foam was use as the supported substrate. Before use, Ni foam was cleaned with \n\n$3\\mathsf{m}\\mathsf{H}\\mathsf{C l}$ to remove the oxidized layer, and then washed several times with ethanol and DI water, and dried in a vacuum oven. The working electrode was prepared by first mixing $5~\\mathrm{mg}$ of active material, $340~\\upmu|\\mathrm{~\\sf~D~I~}$ water, $750~\\upmu\\upmu\\upmu$ ethanol, and $40~\\upmu\\upmu\\upmu$ nafion. The mixture was subsequently sonicated for at least $\\textsf{l h}$ in order to obtain homogeneous slurry. After that, $250~\\upmu\\upmu\\up$ of the resulting slurry was drop casted onto a nickel foam substrate uniformly, covering an area of $\\mathsf{l c m}\\times\\mathsf{l c m}$ , and then dried in the vacuum oven for $\\rceil\\boldsymbol{\\mathsf{h}}$ . An electrode using commercial ${\\sf R u O}_{2}$ was also prepared for comparison. LSV was carried out at a scanning rate of $5\\ m\\vee s^{-1}$ with a reference electrode of ${\\sf A g/A g C l}$ and a counter electrode of platinum. The potential was converted to reversible hydrogen electrode (RHE), that is, $E_{\\mathtt{R H E}}=E_{\\mathtt{A g/A g C l}}+0.059^{*}\\mathsf{p H}+0.7976$ (V). Tafel slope was derived from the LSV curve in the kinetic controlled region. To measure the $C_{\\mathrm{dl}}$ for estimating the ECSA, CV was performed at various scan rates of 20, 40, 60, 80, 100, and $\\mathsf{l}20\\ m\\vee\\mathsf{s}^{-1}$ with a non-Faradic window of 1.012 to 1.092 V versus RHE. The $C_{\\mathrm{d}|}$ was determined from the slope of the linear curve of $\\Delta]$ $\\theta_{\\mathrm{a}}-J_{\\mathrm{c}})/2$ at 1.052 V versus the scan rates. ECSA was then calculated as follows: $\\mathsf{E C S A}=C_{\\sf d I}/C_{\\sf s}$ , where $C_{s}$ is the specific capacitance $(0.04~\\mathsf{m F}~\\mathsf{c m^{-2}},$ ).[69] EIS analysis was performed with a frequency range from $\\mathsf{10^{5}}$ to $0.05~\\mathsf{H z}$ at an AC amplitude of $5~\\mathsf{m V}.$ Electrochemical data were corrected with $95\\%$ IR compensation. The stability was examined using chronopotentiometry at a constant current density of $\\mathsf{10\\ m A\\ c m^{-2}}$ for $50\\mathrm{~h~}$ . The TOF was calculated at the overpotential of $400~\\mathrm{mV}$ as the follow equation:[70] \n\n$$\n{\\mathsf{T O F}}={\\frac{j A}{4F n}}\n$$ \n\nwhere, $j$ is current density $(A c m^{-2})$ ), A is the geometric area of the electrode $(1\\times1~\\mathsf{c m}^{2})$ , F is Faraday constant $(96485\\textsf{s A m o l}^{-1})$ , and $n$ is the number of moles of the metal in the electrode \n\nDFT Calculation: Spin-polarized DFT calculations were performed with the Vienna Ab-initio simulation software package (VASP). The generalized gradient approximation (GGA) of Perdew–Burke–Ernzerhof was used to explain the exchange-correlation energy. A 520  eV plane wave cutoff and a $2\\times1\\times1$ gamma-centered Monkhorst–Pack k-point grid were used for the calculations. Each supercell contains 150 atoms and has a vacuum of $75\\mathring{\\mathsf{A}}$ in the $+c$ direction to avoid interaction between the slabs. The structural composition is shown in Table S1, Supporting Information. The free energies of intermediates, including $^{\\ast}\\mathrm{O}$ and $\\mathrm{\\stackrel{\\ast}{o}{o}H}$ , were calculated relative to $H_{2}O$ and $\\mathsf{H}_{2}$ using the following equations:[71] \n\n$$\n\\Delta G_{*0}=G_{*0}+G_{\\mathsf{H}_{2}}-G_{*}-G_{\\mathsf{H}_{2}0}\n$$ \n\n$$\n\\Delta G_{*\\mathrm{OOH}}=G_{*\\mathrm{OOH}}+\\frac{3}{2}G_{\\mathsf{H}_{2}}-G_{*}-2G_{\\mathsf{H}_{2}\\mathrm{O}}\n$$ \n\nwhere $\\ast$ is an active site on the surface of the catalyst, $^{\\ast}\\mathrm{O}$ and $\\mathrel{\\mathrm{\\cdots}}\\boldsymbol{\\mathrm{OOH}}$ are intermediates adsorbed on the active sites. The free energy of the rate-determining step of the OER reaction is described by the following equation:[72] \n\n$$\n\\Delta G=\\Delta G_{\\mathrm{*OOH}}-\\Delta G_{\\mathrm{*O}}-e U\n$$ \n\nFor an ideal OER catalyst, it is assumed that the value of the applied potential $U$ is 0, that is, $\\mathsf{l}.23\\ \\mathsf{e V}.$ The overpotential of the OER $(\\eta)$ is defined as the following equation: \n\n$$\n\\eta=\\frac{\\Delta G}{e}-1.23\n$$ \n\nThe obtained overpotential, representing the stability of the intermediate,[73] is then used to refer to the reaction mechanism. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Acknowledgements \n\nThis work has been supported by the Ministry of Science and Technology in Taiwan under Grant No. MOST 108-2218-E-006-023 and MOST 109-2224-E-006-007. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Data Availability Statement \n\nResearch data are not shared. \n\n# Keywords \n\nhigh entropy perovskite-oxides, non-equimolar concentration, oxygen evolution reaction \n\nReceived: February 16, 2021 Revised: March 30, 2021 Published online: \n\n[1]\t N.-T.  Suen, S.-F.  Hung, Q.  Quan, N.  Zhang, Y.-J.  Xu, H. M.  Chen, Chem. Soc. Rev. 2017, 46, 337. \n[2]\t W. T.  Hong, K. A.  Stoerzinger, Y.-L.  Lee, L.  Giordano, A.  Grimaud, A. M.  Johnson, J.  Hwang, E. J.  Crumlin, W.  Yang, Y.  Shao-Horn, Energy Environ. Sci. 2017, 10, 2190. \n[3]\t Q. Xiang, F. Li, W. Chen, Y. Ma, Y. Wu, X. Gu, Y. Qin, P. Tao, C. Song, W. Shang, ACS Energy Lett. 2018, 3, 2357. \n[4]\t B.  Zhang, X.  Zheng, O.  Voznyy, R.  Comin, M.  Bajdich, M.  GarcíaMelchor, L. Han, J. Xu, M. Liu, L. Zheng, Science 2016, 352, 333. \n[5]\t F. N. I. Sari, S. Abdillah, J.-M. Ting, Chem. Eng. J. 2021, 416, 129165. \n[6]\t P. Cai, J. Huang, J. Chen, Z. Wen, Angew. Chem., Int. Ed. 2017, 129, 4936. \n[7]\t Y.  Guo, T.  Park, J. W.  Yi, J.  Henzie, J.  Kim, Z.  Wang, B.  Jiang, Y. Bando, Y. Sugahara, J. Tang, Adv. Mater. 2019, 31, 1807134. \n[8]\t Y. Li, Z. Dong, L. Jiao, Adv. Energy Mater. 2020, 10, 1902104. \n[9]\t K.  Liu, C.  Zhang, Y.  Sun, G.  Zhang, X.  Shen, F.  Zou, H.  Zhang, Z. Wu, E. C. Wegener, C. J. Taubert, ACS Nano 2018, 12, 158. \n[10]\t Y.  Fan, S.  Ida, A.  Staykov, T.  Akbay, H.  Hagiwara, J.  Matsuda, K. Kaneko, T. Ishihara, Small 2017, 13, 1700099. \n[11]\t L.  Yu, Q.  Zhu, S.  Song, B.  McElhenny, D.  Wang, C.  Wu, Z.  Qin, J. Bao, Y. Yu, S. Chen, Z. Ren, Nat. Commun. 2019, 10, 5106. \n[12]\t E. A. Ahmad, G. Mallia, D. Kramer, A. R. Kucernak, N. M. Harrison, J. Mater. Chem. A 2013, 1, 11152. \n[13]\t Z. F.  Huang, J.  Wang, Y.  Peng, C. Y.  Jung, A.  Fisher, X.  Wang, Adv. Energy Mater. 2017, 7, 1700544. \n[14]\t H. Wang, M. Zhou, P. Choudhury, H. Luo, Appl. Mater. Today 2019, 16, 56. \n[15]\t S. Song, H. Pan, Z. Wang, B. Yang, Ceram. Int. 1984, 10, 143. \n[16]\t Y. Wang, H.-P. Cheng, J. Phys. Chem. C 2013, 117, 2106. \n[17]\t W.-J.  Yin, B.  Weng, J.  Ge, Q.  Sun, Z.  Li, Y.  Yan, Energy Environ. Sci. 2019, 12, 442. \n[18]\t W. G.  Hardin, D. A.  Slanac, X.  Wang, S.  Dai, K. P.  Johnston, K. J. Stevenson, J. Phys. Chem. Lett. 2013, 4, 1254. \n[19]\t X. Xu, W. Wang, W. Zhou, Z. Shao, Small Methods 2018, 2, 1800071. \n[20]\t J.  Kim, X.  Chen, P.-C.  Shih, H.  Yang, ACS Sustainable Chem. Eng. 2017, 5, 10910. \n[21]\t Y.  Lv, Z.  Li, Y.  Yu, J.  Yin, K.  Song, B.  Yang, L.  Yuan, X.  Hu, J. Alloys Compd. 2019, 801, 19. \n[22]\t J. Bian, Z. Li, N. Li, C. Sun, Inorg. Chem. 2019, 58, 8208. \n[23]\t B.-J.  Kim, E.  Fabbri, D. F.  Abbott, X.  Cheng, A. H.  Clark, M.  Nachtegaal, M.  Borlaf, I. E.  Castelli, T.  Graule, T. J.  Schmidt, J. Am. Chem. Soc. 2019, 141, 5231. \n[24]\t W. Xu, N. Apodaca, H. Wang, L. Yan, G. Chen, M. Zhou, D. Ding, P. Choudhury, H. Luo, ACS Catal. 2019, 9, 5074. \n[25]\t Y.  Xin, S.  Li, Y.  Qian, W.  Zhu, H.  Yuan, P.  Jiang, R.  Guo, L.  Wang, ACS Catal. 2020, 10, 11280. \n[26]\t J.  Suntivich, K. J.  May, H. A.  Gasteiger, J. B.  Goodenough, Y. Shao-Horn, Science 2011, 334, 1383. \n[27]\t A. Grimaud, K. J. May, C. E. Carlton, Y.-L. Lee, M. Risch, W. T. Hong, J. Zhou, Y. Shao-Horn, Nat. Commun. 2013, 4, 2439. \n[28]\t B. Hammer, J. K. Nørskov, Advances in Catalysis, Vol. 45, Academic Press, Cambridge, MA 2000, p. 71. \n[29]\t J. S. Yoo, X. Rong, Y. Liu, A. M. Kolpak, ACS Catal. 2018, 8, 4628. \n[30]\t D.  Wang, Z.  Liu, S.  Du, Y.  Zhang, H.  Li, Z.  Xiao, W.  Chen, R.  Chen, Y. Wang, Y. Zou, J. Mater. Chem. A 2019, 7, 24211. \n[31]\t Y. Zhang, W. Dai, P. Zhang, T. Lu, Y. Pan, J. Alloys Compd. 2021, 868, 159064. \n[32]\t T. Wang, J. Fan, C.-L. Do-Thanh, X. Suo, Z. Yang, H. Chen, Y. Yuan, H. Lyu, S. Yang, S. Dai, Angew. Chem. Int. Ed. 2021, 60, 1. \n[33]\t Y.  Duan, S.  Sun, S.  Xi, X.  Ren, Y.  Zhou, G.  Zhang, H.  Yang, Y.  Du, Z. J. Xu, Chem. Mater. 2017, 29, 10534. \n[34]\t A. A. Ansari, N. Ahmad, M. Alam, S. F. Adil, S. M. Ramay, A. Albadri, A. Ahmad, A. M. Al-Enizi, B. F. Alrayes, M. E. Assal, A. A. Alwarthan, Sci. Rep. 2019, 9, 7747. \n[35]\t D. Phadtare, S. Kondawar, A. Athawale, C. Rode, Mol. Catal. 2019, 475, 110496. \n[36]\t T. D.  Thanh, N. D.  Chuong, J.  Balamurugan, H.  Van Hien, N. H. Kim, J. H. Lee, Small 2017, 13, 1701884. \n[37]\t C. Battistoni, J. Dormann, D. Fiorani, E. Paparazzo, S. Viticoli, Solid State Commun. 1981, 39, 581. \n[38]\t F.  Capece, V.  Di Castro, C.  Furlani, G.  Mattogno, C.  Fragale, M. Gargano, M. Rossi, J. Electron Spectrosc. Relat. Phenom. 1982, 27, 119. \n[39]\t J.  Tang, S.  Ni, Q.  Chen, X.  Yang, L.  Zhang, J. Alloys Compd. 2017, 698, 121. \n[40]\t Z.  Wang, Y.  You, J.  Yuan, Y.-X.  Yin, Y.-T.  Li, S.  Xin, D.  Zhang, ACS Appl. Mater. Interfaces 2016, 8, 6520. \n[41]\t Z.  Dai, C.-S.  Lee, B.-Y.  Kim, C.-H.  Kwak, J.-W.  Yoon, H.-M.  Jeong, J.-H. Lee, ACS Appl. Mater. Interfaces 2014, 6, 16217. \n[42]\t L.  Armelao, G.  Bandoli, D.  Barreca, M.  Bettinelli, G.  Bottaro, A. Caneschi, Surf. Interface Anal. 2002, 34, 112. \n[43]\t D. Li, Y. Gong, Y. Zhang, C. Luo, W. Li, Q. Fu, C. Pan, Sci. Rep. 2015, 5, 12903. \n[44]\t W.  Wang, Y.  Liu, Y. J.  Zhong, L.  Wang, W.  Zhou, S.  Wang, M. O. Tadé, Z. Shao, Sol. RRL 2017, 1, 1700074. \n[45]\t Y.  Pan, X.  Xu, Y.  Zhong, L.  Ge, Y.  Chen, J.-P. M.  Veder, D.  Guan, R.  O’Hayre, M.  Li, G.  Wang, H.  Wang, W.  Zhou, Z.  Shao, Nat. Commun. 2020, 11, 2002. \n[46]\t C.-C. Lin, C. C. L. McCrory, ACS Catal. 2017, 7, 443. \n[47]\t Y. Yang, L. Dang, M. J. Shearer, H. Sheng, W. Li, J. Chen, P. Xiao, Y.  Zhang, R. J.  Hamers, S.  Jin, Adv. Energy Mater. 2018, 8, 1703189. \n[48]\t T. X. Nguyen, Y. H. Su, C. C. Lin, J. Ruan, J. M. Ting, Adv. Sci. 2021, 2002446. \n[49]\t X. Bo, Y. Li, X. Chen, C. Zhao, J. Power Sources 2018, 402, 381. \n[50]\t R.  Singh, J.  Singh, B.  Lal, M.  Thomas, S.  Bera, Electrochim. Acta 2006, 51, 5515. \n[51]\t J.  Melder, P.  Bogdanoff, I.  Zaharieva, S.  Fiechter, H.  Dau, P.  Kurz, Z. Phys. Chem. 2020, 1. \n[52]\t M. F.  Tesch, S. A.  Bonke, T. E.  Jones, M. N.  Shaker, J.  Xiao, K. Skorupska, R. Mom, J. Melder, P. Kurz, A. Knop-Gericke, Angew. Chem., Int. Ed. 2019, 131, 3464. \n[53]\t M.  Risch, K. A.  Stoerzinger, B.  Han, T. Z.  Regier, D.  Peak, S. Y. Sayed, C. Wei, Z. Xu, Y. Shao-Horn, J. Phys. Chem. C 2017, 121, 17682. \n[54]\t M. Kaur, M. Chhetri, C. Rao, Phys. Chem. Chem. Phys. 2020, 22, 811. \n[55]\t L.  Xi, C.  Schwanke, J.  Xiao, F. F.  Abdi, I.  Zaharieva, K. M.  Lange, J. Phys. Chem. C 2017, 121, 12003. \n[56]\t H.  Ooka, T.  Takashima, A.  Yamaguchi, T.  Hayashi, R.  Nakamura, Chem. Commun. 2017, 53, 7149. \n[57]\t T. Takashima, K. Hashimoto, R. Nakamura, J. Am. Chem. Soc. 2012, 134, 1519. \n[58]\t X. T.  Wang, T.  Ouyang, L.  Wang, J. H.  Zhong, T.  Ma, Z. Q.  Liu, Angew. Chem., Int. Ed. 2019, 131, 13425. \n[59]\t D.  Chen, J.  Wang, Z.  Zhang, Z.  Shao, F.  Ciucci, Chem. Commun. 2016, 52, 10739. \n[60]\t L. Han, S. Dong, E. Wang, Adv. Mater. 2016, 28, 9266. \n[61]\t X.  Liu, L.  Zhang, Y.  Zheng, Z.  Guo, Y.  Zhu, H.  Chen, F.  Li, P.  Liu, B. Yu, X. Wang, Adv. Sci. 2019, 6, 1801898. \n[62]\t Z.  Wang, Y.  You, J.  Yuan, Y.-X.  Yin, Y.-T.  Li, S.  Xin, D.  Zhang, ACS Appl. Mater. Interfaces 2016, 8, 6520. \n[63]\t Y.  Bi, Z.  Cai, D.  Zhou, Y.  Tian, Y.  Kuang, Y.  Li, X.  Sun, X.  Duan, J. Catal. 2018, 358, 100. \n[64]\t I.  Zaharieva, D.  González-Flores, B.  Asfari, C.  Pasquini, M. R.  Mohammadi, K.  Klingan, I.  Zizak, S.  Loos, P.  Chernev, H. Dau, Energy Environ. Sci. 2016, 9, 2433. \n[65]\t J. Kim, X. Yin, K.-C. Tsao, S. Fang, H. Yang, J. Am. Chem. Soc. 2014, 136, 14646. \n[66]\t Y. Zhu, L. Zhang, B. Zhao, H. Chen, X. Liu, R. Zhao, X. Wang, J. Liu, Y. Chen, M. Liu, Adv. Funct. Mater. 2019, 29, 1901783. \n[67]\t Y.  Lu, A.  Ma, Y.  Yu, R.  Tan, C.  Liu, P.  Zhang, D.  Liu, J.  Gui, ACS Sustainable Chem. Eng. 2018, 7, 2906. \n[68]\t S. She, J. Yu, W. Tang, Y. Zhu, Y. Chen, J. Sunarso, W. Zhou, Z. Shao, ACS Appl. Mater. Interfaces 2018, 10, 11715. \n[69]\t C. C. McCrory, S. Jung, J. C. Peters, T. F. Jaramillo, J. Am. Chem. Soc. 2013, 135, 16977. \n[70]\t J. Zhang, Y. Hu, D. Liu, Y. Yu, B. Zhang, Adv. Sci. 2017, 4, 1600343. \n[71]\t S.  Wannakao, T.  Maihom, K.  Kongpatpanich, J.  Limtrakul, V. Promarak, Phys. Chem. Chem. Phys. 2017, 19, 29540. \n[72]\t J.  Song, C.  Wei, Z.-F.  Huang, C.  Liu, L.  Zeng, X.  Wang, Z. J.  Xu, Chem. Soc. Rev. 2020, 49, 2196. \n[73]\t L. C. Ho, L. S. Uck, 2018. " + }, + { + "id": "10.1038_s41586-021-03983-5", + "DOI": "10.1038/s41586-021-03983-5", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-03983-5", + "Relative Dir Path": "mds/10.1038_s41586-021-03983-5", + "Article Title": "Roton pair density wave in a strong-coupling kagome superconductor", + "Authors": "Chen, H; Yang, HT; Hu, B; Zhao, Z; Yuan, J; Xing, YQ; Qian, GJ; Huang, ZH; Li, G; Ye, YH; Ma, S; Ni, SL; Zhang, H; Yin, QW; Gong, CS; Tu, ZJ; Lei, HC; Tan, HX; Zhou, S; Shen, CM; Dong, XL; Yan, BH; Wang, ZQ; Gao, HJ", + "Source Title": "NATURE", + "Abstract": "The transition metal kagome lattice materials host frustrated, correlated and topological quantum states of matter(1-9). Recently, a new family of vanadium-based kagome metals, AV(3)Sb(5) (A = K, Rb or Cs), with topological band structures has been discovered(10,11). These layered compounds are nonmagnetic and undergo charge density wave transitions before developing superconductivity at low temperatures(11-19). Here we report the observation of unconventional superconductivity and a pair density wave (PDW) in CsV3Sb5 using scanning tunnelling microscope/spectroscopy and Josephson scanning tunnelling spectroscopy. We find that CsV3Sb5 exhibits a V-shaped pairing gap Delta similar to 0.5 meV and is a strong-coupling superconductor (2 Delta/k(B)T(c) - 5) that coexists with 4a(0) unidirectional and 2a(0) x 2a(0) charge order. Remarkably, we discover a 3Q PDW accompanied by bidirectional 4a(0)/3 spatial modulations of the superconducting gap, coherence peak and gap depth in the tunnelling conductance. We term this novel quantum state a roton PDW associated with an underlying vortex-antivortex lattice that can account for the observed conductance modulations. Probing the electronic states in the vortex halo in an applied magnetic field, in strong field that suppresses superconductivity and in zero field above T-c, reveals that the PDW is a primary state responsible for an emergent pseudogap and intertwined electronic order. Our findings show striking analogies and distinctions to the phenomenology of high-T-c cuprate superconductors, and provide groundwork for understanding the microscopic origin of correlated electronic states and superconductivity in vanadium-based kagome metals.", + "Times Cited, WoS Core": 404, + "Times Cited, All Databases": 443, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000714336200002", + "Markdown": "# Article \n\n# Roton pair density wave in a strong-coupling kagome superconductor \n\nhttps://doi.org/10.1038/s41586-021-03983-5 \n\nReceived: 23 March 2021 \n\nAccepted: 1 September 2021 \n\nPublished online: 29 September 2021 \n\nCheck for updates \n\nHui Chen1,2,3,4,9, Haitao Yang1,2,3,4,9, Bin Hu1,2,9, Zhen Zhao1,2, Jie Yuan1,2, Yuqing Xing1,2, Guojian Qian1,2, Zihao Huang1,2, Geng Li1,2,3, Yuhan $\\yen12$ , Sheng $\\boldsymbol{\\mathsf{M}}\\boldsymbol{\\mathsf{a}}^{1,2}$ , Shunli ${\\mathsf{N i}}^{\\mathsf{1},2}$ , Hua Zhang1,2, Qiangwei Yin5, Chunsheng Gong5, Zhijun Tu5, Hechang Lei5, Hengxin Tan6, Sen Zhou2,3,7, Chengmin Shen1,2, Xiaoli Dong1,2, Binghai Yan6, Ziqiang Wang8 ✉ & Hong-Jun Gao1,2,3,4 ✉ \n\nThe transition metal kagome lattice materials host frustrated, correlated and topological quantum states of matter1–9. Recently, a new family of vanadium-based kagome metals, ${\\bf A}{\\bf V}_{3}{\\bf S}{\\bf b}_{5}$ ( $\\mathbf{A}=\\mathbf{K}$ , Rb or Cs), with topological band structures has been discovered10,11. These layered compounds are nonmagnetic and undergo charge density wave transitions before developing superconductivity at low temperatures11–19. Here we report the observation of unconventional superconductivity and a pair density wave (PDW) in $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ using scanning tunnelling microscope/spectroscopy and Josephson scanning tunnelling spectroscopy. We find that $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ exhibits a V-shaped pairing gap $\\pmb{\\mathscr{s}}-\\pmb{0.5}\\pmb{\\mathrm{meV}}$ and is a strong-coupling superconductor $(2\\varDelta/k_{\\mathrm{B}}T_{\\mathrm{c}}-5)$ that coexists with $4a_{0}$ unidirectional and $2a_{0}\\times2a_{0}$ charge order. Remarkably, we discover a 3Q PDW accompanied by bidirectional $4a_{0}/3$ spatial modulations of the superconducting gap, coherence peak and gap depth in the tunnelling conductance. We term this novel quantum state a roton PDW associated with an underlying vortex–antivortex lattice that can account for the observed conductance modulations. Probing the electronic states in the vortex halo in an applied magnetic field, in strong field that suppresses superconductivity and in zero field above $T_{\\mathrm{c}},$ reveals that the PDW is a primary state responsible for an emergent pseudogap and intertwined electronic order. Our findings show striking analogies and distinctions to the phenomenology of high- $T_{\\mathrm{c}}$ cuprate superconductors, and provide groundwork for understanding the microscopic origin of correlated electronic states and superconductivity in vanadium-based kagome metals. \n\nHigh-quality as-grown $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ crystals (Methods and Supplementary Fig. 1) exhibit a stacking structure of Cs–Sb2–VSb1–Sb2–Cs layers with hexagonal symmetry (space group P6/mmm; Fig. 1a). In the VSb1 layer, the kagome net of vanadium is interwoven with a simple hexagonal net formed by the Sb1 atoms (Fig. 1b). The Cs and Sb2 layers form hexagonal and honeycomb lattices, respectively (Fig. 1b). Samples were characterized and the bulk electronic properties were determined by temperature-dependent magnetization, resistivity and heat capacity (Methods). All measurements indicate the presence of an anomaly at $T\\sim94\\mathsf{K}$ (Supplementary Fig. 2) associated with the charge density wave (CDW) transition11,17. At low temperatures, the magnetization, resistivity and heat capacity measurements show a transition to the superconducting (SC) state at a critical SC temperature $(T_{\\mathrm{c}})$ of ${\\it-}2.8\\mathsf{K}$ . The higher $T_{\\mathrm{c}},$ compared with the one reported in the literature $(2.5{\\mathsf{K}})^{11}$ , is consistent with the high quality of the as-grown $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ sample, which provides the opportunity for a deeper understanding of the nature of superconductivity and coexisting electronic order through atomically resolved scanning tunnelling microscope/spectroscopy (STM/STS). In the STM measurements at $4.2\\mathsf{K}$ , we observe both types of surface (Fig. 1c, d). On the basis of the atomically resolved STM image combined with the crystal structure, we identify the two cleaved terminations as ${\\sqrt{3}}\\times{\\sqrt{3}}R30^{\\circ}$ reconstructed Cs surface and $1\\times15\\mathsf{b}$ surface (Methods and Extended Data Fig. 1). In this work, the STM/STS imaging of the density waves is conducted on large and clean areas of the Sb surfaces (Fig. 1e). \n\n# Unconventional strong-coupling superconductor \n\nWe first study the SC ground state using the STS procedure described in the Methods at an electron temperature of $300\\mathrm{mK}$ (see calibration of electron temperatures in Supplementary Fig. 3). We observe particle– hole symmetric differential conductance (dI/dV) near the Fermi level $(E_{\\mathsf{F}})$ . \n\n![](images/5f7e8efd8cba1a2359dff66194e14498f35eec8e73193f197215b6ebb0d96c7e.jpg) \nFig. 1 | Atomic structures and the surface identification of the $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ . a, 3D c showing the lattice orientation between the Cs surface and Sb surface view of the crystal structure, showing stacking of Cs–Sb2–VSb1–Sb2–Cs layers $(V_{s}=-0.5\\:\\mathrm{V},I_{\\mathrm{t}}=50\\:0\\:\\mathrm{pA)}$ . Bottom panel: schematic atomic structures of the Sb with hexagonal symmetry. b, Atomic structures of VSb, Cs and Sb layers. and Cs surfaces, showing $\\lfloor\\times1$ and ${\\sqrt{3}}\\times{\\sqrt{3}}R30^{\\circ}$ reconstructed structures, c, Atomically resolved STM image, showing the atomic structures of the Cs respectively. e, STM image of a large and clean Sb surface $(V_{s}=-2.0{\\ V},$ surface and the Sb surface, respectively $(V_{s}=-1.0\\:\\mathrm{V},I_{\\mathrm{t}}=10\\:0\\:\\mathrm{pA})$ ). d, Zoom-in of $I_{\\mathrm{t}}{=}100\\ \\mathsf{p A})$ . \n\nThe spatially averaged dI/dV spectra (Fig. 2a) show the V-shaped gap on both Cs and Sb surfaces with two gap-edge peaks at energies symmetric with respect to $\\boldsymbol{E}_{\\mathrm{F}}$ . The $\\mathsf{V}$ -shaped gap is consistent with the gap nodes seen in conductivity measurements19, but the nonzero local density of states (LDOS) at zero bias, lower on the Sb than on the Cs surface (Supplementary Fig. 4), indicates additional in-gap quasiparticle states possibly due to line nodes or ungapped Fermi surface sections. From the dI/dV spectra collected over nearly fifty $30\\mathrm{nm}\\times30\\mathrm{nm}$ regions, we obtain the average SC gap size (Δ) $\\cdot0.52\\pm0.1$ meV (Supplementary Fig. 5). The temperature evolution of the dI/dV spectra on the Cs surface (Fig. 2b) shows that the V-shaped gap reduces with increasing electron temperature and vanishes around ${\\sim}2.3\\mathsf{K}$ . \n\nAs the suppression of the LDOS near $E_{\\mathrm{{F}}}$ can arise from physics other than superconductivity20,21, it is crucial to directly probe the superfluid for SC phase coherence. We thus construct a Josephson STM (Fig. 2c) by fabricating a SC Nb STM tip (Methods and Supplementary Fig. 6). A sharp zero-bias peak with two negative differential conductance dips is observed due to Josephson tunnelling of Cooper pairs (Fig. 2d), which provides strong evidence that the $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ surface is in the SC phase (Supplementary Fig. 7). The temperature-dependent dI/dV spectra are then obtained (Fig. 2e, f). When the electron temperature increases to about $900\\mathrm{mK}$ , two sets of peaks can be clearly resolved with particle– hole symmetry. The outer peaks correspond to the sum $\\pmb{\\Delta}_{\\mathrm{tip}}+\\pmb{\\Delta}_{\\mathrm{sample}}$ of the paring gaps in the tip and the sample, while the inner peaks relate to the difference $\\pmb{\\Delta}_{\\mathrm{tip}}-\\pmb{\\Delta}_{\\mathrm{sample}}$ . On further increasing the temperature, the inner peaks disappear at a transition temperature of ${\\sim}2.3\\mathsf{K}$ , leaving the two remaining peaks from $\\Delta_{\\mathrm{tip}}$ . As the $T_{\\mathrm{c}}$ of the Nb tip is higher than $4.2\\mathsf{K}$ (Supplementary Fig. 6), the transition indicates that superconductivity in the sample is completely suppressed at this temperature. The SC gap of the sample is in excellent agreement with the value measured by the normal W tip. We thus conclude that the observed V-shaped gap (Fig. 2a) is the SC gap that opens at $T_{\\mathrm{c}}\\cdot2.3\\mathsf{K}$ on the surface of the $\\mathrm{CsV}_{3}\\mathsf{S}\\mathsf{b}_{5}.$ The V-shaped SC gap with nonzero LDOS at $\\boldsymbol{E}_{\\mathrm{F}}$ is strongly indicative of unconventional superconductivity22,23. Moreover, the measured gap–to– $T_{\\mathrm{c}}$ ratio $2\\varDelta/k_{\\mathrm{B}}T_{\\mathrm{c}}{\\sim}5.2$ puts the unconventional superconductor in the strong-coupling regime. \n\n# Coexisting CDWs \n\nWe next probe the spatial distribution of the off-diagonal long-rangeordered quantum states using the high-resolution STM/STS at an electron temperature of $300\\mathrm{mK}$ , well below $T_{\\mathrm{c}}$ . As the Cs atoms are unstable on the Cs-terminated surface and strongly affect the tip states, we perform the measurements on the Sb surface directly above the V kagome plane (Fig. 1e). The STM topography (Fig. 3a) over a large $70\\mathrm{nm}\\times70$ nm area (Methods) shows periodic modulations indicating the presence of CDWs. The corresponding Fourier transform after the Lawler–Fujita drift correction24,25 (Methods) reveals, in addition to the atomic Bragg peaks $\\mathbf{0}_{\\mathrm{Bragg}}^{(a,b)}$ of the pristine Sb lattice, two sets of new peaks (Fig. 3b). One set comprises six hexagonal wavevectors at $\\mathbf{\\dot{Q}}_{3\\mathrm{q}\\cdot2a}=\\mathbf{\\Gamma}_{2}^{1}\\mathbf{\\bar{Q}}_{\\mathrm{Bragg}}^{(a,b)}$ ., cTohrereostpheornsdeitnigstaot au $2a_{0}\\times2a_{0}$ asvuepvercstroursc tmuraer koendtbhye ${\\bf Q}_{\\mathrm{1q-4}a}={\\textstyle\\frac{1}{4}}{\\bf Q}_{\\mathrm{Bragg}}^{a}$ QBaragg, corresponding to unidirectional 4a0 modulations. These robust modulations are clearly visible in the topography (Fig. 3a, inset) and suggest the coexistence of superconductivity with $2a_{0}$ bidirectional and $4a_{0}$ unidirectional positional and rotational order (that is, a smectic state in the language of liquid crystals26,27). The dI/dV(r, V) conductance map at $V=-5\\mathsf{m V}$ over the same field of view (Fig. 3c) and the corresponding Lawler–Fujita drift-corrected Fourier transform (Fig. 3d) reveal the outstanding $\\mathbf{Q}_{3\\mathrm{q}\\cdot2a}$ and $\\mathbf{Q}_{19^{-4a}}$ peaks and the quasiparticle interference (QPI) patterns. The Bogoliubov QPI patterns in the SC state are notably different, but with certain unidirectional features similar to the normal-state QPI (ref. 14). Acquiring additional dI/dV maps and Fourier transforms at different bias energies and over different regions (two examples are shown in Fig. 3e, f around the SC gap energy), we find that the two sets of peaks at $\\mathbf{Q}_{3\\mathbf{q}\\cdot2a}$ and $\\mathbf{Q}_{1\\l9^{-4a}}$ in dI/dV maps are nondispersive in energy (Fig. $3\\mathbf{g}$ , Extended Data Fig. 2 and Supplementary Fig. 8). We thus conclude that $2a_{0}\\times2a_{0}$ and $4a_{0}$ unidirectional CDWs14 coexist with superconductivity, giving rise to the smectic superconductor. \n\n# 3Q PDW with $\\pmb{4a_{0}}/3$ period \n\nA striking feature of the dI/dV maps, absent in the topography (Fig. 3b), $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}=\\frac{3}{4}\\mathbf{Q}_{\\mathrm{Bragg}}^{(a,b)}$ airnetdhiestFionucrtiferotrmatnhsfeournmia(xFiagl. .dNeostpeitehtahtethoev3erQ$\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ ${\\bf Q}_{19^{-4a}},$ lap with a higher harmonic of $\\mathbf{Q}_{1\\mathbf{q}\\cdot4a}$ along the ${\\pmb q}_{a}$ direction. These peaks do not exist in the dI/dV maps at energies much higher than the SC gap energy (Extended Data Fig. 3). They suggest an emergent $4a_{0}/3$ bidirectional 3Q electronic modulation without long-range charge order. The $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ peaks are nondispersive at low energies around the \n\n![](images/dcf7a3632f78f25cf2cb54e27f5664c51909c883ca86ebc41b0c06a47769bb04.jpg) \nFig. 2 | V-shaped pairing gap and the Josephson effect observed using a SC STM tip on the Cs and Sb surfaces. a, Spatially averaged dI/dV spectra obtained on the Cs and Sb surfaces over a $30\\mathrm{nm}\\times30$ nm region with a small defect density at $300\\mathrm{mK}$ , showing a particle–hole symmetric V-shaped gap near $E_{\\mathrm{{F}}}$ and nonzero LDOS at zero bias $(V_{s}=-2\\:\\mathrm{mV},I_{\\mathrm{t}}=1\\:\\mathrm{nA}$ , $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V})$ . b, Colour map of temperature-dependent dI/dV spectra obtained on the Cs surface, showing that the V-shaped gap reduces with increasing electron temperature and vanishes around \\~2.3 K (dashed white line; $V_{\\mathrm{s}}{=}{-}2\\mathsf{m}\\mathsf{V},I_{\\mathrm{t}}{=}1\\mathsf{n}\\mathsf{A}$ , $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V})$ . c, Schematic diagram showing the Josephson STM on the $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ surface using a SC (Nb) tip. \nd, A series of dI/dV spectra with the tip approaching towards the sample surface. A sharp zero-bias peak with two negative differential conductance dips is observed, providing strong evidence that the $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ is in the SC phase $(V_{s}=-2.5\\mathsf{m V}$ , $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V})$ . e, Temperature-dependent dI/dV spectra on the Cs surface using a Nb tip at a relatively small tip approaching distance where the zero-bias peak is still present, showing two energy gaps at $\\pmb{\\Delta}_{\\mathrm{tip}}+\\pmb{\\Delta}_{\\mathrm{sample}}$ and $\\varDelta_{\\mathrm{tip}}-\\varDelta_{\\mathrm{sample}},$ respectively $(V_{s}{=}{-}2.5\\operatorname{mV},I_{\\mathrm{t}}{=}20\\operatorname{nA}$ , $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V};$ . f, Colour map of the dI/dV spectra in e, showing the transition temperature of the $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ sample around \\~2.3 K $(V_{\\mathrm{s}}=-2.5\\:\\mathrm{mV},I_{\\mathrm{t}}=20\\:\\mathrm{n}$ A, $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V})$ . \n\nSC gap (Fig. 3g), indicating the possible formation of a primary 3Q PDW. This is in contrast to the long-range CDWs at $\\mathbf{Q}_{3\\mathrm{q}\\cdot2a}$ and $\\mathbf{Q}_{19^{-4a}}$ that induce subsidiary PDWs at the same wavevectors in the SC condensate28–34. The $\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},0.4\\:\\mathrm{mV})$ map after Fourier filtering of atomic Bragg peaks at $\\mathbf{Q}_{\\mathrm{Bragg}}$ and noise from the small- $\\cdot q$ quasiparticle scattering (Supplementary Fig. 9) reveals the spatial pattern of the PDW (Fig. 3h). A hexagonal pattern of the bidirectional PDW with period $4a_{0}/3$ (Supplementary Fig. 9) is clearly observed in the background of the $4a_{0}$ charge stripes. \n\n# Spatial modulations of SC at the PDW wavevector \n\nTo investigate the properties of the PDW and its effects on superconductivity, we measure the $\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},V)$ spectra along a linecut parallel to the $4a_{0}$ stripes indicated in the topography (Fig. 3i). This direction corresponds to the ${\\pmb q}_{b}$ direction in reciprocal space (Fig. 3b), and thus avoids the $4a_{0}$ modulations due to the unidirectional charge order. The spatial evolution of the differential conductance (Fig. 3j) displays intricate modulations in the SC gap Δ(r), the coherence peak height at the gap edge and the zero-bias conductance. To extract quantitative information, we take the second derivative of each conductance curve: ${\\cal D}({\\bf r},V)=-{\\bf d}^{3}I/$ $\\mathsf{d}V^{3}(\\mathbf{r},V)$ . The peaks in $D(\\boldsymbol{\\mathsf{r}},\\boldsymbol{V})$ along the cut (Fig. 3k) determine accurately the coherence peak locations (especially at negative bias) and the SC gap Δ(r), as in a recent study of the PDW modulation of the SC coherence in underdoped cuprates29. The spatial modulation of the local SC gap $\\pmb{\\varDelta}(\\mathbf{r})$ (Fig. 3l), having an amplitude of the order of $7\\%$ of the average gap, is clearly visible with underlying periodicities. Its Fourier spectrum (Fig. 3l) displays pronounced peaks at $\\frac{3}{4}\\mathbf{Q}_{\\mathrm{Bragg}}$ associated with the PDW, in addition to the Bragg peak at $\\mathbf{Q}_{\\mathrm{Bragg}}$ and the $2a_{0}\\mathsf{C D W}$ peak at $\\scriptstyle{\\frac{1}{2}}\\mathbf{Q}_{\\mathrm{Bragg}}.$ The modulation of the SC gap further supports the identification of the $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ peaks in the dI/dV maps (Fig. 3e, f) with the 3Q PDW coupled to the SC condensate. More data, including the SC gap maps acquired in different regions exhibiting $\\mathbf{Q}_{3\\mathrm{q}\\cdot4a/3}$ peaks in the Fourier transforms, are presented in Supplementary Figs. 10 and 11. \n\nTo demonstrate the modulation of the SC coherence by the PDW, we determine from the conductance spectrum (Fig. 3j) the coherence peak height at the gap edge: $P(\\mathbf{r})=\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},+\\varDelta(\\mathbf{r}))$ , the zero-bias conductance $G_{0}(r)={\\mathrm{d}}I/{\\mathrm{d}}V(\\mathbf{r},0)$ and the gap depth $H(\\mathbf{r})=P(\\mathbf{r})-G_{0}(\\mathbf{r})$ . The raw data for $P(\\mathbf{r}),H(\\mathbf{r})$ and $G_{0}(\\mathbf{r})$ (Fig. $3\\mathsf{m})$ display intriguing periodic modulations along the linecut. Remarkably, the modulations of the coherence peak $P(\\mathbf{r})$ and zero-bias conductance $G_{0}(\\mathbf{r})$ are out of phase (Fig. $3\\mathsf{m}$ and Supplementary Fig. 12a), leading to in-phase modulations of the coherence peak $P(\\mathbf{r})$ and gap depth $H(\\mathbf{r})$ . As a higher coherence peak in STS usually reflects a higher superfluid density29, the correlated modulations among $P(\\mathbf{r}),H(\\mathbf{r})$ and $G_{0}(\\mathbf{r})$ amount to a concomitant deeper SC gap and less normal fluid density, demonstrating an unprecedented electronic density wave modulation of superconductivity. After filtering out atomic Bragg oscillations and small- $\\cdot q$ noise due to quasiparticle scattering from the raw data, the spatial modulation of the coherence peak height $P(\\mathbf{r})$ and the SC gap depth $H(\\mathbf{r})$ exhibit remarkable beating patterns of two primary frequencies corresponding to the leading bidirectional $4a_{0}/3$ PDW and a weaker $2a_{0}\\mathsf{C D W}$ (Fig. 3n and Supplementary Fig. 12b). These results demonstrate that the emergent PDW involves both the superfluid and the normal fluid, such that the total electron density in the ground state is only weakly perturbed at the bidirectional Q3q-4a/3. \n\n![](images/ceb66addac4fe76efa7d9f854223ab928a8e037ce349814a2f25b590d65e7914.jpg) \nFig. 3 | STM topography, dI/dV map and linecut at $300\\ \\mathrm{mK}$ revealing CDW, PDW and spatial modulations of superconductivity on Sb surfaces. \n\na, b, The large-scale STM topography of the Sb surface (a) and the magnitude of the drift-corrected, two-fold symmetrized Fourier transform (b), showing wavevectors $\\mathbf{Q}_{3\\mathbf{q}\\cdot2a}$ for $2\\times2\\mathsf{C D W}$ and $\\mathbf{Q}_{19^{.4a}}$ for $4a_{0}$ unidirectional charge order $(V_{\\mathrm{s}}=-10\\:\\mathrm{mV},I_{\\mathrm{t}}=500\\:\\mathrm{pA})$ . The inset in a shows a zoom-in of the outlined area, exhibiting an atomically resolved STM image $(V_{s}=-5\\:\\mathrm{mV},I_{\\mathrm{t}}=1\\:\\mathrm{nA})$ . c, d, dI/dV(r, $-5\\mathsf{m V},$ ) map (c) and the magnitude of the drift-corrected, two-fold symmetrized Fourier transform (d), revealing new 3Q PDW modulations at $\\mathbf{Q}_{3\\mathrm{q}\\mathrm{-}4\\mathrm{a}/3}(V_{\\mathrm{s}}=-5\\mathsf{m V},I_{\\mathrm{t}}=1\\mathsf{n A}$ , $V_{\\mathrm{mod}}=0.2\\:\\mathrm{mV})$ ). e, f $\\dot{,}\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},-0.25\\mathsf{m}\\mathbf{V})$ (e) and $\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},-0.75\\mathrm{mV})$ (f) maps (top) and the magnitude of the drift-corrected Fourier transforms (bottom) over a different region from a. Besides the $\\mathbf{Q}_{3\\mathbf{q}\\cdot2a}$ and $\\mathbf{Q}_{\\mathrm{{lq}}\\cdot4a}$ charge-ordered states present in the topography, the new 3Q PDW modulations at $\\mathbf{Q}_{3\\mathrm{q}\\cdot4a/3}$ can also be observed $(V_{s}=-5\\:\\mathrm{mV},I_{t}=1\\:\\mathrm{nA}$ , $V_{\\mathrm{mod}}=0.2\\:\\mathrm{mV})$ ). g, Energy dependence of the Fourier linecuts along the ${\\pmb q}_{a}$ (top) and ${\\pmb q}_{b}$ (bottom) directions as a function of energy, showing non-dispersive ordering vectors at $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ . h $,\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},V)$ map near the pairing gap at $0.4\\mathrm{mV}$ , after filtering out atomic Bragg peaks and incoherent background, exhibiting a $4a_{0}/3$ checkerboard modulation associated with the bidirectional PDW. i, Atomically resolved STM image displaying the $\\mathbf{Q}_{\\mathrm{1q}\\cdot4a}$ spatial modulation $(V_{s}=-90\\mathrm{mV}_{\\it s}$ $I_{\\mathrm{t}}=2\\mathsf{n}\\mathsf{A},$ . j, k, Evolution of the differential conductance dI/dV(r, V) ( j) and the negative of its second derivative $D({\\bf r},V)=-\\mathbf{d}^{3}I/\\mathbf{d}V^{3}({\\bf r},V)\\cdot$ (k) along the linecut in the ${\\pmb q}_{b}$ direction marked by the blue arrow in i, respectively $(V_{s}=-1\\mathsf{m V},I_{\\mathrm{t}}=1\\mathsf{n A}$ , $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V})$ . l, Plot of 2∆(r) (left) and the corresponding Fourier spectrum (right), showing the $4a_{o}/3$ spatial modulation highlighted by the pink dashed line marking $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ Black dashed lines in right panel denote the every quarter q spacing. m, Spatial modulations of coherence peak height $P(\\mathbf{r})$ , SC gap depth $H(\\mathbf{r})$ and zero-bias conductance $G_{0}(\\mathbf{r})$ , the black dashed lines are for eye-guide. The spectra are offset for clarity. n, Beating pattern simulated using $\\mathbf{Q}_{3\\mathbf{q}\\cdot2a}$ (green curve) and $\\mathbf{Q}_{3\\mathrm{q}\\cdot4a/3}$ (pink curve), showing consistency with Bragg-filtered modulations of $P(\\mathbf{r})$ and $H(\\mathbf{r})$ . \n\n![](images/aed1e82e768ceb28e17f3fff663b120355778e5e3fec347693ddba61718fb1d0.jpg) \nFig. 4 | PDW and pseudogap in $\\mathbf{csv}_{3}\\mathbf{sb}_{5}$ in magnetic fields at 300 mK and in zero field at 4.2 K. a, dI/dV(r, 0) map of the Sb surface in a 0.04 T magnetic field at $300\\mathrm{mK}$ , showing the vortex lattice $(V_{s}=-1\\:\\mathrm{mV},I_{\\mathrm{t}}=1\\:\\mathrm{nA}$ , $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V})$ . $\\mathbf{b},\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},-5\\mathrm{mv}$ ) map in the vortex halo marked by the blue square in a $(V_{s}=-5$ $\\boldsymbol{\\mathsf{m V}},\\boldsymbol{I_{\\mathrm{t}}}=\\boldsymbol{1\\mathsf{n A}}$ , $V_{\\mathrm{mod}}=0.2\\:\\mathrm{mV};$ ). c, The magnitude of the drift-corrected, two-fold symmetrized Fourier transform of b. d, e, $\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},-5\\mathrm{mV})$ map and the magnitude of the drift-corrected, two-fold symmetrized Fourier transform in a \n2.0 T at $300\\mathrm{mK}$ $(V_{s}=-5\\:\\mathrm{mV},I_{\\mathrm{t}}=1\\:\\mathrm{nA}$ , $V_{\\mathrm{mod}}=0.2\\:\\mathrm{mV}.$ ). f, g, dI/dV(r, $-5\\mathsf{m V}$ ) map under zero field at 4.2 K and the magnitude of the drift-corrected, two-fold symmetrized Fourier transform $(V_{s}=-5\\:\\mathrm{mV},I_{\\mathrm{t}}=1\\:\\mathrm{nA}$ , $V_{\\mathrm{mod}}=0.2\\:\\mathrm{mV},$ . h, Spatially averaged dI/dV spectra over the region marked in a obtained under different physical conditions of magnetic field and temperature, showing the spectral changes and the presence of the low-energy pseudogap $(V_{s}=-10\\:\\mathrm{mV},I_{\\mathrm{t}}=1\\:\\mathrm{nA}_{\\mathrm{.}}$ $V_{\\mathrm{mod}}=50\\upmu\\mathrm{V},$ . The spectra are offset for clarity. \n\nThe observation of the PDW at $\\mathbf{Q}_{\\mathrm{pdw}}=\\mathbf{Q}_{3\\mathrm{q}\\cdot4a/3}$ in the superconductor is consistent with the existence of a shallow roton minimum at the same wavevector $\\mathbf{Q}_{\\mathrm{roton}}=\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ in the dynamical density–density response function of the superfluid (Extended Data Fig. 4). The roton gap protects the superfluid from crystallization, allowing only shortranged charge density correlations. The 3Q PDW is described by an inhomogeneous order parameter $\\begin{array}{r}{\\varDelta_{\\mathrm{pdw}}(\\mathbf{r})=\\sum_{\\alpha}\\varDelta_{\\mathbf{Q}_{\\mathrm{p}}^{\\alpha}}(\\mathbf{r})}\\end{array}$ , where $\\Delta_{\\mathbf{Q}_{\\mathrm{p}}^{\\alpha}}(\\mathbf{r}){=}\\varDelta_{\\alpha}$ c $\\cos(\\mathbf{Q}_{\\mathrm{p}}^{\\alpha}\\cdot\\mathbf{r}-\\phi_{\\alpha})$ and $\\mathbf{0}_{\\mathrm{p}}^{\\alpha},$ $\\scriptstyle\\alpha=1$ , 2, 3, are the momenta corresponding to $\\mathbf{Q}_{3\\mathrm{q}\\cdot4a/3}$ in the 3Q directions and $\\phi_{\\alpha}$ is a relative phase. Below $T_{\\mathrm{c}},$ it couples to the uniform SC condensate $\\pmb{\\varDelta}_{\\mathrm{sc}}$ Thus, the intertwined density wave order has the character of delocalized Cooper pair excitations and localized charge excitations. To stress this distinction, we refer to this novel quantum state as a roton PDW, without implying direct observation of roton excitations, which may be visible in the conductance spectrum at higher energies through mode coupling. In this scenario, the low-energy excitations involve both gapless quasiparticles and roton PDW excitations. As a roton is a bound vortex– antivortex pair35–38, the roton PDW can be viewed as a commensurate hexagonal vortex–antivortex lattice (Extended Data Fig. 4) from the zeroes in the complex PDW order parameter $\\boldsymbol{\\varDelta}_{\\mathrm{pdw}}(\\mathbf{r})$ that coexists with the uniform component of the SC order parameter $\\ensuremath{\\Delta_{\\mathrm{sc}}}$ . Such an unconventional SC state necessarily breaks the time-reversal symmetry, exhibiting spontaneous phase windings associated with $\\ensuremath{\\Delta_{\\mathrm{pdw}}}(\\ensuremath{\\mathbf{r}})$ and unconventional SC vortices30,33. The roton PDW provides a qualitative explanation for our observations. The low-energy states inside the $\\upnu$ -shaped SC gap (Fig. 2a) are composed of both localized vortex– antivortex core states and itinerant nodal quasiparticles contributing to the observed thermal transport19. The spatial modulation of the coherence peak height and zero-bias conductance can be accounted for by those in the local superfluid density and the anti-correlated normal fluid density on the vortex–antivortex lattice (Extended Data Fig. 4) under weak modulations of the SC gap. \n\n# PDW as a ‘mother state’ and emergent pseudogap \n\nWe further investigate the nature of the PDW by applying a magnetic field along the $c$ axis. The magnetic-field-dependent dI/dV spectra on the Sb surface away from field-induced vortices show that the SC gap is gradually reduced with increasing field and vanishes at about 2 T (Supplementary Fig. 13). At 0.04 T, we observed SC vortices (Supplementary Fig. 14). Figure 4a centres on a vortex in the hexagonal vortex lattice. In the vortex halo marked in Fig. 4a, we obtain the $\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},-5\\boldsymbol{\\mathrm{mv}})$ map (Fig. 4b). The Fourier transform shows that the 3Q PDW at $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ survives in the vortex halo, with split peaks (Fig. 4c). \n\nIn contrast to the cuprates, where the $8a_{0}$ PDW appears only in the vortex halo with suppressed but nonzero superconductivity33,39, the $4a_{0}/3$ roton PDW is strong enough to emerge both in the vortex halo and in the fully fledged superconductor in zero field. When the magnetic field is raised to $2\\mathsf{T},$ the SC gap disappears and superconductivity is suppressed at $300\\mathrm{mK}$ (Supplementary Fig. 13). The $\\mathrm{d}I/\\mathrm{d}V(\\mathbf{r},-5\\mathrm{mV})$ map and the Fourier transform (Fig. 4d, e) show that, while the QPI pattern changes substantially, all of the density wave peaks remain including the $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ associated with the $4a_{0}/3$ PDW. With superconductivity removed by the magnetic field, these coexisting density waves define a ‘zero-temperature’ pseudogap phase with a suppression of the LDOS over $\\pm5$ meV in the spatially averaged dI/dV spectrum shown in Fig. 4h. In contrast to the $1\\times4$ and $2\\times2\\mathsf{C D W}$ peaks that exist at all energies, the nondispersive $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ peaks are visible only in the energy range of the pseudogap $\\left(\\sim\\pm5\\mathrm{meV}\\right)$ and are absent at higher energies (Extended Data Fig. 3). This suggests an intriguing possibility that the observed $4a_{0}/3$ 3Q PDW is a ‘mother state’ responsible for the pseudogap, as proposed in theories of the cuprates32,40. A Ginzburg–Landau analysis (see Methods “Discussions of PDW as a ‘mother state’”) shows that, owing to the hexagonal symmetry, the 3Q PDW induces a secondary 3Q CDW of identical period, giving rise to an intertwined electronic order at $\\mathrm{Q}_{3\\mathrm{q}\\cdot4a/3}$ as the ‘mother state’ responsible for the pseudogap. We have identified the PDW pseudogap with the energy of the peak in the LDOS near $5\\mathsf{m V}$ in the SC state at $300\\mathrm{mK}$ (Methods and Extended Data Fig. 5) and acquired the pseudogap map, which indeed exhibits spatial gap modulations with Fourier peaks at the PDW vector $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ . \n\nFinally, we warmed up the sample to the normal state above $T_{\\mathrm{c}}$ and acquired dI/dV maps (Fig. 4f) in the same region at $4.2\\mathsf{K}$ . The corresponding Fourier transform (Fig. 4g) shows modified QPI patterns from the SC state at $300\\mathrm{mK}$ (Fig. 3d) due to the closing of the SC gap. The PDW peaks at $\\mathbf{Q}_{3\\mathbf{q}\\cdot4a/3}$ are more diffused, but clearly present, demonstrating that the PDW and the intertwined electronic order persist to the normal state. The spatially averaged dI/dV spectrum at $4.2\\mathsf{K}$ (Fig. 4h) indeed exhibits a broad incoherent normal-state pseudogap correlated with the primary PDW over the energy range $\\mathord{\\sim}\\pm5$ meV. The comparison of the averaged dI/dV spectra (Fig. 4h) obtained in different states including the SC state at $\\begin{array}{r}{0\\mathsf{T},}\\end{array}$ the vortex halo at $0.04{\\sf T},$ the ‘zero-temperature’ pseudogap state at 2 T and $300\\mathrm{mK}$ , and the normal-state pseudogap phase at $4.2\\mathsf{K}$ reveals a rather consistent and enlightening picture of the interplay between superconductivity, the primary PDW, the intertwined density waves and the pseudogap with striking analogy and distinction to the physics of the high- $T_{\\mathrm{c}}$ cuprates. \n\nThe dI/dV map and Fourier transform (Fig. 4f, g) indicate that $2a_{0}\\times2a_{0}$ CDW and $4a_{0}$ unidirectional charge order persist above the SC transition. The properties of the CDWs in the normal state, discussed in more detail in the Methods together with our density functional theory (DFT) calculations (Extended Data Fig. 6 and Supplementary Figs. 15 and 16), are in good agreement with the recent STM work14. The angle-dependent magnetoresistance measurements reveal a twofold resistivity anisotropy (Extended Data Fig. 7) with a sharp onset below ${\\displaystyle-50~}\\mathsf{K}$ , which matches well with the onset temperature $T_{\\mathrm{stripe}}\\sim50\\mathsf{K}$ of the $4a_{0}$ stripes detected by $\\mathsf{S T M}^{14}$ . This suggests an incipient rotational-symmetry-breaking bulk electronic state below $T_{\\mathrm{stripe}},$ which can be either a quasi-three-dimensional (3D) $4a_{0}$ stripe phase with interlayer coupling, or a different state that manifests as the $4a_{0}$ unidirectional charge order on the Sb-terminated surface of $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ . \n\nUnconventional superconductivity can arise in model calculations from local and extended electron correlations on the kagome lattice41–43. We stress, however, that the physics discovered here goes well beyond $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ being another candidate unconventional superconductor. It embodies a set of highly provoking quantum electronic states and excitations that show striking analogies and distinctions and may hold the common set of keys to resolve some of the outstanding issues in the cuprate high- $T_{\\mathrm{c}}$ superconductors, including smectic electronic liquid crystal states, the interplay among PDW, CDW and intertwined electronic order, and their impact on the pseudogap phenomenon and unconventional superconductivity. Our findings provide groundwork and insights for future studies on how the unconventional SC state, the roton PDW and the coexisting charge order originate microscopically from the correlated $Z_{2}$ topological kagome bands, and on the prospects of emergent topological superconductivity in ${\\bf A}{\\bf V}_{3}{\\bf S}{\\bf b}_{5}$ . \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-03983-5. \n\n1. Ye, L. D. et al. Massive Dirac fermions in a ferromagnetic kagome metal. Nature 555, 638–642 (2018). \n2. Yin, J. X. et al. Giant and anisotropic many-body spin–orbit tunability in a strongly correlated kagome magnet. Nature 562, 91–95 (2018). \n3. Liu, Z. et al. Orbital-selective Dirac fermions and extremely flat bands in frustrated kagome-lattice metal CoSn. Nat. Commun. 11, 4002 (2020). \n4. Morali, N. et al. Fermi-arc diversity on surface terminations of the magnetic Weyl semimetal $\\mathsf{C o}_{3}\\mathsf{S}\\mathsf{n}_{2}\\mathsf{S}_{2}$ . Science 365, 1286–1291 (2019). \n5. Liu, D. F. et al. Magnetic Weyl semimetal phase in a Kagomé crystal. Science 365, 1282–1285 (2019). \n6. Kuroda, K. et al. Evidence for magnetic Weyl fermions in a correlated metal. Nat. Mater. 16, 1090 (2017). Yin, J. X. et al. Quantum-limit Chern topological magnetism in ${\\mathsf{T b M n}}_{6}{\\mathsf{S n}}_{6}$ Nature 583, 533–536 (2020). \n8. Yin, J.-X. et al. Negative flat band magnetism in a spin–orbit-coupled correlated kagome magnet. Nat. Phys. 15, 443–448 (2019). \n9. Xing, Y. et al. Localized spin-orbit polaron in magnetic Weyl semimetal $\\mathsf{C o}_{3}\\mathsf{S n}_{2}\\mathsf{S}_{2}$ Nat. Commun. 11, 5613 (2020). \n10. Ortiz, B. R. et al. New kagome prototype materials: discovery of $\\mathsf{K V}_{3}\\mathsf{S b}_{5},\\mathsf{R b V}_{3}\\mathsf{S b}_{5},$ and ${\\mathsf{C s V}}_{3}{\\mathsf{S b}}_{5}.$ Phys. Rev. Mater. 3, 094407 (2019). \n11. Ortiz, B. R. et al. $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}$ : a $Z_{2}$ topological kagome metal with a superconducting ground state. Phys. Rev. Lett. 125, 247002 (2020). \n12. Yin, Q. et al. Superconductivity and normal-state properties of kagome metal ${\\mathsf{R b V}}_{3}{\\mathsf{S b}}_{5}$ Single Crystals. Chin. Phys. Lett. 38, 037403 (2021). \n13. Jiang, Y. X. et al. Unconventional chiral charge order in kagome superconductor $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ Nat. Mater. 20, 1353–1357 (2021). \n14. Zhao, H. et al. Cascade of correlated electron states in a kagome superconductor $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}.$ Nature https://doi.org/10.1038/s41586-021-03946-w (2021). \n15. Liang, Z. et al. Three-dimensional charge density wave and surface-dependent vortex-core states in a kagome superconductor $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}.$ Phys. Rev. X 11, 031026 (2021). \n16.\t Yang, S.-Y. et al. Giant, unconventional anomalous Hall effect in the metallic frustrated magnet candidate, ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ . Sci. Adv. 6, eabb6003 (2020). \n17. Yu, F. H. et al. Concurrence of anomalous Hall effect and charge density wave in a superconducting topological kagome metal. Phys. Rev. B 104, L041103 (2021). \n18. Wang, Y. et al. Proximity-induced spin-triplet superconductivity and edge supercurrent in the topological Kagome metal, $\\mathsf{K}_{1-\\times}\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ Preprint at https://arxiv.org/abs/2012.05898 (2020). \n19.\t Zhao, C. C. et al. Nodal superconductivity and superconducting dome in the topological Kagome metal $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}$ . Preprint at https://arxiv.org/abs/2102.08356 (2021). \n20.\t Chen, H. et al. Evidence for ultralow-energy vibrations in large organic molecules. Nano Lett. 17, 4929–4933 (2017). \n21. Hirjibehedin, C. F. et al. Large magnetic anisotropy of a single atomic spin embedded in a surface molecular network. Science 317, 1199–1203 (2007). \n22.\t Fischer, Ø., Kugler, M., Maggio-Aprile, I., Berthod, C. & Renner, C. Scanning tunneling spectroscopy of high-temperature superconductors. Rev. Mod. Phys. 79, 353–419 (2007). \n23.\t Jiao, L. et al. Chiral superconductivity in heavy-fermion metal $\\mathsf{U T e}_{2}$ . Nature 579, 523–527 (2020). \n24.\t Lawler, M. J. et al. Intra-unit-cell electronic nematicity of the high- $\\cdot\\ensuremath{T_{\\mathrm{c}}}$ copper-oxide pseudogap states. Nature 466, 347–351 (2010). \n25.\t Fujita, K., Hamidian, M. H., Sprau, P. O., Edkins, S. D. & Davis, J. C. S. in Springer Handbook of Microscopy (eds Hawkes, P. W. & Spence, J. C. H.) 1369–1390 (Springer, 2019). \n26.\t Kivelson, S. A., Fradkin, E. & Emery, V. J. Electronic liquid-crystal phases of a doped Mott insulator. Nature 393, 550–553 (1998). \n27.\t Emery, V. J., Fradkin, E., Kivelson, S. A. & Lubensky, T. C. Quantum theory of the smectic metal state in stripe phases. Phys. Rev. Lett. 85, 2160 (2000). \n28.\t Hamidian, M. H. et al. Detection of a Cooper-pair density wave in $\\mathsf{B i}_{2}\\mathsf{S r}_{2}\\mathsf{C a C u}_{2}\\mathsf{O}_{8+x}.$ Nature 532, 343–347 (2016). \n29.\t Ruan, W. et al. Visualization of the periodic modulation of Cooper pairing in a cuprate superconductor. Nat. Phys. 14, 1178–1182 (2018). \n30.\t Agterberg, D. & Tsunetsugu, H. Dislocations and vortices in pair-density-wave superconductors. Nat. Phys. 4, 639–642 (2008). \n\n# Article \n\n31.\t Berg, E., Fradkin, E. & Kivelson, S. A. Charge-4e superconductivity from pair-density-wave order in certain high-temperature superconductors. Nat. Phys. 5, 830–833 (2009). \n32.\t Lee, P. A. Amperean pairing and the pseudogap phase of cuprate superconductors. Phys. Rev. X 4, 031017 (2014). \n33.\t Agterberg, D. F. et al. The physics of pair-density waves: cuprate superconductors and beyond. Annu. Rev. Condens. Matter Phys. 11, 231–270 (2020). \n34.\t Liu, X., Chong, Y. X., Sharma, R. & Davis, J. C. S. Discovery of a Cooper-pair density wave state in a transition-metal dichalcogenide. Science 372, 1447–1452 (2021). \n35.\t Landau, L. On the theory of superfluidity. Phys. Rev. 75, 884–885 (1949). \n36.\t Feynman, R. P. in Progress in Low Temperature Physics Vol. 1 (ed. Gorter, C. J.) 17–53 (Elsevier, 1955). \n37.\t Feynman, R. P. & Cohen, M. Energy spectrum of the excitations in liquid helium. Phys. Rev. 102, 1189–1204 (1956). \n38.\t Nozières, P. Is the roton in superfluid 4He the ghost of a Bragg spot? J. Low Temp. Phys. 137, 45–67 (2004). \n39.\t Edkins, S. D. et al. Magnetic field–induced pair density wave state in the cuprate vortex halo. Science 364, 976–980 (2019). \n40.\t Dai, Z., Zhang, Y.-H., Senthil, T. & Lee, P. A. Pair-density waves, charge-density waves, and vortices in high- $T_{\\mathrm{{c}}}$ cuprates. Phys. Rev. B 97, 174511 (2018). \n41.\t Yu, S. L. & Li, J. X. Chiral superconducting phase and chiral spin-density-wave phase in a Hubbard model on the kagome lattice. Phys. Rev. B 85, 144402 (2012). \n42.\t Kiesel, M. L., Platt, C. & Thomale, R. Unconventional Fermi surface instabilities in the kagome Hubbard model. Phys. Rev. Lett. 110, 126405 (2013). \n43.\t Wang, W. S., Li, Z. Z., Xiang, Y. Y. & Wang, Q. H. Competing electronic orders on kagome lattices at van Hove filling. Phys. Rev. B 87, 115135 (2013). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021 \n\n# Methods \n\n# Single-crystal growth of $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ sample \n\nSingle crystals of $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ were grown from Cs liquid (purity $99.98\\%$ ), V powder (purity $99.9\\%$ ) and Sb shot (purity $99.999\\%$ ) via a modified self-flux method10. The mixture was placed in an alumina crucible and sealed in a quartz ampoule under an argon atmosphere. The mixture was heated to $1,000^{\\circ}\\mathsf{C}$ and soaked for $24\\mathsf{h}$ , and subsequently cooled at $2^{\\circ}\\mathsf{C}\\mathsf{h}^{-1}$ . Finally, the single crystal was separated from the flux and the residual flux on the surface was carefully removed by Scotch tape. Except for the sealing and heat treatment procedures, all of the preparation procedures were carried out in an argon-filled glove box to avoid the introduction of any air and water. The obtained crystals have a typical hexagonal morphology with a size greater than $2\\times2\\times0.3\\mathrm{cm}^{3}$ (Supplementary Fig. 1) and are stable in air. \n\n# Sample characterization \n\nThe X-ray diffraction pattern was collected using a Rigaku SmartLab SE X-ray diffractometer with Cu Kα radiation $(\\lambda=0.15418\\mathrm{nm})$ ) at room temperature. Scanning electron microscopy and energy-dispersive X-ray spectroscopy were performed using a HITACHI S5000 with an energy-dispersive analysis system, Bruker XFlash 6|60. Magnetic susceptibility was determined by a SQUID magnetometer (Quantum Design MPMS XL-1). The SC transition of each sample was monitored down to 2 K under an external magnetic field of 1 Oe. Both in-plane electrical resistivity and Hall resistivity data were collected on a Quantum Design Physical Properties Measurement System. \n\n# Surface determination \n\nThe weak bonds between Cs and Sb2 layers offer a cleave plane and make it possible to have both Cs-terminated and Sb-terminated surfaces. At the interface of the two surfaces, we can clearly identify the atomic structures on both the top and bottom surfaces using high-resolution STM. We find that the lattice in the bottom layer shows a honeycomb configuration, which matches that of the Sb2 layer, while the top surface shows a hexagonal lattice with a spacing of 1 nm, which is about $\\scriptstyle{\\sqrt{3}}$ larger than the lattice constant of the pristine Cs surface (Extended Data Fig. 1). \n\n# STM/STS \n\nThe samples used in the experiments are cleaved at room temperature (300 K) or low temperature (78 K) and immediately transferred to an STM chamber. Experiments were performed in an ultrahigh-vacuum $(1\\times10^{-10}$ mbar) ultralow-temperature STM system equipped with a 9-2-2 T magnetic field. The electronic temperature in the low-temperature STS is calibrated (Supplementary Fig. 3) using a standard superconductor, Nb crystal. All of the scanning parameters (setpoint voltage and current) of the STM topographic images are listed in the figure captions. Unless otherwise noted, the dI/dV spectra were acquired by a standard lock-in amplifier at a modulation frequency of 973.1 Hz. Non-SC tungsten tips were fabricated via electrochemical etching and calibrated on a clean Au(111) surface prepared by repeated cycles of sputtering with argon ions and annealing at $500^{\\circ}\\mathrm{C}$ . \n\n# Josephson scanning spectroscopy \n\nIf the sample surface is SC, a superconductor–insulator–superconductor junction naturally forms under a SC STM tip for superconductor– insulator–superconductor tunnelling. This is known as a Josephson STM. In this case, the SC tip and sample are coupled by the Josephson coupling $E_{\\mathrm{{J}}}$ as the tip approaches sufficiently close to the sample at temperatures below the SC transition temperatures of both the tip and sample. At temperatures $k_{\\mathrm{B}}T>E_{\\mathrm{y}},$ thermally excited Cooper pairs tunnel and give rise to a tunnelling current directly proportional to the phase difference between the SC order parameters in the tip and the sample. This Josephson effect—a sharp zero-bias peak accompanied by negative differential conductance dips on both sides—is a phase-sensitive probe for the existence of superconductivity in the sample44–46. We use a SC Nb tip in the Josephson STM measurement (Supplementary Fig. 6). The Nb tip was fabricated via mechanical cutting of a Nb rod and calibrated on a clean Nb(110) surface prepared by repeated cycles of sputtering with argon ions and annealing at 1, $200^{\\circ}\\mathsf{C}$ . On the basis of the observed dI/dV spectra associated with the Josephson effect in Fig. 2d, we estimate the Josephson energy $E_{\\mathrm{{J}}}{=}1.61\\upmu\\mathrm{{eV}}$ and the charging energy $E_{\\mathrm{c}}{=}160\\upmu\\mathrm{eV},$ , which allow the thermal energy to satisfy $E_{\\mathrm{J}}\\ 10^{7}$ ) of trial alloy composi \n45 tions at $0.1\\mathrm{at}\\%$ resolution, using sub-models linking chemical composition and properties/behaviour; the large datasets built up were then analysed to identify optimal alloys using, inter alia, Pareto front approaches and property estimates based upon design targets [23]. The sub-models used for yield strength, creep resistance and phase stabilities are those from proven efforts for both single crys \n50 tal superalloys for investment casting [23, 24] and powder-processed superalloys [25, 26]. For additive manufacturing, the most important consideration is resistance to processing-related cracking, since the heat transfer characteristics of the process lead to very short heat source/powder interaction time and thus high rates \n55 of thermal straining [27]. This is the proven bottleneck of this digital technology [28]. Thus, for each trial composition in the dataset we made (in the first instance and inspired by the need for pragmatism) estimates of (i) the freezing range on the basis of a Scheil analysis of non-equilibrium solidification, assuming no back-diffusion; (ii) an estimate of the resistance to strain-age cracking \n60 during thermal cycling and post processing. In addition, in order to ensure the performance and stability of an alloy, estimates of (iii) yield stress and (iv) creep resistance, following the approaches of [25] and [23] respectively. This approach requires in turn estimates to be made of the anti-phase boundary energy, $\\gamma^{\\prime}$ fraction and interdiffusion coefficients. Finally (v) the susceptibility of the mi \n65 crostructure to topological close packed (TCP) phase formation was estimated \n\nby the energy level of d-block elements, following [23]. In the present work, much depends upon an accurate determination of the freezing range for different alloys, which is of course more-or-less experimentally inaccessible. We have discovered that the uncertainties in our calculated values depend upon three 0 important factors namely: (i) the choice of thermodynamic database to use in the calculation; (ii) the list of phases included in the thermodynamic calculation for a given alloy; and (iii) the specific composition employed within the alloy’s technical specification. It seems that the literature does not fully address these important points which are discussed further in the Appendix. \n\n75 Figure 1 illustrates the results of our calculations and informs the rationale for the choice of alloy compositions (labelled on all the sub-figures as ABD850AM and ABD-900AM) made in this work. Figure 1 (a) illustrates a weldability diagram employed in our analysis, which has its origins in the welding community [27]. On it is located various existing alloys; difficult-to-process al \n80 loys are expected to lie towards the top right of the diagram and processable ones to the bottom left. The lines drawn correspond to limits for assumed bounds for risk of strain-age cracking, but such a diagram does not account for hot tearing resistance, for which the freezing range is important. Unsurprisingly, there is a strong correlation of strain age cracking merit index with $\\gamma^{\\prime}$ content and creep \n85 resistance (Figure 1 (b, c)), and also the implication that increased hardening by alloying of $\\gamma^{\\prime}$ by Ti, Nb and Ta demands a reduction in Al content; this implies the classical trade-off between manufacturability and materials performance. To account for hot tearing susceptibility, Figure 1 (d & e) illustrates the predicted trade-off between Scheil freezing range, phase constitution and \n90 anticipated strength. It is notable that the strength contour runs from bottom left to top right, which implies that alloys of higher strength typically possess larger $\\gamma^{\\prime}$ fraction and freezing range. A weak correlation in freezing range with $\\gamma^{\\prime}$ fraction was found, but note that – at any given $\\gamma^{\\prime}$ content – there is considerable scope for narrowing or widening the freezing range; this is due to the \n95 solidification path and the last stages of it, see Section 5.1. An upper limit for the freezing range of 280 K has been selected as a first approximation in this work, a value in between that for IN738LC (285 K) and IN718 (265 K). The former alloy has been reported frequently to suffer from hot cracking [29, 30, 31], but the latter has been found to be readily printable [32, 33, 34]. Likewise, the \n100 maximum strain-age cracking index is chosen as $4\\mathrm{\\textrm{wt}}\\%$ based on the microcracking reported in IN939 (4.3 wt $\\%$ ) [35]. Figure 1 (e) confirms that the new alloys ABD-850AM and ABD-900AM are close to the Pareto front for maximum predicted creep performance without excessive $\\gamma^{\\prime}$ fraction, in an attempt to limit the risk of strain-age cracking. Figure 1 (f) illustrates our design concept \n105 more generally – a minimum required creep strength at a maximum anticipated tolerable freezing range and strain-age cracking susceptibility. \n\nIn summary, one should note that our design analysis confirms that the chemical composition influences the predicted mechanical properties and processing behaviour in a complex non-linear manner, which could not have been 110 anticipated without using the detailed modelling described here. Note also that we have not made use of blind empirical approaches based upon neural networks or machine learning, since there is a paucity of information on alloys for additive manufacturing in the literature. At this stage, we do not see how these could be successful. \n\n# 115 3. Experimental Methodology \n\n# 3.1. Alloys for additive manufacturing \n\nThe majority of the work reported in this paper was conducted using the new alloy ABD-850AM, with CM247LC [11] & IN939 [35] – which are longestablished superalloys spanning the alloy design space used widely for struc \n120 tural parts manufactured by conventional processes such as investment casting. In the latter part of the paper, results on a further alloy ABD-900AM are presented. Each alloy was obtained by argon gas atomisation, which produced a distribution of spherical particles with a D50 size of 30 $\\mu\\mathrm{m}$ . The compositions of the powders, determined by inductively coupled plasma-optical emission \n125 spectroscopy (ICP-OES) and ICP-combustion analysis, are given in Table 1. \n\n# 3.2. Processing parameters for selective laser melting (SLM) \n\nTo isolate the effect of alloy composition on defect formation, all alloys have been processed using an identical build strategy and set of laser parameters. The processing parameters used in the current study are the optimised parameters 130 determined by Renishaw plc for CM247LC [36], and also provide suitable (but not necessarily optimised) processing parameters for IN939 & ABD-850AM. By way of background information, we have determined that the broad findings of our study presented here are not altered by modifications in the laser parameters employed [37]. \n\n135 A Renishaw AM-400 machine was employed, which uses a modulated 200 W ytterbium fibre laser to process powder feedstock within a $125\\times125\\times125\\mathrm{mm^{3}}$ : build volume. The modulated laser performs point-to-point scans; the process parameters used were: laser power 200 W, layer thickness $30\\mu\\mathrm{{m}}$ , hatch spacing $50\\mu\\mathrm{m}$ , point distance 90 µm and exposure time at each point 50 µs. It possesses \n140 a reasonably small hatching distance, which promotes remelting that can heal some cracks [38]. A meander scan strategy – a raster scan with $67^{\\circ}$ rotation for each layer [39] – was used. For the processing trials, cubes of dimensions $10\\times$ $10\\times10~\\mathrm{mm^{3}}$ were manufactured for each alloy. Each layer scan of the SLM build was initially offset 100 µm from the edge of the $10\\ \\mathrm{mm}\\times10$ mm build \n145 cross-section. The region within the offset was scanned using the meander scan strategy. The offset border region was then scanned in two passes with the same power but at lower velocity (0.5 m/s) in order to improve the surface finish of the parts, consistent with industrial practice. The cube structure was built on top of 16 inverted pyramidal feet of the same material. \n\n# 150 3.3. Quantification of the extent of cracking \n\nThe cracking behaviour was quantified using stereological assessment of a digitised optical micrographs. The transverse (XY-) plane, i.e. perpendicular to the building direction (Z), was sectioned at half height (Figure 2 a) and prepared using standard metallographic procedures involving polishing and finishing with a 40 nm colloidal silica suspension. The degree of cracking in each material \n\nwere first captured in two locations, i.e. border and bulk, due to their large difference in cracking frequency found. The border region was designated by an area extending 300 $\\mu\\mathrm{m}$ from surface, and the rest is referred to here as the bulk. For each analysis, several random locations were captured and summed 160 ( $\\mathrm{\\sim5~mm^{2}}$ in area) for analysis. The ImageJ software was then employed for image binarisation by applying a threshold to the histogram. Total cracking length over the area measured gives the metric of cracking density, in the unit of mm/mm $^2$ , following the methods used in [11]. \n\n# 3.4. Electron microscopy: microstructure and micro-mechanical analysis \n\n165 The microstructures were examined by a Zeiss Merlin field emission gun scanning electron microscope (FEG-SEM) on both transverse (XY-) and longitudinal (XZ-) sections of the SLM specimens, which are perpendicular and parallel to the build direction (Z) respectively. The XZ- and YZ-planes are assumed to be identical because of the meander scan strategy used. Since defect distri \n170 bution has been a concern here, multiple backscattered electron (BSE) images of the XY-plane surface were obtained at 15 kV and stitched together. Samples were also electrolytically etched using $10\\%$ phosphoric acid at 3 V direct current. This etches away the $\\overset{\\triangledown}{\\boldsymbol{\\gamma}}$ matrix revealing $\\gamma^{\\prime}$ and carbide/boride particles. High resolution imaging of the microstructure following etching was undertaken \n175 using the secondary electron signal with the FEG-SEM, using immersion lens (in-lens/SE) and angle selective backscattered (AsB/BSE) detectors. \n\nA Bruker electron backscattered diffraction (EBSD) system was used to investigate crystal orientation, texture and geometrically necessary dislocation (GND) distribution in the as-fabricated microstructures. To obtain inverse pole 180 figure (IPF) and pole figure maps of the border and the bulk region, large area EBSD scans were conducted of samples both perpendicular and parallel to the build direction, with a step size of 1.12 $\\mu\\mathrm{m}$ . Grain size was measured using ESPRIT 2.1 software and is quoted as an equivalent grain diameter [40]. The pole figure contour is generated by HKL Channel 5 Mambo software [41]. \n\nTo obtain information on GND distribution, high resolution EBSD (HR \n\nEBSD) was conducted on the surfaces perpendicular to the build direction, both next to the border and within the bulk material. The patterns were stored at $400~\\times~300$ resolution with a step size of 445 nm. A cross-correlation based method were used to process the stored EBSD patterns [42]. \n\n# 0 3.5. Assessment of mechanical behaviour \n\nIn the first instance, the Vickers microhardness of each alloy was measured in both the as-fabricated condition and also following a heat treatment schedule, details of which are in Table 2. The tests were carried out using a 0.3 kg force load applied for 10 seconds. Five tests were conducted in each mate \n195 rial in the bulk region on both XY- and XZ-planes. Additionally, an electrothermal-mechancial testing (ETMT) system was used for measuring the mechanical properties of the as-fabricated alloys at room temperature and at 800, 900 and $1000^{\\circ}$ C. The samples were manufactured using identical conditions as for the cube samples, but now with a height of 52 mm. Uniaxial loading was \n200 applied in tension along the build direction for polished samples that were cut by electrical discharge machining (EDM). The sample geometry has a square cross-section of 1 mm length/width with a 16 mm parallel gauge. To minimise the effect from solid-state transformation kinetics during heating to the test temperature, in particular dynamic strain ageing, a heating rate of $100\\mathrm{K/s}$ was \n205 employed and tests were performed at a strain rate of $10^{-2}~\\mathrm{s^{-1}}$ . In the last part of the paper, all alloys were tested in fully heat treated conditions using ETMT, from ambient up to $1000^{\\circ}$ C at a strain rate of $10^{-3}~\\mathrm{{s}^{-1}}$ . The strain was measured using an iMetrum non-contact video extensometry method on a 3-mm gauge length where the temperature distribution is homogeneous. Full \n210 details of the experimental setup are described in greater detail in reference [43]. \n\n# 3.6. Differential scanning calorimetry (DSC) \n\nDifferential scanning calorimetry has proven useful for rationalising our findings, even though it is impossible to replicate with it the heating and cooling \n\nrates of the AM process. Melting and solidification behaviour (phase trans \n215 formation temperatures) of the AM-processed microstructures was investigated using a Netzsch DSC 404 F1. Samples were cut using EDM into disks 3 mm in diameter and ${\\simeq}1$ mm thickness. The measurements were carried out in a flowing argon atmosphere (20 ml/min). The differential heat flux was recorded at a heating rate of 10 K/min to $1450~^{\\circ}$ C, held for 15 mins and then cooled \n220 at the same rate. Baseline calibration runs were performed with an empty crucible and temperatures were calibrated in separate experiments using standard reference material. \n\n# 4. Results \n\n# 4.1. Overview of defect formation: cracking, porosity and lack of fusion \n\n225 Figure 2 (b-d) illustrates the entire cross-sections built for each alloy in the XY-plane (perpendicular to the build direction) in the as-fabricated state. Each is a montage stitched together from 24 binarised SEM images to better reveal the defect shape and locations. Cracking is heavily pronounced in both legacy alloys CM247LC and IN939; some cracks can extend over 300 $\\mu\\mathrm{m}$ and are visible to \n230 the naked eye, e.g. Figure 2 (e), (f) & (h). Furthermore, the frequency of cracks in the border scan regions are significantly higher than the bulk. However, at the resolution of the imaging conditions employed, no cracks were observed in the newly designed alloy ABD-850AM. Crack density in both border and bulk locations has been estimated in the \n235 legacy alloys: 6.7 & 0.08 mm/mm $^2$ in CM247LC and 5.0 & 1.6 mm/mm $^2$ in IN939, respectively. Surface connected cracks – which cannot be healed by hot isostatic pressing (HIP) – have also been examined, and are 35 times more frequent in CM247LC than in IN939. Other defects such as spherical gas porosity and lack of powder fusion, which occur less frequently, were also noted, see \n240 Figure 2 (i) & (j). The former is observed in all the alloys and occasionally in association with cracks. Pores occurred more frequently close to the border regions than in the bulk. Lack of powder-fusion defects occur infrequently in all \n\nalloys. Due to their low occurrence and/or small size these two types of defect have not been examined further in this work. \n\n245 For the avoidance of doubt, the size and morphology of the starting powder was checked for consistency. The powder size distributions are very similar, as determined by laser diffractometry, see Figure 2 (k). The D10, D50 (median) and D90 values are given in Table 3. All three powders were found to exhibit a near-spherical external morphology with only a few satellite particles, see \n250 Figure 2 (l-n). The inescapable conclusion is that it is the alloy composition which is influencing processability. \n\n# 4.2. Detailed characterisation of cracking modes \n\nIn what follows, the cracking behaviour is characterised carefully. Although it is not ideal, we make use of the phenomenological classification described ex255 tensively in the welding literature [44, 45, 46]. We have categorised the observed bulk cracking into three types based upon detailed fractography characterisation: (i) solidification cracking (which is related to the hot tearing phenomenon), (ii) liquation cracking, and (iii) solid-state cracking. The comparison of border and bulk cracking will be discussed in detail in Section 4.5. The following section 260 emphasises CM247LC and IN939, which display extensive cracking. \n\nFigure 3, taken from the XZ-plane, displays locations in CM247LC and IN939 that indicate solidification cracking has occurred. The rounded features of cells and dendrite arms are evident which confirms separation occurred whilst a remnant of liquid was still present and that there was insufficient feeding \n265 of remaining liquid to accommodate the solidification shrinkage strain in this region. Moreover, nano-metre sized MC type carbides are also visible within the intercellular regions, which would have formed during solidification and which would also act to inhibit feeding. This type of cracking normally leaves a large gap between the two surfaces with an irregular shape, where the two surfaces \n270 do not necessarily appear in the same morphology that can close up together. Because of this feature, solidification cracks are the easiest to identify. \n\nEvidence of liquation cracking has also been observed, see Figure 4, but only in CM247LC. There was no definitive observation of this feature in either IN939 or ABD-850AM. \n\n275 Figure 4 (a-c), from the XY-plane, confirms cracking along a grain boundary using secondary electron (SE) and backscattered electron images. The BSE image (Figure 4 (b)) shows fine spherical MC-type carbides distributed in interdendritic regions. The higher magnification SEM image, see Figure 4 (c), shows $\\gamma/\\gamma^{\\prime}$ eutectic phases are also present which is consistent with liquated \n280 regions, and observations of them reported in the literature [14]. Figure 4 (d) & (e) illustrate a crack and its adjacent phases after etching. The grain boundary phases close to carbides exhibit an alternating lamellar morphology, confirming a $\\gamma/\\gamma^{\\prime}$ eutectic region. Furthermore, fine particles are also observed within the matrix near the eutectic in Figure 4 (f), which is likely to be $\\gamma^{\\prime}$ . Figure 4 (g-i) \n285 illustrates another example of liquation from the XZ-plane. The melt pools are outlined in (g) and clearly show the initiation is in the vicinity of melt pool heat affected zone (HAZ). Additionally, the crack tip in (h) again shows segregation of heavy element (i.e. high atomic number) where a liquid film is observed (i). \n\nThe $\\gamma^{\\prime}$ precipitates are observed near the bottom of the build, and it is 290 increasing difficult to find them in other locations. Their size (see Figure 4 (f)) is estimated to be 20 nm, which is in accordance with TEM results in the literature [12]. The formation of precipitation is believed to be triggered by the heat treatment inherent to the SLM process, whereby each point in the AM build is re-heated multiple times as the laser passes the vicinity of the region. \n\n295 In contrast to the above cracking modes which clearly involve both solid and liquid phases, a further category is associated with cracking entirely in the solid state; it will be referred to here as solid-state cracking. This type of cracking can be clearly differentiated by careful metallographic analysis, as it possesses none of the aforementioned characteristics, i.e. exposed dendrites and/or traces \n300 of liquid films. The surfaces on each side are almost identical to each other in shape, typically microscopically “clean”, straight and often associate with sharp kinks. It is often also referred to as ductility dip cracking (DDC) and/or strain-age cracking (SAC) [47, 48, 46]. Evidence for this type of cracking is \n\nshown in Figure 5 for both CM247LC and IN939. In the XZ-plane, solid-state 305 cracking follows grain boundaries whilst exhibiting kinks which can be as sharp as $90^{\\upsilon}$ and in some instances interacting with solidification cracks. Typical crack lengths exceed 100 $\\mu\\mathrm{m}$ ; sometimes they can extend over 300 $\\mu\\mathrm{m}$ , which is significantly larger than the melt pool size (around 60 $\\mu\\mathrm{m}$ ). For avoidance of doubt, long cracks are not necessarily generated in the solid-state, but could 310 result from the propagation of cracks that nucleated as hot tears. \n\nElectrolytic etching was applied to IN939 to better illustrate the relationship between the melt pool and crack path (Figure 5 (d-f) and it is clear that cracks cut through several layers of melt pool without the presence of exposed dendrites, further suggesting its differences to hot tears. Based on these obser315 vations – with no evidence of liquated phases at the grain boundaries and their straight clean character – a solid-state mechanism is responsible. Further validation of this mechanism through high temperature tensile tests will be discussed in Section 5.2. \n\n# 4.3. Location dependency on microstructure and texture development \n\n320 Figure 6 (a-c) displays inverse pole figure (IPF) maps both parallel and perpendicular to the building direction (Z). These were derived from large-area EBSD scans (covering an area of $0.98\\ \\mathrm{mm^{2}}$ ) performed in the bulk of each alloy. For all three alloys, the IPF maps reveal a strong texture dominated by preferential alignment of columnar grains along the building direction. However, \n325 the grains in ABD-850AM and IN939 are less elongated. \n\nThe microstructures of the as-fabricated alloys as revealed by etching are given in Figure 6 (d-f). Evidence is the epitaxial growth from partially remelted previous layers that allows the strong texture to develop. Microstructures perpendicular to build direction confirm the growth front to be predominantly 330 cellular – cell sizes for each alloy vary between 300 nm to 1.5 $\\mu\\mathrm{m}$ , depending on the location. The spacing between primary cells is indicative of extremely high solidificaton rates. In CM247LC, the cell boundaries also exhibit $\\gamma/\\gamma^{\\prime}$ eutectic mixture as expected in this alloy from the DSC results presented later and as \n\npreviously observed elsewhere [14]. \n\n335 The contour pole figures plots quantify the texture strength for the three plane families $\\{1\\ 0\\ 0\\}\\ \\{1\\ 1\\ 0\\}$ and $\\{1\\ 1\\ 1\\}$ with respect to the XY-plane of the sample. They confirm that the $\\{1\\ 0\\ 0\\}$ texture component is the strongest among the three, and it is parallel to the building direction. It is notable that the texture strength is also alloy dependent due to their intrinsic thermophysical \n340 properties — CM247LC and IN939 have similar texture strength whilst the ABD-850AM $\\left\\{100\\right\\}$ texture strength has been found to be considerably weaker. Since there are significant differences of cracking susceptibility at different locations, the texture development from surface to bulk was studied. Figure 7 shows IPF maps obtained from large-area EBSD scans from the border to the \n345 bulk in all three alloys for the XY- and XZ-planes in the as-fabricated condition. Clear differences in grain structure development are evident. Three regions are clearly distinguishable, as indicated using dotted lines: (i) small grains at the border; (ii) columnar grains at the border, and (iii) elongated textured grains in the bulk. To probe the change in the microstructure with respect \n350 to location, each EBSD map was segmented into ten equal width rectangular areas to estimate texture and grain size – their variation with distance from the border are shown in Figure 7 (g-i). Grain size and texture variations are broadly similar from alloy to alloy. In the border, small grains are around 20 $\\mu\\mathrm{m}$ and a local maximum is reached by columnar grains at around 80 $\\mu\\mathrm{m}$ . In the \n355 bulk region, grain size and texture remains relatively uniform. The texture component follows a similar trend to grain size. \n\nGrain misorientation in the vicinity of cracks was investigated with EBSD. Based on 200 observations, cracks occur at high angle grain boundary (HAGB) regardless to their locations – both border and bulk. In addition, all HAGB 360 cracking was found to be associated with solid-state and/or solidification reactions. \n\n# 4.4. Spatial heterogeneity in GND distribution \n\nAs confirmed by Figure 2 and Figure 7, border and bulk regions displayed significantly different microstructures, which potentially influences the cracking 365 phenomenon. This cannot be ignored because near surface cracking at the border cannot be healed by hot isostatic pressing (HIP), and hence it determines the quality of net shape finish and manufacturing precision. In the current study, smooth surfaces were achieved in contrast to components without [49] using the border parameter described in Section 2.2. However, the border scan 370 also promotes local grain growth and cracking. \n\nABD-850AM has been studied by HR-EBSD in detail to determine its micromechanical response – since no cracks were observed, the stress/strain relaxation induced by cracking cannot then arise. The GND density and IPF maps are shown in Figure 8. A distinctive bimodal distribution of GND density was \n375 observed in the AM process, which is very different from the usual single modal distribution with uniaxial deformation [50]. It suggests that some grains possess higher GND density than the others as a result of SLM fabrication. The high and low GND regions can even be present in the same grain, as labelled. A possible cause may be the preferential fibre texture in the building direction of \n380 [0 0 1]. The grains can allow large thermal expansion along [0 0 1], the build direction, due to the anisotropy developed, but constrained laterally in plane. The bimodal GND distribution shown in Figure 8 (c) & (f) confirms a clear difference between the two different locations. Each histogram constitutes with two peaks where log10(ρ) equals 14.1 and 14.9. The microstructure on the border \n385 exhibits a higher population of GND associated with the latter peak compared to the bulk, which implies more plasticity involved. This is expected from the macroscopic stress state expected at the surface, since tensile forces will be induced there. Furthermore, the effect may also be amplified due to the larger grain size as strain accommodation is then harder. Admittedly, the higher GND \n390 distribution on the border provides more mechanical driving force to facilitate cracking, making it more vulnerable than the bulk. As a result, in the legacy alloys for which cracking occurs, higher cracking densities near the border is \n\nfrequently observed. \n\n# 4.5. Characteristics of phase transformations during melting and solidification \n\n395 The DSC thermograms acquired during the heating cycles of the three different alloys are shown in Figure 9. The heating curves reflect the non-equilibrium microstructure in the as-fabricated state and the values of the transformation temperatures measured are listed in Table 4. In all three alloys, an abrupt change in heat flow is observed at the $\\gamma^{\\prime}$ dissolution temperature. But this \n400 feature is only just detectable in the ABD-850AM alloy whereas in CM247LC the onset of melting appears to overlap with the dissolution of $\\gamma^{\\prime}$ as also noted elsewhere [12]. On heating, the temperatures corresponding to the onset of melting ( $T_{S}$ ) and end of melting ( $T_{L}$ ) were obtained by the extrapolation method [51]. Of particular note is the very sharp onset of melting of ABD-850AM at \n405 ${\\sim}1383^{\\circ}$ C. In CM247LC and ABD-850AM, there is a noticeable change in heat flow prior to melting, presumably due to dissolution of the carbide phase. But in IN939 the carbide/boride dissolution cannot easily be de-convoluted from matrix melting. Also shown in Figure 9 are the thermograms resulting from slow cooling and solidification in the DSC. Values for $T_{L}$ , carbide/boride for \n410 mation, end of solidification and $\\gamma^{\\prime}$ formation are given in Table 4. In all three alloys the value of $T_{L_{\\phi}}$ on cooling is significantly lower than on heating, mainly due to nucleation undercooling. In CM247LC, there is a clear eutectic reaction at $1260^{\\circ}$ C, $\\mathop{T_{E}}^{\\underbar{=}}$ probably involving $\\gamma$ , $\\gamma^{\\prime}$ and carbide – which is absent in the other two alloys. \n\n# 415 4.6. Hardness response in the as-fabricated microstructures \n\nClearly, the mechanical response of the as-printed alloys is critical to determining whether solid-state cracking occurs. As a first test of whether this effect is relevant, microhardness tests have been carried out in the as-fabricated state, see Figure 10 (a). The error bars represent the standard deviation in the mea420 surements. In the as-fabricated condition, ABD-850AM has the lowest Hv value whereas the two legacy alloys are notably stronger. This effect arises because \n\nABD-850AM contains little if any $\\gamma^{\\prime}$ precipitation in the as-fabricated state, see Figure 4 (d-f), so that contribution to strengthening must be due to solidsolution hardening and/or substructural hardening. Clearly, the kinetics of $\\gamma^{\\prime}$ \n425 precipitation are sluggish in ABD850AM, which may be a contributory factor to its superior processability; this is explored in greater detail later. Interestingly, with appropriate heat treatment, all alloys developed precipitation of $\\gamma^{\\prime}$ , and also some $\\gamma^{\\prime\\prime}$ in IN939, see Figure 10 (b-d). This allows both ABD-850AM and IN939 to harden significantly – by $\\sim$ 140 Hv and 90 Hv respectively – in contrast \n430 to only a small increase for CM247LC of ${\\sim}10$ Hv. Moreover, an orientation effect is evident with differences between the hardness on the XY-and XZ-planes. This trend is unchanged following heat treatment. \n\n# 5. Discussion \n\nBy carefully controlled processing and characterisation studies, this work \n435 has demonstrated clearly the significant impact of alloy chemistry on susceptibility to defect formation (Table 5), microstructure development and hardness response by heat treatment. In particular, it has proved that theory-based modelling approaches are likely to prove fruitful for designing new grades of alloy for the new AM technology. Nevertheless, the results presented thus far require ra \n440 tionalisation, and moreover they provoke many further questions which demand attention. \n\n# 5.1. Solidification at final stage: Criteria and key elements \n\nAlthough the high solidification cracking susceptibility of CM247LC and IN939 can be rationalised on the basis of their wide freezing ranges, the analysis thus far has limitations since it fails to take account of the very last stages of the solidification path which are acknowledged to be very important and potentially decisive [19, 31]. Thus we now employ a more detailed analysis as proposed by Kou [52], who adapted the model of Rappaz et al. [53, 54], to rationalise the resistance to hot tearing in the vulnerable regime. The critical feature emphasised is the balance between the strain rate of the solidifying solid (promoting cracking) and the feeding rate of liquid (inhibiting cracking). The solidification cracking index (SCI) is then given by [52] \n\n$$\n\\mathrm{SCI}=\\mid\\mathrm{d}T/\\mathrm{d}(f_{s}^{1/2})\\mid\n$$ \n\nwhere $f_{s}$ is solid fraction, $T$ is temperature. It has been clarified by Kou [52] that the use of one specific temperature interval, for example 0.87< $f_{s}$ <0.94 445 originally proposed [52], is somewhat arbitrary. Hence we present the SCI values over the whole range of $f_{s}$ , and then select three ranges at the last stage to discuss the cracking susceptibility over the three alloys, in addition, another two commonly studied alloys IN738LC and IN718, as well as two variants of IN939 and CM247LC, were analysed. \n\n450 The SCI plots of $f_{s}$ versus $\\left|\\mathrm{d}T/\\mathrm{d}(f_{s}^{1/2})\\right|\\mathrm{~a~}$ re displayed in Figure 11 (a) over the range 00.8$ . The magnified graph in Figure 11 (b) exemplifies the propensity for each material to undergo solidification cracking. The discontinuities in curves correspond to phase transforma \n455 tions. The average SCI values are evaluated over critical $f_{\\mathrm{s}}$ ranges of 0.8-0.9, 0.9-0.99 & 0.8-0.99, see Table 6. The SCI values are reasonably similar for the three alloys in the range of 0.8-0.9, but the variation becomes significant in the other two $f_{\\mathrm{s}}{\\mathrm{~ranges}}$ . The key difference is likely to be 0.9< $f_{s}$ <0.99, which is crucial for AM superalloys. \n460 The same analysis was also conducted for IN718, IN738LC and ABD-900AM, see Figure 11 (c). The former two heritage alloys have been frequently investigated in the AM field, where IN718 is deemed to be printable and whilst IN738LC is not. It is clear that for fs>0.85 IN718 exhibits rather low SCI values, whereas IN738LC possesses notably higher values. The average SCI of IN718 \n465 over the critical range 0.9
NiCrCoAlTiNbTaWMoHfZrC
ABD-850AMBal18.6817.601.292.220.600.444.741.890.010.003
CM247LCBal8.308.995.620.75-3.169.450.521.320.070.016
IN939Bal22.1018.801.763.800.971.371.96-0.010.110.160.009
ABD-900AMBal16.9619.932.112.391.781.423.082.090.050.005
\n\nTable 2: Heat treatment program conducted for the alloys. \n\n
SolutionCoolingStablisationCoolingAgeingCooling
ABD-850AM980°C/2hAir850°C/4hAir760°C/16hAir
CM247LC [11]1260°C/2hAir1079°C/2hAir871°C/20hAir
IN939 [69]1160°C/2hAir1000°C/4hAir850°C/16hAir
ABD-900AM1050°C/2hAir850°C/4hAir760°C/16hAir
IN718 [70]980°C/2hAir720°C/8hFurnace620°C/8hAir
\n\nTable 3: Powder size distribution in µm of the three alloys studied. \n\n\n
Min D10D50D90Max
ABD-850AM 0.1 20.635.856.1104.7
CM247LC 0.119.9 32.352.7104.7
IN939 0.124.4 33.55091.2
\n\nTable 4: Phase transition temperatures in the alloys measured using DSC. \n\n\n
DSC (10 K/min)
Heating (°C)Cooling (°C)
CM247LCIN939ABD-850AM CM247LCIN939ABD-850AM
12501088102510721013
Ts (Solidus)126012061330N/AN/A
MC carbide13601319135312951296
TL (Liquidus)13751330138313271377
\n\nTable 5: Summary of defect formation in the three alloys. \n\n\n
CrackingPorosityLack of fusion
SolidificationLiquationSolid state
ABD-850AMNNNYY
CM247LCYYYYY
IN939YYYY
\n\nTable 6: Solidification cracking index (SCI) values for various alloys calculated based upon prediction made using Scheil solidification curves by Thermo-Calc with TTNi8 database. Freezing ranges obtained from both Scheil and equilibrium solidification are also presented. The specific composition used in the calculations are provide in supplementary data (phase selection 1). \n\n
SCI (K) Freezing range (K)
fs = 0.8-0.9 f s 0.9-0.99 fs = 0.8-0.99 Scheil Equilibrium
ABD-850AM 647 5545 4799 266 91
CM247LC 875 15980 14109 392
87
IN939 1247 7170 5922 343 182
IN718 1459 921 1261 264 174
IN738LC 787 6681 5711 286 99
ABD-900AM 1076 3577 2885 268 101
CM247LC Hf free 479 5036 4295 184 76
\n\n![](images/439a43e80eac0aafa7ae9641641c5494a104b896666c2e46049a67f4d6fc4895.jpg) \nFigure 1: Computational alloy design spaces used for new grades of superalloy; locations of heritage alloys are also plotted for comparison. (a) modified weldability diagram with maximum strain-age cracking index identified. (b & c) show strain-age cracking merit index and its relationship to $\\gamma^{\\prime}$ fraction and creep merit index. (d & e) presents magnitude of freezing range in relation to $\\gamma^{\\prime}$ fraction and cr3e9ep merit index, where strain age cracking and creep merit contours are indicated. (f) gives the final design space used to isolate new grades of alloy based upon freezing range, strain-age cracking index and minimum required strength & creep. \n\n![](images/5caa67dec8df904943d350292d15c82f61cf58f306bf1343a5244b39b9633798.jpg) \nFigure 2: Overview of as-fabricated microstructures of ABD-850AM, CM247LC and IN939, viewed perpendicular to the build direction. (a) shows the XY- and XZ-planes sectioned for each cube. (b-d) illustrates the stitched cross-sectional area of the XY-plane using digitised SEM images and (e-g) are magnified corners of these. (h-j) demonstrates typical lack of powder fusion, cracking and gas-related porosity. (k) shows the powder size distribution which is taken from the powder in (l-n) \n\n![](images/68e6df371e7e50b07243c6ebc54214b918c99e6aab06fde8088c34836750f00c.jpg) \nFigure 3: Solidification type cracking observed in both CM247LC and IN939 in the XZ-plane of the as-fabricated microstructure. The primary dendrite arms are evident as they were separated during the last stages of solidification. The building direction is along the Z-axis. \n\n![](images/04629731b520ae3471f6151be222cf00223bbb67a00498ab0dde1282a4c37fff.jpg) \nFigure 4: Liquation type cracking in CM247LC as identified without etching (a-c) and with etching (d & e) in the as-fabricated microstructure. Area in red boxes are shown in more detail. Crack tip characterisation shows MC type carbide and $\\gamma/\\gamma^{\\prime}$ eutectic phases are present along cracking. Nanometre size $\\gamma^{\\prime}$ particles are also visible with etching (f). A further liquation cracking site showing segregation and liquid film in (g-i). The building direction is along the $\\mathrm{_{Z}}$ -axis. \n\n![](images/9cfbdd4368a5fb34c9c45f4e14f5f61c8a80ab6b96ffa96300b4fe68269e56c1.jpg) \nFigure 5: Solid-state cracks observed in CM247LC (a-c) and IN939 (d-f) on XZ-plane in the as-fabricated microstructure. The cracking features no solidifying dendrites or liquation regions. Cracks normally exceeds $100\\ \\mu\\mathrm{{m}}$ in length that propagate through several layers of melt pool. Area in red boxes are shown in more detail. The building direction is along the Z-axis. \n\n![](images/94df3fed860d4d7d280aac44cb1f387de38b50a1b7879d09fd9f47612f169087.jpg) \n44 Figure 6: SEM (etched), IPF and pole figure maps of the three alloys representing preferred texture in the bulk of materials (as-fabricated). (a-f) microstructure of XZ-plane in two magnifications and (g-l) microstructure of XY-plane in two magnifications. (m-o) illustrates the IPF of both planes along building direction and (p-r) demonstrates the bulk texture strength of {1 0 0}, {1 1 0} and {1 1 1} poles. \n\n![](images/630d8ac56ed16879dbd13eb463fe18f2efbaf812721a4c8da1a85de487ef73a3.jpg) \nFigure 7: EBSD scans near the border in orientations both parallel (XZ-) and perpendicular (XY-) to the building direction in the as-fabricated microstructure. Three regions of distinctive crystal orientations were indicated using dotted lines, where the grain size and $\\{1\\ 0\\ 0\\}$ texture component profile vary across the distance. \n\n![](images/e2e55308ce653c8db33b7aa5f4023f77ef58ceddc17edca24211929de0c1ef3f.jpg) \nFigure 8: GND density, IPF (Y-axis) and GND histogram maps are presented in the border and the bulk part of ABD-850AM in the as-fabricated microstructure. Local GND heterogeneity is observed, the histogram reveals a bimodal distribution. \n\n![](images/f6953b34f7b822e92da52d0aab00f1269611c222798962440a8d5044975b6e81.jpg) \nFigure 9: Differential scanning calorimetry (DSC) curves obtained from the three alloys during heating and cooling at $10~\\mathrm{K/min}$ (a-c). Notable phase transformation temperatures are shown by the arrows and values are given in Table 4. \n\n![](images/6aba26adba4ced280a2e6dc6e19a4126bde2a38000b01bbaeb974f1019276026.jpg) \nFigure 10: (a) Vickers hardness, Hv, for as-fabricated and fully heat-treated microstructure parallel and perpendicular to the building direction, (b-d) etched microstructure of CM247LC, IN939 and ABD-850AM at two magnifications. \n\n![](images/0682952546a54a5731eb02a6d79e21adb42c2f58a2e559c43cf371d44ff10472.jpg) \nFigure 11: Solidification cracking index (SCI) of various alloys based upon solidification curves calculated using Thermo-Calc with TTNi8 database. (a) SCI value over the full range of solid fraction, (b, c & d) SCI value of the last stage solidification in the range of 0.8-0.99 of CM247LC, IN939, ABD-850AM, ABD-900AM, IN718, IN738LC, CM247LC Hf free and IN939 $\\mathrm{Zr}$ free. \n\n![](images/f307817d271af6d65b88a6371db27694454d3e41757d4ebc763b5feb47cfcd43.jpg) \nFigure 12: Results of ETMT tensile tests at room temperature and between 800-1000 ◦C in as-fabricated state. (a) Engineering stress-strain curves for all tests at a strain rate of $10^{-2}s^{-1}$ , (b) a magnified view of curves $0.8\\%$ strain), (c-d) illustrate the ultimate tensile strength and ductility values for the three alloys. Note, anomalous yield behaviour is observed for ABD-850AM at $800~^{\\circ}\\mathrm{C}$ where fracture occurred outside the gauge section, hence the ductility measurement was an underestimation. \n\n![](images/62d0a9883de06a1f8fde4c4db774e9ece1f8bd11e8d5b0ea23902d2e0656ab3c.jpg) \nFigure 13: As-fabricated microstructure and mechanical properties determined from ETMT tensile tests of ABD-900AM. (a) the powder characterisation and digitised SEM image, (b) IPF-Z map along building direction, (c) bimodal distribution of $\\gamma^{\\prime}$ in full heat treatment condition. (d & e) shows yield strength and ductility of CM247LC, IN939, ABD-850AM, ABD-850AM mod and ABD-900AM obtained from ETMT tensile tests at a strain rate of $10^{-3}s^{-1}$ at various temperatures in the heat-treated state. The heat treatment conditions is given in Table 2. \n\n![](images/be800b32fec97e10535e5506e15fb83f27637a115686d85cb9568253989f0266.jpg) \nFigure 14: Larson-Miller parameter plot of heat treated IN718, ABD-900AM and CM247LC tested according to ASTM standards. \n\n# 10. Appendix \n\nThe alloy design approach used has most strongly emphasised estimates of 950 (i) the freezing range and (ii) the strain-age cracking index. In what follows, we provide further detail to our calculations, emphasising particularly the source of systematic error which we believe to be present. To facilitate transparency, a Data-In-Brief (supplementary data) is provided which gives details of the computations which can be then repeated by others. \n\n955 The solidification path was calculated using the Thermo-Calc software using the Scheil module and TTNi8 database, at a temperature step size of 0.5 K. The phases selected for inclusion in the calculations were guided by literature observations for phases known to play a role in AM-produced microstructures: $\\gamma^{\\prime}$ [14], $\\eta$ [71], $\\delta$ [72], Laves [73], borides [19], carbides [14] and Ni5M intermetallic \n960 in addition to liquid and $\\gamma$ matrix. The phase descriptors enabled in the calculations are: ‘LIQUID’, ‘FCC A1’, ‘GAMMA PRIME’, ‘LAVES’, ‘ETA’, ‘DELTA’, ‘M3B2 TETR’, ‘NI5M’, ‘M23C6’ and ‘HCP A3’. To clarify, ‘FCC A1’ includes both $\\gamma$ matrix and MC carbide. The readers are refereed to the supplementary data for composition input and results. \n\nThe freezing range ( $\\Delta\\mathrm{T}$ ) has been defined as the temperature difference between the $\\gamma$ phase formation temperature (with supersaturated carbon as solid solution) and a fraction of solid corresponding to $f_{s}=0.99$ . For the majority of the cases, the $\\gamma$ phase formation temperature corresponds to $f_{s}=0$ , but for a few exceptions – for example IN100 – the carbide formation temperature is predicted to be higher than the liquidus temperature thus causing a sharp discontinuity at $f_{s}=0$ ; here the $\\gamma$ phase formation temperature is used instead of $f_{s}=0$ . Hence the equation can be written as \n\n$$\n\\Delta T=T_{f_{\\gamma}}-T_{f_{s}=0.99}\n$$ \n\n965 The Scheil solidification analysis gives different results dependent upon the assumptions made in the thermodynamic database. We believe that three systematic uncertainties are introduced by virtue of (1) the selection of phases \n\nincluded for calculations, (2) the choice of thermodynamic database and (3) the variation in the allowable composition ranges inherited from the different 970 materials suppliers and patents. \n\nFigure 10.1 shows the predicted freezing ranges of a set of alloys calculated by enabling (i) the 10 selected phases described above, and alternatively (ii) all default phases. A general trend is found: the magnitude of the freezing ranges being narrowed by the formation of more phases. This is because dur \n975 ing the solidification process, in particular where $f_{s}$ is greater than 0.9, phase formation helps to consume the excessive rejected solute in the interdendritic liquid. For the alloys plotted, an average difference of 33 K is induced by the choice of phases. Phase formation appears as a discontinuity in the phase fraction/temperature curves. However – and importantly for our alloy design effort \n980 – broadly speaking, the rank order of the alloys when judged on this basis is largely unaffected by the list of phases included. \n\nNext, Figure 10.1 (b & c) illustrate the influence of database choice: results from TTNi8 (b) are compared to those from TCNI8 (c) whilst enabling all phases by default. This time, no general trend of narrowing or broaden985 ing the freezing range is found, yet the magnitude of freezing range change is found to be larger with an average difference of 39 K. Nevertheless, the hardto-print alloys – for example CM247LC or IN792 – always possess relatively large predicted freezing ranges, and easy-to-print alloys – for example IN625 and IN718 – illustrate reasonably low freezing ranges. For avoidance of doubt, 990 though IN738LC obtains marginally lower freezing range than ABD alloys only in the TCNI8 database, the SCI analysis for the last stages of solidification (with TCNI8 database) still shows both ABD alloys obtaining much lower indices (3089 & 2781 K) vs IN738LC (4651 K). Consequently, ABD-850AM and ABD-900AM can be unfailingly distinguished from the very large compositional 995 bank regardless of the selection of phases and/or database. \n\nIn addition, the effect on the freezing range of the allowable compositional range is also considered. This is very relevant to the practitioners in the field because the commercial alloys are usually specified within a range of composi \n\ntions as well as some tolerance of impurities.Unsurprisingly, the level of minor \n1000 element tolerance for some alloys can impose a dramatic change in additive manufacturability [74]. The range of compositions used for calculations are taken from technical data sheets where available (see supplementary data-in-brief). To avoid confusion, the calculations were completed based upon solely on the possible compositional ranges, hence may not necessarily capture the largest \n1005 difference in the freezing range. Figure 10.2 demonstrate the possible locations of each alloy in the design space using the TTNi8 database with phase selections consistent with the manuscript, based upon maximum, minimum and recommended compositions. It is clear that some alloys are very sensitive to compositional variation, including IN738LC, for which the freezing range has \n1010 changed by over 100 K and SAC by ${\\sim}1$ . However, for others alloys the freezing range can be generally insensitive such as IN718, by less than 30 K. The key point here is that the estimate of the freezing range possesses an uncertainty related as much to the specification of alloy composition as to the method of calculation and errors in the underlying data. \n\nThe second parameter which has been used widely in this work is the strain age cracking (SAC) index which describes the propensity of forming $\\gamma^{\\prime}$ precipitates during the so-called “intrinsic heat treatment” – which is repeated reheating and cooling arising from the AM fabrication. The formation of $\\gamma^{\\prime}$ compromises local ductility via effective total fraction of $\\gamma^{\\prime}$ forming elements: Al, Ti, Nb and Ta (wt. $\\%$ ) as acknowledged by [75, 76]. The index is hence expressed in this work as \n\n$$\nM_{\\mathrm{SAC}}=[\\mathrm{Al}]+0.5[\\mathrm{Ti}]+0.3[\\mathrm{Nb}]+0.15[\\mathrm{Ta}]\n$$ \n\n1015 The empirical strain age cracking index provides only a first approximation to a very difficult problem. However, to validate its use – and in the absence of any accurate composition-dependence model for overall transforamtion kinetics in the nickel-based superalloys – the chemical driving force for $\\gamma^{\\prime}$ precipitation in some heritage alloys has been calculated using Thermo-Calc with TTNi8 \n1020 database. Figure A3 shows the $\\gamma^{\\prime}$ precipitation driving force as a function of \n\nSAC index in the temperature range of 800 - $1000^{\\circ}$ C. It is clear that all alloys possess very high chemical driving force to form precipitates if the undercooling is large, as expected, for example at 800◦C, but then no correlation with SAC is found. However, at high temperatures for example 1000◦C, a strong positive 1025 correlation between SAC index and precipitation driving force is found; the correlation coefficient is $\\mathrm{{R=0.91}}$ and the interpolation of the linear fitting is through the origin. The result implies a thermodynamics basis of the SAC index. In principle, the adoption of a new index using chemical driving force would be a step forward further than the SAC index, however to be clear, the contribution 1030 of interfacial energy that facilitates precipitation is not considered. This may be a reasonable approximation, because the interfacial energy for nickel-based superalloys is exceptionally low – typically on the order of $0.01~\\mathrm{Jm^{-2}}$ [77, 78], which is about one-two orders of magnitude less than other f.c.c. alloy systems, for example the Co-Cu and Al-Cu system [77, 79]. Further work is needed to 1035 explore these ideas. \n\nAdditional sub models used for example estimating strength, creep and microstructural stabilities were taken from the literatures [23, 25, 24] with no further improvisation. Hence not detailed in the appendix. \n\n![](images/82fb0b352bdfb0965f2e45578840c53a64e5a71bdcfe49cb1afff0a67185c2b3.jpg) \nFigure 10.1: Freezing range as a function of strain age cracking index for some heritage alloys using different databases and choice of phases. (a) TTNi8 database with phase selection consistent with the manuscript, (b) TTNi8 database with all default phases, (c) TCNI8 database with all default phases. \n\n![](images/274476f971d482a99adabd0aedd0ba49d6405cce4bea146ae63ea8d3c683f748.jpg) \nFigure 10.2: Variation of freezing range and SAC index as a function of composition variants in the specification ranges. Single and double asterisks refer to two possible compositions detailed in supplementary data. \n\n![](images/99de0d87cd0d541db759f163406c46d461dfceca606117ea56c8f5b3c1f97a47.jpg) \nigure 10.3: Illustration of the correlation of precipitation driving force at $800{-}1000^{\\circ}\\mathrm{C}$ with strain age cracking index \n\n# Declaration of interests \n\n☐ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \n\n☒The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: \n\nOxMet Technologies is a spin-out company of the University of Oxford, and some of the authors of this manuscript work for this organization, as listed in the affiliations listed on the first page of the paper. Prof Reed maintains a small $(5\\%)$ shareholding in this company. " + }, + { + "id": "10.1038_s41587-021-00950-3", + "DOI": "10.1038/s41587-021-00950-3", + "DOI Link": "http://dx.doi.org/10.1038/s41587-021-00950-3", + "Relative Dir Path": "mds/10.1038_s41587-021-00950-3", + "Article Title": "Wearable materials with embedded synthetic biology sensors for biomolecule detection", + "Authors": "Nguyen, PQ; Soenksen, LR; Donghia, NM; Angenent-Mari, NM; de Puig, H; Huang, A; Lee, R; Slomovic, S; Galbersanini, T; Lansberry, G; Sallum, HM; Zhao, EM; Niemi, JB; Collins, JJ", + "Source Title": "NATURE BIOTECHNOLOGY", + "Abstract": "Wearable materials are endowed with synthetic biology circuits to detect biomolecules, including SARS-CoV-2 RNA. Integrating synthetic biology into wearables could expand opportunities for noninvasive monitoring of physiological status, disease states and exposure to pathogens or toxins. However, the operation of synthetic circuits generally requires the presence of living, engineered bacteria, which has limited their application in wearables. Here we report lightweight, flexible substrates and textiles functionalized with freeze-dried, cell-free synthetic circuits, including CRISPR-based tools, that detect metabolites, chemicals and pathogen nucleic acid signatures. The wearable devices are activated upon rehydration from aqueous exposure events and report the presence of specific molecular targets by colorimetric changes or via an optical fiber network that detects fluorescent and luminescent outputs. The detection limits for nucleic acids rival current laboratory methods such as quantitative PCR. We demonstrate the development of a face mask with a lyophilized CRISPR sensor for wearable, noninvasive detection of SARS-CoV-2 at room temperature within 90 min, requiring no user intervention other than the press of a button.", + "Times Cited, WoS Core": 344, + "Times Cited, All Databases": 379, + "Publication Year": 2021, + "Research Areas": "Biotechnology & Applied Microbiology", + "UT (Unique WOS ID)": "WOS:000667605500002", + "Markdown": "# Wearable materials with embedded synthetic biology sensors for biomolecule detection \n\nPeter Q. Nguyen $\\textcircled{10}1,2,10$ , Luis R. Soenksen $\\textcircled{1}$ 1,3,4,10, Nina M. Donghia1, Nicolaas M. Angenent-Mari1,4,5, Helena de Puig1,4, Ally Huang1,4,5, Rose Lee1, Shimyn Slomovic1, Tommaso Galbersanini6, Geoffrey Lansberry $\\textcircled{10}$ 1, Hani M. Sallum $@^{1}$ , Evan M. Zhao1, James B. Niemi1 and James J. Collins   1,4,5,7,8,9 ✉ \n\nIntegrating synthetic biology into wearables could expand opportunities for noninvasive monitoring of physiological status, disease states and exposure to pathogens or toxins. However, the operation of synthetic circuits generally requires the presence of living, engineered bacteria, which has limited their application in wearables. Here we report lightweight, flexible substrates and textiles functionalized with freeze-dried, cell-free synthetic circuits, including CRISPR-based tools, that detect metabolites, chemicals and pathogen nucleic acid signatures. The wearable devices are activated upon rehydration from aqueous exposure events and report the presence of specific molecular targets by colorimetric changes or via an optical fiber network that detects fluorescent and luminescent outputs. The detection limits for nucleic acids rival current laboratory methods such as quantitative PCR. We demonstrate the development of a face mask with a lyophilized CRISPR sensor for wearable, noninvasive detection of SARS-CoV-2 at room temperature within 90 min, requiring no user intervention other than the press of a button. \n\nSiycnatlhseytsitcebmisolaongdy h as pernoavbildeed uanrpircehcpeadlenttedofcomnotrdoul aorf biosleongcustom biological circuits1. In parallel, recent developments in wireless technology, wearable electronics, smart materials and functional fibers with new mechanical, electrical and optical properties have led to sophisticated biosensing systems2. Although genetically encoded sensors have been readily incorporated into bench-top diagnostics, examples of wearable devices using these tools are limited. Only a few demonstrations of hygroscopically actuated vents and response to induction molecules have been achieved using living engineered bacteria encapsulated in flexible substrates and hydrogels in a wearable format3–6. This approach encounters several limitations, particularly that of sustaining living organisms in the devices for extended periods. Retaining the viability and function of wearable sensing systems based on living cells requires nutrient delivery and waste extraction, as well as temperature and gas regulation, all of which involve numerous technological hurdles. Genetically engineered cells can also pose biocontainment or biohazard concerns, particularly if integrated into consumer-level garments. Moreover, the mutational pressures on evolving cell populations can result in loss of the genetic phenotype and function. An approach that could resolve the mismatch between the practical requirements of wearable use and the operational limitations of available biomolecular circuits for sensing and response would broaden the applications of wearable materials and may enable assessment of molecular targets difficult to detect through other technologies7. \n\nCell-free synthetic biology reactions are self-contained abiotic chemical systems with all the biomolecular components required for efficient transcription and translation. Such systems can be freeze-dried into shelf-stable formats utilizing porous substrates, which allow for robust distribution, storage and use without specialized environmental or biocontainment requirements8. Genetically engineered circuits, encoded in DNA or RNA, can be added to freeze-dried, cell-free (FDCF) reactions for activation by simple rehydration. Robust FDCF systems have already been developed for inexpensive paper-based nucleic acid diagnostics; sensitive programmable CRISPR-based nucleic acid sensors9,10; on-demand production of antimicrobials, antibodies and enzymes11; and low-cost educational kits for teaching12–14. Here we propose the use of FDCF genetic circuits in combination with specifically designed flexible and textile substrates to create practical wearable biosensors. We report on the design and validation of various wearable FDCF (wFDCF) sensors for small molecule, nucleic acid and toxin detection. The sensors are integrated into flexible multi-material substrates (for example, silicone elastomers and textiles) using genetically engineered components, including toehold switches, transcriptional factors, riboswitches, fluorescent aptamers and CRISPR–Cas12a complexes (Supplementary Fig. 1). \n\n# Results \n\nColorimetric wFDCF wearables. For our first wFDCF demonstration, we embedded colorimetric genetic circuits into cellulose substrates surrounded by a fluid wicking and containment assembly made of flexible elastomers. These prototypes were assembled layer-by-layer to form reaction chambers fluidically connected to top sample portals (Fig. 1a). The devices are flexible, elastic and can rapidly wick in splashed fluids through capillary action (Fig. $^{\\mathrm{1b,c}}.$ ). Pinning geometries throughout the device direct sample fluids towards enclosed hydrophilic paper networks allowing for reaction rehydration (Fig. 1c and Supplementary Fig. 3b). Using an lacZ $\\upbeta$ -galactosidase operon as the circuit output to hydrolyze chlorophenol red- $\\upbeta$ -d-galactopyranoside (CPRG), a yellow-to-purple color change develops upon exposure to a target (Supplementary Figs. 2b and 3a). \n\n![](images/14327e1e3b433218bcd6654f713448234507a9f03121358759742221490c9624.jpg) \nFig. 1 | Wearable cell-free synthetic biology. a, Schematic of the layer-by-layer assembly of the wearable devices. Each layer is fabricated from skin-safe silicone elastomer. The FDCF reactions are embedded in a cellulose matrix placed within each chamber. b, An array of assembled reaction chambers showing the elasticity (center) and flexibility (right) of the devices. c, Portals cut into the outermost layer allow sample access, which is rapidly drawn into the reaction chambers through capillary action. The hydrophobic chamber walls prevent inhibitory dilution through lateral diffusion. d–g, Various types of synthetic biology circuits can be freeze-dried in these wearable devices, for example, constitutively expressed outputs such as LacZ ( $^{\\star}P=0.015$ at $30\\mathrm{min}$ , $^{\\star\\star}P=0.008$ at $45\\mathsf{m i n}$ ) (d); transcription-factor-regulated circuits for small-molecule detection, here shown regulated by TetR $^{\\star}P=0.03$ at $30\\mathrm{min}$ , $^{\\star\\star}P=0.003$ at $35\\mathsf{m i n}$ ) ${\\bf\\Pi}(\\bullet)$ ; toehold switches for nucleic acid sensing such as the demonstrated Ebola RNA-targeting toehold $^{\\prime\\star}P=0.04$ at $25\\mathsf{m i n}$ , $^{\\star\\star}P=0.007$ at $30\\mathsf{m i n}.$ ) $(\\pmb{\\mathsf{f}})$ ; and riboswitches to detect various small molecules such as the theophylline-activated riboswitch ( $^{\\star}P=0.05$ at $25\\mathsf{m i n}$ , $^{\\star\\star}P=0.005$ at $35\\mathrm{{min}}$ ) $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ . Each plot shows mean (line) $\\pm5.0$ . (shaded region) of integrated green channel values from color-deconvoluted images from $\\scriptstyle n=3$ independently fabricated and tested wFDCF reaction chambers. Statistical significance between the two groups as indicated at specific time points was compared using an unpaired two-tailed Student’s t-test. Bottom images are representative color images of the wearable device. aTc, anhydrotetracycline. \n\nWe considered key environmental factors in the design of these prototypes. For instance, sample exposure in the field likely occurs with variable splash volumes (as little as $50\\mathrm{-}100\\upmu\\mathrm{l},$ , relative humidity $(20-40\\%)$ and temperature $(20-37^{\\circ}\\mathrm{C})$ . Thus, we optimized our design to reduce inhibition of genetic circuit operation due to evaporation or excessive dilution of components. In particular, our devices use impermeable chambers exhibiting low evaporation rates ${<}20\\%$ volume per h), which also constrain the rehydration volume to ${\\sim}50\\upmu\\mathrm{l}$ per sensor. In addition, the wFDCF reactions were optimized to generate a higher concentrated reaction upon rehydration. We found that a $\\times1.5$ -concentrated cell-free reaction increased the reaction kinetics to enable signal output at least $10\\mathrm{min}$ faster, ensuring that the desired circuit is completed before eventual evaporation in the device terminates the reaction (Extended Data Fig. 2). The resulting stand-alone colorimetric system is modular and can be used in garments such as bracelets (Supplementary Fig. 3c). \n\nWe tested this colorimetric wearable platform using four different synthetic biology biosensors with lacZ as the output (Fig. 1d–g). These demonstrations include a constitutive lacZ expression reaction (Fig. 1d), a transcription-factor-regulated circuit using the tetracycline repressor (TetR) for the detection of anhydrotetracycline (Fig. 1e), a toehold switch for the detection of Ebola virus RNA (Fig. 1f) and a theophylline riboswitch for small-molecule sensing (Fig. 1g). The TetR sensor shows that our colorimetric platform can integrate well-established transcription-factor-based modules into a wearable format (Fig. 1e). The toehold sensor enabled detection of Ebola virus RNA at a concentration of $300\\mathrm{nM}$ at $30\\mathrm{min}$ compared with a control sample containing no target (unpaired $t$ -test of independent reaction chambers; deconvoluted green channel \n\n$P{=}0.0074\\mathrm{\\cdot}$ ) (Fig. 1f). The riboswitch circuit was able to detect its target molecule, theophylline, at a concentration of $1\\mathrm{mM}$ at $35\\mathrm{min}$ compared with a control sample (unpaired $t$ -test of independent reaction chambers; deconvoluted green channel $P{=}0.005$ ) (Fig. 1g). All of the colorimetric wFDCF sensors reported here exhibited visible changes within ${\\sim}40{\\mathrm{-}}60\\operatorname*{min}$ after exposure to the respective trigger molecules or inducer, and were performed at ambient conditions of $30\\mathrm{-}40\\%$ relative humidity and $30^{\\circ}\\mathrm{C}$ to simulate the average skin surface temperature15. \n\nFluorescent wFDCF devices with fiber optic detection for enhanced sensing. Next, we immobilized and activated FDCF sensors in wearable woven fabrics and individual threads. Figure 2 presents various demonstrations of a highly sensitive, textile-based system (Fig. 2a,b) capable of containing and monitoring the activation of wFDCF reactions with fluorescent (Fig. 2c–e, Extended Data Figs. 4–7 and Supplementary Figs. 7 and 14) or luminescent (Fig. 2f and Extended Data Fig. 3) outputs. To achieve this, we integrated: (1) hydrophilic threads ( $85\\%$ polyester $15\\%$ polyamide) for cell-free reagent immobilization, (2) patterns of skin-safe hydrophobic silicone elastomers for reaction containment, and (3) inter-weaved polymeric optic fibers (POFs) for signal interrogation (Fig. $^{2\\mathrm{a},\\mathrm{b},}$ Extended Data Fig. 2 and Supplementary Fig. 8). This fabric was chosen as our main immobilization substrate after conducting a compatibility screening of over 100 fabrics (for example, silks, cotton, rayon, linen, hemp, bamboo, wool, polyester, polyamide, nylon and combination materials) using a lyophilized constitutive lacZ cell-free reaction (Supplementary Figs. 4–6). The analysis of sensor outputs was executed using a custom-built wearable POF spectrometer (Fig. 2b and Extended Data Fig. 8) that could be monitored with a mobile phone application (Supplementary Fig. 11). Using this integrated platform, we performed distributed on-body sensing of various target exposures as shown in Fig. 2c–f. A sample activation through fluid splashing is shown in Fig. 2a, where the sample wicks through the entry ports with blackout fabrics to rehydrate the FDCF synthetic biology reactions immobilized within the hydrophilic textile fibers. These fibers are located within the excitation and emission layers of the device as shown in Fig. 2a,b. Trigger presence in the splash fluid leads to activation of the sensor circuits, which produce fluorescent or luminescent reporters. \n\nWe first verified the function of this textile platform in fluorescence mode using two independent synthetic biology modules upstream of a superfolder green fluorescent protein (sfGFP) operon. These demonstrations included the activation of constitutive sfGFP expression (Fig. 2c) and sensing of theophylline using an inducible riboswitch (Fig. 2d). A third fluorescence demonstration was done via activation of a 49-nucleotide Broccoli aptamer (Fig. 2e) with substrate specificity to (Z)-4-(3,5-difluoro-4-hydroxybenzylidene)- 2-methyl-1-(2,2,2-trifluoroethyl)-1H-imidazol-5(4H)-one (DFHBI-1T)16. Furthermore, demonstrations utilizing luminescence outputs were conducted using a nanoluciferase (nLuc)17 operon downstream of a HIV RNA toehold switch (Fig. 2f and Extended Data Fig. 3a), as well as a Borrelia burgdorferi RNA toehold switch for the wearable detection of Lyme disease (Extended Data Fig. 3b). \n\nAdditionally, we tested the operation of our platform for the detection of chemical threats such as organophosphate nerve agents used in chemical warfare and the pesticide industry. To achieve this, we modified our POF platform optics for excitation and detection at near-infrared (NIR) fluorescence, generated from a lyophilized acetylcholinesterase (AChE)-choline oxidase-HRP-coupled enzyme reaction (Fig. 2g). In the presence of acetylcholine, this reaction can produce NIR fluorescence that is readily detectable with our wearable prototype. When exposed to an organophosphate AChE inhibitor, the sensor fluorescence is reduced as compared with unexposed controls. Our wearable nerve agent sensor was validated using paraoxon-ethyl as a nerve agent simulant at levels that are four orders of magnitude lower than the reported lethal dose $\\mathrm{(LD_{50})}$ by dermal absorption in mammals18. \n\nThe fluorescent wFDCF platform allows for continuous monitoring of all reaction chambers through the fiber optic network at user-defined sampling intervals for the automated detection of rehydration events and fluorescent outputs from target-activated circuits. This is achieved by illuminating the wFDCF textile reaction with blue light $(447\\mathrm{nm})$ via etched excitation POFs (Fig. 2b and Extended Data Fig. 2). The light emitted from the activated system is then collected by the second set of emission POFs, which exit the fabric weave and bundle into a single trunk connected to the optical sensor of our wearable spectrometer (Extended Data Figs. 2 and 8). Signals coming from each of the devices are filtered and processed to generate temporally and spatially resolved fluorescence images of the POF bundle-ends $(510\\mathrm{nm})$ and averaged pixel intensity traces per channel for quantitative analysis (Fig. 2b). In the case of luminescence demonstrations, all POF bundles are treated as signal emission sensors, without the need for sample illumination. All reported wFDCF fluorescence and luminescence sensor replicates $(n\\geq3)$ exhibited visible fluorescence or luminescence within $5{-}20\\mathrm{min}$ after exposure to relevant trigger conditions, at $30\\mathrm{-}40\\%$ relative humidity and $30^{\\circ}\\mathrm{C}$ . \n\nCRISPR-based wFDCF sensors enable direct nucleic acid detection in wearables. Sensors based on programmable CRISPR and CRISPR-associated (Cas) enzymes9,19,20 have several advantages over other biosensors, including high sensitivity, rapid output, single \n\nFig. 2 | Design and validation of fluorescent and luminescent FDCF synthetic biology wearables. a, Fiber optic-embedded textiles allow excitation and emission detection of rehydrated lyophilized biosensors. Bottom, an example rehydration event shows the aqueous sample being wicked through the portals into internal reaction wells. b, Top, side diagram showing the layers of the assembled device. Contaminated splashes access the device interior through portals in the top layer. Bottom, interior view of the device, where two layers of hydrophobically patterned fabric inter-woven with POFs in a coplanar arrangement allows for embedding of FDCF reaction components and excitation/emission lighting. Excitation POFs are illuminated by LED arrays and emission POFs are bundled to an optical sensor containing a filter (for fluorescence only) and collimating lens. c, Fluorescent signal after rehydration of wFDCF constitutive sfGFP template as compared with control. Fluorescence is statistically distinguishable from the control after $14\\mathrm{min}$ ${}^{\\stackrel{\\star}{\\prime}}P=0.04{}^{\\cdot}$ and $20\\min$ ${\\bf\\Phi}^{\\star\\star}P=0.002;$ ). d, Activation of wFDCF riboswitch with 1 mM theophylline compared with $0.m M$ theophylline control. Statistically distinguishable signals after $19.5\\mathsf{m i n}$ ( ${}^{\\star}P=0.04;$ and $25\\mathrm{{min}}$ 0 $^{\\star\\star}P=0.008;$ ). e, Wearable demonstration of fluorescent aptamer being activated by the presence of $50\\upmu\\upmu$ DFHBI-1T substrate compared with no substrate control. Fluorescent signal is statistically distinguishable after $24.5\\mathsf{m i n}$ ( ${}^{\\prime\\star}P=0.04{}_{\\cdot}^{\\prime}$ ) and 35 min $^{\\prime\\star\\star}P=0.01;$ . f, An HIV toehold sensor with luminescence output. HIV RNA trigger was added at $10\\upmu\\upM$ and was statistically distinguishable from the control ${}^{\\star}P=0.01$ at $6\\mathrm{{min}}$ , $^{\\star\\star}P=0.005$ at $7\\mathsf{m i n}.$ ). g, Wearable detection of organophosphate nerve agents using a lyophilized HRP-coupled enzyme sensor with $50\\mathsf{m}\\mathsf{M}$ acetylcholine with and without $3.7\\mathrm{mg}\\mathrm{m}|^{-1}$ paraoxon-ethyl (AChE inhibitor). Statistical differences from controls are indicated $^{\\star}P=0.03$ at $7\\min$ , $^{\\star\\star}P=0.001$ at $9\\mathsf{m i n}.$ ). All images above plots are recorded POF bundle images synchronized with the reaction time profiles. All plots show mean pixel intensity values (dark data points) $\\pm\\mathsf{s.d}$ . (light colored region). Each experiment is a total of $\\scriptstyle n=9$ fiber optic outputs per condition. Any fibers that were 1 s.d. below the mean of all nine fiber outputs were excluded. Statistical significance was determined by unpaired one-tailed Student’s t-test. Scale bars in brightfield images are $250\\upmu\\mathrm{m}$ . ${\\mathsf{C h O x}},$ choline oxidase; Em, emission; $\\mathsf{E x},$ excitation; RFU, relative fluorescence units. \n\nbase-pair resolution, freeze-drying compatibility and programmability to target any DNA or RNA sequence through interchangeable guide RNAs (gRNAs). Thus, we integrated CRISPR-based specific high-sensitivity enzymatic reporter unlocking (SHERLOCK) sensors into our fluorescence wFDCD platform to demonstrate this detection technique in wearable applications (Fig. 3a). We used Cas13a and Cas12a for the detection of RNA and DNA, respectively. For DNA detection, we used a Cas12a ortholog from Lachnospiraceae bacterium (LbaCas12a)19,21 that displays a nonspecific collateral cleavage activity towards single-stranded DNA (ssDNA) after detection of a gRNA-defined double-stranded DNA (dsDNA) target. This Cas12a-based sensor was paired with recombinase polymerase amplification (RPA)22 and freeze-dried into a one-pot reaction. In the presence of a target dsDNA sequence, isothermally generated RPA amplicons activate Cas12a–gRNA complexes. Then, active Cas12a engages in trans-ssDNase activity and cleaves quenched ssDNA fluorophore probes, resulting in a fluorescence output (Fig. 3a). \n\n![](images/dc11fd0ed78e80deedb090a7f1f0e9c6407f5d59254d1aecc13293c836f62776.jpg) \nNature Biotechnology | www.nature.com/naturebiotechnology \n\n![](images/d14254155235bf58ca1550d053431cd6505aaf73cfa0a88a5958af1a41fd2d32.jpg) \nFig. 3 | Validation of CRISPR-based FDCF wearable sensors. a, The sensing mechanism of the CRISPR–Cas12a system is based on catalytic trans-cleavage of fluorophore-quencher ssDNA probes after activation by an RPA-amplified dsDNA trigger. b, wFDCF mecA CRISPR-based sensor exposed to sample containing 100 fM mecA trigger. Statistically distinguishable signals are indicated for specific time points ( $^{\\prime\\star}P=0.04$ at $68\\mathsf{m i n}$ , $^{\\star\\star}P=0.007$ at $76\\mathsf{m i n}.$ ). c, wFDCF spa CRISPR-based sensor exposed to 100 fM spa trigger $^{\\star}P=0.03$ at 51 min, $^{\\star\\star}P=0.006$ at $62\\mathsf{m i n}$ ). d, wFDCF ermA CRISPR-based sensor exposed to 100 fM ermA trigger ( $^{\\prime\\star}P=0.04$ at $20\\mathrm{min}$ , $^{\\star\\star}P=0.009$ at $60\\mathsf{m i n}$ ). e, Experimental detection of mecA CRISPR-based sensor at 2.7 fM trigger was statistically distinguishable ${}^{\\star}P=0.04$ at $72\\mathrm{min}$ , $^{\\star\\star}P=0.001$ at $82\\mathsf{m i n};$ ), corresponding to 10,000 dsDNA-copies per $\\upmu\\upmu\\upmu$ . Plots b–e show mean pixel intensity (dark data points) $\\pm5.0$ . (light colored region) from three independent wells, each having three fiber optic sensors, for a total of $\\scriptstyle n=9$ fiber optic outputs. Any fibers below 1 s.d. of the mean of all nine fiber outputs were excluded from analysis. Statistical significance calculated as unpaired one-tailed Student’s t-test is indicated for specific time points. f, Orthogonality demonstration of mecA/spa/ermA CRISPR-based multi-sensor wearables. g, Rehydration only yielded activation of sensors when the Cas12a–gRNA sensor was in the presence of its programmed trigger dsDNA as shown by comparing signal intensities from all sensor-trigger combinations. h, Example fluorescence activation of different CRISPR-based sensors upon exposure to specific dsDNA triggers. These experiments were repeated three times with similar results. Scale bars shown are $250\\upmu\\mathrm{m}$ . i, Garment-level integration of fabric-based wearable synthetic biology sensors. Distributed continuous sensing of garment activity can be achieved through multi-bundle imaging. j, Connection of fabric-based module to wearable POF spectrometer with wireless connectivity capabilities. The spectrometer electronics consist of a Raspberry Pi Zero W with a camera module (Raspberry Pi Foundation), as well as LED illumination, environmental sensing and custom-fabricated shields for battery power. The smartphone application for visualization and alarm of wFDCF sensor activation was based on the blynk.io platform (Blynk) which provides support for Raspberry Pi communication. This application allows for wireless recording of experiments and control of device parameters, as well as environmental and geolocation information. CMOS, complementary metal–oxide–semiconductor; L, length. \n\nFor wearable demonstrations, we designed gRNAs against three common resistance markers in Staphylococcus aureus: the mecA gene common in methicillin-resistant S. aureus (MRSA)23, the spa gene which encodes the protein A virulence factor24 and the ermA gene conferring macrolide resistance25. When tested in wFDCF format, the RPA-Cas12a sensors displayed detectable signals within $56{-}78\\mathrm{min}$ $(P{<}0.05)$ with femtomolar limits of detection (Fig. 3b–d). Moreover, using our mecA wFDCF sensor (Fig. 3e and Extended Data Fig. 4), we confirmed single-digit femtomolar sensitivity (2.7 fM). Compatibility with RNA inputs and other CRISPR enzymes such as Cas13a, an ortholog from Leptotrichia wadei bacterium (LwaCas13a)9, was also confirmed (Extended Data Fig. 5), exhibiting similar in-device activation dynamics as that of cell-free reactions conducted in a plate reader. These results suggest that our wearable textile platform could be adapted to achieve sensitivities rivaling those of current laboratory diagnostic tests such as quantitative PCR (qPCR) for monitoring contamination or spread of bacteria and viruses. \n\nTo further demonstrate the modularity of our CRISPR–Cas12a wearable sensors, we tested wFDCF devices containing three orthogonal Cas12a–gRNA complexes in isolated reaction wells (Fig. 3f). In this experiment, each device was splashed with dd- $_\\mathrm{\\cdotH_{2}O}$ containing different targets, each specific to only one Cas12a–gRNA complex. The orthogonal behavior of our CRISPR-based wearable sensors is shown in Fig. $^{3\\mathrm{g,h}}$ , where higher fluorescence was observed for the cases in which the dsDNA trigger matched the predefined Cas12a– gRNA complex at each sensor location. \n\nWith the goal of real-time monitoring of environmental exposure and biohazard detection, we designed a jacket containing a distributed arrangement of wFDCF multi-sensor arrays (Fig. 3i). The various optical fibers carrying the output emission signals from different sensors can be routed into a single bundle for centralized imaging analysis, which we demonstrate using a wFDCF CRISPR–Cas12a-based MRSA-sensing array, containing spa, ermA and mecA sensors, that was activated in the wearable prototype with a fluid splash containing $100\\mathrm{fM}$ of spa DNA trigger (Extended Data Fig. 6). Only the well containing the spa sensor generated a fluorescent signal upon activation. The platform is also compatible with transcription-only outputs, such as rehydrated fluorescent aptamer reactions (Supplementary Fig. 9), where the fluorescence signal is monitored by microscopy over time. \n\nIn addition, the optical sensor allows for facile fluorescent output multiplexing simply by using fluorescent proteins with orthogonal emission profiles (Extended Data Fig. 7). In this example, wFDCF reactions for three constitutively expressed fluorescent output proteins (eforRed26, dTomato27 and $\\mathbf{sfGFP^{28}},$ ) were used to detect distinguishable output signals in a single bundle. We also show that the wFDCF POF system is fully compatible with integrated lyophilized lysis components, allowing for the release and detection of a plasmid-borne mecA gene when challenged with intact bacterial cells (Supplementary Fig. 10). Finally, to develop a complete data feedback cycle between the platform and the user, we integrated the detector system with a custom wireless mobile application that enables continuous cloud-based data logging, signal processing, geolocation tracking and on-the-fly control of various detector components through a smartphone or other networked digital device (Fig. 3j). All images and spectral data presented in Figs. 2 and 3 were collected and processed using wFDCF devices fully integrated with our wearable spectrometer and mobile phone application. Further details on the hardware and software design, as well as implementation of an Opuntia microdasys bioinspired fluid collection29 add-on for improved sample harvesting and routing splashes outside of the sensor zones into the wFDCF modules, can be found in Extended Data Fig. 8 and Supplementary Figs. 11 and 12. \n\nA face-mask-integrated sensor for SARS-CoV-2 detection in exhaled aerosols. Finally, we explored whether our wFDCF system could be adapted to create face masks capable of detecting SARS-CoV-2, as a complementary approach to diagnosis based on nasopharyngeal sampling. Respiratory droplets and aerosols are the transmission routes for respiratory infectious diseases but have been underutilized historically for diagnosis. Work on breath-based sensing has focused on the detection of volatile organic compound biomarkers in infected patients using electrochemical sensors30,31 or downstream mass spectrometry analysis32, which may be challenging to implement on a wide scale. The National Institutes of Health Rapid Acceleration of Diagnostics Initiative has identified SARS-CoV-2 detection from breath sampling technologies as an active area of interest for alleviating testing bottlenecks33. \n\nThe virus accumulates on the inside of masks as a result of coughing, talking or normal respiration34–36. We designed a face-mask sensor containing four modular components: a reservoir for hydration, a large surface area collection sample pad, a wax-patterned $\\upmu\\mathrm{PAD}$ (microfluidic paper-based analytical device) and a lateral flow assay (LFA) strip (Fig. 4a,b). Each module can be oriented on the outside or inside of the face mask, with the exception of the collection pad, which must be positioned on the mask interior facing the mouth and nose of the patient. Capillary action wicks any collected fluid and viral particles from the sample collection pad to the $\\upmu\\mathrm{PAD}.$ which contains an arrangement of freeze-dried lysis and detection components (Fig. 4c). The use of the $\\upmu\\mathrm{PAD}$ format allowed us to rapidly prototype and optimize a passively regulated multi-step reaction process. Each reaction zone is separated by polyvinyl alcohol (PVA) time delays that enable tunable incubation times between each reaction, greatly improving the efficiency of the sensor compared with that of a one-pot lyophilized reaction (Supplementary Fig. 13). The first $\\upmu\\mathrm{PAD}$ reaction zone contains lyophilized lysis reagents including components known to lyse viral membranes37–39. The second $\\upmu\\mathrm{PAD}$ reaction zone is a reverse transcription–recombinase polymerase amplification (RT-RPA) reaction zone containing a customized isothermal amplification reaction developed to target a nonoverlapping region of the SARS-CoV-2 S gene. The final $\\upmu\\mathrm{PAD}$ reaction zone contains a Cas12a SHERLOCK sensor with an optimized $\\mathrm{{gRNA}}$ for detection of the amplified dsDNA amplicon. In the presence of SARS-CoV-2-derived amplicons, the activated Cas12a enables trans-cleavage of a co-lyophilized 6-FAM(TTATTATT)-Biotin ssDNA probe. To enable a simple colorimetric visual readout, an integrated LFA strip is used to detect probe cleavage. The output strip orientation is adjustable to preserve patient confidentiality. Details on the design, performance and rele­ vant molecular sensor sequences are presented in Supplementary Figs. 14 and 15. \n\nFrom activation of the face-mask sensor to a final readout only takes ${\\sim}1.5\\mathrm{h}$ . The limit of detection observed for our sensors is 500 copies (17 aM) of SARS-CoV-2 in vitro transcribed (IVT) RNA, which matches that of World Health Organization-endorsed standard laboratory-based RT–PCR assays40 (Fig. 4d,e). The sensors also do not cross-react to RNA from other commonly circulating human coronavirus strains (HCoVs) (Fig. 4f,g). Notably, our hands-off diagnostic reaction proceeds to full completion even at room temperature, which is considered suboptimal for RT, RPA and Cas12a activities. We also validated the SARS-CoV-2 face-mask sensor using a precision lung simulator attached to a high-fidelity \n\nFig. 4 | A face-mask-integrated SARS-CoV-2 wearable diagnostic. a, Schematic of the sensor components. Puncture of the water blister reservoir results in flow through wicking material, moving viral particles collected from the wearer’s respiration from the sample collection zone to downstream freeze-dried reactions integrated into a $\\upmu\\mathsf{P A D}$ device. The final output is visualized by an LFA strip that is passed externally through the mask. b, Photographs of the SARS-CoV-2 sensor integrated into a face mask. An A-version sensor is shown. c, Key steps of the freeze-dried reactions, each separated by a PVA time delay. Lysis first releases SARS-CoV-2 vRNA, RT-RPA next targets the S gene for signal amplification at room temperature and finally Cas12a detection of the RPA amplicons results in collateral cleavage of FAM-Biotin ssDNA probes. The reaction flows into the LFA where the visual band pattern formation is dependent upon probe cleavage. d, Sensitivity of the A-version face-mask sensors at various inputs on the sensor zone of IVT-generated SARS-CoV-2 S-gene RNA. The limit of detection threshold, $+35.0$ . of the no-template control (NTC), is shown as a red dotted line. e, Representative images of LFA outputs from the sensitivity measurements. f, Specificity demonstration of A-version face-mask sensors shows no cross-reactivity with IVT RNA from other commonly circulating HCoVs. SARS-CoV-2 RNA was added at 100,000 copies. All other HCoV RNAs were tested at 1,000,000 copies. g, Representative images of LFA outputs from the specificity measurements. h, Breath emission simulator setup consisting of a lung simulator for spontaneous breathing generation, a vibrating-mesh nebulizer for aerosol generation and a high-fidelity airway simulator for anatomically precise air flow to the face mask. A B-version face-mask sensor is shown on the simulator. i, On-simulator testing of B-version face-mask sensors under conditions simulating physiological respiratory emission of SARS-CoV-2 target and a face-mask microclimate. j, Representative images of LFA outputs from the on-simulator measurements. All plots (d, f, i) show quantified LFA test band to control band intensity ratios as mean $\\pm{\\mathsf{s.d}}$ from $n{=}4$ independently fabricated and tested face-mask sensors for each of the indicated conditions. AuNP, gold nanoparticle. \n\nhuman airway model (Fig. 4h and Supplementary Fig. 16). The target RNA was nebulized to replicate lung emissions with aerosol diameters matching those naturally occurring in breath exhalation plumes. The breath temperature was regulated to $35^{\\circ}\\mathrm{C}$ and the relative humidity in the mask microclimate was measured to be $100\\%$ relative humidity. Under these realistic simulation conditions, the face-mask sensor was able to detect a contrived SARS-CoV-2 viral RNA (vRNA) fragment after a breath sample collection period of $30\\mathrm{min}$ , with a calculated accumulation of $10^{6}–10^{7}$ vRNA copies on the sample pad, as determined by qPCR with reverse transcription (RT–qPCR) (Fig. 4i,j). Clinical measurements have previously shown that the SARS-CoV-2 breath emission rate of infected patients could reach an output $10^{3}–10^{5}$ copies per min (ref. 35). \n\n![](images/4c459af9eddc913748a199737fe5ed8af6d88ee8ccb1407c708758be26f2f53c.jpg) \n\nUnlike other current nucleic acid tests that require laboratory equipment and trained technicians41–45, our SARS-CoV-2 face-mask sensor requires no power source, operates autonomously without liquid handling, is shelf-stable, functions at near-ambient temperatures, provides a visual output in under $2\\mathrm{h}$ and is only ${\\sim}3\\mathrm{g}$ in weight. All the user has to do is press a button to activate a reservoir containing nuclease-free water. To our knowledge, no other SARS-CoV-2 nucleic acid test achieves high sensitivity and specificity while operating fully at ambient temperatures, allowing integration into a wearable format. We believe our SARS-CoV-2 mask could combine protection and sensing into one system and could be adapted to discriminate between SARS-CoV-2 and other respiratory viruses, as well as different emerging SARS-CoV-2 variants46,47. \n\n# Discussion \n\nWe view the wFDCF platform as being complementary to cell-based synthetic biology sensors. We have shown that it enables wearable biosensors that are shelf-stable, genetically programmable and highly sensitive. However, the current wFDCF technology does have a number of limitations, including the single-use nature of the sensors and inability to operate in particular environmental conditions, such as high humidity or underwater. These challenges are also shared by other sensors in which operation requires open access to the environment and will require further engineering to surmount. Our wFDCF sensors are responsive to external rehydration events, such as splashes with contaminated fluids, and withstand inhibitory evaporative and dilutive effects in open-environment conditions $(30-40\\%$ relative humidity and ${\\sim}25{\\mathrm{-}}30^{\\circ}\\mathrm{C})$ . Alternatively, user-generated samples such as breath emissions can be used if an on-demand hydration system is employed, as we demonstrate for the SARS-CoV-2-sensing face mask. We showed that these freeze-dried systems generate measurable colorimetric, fluorescence or luminescence outputs upon exposure to relevant real-world targets such as MRSA, Ebola virus or SARS-CoV-2 virus. In the wFDCF POF sensors, continuous monitoring enables rapid alert to an exposure event. We also demonstrated the integration of our device designs into garments that are compatible with wireless sensor networks to provide real-time dynamic monitoring of exposure using custom smartphone applications. Although laboratory testing may be more sensitive, our wFDCF sensors have the advantages of a wearable format, autonomous functioning and rapid results. \n\nTo our knowledge, no previous wearable technology has detected viral or bacterial nucleic acid signatures in fluid samples with sensitivities rivaling those of traditional laboratory tests at ambient temperatures. Compared with point-of-care diagnostics, which similarly attempt to eliminate time-consuming and resource-intensive laboratory tests, our sensors do not require the manual application of a swabbed or directly applied sample to provide a readout. They accomplish field sensing on the surface of the user or on surfaces exposed to patient samples, such as the inside of a face mask. Moreover, in contrast to batch-mode point-of-care sensors, they can be networked to provide spatial sensing arrays of lyophilized reactions and lightweight polymer fabrics, thus cloaking the user and continuously generating high-density, real-time outputs without sacrificing comfort or agility in the field. They are designed to operate autonomously and do not require training for use or multiple operations by the user to acquire results, which removes the need to perform regular exposure checks. In contrast to wearable sensors that primarily employ electronic devices to monitor physiological signals such as heart rate or blood oxygen levels, our sensors detect environmental threats or pathogens through nucleic acids, proteins or small molecules. Although electrochemical sensors have been integrated into a wearable format31,48, they only detect chemicals, and an easily programmable wearable form for sensitive nucleic acid detection does not currently exist. Integration of our wearable synthetic biology reactions with these advances in electrochemical devices could be a fertile area for expanding the functionality of wearable sensors31,49. We have also shown that the sensors can be highly modular and adapted to various form factors, such as clothing or face masks. The key functional differences of our platform over current related technologies, including traditional bench-top assays, are summarized in Supplementary Table 4. \n\nPotential field applications for our wFDCF sensors include warfighters and first responders operating in environments where a specific chemical or biological threat is suspected, and clinicians, health workers and researchers working in high-risk areas. For example, wFDCF-enabled coats and gowns in hospitals could provide alerts to prevent the spread of nosocomial infections. An additional promising application is patient-worn, sensor-enabled personal protective equipment, such as the SARS-CoV-2 face mask. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/ s41587-021-00950-3. \n\nReceived: 8 November 2019; Accepted: 10 May 2021; Published: xx xx xxxx \n\n# References \n\n1.\t Khalil, A. S. & Collins, J. J. Synthetic biology: applications come of age. Nat. Rev. Genet. 11, 367–379 (2010). \n2.\t Tao, X. Smart Fibres, Fabrics and Clothing: Fundamentals and Applications (Elsevier, 2001). \n3.\t Liu, X. et al. Stretchable living materials and devices with hydrogel-elastomer hybrids hosting programmed cells. Proc. Natl Acad. Sci. USA 114, 2200–2205 (2017). \n4.\t Liu, X. et al. 3D printing of living responsive materials and devices. Adv. Mater. 30, 1704821 (2018). \n5.\t Moser, F., Tham, E., González, L. M., Lu, T. K. & Voigt, C. A. Light-controlled, high-resolution patterning of living engineered bacteria onto textiles, ceramics, and plastic. Adv. Func. Mater. 29, 1901788 (2019). \n6.\t Wang, W. et al. Harnessing the hygroscopic and biofluorescent behaviors of genetically tractable microbial cells to design biohybrid wearables. Sci. Adv. 3, e1601984 (2017). \n7.\t Slomovic, S., Pardee, K. & Collins, J. J. Synthetic biology devices for in vitro and in vivo diagnostics. Proc. Natl Acad. Sci. USA 112, 14429–14435 (2015). \n8.\t Pardee, K. et al. Paper-based synthetic gene networks. Cell 159, 940–954 (2014). \n9.\t Gootenberg, J. S. et al. Nucleic acid detection with CRISPR-Cas13a/C2c2. Science 356, 438–442 (2017). \n10.\tEnglish, M. A. et al. Programmable CRISPR-responsive smart materials. Science 365, 780–785 (2019). \n11.\tPardee, K. et al. Portable, on-demand biomolecular manufacturing. Cell 167, 248–259 e212 (2016). \n12.\tHuang, A. et al. BioBits Explorer: a modular synthetic biology education kit. Sci. Adv. 4, eaat5105 (2018). \n13.\tStark, J. C. et al. BioBits Bright: a fluorescent synthetic biology education kit. Sci. Adv. 4, eaat5107 (2018). \n14.\tStark, J. C. et al. BioBits Health: classroom activities exploring engineering, biology, and human health with fluorescent readouts. ACS Synth. Biol. 8, 1001–1009 (2019). \n15.\t Choi, J. K., Miki, K., Sagawa, S. & Shiraki, K. Evaluation of mean skin temperature formulas by infrared thermography. Int. J. Biometeorol. 41, 68–75 (1997). \n16.\tFilonov, G. S., Kam, C. W., Song, W. & Jaffrey, S. R. In-gel imaging of RNA processing using broccoli reveals optimal aptamer expression strategies. Chem. Biol. 22, 649–660 (2015). \n17.\tHall, M. P. et al. Engineered luciferase reporter from a deep sea shrimp utilizing a novel imidazopyrazinone substrate. ACS Chem. Biol. 7, 1848–1857 (2012). \n18.\tHayes’ Handbook of Pesticide Toxicology (ed. Krieger, R.) (Academic Press, 2010). \n19.\tChen, J. S. et al. CRISPR-Cas12a target binding unleashes indiscriminate single-stranded DNase activity. Science 360, 436–439 (2018). \n20.\tGootenberg, J. S. et al. Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6. Science 360, 439–444 (2018). \n21.\tLi, S.-Y. et al. CRISPR-Cas12a has both cis- and trans-cleavage activities on single-stranded DNA. Cell Res. 28, 491 (2018). \n22.\tPiepenburg, O., Williams, C. H., Stemple, D. L. & Armes, N. A. DNA detection using recombination proteins. PLoS Biol. 4, e204 (2006). \n23.\tLee, A. S. et al. Methicillin-resistant Staphylococcus aureus. Nat. Rev. Dis. Primers 4, 18033 (2018). \n24.\tFalugi, F., Kim, H. K., Missiakas, D. M. & Schneewind, O. Role of protein A in the evasion of host adaptive immune responses by Staphylococcus aureus. mBio 4, e00575–00513 (2013). \n25.\tWesth, H., Hougaard, D. M., Vuust, J. & Rosdahl, V. T. Prevalence of erm gene classes in erythromycin-resistant Staphylococcus aureus strains isolated between 1959 and 1988. Antimicrob. Agents Chemother. 39, 369–373 (1995). \n26.\tAlieva, N. O. et al. Diversity and evolution of coral fluorescent proteins. PLoS ONE 3, e2680 (2008). \n27.\tShaner, N. C. et al. Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein. Nat. Biotechnol. 22, 1567–1572 (2004). \n28.\tPedelacq, J. D., Cabantous, S., Tran, T., Terwilliger, T. C. & Waldo, G. S. Engineering and characterization of a superfolder green fluorescent protein. Nat. Biotechnol. 24, 79–88 (2006). \n29.\tJu, J. et al. A multi-structural and multi-functional integrated fog collection system in cactus. Nat. Commun. 3, 1247 (2012). \n30.\tGouma, P. I., Wang, L., Simon, S. R. & Stanacevic, M. Novel isoprene sensor for a flu virus breath monitor. Sensors 17, 199 (2017). \n31.\tMaier, D. et al. Toward continuous monitoring of breath biochemistry: a paper-based wearable sensor for real-time hydrogen peroxide measurement i simulated breath. ACS Sens. 4, 2945–2951 (2019). \n32.\tGould, O., Ratcliffe, N., Krol, E. & de Lacy Costello, B. Breath analysis for detection of viral infection, the current position of the field. J. Breath Res. 14, 041001 (2020). \n33.\tTromberg, B. J. et al. Rapid scaling up of Covid-19 diagnostic testing in the United States—the NIH RADx initiative. N. Engl. J. Med. 383, 1071–1077 (2020). \n34.\tLiu, Y. et al. Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals. Nature 582, 557–560 (2020). \n35.\tMa, J. et al. Exhaled breath is a significant source of SARS-CoV-2 emission. Preprint at medRxiv https://doi.org/10.1101/2020.05.31.20115154 (2020). \n36.\tLeung, N. H. L. et al. Respiratory virus shedding in exhaled breath and efficacy of face masks. Nat. Med. 26, 676–680 (2020). \n37.\tDarnell, M. E., Subbarao, K., Feinstone, S. M. & Taylor, D. R. Inactivation of the coronavirus that induces severe acute respiratory syndrome, SARS-CoV. J. Virol. Methods 121, 85–91 (2004). \n38.\tShen, S. et al. The severe acute respiratory syndrome coronavirus 3a is a novel structural protein. Biochem. Biophys. Res. Commun. 330, 286–292 (2005). \n39.\tGui, M. et al. Electron microscopy studies of the coronavirus ribonucleoprotein complex. Protein Cell 8, 219–224 (2017). \n40.\t Vogels, C. B. F. et al. Analytical sensitivity and efficiency comparisons of SARS-CoV-2 RT–qPCR primer–probe sets. Nat. Microbiol. 5, 1299–1305 (2020). \n41.\tBaek, Y. H. et al. Development of a reverse transcription-loop-mediated isothermal amplification as a rapid early-detection method for novel SARS-CoV-2. Emerg. Microbes Infect. 9, 998–1007 (2020). \n42.\tJoung, J. et al. Point-of-care testing for COVID-19 using SHERLOCK diagnostics. Preprint at medRxiv https://doi.org/10.1101/2020.05.04.20091231 (2020). \n43.\tArizti-Sanz, J. et al. Streamlined inactivation, amplification, and Cas13-based detection of SARS-CoV-2. Nat. Commun. 11, 5921 (2020). \n44.\tYan, C. et al. Rapid and visual detection of 2019 novel coronavirus (SARS-CoV-2) by a reverse transcription loop-mediated isothermal amplification assay. Clin. Microbiol. Infect. 26, 773–779 (2020). \n45.\tBroughton, J. P. et al. CRISPR-Cas12-based detection of SARS-CoV-2. Nat. Biotechnol. 38, 870–874 (2020). \n46.\tKoyama, T., Weeraratne, D., Snowdon, J. L. & Parida, L. Emergence of drift variants that may affect COVID-19 vaccine development and antibody treatment. Pathogens 9, 324 (2020). \n47.\tLi, Q. et al. The impact of mutations in SARS-CoV-2 spike on viral infectivity and antigenicity. Cell 182, 1284–1294 e1289 (2020). \n48.\tBarfidokht, A. et al. Wearable electrochemical glove-based sensor for rapid and on-site detection of fentanyl. Sens. Actuators B Chem. 296, 126422 (2019). \n49.\tDincer, C. et al. Disposable sensors in diagnostics, food, and environmental monitoring. Adv. Mater. 31, e1806739 (2019). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. $\\circledcirc$ The Author(s), under exclusive licence to Springer Nature America, Inc. 2021 \n\n# Methods \n\nFabrication of colorimetric synthetic biology wearable modules. Translucent (Fig. 1a, top) and opaque (Fig. 1a, middle/bottom) layers were made using skin-safe Ecoflex silicone elastomer (Smooth-On), precast overnight and laser-cut on a 75 W Epilog Legend 36EXT, according to the layouts shown in Fig. 1a and Supplementary Fig. 2a. After laser-cutting, the silicone pieces were placed in a warm wash $(45^{\\circ}\\mathrm{C})$ with Tergazyme detergent (Alconox) for 1 h with agitation, followed by three washes in $18\\ –\\Omega$ pure water and a final wash in $70\\%$ ethanol, before allowing them to air-dry. Layers were aligned and bonded together by depositing freshly made, uncured liquid silicone elastomer and post-curing overnight at $65^{\\circ}\\mathrm{C}$ in a well-ventilated oven to obtain the final assembled prototypes. The final assembled elastomer prototypes were thoroughly sprayed with RNase Away Decontaminant (Thermo Fisher Scientific) and washed with $70\\%$ ethanol twice before being stored in petri dishes. \n\nFor the support matrices housing the cell-free reactions, clean Whatman No. 4 filter-papers (GE Healthcare Lifesciences) (Fig. 1a, reaction insert) were punched to obtain cellulose discs with dimensions of $8\\mathrm{-mm}$ diameter and $0.5\\mathrm{-mm}$ thickness. These discs were incubated overnight in $0.01\\%$ diethyl pyrocarbonate, washed three times with nuclease-free water, then incubated with $5\\%$ BSA (MilliporeSigma) in $50\\mathrm{mM}$ Tris buffer, $\\mathrm{pH}7.5$ , for 1 h with gentle agitation. The prepared BSA-blocked discs were frozen at $-80^{\\circ}\\mathrm{C}$ and subsequently freeze-dried. These lyophilized BSA-blocked discs were used as a scaffold for the deposition of colorimetric wearable synthetic biology reactions in wFDCF sensors. The saturated reaction discs were finally snap-frozen in liquid nitrogen and freeze-dried for $8{-}12\\mathrm{h}$ in an SP Scientific Freezemobile lyophilizer (SP Industries). \n\nFreeze-dried reaction discs were then inserted through the wicking ports of the elastomer chambers for assembly. The silicone elastomer chambers in the colorimetric device exhibit three $3\\times5\\mathrm{-}\\mathrm{mm}^{2}$ curved wicking ports in each of the four wells, which allow inflow routes for fluid entry while delaying evaporation of cell-free reaction (Supplementary Fig. 2a). The device chamber walls were aligned and bonded using uncured elastomer, to prevent flow or lateral diffusion of the reaction after rehydration. The wicking of contaminated fluid through the entry ports is primarily mediated by capillary action. An exposure event leads to rehydration of the reaction disc containing the chosen FDCF system, which marks $\\scriptstyle t=0$ in the validation experiments (Fig.1d–g). A magnified photograph of an activated reaction well containing an Ebola virus DNA toehold wFDCF sensor is shown in Supplementary Fig. 3a, whereas the activation of a fabricated wearable bracelet using the same system is depicted in Supplementary Fig. 3c. All of the colorimetric wFDCF sensors were tested at $30^{\\circ}\\mathrm{C}$ and ambient humidity to simulate surface body temperature. \n\nPreparation of optimized colorimetric wearable synthetic biology reactions. Each colorimetric wFDCF reaction used for lyophilization, assuming a $50\\mathrm{-}\\upmu\\mathrm{l}$ rehydration volume, was a $75\\mathrm{-}\\upmu\\mathrm{l}$ cell-free NEB PURExpress reaction (New England Biolabs). Thus, each rehydrated reaction is a $\\times1.5$ -concentrated cell-free reaction based on the suggested reaction composition indicated by the manufacturer. Each reaction consisted of: $30\\upmu\\mathrm{l}$ of PURExpress Component A, $22.5\\upmu\\mathrm{l}$ of PURExpress Component B, $0.6\\mathrm{mg}\\mathrm{ml}^{-1}$ CPRG (MilliporeSigma), 76 U of RNase Inhibitor (Roche) and a DNA template encoding the desired artificial genetic circuit at $5\\mathrm{ng}\\upmu\\mathrm{l}^{-1}$ . For the TetR transcriptional regulation circuit, FPLC-purified recombinant TetR protein was supplemented in the reaction at a concentration of $120\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ . During activation of the various wFDCF reactions by rehydration, pure nuclease-free $\\mathrm{H}_{2}\\mathrm{O}$ was used for the constitutive LacZ circuit, $25\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ anhydrotetracycline (aTc) inducer was used for the TetR-regulated circuit, $300\\mathrm{nM}$ of Ebola viral genome trigger was used for the toehold regulated circuit and $1\\mathrm{mM}$ of theophylline was used for the riboswitch-regulated circuit. The theophylline riboswitch reactions also included 2-phenylethyl $\\upbeta$ -d-thiogalactoside (MilliporeSigma), a $\\upbeta$ -galactosidase inhibitor, at a final concentration of $250\\upmu\\mathrm{M}$ to suppress the background due to leakiness in these genetic circuits. The Ebola RNA genome trigger was acquired by an in vitro transcription reaction utilizing the HiScribe T7 Quick High Yield RNA Synthesis Kit (New England Biolabs), using a DNA template as indicated in Supplementary Table 2. Each wFDCF reaction was applied to a BSA-blocked cellulose disc inserted into a 2-ml microcentrifuge tube. After the reaction was absorbed into the disc, the tubes were submerged in liquid nitrogen to snap-freeze the disc and allowed to lyophilize for 12 h. All of the colorimetric wFDCF sensors were tested at $30^{\\circ}\\mathrm{C}$ and ambient humidity to simulate surface body temperature. The colorimetric wFDCF reactions presented in this work were from distinct sensors, in which each data point is the intensity value of a defined area of the green channel from the color-deconvolution function in ImageJ. The selected area size was kept constant for all sensors. Each dataset plotted in Fig. 1 is the average of three independently measured wells. Statistical significance values for specific time points were calculated using unpaired parametric Student’s $t$ -test (two-sided). \n\nEvaporation and dilution experiments in wearable synthetic biology devices. Evaporation tests were performed by cutting $10\\times10–\\mathrm{cm}^{2}$ Whatman No. 4 filter paper squares and performing the cleaning and BSA blocking as described above for the discs. Each square was freeze-dried with $100\\upmu\\mathrm{l}$ of a $1\\times$ PURExpress cell-free reaction with CPRG substrate and a constitutive LacZ plasmid. Various temperature $(27-32^{\\circ}\\mathrm{C})$ and fluid exposure conditions were investigated in \n\ncombination with different coverage ratios of the rehydrated test squares to assess evaporation reduction. Suitable activity of the rehydrated reactions was assessed by visual inspection of the conversion of the colorimetric substrate from yellow to purple. The port designs were selected empirically due to suitable activation of synthetic biology reactions with reduced evaporation rates $\\mathrm{<}20\\%$ of initial fluid volume in 2 h) at $30\\mathrm{-}40\\%$ relative humidity. \n\nKinetic enhancement by freeze-dried concentration of cell-free reaction components. Optimization testing of cell-free component concentrations on the kinetics of the reactions was performed by assembling PURExpress systems, according to the manufacturer’s specifications, at various volumes $(V_{\\mathrm{initial}})$ and then lyophilizing the reactions in PCR tubes overnight (Extended Data Fig. 1a). Next, the lyophilized pellets were rehydrated using the same sample volume $(V_{\\mathrm{final}})$ , so that the tested fold-concentration was $(V_{\\mathrm{initial}}/V_{\\mathrm{final}})$ . PURExpress concentrations ranging from $\\times1$ to $\\times2.5$ were tested in replicate by incubation of $10\\mathrm{-}\\upmu\\mathrm{l}$ reactions at $30^{\\circ}\\mathrm{C}$ for up to $90\\mathrm{{min}}$ , followed by photographic imaging of the colorimetric changes (Extended Data Fig. 1b) and absorbance measurements at $570\\mathrm{nm}$ (Extended Data Fig. 1c). The time to half-maximal output signal for each base or concentrated reaction (Extended Data Fig. 1d) was calculated by a least square fitting of the acquired data. \n\nScreening of textiles for FDCF synthetic biology reactions. General compatibility of different textiles to FDCF synthetic biology reactions was tested in 103 different fabric materials (for example, silks, cotton, rayon, linen, hemp, bamboo, wool, polyester, polyamide, nylon and combination threads) under activation conditions (Supplementary Table 1 and Supplementary Fig. 4). A detailed list of the textiles used for this substrate screening can be found in Supplementary Table 1. This compatibility of these textiles to FDCF synthetic biology reactions was compared with samples using Whatman No. 4 filter paper (GE Healthcare Lifesciences) and samples in liquid form without any substrate as seen in Supplementary Fig. 5. All tests used a T7RNAP-regulated LacZ circuit for constitutive expression. For this evaluation, fabric samples were identified and cut into $2\\times2\\mathrm{-cm}^{2}$ squares. Visible particles were removed from the fabrics using an adhesive roller. All fabric squares were cut into $1\\times2\\mathrm{-cm^{2}}$ pairs and washed thoroughly within $1.5–\\mathrm{ml}$ Eppendorf tubes with $\\mathrm{1ml}$ of dd- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ for $30\\mathrm{min}$ , floating in a sonication bath at $80^{\\circ}\\mathrm{C}$ . The washed samples were left to cool to room temperature and then washed with running dd- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ for 10 s. One of each pair of fabric square types was placed in $1.25\\mathrm{ml}$ of a $5\\%$ BSA solution for $^{12\\mathrm{h}}$ After BSA incubation, the treated fabrics were cleaned with running dd- $\\mathbf{\\cdotH}_{2}\\mathbf{O}$ for 10 s. BSA-blocked and unblocked samples were then placed into fresh Eppendorf tubes with holes in the caps to allow for overnight desiccation of the fabrics at $60^{\\circ}\\mathrm{C}$ Dried BSA-blocked and unblocked fabrics were then cut in triplicate with clean 2-mm-diameter disc biopsy punchers and placed in their respective slots in flat 384-well black polystyrene plates with a clear glass bottoms (Corning, ref. no. 3544) for testing. Cell-free PURExpress in vitro protein synthesis solution (New England Biolabs) was combined with a constitutive LacZ template containing $0.6\\mathrm{mg}\\mathrm{ml}^{-1}$ CPRG and spotted $(1.8\\upmu\\mathrm{l})$ on each of the fabric wells. Control wells containing 2-mm discs of Whatman No. 4 filter paper were also filled with $1.8\\AA{-}\\mu{1}$ constitutive LacZ test reactions, whereas $7\\upmu\\mathrm{l}$ was spotted on empty wells as liquid controls. A transparent adhesive PCR cover compatible with freezing was then placed over the plate and pressed with a roller to seal chambers. A small opening was pierced in each well with a 25-gauge $\\times5/8$ $(0.5\\mathrm{mm}\\times16\\mathrm{mm})$ BD PrecisionGlide Needle (Becton, Dickinson and Company, ref. no. 305122) to allow for sublimation during lyophilization. Prepared plates were wholly immersed into liquid nitrogen for 1 min. A chilled metallic plate (maintained at $-80^{\\circ}\\mathrm{C}$ with dry ice) was immediately put in contact with the bottom of the scored plates with the sealed frozen samples. A single $15\"\\times17\"$ Kimwipe (Kimtech, Kimberly-Clark) was placed on top of the plate humidity openings. Then the 384-well test plate with top Kimwipe and the bottom metallic chiller were wrapped with three layers of aluminium foil. The entire wrapped bundle was then placed inside a sealed glass lyophilization chamber and connected to the freeze-drying machine. Lyophilization was performed for 2 h. Freeze-dried paper samples were rehydrated with dd- $\\cdot\\mathrm{H}_{2}\\mathrm{O}$ to the original reaction volume. The colorimetric change was measured after overnight incubation (12 h) at $37^{\\circ}\\mathrm{C}$ using a BioTek NEO HTS plate reader (BioTek Instruments) in kinetic absorbance readout mode (Supplementary Fig. 5). Best observed functionality, as measured by the aggregated score shown in Supplementary Fig. 6, was achieved using a fabric with $85\\%$ polyester and $15\\%$ polyamide fibers. This substrate was used for all further fluorescence and luminescence experiments, except for the case for a fluorescence Zika DNA toehold sensing reaction (Supplementary Fig. 7), which was also tested on a $100\\%$ mercerized cotton thread to validate the possibility of running FDCF reactions at the single-fiber level with this natural material commonly used in wound care. \n\nFabrication of fluorescence/luminescence synthetic biology wearable textile module. After screening of compatible textiles for FDCF synthetic biology reactions, the best-performing hydrophilic textile substrate ( $85\\%$ polyester/ $15\\%$ polyamide) was used as weft for a textile inter-woven with a warp made of inert flexible POFs and polyester support threads. Such POFs were used for distributed optical interrogation of fluorescent or luminescent synthetic biology reactions \n\nwithin this fabric (three fibers per well). POFs were weaved into this hydrophilic combination fabric using a standard industrial loom (DREAMLUX, Samsara S.r.l.), according to the design presented in Supplementary Fig. 8. Once fabric samples were manufactured, three-strip arrangements of this hydrophilic POF fabric were cut to fit the device and laser-etched $(5\\mathrm{mm})$ to disrupt the cladding in the POFs sections within the reaction zones (Extended Data Fig. $2\\mathrm{a}{-}\\mathrm{e}$ ). Black elastomer layers (top and bottom in Extended Data Fig. 2b) were precast overnight and laser-cut according to the layout shown in Extended Data Fig. $^{2\\mathrm{b},\\mathrm{e}}$ . The silicone elastomer chambers in this device exhibit two $3\\times5\\mathrm{-}\\mathrm{mm}^{2}$ curved wicking ports that allow for fluid entry while still delaying evaporation within reaction fabric. Uncured black silicone elastomer was stamp-patterned onto the precast layers as well as into the internal POF fabric strips to be aligned and assembled, preventing air bubble formation between device layers and elastomer wicking in reaction zones. Final assembly of the base three-well sensor ‘patch’ can be seen in Extended Data Fig. 2b,f,g. Devices were then placed under vacuum for $15\\mathrm{min}$ to remove bubbles and were allowed to cure overnight at $65^{\\circ}\\mathrm{C}$ . As with the colorimetric prototypes, the fluorescent POF prototypes were thoroughly sprayed with RNase Away Decontaminant (Thermo Fisher Scientific) and washed with $70\\%$ ethanol twice before being stored in petri dishes. Once the assembled device was fully cured, POF fibers were separated into excitation and emission bundles and then covered with blackout adhesive fabric as well as black heat shrink tubing $\\left(6\\mathrm{mm}\\right)$ to prevent environmental light leakage. Blackout fabric discs $(10\\mathrm{mm})$ made of a black polyester knit item (no: 322323, MoodFabrics) were soaked in RNase Away Decontaminant for $5\\mathrm{{min}}$ , and washed thoroughly with $70\\%$ ethanol followed by water. The washed blackout fabric was incubated in $0.1\\%$ Triton X-100 for $5\\mathrm{{min}}$ (as a wetting agent to enhance the ability of the textile to absorb water) and then excess solution was removed and the fabric pieces allowed to air-dry. The final blackout fabric discs were placed inside the reaction chamber with tweezers to aid in environmental light-blocking over sensing fibers. Finally, quick-turn stainless steel coupling sockets (no. 5194K42, McMaster-Carr) were added to the ends of the sensor device bundles for connection with the wearable spectrometer. The finalized wFDCF sensor device can be seen in Extended Data Fig. 2f,g. \n\nHardware/software implementation of wearable POF spectrometer. A custom-made wearable spectrometer with internal processing and wireless connectivity modules was fabricated to provide unsupervised sensing of on-body synthetic biology reactions (Extended Data Fig. 8). The device electronics were based on a Raspberry Pi Zero W v.1.3 architecture (Raspberry Pi Foundation) with connection to a custom shield for battery power, an environmental sensing module, a light-emitting diode (LED) illumination module and a flexible camera for imaging (Extended Data Fig. 8a). The Raspberry Pi Zero W was selected as the microprocessor for this application due to its low cost ${'}{<}\\mathrm{US}\\$15.00)$ , small profile/weight $(65\\times30\\times5\\mathrm{mm}^{3}/12\\mathrm{g})$ ), high performance (1 GHz single-core ARM1176JZF-S CPU, 512 MB RAM, VideoCore IV GPU) and on-board wireless connectivity $(802.11\\mathrm{b/g/n}$ LAN, Bluetooth(R) 4.1, Bluetooth Low Energy). Regulated battery power was achieved using a PiZ-UpTime module, which is an uninterruptible power supply shield for Raspberry Pi Zero (Alchemy Power) that uses a rechargeable lithium-ion 14500 battery (battery and power management in Extended Data Fig. 8a) to reliably provide the charge capacity for $48\\mathrm{h}$ of intermittent device operation, continuously collecting data at a frequency of one measurement per minute. In-device sensing of temperature, humidity, atmospheric pressure, altitude, total volatile organic compound and equivalent $\\mathrm{CO}_{2}$ was achieved using an I2C Environmental CCS811/BME280 Qwiic-Breakout (SparkFun Electronics). The POF illumination module was achieved using a Saber Z4 Luxeon $Z20\\mathrm{mm}$ Square Quad Color Mixing Array LED Module with aluminium base (Quadica Developments, Luxeon) connected to a 12-Channel 16-Bit PWM TLC59711 LED Driver with SPI Interface (Adafruit Industries). Four Luxeon Star LEDs were installed in the device with wavelengths $447\\mathrm{nm}$ , $470\\mathrm{nm}$ , $505\\mathrm{nm}$ and $6{,}500\\mathrm{K}$ white (LEDs and driver in Extended Data Fig. 8a). An $8.6\\times8.6\\operatorname*{mm}^{2}$ Zero Spy Camera with $2\"$ cable (Raspberry Pi Foundation) was connected to the Raspberry Pi Zero W using a flat serial interphase connector to provide POF imaging capabilities to the device. A single 5-mm Infinite aspherical plastic collimator (part no.: 191–66041G, Quarton), with numerical aperture 0.27 and effective focal length $4.96\\mathrm{mm}$ , was placed on top of the camera to allow for magnified POF imaging in proximity to the camera. The wearable spectrometer was covered by a two-part case fabricated using black photoreactive resin and a stereolithography three-dimensional printing method using a Form 2 printer (Formlabs) as seen in Extended Data Fig. 8a. A view of the open device is shown in Extended Data Fig. 8b, while a closed view is shown in Extended Data Fig. 8c. This case included geometrical features to fit and align the camera/lens arrangement and the removable $3\\mathrm{-mm}$ -diameter amber acrylic filter for fluorescence readings (slot arrangement in Extended Data Fig. 8d). Also, the case features a slot for the four-LED arrangement and a vent for the environmental sensors, as well as female Luer connection-to-fitting quick-turn stainless steel coupling sockets (no. 5194K42, McMaster-Carr). A top view of the assembled wearable POF spectrometer is shown in Extended Data Fig. 8e, while the integration of this device within a wearable garment with wFDCF sensors is shown in Extended Data Fig. 8f. The final volume of our wearable spectrometer device was approximately $235\\mathrm{cm}^{3}$ with a total weight of around $173.8\\mathrm{g}$ (6.13 ounces), with a total cost \n\nof material and consumable supplies under US\\$100. Base data-collection software (test version) implemented in Python for control of the Raspberry Pi Zero W within the wearable POF spectrometer is also provided as part of the Supplementary Information. \n\nPreparation of optimized fluorescence wearable synthetic biology reactions. Constitutive sfGFP expression reactions for wFDCF testing (Fig. 2c) were prepared by combining $50\\upmu\\mathrm{l}$ of $1\\times\\mathrm{NEB}$ cell-free PURExpress in vitro protein synthesis solution with $0.5\\%$ Roche Protector RNase Inhibitor and $10\\mathrm{ng}\\upmu\\mathrm{l}^{-1}$ constitutive $\\mathrm{P}_{\\mathrm{T7}}$ -sfGFP plasmid $(+)$ or without as controls $\\left(-\\right)$ . Prepared reactions were quickly deposited in-fabric to be snap-frozen and then lyophilized for $4{\\cdot}8\\mathrm{h}$ within the device. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ . \n\nThe theophylline riboswitch sensor reactions for wFDCF testing (Fig. 2d) were prepared using $1\\times\\mathrm{NEB}$ cell-free PURExpress supplemented with $10\\mathrm{ng}\\upmu\\mathrm{l}^{-1}$ theophylline riboswitch sensor E mRNA in dd- $\\cdot\\mathrm{H}_{2}\\mathrm{O}$ The prepared sensor reactions ( $50\\upmu\\mathrm{l}$ per well) were quickly deposited in-fabric, snap-frozen in liquid nitrogen and then lyophilized for $4{-}8\\mathrm{h}$ within the device. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\mathbf{\\cdotH}_{2}\\mathbf{O}$ spiked with $1\\mathrm{mM}$ theophylline for the positive samples, while $0\\mathrm{mM}$ theophylline was used for controls. \n\nDimeric Broccoli fluorescent aptamer sensor reactions for wFDCF testing (Fig. 2e) were prepared using $1.5\\times$ NEB cell-free PURExpress with $25\\mathrm{ng}\\upmu\\mathrm{l}^{-1}$ pJL1-F30–2xd-Broccoli aptamer DNA in dd- $\\mathrm{.H}_{2}\\mathrm{O}$ Prepared sensor reactions $(50\\upmu\\mathrm{l}$ per well) were quickly deposited in-fabric to be snap-frozen and then lyophilized for $4{-}8\\mathrm{h}$ within the device. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ spiked with $50\\upmu\\mathrm{M}$ DFHBI-1T (Tocris Bioscience) substrate for the positive samples, while $0\\upmu\\mathrm{M}$ DFHBI-1T substrate was used for controls. \n\nZika RNA toehold switch sensor reactions for wFDCF testing (Supplementary Fig. 7) were prepared using $1\\times\\mathrm{NEB}$ cell-free PURExpress with $33{\\mathrm{nM}}$ Zika DNA toehold sensor 27B in dd- ${\\bf\\cdot H}_{2}\\mathrm{O}.$ . Prepared sensor reactions were quickly deposited in a mercerized cotton thread or paper samples to be snap-frozen and then lyophilized for $4{-}8\\mathrm{h}$ within a 384-well plate. Activation of sensors was achieved by rehydration with dd- $\\mathbf{\\cdotH}_{2}\\mathbf{O}$ spiked with $2\\upmu\\mathrm{M}$ freshly made Zika trigger RNA for the positive samples, while $0\\upmu\\mathrm{M}$ Zika trigger RNA was used for controls. \n\nFor the wearable nerve agent sensor experiments (Fig. 2g), $50\\mathrm{-}\\upmu\\mathrm{l}$ reactions consisting of $0.5\\mathrm{Uml^{-1}}$ AChE (Type V-S from Electrophorus electricus, MilliporeSigma), $0.1\\mathrm{Uml^{-1}}$ of choline oxidase (recombinant Arthrobacter $\\boldsymbol{s p}$ , MilliporeSigma), $0.1\\mathrm{mg}\\mathrm{ml}^{-1}$ of freshly prepared horseradish peroxidase (Type VI, MilliporeSigma) and $125\\upmu\\mathrm{M}$ of the fluorescent reporter substrate Amplite-IR (AAT Bioquest) in a final buffer of $10\\mathrm{mM}$ HEPES, $\\mathrm{pH}8.0,1\\mathrm{mg}\\mathrm{ml}^{-1}$ BSA, $1\\%$ fish gelatin and $5\\%$ trehalose. The reactions were applied to two Whatman No. 4 filter paper $_{0.8\\mathrm{-}c\\mathrm{m}}$ discs, snap-frozen in liquid nitrogen and lyophilized for at least $12\\mathrm{h}$ . To test in the fluorescent wearable prototype, the paper discs containing the freeze-dried reactions were inserted into the wearable devices and rehydrated with $75\\upmu\\mathrm{l}$ of $50\\upmu\\mathrm{M}$ acetylcholine (MilliporeSigma) with or without the nerve agent paraoxon-ethyl (MilliporeSigma). The fluorescent wearable device for the nerve agent was altered for the detection of NIR fluorescence by replacing the optical components with excitation using a $627-\\mathrm{nm}$ red quad-LED array module (Quadica Developments, Luxeon). Additionally, the emission camera was substituted with a NoIR Zero Spy Camera without infrared filter, on top of which we positioned three gel transmission filters (no. 381, no. 382 and no. 383; Rosco Laboratories) to form a dedicated emission filtering stack with $<1\\%$ cutoff at $660\\mathrm{nm}$ and peak transmittance at $740\\mathrm{nm}$ . All of the fluorescent wFDCF sensors were tested at $30^{\\circ}\\mathrm{C}$ and ambient humidity to simulate surface body temperature. All fluorescent wFDCF data presented in this work were from distinct sensors, in which each data point is the integrated value of color-deconvoluted optical fiber signals from one sensor, using the green channel for fluorescence and the blue channel for luminescence. Any fiber optic signals that were 1 s.d. below the mean of all fibers combined were removed from the analysis. All of the cell-free and enzymatic wFDCF sensor plots are the average of three independent wells with each well containing three separate fiber optic sensors, for a total of nine fiber outputs presented per variable. Statistical significance values for specific time points were calculated using unpaired parametric Student’s t-test (one-sided). \n\nPreparation of optimized luminescence wearable synthetic biology reactions. HIV RNA toehold switch sensor reactions for luminescence wFDCF testing (Fig. 2f and Extended Data Fig. 3a) were prepared in $50\\mathrm{-}\\upmu\\mathrm{l}$ batches using $20\\upmu\\mathrm{l}$ of NEB cell-free PURExpress Component A, $15\\upmu\\mathrm{l}$ of NEB Component B, $2.5\\upmu\\mathrm{l}$ of murine RNase inhibitor (New England Biolabs), $6\\mathrm{{ng}\\upmu l^{-1}}$ HIV toehold sensor template with an nLuc output and $0.5\\upmu\\mathrm{l}$ of luciferin substrate (Promega) in dd- $\\cdot\\mathrm{H}_{2}\\mathrm{O}$ . Prepared sensor reactions ( $50\\upmu\\mathrm{l}$ per well) were quickly deposited in-fabric to be snap-frozen and then lyophilized for $4{-}8\\mathrm{h}$ within the device. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ spiked with $10\\upmu\\mathrm{M}$ HIV trigger RNA freshly made for the positive samples, while $0\\upmu\\mathrm{M}$ HIV trigger RNA was used for controls. The constitutive nLuc control reaction performed in singlicate shown as reference for Extended Data Fig. 3b was performed similarly but substituting the toehold switch with a plasmid with an nLuc operon regulated by a T7 promoter. \n\nB. burgdorferi RNA Lyme disease toehold switch sensor reactions for luminescence wFDCF testing (Extended Data Fig. 3b) were prepared in $50\\mathrm{-}\\upmu\\mathrm{l}$ batches using $20\\upmu\\mathrm{l}$ of NEB cell-free PURExpress solution A, $15\\upmu\\mathrm{l}$ of solution B, $2.5\\upmu\\mathrm{l}$ of murine RNase inhibitor, $18\\mathrm{nM}B$ . burgdorferi toehold DNA with luciferase operon and $2.75\\upmu\\mathrm{l}$ of luciferin substrate (Promega) in dd- $\\mathbf{\\cdotH}_{2}\\mathbf{O}$ . Prepared sensor reactions ( $50\\upmu\\mathrm{l}$ per well) were quickly deposited in-fabric to be snap-frozen and then lyophilized for $4{-}8\\mathrm{h}$ within the device. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ spiked with $3\\upmu\\mathrm{M}R$ . burgdorferi trigger RNA freshly made for the positive samples, while $0\\upmu\\mathrm{M}$ trigger RNA was used for controls. These wFDCF sensors were tested at $30^{\\circ}\\mathrm{C}$ and ambient humidity to simulate surface body temperature. \n\nPreparation of optimized CRISPR–Cas12a-based wearable synthetic biology reactions. CRISPR-based sensor reactions for wFDCF testing in Fig. 3b–e,h and Extended Data Figs. 4 and 6 were prepared using $100\\mathrm{nM}$ Cas12a (New England Biolabs) and $100\\mathrm{nM\\gRNA}$ , $1\\times\\mathrm{NEB}$ buffer 2.1, $0.45\\mathrm{mM}$ dNTPs, $500\\mathrm{nM}$ of each RPA primer, $1\\times$ RPA liquid basic mix (TwistDx), $14\\mathrm{mM}\\mathrm{Mg}{\\mathrm{Cl}_{2}}$ and $5\\upmu\\mathrm{M}$ FAM-Iowa Black FQ quenched ssDNA fluorescent reporter (Integrated DNA Technologies) in dd- $\\mathbf{\\cdotH}_{2}\\mathbf{O}$ . Prepared sensor reactions $(50\\upmu\\mathrm{l}$ per well) were quickly deposited in-fabric to be snap-frozen and then lyophilized for $4{-}8\\mathrm{h}$ within the device. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\mathbf{\\cdotH}_{2}\\mathbf{O}$ spiked with $2.7\\mathrm{fM}$ or $100\\mathrm{fM}$ of mecA, spa or ermA DNA trigger depending on the demonstration. In the sensing performed at $2.7\\mathrm{fM}$ mecA trigger, the detection limit is 10,000 copies of DNA per $\\upmu\\mathrm{l}$ . These wFDCF sensors were tested at $30^{\\circ}\\mathrm{C}$ and ambient humidity to simulate surface body temperature. All of the CRISPR-based wFDCF sensor plots are the average of three independent wells. Each well contained three separate fiber optic sensors, for a total of nine fiber outputs presented per variable. Statistical significance values for specific time points were calculated using unpaired parametric Student’s t-test (one-sided). \n\nPreparation of optimized CRISPR–Cas13a-based wearable synthetic biology reactions. CRISPR–Cas13a-based sensor reactions for wFDCF testing (Extended Data Fig. 5) were prepared using $100\\mathrm{nM}$ Cas13a and $100\\mathrm{nM}$ gRNA, $\\mathrm{i}\\times\\mathrm{NEB}$ buffer 2.1, $0.45\\mathrm{mM}$ dNTP, $14\\mathrm{mM}\\mathrm{Mg}{\\mathrm{Cl}_{2}}$ and $5\\upmu\\mathrm{M}$ FAM-Iowa Black FQ quenched RNA fluorescent reporter (Integrated DNA Technologies) in dd- $\\mathrm{.H}_{2}\\mathrm{O}.$ . Prepared sensor reactions $50\\upmu\\mathrm{l}$ per well) were quickly deposited in-fabric to be snap-frozen and then lyophilized for $4{-}8\\mathrm{h}$ within the device. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ spiked with $20\\mathrm{nM}$ of MRSA RNA trigger. \n\nPreparation of sample lysis-integrated wearable synthetic biology reactions. For wFDCF with integrated lysis reactions, an RNase-free Whatman filter paper disc $(8\\mathrm{mm})$ was filled with concentrated stock solutions that would yield, upon a $50\\mathrm{-}\\upmu\\mathrm{l}$ rehydration volume, $5\\mathrm{mM}$ Tris-HCl $\\mathrm{(pH}7.5)$ ), $1\\%$ Triton X-100, $1\\%$ NP-40, $0.2\\%$ CHAPS, $100\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ lysozyme and $5\\%$ sucrose. This was freeze-dried for 4 h and inserted into the POF wFDCF device below the blackout layer and above a PVA time delay barrier that was sealed around the edges with Ecoflex elastomer to enable an efficient lysis incubation time. All layers containing the lyophilized RPA-Cas12a synthetic biology sensors below the lysis–PVA delay layers were identical to that used in the mecA RPA-Cas12a devices shown in Fig. 3b–e. \n\nGarment-level integration of colorimetric synthetic biology sensors. After fabrication of a colorimetric synthetic biology wearable module, a bracelet ‘garment’ was achieved simply by gluing the module into an elastic band to be placed on the forearm of a mannequin (Supplementary Fig. 3c). \n\nGarment-level integration of fluorescence/luminescence synthetic biology sensors. After fabrication of at least 12 fluorescence/luminescence synthetic biology wearable modules, a commercially available long-sleeve neoprene wetsuit-type jacket (EYCE Dive & Sail) was modified to integrate an array of wFDCF sensors by sewing these modules in predefined high-splash-frequency regions (Figs. 2a and 4a and Extended Data Fig. 8f). Reaction modules were covered at the edges with a blackout fabric border with textile adhesive. POF bundles of these modules were sewn internally and directed to a single multi-bundle arrangement for interrogation via our portable spectrometer device (located in a back pocket within the jacket). The base neoprene fabric used for this jacket was of $3\\mathrm{-mm}$ thickness and treated with a superhydrophobic coating to prevent fluid absorption in places other than the reaction zones. The fabricated wFDCF jacket prototype was specified to fit a medium-sized male torso ( $36\"$ chest by $31\"$ waist). In-garment sensors were tested on a mannequin at room temperature. \n\nConstruction and preparation of SARS-CoV-2 A-version diagnostic face mask. The SARS-CoV-2 in-mask diagnostic consists of the sensor assembly containing the lyophilized reactions which was then inserted into an N95-equivalent face mask (Fig. 4a for a schematic of the sensor; Fig. 4b and Supplementary Fig. 14 for fully assembled face masks). First, capillary wicking material (porous Porex HRM (high-release media) fiber media (no. 36776, Porex Filtration Group), thicknes $=0.5\\mathrm{mm}$ , density $\\mathtt{\\Gamma}=0.07\\mathtt{g}\\mathtt{c}\\mathtt{c}^{-1}$ , porosity $=92\\%$ ) was laser-cut into a shape allowing for an elliptical region approximately $50\\times25\\mathrm{mm}^{2}$ that serves as the sample collection area, accumulating viral particles from a patient’s respiration, vocalization and/or reflexive tussis. The laser-cut wicking material is then adhered to a white PET double-adhesive backing material (3M Microfluidic Diagnostic \n\nTape, no. 9965 (3M)). One end of the wicking material is adhered to a sterile sealed blister-pack containing nuclease-free water. The $\\upmu\\mathrm{PAD}$ device is created by wax printing hydrophobic patterns onto Whatman Grade 1 chromatographic filter paper (Thermo Fisher Scientific) using a Xerox Phaser 8560 solid ink printer. The printed $\\upmu\\mathrm{PAD}$ sheets were then wax reflowed by hot pressing for 15 s at $125^{\\circ}\\mathrm{C}$ using a Cricut EasyPress (Cricut), and then left untouched to cool at room temperature. After wax reflow, the reaction zones have an aperture diameter of $5\\mathrm{mm}$ , while the intervening PVA time delays have an aperture diameter of $3\\mathrm{mm}$ . The PVA time delays were placed onto the time-delay zones first, by pipetting $4\\upmu\\upmu\\upmu$ of $10\\%$ , ${\\sim}67{,}000$ average molecular weight PVA (MilliporeSigma) per delay layer, and allowing it to dry at room temperature overnight. The lysis buffer, RT-RPA reaction and the Cas12a SHERLOCK reactions as described below were then added to the respective lysis zones. \n\nThe lysis reaction added to each sensor lysis zone was $15\\upmu\\mathrm{l}$ of $10\\mathrm{mM}$ Tris-HCl $\\mathrm{(pH}7.5)$ , $1\\%$ Triton X-100, $1\\%$ NP-40, $0.2\\%$ CHAPS, $100\\upmu\\mathrm{g}\\mathrm{ml}^{-1}$ lysozyme and $5\\%$ sucrose. The RT-RPA reaction added to the isothermal amplification zone was $15\\upmu\\mathrm{l}$ of a single lyophilized TwistAmp RPA pellet (TwistDx) that was rehydrated to $50\\upmu\\mathrm{l}$ using a rehydration reaction of $29.6\\upmu\\mathrm{l}$ of Twist Rehydration Buffer and $9.6\\upmu\\mathrm{l}$ of a primer mix (Supplementary Table 2; RT-RPA-F4, RT-RPA-R4 and RT-RPA-R3 primers in the mix are at a ratio of $10\\upmu\\mathrm{M}/10\\upmu\\mathrm{M}/20\\upmu\\mathrm{M})$ . Roche Protector RNase Inhibitor, TAKARA PrimeScript Reverse Transcriptase and Ambion RNase H were all added at $1\\upmu\\mathrm{l}$ each. Nuclease-free water was added at $4.4\\upmu\\mathrm{l}$ . Immediately before pipetting onto the reaction zone, $2.5\\upmu\\mathrm{l}$ of $280\\mathrm{mM}$ MgOAc was added to the RT-RPA reaction and thoroughly mixed. For the Cas12a SHERLOCK reaction, $15\\upmu\\mathrm{l}$ of the following reaction was pipetted onto the SHERLOCK reaction zone: $12.3\\upmu\\mathrm{l}$ of nuclease-free water, $1.5\\upmu\\mathrm{l}$ of NEB Buffer 2.1, $0.3\\upmu\\mathrm{l}$ of $0.5\\mathrm{M}$ DTT, $0.075\\upmu\\mathrm{l}$ of $100\\upmu\\mathrm{M}$ NEB EnGen Lba Cas12a and $0.26\\upmu\\mathrm{l}$ of $40\\upmu\\mathrm{M}$ coronavirus S-gene gRNA. Immediately before pipetting onto the reaction zone, 1 pmol of the 6-FAM/ TTATTATT/Biotin oligo (FB probe, from Integrated DNA Technologies) was added to the Cas12a reaction and thoroughly mixed. Sequences for all primers, RNA targets and the gRNA are presented in Supplementary Table 2. \n\nAll reactions were pipetted onto the reaction zones and the wax-printed sheet is then dipped into liquid nitrogen to freeze all of the embedded reactions, and then immediately wrapped in foil and placed on a lyophilizer. After lyophilization for $4{-}24\\mathrm{h}$ , the wax arrays are removed from the lyophilizer. Cutting of the arrays into individual $\\upmu\\mathrm{PAD}$ strips can be performed before or after the lyophilization process. Each strip is folded using sterilized tweezers into an overlapping accordion arrangement (as shown in Fig. 4b), overlapping the reaction zones and time delays to form a $\\upmu\\mathrm{PAD}$ device. The output end of the laser-cut Porex sample collection section was carefully inserted on top of the lysis zone, while the input end of a Milenia HybriDetect-1 Universal Lateral Flow Assay (TwistDx) was inserted on top of the last PVA time delay. The entire $\\upmu\\mathrm{PAD}$ section was carefully sandwiched and taped together to compress all of the layers. The entire blister-pack water reservoir–Porex sample collection area– $\\cdot\\upmu\\mathrm{PAD}$ –LFA test strip is secured using the double-sided backing to the inside of an N95-equivalent mask, positioning the sample collection area in the region directly in front of the mouth and nose. The LFA test strip is routed to the outside of the mask through a small slit in the mask and the indicator has been oriented to hide the results from external viewing, to ensure patient confidentiality. To access the results, the test strip must be bent over to view the results (Supplementary Fig. 14g). Lastly, a button is affixed to the outside of the mask directly over the water blister reservoir. The button contains a small spike embedded in a compressible foam double-sided adhesive material. When pressed down, the button pierces the foil on the blister, allowing the nuclease-free water to flow through the same collection zone, the $\\upmu\\mathrm{PAD}$ reaction zones and time delays, and finally into the LFA indicator strip. The modular design of the sensor components allows elements such as the water reservoir, $\\upmu\\mathrm{PAD}$ or LFA strip to be adjusted for different orientations or placement on the inside or outside of the mask. Only the sample collection pad module has strict orientation and positional requirements. \n\nBench-top testing of A-version SARS-CoV-2 diagnostic face-mask sensors. For Fig. 4d,f, each data point consisted of a face-mask sensor in which a defined amount of synthetic SARS-CoV-2 RNA fragment containing the specific gRNA-targeting region of the SARS-CoV-2 spike gene was generated by in vitro transcription using the HiScribe T7 Quick High Yield RNA Synthesis Kit (NEB) using synthetic DNA templates with a T7 promoter (Integrated DNA Technologies and Twist Bioscience). Corresponding homologous regions to the spike gene for the commonly circulating HCoV strains 229E, HKU1, NL63 and OC43 were determined by sequence homology alignment of the respective spike genes (Supplementary Fig. 14a) and the RNA targets were generated using the same method described above. All SARS-CoV-2 face-mask sensors were tested at room temperature at ambient humidity. After activation and LFA output formation $(\\sim20-30\\mathrm{min}$ ), the LFA strips were digitized using the scanner function on a Ricoh MP C3504 on default contrast settings. This ensured equal brightness and contrast across all strips in comparison with photography. Each test (T) and control (C) output line from each strip was quantified in ImageJ from the 32-bit converted raw scanned images without any adjustments to brightness or contrast. \n\nFabrication of B-version face-mask sensors. The following optimizations to the A-version sensors were implemented, resulting in the improved B-version. \n\nWax-printed $\\upmu\\mathrm{PAD}$ templates were prepared as described above for the A-version sensors with the following changes (Supplementary Fig. $^{15\\mathrm{a,b}},$ . To prevent failure from flow leakage between different layers of the folded $\\upmu\\mathrm{PAD}$ , unwaxed borders were rendered hydrophobic by drawing over the area with a Super PAP Pen (ThermoFisher) and allowed to air-dry for at least 1 h. The sample collection pads for the B-version sensors were laser-cut from sheets of Porex high-release media no. 36776 with the dominant fiber direction along the long axis of the pad to allow faster flow of the hydration front. The pad geometry was adjusted to enhance water flow by moving the reservoir puncture point to the distal end of the water blister, increasing the pad area in contact with the water reservoir, and reducing the sample collection region. Approximately $2\\mathrm{mm}$ of the outer border of the sample pad was rastered during laser-cutting to heat-seal the Porex material to the PET backing material, preventing delamination. Before assembly, approximately $1\\mathrm{cm}$ of the backing material was peeled away and cut off from the end of the sample pad region that is to be in contact with the reservoir. \n\nBefore the addition of the reagents to the $\\upmu\\mathrm{PAD},$ each reaction zone area was blocked with $5\\mathrm{ml}$ of $1\\%\\mathrm{BSA}+0.02\\%$ Triton X-100 and allowed to air-dry for 12 h to prevent nonspecific adsorption of the biochemical reaction components to the filter paper matrix. PVA at a concentration of $18\\%$ (w/v) at a volume of ${\\sim}5\\upmu\\mathrm{l}$ was applied to each time delay zone and allowed to air-dry for 24 h. The lysis buffer for the B-version sensors was reformulated to $10\\mathrm{mM}$ Tris-HCl $\\left(\\mathrm{pH}7.5\\right)$ ), $5\\%$ sucrose, $0.02\\%$ NP-40 and $2\\%$ CHAPS. The amount of nonionic surfactants in the lysis buffer was reduced to prevent observed degradation of the wax barrier, an observation we had made during design and testing of the A-version $\\upmu\\mathrm{PADs}$ . The CHAPS concentration was increased as it was not found to degrade the wax and this zwitterionic detergent has previously been shown to be effective in lysing coronavirus particles39. A volume of $10\\upmu\\mathrm{l}$ of this lysis buffer was added to the $\\upmu\\mathrm{PAD}$ lysis zone. The RT-RPA and Cas12a SHERLOCK reaction compositions, volumes and lyophilization parameters were unchanged. During final assembly of the B-version sensor, both the sample pad: ${\\tt t}\\mathrm{\\ttPAD}$ and the $\\upmu\\mathrm{PAD}.$ ::LFA contact regions were fully sealed using precut sterile aluminium PCR foil seals (no. 60941-076, VWR) to improve contact transfer and prevent any fluidic short-circuiting that may occur from undesired droplet contact to the folded $\\upmu\\mathrm{PAD}$ edges. To facilitate unimpeded sample flow, venting holes were introduced into the water-containing blister mold to prevent vacuum buildup inside the blister during flow. Three venting holes were punched into the blister surface using an 18-gauge needle and then sealed with a $6\\mathrm{-mm}$ adhesive disc of a single-sided rayon breathable hydrophobic porous film (no. 60941-086, VWR). This allows venting of vacuum while preventing leakage and contamination of the nuclease-free water. For all B-version face-mask-integrated sensors, the water reservoir module was positioned on the exterior of the mask to minimize unwanted contact pressure on the blister-pack during wearing of the mask. The sensor activation mechanism is the same as the A-version sensors. To integrate the sensors into the face masks, 1-cm slits were cut into KN-95 masks through which the sensor ends were threaded and subsequently sealed using adhesive. \n\nBreathing simulator apparatus assembly. Our face-mask sensor testing platform (Fig. 4h and Supplementary Fig. 16) consisted of four modules that performed the following functions: spontaneous breath generation, aerosol production, heating control, and physiologic airway and head simulation. For the breath generation, we employed the TestChest Lung Simulator (Organis), a highly accurate artificial lung that uses an actuated dual bellows design to replicate lung mechanics such as lung vial capacity and tidal volume. The TestChest was connected through ventilator tubing to all other downstream modules for simulated spontaneous breathing. Directly downstream of the TestChest, we placed an in-line Aerogen Solo nebulizer (Aerogen). The Aerogen Solo is a medical-grade vibrating-mesh nebulizer for the administration of lung inhalation therapeutics. Previous studies have demonstrated that the nebulizer generates aerosol droplets that are similar in diameter to those that occur naturally from human lung emissions50. Furthermore, previous work has used the Aerogen system to deliver therapeutic RNA in an animal model51, showing that it can be used to produce transmissible RNA-laden aerosols. The tubing is next wrapped in a temperature-regulated heat pad (Zoo Med Laboratories) that maintains the output temperature at $35^{\\circ}\\mathrm{C}$ . The tubing is connected to a lung input tube in a high-fidelity airway manikin (7-SIGMA Simulation Systems) that faithfully replicates pulmonary and nasopharyngeal structures as well as head movement ranges. The other simulated lung and the simulated esophagus are clamped shut to direct breath output only through the oral cavity. \n\nOn-simulator testing of face-mask-integrated B-version sensors. For all simulator-based testing, a SARS-CoV-2 B-version sensor-containing face mask was fitted onto the 7-SIGMA airway manikin and the TestChest was set to the ‘Normal Stable’ setting, which generates a spontaneous breathing rate of 12 breaths per minute. The entire breathing simulator assembly was then checked for leaks. Temperature regulation was set to maintain an outflow temperature of $35^{\\circ}\\mathrm{C}$ . A 5-ml solution of SARS-CoV-2 F5R11 vRNA IVT target was then pipetted into the Aerogen Solo reservoir and the controller unit activated. The simulated breath was allowed to collect in the face mask and sensor for a period of $30\\mathrm{min}$ , then the sensor was activated on the manikin for processing while maintaining the breathing and heating. The LFA outputs for all sensors were scanned using a Ricoh MP C3504 printer system using default settings. \n\nThe total amount of aerosolized vRNA collected after $30\\mathrm{min}$ on each mask sensor for a given concentration of vRNA IVT target solution was estimated by RT–qPCR analysis of a 6-mm filter paper disc affixed to the sample pad area. After the $30\\mathrm{min}$ of the breathing simulation, the disc was removed and frozen immediately in nuclease-free microcentrifuge tubes at $-80^{\\circ}\\mathrm{C}$ for later analysis. Replicate disc collections were then repeated using the same procedure. For analysis, the discs were thawed and resuspended in $100\\upmu\\mathrm{l}$ of nuclease-free water supplemented with Protector RNase Inhibitor (Roche). RNA was extracted by repeated vortexing for 20-s burst intervals with resting on ice. This extracted sample was used as template in RT–qPCR reactions to obtain the total accumulated target RNA copy number on the $6\\mathrm{-mm}$ sampling disc. The mean collection values (in copies per $\\mathrm{mm}^{2}$ ) are then multiplied by the exposed surface area of the sample collection pad $(2,513\\mathrm{mm}^{2})$ to estimate the total aerosolized vRNA target collected on the sensor. For a stock solution of $16.7\\mathrm{fM}$ vRNA IVT target, the estimated total collected copies per sensor is $2.3\\times10^{6}$ copies. For a stock solution of $1.67\\mathrm{pM}$ vRNA IVT target, the estimated total collected copies per sensor is $5\\times10^{7}$ copies. These values are reported in Fig. 4i,j. The scatter plots for each target concentration show the T/C ratio from five independently fabricated and measured sensors. \n\nSensor and reporter sequences. Supplementary Tables 2 and 3 contain the DNA and RNA sequences of sensors and reporters used in this study. The plasmid construct used for the Zika 27B toehold sensor has been previously described elsewhere52. The Lyme disease and HIV toehold sensors with an nLuc output were cloned into the pBW121 plasmid backbone (Addgene plasmid no. 68779). All other plasmid constructs utilized the pJL1 backbone that has been previously described12,14. The F30 dimeric Broccoli fluorescent aptamer was subcloned into pJL1 from pET28c-F30-2xd-Broccoli, which was a gift from Samie Jaffrey (Addgene plasmid no. 66843; http://n2t.net/addgene:66843; RRID: Addgene_66843). The sequence for the pJL1-sfGFP plasmid can be found on Addgene (plasmid no. 69496). \n\nReporting Summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nAll data needed to evaluate the conclusions in the paper can be found in the paper and the Supplementary materials. Correspondence and requests for materials should be addressed to J.J.C. \n\n# Code availability \n\nThe custom code developed for this work is provided in the Supplementary materials. \n\n# References \n\n50.\tFennelly, K. P. Particle sizes of infectious aerosols: implications for infection control. Lancet Respir. Med. 8, 914–924 (2020). \n51.\tPatel, A. K. et al. Inhaled nanoformulated mRNA polyplexes for protein production in lung epithelium. Adv. Mater. 31, e1805116 (2019). \n52.\tPardee, K. et al. Rapid, low-cost detection of Zika virus using programmable biomolecular components. Cell 165, 1255–1266 (2016). \n\n# Acknowledgements \n\nWe thank Samsara S.r.l.–Dreamlux for aid in the custom fabrication of the wearable fabrics incorporating flexible fiber optics. Our gratitude to G. Vis from SimVS for providing access and support for the TestChest Lung Simulator. In addition, we thank T. E. Reihsen from 7-SIGMA Simulation Systems (7S3) for providing the high-fidelity airway trainer. We are also indebted to X. Tan for consultations on clinical considerations for the SARS-CoV-2 face-mask design. We also acknowledge T. Ferrante for support in the design and fabrication of the optical wearable acquisition device. Materials for the face mask prototype were kindly contributed by 3M through A. Brick. We further thank J. Gootenberg, O. Abudayyeh and the Zhang Lab for providing us with Cas13a enzyme. The nanoluciferase plasmid was kindly donated by D. Thompson from the Church Lab. The pET28c-F30-2xd-Broccoli plasmid was a gift from S. Jaffrey (Addgene plasmid no. 66843). We also thank J. W. Lee for aid in general toehold sensor design, as well as A. Dy and M. Takahashi for discussions and advice relating to the implementation of cell-free synthetic biology circuits. This work was supported by the Defense Threat Reduction Agency grant no. HDTRA1-14-1-0006, the Paul G. Allen Frontiers Group, the Ragon Institute of MGH, MIT and Harvard award no. 234640, the Patrick J. McGovern Foundation, the Wyss Institute for Biologically Inspired Engineering, Harvard University (J.J.C., P.Q.N., L.R.S., N.M.A.-M., H.P., N.M.D.) and by Johnson & Johnson through the J&J Lab Coat of the Future QuickFire Challenge award 2018. L.R.S. was also supported by CONACyT grant no. 342369/408970, and N.M.A.-M. was supported by an MIT-TATA Center fellowship, no. 2748460. \n\n# Author contributions \n\nP.Q.N. and L.R.S. designed and constructed devices, planned and performed experiments, analyzed the data and wrote the manuscript. N.M.D., N.M.A.-M. and H.P. \n\ndesigned and performed experiments and analyzed the data. A.H. and T.G. performed experiments and edited the manuscript. S.S., T.G. and E.M.Z. assisted with aspects of design and construction of sensors or devices. R.L. optimized parts of the freeze-dried reactions. G.L., H.M.S. and J.B.N. contributed to concept development of the face mask. J.J.C. directed overall research and edited the manuscript. \n\n# Competing interests \n\nThe authors have submitted provisional patent applications based on the technology described in this manuscript. J.J.C. is a co-founder and board member of Sherlock Biosciences. \n\n# Additional information \n\nExtended data is available for this paper at https://doi.org/10.1038/s41587-021- 00950-3. \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41587-021-00950-3. \n\nCorrespondence and requests for materials should be addressed to J.J.C. \n\nPeer review information Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\n![](images/ddb110718556aed1287c785af1de1b8734963808abefa2e303692c6d159f5520.jpg) \nExtended Data Fig. 1 | Concentrating PURE cell-free reactions increases reaction kinetics. a, Schematic of reaction concentration through the lyophilization of PURExpress reactions at varying volumes followed by rehydration at a set volume. Using this method, synthetic biology reactions can be concentrated to enhance kinetics through molecular crowding effects or greater density of cell-free components per volume. b, Representative images of PURE reactions with a LacZ output over one hour, at various concentrations. c, Quantified PURExpress reactions with a LacZ output in triplicate; the error bars denote standard deviation. Plots here show mean $\\pm\\thinspace s.{\\mathsf{d}}$ . values for $\\mathsf{n}=3$ independent experiments of rehydrated PURExpress reactions in a microplate assay. d, The half-maximal values from curve fitting the data shown in panel c indicate that the $1.5\\times$ concentrated PURE reaction accelerates the signal output by more than 10 minutes. Propagated error bars here are smaller than the data points. \n\n![](images/db8acd9380d4aa5df3e423424334b3228a64383df6f3c3d35843b54ec539e1d3.jpg) \nExtended Data Fig. 2 | See next page for caption. \n\n# Nature Biotechnology \n\n# Articles \n\nExtended Data Fig. 2 | Fabrication of fiber optic textile-based wFDCF sensor patch. a, A cut strip of hydrophilic POF fabric was laser-etched (5 mm) to ablate the POF outer cladding in the POFs sections closest to the reaction zone. b, Examples of prepared wFDCF fabric-elastomer layers and final assembly into a three-well sensor for garment integration. The POFs in these devices were covered with black heat shrink tubing $\\cdot6\\mathsf{m m})$ . Top elastomer cover features two $5.19\\times1.85\\mathsf{m m}$ curved sample ports instead of three as in the colorimetric prototypes to reduce direct light leakage on top of the POFs that may cause background light detection. c, Schematic of a POF-fabric-elastomer strip for sensing in a single textile layer including two excitation fibers on the sides of an emission fiber. d, Schematic of a double POF-fabric-elastomer strip for sensing with dedicated excitation and emission layers. This design was the one selected for further experiments due to higher hydrophilic fiber content and capacity to immobilize fluid for lyophilization. e, Schematic of a single excitation or emission POF-fabric-elastomer layer overlaid on an applied elastomer pattern for creating the impermeable reaction wells. f, A finalized three-well sensor wFDCF device with heat shrunk POF covers and Luer connectors for interfacing with a portable spectrometer device. g, Top and bottom views of a final three-well sensor wFDCF device. The blackout fabric can be seen through the sample wicking ports and serve to prevent environmental light penetration into reaction wells. \n\n![](images/ee9079e72eb2f3a6b52f1750383c88e1ad73c347eea6b960bd6d60e50ae30ed3.jpg) \nExtended Data Fig. 3 | See next page for caption. \n\n# Nature Biotechnology \n\n# Articles \n\nExtended Data Fig. 3 | Luminescent wFDCF toehold switches for B. burgdorferi and HIV detection. a, Dynamic response of a wFDCF HIV RNA toehold switch sensor with luminescence output in comparison to constitutive $\\mathsf{P}_{\\top\\top}\\dot{}$ :nLuc expression as a positive control $(+)$ . Activation of sensors was achieved by rehydration with a fluid splash of dd- ${\\mathsf{H}}_{2}{\\mathsf{O}}$ spiked with $10\\upmu\\mathsf{M}$ HIV trigger RNA freshly made for the positive samples, while $0~\\upmu\\upmu$ HIV trigger RNA was used for controls. The constitutive $\\mathsf{P}_{\\top\\top}$ ::nLuc positive control reaction shown was also prepared similarly but substituting the toehold switch in the plasmid with a T7 promoter. Results (top) are compared to the same reactions run in a 384-well plate and analyzed using a plate reader in luminescence mode (bottom read). Inset shows identity of each individual fiber in the bundle, where ${\\mathsf{T}}={\\mathsf{H}}{\\mathsf{I}}{\\mathsf{V}}$ toehold with trigger, $(-)=H V$ toehold without trigger, and $(+)$ is the $\\mathsf{P}_{\\mathsf{T7}}$ ::nLuc control. Activation of constitutive reaction peaked at \\~8 minutes, whereas toehold with ${10\\upmu\\mathsf{M}}$ trigger produced its peak signal at ${\\sim}15$ minutes. Both the wFDCF device tests and the plate reader profiles appeared to be temporally aligned and exhibit analogous signal amplitude differences among reactions. b, Dynamic response of a wFDCF Lyme disease RNA toehold switch sensor with luminescence output. Activation of sensors was achieved by rehydration with a fluid splash of dd- $\\cdot\\mathsf{H}_{2}\\mathsf{O}$ spiked with $3\\upmu\\mathsf{M}B.$ . burgdorferi trigger RNA freshly made for the positive samples, while ${0}{\\upmu\\mathsf{M}}$ trigger RNA was used for controls. All sensors shown were activated by rehydration and incubated at a temperature of $30^{\\circ}\\mathsf{C}$ and a relative humidity of $35\\%$ . The plots for the wFDCF results (a, b-top panel) show integrated mean pixel intensity (dark lines) $\\pm\\thinspace s.0$ (shaded regions) for three independent experiments. Scale bars in brightfield images are $250\\upmu\\mathrm{m}$ . The luminescence trace plot (b-bottom panel) presented as reference are singlicates for each condition. \n\n![](images/d89bbfb8f7768ad38d90e1af9ee2259dc77e093169e4d99b103f332488cdaebe.jpg) \nExtended Data Fig. 4 | Limit of detection of wFDCF CRISPR-Cas12a based sensor activated in-fabric. Our wFDCF mecA CRISPR-based sensor was exposed to various dsDNA trigger concentrations containing 0–100 fM mecA trigger, to assess in-fabric reaction fluorescence at $\\scriptstyle{\\mathrm{t}}=90$ min after fluid entry as compared to controls with a scrambled trigger. Increasing concentrations of trigger lead to an increase in fluorescence signal at the evaluation timepoint as denoted by the recorded mean pixel intensity from POF regions $\\therefore n=3)$ . A statistically significant difference between the negative control and trigger presence was observed at $90\\mathsf{m i n}$ only for concentrations equal and above that of 2.7 fM of trigger ${\\mathrm{\\Omega}}^{\\prime}{\\mathsf{P}}=0.002{\\mathrm{\\Omega}},{\\mathrm{\\Omega}}$ , which can be considered the limit of detection for this specific trigger, device configuration and evaluation timepoint. Violin plot shows median and quartiles as dotted lines and data points in dark green. Statistical differences were determined using unpaired one-tailed Student’s t-test. \n\n![](images/f0804281724e9dcbfee48ea5d7e2f8cf353b72302eabd1de1333853844b996ea.jpg) \nExtended Data Fig. 5 | Direct RNA detection in a wFDCF CRISPR-Cas13a based sensor. A CRISPR-Cas13a based MRSA SHERLOCK RNA sensor was prepared and freeze-dried over a wearable textile device for testing. All reactions contained RNaseAlert substrate, a quenched fluorophore probe that is cleaved by activated Cas13a (Integrated DNA Technologies, Coralville, IA). The wearable sensor was activated with a fluid splash of dd- $\\cdot\\mathsf{H}_{2}\\mathsf{O}$ containing 20 nM mecA RNA transcript trigger, while the plate samples were rehydrated with the same trigger concentrations to the originally deposited reaction volume $(4\\upmu\\up L)$ . Reactions in the wFDCF were monitored at $30^{\\circ}\\mathsf{C}$ for 30 minutes using the wearable optical device and the reference control in a BioTek NEO HTS plate reader (BioTek Instruments, Inc., Winooski, VT) in fluorescence mode (Ex. 470 nm / Em. $528\\mathsf{n m}$ ). Normalized pixel intensity in the wearable device is shown as mean (green dark line) $\\pm\\thinspace s.0$ . (green light region) of $\\mathsf{n}=3$ independent experiments and is comparable in dynamics to the results of the kinetic run conducted in the plate reader (red line) shown as a singlicate reference. \n\n![](images/c0a3672d03cb50754df01768230c1d37f9c25ec4101b20f33f5ed8e06b61fb70.jpg) \nExtended Data Fig. 6 | Antibiotic resistance Cas12a sensors for spa, ermA and mecA genes using in-wearable wFDCF sensors demonstrate orthogonal specificity. Only reaction chambers with a Cas12a sensor targeting the S. aureus virulence factor-encoding spa-gene (colored in green) generates a detectable signal within $30\\mathrm{min}$ . The plot shows mean (dark points) $\\pm\\thinspace s.{\\mathsf{d}}$ . (light colored regions) for $\\mathsf{n}=3$ individually fabricated and tested wFDCF reaction chambers for each sensor. The scale bar for the brightfield image of the fiber optic bundle is $250\\upmu\\mathrm{m}$ . \n\n![](images/fddd26c76a54954c995e5f4fd6319e6bae97cc5cf00f1ae5f86fcba4ad49bd6e.jpg) \n\nExtended Data Fig. 7 | Sensor multiplexing using different fluorescent proteins can be detected in a single wFDCF device. Top row, cell-free reactions in tubes demonstrating different fluorescent protein outputs generated post-rehydration from lyophilized FDCF PURE reactions after $30\\min$ at $30^{\\circ}\\mathsf{C}$ . All tubes were photographed with illumination using an Invitrogen Safe Imager 2.0 G6600 Blue Light Transilluminator (Carlsbad, CA). Bottom row, sensor images of wFDCF fiber bundle ends in (1) brightfield (intense light is placed over the laser-ablated POF sensor regions to spatially locate each fiber), (2) image when the sensor is dry, (3) image when wFDCF reaction is hydrated but without plasmid (30 min incubation at $30^{\\circ}C)$ , and (4) image when wFDCF reaction is hydrated with FP plasmids (30 min incubation at $30^{\\circ}\\mathsf{C})$ . These images of the fiber optics are representative of experiments performed independently three times with similar results each time. Scale bars are $250\\upmu\\mathrm{m}$ . \n\n![](images/7aa531a6de4e3e32e7b25b2f279f3ac6e54eb955a594cb3ffdfc622f7e6e3307.jpg) \nExtended Data Fig. 8 | Fabrication of wearable microcontroller system with LED illumination and spectrometric capabilities. a, Exploded isometric view of wearable POF spectrometer components with case and electronics. The device electronics are based on a Raspberry Pi Zero W Version 1.3 (Raspberry Pi Foundation, Cambridge, UK), assembled with a PiZ-UpTime battery power board (Alchemy Power Inc., Santa Clara, CA), an environmental sensing module, an LED illumination module, and a flexible camera for imaging. b, Photograph of an open assembled device. c, Photograph of a fully assembled device ready for imaging. d, Details of camera used in the device as well as the amber fluorescence emission filter and lens for magnification. Slots at the front of the bottom case fit the camera end, the LED arrangement and a vent for the environmental sensors. e, Top view of an assembled device to provide detail of compact electronics arrangement. f, Arrangement of wearable POF spectrometer with wireless connectivity in-garment for wFDCF reaction testing. \n\n# natureresearch \n\nCorresponding author(s): James J. Collins \n\nLast updated by author(s): Apr 29, 2021 \n\n# Reporting Summary \n\nNatureResearchishestmpvetheepbilioftekhatepublishhiformprestrctureforstecyadtaaenc in reporting.ForfurtherinformationonNature Researchpolicies,seeourEditorialPoliciesandtheEditorialPolicyChecklist. \n\n# Statistics \n\nForallstatistiaaeshathfolgeetihggndablegndaineetc \n\n![](images/8210e2847be2cd48d9fa21c68d8a1a24456a72170bece0ead8f20b1200cc7df8.jpg) \n\nOur web collection on statistics for biologists contains articles on many of the points above \n\n# Software and code \n\n# Policy information about availability of computer code \n\nData collection \n\nTwopythonbasedexectablesfortheRaspberyPiZeroWwerecreatedoneforntinousstandalonepolymericopticfiberignal acquisitionadheeforatithbynkbasedbieaplicat(BlycNewok,N)hanenig file \"RPi_W_Python_CFFDWSB_V-1-O-7_A_Sens.py\", and blynk.io-based mobile application code \"RPi_W_Pytho_--_Blkpareidedinelmntalifodutilenywleeloeeanhe followingopensurce(lcensed)dules:atplotlib3.1penC.1PthobasedRaspberymera13.and.1. modulesaspberyPFoundatiambridge,U)aswellasphasedT52111.0 control's modules (Adafruit Industries, New York, NY)and BlynkLib O.2.5 from blynk.io (BlynkInc.,NewYork,NY). \n\n# Data analysis \n\nColorimetricimagesusedage2ntoprocesstherawimagesforquantificationFofluorietricuminescentimages,theimageswere processed by custom Python code.For LFA band intensity analysis, ImageJ 1.52n was used. \n\nr \n\n# Data \n\n# Policy information about availability of data \n\nAllmanuscriptsmustincludeadataavalabilitystatementThisstatementshouldprovidethefollwinginformationhereaplicable: \n\n- Accession codes, unique identifiers, or web links for publicly available datasets - A list of figures that have associated raw data - A description of any restrictions on data availability \n\nAlldataddeadq should be addressed to J.J.C \n\n# Field-specific reporting \n\nPleaseselectelesihfdcfng \n\nLife sciences \n\nBehavioural & social sciences \n\nEcological, evolutionary & environmental sciences \n\nFor areference copy of thedocument with allsections,see nature.com/documents/nr-reporting-summary-flat.pdf \n\n# Life sciences study design \n\nAll studies must disclose on these points even when the disclosure is negative. \n\n
mple sizeSamplesizesforthecoometrceaablesreselectedatfeorprvdeauficientamplingftheperfmaceofthe designeddevicesandacctingforitiinlophlatiehydratiandractpefoaceothefluormetriceable
ata exclusionsfacemasksensorstestingwaspeformedonn=4sensorsforeachvariableonthebenchtopon=5foreachvariableforonthebreathing simulator apparatus. Forthefluoesntndumescetdatafochafnselltapticafibes)eargepielyas calculated.AnfibersbelowDofthemeanwereexcludedfrofinaanalysisThehand-assmbledARS-o-facemasksensorswere
plicationcarefulyinspectedfofabricatirrosisaligeduADushedensruringphlzatiandlssembledsenssdee were excluded from the experiment. StrictptiizedprocdreswereakentensurelohilztioftheDCractisccurredsimilalfoallofthedevicestested.Al hydratedreactionswereperformedintemperature-controlledenvironmentssimulatinghumansurfaceskintemperaturesatambient
ndomizationhumidityteplicatieldnisoheR-Co-ssthemcrcliateoftheaskwasmearedtoaitainempuf 35C and relative humidity of 1oo% to simulate the microclimate inside of a human-worn facemask. ForallourdeviceseachmbledfbricatedeviceasispectedfoamagetthefiberticsADsaterialnceitsed
ndinginspection,the devices were randomly chosen for experiments with the desired wFDCF reaction. BlindingisnotrelevanttoourstudyThedatapresentedarequantitativevalues(seemethodforhowalueswereotained)anddidnot require subjective judgment or interpretation. Blinding is not typically used in the field.
\n\n# Reporting for specific materials, systems and methods \n\nWerequirffladr ssfh \n\n# Materials & experimental systems Methods \n\n![](images/dc5e17a6b97af27e967d4b3794d63c17a1046c68371a72bc3e9fa58799cda10a.jpg) \n\n![](images/9eb3d702695a6c1073693f978774f6d19a42ce4fea53918e88e72c6b30b168ed.jpg) " + }, + { + "id": "10.1038_s41467-021-24382-4", + "DOI": "10.1038/s41467-021-24382-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-24382-4", + "Relative Dir Path": "mds/10.1038_s41467-021-24382-4", + "Article Title": "Skin-like mechanoresponsive self-healing ionic elastomer from supramolecular zwitterionic network", + "Authors": "Zhang, W; Wu, BH; Sun, ST; Wu, PY", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Stretchable ionic skins are intriguing in mimicking the versatile sensations of natural skins. However, for their applications in advanced electronics, good elastic recovery, self-healing, and more importantly, skin-like nonlinear mechanoresponse (strain-stiffening) are essential but can be rarely met in one material. Here we demonstrate a robust proton-conductive ionic skin design via introducing an entropy-driven supramolecular zwitterionic reorganizable network to the hydrogen-bonded polycarboxylic acid network. The design allows two dynamic networks with distinct interacting strength to sequentially debond with stretch, and the conflict among elasticity, self-healing, and strain-stiffening can be thus defeated. The representative polyacrylic acid/betaine elastomer exhibits high stretchability (1600% elongation), immense strain-stiffening (24-fold modulus enhancement), similar to 100% self-healing, excellent elasticity (97.9 +/- 1.1% recovery ratio, <14% hysteresis), high transparency (99.7 +/- 0.1%), moisture-preserving, anti-freezing (elastic at -40 degrees C), water reprocessibility, as well as easy-to-peel adhesion. The combined advantages make the present ionic elastomer very promising in wearable iontronic sensors for human-machine interfacing.", + "Times Cited, WoS Core": 375, + "Times Cited, All Databases": 385, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000672163900004", + "Markdown": "# Skin-like mechanoresponsive self-healing ionic elastomer from supramolecular zwitterionic network \n\nWei Zhang1, Baohu Wu2, Shengtong Sun 1✉ & Peiyi Wu 1✉ \n\nStretchable ionic skins are intriguing in mimicking the versatile sensations of natural skins. However, for their applications in advanced electronics, good elastic recovery, self-healing, and more importantly, skin-like nonlinear mechanoresponse (strain-stiffening) are essential but can be rarely met in one material. Here we demonstrate a robust proton-conductive ionic skin design via introducing an entropy-driven supramolecular zwitterionic reorganizable network to the hydrogen-bonded polycarboxylic acid network. The design allows two dynamic networks with distinct interacting strength to sequentially debond with stretch, and the conflict among elasticity, self-healing, and strain-stiffening can be thus defeated. The representative polyacrylic acid/betaine elastomer exhibits high stretchability $1600\\%$ elongation), immense strain-stiffening (24-fold modulus enhancement), ${\\sim}100\\%$ self-healing, excellent elasticity $(97.9\\pm1.1\\%$ recovery ratio, $<14\\%$ hysteresis), high transparency $(99.7\\pm$ $0.1\\%$ , moisture-preserving, anti-freezing (elastic at $-40^{\\circ}\\mathsf{C})$ , water reprocessibility, as well as easy-to-peel adhesion. The combined advantages make the present ionic elastomer very promising in wearable iontronic sensors for human-machine interfacing. \n\nSrkoi lne, icnovperiontegctihneg btohedyinonfear svoefrt etbisrsaute aanindmarle, ploanysd angketoy world1. Inspired by the ion-conducting nature and sensory functions of the skin, artificial ionic skins based on stretchable ionic conductors like hydrogels, ionogels, and ion-conducting elastomers have received considerable attention resulting in a series of temperature, pressure, and strain sensors2–6. Similar to many biological issues, skin is also self-repairable and selfprotective. As is known, human skin can autonomously heal from wounds to restore its mechanical and electrical properties7. More intriguingly, unlike the vast majority of elastomeric materials, skin shows a nonlinear J-shaped stress–strain mechanoresponse (strain-stiffening); that is, skin is soft to touch yet rapidly stiffens to prevent injury due to a sharp increase of elastic modulus at large strains8,9. Such a unique mechanoresponsive behavior represents one of nature’s key defense mechanisms, which is attributed to its composite structure comprising stiff collagen fibers to resist deformation and interwoven elastin network to ensure elastic recoil. In sharp contrast, although these mechanical properties are also highly desirable for the compliance, healability, and self-protection of skin-like wearable electronic devices, artificial ionic skins that mimic the all-round sensation, self-healing, and strain-stiffening properties of natural skins are still rare. \n\nWhile highly stretchable and self-healable ionic skins have been frequently reported10–14, most of the synthetic ionic conductors are strain-softening. There is often a conflict among elasticity, self-healability, and strain-stiffening for stretchable ionic conductors. In traditional elastomers, good elasticity relies on strong covalently bonded crosslinks, which allow the material to fully recover its original state driven by entropic gain15. In contrast, self-healing generally occurs through the reorganization of the intrinsic elastic network by regenerating dynamic non-covalent bonds7. Stretching such a dynamic network is usually accompanied by crosslinking density reduction and stress relaxation, leading to the remarkable attenuation of material modulus as well as poor elastic recovery from large deformations14,16–19. On the other hand, strain-stiffening materials normally involve two distinct networks with different rigidities that unfold progressively for synergizing softness and firmness20–23. For instance, bottlebrush elastomers could replicate the strain-stiffening characteristics of biological tissues by unfolding flexible strands at lower forces followed by stretching rigid backbone at higher forces9,21–24. In other reported elastomers, integrating permanent chemical crosslinks or crystalline domains with weak intermolecular crosslinks may also lead to strain-induced modulus increase25–27. Therefore, one major challenge to synthesize elastic, self-healing yet strain-stiffening ionic conductors arises in designing multiscale polymer networks, which concurrently possess dynamic yet strong crosslinks as well as supramolecular weak bonding to mimic the respective roles of stiff collagen fiber and soft elastin matrix in natural skin. Tian et al. recently developed a hybrid elastic hydrogel featuring cell-like starch granules embedded in a crosslinked polyacrylamide matrix, which displays both tissue-like strain-stiffening and self-healing behaviors through dynamic hydrogen bonding and granular interactions; however, in their system, chemical crosslinks are still existing, and thus only ${\\sim}90\\%$ healing efficiency was observed28. To the best of our knowledge, there is thus far no report on stretchable ionic conductors with combined good elasticity, full self-healability, and unique strain-stiffening properties. \n\nHerein, we report the design and preparation of a series of highly elastic, transparent, self-healable, and strain-stiffening proton-conductive ionic skins by introducing an entropy-driven supramolecular zwitterionic competing network to the hydrogenbonded (H-bonded) polycarboxylic acid chain network. Different from hydrogels and ionogels that rely on the use of large amounts of solvents, only the equilibrium moisture content of water is existing in the present ionic elastomers. This feature makes the intermolecular dimeric H-bonds strong enough to crosslink polycarboxylic acid chains at ambient conditions, yet become dynamic as immersed in high humidities to allow for full selfhealing. Importantly, the zwitterionic network consisting of weakly complexed zwitterions contributes to the initial softness of the ionic elastomer, which subsequently fragments during stretch resulting in an immensely stiffened H-bonded polycarboxylic acid network. Such a sequential debonding of two competing dynamic networks, as well as the rapid entropy-driven reorganization of zwitterions, leads to ultrahigh stretchability ( $1600\\%$ elongation), apparent strain-stiffening (24 times enhancement of differential modulus), full self-healability (almost $100\\%$ efficiency), and excellent elastic recovery $(97.9\\pm1.1\\%$ recovery ratio, $<14\\%$ hysteresis), in the case of the representative polyacrylic acid (PAA)/ betaine elastomer. The presence of zwitterions also renders the ionic elastomers with moisture-preserving and anti-freezing advantages, allowing the elastomers to steadily conduct protons even in harsh conditions. In addition, the resulting ionic skins are highly adhesive to readily adhere on various substrates and human skins, yet easily peeled off due to the inherent strainstiffening effect. More interestingly, the ionic skin can be recycled by quickly dissolving in water and recasting in air. As skin-like sensors, the ionic elastomers demonstrate timely response to strain and temperature changes, and can be further integrated with elastic conductive fabrics as an iontronic smart sensor to perceive pressure changes, demonstrating its great potential in wearable electronics. \n\n# Results \n\nMolecular design of mechanoresponsive PAA/zwitterion elastomers. Zwitterions, also called internal salts or dipolar ions, are small molecules containing an equal number of cationic and anionic functional groups in the same structure with an overall neutral charge, which perform important biological functions ranging from osmotic pressure regulation to the modification of cell surface properties29,30. As shown in Fig. 1a, we selected five representative zwitterions, including betaine, dimethylglycine, Lproline, sarcosine, and trimethylamine oxide (TMAO), to participate in the polymerization of acrylic acid (AA) for synthesizing a series of proton-conductive elastomers. The preparation process is rather simple by mixing AA, zwitterion, and water in the molar ratio of 1:1:2.5 with Irgacure 2959 as the photoinitiator, followed by ultraviolet (UV)-induced polymerization of AA for $30\\mathrm{min}$ . It is noted that the addition of a specified amount of water has two main roles: (1) the resulting water content in the as-prepared ionic elastomers is almost equal to the equilibrium moisture content at a relative humidity (RH) of $60\\%$ , which avoids drastic dehydration or hydration in air. (2) The presence of a proper amount of water would significantly weaken the direct contact ion pairs of zwitterions31, yet the strong dimeric H-bonds between PAA chains are not largely influenced, leading to a plasticized elastic network. As a result, all the synthesized elastomers are highly stretchable and transparent (Fig. 1b, Supplementary Fig. 1, and Movie 1). For example, the optical transmittance of PAA/betaine elastomer in the visible region can reach $99.7\\pm0.1\\%$ (Supplementary Fig. 2). \n\nWe highlight that nearly all the acid dissociation constants $(\\mathrm{{p}}K_{\\mathrm{{a}}})$ of zwitterions are lower than that of PAA in their bulk aqueous solutions (Fig. 1a), suggesting that zwitterions do not significantly deprotonate the carboxylic acid groups of PAA. Therefore, in the PAA-zwitterion system, three main interactions for chain crosslinking are assumed to exist with reduced bonding strength: COOH dimeric H-bonds, polymer–zwitterion complex, and zwitterion–zwitterion complex, as illustrated in Fig. 1c (the order will be confirmed in the following two-dimensional correlation spectroscopy (2DCOS) analysis; note that the latter two interactions are both water-involved, but for the convenience of discussion, water molecules are not shown in the scheme). Both previous Raman and simulation results implied that highconcentration zwitterions like betaine and TMAO in water would form chain-like aggregation due to the electrostatic interactions between negatively charged carboxylate/oxygen and positively charged nitrogen32–34. To further evidence the presence of the supramolecular zwitterion network, we performed the dynamic light scattering (DLS) analyses of AA/betaine $\\mathrm{{}^{\\prime}H}_{2}\\mathrm{{O}}$ reaction precursor, $\\mathrm{AA}/\\mathrm{H}_{2}\\mathrm{O}$ , and saturated betaine solutions. As shown in Fig. 1d, there are two peaks in the reaction precursor; the size at $2\\mathrm{nm}$ is ascribed to AA clustering via H-bonds, and the size at $37.8\\mathrm{nm}$ should arise from betaine clustering, which is much smaller than that in saturated betaine solution (centered at 615 nm, Supplementary Fig. 3) due to AA-induced pH decrease. Interestingly, the interactions between AA and betaine also contribute to their cosolvency in water (Supplementary Fig. 4), which is reminiscent of deep eutectic solvents with enhanced solubility due to strong hydrogen bonding35. \n\n![](images/cae683811533b7d28bf4f1da89cd4b39f049be60f6a7d6c927354b709a0d89f1.jpg) \nFig. 1 Molecular design and skin-like nonlinear mechanoresponse of PAA/zwitterion elastomers. a Molecular structures and $\\mathsf{p K}_{\\mathsf{a}}$ values of zwitterions and polyacrylic acid (PAA) for the preparation of proton-conductive ionic skins. b A transparent PAA/betaine elastomer film was stretched 12 times. c Schematic structure of PAA/betaine elastomer before and after stretch and the order of interaction strength among the three main interacting pairs as determined from the following 2DCOS analysis. Water molecules are not shown for clarity. As stretched, the supramolecular betaine chain network gradually fragments, leading to the immense stiffening of the elastomer arising from strongly H-bonded and extended PAA chains. d DLS size distribution curves of $A A/H_{2}O$ (molar ratio, 1:2.5) and AA/betaine $H_{2}O$ (molar ratio, 1:1:2.5) solutions. Note that the sub-nanometer sizes may be less precisely determined in the single large scattering angle DLS measurement due to the polydispersity effect51. e True stress and corresponding differential modulus curves of as-prepared PAA/zwitterion elastomers as a function of elongation (stretching rate: $100\\mathrm{mm}\\mathrm{min}^{-1})$ . The inset is the typical differential modulus–elongation curve of porcine skin reproduced from literature9. f PAA/betaine elastomer is mechanically compliant and adhesive to human skin, yet easily peeled off due to the inherent strain-stiffening effect. \n\nAll the above results support a hypothesis that there might be two kinds of chain networks in the PAA/zwitterion elastomer (Fig. 1c): taking PAA/betaine, for example, one is the covalent PAA chains self-crosslinked by strong dimeric H-bonds, and the other is the fugitive supramolecular betaine chains formed by weak ionic complexes. Obviously, these two networks are not independent, but associated via moderate-strength PAA–betaine ionic complexes, which share the same carboxylate groups. In the original state, the weakly bonded betaine network and randomcoil PAA chains contribute to the softness of the elastomer, while as stretched, the fragile betaine chains readily fragment resulting in a stiffened network dominated by strongly H-bonded and extended PAA chains. It is noted that such a covalentsupramolecular dual-network design is distinct from previously reported polyzwitterion-based elastomers10,11,14,36–39, which are strain-softening due to stretch-induced monotonic disassociation of chain crosslinks. \n\nJudging from the true stress- and corresponding differential modulus–elongation curves (Fig. 1e), all the PAA/zwitterion elastomers exhibit intense strain-stiffening behaviors similar to the characterisitics of porcine $s\\mathrm{kin}^{9}$ . The almost identical tensile curves of the five PAA/zwitterion elastomers in three batches each indicate that such unique mechanoresponse is fully reproducible (Supplementary Fig. 5). The maximum elongations of the as-prepared PAA-based elastomers are ca. $1700\\%$ . It is noted that the differential modulus $(\\partial\\sigma_{\\mathrm{true}}/\\partial\\lambda)$ curves of PAA/ zwitterion elastomers as a function of deformation ratio (λ) show a unique sigmoid shape, which contrasts with the steady increase in stiffness displayed by traditional synthetic elastomers9, yet coincides with natural skin’s deformation response more precisely. In the case of the same molar ratio, the type of zwitterions presents relatively small differences in the stiffening trend, yet the initial moduli are affected to a certain content. As shown in Supplementary Fig. 6, the initial modulus of PAA/ TMAO is the lowest, which is ascribed to the highest deprotonation degree of PAA (Supplementary Fig. 7). The initial moduli of the other four PAA/zwitterion elastomers slightly increase in the order of betaine, dimethylglycine, proline, and sarcosine, arising from mainly the increasing relative amount of H-bonded PAA as elucidated by $\\mathsf{p H}$ and attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectral comparison (Supplementary Fig. 7). In the case of PAA/betaine, the differential modulus first slightly decreases from 0.12 to $0.08\\mathrm{MPa}$ in the strain range of $0{-}70\\%$ , and then drastically increases to 3.0 MPa at the maximum $1600\\%$ strain, corresponding to ${\\sim}24$ times stiffness enhancement. Decreasing the amount of betaine in the PAA/betaine elastomer significantly weakens the strain-stiffening effect as well as stretchability (Supplementary Fig. 8), verifying the importance of dual-network design. Control samples by replacing betaine with other ionic salts/acids such as lithium bromide (LiBr) and $\\mathrm{CH}_{3}\\mathrm{COOH}$ show much weakened tensile strength and stretchability as well as diminished strain-stiffening effect (Supplementary Fig. 9), further consolidating the role of the supramolecular betaine network. Moreover, as observed in Fig. 1f, the PAA/betaine elastomer is both mechanically compliant and adhesive to adapt to human skin curvatures, yet easily peeled off due to the intense strain-stiffening effect (Supplementary Movie 1). The cytotoxicity tests with both HeLa and HepG2 cells prove the good biocompatibility of PAA/betaine elastomer that is suitable for on-skin applications (Supplementary Fig. 10). \n\nInternal interactions in PAA/betaine elastomer. To validate the internal interactions in the representative PAA/betaine elastomer, ATR-FTIR spectra of PAA, betaine, and dried PAA/betaine were compared in Fig. 2a. The FTIR spectrum of betaine exhibits two clear peaks at 1618 and $1380\\mathrm{cm}^{-1}$ for $\\nu(\\mathrm{COO^{-}})$ and $\\nu(\\mathrm{C-N})$ , respectively40, and the peak at $1695\\mathrm{cm}^{-1}$ corresponds to $\\nu(\\mathbf{C}=$ O) of PAA with dimeric H-bonds41. As for dried PAA/betaine, both the $\\nu(C=\\mathrm{O})$ of PAA and $\\nu(\\mathrm{C-N})$ of betaine shift to higher wavenumbers, while $\\nu(\\mathrm{COO^{-}})$ of betaine is almost unchanged, which reveals the ionic complexation between PAA and betaine. Such an ionic complexation is further evidenced by the proton nuclear magnetic resonance $\\mathrm{\\Omega^{\\prime1}H\\ N M R)}$ spectral comparison among betaine, PAA, and PAA/betaine dissolved in $\\mathrm{D}_{2}\\mathrm{O}$ (Fig. 2b; see the whole spectra in Supplementary Fig. 11), in which the complexation-related $\\mathrm{H}_{1},\\mathrm{H}_{2}^{\\mathrm{~~}}$ resonance peaks from betaine and $\\mathrm{H_{a}}$ peak from PAA all show remarkable chemical shifts. Furthermore, as presented in Fig. 2c, the $\\mathrm{\\pH}$ of $0.1\\mathrm{M}$ PAA (with respect to monomer concentration) in water is 2.18, while the pH of $\\mathrm{\\bar{0.1}M}$ betaine is 6.5. Mixing PAA and betaine leads to $\\mathsf{p H}$ values higher than that of PAA, suggesting that in PAA/betaine elastomer, betaine slightly deprotonates the carboxylic acid groups of PAA, and protons are the main charge carriers for ionic conductivity. \n\nWe further conducted iso-strain–stress relaxation experiments to study the relationship between stress dissipation and temperature42. As shown in Fig. 2d, a higher temperature is prone to promote the faster stress relaxation of PAA/betaine elastomer with a smaller residual stress. A stretched exponential function model was employed to study the stress relaxation kinetics with a theoretical prediction (Supplementary Table 1). ln $(\\tau^{*})$ as a function of $10\\bar{0}0/T$ was plotted and fitted and an apparent activation energy of $59.6\\mathrm{kJ}\\dot{\\mathrm{mol}}^{-1}$ was calculated by the Arrhenius equation. Such a value is much smaller than a typical covalent bond dissociation energy $(E_{\\mathrm{a}}(\\mathrm{C-C})\\approx350\\mathrm{kJ}\\mathrm{mol^{-1}},$ , implying that the viscoelastic behavior of PAA/betaine elastomer is dominated by non-covalent interactions. The supramolecular nature of PAA/betaine elastomer is also supported by the tensile curves with different stretching rates (Supplementary Fig. 12). A higher stretching rate leads to a higher modulus and more pronounced strain-stiffening effect, due to the delayed and sluggish response of chain disassociation16. \n\nTemperature-variable FTIR spectra of the as-prepared PAA/ betaine elastomer from 20 to $70^{\\circ}\\mathrm{C}$ were recorded to evaluate the strength and thermal sensitivities of the abovementioned interactions. As shown in Fig. 2e, with temperature increase, $\\nu$ $\\left(\\mathrm{COO^{-}}\\right)$ shifts to higher wavenumbers and $\\nu(\\mathrm{C-N})$ shifts to lower wavenumbers, suggesting the conversion of hydrated $\\mathrm{COO^{-}}$ and PAA-complexed $\\mathrm{C-N}$ to self-associated $[\\mathrm{N}(\\mathrm{C}\\dot{\\mathrm{H}}_{3})_{3}]^{+}{:}[\\mathrm{COO}^{-}]$ ion pairs34,40. Meanwhile, $\\nu(\\mathrm{COOH})$ from H-bonded PAA shifts to higher wavenumbers along with the intensity increase of free COOH, suggesting that temperature increase causes the disassociation of dimeric COOH H-bonds into free COOH. The temperature-dependent wavenumber shifts of the three main peaks present all gradual changes in the studied temperature range (Supplementary Fig. 13), indicating their mild thermal response. Conclusively, the increasing temperature would lead to the enhancement of ionic complexation and weakening of Hbonding, resulting in the more pronounced deprotonation degree of PAA and thus improved proton conductivity. From the energetical view, the PAA dimeric H-bonding could be enthalpydriven with temperature-induced weakening effect, while the enhanced betaine ionic complexation at elevated temperatures implies an uncommon entropy-driven physical crosslinking interaction, which may be caused by the desolvation events that give rise to large increases in translational entropy of solvent molecules43. \n\n2DCOS spectra were further generated from the temperaturevariable FTIR spectra, which can discern the sequential thermal response of different species44. On the basis of Noda’s judging rule with the consideration of both signs in synchronous and asynchronous spectra (Fig. 2f), the responsive order of different groups to temperature increase is $1392\\rightarrow1728\\rightarrow1639\\rightarrow1402\\rightarrow$ $\\mathrm{\\bar{1}701\\bar{c m}^{-1}}$ ( $\\stackrel{\\cdot}{\\rightarrow}$ means prior to or earlier than; see determination details in Supplementary Table 2), that is, $\\nu(\\mathrm{C-N})$ (betaine–betaine complex) $\\longrightarrow\\nu\\mathrm{(COOH)}$ (free PAA) $\\rightharpoonup\\nu(\\mathrm{COO^{-}})$ (betaine) $\\to\\nu(\\mathbf{C}\\mathrm{-}\\mathbf{N})$ \n\n![](images/794f507afca62cfee8022de27564cdd87e139dbf0e0469c874a6fd04ad0e84b9.jpg) \nFig. 2 Internal interactions of PAA/betaine elastomer. a FTIR spectra and assignments of PAA, betaine, and dried PAA/betaine. b $^1\\mathsf{H}$ NMR spectra of PAA, betaine, and PAA/betaine in $\\mathsf{D}_{2}\\mathsf{O}$ . The total solute concentrations are all 0.1 M. c pH values of 0.1 M PAA/betaine solutions with different AA:betaine molar ratios. d Iso-strain–stress relaxation curves at different temperatures. The inset is the corresponding fitted result according to Arrhenius equation. e Temperature-variable FTIR spectra of PAA/betaine elastomer upon heating from 20 to $70^{\\circ}\\mathsf C$ in the regions of $v(C=0)$ and $v(C-N)$ (interval: $5^{\\circ}\\mathsf{C})$ . f 2DCOS synchronous and asynchronous spectra generated from (e). In 2DCOS spectra, the warm colors (red and yellow) represent positive intensities, while cold colors (blue) represent negative intensities. \n\n(betaine–PAA complex) $\\rightarrow\\nu(\\mathbf{C}=\\mathbf{O})$ (H-bonded PAA). This sequence suggests a thermal sensitivity order of betaine–betaine ionic complex $>$ betaine–PAA complex ${\\tt>P A A}$ dimeric H-bonds, which primely consolidates our hypothesis about interaction strength in Fig. 1c (weak interaction has a higher thermal sensitivity). \n\nStrain-stiffening mechanism discussion. To elucidate the strainstiffening nature of PAA/betaine elastomer, we observed the strain-induced orientation changes with polarized optical microscopy. As shown in Fig. 3a, interference colors gradually appeared from $50\\%$ strain, and became stronger and stronger with increasing retardations after $100\\%$ strain. This observation accords with the initial slight decrease of differential modulus between 0 and $70\\%$ strain (Fig. 1e), in which supramolecular betaine network may be first destroyed and PAA network is stretched yet not stressed leading to the slight softening of the elastomer. After $100\\%$ strain, betaine network has been fully fragmented and the self-associated PAA chains with dimeric Hbonds are more and more extended resulting in the unidirectional chain alignment along the stretching direction and thus a stiffened material. \n\nSmall-angle X-ray scattering (SAXS) method was also employed to investigate the microstructural evolution of PAA/betaine elastomer. As shown in Fig. 3b, due to the thinner sample thickness with stretch, the scattering intensity of PAA/betaine elastomer decreases as the strain ratio increases. Interestingly, a broad peak between 1 and $2.5\\mathrm{nm}^{-1}$ can be identified in all the samples, which is attributed to the ion aggregation of betaines45. With stretch, the peak position moves toward a larger $q$ value, suggesting that the mean spacing between ion aggregates (d$\\operatorname{spacing}=2\\pi/q$ ) becomes shorter, corresponding to the gradual approaching of fragmented betaine networks to each other forced by the aligned PAA chains. To further profile the strain-stiffening process, we made a molecular dynamics simulation of this process by stretching a periodic amorphous cell containing one 20- repeating-unit PAA chain, 20 betaine molecules, and 50 water molecules (same to the used AA:betaine: $_\\mathrm{H}_{2}\\mathrm{O}$ molar ratio). As shown in Fig. 3c, at the undeformed state, PAA appears as a random-coil chain surrounded by the clustering betaine and water molecules, corresponding to an energetically stable soft network of PAA/betaine elastomer (total energy $=-2296.5\\mathrm{kcalmol^{-1}}$ ; electrostatic energy $=-2598.1\\mathrm{kcalmol^{-1}}.$ ). As stretched to $20\\%$ strain, the PAA chain is strongly extended along the stretching direction, and betaine–betaine network is fragmented with electrostatic energy increasing to $-1274.7\\mathrm{kcalmol^{-1}}$ . Note that the total energy also increases significantly to $8146.0\\mathrm{kcalmol^{-1}}$ , suggesting that the stretched state of the elastomer is metastable, which would autonomously recover to the initial state when released. \n\nOverall, the above polarized optical observations as well as in situ SAXS and molecular dynamics simulation results together consolidate the hypothesis of dual-network design and the key role of supramolecular competing zwitterionic network in the observed strain-stiffening behavior of PAA/betaine elastomer. Moreover, such strain-stiffening phenomenon may also be understood with the classical rubber elasticity theory. For an ideal network with constant volume $(V)$ and no energetic contribution to elasticity, the force $f{=}-T({\\partial S}/{\\partial L})_{T,V},$ where $T$ is the temperature, S the entropy, and $L$ the length46. In other words, the generated force with stretch is mainly determined by the strain-dependent entropy loss of the whole system. In the asprepared PAA/betaine elastomer, the curling, folding, wrapping, and collapsing of PAA chains as well as random clustering of betaines both contribute to a large conformational entropy47. Stretching would always decrease the entropy of PAA chains; however, the entropy-driven reorganizing nature of the betaine clustering network would compensate for the entropy loss of the whole system at small strains, while at large strains, fragmentation of betaine network occurs leading to more remarkable entropy loss. It is thus reasonable that a small applied force is enough to stretch the elastomer at small strains, while a larger force is required to stretch it more, corresponding to the apparent strain-stiffening behavior. \n\n![](images/b4dd59192b706696cfc06c675525de6dade93df95fa521473621716d999cdc67.jpg) \nFig. 3 Strain-stiffening mechanism, elasticity, moisture-preserving, and anti-freezing properties of PAA/betaine elastomer. a Polarized optical images of PAA/betaine elastomer with increasing strains. The film thickness is $0.5\\mathsf{m m}$ , and from top to bottom are the polarized modes in the absence of tint plate, and in the presence of $530\\mathsf{n m}$ tint plate at azimuth angles of $-45^{\\circ}$ and $45^{\\circ}$ , respectively. The observed orientation is parallel to the stretching direction. b SAXS scattering intensity $(I)$ vs scattering vector (q) profiles of PAA/betaine elastomer with different strains. c Molecular dynamics simulation of PAA/betaine elastomer before and after stretching (PAA with 20 repeating units $+20$ betaine $+50\\ H_{2}O;$ . With stretch, PAA chain extends, and the total energy significantly increases to a positive value indicating a metastable state. The increase of electrostatic energy is mainly due to betaine–betaine network fragmentation. d Successive tensile loading–unloading curves of PAA/betaine elastomer as stretched to different strains. The inset is the overlapped curves with single tensile curve to break. e Corresponding strain-dependent dissipation energy and dissipation ratios. f Cyclic tensile curves of PAA/betaine elastomer at a fixed maximum strain of $100\\%$ for uninterrupted 100 cycles (tensile speed $=100\\mathsf{m m}\\mathsf{m i n}^{-1})$ . g Humidity-dependent water content changes of PAA/betaine elastomer at $25^{\\circ}\\mathsf{C}$ . The inset is the water content changes when exposed to RH $60\\%$ for 7 days. h, i Mechanical properties and ionic conductivities of PAA/betaine elastomers equilibrated at different humidities. j DMA tensile curves of PAA/betaine elastomers at different temperatures. The inset picture shows that PAA/betaine elastomer remains elastic at $-40^{\\circ}\\mathsf C$ . k DSC heating and cooling curves of PAA/betaine elastomers equilibrated at RH 70, 80, and $90\\%$ . Data in $(\\pmb{\\mathrm{g}},\\mathbf{i})$ are presented as mean values $\\pm\\mathsf{S D}$ , $n=3$ independent elastomers. \n\nElasticity, moisture-preserving, and anti-freezing properties. In addition to high stretchability and strain-stiffening, PAA/betaine elastomer is also highly elastic with very rapid recovery. As presented in Fig. 3d, cyclically stretching the elastomer to increasing strains $(100-800\\%)$ ) reproduced almost identical curves to the single tensile curve to break, and the elastic recovery ratio can reach $97.9\\pm1.1\\%$ as released from 100 to $800\\%$ strains. The hysteresis area as represented by the calculated dissipation energy increases almost linearly with strain, and corresponding dissipation ratios are rather small $(<14\\%)$ (Fig. 3e). This phenomenon corresponds to the rapid elastic recovery of PAA/betaine elastomer with a low hysteresis, which may be related to the fast reformation of supramolecular betaine chain network in the unloading process48. This is understandable that betaine–betaine crosslinking in the elastomer is entropy-driven, so that the reformation of betaine chain network could autonomously occur with fast crosslink dynamics. To study its anti-fatigue behavior, the PAA/betaine elastomer was subjected to 100 consecutive loading–unloading cycles at a maximum strain of $1000\\%$ as shown in Fig. 3f. It is noted that after the first cycle (irreversible network rearrangement or physical bonding dissociation may occur in the first cycle), the tensile curves became narrower and almost unchanged until a steady state was reached in the following cycles, suggesting again the good elastic recovery of PAA/ betaine elastomer even released from very large strains. \n\nIn nature, many plants accumulate zwitterionic osmolytes like betaine and proline to prevent water crystallization and adjust water stress to help them survive in subzero and water-deficit environments49. Similarly, in the case of PAA/betaine elastomer, the abundant presence of betaine brings excellent moisturepreserving and anti-freezing properties. As demonstrated in Fig. $3\\mathrm{g}$ and Supplementary Fig. 14, the as-prepared elastomer with the AA:betaine: $_{\\mathrm{H}_{2}\\mathrm{O}}$ molar ratio of 1:1:2.5 has an almost equal water content of $21\\mathrm{wt\\%}$ with the elastomer equilibrated at RH $60\\%$ ; increasing environmental humidity would correspondingly increase the equilibrium water content and vice versa. Moreover, at the constant humidity of RH $60\\%$ , the water content of PAA/betaine elastomer is almost unchanged for a long time (7 days), suggesting the excellent moisturizing ability of betaine. As shown in Fig. 3h, the equilibrated PAA/betaine elastomer becomes much more stretchable (up to $4870\\%$ elongation at RH $90\\%$ ) with a decreased tensile strength as the humidity increases. Such a trend was also observed by simply increasing the feed molar ratio of water in the as-prepared PAA–betaine samples (Supplementary Fig. 15). This is reasonable because a high amount of water as a plasticizer would weaken both the PAA dimeric bonds and betaine ionic complexes in PAA/betaine elastomer, which is supported by humidity-dependent ATR-FTIR and second derivative spectral analyses (Supplementary Fig. 16). Moreover, a higher humidity also induces a significant increase of proton conductivity from $0.{\\dot{0}}2\\mathrm{mS}\\mathrm{m}^{-1}$ at RH $20\\%$ to $42.2\\mathrm{mS}\\mathrm{m}$ $^{-1}$ at RH $90\\%$ (Fig. 3i). The freezing resistance of PAA/betaine elastomer is evidenced from the tensile stress–strain curves at different temperatures (Fig. 3j). It was observed that the PAA/ betaine elastomer maintained prominent elasticity at a low temperature as $-40^{\\circ}\\mathrm{C}$ and became brittle lower than $-50^{\\circ}\\mathrm{C}$ . DSC detected an apparent freezing point of mobile water at $-41.1^{\\circ}\\mathrm{C}$ for the elastomer equilibrated at RH $90\\%$ and two freezing points at $-54.8$ and $-44.1^{\\circ}\\mathrm{C}$ for the sample equilibrated at RH $80\\%$ (Fig. 3k). No apparent freezing points were detected for the samples equilibrated at lower humidities than $70\\%$ , indicating that all the water molecules at these conditions are physically bound in the elastomer network. \n\nSelf-healing, water-processable, and adhesive properties. Owing to its supramolecular nature, PAA/betaine is also self-healable as immersed in a high-humidity environment. As shown in Fig. 4a, the scar on PAA/betaine film completely disappeared after $12\\mathrm{{h}}$ at room temperature and RH $80\\%$ , assisted by the mobile water to promote the regeneration of all physical bonds. Similarly, several cut PAA/betaine blocks also healed together at this condition to withstand bending and stretching (Fig. 4b and Supplementary Movie 2). Figure $\\mathtt{4c}$ shows the tensile curves of the original and healed samples for four times, which almost coincide indicating ${\\sim}100\\%$ healing efficiency. Furthermore, PAA/betaine elastomer can also be easily recycled by dissolving in water and recasting in air. Since the elastomer is composed of a linear polymer and abundant small molecules, as displayed in Fig. 4d, a film can be rapidly dissolved in water in $80\\mathrm{min}$ . Recasting the solution to evaporate water in the air at RH $60\\%$ reproduced all the original mechanical properties (Fig. 4e). Furthermore, PAA/betaine elastomer can also be fully dissolved in biologically relevant media (e.g., normal saline, phosphate-buffered saline (PBS) buffer, Dulbecco’s modified Eagle’s medium (DMEM) and RPMI-1640 culture media), and the recasted films remain transparent and highly stretchable (Supplementary Fig. 17). \n\nIn addition, as previously presented in Fig. 1e, the PAA/betaine elastomer is not only soft but also self-adhesive. Here, we evaluate its adhesion energy with various substrates via $90^{\\circ}$ peeling tests. As shown in Fig. 4f, g, the interfacial toughness between PAA/ betaine elastomer and adherends (polytetrafluoroethylene (PTFE), glass, PET, copper, wood, and porcine skin) ranges from $5\\mathrm{J}\\mathrm{m}^{-2}$ for PTFE to a maximum of $1\\dot{7}6\\mathrm{J}\\mathrm{m}^{-2}$ for porcine skin. We attribute the strong adhesion of PAA/betaine elastomer on polar substrates to the presence of multiple interactions including metal coordination, hydrogen bonding, electrostatic attraction, and cation– $\\cdot\\pi$ interactions, as illustrated in Fig. $4\\mathrm{h}^{11}$ . The strongest adhesion occurs on porcine skin, which may be caused by both the rough surface of the skin and the wet interface that facilitates the penetration of PAA and betaine molecules leading to more physical interlocks. \n\nMultiple sensory capabilities of ionic skin. As a unique mechanoresponsive and adhesive ionic skin, PAA/betaine elastomer is able to serve as a sensor to perceive a variety of external stimuli via electrical signals. For instance, as the elastomer is stretched, the resistance increases nonlinearly upward with strain (Fig. 5a). The gauge factors in the small and large strain ranges were calculated to be 1.1 and 8.0, respectively. Cyclically stretching PAA/betaine film to the fixed strains of 50, 100, 150, and $20\\%$ produced repeatable and strain-dependent resistance changes (Fig. 5b). The ability of PAA/betaine elastomers as strain sensors was demonstrated by directly adhering to the adhesive film on the human fingers and throat, and bending or swallowing produced reliable electrical response (Fig. 5c, d and Supplementary Fig. 18). In addition, the change in resistance of the elastomer exhibited excellent stability and repeatability during continuous stretching for 350 cycles at a fixed strain of $20\\%$ (Fig. 5e), indicating its prominent durability. Moreover, the proton conductivity of PAA/betaine elastomer is also sensitive to temperature, and the sensitivity can reach a very high value of $1.5\\bar{8^{\\circ}}\\%^{\\circ}\\mathrm{C}^{-1}$ , higher than conventional polyacrylamide hydrogelbased ionic skin and a few commonly used salt solutions and ionic liquids (Supplementary Fig. 19). As shown in Fig. 5f, heating and cooling the elastomer film produced a very rapid response of resistance changes in a wide temperature range between $^{-25}$ and $70^{\\circ}\\mathrm{C}$ \n\nFurthermore, the PAA/betaine elastomer could also act as an iontronic capacitive sensor to detect pressure changes. As illustrated in Fig. ${5}\\mathrm{g},$ the pressure sensor has a sandwich-like structure consisting of two elastic conductive fabrics as electrodes and PAA/betaine elastomer as the iontronic layer. When a normal force is applied to the sensor, the electrical double layer capacitance at the elastic electrolytic–electronic interface will correspondingly change50. We evaluated pressure sensitivity, response time, and repeatability to characterize the performance of PAA/betaine elastomer-based iontronic sensor. The sensitivity is defined as $S=\\delta(\\Delta C/C_{0})/\\delta P_{\\perp}$ , which is the slope of the measured capacitance-pressure curve (Fig. 5h). As shown, the fabricated sensor could operate over a wide pressure range with a sensitivity of $200\\mathrm{MPa}^{-1}$ in the low-pressure range $(<0.5\\mathrm{{kPa})}$ , and 22.9 and $3.5\\mathrm{MPa}^{-1}$ in the high-pressure range, typical for iontronic sensors50. Upon loading a pressure of $0.36\\mathrm{kPa}$ , the response time appeared to be very short within $700\\mathrm{{ms}}$ (Fig. 5i). As shown in \n\n![](images/6643c0285e538cc8a8e535985fa9042fc3ad63b6202ed9e3d9f95f58738b9865.jpg) \nFig. 4 Self-healing, water-processable, and adhesive properties of PAA/betaine elastomer. a Self-healing process of the PAA/betaine elastomer was observed by the optical microscope. A scar autonomously healed after $12\\mathsf{h}$ at $R H80\\%$ . The experiment was repeated three times independently with similar results. b Three individual PAA/betaine elastomer blocks healed together to withstand bending and stretching. The elastomers were colored blue and orange with methylene blue and semixylenol orange, respectively. c Tensile curves of the original elastomer and those after successive four selfhealing cycles. d PAA/betaine elastomer can be dissolved in water in $80\\mathrm{min}$ . e Tensile curves of the original and recasted PAA/betaine elastomer films at RH $60\\%$ indicating its water reprocessability. f, g Ninety-degree peeling curves and corresponding interfacial toughness of PAA/betaine elastomer with different substrates (peeling rate $=50\\mathsf{m m}\\mathsf{m i n}^{-1}.$ ). Data are presented as mean values $\\pm\\mathsf{S D}_{\\mathsf{\\Pi}}$ $n=3$ independent elastomers. h Schematic adhesion mechanisms. \n\nFig. 5j, dynamically increasing the applied pressure also generated reliable and repeatable capacitance changes. To further characterize its durability, the iontronic sensor was subjected to more than 450 cycles of loading/unloading experiments under the same pressure; as shown in Supplementary Fig. 20, the highly reproduced capacitance signals strongly confirm the robust performance of the sensor. As a demonstration, we adhered four PAA/betaine elastomer-based iontronic sensors on a glove, and pressing an object with the ring, middle, index, and thumb fingers in sequence presented real-time and sequential response from the synchronized four data-collecting channels (Fig. 5k). All the above results suggest the great potential of PAA/betaine elastomer-based ionic skin in detecting timely strain, temperature, and pressure changes that are important in wearable electronics and smart fabrics. \n\n# Discussion \n\nIn this paper, we report, to the best of our knowledge, the first example of ionic skins to mimic the all-around sensory, selfhealing, and strain-stiffening properties of natural skin. The unique mechanoresponsive ionic skin was readily achieved via a dual-network design by introducing an entropy-driven supramolecular zwitterionic competing network to the H-bonded polycarboxylic acid network to mimic the roles of soft elastin network and stiff collagen fibers in natural skins, respectively. Compared to previously reported ionic skin materials involving hydrogels, organohydrogels, ionogels, and ionic conductive elastomers, the present elastomer shows extraordinary mechanical and optical properties in terms of strain-stiffening, full self-healing, ultrahigh stretchability, excellent elastic recovery, high transparency, air stability (for gels, the ability of solvent retention in the air), frost resistance, and self-adhesion (see a rough comparison with several typical ionic skin materials in Table 1; extended comparison can be found in Supplementary Table 3). Intriguingly, the combination of two competing networks attributed from three dynamic interactions with different interacting strengths defeats the inherent conflict among elasticity, self-healability, and strain-stiffening for stretchable ionic conductors. This work not only lays the mechanistic foundation for interpreting the dual crosslinking network-related nonlinear mechanoresponsive behavior but also paves the way for designing robust materials with skin-like sophisticated sensory and mechanical properties. We anticipate our strategy may inspire a series of biomimetic materials with a variety of applications in sensors, wearable electronics, smart textiles, human–machine interfacing, and so on. \n\n![](images/4aafa920c46ae90450b319da091c3c05285782514e0d759ee3bb0f0f09e16f46.jpg) \nFig. 5 Sensing applications of PAA/betaine elastomer-based iontronic sensors. a Strain-dependent resistance changes of PAA/betaine elastomer. b Realtime response curves measured at fixed strains of 50, 100, 150 and $200\\%$ for ten cycles each. c, d The elastomer-based strain sensor senses human finger bending and swallowing movements. e Relative resistance variations of the elastomer-based strain sensor upon stretching to $200\\%$ strain for 350 cycles. f Temperatureinduced real-time resistance changes of PAA/betaine elastomer between $-25$ and $70^{\\circ}\\mathsf{C}$ . $\\pmb{\\mathrm{\\check{g}}}$ Schematic structure for the PAA/betaine elastomer-based iontronic pressure sensor. h Pressure-dependent capacitance variations (loading speed: $5\\mathsf{m m}\\mathsf{m i n}^{-1};$ . $\\mathsf{S}_{1},\\mathsf{S}_{2},$ and $\\mathsf{S}_{3}$ are the calculated sensitivities. i Response time at the loading pressure of $0.36\\mathsf{k P a}$ . j Dynamic loading/unloading curves at different pressures. $\\pmb{\\mathrm{k}}$ Synchronized capacitive response of four iontronic sensors adhered on a glove by pressing with different fingers. \n\n# Methods \n\nMaterials. Betaine, dimethylglycine, L-proline, sarcosine, TMAO, and methylene blue were obtained from Shanghai Titan Technology. AA and semixylenol orange were purchased from Aladdin Chemical. Irgacure 2959 was purchased from TCI chemical. PAA (average $M_{\\mathrm{W}}{\\approx}100,000\\ \\mathrm{g}\\mathrm{mol}^{-1}$ , $35\\mathrm{wt\\%}$ in $\\mathrm{H}_{2}\\mathrm{O}_{\\cdot}^{\\cdot}$ ), acrylamide, $N,N^{\\prime}$ -methylene bisacrylamide, ammonium persulfate, $N,N,N^{\\prime},N^{\\prime}$ -tetramethylethylenediamine, and LiBr were purchased from Sigma-Aldrich. NaCl and $\\mathrm{CH}_{3}\\mathrm{COOH}$ were purchased from Sinopharm Chemical Reagent. RPMI-1640 and DMEM (high glucose) culture media were purchased from Genom Co. Ltd. PBS and normal saline solutions were freshly prepared in the laboratory. \n\nPreparation of PAA/zwitterion elastomers. AA was purified by passing through a basic alumina column to remove inhibitors. The reaction precursor was prepared by mixing AA, zwitterion, $_\\mathrm{H}_{2}\\mathrm{O}$ (molar ratio, AA:zwitterion: $\\mathrm{\\cdotH}_{2}\\mathrm{O}=1{:}1{:}2.5)$ with Irgacure 2959 as photoinitiator (1:500 molar ratio to the monomer). The precursor was then poured into a sealed glass mold with silicone spacer, and polymerized by $360\\mathrm{nm}$ UV irradiation for $30\\mathrm{min}$ . \n\n# Preparation of PAA/betaine elastomer-based iontropic pressure sensor. \n\nPAA/betaine elastomer-based iontropic sensor was fabricated by sandwiching a dielectric layer of PAA/betaine elastomer (thickness: $2\\mathrm{mm}$ ) between two elastic conductive fabrics (LessEMF; surface resistivity ${<}1\\Omega\\thinspace\\mathrm{sq}^{-1}$ ; thickness: $0.40\\mathrm{mm}$ ). Two electrodes were connected to the conductive fabrics to monitor the pressureinduced real-time capacitance changes with a multichannel source meter (DAQ6510, Keithley). \n\nCharacterizations. The size distributions of AA/betaine $/\\mathrm{H}_{2}\\mathrm{O}$ mixture, $\\mathrm{AA}/\\mathrm{H}_{2}\\mathrm{O}$ mixture, and saturated betaine solution were determined by DLS (Malvern Zetasizer Nano ZS) at a backscatter angle of $173^{\\circ}$ . Tensile tests of the elastomers were carried out on a universal testing machine (UTM2103, Shenzhen Suns technology) at a rate of $100\\mathrm{mm}\\mathrm{min}^{-1}$ unless otherwise stated. All the measured samples have a length of $8\\mathrm{mm}$ , a thickness of $0.5\\mathrm{mm}$ , and a width of $5\\mathrm{mm}$ . The transparency of the film (thickness ${\\sim}100\\ \\upmu\\mathrm{m})$ was evaluated with a UV–Visible spectrophotometer (Lambda 950, PerkinElmer). ATR-FTIR spectra were collected on a Nicolet iS50 spectrometer with the ATR diamond crystal. Thermogravimetry analysis (TGA) was performed on TA TGA550 via scanning a temperature range from 30 to $300^{\\circ}\\mathrm{C}$ under airflow (heating rat $\\mathsf{s}=10^{\\circ}\\mathrm{C}\\operatorname*{min}^{-\\mathsf{I}}$ ). Differential scanning calorimetry (DSC) heating and cooling curves were collected using TA DSC250 scanning from $-90^{\\circ}\\mathrm{C}$ to $20^{\\circ}\\mathrm{C}$ at a scanning rate of $5^{\\circ}\\dot{\\mathrm{C}}\\ \\operatorname*{min}^{-1}$ under nitrogen flow. The stress relaxation measurements with the strain of $100\\%$ and tensile tests at specific temperatures were performed on a TA Q800 dynamic mechanical analyzer (DMA). Ninety-degree peeling tests were carried out using the $90^{\\circ}$ peel test apparatus equipped on a vertical dynamometer (ESM303, MARK-10). Before the test, a rectangular copper foil of $4\\times1~\\mathrm{cm}^{2}$ was laminated on the elastomer/substrate and preloaded by $700\\mathrm{g}$ weight for $30\\mathrm{min}$ . The PAA/betaine elastomer film was then delaminated perpendicularly to the substrate at a rate of $50\\mathrm{mm}\\mathrm{min}^{-1}$ . Resistance changes of PAA/betaine elastomer-based sensors were monitored by a multimeter (Tektronix, DMM 4050). \n\nTable 1 A rough comparison of the overall performance between this work and previously reported typical ionic skin materials. \n\n\n
onic skin naterials Mechanoresponse Self-healingMax. strain (%)Elastic recoveryTransparency (%)Air stabilityAnti-. freezingAdhesionRefs.
PAAm/saltSofteningNone~800ratio (%) ~100>95Poor(℃) -17None6,48,52
nydrogel ACC/PAA/Softening20 min,100%>1000PoorOpaquePoorNoneNone18
vinatm hydrogelSofteningFast, 100%>3400 PoorOpaquePoorNoneNone53
nydrogel PDMAPS/claySoftening24h,98%1500NA98.8Poor NAYes11
nydrogel P(SPMA-r-MMA)Softening3h,98.3%2636~89~100GoodNANA54
organohydrogel PMMA-r-BA/SofteningNA85096.198.5GoodNANA13
ODMAPS ionogelSoftening48 h, 100%>10,00063>90Good<-10NA
PIL-based ionogel (MEA-CO-1BA)Stiffening StiffeningNone 24h, 30-40%1390 174497 95~95 90Good Good-75 -14.4NA Yes55
last/bBetaine Stiffening12 h,100%160097.999.7Good-40YesThis work
\n\nSimulation of stress relaxation results. Kohlrausch–Williams–Watts function was employed to simulate the stress relaxation behavior \n\n$$\n\\frac{\\sigma}{\\sigma_{0}}=\\exp\\left(-\\left(\\frac{t}{\\tau}\\right)^{\\beta}\\right)\n$$ \n\nwhere $\\tau^{*}$ is the characteristic relaxation time at which $\\sigma/\\sigma_{0}$ is the numerical value of $1/e$ . The exponent $\\beta$ $(0<\\beta<1)$ is the breadth of the stress relaxation time distribution. $\\tau^{*}$ and $\\beta$ are the fitting parameters, as shown in Supplementary Table 1. \n\nTemperature-variable FTIR measurement. The sample was prepared as follows: ${\\sim}200\\upmu\\mathrm{L}$ of PAA/betaine precursor was cast on a $\\mathrm{CaF}_{2}$ tablet and then covered with another tablet. The tablets were then irradiated under UV light $(365\\mathrm{nm})$ for $^{\\textrm{1h}}$ at room temperature to obtain PAA/betaine elastomer film with suitable thickness for transmission IR measurement. The sample was further put in a chamber at room temperature and RH $60\\%$ for $24\\mathrm{h}$ to reach equilibrium. For temperaturecontrolled measurement, the sealed sample was heated from 20 to $70^{\\circ}\\mathrm{C}$ with an interval of $5^{\\circ}\\mathrm{C}$ in the transmission mode on a Nicolet iS50 FTIR spectrometer. \n\nTwo-dimensional correlation spectroscopy. The temperature-dependent FTIR spectra of PAA/betaine elastomer from 20 to $70^{\\circ}\\mathrm{C}$ were used for performing 2D correlation analysis. 2D correlation analysis was carried out using the software 2D Shige ver. 1.3 ( $\\circledcirc$ Shigeaki Morita, Kwansei-Gakuin University, Japan, 2004–2005), and was further plotted into the contour maps by Origin program, ver. 9.8. In the contour maps, warm colors (red and yellow) are defined as positive intensities, while cold colors (blue) as negative ones. \n\nSmall-angle X-ray scattering. SAXS experiments were performed at the SSRF beamline BL16B (Shanghai, China) at an X-ray energy of $10.0\\mathrm{keV}$ with a wavelength of $\\lambda=1.24\\mathrm{\\AA}$ . Samples were measured perpendicular to the beam with the sample-detector distance of $1.87\\mathrm{m}$ to cover the scattering vector $q$ range from 0.1 to $6\\mathrm{{nm}^{-1}}$ $(q$ is the scattering vector, $q=(4\\pi/\\lambda)\\sin(\\theta);2\\theta$ is the scattering angle). The scattering patterns were obtained with a short exposure time $(120s)$ , and air as the background was subtracted. The SAXS patterns were radially averaged to obtain the intensity profiles. \n\nMolecular dynamics simulation. A periodic model of PAA/betaine elastomer containing one PAA chain (20 repeating units), 20 betaine molecules, and 50 water molecules was constructed in the Amorphous Cell module of Materials Studio, ver. 2019. The structure optimization and the calculation of potential energies were performed in the Forcite module. Cell parameter adjustment and re-optimization were employed to simulate the stretching process. \n\nCytotoxicity tests of PAA/betaine elastomer. The cytotoxicity of PAA/betaine elastomer was evaluated with HeLa cells (cervical cancer) and HepG2 (human hepatocellular carcinomas) cells using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide) assays. The cells were seeded in 96-well plates at a density of $1\\times10^{4}$ cells/well, and then cultured in $5\\%$ $\\mathrm{CO}_{2}$ at $37^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . The original medium was replaced with a fresh culture medium containing PAA/ betaine elastomer at a final concentration of $0{-}2\\mathrm{mg/mL}$ and incubated for 12 and $24\\mathrm{h}$ , respectively. MTT $(10\\upmu\\mathrm{L},0.5\\:\\mathrm{mg/mL})$ was added to each well of the 96-well assay plate for $^{4\\mathrm{h}}$ at $37^{\\circ}\\mathrm{C}$ . After DMSO $\\mathrm{\\langle100\\upmuL/well\\rangle}$ was added, the absorbance was measured at $450\\mathrm{nm}$ using a microplate reader. \n\nReporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nThe data that support the findings of this study are available within the article and its Supplementary information files. \n\nReceived: 23 February 2021; Accepted: 16 June 2021; Published online: 02 July 2021 \n\n# References \n\n1. Wang, M. et al. Artificial skin perception. Adv. Mater. 32, e2003014 (2020). \n2. Keplinger, C. et al. Stretchable, transparent, ionic conductors. Science 341, \n984–987 (2013). \n3. Yang, C. & Suo, Z. Hydrogel ionotronics. Nat. Rev. Mater. 3, 125–142 (2018). \n4. Lee, H.-R., Kim, C.-C. & Sun, J.-Y. Stretchable ionics - a promising candidate for upcoming wearable devices. Adv. Mater. 30, e1704403 (2018). \n5. Shi, L. et al. Highly stretchable and transparent ionic conducting elastomers. Nat. Commun. 9, 2630 (2018). \n6. Sun, J.-Y., Keplinger, C., Whitesides, G. M. & Suo, Z. Ionic skin. Adv. Mater. 26, 7608–7614 (2014). \n7. Kang, J., Tok, J. B. H. & Bao, Z. Self-healing soft electronics. Nat. Electron. 2, 144–150 (2019). \n8. Storm, C., Pastore, J. J., MacKintosh, F. C., Lubensky, T. C. & Janmey, P. A. Nonlinear elasticity in biological gels. Nature 435, 191–194 (2005). \n9. Vatankhah-Varnosfaderani, M. et al. Chameleon-like elastomers with molecularly encoded strain-adaptive stiffening and coloration. Science 359, 1509–1513 (2018). \n10. Lei, Z. & Wu, P. A supramolecular biomimetic skin combining a wide spectrum of mechanical properties and multiple sensory capabilities. Nat. Commun. 9, 1134 (2018). \n11. Gao, G. et al. Bioinspired self-healing human-machine interactive touch pad with pressure-sensitive adhesiveness on targeted substrates. Adv. Mater. 32, e2004290 (2020). \n12. Li, T., Wang, Y., Li, S., Liu, X. & Sun, J. Mechanically robust, elastic, and healable ionogels for highly sensitive ultra-durable ionic skins. Adv. Mater. 32, e2002706 (2020). \n13. Kim, Y. M. & Moon, H. C. Ionoskins: nonvolatile, highly transparent, ultrastretchable ionic sensory platforms for wearable electronics. Adv. Funct. Mater. 30, 1907290 (2019). \n14. Lei, Z. & Wu, P. A highly transparent and ultra-stretchable conductor with stable conductivity during large deformation. Nat. Commun. 10, 3429 (2019). \n15. Zhang, Q. et al. An elastic autonomous self-healing capacitive sensor based on a dynamic dual crosslinked chemical system. Adv. Mater. 30, e1801435 (2018). \n16. Tan, Y. J. et al. A transparent, self-healing and high- $\\cdot\\kappa$ dielectric for low-fieldemission stretchable optoelectronics. Nat. Mater. 19, 182–188 (2020). \n17. Zhang, Q. et al. Exploring a naturally tailored small molecule for stretchable, self-healing, and adhesive supramolecular polymers. Sci. Adv. 4, eaat8192 (2018). \n18. Lei, Z., Wang, Q., Sun, S., Zhu, W. & Wu, P. A bioinspired mineral hydrogel as a self-healable, mechanically adaptable ionic skin for highly sensitive pressure sensing. Adv. Mater. 29, 1700321 (2017). \n19. Dai, X. et al. A mechanically strong, highly stable, thermoplastic, and selfhealable supramolecular polymer hydrogel. Adv. Mater. 27, 3566–3571 (2015). \n20. Hanif, A. et al. A skin-inspired substrate with spaghetti-like multi-nanofiber network of stiff and elastic components for stretchable electronics. Adv. Funct. Mater. 30, 2003540 (2020). \n21. Keith, A. N. et al. Bottlebrush bridge between soft gels and firm tissues. ACS Cent. Sci. 6, 413–419 (2020). \n22. Kouwer, P. H. J. et al. Responsive biomimetic networks from polyisocyanopeptide hydrogels. Nature 493, 651–655 (2013). \n23. Wang, Y. et al. Biomimetic strain-stiffening self-assembled hydrogels. Angew. Chem. Int. Ed. 59, 4830–4834 (2020). \n24. Vatankhah-Varnosfaderani, M. et al. Mimicking biological stress-strain behaviour with synthetic elastomers. Nature 549, 497–501 (2017). \n25. Lin, S., Liu, J., Liu, X. & Zhao, X. Muscle-like fatigue-resistant hydrogels by mechanical training. Proc. Natl Acad. Sci. USA 116, 10244–10249 (2019). \n26. Chen, S. et al. Mechanically and biologically skin-like elastomers for biointegrated electronics. Nat. Commun. 11, 1107 (2020). \n27. Zhang, Q., Liu, X., Duan, L. & Gao, G. A DNA-inspired hydrogel mechanoreceptor with skin-like mechanical behavior. J. Mater. Chem. A 9, 1835–1844 (2021). \n28. Fang, Y. et al. Dynamic and programmable cellular-scale granules enable tissue-like materials. Matter 2, 948–964 (2020). \n29. Erfani, A., Seaberg, J., Aichele, C. P. & Ramsey, J. D. Interactions between biomolecules and zwitterionic moieties: a review. Biomacromolecules 21, 2557–2573 (2020). \n30. Shao, Q. & Jiang, S. Molecular understanding and design of zwitterionic materials. Adv. Mater. 27, 15–26 (2015). \n31. Ye, Z., Sun, S. & Wu, P. Distinct cation–anion interactions in the UCST and LCST behavior of polyelectrolyte complex aqueous solutions. ACS Macro Lett. 9, 974–979 (2020). \n32. Amorim da Costa, A. & Leite, J. E. S. Molecular association of betaine and betaine hydrochloride in aqueous solutions – a study by Raman spectroscopy. Biochim. Biophys. Acta 1525, 161–166 (2001). \n33. Civera, M., Fornili, A., Sironi, M. & Fornili, S. L. Molecular dynamics simulation of aqueous solutions of glycine betaine. Chem. Phys. Lett. 367, 238–244 (2003). \n34. Di Gioacchino, M., Bruni, F. & Ricci, M. A. Aqueous solution of betaine: hydration and aggregation. J. Mol. Liq. 318, 114253 (2020). \n35. Mota-Morales, J. D. et al. Free-radical polymerizations of and in deep eutectic solvents: green synthesis of functional materials. Prog. Polym. Sci. 78, 139–153 (2018). \n36. Pei, X., Zhang, H., Zhou, Y., Zhou, L. & Fu, J. Stretchable, self-healing and tissue-adhesive zwitterionic hydrogels as strain sensors for wireless monitoring of organ motions. Mater. Horiz. 7, 1872–1882 (2020). \n37. Dong, D. et al. High-strength and fibrous capsule–resistant zwitterionic elastomers. Sci. Adv. 7, eabc5442 (2021). \n38. Lei, Z., Zhu, W., Zhang, X., Wang, X. & Wu, P. Bio-inspired ionic skin for theranostics. Adv. Funct. Mater. 30, 2008020 (2020). \n39. Mo, F. et al. Zwitterionic sulfobetaine hydrogel electrolyte building separated positive/negative ion migration channels for aqueous $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}\\mathrm{O}_{2}$ batteries with superior rate capabilities. Adv. Energy Mater. 10, 2000035 (2020). \n40. Viertorinne, M., Valkonen, J., Pitkänen, I., Mathlouthi, M. & Nurmi, J. Crystal and molecular structure of anhydrous betaine, $\\mathrm{(CH_{3})_{3}N C H_{2}C O_{2}}$ . J. Mol. Struct. 477, 23–29 (1999). \n41. Dong, J., Ozaki, Y. & Nakashima, K. Infrared, raman, and near-infrared spectroscopic evidence for the coexistence of various hydrogen-bond forms in poly(acrylic acid). Macromolecules 30, 1111–1117 (1997). \n42. Zhang, X., Wu, B., Sun, S. & Wu, P. Hybrid materials from ultrahighinorganic-content mineral plastic hydrogels: arbitrarily shapeable, strong, and tough. Adv. Funct. Mater. 30, 1910425 (2020). \n43. Yu, A. C. et al. Physical networks from entropy-driven non-covalent interactions. Nat. Commun. 12, 746 (2021). \n44. Sun, S. & Wu, P. Spectral insights into microdynamics of thermoresponsive polymers from the perspective of two-dimensional correlation spectroscopy. Chin. J. Polym. Sci. 35, 700–712 (2017). \n45. Choi, U. H. & Runt, J. in Encyclopedia of Polymeric Nanomaterials (eds Kobayashi, S. & Müllen, K.) (Springer, 2021). \n46. Rubinstein, M. & Colby, R. H. Polymer Physics (Oxford University Press, New York, 2003). \n47. Shao, Y., Jia, H., Cao, T. & Liu, D. Supramolecular hydrogels based on DNA self-assembly. Acc. Chem. Res. 50, 659–668 (2017). \n48. Lei, H. et al. Stretchable hydrogels with low hysteresis and anti-fatigue fracture based on polyprotein cross-linkers. Nat. Commun. 11, 4032 (2020). \n49. Sui, X. et al. Zwitterionic osmolyte‐based hydrogels with antifreezing property, high conductivity, and stable flexibility at subzero temperature. Adv. Funct. Mater. 30, 1907986 (2020). \n50. Chang, Y. et al. First decade of interfacial iontronic sensing: from droplet sensors to artificial skins. Adv. Mater. 32, e2003464 (2020). \n51. Fischer, K. & Schmidt, M. Pitfalls and novel applications of particle sizing by dynamic light scattering. Biomaterials 98, 79–91 (2016). \n52. Song, J. et al. Mechanically and electronically robust transparent organohydrogel fibers. Adv. Mater. 32, 1906994 (2020). \n53. Zhang, Y.-Z. et al. MXenes stretch hydrogel sensor performance to new limits. Sci. Adv. 4, eaat0098 (2018). \n54. Lee, J. et al. Water-processable, stretchable, self-healable, thermally stable, and transparent ionic conductors for actuators and sensors. Adv. Mater. 32, 1906679 (2020). \n55. Ren, Y. et al. Ionic liquid–based click-ionogels. Sci. Adv. 5, eaax0648 (2019). \n56. Yiming, B. et al. A mechanically robust and versatile liquid-free ionic conductive elastomer. Adv. Mater. 33, 2006111 (2021). \n\n# Acknowledgements \n\nWe gratefully acknowledge the financial support from the National Science Foundation of China (NSFC) (Nos. 21991123, 51873035, and 51733003), and “Qimingxing Plan” (19QA1400200). We also thank the staff from BL16B beamline at Shanghai Synchrotron Radiation Facility for assistance during data collection, and Dr. Peng Wei of Donghua University to support the cytotoxicity assay. \n\n# Author contributions \n\nW.Z. carried out most experiments and co-wrote the manuscript. S.S. and P.W. supervised the project and co-wrote the manuscript. B.W. performed SAXS analysis. All authors discussed the results and revised the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-24382-4. \n\nCorrespondence and requests for materials should be addressed to S.S. or P.W. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. \n\n# Reprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1038_s41586-022-05304-w", + "DOI": "10.1038/s41586-022-05304-w", + "DOI Link": "http://dx.doi.org/10.1038/s41586-022-05304-w", + "Relative Dir Path": "mds/10.1038_s41586-022-05304-w", + "Article Title": "Ultra-bright, efficient and stable perovskite light-emitting diodes", + "Authors": "Kim, JS; Heo, JM; Park, GS; Woo, SJ; Cho, C; Yun, HJ; Kim, DH; Park, J; Lee, SC; Park, SH; Yoon, E; Greenham, NC; Lee, TW", + "Source Title": "NATURE", + "Abstract": "Metal halide perovskites are attracting a lot of attention as next-generation lighte-mitting materials owing to their excellent emission properties, with narrow band emission(1-4). However, perovskite light-emitting diodes (PeLEDs), irrespective of their material type (polycrystals or nullocrystals), have not realized high luminullce, high efficiency and long lifetime simultaneously, as they are influenced by intrinsic limitations related to the trade-off of properties between charge transport and confinement in each type of perovskite material(5-8). Here, we report an ultra-bright, efficient and stable PeLED made of core/shell perovskite nullocrystals with a size of approximately 10 nm, obtained using a simple in situ reaction of benzylphosphonic acid (BPA) additive with three-dimensional (3D) polycrystalline perovskite films, without separate synthesis processes. During the reaction, large 3D crystals are split into nullocrystals and the BPA surroundsthe nullocrystals, achieving strong carrier confinement. The BPA shell passivates the undercoordinated lead atoms by forming covalent bonds, and there by greatly reduces the trap density while maintaining good charge-transport properties for the 3D perovskites. We demonstrate simultaneously efficient, bright and stable PeLEDs that have a maximum brightness of approximately 470,000 cd m(-2), maximum external quantum efficiency of 28.9% (average = 25.2 +/- 1.6% over 40 devices), maximum current efficiency of 151 cd A(-1) and half-lifetime of 520 hat 1,000 cd m(-)(2) (estimated half-lifetime >30,000 h at 100 cd m(-2)). Our work sheds light on the possibility that PeLEDs can be commercialized in the future display industry.", + "Times Cited, WoS Core": 594, + "Times Cited, All Databases": 622, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000880580300011", + "Markdown": "# Article \n\n# Ultra-bright, efficient and stable perovskite light-emitting diodes \n\nhttps://doi.org/10.1038/s41586-022-05304-w \n\nReceived: 19 August 2021 \n\nAccepted: 1 September 2022 \n\nPublished online: 9 November 2022 Check for updates \n\nJoo Sung Kim1,9, Jung-Min Heo1,9, Gyeong-Su Park1,2,3, Seung-Je Woo1, Changsoon Cho4, Hyung Joong Yun5, Dong-Hyeok Kim1, Jinwoo Park1, Seung-Chul Lee6,7, Sang-Hwan Park1, Eojin Yoon1, Neil C. Greenham4 & Tae-Woo Lee1,2,7,8 ✉ \n\nMetal halide perovskites are attracting a lot of attention as next-generation lightemitting materials owing to their excellent emission properties, with narrow band emission1–4. However, perovskite light-emitting diodes (PeLEDs), irrespective of their material type (polycrystals or nanocrystals), have not realized high luminance, high efficiency and long lifetime simultaneously, as they are influenced by intrinsic limitations related to the trade-off of properties between charge transport and confinement in each type of perovskite material5–8. Here, we report an ultra-bright, efficient and stable PeLED made of core/shell perovskite nanocrystals with a size of approximately $10\\mathsf{n m}$ , obtained using a simple in situ reaction of benzylphosphonic acid (BPA) additive with three-dimensional (3D) polycrystalline perovskite films, without separate synthesis processes. During the reaction, large 3D crystals are split into nanocrystals and the BPA surrounds the nanocrystals, achieving strong carrier confinement. The BPA shell passivates the undercoordinated lead atoms by forming covalent bonds, and thereby greatly reduces the trap density while maintaining good charge-transport properties for the 3D perovskites. We demonstrate simultaneously efficient, bright and stable PeLEDs that have a maximum brightness of approximately $470,000{\\mathrm{cd}}{\\mathrm{m}}^{-2}$ , maximum external quantum efficiency of $28.9\\%$ (average $=25.2\\pm1.6\\%$ over 40 devices), maximum current efficiency of 151 cd $\\mathbf{A}^{-1}$ and half-lifetime of $520\\mathsf{h}$ at $1,000{\\mathsf{c d}}{\\mathsf{m}}^{-2}$ (estimated half-lifetime ${>}30,000{\\mathrm{h}}$ at $100\\c{\\mathrm{cd}}\\mathrm{m}^{-2},$ ). Our work sheds light on the possibility that PeLEDs can be commercialized in the future display industry. \n\nMetal halide perovskites (MHPs) are being studied as promising candidates for light emitters because of their narrow emission spectra (full-width at half-maximum $\\approx20\\:\\mathrm{nm}\\mathrm{.}$ ), easy colour tuning, excellent charge-transport properties and low-cost solution processability1–4. Because of these advantages, research has mainly focused on achieving highly efficient operation of perovskite light-emitting diodes (PeLEDs). By introducing a perovskite nanocrystal (NC) structure colloidally synthesized with organic ligands or cation alloying (for example, $\\mathbf{FA_{x}G A_{1-x}P b B r_{3}})$ , a high current efficiency of 108 cd $\\mathbf{A}^{-1}$ and external quantum efficiency (EQE) of $23.4\\%$ have been achieved, by realizing strong carrier confinement and bulk/surface defect suppression3,5–12. However, in these perovskite nanocrystal (PeNC) emitters, the insulating characteristics of the organic ligands can impede charge injection and transport, and thereby limit the brightness and the operational lifetime despite their high luminous efficiency8,13–15. By contrast, three-dimensional (3D) polycrystalline perovskite (hereafter, 3D perovskite) film without such organic ligands has good charge-transport characteristics and simple fabrication processes (maximum luminance $>100,000\\mathrm{cd}\\mathrm{m}^{-2}$ , device half-lifetime $(T_{50}){>}200\\mathsf{h}$ at initial brightness of $100\\mathsf{c d}\\mathsf{m}^{-2}.$ ), but suffers from low luminous efficiency because of the poor charge confinement effect in the big grains of $>100\\mathsf{n m}$ , and non-radiative recombination defects at the grain boundary16–20. Although improvements in both perovskite nanocrystals and 3D perovskites have enabled far-reaching advances in the EQE of PeLEDs, owing to the inevitable trade-off between the charge confinement and charge transport, state-of-the-art efficient PeLEDs, with a maximum EQE $>20\\%$ , mostly suffer from low brightness (about $10,000\\mathrm{cd}\\mathrm{m}^{-2})^{7,10,15}$ and short $T_{50}$ ( $<\\mathsf{100h}$ at initial brightness of $100\\mathrm{cd}\\mathsf{m}^{-2})^{10}$ . Therefore, developing a perovskite material system that enables high brightness, high efficiency and long device lifetime simultaneously is of great importance at the current stage of research on PeLEDs. \n\nHere, we developed a simple method to produce in situ-formed core/ shell NCs (hereafter, in situ core/shell) by reacting 3D perovskite films with benzylphosphonic acid (BPA), which can split large crystals into PeNCs and surround them to form a PeNC@BPA composite, in which BPA exists as an organic shell material21. The significantly reduced particle size of in situ core/shell perovskites $(10\\pm2\\mathsf{n m})$ compared with that of the 3D perovskites $(205\\pm97{\\mathsf{n m}},$ showed significantly improved carrier confinement, and the phosphonate group of BPA effectively passivated the defect sites by binding covalently to undercoordinated $\\mathsf{P b}^{2+}$ . In the in situ core/shell perovskites, the trap density was greatly decreased and the radiative recombination efficiency was significantly increased compared to the 3D perovskites. PeLEDs based on the in situ core/shell structure showed a maximum current efficiency of 151 cd $\\mathbf{A}^{-1}$ (maximum EQE of $28.9\\%$ ), maximum brightness of approximately 470,000 cd $\\mathfrak{m}^{-2}$ , very little efficiency roll-off (about $5\\%$ even at 400,000 cd $\\mathfrak{m}^{-2}$ ) and half-lifetime of 520 h at an initial brightness of 1,000 cd $\\mathfrak{m}^{-2}$ (estimated half-lifetime ${>}30{,}000$ h at $100\\mathsf{c d}\\mathsf{m}^{-2},$ with green emission at the electroluminescence peak of $540\\mathsf{n m}$ , and therefore shows excellent efficiency, luminance and lifetime simultaneously. \n\n![](images/59ce5af10d98d2eb757967f42f4b70a5229c24d0406f4570ff3ba59b90db2785.jpg) \nFig. 1 | Emergence of in situ core/shell perovskite with BPA treatment. a, Schematic illustration of the transformation process of 3D (left) into in situ particle (middle) and in situ core/shell (right) structures by BPA treatment. FA, formamidinium; GA, guanidinium; MA, methylammonium. b–e, TEM images of perovskite nanograins during in situ core/shell synthesis with reaction times of 1 s (b), 10 s (c), 20 s (d) and 30 s (e). (Insets: low-magnification TEM images.) f–h, High-resolution TEM images of the boxed regions in b–d. (Insets: fast Fourier transform diffractograms showing the cubic lattice structure; ZA, zone axis). i, High-resolution HAADF-STEM image of the single \nin situ core/shell perovskite particle taken from the boxed region in e, showing a flat interface between the perovskite core and the BPA shell. j, Atomically resolved HAADF-STEM image of the core region taken from the in situ core/ shell perovskite particle with atomic structure model, showing the perfect 3D perovskite crystal structure. k, High-resolution STEM image focusing on the surface region of in situ core/shell perovskite particle. l, The EEL spectra acquired from positions A and B highlighted in k. The Si peak is a background signal from the silicon nitride TEM window grid (a.u., arbitrary unit). \n\n# Article \n\n![](images/3ae3065600c4b4bc085bf8bc89d833c3aaf9b64466d0cb85492260684f4f4d1a.jpg) \nFig. 2 | Surface passivation of BPA ligand. a–c, O 1s XPS core-level spectra of BPA (a), in situ particle perovskite (b) and in situ core/shell perovskite (c). d, Energy level diagram of the pristine 3D, in situ particle, in situ core/shell perovskites obtained from parameters derived from UPS spectra. $(E_{\\mathrm{VAC}}.$ , vacuum level; $E_{\\mathrm{{F}}},$ Fermi level). \n\n# In situ nanostructure formation by BPA treatment \n\nWe first show how posttreatment using BPA forms the in situ nanostructure of the perovskite crystal. 3D perovskite film of $(\\mathrm{FA}_{0.7}\\mathrm{MA}_{0.1}$ $\\mathbf{GA}_{0.2})_{0.87}\\mathbf{Cs}_{0.13}\\mathbf{Pb}\\mathbf{B}\\mathbf{r}_{3}$ was fabricated (Fig. 1a, left) using the additive-based nanocrystal pinning (A-NCP) method3. In this case, ionic defects with low formation energy exist on the crystal surface and inside the crystal, acting as a cause of ion migration and carrier trapping, thereby significantly reducing the luminescence efficiency and operational stability19. First, we added BPA as an additive into the precursor solution, implementing an in situ particle structure in which BPA covers the surface of crystals by attaching as a ligand to the undercoordinated Pb on the surface of 3D perovskites (Fig. 1a, centre). The surface of the 3D perovskite film initially had an irregular shape due to a defective surface; after addition of up to $10\\mathrm{mol\\%}$ of BPA into the precursor, the fabricated film developed a very clear cubic structure as the BPA molecules assembled on the surface (Extended Data Fig. 1). \n\nThe perovskite thin film was further exposed to a BPA solution in tetrahydrofuran (THF), forming in situ core/shell perovskite (Fig. 1a, right). Unlike other long alkyl ligands (for example, oleic acid, decylamine and octylphosphonate), small BPA molecules with strong acidity can penetrate and intercalate into large perovskite crystals22. After sufficient time for the BPA to intercalate into the crystal, BPA binds to the surface sites within the crystal and splits the large crystal domain into a nanosized in situ core/shell structure that is surrounded by BPA. \n\nThe progressive particle refinement of large 3D perovskite grains (polycrystalline grains) to in situ core/shell perovskite (nanocrystal particle) was observed by high-resolution transmission electron microscopy (TEM). With increasing reaction time in BPA–THF solution, initially rectangular 3D crystals with a size of $200\\mathsf{n m}$ showed gradual change in grain shape and decrease in grain size, and finally become spherical in situ core/shell structured nanograins with a size of $10\\:\\mathrm{nm}$ (Fig. 1b–i). The in situ core/shell synthesis process was further confirmed using atomic-scale scanning transmission electron microscopy (STEM) and scanning electron microscopy (SEM). At the beginning of the reaction, BPA molecules bind to defective surfaces of large crystals, which appear as dark contrast regions or vague boundaries on the STEM images, cracking the crystal out and thus reducing the grain size (Extended Data Fig. 2a–c). The grain splitting reveals new defective surfaces, the cycle of BPA binding and breakage is repeated and the grain size gradually decreases with increased coverage of a BPA shell on the surface (Extended Data Fig. 2d–g). Finally, when BPA molecules fully surround the 3D core, which then lacks a defective surface to which BPA can bind, the in situ core/shell structure is achieved (Fig. 1e,i). A perfect 3D lattice structure in the core part and a clear core/shell interface between perovskite and BPA molecule were identified by STEM image and electron energy loss spectra (EELS) (Fig. 1j–l and Extended Data Fig. 3). When the in situ core/shell synthesis was finished, these in situ core/shell grains were located adjacent to each other, after being aggregated by the excess BPA molecules around them, to form macroparticles, as observed in SEM and TEM images and energy dispersive spectroscopy (EDS) maps (Extended Data Figs. 4 and 5). The grain size distribution of these perovskite grains significantly decreased from the 3D perovskite $(205\\pm97{\\mathsf{n m}},$ ) to the in situ particle structure $(123\\pm34\\mathrm{nm})$ and further to the in situ core/shell structure $(10\\pm2\\mathsf{n m})$ (Supplementary Data Fig. 1). \n\n# Surface passivation of the BPA shell \n\nTo elucidate the mode of binding between BPA and the perovskite structure, we performed X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS) analysis. The existence of BPA in perovskite films can be confirmed by the emergence of new peaks in the P $2p$ and O 1s spectra only in the in situ particle and in situ core/shell perovskites (Supplementary Fig. 2a,b). The O 1s spectrum of the BPA before any reaction shows the main oxygen peak from the P–OH group at $_{533.0\\mathrm{eV}}$ and the $\\scriptstyle\\mathbf{P=O}$ group at $531.5\\mathrm{eV}$ in a ratio of 2:1, which is consistent with previously reported O 1s spectra of phosphonic acid derivatives (Fig. 2a)23,24. By contrast, in the O 1s peak of in situ particles and in situ core/shell perovskites a new peak around 531.0 eV appeared (Fig. 2b,c). This change can be ascribed to the formation of covalent bonds during adsorption of phosphonate onto a metallic surface23,25; that is, BPA bonds to the surface of perovskites by forming a new Pb–O–P covalent bond and replaces the bromide vacancy site. In addition, the Pb 4f peak and the Br 3d peak of the BPA-induced structures are shifted to higher binding energy than in the 3D perovskite structure. This difference can be attributed to the higher electronegativity of oxygen atoms compared with that of bromines, and therefore modification of the Fermi level (Supplementary Fig. 2c,d). This was also confirmed by UPS analysis, which showed that the in situ particle and in situ core/ shell perovskite have much lower work functions (4.6eV and 4.00eV, respectively) and higher energy offsets between the work function and valence band (Supplementary Fig. 3 and Fig. 2d). This difference can arise from the gradually diminishing self-p-doping effect caused by ionic defects at the surface and within the crystal in 3D perovskite and in situ particle perovskite, which was suppressed in the in situ core/ shell perovskite. \n\n![](images/bd1bfc7f150512b7866e1f3f31934843c1774b7acd8857538e7e4f4760bb9d6a.jpg) \nFig. 3 | Luminescent property and defect passivation with BPA treatment. were magnified ten times. ${\\pmb{c}}\\mathrm{-}{\\pmb{e}}$ , Two-dimensional (2D) map of temperaturea,b, Steady-state PL spectra (a) and PL lifetime curves (b) of glass/BufHIL/ dependent PL spectra of 3D (c), in situ particle (d) and in situ core/shell perovskite thin films that used 3D, in situ particle and in situ core/shell perovskite film (e) (normalized to peak value). structure. For comparison, PL intensity of 3D and in situ particle perovskites in a \n\n# Improvement in emission characteristics and defect passivation \n\nWe analysed the luminescence properties by conducting photoluminescence quantum efficiency (PLQE) analysis. Although perovskite thin films based on 3D and in situ particle structures showed comparably low internal quantum efficiencies (IQE) of $30\\%$ and $35\\%$ , respectively, in situ core/shell perovskite film showed a much higher IQE of $88\\%$ (Extended Data Fig. 6a–c). Steady-state photoluminescence (PL) spectra and time-correlated single photon counting (TCSPC) measurements also confirmed higher PL intensity and longer PL lifetimes in the in situ core/shell structure compared to the 3D and in situ particle perovskites (Fig. 3a,b). This great improvement in IQE can be realized by reducing the particle size to strengthen charge confinement and defect density by passivating defects, that is, undercoordinated Pb atoms and halide vacancies, which act as non-radiative recombination centres in the perovskite emitter. The improved charge confinement was confirmed by temperature-dependent PL analysis (Fig. 3c–e and Extended Data Fig. 6d–i). From 3D to in situ particle and in situ core/shell structures, the peak centre was blue-shifted, and the exciton binding energy $(E_{\\mathrm{{b}}})$ was increased from 90 meV to 220 meV; this change indicates that the in situ core/shell structure experiences a strong confinement effect from the grain size reduction. \n\nTo further confirm the passivation effect of the BPA-induced nanostructure, we performed trap-density analysis by fabricating a hole-only device and analysing the transport characteristics (Supplementary Fig. 4). The current–voltage $(\\boldsymbol{\\mathsf{I}}-\\boldsymbol{\\mathsf{V}})$ characteristics of these hole-only devices can be classified into three types of region, according to the slope $(k)$ : ohmic region $(k=1)$ in the low-injection regime, a trap-filled limited (TFL) region $(k>3)$ and a space-charge limited current (SCLC) regime $(k=2)^{26}$ . In this way, the total trap state density inside the perovskite film can be calculated as follows: \n\n$$\nn_{\\mathrm{t}}{=}2\\varepsilon\\varepsilon_{0}V_{\\mathrm{TFL}}/(e L^{2})\n$$ \n\nwhere $n_{\\mathrm{t}}$ is the trap state density, $V_{\\mathrm{TFL}}$ is the trap-filled limit voltage, L is the thickness of the perovskites, $e$ is the elementary charge, $\\scriptstyle{\\varepsilon_{0}}$ and $\\varepsilon$ are the vacuum permittivity and relative permittivity, respectively. By \n\n# Article \n\n![](images/e1c6643213f3e2677823ed8af34068b4d12009c463a187ddbb98578203744497.jpg) \nFig. 4 | EL characteristics of PeLEDs with BPA treatment. a, Schematics of energy diagram of PeLEDs. b, Luminance versus voltage. c, EQE versus luminance. d, EQE histogram of PeLEDs (40 devices each). e, Summary of the reported green PeLEDs characteristics on the basis of maximum EQE and luminance. f, Photograph of operating large-area device (pixel size: $120\\mathrm{mm}^{2},$ ). g, Luminance versus time of \nPeLEDs on the basis of in situ core/shell perovskites at various initial brightness. h, Half-lifetime versus brightness from accelerated lifetime test of in situ core/shell PeLEDs. The open circle is the extrapolated half-lifetime for initial brightness of $100\\mathsf{c d}\\mathsf{m}^{-2}$ . i, Summary of the reported PeLED characteristics on the basis of maximum EQE and estimated or measured half-lifetime at $100\\mathsf{c d}\\mathsf{m}^{-2}$ . \n\nestimating $V_{\\mathrm{{TFL}}}$ as the intersection between the ohmic region and TFL region, we calculate $n_{\\mathrm{t}}{=}3.50\\times10^{16}\\mathrm{cm}^{-3}$ for 3D, $n_{\\mathrm{t}}{=}2.36\\times10^{16}\\mathrm{cm}^{-3}$ for in situ particle and $n_{\\mathrm{t}}{=}1.37\\times10^{16}\\mathrm{cm}^{-3}$ for in situ core/shell perovskites. This result is evidence that the passivation effect of the BPA-induced nanostructure in perovskite films also contributes to the increased luminescence efficiency. We also calculated the hole mobility $(\\mu_{\\mathrm{h}})$ of each device by applying the Mott–Gurney law equation in the Child region of trap-free SCLC transport, as below. \n\n$$\n\\mu_{\\mathrm{h}}=\\frac{8L^{3}J}{9\\varepsilon\\varepsilon_{0}V^{2}}\n$$ \n\nHere, $J$ is the current density and V is the voltage. All devices had similar $\\mu_{\\mathrm{h}}$ values: $3.26\\times10^{-2}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ with 3D, $3.08\\times10^{-2}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ with in situ particle and $2.99\\times10^{-2}{\\bf c m}^{2}{\\bf V}^{-1}{\\bf s}^{-1}.$ with in situ core/shell perovskites. This result indicates that the fast charge-transport property in 3D perovskites could be preserved in the in situ core/shell structure because excessive insulating ligand was not used. \n\n# Light-emitting diode performance \n\nEncouraged by the simultaneously increased PL efficiency, decreased trap density and preserved fast charge transport, we fabricated LEDs based on the BPA-induced nanostructured perovskites (Fig. 4a and Supplementary Fig. 5). The PeLEDs based on in situ core/shell perovskites showed a maximum current efficiency of 151 cd $\\mathbf{A}^{-1}$ and maximum EQE of $28.9\\%$ , calculated using the full angular electroluminescence distribution (Fig. 4b,c and Extended Data Fig. $7{\\bf a}-{\\bf g})^{27}$ . In contrast to many previously reported organic LEDs (OLEDs) and PeLEDs that have ultrathin emission layers (EMLs) $(<50\\mathsf{n m})$ , this is a remarkably high EQE, with an EML $>200$ nm in devices in which the microcavity effects are diluted. The result emphasizes the important role of the photon recycling effect in thick EMLs28–31. Optical simulation verified that our PeLEDs can reach an EQE of $29.2\\%$ with the aid of the photon recycling effect (Supplementary Fig. 6). The detailed current–voltage–luminance characteristics are summarized in Extended Data Table 1. Also, the distribution of EQE and luminance obtained from 40 devices showed great reproducibility (Fig. 4d and Extended Data Fig. 7h). In particular, to manufacture efficient in situ core/shell PeLEDs with great reproducibility, the crystallization process of the as-synthesized perovskite thin films must be controlled so that the grain size does not increase too much before the in situ reaction with BPA. When the A-NCP timing is not delayed and the processing temperature is kept at ${<}18^{\\circ}\\mathrm{C}$ , the grain size can be sufficiently small $\\scriptstyle\\left(<100\\mathsf{n m}\\right)$ , so that BPA can completely penetrate the grains during the reaction, and thereby provide nanostructures that are favourable for obtaining high-efficiency devices (Extended Data Fig. 7i). The PeLEDs showed high maximum brightness of $473,990{\\mathrm{cd}}{\\mathrm{m}}^{-2}$ , whereas 3D PeLEDs and in situ particle PeLEDs showed a maximum brightness of only 20,271 cd $\\mathfrak{m}^{-2}$ and 149,331 cd $\\mathfrak{m}^{-2}$ , respectively. The maximum brightness of in situ core/shell PeLEDs is the highest so far reported among PeLEDs based on any of the 3D, quasi-2D or colloidal NC structures, and is even comparable with the highest brightness of state-of-the-art inorganic quantum dot LEDs (334,000 $\\mathsf{c d}\\mathsf{m}^{-2})$ (Fig. 4e)32. Furthermore, owing to the fast charge transport with high IQE, we could realize an ultralow driving voltage of 2.7 V at a brightness of 10,000 cd $\\mathfrak{m}^{-2}$ , which is much lower than the driving voltage of any other state-of-the-art LEDs based on quasi-2D (4.7 V), PeNC (6 V) or organic Ir $\\left(\\mathsf{p p y}_{2}\\right.$ (acac) (4.8 V) structures (Supplementary Table 1). In situ core/shell PeLEDs also maintained an EQE value of $220\\%$ under ultra-high brightness conditions from 50, $000{\\mathrm{cd}}{\\mathrm{m}}^{-2}{\\mathrm{to}}400,000{\\mathrm{cd}}{\\mathrm{m}}$ $\\mathfrak{m}^{-2}$ , and exhibited very low roll-off of about $5\\%$ at a luminance of 400,000 cd $\\mathfrak{m}^{-2}$ (Supplementary Table 2). These results are remarkable considering that reported high-efficiency nanocrystal PeLEDs with EQE $>20\\%$ have low brightness (approximately $10,000{\\mathsf{c d}}{\\mathsf{m}}^{-2},$ and large efficiency roll-off 1 $550\\%$ at $>10,000\\mathsf{c d m}^{-2}.$ ), because they use insulating ligands and therefore have a thickness of emitting layer that is mostly $<30\\mathsf{n m}$ , to compensate for the poor charge-transporting characteristics and to strengthen light outcoupling from the device (Fig. 4e). By contrast, these in situ core/shell perovskites are formed by in situ treatment of 3D perovskites without long insulating ligands, so both high efficiency and high brightness can be realized without significantly sacrificing charge transport, which in turn results in low-efficiency roll-off because of better charge balance with higher charge transport and thus no severe charge accumulation. We also fabricated bright large-area PeLEDs (pixel size: $120\\mathrm{mm}^{2},$ ) based on these in situ core/shell structures. These PeLEDs had high uniformity and maximum EQE of $22.5\\%$ ; these results show the potential of hybrid perovskite emitters for use in solid-state lighting and display applications (Fig. 4f and Extended Data Fig. 8)33. \n\nFinally, the operational lifetimes of the PeLEDs were analysed by applying a constant current and monitoring the luminance. Compared with the $T_{50}$ of 3D (0.2 h) and in situ particle (3.5 h) PeLEDs at initial brightness $(L_{0})=10,000{\\mathrm{cd}}{\\mathrm{m}}^{-2}$ , in situ core/shell PeLEDs showed a much longer $T_{50}0\\mathsf{f}14\\mathsf{h}$ , due to greatly improved luminescent efficiency without sacrifice of charge-transport properties (Extended Data Fig. 9). The operational lifetime of in situ core/shell PeLEDs was further measured at various $L_{0}$ from 1,000 cd $\\mathbf{m}^{-2}$ to 200,000 cd $\\mathfrak{m}^{-2}$ (Fig. $4\\mathrm{g-h})$ . Specifically, in situ core/shell PeLEDs showed ultra-long $T_{50}$ of 520 h at $1,000{\\mathsf{c d}}{\\mathsf{m}}^{-2}$ . By using the accelerated lifetime equation $(L_{0}^{n}T_{50}{=}{\\bf c o n}{.}$ stant, where n is an acceleration factor) $^{34,35}$ with $n{=}1.68$ over 21 devices, we estimated the $T_{50}$ of the device at 100 cd $\\mathfrak{m}^{-2}$ to be 31,808 h, which is, to our knowledge, the highest $T_{50}$ estimated so far in PeLEDs (Fig. 4h,i and Supplementary Table 3). \n\n# Conclusions \n\nWe demonstrated core/shell perovskite NCs with a size of approximately $10\\mathsf{n m}$ by using the in situ reaction of BPA with 3D perovskite thin films. In the reaction process, BPA molecules penetrated into large 3D perovskite crystals and split them into nanosized crystals, thus surrounding the BPA with a core/shell structure. This in situ core/ shell structure enabled increased carrier confinement, reduction in trap density and increase in luminous efficiency without sacrificing the charge-transport properties of 3D perovskites. As a result, simultaneously ultra-bright, efficient and stable PeLEDs with a maximum current efficiency of 151 cd $\\mathbf{A}^{-1}$ (maximum EQE of $28.9\\%$ , maximum luminance of approximately $470,000{\\mathrm{cd}}{\\mathrm{m}}^{-2}$ , very low-efficiency roll-off of about $5\\%$ at 400,000 cd $\\mathfrak{m}^{-2}$ and half-lifetime of 520 h at initial brightness of 1,000 cd $\\mathfrak{m}^{-2}$ (estimated half-lifetime ${>}30{,}000{\\ i}$ h at $100\\mathsf{c d}\\mathsf{m}^{-2},$ were demonstrated. These results suggest that PeLEDs are not only laboratory-level high-efficiency devices, but also promising candidates for commercial self-emissive displays and lighting applications that require ultra-high brightness and long operational lifetimes, comparable to those of state-of-the-art OLEDs or quantum dot LEDs. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-022-05304-w. \n\n1. Kim, Y.-H. et al. Multicolored organic/inorganic hybrid perovskite light-emitting diodes. Adv. Mater. 27, 1248–1254 (2015). \n2. Tan, Z.-K. et al. Bright light-emitting diodes based on organometal halide perovskite. Nat. Nanotechnol. 9, 687–692 (2014). \n3. Cho, H. et al. Overcoming the electroluminescence efficiency limitations of perovskite light-emitting diodes. Science 350, 1222–1225 (2015). \n4. Kim, Y.-H., Cho, H. & Lee, T.-W. Metal halide perovskite light emitters. Proc. Natl Acad. Sci. USA 113, 11694–11702 (2016). \n5. Yang, X. et al. Efficient green light-emitting diodes based on quasi-two-dimensional composition and phase engineered perovskite with surface passivation. Nat. Commun. 9, \n570 (2018). \n6. Zhao, B. et al. High-efficiency perovskite–polymer bulk heterostructure light-emitting diodes. Nat. Photonics 12, 783–789 (2018). \n7. Kim, Y.-H. et al. Comprehensive defect suppression in perovskite nanocrystals for high-efficiency light-emitting diodes. Nat. Photonics 15, 148–155 (2021). \n8. Hassan, Y. et al. Ligand-engineered bandgap stability in mixed-halide perovskite LEDs. Nature 591, 72–77 (2021). \n9. Xiao, Z. et al. Efficient perovskite light-emitting diodes featuring nanometre-sized crystallites. Nat. Photonics 11, 108–115 (2017). \n10. Lin, K. et al. Perovskite light-emitting diodes with external quantum efficiency exceeding \n20 per cent. Nature 562, 245–248 (2018). \n11. Kim, Y.-H., Kim, J. S. & Lee, T. Strategies to improve luminescence efficiency of metal‐ halide perovskites and light‐emitting diodes. Adv. Mater. 31, 1804595 (2019). \n12. Park, M.-H. et al. Boosting efficiency in polycrystalline metal halide perovskite light-emitting diodes. ACS Energy Lett. 4, 1134–1149 (2019). \n13. Cho, H., Kim, Y.-H., Wolf, C., Lee, H.-D. & Lee, T.-W. Improving the stability of metal halide perovskite materials and light-emitting diodes. Adv. Mater. 30, 1704587 (2018). \n14.\t Liu, M., Matuhina, A., Zhang, H. & Vivo, P. Advances in the stability of halide perovskite nanocrystals. Materials 12, 3733 (2019). \n15. Dong, Y. et al. Bipolar-shell resurfacing for blue LEDs based on strongly confined perovskite quantum dots. Nat. Nanotechnol. 15, 668–674 (2020). \n16. Wehrenfennig, C., Eperon, G. E., Johnston, M. B., Snaith, H. J. & Herz, L. M. High charge carrier mobilities and lifetimes in organolead trihalide perovskites. Adv. Mater. 26, \n1584–1589 (2014). \n17.\t Herz, L. M. Charge-carrier mobilities in metal halide perovskites: fundamental mechanisms and limits. ACS Energy Lett. 2, 1539–1548 (2017). \n18.\t Xu, W. et al. Rational molecular passivation for high-performance perovskite light-emitting diodes. Nat. Photonics 13, 418–424 (2019). \n19. Meggiolaro, D., Mosconi, E. & De Angelis, F. Formation of surface defects dominates ion migration in lead-halide perovskites. ACS Energy Lett. 4, 779–785 (2019). \n20.\t Zhang, L. et al. Suppressing ion migration enables stable perovskite light-emitting diodes with all-inorganic strategy. Adv. Funct. Mater. 30, 2001834 (2020). \n21. Ahmed, G. H., Yin, J., Bakr, O. M. & Mohammed, O. F. Successes and challenges of core/shell lead halide perovskite nanocrystals. ACS Energy Lett. 6, 1340–1357 (2021). \n22.\t Park, S. M., Abtahi, A., Boehm, A. M. & Graham, K. R. Surface ligands for methylammonium lead iodide films: surface coverage, energetics, and photovoltaic performance. ACS Energy Lett. 5, 799–806 (2020). \n23.\t Wagstaffe, M. et al. An experimental investigation of the adsorption of a phosphonic acid on the anatase $\\mathsf{T i O}_{2}$ (101) surface. J. Phys. Chem. C 120, 1693–1700 (2016). \n24.\t Li, F., Zhong, H., Zhao, G., Wang, S. & Liu, G. Adsorption of α-hydroxyoctyl phosphonic acid to ilmenite/water interface and its application in flotation. Colloids Surfaces A Physicochem. Eng. Asp. 490, 67–73 (2016). \n25.\t Xuan, T. et al. Highly stable $\\mathsf{C s P b B r}_{3}$ quantum dots coated with alkyl phosphate for white light-emitting diodes. Nanoscale 9, 15286–15290 (2017). \n26.\t Kim, H. et al. Proton-transfer-induced 3D/2D hybrid perovskites suppress ion migration and reduce luminance overshoot. Nat. Commun. 11, 3378 (2020). \n27. Jeong, S.-H. et al. Characterizing the efficiency of perovskite solar cells and light-emitting diodes. Joule 4, 1206–1235 (2020). \n28.\t Pazos-Outon, L. M. et al. Photon recycling in lead iodide perovskite solar cells. Science \n351, 1430–1433 (2016). \n\n# Article \n\n29.\t Stranks, S. D., Hoye, R. L. Z., Di, D., Friend, R. H. & Deschler, F. The physics of light emission in halide perovskite devices. Adv. Mater. 31, 1803336 (2019). \n30.\t Cho, C. et al. The role of photon recycling in perovskite light-emitting diodes. Nat. Commun. 11, 611 (2020). \n31.\t Cho, C. & Greenham, N. C. Computational study of dipole radiation in re‐absorbing perovskite semiconductors for optoelectronics. Adv. Sci. 8, 2003559 (2021). \n32.\t Song, J. et al. Over $30\\%$ external quantum efficiency light‐emitting diodes by engineering quantum dot‐assisted energy level match for hole transport layer. Adv. Funct. Mater. 29, \n1808377 (2019). \n33.\t Kim, Y.-H. et al. Exploiting the full advantages of colloidal perovskite nanocrystals for large-area efficient light-emitting diodes. Nat. Nanotechnol. 17, 590–597 (2022). \n34.\t Dai, X. et al. Solution-processed, high-performance light-emitting diodes based on quantum dots. Nature 515, 96–99 (2014). \n\n35.\t Woo, S.-J., Kim, J. S. & Lee, T.-W. Characterization of stability and challenges to improve lifetime in perovskite LEDs. Nat. Photonics 15, 630–634 (2021). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nSpringer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 \n\n# Methods \n\n# Materials \n\nFormamidinium bromide (FABr, ${\\tt>}99.99\\%$ ), methylammonium bromide (MABr, ${\\tt>}99.99\\%$ ) and guanidinium bromide (GABr, ${\\tt>}99.99\\%$ ) were purchased from Dyesol. Caesium bromide (CsBr), benzylphosphonic acid (BPA, $597\\%$ ), tetrafluoroethylene-perfluoro -3,6-dioxa-4-methyl-7-octene-sulfonic acid copolymer (PFI), chlorobenzene (CB), tetrahydrofuran (THF), and molybdenum oxide $(\\mathsf{M o O}_{3})$ were purchased from Sigma-Aldrich. Lead bromide $(\\mathbf{Pb}\\mathbf{B}\\mathbf{r}_{2}{>}98.0\\%$ (T)) was purchased from TCI. $2,2^{\\prime},2^{\\prime\\prime}$ -(1,3,5-Benzinet riyl)-tris(1-phenyl-1H-benzimidazole) (TPBi) was purchased from OSM. 9,10-Di(naphthalene-2-yl)anthracen-2-yl-(4,1-phenylene) (1-phenyl-1H-benzo[d]imidazole) (ZADN) was purchased from Shinwon Chemtrade. Lithium fluoride (LiF) was supplied by Foosung. Unless otherwise stated, all materials were used without purification. \n\n# Preparation of MHP solution \n\nThe mixed-cation precursor $(\\mathsf{F A}_{0.7}\\mathsf{M A}_{0.1}\\mathsf{G A}_{0.2})_{0.87}\\mathsf{C s}_{0.13}\\mathsf{P b}\\mathsf{B r}_{3})$ was prepared by dissolving stoichiometric ratios of each of FABr, MABr, GABr, CsBr and $\\mathsf{P b B r}_{2}$ (molar ratio $(\\mathrm{FABr+MABr+GABr+CsBr}):\\mathrm{PbBr}_{2}=1.15{\\cdot}1)$ in DMSO at a concentration of 1.2 M (refs. 7,36). In the case of the precursor solution for the in situ particle perovskite, $10\\mathrm{mol\\%}$ of BPA relative to $\\mathsf{P b B r}_{2}$ was added. The solution was stirred overnight in an ${\\sf N}_{2}$ -filled glovebox at room temperature before use. \n\n# Fabrication of PeLEDs \n\nPrepatterned fluorine-doped tin oxide (FTO) $(350\\mathrm{nm},12\\mathrm{-}14\\Omega\\mathrm{sq}^{-1},$ $25\\mathrm{mm}\\times25\\mathrm{mm}$ , Nippon Sheet Glass Co. Ltd.) glasses were sonicated in acetone and 2-propanol for 15 min each sequentially, then boiled in 2-propanol for $30\\mathrm{min}$ . The surface of FTO substrates underwent ultraviolet-ozone treatment to achieve a hydrophilic surface. We used a previously described method to prepare a hole-injection layer (BufHIL) that had a gradient work function, by inducing vertical self-organization of PEDOT:PSS (CLEVIOS P VP AI4083) and PFI copolymer to have surface-enriched PFI buffer layer; the solution with 1:1 weight ratio of PEDOT:PSS to PFI was spin coated to form a $75\\mathsf{n m}$ thickness, then annealed at $150^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ (ref. 1). After baking, the substrates were transferred to an $\\mathsf{N}_{2}$ -filled glovebox for deposition of the MHP layer. MHP films with thicknesses of $270\\ensuremath{\\mathrm{nm}}$ were deposited by spin coating the precursor solution at 6,000 r.p.m. with the A-NCP process3: during the second spin step, TPBi-dissolved CB solution was dropped onto the spinning perovskite film. For synthesis of in situ core/shell perovskite film, BPA dissolved in THF solution was loaded on top of the perovskite, followed by a reaction time of 30 s and direct spin drying afterwards. Samples were then moved to the vacuum chamber $(<10^{-7}$ Torr) to sequentially deposit ZADN $(45\\mathsf{n m})$ , LiF $(1.2\\mathsf{n m})$ and Al $(100\\mathsf{n m})$ . The active area of $4.9\\:\\mathrm{mm}^{2}$ was defined by shadow masking during deposition of the cathode. Finally, the fabricated PeLEDs were encapsulated in a glovebox under a controlled $\\mathsf{N}_{2}$ atmosphere $(0_{2}<10.0$ ppm, ${\\mathsf{H}}_{2}\\mathbf{O}<1.0$ ppm) by using a glass lid and UV-curable epoxy resin with 15 min of UV $(365\\mathsf{n m})$ ) treatment. \n\n# Perovskite film characterization \n\nImages of the surfaces were obtained using a field-emission scanning electron microscope (SUPRA 55VP). XPS and UPS spectra were measured using a photoelectron spectrometer (AXIS-Ultra DLD, Kratos). A monochromatic AlKα line (1,486.6 eV) was used for XPS, and He I radiation (21.2 eV) was used for UPS. Steady-state photoluminescence spectra and ultraviolet–visible (UV–vis) absorption spectra were measured using a JASCO FP8500 spectrofluorometer and Lambda-465 UV–vis spectrophotometer. For transient PL decay measurements, a system composed of a streak camera (c10627, Hamamatsu) and a nitrogen pulse laser (337 nm, $20{\\mathsf{H z}}$ , Usho) was used. PLQY was measured with a PMT and monochromator (Acton Research Corporation) using a $325\\mathsf{n m}$ He:Cd CW laser (Kimmon Koha) at the excitation power of $62.5\\mathsf{m w c m^{-2}}$ . Direct and indirect emission from the perovskite film was measured to determine the accurate PLQY values. For the temperature-dependent PL measurements, the sample was mounted in a cryostat (Advanced Research Systems) under vacuum and the emission spectrum was analysed using a $405\\mathsf{n m}$ laser diode (PicoQuant) at an excitation power of $34\\upmu\\upnu\\mathrm{cm}^{-2}$ . For single-carrier device analysis, $\\mathsf{M o O}_{3}(30\\mathsf{n m})$ and Au ( $\\mathbf{\\bar{50}n m})$ were thermally deposited sequentially onto FTO/ BufHIL/perovskite and encapsulated in an ${\\sf N}_{2}$ atmosphere to obtain the current–voltage curve using a Keithley 236 source measurement unit. \n\n# TEM characterizations \n\nPerovskite thin films were deposited on a 5 nm thick silicon nitride membrane using the same spin-coating conditions as for the actual device. The membrane, with a size of $100\\upmu\\mathrm{m}\\times1,500\\upmu\\mathrm{m}$ , was supported on a $100\\upmu\\mathrm{m}$ thick silicon frame. The silicon nitride membrane grid was loaded on a sample holder for TEM characterization without further processing of the TEM sample preparation. Double Cs-corrected (S) TEM systems (Themis Z, ThermoFisher Scientific) equipped with EELS (Quantum ER965, Gatan) and EDS (Super-X EDS system) were used for atomic-scale structure imaging and chemical analysis of the samples at an accelerating voltage of $200\\mathsf{k V}.$ Due to the electron beam damage of core/shell perovskite nanocrystals by high-energy electron illumination in TEM, we acquired high-resolution TEM images, high-resolution high-angle annular dark field (HAADF)-STEM images, and EELS and EDS data at the low dose rates. Core-loss EELS using a 2 Å nominal probe size and 1.8–2.0 eV energy resolution were obtained with exposures of 12 s (integrated by 60 scans with each taking for 0.2 s). EELS entrance aperture of $\\cdot_{5\\mathsf{m m}}$ , and an energy dispersion of 0.5 eV ch−1 and 1.0 eV ch−1 were used for high-loss EELS (>1,500 eV). \n\n# Characterization of efficiency of PeLEDs \n\nElectroluminescence efficiencies of the fabricated PeLEDs were measured using a Keithley 236 source measurement unit and a Minolta CS-2000 spectroradiometer. EQE of PeLEDs was calculated by measuring full angular electroluminescence distribution27. We cross-checked the accuracy of the analysis by conducting an independent analysis at the University of Cambridge with the same devices, from which we confirmed consistent results (Supplementary Fig. 7). \n\n# Lifetime analysis of PeLEDs \n\nOperational lifetime of PeLEDs was measured under constant-current conditions by simultaneously tracking brightness and applied voltage using an M760 Lifetime Analyzer (McScience) with a control computer under an air-conditioned environment below $18^{\\circ}\\mathsf{C}$ . \n\n# Optical simulation \n\nOutcoupling efficiency, perovskite reabsorption $A_{\\mathrm{{act}}}$ and parasitic absorption $A_{\\mathrm{{para}}}$ were obtained from the calculated Poynting vectors at each interface of glass ${\\mathrm{\\Delta}n=1.5}$ , incoherent)/FTO $(n=1.9,350\\mathrm{nm})/$ BufHIL $(n=1.5,75\\mathrm{{nm})}$ /perovskite/ZADN $(n=2,45\\mathsf{n m})/\\mathrm{L}$ iF $(n=1.4$ , $1.2\\mathsf{n m}$ )/Al (n from ref. 37), by using a recently proposed method30,31 (n is refractive index). The imaginary part of the refractive index spectrum of perovskite was obtained from the measured absorbance, whereas the real part was assumed to be constant $\\langle n_{\\mathrm{perov}}=2.3)$ . The internal radiation spectrum was obtained by the reverse calculation from the measured external radiation spectrum. The maximum EQE values with photon recycling effect were obtained at each perovskite thickness, by integrating the results for dipoles with various wavelengths, orientations (vertical and horizontal), polarizations (s and $p$ ) and positions (20 positions uniformly distributed over the perovskite layer). The relationship between external and internal PLQE was calculated in the same way for the structure of glass/perovskite. \n\n# Article \n\n# Data availability The data that support the findings of this study are available from the corresponding authors upon reasonable request. \n\n36.\t Cho, H. et al. High-efficiency polycrystalline perovskite light-emitting diodes based on mixed cations. ACS Nano 12, 2883–2892 (2018). 37.\t Palik, E. D. & Ghosh, G. Handbook of Optical Constants of Solids (Academic Press, 1998) \n\nAcknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science, ICT and Future Planning) (NRF-2016R1A3B1908431). G.-S.P was supported by the DGIST R&D Program (22-CoE-NT-02) by the Korea government (Ministry of Education and Ministry of Science, ICT and Future Planning). \n\nAuthor contributions J.S.K., J.-M.H. and T.-W.L. initiated and designed the study. J.S.K. and J.-M.H. fabricated LED devices and analysed data. G.-S.P. performed the TEM measurements. \n\nH.J.Y. conducted the UPS and XPS analysis. S.-J.W. and D.-H.K. conducted the temperaturedependent PL and photoluminescence quantum efficiency analysis. S.-J.W. and C.C. conducted the optical simulation of the devices with guidance from N.C.G. J.P. assisted with analysis of the TCSPC data. S.-C.L. provided support for characterization of the materials. S.-H.P. and E.Y. assisted with the fabrication of LED devices. T.-W.L. supervised the work. J.S.K. drafted the first version of the manuscript, with assistance from J.-M.H. and T.-W.L. All authors discussed the results and commented on the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-022-05304-w. \nCorrespondence and requests for materials should be addressed to Joo Sung Kim or Tae-Woo Lee. \nPeer review information Nature thanks Lina Quan, Zhanhua Wei and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/f30bd7036b12ca109de483180e4f78efd6790dd93e6bb4247e97158ddd873781.jpg) \nExtended Data Fig. 1 | Morphology of in situ particle perovskite thin films. SEM images of perovskite thin films made of 1.2M precursor solution with a, $0\\%$ (3D), b, $2.5\\%$ , $\\mathbf{c},5\\%$ , d, $10\\%$ (in situ particle) molar ratio of BPA molecule relative to $\\mathsf{P b B r}_{2}$ . e, HAADF-STEM image and EDS elemental maps of P (green), \nBr (yellow), and Pb (red), respectively. f, HAADF-STEM image and EDS elemental maps of a single perovskite grain showing the uniform dispersion of P (green), Br (yellow), and Pb (red) on the grain. \n\n# Article \n\n![](images/d6af0e5bd672768d6e48fa7c71e10ca4fc16181054c7c1378be7e47b09866a76.jpg) \nExtended Data Fig. 2 | Morphological characterization during in situ core/shell particle synthesis process. a, SEM image of a perovskite thin film (after 1s of reaction time with BPA-THF solution) showing small grains cracked out from large 3D grain. b, STEM image of $50\\mathrm{nm}$ -size perovskite crystal during in situ core/shell synthesis process. Yellow arrows indicate the defective perovskite surfaces that can be bound with BPA. c, HR-TEM image of another perovskite crystal showing ultra-small nanocrystals segregated during \n\nin situ core/shell synthesis process. Insets: Magnified HR-TEM images of ultra-small nanocrystals taken from the white-boxed regions labelled C1 and C2. d, e, High-resolution HAADF-STEM images of single perovskite nanograins with decreasing grain size. Magnified HAADF-STEM images of the grain surfaces (D1, D2, E1, E2, F1, F2, G1, G2) demonstrate that the BPA shell coverages on the grain surfaces gradually increase and the defective surface regions decrease as the grain size decreases. \n\n![](images/8f39ea5dbcaba00bc5f577a13f8083550c10be3c839ada21b499a78efbe1dcee.jpg) \nExtended Data Fig. 3 | Characterization of perovskite/BPA core/shell interface. a, High-resolution HAADF-STEM image of single perovskite grain formed during in situ core/shell synthesis process. b, c, Atomic-scale HAADF-STEM (b) and ABF-STEM (c) images of the boxed area denoted in a. d,e, Magnified HAADF-STEM (d) and ABF-STEM (e) images of the boxed area \nshown in b and c to indicate the positions of EELS acquisition. f, EEL spectra acquired at the atomic positions labelled A, B, and C in d, e. g, EEL spectrum in the energy-loss range of the N-K and O-K edges acquired at the position labelled C. The O-K peak indicates the presence of BPA shells, but N-K peak is simply a background signal from the silicon nitride TEM window grid. \n\n# Article \n\n![](images/b12d6323c61560de58eb31cac72eb77d957fd1921300d5394a69664e90fe5510.jpg) \n\nExtended Data Fig. 4 | SEM image of low-concentration (0.6 M) perovskite thin films with different reaction time between BPA solution and perovskite thin film. a, 3D perovskites without reaction, b, 1 s, c, 15 s, d, 30 s of exposure time to BPA-THF solution before spin-drying. Coloured regions \n\nindicate initial large crystals (red) and split nanograins (green). e, Schematic illustration of the growth process of BPA macroparticle domain and perovskite crystal forming in situ core/shell structure. \n\n![](images/5d10fba4a402673cc57d8ffa877cf34d6027299fcbcaa2a2c01f7f64b0af7438.jpg) \nExtended Data Fig. 5 | HAADF-STEM analysis of  in situ core/shell perovskites. a, TEM image and b, c, magnified HAADF-STEM images of in situ core/shell perovskite thin films. d, HAADF-STEM image of in situ core/ shell grains and EDS elemental maps of P (red), Pb (yellow), and Br (green), \n\nrespectively. The EDS maps clearly show the uniform dispersion of P (red) over macrograins. e, HAADF-STEM image of single macrograins consists of  in situ core/shell nanoparticles. f, EDS spectrum acquired at the location of the red circled region in e. \n\n![](images/dc6b62a9b2fc5244b6f37abb98e8e4fe59d75928d58e2ad9bdabf1ebeae119d2.jpg) \nExtended Data Fig. 6 | Photoluminescence characteristics of perovskite The external PLQE of the in situ core/shell structure was $46\\%$ , which thin films. a, PL spectra and b, normalized PL spectra of quartz/perovskite corresponds to an IQE of $88\\%$ . d–i, Temperature-dependent PL spectrum and thin film measured in integrating sphere. c, External PLQE versus internal corresponding integrated PL intensity with calculated activation energy for: radiation efficiency $(\\eta_{\\mathrm{rad}})$ (i.e. internal quantum efficiency, IQE) of perovskite d,g, 3D, e,h, in situ particle, f,i, in situ core-shell perovskite thin films. film calculated considering the influence of perovskite reabsorption30,31. \n\n![](images/821452bae22a23a1681f74b4a8abdfc6cca24a407ac264efd0988c9362fdc991.jpg) \nExtended Data Fig. 7 | Current-voltage-luminance characteristics of PeLEDs. a, Current density versus voltage; b, luminance versus current density; c, normalized EL spectra; d, CIE coordinate of in situ core/shell PeLEDs; e, power efficiency versus luminance; f, current efficiency versus luminance of PeLEDs based on 3D, in situ particle, in situ core/shell structure. g, Angle-dependent EL intensity and h, luminance histogram of PeLEDs based on in situ core/shell \nstructure. i, EQE histogram of the PeLEDs based on in situ core/shell structure with different processing condition. As the temperature of the glove box increases or the A-NCP process is delayed, the grain size of the spin-coated perovskite thin film increases, which slows the penetration of the BPA solution into perovskite crystal and prevents full conversion of them into the in situ core/shell structure. \n\n![](images/19ecc0499521d1da1798e4da93b2d8304d7277ff9e6b37bdf0f4a9e3878e3324.jpg) \nExtended Data Fig. 8 | Large-area devices. a, Luminance versus voltage; b, EQE versus current density of large-area devices based on in situ core/shell perovskites. c–f, Photographs of large-area devices (pixel size: $120\\mathrm{mm}^{2}.$ ) \noperating at: c, < 10 cd m−2; d, 1,000 cd m−2; e, 100,000 cd m−2; and f, 100,000 cd m−2 under daylight, showing uniform emission over the pixel. \n\n![](images/65e1e6bd57ad11a3fb0d2725bad9ad766c89c94c016a0d0f610b5a417489998c.jpg) \nExtended Data Fig. 9 | Operational lifetime of PeLEDs. a, Luminance versus time of PeLEDs based on 3D, in situ particle, and in situ core/shell perovskites at initial brightness of $10,000{\\mathsf{c d}}{\\mathsf{m}}^{-2}$ , and b, corresponding driving voltage versus operation time. \n\n# Article \n\n
Extended Data Table1| Summarized electrical and luminance characteristics of PeLEDs
PerovskiteVturn-on at 1 cd m-²Lmax (cd m-2) (at bias (V))EQEmax (%) (at bias (V))CEmax (cd A-1) (at bias (V))PEmax (lm W-1) (at bias (V))
3D2.3120,271 (4.1)3.66 (3.2)22.41 (3.2)19.8 (3.2)
In situ particle2.31149,331 (5.0)8.29 (4.1)41.05 (4.4)27.2 (4.1)
In situ core/shell2.22473,990(5.0)28.9(4.1)151.1(4.1)112.8 (3.5)
\n\n$\\mathsf{V}_{\\mathsf{t u r n-o n}}$ : Voltage at luminance of 1 cd $\\mathsf{m}^{-2}$ , $L_{\\mathrm{max}}\\mathrm{.}$ : maximum luminance, $E Q E_{\\operatorname*{max}}$ : maximum EQE, $C E_{\\mathrm{{max}}}$ : maximum current efficiency. " + }, + { + "id": "10.1038_s41467-021-24529-3", + "DOI": "10.1038/s41467-021-24529-3", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-24529-3", + "Relative Dir Path": "mds/10.1038_s41467-021-24529-3", + "Article Title": "Energy-saving hydrogen production by chlorine-free hybrid seawater splitting coupling hydrazine degradation", + "Authors": "Sun, F; Qin, JS; Wang, ZY; Yu, MZ; Wu, XH; Sun, XM; Qiu, JS", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Seawater electrolysis represents a potential solution to grid-scale production of carbon-neutral hydrogen energy without reliance on freshwater. However, it is challenged by high energy costs and detrimental chlorine chemistry in complex chemical environments. Here we demonstrate chlorine-free hydrogen production by hybrid seawater splitting coupling hydrazine degradation. It yields hydrogen at a rate of 9.2 mol h(-1) g(cat)(-1) on NiCo/MXene-based electrodes with a low electricity expense of 2.75 kWh per m(3) H-2 at 500 mA cm(-2) and 48% lower energy equivalent input relative to commercial alkaline water electrolysis. Chlorine electrochemistry is avoided by low cell voltages without anode protection regardless Cl- crossover. This electrolyzer meanwhile enables fast hydrazine degradation to similar to 3 ppb residual. Self-powered hybrid seawater electrolysis is realized by integrating low-voltage direct hydrazine fuel cells or solar cells. These findings enable further opportunities for efficient conversion of ocean resources to hydrogen fuel while removing harmful pollutants.", + "Times Cited, WoS Core": 397, + "Times Cited, All Databases": 410, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000687325900025", + "Markdown": "# Energy-saving hydrogen production by chlorinefree hybrid seawater splitting coupling hydrazine degradation \n\n${\\mathsf{F u}}{\\mathsf{S u n}}^{1},$ , Jingshan Qin2, Zhiyu Wang 1✉, Mengzhou $\\mathsf{Y u}^{3}$ , Xianhong Wu1, Xiaoming Sun2✉ & Jieshan Qiu 1,4✉ \n\nSeawater electrolysis represents a potential solution to grid-scale production of carbonneutral hydrogen energy without reliance on freshwater. However, it is challenged by high energy costs and detrimental chlorine chemistry in complex chemical environments. Here we demonstrate chlorine-free hydrogen production by hybrid seawater splitting coupling hydrazine degradation. It yields hydrogen at a rate of $9.2\\:\\mathrm{mol}\\:\\mathsf{h}^{-1}\\:\\:\\mathsf{g}_{\\mathsf{c a t}}{}^{-1}$ on NiCo/MXenebased electrodes with a low electricity expense of $2.75\\mathrm{~kWh}$ per $\\mathsf{m}^{3}\\mathsf{H}_{2}$ at $500\\mathsf{m A c m^{-2}}$ and $48\\%$ lower energy equivalent input relative to commercial alkaline water electrolysis. Chlorine electrochemistry is avoided by low cell voltages without anode protection regardless $C^{1^{-}}$ crossover. This electrolyzer meanwhile enables fast hydrazine degradation to \\~3 ppb residual. Self-powered hybrid seawater electrolysis is realized by integrating low-voltage direct hydrazine fuel cells or solar cells. These findings enable further opportunities for efficient conversion of ocean resources to hydrogen fuel while removing harmful pollutants. \n\nydrogen $\\left(\\operatorname{H}_{2}\\right)$ represents the ultimate choice of sustainable and secure energy due to its superior energy density of $142.351\\mathrm{MJ}\\mathrm{kg}^{-1}$ and zero-pollution emission1. According to the International Renewable Energy Agency, the market value of hydrogen feedstock would boost to $\\$155$ billion by 2022 as the beginning of the global hydrogen economics2. Water electrolysis excels the traditional petrochemical techniques in terms of processing efficiency, renewables compatibility, and carbon neutrality for yielding high-purity hydrogen3,4. But this technology produces only $4\\%$ of hydrogen in the market due to the unaffordable cost $(>\\$4\\log^{-1})$ of electricity consumption for overcoming the high potential of overall water splitting (OWS) reaction5. Another rarely noticed but critical concern is the demand on large quantities of high-purity water feeds for water electrolysis. It would become a bottleneck to the deployment of this technology in the arid, on and off-shore areas. The ocean provides $96.5\\%$ of the planet’s water reserve, providing infinite hydrogen sources without heavy strain on the global freshwater resource6–8. However, the electrolysis of seawater with complex ionic chemistry faces extra challenges in dealing with the interference of side reactions, ionic poison, and corrosion on cell performance. A notorious problem is the chlorine electro-oxidation reactions (ClOR) and their competition with oxygen evolution reaction (OER) on the anode. This reaction releases toxic and corrosive chlorine species (e.g., $\\mathrm{Cl}_{2},\\mathrm{ClO^{-}})$ , which induces anode dissolution and environmental hazards to reduce the electrolysis efficiency and sustainability9–12. The ClOR can be suppressed by limiting the OER overpotential below $0.48\\mathrm{V}$ under alkaline conditions (Fig. 1a). However, minimizing the polarization overpotential requires conducting the electrolysis at the current densities $\\cdot<200$ $\\mathrm{m}\\bar{\\mathrm{A}}\\mathrm{cm}^{-2}$ ) far lower than the industrial criteria $\\mathrm{\\Gamma}>500{\\mathrm{-1000\\mA}}$ $c m^{-2})^{7,13}$ . Applying the cation-selective layer or chlorine-free anolyte is effective in protecting the anode from chlorine corrosion at industrially required current densities9,13. Nevertheless, it is still hard to eliminate the chlorine crossover and corrosion for long-term seawater electrolysis, and the process suffers high cell voltages $(>1.7{-2.4}\\mathrm{V})$ and electricity consumption. So far, the development of chlorine-free yet energy-saving seawater electrolysis technology still remains challenging for cost-effective and sustainable hydrogen production7,14. \n\nFor commercial alkaline water electrolyzers, the basic electricity demand is $4.3{-}5.73\\mathrm{kWh}$ for yielding $1\\mathrm{m}^{3}$ of $\\mathrm{H}_{2}$ at the cell voltages of $1.8-2.4\\:\\mathrm{V}$ and practical current level of $300{-}500\\mathrm{mA}$ $c\\mathrm{m}^{-2\\breve{1}5-17}$ . Such a high energy consumption fundamentally stems from the OER with large thermodynamic potential $\\mathrm{.}1.23\\mathrm{V}$ vs. \n\nRHE) and slow multiple proton-coupled electron-transfer kinetics18,19. This bottleneck is difficultly broken as long as the sluggish OER is involved in OWS. Replacing the OER by thermodynamically more favorable electro-oxidation reactions offers a ground-breaking strategy for energy-saving hydrogen production while adding extra functionalities like electrosynthesis20–24. Among available options, the hydrazine oxidation reaction (HzOR, $\\mathrm{N}_{2}\\mathrm{H}_{4}+4\\mathrm{O}\\bar{\\mathrm{H}}^{-}\\to\\mathrm{N}_{2}+4\\mathrm{H}_{2}\\mathrm{O}+4\\mathrm{e}^{-}$ , $-0.33\\mathrm{V}$ vs. RHE) holds great potential for yielding hydrogen at much lower voltages than OER with zero pollution emission25–28. For seawater electrolysis, the oxidation potential of $\\mathrm{HzOR}$ is far lower than that of ClOR by $2.05\\mathrm{V}$ (Fig. 1a). This advantage provides the extra benefit in avoiding the notorious problems of chlorine chemistry without limiting the electrolysis current and hydrogen yielding efficiency. On the other hand, hydrazine has been widely used as the deoxidant in the feedwater of power plants, high-energy fuel, and raw materials in the industry. The fabrication, utilization, and disposal of this highly toxic material may severely risk human health and the ecosystem29. Efficient technologies are thus highly desired to degrade the hydrazine in surface water to a trace residual (e.g., 10 ppb in drinking water set by U.S. Environmental Protection Agency, EPA)30. Electrocatalytic HzOR offers a promising way for fast removal of hydrazine from industrial sewage without using extra oxidants (e.g., Fenton’s reagent) or complex separation31. Integrating this technique into the electrolysis of costless seawater is anticipated to bring great benefits in not only environmental sustainability but also the cost-effectiveness of hydrogen production. \n\nHerein, we propose to realize energy-saving yet chlorine-free seawater electrolysis for efficient hydrogen production by a hybrid seawater splitting strategy. This chemistry consumes the seawater on the cathode to generate $\\mathrm{H}_{2}$ by hydrogen evolution reaction (HER); while the crossover of released $\\mathrm{OH^{-}}$ to the anode side supply the hydrazine degradation to harmless $\\mathrm{N}_{2}$ and water with reduced salinity (Fig. 1b). Beyond the state-of-the-art seawater electrolysis, it enables hydrogen production at ultralow cell voltages but large current densities without chlorine hazards and limiting hydrogen-yielding efficiency. The hybrid seawater electrolyzer (HSE) using NiCo/MXene-based superaerophobichydrophilic and hydrazine-friendly electrodes requires a dramatically lower electricity expense of $2.75\\mathrm{kWh}/\\mathrm{m}^{3}\\dot{\\mathrm{H}_{2}}$ than alkaline seawater electrolyzer (ASE) at industrial-scale current densities. This electrolyzer simultaneously allows fast hydrazine degradation to a rather lower residual while harvesting water with reduced salinity from seawater. On this basis, self-powered seawater electrolysis can be further realized by integrating the HSE into solar or hydrazine fuel cells for better cost-effectiveness and sustainability. \n\n![](images/8295c0953580ce6a07008a986b449b3ccb6b7a768203ee8d137d79fe2ef99af1.jpg) \nFig. 1 Schematic illustration of the merits of hybrid seawater splitting for energy-saving and sustainable hydrogen production. a The Pourbaix diagram of HzOR, HER, OER, and ClOR in artificial seawater with $0.5M{\\mathsf{C l}}^{-}$ in pH 7–14. b The merits of HSE over ASE for energy-saving and chlorine-free hydrogen production. \n\n![](images/8bbe933b5b35496086199172e5f4fcf5b93a5c597d66c12e392d486122315c27.jpg) \nFig. 2 Characterizations of NiCo@C/MXene/CF. a Schematic illustration of the synthetic strategy of NiCo@C/MXene/CF. b SEM image showing macroporous scaffold of this electrode. Scale bar, $200\\upmu\\mathrm{m}$ . c SEM image of mesoporous networks of ${\\mathsf{N i C o@C}}$ nanosheets on electrode surface. Scale bar, $3\\upmu\\mathrm{m}$ . d TEM image of a ${\\mathsf{N i C o@C}}$ nanosheet. Scale bar, $100\\mathsf{n m}$ . e HRTEM image of NiCo nanocrystallite on the nanosheet. Scale bar, $3n m$ . f Elemental mapping showing the uniform distribution of C, N, Ti, Ni, and Co elements in this electrode. Scale bar, $5\\upmu\\mathrm{m}$ . \n\n# Results \n\nSynthesis and characterization of NiCo/MXene-based electrode. A NiCo/MXene-based electrode is designed to optimize the gas-releasing capability and water/hydrazine compatibility for propelling hybrid seawater splitting. It is fabricated by assembling NiCo-MOF nanosheets on MXene-wrapped Cu foam (MXene/ CF, Supplementary Fig. 1), followed by annealing in ${\\mathrm{NH}}_{3}$ (denoted as NiCo@C/MXene/CF, Fig. 2a). Scanning electron microscopy (SEM) and Atomic force microscopy (AFM) reveal the formation of a mesoporous array of NiCo-decorated carbon nanosheets $\\operatorname{(NiCo@C)}$ with an average size of $400{-}800\\mathrm{nm}$ and a thickness below $50\\mathrm{nm}$ on MXene/CF (Fig. 2b, c and Supplementary Fig. 2). Such nanoarray-based rough surface can largely weaken the gas adhesion on discontinuous solid-liquid-gas triplephase contact dots, thereby enabling a superaerophobic property32,33. While the MXene layer with abundant -OH and -O groups may effectively attract the water and hydrazine molecules via hydrogen bonding interaction34. Coupling them into 3D configuration yields an electrocatalytic electrode with superaerophobic-hydrophilic and hydrazine-friendly interface, large gas transport channels, high active surface area and superb conductivity for promoting hybrid seawater electrolysis. Transmission electron microscopy (TEM) and $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) reveal that the $\\mathsf{N i C o@C}$ consists of numerous single-crystal NiCo alloy nanoparticles $<10{-}20\\ \\mathrm{nm})$ embedded in the amorphous carbon matrix (Fig. 2d, e and Supplementary Fig. 3)35. The facecentered cubic (fcc) structure of NiCo alloy in NiCo $@$ C/MXene is identified by a rather similar XRD pattern with fcc Ni in $\\operatorname{Ni}@\\operatorname{C}I$ MXene and fcc Co in Co@C/MXene. Coordination states of the metal atoms in $\\operatorname{NiCo@C}$ are further investigated by X-ray absorption fine structure (XAFS). The NiCo@C, Ni@C and $\\mathrm{Co@C}$ nanosheets are peeled off from the CF to minimize the influence of CF on the analysis. The K-edge X-ray absorption near-edge structure (XANES) spectra of Ni and Co in $\\mathsf{N i C o@C}$ are close to that of $\\mathrm{Ni}@\\mathrm{C}$ , $\\mathrm{Co@C}$ and metal foil reference, suggesting a metallic state of these elements (Supplementary Fig. 4a, b). Curve fitting of Fourier-transformed extended X-ray absorption fine structure (FT-EXAFS) spectra reveal the change of coordination number of Ni from 8.3 in $\\mathsf{N i@C}$ to 9.6 in $\\mathsf{N i C o@C}$ while the value of Co increase from 8.4 in $\\mathrm{Co@C}$ to 9.0 in $\\operatorname{NiCo@C}$ (Supplementary Fig. 4c, d). This phenomenon indicates the formation of NiCo alloy instead of their mixture. The presence of Ni-Ni bonds in NiCo alloy is identified by a similar metal bond length in $\\operatorname{NiCo}\\ @\\operatorname{C}$ $(2.64\\dot{\\mathrm{A}})$ and $\\mathrm{Ni}@\\dot{\\mathrm{C}}$ $(2.63\\mathring\\mathrm{A})$ . The alloying of Co with Ni with a smaller atomic size induces a shorter metal bond length of $2.56\\mathring{\\mathrm{A}}$ with respect to $C o\\mathrm{-}C o$ bonds in $\\mathrm{Co@C}\\left(2.63\\mathrm{\\AA}\\right)$ , implying the atomic dispersion of Co atoms in Ni lattice in NiCo alloy. Tiny oxidization states (Ni-O, Co-O) appear for all the samples and metal foil references due to inevitable surface oxidation during XAFS analysis in air. No nickel or cobalt nitrides are formed by annealing NiCo-MOF at a relatively low temperature, which is consistent with the XRD result. Elemental mapping and X-ray photoelectron spectroscopy (XPS) visualize the presence and uniform distribution of C, N, Ti, $\\mathrm{Ni}$ , and Co elements on NiCo@C/MXene/CF (Fig. 2f and Supplementary Fig. 5a). The Ni exists as a metallic state with a strong ${2p_{3/2}}/{2p_{1/2}}$ doublet at $852.8/870.18\\mathrm{eV}$ in Ni $2p$ spectrum (Supplementary Fig. 5b)36. The Co has a mixed metallic and $\\dot{\\mathrm{Co}}^{\\dot{2}+}$ state, identified by the doublets at $778.5/793.3\\$ and $780.7/796.3\\mathrm{eV}$ in Co $2p$ spectrum, respectively (Supplementary Fig. 5c)37. The Ti $2p$ spectrum validates the presence of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene by the signals from Ti-C lattice with $\\mathrm{Ti}^{2+}$ and $\\mathrm{Ti}^{3+}$ species that grafting the surficial groups via Ti-O and Ti-F bonds (Supplementary Fig. 5d, e)19. Strong $\\mathrm{Ti}^{3+}$ signal may be a result of the reaction between oxygen-containing groups on MXene surface and Ti atoms connected to them during annealing. To achieve the best HzOR and HER activity, the NiCo content is optimized to 84.7 wt. $\\%$ in $\\operatorname{NiCo@C}$ with a Ni: Co ratio of 2.7: 1 (Supplementary Fig. 6, 7). The average $\\operatorname{NiCo}\\ @\\operatorname{C}$ loading on MXene/CF is around $1.{\\overset{\\sim}{0}}\\operatorname*{mg}\\operatorname{cm}^{-2}$ . \n\n![](images/5fabb443012eb912de673e9ca1fcc8d102a72597533d7485856b1a9e000043f3.jpg) \nFig. 3 Half-cell HzOR and HER performance of NiCo@C/MXene/CF. a A comparison between HzOR and OER in $1.0{\\ensuremath{M}}$ KOH in anode potential. b A comparison between NiCo@C/MXene/CF and reported 3D electrodes in $H z O R$ activity. c Tafel plots of NiCo@C/MXene/CF, ${N i C o@C/C F}$ and $\\mathsf{P t/C F}$ for $H z O R$ . d The LSVs of NiCo@C/MXene/CF and controlled catalysts including ${N i C o@C/C F}$ , MXene/CF, Pt/CF and CF for $H z O R$ e The LSVs initially and after 2000 sweeps for $H z O R$ . The insert is the chronopotentiometric curves of NiCo@C/MXene/CF and Pt/CF for $H z O R$ at a current density of $100~\\mathsf{m A}$ $\\mathsf{c m}^{-2}$ . All $H z O R$ tests are conducted in 1.0 M KOH with 0.5 M $N_{2}H_{4}$ at a scan rate of $10\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . f The LSVs for HER in $1.0\\mathsf{M}$ KOH or seawater $\\left(\\mathsf{p}\\mathsf{H}\\ 13.8\\right)$ at a scan rate of $10\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . The HER activity of controlled catalysts including ${N i C o@C/C F}$ and MXene/CF is also compared under identical conditions. \n\n# Half-cell HzOR performance of NiCo/MXene-based electrode. \n\nThe HzOR activity of NiCo@C/MXene/CF is evaluated in $1.0\\mathrm{M}$ KOH with various hydrazine concentrations. All the potentials are against the RHE unless otherwise specialized. This electrode exhibits a rapid increase in activity with hydrazine concentration increasing until $0.5\\mathrm{M}$ (Supplementary Fig. 8a). In $1.0\\mathrm{M}$ KOH with $0.5{\\mathrm{M}}{}$ hydrazine, achieving high current densities of 100 and $500\\mathrm{mAcm^{-2}}$ only requires ultralow potentials of $^{-25}$ and 43 $\\mathrm{mV}$ , respectively (Fig. 3a and Supplementary Fig. 9a). In sharp contrast, the sluggish OER needs 37–62 times higher potential $(1.542\\mathrm{-}1.586\\mathrm{V})$ for reaching the same current level in $1.0\\mathrm{M}$ KOH. Compared to reported 3D electrodes, the NiCo@C/MXene/ CF still exhibits far superior HzOR activity under similar conditions (Fig. 3b and Supplementary Table 1). Such a dramatic reduction in anode potential is rather beneficial to hydrogen production at a low cost of electricity. With scan rate increasing from 5 to $100\\mathrm{mV}s^{-1}$ , the HzOR proceeds with a negligible shift of the polarization curves, indicating fast kinetics across the electrode-electrolyte-gas triple-phase interface on $\\operatorname{NiCo@C/}$ MXene/CF (Supplementary Fig. 8b). Fast charge transfer kinetics is further revealed by a small Tafel slope of $73\\mathrm{\\bar{m}V\\ d e c^{-1}}$ (Fig. 3c) and low charge-transfer resistance $(R_{\\mathrm{ct}}=0.25\\ \\Omega)$ ) (Supplementary Fig. 8c). To identify the active phase for HzOR, the performance of controlled catalysts including MXene-free $\\operatorname{NiCo@C/CF}$ , NiCofree MXene/CF, bare CF and $20\\%$ $\\mathrm{Pt/C}$ casting on CF $\\mathrm{(Pt/CF)}$ is evaluated under identical conditions (Fig. 3d). The MXene/CF and bare CF are inactive for $\\scriptstyle{\\mathrm{HzOR}}.$ But the presence of MXene contributes greatly to interconnecting $\\operatorname{NiCo}\\ @\\operatorname{C}$ arrays on CF and reducing interfacial resistance. It leads to superior electrochemical active surface area (ECSA, $54.25~\\mathrm{~m}^{2}~\\mathrm{~g}_{\\mathrm{cat}}^{\\bullet}-1\\rangle$ and interfacial conductivity to MXene-free $\\operatorname{NiCo@C/CF}$ $\\left(35.0\\mathrm{m}^{2}\\mathrm{g_{cat}}^{-1}\\right.$ , $R_{\\mathrm{ct}}=1.8$ $\\Omega$ ) (Supplementary Figs. 8c, 10). Poisoning the electrode by trace amounts (e.g., $10\\mathrm{mM})$ of $\\mathsf{S C N^{-}}$ induces an immediate and dramatic activity decay, implying the primary role of NiCo as the active phase in catalyzing HzOR (Supplementary Fig. 8d)38. When normalized to active mass, the activity of NiCo@C/MXene/CF still exceeds $\\mathrm{Pt/CF}$ by over 10–35 folds and $\\operatorname{NiCo@C/CF}$ for 3.6–4.5 times (Supplementary Fig. 8e, f). The NiCo@C/MXene/CF also excels $\\operatorname{NiCo@C/CF}$ in terms of ECSA-normalized HzOR activity (Supplementary Fig. 11). During the accelerated durability test, this electrode can work steadily for 2000 cycles or $30\\mathrm{h}$ at $100\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ with a negligible activity loss (Fig. 3e). The electrocatalytic tests at a scan rate of $1.0\\mathrm{m}\\dot{\\mathrm{V}}\\mathrm{s}^{-1}$ or against $\\mathrm{Hg/HgO}$ reference electrode rule out the effect of double-layer charging or reference electrode on catalyst performance (Supplementary Figs. 12a and 13a, b). The ICP analysis reveals a very low residue of Ni, Co, and Ti ions in the electrolyte after long-term $\\mathrm{HzOR}$ , showing negligible catalyst leaching during electrolysis (Supplementary Table 2). Afterward, post-mortem SEM, TEM, and XPS analysis show that the NiCo@C/MXene/CF well retains the original 3D architecture, nanoarray-based surface and chemical composition, revealing high robustness against long-term HzOR (Supplementary Fig. 14). \n\nHalf-cell HER performance of NiCo/MXene-based electrode. The NiCo@C/MXene/CF also works efficiently for catalyzing HER. It requires a low overpotential $(\\eta)$ of 49 and $235\\mathrm{mV}$ to reach the current densities of 10 $(\\eta_{\\mathrm{j=10}})$ and $500\\mathrm{mAcm}^{-2}$ $(\\eta_{\\mathrm{j=500}})$ in $1.0\\mathrm{M}$ KOH, respectively (Fig. 3f and Supplementary Fig. 9b). The alkaline HER on this electrode undergoes a fast Volmer-Heyrovsky pathway with a small Tafel slope of $5\\bar{4}.2\\mathrm{mV}\\mathrm{dec^{-1}}$ (Supplementary Fig. 15a). Poisoning tests by $10\\mathrm{mM}\\mathrm{SCN^{-}}$ suggest that the NiCo dominates the HER activity (Supplementary Fig. 15b)38. The presence of MXene on NiCo@C/MXene/CF also induces superior ECSAnormalized activity and charge-transfer kinetics to MXene-free $\\operatorname{NiCo@C/CF}$ for HER (Supplementary Fig. 15c, d). The HER on NiCo@C/MXene/CF exhibits a high turnover frequency (TOF) of $2.1\\ s^{-1}$ at $\\eta=200\\:\\mathrm{mV}$ and exchange current density $(j_{0})$ of $1.34\\mathrm{mA}$ $c\\mathrm{m}^{-2}$ , exceeding the $\\operatorname{NiCo@C/CF}$ by over 3–5.8 times (Supplementary Fig. 16). These results highlight the significance of MXene in improving the per-site electrocatalytic activity of $\\operatorname{NiCo}\\ @\\operatorname{C}I$ MXene/CF. During long-term HER, this electrode can operate steadily for 2000 sweeps or $60\\mathrm{h}$ with $95\\%$ current retention at $\\eta=$ $100\\mathrm{mV}$ in $1.0\\mathrm{M}$ KOH (Supplementary Fig. 17). Afterward, the NiCo@C/MXene/CF also retains the original texture without collapse or leaching (Supplementary Fig. 18 and Table 2). Likewise $\\mathrm{HzOR},$ the effect of double-layer charging or reference electrode on catalyst performance is ruled out by conducting the electrocatalytic tests at a scan rate of $1.0\\mathrm{mVs^{-1}}$ or against $\\mathrm{Hg/HgO}$ reference electrode (Supplementary Figs. 12b and 13c, d). The HER performance of this electrode remains on the top level of reported 3D electrodes under similar alkaline conditions (Supplementary Table 3). Encouragingly, its high activity can be largely maintained in alkaline seawater $\\mathrm{(pH~13.8)}$ , neutral seawater or the electrolyte with seawater $\\mathrm{\\pH}$ (8.3) with poor conductivity and ionic strength at high current densities of $400{-}500\\operatorname{mA}\\operatorname{cm}^{-2}$ (Fig. 3f, Supplementary Figs. 19, 20a). The NiCo@C/MXene/CF also shows comparable performance with commercial $20\\%$ $\\mathrm{Pt/C}$ in $1.0\\mathrm{M}\\mathrm{KOH}$ , alkaline or neutral seawater. It could even outperform the $\\mathrm{Pt/C}$ at the current densities above $120\\mathrm{mAcm}^{-2}$ (Supplementary Fig. 19a, b), making it attractive for large-current hydrogen production. During longterm HER, the NiCo@C/MXene/CF can work for $120\\mathrm{h}$ in both alkaline and neutral seawater, showing good robustness in corrosive seawater (Supplementary Fig. 19c). \n\nPerformance of hybrid seawater electrolyzer. Hybrid seawater splitting coupling HzOR and seawater-efficient HER shows a dramatic advantage over OWS in reducing the electricity consumption of seawater electrolysis. It requires an ultralow cell voltage of $0.31\\mathrm{V}$ to achieving a high current density of $500\\mathrm{mA}$ $c\\mathrm{m}^{-2}$ on NiCo@C/MXene/CF under alkaline conditions $\\left(\\mathrm{pH}13.8\\right)$ (Fig. 4a). Using neutral seawater for HER raises the cell voltage to $0.42\\mathrm{V}$ at a current density of $400\\mathrm{mAcm}^{-2}$ . This activity still far excels the OWS, which has to conquer huge voltages of 1.80–1.82 V for yielding hydrogen at high current densities of $400{-}500\\mathrm{mA}$ $\\mathrm{cm}^{-2}$ on the same electrode in $1.0\\mathrm{M}$ KOH. On this basis, an asymmetric HSE is assembled by using the seawater as the catholyte and $1.0\\mathrm{M}$ KOH with $0.5\\mathrm{M}$ hydrazine as the anolyte feed. The $\\mathrm{NiCo@C/MXene/CF}$ is used as the identical anode and cathode separated by an anion exchange membrane (AEM). It allows for energy-saving hydrogen production from seawater and simultaneous hydrazine degradation in a single cell while harvesting water with a lower salinity from seawater. The asymmetric design ensures hydrogen yielding at high purity while preventing toxic hydrazine to pollute the seawater. It also avoids the interference of HzOR on the performance of HER with overlapped reduction potential, which reduces the HER activity by 1.5–3 folds in alkaline seawater (Supplementary Fig. 21). \n\nFor direct electrolysis of neutral seawater, the HSE can reach a high current density of $500\\mathrm{mAcm}^{-2}$ at a low voltage of $1.05\\mathrm{V}$ , reducing by $45.6\\%$ as compared to ASE $(1.93{\\mathrm{V}})$ (Fig. 4b and Supplementary Fig. 9c). It can steadily work for hydrogen production at a rate of $5.6\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{g}_{\\mathrm{cat}}{}^{-1}$ below $1.0\\mathrm{V}$ (without iR correction) for over $85\\mathrm{h}$ at a current density of $300\\mathrm{mAcm}^{-2}$ (Fig. 4c). Accordingly, the basic electricity expense is reduced to as low as $2.39\\mathrm{kWh}$ for yielding ${\\mathrm{1}}{\\mathrm{m}}^{3}{\\mathrm{H}}_{2}.$ , which is even superior to the theoretical energy demand of OWS $(2.94\\mathrm{kWh}/\\mathrm{m}^{3}\\dot{\\mathrm{H}}_{2}\\mathrm{~}$ ). The HSE also exhibits rather comparable in seawater $\\mathrm{\\pH}$ (8.3) mimicked electrolyte (Supplementary Fig. 20b). Using alkaline seawater with $1.0\\mathrm{M}$ KOH as the catholyte feed in HSE can further reduce the cell voltage to an ultralow value of $0.7\\mathrm{V}$ at a high current density of $500\\mathrm{\\mA}\\mathrm{cm}^{-2}$ , cutting by $63.7\\%$ relative to ASE (Fig. 4b). No $\\mathrm{ClO^{-}}$ generation is detected under such a low potential, allowing the anode corrosion to be fully eliminated regardless of $\\mathrm{Cl^{-}}$ crossover (Fig. 4d and Supplementary Fig. 22, 23). As a sharp contrast, the anode is rapidly dissolved by highconcentration $\\mathrm{ClO^{-}}$ corrosion, inducing fast failure of ASE in only $6{-}7\\mathrm{h}$ . Stable electrolysis can proceed below $0.36\\mathrm{V}$ (without $i R$ correction) for over $120\\mathrm{h}$ at $\\mathrm{i}\\mathrm{00}\\mathrm{mA}\\mathrm{cm}^{-2}$ in HSE (Fig. 4c). Even at a high current density of $500\\mathrm{mAcm}^{-2}$ , the HSE can still steadily work below $1.15\\mathrm{V}$ (without $i R$ correction) for $140\\mathrm{h}$ to yield hydrogen at a fast rate of $9.2\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{g}_{\\mathrm{cat}}{}^{-1}$ . The electricity expense is reduced to $2.75\\mathrm{kWh}/\\mathrm{m}^{3}\\mathrm{H}_{2}$ , cutting by ${\\sim}54\\%$ relative to ASE working at $2.53\\mathrm{V}$ . The HSE also exhibit superior energy equivalent inputs but lower $\\mathrm{CO}_{2}$ equivalent emission to conventional technologies such as alkaline water electrolysis, natural gas steam reforming and recently reported electrochemical methane splitting for hydrogen production (Fig. 4e and Supplementary Table 4), showing a significant advantage in energy efficiency and processing sustainbility39. Gas chromatography (GC) validates the yield of high-purity $\\mathrm{H}_{2}$ and $\\mathrm{N}_{2}$ with a ratio of ca. 2: 1 without ${\\dot{\\mathrm{Cl}}}_{2}$ emission (Supplementary Fig. 24). The Faradaic efficiencies (FE) of HER and HzOR are determined to ca. $96\\%$ and $99\\%$ , respectively (Supplementary Fig. 25). This HSE also far excels the state-of-the-art seawater electrolyzer in terms of energy efficiency for hydrogen production (Fig. 4f and Supplementary Table 5). \n\nThe performance of HSE is also evaluated by using seawater with various $\\mathrm{OH^{-}}$ concentrations $(0.0{-}3.0\\mathrm{M})$ as the catholyte and $1.0\\mathrm{M}$ KOH containing $0.5\\mathrm{M}$ $\\mathrm{N}_{2}\\mathrm{H}_{4}$ as the anolyte, which may give some clues on the effect of $\\mathrm{\\pH}$ gradient over AEM on cell performance. The $\\mathsf{p H}$ gradient across AEM would be first reduced until $\\mathrm{OH^{-}}$ concentrations in the catholyte rising to the same with the anolyte $(1.0\\mathrm{M})$ . Meanwhile, the HER activity is improved with the catholyte $\\mathsf{p H}$ increasing, leading to a fast increase in cell activity (Supplementary Fig. 26). In this case, the direction of $\\mathrm{\\pH}$ gradient over AEM is opposite to that of $\\mathrm{OH^{-}}$ diffusion, thereby playing no significant role in electrocatalytic enhancement. After the catholyte $\\mathrm{\\pH}$ exceeds the anolyte value, the direction of $\\mathrm{\\tt{pH}}$ gradient across AEM would be the same with $\\mathrm{OH^{-}}$ diffusion. But the performance of the electrolyzer is not significantly enhanced at large current densities due to the limitation of AEM in ionic exchange capacity and permeability. Developing high-performance AEM is desired to address this issue for full exploitation of the potential of our hybrid electrolyzer design. \n\nHydrazine is strongly poisonous and carcinogenic with a high risk to human health. The threshold of hydrazine in surface water should be strictly restricted to protect the ecosystem. The HSE coupling HzOR provides the additional function in dealing with toxic hydrazine sewage without using extra oxidants or complex separation technologies. It allows the hydrazine to be removed at a fast rate of $4.34\\pm{\\breve{0}}.007\\mathrm{molh^{-1}g_{c a t}}^{-1}$ during hydrogen production at a high current density of $500\\mathrm{mA}\\mathrm{\\dot{c}}\\mathrm{m\\dot{\\mathrm{^{-}}}}^{2}$ (Fig. $4\\mathrm{g}$ and Supplementary Fig. 27). The residual limit of hydrazine in water can be as low as $3{\\mathrm{ppb}}$ , falling below the allowable value $({\\mathrm{10}}{\\mathrm{ppb}})$ set by $\\mathrm{EPA}^{30}$ . Exceptionally stable hydrazine treatability and high hydrogen-yield rate can be maintained for repeated cycles, showing high effectiveness for practical use. Using hydrazine sewage as the anolyte may in turn further reduce the hydrogen cost along with applying costless seawater as the catholyte feed. On this basis, cost-effective and sustainable hydrogen production might be scaled up by feeding costless seawater and industrial hydrazine sewage into renewables-powered HSE in the coastal region with intense solar irradiation and strong wind pattern (Fig. 4h). \n\n![](images/dbf6d7395e2ebab72cbb86a7fdf5c3269a1825b061bcf7f2340fd8cc5937e612.jpg) \nFig. 4 Performance of HSE for hydrogen production and hydrazine degradation. a The voltage differences (ΔV) between HER and $H z O R$ or OER on NiCo@C/MXene/CF in different electrolytes. b The LSV curves of HSE using neutral or alkaline seawater as the catholyte, compared with ASE. c Durability tests of HSE at various current and catholyte conditions. The ASE is also tested at $500\\mathsf{m A c m^{-2}}$ for comparison. d A comparison of the $\\mathsf{C l O^{-}}$ concentration change in the anolyte during continuous electrolysis at $100\\mathsf{m A c m^{-2}}$ in HSE or ASE. e A comparison of HSE with different hydrogen production techniques in energy equivalent input and ${\\mathsf{C O}}_{2}$ equivalent emission. f A comparison of HSE (champagne region) with the state-of-the-art seawater electrolyzer (pale blue region) in cell voltage and current density. $\\pmb{\\mathrm{\\sigma}}_{\\pmb{\\mathrm{\\mathcal{S}}}}$ The activity and durability of HSE for hydrazine degradation during hydrogen production at $500\\mathsf{m A c m^{-2}}$ . h Schematic drawing of cost-effective and sustainable hydrogen production by renewables-powered HSE with costless seawater and industrial hydrazine sewage as the feeds. \n\nSelf-powered system for low-voltage hydrogen production from seawater. Large-scale renewable energy systems are usually necessary to satisfy the high power demand of water electrolysis. While the HSE with low electricity expense offers the feasibility of integrating with renewable power sources on a smaller scale (e.g., fuel cells, solar cells). This benefit is highly desired to reduce the additional capital and complexity of the hydrogen production system. As a proof-of-concept, a self-powered hydrogen production system is built by integrating the HSE into a single direct hydrazine fuel cell (DHzFC, Fig. 5a, b). The DHzFC is assembled by using NiCo@C/MXene/CF as the anode and $20\\%\\ \\mathrm{Pt/C}$ as the cathode. It exhibits an open-circuit voltage (OCV) of ca. $1.0\\mathrm{V}$ and a maximum power density of $53.5\\mathrm{mW}\\mathrm{cm}^{-2}$ (Supplementary Fig. 28). This self-powered system could yield hydrogen from seawater at a rate of $1.6\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{g_{\\mathrm{cat}}}^{-1}$ with hydrazine as the sole energy consumable (Fig. 5c and Supplementary Movie 1). It achieves a total efficiency of $48.0\\%$ , comparable with the reported systems for converting hydrazine to hydrogen25,26. Hydrogen production with better sustainability and cost-effectiveness can be realized by connecting the HSE into photovoltaic cells powered by easily harvestable and clean solar energy (Fig. 5a, d). Such a solar-driven hydrogen production system could be operated at a current density of ca. $310\\mathrm{mA}\\mathrm{cm}^{-2}$ and an average photovoltage of ca. $0.876\\mathrm{V}$ when powered by a single commercial solar cell (1.0 W) (Supplementary Fig. 29). The hydrogen is yielded at a decent rate of $6.0\\mathrm{mol}\\dot{\\mathrm{h}}^{-1}\\dot{\\mathrm{g}_{\\mathrm{cat}}}^{-1}$ from seawater under AM $1.5\\mathrm{G}$ simulated solar illumination with a power density of $100\\mathrm{mW}$ $\\mathsf{c m}^{-2}$ (Fig. 5e, h and Supplementary Movie 2). Under natural light, this system can also work steadily for efficient hydrogen production (Supplementary Movie 3). \n\n# Discussion \n\nOrigin of the intrinsic activity of NiCo sites for promoting HzOR. Regarding the extensive investigation in HER on NiCo alloy, we mainly focus on the origin of its $\\mathrm{HzOR}$ activity. Typical (100), (110), and (111) facets of fcc $\\mathrm{Ni}_{3}\\mathrm{Co}$ alloy are studied for the first-principle calculation. All these facets exhibit strong chemical interaction with $\\mathrm{N}_{2}\\mathrm{H}_{4}$ molecule via the N-metal donor-acceptor pairs with rather negative binding energy $(E_{\\mathrm{b}})$ of $-1.24$ to $-1.8\\bar{9}\\mathrm{eV}$ (Fig. 6a and Supplementary Table 6). The $\\mathrm{N}_{2}\\mathrm{H}_{4}$ molecule is attracted on $\\mathrm{Ni}_{3}\\mathrm{Co}$ surface in three configurations: on the top sites of $\\mathrm{Ni}$ or $\\mathrm{Co}$ atoms, or the bidentate sites between them. The (100) facet of $\\mathrm{Ni}_{3}\\mathrm{Co}$ alloy shows the strongest $\\mathrm{N}_{2}\\mathrm{H}_{4}$ adsorption with the most negative $\\ensuremath{E_{\\mathrm{b}}}$ of $-1.54$ to $-1.89\\mathrm{eV}$ (Supplementary Table 6). \n\n![](images/5c6edffea466de3dfa5143008fe746e4e460c1a22b95963f5cdf31392bb844ed.jpg) \nFig. 5 Self-powered hybrid seawater electrolysis systems. a Schematic illustration of self-powered hydrogen production systems by integrating HSE to low-voltage DHzFC or solar cell. b Optical image of a self-powered hydrogen production system connecting an HSE to a DHzFC. c Hydrogen-yield rate of an HSE powered by a single $D H z F C$ or solar cell. d Optical image of a solar-driven HSE. e Current density or voltage vs. time curves of this solar-driven hydrogen production system under AM $1.5\\mathsf{G}$ illumination. \n\nOverall, the strongest $\\mathrm{N}_{2}\\mathrm{H}_{4}$ adsorption is achieved by the bidentatetype attraction between both $\\mathrm{\\DeltaN}$ atoms in $\\mathrm{N}_{2}\\mathrm{H}_{4}$ molecule and Ni and Co sites. Charge density difference analysis indicates prominent charge transfer from the $\\mathrm{~N~}$ atoms in $\\mathrm{N}_{2}\\mathrm{H}_{4}$ to nearby Co and Ni atoms (Fig. 6a), which enlarges the N-H bond length in $\\mathrm{N}_{2}\\mathrm{H}_{4}$ adsorbed on $\\mathrm{Ni}_{3}\\mathrm{Co}$ alloy to $1.028\\mathrm{-}1.035\\mathring\\mathrm{A}$ relative to the free molecule $(1.024{-}1.026\\mathring\\mathrm{A})$ . The effect weakens the N-H bonds in adsorbed $\\mathrm{N}_{2}\\mathrm{H}_{4}$ molecule to facilitate the molecular activation for $\\mathrm{HzOR}^{26,40}$ . Among all facets of $\\mathrm{Ni}_{3}\\mathrm{Co}$ alloy, the (100) plane exhibits the highest activity for activating $\\mathrm{N}_{2}\\mathrm{H}_{4}$ molecule, as identified by the longest length of ${\\mathrm{N}}{\\mathrm{-}}{\\mathrm{H}}$ bonds $(1.033{-}1.035\\mathring{\\mathrm{A}})$ (Fig. 6a). The HzOR in alkaline medium may undergo three possible pathways, namely, the $_{1e}$ route with $\\mathrm{NH}_{3}$ and $\\mathrm{N}_{2}$ as the product $\\mathrm{(N_{2}H_{4}+O H}$ $^{-}\\rightarrow\\mathrm{NH}_{3}+0.5\\mathrm{N}_{2}+\\mathrm{H}_{2}\\mathrm{O}+e^{-})$ , the $2e$ pathway yielding $\\mathrm{N}_{2}$ and $\\mathrm{H}_{2}$ $(\\mathrm{N}_{2}\\mathrm{H}_{4}+2\\mathrm{OH}^{-}\\longrightarrow\\mathrm{N}_{2}+\\mathrm{H}_{2}+2$ $\\mathrm{H}_{2}\\mathrm{O}+2e^{-})$ , and $4e$ reaction releasing $\\mathrm{N}_{2}$ $(\\mathrm{N}_{2}\\mathrm{H}_{4}+4\\mathrm{OH}^{-}\\longrightarrow\\mathrm{N}_{2}+4\\mathrm{H}_{2}\\mathrm{O}+4e^{-})$ . Since highpurity $\\mathrm{N}_{2}$ is detected as the only anodic product by GC (Supplementary Fig. 24b), a $4e$ pathway should be responsible for HzOR on our catalyst28,40. On this basis, the elementary reactions for stepwise $\\mathrm{N}_{2}\\mathrm{H}_{4}$ dehydrogenation $(\\mathrm{N}_{2}\\mathrm{H}_{4}\\longrightarrow\\mathrm{N}_{2}\\mathrm{H}_{4}{}^{*}\\stackrel{\\cdot}{\\longrightarrow}\\mathrm{N}_{2}\\mathrm{H}_{3}{}^{*}\\longrightarrow\\mathrm{N}_{2}\\mathrm{H}_{2}{}^{*}\\longrightarrow$ $\\mathrm{N}_{2}\\mathrm{H}^{*}\\to\\mathrm{N}_{2}^{*}$ ) are investigated on three facets of $\\mathrm{Ni}_{3}\\mathrm{Co}$ alloy (Fig. 6b and Supplementary Fig. 30). The $\\mathrm{N}_{2}\\mathrm{H}_{4}$ adsorption on all these facets is thermodynamically spontaneous and the initial dehydrogenation to $\\mathrm{N}_{2}\\mathrm{H}_{3}{}^{*}$ and $\\mathrm{N}_{2}\\mathrm{H}_{2}{^{\\ast}}$ is endothermic. The initial dehydrogenation of $\\mathrm{N}_{2}\\mathrm{H}_{4}{}^{*}$ to ${\\mathrm{N}}_{2}{\\mathrm{H}}_{3}{}^{*}$ encounters a high energy barrier of $0.7\\mathrm{-}0.8\\mathrm{eV}$ on the (111) and (110) facets in contrast to a much lower value of $0.28\\mathrm{eV}$ on the (100) facet. Next dehydrogenation step of $\\mathrm{N}_{2}\\mathrm{H}_{3}{}^{*}$ to $\\mathrm{N}_{2}\\mathrm{H}_{2}{^{*}}$ is also uphill on all facets with a comparable energy barrier of $0.3\\mathrm{-}0.5\\mathrm{eV}$ , followed by the downhill steps of $\\mathrm{N}_{2}\\mathrm{H}_{2}{^{\\ast}}$ dissociation to $\\mathrm{N}_{2}\\mathrm{H}^{*}$ and ${\\mathrm{N}}_{2}{}^{*}$ . These findings suggest the dehydrogenation of ${\\mathrm{N}}_{2}{\\mathrm{H}}_{3}{}^{*}$ to $\\mathrm{N}_{2}\\mathrm{H}_{2}{^{\\ast}}$ is the potential rate-limiting step of HzOR on $\\mathrm{Ni}_{3}\\mathrm{Co}$ (100) facet while that for (110) and (111) facets is the $\\mathrm{N}_{2}\\mathrm{H}_{4}{}^{*}$ to ${\\mathrm{N}}_{2}{\\mathrm{H}}_{3}{}^{*}$ with a much higher energy barrier. Therefore, the $\\mathrm{Ni}_{3}\\mathrm{Co}$ (100) facet is predicted to be the most active for propelling HzOR. \n\nEffect of interfacial properties on electrolysis performance. Besides the NiCo alloy, the MXene also contributes greatly to tailoring the interfacial properties for boosting the performance of NiCo@C/MXene/CF. The $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene has an even superior conductivity (ca. $5600\\mathrm{{Scm^{-1}}},$ ) to soft carbon materials (e.g., $10{-}120\\operatorname{S}\\mathrm{cm}^{-1}$ for reduced graphene oxide, $100\\mathrm{{Scm^{-1}}}$ for carbon black)41. Their presence significantly reduces the interfacial resistance to accelerate the charge-transfer kinetics of both HER and HzOR on NiCo@C/MXene/CF (Supplementary Fig. 8c, 15c). Besides, the presence of abundant -OH and -O groups on MXene surface also facilitates the effective attraction of water and hydrazine molecules onto the electrocatalytic interface by hydrogen bonding attraction42. Efficient water adsorption on $\\scriptstyle\\mathrm{NiCo@C/MXene/CF}$ is revealed by a small water contact angle $\\mathrm{^{\\prime}C A_{w a t e r}}=57^{\\mathrm{o\\cdot}},$ ), superior water adsorption capacity $(31.0\\mathrm{mg}\\$ $\\mathrm{g_{cat}}^{-1})$ ) and rate $(2.6\\mathrm{\\dot{m}g\\ m i n^{-1}g_{c a t}}^{-1})$ to hydrophobic $\\operatorname{NiCo@C/CF}$ (Fig. 6c and Supplementary Fig. 31). This improvement is important to accelerate the Volmer-Heyrovsky kinetics of neutral/alkaline HER (Supplementary Fig. 15a), where the water supplies the hydrogen and its dissociation (Volmer step) is the rate-limiting step3,43. The NiCo@C/MXene/CF also shows superior hydrazine adsorption capacity $(51.6\\mathrm{mg}\\mathrm{g_{cat}}^{-1})$ and rate $({3.\\dot{6}}\\operatorname*{mg}\\operatorname*{min}^{-1}{{\\bf g}_{\\mathrm{cat}}}^{-1})$ to $\\operatorname{NiCo@C/CF}$ $(40.3\\mathrm{mg}\\mathrm{g}_{\\mathrm{cat}}{-1}$ –1, 2.8 mg $\\mathrm{min^{-1}}\\dot{\\bf g}_{\\mathrm{cat}}{-}^{1}\\big)$ , which contribute greatly to a 2-folds faster HzOR kinetics (Figs. 3c, 6d). Such highly hydrophilic and hydrazinefriendly properties are essential to achieving high access of water or hydrazine molecules to the inner Helmholtz plane above the electrocatalytic interface44. It is undoubtedly important to accelerate the HER and $\\mathrm{HzOR},$ where water or hydrazine plays a vital role in governing the overall kinetic performance. \n\n![](images/c2b9e40ea542cf22c02ba1ba1d1cd02e54303ca58283df6964c37eb7f79780c9.jpg) \nFig. 6 Role of NiCo alloy and interfacial properties in promoting electrocatalytic performance. a The structural model of ${\\sf N}_{2}{\\sf H}_{4}$ adsorption on various facets of $N i_{3}C o$ alloy, and corresponding charge density difference analysis, where the yellow or cyan regions indicate the accumulation or depletion of the charge, respectively. The $L_{N-H}$ and $\\boldsymbol{E_{\\mathrm{b}}}$ are the calculated N-H bond lengths (Å) and binding energy of the intermediates on $N i_{3}C o$ alloy. b Free energy profiles of stepwise $H z O R$ on different facets of $N i_{3}C o$ alloy. Inset is the corresponding structural evolution of reaction intermediates adsorbed on the (100) facet of $N i_{3}C O$ . Adsorption capability of (c) water or (d) hydrazine on NiCo@C/MXene or ${\\mathsf{N i C o@C}}$ e The contact angels of water $\\mathtt{\\backslash C A}_{\\mathrm{water}})$ and bubble 1 $\\mathsf{\\langle C A_{b u b b l e}\\rangle}$ on NiCo@C/MXene/CF or ${\\mathsf{N i C o@C/C F}}$ , and the optical images of gas bubbles released from both electrodes during HER. Scale bars: $500\\upmu\\mathrm{m}$ . f Chronopotentiometric curves of NiCo@C/MXene/CF and $N i C o@C/C F$ for hybrid seawater electrolysis. g Schematic illustration of the electrocatalytic enhancement of NiCo@C/MXene/CF at large current densities by overall enhancement in interfacial properties in terms of conductivity, robustness, water/hydrazine adsorption, and gas-releasing capability. \n\nA common feature of HzOR and HER is the intense gasreleasing characteristic. High coverage of gas bubbles on the electrode surface severely blocks the ECSA and induces high ionic diffusion resistance, causing considerably higher ohmic drop than contributed by other factors at high current densities15,45. The overpotential caused by this problem is a dominant factor limiting the water electrolysis performance at high current densities46. Besides, the bubble growth, collapse and detachment from the electrode generate large mechanical strain and stretch force to destruct the catalyst and deteriorate the cell performance47. The bubble problem is even worse for hybrid seawater splitting with intense gas releasing from both anode and cathode. This difficulty is mitigated by engineering a $\\operatorname{NiCo}\\ @\\operatorname{C}I$ MXene/CF electrode with macroporous gas transport channels and a nanoarray-based superaerophobic surface. The electrode with a huge bubble contact angle $\\mathrm{(CA_{bubble}=153~^{\\circ}}$ ) could effectively facilitate the rapid release of small gas bubbles $\\mathopen{}\\mathclose\\bgroup\\left<60-80$ $\\upmu\\mathrm{m})$ during electrolysis (Fig. 6e and Supplementary Fig. 32). This improvement is critical to maintaining a sufficient electrodeelectrolyte-gas triple-phase interface for stable operation of electrolysis under vigorous gas-releasing conditions (Fig. 6f)33,45,48. Without MXene, irregular microstructures are formed on the surface of $\\mathrm{NiCo@C/CF}$ due to poor chemical coupling between $\\operatorname{NiCo}\\ @\\operatorname{C}$ and CF (Supplementary Fig. 1i). Such structural degradation largely reduces not only the ECSA but also the aerophobic properties of the electrode (Fig. 6e and Supplementary Fig. 10). Accordingly, the NiCo@C/CF encounters huge voltage fluctuation caused by vigorous accumulation and detachment of large gas bubbles, which reduces hydrogen yielding efficiency. These results suggest that an overall enhancement in interfacial conductivity, robustness, water/hydrazine adsorption and gas-releasing capability is vital to boosting the electrocatalytic enhancement of NiCo@C/MXene/CF for hybrid seawater splitting at large current densities (Fig. 6g). \n\nIn conclusion, an efficient strategy coupling seawater reduction with thermodynamically favorable hydrazine oxidation is developed to address two extreme challenges of seawater electrolysis: the huge electricity consumption and notorious anode corrosion by chlorine chemistry. A NiCo/MXene-based electrode with superaerophobic-hydrophilic and hydrazine-friendly electrocatalytic interface is designed to fully exploit the potential of this chemistry. It allows for overall enhancement in interfacial conductivity, robustness, water/hydrazine adsorption capability and gas-releasing pattern for boosting electrolysis performance at large current densities. The hybrid seawater electrolyzer enables hydrogen production at ultralow cell voltages of $0.7\\mathrm{-}\\dot{1}.0\\mathrm{V}$ , which fully avoids the chlorine hazards on cell performance in neutral or alkaline seawater. Meanwhile, the hydrogen can be produced at an intense rate of $9.2\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{g}_{\\mathrm{cat}}{}^{-1}$ by stable seawater electrolysis for $140\\mathrm{h}$ at $500\\mathrm{mA}\\mathrm{cm}^{-2}$ with high Faradaic efficiency. The electricity expense is largely reduced by $30\\text{\\textperthousand}$ at a high current density of $500\\mathrm{mA}\\mathrm{cm}^{-\\mathrm{\\breve{2}}}$ relative to commercial alkaline water electrolysis and the state-of-the-art seawater electrolyzers. Simultaneously, rapid hydrazine degradation to a rather low residual of ${\\sim}3\\mathrm{ppb}$ can be achieved at a fast rate of $4.34\\pm0.007\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{g}_{\\mathrm{cat}}{}^{-1}$ Self-powered hybrid seawater electrolysis is also realized by integrating hydrazine fuel cells or solar cells for hydrogen production with better sustainability. Our work may show the practical impact on the efficient utilization of hydrogen reserved with unlimited abundance in the ocean for approaching carbonneutral hydrogen economy. \n\n# Methods \n\nFabrication of NiCo@C/MXene/CF. The MXene/CF was first prepared by immersing copper foam pretreated by $1.0\\mathrm{M}$ HCl into $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\boldsymbol{x}}$ MXene colloids (5 $\\mathrm{mg\\thinspacemL^{-1}},$ ), followed by drying in vacuum at $40^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ . A piece of MXene/CF $(2\\times3\\mathrm{cm}^{2})$ and 2, 6-naphthalenedicarboxylic acid dipotassium $\\mathrm{(0.2mmol)}$ were added into a aqueous solution $(25\\mathrm{mL})$ ) of Ni $(\\mathrm{CH}_{3}\\mathrm{COO})_{2}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ $\\mathrm{.0.1\\mmol},$ and Co $(\\mathrm{CH}_{3}\\mathrm{COO})_{2}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ $\\mathrm{(0.1\\mmol)}^{\\cdot}$ ). The reaction was conducted in a sealed autoclave at $80^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ . The obtained product was annealed at $400^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ at a ramp rate of $5^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ in $\\mathrm{NH}_{3}$ flow to yield NiCo@C/MXene/CF. As a control sample, the $\\operatorname{NiCo@C/CF}$ was also prepared in a similar way in the absence of MXene. The $\\mathrm{Pt/CF}$ electrode with an average mass loading of ca. $\\mathrm{i}.0\\mathrm{mg}\\mathrm{cm}^{-2}$ was also made by casting the catalyst ink $(125\\upmu\\mathrm{L})$ of commercial $20\\%$ Pt/C ( $1.0\\mathrm{mg})$ in ethanol, DI water and Nafion $(5.0~\\mathrm{wt.\\%})$ with a volume ratio of 100: 97: 3 on the CF $(1\\times1\\mathrm{cm}^{2})$ . \n\nMaterial characterization. The SEM and TEM images were taken with a fieldemission scanning electron microscopy (FEI NanoSEM 450) and transmission electron microscopy (FEI TF30). The X-ray diffraction (XRD) analysis was done on a Bruker D8 Advance X-ray spectrometer equipped with a 2D detector $\\mathrm{\\mathop{Cu}~K a,}$ $\\lambda{=}1.5406\\mathrm{\\AA}$ ). The Raman analysis was conducted on a Thermo Fisher Scientific DXR Raman microscopy using laser excitation $\\dot{\\lambda}=532\\mathrm{nm}$ ). The UV-vis analysis was performed on a UV-vis-NIR spectrometer (PerkinElmer Lambda 750). The XPS measurements were performed using Thermo ESCALAB MK II X-ray photoelectron spectrometer with C 1s $(284.6\\mathrm{eV})$ calibration. The weight ratio of the elements in the sample was determined by inductively coupled plasma optical emission spectroscopy (ICP-OES, Optima 2000DV, PerkinElmer). The water contact angle was measured by using a contact angle goniometer (SL150E, USA KINO). The contact angle of the gas bubble in the electrolyte was measured using the OCA21 Dataphysics instrument via the captive-bubble method controlled bubble volume to $2\\upmu\\mathrm{L}$ . The optical images of gas bubbles were recorded by a highspeed CCD camera (i-SPEED 3, AOS Technologies) equipped with an optical microscope (SZ-CTC, OLYMPUS). The water/hydrazine adsorption capability was measured by a QCM 200 electrochemical quartz crystal microbalance (EQCM). The XAFS analysis was conducted in Shanghai Synchrotron Radiation Facility (SSRF). \n\nHalf-cell HzOR test. The tests were conducted on a $\\mathrm{CHI}760\\mathrm{E}$ electrochemical workstation with a standard three-electrode system. The as-prepared samples were directly used as the working electrode with an average $\\operatorname{NiCo}\\ @\\operatorname{C}$ loading of ca. $1.0\\mathrm{mg}\\mathrm{cm}^{-2}$ , while a graphite rod and an $\\mathrm{Ag/AgCl}$ electrode (saturated with KCl solution) were employed as the counter and reference electrode, respectively. The electrolyte was $1.0\\mathrm{M}$ KOH containing $0.5{\\mathrm{M}}{}$ hydrazine. All the tests were maintained in Ar-saturated electrolyte throughout the test period. The linear sweep voltammetry (LSV) curves were recorded from $-1.2$ to $-0.5\\mathrm{V}$ (vs. $\\mathrm{Ag/AgCl})$ at a scan rate of $10\\mathrm{mVs^{-1}}$ . Accelerated durability tests were conducted through continuous potential cycling ranged from $-1.2$ to $-0.5\\mathrm{V}$ (vs. $\\mathrm{Ag/AgCl})$ ) at a scan rate of $50\\mathrm{mVs^{-1}}$ . Chronopotentiometric tests were recorded by applying a current density of $100\\mathrm{mAcm}^{-2}$ . The AC impedance measurements were carried out at a potential of $-0.9\\mathrm{V}$ (vs. $\\mathrm{Ag/AgCl)}$ in a frequency range from $100\\mathrm{kHz}$ to $1\\:\\mathrm{Hz}$ by applying an AC voltage with $5\\mathrm{mV}$ amplitude. All potentials measured were converted to the value against RHE according to the equation: \n\n$$\nE_{R H E}=E_{A g/A g C l}+0.059\\times p H+0.197\n$$ \n\nAll the measurements were performed with $i R$ compensation except for the chronopotentiometric tests. \n\nHalf-cell HER test. The HER tests were conducted by using a similar electrode configuration and workstation with HzOR measurement. The electrolyte was $1.0\\mathrm{M}$ KOH or seawater containing $1.0\\mathrm{M}$ KOH or neutral seawater. For HER in seawater, natural seawater with $\\mathrm{pH}8.3$ was collected from the Bohai Sea (Dalian, China), which was filtered to remove visible impurities before use. All the tests were maintained in Ar-saturated electrolyte throughout the test period. The LSV curves were performed from $-0.9$ to $-1.6\\mathrm{V}$ (vs. $\\mathrm{\\Ag/AgCl)}$ at a scan rate of $10\\mathrm{mVs^{-1}}$ . The AC impedance measurements were carried out at an overpotential of $200\\mathrm{mV}$ over the frequency range of $100\\mathrm{kHz}$ to $1\\mathrm{Hz}$ and an amplitude of $5\\mathrm{mV}$ . Accelerated durability tests were performed in a potential range of $-0.9$ to $-1.5\\mathrm{V}$ (vs. $\\mathrm{Ag/AgCl)}$ at a scan rate of $50\\mathrm{mVs^{-1}}$ . Chronoamperometric measurement was conducted at a controlled overpotential. All potentials measured were converted to the value against RHE according to Eq. (1). All the measurements were performed with iR compensation except for the chronoamperometric tests. \n\nAssembly and tests of HSE. The hybrid seawater electrolyzer was assembled by using a homemade two-electrode flow cell with NiCo@C/MXene/CF with the same area as the identical anode and cathode. The seawater containing $1.0\\mathrm{M}$ KOH or neutral seawater was used as the catholyte while $1.0\\mathrm{M}$ KOH with $0.5{\\mathrm{M}}{}$ hydrazine was fed as the anolyte, which were cycled by the peristaltic pumps (Longer, BT100- 2J). The cathode and anode chambers were separated by an anion exchange membrane (Fumasep FAA-3-PK-130). The electrolysis tests were performed on a CHI 760E electrochemical workstation. The polarization curves were measured at a scan rate of $10\\mathrm{mVs^{-1}}$ with $i R$ compensation. The stability test was carried out at the controlled current densities. The gas products from the cells were collected and examined by gas chromatography (GC, Agilent Technologies 7890 N). Meanwhile, the theoretical amount of evolved gas can be calculated by the equation: \n\n$$\nN=I\\times t/(n\\times F)\n$$ \n\nwhere the $N$ is the theoretical amount (mol) of evolved gas after electrolysis for a certain time $\\mathbf{\\eta}(t)$ at a fixed current $(I)$ , $n$ is the number of electrons transferred $\\scriptstyle\\cdot n=2$ for HER, $n=4$ for HzOR), $F$ is the Faraday constant $(96485{\\mathrm{C}}{\\mathrm{mol}}^{-1})_{,}$ . The Faradaic efficiency (FE) can be estimated according to the ratio of the measured to the theoretical gas amount. \n\nMeasurement of hydrazine degradation rate. The hydrazine content in the electrolyte was determined by the Watt and Chrisp method49. A mixture of para(dimethylamino) benzaldehyde $(5.99\\:\\mathrm{g})$ , concentrated HCl $(30~\\mathrm{mL})$ and ethanol $\\mathrm{300mL},$ was used as the color reagent. During electrolysis, a part of the anolyte was periodically collected and quantitatively diluted with a stock solution of $1.0\\mathrm{M}$ HCl $\\mathrm{\\Omega}_{\\mathrm{\\cdot}10\\mathrm{mL}})$ , followed by adding the color reagent $(5\\mathrm{mL})$ under stirring for 20 min. The hydrazine concentration was determined by the UV-vis spectrum of the obtained solution at $\\lambda=457\\mathrm{nm}$ . The concentration-absorbance curve was calibrated using a standard solution containing hydrazine monohydrate with a series of concentrations in $1.0\\mathrm{M}\\mathrm{KOH}$ by a correlation of $y=1.3037\\ x+0.0014$ ( $R^{2}=$ 0.9999). The removal rate $(k)$ of hydrazine was calculated by the equation: \n\n$$\nk=(a_{0}-a_{t})/(m\\times t)\n$$ \n\nwhere $a_{0}$ and $a_{\\mathrm{t}}$ are the initial and final amount of hydrazine after electrolysis for a certain time $\\mathbf{\\rho}(t)$ , and $m$ is the mass loading of ${\\mathrm{NiCo@C~}}($ (g). \n\nAssembly of the self-powered hydrogen production systems. The direct hydrazine fuel cell was built by using NiCo@C/MXene/CF as the anode and $20\\%$ $\\mathrm{Pt/C}$ loaded on carbon paper as the cathode. Two electrodes were separated with a Nafion 117 membrane. The catholyte was $\\mathrm{O}_{2}$ -saturated 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and the anolyte was $1.0\\mathrm{M}$ KOH containing 0.5 M $\\mathrm{N}_{2}\\mathrm{H}_{4}$ that were fed into the cell at a flow rate of $10\\mathrm{mL}\\mathrm{min}^{-1}$ . This fuel cell was connected to the above HSE for constructing a self-powered hydrogen production system with hydrazine as the sole fuel consumable. The total efficiency (TE, $\\%$ ) of this system was estimated by the equation: \n\n$$\nT E={N_{H2}}/{(2\\times{N_{N2H4}})}\n$$ \n\nwhere $N_{\\mathrm{N2H4}}$ and $N_{{\\mathrm{H}}2}$ are the amount of hydrazine consumed (mol) and $\\mathrm{H}_{2}$ produced (mol), respectively. The solar-powered hydrogen production system was built by connecting such electrolyzer to a commercial Si solar cell $(8\\times11{\\mathrm{~cm}}^{2}$ , 1 W) powered by simulated sunlight (AAA solar simulator, $94032\\mathrm{A}$ , Newport, US) or natural solar light. The Keithley 2450 source meter and multimeter were used to measure the current and voltage in the circuit, respectively. \n\n# Data availability \n\nSource data are provided with this paper. Extra data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper. \n\nReceived: 4 March 2021; Accepted: 23 June 2021; Published online: 07 July 2021 \n\n# References \n\n1. Chu, S. & Majumdar, A. Opportunities and challenges for a sustainable energy future. Nature 488, 294–303 (2012). \n2. International Renewable Energy Agency (IRENA). Hydrogen from renewable power: technology outlook for the energy transition (2018). \n3. Hu, C., Zhang, L. & Gong, J. Recent progress made in the mechanism comprehension and design of electrocatalysts for alkaline water splitting. Energy Environ. Sci. 12, 2620–2645 (2019). \n4. Tiwari, J. N. et al. Multi-heteroatom-doped carbon from waste-yeast biomass for sustained water splitting. Nat. Sustain. 3, 556–563 (2020). \n5. Zhang, L. et al. Beyond platinum: defects abundant $\\mathrm{CoP}_{3}/\\mathrm{Ni}_{2}\\mathrm{P}$ heterostructure for hydrogen evolution electrocatalysis. Small Sci. 1, 2000027 (2021). \n6. Bennett, J. E. Electrodes for generation of hydrogen and oxygen from seawater. Int. J. Hydrog. Energy 5, 401–408 (1980). \n7. Tong, W. et al. Electrolysis of low-grade and saline surface water. Nat. Energy 5, 367–377 (2020). \n8. Hsu, S. et al. An earth-abundant catalyst-based seawater photoelectrolysis system with $17.9\\%$ solar-to-hydrogen efficiency. Adv. Mater. 30, 1707261 (2018). \n9. Kuang, Y. et al. Solar-driven, highly sustained splitting of seawater into hydrogen and oxygen fuels. Proc. Natl Acad. Sci. USA 116, 6624–6629 (2019). \n10. Zhao, Y. et al. Charge state manipulation of cobalt selenide catalyst for overall seawater electrolysis. Adv. Energy Mater. 8, 1801926 (2018). \n11. Yu, L. et al. Non-noble metal-nitride based electrocatalysts for highperformance alkaline seawater electrolysis. Nat. Commun. 10, 5106 (2019). \n12. Gayen, P., Saha, S. & Ramani, V. Selective seawater splitting using pyrochlore electrocatalyst. ACS Appl. Energy Mater. 3, 3978–3983 (2020). \n13. Dresp, S. et al. Efficient direct seawater electrolysers using selective alkaline NiFe-LDH as OER catalyst in asymmetric electrolyte feeds. Energy Environ. Sci. 13, 1725–1729 (2020). \n14. Yu, L. et al. Ultrafast room-temperature synthesis of porous S-doped Ni/Fe (oxy)hydroxide electrodes for oxygen evolution catalysis in seawater splitting. Energy Environ. Sci. 13, 3439–3446 (2020). \n15. Kou, T., Wang, S. & Li, Y. Perspective on high-rate alkaline water splitting. ACS Mater. Lett. 3, 224–234 (2021). \n16. Zhang, J.-Y. et al. Anodic hydrazine oxidation assists energy-efficient hydrogen evolution over a bifunctional cobalt perselenide nanosheet electrode. Angew. Chem. Int. Ed. 57, 7649–7653 (2018). \n17. Lagadec, M. F. & Grimaud, A. Water electrolysers with closed and open electrochemical systems. Nat. Mater. 19, 1140–1150 (2020). \n18. Zhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n19. Yu, M. et al. A hierarchically porous and hydrophilic 3D nickel-iron/MXene electrode for accelerating oxygen and hydrogen evolution at high current densities. Nano Energy 63, 103880 (2019). \n20. You, B. & Sun, Y. Innovative strategies for electrocatalytic water splitting. Acc. Chem. Res. 51, 1571–1580 (2018). \n21. Tong, Y. et al. Oxygen vacancies confined in nickel molybdenum oxide porous nanosheets for promoted electrocatalytic urea oxidation. ACS Catal. 8, 1–7 (2018). \n22. Li, Y., Wei, X., Chen, L., Shi, J. & He, M. Nickel-molybdenum nitride nanoplate electrocatalysts for concurrent electrolytic hydrogen and formate productions. Nat. Commun. 10, 5335 (2019). \n23. Yin, P.-F. et al. Synthesis of palladium-based crystalline@amorphous coreshell nanoplates for highly efficient ethanol oxidation. Adv. Mater. 32, 2000482 (2020). \n24. Xiong, Y. et al. Single-atom Rh/N-doped carbon electrocatalyst for formic acid oxidation. Nat. Nanotechnol. 15, 390–397 (2020). \n25. Liu, X. et al. Self-powered $\\mathrm{H}_{2}$ production with bifunctional hydrazine as sole consumable. Nat. Commun. 9, 4365 (2018). \n26. Liu, Y. et al. Manipulating dehydrogenation kinetics through dual-doping $\\mathrm{Co}_{3}\\mathrm{N}$ electrode enables highly efficient hydrazine oxidation assisting selfpowered $\\mathrm{H}_{2}$ production. Nat. Commun. 11, 1853 (2020). \n27. Wang, Z. et al. Copper-nickel nitride nanosheets as efficient bifunctional catalysts for hydrazine-assisted electrolytic hydrogen production. Adv. Energy Mater. 9, 1900390 (2019). \n28. Qian, Q. et al. Artificial heterointerfaces achieve delicate reaction kinetics towards hydrogen evolution and hydrazine oxidation catalysis. Angew. Chem. Int. Ed. 60, 5984–5993 (2021). \n29. Tang, C. et al. Energy-saving electrolytic hydrogen eeneration: ${\\mathrm{Ni}}_{2}{\\mathrm{P}}$ nanoarray as a high-performance non-noble-metal electrocatalyst. Angew. Chem. Int. Ed. 56, 842–846 (2017). \n30. Beitollahi, H. et al. Recent advances in applications of voltammetric sensors modified with ferrocene and its derivatives. ACS Omega 5, 2049–2059 (2020). \n31. Xu, J. et al. Organic wastewater treatment by a single-atom catalyst and electrolytically produced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Nat. Sustain. 4, 233–241 (2021). \n32. Xu, W., Lu, Z., Sun, X., Jiang, L. & Duan, X. Superwetting electrodes for gasinvolving electrocatalysis. Acc. Chem. Res. 51, 1590–1598 (2018). \n33. Li, H. et al. Systematic design of superaerophobic nanotube-array electrode comprised of transition-metal sulfides for overall water splitting. Nat. Commun. 9, 2452 (2018). \n34. Anasori, B., Lukatskaya, M. R. & Gogotsi, Y. 2D metal carbides and nitrides (MXenes) for energy storage. Nat. Rev. Mater. 2, 16098 (2017). \n35. Zhang, M. et al. Highly efficient $\\mathrm{H}_{2}$ production from $\\mathrm{H}_{2}\\mathrm{S}$ via a robust grapheneencapsulated metal catalyst. Energy Environ. Sci. 13, 119–126 (2020). \n36. Song, F. et al. Interfacing nickel nitride and nickel boosts both electrocatalytic hydrogen evolution and oxidation reactions. Nat. Commun. 9, 4531 (2018). \n37. Liu, S. et al. Metal-organic-framework-derived hybrid carbon nanocages as a bifunctional electrocatalyst for oxygen reduction and evolution. Adv. Mater. 29, 1700874 (2017). \n38. Zheng, Y.-R. et al. Doping-induced structural phase transition in cobalt diselenide enables enhanced hydrogen evolution catalysis. Nat. Commun. 9, 2533 (2018). \n39. Fan, Z. & Xiao, W. Electrochemical splitting of methane in molten salts to produce hydrogen. Angew. Chem. Int. Ed. 60, 7664–7668 (2021). \n40. Feng, G. et al. Atomically ordered non-precious $\\mathrm{Co}_{3}\\mathrm{Ta}$ intermetallic nanoparticles as high-performance catalysts for hydrazine electrooxidation. Nat. Commun. 10, 4514 (2019). \n41. Shahzad, F., Iqbal, A., Kim, H. & Koo, C. M. 2D transition metal carbides (MXenes): applications as an electrically conducting material. Adv. Mater. 32, 2002159 (2020). \n42. Naguib, M., Mochalin, V. N., Barsoum, M. W. & Gogotsi, Y. $25^{\\mathrm{th}}$ anniversary article: MXenes: a new family of two-dimensional materials. Adv. Mater. 26, 992–1005 (2014). \n43. Wu, X. et al. Engineering multifunctional collaborative catalytic interface enabling efficient hydrogen evolution in all $\\mathrm{\\tt{pH}}$ range and seawater. Adv. Energy Mater. 9, 1901333 (2019). \n44. Luo, Z. et al. Reactant friendly hydrogen evolution interface based on dianionic $\\mathbf{MoS}_{2}$ surface. Nat. Commun. 11, 1116 (2020). \n45. Luo, Y. et al. Manipulating electrocatalysis using mosaic catalysts. Small Sci. 1, 2000059 (2021). \n46. Lu, Z. et al. Ultrahigh hydrogen evolution performance of under-water “superaerophobic” $\\mathbf{MoS}_{2}$ nanostructured electrodes. Adv. Mater. 26, 2683–2687 (2014). \n47. Song, Q. et al. General strategy to optimize gas evolution reaction via assembled striped-pattern superlattices. J. Am. Chem. Soc. 142, 1857–1863 (2020). \n48. Yu, X. et al. “Superaerophobic” nickel phosphide nanoarray catalyst for efficient hydrogen evolution at ultrahigh current densities. J. Am. Chem. Soc. 141, 7537–7543 (2019). \n49. Watt, G. W. & Chrisp, J. D. Spectrophotometric method for determination of hydrazine. Anal. Chem. 24, 2006–2008 (1952). \n\n# Acknowledgements \n\nWe sincerely thank Dr. Wenxin Chen at the Beijing Institute of Technology for his kind help on XAFS analysis. This work was supported by the National Natural Science Foundation of China (NSFC, No. 51772040, 51972040, 51522203), Talent Program of Liaoning (No. XLYC1807032), Innovation Program of Dalian City (No. 2018RJ04) and the Fundamental Research Funds for the Central Universities (No. DUT20TD203, DUT20LAB307). \n\n# Author contributions \n\nZ.Y.W., F.S., and J.S.Q. (Prof. Jieshan Qiu) conceived the idea and co-wrote the paper. F.S. and J.S.Q. (Ms. Jingshan Qin) performed the experiments and theoretical calculations. M.Z.Y. and X.H.W. helped with the material characterization. Z.Y.W., X.M.S., and J.S.Q. (Prof. Jieshan Qiu) guided all aspects of the work. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\nAdditional information Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-24529-3. \n\nCorrespondence and requests for materials should be addressed to Z.W., X.S. or J.Q. \n\nPeer review information Nature Communications thanks Sayan Bhattacharyya, Pralay Gayen and other, anonymous, reviewers for their contributions to the peer review of this work. Peer review reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2021 " + }, + { + "id": "10.1007_s40820-020-00580-5", + "DOI": "10.1007/s40820-020-00580-5", + "DOI Link": "http://dx.doi.org/10.1007/s40820-020-00580-5", + "Relative Dir Path": "mds/10.1007_s40820-020-00580-5", + "Article Title": "Electrospinning of Flexible Poly(vinyl alcohol)/MXene nullofiber-Based Humidity Sensor Self-Powered by Monolayer Molybdenum Diselenide Piezoelectric nullogenerator", + "Authors": "Wang, DY; Zhang, DZ; Li, P; Yang, ZM; Mi, QA; Yu, LD", + "Source Title": "nullO-MICRO LETTERS", + "Abstract": "Two-dimensional material has been widely investigated for potential applications in sensor and flexible electronics. In this work, a self-powered flexible humidity sensing device based on poly(vinyl alcohol)/Ti3C2Tx (PVA/MXene) nullofibers film and monolayer molybdenum diselenide (MoSe2) piezoelectric nullogenerator (PENG) was reported for the first time. The monolayer MoSe2-based PENG was fabricated by atmospheric pressure chemical vapor deposition techniques, which can generate a peak output of 35 mV and a power density of 42 mW m(-2). The flexible PENG integrated on polyethylene terephthalate (PET) substrate can harvest energy generated by different parts of human body and exhibit great application prospects in wearable devices. The electrospinned PVA/MXene nullofiber-based humidity sensor with flexible PET substrate under the driven of monolayer MoSe2 PENG, shows high response of similar to 40, fast response/recovery time of 0.9/6.3 s, low hysteresis of 1.8% and excellent repeatability. The self-powered flexible humidity sensor yields the capability of detecting human skin moisture and ambient humidity. This work provides a pathway to explore the high-performance humidity sensor integrated with PENG for the self-powered flexible electronic devices.", + "Times Cited, WoS Core": 366, + "Times Cited, All Databases": 381, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000609817400002", + "Markdown": "# Electrospinning of Flexible Poly(vinyl alcohol)/ MXene Nanofiber‑Based Humidity Sensor Self‑Powered by Monolayer Molybdenum Diselenide Piezoelectric Nanogenerator \n\nReceived: 23 September 2020 \nAccepted: 1 December 2020 \n$\\circledcirc$ The Author(s) 2021 \n\nDongyue Wang1, Dongzhi Zhang1 \\*, Peng Li2 \\*, Zhimin Yang1, Qian $\\mathbf{M}\\mathbf{i}^{1}$ , Liandong Yu1 \\* \n\n# HIGHLIGHTS \n\n•\t A flexible piezoelectric nanogenerator (PENG) based on 2D single-layer $\\mathbf{MoSe}_{2}$ flake on polyethylene terephthalate was fabricated. \n•\t A high-performance flexible poly(vinyl alcohol)/MXene (PVA/MXene)-based humidity sensor was fabricated by electrospinning. \n•\t The PVA/MXene composite-based humidity sensor was self-powered by $\\mathrm{MoSe}_{2}$ PENG and exhibited excellent properties. \n\nABSTRACT  Two-dimensional material has been widely investigated for potential applications in sensor and flexible electronics. In this work, a self-powered flexible humidity sensing device based on poly(vinyl alcohol) $/\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ (PVA/ MXene) nanofibers film and monolayer molybdenum diselenide $(\\mathrm{MoSe}_{2})$ piezoelectric nanogenerator (PENG) was reported for the first time. The monolayer $\\mathbf{MoSe}_{2}$ -based PENG was fabri \n\n![](images/a299e7eaeeda7b03ffc430810a06ab02de1d69664ad13d2056d49fcdbcc6cb4e.jpg) \n\ncated by atmospheric pressure chemical vapor deposition techniques, which can generate a peak output of $35\\mathrm{mV}$ and a power density of $42\\mathrm{mW}\\mathrm{m}^{-2}$ . The flexible PENG integrated on polyethylene terephthalate (PET) substrate can harvest energy generated by different parts of human body and exhibit great application prospects in wearable devices. The electrospinned PVA/MXene nanofiber-based humidity sensor with flexible PET substrate under the driven of monolayer $\\mathbf{MoSe}_{2}$ PENG, shows high response of $\\sim40$ , fast response/recovery time of $0.9/6.3\\mathrm{~s~}$ , low hysteresis of $1.8\\%$ and excellent repeatability. The self-powered flexible humidity sensor yields the capability of detecting human skin moisture and ambient humidity. This work provides a pathway to explore the high-performance humidity sensor integrated with PENG for the self-powered flexible electronic devices. \n\nKEYWORDS  Self-powered sensing; Monolayer molybdenum diselenide; Piezoelectric nanogenerator; Humidity sensor; Flexible electronics \n\n# 1  Introduction \n\nHumidity sensor has become increasingly indispensable in many areas such as industrial manufacture, medical health, and air  quality  monitoring, especially in the Internet of Things and flexible electronics [1]. At present, many kinds of signal detection technique have been developed and applied to humidity detection, including capacitance [2], quartz crystal microbalance [3], bulk acoustic wave (BAW) [4], and surface acoustic wave (SAW) [5]. However, these detection techniques all require complex detection equipment and power source, which increases application cost and energy consumption. The traditional method is using the batteries to drive humidity sensors to work, which limits the wide range of application for sensors in Internet of Things. Usually, a small amount of power can make most types of sensors operate [6]. In view of the large amount of available clean energy existing in the surrounding environment or human body, we can harvest these energies to build sustaining self-powered sensing system [7–9]. Therefore, it is expected to develop a simple and low-cost humidity sensing system without external power supply through self-powered technology [10, 11]. \n\nThe latest technologies for collecting energy mainly include piezoelectricity [12, 13], triboelectricity [14–17], pyroelectricity [18], photoelectricity [19], and electromagnetism [20]. Among these technologies, nanogenerator based on triboelectricity and piezoelectricity is considered to have excellent application prospects due to its high durability and mechanical stability, especially in the field of self-powered sensors [21]. A piezoelectric nanogenerator (PENG) prepared from zinc oxide nanowires was first reported by Wang et al. in 2006, which gained great concern because of its excellent piezoelectric performance [22]. Liu et al. designed a self-powered multifunctional monitoring system using hybrid integrated triboelectric and piezoelectric microsensors, which can effectively monitor the relative humidity (RH) level and carbon dioxide concentration [23]. Zhang et al. reported a novel self-recovering triboelectric nanogenerator (TENG) as an active multifunctional sensor. The device has a wide humidity detection range $20\\%-100\\%$ RH) and rapid response/recovery time ( $18/80~\\mathrm{ms})$ [24]. Xia et al. designed a conductive copper tape-based TENG combined with LiCl for humidity detection. The TENG has a power density of $240.1\\upmu\\mathrm{W}\\mathrm{cm}^{-2}$ , and the RH can be represented by the brightness of the LEDs driven by the TENG [25]. Tai et al. developed an air-driven triboelectric nanogenerator based on Ce-doped ZnO-PANI, which was used to detect the $\\mathrm{NH}_{3}$ concentration, flow rate, and frequency of exhaled gas [26]. Many new nanomaterials with excellent piezoelectric properties were continuously studied. Monolayer boron nitride (BN), $\\mathbf{MoS}_{2}$ , $\\mathbf{MoSe}_{2}$ , $\\mathbf{WTe}_{2}$ , $\\mathsf{W S e}_{2}$ , and $\\mathbf{MoTe}_{2}$ have been theoretically predicted to exhibit piezoelectric property [27]. And it has been experimentally confirmed that single-layer $\\mathbf{MoS}_{2}$ showed piezoelectric effect and was applied to PENG [28, 29]. \n\nIn recent years, two-dimensional (2D) nanomaterials such as graphene, metal oxides, transition metal dichalcogenides (TMDs), metal organic frameworks (MOFs), black phosphorus have attracted tremendous interests due to their excellent physical, chemical, and electrical properties. Especially, 2D nanomaterials have been employed in constructing high-performance sensors and flexible electronic devices [30, 31]. In 2011, MXene was first synthesized by Yury et al. [32]. As a new 2D nanomaterial, MXene exhibits high specific surface area, high conductivity, and excellent flexibility, which is considered to have great application prospects in humidity and wearable sensors. Lu et al. found alkalized MXene exhibited much better sensing properties toward $\\mathrm{NH}_{3}$ and humidity, compared with untreated MXene [33]. Due to excellent metal conductivity and hydrophilicity, MXene not only exhibits more excellent gas and humidity sensing properties, but also a very promising material for building flexible sensors to provide excellent mechanical stimulus sensing performance. Wang et al. reported a piezoresistive flexible sensor prepared by MXene/natural microcapsule, which has a fast response time ( $\\mathrm{14~ms},$ , satisfactory repeatability, and stability [34]. \n\nIn this work, a self-powered flexible humidity sensor based on electrospinned poly (vinyl alcohol) $/\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ (PVA/ MXene) nanofibers film and monolayer molybdenum diselenide $\\mathrm{(MoSe}_{2})$ piezoelectric nanogenerator was reported for the first time. The monolayer $\\mathrm{MoSe}_{2}$ PENG was fabricated on a flexible polyethylene terephthalate (PET) substrate. The PVA/MXene nanofibers film was prepared on the interdigital electrodes (IDEs) as the humidity-sensitive material through electrospinning technology. The prepared self-powered piezoelectric humidity sensor (PEHS) was driven by the monolayer $\\mathbf{MoSe}_{2}$ PENG via converting mechanical energy to electric energy. The self-powered PVA/MXene nanofibers film humidity sensor has a large response, fast response/ recovery time, low hysteresis, and excellent repeatability. Furthermore, the humidity sensing mechanism of PVA/ MXene sensor was explored. \n\n# 2  \u0007Experiment \n\n# 2.1  \u0007Materials \n\nHydrochloric acid (HCl, analytical purity) and lithium f luoride (LiF, $99\\%$ ) were purchased from Sinopharm \n\nChemical Reagent. Titanium aluminum carbide powders $(\\mathrm{Ti}_{3}\\mathrm{AlC}_{2})$ ) and poly (vinyl alcohol) (PVA) were from Shanghai Macklin Biochemical Technology. \n\n# 2.2  \u0007Materials Synthesis \n\nSynthesis of MXene: LiF ${\\bf(1\\cdot g)}$ was dispersed in a polypropylene plastic bottle with $6\\:\\mathrm{M\\:HCl}$ solution $(20~\\mathrm{mL})$ and then was stirred for $5\\mathrm{min}$ to ensure a fully dissolution. One gram of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ was added slowly to the mixed solution to avoid violent reaction of the solution, followed by placed at \n\n![](images/bc454c73bd717d87cabd0526d52e6b9b857c3078ac980fd3a235eae1dfbedf56.jpg) \nFig. 1   Schematic diagram for the fabrication of a $\\mathrm{MoSe}_{2}$ -flake-based PENG and b PVA/MXene humidity sensor. c Schematic of the experimental platform for humidity sensing measurement. d Monolayer $\\mathrm{MoSe}_{2}$ prepared by APCVD. e Optical microscope image of a $\\mathrm{MoSe}_{2}$ piezoelectric device with two electrodes. f Photograph of the flexible PENG device \n\n$35^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ . The product after reaction was washed with deionized water several times until the $\\mathrm{pH}$ of supernatant is greater than or equal to 6. And then, the product was treated via centrifugation at $3500\\mathrm{rpm}$ for $5\\mathrm{min}$ , and the dark green supernatant collected as delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ . \n\nPreparation of $\\mathrm{PVA}/\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ mixed suspensions: Electrospinning is a typical fiber manufacturing process that can produce fibrous nanofilms with larger specific surface area [35, 36]. One gram of PVA was placed in $9\\ \\mathrm{g}$ of deionized water to obtain $10\\%$ (w/w) PVA solution. The solution was stirred for $3\\mathrm{~h~}$ at $90~^{\\circ}\\mathrm{C}$ . Then, the PVA/ MXene solution was prepared by adding $0.1\\mathrm{\\g}$ of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ into PVA solution and magnetic stirring for about $0.5\\mathrm{h}$ . \n\n# 2.3  \u0007Fabrication of the PENG and PEHS \n\nMonolayer $\\mathrm{MoSe}_{2}$ flake was employed for the fabrication of the PENG. Figure 1a shows the schematic diagram for the fabrication of PENG. The electrodes were prepared by photolithography, metal deposition ( $10\\mathrm{{nm}C r/100\\mathrm{{nm}A u}}$ , and lift-off process. As shown in Fig. 1d, e, the monolayer $\\mathbf{MoSe}_{2}$ prepared by atmospheric pressure chemical vapor deposition (APCVD) method was transferred to flexible PET substrate and exhibits irregular hexagon, followed by packaging with polydimethylsiloxane (PDMS) film. The white dots in the middle are the centers of the crystal nucleus. The monolayer $\\mathbf{MoSe}_{2}$ on PET is sealed by PDMS film, which is isolated from the external environment to avoid the influence of environment humidity. Figure 1f shows the photograph of the flexible PENG device. The monolayer $\\mathbf{MoSe}_{2}$ flakes connected with Au electrodes along with armchair are performed. And the $\\mathbf{MoSe}_{2}$ atomic orientation was identified by optical second harmonic generation (SHG) as in Fig. S1. \n\nAs shown in Fig. 1b, the humidity sensor with PVA/ MXene nanofibers film was prepared on interdigital electrodes (IDEs) with epoxy substrate using electrospinning technology. The dimension of IDEs is $\\mathrm{8}\\times8~\\mathrm{mm}^{2}$ , and the thickness is $0.3~\\mathrm{mm}$ . Electrospinning is widely used for preparing continuous nanofibers from viscoelastic fluids through electrostatic repulsion force between surface charges. Electrospinning nanofibers have the advantages of small porosity, high porosity, and large specific surface area, and are promising building blocks for the fabrication of sensors. The applied voltage between positive and negative poles was $18~\\mathrm{kV}_{:}$ and the needle-to-collector distance was $15\\mathrm{cm}$ . The flow rate is $0.3\\mathrm{mLh^{-1}}$ , and the duration is $0.5\\mathrm{h}$ . Schematic of the experimental platform for humidity sensing measurement is shown in Fig. 1c. PENG is driven by a tensile testing machine (MIT-1021). The humidity sensor was driven by PENG via converting mechanical energy into electrical energy. The humidity sensing properties were systematically investigated under a humidity range of $11-97\\%$ RH at $25~^{\\circ}\\mathrm{C}$ . The output voltage of PENG and PEHS was measured by a digital multimeter (Keysight 34470A). \n\n# 2.4  \u0007Characterization Instrument \n\nThe structure and surface morphology of the PVA/MXene nanofibers were characterized using scanning electron microscopy (SEM, Hitachi S–4800, Japan) and transmission electron microscope (TEM, Jeoljem-2100, Japan). The X-ray diffractometer (XRD, Rigaku Miniflex 600) with $\\mathrm{CuK}\\upalpha$ radiation $(\\lambda=0.15418\\mathrm{nm})$ was used to investigate its crystal structure. The $\\mathrm{MoSe}_{2}$ atomic layer was characterized by confocal Raman microscopy (Horiba HR–800) with a laser wavelength of $514\\mathrm{nm}$ . Fourier transform infrared spectroscopy (FTIR) spectra were recorded using a PerkinElmer Spectrum Two FTIR spectrometer. \n\n# 3  \u0007Results and Discussion \n\n# 3.1  \u0007Fundamental Measurement of PENG \n\nThe thickness of monolayer $\\mathbf{MoSe}_{2}$ was identified by AFM. Figure 2a shows the AFM topographic image of the hexagon-like-shaped monolayer $\\mathbf{MoSe}_{2}$ flake, and Fig. 2b exhibits the corresponding height profile, which is about $0.8\\ \\mathrm{nm}$ for the monolayer $\\mathbf{MoSe}_{2}$ structure [37]. Figure 2c shows the characterization result using Raman spectrum. The prepared $\\mathbf{MoSe}_{2}$ has two major characteristic peaks at 239.7 and $289.7\\mathrm{cm}^{-1}$ , which are corresponding to the out-of-plane $\\mathbf{A}_{1\\mathrm{g}}$ and in-plane $\\mathrm{E}_{2\\mathrm{g}}$ modes, respectively [38]. Figure 2d shows the operation scheme of the $\\mathrm{MoSe}_{2}$ piezoelectric device. No induced charge was generated at both ends of the $\\mathbf{MoSe}_{2}$ flake in the initial state. When the PENG was stretched, a monolayer of $\\mathbf{MoSe}_{2}$ would generate charges with opposite polarities at its edges. When the PENG was released, reverse electron flow resulted in a negative voltage peak. Periodic stretching and releasing can cause PENG produces alternating positive and negative voltage output signals (Video S1). The piezoelectric output of a $\\mathbf{MoSe}_{2}$ PENG is related to the magnitude of the applied strain. Figure 2e shows the relationship between open-circuit voltages and the strain of the device. The strain was defined as Eq. (1) [29]: \n\n![](images/5c80ff670cfa2628dcf28425b0fc98226fee9d3810ee3caf593866166c394e5b.jpg) \nFig. 2   a AFM topographic image of the single-layer $\\mathrm{MoSe}_{2}$ flake. b Relative heights along the white lines in Fig. 2a. c Raman spectrum of the monolayer $\\mathrm{MoSe}_{2}$ flake. d Operation scheme of the monolayer $\\mathrm{MoSe}_{2}$ piezoelectric device. e Open-circuit voltages of the device as a function of strain. f Real-time output voltage under $0.36\\%$ strain at a frequency of $0.5\\mathrm{Hz}$ . g Dependence of output voltage and current from a monolayer $\\mathrm{MoSe}_{2}$ device under $0.36\\%$ strain as a function of external loading resistance. h Power versus the loading resistance. i Cyclic test showing the stability of monolayer $\\mathbf{MoSe}_{2}$ device for prolonged period \n\n$$\n\\varepsilon=\\frac{h}{2R}\n$$ \n\nwhere $h$ is the thickness of the flexible substrate, $R$ is the radius of curvature when the PENG was stretched. It can be found that the output voltage rises as the degree of the applied strain increases. The output voltage can reach $55\\mathrm{mV}$ at strain of $0.6\\%$ , which is much higher than monolayer $\\mathbf{MoS}_{2}$ PENG [28]. Figure 2f shows the real-time output voltage $(35\\mathrm{mV})$ under $0.36\\%$ strain at a frequency of $0.5\\mathrm{Hz}$ . As shown in Fig. S2, PENG is bent at different frequencies. The bending frequency has little effect on the voltage output of PENG. In subsequent experiments, we apply strain of $0.36\\%$ to avoid $\\mathbf{MoSe}_{2}$ slippage. \n\nTable 1   Performance of the $\\mathrm{MoSe}_{2}$ PENG in this work compared with the previous work \n\n\n
Piezoelectric materialOpen-circuit voltage (mV)Short-circuit current (nA)Power density (mW m-2)Refs.
ZnO NRs2.885000.08[39]
PVDF-TrFE17~~[40]
SnSz nanosheet330.181.14[41]
KNN piezo-resin/CFRP2~0.16[42]
MoS2 nanosheet150.022[28]
MoSe nanosheet350.442This paper
\n\n![](images/1e122e8899e66ab5713c864edb3e01266fd9ea51486abc52aa3d42cd78cb277b.jpg) \nFig. 3   Energy harvesting and application of $\\mathrm{MoSe}_{2}$ device on various parts of the human body a Index finger joint. B Wrist. c Finger press. d Throat. e Output voltage change of flexible PENG in terms of various sound stimuli, such as “nano,” “energy,” and “sensor.” f Neck bending. g Knee bending. h, i Human motion detection \n\nFigure $2\\mathrm{g}$ shows the output voltage and current from the PENG at $0.36\\%$ strain under different loading resistances. The output current decreases slowly in low resistance range $(1\\Omega{-}100\\mathrm{M}\\Omega)$ and then declines rapidly with the increasing load, and the voltage changes with the opposite trend. Figure 2h shows the output power under different loading resistances. The maximal output power of PENG is up to $5.37\\times10^{-9}\\mathrm{\\mW}$ at a loading resistance of $9.2\\:\\mathrm{M}\\Omega$ and a power density of about $42\\mathrm{\\mW\\m}^{-2}$ , which is higher than other kinds of PENGs (Table 1) [28, 39–42]. As shown in Fig. 2i, the cyclic test shows the good stability of PENG for prolonged period and indicates that the energy conversion is stable. \n\n# 3.2  \u0007Energy Harvesting of Human Activities \n\nWe further explored the energy harvesting of $\\mathbf{MoSe}_{2}$ device on various parts of the human body. Figure 3a illustrates the energy harvesting at the knuckles (Video S2). The device is attached to the finger joint and bends with the finger. We can observe that the PENG generates different output voltages for wrist bending motions at five different angles of $0^{\\circ}$ , \n\n![](images/0aea90858b52e7e8fc6e4f22d55bb0b3a7f785b38ffb0ec843e2e55f853e0028.jpg) \nFig. 4   a SEM of MXene multilayer structure. b TEM images of few-layer MXene nanoflakes. c Corresponding selected-area electron diffraction (SAED) pattern of the hexagonal arrangement of atoms. d, e SEM images of PVA/MXene nanofibers. f Contact angle measurement of MXene and PVA/MXene. g XRD, h EDS, and i FTIR pattern of MXene, PVA, and PVA/MXene composite \n\n$15^{\\circ}$ , $30^{\\circ}$ , $45^{\\circ}$ , and $75^{\\circ}$ . When the bending degree increases, the PENG exhibits an enhanced output voltage. The similar experiment was performed with the device attached to the wrist in Fig. 3b. The bending of the wrist produces a smaller output voltage compared to finger under the same angle. This could be because the knuckles cause a greater degree of bending of flexible PET. The device was placed on a sponge and applied different pressures with fingertip. Figure 3c shows the output voltage under different pressures. The pressure can be identified by detecting the output voltage. Figure 3d shows that the device can identify swallowing action of the throat. And based on this, we detect the relative voltage change of $\\mathbf{MoSe}_{2}$ flexible device by making different kinds of sounds, such as “nano,” “energy,” and “sensor” (Fig. 3e). As shown in Fig. 3f, we also detected the output voltage based on neck bending when the device was attached to the nape. Considering that neck diseases of an increasing number of teenagers due to looking down and playing with mobile phones, this application will have great prospects in the future. Human body is mainly driven by legs to walk and run. Figure 3g–i shows the energy harvesting when the device was attached to the knee and sole of the foot; the device can stably collect the energy generated by the legs and identify different movements like walking and running. \n\n# 3.3  \u0007Characterization of PEHS \n\nFigure 4a shows the SEM of MXene multilayer structure; the small particles between layers may be the broken MXene or $\\mathrm{TiO}_{2}$ [43]. Figure 4b, c shows the TEM images of fewlayer MXene nanoflakes and the corresponding selectedarea electron diffraction (SAED) pattern of the hexagonal arrangement of atoms, respectively. The SAED exhibits the hexagonal arrangement of atoms. As shown in Fig. 4d–f, the SEM images show that the PVA/MXene nanofibers are successfully prepared. The average fiber diameter of PVA/ MXene nanofibers is $170\\mathrm{nm}$ . As shown in Fig. 2g, the water contact angles of MXene and PVA/MXene were $35.7^{\\circ}$ and $24.5^{\\circ}$ , respectively. The PVA/MXene has the minimal contact angle and exhibits excellent hydrophilicity. The XRD characterization results of PVA, MXene, PVA/MXene are illustrated in Fig. 4h. The XRD pattern of MXene shows four prominent peaks at $2\\theta=8.4^{\\circ}$ , $18.1^{\\circ}$ , $26.8^{\\circ}$ , and $60.6^{\\circ}$ , which are assigned to the (002), (006), (008), and (110) planes [32]. The XRD pattern of pure PVA shows two character peaks at $2\\uptheta=19.4^{\\circ}$ and $41.2^{\\circ}$ , which are attributed to the (101) and (220) planes [44]. And it can be found that PVA did not destroy the crystal structure of MXene from the XRD pattern of PVA/MXene. The (002) peak for PVA/MXene is downshifted from $2\\theta=8.4^{\\circ}$ to $2\\boldsymbol{\\Theta}=7.2^{\\circ}$ as compared to that of MXene; this change is considered to be due to the increase in the distance between the MXene nanosheets causing by the deposition of PVA molecules [36]. \n\n![](images/80b12ad7cff65b86ff07321a9609439c4587dfd44766e4ae978183b097245f2b.jpg) \nFig. 5   a Resistance of the MXene, PVA, and PVA/MXene film sensor exposed to various relative humidities. b Dynamic resistance changes of PVA/MXene film sensor exposed to various relative humidities. c Repeatability of PVA/MXene film sensor. d Time-dependent resistance response and recovery curves of the PVA/MXene sensor between 11 and $97\\%$ RH. e Resistance of sensor with increasing and decreasing humidity. f Humidity hysteresis curves of the PVA/MXene nanofibers film sensor \n\nFigure 4i shows energy-dispersive spectrometer (EDS) images of PVA/MXene nanofibers film. The Ti and O elements are derived from MXene and PVA, respectively, and the C element comes from both MXene and PVA. The $\\mathrm{Cu}$ is derived from copper foil substrate. The FTIR characterization results of PVA, MXene, PVA/MXene are illustrated in Fig. S4. The wide peak for all materials at about $3440\\mathrm{cm}^{-1}$ is $\\mathrm{O-H}$ stretching vibration peak. The other typical peaks of PVA are at $2930\\mathrm{cm}^{-1}$ for $\\mathrm{C-H}$ stretch, $1720\\mathrm{cm}^{-1}$ for $\\scriptstyle{\\mathrm{C=O}}$ stretch, $1631~\\mathrm{{cm}^{-1}}$ for $-C-C-$ stretch, $1095~\\mathrm{{cm}^{-1}}$ for $\\scriptstyle\\mathbf{C-O}$ stretch, respectively [45]. The other typical peaks of MXene are observed at 1710 and $550~\\mathrm{cm}^{-1}$ , which are assigned to the stretching vibration of $C{\\mathrm{-}}0$ and $\\mathrm{O-H}$ , respectively [46]. \n\nThe FTIR characterization result of PVA/MXene shows no obvious broad peak or shifts after the addition of MXene [47]. \n\n# 3.4  \u0007Humidity Sensing Properties of PEHS \n\nThe resistances of MXene, PVA, PVA/MXene sensors at different humidity levels are shown in Fig. 5a. Different humidity levels are provided by corresponding saturated salt solutions [48]. The resistance variation range $(0.08\\mathrm{-}9.2\\mathrm{M}\\Omega,$ of PVA/MXene sensor is aligned with the rising $U–R$ (voltageresistance) region of PENG (the U–R curve in Fig. 2g). The PVA sensor exhibited a high resistance state $(\\geq80\\mathbf{M}\\Omega),$ over a wide humidity range $11-52\\%$ RH), and the MXene sensor showed a small resistance change $(2.1\\mathrm{-}3.3\\mathrm{k}\\Omega,$ ), which are not conducive to the combination of the sensor and PENG as a self-powered humidity sensor. Therefore, PVA/MXene sensor driven by the prepared PENG is easier to obtain the corresponding relationship between output voltage and humidity levels. Figure 5b shows the dynamic resistance change of the PVA/MXene sensor exposed to various RHs. The response/recovery time is defined as the time when the sensor achieved $90\\%$ of total resistance variation. Figure 5c, d shows that the sensor has good repeatability and fast response/recovery time $(0.9/6.3\\ \\mathrm{s})$ , respectively. As shown in Fig. 5e, f, we investigated the hysteresis characteristic of PVA/MXene sensor versus RH. The sensor hysteresis is defined as $\\mathrm{H}{=}(R_{\\mathrm{A}}{-}R_{\\mathrm{D}})/S(\\%\\mathrm{RH}).R_{\\mathrm{A}}$ and $R_{\\mathrm{D}}$ are the sensor resistance in the adsorption and desorption process of water molecules, and S is the sensor sensitivity. We investigated the hysteresis characteristic of PVA/MXene sensor versus RH, which shows the PVA/MXene humidity sensor has low hysteresis of $1.8\\%$ . The sensor has excellent humidity sensing performance, which is attributed to the humidity sensitivity of composite material. MXene has strong hydrophilicity and high electrical conductivity. The resistance of MXene film increases with the increase in humidity level, which may be the result of the increase in layer spacing caused by water molecules embedded in the MXene layers [49, 50]. The conductivity change of PVA/MXene can be caused by the adsorption of water molecules under humidity environment. Both PVA and MXene contain a large number of hydroxyl groups (–OH), and the proton can transition between two adjacent hydroxyl groups. In addition, protons can help electron transfer between water molecules. Under low humidity level, proton-assisted electron tunneling is the main reaction process. Under high humidity level, water molecules are firmly bound to hydroxyl groups. Hydrogen ions formed by PVA adsorbed water molecules hop between water molecules. With the increase in humidity, the concentration of hydrogen ions increases, resulting in the decrease in sensor resistance. In addition, MXene can be used as the charge transmission and conduction layer of composite materials due to its excellent metallic conductivity, which is conducive to accelerating the adsorption/desorption process of water molecules. Therefore, the PVA/MXene sensor achieved a fast response/recovery behavior [51, 52]. \n\n![](images/ba62b7381441ba9cb51b692698fe28e03d812926bedb7fcfa158183207ff9017.jpg) \nFig. 6   a Response fitting curves of self-powered MXene, PVA, and PVA/MXene film sensors toward different humidities. b Output voltage for PVA/MXene-based PEHS upon exposure to different humidities. c Repeatability of self-powered PVA/MXene sensor. d Output voltage when the finger slowly approaches the sensor. e Flexible sensor is used to detect human breathing rate. f Test result of detecting the humidity of arm skin surface after different exercise times \n\nTable 2   Performance of the presented sensor in this work compared with the previous work \n\n\n
Sensor materialsMeas. rangeResponseResponse/recovery timeRefs.
RGO/PVP7-97.3%RH72.8/3.5 s (90%)[53]
LiCl40-80% RH12~[25]
Ga/ZnO45-80% RH45 s (90%)[54]
PTFE/A120-100%RH2818/80 ms (~)[24]
PVA/MXene11-97% RH400.9/6.3 s (90%)This paper
\n\nFigure 6a shows the response–humidity fitting curves of MXene, PVA, and PVA/MXene sensors at $11-97\\%$ RH. The actual voltage value is shown in Fig. S3a. The minimum value of output voltage is the reference value of the sensor response. The response of humidity sensor was defined as: $S{=}V_{\\mathrm{RH}}/V_{\\mathrm{min}}$ , where the $V_{\\mathrm{RH}}$ is the output voltage of sensor at the target humidity and the $V_{\\mathrm{min}}$ is the minimum output voltage. The PVA sensor has the same voltage output in the humidity range of $11-52\\%$ because of its large resistance, and the voltage output of MXene sensor is close to 0 because of its small resistance. The experimental results are consistent with the previous analysis results; neither PVA nor MXene sensor is suitable to combine with PENG to detect humidity. The prepared self-powered PVA/MXene sensor holds high humidity response of ${\\sim}40$ . The corresponding equation is $\\mathrm{Y}{=}42.8402{-}0.4494\\mathrm{X}$ , and the regression coefficient $(\\mathbf{R}^{2})$ is 0.9769. Figure 6b shows the output voltage for PVA/MXene nanofibers film sensor driven by PENG when sensor exposed to wide humidity range $11-97\\%$ RH). It can be seen that the output voltage exhibits highest value at $11\\%$ RH and has obvious decrease with increasing humidity. The different humidity levels can be distinguished by particular output voltage. The self-powered PVA/MXene nanofiber film sensor has excellent repeatability as in Fig. 6c. There is no obvious change in output voltage by comparing test result. And we also measured the output voltage when the finger slowly approaches the sensor as in Fig. 6d. Finger approaches the sensor at a constant speed $(0.5\\mathrm{cm\\s^{-1}},$ ) at a distance from the sensor $(6~\\mathrm{cm})$ and then leaves at the same speed. Table 2 summarizes the humidity sensing performance of the presented PEHS in comparison with previous works [24, 25, 53, 54]; the comparison highlights the PEHS has much higher response in a wide RH range. Figure S3b shows the long-term stability of PVA/MXene nanofibers film sensor driven by PENG over a period of 30 days. It can be found that the sensor has no noticeable voltage drift and exhibits excellent stability. Figure 6e shows the output voltage when the flexible sensor is used to detect human breathing rate. Figure 6f shows the test result of detecting the humidity of arm skin surface after different exercise times when the sensor is attached to the arm. The output voltages all occur regular changes. Thus, the flexible humidity sensor driven by PENG exhibits excellent performance on detecting human skin surface moisture and has great application prospects in wearable devices. \n\n# 4  \u0007Conclusions \n\nIn this work, a self-powered humidity sensing device based on monolayer $\\mathbf{MoSe}_{2}$ PENG has been proposed for the detection of humidity. The piezoelectric properties of monolayer layer $\\mathbf{MoSe}_{2}$ were reported at first time. A high peak output of $35\\mathrm{mV}$ can be obtained when the PENG was under $0.36\\%$ strain at a frequency of $0.5\\mathrm{Hz}$ . And the flexible PENG can harvest energy and generate different output voltages by attaching to different parts of human body. The self-powered sensor was prepared by PVA/MXene composite nanofibers film and driven by the monolayer $\\mathbf{MoSe}_{2}$ PENG to detect humidity by converting mechanical energy to electric energy, which has a larger response (40) and 40-fold higher than pure MXene. And the humidity sensor also shows fast response/recovery time of $0.9/6.3\\mathrm{~s~}$ , low hysteresis of $1.8\\%$ , and stable repeatability. Moreover, the PVA/MXene nanofibers film was also used to prepare flexible humidity sensor on a PET flexible substrate and exhibited excellent performance on detecting human skin surface moisture. \n\nAcknowledgements  This work was supported by the National Natural Science Foundation of China (51777215), National Natural Science Foundation of China (51775306), Beijing Municipal Natural Science Foundation (4192027), and the Graduate Innovation Fund of China University of Petroleum (YCX2020097). \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat​iveco​mmons​.org/licen​ses/by/4.0/. \n\nSupplementary Information  The online version contains supplementary material available at(https​://doi.org/10.1007/s4082 0-020-00580​-5) \n\n# References \n\n1.\t J. Cai, C. Lv, E. Aoyagi, S. Ogawa, A. Watanabe, Laser direct writing of a high-performance all-graphene humidity sensor working in a novel sensing mode for portable electronics. ACS Appl. Mater. Interfaces 10, 23987–23996 (2018). https​://doi. org/10.1021/acsam​i.8b073​73 \n2.\t B. Li, Q. Tian, H. Su, X. Wang, T. Wang et al., High sensitivity portable capacitive humidity sensor based on $\\mathrm{In}_{2}\\mathrm{O}_{3}$ nanocubesdecorated GO nanosheets and its wearable application in respiration detection. Sens. Actuat. B 299, 126973 (2019). https​:// doi.org/10.1016/j.snb.2019.12697​3 \n3.\t D. Zhing, D. Wang, P. Li, X. Zhou, X. Zong et al., Facile fabrication of high-performance QCM humidity sensor based on layer-by-layer self-assembled polyaniline/graphene oxide nanocomposite film. Sens. Actuat. B 255, 1869–1877 (2018). https​://doi.org/10.1016/j.snb.2017.08.212 \n4.\t Y. Yao, Y. Xue, Influence of the oxygen content on the humidity sensing properties of functionalized graphene films based on bulk acoustic wave humidity sensors. Sens. Actuat. B 222, 755–762 (2016). https​://doi.org/10.1016/j.snb.2015.08.121 \n5.\t Z. Xu, Y. Yuan, Implementation of guiding layers of surface acoustic wave devices: a review. Biosens. Bioelectron. 99, 500–512 (2018). https​://doi.org/10.1016/j.bios.2017.07.060 \n6.\t Y. Yang, J. Qi, Q. Liao, H. Li, Y. Wang et al., High-performance piezoelectric gate diode of a single polar-surface dominated ZnO nanobelt. Nanotechnology 20, 125201 (2009). https​://doi. org/10.1088/0957-4484/20/12/12520​1 \n7.\t Y. Yang, J. Qi, W. Guo, Y. Gu, Y. Huang et al., Transverse piezoelectric field-effect transistor based on single ZnO nanobelts. Phys. Chem. Chem. Phys. 12, 12415–12419 (2019). https​ ://doi.org/10.1039/C0CP0​0420K​ \n8.\t T. Gao, Y. Ji, Y. Yang, Thermo-phototronic effect induced electricity in long semiconducting ZnO materials for self-powered light and temperature sensors. Adv. Mater. Technol. US 5(7), 2000176 (2020). https​://doi.org/10.1002/admt.20200​0176 \n9.\t Y. Yang, W. Guo, J. Qi, Y. Zhang, Flexible piezoresistive strain sensor based on single Sb-doped ZnO nanobelts. Appl. Phys. Lett. 97, 223107 (2010). https​://doi.org/10.1063/1.35228​85 \n10.\t D. Zhang, K. Zhang, Y. Wang, Y. Wang, Y. Yang, Thermoelectric effect induced electricity in stretchable graphenepolymer nanocomposites for ultrasensitive self-powered strain sensor system. Nano Energy 56, 25–32 (2019). https​://doi. org/10.1016/j.nanoe​n.2018.11.026 \n11.\t Y. Wang, Y. Wang, Y. Yang, Graphene-polymer nanocompositebased redox-induced electricity for flexible self-powered strain sensors. Adv. Energy Mater. 8, 1800961 (2018). https​://doi. org/10.1002/aenm.20180​0961 \n12.\t K. Zhang, S. Wang, Y. Yang, A one-structure-based piezotribo-pyro-photoelectric effects coupled nanogenerator for simultaneously scavenging mechanical, thermal, and solar energies. Adv. Energy Mater. 7, 1601852 (2017). https​://doi. org/10.1002/aenm.20160​1852 \n13.\t W. Qian, W. Yang, Y. Zhang, C.R. Bowen, Y. Yang, Piezoelectric materials for controlling electro-chemical processes. Nano-Micro Lett. 12, 149 (2020). https​://doi.org/10.1007/s4082​ 0-020-00489​-z \n14.\t K. Zhao, Z.L. Wang, Y. Yang, Self-powered wireless smart sensor node enabled by an ultrastable, highly efficient, and superhydrophobic-surface-based triboelectric nanogenerator. ACS Nano 10, 9044–9052 (2016). https​://doi.org/10.1021/acsna​ no.6b058​15 \n15.\t H. Wang, Z. Xiang, P. Giorgia, X. Mu, Y. Yang et al., Triboelectric liquid volume sensor for self-powered lab-on-chip applications. Nano Energy 23, 80–88 (2016). https​://doi.org/10.1016/j. nanoe​n.2016.02.054 \n16.\t Z. Wu, W. Ding, Y. Dai, K. Dong, C. Wu et al., Self-powered multifunctional motion sensor enabled by magnetic-regulated triboelectric nanogenerator. ACS Nano 12, 5726–5733 (2018). https​://doi.org/10.1021/acsna​no.8b015​89 \n17.\t Z. Wu, B. Zhang, H. Zou, Z. Lin, G. Liu et al., Multifunctional sensor based on translational-rotary triboelectric nanogenerator. Adv. Energy Mater. 9, 1901124 (2019). https​://doi.org/10.1002/ aenm.20190​1124 \n18.\t K. Song, N. Ma, Y.K. Mishra, R. Adelung, Y. Yang, Achieving light-induced ultrahigh pyroelectric charge density toward selfpowered UV light detection. Adv. Electron. Mater. 5, 1800413 (2019). https​://doi.org/10.1002/aelm.20180​0413 \n19.\t K. Zhao, B. Ouyang, C.R. Bowen, Z.L. Wang, Y. Yang, Onestructure-based multi-effects coupled nanogenerators for flexible and self-powered multi-functional coupled sensor systems. Nano Energy 71, 104632 (2020). https​://doi.org/10.1016/j. nanoe​n.2020.10463​2 \n20.\t Y. Chen, Y. Cheng, Y. Jie, X. Cao, N. Wang et al., Energy harvesting and wireless power transmission by a hybridized electromagnetic-triboelectric nanogenerator. Energy Environ. Sci. 12, 2678–2684 (2019). https​://doi.org/10.1039/C9EE0​1245A​ \n21.\t Z. Wu, T. Cheng, Z.L. Wang, Self-powered sensors and systems based on nanogenerators. Sensors 20, 2925 (2020). https​://doi. org/10.3390/s2010​2925 \n22.\t Z.L. Wang, J. Song, Piezoelectric nanogenerators based on zinc oxide nanowire arrays. Science 312, 242–246 (2006). https​:// doi.org/10.1126/scien​ce.11240​05 \n23.\t C. Sun, Q. Shi, D. Hasan, M.S. Yazici, M. Zhu et al., Self-powered multifunctional monitoring system using hybrid integrated triboelectric nanogenerators and piezoelectric microsensors. Nano Energy 58, 612–623 (2019). https​://doi.org/10.1016/j. nanoe​n.2019.01.096 \n24.\t M. Ma, Q. Liao, G. Zhang, Z. Zhang, Q. Liang et al., Selfrecovering triboelectric nanogenerator as active multifunctional sensors. Adv. Funct. Mater. 25, 6489–6494 (2015). https​://doi. org/10.1002/adfm.20150​3180 \n25.\t K. Xia, Z. Zhu, J. Fu, Y. Chi, Z. Xu, Multifunctional conductive copper tape-based triboelectric nanogenerator and as a self-powered humidity sensor. IEEE Trans. Electron Devices 66, 2741–2745 (2019). https​://doi.org/10.1109/TED.2019.29116​37 \n26.\t S. Wang, H. Tai, B. Liu, Z. Duan, Z. Yuan et al., A facile respiration-driven triboelectric nanogenerator for multifunctional respiratory monitoring. Nano Energy 58, 312–321 (2019). https​ ://doi.org/10.1016/j.nanoe​n.2019.01.042 \n27.\t K.A.N. Duerloo, M.T. Ong, E.J. Reed, Intrinsic piezoelectricity in two-dimensional materials. J. Phys. Chem. Lett. 3, 2871– 2876 (2012). https​://doi.org/10.1021/jz301​2436 \n28.\t W. Wu, L. Wang, Y. Li, F. Zhang, L. Lin et al., Piezoelectricity of single-atomic-layer $\\mathbf{MoS}_{2}$ for energy conversion and piezotronics. Nature 514, 470–474 (2014). https​://doi.org/10.1038/ natur​e1379​2 \n29.\t D. Zhang, Z. Yang, P. Li, M. Pang, Q. Xue, Flexible self-powered high-performance ammonia sensor based on Au-decorated $\\mathrm{MoSe}_{2}$ nanoflowers driven by single layer $\\mathbf{MoS}_{2}$ -flake piezoelectric nanogenerator. Nano Energy 65, 103974 (2019). https​://doi. org/10.1016/j.nanoe​n.2019.10397​4 \n30.\t E. Lee, A. Vahidmohammadi, B.C. Prorok, Y.S. Yoon, M. Beidaghi et al., Room temperature gas sensing of two-dimensional titanium carbide (MXene). ACS Appl. Mater. Interfaces 9, 37184– 37190 (2017). https​://doi.org/10.1021/acsam​i.7b110​55 \n31.\t Y. Yue, N. Liu, W. Liu, M. Li, Y. Ma et al., 3D hybrid porous Mxene-sponge network and its application in piezoresistive sensor. Nano Energy 50, 79–87 (2018). https​://doi.org/10.1016/j. nanoe​n.2018.05.020 \n32.\t M. Naguib, M. Kurtoglu, V. Presser, J. Lu, J. Niu et al., Twodimensional nanocrystals produced by exfoliation of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ . Adv. Mater. 23, 4248–4253 (2011). https​://doi.org/10.1002/ adma.20110​2306 \n33.\t Z. Yang, A. Liu, C. Wang, F. Liu, J. He et al., Improvement of gas and humidity sensing properties of organ-like MXene by alkaline treatment. ACS Sens. 4, 1261–1269 (2019). https​://doi. org/10.1021/acsse​nsors​.9b001​27 \n34.\t K. Wang, Z. Lou, L. Wang, L. Zhao, S. Zhao et al., Bioinspired interlocked structure-induced high deformability for two-dimensional titanium carbide (MXene)/natural microcapsule-based flexible pressure sensors. ACS Nano 13, 9139–9147 (2019). https​:// doi.org/10.1021/acsna​no.9b034​54 \n35.\t R. Yang, J. He, L. Xu, J. Yu, Effect of solution concentration on diameter and morphology of PVA nanofibres in bubble electrospinning process. J. Mater. Sci. Technol. 26, 1313–1316 (2010). https​://doi.org/10.1179/02670​8310X​12798​71827​4476 \n36.\t C. Jiang, C. Wu, X. Li, Y. Yao, L. Lan et al., All-electrospun flexible triboelectric nanogenerator based on metallic MXene nanosheets. Nano Energy 59, 268–276 (2019). https​://doi. org/10.1016/j.nanoe​n.2019.02.052 \n37.\t X. Chen, P. Hu, K. Song, X. Wang, C. Zuo et al., CVD growth of large-scale hexagon-like shaped $\\mathrm{MoSe}_{2}$ monolayers with sawtooth edge. Chem. Phys. Lett. 733, 136663 (2019). https​://doi. org/10.1016/j.cplet​t.2019.13666​3 \n38.\t Y. Chang, W. Zhang, Y. Zhu, Y. Han, J. Pu et al., Monolayer $\\mathrm{MoSe}_{2}$ grown by chemical vapor deposition for fast photodetection. ACS Nano 8, 8582–8590 (2014). https​://doi.org/10.1021/ nn503​287m \n39.\t P. He, W. Chen, J. Li, H. Zhang, Y. Li et al., Keggin and Dawson polyoxometalates as electrodes for flexible and transparent piezoelectric nanogenerators to efficiently utilize mechanical energy in the environment. Sci. Bull. 65, 35–44 (2020). https​:// doi.org/10.1016/j.scib.2019.09.026 \n40.\t G. Viola, J. Chang, T. Maltby, F. Steckler, M. Jomaa et al., Bioinspired multiresonant acoustic devices based on electrospun piezoelectric polymeric nanofibers. ACS Appl. Mater. Interfaces 12, 34643–34657 (2020). https​://doi.org/10.1021/acsam​i.0c092​38 \n41.\t P.K. Yang, S.A. Chou, C.H. Hsu, R.J. Mathew, K.H. Chiang et al., Tin disulfide piezoelectric nanogenerators for biomechanical energy harvesting and intelligent human-robot interface applications. Nano Energy 75, 104879 (2020). https​://doi.org/10.1016/j. nanoe​n.2020.10487​9 \n42.\t Z. Wang, H. Kurita, H. Nagaoka, F. Narita, Potassium sodium niobate lead-free piezoelectric nanocomposite generators based on carbon-fiber-reinforced polymer electrodes for energy-harvesting structures. Compos. Sci. Technol. 199, 108331 (2020). https​://doi. org/10.1016/j.comps​citec​h.2020.10833​1 \n43.\t C. Peng, X. Yang, Y. Li, H. Yu, H. Wang et  al., Hybrids of two-dimensional Ti3C2 and TiO2 exposing 001 facets toward enhanced photocatalytic activity. ACS Appl. Mater. Interfaces 8, 6051–6060 (2016). https​://doi.org/10.1021/acsam​i.5b119​73 \n44.\t M. Das, D. Sarkar, Development of room temperature ethanol sensor from polypyrrole (PPy) embedded in polyvinyl alcohol (PVA) matrix. Polym. Bull. 75, 3109–3125 (2018). https​://doi. org/10.1007/s0028​9-017-2192-y \n45.\t J. Fan, J. Luo, X. Zhang, B. Zhen, C. Dong et al., A novel electrospun $\\upbeta$ -CD/CS/PVA nanofiber membrane for simultaneous and rapid removal of organic micropollutants and heavy metal ions from water. Chem. Eng. J. 378, 122232 (2019). https​://doi. org/10.1016/j.cej.2019.12223​2 \n46.\t L. Wang, L. Chen, P. Song, C. Liang, Y. Lu et al., Fabrication on the annealed $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene/Epoxy nanocomposites for electromagnetic interference shielding application. Compos Part B 171, 111–118 (2019). https​://doi.org/10.1016/j.compo​sites b.2019.04.050 \n47.\t E.A. Mayerberger, O. Urbanek, R.M. McDaniel, R.M. Street, M.W. Barsoum et al., Preparation and characterization of polymer- $\\mathbf{\\cdot}\\Gamma\\mathrm{i}_{3}\\mathbf{C}_{2}\\mathbf{T}_{\\mathbf{x}}$ (MXene) composite nanofibers produced via electrospinning. J. Appl. Polym. Sci. 134, 45295 (2017). https​://doi. org/10.1002/app.45295​ \n48.\t D. Zhang, D. Wang, X. Zong, G. Dong, Y. Zhang, High-performance QCM humidity sensor based on graphene oxide/tinoxide/ polyaniline ternary nanocomposite prepared by in-situoxidative polymerization method. Sens. Actuat. B 262, 531–541 (2018). https​://doi.org/10.1016/j.snb.2018.02.012 \n49.\t H. An, T. Habib, S. Shah, H. Gao, A. Patel et al., Water Sorption in MXene/polyelectrolyte multilayers for ultrafast humidity sensing. ACS Appl. Nano Mater. 2, 948–955 (2019). https​://doi. org/10.1021/acsan​m.8b022​65 \n50.\t E.S. Muckley, M. Naguib, H.W. Wang, L. Vlcek, N.C. Osti et al., Multimodality of structural, electrical, and gravimetric responses of intercalated MXenes to water. ACS Nano 11, 11118–11128 (2017). https​://doi.org/10.1021/acsna​no.7b052​64 \n51.\t M. Naguib, V.N. Mochalin, M.W. Barsoum, Y. Gogotsi, 25th anniversary article: Mxenes: a new family of two-dimensional materials. Adv. Mater. 26, 992–1005 (2014). https​://doi.org/10.1002/ adma.20130​4138 \n52.\t Z. Ahmad, M. Abbas, I. Gunawan, R.A. Shakoor, F. Ubaid et al., Electro-sprayed PVA coating with texture-enriched surface morphology for augmented humidity sensing. Prog. Org. Coat. 17, 7–9 (2018). https​://doi.org/10.1016/j.porgc​oat.2017.12.010 \n53.\t Y. Su, G. Xie, S. Wang, H. Tai, Q. Zhang et al., Novel highperformance self-powered humidity detection enabled by triboelectric effect. Sens. Actuat. B 251, 144–152 (2017). https​://doi. org/10.1016/j.snb.2017.04.039 \n54.\t T. Zhao, Y. Fu, Y. Zhao, L. Xing, X. Xue, Ga-doped ZnO nanowire nanogenerator as self-powered/active humidity sensor with high sensitivity and fast response. J. Alloys Compd. 648, 571–576 (2015). https​://doi.org/10.1016/j.jallc​om.2015.07.035 " + }, + { + "id": "10.1126_science.abf7136", + "DOI": "10.1126/science.abf7136", + "DOI Link": "http://dx.doi.org/10.1126/science.abf7136", + "Relative Dir Path": "mds/10.1126_science.abf7136", + "Article Title": "Temperature-adaptive radiative coating for all-season household thermal regulation", + "Authors": "Tang, KC; Dong, KC; Li, JC; Gordon, MP; Reichertz, FG; Kim, H; Rho, Y; Wang, QJ; Lin, CY; Grigoropoulos, CP; Javey, A; Urban, JJ; Yao, J; Levinson, R; Wu, JQ", + "Source Title": "SCIENCE", + "Abstract": "The sky is a natural heat sink that has been extensively used for passive radiative cooling of households. A lot of focus has been on maximizing the radiative cooling power of roof coating in the hot daytime using static, cooling-optimized material properties. However, the resultant overcooling in cold night or winter times exacerbates the heating cost, especially in climates where heating dominates energy consumption. We approached thermal regulation from an all-season perspective by developing a mechanically flexible coating that adapts its thermal emittance to different ambient temperatures. The fabricated temperature-adaptive radiative coating (TARC) optimally absorbs the solar energy and automatically switches thermal emittance from 0.20 for ambient temperatures lower than 15 degrees C to 0.90 for temperatures above 30 degrees C, driven by a photonically amplified metal-insulator transition. Simulations show that this system outperforms existing roof coatings for energy saving in most climates, especially those with substantial seasonal variations.", + "Times Cited, WoS Core": 411, + "Times Cited, All Databases": 452, + "Publication Year": 2021, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000733380100054", + "Markdown": "# RADIATIVE COOLING \n\n# Temperature-adaptive radiative coating for all-season household thermal regulation \n\nKechao Tang $^{1,2,3}\\dag$ , Kaichen Dong1,2†, Jiachen $L i^{2.4}+$ , Madeleine P. Gordon4,5, Finnegan G. Reichertz6, Hyungjin $\\arcsin^{2,7}$ , Yoonsoo $\\mathsf{R h o}^{8}$ , Qingjun Wang1,2, Chang-Yu Lin1, Costas P. Grigoropoulos8, Ali Javey2,7, Jeffrey J. Urban5, Jie $\\yen12$ , Ronnen Levinson9, Junqiao $\\mathsf{w}_{\\mathsf{u}}{}^{\\mathsf{1},2,4\\times}$ \n\nThe sky is a natural heat sink that has been extensively used for passive radiative cooling of households. A lot of focus has been on maximizing the radiative cooling power of roof coating in the hot daytime using static, cooling-optimized material properties. However, the resultant overcooling in cold night or winter times exacerbates the heating cost, especially in climates where heating dominates energy consumption. We approached thermal regulation from an all-season perspective by developing a mechanically flexible coating that adapts its thermal emittance to different ambient temperatures. The fabricated temperature-adaptive radiative coating (TARC) optimally absorbs the solar energy and automatically switches thermal emittance from 0.20 for ambient temperatures lower than $\\mathsf{15^{\\circ}C}$ to 0.90 for temperatures above $30^{\\circ}\\mathsf{C}$ , driven by a photonically amplified metal-insulator transition. Simulations show that this system outperforms existing roof coatings for energy saving in most climates, especially those with substantial seasonal variations. \n\nn countries such as the United States, ${\\sim}39\\%$ of the total energy consumption is in buildings $(I)$ . For the residential housing energy portion, $\\sim51\\%$ is consumed for heating and cooling to maintain a desirable indoor temperature $({\\sim}22^{\\circ}\\mathrm{C})$ (2). In contrast to most temperature regulation systems, which require external power input, the mid-infrared (IR) atmospheric transparency window (“sky window”) allows thermal radiation exchange between terrestrial surfaces and the $3\\mathrm{K}$ outer space, thus opening a passive avenue for thermal radiative cooling of buildings. This method to cool an outdoor surface such as a roof has been extensively studied in the past (3–6). It is now advanced by the development of daytime radiative cooling (7–13) using materials with low solar absorptance and high thermal emittance in the form of thin films (8), organic paints (10, 14), or structural materials $(I I)$ . \n\nPast research on daytime radiative cooling, while successful in reducing cooling energy consumption, typically used materials with fixed, cooling-optimized properties, which efficiently emit thermal radiation even when the temperature of the surface is lower than desired, such as during the night or in the winter. This unwanted thermal radiative cooling will increase the energy consumption for heating and may offset the cooling energy saved in hot hours or seasons. This issue is well acknowledged by the research community, and mitigation of the overcooling has become a timely demand (15). To cut the heating penalty from overcooling, a few techniques were recently attempted for switching off thermal radiative cooling at low temperatures (below $22^{\\circ}\\mathrm{C}$ ). Although effective in switching, these techniques typically require either additional energy input $(I6,I7)$ or external activation (18), and in some cases, switching is achieved by mechanical moving parts (19, 20). Developing dynamic structures that automatically cease radiative cooling at low temperatures is therefore highly desirable. Existing efforts in self-switching radiative cooling, however, are either purely theoretical (21–24) or limited to materials characterization with little relevance to practical household thermal regulation (25–28). Very recently, a smart subambient coating was developed (29), focusing on the reduction of solar absorption by fluorescence rather than modulation of thermal emittance by temperature. \n\nWe took a different, holistic approach by designing and fabricating a mechanically flexible coating structure to minimize total energy consumption through the entire year. This temperature-adaptive radiative coating (TARC) automatically switches its sky-window emittance to 0.90 from 0.20 when the surface temperature rises above ${\\sim}22^{\\circ}\\mathrm{C},$ a practical threshold not previously available. Our TARC delivers high radiative cooling power exclusively for the high-temperature condition (Fig. 1A). We also optimized the solar absorptance at ${\\sim}0.25$ (solar reflectance $\\mathbf{\\Lambda}=\\mathbf{\\Lambda}0.75$ ) for all-season energy saving in major US cities (fig. S7). Our \n\nTARC demonstrates effective surface temperature modulation in an outdoor test environment. We performed extensive simulations based on the device properties and the climate database, which show advantages of TARC over existing roof coating materials in energy savings for most US cities in different climate zones (Fig. 1C). The energy savings by TARC not only bring economic benefits but also contribute to environmental preservation by reducing greenhouse gas emissions. \n\nWe developed the TARC based on the wellknown metal-insulator transition (MIT) of the strongly correlated electron materials $\\mathrm{W}_{x}\\mathrm{V}_{1-x}\\mathrm{O}_{2}$ (30–32), and the transition temperature $(T_{\\mathrm{MIT}})$ is tailored to ${\\sim}22^{\\circ}\\mathrm{C}$ by setting the composition $x$ at $1.5\\%$ (33). We embedded a lithographically patterned two-dimensional array of thin $\\mathrm{W}_{x}\\mathrm{V}_{1-x}\\mathrm{O}_{2}$ blocks in a $\\mathrm{BaF_{2}}$ dielectric layer that sits on top of an Ag film (Fig. 2A). In the insulating (I) state of $\\mathrm{W}_{x}\\mathrm{V}_{1-x}\\mathrm{O}_{2}$ at $TT_{\\mathrm{MIT}}$ (34). The absorption is further amplified by the designed photonic resonance with adjacent $\\mathrm{W}_{x}\\mathrm{V}_{1-x}\\mathrm{O}_{2}$ blocks as well as with the bottom Ag layer through the $\\%$ -wavelength cavity. The $\\%$ -wavelength cavity structure induces Fabry-Perot resonance and was used in previous work to enhance thermal emission (21, 23). According to Kirchhoff’s law of radiation (35), the sky-window emittance equals the skywindow absorptance and switches from low to high when the temperature exceeds $T_{\\mathrm{MIT}}$ . Consequently, strong sky-window radiative cooling is turned on in operation exclusively at high temperatures, leaving the system in the solar-heating or keep-warm mode at low temperatures. Details on the fabrication process and structural parameters are found in the supplementary materials (36) (fig. S1). \n\nOur fabricated TARC has high flexibility for versatile surface adaption, as well as a microscale structure consistent with the design (Fig. 2B). We examined the emittance switching over the entire sample using a thermal infrared (TIR) camera (Fig. 2C). We imaged the TARC surface together with two reference samples having similar thicknesses but constant low thermal emittance (0.10, copper plate) or constant high thermal emittance (0.95, black tape), respectively. Although the thermal emission of the reference samples appeared to not be strongly temperature sensitive from 20 to $30^{\\circ}\\mathrm{C},$ , the TARC showed a marked change, corresponding to the switch in sky-window emittance at the MIT around $22^{\\circ}\\mathrm{C}$ . \n\nWe measured the spectral properties of the TARC by a UV-visible-NIR spectrometer and Fourier transform infrared spectroscopy (FTIR) for the solar and TIR wavelength regimes, respectively (Fig. 2D). The solar absorptance $(A,0.3$ to $2.5~\\upmu\\mathrm{m})$ is ${\\sim}0.25$ , and the sky-window emittance $(\\varepsilon_{\\mathrm{w}},8$ to $13\\upmu\\mathrm{m}\\mathrm{,}$ is ${\\sim}0.20$ in the I state and ${\\sim}0.90$ in the M state, consistent with theoretical simulations and other characterization results (fig. S2 and fig. S3). \n\nThe emittance switching of the TARC enables deep modulation of radiative cooling power in response to ambient temperature, which we first measured in vacuum (Fig. 3A). We suspended a heater membrane by thin strings in a vacuum chamber, which was cooled with dry ice to ${\\sim}-78^{\\circ}\\mathrm{C}$ to minimize radiation from the chamber walls. We attached a piece of Al foil with $\\mathfrak{E}_{\\mathrm{Al}}\\approx0.03$ or a TARC of the same size to the top of the heater in two separate measurements. At each stabilized sample temperature $T_{:}$ , the heating powers needed for the two coating scenarios are denoted as $P_{\\mathrm{{Al}}}$ $(T)$ and $P_{\\mathrm{TARC}}(T)$ , respectively. The cooling flux (power per area $\\mathcal{A}$ ) contributed by the TARC was calculated $\\mathrm{as}P_{\\mathrm{cool}}^{\\prime\\prime}(T)=[P_{\\mathrm{TARC}}(T)-$ $P_{\\mathrm{Al}}(T)]/{\\cal A}$ . We used the Al foil reference to calibrate background heat loss from thermal conduction through the strings. We plotted the calibrated cooling power (Fig. 3B), which shows an abrupt increase in $P_{\\mathrm{cool}}^{\\prime\\prime}(T)$ when $T$ rises above the MIT temperature. $P_{\\mathrm{cool}}^{\\prime\\prime}(T)$ measurements in the I state and M state are well fitted by the Stefan-Boltzmann radiation law, with values of sky-window $\\varepsilon_{\\mathrm{w}}$ extracted to be ${\\sim}0.20$ and ${\\sim}0.90$ , respectively, consistent with the spectrally characterized results (Fig. 2D). We considered and corrected the effect of radiation from the chamber wall $({\\sim}-78^{\\circ}\\mathrm{C})$ for the calibration. We introduced a constant factor of $\\gamma$ $(\\approx0.7)$ to account for the difference between the vacuum and ambient measurement conditions (details in fig. S4) (36). \n\nWe demonstrated the actual outdoor performance of the TARC (Fig. 4). We recorded the surface temperatures $(T_{\\mathrm{s}})$ of the TARC, together with a dark roof coating product (Behr no. N520, asphalt gray) and a cool (white) roof coating product (GAF RoofShield white acrylic), over 24 hours on a sunny summer day on a rooftop in Berkeley, California, with a careful design of the measurement system to minimize the effects of artifacts (fig. S5). \n\nFrom 00:00 to 09:00 local daylight time (LDT), when the ambient temperature was below $T_{\\mathrm{MIT}}$ , the TARC was $2^{\\circ}\\mathrm{C}$ warmer than the two reference roof coatings, arising from the low sky-window emittance $(\\varepsilon_{\\mathrm{w}}=0.20)$ of the TARC in the I state and thus a lower radiative cooling power than the references $\\mathrm{\\langle{\\bf{g}}_{w}=0.90\\mathrm{\\rangle}}$ . The $2^{\\circ}\\mathrm{C}$ temperature elevation is consistent with adiabatic simulation results based on these nominal emittance values and the local weather database [see the supplementary materials (36), note A, section I]. From 09:00 to $13{:}00\\ \\mathrm{LDT}$ , when the samples were in direct sunlight, $T_{\\mathrm{s}}$ was dominated by the solar absorption in balance with radiative cooling and air convection, and the differences between the samples agree with the simulated results assuming the solar absorptance $A$ to be 0.15, 0.25, and 0.70 for the white roof coating, TARC, and the dark roof coating, respectively. After 13:00 LDT, we erected a shield to intentionally block direct solar radiation to the surface of the samples. This imitates the scenario of a cloud blocking the sun but with the rest of the sky mostly clear. We quickly observed a convergence of the $T_{\\mathrm{s}}$ curves for all three samples, an indication that the thermal emittance of the TARC in the M state is close to that of the two references (0.90). This condition persisted for a few hours until $T_{\\mathrm{s}}$ started to drop below $T_{\\mathrm{MIT}}=22^{\\circ}\\mathrm{C}.$ . After this point, TARC grew warmer than the two references, with a final temperature difference of ${\\sim}2^{\\circ}\\mathrm{C},$ similar to the 00:00 to 09:00 LDT period. This indicates that the TARC switched to the low-emittance I state. The 24-hour outdoor experiments demonstrate the emittance switching and resultant temperature regulation by TARC. Although the white roof coating shows an advantage over TARC in thermal management in summer daytime and under solar radiation (Fig. 4A), the TARC regulates the roof temperature closer to the heating and cooling setpoints (22 and $24^{\\circ}\\mathrm{C}$ than the white roof coating for almost all of the other conditions, including daytime in other seasons and all of the nighttime (fig. S6). From an all-year-round perspective, the TARC demonstrates superiority compared with regular roof coatings in terms of source energy saving. \n\nTo directly compare their ambient condition cooling fluxes Pc″ool amb), we heated the TARC and the white roof coating to the air temperature with the direct solar radiation blocked. c″ool amb refers to the net cooling flux from the surface—namely, the thermal radiative heat loss flux minus the absorbed diffuse solar irradiance. We plotted the Pc″ool–amb values that we obtained at a low and a high air temperature (Fig. 4B). The TARC exhibits a clear switching of $P_{\\mathrm{cool.amb}}^{\\prime\\prime}$ by a factor over five across the MIT. This behavior is in stark contrast to the nearly constant $P_{\\mathrm{cool.amb}}^{\\prime\\prime}$ around $120~\\mathrm{W/m^{2}}$ for the shaded white roof coating, which is consistent with values (90 to $130~\\mathrm{W/m^{2}}\\cdot$ ) reported in literature for roofs surfaced with daytime radiative cooling materials $(5,9,{\\cal I O})$ . \n\n![](images/07a55dc556c80ce9d55c19af854b69ac642a3512f58416a8bcaaf86b16f677e4.jpg) \nFig. 1. TARC and its benefits for household thermal regulation. (A) Basic property of TARC in sky-window (8 to $13\\upmu\\mathrm{m}\\ '$ ) emittance modulation and schematics for temperature management when used as a household roof coating. The data points are the measured sky-window emittances of a TARC. The two color bands represent the temperature-independent thermal emittance of metals and radiative coolers. (B) TARC compared with other thermal regulation systems, highlighting the unique benefit of TARC of being simultaneously energy-free and temperature adaptive (details in table S1). (C) ${\\mathsf{S C S E S}}_{\\mathsf{m i n}}$ of TARC compared with other existing roof-coating materials for different cities representing the 15 climate zones in the United States. Red and blue circles indicate positive and negative $\\mathsf{S C S E S}_{\\mathsf{m i n}}$ values, respectively. The values are scaled to the area of the circles. Representation of the triangle and circle icons is explained in the materials and methods (subsection, “Projection of energy savings”) $(36)$ . \n\n![](images/2e259632d20980681d306a423593aa74c737a37da4aaa4f9cb96ca6c07ee2f50.jpg) \nFig. 2. Basic properties of TARC with experimental characterization. (A) Schematics of the structure (i), materials composition and working mechanism (ii and iii) of the TARC. Subpanels (iv) and (v) show the simulated distribution of electric field intensity below and above the transition temperature, respectively, when electromagnetic waves with a wavelength of $7.8\\upmu\\mathrm{m}$ were normally incident on the TARC structure. (B) Photograph $(2\\mathsf{c m}\\times2\\mathsf{c m})$ and false-color scanning electron microscope image of TARC showing high flexibility and structural consistency with the design. (C) TIR images of TARC compared with those of two conventional \nmaterials (references) with constantly low or high thermal emittance showing the temperature-adaptive switching in thermal emittance of TARC. (D) Solar spectral absorptance and part of the thermal spectral emittance of TARC at a low temperature and a high temperature, measured by a UV-visible-NIR spectrometer with an integrating sphere and an FTIR spectrometer, respectively. Measurements (solid curves) show consistency with theoretical predictions (dashed curves). The arrow at $7.8\\upmu\\mathrm{m}$ denotes the wavelength where the distribution of electric field intensity shown in subpanels (iv) and (v) of (A) are simulated. \n\nWe performed extensive numerical simulations to analyze the performance of TARC in household energy saving for the US cities from an all-season perspective (36). We show the simulated results (Fig. 4C) for Berkeley where the measurements (Fig. 4, A and B) were performed. We calculated an hour-month map of $T_{\\mathrm{s}}$ using a local weather file (37), laying the basis for estimation of energy saving. We assumed heating and cooling setpoints $T_{\\mathrm{set,heat}}=$ $22^{\\circ}\\mathrm{C}$ and $T_{\\mathrm{set,cool}}~=~24^{\\circ}\\mathrm{C}$ (38), and approximated that the building will need heating when $T_{\\mathrm{s}}T_{\\mathrm{set,cool}}$ . We used past simulations of coolroof energy savings to predict potential spaceconditioning source energy savings (SCSES) per unit roof area attainable by using TARC in place of roofing materials that have static values of solar absorptance and thermal emittance (36). The figure of merit of TARC is represented by ${\\mathrm{scses}}_{\\mathrm{min}}$ , the minimum value of SCSES found over all existing conventional roofing materials, which have constant values of $A_{\\mathrm{ref}}$ and $\\boldsymbol{\\varepsilon}_{\\mathrm{ref}}$ (Fig. 4C, dashed boxes). We mapped ${\\mathrm{scses}}_{\\mathrm{min}}$ for cities representing the 15 US climate zones (Fig. 1C). This figureof-merit map shows that TARC provides clear, positive annual space-conditioning source energy savings relative to existing roof coating materials in most major cities, except for climates that are constantly cold (such as Fairbanks) or hot (such as Miami) throughout the year. It highlights the advantage of TARC, especially in climate zones with wide temperature variations, day to night or summer to winter. For example, we estimate that for a single-family home in Baltimore, Maryland, built before 1980, modeled with roof assembly thermal insulance $4.3\\:\\mathrm{m^{2}/(K{\\cdot}W)}$ , gas furnace annual fuel utilization efficiency $80\\%$ , and air conditioner coefficient of performance 2.64 (38), ${\\mathrm{scses}}_{\\mathrm{min}}$ is $22.4\\mathrm{MJ/(m^{2}{\\cdot}y)}$ , saving 2.64 GJ/y based on a roof area of 118 $\\mathrm{m^{2}}$ . We also calculated the source energy saving of TARC as a function of its solar absorptance (fig. S7), showing that the actual solar absorptance of TARC is close to the optimal value for major US cities. \n\nThe TARC could be readily upgraded for heavy-duty outdoor applications by coating it with a thin polyethylene (PE) membrane, which is nontoxic, hydrophobic, and transparent both in the visible and thermal IR regions. While protecting the TARC from contacting the dust and moisture in complex environments, the PE coating has little impact on the thermal modulation performance (fig. S9). Polymer imprinting instead of photolithography could also be used to more easily produce the material for large scale application. By embedding $\\mathrm{{VO}_{2}}$ particles in layered PE membranes, we estimated the multilayered metamaterial to achieve comparable modulation performance $\\mathrm{\\langle\\Delta\\Omega\\Delta\\Omega\\rangle}\\mathrm{\\langle\\Delta\\Delta\\Omega\\rangle}$ as the TARC we presented and would be producible in a roll-to-roll fashion (figs. S10 and S11). Roll-toroll manufacturing of PE-based TARC would be beneficial because of its high scalability, low cost (9), and the fact that it is free from the liquid evaporation process in fabrication (39). The PE layer can be also replaced by other organic or inorganic materials with negligible optical loss in the wavelength ranges of both solar irradiation and IR atmospheric transparency window, so that the TARC technology can be designed specifically to be endurable in different environmental conditions. \n\n![](images/ff8f27ec030ef8be8dd8d8af50931815126b9e80fd34894a3a562b6ad8905f96.jpg) \nFig. 4. Characterization of TARC in an outdoor environment. (A) Surface temperature of TARC, a commercial dark roof coating $\\mathrm{\\Delta}A=0.70$ , $\\begin{array}{r}{\\varepsilon_{\\mathsf{w}}=0.90\\ '}\\end{array}$ , and a commercial white roof coating $\\langle A=0.15$ , $\\varepsilon_{\\mathrm{w}}=0.90\\},$ ) in an open-space outdoor environment recorded over a day-night cycle. The measurement was taken on 5 July 2020, in Berkeley, California $(37.91^{\\circ}N_{}$ , $122.28^{\\circ}\\mathsf{W},$ . The solid and dashed curves are experimental data and simulation results based on a local weather database (37), respectively. Measurements starting from 14:00 LDT were performed with the direct solar radiation blocked. Temperature observed after sunset show clear signs \nof the TARC shutting off thermal radiative cooling as its surface ambient temperature falls below $T_{\\mathrm{MIT}}$ . (B) Measured ambient cooling power of TARC and white roof coating with direct solar radiation blocked in the outdoor environment. (C) $T_{\\mathrm{s}}$ and the corresponding $\\varepsilon_{\\mathsf{w}}$ mapping of TARC over 24 hours and the full year for Berkeley. Also shown are the SCSES of TARC compared with all other materials with fixed solar absorptance $(A_{\\mathrm{ref}})$ and fixed thermal emittance $(\\upvarepsilon_{\\mathrm{ref}})$ . The icons in the SCSES map correspond to those used in Fig. 1C, denoting the radiative parameters $(A,\\varepsilon_{w})$ of the strongest rival to TARC in source energy savings for the local climate (36). \n\nWe developed a mechanically flexible, energyfree TARC for intelligent regulation of household temperature. Our system features a thermally driven metal-insulator transition in cooperation with photonic resonance, and demonstrates self-switching in sky-window thermal emittance from 0.20 to 0.90 at a desired temperature of ${\\sim}22^{\\circ}\\mathrm{C},$ . These attractive properties enable switching of the system from the radiative cooling mode at high temperatures to the solar-heating or keep-warm mode at low temperatures in an outdoor setting. For most cities in the United States, our simulations indicate the TARC may outperform all conventional roof materials in terms of cutting energy consumption for households. \n\n# REFERENCES AND NOTES \n\n1. US Energy Information Administration, “Annual Energy Review 2020” (2020); https://www.eia.gov/totalenergy/data/annual/ \n2. US Energy Information Administration, “2015 Residential Energy Consumption Survey” (2015); https://www.eia.gov/ consumption/residential/ \n3. A. R. Gentle, G. B. Smith, Adv. Sci. (Weinh.) 2, 1500119 (2015). \n4. M. Dong, N. Chen, X. Zhao, S. Fan, Z. Chen, Opt. Express 27, 31587–31598 (2019). \n5. B. Orel, M. K. Gunde, A. Krainer, Sol. Energy 50, 477–482 (1993). \n6. P. Berdahl, M. Martin, F. Sakkal, Int. J. Heat Mass Transf. 26, 871–880 (1983). \n7. N. N. Shi et al., Science 349, 298–301 (2015). \n8. J. Kou, Z. Jurado, Z. Chen, S. Fan, A. J. Minnich, ACS Photonics 4, 626–630 (2017). \n9. Y. Zhai et al., Science 355, 1062–1066 (2017). \n10. J. Mandal et al., Science 362, 315–319 (2018). \n11. T. Li et al., Science 364, 760–763 (2019). \n12. Z. Li, Q. Chen, Y. Song, B. Zhu, J. Zhu, Adv. Mater. Technol. 5, 1901007 (2020). \n13. P. Berdahl, Appl. Opt. 23, 370–372 (1984). \n14. X. Li et al., Cell Rep. Phys. Sci. 1, 100221 (2020). \n15. G. Ulpiani, G. Ranzi, K. W. Shah, J. Feng, M. Santamouris, Sol. Energy 209, 278–301 (2020). \n16. K. Goncharov et al., “1500 W deployable radiator with loop heat pipe” (SAE Technical Paper 2001-01-2194, 2001); https://doi.org/10.4271/2001-01-2194. \n17. C. Lashley, S. Krein, P. Barcomb, “Deployable radiators-A multi-discipline approach” (SAE Technical Paper 981691, 1998); https://doi.org/10.4271/981691. \n18. H. Zhao, Q. Sun, J. Zhou, X. Deng, J. Cui, Adv. Mater. 32, e2000870 (2020). \n19. Z. Xia, Z. Fang, Z. Zhang, K. Shi, Z. Meng, ACS Appl. Mater. Interfaces 12, 27241–27248 (2020). \n20. H. Nagano, Y. Nagasaka, A. Ohnishi, J. Thermophys. Heat Trans. 20, 856–864 (2006). \n21. M. Ono, K. Chen, W. Li, S. Fan, Opt. Express 26, A777–A787 (2018). \n22. M. Chen, A. M. Morsy, M. L. Povinelli, Opt. Express 27, 21787–21793 (2019). \n23. S. Taylor, Y. Yang, L. Wang, J. Quant. Spectrosc. Radiat. Transf. 197, 76–83 (2017). \n24. W.-W. Zhang, H. Qi, A.-T. Sun, Y.-T. Ren, J.-W. Shi, Opt. Express 28, 20609–20623 (2020). \n25. K. Ito, T. Watari, K. Nishikawa, H. Yoshimoto, H. Iizuka, APL Photonics 3, 086101 (2018). \n26. K. Nishikawa, K. Yatsugi, Y. Kishida, K. Ito, Appl. Phys. Lett. 114, 211104 (2019). \n27. H. Kim et al., Sci. Rep. 9, 11329 (2019). \n28. K. Sun et al., ACS Photonics 5, 2280–2286 (2018). \n29. X. Xue et al., Adv. Mater. 32, e1906751 (2020). \n30. F. J. Morin, Phys. Rev. Lett. 3, 34–36 (1959). \n31. T.-L. Wu, L. Whittaker, S. Banerjee, G. Sambandamurthy, Phys. Rev. B Condens. Matter Mater. Phys. 83, 073101 (2011). \n32. C. Kim, J. S. Shin, H. Ozaki, J. Phys. Condens. Matter 19, 096007 (2007). \n33. S. Lee et al., Science 355, 371–374 (2017). \n34. A. S. Barker, H. W. Verleur, H. J. Guggenheim, Phys. Rev. Lett. 17, 1286–1289 (1966). \n35. J. Agassi, Science 156, 30–37 (1967). \n36. The materials and methods are available as supplementary materials. \n37. US Department of Energy, “EnergyPlus Weather Data” (2021); https://energyplus.net/weather. \n38. P. J. Rosado, R. Levinson, Energy Build. 199, 588–607 (2019). \n39. A. Leroy et al., Sci. Adv. 5, eaat9480 (2019). \n\n# ACKNOWLEDGMENTS \n\nFunding: This work was funded by the Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, US Department of Energy, under contract no. DE-AC02-05-CH11231 (EMAT program KC1201). Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, US Department of Energy, under contract no. DE-AC02-05CH11231. J.W. acknowledges support from a Bakar Prize. R.L. acknowledges support from the Assistant Secretary for Energy Efficiency and Renewable Energy, Building Technologies Office, of the US Department of Energy under contract no. DE-AC02-05CH11231. J.Y. acknowledges support from the National Science Foundation under grant no. 1555336. M.P.G. gratefully acknowledges the National Science Foundation for fellowship support under the National Science Foundation Graduate Research Fellowship Program. Author contributions: K.T., K.D. J.L., and J.W. conceived the general idea. K.T. and K.D. designed the device. K.T. fabricated the device. K.T., M.P.G., H.K., Q.W., A.J., J.J.U., and J.Y. contributed to the spectral characterizations. K.T., K.D., J.L. Y.R., and C.P.G. contributed to the solar simulator characterizations. K.T., J.L., and C.-Y.L. performed the vacuum chamber characterizations. K.T., K.D., J.L., and J.W. performed the field experiments. K.D., J.L. and J.Y. performed the numerical electromagnetic simulations. K.T., F.G.R., and R.L. performed all other simulations. All authors discussed and analyzed the results. K.T., K.D., J.L., and J.W. wrote the manuscript with assistance from other authors. All authors reviewed and revised the manuscript. Competing interests: R.L. is an unpaid, nonvoting member of the board of directors of the Cool Roof Rating Council (CRRC) and a paid consultant to the CRRC. K.T., K.D., J.L., and J.W. are inventors of a provisional patent application related to this work. The authors declare that they have no competing interests. Data and materials availability: All data required to evaluate the conclusions in the manuscript are available in the main text or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abf7136 \nNomenclature \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S19 \nTables S1 to S6 \nReferences (40–105) \n\n13 November 2020; resubmitted 5 May 2021 \nAccepted 26 October 2021 \n10.1126/science.abf7136 " + }, + { + "id": "10.1126_science.abn1818", + "DOI": "10.1126/science.abn1818", + "DOI Link": "http://dx.doi.org/10.1126/science.abn1818", + "Relative Dir Path": "mds/10.1126_science.abn1818", + "Article Title": "Self-assembled monolayers direct a LiF-rich interphase toward long-life lithium metal batteries", + "Authors": "Liu, YJ; Tao, XY; Wang, Y; Jiang, C; Ma, C; Sheng, OW; Lu, GX; Lou, XW", + "Source Title": "SCIENCE", + "Abstract": "High-energy density lithium (Li) metal batteries (LMBs) are promising for energy storage applications but suffer from uncontrollable electrolyte degradation and the consequently formed unstable solid-electrolyte interphase (SEI). In this study, we designed self-assembled monolayers (SAMs) with high-density and long-range-ordered polar carboxyl groups linked to an aluminum oxide-coated separator to provide strong dipole moments, thus offering excess electrons to accelerate the degradation dynamics of carbon-fluorine bond cleavage in Li bis(trifluoromethanesulfonyl)imide. Hence, an SEI with enriched lithium fluoride (LiF) nullocrystals is generated, facilitating rapid Li+ transfer and suppressing dendritic Li growth. In particular, the SAMs endow the full cells with substantially enhanced cyclability under high cathode loading, limited Li excess, and lean electrolyte conditions. As such, our work extends the long-established SAMs technology into a platform to control electrolyte degradation and SEI formation toward LMBs with ultralong life spans.", + "Times Cited, WoS Core": 569, + "Times Cited, All Databases": 589, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000758142600041", + "Markdown": "# BATTERIES Self-assembled monolayers direct a LiF-rich interphase toward long-life lithium metal batteries \n\nYujing Liu1†, Xinyong $\\mathbf{7}\\mathbf{a}\\mathbf{o}^{1\\ast}\\dagger$ , Yao Wang1†, Chi Jiang1, Cong Ma1, Ouwei Sheng1, Gongxun Lu1, Xiong Wen (David) $\\mathbf{Lou}^{2*}$ \n\nHigh–energy density lithium (Li) metal batteries (LMBs) are promising for energy storage applications but suffer from uncontrollable electrolyte degradation and the consequently formed unstable solidelectrolyte interphase (SEI). In this study, we designed self-assembled monolayers (SAMs) with high-density and long-range–ordered polar carboxyl groups linked to an aluminum oxide–coated separator to provide strong dipole moments, thus offering excess electrons to accelerate the degradation dynamics of carbon-fluorine bond cleavage in Li bis(trifluoromethanesulfonyl)imide. Hence, an SEI with enriched lithium fluoride (LiF) nanocrystals is generated, facilitating rapid ${\\mathsf{L}}{\\mathsf{i}}^{+}$ transfer and suppressing dendritic Li growth. In particular, the SAMs endow the full cells with substantially enhanced cyclability under high cathode loading, limited Li excess, and lean electrolyte conditions. As such, our work extends the long-established SAMs technology into a platform to control electrolyte degradation and SEI formation toward LMBs with ultralong life spans. \n\nithium (Li) metal is designated as a promising anode material for next-generation Li-based batteries because of its high specific capacity (3860 mA·hour $\\mathbf{g}^{-1})$ and low redox potential $(-3.04\\:\\mathrm{V}$ versus the standard hydrogen electrode) $(\\boldsymbol{I},2)$ . However, the practical application of Li anodes is limited by dendritic Li growth (3, 4), leading to safety concerns and fast capacity fading of Li metal batteries (LMBs) $(5,6)$ . Among the efforts to inhibit the formation of Li dendrites, modification or rebuilding of the solid-electrolyte interphase (SEI) might be the most crucial (7, 8) because the SEI, which is spontaneously derived from the reaction between chemically active Li metal and the electrolyte, is responsible for $\\mathrm{Li^{+}}$ transport and mechanical accommodation of rapid Li growth (9, 10). Functional fluorinated electrolyte constituents—such as Li bis(trifluoromethanesulfonyl)imide (LiTFSI) $(I I)$ , Li bis(fluorosulfonyl)imide (12), 1,2-difluorobenzene (13), and fluoroethylene carbonate (14)—have been designed to perform interface engineering to regulate the nanostructure and chemical composition of the SEI. The developed SEIs generated by these strategies are all proven to involve the specific constituent of lithium fluoride (LiF), which has high interfacial energy, high chemical stability, and a low $\\mathrm{Li^{+}}$ diffusion barrier (15, 16). Generally, LiF is believed to be the decomposition product of F-containing electrolyte ingredients \n\nand contributes to boosting the cycle life of LMBs. Therefore, precisely controlling the electrolyte decomposition, particularly the C–F dissociation chemistry, to construct a LiF-rich SEI is a logically viable but still challenging method. \n\nTo regulate the electrolyte degradation process, it is desirable to seek a strategy to implement control of the redox state of the electrolyte, focusing on the electronic properties of the anode interface related to the loss or gain of electrons. As a reference, polar groups (e.g., the carboxyl group) can promote the cleavage of fluorinated bonds by changing the kinetics of electron transfer (17). Thus, how the degradation kinetics of fluorinated constituents transform when these disordered and dispersed functional groups become ordered and close-packed is of interest. Selfassembled monolayers (SAMs) have been extensively studied to construct surfaces with highly oriented molecules and ordered terminal groups and thus provide a convenient, flexible, and universal platform through which to tailor the interfacial properties of metals, metal oxides, and semiconductors $(l8,l9)$ . As a specific feature, long-range–ordered SAMs can regulate or even determine the distribution of surface dipoles relative to the molecular electronic structure and the orientation of terminal groups (20–22). Thus, the SAM-induced dipole moment may influence the kinetics of electron transfer and change the electrochemical redox dynamics of electrolytes to regulate the nanostructure of the SEI. As such, SAMs can possibly control the decomposition of fluorinated ingredients contained in electrolytes through ordering of the terminal groups that determine the surface electronic properties. \n\nIn this study, we fabricated SAMs onto an aluminum oxide $\\mathrm{(Al_{2}O_{3})}$ –coated polypropylene separator $\\mathrm{\\small{[Al_{2}O_{3}-O O C(C H_{2})_{2}X]}}$ and employed various terminal functional groups $\\mathrm{(X=NH_{2}}$ , COOH) to guide the smooth deposition of Li metal. The simulation predicts that ordered polar groups, particularly the carboxyl group, expedite the decomposition of C–F bonds involving the excess electrons induced by surface dipoles (Fig. 1A). The proposed mechanism is supported by atomic visualization and spectral interpretation, in which many LiF nanocrystals are identified in the SEI. Through the generation of a LiF-rich SEI, half cells and full cells both exhibit greatly improved cycling stability. \n\nSAM fabrication and structural examination An organic molecule $\\mathrm{\\small{[NH_{2}(C H_{2})_{2}C O O H}}$ or $\\mathrm{\\smallHOOC(CH_{2})_{2}C O O H]}$ with a consistent chain length is selected to establish SAMs on the surface of an $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ -coated separator (figs. S1 and S2) through a facile soaking method. The formation of SAMs originates from the specific binding between the carboxyl group and the hydroxyl-containing $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ surface (23). To verify that SAMs are successfully constructed on the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ surface, atomic force microscopy (AFM) is used to examine the morphological evolution. In particular, the molecules are densely packed like a full monolayer with $\\mathrm{\\sim20{-}\\AA}$ topographic features after modifying the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ matrix (Fig. 1, B to D), indicative of SAM establishment on $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ as $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}N H_{2}}$ and $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ - 1 $\\mathrm{\\partial)OC(CH_{2})_{2}C O O H}$ . In addition, the full $\\mathbf{\\boldsymbol{x}}$ -ray photoelectron spectroscopy (XPS) spectra show that the C content is higher in both $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}N H_{2}}$ $(23.95\\%)$ and $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ - ( $\\mathrm{\\Delta)OC(CH_{2})_{2}C O O H}$ $(23.70\\%)$ ) than in bare $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ $(18.41\\%$ ) (Fig. 1E). More specifically, the peaks at 284.8, 286.2, and $288.6\\mathrm{eV}$ in the C 1s region are assigned to C–C, C–O, and $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ , respectively, and the peaks at 530.8 and $532.1\\mathrm{eV}$ in the O 1s region belong to Al–O–Al and Al– O–C, respectively (fig. S3). The peak intensities (and hence contents) of $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ and Al– O–C in SAM-grafted $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ $\\mathrm{{.Al_{2}O_{3}}}$ -SAMs) are increased compared with those of pristine $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ (fig. S4). In addition, the Fourier transform infrared (FTIR) spectra of $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ -SAMs exhibit the typical signals of $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ $\\mathrm{7730cm^{-1}}$ ), N–H $(\\mathbf{1583\\mathrm{cm}^{-1}})$ , and C–O $(\\mathrm{1168~cm^{-1}}$ ) (24, 25), which belong to the terminal groups of the SAMs (Fig. 1F and fig. S5). In particular, two notable peaks at \\~1638 and $\\sim1443\\mathrm{cm}^{-1}$ appear in $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ -SAMs, representing asymmetric and symmetric bonding modes of the essential (bidentate) interaction between the headgroup carboxylate and the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ surface, respectively (Fig. 1F and fig. S5) (23). Furthermore, the water wetting experiment demonstrates an apparently increased contact angle that can be attributed to the highly ordered alignment of SAMs (fig. S6). These results all indicate that the specific molecules are successfully grafted onto the surface of the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ - coated separator to generate SAMs with ordered terminal groups. \n\n![](images/78993cd017c2e3029cf839d25a1e874a7d9c495c89df87aa646ceee2aaeb789a.jpg) \nFig. 1. Schematic illustration of SAMs in LMBs and characterization of $\\mathsf{A l}_{2}\\mathsf{O}_{3}.$ SAMs. (A) SAMs with carboxyl terminal groups accelerate the reduction of LiTFSI through dipole moment–directed electron provision and thus generate a LiF-rich SEI. PP, polypropylene. (B to D) AFM images showing the topographic features of (B) $A l_{2}O_{3}$ , (C) $A l_{2}O_{3}{-}00\\mathsf{C}(C H_{2})_{2}N H_{2}$ , and (D) $A|_{2}{\\sf O}_{3}{\\cdot}00{\\sf C}({\\sf C}\\mathsf{H}_{2})_{2}{\\sf C}00\\mathsf{H}$ . (E) XPS full-scan survey spectra of $A l_{2}0_{3}$ , $A|_{2}0_{3}–00C(C H_{2})_{2}N H_{2}$ , and $A|_{2}{\\sf O}_{3}{\\cdot}00{\\sf C}({\\sf C}\\mathsf{H}_{2})_{2}{\\sf C}00\\mathsf{H}.$ a.u., arbitrary units. (F) FTIR spectra of $A l_{2}0_{3}$ and $A|_{2}{\\sf O}_{3}{\\cdot}00\\mathsf{C}(\\mathsf{C}\\mathsf{H}_{2})_{2}\\mathsf{C}00\\mathsf{H}$ . \n\n# Li plating and stripping behaviors with SAMs \n\nTo confirm the effect of SAMs on Li deposition, electrochemical Li plating and stripping experiments are carried out using typical coin cells of bare Li and Cu coupled with an $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ -SAMs separator. The results are plotted as coulombic efficiency (CE) versus cycle number of cells at different current densities with the same plating capacity of 1 mA·hour $\\mathrm{cm}^{-2}$ (Fig. 2A). Specifically, the cells equipped with $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ - $\\mathrm{OOC(CH_{2})_{2}C O O H}$ and $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}N H_{2}}$ exhibit stable CEs of ${\\sim}97.7\\$ and ${\\sim}95.3\\% $ , respectively, over 300 cycles under a current density of 1 mA $\\mathrm{cm}^{-2}$ . By contrast, the cell with bare $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ shows inferior cycle life, and the CE fades to $74.2\\%$ after 220 cycles. More specifically, the cell with $\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ is stable with the overpotential of only ${\\sim}15~\\mathrm{mV}$ (Fig. 2B). When the current density is increased to 2 and $3\\mathrm{\\mA\\cm^{-2}}$ , the cells using $\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ also deliver more stable electrochemical cycling and still maintain high CEs of $99.2\\%$ $\\mathrm{\\Omega}^{\\mathrm{\\prime}}2\\mathrm{mAcm}^{-2}$ ) over 300 cycles and $99.4\\%$ ( $\\mathrm{3\\mA\\cm^{-2}},$ ) over 150 cycles, and the cells using $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}N H_{2}}$ have CEs of $93.6\\%$ $\\mathrm{2\\mA\\cm^{-2}}$ ) after 200 cycles and $93.5\\%$ $\\mathrm{3\\mA\\cm^{-2}}.$ ) after 150 cycles. By contrast, the cells with $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ exhibit rather unsatisfactory cycling stability, showing CEs of $82.4\\%(2\\mathrm{mAcm^{-2}})$ at the 200th cycle and $70.9\\%$ $(3\\mathrm{\\mA\\cm^{-2}})$ at the 150th cycle (Fig. 2A). As a comparison, the individual $\\mathrm{{HOOC(CH_{2})_{2}C O O H}}$ or $\\mathrm{{HOOC}(C H_{2})_{2}N H_{2}}$ molecules are directly added into the electrolyte as additives, and these dispersed molecules fail to form SAMs because of the weak solvent polarity of the ether-based electrolyte (figs. S7 and S8). The CE of the cells using both individual additives is apparently lower than that of the cell with ordered SAMs (fig. S9). We also find that the typical FTIR signals representing the interactions between the head group of SAMs and the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ substrate remain evident after 5 or even 100 cycles, indicating that the structure of SAMs does not change substantially during long-term battery cycling (figs. S10 and S11). \n\nThe morphologies of Li deposits are examined through scanning electron microscopy. Li deposition onto the bare Cu electrode results in uneven striped Li with obvious cracks and voids after 10 and 50 cycles, whereas Li deposited in the presence of SAMs exhibits a smooth morphology (figs. S12 and S13). The morphology of the Li deposited with \n\n![](images/05e75b543137d0a10ea09a23458481e0330a15d4b387c665b916cf759b7bd042.jpg) \nFig. 2. Electrochemical performances of Li–Cu half cells and simulations of the degradation mechanism of LiTFSI. (A) CE comparison of the anodes in three cells equipped with $A l_{2}O_{3}$ , $A|_{2}0_{3}{\\cdot}00\\mathsf{C}(\\mathsf{C}\\mathsf{H}_{2})_{2}\\mathsf{N}\\mathsf{H}_{2}$ , and $A|_{2}{\\sf O}_{3}{\\cdot}00{\\sf C}({\\sf C}\\mathsf{H}_{2})_{2}{\\sf C}00\\mathsf{H}$ at current densities of 1, 2, and $3\\mathsf{m A}\\mathsf{c m}^{-2}$ with an areal capacity of 1 mA·hour $\\mathsf{c m}^{-2}$ . (B) Voltage profiles of the cell equipped with $\\mathsf{A l}_{2}\\mathsf{O}_{3}{\\cdot}\\mathsf{O}\\mathsf{O C}(\\mathsf{C H}_{2})_{2}\\mathsf{C}\\mathsf{O}\\mathsf{O H}$ at $1\\mathsf{m A}\\mathsf{c m}^{-2}$ of the 100th and 200th cycles. (C to F) Snapshots of AIMD simulations with instantaneous Bader charges (the unit of charge is |e|) illustrating the degradation dynamics: (C) 0 fs, (D) 50 fs, (E) 200 fs, and (F) 450 fs. (G and H) Electrostatic potential plotted on the isosurface of $\\uprho=0.2|e|{\\mathrm{~}}\\mathsf{b o h r}^{-3}$ (r, charge density) of oriented (G) $\\mathsf{A l}_{2}\\mathsf{O}_{3}{\\cdot}\\mathsf{O}\\mathsf{O C}(\\mathsf{C H}_{2})_{2}\\mathsf{C}\\mathsf{O}\\mathsf{O H}$ and (H) $\\mathsf{A l}_{2}\\mathsf{O}_{3}{\\cdot}\\mathsf{O}0\\mathsf{C}(\\mathsf{C}\\mathsf{H}_{2})_{2}\\mathsf{N}\\mathsf{H}_{2}$ . \n\n$$\n\\begin{array}{r}{\\mathrm{N}(\\mathrm{SO_{2}C F_{3}})_{2}^{-}+\\mathrm{e}^{-}\\rightarrow\\mathrm{NSO_{2}C F_{3}}^{-}+}\\\\ {\\mathrm{SO_{2}C F_{3}}^{-}}\\end{array}\n$$ \n\n$\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ remains uniform, whereas the morphology of the Li deposited with $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ becomes irregularly dendritic with locally aggregated sediments after 200 cycles (fig. S14). In addition, the thickness of deposits is related to the generated inactive Li debris termed “dead Li.” After 50 cycles, the thickness of the deposit with $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}C O O H}$ is found to be $\\sim36~\\upmu\\mathrm{m}$ , smaller than those with $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}N H_{2}}$ $(44\\upmu\\mathrm{m})$ and $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ $(69\\upmu\\mathrm{m})$ , indicating that $\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ can reduce the amount of dead Li (fig. S15). Therefore, SAMs with ordered terminal groups, especially $\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ , are demonstrated to greatly improve the CE and extend the cycle life of half cells. \n\nof the $\\mathrm{\\DeltaN-S}$ bond, as described in reaction Eq. 1 (27) \n\nSubsequently, the $\\mathrm{CF_{3}}^{-}$ group is removed from the $\\mathrm{SO_{2}C F_{3}}^{-}$ fragment at 200 fs, owing to the acquisition of one electron $(\\mathrm{e^{-}})$ . This $\\mathrm{CF_{3}}^{-}$ group is further decomposed into CF and $\\mathrm{F}^{-}$ at 450 fs, eventually resulting in LiF formation. These reactions can be described as follows \n\n# Simulation of functional mechanism of SAMs \n\n$$\n\\mathrm{SO_{2}C F_{3}}^{-}+\\mathrm{e}^{-}\\rightarrow\\mathrm{SO_{2}}^{-}+\\mathrm{CF_{3}}^{-}\n$$ \n\nDensity functional theory (DFT) and ab initio molecular dynamics (AIMD) calculations are carried out to explore the relationship between the oriented functional groups of SAMs and the electrochemical process. First, we illustrate the lowest unoccupied molecular orbital \n\n$$\n\\mathrm{CF_{3}}^{-}+\\mathrm{e^{-}}\\rightarrow\\mathrm{CF}+2\\mathrm{F^{-}}\n$$ \n\n(LUMO) and highest occupied molecular orbital (HOMO) energy levels of related molecules (fig. S16), which are associated with the electrolyte reaction activity in terms of frontier molecular orbital theory (26). Our calculations show that apart from the low-concentration $\\mathrm{LiNO_{3}}$ , LiTFSI has the lowest LUMO energy level $\\left(-1.03\\ \\mathrm{eV}\\right)$ and can therefore be easily reduced (i.e., accept electrons) during the battery cycling operation. \n\nWe construct four configurations based on the corresponding experimental conditions (see the supplementary materials for methodological details) to capture the thermodynamic behavior of LiTFSI. During the AIMD equilibration process up to 12 ps, the formation of LiF is observed only in the case of oriented carboxyl groups (fig. S17). To reveal the LiF formation mechanism, we trace all LiTFSI decomposition steps through the AIMD simulation time (Fig. 2, C to F). The Bader charge analysis reveals that $\\displaystyle{\\sim}-1|e|$ charge is transferred from the carboxyl group to the $\\mathrm{TFSI^{-}}$ anion at 50 fs, leading to cleavage \n\n$\\mathrm{F}^{-}+\\mathrm{Li}^{+}\\longrightarrow\\mathrm{LiF}$ (4) This LiTFSI decomposition mechanism is in good agreement with previous simulation results (28, 29). We attempt to understand the role that high-density and highly ordered functional groups play in this process. Electrostatic potential and differential charge density calculations show that the directed polar functional groups attract electrons from the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ substrate to the electrolyte (Fig. 2, G and H). The red electrostatic potential isosurface indicates electrophilicity, and the blue isosurface represents nucleophilicity (30). The dipole moment induced by carboxyl groups (higher molecular polarity compared with amino groups) facilitates transfer of more electrons from the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ slab to the electrolyte environment than that induced by amino groups (smaller molecular polarity) (31). Furthermore, the differential charge density between $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ and functional groups shows more obvious charge transfer from $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ to carboxyl groups compared with pristine $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ or amino groups (fig. S18), consistent with our electrostatic potential calculation results. In addition to the effect of induced dipole moment, the dipole-dipole interaction between free etherbased solvent molecules and carboxyl group– terminated SAMs that can mitigate solvent decomposition is also taken into consideration (32). Detailed DFT calculations show that such interaction may not be suitable for the low-polarity ether-based electrolyte used here (fig. S19). In short, the ordered orientation of the polar functional groups on the $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ surface enables the same dipole direction, which attracts electrons from $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ to the electrolyte environment. These excess electrons thus facilitate the decomposition of LiTFSI into $\\mathrm{F}^{-}$ species, finally forming LiF. \n\n# Characterization of the LiF-enriched SEI \n\nIn view of the simulated predictions of SAMinduced LiTFSI decomposition, we perform cyclic voltammetry (CV) analysis to examine the surface of Li deposited in the presence of $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}C O O H}$ . In comparison, the percentages of LiF are only 4.2 and $3.8\\%$ in the cells equipped with $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}N H_{2}}$ and $\\mathrm{{Al}_{2}\\mathrm{{O}_{3},}}$ respectively. If $\\mathrm{HOOC(CH_{2})_{2}C O O H}$ molecules are added to the electrolyte as an additive instead of forming ordered SAMs, the Li deposit has only $4.2\\%$ LiF (fig. S22). In addition, the XPS depth profiles of the Li deposited with $\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ show that LiF appears on the SEI surface and its content ratio gradually increases up to the surface of the Li metal anode (fig. S23). The results indicate that the LiF generated by SAMs can efficiently passivate the reactive surfaces to reduce the initial side reaction and can improve $\\mathrm{Li^{+}}$ diffusion throughout the SEI (36). Moreover, as the temperature is increased, the degradation kinetics may accelerate to facilitate LiF formation (fig. S24). \n\n![](images/360217e035355a2076e6a5c6f8def053e4bef39b71f479f1e7dbbc72373c9f9d.jpg) \nFig. 3. Analysis of the interfacial stability and SEI chemical composition. (A) First-cycle CV curves of cells equipped with $A l_{2}O_{3}$ , $A|_{2}0_{3}{\\cdot}00\\mathsf{C}(\\mathsf{C}\\mathsf{H}_{2})_{2}\\mathsf{N}\\mathsf{H}_{2}$ , and $\\mathsf{A l}_{2}\\mathsf{O}_{3}{\\cdot}\\mathsf{O}\\mathsf{O C}(\\mathsf{C H}_{2})_{2}\\mathsf{C}\\mathsf{O}\\mathsf{O H}$ . (B) Electrochemical impedance spectroscopy spectra of the cell equipped with $A|_{2}\\mathrm{O}_{3}{\\cdot}\\mathrm{OOC}(C H_{2})_{2}\\mathrm{COOH}$ before cycling and after 10, 50, and 100 cycles. Z′, real part of complex impedance; $Z^{\\prime\\prime}$ , imaginary part of complex impedance; Rct, charge-transfer resistance; Rb, bulk resistance; ${{\\sf W}_{0}}$ , Warburg impedance; CPE, constant phase element. (C to E) XPS spectra of the SEIs in cells with (C) $A l_{2}O_{3}$ , (D) $A|_{2}0_{3}–000(C H_{2})_{2}N H_{2}$ , and (E) $\\mathsf{A l}_{2}\\mathsf{O}_{3}{-}00\\mathsf{C}(\\mathsf{C H}_{2})_{2}\\mathsf{C O O H}$ . \n\nthe redox reactions of the electrolyte system. The CV curve of the cell with pristine $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ shows two cathodic peaks at ${\\sim}1.56$ and ${\\sim}0.65\\mathrm{V}$ corresponding to reduction of $\\mathrm{LiNO_{3}}$ and solvent, respectively (33). In addition to these two peaks, one pronounced cathodic peak at \\~1.11 V is observed in the CV curves of cells with $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ -SAMs, which is assigned to the reduction of TFSI− (Fig. 3A) (34). This peak of TFSI− reduction attenuates greatly in the subsequent cycles (fig. S20). The CV results demonstrate that SAMs facilitate the preferential reduction of LiTFSI. Impedance tests are also performed on the cells before cycling and after 10, 50, and 100 cycles. The impedance of the cell employing $\\mathrm{Al_{2}O_{3}{-}O O C(C H_{2})_{2}C O O H}$ re \n\nIn our recent studies, we have investigated the SEI in Li metal anodes at subangstrom resolution using cryo–transmission electron microscopy (cryo-TEM) (28, 37–39). In this study, we employ the same technique to directly visualize the nanostructure of the SEI. Metallic Li is deposited on a Cu grid with a capacity of 1 mA·hour $\\mathrm{cm}^{-2}$ at a current density of 1 mA $\\mathrm{cm}^{-2}$ for cryo-TEM observation. In the presence of SAMs, the deposited Li appears homogeneous with spherical morphologies (Fig. 4A and fig. S25). Various Li deposits are visualized by the cryo–scanning transmission electron microscopy (cryo-STEM), and the corresponding distributions and amounts of typical elements—such as C, O, and F—in the SEI are analyzed (Fig. 4, B and C, and figs. S25 to S28). Usually, the content of F in the SEI induced by $\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ is much higher than those induced by $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ - $\\mathrm{OOC(CH_{2})_{2}N H_{2}}$ and pristine $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ (Fig. 4D). However, the SEI generated by the dispersed HOOC $\\mathrm{(CH_{2})_{2}C O O H}$ additive without forming ordered SAMs contains a relatively low amount of F (fig. S29). Therefore, we have obtained highresolution TEM (HRTEM) images of the specific F-enriched SEI nanostructure generated by $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ -OO $\\mathrm{\\Delta)C(CH_{2})_{2}C O O H}$ . The SEI exhibits a classical mosaic structure that consists of an amorphous phase and embedded Li, $\\mathrm{Li_{2}O}$ , LiOH, and LiF nanocrystals (Fig. 4E). The crystalline phases of Li, LiOH, and $\\mathrm{Li_{2}O}$ are confirmed by matching the long-range–ordered lattices with their known lattice planes (Fig. 4, F to H) (39). Specifically, the calibrated interplanar spacing of 2.48 Å well matches the (110) plane of metallic Li (Fig. 4F). More notably, LiF nanoparticles with lattice corresponding to the (111) plane can be clearly detected in the SEI (Fig. 4I and fig. S30). In summary, both the XPS and cryo-TEM results confirm the distribution and enrichment of LiF nanocrystals in the $\\mathrm{Al_{2}O_{3}\\mathrm{-OOC(CH_{2})_{2}C O O H}}$ -induced SEI, consistent with the simulated prediction. \n\nmains relatively stable after 100 cycles (Fig. 3B). By contrast, both cells with $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ and $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}\\mathrm{{.}}}$ 一 $\\mathrm{OOC(CH_{2})_{2}N H_{2}}$ experience more substantial impedance increase (fig. S21 and table S1). The impedance evaluations show that $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ - $\\mathrm{OOC(CH_{2})_{2}C O O H}$ can deliver optimum efficiency in enhancing interfacial stability. \n\nWe next investigate the chemical composition of the SEI by applying XPS on the Li deposits after the first discharge (Fig. 3, C to E). In the C 1s spectra, the peaks assigned to C–C, C–O, $\\mathrm{C=O};$ $\\scriptstyle\\mathrm{C=O-C},$ and $\\mathrm{CF_{3}}$ originate from the decomposition of the electrolyte. In the F 1s spectra, there are two peaks of LiF and $\\mathrm{CF}_{3}$ species at 684.8 and $688.6\\mathrm{eV}.$ , respectively (35). A high percentage of LiF $(6.9\\%)$ is detected on \n\n![](images/fa86280a02f34c2f57aaafd19fe9d417b4306781dbe6a6cdc0974c31f118d6b4.jpg) \nFig. 4. Cryo-TEM visualization of the Li deposits and SEI nanostructures. (A) Morphology of Li plated on a Cu grid in the presence of $A|_{2}0_{3}{\\cdot}00\\mathsf{C}(\\mathsf{C}\\mathsf{H}_{2})_{2}\\mathsf{C}00\\mathsf{H}.$ . (B) Cryo-STEM image of Li deposit in the presence of $A|_{2}\\mathrm{O}_{3}{\\cdot}\\mathrm{O}\\mathrm{OC}(\\mathrm{CH}_{2})_{2}\\mathrm{COOH}$ and (C) corresponding elemental distributions of C, O, F, and S. (D) Elemental mass ratios of the SEIs formed in three cells equipped with $A l_{2}O_{3}$ , $A l_{2}O_{3}{-}00\\mathsf{C}(C H_{2})_{2}N H_{2}$ , and $A|_{2}\\mathrm{O}_{3}{\\cdot}\\mathrm{OOC}(C H_{2})_{2}\\mathrm{COOH}.$ . (E) Enlarged TEM image of the $\\mathsf{L i}/\\mathsf{A l}_{2}\\mathsf{O}_{3}{-}00\\mathsf{C}(\\mathsf{C}\\mathsf{H}_{2})_{2}\\mathsf{C}00\\mathsf{H}$ \ninterface, where the typical mosaic SEI structure and the incorporated crystalline regions are shown. (Inset) Corresponding fast Fourier transform with yellow circle indexed to LiF, $2.32\\AA$ (PDF#45-1460); red circle indexed to Li, $2.48\\AA$ (PDF#15-0401); white circle indexed to $\\mathsf{L i}_{2}0$ 2.66 Å (PDF#12-0254); and blue circle indexed to LiOH, 4.35 Å (PDF#32-0564). (F to I) HRTEM images of (F) Li, (G) LiOH, (H) $\\mathsf{L i}_{2}0$ , and (I) LiF nanocrystals with long-range–ordered lattices. \n\n# Performance of cells containing SAMs under stringent conditions \n\nReversible Li plating and stripping are evaluated by testing symmetric cells. The symmetric cell with carboxyl group–terminated SAMs (SAMsC) exhibits steady cyclability over 1000 cycles for more than 2500 hours, with a small overpotential of $40\\mathrm{mV}$ (Fig. 5A). By contrast, the symmetric cell with $\\mathrm{{Al}_{2}\\mathrm{{O}_{3}}}$ exhibits a much larger overpotential $75\\mathrm{mV}$ for 700 hours), with greatly reduced cycle life. Even when the current density and areal capacity are increased to $5\\mathrm{mAcm^{-2}}$ and 5 mA·hour $\\mathrm{cm}^{-2}$ , respectively, the symmetric cell with SAMsC can still be steadily cycled over 600 hours (Fig. 5B). For the full cell tests, coin cells with a $\\mathrm{LiFePO_{4}}$ (LFP) cathode and a Li anode (Li foil or Li-deposited Cu) are evaluated at a current density of 1 C in a LiTFSI-containing ether electrolyte in the presence of SAMsC and amino group– terminated SAMs (SAMsA). The Li//SAMsC// LFP cell can be cycled steadily over 1000 cycles, with a capacity retention of $92.8\\%$ (fig. S31). Notably, the full cell of Li//SAMsC//LFP under a low capacity ratio of the negative electrode to the positive electrode (N/P ratio of ${\\sim}3^{\\cdot}$ ) can still exhibit an enhanced life span over 450 cycles, with a capacity retention above $80\\%$ and an average CE above $99.9\\%$ (Fig. 5C), indicative of a promising strategy to boost high–energy density LMBs (table S2). Even if the ratio of electrolyte weight to cathode capacity is further decreased to below $5\\mathrm{g}\\mathrm{A}^{-1}$ ·hour−1 with lean electrolyte conditions $(15\\upmu\\mathrm{l})$ , the full cell of Li//SAMsC//LFP shows marked cycling stability, with little capacity loss over 270 cycles (fig. S32). The Li//SAMsC//LFP full cell also delivers higher discharge specific capacities (163 to 137 mA·hour $\\mathbf{g}^{-1}.$ ) at current densities ranging from 0.2 to 3 C (Fig. 5, D and E) than the Li//LFP and Li//SAMsA//LFP cells. After the current density is reduced back to $0.5\\mathrm{C}$ , conditions (fig. S36). The improved cycle life proves the substantial advantages of the LiFrich SEI originating from the surface dipole– directed degradation of Li salts. \n\nWith the use of a SAM-grafted separator, we have demonstrated a strategy to regulate electrolyte degradation for constructing stable LMBs. Comprehensive simulations and characterizations reveal the critical role of ordered polar carboxyl groups in promoting the cleavage of C–F bonds to generate a LiF-rich SEI involving dipole moment–induced excess electrons. The LiF-enriched SEI is beneficial for stabilizing the Li/electrolyte interface, thus substantially inhibiting the formation of Li dendrites and boosting the life span of the Li anode. This long-established SAMs technique based on surface chemistry provides a solution to uncontrollable electrolyte degradation and SEI formation in batteries. With SAM-grafted separators, full cells of LMBs exhibit enhanced cyclability even under stringent conditions. This facile strategy can potentially be extended to other electrode systems by tailoring the molecular structures of SAMs to build better energy devices. \n\n# REFERENCES AND NOTES \n\n![](images/9e95caf74689829296ff63ea0c85dccd84f63c7f26916d73b9c490593f94e815.jpg) \nFig. 5. Electrochemical performance of symmetric half cells and full cells equipped with SAMs. (A and B) Galvanostatic discharge and charge voltage curves of the symmetric coin cells at (A) $1\\mathsf{m A}\\mathsf{c m}^{-2}$ with an areal capacity of 1 mA·hour $\\mathsf{c m}^{-2}$ and at (B) $5\\mathsf{m A c m}^{-2}$ with an areal capacity of 5 mA·hour $\\mathsf{c m}^{-2}$ . (C) Long-term cycling performance of the batteries using a Li-deposited Cu anode (10 mA·hour $\\mathsf{c m}^{-2}.$ ), a LFP cathode (3.2 mA·hour $\\mathsf{c m}^{-2}.$ ), and a LiTFSI-containing ether-based electrolyte $(60~\\upmu|)$ at a current density of 1 C ( $\\mathsf{L}\\mathsf{C}=170\\mathsf{m A}\\mathsf{g}^{-1};$ . (D) Rate performance of Li//LFP, Li//SAMsA//LFP, and Li//SAMsC// LFP full cells with a N/P ratio of 3.5. (E) Discharge and charge voltage profiles of a Li//SAMsC//LFP full cell at different current densities. \n\nthe reversible capacity of Li//SAMsC//LFP recovers to 163 mA·hour $\\mathbf{g}^{-1}:$ , indicating excellent rate performance (Fig. 5D). In addition, SAMs can be employed to boost the performance of cells with highly concentrated electrolytes (HCEs). The SAMsC-based full cell with a higher concentration of LiTFSI generates more LiF in the SEI, thus rendering a prolonged life span of the battery under the HCE condition (fig. S33). Using another typical unstable \n\n1. J. Liu et al., Nat. Energy 4, 180–186 (2019). \n2. X. B. Cheng, R. Zhang, C. Z. Zhao, Q. Zhang, Chem. Rev. 117, 10403–10473 (2017). \n3. L. Li et al., Science 359, 1513–1516 (2018). \n4. D. C. Lin, Y. Y. Liu, Y. Cui, Nat. Nanotechnol. 12, 194–206 (2017). \n5. C. B. Jin et al., Nat. Energy 6, 378–387 (2021). \n6. C. Fang et al., Nature 572, 511–515 (2019). \n7. Z. W. Zhang et al., Science 375, 66–70 (2022). \n8. Y. Gao et al., Nat. Energy 5, 534–542 (2020). \n9. P. C. Zou et al., Chem. Rev. 121, 5986–6056 (2021). \n10. Y. Z. Li et al., Science 358, 506–510 (2017). \n11. J. Alvarado et al., Energy Environ. Sci. 12, 780–794 (2019). \n12. M. Q. Wang et al., J. Phys. Chem. C 122, 9825–9834 (2018). \n13. D. J. Yoo, S. Yang, K. J. Kim, J. W. Choi, Angew. Chem. Int. Ed. 59, 14869–14876 (2020). \n14. X. Q. Zhang, X. B. Cheng, X. Chen, C. Yan, Q. Zhang, Adv. Funct. Mater. 27, 1605989 (2017). \n15. X. L. Fan et al., Sci. Adv. 4, eaau9245 (2018). \n16. M. Chen et al., Adv. Funct. Mater. 31, 2102228 (2021). \n17. M. Mitsuya, Langmuir 10, 1635–1637 (1994). \n18. J. C. Love, L. A. Estroff, J. K. Kriebel, R. G. Nuzzo, G. M. Whitesides, Chem. Rev. 105, 1103–1169 (2005). \n19. R. W. Yi, Y. Y. Mao, Y. B. Shen, L. W. Chen, J. Am. Chem. Soc. 143, 12897–12912 (2021). \n20. S. Duhm et al., Nat. Mater. 7, 326–332 (2008). \n21. T. Morita, S. Kimura, J. Am. Chem. Soc. 125, 8732–8733 (2003). \n22. L. J. Zuo et al., J. Am. Chem. Soc. 137, 2674–2679 (2015). \n23. M. S. Lim et al., Langmuir 23, 2444–2452 (2007). \n24. C. F. Li et al., Nat. Commun. 10, 1363 (2019). \n25. D. C. Lin et al., Nat. Nanotechnol. 11, 626–632 (2016). \n26. Z. X. Wang et al., Adv. Energy Mater. 10, 1903843 (2020). \n27. H. Yildirim, J. B. Haskins, C. W. Bauschlicher Jr., J. W. Lawson, J. Phys. Chem. C 121, 28214–28234 (2017). \n28. O. W. Sheng et al., Adv. Mater. 32, 2000223 (2020). \n29. L. E. Camacho-Forero, P. B. Balbuena, Phys. Chem. Chem. Phys. 19, 30861–30873 (2017). \n30. P. Politzer, J. S. Murray, in Chemical Reactivity Theory, vol. 17 (CRC, 2009), pp. 243–254. \n31. R. A. Lewis et al., Proc. Natl. Acad. Sci. U.S.A. 78, 4579–4583 (1981). \n32. J. Bae et al., Energy Environ. Sci. 12, 3319–3327 (2019). \n\ncathode, the Li//SAMsC// $\\mathrm{\\LiNi_{0.8}C o_{0.1}M n_{0.1}O_{2}}$ (NCM811) full cell also has enhanced cyclability (fig. S34) and rate performance (fig. S35). The potential practical application of SAMs is further demonstrated in pouch cells. The pristine Li//LFP pouch cell with a N/P ratio of ${\\sim}5$ manifests rapid capacity decay toward battery failure, whereas the Li//SAMsC//LFP pouch cell exhibits much better cycling stability, with an extended cycle life under similar \n\n33. H. P. Wu, Y. Cao, L. X. Geng, C. Wang, Chem. Mater. 29, \n3572–3579 (2017). \n34. B. Tong et al., J. Power Sources 400, 225–231 (2018). \n35. S. F. Liu et al., Adv. Mater. 31, 1806470 (2019). \n36. J. H. Zheng et al., J. Mater. Chem. A 9, 10251–10259 (2021). \n37. H. D. Yuan et al., Sci. Adv. 6, eaaz3112 (2020). \n38. Y. J. Liu et al., Acc. Chem. Res. 54, 2088–2099 (2021). \n39. Z. J. Ju et al., Nat. Commun. 11, 488 (2020). \n\n# ACKNOWLEDGMENTS \n\nFunding: The authors acknowledge financial support by the National Natural Science Foundation of China (grants 51722210, \n\n51972285, U21A20174, and 52102314), the Natural Science Foundation of Zhejiang Province (grants LD18E020003 and LQ20E030012), and the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang (2020R01002). Author contributions: Y.L., X.T., Y.W., and X.W.L. conceived the idea and co-wrote the manuscript. Y.L., C.J., and C.M. designed and performed the experiments and analyzed the data. O.S. contributed to interpreting the mechanism. G.L. assisted in TEM characterizations for materials. All authors discussed the results. Competing interests: The authors declare no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abn1818 \nMaterials and Methods \nFigs. S1 to S36 \nTables S1 and S2 \nReferences (40–60) \n9 November 2021; accepted 20 January 2022 \n10.1126/science.abn1818 " + }, + { + "id": "10.1038_s41560-021-00962-y", + "DOI": "10.1038/s41560-021-00962-y", + "DOI Link": "http://dx.doi.org/10.1038/s41560-021-00962-y", + "Relative Dir Path": "mds/10.1038_s41560-021-00962-y", + "Article Title": "Rational solvent molecule tuning for high-performance lithium metal battery electrolytes", + "Authors": "Yu, Z; Rudnicki, PE; Zhang, ZW; Huang, ZJ; Celik, H; Oyakhire, ST; Chen, YL; Kong, X; Kim, SC; Xiao, X; Wang, HS; Zheng, Y; Kamat, GA; Kim, MS; Bent, SF; Qin, J; Cui, Y; Bao, ZN", + "Source Title": "NATURE ENERGY", + "Abstract": "Electrolyte engineering improved cycling of Li metal batteries and anode-free cells at low current densities; however, high-rate capability and tuning of ionic conduction in electrolytes are desirable yet less-studied. Here, we design and synthesize a family of fluorinated-1,2-diethoxyethanes as electrolyte solvents. The position and amount of F atoms functionalized on 1,2-diethoxyethane were found to greatly affect electrolyte performance. Partially fluorinated, locally polar -CHF2 is identified as the optimal group rather than fully fluorinated -CF3 in common designs. Paired with 1.2 M lithium bis(fluorosulfonyl)imide, these developed single-salt-single-solvent electrolytes simultaneously enable high conductivity, low and stable overpotential, >99.5% Li||Cu half-cell efficiency (up to 99.9%, +/- 0.1% fluctuation) and fast activation (Li efficiency >99.3% within two cycles). Combined with high-voltage stability, these electrolytes achieve roughly 270 cycles in 50-mu m-thin Li||high-loading-NMC811 full batteries and >140 cycles in fast-cycling Cu||microparticle-LiFePO4 industrial pouch cells under realistic testing conditions. The correlation of Li+-solvent coordination, solvation environments and battery performance is investigated to understand structure-property relationships. Cycling capability, especially at high rates, is limited for lithium metal batteries. Here the authors report electrolyte solvent design through fine-tuning of molecular structures to address the cyclability issue and unravel the electrolyte structure-property relationship for battery applications.", + "Times Cited, WoS Core": 539, + "Times Cited, All Databases": 561, + "Publication Year": 2022, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000742253900001", + "Markdown": "# Rational solvent molecule tuning for highperformance lithium metal battery electrolytes \n\nZhiao Yu   1,2, Paul E. Rudnicki1, Zewen Zhang $\\oplus3$ , Zhuojun Huang3, Hasan Celik4, Solomon T. Oyakhire1, Yuelang Chen $\\textcircled{10}1,2$ , Xian Kong1, Sang Cheol Kim3, Xin Xiao $\\textcircled{10}$ 3, Hansen Wang3, Yu Zheng1,2, Gaurav A. Kamat $\\left.\\langle\\bullet\\right\\rangle^{\\cdot}$ 1, Mun Sek Kim $\\textcircled{10}1,3$ , Stacey F. Bent1, Jian Qin $@^{1}$ ✉, Yi Cui $\\textcircled{10}3,5\\boxtimes$ and Zhenan Bao   1 ✉ \n\nElectrolyte engineering improved cycling of Li metal batteries and anode-free cells at low current densities; however, high-rate capability and tuning of ionic conduction in electrolytes are desirable yet less-studied. Here, we design and synthesize a family of fluorinated-1,2-diethoxyethanes as electrolyte solvents. The position and amount of F atoms functionalized on 1,2-diethoxyethane were found to greatly affect electrolyte performance. Partially fluorinated, locally polar $-C H F_{2}$ is identified as the optimal group rather than fully fluorinated $-C F_{3}$ in common designs. Paired with 1.2 M lithium bis(fluorosulfonyl)imide, these developed single-salt-single-solvent electrolytes simultaneously enable high conductivity, low and stable overpotential, $>99.5\\%$ Li||Cu half-cell efficiency (up to $99.9\\%_{r\\pm}0.1\\%$ fluctuation) and fast activation (Li efficiency $>99.3\\%$ within two cycles). Combined with high-voltage stability, these electrolytes achieve roughly 270 cycles in $50-\\upmu\\m m$ -thin Li||high-loading-NMC811 full batteries and $>140$ cycles in fast-cycling Cu||microparticle-LiFeP $\\bullet_{4}$ industrial pouch cells under realistic testing conditions. The correlation of $\\mathbf{L}\\mathbf{\\dot{i}}^{+}$ –solvent coordination, solvation environments and battery performance is investigated to understand structure–property relationships. \n\nithium (Li) metal battery is highly pursued as the nextgeneration power source1,2. However, the implementation of Li metal anode is hindered by poor cycle life, which originates from uncontrollable Li/electrolyte side reactions and the resulting unstable and fragile solid–electrolyte interphase (SEI). Subsequently, the notorious issues such as cracking of SEI, dendritic Li growth and ‘dead Li’ formation generate a vicious cycle, leading to irreversible Li consumption and finally battery failure3–5. \n\nLiquid electrolyte engineering is regarded as a cost-effective and pragmatic approach6–10 to address the root cause, that is, uncontrollable parasitic reactions between Li metal anodes and electrolytes. By fine-tuning electrolyte components, the SEI chemistry and Li morphology can be regulated to improve Li metal cyclability. Several promising strategies have been investigated, including high concentration electrolytes11, localized high concentration electrolytes12,13, mixed solvents14–16, additive tuning17, liquified gas electrolytes18, dual-salt-dual-solvent electrolytes19,20 and single-salt-single-solvent electrolytes21–25. \n\nTo enable practical Li metal or anode-free batteries, several key requirements10,21,26 should be simultaneously fulfilled for a promising electrolyte. First, high Coulombic efficiency (CE) including the initial cycles, that is, fast activation of Li metal anode; second, anodic stability to avoid cathode corrosion; third, low electrolyte consumption under practical operating conditions such as lean electrolyte and limited Li inventory; fourth, moderate Li salt concentration for cost-effectiveness and last, high boiling point and the absence of any gassing issue to ensure processability and safety. \n\nBeyond these requirements, high ionic conductivity is another critical parameter for realistic cycling rates. Several papers21,27–29 reported improved Li metal stability using weakly solvating solvents. However, insufficient solvation will cause ion clustering, poor ion motion and low solubility of salts, leading to low ionic conductivity. Therefore, fine-tuning of the solvation capability30 of the solvent is necessary to simultaneously achieve Li metal cyclability, oxidative stability and ionic conductivity of the electrolyte. \n\nIn this work, we systematically investigate a family of fluorinated-1,2-diethoxyethane (fluorinated-DEE) molecules that are readily synthesized on large scales to use as the electrolyte solvents. Selected positions on 1,2-diethoxyethane (DEE, distinct from the diethyl ether previously reported24) are functionalized with various numbers of fluorine (F) atoms through iterative tuning, to reach a balance between CE, oxidative stability and ionic conduction (Fig. 1a). Paired with $1.2\\mathrm{M}$ lithium bis(fluorosulfonyl)imide (LiFSI), these fluorinated-DEE-based, single-salt-single-solvent electrolytes are thoroughly characterized. Their $\\mathrm{Li^{+}}$ –solvent binding energies and geometries (from density functional theory (DFT) calculations), solvation environments (from solvation free energy measurements31, 7Li-nuclear magnetic resonance (NMR), molecular dynamics simulations and diffusion-ordered spectroscopy $(\\mathrm{DOSY})^{32},$ ), and results in batteries (measured ion conductivities and cell overpotentials) are found to be tightly correlated with each other. The above studies lead to an unexpected finding: a partially fluorinated, locally polar ${\\mathrm{-CHF}}_{2}$ group results in higher ionic conduction than fully fluorinated ${\\mathrm{-CF}}_{3}$ while still maintaining excellent electrode stability. Specifically, the best-performing F4DEE and F5DEE solvents both contain ${\\mathrm{-CHF}}_{2}$ group(s). In addition to high ionic conductivity and low and stable overpotential, they achieve roughly $99.9\\%$ Li CE with $\\pm0.1\\%$ fluctuation as well as fast activation, that is, the CEs of the $\\mathrm{Li}||$ copper $\\mathrm{(Cu)}$ half cells reach ${>}99.3\\%$ from the second cycle. Aluminium (Al) corrosion is also suppressed due to the oxidative stability that originates from suitable amount of fluorination. These features enable roughly 270 cycles in thin Li $(50\\mathrm{-}\\upmu\\mathrm{m}$ thick)||high-loading-NMC811 $\\mathrm{(LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2},}$ roughly $4.9\\mathrm{mAh}\\mathrm{cm}^{-2}.$ ) full batteries and ${>}140$ cycles in fast-cycling anode-free $\\mathrm{Cu}\\vert\\vert$ microparticle-LFP $\\mathrm{(LiFePO_{4},}$ roughly $2.1\\mathrm{mAhcm^{-2}}.$ ) industrial pouch cells, both of which stand among the state-of-the-art performances. \n\n![](images/b1b1235d542e6464d8d4a964ddfeb0e380a7c26e8ed52d053481991aba1b3210.jpg) \nFig. 1 | Step-by-step design principles of the fluorinated-DEE solvent family. a, Logical flow, starting from FDMB, for the design of the fluorinated-DEE family. b, Weak $\\mathsf{L i^{+}}$ –FDMB coordination structure. c, Conventional strong coordination structure of $\\mathsf{L i^{+}}$ –EO segments. Two examples are given here: ${\\mathsf{L i}}^{+}.$ – DME in liquid electrolytes and ${\\mathsf{L i}}^{+}$ –polyethylene oxide (PEO) in solid polymer electrolytes. d,e, Spatial configuration and dipole direction of $-C F_{3}$ (d) and $-C H F_{2}$ (e). \n\n# Design logic of fluorinated-DEE molecular family \n\nDespite the high stability towards Li metal anodes and high-voltage cathodes, our previously reported fluorinated 1,4-dimethoxylbutane (FDMB) solvent (Fig. 1a) was found to have the drawbacks of poor ionic conductivity and large overpotential16,21,33, which stem from the weak solvation ability of FDMB molecules (Fig. 1b). Such a feature hindered ion diffusion due to the formation of ionic clusters as most electrolyte solvates, while on the other hand benefiting Li metal anode stability11,34. To address this issue, we rationalize that ethylene oxide structure may be desirable as it is a known and widely used segment27,35 for good solvation and separating $\\mathrm{Li^{+}}$ and the anion. The ether groups in the ethylene oxide segment, separated by two methylene groups, can form a stable five-member ring with $\\mathrm{Li^{+}}$ (Fig. 1c), thus enhancing cation–anion separation. Such a chelating structure has been commonly observed in liquid electrolytes27 containing 1,2-dimethoxyethane (DME) and in solid polymer electrolytes35 using polyethylene oxide. However, here we select DEE (Fig. 1a) instead of DME as the starting backbone for the following additional reasons. First, the DEE electrolyte has been inadequately studied in the community despite recent reports on its superior high-rate performance than DME for Li metal27,28 and silicon36 anodes. Second, the ethyl terminal groups of DEE provide more structural tunability than DME and suitable $\\upbeta$ -fluorination32,37,38 is expected to endow DEE with both stability and high conductivity. \n\nAs will be elaborated in the following sections, the Li metal CE and oxidative stability of unmodified DEE still fall short when tested under strict full-cell conditions, albeit performing slightly better than DME. Therefore, starting from DEE structure, we first incorporate the electron-withdrawing ${\\mathrm{-CF}}_{3}$ groups39 in the $\\upbeta$ -position of DEE, to enhance both Li metal and oxidative stability while retaining its solvation ability of $-\\mathrm{O}-$ groups (Fig. 1a,d). The two obtained electrolyte solvents, F3DEE and F6DEE (Fig. 1a), are found to outperform their DEE counterpart in Li metal batteries, although overfluorination decreases the ionic conductivity of \n\nF6DEE. Next, we further finely tune the degree of fluorination, that is, changing from ${\\mathrm{-CF}}_{3}$ groups to $\\mathrm{-CHF}_{2}.$ to obtain more ionically conductive and stable solvents, F4DEE and F5DEE (Fig. 1a). The partially fluorinated, asymmetric ${\\mathrm{-CHF}}_{2}$ group, as will be discussed in detail later, contains a local dipole (Fig. 1e) that enables strong intermolecular interactions in F4DEE and F5DEE and better $\\mathrm{Li^{+}}$ solvation than its all-fluorinated, symmetric counterpart, ${\\mathrm{-CF}}_{3}$ (Fig. 1d). The stronger intermolecular interaction is also evidenced by the high boiling points and viscosities measured for F4DEE and F5DEE (Supplementary Figs. 1 and 2 and Supplementary Table 1). The iteratively designed molecules F4DEE and F5DEE integrate several desired properties, including fast ion conduction, low and stable cell overpotential, high Li metal efficiency, fast activation and oxidative stability. \n\nNone of the designed molecules are commercially available, and they were obtained by two-step syntheses on large scales (Methods). The general physicochemical properties of this molecular family and their $1.2\\mathrm{M}$ LiFSI electrolytes are determined and shown in Supplementary Table 1. \n\n# Improved ionic transport by experimental results \n\nThe critical targets in this work are to improve the ionic conductivity and interfacial transport issues of the already high-performing FDMB electrolyte. The 1 M LiFSI/FDMB electrolyte was used to maintain consistency with our previous reports16,21,33 while $1.2\\mathrm{M}$ LiFSI was dissolved in fluorinated-DEEs for optimized conductivity. The ionic conductivities measured with separators followed the trend of $\\mathrm{LP40}\\cong\\mathrm{DEE}\\gg\\mathrm{F4DEE}\\cong\\mathrm{F3DEE}>\\mathrm{F5DEE}\\gg\\mathrm{F6DEE}\\cong\\mathrm{FD}$ MB (Fig. 2a), which is fully consistent with our rationales. Those measured without separators by Swagelok cells showed a similar trend (Fig. 2b, Supplementary Fig. 2 and Supplementary Table 1), although the values are higher due to the absence of the separator. \n\nLi||Li symmetric cells were used to evaluate the overall ionic transport, especially interfacial conduction. As shown in Fig. 2c, the overpotential of 1 M LiFSI/FDMB cell vastly increased with cycling; by contrast, the cells using fluorinated-DEE electrolytes maintained stable and low overpotentials. The electrochemical impedance spectra (EIS) of Li||Li cells and the voltage plateau of $\\mathrm{Li}||\\mathrm{Cu}$ cells at different cycle numbers confirmed these cycling observations (Supplementary Figs. 3–9). Although the large overpotential increase in the FDMB electrolyte caused only a small capacity drop in full cells according to our previous reports16,21,33, the excellent maintenance of low overpotential in fluorinated-DEE electrolytes is required for realistic batteries. The zoomed-in plot of Li||Li cycling overpotentials shows the trend of $\\mathrm{DEE}<\\mathrm{F}3\\mathrm{DEE}\\cong\\mathrm{F4DEE}<\\mathrm{F5DEF}$ , ≪ F6DEE $\\ll$ FDMB (Fig. 2d), which is in accord with the inverse of the ion conductivity trends mentioned above. \n\n![](images/987bf2eaa917b0b8a825e020b3ca28828fb410c3127f3a9b18d60e3935ec5ea9.jpg) \nFig. 2 | Ionic conductivity and cycling overpotential of FDMB and fluorinated-DEE electrolytes. a,b, Ionic conductivities of developed electrolytes with (a) and without (b) separators. Each bar stands for the mean of two replicated ion conductivity measurements and every single measurement is shown with hollow dots. The 1 M LiFSI/FDMB data in b were extracted from ref. 21. c,d, Cycling performance of Li||Li symmetric cells. Note: d is a portion of $\\blacktriangledown\\mathbf{c}$ (from 190 h to $230{\\mathsf{h}};$ ) to enable visualization of the overpotential trends. \n\n# Rationales for improved ionic conduction \n\nIn addition to the experimental observations, we here rationalize the improvement of ionic transport in fluorinated-DEE electrolytes via thorough theoretical studies, and correlate both theoretical and experimental results for better understanding the structure–property relationships. \n\nWe first used DFT to determine optimized binding configurations between $\\mathrm{Li^{+}}$ and each type of solvent molecule (Fig. 3a–f). While the coordination structure of $\\mathrm{Li^{+}}$ –FDMB and $\\mathrm{Li^{+}{-}D E E}$ matched with those in the previous report21, the $\\mathrm{Li^{+}}$ ions all showed tripod or tetrapod coordination geometry with fluorinated-DEEs whose F atoms interacted with $\\mathrm{Li^{+}}$ ions. The $\\mathrm{Li^{+}}$ showed stronger interaction (that is, shorter Li–F distance) with ${\\mathrm{-CHF}}_{2}$ than ${\\mathrm{-CF}}_{3}$ . Taking $\\mathrm{Li^{+}}$ –F5DEE as a representative example (Fig. 3f), the Li–F (on $\\mathrm{-CHF}_{2})$ distance was $1.{\\dot{9}}6{\\dot{\\mathrm{A}}}$ versus $2.04\\mathring{\\mathrm{A}}$ for ${\\mathrm{-CF}}_{3}$ . The nonparticipation of ${\\mathrm{-CF}}_{3}$ in $\\mathrm{Li^{+}}$ solvation was also proved by Amanchukwu et al.25 recently. Such a stronger interaction between $\\mathrm{Li^{+}}$ and the ${\\mathrm{-CHF}}_{2}$ group can be rationalized by the fact that ${\\mathrm{-CHF}}_{2}$ group is locally polar and more negatively charged than ${\\mathrm{-CF}}_{3}$ in the calculated electrostatic potentials (Fig. 1e and Supplementary Fig. 10). The upfield shift of ${\\mathrm{-CHF}}_{2}$ signals detected by $^{19}\\mathrm{F}$ -NMR spectra of fluorinated-DEE electrolytes also supports this Li–F interaction40,41 (Supplementary Fig. 11). \n\nMolecular dynamics simulations were conducted to further investigate the $\\mathrm{Li^{+}}$ solvation sheath and determine the distribution of $\\mathrm{Li^{+}}$ solvates (Fig. 3g–l and Supplementary Figs. 12–17). \n\nThe functional groups tightly interacting with $\\mathrm{Li^{+}}$ in the first solvation sheath were consistent with those in the aforementioned DFT results. Particularly, the Li–F radial distribution functions (RDFs) of simulated $1.2\\mathrm{M}$ LiFSI/F5DEE clearly demonstrated more $\\mathrm{~F~}$ atoms on ${\\mathrm{-CHF}}_{2}$ participating in $\\mathrm{Li^{+}}$ solvation than those on ${\\mathrm{-CF}}_{3}$ (Supplementary Fig. 17). More information was provided by the distribution of $\\mathrm{Li^{+}}$ solvates, that is, percentages of solvent surrounded $\\mathrm{Li^{+}}$ (SSL), $\\mathrm{Li^{+}}$ –anion single pair (LASP) and $\\mathrm{Li^{+}}$ –anion cluster (LAC), each of which has a distinct number of $\\mathrm{Li^{+}}$ coordinating anions of 0, 1 and $\\geq2$ in the primary solvation sheath, respectively. It is noteworthy that the classification of these $\\mathrm{Li^{+}}$ solvates is slightly different from the conventional definition of solvent separated ion pair, contact ion pair or aggregate11,15,24,25. The latter ones use the anion as the centre to count the coordinating $\\mathrm{Li^{+}}$ number; instead, the SSL, LASP and LAC herein are proposed on the basis of $\\mathrm{Li^{+}}$ solvation structures. In all electrolytes, LAC dominated the $\\mathrm{Li^{+}}$ solvate species but the content of SSL and LASP (both classified as non-LAC) varied dramatically from one electrolyte to another, indicating substantial difference in ion dissociation degree. While almost no SSL and only a small proportion of LASP was observed in FDMB or F6DEE electrolytes, the non-LAC increased in the order of F5DEE $(7.5\\%$ ${\\mathrm{SSL}}+11.9\\%$ LASP), F4DEE $(9.5\\%$ $\\mathrm{SSL}+10.3\\%$ LASP), F3DEE $(4.9\\%\\mathrm{SSL}+31.4\\%$ LASP) and DEE $(12.0\\%\\mathrm{SSL}+37.6\\%$ LASP). \n\nTo explain structure–property correlations in depth, the following seven parameters/properties were leveraged to cross-validate the $\\mathrm{Li^{+}}$ –solvent interaction, solvation environments and properties measured in batteries (Fig. 3m): (1) $\\mathrm{Li^{+}}$ –solvent binding energies from DFT (Fig. 3a–f); (2) coordinating solvent numbers calculated from DOSY–NMR32 (Supplementary Table 2 and Supplementary Fig. 18); (3) non-LAC percentages from molecular dynamics simulations (Fig. 3g–l and Supplementary Figs. 12–17); (4) chemical shifts of 7Li-NMR (Supplementary Fig. 19); (5) solvation free energies measured according to our recent work31 (Supplementary Fig. 20); (6) ionic conductivities shown in Fig. 2a and (7) overall cycling overpotentials of Li||Li cell extracted from Fig. 2c (converted to inversed overpotentials to better represent conduction property). \n\n![](images/4db6773e4cc5160db296c22f1a258039e14693edeaa4d8cb470e2c4e3d29a7f5.jpg) \nFig. 3 | Theoretical and experimental study on the ${\\bf L}{\\bf\\dot{i}}^{+}$ solvation structures and the structure–property correlations. a–f, Coordination structures and binding energies between one ${\\mathsf{L i}}^{+}$ ion and one solvent molecule calculated using DFT. a, Li+–FDMB. b, Li+–F6DEE. c, Li+–F5DEE. d, Li+–F4DEE. e, ${\\mathsf{L i}}^{+}$ –F3DEE. f, Li+–DEE. g–l, Most probable solvation structures of the first ${\\mathsf{L i}}^{+}$ solvation sheath from molecular dynamics (MD) simulations and the distribution of different ${\\mathsf{L i}}^{+}$ solvates, that is, SSL, LASP and LAC. g, 1 M LiFSI/FDMB. h, 1.2 M LiFSI/F6DEE. i, 1.2 M LiFSI/F5DEE. j, 1.2 M LiFSI/F4DEE. k, 1.2 M LiFSI/ F3DEE. l, 1.2 M LiFSI/DEE. The coordinating atoms on solvents (O and F) are labelled. Colour scheme of molecules: Li, dark grey; F, pink; O, red; C, light blue; N, navy; S, yellow; and H, white. m, Structure–property relationship plot of ${\\mathsf{L i}}^{+}$ –solvent binding, solvation environments and properties measured in batteries. The axes are shown in gradient height and each axis corresponds to the line chart with the same colour. \n\nAs plotted in Fig. $3\\mathrm{m}$ , these parameters follow similar trends against the choice of electrolytes. The main logic and rationales are as follows. First, more solvent molecules participating in the $\\mathrm{Li^{+}}$ solvation sheath, that is, higher coordination numbers calculated by DOSY and more non-LAC solvates shown in molecular dynamics simulations, indicate greater binding ability and stronger $\\mathrm{Li^{+}}$ –solvent interaction regardless of minor deviations in the trend24,42; meanwhile, more coordinating solvents dispel electrondense FSI– anions near $\\mathrm{Li^{+}}$ and cause downfield (less negative) shift of 7Li-NMR peak. Second, solvation free energy is an overall estimation of the solvation environment31 (and the extent of Gibbs free energy decrease) between $\\mathrm{Li^{+}}$ ions and surrounding species including both solvents and anions. Since the anion was fixed as FSI– in this work, stronger binding solvents will lead to more negative solvation energies. Third, at moderate concentrations where the vehicular mechanism dominates $\\mathrm{Li^{+}}$ transport11,34, strong binding solvents and good solvation reduce severe $\\mathrm{Li^{+}{-}F S I^{-}}$ clustering (revealed by increasing non-LAC percentage and downfield $^\\mathrm{7Li}$ shift), and result in separated mobile $\\mathrm{Li^{+}}$ charge carriers11,24,25,36 that are responsible for the higher ionic conductivity and lower overall overpotential obtained in batteries. Last but not the least, it is worth noting that all the fluorinated-DEEs should still be classified as weakly solvating solvents; however, fine-tuning of fluorination enables sufficient solvation for fast transport while retaining electrode stabilities. \n\n![](images/b8684df591b3e1910dc0f4ef6d3096544ce59c65be21b4ad6d8b9d6211e3a0bc.jpg) \nFig. 4 | Li metal efficiency and high-voltage stability. a–d, Li||Cu half cells showing the Li metal initial activation at $0.5\\mathsf{m A c m^{-2}}$ current density and 1 mAh cm−2 areal capacity (a), long cycling at $0.5\\mathsf{m A c m^{-2}}$ and 1 mAh cm−2 (b,c), and initial activation at $0.5\\mathsf{m A c m}^{-2}$ and $5\\mathsf{m A h c m}^{-2}$ (d). Note: c is the zoomed-in plot of b from the 100th to the 600th cycles. e, Aurbach protocol43,44 in Li||Cu half cells to calculate the average Li metal CE (replicated results are shown in Supplementary Fig. 25). f, LSV of Li||Al half cells to show anodic stability and tolerance to Al corrosion. Note: replicated cell results are shown in a–d. \n\nThese arguments can be further cross-validated by attenuated total reflection–Fourier transform infrared spectroscopy (ATR– FTIR, Supplementary Fig. 21). All these factors and their correlations are consistent with each other and fill a broad range of scales ranging from molecular-level structure to mesoscopic $\\mathrm{Li^{+}}$ solvation cluster statistics to bulk electrolyte properties, and finally to battery performance. \n\n# Enhanced Li metal and oxidative stability \n\nNext, we investigated the electrolyte stability at Li metal anode and at high voltage separately. As shown in Fig. $\\mathrm{4a}$ , activation during initial cycles was tested using conventional $\\mathrm{Li}||\\mathrm{Cu}$ half-cell setup at $0.5\\mathrm{mAcm}^{-2}$ current density and $1\\mathrm{mAhcm}^{-2}$ areal capacity. \n\nThe 1 M LiFSI/FDMB showed a five-cycle activation before ramping up to $99\\%$ $\\mathrm{CE^{21}}$ ; while the DEE electrolyte never reached a CE of $99\\%$ (Supplementary Fig. 22). This confirms the argument above that DEE possesses fast ion conduction but sacrifices Li metal stability. In accord with our design, F3DEE and F6DEE solvents showed a substantial improvement over DEE, with activation periods measured to be around 30 and 90 cycles, respectively (Fig. 4a and Supplementary Fig. 22), confirming the benefit of fluorination. However, tens of activation cycles are still far from ideal case. The partially fluorinated electrolytes that contain ${\\mathrm{-CHF}}_{2}$ groups (Fig. 1a) performed much better, as the Li metal anode in F4DEE and F5DEE was activated within only three and four cycles, respectively. The CE of $\\mathrm{Li}||\\mathrm{Cu}$ half cells using $1.2\\mathrm{M}$ LiFSI/F5DEE was further boosted to roughly $99.9\\%$ when hard spring component (thus high pressure) was implemented in coin cells (Fig. 4b and Supplementary Fig. 23). Such a high average CE is reliable10 since the fluctuation range is as low as $\\pm0.1\\%$ from the $100\\mathrm{{th}}$ to the $580\\mathrm{th}$ cycle even under ambient conditions (Fig. $\\mathtt{4c}$ and source data of Fig. 4). When the areal capacity was increased to $5\\mathrm{mAhcm}^{-2}$ , the CE rapidly reached roughly $99.5\\%$ and the activation could even be completed by the second cycle (the second cycle $\\mathrm{CE}>99.3\\%$ ), which is one of the fastest among the state-of-the-art electrolytes (Fig. 4d). At high current densities $(>4\\mathrm{mAcm^{-2}})$ , the CE of $\\mathrm{Li}||\\mathrm{Cu}$ cells showed a slight decrease and fluctuation (Supplementary Fig. 24). The benefit of fluorinated-DEE electrolytes was further validated by Aurbach CE measurements43,44, in which F4DEE and F5DEE showed higher average CEs than other electrolytes (Fig. 4e and Supplementary Fig. 25). \n\nThe anodic stability was evaluated by linear sweep voltammetry (LSV) of Li||Al half cells, where the leakage current is a good metric to evaluate the corrosion of Al current collector7,23. As shown in \n\n![](images/b9029278e2b31408271c3ba408d123fa581825994d68d40d24e53af0f33bab82.jpg) \nFig. 5 | Full-cell performance of FDMB and fluorinated-DEE electrolytes. a,b, Cell structure of Li metal full battery (a) and anode-free pouch cell (b). c,d, Long-cycling performance (c) and voltage polarization $({\\pmb d})$ of thin Li||high-loading-NMC811 coin cells. Conditions: $50\\mathrm{-}\\upmu\\mathrm{m}$ thick Li, $4.9m\\mathsf{A h c m}^{-2}$ NMC811, 2.8–4.4 V, 0.2 C charge $0.3\\mathsf{C}$ discharge and electrolyte-to-cathode ratio $(\\mathsf{E}/\\mathsf{C})=8\\mathsf{g}\\mathsf{A}\\mathsf{h}^{-1}$ . e, Long-cycling performance of thin Li||high-loadingNMC811 coin cells. Conditions: $50\\mathrm{-}\\upmu\\mathrm{m}$ thick Li, $4.9\\mathsf{m A h c m}^{-2}$ NMC811, 2.8–4.4 V, 0.1 C charge 0.3 C discharge and $\\mathsf E/\\mathsf C=8\\mathsf g\\mathsf{A}\\mathsf h^{-1}$ . f, Long-cycling performance of Cu||NMC532 industrial anode-free pouch cells. Conditions: 3.1 mAh cm−2 NMC532, 3–4.4 V, 0.2 C charge $0.3\\mathsf C$ discharge and $\\mathsf{E}/\\mathsf{C}=2.4\\mathsf{g}\\mathsf{A}\\mathsf{h}^{-1}$ . g,h, Long-cycling performance $\\mathbf{\\sigma}(\\mathbf{g})$ and voltage polarization ${\\bf\\Pi}({\\bf h})$ of thick Li||microparticle-LFP coin cells. Conditions: $750\\mathrm{-}\\upmu\\mathrm{m}$ thick Li, $2\\mathsf{m A h c m^{-2}}$ LFP, 2.5–3.9 V, 0.5 C charge, $0.5\\mathsf{C}$ discharge with random $\\phantom{-}0.7\\mathsf{C}$ discharge caused by instrument error and $\\mathsf{E}/\\mathsf{C}=20\\mathsf{g}\\mathsf{A}\\mathsf{h}^{-1}$ . i–k, Long-cycling performance of Cu||microparticle-LFP anode-free pouch cells with different cycling rates. Conditions: $2.1\\mathsf{m A h c m^{-2}}$ LFP, $2.5{-}3.8\\lor,\\mathsf{E}/\\mathsf{C}{=}2.4\\mathsf{g}\\mathsf{A}\\mathsf{h}^{-1}$ , slow charge fast discharge (i, $_{0.2\\mathsf{C}}$ charge 2 C discharge) and fast charge fast discharge (j, 0.5 C charge 2 C discharge, and k, 1 C charge 2 C discharge). Note: replicated cell results are shown in c,e,f,i–k. For NMC811, $\\mathsf{1C}=200\\mathsf{m A g^{-1}}$ ; for LFP, $\\begin{array}{r}{{1}\\mathsf{C}=155\\mathsf{m A}\\mathsf{g}^{-1}}\\end{array}$ . \n\n![](images/f1a973a9b660b7de55fa11eee91fe72fd5d512de64201c51962849cf520dea87.jpg) \nFig. 6 | Li metal morphology in fluorinated-DEE electrolytes. a–d, Li metal morphology after 80 slow cycles (0.2 C slow charge, $0.3\\mathsf{C}$ slow discharge) in Cu||microparticle-LFP anode-free pouch cells using $1.2M$ LiFSI in F3DEE (a), F6DEE (b), F4DEE (c) and F5DEE (d), respectively. e,f, Li metal morphology after 90 fast cycles (1 C fast charge, 2 C fast discharge) in Cu||microparticle-LFP anode-free pouch cells using $1.2M$ LiFSI in F4DEE (e) and F5DEE (f), respectively. Scale bars, $10\\upmu\\mathrm{m}$ . \n\nFig. 4f, the DEE electrolyte was the most vulnerable at high voltage among these electrolytes; however, it was still far more stable against oxidation than DME (Supplementary Fig. 26). The leakage current evolution of $\\mathrm{FDMB}^{21}$ under a high-voltage scan was similar to that of a conventional carbonate electrolyte $\\mathrm{1MLiPF_{6}}$ in ethylene carbonate/dimethyl carbonate (1/1) with $2\\%$ vinylene carbonate and $10\\%$ fluoroethylene carbonate, denoted as $\\mathrm{LP}30+2\\%\\mathrm{VC}+10\\%\\mathrm{FEC})$ , indicating reasonable high-voltage stability. As expected, the anodic stability of fluorinated-DEE electrolytes generally followed the trend of fluorination: $\\mathrm{F5DEE}\\cong\\mathrm{F6DEE}>\\mathrm{F4DEE}\\gg\\mathrm{F3DEE}$ . Potentiostatic polarization tests at high voltage and molecular orbital energy level calculations provided similar trends (Supplementary Figs. 27 and 28). \n\n# Performance of Li metal and anode-free full cells \n\nWe proceeded to full cells to test the practicality of these developed electrolytes. Two types of Li metal battery are examined in this work: Li metal full cells using thin Li foil (Fig. 5a) and industrial anode-free jelly-roll pouch cells (Fig. 5b and Supplementary Table 3). \n\nWe first constructed Li metal full cells by pairing thin Li foil $(50\\mathrm{-}\\upmu\\mathrm{m}$ thick, roughly $10\\mathrm{mAhcm^{-2}}.$ ) with an industrial highloading NMC811 cathode (roughly $4.9\\mathrm{mAhcm^{-2}},$ ). Using the electrolyte-to-cathode ratio of around $8\\mathrm{gAh}^{-1}$ , these coin cells were cycled at $0.2\\mathrm{C}$ charge and $0.3\\mathrm{C}$ discharge. These conditions are harsh among the state-of-the-art cells26. The cycle life, which is defined as the cycle number before reaching $80\\%$ capacity retention, followed the trend of $\\mathrm{F5DEE}>\\mathrm{F4DEE}\\gg\\mathrm{F6DEE}\\cong\\mathrm{F3DEE}>\\mathrm{F}$ $\\mathrm{DMB}\\gg\\mathrm{DEE}$ (Fig. 5c). All the cells showed high and stable full-cell CEs before failure (Supplementary Fig. 29a). The cycle life can be further correlated with voltage polarization45, which is defined as the average voltage gap between charge and discharge. As shown in Fig. 5d and Supplementary Figs. 30 and 31, the poorly performing DEE showed drastic polarization increase with cycling; while the FDMB and F6DEE showed high yet slowly evolving overpotentials. The polarization of the F3DEE cell sharply increased at roughly 100 cycles, coinciding with when the cell suffered drastic capacity loss. Consistent with our expectation, the overpotentials of the long-cycling F4DEE and F5DEE full cells were low and stable throughout the whole cycle life. Using the best-performing electrolyte $1.2\\mathrm{M}$ LiFSI/F5DEE, $50\\mathrm{-}\\upmu\\mathrm{m}$ thick $\\mathrm{Li}||4.9\\mathrm{mAh}\\mathrm{cm}^{-2}$ NMC811 full cells maintained stable capacity for 270 cycles at a slow charging rate of 0.1 C, which are among the best high-loading Li metal full-cell performances12,13,26 (Fig. 5e and Supplementary Table 4). Similar to Li metal coin cells, the industrial anode-free pouch cells using single-crystal NMC532 showed the same trend of cycle life and impedance (Fig. 5f and Supplementary Fig. 32). Other types of cell or different cycling conditions also supported these conclusions (Supplementary Figs. 29 and 33–35). \n\nTo better evaluate the effect of fast ionic transport on full-cell performance, we further selected microparticle-LFP, a poorly conductive yet cost-effective cathode material46,47. We started the investigation with thick Li||LFP half cells at a slightly higher cycling rate $(0.5\\mathrm{C},1\\mathrm{mAcm}^{-2})$ . As demonstrated in Fig. $5\\mathrm{g}$ , the highly conductive electrolytes, F3DEE, F4DEE and F5DEE, resulted in stable cycling with high capacities. The half cell using a less conductive yet Li-metal compatible F6DEE electrolyte delivered lower specific capacity. Although the capacity of both DEE and FDMB cells gradually diminished, we ascribed this to different mechanisms45: for DEE, oxidation still happened at the charge voltage cut-off and the accumulation of side products increased the cell polarization (Fig. 5h and Supplementary Fig. 36), leading to capacity loss; for FDMB, its slow ionic conduction and continuously increasing overpotential due to residue SEI accumulation16,33 were responsible for its steady capacity decay, which was similar to the thin Li||NMC811 case (Fig. 5c,d and Supplementary Fig. 30). The benefit of stable and low overpotentials using F4DEE and F5DEE (Fig. 5h and Supplementary Fig. 36) was further verified by the rate capability tests of LFP half cells (Supplementary Fig. 37). \n\nIndustrial multilayer anode-free pouch cells using microparticleLFP (with a practical loading of $2.1\\mathrm{mAhcm^{-2}},$ were cycled at high rates to examine the limit of the developed electrolytes under stringent conditions. Compared to the lithium-nickelmanganese-cobalt-oxide (NMC) cathodes in anode-free cells, the LFP provides less Li excess inventory on the anode side during the first charging and consequently the cycle life will be shor ter29,46,48–50. Due to this material limitation, LFP-based anode-free batteries have seldom been studied in the community46. As shown in Fig. 5i, at slow charge (0.2 C) and fast discharge (2 C) rate, the F4DEE and F5DEE electrolyte maintained roughly 110 and 140 cycles, respectively, before reaching $80\\%$ capacity. Faster charging rates were further applied. At a $0.5\\mathrm{C}$ charge and 2 C discharge rate, roughly 110 cycles were achieved for both F4DEE and F5DEE (Fig. 5j). When the charging rate was boosted to 1 C, the faster conducting F4DEE electrolyte outperformed F5DEE, enabling 80–90 cycles before fading (Fig. 5k). These fast-cycling conditions are harsh for low-cost microparticle-LFP-based anode-free pouch cells, and the cycle lives are among the state-of-the-art (Supplementary Table 5). Performance of anode-free LFP pouch cells under other cycling conditions also supported our arguments (Supplementary Fig. 38). Moreover, no gassing issue was observed for these pouch cells after fast cycling even though no degassing procedure was implemented, indicating high safety and ease of manufacturing (Supplementary Fig. 39). \n\n![](images/3993c5efe3c683f5cd84ccea921613b38b3d6ad2dfd7d52b115c31197b09a4c9.jpg) \nFig. 7 | SEI examination in fluorinated-DEE electrolytes. a–e, XPS F1s depth profiles (by sputtering for different lengths of time) of cycled Li metal electrodes using 1.2 M LiFSI in DEE (a), F3DEE (b), F6DEE (c), F4DEE (d) and F5DEE (e), respectively. a.u., arbitrary units. f, Oxygen atomic contents by XPS of cycled Li metal electrodes in fluorinated-DEE electrolytes. g–k, Cryo-TEM images of $0.1\\mathsf{m A h c m^{-2}}$ deposited Li metal using 1.2 M LiFSI in DEE $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ , F3DEE (h), F6DEE (i), F4DEE (j) and F5DEE $({\\bf k})$ , respectively. Scale bars, $10\\mathsf{n m}.\\mathsf{I},\\mathsf{N}/\\mathsf{C}$ elemental ratios by cryo-EDS of Li metal deposits in fluorinated-DEE electrolytes. \n\nLi morphology, SEI structure and cathode characterization Li metal morphology and SEI properties are crucial for Li metal battery performance. Anode-free pouch cells after cycling were chosen here for scanning electron microscope (SEM) examination since they generated the Li deposits under realistic full-cell conditions. After 80 cycles at $0.2\\mathrm{C}$ charge and $0.3\\mathrm{C}$ discharge, the ${\\mathrm{Cu}}||{\\mathrm{LFP}}$ pouch cells were charged to the upper cut-off voltage, that is, $\\mathrm{Li^{+}}$ ions in LFP cathode were fully deposited as metallic Li on the anode. As shown in Fig. 6a–d and Supplementary Figs. 40 and 41, chunky and desired Li deposits were observed in all fluorinated-DEE electrolytes. However, careful examination revealed more favourable Li deposition in F4DEE and F5DEE electrolytes where the Li deposits had characteristic length scales much larger than $10\\upmu\\mathrm{m}$ (Fig. 6c,d). In particular, the Li deposits in the F4DEE electrolyte were almost flat with few grain boundaries, and such morphology was consistent with its long cycle life in anode-free cells. The diameters of Li deposits in F3DEE and F6DEE, in contrast, were slightly lower than $10\\upmu\\mathrm{m}$ (Fig. 6a,b). Under fast-cycling condition (1 C charge 2 C discharge), F4DEE and F5DEE maintained chunky Li morphology, which matched well with their outstanding cycle life at a high rate (Fig. 6e,f and Supplementary Fig. 41). The SEM images taken under other cycling conditions (Supplementary Fig. 41) or with $\\mathrm{Cu}||\\mathrm{NMC}532$ pouch cells (Supplementary Fig. 42) exhibited similar features. \n\nNext, X-ray photoelectron spectroscopy (XPS) was used to examine the SEI compositions. The XPS F1s spectra with sputtering showed a distinct difference between DEE and fluorinated-DEEs, in which the latter contained clear LiF signal while the former only showed trivial signal for this species (Fig. 7a–e). Although uniformly distributed LiF throughout depth profiling dominated the surface fluorine species in all fluorinated-DEEs, the anion species $-S O_{\\mathrm{x}}\\mathrm{F}$ remained on the top surface of Li metal in F3DEE and F6DEE electrolytes, indicating incomplete anion decomposition or passivation. The LiF-rich, vertically homogeneous SEI in F4DEE and F5DEE corroborates with their outstanding Li metal efficiency (Fig. 4a–e). Depth profiles of other representative elements demonstrated similar observations (Supplementary Figs. 43–45). Such a fine difference agreed well with our careful design rationales evolving from F3DEE/F6DEE to F4DEE/F5DEE. Furthermore, the O1s spectra showed that $\\mathrm{Li}_{2}\\mathrm{O}$ was present (Supplementary Fig. 43) and the oxygen content was higher in the fluorinated-DEE electrolytes especially in the best-performing F4DEE and F5DEE, indicating an oxygen-rich SEI (Fig. 7f). Such a robust SEI was reported to be beneficial to Li metal efficiency as well as interfacial $\\mathrm{Li^{+}}$ ion transport51,52. \n\nWe further performed cryogenic transmission electron microscopy (cryo-TEM) and corresponding energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (cryo-TEM EDS or cryo-EDS) to unveil the fine structural and local chemical information of compact direct $\\mathrm{SEIs}^{33,53}$ on Li metal surface. All compact SEIs in these electrolytes exhibited thin, uniform and amorphous nanostructure under cryo-TEM (Fig. $7\\mathrm{g-k}$ and Supplementary Fig. 46); however, the SEIs in F4DEE and F5DEE were the thinnest, corroborating with their high CE and fast activation. The nitrogen-to-carbon (N/C) ratio by cryo- EDS served as an indicator of anion-derived favourable SEIs since FSI– is solely the source of N element in these electrolytes. Much higher N/C ratios were observed in F4DEE and F5DEE (Fig. 7l), corresponding to more anion-derived SEIs. These facts were cross-validated by other elemental ratios, especially the sulfur-to-carbon (S/C) and fluorine-to-carbon (F/C) (Supplementary Figs. 47 and 48), again indicating anion-derived inorganic-rich SEIs16,21,33. \n\nRobust cathode–electrolyte interphase and suppression of cathode cracking are also critical for stable full-cell operation23. We analysed the elemental composition of cathode–electrolyte interphase by XPS and found that high C and F content yet negligible Ni species were observed on the cathode surface when using FDMB and fluorinated-DEE electrolytes, confirming their cathode protection effect13,23 (Supplementary Fig. 49). Furthermore, NMC811 particles showed limited intergranular cracking after cycling, again indicating the stability of cathode towards these developed electrolytes (Supplementary Fig. 50). \n\n![](images/663a2177992e5481b02f2c9cd1631565f6bc11a987601ed3793ed80e4445db1b.jpg) \nFig. 8 | Summary and overall evaluation of fluorinated-DEE electrolytes. a, Radar plot evaluating the developed electrolytes. The ratings between 1 and 10 are given according to the measured performance of each electrolyte. The rating of 1 represents extremely slow ionic conduction, large/unstable overpotential, poor Li metal CE, slow CE activation or oxidative instability; while 10 stands for the opposite, ideal properties. The rating values are provided in the source data. b, Development directions for good electrolytes: fast ion conduction, low overpotential, high Li metal efficiency, fast CE activation and high oxidative stability. c, A scheme showing the principles in this work: finding an optimal balance between good and poor solvation, that is, searching relatively strong solvents among weakly binding ones.. \n\n# Overall evaluation of fluorinated-DEE electrolytes \n\nWe evaluated the electrolytes studied in this work from five angles: bulk ionic conduction, overpotential/polarization improvement, Li metal CE, activation speed and oxidative stability (Fig. 8a). The DEE electrolyte exhibits advantageous ionic conduction but poor Li metal CE, slow activation and oxidative instability; conversely, FDMB shows improvement over all the above aspects except for worse ionic conduction and poor interfacial transport. The fluorinated-DEEs all show more balanced behaviour; however, F4DEE and F5DEE outperform F3DEE and F6DEE, which confirms our design logic (Fig. 8b). Our study suggests that the strongest binding solvents (such as DEE) are not necessarily desirable; instead, a balance needs to be achieved by finely modulating the molecular structure of weakly binding solvents, which ensures both electrode stability and sufficient solvation for fast transport (Fig. 8c). \n\n# Conclusions \n\nIn summary, we investigated a family of fluorinated-DEE based electrolytes for Li metal batteries, in which the partially fluorinated ${\\mathrm{-CHF}}_{2}$ group was identified and rationalized as the designer choice. The developed electrolytes, especially F4DEE and F5DEE, simultaneously possess high ionic conductivity, low and stable interfacial transport, reproducibly high Li metal efficiency (up to $99.9\\%$ with only $\\pm0.1\\%$ fluctuation for $1.2\\mathrm{M}$ LiFSI/ F5DEE in $\\mathrm{Li}||\\mathrm{Cu}$ half cells), record-fast activation $\\mathrm{CE}>99.3\\%$ within from the second cycle in $\\mathrm{Li}||\\mathrm{Cu}$ half cells) and high-voltage stability. These features enable long cycle life of Li metal batteries and anode-free pouch cells under lean electrolyte and realistic testing conditions. Thorough morphological characterization and SEI examination revealed flat Li deposition as well as an ideal anion-derived SEI. We also conducted a systematic study on the structure–performance relationships in these electrolytes via multiple theoretical and experimental tools, in which crucial properties including $\\mathrm{Li^{+}}$ –solvent coordination, solvation structure and battery performance were cross-validated and their correlations were thoroughly explained. Our work emphasizes the critical yet less-studied direction, fast ion conduction, in the Li metal battery electrolyte research. It is critical to achieve a balance between fast ion conduction and electrode stability through fine-tuning the solvation ability of the solvent, and molecular design and synthetic tools play important roles here. We believe that rational molecular-level design and chemical synthesis can endow the electrolyte field with more opportunities in the future. \n\n# Methods \n\nGeneral materials. 2,2,3,3-Tetrafluoro-1,4-butanediol, 2-(2,2,2-trifluoroethoxy) ethanol, 2,2-difluoroethanol, ethyl p-toluenesulfonate, 2,2,2-trifluoroethyl $\\boldsymbol{\\mathrm{\\tt~p~}}$ -toluenesulfonate and 2,2-difluoroethyl p-toluenesulfonate were purchased from SynQuest. Ethylene carbonate $(98\\%)$ ), sodium hydride $60\\%$ in mineral oil), methyl iodide, tetraglyme and other general reagents were purchased from Sigma-Aldrich, Fisher Scientific or TCI. All chemicals for reactions were used without further purification. LiFSI was obtained from Guangdong Canrd New Energy Technology and Arkema. DME $(99.5\\%$ over molecular sieves) and DEE (also denoted as ethylene glycol diethyl ether, $99\\%$ ) were purchased from Acros. Anhydrous vinylene carbonate and fluoroethylene carbonate were purchased from Sigma-Aldrich. The commercial carbonate electrolytes LP30 and LP40 were purchased from Gotion. The commercial Li battery separator Celgard 2325 $25\\mathrm{-}\\upmu\\mathrm{m}$ thick, polypropylene/polyethylene/polypropylene) was purchased from Celgard and used in all coin cells. Thick Li foil (roughly $750\\mathrm{-}\\upmu\\mathrm{m}$ thick) and Cu current collector $(25-\\upmu\\mathrm{m}$ thick) were purchased from Alfa Aesar. Thin Li foils (roughly 50- and $20\\mathrm{-}\\upmu\\mathrm{m}$ thick, supported on Cu substrate) were purchased from China Energy Lithium. Commercial LFP and NMC532 cathode sheets were purchased from MTI, and NMC811 cathode sheets were purchased from Targray (roughly 2.2 and $4.9\\mathrm{mAh}\\mathrm{cm}^{-2}$ areal capacity). Industrial dry $\\mathrm{Cu}||\\mathrm{NMC}532$ and Cu||LFP pouch cells were purchased from Li-Fun Technology. Other battery materials, such as 2032-type coin-cell cases, springs and spacers, were all purchased from MTI. \n\nSyntheses. FDMB was synthesized using the same protocol as our previous report21. To a $1,000\\mathrm{-ml}$ round-bottom flask, $64{\\mathrm{g}}$ of 2,2,3,3-tetrafluoro1,4-butanediol and $400\\mathrm{ml}$ of anhydrous tetrahydrofuran were added, and the solution was cooled to $0^{\\circ}\\mathrm{C}$ by ice bath to stir for $10\\mathrm{min}$ . Then $40\\mathrm{g}$ of NaH $60\\%$ in mineral oil) was added in batches and the suspension was stirred at $0^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . Next, $140\\mathrm{g}$ of methyl iodide was added slowly into the stirring suspension and then the ice bath was removed to allow the suspension to warm up to room temperature. After stirring at room temperature for $2\\mathrm{h}$ , the flask was slowly heated up to $60^{\\circ}\\mathrm{C}$ to reflux overnight. After the completion of reaction, the flask was allowed to cool down to room temperature, the mixture was filtered off and the solvents were removed under vacuum. The crude product underwent vacuum distillation (roughly $45^{\\circ}\\mathrm{C}$ under $1\\mathrm{kPa}$ ) three times to yield the final product as a colourless liquid. \n\nFor 2-(2,2-Difluoroethoxy)ethanol (Supplementary Figs. 51–54), in a $1,000\\mathrm{-ml}$ round-bottom flask were added $150\\mathrm{g}$ of 2,2-difluoroethanol, $140\\mathrm{g}$ of ethylene carbonate, $\\mathbf{8}\\mathbf{g}$ of $\\mathrm{\\DeltaNaOH}$ and $200\\mathrm{ml}$ of tetraglyme. Under nitrogen atmosphere, the suspension was heated to $140^{\\circ}\\mathrm{C}$ to stir for $48\\mathrm{h}$ . The suspension was then distilled under vacuum (roughly $65^{\\circ}\\mathrm{C}$ under 1 kPa) three times to yield roughly $100\\mathrm{g}$ of colourless liquid as the product. Yield: roughly $43\\%$ . $^{1}\\mathrm{H}$ -NMR ${400}\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}.$ $\\delta/\\mathrm{{ppm})}$ : 6.00–5.70 (tt, 2H), 3.71 3.60 $(\\mathrm{m},6\\mathrm{H})$ , 3.05 (s, 1H). $^{13}\\mathrm{C}$ -NMR ${\\bf\\chi}_{100}\\bf{M H z}$ , $\\mathrm{CDCl}_{3}$ , $\\delta/\\mathrm{{ppm},}$ ): 116.96–112.17, 73.63, 70.74–70.20, 61.67. 19F-NMR (376 MHz, $\\mathrm{CDCl}_{3}.$ , $\\delta/\\mathrm{{ppm}},$ ): −125.74–−125.96 (dt, 4 F). \n\nFor F3DEE (Supplementary Figs. 51 and 55–57), to a $1,000\\mathrm{-ml}$ round-bottom flask $22{\\mathrm{g}}$ of NaH $60\\%$ in mineral oil) and $400\\mathrm{ml}$ of anhydrous tetrahydrofuran were added, and the suspension was cooled to $0^{\\circ}\\mathrm{C}$ by ice bath to stir for $10\\mathrm{min}$ . Then $56\\mathrm{g}$ of 2-(2,2,2-trifluoroethoxy)ethanol was added dropwise \n\nand the suspension was further stirred at $0^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . Next, $93\\mathrm{g}$ of ethyl $\\mathrm{\\tt{p}}$ -toluenesulfonate was added in batches and the ice bath was removed to allow the suspension to warm up to room temperature. After stirring at room temperature for $^{2\\mathrm{h}}$ , the flask was slowly heated up to $60^{\\circ}\\mathrm{C}$ to reflux overnight. After the completion of reaction, the flask was allowed to cool down to room temperature and $200\\mathrm{ml}$ of deionized water was slowly added into the suspension to dissolve all solids. The remaining tetrahydrofuran in the resulting solution was removed under vacuum, and then the solution was extracted with $500\\mathrm{ml}$ of dichloromethane three times. The dichloromethane layer was washed with brine, dried by anhydrous $\\mathrm{MgSO_{4}}$ and the solvents were removed under vacuum. The crude product underwent vacuum distillation (roughly $40^{\\circ}\\mathrm{C}$ under $1\\mathrm{kPa}$ ) three times to yield roughly $43\\mathrm{g}$ of colourless liquid as the product. Yield: roughly $64\\%$ . $^{1}\\mathrm{H}$ -NMR $(400\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}$ , $\\delta/{\\mathrm{ppm}},$ ): 3.94–3.87 (q, 2H), 3.77–3.59 (m, 4H), 3.55–3.50 (q, 2H), 1.23–1.19 (3H). $^{13}\\mathrm{C}$ -NMR ${\\bf\\dot{100M H z}}$ , $\\mathrm{CDCl}_{3},$ $\\delta/{\\mathfrak{p p m}},$ : 128.44–120.10, 72.25, 70.06, 69.48–68.47, 67.00, 15.34. $^{19}\\mathrm{F}$ -NMR (376 MHz, $\\mathrm{CDCl}_{3}.$ $\\delta/{\\mathrm{ppm}}^{\\cdot}$ ): $-74.66-$ −74.71 (t, 3 F). Electrospray ionization–mass spectrometry (ESI–MS) calculated $[\\mathrm{M}+\\mathrm{H}^{+}]$ : 173.16; found: 173.32. \n\nFor F6DEE (Supplementary Figs. 51 and 58–60), the same procedure as for F3DEE synthesis was adopted, except that $93\\mathrm{g}$ of ethyl $\\boldsymbol{\\mathrm{\\tt~p~}}$ -toluenesulfonate was replaced by $120\\mathrm{g}$ of 2,2,2-trifluoroethyl $\\boldsymbol{\\mathrm{\\tt~p~}}$ -toluenesulfonate. The crude product underwent vacuum distillation (roughly $40^{\\circ}\\mathrm{C}$ under $1\\mathrm{kPa}$ ) three times to yield roughly $50\\mathrm{g}$ of colourless liquid as the product. Yield: roughly $57\\%$ . $^{1}\\mathrm{H}$ -NMR $(400\\mathrm{MHz}$ , $\\mathrm{\\dot{C}D C l_{3}}$ , $\\delta/{\\mathrm{ppm}}^{\\cdot}$ ): 3.92–3.86 (q, 4H), 3.80 (s, 4H). $^{13}\\mathrm{C}$ -NMR ( ${\\bf\\Phi}_{\\mathrm{100MHz}}$ $\\mathrm{CDCl}_{3},$ $\\delta/{\\mathrm{ppm}},$ : 128.28–119.95, 72.14, 69.53–68.52. 19F-NMR (376 MHz, $\\mathrm{CDCl}_{3},\\dot{\\mathcal{C}}$ $\\delta/$ ppm): $-74.97\\mathrm{-}75.01$ (t, 6F). ESI–MS calculated $\\left[\\mathrm{M}{+}\\mathrm{H}^{+}\\right]$ : 227.13; found: 227.20. \n\nFor F4DEE (Supplementary Figs. 51 and 61–63), the same procedure as for F3DEE synthesis was adopted, except that $56\\mathrm{g}$ of 2-(2,2,2-trifluoroethoxy) ethanol was replaced by $50\\mathrm{g}$ of 2-(2,2-difluoroethoxy)ethanol and $93\\mathrm{g}$ ethyl p-toluenesulfonate was replaced by $110\\mathrm{g}$ of 2,2-difluoroethyl $\\boldsymbol{\\mathrm{\\tt~p~}}$ -toluenesulfonate. The crude product underwent vacuum distillation (roughly $60^{\\circ}\\mathrm{C}$ under 1 kPa) three times to yield roughly $45\\mathrm{g}$ of colourless liquid as the product. Yield: roughly $60\\%$ . 1H-NMR $400\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3},$ $\\delta/{\\mathrm{ppm}}^{\\cdot}$ ): 6.00–5.70 (tt, 2H), 3.73–3.68 (td, 4H), 3.69 (s, 4H). $^{13}\\mathrm{C}$ -NMR ( ${\\bf\\dot{100M H z}}$ , $\\mathrm{CDCl}_{3},$ $\\delta/\\mathrm{{ppm}}$ ): 116.80–112.01, 71.35, 70.74– 70.20. 19F-NMR ( $376\\mathrm{MHz}$ , $\\mathrm{{\\langleDCl_{3},\\delta/p p m}}$ ): −125.35–−125.57 (dt, 4F). ESI–MS calculated $\\left[\\mathrm{M}{+}\\mathrm{H}^{+}\\right]$ : 191.15; found: 191.22. \n\nFor F5DEE (Supplementary Figs. 51 and 64–66), the same procedure as for F3DEE synthesis was adopted, except that $56\\mathrm{g}$ of 2-(2,2,2-trifluoroethoxy) ethanol was replaced by $50\\mathrm{g}$ of 2-(2,2-difluoroethoxy)ethanol and $93\\mathrm{g}$ of ethyl p-toluenesulfonate was replaced by $120\\mathrm{g}$ of 2,2-difluoroethyl p-toluenesulfonate. The crude product underwent vacuum distillation (roughly $60^{\\circ}\\mathrm{C}$ under 1 kPa) three times to yield roughly $62{\\mathrm{g}}$ of colourless liquid as the product. Yield: roughly $75\\%$ . 1H-NMR $400\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3},$ $\\delta/{\\mathrm{ppm}}^{\\cdot}$ ): 6.01–5.71 (tt, 1H), 3.92–3.85 (td, 2H), 3.79–3.67 (m, 6H). $^{13}\\mathrm{C}$ -NMR $(100\\mathrm{{MHz}}$ , $\\mathrm{CDCl}_{3}$ , $\\delta/{\\mathrm{ppm}},$ : 128.09–119.74, 116.74–111.94, 71.83, 71.41, 70.82–70.28, 69.21–68.19. $^{19}\\mathrm{F}$ -NMR $(376\\mathrm{MHz}$ , $\\mathrm{CDCl}_{3}.$ $\\delta/\\mathrm{{ppm},}$ : −74.53–−74.58 (t, 3F), −125.37–−125.59 (dt, 2F). ESI–MS calculated $\\mathrm{[M+H^{+}]}$ : 209.14; found: 209.31. \n\nElectrolyte preparation. LiFSI $(2,244\\mathrm{mg})$ was dissolved in $10\\mathrm{ml}$ of DEE or fluorinated-DEEs to obtain the respective $1.2\\ensuremath{\\mathrm{M}}$ LiFSI electrolyte. LiFSI $(1,122\\mathrm{mg},$ was dissolved in $6\\mathrm{ml}$ of DME or FDMB to obtain 1 M LiFSI/DME and 1 M LiFSI/ FDMB, respectively. All the electrolytes were prepared and stored in an argon-filled glovebox (Vigor, oxygen ${<}0.5\\mathrm{ppm}$ , water ${<}0.1\\mathrm{ppm}$ ) at room temperature. \n\nTheoretical calculations. The molecular geometries for the ground states were optimized by DFT at the ${\\mathrm{B}}3{\\mathrm{LYP}}/{6-311}\\mathrm{G}+(d,p$ level, and then the energy, orbital levels and electrostatic potential surfaces of molecules were evaluated at the $\\mathrm{B}3\\mathrm{LYP}/6{-}311\\mathrm{G}+(d,p)$ level as well. All DFT calculations were carried out with Gaussian16 on Sherlock server at Stanford University. \n\nMolecular dynamics simulations were carried out using Gromacs 2018 program54, with electrolyte molar ratios taken from experimental results. Molecular forces were calculated using the Optimized Potentials for Liquid Simulations all atom force field55. Topology files and bonded and Lennard–Jones parameters were generated using the LigParGen server56. Atomic partial charges were calculated by fitting the molecular electrostatic potential at atomic centres in Gaussian16 using the Møller–Plesset second-order perturbation method with a cc-pVTZ basis set57. Due to the use of a non-polarizable force field, partial charges for charged ions were scaled by 0.8 to account for electronic screening, which has been shown to improve predictions of interionic interactions58. The simulation procedure consisted of an energy minimization using the steepest descent method followed by an 8-ns equilibration step using a Berendsen barostat and a 40-ns production run using a Parrinello–Rahman barostat, both at a reference pressure of 1 bar with timesteps of 2 fs. A Nose–Hoover thermostat was used throughout with a reference temperature of $300\\mathrm{K}$ . The particle mesh Ewald method was used to calculate electrostatic interactions, with a real space cut-off of $1.2\\mathrm{nm}$ and a Fourier spacing of $0.12\\mathrm{nm}$ . The Verlet cut-off scheme was used to generate pairlists. A cut-off of $1.2\\mathrm{nm}$ was used for non-bonded Lennard–Jones interactions. Periodic boundary conditions were applied in all directions. Bonds with hydrogen atoms were constrained. Convergence of the system energy, temperature and box size were checked to verify equilibration. The final $30\\mathrm{ns}$ of the production run were \n\nused for the analysis. Density profiles and RDFs were generated using Gromacs, while visualizations were generated with $\\mathrm{\\DeltaVMD^{59}}$ . Solvation shell statistics were calculated using the MDAnalysis Python package60 by histogramming the observed first solvation shells for $\\mathrm{Li^{+}}$ ions during the production simulation, using a method similar to our previous work21. The cut-off distance for each species in the first solvation shell was calculated from the first minimum occurring in the RDF (referenced to $\\mathrm{Li^{+}}$ ions) after the initial peak. The SSL, LASP and LAC each has a distinct number of $\\mathrm{Li^{+}}$ coordinating anions of 0, 1 and $\\geq2$ (2–5 in this work), respectively (Supplementary Figs. 12–17), in the first solvation sheath, and the percentage of each was counted based on this criterion. \n\nGeneral material characterizations. ${}^{1}\\mathrm{H}\\mathrm{-},{}^{13}\\mathrm{C}\\mathrm{-}$ and ${}^{19}\\mathrm{F}$ -NMR spectra were recorded on a Varian Mercury 400 MHz NMR spectrometer and 7Li-NMR spectra were recorded on a UI 500 MHz NMR spectrometer at room temperature. Solvation free energies were measured according to our recent work31. ATR–FTIR spectra were measured using a Nicolet iS50 with a diamond attenuated total reflectance attachment. FEI Magellan 400 XHR and Thermo Fisher Scientific Apreo S LoVac were used for taking SEM images. Ion milling was done by Fischione Model 1061 Ion Mill. For XPS measurements, each Li foil (after ten Li||Li cell cycles) or NMC811 cathode (after 30 Li||NMC811 cell cycles) was washed with DME for $30\\mathrm{s}$ to remove the remaining electrolytes. The samples were transferred and sealed into the XPS holder in the argon-filled glovebox. The XPS profiles were collected with a PHI VersaProbe 1 scanning XPS microprobe. Viscosity measurements were carried out using an Ares G2 rheometer (TA Instruments) with an advanced Peltier system at $25.0^{\\circ}\\mathrm{C}$ . \n\nCryo-TEM and cryo-TEM EDS. A Thermo Fisher Titan 80-300 environmental transmission electron microscope at an accelerating voltage of $300\\mathrm{kV}$ and a Gatan 626 side-entry holder were used for cryo-TEM and cryo-TEM EDS experiments. Cryo-TEM sample preparations prevent air and moisture exposure and reduce electron beam damage, as described previously53. The TEM is equipped with an aberration corrector in the image-forming lens, which was tuned before imaging. Cryo-TEM images were acquired by a Gatan K3 IS direct-detection camera in the electron-counting mode. Cryo-TEM images were taken with an electron dose rate of around $100\\mathrm{e}^{-}\\check{\\mathrm{A}}^{-2}\\mathbf{s}^{-1}$ , and a total of five frames were taken with 0.1 s per frame for each image. \n\nDOSY–NMR. For sample preparation, benzene-d6 was placed in an external coaxial insert and the $^{1}\\mathrm{H}$ chemical shifts were referenced to it at $7.16\\mathrm{ppm}$ . In an argon glovebox, $20\\upmu\\mathrm{l}$ of anhydrous toluene was mixed into $300\\upmu\\mathrm{l}$ of sample solution and then added into the NMR tube. The cap of NMR tube was sealed by parafilm to avoid moisture penetration during the DOSY–NMR experiment. \n\nThe measurement methods and parameters were as follows: all DOSY–NMR experiments were carried out using a ${500}\\mathrm{MHz}$ Bruker Avance I spectrometer equipped with a $z$ axis gradient amplifier and a 5-mm BBO probe with a $z$ axis gradient coil that is capable of a maximum gradient strength at $0.535\\mathrm{Tm^{-1}}$ . The spectrometer frequencies for $\\mathrm{^{1}H}$ - and 7Li- experiments were 500.23 and $194.41\\mathrm{MHz}$ , respectively. ${}^{1}\\mathrm{H}.$ - and $^\\mathrm{7Li}$ -pulsed field gradient (PFG) measurements were performed to determine the diffusion coefficients for the solvents and electrolytes in this work. Both ${}^{1}\\mathrm{H}.$ and 7Li-PFG measurements were performed at $298\\mathrm{K}$ using the standard dstebpgp3s Bruker pulse program, using a double stimulated echo sequence, bipolar gradient pulses for diffusion and three spoil gradients. Apparent diffusion coefficients were calculated by fitting peak integrals to the Stejskal–Tanner equation modified for the dstebpgp3s pulse sequence61, and the signal attenuation due to diffusion as a function of gradient strength was in good agreement with the numerical fits for all data sets (Supplementary Table 2 and Supplementary Fig. 18). The sample temperature was calibrated to $298\\mathrm{K}$ using the $^{1}\\mathrm{H}$ chemical shifts of the ethylene glycol sample62. Similarly, the performance for the PFGs was calibrated at $298\\mathrm{K}$ using dstebpgp3s sequence and the ethylene glycol sample63. The PFG experiments were conducted using the following set of parameters. $^{1}\\mathrm{H}$ -PFG of solvents: diffusion delay $(\\Delta,d20)=40\\mathrm{ms}.$ gradient pulse duration $(\\delta,2\\times\\mathrm{p}30){=}2\\mathrm{ms}$ , gradient recovery delay (d16) $=200{\\upmu\\mathrm{s}}$ , array of gradient strength $(\\mathrm{gpz}6)=5\\%$ to $80\\%$ with 12 linear increments, recycling delay $(\\mathrm{d}1)=2s$ and high power $90^{\\circ}$ pulse $({\\mathsf{p}}1){\\mathsf{=}}9\\upmu{\\mathsf{s}}$ . $\\mathrm{^{1}H}$ -PFG of electrolytes: diffusion delay $(\\Delta,\\mathrm{d}20)=150\\mathrm{ms}$ , gradient pulse duration $(\\delta,2\\times\\mathsf{p}30){=}2\\mathrm{ms}$ , gradient recovery delay $(\\mathrm{d}16)=200{\\upmu\\mathrm{s}}$ , array of gradient strength $\\mathrm{(gpz6)}=5$ to $80\\%$ with linear 12 increments, recycling delay $(\\mathrm{d}1)=2s$ and high power $90^{\\circ}$ pulse $({\\mathsf{p}}1){\\mathsf{=}}9\\upmu{\\mathsf{s}}$ . 7Li-PFG of electrolytes: diffusion delay $(\\Delta,\\mathrm{d}20){=}500\\mathrm{ms}$ , gradient pulse duration $(\\delta,2\\times\\mathrm{p}30){=}4\\mathrm{ms}$ , gradient recovery delay $(\\mathrm{d}16)=200\\upmu s$ array of gradient strength $(\\mathrm{gpz}6)=5\\%$ to $80\\%$ with linear 12 increments, recycling delay $(\\mathrm{d}1)=2s$ and high power $90^{\\circ}$ pulse ${\\mathrm{(p1)}}=13{\\upmu{\\mathrm{s}}}$ . \n\nElectrochemical measurements. All battery components used in this work were commercially available and all electrochemical tests were carried out in a Swagelok-cell, 2032-type coin-cell or pouch-cell configuration. All coin cells were fabricated in an argon-filled glovebox, and one layer of Celgard 2325 was used as a separator. The EIS, $\\mathrm{Li^{+}}$ transference number, LSV and pouch-cell cycling were carried out on a Biologic VMP3 system. The cycling tests for coin cells and some pouch cells were carried out on an Arbin instrument. The EIS measurements \n\nwere taken over a frequency range of 1 MHz to $100\\mathrm{mHz}$ . For the $\\mathrm{Li^{+}}$ transference number measurements, $10\\mathrm{mV}$ constant voltage bias was applied to Li||Li cells. The cathodic cyclic voltammetry tests were carried out over a voltage range of $-0.1$ to $2\\mathrm{V}$ for one cycle in $\\mathrm{\\Li||Cu}$ cells, while the anodic LSV tests were over a voltage range of 2.5 to $6.5\\mathrm{V}$ in Li||Al cells. For Li||Li symmetric-cell cycling, $1\\mathrm{mAcm}^{-2}$ current density and $1\\mathrm{mAhcm}^{-2}$ areal capacity were applied. For $\\mathrm{Li}||\\mathrm{Cu}$ half-cell CE tests, ten precycles between 0 and $1\\mathrm{V}$ were initialized to clean the Cu electrode surface, and then cycling was done by depositing 1 (or 5) $\\mathrm{\\mAhcm^{-2}}$ of Li onto the Cu electrode followed by stripping to 1 V. The CE is calculated by dividing the total stripping capacity by the total deposition capacity after the formation cycles. For the Aurbach CE test43,44, a standard protocol was followed: (1) perform one initial formation cycle with Li deposition of $5\\mathrm{mAhcm}^{-2}$ on Cu under $0.5\\mathrm{mAcm^{-2}}$ current density and stripping to 1 V; (2) deposit $5\\operatorname{mAh}{\\mathsf{c m}}^{-2}$ Li on Cu under $0.5\\mathrm{mAcm^{-2}}$ as a Li reservoir; (3) repeatedly strip/deposit Li of $1\\mathrm{mAhcm}^{-2}$ under $0.5\\mathrm{mAcm^{-2}}$ for ten cycles; (4) strip all Li to 1 V. The Li||NMC and Cu||NMC full cells were cycled with the following method (unless specially listed): after the first two activation cycles at 0.1 C charge/discharge (or $0.1\\mathrm{C}$ charge $0.3\\mathrm{C}$ discharge for anode-free pouch cells), the cells were cycled at different rates. Then a constant-current-constant-voltage protocol was used for cycling: cells were charged to top voltage and then held at that voltage until the current dropped below $0.1\\mathrm{C}$ . The NMC811 coin cells were cycled between 2.8 and $4.4\\mathrm{V}$ and the single-crystal NMC532 pouch cells were cycled between 3.0 and 4.4 V. The Li||LFP and ${\\mathrm{Cu}}||{\\mathrm{LFP}}$ full cells were cycled with the following method (unless specially listed): after the first two activation cycles at $0.1\\mathrm{C}$ charge/discharge (or $0.1\\mathrm{C}$ charge 2 C discharge for anode-free pouch cells), the cells were cycled at different rates. The LFP coin cells were cycled between 2.5 and $3.9\\mathrm{V}$ and the LFP pouch cells were cycled between 2.5 and $3.8\\mathrm{V},$ or between 2.5 and 3.7 V. All pouch cells were clamped in woodworking vises to a rough pressure of $1,000\\mathrm{kPa}$ and cycled under ambient conditions without temperature control. \n\n# Data availability \n\nAll relevant data are included in the paper and its Supplementary Information. \nSource data are provided with this paper. \n\n# Code availability \n\nThe Python script and rationale for analysing the $\\mathrm{Li^{+}}$ solvation structures are available at https://github.com/xianshine/LiSolvationStructure. \n\nReceived: 19 August 2021; Accepted: 24 November 2021; Published online: 13 January 2022 \n\n# References \n\n1.\t Liu, J. et al. Pathways for practical high-energy long-cycling lithium metal batteries. Nat. Energy 4, 180–186 (2019). \n2.\t Cao, Y., Li, M., Lu, J., Liu, J. & Amine, K. Bridging the academic and industrial metrics for next-generation practical batteries. Nat. Nanotechnol. 14, 200–207 (2019). \n3.\t Tikekar, M. D., Choudhury, S., Tu, Z. & Archer, L. A. Design principles for electrolytes and interfaces for stable lithium-metal batteries. Nat. Energy 1, 16114 (2016). \n4.\t Cheng, X.-B. et al. A review of solid electrolyte interphases on lithium metal anode. Adv. Sci. 3, 1500213 (2016). \n5.\t Lin, D., Liu, Y. & Cui, Y. Reviving the lithium metal anode for high-energy batteries. Nat. Nanotechnol. 12, 194–206 (2017). \n6.\t Flamme, B. et al. Guidelines to design organic electrolytes for lithium-ion batteries: environmental impact, physicochemical and electrochemical properties. Green Chem. 19, 1828–1849 (2017). \n7.\t Aspern, N., Röschenthaler, G.-V., Winter, M. & Cekic-Laskovic, I. Fluorine and lithium: Ideal partners for high-performance rechargeable battery electrolytes. Angew. Chemie Int. Ed. 58, 15978–16000 (2019). \n8.\t Jie, Y., Ren, X., Cao, R., Cai, W. & Jiao, S. Advanced liquid electrolytes for rechargeable li metal batteries. Adv. Funct. Mater. 30, 1910777 (2020). \n9.\t Fan, X. & Wang, C. High-voltage liquid electrolytes for Li batteries: progress and perspectives. Chem. Soc. Rev. 50, 10486–10566 (2021). \n10.\tHobold, G. M. et al. Moving beyond $99.9\\%$ Coulombic efficiency for lithium anodes in liquid electrolytes. Nat. Energy 6, 951–960 (2021). \n11.\tYamada, Y., Wang, J., Ko, S., Watanabe, E. & Yamada, A. Advances and issues in developing salt-concentrated battery electrolytes. Nat. Energy 4, 269–280 (2019). \n12.\tCao, X., Jia, H., Xu, W. & Zhang, J.-G. Review—localized high-concentration electrolytes for lithium batteries. J. Electrochem. Soc. 168, 010522 (2021). \n13.\tRen, X. et al. Enabling high-voltage lithium-metal batteries under practical conditions. Joule 3, 1662–1676 (2019). \n14.\tChen, J. et al. Electrolyte design for Li metal-free Li batteries. Mater. Today 39, 118–126 (2020). \n15.\tHoloubek, J. et al. An all-fluorinated ester electrolyte for stable high-voltage li metal batteries capable of ultra-low-temperature operation. ACS Energy Lett. 5, 1438–1447 (2020). \n16.\tWang, H. et al. Dual-solvent li-ion solvation enables high-performance Li-metal batteries. Adv. Mater. 33, 2008619 (2021). \n17.\tZhang, H. et al. Electrolyte additives for lithium metal anodes and rechargeable lithium metal batteries: progress and perspectives. Angew. Chemie Int. Ed. 57, 15002–15027 (2018). \n18.\tYang, Y. et al. Liquefied gas electrolytes for wide-temperature lithium metal batteries. Energy Environ. Sci. 13, 2209–2219 (2020). \n19.\tWeber, R. et al. Long cycle life and dendrite-free lithium morphology in anode-free lithium pouch cells enabled by a dual-salt liquid electrolyte. Nat. Energy 4, 683–689 (2019). \n20.\tLouli, A. J. et al. Diagnosing and correcting anode-free cell failure via electrolyte and morphological analysis. Nat. Energy 5, 693–702 (2020). \n21.\tYu, Z. et al. Molecular design for electrolyte solvents enabling energy-dense and long-cycling lithium metal batteries. Nat. Energy 5, 526–533 (2020). \n22.\tAmanchukwu, C. V. et al. A new class of ionically conducting fluorinated ether electrolytes with high electrochemical stability. J. Am. Chem. Soc. 142, 7393–7403 (2020). \n23.\tXue, W. et al. Ultra-high-voltage Ni-rich layered cathodes in practical Li metal batteries enabled by a sulfonamide-based electrolyte. Nat. Energy 6, 495–505 (2021). \n24.\tHoloubek, J. et al. Tailoring electrolyte solvation for Li metal batteries cycled at ultra-low temperature. Nat. Energy 6, 303–313 (2021). \n25.\tMa, P., Mirmira, P. & Amanchukwu, C. V. Effect of building block connectivity and ion solvation on electrochemical stability and ionic conductivity in novel fluoroether electrolytes. ACS Cent. Sci. 7, 1232–1244 (2021). \n26.\tXiao, J. et al. Understanding and applying coulombic efficiency in lithium metal batteries. Nat. Energy 5, 561–568 (2020). \n27.\tChen, Y. et al. Steric effect tuned ion solvation enabling stable cycling of highvoltage lithium metal battery. J. Am. Chem. Soc. 143, 18703–18713 (2021). \n28.\tPham, T. D. & Lee, K. Simultaneous stabilization of the solid/cathode electrolyte interface in lithium metal batteries by a new weakly solvating electrolyte. Small 17, 2100133 (2021). \n29.\tXu, R. et al. Designing and demystifying the lithium metal interface toward highly reversible batteries. Adv. Mater. 33, 2105962 (2021). \n30.\tChen, X. & Zhang, Q. Atomic insights into the fundamental interactions in lithium battery electrolytes. Acc. Chem. Res. 53, 1992–2002 (2020). \n31.\tKim, S. C. et al. Potentiometric measurement to probe solvation energy and its correlation to lithium battery cyclability. J. Am. Chem. Soc. 143, 10301–10308 (2021). \n32.\tSu, C.-C. et al. Principle in developing novel fluorinated sulfone electrolyte for high voltage lithium-ion batteries. Energy Environ. Sci. 14, 3029–3034 (2021). \n33.\tWang, H. et al. Efficient lithium metal cycling over a wide range of pressures from an anion-derived solid-electrolyte interphase framework. ACS Energy Lett. 6, 816–825 (2021). \n34.\tLiu, X. et al. Enhanced ${\\mathrm{Li^{+}}}$ transport in ionic liquid-based electrolytes aided by fluorinated ethers for highly efficient lithium metal batteries with improved rate capability. Small Methods 9, 2100168 (2021). \n35.\t Halat, D. M. et al. Modifying $\\mathrm{Li^{+}}$ and anion diffusivities in polyacetal electrolytes: a pulsed-field-gradient nmr study of ion self-diffusion. Chem. Mater. 33, 4915–4926 (2021). \n36.\tAndo, H. et al. Mixture of monoglyme-based solvent and lithium bis(trifluoromethanesulfonyl)amide as electrolyte for lithium ion battery using silicon electrode. Mater. Chem. Phys. 225, 105–110 (2019). \n37.\tSasaki, Y., Shimazaki, G., Nanbu, N., Takehara, M. & Ue, M. Physical and electrolytic properties of partially fluorinated organic solvents and its application to secondary lithium batteries: Partially fluorinated dialkoxyethanes. ECS Trans. 16, 23–31 (2019). \n38.\tYue, Z., Dunya, H., Aryal, S., Segre, C. U. & Mandal, B. Synthesis and electrochemical properties of partially fluorinated ether solvents for lithium– sulfur battery electrolytes. J. Power Sources 401, 271–277 (2018). \n39.\tZhang, Y. & Viswanathan, V. Design rules for selecting fluorinated linear organic solvents for li metal batteries. J. Phys. Chem. Lett. 12, 5821–5828 (2021). \n40.\tYu, Z. et al. A dynamic, electrolyte-blocking, and single-ion-conductive network for stable lithium-metal anodes. Joule 3, 2761–2776 (2019). \n41.\tJia, M. et al. Fluorinated bifunctional solid polymer electrolyte synthesized under visible light for stable lithium deposition and dendrite-free all-solid-state batteries. Adv. Funct. Mater. 31, 2101736 (2021). \n42.\tZou, Y. et al. Interfacial model deciphering high-voltage electrolytes for high energy density, high safety, and fast-charging lithium-ion batteries. Adv. Mater. 33, 2102964 (2021). \n43.\tAurbach, D., Gofer, Y. & Langzam, J. The correlation between surface chemistry, surface morphology, and cycling efficiency of lithium electrodes in a few polar aprotic systems. J. Electrochem. Soc. 136, 3198–3205 (1989). \n44.\tAdams, B. D., Zheng, J., Ren, X., Xu, W. & Zhang, J.-G. Accurate determination of coulombic efficiency for lithium metal anodes and lithium metal batteries. Adv. Energy Mater. 8, 1702097 (2018). \n45.\tNiu, C. et al. Balancing interfacial reactions to achieve long cycle life in high-energy lithium metal batteries. Nat. Energy 6, 723–732 (2021). \n46.\tSripad, S., Bills, A. & Viswanathan, V. The iron age of automotive batteries: techno-economic assessment of batteries with lithium metal anodes paired with iron phosphate cathodes. Preprint at ECSarXiv https://doi.org/10.1149/ osf.io/fx4p9 (2021). \n47.\tEftekhari, A. LiFePO4/C nanocomposites for lithium-ion batteries. J. Power Sources 343, 395–411 (2017). \n48.\tNanda, S., Gupta, A. & Manthiram, A. Anode-free full cells: a pathway to high-energy density lithium-metal batteries. Adv. Energy Mater. 11, \n2000804 (2021). \n49.\t Park, S. H., Jun, D., Lee, G. H., Lee, S. G. & Lee, Y. J. Toward high-performance anodeless batteries based on controlled lithium metal deposition: a review. J. Mater. Chem. A 9, 14656–14681 (2021). \n50.\tQian, J. et al. Anode-free rechargeable lithium metal batteries. Adv. Funct. Mater. 26, 7094–7102 (2016). \n51.\tGuo, R. & Gallant, B. M. Li2O solid electrolyte interphase: probing transport properties at the chemical potential of lithium. Chem. Mater. 32, \n5525–5533 (2020). \n52.\t May, R., Fritzsching, K. J., Livitz, D., Denny, S. R. & Marbella, L. E. Rapid interfacial exchange of li ions dictates high coulombic efficiency in li metal anodes. ACS Energy Lett. 6, 1162–1169 (2021). \n53.\tHuang, W., Wang, H., Boyle, D. T., Li, Y. & Cui, Y. Resolving nanoscopic and mesoscopic heterogeneity of fluorinated species in battery solid-electrolyte interphases by cryogenic electron microscopy. ACS Energy Lett. 5, \n1128–1135 (2020). \n54.\tAbraham, M. J. et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX \n1–2, 19–25 (2015). \n55.\tJorgensen, W. L., Maxwell, D. S. & Tirado-Rives, J. Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J. Am. Chem. Soc. 118, 11225–11236 (1996). \n56.\tDodda, L. S., Cabeza de Vaca, I., Tirado-Rives, J. & Jorgensen, W. L. LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands. Nucleic Acids Res. 45, W331–W336 (2017). \n57.\tSambasivarao, S. V. & Acevedo, O. Development of OPLS-AA force field parameters for 68 unique ionic liquids. J. Chem. Theory Comput. 5, \n1038–1050 (2009). \n58.\tSelf, J., Fong, K. D. & Persson, K. A. Transport in superconcentrated LiPF6 and LiBF4/propylene carbonate electrolytes. ACS Energy Lett. 4, \n2843–2849 (2019). \n59.\tHumphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996). \n60.\tMichaud-Agrawal, N., Denning, E. J., Woolf, T. B. & Beckstein, O. MDAnalysis: a toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 32, 2319–2327 (2011). \n61.\tSinnaeve, D. The Stejskal-Tanner equation generalized for any gradient shape-an overview of most pulse sequences measuring free diffusion. Concepts Magn. Reson. Part A 40A, 39–65 (2012). \n62.\tAmmann, C., Meier, P. & Merbach, A. A simple multinuclear NMR thermometer. J. Magn. Reson. 46, 319–321 (1982). \n63.\t Spees, W. M., Song, S.-K., Garbow, J. R., Neil, J. J. & Ackerman, J. J. H. Use of ethylene glycol to evaluate gradient performance in gradient-intensive diffusion MR sequences. Magn. Reson. Med. 68, 319–324 (2012). \n\n# Acknowledgements \n\nThis work is supported by the US Department of Energy, under the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies, the Battery Materials Research Program and Battery500 Consortium. Part of this work was performed at the Stanford Nano Shared Facilities, supported by the National Science Foundation under award no. ECCS-2026822. Z.Y. thanks B. Siegl at Arkema for providing LiFSI. Z.Y. also thanks J. Yang at Stanford University for measuring mass spectrometry and X. Chen at Tsinghua University for discussing the definition of ${\\mathrm{Li^{+}}}$ solvates. Z.Z. acknowledges support from Stanford Interdisciplinary Graduate Fellowship. S.T.O. acknowledges support from the Knight Hennessy Scholarship for graduate studies at Stanford University. G.A.K. gratefully acknowledges support from the National Science Foundation Graduate Research Fellowship under grant no. 1650114. \n\n# Author contributions \n\nZ.Y., Y.Cui and Z.B. conceived the idea. J.Q., Y.Cui and Z.B. directed the project. Z.Y. designed the logical flow and experiments. Z.Y. performed syntheses, material characterizations, DFT calculations, electrochemical measurements and battery tests. P.E.R., X.K. and J.Q. conducted molecular dynamics simulations and rationales. Z.Z. performed cryo-TEM and cryo-TEM EDS experiments. Z.H. took SEM images and collected viscosity data. H.C. performed DOSY–NMR experiments. S.T.O. collected XPS data. Y.Chen collected 7Li- and $^{19}\\mathrm{F}$ -NMR and contributed to key discussion. S.C.K. measured solvation free energies. X.X. carried out ion milling and took part of SEM images. H.W. helped with electrochemical measurements and battery testing. Y.Z. and G.A.K. helped with syntheses. M.S.K. helped with discussion. All authors discussed and analysed the data. Z.Y., S.F.B., J.Q., Y.Cui and Z.B. cowrote and revised the manuscript. \n\n# Competing interests \n\nZ.B., Y.Cui. and Z.Y. declare that this work has been filed as US Provisional Patent Application No. 63/283,828. The remaining authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41560-021-00962-y. \n\nCorrespondence and requests for materials should be addressed to Jian Qin, Yi Cui or Zhenan Bao. \n\nPeer review information Nature Energy thanks the anonymous reviewers for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 " + }, + { + "id": "10.1016_j.bioactmat.2021.06.014", + "DOI": "10.1016/j.bioactmat.2021.06.014", + "DOI Link": "http://dx.doi.org/10.1016/j.bioactmat.2021.06.014", + "Relative Dir Path": "mds/10.1016_j.bioactmat.2021.06.014", + "Article Title": "Mussel-inspired adhesive antioxidant antibacterial hemostatic composite hydrogel wound dressing via photo-polymerization for infected skin wound healing", + "Authors": "Yang, YT; Liang, YP; Chen, JY; Duan, XL; Guo, BL", + "Source Title": "BIOACTIVE MATERIALS", + "Abstract": "With the increasing prevalence of drug-resistant bacterial infections and the slow healing of chronically infected wounds, the development of new antibacterial and accelerated wound healing dressings has become a serious challenge. In order to solve this problem, we developed photo-crosslinked multifunctional antibacterial adhesive anti-oxidant hemostatic hydrogel dressings based on polyethylene glycol monomethyl ether modified glycidyl methacrylate functionalized chitosan (CSG-PEG), methacrylamide dopamine (DMA) and zinc ion for disinfection of drug-resistant bacteria and promoting wound healing. The mechanical properties, rheological properties and morphology of hydrogels were characterized, and the biocompatibility of these hydrogels was studied through cell compatibility and blood compatibility tests. These hydrogels were tested for the in vitro blood-clotting ability of whole blood and showed good hemostatic ability in the mouse liver hemorrhage model and the mouse-tail amputation model. In addition, it has been confirmed that the multifunctional hydrogels have good inherent antibacterial properties against Methicillin-resistant Staphylococcus aureus (MRSA). In the full-thickness skin defect model infected with MRSA, the wound closure ratio, thickness of granulation tissue, number of collagen deposition, regeneration of blood vessels and hair follicles were measured. The inflammation-related cytokines (CD68) and angiogenesis-related cytokines (CD31) expressed during skin regeneration were studied. All results indicate that these multifunctional antibacterial adhesive hemostatic hydrogels have better healing effects than commercially available Tegaderm (TM) Film, revealing that they have become promising alternative in the healing of infected wounds.", + "Times Cited, WoS Core": 440, + "Times Cited, All Databases": 456, + "Publication Year": 2022, + "Research Areas": "Engineering; Materials Science", + "UT (Unique WOS ID)": "WOS:000751867500024", + "Markdown": "# Mussel-inspired adhesive antioxidant antibacterial hemostatic composite hydrogel wound dressing via photo-polymerization for infected skin wound healing \n\nYutong Yang a,b, Yongping Liang b, Jueying Chen b, Xianglong Duan a,c,\\*\\*, Baolin Guo b,\\* \n\na Second Department of General Surgery, Shaanxi Provincial People’s Hospital, Xi’an, 710068, China \nb Frontier Institute of Science and Technology, and State Key Laboratory for Mechanical Behavior of Materials, and Key Laboratory of Shaanxi Province for Craniofacial \nPrecision Medicine Research, College of Stomatology, Xi’an Jiaotong University, Xi’an, 710049, China \nc Second Department of General Surgery, Third Affiliated Hospital of Xi’an Jiaotong University, Xi’an, 710068, China \n\n# A R T I C L E I N F O \n\nKeywords: \nChitosan \nWound dressing \nAntibacterial \nWound healing \nHemostat \nInfected skin wound \n\n# A B S T R A C T \n\nWith the increasing prevalence of drug-resistant bacterial infections and the slow healing of chronically infected wounds, the development of new antibacterial and accelerated wound healing dressings has become a serious challenge. In order to solve this problem, we developed photo-crosslinked multifunctional antibacterial adhesive anti-oxidant hemostatic hydrogel dressings based on polyethylene glycol monomethyl ether modified glycidyl methacrylate functionalized chitosan (CSG-PEG), methacrylamide dopamine (DMA) and zinc ion for disinfection of drug-resistant bacteria and promoting wound healing. The mechanical properties, rheological properties and morphology of hydrogels were characterized, and the biocompatibility of these hydrogels was studied through cell compatibility and blood compatibility tests. These hydrogels were tested for the in vitro blood-clotting ability of whole blood and showed good hemostatic ability in the mouse liver hemorrhage model and the mouse-tail amputation model. In addition, it has been confirmed that the multifunctional hydrogels have good inherent antibacterial properties against Methicillin-resistant Staphylococcus aureus (MRSA). In the full-thickness skin defect model infected with MRSA, the wound closure ratio, thickness of granulation tissue, number of collagen deposition, regeneration of blood vessels and hair follicles were measured. The inflammation-related cytokines (CD68) and angiogenesis-related cytokines (CD31) expressed during skin regeneration were studied. All results indicate that these multifunctional antibacterial adhesive hemostatic hydrogels have better healing effects than commercially available Tegaderm™ Film, revealing that they have become promising alternative in the healing of infected wounds. \n\n# 1. Introduction \n\nSkin constitute the largest multi-layered organ of the human body, which includes the epidermis and dermis [1,2], and it also acts as a barrier for body protection, such as preventing excessive evaporation of water, and protecting the human body from the invasion of pathogens [3–5]. However, once the entire epidermis severely injured, the skin will lose the most basic protective effect, especially the microbial infection of the wound site will severely prolong the healing process [6,7]. If it cannot be treated effectively in time, chronic wounds are easily colo­ nized by pathogens such as Escherichia coli, Staphylococcus aureus, and \n\nStaphylococcus epidermidis, finally causing non-functional scar [8–10]. For a long time in the past, antibiotics have been widely and massively used, which inevitably leads to the emergence of drug-resistance [11–13]. Therefore, it is very important to develop antibiotic-free multifunctional wound dressings to treat bacterial infections. \n\nHydrogel has a unique three-dimensional network structure, composed of natural or synthetic polymers, and shows good water ab­ sorption and biodegradability [14,15]. In particular, hydrogels can provide a moist environment for callus and epithelial cells, and accel­ erate the deposition of collagen and the proliferation of fibroblasts [16–18], thereby effectively promoting epithelialization and speeding \n\nY. Yang et al. \n\nup wound healing [19–21]. Chitosan (CS) is a natural cationic poly­ saccharide which has been widely used in the preparation of hydrogels [22]. However, the application of chitosan is limited by its poor water solubility [23]. In consideration of solving this critical problem, CS is modified by various water-soluble groups. Polyethylene glycol mono­ methyl ether (mPEG) is a highly hydrophilic polymer, which is widely used in biomedical applications due to its excellent biocompatibility [24]. The modification of chitosan with mPEG (CS-PEG) not only im­ proves the water solubility, increases the mechanical strength of the hydrogel, but also shows excellent biocompatibility [25,26]. In addition, study has shown that polysaccharides grafted with mPEG can promote hemostasis [27], which further expands the clinical use of mPEG grafted chitosan-based hydrogels. However, the antibacterial properties of CS-PEG are not enough to deal with wound healing caused by drug-resistant bacteria. \n\nAmong many antibacterial agent, antibacterial activity of metal ion is mild and efficient [28], which can not only effectively sterilize, but also avoid burns that may be caused by photo-thermal antibacterial methods [29]. Zinc ions can cause bacterial death, because zinc ions play an important role in inhibiting active transport and amino acid metabolism and enzyme system destruction [30]. In addition, electro­ static force from positively charged zinc ions and the negatively charged bacteria surface destroys the bacterial cell membrane, causing leakage of cell contents [17]. Furthermore, zinc ions can increase self-cleaning and keratinocyte migration during wound healing, which is useful during skin regeneration [31]. Metal nanoparticles are usually used as carriers for ion release [32]. However, metal nanoparticles are usually simply mixed in the hydrogel, which inevitably causes poor dis­ persibility [33]. In addition, metal particles degrade slowly and are not suitable for wound repair [32,34,35]. The coordination of zinc ions with the polymers might be a promising alternative approach. Zinc ions can form complexation with hydroxyl group and amine groups. As an important adhesive and antioxidant, dopamine with hydroxyl groups can form a stable complexation effect with zinc ions [36,37]. Further­ more, hydrogels containing dopamine usually show excellent tissue adhesion mainly due to the interaction between catechol groups and amino or thiol group of the tissues [38], and they exhibited good adhesion with the tissue to achieve hemostasis [39]. In addition, the antioxidant capacity of dopamine can effectively relieve the oxidative stress of the wound site and improve the speed of wound repair [40]. However, the complexion of zinc ions with dopamine has not been re­ ported for wound dressing. \n\nAmong the various gel polymerization methods, photo-initiated polymerization can control the formation of hydrogel in space and time [41], and has better polymerization efficiency and is unaffected by temperature conditions [42]. Photo-polymerization has been widely used to prepare biomaterials for drug delivery and tissue engineering. However, there are few reports on photo-crosslinked hydrogels for wound repair. \n\nIn this work, we developed adhesive antioxidant antibacterial he­ mostatic composite hydrogels based on polyethylene glycol mono­ methyl ether modified glycidyl methacrylate functionalized chitosan (CSG-PEG) and double bond modified-dopamine (DMA) and zinc ions via photo-polymerization and the coordination of zinc ions with the catechol group of dopamine. The rheological properties, mechanical properties, and adhesion properties of the obtained hydrogels were characterized. In addition, the inherent antibacterial ability, bloodclotting ability, and hemostasis ability of these hydrogels were tested. Besides, the biocompatibility of CSG-PEG/DMA/Zn hydrogel is tested by blood compatibility and cell compatibility. Finally, in a mouse model of full-thickness skin defect infected by drug-resistant bacteria MRSA, the CSG-PEG/DMA/Zn hydrogel was explored to promote the regeneration of blood vessels and hair follicles and to further enhance wound healing. All the results indicated that these multifunctional antibacterial hydro­ gels have enhanced hemostasis and wound healing effects in infected skin tissue defects, showing great potential for clinical application. \n\n# 2. Materials and method \n\n# 2.1. Materials \n\nChitosan $\\mathrm{{(M_{n}=100000{-}3000000a)}}$ , dopamine hydrochloride (DA) (purity $98\\%$ ) and succinic anhydride were obtained from J&K. Poly­ ethylene glycol monomethyl ether (mPEG), methacrylate anhydride $(94\\%)$ , glycidyl methacrylate $(\\geq97\\%)$ and zinc chloride were purchased from Sigma-Aldrich. All other reagents were used without further purification. \n\n# 2.2. Synthesis of mPEG-COOH and CSG-PEG \n\nmPEG-COOH was first synthesized by improving the previously re­ ported method [43]. In short, the active carboxyl end of mPEG is pre­ pared by using succinic anhydride. The specific process of synthesizing mPEG-COOH is shown in the supplementary information (SI). \n\nCSG-PEG is prepared by a two-step one-pot approach based on the reaction between the carboxyl group of mPEG-COOH, the epoxy group on glycidyl methacrylate and the amino group on chitosan. The specific process is shown in SI. \n\n# 2.3. Synthesis of DMA and LAP \n\nMethacrylamide dopamine (DMA) and lithium acylphosphinate (LAP) were synthesized using the reported method [44]. The specific process is shown in SI. \n\n# 2.4. Preparation of CSG-PEG/DMA/Zn hydrogel \n\nFirst, CSG-PEG, DMA, zinc chloride, and LAP were dissolved with concentration of $25\\mathrm{wt\\%}$ , $10\\mathrm{wt\\%}$ , $4.5\\mathrm{wt\\%}$ , and $1\\mathrm{wt}\\%$ respectively. The molar ratio of zinc ions to DMA was set as 1:2, and the corresponding mixed solution of zinc chloride and DMA was prepared. The final con­ centrations of DMA3, DMA6, and DMA9 were $0.3\\mathrm{wt\\%}$ $(15\\upmu\\mathrm{L})$ , $0.6\\mathrm{wt}\\%$ $(30~\\upmu\\mathrm{L})$ , and $0.9\\ \\mathrm{wt}\\%$ $(45~\\upmu\\mathrm{L})$ , respectively. The zinc ions final concen­ tration corresponding to DMA was $0.09\\mathrm{wt\\%}$ $(10\\upmu\\mathrm{L})$ , $0.18~\\mathrm{wt\\%}$ $(20~\\upmu\\mathrm{L})$ , and $0.27~\\mathrm{wt\\%}$ $(30~\\upmu\\mathrm{L})$ , respectively. Next, $400~\\ensuremath{\\upmu\\mathrm{L}}$ of CSG-PEG solution was uniformly mixed with a fixed ratio of DMA/Zn mixture solution (the molar ratio is 2:1), then the LAP aqueous solution with a final concen­ tration of $0.05\\ \\mathrm{wt\\%}$ $(25~\\upmu\\mathrm{L})$ was added under stirring and make up the volume of the hydrogel precursor solution to $500~\\upmu\\mathrm{L}$ with DI water. Finally, hydrogel pre-polymer was put under the excitation of ultraviolet light $(365~\\mathrm{nm})$ for $^{15\\mathrm{~s},}$ and after a while, the sol-gel transition completed. \n\n# 2.5. Characterizations \n\nThe nuclear magnetic resonance $\\mathrm{(^{1}H\\ N M R)}$ , and Fourier transform infrared spectroscopy (FT-IR) were used to confirm the successful preparation of DMA, mPEG-COOH and CSG-PEG. The equilibrium swelling ratio, in vitro degradability, and scanning electron microscope (SEM) were used to confirm swelling and degradation properties and the morphology of CSG-PEG/DMA/Zn hydrogels. The specific processes are shown in SI. \n\n# 2.6. Rheological and mechanical test of hydrogels \n\nThe modulus of these hydrogels is measured by using a TA rheometer (dhr-2), and the modulus changes over time are recorded [45]. Compressive stress-strain curve of CSG-PEG/DMA/Zn hydrogels was obtained by a cyclic compression test with modification according to our previous report [46]. The specific process is shown in SI. \n\n# Y. Yang et al. \n\n# 2.7. Adhesion strength test and antioxidant efficiency of hydrogels \n\nThe adhesion property of the CSG-PEG/DMA/Zn hydrogels was evaluated by a lap-shear test based on the previous study [47]. The specific processes are shown in SI. \n\nThe antioxidant capacity of these hydrogels by scavenging the stable 1,1-diphenyl-2-pyridohydrazino (DPPH) free radicals was evaluated by referring to previous report [48]. The specific process is shown in SI. \n\n# 2.8. In vitro whole blood-clotting performance \n\nThe in vitro whole blood-clotting test was performed according to the previous method [49]. The specific process is shown in SI. \n\n# 2.9. Hemolytic test of hydrogels \n\nA fixed amount of hydrogel was mixed with blood cells, incubated at $37^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ , and then the absorbance at $540\\mathrm{nm}$ was tested to evaluate hemolysis [50]. The specific processes are shown in SI. \n\n# 2.10. Hemostasis performance of hydrogels \n\nReferring to previous research, the hemostatic capability of the CSGPEG/DMA/Zn hydrogel was tested by employing a mouse liver hemor­ rhage model, and mouse-tail amputation model (Kunming mice, 30–35 g, female). The specific process is shown in SI. \n\n# 2.11. Antibacterial property and zinc ions release test of hydrogels \n\nThe antibacterial ability of hydrogels was evaluated through contact antibacterial test and MIC test. $10~\\upmu\\mathrm{L}$ of bacterial suspension ( $\\cdot{10}^{6}$ CFU/ mL) was mixed with the hydrogel in a 48-well plate, then $10~\\upmu\\mathrm{L}$ of bacterial suspension without materials was used as a control. After incubating the plate at $37^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ , a certain amount of sterile PBS was added to each well to re-suspend the surviving bacteria. After incubating at $37^{\\circ}\\mathrm{C}$ for $18{-}24\\mathrm{h}$ , the colony forming unit (CFU) was calculated on the petri dish [51]. The specific processes are shown in SI. The detailed information of MIC test is shown in SI. \n\nThe zinc ion release performance of the hydrogels is tested by a zinc ions kit assay, and the details are shown in the SI. \n\n# 2.12. Cytocompatibility test of hydrogels \n\nThe cytocompatibility test was performed by using leaching solution method and direct contact method according to previous research [52]. The specific process is shown in SI. \n\n# 2.13. In vivo wound healing evaluation with a drug-resistant bacterial infected full-thickness skin defect model \n\nTo further evaluate the enhanced effect of CSG-PEG/DMA/Zn hydrogel on wound healing, a full-thickness skin defect model of MRSA infection was established. Hematoxylin-eosin (H&E) staining was used for histomorphological measurement at different stages of wound regeneration to assess inflammation and epidermal regeneration in the wound area. The collagen amount was evaluated by Masson trichrome staining and commercial kits (Jiancheng bioengineering, China) were used to estimate the content of hydroxyproline [4]. All operations fol­ lowed the manufacturer’s instructions. The specific process is shown in SI. All the animal experiments were approved by the institutional review board of Xi’an Jiaotong University. \n\n# 2.14. Histology and immunohistochemistry \n\nHistological and immunohistochemistry examinations were per­ formed to assess the vascular remodeling and inflammatory cells during \n\nwound healing. CD31 and CD68 were selected for the immunohisto­ chemistry staining [3]. The specific process is shown in SI. \n\n# 2.15. Statistical analysis \n\nStatistical analysis on all experimental data of the study was per­ formed, and the results are expressed as mean $\\pm$ standard deviation (SD). A one-way analysis of variance (ANOVA) followed by Bonferroni post-hoc test was used to make multiple comparisons with SPSS version 24 (IBM) to determine statistical differences $(\\mathbf{P}<0.05)$ . \n\n# 3. Results and discussion \n\n# 3.1. Preparation of CSG-PEG/DMA/Zn hydrogel \n\nChronic wounds infected by MRSA have a high mortality ratio worldwide, so there is an urgent need to develop a series of new hydrogel dressings to address this issue. The regeneration of fullthickness skin wound is a complicated process, which needs many functions of the materials to fulfill this process, including antibacterial property to kill the bacteria, good hemostasis to stop bleeding, and antioxidant property to promote wound healing, ect. However, such multi-functional hydrogel wound dressing is rarely reported. In this study, a series of multifunctional antibacterial and antioxidant adhesion hemostatic hydrogels for wound healing of drug-resistant bacterial in­ fections have been developed. CS is a natural cationic polysaccharide, which is widely used due to its excellent wound healing effect [53], hemostatic ability [54], and antibacterial activity [55]. However, the poor solubility of CS limits its further application [56]. Thus, a series of chitosan derivatives was designed to improve the solubility in water. For example, quaternized chitosan has been widely used, but highly qua­ ternized modification can cause severe cytotoxicity [57]. In this work, as shown in Fig. 1a, mPEG-modified chitosan (CS-PEG) with good biocompatibility and improved solubility was developed by amidation reaction of polyethylene glycol monomethyl ether onto the backbone of CS in an aqueous solution. Furthermore, a double bond was introduced to CS-PEG by grafting glycidyl methacrylate to endow the polymer of CS-PEG with the ability that can form the basic network of the hydrogels by photo-initiated radical polymerization [41]. At the same time, double bond modified-dopamine (DMA) was synthesized in hopes of improving the adhesion and antioxidant capacity of the dressings. Besides, zinc ions was introduced to improve the antibacterial properties of hydrogels [51]. The hydrogel precursor premix was obtained by mixing the zinc chloride $\\mathrm{(ZnCl_{2})}$ aqueous solution with CSG-PEG and DMA. Subse­ quently, dual network cross-linked hydrogel was formed with LAP as photo-initiator through the polymerization of double bonds that derived from CSG-PEG and DMA. At the same time, zinc ions uniformly dispersed in the hydrogel network and coordinated with catechol group of dopamine. The covalent cross-linking between CSG-PEG and DMA serves as the main backbone component of the hydrogel network, and the stacking of dopamine benzene rings, the coordination of metal ions with catechol group and the hydrogen bonding give the hydrogel a second non-covalent physical crosslinking network (Fig. 1b). The mutual coordination of the dual networks contributes to the energy dissipation of the entire system, so that the hydrogel can withstand a certain degree of deformation imposed by external mechanical forces. Zinc ions were uniformly dispersed in the hydrogel system, not only as a cross-linking component, but also show the antibacterial properties [51]. At the same time, zinc ions can also promote the formation of epithelial tissue during wound healing [31]. By increasing the DMA concentration from $0\\mathrm{wt\\%}$ to $0.3\\mathrm{wt\\%}$ , $0.6\\mathrm{wt}\\%$ , and $0.9\\mathrm{wt\\%}$ (relative to the weight of the total hydrogel precursor) and setting the molar ratio of zinc ions concentration to DMA of 1:2, the zinc ions concentration corresponding to the DMA concentration is $0.09\\ \\mathrm{wt\\%}$ , $0.18~\\mathrm{wt\\%}$ , and $0.27~\\mathrm{wt\\%}$ respectively, a series of hydrogels with different rheology, morphology, and mechanical properties were obtained (Fig. 2a). The \n\nY. Yang et al. \n\n![](images/9134c842287c49d77116b886562e9e9d06e5b19ce4043dadb743d2bd53b80c52.jpg) \nFig. 1. (a) Synthesis of DMA, mPEG-COOH, and CSG-PEG; (b) Schematic representation of the CSG-PEG/DMA/Zn hydrogel formation; (c) Properties of hydrogel and its application in infected wound healing. \n\nhydrogels were named as CSG-PEG, CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn, and CSG-PEG/DMA9/Zn as shown in Fig. S1. The obtained adhesive, antioxidant, antibacterial and hemostasis dual network hydrogels were used as a wound dressing during the repair of infected wounds (Fig. 1c). \n\nThe chemical structure of DMA, mPEG-COOH, CSG-PEG and CSGPEG/DMA/Zn hydrogel was studied by FT-IR spectroscopy (Fig. 2b). For DMA, the characteristic signal at $1650~\\mathrm{cm}^{-1}$ was attributed to the stretching vibration of $\\mathtt{C=}0$ in the amide group, indicating that ami­ dation reaction occurred during the synthesis of DMA [58]. In addition, the characteristic signal around $3225~\\mathrm{cm}^{-1}$ exhibited the stretching vi­ bration of –OH in catechol group. For mPEG-COOH, the absorption peaks of $\\mathtt{C=}0$ and $-\\mathtt{C O O}$ with stretching and antisymmetric stretching vibration occurred at $1735\\mathrm{cm}^{-1}\\mathrm{and}1560\\mathrm{cm}^{-1}$ , respectively, indicating that mPEG has been successfully carboxylated [59]. For CSG-PEG, the absorption peak related to mPEG appeared at $840~\\mathrm{cm}^{-1}$ and $960~\\mathrm{cm}^{-1}$ , and the absorption peak of double bond was about $1660~\\mathrm{{cm}^{-1}}$ , indi­ cating that mPEG and glycidyl methacylate have been successfully grafted to CS [60]. The $^\\mathrm{i}\\mathrm{_{H}}$ nuclear magnetic resonance $\\cdot^{1}\\mathrm{H}$ NMR) analysis results of DMA, mPEG-COOH and CSG-PEG (Figs. S2–S4) further proved the successful modification of the dopamine, mPEG and CS. Compared with the infrared spectrum of CSG-PEG, the peak of CSG-PEG/DMA/Zn hydrogel at $16\\bar{6}0~\\mathrm{cm}^{-1}$ disappeared, which indi­ cated that DMA and CSG-PEG were polymerized via photo-polymerization of double bond. \n\n# 3.2. Gelation time, swelling, degradation, rheology, and mechanical properties of hydrogels \n\nThe gelation time of hydrogel is very important in clinical and biomedical applications [61]. The gelation time of hydrogels was eval­ uated by the duration of UV light irradiation, and the gelation time of CSG-PEG, CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn, and CSG-PEG/DMA9/Zn hydrogels was about $^{15\\ s,}$ and this dose of irradi­ ation is safe for biological tissues [62] and is good for their in vivo application. \n\nTissue exudates are produced when the skin is wounded, and excessive exudate will cause bacteria to proliferate and affect the wound healing process. Hydrogel can absorb excess exudate from the wound while maintaining a moist environment [63]. Therefore, the swelling properties of these hydrogels were tested, and equilibrium swelling ratio (ESR) were used to evaluate the water swelling degree of different hydrogels under physiological conditions in vitro $37^{\\circ}\\mathrm{C}$ PBS buffer (Fig. 2c). After all hydrogels reached swelling equilibrium, the ESR of CSG-PEG, CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn and CSG-PEG/DMA9/Zn were $1607\\%\\pm125\\%$ , $1536\\%\\pm71\\%$ , $1321\\%\\pm$ $90\\%$ and $1140\\%\\pm91\\%$ , respectively. The results indicated that the hydrogel with higher DMA and zinc ions content showed lower ESR, which was attributed to the higher cross-linking density due to higher content of zinc ions and DMA, and the hydrophobic nature of DMA and the hydrophobic interaction between DMAs via $\\pi{-}\\pi$ stacking are addi­ tional reasons that lead to lower ESR of the hydrogels containing the DMA. \n\nThe degradation behavior of these hydrogels in $37^{\\circ}\\mathrm{C}$ PBS buffer (pH $=7.4)$ was evaluated by simulating the physiological environment in \n\nY. Yang et al. \n\n![](images/1c363343a2df63bf1b8e0ea68da168b9844ea8c8ca785efc30b5da3e1c9d3cb1.jpg) \nFig. 2. Characterization of CSG-PEG/DMA/Zn hydrogels. (a) Photographs of different hydrogels; (b) FT-IR spectra of DMA, mPEG-COOH, CSG-PEG, and CSG-PEG/ DMA/Zn hydrogel; (c) Equilibrium swelling ratio (ESR) of hydrogels $(\\mathfrak{n}=3)$ ); (d) In vitro degradation curve of hydrogels $\\mathbf{(n=3)}$ ; (e) Rheological behavior of hydrogels; (f–i) Compressive stress-strain curve of CSG-PEG, CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn, and CSG-PEG/DMA9/Zn hydrogels at $60\\%$ strain. \n\nvivo (Fig. 2d). After immersing the hydrogels in PBS for 3 days, the weight remaining ratio of CSG-PEG hydrogel was $60\\%$ of the initial weight, which might be because the unreacted CSG-PEG residuals in the network would diffuse out of the hydrogel matrix to cause the higher weight loss of the hydrogels in the first 3 days. While the weight remaining ratio of the CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn and CSG-PEG/DMA9/Zn hydrogels was $40\\%$ of the initial weight. After 13 days, the residual weight of all hydrogel groups remained at about $20\\%$ , demonstrating that CSG-PEG/DMA/Zn hydrogels showed tunable degradation rate. \n\nThe rheological properties of hydrogels were evaluated, and the temperature was set to $37^{\\circ}\\mathrm{C}$ to simulate body temperature during the test [64]. The storage modulus $(\\mathbf{G}^{\\prime})$ and loss modulus $(\\mathbf{G}^{\\prime\\prime})$ of different hydrogels were tested at a fixed frequency (10 rad $\\begin{array}{r}{\\mathbf{s}^{-1}.}\\end{array}$ ) (Fig. 2e). The minimum storage modulus of CSG-PEG hydrogel was approximately $130\\mathrm{Pa}$ . With the increase of DMA and zinc ions, the storage modulus of CSG-PEG/DMA3/Zn and CSG-PEG/DMA6/Zn hydrogels increased to $185~\\mathrm{Pa}$ and $265~\\mathrm{Pa}$ . CSG-PEG/DMA9/Zn hydrogel showed the highest storage modulus of approximately $283\\ \\mathrm{Pa}$ . These results proved that with the increase of DMA and zinc ions, the non-covalent interaction becomes more obvious leading to the gradual increase of modulus of the hydrogel. \n\nThe good resilience of different hydrogels has been confirmed by cyclic compression test (Fig. 2f–i). When a fixed compressive strain of $60\\%$ was applied to the hydrogel, no obvious damage was seen to the hydrogel, indicating that the hydrogel can withstand a high degree of morphological compression. After 25 loading-unloading cycles, all hydrogel groups can still recover to their original shape in a short time, and the stress-strain curves almost completely overlapped, indicating that these hydrogels have good compressibility. With the increase in the ratio of DMA and zinc ions, the hydrogel had a higher compressive stress. The compressive stress of CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/ Zn, and CSG-PEG/DMA9/Zn hydrogels at strain of $60\\%$ were $19\\mathrm{kPa}$ , 25 kPa, and $37\\mathrm{kPa}$ , respectively, higher than that of CSG-PEG hydrogel (18 kPa). All these results indicated that CSG-PEG/DMA/Zn hydrogels have good energy dissipation capacity when external forces are applied because of the non-covalent cross-linking network. \n\n# 3.3. Morphology, adhesion, and antioxidation of hydrogels \n\nThe uniform and interconnected morphology of these CSG-PEG/ DMA/Zn hydrogels were observed with a scanning electron micro­ scope (SEM) as shown in Fig. 3a. After hydrogels were freeze-dried, all the hydrogels showed similar pore size, and the range of pore size dis­ tribution is $50\\mathrm{-}170\\upmu\\mathrm{m}$ . Specifically, as the content of DMA and zinc ions increased, the average pore size of CSG-PEG, CSG-PEG/DMA3/Zn, CSGPEG/DMA6/Zn, and CSG-PEG/DMA9/Zn hydrogels decreased obvi­ ously, and they were $129.9\\pm19.1~\\upmu\\mathrm{m}$ , $111.1\\pm13.8~\\upmu\\mathrm{m}_{\\mathrm{\\Omega}}$ $102.5\\pm14.3$ $\\upmu\\mathrm{m}$ , and $88.5\\pm11.5{\\upmu\\mathrm{m}}$ respectively (Fig. 3b). This may be due to the $\\pi{-}\\pi$ interaction between DMA and the coordination interaction between catechol group of DMA and zinc ions increasing the degree of cross­ linking of the hydrogel [65]. \n\nWhen hydrogel wound dressing is applied to wound area, the good tissue adhesion of hydrogel can promote to form a physical barrier to prevent bacterial invasion, and provide a moist environment to accel­ erate wound healing [66]. Thus, the adhesion strength of hydrogel was tested to evaluate the tissue adhesion in vitro by conducting a lap shear test with some modification (Fig. 3d) [47]. CSG-PEG hydrogel exhibited the lowest adhesion strength of $6.7\\mathrm{kPa}$ , and the adhesion strength of the hydrogel increased from $7.3\\mathrm{kPa}$ to $11.5\\mathrm{{kPa}}$ (Fig. 3c) by increasing the \n\nY. Yang et al. \n\n![](images/f1fa4be490d81ad7d58dc0de6eee5bde7353d4afd6ed1e5157d4419c9047205e.jpg) \nFig. 3. Morphology, adhesion and antioxidation of CSG-PEG/DMA/Zn hydrogels. (a) SEM images of hydrogels, scale bar: $200~{\\upmu\\mathrm{m}};$ (b) Pore size distribution of hydrogels; (c) Adhesion strength of hydrogels; d) Schematic presentation of the hydrogel adhesion test; e) DPPH scavenging percentage with a concentration of $1\\mathrm{mg/}$ mL hydrogels after hydrogels contact with DPPH for $0.5\\mathrm{~h~}$ . \n\ncontent of DMA and zinc ions. However, the decrease in adhesion strength of CSG-PEG/DMA9/Zn hydrogel is mainly due to the increase in storage modulus of hydrogel [67]. The good adhesion property of the hydrogel was attributed to the following reasons. Firstly, the catechol groups and quinone groups on CSG-PEG/DMA/Zn hydrogel interact with the amino or thiol group of the tissues improving the adhesion strength of the dressings [25]. Besides, chitosan interacts with the phospholipid bilayer on the cell membrane through electrostatic and hydrophobic interactions which can also contribute to the adhesion strength [68]. In general, the adhesion strength of all hydrogel groups is better than commercial dressings (about $5\\mathrm{kPa}$ ) [69], and these hydro­ gels can effectively bond to the surface of the skin tissue as wound dressing. \n\nA large number of free radicals can be produced at the wound site, which will lead to lipid peroxidation, DNA fragmentation and enzyme inactivation [68]. It has been proven that the use of materials containing free radical scavenging capabilities on the wound site can promote wound healing [10]. The free radical scavenging performance was evaluated by the DPPH free radical scavenging efficiency of the hydrogel with a dry weight of $1\\ \\mathrm{mg/mL}$ . As shown in Fig. 3e, the CSG-PEG hydrogel only showed a small amount of free radical scavenging effi­ ciency, which may be because the CS has a certain degree of free radical scavenging capacity [70]. It is worth mentioning that the free radical scavenging efficiency of CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn, and CSG-PEG/DMA9/Zn hydrogels were all above $95\\%$ . The amount of DPPH scavenger contained in the dry weight of CSG-PEG/DMA6/Zn hydrogels of $1~\\mathrm{mg/mL}$ which was $131.6~{\\upmu\\mathrm{mol}}$ , and its amount is close to the molar amount of DPPH $\\cdot100\\upmu\\mathrm{mol};$ . So with respect to DPPH, the amount of DPPH scavenger was not much excessive. Overall, the good free radical scavenging ability of CSG-PEG/DMA/Zn hydrogel makes it have potential value for clinical wound healing applications. \n\n# 3.4. In vitro whole blood-clotting test, blood compatibility, and in vivo hemostasis of hydrogels \n\nWhen the skin is wounded, it will inevitably cause a certain degree of bleeding, so hemostasis is the first stage of wound healing [71]. An ideal wound dressing should promote platelets to aggregate at the wound site and form a blood clot to accelerate the hemostasis [49,72]. In vitro whole blood-clotting test is a common method to evaluate the blood clotting ability of hemostatic hydrogel [73], and a lower blood-clotting index (BCI) indicates a higher blood-clotting efficiency. Commercial gelatin sponge and gauze were selected as the control group of hemo­ static agents. After incubating the different dressings with blood for 10 min at $37^{\\circ}\\mathrm{C}$ , the results showed that BCI values of all hydrogel groups were lower than gauze and gelatin sponge $(\\mathbf{P}\\ <\\ 0.05)$ (Fig. 4a). In addition, the BCI index of all hydrogel groups was lower than that of carboxymethyl cellulose cross-linked gelatin-PEG hydrogel reported by other researchers [74]. These results indicated that CSG-PEG/DMA/Zn hydrogels have more significant hemostatic ability compared to gauze and gelatin sponge. \n\nGood blood compatibility is a prerequisite for the application of biomaterials [75,76]. The blood compatibility of CSG-PEG/DMA/Zn hydrogels were evaluated by in vitro hemolysis test. After incubating for 1 h in a simulated physiological environment in vitro, the appearance and color of four hydrogel groups and the positive control group (Triton X-100) were observed (Fig. 4b). All the hydrogel groups were slightly light yellow and consistent with PBS color, while the positive control group was bright red. Quantitative results showed the hemolysis ratio of all hydrogels was less than $5\\%$ . CSG-PEG showed the lowest hemolysis ratio of $1.97\\%$ . With the increase of the content of DMA and zinc ions, the hemolysis ratio of CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn, and CSG-PEG/DMA9/Zn hydrogels were $2.21\\%$ , $2.48\\%$ , and $2.79\\%$ , respectively, proving that these hydrogels have good blood compatibility. \n\nBecause the CSG-PEG/DMA6/Zn hydrogel exhibited the best adhe­ sion strength, good blood compatibility and blood-clotting index, the hemostatic performance of CSG-PEG/DMA6/Zn was further evaluated in mouse liver hemorrhage model and mouse-tail amputation model (Fig. 4c–h). In the mouse liver hemorrhage model (Fig. $^{4\\mathrm{c})}$ , compared with the blank group $(689.2\\pm33.8~\\mathrm{mg})$ , the blood loss of CSG-PEG/ DMA6/Zn hydrogel was significantly reduced $(223.7\\pm13.8~\\mathrm{mg}$ ) $(\\mathbf{P}<$ 0.01) (Fig. 4g). Next, the hemostatic performance of the mouse-tail amputation model was tested (Fig. 4d), and the blood loss of CSG \n\nY. Yang et al. \n\n![](images/0ae74666212f4288af589b2ffb0c2b27f05b15cf42eb2063f1e8a6a8edf938af.jpg) \nFig. 4. Whole blood-clotting, blood compatibility, and in vivo hemostasis test of CSG-PEG/DMA/Zn hydrogels. (a) Dynamic whole blood-clotting test; (b) Hemolysis ratio $(\\%)$ of hydrogels; Schematic representation of (c) mouse liver hemorrhage model and (d) mouse-tail amputation model; Bloodstain photographs of (e) mouse liver hemorrhage model and (f) mouse-tail amputation model; Quantitative results of blood loss ${\\bf\\langle n=4\\rangle}$ of $\\mathbf{\\delta}(\\mathbf{g})$ mouse liver hemorrhage model and h) mouse-tail amputation model. $\\therefore\\mathsf{P}<0.05$ , $\\ddot{\\mathbf{\\Omega}}^{**}\\mathbf{P}<0.01$ . \n\nPEG/DMA6/Zn hydrogel was significantly reduced $(33.4\\:\\pm\\:9.7\\:\\mathrm{\\mg})$ ) compared with the blank group $(237.8\\pm13.6\\mathrm{mg})$ $(\\mathbf{P}<0.01)$ (Fig. 4h), and it is worth mentioning that the blood loss of CSG-PEG/DMA6/Zn hydrogel is far less than the previously reported chitosan-based wound dressing $(261.28~\\pm~35.61~\\mathrm{{\\mg})}$ [77]. The hemostatic effect of CSG-PEG/DMA6/Zn hydrogel in vivo is mainly due to its hemostasis of chitosan and its good tissue adhesion ability which can adhere tightly to the wound site, providing a stable gel network as a physical barrier to accelerate blood-clotting. \n\n# 3.5. Antibacterial property and cell compatibility of hydrogels \n\nThe antibacterial effect of the hydrogels is important for them as wound dressing [78]. Firstly, these CSG-PEG/DMA/Zn hydrogels were contacted with bacteria to test their inherent antibacterial properties. After co-cultivation at $37^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ , CSG-PEG hydrogel performed a low sterilization ratio, which may be due to the inherent antibacterial of CS. In contrast, there was almost no obvious bacterial colony in the hydrogel group containing zinc ions (Fig. 5a, b, and c). Quantitative results showed that the CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn, and CSG-PEG/DMA9/Zn hydrogels could be effective against Staphylococcus aureus (S. aureus, Gram-positive bacteria) and Escherichia coli (E. coil, Gram-negative bacteria) (Fig. 5d, f), indicating that they have excellent antibacterial properties. As the zinc ions content increases, the anti­ bacterial property of hydrogels was enhanced. In addition, methicillin-resistant Staphylococcus aureus (MRSA), as a common clini­ cally drug-resistant bacteria has also been used to evaluate the inherent antibacterial properties of CSG-PEG/DMA/Zn hydrogels [8]. As shown in Fig. 5e, CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn and CSG-PEG/DMA9/Zn hydrogels also had a good antibacterial effect for MRSA due to the effective antibacterial property of zinc ions [79]. A contact antibacterial test of CSG-PEG/DMA6 hydrogel (Fig. S5) was also conducted. Without the zinc ions, the inhibition ratio of the CSG-PEG/DMA6 hydrogel for E. coil, S. aureus, MRSA is only $22.7\\%$ , $28.0\\%$ , and $30.5\\%$ , indicating that zinc ions are the main antibacterial component in the hydrogel. Furthermore, the minimum inhibitory concentration (MIC) of the CSG-PEG/DMA6/Zn hydrogel was shown in Fig. S6. The OD value of the bacterial stock solution was recorded as a positive control, and the OD value of MHB was recorded as a negative control. The absorbance value of the bacterial suspension after treat­ ment with different concentrations of materials was compared. The MIC of CSG-PEG/DMA6/Zn hydrogel for S. aureus, E. coil and MRSA were 4.0 $\\scriptstyle{\\mathrm{mg/mL}}$ , $12.5~\\mathrm{\\mg/mL}$ , and $4.5~\\mathrm{\\mg/mL}$ , respectively. The release behavior of zinc ions from the hydrogel was also tested. As shown in Fig. S7, zinc ions release showed burst release performance within 1 h and the release amounts were $16.53~\\upmu\\mathrm{g/mL}$ , $41.6~{\\upmu\\mathrm{g/mL}},$ and 62.5 $\\upmu\\mathrm{g/mL}$ , respectively. Then zinc ions release rate was slowed down, and showed a sustained release within $288{\\mathrm{h}}$ . After $288\\mathrm{h}$ , the release of zinc ions from the hydrogels reached $39.3~\\upmu\\mathrm{g/mL}$ , $86.9~\\upmu\\mathrm{g/mL}$ and 118.8 $\\upmu\\mathrm{g/mL}$ , which can provide sustained antibacterial property of the hydrogels. \n\nThe viability of L929 fibroblasts was used to evaluate the cell compatibility of these hydrogels. Firstly, the cytotoxicity of CSG-PEG/ DMA/Zn hydrogels were tested by the leaching solution method. As shown in Fig. 5g, h, and i, the number of cells increased significantly within five days, which indicated that the cells grew well throughout the experiment. At the same time, there was no difference in the cell viability of different concentrations of hydrogels, and the cell viability in the cell culture medium with hydrogel extract was similar to the TCP group, indicating that these hydrogels have good cell compatibility. \n\nSubsequently, the cytotoxicity of the materials was further evaluated by the direct contact method, and tested by co-cultivating the lyophi­ lized hydrogel with the cells seeded on the well plate. As shown in Fig. 5j, the cytotoxicity results on 1st day indicated that with the in­ crease of DMA and zinc ions concentration, cytotoxicity of the hydrogel showed a slight concentration-dependent changes. However, in general, different hydrogel groups all showed obvious good cell viability. After continuing to co-culture L929 cells with hydrogels from the day 1 to the day 3, it showed obvious increase of cell viability. On 3rd day, the cell viability of CSG-PEG/DMA9/Zn hydrogel had a difference compared with CSG-PEG/DMA3/Zn and CSG-PEG/DMA6/Zn $(\\mathbf{P}<0.05)$ . Through LIVE/DEAD cell staining on 3rd day (Fig. 5k), it was found that most of the L929 cells were green and in spindle-shape and only a few of dead cells, which was consistent with the quantitative results of alamarBlue. On 5th day, CSG-PEG, CSG-PEG/DMA3/Zn, CSG-PEG/DMA6/Zn, and CSG-PEG/DMA9/Zn hydrogels were no significant difference in cell viability compared with TCP. These results showed that, consistent with the results of the leaching solution method, the hydrogels have good cell \n\nY. Yang et al. \n\n![](images/e5c52cfc3bd5fc2e39dcbf25b4aa9dc4cd4e05ed16e41a3c4c67c367e156d5ec.jpg) \nFig. 5. Antibacterial and cell compatibility test of CSG-PEG/DMA6/Zn hydrogel. Images of contact antibacterial activity of hydrogel against (a) S. aureus and (b) MRSA and (c) $E.$ coli; Bacterial survival ratio of S. aureus (d), MRSA (e), and E. coli (f); The cell viability on day 1 (g), day 3 (h), and day 5 (i) by using the leaching solution method; (j) The results of L929 cells survival ratio obtained by direct contact method for 1 day, 3 days, and 5 days; (k) LIVE/DEAD staining pictures of hydrogel and cells co-cultured for $^{72\\mathrm{~h~}}$ ${\\bf\\lbrack n=4}{\\bf\\dot{\\Bigl.}}$ ). \n\ncompatibility. The cell proliferation ability of this new type hydrogels is better than our previous reported host-guest interaction hydrogels based on quaternized chitosan [46], and these hydrogels can be used as a potential candidate for clinical dressings. \n\n# 3.6. In vivo wound healing in infected full-thickness skin defect model \n\nAll the above test results showed that CSG-PEG/DMA/Zn hydrogel can be used as a potential wound dressing for skin repair. Among them, CSG-PEG/DMA6/Zn with suitable mechanical strength, good adhesion and hemostatic ability and cell compatibility were chosen as the representative. Drug-resistant MRSA infected mouse full-thickness defect model was established to evaluate the efficacy of these hydro­ gels as wound dressings. Tegaderm™ Film was used as a control group. Since antibiotics was widely used to treat skin wound, CSG-PEG/DMA6 hydrogel loaded with amoxicillin (CSG-PEG/DMA6-Am) in situ was regarded as another control group. As shown in Fig. 6a, b, and c, the results showed that the wound area of all groups had a certain degree of shrinkage from 3 days to 7 days, and to 14 days. After 3 days of treat­ ment, there was still some yellow pus at the wound site (Fig. 6a), indi­ cating that the full-thickness skin defect model of MRSA infection was successfully established. The wound area of CSG-PEG, CSG-PEG/DMA6- Am, and CSG-PEG/DMA6/Zn hydrogel groups were significantly smaller than that of commercial Tegaderm™ Film group (Fig. 6c). The wound closure ratio of CSG-PEG/DMA6/Zn hydrogel group was approximately $25\\%$ higher than that of Tegaderm™ Film group $(\\mathbf{P}<$ 0.01), which showed the best wound repair effect. The wound closure ratio of CSG-PEG and CSG-PEG/DMA6-Am hydrogel groups was similar, and also obviously higher than Tegaderm™ Film group. After 7 days of treatment, the wound closure ratio of CSG-PEG, CSG-PEG/DMA6-Am and CSG-PEG/DMA6/Zn hydrogel groups was $63\\%$ , $74\\%$ , and $86\\%$ , respectively, which showed that the wound healing effect of these hydrogels was better than Tegaderm™ Film group. Besides, the wound closure ratio of CSG-PEG/DMA6/Zn hydrogel group was significantly higher than that of Tegaderm ™ Film group and CSG-PEG hydrogel group $(\\mathbf{P}<0.01)$ ). More importantly, the wound closure rate of the CSGPEG/DMA6/Zn hydrogel group on day 7 was better than that of the other repeorted mPEG-modified chitosan-based hydrogel [26], which is because zinc ions provided the antibacterial effect in the initial stage of infection, and promoted the migration of fibroblasts and vascular remodeling during the wound healing stage. On the 14th day, the wound in the CSG-PEG/DMA6/Zn group was almost completely healed (wound closure ratio was more than $95\\%$ ). The residual area of the wound in the CSG-PEG/DMA6-Am hydrogel was only $10\\%$ , and amount of wound area remained more than $10\\%$ in the other groups. \n\n![](images/2a28d823211ba69cd51245866d48fb7b5156940783dceb5c1701d18097f3109d.jpg) \nFig. 6. (a) Images of the wound healing site on the 3rd, 7th and 14th day; (b) Schematic presentation of the wound healing site on the 3rd, 7th and 14th day; c) Statistical data of wound closure ratio $(\\mathbf{n}=5)$ ; d) Pictures of regenerating granulation tissue on the 7th day (granulation tissue: blue arrows), scale bar: $400~{\\upmu\\mathrm{m}};$ e) The results of the thickness of the regenerated granulation tissue on the 7th day $(\\mathtt{n}=5)$ . $\\therefore\\mathbf{p}<0.05$ , $\\stackrel{*}{\\cdot}\\stackrel{*}{\\cdot}\\mathbf{P}<0.01$ . \n\nGranulation tissue is composed of newly formed capillaries and proliferated fibroblasts, which play a critical role in wound repair [4]. Therefore, the thickness of granulation tissue was measured to distin­ guish the quality of wound repair. As shown in Fig. 6d and e, after 7 days of healing, Tegaderm™ Film showed the thinnest granulation tissue thickness $(441~{\\upmu\\mathrm{m}})$ ). The granulation tissue thickness of CSG-PEG and CSG-PEG/DMA6-Am, and CSG-PEG/DMA6/Zn hydrogel were $527~{\\upmu\\mathrm{m}}$ , and $628~{\\upmu\\mathrm{m}};$ , and $724~{\\upmu\\mathrm{m}}$ , respectively, and $724~{\\upmu\\mathrm{m}}$ was significantly thicker than other groups $(\\mathbf{P}<0.01)$ ). All these results indicated the best effects of CSG-PEG/DMA6/Zn hydrogel in the wound healing process. In conclusion, the hydrogel containing dopamine and zinc ions showed the best treatment effect in entire wound healing stage. This is because dopamine can effectively remove ROS and prevent peroxidation damage at the wound site, and zinc ions can not only effectively kill bacterium, but also promote the proliferation and migration of fibroblasts, which contributes to the formation of epithelial tissue [17,20,80]. In general, CSG-PEG/DMA6/Zn hydrogel is superior to the commercial Tegaderm™ Film due to its inherent antibacterial and wound healing ability. \n\n# 3.7. Histomorphological evaluation \n\nWound healing is a complex and orderly physiological process, which includes hemostasis, inflammation, migration, proliferation and remodeling [81]. Hematoxylin and eosin stained sections (H&E stain­ ing) were used to evaluate the wound healing effect at different stages [82]. As shown in Fig. 7a, all the hydrogel groups showed mild in­ flammatory response after 3 days of treatment, but Tegaderm™ Film group showed strong acute inflammation. Besides, compared with the CSG-PEG and CSG-PEG/DMA6-Am hydrogel groups, the CSG-PEG/DMA6/Zn hydrogel group showed relatively fewer inflam­ matory cells and more fibroblasts. This may be due to the antioxidant ability of dopamine, and zinc ions’ promotion of migration of fibroblasts [20]. On the 7th day, all the groups almost formed varied degrees of epidermal structure, and had a large number of migrated fibroblasts. Compared with Tegaderm™ Film and CSG-PEG, CSG-PEG/DMA6-Am and CSG-PEG/DMA6/Zn hydrogel groups had relatively thicker epidermis. \n\nNew blood vessels provide nutrients and oxygen for wound site, which is essential for wound repairing [83]. The number of blood vessels at the wound site was counted on the 7th day to evaluate wound healing effect (Fig. 7c), and the results showed that the CSG-PEG/DMA6/Zn hydrogel group revealed the best angiogenesis promotion effect (Fig. 7a, pointed by the red arrow), which was significantly higher than Tegaderm™ Film group $(\\mathbf{P}<0.01)$ and CSG-PEG hydrogel group $(\\mathbf{P}<$ 0.05). This is due to the function of zinc ions to promote angiogenesis [80]. On the 14th day, although the Tegaderm™ Film group showed complete epithelial regeneration, but still no obvious hair follicle for­ mation. In contrast, the hydrogel treatment groups, especially epidermal structure of the CSG-PEG/DMA6/Zn hydrogel group appeared similar to the normal tissues, and there was more skin component such as hair follicles (Fig. 7a, pointed by the green arrow). The statistical results showed that the number of hair follicle regeneration in CSG-PEG/DMA6/Zn hydrogel group was significantly higher than that in Tegaderm™ Film $(\\mathbf{P}<0.05)$ and CSG-PEG hydrogel group $(\\mathbf{P}<0.05)$ (Fig. 7b). However, CSG-PEG/DMA6-Am hydrogel group occurred a certain degree of irregular epidermis on the 14th day, which indicated that wound healing effect of CSG -PEG/DMA6-Am hydrogel was not very satisfactory. These results indicated that the CSG-PEG/DMA6/Zn hydrogel exhibits the best effect on extracellular matrix remodeling and tissue regeneration. \n\n![](images/7cc81af57fd3331acbfa40f4729a9bce1da2d8aaee52821d6ab7a9254b020ee9.jpg) \nFig. 7. (a) Morphological results of wound healing site after treatment for 3 days, 7 days and 14 days, and Masson’s trichrome staining at the wound site on the 7th day, scale bar: $200~{\\upmu\\mathrm{m}};$ (b) Newborn hair follicles on 14th day; (c) Regeneration of blood vessels on 7th day; (d) Collagen amount by measuring the content of hydroxyproline. $\\therefore\\mathbf{p}<0.05$ , $\\because\\mathopen{}\\mathclose\\bgroup\\left.\\begin{array}{r l}\\end{array}\\aftergroup\\egroup\\right.<0.01$ . \n\n# 3.8. Analysis of collagen deposition in wound healing \n\nThe process of wound healing always accompanied by changes in collagen metabolism. Hydroxyproline is the most widely distributed key component of collagen (content is $13.4\\%$ [46], and the amount of hy­ droxyproline can reflect the collagen metabolism of wound site [84]. The total collagen level in granulation tissue was tested by analyzing the content of hydroxyproline to evaluate the effects of the four treatments groups. As shown in Fig. 7d, on the 3rd day, CSG-PEG/DMA6/Zn hydrogel group showed the most collagen deposition compared with \n\nY. Yang et al. \n\nother groups $\\mathrm{~(P~<~}0.01\\mathrm{{\\dot{\\iota}}}$ ). The amount of collagen deposition of CSG-PEG/DMA6/Zn hydrogel group was significantly higher than that in the CSG-PEG/DMA-Am hydrogel group on the 7th day $(\\mathbf{P}<0.05)$ . On the 14th day, the collagen deposition of CSG-PEG/DMA6/Zn hydrogel group and CSG-PEG/DMA6-Am hydrogel group was similar, which was still significantly higher than that of Tegaderm™ Film group and CSG-PEG hydrogel group $(\\mathbf{P}<0.01)$ ). Within 14 days of treatment, the collagen content in the wound site continued to increase. Compared with the Tegaderm™ Film group, the hydrogel groups showed a better collagen deposition throughout the repairing process. At the same time, Masson’s trichrome staining was performed on the tissue section on the 7th day to observe collagen deposition (Fig. 7a). The collagen in the wound treated was dyed blue. Compared with Tegaderm™ Film group, the hydrogel treatment groups exhibited more blue color, and the CSG-PEG/DMA6/Zn group showed the best collagen regeneration abil­ ity compared with other hydrogel groups. Therefore, these results proved that the CSG-PEG/DMA6/Zn hydrogel can effectively promote collagen deposition. \n\n# 3.9. The expression of CD31 and CD68 during wound healing \n\nMany studies have shown that cytokine changes during wound healing are closely related to cell metabolism and proliferation [85,86]. CD68 is ubiquitous in monocytes and macrophages, especially near the wounds [87]. CD68 is highly expressed in inflammation, as the level of inflammation decreases, the expression of CD68 decreases [88]. CD31 plays an important role in vascular regeneration for the proliferation and remolding stage of wound healing, and is used to evaluate the neovascularization during wound healing [89]. Therefore, CD68 and CD31 were selected as indicators to evaluate the inflammation and angiogenesis of wound healing process for wound dressing. The immu­ nofluorescence staining of CD68 (Fig. 8a) and the quantitative results (Fig. 8b) showed that the expression of CD68 is higher in the inflam­ mation stage, and the expression level gradually decreases over time during the whole process of wound healing. On the 3rd day and 7th day, compared with other groups, the CSG-PEG/DMA6/Zn hydrogel group showed the lowest CD68 expression $(\\mathbf{P}~<~0.05)$ , which was mainly \n\n![](images/f045664789aa48737a064dcb480960df1896b56a22ed9b95307cbd8c1c669884.jpg) \nFig. 8. Immunofluorescence staining results of wound regeneration site on 3rd day and 7th day with (a) CD68 and on 7th day and 14th day with (d) CD31. Red arrows indicate the expression of CD68, and yellow arrows indicate CD31, scale bar: $50\\upmu\\mathrm{m};$ Quantitative results of (b) CD68 and (c) CD31 relative area ratio $\\left(\\mathbf{n}=3\\right)$ ). For all quantitative data, the data of the commercial film groups on the 3rd day of CD68 and the 7th day of CD31 were taken as $100\\%$ . $\\therefore\\mathbf{P}<0.05$ , $\\ddot{\\mathfrak{s}}\\mathbin{\\ddot{\\times}}\\mathbf{p}_{\\mathbf{\\xi}}<0.01$ . \n\nY. Yang et al. \n\nbecause the zinc ion is antibacterial and can promote fibroblast prolif­ eration. The immunofluorescence staining of CD31 and quantitative results are shown in Fig. 8c and d. Compared with Tegaderm™ Film, CSG-PEG and CSG-PEG/DMA-Am, the wound site treated with CSG-PEG/DMA6/Zn hydrogel showed more CD31 expression on the 7th day. In addition, on the 14th day, the expression levels of CD31 in the CSG-PEG/DMA-Am hydrogel group and the CSG-PEG/DMA6/Zn hydrogel group were similar and significantly higher than Tegaderm™ Film group $(\\mathbf{P}<0.05)$ . In short, by reducing the expression of CD68 and simultaneously promoting the expression of CD31, CSG-PEG/DMA6/Zn hydrogel can significantly promote wound healing and has a better repair effect than Tegaderm™ Film. \n\n# 4. Conclusions \n\nIn this work, we developed a series of multifunctional hydrogels with antibacterial properties, compressibility, adhesion, antioxidation and hemostasis, and further demonstrated that they can be used as a new type of drug-resistant bacteria infected skin wound dressing. These hydrogels showed stable rheological property, short gelation time, excellent tissue adhesion, biocompatibility, antibacterial property and free radical scavenging capability, which can effectively promote wound healing. In addition, the CSG-PEG/DMA6/Zn hydrogel showed good blood-clotting ability in vitro and hemostatic ability in vivo. Compared with Tegaderm™ Film and PEG-CSG and PEG-CSG/DMA-Am, CSG-PEG/ DMA6/Zn hydrogels showed the excellent therapeutic effect in term of the wound closure ratio, granulation tissue regeneration and collagen deposition in the full-thickness skin defect model of MRSA infection. In addition, the results of CD31 and CD68 staining during the wound healing process further showed that these multifunctional hydrogels have effective promotion in the wound healing process by reducing inflammation and promoting vascular regeneration. All results indicate that these multifunctional antibiotic-independent antibacterial adhesion antioxidant hemostasis hydrogels represent competitive candidates and can be used to treat wounds infected by resistant bacteria. \n\n# CRediT authorship contribution statement \n\nYutong Yang: Formal analysis, Writing – original draft, Methodol­ ogy. Yongping Liang: Conducted most of the animal experiments, Formal analysis. Jueying Chen: Conducted the antibacterial test, Formal analysis. Xianglong Duan: Writing – review & editing, Project administration, Funding acquisition. Baolin Guo: Conceptualization, Methodology, Writing – review & editing, Supervision, Funding acquisition. \n\n# Declaration of competing interest \n\nThe authors declare that they have no competing interests. \n\n# Acknowledgments \n\nThis work was jointly supported by the National Natural Science Foundation of China (grant numbers: 51973172, and 51673155), the Natural Science Foundation of Shaanxi Province (No. 2020JC-03 and 2019TD-020), State Key Laboratory for Mechanical Behavior of Mate­ rials, and the Fundamental Research Funds for the Central Universities, and the World-Class Universities (Disciplines) and the Characteristic Development Guidance Funds for the Central Universities, and Opening Project of Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi’an Jiaotong University (No. 2019LHM-KFKT008), and the Key R&D Program of Shaanxi Prov­ ince (No. 2019ZDLSF02-09-01, 2020GXLH-Y-019), Innovation Capa­ bility Support Program of Shaanxi Province (Program No. 2019GHJD14, 2021TD-40), and Scientific Research Program Funded by Shaanxi Provincial Education Department (ProgramNo.18JC027). \n\n# Appendix A. Supplementary data \n\nSupplementary data to this article can be found online at https://doi. org/10.1016/j.bioactmat.2021.06.014. \n\n# References \n\n[1] N. Annabi, D. Rana, E. Shirzaei Sani, R. Portillo-Lara, J.L. Gifford, M.M. Fares, S. M. Mithieux, A.S. Weiss, Engineering a sprayable and elastic hydrogel adhesive with antimicrobial properties for wound healing, Biomaterials 139 (2017) 229–243. \n[2] M. Li, Y. Liang, J. He, H. Zhang, B. Guo, Two-pronged strategy of biomechanically active and biochemically multifunctional hydrogel wound dressing to accelerate wound closure and wound healing, Chem. Mater. 32 (2020) 9937–9953. [3] J. He, Y. Liang, M. Shi, B. Guo, Anti-oxidant electroactive and antibacterial nanofibrous wound dressings based on poly(ε-caprolactone)/quaternized chitosangraft-polyaniline for full-thickness skin wound healing, Chem. Eng. J. 385 (2020) 123464. \n[4] J. He, M. Shi, Y. Liang, B. Guo, Conductive adhesive self-healing nanocomposite hydrogel wound dressing for photothermal therapy of infected full-thickness skin wounds, Chem. Eng. J. 394 (2020) 124888. \n[5] C. Hu, F. Zhang, Q. Kong, Y. Lu, B. Zhang, C. Wu, R. Luo, Y. Wang, Synergistic chemical and photodynamic antimicrobial therapy for enhanced wound healing mediated by multifunctional light-responsive nanoparticles, Biomacromolecules 20 (2019) 4581–4592. \n[6] S. Li, M. Pei, T. Wan, H. Yang, S. Gu, Y. Tao, X. Liu, Y. Zhou, W. Xu, P. Xiao, Selfhealing hyaluronic acid hydrogels based on dynamic Schiff base linkages as biomaterials, Carbohydr. Polym. 250 (2020) 116922. [7] Z. Li, F. Zhou, Z. Li, S. Lin, L. Chen, L. Liu, Y. Chen, Hydrogel cross-linked with dynamic covalent bonding and micellization for promoting burn wound healing, ACS Appl. Mater. Interfaces 10 (2018) 25194–25202. [8] Y. Liang, B. Chen, M. Li, J. He, Z. Yin, B. Guo, Injectable Antimicrobial conductive hydrogels for wound disinfection and infectious wound healing, Biomacromolecules 21 (2020) 1841–1852. [9] C. Qi, L. Xu, Y. Deng, G. Wang, Z. Wang, L. Wang, Sericin hydrogels promote skin wound healing with effective regeneration of hair follicles and sebaceous glands after complete loss of epidermis and dermis, Biomater. Sci. 6 (2018) 2859–2870. \n[10] X. Zhao, M. Zhang, B. Guo, P.X. Ma, Mussel-inspired injectable supramolecular and covalent bond crosslinked hydrogels with rapid self-healing and recovery properties via a facile approach under metal-free conditions, J. Mater. Chem. B 4 (2016) 6644–6651. \n[11] J. Currie, W. Lin, W. Zhang, Patient knowledge and antibiotic abuse: evidence from an audit study in China, J. Health Econ. 30 (2011) 933–949. \n[12] J. Zhang, J. Ge, Y. Xu, J. Chen, A. Zhou, L. Sun, Y. Gao, Y. Zhang, T. Gu, X. Ning, Bioactive multi-engineered hydrogel offers simultaneous promise against antibiotic resistance and wound damage, Int. J. Biol. Macromol. 164 (2020) 4466–4474. \n[13] X. Zhao, Y. Liang, Y. Huang, J. He, Y. Han, B. Guo, Physical double-network hydrogel adhesives with rapid shape adaptability, fast self-healing, antioxidant and NIR/pH stimulus-responsiveness for multidrug-resistant bacterial infection and removable wound dressing, Adv. Funct. Mater. 30 (2020) 1910748. \n[14] S. Ahtzaz, M. Nasir, L. Shahzadi, W. Amir, A. Anjum, R. Arshad, F. Iqbal, A. A. Chaudhry, M. Yar, I.u. Rehman, A study on the effect of zinc oxide and zinc peroxide nanoparticles to enhance angiogenesis-pro-angiogenic grafts for tissue regeneration applications, Mater, DES 132 (2017) 409–418. \n[15] H. Chen, J. Cheng, L. Ran, K. Yu, B. Lu, G. Lan, F. Dai, F. Lu, An injectable selfhealing hydrogel with adhesive and antibacterial properties effectively promotes wound healing, Carbohydr. Polym. 201 (2018) 522–531. \n[16] X. Du, Y. Hou, L. Wu, S. Li, A. Yu, D. Kong, L. Wang, G. Niu, An anti-infective hydrogel adhesive with non-swelling and robust mechanical properties for sutureless wound closure, J. Mater. Chem. B 8 (2020) 5682–5693. \n[17] Y. Gao, Y. Han, M. Cui, H.L. Tey, L. Wang, C. Xu, ZnO nanoparticles as an antimicrobial tissue adhesive for skin wound closure, J. Mater. Chem. B 5 (2017) 4535–4541. \n[18] W. Han, B. Zhou, K. Yang, X. Xiong, S. Luan, Y. Wang, Z. Xu, P. Lei, Z. Luo, J. Gao, Y. Zhan, G. Chen, L. Liang, R. Wang, S. Li, H. Xu, Biofilm-inspired adhesive and antibacterial hydrogel with tough tissue integration performance for sealing hemostasis and wound healing, Bioactive Mater. 5 (2020) 768–778. \n[19] H. Cheng, K. Yue, M. Kazemzadeh-Narbat, Y. Liu, A. Khalilpour, B. Li, Y.S. Zhang, N. Annabi, A. Khademhosseini, Mussel-Inspired multifunctional hydrogel coating for prevention of infections and enhanced osteogenesis, ACS Appl. Mater. Interfaces 9 (2017) 11428–11439. \n[20] Y. Li, X. Liu, L. Tan, Z. Cui, X. Yang, Y. Zheng, K.W.K. Yeung, P.K. Chu, S. Wu, Rapid sterilization and accelerated wound healing using Zn2+ and graphene oxide modified g-C3N4 under dual light irradiation, Adv. Funct. Mater. 28 (2018) 1800299. \n[21] T. Majima, W. Schnabel, W. Weber, Phenyl-2,4,6-Trimethylbenzoylphosphinates as water-soluble photoinitiators - generation and reactivity of O=P(C6h5)(O-) radical-anions, Makromolekulare Chemie-Macromolecular Chemistry and Physics 192 (1991) 2307–2315. \n[22] X. Du, Y. Liu, H. Yan, M. Rafique, S. Li, X. Shan, L. Wu, M. Qiao, D. Kong, L. Wang, Anti-Infective and pro-coagulant chitosan-based hydrogel tissue adhesive for sutureless wound closure, Biomacromolecules 21 (2020) 1243–1253. \n[23] N. Bhattarai, J. Gunn, M. Zhang, Chitosan-based hydrogels for controlled, localized drug delivery, Adv. Drug Deliv. Rev. 62 (2010) 83–99. \nY. Yang et al. \n[24] M.S. Sarwar, A. Ghaffar, Q. Huang, M.S. Zafar, M. Usman, M. Latif, Controlledrelease behavior of ciprofloxacin from a biocompatible polymeric system based on sodium alginate/poly(ethylene glycol) mono methyl ether, Int. J. Biol. Macromol. 165 (2020) 1047–1054. \n[25] T. Ito, C. Yoshida, Y. Murakami, Design of novel sheet-shaped chitosan hydrogel for wound healing: a hybrid biomaterial consisting of both PEG-grafted chitosan and crosslinkable polymeric micelles acting as drug containers, Mater. Sci. Eng. C 33 (2013) 3697–3703. \n[26] D.H. Yang, D.I. Seo, D.-W. Lee, S.H. Bhang, K. Park, G. Jang, C.H. Kim, H.J. Chun, Preparation and evaluation of visible-light cured glycol chitosan hydrogel dressing containing dual growth factors for accelerated wound healing, J. Ind. Eng. Chem. 53 (2017) 360–370. \n[27] J. Zhu, F. Li, X. Wang, J. Yu, D. Wu, Hyaluronic acid and polyethylene glycol hybrid hydrogel encapsulating nanogel with hemostasis and sustainable antibacterial property for wound healing, ACS Appl. Mater. Interfaces 10 (2018) 13304–13316. \n[28] V. Mourin˜o, J.P. Cattalini, A.R. Boccaccini, Metallic ions as therapeutic agents in tissue engineering scaffolds: an overview of their biological applications and strategies for new developments, J. R. Soc. Interface 9 (2012) 401–419. \n[29] Y. Shi, M. Liu, F. Deng, G. Zeng, Q. Wan, X. Zhang, Y. Wei, Recent progress and development on polymeric nanomaterials for photothermal therapy: a brief overview, J. Mater. Chem. B 5 (2017) 194–206. \n[30] A. Sirelkhatim, S. Mahmud, A. Seeni, N.H.M. Kaus, L.C. Ann, S.K.M. Bakhori, H. Hasan, D. Mohamad, Review on zinc oxide nanoparticles: antibacterial activity and toxicity mechanism, Nano-Micro Lett. 7 (2015) 219–242. \n[31] C. Mao, Y. Xiang, X. Liu, Z. Cui, X. Yang, K.W.K. Yeung, H. Pan, X. Wang, P.K. Chu, S. Wu, Photo-Inspired antibacterial activity and wound healing acceleration by hydrogel embedded with Ag/Ag@AgCl/ZnO nanostructures, ACS Nano 11 (2017) 9010–9021. \n[32] Z. Bao, X. Liu, Y. Liu, H. Liu, K. Zhao, Near-infrared light-responsive inorganic nanomaterials for photothermal therapy, Asian J. Pharm. Sci. 11 (2016) 349–364. \n[33] P.G. Jamkhande, N.W. Ghule, A.H. Bamer, M.G. Kalaskar, Metal nanoparticles synthesis: an overview on methods of preparation, advantages and disadvantages, and applications, J. Drug Deliv. Sci. Technol. 53 (2019) 101174. \n[34] N.R. Brun, M. Lenz, B. Wehrli, K. Fent, Comparative effects of zinc oxide nanoparticles and dissolved zinc on zebrafish embryos and eleuthero-embryos: importance of zinc ions, Sci. Total Environ. 476–477 (2014) 657–666. \n[35] G. Applerot, A. Lipovsky, R. Dror, N. Perkas, Y. Nitzan, R. Lubart, A. Gedanken, Enhanced antibacterial activity of nanocrystalline ZnO due to increased ROSmediated cell injury, Adv. Funct. Mater. 19 (2009) 842–852. \n[36] D.E. Fullenkamp, J.G. Rivera, Y.-k. Gong, K.H.A. Lau, L. He, R. Varshney, P. B. Messersmith, Mussel-inspired silver-releasing antibacterial hydrogels, Biomaterials 33 (2012) 3783–3791. \n[37] D. Gan, T. Xu, W. Xing, X. Ge, L. Fang, K. Wang, F. Ren, X. Lu, Mussel-Inspired contact-active antibacterial hydrogel with high cell affinity, toughness, and recoverability, Adv. Funct. Mater. 29 (2019) 1805964. \n[38] X. He, X. Liu, J. Yang, H. Du, N. Chai, Z. Sha, M. Geng, X. Zhou, C. He, Tannic acidreinforced methacrylated chitosan/methacrylated silk fibroin hydrogels with multifunctionality for accelerating wound healing, Carbohydr. Polym. 247 (2020) 116689. \n[39] Y. Liang, Z. Li, Y. Huang, R. Yu, B. Guo, Dual-Dynamic-bond cross-linked antibacterial adhesive hydrogel sealants with on-demand removability for postwound-closure and infected wound healing, ACS Nano 15 (2021) 7078–7093. \n[40] M. Puertas-Bartolome´, L. Benito-Garzo´n, S. Fung, J. Kohn, B. V´azquez-Lasa, J. San Roma´n, Bioadhesive functional hydrogels: controlled release of catechol species with antioxidant and antiinflammatory behavior, Mater. Sci. Eng. C 105 (2019) 110040. \n[41] T. Wang, X.Y. Mu, H.B. Li, W.L. Wu, J. Nie, D.Z. Yang, The photocrosslinkable tissue adhesive based on copolymeric dextran/HEMA, Carbohydr. Polym. 92 (2013) 1423–1431. \n[42] J. Hu, Y. Hou, H. Park, B. Choi, S. Hou, A. Chung, M. Lee, Visible light crosslinkable chitosan hydrogels for tissue engineering, Acta Biomater. 8 (2012) 1730–1738. \n[43] R. Mathiyalagan, Y.J. Kim, C. Wang, Y. Jin, S. Subramaniyam, P. Singh, D. Wang, D.C. Yang, Protopanaxadiol aglycone ginsenoside-polyethylene glycol conjugates: synthesis, physicochemical characterizations, and in vitro studies, Artif. Cell Nanomed. B 44 (2016) 1803–1809. \n[44] S. Hou, P.X. Ma, Stimuli-Responsive supramolecular hydrogels with high extensibility and fast self-healing via precoordinated mussel-inspired chemistry, Chem. Mater. 27 (2015) 7627–7635. \n[45] J. Qu, X. Zhao, P.X. Ma, B. Guo, Injectable antibacterial conductive hydrogels with dual response to an electric field and pH for localized “smart” drug release, Acta Biomater. 72 (2018) 55–69. \n[46] B. Zhang, J. He, M. Shi, Y. Liang, B. Guo, Injectable self-healing supramolecular hydrogels with conductivity and photo-thermal antibacterial activity to enhance complete skin regeneration, Chem. Eng. J. 400 (2020) 125994. \n[47] E. Shirzaei Sani, R. Portillo Lara, Z. Aldawood, S.H. Bassir, D. Nguyen, A. Kantarci, G. Intini, N. Annabi, An antimicrobial dental light curable bioadhesive hydrogel for treatment of peri-implant diseases, Matter 1 (2019) 926–944. \n[48] Y. Liang, X. Zhao, T. Hu, B. Chen, Z. Yin, P.X. Ma, B. Guo, Adhesive hemostatic conducting injectable composite hydrogels with sustained drug release and photothermal antibacterial activity to promote full-thickness skin regeneration during wound healing, Small 15 (2019) 1900046. \n[49] Y. Huang, X. Zhao, Z. Zhang, Y. Liang, Z. Yin, B. Chen, L. Bai, Y. Han, B. Guo, Degradable gelatin-based IPN cryogel hemostat for rapidly stopping deep noncompressible hemorrhage and simultaneously improving wound healing, Chem. Mater. 32 (2020) 6595–6610. \n[50] X. Zhao, P. Li, B. Guo, P.X. Ma, Antibacterial and conductive injectable hydrogels based on quaternized chitosan-graft-polyaniline/oxidized dextran for tissue engineering, Acta Biomater. 26 (2015) 236–248. \n[51] M. Zhang, S. Chen, L. Zhong, B. Wang, H. Wang, F. Hong, Zn2+-loaded TOBC nanofiber-reinforced biomimetic calcium alginate hydrogel for antibacterial wound dressing, Int. J. Biol. Macromol. 143 (2020) 235–242. \n[52] M. Shu, S. Long, Y. Huang, D. Li, H. Li, X. Li, High strength and antibacterial polyelectrolyte complex CS/HS hydrogel films for wound healing, Soft Matter 15 (2019) 7686–7694. \n[53] T. Dai, M. Tanaka, Y.-Y. Huang, M.R. Hamblin, Chitosan preparations for wounds and burns: antimicrobial and wound-healing effects, Expert Rev. Anti Infect. Ther. 9 (2011) 857–879. \n[54] X. Huang, Y. Sun, J. Nie, W. Lu, L. Yang, Z. Zhang, H. Yin, Z. Wang, Q. Hu, Using absorbable chitosan hemostatic sponges as a promising surgical dressing, Int. J. Biol. Macromol. 75 (2015) 322–329. \n[55] A. Verlee, S. Mincke, C.V. Stevens, Recent developments in antibacterial and antifungal chitosan and its derivatives, Carbohydr. Polym. 164 (2017) 268–283. \n[56] T. Furuike, D. Komoto, H. Hashimoto, H. Tamura, Preparation of chitosan hydrogel and its solubility in organic acids, Int. J. Biol. Macromol. 104 (2017) 1620–1625. \n[57] A. Zubareva, B. Shagdarova, V. Varlamov, E. Kashirina, E. Svirshchevskaya, Penetration and toxicity of chitosan and its derivatives, Eur. Polym. J. 93 (2017) 743–749. \n[58] H. Xu, D. Zhang, J. Li, Antibacterial nanoparticles with universal adhesion function based on dopamine and eugenol, J. Bioresour. Bioprod. 4 (2019) 177–182. \n[59] Y.-I. Jeong, D.-G. Kim, M.-K. Jang, J.-W. Nah, Preparation and spectroscopic characterization of methoxy poly(ethylene glycol)-grafted water-soluble chitosan, Carbohydr. Res. 343 (2008) 282–289. \n[60] M. He, C.-C. Chu, Dual stimuli responsive glycidyl methacrylate chitosanquaternary ammonium hybrid hydrogel and its bovine serum albumin release, J. Appl. Polym. Sci. 130 (2013) 3736–3745. \n[61] Y. Hong, Y. Xi, J. Zhang, D. Wang, H. Zhang, N. Yan, S. He, J. Du, Polymersome–hydrogel composites with combined quick and long-term antibacterial activities, J. Mater. Chem. B 6 (2018) 6311–6321. \n[62] I.W.G.o.R.o.S. Cancer, E.t.A.U.L. Meeting, Exposure to Artificial UV Radiation and Skin Cancer, Exposure to Artificial UV Radiation and Skin Cancer, 2006. \n[63] R. Wang, B. Zhou, D.-l. Xu, H. Xu, L. Liang, X.-h. Feng, P.-k. Ouyang, B. Chi, Antimicrobial and biocompatible ε-polylysine–γ-poly(glutamic acid)–based hydrogel system for wound healing, J. Bioact. Compat Polym. 31 (2016) 242–259. \n[64] Z. Zhang, X. Wang, Y. Wang, J. Hao, Rapid-forming and self-healing agarose-based hydrogels for tissue adhesives and potential wound dressings, Biomacromolecules 19 (2018) 980–988. \n[65] Y.P. Liang, X. Zhao, T.L. Hu, Y. Han, B.L. Guo, Mussel-inspired, antibacterial, conductive, antioxidant, injectable composite hydrogel wound dressing to promote the regeneration of infected skin, J. Colloid Interface Sci. 556 (2019) 514–528. \n[66] Q. Tang, C. Chen, Y. Jiang, J. Huang, Y. Liu, P.M. Nthumba, G. Gu, X. Wu, Y. Zhao, J. Ren, Engineering an adhesive based on photosensitive polymer hydrogels and silver nanoparticles for wound healing, J. Mater. Chem. B 8 (2020) 5756–5764. \n[67] J. Yang, J. Keijsers, M. van Heek, A. Stuiver, M.A. Cohen Stuart, M. Kamperman, The effect of molecular composition and crosslinking on adhesion of a bio-inspired adhesive, Polym. Chem. 6 (2015) 3121–3130. \n[68] W. Zhang, R. Wang, Z. Sun, X. Zhu, Q. Zhao, T. Zhang, A. Cholewinski, F. Yang, B. Zhao, R. Pinnaratip, P.K. Forooshani, B.P. Lee, Catechol-functionalized hydrogels: biomimetic design, adhesion mechanism, and biomedical applications, Chem. Soc. Rev. 49 (2020) 433–464. \n[69] J. Qu, X. Zhao, Y. Liang, T. Zhang, P.X. Ma, B. Guo, Antibacterial adhesive injectable hydrogels with rapid self-healing, extensibility and compressibility as wound dressing for joints skin wound healing, Biomaterials 183 (2018) 185–199. \n[70] H. Li, Q. Xu, Y. Chen, A. Wan, Effect of concentration and molecular weight of chitosan and its derivative on the free radical scavenging ability, J. Biomed. Mater. Res. 102 (2014) 911–916. \n[71] C. Liu, C. Liu, S. Yu, N. Wang, W. Yao, X. Liu, G. Sun, Q. Song, W. Qiao, Efficient antibacterial dextran-montmorillonite composite sponge for rapid hemostasis with wound healing, Int. J. Biol. Macromol. 160 (2020) 1130–1143. \n[72] X. Zhao, Y. Liang, B. Guo, Z. Yin, D. Zhu, Y. Han, Injectable dry cryogels with excellent blood-sucking expansion and blood clotting to cease hemorrhage for lethal deep-wounds, coagulopathy and tissue regeneration, Chem. Eng. J. 403 (2021) 126329. \n[73] X. Zhao, B.L. Guo, H. Wu, Y.P. Liang, P.X. Ma, Injectable antibacterial conductive nanocomposite cryogels with rapid shape recovery for noncompressible hemorrhage and wound healing, Nat. Commun. 9 (2018) 1–17. \n[74] D. Li, Y. Ye, D. Li, X. Li, C. Mu, Biological properties of dialdehyde carboxymethyl cellulose crosslinked gelatin–PEG composite hydrogel fibers for wound dressings, Carbohydr. Polym. 137 (2016) 508–514. \n[75] D. Zhang, Z. Xu, H. Li, C. Fan, C. Cui, T. Wu, M. Xiao, Y. Yang, J. Yang, W. Liu, Fabrication of strong hydrogen-bonding induced coacervate adhesive hydrogels with antibacterial and hemostatic activities, Biomater. Sci. 8 (2020) 1455–1463. \n[76] Y. Zhu, J. Zhang, J. Song, J. Yang, T. Xu, C. Pan, L. Zhang, One-step synthesis of an antibacterial and pro-healing wound dressing that can treat wound infections, . Mater. Chem. B 5 (2017) 8451–8458. \n[77] W. Zheng, C. Chen, X. Zhang, X. Wen, Y. Xiao, L. Li, Q. Xu, F. Fu, H. Diao, X. Liu, Layer-by-layer coating of carboxymethyl chitosan-gelatin-alginate on cotton gauze for hemostasis and wound healing, Surf. Coating. Technol. 406 (2021) 126644. \n[78] Y. Zhang, M. Chang, F. Bao, M. Xing, E. Wang, Q. Xu, Z. Huan, F. Guo, J. Chang, Multifunctional Zn doped hollow mesoporous silica/polycaprolactone electrospun membranes with enhanced hair follicle regeneration and antibacterial activity for wound healing, Nanoscale 11 (2019) 6315–6333. \n\n# Y. Yang et al. \n\n[79] Y. Liang, M. Wang, Z. Zhang, G. Ren, Y. Liu, S. Wu, J. Shen, Facile synthesis of ZnO QDs@GO-CS hydrogel for synergetic antibacterial applications and enhanced wound healing, Chem. Eng. J. 378 (2019) 122043. \n[80] Y. Song, H. Wu, Y. Gao, J. Li, K. Lin, B. Liu, X. Lei, P. Cheng, S. Zhang, Y. Wang, J. Sun, L. Bi, G. Pei, Zinc silicate/nano-hydroxyapatite/collagen scaffolds promote angiogenesis and bone regeneration via the p38 MAPK pathway in activated monocytes, ACS Appl. Mater. Interfaces 12 (2020) 16058–16075. \n[81] J. Hoque, R.G. Prakash, K. Paramanandham, B.R. Shome, J. Haldar, Biocompatible injectable hydrogel with potent wound healing and antibacterial properties, Mol. Pharm. 14 (2017) 1218–1230. \n[82] C. Hou, W. He, Z. Wang, B. Yi, Z. Hu, W. Wang, X. Deng, X. Yao, Particulateaggregated adhesives with exudate-sensitive properties and sustained bacteria disinfection to facilitate wound healing, ACS Appl. Mater. Interfaces 12 (2020) 31090–31098. \n[83] M. Li, Z. Zhang, Y. Liang, J. He, B. Guo, Multifunctional tissue-adhesive cryogel wound dressing for rapid nonpressing surface hemorrhage and wound repair, ACS Appl. Mater. Interfaces 12 (2020) 35856–35872. \n[84] S. Sharma, R. Kumar, P. Kumari, R.N. Kharwar, A.K. Yadav, S. Saripella, Mechanically magnified chitosan-based hydrogel as tissue adhesive and antimicrobial candidate, Int. J. Biol. Macromol. 125 (2019) 109–115. \n[85] L. Huang, Z. Zhu, D. Wu, W. Gan, S. Zhu, W. Li, J. Tian, L. Li, C. Zhou, L. Lu, Antibacterial poly (ethylene glycol) diacrylate/chitosan hydrogels enhance mechanical adhesiveness and promote skin regeneration, Carbohydr. Polym. 225 (2019) 115110. \n[86] A. Song, A.A. Rane, K.L. Christman, Antibacterial and cell-adhesive polypeptide and poly(ethylene glycol) hydrogel as a potential scaffold for wound healing, Acta Biomater. 8 (2012) 41–50. \n[87] J.-G. Leu, S.-A. Chen, H.-M. Chen, W.-M. Wu, C.-F. Hung, Y.-D. Yao, C.-S. Tu, Y.- J. Liang, The effects of gold nanoparticles in wound healing with antioxidant epigallocatechin gallate and α-lipoic acid, Nanomedicine 8 (2012) 767–775. \n[88] Y. Shao, M. Dang, Y. Lin, F. Xue, Evaluation of wound healing activity of plumbagin in diabetic rats, Life Sci. 231 (2019) 116422. \n[89] G. Yin, Z. Wang, Z. Wang, X. Wang, Topical application of quercetin improves wound healing in pressure ulcer lesions, Exp. Dermatol. 27 (2018) 779–786. " + }, + { + "id": "10.1021_jacs.1c12764", + "DOI": "10.1021/jacs.1c12764", + "DOI Link": "http://dx.doi.org/10.1021/jacs.1c12764", + "Relative Dir Path": "mds/10.1021_jacs.1c12764", + "Article Title": "Co-Solvent Electrolyte Engineering for Stable Anode-Free Zinc Metal Batteries", + "Authors": "Ming, FW; Zhu, YP; Huang, G; Emwas, AH; Liang, HF; Cui, Y; Alshareef, HN", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Anode-free metal batteries can in principle offer higher energy density, but this requires them to have extraordinary Coulombic efficiency (>99.7%). Although Zn-based metal batteries are promising for stationary storage, the parasitic side reactions make anode-free batteries difficult to achieve in practice. In this work, a salting-in-effect-induced hybrid electrolyte is proposed as an effective strategy that enables both a highly reversible Zn anode and good stability and compatibility toward various cathodes. The as-prepared electrolyte can also work well under a wide temperature range (i.e., from -20 to 50 degrees C). It is demonstrated that in the presence of propylene carbonate, triflate anions are involved in the Zn2+ solvation sheath structure, even at a low salt concentration (2.14 M). The unique solvation structure results in the reduction of anions, thus forming a hydrophobic solid electrolyte interphase. The waterproof interphase along with the decreased water activity in the hybrid electrolyte effectively prevents side reactions, thus ensuring a stable Zn anode with an unprecedented Coulombic efficiency (99.93% over 500 cycles at 1 mA cm(-2)). More importantly, we design an anode-free Zn metal battery that exhibits excellent cycling stability (80% capacity retention after 275 cycles at 0.5 mA cm(-2)). This work provides a universal strategy to design co-solvent electrolytes for anode-free Zn metal batteries.", + "Times Cited, WoS Core": 437, + "Times Cited, All Databases": 444, + "Publication Year": 2022, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000799141600018", + "Markdown": "# Co-Solvent Electrolyte Engineering for Stable Anode-Free Zinc Metal Batteries \n\nFangwang Ming,# Yunpei Zhu,# Gang Huang, Abdul-Hamid Emwas, Hanfeng Liang, Yi Cui,\\* and Husam N. Alshareef\\* \n\nCite This: J. Am. Chem. Soc. 2022, 144, 7160−7170 \n\n![](images/c1a2adf2ce22030cde5217d4c5b1f06a7d4c05abbea53f0c282ca8944555ecf7.jpg) \n\n# Read Online \n\n# ACCESS \n\n山 Metrics & More 品 Article Recommendations \n\nSupporting Information \n\nABSTRACT: Anode-free metal batteries can in principle offer higher energy density, but this requires them to have extraordinary Coulombic efficiency $\\left(>99.7\\%\\right)$ . Although $Z\\mathbf{n}$ -based metal batteries are promising for stationary storage, the parasitic side reactions make anode-free batteries difficult to achieve in practice. In this work, a salting-in-effect-induced hybrid electrolyte is proposed as an effective strategy that enables both a highly reversible $Z\\mathrm{n}$ anode and good stability and compatibility toward various cathodes. The as-prepared electrolyte can also work well under a wide temperature range (i.e., from $-20$ to $\\dot{5}0~^{\\circ}\\mathrm{C}\\dot{}$ ). It is demonstrated that in the presence of propylene carbonate, triflate anions are involved in the $Z\\mathrm{n}^{2+}$ solvation sheath structure, even at a low salt concentration $(2.14\\mathrm{M})$ . The unique solvation structure results in the reduction of anions, thus forming a hydrophobic solid electrolyte interphase. The waterproof interphase along with the decreased water activity in the hybrid electrolyte effectively prevents side reactions, thus ensuring a stable $Z\\mathrm{n}$ anode with an unprecedented Coulombic efficiency $99.93\\%$ over 500 cycles at $\\mathrm{i}\\stackrel{\\cdot}{\\mathrm{mA}}\\mathrm{cm}^{-2}$ ). More importantly, we design an anode-free $Z\\mathbf{n}$ metal battery that exhibits excellent cycling stability ( $80\\%$ capacity retention after 275 cycles at $0.5\\mathrm{\\mA\\cm^{-2}}$ ). This work provides a universal strategy to design co-solvent electrolytes for anode-free $Z\\mathrm{n}$ metal batteries. \n\n![](images/e875b6dc9d8e8e4a1ee39eb1ef46aeae1812295b0726f9d3bb0ba7d247db03c0.jpg) \n\n# INTRODUCTION \n\nThanks to the high theoretical capacity of $Z\\mathrm{n}$ $\\mathrm{820\\mAh\\g^{-1}}$ or $5855\\mathrm{~mAh~cm}^{-3}\\mathrm{\\'}$ , relatively low redox potential $(-0.76~\\mathrm{V}$ vs standard hydrogen electrode), high safety, and low cost,1−7 aqueous rechargeable $Z\\mathrm{n}$ batteries are attractive in the field of stationary storage and micropower systems.8,9 Nevertheless, the practical energy densities of aqueous $Z\\mathbf{n}$ -based batteries are significantly limited using excessive Zn metal anodes (with a thickness of $50{-}200\\ \\mu\\mathrm{m}\\right,$ ). This almost unlimited zinc reservoir may cause seemingly enhanced cycling stability in research labs, which does not reflect the actual performance of the battery when used in practical applications. Inspired by the recently developed anode-free Li- and $\\mathbf{Na}$ -metal batteries,10−16 we wondered if the $Z\\mathrm{n}^{2+}$ ions extracted from a Zn-rich cathode can be reversibly deposited onto and stripped off from the current collector with high Coulombic efficiency (CE); if so, we may not need to use active zinc metal as an anode anymore. Thus, workable anode-free zinc metal batteries (AFZMBs) with greatly improved energy density can be realized.17 However, achieving a stable anode-free battery is not straightforward as there is no reservoir to compensate for the metal losses during cycling. One of the most critical factors for stable anode-free batteries is the Zn plating/stripping efficiency, as the cycle life of anode-free batteries depends sensitively on CE. Other prerequisites for high-performance anode-free batteries include a dendrite-free Zn plating morphology as well as a stable cathode.10,11,13−15,17 \n\nUnfortunately, in conventional aqueous $Z\\mathbf{n}$ batteries, the $Z\\mathrm{n}$ plating/stripping CE is inevitably limited by the water-related parasitic reactions (e.g., hydrogen evolution reaction (HER) and Zn corrosion) and dendrite formation.18,19 These issues pose a serious threat to the stability and cyclability of the standard $Z\\mathbf{n}$ -based batteries, let alone the anode-free ones. Considerable efforts have been devoted to mitigating these issues.20−27 For instance, Archer et al.20 demonstrated the highly reversible epitaxial electrodeposition of $Z\\mathrm{n}$ achieved by using a graphene substrate. Different electrolyte additives are also efficient in regulating the solvation structure or solid electrolyte interphase (SEI), thus realizing enhanced CE.23−25,27 In addition, highly concentrated electrolytes (or “water-in-salt”, WIS)21,22 can realize high reversibility; however, the low-cost and high ionic conductivity merits of aqueous electrolyte are significantly compromised. Among them, SEI rational design is one of the most effective means. In principle, a desirable SEI layer should possess both high hydrophobicity to prevent the $Z\\mathrm{n}$ metal from water, and high ionic conductivity for fast ion migration.28 However, this task is quite challenging and very limited investigations have been published. Therefore, universal strategies that can improve both anode and cathode stability while maintaining the high safety merits are urgently needed and still underdeveloped. \n\n![](images/a88d5dc74e1cc589e1db95b27da337935203e3cacfca25b85f44150aef93941e.jpg) \n\n![](images/832c9d08d67de263e3b9be50f859d00902bac9f97dac7763843439876674381d.jpg) \nScheme 1. Schematic Illustration of the Preparation of the Hybrid Electrolyte, the Corresponding Zn Solvation Structure, and the Resultant Hydrophobic Interphase \nFigure 1. Salt effect and solvation structure investigations. (a) Digital photographs of the (middle) water/PC mixture, the water/PC mixture with the (top) 1 M $\\mathrm{ZnSO}_{4},$ and (bottom) $\\mathrm{Zn}\\big(\\mathrm{CF}_{3}\\mathrm{SO}_{3}\\big)_{2}$ . (b) Digital photographs of the organic solvent/water mixture (left) before and (right) after adding a certain amount of $\\mathrm{Zn}\\big(\\mathrm{CF}_{3}\\mathrm{SO}_{3}\\big)_{2}$ salt. (c) FTIR spectra of pure water, PC, and various electrolytes with $^\\textrm{\\scriptsize1M}$ concentration. (d) Liquidstate NMR spectra of $^{17}\\mathrm{O}$ and $^{67}\\mathrm{Zn}$ in different environments. \n\nHerein, we discover a universal co-solvent strategy to realize not only a highly reversible zinc anode with high plating/ striping average CE (ACE $99.93\\%$ over 500 cycles) but also excellent compatibility and stability toward various cathode materials. As illustrated in Scheme 1, by adding zinc trifluoromethanesulfonate (zinc triflate or $\\mathrm{Zn}(\\mathrm{OTf})_{2})$ into the propylene carbonate (PC)/water mixtures, the originally phase-separated mixtures can be readily miscible to form transparent and stable solutions. The benefits of the introduction of PC solvent were confirmed by both experimental characterizations and molecular dynamics (MD) simulations. The significantly reduced water activity and the as-formed hydrophobic SEI that served as a protective layer are responsible for the high electrochemical performance. The co-solvent electrolyte can greatly enhance the stability of the cathodes as well. Meanwhile, the commercial polyaniline (PANI) exhibits good rate capability and stability under a wide temperature range (i.e., from $-20$ to $50~^{\\circ}\\mathrm{C}^{\\cdot}$ . As a proof-ofconcept, we assemble an AFZMB by coupling the Cu foil with the $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ cathode, which displays extraordinary stability, i.e., $80\\%$ capacity retention of the initial capacity for 275 cycles at the current density of $0.5~\\mathrm{mA}~\\mathrm{cm}^{-2}$ . It is worth noting that organic/water hybrid electrolytes have been previously proposed for Zn batteries; $^{24,27,\\ 29-31}$ however, this work is different from previous studies: (i) the salting-in effect has rarely been reported or discussed, and (ii) we have elucidated the solvation structure of different electrolytes experimentally and theoretically. These results are critical for building the structure−performance relationship as well as for designing high-performance anode-free $Z\\mathrm{n}$ -ion batteries. \n\n# RESULTS AND DISCUSSION \n\nSalt Effect. As a classical solvent in Li-ion batteries, PC shows several traits like a high dielectric constant (64.9 at 25 $^{\\circ}\\mathrm{C})$ ), high stability, low viscosity $(2.53~\\mathrm{mPa\\cdots}$ at $25~^{\\circ}\\mathrm{C}\\ '$ ), and a wide liquid range from $-48.8$ to $242{\\ }^{\\circ}{\\bf C}.{}^{32,33}$ Taking these properties into consideration, we first attempted to select PC as the co-solvent to suppress to intrinsic water-related side reactions while minimally compromising the other advantages of aqueous electrolyte (e.g., high ionic conductivity). Unfortunately, most zinc salts are insoluble or minimally soluble in PC. PC is also less miscible with water, and apparent phase separation can be observed when the PC content is higher than $16.7\\ \\mathrm{\\vol}\\ \\%$ (Figure 1a). When 1 M $\\mathrm{ZnSO}_{4},$ a common salt used in $Z\\mathrm{n}$ -based batteries was added to the above mixed solvent, this liquid phase separation phenomenon is exacerbated, and it also occurs in a lower PC content mixed solvent (i.e., $10\\ \\mathrm{vol}\\ \\%$ PC/water mixture). This result can be attributed to the salting-out effect as $\\mathrm{ZnSO_{4}}$ can be dissolved in water but not in $\\mathrm{PC}.^{^{23,34}}$ The added $\\mathrm{ZnSO_{4}}$ would attract water molecules, resulting in less water available for dissolving PC (note that due to the change in the density of the water after dissolving $\\mathrm{ZnSO}_{4},$ the positions of the water and PC have been exchanged in the vial). However, in sharp contrast, a salting-in effect can be observed when 1 $\\mathbf{M}\\mathrm{Zn}(\\mathrm{OTf})_{2}$ is added to the mixtures, where the originally less miscible mixtures become completely miscible, even when the PC content is as high as $90\\mathrm{\\vol\\}\\%$ . It should be noted that similar to $\\mathrm{ZnSO}_{4},$ $\\mathrm{Zn}(\\mathrm{OTf})_{2}$ is highly soluble in water but almost insoluble in PC (maximum concentration: $0.04\\mathrm{M},$ , Figure S1).35 The distinctly different results demonstrate the critical role of OTf−. To get a better understanding of this phenomenon, the minimum amount of salt required to form a miscible and stable solution was further determined in the mixed solvents by varying the PC content. As displayed in Table S1, the amount of $\\mathrm{Zn}(\\mathrm{OTf})_{2}$ shows a trend of first increasing and then decreasing along with the increase of the PC ratio. In addition, different salts were tested to verify the unique nature of OTf− (Figure S2). These results, we believe, can be interpreted based on the salting-in effect;34 unlike the hydrophilic inorganic $S O_{4}^{2-}$ anion, the OTf− anion consists of two parts, namely, the strongly hydrophobic ${\\mathrm{-CF}}_{3}$ group and the hydrophilic $-S0_{3}^{-}$ group.36 This unique chemical structure endows it with the capability to interact with both water and PC molecules. Therefore, the anion-coordinated PC (or water) as solute can be well dispersed in the water (or PC)-dominated solvent by forming the $\\left[\\mathrm{PC-OTf^{-}-H_{2}O}\\right]$ amphipathic complex (more discussion of the salt effect can be found in the Supporting Information). To prove the universality of such a salting-in effect, we further confirmed its feasibility in the hybrid solvent of water and various commonly used organic solvents (e.g., ethylene carbonate (EC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), and diethyl carbonate (DEC)). As shown in Figure 1b and Figure S3, similar to the PC/water system, with the gradual addition of $\\operatorname{Zn}(\\operatorname{OTf})_{2},$ the previously immiscible solvents become miscible. We also noticed that the minimum required salt amount varies, which is positively proportional to the size of solvent molecules (i.e., $\\mathrm{EC}\\ <\\ \\mathrm{DMC}\\ <\\ \\mathrm{EMC}\\ <$ DEC). This can be rationally related to the fact that long-chain molecules are more hydrophobic, thus making it more difficult for them to be dispersed in water.37 For the hybrid electrolytes involving PC and EC, the smaller amounts of salt for PC should be ascribed to the fact that the PC with higher polarity can be originally dissolved in polar water with a maximum concentration of $16.7~\\mathrm{vol}~\\%$ . \n\nSolvation Structure Investigations. To probe the solvation structure evolution of the hybrid electrolytes, Fourier-transform infrared spectroscopy (FTIR) was conducted. The assignment of the main characteristic peaks can be found in Figure S4 and Table S2. To rule out the influence of the salt concentration, all solutions used were $^\\mathrm{~1~M~}$ . As shown in Figure S5 and Figure 1c, the peak located at $1030~\\mathrm{{cm}^{-1}}$ and the slightly down-shifted peak can be assigned to the free OTf− anions in water and PC, respectively.38 The broad peak that ranges from 1040 to $1070~\\mathrm{\\bar{cm}^{-1}}$ could be ascribed to the partially and fully coordinated OTf− anions.38−40 It is evident that there is no peak in this region in the pure aqueous solution. By contrast, the broad peak gradually intensified and redshifted along with an increase of the PC content, which may have originated from the interactions between OTf anions and PC or $Z\\mathrm{n}^{2+}$ ions (e.g., $\\mathrm{Zn^{2+}{-}O T f^{-}}$ contact ion pairs and aggregate clusters). This indicates that the presence of PC can readily regulate the coordination environment of the OTf− anions. A similar tendency can also be observed for the vibrations of ${\\mathrm{-CF}}_{3}$ and $-S0_{3}^{-}$ (Figure 1c). For the pure PC solvent, the $\\scriptstyle{\\mathrm{C}}={\\mathrm{O}}$ vibration can be seen at $178\\bar{4}~\\mathrm{cm}^{-1}.$ , corresponding to the free PC solvent. However, in the hybrid solutions, a new peak appears at a lower wavelength and then intensifies when more PC is introduced, accompanied by peak redshift. This new peak indicates that partial PC molecules are coordinated with $\\bar{Z}\\mathrm{n}^{2+}$ ions upon the addition of $\\mathrm{Zn}(\\mathrm{OTf})_{2}$ .41 The $_\\mathrm{O-H}$ stretching bands of water were recorded in the region of $2800{-}3800~\\mathrm{cm^{-1}}$ . According to the Gaussian function, the $_\\mathrm{O-H}$ stretching band can be classified as three types of water molecules, namely, “network water $(\\mathrm{NW})^{\\mathfrak{n}}.$ , “intermediate water $(\\mathrm{IW})^{\\flat}.$ , and “multimer water (MW)”.42,43 Obviously, the weakly H-bonded NW can be readily interrupted upon the introduction of PC, as confirmed by the significantly reduced intensity. This is probably related to the $\\left[\\mathrm{PC-OTf^{-}-H_{2}O}\\right]$ species formed by the salting-in effect. Meanwhile, the IW peak experienced an obvious blueshift that should be attributed to the changes of the coordination structure of water molecules. \n\n![](images/e221025747db0824da878a63243d93c5bfadcf0da4b48764b8c8ef5ecadae87e.jpg) \nFigure 2. MD simulations of the ${\\mathrm{Zn}}^{2+}$ −solvation structures. A snapshot of the MD simulation cell and corresponding RDF plots for (a, b) 1 M $\\mathrm{Zn\\bar{(OTf)}}_{2}$ in water, (c, d) $50\\%$ PC-sat., and (e, f) $90\\%$ PC-sat. The insets in panels b, $\\mathrm{{\\_d}},$ and f are the corresponding representative solvation structure within a $0.3\\ \\mathrm{nm}$ scale. \n\nThe above results exemplify that the solvation structure can be adjusted through the addition of PC based on the salting-in effect. To further minimize the side reactions (e.g., hydrogen evolution on Zn anode), we therefore prepared various saturated electrolytes (denoted as $X\\%$ PC-sat., where X stands for the volumetric ratio of PC), which are used for the following investigations (the concentration and ionic conductivity can be found in Table S1 and Figure S6, respectively). The corresponding FTIR spectra are displayed in Figure S7. As expected, similar information with the 1 M electrolytes can be observed. Furthermore, very similar information can also be obtained from the Raman spectra (Figures S8 and S9). \n\nLiquid-state nuclear magnetic resonance (NMR) spectroscopy was performed to investigate the interplay among Zn2+, OTf−, water, and PC in the saturated electrolytes (Figure S10 and Figure 1d). As shown in Figure 1d, the $^{17}\\mathrm{O}$ (water) resonance experiences a downshift with a concomitant peak broadening upon the addition of PC. This result indicates the increased electronic density as a result of the weakening the Hbond network of water, which leads to a shielding effect.44,45 This result is also in good agreement with the FTIR analysis. In contrast, the $^{17}\\mathrm{O}$ resonance signals in OTf− and PC show upshift upon the addition of PC. This could be attributed to the greatly reduced water concentration, leading to an overall lower electronic density around the oxygen nuclei of OTf−. Importantly, compared to water, the $^{17}\\mathrm{O}$ resonance of pure PC appears at the higher chemical shift, suggesting a lower electronic density of $^{17}\\mathrm{O}$ nuclei in PC than that in water. It should be noted that the obvious shift of the $^{17}\\mathrm{O}$ signal can be observed in $\\scriptstyle{\\mathrm{C}}={\\mathrm{O}}$ (PC), while it hardly changes in $\\scriptstyle{\\mathrm{C-O}}$ (Figure S10). This strongly insinuates that the $\\bar{Z}\\mathrm{n}^{2+}$ ions are mostly coordinated with the oxygen nuclei of $\\scriptstyle{\\mathrm{C}}={\\mathrm{O}}$ (PC). In the $^{67}\\mathrm{Zn}$ NMR spectra, a slight upshift could be observed upon increasing the ratio of PC, indicating a decreased electronic density. This further verifies that PC starts replacing water and participating in the formation of the primary $Z\\mathrm{n}^{2+}$ solvation shell. More importantly, the remarkably broadened peaks reveal a significantly reduced $Z\\mathrm{n}^{2+}$ exchange rate during the acquisition time. This is indicative of an enhanced $\\mathrm{Zn^{2+}{-}\\tilde{O}T f^{-}}$ interaction, symbolizing that the OTf− anions have entered the primary solvation shell of $Z\\mathrm{n}^{2+}$ . \n\nMD Simulations. MD simulations were performed on the three electrolytes: 1 M $\\mathrm{Zn}(\\mathrm{OTf})_{2}$ aqueous solution and $50\\%$ PC-sat. and $90\\%$ PC-sat. electrolytes. As expected, in the pure aqueous electrolyte, $Z\\mathrm{n}^{2+}$ is anticipated to coordinate with six water molecules in the first solvation shell (see the scheme in Figure 2b) with negligible contribution from the OTf−. This could be attributed to the high dielectric constant of water, endowing it with the strong ability to separate the cation− anion pairs effectively. Such a coordination structure was further confirmed by the radial distribution function (RDF) result. As depicted in Figure 2b, only an intensive peak can be observed within the $\\mathrm{Zn}^{\\overline{{2}}+}$ primary solvation sheath $(0.3\\ \\mathrm{nm}$ from the $\\mathrm{Zn}^{2+}$ ), revealing a short distance between $Z\\mathrm{n}^{2+}$ and Ow (oxygen in water). Apparently, almost all OTf− anions are isolated by water and away from $Z\\mathrm{n}^{2+}$ . In contrast, a totally different solvation sheath can be observed upon introducing PC (Figure $\\mathrm{2d,f},$ . It is shown that both PC and OTf− are involved in the primary solvation shell of $Z\\mathrm{n}^{2+}$ . Specifically, according to the statistical results of the average coordination number, only two water molecules reside in the first solvation sheath of each $Z\\mathrm{n}^{2+}$ , wherein PC and OTf− dominate. Based on the aforementioned FTIR and NMR results, this can be explained by the weakened $\\mathrm{Zn}^{2+}{\\mathrm{-H}}_{2}\\mathrm{O}$ interaction in the presence of PC. Meanwhile, the strong interactions between $\\mathsf{\\bar{Z}n}^{2+}\\mathrm{-}\\mathsf{P C}$ and PC−OTf− enable their involvement within the primary solvation sheath. The solvated water molecules (around 0.5 per $Z\\mathrm{n}^{2+}$ on average) would be further replaced by PC or OTf− upon increasing the PC content to $90\\mathrm{vol}\\%$ . In return, more OTf− anions (around 3.5 per $Z\\mathrm{n}^{2+}$ on average) are coordinated with $Z\\mathrm{n}^{2+}$ , while a negligible change occurs in the average number of solvated PC. These results again prove that the presence of PC is favorable for the formation of $\\mathrm{Zn}^{2+}-$ OTf− contact ion pairs and aggregates. Figure S11 displays the RDF profiles of the OTf− anion for $50\\%$ PC-sat. and $90\\%$ PCsat. electrolytes. The results reveal that there are obvious interactions between ${\\mathrm{OTf}}^{-}{\\mathrm{-H}}_{2}{\\mathrm{O}}$ and ${\\mathrm{OTf}}^{-}{\\mathrm{-PC}}$ in the cosolvent electrolytes. The representative coordination structures of the OTf− anion (Figure S12) also indicate that the OTf− anions are surrounded by the $\\mathrm{H}_{2}\\mathrm{O}$ and PC molecules. In addition, the hydrogen-bond network $\\mathrm{'}\\mathrm{OTf}^{-}{\\mathrm{-}}\\mathrm{H}_{2}\\mathrm{O}$ and OTf−−PC) domains for the co-solvent electrolytes further confirm that the OTf− anions are hydrogen-bonded with the solvents (Figure S13). It should be noted that the salt concentrations of $50\\%$ PC-sat. and $90\\%$ PC-sat. are only 2.14 and $1.44~\\mathrm{M}_{\\sun}$ , respectively, which are much lower than those of common WIS electrolytes.22,46 In addition, the flammability test confirmed that the $50\\%$ PC-sat. electrolyte still inherits the high-safety merit of aqueous electrolytes (Figure S14 and Supporting Video). \n\n![](images/fea891585f7a9bc7d00d7b4384ee8d97b29661bc275d3bdaedc0d3221621f5a9.jpg) \nFigure 3. Electrochemical and morphological characterizations of the $Z\\mathrm{n}$ Anodes. (a) LSV curves of asymmetric $Z\\mathrm{n-Ti}$ cells in various electrolytes. (b) Tafel plots of zinc in various electrolytesworking electrode: zinc foil, counter electrode: graphite, and reference electrode: $\\mathrm{\\Ag/AgCl}$ (saturated KCl). $Z\\mathrm{n}$ plating/stripping CE of the $Z\\mathrm{n-Cu}$ half cells in various electrolytes with (c) $1\\mathrm{M}\\bar{\\mathrm{Zn}}(\\mathrm{OTf})_{2}$ and (d) saturated $\\mathrm{Zn}(\\mathrm{OTf})_{2}^{\\overline{{}}}$ . Areal capacity: $0.5\\mathrm{\\mAh\\cm^{-2}}$ ; current density: $1\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ . (e) Voltage profiles and charge/discharge curves of $Z\\mathrm{n-Cu}$ cells in $50\\%$ PC-sat. hybrid electrolyte. (f) Representative charge/discharge curves of $Z\\mathrm{n-Cu}$ cells at different rates. $\\mathbf{\\eta}(\\mathbf{g})$ Voltage profiles of symmetric $Z\\mathrm{n-Zn}$ cells. \n\nOn the basis of the above spectroscopic and theoretical modeling investigations, the advantages of the introduction of PC can be summarized as follows: (i) The amount of water was significantly decreased by half and replaced by PC, which is inert to $Z\\mathrm{n}$ . In this way, the (electro)chemical corrosion of the Zn metal can be prohibited to a certain degree (will be discussed later, Figure 3a,b); (ii) upon the introduction of PC in the hybrid electrolyte, H-bonded network water can be readily interrupted as confirmed by the significantly reduced IR intensity (Figure 1c). This should be related to the $\\left[\\mathrm{PC}-\\right.$ $\\mathrm{OTf^{-}{-}H_{2}O]}$ species formed by the salting-in effect. Therefore, the activity of water can be further suppressed; (iii) the $Z\\mathrm{n}$ solvation structure can be readily regulated upon the introduction of PC as confirmed by FTIR and MD simulations. The number of water molecules in the $Z\\mathrm{n}^{2+}$ primary solvation shell would be gradually replaced by the PC molecules and OTf− anions. Such a unique structure leads to the reduction of OTf− anions during discharge, thus leading to the formation of the protective interphase (will be discussed later) to prevent Zn metal from direct contact with water, which can prohibit the side reactions and promote the CE and cycling stability of the Zn anode.22,46,47 \n\nElectrochemical Characterization of the Zn Anodes. Linear sweep voltammetry (LSV) curves were first collected to confirm the stable voltage window of the electrolytes. As depicted in Figure 3a, the onset voltage of an oxygen evolution reaction can be extended from ${\\sim}1.8$ to $2.5\\mathrm{~V~}$ along with the increase of PC content. The anti-corrosion property of zinc metal in various electrolytes was also assessed by Tafel plots (Figure 3b). Generally, a higher corrosion voltage $\\left(E_{\\mathrm{corr}}\\right)$ and a lower corrosion current density $\\left(I_{\\mathrm{corr}}\\right)$ reflect better anticorrosion property.48 With the addition of PC, the $E_{\\mathrm{corr}}$ gradually increases, while the $I_{\\mathrm{corr}}$ significantly decreases (see the fitting results in Figure S15 and Table S3). The digital photographs (Figure S16) of the zinc foil after a corrosion test displays a heavily corroded surface in the aqueous electrolyte, while a smooth and clean surface can be maintained when using $50\\%$ PC-sat., which further demonstrates that zinc metal corrosion can be effectively inhibited in the hybrid electrolytes. The $\\mathrm{{Cu-Zn}}$ asymmetric cells were assembled to evaluate the zinc plating/striping reversibility. As shown in Figure 3c, Figure S17, and Table S4, a less reversible and unstable plating/striping behavior can be observed in the 1 M $\\mathrm{Zn}(\\mathrm{OTf})_{2}$ electrolyte with the low initial CE (ICE) and ACE of only 86.6 and $92.15\\%$ , respectively. Such a low and fluctuant CE should be attributed to the severe parasitic reactions and the dendrites. As anticipated, both ICE and ACE can be improved by introducing PC (the initial increase of CE should be attributed to the conditioning of the Cu foil surface and the formation of a stable SEI). Remarkably, a high CE of $99.8\\%$ can be obtained in $90\\%$ PC-1 M electrolyte. Notably, the ACE can be further enhanced in the saturated electrolytes (Figure 3d, Figure S18, and Table S5), which can eventually approach $99.93\\%$ (vs $99.66\\%$ in the $50\\%$ PC-1 M electrolyte) over 500 cycles in $50\\%$ PC-sat. The ICEs are lower than those in the $1\\mathbf{M}$ electrolytes, which could be related to the decreased ionic conductivity and increased viscosity. Although the performance improvement is limited, it is crucial for anodefree batteries as we mentioned above. We noticed that the CEs in the saturated electrolytes could hardly be improved (close to $100\\%$ ) when the PC content is over 50 vol $\\%$ , while an increased plating/stripping hysteresis (overpotential) was observed due to the compromised ionic conductivity. Therefore, $50\\%$ PC-sat. electrolyte was selected for the following experiments. The zinc plating/stripping CEs in hybrid $50\\%$ PC-sat. and aqueous $(1\\ \\mathrm{M})$ electrolytes were further assessed by a “zinc reservoir” protocol (see details in the Supporting Information).49 A high ACE of $99.73\\%$ can be obtained for the $50\\%$ PC-sat. electrolyte, while it is only $92.5\\%$ for $^{1\\mathrm{{M}}}$ aqueous electrolyte (Figure 3e and Figure S19). The different zinc surfaces after the plating/stripping test (Figure S20) further prove the advantage of the co-solvent electrolyte. The zinc plating/stripping CEs were further evaluated at various rates from 0.1 to $\\bar{5}\\mathrm{\\mA\\cm}^{-2}$ with a fixed plating time of $^\\textrm{\\scriptsize1h}$ . The low CEs (less than $90\\%$ ) can be obtained in the aqueous electrolyte when a rate of $5\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ was applied. Moreover, the severe side reactions and dendrites lead to battery failure only after nine cycles (Figure S21). Remarkably, high ACEs approaching $99\\%$ can be obtained even at a very low (or high) rate of 0.1 (or 5) mA $\\mathrm{cm}^{-2}$ (Figure 3f and Figure S22). The long-term zinc plating/stripping stability was tested using symmetric $Z\\mathrm{n-Zn}$ cells. The low CE and dendrites lead to a fast battery failure when 1 M $\\mathrm{Zn}(\\mathrm{OTf})_{2}$ electrolyte was employed, while stable performances of over $1600\\mathrm{~h~}$ ( $1.7\\%$ depth of discharge, DOD) and $^{100\\mathrm{~h~}}$ ( $68\\%$ DOD) plating/ stripping can be obtained in the hybrid electrolytes (Figure $3\\mathrm{g}$ and Figures S23 and S24). Moreover, even at a high current density of $10\\mathrm{\\mA\\cm^{-2}}$ , the battery can reversibly work for more than $400\\mathrm{~h~}$ (2000 cycles) in the $50\\%$ PC-sat. electrolyte, whereas it is less than $40\\mathrm{~h~}$ in the aqueous electrolyte (Figure S25). The excellent performance at such a high current density benefits from the suppressed dendrite formation as well as the moderate ionic conductivity. Noting that although there are $50\\%$ organic PC in the co-solvent electrolyte, the ionic conductivity $(\\sim16~\\mathrm{mS~cm^{-1})}$ is much higher than that of WIS electrolytes (e.g., $30\\ \\mathrm{m}\\ \\mathrm{ZnCl_{2}}<2.5\\ \\mathrm{mS\\cm^{-1}},$ ).50 That is to say, our hybrid electrolyte can induce comparable $Z\\mathrm{n}$ plating/ stripping efficiency to that of the WIS electrolytes, whereas it features a much lower salt concentration and higher ionic conductivity. It also should be noted that the cells mostly failed as a result of an open circuit instead of a short circuit in the 1 M $[\\mathrm{\\Zn(OTf)}_{2}$ electrolyte, indicating that the $\\mathrm{H}_{2}$ generation poses a much more serious threat to the battery failure rather than the dendrite issue. Accordingly, besides the typical dendrite issue of the $Z\\mathbf{n}$ metal anode, more attention should be paid to inhibit the parasitic reactions in the aqueous electrolytes toward safe and stable zinc-based batteries. \n\n![](images/18d83c632688ab3e06c9caa752e86be67cf518b52518867ce1ec7e57eebdfd50.jpg) \nFigure 4. Morphological evolution of the $Z\\mathrm{n}$ anodes. SEM images of deposited $Z\\mathrm{n}$ in the $\\begin{array}{r}{{1}\\mathrm{{MZn}({O T f})_{2}}}\\end{array}$ wo/PC and $50\\%$ PC-sat. electrolytes. (a) First plating, $(\\boldsymbol{\\mathrm{b}},\\boldsymbol{\\mathrm{c}})$ $100\\mathrm{{th}}$ stripping in 1 M $\\cdot\\operatorname{Zn}(\\mathrm{OTf})_{2}$ wo/ PC electrolyte, (d) first plating, and $(\\mathbf{e},\\mathbf{f})$ 100th stripping in $50\\%\\mathrm{PC}$ -sat. electrolyte. The water contact angle of $(\\mathbf{g})$ the pristine $Z\\mathrm{n}$ and after plating in (h) aqueous 1 $\\mathrm{{MZn}(O T f)}_{2}^{\\cdot}$ electrolyte and (i) $50\\%$ PC-sat. electrolyte. Inset in panel (d) shows the plated “zinc paper” obtained in the $50\\%$ PC-sat. electrolyte. \n\nMorphological Evolution. The morphological evolution of the zinc anodes was further investigated by scanning electron microscopy (SEM, Figure $4\\mathrm{a-f}$ and Figure S26). Obviously, a rough surface with plenty of vertically distributed flakes (see more details in the Supporting Information, Figures S27 and S28) can be observed when the aqueous electrolyte is employed. Upon zinc stripping at the 100th cycle, a thick layer of “dead zinc” $(\\sim9.5~\\mu\\mathrm{m})$ with a loosened, stacked structure can be found. In sharp contrast, a compact and uniform surface can be observed using the $50\\%$ PC-sat. electrolyte. Noticeably, the plated zinc can be easily peeled off, while the underneath $Z\\mathrm{n}$ foil still maintains its smooth and shining nature (inset in Figure 4d). After 100 cycles, almost all the deposited zinc can be stripped away, and a clean and smooth surface can be maintained, confirming the excellent plating/stripping reversibility and high CE. The results here demonstrate that a dendrite-suppressed plating morphology can be achieved in the co-solvent electrolyte, which should be benefited from the unique solvation structure. This is also consistent with the electrochemical results. \n\nSolid Electrolyte Interphase Analysis. From a classical viewpoint, an SEI plays a significant role in contributing to the stability of the organic lithium-ion batteries.51−53 Recently, the SEI on the zinc anode also was demonstrated to be critical in aqueous zinc-based batteries.25,26,54 In this regard, we further evaluated the role of the SEI in aqueous and hybrid electrolytes. Cyclic voltammetry (CV) plots display apparent different behaviors for the two electrolytes. In the aqueous electrolyte, although the cutoff potential was set to $-0.2\\mathrm{~V~}$ vs $\\mathrm{Zn}/\\mathrm{Zn}^{\\dot{2}+}$ to intentionally prohibit the hydrogen evolution reaction (Figure S29a), it still resulted in fast battery failure after 20 cycles (Figure S29b). In contrast, in the $50\\%$ PC-sat. electrolyte (Figure S30), no obvious HER occurs even with sweeping to $-0.6\\:\\mathrm{V}$ . In the cathodic scan, two reduction peaks, $\\mathbf{C}_{1}$ and $\\mathrm{C}_{2},$ are responsible for the $Z\\mathbf{n}$ deposition. The potential differences might be related to the dynamics of the interfacial layers, as two different solvents are presented in the electrolyte. This has also been observed in previous studies.55 Note that the current crossover loop in the first cycle is indicative of the nucleation process.55−58 In addition, an obvious reduction peak $\\mathbf{C}_{3}$ is also seen in the backward scan, which is attributed to further $Z\\mathrm{n}$ deposition in the presence of the passivation layer (originated from the reduction of anion21,46,55). The $Z\\mathbf{n}$ deposition of peak $\\mathbf{C}_{3}$ is also confirmed by the ex situ XRD result (Figure S31). In general, a reversible Zn plating/ stripping process can be observed, while the strongest intensity of deposited $Z\\mathrm{n}$ occurs at $-0.14\\mathrm{V}$ (anodic scan, point D) but not $-0.6\\mathrm{~V~}$ (cathodic scan, point C), suggesting $Z\\mathrm{n}$ can be further deposited during the anodic scan from $-0.6$ to $0\\mathrm{~V~}$ (Figure S31). In the anodic scan, the broad asymmetric peak, which could be fitted into multiple oxidation peaks, is responsible for the dissolution of $Z\\mathrm{n}$ . Another indication of the formation of a passivation layer is the fact that the relatively sharp and symmetric peak $\\mathbf{C}_{1}$ becomes much broader (and can be fitted into at least two peaks) in the subsequent cycles (Figure $S30\\mathrm{b-d})$ . This could be because the passivation layer leads to the dynamics difference, resulting in the splitting of the reduction peak and potential differences. The reduction of the anions is likely to form a robust SEI that can prevent the further decomposition of the electrolyte. X-ray photoelectron spectroscopy (XPS) results also demonstrate the formation of $\\mathrm{ZnCO}_{3}$ and $\\mathrm{ZnF}_{2},$ which could be responsible for the anion reduction (Figure S32).47 Furthermore, the contact angle of the $Z\\mathrm{n}$ anode was performed to investigate the hydrophilicity. As shown in Figure $4\\mathrm{g-i,}$ the decreased contact angle indicates that the $Z\\mathbf{n}$ surface becomes more hydrophilic after the plating process in the $\\begin{array}{r}{\\mathrm{~1~M~Zn(OTf)_{2}~}}\\end{array}$ electrolyte. This is owing to the rough and porous $Z\\mathrm{n}$ plating layer. The more hydrophilic surface could boost the wettability of the $Z\\mathrm{n}$ anode; however, it also facilitates the side reactions. In contrast, a much more hydrophobic surface can be obtained in the $50\\%$ PC-sat. electrolyte as suggested by the large contact angle (i.e., $127.3^{\\circ})$ . Such a hydrophobic surface is critical to induce a localized water-poor environment in the inner Helmholtz layer,36 which can effectively prohibit the interaction between the active $Z\\mathbf{n}$ and water. The hydrophobicity of the $Z\\mathrm{n}$ surface could be ascribed to two reasons: (i) hydrophobic SEI components result from the decomposition of anions from the $Z\\mathrm{n}^{2+}$ solvation sheath and (ii) the dense morphology of $Z\\mathrm{n}$ deposits (Figure 4).59 The contribution of the latter case should be minor as the pristine smooth and shining $Z\\mathbf{n}$ metal only shows a contact angle of $87.7^{\\circ}$ . Electrochemical impedance spectroscopy (EIS) was also carried out to monitor the interfacial impedance (Figure S33). In the $50\\%$ PC-sat. electrolyte, the impedance is significantly decreased after the first cycle. The impedance continues to reduce and then stabilize after 50 cycles. Although a similar trend can also be found in the aqueous electrolyte, the distinct shapes of the EIS curves suggest the different properties of the interphase. Moreover, the battery was quickly dead after only 70 cycles in the aqueous electrolyte, indicating that serious side reactions occurred. The results here confirm the important role of the engineered electrolyte in forming a stable SEI that can efficiently enable uniform Zn plating and prohibit side reactions.25,26 \n\nFull Cells and Anode-Free Design. Better anti-corrosion characteristics and significantly reduced side reactions using the hybrid electrolyte result in dendrite-suppressed and highefficiency Zn anodes. However, this does not necessarily guarantee high-performance full cells. Actually, in the aqueous electrolytes, many cathode materials suffer from electrode dissolution either by chemical or electrochemical means (e.g., $\\mathrm{MnO}_{2}$ and ${\\mathrm{V}}_{2}{\\mathrm{O}}_{5},$ ).3,60,61 As demonstrated by Dahn et al.,62,63 the most stringent proof of stability is not necessarily manifested by the number of cycles but rather by the time the system spends at the fully charged state and from the high \n\n![](images/5e57d8d1c2b2bc35cab7e8ad903e12a414ae7a9abb285708c9250f927c7bb678.jpg) \nFigure 5. Anode-free $\\mathrm{Cu-ZnMn_{2}O_{4}}$ batteries. (a) Schematic illustration of the conventional $Z\\mathbf{n}$ -based battery and anode-free Zn metal battery configurations; cycling performance of (b) conventional $\\mathrm{Zn{-}Z n M n_{2}O_{4}}$ batteries and (c) anode-free $\\mathrm{Cu-ZnMn_{2}O_{4}}$ batteries in different electrolytes with a current density of $0.5\\mathrm{\\mA}\\mathrm{cm}^{-2}$ $(\\sim350\\mathrm{mAg^{-1}})$ ); (d) selected charge/discharge curves of the anode-free $\\mathrm{Cu-ZnMn_{2}O_{4}}$ battery in $50\\%$ PC-sat. electrolyte. \n\nCE at low rates. However, many previous studies evaluated the stability of aqueous zinc-based batteries at very high rates, so the effect of the side reactions on the cycling performance is significantly mitigated. In light of this, we studied the compatibility of the hybrid electrolyte with different cathodes at a low rate of $50\\ \\mathrm{mA}\\ \\mathrm{g}^{-1}$ . As shown in Figures S34 and S35, the specific capacity of the $\\mathrm{ZnHCF}$ cathode degrades rapidly by $50\\%$ within 100 cycles. In addition, the ACE is only around $90\\%$ and the battery experiences a sharp capacity decrease followed by the final failure. Such an inferior performance can be ascribed to the undesired side reactions and dendrites on the anode side and the instability of the cathode in the aqueous environment. On the contrary, an unprecedented cycling performance is seen in the $50\\%$ PC-sat. electrolyte, with negligible capacity decay and a high ACE of ${\\sim}98\\%$ over 700 cycles. Further, the $\\mathrm{ZnHCF}$ cathode also exhibited higher CEs (especially at low rates) in the $50\\%$ PC-sat. electrolyte. The importance and necessity of the proper PC content and the salt concentration were also carefully studied (Figures S36 and S37). Additionally, the compatibility of the hybrid electrolyte with other cathodes (i.e., CuHCF and $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}.$ ) was also confirmed (Figures S38−40 and Figure $5\\mathbf{b}$ ). \n\nGiven the wide liquid temperature range of PC, we further evaluated the high- and low-temperature performance of the co-solvent electrolyte. Differential scanning calorimetry (DSC) profiles confirm that all co-solvent electrolytes are stable from $-90$ to $100^{\\circ}\\mathrm{C}$ (Figure S41). The electrochemical performance of the commercial PANI cathode was then evaluated under different temperatures (i.e., $-20,\\ 0,\\ 25$ , and $50~^{\\circ}\\mathrm{C}\\ '$ ), and the results are shown in Figure S42. It can be seen that the specific capacity and rate capability gradually decrease along with decreasing temperature. For example, 77, 65, and $59\\%$ capacity values can be retained when the rate elevated from 100 to 1000 mA $\\mathbf{g}^{-1}$ (1 C rate $=110\\mathrm{\\mA\\g^{-1}}$ at $50~^{\\circ}\\mathrm{C}\\ '$ ) at 50, 0, and $-20$ ${}^{\\circ}\\mathrm{C},$ respectively. Nevertheless, all the batteries at various temperatures exhibit good stability at 200 and $1000\\ \\mathrm{mA}\\ \\mathrm{g}^{-1}$ . SEM images (Figure S42) also suggest that there is no obvious morphological change of the PANI electrode after cycling. These results validate the fact that the as-prepared co-solvent electrolyte can work well at high and low temperatures. The aforementioned discussions further verify the versatility of our engineered hybrid electrolyte. \n\nAs depicted in Figure 5a, conventional zinc-based batteries usually use thick zinc metal foil $\\left(50-200~\\mu\\mathrm{m}\\right)$ . The massive use of zinc anodes ( ${\\sim}30{-}120$ times excessive) not only results in serious material waste but also significantly compromises the energy density at the cell level. As is well known, aqueous rechargeable batteries feature insufficient energy density, which is typically related to their low operation voltages. However, from the technical point of view, there is still huge room to enhance the cell energy density through optimizing cell design principles, which include key factors like mass loading of a cathode and thickness of a zinc anode. Given that our hybrid electrolyte can readily achieve both high-performance zinc anodes ${\\mathrm{'ACE}}=99.93\\%$ ) and stable cathodes, the configuration of anode-free zinc batteries represents a promising technique to improve the energy density. For the anode-free battery design, the excess utilization of zinc can be avoided, signifying an important step toward aqueous rechargeable batteries with greatly improved energy density. \n\nIn AFZMBs, the cathode performs as the sole source of $Z\\mathrm{n}^{2+}$ during cycling. Accordingly, $Z\\mathrm{n}$ -rich $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ cathode was chosen to avoid the complicated and time-consuming prezincification process. $^{10,11,13,17,64}$ As shown in Figure 5b, the standard $\\mathrm{Zn{-}Z n M n_{2}O_{4}}$ battery ( $100\\ \\mu\\mathrm{{m}}$ -thick $Z\\mathbf{n}$ anode, $>60$ times excess) demonstrates good cycling stability, which can maintain $80\\%$ of the initial capacity for over 300 cycles in the $50\\%$ PC-sat. electrolyte, whilst only $35\\%$ of the initial capacity can be maintained in the aqueous electrolyte. For the anodefree battery, a slightly inferior performance can be obtained in $50\\%$ PC-sat. electrolyte, which can maintain $80\\%$ original capacity for 275 cycles (Figures 5c,d and S43). This is far superior to the one obtained in the conventional aqueous electrolyte and previously reported $\\mathrm{C}/\\mathrm{Cu}–\\mathrm{MnO}_{2}$ AFZMBs 1 $80\\%$ retention after 35 cycles, $68.2\\%$ after 80 cycles, Table S8).17 The fast capacity decay after 200 cycles should be attributed to the limited zinc supplement (zero excess zinc). Post-characterizations of the $\\mathtt{C u}$ foil, $Z\\mathrm{n}$ anode and $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ cathode are shown in Figures S44 and S45. there is no obvious change or impurity phases can be observed in the XRD pattern of $\\mathrm{ZnMn}_{2}\\mathrm{O}_{4}$ cathode after cycling. The SEM images of the $\\mathtt{C u}$ foil/Zn foil reveal that there are some “dead $Z\\mathrm{n}^{\\prime\\prime}$ after cycling, which is one of the reasons causing the capacity fading. As shown in Figure S46, the anode-free configuration can effectively promote the energy density of the device. The successful demonstration of AFZMBs verifies the advantage of the as-designed hybrid electrolyte again. \n\n# CONCLUSIONS \n\nIn summary, we have designed a hybrid electrolyte based on the salting-in effect, in which the hybrid electrolyte consisting of propylene carbonate and water has been shown as a proof of concept. Our hybrid electrolyte can effectively regulate the $Z\\mathrm{n}^{2+}$ solvation structure, as confirmed by various spectroscopic studies and theoretical simulations. The optimized hybrid electrolyte possesses a favorable $Z\\mathrm{n}^{2+}$ solvation sheath, which is critical for the formation of a waterproof solid electrolyte interphase. The hydrophobic interphase combined with the significantly reduced amount of free water can effectively suppress the parasitic reactions. Benefiting from these advantages, the as-designed hybrid electrolyte could enable highly reversible $Z\\mathbf{n}$ anodes, much improved cyclability of the cathodes, as well as good high- and low-temperature performance. Finally, an efficient anode-free Zn-based battery has been demonstrated with excellent cycling stability. More importantly, this strategy can also be applied to other organic/ water hybrid systems. This work demonstrates an alternative strategy to design efficient electrolytes for zinc metal batteries. A step further of engineering hybrid electrolytes can potentially enable other metal batteries with improved trade-off between energy density and cycling stability. \n\n# ASSOCIATED CONTENT \n\n# $\\bullet$ Supporting Information \n\nThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jacs.1c12764. \n\nFlammability test of different electrolytes (MP4) Experimental details, additional characterizations (XRD, SEM, XPS, etc.), additional electrochemical tests, and supplementary tables and notes (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\nYi Cui − Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States; SLAC National Accelerator Laboratory, Stanford Institute for Materials and Energy Sciences, Menlo Park, California 94025, United States; $\\circledcirc$ orcid.org/0000-0002- 6103-6352; Email: yicui@stanford.edu Husam N. Alshareef − Materials Science and Engineering, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia; $\\circledcirc$ orcid.org/0000-0001-5029- 2142; Email: husam.alshareef@kaust.edu.sa \n\n# Authors \n\nFangwang Ming − Materials Science and Engineering, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia; $\\circledcirc$ orcid.org/0000-0003-4574-9720 \nYunpei Zhu − Materials Science and Engineering, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia \nGang Huang − Materials Science and Engineering, Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia \nAbdul-Hamid Emwas − Advanced Nanofabrication Imaging and Characterization Center, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia \nHanfeng Liang − Department of Chemical and Biochemical Engineering, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China; $\\circledcirc$ orcid.org/ 0000-0002-1778-3975 \n\nComplete contact information is available at: https://pubs.acs.org/10.1021/jacs.1c12764 \n\n# Author Contributions \n\n#F.M. and Y.Z. contributed equally. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nResearch reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST). Authors appreciate Dr. Jian Yin, Dr. Zhiming Zhao, and Yongjiu Lei for their kind help and insightful discussion. Authors also thank the Advanced Nanofabrication, Imaging, and Characterization Laboratory at KAUST for their excellent support. \n\n# REFERENCES \n\n(1) Konarov, A.; Voronina, N.; Jo, J. H.; Bakenov, Z.; Sun, Y.-K.; Myung, S.-T. Present and Future Perspective on Electrode Materials \n\n2640. \n(2) Fang, G.; Zhou, J.; Pan, A.; Liang, S. Recent Advances in Aqueous Zinc-Ion Batteries. ACS Energy Lett. 2018, 3, 2480−2501. (3) Ming, J.; Guo, J.; Xia, C.; Wang, W.; Alshareef, H. N. Zinc-Ion Batteries: Materials, Mechanisms, and Applications. Mater. Sci. Eng., R 2019, 135, 58−84. \n(4) Ming, F.; Liang, H.; Lei, Y.; Kandambeth, S.; Eddaoudi, M.; Alshareef, H. N. Layered $\\mathbf{Mg}_{x}\\mathbf{V}_{2}\\mathbf{O}_{5}{\\cdot}n\\mathbf{H}_{2}\\mathbf{O}$ as Cathode Material for High-Performance Aqueous Zinc Ion Batteries. ACS Energy Lett. 2018, 3, 2602−2609. \n(5) Cao, Z.; Zhuang, P.; Zhang, X.; Ye, M.; Shen, J.; Ajayan, P. M. Strategies for Dendrite-Free Anode in Aqueous Rechargeable Zinc Ion Batteries. Adv. Energy Mater. 2020, 10, 2001599. \n(6) Zhang, $\\mathrm{Q.;}$ Luan, J.; Tang, Y.; Ji, X.; Wang, H. Interfacial Design of Dendrite-Free Zinc Anodes for Aqueous Zinc-Ion Batteries. Angew. Chem., Int. Ed. 2020, 59, 13180−13191. \n(7) Liang, H.; Cao, Z.; Ming, F.; Zhang, W.; Anjum, D. H.; Cui, Y.; Cavallo, L.; Alshareef, H. N. Aqueous Zinc-Ion Storage in $\\mathbf{MoS}_{2}$ by Tuning the Intercalation Energy. Nano Lett. 2019, 19, 3199−3206. (8) Parker, J. F.; Chervin, C. N.; Pala, I. R.; Machler, M.; Burz, M. F.; Long, J. W.; Rolison, D. R. Rechargeable Nickel-3D Zinc Batteries: An Energy-Dense, Safer Alternative to Lithium-Ion. Science 2017, 356, 415−418. \n(9) Parker, J. F.; Chervin, C. N.; Nelson, E. S.; Rolison, D. R.; Long, J. W. Wiring Zinc in Three Dimensions Re-writes Battery Performance-Dendrite-Free Cycling. Energy Environ. Sci. 2014, 7, 1117−1124. (10) Cohn, A. P.; Muralidharan, N.; Carter, R.; Share, K.; Pint, C. L. Anode-Free Sodium Battery Through In Situ Plating of Sodium Metal. Nano Lett. 2017, 17, 1296−1301. \n(11) Qian, J.; Adams, B. D.; Zheng, J.; Xu, W.; Henderson, W. A.; Wang, J.; Bowden, M. E.; Xu, S.; Hu, J.; Zhang, J. G. Anode-Free Rechargeable Lithium Metal Batteries. Adv. Funct. Mater. 2016, 26, 7094−7102. \n(12) Zhang, J.-G. Anode-Less. Nat. Energy 2019, 4, 637−638. (13) Louli, A.; Eldesoky, A.; Weber, R.; Genovese, M.; Coon, M.; de Gooyer, J.; Deng, Z.; White, R. T.; Lee, J.; Rodgers, T. In The Life and Death of Anode-Free Lithium Metal Cells, ECS Meeting Abstracts; IOP Publishing, 2020, p 32. \n(14) Nanda, S.; Gupta, A.; Manthiram, A. Anode-Free Full Cells: A Pathway to High-Energy Density Lithium-Metal Batteries. Adv. Energy Mater. 2020, 11, 2000804. \n(15) Louli, A.; Eldesoky, A.; Weber, R.; Genovese, M.; Coon, M.; de Gooyer, J.; Deng, Z.; White, R. T.; Lee, J.; Rodgers, T.; Petibon, R.; Hy, S.; Cheng, S. J. H.; Dahn, J. R. Diagnosing and Correcting AnodeFree Cell Failure via Electrolyte and Morphological Analysis. Nat. Energy 2020, 5, 693−702. \n(16) Tian, Y.; An, Y.; Wei, C.; Jiang, H.; Xiong, S.; Feng, J.; Qian, Y. Recently Advances and Perspectives of Anode-Free Rechargeable Batteries. Nano Energy 2020, 78, No. 105344. \n(17) Zhu, Y.; Cui, Y.; Alshareef, H. N. An Anode-Free $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ Battery. Nano Lett. 2021, 21, 1446−1453. \n(18) Li, C.; Zhang, X.; He, W.; Xu, G.; Sun, R. Cathode Materials for Rechargeable Zinc-Ion Batteries: From Synthesis to Mechanism and Applications. J. Power Sources 2020, 449, No. 227596. \n(19) Wan, F.; Niu, Z. Design Strategies for Vanadium-Based Aqueous Zinc-Ion Batteries. Angew. Chem., Int. Ed. 2019, 58, 16358− 16367. \n(20) Zheng, J.; Zhao, $\\mathrm{Q.;}$ Tang, T.; Yin, J.; Quilty, C. D.; Renderos, G. D.; Liu, X.; Deng, Y.; Wang, L.; Bock, D. C.; Jaye, C.; Zhang, D.; Takeuchi, E. S.; Takeuchi, K. J.; Marschilok, A. C.; Archer, L. A. Reversible Epitaxial Electrodeposition of Metals in Battery Anodes. Science 2019, 366, 645−648. \n(21) Wang, F.; Borodin, O.; Gao, T.; Fan, X.; Sun, W.; Han, F.; Faraone, A.; Dura, J. A.; Xu, K.; Wang, C. Highly Reversible Zinc Metal Anode for Aqueous Batteries. Nat. Mater. 2018, 17, 543−549. (22) Wu, X.; Xu, Y.; Zhang, C.; Leonard, D. P.; Markir, A.; Lu, J.; Ji, X. Reverse Dual-Ion Battery via a $\\mathrm{ZnCl}_{2}$ Water-in-Salt Electrolyte. J. Am. Chem. Soc. 2019, 141, 6338−6344. (23) Hao, J.; Yuan, L.; Ye, C.; Chao, D.; Davey, K.; Guo, Z.; Qiao, S.-Z. Boosting Zn Electrode Reversibility in Aqueous Electrolyte Using Low-Cost Antisolvents. Angew. Chem., Int. Ed. , 60 (), 7366− 7375, DOI: 10.1002/anie.202016531. \n(24) Cao, L.; Li, D.; Hu, E.; Xu, J.; Deng, T.; Ma, L.; Wang, Y.; Yang, $\\mathrm{X.-Q.};$ Wang, C. Solvation Structure Design for Aqueous Zn Metal Batteries. J. Am. Chem. Soc. 2020, 142, 21404−21409. \n(25) Li, D.; Cao, L.; Deng, T.; Liu, S.; Wang, C. Design of a Solid Electrolyte Interphase for Aqueous Zn Batteries. Angew. Chem., Int. Ed. 2021, 60, 13035. \n(26) Zeng, X.; Mao, J.; Hao, J.; Liu, J.; Liu, S.; Wang, Z.; Wang, Y.; Zhang, S.; Zheng, T.; Liu, J.; Rao, P.; Guo, Z. Electrolyte Design for In Situ Construction of Highly $Z\\mathrm{n}^{2+}$ -Conductive Solid Electrolyte Interphase to Enable High-Performance Aqueous Zn-Ion Batteries under Practical Conditions. Adv. Mater. 2021, 33, 2007416. \n(27) Naveed, A.; Yang, H.; Yang, J.; Nuli, Y.; Wang, J. Highly Reversible and Rechargeable Safe Zn Batteries Based on a Triethyl Phosphate Electrolyte. Angew. Chem., Int. Ed. 2019, 58, 2760−2764. (28) Cao, L.; Li, D.; Pollard, T.; Deng, T.; Zhang, B.; Yang, C.; Chen, L.; Vatamanu, J.; Hu, E.; Hourwitz, M. J.; Ma, L.; Ding, M.; Li, $\\mathrm{Q.;}$ Hou, S.; Gaskell, K.; Fourkas, J. T.; Yang, X. Q.; Xu, K.; Borodin, O.; Wang, C. Fluorinated Interphase Enables Reversible Aqueous Zinc Battery Chemistries. Nat. Nanotechnol. 2021, 16, 902−910. (29) Huang, J.-Q.; Guo, X.; Lin, X.; Zhu, Y.; Zhang, B. Hybrid Aqueous/Organic Electrolytes Enable the High-Performance Zn-Ion Batteries. Research 2019, 2019, 2635310. \n(30) Chang, N.; Li, T.; Li, R.; Wang, S.; Yin, Y.; Zhang, H.; Li, X. An Aqueous Hybrid Electrolyte for Low-Temperature Zinc-Based Energy Storage Devices. Energy Environ. Sci. 2020, 13, 3527−3535. \n(31) Han, $\\mathrm{D.}\\mathrm{,}$ Cui, C.; Zhang, K.; Wang, Z.; Gao, J.; Guo, Y.; Zhang, Z.; Wu, S.; Yin, L.; Weng, Z.; Kang, F.; Yang, $\\scriptstyle{\\mathrm{\\mathrm{Q}}}.$ H. A NonFlammable Hydrous Organic Electrolyte for Sustainable Zinc Batteries. Nat. Sustainability 2022, 5, 205−213. \n(32) Xing, L.; Zheng, X.; Schroeder, M.; Alvarado, J.; von Wald Cresce, A.; Xu, K.; Li, $\\mathrm{\\Q.;}$ Li, W. Deciphering the Ethylene Carbonate−Propylene Carbonate Mystery in Li-Ion Batteries. Acc. Chem. Res. 2018, 51, 282−289. \n(33) Peruzzi, N.; Nostro, P. L.; Ninham, B. W.; Baglioni, P. The Solvation of Anions in Propylene Carbonate. J. Solution Chem. 2015, 44, 1224−1239. \n(34) Ebrahimi, N.; Farahbod, B.; Sadeghi, R. Salting-in and Saltingout Effects of Organic and Inorganic Ammonium Salts on the Aqueous Polymer Solutions. J. Chem. Thermodyn. 2018, 123, 86−98. (35) Ye, H.; Xu, J. J. Zinc Ion Conducting Polymer Electrolytes Based on Oligomeric Polyether/PVDF-HFP Blends. J. Power Sources 2007, 165, 500−508. \n(36) Sun, W.; Wang, F.; Zhang, B.; Zhang, M.; Küpers, V.; Ji, X.; Theile, C.; Bieker, P.; Xu, K.; Wang, C.; Winter, M. A Rechargeable Zinc-Air Battery Based on Zinc Peroxide Chemistry. Science 2021, 371, 46−51. \n(37) Narbutt, J. Fundamentals of Solvent Extraction of Metal Ions. In Liquid-Phase Extraction; Elsevier, 2020, pp. 121−155. \n(38) Alía, J.; Díaz, Y.; Edwards, H.; García, F.; Lawson, E. Infrared Spectroscopic Study of Ionic Association of Lithium Trifluoromethanesulfonate in Several Solvents. J. Mol. Struct. 1997, 408, 439−450. (39) Bernson, A.; Lindgren, J. Free Ions and Ion Pairing/Clustering in the System $\\mathrm{LiCF}_{3}\\mathrm{SO}_{3^{-}}\\mathrm{PPO}_{\\mathrm{n}}$ . Solid State Ionics 1993, 60, 37−41. (40) Wendsjö, Å.; Thomas, J. O.; Lindgren, J. Infra-Red and X-Ray Diffraction Study of The Hydration Process in the Polymer Electrolyte System $\\mathrm{M(CF_{3}S O_{3})_{2}P E O_{n}}$ for $\\mathbf{M}=$ Pb. Zn and Ni. Polymer 1993, 34, 2243−2249. \n(41) Wang, F.; Borodin, O.; Ding, M. S.; Gobet, M.; Vatamanu, J.; Fan, X.; Gao, T.; Eidson, N.; Liang, Y.; Sun, W.; Greenbaum, S.; Xu, K.; Wang, C. Hybrid aqueous/non-aqueous electrolyte for safe and high-energy Li-ion batteries. Joule 2018, 2, 927−937. \n(42) Brubach, J.-B.; Mermet, A.; Filabozzi, A.; Gerschel, A.; Lairez, D.; Krafft, M.; Roy, P. Dependence of Water Dynamics upon D200 Signatures of the Hydrogen Bonding in the Infrared Bands of Water. J. Chem. Phys. 2005, 122, 184509. \n(44) Becker, M.; Rentsch, D.; Reber, D.; Aribia, A.; Battaglia, C.; Kühnel, R.-S. The Hydrotropic Effect of Ionic Liquids in Water-inSalt Electrolytes. Angew. Chem., Int. Ed. 2021, 60, 14100−14108. (45) Jiang, L.; Liu, L.; Yue, J.; Zhang, $\\mathrm{Q.;}$ Zhou, A.; Borodin, O.; Suo, L.; Li, H.; Chen, L.; Xu, K.; Hu, Y. S. High-Voltage Aqueous NaIon Battery Enabled by Inert-Cation-Assisted Water-in-Salt Electrolyte. Adv. Mater. 2020, 32, 1904427. \n(46) Suo, L.; Borodin, O.; Gao, T.; Olguin, M.; Ho, J.; Fan, X.; Luo, C.; Wang, C.; Xu, K. “Water-in-Salt” Electrolyte Enables High-Voltage Aqueous Lithium-Ion Chemistries. Science 2015, 350, 938−943. (47) Dong, Y.; Miao, L.; Ma, G.; Di, S.; Wang, Y.; Wang, L.; Xu, J.; Zhang, N. Non-concentrated Aqueous Electrolytes with Organic Solvent Additives for Stable Zinc Batteries. Chem. Sci. 2021, 12, 5843−5852. \n(48) Ma, L.; Chen, S.; Li, N.; Liu, Z.; Tang, Z.; Zapien, J. A.; Chen, S.; Fan, J.; Zhi, C. Hydrogen-Free and Dendrite-Free All-Solid-State Zn-Ion Batteries. Adv. Mater. 2020, 32, 1908121. \n(49) Ma, L.; Schroeder, M. A.; Borodin, O.; Pollard, T. P.; Ding, M. S.; Wang, C.; Xu, K. Realizing High Zinc Reversibility in Rechargeable Batteries. Nat. Energy 2020, 5, 743−749. \n(50) Zhang, C.; Holoubek, J.; Wu, X.; Daniyar, A.; Zhu, L.; Chen, C.; Leonard, D. P.; Rodríguez-Pérez, I. A.; Jiang, J.-X.; Fang, C.; Ji, X. A $\\mathrm{ZnCl}_{2}$ Water-in-Salt Electrolyte for a Reversible Zn Metal Anode. Chem. Commun. 2018, 54, 14097−14099. \n(51) Zhou, Y.; Su, M.; Yu, X.; Zhang, Y.; Wang, J. G.; Ren, X.; Cao, R.; Xu, W.; Baer, D. R.; Du, Y.; Borodin, O.; Wang, Y.; Wang, X. L.; Xu, K.; Xu, Z.; Wang, C.; Zhu, Z. Real-Time Mass Spectrometric Characterization of the Solid-Electrolyte Interphase of a Lithium-Ion Battery. Nat. Nanotechnol. 2020, 15, 224−230. \n(52) Shi, F.; Pei, A.; Boyle, D. T.; Xie, J.; Yu, X.; Zhang, X.; Cui, Y. Lithium Metal Stripping Beneath the Solid Electrolyte Interphase. Proc. Natl. Acad. Sci. U. S. A. 2018, 115, 8529−8534. \n(53) Li, N. W.; Shi, Y.; Yin, Y. X.; Zeng, X. X.; Li, J. Y.; Li, C. J.; Wan, L. J.; Wen, R.; Guo, Y. G. A Flexible Solid Electrolyte Interphase Layer for Long-Life Lithium Metal Anodes. Angew. Chem., Int. Ed. 2018, 57, 1505−1509. \n(54) Cai, Z.; Ou, Y.; Zhang, B.; Wang, J.; Fu, L.; Wan, M.; Li, G.; Wang, W.; Wang, L.; Jiang, J.; Seh, Z. W.; Hu, E.; Yang, X. $\\mathrm{Q.;}$ Cui, Y.; Sun, Y. A Replacement Reaction Enabled Interdigitated Metal/Solid Electrolyte Architecture for Battery Cycling at $20\\mathrm{\\mA\\cm}^{-2}$ and 20 mAh $\\mathsf{c m}^{-2}$ . J. Am. Chem. Soc. 2021, 143, 3143−3152. \n(55) Liu, Z.; Cui, T.; Lu, T.; Shapouri Ghazvini, M.; Endres, F. Anion Effects on the Solid/Ionic Liquid Interface and the Electrodeposition of Zinc. J. Phys. Chem. C 2016, 120, 20224−20231. (56) Abbott, A. P.; Barron, J. C.; Frisch, G.; Ryder, K. S.; Silva, A. F. The Effect of Additives on Zinc Electrodeposition from Deep Eutectic Solvents. Electrochim. Acta 2011, 56, 5272−5279. \n(57) Chunyan, L.; Nishikawa, K.; Moon, J.; Kanamura, K. Electrodeposition of Zn from 1-Allyl-3-Methylimidazolium Bromide Containing $\\mathrm{ZnBr}_{2}$ . J. Electroanal. Chem. 2019, 832, 467−474. \n(58) de Carvalho, M. F.; Barbano, E. P.; Carlos, I. A. Influence of Disodium Ethylenediaminetetraacetate on Zinc Electrodeposition Process and on the Morphology, Chemical Composition and Structure of the Electrodeposits. Electrochim. Acta 2013, 109, 798− 808. \n(59) Feng, L.; Li, S.; Li, Y.; Li, H.; Zhang, L.; Zhai, J.; Song, Y.; Liu, B.; Jiang, L.; Zhu, D. Super-Hydrophobic Surfaces: from Natural to Artificial. Adv. Mater. 2002, 14, 1857−1860. \n(60) Mateos, M.; Makivic, N.; Kim, Y. S.; Limoges, B.; Balland, V. Accessing the Two-Electron Charge Storage Capacity of $\\mathrm{MnO}_{2}$ in Mild Aqueous Electrolytes. Adv. Energy Mater. 2020, 10, 2000332. (61) Moon, H.; Ha, K. H.; Park, Y.; Lee, J.; Kwon, M. S.; Lim, J.; Lee, M. H.; Kim, D. H.; Choi, J.-H.; Choi, J. H.; Lee, K. T. Direct Proof of the Reversible Dissolution/Deposition of $\\mathrm{{Mn^{2+}/M n^{4+}}}$ for Mild-Acid $\\mathrm{Zn}{\\cdot}\\mathrm{Mn}{\\mathrm{O}}_{2}$ Batteries with Porous Carbon Interlayers. Adv. Sci. 2021, 8, 2003714. (62) Burns, J.; Jain, G.; Smith, A.; Eberman, ${\\mathrm{K}}.{\\mathrm{}}$ Scott, E.; Gardner, J.; Dahn, J. Evaluation of Effects of Additives in Wound Li-Ion Cells through High Precision Coulometry. J. Electrochem. Soc. 2011, 158, A255. \n(63) Smith, A.; Burns, J.; Dahn, J. A high Precision Study of the Coulombic Efficiency of Li-Ion Batteries. Electrochem. Solid-State Lett. 2010, 13, A177. \n(64) Lin, L.; Qin, K.; Zhang, $\\mathrm{Q.;}$ Gu, L.; Suo, L.; Hu, Y. s.; Li, H.; Huang, X.; Chen, L. Li-Rich Li2[Ni0. 8Co0. 1Mn0. 1]O2 for AnodeFree Lithium Metal Batteries. Angew. Chem., Int. Ed. 2021, 60, 8289− 8296. " + }, + { + "id": "10.1038_s41565-021-01022-y", + "DOI": "10.1038/s41565-021-01022-y", + "DOI Link": "http://dx.doi.org/10.1038/s41565-021-01022-y", + "Relative Dir Path": "mds/10.1038_s41565-021-01022-y", + "Article Title": "Scalable two-step annealing method for preparing ultra-high-density single-atom catalyst libraries", + "Authors": "Hai, X; Xi, SB; Mitchell, S; Harrath, K; Xu, HM; Akl, DF; Kong, DB; Li, J; Li, ZJ; Sun, T; Yang, HM; Cui, YG; Su, CL; Zhao, XX; Li, J; Pérez-Ramírez, J; Lu, J", + "Source Title": "NATURE nullOTECHNOLOGY", + "Abstract": "A general versatile approach combining wet-chemistry impregnation and two-step annealing is devised for the scalable synthesis of a library of ultra-high-density single-atom catalysts with drastically enhanced reactivity. The stabilization of transition metals as isolated centres with high areal density on suitably tailored carriers is crucial for maximizing the industrial potential of single-atom heterogeneous catalysts. However, achieving single-atom dispersions at metal contents above 2 wt% remains challenging. Here we introduce a versatile approach combining impregnation and two-step annealing to synthesize ultra-high-density single-atom catalysts with metal contents up to 23 wt% for 15 metals on chemically distinct carriers. Translation to a standardized, automated protocol demonstrates the robustness of our method and provides a path to explore virtually unlimited libraries of mono- or multimetallic catalysts. At the molecular level, characterization of the synthesis mechanism through experiments and simulations shows that controlling the bonding of metal precursors with the carrier via stepwise ligand removal prevents their thermally induced aggregation into nulloparticles. The drastically enhanced reactivity with increasing metal content exemplifies the need to optimize the surface metal density for a given application. Moreover, the loading-dependent site-specific activity observed in three distinct catalytic systems reflects the well-known complexity in heterogeneous catalyst design, which now can be tackled with a library of single-atom catalysts with widely tunable metal loadings.", + "Times Cited, WoS Core": 422, + "Times Cited, All Databases": 442, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics; Materials Science", + "UT (Unique WOS ID)": "WOS:000722472000001", + "Markdown": "# Scalable two-step annealing method for preparing ultra-high-density single-atom catalyst libraries \n\nXiao Hai   1,11, Shibo Xi   2,11, Sharon Mitchell $\\textcircled{10}3,11$ , Karim Harrath4,5,11, Haomin Xu   1, Dario Faust Akl3, Debin Kong6, Jing Li   1, Zejun Li1, Tao Sun1, Huimin Yang $\\mathbb{O}^{1}$ , Yige Cui1, Chenliang Su   7, Xiaoxu Zhao   8 ✉, Jun Li   4,5 ✉, Javier Pérez-Ramírez   3 ✉ and Jiong Lu   1,9,10 ✉ \n\nThe stabilization of transition metals as isolated centres with high areal density on suitably tailored carriers is crucial for maximizing the industrial potential of single-atom heterogeneous catalysts. However, achieving single-atom dispersions at metal contents above $2\\times10\\%$ remains challenging. Here we introduce a versatile approach combining impregnation and two-step annealing to synthesize ultra-high-density single-atom catalysts with metal contents up to $23\\%$ for 15 metals on chemically distinct carriers. Translation to a standardized, automated protocol demonstrates the robustness of our method and provides a path to explore virtually unlimited libraries of mono- or multimetallic catalysts. At the molecular level, characterization of the synthesis mechanism through experiments and simulations shows that controlling the bonding of metal precursors with the carrier via stepwise ligand removal prevents their thermally induced aggregation into nanoparticles. The drastically enhanced reactivity with increasing metal content exemplifies the need to optimize the surface metal density for a given application. Moreover, the loading-dependent site-specific activity observed in three distinct catalytic systems reflects the well-known complexity in heterogeneous catalyst design, which now can be tackled with a library of single-atom catalysts with widely tunable metal loadings. \n\nmproving the atom economy of chemical transformations and ensuring the maximal utilization of scarce catalytic materials are central targets for sustainable chemistry1–6. Heterogeneous single-atom catalysts (SACs), integrating monodisperse atomic metal centres with tailorable coordination environments, demonstrate the potential to fulfil both of these objectives in several energy-related transformations7–15. A fundamental challenge in implementing this pioneering class of catalysts in many technical applications is the lack of synthetic routes enabling the preparation of these catalysts with high surface densities16–19. Achieving the latter is particularly important to maximize the productivity per unit reactor volume or area in large-scale processes. Taking nickel SACs, which exhibit highly selective performance in the electrochemical reduction of carbon dioxide20, as a representative example, a literature analysis shows that most of the materials reported to date are based on carbon-related materials and contain metal contents centred around $1\\mathrm{wt\\%}$ , with exceptional cases up to $7\\mathrm{wt\\%}$ (Fig. 1a). These values are significantly lower than the expected theoretical capacity of these carriers for anchoring metal atoms. \n\nOf the distinct synthesis strategies reported for SACs, the postsynthetic introduction of metals via wet deposition routes such as impregnation is among the most amenable to scale-up21–31. This approach also favours surface localization, unlike direct synthesis approaches such as pyrolysis, where a large fraction of the active phase may become embedded in the bulk of carrier materials32. However, when introducing high metal contents, it is difficult to prevent the undesired aggregation of metal species into clusters and nanoparticles especially after applying conventional thermal treatments to remove counterions from common metal precursors (Fig. $^{1\\mathrm{b},\\mathrm{c}}$ and Supplementary Fig. 1)17. Strategies to circumvent this by avoiding metal salt precipitation or using equilibrium adsorption typically restrict the amount deposited on carriers. No published study has achieved ultra-high-density (UHD) SACs—defined herein as having metal contents over $10\\mathrm{{wt\\%}}$ for carbon-based catalysts—by postsynthetic routes, or demonstrated their enhanced productivity in catalytic applications. Another scarcely addressed aspect is the extension to multimetallic systems, which is relevant for the development of technical catalysts since they often incorporate two or more metals, for example, as co-catalysts, promoters or stabilizers. Beyond the selection of carriers with abundant surface anchoring sites for metal atoms, the synthesis mechanism remains poorly understood at the molecular level. \n\n# Two-step annealing approach \n\nThe two-step annealing approach introduced here comprises a versatile and scalable method for the preparation of mono- or multimetallic \n\n![](images/a5aaaf6ee52cb790a0f5d33ea74f666e30ef896808cce3ecf550184ed833662e.jpg) \nFig. 1 | Synthesis of UHD-SACs. a, Literature survey on the metal contents reported in nickel SACs revealing the predominant use of carbon-based carriers. b, Comparison of the size of nickel species obtained on NC via a conventional impregnation strategy involving a single thermal treatment and the two-step annealing strategy introduced in this work as a function of the metal content. c, ADF-STEM images of $10\\mathrm{wt\\%}$ Ni–NC samples by a single thermal treatment (top) and a two-step annealing strategy (bottom). Scale bars, $100\\mathsf{n m}$ (inset, 1 nm). d, Strategy for the preparation of UHD-SACs. e, Metal loadings achieved in this study on NC, PCN and ${\\mathsf{C e O}}_{2}$ supports. \n\nUHD-SACs of more than 15 transition metals on carriers with distinct chemical natures, such as nitrogen-doped carbon (NC), polymeric carbon nitride (PCN) and metal oxides (Supplementary Fig. 2). The approach relies on controlling ligand removal from metal precursors and the associated interactions with the carrier (Fig. 1d). The strength of the proposed method lies in effectively saturating the surface with metal and retaining a high metal coverage by a selective anchoring mechanism that maximizes the probability of bonding the metal to all available coordination sites and enables the removal of unbound species via washing, thereby preventing metal sintering in the subsequent high-temperature step to remove residual ligand and permitting the stabilization of much higher metal contents compared to conventional impregnation routes. The method uses aqueous solutions of common metal precursors (chlorides, sulfates or acetates) or mixtures thereof where multimetallic systems are targeted. To regulate ligand removal, the temperature of the first annealing step $(T_{1})$ needs to be lower than that of the decomposition temperature of the metal precursor; the most labile in the preparation of multimetallic SACs. For this reason, the use of metal chlorides provides greater control due to the strong intrinsic metal–chlorine bonds, which permits the use of higher temperatures in the first annealing step (Supplementary Table 1). The chemisorbed metal precursors are subsequently transformed into UHD-SACs with well-defined atomic structures by a second annealing step at a higher temperature $(T_{2})$ to remove the remaining ligands. \n\nAnalysis by inductively coupled plasma atomic emission spectroscopy (ICP-AES) shows that the two-step annealing method achieves metal contents higher than $10\\mathrm{wt\\%}$ , in several cases exceeding $20\\mathrm{wt\\%}$ , on both NC and PCN carriers for all the metals studied (Fig. 1e). Lower metal loadings of between 2 and $10\\mathrm{{wt\\%}}$ result when using ${\\mathrm{CeO}}_{2}$ as the carrier, reflecting its higher relative molecular weight versus carbon-based materials. To provide a universal basis for comparison, the surface areal density in atoms per square nanometre was evaluated based on the measured Brunauer– Emmett–Teller surface area of the carrier (Supplementary Fig. 3). UHD-SACs derived from PCN evidenced the highest densities for all metals, consistent with the abundance of metal coordination sites presented by this carrier due to the intrinsic crystalline structure based on heptazine units. Discrete ranges of values were observed for first-row ( ${\\bf>}9{\\bf\\AA}$ atoms per $\\mathbf{nm}^{2}.$ ), second-row $_{\\cdot\\sim6}$ atoms per $\\mathrm{nm}^{2^{*}}.$ ) and third-row ( $\\cdot<5$ atoms per $\\mathrm{nm}^{2}$ ) transition metals. The significantly higher values for first-row transition metals could be indicative of some percolation into the lattice. Values between 2.5 and 6 atoms per $\\mathrm{nm}^{2}$ for ${\\mathrm{CeO}}_{2}$ are significantly higher than previous estimates for high-loading catalysts based on this carrier33. Values between 0.4 and 1 atoms per $\\mathrm{nm}^{2}$ are observed for NC, approaching the upper limit of 1.3 atoms per $\\mathrm{nm}^{2}$ calculated from the nitrogen content in the carrier. \n\n![](images/01893464106c229632f702ed5310eb25f50e82b871b96cc297653433b75be349.jpg) \nFig. 2 | Visualization and spectroscopic characterization of UHD-SACs. a, Atomic-resolution ADF-STEM images of various metals on NC support. Scale bars, 1 nm. b, Enlarged area of the ADF-STEM image of $\\mathsf{P t}_{\\mathcal{N}}\\mathsf{N C}$ . Scale bar, $0.5\\mathsf{n m}$ . The inset shows the intensity profile along the dashed white line. c,d, Fourier transformation of Pt $\\mathsf{L}_{3}$ -edge EXAFS $\\mathbf{\\eta}(\\bullet)$ and DRIFTS spectra of adsorbed CO (d) of $\\mathsf{P t}_{1}/\\mathsf{N C}$ , $\\mathsf{P t}_{\\mathsf{\\mathcal{N}}}/\\mathsf{P C N}$ and $\\mathsf{P t}_{1}/\\mathsf{C e O}_{2}$ and reference materials. \n\nTo further confirm the generality of the approach, we extended the synthesis to other commonly used supports, including titanium dioxide and alumina (Supplementary Fig. 4). It is noteworthy that the present strategy is based on the premise that a carrier with surface functionalities able to react with the deposited metal in the investigated temperature range is used. For this reason, platinum single atoms cannot be isolated on amorphous silica with the presented method due to the weak bond between surface oxygen and platinum (Supplementary Fig. 5). Additionally, the simultaneous introduction of multiple metal precursors behaves additively and successfully yields multimetallic UHD-SACs, demonstrating the scope of the method to produce a widely tuneable materials platform (Supplementary Fig. 6). \n\n# Confirming the UHD atomic dispersion \n\nThe atomic metal dispersions of the obtained UHD-SACs on NC were directly imaged by annular dark-field scanning transmission electron microscopy (ADF-STEM, Fig. 2a), revealing densely populated features ascribed to isolated atoms. Low-magnification elemental mapping by energy-dispersive X-ray spectroscopy (EDS) of NC-based UHD-SACs confirmed the uniform metal distribution and the absence of larger aggregates (Supplementary Figs. 7 and 8). The bright dots in the high-magnification ADF-STEM images of platinum on NC, PCN and $\\mathrm{CeO}_{2}$ exhibit diameters of approximately $0.2\\mathrm{nm}$ , reflecting the convolution of an isolated platinum atom with the electron probe (Fig. 2b and Supplementary Fig. 9). PCN-supported UHD-SACs display high metal atom densities (Supplementary Fig. 10a) and heavy elements such as tungsten, iridium and platinum, which are distinguishable on $\\mathrm{CeO}_{2},$ also evidence atomic dispersion (Supplementary Fig. 10b). Elemental uniformity is also visible at a larger scale, as seen in low-magnification \n\n![](images/d667bf646ac4ffea21c608e64fce338229f9cafcfee3b79880d753f818a767ce.jpg) \nFig. 3 | Visualization of multimetallic UHD-SACs. a,b, Atomic-resolution ADF-STEM images of Ni and Pd (a) and Ni–Pd–Pt multimetallic UHD-SACs (b) on NC. c, EDS map of Ni, Pd and Pt in Ni1Pd1Pt1/NC. Scale bars, 1 nm (a and b) and $50\\mathsf{n m}$ (c). \n\nEDS maps (Supplementary Figs. 11–13). The metal contents determined via EDS agree well with ICP-AES-derived values (Supplementary Fig. 14). \n\nPowder X-ray diffraction patterns confirm the absence of crystalline metal compounds in all UHD-SAC samples, evidencing only reflections of the carrier materials (Supplementary Fig. 15a–c). The Fourier-transformed extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) spectra of all the UHD-SAC samples exhibit major peaks around $1.{\\dot{5}}{\\dot{\\mathrm{A}}}$ , corresponding to $_{\\mathrm{M-N/O}}$ bond lengths (Fig. 2c and Supplementary Fig. 15d–f)11,34. No signatures of metal–metal coordination between 2.1 and $2.5\\mathring\\mathrm{A}$ are observed in any of the samples, confirming the absence of metal nanoparticles or clusters. Consistently, infrared spectroscopy of adsorbed CO on $\\mathrm{Pt}_{1}/$ NC, $\\mathrm{Pt_{\\mathrm{1}}/P C N}$ and $\\mathrm{Pt}_{1}/\\mathrm{CeO}_{2}$ reveals only one set of CO absorption bands centred at $2,117\\mathrm{cm}^{-1}$ (Fig. 2d). No infrared peaks in the range of $2,070{-}2,090\\mathrm{cm}^{-1}$ corresponding to platinum nanoparticles can be observed12. These results further validate the atomic-resolution ADF-STEM analyses, demonstrating the successful preparation of UHD-SACs with various metals and carriers. The Pt $\\mathrm{L}_{3}$ -edge X-ray absorption near-edge structure (XANES) spectra and the Pt 4f X-ray photoelectron (XPS) spectra both indicate that all the platinum species are positively charged, and the valence state on NC and PCN is slightly lower than on $\\mathrm{CeO}_{2}$ (Supplementary Fig. 16)11,35. K-edge XANES corroborates this trend for nickel, where the intensity of the white line of $\\mathrm{Ni_{\\mathrm{1}}/N C}$ and $\\mathrm{Ni_{1}/P C N}$ is similar and lower than that observed for $\\mathrm{Ni_{1}/C e O_{2}}$ (Supplementary Fig. 17). ADF-STEM images of $\\mathrm{\\DeltaNi}$ and Pd and of Ni–Pd–Pt UHD-SACs also confirmed the atomic dispersion of the constituent metals in multimetallic systems (Fig. 3a,b). This combination of metals was selected to facilitate characterization, permitting the local identification of multimetallic SACs based on analysis of the intensity profiles over the different atoms, wherein heavier metal atoms exhibit higher contrast and wider peaks in terms of full width at half maximum (Supplementary Fig. 18). The spatial uniformity of individual elements in the Ni–Pd–Pt UHD-SAC is confirmed in the elemental maps acquired by energy-dispersive X-ray spectroscopy (Fig. 3c). \n\n# Amenability to automation and scale-up \n\nMotivated by growing efforts across catalysis research towards automation and standardization of procedures, which are most advanced in computational chemistry and catalyst characterization and testing, we translated the two-step annealing approach to an automated synthesis protocol. The use of a robotic platform (Fig. 4a) permits precise control over the quantity and speed of metal addition and over the extent of sample washing, and requires only minor adaptions of the laboratory-based protocol such as the use of shaking instead of sonication for mixing the carrier with the aqueous solution of the metal precursor (Fig. 4b). Accordingly, the procedure could readily obtain nickel SACs over a broad range of metal content (Fig. 4c). Slightly lower values observed in the samples prepared by the automated compared to the laboratory protocol originate from operating under ambient rather than reduced pressure during the mixing step, which decreases surface wetting of the micropores. Given the virtually limitless potential combinations of metals, carriers and stoichiometry, the possibility to automate the synthesis protocol enabling the reproducible preparation of well-defined UHD-SAC libraries is highly attractive for the derivation of more precise synthesis–property–performance relationships to guide their design in targeted applications. Besides versatility, another important feature of our approach is the scalability. Because the two-step annealing approach employs simple unit operations (impregnation, thermal treatment, washing and filtration), it readily translates to the kilogramme-scale production of UHD-SACs, with no appreciable differences in the properties of the resulting material (Supplementary Fig. 19). \n\n# Mechanistic insights into the controlled ligand removal \n\nTo understand the greater effectiveness of the two-step annealing strategy, we followed the evolution of the metal and anchor site during the synthesis by EXAFS, XANES, XPS and density functional theory (DFT) modelling. Starting from nickel chloride $\\mathrm{(NiCl}_{2})$ and NC, we identify adsorbed $\\mathrm{NiCl}_{2}$ $\\mathrm{(NiCl_{2}/N C)}$ , partially chlorinated (NiCl/NC) and the fully bound Ni $(\\mathrm{Ni_{1}/N C})$ single atoms as key intermediates or products, respectively (Supplementary Fig. 20a). Whereas X-ray diffraction analysis of the materials before and after the respective annealing steps confirms the disappearance of characteristic $\\mathrm{NiCl}_{2}$ reflections, it provides no information on changes in the local environment (Supplementary Fig. 20b). Comparison of both XANES and EXAFS spectra evidences appreciable differences between the intermediates. A single peak at around $1.97\\mathring{\\mathrm{A}}$ for ${\\mathrm{NiCl}}_{2}/{\\mathrm{NC}}$ corresponds to the Ni–Cl bond from pure $\\mathrm{NiCl}_{2}$ . After low-temperature annealing, a strong signal appears at around $1.40\\mathring\\mathrm{A}$ for NiCl/NC, consistent with the newly formed $\\mathrm{{Ni-N}}$ bonds20,36 (Fig. 5a). Concurrently, the peak position of the Ni–Cl bond moved from 1.97 to $1.75\\mathring{\\mathrm{A}}$ due to the transformation of ${\\mathrm{NiCl}}_{2}/{\\mathrm{NC}}$ to a $\\mathrm{NiN_{4}C l}$ structure. From the fitting results (Supplementary Fig. 21 and Supplementary Table 2), the coordination numbers of the nitrogen and chlorine atoms in the first coordination sphere of nickel are around 4.8 and 0.9, respectively, with a square-pyramidal configuration for $\\mathrm{{Ni-N}}$ bonding. Following the high-temperature annealing forming $\\mathrm{Ni_{1}/N C}$ , only the $\\mathrm{Ni-N}$ peak at around $\\overset{\\cdot}{1.40\\mathrm{\\AA}}$ is seen with no evidence of Ni–Cl bonds, indicating that the anchored nickel atoms lose another ligand to form the $\\mathrm{Ni-N_{4}}$ site. The profile of the XANES spectrum of $\\mathrm{Ni_{\\mathrm{1}}/N C}$ (Supplementary Fig. 20c) contains similar characteristic features to the nickel phthalocyanine (NiPc), which has a well-defined $\\mathrm{NiN_{4}}$ structure36. The shoulder at $8{,}340\\mathrm{eV}$ of $\\mathrm{Ni_{1}/N C}$ and NiPc is due to a $1s{-}4p_{z}$ orbital transition characteristic for a square-planar configuration with high $D_{4h}$ local symmetry. This feature is significantly weakened in the NiCl/NC sample, indicating a broken $D_{4h}$ symmetry, which agrees well with our proposed atomic model $\\mathrm{(NiN_{4}C l)}$ in which the Ni–Cl bond displaces the Ni from the $\\mathrm{N_{4}}$ in-plane geometry. \n\n![](images/81a68cab6861b4422bd6b023d6b866ca714d1ab2411ab442c162a5f185305e18.jpg) \nFig. 4 | Automated synthesis protocol. a, Photograph of the robotic synthesis platform and assignment of tools to unit operations. b, Flowsheet of the synthesis protocol, where T is the temperature and t is the time. c, Comparison of metal content achieved by automated and manual synthesis of $\\mathsf{N i}_{\\mathcal{\\breve{N}}}\\mathsf{C}$ catalysts. \n\nAdditionally, the structural evolution of the surface anchoring site was investigated by XPS. The high-resolution N 1s spectra of the anchor site can be fitted by components corresponding to $\\scriptstyle{\\mathrm{C=N-C}}$ $(397.9\\mathrm{eV},$ , marked as N1), ${\\mathrm{C}}{=}\\mathrm{N}{\\mathrm{-}}\\mathrm{H}$ $399.3\\mathrm{eV},$ marked as N2), $\\scriptstyle{\\mathrm{C}}={\\mathrm{N}}-$ Ni–Cl $398.3\\mathrm{eV},$ marked as N3) and ${\\mathrm{C}}{=}\\mathrm{N}{-}\\mathrm{Ni}$ $(398.7\\mathrm{eV},$ marked as N4) species (Fig. 5b)20,37. In the pristine NC, the anchoring sites are composed of two $\\scriptstyle{\\mathrm{C=N-C}}$ (N1) and two ${\\mathrm{C}}{=}\\mathrm{N}{\\mathrm{-}}\\mathrm{H}$ (N2). The intensity of N2 noticeably decreases and is accompanied by a transformation of N1 to N3 during the first-step low-temperature annealing. Concurrently, $_\\mathrm{N-H}$ bonds are suggested to be replaced by newly formed $\\mathrm{\\DeltaN-Ni}$ bonds (N3). The nickel precursor is expected to react with ${\\mathrm{C}}{=}\\mathrm{N}{\\mathrm{-}}\\mathrm{H}$ functional groups by breaking the $_\\mathrm{N-H}$ bond and removing the hydrogen atom at elevated temperature. In the subsequent high-temperature annealing, the $_\\mathrm{N-H}$ bond completely disappears with the accompanying transformation of N3 to N4, suggesting further cleavage of the remaining $_\\mathrm{N-H}$ groups to form exclusively Ni–N4 sites. The binding energies of Ni $2p_{3/2}$ in NiCl/NC and $\\mathrm{Ni_{1}/N C}$ were 855.3 and $855.4\\mathrm{eV},$ respectively (Supplementary Fig. 20d), which are 1.3 and $1.2\\mathrm{eV}$ lower in the $\\mathrm{NiCl}_{2}$ precursor $(\\mathrm{Ni^{2+}},$ , $856.6\\mathrm{eV})$ . The binding energy of Cl $2p_{3/2}$ in NiCl/NC $(197.4\\mathrm{eV})$ is $1.6\\mathrm{eV}$ lower than the precursor ( $199.0\\mathrm{eV},$ Supplementary Fig. 20e). Interestingly, the stepwise removal of chloride ligands can be followed through the $\\operatorname{Cl}2p$ signal of ${\\mathrm{NiCl}}_{2}/{\\mathrm{NC}}.$ , NiCl/NC and $\\mathrm{Ni_{1}/N C,}$ the latter of which shows no peak. These comprehensive structural analyses unambiguously reveal the path of the coordination of nickel atoms from the adsorbed metal precursor, through our proposed intermediate $\\mathrm{NiN_{4}C l}$ and final $\\mathrm{NiN_{4}}$ structures. \n\nBased on these well-established atomic structures, DFT calculations were conducted to gain molecular-level insight into the synthesis mechanism (Fig. 5c). In the first step, the anchoring of a single $\\mathrm{NiCl}_{2}$ entity to the N4 anchor site in the carrier leads to the first transition state (TS1) with a barrier of $1.39\\mathrm{eV}$ and endothermic reaction energy of $0.14\\mathrm{eV}.$ The following rearrangement releasing one HCl molecule is exothermic and occurs spontaneously, forming the first intermediate (Int1). The release of a second HCl molecule drives the transformation of NiCl/NC to Ni/NC $(\\mathrm{Int}2\\rightarrow\\mathrm{Ni}/$ NC) endergonically $(-1.74\\mathrm{eV})$ without an energy barrier. Since the hydrogen and chlorine atoms need to be on the same side, the rotation of a hydrogen atom from the bottom to the top surface must be considered $(\\mathrm{Int1}\\to\\mathrm{Int}2),$ . This process requires a barrier of $0.72\\mathrm{eV}$ with endothermic reaction energy of $0.28\\mathrm{eV}.$ Hence, the formation of $\\mathrm{Ni_{1}/N C}$ proceeds via two endothermic and one spontaneous step, which is in line with our experimental procedure, where two annealing steps are needed. A similar landscape is obtained for the formation of $\\mathrm{Fe_{1}/N C}$ , $\\mathrm{{Cu_{1}/N C}}$ and ${\\mathrm{Ni_{1}}}/{\\mathrm{CeO_{2}}}$ using metal chloride precursors and of $\\mathrm{Ni_{1}/N C}$ using $\\mathrm{NiSO_{4}}$ as a metal precursor (Supplementary Figs. 22 and 23). \n\n# Enhanced productivity of UHD-SACs \n\nAs a proof of concept, we evaluated the catalytic performance of representative UHD-SACs in applications where supported single atoms demonstrate promising technological potential. Nickel SACs excel in the electrochemical reduction of carbon dioxide to carbon monoxide38,39. For the $\\mathrm{Ni_{1}/N C}$ catalyst, the only products detected are gas-phase CO and $\\mathrm{H}_{2}$ and no liquids in the voltage range from 0 to $-1.15\\mathrm{V}$ versus a reversible hydrogen electrode (RHE). The linear sweep voltammetry (LSV) curves reveal significantly higher current density over the UHD $\\mathrm{Ni_{\\mathrm{1}}/N C}$ than the low-density $\\mathrm{Ni_{\\mathrm{1}}/N C}$ (Fig. 6a). In terms of Faradaic efficiency towards CO, the UHD and low-density $\\mathrm{Ni_{\\mathrm{1}}/N C}$ catalysts exhibit a maximum of $97\\%$ at around $-0.95$ and $-0.75\\mathrm{V}$ versus RHE, respectively (Fig. 6b). Although the nickel content in UHD $\\mathrm{Ni_{1}/N C}$ catalyst is ten times higher than in the low-density $\\mathrm{Ni_{1}/N C}$ catalyst, it conserves the high selectivity towards CO. Notably, the UHD $\\mathrm{Ni_{\\mathrm{1}}/N C}$ catalyst maintains greater than $86\\%$ Faradaic efficiency even at a very negative potential of $-1.15\\mathrm{V}$ versus RHE. The activity scaled with the nickel content, showing a gradual increase in the current density of CO for metal contents ranging from 1.6 to $16.3\\mathrm{wt\\%}$ (Supplementary Fig. 24). The site-specific activity is similar across the range of investigated loadings with a slightly lower $(\\sim30\\%)$ activity per site for the highest metal contents in the voltage range from $-0.55$ to $-1.05\\mathrm{V}$ (Supplementary Fig. 25). An approximately $30\\%$ loss in activity per site is probably due to the percolation of a small portion of nickel metal into the inner part of the carbon carrier. These nickel SAC sites buried inside would not be directly accessible by $\\mathrm{CO}_{2},$ leading to a decrease in site-specific reactivity because the total amount of nickel SACs is counted in the calculation. It is expected that for metal species with small atomic radius and high thermal mobility, an increase of metal loading may also result in a slightly higher ratio of single atoms embedded in the bulk of host materials, consistent with our experimental observations (Supplementary Fig. 25). DFT modelling reveals the favourable energetics of the $\\mathrm{CO}_{2}$ reduction reaction over parasitic hydrogen formation at the $\\mathrm{Ni_{\\mathrm{1}}/N C}$ site (Supplementary Fig. 26). The main advantage of the UHD $\\mathrm{Ni_{1}/N C}$ catalyst for $\\mathrm{CO}_{2}$ reduction is that it delivers a much higher CO partial current density due to the high abundance of nickel active sites compared to the conventional low-density counterpart. Furthermore, it preserves stable $\\mathrm{CO}_{2}$ reduction at constant current density for CO $(20\\mathrm{mAcm}^{-2})$ ) during $48\\mathrm{h}$ of continuous operation (Fig. 6c); the current density and Faradaic efficiency profiles during two consecutive linear voltammetry sweeps are identical (Supplementary Fig. 27). ADF-STEM images measured after the electrochemical stability test show identical well-dispersed nickel atoms as seen in the fresh $\\mathrm{Ni_{1}/N C}$ catalyst (Supplementary Fig. 28). \n\n![](images/3f187392ee9267a00aa09d85104bf84c6c059ccc77a44a28de19a92d2072086a.jpg) \nFig. 5 | Mechanistic investigation of the synthesis of UHD-SACs. a,b, Fourier-transformed EXAFS (a) and N 1s XPS (b) spectra of NiCl2/NC, NiCl/NC and ${\\sf N i}_{1}/{\\sf N C}.R$ is the radial distance. c, DFT-calculated energy (E) pathway for the formation of Ni– ${\\cdot}\\mathsf{N}_{4}$ from the $\\mathsf{N i C l}_{2}$ precursor with representative transition states and intermediates depicted inset. $\\Delta G$ is the change in Gibbs free energy and $\\Delta H$ is the change in enthalpy. \n\nIn addition to electrochemical applications, SACs are the preferred nanostructure in several thermally driven reactions. Due to their structural similarities, they have attracted significant interest for the replacement of homogeneous catalysts in organic transformations14. Evaluation of $\\mathrm{{Cu_{1}/P C N}}$ catalysts in the azide–alkyne cycloaddition reaction of 4-ethynylanisole with benzyl azide demonstrated a remarkable enhancement in the performance with increasing metal content, from virtually negligible activity in the conventional SAC to yielding the desired product with $92\\%$ isolated yield with stable performance over ten consecutive runs (Fig. 6d,e and Supplementary Fig. 29). As a result, the site-specific activity for $\\mathrm{Cu}_{1}/\\mathrm{PCN}$ with the highest metal content is observed to be seven times higher than that for $\\mathrm{{Cu}_{\\mathrm{1}}/\\mathrm{{PCN}}}$ with the low metal content (Supplementary Fig. 30). The enhanced productivity not only arises from the increased number of active sites per unit reactor volume or area but also receives a significant contribution from the dramatically increased site-specific activity with increasing copper loading for cross-coupling reactions. This experimental result indicates that well-isolated single-atom sites present in low-loading SACs may not be able to co-adsorb and activate the multiple reactants required for organic cross-coupling reactions, while the synergistic effect derived from the presence of neighbouring single-atom sites promotes a dramatically enhanced site-specific activity for UHD- $\\mathrm{\\cdot}\\mathrm{Cu}_{1}/$ PCN SACs. In a more classical gas-phase application, platinum single-atom catalysts were recently shown to comprise stable and active catalysts as alternatives to currently applied mercury-based catalysts in the production of vinyl chloride monomer (VCM) via acetylene hydrochlorination40. The presence of halogen species in the reaction mixture induces mobility of supported metal atoms but increasing the strength of interaction with the carrier too much renders them inactive. Here the initial yield of VCM over $\\mathrm{Pt_{\\mathrm{1}}/N C}$ catalysts directly correlated with the metal content of the catalysts applied, but an optimal metal content of $4.4\\mathrm{wt\\%}$ was observed for stable performance, above which a gradual drop in VCM yield was observed with time-on-stream due to sintering (Fig. 6f). The initial yield of VCM over $\\mathrm{Pt}_{1}/\\mathrm{NC}$ SAC scales with platinum content, which also suggests that the reactivity of $\\mathrm{Pt_{\\mathrm{1}}/N C}$ SACs indeed scales with metal loading. The larger atomic radius of platinum disfavours its thermal diffusion and percolation into inner bulk. Nearly all the platinum atoms anchored on the surface of NC are readily accessible by the reactants, leading to nearly zero loss of activity per site with increasing platinum loading (Supplementary Fig. 31). The enhanced performance evidenced by these results demonstrates the exciting scope of UHD-SACs to improve both the productivity and understanding of mono- or multimetallic single atom systems in a broad variety of catalytic applications in the near future. \n\n![](images/dc45d6835e7aca884cbd9c09d5d6cfbafe5ab3f05afc3a95125502b70e0c1f56.jpg) \nFig. 6 | Catalytic performance of UHD-SACs. a–c, Electrocatalytic ${\\mathsf{C O}}_{2}$ reduction reaction performance of ${N i_{1}}/{N C}$ catalyst: LSV curve (a), Faradaic efficiency over 1.6, 4.2, 8.3 and $16.3\\mathrm{wt\\%}$ Ni1/NC catalysts (b) and stability test of $16.3\\mathrm{wt\\%}$ Ni1/NC UHD-SAC (c). d,e, $\\mathsf{C u\\mathrm{\\sqrt{PCN}}}$ -catalysed azide–alkyne cycloaddition of 4-ethynylanisol with benzyl azide: loading dependence on catalytic performance (d) and cycling stability test of 21.8 wt% $\\mathsf{C u}_{1}$ /PCN UHD-SAC (e). f, Pt1/NC-catalysed acetylene hydrochlorination as a function of time on stream (TOS). \n\n# Discussion \n\nThe scalable wet-chemistry method established here to prepare UHD-SACs across a broad range of transition metals on chemically distinct carriers comprises a breakthrough towards their practical implementation. Our experimental and theoretical analysis showed that the success of the two-step annealing approach at stabilizing high surface densities of isolated metal atoms derives from the selective bonding of metal precursors to the carrier. This controlled interaction enables the removal of weakly interacting species that would otherwise aggregate upon complete decomposition. Besides monometallic systems, a library of multimetallic systems can be readily accessed, evidencing the general applicability of the two-step annealing method. The reproducibility of the synthesis upon automation and at large scale demonstrates the robustness of the approach, paving the way for the widespread application of UHD-SACs in sustainable chemical and energy transformations. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/ s41565-021-01022-y. \n\n# Received: 5 April 2021; Accepted: 29 September 2021; Published: xx xx xxxx \n\n# References \n\n1.\t Kaiser, S. K., Chen, Z., Faust Akl, D., Mitchell, S. & Pérez-Ramírez, J. Single-atom catalysts across the periodic table. Chem. Rev. 120, 11703–11809 (2020). \n2.\t Li, Z. et al. Well-defined materials for heterogeneous catalysis: from nanoparticles to isolated single-atom sites. Chem. Rev. 120, 623–682 (2019). \n3.\t Li, X., Yang, X., Huang, Y., Zhang, T. & Liu, B. Supported noble‐metal single atoms for heterogeneous catalysis. Adv. Mater. 31, 1902031 (2019). \n4.\t Wang, Y. et al. Catalysis with two-dimensional materials confining single atoms: concept, design, and applications. Chem. Rev. 119, 1806–1854 (2018). \n5.\t Lin, L. et al. Low-temperature hydrogen production from water and methano using $\\mathrm{Pt/\\upalpha}$ -MoC catalysts. Nature 544, 80–83 (2017). \n6.\t Datye, A. K. & Guo, H. Single atom catalysis poised to transition from an academic curiosity to an industrially relevant technology. Nat. Commun. 12, 895 (2021). \n7.\t Yang, X.-F. et al. Single-atom catalysts: a new frontier in heterogeneous catalysis. Acc. Chem. Res. 46, 1740–1748 (2013). \n8.\t Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}}/\\mathrm{FeO}_{x}.$ Nat. Chem. 3, 634–641 (2011). \n9.\t Zhang, L., Zhou, M., Wang, A. & Zhang, T. Selective hydrogenation over supported metal catalysts: from nanoparticles to single atoms. Chem. Rev. 120, 683–733 (2019). \n10.\tLiu, D. et al. Atomically dispersed platinum supported on curved carbon supports for efficient electrocatalytic hydrogen evolution. Nat. Energy 4, 512–518 (2019). \n11.\tJones, J. et al. Thermally stable single-atom platinum-on-ceria catalysts via atom trapping. Science 353, 150–154 (2016). \n12.\tNie, L. et al. Activation of surface lattice oxygen in single-atom $\\mathrm{Pt/CeO}_{2}$ for low-temperature CO oxidation. Science 358, 1419–1423 (2017). \n13.\tWang, A., Li, J. & Zhang, T. Heterogeneous single-atom catalysis. Nat. Rev. Chem. 2, 65–81 (2018). \n14.\tChen, Z. et al. A heterogeneous single-atom palladium catalyst surpassing homogeneous systems for Suzuki coupling. Nat. Nanotechnol. 13, 702–707 (2018). \n15.\tJung, E. et al. Atomic-level tuning of Co–N–C catalyst for high-performance electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Nat. Mater. 19, 436–442 (2020). \n16.\tBeniya, A. & Higashi, S. Towards dense single-atom catalysts for future automotive applications. Nat. Catal. 2, 590–602 (2019). \n17.\tJi, S. et al. Chemical synthesis of single atomic site catalysts. Chem. Rev. 120, 11900–11955 (2020). \n18.\tDing, S., Hülsey, M. J., Pérez-Ramírez, J. & Yan, N. Transforming energy with single-atom catalysts. Joule 3, 2897–2929 (2019). \n19.\tDeRita, L. et al. Catalyst architecture for stable single atom dispersion enables site-specific spectroscopic and reactivity measurements of CO adsorbed to Pt atoms, oxidized Pt clusters, and metallic Pt clusters on $\\mathrm{TiO}_{2}$ J. Am. Chem. Soc. 139, 14150–14165 (2017). \n20.\tYang, H. B. et al. Atomically dispersed Ni(i) as the active site for electrochemical $\\mathrm{CO}_{2}$ reduction. Nat. Energy 3, 140–147 (2018). \n21.\tLiu, Y. et al. A general strategy for fabricating isolated single metal atomic site catalysts in Y zeolite. J. Am. Chem. Soc. 141, 9305–9311 (2019). \n22.\tFei, H. et al. General synthesis and definitive structural identification of $\\mathrm{MN}_{4}\\mathrm{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n23.\tHe, X. et al. A versatile route to fabricate single atom catalysts with high chemoselectivity and regioselectivity in hydrogenation. Nat. Commun. 10, 3663 (2019). \n24.\tWei, H. et al. Iced photochemical reduction to synthesize atomically dispersed metals by suppressing nanocrystal growth. Nat. Commun. 8, 1490 (2017). \n25.\tYang, H. et al. A universal ligand mediated method for large scale synthesis of transition metal single atom catalysts. Nat. Commun. 10, 4585 (2019). \n26.\tZhang, Z. et al. Electrochemical deposition as a universal route for fabricating single-atom catalysts. Nat. Commun. 11, 1215 (2020). \n27.\t Zhao, L. et al. Cascade anchoring strategy for general mass production of highloading single-atomic metal-nitrogen catalysts. Nat. Commun. 10, 1278 (2019). \n28.\tWei, S. et al. Direct observation of noble metal nanoparticles transforming to thermally stable single atoms. Nat. Nanotechnol. 13, 856–861 (2018). \n29.\tYao, Y. et al. High temperature shockwave stabilized single atoms. Nat. Nanotechnol. 14, 851–857 (2019). \n30.\tLiu, P. et al. Photochemical route for synthesizing atomically dispersed palladium catalysts. Science 352, 797–800 (2016). \n31.\tWang, L. et al. A sulfur-tethering synthesis strategy toward high-loading atomically dispersed noble metal catalysts. Sci. Adv. 5, eaax6322 (2019). \n32.\tCheng, Y. et al. Atomically dispersed transition metals on carbon nanotubes with ultrahigh loading for selective electrochemical carbon dioxide reduction. Adv. Mater. 30, 1706287 (2018). \n33.\tKunwar, D. et al. Stabilizing high metal loadings of thermally stable platinum single atoms on an industrial catalyst support. ACS Catal. 9, 3978–3990 (2019). \n34.\tZhang, L. et al. Direct observation of dynamic bond evolution in single‐atom $\\mathrm{Pt/C_{3}N_{4}}$ catalysts. Angew. Chem. Int. Ed. 59, 6224–6229 (2020). \n35.\tLi, H. et al. Synergetic interaction between neighbouring platinum monomers in $\\mathrm{CO}_{2}$ hydrogenation. Nat. Nanotechnol. 13, 411–417 (2018). \n36.\tAvakyan, L. et al. Atomic structure of nickel phthalocyanine probed by X-ray absorption spectroscopy and density functional simulations. Opt. Spectrosc. 114, 347–352 (2013). \n37.\tKabir, S., Artyushkova, K., Serov, A., Kiefer, B. & Atanassov, P. Binding energy shifts for nitrogen‐containing graphene‐based electrocatalysts-experiments and DFT calculations. Surf. Interface Anal. 48, 293–300 (2016). \n38.\tJiang, K. et al. Isolated Ni single atoms in graphene nanosheets for high-performance $\\mathrm{CO}_{2}$ reduction. Energy Environ. Sci. 11, 893–903 (2018). \n39.\t Kim, H. et al. Identification of single-atom Ni site active toward electrochemical $\\mathrm{CO}_{2}$ conversion to CO. J. Am. Chem. Soc. 143, 925–933 (2021). \n40.\tKaiser, S. K. et al. Nanostructuring unlocks high performance of platinum single-atom catalysts for stable vinyl chloride production. Nat. Catal. 3, 376–385 (2020). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2021, corrected publication 2022 \n\n# Methods \n\nSynthesis of NC. A two-dimensional zeolitic imidazolate framework (2D-ZIF-8) was synthesized as the NC precursor. Typically, $\\mathrm{Zn(NO_{3})_{2}{\\cdot}6H_{2}O}$ $(12.75\\mathrm{g)}$ and 2-methylimidazole $(29.15\\mathrm{g})$ were dissolved separately in deionized water $(1,000\\mathrm{ml})$ . Then the two aqueous solutions were rapidly mixed and vigorously stirred for $2\\mathrm{h}$ . The resulting white precipitate was left undisturbed for $12\\mathrm{h}$ . The product was collected by centrifugation, then washed with water and ethanol, and subsequently dried at $80^{\\circ}\\mathrm{C}$ overnight. To prepare NC, the 2D-ZIF-8 $(5\\mathrm{g)}$ was mixed with KCl $(100\\mathrm{g})$ in deionized water $(400\\mathrm{ml})$ and then dried under rotary evaporation. After drying ( $120^{\\circ}\\mathrm{C}$ overnight), the KCl intercalated powder was heated to $700^{\\circ}\\mathrm{C}$ (heating rate, $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1},$ for $5\\mathrm{h}$ in a nitrogen flow. The product was washed with hydrochloric acid (2 M), deionized water and ethanol, then dried at $80^{\\circ}\\mathrm{C}$ overnight. \n\nSynthesis of $\\mathbf{Ni}_{\\mathbf{\\imath}}/\\mathbf{NC}.$ . To achieve $30\\mathrm{wt\\%}$ metal feeding, ${\\mathrm{NiCl}}_{2}{\\cdot}6{\\mathrm{H}}_{2}\\mathrm{O}$ $\\mathrm{\\dot{1}74m g)}$ and NC $(100\\mathrm{mg})$ were dispersed in $20\\mathrm{ml}$ ethanol solution, sonicated for $10\\mathrm{min}$ , and dried first by rotary evaporation and then in an oven at $80^{\\circ}\\mathrm{C}$ . For low-temperature annealing, the powder was heated to $300^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}.$ ) for 5 h in a nitrogen flow. After thorough washing using a water–ethanol mixture, the dried powders $(80^{\\circ}\\mathrm{C})$ were subjected to a high-temperature annealing at $550^{\\circ}\\mathrm{C}$ (heating rate, $2^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ ) for $5\\mathrm{h}$ in a nitrogen flow. \n\nSynthesis of PCN. Bulk PCN was prepared by calcining dicyandiamide at $550^{\\circ}\\mathrm{C}$ (heating rate, $2.3^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ ) in a crucible for $^{3\\mathrm{h}}$ in static air. Exfoliated PCN was obtained via the thermal exfoliation at $500^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ ) for $^{5\\mathrm{h}}$ in static air. \n\nSynthesis of $\\mathbf{Ni_{\\mathrm{1}}/P C N}$ . To achieve $30\\mathrm{wt\\%}$ metal feeding, ${\\mathrm{NiCl}}_{2}{\\cdot}6{\\mathrm{H}}_{2}{\\mathrm{O}}$ $\\mathrm{.174mg}$ and PCN $(100\\mathrm{mg})$ were dispersed in ethanol solution $(20\\mathrm{ml})$ and sonicated for $10\\mathrm{min}$ , followed by rotary evaporation to dry. The oven-dried powder $(80^{\\circ}\\mathrm{C})$ was subsequently heated to $450^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}.$ ) for $^{5\\mathrm{h}}$ in a nitrogen flow. Using a water–ethanol mixture, the obtained powder was washed thoroughly and then dried in an oven at $80^{\\circ}\\mathrm{C}$ . Finally, the powders were heated to $550^{\\circ}\\mathrm{C}$ (heating rate, of $2^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ ) and kept for $^{5\\mathrm{h}}$ under the protection of a nitrogen flow. \n\nSynthesis of $\\mathbf{CeO}_{2}$ . $\\mathrm{Ce}(\\mathrm{CH}_{3}\\mathrm{COO})_{3}{\\cdot}x\\mathrm{H}_{2}\\mathrm{O}$ was heated in air at $350^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1})$ ) for $2\\mathrm{h}$ , then the temperature was increased to $600^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}.$ ) for 5 h. \n\nSynthesis of $\\mathbf{Ni_{1}}/\\mathbf{CeO_{2}}$ . To achieve $10\\mathrm{wt\\%}$ metal feeding, ${\\mathrm{NiCl}}_{2}{\\cdot}6{\\mathrm{H}}_{2}\\mathrm{O}$ $\\mathrm{(45.5mg)}$ and $\\mathrm{CeO}_{2}$ $\\mathrm{100mg)}$ were dispersed in ethanol solution $(20\\mathrm{ml})$ and sonicated for $10\\mathrm{min}$ , followed by rotary evaporation to remove the solvent. The powders were dried in an oven at $80^{\\circ}\\mathrm{C}$ and then heated to $300^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}.$ ) in static air. The obtained powders were washed thoroughly using a water–ethanol mixture and dried in an oven at $80^{\\circ}\\mathrm{C}$ . Finally, the powders are heated to $550^{\\circ}\\mathrm{C}$ (heating rate, of $1^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ ) and kept for $^{5\\mathrm{h}}$ under static air. \n\nSynthesis of $\\mathrm{Ni_{1}P d_{1}/N C.\\ N i C l_{2}{\\cdot}6H_{2}O}$ $24\\mathrm{mg})$ , $\\mathrm{PdCl}_{2}$ ( $20\\mathrm{mg})$ and NC $\\left(100\\mathrm{mg}\\right)$ were dispersed in $0.5\\mathrm{MHCl}$ solution $(20\\mathrm{ml})$ , sonicated for $10\\mathrm{{min}}$ and dried first by rotary evaporation and then in an oven at $80^{\\circ}\\mathrm{C}$ . For the low-temperature annealing, the powder was heated to $200^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}.$ ) for $^{5\\mathrm{h}}$ in a nitrogen flow. After thorough washing using dimethylsulfoxide (DMSO) and water, the dried powder $(80^{\\circ}\\mathrm{C})$ was subjected to a high-temperature annealing at $500^{\\circ}\\mathrm{C}$ (heating rate, $2^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ ) for $^{5\\mathrm{h}}$ in a nitrogen flow. \n\nSynthesis of $\\bf N i_{\\mathrm{1}}P d_{\\mathrm{1}}P t_{\\mathrm{1}}/N C$ . $\\mathrm{NiCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ ( $\\mathrm{20mg},\\$ ), $\\mathrm{PdCl}_{2}$ ( $\\mathrm{14mg)}$ , $\\mathrm{H}_{2}\\mathrm{PtCl}_{2}{.}6\\mathrm{H}_{2}\\mathrm{O}$ $(42\\mathrm{mg})$ and NC $\\left(100\\mathrm{mg}\\right)$ were dispersed in $0.5\\mathbf{M}$ HCl solution $(20\\mathrm{ml})$ , sonicated for $10\\mathrm{min}.$ , and dried by rotary evaporation and in an oven $(80^{\\circ}\\mathrm{C})$ . For the low-temperature annealing, the powder was heated to $200^{\\circ}\\mathrm{C}$ (heating rate, $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1})$ ) for $^{5\\mathrm{h}}$ in a nitrogen flow. After thorough washing with DMSO and water, the dried powder $(80^{\\circ}\\mathrm{C})$ was subjected to a high-temperature annealing at $500^{\\circ}\\mathrm{C}$ (heating rate, $2^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ ) for $^{5\\mathrm{h}}$ in a nitrogen flow. \n\nThe synthesis of other metal UHD-SACs follows the same steps by using the appropriate metal precursor, solvent, annealing temperatures and atmospheres (Supplementary Table 1). \n\nAutomated synthesis. The automated catalyst preparation was carried out in a Chemspeed Flex Isynth synthesis platform. The distinct carriers $(100\\mathrm{mg})$ were dispensed into the reaction block using an in-built extruder for precision dosing. After addition of ethanol (5 ml, ACS reagent grade, Millipore Sigma), the nickel precursor solution $(\\mathrm{NiCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O},$ $99.9\\%$ purity, Sigma Aldrich, in ethanol) of the desired molarity was added gravimetrically $(5\\mathrm{ml})$ . The resulting slurries were shaken $(300{\\mathrm{~r.p.m.}})$ for $30\\mathrm{min}$ , and the solvent was subsequently removed under vacuum $(80^{\\circ}\\mathrm{C},7\\mathrm{h}),$ . The dry powders were transferred to ceramic boats and annealed in flowing nitrogen $(20\\mathrm{ml}\\mathrm{min}^{-1}),$ ) at $300^{\\circ}\\mathrm{C}$ (ramp, $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ ). The annealed powders were subsequently washed (water:ethanol, 1:1, $15\\mathrm{ml}$ ) and vacuum-filtered (frit pore diameter, $16{-}40\\upmu\\mathrm{m}\\mathrm{,}$ ) three times and then dried $(80^{\\circ}\\mathrm{C},$ vacuum) in the synthesis robot. Finally, the powders were subjected to a second annealing step to $550^{\\circ}\\mathrm{C}$ (ramp, $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ ) in a flowing nitrogen atmosphere. \n\nMaterial characterization. Wide-angle X-ray diffraction patterns were collected on a Bruker D8 Focus powder X-ray diffractometer using Cu Kα radiation $(40\\mathrm{kV},$ $40\\mathrm{mA}$ ) at room temperature. Transmission electron microscopy (TEM) images were obtained with an FEI Titan 80-300 S/TEM or a Talos F200X instrument, both operated at $200\\mathrm{kV}.$ ADF-STEM imaging was carried out in an aberration-corrected JEOL ARM-200F system equipped with a cold field emission gun operating at $60\\mathrm{kV.}$ The images were collected with a half-angle range from ${\\sim}81$ to 280 mrad, and the convergence semiangle was set at $\\sim30$ mrad. X-ray photoelectron spectroscopy (XPS) measurements were carried out in a custom-designed ultrahigh-vacuum system with a base pressure lower than $2\\times10^{-10}$ mbar. Al $\\operatorname{K}\\upalpha$ (photon energy $1,486.7\\mathrm{eV}$ ) was used as the excitation source for XPS. The metal loadings in all the samples were measured by ICP-AES. $\\Nu_{2}$ isotherms were measured at $-196^{\\circ}\\mathrm{C}$ using a Quantachrome Instruments AutosorbiQ (Boynton Beach, FL). Fourier transform infrared spectra for CO adsorption were obtained at $25^{\\circ}\\mathrm{C}$ on a Bruker Equinox 55 spectrometer equipped with a mercury cadmium telluride detector. The XANES and EXAFS measurements were carried out at the XAFCA beamline of the Singapore Synchrotron Light Source (SSLS)41 and Shanghai Synchrotron Radiation Facility (SSRF), Shanghai Institute of Applied Physics (SINAP). A Si (111) double-crystal monochromator was used to filter the X-ray beam. Metal foils were used for the energy calibration, and all samples were measured under transmission mode at room temperature. EXAFS oscillations $\\chi(\\boldsymbol{k})$ were extracted and analysed using the Demeter software package42. \n\nQuantum-theoretical calculations. All calculations were performed using DFT within the spin‐polarized Kohn–Sham formalism implemented in the Vienna Ab initio Simulation Package43. The projector augmented‐wave method44,45 was used to represent the core electron states. The generalized gradient approximation with Perdew–Burke–Ernzerhof exchange-correlation functional46 and a plane wave representation for the wave function with a cut‐off energy of $500\\mathrm{eV}$ were used. Lattice parameters and all atoms were fully relaxed for total energy optimization. The convergence criterion for the maximum residual force and energy was set to $0.02\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ and $10^{-5}\\mathrm{eV},$ respectively, during the structure relaxation. A $6\\times6\\times1$ supercell was used to model the graphene surface and the Brillouin zones were sampled by a Monkhorst–Pack $k$ ‐point mesh with a $3\\times3\\times1~k$ ‐point grid. A $15\\mathrm{\\AA}$ vacuum space was set, in the $z$ -direction, to avoid periodic image interactions. The transition states were searched using climbing image nudged elastic band and dimer methods47,48 and further confirmed by having only one imaginary vibrational frequency. \n\nElectrochemical tests using $\\mathbf{Ni}_{\\mathbf{\\imath}}/\\mathbf{NC}.$ All $\\mathrm{CO}_{2}$ reduction experiments were performed using a three-electrode system connected to an electrochemical workstation (CHI 760E). Ag/AgCl with saturated KCl solution and platinum mesh served as the reference electrode and the counterelectrode, respectively. The electrocatalyst was prepared by mixing the catalyst powder $(2\\mathrm{mg})$ , ethanol (1 ml) and Nafion solution $(10\\upmu\\mathrm{l},5\\mathrm{wt\\%})$ ) followed by sonication for 1 h. Then, the catalyst suspension $(100\\upmu\\mathrm{l})$ was dropped onto a dry carbonfibre paper (AvCarb P75T, $0.5\\mathrm{cm}^{2},$ , yielding a loading of $0.4\\mathrm{mgcm^{-2}}$ . All potentials were calculated with respect to the RHE scale according to the Nernst equation $(E_{\\mathrm{RHE}}=E_{\\mathrm{Ag/AgCl}}+0.0591\\times\\mathrm{pH}+0.197\\mathrm{V},$ at $25^{\\circ}\\mathrm{C},$ . The electrolyte was $0.5\\mathrm{M}\\mathrm{KHCO_{3}}$ saturated with $\\mathrm{CO}_{2}$ and had a pH of 7.2. The products and Faradaic efficiency of $\\mathrm{CO}_{2}$ reduction were measured using chronoamperometry at each fixed potential in an H-type electrochemical cell separated by a Nafion 117 membrane. Before the measurement, the electrolyte was saturated by bubbling gaseous $\\mathrm{CO}_{2}$ with a flow rate of $20\\mathrm{ml}\\mathrm{min}^{-1}$ through the cell for $30\\mathrm{min}$ . \n\nAzide–alkyne cycloaddition using $\\mathbf{Cu_{\\mathrm{1}}/P C N}$ . Azide–alkyne cycloaddition was carried out in a $20\\mathrm{ml}$ glass tube with $\\mathrm{Cu}_{\\mathrm{1}}/\\mathrm{PCN}$ catalyst $(2\\mathrm{mol}\\%\\mathrm{Cu})$ ), $0.5\\mathrm{mmol}$ of 4-ethynylanisole, $1.5\\mathrm{mmol}$ of benzyl azide and $\\mathrm{8ml}$ of a 1:1 water/tert-butanol mixture and stirred at $60^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . $^{1}\\mathrm{H}$ NMR and $^{13}\\mathrm{C}$ NMR spectra were recorded on Bruker ${500}\\mathrm{MHz}$ spectrometer using residue solvent peaks as internal standards (DMSO- $.d_{6})$ . GC yield was determined by using decane as an internal standard. \n\nAcetylene hydrochlorination using $\\bf{P t_{\\mathrm{1}}/N C}$ Using a previously reported protocol40, the $\\mathrm{Pt_{\\mathrm{1}}/N C}$ catalyst powder ( $\\mathrm{\\dot{2}00m g)}$ was loaded in a quartz reactor and preheated to the reaction temperature $(200^{\\circ}\\mathrm{C})$ in flowing helium at ambient pressure. Upon switching to the reaction gas mixture (total flow, $15\\mathrm{cm}^{3}\\mathrm{min}^{-1}$ , 40 $\\mathbf{vol\\%}$ $\\mathrm{C}_{2}\\mathrm{H}_{2}$ $44\\mathrm{vol}\\%$ HCl, $16\\mathrm{vol\\%}$ Ar, balance He), the reactor outlet was sampled via gas chromatography–mass spectrometry (GC 7890B, MSD 5977 A, Agilent) every $58\\mathrm{min}$ . The VCM yield was computed from the outlet VCM molar flow divided by the inlet acetylene flow. \n\n# Data availability \n\nAll data that support the findings of this study have been included in the main text and Supplementary Information. Any additional materials and data are available from the corresponding author upon reasonable request. \n\n# References \n\n41.\tDu, Y. et al. XAFCA: a new XAFS beamline for catalysis research. $J.$ Synchrotron Radiat. 22, 839–843 (2015). \n\n42.\tRavel, B. & Newville, M. ATHENA, ARTEMIS, HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 12, 537–541 (2005). \n43.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169 (1996). \n44.\tBlöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953 (1994). \n45.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758 (1999). \n46.\tPerdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865 (1996). \n47.\tHenkelman, G. & Jónsson, H. A dimer method for finding saddle points on high dimensional potential surfaces using only first derivatives. J. Chem. Phys. 111, 7010–7022 (1999). \n48.\tHenkelman, G., Uberuaga, B. P. & Jónsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000). \n\n# Acknowledgements \n\nJ. Lu acknowledges support from MOE grant (R-143-000-B47-114), the Ministry of Education (Singapore) through the Research Centre of Excellence program (Award EDUN C-33-18-279-V12, Institute for Functional Intelligent Materials) and the National University of Singapore Flagship Green Energy Program (R-143-000-A55-646). X.Z. acknowledges support from a Presidential Postdoctoral Fellowship, Nanyang Technological University, Singapore via grant 03INS000973C150. S.M., D.F.A., and J.P.-R. acknowledge funding from the NCCR Catalysis, a National Centre of Competence in Research funded by the Swiss National Science Foundation. Jun Li acknowledges financial support by the National Natural Science Foundation of China (grant number 22033005) and the Guangdong Provincial Key Laboratory of Catalysis (2020B121201002). Computational resources were supported by the Center for \n\nComputational Science and Engineering (SUSTech) and Tsinghua National Laboratory for Information Science and Technology. We would like to acknowledge the Facility for Analysis, Characterization, Testing and Simulation, Nanyang Technological University, Singapore, for use of their electron microscopy facilities. \n\n# Author contributions \n\nX.H. and J. Lu conceived and designed the experiments. J.P.-R. conceived the automated synthesis protocol. J. Lu and J.P.-R. supervised the project and organized the collaboration. X.H. performed materials synthesis. S.M. and D.F.A performed automated synthesis. X.H. and T.S. performed the activity test. S.X. performed the XAFS measurement. X.Z., H.X. and D.K. performed the electron microscopy experiments and data analysis. C.S. helped to perform the CO-DRIFTS measurements. Jing Li performed the XPS measurements. Z.L. performed the nitrogen sorption measurements. H.Y. and Y.C. performed the X-ray diffraction measurements. K.H. and Jun Li carried out theoretical calculations. X.H., S.M., J.P.-R., Jun Li and J. Lu co-wrote the manuscript. All authors discussed and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41565-021-01022-y. Correspondence and requests for materials should be addressed to Xiaoxu Zhao, Jun Li, Javier Pérez-Ramírez or Jiong Lu. Peer review information Nature Nanotechnology thanks Abhaya Datye and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at www.nature.com/reprints. " + }, + { + "id": "10.1038_s41467-021-27698-3", + "DOI": "10.1038/s41467-021-27698-3", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-27698-3", + "Relative Dir Path": "mds/10.1038_s41467-021-27698-3", + "Article Title": "Single-atom Cu anchored catalysts for photocatalytic renewable H2 production with a quantum efficiency of 56%", + "Authors": "Zhang, YM; Zhao, JH; Wang, H; Xiao, B; Zhang, W; Zhao, XB; Lv, TP; Thangamuthu, M; Zhang, J; Guo, Y; Ma, JN; Lin, LN; Tang, JW; Huang, R; Liu, QJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Single-atom catalysts anchoring offers a desirable pathway for efficiency maximization and cost-saving for photocatalytic hydrogen evolution. However, the single-atoms loading amount is always within 0.5% in most of the reported due to the agglomeration at higher loading concentrations. In this work, the highly dispersed and large loading amount (>1 wt%) of copper single-atoms were achieved on TiO2, exhibiting the H-2 evolution rate of 101.7 mmol g(-1) h(-1) under simulated solar light irradiation, which is higher than other photocatalysts reported, in addition to the excellent stability as proved after storing 380 days. More importantly, it exhibits an apparent quantum efficiency of 56% at 365 nm, a significant breakthrough in this field. The highly dispersed and large amount of Cu single-atoms incorporation on TiO2 enables the efficient electron transfer via Cu2+-Cu+ process. The present approach paves the way to design advanced materials for remarkable photocatalytic activity and durability. In this work, the highly dispersed and large loading amount (>1 wt%) of copper single-atoms were achieved on TiO2, resulting into an apparent quantum efficiency of 56% at 365 nm, in addition to an excellent thermal stability as proved after storing 380 days.", + "Times Cited, WoS Core": 417, + "Times Cited, All Databases": 440, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000781259400001", + "Markdown": "# Single-atom Cu anchored catalysts for photocatalytic renewable H2 production with a quantum efficiency of 56% \n\nYumin Zhang 1,5, Jianhong Zhao1,5, Hui Wang2,5, Bin Xiao1,5, Wen Zhang3, Xinbo Zhao1, Tianping Lv1, Madasamy Thangamuthu2, Jin Zhang1, Yan Guo3, Jiani Ma3, Lina Lin4, Junwang Tang $\\textcircled{1}$ 2✉, Rong Huang 4✉ & Qingju Liu1✉ \n\nSingle-atom catalysts anchoring offers a desirable pathway for efficiency maximization and cost-saving for photocatalytic hydrogen evolution. However, the single-atoms loading amount is always within $0.5\\%$ in most of the reported due to the agglomeration at higher loading concentrations. In this work, the highly dispersed and large loading amount $(>1\\mathrm{wt\\%})$ of copper single-atoms were achieved on $\\mathsf{T i O}_{2},$ exhibiting the ${\\sf H}_{2}$ evolution rate of 101.7 mmol $\\displaystyle{\\mathrm{g}}^{-1}{\\mathsf{h}}^{-1}$ under simulated solar light irradiation, which is higher than other photocatalysts reported, in addition to the excellent stability as proved after storing 380 days. More importantly, it exhibits an apparent quantum efficiency of $56\\%$ at $365\\mathsf{n m}$ , a significant breakthrough in this field. The highly dispersed and large amount of $\\mathsf{C u}$ single-atoms incorporation on $\\mathsf{T i O}_{2}$ enables the efficient electron transfer via $\\mathsf{C u}^{2+}\\ –\\mathsf{C u}^{+}$ process. The present approach paves the way to design advanced materials for remarkable photocatalytic activity and durability. \n\nHyprdoromgiesin gevolaultieornaftriovem ssotlrart-edgryivenforwatefrutsuprleittinegneirsgya employed5 and is still used as a benchmark photocatalyst for water splitting6 as it is low cost and more importantly, extremely stable and high efficiency under UV. Even so, $\\mathrm{TiO}_{2}$ still suffers from high charge-carrier recombination and sluggish proton reduction kinetics7. Hence, addressing these issues is essential to enhance the charge separation and to promote $\\mathrm{H}_{2}$ fuel synthesis. Several strategies such as doping, defect engineering, heterojunction formation, morphology variation, etc., have been reported to reduce the charge-carrier recombination and improve the $\\mathrm{H}_{2}$ evolution8. Amongst them, loading a cocatalyst on the surface of the $\\mathrm{TiO}_{2}$ is proved as an appropriate approach to enhance the charge separation through the established metalsemiconductor Schottky junction, which not only extracts the photogenerated electrons but also dramatically reduces the energy barrier for proton reduction. \n\nNoble metals such as Pt, Au, and Pd are commonly used as cocatalysts in photocatalysis due to their low activation energy and efficient charge separation. For example, Pt loading improved $\\mathrm{TiO}_{2}$ for $\\mathrm{H}_{2}$ production by a factor of $12^{\\mathfrak{9}}$ . However, they are not only rare elements and hence high cost but also the efficiency achieved is still moderate. Recently, there were many studies on earth-abundant transition metals (e.g., Cu, Ni, Co, and Fe) to substitute these noble metals as a suitable alternative for photocatalysis10–13. On the other hand, all these cocatalyst-loaded photocatalysts still struggle to achieve a breakthrough inefficiency due to the low-atom utilization while the cocatalysts are in their bulk composition. Very recently, single-atom catalysts (SACs) have been highly focused due to maximizing the reaction active sites, resembling the homogeneous catalysis14,15. The isolated and active metal atoms anchored onto the photocatalysts offer more water-molecule adsorption and active sites. So far, SACs loaded $\\mathrm{TiO}_{2}$ have been investigated for $\\mathrm{H}_{2}$ evolution6,16, $\\mathrm{CO}_{2}$ reduction17, and dye degradation18. However, the aggregation of SACs is inevitable during the catalytic reaction due to their high surface energy or leaching due to the unstable anchoring as the majority were synthesized by post-treatment (e.g., impregnation approach)19–21. More importantly, the larger the percentage of SACs, the higher the activity, whereas to load higher than $0.5\\mathrm{wt\\%}$ of SACs is very challenging as the majority of the studies reported a limited amount of SACs (usually near $0.1{-}0.3\\ \\mathrm{wt}\\ \\%)^{1,2}$ onto the high surface area of substrates and it is difficult to control and reproduce $^{\\mathbf{4},22,23}$ . Hence, obtaining the highly dispersed and high concentration of SACs remains to be the main bottleneck in photocatalytic $\\mathrm{H}_{2}$ production. \n\nThe easily-changed valence states of $\\mathtt{C u}$ nanoparticles have been a promising candidate for efficient charge separation and transfer, leading to higher catalytic performance compared to even noble metal loaded $\\mathrm{TiO}_{2}$ samples24–27. A recent wrap-bakepeel process, using $\\mathrm{SiO}_{2}@\\mathrm{M}/\\mathrm{TiO}_{2}@\\mathrm{SiO}_{2}$ as the intermediate following NaOH etching to produce Cu SACs, has achieved a benchmark apparent quantum efficiency (AQE) of $45.5\\%$ at $340\\mathrm{nm}^{6}$ . It is due to the reduction and regeneration of the active sites during the catalytic cycle. Such a success stimulates us to investigate a more efficient strategy to stabilize Cu SACs and more importantly to generate an in-situ self-heal approach for continuous $\\mathrm{H}_{2}$ production from water, thus no need for the regeneration step. To achieve this, the intact interaction between the single atoms and the support is crucial to obtain atomically evenly-dispersed Cu28,29. \n\nHere, we have developed a bottom-up approach, which is different from the post-treatment approach reported in the literature including the very recent report to obtain evenly dispersed SACs on the substrate6,30. The metal-organic framework (MOF) \n\nMIL-125 was first synthesized using it as a precursor. Then metal ions were anchored into the MOF MIL-125 to generate a metaloxygen-titanium bond, which is the key to ensuring uniformly immobilized metal SAC on the final catalysts31–33. Finally, the metal-MIL-125 intermediates were calcined to synthesize the final photocatalysts. This new strategy ensures atomic dispersion of metal cocatalyst and enables to achieve a higher loading amount ${\\sim}1.5~\\mathrm{wt\\%}$ . The optimised sample shows the photocatalytic $\\mathrm{H}_{2}$ evolution rate of $101.7\\mathrm{mmol}\\mathbf{\\bar{g}}^{-1}\\mathbf{h}^{-1}$ (or $2.{\\dot{0}}3\\ \\mathrm{mmol}\\mathrm{h}^{-1}$ ). To make a straightforward comparison with the reported $\\mathrm{H}_{2}$ evolution rate, we converted it to the widely used unit of mmol per unit mass per unit time under simulated solar light irradiation, somewhat higher than the best photocatalyst $\\mathrm{PtSA-TiO}_{2}$ $(95.3\\mathrm{mmol}\\mathrm{g}^{-\\top}\\mathrm{h}^{-1})$ . The $\\mathrm{CuSA-TiO}_{2}$ exhibits AQE of $56\\%$ at $365\\mathrm{nm}$ irradiation, exceeding all the state-of-the-art $\\mathrm{TiO}_{2}$ -based photocatalysts (AQE of 4.3–45.5%6,34,35). \n\n# Results \n\nPhotocatalytic properties of $\\mathbf{CuSA-TiO}_{2}$ . First, four sets of experiments were performed for AQE optimisation and the detailed conditions were presented in Supplementary Fig. 1. The AQE results of $\\mathrm{CuSA-TiO}_{2}$ under different wavelength light irradiation ( $365\\mathrm{nm}$ , $385\\mathrm{nm}$ , $420\\mathrm{nm}$ , and $520\\mathrm{nm},$ ) are shown in Supplementary Fig. 1a. It indicates a decrease with increasing the wavelength followed by a slight increase at $520\\mathrm{nm}$ due to the Cuinduced defects absorption (Supplementary Fig. 14). Also, the AQE measurement using different amounts of the photocatalyst was carried out, indicating the $\\mathrm{CuSA-TiO}_{2}$ mass can affect AQE (Supplementary Fig. 1b). The changing trend is likely due to the fact that the higher photocatalyst mass would scatter more light when it is over $50\\mathrm{mg}$ . With the 2:1 methanol:water ratio, the AQE at different light intensities was also tested (Supplementary Fig. 1d). The AQE result collected from various ratios of methanol: water indicates that methanol facilitates the $\\mathrm{H}_{2}$ evolution from water. When the light intensity increases from $200\\mathrm{W}/\\mathrm{m}2$ to $500\\mathrm{W}/\\mathrm{m}2$ , the AQE shows a slight increase. Hence, The $\\mathrm{CuSA-TiO}_{2}$ represents an efficient and low-cost photocatalyst for continuous renewable $\\mathrm{H}_{2}$ production. \n\nFirst, the reference MIL-125 derived $\\mathrm{TiO}_{2}$ was tested for photocatalytic $\\mathrm{H}_{2}$ evolution under Xe lamp using methanol as a hole-scavenger. Fig. 1a shows the $\\mathrm{H}_{2}$ evolution activities of $\\mathrm{TiO}_{2}$ and other photocatalysts loaded with different metals such as Co, Ni, Fe, Mn, Zn, and Pt $(0.75\\mathrm{wt\\%}$ metal to precursor MIL$125\\mathrm{(Ti_{v})}$ before sintering). The samples were further analysed to determine the real amount of metal on $\\mathrm{TiO}_{2}$ by an inductively coupled plasma test (Supplementary Table 1). All of them produce $\\mathrm{H}_{2}$ higher than that of pristine $\\mathrm{TiO}_{2}$ $\\left(4.2\\mathrm{mmol}\\mathrm{g}^{-1}\\mathrm{h}^{-1}\\right)$ except Zn and $\\mathrm{Mn}{\\cdot}\\mathrm{TiO}_{2}$ , revealing that the metal single-atoms introduction plays a crucial role in the $\\mathrm{H}_{2}$ evolution reaction. The activity order is $\\mathrm{CuSA-TiO}_{2}$ $(101.7{\\mathrm{mmol}}\\mathrm{g}^{-1}\\mathrm{h}^{-1})>{\\mathrm{PtSA}}{\\mathrm{-TiO}}_{2}$ $(95.3\\mathrm{\\dot{m}m o l\\ g^{-1}h^{-1}})>\\mathrm{FeSA\\–TiO_{2}}$ ( $19.1\\ \\mathrm{mmol}\\ \\mathrm{g}^{-1}\\mathrm{h}^{-1})>\\mathrm{NiSA}-$ $\\mathrm{TiO}_{2}$ $(12.0\\mathrm{\\dot{m}m o l\\mathbf{g}^{-1}h^{-1}})$ > CoSA-TiO2 $(8.2\\mathrm{{\\dot{m}m o l}g^{-1}h^{-1}})\\ >$ $\\mathrm{TiO}_{2}$ $\\mathrm{(4.2\\mmol{g}^{-1}{h}^{-1})\\ >\\ M n S A{-}T i O_{2}}$ $(2.3\\mathrm{mmol}\\bar{\\mathrm{g}}^{-1}\\mathrm{h}^{-1})\\ >$ $\\mathrm{ZnSA-TiO}_{2}$ $(2.2\\mathrm{\\mmol{g}^{-1}{h}^{-1}},$ . Interestingly, the $\\mathrm{CuSA-TiO}_{2}$ evolve higher $\\mathrm{H}_{2}$ than the benchmark $\\mathrm{Pt}$ -loaded $\\mathrm{TiO}_{2}$ . The higher $\\mathrm{H}_{2}$ evolution rate observed for the $\\mathrm{CuSA-TiO}_{2}$ is due to the highly dispersed Cu SACs as proved later and their charge separation and catalytic effect as discussed below. Moreover, the larger loading amount of Cu SACs $(1.5\\mathrm{wt\\%})$ compared with Pt SACs $(0.64\\%)$ allows maximum utilization of the active sites to realize such an amazing activity, which might be ascribed to the easier coordination of dissociated $\\mathrm{Cu}^{2+}$ with oxygen compared with $\\mathrm{[PtCl_{4}]^{2-}}$ . Furthermore, the weight percentage of the $\\mathtt{C u}$ attached to the $\\mathrm{TiO}_{2}$ was optimized as shown in Fig. 1b, and the highest $\\mathrm{H}_{2}$ evolution activity is obtained on ca. $1.5\\mathrm{wt\\%}$ $\\mathrm{CuSA-TiO}_{2}$ (Supplementary Table 1). More importantly, an unprecedented AQE of $56\\%$ at $365\\mathrm{nm}$ has been achieved on the ca. $1.5\\mathrm{wt\\%}$ $\\mathrm{CuSA-TiO}_{2},$ a new record. These results indicate that both the large atomic weight percentage and interaction of $\\mathrm{Cu}$ with $\\mathrm{TiO}_{2}$ are crucial for the extraordinary $\\mathrm{H}_{2}$ evolution. \n\n![](images/849f70877eb6af6caf538846c0b7a2396f70990111c473ce30bac28450811afd.jpg) \nFig. 1 Photocatalytic $\\Hat{\\boldsymbol{\\mathsf{H}}}_{2}$ evolution performance and the formation of Cu SAC in the Ti lattice of $\\mathbf{\\Tilde{i}0_{2}}$ . The photocatalytic ${\\sf H}_{2}$ evolution rate of (a) $\\mathsf{T i O}_{2}$ (non) and ${\\mathsf{M}}{\\mathsf{-T i O}}_{2}$ derived from M-MiL-125 $\\mathrm{\\Delta}\\mathrm{Ti}_{\\mathrm{v}})$ . b $\\mathsf{T i O}_{2}$ and $\\mathsf{T i O}_{2}$ loaded with different ratios of Cu SACs. c The photocatalytic activity of the ca. $1.5\\mathrm{wt\\%}$ $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ for six cyclic water splitting experiments and the last run is the activity of the sample after storing in the lab for 380 days. d The photocatalytic ${\\sf H}_{2}$ evolution mechanism on $1.5\\mathrm{wt\\%}$ CuSA- $\\cdot\\mathsf{T i O}_{2}$ . e The corresponding schematic representation of the formation of copper SAC in the Ti lattice of $T_{\\mathsf{i O}_{2},\\mathsf{\\Lambda}}$ together with the related images. \n\nWhile increasing the $\\mathrm{Cu}$ atoms amount beyond ca. $1.5\\mathrm{wt\\%}$ , the decreased photocatalytic activity was observed. It is perhaps due to the limited pores available for higher Cu precursor anchoring, leading to screening the irradiated light. To show the experimental evidence of excessive $\\mathrm{Cu}$ accumulation, we measured the HRTEM for $2.57\\mathrm{wt\\%}$ $\\mathrm{CuSA-TiO}_{2}$ and $1.5\\mathrm{wt\\%}$ $\\mathrm{CuSA-TiO}_{2}$ , compared with pristine $\\mathrm{TiO}_{2}$ . Supplementary Figure 10 shows the patterns of $1.5\\mathrm{wt}\\%\\mathrm{CuSA}{\\cdot}\\mathrm{TiO}_{2}$ , which is similar to the pristine $\\mathrm{\\bar{TiO}}_{2}$ . While clear patterns of Cu nanoparticles (about $2{\\-}{-}5\\mathrm{nm}$ ) observed in $2.57\\mathrm{wt\\%}$ $\\mathrm{CuSA-TiO}_{2}$ (Supplementary Fig. 2) are marked with arrows and circles. Hence, the poor activity observed for the Cu atom amount beyond ca. $1.5\\mathrm{wt\\%}$ might be ascribed to the Cu accumulation, which inhibits the incident light from reaching the photocatalyst surface. \n\nThe long-term stability and reproducibility of the $\\mathrm{H}_{2}$ evolution using the optimised $\\mathrm{CuSA-TiO}_{2}$ were analyzed by the six consecutive photocatalytic water-splitting experiments under simulated solar light irradiation (Fig. 1c). In addition, the longterm experiment i.e., 20 days were also carried out for the stability test and results are shown in Supplementary Fig. 3. The sample was kept in the solution for each cycle, overall lasting for 20 days. The sample exhibits similar activity. Moreover, the photocatalyst after the long-term test was characterized by the ICP-AES, listed in Supplementary Table 1. The $\\mathtt{C u}$ amount of $\\mathrm{CuSA-TiO}_{2}$ after the long-term test was estimated to be $1.54\\mathrm{wt\\%}$ , which is similar to that of the fresh sample. The long-term activity and ICP-AES result further confirm the long-term stability and reproducibility of $\\mathrm{CuSA-TiO}_{2}$ . \n\nIt can be seen that no noticeable decrease was observed in the $\\mathrm{H}_{2}$ evolution rate, suggesting that the prepared sample is highly stable and the results are reproducible. Furthermore, the photocatalytic activity of the $1.5\\mathrm{wt\\%}\\mathrm{CuSA\\mathrm{-}T i O}_{2}$ after 380-daystorage in the lab was tested and we found that it remains the same as of the freshly prepared sample (Fig. 1c). Supplementary Table 2 lists the very recent progress on $\\mathrm{TiO}_{2}$ -based photocatalysts for water splitting, indicating $\\mathrm{TiO}_{2}$ is still a highly attractive photocatalyst. Compared with these reports, one can see that our $\\mathrm{CuSA-TiO}_{2}$ sample is two times more active than the reported ca $1\\mathrm{wt\\%}$ Pt atom- $\\mathrm{\\cdotTiO}_{2}$ and six times better than the recently reported ${\\mathrm{Cu-TiO}}_{2}$ in terms of specific mass evolution rate. Another finding is that it presents a record AQE of $56\\%$ , which is also more stable $(>30\\mathrm{h})$ . Such enhancement is believed to be due to the unique Cu states on $\\mathrm{TiO}_{2}$ prepared by our preencapsulation synthesis approach. \n\n![](images/6b8ee54df9f42f28dc90719b60ba2d875e0f157809083476ffdd2fb10518041c.jpg) \nFig. 2 Structure and micromorphology of $\\mathbf{CuSA-TiO_{2}}$ . a The XRD images of MIL-125, Cu-MIL-125, $\\mathsf{T i O}_{2},$ and $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ . b HAADF STEM raw image of $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ . (Insert: low magnification TEM images of CuSA- $\\cdot\\mathsf{T i O}_{2}\\dot{\\mathsf{\\Omega}}$ ). c Filtered HAADF STEM image from the area highlighted with a red rectangle in b and the corresponding line scan profiles. d–f Line 1, Line 2, and Line 3 marked in Fig. c. g STEM-EDS mapping of Ti, $\\scriptstyle\\ O,$ and $\\mathsf{C u}$ of the fresh $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ . \n\nMorphology and structure characterization of $\\mathbf{CuSA-TiO}_{2}$ . To explore the science behind the outstanding photocatalytic performance of $1.5\\mathrm{wt\\%}$ $\\mathrm{CuSA-TiO}_{2}$ (named $\\mathrm{\\bar{C}u S A-T i O}_{2}^{\\cdot}$ subsequently), a series of studies were performed. Firstly, the $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) patterns of the as-prepared MIL- $125(\\mathrm{Ti}_{\\mathrm{v}})$ were observed as shown in Fig. 2a, which agrees well with the earlier report36, suggesting that the MOF precursor was prepared successfully. The precursor MOF $(\\mathrm{MIL}{-}125(\\mathrm{Ti}_{\\mathrm{v}}))$ was also observed with a regular cake-like morphology, the high specific surface area (SSA, $1\\breve{3}61\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , Supplementary Fig. 4a–b) and favorable pores31, which facilitates the Cu ions anchoring, leading to the formation of $\\mathrm{CuSA-TiO}_{2}$ with the SSA of $294{\\mathrm{m}}^{2}{\\mathrm{g}}^{-1}$ (Supplementary Fig. 4c–d). After incorporating the Cu in MIL- $125(\\mathrm{Ti}_{\\mathrm{v}})$ , the XRD pattern is nearly identical to that of the pristine MIL$125(\\mathrm{Ti}_{\\mathrm{v}})$ , indicating that $\\dot{\\mathrm{Cu}}^{2+}$ is encapsulated into the framework of MIL-125( $\\mathrm{\\Ti_{v})}$ with high dispersity38. The same conclusion can be drawn from the sintered samples $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}\\mathrm{,}$ . Furthermore, the addition of $\\mathrm{Cu}$ does not change the phase of $\\mathrm{TiO}_{2}{}^{37}$ , so that there is only an anatase crystal structure existing in the $\\mathrm{CuSA-TiO}_{2}$ . Furthermore, the Zeta potential test of MIL$125\\mathrm{(Ti_{v})}$ indicates a potential value of $-40.{\\bar{6}}\\mathrm{mV}$ (Supplementary Fig. 5), that means the dispersion of $\\mathrm{MIL}{-}125(\\mathrm{Ti}_{\\mathrm{v}})$ in water is stable with such large negative charges. More importantly, the positive ${\\mathrm{Cu}}^{2+}$ ions can be readily electrostatically bonded to the Ti vacancies of MIL-125 $\\mathrm{\\Ti_{v})}$ via M-O-Ti structure after adding the $\\mathrm{CuCl}_{2}$ precursor aqueous solution. The Cu-encapsulated MIL-125 $\\mathrm{\\Ti_{v})}$ $\\mathrm{(Cu-MIL-}\\bar{1}25\\mathrm{(Ti_{v}))}$ was then sintered at $450^{\\circ}\\mathrm{C}$ to form Cu SACs on $\\mathrm{TiO}_{2}$ $\\mathrm{(CuSA–TiO_{2})}$ . Such catalyst synthesis temperature was derived from the thermogravimetric differential thermal (TG-DTA) measurement (Supplementary Fig. 6). When the temperature is higher than $450^{\\circ}\\mathrm{C}$ (black curve), the weight loss tends to be stable, which might be explained by the removal of organic ligands and stabilisation of $\\mathtt{C u}$ species at that temperature. Moreover, the actual ratio of Cu SACs on $\\mathrm{TiO}_{2}$ is up to $1.5\\mathrm{wt\\%}$ , indicating the proposed strategy not only ensures the highly dispersed Cu anchoring but also achieves a rather large loading amount of Cu SACs. \n\nFigure 1e shows the synthesis of the final catalyst from the intermediate MOF. The cake-shaped morphology of the intermediates (Supplementary Figure 7) was collapsed to form $\\mathrm{TiO}_{2}$ or $\\mathrm{CuSA-TiO}_{2}$ with clear lattice fringes, upon calcination of the $\\mathrm{MIL}{-}125(\\mathrm{Ti}_{\\mathrm{v}})$ , or $\\mathrm{Cu-MIL}{\\cdot}125(\\mathrm{Ti_{v}})$ . Supplementary Figs. 8 and 9 show the transmission electron microscopy (TEM) image of the MIL-125 derived $\\mathrm{TiO}_{2}$ and the $\\mathrm{CuSA-TiO}_{2}$ , respectively. The collapsed morphology has significant merits as it can allow more Cu atoms exposure. The incorporation of Cu atoms on the Ti vacancy sites in the intermediate MOF is important as indicated in Fig. 1e, which not only stabilises Cu ions but also ensures single atom distribution of $\\mathtt{C u}$ in the prepared photocatalysts. This was investigated by the high-angle annular dark-field (HAADF) STEM (Fig. 2b–c, Supplementary Figs. 10–12). The bright contrast spots can be clearly seen only on the Ti atomic row. These bright spots are attributed to Cu as indicated in Supplementary Fig. 11f–i, confirming that Cu atoms are exclusively present in the Ti vacancies and other Cu configurations (e.g., clusters or nanoparticles) are not detected8. The line scan profiles marked with three blue lines randomly selected are shown in Fig. 2d–f, where lines 1 only contains Ti atoms while line 2 and 3 have both Ti and Cu atoms, confirming that there are Cu-O-Ti clusters. \n\nThe STEM-EDS mapping (Fig. 2g, Supplementary Fig. 12e) and EDS spectrum of $\\mathrm{CuSA-TiO}_{2}$ (Supplementary Fig. 13) verify the existence of Ti, O, and Cu elements. Due to the porous nature and unsaturated bonds of MIL- $125(\\mathrm{Ti}_{\\mathrm{v}})$ , the Cu single atoms can be well stabilized. The stability of $\\mathtt{C u}$ atoms is further studied by measuring the HAADF-STEM of $\\mathrm{CuSA-TiO}_{2}$ after $24\\mathrm{-h}$ photocatalytic reaction (Supplementary Figure 12). The line scan profile and STEM-EDS demonstrates that CuSA is still well dispersed on $\\mathrm{TiO}_{2}$ , confirming the excellent stability and strong anchoring of CuSA on $\\mathrm{TiO}_{2}$ , which is the key reason that our photocatalyst not only shows the record activity but also does not require regeneration as reported by others6. \n\nPhoto-electric characterization of $\\mathbf{CuSA-TiO}_{2}$ . UV-visible absorption spectroscopy (UV-vis) was used to explore the optical properties of $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}$ . The pristine $\\mathrm{TiO}_{2}$ shows an absorption edge starting from ${380}\\mathrm{nm}$ , corresponding to its wide bandgap transition (Supplementary Fig. 14). After loading CuSA, $\\mathrm{CuSA^{-}T i O}_{2}$ exhibits an obvious absorption in the visible region as well, a broad hump between $400\\mathrm{nm}$ and $1050\\mathrm{nm}$ which is attributed to the d-d transition of $\\mathrm{Cu}^{2+}$ state6. It is also evidenced from Supplementary Fig. 14 that the $\\mathrm{TiO}_{2}$ absorption remains unchanged after loading CuSA. The transfer and separation efficiency of photogenerated charge carriers was studied by photoluminescence (PL) experiments. Figure 3a shows the PL spectra of $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}$ excited at $375\\mathrm{nm}$ . It is obvious that the pristine $\\mathrm{TiO}_{2}$ shows high emission intensity due to the serious charge carrier recombination, which is significantly reduced after loading CuSA, indicating that the CuSA loading might effectively facilitate the photogenerated electrons extraction to the Cu active sites39,40. It is possible because the reduction potential of $\\mathrm{Cu}^{2+}/\\mathrm{Cu}^{+}$ $_{\\mathrm{0.16V}}$ vs. NHE) is more positive than the conduction band of $\\mathrm{TiO}_{2}$ ( $_{-0.1\\mathrm{V}}$ vs. NHE)41,42. \n\nPL lifetime is the average time that the fluorophore stays in the excited state before emission occurs43. The instrument response function (IRF) was first measured to be 530 ps (Supplementary \n\nFig. 15). The PL decay tests for $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}$ were then performed with $375\\mathrm{nm}$ excitation beam taking into account $\\mathrm{TiO}_{2}$ absorption spectra (Supplementary Fig. 15) and observed at $430\\mathrm{nm}$ . The decay kinetics were fitted with a biexponential function as shown in Supplementary Table 3 after considering this IRF: $I(\\mathbf{t})=\\mathbf{B}_{1}$ $\\mathrm{\\Delta\\r~\\vert=B_{1}\\ \\exp(-t/\\tau_{1})+B_{2}\\ \\exp(-t/\\tau_{2})}$ , where $\\uptau_{1}$ and $\\tau_{2}$ are the decay times for the faster and slower components, respectively, $\\mathbf{B}_{1}$ and $\\mathbf{B}_{2}$ are the contributions of each component. The carrier lifetime of $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}$ were determined to be $3.82\\mathrm{ns}$ and $2.04\\mathrm{ns}$ , respectively. The $\\mathrm{CuSA-TiO}_{2}$ shows a shorter PL lifetime compared to that of $\\mathrm{TiO}_{2}$ , revealing the faster electron transfer in $\\mathrm{CuSA-TiO_{2}}^{22,44}$ . \n\nTo further understand the charge carrier separation, photoelectrochemical experiments were performed and the photocurrents observed for $\\mathrm{TiO}_{2}$ and $\\mathrm{\\bar{C}u S A-T i O}_{2}$ are shown in Supplementary Fig. 16a. $\\mathrm{CuSA-TiO}_{2}$ exhibits 3 times higher photocurrent than the pristine $\\mathrm{TiO}_{2}$ , indicating the more efficient carrier separation in $\\mathrm{CuSA-TiO}_{2}$ following photoexcitation. This might be due to $\\mathrm{Cu-O}$ as the bridge for more efficient carrier transfer to $\\mathrm{cu}$ active sites for $\\mathrm{H}_{2}$ generation45. In addition, the photocurrent response of $\\mathrm{CuSA-TiO}_{2}$ shows high reproducibility and stability for several on/off cycles. Moreover, the electrochemical impedance spectra (EIS) were used to study the transfer properties of charge carriers46, as indicated in Supplementary Fig. 16b. CuSA- $\\mathrm{\\cdotTiO}_{2}$ shows similar but dramatically decreased EIS Nyquist curves compared to pristine $\\mathrm{TiO}_{2}$ , indicating the CuSA species serve as electron acceptors, thus facilitating the interfacial charge separation. The efficient electron mobility is possibly ascribed to the reversible redox process between $\\dot{\\mathrm{Cu}^{2+}}$ and $\\mathrm{Cu^{+}}$ in $\\mathrm{CuSA-TiO}_{2}$ . Then, the electrochemical linear sweep voltammetry of $\\mathrm{CuSA-TiO}_{2}$ was performed and shown in Supplementary Fig. 17, showing an overpotential of $-0.72\\mathrm{V}$ vs RHE for $\\mathrm{H}_{2}$ production. \n\nValence state characterization of Cu SAs. To examine the real chemical states of the photocatalysts during the photocatalytic reaction, in-situ $\\mathbf{x}$ -ray photoelectron spectroscopy (XPS) spectra of $\\mathrm{CuSA-TiO}_{2}$ before and during the reaction were monitored (Fig. 3b). The $\\mathrm{Cu}2p$ before irradiation appears to be composed of four Gaussian peaks, where $952.9\\mathrm{{\\stackrel{.}{\\mathrm{eV}}}}$ and $932.9\\mathrm{eV}$ are assigned to the $\\mathrm{Cu}2p1/2$ and $\\mathrm{Cu}~2p3/2$ of $\\mathsf{C u}^{2+}$ ( $(70.58\\%$ , Supplementary Table 4), respectively. Another set of peaks at $951.5\\mathrm{eV}$ and $931.8\\mathrm{eV}$ are likely associated with $\\mathrm{Cu^{+}}$ species37 $(29.42\\%)$ , illustrating the $\\mathtt{C u}$ atoms bonded with $\\mathrm{TiO}_{2}$ rather than physical adsorption on the surface. After $30\\mathrm{min}$ irradiation, the $\\mathrm{Cu^{+}}$ content increases to $61.68\\%$ and remains at $62\\substack{-66\\%}$ after that till the end of the reaction. Interestingly, after exposing the used catalyst in the air for $10\\mathrm{min}$ , the ratio of $\\mathrm{Cu^{+}}$ decreases to $53.45\\%$ , and the satellite peak of ${\\mathrm{Cu}}^{2+}$ appears, which is ascribed to the $\\mathrm{Cu^{+}}$ is partially oxidised to ${\\mathrm{Cu}}^{2+}$ again. Also, Ti $2p$ and $\\textit{O}1s$ of $\\mathrm{CuSA^{-}T i O}_{2}$ and reference $\\mathrm{PtSA-TiO}_{2}$ before and after $30\\mathrm{min}$ irradiation were compared in Supplementary Fig. 18. For $\\mathrm{CuSA-TiO}_{2}$ , the content of surface ${\\dot{\\mathrm{Ti}}}^{3+}$ increases from $0.00\\%$ to $47.02\\%$ as well as oxygen vacancy (Vo) increases from $8.81\\%$ to $18.21\\%$ due to light irradiation (Supplementary Table 5), that is believed due to the photogenerated electrons accumulation on both $\\mathrm{Ti^{4+}}$ and ${\\mathrm{Cu}}^{2+}$ species47,48. For $\\mathrm{PtSA-TiO}_{2}$ , only $13.12\\%$ $\\mathrm{Ti}^{3+}$ was formed by irradiation (Supplementary Fig. 18d), which can be explained by the stronger carrier exchange between $\\mathrm{Pt}$ and $\\mathrm{TiO}_{2}$ compared to $\\mathtt{C u}$ and $\\mathrm{TiO}_{2}$ . The $\\mathrm{Pt}4\\bar{f}$ spectrum of $\\mathrm{PtSA-TiO}_{2}$ shows two peaks located at $74.4\\mathrm{eV}$ and $70.9\\mathrm{eV}$ , corresponding to $\\mathrm{Pt}^{2+}$ . After irradiation, the new peak at $69.2\\mathrm{eV}$ appears, corresponding to the metallic $\\mathrm{Pt},$ suggesting the partial reduction of $\\mathrm{Pt}^{\\sum+}$ . The O $\\textbf{1}s$ spectrum of $\\mathrm{Pt}\\bar{\\mathrm{S}}\\bar{\\mathrm{A}}{-}\\mathrm{Ti}\\bar{\\mathrm{O}_{2}}$ (Supplementary Fig. 18f) shows the peak at \n\n![](images/fbca19c4db4ec7a2a5aadc429b95c291b77af0fdc24cb9ec076bbddf7e4aa184.jpg) \nFig. 3 Carrier transfer mode and carrier dynamics of $\\mathbf{CuSA-TiO_{2}}$ . a Photoluminescence spectra of $\\mathsf{T i O}_{2}$ and $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ under an excitation wavelength of $375{\\mathsf{n m}}$ . b In-situ $\\mathsf{C u}2p$ XPS of $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ . c In-situ electron paramagnetic resonance spectra of $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ with various states. d Transient absorption spectra of $\\mathsf{T i O}_{2}$ and $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ in the absence and presence of ${\\sf A g N O}_{3}$ $(2m M)$ , monitored in argon atmosphere after $320{\\mathsf{n m}}$ excitation. e Charge dynamics decay in $\\mathsf{T i O}_{2}$ and $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ with and without methanol $(10\\%)$ ) monitored at $650\\mathsf{n m}$ . f The spectra of ${\\sf H}_{2},$ , HD, and ${\\sf D}_{2}$ evolution on CuSA- $\\cdot\\mathsf{T i O}_{2}$ from the solution of $C D_{3}O D$ in $H_{2}O$ . g The spectra of $\\mathsf{H}_{2},$ HD, and ${\\sf D}_{2}$ evolution on $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ from the solution of $C H_{3}O H$ in $\\mathsf{D}_{2}\\mathsf{O}$ . \nFig. 1d. The valence states of $\\mathrm{Cu}$ in $\\mathrm{CuSA-TiO}_{2}$ before and after irradiation were further confirmed by in-situ electron paramagnetic resonance (EPR) (Fig. 3c). Before irradiation, the EPR spectrum of $\\mathrm{CuSA-TiO}_{2}$ shows a strong signal of ${\\mathrm{Cu}}^{2+}$ , which decreases after $30\\mathrm{min}$ irradiation and then increases after exposure to the air. This result indicates that EPR-silent $\\mathrm{Cu^{+}}$ was formed during irradiation and then oxidized back to $\\mathsf{C u}^{2+}$ when exposed to air. \n\n$530.8\\mathrm{eV}$ before irradiation assigning to the trace oxidation of $\\mathrm{Pt}$ , which vanishes after irradiation, and $\\mathrm{Vo}$ increases from $11.20\\%$ to $22.00\\%$ (Supplementary Table 6), matching well with that of Pt $4f.$ . Interestingly, although Vo change is very similar for both $\\mathrm{CuSA-TiO}_{2}$ and reference $\\mathrm{\\bar{P}t S A-T i O}_{2}$ , the $\\mathrm{Ti}^{3\\dot{+}}$ in the former is much higher than the latter, indicating more photoelectrons transfer from the excited $\\mathrm{TiO}_{2}$ to $\\mathrm{Pt}^{2+}$ than that to ${\\mathrm{Cu}}^{2+}$ , which is reasonable as the reduction potential of $\\mathrm{Pt}^{2+}/\\mathrm{Pt}^{0}$ $(0.758\\mathrm{eV})$ is much more positive than that of $\\mathrm{Cu}^{2+}/\\mathrm{Cu}^{+}$ $(0.153\\mathrm{eV})^{49}$ . We think there is little $\\mathtt{C u}$ metal on the surface of $\\mathrm{TiO}_{2}$ due to the strong interaction between Cu and substrate as mentioned above and one-electron reduction process $(\\mathrm{Cu}^{2+}$ to $\\mathrm{Cu^{+}}$ ) is easier than two-electron process $\\mathrm{\\langle{Cu}}^{\\hat{2}+}$ to ${\\mathrm{Cu}}^{0^{\\cdot}}$ ), which is crucial for the $\\mathsf{C u}^{2+}$ and $\\mathrm{Cu^{+}}$ cycle (or self-healing) as indicated in \n\nCharge dynamics analysis. To further confirm the charge dynamics of the excited $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}$ , the femto second transient absorption spectra (fs-TAS) were monitored and shown in Supplementary Fig. 19 and Fig. 3. Figure 3d shows the \n\nTAS-signals of $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}$ with and without ${\\mathrm{AgNO}}_{3}$ $(2\\mathrm{mM})$ under $320\\mathrm{nm}$ excitation. For $\\mathrm{TiO}_{2}$ , the monotonically strong background is ascribed to the excited photoelectrons either in the conduction band or the trap states50. After introducing $\\mathrm{Ag}$ $^+$ as an electron scavenger, the TAS signal of $\\mathrm{TiO}_{2}$ exhibits the decreased signal intensity, indicating this wavelength range is the fingerprint of photoelectrons. When adding Cu SAC onto $\\mathrm{TiO}_{2}$ , the TAS is nearly identical to that of $\\mathrm{TiO}_{2}$ in the presence of $\\mathrm{Ag^{+}}$ ions, clearly indicating that photogenerated electrons are successfully captured by the $\\bar{\\mathrm{Cu}^{2+}}$ or the efficiency of $\\mathrm{Cu}^{2+}$ to abstract photoelectrons from $\\mathrm{TiO}_{2}$ is close to that of $\\mathrm{Ag^{+}}$ ions, which is believed due to the strong chemical bond interaction in the Cu-O-Ti clusters. For $\\mathrm{CuSA-TiO}_{2}$ in the presence of $\\mathrm{Ag^{+}}$ , the TAS signal further decreases due to the electron scavenging by both $\\mathsf{C u}^{2+}$ and $\\mathrm{Ag^{+}}$ . On the other hand, when adding methanol as a hole scavenger to $\\mathrm{TiO}_{2}$ , the enhanced photoelectron signal is observed at long wavelengths compared with that in the absence of methanol (monitored at $650\\mathrm{nm}$ in Fig. 3e) due to the hole scavenging by methanol. This photoelectron dynamics decay is likely due to the reaction of oxidized species of methanol with the electrons. As expected, $\\mathrm{CuSA-TiO}_{2}$ shows similar features of photoelectron decay in the presence or absence of methanol, confirming that electrons can be efficiently trapped by ${\\mathrm{Cu}}^{2+}$ when holes are scavenged by methanol. The TAS results are well consistent with in-situ XPS and in-situ EPR results. \n\nIsotopic experiments. To differentiate the origin of the evolved $\\mathrm{H}_{2}$ , isotopic tracing experiments were performed on $\\mathrm{CuSA-TiO}_{2}$ . Figure 3f and Supplementary Fig. 20 exhibit the spectra of generated $\\mathrm{H}_{2}$ from deuterated methanol and water $\\mathrm{(\\bar{C}D_{3}O D/H_{2}O)},$ . $\\mathrm{H}_{2}$ is the major product, then HD, and finally deuterium $\\left(\\mathrm{D}_{2}\\right)$ . This indicates that the source of protons is mainly derived from water and partially from methanol, consistent with others51. The same conclusion can be drawn from the other case study using deuterated water and methanol $\\mathrm{(D_{2}O/C H_{3}O H)}$ , as shown in Fig. $3\\mathrm{g}$ and Supplementary Fig. 21. Again, $\\mathrm{D}_{2}$ shows the largest signal, then HD and finally $\\mathrm{H}_{2}.$ , proving water is the major hydrogen source for $\\mathrm{H}_{2}$ evolution. \n\nTheoretic calculations of carrier transfer. The photogenerated electrons transfer to the $\\mathrm{CuSA}$ and their dissipation was modelled by the DFT simulation. The $\\mathrm{CuSA-TiO}_{2}$ sample was modelled using $1.5\\mathrm{wt\\%}$ of Cu replacing Ti (Supplementary Fig. 22). The charge density diagrams of pristine $\\mathrm{TiO}_{2}$ and $\\mathrm{CuSA-TiO}_{2}$ under dark conditions are shown in Fig. 4a, b, respectively. It can be seen that when $\\mathrm{Ti}$ is replaced by Cu (highlighted with a pink dotted square), the unbalanced charges lead to a slight accumulation of electrons on Cu. The gradual increase of electron density around Cu is obvious after irradiation for 100 ps (Fig. 4c), $200{\\mathrm{ps}}$ (Fig. 4d), and 1 ns (Fig. 4e). While the irradiation stops, the charge density on Cu after $100{\\mathrm{ps}}$ is obviously reduced (Fig. 4 f), indicating that the accumulated electrons reduce the ${\\mathrm{Cu}}^{2+}$ to $\\mathrm{cu}$ +. At the same time, the $\\mathrm{Cu^{+}}$ can be oxidized back to ${\\mathrm{Cu}}^{2+}$ when no more photogenerated electrons are transferred to Cu while in contact with oxygen. \n\nThe DFT result for the pristine $\\mathrm{TiO}_{2}$ after irradiation as shown in Supplementary Fig. 23. It can be seen that there is no increase of the charge density on Ti atoms until 1 ns (d1), which is back to the original state when irradiation stops. It suggests the lower charge density and slower charge mobility of pristine $\\mathrm{TiO}_{2}$ compared with $\\mathrm{CuSA-TiO}_{2}$ . To make it clear, the selected areas in 4e and 4 f of Fig. 4 are magnified and compared in Supplementary Figure 24. The black circles and corresponding distances $\\mathrm{D}_{1}$ and $\\bar{\\mathrm{D}_{2}^{\\mathrm{-}}}$ (Supplementary Fig. 24) are used to present the charge density on the Cu atom after irradiation for 1 ns and after turning off the irradiation for $100{\\mathrm{ps}}$ . Obviously, the $\\mathrm{D}_{1}$ is larger than $\\mathrm{D}_{2}$ , indicating that the charge density on the Cu atom after irradiation for 1 ns is quite high while the obviously reduced density is observed when stopping the irradiation after $100\\mathrm{ps}$ . \n\nThe surface photovoltage (SPV) was measured by the Kelvin probe (KP) to monitor the charge separation on $\\mathrm{CuSA-TiO}_{2}$ and $\\mathrm{PtSA-TiO}_{2}$ (Supplementary Fig. 25a–b). The ΔSPV comparison before and after irradiation for $\\mathrm{CuSA-TiO}_{2}$ and $\\mathrm{PtSA-TiO}_{2}$ has been shown in Supplementary Figure 25c. The average ΔSPV before and after irradiation for $\\mathrm{CuSA-TiO}_{2}$ is $185\\mathrm{mV}$ , which is higher than that of $\\mathrm{PtSA-TiO}_{2}$ $\\mathrm{144mV)}$ , indicating the more enhanced charge separation rate in $\\mathrm{CuSA-TiO}_{2}$ . \n\nHydrogen evolution mechanism. The dramatic enhancement in photocatalytic $\\mathrm{H}_{2}$ evolution activity of $\\mathrm{CuSA-TiO}_{2}$ can be attributed to the following reasons. First of all, the synthesis strategy provides suitable sites (Ti vacancy) and a high specific surface area for $\\mathtt{C u}$ atoms stabilization (Fig. 1e). Secondly, the abundant $\\mathsf{C u}^{2+}$ effectively traps the photogenerated electrons, leading to the significantly reduced recombination of the photogenerated charges (step 1 in Fig. 1d). The $\\mathrm{Cu^{+}}$ has a positive potential to reduce $\\mathrm{H}_{2}\\mathrm{O}$ to $\\mathrm{H}_{2}$ (step 2 in Fig. 1d), then $\\mathrm{Cu^{+}}$ returns to ${\\mathrm{Cu}}^{2+}$ . Such an interesting reversible process or in-situ self-healing enables $\\mathrm{CuSA-TiO}_{2}$ to achieve higher photocatalytic activity than the conventional $\\mathrm{Pt/TiO}_{2}{}^{51}$ . It is also higher than other single atom sites decorated photocatalysts reported due to such a high concentration of Cu $(1.5\\mathrm{wt\\%})$ anchored on the surface of $\\mathrm{\\bar{TiO}}_{2}$ . The interaction between $\\mathrm{Cu^{+}}$ and $\\mathrm{H}_{2}\\mathrm{O}$ is also verified by density functional theory (DFT) calculation. The $\\mathrm{H}_{2}\\mathrm{O}$ reduction by $\\mathrm{Cu^{+}}$ needs to overcome the energy barrier of $0.44\\mathrm{eV}$ and is exothermic by $0.83\\mathrm{eV}$ (Supplementary Fig. 26). To verify the oxidized products of methanol, the solution of $\\mathrm{D}_{2}\\mathrm{O}/$ $\\mathrm{CH}_{3}\\mathrm{\\dot{O}H}$ after the reaction was tested by nuclear magnetic resonance (NMR) and detected the by-product HCOOH (Supplementary Fig. 27), confirming that methanol was first oxidised to HCHO and further to HCOOH (Fig. 1d). \n\nIn summary, a reproducible and low-cost pre-encapsulation strategy was developed for stabilizing metal single atoms on $\\mathrm{TiO}_{2}$ and was further demonstrated for solar fuel $\\mathrm{H}_{2}$ synthesis. The strongly anchored Cu single atoms trigger a reversible/selfhealing and continuous photocatalytic process, which has been proved by both experimental and theoretical studies. The synthesised $\\mathrm{CuSA-TiO}_{2}$ shows the higher $\\mathrm{H}_{2}$ evolution rate with the benchmark apparent quantum efficiency of $56\\%$ at $365\\mathrm{nm}$ . The obtained higher activity is due to the advantage of MOF structure with extremely large surface area as the intermediate, which maximises the exposed sites for CuSA immobilization on $\\mathrm{TiO}_{2}$ , reaching ${\\sim}1.5\\mathrm{wt\\%}$ . After calcination, the strongly bonded $\\mathrm{CuSA}$ on $\\mathrm{TiO}_{2}$ effectively separates photoelectrons, and then electrons cascade to reduce water to $\\begin{array}{r}{\\mathbb{H}_{2},}\\end{array}$ along with methanol oxidation. Both the diverse spectroscopic and in-situ experiments as well as DFT results reveal the most efficient charge separation by $\\mathrm{CuSA}$ than any other cocatalysts and prove the significance of the in-situ self-healing effect of $\\mathtt{C u}$ species during the photocatalytic reaction. The present atomic-level photocatalytic material design strategy indeed paves the way towards a competitive $\\mathrm{H}_{2}$ production for commercial application. \n\n# Methods \n\nAll commercially available chemicals, reagents, and solvents were used as received without further purification unless noted otherwise. \n\nPreparation of MOF MIL-125(Tiv) precursor. The precursor of MIL-125 (MIL stands for Material from Institut Lavoisier) was prepared by following the reported procedure1. In a typical process, $3\\mathrm{g}$ of terephthalic acid (1,4-benzenedicarboxylic acid) was added to the $54\\mathrm{ml}$ of N,N dimethylacetamide (DMF) and magnetically stirred for $10\\mathrm{min}$ . Then, $6\\mathrm{mL}$ of methanol was added into the above mixture followed by the addition of $1.2\\mathrm{mL}$ (to create Ti vacancies, we use $1.2\\mathrm{mL}$ instead of $1.56\\mathrm{mL}$ from the literature) of $\\mathrm{Ti(OC_{4}H_{9})_{4}}$ under the stirring condition for $5\\mathrm{min}$ . After that, the solution was transferred into a $100~\\mathrm{mL}$ Schlenk tube and kept at $130^{\\circ}\\mathrm{C}$ for $20\\mathrm{h}$ . After cooling down to room temperature, the precipitate was separated by centrifugation and washed by DMF and methanol consecutively. The free solvent attached to the precipitate was removed by vacuum drying. The final obtained sample is MIL-125. \n\n![](images/884cd88559a3fc31a232216a33f19c417acea9cd000ea3507742f40f05e5a43f.jpg) \nFig. 4 Charge density distribution with or without irradiation. a Charge density distribution of pure $T_{\\mathsf{i O}_{2}}$ . b $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ under dark condition ( $\\mathsf{T u}$ is in the dotted square). c $:C u S A-T i O_{2}$ after 100 ps irradiation. d $\\mathsf{C u S A-T i O}_{2}$ after 200 ps irradiation. e $C u S A\\mathrm{-}\\mathsf{T i O}_{2}$ after 1 ns irradiation. $A C\\cup S A-T i O_{2}$ after turning off the irradiation for 100 ps. In the middle panel, (a1–f1) is the magnified $\\mathsf{C u}$ atom highlighted by pink square in (a–f). Black and red colored circles indicate more electrons’ accumulation on Cu. \n\nSynthesis of SAC-MIL and preparation of final photocatalysts. Typically, $0.5{\\mathrm{g}}$ of MIL-125 particles were dispersed in $40~\\mathrm{mL}$ of DI water, then the metal-salt with different weight ratios (e.g., $6.8\\mathrm{mg}\\mathrm{CuCl}_{2}$ for $0.75\\mathrm{wt\\%\\Cu},$ ) was added into the MIL-125 dispersion and stirred for $^{3\\mathrm{h}}$ for encapsulated precursor synthesis. The resulting materials were then centrifuged and washed with water, dried at $80^{\\mathrm{{o}}}\\mathrm{{C}}$ . Finally, the $\\mathrm{MSA}{\\cdot}\\mathrm{TiO}_{2}$ particles $\\mathbf{\\tilde{M}}=\\mathbf{\\tilde{C}}\\mathbf{u}$ Co, ${\\mathrm{Ni}}.$ , Fe, Mn, Zn, and Pt) were obtained by annealing at $450^{\\mathrm{o}}\\mathrm{C}$ for $^{4\\mathrm{h}}$ in the air. \n\nProcedure of photocatalysis. The photocatalytic water-splitting experiments were performed on the full glass automatic on-line trace gas analysis system (Fig. 28a, Labsolar-6A, Perfect Light Ltd.) and Multichannel photochemical reactor (Fig. 28b, PCX-50C, Perfect Light Ltd.). With Labsolar-6A, a Xe lamp (Perfect light PLSSXE300C) equipped with filters was used as the simulated solar spectral source. (The data in Fig. $\\scriptstyle1({\\mathrm{a-c}})$ was collected with the light intensity of $500\\mathrm{\\bar{W}}/\\mathrm{m}^{2}$ , and that in Supplementary Fig. 3 was collected with the slightly reduced light intensity of $325\\mathrm{\\:W}/\\mathrm{m}^{2}$ due to the safety issue for a very long-time experiment.) The asprepared catalyst $(20\\mathrm{mg})$ was uniformly dispersed in $120\\mathrm{mL}$ of $\\mathrm{H}_{2}\\mathrm{O}/$ methanol aqueous solution by using a magnetic stirrer (containing $\\mathrm{H}_{2}\\mathrm{O}/$ methanol with a ratio of ${\\mathrm{:}}=1{:}2$ ). The system was vacuum-treated several times to remove the dissolved air, and the amount of produced $\\mathrm{H}_{2}$ was measured by an on-line gas chromatograph (GC7900). During the reaction, the temperature was maintained at $40^{\\circ}\\mathrm{C}$ using water circulation. For cyclic experiments, the sample was collected through centrifugation and drying after the photocatalytic reaction, without any other treatment. The sample storage for 380 days was stored in a glass bottle in a normal lab cabinet. \n\nThe PCX-50C, a 1 W UV LED (Wavelength range: $365\\mathrm{nm}$ , light intensity: $34.5\\mathrm{mW}/\\mathrm{cm}^{2};$ was used as the simulated light source for AQE calculation. The asprepared catalyst $(50\\mathrm{mg})$ was uniformly dispersed in $30~\\mathrm{mL}$ aqueous solution under magnetic stirring (containing $\\mathrm{H}_{2}\\mathrm{O}/$ methanol, ${\\bf v}/{\\bf v}=1{:}2$ ). The rest of the conditions were similar as stated above. \n\nThe AQE is calculated by using the following equation and the photocatalytic $\\mathrm{H}_{2}$ evolution (PHE) rate obtained from PCX-50C (Supplementary Fig.28b): \n\n$$\n\\mathrm{AQE}=\\frac{2\\mathrm{MN_{A}h c}}{\\mathrm{AIt}\\lambda}\\times100\\%\n$$ \n\nwhere $\\mathbf{\\delta}_{\\mathrm{M}}$ is the molar amount of hydrogen, $\\mathrm{N_{A}}$ is the Avogadro’s constant, $\\mathbf{h}$ is the Planck constant, $\\boldsymbol{\\mathfrak{c}}$ is the light velocity, I is the intensity of the light, A is the irradiation area measured by the reactor window with a diameter of $3c m$ , t is the reaction time, and $\\lambda$ is the wavelength of light $(365\\mathrm{nm})$ 1. \n\nThe amount of hydrogen via $50\\mathrm{mg}$ photocatalyst in the reactor was measured to be $0.753\\mathrm{mmol}$ within $^{\\textrm{1h}}$ at $40^{\\circ}\\mathrm{C}$ . \n\nCharacterization. The phase structures of the prepared samples were determined by the X-Ray diffraction (XRD) measurements using an $\\mathrm{\\DeltaX}$ -ray diffractometer (Rigaku, Japan) with CuKa irradiation. The accelerating voltage and applied current were $40\\mathrm{kV}$ and $80\\mathrm{mA}$ , respectively. The morphology and microstructure of the samples were examined by emission scanning electron microscope (FE-SEM, Nova nanoSEM 450) and transmission electron microscope (TEM, JEM-2100). The high-angle annular dark-field (HAADF) STEM for $\\mathrm{CuSA-TiO}_{2}$ was obtained using JEM-ARM300F equipment. The Brunauer–Emmett–Teller (BET) specific surface area of the prepared powders was analyzed by a 3H-2000PS2 sorption analyzer, and the porosity of the samples was evaluated based on nitrogen adsorption isotherms at $77\\mathrm{K}$ . UV-vis diffused reflectance spectra of the samples were obtained using a Metash UV-9000S spectrophotometer. X-ray photoelectron spectroscopy (XPS) measurements were accomplished via a photoelectron spectrometer (Thermo ESCALAB 250Xi) with an Al Kα radiation source. The excitation wavelength was $320\\mathrm{nm}$ , the scanning speed was $1200\\mathrm{nm}\\mathrm{min}^{-1}$ , and the PMT voltage was $700\\mathrm{V}$ . The widths of the excitation slit and emission slit were both $5.0\\mathrm{nm}$ . The Fourier transform infrared spectroscopy (FT-IR) spectra of starting materials and the as-synthesized samples were obtained using IR2000 equipment. \n\nSurface photovoltage (SPV) experiments were performed using the SKP5050 Kelvin probe. Electron spin resonance (EPR) spectroscopy was performed on Bruker EMXnano to detect the unpaired electrons of $\\mathrm{Cu}^{\\bar{2}\\dot{+}}$ in CuSA- $\\mathrm{\\cdotTiO}_{2}$ powder at room temperature. Nuclear magnetic resonance (NMR, DRX500) was adopted to identify the product in the solution after the photocatalytic reaction. \n\nPhotoluminescence (PL) spectra and time-resolved fluorescence decay spectroscopy were obtained by an FLS 1000 fluorescence spectrophotometer (UK), where the sample powder was placed on a copper support. When testing the steady-state PL, $375\\mathrm{nm}$ was selected for excitation. For PL decay testing, $375\\mathrm{nm}$ and $430\\mathrm{nm}$ were respectively selected for excitation and detection. \n\nIsotopic experiment. The isotopic experiment was performed using a multichannel photochemical reactor under $365\\mathrm{nm}$ LED irradiation. $10\\mathrm{mg}$ of CuSA$\\mathrm{TiO}_{2}$ was added into the solution of $22.5\\mathrm{mL}$ of water and $7.5\\mathrm{mL}$ of methanol, and irradiated for $24\\mathrm{h}$ . Two separate experiments were carried out under the same conditions except for the deuterated part $\\mathrm{(CD_{3}O D/H_{2}O}$ or $\\mathrm{D}_{2}\\mathrm{O}/\\mathrm{CH}_{3}\\mathrm{OH},$ ). Finally, the products were identified by Mass spectrum (MS, Hiden HPR-40). \n\nInductively coupled plasma optical emission spectrometer (ICP) test. The ICP test was performed by PlasmaQuant PQ9000. The sample was dissolved in $5\\mathrm{mL}$ freshly-made nitrohydrochloric acid at room temperature for $30\\mathrm{min}$ and then heated to $136~^{\\mathrm{o}}\\mathrm{C}$ for another $20\\mathrm{min}$ . After cooling down to room temperature, the solid residue was filtered followed by dilution to $50~\\mathrm{mL}$ for the test. \n\nTransient absorption spectroscopy (TAS) measurement. The fs-TAS measurement was carried out using a commercial transient absorption spectrometer (Newport TAS pump-probe system) that includes a $1\\mathrm{kHz}$ Solstice (Newport Corp.) Ti:sapphire regenerative amplifier outputting $800\\mathrm{nm}$ , 100 fs pulses. This laser light was split into two parts to generate the pump and the probe pulses. The tunable pump pulse was generated in a TOPAS-Prime (Light Conversion Ltd.) optical parametric amplifier and used to excite the sample at ${320}\\mathrm{nm}$ . Broadband probe light $(420-780\\mathrm{nm})$ ) was generated by focusing the Solstice output in a $2\\mathrm{mm}$ sapphire crystal. Both the pump and probe beam overlapped spatially in the sample and the time delay between the pump and probe pulse was scanned by controlling the stage. $1\\mathrm{mg}\\mathrm{m}\\dot{\\mathrm{L}}^{-1}$ sample was dispersed in an aqueous solution and transferred to $1\\mathrm{mm}$ path length cuvettes. Samples were measured after purging with argon. \n\nDensity functional theory (DFT) study. All calculations are performed with the DMOL3 module of Materials Studio 5.0. The ultrasoft pseudopotential was used in the calculation because of its several advantages in efficiency and veracity in the reciprocal space. The electronic exchange-correlation energy is treated within the framework of the generalized gradient approximation (GGA) with Perdew-BurkeErnzerhof (PBE). The plan-wave expansion is truncated by the cutoff energy of $450\\mathrm{eV}$ . The Monkhorst–Park scheme K-point grid sampling is set as $3\\times3\\times9$ for the model. Mulliken population analysis is used to analyze the average net charge. The Mulliken population is defined as the electronic charge assigned to the atoms and atomic orbitals. The convergence value is set as $0.01\\mathrm{nm}$ for the maximum displacement tolerances, $0.01\\mathrm{eV}\\mathrm{\\check{A}}{-}1$ for the maximum force in the geometrical optimization. The convergence accuracy of SCF is $10^{-6}\\mathrm{eV/atom}$ . The crystal structures and atom coordinates were also optimized firstly under the principle of energy minimization to obtain the appropriate cell parameters with stable structures for the model. Based on this principle, the electronic structures and optical properties could be calculated. After geometrical optimization, the lattice parameters of the pure anatase $\\mathrm{TiO}_{2}$ are given as follows: $\\mathtt{a}=\\mathtt{b}=3.79\\mathrm{\\AA}$ , ${\\mathfrak{c}}={\\overset{\\bullet}{9}}.51{\\mathrm{~\\AA}}$ . The supercell built as $8\\times8\\times1$ , thus the crystal parameters of the optimized supercell are $\\mathbf{a}=\\mathbf{b}=30.28\\mathrm{\\AA}$ , ${\\mathfrak{c}}=9.51{\\mathrm{~\\AA}}.$ The simulation of irradiation was realized by adding an electromagnetic field to simulate the UV irradiation. The charge density of the model was recorded in a certain time interval, i.e., 100 ps, 200 ps, and 1 ns. \n\nPhotoelectrochemical measurements. The photoelectrodes were prepared on fluorine-doped tin oxide (FTO) glass slides, which were cleaned with ethanol, rinsed with DI water, and dried before use. A $10\\mathrm{mg}$ of the prepared samples were added into $200\\upmu\\mathrm{L}$ of ethanol and ${800\\upmu\\mathrm{L}}$ water with $10\\upmu\\mathrm{L}$ of Nafion $(5\\mathrm{wt.\\%})$ and then carefully ground for a little while to form a homogenous slurry. Subsequently, the obtained slurry was evenly distributed onto the conductive side of FTO glass. After drying in the air, the photoelectron chemical properties of the obtained electrodes were tested in a three-electrode system using a CHI-760E electrochemical workstation. The prepared electrode, Pt wire, and $\\mathrm{Ag/AgCl}$ electrode were used as the working, counter, and reference electrodes, respectively. The $0.2\\mathbf{M}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ aqueous solution was used as an electrolyte, and the photoelectrodes were irradiated using a $150\\mathrm{W}$ xenon lamp with a light density of $95\\mathrm{mW}/\\mathrm{cm}^{2}$ . The photocurrents of the electrodes were measured using the amperometric (I–t curves) technique under repeatedly interrupted light irradiation. Electrochemical impedance spectroscopy (EIS) measurements were performed at an applied voltage of $5\\mathrm{mV}$ with a frequency in the range of $10^{5}–0.1\\mathrm{Hz}$ . \n\nStatistical analysis. All data were presented as means with standard deviations (SD). \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper. \n\nReceived: 20 February 2021; Accepted: 1 December 2021; Published online: 10 January 2022 \n\n# References \n\n1. Zhao, Y. et al. Simultaneous oxidative and reductive reactions in one system by atomic design. Nat. Catal. 4, 1–10 (2021). \n2. Cao, L. et al. Identification of single-atom active sites in carbon-based cobalt catalysts during electrocatalytic hydrogen evolution. Nat. Catal. 2, 134–141 (2019). \n3. Wang, Y. et al. Current understanding and challenges of solar-driven hydrogen generation using polymeric photocatalysts. Nat. Energy 4, 746–760 (2019). \n4. Dan, K. et al. Recent advances in visible-light driven water oxidation and reduction in suspensions systems. Mater. Today 21, 897–922 (2018). \n5. Moniz, S. J. A. et al. Visible-Light Driven Heterojunction Photocatalysts for Water Splitting– A Critical Review. Energy Environ. Sci. 8, 731–759 (2015). \n6. Lee, B. H. et al. Reversible and cooperative photoactivation of single-atom $\\mathrm{Cu/}$ $\\mathrm{TiO}_{2}$ photocatalysts. Nat. Mater. 18, 620–626 (2019). \n7. Tang, J. et al. Mechanism of photocatalytic water splitting in $\\mathrm{TiO}_{2}$ . Reaction of water with photoholes, importance of charge carrier dynamics, and evidence for four-hole chemistry. J. Am. Chem. Soc. 130, 13885–13891 (2008). \n8. Linsebigler, A. L., Lu, G. & Yates, J. T. Photocatalysis on $\\mathrm{TiO}_{2}$ Surfaces: Principles, Mechanisms, and Selected Results. Chem. Rev. 95, 735–758 (1995). \n9. Cao, S. et al. Photocatalytic pure water splitting with high efficiency and value by Pt/porous brookite $\\mathrm{TiO}_{2}$ nanoflutes. Nano Energy 67, 104287 (2020). \n10. Barroso, M. et al. The role of cobalt phosphate in enhancing the photocatalytic activity of $\\mathrm{a-Fe}_{2}\\mathrm{O}_{3}$ toward water oxidation. J. Am. Chem. Soc. 133, 14868–14871 (2011). \n11. Wang, G. et al. Photoinduction of Cu single atoms decorated on UiO- $66\\mathrm{-NH}_{2}$ for enhanced photocatalytic reduction of $\\mathrm{CO}_{2}$ to liquid fuels. J. Am. Chem. Soc. 142, 19339–19345 (2020). \n12. Xiao, M. et al. Molten‐Salt‐Mediated Synthesis of an Atomic Nickel Co‐ catalyst on $\\mathrm{TiO}_{2}$ for Improved Photocatalytic $\\mathrm{H}_{2}$ . Evolution. Angew. Chem. 132, 7297–7301 (2020). \n13. Xie, J. et al. Highly selective oxidation of methane to methanol at ambient conditions by titanium dioxide-supported iron species. Nat. Catal. 1, 889–896 (2018). \n14. Liu, L. & Corma, A. Metal catalysts for heterogeneous catalysis: from single atoms to nanoclusters and nanoparticles. Chem. Rev. 118, 4981–5079 (2018). \n15. Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt^{1}/F e O_{x}}$ . Nat. Chem. 3, 634–641 (2011). \n16. Hejazi, S. et al. On the controlled loading of single platinum atoms as a cocatalyst on $\\mathrm{TiO}_{2}$ anatase for optimized photocatalytic $\\mathrm{H}_{2}$ generation. Adv. Mater. 32, 1908505 (2020). \n17. Lam, E. et al. Isolated $Z\\mathrm{r}$ surface sites on silica promote hydrogenation of $\\mathrm{CO}_{2}$ to $\\mathrm{CH}_{3}\\mathrm{OH}$ in supported Cu catalysts. J. Am. Chem. Soc. 140, 10530–10535 (2018). \n18. Yin, Y. et al. Boosting Fenton-like reactions via single atom Fe catalysis. Environ. Sci. Technol. 53, 11391–11400 (2019). \n19. Wang, Y. et al. Catalysis with two-dimensional materials confining single atoms: concept, design, and applications. Chem. Rev. 119, 1806–1854 (2019). \n20. Guo, J. et al. Nitrogen-doped porous carbon supported nonprecious metal single-atom electrocatalysts: from synthesis to application. Small Meth. 3, 1–33 (2019). \n21. Zhang, H., Liu, G., Shi, L. & Ye, J. Single-atom catalysts: emerging multifunctional materials in heterogeneous catalysis. Adv. Energy Mater. 8, 1–24 (2018). \n22. Jiang, X. H. et al. Silver Single atom in carbon nitride catalyst for highly efficient photocatalytic hydrogen evolution. Angew. Chem. - Int. Ed. 59, 23112–23116 (2020). \n23. Trofimovaite, R. et al. Single atom $\\mathrm{{Cu(I)}}$ promoted mesoporous titanias for photocatalytic Methyl Orange depollution and $\\mathrm{H}_{2}$ production. Appl. Catal. B Environ. 232, 501–511 (2018). \n24. Seadira, T. W. P., Sadanandam, G., Ntho, T., Masuku, C. M. & Scurrell, M. S. Preparation and characterization of metals supported on nanostructured $\\mathrm{TiO}_{2}$ hollow spheres for production of hydrogen via photocatalytic reforming of glycerol. Appl. Catal. B Environ. 222, 133–145 (2018). \n25. J. & Ran, J. Facile preparation and enhanced photocatalytic $\\mathrm{H}_{2}$ -production activity of $\\mathrm{Cu(OH)}_{2}$ cluster modified $\\mathrm{TiO}_{2}$ . Energy Environ. Sci. 4, 1364–1371 (2011). \n26. Foo, W. J., Zhang, C. & Ho, G. W. Non-noble metal Cu-loaded $\\mathrm{TiO}_{2}$ for enhanced photocatalytic $\\mathrm{H}_{2}$ production. Nanoscale 5, 759–764 (2013). \n27. Xiao, S. et al. Copper nanowires: A substitute for noble metals to enhance photocatalytic $\\mathrm{H}_{2}$ generation. Nano Lett. 15, 4853–4858 (2015). \n28. Saffman, M. The next step in making arrays of single atoms. Nature 567, 468–470 (2019). \n29. Fang, X. et al. Single Pt atoms confined into a metal–organic framework for efficient photocatalysis. Adv. Mater. 30, 1–7 (2018). \n30. Chen, L. N. et al. Efficient hydrogen production from methanol using a singlesite $\\mathrm{Pt^{1}}/\\mathrm{CeO}_{2}$ catalyst. J. Am. Chem. Soc. 141, 17995–17999 (2019). \n31. Song, Y. et al. Metal-organic framework nodes support single-site nickel(II) hydride catalysts for the hydrogenolysis of Aryl Ethers. ACS Catal. 9, 1578–1583 (2019). \n32. Remiro-Buenamañana, S. et al. Influence of co-catalysts on the photocatalytic activity of MIL-125(Ti)- $\\cdot\\mathrm{NH}_{2}$ in the overall water splitting. Appl. Catal. B Environ. 254, 677–684 (2019). \n33. Ji, P. et al. Titanium(III)-oxo clusters in a metal-organic framework support single-site $\\operatorname{Co}(\\operatorname{II})$ -hydride catalysts for arene hydrogenation. J. Am. Chem. Soc. 140, 433–440 (2018). \n34. Xiang, Q., Yu, J. & Jaroniec, M. Synergetic effect of $\\ensuremath{\\mathrm{MoS}}_{2}$ and graphene as cocatalysts for enhanced photocatalytic $\\mathrm{H}_{2}$ production activity of $\\mathrm{TiO}_{2}$ nanoparticles. J. Am. Chem. Soc. 134, 6575–6578 (2012). \n35. Liu, Y. et al. $\\mathrm{TiO}_{2}/\\mathrm{Cu}_{2}\\mathrm{O}$ core/ultrathin shell nanorods as efficient and stable photocatalysts for water reduction. Angew. Chem. - Int. Ed. 54, 15260–15265 (2015). \n36. Dan-Hardi, M. et al. A new photoactive crystalline highly porous titanium(IV) dicarboxylate. J. Am. Chem. Soc. 131, 10857–10859 (2009). \n37. Kampouri, S. et al. Photocatalytic hydrogen generation from a visible-light responsive metal-organic framework system: The impact of nickel phosphide nanoparticles. J. Mater. Chem. A 6, 2476–2481 (2018). \n38. Wang, H. et al. Facile synthesis of ${\\mathrm{Sb}}_{2}{\\mathrm{S}}_{3}/$ /ultrathin $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ sheets heterostructures embedded with $\\mathrm{g-C}_{3}\\mathrm{N}_{4}$ quantum dots with enhanced NIRlight photocatalytic performance. Appl. Catal. B Environ. 193, 36–46 (2016). \n39. Wolff, C. M. et al. All-in-one visible-light-driven water splitting by combining nanoparticulate and molecular co-catalysts on CdS nanorods. Nat. Energy 3, 862–869 (2018). \n40. Liu, H., Zhang, J. & Ao, D. Construction of heterostructured $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}@\\mathrm{NH}_{2}$ - MIL-125(Ti) nanocomposites for visible-light-driven $\\mathrm{H}_{2}$ production. Appl. Catal. B Environ. 221, 433–442 (2018). \n41. Ao, D., Zhang, J. & Liu, H. Visible-light-driven photocatalytic degradation of pollutants over Cu-doped $\\mathrm{NH}_{2}$ -MIL-125(Ti). J. Photochem. Photobiol. A Chem. 364, 524–533 (2018). \n42. Scanlon, D. O. et al. Band alignment of rutile and anatase $\\mathrm{TiO}_{2}$ . Nat. Mater. 12, 798–801 (2013). \n43. Berezin, M. Y. & Achilefu, S. Fluorescence lifetime measurements and biological imaging. Chem. Rev. 110, 2641–2684 (2010). \n44. Luo, H. et al. Pt single-atoms supported on nitrogen-doped carbon dots for highly efficient photocatalytic hydrogen generation. J. Mater. Chem. A 8, 14690–14696 (2020). \n45. Zhu, S. et al. Cooperation between inside and outside of $\\mathrm{TiO}_{2}$ : Lattice $\\mathrm{Cu^{+}}$ accelerates carrier migration to the surface of metal copper for photocatalytic $\\mathrm{CO}_{2}$ reduction. Appl. Catal. B Environ. 264, 118515 (2020). \n46. Ahmed, S. A. Structural, optical, and magnetic properties of Cu-doped $\\mathrm{TiO}_{2}$ samples. Cryst. Res. Technol. 52, 1–8 (2017). \n47. Jiang, Z. et al. Living atomically dispersed Cu ultrathin $\\mathrm{TiO}_{2}$ nanosheet $\\mathrm{CO}_{2}$ reduction photocatalyst. Adv. Sci. 6, 3–7 (2019). \n48. Zhang, Y. et al. Covalent organic framework-supported Fe- $\\mathrm{TiO}_{2}$ nanoparticles as ambient-light-active photocatalysts. J. Mater. Chem. A 7, 16364–16371 (2019). \n49. Kim, M. R., Lee, D. K. & Jang, D. J. Facile fabrication of hollow $\\mathrm{Pt/Ag}$ nanocomposites having enhanced catalytic properties. Appl. Catal. B Environ. 103, 253–260 (2011). \n50. Sachs, M., Pastor, E., Kafizas, A. & Durrant, J. R. Evaluation of surface state mediated charge recombination in anatase and rutile $\\mathrm{TiO}_{2}$ . J. Phys. Chem. Lett. 7, 3742–3746 (2016). \n\n51. Kandiel, T. A., Ivanova, I. & Bahnemann, D. W. Long-term investigation of the photocatalytic hydrogen production on platinized $\\mathrm{TiO}_{2}$ : An isotopic study. Energy Environ. Sci. 7, 1420–1425 (2014). \n\n# Acknowledgements \n\nThis work was mainly supported by the National Natural Science Foundation of China (no.51562038), Yunnan Yunling Scholars Project, the Key Project of Natural Science Foundation of Yunnan (2018FY001(−011)) received by QL, and Yunnan basic applied research project (No. 202101AT070013) receive by YZ. WZ and JM are thankful for the Shannxi Key Research Grant (No. 2020GY-244). HW, MT, and JT are thankful for financial support from the UK EPSRC (EP/S018204/2), Royal Society Newton Advanced Fellowship grant (NAF\\R1\\191163 and NA170422), and Leverhulme Trust (RPG-2017- 122). \n\n# Author contributions \n\nQL and JT conceived and supervised the progress of the entire project. YZ designed the experiments, prepared the materials, and performed the MS, in-situ XPS, isotopic, ICP characterizations, photocatalytic performances test $\\mathrm{{\\widetilde{H}}}_{2}$ evolution test and AQE test) JZ prepared the materials and performed the BET, TG-DTA, in-situ XPS, SPV characterizations, and photocatalytic performances test (long-term stability test). HW repeated activity tests and AQE analysis and discussion of XPS, TAS, PL, AQE, and photochemical results. X. Z. carried out the first-principle DFT modulations and SEM, TEM characterizations. WZ. and YG carried out the TAS measurement and analysis. BX performed the in-situ EPR, XRD characterizations and analyzed the HADDF, STEM-EDS data. TL performed the electrochemical test, PL and PL decay test. MT heavily contributed to the discussion on the fundamental understanding. JZ performed Zeta, UV-vis, and NMR characterizations. JM supervised TAS experiments and heavily contributed to the TAS analysis. LL and RH performed the HADDF characterization. The paper was written through collective contributions from all authors. All authors approved the final version of the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-27698-3. \n\nCorrespondence and requests for materials should be addressed to Junwang Tang, Rong Huang or Qingju Liu. \n\nPeer review information Nature Communications thanks Moussab Harb, Hiroyuki Matsuzaki, Ki Tae Nam and Rosendo Valero for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41560-021-00952-0", + "DOI": "10.1038/s41560-021-00952-0", + "DOI Link": "http://dx.doi.org/10.1038/s41560-021-00952-0", + "Relative Dir Path": "mds/10.1038_s41560-021-00952-0", + "Article Title": "High areal capacity, long cycle life 4 V ceramic all-solid-state Li-ion batteries enabled by chloride solid electrolytes", + "Authors": "Zhou, LD; Zuo, TT; Kwok, CY; Kim, SY; Assoud, A; Zhang, Q; Janek, J; Nazar, LF", + "Source Title": "NATURE ENERGY", + "Abstract": "All-solid-state Li batteries (ASSBs) employing inorganic solid electrolytes offer improved safety and are exciting candidates for next-generation energy storage. Herein, we report a family of lithium mixed-metal chlorospinels, Li2InxSc0.666-xCl4 (0 <= x <= 0.666), with high ionic conductivity (up to 2.0 mS cm(-1)) owing to a highly disordered Li-ion distribution, and low electronic conductivity (4.7 x 10(-10) S cm(-1)), which are implemented for high-performance ASSBs. Owing to the excellent interfacial stability of the SE against uncoated high-voltage cathode materials, ASSBs utilizing LiCoO2 or LiNi0.85Co0.1Mn0.05O2 exhibit superior rate capability and long-term cycling (up to 4.8 V versus Li+/Li) compared to state-of-the-art ASSBs. In particular, the ASSB with LiNi0.85Co0.1Mn0.05O2 exhibits a long life of >3,000 cycles with 80% capacity retention at room temperature. High cathode loadings are also demonstrated in ASSBs with stable capacity retention of >4 mAh cm(-2) (similar to 190 mAh g(-1)).", + "Times Cited, WoS Core": 388, + "Times Cited, All Databases": 412, + "Publication Year": 2022, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000737783400001", + "Markdown": "# High areal capacity, long cycle life 4 V ceramic all-solid-state Li-ion batteries enabled by chloride solid electrolytes \n\nLaidong Zhou $\\textcircled{10}1,2$ , Tong-Tong Zuo $\\textcircled{10}$ 3, Chun Yuen Kwok $\\textcircled{1}$ 1, Se Young Kim1, Abdeljalil Assoud1, Qiang Zhang $\\textcircled{10}4$ , Jürgen Janek $\\oplus3$ and Linda F. Nazar $\\textcircled{1}$ 1,2 ✉ \n\nAll-solid-state Li batteries (ASSBs) employing inorganic solid electrolytes offer improved safety and are exciting candidates for next-generation energy storage. Herein, we report a family of lithium mixed-metal chlorospinels, $\\pmb{\\mathrm{Li}_{2}}\\pmb{\\mathrm{In}}_{x}\\pmb{\\mathrm{Sc}}_{0.666-x}\\pmb{\\mathrm{Cl}}_{4}$ $\\mathbf{(0\\leqx\\leq0.666)}$ , with high ionic conductivity (up to $2.0\\mathsf{m}\\mathsf{S}\\mathsf{c m}^{-1})$ owing to a highly disordered Li-ion distribution, and low electronic conductivity $(4.7\\times10^{-10}5\\mathrm{cm}^{-1})$ , which are implemented for high-performance ASSBs. Owing to the excellent interfacial stability of the SE against uncoated high-voltage cathode materials, ASSBs utilizing $\\mathbf{Licoo}_{2}$ or $\\mathbf{LiNi}_{0.85}\\mathbf{Co}_{0.1}\\mathbf{Mn}_{0.05}\\mathbf{O}_{2}$ exhibit superior rate capability and long-term cycling (up to 4.8 V versus $\\mathbf{Li}{\\mathbf{\\dot{\\eta}}}/\\mathbf{Li})$ compared to state-of-the-art ASSBs. In particular, the ASSB with $\\mathbf{LiNi}_{0.85}\\mathbf{Co}_{0.1}\\mathbf{Mn}_{0.05}\\mathbf{O}_{2}$ exhibits a long life of $>3,000$ cycles with $80\\%$ capacity retention at room temperature. High cathode loadings are also demonstrated in ASSBs with stable capacity retention of $>4m A h\\ c m^{-2}$ $(\\sim190m A\\ h g^{-1})$ . \n\nD echargeable batteries are key technologies for clean energy storage and electric vehicle applications. However, conventional lithium-ion batteries (LIBs) exploit flammable liquid electrolytes, which leads to safety risks, and a graphite negative electrode, which lowers the energy density compared to a lithium-metal anode1. Among the alternatives, all-solid-state Li batteries (ASSBs) using a solid electrolyte (SE) and ideally a lithium-metal anode (or anode-less design2) offer the potential to meet the growing demand for high energy density and superior safety energy-storage systems3,4. Since a highly conductive SE with a wide electrochemical stability window is a key component to realize the promise of ASSBs, a wide range of new materials have been developed5–7. The processing of thin-film SE layers8 as separators has also attracted great interest for further increasing the energy density of ASSBs. Among the different types of SEs, thiophosphates (sulfides) have attracted great interest over the last decade, due to their often high ionic conductivity $(>10\\mathrm{mScm^{-1}})$ and ductile nature9,10. However, because sulfides are oxidized at a low potential $(\\sim2.5\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i})^{11-13}$ , they are not electrochemically or chemically compatible with typical $4\\mathrm{V}$ cathode active materials (CAMs; that is, $\\mathrm{LiCoO}_{2}$ , $\\mathrm{LiNi}_{1-x-y}\\mathrm{Co}_{x}\\mathrm{Mn}_{y}\\mathrm{O}_{2})^{14}$ . Coating of CAM particles with an electronically insulating/ionically conductive, chemically compatible material is required to address this problem, which brings a myriad of additional issues. These include the difficulty of finding and processing suitable materials to achieve a homogeneous, functional coating15–18. The goal is thus to find SE materials with high ionic conductivity and high voltage stability, along with good ductility. \n\nIn 2018, Asano et al. reported that poorly crystalline $\\mathrm{Li}_{3}\\mathrm{YCl}_{6}$ exhibits a relatively good ionic conductivity of $0.51\\mathrm{mScm^{-1}}$ . They were able to achieve stable cycling of ASSBs using this electrolyte with uncoated $\\operatorname{LiCoO}_{2}$ (ref. 19). Since then, chloride SEs have garnered increasing interest due to their intrinsically high oxidative stability $(\\sim4.3\\mathrm{V})$ and apparent chemical stability with many $\\mathrm{CAMs^{20}}$ . Several materials, namely semiglassy $\\mathrm{Li}_{3}\\mathrm{ErCl}_{6}$ (ref. 21), $\\mathrm{Li}_{3}\\mathrm{InCl}_{6}$ (ref. 22), $\\mathrm{Li}_{3-x}\\mathrm{M}_{1-x}\\mathrm{Zr}_{x}\\mathrm{Cl}_{6}$ $\\mathrm{{\\cdot}}\\mathrm{{M}}=\\mathrm{{Y}},$ Er, Yb)23,24, $\\operatorname{Li}_{x}\\operatorname{ScCl}_{3+x}{^{25}}$ , $\\mathrm{Li}_{2}\\mathrm{Sc}_{2/3}\\mathrm{Cl}_{4}$ (ref. 26), poorly crystalline ${\\mathrm{Li}}_{2}{\\mathrm{ZrCl}}_{6}$ (ref. 27) and $\\mathrm{Li}_{3-x}\\mathrm{Yb}_{1-x}\\mathrm{Hf}_{x}\\mathrm{Cl}_{6}$ (ref. 28), were reported that exhibit such promising properties. Nonetheless, a very limited number of chloride SEs show ionic conductivity above $1\\mathrm{m}\\mathrm{S}\\mathrm{cm}^{-1}$ , driving an essential search for new materials. \n\nAnother major challenge for ASSBs is the moderate CAM loadings that are typically utilized in the literature $(<1.25\\mathrm{mAhcm^{-2}}, $ . To improve energy density, high-loading cathodes (that is, with areal capacities $>3\\mathrm{mAhcm}^{-2}.$ ) must be developed to make ASSBs practically competitive with conventional $\\mathrm{LIB}s^{29}$ . However, as the CAM loading increases in ASSBs, the ionic and electronic conduction percolation within the cathode composite declines substantially, leading to poor CAM utilization30. Thus cathode composite engineering, along with a highly conductive SE, is needed. \n\nHerein, we report a family of fast Li-ion conducting chlorides, $\\mathrm{Li}_{2}\\mathrm{In}_{x}\\mathrm{Sc}_{0.666-x}\\mathrm{Cl}_{4}$ $\\left(0}4\\mathrm{mAhcm}^{-2}$ $(>190\\mathrm{mAhg^{-1}})$ \n\n![](images/23501d69d18ac4ba202a6eea86f7d8197af91034dbd7743b27ee7de114d8e5ff.jpg) \nFig. 1 | $\\mathsf{\\pmb{x}}$ -ray diffraction patterns and Li-ion conductivity of $\\pmb{\\mathrm{Li}_{2}}\\pmb{\\mathrm{In}}_{x}\\pmb{\\mathrm{Sc}}_{0.666-x}\\pmb{\\mathrm{Cl}}_{4}$ . a, X-ray diffraction patterns of $\\mathsf{L i}_{2}\\mathsf{I n}_{x}\\mathsf{S c}_{0.666-x}\\mathsf{C l}_{4}$ $(0\\leq x\\leq0.666)$ . b, Nyquist plots of $\\mathsf{L i}_{2}\\mathsf{I n}_{x}\\mathsf{S c}_{0.666-x}\\mathsf{C l}_{4}$ (0.11 $\\leq x\\leq0.666)$ at room temperature, normalized for the pellet thickness. c, Ionic conductivity and activation energy of $\\mathsf{L i}_{2}\\mathsf{I n}_{x}\\mathsf{S c}_{0.666-x}\\mathsf{C l}_{4}$ $\\cdot0\\leq x\\leq0.666;$ as a function of nominal $\\ensuremath{\\vert{\\mathsf{n}}^{3+}}$ content. The ionic conductivity and activation energy values for $x=0$ were previously reported in ref. 26. \n\nwith no fading. These ultra-stable, high-voltage and high-loading solid state cells provide valuable insight into the design and development of ASSBs and may serve as an important point of reference. \n\n# Synthesis and characterization of chloride SEs \n\n$\\mathrm{\\DeltaX}$ -ray diffraction patterns (Fig. 1a) show that the synthesis of $\\mathrm{Li}_{2}\\mathrm{In}_{x}\\mathrm{Sc}_{0.666-x}\\mathrm{Cl}_{4}$ provides an almost phase-pure cubic spinel phase within the solid solution range of $0\\leq x<0.444$ . At higher $\\mathrm{In}^{3+}$ content $(x\\ge0.555)$ the fractions of monoclinic $\\mathrm{Li}_{3}\\mathrm{InCl}_{6}$ and LiCl impurities start to increase (Fig. 1a). The ionic conductivity and activation energy were determined with temperature-dependent electrochemical impedance spectroscopy (EIS) measurements (Fig. 1b and Supplementary Fig. 1). The corresponding room-temperature ionic conductivities and activation energies are summarized in Fig. 1c and Supplementary Table 1. All $\\mathrm{Li}_{_{2}}\\mathrm{In}_{_{x}}\\mathrm{Sc}_{0.666-x}\\mathrm{Cl}_{4}$ phases $(0}600$ cycles. In contrast, the NCM85 liquid cell shows fast capacity fade with $80\\%$ capacity retention over only 100 cycles (Supplementary Fig. 6c,d). Figure $\\ensuremath{4\\mathrm{b}}$ and Supplementary Fig. 6b show the capacity retention and voltage profile of the NCM622 ASSB, which achieves up to $194\\mathrm{mAhg^{-1}}$ and sustains ${}>180\\mathrm{mAhg^{-1}}$ over 320 cycles. Conversely, the NCM622 liquid cell fades very quickly, and the cell retains a mere $62\\mathrm{mAhg^{-1}}$ capacity over 150 cycles (Supplementary Fig. 6e,f) owing to the combination of interphase impedance growth on the cathode and Li metal anode, respectively. \n\nNCM85 ASSBs also exhibit stable cycling and very slow capacity fading at high voltage, even at $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ over ${>}110$ cycles, as shown in Fig. 4d,e. The slow capacity fading is not due to SE decomposition (next section) but is probably related to the known structural transformation of high-Ni NCM at high voltage (H2–H3 transition) and $\\mathrm{O}_{2}$ release. The cell maintains $95\\%$ capacity retention over 110 cycles, which is superior to the liquid cell performance using an advanced electrolyte35. \n\nSince a commercial LIB contains more than $90\\mathrm{wt\\%}$ CAM in the cathode composite, for comparison we also fabricated a NCM85 ASSB with a cathode composite containing $10\\mathrm{wt\\%}$ chloride SE and $90\\mathrm{wt\\%}$ NCM85 (Supplementary Fig. 7). The cell exhibits very good cycling behaviour, but slightly lower discharge capacity $(180\\mathrm{mAhg^{-1}},$ compared to the ASSB with $80\\mathrm{wt\\%}$ NCM85 (Fig. 4a). \n\n![](images/b90f2839b1aa6be1c835a97122cb85bd5ead662d039cc39cdd3faab9e9f688f0.jpg) \nFig. 3 | Room temperature rate capability of ASSBs. a–d, Charge–discharge capacity as a function of cycle number at different C rates for ASSBs consisting of cathode active materials and $20\\mathrm{wt\\%}$ $\\mathsf{L i}_{2}\\mathsf{I n}_{1/3}\\mathsf{S c}_{1/3}\\mathsf{C l}_{4}$ for LCO (a) and NCM85 $\\mathbf{\\eta}(\\bullet)$ and corresponding charge–discharge curves at different C rates for LCO (b) and NCM85 (d). \n\nWe ascribe this to poorer ionic conduction percolation within the cathode composite due to the lower content of SE, which could probably be improved by further nanostructuring the catholyte and optimizing cathode crystallite size and morphology36,37. \n\nTo demonstrate the long-term cycle life of the ASSBs, after the rate cycling studies in Fig. 3d, cycling of the NCM85 ASSBs was continued at a high 3C rate corresponding to charge–discharge in 20 minutes. Over more than 1,000 cycles at room temperature, the NCM85 ASSB exhibits virtually no fading and maintains a capacity of $86\\mathrm{mAhg^{-1}}$ ; moreover, the cell sustains ${>}80\\%$ retention over 3,000 cycles (Fig. $\\mathtt{4c}$ and Supplementary Fig. 8). A second cell was also constructed and exhibited the same excellent long-term cycling stability (Supplementary Fig. 9). At a 2C rate, the cell maintains a high discharge capacity of ${\\sim}155\\mathrm{mAhg^{-1}}$ and sustains ${>}94\\%$ capacity over 1,800 cycles (Supplementary Fig. 10). The overall performance is amongst the best compared with that reported for all-ceramic $\\mathrm{ASSBs^{10,\\bar{19},22-28,38}}$ , as summarized in Supplementary Table 7. \n\n# Electrochemical performance of high-loading ASSBs \n\nWhile the above-mentioned ASSBs exhibit superior electrochemical performance (compared with previously reported results) at typical cathode loadings of $6{-}8\\mathrm{mgcm}^{-2}$ , it is desirable to increase the loading to provide comparable areal capacities to commercial LIBs (typically $>3\\mathrm{mAhcm}^{-2})$ 29. We note the paucity of data on such cells in the literature2,10,29,39. Figure 5a and Supplementary Fig. 11a show the results for high-loading ASSBs $(27\\mathrm{mg}\\mathrm{cm}^{-2}$ LCO; $3.7\\mathrm{mAhcm^{-2}}.$ ) cycled at a high current density of $1.24\\mathrm{mAcm}^{-2}$ at room temperature. They deliver stable capacity retention and high specific capacity $(>3\\mathrm{mAh}\\mathrm{cm}^{-2}$ and ${\\mathrm{>}}11{\\dot{0}}\\operatorname{mAh}\\mathrm{g}^{-1}$ over 180 cycles), albeit with moderately high overpotential under these aggressive conditions. High-loading LCO ASSBs cycled at $50^{\\circ}\\mathrm{C},$ and even a higher current density of $1.79\\mathrm{mAcm}^{-2}$ , deliver excellent reversible capacity and high specific capacity with much lower overpotential (Fig. 5b and Supplementary Fig. 11b). Furthermore, owing to the high electronic conductivity of LCO, ultra-high-loading ASSBs ( $52.46\\mathrm{mg}\\mathrm{cm}^{-2}$ , $7.2\\mathrm{mAh}\\mathrm{cm}^{-2}.$ ) deliver stable areal capacity of $3\\operatorname{mAh}\\mathsf{c m}^{-2}$ at $25^{\\circ}\\mathrm{C}$ and $4.5\\mathrm{mAh}\\mathrm{cm}^{-2}$ at $50^{\\circ}\\mathrm{C}$ at a high current density of $1.20\\mathrm{mAcm}^{-2}$ with no capacity fade for over 500 cycles (Fig. 5c and Supplementary Fig. 11c). \n\nBecause the battery market is focused on high-Ni NCM-type CAMs, we also benchmarked a high-loading NCM85 ASSB $(21.59\\mathrm{mg}\\mathrm{cm}^{-2},$ . The cell (Fig. $\\mathrm{5d,e}$ ) delivers an areal capacity of $4.14\\mathrm{mAh}\\mathrm{cm}^{-2}$ (specific capacity of $192\\mathrm{mAhg^{-1}}$ ; very close to the typical value of ${\\sim}200\\mathrm{mAhg^{-1}}$ observed in liquid LIBs). The high-loading NCM85 ASSBs were repeated twice (22.31 and $22.00\\mathrm{mgcm}^{-2}$ loading, respectively; Supplementary Fig. 12), essentially providing the same results and demonstrating reproducibility. Since using an $\\mathrm{In/InLi}$ anode will significantly lower the cell energy density, micron-sized prelithiated Si can be used as an alternative negative electrode due to its high electronic conductivity and good mechanical properties. Supplementary Fig. 13 illustrates the fabrication of such an NCM85 cell, which exhibits stable cycling and high discharge capacity. \n\n# Origin of superior electrochemical performance \n\nThe underlying origin of the exceptional electrochemical performance of $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ lies in its intrinsically high oxidation stability and high ductility. All lithium metal chlorides should exhibit similar thermodynamic oxidation potentials of $4.21{-}4.25\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ on the basis of theory20; and, in principle, ASSBs utilizing chloride SEs with similar ionic conductivity should also exhibit comparable electrochemical properties. However, previously reported ASSBs with chloride $S\\mathrm{Es}^{19,22-25}$ exhibit poorer performance than we describe above, suggesting that other factors, including the CAM:SE ratio, cathode composite fabrication and cell pressure, could play an important role. \n\nFigure 6a–c shows the EIS spectra, which monitor the internal resistance evolution of an NCM622 ASSB cycled between 2.8 and $4.6\\mathrm{V}$ during the 1st cycle. The points on the voltage profile where the spectra were collected are indicated. The semicircles in the Nyquist plots represent the overlapping charge transfer contributions from the SE–cathode (and anode) interfaces. On charging (Fig. 6b), the cell resistance decreases slightly to reach a minimum at $50\\%$ state of charge (SOC) (point 4) and then maximizes at $100\\%$ SOC (point 7). While the changes are small, they can be ascribed to changes in the electronic40 and ionic41 conductivity of $\\mathrm{Li}_{1-x}\\mathrm{Ni}_{0.6}$ $\\mathrm{Co}_{0.2}\\mathrm{Mn}_{0.2}\\mathrm{O}_{2}$ during delithiation. On discharge (Fig. 6c), the process reverses (points 7–11). The much higher impedance at the lowest frequency $(100\\mathrm{mHz})$ for the fully discharged cell (point 12) and at point 1 (Supplementary Fig. 14) is attributed to diffusion limitation in the bulk NCM particles in their reduced state41. The same processes were observed for NCM85 and LCO, as shown in Supplementary Figs. 15 and 16. Overall, the total cell resistance is very low during cycling $(<80\\Omega)$ . Nyquist plots for NCM622 (Fig. 6d; $2.8\\mathrm{-}4.6\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ ) and LCO (Supplementary Fig. 17; $2.8\\mathrm{-}4.3\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i^{-}}$ ) ASSBs collected at the fully discharged state for cells cycled at $\\mathbf{C}/5$ or $\\mathbf{C}/2$ show negligible internal resistance increase over 10 cycles. Long-term EIS measurements were conducted for NCM85 ASSBs on charge to $4.3\\mathrm{V},$ and the corresponding Nyquist plots in Fig. 6e show no internal resistance increase over 160 cycles. This is in accord with a recent finding that transmission electron microscopy images did not show any change of $\\mathrm{LiNi}_{0.88}\\mathrm{Co}_{0.11}\\mathrm{Al}_{0.01}\\mathrm{O}_{2}$ surfaces in contact with a chloride SE cycled to $4.3\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i^{42}}$ . Such remarkably stable impedance confirms the high oxidation stability of chloride SE (up to $4.6\\mathrm{V}$ versus $\\mathrm{Li^{+}}/$ Li), which allows the use of bare CAMs. \n\n![](images/d8ded4b50efb31ceb6126498ac525e1294d761f32ac6e342e2d58c8758f71c02.jpg) \nFig. 4 | Long-term and high-voltage electrochemical performance of ASSBs. a,b, Charge–discharge capacity and the coulombic efficiency (CE) as a function of cycle number for NCM85 ASSB (a) and NCM622 ASSB (b). $c-e$ , Long-term cycling of the NCM85 ASSB (performed after rate cycling) at $\\textsf{a3C}$ rate (c) and ultra-high voltage NCM85 ASSB cycled between 2.8 and $4.8\\mathsf{V}$ versus $\\mathsf{L i^{+}/L i}$ (d) and the corresponding charge–discharge voltage profile (e). \n\nTo evaluate interphase growth between NCM85 and SE at a higher potential of $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ , the impedance was also monitored at numerous points during the first charge–discharge cycle, and showed excellent reversibility (Supplementary Fig. 18). An accelerated degradation test was conducted by charging the cell to $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ and holding for an extended period. The $4.8\\mathrm{V}$ ageing-test leakage current (Fig. 7a) quickly decreased to reach a minimum value of ${<}1\\upmu\\mathrm{A}$ at the end of a 30 hour hold, which suggests a very stable interface is formed between NCM85 and $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ . The EIS data (Supplementary Fig. 19a) show a continuous increase of cell impedance during this process and a final charge transfer resistance of $31\\mathrm{k}\\Omega$ (Supplementary Fig. 19b), caused by the very large drop in Li-ion mobility41 and electronic conductivity in highly delithiated NCM85 (estimated here to be $\\mathrm{Li}_{0.07}\\mathrm{Ni}_{0.85}\\mathrm{Co}_{0.1}\\mathrm{Mn}_{0.05}\\mathrm{O}_{2})$ . We note that if this impedance originated from the decomposition of $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ at high voltage, the cell would show significantly increased overpotential and decreased capacity in the following cycles; that is not observed, however. Stable cycling (Fig. 7b) after ageing, and low impedance (Fig. 7c) after final discharge, confirms the existence of a stable interface between NCM85 and $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ even at $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ . A similar stable interface was observed for cells aged at $4.3\\mathrm{V}$ and $4.6\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ (Supplementary Figs. 20 and 21). \n\n![](images/f5b20b6cdc8a36c6755892972ff7f04114db85d2603d145b5d4c158b9304c3b9.jpg) \nFig. 5 | High-loading ASSB electrochemical performance. a,b, Charge–discharge capacity and CE as a function of cycle number for LCO ASSBs with areal capacity $>3.5\\mathsf{m A h c m^{-2}}$ cycled at room temperature (RT) between 2.8 and $4.3\\mathsf{V}$ versus $\\mathsf{L i^{+}/L i}$ at C/3 $(1.24\\mathsf{m A}\\mathsf{c m}^{-2})$ (a) and at $50^{\\circ}C$ between 3.0 and $4.3\\mathsf{V}$ versus Li+/Li at $\\mathsf{C}/2$ $(1.79\\mathsf{m A c m^{-2}})$ ) (b). $c-e.$ Ultra-high-loading LCO ASSB with $52.46\\mathsf{m g c m}^{-2}$ loading, cycled at RT between 2.6 and $4.4\\mathsf{V}$ versus $\\mathsf{L i^{+}/L i}$ and at $50^{\\circ}C$ between 2.6 and $4.3\\mathsf{V}$ versus $\\mathsf{L i^{+}/L i}$ at C/ $\\mathsf{)}(1.20\\mathsf{m A c m^{-2}},$ ) (c) and high-loading NCM85 ASSB with $21.59\\mathsf{m g c m}^{-2}$ loading cycled at room temperature between 2.8 and $4.3\\mathsf{V}$ versus $\\mathsf{L i^{+}/L i}$ at $\\mathsf{C}/8(0.49\\mathsf{m A c m^{-2}};$ (d) and the corresponding charge–discharge curves (e). A wider cut-off potential window was used for high-loading ASSBs cycled at RT than at $50^{\\circ}C$ owing to the higher overpotential incurred at these current densities (due to limited kinetics of Li-ion/electron diffusion in the thick cathode composite; see Supplementary Fig. 11 for details). \n\nInterface stability is further confirmed by time-of-flight secondary-ion mass spectrometry (TOF-SIMS) surface analysis (Fig. 7d–f and Supplementary Figs. 22–24). TOF-SIMS is highly sensitive even to small fractions of components, and it has recently been shown that SE degradation at the SE/CAM interface and thin coatings can be well analysed14,43. Cathode composites cycled to different cut-off potentials ( $4.3\\mathrm{V},4.6\\mathrm{V}$ and $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ ) were compared to an uncycled cathode composite and the pristine SE. The $\\mathrm{ClO^{-}}$ and $\\mathrm{{scO^{-}}}$ fragments could be a sign of the decomposition of $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ and reaction with lattice oxygen from NCM at high voltage. However, both signals (Fig. 7e,f) exhibit no obvious increase after cycling compared to the uncycled composite. This indicates minimal reaction of chloride SE occurs with NCM— even up to $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ —as a result of a kinetic overpotential due to the extremely low electronic conductivity $(4.7\\times10^{-10}\\mathrm{Scm^{-1}})$ of $\\mathrm{Li_{2}I n_{1/3}S c_{1/3}C l_{4}}$ . The presence of $\\mathrm{ClO^{-}}$ and $\\mathrm{{scO^{-}}}$ signals in $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ and uncycled composite may well originate from impurities in the synthesis of $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4},$ as residual $\\mathrm{H}_{2}\\mathrm{O}$ could be present in the precursors and quartz tube. The slightly increased signal in the uncycled composite compared to pristine SE could originate either from the residual $_\\mathrm{H}_{2}\\mathrm{O}$ or $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ contamination on the surface of NCM85 particles, as well as from a slightly higher formation rate of secondary ions in the presence of electronically conducting NCM. We point to the much higher and also unchanged signal of $\\mathrm{Cl^{-}}$ ions, which also supports the stability of the SE at the interface with NCM. \n\n![](images/a7e26247aef8b4179630356d551c4365c96c128616ffe508a944140d5039c05f.jpg) \nFig. 6 | ASSB cell impedance evolution during cycling at a C/5 rate. a–c, Impedance evolution during the first cycle of an NCM622 ASSB cycled between 2.8 and $4.6\\mathsf{V}$ versus Li+/Li. The corresponding voltage profile (a) and impedance spectra collected during charging (b) and discharging (c) are shown. The numbers on the voltage profile correspond to the points where the EIS spectra were collected at every hour after a $30\\mathrm{min}$ rest (before and after). d,e, Nyquist plots of an NCM622 ASSB cycled between 2.8 and $4.6\\mathsf{V}$ versus $\\mathsf{L i^{+}/L i}$ for 10 cycles at full discharge, cells were equilibrated for 1 h before and after (d), and an NCM85 ASSB cycled between 2.8 and $4.3\\mathsf{V}$ versus Li+/Li for 160 cycles and equilibrated at full discharge for 1 h before and after (e). The long diffusion tail in the initial spectrum disappears on subsequent discharge because the pristine state is not attained on Li re-insertion. \n\nSulfide SEs, on the other hand, require a CAM coating layer with low electronic and high ionic conductivity to prevent electrolyte oxidation. ${\\mathrm{LiNb}}O_{3}$ is the commonly used material43,44. It is electronically insulating $(10^{-11}\\mathsf{S c m}^{-1})$ and a poor ion conductor $(\\sim10^{-6}\\mathrm{{Scm^{-1}})^{45}}$ . These properties nonetheless present challenges for cathode design because the low Li-ion conductivity limits Li-ion transfer at the CAM/SE interface (Fig. 8a). Not only is it difficult for the thin coating to homogeneously cover the CAM particles, but also the layer can rupture during fabrication of the cathode composite. Partial electronic conduction through cathode particles can thus occur, and trigger sulfide SE oxidation46–48. In contrast, the high potential limit of chloride SEs means bare CAMs can be used, which takes advantage of their inherently high electronic and ionic conductivity. Cathode composites with a high volume ratio of CAM/SE provide direct electronic and Li-ion percolation pathways between CAM particles (Fig. 8a). Due to the high deformability of the chloride SE, simply grinding it with the CAM coats the cathode surface. By controlling the volume ratio between CAM and chloride SE, a semi-uniform, patchy, thin SE coating on the CAM is obtained, as revealed by scanning electron microscopy (SEM) images (Fig. $8\\mathrm{b,c}$ ) and energy-dispersive X-ray spectroscopy (EDX) maps (Fig. 8d) of $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ -coated NCM85. Supplementary Figs. 25 and 26 show the same for other CAMs (LCO and NCM622). While the high ionic conductivity of the halide coating provides excellent transport of Li-ions in/out of the CAM, importantly, its low electronic conductivity prevents electron leakage from the SE that would result in degradation. More stable cycling is observed when the SE exhibits lower electronic conductivity27. The decomposition (oxidation) of any SE at high voltage can only occur via electron diffusion through the interface between the SE and NCM, while a sharp electrochemical potential drop at the interphase layer will prevent this49. As $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ exhibits a very low $\\sigma_{\\mathrm{e}}/\\sigma_{\\mathrm{i}}$ ratio of $\\sim10^{-7}$ , its oxidation at high voltage is strongly limited by poor electron diffusion. This leads to sluggish kinetics, and thus a higher stability window than predicted by thermodynamics. Such a kinetically driven wider electrochemical stability window is commonly observed for other SEs, such as sulfides (thermodynamic stability ${\\sim}2.3\\mathrm{V},$ experimental limit: $2.8\\mathrm{-}3.1\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i})$ 2. Furthermore, when NCM is charged to high voltage (that is, $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}^{\\cdot}$ , the outer surface layer of the NCM particles becomes highly Li-deficient. The significantly lower electronic conductivity (Supplementary \n\n![](images/5798d15960e3f4eef8f0edfae4316482a000e8b7463c1fecdf4101f516a68f83.jpg) \nFig. 7 | Interface evolution between NCM85 and $\\mathsf{L i}_{2}\\mathsf{I n}_{1/3}\\mathsf{S c}_{1/3}\\mathsf{C l}_{4}$ at high voltage up to $\\pmb{4.8\\vee}$ versus Li+/Li. a, Leakage current during a hold of NCM85 ASSB at constant voltage of $4.8\\mathsf{V}$ versus $\\mathsf{L i^{+}/L i}$ after first charge (ageing test). b, Charge–discharge voltage profile of NCM85 ASSB. After initial charge, the cell was aged at $4.8\\mathsf{V}$ versus Li+/Li for 30 hours, followed by continuous cycling after ageing. c, Nyquist plots of NCM85 ASSB at the initial state, after 5th discharge and after cell discharge held at $2.8\\mathsf{V}$ versus Li+/Li for 10 h. d–f, TOF-SIMS surface analysis results of $C^{1^{-}}$ (d), ${\\mathsf{C l O}}^{-}$ (e) and $\\mathsf{S c O^{-}\\left(f\\right)}$ fragments of bare SE, uncycled cathode composite (OCV) and cycled composites with cut-off potentials of $4.3\\mathsf{V}$ (160 cycles), $4.6\\mathsf{V}$ (20 cycles) and $4.8\\mathsf{V}$ (10 cycles) versus $\\mathsf{L i^{+}/L i}$ , at a discharged state. The box plots were obtained on the basis of the corresponding normalized signal intensities of 12 spectra on each sample. Box plot centre line represents the median (of median F1 scores); lower and upper box limits represent the $25\\%$ and $75\\%$ quantiles, respectively; whiskers extend to box limit $\\pm1.5\\times101.$ outlying points plotted individually. The minima, maxima, median, bounds of box and whiskers, and percentile are provided in Supplementary Table 8. \n\nFig. 19b) that results further limits the decomposition of SE at high voltage. Nonetheless, because of the low SE:CAM ratio, contact of the residual bare CAM surfaces still provides an electronic conduit between the particles. Thus, an optimal 3D interconnected mixed ionic/electronic network is realized, which is essential for ASSB performance. Operation of the cell under external pressure is necessary to maintain the network on cycling (Supplementary Figs. 27 and 28), since volume expansion/contraction of the CAM particles will otherwise lead to loss of contact of CAM/SE and increasing cell internal resistance50. However, high-Ni content CAMs, such as NCM85, still inevitably form cracks and voids on extended cycling that slowly degrade the contact, although over $80\\%$ capacity retention can still be maintained over ${3,000+}$ cycles (Fig. 4c). While recognizing that a high applied pressure is not practical in commercial cells, the pressure required partly depends on the nature of the CAM. Hence the development of new CAMs that exhibit minimal volume change on redox along with high ionic/electronic conductivity is important. Future studies also need to probe more precisely how low partial electronic conductivity benefits solid electrolytes by increasing their electrochemical (kinetic) oxidative stability. \n\n# Conclusions \n\nA lithium mixed-metal chloride family of SEs, $\\mathrm{Li}_{2}\\mathrm{In}_{x}\\mathrm{Sc}_{0.666-x}\\mathrm{Cl}_{4},$ exhibits high ionic conductivity up to $2.0\\mathrm{mScm^{-1}}$ over a wide compositional range. The $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ spinel exhibits low electronic conductivity of $4.7\\times10^{-10}\\mathrm{Scm^{-1}}$ , which is one order of magnitude lower than that of $\\mathrm{Li}_{2}\\mathrm{Sc}_{2/3}\\mathrm{Cl}_{4},$ and contributes to its stability at high voltage. Excellent electrochemical performance is demonstrated for bulk-type ASSBs with $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ in combination with bare-LCO, NCM622 and NCM85 at potentials up to $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ . EIS and TOF-SIMS results indicate a stable interface exists between CAMs and chloride SE, confirming the high oxidation stability and chemical compatibility of $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ in contact with uncoated oxide CAMs. These cells show long cycle life, maintaining $80\\%$ capacity retention at high current densities $3.36\\mathrm{mAcm}^{-2}$ ; 3C rate) over more than 3,000 cycles. These promising properties are in part due to the high plasticity of the chloride SE, which allows a semi-uniform thin coating on CAM particles to be obtained by gentle grinding. The residual bare surface facilitates electron transport between cathode particles. Incorporation of the SE in the cathode composite (between 10 and $20\\mathrm{wt\\%}$ ) thus provides a 3D interconnected mixed ionic/electronic network within the cathode composite. The applied pressure ensures good CAM/SE contact during long-term cycling, which is essential for ASSB performance. Thus, ASSBs with high CAM loading (up to $52.5\\mathrm{mg}\\mathrm{cm}^{-2}$ of LCO) deliver stable capacity retention. NCM85 cells are also realized with high areal capacity $(>4\\mathrm{mAh}\\mathrm{cm}^{-2}.$ ), high specific capacity $(>190\\mathrm{mAh}\\bar{\\bf g}^{-1})$ and good cycling behaviour, even at a high cut-off potential of $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ . Further developments that will translate the concepts to more earth-abundant and cost-effective lithium metal chloride SEs—and fluoride SEs for next-generation $5\\mathrm{V}$ cells—are anticipated, along with advances in cell design and architecture. These can potentially meet the growing demand for next-generation energy-storage systems for applications such as electric mobility. \n\n![](images/0eb5d8026b853c6dba7c20c47abe371a083465200866814d0918681232291527.jpg) \nFig. 8 | Ionic and electronic percolation within cathode composite. a, Schematic illustration of ionic and electronic conduction percolation within a cathode composite of $\\mathsf{L i N b O}_{3}$ -coated NCM with a sulfide solid electrolyte, and bare NCM with a chloride solid electrolyte. With the poorly conductive $(\\mathrm{e^{-}/L i^{+}})$ $\\mathsf{L i N b O}_{3}$ coating, both electronic and ionic conductivity between NCM particles are significantly blocked. However, for uncoated NCM and the chloride solid electrolyte, direct contact between NCM particles provides sufficient electronic percolation; combined with Li-ion diffusion through the solid electrolyte and within the NCM particles, conduction within the cathode composite is considerably enhanced. Red arrows show $\\mathsf{e}^{-}$ conduction between NCM particles, and black crosses indicate blockage of conduction. Blue arrows show ${\\mathsf{L i}}^{+}$ conduction between NCM particles and between NCM particles and SE and within SE (the thinner blue arrows on the left indicate poor $\\mathsf{L i^{+}}$ conduction owing to the low ionic conductivity coating of $\\mathsf{L i N b O}_{3})$ . b,c, SEM images of bare NCM85 (b) and $\\mathsf{L i}_{2}|\\mathsf{n}_{1/3}\\mathsf{S c}_{1/3}\\mathsf{C l}_{4}$ -coated NCM85 (c) after grinding. d, Expanded SEM image of $\\mathsf{L i}_{2}\\mathsf{I n}_{1/3}\\mathsf{S c}_{1/3}\\mathsf{C l}_{4}$ -coated NCM85 with EDX mapping of Cl demonstrates the presence of the chloride solid electrolyte on the surface of NCM85 particles. \n\n# Methods \n\nSolid electrolyte synthesis. A simple approach based on mixing and heating of the precursors was used. Stoichiometric amounts of LiCl (Sigma-Aldrich, $99.9\\%$ ), $\\mathrm{InCl}_{3}$ (Alfa Aesar, $99.99\\%$ ) and $\\mathrm{\\ScCl}_{3}$ (Strem Chemical, $99.99\\%$ ) were combined at the targeted ratio, pelletized and placed in a sealed quartz tube under vacuum. The pellet was heated to $650^{\\circ}\\mathrm{C}$ at a heating rate of $5^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ and sintered at $650^{\\circ}\\mathrm{C}$ for 48 hours, then slowly cooled to room temperature at $10^{\\circ}\\mathrm{Ch^{-1}}$ . $\\mathrm{Li}_{2}\\mathrm{Sc}_{2/3}\\mathrm{Cl}_{4}$ was synthesized as described in our previous paper26. \n\n$\\mathbf{X}$ -ray and neutron powder diffraction and structure resolution. Powder X-ray diffraction measurements were conducted at room temperature on a PANalytical Empyrean diffractometer employing CuKα radiation, and the diffractometer was equipped with a PIXcel bidimensional detector. X-ray diffraction patterns were obtained in Bragg–Brentano geometry, with samples placed on a zero-background sample holder in an Ar-filled glovebox and protected by a Kapton film. Selected compositions were measured in Debye–Scherrer geometry with high resolution and long scan times to identify trace impurities, with samples sealed in $0.3\\mathrm{mm}$ (diameter) glass capillaries under argon. \n\nTOF powder neutron diffraction data were collected on POWGEN at the Spallation Neutron Source at Oak Ridge National Laboratory. The sample $(\\sim1\\mathrm{g})$ was loaded into a vanadium can under an argon atmosphere and sealed with a copper gasket and aluminium lid. The sample was measured at $300\\mathrm{K}$ , and a single bank wave with a centre wavelength of $1.5\\dot{\\mathrm{\\AA}}$ was used. Structure analysis was performed using the TOPAS v.6 software package. \n\nIonic conductivity and activation energy measurements. The ionic conductivity was measured by EIS. Typically, ${\\sim}250\\mathrm{mg}$ of the solid electrolyte powder was placed between two stainless steel rods and pressed into a $10\\mathrm{mm}$ diameter pellet by a hydraulic press at 3 tons for 1 min in an Ar-filled glovebox. EIS experiments were performed with $100\\mathrm{mV}$ constant voltage within a frequency range of $1\\mathrm{MHz}$ to $100\\mathrm{mHz}$ using a VMP3 potentiostat/galvanostat (BioLogic). For activation \n\nenergy measurements, ${\\sim}260\\mathrm{mg}$ of the solid electrolyte powder was placed between two stainless steel rods and pressed into a $10\\mathrm{mm}$ diameter pellet by a hydraulic press at 3 tons for $3\\mathrm{min}$ in a custom-made cell, and the cell was then kept in a custom-made cage to maintain a pressure of ${\\sim}250\\ensuremath{\\mathrm{MPa}}$ . The impedance was measured from $35\\mathrm{MHz}$ to $100\\mathrm{mHz}$ at temperatures ranging from 30 to $60^{\\circ}\\mathrm{C}$ using an MTZ-35 impedance analyser (BioLogic). \n\nElectrochemical measurements. ASSBs employing the $\\mathrm{Li_{2}I n_{1/3}S c_{1/3}C l_{4}}$ solid electrolyte in combination with a $\\mathrm{LiCoO}_{2}$ (LCO, Wellcos, $D_{50}{=}16.2\\upmu\\mathrm{m}\\rangle$ , $\\mathrm{LiNi_{0.6}C o_{0.2}M n_{0.2}O_{2}}$ (NCM622, BASF, $D_{50}{=}5\\upmu\\mathrm{m})$ or $\\mathrm{LiNi_{0.85}C o_{0.1}M n_{0.05}O_{2}}$ (NCM85, BASF, $D_{50}{=}5~{\\upmu\\mathrm{m}}$ cathode active material and a $\\mathrm{In/InLi}$ anode were assembled in an argon-filled glovebox. All cathode active materials were stored in Ar-filled glovebox and used as received without any treatment. $\\mathrm{Li}_{6.7}\\mathrm{Si}_{0.7}\\mathrm{Sb}_{0.3}\\mathrm{S}_{5}\\mathrm{I}$ was synthesized following our previously reported procedure34. First, ${\\sim}100\\mathrm{mg}$ of $\\mathrm{Li}_{6.7}\\mathrm{Si}_{0.7}\\mathrm{Sb}_{0.3}\\mathrm{S}_{5}\\mathrm{I}$ powder was placed into a PEEK cylinder and pressed at 2 tons for $1\\mathrm{min}$ ( $10\\mathrm{mm}$ diameter), and then ${\\sim}40\\mathrm{mg}$ of $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ was spread over one side of the $\\mathrm{Li}_{6.7}\\mathrm{Si}_{0.7}\\mathrm{Sb}_{0.3}\\mathrm{S}_{5}\\mathrm{I}$ pellet and pressed at 2 tons for another 1 min. The composite cathode mixtures were prepared by mixing LCO or NCM622 or NCM85 and $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ at a weight ratio of 8:2 or 9:1. On the $\\mathrm{Li}_{2}\\mathrm{In}_{1/3}\\mathrm{Sc}_{1/3}\\mathrm{Cl}_{4}$ side of the SE pellet, ${\\sim}6{-}9\\mathrm{mg}$ of the composite cathode mixture (corresponding to an areal capacity of $\\cdot{\\mathrm{-}}1.1{\\mathrm{-}}1.25{\\mathrm{mAhcm}}^{-2}$ ) was spread and pressed at 3 tons for $3\\mathrm{min}$ . For high-loading cells, ${\\sim}20{\\mathrm{-}}53\\mathrm{mg}$ cathode composite was used, and the corresponding areal capacities are labelled in the figures. On the other side of the pellet, a thin indium foil ( $10\\mathrm{mm}$ diameter, $99.99\\%$ , $0.1\\mathrm{mm}$ thickness) was attached and ${\\sim}1\\mathrm{mg}$ Li foil (Sigma-Aldrich) was pressed into a thin layer (around $5\\mathrm{mm}$ diameter) and placed over the indium foil. The cell was placed into a custom-made stainless steel casing with a constant applied pressure of ${\\sim}250\\mathrm{MPa}$ during cycling. \n\nNCM liquid cells were assembled following standard procedures. For electrode fabrication, NCM622 or NCM85 powder was mixed with Super P carbon (Timcal) and polyvinylidene fluoride (Sigma-Aldrich, average $M_{\\mathrm{w}}\\approx534,000$ GPC) to achieve a final weight ratio of 8:1:1 (active material:carbon:binder). The powdered mixture was then suspended in $N.$ -methyl-2-pyrrolidinone (Sigma-Aldrich, $99.5\\%$ ) to obtain a viscous slurry, which was cast on Al foil with a typical loading of $\\sim$ $3.6\\mathrm{mgcm}^{-2}$ . The electrodes were punched to a $1\\mathrm{cm}^{2}$ geometric area and dried in a vacuum oven at $120^{\\circ}\\mathrm{C}$ overnight. Electrochemical studies were carried out in 2325 coin-type half-cells with a Li-metal anode, Celgard 3501 separator and LP57 electrolyte (Gotion, $1\\mathrm{MLiPF}_{6}$ in ethylene carbonate:ethyl methyl carbonate at a ratio of 3:7). \n\nGalvanostatic cycling of the cell was carried out in different voltage ranges at different rates (as labelled) using a VMP3 (BioLogic) cycler. Rate current density calculations used conventional values for LCO $\\mathrm{^{\\prime}1C=137\\ m A g^{-1}}$ ) and NCM622/ NCM85 $\\mathrm{^{\\prime}1C=180\\ m A g^{-1}}$ ). \n\nASSBs with LCO, NCM622 and NCM85 CAMs were constructed for impedance measurements following the same procedure as above and cycled at $C/5$ as indicated. Measurements were conducted after every 1 hour of charge–discharge, before and after which the cells were placed at rest for $30\\mathrm{min}$ . For the impedance measurements after full discharge, the cells were placed at rest for 1 h before and after the measurement. \n\nASSBs with NCM85 for ageing experiments were constructed following the same procedure. Cells were first charged to $4.3\\mathrm{V},$ 4.6 V and $4.8\\mathrm{V}$ versus $\\mathrm{Li^{+}/L i}$ respectively, followed by constant potential ageing at 4.3 V, $4.6\\mathrm{V}$ and $4.8\\mathrm{V}$ for $30\\mathrm{h}$ . EIS was conducted every $20\\mathrm{min}$ of ageing with constant applied potentials of $4.3\\mathrm{V},$ $4.6\\mathrm{V}$ and $4.8\\mathrm{V},$ and no rest. After ageing, the cells were continuously cycled for several cycles. Then, the final EIS spectra were measured at the discharged state with no constant applied potential and $0.5\\mathrm{h}$ rest after discharge. \n\nTOF-SIMS. Cycled cathode composites NCM85- $\\mathrm{.Li_{2}I n_{1/3}S c_{1/3}C l_{4}}$ (cut-off $4.3\\mathrm{V}$ for 160 cycles, cut-off $4.6\\mathrm{V}$ for 20 cycles and cut-off 4.8 V for 10 cycles) were compared to pristine SE and uncycled cathode composite, and all measurements were conducted at the discharged state. The chemical characterization was performed on a Hybrid TOF-SIMS M6 machine (IONTOF). To transfer the samples from the glovebox into the measurement chamber, the transfer module Leica EM VCT500 (Leica Microsystems) was applied to guarantee an argon atmosphere. The measurements were conducted on the top surface of the cathode composite pellets. \n\nTo avoid topographic interference and ensure reproducibility, we measured 12 mass spectra in different areas on each sample. The measurements were carried out in spectrometry mode (bunched mode), which enables a high mass resolution (full-width at half-maximum $m/\\Delta m>7,000$ at m/z 34.97 $\\left(\\mathrm{Cl^{-}}\\right)^{}$ ). All spectra were collected in negative-ion mode using a $60\\mathrm{keV}$ ${\\mathrm{Bi}_{3}}^{++}$ cluster primary ion gun. The cycle time was set to $100\\upmu\\mathrm{s}$ . The measurement area was set to $150\\times150\\upmu\\mathrm{m}^{2}$ and rasterized with $256\\times256$ pixels. For each patch, 1 frame and 1 shot per pixel and frame were chosen. The primary ion current was about $0.43\\mathrm{pA}$ . To enable the semiquantitative analysis, the stop condition was set with the primary ion dose of $10^{12}$ ions per $\\mathrm{cm}^{2}$ . \n\nThe data evaluation was conducted with Surfacelab v.7.2 software (IONTOF). The secondary-ion signals were normalized to the total ion signals, and all signal intensities were collected from the corresponding normalized secondary-ion images. \n\nScanning electron microscopy. Material morphologies and elemental analysis studies utilized a Zeiss field-emission scanning electron microscope equipped with an EDX detector. \n\nSingle-crystal diffraction. The data were collected on a Bruker Kappa diffractometer equipped with a Smart Apex II CCD, utilizing graphite-monochromated MoKα radiation. The crystal was protected by Paratone-N oil and a liquid nitrogen flow using an Oxford Cryostream controller 700 at $270\\mathrm{K}$ , to ensure no reactivity of the materials occurred. The data were collected by scanning $\\omega$ of $0.3^{\\circ}$ in a few groups of frames at different $\\phi$ and an exposure time of 60 s per frame (generic omega and phi scans). The data were corrected for Lorentz and polarization effects. Absorption correction was carried out using the empirical multiscan method SADABS, part of the Bruker suite. Cell_Now software was used to check for potential twinning and indexing the unit cell reflections, with $I/\\sigma$ below 5 to check for a possible supercell, but no supercells were observed. The structure was solved by direct methods to locate the positions of In and Cl atoms. First, these positions were anisotropically refined using the least-squares method incorporated in the SHELXTL package. The In site was refined as a mixed $\\mathrm{In/Sc}$ of around $67\\%$ and $33\\%$ , respectively. Then, the Li positions were located in the remaining electron density in the Fourier map, which revealed Li–Cl bonds very similar in length to those found in binary and ternary Li chlorides. Subsequently, the Li site occupancies were freely and anisotropically refined except for Li2, which was isotropically refined. The refinement was converged to good residual values $R1=0.0365$ and $\\mathrm{w}R2=0.0762$ for all data. The program Tidy was used to standardize the atomic positions. No constraints were used during the structure refinements, except for the $\\mathrm{{In/Sc}}$ mixed site. \n\n# Data availability \n\nData generated and analysed in this study are included in the paper and Supplementary Information. The single-crystal X-ray crystallographic data for the structure reported in this study has been deposited at the Cambridge Crystallographic Data Centre under deposition number 2115525. These data can be obtained free of charge from the Cambridge Crystallographic Data Centre via www.ccdc.cam.ac.uk. \n\nReceived: 24 March 2021; Accepted: 2 November 2021; Published online: 3 January 2022 \n\n# References \n\n1.\t Trahey, L. et al. Energy storage emerging: a perspective from the Joint Center for Energy Storage Research. Proc. Natl Acad. Sci. USA 1, 12550–12557 (2020). \n2.\t Lee, Y. G. et al. High-energy long-cycling all-solid-state lithium metal batteries enabled by silver-carbon composite anodes. Nat. Energy 5, 299–308 (2020). \n3.\t Randau, S. et al. Benchmarking the performance of all-solid-state lithium batteries. Nat. Energy 5, 259–270 (2020). \n4. Chen, R., Li, Q., Yu, X., Chen, L. & Li, H. Approaching practically accessible solid-state batteries: stability issues related to solid electrolytes and interfaces. Chem. Rev. 120, 6820–6877 (2020). \n5. Zhang, Z. et al. New horizon for inorganic solid state ion conductors. Energy Environ. Sci. 11, 1945–1976 (2018). \n6. Bachman, J. C. et al. Inorganic solid-state electrolytes for lithium batteries: mechanisms and properties governing ion conduction. Chem. Rev. 116, 140–162 (2016). \n7.\t Park, K. H. et al. Design strategies, practical considerations, and new solution processes of sulfide solid electrolytes for all-solid-state batteries. Adv. Energy Mater. 8, 1800035 (2018). \n8. Balaish, M. et al. Processing thin but robust electrolytes for solid-state batteries. Nat. Energy 6, 227–239 (2021). \n9. Kamaya, N. et al. A lithium superionic conductor. Nat. Mater. 10, 682–686 (2011). \n10.\tKato, T. et al. High-power all-solid-state batteries using sulfide superionic conductors. Nat. Energy 1, 16030 (2016). \n11.\t Zhu, Y., He, X. & Mo, Y. Origin of outstanding stability in the lithium solid electrolyte materials: insights from thermodynamic analyses based on first-principles calculations. ACS Appl. Mater. Interfaces 7, 23685–23693 (2015). \n12.\tDewald, G. F. et al. Experimental assessment of the practical oxidative stability of lithium thiophosphate solid electrolytes. Chem. Mater. 31, 8328–8337 (2019). \n13.\tSchwietert, T. K. et al. Clarifying the relationship between redox activity and electrochemical stability in solid electrolytes. Nat. Mater. 19, 428–435 (2020). \n14.\tWalther, F. et al. Visualization of the interfacial decomposition of composite cathodes in argyrodite-based all-solid-state batteries using time-of-flight secondary-ion mass spectrometry. Chem. Mater. 31, 3745–3755 (2019). \n15.\tBanerjee, A., Wang, X., Fang, C., Wu, E. A. & Meng, Y. S. Interfaces and interphases in all-solid-state batteries with inorganic solid electrolytes. Chem. Rev. 120, 6878–6933 (2020). \n16.\tXiao, Y., Miara, L. J., Wang, Y. & Ceder, G. Computational screening of cathode coatings for solid-state batteries. Joule 3, 1252–1275 (2019). \n17.\tNolan, A. M., Liu, Y. & Mo, Y. Solid-state chemistries stable with high-energy cathodes for lithium-ion batteries. ACS Energy Lett. 4, 2444–2451 (2019). \n18.\t Jung, S. H. et al. $\\mathrm{Li_{3}B O_{3}\\mathrm{-Li_{2}C O_{3}}};$ rationally designed buffering phase for sulfide all-solid-state Li-ion batteries. Chem. Mater. 30, 8190–8200 (2018). \n19.\tAsano, T. et al. Solid halide electrolytes with high lithium-ion conductivity for application in 4 V class bulk-type all-solid-state batteries. Adv. Mater. 30, 1803075 (2018). \n20.\tWang, S. et al. Lithium chlorides and bromides as promising solid-state chemistries for fast ion conductors with good electrochemical stability. Angew. Chem. Int. Ed. Engl. 58, 8039–8043 (2019). \n21.\tMuy, S. et al. High-throughput screening of solid-state Li-ion conductors using lattice-dynamics descriptors. iScience 16, 270–282 (2019). \n22.\t Li, X. et al. Air-stable $\\mathrm{Li}_{3}\\mathrm{InCl}_{6}$ electrolyte with high voltage compatibility for all-solid-state batteries. Energy Environ. Sci. 12, 2665–2671 (2019). \n23.\tPark, K. H. et al. High-voltage superionic halide solid electrolytes for all-solid-state Li-ion batteries. ACS Energy Lett. 5, 533–539 (2020). \n24.\tKim, S. Y. et al. Lithium ytterbium based halide solid electrolytes for high voltage all-solid-state batteries. ACS Mater. Lett. 3, 930–938 (2021). \n25.\tLiang, J. et al. Site-occupation-tuned superionic $\\mathrm{Li}_{x}\\mathrm{ScCl}_{3+x}$ halide solid electrolytes for all-solid-state batteries. J. Am. Chem. Soc. 142, 7012–7022 (2020). \n26.\tZhou, L. et al. A new halospinel superionic conductor for high-voltage all solid state lithium batteries. Energy Environ. Sci. 13, 2056–2063 (2020). \n27.\tKwak, H. et al. New cost-effective halide solid electrolytes for all-solid-state batteries: mechanochemically prepared $\\mathrm{Fe}^{3+}$ -substituted $\\mathrm{Li}_{2}\\mathrm{ZrCl}_{6}$ . Adv. Energy Mater. 11, 2003190 (2021). \n28.\tPark, J. et al. Heat treatment protocol for modulating ionic conductivity via structural evolution of $\\mathrm{Li}_{3-x}\\mathrm{Yb}_{1-x}\\mathrm{M}_{x}\\mathrm{Cl}_{6}$ ${\\mathrm{(M=Hf^{4+}}}$ , ${\\mathrm{Zr^{4+}}}$ ) new halide superionic conductors for all-solid-state batteries. Chem. Eng. J. 425, 130630 (2021). \n29.\tKato, Y. et al. All-solid-state batteries with thick electrode configurations. J. Phys. Chem. Lett. 9, 607–613 (2018). \n30.\tMinnmann, P., Quillmann, L., Burkhardt, S., Richter, F. H. & Janek, J. Quantifying the impact of charge transport bottlenecks in composite cathodes of all-solid-state batteries. J. Electrochem. Soc. 168, 040357 (2021). \n31.\t Liu, H. et al. Elucidating the limit of Li insertion into the spinel $\\mathrm{Li_{4}T i_{5}O_{12}}$ . ACS Mater. Lett. 1, 96–102 (2019). \n32.\tZhang, W. et al. Kinetic pathways of ionic transport in fast-charging lithium titanate. Science 367, 1030–1034 (2020). \n33.\tBohnsack, A. et al. Ternary halides of the $\\mathrm{A}_{3}\\mathrm{MX}_{6}$ type. Part VI. Ternary chlorides of the rare-earth elements with lithium, $\\mathrm{Li}_{3}\\mathrm{MCl}_{6}$ ( $\\mathbf{M}=$ Tb-Lu, Y, Sc): synthesis, crystal structures, and ionic motion. Z. Anorg. Allg. Chem. 623, 1067–1073 (1997). \n34.\tZhou, L. et al. New family of argyrodite thioantimonate lithium superionic conductors. J. Am. Chem. Soc. 141, 19002–19013 (2019). \n35.\tXue, W. et al. Ultra-high-voltage Ni-rich layered cathodes in practical Li metal batteries enabled by a sulfonamide-based electrolyte. Nat. Energy 6, 495–505 (2021). \n36.\tShi, T. et al. High active material loading in all-solid-state battery electrode via particle size optimization. Adv. Energy Mater. 10, 1902881 (2019). \n37.\tStrauss, F. et al. Impact of cathode material particle size on the capacity of bulk-type all-solid-state batteries. ACS Energy Lett. 3, 992–996 (2018). \n38.\tHan, F. et al. Interphase engineering enabled all-ceramic lithium battery. Joule 2, 497–508 (2018). \n39.\tKubanska, A., Castro, L., Tortet, L., Dollé, M. & Bouchet, R. Effect of composite electrode thickness on the electrochemical performance of all-solid-state Li-ion batteries. J. Electroceram. 38, 189–196 (2017). \n40.\tAmin, R. & Chiang, Y. M. Characterization of electronic and ionic transport in in $\\mathrm{Li}_{1-x}\\mathrm{Ni}_{0.33}\\mathrm{Mn}_{0.33}\\mathrm{Co}_{0.33}\\mathrm{O}_{2}$ (NMC333) and $\\mathrm{Li}_{1-x}\\mathrm{Ni}_{0.50}\\mathrm{Mn}_{0.20}\\mathrm{Co}_{0.30}\\mathrm{O}_{2}$ (NMC523) as a function of Li content. J. Electrochem. Soc. 163, A1512 (2016). \n41.\tMärker, K. et al. Evolution of structure and lithium dynamics in $\\mathrm{LiNi_{0.8}M n_{0.1}C o_{0.1}O_{2}}$ (NMC811) cathodes during electrochemical cycling. Chem. Mater. 31, 2545–2554 (2019). \n42.\tHan, Y. et al. Single- or poly-crystalline Ni-rich layered cathode, sulfide or halide solid electrolyte: which will be the winner for all-solid-state batteries? Adv. Energy Mater. 11, 2100126 (2021). \n43.\tWalther, F. et al. The working principle of a $\\mathrm{Li_{2}C O_{3}/L i N b O_{3}}$ coating on NCM for thiophosphate-based all-solid-state batteries. Chem. Mater. 33, 2110–2125 (2021). \n44.\t Ohta, N. et al. $\\mathrm{LiNb}{\\mathrm{O}}_{3}$ -coated $\\mathrm{LiCoO}_{2}$ as cathode material for all solid-state lithium secondary batteries. Electrochem. Commun. 9, 1486–1490 (2007). \n45.\tGlass, A. M., Nassau, K. & Negran, T. J. Ionic conductivity of quenched alkali niobate and tantalate glasses. J. Appl. Phys. 49, 4808 (1978). \n46.\t Strauss, F. et al. $\\mathrm{Li}_{2}Z\\mathbf{r}\\mathrm{O}_{3}.$ -coated NMC622 for application in inorganic solid-state batteries: role of surface carbonates in the cycling performance. ACS Appl. Mater. Interfaces 12, 557146–557154 (2020). \n47.\tBanerjee, A. et al. Revealing nanoscale solid–solid interfacial phenomena for long-life and high-energy all-solid-state batteries. ACS Appl. Mater. Interfaces 11, 443138–43135 (2019). \n48.\tZhang, Y. Q. et al. Direct visualization of the interfacial degradation of cathode coating in solid state batteries: a combined experimental and computational study. Adv. Energy Mater. 10, 1903778 (2020). \n49.\tNakamura, T. et al. Guidelines for all-solid-state battery design and electrode buffer layers based on chemical potential profile calculation. ACS Appl. Mater. Interfaces 11, 19968–19976 (2019). \n50.\tKoerver, R. et al. Chemo-mechanical expansion of lithium electrode materials—on the route to mechanically optimized all-solid-state batteries. Energy Environ. Sci. 11, 2142–2158 (2018). \n\n# Acknowledgements \n\nThis work was supported by the Joint Center for Energy Storage Research, an Energy Innovation Hub funded by the US Department of Energy, Office of Science, Basic Energy Sciences and NSERC via their Canada Research Chair and Discovery Grant programmes. The neutron diffraction measurement at the POWGEN instrument at Oak Ridge National Laboratory, Spallation Neutron Source, was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, US Department of Energy. TOF-SIMS measurements were performed at the Justus Liebig University Giessen (funding through Bundesministerium für Bildung und Forschung projects 03XP0177D/03XP0228C). We thank BASF SE for providing NCM622 and NCM85 cathode active materials. \n\n# Author contributions \n\nL.Z. and L.F.N. conceived and designed the experimental work. L.Z. performed the synthesis of the solid electrolytes, powder X-ray diffraction measurements, structural resolution of powder neutron diffraction and the electrochemistry of all-solid-state batteries. T.-T.Z. performed the TOF-SIMS measurements, and data analysis was performed by T.T.Z. and J.J. C.Y.K. performed the SEM measurements. S.Y.K. performed the electrochemistry of liquid NCM cells. A.A. performed single-crystal diffraction and structure resolution. Q.Z. performed the powder neutron diffraction measurements. L.Z. and L.F.N. wrote the manuscript with input from all authors. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41560-021-00952-0. Correspondence and requests for materials should be addressed to Linda F. Nazar. Peer review information Nature Energy thanks Yoon Seok Jung and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. $\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 " + }, + { + "id": "10.1126_science.abj7564", + "DOI": "10.1126/science.abj7564", + "DOI Link": "http://dx.doi.org/10.1126/science.abj7564", + "Relative Dir Path": "mds/10.1126_science.abj7564", + "Article Title": "Topological supramolecular network enabled high-conductivity, stretchable organic bioelectronics", + "Authors": "Jiang, YW; Zhang, ZT; Wang, YX; Li, DL; Coen, CT; Hwaun, E; Chen, G; Wu, HC; Zhong, DL; Niu, SM; Wang, WC; Saberi, A; Lai, JC; Wu, YL; Wang, Y; Trotsyuk, AA; Loh, KY; Shih, CC; Xu, WH; Liang, K; Zhang, KL; Bai, YH; Gurusankar, G; Hu, WP; Jia, W; Cheng, Z; Dauskardt, RH; Gurtner, GC; Tok, JBH; Deisseroth, K; Soltesz, I; Bao, ZN", + "Source Title": "SCIENCE", + "Abstract": "Intrinsically stretchable bioelectronic devices based on soft and conducting organic materials have been regarded as the ideal interface for seamless and biocompatible integration with the human body. A remaining challenge is to combine high mechanical robustness with good electrical conduction, especially when patterned at small feature sizes. We develop a molecular engineering strategy based on a topological supramolecular network, which allows for the decoupling of competing effects from multiple molecular building blocks to meet complex requirements. We obtained simultaneously high conductivity and crack-onset strain in a physiological environment, with direct photopatternability down to the cellular scale. We further collected stable electromyography signals on soft and malleable octopus and performed localized neuromodulation down to single-nucleus precision for controlling organ-specific activities through the delicate brainstem.", + "Times Cited, WoS Core": 383, + "Times Cited, All Databases": 397, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000778894800044", + "Markdown": "# BIOMATERIALS \n\n# Topological supramolecular network enabled high-conductivity, stretchable organic bioelectronics \n\nYuanwen Jiang1†, Zhitao Zhang1†, Yi-Xuan Wang $^{1,2\\ast}\\dag$ , Deling $\\mathsf{L i}^{3,4}\\dag$ , Charles-Théophile Coen1, Ernie Hwaun5, Gan Chen6, Hung-Chin Wu1, Donglai Zhong1, Simiao Niu1, Weichen Wang6, Aref Saberi1, Jian-Cheng Lai1,7, Yilei Wu1, Yang Wang6, Artem A. Trotsyuk8,9, Kang Yong Loh10, Chien-Chung Shih1, Wenhui ${\\tt X}{\\tt u}^{6}$ , Kui Liang11, Kailiang Zhang11, Yihong Bai2, Gurupranav Gurusankar1, Wenping ${\\mathsf{H}}{\\mathsf{u}}^{2}$ , Wang Jia4, Zhen Cheng3, Reinhold H. Dauskardt6, Geoffrey C. Gurtner9, Jeffrey B.-H. $\\mathbf{\\bar{\\tau}_{0k}}^{1}$ , Karl Deisseroth8,12,13, Ivan Soltesz5, Zhenan $\\mathbf{B}\\mathbf{a}\\mathbf{o}^{\\mathbf{1}*}$ \n\nIntrinsically stretchable bioelectronic devices based on soft and conducting organic materials have been regarded as the ideal interface for seamless and biocompatible integration with the human body. A remaining challenge is to combine high mechanical robustness with good electrical conduction, especially when patterned at small feature sizes. We develop a molecular engineering strategy based on a topological supramolecular network, which allows for the decoupling of competing effects from multiple molecular building blocks to meet complex requirements. We obtained simultaneously high conductivity and crack-onset strain in a physiological environment, with direct photopatternability down to the cellular scale. We further collected stable electromyography signals on soft and malleable octopus and performed localized neuromodulation down to single-nucleus precision for controlling organ-specific activities through the delicate brainstem. \n\nmplantable and wearable bioelectronic systems are essential in biomedical applications, including multimodal monitoring of physiological signals for disease diagnosis $(\\boldsymbol{I},\\boldsymbol{2})$ , programmable modulation of \nneural or cardiac activities for therapeutics \n(3, 4), restoration of lost sensorimotor func \ntions for prosthetics $(5,6)$ , and augmented \nreality (7). However, many of these existing \ndevices experience performance degradation, \nand sometimes failure, when operating in a \ndynamic-moving tissue environment (8). This \nstems primarily from the mechanical mis \nmatches between electronics and biological \nsystems (e.g., modulus and stretchability), which \ninevitably lead to interfacial delamination, \n\nfibrotic encapsulation, and/or gradual tissue scarring (9). \n\nTo maintain effective electrical signal exchanges across bioelectrode interfaces, efforts have been made to render rigid electronics and inorganic materials compliant to soft biological tissues (10, 11). Meanwhile, intrinsically stretchable organic electronics are fast emerging as a promising candidate with several specific advantages (12). First, they do not suffer from the inherent trade-off between overall system stretchability and device density for rigid materials. Therefore, high-resolution mapping and intervention can be realized with conformal biointerfaces (13) (Fig. 1A). Second, the high volumetric capacitance of conducting polymers (CPs) can reduce the electrode-tissue interfacial impedance, especially at physiologically relevant frequency ranges $(<10\\ \\mathrm{kHz})$ , which allows high recording fidelity and efficient stimulation charge injection (14, 15). However, electrical conductivities of existing stretchable CPs are too low once they are microfabricated into bioelectronic devices. As a result, rigid metal interconnects are still required, which greatly diminishes the advantages of soft CPs (12). \n\nHere, we describe a rationally designed topological supramolecular network to simultaneously enable three important advancements in bioelectronics. These advancements are (i) biocompatible and stretchable CPs with high conductivity, (ii) direct photopatternability down to cellular-level feature sizes, and (iii) high stretchability maintained after microfabrication with no crack formation under $100\\%$ strain (Fig. 1, B and C), all of which are essential for low-impedance and seamless biointegration (Fig. 1, D to G). \n\nPoly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) is among the highest performing and most investigated CPs for bioelectronic devices (12, 14, 16). Although ionic and molecular additives can improve its conductivity and stretchability $(I7)$ , after solvent treatment or immersion in aqueous biological environments, the performance of existing PEDOT:PSS films typically drops substantially because the non–cross-linked additives are washed away (18). To overcome these challenges, we designed a cross-linkable supramolecular additive based on a polyrotaxane (PR) structure. Our key hypothesis was that incorporating topology into molecular design might decouple competing effects using multiple molecular building blocks to meet complex requirements (19). We chose mechanically interlocked structures because they have large conformational freedom from the mobile junctions (20, 21). Therefore, by using a single supramolecular cross-linker with tailored chemistry and topology, we could achieve all desirable properties in one CP system (Fig. 1B). \n\nOur PR, which we call TopoE, is composed of a polyethylene glycol (PEG) backbone and sliding cyclodextrins (CDs) functionalized with PEG methacrylate (PEGMA) side chains to induce high conductivity, stretchability, and photopatternability (Fig. 2, A and B; synthesis and characterizations are available in figs. S1 to S9 and table S1). Although PEG has been known to induce the aggregation of PEDOT to enhance conductivity (22), its tendency to crystallize would lead to phase separation and poor stretchability. We hypothesized that the sliding CD units may prevent the crystallization of PEG and provide better stretchability. \n\nWe first investigated two control samples with PEG diacrylate (PEGDA) blended into PEDOT:PSS for covalent cross-linking. PEGDA10k was chosen to mimic a PR backbone, whereas PEGDA-575 was chosen for the PR side chain (see materials and methods). In both cases, crack formations were slightly delayed from ${\\sim}5\\%$ to $\\sim50$ or $30\\%$ strain, respectively (Fig. 2C and fig. S11). Further analyses using atomic force microscopy (AFM) and grazing incidence x-ray diffraction (GIXD) spectroscopy revealed that the films were inhomogeneous and suffered severe microphase separations, likely as a result of the crystallization of PEG (figs. S12 to S14). For PEG-ylated cyclodextrin (CD-PEGMA), its poor solubility in water prevented uniform blending with PEDOT:PSS such that the final crack-onset strain was measured to be only $\\sim30\\%$ . Similarly for PR-MA without any PEG side chains, it also could not dissolve well in water to enable good blending with PEDOT: PSS (Fig. 2D and fig. S11). \n\nHowever, PR-PEGMA was found to have the right balance between molecular topology and chemical polarity. It has good solubility in water as a result of the PEG-based backbone and side chains yet low crystallinity because of the bulky CD rings (fig. S14). As a result, the photo–cross-linked TopoE film with PRPEGMA/PEDOT:PSS was uniform and can be stretched up to $150\\%$ strain. The number of side chains on each PR-PEGMA molecule was also found to be important, with eight PEGMA chains being the optimal condition with the best stretchability (fig. S15). We also investigated other common multiarm PEGDA derivatives and observed that only our PR pulley topology was effective in enhancing the stretchability of PEDOT:PSS (fig. S16). The TopoE film can be directly photopatterned down to $2\\upmu\\mathrm{m}$ (Fig. 2E and fig. S17), and the cross-linked film after development maintained high stretchability (fig. S18). With these developments, we chose $\\mathrm{PR}{\\mathrm{-}}\\mathrm{PEGMA}_{8}$ (abbreviated as PR) for all future characterizations and fabrications. \n\n![](images/e667e7eef76b9c2cae92e612abaedcc6d47dc5ffe6382bea3ccc3888b66f0b77.jpg) \nFig. 1. Intrinsically stretchable organic electronics for multimodal and conformal biointerfaces. (A) A stretchable multielectrode array can form seamless interfaces with multiple organs for bidirectional interrogations with high precision. (B) Schematic diagram illustrating the intrinsically stretchable topological supramolecular network with the key molecular building blocks of \nPR monomers. L, length of film. (C) The topological supramolecular network allows direct photopatterning of a large-area, high-density stretchable electrode array. (D to G) Photographic images showing the conformal interface between stretchable PEDOT:PSS devices and underlying tissues, including the brainstem (D), the wrist (E), the finger (F), and the back of the hand (G). \n\nAs the PR content increased, higher stretchability (Fig. 2F and fig. S19) and lower Young’s moduli were obtained (Fig. 2G). Notably, a higher PR content also led to a better PEDOT: PSS conductivity with an enhancement of over two orders of magnitude compared with pristine PEDOT:PSS (Fig. 2H). X-ray photoelectron spectroscopy (XPS) revealed a decreasing trend of the remaining PSS/PEDOT ratio as the PRPEGMA content increased, which indicated that a large portion of insulating PSS was removed after blending and water development (Fig. 2I). Ultraviolet (UV)–visible and Raman spectroscopy also confirmed that less PSS remained in the TopoE film (fig. S20). With PR, its polar PEG chains replaced a portion of PSS in interacting with PEDOT, which led to the enhanced aggregation of PEDOT (22) (Fig. 2B and fig. S21). In addition to increased PEDOT content, AFM phase images of the blended films further revealed that the microscale morphology of PEDOT gradually evolved from grain-like particles to percolated microwebs, which was favorable for enhanced charge transport, especially under strain (figs. S22 and S23). \n\nWe confirmed that the topological network could survive the sulfuric acid–dipping process to further improve conductivity (Fig. 3A) using XPS depth profiling investigation (fig. S24). We also used GIXD spectroscopy to track the change of PEDOT crystallization (Fig. 3, B and C). The neat TopoE film showed a scattering profile with a weak (100) diffraction peak, corresponding to the PEDOT lamellar packing. The acid-treated film, termed TopoE-S, showed high-order diffraction peaks with strong intensities, whereas the (100) peak shifted to a larger $q$ value, which suggests denser lamellar packing and longer-range order (23). The $\\pi{-}\\pi$ (020) peak also emerged in the in-plane direction, indicating longer-range order for $\\pi{-}\\pi$ stackings between PEDOT backbones (24). In addition to the increased PEDOT crystallinity, AFM phase images showed that the PEDOT morphology became interconnected fibers after acid treatment (Fig. 3D). With both these changes, a film conductivity up to ${\\sim}2700\\mathrm{~S~cm^{-1}}$ was obtained for TopoE-S, which is one order of magnitude of enhancement compared with that of TopoE and three orders of magnitude of enhancement compared with that of pristine PEDOT:PSS (Fig. 3E and fig. S25). The TopoE-S film also had high optical transmittance in the visible range as a transparent conductor (fig. S26). \n\nThe photopatterned circular structure of TopoE-S could be stretched to an elliptical shape at $100\\%$ strain while remaining intact without observable cracks (Fig. 3F and figs. S27 and S28). AFM phase images and corresponding fast Fourier transform (FFT) spectrograms of the TopoE-S film under strain showed that the PEDOT microfibers became aligned along the stretching direction and returned to isotropic orientations when strain was released (fig. S29). GIXD spectra confirmed the retention of the PEDOT crystallization in directions both parallel and perpendicular to the strained axis (fig. S30). Finally, cyclic stretching tests between 0 and $100\\%$ strain for the TopoE-S film showed reversible resistance changes for at least 500 cycles (Fig. 3G). For bioelectronics applications, the PEDOT:PSS electrode needs to be immersed in the aqueous physiological environment. Previously reported PEDOT:PSS systems with conductivity-enhancement treatment (23), small molecule plasticizers (17), surfactant blending (25), or polymeric additives (26) all suffered from substantial drops of conductivities upon stretching after immersion (Fig. 3H and fig. S31). By contrast, TopoE-S was able to maintain its high performance at ${\\sim}2700\\mathrm{Scm^{-1}}$ initial conductivity and ${\\sim}6000~\\mathrm{S~cm^{-1}}$ at $100\\%$ strain with chain alignments (Fig. 3H and figs. S29 and S31). \n\nThe electrochemical impedance of TopoE-S measured in phosphate-buffered saline (PBS) solution was found to be lower than that of stretchable cracked Au (c-Au) in all frequency ranges (Fig. 3I). c-Au electrodes are among the best stretchable electrodes for bioelectronics (27). Their high-frequency unit-area impedance is determined by Au thickness and feature size, which are constrained by crack size. Their low-frequency unit-area impedance is several orders of magnitude higher than that of TopoE-S because the effective interfacial capacitance (A) Chemical structure of PR-PEGMA and individual roles of each building block. (B) Schematic diagram illustrating the interaction between PR and PEDOT:PSS for enhanced conductivity. (C and D) Stretching tests showing that the PRblended PEDOT:PSS film could substantially enhance stretchability compared with other control samples. Films were deposited on styrene-ethylene-butylenestyrene (SEBS) elastomers with thicknesses of \\~200 nm. R, resistance. (E) AFM height image and corresponding surface profile of a photopatterned for TopoE-S is much larger than that of c-Au (24) (Fig. 3J). Such a large interfacial capacitance is also responsible for high chargestorage capacity (Fig. 3K) and efficient charge injection (Fig. 3L), which are both important for low-voltage electrical stimulation (18). TopoE-S also maintains the electronic-ionic dual conduction from PEDOT:PSS (figs. S32 and S33). The high electrical conductivity is essential for TopoE-S to outperform c-Au at all frequency ranges (fig. S34). If the electrical conductivity of PEDOT is lower than ${\\sim}300\\mathrm{~S~cm^{-1}}$ , the reduced impedance of PEDOT versus c-Au is only expected in the low-frequency regime. The impedance value of the TopoE-S electrode remained stable in PBS for at least 1 month (fig. S35). When the TopoE-S electrode was at $100\\%$ strain, its impedance only showed a slight increase because of the electrode geometry change, without inducing any cracks (fig. S36). We developed a fabrication process for highdensity stretchable electrode arrays by optimizing the chemical orthogonality and surface energy of each elastomeric layer (Fig. 4, A and B, and figs. S10 and S37). The as-fabricated stretchable TopoE-S array has a narrow distribution for both the impedance amplitude and the phase angle (fig. S38). Because the entire electrode array (as thin as $20\\upmu\\mathrm{m}\\mathrm{,}$ is made of soft and elastic materials, it can be conformably attached onto human skin (Fig. 4C). This allows for high-density surface electromyography (sEMG) recording even on moving muscles. \n\n![](images/ca2c71281bd49f1421b72da9cbd3b9fe71aadec5562ccc45bfda0efa17c64031.jpg) \nFig. 2. PR-based topological network enables simultaneously enhanced conductivity, stretchability, and photopatternability of PEDOT:PSS. \nTopoE array with 2- $\\cdot\\upmu\\mathrm{m}$ width. (F) Resistance change as a function of strain for TopoE films with different PR over PEDOT:PSS dry mass weight ratios. All films in (F) to (I) were UV cross-linked after blending followed by washing in water and blow drying. (G) Statistical comparison of Young’s moduli measured by nanoindentation for different TopoE films indicating that PR can reduce the overall film stiffness. (H) Four-point probe measurements showing enhanced film conductivity with higher PR content. (I) XPS profiles indicating reduced PSS content as the PR over PEDOT:PSS dry mass ratio increases in the film. a.u., arbitrary units. \n\n![](images/4469edf9585ec50d1a071b66ba5542742dcec8e14f9a728f6c75bb4003dca948.jpg) \nFig. 3. Fully cross-linked topological network can afford posttreatment toward record-high conductivity and stretchability. (A) Schematic diagram illustrating the change of crystallinity by acid treatment. (B and C) Twodimensional (2D) spectra (B) and 1D profile (C) of GIXD spectra collected from TopoE and TopoE-S. (D) AFM phase images showing the morphological changes of TopoE and TopoE-S. (E) Electrical measurement showing enhanced conductivity after acid treatment for TopoE-S. (F) Optical microscopy images showing the shape evolution of a TopoE-S pattern during stretching without inducing any cracks. (G) Cyclic stretching test between 0 and $100\\%$ strain showing reversible resistance changes of TopoE-S. (H) Conductivity over strain \nplots showing high conductivity under strain for TopoE-S versus literaturereported PEDOT:PSS after water soaking. All previously reported methods suffer from severe conductivity degradation from soaking and/or from strain (detailed data and references are in fig. S31). (I) Electrochemical impedance spectroscopy measurements showing the reduced impedance per unit area of TopoE-S compared with c-Au. (J) Interfacial capacitance per unit area from TopoE-S and Au as a function of electrode thickness. (K) Cyclic voltammetry scans showing the enhanced charge storage capacity per unit area of TopoE-S over c-Au. (L) Current measurements after transient voltage pulses showing better charge injection per unit area of TopoE-S compared with that of c-Au. \n\n![](images/117fdf61cd4798a88864c332facd616bd0270f2af4181b39fca953224c13fb98.jpg) \nFig. 4. Soft and stretchable electrode array allows stable electrophysiological monitoring of deformable tissues. (A) Exploded view of the multilayered stacks for the stretchable electrode array. (B) Photograph of an as-fabricated device (top) and an optical microscope image of the active site with $100\\mathrm{-}\\upmu\\mathrm{m}$ electrode width (bottom) used for (D) and (E). (C) Photographic image of the sEMG measurement setup including a tissueconforming stretchable electrode array and a flexible flat cable (FFC) for input-output communications. (D) Representative EMG recording traces \nduring a fist gesture with distinct spatiotemporal dynamics of individual channels. (E) Temporal evolution of EMG activity across different channels corresponding to the raw traces in (D) while making a fist. (F) Photographic images of a stretchable electrode array attached to an octopus arm, with an electrode width of $500\\upmu\\mathrm{m}$ . (G) Peristimulus time histogram of evoked EMG activities of the octopus during muscle twitching. (H) Comparison of the signal variance during the resting state recorded by a rigid probe made on polyimide versus a soft and stretchable TopoE-S probe. \n\nThe typical interelectrode distance for sEMG devices is $\\sim5~\\mathrm{mm}$ or larger because the high impedance of rigid electrodes and poor skin contact do not allow reliable recording at smaller sizes (28). Because of the low impedance of PEDOT:PSS and the low modulus of the entire electrode array, we reduced the interelectrode distance down to $500~{\\upmu\\mathrm{m}}$ with electrode widths of $100~{\\upmu\\mathrm{m}}$ while still being able to capture high-fidelity sEMG signals (Fig. 4B). The low unit-area impedance enabled our stretchable electrode array to resolve sEMG propagation dynamics with high spatial resolution (Fig. 4, D and E). Besides recording dynamic information, the integrated EMG signals over time were also distinct enough to differentiate other hand gestures in a highly reproducible manner (figs. S39 to S44). \n\nWe can also measure sEMG signals from soft-bodied creatures, such as an octopus, whose muscles can undergo much larger deformations than those of a human (Fig. 4F). We observed that upon electrical stimulation of the octopus arm, our stretchable sEMG array could consistently record the muscle activity dynamics with good signal-to-noise ratio (Fig. 4G, figs. S45 to S47, and movies S1 and S2). By contrast, a rigid probe made of PEDOT:PSS on polyimide was observed to slip along the muscle surface owing to its inability to follow the tissue contour, which resulted in extremely noisy signals—i.e., a low signal-to-noise ratio (Fig. 4H, figs. S48 and S49, and table S2). \n\nFinally, stretchable bioelectronics made with rigid inorganic materials require special structural designs at compromised device densities, whereas TopoE-S can be directly patterned to high-density stretchable arrays (fig. S50), which allows for bioelectronic applications at intricate locations with high precision. In this regard, the brainstem would be a perfect testbed for several reasons (Fig. 5A, fig. S51, and table S3): It is naturally curved and will experience substantial strains from movement of the cervical spine (10, 29). It serves as the central hub for motor controls of almost all facial and neck motions through 10 pairs of cranial nerves (30). It also regulates cardiac and respiratory functions. \n\nWe first showed that our stretchable electrode array, when placed on the floor of the fourth ventricle of a rat, could follow the underlying curvature to form intimate contact (Fig. 5B and fig. S51). Upon implantation, we delivered current pulses to individual electrodes to stimulate the tongue, whisker, and neck separately while EMG and motion signals at those locations were simultaneously recorded to confirm the organ-specific stimulations (Fig. 5C). After scanning the entire array with a $300\\mathrm{-}\\upmu\\mathrm{m}$ interelectrode distance and a ${50}{\\cdot}{\\upmu\\mathrm{m}}$ electrode width, we observed distinct muscle electrophysiological signals and movements elicited by each electrode (Fig. 5D, figs. S52 to S54, and movies S3 to S5). By normalizing the EMG amplitudes, we were able to construct three high-resolution activation maps that correlated with individual nuclei for hypoglossal, facial, and accessory nerves that innervated the genioglossus for the tongue, the orbicularis oris for the whisker, and the sternocleidomastoid for the neck, respectively (30) (Fig. 5E and fig. S55). Aside from independent controls of different muscle groups, high-resolution stimulation through the stretchable electrode array showed strong side specificity. Only the muscles on the same side (i.e., ipsilateral) of the electrode would be selectively stimulated, in accordance with the functional organization of corresponding cranial nerves (30) (Fig. 5, F and G, and figs. S55 and S56). The amplitude of the evoked muscle signal could also be modulated by the intensity of the input stimulus (fig. S57). Finally, immunohistological analysis indicated that our electrode array did not induce observable tissue damages or inflammatory responses when placed between the cerebellum and the brainstem, whereas rigid plastic probes supported on polyimide substrates caused severe damage by cutting into the soft brainstem—possibly as a result of frequent neck movements—shortly after implantation (Fig. 5, H and I, and figs. S58 to S60). In conclusion, by introducing a rationally designed topological supramolecular network, we achieved a CP with simultaneously high conductivity, stretchability, and photopatternability and demonstrated bioelectronic applications for a soft-bodied octopus and the fragile rat brainstem. \n\n![](images/3d6ef9f15413ab43ddb2b05f076444270bc61164244a1cbf640b1ba39a046b7e.jpg) \nFig. 5. Stretchable high-density array allows localized neuromodulation for precise control of individual muscle activities. (A) Schematic diagram illustrating the application of the stretchable electrode array for precise neuromodulation through localized brainstem stimulation. (B) Microscopic image of a stretchable electrode array conforming to the curved floor of the fourth ventricle with $50\\mathrm{-}\\upmu\\mathrm{m}$ electrode width. (C) Schematic illustration of a multielectrode array placed on the right side of the brainstem. (D) Evoked muscle activities recorded at the tongue (left), whisker (middle), and neck (right) after electrical stimulation at the brainstem. (E) Activation maps based on the muscle activities depicting the \nspatial distribution of different nuclei (marked by dashed lines) in the brainstem with downstream connections to the hypoglossal nerve (left), facial nerve (middle), and accessory nerve (right). (F) Schematic diagram and representative data traces showing the side specificity of the brainstem stimulation. (G) Statistical analyses showing the preferred activation of ipsilateral targets. CMAP, compound muscle action potential. (H and I) Immunohistological staining of a brain slice after the insertion of the soft and stretchable electrode array (H) and a rigid device (I) along the floor of the fourth ventricle between the brainstem and the cerebellum. DAPI, 4′,6-diamidino-2-phenylindole; NF, neurofilament; GFAP, glial fibrillary acidic protein. \n\n# REFERENCES AND NOTES \n\n1. S.-K. Kang et al., Nature 530, 71–76 (2016). \n2. J. Viventi et al., Nat. Neurosci. 14, 1599–1605 (2011). \n3. K. Mathieson et al., Nat. Photonics 6, 391–397 (2012). \n4. Y. S. Choi et al., Nat. Biotechnol. 39, 1228–1238 (2021). \n5. M. Capogrosso et al., Nature 539, 284–288 (2016). \n6. F. B. Wagner et al., Nature 563, 65–71 (2018). \n7. X. Yu et al., Nature 575, 473–479 (2019). \n8. J. C. Barrese et al., J. Neural Eng. 10, 066014 (2013). \n9. J. W. Salatino, K. A. Ludwig, T. D. Y. Kozai, E. K. Purcell, Nat. Biomed. Eng. 1, 862–877 (2017). \n10. S. P. Lacour, G. Courtine, J. Guck, Nat. Rev. Mater. 1, 16063 (2016). \n11. E. Song, J. Li, S. M. Won, W. Bai, J. A. Rogers, Nat. Mater. 19, 590–603 (2020). \n12. T. Someya, Z. Bao, G. G. Malliaras, Nature 540, 379–385 (2016). \n13. S. Wang et al., Nature 555, 83–88 (2018). \n14. B. D. Paulsen, K. Tybrandt, E. Stavrinidou, J. Rivnay, Nat. Mater. 19, 13–26 (2020). \n15. H. Yuk, B. Lu, X. Zhao, Chem. Soc. Rev. 48, 1642–1667 (2019). \n16. D. Khodagholy et al., Nat. Neurosci. 18, 310–315 (2015). \n17. Y. Wang et al., Sci. Adv. 3, e1602076 (2017). \n18. Y. Liu et al., Nat. Biomed. Eng. 3, 58–68 (2019). \n19. Y. Gu et al., Nature 560, 65–69 (2018). \n20. H. Gotoh et al., Sci. Adv. 4, eaat7629 (2018). \n21. Y. Okumura, K. Ito, Adv. Mater. 13, 485–487 (2001). \n22. D. Alemu Mengistie, P.-C. Wang, C.-W. Chu, J. Mater. Chem. A 1, 9907–9915 (2013). \n23. N. Kim et al., Adv. Mater. 26, 2268–2272, 2109 (2014). \n24. S. M. Kim et al., Nat. Commun. 9, 3858 (2018). \n25. S. Savagatrup et al., Adv. Funct. Mater. 25, 427–436 (2015). \n26. C. L. Choong et al., Adv. Mater. 26, 3451–3458 (2014). \n27. N. Matsuhisa et al., Adv. Electron. Mater. 5, 1900347 (2019). \n28. B. Afsharipour, S. Soedirdjo, R. Merletti, Biomed. Signal Process. Control 49, 298–307 (2019). \n29. N. Vachicouras et al., Sci. Transl. Med. 11, eaax9487 (2019). \n30. D. E. Haines, Neuroanatomy: An Atlas of Structures, Sections, and Systems (Lippincott Williams & Wilkins, ed. 8, 2011). \n31. E. Hwaun, ernie7334066/EMG-analysis: publication, Zenodo (2022); https://doi.org/10.5281/zenodo.6236224. \n\n# ACKNOWLEDGMENTS \n\nWe thank K. Sun, D. Liu, and J. Tang for technical support. We thank Agfa-Gevaert N.V. for providing PEDOT:PSS, the Asahi Kasei Corporation for providing SEBS, and the Daikin Corporation for providing poly(vinylidene fluoride)-co-hexafluoropropylene (PVDFHFP). Funding: This work was partly supported by BOE Technology Group Co., Ltd., and the Stanford Wu Tsai Neurosciences Institute Big Idea project on Brain Organogenesis. Part of this work was performed at the Stanford Nano Shared Facilities (SNSF), supported by the National Science Foundation under award ECCS-1542152. The GIXD measurements were performed at Beamline 11-3 of the \n\nStanford Synchrotron Radiation Light (SSRL) source, supported by the Director, Office of Science, Office of Basic Energy Sciences of the US Department of Energy under contract no. DE-AC02- 76SF00515. E.H. and I.S. acknowledge support from an ONR MURI grant (N0014-19-1-2373) and a Wu Tsai Neurosciences Institute Interdisciplinary Scholarship Award on the octopus-related work. D.L. acknowledges support from the National Natural Science Foundation of China Projects (81971668). Y.-X.W. acknowledges financial support from the China Scholarship Council (201806255002) for visiting scholar funding. Author contributions: Y.J. and Z.B. conceived the project. Y.J., Y.-X.W., and Z.B. designed the materials. Y.J. and Y.-X.W. carried out the synthesis. Y.J., Z.Z., Y.-X.W., C.-T.C., D.Z., G.C., H.-C.W., S.N., W.W., A.S., J.-C.L., Y.Wu, Y.Wa., A.A.T., K.Y.L., C.-C.S., W.X., K.L., K.Z., Y.B., and G.G. performed testing and characterizations. Y.J., E.H., and I.S. designed and performed the octopus-related experiments. Y.J. and D.L. carried out the brainstemrelated experiments. Y.J., Z.Z., Y.-X.W., J.B.-H.T., and Z.B. wrote the paper and incorporated comments and edits from all authors. Competing interests: Stanford University has filed patent applications related to this technology. The patent application numbers are 63/139,666 and 62/845,463. The authors declare no other competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. The code used to analyze the EMG signals is available in a GitHub repository (https://github.com/ernie7334066/EMG-analysis) and Zenodo (31). \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abj7564 \nMaterials and Methods \nFigs. S1 to S60 \nTables S1 to S3 \nReferences (32–68) \nMovies S1 to S5 \n31 May 2021; accepted 24 February 2022 \n10.1126/science.abj7564 " + }, + { + "id": "10.1038_s41929-022-00772-9", + "DOI": "10.1038/s41929-022-00772-9", + "DOI Link": "http://dx.doi.org/10.1038/s41929-022-00772-9", + "Relative Dir Path": "mds/10.1038_s41929-022-00772-9", + "Article Title": "High loading of single atomic iron sites in Fe-NC oxygen reduction catalysts for proton exchange membrane fuel cells", + "Authors": "Mehmood, A; Gong, MJ; Jaouen, F; Roy, A; Zitolo, A; Khan, A; Sougrati, MT; Primbs, M; Bonastres, AM; Fongalland, D; Drazic, G; Strasser, P; Kucernak, A", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Non-precious iron-based catalysts (Fe-NCs) require high active site density to meet the performance targets as cathode catalysts in proton exchange membrane fuel cells. Site density is generally limited to that achieved at a 1-3 wt%(Fe) loading due to the undesired formation of iron-containing nulloparticles at higher loadings. Here we show that by preforming a carbon-nitrogen matrix using a sacrificial metal (Zn) in the initial synthesis step and then exchanging iron into this preformed matrix we achieve 7 wt% iron coordinated solely as single-atom Fe-N-4 sites, as identified by Fe-57 cryogenic Mossbauer spectroscopy and X-ray absorption spectroscopy. Site density values measured by in situ nitrite stripping and ex situ CO chemisorption methods are 4.7 x 10(19) and 7.8 x 10(19) sites g(-1), with a turnover frequency of 5.4 electrons sites(-1) s(-1) at 0.80 V in a 0.5 M H2SO4 electrolyte. The catalyst delivers an excellent proton exchange membrane fuel cell performance with current densities of 41.3 mA cm(-2) at 0.90 ViR-free using H-2-O-2 and 145 mA cm(-2) at 0.80 V (199 mA cm(-2) at 0.80 ViR-free) using H-2-air.", + "Times Cited, WoS Core": 377, + "Times Cited, All Databases": 386, + "Publication Year": 2022, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000787831800012", + "Markdown": "# High loading of single atomic iron sites in Fe–NC oxygen reduction catalysts for proton exchange membrane fuel cells \n\nAsad Mehmood $\\oplus1$ , Mengjun Gong $\\oplus1$ , Frédéric Jaouen   2, Aaron Roy2, Andrea Zitolo $\\textcircled{10}$ 3, Anastassiya Khan3, Moulay-Tahar Sougrati2, Mathias Primbs4, Alex Martinez Bonastre5, Dash Fongalland5, Goran Drazic6, Peter Strasser $\\textcircled{15}4$ and Anthony Kucernak   1 ✉ \n\nNon-precious iron-based catalysts (Fe–NCs) require high active site density to meet the performance targets as cathode catalysts in proton exchange membrane fuel cells. Site density is generally limited to that achieved at a 1–3 wt%(Fe) loading due to the undesired formation of iron-containing nanoparticles at higher loadings. Here we show that by preforming a carbon–nitrogen matrix using a sacrificial metal $(z_{n})$ in the initial synthesis step and then exchanging iron into this preformed matrix we achieve $7w t\\%$ iron coordinated solely as single-atom Fe– $\\cdot N_{4}$ sites, as identified by $57F e$ cryogenic Mössbauer spectroscopy and $\\pmb{x}$ -ray absorption spectroscopy. Site density values measured by in situ nitrite stripping and ex situ CO chemisorption methods are $4.7\\times10^{19}$ and $7.8\\times10^{19}$ sites $\\pmb{\\mathsf{g}}^{-1}$ , with a turnover frequency of 5.4 electrons sites $\\mathbf{-1}\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\mathbf{-1}$ at 0.80 V in a 0.5 M ${\\bf H}_{2}\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\large\\suit{\\bf O}_{4}$ electrolyte. The catalyst delivers an excellent proton exchange membrane fuel cell performance with current densities of 41 $.3m\\Delta\\ c m^{-2}$ at $\\mathbf{0.90V}_{i R\\cdot\\mathrm{free}}$ using ${\\bf H}_{2}{\\bf-O}_{2}$ and $145\\mathrm{m}\\mathsf{A}\\mathsf{c m}^{-2}$ at 0.80 V (199 mA cm−2 at $\\mathbf{0.80V_{\\mathrm{i}R\\mathrm{-}f r e e}})$ using $\\Hat{\\boldsymbol{\\mathsf{H}}}_{2}$ –air. \n\nPrzoeptrtoioo-nenmfeoixsrcsihaoavnagrpieeotwymeoerfmagbperpnaleinrceatifounesl,s ypscatereltlimsc ua(lraPerElyaMfnForCatsp)hpe aelsliencgatrification of the transportation sector from small- to medium-size cars to heavy-duty vehicles1,2. Mass production and commercialization of fuel cells is, however, significantly dependent on their cost competitiveness. Currently, the inevitable use of $\\mathrm{Pt}$ -based catalysts contributes about $41\\%$ to the total stack costs3. The sluggish kinetics of the oxygen reduction reaction (ORR) require around $80\\%$ of total Pt loadings at the PEMFC cathode. The development of catalysts free of platinum group metal free (PGM-free) for ORR to replace Pt has been pursued actively for over a decade now and promising activity levels were reported for the class of M–NC catalysts in which M is a transition metal, with Fe and Co leading to the highest ORR activity4–6. The metal ions, for example, Fe, are stabilized by nitrogen ligands of a nitrogen-doped carbon matrix (NC) to form $\\mathrm{Fe-N}_{x}$ coordination that strongly resembles the metal– $\\mathrm{.N_{4}}$ core in metal porphyrins and phthalocyanines4,7–10. The first ever report on the ORR activity of M–NCs dates back to the early 1960s when Jasinski found that metal phthalocyanines catalyse the oxygen reduction in alkaline electrolyte11,12 and the activity in acidic electrolyte was later improved by others using a high-temperature pyrolysis13. \n\nIn recent years, tremendous progress has been made in improving the acidic ORR activity of M–NC materials, particularly with Fe–NCs. However, their activity and stability levels are still well short of the performance criteria2,5,14 required to displace PGM catalysts at the cathode, which highlights the importance of further activity improvement. To enhance the ORR activity, many different synthesis strategies have been pursued to tune the Fe–NC structures7,8,15–20. \n\nThe main goal is to maximize the abundance of atomically dispersed iron as $\\mathrm{Fe-N}_{x}$ and increase their intrinsic activity. However, only a limited success has been seen so far, and most of the reported Fe–NCs reached atomically dispersed iron contents of between 0.5 and $2.0\\mathrm{wt\\%}$ —higher Fe content leads to partial or complete Fe clustering as metallic nanoparticles, iron carbide, iron nitride and so on during pyrolysis9,21. Recently, a few new strategies were introduced to improve the atomic Fe dispersion, among which silica coating of Fe-coordinated C and N precursor(s) is most notable; however, the amount of atomically dispersed iron can only be improved to $3\\mathrm{wt\\%}$ (refs. $22\\substack{-25}$ ). Moreover, the added synthetic complexity for the incorporation of silica or other such coating strategies becomes an important point of concern in the context of their feasibility for scaling $\\mathsf{u p}^{26}$ . Iron, with its relatively more-noble character, has a higher tendency to undergo carbothermal reduction at a high temperature to form metallic particles compared with that of some other metals, for example, Zn or $\\mathbf{Mg}$ which can form similar $\\mathrm{M}{-}\\mathrm{N}_{x}$ sites and are more stable in their oxidized state $\\left(\\mathrm{M}^{2+}\\right)$ (refs. $27-29$ ). Therefore, decoupling the formation step of $\\mathrm{Fe-N_{4}}$ sites from the high-temperature pyrolysis seems critical to overcome the dilemma of a low Fe site density (SD). This was successfully demonstrated by Mehmood et al. in a proof-of-concept study in which thermally stable $\\mathrm{Mg-N_{4}}$ sites were imprinted in a porous $\\operatorname{Mg-NC}$ matrix, which were then converted into $\\mathrm{Fe-N_{4}}$ moieties via low-temperature (trans)metallation with iron30. Later on, Menga et al. showed that $\\mathrm{Zn-N_{4}}$ sites could also be used to prepare Fe–NCs under this active-site imprinting concept31. A high-temperature transmetallation concept that utilized chemical vapour deposition of iron single atoms into an NC matrix was recently demonstrated by Jia’s group32,33. \n\nIn this work, we report substantial progress in an increased Fe– $\\mathrm{N}_{x}\\mathrm{SD}$ by combining the advantages of the postpyrolysis formation of $\\mathrm{Fe-N_{4}}$ moieties and the high density of atomically coordinated $Z\\mathrm{n}$ sites in zeolitic imidazolate framework (ZIF) materials. The resultant Fe–NC catalyst consisted of $7\\mathrm{wt\\%\\Fe{-}N_{4}}$ sites, identified by $^{57}\\mathrm{Fe}$ Mössbauer spectroscopic measurements performed at $5\\mathrm{K},$ inductively coupled plasma mass spectrometry (ICP-MS) and X-ray absorption spectroscopy (XAS). In situ nitrite stripping and ex situ CO chemisorption techniques were utilized to quantify the SDs and turnover frequencies $(\\mathrm{TOFs})^{34,35}$ . In the optimized catalyst, SD values of $4.7\\times10^{19}$ sites $\\mathbf{g}^{-1}$ $(4.0\\times10^{16}\\mathrm{{sites}\\mathrm{{m}^{-2}}},$ ) and $7.8\\times10^{19}$ sites $\\mathbf{g}^{-1}$ $6.8\\times10^{16}$ sites m−2) were obtained with nitrite stripping34,36 and CO chemisorption35,37, respectively, which are far greater than four benchmark $\\mathrm{Fe-NCs^{38}}$ . Such a high density of $\\mathrm{Fe-N_{4}}$ sites translates into an excellent ORR activity in a rotating ring disk electrode (RRDE) as well as in fuel cell measurements. In PEMFC tests under a $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ environment, the optimized Fe–NC catalyst delivered a current density of $41.3\\mathrm{mAcm}^{-2}$ at $0.90\\mathrm{V}_{i R\\mathrm{\\cdotfree}}$ (mass activity of $10.6\\mathrm{Ag^{-1}}.$ ), higher than the reported values, which are in the $25{-}35\\operatorname*{mAcm}^{-2}$ range and achieved using higher Fe–NC loadings of $5{-}6\\mathrm{mgcm}^{-2}$ (mass activities between 4 and $6\\mathrm{Ag^{-1}}$ ) (refs. 26,33,39,40). \n\n# Results \n\nAnalysis of SD and TOF target requirements. If the iron in an Fe–NC catalyst is randomly distributed through the material in atomic sites, then not all of that iron will be present on the surface, that is, some will be buried and inaccessible. Consequently, with a random distribution, the amount of iron accessible on the catalyst will scale with the surface area of the catalyst. Figure 1a shows that the number of iron sites increases in a nearly linear fashion with the catalyst specific surface area (SSA) up until all the iron is on the surface, which occurs in the SSA range of 1,244– $1,316\\mathrm{m}^{2}\\mathrm{g}^{-1}$ $7\\mathrm{wt\\%(Fe)}\\to0\\mathrm{wt\\%(Fe)};$ see Supplementary Note 1 and Supplementary Figs. 1–5 for the calculation details and additional discussion associated with the proportion of edge and basal plane sites, and Supplementary Table 1 for estimates of the basal, edge and buried Fe sites in our catalyst). Note that this surface area is not the maximum possible surface area of the catalyst, which is twice the associated value and reflects the fact that, once the catalyst is composed of two graphene-like sheets, all the iron must be accessible from the surface. If there is segregation of iron either to, or away from, the surface, then the corresponding curves in Fig. 1a will either bow above (segregation to the surface) or below (segregation to the bulk) those lines but will still have the same endpoints. As the mass loading of iron increases from 1 to $7\\mathrm{wt\\%}$ , the curves increase concomitantly, and the average separation between surface iron atoms on the surface $(r_{\\mathrm{Fe-Fe}}^{\\mathrm{avg}},$ independent of the catalyst surface area) decreases from 3.r1FetoF $1.1\\mathrm{nm}$ . As most $\\mathrm{Fe-NC}$ catalysts have an SSA of around $600{-}800\\mathrm{m}^{2}\\mathrm{g}^{-1}$ it is expected that only about half of the total iron is exposed on the surface. Even with a high iron content $(7\\mathrm{wt\\%}$ , that is, $1.6\\mathrm{at\\%}$ ) and a high SSA catalyst (for example, $1,000\\mathrm{m}^{2}\\mathrm{g}^{-1})$ , one can achieve a maximum of only around $7.5\\times10^{20}$ sites $\\mathbf{g}^{-1}$ . This imposes a realistic upper limit of the SD on these sorts of catalysts as even to achieve a metal loading of $7\\mathrm{wt\\%}$ with atomic dispersion, as we have achieved in this study, is difficult. \n\nA further requirement that needs to be achieved in these catalysts is having an appropriate TOF for the ORR. The mass specific current density $(j_{m})\\ ({\\mathrm{A}}{\\mathrm{g}}^{-1})$ can be expressed as the product of the TOF (e site $^{-1}{\\mathbf{S}}^{-1},$ and $e$ $\\left(\\mathbf{C}\\mathbf{e}^{-1}\\right)$ and surface SD: \n\n$$\nj_{m}=\\mathrm{SD}\\times\\mathrm{TOF}\\times e\n$$ \n\nThe US Department of Energy and the Fuel Cells and Hydrogen Joint Undertaking specify the expected requirements for the performance of catalysts at $0.90\\mathrm{V}$ under the appropriate conditions, and these numbers are usually expressed in terms of geometric current densities. For Fig. 1b, we used the US Department of Energy requirement for $0.044\\mathrm{Acm}^{-2}$ to assess the required SD and TOF for Fe–NC catalysts as a function of electrode loading (solid lines) (see Supplementary Note 2 for the calculation details). Note that as the catalyst loading increases, the requirements for SD and TOF decrease, but this is at the expense of very thick catalyst layers $(25\\to250\\upmu\\mathrm{m}$ as the loading increases from 1 to $10\\mathrm{mgcm}^{-2}.$ ) associated with the low density of these catalysts $(\\sim0.4\\mathrm{gcm}^{-3})$ . Very thick catalyst layers pose problems at high current densities due to mass transport effects, and although high loadings might allow the achievement of an areal current density target at high potentials, they are not helpful in making a fuel cell operate in the high current regime, and may lead to optimization strategies that are inappropriate for practical devices. Also displayed in Fig. 1b are the equivalent performance of $\\mathrm{Pt/C}$ catalysts towards the same US Department of Energy target (green squares, and dotted line). As one can estimate the SD on these platinum nanoparticles as equal to the number of platinum atoms on the particle surface (that is, one $\\mathrm{Pt}$ surface atom $=1$ site), this also allows us to specify the required TOF for the ORR on these catalysts as a function of platinum SSA (that is, electrochemical surface area). Typical fuel cell catalysts have platinum surface areas of $90{-}100\\mathrm{m}^{2}\\mathrm{g}^{-1}$ . In this case, this would correspond to a TOF of about $2\\mathrm{ePt_{\\mathrm{surf}}}^{-1}\\mathrm{{\\sfS}^{-1}}$ . At a platinum loading on carbon of ${\\sim}40\\mathrm{wt\\%}$ , the catalyst layer thickness is then about $6\\upmu\\mathrm{m}-$ much thinner than that of the Fe–NC catalyst layers. Thus, we set this TOF as the upper limit for Fe–NC catalysts. Furthermore, geometric arguments of the type discussed above and realized in Fig. 1a suggest that to achieve an Fe–NC active SD higher than ${\\sim}10^{21}\\mathrm{sites}\\mathrm{g}^{-1}$ is not realistically possible. Thus, to achieve the required performance, Fe–NCs must possess SDs and TOFs within the green region, and preferably in the upper right-hand corner of that zone, which remains challenging so far, with Fe–NCs typically limited to a maximum iron content of $3\\mathrm{wt\\%}$ (refs. 22–25). To overcome this barrier, we developed a modified catalyst synthesis, which has achieved a number of single atom iron sites beyond the state-of-art. The SD (measured by nitrite stripping) and TOF (calculated from the $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ PEMFC current density at $0.90\\mathrm{V}_{i R\\mathrm{-free}})$ values achieved in this study are represented by the star in Fig. 1b, which falls in the zone-of-opportunity triangle. \n\nFigure 1c sequentially presents the catalyst synthesis steps. In the first step, a $\\mathrm{{}Z n-N C}$ matrix enriched with $Z\\mathrm{n-N}_{x}$ sites $(\\sim25\\mathrm{wt\\%}$ as measured by ICP-MS) was prepared by pyrolysing a Zn-based metal organic framework (MOF), namely a commercial zinc 2-methylimidazolate (ZIF-8; Basolite Z1200). This nitrogen-doped carbon scaffold, which contained a high concentration of $Z\\mathrm{n-N}_{x}$ sites, was then converted into $\\scriptstyle\\bigsqcup\\scriptscriptstyle\\mathrm{-N}_{x}$ sites (empty square: metal vacancy and/or protonated site; Fig. 1c) by $Z\\mathrm{n}$ leaching in acid. Fe coordination was then performed during refluxing of the demetallated material in iron(II) chloride, which allowed $\\mathrm{Fe}^{2+}$ ions to ion exchange into the $\\scriptstyle\\boxed{\\phantom{-}}-\\Nu_{x}$ sites (metallation). In parallel, some $\\mathrm{Fe-N_{4}}$ sites may have also formed via transmetallation, in which Fe ions exchanged with any of the accessible unleached (acid-stable) $Z\\mathrm{n-N}_{x}$ sites in the NC matrix. The Fe–NC catalyst thus produced contained a high Fe content of $7\\mathrm{wt\\%}$ . As shown in Fig. 1c, the unactivated catalyst, denoted as Fe-NCU, was finally subjected to a high-temperature activation step in the presence of dicyandiamide (DCDA), a blowing agent, to yield Fe–NCΔ-DCDA ( $\\dot{\\Delta}$ represents activation and DCDA the presence of DCDA). \n\nStructural characterization of Fe–NC catalyst. The synthesized Fe–NC catalysts were analysed for their physicochemical features (Fig. 2). Transmission electron microscopy (TEM) images (Fig. 2a and Supplementary Fig. 6) show a truncated polyhedron morphology for the $\\mathrm{Fe-NC^{U}}$ catalyst, identical to that of the unpyrolysed ZIF-8 particles. The majority of the primary catalyst particles are in the $350\\mathrm{-}400\\mathrm{nm}$ size domain with only a few smaller particles $(<300\\mathrm{nm})$ ). However, the morphology of the Fe–NCΔ-DCDA seems to be altered by the DCDA-assisted activation, which leads to more irregularly shaped particles (Fig. 2b and Supplementary Fig. 6). This morphological transformation of catalyst particles is attributed to the presence of DCDA, a commonly used blowing agent that generates nitrogen and ammonia during its decomposition at $300{-}350^{\\circ}\\mathrm{C}$ and leaves a conductive carbon overlayer on top of the polyhedra particles during the activation step41,42. Figure 2c shows a high‐angle annular dark‐field scanning transmission electron microscopy (HAADF‐STEM) image of the Fe–NCΔ-DCDA along with iron mapping (Fig. 2c inset) by energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDXS). A uniform distribution of Fe is visible throughout the carbon matrix and the strong signal intensity reflects a high Fe loading, which was determined to be $7.10\\mathrm{wt\\%}$ by ICP-MS (Supplementary Table 2). Aberration-corrected HAADF-STEM micrographs of $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ catalyst represent Fe sites at atomic resolution (Fig. $^{2\\mathrm{d},\\mathrm{e}}$ and Supplementary Fig. $^{8c,\\mathrm{d}},$ ). The presence of isolated bright spots throughout the carbon matrix indicates the existence of abundant atomic Fe sites, as confirmed by electron energy loss spectroscopy (EELS). The electron energy loss spectrum (Fig. 2f) of the framed area of the micrograph in Fig. 2d shows a clear Fe signal that originates from the single iron atoms. \n\n![](images/87566a065784b0cb5d9a0c861ba7043137d9fab208e60cc1213e566cf6494e46.jpg) \nFig. 1 | Calculation of the Fe–NC SD and effect on performance. a, Calculated surface SD (calculation details in Supplementary Note 1) as a function of different iron contents and the catalyst SSA for single-atom dispersed catalysts. The average iron–iron separation is constant for each iron loading and at a high SSA $({\\sim}1,200\\mathsf{m}^{2}\\mathsf{g}^{-1})$ , all the iron is on the surface (horizontal dotted lines). b, Surface SD versus TOF plot showing the Fe–NC catalyst requirements to achieve an area specific current density of $0.044\\mathsf{A c m}^{-2}$ at $0.90\\mathsf{V}$ as a function of catalyst loading (solid lines) (calculation details in Supplementary Note 2). The star represents the SD and TOF values achieved with the Fe–NC catalyst in this study. Shown is a comparison with the Pt/C catalyst performance requirements for the same current density at a Pt loading of $0.1\\mathsf{m g c m^{-2}}$ using the calculated surface SD of Pt nanocrystals (green squares: specific catalyst surface area and dotted line). c, Cartoon illustrating the synthetic approach for an Fe–NC catalyst with a high Fe loading. A Zn–MOF is pyrolysed at $900^{\\circ}\\mathsf C$ in the first step to obtain a Zn–NC matrix with abundant $Z\\mathsf{n}\\mathrm{-}\\mathsf{N}_{x}$ sites followed by Zn leaching (leached matrix is labelled as □-NC) and then Fe coordination to obtain the unactivated Fe–NCU catalyst. In the final step, Fe– ${\\mathsf{\\cdot N C}}^{\\cup}$ is activated at $900^{\\circ}\\mathsf C$ in the presence of the DCDA activating agent. \n\nThe aberration-corrected HAADF-STEM micrographs of the $\\mathrm{Fe-NC^{U}}$ catalyst (Supplementary Fig. 8a,b) reveal Fe atoms (along with some residual $Z\\mathrm{n}$ ) present in the form of isolated single atoms even before the activation step, with no metal clustering detected. The overall carbon–particle size distribution in the $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ was estimated by multiangle dynamic light scattering and the majority of the particles and/or aggregates $(85\\%)$ were found to be in the $400{-}500\\mathrm{nm}$ range, peaking at $450\\mathrm{nm}$ , whereas the rest $(15\\%)$ were smaller and centred at $215\\mathrm{nm}$ (Fig. 2g). Nitrogen functionalities were quantitatively and qualitatively evaluated by X-ray photoelectron spectroscopy (XPS). The total amount of doped nitrogen in the $\\mathrm{Fe-NC^{U}}$ sample was found to be high, with a value of $12.5\\mathrm{at\\%}$ . This is favourable to stabilize large quantities of Fe ions and thus construct $\\mathrm{Fe-N}_{x}$ moieties by Lewis acid–Lewis base interactions. Deconvolution of the $\\mathrm{\\DeltaN}$ 1s spectrum of this sample revealed that more than $97\\%$ of the doped nitrogen was present as pyridinic, metal-coordinated $(\\mathrm{M}-\\mathrm{N}_{x}$ sites) and pyrrolic N sites (Fig. 2h and Supplementary Fig. 9). The total nitrogen contents in the Fe–NCΔ-DCDA and $\\mathrm{Fe-NC^{\\Delta}}$ catalysts were 6.8 and $7.8\\mathrm{at\\%}$ , respectively. The control sample $\\mathrm{Fe-NC^{\\Delta}}$ was prepared by activating the Fe–NCU without DCDA addition. As can be seen in Fig. 2h and \n\n![](images/188057a7560e1dbc1a36686fac113aa8d0b762812aa3f0164164291ab058caba.jpg) \nFig. 2 | Structural analysis of Fe–NC catalysts. a,b, TEM images of Fe– ${\\mathsf{\\cdot N C}}^{\\cup}$ (a) and Fe– ${\\cdot}{\\mathsf{N C}}^{\\Delta-\\mathsf{D C D A}}$ (b). c, HAADF-STEM image of Fe– ${\\cdot}{\\mathsf{N C}}^{\\Delta-\\mathsf{D C D A}}$ . Inset: Fe mapping by EELS. d,e, Aberration-corrected atomic resolution HAADF-STEM micrographs of Fe– ${\\mathsf{\\cdot N C}}^{\\Delta-\\mathsf{D C D A}}$ at different magnifications. f, EDXS of the framed area of the micrograph in d. g, Particle size distribution of the Fe–NCΔ-DCDA determined by multiangle dynamic light scattering. h, Absolute amounts of total nitrogen and different N sites in the unactivated and activated Fe–NCs determined from the deconvoluted high-resolution N 1s X-ray photoelectron spectra of these catalysts . a.u., arbitrary units. \n\nSupplementary Fig. 9, the catalyst activation resulted in a modified contribution of the different $\\mathrm{~N~}$ groups. Particularly, the peak that corresponds to pyrrolic N increased in the $\\mathrm{Fe-NC^{\\hat{\\Delta}-D C D A}}$ catalyst as compared with that before activation (13.8 relative $\\%$ for $\\mathrm{Fe-NC^{U}}$ versus 28.4 relative $\\%$ for $\\mathrm{Fe-NC^{\\Delta-DCDA}}^{\\cdot}$ ) and a small N-oxide peak also emerged in the N 1s narrow-scan spectrum (Supplementary Fig. 9). As for the unactivated sample, the majority $(>90\\%)$ of nitrogen in Fe–NCΔ-DCDA existed as pyridinic, $\\mathrm{M}{-}\\mathrm{N}_{x}$ and pyrrolic N sites (Supplementary Fig. 9). The distribution of different $\\mathrm{\\DeltaN}$ sites in the $\\mathrm{Fe-NC^{\\Delta}}$ sample is almost identical to that of the Fe–NCΔ-DCDA, which indicates no distinguishable modification of nitrogen functionalities in the presence of DCDA during activation. A comparison of the nitrogen adsorption–desorption isotherms (Supplementary Fig. 10a) shows type I isotherms for all three samples with restricted hysteresis, which indicates predominantly microporous structures. The SSAs of the $\\mathrm{Fe-NC^{U}};$ , Fe–NCΔ and $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ determined by the Brunauer–Emmett–Teller method were 775, 1,070 and $1,155\\mathrm{{m}^{2}\\mathrm{{g}^{-1}};}$ respectively, and their respective micropore volumes were 0.277, 0.398 and $0.432\\mathsf{c m}^{3}\\mathsf{g}^{-1}$ (Supplementary Fig. 10b and Supplementary \n\nTable 3). The considerable increase in SSAs and micropore volumes of the two activated catalysts is attributed to the evaporation of Zn during the activation step (Supplementary Table 2). The presence of DCDA during activation led to an additional enhancement in SSA and micropore volume for the Fe–NCΔ-DCDA catalyst. \n\nRaman analysis of the Fe–NCΔ-DCDA catalyst indicates graphene-like domains with sizes $\\left(L_{\\mathrm{a}}\\right)$ of $7.3\\pm2.3\\mathrm{nm}$ $\\mathrm{\\Delta}n=10\\mathrm{\\Delta}$ ) (Supplementary Note 3 and Supplementary Fig. 11). We used the value with the SSA of the catalyst to estimate the number of basal, edge and buried sites in the catalyst (Supplementary Note 1 and Supplementary Table 1). \n\nEvaluation of Fe coordination and Fe– $\\mathbf{\\cdotN}_{x}$ site formation. XAS measurements were carried out at the various stages of the synthesis process by collecting both the extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) and the X-ray absorption near-edge structure (XANES) regions (Supplementary Note 4). The Fourier transform of the EXAFS spectrum of $\\scriptstyle{\\mathrm{Zn-NC}}$ in the first synthesis step clearly shows the features of single atomic zinc sites (Supplementary Fig. 12a,b). \n\n![](images/7e4259ac5e4f7d93196fa451ef5dd7b378ded9161713d15e7ca2537124899f98.jpg) \nFig. 3 | Analysis of Fe coordination environments before and after activation. a,b, Fe K-edge EXAFS analysis of Fe–NCU (a) and F $e{\\mathsf{-N C}}^{\\Delta-\\mathsf{D C D A}}$ (b) in the Fourier transformed space without a phase-shift correction. The black curves represent the experimental spectra, and the red curves represent the calculated spectra. c,d, 57Fe cryo Mӧssbauer spectra measured at $51$ of Fe–NCU (c) and Fe–NCΔ-DCDA (d). Exp, experimental. \n\nThe EXAFS analysis reveals a first coordination shell that comprises four nitrogen atoms around $Z\\mathrm{n}$ at $2.02\\mathrm{\\AA}.$ , and a second coordination shell due to the $Z\\mathrm{n-C}$ contribution at $3.19\\mathrm{\\AA}$ . The structural parameters obtained from the fitting procedure are reported in Supplementary Table 4, and they are, within statistical error, in good agreement with our previous determination of $\\mathrm{Zn-N_{4}}$ moieties in ZIF-8 pyrolysed catalysts43. The EXAFS spectrum of Fe–NCU can be accurately reproduced by a first coordination shell, which comprises four nitrogen atoms and two axial oxygen atoms around the iron, and a second coordination shell, which includes the Fe–C and Fe–Fe two-body signal (Fig. 3a, Supplementary Fig. 13 and Supplementary Table 4). As also evidenced by Mössbauer spectroscopy, in this step of the synthesis the EXAFS analysis reveals the coexistence of $\\mathrm{Fe-N_{4}}$ moieties and an iron-oxide phase. Moreover, comparison between the XANES spectra of $\\mathrm{Fe-NC^{U}}$ and those of $\\scriptstyle\\gamma-\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ and $\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\alpha\\mathrm{\\alpha\\alpha}}\\mathrm\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm\\mathrm{\\alpha{\\alpha\\alpha}\\mathrm{\\alpha\\alpha}\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm}\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\alpha\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm $ allows us to establish the presence of the ${\\bf{\\alpha}}_{\\mathrm{{\\alpha}}}\\mathrm{{Fe}}_{2}{\\bf{\\mathrm{O}}}_{3}$ phase, because of the closer edge position and the same shape and position of the pre-edge peak (Supplementary Fig. 14). The first shell and the Fe–Fe bond distances agree with the $\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm\\mathrm{\\bf{\\alpha\\alpha}}\\mathrm\\mathrm{\\alpha{\\alpha\\alpha}\\mathrm{\\alpha\\alpha}\\mathrm{\\alpha\\alpha}\\mathrm{\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha}\\mathrm{\\alpha\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\alpha\\mathrm\\alpha}\\mathrm\\mathrm{\\alpha\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\alpha\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\alpha\\alpha\\alpha\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\alpha\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\alpha\\alpha\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\alpha\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm\\mathrm $ crystallographic determination44, whereas the low Fe–Fe coordination number is a consequence of the subnanometric size of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ particles and the coexistence of $\\mathrm{Fe-N_{4}}$ sites. The EXAFS spectrum of the activated $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ catalyst can be correctly reproduced by an ${\\mathrm{FeN}}_{x}{\\mathrm{C}}_{y}$ moiety with four nitrogen atoms at $2.02\\dot{\\mathrm{A}}$ and two Fe–C contributions in the higher coordination shells (Fig. 3b, Supplementary Fig. 15 and Supplementary Table 4). The Fe–N bond length is, within the estimated error, in good agreement with our previous EXAFS determinations on Fe–NC pyrolysed catalysts45. In a recent study, we showed that only cryostatic $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy could spectroscopically distinguish Fe– $\\cdot\\mathrm{N}_{x}$ sites from nano and amorphous iron oxides46. 57Fe Mössbauer spectroscopy was therefore conducted at $5\\mathrm{K}$ to study the Fe speciation in Fe–NC before and after the activation. The spectrum of Fe–NCU was fitted with a sextet component that can clearly be assigned to $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ and with a doublet (labelled $\\mathrm{D}1^{*}$ ) with quadrupole splitting (QS) of $1.1\\mathrm{mm}\\mathrm{s}^{-1}$ (Fig. 3c). The latter can be assigned either to a subtype of $\\mathrm{Fe-N}_{x}$ sites10,31,47 or to superparamagnetic Fe oxide (it can be hypothesized that subnanometric or few-atom clusters of Fe and O remain superparamagnetic even at 5 K). The Fe–NCU therefore contains both $\\mathrm{Fe-N}_{x}$ -like sites and a considerable fraction of Fe as $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ . The $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ is presumably present at a subnanometre size domain (a few atoms of Fe and O) as no obvious iron clustering could be detected by atomic-resolution HAADF-STEM (Supplementary Fig. 8a,b). Although a few pairs of heavy elements (bright spots) are apparent in Supplementary Fig. 8b, which suggests the existence of binuclear $\\mathbf{M}_{2}\\mathbf{N}_{x}$ sites48, however, these may also be Fe (or $Z\\mathrm{n}{\\dot{}}$ ) single atoms embedded in two different layers of graphene sheets but coincident in the two dimensional image. \n\nAfter the activation, however, the sextet signal disappeared and the Mössbauer spectrum was fitted with mainly two doublets, labelled D1 and D2, assigned to $\\mathrm{Fe-N}_{x}$ moieties, and a minor signal of a third doublet (D3) (Fig. 3d). Although the isomer shifts (IS) of D1 and D2 are similar, their QS values strongly differ—D1 typically has a QS close to $1\\mathrm{mm}s^{-1}$ and D2 in the range of $1.9{-}2.6\\operatorname*{mms}^{-1}$ . More precisely, D1 was recently identified from an ex situ experimental characterization combined with density functional theory calculation of the QS of $\\mathrm{Fe-N}_{x}$ sites as a ferric high-spin $\\mathrm{Fe-N_{x}}$ moiety with an oxygen adsorbate on top49. This assignment was strengthened by an in situ Mössbauer spectroscopy study in PEMFC, which showed that D1 in another Fe–NC catalyst reversibly switched to a quadrupole doublet with an IS of ${\\sim}1\\mathrm{mms^{-1}}$ at a low electrochemical potential, which can be unambiguously assigned to a high-spin ferrous species33. Doublet D2 was typically observed in pyrolysed Fe–NC samples, coexisting with D1, with an exact D1/D2 ratio that depended on the synthesis20,45,47,49. From experimental ex situ characterization coupled with the density functional theory prediction of QS values, D2 was recently assigned to $\\mathrm{Fe-N}_{x}$ moieties in the ferrous state and with a low or medium spin state49. Moreover, it was shown that the D2 signal is independent of the cathode potential and atmosphere $\\mathrm{~\\i~}_{\\mathrm{~\\it~\\Omega~}_{2}}$ free or $\\mathrm{O}_{2}\\ \\mathrm{rich})^{50}$ , which supports the fact that it corresponds either to sites situated in the bulk of the carbon matrix and/or to surface sites that bind $\\mathrm{~O}_{2}$ weakly. The minor D3 component can be unambiguously assigned to high-spin ferrous centres, due to its high IS of $1.04\\mathrm{{mms^{-1}}}$ (Supplementary Table 5 and Supplementary Note 5). It may correspond either to a third type of $\\mathrm{Fe-N}_{x}$ sites47 or to $\\mathrm{FeCl}_{2}$ hydrate- or graphite-intercalated $\\mathrm{FeCl}_{2}$ (with IS values that match those of $\\mathrm{D}3^{51,52}$ ) that remain after the activation step. A doublet with IS and QS values similar to those of D3 was observed in the Mössbauer spectrum of an Fe–NC synthesized via the non-contact pyrolysis of $\\mathrm{FeCl}_{3}$ and a nitrogen-doped carbon support, and assigned to $\\mathrm{FeCl}_{2}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ (ref. 32). The conversion from nano-Fe-oxides into $\\mathrm{Fe-N}_{x}$ sites during pyrolysis was recently and independently demonstrated by Wu’s group53 and by Jia’s group32. In our recent work, it was observed that the adsorption of oxygen at the $\\mathrm{Fe-N}_{x}$ sites and subsequent spillover to the neighbouring carbon atoms resulted in a degradation of the ORR activity, which could then be recovered by activating the catalyst at $600^{\\circ}\\mathrm{C}$ (ref. 54). This may indicate a potential formation of iron oxo species and/or nanoxide by oxygen adsorption, which could be reconverted into $\\mathrm{Fe-N}_{x}$ sites by heat treatment. \n\nDetermination of SD and TOF by nitrite and CO methods. An in situ nitrite stripping technique was employed to evaluate the effects of catalyst activation on SD and site activity (Supplementary Note 6)34. A large well-defined nitrite reduction peak was observed for the $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ in its poisoned cyclic voltammetry (CV) between 0.29 and $-0.30\\mathrm{V}_{\\mathrm{RHE}}$ (RHE, reversible hydrogen electrode) (Fig. 4b), whereas only a tiny reductive peak was observed in the corresponding CV of $\\mathrm{Fe-NC^{U}}$ (Fig. 4a). The total amount of charge associated with the NO stripping peak of Fe–NCΔ-DCDA was $37.4\\mathrm{Cg}^{-1}$ (inset of Fig. 4b), which is over six times greater than the $5.8\\mathrm{Cg^{-1}}$ for $\\mathrm{Fe-NC^{U}}$ (inset of Fig. 4a). The corresponding SD values for the Fe– $\\mathsf{N C}^{\\mathrm{U}}$ and $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ were $0.72\\times10^{19}$ sites $\\mathbf{g}^{-1}$ $(0.93\\times10^{16}\\mathrm{{sites}\\mathrm{{m}^{-2}}})$ ) and $4.67\\times10^{19}$ sites $\\mathbf{g}^{-1}$ ( $4.04\\times10^{16}$ sites $\\mathbf{m}^{-2}$ ), respectively (Fig. 4e). This SD value of Fe–NCΔ-DCDA represents only about $7\\%$ of the surface accessible iron based on Fig. 1a (and $6\\%$ of the total iron in the material), but is surprisingly close to the number of edge iron sites $(6\\pm2\\times10^{19}\\mathrm{sitesg^{-1}}^{\\cdot}$ ) estimated for this catalyst based on a domain size of $\\mathrm{L_{a}}{=}7.3{\\pm}2.3{\\mathrm{nm}}$ (Supplementary Note 1 and Supplementary Table 1). Thus, there is the potential to increase the mass activity of the catalyst by about a factor of 13 if all the surface sites can achieve the same activity. The control $\\mathrm{Fe-NC^{\\Delta}}$ sample showed an SD of only $1.12\\times10^{19}{\\mathrm{sitesg}}^{-1}$ , lower than the $4.67\\times10^{19}$ sites $\\mathbf{g}^{-1}$ for $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ , which reflects the importance of DCDA during activation (Supplementary Table 6 and Supplementary Fig. 17). \n\nThe ex situ CO cryo chemisorption technique was also employed for the determination of site densities (Supplementary Note 7 and Supplementary Fig. 19)35,37. The calculated $\\ensuremath{\\mathrm{SD}}_{\\mathrm{CO}}$ values for Fe– $\\mathsf{N C}^{\\bar{\\mathsf{U}}}$ and $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ were $4.86\\times10^{19}$ and $7.83\\times10^{19}\\mathrm{sitesg^{-1}}$ , respectively (Fig. 4e). Although the trends of the SD values for both Fe–NCs are comparable for the CO and nitrite stripping techniques, the SD values determined by CO chemisorption are considerably higher (7 and 1.7 times for the unactivated and activated samples, respectively; see Supplementary Note 7 for a discussion). As CO cryo chemisorption is a gas-phase method, it can probe more $\\mathrm{Fe-N}_{x}$ sites than nitrite stripping, which requires accessibility of nitrite ions to the active sites via a liquid electrolyte. Thus, the CO method presumably represents an upper bound, whereas the nitrite method represents a lower bound on the number of sites38. The 1.7 times higher $\\ensuremath{\\mathrm{SD}}_{\\mathrm{co}}$ versus $\\mathrm{SD}_{\\mathrm{nitrite}}$ for the Fe–NCΔ-DCDA is in line with the previous differences observed among four pyrolysed benchmark Fe–NC samples38. \n\nTOFs were estimated from the decrease in ORR kinetic current on nitrite poisoning and divided by $\\mathrm{SD}_{\\mathrm{nitrite}}$ . Tafel plots for the ORR on these two catalysts (Fig. $^{\\mathrm{4c,d})}$ show the effect of poisoning (see Supplementary Fig. 16a,b for the rotating disk electrode (RDE) responses). It is observed that the $\\mathrm{Fe-NC^{U}}$ catalyst exhibits a low absolute ORR activity and does not show any noticeable ORR performance loss on poisoning (Fig. $\\mathtt{4c}$ and Supplementary Fig. 16a). However, the Fe–NCΔ-DCDA delivers a high ORR activity before poisoning and then undergoes a large activity drop after poisoning, which can be fully recovered by reductive stripping of NO (Fig. 4c and Supplementary Fig. 16b). The derived $\\mathrm{TOF}_{5.2}$ (the subscript represents the electrolyte $\\mathrm{pH}~5.2$ at which TOF is estimated) was assessed at different potentials. The $\\mathrm{TOF}_{5.2}$ value of 0.054 e site $^{-1}{\\sf S}^{-1}$ was calculated at $0.80\\mathrm{V}_{\\mathrm{RHE}}$ for the unactivated sample and could not be assessed at higher potentials (Fig. 4f). The calculated $\\mathrm{TOF}_{5.2}$ values for the $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ catalyst at 0.80, 0.85 and $0.90\\mathrm{V}_{\\mathrm{RHE}}$ were 1.12, 0.13 and $0.02\\mathrm{esite}^{-1}\\mathsf{s}^{-1}$ , respectively (Fig. 4f). Thus, by comparing the $\\mathrm{TOF}_{5.2}$ of the two catalysts at $0.80\\mathrm{V}_{\\mathrm{RHE}}$ (0.054 and 1.12, that is, a $\\times21$ improvement), it becomes clear that the activation step plays a key role not only in improving the SD $(\\times6.5$ , Supplementary Table 6) but even more importantly in improving the TOF of the electrochemically accessible Fe sites. \n\nThe advancement made in the SD and $\\mathrm{TOF}_{5.2}$ levels in the present work was gauged against four Fe–NC catalysts that were benchmarked in our recent work under the CRESCENDO project38. Isoactivity plots were drawn using the SD and $\\mathrm{TOF}_{5.2}$ values (at 0.80 and $0.85\\mathrm{V}_{\\mathrm{RHE}})$ to compare the $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ with the benchmark catalysts. From Fig. 4g,h, it can be seen that the Fe–NCΔ-DCDA possesses an exceptionally high SD, with the improvement ranging between 3- and 18-fold when compared with those of the four state-of-the-art catalysts. Compared with the ZIF-derived CNRS benchmark catalyst optimized for an increased SD, the $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ contained not only more than three times the density of active sites but also higher $\\mathrm{TOF}_{5.2}$ values. At $0.80\\mathrm{V}_{\\mathrm{RHE}},$ $\\mathrm{TOF}_{5.2}$ of the Fe–NCΔ-DCDA catalyst is $1.12\\mathrm{esite}^{-1}s^{-1}$ , that is, more than 1.7 times greater than the $0.65\\mathrm{esite}^{-1}s^{-1}$ for the CNRS catalyst. Among the four benchmark materials, the PAJ catalyst had the lowest SD $(0.25\\times10^{19}$ sites g−1), but the highest $\\mathrm{TOF}_{5.2}$ $\\left(7.23\\mathrm{esite}^{-1}\\mathsf{s}^{-1}\\right.$ at $0.80\\mathrm{V}_{\\mathrm{RHE}})$ . Our Fe– $\\mathrm{NC^{\\Delta\\mathrm{{\\cdotDCDA}}}}$ catalyst combines a very high SD and a relatively high TOF, which leads to a high ORR mass activity. \n\nORR activity and SD–ORR correlation. The ORR activity of Fe–NC catalysts was also evaluated in a $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte $\\left(\\mathrm{pH}0.3\\right)$ . In addition to the $\\mathrm{Fe-NC^{\\mathrm{U}}}$ Fe–NCΔ-DCDA and $\\mathrm{Fe-NC^{\\Delta}}$ catalysts, an additional $\\mathrm{Fe-NC^{\\Delta-CA}}$ sample was synthesized by replacing the DCDA with cyanamide (CA) during the activation to assess the effect of SD and TOF on the ORR performance. As shown in Fig. 5a, ORR voltammetry demonstrates a high ORR performance in the order $\\mathrm{Fe-NC^{\\Delta\\mathrm{-}D C D A}>F e-N C^{\\Delta\\mathrm{-}C A}>F e-N C^{\\Delta}>F e-N C^{\\mathrm{U}}}$ The best-performing Fe–NCΔ-DCDA catalyst delivered an outstanding activity with a half-wave potential $(E_{1/2})$ of $0.815\\mathrm{V}_{\\mathrm{RHE}}$ at a low loading of $0.2\\mathrm{mg}\\mathrm{cm}^{-2}$ and mass activities of $31.9\\mathrm{Ag^{-1}}$ at $0.80\\mathrm{V}_{\\mathrm{RHE}}$ and $4.9\\mathrm{Ag^{-1}}$ at $0.85\\mathrm{V}_{\\mathrm{RHE}}$ , which are far greater than the respective values obtained for the benchmark Fe–NCs (Supplementary Fig. 20). \n\nAlthough we have previously shown that the site activity is $\\mathrm{\\pH}$ independent between $\\mathrm{pH}0.3$ and 5.2 for our benchmark Fe–NC catalyst34, it is unclear whether this is a universal effect for all Fe–NCs. Hence, we used the total kinetic current measured at $\\mathrm{pH}0.3$ (that is, the same approach as used when estimating the site activity by CO chemisorption) to establish an alternative TOF (labelled as $\\mathrm{TOF}_{0.3}$ ) from the combination of the nitrite SD measurement at $\\mathrm{pH}~5.2$ and ORR activity measurement in sulfuric acid at $\\mathrm{pH}0.3$ . \n\n![](images/8a86d8e8b66837592dacd609e674749d50f10c9c58801696adec0707b38b6d5e.jpg) \nFig. 4 | SD and TOF measurements of Fe–NCs in a pH 5.2 electrolyte. a,b, CVs of Fe–NCU (a) and Fe–NCΔ-DCDA (b) catalysts at unpoisoned, poisoned and recovered stages of the nitrite stripping protocol. Insets: amount of charge associated with the reduction of nitrite molecules adsorbed on Fe sites. c,d, Negative shift of the kinetic ORR activities of Fe– ${\\mathsf{\\cdot N C}}^{\\cup}$ $(\\pmb{\\mathscr{c}})$ and Fe– ${\\mathsf{N C}}^{\\Delta-\\mathsf{D C D A}}$ (d) on nitrite poisoning. e, Comparison of SD values determined by nitrite stripping and CO chemisorption methods for both catalysts. f, Comparison of TOFs $(\\mathsf{T O F}_{5.2})$ at 0.80, 0.85 and $0.90\\mathsf{V}_{\\mathsf{R H E}}$ for both catalysts. g,h, Isoactivity plots at $0.80\\mathsf{V}_{\\mathsf{R H E}}\\left(\\pmb{\\mathsf{g}}\\right)$ and $0.85\\lor_{\\mathbb{R}\\mathsf{H E}}$ (h) comparing the ORR performance metric of the Fe–NCΔ-DCDA catalyst developed in this study to recently reported four benchmark Fe–NCs (see Methods section for explanation of labels) 38. The nitrite stripping measurements were performed in a $0.5{\\ensuremath{M}}$ acetate buffer electrolyte $(\\mathsf{p H}5.2)$ at 1,600 r.p.m. and the catalyst loading was $0.2\\mathsf{m g}\\mathsf{c m}^{-2}$ . kin, kinetic. \n\n![](images/adf8dd36dec73f607241f7a2f5e5fadaeb01600e63c6d5c204b62f22e89bf05e.jpg) \nFig. 5 | ORR activity and correlation with SD and kinetic activity in a $\\mathsf{p H}0.3$ electrolyte. a, RDE ORR curves measured in $\\mathsf{O}_{2}$ -saturated $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ with a rotation speed of 900 r.p.m. The catalyst loading was $0.2\\mathsf{m g c m^{-2}}$ , b, Correlation of kinetic ORR activity in $0.5{\\ensuremath{M}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at different potentials with the mass-based SD measured by nitrite stripping. Lines represent the fit to equation (2). Inset: plot of the derived activity of the sites in all the catalysts showing the activity at the equilibrium potential and the Tafel slope determined from the plot. \n\nThe ORR kinetic mass activities at $\\mathrm{pH}0.3$ of the activated Fe–NCs showed a linear correlation with mass-based SD (sites $\\mathbf{g}^{-1}$ ) (Fig. 5b). In addition, the trend of ORR improvement was almost identical for both mass-based and surface-area-based values of SD (Fig. 5b and Supplementary Figs. 24 and 25), which suggests that the active sites are strongly correlated with the surface, as might be expected. It is also intriguing that the plots point to a zero intercept at non-zero SD—this implies that for these catalysts, there is a minimum acceptable SD below which there is no appreciable activity. The lines that fit the datapoints were established by fitting all the data points to the function: \n\n$$\nj\\left(\\eta,\\mathrm{SD}\\right)=\\left(\\mathrm{SD}-\\mathrm{SD}_{0}\\right)q_{\\mathrm{e}}j_{\\mathrm{{o,site}}}\\mathrm{exp}\\left(\\frac{-\\alpha\\eta F}{R T}\\right)\n$$ \n\nwhere $j$ is the mass activity and is a function of the overpotential $\\eta$ and the SD. As fitting parameters we have $\\ensuremath{\\mathrm{SD}}_{0}$ which is the minimum number of sites required before we see any activity, and $j_{\\mathrm{o,site}}$ is the exchange current density associated with a single site in terms of TOFs. $q_{\\mathrm{e}}$ is the charge on an electron. To take the overpotential into account, we applied the Tafel approximation as we are ${\\bf\\nabla}{\\bf\\times}4R T/F(\\mathrm{V})$ away from the equilibrium potential. Hence, we included the overpotential (the potential difference between the potential applied and the equilibrium potential of the oxygen reduction, $1.229\\mathrm{V})$ ) multiplied by the symmetry factor $(\\alpha)$ , Faraday constant ( $\\vec{\\cdot}\\ (\\mathrm{C\\mol^{-1}})$ ) and the temperature and gas constant $T,K$ and $R,8.314\\mathrm{JK^{-1}m o l^{-1}},$ . Equation (2) was fitted to all the datapoints in Fig. 5b simultaneously, with fitting parameters $\\mathrm{SD}_{0},j_{\\mathrm{o,site}}$ and $\\alpha$ using a fitting procedure that samples the parameter space to arrive at a statistically likely global best fit (further details in Supplementary Note 8). The best-fit parameters are $\\mathrm{SD}_{0}{=}6.2\\times10^{18}$ sites $\\mathbf{g}^{-1}$ , $j_{\\mathrm{o,site}}=5.0\\times10^{-7}\\mathrm{esite^{-1}}\\mathrm{s^{-1}}$ and $\\alpha{=}0.96$ . A non-zero value of $\\mathrm{SD}_{0}$ implies that, across the catalysts tested, there is a constant number of sites that are ORR inactive and it is only when there are more than this number of sites that we see any significant ORR activity. This might be due to site overcounting by nitrite stripping, which may imply that a certain number of sites are active for the nitrite adsorption and reduction, but inactive for the ORR. The surprising result is that we can replicate all the data assuming a single type of site with a consistent variation of activity. It is useful to compare the value of $j_{\\mathrm{o,site}}$ with that expected for platinum. Using the data on the exchange current density for $2.48\\mathrm{nm}$ platinum particles55, we calculated a $j_{\\mathrm{o,site}}$ for platinum of $0.012\\mathrm{esite_{\\mathrm{pt}}}^{-1}\\:s^{-1}$ at the equilibrium potential (where we count each surface platinum atom as a site). Hence, the extrapolated exchange current density suggests that surface platinum atoms in platinum nanoparticles are about 20,000-fold more active than the Fe–NC sites under equivalent conditions. However, the improvement in activity of the Fe–NC sites is associated with a low Tafel slope of $61\\mathrm{mV}$ decade−1, which means that the Fe–NC sites increase in activity faster than the Pt ones, for which much higher Tafel slopes 1 $\\mathrm{\\Phi}^{\\prime}{\\sim}137\\mathrm{mV}$ decade−1 outside the oxide region55) are typically measured. The Fe–NC sites have a $\\mathrm{TOF}_{0.3}$ of 0.10, 0.84 and 5.4 e site−1 $\\ensuremath{\\mathbf{s}}^{-1}$ at 0.90, 0.85 and $0.80\\mathrm{V_{RHE}}$ respectively (Supplementary Table 7), significantly greater ( $\\geq5$ times) than the $\\mathrm{TOF}_{5.2}$ values in Fig. 4. \n\nThe selectivity of $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ towards a four-electron oxygen reduction pathway was determined by measuring the peroxide yields at three different loadings (0.1, 0.2 and $0.8\\mathrm{mg}\\mathrm{cm}^{-2}$ ). A relatively low $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield was detected at all the loadings, and remained between 1 and $2\\%$ across the wide potential range (Supplementary Fig. 26), which indicates that $\\mathrm{Fe-N_{4}}$ sites predominantly catalyse the ORR by a four-electron mechanism. \n\nPerformance characterization in a fuel cell. Single-cell PEMFC tests were carried out in $5\\mathrm{cm}^{2}$ and $50\\mathrm{cm}^{2}$ (Supplementary Note 10) cell active areas with $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ as the cathode catalyst $(3.9\\mathrm{mg}\\mathrm{cm}^{-2}$ loading; $1.0\\mathrm{mg}\\mathrm{cm}^{-2}$ in the large area configuration to ameliorate mass transport effects—see the opening paragraphs) (Fig. 6 and Supplementary Figs. 27–37). Under $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ conditions, the catalyst delivers an excellent performance with a current density of $41.3\\mathrm{mAcm}^{-2}$ at the reference cell voltage of $0.90\\mathrm{V}_{i R\\mathrm{-free}}$ (Fig. 6a), which is among the highest reported values for PGM-free catalyst $\\cdot6,20,22,26,33,40,45,56$ . This translates into a mass activity of $10.6\\mathrm{Ag^{-1}}$ , which reflects the high kinetic activity. Recently, current densities in the $25{-}33\\operatorname*{mAcm}^{-2}$ range were reported at $0.90\\mathrm{V}_{i R\\mathrm{-free}},$ but mostly with very-high Fe–NC loadings (ca. $6.0{-}6.8\\operatorname*{mgcm^{-2}}.$ ) (refs. $^{33,40}$ ), which results in low mass activities between 4 and $6\\mathrm{Ag^{-1}}$ . The substantial progress in the kinetic current density of the Fe–NC catalyst accomplished in this work is compared with reported Fe–NC performances in Fig. 6c. In the high current density range, the fuel cell performs very well with a measured current density of $1,130\\mathrm{mAcm}^{-2}$ at $0.60\\mathrm{V}$ (or $1,910\\mathrm{mA}\\ \\mathrm{cm}^{-2}$ at $0.60\\mathrm{V}_{i R\\mathrm{free}})$ and reaches an $i R$ -corrected peak power density $>1.2\\mathrm{W}\\mathrm{cm}^{-2}$ at a cell voltage of $0.49\\mathrm{V}_{i R\\mathrm{-free}}$ (Supplementary Fig. 27). In the $\\mathrm{H}_{2}$ –air operation (Fig. 6b), the measured current density at the reference voltage of $0.80\\mathrm{V}$ was $145\\mathrm{mAcm}^{-2}$ (or $199\\mathrm{mA}$ at $0.80\\mathrm{V}_{i R\\mathrm{free}})$ , which is considerably higher than most of the previously reported values, which range between 75 and $113\\mathrm{mAcm}^{-2}$ (refs. 6,20,22,26,40,56–58). A measured current density of $700\\mathrm{mAcm}^{-2}$ was reached at $0.6\\mathrm{V}$ (or $805\\mathrm{mAcm}^{-2}$ at $0.60\\mathrm{V}_{i R\\mathrm{-free}})$ (Fig. 6b and Supplementary Fig. 29). A peak power density of $429\\mathrm{mW}\\mathrm{cm}^{-2}$ was obtained in the $\\mathrm{H}_{2}$ –air conditions at $0.55\\mathrm{V}$ $(483\\mathrm{mW}\\mathrm{cm}^{-2}$ at $0.62\\mathrm{V}_{i R\\mathrm{-free}})$ (Supplementary Fig. 29). It is expected that further optimization of the primary catalyst particle size and cathode layer structure could potentially lead to even higher performance levels6,26,40,59. Short membrane electrode assembly (MEA) stability tests were carried out in a constant voltage mode at 0.40, 0.70 and $0.80\\mathrm{V}$ in the $\\mathrm{H}_{2}$ –air environment (Supplementary Note 9 and Supplementary Fig. 32). At $0.40\\mathrm{V},$ there was a $68\\%$ retention of the initial current density after ten hours as compared with $40\\mathrm{-}45\\%$ of current density retention observed at higher operating voltages of $0.70{-}0.80\\mathrm{V}.$ These results are consistent with previous studies in which MEAs using Fe–NCs experienced a quick performance loss at high operating voltages caused by demetallation of the $\\mathrm{Fe-N_{4}}$ sites and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ -induced carbon oxidation60,61. Recently, notable improvements in the Fe–NC performance stability in fuel cells by coating a protective carbon layer on the catalyst surface were reported62,63. This is a promising step towards developing strategies to stabilize the long-term performance of MEAs composed of Fe–NCs. Electrodes were also compared before and after the stability tests through in situ cyclic voltammograms under nitrogen, electrochemical impedance spectroscopy (EIS) and XANES. The voltammetry indicates an increase in pseudocapacitance after fuel cell operation, indicative of some corrosion and oxidation of the carbon (Supplementary Fig. 33). The EIS (Supplementary Fig. 34) spectra were obtained before and after the transients at 0.40, 0.70 and $0.80\\mathrm{V}$ at the respective transient voltage and showed an increase in the charge transfer resistance after polarization. The XANES analysis of Fe–NC cathodes before and after the stability tests showed some mobilization of iron, which enters the Nafion electrolyte. Recent Mössbauer studies of Fe–NC fuel cells by one of $\\mathrm{u}\\mathrm{s}^{46}$ suggest that it is most likely that the D1 iron was converted into Fe cations in Nafion because D3 contributes only $3\\%$ of the Mössbauer signal initially and D2 was shown to be robust by operando and/or post-mortem Mössbauer spectroscopy, whereas D1 was shown to be much less stable, both in PEMFC and anion exchange membrane fuel cell conditions for a moderately similar Fe–NC. This degradation highlights the need for the stability improvement of Fe–NC catalysts, especially at high operating voltages. \n\n![](images/00f32ba0d7c1ed5d25c58b49b86bca64c5d310bf50cbfa8f6b4b63c352f76975.jpg) \nFig. 6 | Performance tests with Fe–NCΔ-DCDA as the cathode catalyst in a single-cell PEMFC. a,b, ${\\sf H}_{2}{\\mathrm{-}}\\mathsf{O}_{2}$ (a) and ${\\sf H}_{2}$ –air (b) polarization curve. c, Comparison of the current density and catalyst mass activity of Fe– ${\\mathsf{N C}}^{\\Delta-\\mathsf{D C D A}}$ at a reference voltage of $0.90\\mathsf{V}_{i R\\mathsf{-}\\mathsf{f r e e}}$ under ${\\sf H}_{2}{\\mathrm{-}}\\mathsf{O}_{2}$ conditions with reported values. Test conditions: anode, commercial $\\mathsf{P t/C}$ anode with $0.4\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2}$ (Alfa Aesar, Johnson Matthey); cathode, $F e\\mathrm{-NC^{\\Delta\\cdotDCDA}}$ with a $3.90\\mathsf{m g c m^{-2}}$ loading; Nafion 211 membrane; cell temperature, $80^{\\circ}\\mathsf{C}$ ; $100\\%$ relative humidity at both electrodes. Flow rates of 200 sccm of both gases in the ${\\sf H}_{2}{\\mathrm{-}}{\\sf O}_{2}$ tests, and 300 and 1,000 sccm for ${\\sf H}_{2}$ and air, respectively, for ${\\sf H}_{2}$ –air tests; 1 bar gauge pressure at both electrodes. \n\n# Conclusions \n\nA highly active Fe–NC catalyst was developed from a $Z\\mathrm{n-}$ $\\mathrm{N}_{x}$ -enriched NC matrix by exchanging $Z\\mathrm{n}$ with Fe. The resultant activated Fe–NC catalyst consisted of $7\\mathrm{wt\\%}$ iron exclusively coordinated as $\\mathrm{Fe-N_{4}}$ sites, as identified by $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy and XAS. The activation step played a key role in completely converting nano-Fe-oxides into D1 and D2 sites. The Fe–NCΔ-DCDA catalyst had high SD values of $4.67\\times10^{19}$ and $7.8\\times10^{19}$ sites $\\mathbf{g}^{-1}$ , as determined by nitrite stripping and CO chemisorption methods, respectively. This catalyst delivered an excellent ORR activity in RRDE with a mass activity of $31.9\\mathrm{Ag^{-1}}$ at $0.80\\mathrm{V}_{\\mathrm{RHE}}$ . In PEMFC tests, a current density of $41.3\\mathrm{mAcm}^{-2}$ at $0.90\\mathrm{~V}_{\\mathrm{iR-free}}$ is obtained under $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ and $145\\mathrm{mAcm}^{-2}$ at $0.80\\mathrm{V}$ with a maximum power density of $429\\mathrm{mW}\\mathrm{cm}^{-2}$ at $0.55\\mathrm{V}$ reached in $\\mathrm{H}_{2}$ –air environments. The synthesis strategy presented in this work can potentially overcome many hurdles that could be encountered with other complicated synthesis routes for the mass production of Fe–NCs. \n\n# Methods \n\nSynthesis of electrocatalysts. In the first step, commercial ZIF-8 (Basolite Z1200, Sigma Aldrich) as a combined C and N precursor was pyrolysed in a tube furnace at $900^{\\circ}\\mathrm{C}$ for 1 h under flowing nitrogen gas (research grade, BOC Ltd) to obtain a nitrogen-doped carbon framework that contained abundant $Z\\mathrm{n-N}_{x}$ sites $(Z\\mathrm{n-NC})$ . A heating rate of $3\\mathrm{Kmin^{-1}}$ was used to reach the set temperature of $900^{\\circ}\\mathrm{C}$ . The $Z\\mathrm{n-NC}$ product was then leached by refluxing in a 2 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ solution $95\\%$ $\\mathrm{H}_{2}\\mathrm{SO}_{4},$ Aristar, VWR) for $15\\mathrm{-}18\\mathrm{h}$ to effectively remove most of the coordinated $Z\\mathrm{n}$ (□-NC), although these sites are protonated. Leaching $Z\\mathrm{n-NC}$ under aggressive acid reflux conditions was significantly more effective to remove $Z\\mathrm{n}$ as compared with acid leaching at room temperature. In the second step, $100\\mathrm{mg}$ of □-NC powder was dispersed in $\\mathrm{100ml}$ of methanol (VWR) that contained $100\\mathrm{mg}$ of $\\mathrm{Fe(II)Cl_{2}{\\cdot}4H_{2}O}$ $99\\%$ , Honeywell Fluka). This corresponded to an approximately $22\\mathrm{wt\\%}$ Fe(II) content in the Fe and □-NC mixture. For the scaled-up synthesis, $700\\mathrm{mg}$ of □-NC was dispersed in $250\\mathrm{ml}$ of methanol that contained $700\\mathrm{mg}$ of $\\mathrm{Fe(II)Cl_{2}{\\cdot}4H_{2}O}$ . This mixture was refluxed for 15–18 h with constant stirring followed by thorough washing in de-ionized water and then overnight leaching in $0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4}$ to ensure a complete removal of the physisorbed Fe ions. Afterwards, this iron-coordinated catalyst was subjected to a thorough aqueous washing and was then dried in a vacuum oven overnight at $70^{\\circ}\\mathrm{C}$ . This unactivated catalyst, $\\mathrm{Fe-NC^{\\mathrm{U}}}$ , was then mixed with the DCDA $(99\\%$ , Sigma-Aldrich) in a weight ratio of 2:1 and thoroughly ground for $15\\mathrm{min}$ before it was subjected to the activation step at $900^{\\circ}\\mathrm{C}$ for 1 h under a flow of a $5\\%$ $\\mathrm{H}_{2}/\\mathrm N_{2}$ gas mixture (BOC Ltd). The temperature ramping rate was $3\\mathrm{Kmin^{-1}}$ and the sample was cooled down naturally to room temperature after activation to give final activated catalyst, $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ . For single-cell PEMFC tests, □-NC was additionally ball-milled to prepare the Fe–NCΔ-DCDA catalyst. The ball-milling of the dried □-NC powder was carried out at $400\\mathrm{r.p.m}$ for $2\\mathrm{h}$ prior to the Fe incorporation step by methanol reflux. A control sample, Fe-NCΔ, was prepared by heat treating the Fe–NC under identical conditions, except that no DCDA was added. The $\\mathrm{Fe-NC^{\\Delta\\cdotCA}}$ variant was obtained by using CA $(99\\%$ , Sigma-Aldrich) instead of DCDA under otherwise identical activation conditions. \n\nPhysicochemical characterization. Morphological analysis of the synthesised materials was performed by scanning electron microscopy (Inspect F, FEI) and TEM. Recording of the high-resolution TEM images was carried out using a Talos TEM (F200X, FEI) that was equipped with a scanning transmission electron microscope. To analyse the iron sites at an atomic resolution, a probe spherical aberration-corrected scanning transmission electron microscope (Jeol ARM $200\\mathrm{CF}$ equipped with a cold-field emission electron source was used. To minimize the beam damage, $80\\mathrm{keV}$ and a low beam current were used. HAADF-STEM images were obtained using 68–180 mrad collection half-angles at a 24 mrad probe convergence semi-angle. A Gatan Quantum ER dual EELS system was used for the detection of carbon, nitrogen, oxygen and iron, and elemental mappings were collected using Jeol Centurio EDXS system with a $100\\mathrm{mm}^{2}$ silicon drift detector. Powder samples were directly transferred to lacey carbon-coated copper TEM grids. Surface areas and pore structures of the catalysts were measured by nitrogen physisorption analysis using a Micromeritics Tristar II 3020 instrument. Before the measurements, degassing of the powder samples was done at $140^{\\circ}\\mathrm{C}$ overnight under a continuous flow of $\\Nu_{2}$ gas. A multipoint Brunauer–Emmett–Teller model was employed for to estimate the surface areas. High-purity nitrogen gas (BIP plus-X47S) was used for the sample degassing and adsorption measurements, and high-purity He gas (BIP plus-X47S) was used for the free-space measurement. Pore volumes were determined by the non-local density functional theory method using Microactive for Tristar II software, which was based on a slit-shaped pore model. Particle size distribution of the activated Fe–NCΔ-DCDA catalyst was estimated by multiangle dynamic light scattering using a Zetasizer Ultra particle size analyser (Zetasizer Ultra, Malvern Panalytical). X-ray photoelectron spectroscopy measurements were performed using a PHI 5000 VersaProbe (Ulvac-PHI) spectrometer equipped with a monochromator Al Kα $(1,486.6\\mathrm{eV})$ X-ray source to analyse the surface elemental compositions of catalyst powders. All the measured data were calibrated using the C 1s peak at $284.6\\mathrm{eV}.$ High-resolution N 1s spectra of different catalysts were fitted and deconvoluted for the qualitative and quantitative analysis of different types of nitrogen sites. ICP-MS (Agilent ICP-MS 7900) was used to determine the total Fe contents in the Fe–NC catalysts. \n\nXAS data collection. The Zn K-edge XAS spectrum of Zn–NC was collected in the transmission mode at the SAMBA beamline of Synchrotron SOLEIL, using a sagittally focusing Si(220) double-crystal monochromator. Fe K-edge XAS spectra of Fe–NCU and $\\mathrm{Fe-NC^{\\Delta-DCDA}}$ were collected in fluorescence geometry with a Canberra 35-element monolithic planar Ge pixel array detector. The catalysts were pelletized as disks of $10\\mathrm{mm}$ diameter using boron nitride powder as a binder. \n\nEXAFS data analysis. The EXAFS data analysis was performed with the GNXAS code, which is based on the decomposition of the EXAFS $\\chi(\\boldsymbol{k})$ signal into a summation over $n$ -body distribution functions $\\gamma(n)$ calculated by means of the multiple-scattering theory. Details of the theoretical framework of the GNXAS approach are described in refs. 64,65. The $Z\\mathrm{n}$ and Fe coordination shells were modelled with Γ-like distribution functions, which depend on four parameters, namely, the coordination number $N_{\\sun}$ the average distance $R$ , the mean-square variation $\\sigma^{2}$ and the skewness $\\beta$ . Note that $\\beta$ is related to the third cumulant $C_{3}$ through the relation $C_{3}=\\sigma^{3}\\beta$ . \n\nEach signal as calculated in the Muffin-tin approximation using the Hedin–Lundqvist energy-dependent exchange and correlation potential model, which includes inelastic loss effects. Least-square fits of the EXAFS raw experimental data were performed by minimizing a residual function of the type: \n\n$$\nR_{i}\\left(\\left\\{\\lambda\\right\\}\\right)=\\sum_{i=1}^{N}\\frac{\\left[\\alpha_{\\mathrm{exp}\\left(E_{i}\\right)}-\\alpha_{\\mathrm{mod}}\\left(E_{i};\\lambda_{1},\\lambda_{2},...,\\lambda_{p}\\right)\\right]^{2}}{\\sigma_{i}^{2}}\n$$ \n\nwhere subscripts “exp” and “mod” represent the experimental and modelled response, $N$ is the number of experimental points, $E_{i}\\{\\lambda\\}=(\\lambda_{1},\\lambda_{2},...,\\lambda_{p})$ are the $\\boldsymbol{p}$ parameters to be refined and $\\sigma_{i}^{2}$ is the variance associated with each experimental point $\\alpha_{\\mathrm{exp}}(E_{i})$ . Additional non-structural parameters were minimized, namely $E_{0}$ (core ionization threshold energy) and the many-body amplitude reduction factor $S_{0}^{\\ 2}$ . \n\nMössbauer spectroscopy measurements. The $^{57}\\mathrm{Fe}$ Mössbauer spectrometer (Wissel) was operated in transmission mode with a $^{57}{\\mathrm{Co:Rh}}$ source. The velocity driver was operated in the constant acceleration mode with a triangular velocity waveform. The velocity scale was calibrated with the magnetically split sextet of a high-purity $\\upalpha$ -Fe foil at room temperature. The spectra were fitted to appropriate combinations of Lorentzian profiles that represented quadrupole doublets and sextets by least-squares methods. The fittings were performed with unconstrained parameters (relative area, IS, QS, line width and hyperfine field) for each spectral component. The fitted IS values are reported relative to $\\upalpha$ -Fe at room temperature. Fe–NC catalyst powders were mounted in a $2\\mathsf{c m}^{2}$ holder. Mössbauer measurements at 5 K were performed in a helium flow cryostat (SHI-850 Series, Janis). \n\nElectrochemical measurements to evaluate ORR activity. Catalyst inks were prepared by mixing Fe–NC catalysts and Nafion ionomer $(5\\mathrm{wt\\%}$ , Sigma-Aldrich) in a weight ratio of 2:1 in ultrapure water (MilliQ $18.2\\ensuremath{\\mathrm{M}}\\Omega\\ensuremath{\\mathrm{cm}},$ ) and isopropanol (VWR) solvent (1:1 by volume). The catalyst content in the ink was $0.5\\mathrm{wt\\%}$ . The ink was ultrasonicated for $30{-}60\\mathrm{min}$ to obtain a stable suspension. A low catalyst loading of $0.2\\mathrm{mg}\\mathrm{cm}^{-2}$ was used to evaluate the ORR activity of all the synthesized Fe–NC samples. The effect of catalyst loading, that is, layer thickness, on the hydrogen peroxide yield was investigated for the optimized $\\mathrm{Fe-NC}$ by varying the loadings between 0.1 and $0.8\\mathrm{mgcm}^{-2}$ . All the electrochemical measurements were carried out using a RRDE (Pine Instruments, model AFE6R1AU and rotator model AFMSRCE) in a $0.5\\mathbf{M}$ sulfuric acid solution as the electrolyte in a glass jacket cell at room temperature with a RHE as the reference electrode and a glassy carbon rod as the counter electrode. A Luggin–Haber capillary was used to connect the RHE to the main compartment of the glass cell, and the counter electrode was connected through a porous frit. The RRDE used had a glassy carbon disk of $5\\mathrm{mm}$ diameter with a gold ring. The disk was mirror polished and cleaned in an ultrasonication bath with isopropanol and ultrapure water and was dried prior to the ink deposition. The catalyst ink was drop cast on the glassy carbon disk and dried at room temperature. All the electrochemical tests were \n\ncarried out using a potentiostat (Autolab, model PGSTAT20). Ultrapure oxygen and nitrogen gases (BIP plus-X47S, Air Products) were used to record the ORR curves and background currents, respectively. The catalyst was first activated by conducting CV in an $\\mathrm{O}_{2}$ -saturated electrolyte between 0.00 and $1.00\\mathrm{V_{RHE}}$ at a scan rate of $10\\mathrm{mVs^{-1}}$ . Generally, five CV cycles were enough to reach a stable ORR performance. Subsequently, the ORR activity was measured by performing linear sweep voltammetry in an $\\mathrm{O}_{2}$ -saturated electrolyte at an applied potential range of $1.00{-}0.00\\mathrm{V}_{\\mathrm{RHE}}$ at a scan rate of ${5\\mathrm{mVs^{-1}}}$ with rotation speeds of 900 and $1{,}600\\mathrm{r.p.m}$ . The potential of the gold ring was maintained at $1.50\\mathrm{V_{RHE}}$ during the linear sweep voltammetry measurements to estimate the yield of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ during ORR. Linear sweep voltammetry in a $\\mathrm{N}_{2}$ -saturated electrolyte was also recorded under identical conditions to correct the ORR curves for the background currents. Ohmic resistances were determined by EIS and ORR activities were corrected for the iR loss. \n\nDetermination of site density and turnover frequency by nitrite stripping. In situ determination of the active SD and TOF values of the synthesized catalysts was carried out using the nitrite stripping technique. The experimental protocol reported in our previous work was followed with a modified cleaning protocol34. A catalyst loading of $0.2\\mathrm{mg}\\mathrm{cm}^{-2}$ was used for all the nitrite stripping measurements. The ink was deposited on the disk of the RDE by drop casting and dried at room temperature. All the electrochemical measurements were performed in a $0.5\\mathrm{M}$ sodium acetate buffer as electrolyte $(\\mathrm{pH}5.2)$ . The modified catalyst cleaning protocol consisted of measuring (1) 3 CV cycles in $\\mathrm{O}_{2}$ -saturated electrolyte at a scan rate of $5\\mathrm{mVs^{-1}}$ followed by (2) $20\\mathrm{CV}$ cycles in a $\\Nu_{2}$ -saturated electrolyte at a scan rate of $100\\mathrm{mVs^{-1}}$ and $10\\mathrm{CV}$ cycles at a scan rate of $10\\mathrm{mVs^{-1}}$ . Both (1) and (2) were performed in a 1.05 to $-0.4\\mathrm{V}_{\\mathrm{RHE}}$ potential window and were repeated twice. Afterwards, step (1) was performed one last (third) time before proceeding to the measurement of the ORR activity and rest of the nitrite poisoning procedure. A current integrator (or analogue linear-scan generator) was used while performing the nitrite stripping CV scans for an accurate determination of the stripping charge. The catalyst poisoning step, measurement conditions of the ORR activities and nitrite stripping CVs at the unpoisoned, poisoned and recovered stages were the same those as reported previously34. However, a second nitrite poisoning was also performed on the recovered catalyst at the end. There was no ORR measurement involved in between the unpoisoned, poisoned and recovered stages during the second poisoning measurements. The purpose of the second poisoning was to minimize any potential variation in the baseline CV current due to the involvement of ORR steps. The reported values of stripping charge and site densities were calculated using the second poisoning results. The site densities (gravimetric or mass) were calculated as: \n\n$$\n\\mathrm{SD}={\\frac{Q_{\\mathrm{strip}}\\times N_{\\mathrm{A}}}{n_{\\mathrm{strip}}F}}\n$$ \n\nwhere $Q_{\\mathrm{strip}}\\left(\\mathrm{C}\\mathrm{g}^{-1}\\right)$ is the nitrite reductive stripping charge determined from the stripping peak, $n_{\\mathrm{{strip}}}$ is the number of electrons associated with the reduction of one adsorbed nitrosyl per site and its value is 5, $N_{\\mathrm{A}}$ is Avogadro’s constant $\\mathrm{(mol^{-1})}$ ) and $F$ is Faraday’s constant $\\scriptstyle(\\mathrm{C}\\mathrm{mol}^{-1})$ . Areal site densities $(\\mathrm{sites}\\mathrm{m}^{-2},$ were calculated by dividing the gravimetric SD with the catalyst surface areas. \n\nThe TOF at a given potential, for example, $0.80\\mathrm{V}_{\\mathrm{RHE}},$ was determined using the difference in the kinetic ORR mass activity (obtained by correcting the RDE polarization curves for ohmic and diffusion losses) between the poisoned and unpoisoned states at that potential via: \n\n$$\nT O F=\\frac{\\left(J_{\\mathrm{kinmass}}^{\\mathrm{unpoisoned}}-J_{\\mathrm{kinmass}}^{\\mathrm{poisoned}}\\right)\\times N_{\\mathrm{A}}}{\\mathrm{SD}_{\\mathrm{mass}}\\times F}\n$$ \n\nTOF values were calculated at different potentials in the $0.80{-}0.90\\mathrm{V_{RHE}}$ range. \n\nThe four benchmark Fe–NC catalysts compared in the SD–TOF isoactivity plots and the ORR activities were developed in different laboratories and labelled as CNRS (ZIF-derived catalyst from CNRS/University of Montpellier), UNM (silica-templating-based catalyst from the University of New Mexico), ICL (reference Fe–NC catalyst in the ICL laboratory) and PAJ (commercial catalyst from Pajarito Powder Inc. with the product name PMF-011904). \n\nDetermination of site density by CO chemisorption. SD evaluation with the ex situ CO chemisorption method was done as previously reported35,38 with a Thermo Scientific TPD/R/O 110 instrument. A weighed sample of the catalyst was inserted between two pieces of quartz wool on the bottom of the internal quartz bulb. After cleaning the lines in helium flow $20\\mathsf{c c m m i n^{-1}}$ , $30\\mathrm{min}_{\\cdot}^{\\cdot}$ ), consecutive pretreatment of the samples was done with heating from 25 to $600^{\\circ}\\mathrm{C}$ in helium $(20\\mathsf{c c m m i n^{-1}}10^{\\circ}\\mathsf{C}\\operatorname*{min}^{-1})$ , $15\\mathrm{min}$ hold time at $600^{\\circ}\\mathrm{C},$ ), followed by cooling to room temperature. Pulse chemisorption was done at $-80^{\\circ}\\mathrm{C}$ , after line cleaning with helium for $10\\mathrm{min}$ followed by six consecutive pulses of CO gas with detection of the signals with a thermal conductivity detector. For the catalyst surface areas and masses employed in this study, the CO cryo adsorption reached saturation after three pulses. The molar amount of adsorbed CO per mass $n_{\\mathrm{{co}}}$ $\\mathrm{(nmol\\mg_{cat}^{-1}},$ ) \n\nwas calculated by the difference in integral pulse area across the last three pulses and the calibration factor $c_{\\mathrm{i}}$ . \n\n$$\nn_{\\mathrm{CO}}={\\frac{c_{\\mathrm{f}}\\times\\Delta A\\times10^{6}}{m_{\\mathrm{cat}}}}\n$$ \n\nThe mass-based SD with CO chemisorption $(\\mathrm{SD}_{\\mathrm{mass}}$ (CO)) was then calculated from $\\mathtt{n_{C O}}$ via Avogadro’s constant $(\\mathrm{N_{A}})$ according to \n\n$$\n\\mathrm{SD}_{\\mathrm{mass}\\mathrm{CO}}=n_{\\mathrm{CO}}\\times N_{\\mathrm{A}}\\times10^{-6}\n$$ \n\nPEMFC tests using small size single cell $(5\\thinspace\\mathbf{cm}^{2})$ . For single cell PEMFC tests, the MEAs were prepared using an Fe–NC based cathode and a commercial anode with a loading of $0.4\\mathrm{mg}_{\\mathrm{pt}}\\mathrm{cm}^{-2}$ (Alfa Aesar, Johnson Matthey, Hydrogen Reformate/ Cathode). Cathode catalyst ink was prepared by mixing the Fe– $\\cdot\\mathrm{\\mathrm{NC^{\\Delta\\cdotDCDA}}}$ catalyst $(20\\mathrm{mg})$ , $5\\mathrm{wt\\%}$ Nafion ionomer $\\mathrm{(20mg)}$ , ultrapure water $260\\mathrm{mg})$ and isopropanol $(540\\mathrm{mg})$ . Vulcan XC72 $(15\\mathrm{wt\\%})$ ) was added to improve the electrical conductivity. The ink was ultrasonicated for 1 h. The Nafion content in the ink was $50\\mathrm{wt\\%}$ with respect to Fe–NC and around $46\\mathrm{wt\\%}$ with respect to the sum of the Fe–NC and Vulcan XC72. Fe–NC ink was drop cast onto a gas diffusion layer (GDL, 29 BC, SGL) followed by drying in a vacuum oven at $70^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . The final Fe–NC cathode loading was $3.9\\mathrm{mg}\\mathrm{cm}^{-2}$ . MEA was fabricated by hot pressing the commercial anode and an Fe–NC cathode on each side of a Nafion 211 membrane at $130^{\\circ}\\mathrm{C}$ for $3\\mathrm{{min}}$ under an applied pressure of $400\\mathrm{kg}\\mathrm{cm}^{-2}$ . The geometric area of the MEA was $5\\mathrm{cm}^{-2}$ , which was installed in a single cell with a serpentine-type flow field design. Glass-reinforced PTFE gaskets were used to control the MEA compression between 20 and $25\\%$ . Fuel cell tests were conducted at $80^{\\circ}\\mathrm{C}$ by supplying hydrogen at the anode and oxygen/air at the cathode. All the gases were fully humidified $100\\%$ relative humidity) and 1 bar of gauge pressure was maintained at both sides. For the $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ tests, the flow rates of both gases were maintained at $200\\mathrm{sccm}$ . For the $\\mathrm{H}_{2}$ –air tests, flow rates of $300\\mathrm{sccm}$ for hydrogen and $1,000\\mathsf{s c c m}$ for air were used. Both hydrogen and oxygen gases were of ultrapure grade (BIP Plus, Air Products). Polarization curves were recorded using an 850e Fuel Cell Test System (Scribner Associates) by holding the cell voltage for 1 min at each point as simultaneous measurements of the high frequency resistance were performed on the test station at a fixed frequency of 1 kHz. Full impedance spectra were also performed before and after the long-term polarization tests. EIS was performed using a $5\\mathrm{mV}$ sinusoidal perturbation in the frequency range $10^{5}–0.1\\mathrm{Hz}$ using ten measurement points per decade. \n\n# Data availability \n\nThe data used in the production of the figures in this paper are available for download at https://doi.org/10.5281/zenodo.6411262. Additional data can be available from the authors upon reasonable request. \n\nReceived: 12 February 2021; Accepted: 11 March 2022; Published online: 25 April 2022 \n\n# References \n\n1.\t Hydrogen Roadmap Europe (Fuel Cells and Hydrogen 2 Joint Undertaking, 2019); https://www.fch.europa.eu/sites/default/files/Hydrogen%20 Roadmap%20Europe_Report.pdf \n2.\t Multi-Year Research Development, and Demonstration Plan: Section 3.4 Fuel Cells, Office of Energy Efficiency and Renewable Energy (Fuel Cell Technologies Office, 2016); https://www.energy.gov/sites/prod/files/2017/05/ f34/fcto_myrdd_fuel_cells.pdf \n3.\t Wilson, A., Kleen, G. & Papageorgopoulos, D. Fuel Cell System Cost–2017 (DOE Hydrogen and Fuel Cells Program, 2017). \n4.\t Jaouen, F. et al. Recent advances in non-precious metal catalysis for oxygen-reduction reaction in polymer electrolyte fuel cells. Energy Environ. Sci. 4, 114–130 (2011). \n5.\t Jaouen, F. et al. Toward platinum group metal-free catalysts for hydrogen/air proton-exchange membrane fuel cells. Johns. Matthey Technol. Rev. 62, 231–255 (2018). \n6.\t Chung, H. T. et al. Direct atomic-level insight into the active sites of a high-performance PGM-free ORR catalyst. Science 357, 479–484 (2017). \n7.\t Lefèvre, M., Proietti, E., Jaouen, F. & Dodelet, J.-P. Iron-based catalysts with improved oxygen reduction activity in polymer electrolyte fuel cells. Science 324, 71–74 (2009). \n8.\t Wu, G., More, K. L., Johnston, C. M. & Zelenay, P. High-performance electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt. Science 332, 443–447 (2011). \n9.\t Tylus, U. et al. Elucidating oxygen reduction active sites in pyrolyzed metal–nitrogen coordinated non-precious-metal electrocatalyst systems. J. Phys. Chem. C 118, 8999–9008 (2014). \n10.\tSahraie, N. R. et al. Quantifying the density and utilization of active sites in non-precious metal oxygen electroreduction catalysts. Nat. Commun. 6, 8618 (2015). \n11.\tJasinski, R. A new fuel cell cathode catalyst. Nature 201, 1212–1213 (1964). \n12.\tJasinski, R. Cobalt phthalocyanine as a fuel cell cathode. J. Electrochem. Soc. 112, 526 (1965). \n13.\tGupta, S., Tryk, D., Bae, I., Aldred, W. & Yeager, E. Heat-treated polyacrylonitrile-based catalysts for oxygen electroreduction. J. Appl. Electrochem. 19, 19–27 (1989). \n14.\tMartinez, U., Babu, S. K., Holby, E. F. & Zelenay, P. Durability challenges and perspective in the development of PGM-free electrocatalysts for the oxygen reduction reaction. Curr. Opin. Electrochem. 9, 224–232 (2018). \n15.\tMalko, D., Lopes, T., Symianakis, E. & Kucernak, A. The intriguing poison tolerance of non-precious metal oxygen reduction reaction (ORR) catalysts. J. Mater. Chem. A 4, 142–152 (2016). \n16.\tKramm, U. I. et al. On an easy way to prepare metal–nitrogen doped carbon with exclusive presence of MeN4-type sites active for the ORR. J. Am. Chem. Soc. 138, 635–640 (2016). \n17.\tRanjbar Sahraie, N., Paraknowitsch, J. P., Göbel, C., Thomas, A. & Strasser, P. Noble-metal-free electrocatalysts with enhanced ORR performance by task-specific functionalization of carbon using ionic liquid precursor systems. J. Am. Chem. Soc. 136, 14486–14497 (2014). \n18.\tSerov, A., Artyushkova, K. & Atanassov, P. Fe–N–C oxygen reduction fuel cell catalyst derived from carbendazim: synthesis, structure, and reactivity. Adv. Energy Mater. 4, 1301735 (2014). \n19.\tZhang, H. et al. Single atomic iron catalysts for oxygen reduction in acidic media: particle size control and thermal activation. J. Am. Chem. Soc. 139, 14143–14149 (2017). \n20.\t Zhang, H. et al. High-performance fuel cell cathodes exclusively containing atomically dispersed iron active sites. Energy Environ. Sci. 12, 2548–2558 (2019). \n21.\tFerrandon, M. et al. Multitechnique characterization of a polyaniline–iron– carbon oxygen reduction catalyst. J. Phys. Chem. C 116, 16001–16013 (2012). \n22.\tWan, X. et al. Fe–N–C electrocatalyst with dense active sites and efficient mass transport for high-performance proton exchange membrane fuel cells. Nat. Catal. 2, 259–268 (2019). \n23.\t Liu, M., Liu, J., Li, Z., Song, Y. & Wang, F. A silica-confined strategy for completely atomic level Fe(II)–NC catalysts with a non-planar structure toward oxygen reduction reaction. J. Catal. 370, 21–29 (2019). \n24.\tHe, Y. et al. Highly active atomically dispersed $\\mathrm{CoN_{4}}$ fuel cell cathode catalysts derived from surfactant-assisted MOFs: carbon-shell confinement strategy. Energy Environ. Sci. 12, 250–260 (2019). \n25.\t Hu, B.-C. et al. $\\mathrm{SiO}_{2}$ -protected shell mediated templating synthesis of Fe–N-doped carbon nanofibers and their enhanced oxygen reduction reaction performance. Energy Environ. Sci. 11, 2208–2215 (2018). \n26.\t He, Y., Liu, S., Priest, C., Shi, Q. & Wu, G. Atomically dispersed metal– nitrogen–carbon catalysts for fuel cells: advances in catalyst design, electrode performance, and durability improvement. Chem. Soc. Rev. 49, 3484–3524 (2020). \n27.\tDas, R., Pachfule, P., Banerjee, R. & Poddar, P. Metal and metal oxide nanoparticle synthesis from metal organic frameworks (MOFs): finding the border of metal and metal oxides. Nanoscale 4, 591–599 (2012). \n28.\tMorozan, A., Goellner, V., Nedellec, Y., Hannauer, J. & Jaouen, F. Effect of the transition metal on metal–nitrogen–carbon catalysts for the hydrogen evolution reaction. J. Electrochem. Soc. 162, H719 (2015). \n29.\tEllingham, H. J. T. Reducibility of oxides and sulfides in metallurgical processes. J. Soc. Chem. Ind. 63, 125–133 (1944). \n30.\tMehmood, A. et al. Facile metal coordination of active site imprinted nitrogen doped carbons for the conservative preparation of non‐noble metal oxygen reduction electrocatalysts. Adv. Energy Mater. 8, 1701771 (2018). \n31.\tMenga, D. et al. Active‐site imprinting: preparation of Fe–N–C catalysts from zinc ion–templated ionothermal nitrogen‐doped carbons. Adv. Energy Mater. 9, 1902412 (2019). \n32.\tLi, J. et al. Evolution pathway from iron compounds to $\\mathrm{Fe_{1}(I I){-}N_{4}}$ sites through gas-phase iron during pyrolysis. J. Am. Chem. Soc. 142, 1417–1423 (2019). \n33.\tJiao, L. et al. Chemical vapour deposition of Fe–N–C oxygen reduction catalysts with full utilization of dense Fe– ${\\bf\\cdot N_{4}}$ sites. Nat. Mater. 20, 1385–1391 (2021). \n34.\tMalko, D., Kucernak, A. & Lopes, T. In situ electrochemical quantification of active sites in Fe–N/C non-precious metal catalysts. Nat. Commun. 7, 13285 (2016). \n35.\tLuo, F. et al. Accurate evaluation of active-site density (SD) and turnover frequency (TOF) of PGM-free metal–nitrogen-doped carbon (MNC) electrocatalysts using CO cryo adsorption. ACS Catal. 9, 4841–4852 (2019). \n36.\tMalko, D., Kucernak, A. & Lopes, T. Performance of Fe–N/C oxygen reduction electrocatalysts toward ${\\mathrm{NO}}^{2-}$ , NO, and $\\mathrm{NH}_{2}\\mathrm{OH}$ electroreduction: from fundamental insights into the active center to a new method for environmental nitrite destruction. J. Am. Chem. Soc. 138, 16056–16068 (2016). \n37.\tLeonard, N. D. et al. Deconvolution of utilization, site density, and turnover frequency of Fe–nitrogen–carbon oxygen reduction reaction catalysts prepared with secondary N-precursors. ACS Catal. 8, 1640–1647 (2018). \n38.\tPrimbs, M. et al. Establishing reactivity descriptors for platinum group metal (PGM)-free Fe–N–C catalysts for PEM fuel cells. Energy Environ. Sci. 13, 2480–2500 (2020). \n39.\tOsmieri, L. et al. Status and challenges for the application of platinum group metal-free catalysts in proton exchange membrane fuel cells. Curr. Opin. Electrochem. 25, 100627 (2021). \n40.\tUddin, A. et al. High power density platinum group metal-free cathodes for polymer electrolyte fuel cells. ACS Appl. Mater. Interfaces 12, 2216–2224 (2019). \n41.\tGupta, S. et al. Engineering favorable morphology and structure of Fe–N–C oxygen‐reduction catalysts through tuning of nitrogen/carbon precursors. ChemSusChem 10, 774–785 (2017). \n42.\tTerrell, E. & Garcia-Perez, M. Application of nitrogen-based blowing agents as an additive in pyrolysis of cellulose. J. Anal. Appl. Pyrol. 137, 203–211 (2019). \n43.\tLi, J. et al. Volcano trend in electrocatalytic $\\mathrm{CO}_{2}$ reduction activity over atomically dispersed metal sites on nitrogen-doped carbon. ACS Catal. 9, 10426–10439 (2019). \n44.\tWyckoff, R. W. G. Crystal Structures (John Wiley, 1963). \n45.\tZitolo, A. et al. Identification of catalytic sites for oxygen reduction in iron- and nitrogen-doped graphene materials. Nat. Mater. 14, 937–942 (2015). \n46.\tLi, J. et al. Identification of durable and non-durable $\\mathrm{FeN}_{x}$ sites in Fe–N–C materials for proton exchange membrane fuel cells. Nat. Catal. 4, 10–19 (2021). \n47.\tKramm, U. I., Lefèvre, M., Larouche, N., Schmeisser, D. & Dodelet, J.-P. Correlations between mass activity and physicochemical properties of Fe/N/C catalysts for the ORR in PEM fuel cell via $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy and other techniques. J. Am. Chem. Soc. 136, 978–985 (2014). \n48.\tKneebone, J. L. et al. A combined probe-molecule, Mössbauer, nuclear resonance vibrational spectroscopy, and density functional theory approach for evaluation of potential iron active sites in an oxygen reduction reaction catalyst. J. Phys. Chem. C 121, 16283–16290 (2017). \n49.\tMineva, T. et al. Understanding active sites in pyrolyzed Fe–N–C catalysts for fuel cell cathodes by bridging density functional theory calculations and $^{57}\\mathrm{Fe}$ Mössbauer spectroscopy. ACS Catal. 9, 9359–9371 (2019). \n50.\tJing, M. et al. A feasible strategy to enhance mass transfer property of carbon nanofibers electrode in vanadium redox flow battery. Electrochim. Acta https://doi.org/10.1016/j.electacta.2021.138879 (2021). \n51.\tBirchall, T. An investigation of some iron halide complexes by Mössbauer spectroscopy. Can. J. Chem. 47, 1351–1354 (1969). \n52.\tWang, Z. & Inagaki, M. Mössbauer study of iron chloride–graphite intercalation compounds synthesized in molten salt. Carbon 29, 423–427 (1991). \n53.\tLi, J. et al. Thermally driven structure and performance evolution of atomically dispersed $\\mathrm{FeN_{4}}$ sites for oxygen reduction. Angew. Chem. Int. Ed. 58, 18971–18980 (2019). \n54.\tBoldrin, P. et al. Deactivation, reactivation and super-activation of Fe–N/C oxygen reduction electrocatalysts: gas sorption, physical and electrochemical investigation using NO and $\\mathrm{~O}_{2}$ . Appl. Catal. B 292, 120169 (2021). \n55.\t Zalitis, C. M., Kucernak, A. R. J., Lin, X. & Sharman, J. D. B. Electrochemical measurement of intrinsic oxygen reduction reaction activity at high current densities as a function of particle size for $\\mathrm{Pt}_{4}{-}x\\mathrm{Co}_{x}/\\mathrm{C}$ $\\mathit{\\Psi}_{\\left(x=0,1,3\\right)}$ ) catalysts. ACS Catal. 10, 4361–4376 (2020). \n56.\tAl-Zoubi, T. et al. Preparation of nonprecious metal electrocatalysts for the reduction of oxygen using a low-temperature sacrificial metal. J. Am. Chem. Soc. 142, 5477–5481 (2020). \n57.\tLi, J. et al. Structural and mechanistic basis for the high activity of Fe–N–C catalysts toward oxygen reduction. Energy Environ. Sci. 9, 2418–2432 (2016). \n58.\tXie, X. et al. Performance enhancement and degradation mechanism identification of a single-atom Co–N–C catalyst for proton exchange membrane fuel cells. Nat. Catal. 3, 1044–1054 (2020). \n59.\tBanham, D. et al. Critical advancements in achieving high power and stable nonprecious metal catalyst-based MEAs for real-world proton exchange membrane fuel cell applications. Sci. Adv. 4, eaar7180 (2018). \n60.\tChenitz, R. et al. A specific demetalation of Fe– ${\\bf\\cdot N_{4}}$ catalytic sites in the micropores of $\\mathrm{NC\\_Ar+NH_{3}}$ is at the origin of the initial activity loss of the highly active $\\mathrm{Fe/N/C}$ catalyst used for the reduction of oxygen in PEM fuel cells. Energy Environ. Sci. 11, 365–382 (2018). \n61.\tGao, Y. et al. New insight into effect of potential on degradation of Fe-NC catalyst for ORR. Front. Energy 15, 421–430 (2021). \n62.\tLitster, S. Advanced PGM-free Cathode Engineering for High Power Density and Durability, DOE Annual Merit Review Presentation Database (DOE Hydrogen Program, 2021). \n63.\tZelenay, P. & Meyers, D. ElectroCat 2.0 (Electrocatalysis Consortium), Annual Merit Review Presentation Database (DOE Hydrogen Program, 2021). \n64.\tFilipponi, A. & Di Cicco, A. X-ray-absorption spectroscopy and $n$ -body distribution functions in condensed matter. II. Data analysis and applications. Phys. Rev. B 52, 15135–15149 (1995). \n65.\tFilipponi, A., Di Cicco, A. & Natoli, C. R. X-ray-absorption spectroscopy and $n$ -body distribution functions in condensed matter. I. Theory. Phys. Rev. B 52, 15122–15134 (1995). \n66.\tArtyushkova, K. Misconceptions in interpretation of nitrogen chemistry from X-ray photoelectron spectra. J. Vac. Sci. Technol. A 38, 031002 (2020). \n\n# Acknowledgements \n\nThis work was funded by the Fuel Cells and Hydrogen 2 Joint Undertaking under grant agreement no. 779366. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme, Hydrogen Europe and Hydrogen Europe research. The work was supported by the UK Engineering and Physical Sciences Research Council under project EP/P024807/1. \n\n# Author contributions \n\nA.M. and A.K. conceived the idea and designed the experiments. A.M. and M.G. synthesized the materials and carried out electrochemical tests and physical characterizations. A.K. developed the geometrical models of the catalyst. A.M. and M.G. carried out the small-size single-cell tests. F.J., A.R. and M.-T.S. performed the Mössbauer measurements and data analysis, A.Z. and A.K. performed the XAS measurements, data analysis and fitting, and interpretation of the XANES and EXAFS results, \n\nM.P. and P.S. conducted CO chemisorption measurements and data analysis, A.M.B. and D.F. carried out large-size single-cell tests, and G.D. performed energy-dispersive X-ray spectroscopy STEM and atomic-resolution STEM measurements and data analysis. A.M., F.J. and A.K. wrote and edited the manuscript with feedback from all the contributing authors. A.K. acted as the project supervisor. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41929-022-00772-9. \nCorrespondence and requests for materials should be addressed to Anthony Kucernak. Peer review information Nature Catalysis thanks the anonymous reviewers for their contribution to the peer review of this work. \nReprints and permissions information is available at www.nature.com/reprints. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 " + }, + { + "id": "10.1038_s41467-022-35533-6", + "DOI": "10.1038/s41467-022-35533-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-35533-6", + "Relative Dir Path": "mds/10.1038_s41467-022-35533-6", + "Article Title": "Ampere-level current density ammonia electrochemical synthesis using CuCo nullosheets simulating nitrite reductase bifunctional nature", + "Authors": "Fang, JY; Zheng, QZ; Lou, YY; Zhao, KM; Hu, SN; Li, G; Akdim, O; Huang, XY; Sun, SG", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "The development of electrocatalysts capable of efficient reduction of nitrate (NO3-) to ammonia (NH3) is drawing increasing interest for the sake of low carbon emission and environmental protection. Herein, we present a CuCo bimetallic catalyst able to imitate the bifunctional nature of copper-type nitrite reductase, which could easily remove NO2- via the collaboration of two active centers. Indeed, Co acts as an electron/proton donating center, while Cu facilitates NOx- adsorption/association. The bio-inspired CuCo nullosheet electrocatalyst delivers a 1001% Faradaic efficiency at an ampere-level current density of 1035mAcm(-2) at -0.2V vs. Reversible Hydrogen Electrode. The NH3 production rate reaches a high activity of 4.8mmolcm(-2) h(-1) (960mmol g(cat)(-1) h(-1)). A mechanistic study, using electrochemical in situ Fourier transform infrared spectroscopy and shell-isolated nulloparticle enhanced Raman spectroscopy, reveals a strong synergy between Cu and Co, with Co sites promoting the hydrogenation of NO3- to NH3 via adsorbed *H species. The well-modulated coverage of adsorbed *H and *NO3 led simultaneously to high NH3 selectivity and yield.", + "Times Cited, WoS Core": 387, + "Times Cited, All Databases": 389, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000972743600016", + "Markdown": "# Ampere-level current density ammonia electrochemical synthesis using CuCo nanosheets simulating nitrite reductase bifunctional nature \n\nReceived: 29 July 2022 \n\nAccepted: 8 December 2022 \n\nPublished online: 22 December 2022 \n\n# Check for updates \n\nJia-Yi Fang 1,4, Qi-Zheng Zheng 1,4, Yao-Yin Lou 1,2 , Kuang-Min Zhao 1, Sheng-Nan Hu 1, Guang Li1, Ouardia Akdim3, Xiao-Yang Huang1,3 & Shi-Gang Sun 1 \n\nThe development of electrocatalysts capable of efficient reduction of nitrate $(\\mathsf{N O}_{3}^{-})$ to ammonia $(\\mathsf{N H}_{3})$ is drawing increasing interest for the sake of low carbon emission and environmental protection. Herein, we present a CuCo bimetallic catalyst able to imitate the bifunctional nature of copper-type nitrite reductase, which could easily remove $\\mathsf{N O}_{2}^{-}$ via the collaboration of two active centers. Indeed, Co acts as an electron/proton donating center, while Cu facilitates ${\\mathsf{N O}}_{\\mathsf{x}}^{-}$ adsorption/association. The bio-inspired CuCo nanosheet electrocatalyst delivers a $100\\pm1\\%$ Faradaic efficiency at an ampere-level current density of $1035\\mathsf{m A c m}^{-2}$ at $-0.2\\ensuremath{\\mathsf{V}}$ vs. Reversible Hydrogen Electrode. The ${\\mathsf{N H}}_{3}$ production rate reaches a high activity of $4.8\\mathsf{m m o l c m}^{-2}\\mathsf{h}^{-1}$ (960 mmol $\\mathbf{g_{cat}}^{-1}\\mathbf{h}^{-1})$ . A mechanistic study, using electrochemical in situ Fourier transform infrared spectroscopy and shell-isolated nanoparticle enhanced Raman spectroscopy, reveals a strong synergy between Cu and Co, with Co sites promoting the hydrogenation of ${\\mathsf{N O}}_{3}^{-}$ to ${\\mathsf{N H}}_{3}$ via adsorbed $^{*}\\mathsf{H}$ species. The wellmodulated coverage of adsorbed $^{*}\\mathsf{H}$ and ${^*}\\mathsf{N O}_{3}$ led simultaneously to high ${\\mathsf{N H}}_{3}$ selectivity and yield. \n\nNitrate anions $(\\mathsf{N O}_{3}^{-})$ , widely present in industrial and agricultural wastewater, pose a real potential threat to human health and ecological balance, especially their incomplete conversion into nitrites $(\\mathsf{N O}_{2}^{-})$ which are thought to be cancerogenic by inducing liver damage and methaemoglobinaemia1. The conventional biological treatments for ${\\mathsf{N O}}_{3}{}^{-}$ removal into nitrogen $(\\mathsf{N}_{2})$ gas, involving nitrification and denitrification processes, are energy intensive (\\~11.7 to $12.5\\mathsf{k W h\\ k g\\mathsf{N}}^{-1})^{2}$ . Actually, the reduction of ${\\mathsf{N O}}_{3}^{-}$ into ${\\mathsf{N H}}_{3}$ has become of great interest from an industrial point of view since $\\mathsf{N H}_{3}$ is a highly important industrial chemical for the synthesis of pharmaceuticals, fertilizers, dyes, plastic, etc.3, and is also considered for hydrogen storage/release as a carbon-free hydrogen carrier4. To date, the industrial synthesis of ${\\mathsf{N H}}_{3}$ relies heavily on the non-sustainable and eco-unfriendly Haber–Bosch route, which requires harsh conditions i.e., high temperature $(400-600^{\\circ}\\mathsf{C})$ and high pressure $(200-350\\mathsf{a t m})$ , and heavily relies on fossil energy3. The total amount of ${\\mathsf{C O}}_{2}$ produced during the Haber–Bosch process accounts for roughly $1.2\\%$ of the global annual $\\mathbf{CO}_{2}$ emissions, more than any other industrial chemicals synthesis5. \n\nElectrocatalytic reduction of ${\\mathsf{N O}}_{3}^{-}$ into $\\mathsf{N H}_{3},$ powered by green energy, has drawn increasing attention and is considered as a sustainable complementary process to the Haber–Bosch process2,6,7, since this technology can simultaneously meet the 21st session of the Conference of the Parties (COP) two-degree scenario (2DS) target for $\\mathsf{N H}_{3}$ and protect the environment from the eutrophic water pollution. The rational design of novel electrocatalysts with both high activity and selectivity is crucial for reducing ${\\mathsf{N O}}_{3}^{-}$ $(\\mathsf{N O}_{3}\\mathsf{^{-}R R})$ and achieving large-scale applications, and satisfying high industrial demands. Since Nature has developed sophisticated and efficient machinery such as enzymes8,9, it is interesting to design catalysts by studying the mechanism of enzymatic reduction. Indeed, biocatalytic reduction of ${\\mathsf{N O}}_{3}{}^{-}$ to ${\\mathsf{N H}}_{3}$ widely exists inside many microorganisms, where ${\\mathsf{N O}}_{3}^{-}$ ions are firstly reduced into $\\mathsf{N O}_{2}^{-}$ by ${\\mathsf{N O}}_{3}^{-}$ reductases that accept electrons from quinone10. The generated $\\mathsf{N O}_{2}^{-}$ is further converted to $\\mathsf{N H}_{3}$ by nitrite reductases (NIRs) using quinone as electron donors. Among various NIRs, the Cu-type NIRs (Cu-NIRs) found in Rhizobium is one of the most important enzymes for $\\mathsf{N}_{2}$ fixation. Cu-NIRs are trimeric proteins composed of 3 identical subunits, and each monomer has two types of Cu atomic active centers, acting as electron-donating centers (T1Cu) and catalytic centers (T2Cu), respectively10. The reported mechanism proposes that $^{*}\\mathsf{N O}_{2}^{-}$ (where \\* denotes an adsorbed specie) is bound to the T2Cu in a bidentate form via two oxygen atoms. Due to the electrons transfer from T1Cu to T2Cu, the T2Cu oxidation state decreases from (II) to (I), facilitating $^{*}\\mathsf{N O}_{2}^{-}$ association with T2Cu in a bridging nitro binding form. Meanwhile, the aspartate acid besides the $\\mathtt{T2C u}$ provides proton to one oxygen and extends the N-O bond length, leading to the breaking of the N-O bond11. According to the mechanism of $\\mathsf{N O}_{2}^{-}$ reduction on T2Cu and T1Cu, it can be speculated that moderate affinity with ${\\mathsf{N O}}_{3}^{-}$ , protons availability and electrons provision are the key factors for the high efficiency in $N O_{3}^{-}\\mathsf{R R}$ to $\\mathsf{N H}_{3}$ . Jimmy C. Yu et al.12 proved that hydrogen adsorption $({^*}\\mathsf{H})$ , with moderate adsorption energy on catalysts, can behave as an important reactive species for the hydrogenation of $\\mathsf{N O}_{\\mathsf{x}}$ intermediates to $\\mathsf{N H}_{3}$ whilst suppressing the hydrogen evolution reaction (HER) competition. Matthew J. Liu et al.13 also found that the $N O_{3}^{-}\\mathsf{R R}$ activity and product selectivity highly depended on the $^{*}\\mathsf{H}$ coverage on the titanium surface at different potentials with the increase of $N O_{3}^{-}\\mathsf{R R}$ overpotential. \n\nVery recently, Schuhmann and his colleagues14 reported a tandem mechanism for ${\\mathsf{P O}}_{4}^{3-}$ -modified CuCo binary metal sulfides. They proposed that $\\mathsf{N O}_{2}^{-}$ intermediates were preferentially formed on Cubased phases followed by splitting over nearby Co-based phases; however, the role of ${}^{*}\\mathsf{H}$ during ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ was unclear and the effect of the electronic structure of alloyed catalysts on the adsorption of reaction intermediates lacked further discussions in the proposed mechanism14. In this study, inspired by the bifunctional nature of the Cu-NIRs, we prepared CuCo alloy nanosheets via a one-step electrodeposition route. The CuCo alloy could well mimic the behavior of the two catalytic centers in Cu-NIRs. The Co species could efficiently provide the electrons and generate the hydrogen protons to the nearby Cu species with high adsorption of ${\\mathsf{N O}}_{3}^{-}$ and its derivatives. The as-prepared CuCo nanosheet exhibited superior catalytic performances, as (1) the lowest $\\boldsymbol{\\mathsf{\\Pi}}\\mathfrak{\\Pi}$ of $290\\mathrm{mV}$ for ammonia production (at $0.4\\mathsf{V}$ vs. reversible hydrogen electrode (RHE), all electrode potentials mentioned below were provided with respect to RHE unless specially stated); (2) an ampere-level current density of $1035\\mathsf{m A c m}^{-2}$ with a $100\\%$ Faradaic efficiency for ${\\mathsf{N H}}_{3}$ generation at an overpotential of $890\\mathrm{mV}$ , and a corresponding $\\mathsf{Y i e l d}_{\\mathsf{N H}_{3}}$ of $4.8\\mathsf{m m o l c m^{-2}h^{-1}}$ ; (3) a wide potential window $(300\\mathsf{m V},$ , from $-0.1$ to $-0.4\\mathsf{V}$ for $\\mathsf{N H}_{3}$ generation with $590\\%$ Faradaic efficiency (FE), which is one of the most advanced catalysts for ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ so far. Electrochemical in situ Fourier transform infrared spectroscopy (FTIR) and in situ shell-isolated nanoparticle enhanced Raman spectroscopy (SHINERS) associated with density functional theory (DFT) calculations were conducted to clarify the pathways and mechanisms of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ , with the aim to contribute to subsequent catalyst optimization and scaling up. \n\n# Results \n\n# Preparation and characterization of CuCo bimetallic electrocatalysts \n\nCuCo bimetallic materials were synthesized by co-electrodeposition of Cu and Co on Ni foams’ surfaces (Fig. 1a and Method section). Ni foam is widely used as a supporting substrate for nanostructured electrocatalysts due to its smooth surface and good conductivity, benefiting the electrodeposition by an efficient electron transfer15–17. Meanwhile, Ni was proved as a relatively inert material for ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}^{18,19}$ , without affecting the CuCo catalysts’ performance. The $\\mathrm{Cu/Co}$ molar ratio was determined using an inductively coupled plasma-optical emission spectrometer (ICP-OES) (Supplementary Table S1). The catalyst with a $\\mathrm{Cu/Co}$ molar ratio of ca. 50/50 was named $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ and was considered as a reference in this study. The alloying of $\\mathtt{C u}$ and Co in $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ was confirmed by X-ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM). Indeed, in the diffractogram (Fig. 1b and Supplementary Fig. S1) shifts in the Cu (111) and Cu (200) diffraction peaks toward higher degrees were observed after the addition of Co to Cu, which were attributed to the shrinkage of the lattice spacing caused by the partial alloying of Co atom with a smaller diameter compared to Cu atom20. Furthermore, the lattice spacing of the Cu (111) plane contracted to $0.208\\mathrm{nm}$ after alloying Cu with Co (Fig. 1c), when it was $0.212\\mathsf{n m}$ for the Cu (111) plane for the pure Cu catalyst (Supplementary Fig. S2a)15. Scanning electron microscopy (SEM) was applied to examine the morphologies of Cu, Co and $\\mathsf{C u}_{\\mathrm{x}}\\mathrm{Co}_{\\mathrm{y}}$ catalysts and showed micro-pines structure for all the catalysts (Supplementary Fig. S3a–j). At the nanoscale level, small bump structures on the surface of the micro-pines were observed on pure Cu (Supplementary Fig. S3a, b). After the incorporation of Co, a nanosheet structure emerged on the micro-pine’s surface of the $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ catalyst (Fig. 1d and Supplementary Fig. S3e, f), very similar to the structure of pure Co (Supplementary Fig. S3i, j). The thickness of the $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ nanosheet was evaluated by atomic force microscopy (AFM) and was around $10\\mathsf{n m}$ (Fig. 1e). Besides, the EDS mapping analysis disclosed an even distribution of Cu and Co in $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (Fig. 1f). \n\nThe electronic properties of the $\\mathbf{Cu}_{50}\\mathbf{Co}_{50}$ nanosheet were explored by X-ray photoelectron spectroscopy (XPS). $\\mathsf{C u}^{2+}2p$ peaks were observed in the high-resolution Cu $2p$ spectra (Fig. 1g), and was due to the partial oxidation of the alloy’s surface exposed to air, and the same observation was made for Co (Fig. 1h). The decrease of the $\\mathtt{C u}2p$ binding energy, compared with pure $\\mathtt{C u}$ (Supplementary Fig. S4a) and the notable increase of the Co $2p$ binding energy, compared with pure Co (Supplementary Fig. S4b), revealed a redistribution of the electrons between Cu and Co after their alloying21, leading to the movement of the $d$ band towards the Fermi level22 comparing with the pure Cu catalyst. X-ray absorption spectroscopy (XAS) analysis was also performed to check the redistribution of electrons between Cu and Co. Extended X-ray absorption fine structure (XANES) spectra depicted a negative shift of the absorption edge position for the Cu K-edge after interacting with Co (indicated by the red arrow in the inset) (Supplementary Fig. S5), illustrating the electron density transfer from Co to ${\\mathsf{C}}{\\mathsf{u}}^{23}$ . In addition, according to the Bader charge analysis (Supplementary Fig. S6), compared with monometallic Cu and Co, a charge redistribution on CuCo(111) was observed, where the Cu center displayed a higher electrons density compared to the Co center (Supplementary Fig. $S7)^{24}$ . The correlation between electrons redistribution within Cu and Co and the adsorption energy of ${}^{*}\\mathsf{H}$ ${^*{\\mathsf{N O}}_{3}}$ and the $^{*}\\mathsf{N O}_{\\mathsf{x}}$ intermediates25 are discussed further in the mechanistic study section. \n\n# Electrochemical activity and kinetics of $\\mathsf{N O}_{3}\\mathrm{^-RR}$ \n\n$N O_{3}^{-}\\mathsf{R R}$ was first investigated by linear sweep voltammetry (LSV) at a low scan rate of $1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ on all the prepared electrocatalysts. The reduction of $\\mathsf{N O}_{\\mathsf{x}}$ species contributed mainly to the current density (solid curve), indicating a high catalytic activity toward $N O_{3}^{-}\\mathsf{R R}$ for all the catalysts (Fig. 2a). The substrate of Ni foam was inactive for $N O_{3}^{-}\\mathsf{R R}$ compared with the electrodeposited catalysts (Supplementary Figs. S8, S9). The overpotential $\\boldsymbol{\\mathsf{\\Pi}}_{\\mathsf{\\Pi}}$ at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ (denoted $\\eta_{\\mathrm{ounAcm}^{-2}}$ $\\boldsymbol\\upeta=\\boldsymbol E^{\\mathrm{o}}-\\boldsymbol E,$ where $\\boldsymbol{E}$ is the potential with a current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ , $\\begin{array}{r}{E^{\\mathrm{{o}}}=0.69\\:\\mathrm{V};}\\end{array}$ ), where $N O_{3}^{-}\\mathsf{R R}$ is under kinetic control, was used as a criterion to compare the catalysts’ activity. $\\mathbf{Cu}_{50}\\mathbf{Co}_{50}$ and Cu exhibited a lower energy barrier for ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ , with $\\eta_{\\mathrm{{olomAcm}^{-2}}}$ of 498 and $503\\mathsf{m V}$ respectively, compared to Co, that displayed a $\\eta_{\\mathrm{alomAcm}^{-2}}$ of $690\\mathrm{mV}$ In fact, two reduction current peaks (peak S1 and S2) were observed in the curves of $\\mathtt{C u}$ and $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ . At the initial stage of the reaction, Cu and $\\mathbf{Cu}_{50}\\mathbf{Co}_{50}$ seemed to display a similar behavior toward $N O_{3}^{-}\\mathrm{RR}$ suggesting the important role of $\\mathtt{C u}$ at this stage. According to previous studies26,27, the peak S1 near $_{0.08\\mathrm{~V~}}$ was assigned to $^{*}{\\mathsf{N O}}_{3}^{-}$ (adsorbed ${\\mathsf{N O}}_{3}^{-}$ ) reduction into $^{*}\\mathsf{N O}_{2}^{-}$ (1) following a 2-electrons transfer process, while the peak S2 was allocated to the $^{*}\\mathsf{N O}_{2}^{-}$ reduction into ${^*}\\mathsf{N}\\mathsf{H}_{3}$ (2) following a 6-electrons transfer process. In the peak S2 region, $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ displayed a positive potential shift of $67\\mathrm{mV}.$ , compared to Cu, suggesting a significant synergy between Co and Cu and a drop of the barrier energy of $^{*}\\mathsf{N O}_{2}^{-}$ reduction to ${^*}\\mathsf{N}\\mathsf{H}_{3}$ , as the applied potential increases. \n\n![](images/2e981a416dd3d1e31bef956bfac9aff5149b1b04395c39be76bfb95b94c137d5.jpg) \nig. 1 | Preparation strategy and characterization of catalysts. a Schematic from AFM images (e), and EDS mapping analysis (f) of $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ . XPS peaks spectra iagram of $\\mathtt{C u C o}$ alloy electrodeposition on nickel foam’s surface. b XRD spectra of of $\\operatorname{Cu}2p\\left(\\mathbf{g}\\right)$ and Co $2p$ (h) of $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ . $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ , Cu, and Co. HRTEM image (c), SEM image (d), linear topography profiles \n\n$$\n\\mathbf{\\nabla}^{*}\\mathsf{N O}_{3}^{-}+2\\mathbf{e}^{-}+\\mathsf{H}_{2}\\mathbf{O}\\to\\mathbf{\\nabla}^{*}\\mathsf{N O}_{2}^{-}+2\\mathbf{OH}^{-}\n$$ \n\n$$\n\\mathrm{^{*}N O_{2}^{-}}+6\\mathrm{e^{-}}+5\\mathrm{H_{2}O}\\rightarrow\\mathrm{^{*}N H_{3}}+70\\mathrm{H^{-}}\n$$ \n\nIn the aim to investigate the reaction routes for all the catalysts, the number of electrons transferred (n) during the ${\\mathsf{N O}}_{3}^{-}$ reduction reaction was estimated from the slope of the Koutecký–Levich (K–L) plots (Supplementary Fig. S10). For the Cu catalyst (Supplementary Fig. S11a), n was 2 at $-0.1\\upnu$ and a quasi-first-order reaction relationship between $j$ and the ${\\mathsf{N O}}_{3}^{-}$ concentration was obtained (Supplementary Fig. S12), validating the rate-determinate step (RDS) as the reduction route described by Eq. (1). The n value increased to 6 at $-0.25\\mathsf{V}$ validating the reduction route described in Eq. (2). In comparison, a direct 8-electrons transfer process was observed on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ in the potential region between the peaks S1 and S2 (Fig. 2b), revealing a strong alloying effect promoting simultaneously both routes. Though an 8-electrons transfer process also occurred on the pure Co catalyst at a far less negative potential of ca. $-0.45\\mathrm{v}$ (Supplementary Fig. S11b), i.e., at a higher barrier energy. \n\nIn the potential region of peak S1, the Tafel slopes derived from the $j{\\cdot}E$ curves (Fig. 2c), for $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ was $205.75\\mathrm{mV}$ decade−1, which was slightly lower than $\\mathtt{C u}$ $(232.43\\mathrm{mV}$ decades−1), indicating that the addition of Co could promote the electrons transfer over the catalyst/ electrolyte interface during $^{*}\\mathsf{N O}_{3}^{-}$ reduction to $^{*}\\mathsf{N O}_{2}^{-}$ . This result was supported by EIS data (Supplementary Fig. S13), demonstrating a smaller charge-transfer resistance on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ compared to $\\mathtt{C u}$ (3.51 vs. 3.81 Ω). The Co catalyst had minor electrocatalytic activity for ${\\mathsf{N O}}_{3}^{-}$ reduction at this relatively positive working potential, so its Tafel slop in this potential region was not determined. In the potential region of peak S2, the Tafel slope (Fig. 2d) of $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ $(148.95\\mathrm{mV}$ decades−1) was significantly lower than $\\mathtt{C u}$ $229.75\\mathrm{mV}$ decades−1); this was explained by an electron redistribution between Cu and Co over $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ and was emphasized in the characterization section. The Co catalyst displayed the lowest Tafel slope value of $94.24\\mathrm{{mV}}$ decades−1, but at a more negative potential, i.e., $95\\mathsf{m V}$ shift, than $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ . This latter result suggested that after crossing a high energy barrier, Co displayed better kinetics’ performances toward the $\\mathsf{N O}_{3}\\mathsf{^{-}R R}$ for ${\\mathsf{N H}}_{3}$ production compared to the Cu-based catalysts. Alloying Co to Cu implemented a faster electron transfer rate and improved kinetics’ performances toward the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}.$ In addition to being affected by the properties of the catalysts, the $\\mathsf{N O}_{3}\\mathsf{^{-}R R}$ was also diffusion-controlled (Fig. 2e). To further evaluate the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ activity of the catalysts under steady-state conditions, potentiostatic electrolytic reduction of ${\\mathsf{N O}}_{3}{}^{-}$ in a homemade H-type electrolytic cell (Supplementary Fig. S14) was carried out by electrodepositing the catalysts on Ni foams’ surfaces. A magnetic stirring rate of 1000 rpm was used to minimize the effect of diffusion and fresh electrolyte solution was constantly supplemented to maintain a constant ${\\mathsf{N O}}_{3}^{-}$ ion concentration. In these conditions, the current densities obtained on the $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ catalyst reached an Ampere level at $-0.2\\upnu$ vs. RHE (Fig. 2f). \n\n![](images/917d7e0ef8735acf323ed48781f9a0f8adc2e8657a6323b9f969f6fd18102657.jpg) \nFig. 2 | Electrochemical responses of $\\mathbf{Cu_{50}C o_{50}},$ , pure Cu, and pure Co catalysts. $\\mathbf{a}j\\mathbf{-}E$ curve $80\\%$ iR corrected) over $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ , pure $\\mathsf{C u}$ , and pure Co modified Ni foams (catalysts loading was $5\\mathsf{m g c m}^{-2}.$ ) in 1 M KOH solution containing $100\\mathrm{mM}$ ${\\mathsf{K N O}}_{3}$ (solid lines) or in the absence of ${\\mathsf{K N O}}_{3}$ (dotted line) at a scan rate of $1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ (the red dash line presenting the j of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ , the shading S1 and S2 presenting the peak around 0.2 to $_{0.05\\mathrm{v}}$ and 0.05 to $-0.15\\mathrm{v}$ , respectively). $\\mathbf{b}j\\mathbf{-}E$ curve $80\\%$ iR corrected) at 400 rpm and electron transfer numbers at different potentials calculated by the $\\mathsf{K}{\\mathsf{-L}}$ equation for $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ on RDE in 100 $\\mathsf{1M K N O}_{3}+\\mathsf{1M}\\mathsf{I}$ KOH \nelectrolyte at a scan rate of $10\\mathrm{mVs^{-1}}$ (catalysts loading was $0.25\\mathrm{mgcm}^{-2},$ . Tafel slopes in the potential range of peak S1 (c) S2 (d). $\\mathbf{e}j{\\cdot}E$ curves over $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ modified Ni foam in 1 M KOH solution containing $100\\mathrm{mM}\\mathrm{KNO}_{3}$ at different scan rates without agitation (solid line) and at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ with agitation (catalysts loading was $5\\mathsf{m g c m}^{-2}$ ). f Time-dependent current density curves over $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ , Cu, Co modified Ni foam at $-0.2\\ensuremath{\\mathrm{V}}$ with a magnetic stirring speed of 1000 rpm (catalysts loading was $5\\mathsf{m g c m}^{-2},$ . \n\n${\\mathsf{N H}}_{3}$ and $\\mathsf{N O}_{2}^{-}$ were quantitatively detected by the Nessler Reagent method and ion chromatography, respectively (Supplementary Fig. S15)28,29. The gas products were analyzed during the reaction by gas chromatography and online electrochemical mass spectrometry (OEMS)30. There was no $\\mathsf{N}_{2}$ production detected and the amount of the stripped ${\\mathsf{N H}}_{3}$ in this work was negligible. (Supplementary Fig. S16) In order to figure out the effect of Co content on the $\\mathsf{N O}_{3}\\mathsf{^{-}R R}$ activity, CuCo bimetallic catalysts with different $\\mathrm{Cu/Co}$ ratios were prepared, i.e., $\\mathrm{Cu}_{65}\\mathrm{Co}_{35}$ and $\\mathsf{C u}_{15}\\mathsf{C o}_{85}$ . As shown in Fig. 3a, when a potential of $_{0\\vee}$ was applied, the Faraday efficiency of ${\\sf N H}_{3}\\left({\\sf F E}_{{\\sf N H}_{3}}\\right)$ and $\\mathsf{N O}_{2}^{-}(\\mathsf{F E}_{\\mathsf{N O}_{2}^{-}})$ on pure Cu were $32\\%$ and $60\\%$ , respectively. The corresponding molar ratio of $\\mathsf{N O}_{2}^{-}$ to ${\\mathsf{N H}}_{3}$ was seven times higher (Fig. 3c), suggesting an accumulation of ${\\mathsf{N O}}_{2}^{-}$ due to the low kinetic of $^{*}\\mathsf{N O}_{2}^{-}$ hydrogenation to ${^*}\\mathsf{N}\\mathsf{H}_{3}$ on the Cu surface. With the addition of Co to Cu, both the $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ and the geometrically normalized current density of ${\\mathsf{N H}}_{3}$ production $(j_{\\mathrm{NH_{3}}})$ increased significantly (Fig. 3a, b). A volcano shape was observed and the highest $j_{N H_{3}}$ was obtained on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (i.e., $347\\mathrm{mAcm}^{-2}j_{\\mathrm{NH_{3}}}$ and $88\\%\\mathrm{FE_{NH_{3}})}$ , and was ten times higher than monometallic Cu (i.e., $34\\mathsf{m A}\\mathsf{c m}^{-2}$ and $32\\%\\mathsf{F E}_{\\mathsf{N H}_{3}})$ , and nearly 17 times higher than monometallic Co catalyst (i.e., $2\\mathrm{i}\\mathsf{m}\\mathsf{A}\\mathsf{c m}^{-2}$ and $84\\%\\mathsf{F E}_{\\mathsf{N H}_{3}}.$ . Furthermore, the molar ratio of ${\\mathsf{N O}}_{2}^{-}$ to $\\mathsf{N H}_{3}$ exhibited a dramatic drop from 7 to 0.6 as the Co content was raised from 0 to $100\\%$ (Fig. 3c). This observation suggested that the incorporation of Co enhanced further the $^{*}\\mathsf{N O}_{2}^{-}$ hydrogenation into $\\mathsf{N H}_{3}$ . Moreover, when the ratio of Co was increased by over $50\\%$ , the $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ was remained constant, but the $j_{N H_{3}}$ declined dramatically, indicating that a moderate $\\mathrm{Cu/Co}$ ratio was important to maintain high catalytic performance for ${\\mathsf{N H}}_{3}$ production. The electrochemically active surface area (ECSA) was also measured (Supplementary Figs. S17f, S18b), and all the catalysts had comparable ECSA. The maximum ECSA normalized current density for ${\\mathsf{N H}}_{3}$ production $(j_{\\mathrm{NH_{3}(E C S A)}})$ was obtained on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ (Supplementary Fig. S19), indicating that this catalyst had the highest intrinsic activity for $\\mathsf{N H}_{3}$ production. \n\nTo clarify the possible $^{14}\\mathsf{N}$ pollution, the electrolysis in the electrolyte free of ${\\mathsf{N O}}_{3}^{-}$ ions was performed and little ${\\mathsf{N H}}_{3}$ was produced (Supplementary Fig. S20). $j_{\\mathrm{NH}_{3}}$ in the solution with ${\\mathsf{N O}}_{3}^{-}$ ions was over 150-fold higher than that in the electrolyte free of ${\\mathsf{N O}}_{3}{}^{-}$ . The content of $^{14}\\mathsf{N}\\mathsf{H}_{4}^{+}$ was also analyzed by $\\mathsf{\\Pi}^{\\mathrm{1}}\\mathsf{H}$ NMR test29,31 and was ca. $4.62\\mathrm{mmolcm^{-2}h^{-1}}.$ . The obtained results were close to the one from the spectrophotometric analysis $(4.75\\mathrm{mmol}\\mathrm{cm}^{-2}\\mathsf{h}^{-1})$ (Supplementary \n\n![](images/b4ed1bc9679ad93f19d8de685373beeecf947e44535b921d841ec52e18738892.jpg) \nFig. 3 | Electrochemical performance of catalysts. $\\mathrm{FE}_{\\mathrm{NH_{3}}}$ and $\\mathsf{F E}_{\\mathsf{N O}_{2}^{-}}$ of $N O_{3}^{-}\\mathsf{R R}$ (a), bias-current density and products yield for $\\mathsf{N H}_{3}$ (b), and the ratio of $\\mathsf{N O}_{2}^{-}$ to ${\\mathsf{N H}}_{3}$ generated (c) for different $\\mathrm{Cu/Co}$ ratio at $_{0\\vee}$ in $100\\mathsf{m M K N O}_{3}+1\\mathsf{M}$ KOH electrolyte (catalysts loading was $5\\mathsf{m g c m}^{-2},$ ). $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ (d) and $\\mathsf{N H}_{3}$ product yield (e) at different electrode potentials on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ , pure Cu and pure Co catalysts modified Ni foam (catalysts loading was $5\\mathsf{m g c m}^{-2}.$ ). Comparison of the electrocatalytic ${\\mathsf{N O}}_{3}{\\cdot}$ RR performances of $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ modified Ni foam with other extensively reported \nelectrocatalysts (f). $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ and $\\mathsf{Y i e l d}_{\\mathsf{m a s s\\mathrm{-}N H_{3}}}$ on $\\mathrm{\\mathsf{Cu}}_{50}\\mathrm{Co}_{50}/\\mathrm{Ni}$ foam under the applied potential of $-0.2\\mathrm{\\bar{V}}$ during 10 periods of 1 h electrocatalytic ${\\mathsf{N O}}_{3}{\\mathsf{R R}}$ (g) (catalysts loading was $5\\mathsf{m g c m}^{-2},$ . The time-dependent concentration of $\\mathsf{N O}_{3}^{-}$ , $\\mathsf{N O}_{2}^{-}$ and ${\\mathsf{N H}}_{3}$ and corresponding FE over $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ modified Ni foam at $-0.1\\upnu$ (h) (catalysts loading was $5\\mathsf{m g c m}^{-2},$ . Error bars represent the standard deviations calculated from three independent measurements. \n\nFig. S21d), and confirmed the reliability of the quantification methods used in this work. The typical two peaks of $^{15}\\mathsf{N H}_{4}^{\\mathrm{~+~}}$ after the electrolysis of $^{15}{\\mathsf{N O}}_{3}^{-}$ also suggested that the ${\\mathsf{N H}}_{3}$ product indeed came from the electrocatalytic reduction of ${\\mathsf{N O}}_{3}^{-}$ (Supplementary Fig. S21e). \n\nIt is known that the applied potential influences the products’ selectivity13, so we investigated the effect of the applied potential toward the $N O_{3}^{-}\\mathsf{R R}$ (Fig. 3d, e and Supplementary Fig. S22). The $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ was about $51\\%$ at a $\\boldsymbol{\\mathsf{\\Pi}}\\mathfrak{\\Pi}$ of $290\\mathrm{mV}$ (at 0.4 V) on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ . The $\\boldsymbol{\\mathsf{\\Pi}}\\mathfrak{\\Pi}$ was comparatively much lower than that of the state-of-the-art catalysts reported in the literature (Fig. 3f and Supplementary Table S2). When the $\\boldsymbol{\\mathsf{\\Pi}}_{\\mathsf{\\Pi}}$ reached $590\\mathrm{mV}$ (at 0.1 V), the ${\\mathsf{F E}}_{\\mathsf{N H}_{3}}$ got about $65\\%$ on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ (Fig. 3d and Supplementary Fig. S23). In comparison, the $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ was around $21\\%$ on Cu at 0.1 V (Fig. 3d), with $\\mathsf{N O}_{2}^{-}$ as the main product. As the electrode potential shifted negatively, the intermediate $\\mathsf{N O}_{2}^{-}$ was rapidly reduced (Supplementary Fig. S23). At $-0.2\\upnu$ , the $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ achieved $100\\pm1\\%$ , and $j_{\\mathsf{N H}_{3}}$ reached $1035\\mathsf{m A c m}^{-2}$ (Supplementary Fig. S24b), corresponding to an ${\\mathsf{N H}}_{3}$ production rate of $4.8\\mathsf{m m o l c m^{-2}h^{-1}}$ that is about two and eight times higher than the ones obtained on monometallic Co and $\\mathtt{C u}$ (Fig. 3e and Supplementary Fig. S25), respectively. Based on the charge consumed during the CuCo electrodeposition on the Ni foam substrate, the mass activity of ${\\mathsf{N H}}_{3}$ yield $(\\mathsf{Y i e l d}_{\\mathsf{m a s s-N H}_{3}}.$ ) on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ was estimated roughly to \n\n960 mmol $\\ensuremath{\\mathbf{g}}_{\\mathrm{cat}}^{}{}^{-1}\\ensuremath{\\mathsf{h}}^{-1}$ at $0.2\\mathrm{V}$ . The obtained ${\\tt Y i e l d}_{\\tt m a s s-N H_{3}}$ was slightly underestimated since hydrogen evolution was observed during CuCo electrodeposition. It should be noted that the production of ${\\mathsf{N H}}_{3}$ from electrocatalytic ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ is currently at a laboratory scale. More followup pilot tests and scale-up work are required to meet the industrial demands. Based on the preliminary calculations, we consider that our work inspired by the bifunctional nature of nitrite reductase, provides a new expectation and shows a great prospect, and after further development could compete with the well-established Haber–Bosch process12,32 which currently shows a ${\\tt Y i e l d}_{\\tt m a s s-N H_{3}}$ of ca. $200\\mathrm{mmol(g_{cat}}^{-1}\\mathsf{h}^{-1}$ at industrial scale. The potential window for ${\\mathsf{F E}}_{\\mathsf{N H}_{3}}$ above $90\\%$ was wide and ranged from $-0.1$ to $-0.4\\upnu$ (Fig. 3d). Ten cycles of electrolysis at constant potential were performed to check the stability of $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (Fig. 3g) and the results displayed a stable $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ exceeding $90\\%$ over the cycles. According to the SEM analysis, the decay of the yield for ${\\mathsf{N H}}_{3}$ would be due to the nanosheet agglomeration after the consecutive recycling tests (Supplementary Fig. S26a, b). Furthermore, XRD (Supplementary Fig. S26c) and XPS (Supplementary Fig. S26d, e) analysis was also performed on the samples after the consecutive recycling tests, and the results demonstrated negligible changes in the chemical compositions and oxidation states, which confirmed the excellent stability of the catalyst. \n\n![](images/91b780c7cfcbe021ed29486b6d26160b509e142397d2e25aa86e2196248826a3.jpg) \nFig. 4 | Electrochemical in situ FTIR spectra. Electrochemical thin-layer in situ FTIR spectra of $N O_{3}^{-}\\mathsf{R R}$ on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (a), Cu (b), and Co (c) in $100\\mathrm{{mM}}$ ${\\mathsf{K N O}}_{3}+1{\\mathsf{M}}$ KOH. ${\\bf d}\\frac{\\mathbb{I}_{\\mathrm{NO}_{2}^{-}}}{\\mathbb{I}_{\\mathrm{NH}_{2}\\mathrm{OH}}+\\mathbb{I}_{\\mathrm{NO}_{2}^{-}}}$ ratio at different electrode potentials. ATR-FTIR spectra on $\\mathbf{Cu}_{50}\\mathbf{Co}_{50}$ (e), Cu (f), and Co (g) in 1 M KOH. \n\nThe concentration of ${\\mathsf{N O}}_{3}^{-}$ in real wastewater can vary from $0.88\\mathrm{mmolL^{-1}}$ to $1.95\\mathrm{molL}^{-1}:$ 33. Therefore, ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ was performed at a wide range of ${\\mathsf{N O}}_{3}^{-}$ concentrations $\\mathbf{(1-100mmolL^{-1}},$ ). The $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ was maintained above $95\\%$ in the whole range of ${\\mathsf{N O}}_{3}^{-}$ concentrations (Supplementary Fig. S27) at $-0.1{\\ \\mathsf{V}}.$ . The $\\mathsf{N O}_{3}\\mathsf{^{-}R R}$ in neutral conditions was carried out on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ catalysts at $-0.2\\ensuremath{\\mathsf{V}}$ in an electrolyte solution of $0.1\\mathsf{M}\\mathsf{K N O}_{3}+0.5\\mathsf{M}\\mathsf{K}_{2}\\mathsf{S O}_{4}$ . The current density of $N O_{3}^{-}\\mathsf{R R}$ on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ in a neutral condition was higher than the one on monometallic Cu and Co, and the $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ over $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ was more than $90\\%$ (Supplementary Fig. S28). These experiments demonstrated the excellent property of $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ toward ${\\mathsf{N O}}_{3}^{-}$ recovery in various environmental wastewater systems. In batch conditions with an initial nitrate’s concentration of $100\\mathrm{mmolL}^{-1}$ ( $\\mathsf{\\cdot}a.6200\\mathsf{p p m})$ at a reduction potential of $_{-0.1\\vee}$ and after $10\\mathsf{h}$ , the nitrate’s removal efficiency reached $99.5\\%$ , with a $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ of $96\\%$ (Fig. 3h). The remaining ${\\mathsf{N O}}_{3}{}^{-}$ in the solution was 31 ppm which was much lower than the limitations fixed by the World Health Organization for drinking water, (i.e., $50\\ \\mathsf{p p m})^{34}$ . Several processes can be then considered for further extracting $\\mathsf{N H}_{3}$ , such as air stripping, ion exchange, struvite precipitation, etc.35. \n\nElectrochemical in situ FTIR, SHINERS and DFT calculations were conducted to elucidate the reaction mechanism as well as the origin of the different activities observed between the catalysts. \n\n# Electrochemical in situ FTIR analysis of $\\mathsf{N O}_{3}^{-}\\mathsf{R R}$ \n\nThe electrochemical thin-layer in situ FTIR can track intermediates in solution within the thin-layer (thickness around $10\\upmu\\mathrm{m})$ between the electrode and IR window and species adsorbed on the electrode surface36. A reference spectrum $(\\mathsf{R}_{\\mathsf{R e f}})$ at reference potential $(E_{\\mathrm{R}},0.4\\vee)$ \n\nwas firstly acquired, and then the potential was stepped to studied potentials $(E_{\\mathsf{S}})$ and to collect working spectra $(\\mathsf{R}_{\\mathsf{S}})$ . The resulting spectra were represented as relative changes in the reflectance: $\\Delta\\mathsf{R}/\\$ ${\\bf R}=({\\sf R}_{\\sf S}{\\cdot}{\\sf R}_{\\sf r e f})/{\\sf R}_{\\sf R e f}.$ As a result, the downward band in the resulting spectra indicated the formation of ${\\mathsf{N O}}_{3}^{-}$ intermediates at $E_{\\mathrm{S}}$ while the upward band referred to the consumption of ${\\mathsf{N O}}_{3}^{-}$ . The FTIR peaks observed on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}.$ Cu, and Co are compiled in Supplementary Table S3. As illustrated in Fig. 4, in the potential range from 0.4 to $-0.2\\upnu$ , the absorption bands were assigned to intermediates present in the electrolyte, since the wavenumbers of all the absorption bands were independent of the working potential37. In Fig. 4a, five obvious absorption bands appeared in the infrared spectra of $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ viz. (1) At the working potential of $0.2\\mathsf{V}$ , close to the onset potential of the LSV curve, the upward absorption bands at 1392 and $1354\\mathrm{cm}^{-1}$ were ascribed respectively to N-O symmetric and asymmetric stretching vibration of ${\\mathsf{N O}}_{3}{}^{-38}$ , indicating consumption of ${\\mathsf{N O}}_{3}^{-}$ species in the thin layer; (2) at the same time, the downward band at $1236\\mathrm{cm}^{-1}$ appeared and was attributed to N-O antisymmetric stretching vibration of ${\\mathsf{N O}}_{2}{}^{-39}$ , indicating $\\mathsf{N O}_{2}^{-}$ formation from ${\\mathsf{N O}}_{3}{}^{-}$ reduction; (3) with potential negatively moving to 0.1 V, another intermediate observed around 11 $10\\mathsf{c m}^{-1}$ was ascribed to -N-O- stretching vibration of hydroxylamine $(\\mathsf{N H}_{2}\\mathsf{O H})^{39,40}$ , which was a key intermediate for $\\mathsf{N H}_{3}$ formation; (4) The upward band around $1638\\mathsf{c m}^{-1}$ was attributed to water electrolysis responsible of hydrogen generation involved in the hydrodeoxidation of ${\\mathsf{N O}}_{3}^{-}$ in the solution of thin-layer41. \n\nThe FTIR spectra collected on $\\mathtt{C u}$ (Fig. 4b) were very similar to the $\\mathbf{Cu}_{50}\\mathbf{Co}_{50}$ catalyst’s ones, indicating that the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ behaviors were similar for both catalysts. However, the ${\\mathsf{N O}}_{3}^{-}$ consumption on $\\mathtt{C u}$ at a potential of 0.1 V was $100\\mathrm{mV}$ more negative than the one obtained on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ , indicating a better kinetic with the latter one. In addition, with the negative shift of the working potential, the band intensity of $\\mathsf{N O}_{2}^{-}$ relative to the sum intensity of $\\mathsf{N O}_{2}^{-}$ and ${\\sf N H}_{2}{\\sf O H}$ production (i.e., $\\frac{\\mathbf{I}_{\\mathrm{NO_{2}^{-}}}}{\\mathbf{I}_{\\mathrm{NH_{2}O H}}+\\mathbf{I}_{\\mathrm{NO_{2}^{-}}}}\\Big)$ on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ dropped down sharply, while the $\\frac{\\mathsf{I}_{\\mathsf{N O}_{2}^{-}}}{\\mathsf{I}_{\\mathsf{N H}_{2}\\mathrm{OH}}+\\mathsf{I}_{\\mathsf{N O}_{2}^{-}}}$ ratio was almost independent of the potential on $\\mathtt{C u}$ (Fig. 4d). The two phenomena, i.e., the appearance of ${\\mathsf{N H}}_{2}{\\mathsf{O H}}$ after the formation of ${\\mathsf{N O}}_{2}^{-}$ and the increase of $\\mathsf{N H}_{2}\\mathsf{O H}$ at the expense of the consumption of ${\\mathsf{N O}}_{2}^{-}$ , suggested that ${}^{*}\\mathsf{N H}_{2}\\mathsf{O H}$ was obtained by the deep hydrogenation of $^{*}\\mathsf{N O}_{2}^{}{}^{42}$ . The $\\frac{\\mathsf{I}_{\\mathsf{N O}_{2}^{-}}}{\\mathsf{I}_{\\mathsf{N H}_{2}\\mathsf{O H}}+\\mathsf{I}_{\\mathsf{N O}_{2}^{-}}}$ ratio on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ was much lower than the one on Cu catalyst, demonstrating that alloying $\\mathtt{C u}$ with Co could deeply enhance the hydrogenation of ${^*{\\mathsf{N O}}}_{2}$ to the final product ${\\mathsf{N H}}_{3}$ on $\\mathrm{Cu/Co}$ alloy catalysts. Thereby we speculated that Co sites were responsible for the variation of the INH ONHO+2\u0001 INO\u0001 ratio, owing to their excellent protons’ adsorption $({}^{*}\\mathsf{H})$ capacity, as it will be demonstrated in the next section, promoting the hydrodeoxidation of ${\\bf\\ddot{\\tau}}_{\\bf N O}_{2}$ to ${}^{*}\\mathsf{N H}_{2}\\mathsf{O H}$ according to Eqs. (3) and (4):43 \n\n![](images/8ff583bf1099a5e16dceec35fb489e078ec380912bf6477211afc191fde50a3e.jpg) \nFig. 5 | Electrochemical SHINERS spectra of $\\mathbf{NO_{3}}^{-}\\mathbf{RR}.$ SHINERS spectra between $230{\\mathrm{-}}750{\\mathrm{cm}}^{-1}$ on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (a), Cu (b), and Co (c). SHINERS spectra between $750{-}1700\\mathrm{cm}^{-1}$ on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (d) in $100\\mathrm{{mM}}$ $\\mathsf{K N O}_{3}+\\mathsf{10m M}$ KOH during cathodic polarization from 0.7 to $-0.1\\mathsf{V}.$ \n\n$$\n{}^{*}\\mathsf{N O}_{2}+2^{*}\\mathsf{H}\\to{}^{*}\\mathsf{N O}+\\mathsf{H}_{2}\\mathsf{O}\n$$ \n\n$$\n{}^{*}\\mathsf{N O}+3^{*}\\mathsf{H}\\to{}^{*}\\mathsf{N H}_{2}\\mathsf{O H}\n$$ \n\nOn pure Co (Fig. 4c), no spectra bands of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ were detected until the working potential negatively shifted to $\\displaystyle{0\\vee}$ . The absence of $\\mathsf{N O}_{2}^{-}$ on the Co catalyst suggested a low ${\\mathsf{N O}}_{2}^{-}$ accumulation in the thin layer solution, corroborating very well first the results obtained from the $\\mathsf{K}{\\mathsf{-L}}$ equation where the Co catalyst was more inclined to perform continuous hydrogenation of ${\\mathsf{N O}}_{3}^{-}$ to ${\\mathsf{N H}}_{3}$ via an 8-electrons transfer and second the lower Tafel slope in the Peak S2 region data. \n\nIn comparison with thin-layer in situ FTIR, attenuated total reflection in situ FTIR analysis (ATR-FTIR) is more sensitive to the signal of adsorbed species on catalysts’ surfaces44. Two weak vibration bands of adsorbed NO in two different adsorption modes (“bridge” and “on top”) were detected at 1557 and $1639\\mathrm{cm}^{-1}$ on the $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ catalyst (Supplementary Fig. S29a)38,45. Interestingly, a downward band center at $2109\\mathrm{cm}^{-1}$ at $0.5\\ensuremath{\\mathrm{V}}$ was observed in ${\\mathsf{N O}}_{3}{\\mathrm{\\cdot}}$ –free electrolyte on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (Fig. 4e), and the band center was negatively shifted to $2085\\mathsf{c m}^{-1}$ at $-0.4\\mathsf V$ , yielding a Stark turn rate of $26.7\\mathsf{c m}^{-1}\\mathsf{V}^{-1}$ . These IR features could be attributed to adsorbed ${^*}\\mathsf{H}$ on the $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ surface, and indicated also the enhancement of ${}^{*}\\mathsf{H}$ adsorbed on the $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ surface at a higher η, which is consistent with the reported studies46,47. The fact that $^*\\mathsf{H}$ was observed on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ and Co (around $2110\\mathsf{c m}^{-1}.$ ) (Fig. 4e, g and Supplementary Fig. S30c) while being absent on Cu (Fig. 4f and Supplementary Fig. S30b), indicated that $^{*}\\mathsf{H}$ on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ was mainly attributed to water dissociation on Co sites. When the potential negatively shifted, the intensity of $\\mathsf{C o-H}$ gradually raised, demonstrating that more $^{*}\\mathsf{H}$ were generated which in turn enhanced the hydrodeoxidation reaction and gave a lower INH2 IONHO+2\u0001 INO\u0001 ratio value. The wavenumber attributed to $^*\\mathsf{H}$ on Co was slightly higher than the one on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ indicating a stronger affinity of $^*\\mathsf{H}$ for pure Co catalyst. In the presence of ${\\mathsf{N O}}_{3}^{-}$ , Co-H was still present in the spectra of pure Co (Supplementary Fig. S30c), while it was vanished in the spectra of $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (Supplementary Fig. S30a). This could be explained by the fact that $^*\\mathsf{H}$ could adsorb quickly on Co sites inhibiting the adsorption of $\\mathsf{N O}_{\\mathsf{x},}$ then the adsorbed hydrogen can react with the equivalent amount of $^{*}\\mathsf{N O}_{\\mathsf{x}}$ on nearby Cu sites giving a high reaction kinetics. In the case of monometallic Co, the active sites are majorly occupied by $^*\\mathsf{H}$ species preventing the adsorption of $\\mathsf{N O}_{\\mathsf{x}}$ onto the catalyst’s surface, leading to weak activity. The presence of active hydrogen $(\\mathsf{H}^{*})$ in the reaction process was also verified by electron paramagnetic resonance (EPR) analysis on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ catalyst (Supplementary Fig. S31) using 5,5-dimethyl-1-pyrroline $N\\cdot$ oxide (DMPO) as a spin trap48. The intensity of the EPR signal of the DMPO-H adduct on the $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ catalyst decreased when nitrate was added into the electrolyte, indicating the consumption of active hydrogen during ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}.$ These results were consistent with the ATR-FTIR analysis. Based on the coupling of thin-layer in situ FTIR and ATR-FTIR analysis, therefore, we proposed the following pathway for the $N O_{3}^{-}\\mathrm{RR}$ on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ : ${\\tt N O}_{3}^{-}\\rightarrow{^\\ast\\tt N O}_{3}\\rightarrow{^\\ast\\tt N O}_{2}\\rightarrow{^\\ast\\tt N H}_{2}{\\tt O H}\\rightarrow{^\\ast\\tt N H}_{3},$ where $^*\\mathsf{H}$ on Co sites can promote the deep hydrodeoxidation of $\\mathsf{N O}_{2}^{-}$ to $\\mathsf{N H}_{2}\\mathsf{O H}$ . \n\n# SHINERS analysis of $\\mathsf{N O}_{3}\\mathrm{^-RR}$ \n\nThe reaction intermediates provided by electrochemical in situ FTIR spectra were still insufficient to figure out the overall roadmap of $N O_{3}^{-}\\mathsf{R R}$ to $\\mathsf{N H}_{3}$ , in this aim, SHINERS spectra of the catalysts were collected to probe the catalysts’ surface during the reaction. Supplementary Table S4 compiled the Raman scattering peaks observed during ${\\mathsf{N O}}_{3}{}^{-}$ reduction on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ Cu, and Co, which were not detected on $\\mathsf{A u@S i O}_{2}$ (Supplementary Fig. S32). The wavenumber below $750\\mathsf{c m}^{-1}$ corresponds mainly to the chemical properties of the catalyst’s surface43. SHINERS spectra of $\\mathtt{C u}_{50}\\mathtt{C o}_{50},$ Cu, and Co, in this section, were summarized and shown in Fig. 5. At $0.6{\\:}\\mathsf{V}_{\\cdot}$ , a characteristic band at $625\\mathrm{cm^{-1}}$ associated with $\\mathrm{Cu}_{2}\\mathrm{O}^{49}$ was observed on Cu and $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ (Fig. 5a, b), indicating partial oxidation of the catalysts surface due to air exposition before ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ ; these results were consistent with the XPS data. As the working potential decreased to $0.3{\\tt V}_{\\mathrm{.}}$ , the band intensity of $\\mathtt{C u}_{2}0$ gradually shrank, and a peak at $714\\thinspace{\\mathrm{cm}}^{-1}$ emerged in replacement and was associated with the bending mode of free $\\mathrm{Cu-OH_{ad}}^{50,51}$ , indicating a gradual reduction of $\\mathtt{C u}$ before $\\mathsf{N O}_{3}\\mathsf{^{-}R R}$ started to occur at $0.2\\mathrm{V}$ . Besides, the band at $431\\mathrm{cm}^{-1}$ can be assigned to $\\mathsf{C u}{\\cdot}\\mathsf{O}_{\\mathsf{x}}$ due to the adsorption of oxynitride on Cu surface51, and the band’s intensity increased as the potential moved negatively. For Co (Fig. 5c), a band at $568\\mathsf{c m}^{-1}$ was also observed, associated with the formation of ${\\bf{C o-O_{x}}}$ caused by the same oxynitride species adsorbed on the catalyst’s surface52. \n\n![](images/852f20bda8b552414b1b61e2e322c4c4ecc5a5e525efcbe5830fbd5cbe582897.jpg) \nFig. 6 | DFT calculations of ${\\bf N O}_{3}{\\bf\\ddot{R R}}$ and HER on Cu(111), Co(111), and CuCo(111). Reaction-free energies for different intermediates of ${\\bf N O}_{3}{\\bf\\ddot{R R}}$ (a) and HER (b) at $-0.2\\mathsf{V}v$ s. RHE on CuCo(111), pure Cu(111), and pure Co(111) surface, respectively. \n\nIn addition, the signals of ${\\mathsf{N O}}_{3}^{-}$ and its reduced intermediates adsorbed on the catalysts’ surface were observed in the spectra between 750 and $1700\\mathsf{c m}^{-1}$ . As the potential decreased from 0.7 to $-0.1\\mathsf{V}_{\\rho}$ , several peaks appeared in sequences on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ (Fig. 5d) viz. (1) At open circuit potential (OCP) and $0.7\\mathrm{V}$ , the only obvious peak viewed at around $1049\\mathrm{cm}^{-1}$ was attributed to the symmetric ${\\mathsf{N O}}_{3}^{-}$ stretching from solution ${\\mathsf{N O}}_{3}^{-}$ species53. (2) When the potential was decreased to $0.4\\mathsf{V}.$ the ${\\mathsf{N O}}_{3}^{-}$ species in the solution started to adsorb on the surface of $\\mathbf{Cu}_{50}\\mathbf{Co}_{50}$ since four peaks appeared in three different forms as NO stretching vibration from the unidentate nitrate near $998\\mathrm{cm}^{-1}.$ , symmetric and antisymmetric stretching vibration of the $\\mathsf{N O}_{2}$ group from the chelated nitro configuration around 1125 and $1254\\mathrm{cm}^{-154}$ , and the $N=O$ stretching vibration of the bridged nitro group closed to $1439\\mathrm{cm}^{-1}.$ , respectively55. (3) As the working potential shifted negatively further to $_{0.2\\mathrm{v}}$ , the symmetric ${\\mathsf{N O}}_{3}^{-}$ stretch of $^{*}\\mathsf{N O}_{3}^{-}$ appeared around $1028\\mathsf{c m}^{-1}$ 56,57 and symmetric bending vibrations of the HNH near 1315 and $1374\\mathrm{cm}^{-1}$ were apparent;55,57 $N=O$ stretch of ${\\mathsf{H N O}}^{56}$ was visible around $1540\\mathsf{c m}^{-1}$ . (4) When the potential negatively shifted further to $0.1\\mathrm{V}_{\\cdot}$ , the HNO peak near $1540\\mathsf{c m}^{-1}$ disappeared quickly; meanwhile, the antisymmetric bending vibration of the HNH of ${\\mathsf{N H}}_{3}$ at $1591\\mathrm{cm}^{-1}$ came out58, which indicated an efficient formation of ${\\mathsf{N H}}_{3}$ from HNO hydrodeoxidation. \n\nThe SHINERS spectra on Cu and Co catalysts (Supplementary Fig. S33a, b) were similar to the one of $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ , but a new peak close to $800\\mathsf{c m}^{-1}$ related to the bending vibration of ${\\mathsf{N O}}_{2}^{-}$ group was only observed on Cu (Supplementary Fig. $S33\\mathsf{a})^{26}$ . This could be due to the accumulation of $\\mathsf{N O}_{2}^{-}$ species near by the Cu surface due to its poor ability for deep ${\\mathsf{N O}}_{2}^{-}$ hydrodeoxidation properties. The intensity of $\\nu_{\\mathsf{s}(\\mathsf{N}O_{3}^{-})}$ from ${\\mathsf{N O}}_{3}^{-}$ species in solution on Co at low overpotential was similar to the one on $\\mathtt{C u}_{50}\\mathtt{C o}_{50}$ and $\\mathtt{C u}$ , however, the band’s intensities of all the intermediates formed on Co were very weak (Supplementary Fig. S33b), meaning that a low amount of $^{*}\\mathsf{N O}_{3}^{-}$ species and its derivates were adsorbed on the Co surface. It can be rationally speculated that the affinity of $^{*}\\mathsf{H}$ species to the Co surface was such strong that the active sites on the Co catalyst were majorly occupied by $^*\\mathsf{H}$ species leading to low coverage of $^{*}\\mathsf{N O}_{3}^{-}$ species, bringing a $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ close to $85\\%$ (Fig. 3b) at the expense of a low current density of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ of $25.4\\mathsf{m A c m}^{-2}$ (Supplementary Fig. S24a) at $_{0\\vee}$ . Similarly, $^*\\mathsf{H}$ species affinity for Cu surface was so weak that most active sites were occupied by $^{*}\\mathsf{N O}_{3}^{-}$ species, leading to a relatively high current density up to \n\n$104.8\\mathsf{m A c m}^{-2}$ (Supplementary Fig. S24a) and yet an unsatisfactory $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ of $32\\%$ (Fig. 3b). Therefore only if a balanced coverage of $^{*}\\mathsf{H}$ and ${^*{\\mathsf{N O}}_{3}}$ species is achieved, a satisfactory $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ and $j$ can be simultaneously obtained, which is the case with $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ where $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ and $j$ were $88\\%394.6\\mathsf{m V}$ respectively. \n\nWith combined electrochemical in situ FTIR and SHINERS spectroscopic analysis, the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ pathway on Cu, Co and CuCo was proposed as a series of deoxygenation reactions according to the following path, $\\mathsf{N O}_{3}^{-}\\to^{*}\\mathsf{N O}_{3}\\to^{*}\\mathsf{N O}_{2}\\to^{*}\\mathsf{N O}$ , accompanied by a series of hydrogenation reactions: $\\mathrm{^{*}N O}\\rightarrow\\mathrm{^{*}N O H}\\rightarrow\\mathrm{^{*}N H_{2}O H}\\rightarrow\\mathrm{^{*}N H_{3}}\\rightarrow\\mathrm{NH_{3}}$ . \n\n# DFT calculations \n\nBased on all the aforementioned observations and to shed light on the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ mechanism on Cu, Co, and CuCo at the atomic level, the density functional theory (DFT) calculations were conducted and the Gibbs free energies $(\\Delta\\mathsf{G})$ of ${^*{\\mathsf{N O}}_{3}}$ species and their derivates on $\\mathtt{C u(111)}$ , ${\\mathrm{Co}}(111)$ and CuCo(111) surface were presented in Fig. 6a. \n\nIn terms of thermodynamics, the rate-determining step (RDS) on $\\mathtt{C u(111)}$ , Co(111) and CuCo(111) was the initial ${^*}\\mathsf{N O}_{3}$ adsorption step and lower energy was required on CuCo(111) (0.17 eV), compared to Cu(111) (0.61 eV) and Co(111) (0.34 eV), indicating stronger adsorption of ${\\mathsf{N O}}_{3}^{-}$ species on $\\mathsf{C u C o}(\\mathsf{111})^{15,59}$ . Interestingly, the $\\Delta G$ of the initial ${^*}\\mathsf{N O}_{3}$ species on Co(111) was lower than the one obtained on $\\mathtt{C u(111)}$ , which should lead to better ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ performances. However, this result contradicted the fact that $\\eta_{\\mathrm{alomAcm}^{-2}}$ of ${\\sf N O}_{3}{\\mathrm{^-RR}}$ on Cu was $503\\mathrm{mV}$ more positive than on Co $(\\eta_{\\mathrm{olomAcm^{-2}}}$ of $690\\mathrm{mV},$ . This inconformity could be explained by a strong competition of ${}^{*}\\mathsf{H}$ species on the catalyst sites’ surface compared to nitrogenous species, as proved by in situ FTIR and SHINERS analysis. Indeed, Co was capable of promoting hydrogenation during the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ by transferring in situ $^{*}\\mathsf{H}$ species13, because of its excellent adsorption for $^*\\mathsf{H}$ species60. However, the excessive adsorption of $^{*}\\mathsf{H}$ can reduce the coverage of ${^*}\\mathsf{N O}_{3}$ species and their intermediates, thereby weakening the electrochemical activity toward $N O_{3}^{-}\\mathsf{R R}$ . Compared with the $\\Delta G$ of ${^*}\\mathsf{N O}_{3}$ and $^{*}\\mathsf{H}$ on Co(111) (Fig. 6b and Supplementary Table S11), the adsorption for $^{*}\\mathsf{H}$ was stronger, but the adsorption for ${\\mathsf{N O}}_{3}^{-}$ was poor. With the incorporation of the Cu atom, the electronic structure changed, enhancing the adsorption of ${\\mathsf{N O}}_{3}^{-}$ species on CuCo(111) and furthermore, the partial replacement of Co sites with Cu sites also reduced the coverage of $^{*}\\mathsf{H}$ species. \n\nBased on the comprehension of the results discussed above, the redistribution of electrons in $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ facilitated the electrons transfer rate and uplifted the catalytic kinetic of the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ (Supplementary Figs. S6, S7). The fair coverage of $^*\\mathsf{H}$ and ${^*{\\mathsf{N O}}_{3}}$ species were important to obtain simultaneously a high $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ and $j_{\\mathrm{NH_{3}}}$ . Coadjustment of $\\mathtt{C u}$ and Co sites on $\\mathrm{Cu}_{50}\\mathrm{Co}_{50}$ can balance the adsorption energy between ${^*}\\mathsf{H}$ and ${^*}\\mathsf{N O}_{3}$ species, not only by lowering the energy barrier of ${\\mathsf{N O}}_{3}^{-}$ reduction but also by improving the hydrogenation capability with the enhanced $^{*}\\mathsf{H}$ adsorption compared with pure Cu, and at the same time avoiding the excessive $^{*}\\mathsf{H}$ occupation of the active sites compared to pure Co. \n\nTo conclude, we presented a novel Cu-based catalyst able to mimic the Cu core center of the Cu-NIR for the electrocatalytic ${\\mathsf{N O}}_{3}^{-}$ reduction. The addition of Co to Cu formed a micro-pine structure with nanosheets and enhanced dramatically the proton availability over the surface of the catalyst from water electrolysis, resulting in an almost full Faraday efficiency of ${\\mathsf{N H}}_{3}$ production at an ampere-level current density of $1035\\mathsf{m A c m}^{-2}$ at $-0.2\\ensuremath{\\upnu}$ . This process exhibited a high activity and could be proposed as a sustainable and eco-friendly complementary route of ${\\mathsf{N H}}_{3}$ production. In batch conditions, the catalyst was able to achieve a $\\mathsf{F E}_{\\mathsf{N H}_{3}}$ of $96\\%$ and a nitrate’s removal of $99.5\\%$ , from an initial concentration of 6,200 ppm, reaching a final concentration of 31 ppm after $10\\mathsf{h}$ of reaction, lower than the limitations fixed by the World Health Organization for drinking water. A mechanism was established by combining in situ FTIR and SHINERS spectroscopic investigations and DFT calculations. The synergy between $\\mathtt{C u}$ and Co can reduce the high energy barrier of the ratedetermining step of the initial ${^*{\\mathsf{N O}}_{3}}$ adsorption step on Cu, due to a regulation of the electronic structure. The $\\Delta G$ of the hydrogenation of the intermediate species, ${^*}\\mathrm{NO}_{\\mathrm{x}},$ could also be reduced due to the facile adsorption of ${}^{*}\\mathsf{H}$ species on Co(111) compared to Cu(111). We proposed that a rational control of the $^{*}\\mathsf{H}$ adsorption over the surface of the bimetallic catalyst is the key to managing further adsorption of intermediates from ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ to achieve excellent performances. This discovery can provide an additional dimension to research into surface adsorption-modulated bimetallic catalysts for highly reactive hydrodeoxidation reactions and can provide a novel strategy for the development of multi-component heterogeneous catalysts for efficient ${\\mathsf{N H}}_{3}$ production and wastewater treatment. \n\n# Methods Preparation of $\\mathbf{Cu_{x}C o_{y}}$ , Cu, and Co catalysts \n\nThe catalysts were prepared via an electrodeposition process under the current density of $50\\mathsf{m A}\\mathsf{c m}^{-2}$ for 300 s in a two-electrodes system where a platinum plate was used as the counter electrode and the Ni foam as the working electrode. Ni foams were pretreated with acetone and ethanol, and then repeatedly rinsed with ultrapure water and dried under a heating lamp. The deposition electrolyte $(50\\mathrm{mL})$ ) comprised of 0.015 M trisodium citrate pentahydrate solutions and $50\\mathrm{mM}$ $\\mathrm{CuSO_{4}}+\\mathrm{CoSO_{4}}^{61,62}$ . The $\\mathsf{C u}_{\\mathrm{x}}\\mathrm{Co}_{\\mathrm{y}}$ catalysts with Cu:Co ratios of 65:35, 50:50, and 15:85, denoted as $\\mathrm{Cu}_{65}\\mathrm{Co}_{35},$ , $\\mathtt{C u}_{50}\\mathtt{C o}_{50},$ and $\\mathsf{C u}_{15}\\mathsf{C o}_{85}$ , were obtained in the deposition solutions with the ratio of $\\mathrm{CuSO_{4}}$ to $\\mathrm{CoSO_{4}}$ as 60:40, 45:55, and 10:90, respectively. The $\\mathtt{C u}$ and Co catalysts were prepared. The preparation for pure Cu and Co catalysts followed the same steps as the $\\mathsf{C u}_{\\mathrm{x}}\\mathrm{Co}_{\\mathrm{y}}$ synthesis, except that only $\\mathsf{C u S O_{4}}$ or $\\mathrm{CoSO_{4}}$ solution was present in the electroplating solution. The catalysts were finally rinsed with ultrapure water and dried under the protection of Ar. \n\n# Material characterization \n\nMorphology and elemental composition were characterized using a scanning electron microscope (SEM, ZEISS Sigma) with an energy dispersive X-ray spectrometer at an operating voltage of $15\\mathsf{k V}$ . The lattice arrangement was observed using a high-resolution transmission electron microscope (HRTEM, FEI-Tecnai G2 F20) at an accelerated voltage of $200\\mathsf{k V}.$ . The chemical composition was analyzed by an inductively coupled plasma emission spectrometer (ICP-OES, Thermo Fisher iCap 7000). X-ray diffractometer (XRD, SmartLab-SE) with CuKα X-ray source was used for crystal material structure analysis. Al Ka X-ray excited Thermo Fisher Scientific Nexsa X-ray Photoelectron spectrometer (XPS, Nexsa) was used for chemical state analysis. All XPS spectra were corrected with a C 1 s spectral line of 284.8 eV. X-ray absorption fine structure (XAFS) spectra at Cu K-edge and Co K-edge were obtained on the 1W1B beamline of Beijing Synchrotron Radiation Facility (BSRF) operated at $2.5\\mathsf{G e V}$ and $250\\mathrm{mA}$ Standard data processing, including energy calibration and spectral normalization of the raw spectra was performed using Athena software. \n\n# Electrochemical test \n\nThe electrochemical measurements were performed using a threeelectrodes system connected to the $\\mathrm{CHI}760\\mathrm{E}$ workstation (Chenhua, Shanghai) in a homemade H-type cell (separated by Nafion 117 membrane; with magnetic stirring of $1000~\\mathrm{rpm})$ . The Nafion 117 was preprocessed according to the reported procedures. The $\\mathbf{Cu_{x}C o_{y}/N i}$ foams $(0.5\\mathsf{c m}^{2}\\times0.5\\mathsf{c m}^{2})$ ) were used as working electrodes, and platinum plate and ${\\sf H g/H g O}$ electrode (filled with 1 M KOH solution) were used as counter and reference electrodes, respectively. Before the testing, all the catalysts were electro-reduced at $-0.2\\mathsf{V}$ vs. RHE for 600 s in 1 M KOH solution to eliminate surface oxidation. 1 M KOH aqueous solution containing different ${\\mathsf{K N O}}_{3}^{-}$ concentrations (5, 10, 50, and $100\\mathrm{{mM}}$ ) were used as an electrolyte $(30\\mathrm{ml})$ . The electrolyte was bubbled with Ar to remove $0_{2}$ and ${\\sf N}_{2}$ for $10\\mathrm{min}$ before the experiment. The electrochemical linear voltammetry (LSV) curves were obtained in a single cell. The current density was normalized to the geometric electrode area $(0.25\\mathrm{cm}^{2})$ unless otherwise specified. The cyclic voltammetry curves in electrochemical double-layer capacitance $\\mathrm{(C_{dl})}$ determination were measured in a potential window where no Faradaic process occurred in an electrolyte of 1 M KOH at different scanning rates of 20, 40, 60, 80, and $100\\mathrm{{mVs^{-1}}}$ . All the potentials were converted to the RHE reference scale by $\\begin{array}{r}{E_{\\left(\\mathrm{V}v s.\\mathrm{RHE}\\right)}=E_{\\left(\\mathrm{V}v s.\\mathrm{Hg}/\\mathrm{HgO}\\right)}+0.0591\\times\\mathrm{pH}+0.098.}\\end{array}$ Note that ${\\mathsf{N H}}_{3}$ volatilization in the 1 M KOH electrolytes $\\left(\\mathsf{p H13.6}\\right)$ is negligible during the 1-h electrolysis. \n\n# Kinetic evaluation \n\nThe electrochemical kinetic analysis of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ was performed based on the Koutecký–Levich (K–L) equation, as shown in Eq. (5): \n\n$$\n\\frac{1}{i_{m}}=\\frac{1}{i_{K}}+\\frac{1}{0.2\\mathsf{n F}D^{2/3}\\nu^{-1/6}C\\omega^{1/2}}\n$$ \n\nWhere $i_{m}$ is the test current; $i_{K}$ is the kinetic current of ${\\mathsf{N O}}_{3}^{-}$ reduction; $n$ is the number of electrons transferred in the reaction; $F$ is the Faraday constant, $96485\\mathrm{C}\\mathrm{mol^{-1}},$ $D$ represents the effective diffusion coefficient of $0.1\\mathrm{mol}\\mathrm{L}^{-1}\\mathrm{\\NO}_{3}^{-}$ at $25^{\\circ}\\mathrm{C},$ $1.4\\times10^{-5}\\mathsf{c m}^{2}\\mathsf{s}^{-1}$ ; $\\upsilon$ represents the kinematic viscosity of water at $25^{\\circ}\\mathrm{C}$ , $1\\times10^{-6}\\mathsf{m}^{2}\\mathsf{s}^{-1}$ ; $c$ is ${\\mathsf{N O}}_{3}^{-}$ concentration, mmol $\\mathsf{L}^{-1}:\\omega$ is the electrode speed, rpm. \n\nThe working electrode was prepared as follows: (1) $5\\mathrm{mg}$ of catalyst powder dropped down from $\\mathbf{Cu_{x}C o_{y}/N i}$ foam and was dispersed in the solution of ${\\bf600\\upmu L}$ isopropanol $+380\\upmu\\mathrm{L}$ ultrapure water $+20\\upmu\\mathrm{L}$ $5\\%$ Nafion solution, and then sonicated for at least 1 h to get a homogeneous ink; (2) $10\\upmu\\mathrm{L}$ ink was drop-casted onto the rotating disk electrode $(\\varnothing,0.196\\mathrm{cm}2),$ ) with the loading of $0.255\\mathrm{mg_{catalyst}c m}$ $\\mathsf{c m}^{-2}$ for the further LSV analysis at different speeds (100, 225, 400, and 625 rpm) with a scan rate of $10\\mathrm{mVs^{-1}}$ . A platinum electrode and an ${\\sf H g/H g O}$ electrode were used as counter electrode and reference electrode, respectively. An aqueous solution of $\\mathsf{1m o l L^{-1}}$ KOH containing $100\\mathrm{mmol}\\mathrm{L}^{-1}\\mathsf{K N O}_{3}$ was used as the electrolyte. Ar was used to purge the dissolved $0_{2}$ and ${\\sf N}_{2}$ from the electrolyte. \n\n# Product detection and efficiency calculation \n\nThe $\\mathsf{N H}_{3}$ concentration was quantified by the Nessler Reagent method28. The electrolytes sampled after electrolysis for 1 h were first neutralized with 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and then mixed with $6.25\\mathrm{mL}$ ultrapure water and $0.25\\mathrm{mL}$ of Nessler reagent for the chromogenic reaction. The absorbance of the mixed solution was measured at a wavelength of $420\\mathsf{n m}$ after keeping it at room temperature for $30\\mathrm{min}$ . The quantitation of ${\\mathsf{N H}}_{3}$ was performed by the standard curves, which was built using standard $N H_{4}C l$ solutions in 1 M KOH. The $\\mathsf{\\Pi}^{\\mathrm{1}}\\mathsf{H}$ NMR $(500\\mathsf{M H z})$ determination31 was also carried out to quantify the $^{14}\\mathsf{N}\\mathsf{H}_{4}^{+}$ and $^{15}\\mathrm{N}\\mathrm{H}_{4}^{+}$ after electrolysis at $-0.2\\upnu$ vs. RHE for 1 h. The electrolytes were mixed with 0.4 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ at a ratio of 500:125 to ensure adequate protonation of $\\mathsf{N H}_{3}$ . Then, $125\\upmu\\upmu$ of the diluted electrolytes or standard solution were mixed with $125\\upmu\\upmu$ of $10\\mathrm{\\:mM}$ maleic acid in DMSO-D6, $50\\upmu\\upmu\\upmu$ of 4 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4},$ , and $300\\upmu\\mathrm{l}$ of ${\\sf H}_{2}{\\sf O}$ . \n\nThe ${\\mathsf{N O}}_{3}^{-}$ and ${\\mathsf{N O}}_{2}^{-}$ in the solution were quantitatively determined by ion chromatography (IC). The possible gas products of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}},$ , such as $\\mathsf{H}_{2},\\mathsf{N}_{2},$ NO, ${\\mathsf{N O}}_{2},$ ${\\sf N}_{2}0$ , and $\\mathsf{N H}_{3}(\\mathsf{g})$ were analysed using a gas chromatography (GC) and online electrochemical mass spectrometry (OEMS)30. \n\nThe Faradaic efficiency was calculated according to the following equation: \n\n$$\n\\mathsf{F E}=\\frac{\\mathsf{n c V}_{\\mathrm{catholyte}}\\mathsf{F}}{\\mathsf{Q}}\\times100\\%\n$$ \n\nwhere $c$ represents the concentration of the product, mol $\\mathsf{c m}^{-3}$ ; Vcatholyte is the volume of catholyte, mL; $Q$ is the total amount of charge consumed, C. \n\nThe yield rate of ${\\mathsf{N H}}_{3}$ was calculated according to the following equations: \n\n$$\n\\mathrm{\\DeltaYield{}_{N H_{3}}=\\frac{c V_{c a t h o l y t e}}{S t}}\n$$ \n\n$$\n\\mathrm{Yield}_{\\mathrm{mass-NH}_{3}}=\\frac{c V_{c a t h o l y t e}}{m t}\n$$ \n\nwhere $s$ is the area of the geometrical cathode, $\\mathsf{c m}^{-2}$ ; $m$ is the mass of the catalyst on the cathode; $t$ is the time of the electrolysis. \n\n# Electrochemical in situ FTIR reflection analysis \n\nElectrochemical in situ FTIR reflection spectroscopy44. Electrochemical thin-layer in situ FTIR spectroscopy measurements were performed on a Nicolet Nexus 8700 FTIR spectrometer equipped with a liquid $\\mathsf{N}_{2}\\mathsf{-}$ cooled system and MCT-A detector. The glassy carbon electrode loading with catalysts was used as the working electrode, which was pressed vertically on the $\\mathsf{C a F}_{2}$ window plate to form a thin liquid layer with a thickness of about $10\\upmu\\mathrm{m}$ . A platinum foil and an ${\\sf H g/H g O}$ electrode (filled with 1 M KOH solution) were used as the counter electrode and reference electrode, respectively. The incoming infrared beam was approximately aligned with the normal electrode surface. Unless otherwise noted, the sample spectra were averaged from 200 interference spectra with a resolution of $8\\mathsf{c m}^{-1}$ . Reference spectrum $(\\mathsf{R}_{\\mathsf{R e f}})$ were collected at $0.4\\mathsf{V}$ , and sample spectra $(\\mathsf{R}_{\\mathsf{S}})$ were collected in the potential region from $_{0.4\\mathrm{V}}$ to $-0.2\\upnu$ and stepped by $100\\mathrm{mV}$ . The spectra were reported as $\\Delta{\\sf R}/{\\sf R}=(\\sf R_{S}-\\sf R_{\\mathrm{Ref}})/\\mathrm{R}_{\\mathrm{Ref}}.$ \n\nAttenuated Total Reflection in situ FTIR reflection spectroscopy36. The gold-plated Si prism with catalysts were assembled into a homemade spectral-electrochemical cell, which contained a carbon sheet as a counter electrode and ${\\sf H g/H g O}$ electrode as a reference electrode. It was then fixed in a homemade optics system built in the chamber of a Nicolet Nexus 8700 FTIR spectrometer for electrochemical ATR-FTIR measurements at an incidence angle of ca. $65^{\\circ}$ . The ATR-FTIR spectra were reported in the same way of thin-layer in situ FTIR, except that ${\\sf R}_{\\sf R e f}$ was taken at $0.5\\ensuremath{\\mathrm{V}}$ and $\\mathtt{R}_{\\mathtt{S}}$ were collected in the potential region from 0.5 to $-0.4\\:\\mathrm{V}$ . \n\n# SHINERS analysis \n\nSHINERS spectra were recorded in a custom-made in situ Raman spectroelectrolysis cell using an XplorA confocal microprobe Raman spectrometer (HORIBA Jobin Yvon)63. The excitation wavelength of the laser was $637.8\\ensuremath{\\mathrm{nm}}$ and came from a He-Ne laser with a power of about $6\\mathrm{mw}$ . The electrochemically polished gold electrode (diameter $3\\mathrm{mm}^{\\cdot}$ ) was modified by $10\\upmu\\mathrm{L}$ catalyst ink with $10\\upmu\\mathrm{L}$ homemade shell-isolated gold nanoparticle, which was provided by Prof. Jian-Feng Li at Xiamen University, China, and applied as the working electrode. ${\\sf H g/H g O}$ electrode was used as the reference electrode, and platinum wires was used as the counter electrode. A long-focus objective $(8\\mathsf{m m})$ of $\\mathbf{A}\\times50$ magnification was used. A Si wafer $(520.6\\mathsf{c m}^{-1})$ ) was used to calibrate the Raman frequency before the experiment. The SHINERS spectra were obtained using the cumulative results of four tests for 30 s each. \n\n# EPR Experiments \n\n5,5-dimethyl-1-pyrroline $N\\cdot$ -oxide (DMPO) was used to capture the instable hydrogen radical to form the DMPO-H adduct to generate EPR spectra64. In the experiments, $5\\ensuremath{\\mathrm{ml}}$ electrolyte was mixed with $10\\upmu\\mathrm{L}$ DMPO and was deoxygenated by bubbling Ar. The potentiostatic electrolysis was carried out for $5\\mathrm{{min}}$ in the H-type cell under the protection of Ar. EPR measurement was performed by Bruker EMX-10/ 12 spectrometer operating at a frequency near $9.5\\mathsf{G H z}$ sweep width of $200\\mathbf{G}$ and power of $20\\mathsf{m}\\mathsf{W}$ . \n\n# DFT calculations \n\nAll DFT calculations in this work were carried out with the Vienna Ab initio Simulation Package $(\\mathsf{V A S P})^{65}$ . And the projector augmentedwave (PAW) pseudopotential was selected to deal with the corevalence interaction66. The generalized gradient approximation (GGA) of Perdew–Burke–Ernzerhof (PBE) was used to account for the exchange and correlation of electronics and the cut-off energy of plane-wave was $600{\\mathrm{eV}}^{67}$ . The energy convergence criterion was within $10^{-5}\\mathrm{eV}$ and the Hellmann–Feynman force was smaller than $0.01\\mathrm{eV}\\mathring{\\mathbf{A}}^{-1}$ on each atom. The converged unit cell models of Cu $(3.64\\times3.64\\times3.64\\mathring{\\mathrm{A}}^{3})$ , Co $(3.52\\times3.52\\times3.52\\mathring{\\mathrm{A}}^{3})$ , and CuCo $(3.78\\times3.49\\times3.49\\mathring{\\mathrm{A}}^{3})$ were used in DFT calculations, respectively. The dimension of a $2\\times2$ supercell of Cu (111) $(8.91\\times10.28\\mathring{\\mathbf{A}}^{2})$ , a $2\\times2$ supercell of Co (111) $(8.62\\times9.95\\mathring{\\mathbf{A}}^{2},$ and a $2\\times2$ supercell of CuCo (111) $(9.03\\times9.87\\mathring{\\mathbf{A}}^{2})$ were used, respectively. These supercells were constructed and contained three layers and a sufficient vacuum layer of $15\\mathring{\\mathbf{A}}$ thicknesses. For the structural optimization, the bottom two layers were fixed and the top layer was fully relaxed68. For unit cell geometry optimization, an $8\\times8\\times8{\\sf k}$ -point analysis was used. A grid of $3\\times3\\times1$ k-point mesh was used for these supercell calculations15. The calculations of all molecules and intermediate species on Co(111) and CuCo(111) were performed with spin polarization69. Dipole corrections in the z direction were included in all computations to minimize inaccuracies in the total energy because of simulated slab interactions. The spin polarization was not taken into account in the calculations of intermediate species on $\\mathtt{C u(111)}$ due to the spin polarization did not affect the $\\mathtt{C u}$ (111) calculations. \n\n# Data availability \n\nThe raw data of the figures in the main manuscript are available in figshare with the identifier(s) https://doi.org/10.6084/m9.figshare. 21671075. All other data needed to evaluate the conclusions in the paper are present in the paper and the Supplementary Information or can be obtained from the corresponding authors on reasonable request. \n\n# Code availability \n\nThe code used in this work can be obtained from the corresponding authors on reasonable request. \n\n# References \n\n1. Yao, F. et al. Highly selective electrochemical nitrate reduction using copper phosphide self-supported copper foam electrode: performance, mechanism, and application. Water Res 193, 116881 (2021). \n\n# Article \n\nammonia fertilizer via an electrified membrane. Environ. Sci. Technol. 56, 11602–11613 (2022). \n3. Ye, S. et al. Elucidating the activity, mechanism and application of selective electrosynthesis of ammonia from nitrate on cobalt phosphide. Energy Environ. Sci. 15, 760–770 (2022). \n4. Nishina, K. New ammonia demand: ammonia fuel as a decarbonization tool and a new source of reactive nitrogen. Environ. Res. Lett. 17, 021003 (2022). \n5. Liu, X., Elgowainy, A. & Wang, M. Life cycle energy use and greenhouse gas emissions of ammonia production from renewable resources and industrial by-products. Green. Chem. 22, 5751–5761 (2020). \n6. Liu, H. et al. Efficient electrochemical nitrate reduction to ammonia with copper-supported rhodium cluster and single-atom catalysts. Angew. Chem. Int. Ed. 61, e202202556 (2022). \n7. Wu, Z. Y. et al. Electrochemical ammonia synthesis via nitrate reduction on Fe single atom catalyst. Nat. Commun. 12, 2870 (2021). \n8. Min, Y. et al. Integrating single-cobalt-site and electric field of boron nitride in dechlorination electrocatalysts by bioinspired design. Nat. Commun. 12, 303 (2021). \n9. Li, Y. et al. Enzyme mimetic active intermediates for nitrate reduction in neutral aqueous media. Angew. Chem. Int. Ed. 59, 9744–9750 (2020). \n10. Kuypers, M. M. M., Marchant, H. K. & Kartal, B. The microbial nitrogen-cycling network. Nat. Rev. Microbiol. 16, 263–276 (2018). \n11. Sundararajan, M., Hillier, I. H. & Burton, N. A. Mechanism of nitrite reduction at $\\mathsf{T}_{2}\\mathsf{C u}$ centers: electronic structure calculations of catalysis by copper nitrite reductase and by synthetic model compounds. J. Chem. Phys. B 111, 5511–5517 (2007). \n12. Li, J. et al. Efficient ammonia electrosynthesis from nitrate on strained ruthenium nanoclusters. J. Am. Chem. Soc. 142, 7036–7046 (2020). \n13. Liu, M. J. et al. Catalytic performance and near-surface X-ray characterization of titanium hydride electrodes for the electrochemical nitrate reduction reaction. J. Am. Chem. Soc. 144, 5739–5744 (2022). \n14. He, W. et al. Splicing the active phases of copper/cobalt-based catalysts achieves high-rate tandem electroreduction of nitrate to ammonia. Nat. Commun. 13, 1129 (2022). \n15. Wang, Y. et al. Enhanced nitrate-to-ammonia activity on coppernickel alloys via tuning of intermediate adsorption. J. Am. Chem. Soc. 142, 5702–5708 (2020). \n16. Yuan, C. et al. Growth of ultrathin mesoporous $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ nanosheet arrays on Ni foam for high-performance electrochemical capacitors. Energy Environ. Sci. 5, 7883–7887 (2012). \n17. Zhang, G. Q., Wu, H. B., Hoster, H. E., Chan-Park, M. B. & Lou, X. W. Single-crystalline ${\\mathsf{N i C o}}_{2}{\\mathsf{O}}_{4}$ nanoneedle arrays grown on conductive substrates as binder-free electrodes for high-performance supercapacitors. Energy Environ. Sci. 5, 9453–9456 (2012). \n18. Zhang, Y. et al. Exhaustive conversion of inorganic nitrogen to nitrogen gas based on a photoelectro-chlorine cycle reaction and a highly selective nitrogen gas generation cathode. Environ. Sci. Technol. 52, 1413–1420 (2018). \n19. Zhang, Y. et al. Electrochemical reduction of nitrate via Cu/Ni composite cathode paired with Ir-Ru/Ti anode: High efficiency and ${\\sf N}_{2}$ selectivity. Electrochim. Acta 291, 151–160 (2018). \n20. Baricco, M., Rizzi, P. & Enzo, S. X-ray diffraction study of nanocrystalline phases formation in metallic systems. Mater. Sci. Forum 278- 281, 559–564 (1998). \n21. Hsieh, H. H. et al. Electronic structure of Ni-Cu alloys: the d-electron charge distribution. Phys. Rev. B 57, 15204–15210 (1998). activity of Co-based non-noble bimetal catalysts for hydrolysis of ammonia borane. ACS Sustain. Chem. Eng. 8, 8256–8266 (2020). \n23. Smith, M. L., Campos, A. & Spivey, J. J. Reduction processes in Cu/ ${\\mathsf{S i O}}_{2},$ , ${\\mathsf{C o}}/{\\mathsf{S i O}}_{2}.$ and $\\mathsf{C u C o}/\\mathsf{S i O}_{2}$ catalysts. Catal. Today 182, 60–66 (2012). \n24. Ma, F. et al. Graphene-like two-dimensional ionic boron with double dirac cones at ambient condition. Nano Lett. 16, 3022–3028 (2016). \n25. Bhattacharjee, S., Waghmare, U. V. & Lee, S. C. An improved d-band model of the catalytic activity of magnetic transition metal surfaces. Sci. Rep. 6, 35916 (2016). \n26. Bae, S.-E., Stewart, K. L. & Gewirth, A. A. Nitrate adsorption and reduction on $\\mathsf{C u}(100)$ in acidic solution. J. Am. Chem. Soc. 129, 10171–10180 (2007). \n27. Molodkina, E. B. et al. Electroreduction of nitrate ions on Pt(111) electrodes modified by copper adatoms. Electrochim. Acta 56, 154–165 (2010). \n28. Zhao, Y. et al. Ammonia detection methods in photocatalytic and electrocatalytic experiments: how to improve the reliability of $N H_{3}$ production rates? Adv. Sci. 6, 1802109 (2019). \n29. Andersen, S. Z. et al. A rigorous electrochemical ammonia synthesis protocol with quantitative isotope measurements. Nature 570, 504–508 (2019). \n30. Shen, S. et al. Tuning electrochemical properties of Li-rich layered oxide cathodes by adjusting Co/Ni ratios and mechanism investigation using in situ X-ray diffraction and online continuous flow differential electrochemical mass spectrometry. ACS Appl. Mater. Interfaces 10, 12666–12677 (2018). \n31. Hodgetts, R. Y. et al. Refining universal procedures for ammonium quantification via rapid 1H NMR analysis for dinitrogen reduction studies. ACS Energy Lett. 5, 736–741 (2020). \n32. Humphreys, J., Lan, R. & Tao, S. Development and recent progress on ammonia synthesis catalysts for Haber–Bosch process. Adv. Energy Sustain. Res. 2, 2000043 (2020). \n33. van Langevelde, P. H., Katsounaros, I. & Koper, M. T. M. Electrocatalytic nitrate reduction for sustainable ammonia production. Joule 5, 290–294 (2021). \n34. World Health Organization. Water, S. A. H. T. Guidelines for Drinking-Water Quality (World Health Organization, 2022). \n35. Xiang, S. et al. New progress of ammonia recovery during ammonia nitrogen removal from various wastewaters. World J. Microbiol. Biotechnol. 36, 144 (2020). \n36. Zhou, Z.-Y., Wang, Q., Lin, J.-L., Tian, N. & Sun, S.-G. In situ FTIR spectroscopic studies of electrooxidation of ethanol on Pd electrode in alkaline media. Electrochim. Acta 55, 7995–7999 (2010). \n37. Ye, J.-Y. et al. Ammonia electrooxidation on dendritic Pt nanostructures in alkaline solutions investigated by in-situ FTIR spectroscopy and online electrochemical mass spectroscopy. J. Electroanal. Chem. 819, 495–501 (2018). \n38. Figueiredo, M. C., Souza-Garcia, J., Climent, V. & Feliu, J. M. Nitrate reduction on Pt(111) surfaces modified by Bi adatoms. Electrochem. Commun. 11, 1760–1763 (2009). \n39. Pérez-Gallent, E., Figueiredo, M. C., Katsounaros, I. & Koper, M. T. M. Electrocatalytic reduction of nitrate on copper single crystals in acidic and alkaline solutions. Electrochim. Acta 227, 77–84 (2017). \n40. Rosca, V., Beltramo, G. L. & Koper, M. T. M. Hydroxylamine electrochemistry at polycrystalline platinum in acidic media: a voltammetric, DEMS and FTIR study. J. Electroanal. Chem. 566, 53–62 (2004). \n41. Ataka, K., Yotsuyanagi, Takao & Osawa, M. Potential-dependent reorientation of water molecules at an electrode/electrolyte interface studied by surface-enhanced infrared absorption spectroscopy. J. Chem. Phys. 100, 10664–10672 (1996). oxidation of nitric oxide. Electrochim. Acta 49, 1307–1314 (2004). \n43. Le, Ru,E. C. & Etchegoin, P. G. Single-molecule surface-enhanced Raman spectroscopy. Annu. Rev. Phys. Chem. 63, 65–87 (2012). \n44. Zhou, Z.-Y., Tian, N., Chen, Y.-J., Chen, S.-P. & Sun, S.-G. In situ rapidscan time-resolved microscope FTIR spectroelectrochemistry: study of the dynamic processes of methanol oxidation on a nanostructured Pt electrode. J. Electroanal. Chem. 573, \n111–119 (2004). \n45. Agrawal, V. K. & Trenary, M. An infrared study of NO adsorption at defect sites on Pt(111). Surf. Sci. 259, 116–128 (1991). \n46. Yao, Y., Zhu, S., Wang, H., Li, H. & Shao, M. A spectroscopic study on the nitrogen electrochemical reduction reaction on gold and platinum surfaces. J. Am. Chem. Soc. 140, 1496–1501 (2018). \n47. Zhu, S. et al. The role of ruthenium in improving the kinetics of hydrogen oxidation and evolution reactions of platinum. Nat. Catal. \n4, 711–718 (2021). \n48. Liu, R. et al. Defect sites in ultrathin Pd nanowires facilitate the highly efficient electrochemical hydrodechlorination of pollutants by H\\*ads. Environ. Sci. Technol. 52, 9992–10002 (2018). \n49. Deng, Y., Handoko, A. D., Du, Y., Xi, S. & Yeo, B. S. In situ Raman spectroscopy of copper and copper oxide surfaces during electrochemical oxygen evolution reaction: identification of CuIII oxides as catalytically active species. ACS Catal. 6, 2473–2481 (2016). \n50. Bodappa, N. et al. Early stages of electrochemical oxidation of Cu(111) and polycrystalline Cu surfaces revealed by in situ Raman spectroscopy. J. Am. Chem. Soc. 141, 12192–12196 (2019). \n51. Zhao, Y. et al. Speciation of Cu surfaces during the electrochemical CO reduction reaction. J. Am. Chem. Soc. 142, 9735–9743 (2020). \n52. Orlovskaya, N. et al. Detection of temperature- and stress-induced modifications of $\\mathsf{L a C o O}_{3}$ by micro-Raman spectroscopy. Phys. Rev. B 72, 014122 (2005). \n53. Zhou, Z., Huang, G. G., Kato, T. & Ozaki, Y. Experimental parameters for the SERS of nitrate ion for label-free semi-quantitative detection of proteins and mechanism for proteins to form SERS hot sites: a SERS study. J. Raman. Spectrosc. 42, 1713–1721 (2011). \n54. GOODGAME, D. M. L. & HITCHMAN, M. A. Studies of nitro and nitrito complexes. II. Complexes containing chelating ${\\mathsf{N O}}_{2}$ groups. Inorg. Chem. 4, 721–725 (1964). \n55. Nakamoto, K. Infrared and Raman Spectra of Inorganic and Coordination Compounds (John Wiley & Sons, 2008). \n56. Ling, Y., Mills, C., Weber, R., Yang, L. & Zhang, Y. NMR, IR/Raman, and structural properties in HNO and RNO $\\mathrm{\\Delta}\\mathrm{R}=$ alkyl and aryl) metalloporphyrins with implication for the HNO-myoglobin complex. J. Am. Chem. Soc. 132, 1583–1591 (2010). \n57. Butcher, D. P. & Gewirth, A. A. Nitrate reduction pathways on Cu single crystal surfaces: Effect of oxide and Cl−. Nano Energy 29, \n457–465 (2016). \n58. Wen, N. & Brooker, M. H. Ammonium carbonate, ammonium bicarbonate, and ammonium carbamate equilibria: a Raman study. J. Chem. Phys. 99, 359–368 (1995). \n59. Hu, T., Wang, C., Wang, M., Li, C. M. & Guo, C. Theoretical insights into superior nitrate reduction to ammonia performance of copper catalysts. ACS Catal. 11, 14417–14427 (2021). \n60. Sheng, W., Myint, M., Chen, J. G. & Yan, Y. Correlating the hydrogen evolution reaction activity in alkaline electrolytes with the hydrogen binding energy on monometallic surfaces. Energy Environ. Sci. 6, \n1509–1512 (2013). \n61. Silva, F. L. G. et al. Response surface analysis to evaluate the influence of deposition parameters on the electrodeposition of Cu–Co alloys in citrate medium. J. Appl. Electrochem. 38, \n1763–1769 (2008). \n62. Wu, W., Yang, F., Luo, M., Tian, Z. & Zhou, S. Electrodeposition of copper in a citrate bath and its application to a micro-electromechanical system. Acta Phys. Chim. Sin. 26, 2625–2632 (2010). \n63. Su, M., Dong, J.-C. & Li, J.-F. In-situ Raman spectroscopic study of electrochemical reactions at single crystal surfaces. Electrochemistry 26, 54–60 (2020). \n64. Wang, Y. et al. Structurally disordered ${\\mathsf{R u O}}_{2}$ nanosheets with rich oxygen vacancies for enhanced nitrate electroreduction to ammonia. Angew. Chem. Int. Ed. 61, e202202604 (2022). \n65. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n66. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n67. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 78, 1396–1396 (1997). \n68. Chen, G.-F. et al. Electrochemical reduction of nitrate to ammonia via direct eight-electron transfer using a copper–molecular solid catalyst. Nat. Energy 5, 605–613 (2020). \n69. Prieto, G. et al. Design and synthesis of copper-cobalt catalysts for the selective conversion of synthesis gas to ethanol and higher alcohols. Angew. Chem. Int. Ed. 53, 6397–6401 (2014). \n\n# Acknowledgements \n\nThis research was financially supported by the National Natural Science Foundation of China (NSFC) (Nos. 22002131, Y.-Y.L.) and China Postdoctoral Science Foundation (Grant No 2020M671963, Y.-Y.L.). X.-Y.H. thanks R.O. from Seoul National University for the fruitful discussions. We are thankful to the Beijing Synchrotron Radiation Facility (1W1B, BSRF) for their help with the characterizations. \n\n# Author contributions \n\nY.-Y.L., J.-Y.F., & S.-G.S. contributed to the conception of the study. J.- Y.F. performed the experiments. S.-N.H. provided assistance with the HRTEM analysis. K.-M.Z. helped with the SHINERS analysis. G.L. helped with the electrochemical in situ FTIR analysis. Q.-Z.Z. performed the DFT calculations analysis. J.-Y.F. & Y.-Y.L. performed the data analyses and wrote the manuscript. X.-Y.H., O.A., & S.-G.S. contributed significantly to the analysis and manuscript preparation. The project was supervised by Y.-Y.L. and S.-G.S. All authors helped perform the analysis with constructive discussions. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\nAdditional information \nSupplementary information The online version contains supplementary material available at \nhttps://doi.org/10.1038/s41467-022-35533-6. \n\nCorrespondence and requests for materials should be addressed to Yao-Yin Lou or Shi-Gang Sun. \n\nPeer review information Nature Communications thanks Chuan-Xin He, Jeonghoon Lim and the other anonymous reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1038_s41467-022-33007-3", + "DOI": "10.1038/s41467-022-33007-3", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-33007-3", + "Relative Dir Path": "mds/10.1038_s41467-022-33007-3", + "Article Title": "Reversible hydrogen spillover in Ru-WO3-x enhances hydrogen evolution activity in neutral pH water splitting", + "Authors": "Chen, JD; Chen, CH; Qin, MK; Li, B; Lin, BB; Mao, Q; Yang, HB; Liu, B; Wang, Y", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Noble metal electrocatalysts (e.g., Pt, Ru, etc.) suffer from sluggish kinetics of water dissociation for the electrochemical reduction of water to molecular hydrogen in alkaline and neutral pH environments. Herein, we found that an integration of Ru nulloparticles (NPs) on oxygen-deficient WO3-x manifested a 24.0-fold increase in hydrogen evolution reaction (HER) activity compared with commercial Ru/C electrocatalyst in neutral electrolyte. Oxygen-deficient WO3-x is shown to possess large capacity for storing protons, which could be transferred to the Ru NPs under cathodic potential. This significantly increases the hydrogen coverage on the surface of Ru NPs in HER and thus changes the rate-determining step of HER on Ru from water dissociation to hydrogen recombination.", + "Times Cited, WoS Core": 349, + "Times Cited, All Databases": 360, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000853935100017", + "Markdown": "# Reversible hydrogen spillover in Ru-WO3-x enhances hydrogen evolution activity in neutral pH water splitting \n\nReceived: 25 April 2022 \n\nAccepted: 29 August 2022 \n\nPublished online: 14 September 2022 \n\nCheck for updates \n\nJiadong Chen 1,2,5, Chunhong Chen1,5, Minkai Qin1,5, Ben Li1, Binbin Lin1, Qing Mao3, Hongbin Yang2, Bin Liu $\\textcircled{1}2,4$ & Yong Wang 1 \n\nNoble metal electrocatalysts (e.g., Pt, Ru, etc.) suffer from sluggish kinetics of water dissociation for the electrochemical reduction of water to molecular hydrogen in alkaline and neutral pH environments. Herein, we found that an integration of Ru nanoparticles (NPs) on oxygen-deficient $\\mathsf{W O}_{3\\cdots}$ manifested a 24.0-fold increase in hydrogen evolution reaction (HER) activity compared with commercial $\\mathtt{R u/C}$ electrocatalyst in neutral electrolyte. Oxygen-deficient $\\mathsf{w o}_{3\\cdots}$ is shown to possess large capacity for storing protons, which could be transferred to the Ru NPs under cathodic potential. This significantly increases the hydrogen coverage on the surface of Ru NPs in HER and thus changes the rate-determining step of HER on Ru from water dissociation to hydrogen recombination. \n\nHydrogen, with high gravimetric energy density, is an ideal candidate to replace the traditional fossil fuels and also a pivotal ingredient for essential industrial chemicals (e.g., petroleum refining and ammonia synthesis)1–5. Water electrolysis driven by renewable electricity offers great promises for eco-friendly hydrogen production. Electrolysis of water can be realized in acidic, neutral and alkaline environment, among which, water reduction in neutral/alkaline medium is much more sluggish because of the slow water dissociation reaction6–8. Consequently, even platinum $(\\mathsf{P t})$ , the state-of-the-art hydrogen evolution reaction (HER) catalyst, shows two to three orders of magnitude lower activity in neutral/alkaline medium as compared to acidic medium9. Although HER in acidic condition exhibits better activity, equipment and catalyst corrosion limit the lifetime of operation. Neutral media provides a more favorable condition for catalysts to remain stable and less corrosive environment for electrolysers10. And electrolysers capable of operating in neutral media offer the possibility of achieving hydrogen production directly from seawater without the need for desalination10,11. \n\nIn practical application, catalysts usually operate at large overpotentials to achieve large current densities. In this case, early studies show that HER in neutral/alkaline medium starts from water dissociation $(\\mathsf{M}+\\mathsf{e}^{-}+\\mathsf{H}_{2}\\mathsf{O}\\to\\mathsf{M}-\\mathsf{H}_{\\mathrm{ad}}+\\mathsf{O}\\mathsf{H}^{-}$ , where $\\mathsf{\\mathbf{M}}$ refers to the active site and $\\mathsf{H}_{\\mathbf{ad}}$ stands for adsorbed H), followed by either the Heyrovsky reaction $(\\mathsf{H}_{2}\\boldsymbol{\\mathbf{O}}+\\mathsf{e}^{-}+\\mathsf{M}-\\mathsf{H}_{\\mathrm{ad}}\\to\\mathsf{M}+\\boldsymbol{\\mathbf{O}}\\mathsf{H}^{-}+\\mathsf{H}_{2})$ or the Tafel reaction $\\mathrm{(H_{ad}+H_{a d}\\to H_{2})^{10,12,13}}$ . Compared with HER in acidic environment, the additional splitting of water molecules to supply protons in neutral/ alkaline medium is more sluggish in kinetics, resulting in low hydrogen coverage $(\\mathbf{M}-\\mathbf{H_{\\mathbf{ad}}})$ on the surface of the catalyst during HER. \n\nTo enhance HER in neutral/alkaline medium, prior approaches were mainly dedicated to facilitating sluggish water dissociation reaction by means of incorporating a specific component (e.g., transition metal hydroxide) onto the catalytically active species (e.g., Pt) or inducing surface reconstruction to expose more active sites14–18. The water dissociation process releases $\\mathsf{H}^{+}$ , which will be bound on the surface of the catalyst, undergoing hydrogen recombination to evolve molecular hydrogen. The sluggish water dissociation reaction in neutral/alkaline medium results in a low H coverage on the surface of HER catalyst, which impedes HER catalysis19–21. Hydrogen spillover, the migration of activated hydrogen atoms generated by the dissociation of di-hydrogen adsorbed on a metal surface onto a reducible metal oxide support, is a common phenomenon in heterogeneous catalysis22–26. Recently, hydrogen spillover strategy has been taken into account for the catalysts design to achieve the compelling HER performance, such as Pt alloys- $\\cdot{\\bf C o P}^{27}$ , $\\mathsf{P t}/\\mathsf{C o P}^{28}$ , and $\\mathsf{P t/T i O}_{2}{}^{29}$ electrocatalysts, delivering the optimal HER activity. However, spillover strategies have rarely been studied on neutral HER and the exact mechanism of hydrogen spillover to improve HER is still unclear. \n\nIn this work, we develop an effective strategy to significantly increase the H coverage on the catalyst during HER in neutral environment. Specifically, we propose a Ru nanoparticles (NPs) on oxygendeficient tungsten oxide $(\\mathsf{R u-W O}_{3-\\times})$ system, in which protons inserted into $\\mathsf{W O}_{3\\cdot\\mathsf{x}}$ can be transferred to Ru NPs during HER, thereby greatly increasing the hydrogen coverage on Ru NPs and enhancing the HER performance. Through combined in situ Raman spectroscopy investigations, electrochemical measurements and DFT calculations, the hydrogen spillover from $\\mathsf{w o}_{3-\\mathsf{x}}$ to Ru NPs during HER has been explicitly demonstrated. Consequently, the HER activity of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\mathbf{x}}$ is enhanced by a factor of 24.0 as compared with the commercial $\\mathtt{R u/C}$ $(5.0\\ \\mathrm{wt}.\\%)$ electrocatalyst in $1.0\\mathsf{M}$ phosphate buffer solution (PBS) electrolyte. \n\n# Results \n\n# Origin of unsatisfied HER activity of $\\mathbf{Ru}/\\mathbf{C}$ in neutral medium \n\nRu, having a lower cost but comparable hydrogen binding energy as compared to $\\mathsf{P t}^{30-34}$ , is regarded as one of the good candidates to replace Pt in HER. Early studies demonstrated good HER activity of commercial $\\mathtt{R u/C}$ in acidic medium35,36. However, the HER activity of $\\mathtt{R u/C}$ significantly reduced in neutral environment. To figure out the sluggish kinetics of HER on $\\mathtt{R u/C}$ in neutral medium, we performed microkinetic analysis. The HER activity of commercial $\\mathsf{R u}/\\mathsf{C}\\left(5.0\\ \\mathsf{w t.\\%}\\right)$ electrocatalyst was first evaluated in $1.0\\mathsf{M}$ PBS (Fig. 1a). The $\\mathtt{R u/C}$ electrocatalyst displays a large overpotential of $86\\mathrm{mV}$ at a current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ with a Tafel slope as large as $78\\mathsf{m V d e c^{-1}}$ . By fitting the electrochemical data using a microkinetic model, the HER on $\\mathsf{R u/C}$ in neutral medium was found to be rate-limited at the water dissociation step, which led to the low hydrogen coverage $(\\boldsymbol{\\theta}_{\\mathsf{H}})$ on the surface of Ru during HER (Fig. 1b, Supplementary Note 1, Supplementary Tables $_{1-6}$ , and Supplementary Figs. 1 and 2). The low $\\theta_{\\mathrm{H}}$ on $\\mathtt{R u/C}$ in HER was experimentally verified by in situ Raman spectroscopy, where no observable peaks appear in the Raman frequency range of Ru-H vibration (Fig. $\\mathrm{1c)}^{37,38}$ . Therefore, effective strategies need to be proposed to enhance the HER activity of $\\mathtt{R u/C}$ in neutral media. \n\nOxygen-deficient tungsten oxide $(\\mathsf{W O}_{3-\\mathsf{x}})$ displays the excellent capability of storing protons in water39–41. If the inserted protons in $\\mathsf{w o}_{3-\\mathbf{x}}$ are mobile, $\\mathsf{w o}_{3-\\mathbf{x}}$ may be used as a proton reservoir to supply H to increase $\\theta_{\\mathrm{H}}$ on Ru during HER, which thus shall promote the HER kinetics of Ru in neutral medium. Inspired by this possibility, we prepared Ru NPs on oxygen-deficient $\\mathsf{w o}_{3-\\mathsf{x}}$ $(\\mathsf{R u-W O}_{3-\\times})$ electrocatalysts and studied their HER catalysis. \n\n# Synthesis and characterization of $\\mathbf{R}\\mathbf{u}\\mathbf{\\cdot}\\mathbf{W}\\mathbf{O}_{3\\mathbf{-}\\mathbf{x}}$ \n\n${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3{-}\\mathbf{x}}$ was prepared by a three-step method as schematically illustrated in Fig. 2a. ${\\sf W O}_{3}/{\\sf C P}$ was first synthesized by a simple hydrothermal method and then impregnated in ${\\sf R u C l}_{3}$ solution, followed by a heat treatment in ${\\sf H}_{2}/{\\sf A}{\\sf r}$ mixed atmosphere (10/90 molar ratio) to form $\\mathsf{R u-W O}_{3-\\mathsf{x}}/\\mathsf{C P}$ . The crystal structure of the as-prepared ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ catalyst was examined by $\\mathsf{x}$ -ray diffraction (XRD) as shown in Fig. 2b. The $\\mathsf{R u-W O}_{3-\\mathsf{x}}/\\mathsf{C P}$ displays clear diffraction peaks of hexagonal ${\\mathsf{W O}}_{3}$ (JCPDS No. $85\\mathrm{-}2460)^{42}$ , but no diffraction peaks related to Ru NPs, possibly due to their small sizes and low content. In addition, the peaks of ${\\sf R u-W O}_{3-\\times}/{\\sf C P}$ are shifted to high angles, indicating lattice shrinkage, which may be caused by oxygen vacancies40. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) measurements were performed to probe the morphological information. The ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ exhibits nanowires with smooth surfaces grown on carbon fibers (Supplementary Fig. 3a–d). High-resolution TEM (HRTEM) image of a single nanowire gives a lattice spacing of $3.84\\mathring{\\mathsf{A}}$ (Supplementary Fig. $3\\mathrm{e})^{43,44}$ , which is attributed to the (002) facet of hexagonal $\\mathsf{w o}_{3}$ (JCPDS No. 85-2460). Energy dispersive $\\mathsf{x}$ -ray spectroscopy (EDX) elemental mapping of a single $\\mathsf{w o}_{3}$ nanowire reveals uniform distribution of the W and O elements (Supplementary Fig. 3f–h). Comparatively, the ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ displays rough nanowires (Supplementary Fig. 4a, b), indicating successful loading of Ru NPs, which is further verified by the TEM measurements (Supplementary Fig. $_{4c-e)}$ . Both lattice spacings resulting from hexagonal ${\\mathsf{W O}}_{3}$ and hexagonal Ru are clearly visible in the HRTEM images of $\\scriptstyle\\mathsf{R u-W O}_{3-\\mathsf{X}}/\\mathbf{CP}$ (Fig. 2c, d and Supplementary Fig. 4f). On the other hand, the lattice fringes of ${\\mathsf{W O}}_{3}$ at the edge become blurred, which may be due to the formation of oxygen vacancies induced by hydrogen reduction45. EDX elemental mappings reveal uniform distribution of Ru, W and O elements (Supplementary Fig. 4g). Moreover, the average size of the Ru NPs on Ru${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ is $3.5\\mathsf{n m}$ (Supplementary Fig. 4h). The mass content of Ru in $\\mathsf{R u-W O}_{3-\\mathsf{x}}/\\mathsf{C P}$ was determined to be 5.1 wt. $\\%$ by inductively coupled plasma optical emission spectrometry (ICP-OES) (Supplementary Table 7). The formation of oxygen vacancies in $\\mathsf{R u-W O}_{3-\\mathsf{X}}/\\mathsf{C P}$ was confirmed by the electron paramagnetic resonance (EPR) measurement as shown in Fig. 2e. To probe the valence states and further explore the oxygen vacancies in $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ , X-ray photoelectron spectroscopy (XPS) was performed. Ru $3d_{5/2}$ core level XPS spectrum displays two peaks at $280.28\\mathrm{eV}$ and 281.28 eV, respectively, matching well with $\\mathtt{R u(0)}$ and Ru(IV) (Fig. $2\\mathsf{f})^{30,31}$ . The Ru $3p$ XPS spectrum shows two pairs of peaks, in which the dominant peaks at $461.88\\mathrm{eV}$ and 484.14 eV can be assigned to Ru $3p_{3/2}$ and Ru $3p_{1/2}$ of $\\mathtt{R u}(0)$ and the rest of the peaks are from Ru(IV), manifesting that the Ru precursor has been successfully reduced to metallic Ru. The W 4f XPS spectrum of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ displays two peaks at $35.58\\mathrm{eV}$ and $37.68\\mathrm{eV}$ , which correspond well to the W $4f_{2/7}$ and W $4f_{2/5}$ of W(VI), respectively (Fig. $2\\mathbf{g})^{40,41}$ . Additionally, two more deconvoluted peaks at $34.53\\mathrm{eV}$ and 36.63 eV can be assigned to $\\mathsf{w}(\\mathsf{V})^{43,45}$ . Notably, a few hydrogen atoms may be induced in the surface of $\\mathsf{w o}_{3-\\mathsf{x}}$ support in the $\\mathsf{H}_{2}/\\mathsf{A r}$ reduction process and this may also lead to the appearance of W(V). In O 1s XPS spectrum, two deconvoluted peaks are observed. The peak centered at $531.70\\mathrm{eV}$ is assigned to the OH groups or a lattice oxygen bounded to a W(V) atom (close to a vacancy)45. And another peak at $530.30\\mathrm{eV}$ is ascribed to the lattice oxygen. The percentage of oxygen vacancies in $\\mathsf{R u-W O}_{3-\\mathsf{X}}/\\mathsf{C P}$ is determined to be around $34.3\\%$ , consistent with the W(V) content deduced from W 4f XPS spectrum. In addition, ${\\mathsf{W O}}_{3-\\mathsf{X}}/{\\mathsf{C P}}$ was prepared, and the corresponding W $4f$ and O1s XPS of ${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ showed that there were also a large number of oxygen vacancies (Supplementary Fig. 5). To further investigate oxygen vacancies in ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\mathbf{x}}$ and $\\mathsf{w o}_{3-\\mathsf{x}},$ we conducted $\\mathbf{O}_{2}$ -temperature programmed desorption $(\\mathsf{O}_{2}\\mathsf{-T P D})$ ). The corresponding result reveals oxygen vacancies in $\\mathsf{w o}_{3-\\mathbf{x}}$ and ${\\sf R u-W O}_{3-\\mathrm{x}},$ which matches well with the EPR and O 1s XPS results (Supplementary Fig. 6). \n\n![](images/f28a75ce424844ffe2d9fac23615212b25512fd5461c418b39997a0cf05984c7.jpg) \nig. 1 | HER performance of commercial $\\mathbf{Ru}/\\mathbf{C}$ (5 wt%) in 1.0 M PBS. a LSV curve from the microkinetic analysis. The microkinetic model was built based on three and the corresponding Tafel plot for commercial $\\mathtt{R u/C}$ (5.0 wt. $\\%^{\\dag}$ loaded on CP. elementary reactions. c In situ Raman spectra recorded on $\\mathtt{R u/C}$ (5.0 wt.%) in $1.0\\mathsf{M}$ can rate: $2\\mathrm{mV}/\\mathrm{s}$ . b Hydrogen coverage as a function of current density obtained PBS in the potential range from $-0.6$ to $-0.9{\\mathrm{V}}$ vs. Ag/AgCl. \n\n![](images/b22167fab8c80e5d52c4a4fe8162a3b69e19f829905508134173ea967aca61a1.jpg) \nFig. 2 | Preparation and characterization of $\\mathbf{Ru}\\mathbf{.}\\mathbf{W}\\mathbf{O}_{3\\mathbf{-}\\mathbf{\\times}}/\\mathbf{CP}$ . a Schematic illustra- c of R $\\scriptstyle\\mathbf{u}-\\mathbf{WO}_{3-\\mathbf{x}}/\\mathbf{CP}$ . The blue spheres represent Ru atoms. e EPR spectra of $\\mathsf{W O}_{3}$ and tion showing the procedure to prepare $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ . b XRD patterns of ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ ${\\sf R u-W O}_{3-{\\bf x}}.$ . f Ru $3d_{5/2}$ and Ru $3p$ XPS spectra of $\\scriptstyle\\mathsf{R u-W O}_{3-\\mathsf{X}}/\\mathsf{C P}$ g W 4f and O 1s XPS and R $\\scriptstyle1-W O_{3-\\times}/\\mathbf{CP}$ . c HRTEM image of $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ . d Filtered HRTEM image (using spectra of $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ . ASBF filter) and the corresponding structural model of Ru nanoparticle marked in \n\n# HER performance of $\\scriptstyle\\mathbf{Ru-WO}_{3-\\times}/\\mathbf{CP}$ in neutral media \n\nThe HER performance of the as-prepared electrocatalysts was examined in a three-electrode system in $\\mathsf{N}_{2}$ saturated $1.0\\mathsf{M}$ PBS. In comparison to $\\mathsf{W O}_{3-\\mathsf{x}}/\\mathsf{C P}$ and commercial $\\mathtt{R u/C}$ (5.0 wt.%)/CP, the Ru${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ exhibits a greatly improved HER activity, reaching a current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ at an overpotential as low as $19\\mathrm{mV}$ (Fig. 3a). Notably, the current density of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ is enhanced by a factor of 24.0 as compared to the commercial $\\mathtt{R u/C}$ $(5.0\\ \\mathrm{\\wt.\\%})/\\mathrm{CP}$ at the potential of $-0.150\\mathrm{v}$ vs. RHE. Meanwhile, the Tafel slope of $\\mathsf{R u\\mathrm{-}}\\mathsf{W O}_{3-\\mathsf{x}}/$ CP also significantly reduces to $41\\mathsf{m V}\\mathsf{d e c}^{-1}$ (Fig. 3b), manifesting a change of the rate-determining step (RDS) of HER from water dissociation for $\\mathtt{R u/C}$ to hydrogen recombination for $\\mathsf{R u-W O_{3-x}}^{46,47}$ . It is noteworthy that the ${\\sf R u-W O}_{3-\\times}/{\\sf C P}$ is among the best HER electrocatalysts reported in the neutral medium (Fig. 3c and Supplementary Table 8). Moreover, we also calculated the LSV curves normalized by the electrochemically active surface area and $\\scriptstyle\\mathsf{R u-W O}_{3-\\mathsf{x}}/\\mathbf{CP}$ still shows much better HER activity than $\\mathsf{R u/C}$ (5.0 wt.%)/CP (Supplementary Figs. 7 and 8). The HER activity and stability under higher current densities were also evaluated. As shown in Supplementary Fig. 9, Ru${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ displays a low overpotential of $225\\mathrm{mV}$ to achieve a current density of $1\\mathsf{A c m}^{-2}$ , and the potential of ${\\sf R u-W O}_{3-\\times}/{\\sf C P}$ remains stable to attain $1\\mathsf{A c m}^{-2}$ in the chronopotentiometry test. Besides activity, the ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ also displays excellent durability in catalyzing HER (Fig. 3d). Both the structure and composition of $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ remain unchanged before and after the HER stability test as examined by SEM, HRTEM and ICP-OES (Supplementary Fig. 10 and Supplementary Table 7). Moreover, to explore whether oxygen vacancies have an effect on the HER activity, ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ was also synthesized for comparison. As shown in Supplementary Fig. 11, the HER activity of Ru${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ is better than that of $\\mathsf{R u/C}$ $(5.0~\\mathrm{wt.\\%})/\\mathrm{CP}$ , but is still much worse than that of $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ . The corresponding Tafel plots indicate that the reaction kinetics of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ is slower than that of Ru${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ , but faster than that of $\\mathsf{t u}/\\mathsf{C}\\ (5.0\\ \\mathsf{w t.}\\%)/\\mathsf{C P}$ These results suggest that oxygen-deficient tungsten oxide is beneficial for activity improvement. Moreover, ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ keeps stable in the long-term stability test, and no obvious HER activity decay is observed. In addition, ${\\mathsf{W O}}_{3}$ or $\\mathsf{w o}_{3-\\mathsf{x}}$ gradually dissolves in alkaline electrolyte48,49. Thus, it is not appropriate to apply ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\mathbf{x}}$ in alkaline condition because of the stability issue. \n\nFig. 3 | HER performance in 1.0 M PBS. a LSV curves in $1.0\\mathsf{M}$ PBS. b The corresponding Tafel plots. c HER activity comparison of ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ with other reported state-of-the-art electrocatalysts in $1.0\\mathsf{M}$ PBS. The corresponding \n\nTo dig out the origin of the enhanced HER activity of $\\mathsf{R u\\mathrm{-}}\\mathsf{W O}_{3-\\mathsf{x}}/$ CP, we first examined the tungsten oxide support. According to previous reports, creating oxygen vacancies in tungsten oxide could increase its capacitance40,41. Since proton storage in tungsten oxide is positively correlated with its capacitive performance, gravimetric capacitance of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times},{\\mathsf{W O}}_{3-\\times}$ and $\\mathsf{w o}_{3}$ were calculated from cyclic voltammetry (CV) measurements. Here, we separated the capacitive and diffusion-controlled contribution in the measured capacitance using the following equation: i $\\mathrm{(V)}=k_{1}\\nu+k_{2}\\nu^{1/2}.$ where i (V), $k_{1}\\nu,$ and $k_{2}\\nu^{1/2}$ are total current, capacitive current and diffusion-controlled current in CV, respectively39. The results at various scan rates show that the capacitance of $\\mathsf{W O}_{3-\\mathbf{x}}$ is enhanced by a factor of around 23.0 as compared to that of ${\\mathsf{W O}}_{3}$ (Supplementary Figs. 12–17). Loading Ru NPs onto $\\mathsf{w o}_{3-\\mathsf{x}}$ could further increase the capacitance to some extent. The proton insertion/extraction kinetics was assessed using the equation: $i=a\\nu^{\\mathrm{b}}$ , where $i$ is the current response, $a$ is an adjustment coefficient, $\\nu$ is the sweep rate and the power exponent b is a parameter to analyze the kinetics50,51. A $b$ value of 0.5 means diffusion-controlled kinetics and a $^{b}$ value of 1.0 indicates an ideal capacitive or non-diffusioncontrolled behavior. By plotting log $(i)$ vs. log $(\\nu)$ , the $b$ value of Ru$\\mathsf{w o}_{3-\\mathsf{x}}$ is estimated to be 0.99 and 0.82 (Supplementary Fig. 13a, b), respectively, based on the oxidation and reduction redox peak, indicating the dominant pseudocapacitive behavior of proton extraction/ insertion and that the proton extraction is more rapid than its insertion in ${\\sf R u-W O}_{3-{\\bf x}}.$ . \n\n![](images/232f4f44e10ce2ae1b85c7d35afd0936de15a1d3dc7577174ccaa8eea3c50353.jpg) \nreferences for these reported electrocatalysts are shown in Supplementary Table 8. d Chronopotentiometric curve recorded at a constant cathodic current density of $20\\mathsf{m A}\\mathsf{c m}^{-2}$ . Inset compares the LSV curves before and after the stability test. \n\nTo study the HER process, in situ Raman spectroscopy was performed. The in situ Raman spectra of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ were collected in the potential range from $-0.1$ to $-0.7\\:\\mathrm{V}$ (vs. $\\mathbf{Ag/AgCl},$ , which includes both the non-Faradaic current region and the HER region. For the initial state at open circuit, the typical Raman peaks of $\\mathsf{w o}_{3-\\mathsf{x}}$ were observed at $778\\mathsf{c m}^{-1}$ (Fig. 4a), which is attributed to the W-O stretching vibration45,52. The Raman signal at $778\\mathsf{c m}^{-1}$ gradually decreased with increasing applied cathodic potential and this signal completely disappeared at $-0.5\\mathsf{V}$ (vs. $\\mathbf{Ag/AgCl})$ , due to proton insertion in $\\mathsf{w o}_{3-\\mathsf{x}}\\mathsf{\\Omega}^{53,54}$ . Additionally, a new Raman peak at $878\\mathsf{c m}^{-1}$ appeared after the applied potential reached $-0.6\\:\\mathsf{V}$ (vs. $\\mathbf{Ag/AgCl})$ ) and the intensity of this peak further increased with increase in applied cathodic potential. Based on previous reports, the Raman peak at $878\\mathrm{cm}^{-1}$ may result from the Ru-H stretching vibration37,38. To figure out the attribution of the Raman peak at $878\\mathsf{c m}^{-1}.$ , a deuterium isotopic substitution experiment was performed. Once $\\mathsf{H}_{2}\\mathsf{O}$ was changed to ${\\sf D}_{2}0$ , the Raman peak at $878\\mathrm{cm}^{-1}$ shifted to a lower wavenumber at 611 $\\mathsf{c m}^{-1}$ (Fig. 4b). The downward shift ratio $(\\gamma)$ in the isotopic substitution experiment can be estimated by: $\\gamma=\\nu(\\mathrm{Ru\\cdotD})/\\nu(\\mathrm{Ru\\cdotH})$ (see details in Supplementary Note 2). The estimated downward shift ratio $(\\gamma)$ of the $\\mathsf{R u\\mathrm{\\cdotH}}$ peak is $\\sim71.0\\%$ , very close to the theoretical $70.0\\%$ . Furthermore, DFT calculation was performed to determine the vibrational frequency of $\\mathsf{H}^{*}$ on metallic Ru. Here, we considered two Ru models. The Raman frequency of the $\\mathsf{R u\\mathrm{\\cdotH}}$ stretching vibration was calculated to be 875 and $880\\mathsf{c m}^{-1}$ for the ridge and top sites on the Ru cluster (Fig. 4c). These results corroborate the attribution of the Raman peak at $878\\mathsf{c m}^{-1}$ to the Ru-H stretching vibration. When the potential was swept back from $-0.6\\ensuremath{\\mathsf{V}}$ to $-0.2\\mathsf{V}$ (vs. Ag/AgCl) in $1.0\\mathsf{M}$ PBS, the characteristic Raman peak of W-O stretching vibration re-appeared at $-0.5\\mathsf{V}$ (vs. Ag/AgCl) and the peak intensity increased with further decrease in the cathodic potential, suggesting that the proton extraction started at $-0.5\\mathsf{V}$ (vs. Ag/AgCl) (Fig. 4d). Notably, when the applied cathodic potential was increased, the Raman peak intensity of Ru-H first remained steady until $-0.5\\mathsf{V}$ (vs. Ag/AgCl) and then gradually increased, suggesting increase of hydrogen coverage on Ru, which may result from proton transfer from $\\mathsf{w o}_{3-\\mathsf{x}}$ to Ru NPs. Moreover, the deuterium isotopic substitution experiment should also be performed on ${\\mathsf{W O}}_{3\\cdot\\times}/{\\mathsf{C P}}$ . As shown in Supplementary Fig. 18, there is no obvious difference between the Raman results in deuterium isotopic substitution and non-deuterium isotopic substitution experiments. Only W-O Raman peaks can be seen in the Raman spectra. \n\nFurthermore, the hydrogen coverage $(\\boldsymbol{\\theta}_{\\mathsf{H}})$ on ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ in HER was studied by microkinetic analysis (Supplementary Note 1, \n\n![](images/938f755b9967db6e827e97b81a280cb11b4d6e854cc8e4f8dceddabfe6a6bfbc.jpg) \nFig. 4 | Insights of hydrogen spillover. a In situ Raman spectra of $\\scriptstyle\\mathsf{R u-W O}_{3-\\mathsf{X}}/\\mathbf{CP}$ obtained from microkinetic analysis. f Fitted data of $\\mathbf{C}_{\\Psi}$ at different overpotentials recorded in 1.0 M PBS from $-0.1$ to $-0.7\\:\\mathrm{V}$ vs. $\\scriptstyle\\mathbf{Ag}/\\mathbf{AgCl}$ . b In situ Raman spectra of for various electrocatalysts during HER in $1.0\\mathsf{M}$ PBS. $\\pmb{\\mathrm{g}}$ The onset potential of $\\boldsymbol{\\mathsf{H}}^{+}$ ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ recorded from $-0.2$ to −0.7 V vs. $\\mathbf{Ag/AgCl}$ in 1.0 M PBS (in ${\\bf D}_{2}0^{\\cdot}$ ). c Side insertion and extraction for $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ and ${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ . h CV curve of $\\mathsf{w o}_{3-\\mathsf{x}}$ and top view illustrations of DFT models used for Raman frequency calculation of recorded in 1.0 M PBS. Scan rate: 5 mV/s. i CV curve of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\mathbf{x}}$ recorded in $1.0\\mathsf{M}$ $\\mathsf{R u\\mathrm{\\cdotH}}$ vibration. d In situ Raman spectra of $\\scriptstyle\\mathsf{R u-W O}_{3-\\mathsf{X}}/\\mathbf{CP}$ recorded in 1.0 M PBS from PBS. Scan rate: $5\\mathrm{mV/s}$ . $-0.6$ to $-0.2\\mathrm{V}$ vs. $\\scriptstyle\\mathbf{Ag}/\\mathbf{AgCl}.$ . e Hydrogen coverage as a function of current density \n\nSupplementary Tables $_{1-6}$ , and Supplementary Figs. 1 and 2). Compared with $\\theta_{\\mathsf{H}}$ on $\\mathsf{R u}/\\mathsf{C}\\ (5.0\\ \\mathsf{w t.}\\%)/\\mathsf{C P}$ (Fig. 1b), $\\theta_{\\mathsf{H}}$ on $\\mathsf{R u\\mathrm{-}}\\mathsf{W O}_{3-\\mathsf{x}}/$ CP significantly increases (Fig. 4e), matching well with the in situ Raman spectra (Figs. 1c and 4a). Operando electrochemical impedance spectroscopy (EIS) measurement was further conducted to probe the hydrogen adsorption/desorption process in ${\\sf H E R}^{27,53}$ . The obtained EIS data was simulated using an equivalent circuit model as shown in Supplementary Fig. 19 and Supplementary Table 9. The first parallel circuit, with one resistor $(R_{\\mathrm{c}})$ and one constant phase element $(\\mathsf{C P E_{1}})$ , corresponds to the inner layer of electrode material, where $R_{\\mathrm{c}}$ is the charge transfer resistance and $\\mathrm{CPE}_{1}$ corresponds to the double-layer capacitance. The second parallel circuit simulates the electrolyte-catalyst interfacial charge transfer27,55,56, which is able to reflect the hydrogen intermediate adsorption behavior on the catalytically active sites $(R_{\\mathrm{i}}$ is the charge transfer resistance and $\\mathbf{C}\\boldsymbol{\\Phi}$ represents the hydrogen adsorption pseudo-capacitance). $\\mathbf{C}\\boldsymbol{\\Phi}$ as a function of overpotential was integrated to calculate the hydrogen adsorption charge $(Q_{\\mathsf{H}^{*}})$ . Compared with $Q_{\\mathrm{H^{*}}}$ for $\\mathtt{R u/C}$ (5.0 wt. $\\%$ )/CP, $Q_{\\mathrm{H^{*}}}$ (originated from Ru) $(Q_{\\mathrm{H}^{*}\\mathrm{(Ru}\\cdot\\mathrm{WO3-x}/\\mathrm{CP})}-Q_{\\mathrm{H}^{*}\\mathrm{(WO3-x}/\\mathrm{CP})})$ for ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ increases a lot (Fig. 4f), in good agreement with the greatly increased $\\theta_{\\mathsf{H}}$ on ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ deduced from microkinetic analysis. \n\nTo explore factors that influence proton insertion/extraction in tungsten oxide, in situ Raman measurements were also performed on ${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ (Supplementary Fig. 20). By comparing the onset potential of proton insertion/extraction, it is found that introduction of Ru onto $\\mathsf{w o}_{3-\\mathsf{x}}$ results in a more positive onset potential for proton insertion while a more negative onset potential for proton extraction (Fig. 4g). This indicates that Ru NPs can not only promote proton insertion but also accelerate proton extraction from $\\mathsf{w o}_{3-\\infty}.$ . Furthermore, CV was performed in $1.0\\mathsf{M}$ PBS to investigate the proton insertion/extraction behavior (Fig. 4h, i). In the CV curves, obvious proton insertion peaks are observed on $\\mathsf{w o}_{3-\\mathbf{x}}$ at $_{0.160\\mathrm{V}}$ (vs. RHE) and ${\\sf R u-W O}_{3-\\mathrm{x}}$ at 0.288 V (vs. RHE)39,40. Furthermore, a distinct proton extraction peak at $0.422\\mathrm{v}$ (vs. RHE) can be observed on $\\mathsf{R u\\mathrm{\\cdot}W O}_{3\\mathrm{-}\\mathbf{\\times}},$ but not on $\\mathsf{w o}_{3-\\mathsf{x}},$ strongly illustrating that Ru NPs can promote proton extraction from $\\mathsf{w o}_{3-\\mathbf{x}}$ . \n\nTheoretical insights of reversible hydrogen spillover in HER To gain some theoretical insights on whether hydrogen spillover can take place from $\\mathsf{W O}_{3-\\mathbf{x}}$ to Ru NPs, DFT calculations were carried out to determine the hydrogen transfer energy barrier. The Gibbs free energy change at each step of hydrogen transfer from the interior of $\\mathsf{w o}_{3-\\mathsf{x}}$ to the surface of Ru NPs was computed. As hydrogen spillover occurs on proton-inserted $\\mathsf{W O}_{3-\\mathrm{x}}\\left(\\mathsf{H}_{\\mathrm{x}}\\mathsf{W O}_{3-\\mathrm{x}}\\right)$ , a moderate amount of H was added into the as-built $\\mathsf{W O}_{3-\\mathbf{x}}$ model to simulate the actual situation. As shown in Fig. ${5}\\mathsf{a-c}$ , hydrogen adsorption is extremely weak on the external surface of $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}}$ (site 2, 3 and 4), while it becomes much stronger on the inner surface (site 1), suggesting that interior of $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}}$ is more favorable for hydrogen adsorption. The difference of hydrogen adsorption between internal and external surface results in a large difference in Gibbs free energy of adsorbed hydrogen $(\\Delta G_{\\mathrm{H^{*}}})$ between site 1 and site 2, with a thermodynamic barrier of 0.44 eV. Meanwhile, the kinetic barrier of hydrogen transfer from site 1 to site 2 was calculated to be $0.62\\mathrm{eV}$ , indicating difficulty of hydrogen transfer from site 1 to site 2. On the contrary, $\\Delta G_{\\mathrm{H}^{*}}$ values of site 2, 3 and 4 on ${\\sf R u}{\\cdot}{\\sf H}_{\\sf x}{\\sf W}\\sf0_{3-\\sf x}$ become more negative, suggesting much improved hydrogen adsorption on the external surface of $\\mathsf{R u}\\mathsf{\\Pi}_{\\mathsf{x}}\\mathsf{W}\\mathsf{O}_{3-\\mathsf{x}}$ . Benefitted from the enhanced hydrogen adsorption, the thermodynamic barrier of hydrogen transfer from site 1 to site 2 reduces to 0.11 eV. Furthermore, the kinetic hydrogen transfer barrier (from site 1 to site 2 on ${\\sf R u}{\\cdot}{\\sf H}_{\\sf x}W0_{3-{\\sf x}})$ was calculated to be $0.25\\mathrm{eV}$ , manifesting that the hydrogen transfer process is greatly promoted on ${\\sf R u}{\\cdot}{\\sf H}_{\\sf x}{\\sf W}\\sf0_{3-x}$ . Additionally, it is found that the hydrogen adsorption on Ru surface (site 5) is stronger than that on $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}},$ as indicated by the most negative $\\Delta G_{\\mathrm{H^{*}}}$ of $-0.078\\mathrm{eV}$ on site 5. Therefore, the adsorbed hydrogen can be spontaneously transferred from external surface of $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}}$ to Ru (from site 4 to site 5). To unravel the facilitated hydrogen transfer process on ${\\sf R u-W O}_{3-\\mathrm{x}},$ the charge density difference was calculated to explore the charge distribution at the interface. As shown in Fig. 5d, electron accumulation is observed below the surface layer of $\\mathsf{w o}_{3\\cdots}$ High density electrons are favorable to trap hydrogen atoms via interacting with unsaturated electrons in the H 1s orbital. Therefore, hydrogen adsorption is significantly enhanced on the external surface of $\\mathsf{w o}_{3-\\mathsf{x}}.$ Moreover, electron accumulation below the surface layer of $\\mathsf{w o}_{3-\\mathsf{x}}$ also attracts protons in the interior to the surface by electrostatic interaction. As a result, hydrogen spillover from $\\mathsf{w o}_{3-\\mathsf{x}}$ to Ru is thermodynamically and kinetically facilitated. Next, to investigate the cause of charge transfer between Ru NPs and $\\mathsf{w o}_{3-\\mathsf{x}},$ the work functions $(\\Phi)$ of Ru and $\\mathsf{w o}_{3-\\mathsf{x}}$ were calculated. The work function of Ru NPs was determined to be 4.91 eV, much smaller than that of $\\mathsf{w o}_{3-\\mathbf{x}}$ $(9.14\\mathrm{eV})$ , revealing electron transfer from Ru to $\\mathsf{w o}_{3-\\mathbf{x}}$ (Fig. 5e and Supplementary Figs. 21 and 22). Taking into account the size distribution of Ru NPs, the work function of bulk Ru was also computed, which is slightly larger than that of Ru NPs but still much smaller than that of $\\mathsf{w o}_{3-\\infty}.$ Combining with the above analyses, a reasonable explanation for hydrogen spillover from $\\mathsf{w o}_{3-\\infty}$ to Ru is given as follows: the difference in work function between Ru NPs and $\\mathsf{w o}_{3-\\mathsf{x}}$ leads to electron accumulation at the subsurface of $\\mathsf{w o}_{3-\\mathsf{x}},$ which enhances hydrogen adsorption and also drives moving internal protons to the external surface. In addition, DFT calculations were also performed to reveal the free energy change in H transfer and the electronic structure of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ (Supplementary Fig. 23). The free energy change in H transfer of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ is comparable to that of ${\\sf R u}{\\cdot}{\\sf W O}_{3-\\times}/{\\sf C P}$ , and the kinetic energy barrier of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ from site 1 to site 2 is determined to be 0.31 eV, only slightly higher than that of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ , indicating that H transfer is also favorable on ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ . The charge difference of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ also reveals that electrons transfer from Ru to $\\mathsf{w o}_{3}$ , which is the same as that of ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ . \n\n![](images/28c90b3d9d4e7141722292d6ac0c31b610c73c8e9dfdab6b8a914899cdc49cfb.jpg) \nFig. 5 | DFT calculations of hydrogen transfer energy barrier. a Calculated free energy diagram for HER on $\\mathsf{R u\\mathrm{-}H_{x}W O_{3-x}}$ and $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}}$ . b The optimized $\\boldsymbol{\\mathsf{H}^{*}}$ adsorption structure on various sites of ${\\sf R u}{\\cdot}{\\sf H}_{\\sf x}{\\sf W}0_{3-{\\sf x}}.$ c The optimized $\\mathsf{H}^{*}$ adsorption structure on various sites of $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}}$ . d Electron density difference \nplot across the ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\mathbf{x}}$ interface. Electron accumulation and depletion are indicated in yellow and blue, respectively. e Work function calculations for various Ru and $\\mathsf{w o}_{3-\\infty}$ . \n\nTo explore the RDS of HER on $\\mathsf{R u-H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}},$ we conducted DFT calculations to investigate the energy barrier of reaction steps. It is well-known that water dissociation is the RDS in alkaline and neutral media water oxidation, which can be deduced from the very large Tafel slopes. The Heyrovsky reaction and Tafel reaction are closely correlated with the Gibbs free energy of adsorbed hydrogen $(\\Delta G_{\\mathrm{H}^{*}})$ , which is the typical HER descriptor. We calculated the energy barrier of water dissociation and the $\\Delta G_{\\mathrm{H}^{\\ast}}$ on various sites to explore the RDS of HER taking place on $\\mathsf{R u\\mathrm{\\mathbf{\\cdot}H_{x}W O_{3-x}}}$ As revealed in Supplementary Figs. 24–26, the barrier for water dissociation on Ru is about $0.46\\mathrm{eV}$ and that on $\\mathsf{W O}_{3-\\mathbf{x}}$ is around $0.35\\mathrm{eV}.$ . The water dissociation on $\\mathsf{W O}_{3-\\mathsf{x}}$ is more favorable than that on Ru. As the further increase of overpotential, $\\mathsf{w o}_{3-\\mathsf{x}}$ will dissociate the water to generate protons, which can also spillover to $\\mathtt{R u}$ . The OH on the surface of $\\mathsf{W O}_{3-\\mathbf{x}}$ will undergo desorption and then be quickly captured by the buffer electrolyte. The OH concentration on the catalyst’s surface is low because the buffer electrolyte can react quickly with the desorbed OH to produce ${\\sf H}_{2}{\\sf O}.$ . As shown in Supplementary Figs. 27 and 28, the $\\Delta G_{\\mathrm{H}^{\\ast}}$ on the corner and edge sites of Ru clusters of ${\\sf R u}{\\cdot}{\\sf H}_{\\sf x}{\\sf W}\\sf0_{3-x}$ are close to $0\\mathrm{eV}$ , which is the thermodynamically neutral state. To further explore the reaction process, we calculated the energy barriers of the Tafel step and Heyrovsky step on Ru, respectively. As shown in Supplementary Figs. 29–31, the Heyrovsky step shows a lower energy barrier than the Tafel step, suggesting that the hydrogen atoms on Ru transferred from $\\mathsf{w o}_{3-\\mathbf{x}}$ tend to follow the Heyrovsky mechanism to generate dihydrogen. As the energy barrier of hydrogen transfer from $\\mathsf{w o}_{3-\\mathsf{x}}$ to Ru is only $0.25\\mathrm{eV}$ , the whole process to generate di-hydrogen including hydrogen atoms spillover from $\\mathsf{w o}_{3-\\mathsf{x}}$ to Ru followed by the Heyrovsky step to generate di-hydrogen has an energy barrier of $0.38\\mathrm{eV}$ , indicating Heyrovsky step is the rate limiting step in this process (Fig. 5a). However, the di-hydrogen produced by water dissociation over Ru itself has a higher energy barrier of $0.46\\mathrm{eV}$ , suggesting that this process is more difficult than the spillover mechanism to generate molecular hydrogen. Therefore, the H atoms involved in the reaction tend to come from H transfer from ${\\sf H}_{\\sf x}{\\sf W}{\\sf O}_{3-{\\sf x}}$ to Ru rather than water dissociation on Ru of $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ . \n\nBased on the above investigations, a possible mechanism is proposed to account for the greatly enhanced HER activity of Ru$\\mathsf{w o}_{3-\\mathbf{x}}$ in neutral medium (Fig. 6). Under applied cathodic potential, protons in the electrolyte were inserted into the oxygen-deficient $\\mathsf{w o}_{3-\\mathbf{x}}$ and then coupled with electrons to form $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}}$ . The plenty of oxygen vacancies in $\\mathsf{w o}_{3-\\mathbf{x}}$ significantly increased the proton storage capacity and at the same time improved the charge transfer. As a result, the oxygen-deficient $\\mathsf{w o}_{3-\\mathbf{x}}$ served as a proton reservoir to supply protons onto Ru surface, which recombined to evolve molecular hydrogen. As the further increase of overpotential, $\\mathsf{W O}_{3-\\mathbf{x}}$ will dissociate the water to generate protons, which also spilled over to Ru. The hydrogen spillover from $\\mathsf{w o}_{3-\\mathsf{x}}$ to Ru changed the RDS of HER on Ru in neutral medium from water dissociation to hydrogen recombination, which greatly improved the HER kinetics (denoted as pathway 1). In addition, hydrogen recombination on $\\mathsf{H}_{\\mathsf{x}}\\mathsf{W O}_{3-\\mathsf{x}}$ (denoted as pathway 2) and hydrogen formation on Ru NPs (denoted as pathway 3), where hydrogen is all provided by water dissociation on Ru, are both unfavorable. \n\n# Discussion \n\nIn summary, we report the design and performance of ${\\sf R u-W O}_{3-\\mathrm{x}}$ to facilitate different parts of the multistep HER process in neutral environment: the oxygen-deficient $\\mathsf{w o}_{3-\\mathbf{x}}$ possesses a large capacity for storing protons, which can be transferred to the surface of Ru NPs under cathodic potential. This hydrogen spillover from $\\mathsf{w o}_{3-\\mathsf{x}}$ to Ru changes the RDS of HER on Ru in neutral medium from water dissociation to hydrogen recombination, which greatly improves the HER kinetics. \n\n# Methods \n\n# Materials \n\nRuthenium (III) chloride anhydrous $(\\mathsf{R u C l}_{3})$ and ammonium metatungstate hydrate $((\\boldsymbol{\\mathrm{NH_{4}}})_{6}\\boldsymbol{\\mathrm{H}_{2}}\\boldsymbol{\\mathrm{W_{12}}}\\boldsymbol{\\mathrm{O}}_{40}{\\cdot}\\boldsymbol{\\mathrm{xH}_{2}}\\boldsymbol{\\mathrm{O}})$ with $99.5\\%$ metals basis were purchased from Shanghai Macklin Biochemical Co., Ltd. Potassium phosphate monobasic $(\\mathsf{K H}_{2}\\mathsf{P O}_{4}$ , AR, $99.5\\%$ and potassium hydrogen phosphate $(\\mathsf{K}_{2}\\mathsf{H P O}_{4}$ , $298\\%$ , ACS) were obtained from Shanghai Aladdin Bio-Chem Technology Co., Ltd. The TGP-H-060 TORAY carbon paper (CP) was purchased form Suzhou Sinero Technology Co., Ltd. The ethanol $(\\mathbf{CH}_{3}\\mathbf{CH}_{2}\\mathbf{OH}$ AR, $299.5\\%$ ) and acetone $(\\mathbf{C}_{3}\\mathbf{H}_{6}0_{.}$ AR, $295\\%$ ) were purchased from Sinopharm Chemical Reagent Co., Ltd. Nickel(II) acetate tetrahydrate (Ni(O$\\mathrm{COCH}_{3})_{2}{\\cdot}4\\mathsf{H}_{2}0$ , AR, $98\\%$ ), chloroplatinic acid hexahydrate $(\\mathsf{H}_{2}\\mathsf{P t C l}_{6}{\\cdot}6\\mathsf{H}_{2}\\mathsf{O}$ , ACS reagent, $237.50\\%$ Pt basis), sodium borohydride $(N a B H_{4}$ granular, $99.99\\%$ trace metals basis), sodium hydroxide (NaOH, ACS reagent, $297.0\\%$ , pellets), and molybdenum(VI) oxide $(\\mathsf{M o O}_{3}$ , nanopowder, $100\\mathsf{n m}$ (TEM), $99.5\\%$ trace metals basis) were purchased from Sigma-Aldrich. All chemicals were used as received with purification. Ultrapure water (deionized) was used in all the experiments. \n\n# Preparation of ${\\bf W O}_{3}/{\\bf C P}$ \n\nA piece of CP $(4\\mathsf{c m}\\times3\\mathsf{c m}\\times0.19\\mathsf{m m})$ was cleaned by ultrasonication in acetone for $15\\mathrm{{min}}$ , and then dried in air. $(\\mathsf{N H}_{4})_{6}\\mathsf{H}_{2}\\mathsf{W}_{12}\\mathsf{O}_{40}{\\cdot}\\mathsf{x H}_{2}\\mathsf{O}$ (4.0 mmol, 11.825 g) was dissolved in $60.0\\mathrm{ml}$ ultrapure water, followed by magnetic stirring for $20\\mathrm{min}$ to obtain a homogeneous solution. The above solution was transferred into a $100\\mathrm{ml}$ autoclave and CP was placed vertically in the solution. Then, the autoclave was heated at $180^{\\circ}\\mathrm{C}$ for $16\\mathsf{h}$ . The obtained ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ was washed in deionized water and dried at $70^{\\circ}\\mathrm{C}$ overnight. \n\n# Preparation of ${\\bf W O}_{3-\\times}/{\\bf C P}$ \n\n${\\sf W O}_{3}/{\\sf C P}$ ( $1\\mathsf{c m}\\times1.5\\mathsf{c m})$ was annealed at $400^{\\circ}\\mathrm{C}$ for $2\\mathfrak{h}$ at a heating rate of $5^{\\circ}{\\bf C}/\\mathrm{min}$ in ${\\sf H}_{2}/{\\sf A}{\\sf r}$ (10/90) atmosphere to obtain ${\\mathsf{W O}}_{3\\cdot\\times}/{\\mathsf{C P}}$ . \n\n![](images/de01c86ce17bb774794c93ba57bc37863b7fa0c904dfe56a87fd84a0b48f4b29.jpg) \nFig. 6 | Illustration of hydrogen spillover. Schematic diagram showing how hydrogen spillover from $\\mathsf{w o}_{3-\\mathbf{x}}$ to Ru enhances HER in neutral environment. The white and red arrows indicate the formation process of OH and H from the dissociation of water, respectively. Black arrows indicate the transfer process of H. The \n\npurple arrow indicates the desorption of OH adsorbed on the surface. The blue, orange and green arrows indicate the different ways of formation of molecular hydrogen. \n\n# Preparation of $\\scriptstyle\\mathbf{R}\\mathbf{u}\\cdot\\mathbf{W}\\mathbf{O}_{3-\\mathbf{\\times}}/\\mathbf{C}\\mathbf{P}$ \n\n${\\mathsf{R u C l}}_{3}$ $_{(40.0\\mathrm{mg})}$ was dissolved in $20.0\\ensuremath{\\mathrm{ml}}$ deionized water by magnetic stirring and ultrasonication to obtain $2.0\\mathrm{mg/ml\\RuCl_{3}}$ solution. $\\mathsf{w o}_{3}/$ CP ( $1\\mathsf{c m}\\times1.5\\mathsf{c m})$ was immersed in $10\\mathrm{ml}2.0\\mathrm{mg/ml}\\mathrm{RuCl}_{3}$ solution for $2\\mathsf{m i n}$ . Subsequently, the ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ was taken out and dried in an infrared desiccator for $8\\mathrm{{min}}$ to obtain ${\\mathsf{R u C l}}_{3}–{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ . Finally, the ${\\mathsf{R u C l}}_{3}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ was annealed at $400^{\\circ}\\mathrm{C}$ for $2\\mathfrak{h}$ at a heating rate of $5^{\\circ}\\mathrm{C}/$ min in ${\\sf H}_{2}/{\\sf A}{\\sf r}$ (10/90) atmosphere to obtain $\\scriptstyle{\\mathsf{R u}}\\cdot{\\mathsf{W O}}_{3-\\times}/{\\mathsf{C P}}$ . \n\n# Preparation of $\\mathbf{Ru-WO_{3}/C P}$ \n\n$\\mathsf{N a B H}_{4}$ $(100.0\\mathrm{mg})$ was dissolved in 20.0 ml 1.0 M NaOH solution under magnetic stirring to obtain $5.0\\mathrm{mg/ml~\\NaBH_{4}}$ solution. ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ $(1\\mathsf{c m}\\times1.5\\mathsf{c m})$ was immersed in $10\\mathrm{ml}2.0\\mathrm{mg/ml\\RuCl_{3}}$ solution for $2\\mathsf{m i n}$ . Subsequently, the ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ was taken out and dried in an infrared desiccator for 8 min to obtain ${\\mathsf{R u C l}}_{3}–{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ . Finally, ${\\mathsf{R u C l}}_{3}.$ ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ was immersed in $5.0\\mathrm{mg/ml\\NaBH_{4}}$ solution for 10 min to obtain ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ . \n\n# Materials characterizations \n\nPower XRD patterns were recorded on a Rigaku Ultima IV $\\mathtt{C u}\\ \\mathsf{K}\\upalpha$ radiation, $\\lambda{=}1.54\\mathring\\mathrm{A}$ ) diffractometer at the operating voltage of $40\\up k\\upnu$ and current of $20\\mathrm{mA}$ . The HRTEM measurement was conducted on a JEOL JEM-2100F with a $200\\mathsf{k V}$ acceleration voltage. XPS spectra were collected on a Thermo Scientific ESCALAB 250Xi with Al $\\upkappa\\upalpha$ radiation (1486.6 eV). SEM images were taken on a Hitachi SU8010 microscope. Raman spectroscopy analysis was performed on a JY, HR 800 Raman spectrometer with a 514 nm laser. EPR experiment was conducted on a Bruker A300-10/12. Oxygen temperature programmed desorption $(0_{2}$ -TPD) analysis was performed on a BELCAT II fully automatic chemisorber instrument (MicrotracBEL). The procedures were as follows: (1) each sample was pretreated under a He flow $(50\\mathrm{ml}\\mathrm{min}^{-1})$ at $300^{\\circ}\\mathsf{C}$ for $30\\mathrm{min}.$ ; (2) the sample was purged with $5\\%0_{2}/\\mathrm{He}$ for 1 h at $50^{\\circ}\\mathrm{C}$ for $\\mathbf{O}_{2}$ adsorption; (3) the sample was heated to $700^{\\circ}\\mathrm{C}$ at a heating rate of $10^{\\circ}\\mathrm{C}\\mathsf{m i n}^{-1}$ under a pure He gas flow. The signal of $\\mathbf{O}_{2}$ desorption was measured by a thermal conductivity detector. \n\n# Electrochemical measurements \n\nAll of the electrochemical measurements were conducted on a CHI 760E electrochemical workstation (CH Instruments Ins.) in a threeelectrode system at room temperature. The geometric area of the CP is $1\\mathsf{c m}\\times1$ cm. A graphite rod electrode and a saturated calomel electrode (SCE) were used as the counter electrode and the reference electrode, respectively. The potential of SCE vs. reversible hydrogen electrode (RHE) was determined by performing CV scans (scan rate: $1\\mathrm{mV}/\\mathrm{s})$ in a hydrogen-saturated electrolyte with a Pt plate as both the working and counter electrode, and the average value of the two potentials at the current of zero in the CV curve is regarded as the potential of SCE vs. RHE. Linear sweep voltammetry (LSV) was performed at a scan rate of $2\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ after purging $\\mathsf{H}_{2}$ in the electrolyte for $20\\mathrm{min}$ . All of the potentials in LSV are iR-corrected. The resistance for iR-compensation was tested at the open circuit potential. EIS was conducted in the frequency range from $10^{5}\\mathsf{H z}$ to $10^{-3}{\\mathsf{H z}}$ . All potentials are referenced to the RHE by the Nernst equation: $E_{\\mathrm{(RHE)}}=E_{\\left({\\mathrm{SCE)}}\\right.}+0.0591\\times{\\mathrm{pH}}+0.242{\\mathrm{V}},$ unless otherwise stated. In total, $1.0\\mathsf{M}$ phosphate buffered solution (PBS) was prepared by mixing $1.0\\mathsf{M}\\mathsf{K}_{2}\\mathsf{H P O}_{4}$ with $1.0\\mathsf{M}\\mathsf{K H}_{2}\\mathsf{P O}_{4}$ in a volume ratio of 2:1. In this work, only the potentials in the Raman spectra are relative to the $\\mathbf{Ag/AgCl}$ electrode; all other potentials are relative to the RHE. \n\n# CV measurements to determine the specific capacitance \n\nAs CP has double-layer capacitance, the powders of $\\mathsf{w o}_{3}$ , $\\mathsf{w o}_{3-\\mathsf{x}}$ and ${\\mathsf{R u}}{\\cdot}{\\mathsf{W O}}_{3-\\times},$ which were peeled off from ${\\mathsf{W O}}_{3}/{\\mathsf{C P}}$ , ${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ and Ru${\\mathsf{W O}}_{3-\\mathsf{x}}/{\\mathsf{C P}}$ , were used for the CV measurements. The ink for the working electrode was prepared by dispersing $5\\mathrm{mg}$ of catalyst in a mixture of $480{\\upmu\\mathrm{l}}$ of ethanol and $20\\upmu\\upmu\\upmu$ of $5\\mathrm{wt\\%}$ Nafion solution, followed by sonication for $30\\mathrm{min}$ to obtain a homogeneous dispersion. A $10\\upmu\\mathrm{l}$ of the ink was cast on the glassy carbon electrode ( $\\cdot5\\mathsf{m m}$ of diameter) and then dried in air; the as-prepared electrode served as the working electrode. A SCE and a graphite rod electrode were used as the reference electrode and the counter electrode, respectively. All of the CV scans were performed after purging $\\mathsf{N}_{2}$ into the electrolyte for $20\\mathrm{min}$ . \n\n# In situ Raman spectroscopy measurements \n\nIn situ Raman spectra were recorded on a LabRAM HR Evolution (HORIBA Scientific) spectrometer. The electrochemical cell used for Raman measurement was homemade by Teflon and a quartz plate was employed as the window to cross the laser. A Pt wire and an $\\ensuremath{\\mathbf{A}}\\ensuremath{\\mathbf{g}}/\\ensuremath{\\mathbf{A}}\\ensuremath{\\mathbf{g}}\\ensuremath{\\mathbf{C}}\\ensuremath{\\mathbf{l}}$ electrode (1.0 M KCl as inner filling electrolyte) were applied as the counter electrode and the reference electrode, respectively. To apply a controlled potential on the catalyst during the Raman measurement, chronoamperometry was performed at various potentials in 1.0 M PBS. The illustration of operando Raman spectroscopy setup is shown in Supplementary Fig. 32. \n\n# DFT calculation \n\nDensity functional theory (DFT) calculations using the plane-wave technique were conducted in the Vienna Ab Initio Simulation Package. The exchange-correlation functional was the Perdew-Burke-Emzerhof parametrization of the generalized gradient approximation. The electron-ion interactions were described by the projector augmented wave. Van der Waals interactions were corrected by the DFT-D3 method. A plane-wave basis was set with the cutoff energy of $400\\mathrm{eV}$ . The Brillouin zone was built with a $(2\\times2\\times1)$ Monkhoest-Pack k-point mesh for all models in the optimization of the supercell structure. The force residue for relaxation of all the atoms was set as $0.02\\mathrm{eV}/\\mathring{\\mathbf{A}}$ The lattice parameter used for hexagonal $\\mathsf{w o}_{3}$ was $7.51\\mathring{\\mathrm{A}}\\times7.51\\mathring{\\mathrm{A}}\\times7.71\\mathring{\\mathrm{A}}$ $(\\mathsf{a}\\times\\mathsf{b}\\times\\mathsf{c})$ . Gibbs free energy of hydrogen adsorption was calculated by: \n\n$$\n\\Delta G_{\\mathrm{H}}=E_{\\mathrm{H/surf}}-E_{\\mathrm{surf}}-1/2E_{\\mathrm{H}2}+\\Delta E_{\\mathrm{ZPE}}-T\\Delta S_{\\mathrm{H}}\n$$ \n\nwhere $E_{\\mathrm{H/surf}}$ is the total energy of surface with adsorbate, $\\ensuremath{E_{\\mathrm{surf}}}$ is the energy of clean surface, $\\boldsymbol{E}_{\\mathrm{H}2}$ is the energy of a gas phase $\\mathsf{H}_{2}$ molecule, $\\Delta E_{Z\\mathrm{PE}}$ represents the zero-point energy of the system and was taken as 0.05 eV, and $T\\Delta S_{\\mathrm{H}}$ is the contribution from entropy and was simplified as $0.20\\mathrm{eV}$ at 298 K. In this work, the final state of the calculated $\\mathsf{H}_{2}$ is in gas phase. \n\n# Reporting summary \n\nFurther information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nThe remaining data contained within the paper and Supplementary Files are available from the authors upon request. \n\n# References \n\n1. Dresselhaus, M. & Thomas, I. Alternative energy technologies. Nature 414, 332–337 (2001). \n2. Holladay, J. D., Hu, J., King, D. L. & Wang, Y. An overview of hydrogen production technologies. Catal. Today 139, 244–260 (2009). \n3. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science 355, eaad4998 (2017). \n4. Turner, J. A. Sustainable hydrogen production. Science 305, 972–974 (2004). cycloalkanol oxidation integrated with hydrogen evolution. Chem. Eng. J. 442, 136264–136274 (2022). \n6. You, B. et al. Universal surface engineering of transition metals for superior electrocatalytic hydrogen evolution in neutral water. J. Am. Chem. Soc. 139, 12283–12290 (2017). \n7. Peng, J. et al. Recent advances in 2D transition metal compounds for electrocatalytic full water splitting in neutral media. Mater. Today Adv. 8, 100081–100097 (2020). \n8. Han, G. H. et al. Micro-nanoporous ${\\mathsf{M o O}}_{2}@{\\mathsf{C o M o}}$ heterostructure catalyst for hydrogen evolution reaction. Appl. Catal., B 270, 118895–118904 (2020). \n9. Subbaraman, R. et al. Enhancing hydrogen evolution activity in water splitting by tailoring $L i^{+}{\\mathrm{-}}N i(O H)_{2}$ -Pt interfaces. Science 334, 1256–1260 (2011). \n10. Dinh, C.-T. et al. Multi-site electrocatalysts for hydrogen evolution in neutral media by destabilization of water molecules. Nat. Energy 4, 107–114 (2019). \n11. Zhou, Z. et al. Electrocatalytic hydrogen evolution under neutral pH conditions: current understandings, recent advances, and future prospects. Energy Environ. Sci. 13, 3185–3206 (2020). \n12. Men, Y. et al. Tailoring the electronic structure of ${\\mathsf{C o}}_{2}{\\mathsf{P}}$ by N doping for boosting hydrogen evolution reaction at all pH values. ACS Catal. 9, 3744–3752 (2019). \n13. Men, Y. et al. Nitrogen-doped CoP as robust electrocatalyst for high-efficiency pH-universal hydrogen evolution reaction. Appl. Catal. B 253, 21–27 (2019). \n14. Anantharaj, S. et al. Enhancing electrocatalytic total water splitting at few layer Pt-NiFe layered double hydroxide interfaces. Nano Energy 39, 30–43 (2017). \n15. Yin, H. et al. Ultrathin platinum nanowires grown on single-layered nickel hydroxide with high hydrogen evolution activity. Nat. Commun. 6, 1–8 (2015). \n16. Wang, P. et al. Precise tuning in platinum-nickel/nickel sulfide interface nanowires for synergistic hydrogen evolution catalysis. Nat. Commun. 8, 1–9 (2017). \n17. Qin, S. et al. Ternary nickel–tungsten–copper alloy rivals platinum for catalyzing alkaline hydrogen oxidation. Nat. Commun. 12, 1–10 (2021). \n18. Lu, B. et al. Ruthenium atomically dispersed in carbon outperforms platinum toward hydrogen evolution in alkaline media. Nat. Commun. 10, 1–11 (2019). \n19. Yang, Y. et al. Hierarchical nanoassembly of $\\mathsf{M o S}_{2}/\\mathsf{C o}_{9}\\mathsf{S}_{8}/$ ${\\sf N i}_{3}{\\sf S}_{2}/{\\sf N i}$ as a highly efficient electrocatalyst for overall water splitting in a wide pH range. J. Am. Chem. Soc. 141, 10417–10430 (2019). \n20. Feng, L.-L. et al. High-index faceted $\\mathsf{N i}_{3}\\mathsf{S}_{2}$ nanosheet arrays as highly active and ultrastable electrocatalysts for water splitting. J. Am. Chem. Soc. 137, 14023–14026 (2015). \n21. Jiang, W.-J., Tang, T., Zhang, Y. & Hu, J.-S. Synergistic modulation of non-precious-metal electrocatalysts for advanced water splitting. Acc. Chem. Res. 53, 1111–1123 (2020). \n22. Khoobiar, S. Particle to particle migration of hydrogen atoms on platinum-alumina catalysts from particle to neighboring particles. J. Phys. Chem. 68, 411–412 (1964). \n23. Miu, E. V. & McKone, J. R. Comparisons of ${\\mathsf{W O}}_{3}$ reduction to ${\\sf H}_{\\sf x}\\sf W O_{3}$ under thermochemical and electrochemical control. J. Mater. Chem. A 7, 23756–23761 (2019). \n24. Prins, R. Hydrogen spillover. Facts and fiction. Chem. Rev. 112, 2714–2738 (2012). \n25. Levy, R. & Boudart, M. The kinetics and mechanism of spillover. J. Catal. 32, 304–314 (1974). \n26. Roland, U., Braunschweig, T. & Roessner, F. On the nature of spiltover hydrogen. J. Mol. Catal. A Chem. 127, 61–84 (1997). phenomenon of ctrocatalyti drogen evolution. Nat. Commun. 12, 3502–3513 (2021). \n28. Li, J. et al. Ethylene-glycol ligand environment facilitates highly efficient hydrogen evolution of Pt/CoP through proton concentration and hydrogen spillover. Energy Environ. Sci. 12, \n2298–2304 (2019). \n29. Wei, Z. W. et al. Reversed charge transfer and enhanced hydrogen spillover in platinum nanoclusters anchored on titanium oxide with rich oxygen vacancies boost hydrogen evolution reaction. Angew. Chem. Int. Ed. 133, 16758–16763 (2021). \n30. Wang, J. et al. Highly uniform Ru nanoparticles over N-doped carbon: pH and temperature-universal hydrogen release from water reduction. Energy Environ. Sci. 11, 800–806 (2018). \n31. Mahmood, J. et al. An efficient and pH-universal ruthenium-based catalyst for the hydrogen evolution reaction. Nat. Nanotechnol. 12, \n441–446 (2017). \n32. Chen, J. et al. Improving alkaline hydrogen evolution reaction kinetics on molybdenum carbide: introducing Ru dopant. J. Catal. \n392, 313–321 (2020). \n33. Chen, J., Wang, H., Gong, Y. & Wang, Y. Directly immobilizing a Ru–tannic acid linkage coordination complex on carbon cloth: an efficient and ultrastable catalyst for the hydrogen evolution reaction. J. Mater. Chem. A 7, 11038–11043 (2019). \n34. Liu, Y. et al. Ru modulation effects in the synthesis of unique rod-like Ni@Ni2P-Ru heterostructures and their remarkable electrocatalytic hydrogen evolution performance. J. Am. Chem. Soc. 140, \n2731–2734 (2018). \n35. Li, F. et al. Mechanochemically assisted synthesis of a Ru catalyst for hydrogen evolution with performance superior to Pt in both acidic and alkaline media. Adv. Mater. 30, 1803676 (2018). \n36. Qin, X. et al. The role of Ru in improving the activity of Pd toward hydrogen evolution and oxidation reactions in alkaline solutions. ACS Catal. 9, 9614–9621 (2019). \n37. Hagemann, H. & Moyer, R. O. Raman spectroscopy studies on $M_{2}R u H_{6}$ where $\\mathsf{M}=\\mathsf{C a}$ , Sr and Eu. J. Alloy. Compd. 330, \n296–300 (2002). \n38. Hagemann, H. et al. Structural and vibrational properties of ${\\mathsf{C a}}_{2}{\\mathsf{F e H}}_{6}$ and Sr2RuH6. J. Phys. Chem. Solids 72, 286–289 (2011). \n39. Jiang, H. et al. Insights on the proton insertion mechanism in the electrode of hexagonal tungsten oxide hydrate. J. Am. Chem. Soc. \n140, 11556–11559 (2018). \n40. Park, J. et al. Investigation of the support effect in atomically dispersed Pt on $\\mathsf{W O}_{3-\\mathsf{x}}$ for utilization of Pt in the hydrogen evolution reaction. Angew. Chem. Int. Ed. 58, 16038–16042 (2019). \n41. Huang, Z. H. et al. Electrical and structural dual function of oxygen vacancies for promoting electrochemical capacitance in tungsten oxide. Small 16, 2004709 (2020). \n42. Gong, H. et al. Preparation and supercapacitive property of molybdenum disulfide $(\\mathsf{M o S}_{2})$ nanoflake arrays-tungsten trioxide $(\\mathsf{W O}_{3})$ nanorod arrays composite heterojunction: a synergistic effect of one-dimensional and two-dimensional nanomaterials. Electrochim. Acta 263, 409–416 (2018). \n43. Wang, L., Liu, Y., Han, G. & Zhao, H. Controllable synthesis of hexagonal ${\\mathsf{W O}}_{3}$ nanorod-cluster films with high electrochromic performance in NIR range. J. Alloy. Compd. 890, 161833 (2022). \n44. Shen, L., Luo, G., Zheng, J. & Xu, C. Effect of pH on the electrochromic and photoluminescent properties of Eu doped ${\\mathsf{W O}}_{3}$ film. Electrochim. Acta 278, 263–270 (2018). \n45. Zheng, T. et al. Conductive tungsten oxide nanosheets for highly efficient hydrogen evolution. Nano Lett. 17, 7968–7973 (2017). \n46. Mir, R. A., Kaur, G. & Pandey, O. Facile process to utilize carbonaceous waste as a carbon source for the synthesis of low cost electrocatalyst for hydrogen production. Int. J. Hydrog. Energy 45, \n23908–23919 (2020). \n47. Malakzadeh, M., Raoof, J. B., Ghafarnejad, A. & Ojani, R. In-situ electrosynthesis Cu-PtBTC MOF-derived nanocomposite modified glassy carbon electrode for highly performance electrocatalysis of hydrogen evolution reaction. J. Electroanal. Chem. 900, 115716 (2021). \n48. Pan, J. et al. A high-performance electrochromic device assembled with hexagonal ${\\mathsf{W O}}_{3}$ and NiO/PB composite nanosheet electrodes towards energy storage smart window. Sol. Energy Mater. Sol. Cells 207, 110337 (2020). \n49. Liang, J. et al. Nano ${\\mathsf{W O}}_{3}$ -catalyzed one-pot process for mild oxidative depolymerization of lignin and its model compounds. ChemCatChem 13, 3836–3845 (2021). \n50. Kim, H.-S. et al. Oxygen vacancies enhance pseudocapacitive charge storage properties of $\\mathsf{M o O}_{3\\cdot\\mathsf{x}}$ . Nat. Mater. 16, 454–460 (2017). \n51. Wang, J., Polleux, J., Lim, J. & Dunn, B. Pseudocapacitive contributions to electrochemical energy storage in $\\mathsf{T i O}_{2}$ (anatase) nanoparticles. J. Phys. Chem. C. 111, 14925–14931 (2007). \n52. Paulsen, A. L., Kalampounias, A. G., Berg, R. W. & Boghosian, S. Raman spectroscopic study of tungsten (VI) oxosulfato complexes in $\\mathsf{W O}_{3}–\\mathsf{K}_{2}\\mathsf{S}_{2}\\mathsf{O}_{7}–\\mathsf{K}_{2}\\mathsf{S}\\mathsf{O}_{4}$ molten mixtures: stoichiometry, vibrational properties, and molecular structure. J. Phys. Chem. A 115, 4214–4222 (2011). \n53. Xie, C. et al. In-situ phase transition of ${\\mathsf{W O}}_{3}$ boosting electron and hydrogen transfer for enhancing hydrogen evolution on Pt. Nano Energy 71, 104653–104660 (2020). \n54. Mitchell, J. B. et al. Transition from battery to pseudocapacitor behavior via structural water in tungsten oxide. Chem. Mater. 29, 3928–3937 (2017). \n55. Chen, W. et al. Activity origins and design principles of nickel-based catalysts for nucleophile electrooxidation. Chem 6, 2974–2993 (2020). \n56. Lu, Y. et al. Identifying the geometric site dependence of spinel oxides for the electrooxidation of 5-hydroxymethylfurfural. Angew. Chem. Int. Ed. 59, 19215–19221 (2020). \n\n# Acknowledgements \n\nWe are grateful for the financial support from the National Key R&D Program of China (2021YFB3801600), the National Natural Science Foundation of China (21872121, 21908189), the Fundamental Research Funds for the Central Universities (2017XZZX002−16), Ministry of Education of Singapore (Tier 1: RG4/20 and Tier 2: MOET2EP10120-0002), and Agency for Science, Technology and Research (AME IRG: A20E5c0080). \n\n# Author contributions \n\nY.W. and B.L. conceived the study. J.C., C.C. and M.Q. designed the experiment and performed the initial tests. J.C., Q.M., B.Lin, B.Li and H.Y. conducted the theoretical calculations. J.C., C.C. and M.Q. wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at \nhttps://doi.org/10.1038/s41467-022-33007-3. \n\nCorrespondence and requests for materials should be addressed to Bin Liu or Yong Wang. \n\nPeer review information Nature Communications thanks Arik Beck and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1038_s41467-022-28995-1", + "DOI": "10.1038/s41467-022-28995-1", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-28995-1", + "Relative Dir Path": "mds/10.1038_s41467-022-28995-1", + "Article Title": "Protruding Pt single-sites on hexagonal ZnIn2S4 to accelerate photocatalytic hydrogen evolution", + "Authors": "Shi, XW; Dai, C; Wang, X; Hu, JY; Zhang, JY; Zheng, LX; Mao, L; Zheng, HJ; Zhu, MS", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "An alternative approach to defect-trapped Pt single-sites on a semiconductor is reported. Here, protruding Pt sites inhibit charge recombination and cause a tip effect which enhances H-2 evolution yield rates with minimal co-catalyst loading. Single-site cocatalysts engineered on supports offer a cost-efficient pathway to utilize precious metals, yet improving the performance further with minimal catalyst loading is still highly desirable. Here we have conducted a photochemical reaction to stabilize ultralow Pt co-catalysts (0.26 wt%) onto the basal plane of hexagonal ZnIn2S4 nullosheets (Pt-SS-ZIS) to form a Pt-S-3 protrusion tetrahedron coordination structure. Compared with the traditional defect-trapped Pt single-site counterparts, the protruding Pt single-sites on h-ZIS photocatalyst enhance the H-2 evolution yield rate by a factor of 2.2, which could reach 17.5 mmol g(-1) h(-1) under visible light irradiation. Importantly, through simple drop-casting, a thin Pt-SS-ZIS film is prepared, and large amount of observable H-2 bubbles are generated, providing great potential for practical solar-light-driven H-2 production. The protruding single Pt atoms in Pt-SS-ZIS could inhibit the recombination of electron-hole pairs and cause a tip effect to optimize the adsorption/desorption behavior of H through effective proton mass transfer, which synergistically promote reaction thermodynamics and kinetics.", + "Times Cited, WoS Core": 356, + "Times Cited, All Databases": 363, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000767892300022", + "Markdown": "# Protruding Pt single-sites on hexagonal ZnIn2S4 to accelerate photocatalytic hydrogen evolution \n\nXiaowei Shi1, Chao Dai1, Xin Wang1, Jiayue ${\\mathsf{H}}{\\mathsf{u}}^{2}.$ , Junying Zhang 3, Lingxia Zheng1, Liang Mao 4✉ Huajun Zheng 1✉ & Mingshan Zhu 2✉ \n\nSingle-site cocatalysts engineered on supports offer a cost-efficient pathway to utilize precious metals, yet improving the performance further with minimal catalyst loading is still highly desirable. Here we have conducted a photochemical reaction to stabilize ultralow $\\mathsf{P t}$ co-catalysts $(0.26\\mathrm{wt\\%})$ onto the basal plane of hexagonal $Z n|n_{2}S_{4}$ nanosheets $(P\\mathsf{t}_{\\mathsf{S S}}–Z|\\mathsf{S})$ to form a $P t-S_{3}$ protrusion tetrahedron coordination structure. Compared with the traditional defect-trapped $\\mathsf{P t}$ single-site counterparts, the protruding $\\mathsf{P t}$ single-sites on $h$ -ZIS photocatalyst enhance the ${\\sf H}_{2}$ evolution yield rate by a factor of 2.2, which could reach 17.5 mmol g $^{-1}{\\mathsf h}^{-1}$ under visible light irradiation. Importantly, through simple drop-casting, a thin $\\mathsf{P t}_{\\mathsf{S S}^{-}}\\mathsf{Z}|\\mathsf{S}$ film is prepared, and large amount of observable ${\\sf H}_{2}$ bubbles are generated, providing great potential for practical solar-light-driven ${\\sf H}_{2}$ production. The protruding single Pt atoms in $\\mathsf{P t}_{\\mathsf{S S}^{-}}$ ZIS could inhibit the recombination of electron-hole pairs and cause a tip effect to optimize the adsorption/desorption behavior of H through effective proton mass transfer, which synergistically promote reaction thermodynamics and kinetics. \n\nW ater splitting for hydrogen $\\left(\\operatorname{H}_{2}\\right)$ generation through solar light has attracted increasing attention since it supplies a significant carbon-neutral technology for zero-emission renewable energy evolution. The design of a photocatalyst with high efficiency and long durability is a focused task for researchers to scale up $\\mathrm{H}_{2}$ evolution reaction (HER) in the past decades1. Two-dimensional (2D) hexagonal $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ ( $h$ -ZIS), a typical ternary chalcogenide with favorable H adsorption features at edge S atom in (110) facet $(\\Delta G_{\\mathrm{H}}^{*}=-0.16\\mathrm{eV})$ and robust resistance to photocorrosion, has been regarded as a promising candidate for photocatalytic water splitting2–6. The current guiding principles for advancing the catalytic performance of $h$ - ZIS are as follows. First, increase the active site density in $h$ -ZIS through preferentially exposing the edge sites6,7. Unfortunately, unleashing the intrinsically high activity of $h$ -ZIS is still retarded by the severe recombination of electron-hole pairs, where only a small quantity of electrons could survive at the active sites. Second, create in-plane sulfur vacancies or dope metallic heteroatoms to substitute Zn atoms7–10. The lifetime of photoexcited electrons is prolonged, and the basal-plane S atoms in those $h$ -ZIS are also stimulated as centers for HER; however, these S sites suffer from less favorable hydrogen adsorption features $(\\Delta G_{\\mathrm{H}}^{*}=-0.25\\mathrm{eV})$ despite the increased site density9. Apparently, $h$ -ZIS only becomes applicable toward photocatalytic HER when the rapid carrier recombination and limited active site obstacles are simultaneously overcome. \n\nAs a lamellar material, the basal plane of $h$ -ZIS provides plenty of platforms for noble-metal nanoparticles loading, especially platinum $\\left(\\mathrm{Pt}\\right)$ , while the scarcity and high cost of the noble-metal co-catalysts tremendously inhibit their large-scale implementation2,11–13. Alternatively, single-site co-catalysts (SSCs) emerge as a frontier for catalysis science due to their high atom efficiency and outstanding activity14,15. The strong metal-support interaction caused by metal atoms and coordinated atoms would affect the charge distributions and introduce the electronic structure modifications, which influence the electron-hole pairs recombination and the adsorption behavior during the catalytic process, and eventually change their catalytic activity and selectivity16–19. One of the effective strategies for advanced SSCs is to produce more active sites through increasing metal loading with no aggregation, and accordingly, several Pt single-site $(\\mathrm{Pt}_{\\mathrm{SS}})$ -based photocatalysts (Pt loading with $8.7\\mathrm{wt\\%}^{20}$ or $12.0\\mathrm{wt\\%}^{21}.$ ) have exhibited exciting $\\mathrm{H}_{2}$ evolution rate and observable bubbles under visible light irradiation. For practical applications, achieving maximum catalytic performance with minimal noblemetal atoms is essentially required. Recently, Pt SSCs supported on highly curved substrates were successfully prepared as electrocatalyst to mimic the metal sites at the edges and corners of particles22. Owing to the accumulation of electrons around $\\mathrm{Pt}$ regions triggered by the tip effect, an accelerated HER kinetics was achieved. Principally, the generation of tip enhancement is biased onto curvaturerich configurations (typically corner, vertex, or protrusion)23. To this end, direct anchoring $\\mathrm{Pt}~\\mathrm{SSCs}$ onto $h$ -ZIS nanosheets might be an effective approach to form tridimensional protrusion that could produce high- and cost-efficient photocatalysts for HER. \n\nIn this work, a photochemical route was employed to synthesize $h$ -ZIS with Pt single sites $(\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{ZIS})^{24}$ . The light-induced reaction is more moderate and controllable than traditional annealing methods, so the structure of $h$ -ZIS could be well preserved without generating any vacancy defects. During photochemical processes, $\\mathrm{PtCl}_{6}\\tilde{2}-$ ions were reduced and concurrently immobilized on the basal plane of $h$ -ZIS nanosheets, forming $\\mathrm{Pt}{-}S_{3}$ tetrahedron coordination structure with surrounding S atoms. Experiments and simulations jointly manifest that the atomically dispersed Pt atoms could serve as sinks to facilitate the separation of photoexcited electron-hole pairs as well as active centers to enhance the HER performance through the accelerating catalytic kinetics. As a result, the synergetic effect of atomic-level $\\mathrm{Pt}$ and $h$ -ZIS produces a higher photocatalytic activity for $\\mathrm{H}_{2}$ evolution, where the activity outperforms that of defect-trapped $\\mathrm{Pt}$ single-site counterpart. In addition, a thin film of $\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{Z}\\bar{\\mathrm{I}}\\bar{\\mathrm{S}}$ on the solid substrate could readily be achieved through a drop-casting approach, and a large amount of $\\mathrm{H}_{2}$ bubbles are generated during light irradiation (Supplementary Movies 1 and 2). \n\n# Results \n\nStructure analysis and characterization. Ultrathin $h$ -ZIS nanosheets with thickness ranging from 2.46 to $4.94\\mathrm{nm}$ were prepared by a hydrothermal method (Supplementary Fig. $1)^{9}$ . $\\bar{\\mathrm{H}}_{2}\\bar{\\mathrm{PtCl}}_{6}$ aqueous solution was introduced into $h$ -ZIS dispersion with magnetic stirring. The interfacial charges of $h$ -ZIS and $\\mathrm{Pt}$ species $\\mathrm{(\\bar{H}P t C l}_{6}-$ or $\\mathsf{\\bar{P}t C l}_{6}{}^{2-})$ were opposite, so they would be spontaneously assembled through electrostatic interaction in the solution, with $\\mathrm{Pt}$ -ZIS mixture generated (Supplementary Fig. 2). After irradiation under visible light for $60\\mathrm{min}$ , Pt sites were immobilized on $h$ -ZIS, and the mixture was centrifuged and collected (see the Experimental Section and Supplementary Fig. 3). By alerting the volume of added ${\\mathrm{H}}_{2}{\\mathrm{PtCl}}_{6}{\\mathrm{:}}$ , Pt loading content could be tuned, as quantified by the inductively coupled plasma optical emission spectroscopy (ICP-OES) analysis (Supplementary Table 1). Additionally, the molar ratio of $Z\\mathrm{n}$ and In in $\\operatorname*{Pt}_{0.3}$ -ZIS was calculated to be 0.225:0.451, which is consistent with the theoretical molar ratio of 1:2. \n\n$\\mathrm{\\DeltaX}$ -ray diffraction (XRD) patterns and Raman spectra with negligible changes are observed between $h$ -ZIS and $\\mathrm{\\Pt}$ -ZIS, suggesting that Pt atoms incorporation does not destroy the crystal structure of $h$ -ZIS (Supplementary Fig. 4). Transmission electronmicroscopy (TEM) and high-resolution TEM (HRTEM) images in Supplementary Fig. 5 depict a sheet-like structure of $h$ - ZIS and the lattice fringe of $0.41\\mathrm{nm}$ corresponds to the (006) facet. After $\\mathrm{Pt}$ deposition, the obtained $\\mathrm{Pt}$ -ZIS nanosheets maintain the thickness $(3.10-5.11\\mathrm{nm})$ of pristine $h$ -ZIS recorded by atomic force microscope (AFM) (Supplementary Figs. 6 and 7). As shown in TEM and HRTEM images, no $\\mathrm{Pt}$ nanoparticles are observed with $\\mathrm{Pt}$ loading content in the range of $0.1\\mathrm{-}1.4\\mathrm{wt}\\%$ , and the energy-dispersive X-ray spectroscopy (EDS) also exhibits homogeneous dispersion of $\\mathrm{Pt}$ on $h$ -ZIS nanosheets without any aggregation (Fig. 1a–d and Supplementary Figs. 8–10). When further increasing the Pt amount to $3.0\\mathrm{wt\\%}$ , nanoparticles were formed, which is proved by the green circles and corresponding EDS spectrum (Supplementary Fig. 11). In addition, the lattice fringe of 0.293 and $0.196\\mathrm{nm}$ attribute to the $h$ -ZIS (104) and Pt (200) facet, respectively. To reveal the configuration of Pt cocatalyst on $h$ -ZIS nanosheets, aberration-corrected high angle annular dark field STEM (HAADF-STEM) measurements were carried out on $h$ -ZIS and $\\mathrm{Pt}_{0.3}$ -ZIS. Since the contrast in HAADFSTEM image is proportional to the square of atomic number, $\\mathrm{Pt}$ is much brighter than $Z\\mathrm{n}$ , In, and S atoms, and the atomically dispersed bright spots (circled) in Fig. 1e and Supplementary Fig. 12 confirm the formation of single Pt atoms25. On the contrary, no bright spots could be observed in $h$ -ZIS, and the cross-sectional profiles of atom contrast show almost identical intensity (Supplementary Fig. 13). As a result, the cross-sectional intensity in Fig. 1f and g, together with the ICP-OES results and electron spin resonance (ESR) spectra (Supplementary Fig. 14), directly identify that Pt SSCs exist, not as interior dopants substituting for $Z\\mathrm{n}$ or In in $h$ -ZIS skeletons, but as external adatoms conjugating with $h$ -ZIS to engender tridimensional protrusions, different from extensively reported planar geometry of metal- $\\mathbf{\\cdotN_{x}-}$ and defect-trapped- $\\mathsf{S S C s}^{'13,2\\bar{6}}$ . To illustrate the exact position of $\\mathrm{Pt}$ single sites, density functional theory (DFT) \n\n![](images/5d01198aef38f551ff0a1c6ea4b969cb1c0bc3689c3fd8d72a50c152d2648e68.jpg) \nFig. 1 Structural characterization of $p t_{0.3}\\mathbf{-}\\mathbf{Z}\\mathbf{l}\\mathbf{S},$ . a TEM image of $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . b, c HRTEM image of $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . d Elemental mapping of $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . The scale bars are $50\\mathsf{n m}$ . e HAADF-STEM image of $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . f Magnified HAADF-STEM image of $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . g Strength profiles from the areas labeled by green line. h Optimized structure of $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . The yellow, gray, pink, and green spheres represent the S, Zn, In, and Pt atom, respectively. i Simulated HAADF-STEM image of $\\mathsf{P t}_{\\mathsf{S S}^{-}}\\mathsf{Z l S}$ according to DFT-optimized structure. \n\ncalculations were carried out to determine the energies of $\\mathrm{\\Pt}$ atoms on various sites. Six different locations were established, including $Z\\mathrm{n-S}$ hollow site, $Z\\mathrm{n}$ atop, S atop on $Z\\mathrm{n-S}$ plane, In-S hollow site, In atop, and S atop on In-S plane, respectively, and $Z\\mathrm{n-S}$ hollow site with the largest adsorption energy is confirmed to be the most stable location for Pt atom occupation (Supplementary Figs. 15–17). The distribution of $\\mathrm{Pt}$ atoms on $h$ -ZIS and their propensity to agglomerate was also examined by calculating the energy difference between an isolated $\\mathrm{Pt}$ atom and a Pt dimer $(\\Delta E_{\\mathrm{d}})$ , in which the total energy of the isolated configuration was used as reference energy. As shown in Supplementary Fig. 18, it is more favorable for the Pt atoms to be isolated at $Z\\mathrm{n-S}$ hollow site due to the positive $\\Delta E_{\\mathrm{d}}$ of $2.03\\mathrm{eV}$ , which fully supports the experimental observations of the $\\mathrm{Pt}$ single atom in $\\mathrm{Pt}_{0.3}$ -ZIS. Based on the DFT-optimized structure, a STEM simulation on Pt SSCs dispersed $h$ -ZIS was performed. The simulated result is in good agreement with the experimental HAADF-STEM image, demonstrating that $\\mathrm{Pt}$ single sites prefer to chemisorb above the Zn-S hollow site in $h$ -ZIS basal plane (Fig. 1h and i). \n\nElectronic states of atoms in Pt-ZIS. Elemental composition and chemical states of $\\mathrm{\\Pt}$ -ZIS were characterized by $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS). The high-resolution $Z\\mathrm{n}~2p$ and In $3d$ XPS peaks corresponding to $h$ -ZIS, $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ , and $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ exhibit little shift (Supplementary Fig. 19). The S $2p$ spectrum for $h$ -ZIS shows two peaks at 161.8 and $163.0\\mathrm{eV}$ , respectively. After loading Pt single sites, a blue-shift of ${\\sim}0.4\\mathrm{eV}$ in $\\mathrm{Pt}_{0.3^{-}}\\mathrm{ZIS}$ is observed, indicating that the electrons are transferred from $\\mathrm{Pt}$ to $h$ -ZIS and enriched around S atom. This also proves that the decoration of $\\mathrm{Pt}$ single atoms would modulate the electronic structures of $h$ -ZIS (Fig. 2a)20,27. With the increasing amount of $\\mathrm{Pt}$ to $3.0\\mathrm{wt\\%}$ , a smaller blue-shift of about $0.3\\mathrm{eV}$ is detected. For the $\\operatorname*{Pt}4f$ spectra, $\\mathrm{Pt/C}$ exhibits three peaks at 71.90, 71.77, and $73.19\\mathrm{eV}$ , which correspond to the $\\bar{\\mathrm{Pt^{0}}}$ , $\\mathrm{Pt}^{2+}$ , and $\\mathrm{Pt^{4+}}$ state, respectively (Fig. 2b)16. In contrast, the $\\mathrm{Pt}_{0.3}$ -ZIS mainly contains $\\mathrm{Pt}^{\\delta^{\\star}+}$ species $(72.10\\mathrm{eV})$ , revealing the formation of a higher coordination number with the Pt–S bonds than the $\\mathrm{Pt-Pt}$ bonds28–30. Interestingly, both $\\mathrm{Pt^{0}}$ and $\\mathrm{Pt}^{\\delta+}$ peaks appear in the spectrum of $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ (70.90 and $72.09\\mathrm{eV}.$ , which is probably owing to the well-constructed both Pt single atoms and nanoparticles29. The detailed information for XPS fits is listed in Supplementary Tables 2–5. \n\nFurthermore, X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure spectroscopy (EXAFS) were conducted to investigate the local atomic structure and electronic environment of $\\mathrm{Pt}$ species in $\\mathrm{Pt}$ -ZIS. EXAFS results in Fig. 2c show $k^{2}$ -weighted Fourier transforms from the Pt $\\mathrm{L}_{3}$ - edge EXAFS oscillations of $\\mathrm{Pt}_{1.4}$ -ZIS and $\\mathrm{Pt}_{3.0}$ -ZIS in comparison to that of Pt foil and $\\mathrm{PtO}_{2}$ $k^{2}$ -weighted $\\chi(\\boldsymbol{k})$ signals in Supplementary Fig. 20). The only prominent shell in $\\mathrm{Pt}_{1.4}$ -ZIS locating at near $2.\\overset{\\sim}{0}\\mathrm{\\AA}$ without any $\\mathrm{Pt-Pt}$ contribution in the range of $2{-}3\\mathrm{\\AA}$ testifies the atomically dispersed $\\mathrm{Pt}$ on $h{-}Z\\mathrm{IS}^{17,\\tilde{29}}$ , whereas an additional peak at about $\\dot{2}.6\\mathring{\\mathrm{A}}$ arises in $\\mathrm{Pt}_{3.0}$ -ZIS, closing to that of $\\mathrm{Pt-Pt}$ contribution. To gain visual illustrations of $\\mathrm{Pt}$ coordination conditions, wavelet transform (WT) of the $k^{2}$ - weighted EXAFS spectra, a reflection of structure information in the resolution of $R$ space and $K$ space, are shown in Fig. 2d. $\\mathrm{Pt}_{1.4^{-}}$ ZIS exhibits the maximum WT intensity at $1.8{-}2.1\\mathring\\mathrm{A}$ in $R$ space and $3{-}6\\mathring{\\mathrm{A}}$ in $k$ space, ascribing to $\\mathrm{Pt}{-}S$ bond in the first coordination shell31,32. While a new WT intensity maximum near $2.5{-}2.8\\mathring\\mathrm{A}$ and $9{-}11\\mathring{\\mathrm{A}}$ suggests the coexistence of $\\mathrm{Pt}{-}S$ and $\\mathrm{\\Pt{-}P t}$ bonds in $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ . The Fourier-transform EXAFS curves and the corresponding fitting results in Supplementary Fig. 21 and Supplementary Table 6 give the $\\mathrm{Pt}{-}\\bar{\\mathsf{S}}$ coordination number of 2.6 for $\\mathrm{Pt}_{1.4}–\\mathrm{ZIS}$ , implying a similar coordination condition of $\\mathrm{Pt}{-}{\\cal S}_{3}$ in $\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{ZIS}$ as depicted by HAADF-STEM image and DFT simulations. The XANES spectra of $\\mathrm{Pt}~\\mathrm{L}_{3}$ -edge show that the white-line intensity of $\\mathrm{Pt}_{1.4}$ -ZIS is lower than that of $\\mathrm{PtO}_{2}$ , but higher than that of $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ and $\\mathrm{Pt}$ foil, demonstrating the Pt atoms are in an oxidation state originating from covalent $\\mathrm{Pt}{-}S$ bonds, which is consistent with XPS results (Supplementary Fig. 22)19. \n\n![](images/4741bf76d7c29a1ab56d6a07a92858eed692480ac13a7afd4852ff5a8bc0cec2.jpg) \nFig. 2 Electronic states of atoms in photocatalysts. a High-resolution XPS spectra $(\\mathsf{S}2p)$ of $h$ -ZIS, $\\mathsf{P t}_{3.0^{-}}Z|\\mathsf{S}$ , and $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . b High-resolution $\\mathsf{X P S}$ spectra (Pt 4f) of $\\mathsf{P t/C}$ , $\\mathsf{P t}_{3.0^{-}}\\mathsf{Z}|\\mathsf{S},$ and $\\mathsf{P t}_{0.3}–Z\\mathsf{l S}$ . c Fourier transform of $k^{2}$ -weighted Pt $\\mathsf{L}_{3}$ -edge of the EXAFS spectra for Pt foil, $\\mathsf{P t O}_{2},$ $\\mathsf{P t}_{1.4}\\mathrm{-}\\mathsf{Z}|\\mathsf{S},$ and $\\mathsf{P t}_{3.0^{-}}\\mathsf{Z l S}$ . d Wavelet transform for the $k^{2}$ -weighted EXAFS spectra of $\\mathsf{P t}$ foil, $\\mathsf{P t O}_{2},$ $\\mathsf{\\Pi}_{2},\\mathsf{P t}_{1.4}\\mathrm{-}\\mathsf{Z}|\\mathsf{S},$ and $\\mathsf{P t}_{3.0^{-}}\\mathsf{Z}|\\mathsf{S}.$ R is the interatomic distance. FTIR spectra of CO adsorbed after the desorption processes for e $h$ -ZIS, $\\textsf{f P t}_{0.3}–Z|\\mathsf{S},$ and $\\pmb{\\mathrm{g}}\\mathsf{P t}_{3.0^{-}}\\mathsf{Z}|\\mathsf{S}$ . \n\nMoreover, we investigated the CO adsorption behavior on different photocatalysts using Fourier-transform infrared (FTIR) spectroscopy to provide additional information about the dispersion and chemical state of $\\mathrm{Pt}$ (Fig. 2e–g). For $\\mathrm{Pt}_{0.3}–Z\\mathrm{IS}.$ only a weak vibration band appears at $2093\\mathrm{cm}^{-1}$ corresponding to CO adsorption on $\\mathrm{Pt}^{\\delta+33,\\hat{34}}$ . While the adsorption of CO also produces a strong vibration band at $2033\\mathrm{cm}^{-1}$ and another weak band at $1961\\mathrm{cm}^{-1}$ for $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ . The main band at $2033\\mathrm{cm}^{-1}$ can be ascribed to linearly bonded CO on $\\mathrm{Pt^{0}}$ sites, and the band at $1961\\mathrm{cm}^{-1}$ is caused by CO adsorbed on the interface between Pt clusters and the support33. All these characterizations provide compelling evidence that our protocol affords $\\mathrm{Pt}_{0.3}–Z\\mathrm{IS}$ with only positively charged Pt single atoms, while $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ with both single atoms and $\\mathrm{Pt}$ nanoparticles. \n\nPhotocatalytic $\\mathbf{H}_{2}$ evolution performances. With protrusionshaped SSCs in hand, we next explored their photocatalytic HER activities in an aqueous solution with $10\\mathrm{vol}\\%$ triethanolamine (TEOA) as the sacrificial agent under visible light $(\\lambda>420\\mathrm{nm})$ ) irradiation. According to Fig. 3a, all $\\mathrm{\\Pt}$ -loaded $h$ -ZIS photocatalysts exhibit higher $\\mathrm{H}_{2}$ evolution performance than the counterpart $h$ -ZIS: $19.67\\upmu\\mathrm{mol}\\mathrm{h}^{-1}$ with $20\\mathrm{mg}$ photocatalyst). The optimized rate $(350.1\\upmu\\mathrm{mol}\\mathrm{h}^{-1})$ is acquired at $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS},$ which is about 17.8 times enhanced than that of pristine $h$ -ZIS. When Pt loading content exceeds $0.3\\mathrm{wt\\%}$ , the activity experiences a decrease, and the catalytic efficiency of each $\\mathrm{\\Pt}$ site is reduced (Supplementary Fig. 23). In addition, $h$ -ZIS with sulfur vacancies $(\\bar{h}{-}\\bar{Z}\\mathrm{IS-}\\mathrm{V}_{\\mathrm{S}})$ was synthesized through the treatment of $\\mathrm{NaBH_{4}}$ in a water bath. Benefiting from the existence of localized states caused by sulfur vacancies, $h$ -ZIS- ${\\bf\\nabla}\\cdot{\\bf V_{S}}$ performs a narrower bandgap $(2.66\\mathrm{eV})$ and a longer average fluorescence lifetime (5.86 ns) than $h$ -ZIS $(2.79\\mathrm{e}\\bar{\\mathrm{V}}$ and 3.02 ns) (Supplementary Figs. 24 and 25). As a result, the photocatalytic activity of $h$ -ZIS is enhanced after creating sulfur vacancies. Then $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS–V}_{\\mathrm{S}}$ $(0.28\\mathrm{wt\\%}$ Pt) was also prepared by the same photochemical procedure (Supplementary Fig. 26). The obviously decreased ESR signal of $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS–V}_{\\mathrm{S}}$ and the calculated adsorption energy reveal that $\\mathrm{Pt}$ single atoms incline to be trapped at defect sites rather than protrude out of $h{\\mathrm{-}}Z{\\mathrm{IS-V}}_{\\mathrm{S}}$ surface (Supplementary Figs. 26, 27). The recorded $\\mathrm{H}_{2}$ generation rate for $\\mathrm{\\bar{P}t_{0.3}-Z I S-\\bar{V}_{S}}$ is only about half of that for $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ (Fig. 3b). These results imply that the excellent catalytic activity of $\\mathrm{Pt}_{0.3}$ -ZIS could be mainly attributed to the protrusion-like Pt species on 2D $h$ -ZIS. Similar to the trend of visible light, $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ also displays a boosted activity under simulated solar light with a total $\\mathrm{H}_{2}$ generation of $3504\\mathrm{\\upmumol}$ within $6\\mathrm{h}$ , whereas only $245.7\\ \\upmu\\mathrm{mol}\\ \\mathrm{H}_{2}$ is formed by $h$ -ZIS (Supplementary Fig. 28). Additionally, $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ could introduce acceptable HER performance even in pure water and the $\\mathrm{H}_{2}$ evolution rate is ${\\bar{\\sim}}24.04\\ \\upmu\\mathrm{mol}\\ \\mathrm{h}^{-1}$ $(120\\dot{2}\\upmu\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{g}^{-1})$ under visible light irradiation (Supplementary Fig. 29). Dependence of apparent quantum efficiency (AQE) at each wavelength for $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ derived from the amount of generated $\\mathrm{H}_{2}$ was estimated by various band-pass filters (Fig. 3c and Supplementary Table 7). The AQE matches well with the absorption spectrum of $\\mathrm{Pt}_{0.3}–Z\\mathrm{IS}$ , and reaches up to $50.4\\%$ at $420\\mathrm{nm}$ . Experiments in dark or without photocatalysts show no $\\mathrm{H}_{2}$ evolution, demonstrating that $\\mathrm{H}_{2}$ is generated by the photocatalysis processes. Such high AQE and catalytic HER activity of $\\mathrm{Pt}_{0.3}$ -ZIS is far beyond the majority of representative photocatalysts (details see the comparisons in Fig. 3d and Supplementary Table 8). Furthermore, $\\bar{\\mathrm{Pt}}_{0.3}$ -ZIS almost maintains its photocatalytic $\\mathrm{H}_{2}$ evolution rate at the initial level after continuous irradiation for $50\\mathrm{h}$ (Fig. 3e). The characterizations including XRD, XPS, TEM, and HAADFSTEM, demonstrate that the structures undergo negligible changes, manifesting high stability of $\\mathrm{Pt}_{0.3}$ -ZIS (Supplementary Figs. 30–33). \n\n![](images/11b3fac52a832b54c855eff9d7c6c9515d0d5d459bedb6ee8fa51b323f68f980.jpg) \nFig. 3 Evaluation of photocatalytic HER performances. a Visible light $(\\lambda>420\\mathsf{n m})$ photocatalytic ${\\sf H}_{2}$ evolution activities of $h$ -ZIS and Pt-ZIS with different Pt loading content. b Visible light $(\\lambda>420\\mathsf{n m})$ photocatalytic ${\\sf H}_{2}$ evolution activity of $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ in comparison with $h$ -ZIS, $h{-}Z|\\mathsf{S-}\\mathsf{V}_{\\mathsf{S}},$ and $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}\\mathrm{-}\\mathsf{V}_{\\mathsf{S}}$ . c Wavelength dependence of the AQE for $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . d ${\\sf H}_{2}$ evolution rates for $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ in this work compared with representative recently reported photocatalysts. e Cycling stability test of $\\mathsf{P t}_{0.3}$ -ZIS. f, $\\pmb{\\mathsf{g}}$ Digital photograph of ${\\sf H}_{2}$ evolution using $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ film without and with visible light irradiation. \n\nDue to its outstanding performance, we dispersed $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ into ethanol solution and then drop-casted onto FTO substrate $(1.5\\times2\\mathrm{cm}^{2})$ to form a thin film ( ${\\langle}{\\sim}3\\upmu\\mathrm{m}$ thick) with excellent transmittance (Supplementary Figs. 34 and 35). As a proof-ofconcept, the resultant $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ film was employed as a photocatalyst for $\\mathrm{H}_{2}$ production. No $\\mathrm{H}_{2}$ is generated before irradiation, while small $\\mathrm{H}_{2}$ bubbles start to appear continuously when turning on the light (Fig. 3f, $\\mathbf{g}$ and Supplementary Movies 1, 2). The $\\mathrm{H}_{2}$ generation rate over the film achieves as high as $0.967\\mathrm{Lh}^{-1}\\mathbf{\\bar{\\phi}}_{\\mathrm{m}^{-2}}^{}$ $(43.17\\mathrm{mmol}\\mathrm{h}^{-1}\\mathrm{m}^{-2})$ under visible light irradiation, outperforming numerous recent reported photocatalysis films, such as $\\mathrm{C}_{3}\\mathrm{N}_{4}$ film $\\mathrm{(0.19Lh^{-1}~m^{-2})}$ and $\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{MOF}$ $(\\dot{0}.398\\mathrm{Lh}^{-1}\\mathrm{m}^{-2})$ , which dictates an enormous potential for real applications21,35. \n\nInsight of the increased photocatalytic activity. To shed light on the origin of enhanced activity, three elementary processes in photocatalysis HER, namely light absorption, charge separation, and interfacial $\\mathrm{H}_{2}$ catalysis, are taken into consideration. The optical absorption properties were examined by ultraviolet-visible (UV-vis) diffuse reflectance spectra. An absorption edge at around $440\\mathrm{nm}$ corresponding to the bandgap of about $2.85\\mathrm{eV}$ , is observed for $\\mathrm{Pt}_{0.3}$ -ZIS. It is slightly larger than that of pristine $h$ - ZIS $(2.79\\mathrm{eV})$ , revealing a blue-shift absorption edge of $h$ -ZIS upon $\\mathrm{Pt}$ stabilizing (Fig. 4a and b). These results are similar to those achieved from the photocurrent action spectra of different photocatalysts film electrodes (Supplementary Fig. 36). Even though the light absorption is enhanced in the visible range with further increasing the amount of $\\mathrm{Pt}$ $\\mathrm{(Pt}_{3.0}–Z\\mathrm{IS)}$ , the measured photocurrent action spectrum of $\\mathrm{Pt}_{3.0}–\\mathrm{ZIS}$ is quite different from its UV-vis absorbance, in which there is almost no photocurrent at $500\\mathrm{nm}$ . Additionally, the AQE of $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ was also recorded (Supplementary Fig. 37 and Table S7). Consistent with the photocurrent action, the AQE of $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ does not follow well with the UV-vis spectrum and only a little amount of $\\mathrm{H}_{2}$ is generated at $500\\mathrm{nm}$ . Considering that the $\\mathrm{Pt}$ colloids exhibit broadband optical absorption from ultraviolet to the visible light region, we can conclude that $\\mathrm{Pt}$ nanoparticles formed in $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ could extend the light absorption, but have limited contributions to the photocatalytic performances of $h{-}Z\\mathrm{IS}^{36}$ . The digital images demonstrate an obvious color change from ivory to pale yellow for $h$ -ZIS and $\\mathrm{Pt}_{0.3}$ -ZIS, and finally to dark brown for $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ . The relationship between VBM, $E_{\\mathrm{f}},$ and $E_{\\mathrm{vac}},$ and the UPS spectra of different photocatalysts are shown in Fig. 4c. The vacuum level $(E_{\\mathrm{vac}})$ should be located $21.2\\mathrm{eV}$ above the cutoff energy $(E_{\\mathrm{cutoff}})$ of the spectrum. The relative locations of valence band maximum (VBM) are calculated to be $-6.14\\mathrm{eV}$ ( $h$ -ZIS) and $-6.12\\mathrm{eV}$ $\\mathrm{(Pt_{0.3}-Z I S)}$ compared with $\\mathrm{{E}_{\\mathrm{{vac}}}}$ according to UPS spectra (Fig. 4d). As a result, $h$ -ZIS and $\\operatorname*{Pt}_{0.3}$ -ZIS display the conduction band minimum (CBM) potential of $-3.35$ and $-3.27\\mathrm{eV}$ , respectively (Fig. 4e). The detailed band positions are illustrated in Supplementary Table 9. The elevation of CBM endows the photoexcited electrons in $\\mathrm{Pt}_{0.3}$ -ZIS with a higher reduction ability to react with hydrogen ions and form molecular hydrogen in HER compared with $h{-}Z\\mathrm{IS^{4}}$ . This favorable feature of the band structure is advantageous to prohibit the recombination of electron-hole pairs, and is responsible for the enhanced photocatalytic performance of $\\mathrm{Pt}_{0.3}$ -ZIS. \n\n![](images/3a17e6f75d228c05f3e3f6413796ca7230be675c33f4fe014ba6e56944c5a6af.jpg) \nFig. 4 Mechanism insight the photocatalytic $\\Hat{\\boldsymbol{\\mathsf{H}}}_{2}$ evolution. a UV–vis diffuse reflectance spectra for $h$ -ZIS, $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S},$ and $\\mathsf{P t}_{3.0^{-}}\\mathsf{Z}|\\mathsf{S},$ insert: digital images for $h$ -ZIS, $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S},$ and $\\mathsf{P t}_{3.0^{-}}\\mathsf{Z}|\\mathsf{S},$ the concentration of suspensions is $2\\mathsf{m g}\\mathsf{m}\\mathsf{L}^{-1}$ . b Bandgap for $h$ -ZIS and $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ . c Comparison and relationship of VBM, $E_{\\mathfrak{f}},$ and $E_{\\mathsf{v a c}}$ of UPS spectra. d UPS spectra of $h$ -ZIS and $\\mathsf{P t}_{0.3^{-}}Z|\\mathsf{S}$ in the valence band region. e Schematic illustration of the band structure of $h-21S$ and $\\mathsf{P t}_{0.3^{-}}$ ZIS. f Normalized time profiles of transient absorption at $1150\\mathsf{n m}$ during the TDR of $h$ -ZIS, $\\mathsf{P t}_{0.3}\\mathsf{-}Z\\mathsf{I S},$ , and $\\mathsf{P t}_{3.0^{-}}\\mathsf{Z}|\\mathsf{S}$ . \n\nThe electron dynamics involved in photocatalysis were revealed by time-resolved diffuse reflectance (TDR) spectroscopy, a robust technique to provide direct evidence for the effect of Pt loading on charge separation in semiconductors37,38. The pump light with a central wavelength of $420\\mathrm{nm}$ was used, which is effective for photoinduced an interband transition in $h$ -ZIS. It turns out that probing in the wavelength range of $900{-}1200\\mathrm{nm}$ yielded similar TDR spectra, featuring free or trapped photoexcited electrons (Supplementary Fig. 38)6,39,40. And a set of representative data obtained at $1150\\mathrm{nm}$ combined with the biexponential fitting results are illustrated. In Fig. 4f, the two-time constants for $h$ -ZIS are $\\uptau_{1}=12.5$ ps $(52.7\\%)$ and $\\tau_{2}=567$ ps $(47.3\\%)$ , respectively, and the weighted average lifetime is 554 ps. In comparison, the characterized two-time constants for $\\operatorname*{Pt}_{0.3}$ -ZIS $\\stackrel{\\prime}{\\tau}_{1}=0.\\stackrel{\\bar{2}59}{\\cdot}$ ps $(97.0\\%)$ and $\\tau_{2}=16.6$ ps $\\left(3.0\\%\\right)_{,}^{\\cdot}$ and $\\mathrm{Pt}_{3.0}$ -ZIS 1 $\\mathbf{\\check{r}}_{1}=0.782$ ps $(89.2\\%)$ and $\\tau_{2}=31.6$ ps $(10.8\\%)\\}$ lead to much shorter average lifetime of 11.1 and $26.4\\mathrm{ps}$ , respectively. In general, the average recovery lifetime is considered as a crucial indicator for evaluating the separation efficiency of photoexcited electron-hole pairs, and such a shortened lifetime indicates the opening of an additional pathway for electron transfer after Pt deposition41,42. Based on the mean transient decay times of $h$ -ZIS $(\\tau_{\\mathrm{ZIS}})$ , $\\operatorname*{Pt}_{0.3}$ -ZIS $(\\tau_{0.3})$ , and $\\mathrm{Pt}_{3.0}$ -ZIS $(\\tau_{3.0})$ , we can determine the injection rate through the equation as $k_{\\mathrm{ET}}=(1/\\tau_{x})-(1/\\tau_{\\mathrm{ZIS}}).$ where $x$ represents the weight ratio of $\\mathrm{Pt}^{43,44}$ . It is calculated that the $k_{\\mathrm{ET}}$ of $\\mathrm{\\Pt{_{0.3}}}{-}\\mathrm{ZIS}$ is $8.8\\times10^{7}\\:s^{-1}$ , to be ${\\sim}2.4$ times faster than that of $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ $(3.6\\times10^{7}\\mathrm{s^{-1}},$ ). In addition, as a more significant parameter for photocatalytic activity, the efficiency of electron injection $(\\eta_{\\mathrm{inj}})$ from $h$ -ZIS to Pt is calculated as $\\eta_{\\mathrm{inj}}=1-\\tau_{x}/\\dot{\\tau}_{\\mathrm{ZIS}}{}^{43,44}$ IS43,44, and Pt0.3-ZIS affords a higher ηinj (ηinj = $98.0\\%$ ) than that of $\\mathrm{Pt}_{3.0}$ -ZIS $(\\eta_{\\mathrm{inj}}=95.2\\%$ ). \n\nAdditionally, steady-state photoluminescence (PL) spectra were recorded (Supplementary Fig. 39). Loading $\\mathrm{\\Pt}$ onto $h$ -ZIS results in significant PL quenching for $\\mathrm{\\Pt}$ -ZIS, and $\\mathrm{Pt}_{0.3}$ -ZIS exhibits the lowest PL intensity among the photocatalysts, demonstrating an improvement in charge separation45. Concurrently, the photocurrent intensity of $\\mathrm{Pt}_{0.3}–\\mathrm{ZIS}$ is around 6.5 and 3.9 times compared with that of $h$ -ZIS and $\\mathrm{Pt}_{3.0}$ -ZIS, respectively (Supplementary Fig. 40a). EIS Nyquist plots of $h$ -ZIS, $\\bar{\\mathrm{Pt}}_{0.3}$ -ZIS, and $\\bar{\\mathrm{Pt}}_{3.0^{-}}\\mathrm{ZIS}$ together with simulated equivalent electrical circuits are also provided in Supplementary Fig. 40b and $\\mathbf{\\boldsymbol{c}},$ respectively, in which $R_{\\mathrm{{ct}}}$ is interfacial charge-transfer resistance46. Based on the model, $\\mathrm{Pt}_{0.3}–Z\\mathrm{IS}$ shows the smallest semicircle diameter and $R_{\\mathrm{{ct}}}$ value (Supplementary Table 10), proving the lowest resistance of interfacial charge transfer in $\\mathrm{Pi}_{0.3}–\\mathrm{ZIS}^{\\mathbf{\\bar{4}}7}$ . The efficient charge separation in $\\mathrm{Pt}_{0.3}–Z\\mathrm{IS}$ was also confirmed by photocatalytic activation of peroxymonosulfate (PMS) to degrade antibiotic ornidazole (ONZ) pollutants (Supplementary Fig. 41). For $\\operatorname*{Pt}_{0.3^{-}}$ ZIS, the degradation efficiency of ONZ is 1.8 and 1.7 times and the utilization efficiency of PMS is 2.4 and 1.8 times than $h$ -ZIS and $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS},$ respectively. The effective electrons injection from $\\mathrm{Pt}_{0.3}$ -ZIS to PMS molecules generate more reactive species, contributing to the higher photocatalytic performance than $\\dot{h}$ -ZIS and $\\mathrm{Pt}_{3.0}$ -ZIS. These results disclose that more rapid and efficient directional migration of photogenerated electrons is realized by isolated $\\mathrm{Pt}$ atoms decoration, partly accounting for $\\mathrm{Pt}_{0.3}–Z\\mathrm{IS}$ with the greatly enhanced photocatalytic performance38,48. \n\nDFT calculations were further carried out to dive fundamental insight into the effect of atomical Pt decoration. The charge density difference isosurface images reveal a strong charge redistribution at $\\mathrm{\\Pt}$ -bonding region after the presence of protrusion-like single Pt atom on the basal plane of $h$ -ZIS, and the calculated Bader charge shows that $0.06~e$ is transferred from $\\mathrm{Pt}$ to S atoms in the $h$ -ZIS substrate, confirming the strong interaction between $\\mathrm{\\Pt}$ and $h$ -ZIS (Fig. 5a and b)30. It is also observed that the $\\mathrm{Pt}{-}{\\cal S}_{3}$ coordination has obvious charge transfer along the $\\textbf{z}$ direction. When the $\\mathrm{Pt}$ adsorbate hybridizes with the $\\boldsymbol{p}$ band of S, the adsorbate state split into localized bonding and antibonding states. In the projected density of states (PDOS) profile for $\\mathrm{Pt_{SS}}$ -ZIS, the dominant feature is $\\ P t\\ 5d-S\\ 3p$ bonding resonances below the Fermi level and forming hybridized electronic states (Fig. 5c). Such states are considered as the electron acceptor states that could endow $\\mathrm{Pt}_{\\mathrm{SS^{-}}}\\mathrm{ZIS}$ with metallic conductive character to inhibit the recombination of electronhole pairs49. Moreover, the antibonding states of $\\mathrm{Pt_{SS}}$ -ZIS with the position all above the Fermi level involve in constructing conduction band, which probably leads to the upshift of $\\mathrm{CBM^{19}}$ . This enlarged bandgap for $\\mathrm{Pt_{SS}}$ -ZIS is consistent with the UV-vis absorption spectra and UPS spectra. Hence, theoretical calculations suggest that the covalent $\\mathrm{Pt}{-}S$ coordination bond within $\\mathrm{Pt_{SS}}$ -ZIS forms additional charge-transfer channels to improve the charge mobility, causing an enhanced photocatalytic activity. To disclose the underlying interfacial catalytic contribution of $\\mathrm{H}_{2}\\mathrm{O}$ to $\\mathrm{H}_{2}$ from $\\mathrm{\\Pt}$ single site, the adsorption of H atom on $\\mathrm{\\Pt}$ atom was investigated. It is demonstrated that the adsorption strength of H decreases with an increase in the number of adsorbed H atoms, eventually leading to a minimum value when four $\\mathrm{~H~}$ atoms are adsorbed (Fig. 5d). The single $\\mathrm{~H~}$ atom exhibits adsorption energy $\\left(E_{\\mathrm{a}}\\right)$ of $0.613\\mathrm{eV}$ , while it decreases to $0.564\\mathrm{eV}$ per $\\mathrm{~H~}$ in the case of two H atoms. As the number of interacting $\\mathrm{~H~}$ atoms increases, the $\\mathrm{Pt}$ to $\\mathrm{~H~}$ interaction for bond formation becomes a compromise between the $_\\mathrm{H-H}$ electrostatic repulsion and the orbital hybridization of $\\mathrm{Pt\\mathrm{-}H}^{50}$ . Specifically, when three H atoms adsorb onto a single Pt atom, they locate symmetrically around Pt site, leading to corresponding adsorption energy of $0.543\\mathrm{eV}$ per H. With the number of H atoms reaching four, the adsorption configuration is one in which a $\\mathrm{H}_{2}$ dimer and two isolated $\\mathrm{H}$ atoms are formed with an adsorption energy of $0.436\\mathrm{eV}$ per $\\mathrm{~H~}$ (Fig. 5d and e). The bond length of $\\mathrm{Pt}{-}3\\mathrm{H}$ is elongated from 1.551 to $1.746\\mathring{\\mathrm{A}};$ and that of $\\mathrm{Pt-4H}$ is $1.723\\mathring{\\mathrm{A}}.$ , which are much longer than that of $\\mathrm{Pt-}\\mathrm{1H}$ $(1.567\\mathring\\mathrm{A})$ and Pt-2H $(1.566\\mathring{\\mathrm{A}})$ (the detailed distance of $_\\mathrm{H-H}$ atoms and $\\mathrm{Pt\\mathrm{-}H}$ atoms are labeled in Fig. 5d). Moreover, the distance between 3H and 4H is only $0.881\\AA$ , close to that in $\\mathrm{H}_{2}$ molecule $(0.740\\mathring\\mathrm{A})$ . These phenomena indicate the weakened adsorption strength of 3H and 4H on $\\mathrm{Pt}$ single site, thus promoting the desorption of 3H and 4H and ease of $\\mathrm{H}_{2}$ production on $\\mathrm{Pt}$ atom. Finally, we performed the H adsorption free energy $(\\Delta G_{\\mathrm{H}}^{*})$ to examine the HER activity for different sites and the number of $\\mathrm{H}$ atoms. Our simulations indicate that the adsorbed $\\mathrm{~H~}$ on $\\mathrm{{Pt}_{\\mathrm{{;}}}}$ neighboring S, neighboring $Z\\mathrm{n}$ , and second-neighboring Zn move to the tilted top site toward adjacent $Z\\mathrm{n}$ atom on the surface after relaxation with an identical $\\Delta G_{\\mathrm{H}}^{*}$ of $-0.36\\mathrm{eV}$ , and the $\\Delta G_{\\mathrm{H}}^{*}$ of second-neighboring S is 0.61 eV (Supplementary Figs. 42, 43, and Table 11). Furthermore, the $\\Delta G_{\\mathrm{H}}^{*}$ gradually increases for the second $(-0.26\\mathrm{eV})$ and third $(-0.23\\mathrm{eV})$ adsorbed H atoms on $\\mathrm{Pt}$ single site, and it becomes positive for the fourth adsorbed H atom $(+0.10\\mathrm{eV})$ (Supplementary Fig. 44). Commonly, one material is regarded as a good HER catalyst when the value of $\\Delta G_{\\mathrm{H}}^{*}$ is close to thermoneutral $(\\Delta G_{\\mathrm{H}}^{*}\\approx0)^{51}$ . Therefore, we suggest that the $\\mathrm{Pt}$ single atom would be the active site for HER and the catalyst that forms in situ states might be $\\mathrm{H}_{3,\\mathrm{ads}}\\mathrm{Pt}\\mathrm{-}\\mathrm{ZIS}^{31}$ . DFT simulations were also carried out on $\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{ZIS}{-}\\mathrm{V}_{\\mathrm{S}}$ . Unlike $\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{ZIS},$ $\\mathrm{~H~}$ atom tends to be adsorbed right above $\\mathrm{Pt}$ atom after structural relaxation, suggesting that it is difficult for $\\mathrm{Pt}$ atom in $\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{ZIS}{-}\\mathrm{V}_{\\mathrm{S}}$ to adsorb more H atom (Supplementary Fig. 45). Additionally, the calculated $\\Delta G_{\\mathrm{H}}^{*}$ for $\\mathrm{~H~}$ atom on $\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{ZIS}{-}\\mathrm{V}_{\\mathrm{S}}$ is $-0.22\\mathrm{eV}$ , which is larger than that of $\\mathrm{H}_{3,\\mathrm{ads}}\\mathrm{Pt}_{\\mathrm{SS}^{-}}\\mathrm{ZIS}$ $(+0.10\\mathrm{eV})$ . These results prove the recently reported tip enhancement effect that protrusion-like single atoms could continuously enrich protons, which issues an improvement in proton mass transfer, thus boosting the kinetics of $\\mathrm{H}_{2}$ production on the Pt single atom22,26,50,52. Active blocking experiment by introducing thiocyanate ion $(\\mathsf{S C N^{-1}})$ into the catalyst system dictates a drastically decreased $\\mathrm{H}_{2}$ generation rate from 350.1 to $27.44\\upmu\\mathrm{mol}$ $\\mathbf{h}^{-1}$ with the increase of KSCN concentration, confirming that Pt single atoms indeed serve as the centers for HER (Supplementary Fig. 46). Based on calculations, the adsorbed Pt single sites onto the surface of $h$ -ZIS manifests a fast formation and release of molecular hydrogen, leading to an outstanding catalytic activity. \n\n![](images/2c385812a79f149ebe703739b45115e31ffa32d41dd83ad3caf65dd3f04b717d.jpg) \nFig. 5 Density functional theory (DFT) calculations. a Top and b side view of calculated charge difference surfaces of $\\mathsf{P t}_{\\mathsf{S S}^{-}}\\mathsf{Z l S}$ with yellow and cyan colors represent positive and negative electron density isosurfaces, respectively. The value of isosurface is $0.002\\mathrm{e}/\\mathsf{b o h r}^{3}$ . c Density of states of the $h$ -ZIS and $\\mathsf{P t}_{55^{-}}\\mathsf{Z}|\\mathsf{S}$ . d Calculated adsorption energies of $\\mathsf{H}$ atoms as a function of the H coverages (from one H atom to four H atoms) on the single $\\mathsf{P t}$ atom photocatalysts with $h$ -ZIS as support. The $H-H$ and $\\mathsf{P t\\mathrm{-}H}$ distances are shown in the figure. The adsorption energies $(\\mathsf{E}_{\\mathsf{a}})$ were calculated by: $\\dot{\\mathsf{E}}_{\\mathrm{a}}=\\left[\\mathsf{E}_{\\mathsf{P t}_{55}-Z15}+\\frac{\\mathsf{n}}{2}\\mathsf{E}_{\\mathsf{H}_{2}}-\\mathsf{E}_{\\mathsf{P t}_{55}-Z15+\\mathsf{n}\\mathsf{H}}\\right]/\\mathsf{n}$ . The yellow, gray, pink, green, and purple spheres represent the S, Zn, In, Pt, and H atoms, respectively. e Side view of $\\mathsf{P t}_{\\mathsf{S S}^{-}}\\mathsf{Z l S}$ schematic structure with one $\\mathsf{H}$ atom, two H atoms, three H atoms, and four H atoms chemisorbed on Pt atom, termed as $H_{1,\\mathrm{ads}}P t-Z1S$ , ${\\sf H}_{2,\\sf a d s}{\\sf P}{\\sf t}.$ - ZIS, $H_{3,\\mathsf{a d s}}P t-Z|S,$ and $H_{4,\\mathsf{a d s}}P t-Z|S,$ , respectively. \n\n# Discussion \n\nBy combining experimental results with theoretical calculations, the high catalytic performance of $\\mathrm{Pt}_{0.3}$ -ZIS accompanied with long durability is confirmed. The enhanced $\\mathrm{H}_{2}$ generation rate is due to the atomic protrusion-like $\\mathrm{Pt}$ atoms with triple roles in the photocatalytic HER. First, single $\\mathrm{Pt}$ atoms immobilized onto $h$ -ZIS could tune the band structure of $h$ -ZIS on upshifting the CBM, providing a larger reduction driving force. Second, the atomically dispersed Pt are acted as electron wells to accelerate charge separation and transportation. Third, the tridimensional protrusions induce effective proton mass transfer to the active $\\mathrm{Pt}$ site and an almost thermoneutral $\\Delta G_{\\mathrm{H}}^{*}$ for HER, which is also supported by the smallest overpotential of $\\mathrm{\\bar{Pt}}_{0.3}–Z\\mathrm{IS}$ among $J{-}V$ curves (Supplementary Fig. 47). A reasonable photocatalytic mechanism for HER from water is proposed (Supplementary Fig. 48). Upon light irradiation, the electron and hole pairs are generated and then migrate from the interior to the surface of $h$ -ZIS. Due to the covalent $\\mathsf{\\bar{P}t}{-}\\mathsf{S}$ coordination bond, electrons are injected from the neighboring S atoms into Pt single atoms efficiently, followed by the reaction with adsorbed protons to generate $\\mathrm{H}_{2}$ . Simultaneously, the holes in $h$ -ZIS are consumed by TEOA. \n\nIn summary, compared to the conventional defect-trappedSSCs, atomically dispersed $\\mathrm{Pt}$ sites are immobilized onto the basal plane of $h$ -ZIS nanosheets to generate catalysts by a facile photochemical strategy. The efficient water reduction activity over $\\mathrm{Pt}_{0.3}$ -ZIS proceeds via regulated band structure, improved charge separation, reduced $\\mathrm{H}_{2}$ evolution overpotential, and advanced protons mass transfer. The demonstration herein of constructing tridimensional protrusions through immobilizing ultralow content $\\mathrm{Pt}~\\mathsf{S S C s}$ onto 2D $h$ -ZIS nanosheets presents a promising, cost- and energy-efficient avenue for boosting photocatalysis $\\mathrm{H}_{2}$ evolution, and this prototype potentially would stimulate innovative ideas of enabling future ambient HER catalysts of industrial interest. The phenomenon of triggering tip enhancement by highcurvature nano-textures could function as a general prescription to enhance the performances of catalysts achieved in other reactions, such as organic pollutants degradation, $\\mathrm{O}_{2}$ reduction, $\\mathrm{CO}_{2}$ reduction, and $\\mathrm{N}_{2}$ fixation. \n\n# Methods \n\nSynthesis of hexagonal $Z n\\ln_{2}S_{4}$ (h-ZIS) nanosheets. In a typical synthesis, $68\\mathrm{mg}\\mathrm{ZnCl_{2}}$ (Aladdin, $99.95\\%$ ), 293 mg $\\mathrm{InCl}_{3}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}$ (Aladdin, $99.9\\%$ , and $300\\mathrm{mg}$ trisodium citrate (Aladdin, $99.0\\%$ ) are dissolved into $25\\mathrm{mL}$ of deionized water and $5\\mathrm{mL}$ of glycol (Shanghai LingFeng Chemical Reagent Co. LTD., AR). After being drastically stirred for $30\\mathrm{min}$ at room temperature, $150\\mathrm{mg}$ thioacetamide (TAA, SCR, AR) is then added into the solution. After another $30\\mathrm{min}$ stirring, the heterogeneous solution was transferred into a $50~\\mathrm{mL}$ Teflon-lined stainless steel autoclave and maintained at $120^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ in an oven. After natural cooling, the products were collected by centrifugation, rinsed two times with ethanol and distilled water, and then freeze-dried. \n\nSynthesis of hexagonal $Z n l n_{2}S_{4}$ thin layers with S-vacancy $(h-Z|S-V_{S})$ . The asobtained $h$ -ZIS $\\left(100\\mathrm{mg}\\right)$ was dissolved into $50~\\mathrm{mL}$ storage bottle containing $0.1\\mathrm{{M}}$ $\\mathrm{{NaBH_{4}}}$ (Sinopharm Chemical ReagentCo., Ltd, AR). The mixture was heated at $60^{\\circ}\\mathrm{C}$ in a water bath. After $5\\mathrm{{min}}$ , the resultant dispersion was centrifuged, and then freeze-dried. \n\nSynthesis of Pt-loaded $\\pmb{h}$ -ZIS and $h{-}Z1S{-}V_{S}$ atomic layers (Pt-ZIS and Pt-ZIS$\\mathbf{v}_{\\mathsf{s}})$ . In a typical procedure of photochemical loading $\\mathrm{Pt}$ on $h$ -ZIS, $20\\mathrm{mg}$ thin layers $h$ -ZIS and different amounts of $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ $\\mathrm{\\cdot4\\mg\\mL^{-1}},$ ) were dispersed in an aqueous solution containing $45\\mathrm{mL}$ $_\\mathrm{H}_{2}\\mathrm{O}$ and $5\\mathrm{mL}$ triethanolamine (TEOA, XiLong Scientific, AR). Subsequently, the suspension is bubbled with argon gas through the reactor for $30\\mathrm{min}$ to completely remove the dissolved oxygen and ensure that the reactor is in an anaerobic condition. The dispersion was kept stirring with a magnetic stirrer during visible light irradiation $(\\lambda>420\\mathrm{nm})$ . After the light treatment for $60\\mathrm{min}$ , the sample was centrifuged and washed by deionized water twice and then freeze-dried. By alerting the volume of $\\mathrm{H}_{2}\\mathrm{PtCl}_{6}$ solution, the Pt content relative to $h$ -ZIS was adjusted to about 0.1, 0.3, 0.7, 1.4, and $3.0\\mathrm{wt\\%}$ , which were named as $\\mathrm{Pt}_{0.1}$ -ZIS, $\\mathrm{Pt}_{0.3}$ -ZIS, $\\mathrm{Pt}_{0.7}$ -ZIS, $\\mathrm{Pt}_{1.4}$ -ZIS, and $\\mathrm{Pt}_{3.0^{-}}\\mathrm{ZIS}$ , respectively. For the synthesis of $\\mathrm{Pt}_{0.3^{-}}\\mathrm{ZIS-V}_{\\mathrm{S}},$ the procedure was similar to that of $\\mathrm{Pt}_{0.3}$ -ZIS except changing $h$ -ZIS to $h$ -ZIS- ${\\bf\\nabla}\\cdot{\\bf V_{S}}$ . \n\nPreparation of $\\mathsf{P t}_{0.3}–\\mathsf{Z l S}$ thin films. Typically, $\\mathrm{Pt}_{0.3}$ -ZIS $\\mathrm{\\Omega}^{\\mathrm{}}30\\mathrm{mg})$ powder was dispersed into ethanol (2 mL) and then sonicated for $10\\mathrm{min}$ to obtain a colloidal solution. The film was prepared by drop-casting $400\\upmu\\mathrm{L}$ of the colloidal solution onto roughened glass $(\\bar{1}.5\\bar{\\times}2\\mathrm{cm}^{2})$ . Then the film was dried in a vacuum oven at the temperature of $60^{\\circ}\\mathrm{C}$ . \n\nPhotocatalytic hydrogen production. Twenty milligrams of photocatalysts was dispersed in $45\\mathrm{mL}$ aqueous solution containing $10\\mathrm{vol\\%}$ TEOA using an ultrasonic bath. Subsequently, the suspension was bubbled with argon gas through the reactor for $30\\mathrm{min}$ to completely remove the dissolved oxygen and ensure that the reactor was in an anaerobic condition. The samples were irradiated under visible light using a 300 W Xenon lamp for $\\mathrm{H}_{2}$ generation (PLS-SXE300D, Beijing Perfectlight Technology Co., Ltd, $300\\mathrm{mW}\\mathrm{cm}^{-2}$ ). The reaction temperature is kept at about $8{}^{\\circ}\\mathrm{C}$ . The visible light is filtered with a nominal $420\\mathrm{nm}$ cutoff filter. The volume of $\\mathrm{H}_{2}$ was measured by Shimadzu GC-8A gas chromatograph equipped with an MS5A column and thermal conductivity detector. The apparent quantum efficiency (AQE) was calculated using the following equation, \n\n$$\n\\mathrm{AQE}\\left(\\mathcal{Y}_{0}\\right)=\\frac{N_{e}}{N_{p}}\\times100\\%=\\frac{2\\times n_{H_{2}}\\times N_{A}\\times h\\times c}{S\\times P\\times t\\times\\lambda}\\times100\\%\n$$ \n\nwhere $N_{p}$ is the total incident photons, $N_{e}$ is the total reactive electrons, $n_{H_{2}}$ is the amount of $\\mathrm{H}_{2}$ molecules, $N_{A}$ is Avogadro constant, $h$ is the Planck constant, $\\boldsymbol{\\mathscr{c}}$ is the speed of light, $s$ is the irradiation area, $P$ is the intensity of irradiation light, $t$ is the photoreaction time, and $\\lambda$ is the wavelength of the monochromatic light. For the stability test, the photocatalyst was continuously irradiated for $50\\mathrm{h}$ . The turnover frequency (TOF) was calculated according to the following equation: \n\n$$\n\\mathrm{TOF}={\\frac{n_{(\\mathrm{H}_{2})}}{n_{(\\mathrm{Pt})}\\cdot\\tau}}\n$$ \n\n# Data availability \n\nAll data relevant to this study are available from the corresponding author upon reasonable request. The source data are provided as a Source data file. Source data are provided with this paper. \n\nReceived: 20 May 2021; Accepted: 15 February 2022; Published online: 11 March 2022 \n\n# References \n\n1. Chen, X., Shen, S., Guo, L. & Mao, S. S. Semiconductor-based photocatalytic hydrogen generation. Chem. Rev. 110, 6503–6570 (2010). \n2. Lei, Z. et al. Photocatalytic water reduction under visible light on a novel $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ catalyst synthesized by hydrothermal method. Chem. Commun. 17, 2142–2143 (2003). \n3. Yang, M.-Q. et al. Self-surface charge exfoliation and electrostatically coordinated 2D hetero-layered hybrids. Nat. Commun. 8, 14224 (2017). \n4. Yang, W. et al. Enhanced photoexcited carrier separation in oxygen-doped $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ nanosheets for hydrogen evolution. Angew. Chem. Int. Ed. 55, 6716–6720 (2016). \n5. Wang, S., Guan, B. Y., Wang, X. & Lou, X. W. D. Formation of hierarchical $\\mathrm{Co}_{9}\\mathrm{S}_{8}@\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ heterostructured cages as an efficient photocatalyst for hydrogen evolution. J. Am. Chem. Soc. 140, 15145–15148 (2018). \n6. Shi, X. et al. Ultrathin $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ nanosheets with active (110) facet exposure and efficient charge separation for cocatalyst free photocatalytic hydrogen evolution. Appl. Catal. B Environ. 256, 118616 (2020). \n7. Du, C. et al. Half-unit-cell $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ monolayer with sulfur vacancies for photocatalytic hydrogen evolution. Appl. Catal. B Environ. 248, 193–201 (2019). \n8. Zhang, S. et al. $\\ensuremath{\\mathrm{MoS}}_{2}$ quantum dot growth induced by S vacancies in a $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ monolayer: atomic-level heterostructure for photocatalytic hydrogen production. ACS Nano 12, 751–758 (2018). \n9. Shi, X. et al. Inert basal plane activation of two-dimensional $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}$ via Ni atom doping for enhanced co-catalyst free photocatalytic hydrogen evolution. J. Mater. Chem. A 8, 13376–13384 (2020). \n10. Luo, N. et al. Visible-light-driven coproduction of diesel precursors and hydrogen from lignocellulose-derived methylfurans. Nat. Energy 4, 575–584 (2019). \n11. Chen, Y. et al. Selective recovery of precious metals through photocatalysis. Nat. Sustain. 4, 618–626 (2021). \n12. Qi, K. et al. Single-atom cobalt array bound to distorted 1T $\\ensuremath{\\mathrm{MoS}}_{2}$ with ensemble effect for hydrogen evolution catalysis. Nat. Commun. 10, 5231 (2019). \n13. Huang, Y. et al. Atomically engineering activation sites onto metallic 1T- $\\ensuremath{\\mathrm{MoS}}_{2}$ catalysts for enhanced electrochemical hydrogen evolution. Nat. Commun. 10, 982 (2019). \n14. Chen, Y. et al. Single-atom catalysts: synthetic strategies and electrochemical applications. Joule 2, 1242–1264 (2018). \n15. Wang, Y. et al. Catalysis with two-dimensional materials confining single atoms: concept, design, and applications. Chem. Rev. 119, 1806–1854 (2019). \n16. Park, J. et al. Investigation of the support effect in atomically dispersed Pt on $\\mathrm{WO}_{3-\\mathbf{x}}$ for utilization of $\\mathrm{Pt}$ in the hydrogen evolution reaction. Angew. Chem. Int. Ed. 58, 16038–16042 (2019). \n17. Yan, Q.-Q. et al. Reversing the charge transfer between platinum and sulfurdoped carbon support for electrocatalytic hydrogen evolution. Nat. Commun. 10, 4977 (2019). \n18. Deng, J. et al. Triggering the electrocatalytic hydrogen evolution activity of the inert two-dimensional $\\ensuremath{\\mathrm{MoS}}_{2}$ surface via single-atom metal doping. Energy Environ. Sci. 8, 1594–1601 (2015). \n19. Fang, S. et al. Uncovering near-free platinum single-atom dynamics during electrochemical hydrogen evolution reaction. Nat. Commun. 11, 1029 (2020). \n20. Zeng, Z. et al. Single-atom platinum confined by the interlayer nanospace of carbon nitride for efficient photocatalytic hydrogen evolution. Nano Energy 69, 104409 (2020). \n21. Zuo, Q. et al. Ultrathin metal–organic framework nanosheets with ultrahigh loading of single Pt atoms for efficient visible-light-driven photocatalytic $\\mathrm{H}_{2}$ evolution. Angew. Chem. Int. Ed. 58, 10198–10203 (2019). \n22. Liu, D. et al. Atomically dispersed platinum supported on curved carbon supports for efficient electrocatalytic hydrogen evolution. Nat. Energy 4, 512–518 (2019). \n23. Li, J. et al. Accelerated dinitrogen electroreduction to ammonia via interfacial polarization triggered by single-atom protrusions. Chem 6, 885–901 (2020). \n24. Liu, P. et al. Photochemical route for synthesizing atomically dispersed palladium catalysts. Science 352, 797–800 (2016). \n25. Hejazi, S. et al. On the controlled loading of single platinum atoms as a cocatalyst on $\\mathrm{TiO}_{2}$ anatase for optimized photocatalytic $\\mathrm{H}_{2}$ generation. Adv. Mater. 32, 1908505 (2020). \n26. Lau, T. H. M. et al. Engineering monolayer 1T- ${\\cdot\\mathrm{MoS}_{2}}$ into a bifunctional electrocatalyst via sonochemical doping of isolated transition metal atoms. ACS Catal. 9, 7527–7534 (2019). \n27. Wu, X. et al. Surface step decoration of isolated atom as electron pumping: atomic-level insights into visible-light hydrogen evolution. Nano Energy 45, 109–117 (2018). \n28. Zhang, J. et al. Single platinum atoms immobilized on an MXene as an efficient catalyst for the hydrogen evolution reaction. Nat. Catal. 1, 985–992 (2018). \n29. Zhu, J. et al. Enhanced electrocatalytic hydrogen evolution activity in singleatom Pt-decorated $\\mathrm{VS}_{2}$ nanosheets. ACS Nano 14, 5600–5608 (2020). \n30. Jiang, K. et al. Single platinum atoms embedded in nanoporous cobalt selenide as electrocatalyst for accelerating hydrogen evolution reaction. Nat. Commun. 10, 1743 (2019). \n31. Wu, C. et al. Monoatomic platinum-anchored metallic $\\mathbf{MoS}_{2}$ : correlation between surface dopant and hydrogen evolution. J. Phys. Chem. Lett. 10, 6081–6087 (2019). \n32. Guan, Y. et al. Ganoderma-like $\\mathrm{MoS}_{2}/\\mathrm{NiS}_{2}$ with single platinum atoms doping as an efficient and stable hydrogen evolution reaction catalyst. Small 14, 1800697 (2018). \n33. Qiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}/F e O_{x}}$ . Nat. Chem. 3, 634–641 (2011). \n34. Zhang, Z. et al. Thermally stable single atom $\\mathrm{Pt/m}{\\cdot}\\mathrm{Al}_{2}\\mathrm{O}_{3}$ for selective hydrogenation and CO oxidation. Nat. Commun. 8, 16100 (2017). \n35. Schröder, M. et al. Hydrogen evolution reaction in a large-scale reactor using a carbon nitride photocatalyst under natural sunlight irradiation. Energy Technol. 3, 1014–1017 (2015). \n36. Zhang, N. et al. Near-field dielectric scattering promotes optical absorption by platinum nanoparticles. Nat. Photon 10, 473–482 (2016). \n37. Di, J. et al. Isolated single atom cobalt in $\\mathrm{Bi_{3}O_{4}B r}$ atomic layers to trigger efficient $\\mathrm{CO}_{2}$ photoreduction. Nat. Commun. 10, 2840 (2019). \n38. Xiao, X. et al. A promoted charge separation/transfer system from Cu single atoms and $\\mathrm{C}_{3}\\mathrm{N}_{4}$ layers for efficient photocatalysis. Adv. Mater. 32, 2003082 (2020). \n39. Zhu, M. et al. Metal-free photocatalyst for $\\mathrm{H}_{2}$ evolution in visible to nearinfrared region: black phosphorus/graphitic carbon nitride. J. Am. Chem. Soc. 139, 13234–13242 (2017). \n40. Zhu, M., Sun, Z., Fujitsuka, M. & Majima, T. Z-Scheme photocatalytic water splitting on a 2D heterostructure of black phosphorus/bismuth vanadate using visible light. Angew. Chem. Int. Ed. 57, 2160–2164 (2018). \n41. Gao, S. et al. Highly efficient and exceptionally durable $\\mathrm{CO}_{2}$ photoreduction to methanol over freestanding defective single-unit-cell bismuth vanadate layers. J. Am. Chem. Soc. 139, 3438–3445 (2017). \n42. Wang, S., Guan, B. Y. & Lou, X. W. D. Construction of $\\mathrm{ZnIn}_{2}\\mathrm{S}_{4}\\mathrm{-In}_{2}\\mathrm{O}_{3}$ hierarchical tubular heterostructures for efficient $\\mathrm{CO}_{2}$ photoreduction. J. Am. Chem. Soc. 140, 5037–5040 (2018). \n43. Žídek, K. et al. Ultrafast dynamics of multiple exciton harvesting in the CdSe–ZnO system: electron injection versus Auger recombination. Nano Lett. 12, 6393–6399 (2012). \n44. Abdellah, M. et al. Balancing electron transfer and surface passivation in gradient CdSe/ZnS core–shell quantum dots attached to ZnO. J. Phys. Chem. Lett. 4, 1760–1765 (2013). \n45. Wang, W.-K. et al. Single-molecule and -particle probing crystal edge/corner as highly efficient photocatalytic sites on a single $\\mathrm{TiO}_{2}$ particle. Proc. Natl Acad. Sci. USA 116, 18827–18833 (2019). \n46. Jiang, W. et al. Consciously constructing heterojunction or direct Z-scheme photocatalysts by regulating electron flow direction. ACS Catal. 8, 2209–2217 (2018). \n47. Zhao, Q. et al. Single nickel atoms anchored on nitrogen-doped graphene as a highly active cocatalyst for photocatalytic $\\mathrm{H}_{2}$ evolution. ACS Catal. 8, 11863–11874 (2018). \n48. Tian, B. et al. Supported black phosphorus nanosheets as hydrogen-evolving photocatalyst achieving $5.4\\%$ energy conversion efficiency at $353\\mathrm{K}.$ Nat. Commun. 9, 1397 (2018). \n49. Wang, P. et al. Atomic insights for optimum and excess doping in photocatalysis: a case study of few-layer $\\mathrm{Cu}–\\mathrm{ZnIn}_{2}S_{4}$ . Adv. Funct. Mater. 29, 1807013 (2019). \n50. Cheng, N. et al. Platinum single-atom and cluster catalysis of the hydrogen evolution reaction. Nat. Commun. 7, 13638 (2016). \n51. Hinnemann, B. et al. Biomimetic hydrogen evolution: $\\ensuremath{\\mathrm{MoS}}_{2}$ nanoparticles as catalyst for hydrogen evolution. J. Am. Chem. Soc. 127, 5308–5309 (2005). \n52. Liu, M. et al. Enhanced electrocatalytic $\\mathrm{CO}_{2}$ reduction via field-induced reagent concentration. Nature 537, 382–386 (2016). \n\n# Acknowledgements \n\nThis work is supported by the National Natural Science Foundation of China (Nos. 21902143 and 51702287), Natural Science Foundation of Zhejiang Province (No. LY21B030005), Guangdong Basic and Applied Basic Research Foundation (No. 2020B1515020038), and the Natural Science Foundation of Jiangsu Province (No. BK20190640). M.Z. thanks the Pearl River Talent Recruitment Program of Guangdong Province (2019QN01L148). We thank the Taiwan National Synchrotron Radiation Research Center for XAFS measurement. \n\n# Author contributions \n\nX.S. and M.Z. constructed and planned the whole project. X.S., C.D., and X.W. performed the synthesis, characterization, and photocatalysis. X.S. and C.D. performed the XAS in terms of XANES and EXAFS tests. X.W. performed the in situ FTIR tests. J.H. performed the photodegradation and photo-electrochemical experiments. L.M. and J.Z. conducted the DFT calculations. X.S. and L.M. writing—original draft, M.Z., L.Z., and H.Z. writing—review and editing. All authors analyzed the data and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-28995-1. \n\nCorrespondence and requests for materials should be addressed to Liang Mao, Huajun Zheng or Mingshan Zhu. \n\nPeer review information Nature Communications thanks Kyu Hyoung Lee and the other, anonymous, reviewers for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1016_S1872-2067(22)64106-8", + "DOI": "10.1016/S1872-2067(22)64106-8", + "DOI Link": "http://dx.doi.org/10.1016/S1872-2067(22)64106-8", + "Relative Dir Path": "mds/10.1016_S1872-2067(22)64106-8", + "Article Title": "S-Scheme photocatalyst TaON/Bi2WO6 nullofibers with oxygen vacancies for efficient abatement of antibiotics and Cr(VI): Intermediate eco-toxicity analysis and mechanistic insights", + "Authors": "Li, SJ; Cai, MJ; Liu, YP; Wang, CC; Lv, KL; Chen, XB", + "Source Title": "CHINESE JOURNAL OF CATALYSIS", + "Abstract": "Enlightened by natural photosynthesis, developing efficient S-scheme heterojunction photocatalysts for deleterious pollutant removal is of prime importance to restore environment. Herein, novel TaON/Bi2WO6 S-scheme heterojunction nullofibers were designed and developed by in-situ growing Bi2WO6 nullosheets with oxygen vacancies (OVs) on TaON nullofibers. Thanks to the efficiently spatial charge disassociation and preserved great redox power by the unique S-scheme mechanism and OVs, as well as firmly interfacial contact by the core-shell 1D/2D fibrous hetero-structure via the in-situ growth, the optimized TaON/Bi2WO6 heterojunction unveils exceptional visible-light photocatalytic property for abatement of tetracycline (TC), levofloxacin (LEV), and Cr(VI), respectively by 2.8-fold, 1.0-fold, and 1.9-fold enhancement compared to the bare Bi2WO6, while maintaining satisfactory stability. Furthermore, the systematic photoreaction tests indicate TaON/Bi2WO6 has the high practicality in the elimination of pollutants in aquatic environment. The degradation pathway of tetracycline and intermediate eco-toxicity were determined based on HPLC-MS combined with QSAR calculation, and a possible photocatalytic mechanism was elucidated. This work provides a guideline for designing high-performance TaON-based S-scheme photocatalysts with defects for environment protection. (C) 2022, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.", + "Times Cited, WoS Core": 360, + "Times Cited, All Databases": 378, + "Publication Year": 2022, + "Research Areas": "Chemistry; Engineering", + "UT (Unique WOS ID)": "WOS:000884673500004", + "Markdown": "Article \n\n# S‐Scheme photocatalyst TaON/Bi2WO6 nanofibers with oxygen vacancies for efficient abatement of antibiotics and $\\mathbf{Cr(VI)}$ : Intermediate eco‐toxicity analysis and mechanistic insights \n\nShijie Li a,b,\\*, Mingjie Cai a,b, Yanping Liu a,b, Chunchun Wang a,b, Kangle Lv c, Xiaobo Chen d,# \n\na Key Laboratory of Health Risk Factors for Seafood of Zhejiang Province, National Engineering Research Center for Marine Aquaculture, College of \nMarine Science and Technology, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China \nb Institute of Innovation & Application, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China \nc Key Laboratory of Catalysis and Energy Materials Chemistry of Ministry of Education, South‐Central Minzu University, Wuhan 430074, Hubei, China \nd Department of Chemistry, University of Missouri‐Kansas City, MO 64110, USA \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nArticle history: Received 6 March 2022 Accepted 13 April 2022 Available online 30 September 2022 \n\nKeywords: \nTaON/Bi2WO6 \nS‐Scheme heterojunction \nElectrospinning \nOxygen vacancy \nAntibiotic degradation \nCr(VI) reduction \n\nEnlightened by natural photosynthesis, developing efficient S‐scheme heterojunction photocatalysts for deleterious pollutant removal is of prime importance to restore environment. Herein, novel $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ S‐scheme heterojunction nanofibers were designed and developed by in‐situ growing ${\\mathrm{Bi}}_{2}{\\mathrm{W}}{0}_{6}$ nanosheets with oxygen vacancies (OVs) on TaON nanofibers. Thanks to the efficiently spatial charge disassociation and preserved great redox power by the unique S‐scheme mechanism and OVs, as well as firmly interfacial contact by the core‐shell 1D/2D fibrous hetero‐structure via the in‐situ growth, the optimized $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ heterojunction unveils exceptional visible‐light photocatalytic property for abatement of tetracycline (TC), levofloxacin (LEV), and $\\mathrm{Cr(VI)}$ respec‐ tively by 2.8‐fold, 1.0‐fold, and 1.9‐fold enhancement compared to the bare $B i_{2}W O_{6},$ while main‐ taining satisfactory stability. Furthermore, the systematic photoreaction tests indicate Ta‐ $0\\mathrm{N}/\\mathrm{Bi_{2}W}0_{6}$ has the high practicality in the elimination of pollutants in aquatic environment. The degradation pathway of tetracycline and intermediate eco‐toxicity were determined based on HPLC–MS combined with QSAR calculation, and a possible photocatalytic mechanism was elucidat‐ ed. This work provides a guideline for designing high‐performance TaON‐based S‐scheme photo‐ catalysts with defects for environment protection. \n\n$\\mathbb{C}2022$ , Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nThe fast urbanization and industrialization has brought about environmental crises in the globe [1]. Particularly, the massive consumption and discharge of hazardous pharmaceu‐ tical antibiotics and heavy metal leads to their prevalence in water bodies, which has been one of the critical environmental issues, posing a horrible threat to life of mankind and the eco‐ system. Therefore, the effective decontamination of these toxic pollutants in water environment is an urgent task. Photocataly‐ sis technology owns the advantage of eco‐friendliness, sus‐ tainability and high‐efficiency, which is demonstrated to be a promising route for environmental remediation [2–5]. The huge challenge to its large‐scale application lies in the devel‐ opment of outstanding photocatalysts [6–15]. \n\nTaON, an emerging star photocatalyst, has shown enormous potential in the application of photocatalytic water splitting [16–18] and pollutants degradation [19] under visible light by virtue of its favorable optical/electronic properties and good sunlight absorption $(E_{\\mathrm{g}}\\approx2.4\\mathrm{-}2.6~\\mathrm{eV}]$ , etc. Particularly, the ex‐ traordinary reduction ability of photo‐excited electrons (e–) originating from the negative conduction band (CB) is condu‐ cive to reduction reactions. Nevertheless, its poor oxidation power of photo‐induced holes $\\left(\\mathrm{h}{+}\\right)$ deriving from the high va‐ lence band (VB) inevitably incurs insufficient competent in oxidation reactions. Furthermore, the short charge transport distance in TaON causes severe $\\mathrm{e^{-}{\\cdot}h^{+}}$ reunion [20,21]. There‐ fore, designing TaON‐involved photocatalysts with effective $\\mathrm{e^{-}{\\cdot}h^{+}}$ separation and superior redox power is full of opportuni‐ ties and challenges. \n\nThe emerging S‐scheme heterojunction system is endowed with notable merits of effective $\\mathrm{e^{-}{\\cdot}h^{+}}$ separation and great photo‐redox power, therefore achieving the upgraded photo‐ catalytic property [22–40]. Noticeably, the formed internal electric field (IEF) at the hetero‐interface promotes the reinte‐ gration of weak photo‐carriers and simultaneously achieves the effectively spatial separation of powerful ones. Furthermore, the introduction of oxygen vacancies (OVs) into the heterojunc‐ tions is a pragmatic route to advance the catalytic performance via the optimization of the light absorption and the improve‐ ment of $\\mathrm{e^{-}{\\cdot}h^{+}}$ disassociation [41,42]. Thus, seeking for a proper oxidation photocatalyst to build TaON‐based S‐scheme hetero‐ junction with OVs is a promising choice. Bi2WO6 $E_{\\mathrm{g}}\\approx2.6\\mathrm{-}2.85$ eV) as a classic material of the aurivillius family demonstrates vast potential for visible‐light photocatalysis, owing to its good photo‐chemical/electronic properties, non‐toxicity, rich source, and remarkable oxidation potential of $\\mathrm{VB\\h^{+}}$ [43,44]. Noticea‐ bly, the exceptional characteristics and markedly varied work functions of both TaON and ${\\mathrm{Bi}}_{2}{\\mathrm{W}}{0}_{6}$ are indicative of the high practicability of creating $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ S‐scheme heterojunc‐ tion. \n\nInterface design between semiconductors is another key factor in attaining high‐performance S‐scheme photocatalysts. Especially, unique 1D/2D core‐shell heterostructures with closely contacted interface have demonstrated some admirable advantages of exposing abundant active sites and fostering interfacial transport of $\\mathrm{e^{-}{\\cdot}h^{+}}.$ , which are in favor of the photore‐ action [45–47]. \n\nEnlightened by the above facts, we design an unique S‐scheme core‐shell 1D/2D heterostructure of $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ with OVs built by in‐situ growth of ${\\mathrm{Bi}}_{2}{\\mathrm{W}}{0}_{6}$ (BWO) nanosheets (NSs) with OVs on TaON (TON) nanofibers (NFs) for boosted photocatalytic pharmaceuticals degradation and $\\mathrm{Cr(VI)}$ reduc‐ tion. The TON NFs synthesized by electrospinning route are comprised of nanoparticles, presenting loose and interweaved network, which renders TON NFs an ideal support to grow BWO NSs. It was revealed that the S‐scheme mechanism as‐ sisted by OVs contributes to the remarkable activity enhance‐ ment towards the destruction of antibiotics and $\\mathrm{Cr(VI)}$ under \n\nvisible light irradiation. \n\n# 2. Experimental \n\nThe content of sample characterization, degradation prod‐ uct determination, and intermediate eco‐toxicity analysis are shown in Supporting Information. \n\n# 2.1. Synthesis of catalysts \n\n# 2.1.1. Synthesis of TaON nanofibers \n\nThe synthesis of TON NFs was accomplished by a simple electrospinning route. To be brief, the spinning solution com‐ posed of $\\mathrm{Ta(OEt)_{4}}$ $(10~\\mathrm{wt\\%})$ , polyvinylpyrrolidone (PVP) (5 $\\mathrm{wt\\%})$ ) and ethanol/acetic acid (3.3:1) mixed solution were magnetically agitated for $20\\mathrm{~h~}$ . Afterwards, the obtained clear spinning solution was poured into a $10~\\mathrm{mL}$ syringe for electro‐ spinning. The electrospun NFs were sintered at $600^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{~h~}}$ to get Ta2O5 NFs. After that, TON NFs was acquired by the proper nitridization of $\\mathrm{Ta}_{2}0_{5}$ NFs at $850^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{h}}$ in ammonia. \n\n# 2.1.2. Synthesis of TaON/OVs‐mediated Bi2WO6 (TON/BWO) core‐shell nanofibers \n\nBriefly, $N a_{2}\\mathrm{W}0_{4}{\\cdot}2\\mathrm{H}_{2}0$ (0.2 mmol, $0.066\\mathrm{g})$ and 1 $3\\mathrm{i}(\\mathrm{NO}_{3})_{3}{\\cdot}5\\mathrm{H}_{2}0$ (0.4 mmol, 0.194 g) were sequentially placed in $40~\\mathrm{mL}$ ethylene glycol with ultra‐sonication for $30~\\mathrm{min}$ . After addition of a certain amount of TON NFs, the resultant mixture was stirred for $^{10\\mathrm{~h~}}$ to get the well‐dispersed suspension, which was then reacted at $150~^{\\circ}\\mathrm{C}$ for $20\\mathrm{~h~}$ in a Teflon‐lined autoclave. The cooled precipitants were washed fully. Note that the obtained materials are marked as BWO/TON‐1, BWO/TON‐2, and BWO/TON‐3, according to the TON/BWO mass ratios of $10\\mathrm{\\:wt\\%}$ , $20\\mathrm{wt\\%},$ and $30\\mathrm{wt\\%}$ respectively. Pris‐ tine BWO was prepared in the identical manner without TON NFs. \n\n# 2.2. Photocatalytic experiments \n\nThe photocatalytic degradation of antibiotics (TC $(20{\\mathrm{~mg/L}},$ $100~\\mathrm{{mL},}$ $\\mathrm{pH}5.2\\AA$ ) and LEV $(20~\\mathrm{mg/L},100~\\mathrm{mL},\\mathrm{pH}~6.7)\\big]$ and re‐ duction of $\\operatorname{Cr}(\\mathrm{{VI})}$ ( ${\\mathrm{~\\cdot~}}10{\\mathrm{~mg/L}}$ $100~\\mathrm{{mL}}$ , $\\mathrm{pH}=2.5\\$ ) over the cata‐ lysts $\\mathrm{20~mg)}$ were executed in a photocatalytic reactor under simulated visible‐light photons (300 W xenon lamp, $\\lambda\\geq420$ nm). Prior to illumination, the contaminant solutions and cata‐ lysts were mixed completely with sonicating for $20~s$ and stir‐ ring for $30~\\mathrm{{min}}$ in darkness. During the irradiation, the disper‐ sion was periodically taken and centrifuged to take out the catalysts prior to analysis. The concentrations of TC and LEV were measured using a UV‐vis spectrophotometer at wave‐ length of 357 and $291{\\mathrm{~nm}}$ , respectively. Meanwhile, the $\\mathrm{Cr(VI)}$ concentration was determined on a UV‐vis spectrophotometer at $540~\\mathrm{nm}$ basing on the 1,5‐diphenylcarbazide (DPC) ap‐ proach. Five‐cycle experiments on the removal of TC, LEV and $\\mathrm{Cr(VI)}$ were conducted to check the stability of the sample. Spe‐ cifically, after each run, the sample was recovered by centrifu‐ gation, washed with deionized water and dried at 60 in an oven for next run. The total organic carbon (TOC) measurements for TC degradation were conducted by applying a TOC analyzer (Shimadzu TOC‐LCSH/CPH). The photocatalytic tests were implemented in triplicate to avoid error. \n\n# 2.3. Active substance determination \n\nScavenger experiments were implemented to unravel the contribution of different active substances in photocatalytic decontamination of TC and $\\mathrm{Cr(VI)}$ over BWO/TON‐2 via intro‐ ducing various agents into the catalytic system, including ${\\mathrm{KBrO}}_{3},$ isopropanol (IPA), 2,2,6,6‐tetramethylpiperidinooxy (TEMPO), and ethylenediaminetetraacetic acid disodium salt (EDTA‐2Na). Electron spin resonance (ESR) analysis was per‐ formed on a spectrometer (Bruker ESR 300E) for the identifi‐ cation of $\\bullet0\\mathrm{H}$ in water and $0z^{\\bullet-}$ in methanol solutions, respec‐ tively. \n\n# 3. Results and discussion \n\n# 3.1. Phases and morphologies \n\nTaON/OVs‐mediated ${\\mathrm{Bi}}_{2}{\\mathrm{W}}{\\mathrm{O}}_{6}$ (TON/BWO) S‐scheme nano‐ fibers were synthesized via an electrospinning‐sovothermal reaction route (Fig. 1). The TON NFs built by nanoparticles (NPs) are first prepared by an electrospinning route and these NFs are interleaved to form a loose fibrous network, which renders TON NFs a perfect substrate to anchor BWO NSs. Next, the in‐situ growth of BWO NSs on TON NFs via a solvothermal treatment gives birth to TON/BWO heterojunction nanofibers. \n\nX‐ray diffraction (XRD) patterns of TON, BWO, and TON/BWO heterojunctions are displayed in Fig. 2. The XRD patterns of TON and BWO are in well agreement with mono‐ clinic TaON (JCPDS 41‐1104) and orthorhombic ${\\mathrm{Bi}}_{2}{\\mathrm{W}}{0}_{6}$ (JCPDS 73‐1126), respectively. The XRD profiles of TON/BWO hetero‐ junctions display the typical peaks of both TON and BWO, con‐ firming the presence of TON and BWO in the heterojunctions. Further, the combination of TON and BWO makes the slight shift of the diffraction peaks, which is attributed to the strong interactions between the semiconductors. The XRD result im‐ plies the successful synthesis of TON/BWO composites. \n\nThe microstructures of TON and TON/BWO heterojunctions were visualized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). As seen in Figs. 3(a), (e), TON present the fibrous network composed of porous NFs (diameter: ${\\sim}100{\\mathrm{-}}200~\\mathrm{nm}$ ), which are assembled by nanoparti‐ cles. Note that the surface of the NFs is smooth. All the TON/BWO heterojunctions consist of interwoven nanofibers with rough surfaces due to that BWO 2D NSs are anchored on the surface of 1D NFs (Figs. 3(b)‒(d), (f)‒(g)). Notably, TON/BWO–2 presents a unique 1D/2D core‐shell architecture, where numerous 2D BWO NSs with the dimension scope of ${\\sim}150{\\mathrm{-}}450~\\mathrm{nm}$ are uniformly grown onto 1D TON NFs to create 1D/2D core‐shell fibrous hetero‐structure with closely con‐ nected interface (Figs. 3(c), (g)). This compact combination is favorable to the separation of photo‐excited charge carriers. The TEM (Figs. 3(i), (g)) and HRTEM (Fig. 3(k)) were further applied to analyze TON/BWO‐2. The TEM image confirms the 1D/2D core‐shell fibrous hetero‐structure of TON/BWO‐2 (Figs. 3(i), (j)). Two sets of lattice fringes of 0.28 and $0.32~\\mathrm{nm}$ appeared in the HRTEM are assigned to the (111) crystal facet of TON (JCPDS 41‐1104) and (113) crystal facet of BWO (JCPDS 73‐1126), respectively (Fig. 3(k)). The energy dispersive X‐ray spectroscopy(EDS) spectrum (Fig. S1) and elemental mappings (Fig. S2) collectively certify the presence of Ta, N, O, Bi, and W elements in TON/BWO‐2, further demonstrating the synthesis of the TON/BWO hybrid. \n\n![](images/671a3812d23e69acbf3b23b30a3710856cb8cba6d47f885a0cb5340dbcf30144.jpg) \nFig. 1. A scheme of the synthesis procedure of TON/BWO heterojunc‐ tion nanofibers. \n\n![](images/e3fa39aca3f3383a32e2c3d9bfa6cb0814433a62e0f77e062929f259dbeebbee.jpg) \nFig. 2. XRD patterns of TON, BWO, and TON/BWO heterojunctions. \n\nThe chemical compositions and states of BWO, TON, and TON/BWO‐2 were explored by X‐Ray photoelectron spectros‐ copy (XPS) (Fig. 4). The survey spectrum of TON/BWO‐2 veri‐ fies the heterojunction is composed of Ta $4f,$ O 1s, N 1s, Bi $4f,$ and W $4f$ (Fig. 4(a)), confirming the co‐existence of TON and BWO, which is in accordance with the XRD (Fig. 2), EDX (Fig. S1, S2), and TEM analyses (Fig. 3(k)). For TON, two peaks with binding energies of 25.20 and $27.00\\ \\mathrm{eV}$ are assigned to $\\mathrm{Ta^{5+}}$ $4f_{7/2}$ and $\\mathrm{Ta}^{5+}4f_{5/2}$ (Fig. 4(b)) [16]. One clear peak appeared at $395.9\\mathrm{eV}$ corresponds to $\\mathsf{N}^{3-}$ 1s (Fig. 4(c)) [18]. For BWO, the Bi 4f XPS spectrum exhibits two peaks centered at 158.35 and $163.70\\mathrm{eV}.$ , which pertain to $\\mathrm{Bi}^{3+}4f_{7/2}$ and $\\mathrm{Bi}^{3+}4f_{5/2}$ , respectively [48,49] (Fig. 4(d)). Two peaks of $\\mathsf{W}^{6+}~4f_{7/2}$ and $\\mathsf{W}^{6+}~4f_{5/2}$ are situated at 34.40 and $36.45\\mathrm{~eV}$ , respectively (Fig. 4(e)) [25,50]. Three O 1s peaks with binding energies of 530.10, 531.15 and $532.30~\\mathrm{eV}$ belong to lattice oxygen, defective oxygen, and the adsorbed oxygen (Fig. 4(f)). Notably, in TON/BWO‐2, the bind‐ ing energies of Ta 4f, O 1s and N 1s shift positively with respect to those of TON. Conversely, the binding energies of Bi 4f, O 1s and W 4f shift negatively compared with those of BWO. Such variations suggest the existence of TON‐to‐BWO electron movement upon the hybridization of them, leading to the crea‐ tion of an IEF directing from TON to BWO at the interface. The above XRD, SEM, TEM, EDS, EDS‐mapping and XPS results cor‐ roborate the triumphant synthesis of TON/BWO heterojunc‐ tions with compact connection. \n\n![](images/c380bba0aaa04d6d6e1b18903217e98888f522b7be19c43c1db2314fb4d99f7c.jpg) \nFig. 3. SEM images of TON (a,e), TON/BWO‐1 (b,f), TON/BWO‐2 (c,g), and TON/BWO‐3 (d,h). TEM images (i,j), and HRTEM image (k) of TON/BWO‐2. \n\n![](images/1f2d6dcf25674a236c8750820ee6e9a2034808d1b37c560ebc9ed574b42ccdb1.jpg) \nFig. 4. XPS survey spectrum (a) and high resolution XPS spectra of Ta $4f$ (b), N 1s (c), Bi 4f (d), W 4f (e), and O 1s (f) of TON, BWO and TON/BWO‐2. \n\n# 3.2. Photocatalytic performance \n\n# 3.2.1. Photocatalytic destruction of antibiotics \n\nPhotocatalytic properties of BWO, TON and TON/BWO het‐ erojunctions were evaluated by the photocatalytic degradation of antibiotics (TC and LEV) and reduction of $\\operatorname{Cr}(\\mathrm{{VI})}$ . Fig. 5(a) presents the photo‐degradation performance of TC over the synthesized samples. Control experiment exhibits that no TC is decomposed under visible light without a photocatalyst. The degradation efficiency of TC by BWO and TON within $50\\mathrm{min}$ is merely $51.7\\%$ and $23.7\\%$ , respectively, indicating their limited catalytic activity. Excitingly, the TON/BWO heterojunctions demonstrate impressively better photocatalytic abilities to degrade TC ( $58.8\\%$ for TON/BWO‐1, $93.2\\%$ for TON/BWO‐2, and $82.1\\%$ for TON/BWO‐3), evidencing the advantages of building TON/BWO S‐scheme heterojunction in the enhance‐ ment of photocatalytic behavior. TON/BWO‐2 is found to be the most effective, signifying that the catalytic performance of TON/BWO is dependent on the molar ratio of TON/BWO in the heterojunction. In addition, a mechanical mixture of $16.7~\\mathrm{wt\\%}$ TON and $83.3~\\mathrm{wt\\%}$ BWO exhibits a far poorer activity $(35.7\\%)$ than TON/BWO‐2 $(93.2\\%)$ , highlighting the significance of a close connection between the constituents for photoreaction. The apparent rate constant $(k)$ is acquired with the well fitted pseudo‐first‐order kinetic curves (Fig. 5(b)). TON/BWO–2 manifests the largest $k$ of $0.0527\\mathrm{min}^{-1}$ , which is about 10.9, 3.8 and 6.3 times that of TON $\\left(0.0048\\operatorname*{min}^{-1}\\right)$ ), BWO $\\left[0.0140\\mathrm{min^{-1}}\\right]$ ), and the mixture $(0.0083\\mathrm{min^{-1}})$ , respectively. \n\nThe impact of some pivotal environmental factors (e.g., cat‐ alyst dosage, pH, common ions and actual waters on the pho‐ tocatalytic TC degradation over TON/BWO‐2 were evaluated (Figs. 5(c)‒(f) and Fig. S3). From Fig. 5(c), as the TON/BWO‐2 dosage is augmented from 10 to $30\\mathrm{mg},$ the catalytic behavior is upgraded because of the increased active sites. Further aug‐ menting TON/BWO‐2 dosage up to $50~\\mathrm{mg}$ restrains the TC degradation, probably caused by the shielding effect and/or agglomeration of excessive catalysts [51,52]. Note that the cat‐ alytic efficacy achieved by using $20~\\mathrm{mg}$ is similar to that apply‐ ing $30~\\mathrm{mg}.$ Thus, the dosage of $20~\\mathrm{mg}$ is selected. From Fig. S3, TON/BWO‐2 exhibits the best catalytic performance at $\\mathsf{p H}\\ 9_{\\mathsf{i}}$ indicating the alkaline environment in conducive to the TC degradation. As shown in Fig. 5(d), $\\mathrm{Cl^{-}}$ or ${\\mathsf{N O}}_{3}{}^{-}$ ions has little effect on the TC degradation. Nevertheless, the addition of $S0_{4}2–$ – and $\\mathrm{CO}_{3}2\\mathrm{-}$ renders the TC degradation rate decrease from $93.2\\%$ to $75.1\\%$ and $80.6\\%$ , probably due to that $S0_{4}2-$ and $\\mathsf{C O}_{3}^{-}$ could take up some active substances [49,52]. The catalyt‐ ic performance of TON/BWO‐2 in real water bodies (deionized water, tap water, and river water) was evaluated (Fig. 5(e)). It is found that the TC degradation rates by TON/BWO‐2 in tap water $(88.7\\%)$ and river water $(69.7\\%)$ are lower than that in deionized water $(93.2\\%)$ . That is due to the chemicals of prac‐ tical water sources compete with TC for reactive sites [23,53]. The result indicates TON/BWO‐2 has a promising potential for aqueous environmental restoration. \n\n![](images/71fa805fdfd68e5d091c8ce2d66af1db51514b585211d2a5b0b726538c5b6eca.jpg) \nFig. 5. The photocatalytic property of TON, BWO and TON/BWO heterojunctions in TC degradation (a) and photoreaction kinetics under visible light (b). Impact of some pivotal parameters: catalyst dosage (c), ions $\\left(C=0.05\\mathrm{\\mol/L}\\right)$ (d), and water matrices (e), on the TC abatement efficacy over TON/BWO‐2. (f) Recycle test on TC degradation over TON/BWO‐2. The photocatalytic activity of TON, BWO and TON/BWO‐2 in LEV degradation (g) and photoreaction kinetics under visible light (h). (i) Recycle test on LEV abatement over TON/BWO‐2. \n\nFrom the perspective of practical application, the stability and reusability of TON/BWO‐2 were checked by implementing five successive runs of TC degradation (Fig. 5(f)). Noticeably, TON/BWO‐2 demonstrates high photocatalytic stability and the TC degradation rate is still up to $84.4\\%$ at the fifth run. Further XRD (Fig. S4) and SEM (Fig. S5) analyses reflect the recycled TON/BWO‐2 exhibits no remarkable changes in the phase and morphology, verifying the high stability of TON/BWO‐2. \n\nAs a significant advantage of a photocatalyst, the minerali zation behavior of TON/BWO‐2 was appraised by total organic carbon (TOC) measurement. From Fig. S6, the TOC removal rate of TC by TON/BWO‐2 is up to ${\\sim}57.1\\%$ after $50\\mathrm{min}$ of visi‐ ble‐light illumination, confirming the robust mineralization ability of TON/BWO‐2. \n\nTo confirm the non‐selective photocatalytic potentiality of TON/BWO‐2 for antibiotic degradation, the photocatalytic ex‐ periments of TON/BWO‐2 for LEV degradation were conducted (Fig. 5(g)). As expected, TON/BWO‐2 unveils the best catalytic activity for LEV degradation, and the LEV degradation rate constant $(k)$ is up to $0.0307\\ \\mathrm{min^{-1}}$ , which is about 7.1, 1.0 and 2.6 folds greater than that of TON $\\left(0.0038\\operatorname*{min}^{-1}\\right)$ , BWO (0.0152 $\\operatorname*{min}^{-1}.$ ), and the mixture $\\left(0.0086\\operatorname*{min}^{-1}\\right)$ ), respectively (Fig. 5(h)). Further, the recycling durability of TON/BWO‐2 was further investigated, and the results further evidence the high stability of TON/BWO‐2. Beyond that, the TON/BWO‐2 also can effec‐ tively mineralize the LEV with the LEV TOC removal rate of ${\\sim}43.3\\%$ within $60\\ \\mathrm{min}$ (Fig. S7). These above photocatalytic experiments suggest that TON/BWO‐2 has the significant po‐ tential for the degradation of pharmaceutical antibiotics. \n\n# 3.2.2. Degradation routes and eco‐toxicity analysis \n\nTo unclose the TC decomposition process and assess the variation of the eco‐toxicity in the TON/BWO system, the MALDI‐TOF‐MS spectrometry was adopted to identify the in‐ termediates at reaction time of 0, 25 and $50\\ \\mathrm{min}$ (Fig. S8). Clearly, as the reaction progresses, the TC signal $(m/z\\ =$ 445.16) is decreased drastically along with the emergence of new peaks, evidencing the decomposition of TC into intermedi‐ ates. Based on the produced intermediates (Table S1), two pathways are deduced for the degradation of TC over TON/BWO‐2 (Fig. 6(a)). In pathway I, the generation of P1 $(m/z=481)$ is realized through the hydroxylation of TC under the attack of •OH species. Subsequently, it undergoes a series of reactions (e.g., deamidation, demethylation, deamination and dihydroxylation) for P2 $\\left(m/z=331\\right)$ . Then P3 is formed via ring‐opening reaction induced by $\\bullet0_{2}^{-}$ and $\\mathbf{h}^{+}$ . Further, P3 $(m/z$ $=236\\vec{\\bf\\Phi}.$ ) is transformed into P4 $(m/z=194)$ ) by demethylation and the loss of a methanol group. In pathway II, TC is directly demethylated to produce P5 $(m/z=417)$ , due to the attack of $\\bullet0_{2}\\overline{{\\cdot}}$ and •OH. P5 is further converted into P6 $\\left(m/z=433\\right)$ ) via the hydroxylation reaction. P6 is degraded into P7 $\\left(m/z=349\\right)$ ) via multi‐step fragmentations, including deamidation and di‐ hydroxylation and ring cleavage. After that, P7 is further disin‐ tegrated along with ring opening, hydroxyl elimination and oxidation reaction to generate P8 $(m/z=305)$ and P9 $(m/z=$ 261). As the catalytic reaction goes on, the above chemicals are further split into low‐molecular‐weight products P10 $(m/z=$ 114), P11 $(m/z=214)$ , P12 $(m/z=158)$ and P13 $(m/z=136)$ under the assault of $\\bullet0\\mathrm{H}$ , $\\ln^{+}$ and $\\bullet0_{2}\\overline{{^{-}}}$ . Ultimately, these organic compounds would be mineralized to $\\mathrm{CO}_{2},\\mathrm{H}_{2}0$ and other small molecules, as certified by the TOC analysis (Fig. S6). \n\nThe eco‐toxicity (e.g., fathead minnow $\\mathrm{LC}_{50}$ (96 h), daphnia magna LC50 $(48\\ \\mathrm{h})$ , and developmental toxicity) of TC and its intermediates was further appraised by employing the toxicity estimation software tool (T.E.S.T.) on the basis of QSAR predic‐ tion (Table S2). The acute toxicity were assessed by fathead minnow $\\mathrm{LC}_{50}$ (96 h) and daphnia magna LC50 (48 h) (Fig. 6(b), (c)). The $\\mathrm{LC}_{50}$ values of fathead minnow and daphnia magna for TC are $0.90\\mathrm{mg/L}$ and $8.70~\\mathrm{{mg/L},}$ which are considered as “very toxic” and “harmful” drug, respectively. The $\\mathrm{LC}_{50}$ values of fat‐ head minnow and daphnia magna for all intermediates except P5 are higher than that of TC, demonstrating the toxicity of intermediate products decreases dramatically. Similar results are found for the developmental toxicity (Fig. 6(d)). All the degradation products except P8 manifest lower developmental toxicity than TC. Notably, the developmental toxicity values of P10 and P13 are 0.32 and 0.41, respectively, which reflects that they belong to developmental non‐toxicant $(<0.5)$ . The results indicate that the eco‐toxicity of TC solutions can be effectively abated in the TON/BWO‐2 photocatalytic system. \n\n![](images/ab73cf847a2f2faeab571d4da5156c28cacf00809b310f045f3dab355458e49d.jpg) \nFig. 6. TC decomposition routes over TON/BWO‐2 (a), daphnia magna $\\mathrm{LC}_{50}$ (b), fathead minnow $\\mathrm{LC}_{50}$ (c), and developmental toxicity evaluation (d). \n\n# 3.2.3. Photocatalytic reduction of Cr(VI) \n\nPhotocatalytic experiments for the $\\mathrm{Cr(VI)}$ reduction were conducted to assess the visible‐light photocatalytic reduction potentiality of BWO, TON and TON/BWO‐2 (Fig. 7(a)). TON/BWO‐2 accomplishes $95.6\\%$ $\\mathrm{Cr(VI)}$ reduction within 50 min, which far outperforms TON $(47.5\\%)$ , BWO $(66.8\\%)$ , and the mixture $(58.7\\%)$ (Fig. 7(a)). This indicates that the fabrica‐ tion of TON/BWO S‐scheme heterojunction is capable of ad‐ vancing the electrons/holes separation and sustaining the strong reduction potential of photo‐excited electrons for $\\mathrm{Cr(VI)}$ reduction. The k of TON/BWO‐2 in $\\mathrm{Cr(VI)}$ reduction is as high as $0.0591\\ \\mathrm{min}^{-1}$ , which is 2.9, 5.1 and 3.7 folds that of BWO ( $0.0206\\ \\mathrm{min^{-1}}\\mathrm{.}$ ), TON $(0.0117\\ \\mathrm{min^{-1}}^{\\cdot}$ ), and the mixture (0.0161 $\\operatorname*{min}^{-1}.$ ), respectively (Fig. 7(b)). In this regard, TON/BWO‐2 has a remarkable potential as a $\\operatorname{Cr}(\\operatorname{VI})$ photo‐reduction candidate. \n\nThe photocatalytic $\\mathrm{Cr(VI)}$ removal efficacy over TON/BWO‐2 under various $\\mathsf{p H}$ conditions was examined. As exhibited in Fig. 7(c), the catalytic behavior of TON/BWO‐2 weakens with augmenting the $\\mathrm{\\tt{pH}},$ due to the abundant $\\mathrm{H^{+}}$ ions are available to the reduction of $\\mathrm{Cr(VI)}$ into $\\mathrm{Cr}(\\mathrm{III})$ [3,49]. By contrast, the strong alkaline environment promotes the for‐ mation of $\\mathrm{Cr}(\\mathrm{III})$ precipitation, which takes up the reaction sites of TON/BWO‐2 and undermines $\\operatorname{Cr}(\\operatorname{III})$ photo‐reduction. Thus, the acid environment is beneficial to $\\mathrm{Cr(VI)}$ reduction and the TON/BWO‐2 delivers the highest photocatalytic $\\mathrm{Cr(VI)}$ reduc‐ tion activity $(95.6\\%)$ at $\\mathrm{pH}=2.5$ . \n\nTo further verify its practicability, the catalytic experiments of TON/BWO‐2 for $\\mathrm{Cr(VI)}$ reduction were implemented in de‐ ionized water, tap water, and river water, respectively (Fig. 7(d)). It is revealed that TON/BWO‐2 is capable of efficiently reducing $\\mathrm{Cr(VI)}$ in these water sources. The moderate activity decline in tap water and river water can be attributed to the substances in them interfere with $\\mathrm{Cr(VI)}$ removal. \n\nThe stability of TON/BWO‐2 was further evaluated by recy‐ cling photocatalytic $\\mathsf{C r}(\\mathsf{V I})$ reduction experiments (Fig. S9). Distinctly, no appreciable decrease of the catalytic activity is detected after five cycles and the $\\mathrm{Cr(VI)}$ reduction rate still reaches up to $82.8\\%$ in the fifth run, confirming a robust stabil‐ ity of TON/BWO‐2. \n\nOn basis of the photocatalytic experiments, TON/BWO‐2 holds a great potential for photocatalytic decontamination of pharmaceutical antibiotics and $\\mathrm{Cr(VI)}$ . \n\n# 3.3. Photocatalytic mechanism \n\nTrapping experiments and ESR measurements were im‐ plemented for in‐depth comprehension of the photocatalytic mechanism. The photoreaction are driven by the pho‐ to‐generated reactive substances, primarily including e–, •OH, $\\bullet0_{2}\\overline{{{\\bf\\psi}}}$ , and $\\mathbf{h}^{+}.$ , which can be scavenged by ${\\mathrm{KBrO}}_{3},$ IPA, TEMPO, and EDTA‐2Na, respectively. The photocatalytic TC degradation and $\\mathrm{Cr(VI)}$ reduction efficacy within $50~\\mathrm{min}$ over TON/BWO–2 in the presence of quenchers were evaluated and the results are presented in Figs. 8(a) and (b). From Fig. 8(a), the suppres‐ sive effect of the quenchers on TC degradation follows the se quence $\\mathrm{TEMPO}>\\mathrm{IPA}>$ EDTA‐2Na. Thus, •OH and $\\bullet0_{2}\\overline{{{}}}$ are the dominant reactive species of the reaction while $\\ln^{+}$ plays an auxiliary role in TC degradation. From Fig. 8(b), the $\\mathrm{Cr(VI)}$ re‐ duction has hardly been affected by IPA, suggesting the negligi‐ ble role of •OH. EDTA‐2Na shows a positive effect on the $\\mathrm{Cr(VI)}$ photo‐reduction, which is mainly originated from the improved separation of photo‐generated high‐energetic $\\mathbf{e}^{-}$ for $\\mathrm{Cr(VI)}$ re‐ duction. By contrast, the $\\mathrm{Cr(VI)}$ reduction is substantially su pressed by ${\\mathrm{KBrO}}_{3}$ and TEMPO, signifying that $\\mathrm{Cr(VI)}$ reduction is dominated by $\\mathbf{e}^{-}$ and $\\bullet0_{2}\\overline{{^{-}}}$ . \n\n![](images/825e8a744761609e616bb99d80e3c6c85e0157915b895407bca73f3b1e26d478.jpg) \nFig. 7. (a) The photocatalytic property of TON, BWO and TON/BWO‐2 in $\\mathrm{Cr(VI)}$ reduction and (b) reaction kinetics under visible light. The influence of pH (c) and water bodies (d) on $\\mathrm{Cr(VI)}$ reduction efficiency over TON/BWO‐2. \n\nESR tests were implemented to unravel the mechanism of photo‐activity enhancement. From Figs. 8(c), (d), TON displays the characteristic ${\\tt D M P O-}{\\bullet}{0}_{2}{^{-}}$ signal, whereas the DMPO‐•OH signal is not identified. This phenomenon is due to that the VB $\\mathbf{h}^{+}$ of TON cannot induce the formation of •OH in view of its EVB (1.89 V) more negative than $\\mathrm{H}_{2}0/{\\bullet}0\\mathrm{H}$ (2.40 V) or $\\mathrm{\\Delta0H^{-}/{\\bullet0H}}$ (1.99 V). On the contrary, the typical DMPO‐•OH signal rather than ${\\tt D M P O-}{\\tt O}_{2}{\\tt^{-}}$ signal is observed in the BWO system, due to its $\\mathrm{CB~e^{-}}$ is not capable of reducing $0_{2}$ to yield $0_{2}\\mathrm{^-}$ in light of its $E_{\\mathrm{CB}}$ (0.31 V) less negative than $0_{2}/{\\bullet}0_{2}^{-}$ (–0.33 V). Notably, the ${\\tt D M P O-}{\\tt O}_{2}{\\tt^{-}}$ and DMPO‐•OH signal intensity of TON/BWO‐2 are prominently strengthened as compared to that of TON or BWO (Figs. 8(c), (d)), implying the interfacial charge transportation should comply with the S‐scheme mechanism instead of type‐II mechanism, which pronouncedly avails the formation of $\\bullet0z^{-}$ and •OH substances \n\nTo unveil the part of the contact between the antibiotic and TON/BWO nanofibers in the antibiotic degradation, a separa‐ tion system was delicately designed and put up (Fig. 8(e)) [54]. A sealed dialysis bag containing $50~\\mathrm{mL}$ of $20~\\mathrm{{mg/L}}$ TC solution is placed in $200~\\mathrm{{mL}}$ deionized $\\mathrm{H}_{2}0$ in the container. Note that reactive substances and ions, excluding TON/BWO‐2 sample, can readily penetrate into the dialysis bag. From Fig. 8(f), the control test reflects that about $23.2\\%$ of TC molecules could seep through the bag into the outer system with $50\\mathrm{min}$ of irra‐ diation. When TON/BWO‐2 nanofibers are introduced in outer system, there is no apparent decline in the TC concentration after $50~\\mathrm{min}$ of irradiation compared with the control experi‐ ment, implying that TON/BWO‐2 could not effectively degrade the TC solutions sealed in the dialysis bag. By contrast, TON/BWO‐2 has completely decomposed all the TC outside the bag, signifying that TON/BWO‐2 could effectively decompose the surrounded TC molecules via ROS species. This fact con‐ firms the significant role of the intimate contact between TON/BWO–2 and antibiotics in the sufficiently photocatalytic elimination of antibiotic by TON/BWO‐2. \n\nThe Brunauer‐Emmett‐Teller (BET) surface area (ABET) as a significant indicator for the photoreaction was determined by ${\\sf N}_{2}$ adsorption‐desorption isotherms. From Fig. S10, all the tested samples manifest type IV isotherms, suggesting the mesoporous architecture. Noticeably, all the TON/BWO het‐ erojunction NFs present larger ABET $(42.09\\mathrm{~\\bf~m}^{2}\\mathrm{~\\bf~g}^{-1}$ for TON/BWO‐1, $44.34~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ for TON/BWO–2, and $44.81\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}$ for TON/BWO‐3) than pristine TON $\\left(10.64\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}\\right)$ , which is originated from the creation of hierarchical 1D/2D hetero‐ structure. Actually, the high ABET is conducive to photoreaction [6,52]. \n\nThe photo/electrochemical characteristics and photolumi‐ nescence spectra of the synthesized samples were collected to explore the charge separation rates (Fig. 9). The pho‐ to/electrochemical characteristics were analyzed via transient photocurrent response (TPR) (Fig. 9(a)) and electrochemical impedance spectra (EIS) tests (Fig. 9(b)). Fundamentally, the stronger TPR represents more photo‐excited $\\mathrm{e^{-}{\\cdot}h^{+}}$ pairs are effectively separated [55–58]. In comparison with TON and BWO, TON/BWO heterojunctions exhibit an appreciable in‐ crease of photocurrent intensity, signifying that the superior $\\mathrm{e^{-}{\\cdot}h^{+}}$ separation efficiency of these heterojunction. Note that TON/BWO‐2 achieves the strongest TPR, suggesting the best charge separation efficiency. Fig. 9(b) displays the EIS of TON, BWO, and TON/BWO heterojunctions. Basically, the arc radius is proportional to the intrinsic charge transit resistance. Clear‐ ly, TON/BWO‐2 manifests the smallest Nyquist plot diameter, demonstrating the best electronic conductivity of TON/BWO‐2. Furthermore, the photoluminescence (PL) spectra and time‐resolved PL spectra (TRPL) of the samples were recorded and the results are presented in Figs. 9(c), (d). In general, the stronger the PL signal, the severer the $\\mathrm{e^{-}{\\cdot}h^{+}}$ recombination [31,37]. Evidently, the PL emission intensities comply with the order $\\mathrm{BWO}>\\mathrm{TON/BWO}-1>\\mathrm{TON/BWO}-3>\\mathrm{TON/BWO}-2,\\mathrm{i}$ m‐ plying that constructing TON/BWO S‐scheme heterojunctions can effectively retard photo‐induced $\\mathrm{e^{-}{\\cdot}h^{+}}$ reunion. It is worthy of emphasis that TON/BWO‐2 obtains the highest photocur‐ rent, the smallest resistance, and the lowest PL intensity, which principally contributes to the optimal catalytic performance. Further, the TRPL spectra of BWO and TON/BWO‐2 were fitted using the biexponential function: $y=y_{0}\\ +\\ A_{1}\\mathrm{exp}(-t/\\tau_{1})\\ +\\ A_{2}$ $e x p(-t/\\tau_{2})+A_{3}\\mathrm{exp}(-t/\\tau_{3})$ (1). As expected, TON/BWO–2 owns longer average carrier lifetime $(\\tau_{\\mathrm{avg}}\\colon0.622\\ \\mathrm{ns})$ than BWO ( $\\dot{\\tau}_{\\mathrm{avg}}$ : $0.444\\mathrm{~ns}]$ , evidencing the enhancement of the overall $\\mathrm{e^{-}{\\cdot}h^{+}}$ separation efficiency. \n\n![](images/51ee08bd4b11086ab521e0fae8c82ed5b04196af1ed523ee51b901ec154e7609.jpg) \nFig. 8. Photocatalytic removal of TC (a) and of $\\mathrm{Cr(VI)}$ (b) with the introduction of various trapping agents over TON/BWO‐2. ESR spectra of the $\\mathrm{DMPO{-}{\\bullet}O_{2}}^{-}$ (c) and $\\mathrm{DMPO-}{\\bullet}0\\mathrm{H}$ (d) over TON, BWO and TON/BWO‐2 with $5~\\mathrm{min}$ of visible‐light illumination. (e) A scheme of the reactor with the separation dialysis bag. (f) Percentages of TC inside and outside the dialysis bag. \n\n![](images/38bffa4c692c98fec51ef52dbe98be5a1016f99a5e919f43f286db14ed305af2.jpg) \nFig. 9. TPR (a), and EIS (b) plots of BWO, TON and TON/BWO heterojunctions. (c) PL of BWO and TON/BWO heterojunctions. (d) TRPL of BWO and TON/BWO‐2. \n\nThe above TPR, EIS, PL and TRPL analyses (Fig. 9) collec‐ tively certify fabricating TON/BWO S‐scheme heterojunction is conducive to boosting the spatial separation of $\\mathbf{e}^{-}$ and $\\ln^{+}$ with optimal redox power, leading to the photocatalytic perfor‐ mance enhancement. \n\nTo better comprehend the photoreaction mechanism, the electronic structure ( $\\cdot E_{\\mathrm{CB}}$ and $\\scriptstyle{E_{\\mathrm{VB}}}]$ of TON and BWO were ana‐ lyzed using UV‐Vis DRS and Mott‐Schottky (M‐S) plots. The UV‐Vis DRS were implemented to identify optical characteris‐ tics of BWO, TON, and TON/BWO heterojunctions. As seen in Fig. 10(a). The absorption edges of TON and BWO are deter‐ mined at ${\\sim}504$ [16] and ${\\sim}440~\\mathrm{nm}$ [44,59], certifying they are visible‐light‐active catalysts. Encouragingly, after the hybridi‐ zation of BWO and TON, the built TON/BWO heterojunctions are endowed with better visible‐light absorption as compared with BWO, primarily due to the interfacial interaction between the components, which is beneficial to photoreaction. The bandgap energy $\\left(E_{\\mathrm{g}}\\right)$ of BWO and TON are determined as ${\\sim}2.79$ and ${\\sim}2.50~\\mathrm{eV}$ basing on Tauc plots (Fig. 10(b)). The M‐S curves illustrate that TON and BWO present a positive slope, certifying the n‐type semiconductor nature of them (Fig. 10(c)). Moreo‐ ver, the flat‐band potentials $\\left(E_{\\mathrm{fb}}\\right)$ of BWO (0.21 vs. Ag/AgCl) and TON (–0.71 vs. Ag/AgCl) are derived from M‐S plots. In light of the Nernst equation: $E_{\\mathrm{NHE}}=E_{\\mathrm{Ag/AgCl}}+0.197$ (2), the $E_{\\mathrm{fb}}$ of BWO and TON are equivalent to 0.41 and $-0.51\\mathrm{\\DeltaV}$ (vs. NHE). Consid‐ ering that the $E_{\\mathrm{CB}}$ of a n‐type semiconductor is ${\\sim}0.1\\mathrm{~V~}$ more negative than the $E_{\\mathrm{fb},}$ thus, the $E_{\\mathrm{CB}}$ of BWO and TON are about 0.31 and $-0.61\\mathrm{~V~}$ (vs. NHE), respectively. Further, the EVB of BWO and TON are about 3.10 and 1.89 V (vs. NHE) according to the equation: $E_{\\mathrm{VB}}-E_{\\mathrm{CB}}=E_{\\mathrm{g}}$ (3). With these analyses, the band energy structures of BWO and TON are depicted in Fig. 10(d). \n\nEPR characterization was implemented to investigate the OVs of BWO, TON, TON/BWO‐2 (Fig. 10(e)). Distinctly, the weak EPR signal at $g=2.002$ for TON reflects the low concen‐ tration of OVs. Furthermore, the identification of an intense EPR signal at $g=2.002$ confirms the existence of rich OVs in both BWO and TON/BWO‐2 [52,60–62], in line with the XPS result. It is well‐known that OVs is beneficial to the photoreac‐ tion [63]. \n\n![](images/2366902bd9aafd815a4eef3f8a8d1ded0997950242e0d3f84d8c40ac83967fcb.jpg) \nFig. 10. (a) UV‐Vis DRS spectra of BWO, TON and TON/BWO heterojunctions. Tauc plots (b), Mott‐Schottky plots (c), and band structures (d) of BWO and TON. (e) EPR spectra of BWO, TON and TON/BWO‐2. (f) UPS spectra of BWO and TON. \n\nThe discrepancy of work functions $(\\phi)$ of semiconductors principally accounts for the interfacial charge transit. Thus, the ultraviolet photoelectron spectroscopy (UPS) was applied to determine the $\\Phi$ of TON and BWO (Fig. 10(f)). The $\\Phi$ values of BWO and TON are 5.23 and $4.43\\mathrm{eV}_{\\cdot}$ , respectively, reflecting that upon the creation of the heterojunction, the $\\mathbf{e}^{-}$ of TON would preferably inject into BWO across the interface because of the lower Fermi level $\\left(E\\mathrm{f}\\right)$ of BWO than TON, which accords well with the XPS results. \n\nOn the basis of the above analyses, an S‐scheme mechanism proposed for the photoreaction of TON/BWO is illustrated in Fig. 11. Before the contact of them, TON has a smaller $\\Phi$ and higher $E_{\\mathrm{f}}$ with respect to that of BWO. When they are in contact, $\\mathrm{e^{-}}$ of TON spontaneously injects into BWO because of the dis‐ crepancy of their $\\phi$ and $E_{\\mathrm{f}}$ . Such $\\mathbf{e}^{-}$ transfer makes the two sys‐ tems reach the balanced $E_{\\mathrm{f}},$ leading to the generation of an e‒ accumulation (loss) layer in BWO (TON), establishment of IEF pointing from TON to BWO, and emergence of band bending at the interface (Fig. 11). When exposed to visible light, both TON and BWO are excited to generate $\\mathbf{e}^{-}\\mathbf{-}\\mathbf{h}^{+}$ pairs. Under the syner‐ gistic effect of the IEF, bands bending and the Coulomb’s attrac‐ tion, photo‐excited $\\:\\mathrm{e^{-}}\\:$ in the CB of BWO is thermodynamically migrated to recombine with photo‐generated $\\ln^{+}$ in the VB of TON. Such charge drifts ensure the rapid recombination of weak charge carriers and effective preservation of the powerful $\\ln^{+}$ and $\\mathrm{e^{-}}$ in the VB of BWO and CB of TON for photocatalytic antibiotic oxidation and $\\mathrm{Cr(VI)}$ reduction, respectively. To be specific, the high energetic $\\mathrm{h}^{+}$ in the VB of BWO reacts with $\\mathrm{H}_{2}0$ or $0\\mathrm{H^{-}}$ to yield •OH. Meanwhile, the powerful $\\mathbf{e}^{-}$ in the CB of TON preferably reduces $0_{2}$ to form $\\bullet0_{2}\\-^{-}$ . Distinctly, the S‐scheme heterojunction synchronously achieves efficient charge separation and optimum photo‐redox power for boost‐ ed generation of active substances, leading to the superior cat‐ alytic performance [22,31,64], as confirmed by the photocata‐ lytic tests (Figs. 5‒7), PL spectra (Figs. 9(c), (d)), pho‐ to/electrochemical characterizations (Figs. 9(a), (b)), trapping tests (Figs. 8(a), (b)) and ESR analyses (Figs. 8(c), (d)). Ulti‐ mately, the photo‐created $\\ln^{+}$ , $\\bullet0_{2}\\overline{{^{-}}}$ and $\\bullet0\\mathrm{H}$ drive the effective decomposition, mineralization, and detoxification of antibiotics (Figs. 5, 6, 8(a)). Meanwhile, $\\bullet0_{2}\\overline{{^{-}}}$ synergizing with $\\mathbf{e}^{-}$ is engaged in photocatalytic $\\mathrm{Cr(VI)}$ reduction (Figs. 7, 8(b)). Of note, the OVs guarantees the improvement of sunlight response and the efficient charge separation of the heterojunction [41,52,65], which is beneficial to catalytic reactions. Overall, the designed TON/BWO S‐scheme heterojunction with OVs contributes to the better visible‐light absorption, promoted charge separation and stronger redox ability, leading to an upgraded photocata‐ lytic performance for the abatement of antibiotics and $\\operatorname{Cr}(\\mathrm{{VI})}$ . \n\n![](images/5580c893470ba7c15e1a9b07fecfd221bddbe8785ae74dc89c134e503e7ff772.jpg) \nFig. 11. Mechanistic illustration of the photocatalytic abatement of antibiotics and $\\mathrm{Cr(VI)}$ in the TON/BWO system under visible light. \n\n# 4. Conclusions \n\nNovel S‐scheme core‐shell heterojunction nanofibers of $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ were synthesized via in‐situ growing oxy‐ gen‐defective ${\\mathrm{Bi}}_{2}{\\mathrm{W}}{0}_{6}$ on the surface of TaON nanofibers. The unique 1D/2D heterostructure nanofibers inherit distinct ben‐ efits: (1) 1D TaON/2D Bi2WO6 core‐shell heterostructure with tight connection favors the interfacial transfer of charges and augments the exposed active sites; (2) the S‐scheme charge transport mechanism considerably suppresses the reunion of powerful photo‐carriers as well as optimizes the redox ability of the heterojunction; (3) the OVs of $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ could ren‐ der it with improved activation and photocatalytic perfor‐ mance. Therefore, the optimized TaON/Bi2WO6 demonstrates boosted photocatalytic antibiotic degradation and $\\operatorname{Cr}(\\operatorname{VI})$ re‐ duction performance, outperforming bare TaON and ${\\tt B i}_{2}{\\tt W O}_{6}$ Moreover, $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ also demonstrates high stability, mineralization and detoxification performance. Further study signifies that the photo‐induced •OH, $\\mathbf{h}^{+},$ and $\\bullet0_{2}\\overline{{^{-}}}$ substances strongly oxidize, mineralize, and detoxify the antibiotic, and the $\\mathrm{Cr(VI)}$ photo‐reduction is dominated by $\\bullet0_{2}\\overline{{^{-}}}$ , and $\\:\\boldsymbol{\\mathrm{e^{-}}}\\:$ species. Moreover, the good contact between the antibiotic and Ta‐ $0\\mathsf{N/B i_{2}W O_{6}}$ nanofibers is pivotal for the efficient degradation of antibiotic. This work introduces a promising TaON‐based photocatalyst and indicates that the combination of an S‐scheme heterojunction and OVs can be a promising strategy for developing high‐performance photocatalytic systems for environmental remediation. \n\n# Acknowledgments \n\nThis work has been financially supported by the Natural Science Foundation of Zhejiang Province (LY20E080014), the Science and Technology Project of Zhoushan (2022C41011, 2020C21009), and the National Natural Science Foundation of China (51708504). X. C. appreciates the support from the School of Biological and Chemical Sciences, Department of Chemistry, University of Missouri‐Kansas City. \n\n# Electronic supporting information \n\nSupporting information is available in the online version of this article. \n\n# Graphical Abstract \n\nChin. J. Catal., 2022, 43: 2652–2664 doi: 10.1016/S1872‐2067(22)64106‐8 \n\nS‐scheme photocatalyst TaON/ $\\mathbf{\\DeltaBi_{2}W O_{6}}$ nanofibers with oxygen vacancies for efficient abatement of antibiotics and Cr(VI): Intermediate eco‐toxicity analysis and mechanistic insights \n\nShijie ${\\mathrm{Li}}^{*}$ , Mingjie Cai, Yanping Liu, Chunchun Wang, Kangle Lv, Xiaobo Chen \\* Zhejiang Ocean University, China; South‐Central Minzu University, China; University of Missouri‐Kansas City, USA \n\n![](images/a7b93feadbe65c35732f9b9818aff5174b3dd4d347477b3e9a3f436a2d104f87.jpg) \n\nA novel $\\mathrm{Ta0N/Bi_{2}W0_{6}}$ core‐shell S‐scheme heterojunction nanofibers with oxygen vacancies has been designed for highly efficient visi‐ ble‐light photocatalytic abatement of antibiotics and $\\mathrm{Cr(VI)}$ . The superior catalytic performance is benefiting from the efficient separation of high energetic charge carriers with optimal photo‐redox power by S‐scheme mechanism and rich oxygen vacancies, as well as the compact contact by the in‐situ growth. \n\n# References \n\n[1] S. Y. Bunting, D. J. Lapworth, E. J. Crane, J. Grima‐Olmedo, A. Koroša, A. Kuczyńska, N. Mali, L. Rosenqvist, M. E. V. Vliet, A. Togola, B. Lopez, Environ. Pollut., 2020, 269, 115945. [2] Y. Zhou, L. Zhou, Y. Zhou, M. Xing, J. Zhang, Appl. Catal. B, 2020, 279, 119365. \n[3] B. Shen, C. Dong, J. Ji, M. Xing, J. Zhang, Chin. Chem. Lett., 2019, 30, 2205–2210. [4] C. Liu, Y. Feng, Z. Han, Y. Sun, X. Wang, Q. Zhang, Z. Zou, Chin. J. Catal., 2021, 42, 164–174. \n[5] A. Meng, L. Zhang, B. Cheng, J. Yu, Adv. Mater., 2019, 31, 1807660. [6] G. Yu, Y. Zhang, X. Du, J. Wu, C. Liu, Z. Zou, J. Colloid Interface Sci., 2022, 623, 205–215. [7] M. Tayyab, Y. Liu, S. Min, R. M. Irfan, Q. Zhu, L. Zhou, J. Lei, J. Zhang, Chin. J. Catal., 2022, 43, 1165–1175. [8] B. Fang, Z. Xing, D. Sun, Z. Li, W. Zhou, Adv. Powder Mater., 2022, 1, 100021. \n[9] Q. Zhu, Z. Xu, B. Qiu, M. Xing, J. Zhang, Small, 2021, 17, 2101070. \n[10] G. Duoerkun, Y. Zhang, Z. Shi, X. Shen, W. Cao, T. Liu, J. Liu, Q. Chen, L. Zhang, Adv. Fiber Mater., 2020, 2, 13–22. \n[11] K. Li, S. Zhang, Y. Li, J. Fan, K. Lv, Chin. J. Catal., 2021, 42, 3–14. \n[12] Z. Wang, Z. Lin, S. Shen, W. Zhong, S. Cao, Chin. J. Catal., 2021, 42, 710–730. \n[13] R. He, R. Chen, J. Luo, S. Zhang, D. Xu, Acta Phys.‐Chim. Sin., 2021, 37, 2011022. \n[14] S. Huo, W. Gao, P. Zhou, Z. Deng, Z. Han, X. Cui, X. Lu, Adv. Powder Mater., 2022, 1, 100028. \n[15] X. Meng, W. Xu, Z. Li, J. Yang, J. Zhao, X. Zou, Y. Sun, Y. Dai, Adv. Fiber Mater., 2020, 2, 93–104. \n[16] L. Pei, Y. Yuan, W. Bai, T. Li, H. Zhu, Z. Ma, J. Zhong, S. Yan, Z. Zou, ACS Catal., 2021, 10, 15083–15091. \n[17] M. Hara, G. Hitoki, T. Takata, J. N. Kondo, H. Kobayashi, K. Domen, Catal. Today, 2003, 78, 555‐560. \n[18] L. Wei, M. A. S. Adamson, J. Vela, ChemNanoMat, 2020, 6, 1179–1185. \n[19] J. Hou, H. Cheng, C. Yang, O. Takeda, H. Zhu, Nano Energy, 2015, 18, 143–153. \n[20] S. Chen, Y. Qi, T. Hisatomi, Q. Ding, T. Asai, Z. Li, S. S. K. Ma, F. Zhang, K. Domen, C. Li, Angew. Chem. Int. Ed., 2015, 54, 8498–8501. \n[21] M.‐Y. Tsang, N. E. Pridmore, L. J. Gillie, Y.‐H. Chou, R. Brydson, R. E. Douthwaite, Adv. Mater., 2012, 24, 3406–3409. \n[22] L. Zhang, J. Zhang, H. Yu, J. Yu, Adv. Mater., 2022, 34, 2107668. \n[23] Y. Cheng, M. Gong, T. Xu, E. Liu, J. Fan, H. Miao, X. Hu, ACS Appl. Mater. Interfaces, 2022, 14, 23785–23796. \n[24] G. Han, F. Xu, B. Cheng, Y. Li, J. Yu, L. Zhang, Acta Phys.‐Chim. Sin., 2022, 38, 2112037. \n[25] Y. Ren, Y. Li, X. Wu, J. Wang, G. Zhang, Chin. J. Catal., 2021, 42, 69–77. \n[26] S. Wageh, A. A. Al‐Ghamdi, R. Jafer, X. Li, Chin. J. Catal., 2021, 42, 667–669. \n[27] M. Sayed, B. Zhu, P. Kuang, X. Liu, B. Cheng, A. A. A. Ghamdi, S. Wageh, L. Zhang, J. Yu, Adv. Sustainable Syst., 2022, 6, 2100264. \n[28] L. Sun, L. Li, J. Yang, J. Fan, Q. Xu, Chin. J. Catal., 2022, 43, 350–358. \n[29] A. Meng, B. Cheng, H. Tan, J. Fan, C. Su, J. Yu, Appl. Catal. B, 2021, 289, 120039. \n[30] F. Xu, K. Meng, S. Cao, C. Jiang, T. Chen, J. Xu, J. Yu, ACS Catal., 2022, 12, 164–172. \n[31] J. Luo, P. Lin, P. Zheng, X. Zhou, X. Ning, L. Zhan, Z. Wu, X. Liu, X. Zhou, Chemosphere, 2022, 298, 134297. \n[32] F. Xu, K. Meng, B. Cheng, S. Wang, J. Xu, J. Yu, Nat. Commun., 2020, 11, 4613. \n[33] F. Chang, S. Li, Z. Shi, Y. Qi, D.‐G. Liu, X. Liu, S. Chen, Sep. Purif. Technol., 2022, 278, 119662. \n[34] P. Xia, S. Cao, B. Zhu, M. Liu, M. Shi, J. Yu, Y. Zhang, Angew. Chem. Int. Ed., 2020, 59, 5218–5225. \n[35] Q. Xu, L. Zhang, B. Cheng, J. Fan, J. Yu, Chem, 2020, 6, 1543–1559. \n[36] C. Cheng, B. He, J. Fan, B. Cheng, S. Cao, J. Yu, Adv. Mater., 2021, 33, 2100317. \n[37] S. Li, C. Wang, M. Cai, F. Yang, Y. Liu, J. Chen, P. Zhang, X. Li, X. Chen, Chem. Eng. J., 2022, 428, 131158. \n[38] W. Wang, X. Li, F. Deng, J. Liu, X. Gao, J. Huang, J. Xu, Z. Feng, Z. Chen, L. Han, Chin. Chem. Lett., 2022, doi: 10.1016/j.cclet.2022.01.058 \n[39] X. Li, Q. Luo, L. Han, F. Deng, Y. Yang, F. Dong, J. Mater. Sci. Technol., 2022, 114, 222–232. \n[40] X. Li, J. Xiong, X. Gao, J. Ma, Z. Chen, B. Kang, J. Liu, Hai Li, Z. Feng, J. Huang, J. Hazard. Mater., 2020, 387, 121690. \n[41] K. Qi, S. Liu, M. Qiu, Chin. J. Catal., 2018, 39, 867–875. \n[42] X. Li, B. Kang, F. Dong, Z. Zhang, X. Luo, L. Han, J. Huang, Z. Feng, Z. Chen, J. Xu, B. Peng, Z. L. Wang, Nano Energy, 2021, 81, 105671. \n[43] T. Yan, H. Liu, Z. Jin, ACS Appl. Mater. Interfaces, 2021, 13, 24896–24906. \n[44] T. Chen, L. Liu, C. Hu, H. Huang, Chin. J. Catal., 2021, 42, 1413–1438. \n[45] X. Zhou, C. Shao, S. Yang, X. Li, X. Guo, X. Wang, X. Li, Y. Liu, ACS Sustainable Chem. Eng., 2018, 6, 2316–2323. \n[46] F. Yang, Y. Shen, Z. Cen, J. Wan, S. Li, G. He, J. Hu, K. Xu, Sci. China Mater., 2022, 65, 356–363. \n[47] J. Ge, Y. Sun, W. Chen, F. Song, Y. Xie, Y. Zheng, P. Rao, Dalton Trans., 2021, 50, 13801–13814. \n[48] S. Li, C. Wang, Y. Liu, B. Xue, W. Jiang, Y. Liu, L. Mo, X. Chen, Chem. Eng. J., 2021, 415, 128991. \n[49] C. Wang, S. Li, M. Cai, R. Yan, K. Dong, J. Zhang, Y. Liu, J. Colloid Interface Sci., 2022, 619, 307–321. \n[50] H. Lei, M. Wu, Y. Liu, F. Mo, J. Chen, S. Ji, Y. Zou, X. Dong, Chin. Chem. Lett., 2021, 32, 2317–2321. \n[51] J. Luo, X. Zhou, F. Yang, X. Ning, L. Zhan, Z. Wu, X. Zhou, J. Clean. Prod., 2022, 357, 131992. \n[52] S. Li, M. Cai, C. Wang, Y. Liu, N. Li, P. Zhang, X. Li, J. Mater. Sci. Technol., 2022, 123, 177–190. \n[53] S. Li, M. Cai, Y. Liu, J. Zhang, C. Wang, S. Zang, Y. Li, P. Zhang, X. Li, Inorg. Chem. Front., 2022, 9, 2479–2497. \n[54] X. Shen, T. Zhang, P. Xu, L. Zhang, J. Liu, Z. Chen, Appl. Catal. B, 2017, 219, 425–431. \n[55] F. Zhang, X. Li, X. Dong, H. Hao, X. Lang, Chin. J. Catal., 2022, 43, 2395–2404. \n[56] J. Xiong, X. Li, J. Huang, X. Gao, Z. Chen, J. Liu, H. Li, B. Kang, W. Yao, Y. Zhu, Appl. Catal. B, 2020, 266, 118602. \n[57] C. Liu, Y. Zhang, J. Wu, H. Dai, C. Ma, Q. Zhang, Z. Zou, J Mater Sci Technol, 2022, 114, 81–89. \n[58] G. Zhao, W. Ma, X. Wang, Y. Xing, S. Hao, X. Xu, Adv. Powder Mater., 2022, 1, 100008. \n[59] H. Huang, J. Zhao, Y. Du, C. Zhou, M. Zhang, Z. Wang, Y.‐X. Weng, J. Long, J. Hofkens, J.A. Steele, M. Roeffaers, ACS Nano, 2020, 14, 16689–16697. \n[60] Q. Wang, W. Wang, L. Zhong, D. Liu, X. Cao, F. Cui, Appl. Catal. B, 2018, 220, 290–302. \n[61] Z. Cui, X. Dong, Y. Sun, Y. Zhou, Y. Zhang, F. Dong, Nanoscale, 2018, 10, 16928–16934. \n[62] H. Li, S. Chen, H. Shang, X. Wang, Z. Yang, Z. Ai, L. Zhang, Sci. Bull., 2020, 65, 1916–1923. \n\n[63] X. Li, J. Xiong, Y. Xu, Z. Feng, J. Huang, Chin. J. Catal., 2019, 40, 424–443. [64] X. Li, J. Liu, J. Huang, C. He, Z. Feng, Z. Chen, L. Wan, F. Deng, Acta \n\nPhys. ‐Chim. Sin., 2021, 37, 2010030. [65] X. Yang, S. Wang, T. Chen, N. Yang, K. Jiang, P. Wang, S. Li, X. Ding, H. Chen, Chin. J. Catal., 2021, 42, 1013–1023. \n\n# 新型氮氧化钽/氧空位钨酸铋S型异质结纤维用于高效光催化降解抗生素和还原六价铬: 产物毒性分析和光催化机理研究 \n\n李世杰a,b,\\*, 蔡铭洁a,b, 刘艳萍a,b, 王春春a,b, 吕康乐c, 陈晓波d,#浙江海洋大学国家海洋设施养殖工程技术研究中心, 海洋科学与技术学院, 浙江省海产品健康危害因素关键技术研究重点实验室, 浙江海洋大学, 浙江舟山316022, 中国b浙江海洋大学创新应用研究院, 浙江舟山316022, 中国c中南民族大学催化材料科学教育部重点实验室, 湖北武汉430074, 中国d密苏里大学堪萨斯分校, 美国 \n\n摘要: 近年来,环境污染问题严重地威胁着人类的生存和健康. 半导体光催化是一种绿色环保的治理环境污染技术, 该技术实现大规模应用的关键在于构建高效的光催化剂. TaON因优异的光电性质、稳定的物理化学性质及适合的能带结构等优势, 被广泛应用于光催化水裂解和有害污染物降解等领域. 但光生载流子快速复合和比表面积小等问题严重制约了其大规模应用. 近年来, 人们发现构建新型S型异质结能有效促进光生电子和空穴分离, 同时充分保存具有强氧化还原能力的电子和空穴, 进而有效提升材料的光催化性能. 因此, 通过构建新型TaON S型异质结光催化材料有f望开发出高效的可见光光催化体系. \n\n本文采用静电纺丝-煅烧-氮化工艺制备出由纳米颗粒组成的多孔TaON纳米纤维, 然后采用溶剂热法制得一系列富含氧空位的 $\\mathrm{TaON/Bi_{2}W O_{6}}$ S型异质结纤维, 并用于可见光照射下光催化降解抗生素和还原 ${\\mathrm{Cr}}^{6+}$ . 实验发现, 富含氧空位的${\\mathrm{Bi}_{2}}\\mathrm{WO}_{6}$ 二维纳米片均匀生长在TaON纳米纤维上形成了良好的1D/2D核壳结构, 此异质结界面结构有利于界面间电荷的分离和传输. 当 $\\mathrm{TaON/Bi_{2}W O_{6}}$ 质量比为 $20\\mathrm{wt\\%}$ 时, 在可见光下分别照射50, 60和 $50\\mathrm{min}$ , $20\\mathrm{mg}$ 复合纤维可降解 $93.2\\%$ 的四环素溶液 $20\\mathrm{mg/L}$ , $100~\\mathrm{mL}$ , $\\mathrm{pH}=5.2\\$ ), $83.7\\%$ 的左氧氟沙星溶液( $20\\mathrm{mg/L}$ , $100~\\mathrm{mL}$ , $\\mathsf{p H}6.7$ )以及还原 $95.6\\%$ 的 ${\\mathrm{Cr}}^{6+}$ 溶液( $10\\mathrm{mg/L}$ ,$100~\\mathrm{mL}$ , $\\mathrm{pH}=2.5\\$ ), 其对三种污染物的去除速率分别是纯 ${\\mathrm{Bi}_{2}\\mathrm{WO}_{6}}$ 的3.8, 2和2.9倍, 且远高于纯TaON纤维. 此外, 该复合纤维具有良好的矿化能力及循环稳定性, 在实际废水中依然表现出较好的催化降解活性. 表征结果表明, 复合纤维光催化活性增强是由于TaON与 ${\\mathrm{Bi}_{2}}\\mathrm{WO}_{6}$ 之间形成了S型的异质结, 并富含氧空位; 在内电场, 能带弯曲和库仑力的协同作用下, 实现了强氧化还原能力的电子和空穴的高效分离和保存, 有效提升了体系的光催化性能. 综上, 本文采用缺陷工程结合异质构筑策略有效地提升了体系的光催化活性, 为开发高效的光催化体系提供一定的参考. \n\n关键词: $\\mathrm{TaON/Bi_{2}W O_{6}}$ ; S型异质结; 静电纺丝; 氧空位; 抗生素降解; 六价铬还原 \n\n收稿日期: 2022-03-06. 接受日期: 2022-04-13. 上网时间: 2022-09-05. \n\\*通讯联系人. 电话: (0580)2550008; 电子信箱: lishijie@zjou.edu.cn \n#通讯联系人. 电子信箱: chenxiaobo@umkc.edu \n基 金 来 源 : 浙 江 省 自 然 科 学 基 金 (LY20E080014); 舟 山 市 科 技 计 划 项 目 (2022C41011, 2020C21009); 国 家 自 然 科 学 基 金(51708504). \n本文的电子版全文由Elsevier出版社在ScienceDirect上出版(http://www.sciencedirect.com/journal/chinese-journal-of-catalysis). " + }, + { + "id": "10.1002_anie.202202556", + "DOI": "10.1002/anie.202202556", + "DOI Link": "http://dx.doi.org/10.1002/anie.202202556", + "Relative Dir Path": "mds/10.1002_anie.202202556", + "Article Title": "Efficient Electrochemical Nitrate Reduction to Ammonia with Copper-Supported Rhodium Cluster and Single-Atom Catalysts", + "Authors": "Liu, HM; Lang, XY; Zhu, C; Timoshenko, J; Rüscher, M; Bai, LC; Guijarro, N; Yin, HB; Peng, Y; Li, JH; Liu, Z; Wang, WC; Roldan Cuenya, B; Luo, JS", + "Source Title": "ANGEWANDTE CHEMIE-INTERNATIONAL EDITION", + "Abstract": "The electrochemical nitrate reduction reaction (NITRR) provides a promising solution for restoring the imbalance in the global nitrogen cycle while enabling a sustainable and decentralized route to source ammonia. Here, we demonstrate a novel electrocatalyst for NITRR consisting of Rh clusters and single-atoms dispersed onto Cu nullowires (NWs), which delivers a partial current density of 162 mA cm(-2) for NH3 production and a Faradaic efficiency (FE) of 93 % at -0.2 V vs. RHE. The highest ammonia yield rate reached a record value of 1.27 mmol h(-1) cm(-2). Detailed investigations by electron paramagnetic resonullce, in situ infrared spectroscopy, differential electrochemical mass spectrometry and density functional theory modeling suggest that the high activity originates from the synergistic catalytic cooperation between Rh and Cu sites, whereby adsorbed hydrogen on Rh site transfers to vicinal *NO intermediate species adsorbed on Cu promoting the hydrogenation and ammonia formation.", + "Times Cited, WoS Core": 369, + "Times Cited, All Databases": 377, + "Publication Year": 2022, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000780914100001", + "Markdown": "# Efficient Electrochemical Nitrate Reduction to Ammonia with Copper-Supported Rhodium Cluster and Single-Atom Catalysts \n\nHuimin Liu, Xiuyao Lang, Chao Zhu, Janis Timoshenko, Martina Rüscher, Lichen Bai, Néstor Guijarro, Haibo Yin, Yue Peng, Junhua Li, Zheng Liu, Weichao Wang, Beatriz Roldan Cuenya, and Jingshan Luo\\* \n\nAbstract: The electrochemical nitrate reduction reaction (NITRR) provides a promising solution for restoring the imbalance in the global nitrogen cycle while enabling a sustainable and decentralized route to source ammonia. Here, we demonstrate a novel electrocatalyst for NITRR consisting of Rh clusters and single-atoms dispersed onto Cu nanowires (NWs), which delivers a partial current density of $162\\mathrm{mAcm}^{-2}$ for $\\mathrm{NH}_{3}$ production and a Faradaic efficiency (FE) of $93\\%$ at $-0.2\\:\\mathrm{V}$ vs. RHE. The highest ammonia yield rate reached a record value of $1.27\\mathrm{mmolh}^{-1}\\mathrm{cm}^{-2}$ . Detailed investigations by electron paramagnetic resonance, in situ infrared spectroscopy, differential electrochemical mass spectrometry and density functional theory modeling suggest that the high activity originates from the synergistic catalytic cooperation between Rh and $\\mathrm{cu}$ sites, whereby adsorbed hydrogen on Rh site transfers to vicinal $^{*}\\mathrm{\\bfNO}$ intermediate species adsorbed on $\\mathrm{cu}$ promoting the hydrogenation and ammonia formation. \n\n# Introduction \n\nAmmonia is an essential chemical and the cornerstone of the large and ever-growing fertilizer industry. It is also a potential hydrogen carrier and can be cracked into $\\mathrm{H}_{2}$ and ${\\bf N}_{2}$ at the destination affording hydrogen on demand. Unlike liquid hydrogen that needs harsh conditions to be stored, ammonia can be readily liquefied by increasing the pressure to ${\\approx}10$ bar at room temperature, or by cooling to $-33^{\\circ}\\mathrm{C}$ at atmospheric pressure.[1] Indeed, ammonia is foreseen to gain momentum as a carbon-free fuel for ships, heavy transport vehicles once direct ammonia fuel cells reach a higher level of maturity.[2] \n\nCurrently, the worldwide production of ammonia relies on the Haber–Bosch (HB) process, which consumes about $5.5\\mathrm{EJ}$ of energy every year $(\\approx38\\:\\mathrm{GJ/t_{NH_{3}}})$ and emits over 450 million metric tons of carbon dioxide $(\\approx2.9\\mathrm{t}_{\\mathrm{CO}_{2}}/\\mathrm{t}_{\\mathrm{NH}_{3}})$ .[3] With the growing interest of using ammonia in nonagriculture sectors (e.g. energy), the production scale of ammonia and ammonia-related emissions will be further expanded. Thus, to meet the COP21 two-degree scenario (2DS) target[3] for ammonia, there is a compelling need to replace the conventional HB process by alternative sustainable strategies compatible with renewables that could meet the increasing demand. Electrochemical nitrate reduction (NITRR) has the potential of decentralized production of “green” ammonia with an economically-competitive rate.[4] On the one hand, excessive use of fertilizer and other human activities have contributed a lot of nitrate in ground and surface water. Recycling redundant nitrates and converting them to ammonia could add direct economic value to the remediation process.[1,5] On the other hand, with the development of electrochemical conversion of nitrogen to nitrate via non-thermal plasma techniques and nitrogen oxidation,[6] ammonia production from nitrate is no longer a reversal of the Ostwald process and the production scale can be further extended. Therefore, the NITRR could provide a sustainable alternative to the HB process and simultaneously provide a solution for restoring the imbalance in the global nitrogen cycle.[7] \n\nIn the early years, Cu-based catalysts have been reported for the NITRR. However, as the research foothold is only the remediation of nitrate in the environment, most catalysts are designed to produce nitrogen.[8] Although there were a few Cu-based catalysts reported for ammonia synthesis, the in-depth mechanistic studies were lacked. Recently, Cubased catalysts for NITRR undergone an upsurge in research again,[9] displaying Faradaic efficiencies (FE) greater than $90\\%$ and partial current densities for ammonia production close to $100\\mathrm{mAcm}^{-2}$ . However, they usually operated only at very negative applied potentials (around $-0.4\\mathrm{-}\\mathrm{-}0.7\\:\\mathrm{V}$ vs. RHE), which is energetically inefficient. It has been argued that the weak adsorption of H on Cu may be the main limiting factor for the NITRR, i.e., only at very negative applied potentials the $^*\\mathrm{H}$ coverage is high enough to maintain a significant surface hydrogenation rate.[10] Therefore, it is expected that by activating the hydrogenation ability of Cu-based catalyst at more positive applied potentials the overpotential for the NITRR could be drastically reduced. Rhodium (Rh) is known to exhibit excellent hydrogen adsorption–desorption features,[11] as demonstrated by its uppermost and centered position in the hydrogen evolution reaction (HER) volcano plot. We therefore hypothesize that proper distribution of Rh over Cu sites could patch the poor hydrogenation capabilities of bare $\\mathrm{cu}$ and improve the NITRR performance. \n\nInspired by recent advances in cluster and single-atom catalysis,[12] here we constructed a series of electrodes based on Rh clusters and single-atom supported on Cu NWs $(\\mathrm{Rh}@\\mathrm{Cu}$ , henceforth). The NITRR was explored as a function of the Rh-content, revealing a record partial current density for $\\mathrm{NH}_{3}$ production of $162\\mathrm{mAcm}^{-2}$ and a $93\\%$ FE at $-0.2\\:\\mathrm{V}$ vs. RHE for very low Rh loading $(\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%)$ ). Importantly, $^{15}\\mathrm{N}$ labelling together with nuclear magnetic resonance (NMR) experiments confirmed nitrate as the only $\\mathbf{N}$ -source of the produced ammonia. Mechanistic insights on the reaction gathered by electron paramagnetic resonance (EPR) spectroscopy, in situ infrared spectroscopy, in situ Raman spectroscopy, on-line differential electrochemical mass spectrometry (DEMS) and density functional theory (DFT) modeling provided compelling evidence of the synergistic catalytic cooperation between Cu and Rh. The Cu site preferentially stabilizes nitrogen intermediate species, whereas the vicinal Rh supplies the activated H species required for the surface hydrogenation to proceed. Ultimately, ammonia is released as the product. \n\n# Results and Discussion \n\n# Catalyst Preparation and Characterization \n\nThe electrodes made of $\\mathrm{Cu}_{2}\\mathrm{O}$ NWs were first fabricated as reported in previous work.[13] Then, the $\\mathrm{Cu}_{2}\\mathrm{O}$ NWs were reduced to Cu NWs by electrochemical reduction. Finally, Cu NWs coated with either homogeneously distributed Rh cluster and single-atom $(\\mathrm{Rh}@\\mathrm{Cu})$ or Rh nanoparticles (NP $\\boldsymbol{\\mathrm{Rh}@\\mathrm{Cu}})$ were synthesized by galvanic replacement reaction between Cu and $\\mathbf{Rh}^{3+}$ , as detailed in the Supporting Information. The scanning electron microscopy (SEM) images confirmed the micrometer-long $\\mathrm{cu}$ NWs, and the Xray diffraction (XRD) pattern solely detected the characteristic reflections of $\\mathtt{C u}$ without oxide phases (Figure S1). \n\nThree different $\\boldsymbol{\\mathrm{Rh}@}\\boldsymbol{\\mathrm{Cu}}$ catalysts in terms of different Rh loading were prepared, namely samples with $12.5\\%$ (NP $\\mathrm{Rh}@\\mathrm{Cu}-12.5\\%$ ), $0.6\\%$ $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%)$ ) and $0.3\\%$ ( $\\operatorname{Rh}@\\operatorname{Cu-}$ $0.3\\%$ of Rh, respectively. The SEM and transmission electron microscopy (TEM) images of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ (Figure 1a, b and S2, S3), NP $\\mathrm{Rh}@\\mathrm{Cu}-12.5\\%$ (Figure S4, S6) and $\\mathrm{Rh}@\\mathrm{Cu}.0.3\\%$ (Figure S7) samples recorded before and after the NITRR did not reveal major structural variations on the NWs. This can be attributed to the small feature size of the Rh deposited on the surface in all cases and the stability under cathodic operation of the Cu NWs. Indeed, XRD patterns for all samples did not reveal any change upon the NITRR tests, which confirmed the robustness of the $\\mathrm{cu}$ electrodes and the low Rh contents (Figure S8 and 1i). In order to better assess the presence of Rh, elemental mapping was performed. Overall, the content of Rh estimated by energy-dispersive X-ray spectroscopy (EDS) and inductive coupled plasma-optical emission spectroscopy (ICP-OES) matched well, that is, $12.5\\%$ (Figure S4–S6), $0.6\\%$ (Figure $\\mathrm{1c-g\\rangle}$ and $0.3\\%$ (Figure S7), respectively, and barely changed upon operation. In addition, the aberrationcorrected high-angle annular dark-field scanning transmission electron microscopy (AC-HAADF-STEM) was employed to further detect Rh atoms based on contrast difference. As shown in Figure 1h, many bright dots and atom-sized features attributed to individual Rh atoms as well as very small Rh clusters can be discerned on the surface of $\\mathrm{cu}$ (111) in $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ . In contrast, the higher loading of $\\mathrm{Rh}@\\mathrm{Cu}-12.5\\%$ leads to Rh nanoparticles with a characteristic lattice fringe of $0.220\\mathrm{nm}$ corresponding to Rh (111), which can be well differentiated from the characteristic lattice spacing of $0.209\\mathrm{nm}$ assigned to $\\mathrm{cu}$ (111) (Figure S4). Finally, for the $\\mathrm{Rh}@\\mathrm{Cu}.0.3\\%$ sample, since the amount of Rh are even lower, we speculated that Rh in this sample is also in the form of single atoms and clusters. \n\nWe also used $\\mathbf{\\boldsymbol{X}}$ -ray absorption spectroscopy (XAS), including X-ray absorption near edge structure (XANES) and extended $\\mathbf{\\boldsymbol{X}}$ -ray absorption fine structure (EXAFS) to analyze the chemical state and local structure of Rh in $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ . The Rh K-edge XANES spectrum for $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ lies in between those corresponding to Rh foil and $\\mathrm{Rh}_{2}\\mathrm{O}_{3}$ reference samples. Indeed, linear combination analysis of XANES spectra (see the inset of Figure 1j), where the spectrum for $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ sample is fitted with a linear combination of spectra for Rh foil and $\\mathrm{Rh}_{2}\\mathrm{O}_{3}$ , provides a good agreement with experimental $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ sample spectrum, and suggests that ca. $63\\%$ of Rh is in reduced form and ca. $37\\%$ of Rh is oxidized. The presence of oxidized Rh species can be attributed to the sample being placed in air so that its surface is inevitably oxidized. During the subsequent NITRR test, the applied potentials is from $0\\mathrm{v}$ to $-0.5\\mathrm{V}$ vs. RHE, which is much lower than the standard reduction potential of $\\mathbb{R}\\mathrm{h}^{3+}/\\mathbb{R}\\mathrm{h}$ ( $_{0.758\\mathrm{V}}$ vs. RHE),[14] thus we expect that the oxide cannot be retained and the main form of Rh in the working catalyst is $\\mathbf{R}\\mathbf{h}^{0}$ . The frequency of Rh K-edge EXAFS spectrum of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ at large $k$ -values matches well with that of EXAFS spectrum for Rh foil (Figure 1k). This suggests that the distances between Rh and neighboring metal atoms are very close to these distances in Rh foil, and strongly supports the formation of Rh-rich phase. Note that in the case of homogeneous Rh alloying with $\\mathtt{C u}$ , we would expect a significant contraction of interatomic distances (and, hence, a decrease in EXAFS frequencies) due to a very large Cu to Rh ratio in our sample, and the significantly smaller lattice constant of metallic copper compared to metallic rhodium. Combined with AC-HAADF-STEM, these XAS results show that part of Rh exists in the form of small clusters in $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ . Fourier-transformed (FT) EXAFS spectra (Figure 1l) confirm conclusions from the visual examination of XANES and EXAFS data. FT-EXAFS spectra are dominated by three peaks. The first one at ca. $1.{\\overset{-}{7}}\\mathrm{\\AA}$ (phase uncorrected) was assigned to Rh O bond, and the peaks between ca. $2.1\\mathring{\\mathrm{A}}$ and $2.5\\mathring\\mathrm{\\mathrm{A}}$ were assigned to a superposition of $\\mathrm{\\sfRh\\mathrm{-}C u}$ and Rh Rh bond contributions. This provides compelling evidence of the existence of single atom Rh and Rh clusters. \n\n![](images/71e2630278bb4d042c5934656fdde7a2111067bd25348874959d3bd73c111bc5.jpg) \nFigure 1. Structure and composition characterization of the $R\\textcircled{\\omega}C u.0.6\\%$ sample. a) Scanning electron microscopy (SEM) image. b) High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). c–f) HAADF-STEM image and elemental mapping images. g) Energy-dispersive X-ray spectroscopy (EDS) and the insert map is the content of Rh and $\\mathsf{C u}$ obtained by inductively coupled plasma-optical emission spectroscopy (ICP-OES). h) Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (AC-HAADFSTEM) image. i) X-ray diffraction (XRD) pattern of $R\\mathsf{h}@\\mathsf{C u}.0.6\\%$ after NITRR test under $-0.2\\:\\forall$ vs. RHE. j) Rh K-edge X-ray absorption near edge structure (XANES). k) Extended X-ray absorption fine structure (EXAFS) spectra in $\\mathbf{k}.$ space and l) Fourier-transformed EXAFS spectra in R-space for $R\\textcircled{\\omega}C\\textcircled{\\mathsf{u}}.0.6\\%$ foil. Spectra for Rh foil and ${\\mathsf{R h}}_{2}{\\mathsf{O}}_{3}$ are also shown for comparison. Inset in $\\left(\\mathrm{j}\\right)$ shows the linear combination fit (red dashed line) for Rh K-edge XANES spectrum, using the spectra of Rh foil and ${\\mathsf{R h}}_{2}{\\mathsf{O}}_{3}$ as references. \n\nEXAFS data fitting was next performed for quantitative analysis. The results of the fitting are summarized in Figure S9 and Table S1. Good agreement between experimental and modeled data (Figure S9), and the reasonable values of R-factors (Table S1) support the validity of the fitting models. The obtained values for Rh O and Rh Rh bond lengths and disorder factors are in reasonable agreement with those for bulk reference materials. The Rh Cu bond length obtained for $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ is between the Rh Rh bond length $(2.64\\pm0.04\\mathring{\\mathrm{A}})$ and the typical bond lengths in metallic Cu (ca. 2.56 Å), as expected for bimetallic systems.[15] The slightly shorter Rh Rh bond length observed for the $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ sample $(2.64\\pm0.04\\:\\mathring{\\mathrm{A}})$ than that in Rh foil $(2.68\\mathrm{\\AA})$ may, in turn, suggest that the size of Rh clusters is small, resulting in a relatively large contribution of compressed Rh Rh distances at the cluster surface[16] (although the contraction of distances due to partial alloying with $\\mathrm{cu}$ cannot be excluded). \n\nWe note that the obtained coordination numbers for $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ are lower than the corresponding values of bulk materials due to sample-averaging effect: for a mixture of phases, the coordination numbers yielded by EXAFS fitting correspond to $N^{\\mathrm{true}_{*}}x$ , where $x$ is the concentration of the particular Rh species, and $N^{\\mathrm{true}}$ is the actual average number of nearest neighbors of given type in this species. By comparing the Rh\u0000O coordination number, obtained from EXAFS fitting $(2.6\\pm0.3)$ , with the Rh\u0000O coordination number in bulk oxide (6), we conclude that ca. $x_{\\mathrm{oxide}}=43\\%$ of the Rh is oxidized while ca. $x_{\\mathrm{{metal}}}=57\\%$ of Rh thus is in metallic state, which is in a good agreement with the results from XANES analysis. By correcting the Rh Rh and Rh Cu coordination numbers from EXAFS fit using this $x_{\\mathrm{metal}}$ value, we obtained the true number of Rh and $\\mathtt{C u}$ neighbors for each Rh atom in metallic phases, namely $\\mathbf{N}_{\\mathrm{Rh}}.$ \n\n${\\mathrm{Rh}}^{\\mathrm{true}}=7\\pm1$ and $\\mathrm{N_{Rh-Cu}}^{\\mathrm{true}}=4\\pm1$ . Further we assumed the simplest case, where only two different metallic Rh species are present—pure Rh clusters and Rh single atoms incorporated in pure Cu. Following a similar argument, from the comparison of $N_{\\mathrm{Rh-Cu}}^{\\mathrm{true}}$ with the expected coordination number for Rh embedded in fcc-type copper (12), we conclude that ca. $33\\%$ of the metallic rhodium forms single atom Rh species within copper matrix. The remaining $66\\%$ of metallic Rh are thus present in form of metallic Rh clusters. \n\n# Activity and Selectivity for NITRR to Ammonia \n\nTo explore the NITRR performance of the $\\boldsymbol{\\mathrm{Rh}@}\\boldsymbol{\\mathrm{Cu}}$ electrocatalysts, we first recorded linear sweep voltammograms using $0.1\\mathbf{M}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ as supporting electrolytes (pH was adjusted to 11.5) both with and without 0.1 M ${\\bf K N O}_{3}$ as nitrogen source. As depicted in Figure 2a, the current density of $\\boldsymbol{\\mathrm{Rh}@}\\boldsymbol{\\mathrm{Cu}}$ catalysts with various Rh content drastically increases in the presence of nitrate. The $\\operatorname{Rh}@\\operatorname{Cu-}$ $0.6\\%$ sample shows the maximum current density and a sharp onset at $0.2{\\mathrm{V}}$ vs. RHE. As the potential becomes negative, HER and NITRR compete. However, the number of electrons transferred for HER is less than that required for NITRR, and the current appears flat. When the potential becomes more negative, HER competition dominates. At high (more negative) applied potentials, especially when looking at curves of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ and $\\mathrm{Rh}@\\mathrm{Cu}-12.5\\%$ , the current decreases in a rather irregular fashion. This has been ascribed to the significant hydrogen production occurring at the electrodes’ surface, where the generated hydrogen bubbles disturb the electrolyte near the electrode. Furthermore, the product analysis by the colorimetric method (Figure S10–S11) confirmed that the $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ sample displayed the highest performance. Both lower $\\operatorname{Rh}@\\operatorname{Cu}.$ - $0.3\\%$ ) and higher (NP $\\mathrm{Rh}@\\mathrm{Cu}-12.5\\%$ ) Rh loadings led to a lower performance (Figure 2b and Figure S12, S13). The sample with too little Rh doping may not have obvious synergistic effect between $\\mathrm{cu}$ and Rh, while too much Rh loading will lead to the enhancement of competing HER. Therefore, $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ was the focus of our investigation. Further characterization of the reaction products demonstrated a steady increase of ammonia production up to $-0.4\\:\\mathrm{V}$ vs. RHE, reaching a record value of $21.61\\mathrm{mg}\\mathrm{h}^{-1}\\mathrm{cm}^{-2}$ , or $1.27\\mathrm{mmolh}^{-1}\\mathrm{cm}^{-2}$ (see Table S2 or Figure S14), whereas FE values hit a maximum of $93\\%$ at $-0.2\\mathrm{V}$ vs. RHE (Figure 2c). The slight deterioration of these values at more negative potentials could be ascribed to the competing HER. The FE of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ is obviously improved compared with bare Cu foil, Cu NWs and Rh nanoparticles (NPs) (Figure 2d and S15–S18). The partial current density for ammonia production of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ reached $162.0\\mathrm{mAcm}^{-2}$ at $-0.2\\:\\mathrm{V}$ vs. RHE (Figure 2e and Table S2), which was also much higher than Rh NPs and had a $24.6\\%$ increase compared to Cu NWs $(130.0\\mathrm{mAcm}^{-2})$ . In addition, the potential at which the $\\mathrm{NH}_{3}$ production reaches peak FE for the $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ sample is $200\\mathrm{mV}$ more positive than that of pure Cu NWs (Figure 2d, S16). Overall, the above results provide compelling evidence of the synergy between Rh and $\\mathrm{cu}$ NWs when appropriately interfaced. Finally, the influence of the nitrate concentration on the performance was assessed and the optimized FE for ammonia production was achieved in electrolyte with $100\\mathrm{mM}$ $\\mathrm{NO}_{3}^{-}$ (Figure 2f). The FE for ammonia production was slightly reduced as the ${\\bf N O}_{3}^{-}$ concentration decreased, likely because of the increased contribution of the competing HER. Interestingly, the FE of ammonia production decreased with the increase of ${\\bf N O}_{3}^{-}$ concentration to $^{1\\mathbf{M}}$ . We hypothesize that the large concentration of produced ammonia in this case might not be removed rapidly from the catalyst surface in time, resulting in the deactivation of the active sites for NITRR. The maximum FE of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ for NITRR in $0.1\\mathbf{M}$ $\\mathrm{Na}_{2}\\mathrm{SO}_{4}$ with $0.1\\mathrm{~M~}\\mathrm{NO_{3}}^{-}$ and $0.1\\mathbf{M}$ PBS $(\\mathrm{pH}7)$ with $0.1\\mathrm{~M~NO_{3}}^{-}$ is $96\\%$ and $80\\%$ , respectively. These demonstrate that $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ also displays a good NITRR performance in neutral electrolytes, which is promising for environmental application (Figure S19–S20). \n\n![](images/97427e6cf8f4280010b79a624aeecc844ecf62e55a6ef96862a8b71969331cb9.jpg) \nFigure 2. Electrocatalytic performance of ${\\mathsf{R h@C u}}$ systems. a) Linear sweep voltammograms of $R\\mathsf{h}@\\mathsf{C u}.0.3\\%$ , R $h@C u.0.6\\%$ and NP ${\\mathsf{R h@C u}}$ - $12.5\\%$ in 0.1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ electrolyte $\\left(\\mathsf{p}\\mathsf{H}\\mathsf{I}\\mathsf{I}.5\\right)$ in the absence of ${\\mathsf{N O}}_{3}^{-}$ (dotted line) and in the presence of ${\\mathsf{N O}}_{3}^{-}$ (solid line). b) FE of NITRR to ammonia over $\\mathsf{R h}@\\mathsf{C u}.0.3\\%$ , $R\\textcircled{a}C\\textcircled{u}.0.6\\%$ and NP R $10\\%0.4-12.5\\%$ at $-0.2\\:\\forall$ vs. RHE. c) Potential-dependent yield rate and FE of ammonia over [ $2h@C u.0.6\\%$ . d) Potential-dependent FE of ammonia over Cu NWs, $R\\textcircled{\\circ}C\\textcircled{\\mathsf{u}}.0.6\\%$ and carbon cloth loaded with Rh NPs. e) NITRR partial current densities for $N H_{3}$ of $\\mathsf{C u}$ NWs, $R\\textcircled{\\infty}C\\textcircled{\\mathsf{u}}.0.6\\%$ and carbon cloth loaded with Rh NPs under applied potentials of 0, $-0.1$ , $-0.2$ , $-0.3$ and $-0.4\\:\\forall$ vs. RHE. f) Yield rate and FE of NITRR to ammonia on $R\\textcircled{\\omega}C\\textcircled{u}.0.6\\%$ in 0.1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ electrolyte $\\left(\\mathsf{p H11}.5\\right)$ with $2\\mathsf{m M}$ , $\\mathsf{10}\\mathsf{m}\\mathsf{M}$ , $50~{\\mathsf{m}}{\\mathsf{M}}$ , $\\boldsymbol{\\mathsf{100}}\\boldsymbol{\\mathsf{m}}\\boldsymbol{\\mathsf{M}}$ and $1000\\ m\\mathsf{M}\\ \\mathsf{N O}_{3}^{-}$ . \n\nTo confirm the origin of the nitrogen incorporated in the synthesized ammonia, several control experiments were undertaken.[17] Firstly, the yield of synthesized ammonia was monitored in the presence of ${\\bf N O}_{3}^{-}$ and under open circuit conditions, that is, without current flowing through the cell. This experiment showed a negligible amount of ammonia. Likewise, under applied potential, we did not detect obvious ammonia production unless nitrates were added in the solution (Figure 3a). Overall, these results evidence the direct correlation between the presence of ${\\bf N O}_{3}^{-}$ in solution and generation of ammonia. Secondly, to unambiguously verify that ammonia originates from ${\\mathrm{NO}}_{3}{}^{-}$ , isotope labelling experiments wherein NITRR were carried out in the presence of ${}^{14}\\mathrm{NO}_{3}{}^{-}$ or $^{15}\\mathrm{NO}_{3}{}^{-}$ followed by product identification and quantifications via $\\mathrm{^{1}H}$ NMR. The characteristic splitting of the $\\mathrm{^{1}H}$ resonance into three symmetric signals in the case of using $^{14}\\mathrm{NO}_{3}{}^{-}$ and the corresponding splitting into two signals when using $^{15}\\mathrm{NO}_{3}^{-}$ , evidence the formation of $^{14}\\mathrm{N}\\mathrm{H_{4}}^{+}$ and $^{15}\\mathrm{N}\\mathrm{H_{4}}^{+}$ , respectively (Figure 3b and S21). We confirmed that the concentrations of detected $^{14}\\mathrm{N}\\mathrm{H_{4}}^{+}$ and $^{15}\\mathrm{N}\\mathrm{H}_{4}{}^{+}$ are virtually the same (Figure 3c,d). These data further corroborated that the ${\\bf N O}_{3}^{-}$ in solution is the only source of nitrogen during the electrochemical synthesis of ammonia. Moreover, the calculated FEs of ammonia measured by colorimetric method and $\\mathrm{^{1}H}$ NMR spectra method were compared, and the results are consistent (Figure 3e). In addition, the ammonia yield rate, FE and current density of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ showed no obvious decay after 15 periods of $^{1\\mathrm{h}}$ electrocatalytic NITRR (Figure 3f and Figure S22). Long-term and continuous electrocatalytic NITRR of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ was also explored by continuously flowing electrolyte to replenish the constantly consumed ${\\bf N O}_{3}^{-}$ , and the FE can still maintain $80\\%$ after $30\\mathrm{h}$ test, demonstrating excellent stability. The TEM and EDS of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ after NITRR for $30\\mathrm{h}$ proved the stability of the structure (Figure S23). \n\n# Mechanism Study and DFT Calculation \n\nWe next sought to understand the origin of the remarkable performance of the $\\boldsymbol{\\mathrm{Rh}@}\\boldsymbol{\\mathrm{Cu}}$ electrocatalyst for NITRR, especially at low overpotential. For instance, at $-0.1\\mathrm{V}$ vs. RHE, it was found that the production of ammonia for the optimized $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ electrode was over 100 times higher than that of Rh NPs, and 2 times higher than that of $\\mathrm{cu}$ NWs (Figure S24). It is plausible to consider Cu as the main active site while the Rh site acts as a promoter. The experimental results of less activity of $R\\mathrm{h}@\\mathrm{Cu-}15\\%$ compared to $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ confirm that the introduction of a small amount of Rh into $\\mathrm{cu}$ can promote ammonia production, but excess Rh will promote the HER due to the strong adsorption capacity of Rh to H (Figure S25). Therefore, we speculate that the introduction of Rh promotes the hydrogenation step of NITRR. The kinetic isotope experiments indicated that when $\\mathrm{H}_{2}\\mathrm{O}$ solvent is replaced by ${\\bf D}_{2}\\mathrm{O}$ to carry out the NITRR, the FEs of ammonia production on Cu NWs and $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ do not change significantly, but both the current density and ammonia yield rate of Cu NWs are significantly lower. In comparison, the current density and ammonia yield rate of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ do not change significantly when $\\mathrm{H}_{2}\\mathrm{O}$ is replaced to ${\\bf D}_{2}\\mathrm{O}$ (Figure S26). This indicates that the hydrogenation step of Cu NWs for NITRR is the rate-limiting step. After introducing Rh, the hydrogenation step of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ is no longer ratelimiting. Therefore, this result suggests that the introduction of Rh promotes the hydrogenation step in NITRR. In situ infrared spectroscopy (IR) results show that only a weak peak corresponding to $\\left.\\mathbf{-NH}_{2}\\right.$ can be detected from $-0.1\\mathrm{V}$ vs. RHE when pure Cu NWs catalyzes NITRR, while an obvious peak corresponding to $\\left.-\\mathrm{N}\\mathrm{H}_{2}\\right.$ is noticed from $0.2{\\mathrm{V}}$ vs. RHE when $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ catalyzes NITRR (Figure 4a). Since Rh displays a near-optimum H adsorption Gibbs free energy, we speculate that the incorporation of Rh drastically improves the surface adsorption of $\\mathrm{~H~}$ in the electrode, which could promote the hydrogenation of the intermediate nitrogen species adsorbed on the nearby Cu sites by a hydrogen transfer mechanism at low applied potentials.[18] \n\n![](images/eb5fb4ffcdb9085446afa09743baf999d5b37897d66ac4dd5645cb5be71dd7dd.jpg) \nFigure 3. Control tests and isotope labeling experiments of $R\\mathsf{h}@\\mathsf{C u}.0.6\\%$ . a) The ammonia yield of electrocatalysis over $R\\textcircled{\\omega}C\\textcircled{\\mathsf{u}}.0.6\\%$ in 0.1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ electrolyte $\\left(\\mathsf{p}\\mathsf{H}\\mathsf{I}\\mathsf{I}.5\\right)$ with ${\\mathsf{N O}}_{3}^{-}$ at $-0.2\\:\\forall$ vs. RHE, without ${\\mathsf{N O}}_{3}^{-}$ at $-0.2\\:\\forall$ vs. RHE and without applied potential in the presence of ${\\mathsf{N O}}_{3}^{-}$ , respectively. b) $\\mathsf{\\Pi}^{\\mathsf{I}}\\mathsf{H}$ nuclear magnetic resonance (NMR) spectra of the electrolyte after electrocatalytic NITRR over R $h\\textcircled{\\sc}C\\mathsf{u}.0.6\\%$ at $-0.2\\:\\forall$ vs. RHE using $^{15}{\\mathsf{N O}}_{3}^{-}$ and $^{14}{\\mathsf{N O}}_{3}^{-}$ as the nitrogen source. c) The standard curve of integral area $(^{14}\\mathsf{N H}_{4}^{+}/\\mathsf C_{4}\\mathsf H_{4}\\mathsf O_{4})$ as a function of $^{14}{\\mathsf{N H}}_{4}^{\\ +}$ concentration. The star represents the concentration of $^{14}{\\mathsf{N}}{\\mathsf{H}}_{4}^{\\ +}$ after NITRR. d) The standard curve of integral area $(^{15}\\mathsf{N H}_{4}{}^{+}/\\mathsf C_{4}\\mathsf H_{4}\\mathsf O_{4})$ as a function of $^{15}{\\mathsf{N H}}_{4}^{~+}$ concentration. The star represents the concentration of $^{15}{\\mathsf{N H}}_{4}^{~+}$ after NITRR. e) FE of NITRR at $-0.2\\:\\forall$ vs. RHE using $^{15}{\\mathsf{N O}}_{3}^{-}$ and $^{14}{\\mathsf{N O}}_{3}^{-}$ as the nitrogen source, detected by colorimetric method and nuclear magnetic methods. f) Yield rate and FE of ammonia over $R\\textcircled{\\omega}C\\textcircled{\\mathsf{u}}.0.6\\%$ under the applied potential of $-0.2\\:\\forall$ vs. RHE during 15 periods of 1 h electrocatalytic NITRR. \n\nIn order to test our hypothesis, we monitored the formation of $\\mathrm{~H~}$ radical $(\\mathrm{H}^{\\bullet})$ upon running HER by EPR using dimethyl-1-pyrroline-N-oxide (DMPO) as the radical trapping reagent.[19] The $^{*}\\mathrm{H}$ -adsorbed on the catalyst surface during HER has two destinies, which can be dimerized to $\\mathrm{H}_{2}$ , or desorb from the catalyst surface to the solution and form $\\mathbf{H^{\\bullet}}$ radical trapped by DMPO.[20] Under alkaline conditions, the overall HER performance is limited by the ability to adsorb hydrogen. In view of the trend in the HER performance, i.e, Rh $\\mathrm{NPs}>\\mathrm{Rh}@\\mathrm{Cu}{-}0.6\\%>\\mathrm{Cu}$ NWs, we could anticipate the poor $^*\\mathrm{H}$ -adsorption characteristic of the Cu NWs (Figure S27), which is in good agreement with DFT results (Figure S28). In the absence of nitrate, EPR spectra revealed 9 signals with an intensity ratio of 1: 1:2 :1: 2: 1:2 :1: 1, which indicates the formation of $\\mathrm{~H~}$ - DMPO in all cases (Figure 4b). It is worth noting that the intensity of the signals, which is proportional to the concentration of H-DMPO, follows the same trend observed in the HER performance, and further corroborates the low degree of $\\mathrm{~H~}$ adsorption on Cu NWs. In comparison, the strong EPR signal obtained for the $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ sample demonstrates an efficient adsorption-desorption of H. Based on the DFT calculation, the adsorption of H on Rh is easier than that of nitrate, and also easier than $\\mathrm{~H~}$ on $\\mathrm{cu}$ site. Therefore, H preferentially adsorbs on Rh sites compared to Cu sites of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ (Figure S28, S29). \n\nWe next investigated whether the $^{*}\\mathrm{H}$ -adsorbed on the Rh site could participate in the hydrogenation of the NITRR intermediates by recording the EPR spectra of the electrolyte after NITRR at $-0.1\\mathrm{V}$ vs. RHE (Figure 4c). Interestingly, the H-DMPO signal did not change in the presence of nitrate for Rh NPs, while it became undetectable for $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ and $\\mathrm{cu}$ NWs. This result suggests that the $\\boldsymbol{\\mathrm{\\Pi}}^{\\bullet}$ generated at the surface of $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ and Cu NWs is rapidly consumed in the hydrogenation of adjacent surface-activated nitrogen-containing intermediates. However, the Rh NPs are barely active towards NITRR, which is likely because of its unfavorable adsorption of nitrate with respect to the competing HER reaction steps. These findings support the hypothesis that the NITRR mechanism involves hydrogen transfer steps. It is worth noting that a similar hydrogen transfer mechanism could also be detected on the preliminary studies carried out using a similar system, i.e., $\\mathrm{Ru}@\\mathrm{Cu}.3.4\\%$ (Figure S30). This delivers the highest ammonia yield of $19.42\\mathrm{mg}\\mathrm{h}^{-1}\\mathrm{cm}^{-2}$ $(1.14\\mathrm{mmolh}^{-1}\\mathrm{cm}^{-2})$ and FE of $93.4\\%$ at $-0.2\\:\\mathrm{V}$ vs. RHE, which is also higher than those of bare Cu NWs. More generally, this supports the notion that the hydrogen transfer mechanism, evidenced in $\\boldsymbol{\\mathrm{Rh}@}\\boldsymbol{\\mathrm{Cu}}$ systems, could be found in a wide variety of metal-supported on $\\mathrm{Cu}$ electrocatalysts systems (Figure S30). \n\n![](images/51e80310c88c0b76fcc433506eb5608472cbb2ad307f2d40508395d50c9b6e57.jpg) \nFigure 4. Origin of the NITRR performances over $R\\mathsf{h}@\\mathsf{C u}.0.6\\%$ . a) Electrochemical in situ infrared spectroscopy (IR) of $R\\textcircled{\\circ}C\\textcircled{\\mathsf{u}}.0.6\\%$ and $\\mathsf{C u}$ NWs with different potentials at 0.1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ electrolyte $\\left(\\mathsf{p}\\mathsf{H}\\ \\mathsf{l}\\ \\mathsf{l}.5\\right)$ with 0.1 M $K N O_{3}$ . b) Electron paramagnetic resonance (EPR) spectra of the solutions obtained after 3 min of electrocatalysis at $-0.1\\vee$ vs. RHE by $\\mathsf{C u}$ NWs, $R\\textcircled{\\omega}C\\textcircled{u}.0.6\\%$ and Rh NPs loading on carbon cloth in 0.1 M ${\\mathsf{N a}}_{2}{\\mathsf{S O}}_{4}$ electrolyte $\\left(\\mathsf{p}\\mathsf{H}\\mathsf{I}\\mathsf{I}.5\\right)$ under argon. c) EPR spectra of the solutions obtained after 3 min of NITRR at $-0.1$ V vs. RHE by $\\mathsf{C u}$ NWs, ${\\mathsf{R h@C u}}$ - $0.6\\%$ and Rh NPs loading on carbon cloth in 0.1 M $N a_{2}S O_{4}$ electrolyte $\\left(\\mathsf{p}\\mathsf{H}\\mathsf{I}\\mathsf{I}.5\\right)$ with 0.1 M $K N O_{3}$ under argon. d) Differential electrochemical mass spectrometry (DEMS) measurements of NITRR over $R\\mathsf{h}@\\mathsf{C u}.0.6\\%$ . e) Gibbs free energy diagram of various intermediates generated during electrocatalytic NITRR over the pure Cu NWs and $R\\textcircled{\\omega}C\\textcircled{\\mathsf{u}}.0.6\\%$ , it is assumed that all Rh in $R\\textcircled{\\omega}C\\textcircled{\\mathsf{u}}.0.6\\%$ exists in the form of clusters. The structural models represent the adsorption form of various intermediates on $R\\textcircled{\\omega}C\\textcircled{u}.0.6\\%$ during NITRR, $\\mathsf{C u}$ blue, Rh light gray, N light blue, O red and H light pink atoms. \n\nIn order to construct a comprehensive description of the reaction mechanism, on-line differential electrochemical mass spectrometry (DEMS) was utilized to detect the intermediate species generated during the NITRR. Figure 4d and Figure S31 display the mass-to-charge ratio $(m/z)$ signals recorded as a function of time while performing 4 subsequent voltammetry scan cycles (each cycle involves a scan from $0.78{\\mathrm{V}}$ to $-1.42\\mathrm{V}$ vs. RHE). Note that $m/z$ signals at 46, 30, 33 and 17 were detected and tracked, corresponding to $\\mathrm{NO}_{2}$ , NO, $\\mathrm{\\bfNH}_{2}\\mathrm{\\bfOH}$ and $\\mathrm{NH}_{3}$ , respectively. The in situ Raman spectroscopy was also conducted to characterize the valence states of Rh and $\\mathrm{Cu}$ in $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ during NITRR test (Figure S32). Raman spectroscopy of initial $\\operatorname{Rh}@\\operatorname{Cu-}$ $0.6\\%$ showed characteristic peak of $\\mathrm{Cu}_{2}\\mathrm{O}$ at $218~\\mathrm{cm}^{-1}$ , $\\mathrm{CuO}$ at $298\\mathrm{cm}^{-1}$ and $622~\\mathrm{{cm}^{-1}}$ , $\\mathbf{Rh}_{2}\\mathbf{O}_{3}$ at $527\\mathrm{cm}^{-1}$ without applying potential. These agree well with the XAS results which evidenced that Rh on the catalyst surface was partially oxidized in air. As the applied potential decreases (more negative), all peaks decreased gradually and disappeared from $0\\mathrm{v}$ vs. RHE onwards. Therefore, the oxidation states of Rh clusters, single Rh atoms and $\\mathtt{C u}$ were mostly zero during NITRR. Based on the DEMS, in situ Raman results and with the aid of DFT, we proposed a reaction pathway and calculated the corresponding Gibbs free energy of each intermediate over $\\mathrm{Cu}$ and $\\mathrm{Rh}@\\mathrm{Cu}.0.6\\%$ (Figure 4e and S33, S34). The NITRR could be broken down into a series of deoxygenation reactions, ${}^{*}\\mathrm{NO}_{3}{\\longrightarrow}^{*}\\mathrm{NO}_{2}{\\longrightarrow}^{*}\\mathrm{NO}$ , followed by hydrogenation steps $^{*}\\mathrm{NO}{\\longrightarrow}^{*}\\mathrm{NOH}{\\longrightarrow}^{*}\\mathrm{NH}_{2}\\mathrm{OH}{\\longrightarrow}^{*}\\mathrm{NH}_{3}$ and finally desorption of ammonia. In order to clearly explore the contributions of Rh clusters and Rh single atoms, we calculated both of them. Interestingly, while the incorporation of Rh clusters and Rh single atoms barely affects the deoxygenation steps, it drastically reduces the thermodynamic barrier for hydrogenation. In fact, for pure Cu NWs, the conversion of $^{*}\\mathrm{\\bf{NO}}$ on $\\mathrm{cu}$ into $*_{\\mathrm{{NOH}}}$ is a protoncoupled electron transfer step with protons from electrolyte $({}^{*}\\mathrm{NO}+\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{e}^{-}{\\longrightarrow}^{*}\\mathrm{NOH}+\\mathrm{OH}^{-})$ due to the very little coverage of $^{*}\\mathrm{H}$ on $\\mathtt{C u}$ surface, which involved a high free energy increment $(0.35\\mathrm{eV})$ . In comparison, the hydrogenation process of $^{*}\\mathrm{\\bfNO}$ on $\\mathrm{Cu}$ into $*_{\\mathrm{{NOH}}}$ can be significantly promoted with an energy release of $0.85\\mathrm{eV}$ , when this step is triggered by $^*\\mathrm{H}$ on Rh clusters via in situ hydrogen transfer without electron transfer $({}^{*}\\mathrm{NO}+{}^{*}\\mathrm{H}{\\rightarrow}{}^{*}\\mathrm{NOH})$ ) (Figure 4e). When this step is triggered by Rh single atoms, it also involved a low free energy increment $(0.01\\mathrm{eV})$ (Figure S34). Therefore, Rh clusters in $\\boldsymbol{\\mathrm{Rh}@}\\boldsymbol{\\mathrm{Cu}}$ play a more critical role in the in situ hydrogen transfer during the NITRR catalysis. Overall, the decreased free energy of the subsequent steps accounts for the improved FE and current density when the Rh is supported on Cu NWs. \n\n# Conclusion \n\nWe have demonstrated that by interfacing a Rh cluster and single-atom Rh with Cu NWs, the hydrogenation steps of ammonia synthesis from NITRR at low applied potentials can be effectively controlled to optimize the catalytic selectivity. Partial current densities up to $162.0\\mathrm{mAcm}^{-2}$ and FE of $93\\%$ at potentials as low as $-0.2\\:\\mathrm{V}$ vs. RHE were achieved. The highest ammonia yield rate reached $1.27\\mathrm{mmolh}^{-1}\\mathrm{cm}^{-2}$ , which exceeded that of the state-of-theart NITRR catalysts. Mechanistic insights sought by utilizing a series of techniques suggested that the excellent activity and efficiency is attributed to the transfer of adsorbed $^*\\mathrm{H}$ from Rh sites to the $^{*}\\mathrm{\\bfNO}$ -adsorbed intermediate species located on Cu sites, thus facilitating the hydrogenation step for ammonia synthesis. This study not only provides insights for designing NITRR catalysts with high activity and selectivity, but also promotes the further exploration of the NITRR mechanism. \n\n# Author Contributions \n\nJ.S.L. conceived, designed and supervised the project. H.M.L. developed the catalysts, performed the characterizations, conducted electrochemical tests, and analyzed the data. X.Y.L. and W.C.W helped with the theoretical calculations. C.Z. and Z.L. helped with the aberrationcorrected high-angle annular dark-field scanning transmission electron microscopy tests. N.G. contributed to the discussion and the writing of the manuscript. H.B.Y, Y.P. and J.H.L. helped with the differential electrochemical mass spectrometry test. J.T., M.R. and L.B. performed the XAS experiments. H.M.L. and J.S.L. wrote the manuscript. All authors discussed the results and contributed to the manuscript. \n\n# Acknowledgements \n\nThe authors thank Dr. Lili Wan for part of experimental test. This work is supported by the Chinese Thousand Talents Program for Young Professionals, the startup funding from Nankai University, the $^{\\cdot\\cdot}111^{\\prime\\prime}$ project (Grant No. B16027), the Spanish Ministry of Science & Innovation for the ”Ramon y Cajal“ Program (RYC- RYC2018-023888- I), and the Singapore Ministry of Education AcRF Tier 2 (2016-T2-2-153, 2016-T2-1-131), AcRF Tier 1 (RG7/18 and \n\nRG161/19). L. Bai acknowledges the Early Postdoc Mobility Fellowship (P2ELP2_199800) from the Swiss National Science Foundation. XAS experiments were performed at CLAESS beamline at ALBA Synchrotron with the collaboration of ALBA staff. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Data Availability Statement \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\nKeywords: Ammonia Synthesis $\\cdot\\cdot$ Copper Nanowires · Electrochemical Nitrate Reduction $\\cdot^{\\cdot}$ Hydrogen Transfer Mechanism $\\cdot$ Single-Atom Catalysts \n\n[1] D. R. MacFarlane, P. V. Cherepanov, J. Choi, B. H. R. Suryanto, R. Y. Hodgetts, J. M. Bakker, F. M. Ferrero Vallana, A. N. Simonov, Joule 2020, 4, 1186–1205. \n[2] R. F. Service, Science 2018, 361, 120–123. \n[3] J. Lim, C. A. Fernandez, S. W. Lee, M. C. Hatzell, ACS Energy Lett. 2021, 6, 3676–3685. \n[4] H. M. Liu, Y. D. Zhang, J. S. Luo, J. Energy Chem. 2020, 49, 51–58. \n[5] a) C. A. Clark, C. P. Reddy, H. Xu, K. N. Heck, G. Luo, T. P. Senftle, M. S. Wong, ACS Catal. 2019, 10, 494–509; b) L. Su, D. Han, G. Zhu, H. Xu, W. Luo, L. Wang, W. Jiang, A. Dong, J. Yang, Nano Lett. 2019, 19, 5423–5430. \n[6] a) C. C. Dai, Y. M. Sun, G. Chen, A. C. Fisher, Z. C. J. Xu, Angew. Chem. Int. Ed. 2020, 59, 9418–9422; Angew. Chem. 2020, 132, 9504–9508; b) L. Q. Li, C. Tang, X. Y. Cui, Y. Zheng, X. S. Wang, H. L. Xu, S. Zhang, T. Shao, K. Davey, S. Z. Qiao, Angew. Chem. Int. Ed. 2021, 60, 14131–14137; Angew. Chem. 2021, 133, 14250–14256. \n[7] I. K. Phebe, H. van Langevelde, M. T. M. Koper, Joule 2020, 5, 1–5. \n[8] a) S. X. Yang, L. Z. Wang, X. M. Jiao, P. Li, Int. J. Electrochem. Sci. 2017, 12, 4370–4383; b) Y. M. Zhang, Y. L. Zhao, Z. Chen, L. Q. Wang, P. P. Wu, F. Wang, Electrochim. Acta 2018, 291, 151e160. \n[9] a) G. F. Chen, Y. Yuan, H. Jiang, S. Y. Ren, L. X. Ding, L. Ma, T. Wu, J. Lu, H. Wang, Nat. Energy 2020, 5, 605–613; b) Y. Wang, W. Zhou, R. Jia, Y. Yu, B. Zhang, Angew. Chem. Int. Ed. 2020, 59, 5350–5354; Angew. Chem. 2020, 132, 5388–5392; c) Y. H. Wang, A. Xu, Z. Y. Wang, L. S. Huang, J. Li, F. W. Li, J. Wicks, M. C. Luo, D. H. Nam, C. S. Tan, Y. Ding, J. W. Wu, Y. W. Lum, C. T. Din, D. Sinton, G. F. Zheng, E. H. Sargent, J. Am. Chem. Soc. 2020, 142, 5702–5708. \n[10] J. X. Liu, D. Richards, N. Singh, B. R. Goldsmith, ACS Catal. 2019, 9, 7052–7064. \n[11] J. K. Nørskov, T. Bligaard, A. Logadottir, J. R. Kitchin, J. G. Chen, S. Pandelov, U. Stimming, J. Electrochem. Soc. 2005, 152, J23–J26. \n[12] a) H. Yan, H. Cheng, H. Yi, Y. Lin, T. Yao, C. Wang, J. Li, S. Wei, J. Lu, J. Am. Chem. Soc. 2015, 137, 10484–10487; b) B. Qiao, A. Wang, X. Yang, L. F. Allard, Z. Jiang, Y. Cui, J. Liu, J. Li, T. Zhang, Nat. Chem. 2011, 3, 634–641. \n[13] J. S. Luo, L. Steier, M. K. Son, M. Schreier, M. T. Mayer, M. Gratzel, Nano Lett. 2016, 16, 1848–1857. \n[14] T. Ohno, N. Murakami, T. Tsubota, H. Nishimura, Appl. Catal. A, 349, 70–75. \n[15] J. Timoshenko, H. S. Jeon, I. Sinev, F. T. Haase, A. Herzog, B. Roldan Cuenya, Chem. Sci. 2020, 11, 3727–3736. \n[16] J. Timoshenko, A. Halder, B. Yang, S. Seifert, M. J. Pellin, S. Vajda, A. I. Frenkel, J. Phys. Chem. C 2018, 122, 21686–21693. \n[17] H. M. Liu, N. Guijarro, J. S. Luo, J. Energy Chem. 2021, 61, 149–154. \n[18] J. Wang, L. Yu, L. Hu, G. Chen, H. Xin, X. Feng, Nat. Commun. 2018, 9, 1795. \n[19] T. M. Masahiro Kohno, T. Ozawa, Y. Niwano, J. Clin. Biochem. Nutr. 2011, 49, 96–101. \n[20] L. L. Zhu, H. P. Lin, Y. Y. Li, F. Liao, Y. Lifshitz, M. Q. Sheng, S. T. Lee, M. W. Shao, Nat. Commun. 2016, 7, 12272. " + }, + { + "id": "10.1038_s41467-022-30379-4", + "DOI": "10.1038/s41467-022-30379-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-30379-4", + "Relative Dir Path": "mds/10.1038_s41467-022-30379-4", + "Article Title": "Unraveling the electronegativity-dominated intermediate adsorption on high-entropy alloy electrocatalysts", + "Authors": "Hao, JC; Zhuang, ZC; Cao, KC; Gao, GH; Wang, C; Lai, FL; Lu, SL; Ma, PM; Dong, WF; Liu, TX; Du, ML; Zhu, H", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "High-entropy alloy catalysts are an emerging class of materials and identification of catalytically active sites is critical. Here, we provide evidence that metal site electronegativity differences stabilize bound *OH and *H intermediates. High-entropy alloys have received considerable attention in the field of catalysis due to their exceptional properties. However, few studies hitherto focus on the origin of their outstanding performance and the accurate identification of active centers. Herein, we report a conceptual and experimental approach to overcome the limitations of single-element catalysts by designing a FeCoNiXRu (X: Cu, Cr, and Mn) High-entropy alloys system with various active sites that have different adsorption capacities for multiple intermediates. The electronegativity differences between mixed elements in HEA induce significant charge redistribution and create highly active Co and Ru sites with optimized energy barriers for simultaneously stabilizing OH* and H* intermediates, which greatly enhances the efficiency of water dissociation in alkaline conditions. This work provides an in-depth understanding of the interactions between specific active sites and intermediates, which opens up a fascinating direction for breaking scaling relation issues for multistep reactions.", + "Times Cited, WoS Core": 410, + "Times Cited, All Databases": 413, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000795204200020", + "Markdown": "# Unraveling the electronegativity-dominated intermediate adsorption on high-entropy alloy electrocatalysts \n\nJiace Hao1,6, Zechao Zhuang2,6, Kecheng Cao3, Guohua Gao4, Chan Wang1, Feili Lai5, Shuanglong Lu1, Piming Ma1, Weifu Dong1, Tianxi Liu1, Mingliang Du 1 & Han Zhu 1✉ \n\nHigh-entropy alloys have received considerable attention in the field of catalysis due to their exceptional properties. However, few studies hitherto focus on the origin of their outstanding performance and the accurate identification of active centers. Herein, we report a conceptual and experimental approach to overcome the limitations of single-element catalysts by designing a FeCoNiXRu (X: Cu, Cr, and Mn) High-entropy alloys system with various active sites that have different adsorption capacities for multiple intermediates. The electronegativity differences between mixed elements in HEA induce significant charge redistribution and create highly active Co and Ru sites with optimized energy barriers for simultaneously stabilizing ${\\mathsf{O H}}^{\\star}$ and $\\boldsymbol{\\mathsf{H}}^{\\star}$ intermediates, which greatly enhances the efficiency of water dissociation in alkaline conditions. This work provides an in-depth understanding of the interactions between specific active sites and intermediates, which opens up a fascinating direction for breaking scaling relation issues for multistep reactions. \n\nElrmecaqtnurioyrceanteafelfryegtciytci oreenavncetdrisosintoasnblhaeonledld ttohrreo kaeteaysl tstote tmthose, uwefnheictihehnehciryghtleoysf (selectivity) of reaction pathways during catalytic process. A great challenge facing materials scientists arises from the ongoing need for advanced electrocatalysts with reasonable activities that meet the needs of rapid development1–3. Recently, high-entropy alloy (HEA) catalysts with near-equiatomic proportions, have attracted wide attention due to their unprecedented properties caused by high configuration entropy, lattice distortion, sluggish diffusion, and cocktail effects4–8. A series of nanoscale HEA catalysts have been applied for ammonia oxidation, water splitting, methanol oxidation, $\\mathrm{CO}_{2}$ reduction, and dye degradation, and they deliver superior performance than conventional alloys7–13. Infinite elemental combinations and unconventional compositions offer many possibilities for regulating catalytic performance and overcoming the limitations of single-element catalysts, making HEAs an intriguing option in the field of electrocatalysis11. \n\nThe catalytic activities of monometallic catalysts depend substantially on the adsorption of reactants on surface-active sites14. Scaling relation issues applicable to many multistep reactions require the stabilization of multiple intermediates during the reaction, but the limited number of active sites with monometallic catalysts cannot achieve simultaneous stabilization of all intermediates on the available active sites with optimal binding energies15,16. Nano-catalysts have been rapidly developed in recent years with effectively explored strategies (including alloying, nanostructuring, defect, heterostructure, and lattice strain) to reveal the active sites and cooperation with each other (Fig. 1a)17–23. Single atom catalysts (SACs) have attracted tremendous effort to exploit effective routes with good control over coordination environment, composition (dimer), metal loading, and substrate, which are needed for the discovery of the correlations between compositional engineering and optimization of catalytic behavior (Fig. 1b)24. Numerous studies have been devoted to focusing on active sites and mechanisms of nano catalysts and SACs, and however, as an equally important catalyst system, accurate identification of active centers and their activity origins in HEA catalysts are greatly neglected. Furthermore, the relationships between multiple active sites in HEAs and reaction intermediates are still obscure with the lack of guidelines for designing reasonable active sites. \n\nHerein we propose a conceptual and experimental approach to overcome the limitations of single-element catalysts by designing a FeCoNiXRu (X: Cu, Cr, and Mn) HEA system with two kinds of active sites that have different adsorption capacities for multiple intermediates. HEA NPs are synthesized in electrospun carbon nanofibers (CNFs) and displayed a thermodynamically driven phase transition, as revealed by in situ characterization. We employ the HEAs as electrocatalysts for the alkaline hydrogen evolution reaction (HER) and successfully identify electronegativity-dependent preferences for active site adsorption of the intermediates $\\mathrm{\\dot{OH}^{*}}$ and $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ during $_\\mathrm{H}_{2}\\mathrm{O}$ dissociation and $\\mathrm{H}_{2}$ production steps (Fig. 1c). In the FeCoNiMnRu NP, the Co sites are the most active centers with the lowest energy barrier $(0.34\\mathrm{eV})$ for water dissociation. During the \n\n# a Nano-catalysts \n\n![](images/1c076f73d3ed3ca479d4b86b187bfacc87b403ff6393f1c8257962b0e679957a.jpg) \nFig. 1 Illustration of the concepts for designing nano catalysts, SACs and HEA catalysts. Designed strategies for creating active sites in (a) nano catalysts and (b) SACs. c Schematic illustration of HEA electrocatalysts with identified electronegativity-dependent preferences for active site adsorption of the intermediates $\\boldsymbol{\\mathrm{OH}^{\\star}}$ and $\\mathsf{H}^{\\star}$ during $H_{2}O$ dissociation and ${\\sf H}_{2}$ production steps. d Adjustments of the HER activities of HEA electrocatalysts by tailoring the electronegativity of the composition. e Identifying active sites of HEA for stabilization of intermediates by operando electrochemical Raman spectra. \n\n![](images/d4e216c0e58d82a7e2095df1b7ea79d91721f7723b93626c7cfe6c0d4002b077.jpg) \nFig. 2 Morphological and structural characterization of FeCoNiMnRu/CNFs. a FE-SEM, b TEM and c, d HRTEM images of FeCoNiMnRu/CNFs. The inset in $\\mathbf{\\eta}(\\bullet)$ is the corresponding FFT pattern of a FeCoNiMnRu HEA NP. e HAADF-STEM and the corresponding STEM-EDX mapping images of a FeCoNiMnRu HEA NP supported on CNFs. f XRD patterns of FeCoNiMnRu/CNFs with detailed Rietveld refinements. g Real-time in situ XRD patterns for FeCoNiMnRu/ CNFs with temperatures ranging from 25 to $1000^{\\circ}\\mathsf C$ . h The corresponding enlarged in situ XRD patterns of FeCoNiMnRu/CNFs. The heating rate was kept at $30^{\\circ}\\mathsf{C}\\mathsf{m i n}^{-1}$ during the whole process. i The thermodynamically driven phase transition of FeCoNiMnRu NPs in CNF nanofiber reactors. \n\nsubsequent $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ adsorption/desorption process, $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ leaves Co and is absorbed on Ru sites, which exhibit the lowest $\\Delta G_{\\mathrm{H^{*}}}$ of $-0.07\\mathrm{eV}$ . Adjustments of the HER activities of HEA catalysts are shown experimentally and theoretically by tailoring the electronegativity of the composition (Fig. 1d and e). Constructing controllable multifunctional active sites on HEA surfaces allows for different interactions with related intermediates, which is a powerful option for solving this scaling relation challenge. \n\n# Results \n\nSynthesis and materials characterization. The model electrocatalysts, single-phase FeCoNiXRu solid solution HEA NPs 1 $\\mathrm{{\\cdot}}\\mathrm{{}}\\mathrm{{}}\\mathrm{{}}\\mathrm{{=}}\\mathrm{{\\vec{C}r}}$ , Mn, and $\\mathrm{Cu}$ ), were synthesized in carbon nanofibers $(\\mathrm{FeCoNiXRu}/\\mathrm{CNFs})$ through a polymer nanofiber reactor strategy by combining the electrospinning technology and graphitization process. The schematic illustration of the synthetic procedure for FeCoNiXRu/CNFs $(\\mathrm{X}=\\mathrm{Cr}$ , Mn, and $\\mathrm{Cu}$ are shown in Supplementary Fig. 1 and the details are described in the Experimental section. \n\nAs revealed by the field emission scanning electron microscopy (FE-SEM) image in Fig. 2a, large amounts of FeCoNiMnRu NPs were densely and uniformly anchored in CNFs, and intertwined CNFs with diameters ranging from 100 to $200\\mathrm{nm}$ exhibited porous three-dimensional (3D) networks. The transmission electron microscopy (TEM) image (Fig. 2b) also displays the uniform distribution of FeCoNiMnRu NPs with an average diameter of approximately $14.2\\pm9.1\\mathrm{{nm}}$ (Supplementary Fig. 2). Figure 2c and d display distinctly visible lattice fringes with interplanar crystal spacings of 2.1 and $1.8\\mathring{\\mathrm{A}},$ corresponding to the (111) and (200) facets. All interplanar spacings were determined by measuring the total distances of 20 successive corresponding planes (Supplementary Fig. 3). In addition, the fast Fourier transform (FFT) pattern (inset in Fig. 2c) further reveals the facecentered cubic $(f c c)$ crystal structures of FeCoNiMnRu HEA NPs and exhibits the presence of typical (111), (200), and (220) planes. High-angle annular dark-field STEM (HAADF-STEM) and STEM energy dispersive X-ray (STEM-EDX) elemental mapping images (Fig. 2e) show the homogeneous distribution of elements Fe, Co, Ni, Mn, and Ru in a single FeCoNiMnRu HEA NP. Additionally, the line-scan EDX spectra (Supplementary Fig. 4) also reveal the distribution of Mn, Fe, Co, Ni, and Ru elements throughout the whole HEA NP, further demonstrating the formation of homogeneous structures in FeCoNiMnRu HEA. \n\nThe mapping area contains 10 HEA NPs (Supplementary Fig. 5) and the line-scan STEM-EDX of 3 HEA NPs (Supplementary Fig. 6) have also been conducted. The results exhibit the uniform distribution of Fe, Co, Ni, Mn, and Ru elements among all the HEA NPs, further suggesting the repeatability of HEA NPs with uniform composition distribution. The content of each element in FeCoNiMnRu/CNFs was measured by inductively coupled plasma-optical emission spectrometry (ICP-OES). The composition of HEA was calculated to be $\\mathrm{Fe_{0.23}C o_{0.22}N i_{0.22}M n_{0.14}R u_{0.19}}$ (Supplementary Table 1). A calculated mixing entropy of $\\Delta S>1.59\\mathrm{R}$ was determined from ICP-OES results, suggesting the intrinsic nature of HEAs without phase separation. The FeCoNiXRu/CNFs $[\\mathrm{X=Cr}$ and $\\mathtt{C u}$ ) (Supplementary Fig. 7 and Supplementary Tables 2, 3) with similar Ru contents and control samples of FeCoNi/CNFs, FeCoNiMn/CNFs, and FeCoNiRu/ CNFs (Supplementary Fig. 8) were prepared using the same approach and they all exhibited morphologies similar to that of FeCoNiMnRu/CNFs. \n\nThe crystalline structures of FeCoNiMnRu/CNFs (Fig. 2f) prepared at $1000^{\\circ}\\mathrm{C}$ under $^{3\\mathrm{h}}$ treatment and the corresponding control samples (Supplementary Fig. 9) were investigated with X-ray diffraction (XRD) patterns. As shown in Fig. 2f, the FeCoNiMnRu/CNFs exhibits three main diffraction peaks at $2\\Theta=43^{\\circ}$ , $50^{\\circ}$ and $74^{\\circ}$ , which can be indexed to the (111), (200), and (220) planes of the fcc phases (PDF#47-1417), respectively. No separated XRD peaks from Fe, Co, Ni, Mn, Ru, or metal oxides were observed, suggesting the formation of a single-phase HEA. In addition, the corresponding XRD detailed Rietveld refinements also confirm the single phase HEA structure of FeCoNiMnRu NPs. Compared with the standard line patterns of the FeNi alloy (PDF#47-1417), the fcc diffraction peaks of the FeCoNiMnRu HEA shifted slightly to lower angles due to the lattice distortions caused by the incorporation of Ru, Mn and Fe atoms and the resulted high entropy4. \n\nAll of the XRD patterns of FeCoNi/CNFs, FeCoNiMn/CNFs and FeCoNiRu/CNFs (Supplementary Fig. 9) exhibit the characteristic peaks for the (111), (200), and (220) planes of the fcc phase, suggesting that the fcc crystal structures can be well maintained after changing in the numbers of elements. Furthermore, with the incorporation of Mn and Ru atoms along with Fe, Co and Ni atoms, the peak positions of the (111) planes for FeCoNiMn/CNFs, FeCoNiRu/CNFs, and FeCoNiMnRu/ CNFs gradually move to lower angles, suggesting a strong high −entropy effects6. As shown in Supplementary Fig. 10, the XRD patterns of FeCoNiXRu/CNFs ( $\\mathrm{\\DeltaX=Cr}$ , Mn and $\\mathrm{Cu}$ ) confirm the fcc structures, and the diffraction peaks exhibit slight differences caused by the different compositions. \n\nThe temperature-dependent in situ XRD patterns are illustrated in Fig. $2\\mathrm{g}$ with temperatures range from 25 to $1000^{\\circ}\\mathrm{C}.$ . As shown in Fig. 2g, only taenite (FeNi alloy, PDF#47−1417) is observed after treated after $600^{\\circ}\\mathrm{C},$ with (111) planes at $2\\mathsf{\\theta}=43.8^{\\circ}$ . The FeCoNiMnRu HEA fcc phase and $\\mathrm{Mn}_{3}\\mathrm{Co}_{7}$ phase (marked as $\\#$ , PDF#18–0407) coexisted between 800 and $1000^{\\circ}\\mathrm{C},$ where the HEA becomes the dominant phase. The fraction of the HEA fcc phase increases with the increase of equilibration temperature, while the fraction of the $\\mathrm{Mn}_{3}\\mathrm{Co}_{7}$ phase decreased from 800 to $1000^{\\circ}\\mathrm{C},$ suggesting that more Mn and Co atoms diffused into the HEA fcc crystal lattice to produce a nearequimolar mixture of component by way of an effect driven by thermodynamics. During annealing at $1000^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ , full conversion to single-phase HEA occurred without observation of additional peaks, suggesting the complete formation of FeCoNiMnRu HEA. Figure 2h clearly shows that the peak positions of (111) planes for HEA initially shifted to lower 2θ angles between 800 and $1000^{\\circ}\\mathrm{C}$ and the asymmetry of diffraction peak strengthened with increased temperatures, suggesting the generation of a larger lattice distortion caused by differences in the atomic radii10. Then, the prolonged annealing treatment can reduce the lattice distortion of the HEA crystal, as evidenced by the positively shifted peak position and the enhanced symmetry of diffraction peaks. In regard of (200) and (220) planes (Supplementary Fig. 11), the peak shifts display the same trend as that of (111) planes. \n\nWe proposed a possible growth process of HEA NPs and the thermodynamically driven phase transition of FeCoNiMnRu NPs in CNF nanofiber reactors is illustrated in Fig. 2i. During graphitization, the $\\mathrm{Fe/Co/Ni/Mn/Ru}$ mixed metal precursors decomposed first, and then the reduced metal clusters were bonded and confined within the PAN-derived CNFs. At relative low temperature $600{-}800^{\\circ}\\mathrm{C},$ the metal elements with small atom radii differences prefer to form alloy phase and insufficient heating energy at low temperature cause the slightly atom diffusion, which make both of HEA and $\\mathrm{Mn}_{3}\\mathrm{Co}_{7}$ phases co-exist. At high temperature $1000^{\\circ}\\mathrm{C},$ sufficient dynamic energy caused the metal atoms to diffuse dramatically, leading to homogeneous formation of single-phase HEA alloy. It is concluded that the high temperature coupled with prolonged heating treatment provided the activation energy that drove complete mixing of multiple metal element atoms. The XRD patterns of FeCoNiMnRu/CNFs synthesized at 800, 900, and $1000^{\\circ}\\mathrm{C}$ under prolonged heat treatment for $^{3\\mathrm{h}}$ were also performed. As shown in Supplementary Fig. 12, compared with the in situ XRD patterns of FeCoNiMnRu/CNFs without prolonged heat treatment, all the diffraction peaks for fcc HEA NPs ((111), (200), (220) planes) exhibit positively shifts to high values, suggesting the reduced lattice parameters and lattice distortion. It is indicated that after the prolonged heat treatment for $^{3\\mathrm{h}}$ all of the diffraction peaks for $\\mathrm{Mn}_{3}\\mathrm{Co}_{7}$ phase vanished, suggesting the complete formation of FeCoNiMnRu HEA. Figure 2f and Supplementary Fig. 13 show the XRD patterns of $\\mathrm{FeCoNiMnRu/CNFs-800-3h}$ and FeCoNiMnRu/CNFs-1000-3h with detailed Rietveld refinements. Both of the FeCoNiMnRu HEA NPs obtained at $800^{\\circ}\\mathrm{C}$ and $1000^{\\circ}\\mathrm{C}$ under $^{3\\mathrm{h}}$ prolonged treatment was single phase structure with similar component. Therefore, negatively shifted peak position through in situ XRD results from 800 to $1000^{\\circ}\\mathrm{C}$ suggest the growth process of single-phase HEA (Fig. 2g). The XRD results of FeCoNiMnRu/CNFs with prolonged heat treatment from $1000^{\\circ}\\mathrm{C}$ to $1000{-}3\\mathrm{h}$ exhibit a positively shifted peaks position, further show a structural symmetry optimization by reducing the lattice distortion in HEA NPs. \n\nThe $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy (XAS) (Fig. 3a–d) was performed to investigate the chemical states of FeCoNiMnRu/ CNFs. The X-ray absorption near-edge structure (XANES) results (Fig. 3a and c) indicate that the pre-absorption edge features for Co and the absorption edge for Ru both are metallicity by comparing with reference metal Co, CoO and $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ foils, demonstrating that the Co and Ru elements in HEA NPs are in metallic state. The post-edge for Co and Ru in HEA exhibits slight deviation in the shape and intensity when compared with the reference metal Co and Ru foils. These features indicate the alloy formation rather than elemental segregation into pure metals, which would show the same length as metal Co and Ru foils. The extended X-ray absorption fine structure (EXAFS) of Co and $\\mathtt{R u}$ were determined through the fitting of the Fourier transform (FT) spectra. As shown in Fig. 3b and d, the FT-EXAFS spectra indicate that the average bond length of Ru and Co in HEA NPs is quite different from the metallic bond in bulk Co and Ru references, suggesting that the Co and Ru elements are surrounded by different metallic species (Fe, Mn and Ni). The bond structures of $\\scriptstyle{\\mathrm{Co}}$ and Ru in HEA reveal the similar average bond length without any oxidation when compared CoO and $\\bar{\\mathrm{Co}}_{3}\\mathrm{O}_{4}$ foils, further confirming the metallic states of Co and \n\n![](images/afcb01a522bdf9bcb8e0d3ff92f18d3bbaf318d70134ee48a1f46663a0900f87.jpg) \nFig. 3 Surface chemical states characterized by X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS). a The Co K-edge XANES spectra and b FT-EXAFS spectra of FeCoNiMnRu/CNFs, Co foil, CoO foil, and $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ foil. c The Ru K-edge XANES spectra and d FT-EXAFS spectra of FeCoNiMnRu/CNFs, Ru foil, and ${\\mathsf{R u O}}_{2}$ foil. High-resolution XPS spectra of as-prepared FeCoNiMnRu/CNFs: e Fe $2p,$ f Co $2p,$ g Ni $2p$ , h Mn $2p,$ and i Ru $3p$ . \n\nRu in HEA after stability test. According to the EXAFS fitting (Supplementary Fig. 14), the bond length (R) and coordination numbers of each bond type in the HEA were summarized in Supplementary Table 4. The reliability of the fitting method is supported by smaller R factors. \n\nX-ray photoelectron spectroscopy (XPS) was utilized to investigate the surface compositions and electronic effects of the as-prepared FeCoNiMnRu/CNFs. The XPS survey spectrum of the as-prepared FeCoNiMnRu/CNFs is shown in Supplementary Fig. 15. Figure 3e shows the presence of $\\mathrm{Fe}^{0}$ , $\\mathrm{Fe}^{2\\bar{+}}$ and $\\mathrm{Fe}^{3+}$ species, and the BEs at 707.1, 711.5, $724.8\\mathrm{eV}$ , 714.3 and $727.2\\mathrm{eV}$ are ascribed to Fe0 2p3/2, Fe2+ $2p_{3/2}$ , $\\mathrm{Fe}^{2+}$ $2p_{1/2}$ , $\\mathrm{Fe}^{3+}$ $2p_{3/2}$ and $\\mathrm{Fe}^{3+}$ $2p_{1/2},$ respectively. Another peak with a BE at $720.6\\mathrm{eV}$ is attributed to the satellite peaks of Fe $2p^{25}$ . For the Co $2p$ spectrum (Fig. 3f), the main doublets at 777.8, 792.7, 779.7, 795.1, 782.2 and $796.6\\mathrm{eV}$ correspond to $\\mathrm{Co}^{0}2p_{3/2},\\mathrm{Co}^{0}2p_{1/2},\\mathrm{Co}^{3+}2p_{3/2},\\mathrm{Co}^{3+}$ $2p_{1/2},\\ C o^{2+}\\ 2p_{3/2}$ and $\\mathrm{Co}^{2+}2\\dot{p}_{1/2}$ respectively26. The Ni $2p$ spectrum (Fig. 3g) displays the coexistence of metallic $\\mathrm{Ni}^{0}$ (852.6 and $869.9\\mathrm{eV}$ for $\\mathrm{\\bar{Ni}}^{0}2\\mathrm{\\bar{\\itp}}_{3/2}$ and $\\mathrm{Ni}^{0}2p_{1/2})$ , $\\mathrm{Ni}^{2+}$ (854.5 and $871.8\\mathrm{eV}$ for $\\mathrm{Ni}^{2+}2p_{3/2}$ and $\\mathrm{Ni}^{2+}2p_{1/2})$ , and $\\mathrm{Ni}^{3+}$ (856.7 and $874.2\\mathrm{eV}$ for $\\mathrm{Ni}^{3+}2p_{3/2}$ and $\\mathrm{Ni}^{3+}2p_{1/2})^{27}$ . The high-resolution Mn $2p$ spectrum (Fig. 3h) suggests the coexistence of $\\mathbf{\\bar{M}n}^{2+}2p_{3/2}$ $(641.6\\mathrm{eV})$ , $\\mathrm{Mn}^{2+}$ ${2\\tilde{p_{1/2}}(653.1\\ \\mathrm{\\tilde{eV}})},{\\mathrm{Mn}}^{3+}{2\\tilde{p}}_{3/2}(643.4\\mathrm{eV})$ and $\\bar{\\mathrm{Mn}}^{3+}2p_{1/2}\\:(654.6\\:\\mathrm{eV})$ . Two satellite peaks (marked as “Sat.”) appear at binding energies (BEs) of 648.5 and $659.7\\ \\mathrm{eV}^{28}$ . \n\nThe $\\mathrm{Ru}3p$ XPS spectrum of FeCoNiMnRu/CNFs (Fig. 3i) exhibit only metallic Ru states (462.0 and $484.1\\mathrm{eV}$ for $\\mathrm{Ru}^{0}~3\\bar{p}_{3/2}$ and ${\\mathrm{Ru}}^{0}$ $3p_{1/2})^{29}$ . The $\\textsc{o}1s$ spectrum (Supplementary Fig. 16) reveals peaks at 531.8 and $532.8\\mathrm{eV}$ , which are ascribed to hydroxyl groups and residual oxygen-containing groups on the surface of FeCoNiMnRu/CNFs, respectively30. There are no peaks observed for lattice $\\mathrm{O}^{2-}$ of metal oxides, and the strong adsorption of hydroxyl groups would be beneficial for water splitting. The Fe $2p$ , Co $2p$ , Ni $2p\\mathrm{.}$ , Mn $2p$ and $\\mathtt{R u\\ 2p}$ XPS spectra of the controlled samples including Ru/CNFs, FeCoNi/CNFs, FeCoNiMn/CNFs, and FeCoNiRu/CNFs were performed to provide more electron interaction information among the metal elements in HEA (Supplementary Fig. 17). The corresponding BE information were summarized in Supplementary Table 5. The BEs for Co, Ni, Fe and Mn in FeCoNiMnRu/CNFs show negative shifts when compared with FeCoNi/CNFs, FeCoNiRu/CNFs and FeCoNiMn/CNFs, respectively (Supplementary Fig. 17a–d). As shown in Supplementary Fig. 17e, the BEs for Ru in FeCoNiMnRu/CNFs exhibit positive shift when compared with the FeCoNiRu/CNFs and Ru/CNFs, suggesting that the Ru in HEA NPs served as the electron acceptor. The results strongly demonstrate the electron transfers from Fe, Co, Ni and Mn atoms to Ru atoms in HEA NPs that is due to the higher electronegativity of Ru (2.20) than those of Ni (1.91), Co (1.88), Fe (1.83), and $\\arcsin(1.55)^{31}$ . \n\nEvaluation of electrochemical performance. To evaluate the electrochemical performance, all of the as-prepared electrocatalysts were used as the working electrodes in a typical three-electrode system. A saturated calomel electrode (SCE) electrode and graphite rod were used as reference and counter electrodes, respectively. The HER, oxygen evolution reaction (OER) and overall water splitting (OWS) reaction were performed in Ar-saturated $1.0\\mathrm{M}$ \n\n![](images/86f6fe1abf15090f3da1a1567a1d41efe38a61b5317e6f7aa39cb4576df08ee9.jpg) \nFig. 4 Electrochemical performance of HEA electrocatalysts. a HER polarization curves, b the corresponding histogram for overpotentials at $100\\mathsf{m A c m^{-2}}$ and Tafel slopes obtained for Ru/CNFs, FeCoNi/CNFs, FeCoNiMn/CNFs, FeCoNiRu/CNFs, FeCoNiMnRu/CNFs, and $\\mathsf{P t/C}$ in 1.0 M KOH electrolyte. c ECSA-normalized HER polarization curves of the as-prepared electrocatalysts. d OER polarization curves for the as-prepared electrocatalysts, commercial ${\\sf R u O}_{2}$ and $\\mathsf{I r O}_{2}$ in $1.0\\mathsf{M}$ KOH electrolyte. e Comparison of HER and OER overpotentials at $10\\mathsf{m A c m}^{-2}$ in $1.0\\mathsf{M}\\mathsf{K}\\mathsf{O}\\mathsf{H}$ for different catalysts. Those recently reported literatures for HER and OER electrocatalysts were shown in Supplementary Tables 6 and 7. f Polarization curves for full water splitting by the asprepared electrocatalysts in a two-electrode configuration at a scan rate of $2{\\mathsf{m}}{\\mathsf{V}}{\\mathsf{s}}^{-1}$ . $\\pmb{\\mathsf{g}}$ Long-term stability measurement of the FeCoNiMnRu/CNFs electrode at $-1.16\\vee$ vs. RHE in 1 M KOH electrolyte for $600\\mathsf{h}$ . The insets in $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ are the XRD patterns (left) and STEM-EDS mapping images (right) of FeCoNiMnRu/CNFs after the long-term stability test. \n\nKOH electrolyte, and all potentials were calibrated with a reversible hydrogen electrode (RHE). As shown in Fig. 4a, the FeCoNiMnRu/ CNFs achieves the lowest overpotentials of $71\\mathrm{mV}$ to produce a current density of $100\\mathrm{mA}\\mathrm{cm}^{-2}$ and a Tafel slope of $67.4\\dot{\\mathrm{mV}}\\mathrm{dec}^{-1}$ (Supplementary Fig. 18), which are much more excellent than the indicated values for ${\\mathrm{Ru/CNFs}}$ ( $\\mathrm{421mV}$ and $337.1\\mathrm{mV}\\mathrm{dec}^{-1}.$ ), FeCoNi/CNFs $:410\\mathrm{mV}$ and $180.9\\mathrm{mV}\\mathrm{dec}^{-1}.$ ), FeCoNiMn/CNFs 1 $329\\mathrm{mV}$ and $162.3\\mathrm{mV}\\mathrm{dec}^{-1}.$ ), and $\\mathrm{FeCoNiRu/CNFs}$ ( $\\mathrm{122mV}$ and $120.9\\mathrm{mV}\\mathrm{dec}^{-1},$ ). The commercial $\\mathrm{Pt/C}$ cannot support a current density of $100\\mathrm{mA}\\mathrm{cm}^{-2}$ below $-0.2\\mathrm{V}$ , suggesting the excellent HER activity of HEAs under alkaline conditions. The low Tafel slope of FeCoNiMnRu/CNFs $(67.4\\mathrm{mV}\\mathrm{dec}^{-1}),$ indicates the operation of the Volmer–Heyrovsky mechanism22. The overpotentials at $100\\mathrm{mAcm}^{-2}$ and Tafel slopes of the as-prepared electrocatalysts are summarized in Fig. 4b. The remarkable electrocatalytic activity is further supported by electrochemical impedance spectroscopy (EIS) performed at an overpotential of $50\\mathrm{mV}$ As shown in Supplementary Fig. 19, the Nyquist plots of the asprepared electrodes exhibit the characteristic semicircles. The FeCoNiMnRu/CNFs presents the smallest charge transfer resistance $\\mathrm{(R_{ct})}$ value of $11.4\\Omega$ compared to the FeCoNi/CNFs $(637.9\\Omega)$ , FeCoNiMn $(950.1\\Omega)$ and FeCoNiRu/CNFs $(18.6\\Omega)$ , which served to accelerate the sluggish reaction kinetics. \n\nTo evaluate the active sites and the intrinsic activities of the asprepared electrocatalysts, electrochemical surface areas (ECSAs) were measured by a double-layer capacitance $\\mathrm{(C_{dl})}$ method32. As shown in Supplementary Fig. 20, the $\\mathrm{C_{dl}}$ values for FeCoNi/CNFs, FeCoNiMn/CNFs, FeCoNiRu/CNFs, and FeCoNiMnRu/CNFs are 16.4, 62.1, 110.5, and $104.6\\mathrm{mF}$ . The ECSA–normalized LSV curves (Fig. 4c) show that the intrinsic activity of $\\mathrm{FeCoNiMnRu}/$ CNFs at $\\bar{0}.01\\mathrm{mA}\\mathrm{cm}^{-2}$ (ECSA) is $85\\mathrm{mV}$ , which is remarkably enhanced relative to the values of FeCoNi/CNFs $(341\\mathrm{mV})$ , FeCoNiMn/CNFs $(309\\mathrm{mV})$ , and FeCoNiRu/CNFs ( $\\mathrm{146mV)}$ , suggesting the high intrinsic HER activity of HEA. Figure 4d shows the OER LSV curves of the as-prepared electrodes. The FeCoNiMnRu/CNFs requires the lowest overpotential of $308\\mathrm{mV}$ to reach $100\\mathrm{mA}\\mathrm{cm}^{-2}$ , as shown by the indicated values for $\\mathrm{Ru}/$ CNFs ( $\\mathrm{564}\\mathrm{mV}.$ , FeCoNi/CNFs $(382\\mathrm{mV})$ , FeCoNiMn/CNFs $(344\\mathrm{mV})$ , and FeCoNiRu/CNFs $(318\\mathrm{mV})$ . The remarkably enhanced OER kinetics of the FeCoNiMnRu HEA are reflected by the low Tafel slope of $61.3\\mathrm{mV}\\mathrm{dec}^{-1}$ (Supplementary Fig. 21). \n\nComparisons of the overpotentials and Tafel slopes for different electrocatalysts are summarized in Supplementary Fig. 22. The OER results exhibit a trend similar to that for HER activity in that HEA shows superior activity. As shown in Supplementary Fig. 23, the HER and OER LSV curves normalized by geometric area and mass loading of noble metal indicate that the FeCoNiMnRu/CNFs exhibit outstanding electrocatalytic activities and even prominently surpass the state-of-art $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%})$ , $\\mathrm{IrO}_{2}$ and ${\\mathrm{RuO}}_{2}$ electrocatalysts at high current density. At overpotential of $300\\mathrm{mV}$ for HER the $\\mathrm{FeCoNiMnRu/CNFs}$ show higher mass activity of 2666 than that of $\\mathrm{Pt/C}$ $\\mathrm{^{'}1688\\ m A\\ m g^{-1}{}_{P t}^{'}}$ . In addition, at overpotential of $450\\mathrm{mV}$ for $\\mathrm{OER},$ the FeCoNiMnRu/CNFs obtain the highest mass activity of $487\\mathrm{mA}\\mathrm{mg}^{-1}\\mathrm{_{Ru}^{}},$ which is significantly higher than ${\\mathrm{RuO}}_{2}$ $(14\\dot{6}\\mathrm{mA}\\mathrm{mg^{-1}}_{\\mathrm{Ru}})$ , and $\\mathrm{IrO}_{2}$ $(49\\mathrm{m}\\mathrm{\\bar{A}m g^{-1}}_{\\mathrm{Ir}})$ ). Furthermore, the overpotentials required for a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ are compared with those recently reported HER, OER, and OWS electrocatalysts in alkaline electrolytes (Fig. 4e, Supplementary Tables 6–8), which demonstrate the excellent activity of FeCoNiMnRu/CNFs. \n\nIn addition, the electrocatalytic activities of Ru-containing electrocatalysts have been further evaluated by comparing a series of FeCoNiMnRu/CNFs with different Ru contents. The FeCoNiMnRu/CNFs with different Ru contents were denoted as $\\mathrm{FeCoNiMnRu}_{0.5}/\\mathrm{CNFs}$ FeCoNiMnRu/CNFs, and FeCo$\\mathrm{NiMnRu_{2}/C N F s}$ , and the corresponding Ru contents were 2.41, 4.23 and $7.13\\mathrm{wt\\%}$ , respectively, which were measured by ICP-OES. As shown in Supplementary Fig. 24, it is shown that the FeCoNiMnRu/CNFs and $\\mathrm{FeCoNiMnRu_{2}/C N F s}$ display very similar values of overpotentials and Tafel slopes at $100\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ , while $\\mathrm{FeCoNiMnRu_{0.5}/C N F s}$ show obviously inferior activity. The ECSA values of FeCoNiMnRu/CNFs, $\\mathrm{FeCoNiMnRu_{0.5}/C N F s}$ and $\\mathrm{FeCoNiMnRu_{2}/C N F s}$ were calculated to be 2614, 2818, and $2093\\ \\mathrm{cm}^{2}$ for $\\mathrm{FeCoNiMnRu/CNFs}$ , F $\\mathrm{\\langleCoNiMnRu_{0.5}/C N F s_{\\Omega}}$ and $\\mathrm{FeCoNiMnRu_{2}/C N F s}$ , respectively. The $\\mathrm{R_{ct}}$ values of FeCoNiMnRu/CNFs, FeC $\\mathrm{\\oNiMnRu_{0.5}/C N F}$ s, and $\\mathrm{FeCoNiMnRu_{2}/}$ CNFs were measured to be 11.4, 16.3, and $5.1\\ \\Omega$ respectively. The OER activities were also evaluated by LSV curves. The overpotentials at $100\\mathrm{mA}\\mathrm{cm}^{-2}$ of FeCoNiMnRu/CNFs, FeCo$\\mathrm{NiMnRu}_{0.5}/\\mathrm{CNFs}$ , and $\\mathrm{FeCoNiMnRu_{2}/C N F s}$ were determined to be 308, 324, and $299\\mathrm{mV}$ , respectively. The results indicate that FeCoNiMnRu/CNFs achieved higher current density than that of $\\mathrm{FeCoNiMnRu_{2}/C N F s}$ at high overpotential $(>300\\mathrm{mV})$ . Therefore, at relative low Ru content range $(2{-}4~\\mathrm{wt\\%})$ , high Ru contents would lead to enhanced activity for water splitting. When the Ru contents increased to very high values $(>4\\mathrm{wt\\%})$ , the Ru contents could pose negligible or negative effects on improving the electrocatalytic activity. Inspired by the above results, we further fabricated an alkaline electrolyzer by employing FeCoNiMnRu/ CNFs as both the anode and cathode to explore practical electrolytic applications (Fig. 4f). Interestingly, the FeCo$\\mathrm{NiMnRu/CNFs\\rvert\\lvertFeCoNiMnRu/CNFs}$ system requires only a low voltage of $1.65\\mathrm{V}$ at $100\\mathrm{mAcm}^{-2}$ , which is lower than those of FeCoNiMn/CNFs||FeCoNiMn/CNFs (1.93 V), FeCoNiRu/CNFs|| FeCoNiRu/CNFs (1.71 V), and $\\mathrm{Pt/C||\\mathrm{RuO}}_{2}$ (Supplementary Fig. 25). \n\nThe electrochemical durability of FeCoNiMnRu/CNFs was characterized by LSV, CV cycles, and chronoamperometry measurements. Supplementary Fig. 26 shows the LSV curves of FeCoNiMnRu/CNFs before and after 10000 CV cycles; they nearly overlap with each other, suggesting the superior stability of FeCoNiMnRu/CNFs. The chronoamperometric curve (Fig. 4g) for FeCoNiMnRu/CNFs was measured at $-1.16\\mathrm{V}$ vs. RHE for more than $600\\mathrm{h}$ in $1.0\\mathrm{M}$ KOH. The current density at $1\\mathrm{A}\\mathrm{cm}^{-2}$ displays no evident changes, also suggesting its remarkable stability. This is ascribed to the wondrous corrosion resistance of HEA structures. The OER stability of FeCiNiMnRu/CNFs was conducted at $1.55\\mathrm{V}$ vs. RHE for $\\mathrm{i0h}$ (Supplementary Fig. 27). The current density showed no obvious decay during the test, and furthermore, the LSV curves before and after stability display negligible change. In addition, as shown in Supplementary Fig. 28, at $60^{\\circ}\\mathrm{C},$ , the $\\mathrm{FeCoNiMnRu/CNFs}$ can maintain a high current density of $1000\\mathrm{mAcm}^{-2}$ at $-2.22\\mathrm{V}$ vs. RHE for $\\mathsf{100h,}$ suggesting no obvious degradation in current density. In $10\\mathrm{M}$ KOH, the FeCoNiMnRu/CNFs also can afford a high current density of $1000\\mathrm{mAcm}^{-2}$ at $-0.77\\mathrm{V}$ vs. RHE for $\\mathrm{100\\bar{h}}$ without current density degradation (Supplementary Fig. 29). \n\nAs illustrated in the FE-SEM, TEM and HRTEM images of the FeCoNiMnRu/CNFs electrode after the long-term stability test (Supplementary Fig. 30), the electrode can well maintain its initial nanoparticle morphology comprising HEA and 3D nanofiber networks. XRD patterns (inset in Fig. 4g) of FeCoNiMnRu/CNFs obtained before and after the stability test show that the HEA can also retain the same fcc structure seen for the initial structure without any newly formed phases, suggesting ultrastable HER performance with an alkaline electrolyte. STEM-EDS element mapping images (inset in Fig. 4g) confirm the lack of phase separation and the homogeneous distribution of Fe, Co, Ni, Mn, and Ru in HEA NPs after the stability test. \n\nWe further used the XAS to investigate the chemical states of FeCoNiMnRu/CNFs before and after the HER stability test. As shown in Fig. 5a–f, the pre-absorption edge features for Co and the absorption edge for Ru both are metallicity by comparing with reference metal Co and Ru foils, demonstrating that the Co and Ru elements in HEA NPs are in metallic state. Meanwhile, after the stability test, the XANES of Co and Ru in HEA NPs also keep metallic state, suggesting the excellent oxidation resistance during the long-term HER stability test. The FT-EXAFS spectra (Fig. 5b and e) indicate that the bond structure of Co and Ru in HEA before and after stability test reveal the similar average bond length without any oxidation when compared CoO and $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ foils (Fig. 3a–d), further confirming the metallic states of Co and Ru in HEA after stability test. According to the EXAFS fitting (Fig. 5c and f), the bond length (R) and coordination numbers of each bond type in the HEA before and after stability test were summarized in Supplementary Table 4. The FT-EXAFS and WTEXAFS spectra (Fig. 5g–i) of Co and Ru in HEA before and after stability tests have negligible mismatch, which means that the FeCoNiMnRu HEA keep metallic states in long-term stability tests, exhibiting extraordinary durability. The reliability of the fitting method is supported by smaller R factors. \n\nThe relationship between active sites and intermediates. These discriminating enhancements of HER, OER, and OWS activities imply key roles for multiple metals serving as active centers, and we further used density functional theory (DFT) calculations to determine the cooperation of multiple metal active sites in the alkaline HER. The Tafel slope of the FeCoNiMnRu/CNFs $(67.4\\mathrm{mV}\\mathrm{dec}^{-1}.$ ) suggested the Volmer–Heyrovsky reaction pathway. Figure 6a illustrates the atomic configurations at catalytic sites of FeCoNiMnRu HEA in the four different stages. The $\\dot{\\mathrm{H}}_{2}\\mathrm{O}^{\\ast}$ molecule absorbed on the HEA surface (stage 1) is destabilized at the $_\\mathrm{H-OH}$ bond (stage 2), which is then dissociated to generate coadsorption of $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ and $\\mathrm{\\dot{O}H^{*}}$ intermediates (stage 3). The $\\boldsymbol{\\mathrm{\\Pi}}^{\\boldsymbol{\\mathrm{H}}^{*}}$ intermediate will be detached from the surfaces after combining with another $\\boldsymbol{\\mathrm{H}}^{*}$ to give $\\mathrm{H}_{2}$ production (stage 4). The water dissociation into $\\boldsymbol{\\mathrm{H}}^{*}$ and $\\mathrm{\\check{O}H{\\ }^{*}}$ and adsorption of the $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ are potential-determining steps (PDS), which determine the water dissociation rates. The chemical structures of the FeCoNiMnRu HEA were shown in Supplementary Fig. 31. Figure 6b shows the energy profile for water dissociation on Fe, Co, Ni, and Ru sites of the FeCoNiMnRu HEA surface at four states. In addition, the chemical structures and atomic configurations of Fe, Co, Ni, and Ru sites of FeCoNiMnRu HEA during $\\mathrm{H}_{2}\\mathrm{O}$ dissociation are shown in Supplementary Figs. 32–35. Interestingly, the energy barrier for breaking the $_\\mathrm{H-OH}$ bond (stage $1\\rightarrow$ stage 2) on $\\scriptstyle\\mathrm{Co}$ site of HEA is the lowest as $0.34\\mathrm{eV}$ in comparison with the Fe site $(0.70\\mathrm{eV})$ , Ni site $(0.63\\mathrm{eV})$ , and Ru site $(\\bar{0}.67\\mathrm{eV})$ . These results suggest that the $_{\\mathrm{H}_{2}\\mathrm{O}}$ adsorption and dissociation are more favorable at Co site, which is beneficial to accelerating water dissociation for the generation of $\\boldsymbol{\\mathrm{H}}^{*}$ intermediates. \n\n![](images/0903c1ce3248958dd05a710e8f8a03492377bb831b93324cf332112e43ce929f.jpg) \nFig. 5 Stability characterization by XAS. a The Co K-edge XANES spectra and b FT-EXAFS spectra of FeCoNiMnRu/CNFs before and after stability test, and Co foil. c The corresponding FT-EXAFS fitting curves of FeCoNiMnRu/CNFs before and after stability test. d The Ru K-edge XANES spectra and e FT-EXAFS spectra of FeCoNiMnRu/CNFs before and after stability test, and Ru foil. f The corresponding FT-EXAFS fitting curves of FeCoNiMnRu/CNFs before and after stability test. The WT-EXAFS spectra of Co and $\\mathsf{R u}$ in $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ metal foils and h, i FeCoNiMnRu/CNFs before and after stability tests. \n\nWe further calculated the Gibbs free energies of atomic hydrogen adsorbed $(\\Delta G_{\\mathrm{H^{*}}})$ (Fig. 6c) at four catalytic sites of HEA to reveal the influence of different metal sites on hydrogen adsorption. Atomic configurations of the FeCoNiMnRu HEA at the $\\boldsymbol{\\mathrm{H}}^{*}$ adsorption stage on Fe, Co, Ni, and Ru sites are shown in Supplementary Fig. 36. The DFT results indicated that the Ru sites achieve the most appealing $\\Delta G_{\\mathrm{H^{*}}}$ of $-0.07\\mathrm{eV}$ , as compared to those of Fe $(-0.13\\mathrm{eV})$ , Ni $(-0.27\\mathrm{eV})$ , and Co $(-0.4\\bar{3}\\mathrm{eV})$ , which suggests that $\\boldsymbol{\\mathrm{H}}^{*}$ is preferentially stabilized at the Ru sites. Therefore, during the whole electrocatalytic water splitting process, the $\\scriptstyle{\\mathrm{Co}}$ and Ru sites function to simultaneously accelerate the $_\\mathrm{H}_{2}\\mathrm{O}$ disassociation and $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ adsorption with the lowest energies, and this remarkable cooperation avoids active site blocking and accelerates the whole water dissociation process. \n\nThe active sites in HEA for the stabilization of intermediates were further investigated by operando electrochemical Raman spectra. As shown in Fig. 6d, the Raman spectrum of FeCoNiMnRu/CNFs determined at $0\\mathrm{V}$ displays three peaks at 1316, 1590, and $2616\\mathrm{cm}^{-1}$ , corresponding to the D band, G band, and 2D band of CNFs, respectively33. When a potential of $60\\mathrm{mV}$ was applied, new Raman peaks corresponding to $\\mathrm{Fe-O}$ bonds were observed at 215 and $290\\mathrm{cm}^{-1}$ , while Raman peaks at 585 and $704\\mathrm{cm}^{-1}$ were ascribed to Co-O bonds $34-36$ . The Raman peaks located at approximately 446 and $530\\mathrm{cm}^{-1}$ were attributed to the emergence of Ni-O bonds37. The newly formed Fe–O, $\\mathrm{\\DeltaNi-O}$ , and $\\bar{\\mathrm{Co-O}}$ bonds suggest the generation of $\\mathrm{Fe-OH}^{*}$ , Ni$\\mathrm{OH}^{*}$ , and ${\\mathrm{Co-OH}}^{*}$ intermediates, which originate from the cleavage of $_\\mathrm{H}_{2}\\mathrm{O}$ molecules. Interestingly, two sharp Raman peaks that emerged at 2069 and $2092\\mathrm{cm}^{-1}$ correspond to the Ru-H bonds, strongly suggesting the formation of ${\\mathrm{R}}{\\mathrm{{\\dot{u}}}}{-}\\mathrm{H}^{*}$ intermediates38,39. With increasing applied potentials ranging from 60 to $180\\mathrm{mV}$ , the intensities of all characteristic Raman peaks continuously increased, suggesting enhanced HER activity. We further obtained operando electrochemical Raman spectra of FeCoNiMn/CNFs during the HER process (Supplementary Fig. 37). Without the Ru metal, no Raman peaks for $\\mathrm{\\Ru-H}$ bonds were observed in the vicinity of $2000{-}2200\\mathrm{cm}^{-1}$ , directly confirming the ability of Ru to absorb $\\boldsymbol{\\mathrm{\\Pi}}^{\\boldsymbol{\\mathrm{*}}}$ . The Raman results provided direct evidence that $\\scriptstyle{\\mathrm{Co}}$ and Ru active sites in the FeCoNiMnRu HEA stabilize different intermediates. In the typical FeCoNiMnRu HEA, the Co sites facilitate $_\\mathrm{H}_{2}\\mathrm{O}$ dissociation, and the Ru sites simultaneously accelerate the combination of $\\boldsymbol{\\mathrm{H}}^{*}$ to $\\mathrm{H}_{2}$ . Therefore, the stabilization of multiple intermediates on various active sites in HEA was verified experimentally and theoretically. \n\n![](images/cffcd2c918f908b936b956a7ac93a092a4082b662d05d3a58d5fdefd5bca63df.jpg) \nFig. 6 Theoretical calculation and in situ electrochemical-Raman characterization. a The atomic configurations on catalytic sites of FeCoNiMnRu HEA at the four stages during $H_{2}O$ dissociation. b Reaction energy profile for water dissociation on various catalytic sites of the FeCoNiMnRu HEA surface. c Gibbs free energy $(\\Delta G_{\\mathsf{H}^{\\star}})$ profiles on various catalytic sites of the FeCoNiMnRu HEA surface. d–f Operando electrochemical-Raman spectra collected for FeCoNiMnRu/CNFs during the HER process in $1.0{\\ensuremath{\\mathsf{M}}}$ KOH electrolyte. \n\nThe above results indicated that the Fe, Co, Ni, and Ru sites in HEAs play different roles in the HER, and we further present a series of FeCoNiXRu $\\mathrm{{\\langleX=Mn}}$ , Cr, $\\mathrm{Cu}^{\\cdot}$ ) HEAs by using fifth elements (X) with different electronegativities to understand the relationship between electronegativity and HER activity. Considering that the difference in atomic configurations may change the adsorption energy, 8 randomly selected configurations of FeCoNiXRu $\\mathrm{\\bf{X}}=\\mathrm{\\bf{M}}\\mathrm{\\bf{\\bar{n}}}$ , Cr, $\\mathrm{Cu}^{\\cdot}$ ) HEA were analyzed by DFT calculation. The chemical structures of FeCoNiMnRu, FeCoNiCrRu and FeCoNiCuRu HEA with 8 randomly selected configurations are shown in Supplementary Figs. 38–40. As shown in Fig. 7a and b, the overpotentials at $10\\bar{0}\\mathrm{mA}\\mathrm{cm}^{-2}$ for FeCoNiCuRu/CNFs $(245\\mathrm{mV},$ ), FeCoNiCrRu/CNFs $(126\\mathrm{mV})$ , and FeCoNiMnRu/CNFs $(71\\mathrm{mV})$ suggest a strong relationship with the electronegativity of the fifth metal in HEA. For the OER (Supplementary Fig. 41), the low electronegativity of Mn (1.55) compared with those of Cr (1.66) and Cu (1.90) gives \n\nFeCoNiMnRu/CNFs the best OER activity with the lowest overpotential of $308\\mathrm{mV}$ at current density of $100\\mathrm{mAcm}^{-2}$ . The d-band center of each metal sites in FeCoNiMnRu and the three HEA structures were calculated and shown in Fig. 7c and d. The d-band orbitals with large spin polarization can be divided into spin up and spin down. As shown in Fig. 7d, a smaller number of spin states occupy the spin down orbitals, which is likely to be a spin-polarized catalytic active center and generally participate in catalytic reactions. As shown in Supplementary Figs. 42–44, there are much more electrons can be observed on Ru after the charge distributions in all three HEA structures. The results indicate the charge transfers from Fe, Co, Ni and Mn metals to Ru metal. \n\nWe further calculated the energy profile for water dissociation on Fe (Supplementary Figs. 45, 46), Co (Fig. 7e), Ni (Supplementary Figs. 47, 48), and Ru (Supplementary Fig. 49) sites on different FeCoNiMnRu, FeCoNiCrRu, and FeCoNiCuRu HEA surfaces. As shown in Fig. 7e, the energy profiles for the water dissociation on Co site of the three HEA surfaces demonstrate that the Co sites in FeCoNiMnRu HEA has the lowest energy barrier $(0.34\\mathrm{eV})$ for dissociation of water into $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ and $\\boldsymbol{\\mathrm{OH}^{*}}$ when compared with those of FeCoNiCrRu $(0.47\\mathrm{eV})$ and FeCoNiCuRu $(0.6\\bar{6}\\mathrm{eV})$ HEAs. Figure 7f strongly confirms that the electronegativity of the fifth metal in HEA can regulate the energy barrier for water dissociation at each metal site. In particular, energy barriers for water dissociation on Fe, Co, and Ru sites are reduced by introducing the less-electronegative Mn, and the Co site still exhibits the lowest value of $0.34\\mathrm{eV}$ , suggesting Co sites are the preferred locations for water disassociation. \n\n![](images/92474a13b850046662e7e3071998e9bd090d7a97637619f4ff060fe1452ca16a.jpg) \nFig. 7 Relationship between metal electronegativity and electrochemical performance. a HER polarization curves obtained on FeCoNiXRu/CNFs $({\\mathsf{X}}={\\mathsf{C r}}$ Mn, and $\\mathsf{C u})$ in $1.0\\mathsf{M}\\mathsf{K}\\mathsf{O}\\mathsf{H}$ electrolyte. b Correlation between the HER overpotentials at $100\\mathsf{m A c m}^{-2}$ Tafel slopes, and the electronegativities of metals $\\mathsf{X}$ (Cr, Mn, and $\\mathsf{C u})$ . c The ${\\mathsf{d}}$ -orbital projected density of states (PDOS) of Fe, Co, Ni, Mn, Ru, and FeCoNiMnRu. d Comparison of PDOS of FeCoNiXRu $\\langle X=M{\\mathsf{n}}$ , Cr, $\\mathsf{C u},$ HEA. e Reaction energy profile for water dissociation at Co sites of FeCoNiMnRu, FeCoNiCrRu, and FeCoNiCuRu HEA surfaces. f Correlation between the energy barrier for $H_{2}O$ dissociation at different metal sites and the electronegativities of metals (Cr, Mn, and Cu). $\\pmb{\\mathsf{g}}$ Gibbs free energy $(\\Delta G_{\\mathsf{H}^{\\star}})$ profiles at Ru sites on the FeCoNiMnRu, FeCoNiCrRu, and FeCoNiCuRu HEA surfaces. h Correlation between $\\Delta G_{\\mathsf{H}}$ \\* at different metal sites and the electronegativities of metals $\\mathsf{X}$ (Cr, Mn, and $\\mathsf{C u}$ ). \n\nAdditionally, the calculated $\\Delta G_{\\mathrm{H^{*}}}$ values for $\\begin{array}{r}{\\mathrm{{Ru},}}\\end{array}$ Fe, Co, Ni sites in FeCoNiMnRu, FeCoNiCrRu and FeCoNiCuRu are shown in Fig. $\\mathrm{7g}$ and Supplementary Figs. 50–52. The atomic configurations for $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ adsorption at the Fe, Co, $\\mathrm{Ni,}$ and Ru catalytic sites of FeCoNiCrRu, and FeCoNiCuRu HEA are shown in Supplementary Figs. 53 and 54. The results also demonstrate that optimized $\\Delta G_{\\mathrm{H^{*}}}$ values can be realized by introducing less-electronegative metals (Fig. 7h). Furthermore, all Ru sites in FeCoNiMnRu, FeCoNiCrRu, and FeCoNiCuRu showed the most appealing $\\Delta G_{\\mathrm{H^{*}}}$ compared with those of Fe, Co, and Ni sites, indicating that Ru sites are still the preferred sites for $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ adsorption. The $\\Delta G_{\\mathrm{H^{*}}}$ on Fe, Co, Ni, and Ru sites in FeCoNiXRu $\\mathrm{{\\bf{X}}}=\\mathrm{{Mn}},$ , Cr, Cu) with 8 randomly selected configurations were analyzed by DFT calculation, and the values of $\\Delta G_{\\mathrm{H^{*}}}$ were summarized in Supplementary Fig. 55 and Tables 9–11. DFT Results suggest that all of the Ru sites in FeCoNiXRu $\\mathrm{{\\cdot}}\\mathrm{{X}}=\\mathrm{{Mn}}$ , Cr, Cu) display lower values than Fe, Co, and $\\mathrm{\\DeltaNi}$ sites, demonstrating that the atomic configurations may not affect the $\\Delta G_{\\mathrm{H^{*}}}$ order on Fe, Co, and Ni. In addition, the Ru sites in FeCoNiMnRu also exhibit the lowest $\\Delta G_{\\mathrm{H^{*}}}$ than those Ru sites in FeCoNiCrRu, and FeCoNiCuMn HEA, further indicating that the five metal with low electronegativity in HEA could reduce the $\\Delta G_{\\mathrm{H^{*}}}$ . According to the bond length and coordination numbers of Co and $\\mathtt{R u}$ in HEA, as investigated by XAS (Fig. 3), we have chosen the atomic configuration 4 accordingly with XAS results as a representative sample to show the relationship between the $\\Delta G_{\\mathrm{H^{*}}}$ and electronegativity, unveiling the electrocatalytic mechanism of HER on FeCoNiXRu $\\mathrm{{\\cdot}}\\mathrm{{{X}}}=\\mathrm{{Mn}}$ , Cr, Cu) HEA. \n\nBased on the above results, the relationships between metal electronegativities in HEAs and the energy barriers for water dissociation and $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ adsorption at various active metal sites have been established. Charge transfer between different surface atoms occurs in HEAs containing five principal elements with different electronegativities, further leading to significant charge redistribution on the surfaces of alloys (Supplementary Figs. 42–44). In the FeCoNiMnRu HEA, the electronegativity differences in Fe (1.83), Co (1.88), Ni (1.91), Mn (1.55), and Ru (2.20) induce significant charge redistribution and create the most active Co and Ru sites with optimized energy barriers for simultaneously stabilizing $\\boldsymbol{\\mathrm{OH}^{*}}$ and $\\scriptstyle{\\mathrm{\\mathrm{~H}}}^{*}$ intermediates, greatly promoting the HER efficiency in alkaline solution. We prepared a series of HEAs by fixing Fe, Co, $\\mathrm{Ni},$ and Ru metals and varying the fifth metal among Mn, Cr, and \n\nCu. The decrease in electronegativities from $\\mathrm{Cu}$ (1.90) to Mn (1.55) leads to the reduced energy barriers for water dissociation and ${\\mathrm{~H~}}^{*}$ adsorption. Changing in the fifth metal in a HEA did not affect the adsorption energy order on active site in HEA; Co site was the most active sites for $\\mathrm{\\bar{OH}^{*}}$ adsorption, while Ru site was the most active sites for $\\boldsymbol{\\mathrm{H}}^{*}$ adsorption. In a FeCoNiMnRu NP, the Co site was the preferred active site with the lowest energy barriers $(0.34\\mathrm{eV})$ for water dissociation when compared with Fe, $\\mathrm{Ni,}$ and Ru sites. During the subsequent $\\boldsymbol{\\mathrm{H}}^{*}$ adsorption/desorption process, $\\boldsymbol{\\mathrm{\\Pi}}^{\\boldsymbol{\\mathrm{H}}^{*}}$ leaves $\\mathrm{Co}$ and is absorbed on Ru sites due to its lowest $\\Delta\\mathrm{G_{H^{*}}}$ of $-0.07\\mathrm{eV}$ . Adjustments of the HER activities of HEA catalysts were shown experimentally and theoretically by tailoring the electronegativities of the compositions. \n\n# Discussion \n\nIn summary, FeCoNiMnRu HEA NPs were designed and synthesized in electrospun CNFs by combining the electrospinning technique and graphitization process. The transformation from a multiphase to a single-phase HEA was evident from the real-time in situ XRD results and demonstrated a thermodynamically driven phase transition. The FeCoNiMnRu/CNFs achieved low overpotentials of 71 and $308\\mathrm{mV}$ to drive a current density of $\\mathrm{\\bar{100}m A c m}^{-2}$ for the HER and OER, respectively. It required only $1.65\\mathrm{V}$ to achieve two-electrode overall water splitting, and the chronoamperometric curve exhibited a stable current density of $1\\mathrm{A}\\mathrm{cm}^{-2}$ during continuous electrolysis for more than $600\\mathrm{h}$ in $1.0\\mathrm{M}$ KOH, suggesting its remarkable stability. In the FeCoNiMnRu HEA, the $\\scriptstyle{\\mathrm{Co}}$ site facilitated $_\\mathrm{H_{2}O}$ dissociation, and the Ru sites simultaneously accelerated the combination of $\\boldsymbol{\\mathrm{\\Pi}}^{*}$ to $\\mathrm{H}_{2}$ . The ability to stabilize multiple intermediates on various active sites in HEAs was verified experimentally and theoretically. Adjustments of the HER activities of HEA catalysts were shown experimentally and theoretically by tailoring the electronegativities of the composition. This work provides an in-depth understanding of the correlation between specific active sites and intermediates, opening up a fascinating approach for overcoming the scaling relation issues seen for multistep reactions. \n\n# Methods \n\nMaterials. Anhydrous ferric trichloride $\\mathrm{\\mathrm{FeCl}}_{3}$ , $297.0\\%$ ), nickel chloride hexahydrate $(\\mathrm{NiCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O};$ AR), and $^{\\mathrm{N,N}}$ -dimethylformamide (DMF, $299.0\\%$ ) were acquired from Sinopharm Chemical Reagent Co., Ltd. Manganese chloride tetrahydrate $(\\mathrm{MnCl}_{2}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}_{3} $ , $99.99\\%$ ), cobalt chloride hexahydrate $(\\mathrm{CoCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O},$ AR), anhydrous copper chloride $\\mathrm{(CuCl}_{2}$ , $98\\%$ ), commercial $\\mathrm{Pt/C}$ $(20\\mathrm{wt\\%})$ , ruthenium oxide $(\\mathrm{RuO}_{2})$ , iridium dioxide $\\left(\\mathrm{IrO}_{2}\\right)$ , and potassium hydroxide (KOH, GR, $95\\%$ were purchased from Shanghai Macklin Biochemical Co., Ltd. Chromium chloride hexahydrate $\\mathrm{(CrCl}_{3}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ , $99\\%$ ) was acquired from Beijing Innochem Science & Technology Co., Ltd. Ruthenium chloride trihydrate $\\mathrm{(RuCl}_{3}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ , $95\\%$ ) was provided by Bide Pharmatech Ltd. Polyacrylonitrile (PAN, $\\mathrm{M}_{\\mathrm{w}}=1.49\\times10^{5}$ , copolymerized with $10\\mathrm{wt\\%}$ acrylate) was supplied by Sinopec Shanghai Petrochemical Co., Ltd. Nafion117 solution $(5\\mathrm{wt\\%})$ was obtained from Shanghai Aladdin Biochemical Technology Co., Ltd. \n\nSynthesis of FeCoNiMnRu HEA nanoparticles supported on CNFs. Typically, $0.5\\mathrm{mmol}$ of $\\mathrm{MnCl}_{2}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O} $ , $0.5\\mathrm{mmol}$ of $\\mathrm{FeCl}_{3}$ , $0.5\\mathrm{mmol}$ of ${\\mathrm{CoCl}}_{2}{\\cdot}6{\\mathrm{H}}_{2}{\\mathrm{O}}$ , $0.5\\mathrm{mmol}$ of ${\\mathrm{NiCl}}_{2}{\\cdot}6{\\mathrm{H}}_{2}\\mathrm{O}$ , $0.5\\mathrm{mmol}$ of ${\\mathrm{RuCl}}_{3}{\\cdot}3{\\mathrm{H}}_{2}{\\mathrm{O}}$ and $1.5\\mathrm{g}$ of PAN were dissolved in $22{\\mathrm{g}}$ of dimethyl formamide (DMF). Homogeneous metal salts/PAN polymer solution was acquired after stirred by magnetic stirring apparatus for $^{8\\mathrm{h}}$ at room temperature. Afterwards, the syringes with stainless needles were filled with the as-prepared precursor solution and assembled to the electrospinning machine (YFSP-T, Tianjin Yunfan Technology Co., Ltd.) with an anode voltage of $20\\mathrm{kV}$ an injection rate of $0.3\\mathrm{mL/h}$ , and a distance between the collector and needle of $18\\mathrm{cm}$ . The as-prepared MnFeCoNiRu/PAN precursor nanofibers were put into the heating section of the home-built chemical vapor deposition (CVD) furnace. For the pre-oxidation process, the membranes were heated to $230^{\\circ}\\mathrm{C}$ in air with a heating rate of $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ and maintained for $^{3\\mathrm{h}}$ . Then, the furnace was heated to $1000^{\\circ}\\mathrm{C}$ under Ar atmosphere with a heating rate of $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ and maintained for $^{3\\mathrm{h}}$ . Finally, the as-synthesized FeCoNiMnRu HEA/CNFs was obtained after the furnace cooling down to room temperature under Ar atmosphere. \n\nSynthesis of metal alloy and HEA nanoparticles supported on CNFs. ${\\mathrm{Ru/CNFs}}$ FeCoNi/CNFs, FeCoNiMn/CNFs, FeCoNiRu/CNFs, FeCoNiCrRu/CNFs, and FeCoNiCuRu/CNFs were also synthesized through the same processes with those of FeCoNiMnRu/CNFs. The precursor solutions of above control samples contained $0.5\\mathrm{mmol}$ of each Fe, Co, Ni, Cu, Mn, Ru, Cr metal salts, $1.5\\:\\mathrm{g}$ PAN, and $22{\\mathrm{g}}$ DMF. FeCoN $\\mathrm{\\Omega}\\mathrm{/iMnRu}_{0.5}/\\mathrm{CNFs}$ and $\\vec{\\cdot}\\mathrm{e}{\\mathrm{CoNiMnRu}_{2}},$ /CNFs were prepared by halving and doubling the amount of $\\mathrm{RuCl}_{3}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ . FeCoNiMnRu/CNFs synthesized at 800 and $900^{\\circ}\\mathrm{C}$ were also synthesized to unveil the thermodynamically driven phase transition process of HEA NPs. \n\nMaterials characterizations. The field-emission scanning electron microscope (FE-SEM, HITACHI S-4800) at an acceleration voltage of $3\\mathrm{kV}$ was applied to collect the FE-SEM images. The transmission electron microscope (TEM, JEM$2100\\mathrm{\\plus})$ at an acceleration voltage of $200\\mathrm{kV}$ was used to record the TEM images. Bright field and high-angle annular dark field scanning transmission electron microscopy (STEM) images, energy dispersive X-ray spectroscopy (EDX) mapping images, and line-scan EDX spectra were characterized by a Tecnai G2 F30S-Twin, Philips-FEI at an acceleration voltage of $300\\mathrm{kV}$ Data of inductively coupled plasma-optical emission spectrometry (ICP-OES) were acquired by Agilent 720ES. $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) patterns were taken via a Smartlab 9kw advance powder X-ray Cu $\\mathrm{K}_{\\mathrm{a}}$ radiation diffractometer $(\\lambda=1.5406\\mathrm{\\AA})$ in the 2θ range of $20{\\sim}80^{\\circ}$ at the scanning rate of 0.5 or $10^{\\circ}\\operatorname*{min}^{-1}$ , with the Cu $\\mathrm{K}_{\\upalpha}$ source operating at $40\\mathrm{kV}$ and $40\\mathrm{mA}$ . X-ray photoelectron (XPS) spectra were acquired by Thermo Scientific K-Alpha with the Al (mono) $\\mathrm{K}_{\\mathrm{a}}$ source $(1486.6\\mathrm{eV})$ operating at $12\\mathrm{kV}$ and $6\\mathrm{mA}$ . The binding energies were calibrated with C 1 s $(284.8\\mathrm{eV})$ as the standard. The BL08U1-A at the Shanghai Synchrotron Radiation Facility (SSRF) operated at $500\\mathrm{eV}$ with injection currents of $100\\mathrm{mA}$ was used to obtain the Co K-edge and Ru K-edge X-ray absorption near edge structure (XANES) spectra, with radiation monochromatized by a Si (111) double-crystal monochromator. Metal Co, $\\begin{array}{r}{\\mathrm{{Ru,}}}\\end{array}$ CoO, $\\mathrm{Co}_{3}\\mathrm{O}_{4}.$ , and $\\mathrm{RuO}_{2}$ were taken as controls. The operando electrochemical Raman test was carried out in a round home-made electrolyzer. $\\mathrm{\\Ag/AgCl}$ electrode and $\\mathrm{\\Pt}$ wire served as the RE and CE, respectively. The prepared electrocatalysts were dispersed on the glass carbon electrode (GCE). The electrochemical processes were conducted in $1.0\\mathrm{\\dot{M}\\ K O H}$ saturated with Ar and controlled by a CHI660E electrochemical workstation. Raman spectrometer (inVia) used the laser wavelength of $785\\mathrm{nm}$ . \n\nElectrochemical Characterization. Electrochemical measurements were all conducted in a typical three-electrode system at $25^{\\circ}\\mathrm{C}$ in $1.0\\mathrm{M}$ KOH with a Autolab electrochemical workstation. Saturated calomel electrode (SCE) and graphite rod were used as reference electrode (RE) and count electrode (CE), respectively. The SCE was calibrated before each test. The self-supported CNFs-based materials were cut into $1\\times1\\mathrm{cm}^{-2}$ and served as working electrode (WE). Potentials were converted to the reversible hydrogen electrode (RHE) by the equation $\\mathrm{E}_{\\mathrm{RHE}}=$ $\\mathrm{E_{SCE}+0.244+0.059\\times p H}$ . Pt/C $(20\\mathrm{wt\\%})$ , $\\mathrm{RuO}_{2}$ and $\\mathrm{IrO}_{2}$ powder were taken as controls and deposited on glassy carbon electrode (GCE) with diameter of $3\\mathrm{mm}$ for measurement. To prepare the electrocatalyst ink, $3\\mathrm{mg}$ of electrocatalyst was dispersed into $1\\mathrm{mL}$ mixed solvent with a volume ratio of Visopropanol: $\\mathrm{V}_{\\mathrm{water}}=3{:}1$ . After $30\\mathrm{min}$ of ultrasonication, $25\\upmu\\mathrm{L}$ Nafion117 solution was added. After another $30\\mathrm{min}$ for ultrasonication, ${5}\\upmu\\mathrm{L}$ electrocatalyst ink was casted on GCE and dried in the air naturally. All linear sweep voltammetry (LSV) curves were obtained at a scan rate of $2\\mathrm{m}\\mathrm{{V}}\\mathrm{{s}}^{-1}$ with $95\\%$ iR-compensation. Tafel plots were gained according to the Tafel equation: \n\n$$\n\\eta=a+b\\log j\n$$ \n\nwhere $\\eta,b,$ and $j$ represent the overpotential, Tafel slope, and current density, respectively. Electrochemical double layer capacitances $\\mathrm{(C_{dl})}$ were measured by analyzing the cyclic voltammetry (CV) curves at scan rate of 10, 20, 30, 40, and $50\\mathrm{mVs^{-1}}$ in the range of $-0.78$ to $-1.00\\mathrm{V}$ vs. SCE. Plotting the $\\Delta i/2$ $(\\Delta i=i_{a}-i_{c},$ where $i_{a}$ and $i_{c}$ represent the positive and negative current, respectively) at $-0.89\\mathrm{V}$ vs. SCE against the scan rate (v), the $\\mathrm{C_{dl}}$ can be calculated by the equation: $\\mathrm{C_{dl}}=\\Delta i/$ $2\\nu.$ Electrochemical active surface area (ECSA) was estimated by the equation: $\\mathrm{ECSA}=\\mathrm{C_{\\mathrm{dl}}}/\\mathrm{C_{s}},$ where the specific capacitance value $\\textstyle(\\mathrm{C}_{\\mathrm{s}})$ was taken $0.04\\mathrm{~mF~cm^{-2}}$ . The ECSA-normalized LSV curves were acquired by the equation: $j_{\\mathrm{ECSA}}=i/\\mathrm{ECSA}$ where $j_{\\mathrm{ECSA}}$ and $i$ is the current density normalized to ECSA and current of the working electrode, respectively. $10,000\\mathrm{CV}$ cycles in the range of $-0.4$ to $0.05\\mathrm{~V~}\\nu s$ . RHE at a scan rate of $100\\mathrm{m}\\dot{\\mathrm{V}}\\mathrm{s}^{-1}$ and chronoamperometry were performed to evaluate the durability of samples. In the course of the chronoamperometry test, $10\\mathrm{min}$ pauses were inset into the electrolysis process with intervals of about $^{10\\mathrm{h}}$ operating. Meanwhile, the electrolyte was renewed and the RE was calibrated during the pauses. For the comparison of mass activities and eliminating the difference in electrode structure, $\\mathrm{Pt/C}$ , $\\mathrm{RuO}_{2}$ , $\\mathrm{IrO}_{2}$ , and FeCoNiMnRu/CNFs powder were dropped onto GCE, and the calculation process is shown as follow: $J_{\\mathrm{{mass}}}=J_{\\mathrm{{geo}}}$ $\\times~0.07069~\\mathrm{cm}^{2}/\\mathrm{m}$ , $\\mathrm{m}=3\\mathrm{mg}\\times\\mathrm{{\\boldsymbol{\\omega}}}\\times(5\\mathrm{\\upmuL}/1000\\mathrm{\\upmuL})$ , where $\\mathbf{m}$ and ω are the mass loading and mass fraction of noble metal (Ru, Pt, or Ir). \n\nComputational methods. We have employed the first-principles40,41 to perform all Spin-polarization density functional theory (DFT) calculations within the generalized gradient approximation (GGA) using the Perdew-Burke-Ernzerhof $(\\mathrm{PBE})^{42}$ formulation. vdW corrections was added. We have chosen the projected augmented wave (PAW) potentials43,44 to describe the ionic cores and take valence electrons into account using a plane wave basis set with a kinetic energy cutoff of $400\\mathrm{eV}$ . Partial occupancies of the Kohn−Sham orbitals were allowed using the Gaussian smearing method and a width of $0.05\\mathrm{eV}$ . The electronic energy was considered self-consistent when the energy change was smaller than $10^{-6}\\mathrm{eV}$ . A geometry optimization was considered convergent when the energy change was smaller than $0.04\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ . The vacuum spacing in a direction perpendicular to the plane of the structure is $15\\mathrm{\\AA}$ . The Brillouin zone integration is performed using $3\\times$ $3\\times1$ Monkhorst-Pack $\\mathrm{\\Deltak}$ -point sampling for a structure. Finally, the adsorption energies $\\mathrm{(E_{ads})}$ were calculated as Eq. (2): \n\n$$\n\\mathrm{E_{ads}=E_{a d/s u b}-E_{a d}-E_{s u b}}\n$$ \n\nwhere $\\mathrm{E_{ad/sub}},$ $\\mathrm{{{E}_{a d}},}$ and $\\mathrm{E_{sub}}$ are the total energies of the optimized adsorbate/ substrate system, the adsorbate in the structure, and the clean substrate, respectively. The free energy was calculated using the Eq. (3): \n\n$$\n\\mathrm{G=E+ZPE-TS}\n$$ \n\nwhere G, E, ZPE, and TS are the free energy, total energy from DFT calculations, zero point energy, and entropic contributions, respectively. The ZPE has been calculation using the $6\\times2\\times2$ Monkhorst-Pack k-point and $\\mathrm{DFT+U}$ correction has been used in our systems. In our alloy structure, the FCC structure has been obtained with the 80 atoms. \n\n# Data availability \n\nSource data are provided with this paper. The data used in this study are presented in the text and Supplementary Information. Additional data and information are available from the corresponding author upon reasonable request. Additionally, data reported herein have been deposited in the Figshare database, and are accessible through https://figshare. com/articles/figure/Source_Data_zip/19513684. Source data are provided with this paper. \n\nReceived: 7 September 2021; Accepted: 22 April 2022; Published online: 13 May 2022 \n\n# References \n\n1. Du, Z. et al. High-entropy atomic layers of transition-metal carbides (MXenes). Adv. Mater. 33, 2101473 (2021). \n2. Tan, Chaoliang. et al. Recent advances in ultrathin two-dimensional nanomaterials. Chem. Rev. 117, 6225–6331 (2017). \n3. Zhu, J., Hu, L., Zhao, P., Lee, L. Y. S. & Wong, K. Recent advances in electrocatalytic hydrogen evolution using nanoparticles. Chem. Rev. 120, 851–918 (2020). \n4. Huang, K. et al. Exploring the impact of atomic lattice deformation on oxygen evolution reactions based on a sub- $5\\mathrm{nm}$ pure face-centred cubic high-entropy alloy electrocatalyst. J. Mater. Chem. A 8, 11938–11947 (2020). \n5. Glasscott, M. W. et al. Electrosynthesis of high-entropy metallic glass nanoparticles for designer, multi-functional electrocatalysis. Nat. Commun. 10, 2650 (2019). \n6. Jin, Z. et al. Top−down synthesis of noble metal particles on high-entropy oxide supports for electrocatalysis. Chem. Mater. 33, 1771–1780 (2021). \n7. Tomboc, G. M., Kwon, T., Joo, J. & Lee, K. High entropy alloy electrocatalysts: a critical assessment of fabrication and performance. J. Mater. Chem. A 8, 14844–14862 (2020). \n8. Yao, Y. et al. Carbothermal shock synthesis of high-entropy-alloy nanoparticles. Science 359, 1489–1494 (2018). Mori, K. et al. Hydrogen spillover-driven synthesis of high-entropy alloy nanoparticles as a robust catalyst for $\\mathrm{CO}_{2}$ hydrogenation. Nat. Commun. 12, 3884 (2021). \n10. Qiu, H. et al. Noble metal-free nanoporous high-entropy alloys as highly efficient electrocatalysts for oxygen evolution reaction. ACS Mater. Lett. 1, 526–533 (2019). \n11. Jin, Z. et al. Nanoporous Al-Ni-Co-Ir-Mo high-entropy alloy for record-high water splitting activity in acidic environments. Small 15, 1904180 (2019). \n12. Lv, Z. Y. et al. Development of a novel high-entropy alloy with eminent efficiency of degrading azo dye solutions. Sci. Rep. 6, 34213 (2016). \n13. Cai, Z. et al. Nanoporous ultra-high-entropy alloys containing fourteen elements for water splitting electrocatalysis. Chem. Sci. 12, 11306 (2021). \n14. Vasileff, A., Xu, C., Jiao, Y., Zheng, Y. & Qiao, S. Surface and interface engineering in copper-based bimetallic materials for selective $\\mathrm{CO}_{2}$ electroreduction. Chem 4, 1809–1831 (2018). \n15. Wen, L. et al. Cr-dopant induced breaking of scaling relations in CoFe layered double hydroxides for improvement of oxygen evolution reaction. Small 15, 1902373 (2019). electrochemical conversion of $\\mathrm{CO}_{2}$ . Adv. Energy Mater. 6, 1600463 (2016). \n17. Chen, C. et al. Highly crystalline multimetallic nanoframes with threedimensional electrocatalytic surfaces. Science 343, 1339–1343 (2014). \n18. Yang, T. et al. Noble-metal nanoframes and their catalytic applications. Chem. Rev. 121, 796–833 (2021). \n19. Voiry, D., Yang, J. & Chhowalla, M. Recent strategies for improving the catalytic activity of 2D TMD nanosheets toward the hydrogen evolution reaction. Adv. Mater. 28, 6197–6206 (2016). \n20. Huang, H. et al. Understanding of strain effects in the electrochemical reduction of $\\mathrm{CO}_{2}$ : using Pd nanostructures as an ideal platform. Angew. Chem. Int. Ed. 56, 3594–3598 (2017). \n21. Sneed, B. T., Younga, A. P. & Tsung, C. Building up strain in colloidal metal nanoparticle catalysts. Nanoscale 7, 12248–12265 (2015). \n22. Zhang, S. et al. In situ interfacial engineering of nickel tungsten carbide Janus structures for highly efficient overall water splitting. Sci. Bull. 65, 640–650 (2020). \n23. Gamler, J. T. L., Ashberry, H. M., Skrabalak, S. E. & Koczkur, K. M. Random alloyed versus intermetallic nanoparticles: a comparison of electrocatalytic performance. Adv. Mater. 30, 1801563 (2018). \n24. Wang, Y. et al. Advanced electrocatalysts with single-metal-atom active sites. Chem. Rev. 120, 12217–12314 (2020). \n25. Zhang, Y. et al. Stabilizing oxygen vacancy in entropy-engineered ${\\mathrm{CoFe}}_{2}{\\mathrm{O}}_{4}$ -Type catalysts for Co-prosperity of efficiency and stability in an oxygen evolution reaction. ACS Appl. Mater. Interfaces 12, 32548–32555 (2020). \n26. Wang, S. et al. $\\scriptstyle\\mathrm{Co,N}$ -codoped graphene as efficient electrocatalyst for hydrogen evolution reaction: Insight into the active centre. J. Power Sources 363, 260–268 (2017). \n27. Li, S. et al. Nanoporous high-entropy alloys with low Pt loadings for highperformance electrochemical oxygen reduction. J. Catal. 383, 164–171 (2020). \n28. Cui, M. et al. High-entropy metal sulfide nanoparticles promise highperformance oxygen evolution reaction. Adv. Energy Mater. 11, 2002887 (2021). \n29. Zhang, Z. et al. Simple construction of ruthenium single atoms on electrospun nanofibers for superior alkaline hydrogen evolution: a dynamic transformation from clusters to single atoms. Chem. Eng. J. 392, 123655 (2020). \n30. Li, Z. et al. Cation and anion Co-doped perovskite nanofibers for highly efficient electrocatalytic oxygen evolution. ACS Appl. Mater. Interfaces 12, 41259–41268 (2020). \n31. Xu, X. et al. Elemental core level shift in high entropy alloy nanoparticles via X-ray photoelectron spectroscopy analysis and first-principles calculation. ACS nano 14, 17704–17712 (2020). \n32. Voiry, D. et al. Best practices for reporting electrocatalytic performance of nanomaterials. ACS Nano 12, 9635–9638 (2018). \n33. Zhang, C. et al. Single-atomic ruthenium catalytic sites on nitrogen-doped graphene for oxygen reduction reaction in acidic medium. ACS Nano 11, 6930–6941 (2017). \n34. Nieuwoudt, M. K., Comins, J. D. & Cukrowski, I. The growth of the passive film on iron in $0.05\\mathrm{~M~NaOH}$ studied in situ by Raman micro-spectroscopy and electrochemical polarisation. Part I: near-resonance enhancement of the Raman spectra of iron oxide and oxyhydroxide compounds. J. Raman Spectrosc. 42, 1335–1339 (2011). \n35. Lee, A. P. et al. In situ Raman spectroscopic studies of the teeth of the chiton Acanthopleura hirtosa. JBIC 3, 614–619 (1998). \n36. Chen, Z. et al. Reversible structural evolution of $\\mathrm{NiCoO_{x}H_{y}}$ during the oxygen evolution reaction and identification of the catalytically active phase. ACS Catal. 8, 1238–1247 (2018). \n37. Chen, J. et al. Interfacial interaction between FeOOH and Ni–Fe LDH to modulate the local electronic structure for enhanced OER electrocatalysis. ACS Catal. 8, 11342–11351 (2018). \n38. Sato, T. et al. Raman and infrared spectroscopic studies on ${\\mathrm{Li}}_{4}{\\mathrm{RuH}}_{6}$ combined with first-principles calculations. Mater. Trans. 55, 1117–1121 (2014). \n39. Smith, P. W., Ellis, S. R., Handford, R. C. & Tilley, T. D. An anionic ruthenium dihydride $\\mathrm{[Cp^{*}(^{i}P r_{2}M e P)R u H_{2}]^{-}}$ and its conversion to heterobimetallic $\\mathrm{Ru}(\\upmu-$ $\\mathrm{H})_{2}\\mathrm{M}$ ( $\\mathrm{\\Delta}\\mathrm{M}{=}\\mathrm{Ir}$ or $\\mathrm{Cu}$ complexes. Organometallics 38, 336–342 (2019). \n40. Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n41. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n42. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n43. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n44. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n\n# Acknowledgements \n\nThis study is supported by the National Natural Science Foundation of China (NSFC) (Grant nos. 52073124, 51803077), Natural Science Foundation of Jiangsu Province (Grant nos. BK20180627), Postdoctoral Science Foundation of China (2018M630517, 2019T120389), the MOE & SAFEA, 111 Project (B13025), and the Fundamental Research Funds for the Central Universities. We also thank the characterizations supported by Central Laboratory, School of Chemical and Material Engineering, Jiangnan University. \n\n# Author contributions \n\nH.Z. conceived and supervised the research. H.Z, J.H., and Z. Z. designed the experiments. J. H. performed most of the experiments and data analysis. H.Z., C. W., G. G., F. L., and T. L. performed the DFT calculations and mechanistic analysis. J.H., S.L., P. M., W. D., and F. L. prepared the electrodes and helped with electrochemical measurements. K. C. conducted and analyzed HRTEM micrographs and mapping images. J. H., Z. Z., M. D., and H. Z. wrote the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-30379-4. \n\nCorrespondence and requests for materials should be addressed to Han Zhu. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. 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If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1038_s41467-022-29875-4", + "DOI": "10.1038/s41467-022-29875-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-29875-4", + "Relative Dir Path": "mds/10.1038_s41467-022-29875-4", + "Article Title": "Activating lattice oxygen in NiFe-based (oxy)hydroxide for water electrolysis", + "Authors": "He, ZY; Zhang, J; Gong, ZH; Lei, H; Zhou, D; Zhang, NA; Mai, WJ; Zhao, SJ; Chen, Y", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Transition metal oxides or (oxy)hydroxides have been intensively investigated as promising electrocatalysts for energy and environmental applications. Oxygen in the lattice was reported recently to actively participate in surface reactions. Herein, we report a sacrificial template-directed approach to synthesize Mo-doped NiFe (oxy)hydroxide with modulated oxygen activity as an enhanced electrocatalyst towards oxygen evolution reaction (OER). The obtained MoNiFe (oxy)hydroxide displays a high mass activity of 1910 A/g(metal) at the overpotential of 300 mV. The combination of density functional theory calculations and advanced spectroscopy techniques suggests that the Mo dopant upshifts the O 2p band and weakens the metal-oxygen bond of NiFe (oxy)hydroxide, facilitating oxygen vacancy formation and shifting the reaction pathway for OER. Our results provide critical insights into the role of lattice oxygen in determining the activity of (oxy)hydroxides and demonstrate tuning oxygen activity as a promising approach for constructing highly active electrocatalysts. While (oxy)hydroxides are effective oxygen evolution electrocatalysts, the impacts of pre-catalyst properties on catalyst activities are challenging to assess. Here, authors find Mo dopants in Ni-Fe (oxyhydroxides) to promote lattice oxygen participation and to boost oxygen evolution activities.", + "Times Cited, WoS Core": 366, + "Times Cited, All Databases": 370, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000785003900005", + "Markdown": "# Activating lattice oxygen in NiFe-based (oxy) hydroxide for water electrolysis \n\nZuyun He1,5, Jun Zhang 2,5, Zhiheng Gong1, Hang Lei3, Deng Zhou4, Nian Zhang $\\textcircled{6}$ 4, Wenjie Mai $\\textcircled{1}$ 3, Shijun Zhao $\\textcircled{1}$ 2✉ & Yan Chen 1✉ \n\nTransition metal oxides or (oxy)hydroxides have been intensively investigated as promising electrocatalysts for energy and environmental applications. Oxygen in the lattice was reported recently to actively participate in surface reactions. Herein, we report a sacrificial template-directed approach to synthesize Mo-doped NiFe (oxy)hydroxide with modulated oxygen activity as an enhanced electrocatalyst towards oxygen evolution reaction (OER). The obtained MoNiFe (oxy)hydroxide displays a high mass activity of $1910\\mathrm{~A/g}_{\\mathrm{metal}}$ at the overpotential of $300\\mathsf{m V}$ . The combination of density functional theory calculations and advanced spectroscopy techniques suggests that the Mo dopant upshifts the $\\textsf{O}2p$ band and weakens the metal-oxygen bond of NiFe (oxy)hydroxide, facilitating oxygen vacancy formation and shifting the reaction pathway for OER. Our results provide critical insights into the role of lattice oxygen in determining the activity of (oxy)hydroxides and demonstrate tuning oxygen activity as a promising approach for constructing highly active electrocatalysts. \n\nT irnatnesnitsiiovne mientvael iogxaitdeed so (o xmyi)sihnygdraolxtiedrensa vhea e cbtereoncatalysts because of their high catalytic activity, low cost, and good stability. The surface metal sites in these materials are generally considered as the active sites for surface reactions1,2. Interestingly, recent studies have shown that oxygen in the lattice of metal oxides and (oxy)hydroxides can also participate in surface reactions and may play a critical role in regulating the catalyst activity $^{3-5}$ . For example, Grimaud6 and Mefford7 reported that lattice oxygen could participate in the oxygen evolution reaction (OER) on the $(\\mathrm{La},\\mathrm{Sr})\\mathrm{CoO}_{3}$ surface, which was later referred to as lattice oxygen mechanism (LOM). Similar LOM mechanisms were then discovered for the OER on other oxides and (oxy)hydroxides, such as $\\mathrm{SrCo}_{1\\mathrm{-y}}\\mathrm{Si}_{\\mathrm{y}}\\mathrm{O}_{3\\mathrm{-}\\delta}{}^{8}$ $\\mathrm{PrBa}_{0.5}\\mathrm{Sr}_{0.5}\\mathrm{Co}_{1.5}\\mathrm{Fe}_{0.5}\\mathrm{O}_{5+\\delta}^{\\cdot}9$ , $\\mathrm{Sr(Co_{0.8}F e_{0.2})_{0.7}B_{0.3}O_{3-\\delta}10}$ , $\\mathrm{Co}\\mathrm{Zn}$ (oxy)hydroxide11, $\\mathrm{CoAl}_{2}\\mathrm{O}_{4}{}^{12}$ , $\\mathrm{Na_{x}M n_{3}O_{7}}13$ and NiFe (oxy) hydroxide14. In addition to the OER reaction at room temperature, Hwang et al.15 reported that the NO oxidation reaction on $\\mathrm{La}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3}$ oxides also strongly depended on the surface oxygen activity, which is defined as the oxygen $2p$ -band center relative to the Fermi level. Chen et al.16 tuned the oxygen activity in perovskite ferrite by Co doping, leading to a change in hydrogen oxidation reaction performance at elevated temperatures. All these results demonstrate that modulating lattice oxygen activity is an effective method for improving the activity of transition metal oxide or (oxy)hydroxide electrocatalysts. \n\nOER is regarded as the main bottleneck in many electrochemical energy devices due to its sluggish reaction kinetics9. Because of the highly oxidative environment, OER catalysts suffer from effects such as spontaneous dissolution and surface reconstruction during operation, which strongly impact the stability of the devices17,18. These effects in certain cases were also reported to promote the OER activities19–22. For instance, several research groups reported highly active OER catalysts with perovskite oxide8,23, nitride24, or phoshide25 as the core materials, and with self-reconstructed amorphous phase or (oxy)hydroxides as the active phase on the surface18,19,26. Jiang et al.27 demonstrated that the leaching of lattice $\\mathrm{Cl^{-}}$ from cobalt oxychloride $(\\mathrm{Co}_{2}(\\mathrm{OH})_{3}\\mathrm{Cl})$ during the OER process could trigger the atomic-level unsaturated sites and efficiently boost catalytic activity. While all the pioneering works mentioned above have demonstrated the selfreconstruction or material leaching effects during operation as an effective way to achieve highly active catalysts, the impacts of pre-catalysts on the activity of final catalysts are still lack of investigation. \n\nIn this work, we report a sacrificial template-directed approach to synthesize ultrathin NiFe-based (oxy)hydroxide with modulated lattice oxygen activity as highly efficient and stable OER catalysts. $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets are used as sacrificial templates to adsorb metal cations to form self-assembled NiFe (oxy)hydroxide on the surface. After removing the $\\mathbf{MoS}_{2}$ sacrificial template by Mo leaching under the OER condition, ultra-thin NiFe (oxy) hydroxides with Mo doping (MoNiFe (oxy)hydroxide) are obtained. The MoNiFe (oxy)hydroxide displays enhanced OER performance, with a high mass activity of 1 $\\scriptstyle\\mathtt{10\\ A/g_{\\mathrm{metal}}}$ at the overpotential of $300\\mathrm{mV}$ , which is about 60 times higher than that of NiFe (oxy)hydroxide. The combination of synchrotron-based soft $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy (sXAS), X-ray photoelectron spectroscopy (XPS), in-situ Raman spectroscopy, and density functional theory (DFT) calculation results suggest that the lattice oxygen activity of NiFe (oxy)hydroxide is effectively modulated by Mo doping, resulting in the shift of reaction pathway and a significantly improved intrinsic OER activity. The approach used in this work can be easily adapted for synthesizing (oxy)hydroxide with controlled oxygen activity for other reactions such as $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generation and biomass conversion in energy and environmental applications. \n\n# Results \n\nSynthesis and characterization of catalysts. Ultrathin NiFe (oxy) hydroxide with Mo doping was synthesized using a sacrificial template-directed synthesis approach, as shown in Fig. 1a. First, $\\mathrm{Mo}\\bar{\\mathsf{S}}_{2}$ nanosheets were grown on carbon cloth substrates by a hydrothermal reaction (Fig. 1b), which were then used as the template to physically adsorb Ni and Fe ions from the solution. After drying the material in air, we obtained a hetero-structured pre-catalyst, which consists of an ultra-thin layer of NiFe layered double hydroxide (LDH) coated on $1\\mathrm{T}$ phase $\\mathbf{MoS}_{2}$ nanosheets (Supplementary Figs. 1, 2). The ratio of Ni and Fe in the LDH can be easily controlled by varying the ion ratio in the solution. The as-synthesized $\\ensuremath{\\mathrm{MoS}}_{2},$ /NiFe LDH pre-catalysts were then subjected to cyclic voltammetry (CV) to remove the $\\mathbf{MoS}_{2}$ sacrificial template through the Mo leaching process. \n\nThe final structure we obtained were ultra-thin $(\\mathrm{Ni_{1-x}F e_{x}})$ (oxy) hydroxides with Mo doping (MoNiFe- $.\\mathbf{x\\%}$ (oxy)hydroxide, $\\mathbf{x}=0\\%$ , $5\\%$ , $27\\%$ , $50\\%$ , $85\\%$ , $100\\%$ ) on the carbon fiber substrates. Fig. 1c–h show the characterization results for a representative MoNiFe- $27\\%$ sample with Ni: $\\mathrm{Fe}=73$ : 27. The scanning electron microscopy (SEM) image (Fig. 1c) shows that the (oxy)hydroxide layer uniformly covers the carbon fiber. The atomic force microscopy (AFM) results of the (oxy)hydroxide flake prepared by ultrasonic treatment suggest that the active catalyst was ultrathin with an atomic thickness of $0.8\\mathrm{nm}$ (mono-layer, denoted as 1 L) or $1.5\\mathrm{nm}$ (double-layer, denoted as 2 L) (Fig. 1d). Using inductively coupled plasma-optical emission spectrometry (ICP-OES), the Ni, Fe, and Mo contents of the obtained catalyst were determined to be 48.7, 19.4, and $0.11\\upmu\\mathrm{g}/\\mathrm{cm}^{2}$ , respectively, indicating a small concentration $(0.1\\%)$ of Mo doping in MoNiFe- $27\\%$ (oxy)hydroxide (Supplementary Fig. 3). The presence of Mo dopant in NiFe (oxy)hydroxide was further confirmed by the aberration-corrected high-angle annular dark-field scanning transmission electron microscope (HAADFSTEM) (Supplementary Fig. 4). Because of the low loading mass of MoNiFe (oxy)hydroxide, we could not determine the crystal structure of MoNiFe- $27\\%$ (oxy)hydroxide using X-ray diffraction measurement (Supplementary Fig. 5). We relied on the transmission electron microscopy (TEM) measurement to confirm the formation of (oxy)hydroxide phase. Figure 1e, f show the TEM images of MoNiFe- $27\\%$ (oxy)hydroxide flakes. The spacing between two adjacent lattice planes is quantified to be $0.2\\mathrm{nm}$ (Fig. 1f), which is assigned to the (105) plane of oxyhydroxide. The selected area electron diffraction (SAED) pattern of the (oxy)hydroxide in Fig. 1g exhibits clear diffraction rings of (101), (110) plane for Ni-based hydroxide (PDF-#14-0117) and (105), (006) plane for Ni-based oxyhydroxide (PDF-#06-0075). The energy dispersive spectroscopy (EDS) mapping revealed the uniform distribution of O, Fe, $\\mathrm{Ni,}$ and Mo elements in MoNiFe (oxy)hydroxide (Fig. 1h). MoNiFe- ${\\bf\\cdot x\\%}$ (oxy)hydroxide samples with other Fe contents exhibited very similar structure characteristics (Supplementary Fig. 6). All the MoNiFe- $.\\mathbf{x}\\%$ exhibited similar Mo content (Supplementary Fig. 7). \n\nOxygen evolution reaction performance evaluation. Having confirmed the successful synthesis of MoNiFe (oxy)hydroxide by using $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets as sacrificial templates and Mo sources, the OER activities of the obtained catalysts were further evaluated. To reveal the role of Mo dopant, pure NiFe (oxy)hydroxides with various Fe contents were synthesized for comparison, which were denoted as NiFe- $.\\mathbf{x}\\%$ $\\mathbf{\\tilde{x}}=0\\%$ , $5\\%$ , $27\\%$ , $50\\%$ , $85\\%$ , $100\\%$ ). \n\nWe systematically evaluated the OER activity of MoNiFe (oxy) hydroxide and NiFe (oxy)hydroxide reference samples using a typical three-electrode configuration in $1.0\\mathrm{M}$ KOH at room temperature. The OER activity of MoNiFe (oxy)hydroxide and NiFe (oxy)hydroxide exhibited similar dependence on the Fe contents. As shown in Supplementary Fig. 8-9, the current density firstly increased with Fe contents, but declined after Fe contents further increased. The optimal Fe content was $27\\%$ for both MoNiFe and NiFe (oxy)hydroxide samples. For the samples with the same Fe content, the MoNiFe (oxy)hydroxide exhibited a noticeable higher OER activity than the NiFe (oxy)hydroxide reference samples. For clarity, we show the cyclic voltammetry (CV) polarization curves for the Ni, MoNi, Fe, MoFe, NiFe- $27\\%$ , and MoNiFe- $27\\%$ (oxy)hydroxides in Fig. 2a. The MoNiFe- $27\\%$ (oxy)hydroxide delivered an overpotential of $242\\mathrm{mV}$ at the current density of $10\\mathrm{mA}/\\mathrm{cm}^{2}$ , which was much lower than the NiFe- $27\\%$ did $(306\\mathrm{mV},$ . To reach a current density of $\\mathrm{100\\mA/}$ $\\mathrm{cm}^{2}$ , the MoNiFe- $27\\%$ (oxy)hydroxide required only $290\\mathrm{mV}$ overpotential. Electrochemical impedance spectra (EIS) and Tafel curves were also measured to evaluate the OER kinetics. The semicircle of EIS curves for the MoNiFe (oxy)hydroxide samples was much smaller than that of NiFe (oxy)hydroxide with the same Fe content (Supplementary Fig. 10), indicating a smaller charge transfer resistance after Mo doping. The Tafel slope for the MoNiFe- $27\\%$ (oxy)hydroxide was 23 mV/dec, which was the smallest among all samples (Fig. 2c), indicating its fastest OER kinetics. \n\n![](images/cde4ec986c80e184e0827ecf260bfccd2ad7bf9c1066a446378131371b001f2e.jpg) \nFig. 1 Preparation and characterizations of the MoNiFe (oxy)hydroxide. a Schematic illustration of the preparation process of the MoNiFe (oxy) hydroxide. Scanning electron microscopy (SEM) images of b the ${M o S}_{2}$ nanosheet template and c MoNiFe (oxy)hydroxide. d Atomic force microscopy (AFM) image of the MoNiFe (oxy)hydroxide flakes. The inset figure is the corresponding line-trace height profile across a MoNiFe (oxy)hydroxide flake. High-resolution transmission electron microscopy (HRTEM) images with e low magnification and f high magnification, g selected area electron diffraction (SAED) pattern and h energy dispersive spectroscopy (EDS) mapping for the MoNiFe (oxy)hydroxide with Ni:Fe ratio of 73: 27. \n\nWe further quantified the mass activity of the electrocatalysts by normalizing the CV curves using loading mass obtained from ICP-OES results (Supplementary Fig. 11). Consistently, the MoNiFe (oxy)hydroxide showed significantly higher mass activity than that for the NiFe (oxy)hydroxide. Particularly, the MoNiFe$27\\%$ (oxy)hydroxide exhibited the highest mass activity among all samples, with a current density of $1910\\mathrm{A/g}$ at the overpotential of $300\\mathrm{\\bar{mV}}$ . Such high mass activity of MoNiFe- $27\\%$ (oxy)hydroxide is about 60 times higher than that of NiFe- $27\\%$ (oxy)hydroxide (Fig. 2b). In addition, MoNiFe- $27\\%$ (oxy)hydroxide also delivered a noticeable lower overpotential and higher mass activity than the benchmark ${\\mathrm{RuO}}_{2}$ and $\\mathrm{IrO}_{2}$ catalysts (Supplementary Fig. 12, note 1). The high mass activity of MoNiFe (oxy)hydroxide is attributed to the following two reasons: first, the ultra-thin nature of the catalyst layer enables the full exposure of active sites and strongly facilitates the charge transfer process between the conductive substrate and the catalyst; secondly, as will be shown in the later section, Mo doping can effectively modulate the lattice oxygen activity of NiFe (oxy)hydroxide, leading to the strongly enhanced intrinsic OER activity. \n\n![](images/4a10ad6a499b8958097abac5b5b7059017ba62a11117d29f342d2297f1f087f5.jpg) \nFig. 2 OER performance of the NiFe and MoNiFe (oxy)hydroxides. a Cyclic voltammetry polarization curves, b mass activities and c Tafel curves of ${\\mathsf{N i}},$ MoNi, Fe, MoFe, NiFe- $27\\%$ , MoNiFe- $27\\%$ (oxy)hydroxide. d Chronopotentiometry curves at the current density of $10\\mathsf{m A}/\\mathsf{c m}^{2}$ for MoNiFe- $27\\%$ (oxy) hydroxide and commercial ${\\sf R u O}_{2}$ . The inset figure is the corresponding cyclic voltammetry polarization curves before and after chronopotentiometry measurement. \n\nThe stability of MoNiFe (oxy)hydroxide was evaluated by chronopotentiometry (CP) tests at the current density of $10\\mathrm{mA}/$ $\\mathrm{cm}^{2}$ . As shown in Fig. 2d, the MoNiFe- $27\\%$ (oxy)hydroxide displayed significantly better stability than the commercial $\\mathrm{RuO}_{2}$ catalyst. The inset figure in Fig. 2d shows the CV curves of MoNiFe (oxy)hydroxide and ${\\mathrm{RuO}}_{2}$ before and after CP measurement. The decline of OER performance for MoNiFe$27\\%$ (oxy)hydroxide was much smaller than that of $\\mathrm{RuO}_{2}$ . The structure and composition of MoNiFe (oxy)hydroxide catalyst remain unchanged after the long-time operation, as revealed by SEM, TEM, EDS, XPS, and ICP-OES characterizations (Supplementary Fig. 13-17, note 2). It is reported that the OER stability of (oxy)hydroxide is strongly dependent on its structural charcteristics28,29. Chen et al.28 reported that the slow diffusion of proton acceptors within interlayer in NiFe hydroxide could lead to a local acidic environment. This can be one primary reason for the performance degradation of multilayer NiFe hydroxide due to the local etching process. The ultra-thin nature of our MoNiFe (oxy)hydroxide can effectively prevent such local etching, and therefore is beneficial for the catalyst to remain stable during operation in alkaline solution. \n\nElucidation of the OER mechanism. To reveal the mechanism of the high intrinsic OER activity of MoNiFe (oxy)hydroxides, isotope-labeling experiments and DFT calculations were carried out on NiFe- $27\\%$ and MoNiFe- $27\\%$ (oxy)hydroxide. For simplicity, the NiFe- $27\\%$ and MoNiFe- $27\\%$ (oxy)hydroxide will be referred to as NiFe and MoNiFe (oxy)hydroxide in the following context. \n\nAs mentioned above, the OER on NiFe-based (oxy)hydroxides was reported to follow the LOM, in which lattice oxygen directly participates in the OER reactions14,30. To validate the participation of lattice oxygen in OER for our material systems, the $\\mathrm{i8_{O}}$ isotope-labeling experiments were carried out using the procedure described in the experimental section. In-situ differential electrochemical mass spectrometry (DEMS) measurements results on the $^{18}\\mathrm{O}$ -labeled NiFe and MoNiFe (oxy)hydroxide showed the signals of $\\mathrm{m}/\\mathrm{z}=32$ , $\\mathrm{m}/\\mathrm{z}=34$ , and $\\dot{\\mathrm{m}}/\\mathrm{z}=36$ (Supplementary Fig. 18), suggesting the presence of $^{16}\\mathrm{O}_{2}$ , $^{16}\\mathrm{O}^{18}\\mathrm{O}$ , and $^{18}\\mathrm{O}_{2}$ in the gas production31–33. This result implies that both NiFe and MoNiFe (oxy)hydroxide follow the LOM mechanism14,30. The mass spectrometric cyclic voltammograms (MSCVs) which plot the real-time gas product contents as a function of applied potential can provide direct comparison about the participation of lattice oxygen in OER process. The $^{18}\\mathrm{O}$ -labeled MoNiFe (oxy)hydroxide is with noticeably higher contents of $^{16}\\mathrm{O}^{18}\\mathrm{O}$ and $\\mathrm{\\dot{1}8}_{\\mathrm{O}_{2}}$ in the reaction product than the $^{18}\\mathrm{O}$ -labeled NiFe (oxy)hydroxide (Fig. 3a–d and Supplementary Fig. 19-20), implying the lattice oxygen of MoNiFe (oxy) hydroxide participated more actively into the OER reaction than that of NiFe (oxy)hydroxide. \n\nIn addition to the DEMS measurement, the quasi in-situ Raman spectra were also used to confirm the participation of lattice oxygen in OER. The samples were first activated in electrolyte with $\\mathrm{^{18}\\mathrm{\\bar{O}}}$ to form $^{18}\\mathrm{O}$ -NiOOH species, and then were subjected to a positive potential ( $\\mathrm{~\\i.65V}$ vs. RHE) in electrolyte with $\\dot{\\mathrm{H}}_{2}^{16}\\mathrm{O}$ . The Raman peaks of the samples activated in electrolyte with $^{18}\\mathrm{O}$ (named as $^{18}\\mathrm{O}$ -labelled sample) shifted to lower wavenumber comparing to that of the samples activated in electrolyte with $^{16}\\mathrm{O}$ (named as $^{16}\\mathrm{O}$ -labelled sample), because of the impact of oxygen mass on the vibration mode2,34(Fig. 3e, f). This result suggests that we successfully labelled both NiFe and MoNiFe samples with $^{18}\\mathrm{O}$ Then, the $^{18}\\mathrm{O}$ -labelled (oxy)hydroxides were placed in electrolyte with $^{16}\\mathrm{O}$ and were treated by applying a positive potential of $1.65\\mathrm{V}$ (vs. RHE) for different periods of time (1 min to $20\\mathrm{min}$ ). The Raman spectra of the obtained samples are shown in Fig. 3e, f. The Raman peak of $^{18}\\mathrm{O}$ -labelled MoNiFe (oxy)hydroxide shifts back to the position for $^{16}\\mathrm{O}$ -labelled MoNiFe (oxy)hydroxide within 1 min of treatment, which is much faster than that for the NiFe (oxy) hydroxide $(20\\mathrm{min})$ . This result suggests that while both samples follow the LOM mechanism, the MoNiFe (oxy)hydroxide exhibits much higher rate of oxygen exchange between lattice oxygen and electrolyte. The Raman spectra and DEMS results on the $^{18}\\mathrm{O}$ -labeled samples consistently suggest that Mo doping in NiFe (oxy)hydroxide effectively promots the lattice oxygen to participate in the OER reaction. \n\n![](images/91f7a796a060bd43e14c165911bcdf24c6f6013f23ebb7174241c1fcd7421389.jpg) \nFig. 3 Evidence of lattice oxygen participating in OER provided by $\\mathfrak{v}_{0}$ isotope-labeling experiments. Mass spectrometric cyclic voltammograms results showing different gaseous products content of OER reaction as a function of applied potential for the $^{18}\\mathrm{O}$ -labeled samples: $^{16}\\mathrm{O}^{18}\\mathrm{O}$ for a NiFe (oxy) hydroxide and b MoNiFe (oxy)hydroxide, $^{18}\\mathrm{O}_{2}$ for c NiFe (oxy)hydroxide and d MoNiFe (oxy)hydroxide. The contents of all the species were normalized by the amount of $^{16}\\mathrm{O}_{2}$ in the reaction products. Quasi in-situ Raman spectra of e $^{18}\\mathrm{O}$ -labelled NiFe and f $^{18}\\mathrm{O}$ -labelled MoNiFe (oxy)hydroxides after being applied a positive potential of 1.65 V (vs. RHE) in $1.0\\mathsf{M}\\mathsf{K}\\mathsf{O}\\mathsf{H}$ with $H_{2}^{\\mathrm{\\ell16}}\\mathrm{O}$ for different time (1 min to $20\\mathsf{m i n}\\dot{}$ ). The Raman spectra of $^{16}\\mathrm{O}$ -labelled samples were shown in black dash lines for comparison. \n\nIn additional to $^{18}\\mathrm{O}$ isotope-labeling experiments, DFT calculations were also carried out to identify the OER mechanism on NiFe and MoNiFe (oxy)hydroxide. Both adsorbate evolution mechanism (AEM) pathway (Supplementary Fig. 21a) and LOM pathway (Fig. 4a) of OER were considered. In the AEM pathway, the Fe sites were found to be the active sites with lower barriers than Ni sites (Supplementary Fig. 21b, c). The deprotonation of $^{*}\\mathrm{OH}$ in AEM pathway serves as the potential determining step (PDS) for both NiFe and MoNiFe (oxy)hydroxide, with a barrier of $1.05\\mathrm{eV}$ and $0.76\\mathrm{eV}$ , respectively. In the LOM pathway, the (oxy)hydroxides first go through the deprotonation process to form oxyhydroxide (step 1) (Fig. 4a). The exposed lattice oxygen then receives $\\mathrm{OH^{-}}$ via nucleophilic attack to form $^{*}\\mathrm{OOH}$ (step 2). After the deprotonation of $^{*}\\mathrm{OOH}$ (step 3), gaseous $\\mathrm{O}_{2}$ releases from the lattice, and an oxygen vacancy is generated on the surface (step 4). The resulting oxygen vacancy sites are refilled by $\\mathrm{OH^{-}}$ and the surface is recovered (step 5). The calculated Gibbs free energy diagrams of OER on NiFe and MoNiFe (oxy) hydroxide are displayed in Fig. 4b. For the NiFe (oxy)hydroxide, the desorption of $\\mathrm{O}_{2}$ , which was accompanied by the formation of oxygen vacancy, was found to be the PDS with a high energy barrier of $0.75\\mathrm{eV}$ . In contrast, the barrier of oxygen vacancy formation became much smaller after Mo doping, which pushed the PDS on MoNiFe (oxy)hydroxide to the deprotonation of $^{*}\\mathrm{OOH}$ with a decreased energy barrier of $0.42\\mathrm{eV}$ . It is noted that both the barriers of PDS for NiFe and MoNiFe (oxy)hydroxide in LOM pathway were much lower than that in AEM pathway, suggesting that both the NiFe and MoNiFe (oxy)hydroxide follow the LOM mechanism14,30. This result is consistent with the results of the $^{18}\\mathrm{O}$ isotope-labeling experiments. The changes in mechanism and PDS derived from Mo doping are quite different from other cation doping reported by previous works35–37. \n\nThe DFT results suggest that Mo doping shifts the PDS from oxygen vacancy formation to the deprotonation of $^{*}\\mathrm{OOH}$ . Such a transition of PDS from the one involving only lattice oxygen to the one involving surface proton transfer might result in enhanced dependence of the OER activity on the proton activity in solution. Therefore, to confirm such a shift of PDS by Mo doping as revealed by calculations, we evaluated the dependence of OER activity of NiFe and MoNiFe(oxy)hydroxide on proton activity by carrying out $\\mathrm{\\pH}$ dependence measurements and deuterium isotopic labeling experiments. \n\nThe OER activities of NiFe and MoNiFe (oxy)hydroxide were assessed at different $\\mathrm{\\tt{pH}}$ conditions $\\mathrm{\\pH}=11.78$ , 12.75, 12.91, and 13.65) (Fig. 4c,d). Fig. 4d shows the OER current density at $1.52\\mathrm{V}$ (vs. RHE) in log scale as a function of $\\mathfrak{p H}$ , from which the proton reaction orders on RHE scale $\\mathrm{\\Delta}\\cdot\\uprho^{\\mathrm{R}\\hat{\\mathrm{HE}}}=\\partial\\mathrm{log}i/\\partial\\mathrm{pH})$ are calculated to be 0.38 and 0.87 for NiFe and MoNiFe (oxy) hydroxide, respectively. The higher $\\uprho^{\\mathrm{RHE}}$ for MoNiFe (oxy) hydroxide implied a stronger pH-dependent OER activity, which might be due to the higher degree of decoupled protonelectron transfer during the PDS step, i.e., the deprotonation of $^{*}\\mathrm{OOH}$ . (Supplementary note 3, Supplementary Fig. 22-23)8,9,38. To further prove the impact of proton activity, the OER activity of NiFe and MoNiFe (oxy)hydroxide were also evaluated in the $\\mathrm{\\DeltaNaOD}$ and NaOH solution. The LSV curves for NiFe and MoNiFe (oxy)hydroxide measured in $1\\mathrm{M\\NaOH}$ (dissolved in $\\mathrm{H}_{2}\\mathrm{O}),$ ) and NaOD (dissolved in $\\mathrm{D}_{2}\\mathrm{O}$ ) solution are shown in Fig. 4e. To show the kinetic isotope effect (KIE) for NiFe and MoNiFe (oxy)hydroxide clearly, the ratio of current density obtained in NaOH and in NaOD at the given potential39,40 is plotted in Fig. 4f. MoNiFe (oxy)hydroxide exhibited a noticeably larger KIE value in comparison to NiFe (oxy)hydroxide, suggesting a severe degradation of OER activity in NaOD. This result suggests that proton transfer has a greater impact on the OER process on MoNiFe (oxy)hydroxide than that on NiFe (oxy)hydroxide. The deuterium isotopic experiments performed in NaOH/NaOD with a different concentration of $0.5{\\mathrm{M}}{}$ provided consistent results (Supplementary Fig. 24). The large isotopic effect of MoNiFe (oxy)hydroxide suggests that the proton transfer is involved in the PDS. This conclusion is in accord with the DFT calculation results, which show that the \n\n![](images/0aafec5849208fbfe2cdd6fb4e2df7161931582ac37856d00c0a906eca93c3c7.jpg) \nFig. 4 OER mechanism revealed by DFT calculation, pH dependence, and deuterium isotopic labeling experiments. a Schematic illustration and b Gibbs free energy diagrams of the LOM pathway on NiFe and MoNiFe (oxy)hydroxide. c Linear sweep voltammetry (LSV) curves for NiFe and MoNiFe (oxy) hydroxide measured in KOH with ${\\mathsf{p H}}=11.78$ , 12.75, 12.91, and 13.65. d OER current density at $1.52\\mathrm{V}$ versus RHE plotted in log scale as a function of pH, from which the proton reaction orders $\\langle\\boldsymbol{\\uprho}^{\\mathsf{R H E}}=\\partial\\mathsf{l o g}i/\\partial\\mathsf{p H}\\rangle$ were calculated. e LSV curves for NiFe and MoNiFe (oxy)hydroxide measured in $1M N a O H$ and ${1\\textsf{M N a O D}}$ solution. The LSV curves are without iR compensation. f The kinetic isotope effect of MoNiFe and NiFe (oxy)hydroxide. $j^{\\mathsf{H}}$ and $j^{\\mathsf{D}}$ are referred to the current density measured in NaOH and NaOD solution, respectively. \n\nPDS step of OER on MoNiFe (oxy)hydroxide is the deprotonation of $^{*}\\mathrm{OOH}$ (Fig. 4b). \n\nAnalysis of lattice oxygen activity. Further insight into the underlying reason for the shift of the reaction pathway was deduced by analyzing the oxygen activity of the NiFe and MoNiFe (oxy)hydroxide based on DFT calculations of electronic structures. \n\nThe oxygen activity can be represented by the metal-oxygen bond strength, which was evaluated by calculating the crystal orbital Hamilton populations (COHP) by DFT (Fig. 5a and Supplementary Fig. 25)26,41. The negative and positive values of -COHP correspond to the anti-bonding (grey area) and bonding state (white area), respectively. The occupied anti-bonding states of Ni and Fe $3d$ band appeared under Fermi level for both NiFe and MoNiFe (oxy)hydroxide (-COHP peak whose energy level is higher than $-2.5\\mathrm{eV}$ , Fig. 5a and Supplementary Fig. 25). Owing to the upshift of the O $2p$ band, MoNiFe (oxy)hydroxide shows a more significant overlap between the O $2p$ band and Ni $3d$ and Fe $3d$ anti-bonding state under Fermi level than NiFe (oxy) hydroxide. To quantify the metal-oxygen bond strength, the integral of -COHP up to the Fermi level $\\mathrm{\\langle-IpCOHP_{Fermi}\\rangle}$ of Ni-O (Fe-O) bonding were determined to be 2.41 (1.78) and 1.19 (1.34) for NiFe and MoNiFe (oxy)hydroxide, respectively (Fig. 5b). The lower value of - $\\mathrm{\\cdotIpCOHP_{Fermi}}$ for the MoNiFe indicates that Mo doping results in more electrons filled into the anti-bonding orbitals, leading to the weaker metal-oxygen bond. Such a weakened metal-oxygen bond can facilitate oxygen vacancy formation. \n\n![](images/b5043e0b2e2f80e8bf069a17dc9cf3ceb3536ec97c050b90357bc6275561e44e.jpg) \nFig. 5 Lattice oxygen activity determined by density functional theory (DFT) calculations. a Crystal orbital Hamilton populations ${\\mathsf{\\ C O H P}})$ of the Ni-O bond in NiFe and MoNiFe (oxy)hydroxide. b The integrated ${\\mathsf{-C O H P}}$ up to Fermi level comparison of Ni-O and Fe-O in NiFe and MoNiFe (oxy)hydroxide. TM refers to transition metal. c Projected density of states of NiFe and MoNiFe (oxy)hydroxide. The anti-bonding states below the Fermi level were highlighted by dash circles. d Schematic band diagrams of NiFe and MoNiFe (oxy)hydroxide. The $d$ -orbitals split into electron-filled lower Hubbard band (LHB) and empty upper Hubbard band (UHB) with an energy difference of U. e The oxygen vacancy formation energy $(E_{f_{-}v a c})$ of NiFe and MoNiFe (oxy)hydroxide. \n\nSecondly, we calculated the O $2p$ band center $(\\mathfrak{E}_{\\mathrm{O}-2p})$ position for both NiFe and MoNiFe (oxy)hydroxide. The density of state (DOS) profile of NiFe and MoNiFe (oxy)hydroxide are shown in Fig. 5c. The O $2p$ band center is determined to be $-1.58\\mathrm{eV}$ and $-\\mathrm{i}.40\\mathrm{eV}$ for NiFe and MoNiFe (oxy)hydroxide, respectively (Fig.5c). The O $2p$ band noticeably shiftes toward the Fermi level after Mo doping into NiFe (oxy)hydroxide. The distance between the O $2p$ band center to the Fermi level has been frequently employed as a descriptor for oxygen activity15,42,43. It is reported that O $2p$ -band center is required to be high enough to guarantee the lattice oxygen to escape from the lattice43. The upshift of the O $2p$ band results in deeper penetration of Fermi level into the O $2p$ band, which further facilitates the electron flow away from oxygen sites when an anodic potential is applied, making the lattice oxygen release from the lattice more easily3,12,43. As a consequence, oxygen with high O $2p$ band position exhibites facilitated oxygen vacancy formation process and thus promotes the LOM mechanism42. \n\nIn addition to the O $2p$ band position, the Mott-Hubbard splitting in $d$ -orbitals was also investigated. For late transition metals, $d$ -orbitals can further split into electron-filled lower Hubbard band (LHB) and empty upper Hubbard band (UHB) due to the strong $d\\ –d$ Coulomb interaction3,14. The LHB/UHB center is determined by the total metal $3d$ -orbital distribution below/above $\\mathrm{E_{Fermi}}$ in DOS diagrams. The specific positions of LHB and UHB were calculated to be $-4.36\\mathrm{eV}$ and $2.01\\mathrm{eV}$ for NiFe (oxy)hydroxide, and $-4.67\\:\\mathrm{eV}$ and $2.90\\mathrm{eV}$ for MoNiFe (oxy)hydroxide, respectively. The energy distance between the LHB and UHB band center $(U)$ is also an important parameter governing the lattice oxygen activity3,14. The $U$ values of NiFe and MoNiFe (oxy)hydroxide were calculated to be $6.38\\mathrm{eV}$ and $7.58\\mathrm{eV}$ , respectively, indicating a stronger $d\\ –d$ Coulomb interaction after Mo doping. Such an enlarged $U$ value gives rise to the downshift of LHB (Fig. 5d). As a result, as anodic potential is applied, the electron removal from oxygen sites is strongly facilitated11,14. It is noted that the LHB center is located beneath the O $2p$ band center. Therefore, the downshift of LHB center and upshift of O $2p$ band center for MoNiFe (oxy)hydroxide leads to a smaller overlap of metal $3d$ -orbital and oxygen $2p$ -orbital, which results in the weaker metal-oxygen bond. In addition, the density of states of metal $3d$ -orbital, especially for $\\mathrm{Ni}\\ 3d$ -orbital, upshift close to Fermi level. Although such upshift lead to an increased overlap between $\\mathrm{Ni}3d.$ -orbital and O $2p$ -orbital in DOS diagrams, the overlap of O $2p\\cdot\\ensuremath{\\mathrm{Ni}}3d$ orbital occurs on the anti-bonding states below Fermi level as highlighted in dash circles in Fig. 5c and results in a weaker Ni-O bond, which is consistent with the COHP calculations (Fig. 5b). \n\nThe weakened metal-oxygen bond, the upshifted O $2p$ band relative to Fermi level, and the enlarged $U$ value in the MoNiFe (oxy)hydroxide in comparison with the NiFe (oxy)hydroxide indicated that Mo doping effectively activated the lattice oxygen, thereby promoting the oxygen vacancy formation process15,42,43. To further confirm such impact of Mo doping, we directly calculated the oxygen vacancy formation energy $(E_{f_{-}\\nu a c})$ using DFT. The $E_{f_{-}\\nu a c}$ of MoNiFe (oxy)hydroxide was determined to be $0.56\\mathrm{eV}$ , which is much lower than the $1.51\\mathrm{eV}$ for the NiFe (oxy) \n\n![](images/1000d87c21e7ffb7d6da1c54d78a5f80e66212632b092c8a0c66928457730946.jpg) \nFig. 6 Lattice oxygen activity determined by advanced spectroscopy techniques. a O K-edge, b Ni L-edge, and c Fe L-edge soft X-ray absorption spectroscopies $({\\mathsf{s}}\\mathsf{X A}{\\mathsf{S}})$ of NiFe and MoNiFe (oxy)hydroxide. The step at the background of O K-edge spectra was normalized to be $1^{46}$ . The background of Ni L-edge and Fe L-edge spectra were subtracted. The raw data and the background of ${\\mathsf{s}}\\mathsf{X A S}$ spectra are shown in Supplementary Fig. 35-37. d Oxidation state of nickel in NiFe and MoNiFe (oxy)hydroxide determined by Ni $2p\\times$ -ray photoelectron spectroscopy (XPS). The inset figure is the Ni 2p XPS spectrum of MoNiFe (oxy)hydroxide. e Redox peaks of Ni in cyclic voltammetry (CV) curves of NiFe and MoNiFe (oxy)hydroxide. f In-situ Raman spectra map of NiFe and MoNiFe (oxy)hydroxide acquired during CV measurement, in which the dash lines mark the required potential for driving the transition from $\\mathsf{N i}^{2+}$ to $N i^{3+}$ . \n\nhydroxide, as shown in Fig. 5e. This result was also confirmed by the higher content of defective oxygen in MoNiFe (oxy)hydroxide by $\\mathrm{~O~l~}s$ XPS anlysis (Supplementary Fig. 26, note 4). Our DFT calculation further shows that the LOM pathway is still dominant for both NiFe and MoNiFe (oxy)hydroxide when there is oxygen vacancy presence on the surface (Supplementary Fig. 27-30, note 5). \n\nThe DFT results above demonstrated that Mo doping in NiFe (oxy)hydroxide effectively enhanced the oxygen activity. In the following section, we further compare the lattice oxygen activity of NiFe and MoNiFe (oxy)hydroxide experimentally by probing the local density of states around the oxygen ligands, the metal oxidation state, and cationic electrochemical redox process using advanced spectroscopy techniques, including synchrotron-based sXAS, XPS, in-situ Raman spectroscopy. \n\nFirst, the variation of the local density of states around the oxygen ligands of NiFe and MoNiFe (oxy)hydroxide was detected by carrying out O K-edge sXAS measurement with total electron yield (TEY) mode. The O K-edge sXAS spectra consist of two characteristic peaks at ${\\sim}533.5\\mathrm{eV}$ and ${\\sim}540\\mathrm{eV}$ , which were assigned to the O $2p$ - metal $3d$ hybridization and the O $2p$ - metal $4s p$ hybridization44,45. As shown in Fig. 6a, the intensity of O K-edge decreases after Mo doping, indicating a decrease in unoccupied density of states46 and a weakening of $3d/4s p-2p$ hybridization44,47. Such decreased intensity in O K-edge spectra, accompanying with the increased intensity of Ni L-edge and Fe L-edge peak for MoNiFe (oxy)hydroxide (Fig. 6b, c), suggests a higher electron density at the O site and a lower electron density at the Ni/Fe sites, a higher ionic metal-oxygen bond46,48. This result is consistent with the weaker metal-oxygen bond after Mo doping, as revealed by the COHP calculation (Fig. 5b). In addition, the increased electron density on oxygen sites in MoNiFe (oxy)hydroxide might promote the donation of electrons from oxygen as an anodic potential was applied. The O K-edge sXAS result suggests that the Mo doping effectively increased the local density of states around the oxygen ligands, which can potentially give rise to the lattice oxygen activation. \n\nThere have been many previous works that demonstrated that the oxygen activity could be probed indirectly by characterizing the metal oxidation state, and a higher oxidation state of the transition metal was normally correlated to an increased oxygen activity7,14,49. For example, Grimaud et al.49 reported that the hybridization of $_{\\mathrm{Co-O}}$ bonds in perovskites cobaltite increased with cobalt oxidation state, which was correlated to the upshift of O $\\boldsymbol{p}$ -band center relative to Fermi level. Mefford et al.7 also showed that the $d$ -orbitals of cobalt have a greater overlap with the $s,p$ orbitals of oxygen as the cobalt oxidation state increased, leading to the promoted lattice oxygen activity of perovskite cobaltite. Zhang et al.14 reported that the formation of $\\mathrm{Ni^{4+}}$ species in Ni-based (oxy)hydroxide can drive holes into oxygen ligands to trigger lattice oxygen activation. In addition, an enlarged $U$ value, a descriptor for enhanced oxygen activity, was reported to be related to the increased valence state of the metal11,50. Inspired by these pioneering works, we compared the change of oxidation states of Ni and Fe in (oxy)hydroxide after Mo doping. \n\nThe Ni L-edge sXAS spectra of NiFe and MoNiFe (oxy) hydroxide are shown in Fig. 6b. The MoNiFe (oxy)hydroxide exhibited higher intensity than that of NiFe (oxy)hydroxide. In addition to intensity changes, the Ni L-edge spectra of MoNiFe (oxy)hydroxide shifted to higher photon energy relative to NiFe (oxy)hydroxide (Supplementary Fig. 31). Both the higher intensity and positive shift of Ni L-edge peak for MoNiFe (oxy) hydroxide than NiFe (oxy)hydroxide suggest an increased number of unoccupied density of states on Ni sites51,52. Similarly, the Fe L-edge spectra of MoNiFe (oxy)hydroxide exhibited higher intensity than that of the NiFe (oxy)hydroxide, indicating an increased unoccupied density of states on Fe sites (Fig. 6c). The changes in Ni/Fe L-edge spectra derived from the partial electron transfer from Ni/Fe sites to the Mo sites through bridging oxygen $(\\upmu\\mathrm{-}\\mathrm{O})$ in Ni-O-Mo-O-Fe moiety in MoNiFe (oxy)hydroxide (Supplementary Fig. 32, note $\\dot{6})^{36}$ , leading to the electron depletion in metal sites and the increment of metal oxidation state. In addition to the sXAS results, the XPS analysis (Fig. 6d, Supplementary Fig. 33-34) provided the same conclusion of higher metal oxidation state in the MoNiFe (oxy)hydroxide with detailed discussion in Supplementary note 7. \n\nAs mentioned above, the upshifted O $2p$ band and enlarged $U$ value in MoNiFe (oxy)hydroxide would promote the lattice oxygen redox chemistry as an anodic potential is applied. Because of the competition of electron donation from oxygen anion and metal cations redox process, the enhanced oxygen reactivity should be reflected on the delayed cationic electrochemical redox process (Supplementary Fig. 38, note 8)3. As shown in Fig. 6e, the $\\mathrm{\\hat{N}i^{2+}}/\\mathrm{Ni^{3+}}$ redox peak for MoNiFe (oxy)hydroxide ( $\\cdot450\\mathrm{V}$ vs. RHE) shifted positively compared to that of NiFe (oxy)hydroxide 1 $\\mathrm{.414V}$ vs. RHE), indicating that Ni in (oxy)hydroxide required higher positive potential to oxidize after Mo doping. We further carried out in-situ Raman spectroscopy to confirm such a change of $\\mathrm{Ni}^{2+}/\\mathrm{Ni}^{3+}$ electrochemical redox during OER process (Fig. 6f). Two characteristic peaks of $\\mathrm{Ni}^{3+}$ -O were found on the Raman spectra at 476 and $557\\mathrm{cm}^{-1}$ when a sufficiently high positive potential was applied. These two peaks corresponded to the $E_{\\mathrm{g}}$ bending vibration $\\left(\\delta(\\mathrm{Ni-O})\\right)$ and $A_{\\mathrm{{lg}}}$ stretching vibration $\\left(\\nu(\\mathrm{Ni\\mathrm{-}}\\right)$ O)) mode in $\\gamma{\\mathrm{-NiOOH}}$ , respectively2. The emergence of the Raman peaks of $\\mathrm{Ni}^{3+}$ -O occurred at $0.44\\mathrm{V}$ and $0.{\\dot{4}}8\\mathrm{V}$ (vs. $\\mathrm{Hg/}$ $\\mathrm{HgO)}$ for NiFe and MoNiFe (oxy)hydroxide, respectively. These results suggest that the nickel redox process gets delayed after Mo doping due to the facilitated lattice oxygen oxidation, which is consistent with DFT calculation results. \n\nAll the DFT calculations and experimental results above consistently suggest that the lattice oxygen activity was strongly enhanced by Mo doping, leading to the facilitated oxygen vacancies formation. Consistently, we observed the reaction barrier of oxygen vacancy formation for the MoNiFe (oxy) hydroxide to be much smaller than that for the NiFe (oxy) hydroxide (Fig. 4b). Consequently, the PDS transforms from oxygen vacancy formation for the NiFe (oxy)hydroxide to the $^{*}{\\mathrm{OOH}}$ deprotonation for the MoNiFe (oxy)hydroxide. These results provide critical insight into the role of lattice oxygen in determining the electrocatalytic activity of transition metal (oxy) hydroxide. \n\nOverall water splitting performance. To demonstrate the practical application of MoNiFe (oxy)hydroxide for electrochemical production of hydrogen, a two-electrode electrolytic cell was constructed using ${\\mathrm{MoS}}_{2}/{\\mathrm{NiFe}}$ LDH pre-catalyst as both anode and cathode for overall water splitting. During the water splitting process, the anode was transformed from the $\\ensuremath{\\mathrm{MoS}}_{2}$ /NiFe LDH pre-catalyst into MoNiFe (oxy)hydroxide, while the $\\mathrm{MoS}_{2}.$ /NiFe LDH cathode remained unchanged (Supplementary Fig. 39). The final cell structure was denoted as $\\mathrm{MoS}_{2}/$ NiFe LDH | MoNiFe in the following context. A reference cell with commercial noblemetal-based catalysts $\\mathrm{Pt/C}$ and ${\\mathrm{RuO}}_{2}$ as cathode and anode, respectively, was also tested for comparison (denoted as $\\mathrm{Pt/C}|$ $\\mathrm{RuO}_{2}^{\\cdot}$ ). The polarization curves of the cell with ${\\bf M o S}_{2}/{\\bf N i F e}$ $\\mathrm{LDH}|$ MoNiFe coupled electrodes and the reference cell with $\\mathrm{Pt}/\\$ $\\mathbf{C}\\left|\\mathrm{RuO}_{2}\\right.$ coupled electrodes for overall water splitting in $1\\mathrm{M}$ KOH electrolyte were shown in Fig. 7a. The electrolytic cell with ${\\mathrm{MoS}}_{2}/{\\mathrm{NiFe}}$ LDH | MoNiFe coupled electrodes presented higher overpotential at low current density than the cell with $\\mathrm{Pt/C}|$ ${\\mathrm{RuO}}_{2}$ coupled electrodes. Nevertheless, the cell with $\\mathrm{MoS}_{2}/\\mathrm{NiFe}$ LDH | MoNiFe coupled electrodes exhibited a noticeable better performance at high current density. To reach a current density of $100\\mathrm{mA}/\\mathrm{cm}^{2}$ , the cell with $\\mathrm{MoS}_{2}/\\mathrm{NiFe\\LDH}\\mid$ MoNiFe coupled electrodes only required a voltage of $1.728\\mathrm{V}$ , which was significantly lower than the reference cell with $\\mathrm{Pt/C}|\\mathrm{RuO}_{2}$ coupled electrodes $(1.755\\mathrm{V})$ . \n\nTo achieve sufficient hydrogen production rate, the electrolytic cell needs to operate at a high current density. Therefore, the stability of the electrolytic cell was evaluated at a current density of $10\\mathrm{\\mA}/\\mathrm{cm}^{2}$ and $10\\dot{0}\\mathrm{mA}/\\mathrm{cm}^{2}$ . At a current density of $10\\mathrm{mA}/$ $\\mathrm{cm}^{2}$ , both the cell with $\\mathbf{MoS}_{2}$ /NiFe LDH | MoNiFe coupled electrodes and the one with $\\mathrm{Pt/C}\\mid\\mathrm{RuO}_{2}$ coupled electrodes displayed excellent stability (Supplementary Fig. 40). At a current density of $100\\mathrm{mA}/\\mathrm{cm}^{2}$ , the cell with $\\mathrm{MoS}_{2}/\\mathrm{NiFe\\LDH}|$ MoNiFe coupled electrodes remained stable during operation, while the cell with $\\mathrm{Pt/C}\\mid\\mathrm{RuO}_{2}$ coupled electrodes degraded rapidly (Fig. 7b). \n\nFinally, we compared the cell voltage for $\\mathrm{MoS}_{2}/\\mathrm{NiFe}$ LDH | MoNiFe at a high current density of $100\\mathrm{mA}/\\mathrm{cm}^{2}$ with recently reported noble-metal-free electrocatalysts for overall water splitting (Fig. 7c, Supplementary Table 1). As shown in Fig. 7c, our cell performance at high current density ( $\\mathrm{1.728V}$ at $\\mathrm{100\\mA/}$ $\\mathsf{c m}^{2}$ ) is competitive among the noble-metal-free electrocatalysts reported in the literature. \n\n# Discussion \n\nIn this work, a sacrificial template-directed approach was reported to synthesize ultra-thin NiFe-based (oxy)hydroxide with Mo doping as highly efficient and stable OER catalysts. $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets grown by hydrothermal approach were used as templates to adsorb metal cations to form self-assembly NiFe (oxy) hydroxide and served as Mo sources for doping. The obtained MoNiFe (oxy)hydroxide exhibited a high mass activity of $1910\\mathrm{A}/$ $\\mathrm{g}_{\\mathrm{metal}}$ at the overpotential of $300\\mathrm{mV}$ , which is 60 times higher than that of the NiFe (oxy)hydroxide. The electrolytic cell with ${\\bf M o S}_{2}/{\\bf N i F e}$ LDH | MoNiFe coupled electrodes exhibited good activity and stability for the overall water splitting, which required a low voltage of $1.728\\mathrm{V}$ to achieve a current density of $\\mathrm{100mA/}$ $\\mathrm{cm}^{2}$ . DFT calculation suggested that MoNiFe (oxy)hydroxide exhibited higher lattice oxygen activity, which was represented by the weakened metal-oxygen bond, upshifted O $2p$ center relative to Fermi level, enlarged $U$ values, and lower oxygen vacancy formation energy. Consistently, synchrotron-based sXAS, XPS, and in-situ Raman measurements demonstrated that the MoNiFe (oxy)hydroxide was with higher local density of states around the oxygen ligands, a higher metal oxidation state, and a delayed cationic electrochemical redox process in comparison with the NiFe (oxy)hydroxide. Such activation of lattice oxygen shifted the potential determining step from oxygen vacancy formation for the NiFe (oxy)hydroxide to the $^{*}\\mathrm{OOH}$ deprotonation for the MoNiFe (oxy)hydroxide, resulting in strongly enhanced intrinsic OER activity. The methodology used in this work can be easily adapted for constructing other transition metal (oxy)hydroxide with modulated oxygen activity for catalyzing other reactions such as biomass electrooxidation reactions. The mechanistic understanding of the role of lattice oxygen in determining surface reactions can guide the rational design of high-performance photo-, thermal-, or electro-catalysts. \n\n![](images/3dabfe22293810e9611497da3f41fc3c4f15e1fe7cc55213979e0bafd8b71dd7.jpg) \nFig. 7 The overall water splitting performance. a Polarization curves of the electrolytic cell with $M O S_{2},$ /NiFe LDH | MoNiFe coupled electrodes and the reference cell with Pt/C | ${\\sf R u O}_{2}$ coupled electrodes for overall water splitting. b Chronopotentiometry curves at the current density of $100\\mathsf{m A}/\\mathsf{c m}^{2}$ of the electrolytic cell with $M O S_{2},$ /NiFe LDH | MoNiFe coupled electrodes and the reference cell with Pt/C $|\\mathsf{R u O}_{2}$ coupled electrodes. c The comparison of overall water splitting performance at the current density of $100\\mathsf{m A}/\\mathsf{c m}^{2}$ for $M\\circ\\mathsf{S}_{2},$ /NiFe LDH | MoNiFe and other noble-metal-free electrocatalysts in recently reported literature, such as MnCo-CH@NiFe-OH $(1.69\\lor)^{61}$ , NiFe-LDH/Ni $(\\mathsf{O H})_{2}$ $(1.81\\lor)^{62}$ , NiCoFe-O@NF $(1.7\\lor)^{63}$ , $\\mathsf{N i P}_{2}/\\mathsf{N i S e}_{2}(1.8\\mathsf{V})^{64}$ , Ni2P-Fe2P/NF $(1.68\\lor)^{65}.$ , NiFeP-CNT@NiCo/CP (1.92 V)66, FeCo/Co2P@NPCF $(1.98\\lor)^{67}$ , Co-NC/CP $(1.86\\lor)^{68}$ and CoP NFs $(1.92\\lor)^{69}$ . \n\n# Methods \n\nSynthesis of MoNiFe (oxy)hydroxide. $\\mathbf{MoS}_{2}$ nanosheets were grown on carbon cloths by a hydrothermal method with ammonium molybdate tetrahydrate $[(\\mathrm{NH_{4}})_{6}\\mathrm{Mo}_{7}\\mathrm{O}_{24}{\\cdot}4\\mathrm{H}_{2}\\mathrm{O}]$ and thiourea $\\mathrm{(CH_{4}N_{2}S)}$ as the precursors. The obtained $\\ensuremath{\\mathrm{MoS}}_{2}$ nanosheets were immersed into a mixed solution of nickel acetate and ferrous sulfate to adsorb Fe and Ni ions onto the surface. After drying in air, the $\\ensuremath{\\mathrm{MoS}}_{2}/\\ensuremath{\\mathrm{\\Omega}}$ /NiFe LDH pre-catalysts were constructed. The $\\ensuremath{\\mathrm{MoS}}_{2},$ NiFe LDH pre-catalysts were subjected to cyclic voltammetry activation in 1 M KOH solution to obtain self-reconstruction Mo doping NiFe (oxy)hydroxide through Mo leaching. The NiFe (oxy)hydroxide reference sample was synthesized by a commonly used wetchemical method. Further detailed information about NiFe and MoNiFe (oxy) hydroxides synthesis can be found in Supplementary note 9, 10. \n\nCharacterizations. The morphologies of samples were characterized by highresolution field emission scanning electron microscopy (SEM) (SU8010, Hitachi, Japan). The chemical composition was detected by inductively coupled plasmaoptical emission spectrometry (ICP-OES) (Agilent 730 series) and X-ray photoelectron spectroscopy (XPS) (Escalab250Xi, Thermo Scientific) with Al anode. High-resolution transmission electron microscopy (HRTEM) images and energy dispersive spectroscopy (EDS) were recorded by a JEM-3200FS microscope. In-situ Raman measurements were performed on a confocal microscopic system (LabRAM HR Evolution, Horiba, France) equipped with a semiconductor laser $(\\lambda=532\\mathrm{nm}$ , Laser Quantum Ltd.). The laser was focused using a $50\\times$ objective lens and 600 lines $\\mathrm{{'mm}}$ grating. The Raman spectra were collected continuously with a step of $2\\mathrm{mV}$ during linear sweep voltammetry measurement with a scanning rate of $0.1\\mathrm{mV}/\\mathrm{s}$ . Synchrotron-based soft X-ray absorption spectroscopy (sXAS) was carried out at the BL02B02 station in Shanghai Synchrotron Radiation Facility53. \n\nElectrochemical measurements. The electrochemical measurements were performed in a three-electrode system using a CHI-660E electrochemical station. 1 M KOH aqueous solution was used as the electrolyte, and it was bubbled by $\\mathrm{O}_{2}$ for $30\\mathrm{min}$ prior to OER measurements. The catalyst-loaded carbon cloths acted as the working electrode. The reference electrode and counter electrode were a $\\mathrm{\\Ag/AgCl}$ electrode prefilled with saturated KCl aqueous solution and a Pt mesh, respectively. All electrode potentials were given versus the reversible hydrogen electrode (vs. RHE) unless otherwise mentioned. The detailed information about the electrochemical measurements can be found in Supplementary note 11. \n\n$\\mathfrak{v}_{0}$ -labeling experiment. NiFe and MoNiFe (oxy)hydroxides were labeled with $^{18}\\mathrm{O}$ -isotopes by potentiostatic reaction at $1.65\\mathrm{V}$ (vs. $\\mathrm{\\Ag/AgCl})$ for $30\\mathrm{min}$ in KOH solution with $\\mathrm{\\dot{H}}_{2}{}^{18}\\mathrm{O}$ . Afterward, the $^{18}\\mathrm{O}$ -labeled catalysts were rinsed with $\\mathrm{H}_{2}^{\\mathbf{\\alpha}16}\\mathrm{O}$ for serval times to remove the remaining $\\mathrm{H}_{2}^{\\mathrm{~18}}\\mathrm{O}$ . \n\nDEMS measurements. DEMS measurements were carried out using a QAS 100 device (Linglu Instruments, Shanghai). The NiFe or MoNiFe (oxy)hydroxide with $^{18}\\mathrm{O}$ -labeling, a $\\mathrm{Ag/AgCl}$ electrode prefilled with saturated KCl aqueous solution, and a Pt mesh were used as working electrode, reference electrode, and counter electrode, respectively. CV measurement was performed in KOH solution with $\\mathrm{H}_{2}^{\\mathbf{\\alpha}16}\\mathrm{O}$ with a scan rate of $5\\mathrm{mV/s}$ . In the meantime, gas products with different molecular weights were detected in real time by mass spectroscopy. \n\nTheoretical calculation. Spin-polarized DFT calculations were performed using the Vienna ab initio simulation package (VASP)54. The generalized gradient approximation (GGA) of the Perdue-Burke-Ernzerhof (PBE) version55 was used to describe the exchange-correlation interactions. The projector-augmented wave (PAW) method is used to model core-valence electron interactions56. The COHP of considered atomic pairs was calculated by the Lobster code57–60. The detailed information about the DFT calculation can be found in Supplementary note 12. \n\n# Data availability \n\nThe data that support the findings of this study are available from https://figshare.com/s/ 489adcc0875ef42536c8. Source data are provided with this paper. \n\nReceived: 12 September 2021; Accepted: 4 April 2022; Published online: 21 April 2022 \n\n# References \n\n1. Zhao, T. et al. In situ reconstruction of V-doped ${\\mathrm{Ni}}_{2}{\\mathrm{P}}$ pre-catalysts with tunable electronic structures for water oxidation. Adv. Funct. Mater. 31, 2100614 (2021). \n2. Lee, S., Bai, L. & Hu, X. Deciphering iron-dependent activity in oxygen evolution catalyzed by nickel-iron layered double hydroxide. Angew. Chem. Int. Ed. Engl. 59, 8072–8077 (2020). \n3. Zhang, N., Chai, Y. Lattice oxygen redox chemistry in solid-state electrocatalysts for water oxidation. Energy Environ. Sci. 14, 4647–4671 (2021). \n4. Kuznetsov, D. A. et al. Tailoring lattice oxygen binding in ruthenium pyrochlores to enhance oxygen evolution activity. J. Am. Chem. Soc. 142, 7883–7888 (2020). \n5. Zhu, Y. et al. Boosting oxygen evolution reaction by creating both metal ion and lattice-oxygen active sites in a complex oxide. Adv. Mater. 32, 1905025 (2020). \n6. Grimaud, A. et al. Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution. Nat. Chem. 9, 457–465 (2017). \n7. Mefford, J. T. et al. Water electrolysis on $\\mathrm{La}_{1-\\mathrm{x}}\\mathrm{Sr}_{\\mathrm{x}}\\mathrm{CoO}_{3-\\delta}$ perovskite electrocatalysts. Nat. Commun. 7, 11053 (2016). \n8. Pan, Y. et al. Direct evidence of boosted oxygen evolution over perovskite by enhanced lattice oxygen participation. Nat. Commun. 11, 2002 (2020). \n9. Zhu, Y. et al. Oxygen defect engineering in double perovskite oxides for effective water oxidation. J. Mater. Chem. A 8, 10957–10965 (2020). \n10. She, S. et al. Realizing ultrafast oxygen evolution by introducing proton acceptor into perovskites. Adv. Energy Mater. 9, 1900429 (2019). \n11. Huang, Z.-F. et al. Chemical and structural origin of lattice oxygen oxidation in Co-Zn oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). with self-termination of surface reconstruction for water oxidation. Nat. Catal. 2, 763–772 (2019). \n13. Huang, Z.-F. et al. Tuning of lattice oxygen reactivity and scaling relation to construct better oxygen evolution electrocatalyst. Nat. Commun. 12, 3992 (2021). \n14. Zhang, N. et al. Lattice oxygen activation enabled by high-valence metal sites for enhanced water oxidation. Nat. Commun. 11, 4066 (2020). \n15. Hwang, J. et al. Regulating oxygen activity of perovskites to promote $\\mathrm{NO}_{\\mathrm{x}}$ oxidation and reduction kinetics. Nat. Catal. 4, 663–673 (2021). \n16. Chen, H., et al. Activating lattice oxygen in perovskite oxide by B site cation doping for modulated stability and activity at elevated temperatures. Adv. Sci. 8, 2102713 (2021). \n17. Xu, Z. J. Transition metal oxides for water oxidation: All about oxyhydroxides? Sci. China Mater. 63, 3–7 (2019). \n18. Jin, S. Are metal chalcogenides, nitrides, and phosphides oxygen evolution catalysts or bifunctional catalysts? ACS Energy Lett. 2, 1937–1938 (2017). \n19. Liu, J. & Guo, L. In situ self-reconstruction inducing amorphous species: A key to electrocatalysis. Matter 4, 2850–2873 (2021). \n20. Liu, X. et al. Comprehensive understandings into complete reconstruction of precatalysts: synthesis, applications, and characterizations. Adv. Mater. 33, 2007344 (2021). \n21. Wang, Y. et al. Anion etching for accessing rapid and deep self-reconstruction of precatalysts for water oxidation. Matter 3, 2124–2137 (2020). \n22. Wang, J. et al. Redirecting dynamic surface restructuring of a layered transition metal oxide catalyst for superior water oxidation. Nat. Catal. 4, 212–222 (2021). \n23. Lopes, P. P. et al. Dynamically stable active sites from surface evolution of perovskite materials during the oxygen evolution reaction. J. Am. Chem. Soc. 143, 2741–2750 (2021). \n24. Chen, P. et al. Metallic $\\mathrm{Co_{4}N}$ porous nanowire arrays activated by surface oxidation as electrocatalysts for the oxygen evolution reaction. Angew. Chem. Int. Ed. Engl. 127, 14923–14927 (2015). \n25. Stern, L.-A., Feng, L., Song, F. & Hu, X. ${\\mathrm{Ni}}_{2}{\\mathrm{P}}$ as a Janus catalyst for water splitting: the oxygen evolution activity of ${\\mathrm{Ni}}_{2}{\\mathrm{P}}$ nanoparticles. Energy Environ. Sci. 8, 2347–2351 (2015). \n26. Zhao, S. et al. Structural transformation of highly active metal-organic framework electrocatalysts during the oxygen evolution reaction. Nat. Energy 5, 881–890 (2020). \n27. Jiang, H. et al. Tracking structural self-reconstruction and identifying true active sites toward cobalt oxychloride precatalyst of oxygen evolution reaction. Adv. Mater. 31, 1805127 (2019). \n28. Chen, R. et al. Layered structure causes bulk NiFe layered double hydroxide unstable in alkaline oxygen evolution reaction. Adv. Mater. 31, 1903909 (2019). \n29. Tripkovic, V., Hansen, H. A. & Vegge, T. From 3D to 2D Co and Ni oxyhydroxide catalysts: Elucidation of the active site and influence of doping on the oxygen evolution activity. ACS Catal. 7, 8558–8571 (2017). \n30. Ferreira de Araujo, J., Dionigi, F., Merzdorf, T., Oh, H. S. & Strasser, P. Evidence of Mars-Van-Krevelen mechanism in the electrochemical oxygen evolution on Ni-based catalysts. Angew. Chem. Int. Ed. Engl. 60, 14981–14988 (2021). \n31. Roy, C. et al. Impact of nanoparticle size and lattice oxygen on water oxidation on $\\mathrm{NiFeO_{x}H_{y}}$ . Nat. Catal. 1, 820–829 (2018). \n32. Wen, Y. et al. Stabilizing highly active Ru sites by suppressing lattice oxygen participation in acidic water oxidation. J. Am. Chem. Soc. 143, 6482–6490 (2021). \n33. Shi, Z. et al. Confined Ir single sites with triggered lattice oxygen redox: Toward boosted and sustained water oxidation catalysis. Joule 5, 2164–2176 (2021). \n34. Lee, S., Banjac, K., Lingenfelder, M. & Hu, X. Oxygen Isotope Labeling Experiments Reveal Different Reaction Sites for the Oxygen Evolution Reaction on Nickel and Nickel Iron Oxides. Angew. Chem. Int. Ed. Engl. 58, 10295–10299 (2019). \n35. Baker, J. G. et al. The role of aluminum in promoting Ni-Fe-OOH electrocatalysts for the oxygen evolution reaction. ACS Appl. Energy Mater. 2, 3488–3499 (2019). \n36. Jiang, J. et al. Atomic-level insight into super-efficient electrocatalytic oxygen evolution on iron and vanadium co-doped nickel (oxy)hydroxide. Nat. Commun. 9, 2885 (2018). \n37. Li, P. et al. Tuning electronic structure of NiFe layered double hydroxides with vanadium doping toward high efficient electrocatalytic water oxidation. Adv. Energy Mater. 8, 1703341 (2018). \n38. Zhu, Y. et al. Tuning proton-coupled electron transfer by crystal orientation for efficient water oxidization on double perovskite oxides. Nat. Commun. 11, 4299 (2020). \n39. Bai, L., Lee, S. & Hu, X. Spectroscopic and electrokinetic evidence for a bifunctional mechanism of the oxygen evolution reaction. Angew. Chem. Int. Ed. Engl. 60, 3095–3103 (2021). \n40. Tse, E. C. M., Hoang, T. T. H., Varnell, J. A. & Gewirth, A. A. Observation of an inverse kinetic isotope effect in oxygen evolution electrochemistry. ACS Catal. 6, 5706–5714 (2016). \n41. Liu, X., Jiao, Y., Zheng, Y., Jaroniec, M. & Qiao, S.-Z. Building up a picture of the electrocatalytic nitrogen reduction activity of transition metal single-atom catalysts. J. Am. Chem. Soc. 141, 9664–9672 (2019). \n42. Lee, Y.-L., Kleis, J., Rossmeisl, J., Shao-Horn, Y. & Morgan, D. Prediction of solid oxide fuel cell cathode activity with first-principles descriptors. Energy Environ. Sci. 4, 3966–3970 (2011). \n43. Sun, Y. et al. Covalency competition dominates the water oxidation structureactivity relationship on spinel oxides. Nat. Catal. 3, 554–563 (2020). \n44. Yang, J. et al. Surface-confined fabrication of ultrathin nickel cobalt-layered double hydroxide nanosheets for high-performance supercapacitors. Adv. Funct. Mater. 28, 1803272 (2018). \n45. Rojas, T. C. et al. Preparation, characterization and thermal evolution of oxygen passivated nanocrystalline cobalt. J. Mater. Chem. 9, 1011–1017 (1999). \n46. Liang, Y. et al. $\\mathrm{Co}_{3}\\mathrm{O}_{4}$ nanocrystals on graphene as a synergistic catalyst for oxygen reduction reaction. Nat. Mater. 10, 780–786 (2011). \n47. Kwon, J.-H. et al. Nanoscale spin-state ordering in $\\mathrm{LaCoO}_{3}$ epitaxial thin films. Chem. Mater. 26, 2496–2501 (2014). \n48. Zhou, J. G. et al. Electronic structure of $\\mathrm{TiO}_{2}$ nanotube arrays from X-ray absorption near edge structure studies. J. Mater. Chem. 19, 6804 (2009). \n49. Grimaud, A. et al. Double perovskites as a family of highly active catalysts for oxygen evolution in alkaline solution. Nat. Commun. 4, 2439 (2013). \n50. Zaanen, J., Sawatzky, G. A. & Allen, J. W. Band gaps and electronic structure of transition-metal compounds. Phys. Rev. Lett. 55, 418–421 (1985). \n51. Wang, D. et al. In situ X-ray absorption near-edge structure study of advanced $\\mathrm{NiFe(OH)_{x}}$ electrocatalyst on carbon paper for water oxidation. J. Phys. Chem. C. 119, 19573–19583 (2015). \n52. Al Samarai, M. et al. Elucidation of structure-activity correlations in a nickel manganese oxide oxygen evolution reaction catalyst by operando Ni L-edge Xray absorption spectroscopy and 2p3d resonant inelastic X-ray scattering. ACS Appl. Mater. Interfaces 11, 38595–38605 (2019). \n53. Ren, G. et al. Photon-in/photon-out endstation for studies of energy materials at beamline 02B02 of Shanghai Synchrotron Radiation Facility. Chin. Phys. B \n29, 016101 (2020). \n54. Kresse, G. & Furthmuller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. \n6, 15–50 (1996). \n55. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n56. Blochl, P. E. Projector augmented-wave method. Phys. Rev. B Condens. Matter \n50, 17953–17979 (1994). \n57. Dronskowski, R. & Blochl, P. E. Crystal orbital Hamilton populations (COHP). Energy-resolved visualization of chemical bonding in solids based on density-functional calculations. J. Phys. Chem. 97, 8617–8624 (1993). \n58. Maintz, S., Deringer, V. L., Tchougreeff, A. L. & Dronskowski, R. Analytic projection from plane-wave and PAW wavefunctions and application to chemical-bonding analysis in solids. J. Comput. Chem. 34, 2557–2567 (2013). \n59. Maintz, S., Deringer, V. L., Tchougreeff, A. L. & Dronskowski, R. LOBSTER: A tool to extract chemical bonding from plane-wave based DFT. J. Comput. Chem. 37, 1030–1035 (2016). \n60. Deringer, V. L., Tchougreeff, A. L. & Dronskowski, R. Crystal orbital Hamilton population (COHP) analysis as projected from plane-wave basis sets. J. Phys. Chem. A 115, 5461–5466 (2011). \n61. Zeng, Y. et al. Construction of hydroxide pn junction for water splitting electrocatalysis. Appl. Catal. B 292, 120160 (2021). \n62. Gultom, N. S., Abdullah, H., Hsu, C.-N. & Kuo, D.-H. Activating nickel iron layer double hydroxide for alkaline hydrogen evolution reaction and overall water splitting by electrodepositing nickel hydroxide. Chem. Eng. J. 419, \n129608 (2021). \n63. Wang, Z. et al. Contemporaneous inverse manipulation of the valence configuration to preferred ${\\mathrm{Co}}^{2+}$ and $\\mathrm{Ni}^{3+}$ for enhanced overall water electrocatalysis. Appl. Catal. B 284, 119725 (2021). \n64. Yang, L., Huang, L., Yao, Y. & Jiao, L. In-situ construction of lattice-matching $\\mathrm{NiP}_{2}/\\mathrm{NiSe}_{2}$ heterointerfaces with electron redistribution for boosting overall water splitting. Appl. Catal. B 282, 119584 (2021). \n65. Wu, L. et al. Heterogeneous bimetallic phosphide ${\\mathrm{Ni}}_{2}{\\mathrm{P}}{\\mathrm{-Fe}}_{2}{\\mathrm{P}}$ as an efficient bifunctional catalyst for water/seawater splitting. Adv. Funct. Mater. 31, 2006484 (2020). \n66. Wang, Z. et al. A hierarchical carbon nanotube forest supported metal phosphide electrode for efficient overall water splitting. J. Mater. Chem. A 9, 1150–1158 (2021). \n67. Shi, Q. et al. High‐performance trifunctional electrocatalysts based on FeCo/ $\\mathrm{Co}_{2}\\mathrm{P}$ hybrid nanoparticles for zinc-air battery and self‐powered overall water splitting. Adv. Energy Mater. 10, 1903854 (2020). \n68. Huang, H. et al. Rapid and energy-efficient microwave pyrolysis for high-yield production of highly-active bifunctional electrocatalysts for water splitting. Energy Environ. Sci. 13, 545–553 (2020). \n69. Zhu, Y. et al. Anionic defect engineering of transition metal oxides for oxygen reduction and evolution reactions. J. Mater. Chem. A 7, 5875–5897 (2019). \n\n# Acknowledgements \n\nThis work was supported by the National Natural Science Foundation of China (11975102, Y.C.); the State Key Laboratory of Pulp and Paper Engineering (2020C01, Y.C.); the Guangdong Pearl River Talent Program (2017GC010281, Y.C.). The synchrotron experiments were carried out at Beamline 02B of the Shanghai Synchrotron Radiation Facility, which is supported by ME2 project under contract from the National Natural Science Foundation of China (11227902, N.Z.). S. Zhao acknowledges the support from the City University of Hong Kong (No. 9610425, S.Z.). The computational time provided by the Shanghai Supercomputer Center and the CityU Burgundy Supercomputer is highly acknowledged. \n\n# Author contributions \n\nZ.H. and Y.C. conducted the experiments and analyzed the results. J.Z. and S.Z. are responsible for the DFT calculations. Z.H., Z.G., D.Z., N.Z., and Y.C. are responsible for the testing and analysis of XAS. Z.H., H.L., W.M., and Y.C. are responsible for the in-situ Raman measurement and analysis. Z.H., J.Z., S.Z., and Y.C. planned and designed the project and wrote the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-29875-4. \n\nCorrespondence and requests for materials should be addressed to Shijun Zhao or Yan Chen. \n\nPeer review information Nature Communications thanks Tejs Vegge and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. " + }, + { + "id": "10.1038_s41586-021-04223-6", + "DOI": "10.1038/s41586-021-04223-6", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-04223-6", + "Relative Dir Path": "mds/10.1038_s41586-021-04223-6", + "Article Title": "Deep physical neural networks trained with backpropagation", + "Authors": "Wright, LG; Onodera, T; Stein, MM; Wang, TY; Schachter, DT; Hu, Z; McMahon, PL", + "Source Title": "NATURE", + "Abstract": "Deep-learning models have become pervasive tools in science and engineering. However, their energy requirements now increasingly limit their scalability(1). Deep-learning accelerators(2-9) aim to perform deep learning energy-efficiently, usually targeting the inference phase and often by exploiting physical substrates beyond conventional electronics. Approaches so far(10-22) have been unable to apply the backpropagation algorithm to train unconventional novel hardware in situ. The advantages of backpropagation have made it the de facto training method for large-scale neural networks, so this deficiency constitutes a major impediment. Here we introduce a hybrid in situ-in silico algorithm, called physics-aware training, that applies backpropagation to train controllable physical systems. Just as deep learning realizes computations with deep neural networks made from layers of mathematical functions, our approach allows us to train deep physical neural networks made from layers of controllable physical systems, even when the physical layers lack any mathematical isomorphism to conventional artificial neural network layers. To demonstrate the universality of our approach, we train diverse physical neural networks based on optics, mechanics and electronics to experimentally perform audio and image classification tasks. Physics-aware training combines the scalability of backpropagation with the automatic mitigation of imperfections and noise achievable with in situ algorithms. Physical neural networks have the potential to perform machine learning faster and more energy-efficiently than conventional electronic processors and, more broadly, can endow physical systems with automatically designed physical functionalities, for example, for robotics(23-26), materials(27-29) and smart sensors(30-32).", + "Times Cited, WoS Core": 355, + "Times Cited, All Databases": 386, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000749546400022", + "Markdown": "# Article \n\n# Deep physical neural networks trained with backpropagation \n\nhttps://doi.org/10.1038/s41586-021-04223-6 \n\nReceived: 19 May 2021 \n\nAccepted: 9 November 2021 \n\nPublished online: 26 January 2022 \n\nOpen access \n\n# Check for updates \n\nLogan G. Wright1,2,4 ✉, Tatsuhiro Onodera1,2,4 ✉, Martin M. Stein1, Tianyu Wang1, Darren T. Schachter3, Zoey Hu1 & Peter L. McMahon1 ✉ \n\nDeep-learning models have become pervasive tools in science and engineering. However, their energy requirements now increasingly limit their scalability1. Deep-learning accelerators2–9 aim to perform deep learning energy-efficiently, usually targeting the inference phase and often by exploiting physical substrates beyond conventional electronics. Approaches so far10–22 have been unable to apply the backpropagation algorithm to train unconventional novel hardware in situ. The advantages of backpropagation have made it the de facto training method for large-scale neural networks, so this deficiency constitutes a major impediment. Here we introduce a hybrid in situ–in silico algorithm, called physics-aware training, that applies backpropagation to train controllable physical systems. Just as deep learning realizes computations with deep neural networks made from layers of mathematical functions, our approach allows us to train deep physical neural networks made from layers of controllable physical systems, even when the physical layers lack any mathematical isomorphism to conventional artificial neural network layers. To demonstrate the universality of our approach, we train diverse physical neural networks based on optics, mechanics and electronics to experimentally perform audio and image classification tasks. Physics-aware training combines the scalability of backpropagation with the automatic mitigation of imperfections and noise achievable with in situ algorithms. Physical neural networks have the potential to perform machine learning faster and more energy-efficiently than conventional electronic processors and, more broadly, can endow physical systems with automatically designed physical functionalities, for example, for robotics23–26, materials27–29 and smart sensors30–32. \n\nLike many historical developments in artificial intelligence33,34, the widespread adoption of deep neural networks (DNNs) was enabled in part by synergistic hardware. In 2012, building on earlier works, Krizhevsky et al. showed that the backpropagation algorithm could be efficiently executed with graphics-processing units to train large DNNs35 for image classification. Since 2012, the computational requirements of DNN models have grown rapidly, outpacing Moore’s law1. Now, DNNs are increasingly limited by hardware energy efficiency. \n\nThe emerging DNN energy problem has inspired special-purpose hardware: DNN ‘accelerators’2–8, most of which are based on direct mathematical isomorphism between the hardware physics and the mathematical operations in DNNs (Fig. 1a, b). Several accelerator proposals use physical systems beyond conventional electronics8, such as optics9 and analogue electronic crossbar arrays3,4,12. Most devices target the inference phase of deep learning, which accounts for up to $90\\%$ of the energy costs of deep learning in commercial deployments1, although, increasingly, devices are also addressing the training phase (for example, ref. 7). \n\nHowever, implementing trained mathematical transformations by designing hardware for strict, operation-by-operation mathematical isomorphism is not the only way to perform efficient machine learning. Instead, we can train the hardware’s physical transformations directly to perform desired computations. Here we call this approach physical neural networks (PNNs) to emphasize that physical processes, rather than mathematical operations, are trained. This distinction is not merely semantic: by breaking the traditional software–hardware division, PNNs provide the possibility to opportunistically construct neural network hardware from virtually any controllable physical system(s). As anyone who has simulated the evolution of complex physical systems appreciates, physical transformations are often faster and consume less energy than their digital emulations. This suggests that PNNs, which can harness these physical transformations most directly, may be able to perform certain computations far more efficiently than conventional paradigms, and thus provide a route to more scalable, energy-efficient and faster machine learning. \n\n![](images/b63f8de339d26114efc9d083b05041dddddf9a673257dd6c45700afc0616459e.jpg) \nFig. 1 | Introduction to PNNs. a, Artificial neural networks contain operational units (layers): typically, trainable matrix-vector multiplications followed by element-wise nonlinear activation functions. b, DNNs use a sequence of layers and can be trained to implement multi-step (hierarchical) transformations on input data. c, When physical systems evolve, they perform, in effect, computations. We partition their controllable properties into input data and control parameters. Changing parameters alters the transformation performed on data. We consider three examples. In a mechanical (electronic) system, input data and parameters are encoded into time-dependent forces (voltages) applied to a metal plate (nonlinear circuit). The controlled \n\nmultimode oscillations (transient voltages) are then measured by a microphone (oscilloscope). In a nonlinear optical system, pulses pass through a $\\chi^{(2)}$ crystal, producing nonlinearly mixed outputs. Input data and parameters are encoded in the input pulses’ spectra, and outputs are obtained from the frequency-doubled pulses’ spectra. d, Like DNNs constructed from sequences of trainable nonlinear mathematical functions, we construct deep PNNs with sequences of trainable physical transformations. In PNNs, each physical layer implements a controllable physical function, which does need to be mathematically isomorphic to a conventional DNN layer. \n\nPNNs are particularly well motivated for DNN-like calculations, much more so than for digital logic or even other forms of analogue computation. As expected from their robust processing of natural data, DNNs and physical processes share numerous structural similarities, such as hierarchy, approximate symmetries, noise, redundancy and nonlinearity36. As physical systems evolve, they perform transformations that are effectively equivalent to approximations, variants and/ or combinations of the mathematical operations commonly used in DNNs, such as convolutions, nonlinearities and matrix-vector multiplications. Thus, using sequences of controlled physical transformations (Fig. 1c), we can realize trainable, hierarchical physical computations, that is, deep PNNs (Fig. 1d). \n\nAlthough the paradigm of constructing computers by directly training physical transformations has ancestry in evolved computing materials18, it is today emerging in various fields, including optics14,15,17,20, spintronic nano-oscillators10,37, nanoelectronic devices13,19 and small-scale quantum computers38. A closely related trend is physical reservoir computing (PRC)21,22, in which the transformations of an untrained physical ‘reservoir’ are linearly combined by a trainable output layer. Although PRC harnesses generic physical processes for computation, it is unable to realize DNN-like hierarchical computations. In contrast, approaches that train the physical transformations13–19 themselves can, in principle, overcome this limitation. To train physical transformations experimentally, researchers have frequently relied on gradient-free learning algorithms10,18–20. Gradient-based learning algorithms, such as the backpropagation algorithm, are considered essential for the efficient training and good generalization of large-scale DNNs39. Thus, proposals to realize gradient-based training in physical hardware have appeared40–47. These inspiring proposals nonetheless make assumptions that exclude many physical systems, such as linearity, dissipation-free evolution or that the system be well described by gradient dynamics. The most general proposals13–16 overcome such constraints by performing training in silico, that is, learning wholly within numerical simulations. Although the universality of in silico training is empowering, simulations of nonlinear physical systems are rarely accurate enough for models trained in silico to transfer accurately to real devices. \n\nHere we demonstrate a universal framework using backpropagation to directly train arbitrary physical systems to execute DNNs, that is, PNNs. Our approach is enabled by a hybrid in situ–in silico algorithm, called physics-aware training (PAT). PAT allows us to execute the backpropagation algorithm efficiently and accurately on any sequence of physical input–output transformations. We demonstrate the universality of this approach by experimentally performing image classification using three distinct systems: the multimode mechanical oscillations of a driven metal plate, the analogue dynamics of a nonlinear electronicoscillator and ultrafast optical second-harmonic generation (SHG). We obtain accurate hierarchical classifiers that utilize each system’s unique physical transformations, and that inherently mitigate each system’s unique noise processes and imperfections. Although PNNs are a radical departure from traditional hardware, it is easy to integrate them into modern machine learning. We show that PNNs can be seamlessly combined with conventional hardware and neural network methods via physical–digital hybrid architectures, in which conventional hardware learns to opportunistically cooperate with unconventional physical resources using PAT. Ultimately, PNNs provide routes to improving the energy efficiency and speed of machine learning by many orders of magnitude, and pathways to automatically designing complex functional devices, such as functional nanoparticles28, robots25,26 and smart sensors30–32. \n\n![](images/096af250f69968a42b25be4174d30abed0a2f72959596fb8fce76ede3b33fcb1.jpg) \nFig. 2 | An example PNN, implemented experimentally using broadband optical SHG. a, Input data are encoded into the spectrum of a laser pulse (Methods, Supplementary Section 2). To control transformations implemented by the broadband SHG process, a portion of the pulse’s spectrum is used as trainable parameters (orange). The physical computation result is obtained from the spectrum of a blue (about $390{\\mathsf{n m}},$ ) pulse generated within $\\mathbf{a}\\chi^{(2)}$ \nmedium. b, To construct a deep PNN, the outputs of the SHG transformations are used as inputs to subsequent SHG transformations, with independent trainable parameters. c, d, After training the SHG-PNN (see main text, Fig. 3), it classifies test vowels with $93\\%$ accuracy. c, The confusion matrix for the PNN on the test set. d, Representative examples of final-layer output spectra, which show the SHG-PNN’s prediction. \n\n# An example PNN based on nonlinear optics \n\nFigure 2 shows an example PNN based on broadband optical pulse propagation in quadratic nonlinear media (ultrafast SHG). Ultrafast SHG realizes a physical computation roughly analogous to a nonlinear convolution, transforming the input pulse’s near-infrared spectrum (about $800\\cdot\\mathrm{{nm}}$ centre wavelength) into the blue (about $400\\mathsf{n m}$ ) through a multitude of nonlinear frequency-mixing processes (Methods). To control this computation, input data and parameters are encoded into sections of the spectrum of the near-infrared pulse by modulating its frequency components using a pulse shaper (Fig. 2a). This pulse then propagates through a nonlinear crystal, producing a blue pulse whose spectrum is measured to read out the result of the physical computation. \n\nTo realize vowel classification with SHG, we construct a multilayer SHG-PNN (Fig. 2b) where the input data for the first physical layer consist of a vowel-formant frequency vector. After the final physical layer, the blue output spectrum is summed using a digital computer into seven spectral bins (Fig. 2b, d, Supplementary Figs. 21, 22). The predicted vowel is identified by the bin with the maximum energy (Fig. 2c). In each layer, the output spectrum is digitally renormalized before being passed to the next layer (via the pulse shaper), along with a trainable digital rescaling. Mathematically, this transformation is given by $\\mathbf{X}^{[l+1]}=\\frac{a\\mathbf{y}^{[l]}}{\\operatorname*{max}(\\mathbf{y}^{[l]})}+b$ , where $\\mathbf{x}^{[l]}$ and $\\mathbf{y}^{[l]}$ are the inputs and outputs of the [l]th layer, respectively, and $a$ and $b$ are scalar parameters of the transformation.  Thus, the SHG-PNN’s computations are carried out almost entirely by the trained optical transformations, without digital activation functions or output layers. \n\n![](images/1d3a141ddf7736a9391277596d8b8451509b7e1a4f4a170932cdd35b3580541c.jpg) \nFig. 3 | Physics-aware training. a, PAT is a hybrid in situ–in silico algorithm to apply backpropagation to train controllable physical parameters so that physical systems perform machine-learning tasks accurately even in the presence of modelling errors and physical noise. Instead of performing the training solely within a digital model (in silico), PAT uses the physical systems to compute forward passes. Although only one layer is depicted in a, PAT \ngeneralizes naturally to multiple layers (Methods). b, Comparison of the validation accuracy versus training epoch with PAT and in silico training, for the experimental SHG-PNN depicted in Fig. 2b. c, Final experimental test accuracy for PAT and in silico training for SHG-PNNs with increasing numbers of physical layers. The length of error bars represent two standard errors. \n\nDeep PNNs essentially combine the computational philosophy of techniques such as $\\mathsf{P R C}^{21,22}$ with the trained hierarchical computations and gradient-based training of deep learning. In PRC, a physical system, often with recurrent dynamics, is used as an untrained feature map and a trained linear output layer (typically on a digital computer) combines these features to approximate desired functions. In PNNs, the backpropagation algorithm is used to adjust physical parameters so that a sequence of physical systems performs desired computations physically, without needing an output layer. For additional details, see Supplementary Section 3. \n\n# Physics-aware training \n\nTo train the PNNs’ parameters using backpropagation, we use PAT (Fig. 3). In the backpropagation algorithm, automatic differentiation determines the gradient of a loss function with respect to trainable parameters. This makes the algorithm $N$ -times more efficient than finite-difference methods for gradient estimation (where N is the number of parameters). The key component of PAT is the use of mismatched forward and backward passes in executing the backpropagation algorithm. This technique is well known in neuromorphic computing48–53, appearing recently in direct feedback alignment52 and quantization-aware training48, which inspired PAT. PAT generalizes these strategies to encompass arbitrary physical layers, arbitrary physical network architectures and, more broadly, to differentially programmable physical devices. \n\nPAT proceeds as follows (Fig. 3). First, training input data (for example, an image) are input to the physical system, along with trainable parameters. Second, in the forward pass, the physical system applies its transformation to produce an output. Third, the physical output is compared with the intended output to compute the error. Fourth, using a differentiable digital model, the gradient of the loss is estimated with respect to the controllable parameters. Finally, the parameters are updated according to the inferred gradient. This process is repeated, iterating over training examples, to reduce the error. See Methods for the intuition behind why PAT works and the general multilayer algorithm. \n\nThe essential advantages of PAT stem from the forward pass being executed by the actual physical hardware, rather than by a simulation. Our digital model for SHG is very accurate (Supplementary Fig. 20) and includes an accurate noise model (Supplementary Figs. 18, 19). However, as evidenced by Fig. 3b, in silico training with this model still fails, reaching a maximum vowel-classification accuracy of about $40\\%$ . In contrast, PAT succeeds, accurately training the SHG-PNN, even when additional layers are added (Fig. 3b, c). \n\n# Diverse PNNs for image classification \n\nPNNs can learn to accurately perform more complex tasks, can be realized with virtually any physical system and can be designed with a variety of physical network architectures. In Fig. 4, we present three PNN classifiers for the MNIST (Modified National Institute of Standards and Technology database) handwritten digit classification task, based on three distinct physical systems. For each physical system, we also demonstrate a different PNN architecture, illustrating the variety of physical networks possible. In all cases, models were constructed and trained using PyTorch54. \n\n![](images/316d218227be5006f7f1e8a812b5d528849e7e1abf9744e5fd19d347f1e1875f.jpg) \nFig. 4 | Image classification with diverse physical systems. We trained reference model where the physical transformations implemented by the PNNs based on three physical systems (mechanics, electronics and optics) to speaker are replaced by identity operations. d, Confusion matrix for the classify images of handwritten digits. a, The mechanical PNN: the multimode mechanical PNN after training. e–h, The same as a–d, respectively, but for a oscillations of a metal plate are driven by time-dependent forces that encode nonlinear analogue-electronic PNN. i–l, The same as a–d, respectively, for a the input image data and parameters. b, The mechanical PNN multilayer hybrid physical–digital PNN based on broadband optical SHG. The final test architecture. c, The validation classification accuracy versus training epoch for accuracy is $87\\%$ , $93\\%$ and $97\\%$ for the mechanical, electronic and optics-based the mechanical PNN trained using PAT. The same curves are shown also for a PNNs, respectively. \n\nIn the mechanical PNN (Fig. 4a–d), a metal plate is driven by time-varying forces, which encode both input data and trainable parameters. The plate’s multimode oscillations enact controllable convolutions on the input data (Supplementary Figs. 16, 17). Using the plate’s trainable transformation sequentially three times, we classify 28-by-28 (784 pixel) images that are input as an unrolled time series. To control the transformations of each physical layer, we train element-wise rescaling of the forces applied to the plate (Fig. 4b, Methods). PAT trains the three-layer mechanical PNN to $87\\%$ accuracy, close to a digital linear classifier55. When the mechanical computations are replaced by identity operations, and only the digital rescaling \n\n# Article \n\noperations are trained, the performance of the model is equivalent to random guessing $(10\\%)$ . This shows that most of the PNN’s functionality comes from the controlled physical transformations. \n\nAn analogue-electronic PNN is implemented with a circuit featuring a transistor (Fig. 4e–h), which results in a noisy, nonlinear transient response (Supplementary Figs. 12, 13). The usage and architecture of the electronic PNN are mostly similar to that of the mechanical PNN, with several minor differences (Methods). When trained using PAT, the analogue-electronic PNN performs the classification task with $93\\%$ test accuracy. \n\nUsing broadband SHG, we demonstrate a physical–digital hybrid PNN (Fig. 4i–l). This hybrid PNN involves trainable digital linear input layers followed by trainable ultrafast SHG transformations. The trainable SHG transformations boost the performance of the digital baseline from roughly $90\\%$ accuracy to $97\\%$ . The classification task’s difficulty is nonlinear with respect to accuracy, so this improvement typically requires increasing the number of digital operations by around one order of magnitude55. This illustrates how a hybrid physical–digital PNN can automatically learn to offload portions of a computation from an expensive digital processor to a fast, energy-efficient physical co-processor. \n\nTo show the potential for PNNs to perform more challenging tasks, we simulated a multilayer PNN based on a nonlinear oscillator network. This PNN is trained with PAT to perform the MNIST task with $99.1\\%$ accuracy, and the Fashion-MNIST task, which is considered significantly harder56, with $90\\%$ accuracy, in both cases with simulated physical noise, and with mismatch between model and simulated experiment of over $20\\%$ (Supplementary Section 4). \n\n# Discussion \n\nOur results show that controllable physical systems can be trained to execute DNN calculations. Many systems that are not conventionally used for computation appear to offer, in principle, the capacity to perform parts of machine-learning-inference calculations orders of magnitude faster and more energy-efficiently than conventional hardware (Supplementary Section 5). However, there are two caveats to note. First, owing to underlying symmetries and other constraints, some systems may be well suited for accelerating a restricted class of computations that share the same constraints. Second, PNNs trained using PAT can only provide significant benefits during inference, as PAT uses a digital model. Thus, as in the hybrid network presented in Fig. 4i–l, we expect such PNNs to serve as a resource, rather than as a complete replacement, for conventional general-purpose hardware (Supplementary Section 5). \n\nTechniques for training hardware in situ7,40–47 and methods for reliable in silico training (for example, refs. 57–60) complement these weaknesses. Devices trained using in situ learning algorithms will perform learning entirely in hardware, potentially realizing learning faster and more energy-efficiently than current approaches. Such devices are suited to settings in which frequent retraining is required. However, to perform both learning and inference, these devices have more specific hardware requirements than inference-only hardware, which may limit their achievable inference performance. In silico training can train many physical parameters of a device, including ones set permanently during fabrication12–16. As the resulting hardware will not perform learning, it can be optimized for inference. Although accurate, large-scale in silico training has been implemented4–6,57–60, this has been achieved with only analogue electronics, for which accurate simulations and controlled fabrication processes are available. PAT may be used in settings where a simulation–reality gap cannot be avoided, such as if hardware is designed at the limit of fabrication tolerances, operated outside usual regimes or based on platforms other than conventional electronics. \n\nImprovements to PAT could extend the utility of PNNs. For example, PAT’s backward pass could be replaced by a neural network that directly estimates parameter updates for the physical system. Implementing this ‘teacher’ neural network with a PNN would allow subsequent training to be performed without digital assistance. \n\nThis work has focused so far on the potential application of PNNs as accelerators for machine learning, but PNNs are promising for other applications as well, particularly those in which physical, rather than digital, data are processed or produced. PNNs can perform computations on data within its physical domain, allowing for smart sensors30–32 that pre-process information before conversion to the electronic domain (for example, a low-power, microphone-coupled circuit tuned to recognize specific hotwords). As the achievable sensitivity, resolution and energy efficiency of many sensors is limited by conversion of information to the digital electronic domain, and by processing of that data in digital electronics, PNN sensors should have advantages. More broadly, with PAT, one is simply training the complex functionality of physical systems. Although machine learning and sensing are important functionalities, they are but two of many23–32 that PAT, and the concept of PNNs, could be applied to. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-04223-6. \n\n1. Patterson, D. et al. Carbon emissions and large neural network training. Preprint at https:// arxiv.org/abs/2104.10350 (2021). \n2. Reuther, A. et al. Survey of machine learning accelerators. In 2020 IEEE High Performance Extreme Computing Conference (HPEC) 1–12 (IEEE, 2020). \n3. Xia, Q., & Yang, J. J. Memristive crossbar arrays for brain-inspired computing. Nat. Mater. 18, 309–323 (2019). \n4. Burr, G. W. et al. Neuromorphic computing using non-volatile memory. Adv. Phys. X 2, 89–124 (2017). \n5. Khaddam-Aljameh, R. et al. HERMES core—a 14nm CMOS and PCM-based in-memory compute core using an array of 300ps/LSB linearized CCO-based ADCs and local digital processing. In 2021 Symposium on VLSI Circuits (IEEE, 2021). \n6. Narayanan, P. et al. Fully on-chip MAC at 14nm enabled by accurate row-wise programming of PCM-based weights and parallel vector-transport in duration-format. In 2021 Symposium on VLSI Technology (IEEE, 2021). \n7. Kohda, Y. et al. Unassisted true analog neural network training chip. In 2020 IEEE International Electron Devices Meeting (IEDM) (IEEE, 2020). \n8. Marković, D., Mizrahi, A., Querlioz, D. & Grollier, J. Physics for neuromorphic computing. Nat. Rev. Phys. 2, 499–510 (2020). \n9. Wetzstein, G. et al. Inference in artificial intelligence with deep optics and photonics. Nature 588, 39–47 (2020). \n10. Romera, M. et al. Vowel recognition with four coupled spin-torque nano-oscillators. Nature 563, 230–234 (2018). \n11. Shen, Y. et al. Deep learning with coherent nanophotonic circuits. Nat. Photon. 11, 441–446 (2017). \n12. Prezioso, M. et al. Training and operation of an integrated neuromorphic network based on metal-oxide memristors. Nature 521, 61–64 (2015). \n13. Euler, H.-C. R. et al. A deep-learning approach to realizing functionality in nanoelectronic devices. Nat. Nanotechnol. 15, 992–998 (2020). \n14. Hughes, T. W., Williamson, I. A., Minkov, M. & Fan, S. Wave physics as an analog recurrent neural network. Sci. Adv. 5, eaay6946 (2019). \n15. Wu, Z., Zhou, M., Khoram, E., Liu, B. & Yu, Z. Neuromorphic metasurface. Photon. Res. 8, 46–50 (2020). \n16. Furuhata, G., Niiyama, T. & Sunada, S. Physical deep learning based on optimal control of dynamical systems. Phys. Rev. Appl. 15, 034092 (2021). \n17. Lin, X. et al. All-optical machine learning using diffractive deep neural networks. Science 361, 1004–1008 (2018). \n18. Miller, J. F., Harding, S. L. & Tufte, G. Evolution-in-materio: evolving computation in materials. Evol. Intell. 7, 49–67 (2014). \n19. Chen, T. et al. Classification with a disordered dopant-atom network in silicon. Nature 577, 341–345 (2020). \n20.\t Bueno, J. et al. Reinforcement learning in a large-scale photonic recurrent neural network. Optica 5, 756–760 (2018). \n21. Tanaka, G. et al. Recent advances in physical reservoir computing: a review. Neural Netw. 115, 100–123 (2019). \n22. Appeltant, L. et al. Information processing using a single dynamical node as complex system. Nat. Commun. 2, 468 (2011). \n23.\t Mouret, J.-B. & Chatzilygeroudis, K. 20 years of reality gap: a few thoughts about simulators in evolutionary robotics. In Proc. Genetic and Evolutionary Computation Conference Companion 1121–1124 (2017). \n24.\t Howison, T., Hauser, S., Hughes, J. & Iida, F. Reality-assisted evolution of soft robots through large-scale physical experimentation: a review. Artif. Life 26, 484–506 (2021). \n25.\t de Avila Belbute-Peres, F., Smith, K., Allen, K., Tenenbaum, J. & Kolter, J. Z. End-to-end differentiable physics for learning and control. Adv. Neural Inf. Process. Syst. 31, 7178–7189 (2018). \n26.\t Degrave, J., Hermans, M., Dambre, J. & Wyffels, F. A differentiable physics engine for deep learning in robotics. Front. Neurorobot. 13, 6 (2019). \n27. Molesky, S. et al. Inverse design in nanophotonics. Nat. Photon. 12, 659–670 (2018). \n28. Peurifoy, J. et al. Nanophotonic particle simulation and inverse design using artificial neural networks. Sci. Adv. 4, eaar4206 (2018). \n29.\t Stern, M., Arinze, C., Perez, L., Palmer, S. E. & Murugan, A. Supervised learning through physical changes in a mechanical system. Proc. Natl Acad. Sci. USA 117, 14843–14850 (2020). \n30. Zhou, F. & Chai, Y. Near-sensor and in-sensor computing. Nat. Electron. 3, 664–671 (2020). \n31. Martel, J. N., Mueller, L. K., Carey, S. J., Dudek, P. & Wetzstein, G. Neural sensors: learning pixel exposures for HDR imaging and video compressive sensing with programmable sensors. IEEE Trans. Pattern Anal. Mach. Intell. 42, 1642–1653 (2020). \n32.\t Mennel, L. et al. Ultrafast machine vision with 2D material neural network image sensors. Nature 579, 62–66 (2020). \n33. Brooks, R. A. Intelligence without reason. In Proc. 12th International Joint Conference on Artificial Intelligence Vol. 1, 569–595 (Morgan Kaufmann, 1991). \n34.\t Hooker, S. The hardware lottery. Preprint at https://arxiv.org/abs/2009.06489 (2020). \n35.\t Krizhevsky, A., Sutskever, I. & Hinton, G. E. Imagenet classification with deep convolutional neural networks. Adv. Neural Inf. Process. Syst. 25, 1097–1105 (2012). \n36. Lin, H. W., Tegmark, M. & Rolnick, D. Why does deep and cheap learning work so well? J. Stat. Phys. 168, 1223–1247 (2017). \n37. Grollier, J. et al. Neuromorphic spintronics. Nat. Electron. 3, 360–370 (2020). \n38. Mitarai, K., Negoro, M., Kitagawa, M. & Fujii, K. Quantum circuit learning. Phys. Rev. A 98, 032309 (2018). \n39. Poggio, T., Banburski, A. & Liao, Q. Theoretical issues in deep networks. Proc. Natl Acad. Sci. USA 117, 30039–30045 (2020). \n40.\t Scellier, B. & Bengio, Y. Equilibrium propagation: bridging the gap between energy-based models and backpropagation. Front. Comput. Neurosci. 11 (2017). \n41. Ernoult, M., Grollier, J., Querlioz, D., Bengio, Y. & Scellier, B. Equilibrium propagation with continual weight updates Preprint at https://arxiv.org/abs/2005.04168 (2020). \n42.\t Laborieux, A. et al. Scaling equilibrium propagation to deep convnets by drastically reducing its gradient estimator bias. Front. Neurosci. 15 (2021). \n43.\t Martin, E. et al. Eqspike: spike-driven equilibrium propagation for neuromorphic implementations. iScience 24, 102222 (2021). \n44.\t Dillavou, S., Stern, M., Liu, A. J., & Durian, D. J. Demonstration of decentralized, physics-driven learning. Preprint at https://arxiv.org/abs/2108.00275 (2021). \n45.\t Hermans, M., Burm, M., Van Vaerenbergh, T., Dambre, J. & Bienstman, P. Trainable hardware for dynamical computing using error backpropagation through physical media. Nat. Commun. 6, 6729 (2015). \n46.\t Hughes, T. W., Minkov, M., Shi, Y. & Fan, S. Training of photonic neural networks through in situ backpropagation and gradient measurement. Optica 5, 864–871 (2018). \n47.\t Lopez-Pastor, V. & Marquardt, F. Self-learning machines based on Hamiltonian echo backpropagation. Preprint at https://arxiv.org/abs/2103.04992 (2021). \n48.\t Hubara, I., Courbariaux, M., Soudry, D., El-Yaniv, R. & Bengio, Y. Quantized neural networks: training neural networks with low precision weights and activations. J. Mach. Learn. Res. 18, 6869–6898 (2017). \n49.\t Frye, R. C., Rietman, E. A. & Wong, C. C. Back-propagation learning and nonidealities in analog neural network hardware. IEEE Trans. Neural Netw. 2, 110–117 (1991). \n50.\t Cramer, B. et al. Surrogate gradients for analog neuromorphic computing. Preprint at https://arxiv.org/abs/2006.07239 (2020). \n51. Adhikari, S. P. et al. Memristor bridge synapse-based neural network and its learning. IEEE Trans Neural Netw. Learn. Syst. 23,1426–1435 (2012). \n52.\t Lillicrap, T. P., Cownden, D., Tweed, D. B. & Akerman, C. J. Random synaptic feedback weights support error backpropagation for deep learning. Nat. Commun. 7, 13276 (2016). \n53.\t Launay, J., Poli, I., Boniface, F., & Krzakala, F. Direct feedback alignment scales to modern deep learning tasks and architectures. Preprint at https://arxiv.org/abs/2006.12878 (2020). \n54.\t Paszke, A. et al. PyTorch: an imperative style, high-performance deep learning library. Adv. Neural Inf. Process. Syst. 32, 8024–8035 (2019). \n55.\t LeCun, Y., Bottou, L., Bengio, Y. & Haffner, P. Gradient-based learning applied to document recognition. Proc. IEEE 86, 2278–2324 (1998). \n56.\t Xiao, H., Rasul, K., & Vollgraf, R. Fashion-MNIST: a novel image dataset for benchmarking machine learning algorithms. Preprint at https://arxiv.org/abs/1708.07747 (2017). \n57.\t Spoon, K. et al. Toward software-equivalent accuracy on transformer-based deep neural networks with analog memory devices. Front. Comput. Neurosci. 53, (2021). \n58.\t Kariyappa, S. et al. Noise-resilient DNN: tolerating noise in PCM-based AI accelerators via noise-aware training. IEEE Trans. Electron Devices 68, 4356–4362 (2021). \n59.\t Gokmen, T., Rasch, M. J. & Haensch. W. The marriage of training and inference for scaled deep learning analog hardware. In 2019 IEEE International Electron Devices Meeting (IEDM) (IEEE, 2019). \n60.\t Rasch, M. J. et al. A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays. In 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS) (IEEE, 2021). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 \n\n# Article Methods \n\n# Physics-aware training \n\nTo train the PNNs presented in Figs. 2–4, we used PAT to enable us to perform backpropagation on the physical apparatuses as automatic differentiation (autodiff) functions within PyTorch54 (v1.6). We used PyTorch Lightning61 (v0.9) and Weights and Biases62 (v0.10) during development as well. PAT is explained in detail in Supplementary Section 1, where it is compared with standard backpropagation, and training physical devices in silico. Here we provide only an overview of PAT in the context of a generic multilayer PNN (Supplementary Figs. 2, 3). \n\nPAT can be formalized by the use of custom constituent autodiff functions for the physically executed submodules in an overall network architecture (Supplementary Fig. 1). In PAT, each physical system’s forward functionality is provided by the system’s own controllable physical transformation, which can be thought of as a parameterized function $f_{\\mathfrak{p}}$ that relates the input $\\mathbf{x}$ , parameters θ, and outputs y of the transformation via $\\mathbf{y}=f_{\\mathsf{p}}$ (x,θ). As a physical system cannot be auto-differentiated, we use a differentiable digital model $f_{\\mathrm{m}}$ to approximate each backward pass through a given physical module. This structure is essentially a generalization of quantization-aware training48, in which low-precision neural network hardware is approximated by quantizing weights and activation values on the forward pass, but storing weights and activations, and performing the backward pass with full precision. \n\nTo see how this works, we consider here the specific case of a multilayer feedforward PNN with standard stochastic gradient descent. In this case, the PAT algorithm with the above-defined custom autodiff functions results in the following training loop: \n\nPerform forward pass: \n\n$$\n\\mathbf{x}^{[l+1]}{=}\\mathbf{y}^{[l]}{=}f_{\\mathrm{p}}(\\mathbf{x}^{[l]},\\mathbf{\\boldsymbol{\\Theta}}^{[l]})\n$$ \n\nCompute (exact) error vector: \n\n$$\n{\\displaystyle{g}_{{\\bf{y}}^{[N]}}=\\frac{\\partial L}{\\partial{\\bf{y}}^{[N]}}=\\frac{\\partial\\ell}{\\partial{\\bf{y}}^{[N]}}({\\bf{y}}^{[N]},{\\bf{y}}_{\\mathrm{target}})}\n$$ \n\nPerform backward pass \n\n$$\n{\\displaystyle{\\boldsymbol g}_{{\\bf y}^{[l-1]}}=\\left[\\frac{\\partial f_{\\mathrm{m}}}{\\partial{\\bf x}}({\\bf x}^{[l]},{\\bf\\pmb\\theta}^{[l]})\\right]^{\\mathrm{T}}}{\\bf g}_{{\\bf y}^{[l]}}}\n$$ \n\n$$\n\\boldsymbol{g}_{\\mathbf{\\pmb{\\theta}}^{[l-1]}}=\\left[\\frac{\\partial f_{\\mathrm{m}}}{\\partial\\mathbf{\\pmb{\\theta}}}(\\mathbf{x}^{[l]},\\mathbf{\\pmb{\\theta}}^{[l]})\\right]^{\\top}\\boldsymbol{g}_{\\mathbf{y}^{[l]}}\n$$ \n\nUpdate parameters: \n\n$$\n{\\Theta^{[l]}\\to\\Theta^{[l]}-\\eta\\frac{1}{N_{\\mathrm{data}}}\\sum_{k}g_{\\L_{\\L}^{[l]}}^{(k)}}\n$$ \n\nwhere $g_{\\pmb{\\uptheta}^{[l]}}$ and $g_{\\mathbf{v}^{[l]}}$ are estimators of the physical systems’ exact gradients, $\\frac{\\partial{\\cal L}}{\\partial\\pmb{\\theta}^{[l]}}$ and ∂∂yL[ , respectively for the [ ]th layer, obtained by autodifferentiation of the model, $\\iota$ is the loss, $\\ell$ is the loss function (for example, cross-entropy or mean-squared error), $\\mathbf{y_{target}}$ is the desired (target) output, $N_{\\mathrm{data}}$ is the size of the batch and $\\eta$ is the learning rate. $\\mathbf{x}^{[l+\\mathrm{i}]}$ is the input vector to the $[l+1]$ th layer, which for the hidden layers of the feedforward architecture is equal to the output vector of the previous layer, $\\mathbf{x}^{[l+1]}{=}\\mathbf{y}^{[l]}{=}f_{\\mathrm{p}}(\\mathbf{x}^{[l]},\\bar{\\mathbf{\\Theta}}^{[l]})$ , where ${\\pmb\\theta}^{[l]}$ is the controllable (trainable) parameter vector for the [ ]th layer. For the first layer, the input data vector x [1] is the data to be operated on. In PAT, the error vector is exactly estimated $(g_{\\mathbf{y}_{\\bot}^{[M]}}=\\frac{\\partial L}{\\partial\\mathbf{y}^{[M]}})$ as the forward pass is performed by the physical system. This error vector is then backpropagated via equation (3), which involves Jacobian matrices of the differential digital model evaluated at the correct inputs at each layer (that is, the actual physical inputs) ∂xm (x[ ], θ[ ]) , where T represents the transpose operation. Thus, in addition to utilizing the output of the PNN $(\\mathbf{\\dot{y}}^{[N]})$ via physical computations in the forward pass, intermediate outputs $(\\mathbf{y}^{[l]})$ are also utilized to facilitate the computation of accurate gradients in PAT. \n\nAs it is implemented just by defining a custom autodiff function, generalizing PAT for more complex architectures, such as multichannel or hybrid physical–digital models, with different loss functions and so on is straightforward. See Supplementary Section 1 for details. \n\nAn intuitive motivation for why PAT works is that the training’s optimization of parameters is always grounded in the true optimization landscape by the physical forward pass. With PAT, even if gradients are estimated only approximately, the true loss function is always precisely known. As long as the gradients estimated by the backward pass are reasonably accurate, optimization will proceed correctly. Although the required training time is expected to increase as the error in gradient estimation increases, in principle it is sufficient for the estimated gradient to be pointing closer to the direction of the true gradient than its opposite (that is, that the dot product of the estimated and true gradients is positive). Moreover, by using the physical system in the forward pass, the true output from each intermediate layer is also known, so gradients of intermediate physical layers are always computed with respect to correct inputs. In any form of in silico training, compounding errors build up through the imperfect simulation of each physical layer, leading to a rapidly diverging simulation–reality gap as training proceeds (see Supplementary Section 1 for details). As a secondary benefit, PAT ensures that learned models are inherently resilient to noise and other imperfections beyond a digital model, as the change of loss along noisy directions in parameter space will tend to average to zero. This makes training robust to, for example, device– device variations, and facilitates the learning of noise-resilient (and, more speculatively, noise-enhanced) models8. \n\n# Differentiable digital models \n\nTo perform PAT, a differentiable digital model of the physical system’s input–output transformation is required. Any model, $f_{\\mathrm{m^{\\prime}}}$ of the physical system’s true forward function, $f_{\\mathfrak{p^{\\prime}}}$ can be used to perform PAT, so long as it can be auto-differentiated. Viable approaches include traditional physics models, black-box machine-learning models13,63,64 and physics-informed machine-learning65 models. \n\nIn this work, we used the black-box strategy for our differentiable digital models, namely DNNs trained on input–output vector pairs from the physical systems as $f_{\\mathrm{m}}$ (except for the mechanical system). Two advantages of this approach are that it is fully general (it can be applied even to systems in which one has no underlying knowledge-based model of the system) and that the accuracy can be extremely high, at least for physical inputs, $({\\bf x},\\pmb\\theta)$ , within the distribution of the training data (for out-of-distribution generalization, we expect physics-based approaches to offer advantages). In addition, the fact that each physical system has a precise corresponding DNN means that the resulting PNN can be analysed as a network of DNNs, which may be useful for explaining the PNN’s learned physical algorithm. \n\nFor our DNN differentiable digital models, we used a neural architecture search66 to optimize hyperparameters, including the learning rate, number of layers and number of hidden units in each layer. Typical optimal architectures involved 3–5 layers with 200–1,000 hidden units in each, trained using the Adam optimizer, mean-squared loss function and learning rates of around $10^{-4}$ . For more details, see Supplementary Section 2D.1. \n\nFor the nonlinear optical system, the test accuracy of the trained digital model (Supplementary Fig. 20) shows that the model is remarkably accurate compared with typical simulation–experiment agreement in broadband nonlinear optics, especially considering that the pulses used exhibit a complex spatiotemporal structure owing to the pulse shaper. The model is not, however, an exact description of the physical system: the typical error for each element of the output vector is about 1– $2\\%$ . For the analogue electronic circuit, agreement is also good, although worse than the other systems (Supplementary Fig. 23), corresponding to around $5-10\\%$ prediction error for each component of the output vector. For the mechanical system, we found that a linear model was sufficient to obtain excellent agreement, which resulted in a typical error of about $1\\%$ for each component of the output vector (Supplementary Fig. 26). \n\n# In silico training \n\nTo train PNNs in silico, we applied a training loop similar to the one described above for PAT except that both the forward and backward passes are performed using the model (Supplementary Figs. 1, 3), with one exception noted below. \n\nTo improve the performance of in silico training as much as possible and permit the fairest comparison with PAT, we also modelled the input-dependent noise of the physical system and used this within the forward pass of in silico training. To do this, we trained, for each physical system, an additional DNN to predict the eigenvectors of the output vector’s noise covariance matrix, as a function of the physical system’s input vector and parameter vector. These noise models thus provided an input- and parameter-dependent estimate of the distribution of noise in the output vector produced by the physical system. We were able to achieve excellent agreement between the noise models’ predicted noise distributions and experimental measurements (Supplementary Figs. 18, 19). We found that including this noise model improved the performance of experiments performed using parameters derived from in silico training. Consequently, all in silico training results presented in this paper make use of such a model, except for the mechanical system, where a simpler, uniform noise model was found to be sufficient. For additional details, see Supplementary Section 2D.2. \n\nAlthough including complex, accurate noise models does not allow in silico training to perform as well as PAT, we recommend that such models be used whenever in silico training is performed, such as for physical architecture search and design and possibly pre-training (Supplementary Section 5), as the correspondence with experiment (and, in particular, the predicted peak accuracy achievable there) is significantly improved over simpler noise models, or when ignoring physical noise. \n\n# Ultrafast nonlinear optical pulse propagation experiments \n\nFor experiments with ultrafast nonlinear pulse propagation in quadratic nonlinear media (Supplementary Figs. 8–10), we shaped pulses from a mode-locked titanium:sapphire laser (Spectra Physics Tsunami, centred around $780\\mathsf{n m}$ and pulse duration around 100 fs) using a custom pulse shaper. Our optical pulse shaper used a digital micromirror device (DMD, Vialux V-650L) and was inspired by the design in ref. 67. Despite the binary modulations of the individual mirrors, we were able to achieve multilevel spectral amplitude modulation by varying the duty cycle of gratings written to the DMD along the dimension orthogonal to the diffraction of the pulse frequencies. To control the DMD, we adapted code developed for ref. 68, which is available at ref. 69. \n\nAfter being shaped by the pulse shaper, the femtosecond pulses were focused into a $0.5{\\cdot}\\mathsf{m m}$ -long beta-barium borate crystal. The multitude of frequencies within the broadband pulses then undergo various nonlinear optical processes, including sum-frequency generation and SHG. The pulse shaper imparts a complex phase and spatiotemporal structure on the pulse, which depend on the input and parameters applied through the spectral modulations. These features would make it impossible to accurately model the experiment using a one-dimensional pulse propagation model. For simplicity, we refer to this complex, spatiotemporal quadratic nonlinear pulse propagation as ultrafast SHG. \n\nAlthough the functionality of the SHG-PNN does not rely on a closed-form mathematical description or indeed on any form of mathematical isomorphism, some readers may find it helpful to understand the approximate form of the input–output transformation realized in this experimental apparatus. We emphasize that the following model is idealistic and meant to convey key intuitions about the physical transformation: the model does not describe the experimental transformation in a quantitative manner, owing to the numerous experimental complexities described above. \n\nThe physical transformation of the ultrafast SHG setup is seeded by the infrared light from the titanium:sapphire laser. This ultrashort pulse can be described by the Fourier transform of the electric field envelope of the pulse, $A_{0}(\\omega)$ , where $\\omega$ is the frequency of the field detuned relative to the carrier frequency. For simplicity, consider a pulse consisting of a set of discrete frequencies or frequency bins, whose spectral amplitudes are described by the discrete vector $\\mathbf{A}_{0}=[A_{0}(\\omega_{1}),A_{0}(\\omega_{2}),...,A_{0}(\\omega_{N})]^{\\mathrm{T}}$ . After passing through the pulseshaper, the spectral amplitudes of the pulse are then given by \n\n$$\n\\mathbf{A}=[\\sqrt{x_{1}}A_{0}(\\omega_{1}),\\sqrt{x_{2}}A_{0}(\\omega_{2}),...,\\sqrt{\\theta_{1}}A_{0}(\\omega_{N_{x}+1}),\\sqrt{\\theta_{2}}A_{0}(\\omega_{N_{x}+2}),...]^{\\mathrm{T}},\n$$ \n\nwhere $N_{x}$ is the dimensionality of the data vector, $\\theta_{i}$ are the trainable pulse-shaper amplitudes and $x_{i}$ are the elements of the input data vector. Thus, the output from the pulse shaper encodes both the machine-learning data as well as the trainable parameters. Square roots are present in equation (5) because the pulse shaper was deliberately calibrated to perform an intensity modulation. \n\nThe output from the pulse shaper (equation (5)) is then input to the ultrafast SHG process. The propagation of an ultrashort pulse through a quadratic nonlinear medium results in an input–output transformation that roughly approximates an autocorrelation, or nonlinear convolution, assuming that the dispersion during propagation is small and the input pulse is well described by a single spatial mode. In this limit, the output blue spectrum $B(\\omega_{i})$ is mathematically given by \n\n$$\nB(\\omega_{i})=k\\sum_{j}A(\\omega_{i}+\\omega_{j})A(\\omega_{i}-\\omega_{j}),\n$$ \n\nwhere the sum is over all frequency bins $j$ of the pulsed field. The output of the trainable physical transformation $\\scriptstyle\\mathbf{y}=f_{\\mathrm{n}}\\left(\\mathbf{x},\\mathbf{\\boldsymbol{\\mathsf{0}}}\\right)$ is given by the blue pulse’s spectral power, $\\mathbf{y}=[|B_{\\omega_{1}}|^{2},|B_{\\omega_{2}}|^{2},...,|B_{\\omega_{N}}|^{2}]^{\\mathrm{T}}$ , where $N$ is the length of the output vector. \n\nFrom this description, it is clear that the physical transformation realized by the ultrafast SHG process is not isomorphic to any conventional neural network layer, even in this idealized limit. Nonetheless, the physical transformation retains some key features of typical neural network layers. First, the physical transformation is nonlinear as the SHG process involves the squaring of the input field. Second, as the terms within the summation in equation (6) involve both parameters and input data, the transformation also mixes the different elements of the input data and parameters to product an output. This mixing of input elements is similar, but not necessarily directly mathematically equivalent to, the mixing of input vector elements that occur in the matrix-vector multiplications or convolutions that appear in conventional neural networks. \n\n# Vowel classification with ultrafast SHG \n\nA task often used to demonstrate novel machine-learning hardware is the classification of spoken vowels according to formant frequencies10,11. The task involves predicting the spoken vowels given a 12-dimensional input data vector of formant frequencies extracted from audio recordings10. Here we use the vowel dataset from ref. 10, which is based on data originally from ref. 70; data available at https:// homepages.wmich.edu/\\~hillenbr/voweldata.html. This dataset consists of 273 data input–output pairs. We used 175 data pairs as the training \n\n# Article \n\nset—49 for the validation and 49 for the test set. For the results in Figs. 2, 3, we optimized for the hyperparameters of the PNN architecture using the validation error and only evaluated the test error after all optimization was conducted. In Fig. 3c, for each PNN with a given number of layers, the experiment was conducted with two different training, validation and test splits of the vowel data. In Fig. 3c, the line plots the mean over the two splits, and the error bars are the standard error of the mean. \n\nFor the vowel-classification PNN presented in Figs.  2, 3, the input vector to each SHG physical layer is encoded in a contiguous short-wavelength section of the spectral modulation vector sent to the pulse shaper, and the trainable parameters are encoded in the spectral modulations applied to the rest of the spectrum. For the physical layers after the first layer, the input vector to the physical system is the measured spectrum obtained from the previous layer. For convenience, we performed digital renormalization of these output vectors to maximize the dynamic range of the input and ensure that inputs were within the allowed range of 0 to 1 accepted by the pulse shaper. Relatedly, we found that training stability was improved by including additional trainable digital re-scaling parameters to the forward-fed vector, allowing the overall bias and amplitude scale of the physical inputs to each layer to be adjusted during training. These digital parameters appear to have a negligible role in the final trained PNN (when the physical transformations are replaced by identity operations, the network can be trained to perform no better than chance, and the final trained values of the scale and bias parameters are all very close to 1 and 0, respectively). We hypothesize that these trainable rescaling parameters are helpful during training to allow the network to escape noise-affected subspaces of parameter space. See Supplementary Section 2E.1 for details. \n\nThe vowel-classification SHG-PNN architecture (Supplementary Fig. 21) was designed to be as simple as possible while still demonstrating the use of a multilayer architecture with a physical transformation that is not isomorphic to a conventional DNN layer, and so that the computations involved in performing the classification were essentially all performed by the physical system itself. Many aspects of the design are not optimal with respect to performance, so design choices, such as our specific choice to partition input data and parameter vectors into the controllable parameters of the experiment, should not be interpreted as representing any systematic optimization. Similarly, the vowel-classification task was chosen as a simple example of multidimensional machine-learning classification. As this task can be solved almost perfectly by a linear model, it is in fact poorly suited to the nonlinear optical transformations of our SHG-PNN, which are fully nonlinear (Supplementary Figs. 9, 10). Overall, readers should not interpret this PNN’s design as suggestive of optimal design strategies for PNNs. For initial guidelines on optimal design strategies, we instead refer readers to Supplementary Section 5. \n\n# MNIST handwritten digit image classification with a hybrid physical–digital SHG-PNN \n\nThe design of the hybrid physical–digital MNIST PNN based on ultrafast SHG for handwritten digit classification (Fig. 4i–l) was chosen to demonstrate a proof-of-concept PNN in which substantial digital operations were co-trained with substantial physical transformations, and in which no digital output layer was used (although a digital output layer can be used with PNNs, and we expect such a layer will usually improve performance, we wanted to avoid confusing readers familiar with reservoir computing, and so avoided using digital output layers in this work). \n\nThe network (Supplementary Fig. 29) involves four trainable linear input layers that operate on MNIST digit images, whose outputs are fed into four separate channels in which the SHG physical transformation is used twice in succession (that is, it is two physical layers deep). The output of the final layers of each channel (the final SHG spectra) are concatenated, then summed into ten bins to perform a classification. The structure of the input layer was chosen to minimize the complexity of inputs to the pulse shaper. We found that the output second-harmonic spectra produced by the nonlinear optical process tended towards featureless triangular spectra if inputs were close to a random uniform distribution. Thus, to ensure that output spectra varied significantly with respect to changes in the input spectral modulations, we made sure that inputs to the pulse shaper would exhibit a smoother structure in the following way. For each of 4 independent channels, 196-dimensional input images (downsampled from 784-dimensional $28\\times28$ images) are first operated on by a 196 by 50 trainable linear matrix, and then (without any nonlinear digital operations), a second 50 by 196 trainable linear matrix. The second 50 by 196 matrix is identical for all channels, the intent being that this matrix identifies optimal ‘input modes’ to the SHG process. By varying the middle dimension of this two-step linear input layer, one may control the amount of structure (number of ‘spectral modes’) allowed in inputs to the pulse shaper, as the middle dimension effectively controls the rank of the total linear matrix. We found that a middle dimension below 30 resulted in the most visually varied SHG output spectra, but that 50 was sufficient for good performance on the MNIST task. In this network, we also utilized skip connections between layers in each channel. This was done so that the network would be able to ‘choose’ to use the linear digital operations to perform the linear part of the classification task (for which nearly $90\\%$ accuracy can be obtained55) and to thus rely on the SHG co-processor primarily for the harder, nonlinear part of the classification task. Between the physical layers in each channel, a trainable, element-wise rescaling was used to allow us to train the second physical layer transformations efficiently. That is, $x_{i}=a_{i}y_{i}+b_{i}$ where $b_{i}$ and $a_{i}$ are trainable parameters, and $x_{i}$ and $y_{i}$ are the input to the pulse shaper and the measured output spectrum from the previous physical layer, respectively. \n\nFor further details on the nonlinear optical experimental setup and its characterization, we refer readers to Supplementary Section 2A. For further details on the vowel-classification SHG-PNN, we refer readers to Supplementary Section 2E.1, and for the hybrid physical–digital MNIST handwritten digit-classification SHG-PNN, we refer readers to Supplementary Section 2E.4. \n\n# Analogue electronic circuit experiments \n\nThe electronic circuit used for our experiments (Supplementary Fig. 11) was a resistor-inductor-capacitor oscillator (RLC oscillator) with a transistor embedded within it. It was designed to produce as nonlinear and complex a response as possible, while still containing only a few simple components (Supplementary Figs. 12, 13). The experiments were carried out with standard bulk electronic components, a hobbyist circuit breadboard and a USB data acquisition (DAQ) device (Measurement Computing USB-1208-HS-4AO), which allowed for one analogue input and one analogue output channel, with a sampling rate of 1 MS $\\mathsf{\\pmb{s}}^{-1}$ . \n\nThe electronic circuit provides only a one-dimensional time-series input and one-dimensional time-series output. As a result, to partition the inputs to the system into trainable parameters and input data so that we could control the circuit’s transformation of input data, we found it was most convenient to apply parameters to the one-dimensional input time-series vector by performing trainable, element-wise rescaling on the input time-series vector. That is, $x_{i}=a_{i}y_{i}+b_{i}$ , where $b_{i}$ and $a_{i}$ are trainable parameters, $y_{i}$ are the components of the input data vector and $x_{i}$ are the re-scaled components of the voltage time series that is then sent to the analogue circuit. For the first layer, $y_{i}$ are the unrolled pixels of the input MNIST image. For hidden layers, $y_{i}$ are the components of the output voltage time-series vector from the previous layer. \n\nWe found that the electronic circuit’s output was noisy, primarily owing to the timing jitter noise that resulted from operating the DAQ at its maximum sampling rate (Supplementary Fig. 23). Rather than reducing this noise by operating the device more slowly, we were motivated to design the PNN architecture presented in Fig. 4 in a way that allowed it to automatically learn to function robustly and accurately, even in the presence of up to $20\\%$ noise per output vector element (See Supplementary Fig. 24 for an expanded depiction of the architecture). First, seven, three-layer feedforward PNNs were trained together, with the final prediction provided by averaging the output of all seven, three-layer PNNs. Second, skip connections similar to those used in residual neural networks were employed71. These measures make the output of the network effectively an ensemble average over many different subnetworks71, which allows it to perform accurately and train smoothly despite the very high physical noise and multilayer design. \n\nFor further details on the analogue electronic experimental setup and its characterization, we refer readers to Supplementary Section 2B. For further details on the MNIST handwritten digit-classification analogue electronic PNN, we refer readers to Supplementary Section 2E.2. \n\n# Oscillating mechanical plate experiments \n\nThe mechanical plate oscillator was constructed by attaching a 3.2 cm by $3.2\\mathrm{cm}$ by $1\\mathsf{m m}$ titanium plate to a long, centre-mounted screw, which was fixed to the voice coil of a commercial full-range speaker (Supplementary Figs. 14, 15). The speaker was driven by an audio amplifier (Kinter ${\\bf K}2020{\\bf A}^{+}.$ ) and the oscillations of the plate were recorded using a microphone (Audio-Technica ATR2100x-USB Cardioid Dynamic Microphone). The diaphragm of the speaker was completely removed so that the sound recorded by the microphone is produced only by the oscillating metal plate. \n\nAs the physical input (output) to (from) the mechanical oscillator is a one-dimensional time series, similar to the electronic circuit, we made use of element-wise trainable rescaling to conveniently allow us to train the oscillating plate’s physical transformations. \n\nThe mechanical PNN architecture for the MNIST handwritten digit classification task was chosen to be the simplest multilayer PNN architecture possible with such a one-dimensional dynamical system (Supplementary Fig. 27). As the mechanical plate’s input–output responses are primarily linear convolutions (Supplementary Figs. 16, 17), it is well suited to the MNIST handwritten digit classification task, achieving nearly the same performance as a digital linear model55. \n\nFor further details on the oscillating mechanical plate experimental setup and its characterization, we refer readers to Supplementary Section 2C. For further details on the MNIST handwritten digit-classification oscillating mechanical plate PNN, we refer readers to Supplementary Section 2E.3. \n\n# Data availability \n\nAll data generated during and code used for this work are available at https://doi.org/10.5281/zenodo.4719150. \n\n# Code availability \n\nAn expandable demonstration code for applying PAT to train PNNs is available at https://github.com/mcmahon-lab/Physics-Aware-Training. All code used for this work is available at https://doi.org/10.5281/ zenodo.4719150. \n\n61.\t Falcon, W. et al. PyTorch Lightning (2019); https://github.com/PyTorchLightning/ pytorch-lightning \n62.\t Biewald, L. Experiment Tracking with Weights and Biases (2020); https://www.wandb. com/ \n63.\t Kasim, M. F. et al. Building high accuracy emulators for scientific simulations with deep neural architecture search. Preprint at https://arxiv.org/abs/2001.08055 (2020). \n64.\t Rahmani, B. et al. Actor neural networks for the robust control of partially measured nonlinear systems showcased for image propagation through diffuse media. Nat. Mach. Intell. 2, 403–410 (2020). \n65.\t Karniadakis, G. E. et al. Physics-informed machine learning. Nat. Rev. Phys. 3, 422–440 (2021). \n66.\t Akiba, T., Sano, S., Yanase, T., Ohta, T. & Koyama, M. Optuna: a next-generation hyperparameter optimization framework. In Proc. 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2623–2631 (2019). \n67.\t Liu, W. et al. Programmable controlled mode-locked fiber laser using a digital micromirror device. Opt. Lett. 42, 1923–1926 (2017). \n68.\t Matthès, M. W., del Hougne, P., de Rosny, J., Lerosey, G. & Popoff, S. M. Optical complex media as universal reconfigurable linear operators. Optica 6, 465–472 (2019). \n69.\t Popoff, S. M. & Matthès, M. W. ALP4lib: q Python wrapper for the Vialux ALP-4 controller suite to control DMDs. Zenodo https://doi.org/10.5281/zenodo.4076193 (2020). \n70.\t Hillenbrand, J., Getty, L. A., Wheeler, K. & Clark, M. J. Acoustic characteristics of American English vowels. J. Acoust. Soc. Am. 97, 3099–3111 (1995). \n71.\t Veit, A.,Wilber, M. & Belongie, S. Residual networks behave like ensembles of relatively shallow networks Preprint at https://arxiv.org/abs/1605.06431 (2016). \n\nAcknowledgements We thank NTT Research for their financial and technical support. Portions of this work were supported by the National Science Foundation (award CCF-1918549). L.G.W. and T.W. acknowledge support from Mong Fellowships from Cornell Neurotech during early parts of this work. P.L.M. acknowledges membership of the CIFAR Quantum Information Science Program as an Azrieli Global Scholar. We acknowledge discussions with D. Ahsanullah, M. Anderson, V. Kremenetski, E. Ng, S. Popoff, S. Prabhu, M. Saebo, H. Tanaka, R. Yanagimoto, H. Zhen and members of the NTT PHI Lab/NSF Expeditions research collaboration, and thank P. Jordan for discussions and illustrations. \n\nAuthor contributions L.G.W., T.O. and P.L.M. conceived the project and methods. T.O. and L.G.W. performed the SHG-PNN experiments. L.G.W. performed the electronic-PNN experiments. M.M.S. performed the oscillating-plate-PNN experiments. T.W., D.T.S. and Z.H. contributed to initial parts of the work. L.G.W., T.O., M.M.S. and P.L.M. wrote the manuscript. P.L.M. supervised the project. \n\nCompeting interests L.G.W., T.O., M.M.S. and P.L.M. are listed as inventors on a US provisional patent application (number 63/178,318) on physical neural networks and physics-aware training. The other authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-04223-6. \nCorrespondence and requests for materials should be addressed to Logan G. Wright, Tatsuhiro Onodera or Peter L. McMahon. \nPeer review information Nature thanks Tayfun Gokmen and Damien Querlioz for their contribution to the peer review of this work. Peer reviewer reports are available. \nReprints and permissions information is available at http://www.nature.com/reprints. " + }, + { + "id": "10.1038_s41467-022-31664-y", + "DOI": "10.1038/s41467-022-31664-y", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-31664-y", + "Relative Dir Path": "mds/10.1038_s41467-022-31664-y", + "Article Title": "Ultra-wide bandgap semiconductor Ga2O3 power diodes", + "Authors": "Zhang, JC; Dong, PF; Dang, K; Zhang, YN; Yan, QL; Xiang, H; Su, J; Liu, ZH; Si, MW; Gao, JC; Kong, MF; Zhou, H; Hao, Y", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Ultra-wide bandgap semiconductor Ga2O3 based electronic devices are expected to perform beyond wide bandgap counterparts GaN and SiC. However, the reported power figure-of-merit hardly can exceed, which is far below the projected Ga2O3 material limit. Major obstacles are high breakdown voltage requires low doping material and PN junction termination, contradicting with low specific on-resistance and simultaneous achieving of n- and p-type doping, respectively. In this work, we demonstrate that Ga2O3 heterojunction PN diodes can overcome above challenges. By implementing the holes injection in the Ga2O3, bipolar transport can induce conductivity modulation and low resistance in a low doping Ga2O3 material. Therefore, breakdown voltage of 8.32 kV, specific on-resistance of 5.24 m Omega.cm(2), power figure-of-merit of 13.2 GW/cm(2), and turn-on voltage of 1.8 V are achieved. The power figure-of-merit value surpasses the 1-D unipolar limit of GaN and SiC. Those Ga2O3 power diodes demonstrate their great potential for next-generation power electronics applications.", + "Times Cited, WoS Core": 372, + "Times Cited, All Databases": 381, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000821634700017", + "Markdown": "# Ultra-wide bandgap semiconductor Ga2O3 power diodes \n\nJincheng Zhang1, Pengfei Dong1, Kui Dang 1, Yanni Zhang1, Qinglong Yan1, Hu Xiang1, Jie $\\mathsf{S u}^{1}$ , Zhihong Liu1, Mengwei Si 2, Jiacheng ${\\mathsf{G a o}}^{3}$ , Moufu Kong3, Hong Zhou $\\textcircled{1}$ 1✉ & Yue Hao1 \n\nUltra-wide bandgap semiconductor $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ based electronic devices are expected to perform beyond wide bandgap counterparts GaN and SiC. However, the reported power figure-ofmerit hardly can exceed, which is far below the projected $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ material limit. Major obstacles are high breakdown voltage requires low doping material and PN junction termination, contradicting with low specific on-resistance and simultaneous achieving of $\\mathsf{n-}$ and p-type doping, respectively. In this work, we demonstrate that $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ heterojunction PN diodes can overcome above challenges. By implementing the holes injection in the ${\\mathsf{G a}}_{2}{\\mathsf{O}}_{3},$ bipolar transport can induce conductivity modulation and low resistance in a low doping $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ material. Therefore, breakdown voltage of $8.32\\mathsf{k V}$ , specific on-resistance of $5.24~\\mathsf{m}\\Omega\\cdot\\mathsf{c m}^{2}$ , power figure-of-merit of $13.2\\mathsf{G W}/\\mathsf{c m}^{2}$ , and turn-on voltage of $\\boldsymbol{1.8\\vee}$ are achieved. The power figure-of-merit value surpasses the 1-D unipolar limit of GaN and SiC. Those $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ power diodes demonstrate their great potential for next-generation power electronics applications. \n\nA dprvoavnicdeidng hmigichoerndcuocntvoer smioant reifafilciheonlcdys agsr awtellpraosmimsea no-f taining higher voltage for modern industrial- and consumer-scale power electronics. Ultra-wide bandgap (UWB) semiconductor with general bandgap $(E_{\\mathrm{g}})$ greater than $4\\mathrm{eV}$ can sustain a higher critical field $\\left(E_{c}\\right)$ and hence a higher blocking voltage is achievable at a smaller resistance and power electronic component dimension, which turns out to be more efficient than its narrow bandgap material Si and wide bandgap material GaN and SiC counterparts, as summarized in Table 1 of Supplementary Information. The general concept lies behind is that the high electric-field $(E)$ and high temperature driven of the electron excitation from valance band to conduction band is inherently suppressed by the UWB. Therefore, power electronics based on UWB materials are spontaneously endowed with high breakdown voltage (BV) at a lower material thickness and resistance. Combined with good mobility $(\\mu)$ , a crucial power device parameter Baliga’s figure-of-merit $\\operatorname{\\mathrm{(B\\mathrm{-}F O M}\\mathrm{-}}\\mu\\times\\bar{E}_{c}^{3})$ of UWB semiconductors could be several or tens of folds of those wide bandgap materials GaN and SiC as well as more than thousands of times of narrow bandgap material $\\mathrm{Si}^{1,2}$ . However, it should be noted that the major tyranny of the UWB forbids achieving effective both n- and p-type doping simultaneously. Among those intriguing UWB semiconductor materials, the emerging ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ is now regarded as one of the most promising materials for nextgeneration high-power and high-efficiency electronics, due to its cost-effective melt-grown large-scale and low defect density substrate as well as the controllable n-type doping3. \n\n$\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ with $E_{\\mathrm{g}}=4.6\\small{-4.8}\\mathrm{eV}$ , high $E_{\\mathrm{C}}=8\\mathrm{MV/cm}$ and decent intrinsic $\\mu=250\\mathrm{{\\dot{c}m^{2}/V s}}$ has yielded a B-FOM to be around 3000, which is four times GaN and ten times SiC. Being the mainstream of the UWB semiconductor, ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ -based power electronics are expected to bring higher blocking voltage at a lower specific onresistance $(R_{\\mathrm{on,sp}})$ for power switching applications. Tremendous efforts have been dedicated to explore the material property and push the device limit, and hence significant progresses are acquired during the past 5 years. Despite those intriguing achievements, it should be noted that those performances especially the representative device parameter power figure-of-merit $(\\mathrm{P-}\\mathrm{\\dot{F}O M}=\\mathrm{\\dot{BV}}^{2}/R_{\\mathrm{on},\\mathrm{sp}})$ are much inferior to the projected material limit, or even cannot be comparable with the 1-D unipolar limit of the GaN and $\\mathrm{SiC}^{4,5}$ . Like other UWB semiconductors with the difficulties of achieving both highly conductive p- and $\\mathfrak{n}$ -type materials at the meantime, one of the major obstacles is the lack of p-type ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ which can be utilized as the PN homojunction termination for the BV improvement. It was calculated that shallow acceptor does not exist and it was also predicted that the holes are self-trapped inherently6. As a result, unipolar ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power electronics dominate most of the research and few reports are available about the bipolar transport study. Due to the challenge of realizing p-type ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ on lightly-doped n-type ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer, the BV of the vertical ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes was limited, although various types of edge termination (ET) methods were employed7. On the other hand, some wide-bandgap p-type materials like $\\mathrm{NiO}_{x}$ with $E_{\\mathrm{g}}$ of $3.8\\substack{-4\\mathrm{eV}}$ and $\\mathrm{Cu}_{2}\\mathrm{O}$ with $E_{\\mathrm{g}}\\sim3\\mathrm{eV}$ , controllable doping and decent hole mobility of $0.5{-}5\\mathrm{cm}^{2}/\\mathrm{V}s$ turn out to be a good counterpart of p-type ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ to boost the diodes performance8,9. The combination of $\\mathrm{{p-NiO_{x}}}$ and $\\mathrm{n-Ga}_{2}\\mathrm{O}_{3}$ is a feasible route for the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ development, and the recent progress of the $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ PN hetero-junction (HJ) diodes shows a P-FOM of $1.37\\mathrm{GW}/\\mathrm{cm}^{2}$ , which is comparable to the P-FOM value of state-of-the-art Schottky barrier diodes (SBDs)10,11. Even incorporating $\\mathrm{{p-NiO_{x}}}$ into ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ material system, the potential of ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ HJ PN diodes is only explored for less than $10\\%$ of the material limitation. Meanwhile, the conductivity modulation effect is observed in $\\mathrm{Ga}_{2}\\mathrm{O}_{3}\\mathrm{H}]$ PN diodes, indicating the holes can be injected in the $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ layer12. However, under what bias condition and to what extent the conductivity modulation can impact the $R_{\\mathrm{on,sp}}$ are still not explored. In addition, the in-depth understanding of bipolar transport in the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer, especially hole transport and lifetime extraction are still forfeiting. Against the generally believed holes are self-trapped, the hole lifetime is a crucial and fundamental parameter to determine whether the bipolar transport is about to happen and to what extent it will impact the PN diode performances. Another critical issue regards the practical application of UWB PN diode is the requirement of low turn-on voltage $(V_{\\mathrm{on}})$ for high-efficiency application, since the general forward bias $(V_{\\mathrm{F}})$ is limited to be around $3\\mathrm{V}$ . This is very challenging for homo-junction PN diode for wide bandgap semiconductor GaN and SiC with $V_{\\mathrm{on}}\\sim3\\:\\mathrm{V};$ regardless of the even wider bandgap ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ . \n\nIn this article, a general design strategy of UWB semiconductor power diodes is provided to achieve high BV and low $R_{\\mathrm{on,sp}}$ simultaneously through the introduction of hole injection and transport in ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ to minimize the $R_{\\mathrm{on,sp}},$ suppressing the background carrier density to improve the BV, employing low conduction band offset $\\mathrm{\\ttp}{\\mathrm{-}}\\mathrm{\\ttNiO}_{x}$ to reduce $V_{\\mathrm{on}},$ and a composite E management technique with implanted ET and field plate architecture to further strengthen the BV. We setup a milestone of the UWB power diodes by acquiring a BV of $8.32\\mathrm{kV}$ and $\\mathrm{\\bfP}$ - $\\mathrm{FOM}=\\mathrm{BV}^{2}/\\bar{R}_{\\mathrm{on,sp}}$ of $13.21\\mathrm{GW}/\\mathrm{cm}^{2}$ , which is a record P-FOM value among all types of UWB power diodes to date, and it also exceeds the 1-D unipolar limit of GaN and SiC. Meanwhile, a conductivity modulation phenomenon induced bipolar transport of electron and hole pairs is identified with hole lifetime determined to be 5.4–23.1 ns. Considering some real application circumstances of diodes at a $V_{\\mathrm{F}}$ of $3\\mathrm{V}$ , benchmarking of the BV and $R_{\\mathrm{on,sp}}$ extracted at $V_{\\mathrm{F}}=3\\:\\mathrm{V}$ also shows a record P-FOM value to date, validating the great promise of UWB power diodes for nextgeneration high-voltage and high-power electronics. \n\n# Results and discussions \n\nHigh BV and low $R_{\\mathrm{on,sp}}$ design strategy and implementation. The most intriguing aspect of ${\\beta\\mathrm{-}{\\mathrm{}G a}_{2}}{\\mathrm{O}}_{3}$ is that its native substrate can be substantially grown by the melt-grown methodology, which lays a basic foundation for low-cost and large-diameter with low defect density substrate13. The ${\\beta\\mathrm{-}{\\mathrm{}G a_{2}O_{3}}}$ epi-layer can be epitaxied by various routes, such as molecular beam epitaxy, metalorganic chemical vapor deposition (MOCVD), mist-CVD, halide vapor phase epitaxy (HVPE), and some other low-cost techniques14,15. HVPE is the most widely adopted methodology for balancing the epitaxial speed, substrate size, defect density, and complicity. The ${\\beta}{-}\\mathrm{{Ga}}_{2}\\mathrm{{O}}_{3}$ background doping regulation is a challenge, resulting in a non-controllable electron density of $2{-}4\\times10^{16}\\mathrm{cm}^{-3}$ . Unintentional doping from precursors like Si or H, and defects like O vacancies all contribute to the n-type conduction in the ${\\beta\\mathrm{-}{\\mathrm{}G a}_{2}}{\\mathrm{O}}_{3}$ layer. \n\nIdeal power devices should embrace high BV and low $R_{\\mathrm{on,sp}}$ to provide high blocking capability and low loss simultaneously16. In order to improve the BV of the UWB ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes, the minimal doping concentration is the first essential, since the slope of the E is governed by the doping concentration16. Summarized in Supplementary Fig. 1, it was found that the BV of the reported ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes is limited to be less than $3\\mathrm{kV}$ , where the donor concentration is the major tyranny. Some other subsidiary factors like ETs or advanced E management techniques are all prerequisites for a minimized peak E at the anode edge to achieve a high desirable BV. PN junction is one of the most straightforward approaches to suppress the peak E at the interface. However, the forfeit of the ${\\tt p}{\\tt-}\\tt G a_{2}\\mathrm{O}_{3}$ on the $\\mathrm{n-Ga}_{2}\\mathrm{O}_{3}$ makes the PN home-junction an impossible mission to further explore the maximum BV potentials of diodes. It should be noted that only extending the spacing of two electrodes to increase the BV is of marginal value by sacrificing the $R_{\\mathrm{on,sp}}$ and averaged E. In terms of manipulating the $R_{\\mathrm{on,sp}},$ to increase the doping concentration seems to be the simplest, however, the BV will be essentially compromised. A unique physical phenomenon of power diode, which is called conductivity modulation of the PN or PIN junction at forward bias will substantially guarantee a low $R_{\\mathrm{on,sp}}$ even at a low doping concentration. Regardless of the challenge on the formation of PN homo-junction, the high $V_{\\mathrm{on}}>4\\mathrm{V}$ is another suffering for the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ homo-junction PN diodes. \n\nRecently, the implementation of the $\\mathrm{\\ttp\\mathrm{-}N i O_{\\mathrm{x}}}$ into the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ system opens up another route for expanding the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ application from the SBDs to the HJ PN diode17–20. Although the performance of the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ HJ diode is still inferior to the SBDs at current stage, however, we argue that some fundamental limitations which have haunted the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes research for a decade could be essentially clarified. First, $\\mathrm{{p-NiO_{x}}}$ flavors a low conduction band offset of ${\\sim}2.1\\mathrm{eV}$ such that the high $\\mathrm{\\DeltaV_{on}}$ issue of the homo-junction could be partially resolved. Second, with a PN HJ structure, the conductivity modulation is theoretically expected so that the $\\mathrm{R}_{\\mathrm{on,sp}}$ can be minimized at a low doping concentration and high $V_{\\mathrm{F}}$ . In addition, by combining the ETs and advanced E management, the BV can be further enhanced. Comparison of the E management strategies is summarized in Supplementary Fig. 2. \n\nFigure 1a shows the 3-D cross-sectional image of two representative $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ HJ PN diodes, the top view image is exhibited as Fig. 1b, and the false-colored scanning electron microscopy (SEM) image at the crucial area of the anode edge is listed in Fig. 1c. In the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes, the doping concentration of the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ epi-layer is suppressed from the $2\\times10^{16}\\mathrm{cm}^{-3}$ to around $5{-}7\\times10^{15}\\mathrm{cm}^{-3}$ for two wafers with different thicknesses by adopting a long duration of the oxygen thermal anneal process, as shown in Fig. $\\mathbf{1}\\mathbf{d}^{21}$ . $C{-}V$ curves are shown in Supplementary Fig. 3. Heavily doped $\\mathrm{{\\ttp}-N i O_{x}}$ layer on top is utilized to form an Ohmic contact, as described in Fig. 1e. The simulated energy band diagram of the $\\mathrm{p{-NiO}_{x}/n{-G a_{2}O_{3}}\\tilde{H}J}$ is shown in Fig. 1f with the conduction band and valance band offset to be $\\bar{2.15}\\mathrm{eV}$ and $2.8\\mathrm{eV}$ , respectively. The ET process by $\\mathbf{Mg}$ doping to form a high-resistivity region underneath the electrode is utilized to withstand a high E and the coupled field plate is implemented to further mitigate crowded peak E at the anode edge15. \n\nDiodes characterizations. Figure 2a compares the log-scale forward current-forward bias-ideality factor $\\left(I_{\\mathrm{F}}{-}V_{\\mathrm{F}}{-}\\eta\\right)$ characteristics of two $\\mathrm{Ga}_{2}\\mathrm{O}_{3}\\mathrm{H}]$ PN diodes with ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ thickness $\\left(\\mathrm{T}_{\\mathrm{Ga2O3}}\\right)$ of 7.5 and $13\\upmu\\mathrm{m}$ at a radius of $75\\upmu\\mathrm{m}$ . The kink effect observed at $V_{\\mathrm{F}}$ around $1.5\\mathrm{V}$ is related to the variation of the barrier height and ideality factor, which is most likely to be induced by the two different barriers connected in parallel. $I_{\\mathrm{F}}$ on/off ratio of $10^{9}-10^{10}$ and $\\eta$ smaller than 2 can last for 4–5 decades of the $I_{\\mathrm{F}}$ . Figure 2b shows the linear-scale forward $I_{\\mathrm{F}^{-}}V_{\\mathrm{F}^{-}}R_{\\mathrm{on},\\mathrm{sp}}$ curves of the same diodes as Fig. 2a. Even with a PN HJ structure, a relatively decent $V_{\\mathrm{on}}=1.8\\:\\mathrm{V}$ is acquired, which is much smaller than the $V_{\\mathrm{on}}$ of SiC and GaN PN diodes. The small $V_{\\mathrm{on}}$ is benefited from two aspects, the small conduction band offset between $\\mathrm{\\ttp\\mathrm{-}N i O_{x}}$ and $\\bar{\\bf n}{-}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ and the interface recombination current17. Minimal Diff. $R_{\\mathrm{on,sp}}$ is extracted to be 2.9 and $5.24\\mathrm{m}\\Omega\\mathrm{cm}^{2}$ for $T_{\\mathrm{Ga}2\\mathrm{O}3}=7.5$ and $13\\upmu\\mathrm{m}$ , respectively. Unlike SBDs with increased $R_{\\mathrm{on,sp}}$ at an increased $V_{\\mathrm{F}}$ the $R_{\\mathrm{on,sp}}$ of the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ HJ PN diodes drops at an increased $V_{\\mathrm{F}},$ most likely due to bipolar transportinduced conductivity modulation effect. It should be noted that such conductivity modulation effect is the key to enable the simultaneous achievement of low $R_{\\mathrm{on,sp}}$ and high BV. Figure 2c describes the radius-dependent $I_{\\mathrm{F}^{-}}V_{\\mathrm{F}^{-}}R_{\\mathrm{on},\\mathrm{sp}}$ curves for diodes with $T_{\\mathrm{Ga2O3}}=13\\upmu\\mathrm{m}$ . Log-scale $I_{\\mathrm{F}}–V_{\\mathrm{F}}$ characteristic is summarized in Supplementary Fig. 4. By increasing the radius, the insulating $\\mathbf{Mg}$ implanted region constitutes to a smaller portion of the area so that $R_{\\mathrm{on,sp}}$ decreases when radius increases. The resistance (Res.) contribution from each layer based on the equation Res. $=$ thickness/ $(N_{\\mathrm{D}}\\times\\mu\\times q)$ is summarized in Supplementary Fig. $5^{22}$ . For diodes with $T_{\\mathrm{Ga2O3}}=7.5/13\\upmu\\mathrm{m}$ , $N_{\\mathrm{D}}=6\\times$ $10^{15}\\mathrm{cm}^{-3}$ , $\\mu=200\\mathrm{cm}^{2}/\\mathrm{Vs},$ and $q=1.6\\times10^{-19}\\mathrm{C},$ the resistance of the drift layer is calculated to be $3.89/6.77\\mathrm{m}\\Omega\\mathrm{cm}^{2}$ . It should be noted that this calculation is based on the low-level injection prerequisite. At $V_{\\mathrm{F}}=5\\mathrm{V}.$ , conductivity modulation effect of the HJ PN diode begins to dominate so that the $R_{\\mathrm{on,sp}}$ drops, which is favorable for resistance minimization. Figure 2d and e summarizes the $\\mathrm{T}$ -dependent linear-scale $I{-}V{-}\\bar{R}_{\\mathrm{on,sp}}$ and log-scale $\\boldsymbol{I_{\\mathrm{F}}}.$ 一 $V_{\\mathrm{F}}$ of the diode with radius $=75\\upmu\\mathrm{m}$ and $T_{\\mathrm{Ga2\\dot{O}3}}=13\\upmu\\mathrm{m}$ . On/off ratios of $10^{10}$ and $10^{8}$ are achieved at $T=25^{\\circ}\\mathrm{C}$ and $150^{\\circ}\\mathrm{C},$ respectively. At all temperature ranges, the differential (Diff.) $R_{\\mathrm{on,sp}}$ drops at an increased $V_{\\mathrm{F}}$ verifying the conductivity modulation effect of the $\\mathrm{Ga}_{2}\\mathrm{O}_{3}\\ \\mathrm{HJ}$ PN diodes. Figure 2f shows the extracted T-dependent ideality factor $\\eta$ and $R_{\\mathrm{on,sp}}$ from temperatures of $25\\mathrm{-}150^{\\circ}\\mathrm{C}$ . The $\\boldsymbol{\\upeta}$ is extracted from the forward current equation $J{=}J_{\\mathrm{s}}(\\exp(q V_{\\mathrm{F}}/\\eta k T)-1)$ , whereas $J_{s}$ is the reverse saturation current, $\\mathrm{v_{F}}$ is the applied forward bias, $q$ is the electron charge, $\\mathbf{k}$ is the Boltzmann’s constant, and $T$ is the absolute temperature. The $\\eta$ is extracted to be around 1.5 at $T=25^{\\circ}\\mathrm{C}.$ . \n\n![](images/bfc894c5f8efbb724fcff8b5d045f77b802330b3acb80b383f2eb5fa03fe1a73.jpg) \nFig. 1 UWB power diodes design and implementation. a 3-D cross-sectional schematic of the $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ power diodes with HJ architecture and composite electric field management. b Top view of a fabricated $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ power diode. c False-colored SEM image of the cross-sectional anode field plate region with ${\\mathsf{p}}{\\mathsf{-N i O}}_{\\mathsf{x}}$ thickness of $400\\mathsf{n m}$ . d Extracted carrier concentration of two representative samples with concentration of $5\\times10^{15}–7\\times10^{15}\\mathsf{c m}^{-3}$ . e Currentvoltage behavior of the ${\\mathsf{N i}}$ pads on $\\mathsf{p}{\\mathsf{-N i O}}_{\\mathsf{x}}$ with $N_{\\mathsf{A}}=10^{19}\\mathsf{c m}^{-3}$ , showing an Ohmic contact. f Simulated band diagram of the $\\mathsf{p}{\\mathsf{-N i O}}_{\\mathsf{x}}/\\mathsf{n}{\\mathsf{-G a}}_{2}\\mathsf{O}_{3}$ HJ structure. The band bending occurs in $\\mathsf{n}\\mathsf{-}\\mathsf{G a}_{2}\\mathsf{O}_{3}$ and the conduction band offset is only $2.1\\mathrm{eV},$ , showing the great promise of low $V_{\\mathsf{o n}}$ even for a UWB material. \n\n![](images/6667576bcda1d4466774bb85c1d6742a3be0cc39561d0b2957aa7547953df021.jpg) \nFig. 2 UWB $\\mathtt{G a}_{2}\\mathtt{O}_{3}$ power diodes forward characteristics. a Forward current-voltage-ideality factor characteristics of two ${\\mathsf{G a}}_{2}{\\mathsf{O}}_{3}$ power diodes with $T_{\\mathsf{G a2O3}}=7.5$ and $13\\upmu\\mathrm{m}$ . b Forward current–voltage-specific on-resistance $R_{\\tt o n,\\tt s p}$ characteristics of the same diodes as a. A decent $V_{\\mathsf{o n}}=1.8\\:\\vee$ with minimal Diff. $R_{\\tt o n,s p}=2.9$ and $5.24\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ as well as extracted overall $R_{\\tt o n,s p}$ $\\langle\\textcircled{a}V_{\\mathsf{F}}=3\\mathsf{V}\\rangle$ of 15.3 and $29.5\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ for $T_{\\tt G a2O3}=7.5$ and ${13\\ \\upmu\\mathrm{m}}$ are achieved. c Radius-dependent forward current-voltage-resistance curves for diodes with $T_{\\mathsf{G a2O3}}=13\\upmu\\mathrm{m}$ . T-dependent d log-scale and e linear-scale forward characteristics of diode with $T_{\\mathsf{G a2O3}}=13\\upmu\\mathrm{m}$ . $_{\\mathsf{O n/O\\dag\\dag}}$ ratio of $10^{10}$ and $\\scriptstyle10^{8}$ are achieved for $T=25^{\\circ}{\\mathsf{C}}$ and ${150^{\\circ}}\\mathsf C,$ respectively. At all temperatures, $R_{\\tt o n,\\tt s p}$ drops when $V_{F}$ increases, verifying the conductivity modulation effect. f Extracted $\\intercal$ -dependent ideality factor and $R_{\\tt o n,s p}$ values as e. \n\nBased on the simulation, it is very interesting to find that hole concentration in the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer at the HJ-interface is comparable with the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ doping concentration of $6\\times\\dot{10}^{15}\\mathrm{cm}^{-3}$ at $V_{\\mathrm{F}}=3.5\\:\\mathrm{V}_{\\mathrm{:}}$ as shown in Supplementary Figs. 6 and 7. That is to say, the hole injection-related conductivity modulation can help to reduce the $R_{\\mathrm{on,sp}}$ only with $V_{\\mathrm{F}}{\\geq}3.5\\dot{\\mathrm{V}}$ since the hole is with more than 1 order of magnitude lower mobility. The simulation result is in good agreement with the forward $I_{\\mathrm{F}}–V_{\\mathrm{F}}$ characteristic, since the $R_{\\mathrm{on,sp}}=7\\:\\mathrm{m}\\Omega\\:\\mathrm{cm}^{2}$ (at \n\n$V_{\\mathrm{F}}=3.5\\:\\mathrm{V},$ roughly equals to the resistance summary of $\\boldsymbol{\\mathrm{\\tt~p~}}$ -side Ohmic contact, $\\mathrm{{\\ttp}\\mathrm{-}N i O_{x}}$ layer, $\\mathrm{n-Ga}_{2}\\mathrm{O}_{3}$ drift layer, $\\mathrm{n^{+}{-}G a_{2}O_{3}}$ substrate and $\\mathfrak{n}$ -side Ohmic contact. In other words, the hole injection and conductivity modulation are negligible at the $V_{\\mathrm{F}}$ range of $V_{\\mathrm{on}}=1.8\\:\\mathrm{V}$ to $3.5\\mathrm{V}$ , due to significant valance band offset between $\\mathsf{p}{\\mathrm{-NiO}}_{x}$ and $\\mathrm{n-Ga}_{2}\\mathrm{O}_{3}$ , so that few holes can be injected across this barrier. At $V_{\\mathrm{F}}\\sim3.5\\:\\mathrm{V}$ , holes are injected from $\\mathrm{{p-NiO_{x}}}$ to $\\mathrm{n-Ga}_{2}\\mathrm{O}_{3}$ most likely via trap assisted tunneling and hopping mechanisms. By increasing the $\\mathrm{v_{F}}$ beyond $3.5\\mathrm{V}$ to lower the PN HJ barrier, more holes are injected into $\\mathrm{n-Ga}_{2}\\mathrm{O}_{3}$ layer and hence high level injection phenomenon will raise the electron concentration in the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer to maintain the charge neutrality condition. Therefore, the $\\mathrm{R}_{\\mathrm{on},\\mathrm{sp}}$ is further reduced when the $V_{\\mathrm{F}}$ is increased. At $V_{\\mathrm{F}}=5\\mathrm{V}$ , the hole concentration is simulated to be $3.8\\times10^{16}\\mathrm{cm}^{-3}$ and $6\\times10^{15}\\mathrm{cm}^{-3}$ at HJinterface and $6\\upmu\\mathrm{m}$ away from the HJ-interface, respectively. The averaged hole (also electron) concentration is extracted to be $1.9\\times10^{16}\\mathrm{cm}^{-3}$ within this $6\\mathrm{-}\\upmu\\mathrm{m}$ range, by integrating concentration and then divided by the total length of $6\\upmu\\mathrm{m}$ . Therefore, the resistance of the significant hole injection region is roughly calculated to be $1.32\\mathrm{m}\\Omega\\mathrm{cm}^{2}$ , by considering the electron mobility of $150~\\mathrm{cm}^{2}/\\mathrm{Vs}$ at this electron concentration. By adding up another $7{\\cdot}||\\mathbf{m}$ low level injected $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ layer resistance of 6.77/ $1\\bar{3}\\times7=3.65\\:\\mathrm{m}\\Omega\\:\\mathrm{cm}^{2}$ , the $13\\mathrm{-}\\upmu\\mathrm{m}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ drift layer owns a $R_{\\mathrm{on,sp}}$ of $4.97\\mathrm{m}\\Omega\\mathrm{cm}^{2}$ . This estimation of the $R_{\\mathrm{on,sp}}$ coincides with our extracted $R_{\\mathrm{on,sp}}$ from the $I_{\\mathrm{F}}–V_{\\mathrm{F}},$ verifying the correctness of the explanation, hole concentration simulation, and calculation of the hole injection into the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer. \n\nThe T-dependent reverse $I{-}V$ characteristics of diode with $T_{\\mathrm{Ga2O3}}{=}7.5~{\\upmu\\mathrm{m}}$ are plotted in Fig. 3a from $T=25\\mathrm{-}150^{\\circ}\\mathrm{C}$ . By increasing the $T,\\quad I_{\\mathrm{R}}$ increases, indicating a non-avalanche breakdown behavior. Even at $T=150^{\\circ}\\mathrm{{C}},$ the $I_{\\mathrm{R}}$ is just $\\mathrm{1}\\mathrm{mA}/\\mathrm{cm}^{2}$ at a reverse bias of $3\\mathrm{kV}$ . By further pushing the reverse bias to $5.1\\mathrm{kV}$ we observe a hard breakdown with \n\n![](images/3ec3957c7f825631944d4756c340e6427aed9855ff9b97138c2d67b22da72318.jpg) \nFig. 3 UWB $\\mathtt{G a}_{2}\\mathtt{O}_{3}$ power diodes with high breakdown voltages. a $\\intercal$ -dependent reverse current–voltage characteristics of diode with $T_{\\mathsf{G a2O3}}=7.5\\upmu\\mathrm{m}$ . With increased $T,I_{{\\sf R}}$ increases, indicating a non-avalanche breakdown. Room temperature reverse current–voltage characteristics of diodes with $T_{\\mathsf{G a2O3}}=7.5\\upmu\\mathrm{m}$ (b) and ${13\\upmu\\mathrm{m}}$ $(\\bullet)$ at various radiuses. A BV of $5.1\\mathsf{k V}$ and $8.32\\mathsf{k V}$ are achieved for diodes with $T_{\\mathsf{G a2O3}}=7.5$ and $13\\upmu\\mathrm{m}_{i}$ yielding an averaged E of $6.45\\mathsf{M V/c m}$ and $6.2M V/\\mathsf{c m},$ respectively. d Simulated E distribution of the diode with $\\mathsf{B V}=8.32\\mathsf{k V}$ and $\\mathsf{T}_{\\mathsf{G a2O3}}=13\\upmu\\mathrm{m}$ . Due to the small $N_{\\mathsf{D}}=6\\times10^{15}\\mathsf{c m}^{-3},$ , a fully depletion and a small E slope of the drift layer is observed. \n\n$T_{\\mathrm{Ga2O3}}=7.5\\upmu\\mathrm{m}$ , as indicated in Fig. 3b. The averaged $E$ field is calculated to be around $6.45\\mathrm{MV/cm}$ by considering $E=5.1\\mathrm{kV}/\\$ $(0.4\\upmu\\mathrm{m}+7.5\\upmu\\mathrm{m})$ . Combined with the $R_{\\mathrm{on,}s\\mathrm{p}}=2.9\\mathrm{\\m}\\Omega\\mathrm{cm}^{2}$ , the $\\mathrm{P-FOM}=\\mathrm{BV}^{\\dot{2}}/R_{\\mathrm{on,}s\\mathrm{p}}$ is yielded to be $8.97\\dot{\\mathrm{GW}}/\\mathrm{cm}^{2}$ . As for the diode with $T_{\\mathrm{Ga2O3}}=13\\upmu\\mathrm{m}$ , a maximum BV of $8.32\\mathrm{kV}$ is acquired at an $I_{\\mathrm{R}}=0.2\\ \\mathrm{mA}/\\mathrm{cm}^{2}$ , as exhibited in Fig. 3c. The asmeasured figure is shown in Supplementary Fig. 8. This $\\mathrm{BV}=8.32\\mathrm{kV}$ is the highest BV value among all ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power FETs and diodes to date. As a result, the P-FOM is calculated to be $(8.32\\mathrm{kV})^{2}/5.24\\mathrm{m}\\Omega\\mathrm{cm}^{2}=13.21\\mathrm{GW}/\\mathrm{cm}^{2}$ . Besides the record P-FOM, this HJ PN diode also has a high averaged $E=8.32\\mathrm{kV}/$ $(0.4\\upmu\\mathrm{m}+13\\upmu\\mathrm{m})=6.2\\mathrm{MV/cm}$ . Figure 3d describes the E simulation result of the HJ PND with $T_{\\mathrm{Ga2O3}}=13\\upmu\\mathrm{m}$ and $\\mathrm{BV}=8.32\\mathrm{kV}$ . The simulated peak $\\mathrm{~E~}$ in the $\\mathrm{{\\ttp}-N i O_{x}}$ layer is around $4.9\\ \\mathrm{MV/cm},$ which is slightly lower than its theoretical limit, considering the $3.9\\mathrm{eV}$ bandgap. The peak $\\mathrm{~E~}$ at the $\\mathrm{\\ttp\\mathrm{-}N i O_{x}}$ side is lower when compared with the peak $E$ at the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ side, due to much higher dielectric constant of $\\mathrm{{\\ttp}\\mathrm{-}N i O_{x}}$ . Due to the small $N_{\\mathrm{D}}$ and the depletion effect from the $\\mathrm{{p-NiO_{x}}}$ as well as the functionalities of the ET and coupled field plate, a fully depletion and small E slope are observed in the drift layer, resulting a peak $E{=}7\\ensuremath{\\mathrm{MV/cm}}$ in the $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ at the HJ-interface. \n\nHoles in $\\mathbf{Ga}_{2}\\mathbf{O}_{3}$ layer. Similar to other UWB semiconductors like diamond, BN, and AlN, high ionization efficiency of n- and p-type doing simultaneously turns out to be a big challenge, considering the UWB nature of those UWB semiconductor materials. The direct observation of conductivity modulation is a straightforward evidence of bipolar transport and hole existence in the $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ layer, which deviates from the general prediction that holes are less likely to occur in ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ . Three reasons are attributed to the challenge of acquiring holes in $\\mathrm{Ga}_{2}\\mathrm{O}_{3}.$ no calculated shallow acceptors, large effective mass from the flat valance band, and free holes tend to be self-trapped by polarons. However, we argue that with the unique PN HJ structure under high $V_{\\mathrm{{F}}}$ condition, holes from the heavily-doped $\\mathrm{\\ttp\\mathrm{-}N i O_{x}}$ are capable of being injected to the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer, although the hole mobility is relatively low. Under a very positive $V_{\\mathrm{F}}$ condition (e.g., $5\\mathrm{V},$ ), energy band of the $\\mathrm{{\\ttp}-N i O_{x}}$ is pulled down so that holes at the Fermi tail witness no significant barrier height to travel across the PN HJ-interface and then diffuse in the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer, leading to the conductivity modulation effect. In other words, the holes can be manufactured in the UWB ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer by hole injection at a very positive $V_{\\mathrm{F}}$ . In order to verify the hole transportation and survival in the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ not so short by self-trapping effect of the polarons, hole lifetime extraction or measurement is urgently needed. \n\nThe reverse recovery measurement technique is implemented to determine the hole lifetime in the ${\\mathrm{Ga}}_{2}{\\mathrm{\\bar{O}}}_{3}$ layer, and the schematic of the measurements are summarized in Supplementary Fig. $9\\mathsf{a}^{23}$ . Once the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ diode is switched from positive $V_{\\mathrm{F}}$ to a reverse bias, a period of time is needed to remove holes from the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ either via electron-hole pair recombination or to be trapped by polarons. The hole lifetime $(\\tau_{\\mathfrak{p}})$ can be determined by the equation $\\tau_{\\mathrm{p}}=t_{\\mathrm{sd}}/(\\mathrm{erf}^{-1}(I_{\\mathrm{F}}/(I_{\\mathrm{F}}+I_{\\mathrm{R}})))^{\\frac{\\hbar}{2}}$ , whereas $t_{\\mathrm{sd}},I_{\\mathrm{F}},$ and $I_{\\mathrm{R}}$ represent charge storage time, forward current, and reverse current, respectively24. During the reverse recovery measurement, the $V_{\\mathrm{F}}$ is extracted to be $2.97\\mathrm{\\bar{V}}$ and $4.73\\mathrm{V}$ for injection current of $5\\mathrm{mA}$ and $25\\mathrm{mA}$ , respectively, at a diode radius of $40\\upmu\\mathrm{m}$ . Meanwhile, the subsequently applied reverse bias is $-8\\mathrm{V}$ . The reverse recovery and input–output measurement of the pulsed current–voltage characteristics of the UWB $\\mathrm{Ga}_{2}\\mathrm{O}_{3}\\ \\mathrm{H}]$ PN diode at a diode current of $5\\mathrm{mA}$ is shown in Fig. 4a. For the HJ PN diode, the $I_{\\mathrm{F}}$ is $5\\mathrm{mA}$ which is 3 orders of magnitudes more than $I_{\\mathrm{R}},$ so that $I_{\\mathrm{F}}/(I_{\\mathrm{F}}+I_{\\mathrm{R}})$ can be simplified to be 1. Then the $\\tau_{\\mathrm{{p}}}$ can be simplified to $\\pi/4\\times t_{\\mathrm{sd}},$ which is ${\\sim}80\\%$ of the $t_{\\mathrm{sd}}$ when the diode is switched until the anode current is recovered to be around 0. Therefore, hole lifetime $\\tau_{\\mathrm{{p}}}$ is determined to be 23.1 ns at a forward injection current $\\boldsymbol{I_{\\mathrm{F}}}$ of $5\\mathrm{mA}$ . The $\\tau_{\\mathrm{{p}}}$ dependence on $I_{\\mathrm{F}}$ is summarized in Fig. 4b, with a minimal $\\tau_{\\mathrm{{p}}}$ of $5.4\\mathrm{ns}$ . In order to exclude the subsidiary impact on the measurements, the reverse recovery measurement is performed on ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ SBD (Supplementary Fig. 9b) and the recovery time in the SBD is determined to be $1.8\\mathrm{ns}$ which is 1 order of magnitude lower when compared with the HJ PN diode. By injecting holes into the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer at high $V_{\\mathrm{F}},$ the hole lifetime is then determined to be 5.4–23.1 ns. By combining the calculated hole effective mass $({m_{\\mathrm{p}}}^{*})$ of $4.46m_{\\mathrm{o}}$ (Supplementary Fig. 10), the hole mobility $(\\mu_{\\mathrm{p}})$ can be roughly estimated by the equation $\\mu_{\\mathrm{p}}{=}q\\times\\tau_{\\mathrm{p}}/m_{\\mathrm{p}}^{\\ *}$ , yielding the $\\mu_{\\mathrm{p}}$ to be $\\mathrm{{'}}1.93\\mathrm{{-}}8.3\\mathrm{{cm}^{2}/\\mathrm{{\\bar{V}s}}}$ . \n\n![](images/50a9a2e9458cc3120757d6ff571efc57e943d7cb8c3460d0ce94b1387b6df991.jpg) \nFig. 4 Hole lifetime determination in $\\mathfrak{G a}_{2}\\mathfrak{O}_{3}$ layer. a Time-dependent of the reverse recovery characteristics of $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ HJ PN diode at a forward injection current of $5\\mathsf{m A}$ . b Lifetime dependence on the forward injection current with current ranges from $5\\mathsf{m A}$ to $25{\\mathsf{m A}}$ . At current of $5\\mathsf{m A}.$ , the lifetime is determined to be 23.1 ns. At high $V_{F}$ condition, holes diffuse from ${\\mathsf{p}}{\\mathsf{-N i O}}_{\\mathsf{x}}$ to $\\mathsf{n}{\\mathsf{-}}\\mathsf{G a}_{2}\\mathsf{O}_{3}$ without seeing obvious barrier, so that the hole lifetime in the ${\\sf G a}_{2}{\\sf O}_{3}$ layer can be determined. \n\nPerformance benchmarking. The combination of the conductivity modulation induced low $R_{\\mathrm{on,sp}}$ and low doping concentration as well as the composite $\\mathrm{~E~}$ regulation led record BV renders a substantial performance enhancement by setting a record P-FOM of all UWB power diodes (Fig. 5a), including ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ , diamond, and high Al$\\mathrm{\\bar{Al}}_{x}\\mathrm{Ga}_{1-x}\\mathrm{N}$ $(x>60\\%)$ power diodes25–44. Compared with all other ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes, the BV of this work is around three times the previously reported best BV of $2.9\\mathrm{kV}$ with a lower $R_{\\mathrm{on,sp}}$ The most enticing aspect of this work is that the performance of the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ device exceeds the 1-D unipolar limit of the SiC and GaN. In terms of real application of the HJ PN diode in the circuit, the overall $R_{\\mathrm{on},\\mathrm{sp}}$ at a general $V_{\\mathrm{F}}=3\\mathrm{V}$ instead of the minimal differential $R_{\\mathrm{on,sp}}$ is more realistic. In order to eliminate the impact of $V_{\\mathrm{on}},$ an overall $R_{\\mathrm{on,sp}}$ of $15.3\\mathrm{m}\\Omega\\mathrm{cm}^{2}$ and $29.5\\mathrm{m}\\Omega\\mathrm{cm}^{2}$ are extracted for $T_{\\mathrm{Ga2O3}}$ of $7.5\\upmu\\mathrm{m}$ and $13\\upmu\\mathrm{m}$ at a $V_{\\mathrm{F}}=3\\mathrm{V}$ , respectively, as shown in Fig. 2b. Benchmarking against all other state-of-the-art representative diodes, including SiC SBDs/JBS diodes/PN diodes and GaN SBDs/ PN diodes with extracted $R_{\\mathrm{on,sp}}$ at a fixed $V_{\\mathrm{F}}=3\\mathrm{V}_{\\mathrm{:}}$ our ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}{\\mathrm{HJ}}$ PN diodes achieve a record of nowadays power diodes, as compared in Fig. $5\\mathrm{b}^{33,45-53}$ . Even under the real application circumstance, the $\\mathrm{P-FOM}=\\mathrm{BV}^{2}/R_{\\mathrm{on,sp}}$ of the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes still surpasses the 1-D unipolar limit of the SiC. These intriguing results verify the great promise of UWB semiconductor ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes for nextgeneration high-voltage and high-power electronics. \n\n![](images/c202cb217b77c43dfe06d0c4298a97a1c16b4f9bc5724f4f01e9f9ce43fee7ff.jpg) \nFig. 5 Benchmarking UWB $\\mathfrak{G a}_{2}\\mathfrak{O}_{3}$ power diodes against state-of-the-art other diodes. a Minimal $R_{\\tt o n,\\tt s p}$ versus BV of some representative UWB power diodes, including ${\\mathsf{G a}}_{2}{\\mathsf{O}}_{3},$ diamond, and high-Al AlGaN, which are reported in the literatures. Our $\\mathsf{G a}_{2}\\mathsf{O}_{3}$ power diodes set a milestone for the UWB power diodes by breaking the 1-D unipolar figure-of-merit limit of GaN and SiC. b Extracted $R_{\\tt o n,s p}(\\textcircled{\\alpha}3\\vee)$ versus BV of some highest performance GaN, SiC, and diamond diodes. By considering some real application circumstances, the $R_{\\circ\\mathsf{n},\\mathsf{s p}}=3\\mathsf{V}/(\\mathsf{I}_{\\mathsf{F}}@3\\mathsf{V})$ is preferred over the minimal $R_{\\tt o n,\\tt s p}$ to eliminate the impact of the $V_{\\mathsf{o n}}$ . GaN and SiC PN diodes are excluded due to the $V_{\\mathrm{on}}\\sim3\\:\\vee$ . Our UWB power diodes demonstrate a substantial enhancement of the performance over other diodes by surpassing the 1-D unipolar limit of the SiC. The $R_{\\tt o n,\\tt s p}$ extraction for lateral diodes is yielded by $R_{\\tt o n,s p}=$ on-resistance $\\times$ (anode–cathode spacing $+1.5\\upmu\\mathrm{m}$ transfer length for both electrodes). \n\nIn summary, we show that UWB semiconductor ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ power diodes are capable of delivering a record high $\\mathrm{BV}^{2}/R_{\\mathrm{on},\\mathrm{sp}},$ which breaks the 1-D unipolar limit of the SiC and GaN figure-of-merit. The incorporation of suppressed background doping, HJ PN structure, and the composite electric field management technique yields a high BV which makes the averaged electric field approach the material limit. Taking advantage of the hole injection as well as the conductivity modulation, the $R_{\\mathrm{on,sp}}$ can be essentially minimized even the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ is with a low doping concentration. The hole lifetime is determined to be 5.4–23.1 ns, which verifies the existence of the hole in the ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ layer. By carefully engineering the energy band offset, a decent $V_{\\mathrm{on}}$ can also be derived for a high efficiency rectifying. This unique technology by implementing the low doping material, electric field suppression, hole injection as well as the conductivity modulation, and energy band engineering offers an effective route for the innovation of other UWB power diodes, such as diamond, BN, high Al mole fraction $\\mathrm{\\mathbf{Al_{x}G a_{1-x}\\bar{N}}}$ . \n\n# Methods \n\nFabrication of UWB $\\boldsymbol{\\mathsf{G a}}_{2}\\boldsymbol{\\mathsf{O}}_{3}$ power diodes. ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ epi-wafers with epi-layer thicknesses of $7.5\\upmu\\mathrm{m}$ and $13\\upmu\\mathrm{m}$ were epitaxial by HVPE on a (001) substrate with substrate doping concentration of $2\\times\\mathrm{i}0^{19}\\mathrm{cm}^{-3}$ . Substrates were first thinned down from $650\\upmu\\mathrm{m}$ to $300\\upmu\\mathrm{m}$ by polishing to minimize on-resistance. Then, $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ epi-wafers were annealed in the low-pressure-CVD furnace at $500^{\\circ}\\mathrm{C}$ under the $\\mathrm{O}_{2}$ ambient to partially compensate the donors in the epi-layer. N-side Ohmic contacts were formed by evaporating Ti/Au metals followed with rapid thermal anneal at $450^{\\circ}\\mathrm{C}$ . Angle-dependent $\\mathbf{Mg}$ ion implantation was utilized to form a highresistivity layer to serve as the ET. Bi-layers of $\\mathrm{\\Deltap{-}N i O_{x}}$ were sputtered at room temperature with first and second layer doping concentration of $1\\times10^{18}\\mathrm{cm}^{-3}$ and $1\\times\\dot{1}0^{19}\\mathrm{cm}^{-3}$ , respectively. The doping concentration of the $\\mathrm{{\\ttp}-N i O_{x}}$ layer was confirmed by the Hall measurements and the Hall mobility of the second $\\mathrm{\\Deltap{-}N i O_{x}}$ layer is $1.1\\mathrm{cm}^{2}/\\mathrm{Vs}$ . P-side Ohmic contacts were formed by depositing Ni/Au layers. The field plate was constructed by depositing $300\\mathrm{nm}$ of $\\mathrm{SiO}_{2}$ , $\\mathrm{SiO}_{2}$ etching, and field plate metal evaporation. A summary of the device process schematic flow is shown in Supplementary Fig. 11. \n\nDevice characterizations. The forward $I{-}V$ and $C{-}V$ characteristics were carried out by the Keithley 4200 semiconductor analyzer systems. Reverse $I{-}V$ measurements were performed by Agilent B-1505A high voltage semiconductor analyzer systems with extended high-voltage module up to $10\\mathrm{kV}$ . The hole lifetime measurements were carried out by reverse recovery measurement methods as Supplementary Fig. 9. \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. The reason for controlled access is due to privacy issue. The data is available from the corresponding author H.Z. for research purposes and the corresponding author will send the data within one week once received the request. \n\n# Code availability \n\nThe simulation code that supports the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. The reason for controlled access is due to privacy issue. The data are available from the corresponding author H.Z. for research purposes and the corresponding author will send the data within one week once received the request. \n\nReceived: 2 November 2021; Accepted: 22 June 2022; Published online: 06 July 2022 \n\n# References \n\n1. Pearton, S. J. et al. A review of ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ materials, processing, and devices. Appl. Phys. Rev. 5, 011301 (2018). \n2. Higashiwaki, M. & Jessen, G. H. Guest Editorial: the dawn of gallium oxide microelectronics. Appl. Phys. Lett. 112, 060401 (2018). \n3. Zhou, H. et al. A review of the most recent progresses of state-of-art gallium oxide power devices. J. Semicond. 40, 011803 (2019). \n4. Zheng, Z. et al. Gallium nitride-based complementary logic integrated circuits. Nat. Electron. 4, 595–604 (2021). \n5. Nela, L. et al. Multi-channel nanowire devices for efficient power conversion. Nat. Electron. 4, 284–290 (2021). \n6. Tsao, J. Y. et al. Ultrawide-bandgap semiconductors: research opportunities and challenges. Adv. Electron. Mater. 4, 1600501 (2018). \n7. Li, W., Nomoto, K., Hu, Z., Jena, D. & Xing, H. G. Field-plated ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ trench Schottky barrier diodes with a $\\mathrm{BV^{2}/R_{o n,s p}}$ of up to $0.95\\mathrm{GW}/\\mathrm{cm}^{2}$ . IEEE Electron Device Lett. 41, 107–110 (2020). \n8. Lin, T., Li, X. & Jang, J. High performance p-type $\\mathrm{NiO_{x}}$ thin-film transistor by Sn doping. Appl. Phys. Lett. 108, 233503 (2016). \n9. Pattanasattayavong, P., Thomas, S., Adamopoulos, G., McLachlan, M. A. & Anthopoulos, T. D. p-channel thin-film transistors based on spray-coated $\\mathrm{Cu}_{2}\\mathrm{O}$ films. Appl. Phys. Lett. 102, 163503 (2013). \n10. Wang, C. et al. Demonstration of the $\\mathrm{P{-}N i O_{x}/n{-}G a_{2}O_{3}}$ heterojunction gate FETs and diodes with $\\mathrm{BV}^{2}/\\mathrm{R}_{\\mathrm{on},s\\mathrm{p}}$ figure of merits of $0.39\\mathrm{\\GW}/\\mathrm{cm}^{2}$ and $1.38\\mathrm{GW}/\\mathrm{cm}^{2}$ . IEEE Electron Device Lett. 42, 485–488 (2021). \n11. Roy, S. et al. High-k oxide field-plated vertical $(001)\\beta{\\mathrm{-Ga}}_{2}\\mathrm{O}_{3}$ Schottky barrier diode with baliga’s figure of merit over $1\\mathrm{GW}/\\mathrm{cm}^{2}$ . IEEE Electron Device Lett. 42, 1540–1143 (2021). \n12. Zhou, F. et al. 1.95-kV Beveled-Mesa $\\mathrm{NiO}/\\upbeta\\mathrm{-}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ heterojunction diode with $98.5\\%$ conversion efficiency and over million-times overvoltage ruggedness. IEEE Trans. Power Electron. 37, 1223–1227 (2021). \n13. Irmscher, K., Galazka, Z., Pietsch, M., Uecker, R. & Fornari, R. Electrical properties of beta- ${\\cal G}{\\sf a}_{2}{\\sf O}_{3}$ single crystals grown by the Czochralski method. J. Appl. Phys. 110, 063720 (2011). \n14. Thomas, S. R. et al. High electron mobility thin-film transistors based on ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ grown by atmospheric ultrasonic spray pyrolysis at low temperatures. Appl. Phys. Lett. 105, 092105 (2014). \n15. Wang, C. et al. Progress in state-of-the-art technologies of ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ devices. J. Phys. D: Appl. Phys. 54, 243001 (2021). \n16. Baliga, B. J. Fundamentals of Power Semiconductor Devices (Springer, 2008). \n17. Lu, X. et al. 1-kV sputtered $\\mathsf{p}{\\mathrm{-NiO/n}}{\\mathrm{-Ga}}_{2}\\mathrm{O}_{3}$ heterojunction diodes with an ultra-low leakage current below $1\\upmu\\mathrm{A}/\\mathrm{cm}^{2}$ . IEEE Electron Device Lett. 41, 449–452 (2020). \n18. Gong, H. H. et al. A 1.86-kV double-layered NiO/β ${\\tt b}_{-}{\\tt G a}_{2}{\\tt O}_{3}$ vertical $\\mathtt{p-n}$ heterojunction diode. Appl. Phys. Lett. 117, 022104 (2020). \n19. Kokubun, Y., Kubo, S. & Nakagomi, S. All-oxide p–n heterojunction diodes comprising p-type NiO and n-type ${\\upbeta}{\\mathrm{-}}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ . Appl. Phys. Exp. 9, 091101 (2016). \n20. Schlupp, P., Splith, D., Wenckstern, H. V. & Grundmann, M. Electrical properties of vertical $\\mathsf{p}–\\mathrm{NiO}/\\mathrm{n}–\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ and $\\mathrm{p}{\\mathrm{-}}Z\\mathrm{nCo}_{2}\\mathrm{O}_{4}/\\mathrm{n-}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ pnheterodiodes. Phys. Status Solidi A 216, 1800729 (2019). \n21. Lv, Y. et al. Oxygen annealing impact on ${\\upbeta}{\\mathrm{-}}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ MOSFETs: improved pinch-off characteristic and output power density. Appl. Phys. Lett. 117, 133503 (2020). \n22. Schroder, D. K. Semiconductor Material and Device Characterization, 3rd ed. (Hoboken, NJ, USA: Wiley, 2006). \n23. Dutta, M. et al. Determination of minority carrier lifetime of holes in diamond p-i-n diodes using reverse recovery method. IEEE Electron Device Lett. 39, 552–555 (2018). \n24. Streetman, B. & Banerjee, S. K. Junctions. in Solid State Electronic Devices 6th edn, (Englewood Cliffs, NJ, USA: Prentice-Hall, 2006). \n25. Lv, Y. et al. Demonstration of ${\\upbeta}{\\mathrm{-}}{\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ junction barrier Schottky diodes with a Baliga’s figure of merit of $0.85\\mathrm{\\GW/cm^{2}}$ or a $5\\mathrm{A}/700\\mathrm{~V~}$ handling capabilities. IEEE Trans. Power Electron. 36, 6179–6182 (2021). \n26. Yang, J. et al. High breakdown voltage $\\left(-201\\right)$ ${\\upbeta}{\\mathrm{-}}{\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ Schottky rectifiers. IEEE Electron Device Lett. 38, 906–910 (2017). \n27. Allen, N. et al. Vertical ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ Schottky barrier diodes with small-angle beveled field plates: a Baliga’s figure-of-merit of $0.6~\\mathrm{GW}/\\mathrm{cm}^{2}$ . IEEE Electron Device Lett. 40, 1399–1402 (2019). \n28. Konishi, K. et al. 1-kV vertical ${\\upbeta}{\\mathrm{-}}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ field-plated Schottky barrier diodes. Appl. Phys. Lett. 110, 103506 (2017). \n29. Li, W. et al. $2.44~\\mathrm{kV}$ ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ vertical trench Schottky barrier diodes with very low reverse leakage current. In Proc. IEEE International Electron Devices Meeting (IEDM), 8.5.1-8.5.4 (2018). \n30. Lin, C. H. et al. Vertical $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ Schottky barrier diodes with guard ring formed by nitrogen-ion implantation. IEEE Electron Device Lett. 40, 1487–1490 (2019). \n31. Zhou, H. et al. High-performance vertical ${\\upbeta}{\\mathrm{-}}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ Schottky barrier diode with implanted edge termination. IEEE Electron Device Lett. 40, 1788–1791 (2019). \n32. Yan, Q. et al. ${\\displaystyle\\beta{\\mathrm{-}}{\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}}$ hetero-junction barrier Schottky diode with reverse leakage current modulation and $\\mathrm{BV}^{2}/\\mathrm{R}_{\\mathrm{on},\\mathrm{sp}}$ value of $0.93\\mathrm{\\GW}/\\mathrm{cm}^{2}$ . Appl. Phys. Lett. 118, 122102 (2021). \n33. Gong, H. et al. $1.37\\mathrm{~kV}/12$ A $\\mathrm{NiO}/\\upbeta$ ${\\cdot}\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ heterojunction diode with nanosecond reverse recovery and rugged surge-current capability. IEEE Trans. Power Electron. 36, 12213–12217 (2021). \n34. Hao, W. et al. Low defect density and small I-V curve hysteresis in $\\mathrm{{NiO/\\beta}}$ - ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ pn diode with a high PFOM of $0.65~\\mathrm{GW}/\\mathrm{cm}^{2}$ . Appl. Phys. Lett. 118, 043501 (2021). \n35. Zhang, Y. et al. Demonstration of a 2 k $/\\mathrm{\\Al_{0.85}G a_{0.15}N}$ Schottky barrier diode with improved on-current and ideality factor. IEEE Electron Device Lett. 41, 457–460 (2020). \n36. Donato, N., Rouger, N., Pernot, J., Longobardi, G. & Udrea, F. Diamond power devices: state of the art, modelling, figures of merit and future perspective. J. Phys. D: Appl. Phys. 53, 093001 (2020). \n37. Makino, T. et al. Diamond Schottky-pn diode with high forward current density and fast switching operation. Appl. Phys. Lett. 94, 262101 (2009). \n38. Traore, A. et al. $\\mathrm{Zr/}$ oxidized diamond interface for high power Schottky diodes. Appl. Phys. Lett., 104, 052105 (2014). \n39. Wang, J. et al. Demonstration of $\\mathrm{Al}_{0.85}\\mathrm{Ga}_{0.15}\\mathrm{N}$ Schottky barrier diode with ${>}3\\mathrm{kV}$ breakdown voltage and the reverse leakage currents formation mechanism analysis. Appl. Phys. Lett. 118, 173505 (2021). \n40. Butler, J. E. et al. Exceptionally high voltage Schottky diamond diodes and low boron doping. Semicond. Sci. Technol. 18, S67–S71 (2003). \n41. Fu, H. et al. Demonstration of AlN Schottky barrier diodes with blocking voltage over 1kV. IEEE Electron Device Lett. 38, 1286 (2017). \n42. Gong, H. et al. $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ vertical heterojunction barrier Schottky diodes terminated with p-NiO field limiting rings. Appl. Phys. Lett. 118, 202102 (2021). \n43. Yu, Y. et al. $1.2\\ \\mathrm{kV}/2.9\\ \\mathrm{m}\\Omega{\\cdot}\\mathrm{cm}^{2}$ vertical $\\mathrm{NiO}/\\upbeta$ - ${\\cal G}{\\sf a}_{2}{\\sf O}_{3}$ heterojunction diodes with high switching performance. In Proc. 32nd International Symposium on Power Semiconductor Devices ICs (ISPSD), 178–181 (2020). \n44. Gong, H. et al. Vertical field-plated $\\mathrm{NiO/Ga_{2}O_{3}}$ heterojunction power diodes. In Proc. Electron Devices Technology and Manufacturing Conference (EDTM), 2021. \n45. Xiao, M. et al. $10~\\mathrm{kV}$ , $39\\mathrm{m}\\Omega{\\cdot}\\mathrm{cm}^{2}$ multi-channel AlGaN/GaN codes. IEEE Electron Device Lett. 42, 808–811 (2021). \n46. Xiao, M. et al. $5\\mathrm{kV}$ multi-channel AlGaN/GaN power Schottky barrier diodes with junction-fin-anode. In Proc. IEEE International Electron Devices Meeting (IEDM), pp. 5.4.1–5.4.4 (2020). \n47. Han, S. W. et al. Experimental demonstration of charge-balanced GaN superheterojunction Schottky barrier diode capable of $2.8~\\mathrm{kV}$ switching. IEEE Electron Device Lett. 41, 1758–1761 (2020). \n48. Colón, A. et al. Demonstration of a $9\\mathrm{kV}$ reverse breakdown and $59~\\mathrm{m}\\Omega.\\mathrm{cm}^{2}$ specific on-resistance AlGaN/GaN Schottky barrier diode. Solid-State Electron. \n151, 47–51 (2019). \n49. Ma, J. et al. $2\\mathrm{kV}$ slanted tri-gate GaN-on-Si Schottky barrier diodes with ultra-low leakage current. Appl. Phys. Lett. 112, 052101 (2018). \n50. Zhang, T. et al. $\\mathrm{A}>3\\mathrm{kV}/2.94\\mathrm{m}\\Omega.\\mathrm{cm}^{2}$ and low leakage current with low turnon voltage lateral GaN Schottky barrier diode on silicon substrate with anode engineering technique. IEEE Electron Device Lett. 40, 1583–1586 (2019). \n51. Ghandi, R., Bolotnikov, A., Lilienfeld, D., Kennerly, S. & Ravisekhar, R. 3 kV SiC charge-balanced diodes breaking unipolar limit. In Proc. 31st International Symposium on Power Semiconductor Devices ICs (ISPSD), \n179–182 (2019). \n52. Lynch, J., Yun, N. & Sung, W. Design considerations for high voltage SiC power devices: an experimental investigation into channel pinching of $10~\\mathrm{kV}$ SiC junction barrier Schottky (JBS) diodes. In Proc. 31st International Symposium on Power Semiconductor Devices ICs (ISPSD), 223–226 (2019). \n53. Millan, J. et al. High-voltage SiC devices: diodes and MOSFETs. In Proc. International Semiconductor Conference (CAS), 11–18 (2015). \n\n# Acknowledgements \n\nThe work was supported by National Natural Science Foundation of China under the grant nos. 62004147 and 61925404. We are grateful to Dr. Y. Huang from Xidian Wuhu \n\nresearch institute for the 10-kV high voltage breakdown measurements. We are also grateful to Prof. Y. H. Zhang for the valuable discussions. \n\n# Author contributions \n\nH.Z. and J.C.Z. conceived the idea and proposed the $\\mathrm{Ga}_{2}\\mathrm{O}_{3}$ HJ PN diodes. Y.H. supervised the whole process and designed the experiment. P.F.D. did the device fabrication and some I-V characterizations. K.D., Y.N.Z., and Q.L.Y. carried out the breakdown measurements, taking SEM and TEM pictures, wafer packaging. H.X., Z.H.L., and M.W.S. carried out the hole lifetime measurements and set-up, partial $I{-}V$ measurements, and partial data analyze. J.S. performed the DFT calculations. J.C.G. and M.F.K. performed the hole injection TCAD simulation. H.Z. and J.C.Z. co-wrote the manuscript and all authors commented on it. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-31664-y. \n\nCorrespondence and requests for materials should be addressed to Hong Zhou. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1038_s41467-022-29837-w", + "DOI": "10.1038/s41467-022-29837-w", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-29837-w", + "Relative Dir Path": "mds/10.1038_s41467-022-29837-w", + "Article Title": "Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation", + "Authors": "Zhu, JG; Wang, YX; Huang, Y; Gopaluni, RB; Cao, YK; Heere, M; Mühlbauer, MJ; Mereacre, L; Dai, HF; Liu, XH; Senyshyn, A; Wei, XZ; Knapp, M; Ehrenberg, H", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Accurate capacity estimation is crucial for lithium-ion batteries' reliable and safe operation. Here, the authors propose an approach exploiting features from the relaxation voltage curve for battery capacity estimation without requiring other previous cycling information. Accurate capacity estimation is crucial for the reliable and safe operation of lithium-ion batteries. In particular, exploiting the relaxation voltage curve features could enable battery capacity estimation without additional cycling information. Here, we report the study of three datasets comprising 130 commercial lithium-ion cells cycled under various conditions to evaluate the capacity estimation approach. One dataset is collected for model building from batteries with LiNi0.86Co0.11Al0.03O2-based positive electrodes. The other two datasets, used for validation, are obtained from batteries with LiNi0.83Co0.11Mn0.07O2-based positive electrodes and batteries with the blend of Li(NiCoMn)O-2 - Li(NiCoAl)O-2 positive electrodes. Base models that use machine learning methods are employed to estimate the battery capacity using features derived from the relaxation voltage profiles. The best model achieves a root-mean-square error of 1.1% for the dataset used for the model building. A transfer learning model is then developed by adding a featured linear transformation to the base model. This extended model achieves a root-mean-square error of less than 1.7% on the datasets used for the model validation, indicating the successful applicability of the capacity estimation approach utilizing cell voltage relaxation.", + "Times Cited, WoS Core": 342, + "Times Cited, All Databases": 360, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000788592600010", + "Markdown": "# Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation \n\nJiangong Zhu 1,2,7, Yixiu Wang3,7, Yuan Huang1,2, R. Bhushan Gopaluni3, Yankai Cao3, Michael Heere2,4, Martin J. Mühlbauer2, Liuda Mereacre2, Haifeng Dai 1✉, Xinhua Liu $\\textcircled{1}$ 5, Anatoliy Senyshyn $\\textcircled{1}$ 6, Xuezhe Wei1, Michael Knapp 2✉ & Helmut Ehrenberg 2 \n\nAccurate capacity estimation is crucial for the reliable and safe operation of lithium-ion batteries. In particular, exploiting the relaxation voltage curve features could enable battery capacity estimation without additional cycling information. Here, we report the study of three datasets comprising 130 commercial lithium-ion cells cycled under various conditions to evaluate the capacity estimation approach. One dataset is collected for model building from batteries with $\\mathsf{L i N i}_{0.86}\\mathsf C\\mathsf{o}_{0.11}\\mathsf{A l}_{0.03}\\mathsf{O}_{2}.$ -based positive electrodes. The other two datasets, used for validation, are obtained from batteries with $\\mathsf{L i N i}_{0.83}\\mathsf{C o}_{0.11}\\mathsf{M n}_{0.07}\\mathsf{O}_{2}$ -based positive electrodes and batteries with the blend of $\\mathsf{L i}(\\mathsf{N i}\\mathsf{C o M n})\\mathsf{O}_{2}\\textrm{-}\\mathsf{L i}(\\mathsf{N i}\\mathsf{C o A l})\\mathsf{O}_{2}$ positive electrodes. Base models that use machine learning methods are employed to estimate the battery capacity using features derived from the relaxation voltage profiles. The best model achieves a root-mean-square error of $1.1\\%$ for the dataset used for the model building. A transfer learning model is then developed by adding a featured linear transformation to the base model. This extended model achieves a root-mean-square error of less than $1.7\\%$ on the datasets used for the model validation, indicating the successful applicability of the capacity estimation approach utilizing cell voltage relaxation. \n\nithium-ion batteries have become the dominant energy storage device for portable electric devices, electric vehicles (EVs), and many other applications1. However, battery degradation is an important concern in the use of lithium-ion batteries as its performance decreases over time due to irreversible physical and chemical changes2,3. State of Health (SoH) has been used as an indicator of the state of the battery and is usually expressed by the ratio of the relative residual capacity with respect to the initial capacity4. The accurate battery capacity estimation is challenging but critical to the reliable usage of the lithium-ion battery, i.e., accurate capacity estimation allows an accurate driving range prediction and accurate calculation of the maximum energy storage capability in a vehicle. Typically, the battery capacity is gained by a full discharge process after it has been fully charged. In a real-life usage scenario, the battery full charge is often achieved while the EVs are parking with grid connection, however, the battery discharge depends on the user behavior with uncertainties in environmental and operational conditions, a complete discharge curve is seldom available for on-board battery health monitoring. The battery charging and discharging voltage, as one of the easily obtained parameters, depend on both, thermodynamic and kinetic characteristics of the battery. Thus, those methods using a charge/discharge process are proposed to estimate capacity for practical applications5,6, in which the input variables are extracted from the measured voltage curves, and the data-driven methods using statistical and machine learning techniques have been popular in battery research recently due to their strong data processing and nonlinear fitting capabilities6,7. The data-driven methods do not need a deep understanding of battery electrochemical principles, but large numbers of data are required to ensure the reliability of model8. Severson et al.9 reported a promising route using machine learning to construct models that accurately predicted graphite $\\mathrm{||LiFePO_{4}}$ (LFP) commercial cell lives using charge-discharge voltage data. Zhang et al.10 identified battery degradation patterns from impedance spectroscopy using Gaussian process machine learning models. Ding et al.11 introduced a machine learning method for the improvement of the efficiency of membrane electrode assembly design and experiment. Such data-driven methods focus on the relationships among the input and output features, and a key part of data-driven battery state estimation is the extraction of degradation features, which largely determines the estimation performance12–14. \n\nIn practical electric transport applications, battery charging is essential and happens regularly compared to the random discharge process affected by the driving behaviors and road environments. Therefore, extracting voltage features from the charging process has attracted wide attention. Taking into account the state-of-the-art literature, three classes of voltage-based extraction methods can be defined: (I) CC (constant current) charge voltagebased, (II) CC-CV (constant current–constant voltage) charge voltage-based, and (III) rest voltage-based as listed in Supplementary Table 1. The partial charge process in a specific voltage range for feature extraction is commonly used for capacity estimation15, and the estimation accuracy of the state of art is ranging from a root-mean-square error (RMSE) of $0.39\\%$ to a RMSE of $4.26\\%$ based on in-house experiments and different public datasets5,6,16. The transformations of the partial voltage curves, i.e., differential voltage analysis17,18 and incremental capacity analysis19–21, are used for battery aging mechanism identification and capacity fade evaluation. Typically, SVR (Support Vectors Regression)22, GPPF (Gaussian Process Particle Filter)23, BPNN (Back-Propagation Neural Network)24, and linear model20 are applied to estimate battery capacity using the partial incremental capacity curve. Compared to the charge voltage-based methods, studies extracting features from the rest voltage are few. \n\nA representative battery capacity estimation method utilizing the resting process was proposed by Baghdadi et al.25. They proposed a linear model to estimate battery capacity using the voltage after $30\\mathrm{min}$ rest when the cell is fully charged, and the capacity estimation percentage error is ranging from 0.7 to $3.3\\%$ for three different commercial batteries. Schindler et al.26 and Lüders et al.27 took the voltage relaxation for the lithium plating detection in the battery capacity fade process. Qian et al.28 used an equivalent circuit model (ECM) to describe the voltage relaxation and found that the extracted parameters provided an evaluation of the battery SoH and aging mechanisms. Attidekou et al.29 modeled the battery capacity decay during rest periods at $100\\%$ SoC using a dynamic time constant derived from the resistor-capacitor (RC) network model. However, as the amount of RC links increases, the complexity of the ECM will increase accordingly, which makes it difficult to use in an on-board application30. Besides, the accuracy and robustness of capacity estimation are difficult to evaluate because of the differences in battery types and working conditions8,9. \n\nIt has been proven that the relaxation process including the relaxation voltage value at a specific time and the voltage curve during a specific period shows a relationship with the battery $\\mathrm{SoH}^{26-29,31}$ . From the review of battery charging studies32–34, the real-time data of $\\mathrm{EV}s^{35,36}$ , and a survey of real-world EV charging (Supplementary Note 1, Supplementary Table 2 and 3, and Supplementary Figs. 1 and 2), in addition to the CC charging strategy, the multistage current charging algorithm using a SoC dependent charging current is a promising method to maximize the charging efficiency. The start of charge for the EVs is normally distributed around intermediate SoCs as expected from the statistics35,37,38. The various multistage current charge strategies and the uncertain start of charge points bring difficulties to the acquirement of specific voltage ranges under constant current in the voltage-based methods. The relaxation after being fully charged is relatively unaffected by the charging process and is also easy to obtain since the battery is fully charged with high probability in real EV usage35,37,38, there is also no need for additional devices as the voltage data can be directly obtained from the battery management system. However, to the best of our knowledge, the relaxation voltage curve of the battery has not yet been studied systematically with machine learning methods for large-scale data from different battery types. Herein, an approach based on features extracted from the battery relaxation voltage is proposed, which focuses on short-term battery capacity estimation without any previous cycling information for on-board implementation. \n\nIn this study, base models using machine learning methods, i.e., the linear model (ElasticNet39), and nonlinear models (XGBoost40 and Support Vector Regression $(\\mathrm{SVR})^{41}.$ ), using large datasets from three kinds of commercial lithium-ion batteries are employed. The model inputs are statistical features extracted from the voltage relaxation curve. Batteries with $\\mathrm{LiNi}_{0.86}\\mathrm{Co}_{0.11}\\mathrm{Al}_{0.03}\\mathrm{O}_{2}$ positive electrode (NCA battery) cycled at different temperatures and current rates are used for base model building, showing the best test performance with a RMSE of $1.0\\%$ . The transfer learning method is applied on batteries with $\\mathrm{LiNi}_{0.83}\\mathrm{Co}_{0.11}\\mathrm{Mn}_{0.07}\\mathrm{O}_{2}$ positive electrode (NCM battery) and batteries with 42 (3) wt. $\\%$ $\\mathrm{Li}(\\mathrm{NiCoMn})\\mathrm{O}_{2}$ blended with 58 (3) wt. $\\%$ $\\mathrm{Li}(\\mathrm{NiCoAl})\\mathrm{O}_{2}$ positive electrode $(\\mathrm{NCM}+\\mathrm{NCA}$ battery), obtaining $1.7\\%$ RMSE and $1.6\\%$ RMSE respectively, and enabling the generalizability of our approach. \n\n# Results \n\nData generation. Large cycling datasets on NCA battery, NCM battery, and $\\mathrm{{NCM}+\\tilde{N}C A}$ battery are created in this study. The batteries are cycled in a temperature-controlled chamber with different charge current rates. The battery specifications are listed in Supplementary Table 4. Long-term cycling is conducted on all cells with a summary of cycling conditions in Table 1. The temperatures chosen are 25, 35, and $45^{\\circ}\\mathrm{C}$ . Current rates ranging from $0.25\\mathrm{C}$ (0.875 A) to 4 C (10 A) are used. The current rate is calculated from the nominal capacity of batteries, i.e., $1\\mathrm{C}$ is equal to $3.5\\mathrm{A}$ for the NCA battery and NCM battery, and 1 C is equal to $2.5\\mathrm{A}$ for the $\\mathrm{{NCM}+N C A}$ battery. The cells are named as CYX-Y/Z according to their cycling conditions. X means the temperature, $\\mathrm{Y}/\\mathrm{Z}$ represents the charge/discharge current rate. The number of cells assigned to each cycling condition in Table 1 is aimed to obtain a dataset covering possible variations between cells. One data unit comprises a relaxation voltage curve after full charge with the following discharge capacity. Each relaxation voltage curve is transformed into six statistical features, i.e., variance (Var), skewness (Ske), maxima (Max), minima (Min), mean (Mean), and excess kurtosis (Kur). The mathematical description of the six features is depicted in Supplementary Table 5. The datasets collected from NCA, NCM, and $\\mathrm{{NCM}+N C A}$ cells are named as dataset 1, dataset 2, and dataset 3 in this study, respectively. Dataset 1 is used for base model training and test. Dataset 2 and dataset 3 are used for assessing and improving the generalizability of the proposed approach by transfer learning. \n\n
Table 1 Cycled batteries and cycling conditions for the dataset generation.
DatasetsCell typeCycling temperature (±0.2 °℃)Charge current rate (C)/discharge rate (C) Number of cellsNumber of data units
Dataset 1NCA battery250.25/171853
Type: 18,6500.5/1193278
Cutoffvoltage: 2.65-4.2V1/19260
Nominal capacity: 3.5 Ah350.5/131112
452815,775
Dataset2 NCM battery25235490
Type: 18,650354.4712
Cutoff voltage: 2.5-4.2 V452817,600
Nominal capacity: 3.5Ah
Dataset 3NCM+NCA battery250.5/132843
Type: 186500.5/232913
Cutoff voltage: 2.5-4.2 V0.5/432826
Nominal capacity: 2.5 Ah
\n\nAll cells are commercial 18,650 type batteries. The cycling temperature is controlled by climate chambers $(\\pm0.2^{\\circ}\\mathsf{C})$ . The current rate is calculated from the battery nominal capacity $(1mathsf{C}=3.5\\mathsf{A}$ for the NCA battery and NCM battery, and $\\mathsf{1C}=2.5\\mathsf{A}$ for the NCM + NCA battery). \n\nVoltage and current are the basic data recorded in these experiments, which include charging, discharging, and relaxation processes. The cell cycling is performed with constant current (CC) charging to $4.2\\mathrm{V}$ with current rates ranging from $0.25\\mathrm{C}\\left(0.875\\mathrm{A}\\right)$ to 1 C (3.5 A), followed by a constant voltage (CV) charging step at $4.2\\mathrm{V}$ until a current of $0.05\\mathrm{C}$ is reached. Constant current is then employed for the discharge to $2.65\\mathrm{V}$ for the NCA cells and $2.5\\mathrm{V}$ for the NCM and $\\mathrm{{NCM+NCA}}$ cells, respectively. One complete cycling curve using a $0.5\\mathrm{C}$ charging rate for the NCA cell is shown in Fig. 1a, which includes five processes, i.e., (I) CC charging, (II) CV charging, (III) relaxation after charging, (IV) CC discharging, and (V) relaxation after discharging. The CC discharging capacity is treated as the battery residual capacity during cycling. The relaxation time between the CV charging and CC discharging is $30\\mathrm{min}$ for the NCA battery and NCM battery with a real sampling time of $120s.$ , and it is $60\\mathrm{min}$ for the $\\mathrm{{NCM}+N C A}$ battery with a sampling time of $30\\mathrm{{s}}$ . The starting and ending voltage during the battery relaxation show a declining trend with increasing cycle number as presented in Fig. 1b. \n\nThree datasets with capacity down to $71\\%$ of the nominal capacity are generated. The battery capacity as a function of cycle number for the NCA cells is shown in Fig. 1c. The cycle number is ranging from 50 to 800 in the $100\\mathrm{-}71\\%$ capacity window. It is evident that both, charging current and temperature have a strong influence on the capacity decay, and the battery capacity shows significant variance as depicted in the embedded plot in Fig. 1c, indicating the degradation distribution of the cycled cells. The worst scenario is the one with cells cycled at 1C charge at $25^{\\circ}\\mathrm{C}$ (CY25-1/1), only 50 cycles can be obtained until the cells reach $71\\%$ of the nominal capacity. In all, $71\\%$ capacity is reached after 125 and 600 cycles at 25 and $35^{\\circ}\\mathrm{C}$ respectively, for cells charged with $0.5\\mathrm{C}$ $(\\mathrm{CY}25–0.5/1$ , and CY35-0.5/1). In total, $71\\%$ capacity is reached after 250 cycles at $25^{\\circ}\\mathrm{C}$ with $0.25\\mathrm{C}$ charging current $(\\mathrm{CY}25–0.25/1)$ and in a range of 500–800 cycles at $45^{\\circ}\\mathrm{C}$ with $0.5\\mathrm{C}$ charging current (CY45-0.5/1). The cycling data of the NCM cells are shown in Fig. 1d. Fatigue down to $71\\%$ residual capacity is found between 250 and 500 cycles $(25^{\\circ}\\mathrm{C})$ , 1250 and 1500 cycles $(35^{\\circ}\\mathrm{C})$ , and around 1000 cycles at $45^{\\circ}\\mathrm{C}$ cycling temperature. The capacity fade results indicate that increasing the temperature to 35 and $45^{\\circ}\\mathrm{C}$ has a beneficial effect on the capacity retention and that the charging current is at the limit of what the cells can handle. For NCA and NCM cells, a capacity spread for the cells cycled under equal conditions is observed, which is speculated to be ascribed to the intrinsic manufacturing variations as this spread is already seen at the beginning of cycling42,43. The cycling data of the $\\mathrm{{NCM+NCA}}$ cells are shown in Fig. 1e, exhibiting a linear degradation trend regardless of the cycling discharge rates, and $71\\%$ residual capacity appears in a range of 750 to 850 cycles showing the influence of the cell cycling conditions. \n\nFeature extraction. Summarizing statistics are proven to be effective to illustrate numerically the shape and position change of the voltage curve5,9. As mentioned above, the relaxation process after fully charging is taken for feature extraction because of its strong relationship with battery degradation and its easy acquisition in battery real use. Each voltage relaxation curve is converted to six statistical features, i.e., Var, Ske, Max, Min, Mean, and Kur, as displayed in Fig. 2. \n\nThe relationship between battery capacity and the corresponding features is dependent on the cycling conditions as presented in Fig. 2. It can be seen that it is difficult to describe the relationships only by linear functions. The Var in Fig. 2a represents the distribution of the voltage points in one relaxation process, a decrease of Var versus capacity fade means that the relaxation voltages show a sharper distribution with increasing cycle number, and vice versa. Both Ske and Kur are normalized using Var, they are used to describe the shape of the corresponding voltage curve. The Ske in Fig. 2b is positive for almost all cycling conditions, indicating that more than half of the sampled voltage data are below the average voltage (Mean), which corresponds to the shape of the relaxation voltage curve, i.e., with respect to the relaxation time, the voltage drops initially fast and then gradually slows down. The Max in Fig. 2c presents a monotonous decrease of the maximum voltage versus capacity drop for all cycling conditions. The Min and Mean first increase and then decrease versus the capacity reduction as displayed in Fig. 2d, e, respectively. The Kur shown in Fig. 2f is the excess kurtosis obtained from the kurtosis of the raw data minus the kurtosis of a normal distribution. The excess kurtosis is negative for all cycling conditions, meaning that the distribution of the relaxation voltage is gentler than a normal distribution. \n\n![](images/6bd6a0c74e23be94f47d40f7abc832208be680504629b34db3858bc37a6094f4.jpg) \nFig. 1 Battery cycling data. Voltage and current profile in the first cycle of one CY25-0.5/1 NCA battery (a). A plot of relaxation voltage change (region III) while cycling for one NCA cell (b). NCA battery discharge capacity (until $71\\%$ of nominal capacity) versus cycle number of NCA battery (c), NCM battery (d), and $N C M+N C A$ battery (e). The embedded plots in c, d, and e are the cycle distribution of cells at around $71\\%$ of nominal capacity, the points are offset randomly in the horizontal direction to avoid overlapping. \n\n![](images/46be618726721b1a32ea40083c1f595e43b65febb08fac3150635d6afc5251ef.jpg) \nFig. 2 Extracted features from the voltage relaxation curves as a function of battery capacity for NCA cells. (a) Variance (Var), (b) skewness $({\\mathsf{S k e}})$ , (c) maxima (Max), (d) minima (Min), (e) mean (Mean), and (f) excess kurtosis (Kur). Feature changes between $3500~\\mathrm{mAh}$ and $2500~\\mathrm{{mAh}}$ $71\\%$ of nominal capacity) for NCA cells are shown to be consistent with the used datasets. The mathematical description of the six features is depicted in Supplementary Table 5. \n\nCapacity estimation. Based on the features extracted from the relaxation voltage curve after charging, data-driven methods are used for battery capacity estimation. Owing to the difference in the order of magnitudes of the features, a standard normalization for battery features is performed for dataset 1. The features of dataset 2 and dataset 3 are normalized by applying the same normalizing scales as used for dataset 1. The capacity is uniformized considering the difference in the battery nominal capacity. The XGBoost40 is selected as the main machine learning method. The ElasticNet39 as the multivariate linear model is used for comparison, and the $\\mathrm{SVR^{41}}$ is a support for the verification of the transfer learning approach. For the base model training and test, different data splitting strategies are compared with dataset 1 in Supplementary Note 2 and Supplementary Tables 6–9. The best test result of the temperature dependence splitting method shows a $1.5\\%$ RMSE. A $2.3\\%$ test RMSE is obtained from the time-series data splitting method. The data random splitting and cell stratified sampling methods achieve good estimation accuracy with $1.1\\%$ RMSEs, implying that the variation of the working conditions leading to different degradation patterns is essential to improve the generalization of the model. The results of cell stratified sampling method meaning that the data from the same cell is either in the training set or in the test set are presented in this study (Strategy $\\mathrm{~D~}$ in Supplementary Note 2). The cells are approximately in a 4:1 ratio for training and test (Supplementary Table 9). In the model training process, the K-fold cross-validation with $K=5$ is used to determine the hyperparameters of the models. A feature reduction is performed by using different feature combinations to reduce the number of inputs and simplify the model complexity. The cross-validation RMSEs under different feature combinations using the XGBoost method are compared in Fig. 3. The $i$ and $j$ are used to represent different feature combinations referring the Supplementary Table 10. \n\nIt shows that the RMSE gradually decreases as the number of features increases, and the accuracy improvement is no longer obvious after using three features in Fig. 3. The best estimation result is obtained by the input [Var, Ske, Max] in a three feature combination. The effect of the duration of the relaxation on the capacity estimation is presented in Supplementary Fig. 3, in which the RMSEs of training and test decrease as the relaxation time increases in the XGBoost method, indicating that longer relaxation time improves the model accuracy. Therefore, the Var, Ske, and Max of the voltage relaxation after $30\\mathrm{min}$ are extracted as inputs for the base model. The hyperparameters of each algorithm are available in Supplementary Table 11. The RMSEs of different estimation methods on dataset 1 are summarized in Fig. 4a. It can be concluded that the test RMSE of XGBoost and SVR all reaches $1.1\\%$ , showing better performance than the linear model, and the RMSEs of train and test are close to each other, indicating the effectiveness of data splitting. The estimated capacity versus real capacity is illustrated in Fig. 4b–d for visualization purposes. \n\nPerformance of the proposed approach. The performance of the proposed approach is benchmarked with state-of-the-art models using voltage curves for battery capacity estimation as shown in Table 2. One representative method is selected from each class of the presented capacity estimation methods (Supplementary Table 1). Since the datasets used in the literature are different in battery material and test procedures from ours, the strategy to solve this difference is to apply their algorithms to our datasets. A detailed description of data processing and estimation results for each method is presented in Supplementary Note 3 and Supplementary Figs. 4–7. The performance of the linear model to estimate the battery capacity based on the resting voltage in Baghdadi et al.25 shows a $2.5\\%$ RMSE, which can be explained by the large data volume and variety of working conditions in our dataset 1 highlighting the difficulty of capacity estimation only with the linear model. In the CC charge voltage-based methods, the random forest regression (RFR) method16 using the voltage ranging from $3.6\\mathrm{V}$ to $3.8\\mathrm{V}$ achieves a RMSE of $1.0\\%$ on dataset 1, which is $0.1\\%$ less than our RMSE based on the voltage relaxation. A method based on the remaining electrical charge with a threshold according to the incremental capacity value is proposed in Peri et al.20. The application of the same incremental capacity transformation method on dataset 1 provides a RMSE of $1.3\\%$ , indicating that our proposed approach has better accuracy. The Gaussian process regression (GPR) method44 using a full CC-CV charge voltage curve obtains good estimation results on dataset 1 with a test RMSE of $1.1\\%$ . Compared with the current research status, especially with respect to large datasets, the proposed approach using resting voltage can achieve a good estimation accuracy. As mentioned in the introduction section, there are some challenges in the acquisition of specific charging voltage curves because the start of battery charge is usually dependent on the driver behavior and the charge modes differ significantly from the charging stations in the real application of EVs. The relaxation process of a battery being fully charged is easily obtained without the requirement of specific working conditions and voltage ranges, which offers a new sight for battery capacity estimation. \n\n![](images/f7144892102d556a2e421ec81f8a89a7fed5126f1c6f560839e0c987e38c140a.jpg) \nFig. 3 Cross-validation root-mean-square error (RMSE) of the XGBoost method using different feature combinations. $({\\boldsymbol{{j}}},{\\boldsymbol{{j}}})$ means different feature combinations referring the Supplementary Table 10. The $(7,1)=\\mathsf{\\Gamma}[\\mathsf{V a r}_{\\cdot}$ Ske, Max] obtains the best cross-validation $\\mathsf{R M S E}=1.0\\%$ within a three feature combination. \n\nPhysical explanation. The alternating current (AC) electrochemical impedance provides information in the frequency domain on the degradation mechanisms of the battery as proven in ref. 45. The degradation mechanisms can be determined from the change of electrochemical impedance parameters extracted by fitting the impedance spectra with an $\\mathrm{EC}\\mathrm{\\bar{M}}^{46}$ . A schematic plot of electrochemical impedance spectra during cycling and the corresponding ECM are complemented in Supplementary Figure 8. \n\n![](images/2123dbc77bbdd2f98db592fc04f3dd3ab1bd47cdafbd9417782294d6f9ced749.jpg) \nFig. 4 Results of battery capacity estimation with the input of three features [Var, Ske, Max] by different estimation methods. The capacity results are uniformized by the nominal capacity for comparison. root-mean-square error (RMSE) of battery capacity estimation ${\\bf\\Pi}({\\bf a})$ , test results of estimated capacity versus real capacity by ElasticNet (b), XGBoost $(\\bullet),$ and Support Vectors Regression (SVR) (d). \n\n
Table 2 Test means root-mean-square error (RMSE) of different models using voltage-based features for battery capacity estimation.
Features fromMethodsTest RMSE on Dataset 1
Rest voltage-basedLinear model250.025
Constant current charge voltage- basedRandom forest regression160.010
Incremental capacity analysis transformationLinear model200.013
Constant current-constant voltage Gaussian process charge voltage-basedregression440.011
\n\nBasically, an increase of R0 is likely due to contact loss and the reduction of ionic conductivity in the electrolyte47. R1 represents the resistance associated with the anode solid electrolyte interphase (SEI) indicated by the semicircle at high frequencies46. R2 is the charge-transfer resistance describing the rate of electrochemical reaction, which is related to the loss of electrode material through particle cracking18,48. The capacity loss of the cycled cells in dataset 1 and dataset 2 has been investigated by in situ neutron powder diffraction in our previous work42, which exhibits that the decrease in lithium content in the positive and negative electrodes correlates well with the observed discharge capacity. Both positive and negative electrodes do not decompose to other crystalline phases during cycling, but the lithium loss in the electrodes leading to lithiated material loss is traced by detecting changes in the lattices of the electrodes. The lithiated material loss and the SEI formation are suspected to contribute to the lithium loss. \n\nHerein, the dominating aging factors for each cycling group are discussed by fitted electrochemical impedance parameters in \n\nFig. 5. The coefficient of determination $(\\mathbb{R}^{2})$ of each measured impedance spectrum between the raw and fitted data is summarized in Supplementary Table 12. All $\\mathrm{R}^{2}$ values are greater than 0.999, indicating the credible fitting accuracy. All the raw and fitted impedance data can be found from the data availability. By comparison of the resistance increment from the initial value $(\\dot{\\mathrm{R}}_{\\mathrm{init}})$ for all three type cells, the increment of R0 is minimal (Fig. 5a–c), followed by R1 (Fig. 5d–f). R2 shows the highest increase during the battery capacity fade as shown in Fig. 5g–i. The dominating degradation factors are different under different working conditions. For the NCA cell, as shown in Fig. 5a, the CY25-0.25/1 shows a steady and relatively small increase of R0, nevertheless, its R1 in Fig. 5d shows an accelerated rise, indicating the increase in the thickness of the SEI layer. The R2 of CY25- $0.25/1$ in Fig. $5\\mathrm{g}$ presents a similar increasing trend to its R0. The R0 of $\\mathrm{CY}25–0.5/1$ and $\\mathrm{CY}25–1/1$ in Fig. 5a remains the largest resistive contribution throughout, but their R1 and R2 are relatively lower than that of others, which indicates a more serious cell degradation such as electrolyte dry-out or contact loss likely caused by lithium plating47,49. For the results of NCM cells in Fig. 5b, e, h, all resistances of $\\mathrm{CY}25–0.5/1$ increase slowly, while resistances of cells cycled at 35 and $45^{\\circ}\\mathrm{C}$ exhibit a large increase rate. For the $\\mathrm{{NCA}+\\mathrm{{NCM}}}$ cells, the influence of discharge rate is mainly represented by R1 by comparing the results in Fig. 5c, f, i. The CY25-0.5/4 SEI resistance increase in Fig. 5f is significantly slower than that of other cycling conditions. The temperature influence on the degradation mechanism can be seen in Fig. 5g, h, in which the increase of R2 is associated mainly with the increase of ambient temperature. The cells cycled at 45 and $35^{\\circ}\\mathrm{C}$ mainly lead to an increase of R2, which could be associated with the positive active material loss, e.g., particle cracking and pulverization50,51. The diversity of the battery internal degradation mechanisms results in various degradation paths, which can explain the difficulty in applying a simple linear model on the battery capacity estimation. Additionally, it seems that different battery types follow to some extent similar degradation rules, e.g., the exponential rise of R2, inspiring the use of transfer learning in the following part. \n\n![](images/ccf20298f3335ec1843de072b3e31f8a592c3be7a802cde118b2e0d6de433308.jpg) \nFig. 5 AC electrochemical impedance variations of the lithium-ion cells during cycling. The resistance increment from the initial value $(R_{\\mathrm{init}})$ is calculated for comparison. The ohmic resistance of NCA cells (a), NCM cells $(\\pmb{\\ b})$ , and ${\\mathsf{N C A}}+{\\mathsf{N C M}}$ cells (c). SEI resistance of NCA cells (d), NCM cells (e), and NCA $+N C M$ cells (f). Charge transfer resistance of NCA cells $\\mathbf{\\sigma}(\\mathbf{g})$ , NCM cells ${\\bf\\Pi}({\\bf h})$ , and $N C A+N C M$ cells (i). Only resistances before the capacity reducing to $71\\%$ of nominal capacity are shown to be consistent with the datasets in the study. The coefficient of determination $(R^{2})$ between the raw and fitted impedance data is summarized in Supplementary Table 12. The SEI resistances are not identified in some cycles (seen in Supplementary Table 12) for the NCA battery (d) and NCM battery (e). The shared information of raw impedance data and fitted data can be found in the data availability. \n\nApproach verification by transfer learning. The transfer learning (TL) method, which is applied to improve the learning ability by rebuilding the machine learning model using a relatively small amount of newly collected data, is proposed for easy adaption to the variation of voltage features existing in dataset 2 and dataset 3 in which different batteries and cycling conditions are used. The model weights are pre-trained through dataset 1 to obtain the base model. Then, some new data units from dataset 2 and dataset 3 are set as the input variable to re-train the TL model. Different data selection methods are discussed in Supplementary Note 4 and Supplementary Table 13, depicting that the variation of working conditions is necessary to improve the accuracy of the model estimation. One cell is randomly selected from each cycling condition in dataset 2 and dataset 3, then the data units in each cell are chosen with an interval of 100 cycles as the input variables for the re-training of TL models (Strategy D in Supplementary Note 4). The sizes of the input variable are summarized in Supplementary Table 14 (occupying $0.06\\%$ of dataset 2 and $0.35\\%$ of dataset 3). Verification on dataset 2 and dataset 3 without changing any weights of the base model is used as a zeroshot learning (ZSL) reference. The full base model is retrained using the same input variables from dataset 2 and dataset 3 as a No TL comparison. Two TL methods (TL1 and TL2) with fine-tuning strategies are activated to adjust the weights of a newly added layer, while the weights of other layers remain unchanged. TL1 means that a linear transformation layer is added before the output of capacity. TL2 means that a linear transformation layer before the base model is constructed to adapt the input features as illustrated in Supplementary Fig. 9. The test RMSEs are compared in Table 3. \n\nThe ZSL strategy obtains more than $3.4\\%$ test RMSE on all datasets directly using the base models. The error between the estimated capacity and real capacity is quite large as shown in Supplementary Fig. 10, meaning that the differences in battery types and materials cannot be ignored. When the base model is retrained in the No TL strategy, the XGBoost reaches a $2.9\\%$ test RMSE on dataset 2 and a $2.0\\%$ test RMSE on dataset 3, and the SVR gives no obvious improvement in the accuracy (Supplementary Fig. 11 and Supplementary Table 15). When the TL1 is applied on dataset 2 and dataset 3, the test RMSE of the SVR method goes down to 2.6 and $3.5\\%$ respectively, but a high number of outliers still appears in Supplementary Fig. 12. The results of estimated capacity versus real capacity by TL2 are presented in Fig. 6. The test RMSE is reduced to $2.4\\%$ by the XGBoost using the TL2 on dataset 2, noting that the performance of XGBoost using the No TL on dataset 3 is better than that of TL, which could be ascribed to the narrow distribution of capacity fade in dataset 3. The best accuracies on dataset 2 and dataset 3 are all reached by SVR using the TL2, showing test RMSEs of 1.7 and $1.6\\%$ , respectively. It can be concluded that the use of TL2 improves the estimation accuracy, and the reason behind the accuracy improvement is that a linear transformation of the input features helps the model adapt to the differences in battery types but similarity degradation modes. Interestingly, we find that the SVR is more reliable and suitable for transfer learning than the XGBoost with a small amount of newly collected data. The possible reason is that the XGBoost is a discrete gradient boosting framework, the output of the model is limited by the base model even if a new layer is added before the base model, whereas the SVR is a kernel-based framework, in which the continuous calculation achieves a better prediction under the designed TL2. In summary, the proposed approach using the relaxation voltage curve is useful to estimate the battery capacity, and the transfer learning improves the accuracy of capacity estimation requiring little tuning to adapt to the difference in batteries. \n\n
Table 3 Test RMSEs of battery capacity estimation using zero-shot learning (ZSL) and different transfer learning (TL) methods on dataset 2 and dataset 3.
MethodsDatasetZSLNo TLTL1TL2
XGBoostDataset2 Dataset30.038 0.0380.029 0.0200.0270.024
Dataset 20.0340.0390.034 0.0260.024
Support vectorsDataset30.0730.0520.0350.017
regression0.016
\n\n# Discussion \n\nAccurate identification of lithium-ion battery capacity facilitates the accurate estimation of the driving range which is a primary concern for EVs. An approach without requiring information from the previous cycling to estimate battery capacity is proposed. The proposed approach uses three statistical features ([Var, Ske, Max]) extracted from the voltage relaxation curve as input to predict the capacity in the next cycle. The transfer learning embedding machine learning methods is applied on 130 cells to establish a suitable model and for the verification of the approach. The best base model achieves a root-mean-square error of $1.1\\%$ . The transfer learning adding a linear transformation layer before the base model shows good predictive ability within a RMSE of $1.7\\%$ on different batteries. The retraining of transfer learning only needs a small number of data units on the condition that a variation of the input data needs to be guaranteed to improve the applicability of the proposed approach. \n\n![](images/10f044569c66e89142c2f8538156dc47a10e75b4e279c382361b91bca77134c7.jpg) \nFig. 6 Test results of estimated capacity versus real capacity by transfer learning. The capacity results are uniformized by the nominal capacity for comparison. Results of TL2 embedding XGBoost method (a) and embedding SVR (b) on dataset 2. Results of TL2 embedding XGBoost method (c) and embedding SVR (d) on dataset 3. Additional results are disclosed in Supplementary Figs. 10–12. \n\nThe relaxation process of a battery after full charge is easily obtained without the requirement of specific working conditions and voltage ranges, providing a new possibility for battery capacity estimation using data-driven methods in the system implementation of EV applications. \n\n# Methods \n\nCell selection and cycling. Commercially available lithium-ion batteries, i.e., LG INR18650-35E (3.5 Ah, 3.6 V), Samsung INR18650-MJ1 (3.5 Ah, 3.6 V), and Samsung INR18650-25R (2.5Ah, 3.6 V), have been tested. More battery specifications are listed in Supplementary Table 4. The positive electrode compositions of the INR18650-35E battery and INR18650-MJ1 battery are $\\mathrm{LiNi}_{0.86}\\mathrm{Co}_{0.11}\\mathrm{Al}_{0.03}\\mathrm{O}_{2}$ and $\\mathrm{Li}(\\mathrm{Ni}_{0.83}\\mathrm{Co}_{0.11}\\mathrm{Mn}_{0.07})\\mathrm{O}_{2}$ respectively, and the negative electrodes for both cell types have roughly $97\\mathrm{wt\\%}$ C and $2\\mathrm{wt\\%}$ Si as well as traces of H, N, and S from Sorensen et al.42. The positive electrode of the INR18650-25R battery is the blend of 42 (3) wt. $\\%$ $\\mathrm{Li}(\\mathrm{NiCoMn}){\\mathrm{O}}_{2}\\cdot5\\xi$ 8 (3) wt.% $\\mathrm{Li}(\\mathrm{NiCoAl})\\mathrm{O}_{2}$ , and the negative electrode is graphite from ref. 18. The INR18650-35E battery is named as NCA battery. The INR18650-MJ1 is named as NCM battery. The INR18650-25R is named as $\\mathrm{{NCM+NCA}}$ battery according to the positive electrode. A potentiostat (BioLogic BCS-815, France) is employed for cell cycling. The measurements are conducted at 25, 35, and $45^{\\circ}\\mathrm{C}$ in a climate chamber (BINDER, $\\pm0.2^{\\circ}\\mathrm{C}$ , Germany). Long-term cycling is conducted on a total of 130 cells with a summary of cycling conditions as provided in Table 1. A schematic connection of the potentiostat, chamber, and cells is shown in Supplementary Figure 13. For the NCA and NCM batteries, the metal taps are spot-welded to the cells, and the contact is soldered to the metal taps. A four-wire holder is used for the $\\mathrm{{NCM+NCA}}$ battery. For partially charged/ discharged NCA and NCM cells, the electrochemical impedance is measured in the fully charged state using a frequency range of $10\\mathrm{kHz}$ to $50~\\mathrm{mHz}$ (20 data points per decade of frequency) and a potential amplitude of $20\\mathrm{mV}$ . 30 min are set at the open circuit voltage before the electrochemical impedance tests. The electrochemical impedance is tested every 25 cycles for the NCA battery and every 50 cycles for the NCM battery. For the $\\mathrm{{NCM+NCA}}$ battery, the electrochemical impedance is conducted every 50 cycles at full charge in a range of $10\\mathrm{kHz}$ to $0.01\\mathrm{Hz}$ (6 data points per decade of frequency) with a sinusoidal amplitude of 250 mA. 60 min are set at the open circuit voltage before the electrochemical impedance tests. The NCA cells and NCM cells are tested from 2016 to 2018, and the $\\mathrm{{NCM+NCA}}$ cells are cycled in 2020. Different experimenters at different test periods are responsible for the difference in battery connection methods and experimental parameters in AC impedance tests, e.g., perturbation modes, perturbation amplitudes, and open circuit voltage time. \n\nMachine learning methods. Two transfer learning strategies embedding the XGBoost method and SVR method are applied in our study, and an illustration of the implemented transfer learning process is shown in Supplementary Fig. 9. The algorithms of the ElasticNet method, XGBoost method, and SVR method are introduced in Supplementary Note 5. \n\n(1) The base model is trained on all experimental data of NCA batteries (dataset 1). Firstly, the base model is directly verified on dataset 2 and dataset 3 without changing model weights as a zero-shot learning (ZSL) reference. \n(2) The base model is retrained using some new data units (Strategy D in Supplementary Note 4) as input variables from dataset 2 and dataset 3 as a No TL comparison. \n(3) Two transfer learning strategies (TL1 and TL2) are proposed by adding layers behind and in front of the base model. All weights in the base model are frozen in the transfer learning strategies except the newly added layer. In detail, TL1 means that a linear transformation layer is added before the output of capacity, which is described as \n\n$$\n\\mathrm{Q}^{\\prime}=\\mathrm{wQ}+\\mathrm{b}\n$$ \n\nTL2 means that a linear transformation layer is constructed to adapt the input features, which is described as \n\n$$\n\\left[\\begin{array}{l}{\\mathrm{Var}^{\\prime}}\\\\ {\\mathrm{Ske}^{\\prime}}\\\\ {\\mathrm{Max}^{\\prime}}\\end{array}\\right]=W\\left[\\begin{array}{l}{\\mathrm{Var}}\\\\ {\\mathrm{Ske}}\\\\ {\\mathrm{Max}}\\end{array}\\right]+b\n$$ \n\n$w,W_{;}$ , and $b$ are the weights in the added layer. The target dataset from dataset 2 and dataset 3 are selected to train the new layer weights. \n\nThe transfer learning models are verified on the remaining dataset 2 and dataset 3 respectively. The test RMSEs are compared in Table 3, and the estimation results are presented in Fig. 6 and Supplementary Figs. 10–12 for visualization purposes. \n\n# Data availability \n\nThe data generated in this study have been deposited in the Zenodo database under accession code [https://doi.org/10.5281/zenodo.6379165]. \n\n# Code availability \n\nThe data processing is performed in python and is available at [https://github.com/YixiuWang/data-driven-capacity-estimation-from-voltage-relaxation]. Code for the modeling work is available from the corresponding authors upon request. \n\nReceived: 1 August 2021; Accepted: 1 April 2022; Published online: 27 April 2022 \n\n# References \n\n1. Bresser, D. et al. Perspectives of automotive battery R&D in China, Germany, Japan, and the USA. J. Power Sources 382, 176–178 (2018). \n2. Harper, G. et al. Recycling lithium-ion batteries from electric vehicles. Nature 575, 75–86 (2019). \n3. Waag, W., Käbitz, S. & Sauer, D. U. Experimental investigation of the lithiumion battery impedance characteristic at various conditions and aging states and its influence on the application. Appl. Energy 102, 885–897 (2013). Xiong, R., Li, L. & Tian, J. Towards a smarter battery management system: a critical review on battery state of health monitoring methods. J. Power Sources 405, 18–29 (2018). \n5. Roman, D., Saxena, S., Robu, V., Pecht, M. & Flynn, D. Machine learning pipeline for battery state-of-health estimation. Nat. Mach. Intell. 3, 447–456 (2021). \n6. Li, W. et al. Online capacity estimation of lithium-ion batteries with deep long short-term memory networks. J. Power Sources 482, 228863 (2021). \n7. Liu, K., Shang, Y., Ouyang, Q. & Widanage, W. D. A data-driven approach with uncertainty quantification for predicting future capacities and remaining useful life of lithium-ion battery. IEEE Trans. Ind. Electron. 68, 3170–3180 (2020). \n8. Hu, X., Xu, L., Lin, X. & Pecht, M. Battery lifetime prognostics. Joule 4, 310–346 (2020). \n9. Severson, K. A. et al. Data-driven prediction of battery cycle life before capacity degradation. Nat. Energy 4, 383–391 (2019). \n10. Zhang, Y. et al. Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning. Nat. Commun. 11, 1–6 (2020). \n11. Ding, R. et al. Designing Ai-aided analysis and prediction models for nonprecious metal electrocatalyst-based proton-exchange membrane fuel cells. Angew. Chem. Int. Ed. 59, 19175–19183 (2020). \n12. Lin, C., Cabrera, J., Denis, Y., Yang, F. & Tsui, K. SOH estimation and SOC recalibration of lithium-ion battery with incremental capacity analysis & cubic smoothing spline. J. Electrochem. Soc. 167, 090537 (2020). \n13. Tagade, P. et al. Deep Gaussian process regression for lithium-ion battery health prognosis and degradation mode diagnosis. J. Power Sources 445, 227281 (2020). \n14. Chen, K. et al. Practical failure recognition model of lithium-ion batteries based on partial charging process. Energy 138, 1199–1208 (2017). \n15. Tang, X. et al. A fast estimation algorithm for lithium-ion battery state of health. J. Power Sources 396, 453–458 (2018). \n16. Li, Y. et al. Random forest regression for online capacity estimation of lithiumion batteries. Appl. Energy 232, 197–210 (2018). \n17. Goh, T., Park, M., Seo, M., Kim, J. G. & Kim, S. W. Capacity estimation algorithm with a second-order differential voltage curve for Li-ion batteries with NMC cathodes. Energy 135, 257–268 (2017). \n18. Zhu, J. et al. Investigation of lithium-ion battery degradation mechanisms by combining differential voltage analysis and alternating current impedance. J. Power Sources 448, 227575 (2020). \n19. Dubarry, M. & Beck, D. Analysis of synthetic voltage vs. capacity datasets for big data Li-ion diagnosis and prognosis. Energies https://doi.org/10.3390/ en14092371 (2021). \n20. Pei, P. et al. Capacity estimation for lithium-ion battery using experimental feature interval approach. Energy https://doi.org/10.1016/j.energy.2020.117778 (2020). \n21. Qiao, D. et al. Online quantitative diagnosis of internal short circuit for lithium-ion batteries using incremental capacity method. Energy 243, 123082 (2021). \n22. Li, X., Yuan, C. & Wang, Z. State of health estimation for Li-ion battery via partial incremental capacity analysis based on support vector regression. Energy https://doi.org/10.1016/j.energy.2020.117852 (2020). \n23. Lyu, Z., Gao, R. & Li, X. A partial charging curve-based data-fusion-model method for capacity estimation of Li-Ion battery. J. Power Sources https://doi. org/10.1016/j.jpowsour.2020.229131 (2021). \n24. Zhang, C. et al. An adaptive battery capacity estimation method suitable for random charging voltage range in electric vehicles. IEEE Trans. Ind. Electron. https://doi.org/10.1109/tie.2021.3111585 (2021). \n25. Baghdadi, I., Briat, O., Gyan, P. & Vinassa, J. M. State of health assessment for lithium batteries based on voltage–time relaxation measure. Electrochim. Acta 194, 461–472 (2016). \n26. Schindler, S., Bauer, M., Petzl, M. & Danzer, M. A. Voltage relaxation and impedance spectroscopy as in-operando methods for the detection of lithium plating on graphitic anodes in commercial lithium-ion cells. J. Power Sources 304, 170–180 (2016). \n27. von Lüders, C. et al. Lithium plating in lithium-ion batteries investigated by voltage relaxation and in situ neutron diffraction. J. Power Sources 342, 17–23 (2017). \n28. Qian, K. et al. State-of-health (SOH) evaluation on lithium-ion battery by simulating the voltage relaxation curves. Electrochim. Acta 303, 183–191 (2019). \n29. Attidekou, P. S., Wang, C., Armstrong, M., Lambert, S. M. & Christensen, P. A. A new time constant approach to online capacity monitoring and lifetime prediction of lithium ion batteries for electric vehicles (EV). J. Electrochem. Soc. 164, A1792 (2017). \n30. Li, W. et al. Digital twin for battery systems: cloud battery management system with online state-of-charge and state-of-health estimation. J. Energy Storage 30, 101557 (2020). \n31. Fang, Q., Wei, X., Lu, T., Dai, H. & Zhu, J. A state of health estimation method for lithium-ion batteries based on voltage relaxation model. Energies 12, 1349 (2019). \n32. Chen, C., Wei, Z. & Knoll, A. C. Charging optimization for li-ion battery in electric vehicles: a review. IEEE Transactions on Transportation Electrification, 1-1, https://doi.org/10.1109/tte.2021.3135525 (2021). \n33. Attia, P. M. et al. Closed-loop optimization of fast-charging protocols for batteries with machine learning. Nature 578, 397–402 (2020). \n34. Khan, A. B. & Choi, W. Optimal charge pattern for the high-performance multistage constant current charge method for the Li-ion batteries. IEEE Trans. Energy Convers. 33, 1132–1140 (2018). \n35. Li, K. et al. Battery life estimation based on cloud data for electric vehicles. J. Power Sources https://doi.org/10.1016/j.jpowsour.2020.228192 (2020). \n36. Wang, Z., Hong, J., Liu, P. & Zhang, L. Voltage fault diagnosis and prognosis of battery systems based on entropy and Z -score for electric vehicles. Appl. Energy 196, 289–302 (2017). \n37. Smart, J. & Schey, S. Battery electric vehicle driving and charging behavior observed early in the EV project. SAE Int. J. Alternative Powertrains 1, 27–33 (2012). \n38. Yang, J., Dong, J., Zhang, Q., Liu, Z. & Wang, W. An investigation of battery electric vehicle driving and charging behaviors using vehicle usage data collected in Shanghai, China. Transp. Res. Rec. 2672, 20–30 (2018). \n39. Zou, H. & Hastie, T. Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B. (Stat. Methodol.) 67, 301–320 (2005). \n40. Chen, T. & Guestrin, C. in Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. 785–794 (Association for Computing Machinery, 2016). \n41. Awad, M. & Khanna, R. in Efficient learning machines 67–80 (Springer, 2015). \n42. Sørensen, D. R. et al. Fatigue in high-energy commercial li batteries while cycling at standard conditions: an in situ neutron powder diffraction study. ACS Appl. Energy Mater. 3, 6611–6622 (2020). \n43. Baumhöfer, T., Brühl, M., Rothgang, S. & Sauer, D. U. Production caused variation in capacity aging trend and correlation to initial cell performance. J. Power Sources 247, 332–338 (2014). \n44. Yang, D., Zhang, X., Pan, R., Wang, Y. & Chen, Z. A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve. J. Power Sources 384, 387–395 (2018). \n45. Gaberšček, M. Understanding Li-based battery materials via electrochemical impedance spectroscopy. Nat. Commun. 12, 1–4 (2021). \n46. Meddings, N. et al. Application of electrochemical impedance spectroscopy to commercial Li-ion cells: a review. J. Power Sources 480, 228742 (2020). \n47. Schuster, S. F. et al. Nonlinear aging characteristics of lithium-ion cells under different operational conditions. J. Energy Storage 1, 44–53 (2015). \n48. Schindler, S. & Danzer, M. A. A novel mechanistic modeling framework for analysis of electrode balancing and degradation modes in commercial lithiumion cells. J. Power Sources 343, 226–236 (2017). \n49. Bauer, M., Guenther, C., Kasper, M., Petzl, M. & Danzer, M. A. Discrimination of degradation processes in lithium-ion cells based on the sensitivity of aging indicators towards capacity loss. J. Power Sources 283, 494–504 (2015). \n50. Zhu, J. et al. Low-Temperature Separating Lithium-Ion Battery Interfacial Polarization Based on Distribution of Relaxation Times (DRT) of Impedance. IEEE Trans. Transportation Electrification 7, 410–421 (2020). \n51. Stiaszny, B. et al. Electrochemical characterization and post-mortem analysis of aged LiMn2O4–NMC/graphite lithium ion batteries part II: Calendar aging. J. Power Sources 258, 61–75 (2014). \n\n# Acknowledgements \n\nThis work contributes to the research performed at CELEST (Center for Electrochemical Energy Storage Ulm-Karlsruhe) and is supported in the frame of the Alexander von Humboldt Postdoctoral Research Program. Jiangong Zhu would like to thank the foundation of the National Natural Science Foundation of China (NSFC, Grant No. 52107230) and he is supported by the Fundamental Research Funds for the Central Universities. Haifeng Dai would like to thank the foundation of the National Natural Science Foundation of China (NSFC, Grant No. U20A20310). \n\n# Author contributions \n\nConceptualization, writing, and original draft preparation were done by J.Z., Y.W., and H.D. The experimental studies were performed by J.Z., L.M., M.J.M., and M.H. The computational studies are performed by Y.W., J.Z., and Y.H. R.B.G., Y.C., X.L., H.D., M.K., M.H., A.S., and H.E. were involved in the writing, review, and editing of this manuscript. H.D., M.K., X.W., and H.E. supervised the work. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-29837-w. \n\nCorrespondence and requests for materials should be addressed to Haifeng Dai or Michael Knapp. \n\nPeer review information Nature Communications thanks Penelope Jones, Shunli Wang, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\n# Reprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41586-021-04323-3", + "DOI": "10.1038/s41586-021-04323-3", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-04323-3", + "Relative Dir Path": "mds/10.1038_s41586-021-04323-3", + "Article Title": "Vertical MoS2 transistors with sub-1-nm gate lengths", + "Authors": "Wu, F; Tian, H; Shen, Y; Hou, Z; Ren, J; Gou, GY; Sun, YB; Yang, Y; Ren, TL", + "Source Title": "NATURE", + "Abstract": "Ultra-scaled transistors are of interest in the development of next-generation electronic devices(1-3). Although atomically thin molybdenum disulfide (MoS2) transistors have been reported(4), the fabrication of devices with gate lengths below 1 nm has been challenging(5). Here we demonstrate side-wall MoS2 transistors with an atomically thin channel and a physical gate length of sub-1 nm using the edge of a graphene layer as the gate electrode. The approach uses large-area graphene and MoS2 films grown by chemical vapour deposition for the fabrication of side-wall transistors on a 2-inch wafer. These devices have On/Off ratios up to 1.02 x 10(5) and subthreshold swing values down to 117 mV dec(-1). Simulation results indicate that the MoS2 side-wall effective channel length approaches 0.34 nm in the On state and 4.54 nm in the Off state. This work can promote Moore's law of the scaling down of transistors for next-generation electronics.", + "Times Cited, WoS Core": 332, + "Times Cited, All Databases": 358, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000918198200001", + "Markdown": "# Article \n\n# Vertical MoS transistors with sub-1-nm gate lengths \n\nhttps://doi.org/10.1038/s41586-021-04323-3 \n\nReceived: 1 December 2020 \n\nAccepted: 9 December 2021 \n\nPublished online: 9 March 2022 Check for updates \n\nFan Wu1,2,4, He Tian1,2,4 ✉, Yang Shen1,2,4, Zhan Hou1,2, Jie Ren1,2, Guangyang Gou1,2, Yabin Sun3, Yi Yang1,2 & Tian-Ling Ren1,2 ✉ \n\nUltra-scaled transistors are of interest in the development of next-generation electronic devices1–3. Although atomically thin molybdenum disulfide $(\\mathsf{M o S}_{2})$ transistors have been reported4, the fabrication of devices with gate lengths below 1 nm has been challenging5. Here we demonstrate side-wall $\\mathsf{M o S}_{2}$ transistors with an atomically thin channel and a physical gate length of sub-1 nm using the edge of a graphene layer as the gate electrode. The approach uses large-area graphene and $\\mathsf{M o S}_{2}$ films grown by chemical vapour deposition for the fabrication of side-wall transistors on a 2-inch wafer. These devices have On/Off ratios up to $1.02\\times10^{5}$ and subthreshold swing values down to 117 mV dec–1. Simulation results indicate that the $\\mathsf{M o S}_{2}$ side-wall effective channel length approaches $0.34\\mathrm{nm}$ in the On state and $4.54\\mathsf{n m}$ in the Off state. This work can promote Moore’s law of the scaling down of transistors for next-generation electronics. \n\nSince the first integrated circuit was built in the 1960s, silicon (Si) transistors have shrunk, following the guide of Moore’s law, so that more devices can be built on one chip6. Si transistors are now approaching the scaling limit when the gate lengths $(L_{\\mathrm{g}})$ scale down to below $5\\mathsf{n m}$ (ref. 7). Theoretical analysis indicates that short channel effects (SCEs), including direct source-to-drain tunnelling currents and the drain-induced barrier lowering (DIBL) effect, can influence the scaling down procedure8. The $L_{\\mathrm{g}}$ of state-of-art Si transistor is $3\\mathsf{n m}$ based on V-shaped grooves wet etching technology (ref. 9). It is very important to explore new materials with further $L_{\\mathrm{g}}$ scaling down potential. \n\nIn recent years, two-dimensional materials, covering a wide range of electrical conductivity from semi-metal, semiconductor to insulator, have attracted great attention for next-generation electronic devices4,10,11. Graphene, as a semi-metal material, shows high intrinsic electrical conductivity, and can be used as electrodes12–14. $\\mathsf{M o S}_{2}$ , as a representative for two-dimensional (2D) transition metal dichalcogenides (TMDCs), has a larger bandgap $2.0\\mathrm{eV}$ for monolayer) than Si $(1.12\\mathrm{eV})^{4}$ . Also, its native n-doped behaviour, larger electron effective mass15 and lower dielectric constant16,17 lead to superior resistance to SCEs18. Therefore, $\\mathsf{M o S}_{2}$ is expected to be an ideal candidate to replace Si as the channel material in future transistors3,19. \n\nNowadays, for 2D material-based transistors, there are three typical device structures, as shown in Fig. 1a–c. Global back-gated transistors are widely used, because of the simple fabrication process20, but the relatively large effective oxide thickness (EOT) restrains the performance improvement. Another device structure is the local(top)-gated transistor. The EOT can be scaled down to sub-1 nm through atomic layer deposition (ALD) of oxide with high dielectric constant $(k)$ . Therefore, subthreshold swing (SS) can be greatly reduced. However, whether for a global gate or a local gate, the $L_{\\mathrm{g}}$ is typically determined by the resolution of lithography. Even using electron-beam lithography (EBL) technology, the $L_{\\mathrm{g}}$ can hardly be scaled down below 5 nm (ref. 21). In 2016, Desai et al. promoted a prototype of a junction-less 2D $\\mathsf{M o S}_{2}$ transistor using metallic single-wall carbon nanotube (SWCNT) as the gate electrode that demonstrated $1\\mathsf{n m}L_{\\mathrm{g}}$ (ref. 5). Among the three typical transistor structures, it is hard to further scale down $L_{\\mathrm{g}}$ below 1 nm. To date, it is very important to explore 2D TMDC transistors with gate length approaching the ultimate scaling limits. \n\nIn this work, we demonstrate side-wall 2D transistors gated by the edge of graphene that only have sub-1 nm gate length controlling the atomic $\\mathsf{M o S}_{2}$ channel (Fig. 1d). Large-area chemical vapour deposition (CVD) graphene and $\\mathsf{M o S}_{2}$ are used for wafer-scale production. The additional aluminium (Al) layer screens the vertical electrical field from the upper surface of graphene, so that the effective gate electrical field comes from the edge of graphene, which can only influence part of the vertical $\\mathsf{M o S}_{2}$ channel. The CVD graphene films have high electrical conductivity that can minimize the voltage drop along the gate layer. The $\\mathbf{0.34}\\mathsf{n m}$ gate length side-wall transistors show good switching characteristics, with the On/Off ratio up to $1.02\\times10^{5}$ . Sentaurus technology computer-aided design (TCAD) simulation results show that 2D planar characteristics of graphene provide the ability for gate control, which can deplete the vertical $\\mathsf{M o S}_{2}$ side-wall channel that align to the graphene plane. This work promotes a wafer-scale production method for scaling $L_{\\mathrm{g}}$ down below 1 nm. More importantly, it provides a great insight into the ultimate scaling, which can be regarded as the smallest gate-length transistor to date based to the best of our knowledge (Fig. 1e). \n\n# Fabrication and characterization \n\nTo fabricate the $0.34\\mathrm{nm}$ gate-length side-wall transistor, a monolayer CVD graphene film was first wet-transferred to a highly p-doped \n\n# Article \n\n![](images/1cd3f4571aeec2c9036fbdd28604b35a05c1ea1659795b584d0efae5084b8674.jpg) \nFig. 1 | Comparison of the $\\mathbf{0.34\\nm}L_{\\mathrm{g}}$ side-wall transistor with other typical structure transistors. a, Global (back) gate structure. b, Local (top) gate structure. c, 1 nm SWCNT buried gate structure19. d, Our 0.34 nm side-wall \n\n$\\mathsf{S i}/295\\mathsf{n m S i O}_{2}$ substrate followed by patterning graphene as the gate electrode (Fig. 2a). After that, EBL was performed and a 25 nm Al layer was deposited by electron-beam evaporation (Fig. 2b). To verify the electrical conductivity, the as-fabricated graphene transistor with Al contact is measured (Extended Data Fig. 1). The samples were naturally oxidized in the air for more than 3 days to form an approximately $5\\mathsf{n m}$ dense oxidization layer $(\\mathsf{A l O}_{x})$ around Al, including the formation of $\\mathsf{A l O}_{x}$ at the Al–graphene interfaces (Fig. 2c). The high-quality and dense $\\mathbf{AlO}_{x}$ layer at the Al–graphene interfaces are also confirmed (Extended Data Fig. 2). The Al layer also serves as the self-aligned mask for further graphene and $\\mathsf{S i O}_{2}$ inductively coupled plasma etching. Extra approximately $20\\mathsf{n m}\\mathsf{S i O}_{2}$ was etched to form the side-wall structure (Fig. 2d) and $14\\:\\mathrm{nm}$ high- ${\\cdot{k}\\mathsf{H f}}{0_{2}}$ as the gate dielectric was grown by means of ALD (Fig. 2e). The monolayer $\\mathsf{C V D M o S}_{2}$ film was then wet-transferred and patterned on the substrate. The Ti/Pd $(2\\mathsf{n m}/35\\mathsf{n m})$ ) as source and drain contacts were made on the $\\mathsf{M o S}_{2}$ to complete the device (Fig. 2f). The final device has five electrical terminals named source (S), drain (D), the Al screening layer (Al), $\\mathbf{0.34}\\mathsf{n m}$ graphene edge gate (G) and the fixed back-gated Si (B). By applying a negative voltage to the edge of the graphene gate to locally deplete the vertical $\\mathsf{M o S}_{2}$ channel, the transistor can be completely turned off. The idealized device structure is shown in Fig. 2g. The more detailed fabrication process can be seen in the Methods section. \n\nTo confirm the device structure, a representative sample after fabrication was characterized (Fig. 2h, i). For the false-coloured scanning electron microscopy (SEM) image, the purple region contains a monolayer graphene $'A l O_{x}/A l/A l O_{x}/\\mathrm{HfO}_{2}$ stack. The yellow and blue regions represent the $\\mathsf{M o S}_{2}$ channel and Ti/Pd metal contacts. The cross-section transmission electron microscopy (TEM) image shows the profile of the device core region; the layered structure of a vertical $\\mathsf{M o S}_{2}$ channel gated by the edge of graphene can be recognized. The topography $\\mathsf{M o S}_{2}$ film $/\\mathrm{Hf}\\mathbf{O}_{2}$ stack was smooth. The whole $\\mathsf{M o S}_{2}$ channel length is designed to be at most $1\\upmu\\mathrm{m}$ (approximately $500\\mathsf{n m}$ in the device of Fig. 2i) by considering the lift-off process. The spatial distribution of aluminium, hafnium, carbon, molybdenum, sulfur and oxygen was observed in the energy dispersive spectrometer (EDS) mapping of the core region (Fig. 2j and Extended Data Fig. 3), thus confirming the location of the monolayer graphene, ${\\mathsf{H f O}}_{2},$ Al, $\\mathsf{A l O}_{x}$ and monolayer $\\mathsf{M o S}_{2}$ in this device. In the fabrication flow, the CVD graphene and $\\mathsf{M o S}_{2}$ films were applied as gate and channel materials, which realizes wafer-scale production (Fig. 2k). \n\ntransistor with the edge of graphene as gate electrode. e, The physical limit of gate length by using different gate and channel conditions. \n\n# Electrical measurement \n\nFor the proposed side-wall gated transistor, there are three terminals that can modulate the carrier density of a $\\mathsf{M o S}_{2}$ channel: (1) the graphene layer terminal; (2) the Al screening layer terminal; and (3) the back-gated Si terminal. In the experiment, the graphene acts as the unique gate, while the back-gated Si terminal is fixed at $50\\mathrm{v}$ and the Al layer is fixed at $\\displaystyle{0\\vee}$ The Al layer screens the vertical electric field from the upper surface of graphene gate, so that only the electrical field from the edge of graphene can influence the vertical $\\mathsf{M o S}_{2}$ channel, realizing a $_{10.34\\mathsf{n m}}$ physical gate length, as shown in Fig. 1d, f. \n\nBack-gated $\\mathsf{M o S}_{2}$ transistors are first measured (15 typical devices, see Extended Data Fig. 4). The measured electrical results indicate that by applying positive back gate voltage $V_{\\mathrm{BS}}=50\\mathrm{V},$ , the lower extension $\\mathsf{M o S}_{2}$ region on $275\\mathsf{n m S i O}_{2}/14\\mathsf{n m H f O}_{2}$ can be tuned to relatively high electron carrier density. Then a typical proposed $0.34\\mathrm{nm}$ gate-length side-wall gated transistor with approximately 1 ${\\bf\\cdot}\\upmu\\mathrm{m}\\mathsf{M o S}_{2}$ channel length was measured. The drain-source current $(I_{\\mathrm{DS}})$ versus the voltage applied on graphene $(\\boldsymbol{V_{\\mathrm{Gr}}})$ transfer characteristics with $0.34\\mathrm{nm}$ side-wall gate at different drain bias $(V_{\\mathrm{DS}}=10\\mathrm{mV},1\\mathrm{v},3\\mathrm{v})$ are carried out at $V_{\\mathrm{BS}}=50$ V and the voltage applied at the Al layer $(V_{\\mathrm{Al}})$ is $_{0\\vee}$ in Fig. 3a, which demonstrate the feasibility of the graphene edge as a gate to turn off the channel. The SS value is $151\\mathsf{m V}\\mathsf{d e c}^{-1}$ at $V_{\\mathrm{DS}}=1\\mathrm{V}$ and the On/Off ratio can reach up to $3.44\\times10^{5}$ at $V_{\\mathrm{DS}}=3\\:\\mathrm{V}$ at room temperature. The DIBL effect is approximately $126\\mathsf{m}\\mathsf{V}^{-1}$ . The $I_{\\mathrm{DS}}{-}V_{\\mathrm{DS}}$ output curves under different values of $V_{\\mathrm{Gr}}$ bias (from −2.5 V to 2.5 V, 0.5 V step) at $V_{\\mathrm{BS}}=50\\mathrm{V}$ , $V_{\\mathrm{Al}}=0$ V are shown in Fig. 3b with a linear-like characteristic. The $I_{\\mathrm{DS}}-V_{\\mathrm{Gr}}$ transfer characteristics under different values of $V_{\\mathrm{BS}}$ bias (from $-30\\mathrm{v}$ to 50 V, 20 V step) at $V_{\\mathrm{DS}}=1\\mathrm{V}.$ , $V_{\\mathrm{Al}}=0$ V were also measured (Fig. 3c). By varying $V_{\\mathrm{BS}}$ from $-30\\mathrm{v}$ to 50 V, which can affect the extension of $\\mathsf{M o S}_{2}$ region, the On-state current increases from $4.1\\times10^{-9}$ A to $3.4\\times10^{-7}\\mathrm{A}$ at $V_{\\mathrm{DS}}=1\\mathrm{V}$ (Fig. 3c). Non-ideal On-state current $(3.4\\times10^{-7}\\mathrm{A})$ at $V_{\\mathrm{DS}}=1\\mathrm{V}$ and $V_{\\mathrm{BS}}=50\\mathrm{V}$ also proves the ultra-thin gate length owing to the present of an ungated region in the $\\mathsf{M o S}_{2}$ channel. In addition, the transfer curves slightly left shift under larger $V_{\\mathrm{BS}}$ because the $V_{\\mathrm{Gr}}$ has to be more negative to deplete the vertical $\\mathsf{M o S}_{2}$ channel owing to the ultra-thin $0.34\\mathrm{nm}$ gate length. The $I_{\\mathrm{DS}}^{}-V_{\\mathrm{BS}}^{}$ transfer characteristics with different $V_{\\mathrm{Al}}$ and $V_{\\mathrm{Gr}}$ at $V_{\\mathrm{DS}}=1$ V can verify the modulation ability of the side wall (Fig. 3d and Extended Data Fig. 5). The screening function of the Al layer is further verified by tuning both the Al layer and the graphene layer from $_{0\\vee}$ to 3 V; the On-state current effectively increases from \n\n![](images/de138de54dec2280816d4ae7a75b907b135323a80ddf921c7ab5ed95a8b3e6ed.jpg) \nFig. 2 | The $\\mathbf{0.34\\nm}$ gate-length side-wall monolayer $\\mathbf{MoS}_{2}$ transistor device structure and characterization. a–f, The process flow for the device fabrication. a, CVD graphene film wet transfer and pattern. b, Deposit Al layer. c, Natural oxidization process of Al layer. d, The $\\mathsf{S i O}_{2}$ self-aligned etching. e, ALD ${\\mathsf{H f O}}_{2}$ layer. f, CVD $\\mathsf{M o S}_{2}$ film wet transfer, pattern and deposit metal as contact. g, Schematic of side-wall gate structure with a monolayer $\\mathsf{M o S}_{2}$ channel and $0.34\\mathrm{nm}$ monolayer graphene edge gate. h, False-coloured SEM image of the device showing the ${\\mathsf{H f O}}_{2}$ gate dielectric (green), Al screening layer (purple), monolayer $\\mathsf{M o S}_{2}$ channel (yellow) and the Ti/Pd \nsource and drain electrodes (blue). i, Cross-sectional TEM image of a representative device showing the monolayer graphene edge gate, ${\\mathsf{H f O}}_{2}$ gate dielectric, Al screening layer and monolayer $\\mathsf{M o S}_{2}$ channel. j, EDS mapping showing the spatial distribution of aluminium, hafnium, carbon, molybdenum, sulfur and oxygen in the device region, confirming the location of the Al screening layer, ${\\mathsf{H f O}}_{2}$ dielectric, monolayer graphene and $\\mathsf{M o S}_{2}$ film. k, Optical image of a 2-inch wafer-scale fabrication of the $0.34\\:\\mathrm{nm}L_{\\mathrm{g}}$ side-wall transistors. \n\n$3.8\\times10^{-8}\\mathrm{A}$ to $6.9\\times10^{-7}{\\bf A}.$ . In the transfer characteristics (Fig. 3a, c, d), the leakage current from the monolayer graphene side-wall gate $(I_{\\mathrm{Gr}})$ , the Al screening layer $(I_{\\mathrm{Al}})$ and the highly p-doped Si substrate $(I_{\\mathrm{BS}})$ are shown, close to the noise level (less than $10^{-11}\\mathsf{A}$ ). The Off-state current of our $0.34\\mathrm{nm}$ gate-length side-wall transistors are also constrained by the leakage current level, which is $3.7\\times10^{-12}$ A in the device of Fig. $3\\mathsf{a}\\mathsf{-}\\mathsf{d}.$ Considering the $4\\upmu\\mathrm{m}$ channel width, the Off-state current density is less than $10^{-12}\\mathsf{A}\\upmu\\mathrm{m}^{-1}$ , meeting the requirement of $10^{-11}\\mathsf{A}\\upmu\\mathsf{m}^{-1}$ for $7\\mathsf{n m}$ node low stand-by power transistors22. \n\nThe discussed electrical characteristics above are from one typical device. The detailed electrical characteristic that demonstrates the tunability of the Al layer can be seen in Extended Data Fig. 6. To prove the reproducibility, another 49 devices were measured, including 28 devices with 1 $.\\upmu\\mathrm{m}$ channel length $(L_{\\mathrm{ch}})$ and 21 devices with $0.5\\upmu\\mathrm{m}L_{\\mathrm{ch}},$ see details in Extended Data Fig. 7. The $I_{\\mathrm{DS}}-V_{\\mathrm{Gr}}$ transfer curves from 10 representative devices with $L_{\\mathrm{ch}}=1\\upmu\\mathrm{m}$ at $V_{\\mathrm{DS}}=1\\mathrm{V}$ , $V_{\\mathrm{BS}}=50\\mathrm{V}$ and $V_{\\mathrm{Al}}=0~\\mathsf{V}$ (Fig. 3e) show the uniformity of these $\\mathbf{0.34\\nm}$ gate-length side-wall transistors. The distribution of On/Off ratio and SS value are collected (Fig. 3f), with the maximum On/Off ratio of $1.02\\times10^{5}$ at $V_{\\mathrm{DS}}=1\\mathrm{V}$ and the minimum SS value of 117 mV dec–1. Among the 50 measured devices, the maximum drive current density is $0.545\\upmu\\mathrm{A}\\upmu\\mathrm{m}^{-1}$ at $V_{\\mathrm{DS}}=1\\:\\mathrm{V}$ and $V_{\\mathrm{GS}}=2.4\\:\\mathrm{V}$ (device 40 in Extended Data Fig.  7). The On-state current can be further improved by decreasing the whole $\\mathsf{M o S}_{2}$ channel length. Details are discussed in the following TCAD simulation section. \n\n# TCAD simulation \n\nTo understand the electrical behaviours and the underline device physics, Sentaurus TCAD was performed (Fig. 4a). The detailed parameters about the graphene, $\\mathsf{M o S}_{2}$ and dielectric are shown in Extended Data Tables 1 and 2. The lower plane of the extended lateral $\\mathsf{M o S}_{2}$ channel is $10\\mathsf{n m}$ below the graphene gate plane in the simulation. The simulated $I_{\\mathrm{DS}}-V_{\\mathrm{GS}}$ curves have similar trends with the experimental curves (Fig. 4b). Both simulated and experimental curves show negative shifts as $\\boldsymbol{V_{\\mathrm{DS}}}$ becomes more positive, which indicates DIBL in small size transistors. The threshold voltage $(V_{\\mathrm{th}})$ in the simulation is slightly more negative than that in the experiment, which can be attributed to the idealized materials and interfaces. \n\nThe electric field contour plots in the On state $\\cdot V_{\\mathrm{DS}}=3\\:\\mathrm{V}$ , $V_{\\mathrm{Gr}}{=}2.4\\:\\mathsf{V}$ , $V_{\\mathrm{BS}}=50~\\mathrm{V}.$ $V_{\\mathrm{Al}}=0~\\mathsf{V}$ ) and Off state ( $\\cdot V_{\\mathrm{DS}}=3\\:\\mathrm{V}$ , $V_{\\mathrm{Gr}}=-1.5\\:\\mathrm{V}_{\\cdot}$ , $V_{\\mathrm{BS}}=50~\\mathrm{V}_{\\cdot}$ , $V_{\\mathrm{Al}}=0\\:\\mathrm{V})$ are shown in Fig. 4c, d. In the Off state (Fig. 4d), the effective gated electric field comes from the edge of graphene, proving the $0.34\\mathrm{nm}$ physical gate length. The electron density along the vertical $\\mathsf{M o S}_{2}$ channel in the On state $(V_{\\mathrm{Gr}}-V_{\\mathrm{th}}{=}0.26\\ V)$ and Off state $(V_{\\mathrm{Gr}}-V_{\\mathrm{th}}{=}-0.47\\:\\mathrm{V}$ ) under $V_{\\mathrm{DS}}=50\\mathrm{mV}$ , $V_{\\mathrm{BS}}=50\\mathrm{V}$ and $V_{\\mathrm{Al}}=0$ V are also shown in Fig. 4e, f, which has a region of low electron density and electric field. By defining the effective channel length $(L_{\\mathrm{eff}})$ as the channel region with electron density $n
Tch (nm)MoS Eg (eV)MoS2 εMoS2 x (eV)
0.652.003.934.20
1.301.594.71
1.951.474.90
2.601.446.24
3.251.427.71
10.41.3010.0
20.81.3010.5
\n\n# Article \n\nExtended Data Table 2 | The detailed parameters for $H f O_{2}$ and natural $\\pmb{\\Delta}\\mathfrak{l}\\pmb{\\ O}_{\\mathbf{x}}$ . Here, ${\\boldsymbol{\\mathsf{T}}}_{\\mathsf{c h}}$ is the channel thickness, $\\overline{E}_{9}$ is the band gap, ε is the relative dielectric constant, $\\pmb{\\ x}$ is the electron affinity, ${\\mathfrak{m}}_{\\mathtt{e}}$ is the electron effective mass, ${\\upmu}_{\\mathsf{e}}$ is the electron mobility, the initial doping of $\\boldsymbol{\\mathsf{M o}}_{\\mathsf{s}2}$ is $10^{16}\\small{\\sim}10^{17}\\mathsf{c m}^{-3}$ , and graphene is modeled as metal with work function set as 4.6 eV. \n\n
HfO2 εme (mo)AlOxεAIOxx (eV)AIOx Eg (eV)
17.0~18.00.559.003.706.70
" + }, + { + "id": "10.1103_PhysRevX.12.031042", + "DOI": "10.1103/PhysRevX.12.031042", + "DOI Link": "http://dx.doi.org/10.1103/PhysRevX.12.031042", + "Relative Dir Path": "mds/10.1103_PhysRevX.12.031042", + "Article Title": "Beyond Conventional Ferromagnetism and Antiferromagnetism: A Phase with Nonrelativistic Spin and Crystal Rotation Symmetry", + "Authors": "Smejkal, L; Sinova, J; Jungwirth, T", + "Source Title": "PHYSICAL REVIEW X", + "Abstract": "Recent series of theoretical and experimental reports have driven attention to time-reversal symmetry -breaking spintronic and spin-splitting phenomena in materials with collinear-compensated magnetic order incompatible with conventional ferromagnetism or antiferromagnetism. Here we employ an approach based on nonrelativistic spin-symmetry groups that resolves the conflicting notions of unconventional ferromagnetism or antiferromagnetism by delimiting a third basic collinear magnetic phase. We derive that all materials hosting this collinear-compensated magnetic phase are characterized by crystal-rotation symmetries connecting opposite-spin sublattices separated in the real space and opposite-spin electronic states separated in the momentum space. We describe prominent extraordinary characteristics of the phase, including the alternating spin-splitting sign and broken time-reversal symmetry in the nonrelativistic band structure, the planar or bulk d-, g-, or i-wave symmetry of the spin-dependent Fermi surfaces, spin -degenerate nodal lines and surfaces, band anisotropy of individual spin channels, and spin-split general, as well as time-reversal invariant momenta. Guided by the spin-symmetry principles, we discover in ab initio calculations outlier materials with an extraordinary nonrelativistic spin splitting, whose eV-scale and momentum dependence are determined by the crystal potential of the nonmagnetic phase. This spin -splitting mechanism is distinct from conventional relativistic spin-orbit coupling and ferromagnetic exchange, as well as from the previously considered anisotropic exchange mechanism in compensated magnets. Our results, combined with our identification of material candidates for the phase ranging from insulators and metals to a parent crystal of cuprate superconductors, underpin research of novel quantum phenomena and spintronic functionalities in high-temperature magnets with light elements, vanishing net magnetization, and strong spin coherence. In the discussion, we argue that the conflicting notions of unconventional ferromagnetism or antiferromagnetism, on the one hand, and our symmetry-based delimitation of the third phase, on the other hand, favor a distinct term referring to the phase. The alternating spin polarizations in both the real-space crystal structure and the momentum-space band structure characteristic of this unconventional magnetic phase suggest a term altermagnetism. We point out that d-wave altermagnetism represents a realization of the long-sought-after counterpart in magnetism of the unconventional d-wave superconductivity.", + "Times Cited, WoS Core": 349, + "Times Cited, All Databases": 356, + "Publication Year": 2022, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000865310200001", + "Markdown": "# Beyond Conventional Ferromagnetism and Antiferromagnetism: A Phase with Nonrelativistic Spin and Crystal Rotation Symmetry \n\nLibor Šmejkal,1,2 Jairo Sinova,1,2 and Tomas Jungwirth 2,3 1Institut für Physik, Johannes Gutenberg Universität Mainz, 55128, Mainz, Germany \n2Institute of Physics, Czech Academy of Sciences, Cukrovarnická 10, 162 00, Praha 6, Czech Republic \n3School of Physics and Astronomy, University of Nottingham, NG7 2RD, Nottingham, United Kingdom \n\n![](images/bbffaff04f153d6fc44b3ab0cee97a7e457085a9d6d7fdd1932e06c568ee5257.jpg) \n\n(Received 6 February 2022; revised 6 April 2022; accepted 11 August 2022; published 23 September 2022) \n\nRecent series of theoretical and experimental reports have driven attention to time-reversal symmetrybreaking spintronic and spin-splitting phenomena in materials with collinear-compensated magnetic order incompatible with conventional ferromagnetism or antiferromagnetism. Here we employ an approach based on nonrelativistic spin-symmetry groups that resolves the conflicting notions of unconventional ferromagnetism or antiferromagnetism by delimiting a third basic collinear magnetic phase. We derive that all materials hosting this collinear-compensated magnetic phase are characterized by crystal-rotation symmetries connecting opposite-spin sublattices separated in the real space and opposite-spin electronic states separated in the momentum space. We describe prominent extraordinary characteristics of the phase, including the alternating spin-splitting sign and broken time-reversal symmetry in the nonrelativistic band structure, the planar or bulk $d\\cdot$ -, $g-$ , or $i$ -wave symmetry of the spin-dependent Fermi surfaces, spindegenerate nodal lines and surfaces, band anisotropy of individual spin channels, and spin-split general, as well as time-reversal invariant momenta. Guided by the spin-symmetry principles, we discover in ab initio calculations outlier materials with an extraordinary nonrelativistic spin splitting, whose eV-scale and momentum dependence are determined by the crystal potential of the nonmagnetic phase. This spinsplitting mechanism is distinct from conventional relativistic spin-orbit coupling and ferromagnetic exchange, as well as from the previously considered anisotropic exchange mechanism in compensated magnets. Our results, combined with our identification of material candidates for the phase ranging from insulators and metals to a parent crystal of cuprate superconductors, underpin research of novel quantum phenomena and spintronic functionalities in high-temperature magnets with light elements, vanishing net magnetization, and strong spin coherence. In the discussion, we argue that the conflicting notions of unconventional ferromagnetism or antiferromagnetism, on the one hand, and our symmetry-based delimitation of the third phase, on the other hand, favor a distinct term referring to the phase. The alternating spin polarizations in both the real-space crystal structure and the momentum-space band structure characteristic of this unconventional magnetic phase suggest a term altermagnetism. We point out that $d$ -wave altermagnetism represents a realization of the long-sought-after counterpart in magnetism of the unconventional $d$ -wave superconductivity. \n\nDOI: 10.1103/PhysRevX.12.031042 \n\nSubject Areas: Condensed Matter Physics, Magnetism, Spintronics \n\n# I. INTRODUCTION \n\nRecent predictions of time-reversal symmetry breaking [1–3] and spin splitting [1,2,4–12] in electronic bands, typical of ferromagnets, in materials with collinearcompensated magnetic order, typical of antiferromagnets, are incompatible with the conventional division into the ferromagnetic and antiferromagnetic phases. The consequences of the intriguing electronic structure of these collinear-compensated magnets have been illustrated by predictions of odd-under-time-reversal responses, including anomalous Hall and Kerr effects [1–3,9,13–15], as well as spin current, giant and tunneling magnetoresistance, and spin-torque phenomena [6,11,12,16–18]. Some of the predictions of these unexpected responses have been already supported by experiments [9,19–22]. \n\nIn this article, we resolve the conflicting notions of unconventional ferromagnetism or unconventional antiferromagnetism by deriving that on the basic level of uncorrelated nonrelativistic nonfrustrated (collinear) magnetism, symmetry allows for three instead of two distinct phases. We employ a symmetry approach based on a nonrelativistic spin-group formalism [23–25]. To explain its merits, we first recall the conventional theory frameworks. \n\nA traditional approach to the basic categorization of a magnetic materials phases based on models focusing on spatial and spin arrangements of magnetic atoms alone while omitting nonmagnetic atoms in the lattice can be traced back to the seminal works on Ne´el’s collinear antiferromagnetism [26]. Subsequently, the approach was employed, e.g., when discussing the competition of Ne´el’s antiferromagnetism and the spin-liquid phase in the context of high-temperature cuprate superconductors [27]. Recently, models considering clusters of magnetic atoms have underpinned the multipole theory of the anomalous Hall effect in noncollinear-compensated magnets [28], and of the nonrelativistic spin splitting in collinearcompensated magnets [5,8]. However, these models are principally incapable of providing a general classification and description of the underlying magnetic phases in prominent families of materials. A specific example is rutile crystals with the collinear-compensated magnetic order [1,4,7], in which the nonmagnetic atoms have been recognized to play a key role in the anomalous timereversal symmetry-breaking spin phenomena [1,3]. In particular, $\\mathrm{RuO}_{2}$ is a prominent room-temperature metallic member of this rutile family, in which the unconventional spin physics and spintronics have already been studied both theoretically and experimentally [1,4,16–18,20–22]. \n\nA traditional symmetry description of the full structure of magnetic crystals, including the nonmagnetic atoms, considers transformations in coupled real physical space and the space of magnetic moment vectors. In other words, the transformations acting on the coordinates of the atoms, subject to the standard crystallographic restrictions, simultaneously act on the components of the magnetic moment vectors [24,25,29] (see Supplemental Material Sec. I Fig. S1 [30]). This symmetry formalism naturally arises from the classical orbital-current model of magnetic moments [31], as well as from the relativistic quantummechanical description of coupled spin and orbital degrees of freedom of electrons [31,32]. The corresponding magnetic groups [29,31,33–35] have been broadly applied in the research of equilibrium and nonequilibrium phenomena, including their modern topological variants [36–38], and have represented the primary tool for a systematic classification of hundreds of magnetic structures in materials databases [35,39]. \n\nMagnetic groups are indispensable for the description of effects governed by relativistic physics. However, the inherent relativistic nature of the magnetic-group symmetry transformations in coupled real and spin space makes the magnetic groups generally unsuitable for the classification of nonrelativistic phenomenology, which typically plays the leading role in magnetism [23,40]. Magnetic space groups of type II describing time-reversal invariant crystals without a magnetic order, are an exception for which a transition to a nonrelativistic physics description in decoupled spin and real space can be generally performed by making a direct product with the SU(2) group of spinspace rotation transformations [24,28]. For the remaining magnetic space groups of types I, III, and IV encompassing collinear as well as noncollinear magnets [7,10], a transition to the nonrelativistic physics description is not available [5,8,28]. Therefore, the strong nonrelativistic spinsplitting phenomena are not generally described by magnetic groups augmented by spin-space transformations [7,10]. \n\nIn this article, we use an approach to rigorously and systematically classify and describe nonrelativistic magnetic materials phases and their physical properties based on the spin-group formalism [23–25] of symmetry transformations in decoupled real and spin space. The spin groups are a generalization of the conventional magnetic groups [23–25]. They consider pairs of transformations $[R_{i}\\backslash|R_{j}]$ , where the transformations on the left of the double vertical bar act only on the spin space and on the right of the double vertical bar only on the real space [23–25] (see Supplemental Material Sec. I Fig. S1 [30]). The symmetry landscape of the spin groups is much richer because, in general, different rotation transformations can simultaneously act on the spin and real space, and only the transformations in the real space are crystallographically restricted. (The same rotation transformations simultaneously acting on the spin and real space are contained in both magnetic and spin groups.) Despite their richness, studies based on the spin symmetries have appeared only sporadically in the literature. For example, in the past they were used for the classification of possible spin arrangements on crystals and spin dynamics, with an emphasis on complex noncollinear or disordered structures, while not focusing on the electronic structure [40]. Very recently, they have been applied in studies of magnons [41] or topological quasiparticles [42–45]. Overall, however, the spin-group formalism has remained largely unexploited and undeveloped [46]. \n\nThe nonrelativistic spin groups represent an example of approximate or so-called “hidden” symmetries in the sense that relativistic effects are generally present in all magnets. The key significance of the nonrelativistic spin groups is that they can offer a systematic symmetry description of physics that is commonly leading in magnetism and that arises from the strong nonrelativistic electromagnetic crystal potentials [23,40]. Here, by the electric crystal potential, we refer to the internal potential in the nonmagnetic phase of the crystal, as described, e.g., by the local density approximation of the density-functional theory (DFT); by the additional magnetic component, we refer to the modification of the internal crystal potential due to the transition to the magnetically ordered phase. Since the magnetic groups represent only a small subset of the spin groups [25], they are prone to omitting prominent magnetic phases dominated by the nonrelativistic electromagnetic crystal potentials. For example, the magnetic groups, which generally encompass collinear and noncollinear magnets, can determine only whether a net magnetization is allowed or not, but do not distinguish ferromagnets from antiferromagnets in which magnetization arises only as a weak relativistic perturbation [31]. For the band structures, the magnetic groups can be used to identify a violation of Kramers spin degeneracy [10,36,47–52]. However, both the magnetic-group formalism and Kramers theorem [53,54] entangle nonrelativistic and relativistic physics. Consequently, the nonrelativistic spin splitting in materials from the magnetic groups violating the Kramers spin degeneracy were identified by performing numerical DFT calculations with the relativistic spin-orbit coupling turned off [10]. \n\nIn our work, by employing and developing the spingroup formalism, we derive three distinct phases of nonrelativistic collinear magnetism: The first phase has one spin lattice (or opposite-spin sublattices not connected by any symmetry transformation). It corresponds to conventional ferromagnetism (ferrimagnetism) [31]. The second phase has opposite-spin sublattices connected by translation or inversion (or both), and corresponds to conventional antiferromagnetism [23,26,41]. The third phase has opposite-spin sublattices connected by rotation (proper or improper and symmorphic or nonsymmorphic) but not connected by translation or inversion. Unlike the conventional ferromagnetic phase with a nonrelativistic magnetization and spin-split bands that break time-reversal symmetry [31], and unlike the conventional antiferromagnetic phase with nonrelativistic spin-degenerate timereversal invariant bands and zero net magnetization [26,32,55–58], the third phase has split but equally populated spin-up and spin-down energy isosurfaces in the band structure that break time-reversal symmetry. The spingroup formalism allows us to provide a complete classification and description of the specifics of the spinmomentum locking in the band structure of the third phase. Our direct link of the spin groups to real material candidates establishes that the third phase is abundant. We also show that it is a strong, robust, and fundamental phase, as it does not require (but can coexist with) relativistic spin-orbit coupling, electronic correlations, or magnetic fluctuations or frustrations. We point out that our classification and description based on the spin-group formalism are universally applicable to any effective single-particle Kohn-Sham Hamiltonian, as well as for the Dyson-equation description of correlated or disordered systems. \n\nPrinciples based on the spin-group symmetries guide us to our discovery of outlier materials hosting the third phase, with an extraordinary microscopic spin-splitting mechanism, whose eV scale and momentum dependence are determined by the electric crystal potential, i.e., by the scale and momentum dependence of the band splitting of the nonmagnetic phase. It is fundamentally distinct from the earlier-considered various internal magnetic-interaction mechanisms [4,7,8,17,59,60], such as the anisotropic spin-dependent hopping in the magnetic state [8,17]. The spin-splitting mechanism in the third magnetic phase by the electric crystal potential is nonrelativistic and accompanied by zero net magnetization. Therefore, it also starkly contrasts with the conventional mechanisms of the ferromagnetic splitting due to the nonzero net magnetization, or the relativistic spin-orbit splitting due to the broken inversion symmetry. It opens a new paradigm for designing spin quantum phases of matter based on the strong crystalpotential effects complementing the widely explored relativistic or many-body correlation phenomena [61]. \n\nThe focus of our work is on the classification and description of the nonrelativistic band structures of materials hosting the third phase and the identification of new material candidates, which opens a range of potential science and technology implications of this magnetic phase. In the Supplemental Material Sec. I [30], we briefly comment on the links to relativistic effects and noncollinear magnetism [3]. \n\n# II. DERIVATION OF SPIN-GROUP CATEGORIZATION OF NONRELATIVISTIC COLLINEAR MAGNETISM \n\nWe start with the derivation of the three distinct spingroup types describing, respectively, the three nonrelativistic phases of collinear magnets. In general, spin groups can be expressed as a direct product $\\mathbf{r}_{s}\\times\\mathbf{R}_{s}$ of so-called spin-only group $\\mathbf{r}_{s}$ containing transformations of the spin space alone, and so-called nontrivial spin groups ${\\bf R}_{s}$ containing the elements $[R_{i}\\backslash|R_{j}]$ , but no elements of the spin-only group [24,25]. For the collinear spin arrangements on crystals, the spin-only group is given by [24,25] $\\mathbf{r}_{s}=\\mathbf{C}_{\\infty}+\\bar{C}_{2}\\mathbf{C}_{\\infty}$ . Here, $\\mathbf{C}_{\\infty}$ is a group representing all rotations of the spin space around the common axis of spins, and $\\bar{C}_{2}$ is a $180^{\\circ}$ rotation around an axis perpendicular to the spins, combined with the spin-space inversion. We recall that the spin-space inversion in the spin groups enters via the time reversal [24,25,40]. We also again emphasize here that the relativistic magnetic space groups encompass collinear, as well as general noncollinear magnets [7,10]. This implies that, e.g., a conjecture based on the spin-space $\\bar{C}_{2}$ symmetry that nonrelativistic spin splitting is generally excluded in materials belonging to the type IV magnetic space groups [7,10] is invalid. \n\nThe form of the nonrelativistic spin-only group $\\mathbf{r}_{s}$ for collinear magnets has two basic general implications independent of the specific nontrivial spin group ${\\bf R}_{s}$ . The first implication follows from $\\mathbf{C}_{\\infty}$ . This symmetry makes spin a good quantum number with a common quantization axis independent of the crystal momentum across the nonrelativistic band structure. The electronic structure is thus strictly separated into nonmixing spin-up and spin-down channels. \n\nThe second implication follows from the $\\bar{C}_{2}$ symmetry in the spin-only group of collinear magnets. Since the spinspace inversion enters via the time reversal [24,25,40], it is accompanied by a time reversal in the real space $(\\mathcal{T})$ . Although $\\tau$ acts as an identity on the real-space coordinates of the atoms, it flips the sign of the crystal momentum. This is important for the band-structure spin symmetries. In particular, we now use the symmetry $\\big[\\bar{C}_{2}\\big|\\big|\\mathcal{T}\\big]$ , which follows directly from the above spin-only group symmetry of the collinear magnets and from the simultaneous action of the time reversal on the spin and real (momentum) space. When applying the transformation $[\\bar{C}_{2}||\\mathcal{T}]$ on spin $(s)$ and crystal-momentum $(\\mathbf{k})$ -dependent bands $\\epsilon(s,{\\bf k})$ , we obtain $[\\bar{C}_{2}\\|\\mathcal{T}]\\epsilon(s,\\mathbf{k})=\\epsilon(s,-\\mathbf{k})$ . We see that the $[\\bar{C}_{2}||\\mathcal{T}]$ transformation acts the same way on $\\epsilon(s,{\\bf k})$ as the real-space inversion. Next, since $\\big[\\bar{C}_{2}\\big|\\big|\\mathcal{T}\\big]$ is a symmetry of nonrelativistic collinear spin arrangements on crystals, $[\\bar{C}_{2}\\|{\\cal T}]\\epsilon(s,{\\bf k})=\\epsilon(s,{\\bf k})$ , and hence, $\\epsilon(s,{\\bf k})=$ $\\epsilon(s,-\\mathbf{k})$ . We derive that the nonrelativistic bands of all collinear magnets are invariant under real-space (crystalmomentum) inversion not only in inversion-symmetric collinear magnets [1,7,8], but even if the crystals lack the real-space inversion symmetry. \n\nWe now move on to the nontrivial spin groups. While the above spin-only group is common to all nonrelativistic collinear magnets, we derive three different types of the nontrivial spin groups corresponding, respectively, to the three distinct phases. The nontrivial spin groups are obtained by combining groups of spin-space transformations with groups of real-space crystallographic transformations [24,25]. Regarding the groups of spin-space transformations, there can be some freedom in their choice [24,25]. For the collinear spin arrangements, one of the two spin-space transformation groups is ${\\bf S}_{1}=\\{E\\}$ ; i.e., it contains just the spin-space identity [24]. We choose the second group in the form of $\\mathbf{S}_{2}=\\{E,C_{2}\\}$ which is favorable for our derivation of the categorization into the three phases of nonrelativistic collinear magnets. The group contains the spin-space identity and the $180^{\\circ}$ rotation of the spin space around an axis perpendicular to the spins. (We note that because of the above spin-only group symmetry element $\\bar{C}_{2}$ , and because the product of spinspace transformations $\\bar{C}_{2}C_{2}$ is equal to the spin-space inversion, an alternative choice [24] of $\\mathbf{S}_{2}$ contains the spin-space inversion instead of $C_{2}$ .) \n\nAfter introducing the spin-only group and the spin-space transformations in the nontrivial spin groups, we move on to the real-space crystallographic transformations in the nontrivial spin groups. The procedure of constructing the nontrivial spin groups applies equally when considering crystallographic space groups (i.e., those containing also translations) or crystallographic point groups (i.e., those where the translations are replaced by identity). To categorize the nonrelativistic collinear magnets based on their magnetic crystal structure, we need to consider the crystallographic space groups. However, to make our manuscript concise, we do not explicitly list all nontrivial spin groups constructed from the crystallographic space groups. This is because the physical consequence of the third phase that we focus on in this work is the spin-momentum locking in the nonrelativistic band structure. In other words, we focus on determining which momenta in the Brillouin zone have spin-degenerate eigenstates protected by the spin-group symmetries, and for which momenta the spin-group symmetries allow for lifting the spin degeneracy. For all collinear spin arrangements on crystal independent of the crystal’s real-space translation symmetries, and independent of whether the crystal does or does not have the real-space inversion symmetry, the spinmomentum locking is described by the direct product of the spin-only group and nontrivial spin groups constructed from the crystallographic point groups containing the real-space inversion symmetry (crystallographic Laue groups). \n\nThe general independence of the spin-momentum locking of translations is a consequence of the strict separation of the nonrelativistic band structure into nonmixing spin-up and spin-down channels protected by the spin-only group symmetries of the collinear magnets. The separate spin-up and spin-down channels then have equal energies at a given momentum $\\mathbf{k}$ in the Brillouin zone when the nontrivial spin group contains a symmetry element $\\big[C_{2}\\big|\\big|R\\big]$ , where $R$ transforms the momentum $\\mathbf{k}$ on itself or a momentum separated from $\\mathbf{k}$ by a reciprocal lattice vector ( $R$ belongs to the little group of $\\mathbf{k}$ ). Since $\\mathbf{k}$ is invariant under translations, the spin degeneracy at a given momentum $\\mathbf{k}$ is protected by ${\\big[}C_{2}{\\big|}|R{\\big]}$ irrespective of whether $R$ does or does not contain a translation. Note that additional band degeneracies can exist within one spin channel, i.e., degeneracies in band indices other than spin that are protected by crystallographic space-group symmetries. These features, whose systematic study is beyond the scope of our present manuscript, can be readily included in the symmetry analysis based on the nonrelativistic spin-group formalism and can be important when, e.g., exploring exotic (topological) quasiparticles near such degeneracy points [42–45]. \n\nThe general invariance of bands of nonrelativistic collinear magnets under real-space (crystal-momentum) inversion is derived above from the spin-only group symmetry $[\\bar{C}_{2}\\vert\\vert\\mathcal{T}]$ . Later in the text, we give specific examples of the inversion-symmetric spin-momentum locking in the band structures of the third phase in crystals with or without the inversion symmetry. \n\nBy using the isomorphism theorem [24], we construct all the nontrivial spin (Laue) groups, whose elements on the left of the double vertical bar form a group of the spinspace transformations and on the right of the double vertical bar a (Laue) group of the real-space crystallographic transformations. It implies the procedure of combining all isomorphic coset decompositions of the two groups, i.e., decompositions with the same number of cosets for the two groups [24]. (A coset decomposition of a group $\\mathbf{X}$ is given by ${\\bf X}={\\bf x}+X_{1}{\\bf x}+X_{2}{\\bf x}+\\cdot\\cdot\\cdot_{3}$ , where $\\mathbf{x}$ is a subgroup of $\\mathbf{X}$ , and $X_{i}$ are elements of $\\mathbf{X}$ [24].) The details of our derivation are in the Supplemental Material Sec. II [30]. Here we summarize the result in which all the nontrivial spin Laue groups describing $\\epsilon(s,{\\bf k})$ of collinear magnets are arranged into the following three distinct types using the isomorphic coset decompositions. \n\nThe first type of nontrivial spin Laue group is given by $\\mathbf{R}_{s}^{\\mathrm{I}}=[E\\vert\\vert\\mathbf{G}]$ , where $\\mathbf{G}$ are the crystallographic Laue groups. Because there are 11 different crystallographic Laue groups, there are also 11 different ${\\bf R}_{s}^{\\mathrm{I}}$ groups. As highlighted in Fig. 1, the ${\\bf R}_{s}^{\\mathrm{I}}$ groups do not imply spin degeneracy of $\\epsilon(s,{\\bf k})$ at any $\\mathbf{k}$ -point. They describe nonrelativistic spin-split band structures with broken time-reversal symmetry and nonzero magnetization corresponding to conventional collinear ferromagnets (ferrimagnets) whose magnetic crystal structure contains one spin lattice (or the opposite-spin sublattices are not connected by any spin-space-group transformation). \n\nThe second type of nontrivial spin Laue group is given by $\\mathbf{R}_{s}^{\\mathrm{II}}=[E\\lVert\\mathbf{G}]+[C_{2}\\lVert\\mathbf{G}]$ . Here, the $\\big[C_{2}\\big|\\big|E\\big]$ symmetry (recall that $\\mathbf{G}$ is a group containing the real-space identity $E$ element) implies spin degeneracy of $\\epsilon(s,{\\bf k})$ for all $\\mathbf{k}$ -vectors in the Brillouin zone. The 11 different ${\\bf R}_{s}^{\\mathrm{II}}$ groups describe nonrelativistic spin-degenerate time-reversal invariant band structures with zero magnetization of conventional collinear antiferromagnets (see Fig. 1). The corresponding antiferromagnetic spin arrangements on crystals have a symmetry $\\left[C_{2}\\middle|\\middle|\\mathbf{t}\\right]$ in their spin-space group, which interchanges atoms and rotates the spin by $180^{\\circ}$ between opposite-spin sublattices. Here, t on the right side of the double vertical bar is a real-space translation. Examples [62,63] are antiferromagnets FeRh or $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ . The ${\\bf R}_{s}^{\\mathrm{II}}$ groups also describe nonrelativistic spin-degenerate collinear antiferromagnetism in crystals with the opposite-spinsublattice transformation symmetry $\\big[C_{2}\\big|\\big|\\bar{E}\\big],$ where $\\bar{\\boldsymbol{E}}$ on the right side of the double vertical bar is the real-space inversion. This is because of the spin-only group symmetry $[\\bar{C}_{2}\\vert\\vert\\mathcal{T}]$ that implies the inversion symmetry of the bands, i.e., that the bands in all nonrelativistic collinear magnets are invariant under the transformation $[E\\rVert\\bar{E}]$ . Symmetries $\\big[C_{2}\\big|\\big|\\bar{E}\\big]$ and $[E\\rVert\\bar{E}]$ give the $\\big[C_{2}\\big|\\big|E\\big]$ symmetry that implies the spin degeneracy across the Brillouin zone (for a more detailed derivation, see Supplemental Material Sec. II [30]). Here, the examples [50,64] are antiferromagnets CuMnAs or $\\mathrm{Mn}_{2}\\mathrm{Au}$ . \n\n![](images/888c42fcb587980d09ecb6ab6fa5c30061ca36e0c695a5b92ed56bbf3a197ec3.jpg) \nFIG. 1. Illustration (in columns) of the three nonrelativistic collinear magnetic phases. Top box: Illustrative collinear spin arrangements and magnetization densities on crystals. Opposite spin directions are depicted by blue and red color. Spin arrows are placed outside the real-space cartoons to highlight that the overall spin axis orientation is not related to the real space coordinates for the nonrelativistic spin-group symmetries. 1st magnetic phase (conventional ferromagnetism) crystal corresponds to Fe, 2nd magnetic phase (conventional antiferromagnetism) to MnPt, and the 3rd unconventional magnetic phase (altermagnetism) to $\\mathrm{RuO}_{2}$ . Magenta arrow and magenta label highlight opposite-spin-sublattice transformation symmetries characteristic of the 2nd magnetic phase (real-space translation or inversion) and the 3rd magnetic phase (real-space rotation). Bottom box: Cartoons of band-structures and corresponding energy iso-surfaces show ferromagnetically spin-split bands (opposite spin states depicted by blue and red color), a spin-degenerate antiferromagnetic band, and bands in the 3rd magnetic phase with alternating sign of the spin splitting. The opposite-spinsublattice transformation of the spin Laue group which maps the same-energy eigenstates with opposite spins on the same $\\mathbf{k}$ -vector in the 2nd magnetic phase and on different k-vectors in the 3rd magnetic phase is again highlighted. The remaining rows give the spin Laue group structure for the given phase with the number of different groups in brackets, and presence/absence of time-reversal-symmetry breaking, compensation and $d\\mathrm{-},g\\mathrm{-}$ , and $i$ -wave symmetries. \n\nThe remaining third distinct type of nontrivial spin Laue group describes the third magnetic phase and is given by \n\n$$\n\\mathbf{R}_{s}^{\\mathrm{III}}=[E\\|\\mathbf{H}]+[C_{2}\\|A][E\\|\\mathbf{H}]=[E\\|\\mathbf{H}]+[C_{2}\\|\\mathbf{G}-\\mathbf{H}].\n$$ \n\nHere, $\\mathbf{H}$ is a halving subgroup of the crystallographic Laue group $\\mathbf{G}$ and the coset $\\mathbf{G}-\\mathbf{H}=A\\mathbf{H}$ is generated by transformations $A$ that can be only real-space proper or improper rotations and cannot be real-space inversion. (Note that this implies that the real-space inversion that is always present in $\\mathbf{G}$ is contained in H.) We see from Eq. (1) that for $\\mathbf{R}_{s}^{\\mathrm{III}}$ , $\\mathbf{G}$ is expressed as a sublattice coset decomposition, where the halving subgroup H contains only the real-space transformations which interchange atoms between same-spin sublattices, and the coset $\\mathbf{G}-\\mathbf{H}$ contains only the real-space transformations which interchange atoms between opposite-spin sublattices. The third magnetic phase corresponds to the magnetic crystal structures in which opposite-spin sublattices are connected by rotation (proper or improper and symmorphic or nonsymmorphic) and are not connected by translation or inversion. \n\nThe third-phase magnets have nonrelativistic spin-split band structures with broken time-reversal symmetry and zero magnetization [1] (see Fig. 1). The broken timereversal symmetry is seen when multiplying $\\left[C_{2}\\big|\\big|\\mathbf{G}-\\mathbf{H}\\right]$ by the spin-only group symmetry $\\begin{array}{r l}{[\\bar{C}_{2}\\|\\mathcal{T}].}\\end{array}$ , which gives $\\big[\\bar{E}\\big|\\big|\\mathcal{T}(\\mathbf{G}-\\mathbf{H})\\big]$ [or equivalently, $[T||T(\\mathbf{G}-\\mathbf{H})]]$ ; i.e., spin groups of the third type do not contain the time-reversal symmetry element. (Recall that the coset $\\mathbf{G}-\\mathbf{H}$ does not contain the identity element.) Lifted spin degeneracies in the $\\pmb{\\mathrm{R}}_{s}^{\\mathrm{III}}$ groups are allowed for crystal momenta whose little group does not contain $A\\mathbf{H}$ elements. They satisfy $A\\mathbf{H}\\mathbf{k}=$ $\\mathbf{k}^{\\prime}\\neq\\mathbf{k}$ , implying that $\\epsilon(s,\\mathbf{k})=[C_{2}\\|A\\mathbf{H}]\\epsilon(s,\\mathbf{k})=\\epsilon(-s,\\mathbf{k}^{\\prime})$ (see Fig. 1). It guarantees that the spin-up and spin-down energy isosurfaces are split, but have the same number of states. These nonrelativistic band-structure signatures of the $\\pmb{\\mathrm{R}}_{s}^{\\mathrm{III}}$ phase are unparalleled in the ${\\bf R}_{s}^{\\mathrm{I}}$ or ${\\bf R}_{s}^{\\mathrm{II}}$ phases. Simultaneously, there are ten different $\\mathbf{R}_{s}^{\\mathrm{III}}$ groups which is comparable to the number of ${\\bf R}_{s}^{\\mathrm{I}}$ or ${\\bf R}_{s}^{\\mathrm{II}}$ groups, suggesting that the third phase is abundant. The ten nontrivial spin Laue groups of the third phase are listed in Fig. 2, where we adopt Litvin’s notation of the spin groups [25], with the upper index 1 refers to the spin-space identity and the upper index 2 to the spin-space rotation $C_{2}$ . Note that they are constructed from only eight different crystallographic Laue groups. However, the third-phase spin Laue groups cannot be constructed for the three remaining crystallographic \n\nLaue groups, namely, from $\\mathbf{G}=\\bar{1}$ , 3; or $m3$ . In the Supplemental Material Sec. II Table S1 [30], we list all 37 nontrivial spin point groups of the third magnetic phase, together with their corresponding ten nontrivial spin Laue groups. \n\nBefore moving to the analysis of the spin-momentum locking protected by the symmetries of the third-phase spin groups, we emphasize the additional differences from the magnetic groups. The latter are constructed by combining crystallographic groups (with the same transformations acting simultaneously on coordinates of atoms and components of magnetic moment vectors) with one group containing the identity element alone, and a second group containing the identity and the time reversal. Comparing this construction to the spin-group formalism with $\\mathbf{S}_{1}$ also containing only the identity element and $\\mathbf{S}_{2}$ with again two elements, implies that for describing all magnetic structures, the relativistic symmetry formalism has the same number of different magnetic groups as is the number of different nonrelativistic spin groups describing exclusively collinear spin arrangements. For the Laue (point) groups, the total number is 32 (122). Our nonrelativistic spin groups then split into 11 (32) nontrivial spin Laue (point) groups of the ferromagnetic phase, 11 (53) of the antiferromagnetic phase, and ten (37) of the third magnetic phase (see Supplemental Material Sec. II Table S1 [30]). \n\nWe also note that because of the crystallographic operations applied in the coupled real and spin space, there is no counterpart in the magnetic groups of the sublattice coset decomposition form of the ${\\bf R}_{s}^{\\mathrm{III}}$ spin groups (see Supplemental Material Sec. II [30]). As we further highlight below, the decomposition into same-spin- and opposite-spin-sublattice transformations in $\\pmb{{\\cal R}}_{s}^{\\mathrm{III}}$ plays a central role in understanding the third magnetic phase. \n\n# III. SPIN-MOMENTUM LOCKING PROTECTED BY SPIN SYMMETRIES \n\nWe now discuss the basic characteristics of the spinmomentum locking in the third magnetic phase as derived from the spin Laue group symmetries, i.e., from the symmetries of the direct product of the spin-only group and the nontrivial spin Laue groups. We derive above that the nonrelativistic collinear magnetic order described by the spin-only group symmetries implies that spin is a good quantum number with a common $\\mathbf{k}$ -independent quantization axis, and that the bands are space-inversion symmetric (symmetric with respect to the inversion of $\\mathbf{k}$ ). We also derive that the bands in the third phase described by the nontrivial spin Laue groups $\\pmb{{\\cal R}}_{s}^{\\mathrm{III}}$ break the time-reversal symmetry. The space-inversion symmetry implies that the bands are even in momentum around the $\\mathbf{\\deltaT}$ -point. Moreover, the $\\mathbf{\\deltaT}$ -point is invariant under all real-space transformations. The $\\big[C_{2}\\big|\\big|A\\big]$ symmetry present in the $\\mathbf{R}_{s}^{\\mathrm{III}}$ groups thus guarantees spin degeneracy of the $\\mathbf{\\deltaT}$ -point. \n\n![](images/49ce204c290ff5b45fa12713d54c96dd2b36c47b72b8151b323070e69d6bdd70.jpg) \nFIG. 2. Classification of spin-momentum locking in the third magnetic phase protected by spin-group symmetries, and material candidates. The columns describe the characteristic planar $(P)$ or bulk $(B)$ spin-momentum locking on model Hamiltonian bands with the characteristic spin-group integer and the even-parity wave form of altermagnetism, the crystallographic Laue group G, the halving subgroup $\\mathbf{H}$ of symmetry elements which interchange atoms between same-spin sublattices, a generator $A$ of symmetry elements which interchange atoms between opposite-spin sublattices, the nontrivial spin Laue group $R_{s}^{\\mathrm{III}}$ (in brackets we list the number of symmetry elements), and material candidates of the third magnetic phase. The model Hamiltonian bands on which we illustrate the spinmomentum locking character are described in Supplemental Material Sec. III [30]. References describing the materials are in the main text and Supplemental Material Secs. V–VI [30]. \n\nOn the other hand, lifted spin degeneracies in the rest of the Brillouin zone, including other time-reversal invariant momenta, are not generally excluded in the third phase. \n\nThese basic spin-momentum locking characteristics of the third phase are in striking contrast to the spinmomentum locking in crystals with Kramers spin degeneracy lifted by the relativistic spin-orbit coupling. The relativistic spin-momentum locking has the form of a continuously varying spin texture in the momentum space, it is not symmetric with respect to the inversion of $\\mathbf{k}$ because of the required broken real-space inversion symmetry of the crystal, the bands are time-reversal invariant, and all time-reversal invariant momenta are spin degenerate. These distinct characteristics of the relativistic spin-momentum locking apply to nonmagnetic systems [65], as well as to conventional antiferromagnets with broken real-space inversion symmetry and spin-orbitcoupling effects included. An example is the relativistic time-reversal invariant band structure with Rashba spin splitting in a noncentrosymmetric antiferromagnet $\\mathbf{BiCoO}_{3}$ with the opposite-spin sublattices connected by translation [52]. \n\nOther prominent spin-momentum locking features in the third phase are protected by the specific ${\\big[}C_{2}{\\big|}{\\big|}A{\\big]}[E]{\\big|}\\mathbf{H}{\\big]}$ symmetries present in the given $\\mathbf{R}_{s}^{\\mathrm{III}}$ group. For example, a symmetry $[C_{2}||{\\cal M}_{c}].$ , where $c$ is the axis perpendicular to the a- $b$ mirror plane, defines a spin-degenerate $k_{a}-k_{b}$ nodal plane at $k_{c}=0$ , or other $k_{c}$ separated from $M_{c}k_{c}=-k_{c}$ by a reciprocal lattice vector. This is because $[C_{2}||{M}_{c}]$ transforms a wave vector from this plane on itself, or on an equivalent crystal momentum separated by the reciprocal lattice vector, while spin is reversed. Similarly, a $\\big[C_{2}\\big|\\big|C_{n,c}\\big]$ symmetry, where $C_{n,c}$ is an $n$ -fold rotation symmetry around the $c$ axis, imposes a spin-degenerate nodal line parallel to the $k_{c}$ axis for wave vectors with $k_{a}=k_{b}=0$ , or other $k_{a(b)}$ separated from $C_{n,c}k_{a(b)}$ by a reciprocal lattice vector. We note that the high-symmetry planes or lines are typically of main focus when assessing the electronic structures. This may explain why, apart from the omission by the conventional magnetic groups, the third phase remained unnoticed during the decades of DFT and experimental studies of band structures. \n\nEach of the ten ${\\bf R}_{s}^{\\mathrm{III}}$ spin Laue groups classifying the spin-momentum locked band structures can be assigned a characteristic even integer, which we define as follows. When making a closed loop in the momentum space around the $\\mathbf{\\deltaT}$ -point in a plane orthogonal to a spin-degenerate nodal surface crossing the $\\mathbf{\\deltaT}.$ -point, the spin rotates by $360^{\\circ}$ following two discrete reversals. Each spin-degenerate nodal surface crossing the $\\mathbf{\\deltaT}$ -point that is present in the crystal momentum space generates such a spin rotation. We define the characteristic spin-group integer as a number of these spin-degenerate nodal surfaces crossing the $\\Gamma$ -point. The spin-group integer is given in Fig. 2, and it is an even number ranging from 2 to 6. As an illustration, we show in the Supplemental Material Sec. III and Fig. S2 [30] spin-degenerate nodal planes crossing the $\\mathbf{\\deltaT}$ -point corresponding to mirror-symmetry planes combined with spinspace rotation for representative $R_{s}^{\\mathrm{III}}$ groups from Fig. 2. \n\nIn Fig. 2, we show the characteristic spin-group integer next to a spin-momentum locking depicted on top of model Hamiltonian bands. The six model Hamiltonians, with anisotropic $d$ -wave, $g\\mathrm{.}$ -wave, and $i$ -wave harmonic symmetry are listed in Supplemental Material Sec. III [30] and are derived to have the same spin-degenerate nodal planes crossing the $\\mathbf{\\deltaT}.$ -point as the nodal planes corresponding to the representative $R_{s}^{\\mathrm{III}}$ groups in Supplemental Material Fig. S2 [30]. We obtain either planar or bulk nonrelativistic spin-momentum locking, with the characteristic spin-group integer from 2 to 6. The planar spin-momentum locking is relevant for (quasi)two-dimensional and three-dimensional crystals, while the bulk spin-momentum locking only for three-dimensional crystals. We note that the earlier reported materials [1,2,4–11,16–22,66–68] $\\mathrm{FeF}_{2}$ , $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ , $\\mathrm{RuO}_{2}$ , $\\kappa{\\mathrm{-Cl}}$ , $\\mathrm{{MnF}}_{2}$ , $\\mathrm{Mn}_{5}\\mathrm{Si}_{3}$ , $\\mathrm{LaMnO}_{3}$ , $\\mathrm{FeSb}_{2}$ , and ${\\mathrm{CaCrO}}_{3}$ referred to as unconventional spin-split antiferromagnets in these studies, all correspond to the third magnetic phase with the characteristic planar spin-momentum locking and spin-group integer 2. \n\nThe presence of nonrelativistic anisotropic spindependent conductivities in the third-phase magnets and the corresponding giant-magnetoresistance and spin-torque phenomena [16,17] is symmetrywise more restrictive than the presence of the phase itself [17]. Only the ${\\bf R}_{s}^{\\mathrm{III}}$ spin \n\nLaue groups with the characteristic spin-group integer 2 $(\\mathbf{R}_{s}^{\\mathrm{III}}={}^{2}m^{2}m^{1}m$ , ${^2}4/{^1}m$ , ${^2}4/{^1}m^{2}m^{1}m$ , and ${^2}2/{^2m})$ ) have a sufficiently low symmetry that allows for these prominent time-reversal symmetry-breaking spintronic effects in the third magnetic phase. \n\n# IV. SPIN SPLITTING BY THE ELECTRIC CRYSTAL POTENTIAL \n\nIn Supplemental Material Sec. IV [30], we summarize the properties of the third magnetic phase derived from the spin Laue group symmetries. Among those, we highlight here the symmetry principles which guide us to the discovery of an extraordinary spin-splitting mechanism, which we illustrate on $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ and $\\mathrm{RuO}_{2}$ . The latter example, in which the amplitude of the extraordinary spin splitting is on the eV scale, is the workhorse material in the emerging research field of time-reversal symmetry-breaking spintronic phenomena in the third magnetic phase [1,3,16–18,20–22]. \n\nThe spin-symmetry guiding principles for the extraordinary spin splitting by the electric crystal potential are as follows: (i) The magnetic crystals should be anisotropic to allow for the symmetries defining the third magnetic phase $\\left[C_{2}\\big|\\big|\\mathbf{G}-\\mathbf{H}\\right]$ , which separate opposite-spin equal-energy states in the momentum space. (ii) The symmetries interchanging atoms within the same-spin sublattice $\\big[E\\big||\\mathbf{H}\\big]$ should be low enough to generate a sufficient anisotropy in the momentum space of the bands dominated by the given sublattice. (iii) The symmetries of $\\mathbf{G}$ are high enough to allow for the orbital degeneracy at the $\\mathbf{\\deltaT}$ -point; this is fulfilled in all groups $\\mathbf{G}$ allowing for the third magnetic phase, except for $\\mathbf{G}=m m m$ or $2/m$ . (iv) The chemistry should allow for these degenerate orbitals to be present in the material and in the desired part of the energy spectrum (e.g., near the Fermi level). \n\nWe first illustrate how these principles for identifying outlier spin splittings materialize in a pristine way in ruthenate $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ when hosting the third magnetic phase. The signature of the extraordinary microscopic spinsplitting mechanism is that its size and momentum dependence are determined by the electric crystal potential of the nonmagnetic phase. The material fulfills all the above spin-symmetry guiding principles, including its corresponding $\\mathbf{G}=4/m$ . (In contrast, $\\mathrm{LaMnO}_{3}$ , $\\kappa$ -Cl, $\\mathrm{FeSb}_{2}$ , or ${\\mathrm{CaCrO}}_{3}$ have $\\mathbf{G}=m m m$ [2,6,10,11,68] that excludes this electric-crystal-potential mechanism of the spin splitting.) \n\nThe real-space crystal structure of ${\\mathrm{KRu}}_{4}{\\mathrm{O}}_{8}$ , as reported in earlier studies [69,70], is schematically illustrated in Fig. 3(a). The symmetry of the lattice is body-centered tetragonal (crystallographic space group $I4/m\\rangle$ ). Red and blue color in Fig. 3(a) represent the collinear antiparallel spin arrangement on the crystal. In addition, the $A$ and $B$ symbols label the real-space sublattices corresponding to the opposite spins in the third magnetic phase. The $A$ and $B$ real-space sublattices are strongly anisotropic and related by a mutual planar rotation by $90^{\\circ}(C_{4z})$ . Correspondingly, the nontrivial spin Laue group describing the spinmomentum locking in the third magnetic phase is ${^2}4/{^1}m$ . According to Eq. (1), it can be decomposed as \n\n![](images/0cd3d97716423a3143f07304f5d2e2a83e12c44c2f5daf6b2cc5514e005092b3.jpg) \nFIG. 3. Spin splitting by the electric crystal potential in $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ in the third magnetic phase. (a) Schematic spin arrangement on the $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ crystal with opposite-spin directions depicted by red and blue color. Magenta arrow and its label highlights the opposite-spinsublattice transformation containing a real-space fourfold rotation. (b) Calculated spin-momentum locking with the characteristic spingroup integer 2 on top of two DFT Fermi surface sheets. (c),(d) DFT band structure of the nonmagnetic phase and the third magnetic phase, respectively. Gray shading highlights the $\\mathbf{k}$ -dependent splitting by the anisotropic electric crystal potential. (e),(f) Projection of bands on the sublattices $A$ and $B$ in the nonmagnetic phase (black) and third magnetic phase (red and blue) for the upper bands and lower bands, respectively. Color shading in (f) highlights the nearly $\\mathbf{k}$ -independent magnetic splitting of the lower bands, and its opposite sign for the sublattices $A$ and $B$ bands. (g) Real-space DFT spin density around the Ru atom in sublattices $A$ and $B$ . \n\n$$\n^{2}4/^{1}m=[E\\|2/m]+[C_{2}\\|C_{4z}][E\\|2/m].\n$$ \n\nFigure 3(b) shows the DFT calculation of the spinmomentum locking protected by the spin-group symmetries, on top of two selected $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ Fermi surface sheets. (The band structure is obtained using the DFT full-potential linearized augmented-plane-wave code ELK within the local-spin-density generalized-gradient approximation [71].) In particular, the $\\big[C_{2}\\big|\\big|C_{4z}\\big]$ symmetry leads to three spin-degenerate nodal lines parallel to the $k_{z}$ axis, $[0,0,k_{z}]$ , $[2,0,k_{z}]$ , and $[0,2,k_{z}]$ marked by gray points in Fig. 3(b) (here the wave vectors are in units of $\\pi$ divided by the lattice constant). The latter two correspond, for $k_{z}=0$ , to time-reversal invariant momenta $\\mathbf{S}_{1}$ and $\\mathbf{S}_{2}$ . On the other hand, the spin degeneracy is strongly lifted at time-reversal invariant momenta $\\mathbf{X}$ and $\\mathbf{Y}$ corresponding to the directions of the real-space anisotropy axes of the two sublattices. Consistently, the little crystallographic Laue group at the $\\mathbf{X}$ and $\\mathbf{Y}$ wave vectors is $2/m$ , which coincides with the halving subgroup of same-spin-sublattice transformations. The spin-momentum locking is planar, reflecting the realspace planar mutual rotations of the crystal anisotropies of the opposite-spin sublattices, and the characteristic spingroup integer is 2. \n\nWe now move on to the demonstration of the spin splitting whose size and momentum dependence are determined by the electric crystal potential and compare this extraordinary microscopic mechanism to the more conventional magnetic spin-splitting mechanism. The analysis is presented in Figs. 3(c)–3(g). Energy bands in the nonmagnetic and third magnetic phase are shown in Figs. 3(c) and 3(d). The high-energy band around $0.9\\ \\mathrm{eV}$ in the depicted portion of the Brillouin zone is twofold spin degenerate in the nonmagnetic phase [upper part of Fig. 3(c)]. The magnetic component of the internal electromagnetic crystal potential in the magnetic phase generates an anisotropic $\\mathbf{k}$ -dependent spin splitting, as shown in the upper part of Fig. 3(d) where the red and blue color correspond to opposite spin states. The sign of the spin splitting alternates, following the symmetries of the spin group. This type of spin splitting belongs to a family generally referred to as internal magnetic-interaction mechanisms [4,7,8,17]. \n\nThe other bands of $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ for energies near the Fermi level also show a spin splitting within the DFT bandstructure theory. However, here the microscopic origin is fundamentally distinct from the internal magnetic-interaction mechanisms. In the nonmagnetic phase, we observe in the lower part of Fig. 3(c) a couple of twofold spindegenerate bands whose mutual splitting (highlighted by gray shading) by the electric crystal potential is $\\mathbf{k}$ dependent, merging at the fourfold degenerate Γ, $\\mathbf{S}_{1}$ , and $\\mathbf{S}_{2}$ points. Remarkably, the $\\mathbf{k}$ -dependent spin splitting in the magnetic phase in the lower part of Fig. 3(d) (highlighted again by gray shading) copies the size and k dependence of the band splitting by the electric crystal potential of the nonmagnetic phase. Its microscopic explanation is provided in Figs. 3(f) and $3(\\mathrm{g)}$ . \n\nWe start the discussion of Fig. 3(f) from the projections of the bands on the sublattices $A$ and $B$ in the nonmagnetic phase (black lines). The projections are dominated by Ru $d_{x z}$ and $d_{y z}$ orbitals. This is in agreement with earlier report [70], which showed the presence of $\\ensuremath{\\mathrm{Ru}}\\ t_{2g}$ orbitals near the Fermi level. At the $\\mathbf{\\deltaT}$ -point, the $A$ and $B$ projected bands are degenerate, which is consistent with the octahedral environment with the tetragonal symmetry [72]. Including spin, the $\\mathbf{\\deltaT}.$ -point is then fourfold degenerate in the nonmagnetic phase. \n\nThe band whose dominant weight is on sublattice $A$ is strongly anisotropic with respect to $\\mathbf{k}$ when moving toward the $\\mathbf{X}$ and $\\mathbf{Y}$ points [left panel of Fig. 3(f)]. The same applies to the sublattice $B$ band; however, the sense of the anisotropy reverses [right panel of Fig. 3(f)]. The band anisotropies reflect the strong crystalline anisotropy, conspiring with the favorable symmetry of the involved orbitals. By adding up the $A$ and $B$ projections, we obtain the bands shown in Fig. 3(c). They progressively split by the electric crystal potential when the $\\mathbf{k}$ -vector moves from the $\\mathbf{\\deltaT}$ -point toward, e.g., the $\\mathbf{X}$ point, with the lower band dominated by one sublattice and the upper band by the other sublattice. Along the $\\boldsymbol{\\Gamma}-\\boldsymbol{\\mathbf{Y}}$ line, the sublattice indices of the lower and upper bands switch places. \n\nThe bands in the magnetic phase projected again on sublattices $A$ and $B$ are also plotted in Fig. 3(f). As in Fig. 3(d), the red and blue colors correspond to opposite spins. We see that for bands with dominant weight on sublattice $A$ , spin states shown in red move up in energy, while the opposite spin states shown in blue move down [left panel of Fig. 3(f)]. The magnetic component of the internal crystal potential in the magnetic phase generates in this case a splitting (highlighted by light-blue shading), which is nearly k independent. This scenario is fundamentally distinct from the strongly $\\mathbf{k}$ -dependent magnetic splitting of the high-energy band shown in Fig. 3(e). It is reminiscent of ferromagnets. However, unlike the common ferromagnetic case, the nearly $\\mathbf{k}$ -independent magnetic splitting reverses sign for the sublattice $B$ bands [right panel of Fig. 3(f)]. This locality, in which band states near the Fermi level with one spin have a dominant weight on one sublattice, is again distinct from the delocalized nature of spin states in the high-energy bands shown in Fig. 3(e). It also starkly contrasts with the conventional mechanisms of the ferromagnetic splitting of band spin states experiencing the global magnetization or the relativistic spin-orbit splitting due to the global electric inversion asymmetry. An additional illustration of the locality is shown in Fig. $3(\\mathrm{g)}$ where we plot the real-space DFT spin density around the Ru atom in sublattices $A$ and $B$ . Consistent with the spin-group symmetry and the dominant $d_{x z}$ and $d_{y z}$ orbitals near the Fermi level, the opposite-spin local densities in the two sublattices are highly anisotropic with the mutually rotated real-space anisotropy axes. \n\nAdding up the $A$ and $B$ sublattice projections of Fig. 3(f) then explains the formation of two pairs of spin-split bands seen in Fig. 3(d). The mutual magnetic splitting between the two pairs is nearly $\\mathbf{k}$ independent, while the spin splitting within each pair is a $\\mathbf{k}$ -dependent copy of the band splitting by the anisotropic electric crystal potential of the nonmagnetic phase [Fig. 3(c)]. It also explains that the two pairs have opposite sign of the spin splitting and that, within each pair, the spin-splitting sign is opposite when moving from the $\\mathbf{\\deltaT}.$ -point toward the $\\mathbf{X}$ or $\\mathbf{Y}$ points. We see from Figs. 3(d) and 3(f) that even if the nearly $\\mathbf{k}$ -independent magnetic splitting were small, the electric crystal potential of the nonmagnetic phase would still determine the splitting between the two nearest bands with opposite spin in the magnetic phase at $\\mathbf{k}$ -vectors sufficiently close to the $\\mathbf{\\deltaT}$ -point. This is a consequence of the nearly $\\mathbf{k}$ -independent magnetic band splitting and of the spin degeneracy of the $\\Gamma$ -point in the third magnetic phase. \n\nIn the studied ${\\mathrm{KRu}}_{4}{\\mathrm{O}}_{8}$ , the spin splitting originating from this extraordinary electric-crystal-potential mechanism reaches a $300\\mathrm{-meV}$ scale. In Supplemental Material Sec. V and Fig. S3 [30], we show that in $\\mathrm{RuO}_{2}$ , a spin splitting reaching a 1-eV scale [1,4,17] is also due to the electric-crystal-potential mechanism. These spin-splitting magnitudes are comparable to spin splittings in ferromagnets but, unlike ferromagnets, are accompanied by a zero net magnetization. They also illustrate that spin splittings in the third magnetic phase can exceed by an order of magnitude the record relativistic spin-orbit splittings in bulk crystals with heavy elements [73]. Moreover, unlike the spin-orbit split bands, the third magnetic phase preserves a common $\\mathbf{k}$ -independent spin quantization axis. \n\nFinally, we emphasize that relativistic DFT calculations in $\\mathrm{RuO}_{2}$ and $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ presented in Supplemental Material Sec. V and Figs. S3 and S4 [30] show the expected weak effect of the spin-orbit coupling on the bands. This highlights that the apparent prominent features of the relativistic bands, including the spin-momentum locking characteristics and the electric-crystal-potential mechanism of the spin splitting, still reflect the nonrelativistic spin-group symmetries. In contrast, these prominent symmetries are omitted by the relativistic magnetic groups of $\\mathrm{RuO}_{2}$ and $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ . In general, as also illustrated in Supplemental Material Secs. III and IV and Figs. S3 and S4 [30], only the spin-group formalism facilitates the sublattice coset decomposition into transformations which interchange atoms between same-spin and opposite-spin sublattices, which plays the central role in understanding the third magnetic phase. Apart from the spin-symmetry guiding principles and DFT calculations of the spin splitting by the electric crystal potential, we also provide a description of this extraordinary mechanism by a minimal lattice model in Supplemental Material Sec. V Fig. S5 [30]. \n\n# V. CANDIDATE MATERIALS \n\nFigure 2 lists the selected candidate materials for the third magnetic phase. In Fig. 4, we highlight $\\mathrm{CrSb}$ , a metal with the critical temperature of $705\\mathrm{~K~}$ [74]. As shown in Fig. 4(a), it crystallizes in the hexagonal NiAs-type structure (crystal space group $P6_{3}/m m c)$ [74,75]. The collinear antiparallel spin arrangement corresponds to the nontrivial spin Laue group $^{2}6/^{2}m^{2}m^{1}m$ $([E||\\bar{3}m]+$ $[C_{2}\\vert\\vert C_{6z}][E\\vert\\vert\\bar{3}m])$ . It contains the $[C_{2}||M_{z}]$ symmetry, which makes the spin-momentum locking bulklike. Additional mirror planes orthogonal to the three hexagonal crystal axes combined with the spin rotation imply that the characteristic spin-group integer is 4 (see Supplemental \n\nMaterial Fig. S2 [30]). This is confirmed by the DFT calculations in Fig. 4(b). \n\nCrSb has a more complex band structure than $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ , as shown in Fig. 4(c). Nevertheless, we can trace a pair of bands with opposite spin [highlighted by gray shading in Fig. 4(c)] which are degenerate at the $\\mathbf{\\deltaT}$ , $\\mathbf{L}_{1}$ , and $\\mathbf{L}_{2}$ points and split when moving away from these high-symmetry points. The spin splitting is as high as $1.2\\mathrm{eV}.$ . We also note that $\\mathrm{CrSb}$ hosts an exotic spin-polarized quasiparticle which is fourfold degenerate at the $\\Gamma$ -point and spin split away from the Γ-point. \n\nA semiconducting MnTe, which is isostructural to $\\mathrm{CrSb}$ , also hosts an extraordinarily large spin splitting in the valence band of $1.1\\ \\mathrm{eV}.$ In Supplemental Material Sec. V Fig. S6 [30], we give a summary of the spin splittings vs critical temperature in selected materials hosting the third magnetic phase. In Supplemental Material Sec. VI and Figs. S7 and S8 [30], we discuss additional material candidates among insulators, semiconductors, and metals, and give an example illustrating the inversion symmetry of the nonrelativistic bands of the third magnetic phase even when the crystal is inversion asymmetric $\\mathrm{(VNb}_{3}\\mathrm{S}_{6})$ . \n\nFinally, we discuss the parent cuprate ${\\mathrm{La}}_{2}{\\mathrm{CuO}}_{4}$ of a high-temperature superconductor [27,76]. The band structure for the collinear antiparallel spin arrangement on this crystal falls into the $\\mathbf{R}_{s}^{\\mathrm{III}}$ nontrivial spin Laue group $^2m^{2}m^{1}m$ $([E||2/m]+[C_{2}||C_{2y}][E||2/m])$ . The symmetry element $\\left[C_{2}\\big|\\big|C_{2y}\\right]$ generates a planar spin-momentum locking with the characteristic spin-group integer 2. Remarkably, according to our symmetry analysis based on the spingroup theory, the energy bands of ${\\mathrm{La}}_{2}{\\mathrm{CuO}}_{4}$ are spin split and break time-reversal symmetry. This is confirmed by the DFT calculations in Supplemental Material Fig. S9 [30] and is in contrast with the conventional perception of spindegenerate bands in ${\\mathrm{La}}_{2}{\\mathrm{CuO}}_{4}$ [76]. The omission of the spin-splitting physics in earlier electronic-structure studies of cuprates could be explained by the focus on highsymmetry lines or planes, such as the $k_{z}=0$ plane [61], where the states are spin degenerate (see Supplemental Material Fig. S9 [30]). \n\n![](images/311527c786f819f6e847f19960c8fd578cfa40a4e07ae819c00cb3fe60aa6cb1.jpg) \nFIG. 4. Metallic high critical temperature $\\mathrm{CrSb}$ with the third magnetic phase. (a) Schematic crystal structure with DFT spin densities. Cr sublattices and the respective magnetization densities with opposite orientation of the magnetic moment are depicted by red and blue color. Magenta arrow and its label highlights the opposite-spin-sublattice transformation containing a real-space mirror or sixfold rotation. (b) Calculated bulklike spin-momentum locking with the characteristic spin-group integer 4 on top of two selected DFT Fermi surface sheets. (c) DFT band structure in the third magnetic phase. Wave-vector dependence of the spin splitting between the bands highlighted by the gray shading is plotted in the lower panel. \n\n# VI. BROAD RELEVANCE IN CONDENSED-MATTER PHYSICS \n\nOur spin-group delimitation and description of the third magnetic phase and the discovery of the extraordinary spinsplitting mechanism by the electric crystal potential in the Ru-oxide crystals provides a unifying theory picture of recent intriguing theoretical and experimental observations of broken time-reversal symmetry transport anomalies and spintronic effects in the magnetically compensated $\\mathrm{RuO}_{2}$ . These include the large crystal (anomalous) Hall effect, charge-spin conversion and spin-torque phenomena, and giant and tunneling magnetoresistance [1,3,16–22]. Our identification of the third magnetic phase in chalcogenide $\\mathrm{CoNb}_{3}\\mathrm{S}_{6}$ , perovskite $\\mathrm{CaMnO}_{3}$ , or cuprate ${\\mathrm{La}}_{2}{\\mathrm{CuO}}_{4}$ also sheds new light on puzzling time-reversal breaking magnetotransport anomalies reported in earlier studies of these materials [77–79]. \n\nThe diversity of the material types illustrates the relevance of the third magnetic phase for a range of condensed-matter physics fields prone to generate new discoveries. Spintronics based on this phase [1,3,6,9,11,12,16–22] would circumvent the traditional prerequisites of magnetization or relativistic spin-orbit coupling in conventional ferromagnetic spintronics [80–83]. Unlike ferromagnets, the third magnetic phase eliminates stray fields and adds insensitivity to external magnetic field perturbations, while allowing for the strong nonrelativistic effects which facilitate the reading and writing functionalities in commercial spintronics. When comparing to the relativistic nonmagnetic spin-texture phases, these textures share with the third magnetic phase the zero net magnetization. However, large relativistic spin splittings require rare heavy elements. In addition, the relativistic phases suffer from spin decoherence even for small-angle elastic scattering off common isotropic impurities. We illustrate that this obstacle is diminished in the third magnetic phase by the collinearity of spins and by the possibility of a large- $\\mathbf{\\nabla}\\cdot\\mathbf{k}$ -vector separation in the Brillouin zone of the equalenergy eigenstates with the opposite spin. \n\nOur results on the ruthenate $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ illustrate the distinct features of nonrelativistic valleytronics in the third magnetic phase, in comparison to valleytronics in nonmagnetic 2D materials [84]. Here the specific merit of the third magnetic phase are spin-split valleys at time-reversal invariant momenta. Both the spintronics and valleytronics fields can take advantage of the spin-conserving nature of the third magnetic phase, stemming from its nonrelativistic origin in the nonfrustrated collinear magnetic crystals. \n\nUnexplored connections might also exist between the third magnetic phase and topological insulators and semimetals. In this context, we point out that, on the one hand, symmetry prohibits a realization of the third magnetic phase in one-dimensional chains; collinear antiferromagnetic spin arrangements on one-dimensional chains have the $\\big[C_{2}\\big|\\big|\\bar{E}\\big]$ (and possibly also $\\big[C_{2}\\big|\\big|\\mathbf{t}\\big]\\big)$ symmetry and, therefore, have spin-degenerate bands. On the other hand, we identify candidates of the third magnetic phase among quasi-one-dimensional, quasi-two-dimensional, and threedimensional insulators and metals. This opens the possibility of searching for unconventional spin-polarized fermion quasiparticles (cf. CrSb), topological insulators, and topological semimetals, including Chern insulators with the quantized Hall effect in high-temperature systems with vanishing internal or external magnetic dipole. \n\nIn the field of electromagnetic multipoles, the zero magnetic dipole of the third magnetic phase opens a new route for realizing magnetic toroidal phases [8,85]. Related to this is the field of Fermi-liquid instabilities [86], where we show that the principally uncorrelated third magnetic phase represents an unprecedented example of an anisotropic ( $d$ -wave, $g\\cdot$ -wave, or $i$ -wave) instability. Certain anisotropic instabilities were expected in the past to arise in correlated systems [4,86]. Our recognition of the $d$ -wave spin-momentum locking in the parent cuprate crystals of high-temperature $d$ -wave superconductors [87] brings a new element into the research of the coexistence and interplay of magnetic and superconducting quantum orders. In addition to bulk systems, intriguing phenomena can be envisaged also in heterostructures in fields such as topological superconductivity [88]. \n\nAn extensive perspective on how the emerging third magnetic phase can enrich basic condensed-matter physics concepts and have impact on prominent condensed-matter research and application areas is given in Ref. [89]. \n\n# VII. DISCUSSION: UNCONVENTIONAL MAGNETIC PHASE \n\nA phase of matter is commonly associated with a uniform state of a physical system and is distinguished from other phases by, among others, crystal structure, composition, or type of order (e.g., magnetic). Each phase in a material system generally exhibits a characteristic set of physical properties, and symmetry is among the fundamental guiding principles for identifying the distinct phases of matter and for describing their phenomenology [31,90]. We show in this work that on the basic level of nonrelativistic physics of nonfrustrated (collinear) magnetism, spin-group symmetries in the crystal-structure real space and electronic-structure momentum space allow, besides the conventional ferromagnetism and antiferromagnetism, for the third distinct magnetically ordered phase. As summarized in Supplemental Material Figs. S10 and S11 [30], the conventional ferromagnetism is characterized by a type of crystal structure and magnetic order with nonzero magnetization allowed by the spin-group symmetry, while the conventional antiferromagnetism is characterized by a different type of crystal structure and magnetic order with zero net magnetization protected by the spin-group symmetry. The key distinction between the nonrelativistic phenomenologies of the two conventional magnetic phases is the spin-split time-reversal symmetrybroken electronic structure and corresponding time-reversal symmetry-breaking responses in ferromagnets contrasting with the spin-degenerate time-reversal symmetric electronic structure and the absence of time-reversal symmetrybreaking responses in antiferromagnets. \n\nThe unconventional magnetic phase classified and described in this work has a type of crystal structure and magnetic order that is distinct from the conventional ferromagnets and antiferromagnets. Its zero net magnetization is protected by the spin-group symmetries that, simultaneously, allow for spin-split time-reversal symmetrybroken electronic structure and corresponding time-reversal symmetry-breaking responses. In trying to retain the classification with only the two traditional basic phases of magnetically ordered materials, a conflict arises. Placing emphasis on the phenomenology of the spin-split timereversal symmetry-broken electronic structure and responses would lead to a notion of unconventional ferromagnetism. In contrast, emphasizing the zero net magnetization would lead to a notion of unconventional antiferromagnetism. Our work provides a resolution of the conflict by delimiting the unconventional magnetic phase of the $d$ -wave (or high even-parity wave) form as a third distinct symmetry type. The alternating spin polarizations in both real-space crystal structure and momentum-space band structure characteristic of this unconventional magnetic phase suggest a term altermagnetism. \n\nWe note that on the basic level of nonrelativistic spingroup symmetries, altermagnetism is delimited as an exclusive separate phase next to the conventional ferromagnetism and antiferromagnetism, while ferrimagnets are a subclass of ferromagnets. Indeed, in general, a distinction between ferrimagnetic crystals characterized by oppositespin sublattices not connected by any symmetry transformation, and crystals commonly referred to as ferromagnets can be ambiguous. For example, in crystals referred to as ferrimagnets, all magnetic atoms can be the same chemical elements, and the absence of any crystallographic transformation connecting the opposite-spin sublattices then originates from different local symmetries of the sites occupied by magnetic atoms from the opposite-spin sublattices. This can be compared to crystals commonly regarded as ferromagnets, where the microscopic spin density changes in magnitude and can also change in sign as a function of the spatial coordinate within the crystal unit cell. Whether or not such variations are correlated with individual atomic species does not change the symmetry of the system. \n\nFinally, we point out that altermagnetism is a realization of a long-sought-after counterpart in magnetism of unconventional superconductivity [91]. Magnetism and superconductivity were once regarded as the best understood fields in many-body solid-state physics. Moreover, they were connected by a striking analogy: The electronelectron Cooper pairs forming around the Fermi surface and driving the conventional $s$ -wave superconductivity have a counterpart in the majority spin electron—minority spin-hole pairs distributed isotropically around the Fermi surface in the conventional model of (s-wave) ferromagnetism [91]. The discovery of the unconventional $d$ -wave superconductivity not only opened an entirely new research landscape of this many-body phase [87] but also raised a fundamental question of whether and how an unconventional $d$ -wave counterpart could be realized in magnetism [91]. Earlier considerations focused on possible realizations of the unconventional $d.$ -wave magnetism due to strong electronic correlations [86,92,93]. In contrast, our identification is directly linked to symmetries of the crystal potential and does not require strongly correlated systems. This makes the altermagnetic materials discussed in our work realistic candidates for a robust unconventional $d$ -wave (or higher even-parity wave) magnetism that can host unconventional time-reversal symmetry-breaking responses of comparable strength to the conventional ( $\\scriptstyle{\\mathsf{\\bar{s}}}$ -wave) ferromagnets. \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge fruitful interactions with Igor Mazin, Rafael González-Hernández, Helen Gomonay, and Roser Valentí. This work is supported by Ministry of Education of the Czech Republic Grants No. LNSM-LNSpin and No. LM2018140, the Czech Science Foundation Grant No. 19-28375X, EU Future and Emerging Technologies Open RIA Grant No. 766566, $\\mathrm{SPIN}+\\mathrm{X}$ (Grant No. DFG SFB TRR 173) and Elasto-Q-Mat (Grant No. DFG SFB TRR 288). We acknowledge the computing time granted on the supercomputer Mogon at Johannes Gutenberg University Mainz. \n\nMagnetism in Doped $\\mathrm{FeSb}_{2}$ , Proc. Natl. Acad. Sci. U.S.A. 118, e2108924118 (2021). [3] L. Šmejkal, A. H. MacDonald, J. Sinova, S. Nakatsuji, and T. Jungwirth, Anomalous Hall Antiferromagnets, Nat. Rev. Mater. 7, 482 (2022). [4] K.-H. Ahn, A. Hariki, K.-W. Lee, and J. Kuneš, Antiferromagnetism in $\\mathrm{RuO}_{2}$ as d-Wave Pomeranchuk Instability, Phys. Rev. B 99, 184432 (2019). [5] S. Hayami, Y. Yanagi, and H. Kusunose, MomentumDependent Spin Splitting by Collinear Antiferromagnetic Ordering, J. Phys. Soc. Jpn. 88, 123702 (2019). [6] M. Naka, S. Hayami, H. Kusunose, Y. Yanagi, Y. Motome, and H. Seo, Spin Current Generation in Organic Antiferromagnets, Nat. Commun. 10, 4305 (2019). [7] L.-D. Yuan, Z. Wang, J.-W. Luo, E. I. Rashba, and A. Zunger, Giant Momentum-Dependent Spin Splitting in Centrosymmetric Low-Z Antiferromagnets, Phys. Rev. B 102, 014422 (2020). [8] S. Hayami, Y. Yanagi, and H. Kusunose, Bottom-Up Design of Spin-Split and Reshaped Electronic Band Structures in Antiferromagnets without Spin-Orbit Coupling: Procedure on the Basis of Augmented Multipoles, Phys. Rev. B 102, 144441 (2020). [9] H. Reichlova et al., Macroscopic Time Reversal Symmetry Breaking Arising from Antiferromagnetic Zeeman Effect, arXiv:2012.15651v1. \n[10] L.-D. Yuan, Z. Wang, J.-W. Luo, and A. Zunger, Prediction of Low-Z Collinear and Noncollinear Antiferromagnetic Compounds Having Momentum-Dependent Spin Splitting Even without Spin-Orbit Coupling, Phys. Rev. Mater. 5, 014409 (2021). \n[11] M. Naka, Y. Motome, and H. Seo, Perovskite as a Spin Current Generator, Phys. Rev. B 103, 125114 (2021). \n[12] H.-Y. Ma, M. Hu, N. Li, J. Liu, W. Yao, J.-F. Jia, and J. Liu, Multifunctional Antiferromagnetic Materials with Giant Piezomagnetism and Noncollinear Spin Current, Nat. Commun. 12, 2846 (2021). \n[13] K. Samanta, M. Ležaić, M. Merte, F. Freimuth, S. Blügel, and Y. Mokrousov, Crystal Hall and Crystal MagnetoOptical Effect in Thin Films of $\\mathrm{SrRuO}_{3}$ , J. Appl. Phys. 127, 213904 (2020). \n[14] M. Naka, S. Hayami, H. Kusunose, Y. Yanagi, Y.Motome, and H. M. Seo, Anomalous Hall Effect in κ Organic Antiferromagnets, Phys. Rev. B 102, 075112 (2020). \n[15] X. Zhou, W. Feng, X. Yang, G.-Y. Guo, and Y. Yao, Crystal Chirality Magneto-Optical Effects in Collinear Antiferromagnets, Phys. Rev. B 104, 024401 (2021). \n[16] R. González-Hernández, L. Smejkal, K. Vyborny, Y. Yahagi, J. Sinova, T. Jungwirth, and J. Zelezny, Efficient Electrical Spin Splitter Based on Nonrelativistic Collinear Antiferromagnetism, Phys. Rev. Lett. 126, 127701 (2021). \n[17] L. Šmejkal, A. B. Hellenes, R. González-Hernández, J. Sinova, and T. Jungwirth, Giant and Tunneling Magnetoresistance in Unconventional Collinear Antiferromagnets with Nonrelativistic Spin-Momentum Coupling, Phys. Rev. X 12, 011028 (2022). \n[18] D.-F. Shao, S.-H. Zhang, M. Li, C.-B. Eom, and E. Y. Tsymbal, Spin-Neutral Currents for Spintronics, Nat. Commun. 12, 7061 (2021). \n[19] Z. Feng et al., Observation of the Crystal Hall Effect in a Collinear Antiferromagnet, arXiv:2002.08712. \n[20] A. Bose et al., Tilted Spin Current Generated by the Collinear Antiferromagnet Ruthenium Dioxide, Nat. Electron. 5, 267 (2022). \n[21] H. Bai et al., Observation of Spin Splitting Torque in a Collinear Antiferromagnet $\\mathrm{RuO}_{2}$ , Phys. Rev. Lett. 128, 197202 (2022). \n[22] S. Karube et al., Observation of Spin-Splitter Torque in Collinear Antiferromagnetic $\\mathrm{RuO}_{2}$ , arXiv:2111.07487. \n[23] W. F. Brinkman and R. J. Elliott, Theory of Spin-Space Groups, Proc. R. Soc. A 294, 343 (1966). \n[24] D. Litvin and W. Opechowski, Spin Groups, Physica (Amsterdam) 76, 538 (1974). \n[25] D. B. Litvin, Spin Point Groups, Acta Crystallogr., Sect. A 33, 279 (1977). \n[26] L. N´eel, Magnetism and Local Molecular Field, Science 174, 985 (1971). \n[27] P. W. Anderson, The Resonating Valence Bond State in $\\mathrm{La}_{2}\\mathrm{CuO}_{4}$ and Superconductivity, Science 235, 1196 (1987). \n[28] M.-T. Suzuki, T. Koretsune, M. Ochi, and R. Arita, Cluster Multipole Theory for Anomalous Hall Effect in Antiferromagnets, Phys. Rev. B 95, 094406 (2017). \n[29] C. J. Bradley and A. P. Cracknell, The Mathematical Theory of Symmetry in Solids (Oxford University Press, New York, 1972). \n[30] See Supplemental Material at http://link.aps.org/ supplemental/10.1103/PhysRevX.12.031042 for comparison of relativistic magnetic symmetries and nonrelativistic spin symmetries, details of the derivation of spin group categorization and symmetry delimination of collinear magnets, altermagnetic model Hamiltonians, summary of symmetry properties of altermagnets, and calculated bandstructures of selected candidate altermagnets. \n[31] L. Landau and E. Lifshitz, Electrodynamics of Continuous Media, 2nd ed., Course of Theoretical Physics Vol. 8 (Pergamon Press, Oxford, 1965). \n[32] E. Turov, Physical Properties of Magnetically Ordered Crystals (Academic Press, New York, 1965). \n[33] N. V. Shubnikov and A. V. Belov, Colored Symmetry (Macmillan Publishers, New York, 1964). \n[34] B. A. Tavger and V. M. Zaitsev, Magnetic Symmetry of Crystals, Sov. Phys. JETP 3, 430 (1956). \n[35] D. B. Litvin, Magnetic Group Tables (International Union of Crystallography, Chester, England, 2013). \n[36] L. Šmejkal, Y. Mokrousov, B. Yan, and A. H. MacDonald, Topological Antiferromagnetic Spintronics, Nat. Phys. 14, 242 (2018). \n[37] H. Watanabe, H. C. Po, and A. Vishwanath, Structure and Topology of Band Structures in the 1651 Magnetic Space Groups, Sci. Adv. 4, eaat8685 (2018). \n[38] Y. Xu, L. Elcoro, Z.-D. Song, B. J. Wieder, M. G. Vergniory, N. Regnault, Y. Chen, C. Felser, and B. Andrei Bernevig, High-Throughput Calculations of Magnetic Topological Materials, Nature (London) 586, 702 (2020). \n[39] S. V. Gallego, J. Manuel Perez-Mato, L. Elcoro, E. S. Tasci, R .M. Hanson, K. Momma, M. I. Aroyo, and G. Madariaga, MAGNDATA: Towards a Database of Magnetic Structures. I. The Commensurate Case, J. Appl. Crystallogr. 49, 1750 (2016). \n[40] A. F. Andreev and V. Marchenko, Symmetry and the Macroscopic Dynamics of Magnetic Materials, Usp. Fiz. Nauk 130, 39 (1980). \n[41] A. Corticelli, R. Moessner, and P. A. McClarty, Spin-Space Groups and Magnon Band Topology, Phys. Rev. B 105, 064430 (2022). \n[42] P.-J. Guo, Y.-W. Wei, K. Liu, Z.-X. Liu, and Z.-Y. Lu, Eightfold Degenerate Fermions in Two Dimensions, Phys. Rev. Lett. 127, 176401 (2021). \n[43] P. Liu, J. Li, J. Han, X. Wan, and Q. Liu, Spin-Group Symmetry in Magnetic Materials with Negligible Spin-Orbit Coupling, Phys. Rev. X 12, 021016 (2022). \n[44] J. Yang, Z.-X. Liu, and C. Fang, Symmetry Invariants of Spin Space Groups in Magnetic Materials, arXiv:2105.12738. \n[45] P. Liu, J. Han, and Q. Liu, Flavor Weyl Fermions Protected by SU(2) Isospin Symmetry in Spin-Orbit-Free Antiferromagnetic Semimetals, arXiv:2107.09984. \n[46] P. M. Lenggenhager, X. Liu, T. Neupert, and T. Bzdušek, Triple Nodal Points Characterized by Their Nodal-Line Structure in All Magnetic Space Groups, Phys. Rev. B 106, 085128 (2022). \n[47] W. H. Kleiner, Space-Time Symmetry of Transport Coefficients, Phys. Rev. 142, 318 (1966). \n[48] R. Ramazashvili, Kramers Degeneracy in a Magnetic Field and Zeeman Spin-Orbit Coupling in Antiferromagnetic Conductors, Phys. Rev. B 79, 184432 (2009). \n[49] P. Tang, Q. Zhou, G. Xu, and S.-C. Zhang, Dirac Fermions in an Antiferromagnetic Semimetal, Nat. Phys. 12, 1100 (2016). \n[50] L. Šmejkal, J. Železný, J. Sinova, and T. Jungwirth, Electric Control of Dirac Quasiparticles by Spin-Orbit Torque in an Antiferromagnet, Phys. Rev. Lett. 118, 106402 (2017). \n[51] L. Šmejkal, T. Jungwirth, and J. Sinova, Route towards Dirac and Weyl Antiferromagnetic Spintronics, Phys. Status Solidi RRL 11, 1700044 (2017). \n[52] K. Yamauchi, P. Barone, and S. Picozzi, Bulk Rashba Effect in Multiferroics: A Theoretical Prediction for $\\mathrm{\\bfBiCoO}_{3}$ , Phys. Rev. B 100, 245115 (2019). \n[53] H. A. Kramers, The´orie g´ene´rale de la rotation paramagn´etique dans les cristaux, Proc. Amsterdam Acad. 33, 959 (1930). \n[54] E. Wigner, Ueber die Operation der Zeitumkehr in der Quantenmechanik, Nach. Ges. Wiss. Göttingen Math.-Phys. Kl. 1932, 546 (1932). \n[55] A. S. Núñez, R. A. Duine, P. Haney, and A. H. MacDonald, Theory of Spin Torques and Giant Magnetoresistance in Antiferromagnetic Metals, Phys. Rev. B 73, 214426 (2006). \n[56] C. Sürgers, G. Fischer, G. Winkel, and H. V. Löhneysen, Large Topological Hall Effect in the Non-Collinear Phase of an Antiferromagnet, Nat. Commun. 5, 3400 (2014). \n[57] C. Sürgers, W. Kittler, T. Wolf, and H. V. Löhneysen, Anomalous Hall Effect in the Noncollinear Antiferromagnet $\\mathrm{{Mn}}_{5}\\mathrm{{Si}}_{3}$ , AIP Adv. 6, 055604 (2016). \n[58] N. J. Ghimire, A. S. Botana, J. S. Jiang, J. Zhang, Y.-S. Chen, and J. F. Mitchell, Large Anomalous Hall Effect in the Chiral-Lattice Antiferromagnet $\\mathrm{CoNb}_{3}\\mathrm{S}_{6}$ , Nat. Commun. 9, 3280 (2018). \n[59] S. I. Pekar and E. I. Rashba, Combined Resonance in Crystals in Inhomogeneous Magnetic Fields, J. Exp. Theor. Phys. 20, 1927 (1965). \n[60] S. A. Egorov and R. A. Evarestov, Colossal Spin Splitting in the Monolayer of the Collinear Antiferromagnet $\\mathrm{MnF}_{2}$ , J. Phys. Chem. Lett. 12, 2363 (2021). \n[61] J. A. Sobota, Y. He, and Z.-X. Shen, Angle-Resolved Photoemission Studies of Quantum Materials, Rev. Mod. Phys. 93, 025006 (2021). \n[62] X. Marti et al., Room-Temperature Antiferromagnetic Memory Resistor, Nat. Mater. 13, 367 (2014). \n[63] J. Li, Y. Li, S. Du, Z. Wang, B.-L. Gu, S.-C. Zhang, K. He, W. Duan, and Y. Xu, Intrinsic Magnetic Topological Insulators in van der Waals Layered $\\mathrm{MnBi}_{2}\\mathrm{Te}_{4}$ -Family Materials, Sci. Adv. 5, eaaw5685 (2019). \n[64] H. J. Elmers et al., Ne´el Vector Induced Manipulation of Valence States in the Collinear Antiferromagnet $\\ensuremath{\\mathrm{Mn}_{2}}\\ensuremath{\\mathrm{Au}}$ , ACS Nano 14, 17554 (2020). \n[65] R. Winkler, Spin-Orbit Coupling Effects in TwoDimensional Electron and Hole Systems, Springer Tracts in Modern Physics Vol. 191 (Springer, Berlin, 2003). \n[66] Y. Noda, K. Ohno, and S. Nakamura, MomentumDependent Band Spin Splitting in Semiconducting $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ : A Density Functional Calculation, Phys. Chem. Chem. Phys. 18, 13294 (2016). \n[67] S. López-Moreno, A. H. Romero, J. Mejía-López, A. Muñoz, and I. V. Roshchin, First-Principles Study of Electronic, Vibrational, Elastic, and Magnetic Properties of $\\mathrm{FeF}_{2}$ as a Function of Pressure, Phys. Rev. B 85, 134110 (2012). \n[68] T. Okugawa, K. Ohno, Y. Noda, and S. Nakamura, Weakly Spin-Dependent Band Structures of Antiferromagnetic Perovskite $\\mathrm{LaMO}_{3}$ $M=r,$ , Mn, Fe), J. Phys. Condens. Matter 30, 075502 (2018). \n[69] W. Kobayashi, Transport Properties of Quasi-OneDimensional $\\mathrm{KRu}_{4}\\mathrm{O}_{8}$ , Phys. Rev. B 79, 155116 (2009). \n[70] T. Toriyama, M. Watanabe, T. Konishi, and Y. Ohta, QuasiOne-Dimensional Electronic Structure of Hollandite Ruthenate $\\mathrm{K}_{2}\\mathrm{Ru}_{8}\\mathrm{O}_{16}$ , Phys. Rev. B 83, 195101 (2011). \n[71] K. Dewhurst, ELK code, http://elk.sourceforge.net. \n[72] D. I. Khomskii, Transition Metal Compounds (Cambridge University Press, Cambridge, England, 2014). \n[73] K. Ishizaka et al., Giant Rashba-Type Spin Splitting in Bulk BiTeI, Nat. Mater. 10, 521 (2011). \n[74] I. J. Park, S. Kwon, and R. K. Lake, Effects of Filling, Strain, and Electric Field on the N´eel Vector in Antiferromagnetic CrSb, Phys. Rev. B 102, 224426 (2020). \n[75] J. Yuan, Y. Song, X. Xing, and J. Chen, Magnetic Structure and Uniaxial Negative Thermal Expansion in Antiferromagnetic CrSb, Dalton Trans. 49, 17605 (2020). \n[76] C. Lane, J. W. Furness, I. G. Buda, Y. Zhang, R. S. Markiewicz, B. Barbiellini, J. Sun, and A. Bansil, Antiferromagnetic Ground State of $\\mathrm{La}_{2}\\mathrm{CuO}_{4}$ : A ParameterFree Ab Initio Description, Phys. Rev. B 98, 125140 (2018). \n[77] G. Tenasini et al., Giant Anomalous Hall Effect in QuasiTwo-Dimensional Layered Antiferromagnet $\\mathrm{Co}_{1}/{}^{3}\\mathrm{Nb}\\mathrm{S}_{2}$ , Phys. Rev. Research 2, 023051 (2020). \n[78] L. Vistoli et al., Giant Topological Hall Effect in Correlated Oxide Thin Films, Nat. Phys. 15, 67 (2019). \n[79] J. Wu, A. T. Bollinger, X. He, and I. Božović, Spontaneous Breaking of Rotational Symmetry in Copper Oxide Superconductors, Nature (London) 547, 432 (2017). \n[80] C. Chappert, A. Fert, and F. N. Van Dau, The Emergence of Spin Electronics in Data Storage, Nat. Mater. 6, 813 (2007). \n[81] D. C. Ralph and M. D. Stiles, Spin Transfer Torques, J. Magn. Magn. Mater. 320, 1190 (2008). \n[82] S. Bhatti, R. Sbiaa, A. Hirohata, H. Ohno, S. Fukami, and S. N. Piramanayagam, Spintronics Based Random Access Memory: A Review, Mater. Today 20, 530 (2017). \n[83] A. Manchon, J. Zelezny, I. M. Miron, T. Jungwirth, J. Sinova, A. Thiaville, K. Garello, and P. Gambardella, Current-Induced Spin-Orbit Torques in Ferromagnetic and Antiferromagnetic Systems, Rev. Mod. Phys. 91, 035004 (2019). \n[84] J. R. Schaibley, H. Yu, G. Clark, P. Rivera, J. S. Ross, K. L. Seyler, W. Yao, and X. Xu, Valleytronics in 2D Materials, Nat. Rev. Mater. 1, 16055 (2016). \n[85] S. Hayami, M. Yatsushiro, Y. Yanagi, and H. Kusunose, Classification of Atomic-Scale Multipoles under Crystallographic Point Groups and Application to Linear Response Tensors, Phys. Rev. B 98, 165110 (2018). \n[86] C. Wu, K. Sun, E. Fradkin, and S.-C. Zhang, Fermi Liquid Instabilities in the Spin Channel, Phys. Rev. B 75, 115103 (2007). \n[87] Q. Si, R. Yu, and E. Abrahams, High-Temperature Superconductivity in Iron Pnictides and Chalcogenides, Nat. Rev. Mater. 1, 16017 (2016). \n[88] K. Flensberg, F. von Oppen, and A. Stern, Engineered Platforms for Topological Superconductivity and Majorana Zero Modes, Nat. Rev. Mater. 6, 944 (2021). \n[89] L. Smejkal, J. Sinova, and T. Jungwirth, Emerging Research Landscape of Altermagnetism, arXiv:2204.10844. \n[90] J. E. Moore, The Birth of Topological Insulators, Nature (London) 464, 194 (2010). \n[91] A. Schofield, There and Back Again: From Magnets to Superconductors, Physics 2, 93 (2009). \n[92] L. Classen, A. V. Chubukov, C. Honerkamp, and M. M. Scherer, Competing Orders at Higher-Order van Hove Points, Phys. Rev. B 102, 125141 (2020). \n[93] R. A. Borzi, S. A. Grigera, J. Farrell, R. S. Perry, S. J. S. Lister, S. L. Lee, D. A. Tennant, Y. Maeno, and A. P. Mackenzie, Formation of a Nematic Fluid at High Fields in $\\mathrm{Sr}_{3}\\mathrm{Ru}_{2}\\mathrm{O}_{7}$ , Science 315, 214 (2007). " + }, + { + "id": "10.1038_s41929-022-00840-0", + "DOI": "10.1038/s41929-022-00840-0", + "DOI Link": "http://dx.doi.org/10.1038/s41929-022-00840-0", + "Relative Dir Path": "mds/10.1038_s41929-022-00840-0", + "Article Title": "The role of Cu1-O3 species in single-atom Cu/ZrO2 catalyst for CO2 hydrogenation", + "Authors": "Zhao, HB; Yu, RF; Ma, SC; Xu, KZ; Chen, Y; Jiang, K; Fang, Y; Zhu, CX; Liu, XC; Tang, Y; Wu, LZ; Wu, YQ; Jiang, QK; He, P; Liu, ZP; Tan, L", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Copper-based catalysts for the hydrogenation of CO2 to methanol have attracted much interest. The complex nature of these catalysts, however, renders the elucidation of their structure-activity properties difficult. Here we report a copper-based catalyst with isolated active copper sites for the hydrogenation of CO2 to methanol. It is revealed that the single-atom Cu-Zr catalyst with Cu-1-O-3 units contributes solely to methanol synthesis around 180 degrees C, while the presence of small copper clusters or nulloparticles with Cu-Cu structural patterns are responsible for forming the CO by-product. Furthermore, the gradual migration of Cu-1-O-3 units with a quasiplanar structure to the catalyst surface is observed during the catalytic process and accelerates CO2 hydrogenation. The highly active, isolated copper sites and the distinguishable structural pattern identified here extend the horizon of single-atom catalysts for applications in thermal catalytic CO2 hydrogenation and could guide the further design of high-performance copper-based catalysts to meet industrial demand.", + "Times Cited, WoS Core": 342, + "Times Cited, All Databases": 351, + "Publication Year": 2022, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000854746500003", + "Markdown": "# The role of Cu1–O3 species in single-atom Cu/ZrO2 catalyst for $\\mathbf{CO}_{2}$ hydrogenation \n\nHuibo Zhao1, Ruofan $\\boldsymbol{\\mathsf{Y}}\\boldsymbol{\\mathsf{u}}^{\\intercal}$ , Sicong Ma $\\oplus2$ , Kaizhuang $\\mathsf{\\pmb{X}}\\mathsf{\\pmb{u}}^{1}$ , Yang Chen1, Kun Jiang1, Yuan Fang1, Caixia Zhu1, Xiaochen Liu1, Yu Tang $\\oplus1$ , Lizhi $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{1}$ , Yingquan $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{3}$ , Qike Jiang4, Peng He3,5, Zhipan Liu $\\textcircled{10}2,6\\boxtimes$ and Li Tan $\\textcircled{10}$ 1 ✉ \n\nCopper-based catalysts for the hydrogenation of $\\mathbf{co}_{2}$ to methanol have attracted much interest. The complex nature of these catalysts, however, renders the elucidation of their structure–activity properties difficult. Here we report a copper-based catalyst with isolated active copper sites for the hydrogenation of $\\mathbf{co}_{2}$ to methanol. It is revealed that the single-atom $\\pmb{C u-Z r}$ catalyst with $\\mathbf{c_{u_{1}-0_{3}}}$ units contributes solely to methanol synthesis around ${180^{\\circ}}\\mathsf{C}_{\\iota}$ , while the presence of small copper clusters or nanoparticles with $\\tt c u\\mathrm{-}\\tt c u$ structural patterns are responsible for forming the CO by-product. Furthermore, the gradual migration of $\\mathbf{Cu}_{1}\\mathbf{-}\\mathbf{O}_{3}$ units with a quasiplanar structure to the catalyst surface is observed during the catalytic process and accelerates $\\mathbf{co}_{2}$ hydrogenation. The highly active, isolated copper sites and the distinguishable structural pattern identified here extend the horizon of single-atom catalysts for applications in thermal catalytic $\\mathbf{co}_{2}$ hydrogenation and could guide the further design of high-performance copper-based catalysts to meet industrial demand. \n\nhe excessive use of fossil fuels in recent decades has led to a dramatic increase in the amount of $\\mathrm{CO}_{2}$ in the atmosphere, which has caused serious damage to the natural environment. Hence, the related C1 chemistry has become an important research area because one of the most challenging scientific issues is to find alternative energy sources to replace petroleum in the 21st century1. In particular, the industrial conversion of excess $\\mathrm{CO}_{2}$ into high-value-added chemicals and energy fuels can not only effectively mitigate the greenhouse effect, but also represents a sustainable use of natural resources2–7. Methanol $(\\mathrm{CH}_{3}\\mathrm{OH})$ , as a basic industrial raw material, can be used to synthesize a series of important industrial chemicals, such as low-carbon olefins and gasoline8–13. It is thus obvious that the process of $\\mathrm{CH}_{3}\\mathrm{OH}$ catalysis from $\\mathrm{CO}_{2}$ is of great commercial value. Therefore, in the past few decades, much research has been performed to find catalysts with good performance, including metal–metal oxides $\\mathrm{(Cu/ZnO/Al_{2}O_{3}}$ (refs. 14,15), $\\mathrm{{Cu}/I n_{2}O_{3}}$ (ref. 16), $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ (refs. $^{17-19^{\\circ}}.$ ), $\\mathrm{Pd}/\\mathrm{ZnO}$ (ref. 20)), metal-oxide solid solutions $(\\mathrm{ZnO}/\\mathrm{ZrO}_{2}$ (ref. 21), $\\mathrm{In}_{2}\\mathrm{O}_{3}/\\mathrm{ZrO}_{2}$ (ref. 22), $\\mathrm{CdZrO}_{x}$ (ref. 23)) and metal alloys $(\\mathrm{Ni}_{x}\\mathrm{Ga}_{y}$ (ref. 24), $\\mathrm{Pd}_{x}\\mathrm{Ga}_{y}$ (ref. 25), $\\mathrm{Pt}_{x}\\mathrm{Co}_{y}$ (ref. 26), etc.). \n\nAmong $\\mathrm{CO}_{2}$ hydrogenation catalysts, copper catalysts have attracted much attention because of their excellent catalytic activity and stability for $\\mathrm{CH}_{3}\\mathrm{OH}$ synthesis19,27. However, the actual active sites for various products in copper-based catalysts are difficult to pinpoint due to the complex coordination structure of copper species. The diversity of valence states of copper species and the particularity of hydrogenation reactions means that copper mostly exists in mixed valence states during these reactions. There are conflicting reports in the literature showing that either ${\\mathrm{Cu}}^{0}$ , $\\mathrm{Cu^{+}}$ or ${\\mathrm{Cu}}^{\\delta+}$ may be active sites18,19,28,29. Moreover, the physical size of copper nanoparticles also profoundly affects the catalytic performance17,30–33. These different factors have a great impact on the coordination structure of copper itself, which makes it difficult to study the actual active copper sites for $\\mathrm{CO}_{2}$ hydrogenation. Although substantial progress has been made in understanding the active sites of copper catalysts, there is still much controversy about the structure–performance correlation between catalyst and reaction18,32,34–36. \n\nFor the above reasons, catalysts with stable and uniform sites are necessary for the study of related catalytic structure–activity relationships. The single-atom catalyst is an ideal model for active sites study due to its uniform metal sites which are embodied in the homogeneous catalyst37–39. However, such work is rarely reported because it is difficult to construct effective and stable active sites in the thermal catalytic hydrogenation of $\\mathrm{CO}_{2}$ to $\\mathrm{CH}_{3}\\mathrm{OH}$ (refs. 33,40–42). Here we synthesized an efficient $\\mathrm{Cu}_{1}/\\mathrm{ZrO}_{2}$ single-atom catalyst to realize the $\\mathrm{CO}_{2}$ hydrogenation reaction to $\\mathrm{CH}_{3}\\mathrm{OH}$ at relatively low temperature $(180^{\\circ}\\mathrm{C})$ . Compared to typical $\\mathrm{Cu}/\\mathrm{Zr}\\mathrm{O}_{2}$ catalysts, the monoatomic dispersed $\\mathrm{Cu}_{1}/\\mathrm{ZrO}_{2}$ displayed a higher turnover frequency (TOF) for $\\mathrm{CH}_{3}\\mathrm{OH}$ and $100\\%$ $\\mathrm{CH}_{3}\\mathrm{OH}$ selectivity. Starting from the structure of the monatomic catalyst model, the relationship between the structure of active copper sites and the formation of methanol or CO is explored in depth. \n\n# Results \n\nThe design of copper catalysts with different structure models. A series of $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalysts with different copper loadings (1–15 $\\mathrm{wt\\%}$ ) were synthesized by a modified co-precipitation and impregnation method. The copper-based amorphous/monoclinic $\\mathrm{ZrO}_{2}$ with different amounts of copper $(x\\mathrm{~wt\\%})$ were named CAZ- $x$ and CMZ- $x_{i}$ , respectively. The actual copper concentration in various $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ samples was measured by inductively coupled plasma optical emission spectrometry (ICP-OES) (Supplementary Table 1). As shown in Supplementary Fig. 1a, all the $\\mathrm{Cu}/{\\mathsf{a}}–\\mathrm{Zr}\\mathrm{O}_{2}$ catalysts with different copper loading amounts exhibited an amorphous state of $\\mathrm{ZrO}_{2}$ and no $\\mathrm{\\DeltaX}$ -ray diffraction peaks of $\\mathtt{C u O}$ species, suggesting that the copper species were highly dispersed on $\\mathsf{a{-}Z r O_{2}}$ (ref. 43). The similar specific surface areas and pore structures also indicated a high degree of dispersion of copper species (Supplementary Table 2). Notably, $\\mathsf{a{-}Z r O}_{2}$ transformed to tetragonal phase without adding ${\\mathrm{Cu}}^{2+}$ precursor during the same co-precipitation procedure (Supplementary Fig. 1b). The change in phase indicated that a strong interaction effect existed between copper and $\\mathrm{ZrO}_{2}$ . The broad Raman spectroscopy peak at $523\\mathrm{cm}^{-1}$ also confirmed amorphous zirconia was formed in $\\mathrm{Cu}/{\\mathsf{a}}–\\mathrm{Zr}\\mathrm{O}_{2}$ catalysts with various copper loadings (Supplementary Fig. 2)44. \n\nTo confirm the hyperfine structure of the $\\mathrm{Cu}/{\\mathsf{a}}–\\mathrm{Zr}\\mathrm{O}_{2}$ catalysts at the atomic scale, high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and X-ray absorption spectroscopy (XAS) were used. The HAADF-STEM images of CAZ-1 (Fig. 1a and Supplementary Fig. 3) showed that the sample consisted of $\\mathsf{a{-}Z r O_{2}}$ with no copper species nanoparticles on it. Elemental mapping (Fig. 1d) also confirmed highly dispersed copper sites were located in the CAZ-1 catalyst, consistent with the XRD and HAADF-STEM results. For copper loading amounts of up to $15\\mathrm{wt\\%}$ , the copper species remained highly dispersed on the $\\mathrm{ZrO}_{2}$ substrate (Fig. 1b and Supplementary Fig. 4). Extended X-ray absorption fine structure (EXAFS) spectroscopy in R space and corresponding wavelet transform (WT) spectra supplied more important information about the structure of the catalysts, as shown in Fig. 1g,h and Supplementary Fig. 5a. Only one apparent peak at $1.{\\overset{\\vartriangle}{9}}2{\\overset{\\vartriangle}{\\mathrm{\\AA}}}$ corresponding to the first coordination shell of $\\mathrm{Cu-O}$ scattering could be detected in CAZ-1 and CAZ-15. This provided evidence that copper sites were atomically dispersed in CAZ-1 and CAZ-15 because no Cu–(O)–Cu or Cu–Cu metallic bonds were observed45. It is difficult to completely exclude copper single atoms by just increasing the copper loading in CAZ- $x$ catalysts due to the unique molecular interactions between copper and $\\mathsf{a}{\\mathsf{-}}{\\mathsf{Z r O}}_{2}$ . Therefore, catalysts containing $15\\mathrm{wt\\%}$ copper were synthesized with $\\mathtt{C u O}$ nanoparticles over monoclinic $\\mathrm{ZrO}_{2}$ substrate (CMZ-15) and bare Q50 $(\\mathrm{SiO}_{2})$ (CS-15), and served as reference catalysts. The obvious $\\mathrm{\\DeltaX}$ -ray diffraction peaks at $35.5^{\\circ}$ and $38.7^{\\circ}$ (Supplementary Fig. 6a,b) and the Raman peak at $291\\mathrm{cm}^{-1}$ (Supplementary Fig. 2) correspond to the existence of $\\mathtt{C u O}$ nanoparticles46. The highly agglomerated $\\mathtt{C u O}$ particles were also observed in the CMZ-15 (15- $30\\mathrm{nm},$ and CS-15 $(\\sim0.6\\upmu\\mathrm{m})$ catalysts from transmission electron microscopy (TEM) images and correspoding elemental mapping (Fig. 1c,f and Supplementary Fig. 7a–j). Moreover, an additional smaller peak corresponding to CuO at $2.81\\mathring{\\mathrm{A}}$ was observed in EXAFS and WT spectra (Fig. 1g, Supplementary Fig. 5b), ascribed to Cu–(O)–Cu scattering at the second shell, confirming the formation of CuO particles47. In summary, the copper species existed as single atoms and large CuO particles in the CAZ- $x$ $\\begin{array}{r}{\\langle x=1-15~\\mathrm{wt\\%}}\\end{array}$ ) series catalysts and CMZ-15 samples, respectively. \n\nCatalytic performance for $\\mathbf{CO}_{2}$ hydrogenation. The catalytic performance of $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalysts for hydrogenation of $\\mathrm{CO}_{2}$ to $\\mathrm{CH}_{3}\\mathrm{OH}$ was evaluated at $180^{\\circ}\\mathrm{C}$ and $3\\mathrm{MPa}$ with $\\mathrm{CO}_{2}/\\mathrm{H}_{2}$ mixed gas $(\\mathrm{CO}_{2};\\mathrm{H}_{2}=1{:}3)$ . Prior to reaction, CAZ- $x$ ( $\\overset{\\prime}{\\boldsymbol{x}}=1-15~\\mathrm{wt\\%}$ ) catalysts were pretreated at $230^{\\circ}\\mathrm{C}$ for $10\\mathrm{{h}}$ under an argon atmosphere. CAZ-1, CMZ-15 and CS-15 were pretreated at $300{-}370^{\\circ}\\mathrm{C}$ under a hydrogen atmosphere to form metallic copper particle species. The $\\mathrm{CO}_{2}$ conversion over all the catalysts was controlled to less than $10\\%$ to study their intrinsic activity, which was far lower than the $\\mathrm{CO}_{2}$ equilibrium conversion under reaction conditions \n\n1 $29.7\\%$ at $180^{\\circ}\\mathrm{C};$ Supplementary Fig. 8). As shown in Fig. 2a,b and Supplementary Table 3, using CAZ-1 resulted in the detection of only $\\mathrm{CH}_{3}\\mathrm{OH}$ , and no by-products, and this catalyst preferentially produced $\\mathrm{CH}_{3}\\mathrm{OH}$ with a $\\mathrm{TOF}_{\\mathrm{Cu}}$ value of up to $1.37\\mathrm{h}^{-1}$ . We have therefore synthesized a ‘homogeneous’ active site catalyst with excellent stability for $\\mathrm{CH}_{3}\\mathrm{OH}$ production from $\\mathrm{CO}_{2}$ hydrogenation. However, $\\mathrm{CO}_{2}$ could not be activated by CAZ-1-r (CAZ-1 pre-reduced by $\\mathrm{H}_{2}$ at $370^{\\circ}\\mathrm{C}$ to form large copper particles), CMZ15 and CS-15 catalysts, according to the high aggregation of copper species into large particles, confirmed by the X-ray diffraction results (Supplementary Figs. 6a,b and 9) and $\\mathrm{H}_{2}$ temperature programmed reduction (TPR) (Supplementary Fig. 10b). Therefore, the highly dispersed, isolated copper species might be the actual active sites for $\\mathrm{CH}_{3}\\mathrm{OH}$ synthesis from $\\mathrm{CO}_{2}$ at low temperatures. Compared with the $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalysts reported previously in the literature, the CAZ-1 with single-atom copper sites in this work offers advantageous catalytic performance for methanol synthesis (Supplementary Table 4). As the copper amount increases in the CAZ- $x$ catalysts (Fig. 2c), CO starts to be produced from CAZ-4 catalyst, indicating additional active sites were formed in these high-copper-loading catalysts (Supplementary Fig. 11) during the reaction process. It was inferred that the copper clusters or small nanoparticles that form on CAZ- $x$ catalysts $(>4\\mathrm{wt\\%\\Cu)}$ played a crucial role in accelerating reverse water gas shift (RWGS) reaction since no activity was observed over CAZ-1-r, CMZ-15 and CS-15 catalysts with large metallic copper particles. These catalysts exhibited excellent intrinsic activity in the low loading range $(<2\\mathrm{wt\\%}\\mathrm{Cu})$ . A good linear growth relationship of $\\mathrm{CO}_{2}$ conversion was observed for CAZ-1, CAZ-1.5, CAZ-2 and CAZ-2.5, with only $\\mathrm{CH}_{3}\\mathrm{OH}$ being produced (Supplementary Fig. 12a). The ratios of $\\mathrm{R}_{x}/\\mathrm{R}_{1}$ $\\mathrm{\\mathrm{R}}_{x}=\\mathrm{CO}_{2}$ conversion/actual copper loading, $x=1.5$ , 2, 2.5, 4) for CAZ-1.5/CAZ-1, CAZ-2/CAZ-1, CAZ-2.5/CAZ-1 and CAZ-4/ CAZ-1 are 0.99, 0.96, 0.97 and 0.67, respectively, indicating that the active copper sites were uniformly dispersed and exposed on the catalysts’ surface in the single-atom state in CAZ- $x$ ( $\\stackrel{\\prime}{x}=1-2.5)$ . However, the increasing trend of conversion rate decreased for copper contents higher than $4\\mathrm{wt\\%}$ $\\mathrm{'R_{4}/R_{1}}{=}0.67\\$ , since the copper clusters could not provide $\\mathrm{CO}_{2}$ activation ability as strong as that of isolated active copper sites, and hence the CO selectivity was much lower than the $\\mathrm{CH}_{3}\\mathrm{OH}$ selectivity. When the copper loading amount was more than $8\\mathrm{wt\\%}$ , the surface of the catalyst was filled up with copper clusters and isolated ${\\mathrm{Cu}}^{\\mathfrak{s}+}$ sites at the same time as large particles of ${\\mathrm{Cu}}^{0}$ —which have no $\\mathrm{CO}_{2}$ activation ability—gradually formed (Supplementary Fig. 12b), resulting in no further increase of the $\\mathrm{CO}_{2}$ conversion due to the saturation of surface-active sites. \n\nFurther evidence for this mechanism is provided by the catalytic performance and ICP-OES results (Supplementary Table 1) of CAZ-15-H (where CAZ-15-H is CAZ-15 pretreated with ${\\mathrm{HNO}}_{3}$ for $20\\mathrm{{h}}^{\\cdot}$ ), where the large copper nanoparticles were partially removed. The catalytic performance was similar to that of CAZ-8–15 and the actual copper loading amount was close to that of CAZ-8, indicating that the effective active sites of copper species on $\\mathsf{a}{\\mathsf{-}}\\mathsf{Z r}\\mathsf{O}_{2}$ surface comprised about $7-8\\mathrm{wt\\%}$ . In addition, we also proved that the active sites in the catalyst were in a very stable structure that even strong acid could not break. CAZ-1 was also tested in the $\\mathrm{CO}_{2}$ conversion reaction continuously for $\\boldsymbol{100}\\mathrm{h}$ to evaluate its catalytic stability (Fig. 2d and Supplementary Fig. 13a,b). After an induction period of a couple of hours, the catalyst with isolated active copper sites gave both very stable $\\mathrm{CO}_{2}$ conversion and target product selectivity, demonstrating that the catalyst possesses an extremely stable structure in the $\\mathrm{CO}_{2}$ hydrogenation reaction. Furthermore, fresh and used CAZ-1 catalysts had similar weight loss and heat absorption/exothermic trends, indicating that CAZ-1 has a stable structure with no carbon deposition on its surface during low-temperature reaction (Supplementary Fig. 14). \n\n![](images/43a8dbc10f5fa4abb354869c51a99e1fe634e595411845a1a21e53c1e6426092.jpg) \nFig. 1 | Characterization of different $\\mathsf{C u}/\\mathsf{Z r O}_{2}$ catalysts. a–f, HAADF-STEM image and elemental mapping of CAZ-1 (a,d), and TEM image and elemental mapping of CAZ-15 (b,e) and CMZ-15 (c,f). g, The corresponding $k^{2}$ -weighted Fourier transform spectra of as-prepared samples and references. h, The WT spectroscopy of CAZ-1. \n\nSurface electronic state and coordination structure. The electronic state and short-range coordination environment of the catalysts were investigated to study their relationship to the catalytic performance. The $\\mathrm{Cu}2p$ species for CAZ-1 and CAZ-1-U (where U signifies used) were located at about $931.9\\mathrm{eV},$ and their Auger electron spectroscopy (AES) (Supplementary Fig. 15a,b) signals were located at $916.5\\mathrm{eV},$ indicating the presence of $\\mathrm{Cu^{+}}$ in the samples before and after the reaction48. For the CAZ-15 sample, the content of ${\\mathrm{Cu}}^{2+}$ species decreased significantly after the reaction (from $66\\%$ to $32\\%$ ; Supplementary Table 5 and Supplementary Fig. 15a,b), indicating that the ${\\mathrm{Cu}}^{2+}$ was partially in situ reduced to ${\\mathrm{Cu}}^{0}$ during the reaction (Supplementary Fig. 12b). The coexisting ${\\mathrm{Cu}}^{0}$ clusters or small particles and ${\\mathrm{Cu}}^{\\mathfrak{s}+}$ species in CAZ-15 convert $\\mathrm{CO}_{2}$ to CO and $\\mathrm{CH}_{3}\\mathrm{OH}$ , respectively. \n\nBecause the accuracy of X-ray photoelectron spectroscopy (XPS) was insufficient while the copper species were highly dispersed with low loading amounts49–53, the valence state of catalysts was confirmed by X-ray absorption near-edge structure (XANES) measurements for more accurate investigations (Fig. 3a–d and Supplementary Fig. 16a–c). In comparison to the copper foil, the absorption edges for CAZ-1 and CAZ-1-U shifted to higher energy, indicating that the copper atoms were in an oxidized state (Fig. 3a). Peaks A ${(\\mathrm{Cu}^{2+}}$ , $8,978\\mathrm{eV},$ $1s\\to3d$ ), B $(\\mathrm{Cu}^{2+},8,985\\mathrm{eV},1s\\to4p)$ and C $(\\mathrm{Cu}^{2+}$ , $8{,}997\\mathrm{eV}_{:}$ , $1s\\to4p$ ) were similar to those of $\\mathtt{C u O}$ in the XANES spectrum (Fig. 3b), but the details were different (the intensity of these peaks, especially peak D at $9,010.8\\mathrm{eV},$ represent multiple scattering of ${\\mathrm{Cu}}^{2+}$ ). This indicated that the valence of copper species in fresh and used CAZ-1 were close to $^{2+}$ (refs. 45,51,54). To reflect the true valence information of copper species in CAZ-1 during the reaction process, an in situ XAS test was performed. As shown in Fig. 3a–c, the absorption edge and first derivative of CAZ-1 (in situ) was between $\\mathrm{Cu^{+}}$ and ${\\mathrm{Cu}}^{2+}$ , suggesting the oxidation state of ${\\mathrm{Cu}}^{\\delta+}$ $(1<\\delta<2)$ species. Based on the XANES spectra of copper foil, $\\mathrm{Cu}_{2}\\mathrm{O}$ and CuO, the valence of ${\\mathrm{Cu}}^{\\delta+}$ (in situ) was estimated to be ${\\sim}1.4$ according to our linear fitting results, as shown in Fig. 3d. Therefore, it was deduced that the valence of copper species in CAZ-1 and CAZ-1-U was close to $^{2+}$ but would be decreased to ${\\sim}1.4+$ during the $\\mathrm{CO}_{2}$ hydrogenation reaction. Although the fresh CAZ-15 also gave a similar XANES spectra as CAZ-1, the copper species would be changed into a different state during the reaction process, leading to their distinctly different catalytic performances (Supplementary Fig. 6c,d and Fig. 2c). As for CMZ-15, an apparent pre-edge peak at $_{8,984e V}$ was detected, which confirmed that the $\\mathtt{C u O}$ particle was embodied in CMZ-15 (Supplementary Fig. 6c, $\\mathbf{d})^{55}$ , corresponding to the X-ray diffraction results (Supplementary Fig. 6a). \n\n![](images/986370ef6e12c505798886803af95752bb35d2ffcb14d33d269d50a426562bf4.jpg) \nFig. 2 | Catalytic performance of different copper-based catalysts. a, ${\\mathsf{T O F}}_{\\subset\\mathrm{{u}}}$ values and space-time yield (STY) of CAZ-1, CMZ-15 and CS-15. b, ${\\mathsf{C O}}_{2}$ conversion and product selectivity of CAZ-1, CMZ-15 and CS-15. c, The catalytic activity of CAZ- $x$ and CAZ-15-H. d, The stability test of CAZ-1. Reaction conditions: $0.5g$ catalyst, $3M P a$ , $180^{\\circ}\\mathsf C$ , $C O_{2}:H_{2}=1:3,$ , $10\\mathsf{m l}\\mathsf{m i n}^{-1}$ . \n\nThe EXAFS fitting data for $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ are shown in Fig. $3\\mathrm{e-g},$ Supplementary Fig. 16d–j and Supplementary Table 6. The copper species in CAZ-1 remained monodispersed after the reaction, and the average $\\mathrm{Cu-O}$ coordination numbers before and after the reaction were 2.84 and 2.72, respectively. Combined with the results of theoretical calculations $\\mathrm{(Cu_{1}–O_{3}}$ has the lowest surface potential; Supplementary Fig. 17), these data indicate that the local structure of CAZ-1 comprised one isolated copper atom coordinated with about three oxygen atoms $\\mathrm{{Cu}}_{1}–\\mathrm{{O}}_{3}$ units) in a quasiplanar structure with an angle of about $11^{\\circ}$ between the copper and oxygen atoms on the a- $\\mathrm{ZrO}_{2}$ surface (Fig. 3h). Furthermore, in situ EXAFS was used to study the structure of CAZ-1 under operando conditions. The fitted data indicated that reduction of the copper species in CAZ-1 to metallic copper was difficult under the reaction conditions, which was consistent with the results of $\\mathrm{H}_{2}$ -TPR (Supplementary \n\nFig. 10a, c), indicating that the copper species were still distributed in a single-atom state. The $\\mathrm{Cu-O}$ coordination number slightly decreased to 2.56 during the reaction, accompanied by a slight decrease in the valence state. Meanwhile, the $\\mathrm{Cu-O}$ bond became slightly longer under the reaction conditions (increasing from 1.92 to $2.0\\dot{5}\\mathring{\\mathrm{A}}$ ; Supplementary Table 6), indicating that the $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ sites were activated under the reaction conditions. \n\nThe active sites for copper-based catalysts. It was hypothesized that isolated $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ sites might favour $\\mathrm{CO}_{2}$ conversion to $\\mathrm{CH}_{3}\\mathrm{OH}$ . Because no copper particles were detected in the spent CAZ-1 (Fig. 4a and Supplementary Fig. 18a), we concluded that isolated $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ active sites in $\\mathrm{Cu}/\\mathrm{Zr}\\mathrm{O}_{2}$ were in fact stable. However, the local copper particles with $0.21\\mathrm{nm}$ spacing of the $\\mathrm{Cu}(111)$ planes16,56–58 detected in CAZ-15-U by HRTEM (Fig. 4b and Supplementary Fig. 18b) revealed that copper species were partially aggregated and reduced during the catalytic process, consistent with the X-ray diffraction results (Fig. 4c). $\\mathrm{H}_{2}$ -TPR was also performed to elucidate the evolution of the copper species under a reduced atmosphere (Supplementary Fig. 10). The TPR results indicated that reduction of the ${\\mathrm{Cu}}^{\\mathfrak{d}+}$ species in CAZ-1 was difficult: only one peak at $360^{\\circ}\\mathrm{C}$ appeared, which was much higher than the actual reaction temperature, indicating the stability of $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ active sites. As the copper content increased from $1\\mathrm{wt\\%}$ to $15\\mathrm{wt\\%}$ , this reduction peak shifted to lower temperatures, demonstrating that the interaction between the copper species and $\\mathrm{ZrO}_{2}$ carrier gradually weakened. The explanation for this behaviour is that the copper species is more easily aggregated and thereby further reduced as its loading amount increased. The $\\mathrm{\\DeltaX}$ -ray diffraction results (Fig. 4c and Supplementary Fig. 12b) also supported this hypothesis: no copper particle diffraction peaks were detected and the crystal structure remained in the amorphous state for used CAZ-1 catalyst. In contrast, two obvious sharp peaks $.43.3^{\\circ}$ and $50.4^{\\circ})^{59,60}$ appeared in used CMZ-15 and CS-15, suggesting the formation of copper from $\\mathtt{C u O}$ reduction (Supplementary Fig. 6), which was corroborated by TEM (Supplementary Figs. 19 and 20). Furthermore, in situ X-ray diffraction was employed to investigate the dynamic evolution of ${\\mathrm{Cu}}^{\\delta+}$ species in $\\mathrm{Cu}/{\\mathsf{a}}–\\mathrm{Zr}\\mathrm{O}_{2}$ under a hydrogen atmosphere. As shown in Fig. 4d, no signal of ${\\mathrm{Cu}}^{0}$ was observed in CAZ-1 catalyst with increasing temperature $(30\\rightarrow180\\rightarrow230\\rightarrow300\\rightarrow350^{\\circ}\\mathrm{C})$ . However, for CAZ-15, two faint signals at $43.3^{\\circ}$ and $50.4^{\\circ}$ appeared, and the intensity of these gradually increased as the temperature increased from 180 to $350^{\\circ}\\mathrm{C}$ in a hydrogen atmosphere. Therefore, the ${\\mathrm{Cu}}^{2+}$ species in CAZ-15 were partially reduced at $180^{\\circ}\\mathrm{C}$ and high temperatures could further increase their degree of reduction. $\\mathrm{H}_{2}$ temperature-programmed desorption (TPD) (Supplementary Fig. 21) showed peaks at ${\\sim}420^{\\circ}\\mathrm{C}$ that were assigned to sites of $\\mathrm{H}_{2}$ absorption at copper species and $\\phantom{+}\\mathrm{\\phantom{}_{1-}Z r O}_{2}$ substrate. Compared with CAZ-1, the corresponding peak in CAZ-15 migrated to a higher temperature $(415^{\\circ}\\mathrm{C}\\rightarrow430^{\\circ}\\mathrm{C})$ , possibly caused by the greater number of supplied adsorption sites on the CAZ-15 surface, indicating that the structure of copper species in CAZ-15 was more complex and non-unique. Based on the above results, it was concluded that the dispersion of copper species in CAZ-1 was still in the single-atom state; copper single atoms with partially reduced clusters or nanoparticles coexisted in CAZ-15 during the reaction. As for CMZ-15 and CS-15, both the X-ray diffraction (Supplementary Fig. 6) and TEM (Supplementary Figs. 19 and 20) results indicated that almost all the copper species on the surface were reduced to larger copper particles during the reaction. \n\n![](images/9a79f318b0b608d7c9c1afffd246ac0f5bd2ca264b3ce6b49d52dd534b1f23b3.jpg) \nFig. 3 | Electronic property and structure of CAZ-1. a, Cu K-edge XANES spectra of $\\mathsf{C u}/\\mathsf{Z r O}_{2}$ and standards. b, Comparison of XANES spectra of CAZ-1, CAZ-1-U and $\\mathtt{C u O}$ standard. c, The first derivatives of XANES spectra of CAZ-1 (in situ) and reference materials. d, The mean chemical valence of $\\mathsf{C u}^{\\delta+}$ species in CAZ-1 under in situ test conditions. $\\scriptstyle\\mathbf{e}-\\mathbf{g},$ Fitting of $k^{2}$ -weighted EXAFS data of CAZ-1 (e), CAZ-1-U (f) and CAZ-1 (in situ) $\\mathbf{\\sigma}(\\mathbf{g})$ in the region of $1.0{-}3.0\\mathring{\\mathsf{A}}.$ h, The proposed $\\mathsf{C u}_{1}–\\mathsf{O}_{3}$ configuration of CAZ-1. The in situ XAS test condition: sample was pretreated with pure argon $(30\\mathsf{m l}\\mathsf{m i n}^{-1})$ at $230^{\\circ}\\mathsf C$ for $2h$ , then cooled down to ${180^{\\circ}C}$ and treated in mixed gas $\\mathsf{C O}_{2};\\mathsf{H}_{2}=1;3$ ) at 1 MPa. The gas flow was then adjusted to $10\\mathsf{m l}\\mathsf{m i n}^{-1}$ and the data recorded. \n\n![](images/20633b4c71e7aa7d8191945b6f21dc47a7b6c000f7c1f8f9bdc7627d0a1c4902.jpg) \nFig. 4 | Morphology and crystal structure of different $C u/a{-}Z_{r}O_{2}$ catalysts. a, HAADF-STEM image of CAZ-1-U. Black spots in the yellow circles may be single copper atoms or background. b, HRTEM image of CAZ-15-U. c, X-ray diffraction profiles of CAZ-1, CAZ-1-U, CAZ-15 and CAZ-15-U $_{\\therefore}^{\\prime\\prime}04-0836^{\\prime\\prime}$ is the standard card of copper metal). d, In situ $\\mathsf{X}$ -ray diffraction profiles for different $C u/a\\ –Z r O_{2}$ under pure hydrogen. \n\nCopper loading amounts of less than $2\\mathrm{wt\\%}$ in CAZ- $x$ catalysts yielded $\\mathrm{CH}_{3}\\mathrm{OH}$ as the only product because isolated $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ units play a crucial role in $\\mathrm{CH}_{3}\\mathrm{OH}$ synthesis (Fig. 2c). As the copper loading amount was increased to $4\\mathrm{wt\\%}$ , a small amount of CO was produced because a small number of reduced copper clusters or nanoparticles were formed during the reaction (Supplementary Fig. 11), which might be active sites for the RWGS reaction. Increasing the copper content to $8\\mathrm{wt\\%}$ also increased the proportion of CO in the products due to more copper clusters or small nanoparticles being formed. Overall, the evidence suggested that single-atom copper species with isolated $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ units and copper clusters or small nanoparticles were the active sites for generating $\\mathrm{CH}_{3}\\mathrm{OH}$ and CO, respectively. However, it was found that when the copper loading amount was further increased to 12 and $15\\mathrm{wt\\%}$ , the $\\mathrm{CO}_{2}$ conversion and product distribution did not change further. Large particles of copper formed as the copper content further increased, but these do not activate $\\mathrm{CO}_{2}$ at low temperatures, consistent with the reaction results with CMZ-15 and CS-15 catalysts (Fig. $^{2\\mathrm{a},\\mathrm{b}^{\\cdot}}$ ). \n\nIn addition, the more obvious copper bulk structure in $\\mathrm{\\DeltaX}$ -ray diffraction (Fig. 4c), and the lower-temperature $\\mathrm{H}_{2}$ -TPR copper reduction peak (Supplementary Fig. 10c), together indicated that more metallic copper particles were generated by reducing ${\\mathrm{Cu}}^{2+}$ species over CAZ-15 during the reaction. \n\n$\\mathbf{C}\\mathbf{u}^{\\delta+}$ species migration during the reaction. Capturing the evolution of active metal species during reactions is essential for the in-depth understanding of active sites, especially in reactions involving hydrogen. A number of studies have shown that the gases used in the pretreatment or reaction process greatly affect the structure of catalysts, including active species migration33,34 and surface reconstruction61,62. A similar effect also existed in our $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalyst system, where the reaction gas promoted the migration of $\\mathrm{Cu}^{\\delta+}$ species from bulk to the surface of the support. Time-of-flight secondary-ion mass spectrometry (TOF-SIMS) is an extremely sensitive method for analysing the dispersion of elements on a catalyst surface, and can detect the top 1–3 atomic layers of elements on such a surface (Fig. 5a,b). Figure 5 compares fresh and used catalyst: more bright red spots were detected in Fig. 5b, suggesting more copper species appeared on the surface of CAZ-1-U. Semiquantitative analysis of the copper surface (Fig. 5c) also showed that the surface of CAZ-1-U contained more copper species, indicating that these species migrate to the surface during the reaction. These results were also supported by XPS analysis (Supplementary Fig. 22): the intensity of $\\mathrm{Cu}2p$ spectra for CAZ-1-U and CAZ-15-U were much stronger than for fresh catalysts, indicating that copper species were becoming enriched on the surface of used catalysts after the reaction. Meanwhile, $\\mathrm{Cu/Zr}$ ratios calculated by XPS further confirmed the above conclusion. The surface $\\mathrm{{Cu/Zr}}$ ratios of fresh CAZ-1 and CAZ-15 samples were 0.0012 and 0.24, and the corresponding ratios for used catalysts were 0.0018 and 0.38 (Supplementary Table 5), clearly indicating that there were more active copper sites on the surface of the catalysts after the reaction. Moreover, diffuse reflectance infrared Fourier transform spectroscopy with CO absorption (DRIFT-CO) was used to verify the copper migration and supplied further important evidence. The catalysts were adsorbed to saturation in CO atmosphere before the desorption experiment was carried out with argon. The absorbed peak at $2,102\\mathrm{cm}^{-1}$ was assigned to linear adsorption of CO on the copper species (Supplementary Fig. 23a,b)46,63. For the fresh catalyst, the CO concentration decreased rapidly with the argon purge time, and the surface residual concentration was close to zero at $20\\mathrm{min}$ . In comparison, the desorption rate of CO on CAZ-1-U was much slower than that on the fresh catalyst, while the obvious CO signal was still observed after $20\\mathrm{min}$ of gas purging. For a more intuitive comparison, the area of the CO absorption peak was normalized to $2,102\\mathrm{cm}^{-1}$ to give a time-dependent surface concentration attenuation spectrum with the argon purging time (Supplementary Fig. 23c). It was concluded that the level of CO absorption on CAZ-1-U was much more than that on fresh catalyst, proving that the surface of the used catalyst contained more copper sites. \n\nBased on the above details of the copper migration, it was inferred that a dynamic change of $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ active sites occurred during the reaction process. EXAFS data indicated that the copper species in $\\mathrm{Cu}/{\\mathsf{a}}–\\mathrm{Zr}\\mathrm{O}_{2}$ were mainly single atoms dispersed in the fresh catalysts, and that the copper species would migrate to the surface at a certain rate under the induction of reaction gas. This explains why the reaction had a certain initial induction period (Fig. 2d and Supplementary Fig. 13). It was concluded that the unique $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ structure in CAZ-1 was vital for $\\mathrm{CH}_{3}\\mathrm{OH}$ synthesis at low temperatures. The copper sites in CAZ-1 remained copper single atoms with isolated $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ structure after migrating to the surface due to the small amount of copper. However, more copper sites in CAZ-15 were accumulated and in situ reduced during migration in a hydrogen atmosphere process (Fig. $^{\\mathrm{4c,d}},$ ). Therefore, the migration behaviour of copper species during the reaction can be divided into three types according to the catalytic activity results. When the copper content was less than $2\\mathrm{wt\\%}$ , the migrated copper species did not accumulate during the reaction process but were still distributed in a monodispersed state, hence only $\\mathrm{CH}_{3}\\mathrm{OH}$ was produced and $\\mathrm{CO}_{2}$ conversion was enhanced linearly with increasing copper loading. When the copper loading was $4{-}8~\\mathrm{wt}\\%$ , the copper species migrated to the surface and partially agglomerated, and the activity showed that $\\mathrm{CO}_{2}$ conversion and CO selectivity increased while $\\mathrm{CH}_{3}\\mathrm{OH}$ selectivity decreased due to the formed copper clusters or small nanoparticles producing CO via the RWGS reaction. Finally, when the copper loading was higher than $8\\mathrm{wt\\%}$ , some of the copper species aggregated to form large copper particles without $\\mathrm{CO}_{2}$ activation ability, and thus the conversion of $\\mathrm{CO}_{2}$ and the product distribution were no longer changed. A schematic diagram illustrating this is shown in Fig. 5d. \n\nThe reaction mechanism of $\\mathbf{CO}_{2}$ hydrogenation. To clarify the structure influence for absorbed species on the surface, in situ DRIFT analysis was carried out under reaction conditions. All the tests were performed at $180^{\\circ}\\mathrm{C}$ and the assignments of all band vibration peaks are listed in Supplementary Table 7. As shown in Fig. 6a for CAZ-1, the active species were mainly first excited in $\\mathrm{HCO}_{3}{}^{*}$ : the peaks located at 1,695 and $1{,}431\\mathrm{cm}^{-1}$ were assigned to ionic bicarbonate species $\\mathrm{i-HCO}_{3}{}^{*}$ and the peaks at 1,631 and $1{,}226\\mathsf{c m}^{-1}$ to $\\nu_{\\mathrm{as}}(\\mathrm{HCO}_{3})$ and $\\nu_{\\mathrm{s}}(\\mathrm{HCO}_{3})$ of bidentate bicarbonate species ${\\mathsf{b}}{\\mathrm{-HCO}}_{3}^{\\ast}$ (ref. 64), respectively. As the reaction proceeded, the $\\mathrm{HCO}_{3}{}^{*}$ were slowly transformed into formate species, according to the peaks at 1,595, 1,384, 1,371, 2,736, 2,877 and $2{,}970\\mathrm{cm}^{-1}$ which were attributed to $\\nu_{\\mathrm{as}}(\\mathrm{OCO})$ , $\\delta(\\mathrm{CH})$ , $\\nu_{s}(\\mathrm{OCO})$ , $\\delta(\\mathrm{CH})+\\nu_{\\mathrm{as}}(\\mathrm{OCO})$ , $\\nu(\\mathrm{CH})$ and $\\delta(\\mathrm{CH})+\\nu_{\\mathrm{{s}}}(\\mathrm{OCO})^{21,36,65,66}$ . In fact, the transformation of bicarbonates to formate appears to follow the path: $\\mathrm{HCO}_{3}{^*}\\rightarrow\\mathrm{CO}_{2}\\rightarrow\\mathrm{HCOO^{*}}$ . The $\\mathrm{H}_{2}$ was also necessary because no evolution of $\\mathrm{HCO}_{3}{}^{*}$ to $\\mathrm{HCOO^{*}}$ could be detected in CAZ-1 by only absorbed $\\mathrm{CO}_{2}$ (Supplementary Fig. 24). Meanwhile, vibration peaks at 1,072, 1,146, 2,827 and $2{,}935\\mathrm{cm}^{-1}$ for $\\mathrm{CH}_{3}\\mathrm{O}^{*}$ were also detected, and assigned to $\\nu(\\mathrm{CO})$ -terminal, $\\nu(\\mathrm{CO})$ -bridge, $\\nu_{s}(\\mathrm{CH}_{3})$ and $\\nu_{\\mathrm{as}}(\\mathrm{CH}_{3})^{21,36,65}$ . Therefore, the process of $\\mathrm{CO}_{2}$ hydrogenation to $\\mathrm{CH}_{3}\\mathrm{OH}$ in CAZ-1 followed the formate path. Furthermore, it was proved that the $\\mathrm{CH}_{3}\\mathrm{OH}$ did not came from the hydrogenation process of in-situ-produced CO via the RWGS route because the reaction results showed no catalytic activity over CAZ-1 in the CO hydrogenation process under the same reaction conditions (Supplementary Table 3). For CAZ-15 catalyst, the $\\mathrm{CH}_{3}\\mathrm{OH}$ signal located at $1{,}007\\mathrm{cm}^{-1}$ was detected during the in situ DRIFT test66, which indicated the process of $\\mathrm{CH}_{3}\\mathrm{OH}$ formation was strongly promoted on CAZ-15 due to the quantity of active sites for $\\mathrm{CH}_{3}\\mathrm{OH}$ synthesis (Supplementary Fig. 25). In fact, the $\\mathrm{CO}_{2}$ adsorption capacity of the catalysts was not significantly changed by only increasing the loading of copper species, because CAZ-1 and CAZ-15 had similar adsorption modes and adsorption amounts for $\\mathrm{CO}_{2}$ $\\cdot3.0\\mathrm{mmol}\\mathrm{g}_{\\mathrm{cat}}^{-1}$ in CAZ-1, $2.9\\mathrm{mmol}\\mathrm{g}_{\\mathrm{cat}}^{-1}$ in CAZ-15; Supplementary Fi3g..02m6)m. Iotl gwcats concluded 2t.h9atmtmheoligncartease in methanol production rate was not affected by the adsorption capacity in these two catalysts, but was mainly caused by the different numbers of active sites. An increased copper loading of $15\\mathrm{wt\\%}$ resulted in the absorption of intermediate species on the surface of CAZ-15 being much more complex than that on CAZ-1. In addition to the adsorbed bicarbonate (1,621, $1{,}225\\mathrm{cm}^{-1}.$ ), carbonate (1,247, 1,324, 1,455, $1{,}505\\mathrm{cm}^{-1}.$ , formate $(1,360,1,384,2,864,2,974c m^{-1})$ and methoxy species (1,070, 1,146, 2,836, $2{,}921\\mathrm{cm}^{-1}.$ ), carboxylate signals were also captured at 1,287 and $1{,}756\\ c m^{-1}$ (ref. 67). The formation of $\\mathrm{CH}_{3}\\mathrm{OH}$ was accompanied by the RWGS reaction because more complex active copper sites (single-atom, cluster and particle) were provided by the reaction, leading to a decrease in $\\mathrm{CH}_{3}\\mathrm{OH}$ selectivity. As for CMZ-15 with large copper nanoparticles (Supplementary Fig. 27), all the absorbed species were $\\mathrm{CO}_{3}{}^{*}$ or $\\mathrm{HCO}_{3}{}^{*}$ but no further hydrogenation intermediates were observed, demonstrating that these large nanoparticles could not produce the further hydrogenation of carbonate at low temperature, which corresponded to the results of activity testing. \n\n![](images/4d91503d55231e128fbc986582fa39696d045738b53af65853e5de63823ba794.jpg) \nFig. 5 | Migration of ${\\mathsf{C u}}^{\\delta+}$ species to the surface. a,b, TOF-SIMS images and spectra of CAZ-1 showing the copper mapping of fresh CAZ-1 (a) and the copper mapping of CAZ-1-U (b). Scale bars, $10\\upmu\\mathrm{m}$ . The scale at the right of each image shows the measured intensity in counts per pixel. c, Semiquantitative analysis of TOF-SIMS spectra of CAZ-1 and CAZ-1-U. d, Schematic diagram of the migration of copper species in CAZ-1(left) and CAZ-15 (right) during the hydrogenation reaction. \n\nBased on the above information, intensity–time shift spectra supplied the dynamic behaviour of intermediates converting on CAZ-1 and CAZ-15 in the reaction (Fig. 6b). The peaks at 2,877 and $2,935\\mathrm{cm}^{-1}$ in CAZ-1 and at 2,864 and $2,921\\mathrm{cm}^{-1}$ in CAZ-15 were chosen to study the dynamic evolution of $\\mathrm{CH}_{3}\\mathrm{O}^{*}$ and $\\mathrm{HCOO^{*}}$ under reaction conditions $(180^{\\circ}\\mathrm{C},3\\mathrm{MPa})$ . The ratio of $\\mathrm{HCOO^{*}}/$ $\\mathrm{CH}_{3}\\mathrm{O}^{*}$ increased over both CAZ-1 and CAZ-15 catalysts with longer reaction times, indicating that the transformation process of $\\bar{\\mathrm{HCOO^{*}}}$ to $\\mathrm{CH}_{3}\\mathrm{O}^{*}$ was the rate-limiting step compared to the $\\mathrm{HCOO^{*}}$ -generating process in the synthesis of $\\mathrm{CH}_{3}\\mathrm{OH}$ from $\\mathrm{CO}_{2}$ . \n\nFurthermore, the rate of increase of $\\mathrm{HCOO^{*}/C H_{3}O^{*}}$ on CAZ-15 was much slower than that on CAZ-1, suggesting that the consumption of $\\mathrm{HCOO^{*}}$ species would be faster on the surface of CAZ-15. Because the relative rates of $\\mathrm{HCOO^{*}}$ formation and its further conversion to $\\mathrm{CH}_{3}\\mathrm{O}^{*}$ were the same for each $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ site in producing methanol over CAZ-1 and CAZ-15, the only reason to explain the different rates of increase of $\\mathrm{HCOO^{*}/C H_{3}O^{*}}$ over these two catalysts is that CAZ-15 contains more different types of active copper sites for $\\mathrm{HCOO^{*}}$ conversion reactions, such as $\\mathrm{HCOO^{*}\\rightarrow C O}$ . \n\nThe excellent selectivity to $\\mathrm{CH}_{3}\\mathrm{OH}$ of CAZ-1 could be attributed to its unique $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ catalytic centre as confirmed by density functional theory (DFT) calculations. The structure of $\\mathsf{C u}_{1}\\mathsf{O}_{1}$ on amorphous $\\mathrm{ZrO}_{2}$ $\\mathrm{(Cu_{1}O_{1}/a-Z r O_{2})}$ surface was obtained by using stochastic surface walking (SSW) global optimization based on global neural network potential (SSW-NN) simulation to explore the global potential energy surface of the $\\mathrm{Cu_{1}O_{1}/Z r O_{2}}$ system. The stability energy of $\\mathrm{Cu}_{1}\\mathrm{O}_{1}$ on $\\mathsf{a}{\\mathsf{-}}{\\mathsf{Z r O}}_{2}$ was $-1.53\\mathrm{eV},$ much lower than that on $\\mathrm{ZrO}_{2}$ flat (111) and terrace (112) surfaces, which have stability energies of 1.10 and $0.17\\mathrm{eV}$ that point to high thermodynamic stability (Supplementary Fig. $28\\mathsf{a}\\mathsf{-c})$ . The most stable structure of $\\mathrm{{Cu}_{1}\\mathrm{{O}_{1}}}$ on amorphous $\\mathrm{ZrO}_{2}$ showed a special $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ quasiplanar configuration with $\\mathrm{Cu-O}$ bond distances of 1.814, 1.920 and $1.921\\mathring\\mathrm{A}$ (Supplementary Fig. 29), which agreed well with the EXAFS results. Moreover, the large oxygen vacancy formation energy of $3.7\\mathrm{eV}$ on $\\mathrm{Cu}_{1}\\mathrm{O}_{1}/\\mathrm{a}{-}\\mathrm{Zr}\\mathrm{O}_{2}$ indicated the absence of $\\mathrm{\\DeltaO_{v}},$ further proving that the amorphous $\\mathrm{ZrO}_{2}$ surface can anchor and stabilize isolated copper atoms (Supplementary Fig. 28c). Electronic structure analysis showed that these isolated copper atoms existed in the form of ${\\mathrm{Cu}}^{2+}$ cation (Supplementary Table 8), consistent with the experimental XANES results before and after the reaction. When the $\\mathrm{Cu}_{1}\\mathrm{O}_{1}/\\mathrm{a}{-}\\mathrm{Zr}\\mathrm{O}_{2}$ was exposed to the reaction atmosphere with reductive $\\mathrm{H}_{2}$ gas, a hydrogen atom can strongly adsorb on an oxygen atom near a copper atom with the adsorption energy of $-1.76\\mathrm{eV.}$ This led to the reduction of ${\\mathrm{Cu}}^{2+}$ to the $\\mathrm{Cu}^{\\delta+}$ $(1<\\delta<2)$ cation (Supplementary Table 8), consistent with the in situ XAS results during the reaction process (Fig. 3d). Therefore, the ${\\mathrm{Cu}}^{\\delta+}$ cation was used as the active site to explore the mechanism of the $\\mathrm{CO}_{2}$ reduction process. \n\n![](images/090d5f209cb5686280456cb3c1a73969bed2f89cd25489c4401265d95bddee8a.jpg) \nFig. 6 | Characterization and evolution of reactive intermediates. a,b, In situ DRIFT spectroscopy of CAZ-1 for different wavenumber intervals: 800– $1,900{\\mathsf{c m}}^{-1}$ (a) and $2,650{-}3,110\\mathsf{c m}^{-1}$ (b). Dashed lines identify the changes of peaks related to different intermediates. c, The ratio of HCOO\\* to $C H_{3}O^{\\prime}$ intermediates changes as a function of time. Analysis conditions: the sample was first pretreated under an argon atmosphere at $230^{\\circ}\\mathsf C$ for $60\\mathrm{{min}}$ , then mixed gas $(\\mathsf{C O}_{2};\\mathsf{H}_{2}=1;3)$ was introduced into cell to a pressure of 3 MPa and data were recorded at $180^{\\circ}\\mathsf C$ for 100 or $200\\mathsf{m i n}$ . \n\n![](images/1321d20f71edf38f356227e6fed756ffc9470cc49c043c26e3c6e0f6364d6e94.jpg) \nFig. 7 | Mechanism analysis of $\\mathbf{CO}_{2}$ hydrogenation to ${\\mathsf{C H}}_{3}{\\mathsf{O H}}/{\\mathsf{C O}}$ on isolated ${\\mathsf{C u}}^{\\delta+}$ $\\delta+(1<\\delta<2)$ cation. a, Gibbs free-energy profile of ${\\mathsf{C O}}_{2}$ hydrogenation to ${\\mathsf{C H}}_{3}{\\mathsf{O H}}/{\\mathsf{C O}}$ . b,c, Variation in reaction intermediate concentrations $(\\pmb{\\ b})$ and reaction rates (c) during the microkinetics simulation. The asterisk indicates the adsorption state and the reaction snapshots are shown with Cu, $Z\\mathsf{r},$ O, C and $\\mathsf{H}$ in orange, cyan, red, grey and white, respectively. \n\nFigure 7 and Supplementary Figs. 30 and 31 show the calculated lowest-energy pathway for $\\mathrm{CO}_{2}$ hydrogenation, which involves $\\scriptstyle{\\mathrm{HCOO^{*}}}$ , $\\mathrm{H}_{2}\\mathrm{COO^{*}}$ and $\\mathrm{CH}_{3}\\mathrm{O}^{*}$ key intermediates. The reaction started with the dissociative adsorption of an $\\mathrm{H}_{2}$ molecule on a $\\mathrm{Cu-O}$ pair to form $\\mathrm{{Cu-H}}$ and OH groups (Supplementary Fig. 32), which was endothermic at $0.57\\mathrm{eV}.$ The dissociation energy barrier of $\\mathrm{H}_{2}$ is $0.61\\mathrm{eV}.$ A $\\mathrm{CO}_{2}$ molecule was adsorbed physically near the $\\mathrm{{Cu-H}}$ group, resulting in a free-energy change of $0.64\\mathrm{eV}.$ While there were two possible channels for $\\mathrm{CO}_{2}$ hydrogenation, that is, to $\\mathrm{HCOO^{*}}$ or to $\\mathrm{COOH^{\\ast}}$ , our calculations showed that the formation of the $\\mathrm{COOH^{*}}$ group had a high barrier of $0.43\\mathrm{eV},$ but the formation of $\\mathrm{HCOO^{*}}$ was nearly barrierless $\\left(0.08\\mathrm{eV}\\right)$ . Thermodynamically, the $\\mathrm{COOH^{*}}$ group was also $0.39\\mathrm{eV}$ less stable than the $\\mathrm{HCOO^{*}}$ group. The formed $\\mathrm{HCOO^{*}}$ adopted a bidentate configuration with two oxygen ends linking with the zirconium and copper atoms at distances of 2.20 and $1.85\\mathring{\\mathrm{A}}.$ , respectively. This indicated that the $\\mathrm{HCOO^{*}}$ pathway was the only viable route for $\\mathrm{CO}_{2}$ hydrogenation. \n\nAfter $\\mathrm{HCOO^{*}}$ formation, a second $\\mathrm{H}_{2}$ molecule dissociated on the copper and the neighbouring two-coordinated surface oxygen with an endothermic energy of $0.61\\mathrm{eV}.$ The C atom of the $\\mathrm{HCOO^{*}}$ group could then be hydrogenated to $\\mathrm{CH}_{2}\\mathrm{OO^{*}}$ group with a barrier of $0.70\\mathrm{eV}$ and a reaction energy of $0.22\\mathrm{eV.}$ After that, $\\mathrm{CH}_{2}\\mathrm{OO^{*}}$ could easily pick up the neighbouring hydrogen atom to form $\\mathrm{CH}_{2}\\mathrm{OOH}^{*}$ with a barrier of only $0.01\\mathrm{eV}.$ The $\\mathrm{CH}_{2}\\mathrm{OOH}^{*}$ could further break the $C{\\mathrm{-}}\\mathrm{O}$ bond to form $\\mathrm{CH}_{2}\\mathrm{O}^{*}$ and hydroxyl groups by overcoming a barrier of $1.08\\mathrm{eV}.$ The generated hydroxyl groups could react with the neighbouring hydrogen atom to form a water molecule with a reaction barrier of $1.04\\mathrm{eV}$ and a reaction energy of $0.50\\mathrm{eV}.$ The water molecule could desorb readily (exothermic by $0.15\\mathrm{eV})$ . $\\mathrm{CH}_{2}\\mathrm{O}^{*}$ could stepwisely react with neighbouring hydrogen atoms to form $\\mathrm{CH}_{3}\\mathrm{O}^{*}$ and $\\mathrm{CH}_{3}\\mathrm{OH}^{*}$ . The reaction barriers for these two hydrogenation steps were 0.13 and $0.70\\mathrm{eV}$ with the reaction energies being $-1.66$ and $0.63\\mathrm{eV},$ respectively. The desorption of $\\mathrm{CH}_{3}\\mathrm{OH}$ would further release $0.57\\mathrm{eV}$ energy. \n\n![](images/286b415a16d2e8f1e5c86dfe094fffac56ee8d8e4e463c9e7c2883091888ff03.jpg) \nFig. 8 | Schematic diagram for ${\\mathsf{C O}}_{2}$ hydrogenation reaction on different types of copper species. The physical model correlates the particle diameter and the ${\\mathsf{C O}}_{2}$ hydrogenation reaction pathway at low temperature: ${\\mathsf C}{\\mathsf O}_{2}/{\\mathsf H}_{2}$ can only produce methanol on single-atom copper species; on copper clusters or nanoparticles, only CO generation can be promoted; larger copper particles have almost no catalytic activity to ${\\mathsf{C O}}_{2}/{\\mathsf{H}}_{2}$ mixed gas. Reaction conditions: $0.5g$ sample, $3M P a$ , $180^{\\circ}\\mathsf C$ , ${\\mathsf{C O}}_{2}{:}{\\mathsf{H}}_{2}=1{:}3,$ , $10\\mathsf{m l}\\mathsf{m i n}^{-1}$ . \n\nHaving established the overall reaction profiles, we can now determine the reaction rate of $\\mathrm{CO}_{2}$ hydrogenation on an isolated $\\mathrm{Cu}^{\\delta+}$ cation site based on microkinetics simulation. Our microkinetics numerical simulation results are shown in Fig. 7b. At the steady state, the dominant reaction intermediates on the surface were $\\mathrm{HCOO^{*}}$ species, the concentration of which increased from 0 to 0.8 with increasing time. This proved that the consumption of $\\scriptstyle{\\mathrm{HCOO^{*}}}$ species was the rate-determining step, a finding that is consistent with the in-situ DRIFT spectroscopy. At $180^{\\circ}\\mathrm{C}_{:}$ the calculated TOF for $\\mathrm{CO}_{2}$ hydrogenation to $\\mathrm{CH}_{3}\\mathrm{OH}$ on an isolated ${\\mathrm{Cu}}^{\\delta+}$ cation was around $2.89\\mathrm{h}^{-1}$ , which was about two orders of magnitude larger than the $\\mathrm{CO}_{2}$ hydrogenation to C $)(0.03\\mathrm{h}^{-1})$ , as illustrated in Fig. 7c, and the selectivity of $\\mathrm{CO}_{2}$ hydrogenation to methanol was near $100\\%$ . The theoretical TOF for $\\mathrm{CO}_{2}$ hydrogenation to methanol was quite close to the experimental TOF value $(1.37\\mathrm{h}^{-1})$ . \n\nBased on the above results, we can establish a reaction model for $\\mathrm{CO}_{2}$ hydrogenation over the CAZ- $x$ series catalysts, as shown in Fig. 8. When the copper species is distributed in a single-atom level with uniform $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ catalytic centres on the surface of $\\mathrm{ZrO}_{2}$ , $\\mathrm{CO}_{2}$ is converted to methanol with $100\\%$ selectivity. When the copper species exists in the form of clusters or small nanoparticles, $\\mathrm{CO}_{2}$ can only produce unwanted CO. As the copper species is in larger particles, $\\mathrm{CO}_{2}$ is hard to activate and there is almost no catalytic activity. Under typical catalytic conditions, the $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ sites in copper single atoms and the copper clusters/small nanoparticles in combination contribute to methanol and CO synthesis from $\\mathrm{CO}_{2}$ hydrogenation, while the larger copper particles are not active sites for $\\mathrm{CO}_{2}$ hydrogenation. \n\n# Conclusions \n\nThis work reveals the strong dependence of $\\mathrm{CO}_{2}$ hydrogenation activity and selectivity on the nature of surface copper species for $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalysts. The undercoordinated cationic $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ species accumulate dynamically on the catalyst surface, forming stable active sites during the catalysis process, and achieving high selectivity to $\\mathrm{CH}_{3}\\mathrm{OH}$ $(100\\%)$ in $\\mathrm{CO}_{2}$ hydrogenation at $180^{\\circ}\\mathrm{C}$ . The copper single-atom catalyst can dissociate hydrogen readily with the help of nearby oxygen atoms and activate $\\mathrm{CO}_{2}$ to generate $\\mathrm{HCOO^{*}}$ , a key intermediate in $\\mathrm{CH}_{3}\\mathrm{OH}$ synthesis. The $\\mathrm{HCOO^{*}}$ pathway is the only viable route for $\\mathrm{CO}_{2}$ hydrogenation on the isolated $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ active sites. In contrast, small copper clusters and/or nanoparticles are active sites for CO formation via the RWGS route, while large copper particles barely activate $\\mathrm{CO}_{2}$ at low temperatures. The characteristic geometry and unique activity revealed in the copper single-atom catalyst provide a deep understanding of copper-catalysed $\\mathrm{CO}_{2}$ hydrogenation, and will guide future applications of single-atom catalysts in thermal catalytic $\\mathrm{CO}_{2}$ transformations. \n\n# Methods \n\nSynthesis of CAZ-1. CAZ-1 was synthesized by a co-precipitation method using $\\mathrm{Na}_{2}\\mathrm{CO}_{3}$ as precipitant. First, $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}{\\cdot}3\\mathrm{H}_{2}\\mathrm{O}$ (Sigma-Aldrich, $98\\mathrm{-}103\\%$ ) and $\\mathrm{Zr(NO_{3})_{4}}{\\cdot}5\\mathrm{H}_{2}\\mathrm{O}$ (Macklin, AR) precursors were weighed according to the metal loading and dissolved together into $\\mathrm{100ml}$ deionized water to make a $0.03\\mathrm{M}$ solution (solution A). An appropriate amount of $\\mathrm{Na}_{2}\\mathrm{CO}_{3}$ was weighed and dissolved in $\\mathrm{100ml}$ deionized water to make a $0.06\\mathrm{M}$ solution (solution B). After dissolution was complete, a peristaltic pump was used to slowly drip the two solutions A and B into another beaker containing $\\mathrm{100ml}$ of deionized water at a rate of $0.3\\mathrm{ml}\\mathrm{min}^{-1}$ . Throughout the dropping process, the mixture was stirred at $350\\mathrm{rpm}$ while heating at $80^{\\circ}\\mathrm{C}$ . Once the dropping was complete, stirring was stopped and the flocculent precipitate that had formed was aged at $80^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ . After ageing, it was cooled to room temperature and washed with deionized water to $\\mathrm{pH7}$ , followed by drying in an oven at $80^{\\circ}\\mathrm{C}$ overnight. Finally, the blue solid sample was ground into powder and calcined in a muffle furnace by heating at $2^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ to $350^{\\circ}\\mathrm{C}$ over $^{5\\mathrm{h}}$ . \n\nCatalyst characterization. The actual loading of copper in different catalysts was determined by ICP-OES performed on an iCAP 7000 (Thermo Fisher). The test method was as follows: $10\\mathrm{mg}$ of sample was dissolved in a mixed solution ( $2\\mathrm{ml}$ $\\mathrm{HNO}_{3}+6\\mathrm{ml}\\mathrm{HCl}+2\\mathrm{ml}\\mathrm{HF}$ ) overnight, then added to a $50\\mathrm{ml}$ volumetric flask and diluted to the scale line. Four internal copper concentration standard solutions (1, $10,50,100\\mathrm{ppm}_{.}$ ) were analysed and used to create a standard curve $(R^{2}>0.9999)$ ) before testing all samples. X-ray diffraction measurements were performed on a Rigaku X-ray diffractometer equipped with graphite-monochromatized Cu $\\mathrm{K}\\upalpha$ radiation (scan angle, $10^{\\circ}-90^{\\circ}$ ; scan speed, $2^{\\circ}\\mathrm{{min}^{-1}}$ ; voltage, $40\\mathrm{kV};$ current, $40\\mathrm{mA}\\cdot$ ). The Raman spectroscopy data were collected on a Thermo Fisher DXR2xi with a $532\\mathrm{nm}$ light source. In situ X-ray diffraction experiments were carried out on a Rigaku Ultima $4\\mathrm{X}$ -ray diffractometer with Cu Ka radiation $(40\\mathrm{kV},40\\mathrm{mA}$ ) in the temperature range of $10^{\\circ}{-}80^{\\circ}\\mathrm{C}$ with a scanning step length of 0.33 under a hydrogen atmosphere $\\mathrm{30mlmin^{-1}},$ . The curves were recorded at 30, 180, 230, 300 and $350^{\\circ}\\mathrm{C}$ . The morphology and elemental mapping of catalysts were measured on a JEM ARM200F thermal-field emission microscope with a probe spherical aberration $\\scriptstyle(\\mathbf{C}s)$ corrector working at $200\\mathrm{kV},$ and by TEM (FEI Talos $\\mathrm{F}200\\mathrm{S}\\mathrm{G}2\\mathrm{\\Omega},$ ) at $200\\mathrm{kV}.$ The $\\mathrm{H}_{2}$ -TPR curves of samples were collected with an AutoChem II 2920 chemisorption analyser (Micromeritics) equipped with a thermal conductivity detector (TCD). Helium at $30\\mathrm{ml}\\mathrm{min}^{-1}$ was used to pretreat the samples at $250^{\\circ}\\mathrm{C}$ for $2\\mathrm{h}$ to remove moisture from the surface. Then $10\\%\\mathrm{H}_{2}/\\mathrm{He}$ was passed into the reactor, with the temperature increasing at $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ to $700^{\\circ}\\mathrm{C}$ and data were recorded every $0.5\\mathrm{min}$ . $\\mathrm{H}_{2}$ -TPD curves of samples were also collected on an AutoChem II 2920 chemisorption analyser (Micromeritics). The samples were first pretreated at $300^{\\circ}\\mathrm{C}$ at a heating rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ in helium for $30\\mathrm{min}$ , and then cooled to room temperature and further saturated by $10\\%\\mathrm{H}_{2}/\\mathrm{Ar}$ for $30\\mathrm{min}$ . After purging the physically adsorbed hydrogen on the surface with helium at $50^{\\circ}\\mathrm{C}$ for $^\\mathrm{1h}$ , the temperature was slowly increased to $750^{\\circ}\\mathrm{C}$ and the thermal \n\nconductivity detector signal recorded at the same time. $\\mathrm{CO}_{2}$ -TPD measurements were performed in the same way as for $\\mathrm{H}_{2}$ -TPD except that $5\\%$ $\\mathrm{CO}_{2}$ was used as the adsorption gas. \n\nXPS and AES data were collected on an ESCALAB 250 photoelectron spectroscope (Thermo Fisher Scientific) equipped with monochromatic Al $\\mathrm{K}\\upalpha$ radiation (200 W, $E=1,486.6\\mathrm{eV}$ ). The binding energy of all samples was calibrated to the C 1s peak of environmental carbon at $284.8\\mathrm{eV}.$ \n\nThe ex situ and in situ XAS experiments were performed at beamline BL14W1 of the Shanghai Synchrotron Radiation Facility (SSRF) in fluorescence mode with a Si(111) monochromator. A Lytle detector and a silicon solid detector were used to collect ex situ and in situ XAS data, respectively. At the same time, a $6\\upmu\\mathrm{m}$ nickel filter was used to filter the signal. A copper foil was taken as a reference sample and measured for energy-calibration purposes $\\mathrm{'}E_{0}{=}8,979\\mathrm{eV}\\mathrm{\\rangle}$ ). The first maximum point of the first-order derivative of the XANES was defined as $E_{0}$ . For ex situ experiments, Cu K-edge spectra were collected at room temperature $(25^{\\circ}\\mathrm{C})$ . The CAZ-1, CAZ-1-U, CAZ-15 and CMZ-15 samples were pressed into pellets without any dilution. The in situ testing for CAZ-1 catalyst was performed by using a reactor with a beryllium window. Multiple repeated scans $\\ensuremath{\\left(\\sim20\\mathrm{min}\\right.}$ for each scan) were applied to achieve high data quality. Multiple data scans were collected and merged to improve the signal-to-noise ratio. A K-type thermocouple was placed in contact with the catalyst bed to control the temperature, and the flow rate of the gas was controlled by multiple flow controllers. CAZ-1 sample was first pressed into a $1.5\\mathrm{cm}$ disc, then placed in a cell for pretreatment at $230^{\\circ}\\mathrm{C}$ under an argon gas flow $\\mathrm{\\langle30mlmin^{-1}}$ ) for $2\\mathrm{h}$ . The temperature was then lowered to $180^{\\circ}\\mathrm{C}$ and the gas changed to $\\mathrm{CO_{2}}/\\mathrm{H}_{2}\\left(25/75,10\\mathrm{ml}\\mathrm{min^{-1}}\\right)$ . After the pressure was stabilized at 1 MPa, the continuous spectrum was collected. EXAFS data processing (including calibration, merge, and analysis) was done with Athena/Artemis software packages68, based on FEFF6. Bond length (R), Debye-Waller factor $\\left(\\sigma^{2}\\right)$ , amplitude factor $(S_{0}^{2})$ and energy shift $(\\Delta E_{0})$ were used to optimize the fitting results. The WT wSa0s performed with the HAMA Fortran package (http://www.esrf. eu/UsersAndScience/Experiments/CRG/BM20/Software/Wavelets/HAMA). In a typical WT analysis, $k_{\\mathrm{weight}}=2$ , and the Morlet function was used, with $\\kappa{=}10$ , $\\sigma=1$ . \n\nDRIFT-CO chemisorption measurements were carried on a Nicolet iS50 spectrometer (Thermo Fisher Scientific) with a mercury–cadmium–telluride detector and a Harrick reaction cell. The sample was first treated in an argon atmosphere $(30\\mathrm{ml}\\mathrm{min}^{-1},$ ) at $300^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ , then cooled to $30^{\\circ}\\mathrm{C}$ for background collection. After that, $10\\%$ CO/Ar was passed through the sample until the adsorption was saturated, then the $10\\%$ CO/Ar was cut off and the desorption spectra recorded as 32 scans at a resolution of $4\\mathrm{cm}^{-1}$ under an argon purge. In situ DRIFT experiments at high pressure $(3\\mathrm{{MPa})}$ were measured on a Fourier transform infrared spectrometer (Bruker Vertex 70) with a mercury–cadmium–telluride detector and a Harrick reaction cell. The samples were first pretreated with helium at $230^{\\circ}\\mathrm{C}$ or hydrogen at $250^{\\circ}\\mathrm{C}$ for $60\\mathrm{min}$ , then cooled to $150^{\\circ}\\mathrm{C}$ and treated with $\\mathrm{CO}_{2}/\\mathrm{H}_{2}/\\mathrm{Ar}$ (24/72/4) or $\\mathrm{CO}_{2}$ alone. After the pressure reached 3 MPa the background was collected. Finally, the temperature was raised to $180^{\\circ}\\mathrm{C}$ and the spectra recorded over the absorption time. \n\nTOF-SIMS experiments were tested on a PHI nano TOF II with ${\\mathrm{Bi}_{3}}^{+}$ as the ion species. The energy, ion current, raster size, mass range, mode and analysis time for each test were $30\\mathrm{keV},$ 2 nA, $100\\upmu\\mathrm{m}\\times100\\upmu\\mathrm{m}$ , $0{-}1{,}850\\upmu\\mathrm{g/L}$ , high mass resolution mode and 5 min, respectively. \n\nThe $\\mathrm{H}_{2}{-}\\mathrm{D}_{2}$ exchange experiments were carried out in a flow reactor at $180^{\\circ}\\mathrm{C}$ and the formation rate of the HD product was measured by the mass signal intensity (ionic current). First, $0.1\\mathrm{g}$ sample was pretreated for 1 h in different $(30\\mathrm{ml}\\mathrm{min}^{-1}.$ ) atmospheres (pure $\\mathsf{a{-}Z r O_{2}}.$ , CAZ-1-U, CAZ-15-U and pure Q50 were pretreated at $230^{\\circ}\\mathrm{C}$ with argon, CMZ-15 was pretreated at $250^{\\circ}\\mathrm{C}$ with hydrogen), followed by passing a mixture of $\\mathrm{D}_{2}$ and $\\mathrm{H}_{2}$ ( $\\mathrm{\\cdot}10\\mathrm{ml}\\mathrm{min^{-1}}.$ ) through the sample. The reaction products $\\mathrm{H}_{2}$ , $\\mathrm{D}_{2}$ and HD were analysed by mass spectrometry (OmniStar). The mass-to-charge ratios using $\\mathrm{H}_{2},\\mathrm{D}_{2}$ and HD are 2, 4 and 3, respectively. \n\nCatalytic evaluation. The catalytic performance of all catalysts was tested on a high-pressure, continuous-flow, fixed-bed reactor built by Xiamen Better Works Engineering. We mixed $500\\mathrm{mg}$ of CAZ- $x$ catalysts $(40-60\\ \\mathrm{mesh})$ with $2\\mathrm{g}$ of quartz sand (40–60 mesh) and pretreated this mixture in an argon atmosphere at $230^{\\circ}\\mathrm{C}$ (CAZ-1-r was reduced by $\\mathrm{H}_{2}$ at $370^{\\circ}\\mathrm{C})$ ) in a flow of $30\\mathrm{ml}\\mathrm{min}^{-1}$ for $10\\mathrm{{h}}$ . CMZ15 and CS-15 were pretreated with hydrogen at $250^{\\circ}\\mathrm{C}$ in a flow of $30\\mathrm{ml}\\mathrm{min}^{-1}$ for 10 h. The temperature was then cooled to ${180^{\\circ}\\mathrm{C}},$ and $\\mathrm{CO}_{2}/\\mathrm{H}_{2}/\\mathrm{Ar}$ (24/72/4, 3 MPa) was introduced. After the pressure and temperature stabilized, the gas flow was changed to $10\\mathrm{ml}\\mathrm{min}^{-1}$ and a Shimadzu chromatograph equipped with a flame ionization detector and a thermal conductivity detector was used to analyse products online every $30\\mathrm{min}$ . The catalytic performance of catalysts was evaluated in terms of $\\mathrm{CO}_{2}$ conversion, product selectivity, TOF and space-time yield (STY). The computational formulas were as follows: \n\n$$\n\\begin{array}{r}{\\mathrm{CO_{2}c o n v e r s i o n},C_{\\mathrm{CO_{2}}}\\left(\\%\\right)=\\frac{X_{\\mathrm{CO_{2},i n}}-X_{\\mathrm{CO_{2},o u t}}}{X_{\\mathrm{CO_{2},i n}}}\\times100\\%}\\end{array}\n$$ \n\n$$\n\\begin{array}{r}{\\mathrm{Product}\\left(i\\right)\\mathrm{selectivity},\\mathrm{Sel}_{i}\\%=\\frac{R_{i}\\times f_{i,\\mathrm{m}}}{\\sum_{i}R_{i}\\times f_{i,\\mathrm{m}}}\\times100\\%}\\end{array}\n$$ \n\n( −1 −1) = FCO2,in×CCO2 ×SelCH3OH×1,000 (4) \n\nwhere $X_{\\mathrm{CO_{2},i n}}$ and $X_{\\mathrm{CO_{2},o u t}}$ are the mole fractions of $\\mathrm{CO}_{2}$ in pristine and exit mixed gas, resXpeCcOt2i,ivnely; $R_{i}$ XisC tO2h,eouatrea ratio of products in the chromatogram, $f_{i,\\mathrm{{m}}}$ is the correction for mass; $F_{\\mathrm{CO}_{2},\\mathrm{in}}(\\mathrm{molh^{-1}})$ is the molar flow rate of $\\mathrm{CO}_{2}$ in pristine mixed gas; $M_{\\mathrm{{Cu}}}$ is the molecuFlCaOr2,iwneight of copper, $63.546\\mathrm{gmol^{-1}}$ and $W_{\\mathrm{cat}}\\left(\\mathbf{g}\\right)$ and $L_{\\mathrm{Cu}}\\left(\\%\\right)$ are the catalyst weight and the actual loading of copper, respectively. \n\nDFT calculations. The reaction profiles were calculated using plane-wave DFT calculations as implemented in ${\\mathrm{VASP}}^{69}$ , where electron–ion interaction was represented by the projector-augmented wave pseudopotential70,71. The exchange functional utilized was the spin-polarized GGA- $\\cdot\\mathrm{PBE}^{72}$ and the kinetic energy cut-off was set as $450\\mathrm{eV}.$ The first Brillion zone $k$ -point sampling utilizes only the gamma-point since the supercell was rather large, which was shown to provide converged energetics. The energy and force criterion for convergence of the electron density and structure optimization were set at $10^{-5}\\mathrm{eV}$ and $0.05\\mathrm{{\\bar{e}V}\\bar{A}^{-1}}$ , respectively. \n\nSSW-NN simulation. The active site structure was resolved by the machine-learning-based fast global potential energy surface (PES) exploration using the SSW method as implemented in LASP code73. The PES of the catalyst system (containing elements Cu, Zr, O and H) was described by the global neural network (G-NN) potential, which was generated by iteratively self-learning the global PES dataset from SSW exploration. In the past few years, the SSW-NN method has been successfully applied in solving the structures of complex systems, including oxide13,74,75, zeolite74 and molecule crystals76. The procedure for SSW-NN simulation is briefly summarized below. \n\nFirst, the global dataset was built iteratively during the self-learning of the G-NN potential. These PES data came initially from the DFT-based SSW simulation and were then amended by G-NN-based SSW PES exploration. To cover all the likely compositions of the four-element $\\mathrm{Cu{-}Z r{-}O{-}H}$ systems, SSW simulations were performed starting from different types of structures (including bulk, layer and cluster), compositions and atom numbers per supercell. Overall, these SSW simulations generated more than $10^{7}$ structural configurations on the PES and a fraction of these were selected as the dataset to be computed by high-accuracy DFT calculations. The final dataset of the $\\mathrm{Cu-Zr}$ –O–H G-NN potential contains 60,271 structures, as detailed in Supplementary Table 9. \n\nSecond, a final G-NN potential was trained on the global dataset using the method introduced in our previous work77,78. To achieve a high accuracy for PES, we adopted a large set of power-type structure descriptors, which contained 324 descriptors for every element, including 148 two-body, 170 three-body and 6 four-body descriptors, and compatibly, the neural network had two hidden layers (324-50-50-1 net) each with 50 neurons and one output layer with one neuron, equivalent to 75,000 network parameters in total. Minimum–maximum scaling was utilized to normalize the training data sets. Hyperbolic tangent activation functions were used for the hidden layers, while a linear transformation was applied to the output layer of all networks. The limited-memory Broyden– Fletcher–Goldfarb–Shanno method was used to minimize the loss function to match DFT energy, force and stress. The final energy and force criterions of the r.m.s. errors of the G-NN potential were $6.0\\mathrm{meV}$ per atom and $0.151\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ , respectively. The NN potential of CuZrOH.pot can be found at www.lasphub.com/ supportings/CuZrOH.pot. \n\nFinally, SSW-NN global optimization was utilized to obtain a reasonable model of $\\mathrm{\\mathbf{C}\\mathbf{u}_{\\mathrm{sAC}}}$ on amorphous $\\mathrm{ZrO}_{2}$ by exhaustively searching the phase space of $\\mathrm{{Cu}_{\\mathrm{1}}\\mathrm{{O}_{\\mathrm{1}}/}}$ $\\mathrm{ZrO}_{2}$ . The model was built as follows: \n\n1. From the most stable monoclinic $\\mathrm{ZrO}_{2}$ bulk structure, the most stable $\\left(-111\\right)$ surface in a $\\boldsymbol{p}$ $(4\\times4)$ supercell was cleaved that contains three $\\mathrm{ZrO}_{2}$ layers with 144 atoms ${(48\\mathrm{Zr}0_{2}}$ formula units). \n2. To create defects, three $\\mathrm{ZrO}_{2}$ formula units (nine atoms) were artificially removed from the $\\mathrm{m}{-}\\mathrm{Zr}\\mathrm{O}_{2}$ (−111) surface, and utilized to represent the locally amorphous structure (Supplementary Fig. 33). \n3. One CuO formula unit (two atoms) was randomly added at the $\\mathrm{ZrO}_{2}$ defect sites. \n4. Starting from the $\\mathrm{Cu_{1}O_{1}/Z r O_{2}}$ model, more than 10,000 minima were explored by SSW-NN simulation. From that, the most stable structure of $\\mathrm{{Cu}_{\\mathrm{1}}\\mathrm{{O}_{\\mathrm{1}}}}$ on amorphous $\\mathrm{ZrO}_{2}$ was obtained, which featured a special $\\mathrm{Cu}_{1}–\\mathrm{O}_{3}$ quasiplanar configuration decorated at the $\\mathrm{ZrO}_{2}$ defect sites. This structure had $\\mathrm{Cu-O}$ bond distances of 1.814, 1.920 and 1.921 Å (Supplementary Fig. 29), which were very consistent with the EXAFS results. The stable structures were then verified by DFT calculations and then adopted for further computing the $\\mathrm{CO}_{2}$ hydrogenation pathway. \n\n# Data availability \n\nData presented in the main figures of the manuscript and Supplementary Information are publicly available through the Zenodo repository (https:// zenodo.org/deposit/6874758); all other relevant raw data are available from the corresponding authors upon reasonable request. Source data are provided with this paper. \n\n# Code availability \n\nThe software code of LASP and NN potential used within the article is available from the corresponding author upon request or on the website http://www. lasphub.com. \n\nReceived: 24 June 2021; Accepted: 8 August 2022; Published online: 15 September 2022 \n\n# References \n\n1.\t Li, J. et al. Integrated tuneable synthesis of liquid fuels via Fischer–Tropsch technology. Nat. Catal. 1, 787–793 (2018). \n2.\t Jenkinson, D. S., Adams, D. E. & Wild, A. Model estimates of $\\mathrm{CO}_{2}$ emissions from soil in response to global warming. Nature 351, 304–306 (1991). \n3.\t Kang, X. et al. Highly efficient electrochemical reduction of $\\mathrm{CO}_{2}$ to $\\mathrm{CH}_{4}$ in an ionic liquid using a metal–organic framework cathode. Chem. Sci. 7, \n266–273 (2016). \n4.\t Zhong, J. et al. State of the art and perspectives in heterogeneous catalysis of $\\mathrm{CO}_{2}$ hydrogenation to methanol. Chem. Soc. Rev. 49, 1385–1413 (2020). \n5.\t Yao, B. et al. Transforming carbon dioxide into jet fuel using an organic combustion-synthesized $_{\\mathrm{Fe-Mn-K}}$ catalyst. Nat. Commun. 11, 6395 (2020). \n6.\t Hu, J. et al. Sulfur vacancy-rich $\\mathbf{MoS}_{2}$ as a catalyst for the hydrogenation of $\\mathrm{CO}_{2}$ to methanol. Nat. Catal. 4, 242–250 (2021). \n7.\t Tan, L. et al. Development of soluble UiO-66 to improve photocatalytic $\\mathrm{CO}_{2}$ reduction. Catal. Today https://doi.org/10.1016/j.cattod.2022.05.001 (2022). \n8.\t Ferri, P. et al. Chemical and structural parameter connecting cavity architecture, confined hydrocarbon pool species, and MTO product selectivity in small-pore cage-based zeolites. ACS Catal. 9, 11542–11551 (2019). \n9.\t Ilias, S. & Bhan, A. Mechanism of the catalytic conversion of methanol to hydrocarbons. ACS Catal. 3, 18–31 (2013). \n10.\tTan, L. et al. Bifunctional capsule catalyst of $\\mathrm{\\Al}_{2}\\mathrm{O}_{3}@\\mathrm{Cu}$ with strengthened dehydration reaction field for direct synthesis of dimethyl ether from syngas. Ind. Eng. Chem. Res. 58, 22905–22911 (2019). \n11.\tTan, L. et al. Design of a core–shell catalyst: an effective strategy for suppressing side reactions in syngas for direct selective conversion to light olefins. Chem. Sci. 11, 4097–4105 (2020). \n12.\t Tan, L. et al. Direct $\\mathrm{CO}_{2}$ hydrogenation to light olefins by suppressing CO by-product formation. Fuel Process. Technol. 196, 106174 (2019). \n13.\tMa, S., Huang, S.-D. & Liu, Z.-P. Dynamic coordination of cations and catalytic selectivity on zinc–chromium oxide alloys during syngas conversion. Nat. Catal. 2, 671–677 (2019). \n14.\tBehrens, M. et al. The active site of methanol synthesis over $\\mathrm{Cu}/\\mathrm{ZnO}/\\mathrm{Al}_{2}\\mathrm{O}_{3}$ industrial catalysts. Science 336, 893–897 (2012). \n15.\tBeck, A. et al. Following the structure of copper–zinc–alumina across the pressure gap in carbon dioxide hydrogenation. Nat. Catal. 4, 488–497 (2021). \n16.\t Shi, Z. et al. $\\mathrm{CO}_{2}$ hydrogenation to methanol over Cu–In intermetallic catalysts: effect of reduction temperature. J. Catal. 379, 78–89 (2019). \n17.\t Li, K. & Chen, J. G. $\\mathrm{CO}_{2}$ hydrogenation to methanol over $\\mathrm{ZrO}_{2}.$ -containing catalysts: insights into $\\mathrm{ZrO}_{2}$ induced synergy. ACS Catal. 9, 7840–7861 (2019). \n18.\tSamson, K. et al. Influence of $\\mathrm{ZrO}_{2}$ structure and copper electronic state on activity of $\\mathrm{Cu}/\\mathrm{Zr}\\mathrm{O}_{2}$ catalysts in methanol synthesis from $\\mathrm{CO}_{2}$ . ACS Catal. 4, \n3730–3741 (2014). \n19.\tWu, C. et al. Inverse $\\mathrm{ZrO_{2}/C u}$ as a highly efficient methanol synthesis catalyst from $\\mathrm{CO}_{2}$ hydrogenation. Nat. Commun. 11, 5767 (2020). \n20.\t Bahruji, H. et al. $\\mathrm{Pd}/\\mathrm{ZnO}$ catalysts for direct $\\mathrm{CO}_{2}$ hydrogenation to methanol. J. Catal. 343, 133–146 (2016). \n21.\tWang, J. et al. A highly selective and stable $\\scriptstyle{\\mathrm{ZnO-ZrO}}_{2}$ solid solution catalyst for $\\mathrm{CO}_{2}$ hydrogenation to methanol. Sci. Adv. 3, e1701290 (2017). \n22.\tMartin, O. et al. Indium oxide as a superior catalyst for methanol synthesis by $\\mathrm{CO}_{2}$ hydrogenation. Angew. Chem. Int. Ed. 55, 6261–6265 (2016). \n23.\tWang, J. et al. High-performance $\\mathrm{MaZrO}_{x}$ $\\mathrm{Ma}=\\mathrm{Cd}$ , Ga) solidsolution catalysts for $\\mathrm{CO}_{2}$ hydrogenation to methanol. ACS Catal. 9, \n10253–10259 (2019). \n24.\tSharafutdinov, I. et al. Intermetallic compounds of Ni and Ga as catalysts for the synthesis of methanol. J. Catal. 320, 77–88 (2014). \n25.\tKong, H., Li, H.-Y., Lin, G.-D. & Zhang, H.-B. Pd-decorated CNT-promoted Pd- ${\\mathrm{Ga}}_{2}{\\mathrm{O}}_{3}$ catalyst for hydrogenation of $\\mathrm{CO}_{2}$ to methanol. Catal. Lett. 141, \n886 (2011). \n26.\tBai, S., Shao, Q., Feng, Y., Bu, L. & Huang, X. Highly efficient carbon dioxide hydrogenation to methanol catalyzed by zigzag platinum–cobalt nanowires. Small 13, 1604311 (2017). \n27.\tGraciani, J. et al. Highly active copper–ceria and copper–ceria–titania catalysts for methanol synthesis from $\\mathrm{CO}_{2}$ . Science 345, 546–550 (2014). \n28.\t Yu, J. et al. Stabilizing $\\mathrm{Cu^{+}}$ in $\\mathrm{Cu}/\\mathrm{SiO}_{2}$ catalysts with a shattuckite-like structure boosts $\\mathrm{CO}_{2}$ hydrogenation into methanol. ACS Catal. 10, \n14694–14706 (2020). \n29.\tYang, H. et al. A highly stable copper-based catalyst for clarifying the catalytic roles of ${\\mathrm{Cu}}^{0}$ and $\\mathrm{Cu^{+}}$ species in methanol dehydrogenation. Angew. Chem. Int. Ed. 57, 1836–1840 (2018). Technol. 5, 869 (2015). \n31.\tRong, W. et al. Size-dependent activity and selectivity of atomic-level copper nanoclusters during $\\mathrm{CO/CO}_{2}$ electroreduction. Angew. Chem. Int. Ed. 60, 466–472 (2021). \n32.\tZhu, Y. et al. Copper–zirconia interfaces in UiO-66 enable selective catalytic hydrogenation of $\\mathrm{CO}_{2}$ to methanol. Nat. Commun. 11, 5849 (2020). \n33.\tZhou, H. et al. Engineering the $\\mathrm{Cu/Mo_{2}C T_{\\it x}}$ (MXene) interface to drive $\\mathrm{CO}_{2}$ hydrogenation to methanol. Nat. Catal. 4, 860–871 (2021). \n34.\tTada, S. et al. Design of interfacial sites between Cu and amorphous $\\mathrm{ZrO}_{2}$ dedicated to $\\mathrm{CO}_{2}$ -to-methanol hydrogenation. ACS Catal. 8, 7809–7819 (2018). \n35.\tTada, S. et al. Cu species incorporated into amorphous $\\mathrm{ZrO}_{2}$ with high activity and selectivity in $\\mathrm{CO}_{2}$ -to-methanol hydrogenation. J. Phys. Chem. C. 122, 5430–5442 (2018). \n36.\tMa, Y. et al. Reactivity of a zirconia–copper inverse catalyst for $\\mathrm{CO}_{2}$ hydrogenation. J. Phys. Chem. C. 124, 22158–22172 (2020). \n37.\tQiao, B. et al. Single-atom catalysis of CO oxidation using $\\mathrm{Pt_{1}}/\\mathrm{FeO}_{x}.$ Nat. Chem. 3, 634–641 (2011). \n38.\t Nguyen, L. et al. $\\ensuremath{\\mathrm{Ir}}_{1}Z\\ensuremath{\\mathrm{n}}_{n}$ bimetallic site for efficient production of hydrogen from methanol. ACS Sustain. Chem. Eng. 7, 18793–18800 (2019). \n39.\tTang, Y. et al. Synergy of single-atom $\\mathrm{Ni}_{\\mathrm{1}}$ and $\\mathrm{{Ru}}_{\\mathrm{1}}$ sites on $\\mathrm{CeO}_{2}$ for dry reforming of $\\mathrm{CH}_{4}$ . J. Am. Chem. Soc. 141, 7283–7293 (2019). \n40.\tLi, H. et al. Synergetic interaction between neighbouring platinum monomers in $\\mathrm{CO}_{2}$ hydrogenation. Nat. Nanotechnol. 13, 411–417 (2018). \n41.\tYe, X. et al. Highly selective hydrogenation of $\\mathrm{CO}_{2}$ to ethanol via designed bifunctional $\\mathrm{Ir}_{1}{-}\\mathrm{In}_{2}\\mathrm{O}_{3}$ single-atom catalyst. J. Am. Chem. Soc. 142, 19001–19005 (2020). \n42.\t Han, Z., Tang, C., Wang, J., Li, L. & Li, C. Atomically dispersed $\\mathrm{Pt}_{n}^{+}$ species as highly active sites in $\\mathrm{Pt/In}_{2}\\mathrm{O}_{3}$ catalysts for methanol synthesis from $\\mathrm{CO}_{2}$ hydrogenation. J. Catal. 394, 236–244 (2021). \n43.\tWitoon, T., Chalorngtham, J., Dumrongbunditkul, P., Chareonpanich, M. & Limtrakul, J. $\\mathrm{CO}_{2}$ hydrogenation to methanol over $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalysts: effects of zirconia phases. Chem. Eng. J. 293, 327–336 (2016). \n44.\tChen, C. et al. The significant role of oxygen vacancy in $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalyst for enhancing water–gas-shift performance. Int. J. Hydrog. Energy 39, 317–324 (2014). \n45.\tIkuno, T. et al. Methane oxidation to methanol catalyzed by Cu-oxo clusters stabilized in NU-1000 metal–organic framework. J. Am. Chem. Soc. 139, 10294–10301 (2017). \n46.\tWang, L.-C. et al. Structural evolution and catalytic properties of nanostructured $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalysts prepared by oxalate gel-coprecipitation technique. J. Phys. Chem. C. 111, 16549–16557 (2007). \n47.\tVelu, S., Suzuki, K., Gopinath, C. S., Yoshida, H. & Hattori, T. XPS, XANES and EXAFS investigations of $\\mathrm{CuO/ZnO/Al_{2}O_{3}/Z r O_{2}}$ mixed oxide catalysts. Phys. Chem. Chem. Phys. 4, 1990–1999 (2002). \n48.\t Qian, J. et al. Exploration of ${\\mathrm{CeO}}_{2}$ –CuO quantum dots in situ grown on graphene under hypha assistance for highly efficient solar-driven hydrogen production. Inorg. Chem. 57, 14532–14541 (2018). \n49.\tYuan, L. et al. Dynamic evolution of atomically dispersed Cu species for $\\mathrm{CO}_{2}$ photoreduction to solar fuels. ACS Catal. 9, 4824–4833 (2019). \n50.\t Qiu, X. et al. Hybrid $\\mathrm{Cu}_{x}\\mathrm{O}/\\mathrm{TiO}_{2}$ nanocomposites as risk-reduction materials in indoor environments. ACS Nano 6, 1609–1618 (2012). \n51.\tYang, J. et al. Dynamic behavior of single-atom catalysts in electrocatalysis: identification of $\\mathrm{Cu-N}_{3}$ as an active site for the oxygen reduction reaction. J. Am. Chem. Soc. 143, 14530–14539 (2021). \n52.\tNosaka, Y., Takahashi, S., Sakamoto, H. & Nosaka, A. Y. Reaction mechanism of $\\mathrm{{Cu}(I I)}$ -grafted visible-light responsive $\\mathrm{TiO}_{2}$ and $\\mathrm{WO}_{3}$ photocatalysts studied by means of ESR spectroscopy and chemiluminescence photometry. J. Phys. Chem. C 115, 21283–21290 (2011). \n53.\tChusuei, C. C., Brookshier, M. A. & Goodman, D. W. Correlation of relative X-ray photoelectron spectroscopy shake-up intensity with CuO particle size. Langmuir 15, 2806–2808 (1999). \n54.\t Sato, A. G. et al. Effect of the $\\mathrm{ZrO}_{2}$ phase on the structure and behavior of supported Cu catalysts for ethanol conversion. $J.$ Catal. 307, 1–17 (2013). \n55.\tLamberti, C. et al. XAFS, IR, and UV–vis study of the CuI environment in CuI–ZSM-5. J. Phys. Chem. B 101, 344–360 (1997). \n56.\tZhang, Z. et al. Transfer hydrogenation of fatty acids on $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ demystifying the role of carrier structure and metal–support interface. ACS Catal. 10, 9098–9108 (2020). \n57.\t Cui, G. et al. $\\boldsymbol{Z}\\boldsymbol{\\mathrm{rO}}_{2}{-}\\boldsymbol{x}$ modified Cu nanocatalysts with synergistic catalysis towards carbon–oxygen bond hydrogenation. Appl. Catal. B 280, 119406 (2021). \n58.\t Gao, J. et al. $\\mathrm{{Cu_{2}I n}}$ nanoalloy enhanced performance of $\\mathrm{Cu}/\\mathrm{ZrO}_{2}$ catalysts for the $\\mathrm{CO}_{2}$ hydrogenation to methanol. Ind. Eng. Chem. Res. 59, 12331–12337 (2020). \n59.\tZhang, Z. et al. The most active Cu facet for low-temperature water gas shift reaction. Nat. Commun. 8, 488 (2017). \n60.\t Ladera, R. et al. Catalytic valorization of $\\mathrm{CO}_{2}$ via methanol synthesis with Ga-promoted $\\mathrm{Cu-ZnO-ZrO_{2}}$ catalysts. Appl. Catal. B 142-143, 241–248 (2013). \n61.\tZhang, X. et al. Reaction-driven surface reconstruction of $\\mathrm{ZnAl_{2}O_{4}}$ boosts the methanol selectivity in $\\mathrm{CO}_{2}$ catalytic hydrogenation. Appl. Catal. B 284, 119700 (2021). \n62.\tYan, G. et al. Reaction product-driven restructuring and assisted stabilization of a highly dispersed Rh-on-ceria catalyst. Nat. Catal. 5, 119–127 (2022). \n63.\tDandekar, A. & Vannice, M. A. Determination of the dispersion and surface oxidation states of supported Cu catalysts. J. Catal. 178, 621–639 (1998). \n64.\t Pokrovski, K., Jung, K. T. & Bell, A. T. Investigation of CO and $\\mathrm{CO}_{2}$ adsorption on tetragonal and monoclinic zirconia. Langmuir 17, 4297–4303 (2001). \n65.\tYang, C. et al. Strong electronic oxide–support interaction over $\\mathrm{In}_{2}\\mathrm{O}_{3}/\\mathrm{ZrO}_{2}$ for highly selective $\\mathrm{CO}_{2}$ hydrogenation to methanol. J. Am. Chem. Soc. 142, 19523–19531 (2020). \n66.\tWang, Y. et al. Strong evidence of the role of $\\mathrm{H}_{2}\\mathrm{O}$ in affecting methanol selectivity from $\\mathrm{CO}_{2}$ hydrogenation over $\\mathrm{Cu-ZnO-ZrO_{2}}$ . Chem 6, 419–430 (2020). \n67.\t Li, H. et al. $\\mathrm{CO}_{2}$ activation on ultrathin $\\mathrm{ZrO}_{2}$ film by $\\mathrm{H}_{2}\\mathrm{O}$ co-adsorption: in situ NAP-XPS and IRAS studies. Surf. Sci. 679, 139–146 (2019). \n68.\tRavel, B. & Newville, M. ATHENA, ARTEMIS, HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 12, 537–541 (2005). \n69.\tKresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n70.\tKresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n71.\tBlöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n72.\tPerdew, J. P. & Wang, Y. Accurate and simple analytic representation of the electron-gas correlation energy. Phys. Rev. B 45, 13244–13249 (1992). \n73.\tHuang, S.-D., Shang, C., Kang, P.-L., Zhang, X.-J. & Liu, Z.-P. LASP: fast global potential energy surface exploration. WIREs Comput. Mol. Sci. 9, e1415 (2019). \n74.\tGuan, S.-H., Zhang, K.-X., Shang, C. & Liu, Z.-P. Stability and anion diffusion kinetics of yttria-stabilized zirconia resolved from machine learning global potential energy surface exploration. J. Chem. Phys. 152, 094703 (2020). \n75.\tMa, S., Shang, C., Wang, C.-M. & Liu, Z.-P. Thermodynamic rules for zeolite formation from machine learning based global optimization. Chem. Sci. 11, 10113–10118 (2020). \n76.\tGuan, S.-H., Shang, C., Huang, S.-D. & Liu, Z.-P. Two-stage solid-phase transition of cubic ice to hexagonal ice: structural origin and kinetics. J. Phys. Chem. C 122, 29009–29016 (2018). \n77.\tHuang, S.-D., Shang, C., Zhang, X.-J. & Liu, Z.-P. Material discovery by combining stochastic surface walking global optimization with a neural network. Chem. Sci. 8, 6327–6337 (2017). \n\n78.\tBehler, J. & Parrinello, M. Generalized neural-network representation of high-dimensional potential-energy surfaces. Phys. Rev. Lett. 98, 146401 (2007). \n\n# Acknowledgements \n\nThis work was supported by the National Natural Science Foundation of China under grant numbers 22172032, 21902027, 51701201 and U19B2003, the National Key Research and Development Program of China under grant number 2018YFA0208600, the Natural Science Foundation of Fujian Province under grant numbers 2020J05121 and 2020J01443, and the DNL Cooperation Fund, CAS (DNL201903). The X-ray experiment was supported by BL14W1, Shanghai Synchrotron Radiation Facility (j21sr0041). We thank the staff at the BL14W1 beamline of the Shanghai Synchrotron Radiation Facility and M. Shakouri at the Canadian Light Source for assistance with the EXAFS and XANES measurements. \n\n# Author contributions \n\nL.T. conceived and designed the experiments. H.Z. performed the catalyst synthesis, characterization and performance experiments. Z.L. and S.M. contributed to the DFT calculation and wrote the related section of the manuscript. R.Y., K.X., Y.C., K.J., Y.F., C.Z. and X.L. assisted with the synthesis and performance testing of the catalysts. Y.T. and L.W. helped to analyse the XPS and XAS data. Q.J. conducted the HAADF-STEM experiments. P.H. and Y.W. assisted with the in situ DRIFT experiments. Data were discussed among all coauthors. L.T. and H.Z. wrote the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41929-022-00840-0. \n\nCorrespondence and requests for materials should be addressed to Zhipan Liu or Li Tan. \n\nPeer review information Nature Catalysis thanks Xiaodong Wen, Shohei Tada and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nSpringer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 " + }, + { + "id": "10.1038_s41467-022-30939-8", + "DOI": "10.1038/s41467-022-30939-8", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-30939-8", + "Relative Dir Path": "mds/10.1038_s41467-022-30939-8", + "Article Title": "Lanthanum nitrate as aqueous electrolyte additive for favourable zinc metal electrodeposition", + "Authors": "Zhao, RR; Wang, HF; Du, HR; Yang, Y; Gao, ZH; Qie, L; Huang, YH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Aqueous zinc batteries are appealing devices for cost-effective and environmentally sustainable energy storage. However, the zinc metal deposition at the anode strongly influences the battery cycle life and performance. To circumvent this issue, here we propose the use of lanthanum nitrate (La(NO3)(3)) as supporting salt for aqueous zinc sulfate (ZnSO4) electrolyte solutions. Via physicochemical and electrochemical characterizations, we demonstrate that this peculiar electrolyte formulation weakens the electric double layer repulsive force, thus, favouring dense metallic zinc deposits and regulating the charge distribution at the zinc metal|electrolyte interface. When tested in Zn||VS2 full coin cell configuration (with cathode mass loading of 16 mg cm(-2)), the electrolyte solution containing the lanthanum ions enables almost 1000 cycles at 1 A g(-1) (after 5 activation cycles at 0.05 A g(-1)) with a stable discharge capacity of about 90 mAh g(-1) and an average cell discharge voltage of similar to 0.54 V. Zinc metal is a promising anode material for aqueous secondary batteries. However, the unfavourable morphologies formed on the electrode surface during cycling limit its application. Here, the authors report the tailoring of the surface morphology using a lanthanum nitrate aqueous electrolyte additive.", + "Times Cited, WoS Core": 339, + "Times Cited, All Databases": 346, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000808000200007", + "Markdown": "# Lanthanum nitrate as aqueous electrolyte additive for favourable zinc metal electrodeposition \n\nRuirui Zhao1, Haifeng Wang1, Haoran ${\\sf D}{\\sf u}^{1}$ , Ying Yang1, Zhonghui Gao1, Long Qie1,2✉ & Yunhui Huang 2✉ \n\nAqueous zinc batteries are appealing devices for cost-effective and environmentally sustainable energy storage. However, the zinc metal deposition at the anode strongly influences the battery cycle life and performance. To circumvent this issue, here we propose the use of lanthanum nitrate $(\\mathsf{L a}(\\mathsf{N O}_{3})_{3})$ as supporting salt for aqueous zinc sulfate $(Z n S O_{4})$ electrolyte solutions. Via physicochemical and electrochemical characterizations, we demonstrate that this peculiar electrolyte formulation weakens the electric double layer repulsive force, thus, favouring dense metallic zinc deposits and regulating the charge distribution at the zinc metal|electrolyte interface. When tested in $Z\\mathsf{n}||\\mathsf{V}\\mathsf{S}_{2}$ full coin cell configuration (with cathode mass loading of $16\\mathrm{mg}\\mathrm{cm}^{-2}.$ ), the electrolyte solution containing the lanthanum ions enables almost 1000 cycles at ${1\\o\\mathsf{A}\\mathsf{g}^{-1}}$ (after 5 activation cycles at $0.05\\mathsf{A g}^{-1};$ ) with a stable discharge capacity of about $90\\mathsf{m A h}\\mathsf{g}^{-1}$ and an average cell discharge voltage of ${\\sim}0.54\\lor$ . \n\nD $Z_{\\mathrm{n-MnO}_{2}}$ 2 $\\mathbf{Z}\\mathbf{n}{\\cdot}\\mathbf{B}\\mathbf{r}_{2},$ geasnod $Z\\mathrm{n}$ -ueAoirusb $Z\\mathrm{n}$ -rbiaes)e,d nbcaltutedriinesg (hei.g .h, safety, low cost, and nontoxicity, the sustained chemical corrosion (the corrosion caused by the side-reactions between $Z\\mathrm{n}$ metal and aqueous electrolytes) and low reversibility of $Z\\mathrm{n}$ electrodes encumber their practical applications1–4. In aqueous electrolytes, the electrodeposition of hexagonal close-packed $Z\\mathrm{n}$ metal has a strong propensity to form hexagonal platelets, which generates porous $Z\\mathrm{n}$ depositions with irregular morphologies5–7. Such a porous structure is bound to exacerbate the chemical corrosion during the repeated plating and stripping of the Znmetal phase due to the increased exposure of Zn electrodes to the electrolytes. The loose Zn particles with irregular morphology also cause the loss of electrical contact between the deposits and substrates and further deteriorates the reversibility of Zn electrodes4. What is worse, the dendritic Zn particles with irregular morphology may easily pierce the separator and lead to short circuits of batteries8. \n\nTo induce uniform Zn deposition, several strategies have been proposed: (1) constructing artificial interface layers to restrict the Zn crystal growth and protect the Zn metal electrode from detrimental reactions with the aqueous electrolyte9–11; (2) using substrates with a low lattice mismatch and low affinity to lock the crystal orientation for the uniform Zn electrodeposition8,12; (3) increasing the driving force for the nucleation of $Z\\mathrm{n}$ deposits to induce the uniform distribution of $Z\\mathrm{n}$ -metal nuclei13. However, most of the above approaches rely on the modification of the Zn electrodes or current collectors, which decrease the overall energy density of the cells14–16. Besides, the long-term cycling of $Z\\mathrm{n}$ electrodes under conditions of high depth of discharge (DOD) and/or high areal capacity of Zn remains challenging3,4. It is highly desired to explore new solutions to enable high effective $Z\\mathrm{n}$ deposition without sacrificing the energy density. \n\nThe morphology of the deposited Zn directly affects the reversibility of Zn electrodes and the lifespan of $Z\\mathrm{n}$ -based batteries17–19. It is acknowledged that the morphology of the deposited Zn is related to multiple factors, including the intrinsic crystal anisotropy, electrolytes, substrate chemistry and geometry8,13,20–22 The process of $Z\\mathrm{n}$ electrodeposition includes the desolvation and reduction of the $Z\\mathrm{n}^{2+}$ ions, and the following formation and growth of the nucleus on conductive substrates. The final morphology of deposited metal is related to both the structure of as-formed grain crystals, which are observed as irregular hexagonal flakes for $Z\\mathrm{n}$ , and the interactions between them23. Based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, the interactions between Zn deposits in aqueous electrolytes are mainly related to the van der Waals (VDW) attractive force and the electrostatic repulsion due to the electric double layer (EDL) of counterions (Supplementary Figs. 1, 2 and Supplementary Notes 1, 2)24–26. In $\\mathrm{ZnSO_{4}}$ electrolyte, the Zn tends to electrodeposit as scattered and loose platelets, indicating a repulsive-force-governed $Z\\mathrm{n}$ deposition process. To induce dense and compact $Z\\mathrm{n}$ coherent electrodeposition, we need to regulate the interactions between the $Z\\mathrm{n}$ deposits from repulsion to attraction. As the VDW force, which depends mainly on the distance between the particles, could be considered as fixed for the Zn deposits and is difficult to be manipulated, thus the possible solution is to weaken the EDL repulsion force between the Zn deposits. \n\nBased on the Poisson-Boltzmann (PB) model, the EDL repulsive force between the negatively-charged surfaces of $Z\\mathrm{n}$ deposits is mainly influenced by the thickness of the EDL, which is known as the Debye length $(\\dot{1}/\\kappa)^{27}$ . Theoretically, by reducing the Debye length, the EDL repulsion force between two charged particles could be reduced. Here, we introduce $\\mathrm{La}^{3+}$ ions, which serve as high-valence competitive ions to decrease the Debye length28–33, to the aqueous $\\mathrm{ZnSO_{4}}$ electrolytes. The electrochemical and morphology characterizations confirmed the presence of the insert $\\mathrm{La}^{3\\dagger}$ ions weakens EDL repulsive force between the $Z\\mathrm{n}$ deposits, changes the preferred orientation of $Z\\mathrm{n}$ deposits, and results in dense and compact Zn coherent electrodeposition. With $\\mathrm{La}^{3+}$ -modified electrolyte, the corrosion rate (the speed of corrosion loss) of $Z\\mathrm{n}$ electrodes is significantly relieved with the corrosion current (the current produced in an electrochemical cell while corrosion is occurring) decreased from 421.6 to $6.3\\upmu\\mathrm{Acm}^{-2},34$ enabling a high average Coulombic efficiency $\\mathrm{\\Phi}\\mathrm{\\Phi}\\mathrm{\\left.\\mathrm{f}\\right>}99.9\\%$ for 2100 plating/stripping cycles. At a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ and $\\mathrm{\\DOD}_{\\mathrm{Zn}}$ of $80\\%$ , the $Z\\mathrm{n}||Z\\mathrm{n}$ cell with the modified electrolyte exhibited a stable $Z\\mathrm{n}$ deposition for $\\sim160\\mathrm{h}$ . Benefitting from the stale $Z\\mathrm{n}$ anodes, the $\\mathrm{Zn}||\\mathrm{VS}_{2}$ cell in $\\mathrm{La}^{3+}$ - modified electrolyte with a limited $Z\\mathrm{n}$ supply $\\mathrm{11.6\\mAh}$ $c\\mathrm{m}^{-2})$ and a high-loading $\\mathrm{VS}_{2}$ cathode ( $\\mathrm{16.0\\mg\\cm^{-2}},$ delivers a stable discharge capacity of about $90\\mathrm{mAh}\\ \\mathrm{g}^{-1}$ and an average cell discharge voltage of ${\\sim}0.54\\mathrm{V}$ . The as-proposed strategy demonstrates the importance of the thickness of EDL on the electrodeposition behaviors of $Z\\mathrm{n}^{2+}$ ions and might also be applicable for other metal anodes. \n\n# Results \n\nElectrochemical characterization of zinc metal electrode with $\\mathbf{L}\\mathbf{a}^{3+}$ -containing aqueous electrolyte solution. The $\\mathrm{La}^{3+}$ -modified electrolyte $\\mathrm{\\bar{(La^{3+}}}.\\mathrm{ZS)}$ was prepared by dissolving $\\mathrm{La}(\\mathrm{NO}_{3})_{3}$ into $\\mathrm{ZnSO_{4}}$ solution (ZS), a common electrolyte for aqueous $Z\\mathrm{n}$ -ion batteries. To verify the effects of $\\mathrm{La}^{3+}$ on $Z\\dot{\\bf n}$ deposition, we firstly compared the plating/stripping performance of $\\mathrm{\\bar{Z}n}||\\mathrm{Zn}$ cells in ZS and $\\mathbf{\\dot{L}a}^{3+}$ -ZS electrolytes with a current density of $\\mathrm{i}\\mathrm{mA}\\mathrm{cm}^{-2}$ and an areal capacity of $\\mathrm{i}^{\\cdot}\\mathrm{mAh}\\mathrm{cm}^{-2}$ (Fig. 1a). The $Z\\mathrm{n}||Z\\mathrm{n}$ cell with ZS electrolyte shows a decreasing voltage hysteresis (the voltage difference between the middle of the plating and stripping curves) during the first $50\\mathrm{h}$ . However, the stabilized voltage drops suddenly after ${\\sim}320\\mathrm{h},$ indicating the failure of the cell. In comparison, the $Z\\mathrm{n}||Z\\mathrm{n}$ cell with $\\mathrm{La}^{3+}$ -ZS electrolyte exhibits stable voltage profiles $>1200\\mathrm{h}$ with a negligible potential fluctuation. The voltage hysteresis remains $<100\\mathrm{mV}$ during cycling. Similar results are also observed at a lower current density of $0.5\\mathrm{\\mA}\\mathrm{cm}^{-2}$ , where the $\\mathrm{\\DeltaZn||}$ Zn cell with $\\mathrm{La}^{3+}$ -ZS electrolyte is cycled for more than $1800\\mathrm{h}.$ much longer than the one in ZS electrolyte ${\\sim}440\\mathrm{h}$ , Supplementary Fig. 3). \n\nTo figure out how the $\\mathrm{La}^{3+}$ -ZS electrolyte affects the Zn electrodeposition, we disassembled the cycled $Z\\mathrm{n}||Z\\mathrm{n}$ cells (after 100 cycles with a current density of $1\\mathrm{\\mA}\\mathrm{cm}^{-2}$ and an areal capacity of $1\\mathrm{mAh}\\mathrm{cm}^{-2}.$ ) and analyzed the morphology of the cycled Zn electrodes by a scanning electron microscopy (SEM). As the result shown in Fig. 1b, the cycled $Z\\mathrm{n}$ electrode in ZS electrolyte shows a porous $Z\\mathrm{n}$ layered structure with irregular morphology which could lead to cell failure upon prolonged cycling5. In addition, this structure also leads to more side reactions between the Zn electrode and electrolyte due to the exposed surface, and thus more by-products accumulation. In comparison, after being cycled under a same test condition, the Zn electrode with $\\mathrm{La}^{3\\mp}{-}\\dot{\\mathrm{ZS}}$ electrolyte displays a dense surface with the deposited $Z\\mathrm{n}$ particles closely connected with each other (Fig. 1c). Figure 1d displays the cross-sectional SEM image of the cycled Zn electrodes in ZS electrolyte, where the $Z\\mathrm{n}$ electrode is depleted with $12\\ \\upmu\\mathrm{m}$ in thickness of $Z\\mathrm{n}$ foil left, indicating the formation of the large amounts of electronically-disconnected (i.e., “dead”) $Z\\mathrm{n}$ and by-products35,36. In contrast, the cycled $Z\\mathrm{n}$ electrode in $\\mathrm{La}^{3+}$ -ZS electrolyte shows a dense $Z\\mathrm{n}$ -deposition layer with ${\\sim}74\\upmu\\mathrm{m}Z\\mathrm{n}$ foil left (Fig. 1e). Considering the thickness of the fresh $Z\\mathrm{n}$ electrode used is $80\\upmu\\mathrm{m}$ , the use of $\\mathrm{La}^{3+}$ -ZS electrolyte reduces the $Z\\mathrm{n}$ consumption by $91\\%$ compared with the one in ZS electrolyte. The SEM results demonstrate that the introduction of $\\mathrm{La}(\\mathrm{NO}_{3})_{3}$ into the ZS electrolyte induces dense Zn electrodeposition and enhances the utilization of $Z\\mathrm{n}$ foil. \n\n![](images/5ec8428e6c5d562af28f3bb857ba4c2d8c46de6f5313cbf86d54fd2cf7da8934.jpg) \nFig. 1 The plating/stripping behaviors for Zn electrodes in ZS and $\\pmb{\\lfloor\\alpha^{3+}}$ -ZS electrolytes. a Cycling performance of the $Z n\\vert\\vert Z n$ cells with a current density of $1\\mathsf{m A c m}^{-2}$ and an areal capacity of $1\\mathsf{m A h c m}^{-2}$ ; the top and cross-sectional SEM images of the $Z n$ electrodes for $Z n\\vert\\vert Z n$ cells in (b, d) ZS and $(\\pmb{\\mathscr{e}}_{\\pmb{r}}\\pmb{\\mathscr{e}})$ $\\mathsf{L a}^{3+}\\ –\\mathsf{Z S}$ electrolytes after 100 cycles under a current density of $1\\mathsf{m A c m}^{-2}$ for 1 h. f Cycling performance of the $Z n\\vert\\vert Z n$ cells with a limited $Z n$ supply $(\\mathsf{D O D}_{Z\\mathsf{n}}=80\\%)$ , a current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ , and an areal capacity of $5.93\\:\\mathrm{mAh}\\:\\mathrm{cm}^{-2}$ . $\\pmb{\\mathsf{g}}$ The selected enlarged voltage profiles of (f). h CE of the $Z_{\\mathsf{n}||}$ Ti cells with a current density of $2{\\mathsf{m A}}{\\mathsf{c m}}^{-2}$ and a cut-off charging voltage of $0.4\\mathsf{V}$ . \n\nFor practical applications, the depth of discharge of the Zn electrodes $\\mathrm{(DOD_{Zn})}$ significantly affects the cycling life and the overall specific energy of the full $\\mathrm{cell}^{3,4}$ . The plating/stripping performance of the symmetrical $Z\\mathrm{n}||Z\\mathrm{n}$ cells under different $\\mathrm{\\DeltaDOD}_{\\mathrm{Zn}}$ was tested using thin $Z\\mathrm{n}$ electrodes $(13\\upmu\\mathrm{m},7.40\\mathrm{mAh\\cm}^{-2})$ with ZS and $\\mathrm{La}^{3+}\\ –\\Zs$ electrolyte. Figure 1f displays the results of the cells under a condition of $\\mathrm{DOD}_{\\mathrm{Zn}}=80\\%$ $\\mathrm{\\bar{(10mAcm^{-2}}}$ , $5.93\\mathrm{mAh}$ $\\mathrm{cm}^{-2},$ ). Under such a high $\\mathrm{DOD}_{\\mathrm{Zn}}$ , the control $Z\\mathrm{n}||Z\\mathrm{n}$ cell with ZS electrolyte showed a sharp voltage increase at the end of the initial stripping/plating process and failed after $^{3\\mathrm{h}}$ of cycling (Fig. 1g). When $\\bar{\\mathrm{La}^{3+}}$ -ZS electrolyte was employed, the cell exhibited stable voltage profiles $>140\\mathrm{h}$ with a voltage hysteresis of ${\\sim}100\\mathrm{mV}$ . When the current density was lowered to $\\mathrm{{i}}\\mathrm{{m}}\\mathrm{{\\dot{A}}}\\mathrm{{cm}}^{-2}$ , the $Z\\mathrm{n}||Z\\mathrm{n}$ cell with $\\mathrm{La}^{3+}$ -ZS electrolyte delivered a stable cycling life for $>~450\\mathrm{h}$ (Supplementary Fig. 4), much longer than that with ZS electrolyte. The performance of the symmetric cells with the $\\mathrm{La}^{3+}$ -ZS electrolyte are well-positioned when compared with the state-of-the-art literature of aqueous zinc metal lab-scale cells (see Supplementary Table 1). \n\nWe further investigated the reversibility of Zn electrodes in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes with asymmetric $\\mathrm{\\DeltaZn||Ti}$ cells by plating \n\n$1\\mathrm{mAh}\\mathrm{cm}^{-2}$ of $Z\\mathrm{n}$ onto the Ti foil at a current density of $2\\operatorname{mA}\\operatorname{cm}^{-2}$ and then stripping to $0.4\\mathrm{V}$ . Figure 1h shows the Coulombic efficiency (CE) of both cells. The control cell with ZS electrolyte failed after $<\\ 400$ plating/stripping cycles with fluctuation of the CE noticed at the end of cycle life, indicating the poor reversibility of $Z\\mathrm{n}$ in ZS electrolyte. While when $\\mathrm{La}^{3+}$ - ZS electrolyte was used, the cell delivered 2100 plating/stripping cycles with an average CE of $99.9\\%^{37,38}$ . The flat stripping/plating voltage profiles for $\\mathrm{\\bar{Z}n\\vert\\vert T i}$ cell with $\\mathrm{La}^{3+}$ -ZS electrolyte, and the surge of charge capacity at the $400^{\\mathrm{th}}$ cycle for the one with ZS electrolyte support the claim of the stability of Zn electrodes in $\\mathrm{La}^{3+}$ -ZS electrolyte (Supplementary Fig. 5). Similar results are also obtained when the Ti-foil electrodes were replaced by carbon papers (Supplementary Fig. 6). Even under current densities of $\\mathrm{\\i}0\\mathrm{\\mA\\cm}^{-2}$ and $20\\mathrm{\\dot{m}A}\\mathrm{\\dot{c}m}^{-2}$ , the $Z\\mathrm{n}$ electrodes in $\\mathrm{La}^{3+}$ -ZS electrolyte also demonstrated better reversibility than those of the control cells (Supplementary Figs. 7 and 8). \n\nEx situ morphological and structural analyses of the zinc metal depositions. It is known that the Zn deposits in ZS electrolyte tend to exhibit a hexagonal-platelet morphology due to the lower thermodynamic free energy of the exposed (002) plane8. To investigate how the $\\mathrm{La}^{3+}\\ –\\dot{Z}S$ electrolyte affects the electrodeposition behavior of $Z\\mathrm{n}.$ , we checked the morphology for Zn deposits in ZS and $\\mathrm{La}^{3+}{-}\\mathrm{ZS}$ electrolytes at different current densities with a fixed deposition amount of $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ . As the ex situ SEM images shown in Fig. 2a–d, the Zn deposits obtained in ZS electrolyte are built with hexagonal platelets, and the thickness of the platelets increases gradually with the increase of the current densities. However, even when the current density was increased to $20\\mathrm{mA}\\mathrm{cm}^{-2}$ , the as-deposited platelets remained scattered. Such loose and separate structures are resulted from the strong repulsion force between the $Z\\mathrm{n}$ deposits, which prevents the consolidation of the platelets. The $Z_{\\bar{\\mathrm{{n}}}}$ deposits show dense and compact morphologies in $\\mathrm{La}^{3+}$ -ZS electrolyte at all the current densities from 1 to $20\\mathrm{mA}\\mathrm{cm}^{-2}$ (Fig. 2e–h). Here, the porous structures observed may origin from the nonuniform distribution of the $Z\\mathrm{n}$ nucleation on the substrate. The highmagnification SEM image for $Z\\mathrm{n}$ deposits at a current density of $1\\mathrm{mA}\\mathrm{cm}^{-2}$ displays that the compact $Z\\mathrm{n}$ deposits are piled with Zn platelets (Fig. 2i), the decreased presence of the porous structures between the $Z\\mathrm{n}$ platelets reveals that the interactions between the $Z\\mathrm{n}$ deposits have been successfully regulated from repulsion to attraction by adding $\\mathrm{La}(\\mathrm{NO}_{3})_{3}$ into ZS electrolyte. \n\n![](images/601eb1bc699c991311a54b6c76429f7e3401a796e1552592f1fa756fc170e83c.jpg) \nFig. 2 The morphology analysis of Zn deposits. The SEM images of $Z n$ deposits from the $Z n$ electrodes of $Z n\\vert\\vert Z n$ cells with a fixed areal capacity of $1\\mathsf{m A h c m}^{-2}$ and different current densities from 1 to $20\\mathsf{m A c m}^{-2}$ in $(\\mathsf{a}\\cdot\\mathsf{d})$ ZS and $(e\\cdot h)$ $\\mathsf{L a}^{3+}\\ –\\mathsf{Z S}$ electrolytes. i The high-magnification SEM image of the Zn electrode for a $Z n\\vert\\vert Z n$ cell in $\\mathsf{L}a^{3+}\\ –\\mathsf{Z}\\mathsf{S}$ electrolyte after 10 cycles under a current density of $1\\mathsf{m A c m}^{-2}$ for 1 h. j GIXRD patterns of $Z n$ deposits from the Zn electrodes of a $Z n\\vert\\vert Z n$ cell under a current density of $1\\mathsf{m A c m}^{-2}$ for 1 h showing the reduced (002) planes in $\\mathsf{L a}^{3+\\_Z\\mathsf{S}}$ electrolyte. $\\pmb{\\mathrm{k}}$ The illustration of the hexagonal close packed (hcp) structure of $Z n$ . \n\nThe structure of the Zn deposits obtained from ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes was further characterized by grazing incidence X-ray diffraction (GIXRD), a powerful tool to investigate the texturing and orientation anisotropy of thin film. As the result shown in Fig. 2j, the $Z\\mathrm{n}$ deposits obtained in $\\mathrm{La}^{3+}$ -ZS electrolyte display a relatively weaker (002) peak. Quantitatively, the relative intensity ratio of peak (002) $\\left(\\mathrm{I}_{(002)}\\right)$ to that of peak (100) $\\left(\\mathrm{I}_{\\left(100\\right)}\\right)$ decreases from 1.4 to 0.92, indicating that the reduced (002) planes for the $Z\\mathrm{n}$ deposits in $\\mathrm{La}^{3+}$ -ZS electrolyte. Considering the hcp structure of $Z\\mathrm{n}$ (Fig. 2k) and reduced (002) plane of the Zn deposits obtained from $\\mathrm{La}^{3+}$ -ZS electrolyte, it is safe to conclude that the as-obtained $Z\\mathrm{n}$ deposits are piled up along the c axis, which could be regarded as a coherent deposition5,39. \n\nPhysicochemical investigation on the role of charges for the zinc metal deposition process. To distinguish the function of $\\mathrm{La}(\\mathrm{NO}_{3})_{3}$ additive, we prepared another control electrolyte (marked as $\\mathrm{NO_{3}}^{-}{^{-}\\mathrm{-}}Z\\mathrm{S})$ , which has the same $\\mathrm{NO}_{3}{}^{-}$ concentration as that of the $\\mathrm{La}^{3+}$ -ZS electrolyte $(0.0255\\mathrm{m})$ , by adding $\\mathrm{Zn}(\\mathrm{NO}_{3})_{2}$ to the ZS electrolyte. The cycling stability of the $\\mathrm{Zn|\\bar{\\l}}$ Zn cells with ZS, $\\mathrm{La}^{3+}$ -ZS, and $\\mathrm{NO_{3}}^{-}{^{-}\\mathrm{ZS}}$ electrolytes was compared with a current density of $1\\mathrm{mA}\\mathrm{cm}^{-2}$ and an areal capacity of $1\\mathrm{mAh}\\mathrm{cm}^{-2}$ (Supplementary Fig. 9). The cell with $\\mathrm{NO}_{3}{}^{-}$ -ZS electrolyte failed after $\\sim550$ cycles, longer than the control cell, but only less than half of the one using $\\mathrm{La}^{3+}$ -ZS electrolyte $(>1200$ cycles). Such results imply that the improved cycling stability of the $Z\\mathrm{n}$ electrodes in $\\dot{\\mathrm{La}^{3+}}$ -ZS electrolyte is mainly attributed to the $\\mathrm{La}^{3+}$ ions. To determine how the $\\mathrm{La}^{3+}$ ions affect the Zn plating/stripping behaviors, we further investigated the cycled Zn electrodes in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes with energy-dispersive $\\mathrm{\\DeltaX}$ -ray spectroscopy (EDS). The corresponding SEM images are shown in Supplementary Fig. 10 and the selected regions of the Zn electrodes can represent the electrodes cycled in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes. As the results shown in Fig. 3a, b, only the signals belonging to C, S, O, and Zn elements are detected for both samples. The absence of the La in the cycled $Z\\mathrm{n}$ electrode with $\\mathrm{La}^{3\\dagger}$ -ZS electrolyte suggests that the $\\mathrm{Li}^{3+}$ ions in $\\mathrm{La}^{3+}$ -ZS electrolyte are not reduced or involved in the formation of the by-products. The inert nature of $\\mathrm{La}^{3+}$ ions guarantees the durability of the $\\mathrm{La}^{3+}$ -ZS electrolyte during long-term cycling. Here, the similar CPS amounts (in Fig. 3a, b) for $Z\\mathrm{n}$ , O, S elements of the cycled Zn electrode only imply the similar chemical composition for the passivation layer of the cycled Zn electrodes in ZS and $\\mathrm{La}^{3+}\\mathrm{-}\\mathrm{ZS}$ electrolytes. Actually, the XRD patterns of cycled Zn electrodes confirmed the formation of the by-products is hindered in $\\mathrm{La}^{3+}{-}\\mathrm{ZS}$ electrolyte compared with the ones in ZS electrolyte (Supplementary Fig. 11). \n\n![](images/deb8e6a6acf8d5fd3397556efb0a44e8598c32e3cded1c27c3d10d8c30cc779e.jpg) \nFig. 3 The role of the $\\pmb{\\lfloor\\alpha^{3+}}$ -modified electrolyte on Zn deposition. EDS of the Zn electrodes disassembled from the $Z n\\vert\\vert Z n$ cells after 100 cycles at a current density of $1\\mathsf{m A c m}^{-2}$ for $1\\mathfrak{h}$ in (a) ZS and (b) $\\mathsf{L}\\mathsf{a}^{3+}$ -ZS electrolytes. c Chronoamperogram (CA) of the Zn electrodes of a $Z n\\vert\\vert Z n$ beaker cell with an $\\mathsf{A g/A g C l}$ reference electrode in ZS or $\\mathsf{L a}^{3+}\\ –\\mathsf{Z S}$ electrolytes at an overpotential of $-200\\mathsf{m V}$ d Cyclic voltammograms (CV) of $Z\\mathsf{n}||\\mathsf{T i}$ cells in ZS and $\\mathsf{L a}^{3+}\\ –\\mathsf{Z S}$ electrolytes. e The statistical Zeta potentials of Zn depositions (we disassembled the $Z\\mathsf{n}||\\mathsf{T i}$ cell after discharging $1h$ at the current density of $1\\mathsf{m A c m}^{-2}$ , took out the Ti electrode, and collected the deposited $Z n$ metal on the Ti electrode.) in ZS and $\\mathsf{L}a^{3+}\\ –\\mathsf{Z S}$ electrolytes. f Linear polarization curves of the fresh Zn electrodes (the commercial $Z n$ foils delivering the same surface condition and effective surface area) collected with a scanning rate of $0.1\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in ZS and $\\mathsf{L a}^{3+}\\ –\\mathsf{Z S}$ electrolytes using a three-electrode cell. The three-electrode cell was constructed using the fresh Zn electrode as the working electrode, Pt wire as the counter electrode, and $\\mathsf{A g/A g C l}$ electrode as the reference electrode. \n\nThe Zn deposits growth mechanism in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes was further investigated by Chronoamperometry (CA) in a three-electrode cell set-up, where the working electrode and the counter electrode both are $Z\\mathrm{n}$ foils, and the reference electrode is an $\\mathrm{\\Ag/AgCl}$ electrode (Supplementary Fig. 12). CA is an electrochemical method characterizing the concentration change of electroactive species in the vicinity of the surface40. The current response, which is determined by the nucleation centers41–43, is recorded vs. time of the $Z\\mathrm{n}||Z\\mathrm{n}$ cells with ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes at an overpotential of $-200\\mathrm{mV}$ for a deposition time of $180s$ is provided in Fig. 3c. In ZS electrolyte, the current density reaches its steady value $(\\sim-26\\mathrm{mAcm}^{-2})$ soon after the overpotential was applied, implying the activation of all the nucleation sites. In contrast, the current density for the cell with $\\mathrm{La}^{3+}$ -ZS electrolyte is characterized by prolonged activation time, indicating that the number of nuclei increases gradually with time and the progressive nucleation is governing during $Z\\mathrm{n}$ deposition in $\\mathrm{La}^{3+}$ -ZS electrolyte40,42. It is also noticed that the steady current density in ZS electrolyte $(\\sim-26\\mathrm{mAcm}^{-2})$ is higher than that in $\\mathrm{La}^{3+}$ -ZS electrolyte $(\\sim-22\\mathrm{mA}\\mathrm{cm}^{-2})$ . The differences in the nucleation mechanisms and steady current densities could be ascribed to the adsorption of the $\\mathrm{La}^{3+}$ ions on the surface of the Zn electrodes, which decrease the number of the active nucleation sites and slow down the formation of the nuclei in $\\mathrm{La}^{3+}$ -ZS electrolyte. \n\nThe adsorption of metal ions on an electrode is typically regarded as a monolayer-adsorption process44–48. According to the Langmuir isotherm, the relationship between the equilibrium coverage $\\mathbf{\\eta}(\\theta)$ and the concentration $(c)$ of the adsorbents in the bulk solution follows Eq. (1): \n\n$$\n\\theta=\\frac{c K}{1+c K}\n$$ \n\nWhere $K$ is the equilibrium constant and depends only on the electrode potential and temperature. As the concentration of $\\mathrm{La}(\\mathrm{NO}_{3})_{3}$ in $\\mathrm{La}^{3+}$ -ZS electrolyte is only $0.0085\\mathrm{m}$ , much less than that of $\\mathrm{ZnSO_{4}}$ ( $(2\\mathrm{m})$ , the equilibrium adsorbent coverage $\\theta$ could be regarded as the same for the $Z\\mathrm{n}$ electrodes in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes, which means the current density $(j)$ of the CA curves is proportional to the number of the adsorbed $\\dot{Z}\\mathrm{n}^{2+}$ ions. In other words, the lower current density signifies less $Z\\mathrm{n}^{2+}$ ions are adsorbed on the electrode in $\\mathrm{La}^{\\dot{3}+}\\ –\\mathrm{ZS}$ electrolyte, which is the result of the completive adsorption of inert $\\mathrm{La}^{3+}$ ions. Besides, the $Z\\mathrm{n}$ nucleation in $\\mathrm{La}^{3+}$ -ZS electrolyte shows larger polarization voltage than that in ZS electrolyte $(|\\mathrm{PP}^{\\prime}|=94~\\mathrm{m}\\bar{\\mathrm{V}}$ , Fig. 3d), also reflecting the competitive adsorption between $Z\\mathrm{n}^{2+}$ and $\\mathrm{La}^{3+}$ ions in $\\bar{\\mathrm{La}}^{3+}$ -ZS electrolyte. \n\nTo analyze the net charge of the Zn deposits in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes, we disassembled the $\\mathrm{\\DeltaZn||Ti}$ cell after discharging $^{\\textrm{1h}}$ at the current density of $1\\mathrm{mA}\\mathrm{cm}^{-2}$ , collected the deposited $Z\\mathrm{n}$ metal from the Ti electrode, and checked the Zeta potentials of the deposited Zn metal. As the results shown in Fig. 3e, the deposited Zn flakes obtained from ZS electrolyte show a Zeta potential of $\\mathrm{\\sim-4.4mV}$ , indicating that the Zn deposits are negatively charged. These negatively charged $Z\\mathrm{n}$ flakes repel with each other, leading to the porous $Z\\mathrm{n}$ deposits in ZS electrolyte. In comparison, a Zeta potential of the Zn deposits obtained from $\\mathrm{La}^{3+}$ -ZS electrolyte is only $\\mathrm{\\sim-0.7mV}$ , implying fewer net charges on the surface of $Z\\mathrm{n}$ flakes. The reduced net charges are attributed to that high-valence $\\mathrm{La}^{3+}$ ions into ZS electrolyte decrease the Stern potential of $Z\\mathrm{n}$ deposits faster than $Z\\mathrm{n}^{2+}$ ions30,33, which means shorter distance is needed to reach same stern potential and Zeta potential, indicating the EDL is compressed with $\\mathrm{La}^{3+}$ ions (Supplementary Fig. 13 and Supplementary Note 3). Fewer net charges on the surface of $Z\\mathrm{n}$ deposits lead to a reduced EDL force between Zn deposits. Based on the DLVO theory, the interaction between the $Z\\mathrm{n}$ deposits is determined by the EDL repulsion and the VDW attraction23. With the reduced EDL force between Zn deposits in $\\mathrm{La}^{3+}$ -ZS electrolyte, the VDW attraction becomes prominent, and the deposited Zn metal tend to agglomerate along the (002) plane (Supplementary Fig. 14 and Supplementary Note 4), leading to the formation of the dense and stacked Zn deposits. \n\n![](images/6215003089ee6dc507f9e2550c98f67db2f645545bb9f7d0dea68ad307690579.jpg) \nFig. 4 The illustrations of the coherent electrodeposition induced by a compressed electric double layer of Zn particles. The comparison of the electric double layer of the $Z n$ deposits in (a) ZS and (b) $\\mathsf{L a}^{3+}\\ –\\mathsf{Z S}$ electrolytes; the as-proposed growth models of the $Z n$ deposits in (c) ZS and (d) $\\mathsf{L a}^{3+\\_Z\\mathsf{S}}$ electrolytes. \n\nThe introduction of $\\mathrm{La}^{3+}$ into ZS electrolyte also suppresses the parasitic reaction between electrolytes and Zn electrodes. As the linear polarization curves of the fresh $Z\\mathrm{n}$ electrodes in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes shown in Fig. 3f. Compared with that of the $Z\\mathrm{n}$ electrodes in ZS electrolyte, the corrosion potential (the characteristic or property of metal and nonmetal surfaces to lose electrons in the presence of an electrolyte) of the $Z\\mathrm{n}$ electrode in $\\mathrm{La}^{3+}$ -ZS electrolyte increases from $-996.4$ to $-957.9\\mathrm{mV}$ (vs. $\\mathrm{Ag/}$ $\\mathrm{AgCl})^{34}$ , implying a lower tendency of corrosion of Zn electrodes. In addition, the corrosion current $\\left(\\mathrm{I}_{\\mathrm{corr}}\\right)$ of $Z\\mathrm{n}$ electrodes is reduced from $421.6\\upmu\\mathrm{A}\\mathrm{cm}^{-2}$ in ZS electrolyte to $6.3\\upmu\\mathrm{Acm}^{-2}$ in $\\mathrm{La}^{3+}$ -ZS electrolyte, implying that the corrosion was inhibited by $98\\%$ with the addition of $\\mathrm{La}^{\\breve{3}+}$ based on the Eq. $(2)^{49}$ . \n\nBased on the above discussion, we illustrate the schemes of $Z\\mathrm{n}$ coherent electrodeposition induced by the compressed electric double layer of $Z\\mathrm{n}$ deposits. As shown in Fig. 4a, b, the $Z\\mathrm{n}$ electrode is negatively charged during electrodeposition, delivering a potential of $\\Psi_{0}$ . According to the electric double layer theory, positive $Z\\mathrm{n}^{2+}$ ions are absorbed onto the Zn electrode. Thereby, the potential of the surface of $Z\\mathrm{n}$ deposits in ZS electrolyte increases from $\\Psi_{0}$ to $\\boldsymbol{\\Psi}_{\\varsigma}$ . While in $\\mathrm{La}^{3+}$ -ZS electrolyte, both the bivalent $Z\\mathrm{n}^{2+}$ ions and trivalent $\\mathrm{La}^{3+}$ ions are absorbed on the surface of $Z\\mathrm{n}$ deposits, resulting in fewer net negative charges than that in ZS electrolyte. In this context, the surface of Zn deposits presents a higher potential $\\boldsymbol{\\Psi}_{\\sf S^{'}}$ than $\\Psi_{\\varsigma}$ . The EDL repulsion decreases due to the fewer net charges, and the electric double layer gets thinner in a $\\mathrm{La}^{3+}$ -ZS electrolyte than in a ZS electrolyte50. As illustrated in Fig. 4c, in ZS electrolyte, the electrodeposited $Z\\mathrm{n}$ tends to grow into separate hexagonal plates due to the EDL repulsion dominated interactions between the Zn deposits32,51. While when $\\mathrm{La}^{3+}$ -ZS electrolyte is used, the competitive adsorption of the inert $\\mathrm{La}^{3+}$ ions on the surface of the Zn electrodes reduces the EDL repulsion between the $Z\\mathrm{n}$ deposits and leads to the coherent electrodeposition of the $Z\\mathrm{n}$ deposits along (002) plane (Fig. 4d). \n\nElectrochemical energy storage testing in $\\mathbf{Z}\\mathbf{n}||\\mathbf{V}\\mathbf{S}_{2}$ coin cell configuration. The $\\mathrm{La}^{\\bar{3}+}$ -ZS electrolyte was also tested in full coin cell configuration using a Zn metal anode and a $\\mathrm{VS}_{2}$ -based cathode (Fig. 5). Here, the $\\mathrm{VS}_{2}$ was synthesized via a hydrothermal method (Supplementary Fig. 15). The $\\mathrm{Zn}||\\mathrm{VS}_{2}$ cell with $\\mathrm{La}^{3+}$ -ZS electrolyte exhibits slightly higher specific capacities than those with ZS electrolyte at specific current of 0.1, 0.2, 0.5, 1.0, and $2.0\\mathrm{Ag}^{-1}$ (Fig. 5a). The higher and more stable CE values during cycling indicate that $\\mathrm{La}^{3+}{-}\\mathrm{ZS}$ electrolyte benefits the $\\mathrm{\\Delta}Z\\mathrm{n}||$ $\\mathrm{VS}_{2}$ cell performance (Supplementary Figs. 16). We further tested the cycling performance of the $\\mathrm{\\Delta}\\dot{\\mathrm{Zn}}||\\dot{\\mathrm{VS}}_{2}$ cell with a limited $Z\\mathrm{n}$ supply $(7.4\\mathrm{mAh}\\mathrm{cm}^{-2}$ ) and a high-loading cathode $(8.0\\mathrm{mg}\\mathrm{cm}^{-2})$ at a specific current of $0.1\\mathrm{A}\\bar{\\mathrm{g}}^{-1}$ after 5 activation cycles at $0.05\\mathrm{Ag^{-1}}$ . As the results displayed in Fig. 5b, the $\\mathrm{Zn}||$ $\\dot{\\mathrm{VS}}_{2}$ cell with ZS electrolyte shows a rapid capacity decay and failed after 30 cycles. Whereas the cell with $\\mathrm{La}^{\\mathsf{\\hat{3}+}}$ -ZS electrolyte remains a discharge capacity of $108\\mathrm{mAh}\\mathrm{g}^{-1}$ after 100 cycles. The normalized discharge/charge profiles of the $\\mathrm{Zn}||\\mathrm{VS}_{2}$ cell at the $20^{\\mathrm{th}}$ cycle were compared in Fig. 5c, where the cell in ZS electrolyte shows larger voltage hysteresis (the voltage gap at $50\\%$ capacity) than that of the one in $\\dot{\\mathrm{La}}^{3+}$ -ZS electrolyte. In addition, the voltage hysteresis of the cells in $\\mathrm{La}^{3+}$ -ZS electrolyte decreases slightly from $\\mathrm{i}18\\mathrm{mV}$ in the $6^{\\mathrm{{th}}}$ cycle to $101\\mathrm{mV}$ in the $24^{\\mathrm{th}}$ cycle, whereas the ones in ZS electrolyte increases gradually with cycles (Fig. 5c and Supplementary Fig. 17). The long-term cycling stability of $\\mathrm{Zn}||\\mathrm{VS}_{2}^{-}$ cells in ZS and $\\mathrm{La}^{3+}$ -ZS electrolytes at a specific current of $\\mathrm{~\\dot{~}_{1}~A~g^{-1}~}$ are compared in Supplementary Fig. 18. Benefitting from the improved stability and reversibility of the Zn electrode in $\\mathrm{La}^{3+}{-}\\mathrm{ZS}$ electrolyte, the $\\mathrm{\\Zn}||\\mathrm{VS}_{2}$ cell with $\\mathrm{La}^{3+}$ -ZS electrolyte delivers cycling stability (1000 cycles) with a high average CE of $99.89\\%$ . In comparison, the $\\mathrm{Zn}||\\mathrm{VS}_{2}$ cell with ZS electrolyte faded quickly and failed in less than 400 cycles. Furthermore, compared with that of the one using ZS electrolyte, the cycling performance of the $\\mathrm{Zn}||\\mathrm{VS}_{2}$ cell with a limited Zn supply $(11.6\\mathrm{mAh}\\mathrm{cm}^{-2}$ ) and a high-loading $\\mathrm{VS}_{2}$ cathode $(1\\bar{6}.0\\mathrm{mg}\\mathrm{cm}^{-2})$ ) using $\\mathrm{La}^{3+}{-}\\mathrm{ZS}$ electrolyte showed significantly improved cycling stability and higher average discharge voltage (the voltages of cells at medium discharge capacity) $0.54\\mathrm{V}$ vs. $0.49\\mathrm{V}$ at a high areal current density of $16.0\\mathrm{m}\\dot{\\mathrm{A}}\\mathrm{cm}\\dot{{^-}}{^2}$ during the long-term cycling (Fig. 5d and Supplementary Fig. 19), which benefit from the intact Zn electrodes (Supplementary Fig. 20). \n\n![](images/8ae71914aff0b4461786803c0575a69f91facda65bcc34b9a385d2bf5fb6cb32.jpg) \nFig. 5 The electrochemical performance of $\\pmb{Z}\\pmb{n}||\\pmb{v}\\pmb{\\mathsf{s}}_{2}$ cells in ZS and $\\pmb{L a^{3}}+\\limits_{-2S}$ electrolytes. a The rate performance. b The cycling performance with a limited Zn supply (N/P capacity ratio: 4.3). c Normalized charge-discharge curves of $\\mathbf{(6)}$ at the $20^{\\mathrm{th}}$ cycle. d The cycling performance with a limited $Z n$ supply $(11.6\\mathsf{m A h c m}^{-2})$ and a high-loading $\\mathsf{V S}_{2}$ cathode $(16.0\\mathsf{m g}\\mathsf{c m}^{-2};$ at a current density of $16.0\\mathsf{m A c m}^{-2}$ . \n\nIn summary, by introducing high-valence $\\mathrm{\\bar{L}a}^{3+}$ ions into aqueous $\\mathrm{ZnSO_{4}}$ electrolyte, we successfully compressed the EDL, reduced the EDL repulsion between the $Z\\mathrm{n}$ deposits, and obtained coherentelectrodeposited Zinc with a compact structure and improved electrochemical stability. With this EDL-compressing approach, a stable Zn plating/stripping performance for $>1200\\mathrm{h}$ , a high average Coulombic efficiency of $99.9\\%$ for over 2100 cycles, a prolonged cycling stability under a deep-discharge condition $(80\\%\\mathrm{\\DOD}_{\\mathrm{Zn}})$ ), and stable $\\mathrm{Zn}||\\mathrm{VS}_{2}$ coin cell performance were realized. \n\n# Methods \n\nThe preparation of the electrolytes. The ZS electrolyte $(2\\mathrm{m}\\mathrm{~ZnSO_{4}},$ ) was prepared by dissolving $17.25\\mathrm{g}$ of $\\mathrm{ZnSO_{4}}$ $99.995\\%$ , Aladdin) into $30\\mathrm{ml}$ of deionized (DI) water. The $\\bar{\\mathrm{La}^{3+}}$ -ZS electrolyte $(2\\mathrm{m}\\mathrm{~ZnSO_{4}}$ and $0.0085\\mathrm{m}\\ \\mathrm{La}(\\mathrm{NO}_{3})_{3}.$ ) was prepared by adding $110.4\\mathrm{mg}$ of $\\mathrm{La}(\\mathrm{NO}_{3})_{3}$ $(99\\%,$ Aladdin) into $30~\\mathrm{mL}$ of ZS solution. To inquire the role of $\\mathrm{NO}_{3}{}^{-}$ , $\\mathrm{NO}_{3}{}^{-}$ -ZS electrolyte with a same concentration of ${\\mathrm{NO}}_{3}{}^{-}$ as $\\mathrm{La}^{3+}$ -ZS was prepared by adding $113.8\\mathrm{mg}$ of $\\mathrm{Zn}(\\mathrm{NO}_{3})_{2}$ (AR, Sinopharm Chemical) into $30~\\mathrm{mL}$ of ZS solution. \n\nSynthesis of $\\pmb{\\mathsf{v}}\\pmb{\\mathsf{s}}_{2}$ powders. $\\mathrm{VS}_{2}$ Powders were synthesized by a hydrothermal method52. In a typical procedure, $3\\mathrm{ml}$ of $\\mathrm{NH}_{3}\\mathrm{H}_{2}\\mathrm{O}$ and $23\\mathrm{mmol}$ of thioacetamide (TAA) was added to a $45\\mathrm{ml}$ of 3 mmol $\\mathrm{NH_{4}V O_{3}}$ solution one by one with an interval time of $^{\\textrm{1h}}$ under stirring. After being stirred for another hour, the asreceived brown mixture was transferred into a $50\\mathrm{ml}$ Teflon-lined autoclave and maintained at $180^{\\circ}\\mathrm{C}$ for $20\\mathrm{h}$ . After the reaction, the solid product was collected by centrifuging and washing with DI water and ethanol thoroughly and dried in a vacuum oven at $50^{\\circ}\\mathrm{C}$ overnight. Finally, the as-collected black powders were annealed in $\\Nu_{2}$ at $180^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{h}}$ to obtain the $\\mathrm{VS}_{2}$ powders. \n\nCharacterizations. The morphologies and structures of the samples were characterized by field emission scanning electron microscopy (SEM, Nova NanoSEM \n\n450) equipped with energy-dispersive X-ray spectroscopy (EDS). X-ray diffraction (XRD) patterns were recorded with a Bruker-AXS microdiffractometer (D-8 ADVANCE) using $\\mathrm{Cu-K_{\\mathrm{a1}}}$ radiation $(\\lambda=1.5406\\mathrm{\\AA}$ ) from $10^{\\circ}$ to $90^{\\circ}$ . Grazing incidence X-ray diffraction (GIXRD) patterns were collected from 35 to $47^{\\circ}$ on a Rigaku SmartLab X-ray diffractometer with a $\\mathrm{Cu-K_{\\alpha1}}$ radiation with a step size of $0.0001^{\\circ}$ . All the electrode samples were collected by disassembling the $Z\\mathrm{n}||Z\\mathrm{n}$ cells after a certain number of cycles at different currents. After being rinsed in DI water and dried in the air, the sampled electrodes were transferred into the SEM and XRD equipment for the morphology analysis of $Z\\mathrm{n}$ deposits. \n\nElectrochemical measurements. All the electrochemical measurements are conducted in air, and the temperature is controlled at $25.0\\pm2.0^{\\circ}\\mathrm{C}$ . The $\\mathrm{VS}_{2}$ electrodes were prepared by a blade-cast method. Briefly, the $\\mathrm{VS}_{2}$ powders, acetylene black carbon, and polyvinylidene fluoride (PVDF) were mixed with a weight ratio of 7: 2: 1 in N-methyl-2-pyrrolidone (NMP) with an electric mixer (AR-100, THINKY). Then, the as-prepared slurry was blade-casted onto a Ti foil $:15\\upmu\\mathrm{m}$ in thickness, $99\\%$ , Dongguan XingYe Metal Material). After being dried in a vacuum oven at $50^{\\circ}\\mathrm{C}$ overnight, $\\mathrm{VS}_{2}$ electrodes were obtained by cutting the above Ti foil into circular sheets with a diameter of $8\\mathrm{mm}$ . The CR-2032 coin cells were assembled using glass fiber (GF-B, $\\Phi19$ ) as separators, $Z\\mathrm{n}$ plates or $\\mathrm{VS}_{2}$ electrodes as the working electrodes, and $Z\\mathrm{n}$ plates ${\\mathrm{80}}\\upmu\\mathrm{m}$ in thickness unless otherwise specified, $99\\%$ , Dongguan XingYe Metal Material), Ti foils, or carbon papers ${\\mathsf{90}}\\upmu\\mathrm{m}$ in thickness, $98.5\\%$ , CeTech) as the counter electrodes, $100~\\upmu\\mathrm{l}$ of electrolytes were added to each cells. For the electrochemical characterizations of the $\\mathrm{Zn}||\\mathrm{VS}_{2}$ cells with a limited $Z\\mathrm{n}$ supply ${\\mathrm{:}}13{\\upmu\\mathrm{m}}$ $7.40\\mathrm{mAh}\\mathrm{cm}^{-2}$ ), the areal mass loading of $\\mathrm{VS}_{2}$ electrodes was ${\\sim}8.0\\ \\mathrm{mg}\\mathrm{cm}^{-2}$ , while the number is $\\sim1.0\\mathrm{mg}\\mathrm{cm}^{-2}$ for all other $\\mathrm{Zn}||$ $\\mathrm{VS}_{2}$ cells. The CE tests was measured with $\\mathrm{\\DeltaZn||Ti}$ (or $\\mathrm{{Zn}||C)}$ cells with a $Z\\mathrm{n}$ deposition of $1.0\\mathrm{mAh}\\mathrm{cm}^{-2}$ $2\\operatorname{mA}\\operatorname{cm}^{-2}$ for $0.5\\mathrm{h}$ ) and a charge cut-off voltage of $0.4\\mathrm{V}$ . All the above tests were performed on a Neware Battery Tester. To test the corrosion rate of $Z\\mathrm{n}$ foil, a three-electrode cell was constructed using $Z\\mathrm{n}$ foil as the working electrode, Pt wire $(\\Phi0.5,99.99\\%$ , Gaoss Union) as the counter electrode, and $\\mathrm{Ag/AgCl}$ electrode as the reference electrode and tested on an electrochemical workstation (VMP3, Bio-Logic). The efficiency of protection $(\\eta\\%)$ for $Z\\mathrm{n}$ electrodes in a $\\mathrm{La}^{3+}$ -ZS electrolyte was calculated by using the values of the corrosion current $\\mathrm{I}_{\\mathrm{corr}}$ shown as the Eq. 2: \n\n$$\n\\eta\\%=\\left(\\frac{\\mathrm{I}_{\\mathrm{corr(ZS)}}-\\mathrm{I}_{\\mathrm{corr\\bigl(La^{3+}-Z S\\bigr)}}}{\\mathrm{I}_{\\mathrm{corr(ZS)}}}\\right)\\times100\\\n$$ \n\nThe linear polarization curve, chronoamperometry (CA) (at overpotentials of $-200\\mathrm{mV})$ , and cyclic voltammetry (CV) curves at a scan rate of $0.1\\mathrm{mV}s^{-1}$ were recorded electrochemical workstation (VMP3, Bio-Logic). The Zeta potential was collected on a Zeta potential analyzer (Malvern Zetasizer Nano ZS90). \n\n# Data availability \n\nAll data that support the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper. \n\nReceived: 27 October 2021; Accepted: 20 May 2022; Published online: 06 June 2022 \n\n# References \n\n1. Du, H. et al. High-capacity and long-life zinc electrodeposition enabled by a self-healable and desolvation shield for aqueous zinc-ion batteries. Angew. Chem., Int. Ed. Engl. 61, e202114789 (2022). \n2. Zhao, Z. et al. Long-life and deeply rechargeable aqueous $Z\\mathrm{n}$ anodes enabled by a multifunctional brightener-inspired interphase. Energy Environ. Sci. 12, 1938–1949 (2019). \n3. Zampardi, G. & La Mantia, F. Open challenges and good experimental practices in the research field of aqueous $Z\\mathrm{n}$ -ion batteries. Nat. Commun. 13, 687 (2022). \n4. Ma, L. et al. Realizing high zinc reversibility in rechargeable batteries. Nat. Energy 5, 743–749 (2020). \n5. Sato, R. Crystal growth of electrodeposited zinc: an electron diffraction and electron microscopic study. J. Electrochem. Soc. 106, 206–211 (1959). \n6. Ma, L. et al. Critical factors dictating reversibility of the zinc metal anode. Energy Environ. Mater. 3, 516–521 (2020). \n7. Li, C., Xie, X., Liang, S. & Zhou, J. Issues and future perspective on zinc metal anode for rechargeable aqueous zinc-ion batteries. Energy Environ. Mater. 3, 146–159 (2020). \n8. Zheng, J. et al. Reversible epitaxial electrodeposition of metals in battery anodes. Science 366, 645–658 (2019). \n9. Zhao, R. et al. Redirected Zn electrodeposition by an anti-corrosion elastic constraint for highly reversible $Z\\mathrm{n}$ anodes. Adv. Funct. Mater. 31, 2001867 (2021). \n10. Kang, L. et al. Nanoporous $\\mathrm{CaCO}_{3}$ coatings enabled uniform Zn stripping/ plating for long-life zinc rechargeable aqueous batteries. Adv. Energy Mater. 8, 1801090 (2018). \n11. Xie, X. et al. Manipulating the ion-transference kinetics and interface stability for high-performance zinc metal anode. Energy Environ. Sci. 13, 503–510 (2020). \n12. Zhang, Q. et al. Revealing the role of crystal orientation of protective layers for stable zinc anode. Nat. Commun. 11, 3961 (2020). \n13. Zheng, J. et al. Regulating electrodeposition morphology in high-capacity aluminium and zinc battery anodes using interfacial metal-substrate bonding. Nat. Energy 6, 398–406 (2021). \n14. Zhu, M. et al. A patternable and in situ formed polymeric zinc blanket for a reversible zinc anode in a skin-mountable microbattery. Adv. Mater. 33, e2007497 (2021). \n15. Zeng, Y. et al. Dendrite-free zinc deposition induced by multifunctional CNT frameworks for stable flexible Zn-ion batteries. Adv. Mater. 31, 1903675 (2019). \n16. Ye, Y. et al. Ultralight and fire-extinguishing current collectors for high-energy and high-safety lithium-ion batteries. Nat. Energy 5, 786–793 (2020). \n17. Cao, J. et al. Manipulating crystallographic orientation of zinc deposition for dendrite-free zinc ion batteries. Adv. Energy Mater. 11, 2101299 (2021). \n18. Jin, S. et al. Stabilizing zinc electrodeposition in a battery anode by controlling crystal growth. Small 17, 2101798 (2021). \n19. Dong, Y., Zhang, Z., Alvarez, A. & Chen, I. W. Potential jumps at transport bottlenecks cause instability of nominally ionic solid electrolytes in electrochemical cells. Acta Mater. 199, 264–277 (2020). \n20. Zheng, J. et al. Spontaneous and field-induced crystallographic reorientation of metal electrodeposits at battery anodes. Sci. Adv. 6, eabb1122 (2020). \n21. Monroe, C. & Newman, J. The impact of elastic deformation on deposition kinetics at lithium/polymer interfaces. J. Electrochem. Soc. 152, A396 (2005). \n22. Shi, F. et al. Strong texturing of lithium metal in batteries. Proc. Natl Acad. Sci. U.S.A. 114, 12138–12143 (2017). \n23. Israelachvili, J. N. Intermolecular and Surface Forces. Ch. 12–13, Pages 176–259, (Harcourt Brace & Company, 1991). \n24. Smith, A. M., Borkovec, M. & Trefalt, G. Forces between solid surfaces in aqueous electrolyte solutions. Adv. Colloid Interface Sci. 275, 102078 (2020). \n25. Christenson, H. K. DLVO (Derjaguin–Landau–Verwey–Overbeek) theory and solvation forces between mica surfaces in polar and hydrogen-bonding liquids. J. Chem. Soc. Faraday Trans. 1 80, 1933–1946 (1984). \n26. Lee, S.-Y., Lee, S.-H. & Park, J.-G. Interaction forces between silica particles and wafer surfaces during chemical mechanical planarization of copper. J. Electrochem. Soc. 150, G327 (2003). \n27. Israelachvili, J. N. Intermolecular and Surface Forces. Ch. 12, Page 238, (Harcourt Brace & Company, 1991). \n28. van Oss, C. J. & Giese, R. F. Surface modification of clays and related materials. J. Dispers. Sci. Technol. 24, 363–376 (2007). \n29. Omija, K., Hakim, A., Masuda, K., Yamaguchi, A. & Kobayashi, M. Effect of counter ion valence and $\\mathrm{\\pH}$ on the aggregation and charging of oxidized carbon nanohorn (CNHox) in aqueous solution. Colloids Surf. A 619, 126552 (2021). \n30. Valmacco, V. et al. Forces between silica particles in the presence of multivalent cations. J. Colloid Interface Sci. 472, 108–115 (2016). \n31. Kotynska, J. & Figaszewski, Z. A. Binding of trivalent metal ions $(\\mathrm{Al}^{3+}$ , $\\mathrm{In}^{3+}$ , $\\mathrm{La}^{3\\dot{+}}$ ) with phosphatidylcholine liposomal membranes investigated by microelectrophoresis. Eur. Phys. J. E 41, 70 (2018). \n32. Pashley, R. M. Forces between mica surfaces in $\\mathrm{La}^{3+}$ and $\\mathrm{Cr}^{3+}$ electrolyte solutions. J. Colloid Interface Sci. 102, 23–35 (1984). \n33. Sabín, J. et al. On the effect of $\\mathrm{Ca}^{2+}$ and $\\mathrm{La}^{3+}$ on the colloidal stability of liposomes. Langmuir 21, 10968–10975 (2005). \n34. Zhang, X. G. Corrosion and Electrochemistry of Zinc. Ch. 5, Pages 125–156, (Springer, 1996). \n35. Fang, C. et al. Quantifying inactive lithium in lithium metal batteries. Nature 572, 511–515 (2019). \n36. Huang, C.-J. et al. Decoupling the origins of irreversible coulombic efficiency in anode-free lithium metal batteries. Nat. Commun. 12, 1452 (2021). \n37. Sun, P. et al. Simultaneous regulation on solvation shell and electrode interface for dendrite-free $Z\\mathrm{n}$ ion batteries achieved by a low-cost glucose additive. Angew. Chem., Int. Ed. 60, 18247–18255 (2021). \n38. Huang, C. et al. Stabilizing zinc anodes by regulating the electrical double layer with saccharin anions. Adv. Mater. 33, 2100445 (2021). \n39. Xiang, Z. D., Rose, S. & Datta, P. K. Pack deposition of coherent aluminide coatings on $\\upgamma$ -TiAl for enhancing its high temperature oxidation resistance. Surf. Coat. Technol. 161, 286–292 (2002). \n40. Moffat, T. P., Wheeler, D. & Josell, D. Electrodeposition of Copper in the SPSPEG-Cl Additive System. J. Electrochem. Soc. 151, C262 (2004). \n41. Benea, L. & Danaila, E. Nucleation and growth mechanism of $\\mathrm{Ni}/\\mathrm{TiO}_{2}$ nanoparticles electro-codeposition. J. Electrochem. Soc. 163, D655 (2016). \n42. Scharifker, B. & Hills, G. Theoretical and experimental studies of multiple nucleation. Electrochim. Acta. 28, 879–889 (1983). \n43. Torabi, M. & Dolati, A. A kinetic study on the electrodeposition of nickel nanostructure and its electrocatalytic activity for hydrogen evolution reaction. J. Appl. Electrochem. 40, 1941–1947 (2010). \n44. Lu, J. & Barkey, D. P. A thermodynamic study of adsorption of benzyl viologen and polyethylene glycol and their displacement by 3-mercapto-1- propanesulfonate during copper electrodeposition. J. Electrochem. Soc. 165, D231 (2018). \n45. Bard, A. J. & Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications. Ch. 13, 552–554, (Wiely, 2001). \n46. Bard, A. J. & Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications. Ch. 13, Pages 566–567, (Wiely, 2001). \n47. Fu, X., Shen, W., Yao, T. & Hou, W. Physical Chemistry. Pages 434–435, (Higher Education Press, 2006). \n48. Khaled, K. F. Adsorption and inhibitive properties of a new synthesized guanidine derivative on corrosion of copper in $0.5\\mathrm{~M~}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ . Appl. Surf. Sci. 255, 1811–1818 (2008). \n49. Elrouby, M., El –Shafy Shilkamy, H. A. & Elsayed, A. Development of the electrochemical performance of zinc via alloying with indium as anode for alkaline batteries application. J. Alloy. Compd. 854, 157285 (2021). \n50. Kunsong, M. & Alain, C. P. Colloidal behaviour of montmorillonite in the presence of $\\mathrm{Fe}^{3+}$ ions. Colloids Surf. A 155, 359–372 (1999). \n51. Szilagyi, I., Trefalt, G., Tiraferri, A., Maroni, P. & Borkovec, M. Polyelectrolyte adsorption, interparticle forces, and colloidal aggregation. Soft Matter 10, 2479 (2014). \n52. He, P. et al. Layered $\\mathrm{VS}_{2}$ nanosheet-based aqueous $Z\\mathrm{n}$ ion battery cathode. Adv. Energy Mater. 7, 1601920 (2017). \n\n# Acknowledgements \n\nL. Q. thanks the support from the National Key Research and Development Program (2021YFB2400300) and the Fundamental Research Funds for the Central Universities (2021GCRC001). \n\n# Author contributions \n\nR.Z. and L.Q. conceived and designed the research. R.Z. carried out the main experiments. H.W. contributed assistantly the data curation. H.D. helped with the synthesis of $\\mathrm{VS}_{2}$ . Y.Y. and Z.G. helped with the Chronoamperogram measurements and analysis. R.Z., L.Q., and Y.H. wrote the manuscript. All authors discussed the results and reviewed the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-30939-8. \n\nCorrespondence and requests for materials should be addressed to Long Qie or Yunhui Huang. \n\nPeer review information Nature Communications thanks Kothandaraman ramanujam, Deepa Madan, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1007_s40820-022-00960-z", + "DOI": "10.1007/s40820-022-00960-z", + "DOI Link": "http://dx.doi.org/10.1007/s40820-022-00960-z", + "Relative Dir Path": "mds/10.1007_s40820-022-00960-z", + "Article Title": "Metal-Organic Frameworks Functionalized Separators for Robust Aqueous Zinc-Ion Batteries", + "Authors": "Song, Y; Ruan, PC; Mao, CW; Chang, YX; Wang, L; Dai, L; Zhou, P; Lu, BA; Zhou, J; He, ZX", + "Source Title": "nullO-MICRO LETTERS", + "Abstract": "Aqueous zinc-ion batteries (AZIBs) are one of the promising energy storage systems, which consist of electrode materials, electrolyte, and separator. The first two have been significantly received ample development, while the prominent role of the separators in manipulating the stability of the electrode has not attracted sufficient attention. In this work, a separator (UiO-66-GF) modified by Zr-based metal organic framework for robust AZIBs is proposed. UiO-66-GF effectively enhances the transport ability of charge carriers and demonstrates preferential orientation of (002) crystal plane, which is favorable for corrosion resistance and dendrite-free zinc deposition. Consequently, ZnlUiO-66-GF-2.21Zn cells exhibit highly reversible plating/stripping behavior with long cycle life over 1650 h at 2.0 mA cm(-2) , and Zn1UiO-66-GF-2.21MnO(2) cells show excellent long-term stability with capacity retention of 85% after 1000 cycles. The reasonable design and application of multifunctional metal organic frameworks modified separators provide useful guidance for constructing durable AZIBs.", + "Times Cited, WoS Core": 339, + "Times Cited, All Databases": 352, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000885744900003", + "Markdown": "# Metal–Organic Frameworks Functionalized Separators for Robust Aqueous Zinc‑Ion Batteries \n\nReceived: 13 August 2022 \nAccepted: 5 October 2022 \nPublished online: 9 November 2022 \n$\\circledcirc$ The Author(s) 2022 \n\nYang Song1, Pengchao Ruan2, Caiwang Mao1, Yuxin Chang1, Ling Wang1, Lei Dai1, Peng Zhou3, Bingan $\\mathrm{Lu}^{4}$ , Jiang Zhou2 \\*, Zhangxing He1 \\* \n\n# HIGHLIGHTS \n\n•\t Metal-organic frameworks (UiO-66) functionalized glass fiber separator was constructed to accelerate the transport of charge carriers and provide a uniform electric field distribution on the surface of zinc anode. \n•\t Zinc anode demonstrates preferential orientation of (002) plane under the control of UiO-66-GF, which effectively inhibits dendrites. \n•\t Density functional theory calculation confirms that the adsorption effect of (002) plane on $\\mathrm{~H~}$ is weaker, thus improving corrosion resistance and suppressing the hydrogen evolution reaction. \n•\t Symmetric cells exhibit highly reversible plating/stripping behavior with long cycle life over $1650\\mathrm{h}$ and full cells demonstrate excellent long-term stability $(85\\%)$ for 1000 cycles. \n\nABSTRACT  Aqueous zinc-ion batteries (AZIBs) are one of the promising energy storage systems, which consist of electrode materials, electrolyte, and separator. The first two have been significantly received ample development, while the prominent role of the separators in manipulating the stability of the electrode has not attracted sufficient attention. In this work, a separator (UiO66-GF) modified by $Z\\mathrm{r}$ -based metal organic framework for robust AZIBs is proposed. UiO-66-GF effectively enhances the transport ability of charge carriers and demonstrates preferential orientation of (002) crystal plane, which is favorable for corrosion resistance and dendrite-free zinc deposition. Consequently, Zn|UiO-66-GF-2.2|Zn cells exhibit highly reversible plating/stripping behavior with long cycle life over $1650\\mathrm{h}$ at $2.0\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ , and $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cells show excellent long-term stability with capacity retention of $85\\%$ after 1000 cycles. The reasonable design and application of multifunctional metal organic frameworks modified separators provide useful guidance for constructing durable AZIBs. \n\n![](images/956f70c344f336f3c8fa7e9ec3a6f76d36dd88b778f687d9f389a95cf2c3f709.jpg) \n\nKEYWORDS  Aqueous zinc-ion batteries; Separators; Metal–organic frameworks; Ion transport; Dendrite-free \n\n# 1  Introduction \n\nAqueous zinc-ion batteries (AZIBs) have a high application potential, owing to their simple fabrication process, intrinsic safety, and economic feasibility, for a new generation of energy storage devices [1–3]. However, numerous challenges impede their practical application, particularly the inevitable issues in zinc anode, including dendrites, hydrogen evolution reaction (HER), corrosion, and passivation [4–6]. The formation and growth of dendrites generated by inhomogeneous zinc plating destroy anode–electrolyte interface and even induce short circuit, resulting in a short cycle life and poor electrochemical performance [7, 8]. Most of the current modification studies focus on the interfacial modification or structural design of zinc anode and optimal configuration of electrolyte additives to regulate the plating/stripping behavior of zinc-ions [9]. As a key part of AZIBs, separator plays a crucial role in ions transport and electrolyte carriage. The research on separators is still in its infancy, indicating that its application potential and research value need to be developed urgently [10, 11]. \n\nSeparator acts to transport ions and prevent physical contact between cathode and anode. However, voids with different sizes in glass fiber (GF) are the dominant separator in AZIBs, triggering an inhomogeneous deposition of zinc-ions and dendrite growth, eventually causing a short circuit. Inspired by lithium-ion batteries (LIBs), various multi-functional materials including graphene oxide (GO) layer [12], polypyrrole (PPy) layer [13], and Sn coating [14] have been used in the separators for uniform zinc deposition. The large specific surface area of the intermediate layer enhances the reaction kinetics, and the good zinc affinity makes the zinc-ions flux uniform. Janus separator obtained by vertically growing graphene on GF has large surface area and three-dimensional (3D) framework, which is favorable for the uniform deposition of zinc-ions, thereby suppressing the formation of dendrites [15]. To compensate for the defect of nonuniform void size of GF, functional supramolecules [16] and $\\mathbf{BaTiO}_{3}$ [17] were introduced into GF by vacuum filtration. This not only effectively accelerates the transmission of zinc-ions, but also uniformly distributes zinc-ions to the separator-zinc anode interface for highly reversible plating/stripping. To reduce the working cost and simplify the preparation process, new cost-effective separators, such as weighing paper (WP) [18] and commercial cotton towel (CT) [19], adsorb zinc-ions through their plenteous functional groups to enhance the reversibility of zinc anode. Metal–organic frameworks (MOFs) with large specific surface areas and topological structures are ideal materials for fabricating high-performance separators and have been applied in studies on lithium-sulfur (Li–S) batteries [20]. However, their excellent ion transport ability has not been embodied in AZIBs. \n\nIn this work, we prepared a separator functionalized by a $\\mathrm{Zr}$ -based MOF (UiO-66-GF) via a hydrothermal method, used in high-performance AZIBs (Fig. 1a). UiO-66 exhibits structural robustness. The strong $Z\\mathrm{r-O}$ bond coordination contributes to its stability under thermal, chemical, and aqueous conditions, which is the major advantage over other MOFs materials [21]. The rich Lewis acidic sites and channels in UiO-66 also enhance the ion transport ability [22]. The large specific surface area and abundant pore structure of UiO-66 provide UiO-66-GF with high transport ability for charge carriers at separator–electrolyte interface. UiO66 induces preferential orientation of (002) crystal plane [23], which is conducive to the growth of zinc-ions in the horizontal direction without dendrites [24]. Furthermore, undesirable side reactions, including corrosion and HER, are significantly suppressed, mainly manifested by the reduction of by-products on the zinc anode surface. Zn|UiO-66-GF$2.21Z\\mathrm{n}$ cell enables over $1650\\mathrm{h}$ of reversible plating/stripping with high Coulombic efficiency (CE) and low polarization $(39\\mathrm{mV})$ [25]. In addition, $\\mathrm{Zn|UiO{-}66{\\-}G F{-}2{.}2|M n O_{2}}$ cell exhibits high specific discharge capacity of $230.8\\ \\mathrm{mAh\\g^{-1}}$ at $0.1\\mathrm{Ag}^{-1}$ and excellent long-term stability with capacity retention of $85\\%$ after 1000 cycles at $1.0\\mathrm{A}\\mathrm{g}^{-1}$ . This work provides a new concept for the construction of stable zinc anode and durable AZIBs [26]. \n\n# 2  \u0007Experimental \n\n# 2.1  \u0007Materials \n\nGlass fiber separators were purchased from Tianjin Aiweixin Chemical Technology Co., Ltd. Terephthalic acid $\\mathrm{(H}_{2}\\mathrm{BDC)}$ was purchased from J&K Scientific Ltd. $\\mathrm{zrCl}_{4}$ was purchased from Shanghai Aladdin Biochemical Technology Co., Ltd. Other chemical substances were of analytical grade and had not undergone other treatments. \n\n![](images/1ac5652ed03e890bb9666cb88c4163115ffd8abf28e9a369b56820930d357c4b.jpg) \nFig. 1   Synthesis of UiO-66-GF and characterizations of UiO-66. a Preparation diagram of UiO-66-GF and structural diagram of UiO-66. b XRD patterns of UiO-66. c ${\\bf N}_{2}$ adsorption/desorption isotherm and pore size distribution of UiO-66. d XPS full spectrum of UiO-66. Highresolution XPS spectra of e $\\mathrm{Zr}3d$ , f C $1s$ , and $\\mathbf{g}\\operatorname{O}$ 1s \n\n# 2.2  \u0007Preparation of Materials \n\nAll glass fiber separators were ultrasonically treated with absolute ethanol for $0.5\\mathrm{~h~}$ to clean the impurities on the surface and ensure the accuracy of the experimental data. UiO-66 was synthesized by hydrothermal method. Firstly, 0.6 and $2.2~\\mathrm{mmol~L^{-1}}$ of $\\mathrm{ZrCl_{4}}$ (0.14 and $0.513{\\mathrm{~g}}$ ) were added to a beaker containing $40~\\mathrm{mL}$ of N, N dimethylformamide (DMF), respectively. $\\mathrm{H}_{2}\\mathrm{BDC}$ (0.1 and $0.365\\:\\mathrm{g}$ ) and $4~\\mathrm{mL}$ of acetic acid were then added to the mixed solution, respectively. Finally, ultrasonic treatment was performed for $0.5\\mathrm{h}$ . Glass fiber separators were added to the above solution, soaked for $10\\mathrm{min}$ , transferred to a $100~\\mathrm{mL}$ of Teflonlined stainless-steel autoclave, and heated in an oven set at $120~^{\\circ}\\mathrm{C}$ for $16\\mathrm{~h~}$ . When the hydrothermal reaction was completed and the temperature was cooled to $25~^{\\circ}\\mathrm{C}$ , glass fiber separators were washed with methanol and placed in a vacuum drying oven at $80~^{\\circ}\\mathrm{C}$ for $8\\mathrm{h}$ . The white solution in the stainless-steel autoclave was centrifuged with methanol and dried at $80~^{\\circ}\\mathrm{C}$ for $8\\mathrm{~h~}$ to obtain a white powder UiO66. According to the amount of $\\mathrm{ZrCl_{4}}$ (0.6 and $2.2\\ \\mathrm{mmol}$ ${\\mathrm{L}}^{-1},$ , the obtained MOFs are denoted as UiO-66-0.6 and UiO-66-2.2, respectively. The original glass fiber separator is denoted as GF. The obtained MOFs in situ grown glass fiber separators are denoted as UiO-66-GF-0.6 and UiO66-GF-2.2, respectively. \n\n$0.3803\\ \\mathrm{g\\MnSO_{4}{\\cdot}H_{2}O}$ and $0.237\\mathrm{\\g\\KMnO_{4}}$ were added to $15~\\mathrm{mL}$ of distilled water and stirred for $15\\mathrm{min}$ until they were completely dissolved. The above $\\mathrm{KMnO}_{4}$ solution was then added dropwise to $\\mathbf{MnSO}_{4}{\\cdot}\\mathbf{H}_{2}\\mathbf{O}$ . After stirring for $30\\mathrm{min}$ , the mixed solution was transferred to a $100~\\mathrm{mL}$ Teflon-lined stainless-steel autoclave and heated at $160^{\\circ}\\mathrm{C}$ for $12\\mathrm{~h~}$ . After natural cooling, the resulting precipitate was centrifuged three times with distilled water and then placed in a vacuum drying oven at $80~^{\\circ}\\mathrm{C}$ to dry for $8\\mathrm{~h~}$ . The obtained $\\mathbf{\\alpha}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{(\\mathbf{x-MnO}_{2}}}$ powder was used as cathode material. $\\mathbf{\\alpha}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{(\\alpha-MnO_{2}}}$ , Super P, and polyvinylidene fluoride (PVDF) were mixed in a ratio of 7:2:1 with N-methyl pyrrolidone (NMP) as the solvent. After the slurry was formed, it was coated on a metal mesh $\\phi=14~\\mathrm{mm}$ ) and placed in a vacuum drying oven at $80~^{\\circ}\\mathrm{C}$ for $8\\mathrm{h}$ . \n\n# 2.3  \u0007Characterizations \n\nThe crystal structures of the samples were studied by X-ray diffraction (XRD, D8 Advance A25 Instrument, Bruker, Germany). Morphology was observed by scanning electron microscopy (SEM, JSM-IT100, JEOL, Japan), and energy-dispersive X-ray (EDX) analysis was carried out to analyze the surface elemental composition. X-ray photoelectron spectroscopy (XPS, K-alpha Plus Instrument, Thermo Fisher, USA) was carried out to study surface chemical states. Distilled water was used as the test liquid to test the hydrophilicity of the sample by contact angle tester (HARKE-SPCA, Beijing Hake Test Instrument Factory, China). The surface areas of the samples, degassed at $120^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ under vacuum, were evaluated using ${\\bf N}_{2}$ adsorption/ desorption isotherms at $-196^{\\circ}\\mathrm{C}$ (BET, 3H-2000PM1, BSD Instrument, China). Molecular structures and functional group types were analyzed by Fourier transform infrared spectroscopy (FTIR, VERTEX 80v, Bruker, Germany). \n\n# 2.4  \u0007Electrochemical Measurements \n\nAll CR2016 coin cells were assembled in air. Full cell was assembled with zinc foil as anode, $\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta}\\mathbf{\\alpha\\beta}\\mathbf{\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta\\alpha}\\mathbf{\\beta\\beta\\alpha}\\mathbf{\\beta\\alpha\\beta\\beta}\\mathbf\\mathbf{\\alpha\\alpha}\\beta\\beta\\mathbf{\\alpha\\beta\\beta\\beta\\alpha\\beta\\beta\\beta\\alpha\\beta\\beta\\alpha\\beta\\beta\\beta\\alpha\\beta\\beta\\alpha\\beta\\beta\\beta\\alpha\\beta\\beta\\alpha\\beta\\beta\\beta\\alpha\\beta\\beta\\alpha\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta\\delta $ as cathode, and aqueous solution of $\\mathrm{2.0\\mol{L}^{-1}\\mathrm{Zn}S O_{4}+0.1\\ m o l{L}^{-1}}$ $\\mathrm{MnSO_{4}}$ as electrolyte. Zinc foil was used as anode and cathode, and $2.0\\ \\mathrm{mol}\\ \\mathrm{L}^{-1}\\ \\mathrm{ZnSO}_{4}$ aqueous solution was used as an electrolyte to assemble symmetrical cell. Asymmetric cells were assembled with copper foil and titanium foil as cathode, zinc foil as anode, and $2.0\\ \\mathrm{mol}\\ \\mathrm{L}^{-1}\\ \\mathrm{ZnSO}_{4}$ aqueous solution as electrolyte. All cells were placed on LAND test system (CT2001A, Wuhan Lanhe, China) for $^{4\\mathrm{h}}$ before constant current charge–discharge. Rate performances of full cells were analyzed at current densities of 0.1, 0.3, 0.5, 1.0, 1.2, 1.5, 2.0, 4.0, and $0.1\\mathrm{Ag}^{-1}$ . Cycling performances were analyzed at current densities of 0.5 and $1.0\\mathrm{Ag}^{-1}$ . Galvanostatic intermittent titration technique (GITT) was performed on LAND test system. Cells were cycled 10 times at $0.5\\mathrm{A}$ $\\mathbf{g}^{-1}$ to maintain stability. The current pulse was lasted for $10\\mathrm{min}$ at $0.1\\mathrm{Ag}^{-1}$ , and then cells were relaxed for $30\\mathrm{min}$ to bring the voltage to equilibrium. Rate performances of symmetric cells were analyzed at current densities of 0.25, 0.5, 1.0, 2.0, and $4.0\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ . Nucleation overpotential (NOP) and Coulombic efficiency (CE) were measured by asymmetric cells at $2.0\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ . Chronoamperogram (CA), linear polarization test, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) were measured by electrochemical workstation (CHI660E, Shanghai Chenhua, China). CA test was performed at a scan rate of ${5\\mathrm{mV}\\mathrm{s}^{-1}}$ in $2.0\\mathrm{mol}\\mathrm{L}^{-1}\\mathrm{Zn}\\mathrm{SO}_{4}$ solution, and linear polarization test was performed at a scan rate of $10\\ \\mathrm{mV\\s^{-1}}$ . The ionic conductivities $(\\upsigma)$ of stainless steel (SS)|GF|SS, SS|UiO-66-GF-0.6|SS, and SS|UiO-66-GF-2.2|SS cells were tested by EIS in the frequency range from 0.1 to $100,000\\mathrm{Hz}$ using an electrochemical workstation (CHI660E, Shanghai Chenhua, China). The ionic conductivity was calculated by ${\\upsigma}=\\mathrm{d}/R_{\\mathrm{b}}{\\mathrm{S}}S$ , where d is the thickness of the separator and $R_{\\mathrm{b}}$ and $S$ represent the bulk resistance and the effective area of the separator, respectively. CV test of full cell was carried out in a range of $0.8\\mathrm{-}1.8\\mathrm{~V~}$ at a scan rate of $0.1\\ \\mathrm{mV\\s^{-1}}$ . CV test of $\\mathrm{Zn//Ti}$ asymmetric cell was carried out at a scan rate of $0.5~\\mathrm{mV~s^{-1}}$ . EIS test was carried out in a range of $0.01\\mathrm{-}100,000\\mathrm{Hz}$ . \n\n# 2.5  \u0007Density Functional Theory (DFT) Calculation \n\nDFT simulations were performed using the software Visualization for Electronic and Structural Analysis (VESTA). In our calculations, we use a $7\\times7\\times7$ k-point mesh for $Z\\mathrm{n}$ optimization, while constructing a $p$ $(3\\times3\\times2)$ supercell of $Z\\mathrm{n}$ . The adsorption energy $(E_{\\mathrm{abs}})$ of $Z\\mathrm{n}$ atom on Zn (002), (100), and (101) planes was calculated by $E_{\\mathrm{abs}}{=}E_{\\mathrm{Zn-H}}{-}E_{\\mathrm{H}}{-}E_{\\mathrm{Zn}}$ , where $E_{\\mathrm{Zn-H}},E_{\\mathrm{H}}$ , and $E_{\\mathrm{Zn}}$ are the energy after $Z\\mathrm{n}$ adsorbs H, energy of a single $\\mathrm{~H~}$ , and energy without $\\mathrm{~H~}$ adsorption, respectively. Hydrogen adsorption $\\Delta G_{\\mathrm{H}}$ was calculated by $\\Delta G_{\\mathrm{H}}=\\Delta E_{\\mathrm{DFT}}+\\Delta E_{\\mathrm{ZPE}}-T\\Delta S$ , where $\\Delta E_{\\mathrm{DFT}}$ , $\\Delta E_{\\mathrm{ZPE}}$ , and TΔS denote the DFT calculated adsorption energy, change of zero point energy, and change of entropic contribution, respectively. TS term for $\\mathrm{~H~}$ adsorbate is considered negligible, and $T\\Delta S\\approx-0.5~S S_{\\mathrm{{H}_{2}}}{=}-0.24~\\mathrm{{eV}.}$ \n\n# 3  \u0007Results and Discussion \n\n# 3.1  \u0007Synthesis of UiO‑66‑GF and Characterizations of UiO‑66 \n\nAs illustrated in Figs. S1 and S2, UiO-66 with a face-centered cubic crystal structure has a diameter of approximately $70\\mathrm{nm}$ . The distributions of C, O, and Zr elements are consistent with the positions of SEM image. Each zirconium metal center is linked to 12 benzene-1,4-dicarboxylates (BDC) to form a 3D framework, which is favorable for its stable existence in GF [27]. According to the amount of $\\mathrm{ZrCl_{4}}$ (0.6 and $2.2\\mathrm{mmol}\\mathrm{L}^{-1}$ ) used in the synthesis process, the obtained MOFs are denoted as UiO-66-0.6 and UiO66-2.2, respectively. Furthermore, UiO-66-0.6 and UiO66-2.2 are in good agreement with XRD pattern (UiO-66 simulated) obtained by UiO-66 crystal structure parameter simulation (Fig. 1b). Characteristic diffraction peaks of UiO66 at $7.3^{\\circ}$ , $8.5^{\\circ}$ , and $25.6^{\\circ}$ are consistent with the reported results, which demonstrates the successful synthesis of UiO66 [28]. There is a sharp peak with weak intensity at $12.0^{\\circ}$ , which is attributed to the residual solvent [29]. Figure 1c presents a reversible type I isotherm without hysteresis, which corresponds to the typical microporous structure of MOFs. The large specific surface area $(990.3~\\mathrm{m}^{2}~\\mathrm{g}^{-1})$ and porous structure of UiO-66 provide more transport channels to facilitate the migration and diffusion of zinc-ions. As shown in Fig. 1d, the signals of $\\mathrm{~C~}1s,\\mathrm{~O~}1s,\\mathrm{Zr}\\:3d.$ , and $Z\\mathrm{r}$ $3p$ are detected in the XPS full spectrum, further implying the successful synthesis of UiO-66 [30]. The high-resolution XPS spectrum of $\\ensuremath{\\mathrm{Zr}}3d$ of UiO-66 in Fig. 1e exhibits corresponding peaks of $\\mathrm{Zr}3d_{5/2}$ and $\\mathrm{Zr}3d_{3/2}$ at 182.6 and $185.1\\mathrm{eV}$ , respectively, which indicates that the $Z\\mathrm{r}$ element in UiO-66 exists in the form of $\\mathbf{\\boldsymbol{Z}r O}_{2}$ [31]. The $\\mathrm{~C~}1s$ spectrum has three peaks including those of C–C $284.8\\ \\mathrm{eV}$ ), C–O $(285.9\\mathrm{eV})$ , and $0-C=0$ $(288.8\\mathrm{eV})$ (Fig. 1f) [32], and O 1s spectrum has four distinct peaks at 530.4, 531.9, 532.2, and $533.2\\mathrm{eV},$ , corresponding to Zr–O–Zr, $Z\\mathrm{r}$ –OH, –OH, and $0-C=0$ , respectively (Fig. 1g) [33]. \n\n# 3.2  \u0007Characterizations of UiO‑66‑GF \n\nDue to the poor affinity and attraction for zinc-ions, GF is incapable of inhibiting the concentrated and disordered Zn deposition on the electrodes [16]. Moreover, although abundant porous space on the surface of GF provides a prerequisite for a rapid penetration of electrolyte (Fig. 2a), uneven distribution of porous space still limits the uniform transport of carriers, which is not conducive to the uniform plating/stripping of zinc anode, thus facilitating the formation of dendrites. Sparsely grown MOFs in UiO-66-GF-0.6 provide inadequate ion transport channels, limiting the effect of inducing uniform deposition of zinc-ions (Fig. 2b). On the contrary, MOFs inside UiO-66-GF-2.2 are uniform and can fill the voids with different sizes in GF (Fig. 2c), making the flux of zinc-ions uniform. Therefore, the uniform Zn plating layers are obtained instead of dendrites. All elements of GF are consistent with SEM image position (Figs. 2d and S3a-d). C, O, and Zr elements can also be observed in UiO-66-GF-0.6 and UiO-66-GF-2.2 (Fig. 2e and S3e–j). Moreover, significant UiO-66 diffraction peaks are observed for UiO-66-GF-0.6 and UiO-66-GF-2.2 (Fig. 2f). The peak intensity increases with concentration of the solution, which demonstrates the successful synthesis of UiO66-GF. In the FTIR spectra of GF (Fig. 2g), the peak at $1020\\mathrm{cm}^{-1}$ is ascribed to the asymmetric stretching vibration of Si–O–Si [34]. Among the diffraction peaks of UiO-66, the peak at $744~\\mathrm{cm}^{-1}$ corresponds to the characteristic peak of $Z\\mathrm{r}{-}\\mathrm{O}{-}Z\\mathrm{r}$ , and the peaks at 1402, 1586, and $1659\\mathrm{cm}^{-1}$ correspond to the vibrational peaks of aromatic benzene ring, respectively [35]. In addition, these peaks are also detected in UiO-66-GF, reflecting the perfect combination of UiO-66 and GF. When the electrolyte droplets reach different surfaces, droplets can be fully absorbed in $3\\mathrm{~s~}$ , indicating that the surfaces of UiO-66-GF still maintain good wettability (Fig. 2h). \n\n# 3.3  \u0007Enhancements in Stability and Reversibility by UiO‑66‑GF \n\nTo verify the effectiveness of UiO-66-GF, long-term plating/stripping performances of Zn|GF|Zn, Zn|UiO-66-GF$0.6|Z\\boldsymbol{\\mathrm{n}}$ , and Zn|UiO-66-GF-2.2|Zn cells were compared. At $0.5\\mathrm{\\mA\\cm^{-2}}$ , $Z_{\\mathrm{{nlGFlZn}}}$ cell suffers from serious polarization at initial phase with poor cycling stability of $200\\mathrm{{h}}$ (Fig. S4). Zn|UiO-66-GF-0.6|Zn cell runs for $420\\mathrm{h}$ , while $Z_{ Ḋ }\\mathrm{n}\\vert\\mathrm{UiO-}66\\mathrm{-}\\mathrm{GF-}2.2\\vert Z_{\\mathrm{n}}\\$ cell can work stably for $1000\\mathrm{~h~}$ without considerable voltage fluctuation, along with the smaller overpotential compared with $Z_{\\mathrm{{nlGFlZn}}}$ cell $33~\\nu s$ . $56\\mathrm{mV}$ ). When the current density increases to $2.0\\mathrm{mA}\\mathrm{cm}^{-2}$ , \n\n![](images/0db65a17a18e288b0cb5bf5b984a1184616339f4f686f539532465eaf81f70fb.jpg) \nFig. 2   Characterizations of UiO-66-GF. SEM images of a GF, b UiO-66-GF-0.6, and c UiO-66-GF-2.2 at different magnifications. d SEM image of GF and element mapping for C, O, and Si. e SEM image of UiO-66-GF-2.2 and element mapping for C, O, and Zr. f XRD patterns of GF, UiO-66-GF-0.6, and UiO-66-GF-2.2. g FTIR spectra of GF, UiO-66-GF, and UiO-66. h Contact angle tests for three separators after 0 and 3 s \n\nZn|UiO-66-GF-2.2|Zn cell still maintains the cycling stability for more than $1650\\mathrm{h}$ (Fig. 3a), with a lower overpotential of $39~\\mathrm{mV};$ , while Zn|GF|Zn cell is short-circuited after $195\\mathrm{h}$ . Although other studies in this area demonstrate good performances, the design in this work is more efficient and profound (Fig. 3b) [36–47]. Meanwhile, hysteresis voltage of Zn|UiO-66-GF- $2.21Z\\mathrm{n}$ cell is always lower than that of Zn|GF|Zn cell (Fig. S5), favorable for uniform nucleation of zinc-ions [48]. Rate performances of symmetric cells at various current densities were compared to evaluate the effect of UiO-66-GF on reaction kinetics of zinc plating/stripping. As revealed by Fig. S6, polarization curves keep steady in each 20 cycles test. As current density increases from 0.25 to $4.0\\mathrm{mA}\\mathrm{cm}^{-2}$ , corresponding polarization voltage displays a minor increase from 56 to $82\\mathrm{mV}$ for Zn|UiO-66-GF- $\\cdot2.2|Z_{\\mathrm{{n}}}$ cell, which is considerably lower than those of $Z_{\\mathrm{{n}|G F|Z_{\\mathrm{{n}}}}}$ and $Z\\mathrm{n}|\\mathrm{UiO}{-}66{-}\\mathrm{GF}{-}0.6|Z\\mathrm{n}$ cells, indicating a stable and reversible zinc anode provided by UiO-66-GF-2.2. CEs of asymmetric cells were tested to investigate the persistence and reversibility for zinc plating/stripping. As expected, Zn|UiO-66-GF-2.2|Cu cell shows longer cycle life (350 cycles) along with lower polarization and better reversibility at $2.0\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ , compared with Zn|GF|Cu cell (80 cycles) and Zn|UiO-66-GF-0.6|Cu cell (190 cycles) (Fig. 3c, d) [49]. A lower NOP corresponds to a more stable and uniform zinc plating/stripping process and longer cycle life of cell [50]. The NOP of Zn|UiO-66-GF-2.2|Cu cell is $25~\\mathrm{mV}$ at $2.0\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ , lower than that of $Z_{\\mathrm{{nlGFlCu}}}$ cell $(63~\\mathrm{mV})$ ), demonstrating that UiO-66-GF can reduce the deposition barrier of zinc-ions (Fig. 3e) [51]. Cyclic voltammetry (CV) \n\n![](images/a774e1b48655bcc1e3b41f89e119aab543cb4e57917d361e0d26424731af7b2b.jpg) \nFig. 3   Enhancements in stability and reversibility by UiO-66-GF. a Galvanostatic charge/discharge cycling voltage profiles of $Z_{\\mathrm{{nlGFlZn}}}$ , Zn|UiO-66-GF-0.6|Zn, and $Z_{ Ḋ }\\mathrm{n}\\vert\\mathrm{UiO-}66\\mathrm{-}\\mathrm{GF-}2.2\\vert Z_{\\mathrm{n}}$ cells at a current density of $2.0\\ \\mathrm{mA}\\ \\mathrm{cm}^{-\\bar{2}}$ for $1.0\\ \\mathrm{mAh\\cm}^{-2}$ . b Comparison of cyclic reversibility obtained in this work and previous studies. c CE plots of three cells at a current density of $2.0\\mathrm{mA}\\mathrm{cm}^{-2}$ with a capacity of $1.{\\dot{0}}\\operatorname{mAh}\\operatorname{cm}^{-2}$ . d Corresponding plating/stripping profiles of three cells at the $50^{\\mathrm{th}}$ cycle. e NOPs of $Z_{\\mathrm{{nlGFlCu}}}$ and Zn|UiO-66-GF-2.2|Cu cells. f CV curves of Zn|GF|Ti and Zn|UiO-66-GF-2.2|Ti cells at $0.5~\\mathrm{mV~s^{-1}}$ . $\\mathbf{g}$ Linear polarization curves of $Z_{\\mathrm{{nlGF|Zn}}}$ and Zn|UiO-66-GF- $2.2\\vert Z_{\\mathrm{n}}$ cells. h EIS of SS|GF|SS, SS|UiO-66-GF-0.6|SS, and SS|UiO-66-GF-2.2|SS cells for the calculation of ionic conductivities. The electrical field models based on i GF and j UiO-66-GF \n\ncurves of Zn|GF|Ti and Zn|UiO-66-GF-2.2|Ti cells exhibit similar oxidation and reduction peaks, and the potential difference between A and B $(\\mathbf{B}^{\\prime})$ is NOP (Fig. 3f). Compared with Zn|GF|Ti cell, NOP of Zn|UiO-66-GF-2.2|Ti cell is reduced by $16~\\mathrm{mV},$ displaying that UiO-66-GF-2.2 effectively reduces the deposition barrier of zinc-ions [52], which is consistent with the results of Fig. 3e. \n\nThe corrosion protections of GF and UiO-66-GF for zinc anode were analyzed by linear polarization test, directly reflected by the corrosion current (Figs. 3g and S7). The corrosion currents of Zn|GF|Zn, Zn|UiO-66-GF$0.6|Z\\boldsymbol{\\mathrm{n}}$ , and $Z_{ Ḋ }\\mathrm{n}\\vert\\mathrm{UiO-}66\\mathrm{-}\\mathrm{GF-}2.2\\vert Z_{\\mathrm{n}}\\$ cells are 1.4, 1.0, and $0.9\\mathrm{\\mA\\cm^{-2}}$ , respectively. These results can be explained as UiO-66-GF regulates the flux of zinc-ions and prevents a massive aggregation of cations on zinc anode by inhibiting concentration polarization and reduces the space charge and surface barrier to accelerate the transport kinetics of zinc-ions on electrode surface [53]. Furthermore, UiO66-GF can effectively promote charge carrier transport, as confirmed by EIS. The ionic conductivities of SS|GF|SS, SS|UiO-66-GF-0.6|SS, and SS|UiO-66-GF-2.2|SS cells are 4.83, 7.91, and $20.97~\\mathrm{mS~cm^{-1}}$ , respectively, which can be attributed to the ultra-large specific surface area of UiO66 yielding an excellent transport process (Fig. 3h) [54]. COMSOL finite-element simulations were performed to illustrate the role of UiO-66-GF in regulating the interfacial electric field. Zinc anode surface with GF exhibits a non-uniformly distributed electric field and the increasing field strength leads to the continuous accumulation of charges (Fig. 3i), promoting the preferential deposition of more zinc-ions at the tip and the final formation of dendrites. When UiO-66-GF was employed, electric field of zinc anode surface was uniform (Fig. 3j), helping to achieve a uniform plating/stripping process [55]. This result is consistent with the structure of zinc anode for Zn|UiO-66-GF-2.2|Zn cell has a neat and smooth surface and cross section after cycling (Fig. S8). The mechanism of zinc deposition behavior can be verified by chronoamperometry (CA) tests (Fig. S9), where the two-dimension (2D) diffusion process of zinc-ions in Zn|GF|Zn cell is long and intense, corresponding to inhomogeneous zinc nucleation [56]. In contrast, Zn|UiO-66-GF-0.6|Zn and Zn|UiO-66- GF-2.2|Zn cells enter a stable 3D diffusion process after $30~\\mathrm{s}$ of planar diffusion and nucleation, which indicates that zinc ions are diffused uniformly and grow, likely as the confinement effect of UiO-66 inhibits the formation of dendrites [57]. \n\n# 3.4  \u0007Electrochemical Performances of Full Cells \n\nTo evaluate the role of UiO-66-GF (Fig. 4a), full cells with $\\mathbf{\\alpha}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{{\\alpha}}\\mathbf{\\alpha}\\mathbf{{\\alpha}}\\mathbf{\\alpha}\\mathbf{}\\mathrm{\\alpha}\\mathbf{}\\alpha{\\alpha}\\mathbf{}\\alpha\\mathbf{}\\alpha\\mathbf{}\\alpha\\alpha}\\mathbf{}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathbf{\\alpha}\\mathrm\\alpha{\\alpha}\\mathrm\\alpha\\mathbf{}\\alpha\\alpha\\alpha\\mathbf{}\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\mathbf\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\alpha\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r a n\\ c o r$ cathode (Fig. S10) were assembled. CV tests were performed to investigate the redox reaction and reversibility during the charge/discharge process. CV curves have the same shape and peak position, indicating that UiO-66 does not change the electrochemical process (Figs. 4b and S11). Two groups of redox peaks represent reversible (de) intercalation of hydrogen ions and zinc-ions from $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ , respectively [58]. Compared with $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell, $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell has higher peak current density and smaller voltage gap, demonstrating a high electrochemical activity and a lower polarization [59]. Charge transfer resistance $(R_{\\mathrm{ct}})$ of $\\mathrm{Zn|UiO-66-GF-2.2|MnO_{2}}$ cell $(133.6\\Omega)$ is lower than those of $\\mathbf{Zn}|\\mathbf{GF}|\\mathbf{MnO}_{2}$ $(361.2~\\Omega)$ and $\\mathrm{Zn|UiO-66\\mathrm{-}G F\\mathrm{-}0.6|M n O_{2}}$ cells $(251.4\\Omega)$ (Figs. $\\scriptstyle4\\ c$ and S12), which confirms fast electrochemical kinetics [60]. Rate performance tests exhibit that the capacities of Zn|UiO-66- GF $-0.6|\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ and $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cells basically return to the initial value after cycling, with better reaction kinetics than that of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell (Figs. 4d and S13) [61]. Overall, $\\mathrm{Zn|UiO-66-GF-2.2|MnO_{2}}$ cell has higher capacity and more stable voltage platforms (Figs. 4e and S14). Furthermore, GITT measurements were performed to verify the effect of UiO-66 on zinc-ions transfer. Hysteresis voltage generated after intermittency of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell is almost twice that of $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell, reflecting that electrochemical reaction resistance is smaller in $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell (Fig. 4f) [62]. The zinc-ions diffusion coefficient $(D_{\\mathrm{Zn}})$ of $\\mathrm{Zn|UiO-66-GF-2.2|MnO_{2}}$ cell is higher than that of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell $(1.30906\\times10^{-10}\\nu s$ $1.46465\\times10^{-11}{\\mathrm{cm}}^{2}{\\mathrm{s}}^{-1})$ , which indicates UiO-66-GF-2.2 accelerates the transport of zinc ions at the interface of $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ (Fig. $\\mathrm{4g\\dot{}}$ [63]. \n\nIn addition, long-term cycling stabilities of cells at different current densities were also evaluated. Initial specific discharge capacity of $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell is 198.5 mAh $\\mathbf{g}^{-1}$ at $0.5\\mathrm{A}\\mathrm{g}^{-1}$ along with $81.9\\%$ capacity retention after 1000 cycles, which is higher than those of Zn|UiO-66- GF- $-0.6|\\mathrm{MnO}_{2}$ cell $\\mathrm{^{186.3mAhg^{-1}}}$ , $68.2\\%$ and $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell $\\mathrm{(165~mAh~g^{-1}}$ , $58.5\\%$ (Fig. S15). When current density increases to $1.0\\mathrm{~A~g^{-1}}$ , specific discharge capacity of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell decreases after only 200 cycles (Fig. 4h), while the $\\mathrm{Zn|UiO–66–GF–0.6|MnO_{2}}$ is stable for 600 cycles (Fig. S16). $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell still provides high discharge capacity after 1000 cycles $(186.55\\mathrm{mAh\\g^{-1}},$ along with a high capacity retention $(85\\%)$ . Meanwhile, zinc anode of $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell does not exhibit significant surface changes after cycling and there are no obvious dendrites in cross-sectional SEM image (Fig. S17), reflecting UiO-66-GF which enables more uniform flux of zinc-ions, promoting uniform nucleation and deposition, and eliminating dendrites [64]. $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell also demonstrates excellent self-discharge resistance, owing to the protection of the electrodes by UiO-66-GF-2.2 [65]. \n\n![](images/aca008d5462b2c1a6e4913ff44373f1ec8df5c5a1a76642a04e9d460bb77fa19.jpg) \nFig. 4   Electrochemical performances of full cells. a Electrochemical behavior of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell. b CV curves of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ and Zn|UiO$66{\\cdot}\\mathrm{GF}{-}2.2|\\mathrm{MnO}_{2}$ cells. c EIS spectra and corresponding equivalent circuit diagram of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ and Zn|UiO-66-GF- $2.2|\\mathbf{MnO}_{2}$ cells. d Rate performances of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ and Zn|UiO-66-GF- $2.2|\\mathrm{MnO}_{2}$ cells. e Charge/discharge profiles of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ and Zn|UiO-66-GF- $2.2|\\mathrm{MnO}_{2}$ cells at $0.3\\mathrm{~A~g^{-1}}$ . f GITT curves and $\\mathbf{g}$ zinc-ions diffusion coefficients during discharging of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ and Zn|UiO-66-GF- $2.2|\\mathrm{MnO}_{2}$ cells. h Cycling performances and CEs of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ and $\\mathrm{Zn|UiO-66-GF-2.2|MnO_{2}}$ cells at $1.0\\mathrm{A}\\mathrm{g}^{-1}$ . i Cycling performances after resting for $24\\mathrm{h}$ of three cells at $0.5\\mathrm{Ag}$ .−1 \n\nAfter resting for $24\\mathrm{h}$ , $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell maintains a sufficient discharge capacity due to self-discharge reduction [66]. Specific discharge capacity of Zn|UiO-66- $\\mathrm{GF}{-}2.2|\\mathrm{MnO}_{2}$ ( $141\\mathrm{\\mAh\\g^{-1}},$ ) is considerably higher than those of $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ $31.5\\mathrm{mAh}\\mathrm{g}^{-1},$ ) and Zn|UiO-66-GF$0.6|\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ $93.7\\mathrm{~mAh~g^{-1}},$ cells after 400 cycles, implying that UiO-66-GF-2.2 can effectively improve the stability and service life of cells (Fig. 4i). \n\n# 3.5  \u0007Characterization of Zinc Anode during Repeated Cycling and Mechanism Analysis \n\nTo elucidate the mechanism of UiO-66-GF on the inhibition of zinc dendrites and corrosion resistance, XRD patterns of zinc anodes before and after cycling were measured (Fig. 5a). The diffraction intensity of (101) plane of zinc anode becomes higher in $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ cell after cycling, indicating that zinc-ions tend to deposit in the vertical direction. However, zinc anode in $\\mathrm{Zn|UiO–66–GF–2.2|MnO_{2}}$ cell shows a higher (002) preferred crystal orientation and a significantly higher (002)/(101) diffraction intensity ratio after cycling, proving that zinc-ions tend to deposit in the horizontal direction (Fig. 5b). The atomic arrangement and interfacial charge density distribution of the (002) and (101) planes is different. UiO-66-GF induces the growth of zinc-ions in (002) plane, culminating in dendrite-free zinc deposition (Fig. 5c-d) [67]. Further analysis of XRD data exhibits that UiO-66-GF-2.2 inhibits the formation of by-products such as $\\mathrm{ZnSO_{4}{\\cdot}3Z n(O H)_{2}{\\cdot}4H_{2}O}$ (JCPDS No. 00-009-0204), which also corresponds to EDX results (Fig. S18). In addition, adsorption energies between $\\mathrm{~H~}$ and $Z\\mathrm{n}$ (002), (100), and (101) crystal planes were analyzed using DFT calculations (Fig. 5e) [68]. Zn (002) plane demonstrates lower adsorption energy for $\\mathrm{~H~}(-1.731\\ \\mathrm{eV})$ than that of (100) $(-1.954\\ \\mathrm{eV})$ and (101) planes $(-2.369\\mathrm{eV})$ , indicating a weaker adsorption of $\\mathrm{\\DeltaH}$ by (002) plane, which is beneficial to improve corrosion resistance and suppress HER. The catalytic activities of HER on different crystal planes of zinc were evaluated by $\\Delta G_{\\mathrm{H}}$ . Theoretically, a large $\\Delta G_{\\mathrm{H}}$ implies a high reaction overpotential of HER. $\\Delta G_{\\mathrm{H}}$ of Zn (002) is $0.759\\mathrm{eV}$ , which is larger than those of $Z\\mathrm{n}$ (100) $(0.536~\\mathrm{eV})$ and $Z\\mathrm{n}$ (101) planes $(0.121\\ \\mathrm{eV})$ , indicating that the construction of $Z\\mathrm{n}$ (002) plane helps inhibit the side reactions. \n\n![](images/0276dcd3b14bfd865aefa53bc28a560ff05de9ff4d3cb5363b14b3f9b54c226d.jpg) \nFig. 5   Characterization of zinc anode during repeated cycling and mechanism analysis. a XRD patterns of pristine Zn, $\\mathrm{Zn}|\\mathrm{GF}|\\mathrm{MnO}_{2}$ , and Zn|UiO66-GF- $2.2|\\mathbf{MnO}_{2}$ cells after cycling. b Schematic illustration of preferred orientations of $Z\\mathrm{n}$ crystal plane. Mechanism comparison of the deposition processes for zinc anodes using c GF and d UiO-66-GF-2.2. e Adsorption energies between H and $Z\\mathrm{n}$ (002), (100), and (101) crystal planes \n\nIn general, HER not only leads to a local $\\mathrm{pH}$ increase in the electrolyte, but also continuously consumes the water in the electrolyte, eventually leading to increases in the concentrations of $\\mathrm{OH^{-}}$ and ${\\mathrm{SO}}_{4}^{2-}$ . UiO-66-GF-2.2 demonstrates preferential orientation of (002) plane. DFT calculations exhibit a weaker adsorption of $\\mathrm{~H~}$ by (002) plane. Therefore, UiO-66-GF-2.2 can effectively inhibit HER and further reducing the concentration of harmful anions in the electrolyte. Meanwhile, after using UiO-66-GF-2.2, the flux of zinc-ions becomes uniform, which makes the concentration of zinc-ions reach the surface of zinc anode more consistent. Uniform concentration of zinc-ions in the electrolyte near anode can reduce the generation of electrochemical corrosion products, thereby slowing down the generation of passivation layers, accelerating the rate of ion transfer, and enabling durable AZIBs. \n\n# 4  \u0007Conclusion \n\nIn conclusion, a separator (UiO-66-GF) modified by Zrbased MOF for robust AZIBs is successfully proposed. UiO66 has large specific surface area and abundant pore structure, which enables the electrolyte to penetrate uniformly and effectively reduces the local current density. Benefiting from the well-filled interspace, the sufficient contact of zinc anode with electrolyte not only reduces the NOP, but also uniformizes the electric field distribution to tune the zinc deposition. UiO-66-GF effectively enhances transport ability of charge carriers and demonstrates preferential orientation of (002) crystal plane due to the uniform interfacial charge of (002) deposition, which is favorable for the growth of zinc along the horizontal direction. Furthermore, Zn|UiO-66-GF$2.21Z\\mathrm{n}$ cell enables reversible plating/stripping with long cycle life over $1650\\mathrm{h}$ at $2.0\\mathrm{\\mA\\cm^{-2}}$ , and excellent longterm stability with capacity retention of $85\\%$ is obtained for Zn|UiO-66-GF- $2.2|\\mathbf{MnO}_{2}$ cell after 1000 cycles at $1.0\\mathrm{A}$ $\\mathbf{g}^{-1}$ . This work provides a facile and economical approach for separator modifications, which is beneficial to further promote the practical application of AZIBs. \n\nAcknowledgements  This work was supported by the National Natural Science Foundation of China (Nos. 51872090, 51972346), the Hebei Natural Science Fund for Distinguished Young Scholar (No. E2019209433), the Natural Science Foundation of Hebei Province (No. E2020209151), the Hunan Natural Science Fund for Distinguished Young Scholar (2021JJ10064), and the Program of Youth Talent Support for Hunan Province (2020RC3011). This work was carried out in part using computing resources at the High-Performance Computing Center of Central South University. The work was carried out at Shanxi Supercomputing Center of China, and the calculations were performed on TianHe-2. \n\nFunding  Open access funding provided by Shanghai Jiao Tong University. \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\nSupplementary Information  The online version contains supplementary material available at https://​doi.​org/​10.​1007/ s40820-​022-​00960-z. \n\n# References \n\n1.\t N. Guo, W. Huo, X. Dong, Z. Sun, Y. Lu et al., A review on 3D zinc anodes for zinc ion batteries. Small Methods 6(9), 2200597 (2022). https://​doi.​org/​10.​1002/​smtd.​20220​0597 \n\n2.\t P. Ruan, X. Xu, D. Zheng, X. Chen, X. Yin et al., Promoting reversible dissolution/deposition of $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ for high-energydensity zinc batteries via enhancing cut-off voltage. Chemsuschem 15(18), 202201118 (2022). https://​doi.​org/​10.​1002/​ cssc.​20220​1118 \n3.\t X. Li, Z. Chen, Y. Yang, S. Liang, B. Lu et al., The phosphate cathodes for aqueous zinc-ion batteries. Inorg. Chem. Front. 9(16), 3986–3998 (2022). https://​doi.​org/​10.​1039/​D2QI0​ 1083F \n4.\t B. Li, X. Zhang, T. Wang, Z. He, B. Lu et  al., Interfacial engineering strategy for high-performance zinc metal anode. Nano-Micro Lett. 14, 6 (2022). https://​doi.​org/​10.​1007/​ s40820-​021-​00764-7 \n5.\t Z. Liu, Y. Yang, S. Liang, B. Lu, J. Zhou et al., pH-buffer contained electrolyte for self-adjusted cathode-free $\\mathbf{Z}\\mathbf{n}\\mathbf{-}\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ batteries with coexistence of dual mechanisms. Small Struct. 2(11), 2100119 (2021). https://​doi.​org/​10.​1002/​sstr.​20210 0119 \n6.\t C. Li, X. Xie, H. Liu, P. Wang, C. Deng et al., Integrated “allin-one” strategy to stabilize zinc anodes for high-performance zinc-ion batteries. Natl. Sci. Rev. 9(3), 177 (2022). https://​doi. org/​10.​1093/​nsr/​nwab1​77 \n7.\t Y. Geng, L. Pan, Z. Peng, Z. Sun, H. Lin et al., Electrolyte additive engineering for aqueous Zn ion batteries. Energy Storage Mater. 51, 733–755 (2022). https://​doi.​org/​10.​1016/j. ensm.​2022.​07.​017 \n8.\t C. Xie, Y. Li, Q. Wang, D. Sun, Y. Tang et al., Issues and solutions toward zinc anode in aqueous zinc-ion batteries: a mini review. Carbon Energy 2(4), 540–560 (2020). https://​doi.​org/ 10.​1002/​cey2.​67 \n9.\t P. Ruan, S. Liang, B. Lu, H. Fan, J. Zhou et al., Design strategies for high-energy-density aqueous zinc batteries. Angew. Chem. Int. Ed. 61(17), 202200598 (2022). https://​doi.​org/​10. 1002/​anie.​20220​0598 \n10.\t Y. Zhang, G. Yang, M.L. Lehmann, C. Wu, L. Zhao et al., Separator effect on zinc electrodeposition behavior and its implication for zinc battery lifetime. Nano Lett. 21(24), 10446–10452 (2021). https://​doi.​org/​10.​1021/​acs.​nanol​ett.​ 1c037​92 \n11.\t G.A. Elia, J.B. Ducros, D. Sotta, V. Delhorbe, A. Brun et al., Polyacrylonitrile separator for high-performance aluminum batteries with improved interface stability. ACS Appl. Mater. Interfaces 9(44), 38381–38389 (2017). https://​doi.​org/​10. 1021/​acsami.​7b093​78 \n12.\t J. Cao, D. Zhang, X. Zhang, M. Sawangphruk, J. Qin et al., A universal and facile approach to suppress dendrite formation for a Zn and Li metal anode. J. Mater. Chem. A 8(18), 9331–9344 (2020). https://​doi.​org/​10.​1039/​d0ta0​2486d \n13.\t C. Peng, Y. Zhang, S. Yang, L. Zhang, Z. Wang et al., Flexible zincophilic polypyrrole paper interlayers for stable Zn metal anodes: higher surface flatness promises better reversibility. Nano Energy 98, 107329 (2022). https://​doi.​org/​10.​1016/j. nanoen.​2022.​107329 \n14.\t Z. Hou, Y. Gao, H. Tan, B. Zhang, Realizing high-power and high-capacity zinc/sodium metal anodes through interfacial chemistry regulation. Nat. Commun. 12, 3083 (2021). https://​ doi.​org/​10.​1038/​s41467-​021-​23352-0 \n15.\t R. Yuksel, O. Buyukcakir, P.K. Panda, S.H. Lee, Y. Jiang et al., Necklace-like nitrogen-doped tubular carbon 3D frameworks for electrochemical energy storage. Adv. Funct. Mater. 30(10), 1909725 (2020). https://​doi.​org/​10.​1002/​adfm.​20190​ 9725 \n16.\t T. Liu, J. Hong, J. Wang, Y. Xu, Y. Wang, Uniform distribution of zinc ions achieved by functional supramolecules for stable zinc metal anode with long cycling lifespan. Energy Storage Mater. 45, 1074–1083 (2022). https://​doi.​org/​10.​1016/j.​ensm.​ 2021.​11.​002 \n17.\t Y. Liang, D. Ma, N. Zhao, Y. Wang, M. Yang et al., Novel concept of separator design: efficient ions transport modulator enabled by dual-interface engineering toward ultra-stable Zn metal anodes. Adv. Funct. Mater. 32(25), 2112936 (2022). https://​doi.​org/​10.​1002/​adfm.​20211​2936 \n18.\t Y. Guo, W. Cai, Y. Lin, Y. Zhang, S. Luo et al., An ion redistributor enabled by cost-effective weighing paper interlayer for dendrite free aqueous zinc-ion battery. Energy Storage Mater. 50, 580–588 (2022). https://​doi.​org/​10.​1016/j.​ensm.​2022.​06. 001 \n19.\t P. Cao, H. Zhou, X. Zhou, Q. Du, J. Tang et  al., Stabilizing zinc anodes by a cotton towel separator for aqueous zincion batteries. ACS Sustain. Chem. Eng. 10(26), 8350–8359 (2022). https://​doi.​org/​10.​1021/​acssu​schem​eng.​2c011​33 \n20.\t G. Gao, Y. Wang, S. Wang, R. Yang, Y. Chen et al., Stepped channels integrated lithium-sulfur separator via photoinduced multidimensional fabrication of metal-organic frameworks. Angew. Chem. Int. Ed. 60(18), 10147–10154 (2021). https:// doi.​org/​10.​1002/​anie.​20201​6608 \n21.\t R. Rego, M. Kurkuri, M. Kigga, A comprehensive review on water remediation using UiO-66 MOFs and their derivatives. Chemosphere 302, 134845 (2022). https://​doi.​org/​10.​1016/j.​ chemo​sphere.​2022.​134845 \n22.\t M. Sun, J. Li, H. Yuan, X. Zeng, J. Lan et al., Fast $\\mathrm{Li^{+}}$ transport pathways of quasi-solid-state electrolyte constructed by 3D MOF composite nanofibrous network for dendrite-free lithium metal battery. Mater. Today Energy 29, 101117 (2022). https://​doi.​org/​10.​1016/j.​mtener.​2022.​101117 \n23.\t X. Liu, F. Yang, W. Xu, Y. Zeng, J. He et al., Zeolitic imidazolate frameworks as $Z\\mathrm{n}^{2+}$ modulation layers to enable dendrite-free $Z\\mathrm{n}$ anodes. Adv. Sci. 7(21), 2002173 (2020). https://​doi.​org/​10.​1002/​advs.​20200​2173 \n24.\t L. Wang, Y. Zhu, C. Du, X. Ma, C. Cao, Advances and challenges in metal-organic framework derived porous materials for batteries and electrocatalysis. J. Mater. Chem. A 8(47), 24895–24919 (2020). https://​doi.​org/​10.​1039/​d0ta0​8311a \n25.\t K. Wu, J. Yi, X. Liu, Y. Sun, J. Cui et  al., Regulating Zn deposition via an artificial solid-electrolyte interface with aligned dipoles for long life Zn anode. Nano-Micro Lett. 13, 79 (2021). https://​doi.​org/​10.​1007/​s40820-​021-​00599-2 \n26.\t Y. Fu, Q. Wei, G. Zhang, X. Wang, J. Zhang et al., High-performance reversible aqueous Zn-ion battery based on porous $\\mathbf{M}\\mathbf{n}\\mathrm{O}_{\\mathrm{x}}$ nanorods coated by MOF-derived N-doped carbon. Adv. Energy Mater. 8(26), 1801445 (2018). https://​doi.​org/​ 10.​1002/​aenm.​20180​1445 \n27.\t S. Wang, W. Morris, Y. Liu, C.M. McGuirk, Y. Zhou et al., Surface-specific functionalization of nanoscale metal-organic frameworks. Angew. Chem. Int. Ed. 54(49), 14738–14742 (2015). https://​doi.​org/​10.​1002/​anie.​20150​6888 \n28.\t F. Ahmadijokani, R. Mohammadkhani, S. Ahmadipouya, A. Shokrgozar, M. Rezakazemi et al., Superior chemical stability of UiO-66 metal-organic frameworks (MOFs) for selective dye adsorption. Chem. Eng. J. 399, 125346 (2020). https://​doi.​org/​ 10.​1016/j.​cej.​2020.​125346 \n29.\t Y. Jiang, G. Cheng, Y. Li, Z. He, J. Zhu et  al., Promoting vanadium redox flow battery performance by ultra-uniform $\\mathrm{ZrO}_{2}@\\mathrm{C}$ from metal-organic framework. Chem. Eng. J. 415, 129014 (2021). https://​doi.​org/​10.​1016/j.​cej.​2021.​129014 \n30.\t W. Li, J. Liu, C. Yan, Multi-walled carbon nanotubes used as an electrode reaction catalyst for $\\mathrm{VO_{2}}^{+}/\\mathrm{VO}^{2+}$ for a vanadium redox flow battery. Carbon 49(11), 3463–3470 (2011). https://​ doi.​org/​10.​1016/j.​carbon.​2011.​04.​045 \n31.\t H . Z h o u , Y. S h e n , J . X i , X . Q i u , L . C h e n , $\\mathbf{\\boldsymbol{Z}r O}_{2}$ -nanoparticle-modified graphite felt: bifunctional effects on vanadium flow batteries. ACS Appl. Mater. Interfaces 8(24), 15369–15378 (2016). https://​doi.​org/​10.​1021/​acsami. 6b037​61 \n32.\t C. Chen, D. Chen, S. Xie, H. Quan, X. Luo et al., Adsorption behaviors of organic micropollutants on zirconium metalorganic framework UiO-66: analysis of surface interactions. ACS Appl. Mater. Interfaces 9(46), 41043–41054 (2017). https://​doi.​org/​10.​1021/​acsami.​7b134​43 \n33.\t X. Min, X. Wu, P. Shao, Z. Ren, L. Ding et al., Ultra-high capacity of lanthanum-doped UiO-66 for phosphate capture: unusual doping of lanthanum by the reduction of coordination number. Chem. Eng. J. 358, 321–330 (2019). https://​doi.​org/​ 10.​1016/j.​cej.​2018.​10.​043 \n34.\t Q. Li, F. Zeng, Y. Guan, Z. Jin, Y. Huang et al., Poly (dimethylsiloxane) modified lithium anode for enhanced performance of lithium-sulfur batteries. Energy Storage Mater. 13, 151–159 (2018). https://​doi.​org/​10.​1016/j.​ensm.​2018.​01.​002 \n35.\t Z. Man, Y. Meng, X. Lin, X. Dai, L. Wang et al., Assembling UiO- $66@\\mathrm{TiO}_{2}$ nanocomposites for efficient photocatalytic degradation of dimethyl sulfide. Chem. Eng. J. 431, 133952 (2022). https://​doi.​org/​10.​1016/j.​cej.​2021.​133952 \n36.\t X. Yang, C. Li, Z. Sun, S. Yang, Z. Shi et  al., Interfacial manipulation via in-situ grown ZnSe overlayer toward highly reversible Zn metal anodes. Adv. Mater. 33(52), 2105951 (2021). https://​doi.​org/​10.​21203/​rs.3.​rs-​400312/​v1 \n37.\t W. Deng, N. Zhang, X. Wang, Hybrid interlayer enables dendrite-free and deposition-modulated zinc anodes. Chem. Eng. J. 432, 134378 (2022). https://​doi.​org/​10.​1016/j.​cej.​2021.​ 134378 \n38.\t J. Yan, M. Ye, Y. Zhang, Y. Tang, C. Li, Layered zirconium phosphate-based artificial solid electrolyte interface with zinc ion channels towards dendrite-free Zn metal anodes. Chem. Eng. J. 432, 134227 (2022). https://​doi.​org/​10.​1016/j.​cej.​2021. 134227 \n39.\t Y. Wang, Y. Liu, H. Wang, S. Dou, W. Gan et al., MOF-based ionic sieve interphase for regulated $Z\\mathrm{n}^{2+}$ flux toward dendritefree aqueous zinc-ion batteries. J. Mater. Chem. A 10(8), 4366–4375 (2022). https://​doi.​org/​10.​1039/​d1ta1​0245a \n40.\t H. He, H. Tong, X. Song, X. Song, J. Liu, Highly stable Zn metal anodes enabled by atomic layer deposited $\\mathrm{Al}_{2}\\mathrm{O}_{3}$ coating for aqueous zinc-ion batteries. J. Mater. Chem. A 8(16), 7836–7846 (2020). https://​doi.​org/​10.​1039/​d0ta0​0748j \n41.\t Z. Miao, Q. Liu, W. Wei, X. Zhao, M. Du et al., Unveiling unique steric effect of threonine additive for highly reversible Zn anode. Nano Energy 97, 107145 (2022). https://​doi.​org/​10. 1016/j.​nanoen.​2022.​107145 \n42.\t Z. Cao, X. Zhu, D. Xu, P. Dong, M.O.L. Chee et al., Eliminating Zn dendrites by commercial cyanoacrylate adhesive for zinc ion battery. Energy Storage Mater. 36, 132–138 (2021). https://​doi.​org/​10.​1016/j.​ensm.​2020.​12.​022 \n43.\t L. Dong, W. Yang, W. Yang, H. Tian, Y. Huang et al., Flexible and conductive scaffold-stabilized zinc metal anodes for ultralong-life zinc-ion batteries and zinc-ion hybrid capacitors. Chem. Eng. J. 384, 123355 (2020). https://​doi.​org/​10.​1016/j.​ cej.​2019.​123355 \n44.\t C. Li, Z. Sun, T. Yang, L. Yu, N. Wei et al., Directly grown vertical graphene carpets as Janus separators toward stabilized Zn metal anodes. Adv. Mater. 32(33), 2003425 (2020). https:// doi.​org/​10.​1002/​adma.​20200​3425 \n45.\t C. Deng, X. Xie, J. Han, Y. Tang, J. Gao et al., A sieve-functional and uniform-porous kaolin layer toward stable zinc metal anode. Adv. Funct. Mater. 30(21), 2000599 (2020). https://​doi.​org/​10.​1002/​adfm.​20200​0599 \n46.\t Z. Wang, L. Dong, W. Huang, H. Jia, Q. Zhao et al., Simultaneously regulating uniform $Z\\mathrm{n}^{2+}$ flux and electron conduction by MOF/rGO interlayers for high-performance Zn anodes. Nano-Micro Lett. 13, 73 (2021). https://​doi.​org/​10.​1007/​ s40820-​021-​00594-7 \n47.\t B.S. Lee, S. Cui, X. Xing, H. Liu, X. Yue et  al., Dendrite suppression membranes for rechargeable zinc batteries. ACS Appl. Mater. Interfaces 10(45), 38928–38935 (2018). https://​ doi.​org/​10.​1021/​acsami.​8b140​22 \n48.\t Q. Yang, G. Liang, Y. Guo, Z. Liu, B. Yan et al., Do zinc dendrites exist in neutral zinc batteries: a developed electrohealing strategy to in situ rescue in-service batteries. Adv. Mater. 31(43), 1903778 (2019). https://​doi.​org/​10.​1002/​adma.​20190​ 3778 \n49.\t Y. Zeng, P. Sun, Z. Pei, Q. Jin, X. Zhang et al., Nitrogen-doped carbon fibers embedded with zincophilic Cu nanoboxes for stable Zn-metal anodes. Adv. Mater. 34(18), 2200342 (2022). https://​doi.​org/​10.​1002/​adma.​20220​0342 \n50.\t W. Zhou, M. Chen, Q. Tian, J. Chen, X. Xu et al., Cottonderived cellulose film as a dendrite-inhibiting separator to stabilize the zinc metal anode of aqueous zinc ion batteries. Energy Storage Mater. 44, 57–65 (2022). https://​doi.​org/​10. 1016/j.​ensm.​2021.​10.​002 \n51.\t Y. Zeng, X. Zhang, R. Qin, X. Liu, P. Fang et al., Dendritefree zinc deposition induced by multifunctional CNT frameworks for stable flexible $Z\\mathrm{n}$ -ion batteries. Adv. Mater. 31(36), 1903675 (2019). https://​doi.​org/​10.​1002/​adma.​20190​3675 \n52.\t Y. Chu, S. Zhang, S. Wu, Z. Hu, G. Cui et al., In situ built interphase with high interface energy and fast kinetics for high performance Zn metal anodes. Energy Environ. Sci. 14(6), 3609–3620 (2021). https://​doi.​org/​10.​1039/​d1ee0​0308a \n53.\t X. Pu, B. Jiang, X. Wang, W. Liu, L. Dong et al., High-performance aqueous zinc-ion batteries realized by MOF materials. Nano-Micro Lett. 12, 152 (2020). https://​doi.​org/​10.​1007/ s40820-​020-​00487-1 \n54.\t L. Hong, X. Wu, L. Wang, M. Zhong, P. Zhang et al., Highly reversible zinc anode enabled by a cation-exchange coating with $Z\\mathrm{n}$ -ion selective channels. ACS Nano 16(4), 6906–6915 (2022). https://​doi.​org/​10.​1021/​acsna​no.​2c023​70 \n55.\t W. Shang, Q. Li, F. Jiang, B. Huang, J. Song, B. Zn et al., $\\mathrm{I}_{2}$ battery’s performance by coating a zeolite-based cationexchange protecting layer. Nano-Micro Lett. 14, 82 (2022). https://​doi.​org/​10.​1007/​s40820-​022-​00825-5 \n56.\t J. Zhao, J. Zhang, W. Yang, B. Chen, Z. Zhao et al., “Waterin-deep eutectic solvent” electrolytes enable zinc metal anodes for rechargeable aqueous batteries. Nano Energy 57, 625–634 (2019). https://​doi.​org/​10.​1016/j.​nanoen.​2018.​12.​086 \n57.\t T. Wang, Q. Xi, Y. Li, H. Fu, Y. Hua et al., Regulating dendrite-free zinc deposition by red phosphorous-derived artificial protective layer for zinc metal batteries. Adv. Sci. 9(18), 2200155 (2022). https://​doi.​org/​10.​1002/​advs.​20220​0155 \n58.\t X. Chen, P. Ruan, X. Wu, S. Liang, J. Zhou, Crystal structures, reaction mechanisms, and optimization strategies of $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ cathode for aqueous rechargeable zinc batteries. Acta Phys. Chim. Sin. 38(12), 2111003 (2022). https://​doi.​org/​10.​3866/ pku.​Whxb2​02111​003 \n59.\t H. Yu, Y. Chen, H. Wang, X. Ni, W. Wei et al., Engineering multi-functionalized molecular skeleton layer for dendrite-free and durable zinc batteries. Nano Energy 99, 107426 (2022). https://​doi.​org/​10.​1016/j.​nanoen.​2022.​107426 \n60.\t D. Zuo, S. Song, C. An, L. Tang, Z. He et  al., Synthesis of sandwich-like structured $S\\mathrm{n}/\\mathrm{SnO}_{\\mathrm{x}}@$ MXene composite through in-situ growth for highly reversible lithium storage. Nano Energy 62, 401–409 (2019). https://​doi.​org/​10.​1016/j. nanoen.​2019.​05.​062 \n61.\t H. Moon, K.H. Ha, Y. Park, J. Lee, M.S. Kwon et al., Direct proof of the reversible dissolution/deposition of $\\mathrm{Mn}^{2+}/\\mathrm{Mn}^{4+}$ for mild-acid $\\mathbf{Z}\\mathrm{n}\\mathbf{-}\\mathbf{M}\\mathrm{n}\\mathbf{O}_{2}$ batteries with porous carbon interlayers. Adv. Sci. 8(6), 2003714 (2021). https://​doi.​org/​10.​1002/​ advs.​20200​3714 \n62.\t J. Hao, J. Long, B. Li, X. Li, S. Zhang et al., Toward high-performance hybrid $Z\\mathrm{n}$ -based batteries via deeply understanding their mechanism and using electrolyte additive. Adv. Funct. Mater. 29(34), 1903605 (2019). https://​doi.​org/​10.​1002/​adfm. 20190​3605 \n63.\t P. Ruan, X. Xu, X. Gao, J. Feng, L. Yu et al., Achieving longcycle-life Zn-ion batteries through interfacial engineering of $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ -polyaniline hybrid networks. Sustain. Mater. Technol. 28, 00254 (2021). https://​doi.​org/​10.​1016/j.​susmat.​2021. e00254 \n64.\t Y. Tang, C. Liu, H. Zhu, X. Xie, J. Gao et al., Ion-confinement effect enabled by gel electrolyte for highly reversible dendritefree zinc metal anode. Energy Storage Mater. 27, 109–116 (2020). https://​doi.​org/​10.​1016/j.​ensm.​2020.​01.​023 \n65.\t Y. Liu, X. Zhou, X. Wang, G. Chen, R. Liu et al., Hydrated titanic acid as an ultralow-potential anode for aqueous zinc-ion full batteries. Chem. Eng. J. 420, 129629 (2021). https://​doi. org/​10.​1016/j.​cej.​2021.​129629 \n66.\t Z. Huang, T. Wang, H. Song, X. Li, G. Liang et al., Effects of anion carriers on capacitance and self-discharge behaviors of zinc ion capacitors. Angew. Chem. Int. Ed. 60(2), 1011–1021 (2021). https://​doi.​org/​10.​1002/​anie.​20201​2202 \n67.\t D. Yuan, J. Zhao, H. Ren, Y. Chen, R. Chua et al., Anion texturing towards dendrite-free Zn anode for aqueous rechargeable batteries. Angew. Chem. Int. Ed. 60(13), 7213–7219 (2021). https://​doi.​org/​10.​1002/​anie.​20201​5488 \n68.\t Y. Zhong, Z. Cheng, H. Zhang, J. Li, D. Liu et al., Monosodium glutamate, an effective electrolyte additive to enhance cycling performance of Zn anode in aqueous battery. Nano Energy 98, 107220 (2022). https://​doi.​org/​10.​1016/j.​nanoen. 2022.​107220 " + }, + { + "id": "10.1016_S1872-2067(21)63883-4", + "DOI": "10.1016/S1872-2067(21)63883-4", + "DOI Link": "http://dx.doi.org/10.1016/S1872-2067(21)63883-4", + "Relative Dir Path": "mds/10.1016_S1872-2067(21)63883-4", + "Article Title": "Integration of 2D layered CdS/WO3 S-scheme heterojunctions and metallic Ti3C2 MXene-based Ohmic junctions for effective photocatalytic H2 generation", + "Authors": "Bai, JX; Shen, RC; Jiang, ZM; Zhang, P; Li, YJ; Li, X", + "Source Title": "CHINESE JOURNAL OF CATALYSIS", + "Abstract": "The rapid recombination of photo-generated electron-hole pairs, insufficient active sites, and strong photocorrosion have considerably restricted the practical application of CdS in photocatalytic fields. Herein, we designed and constructed a 2D/2D/2D layered heterojunction photocatalyst with cascaded 2D coupling interfaces. Experiments using electron spin resonullce spectroscopy, ultraviolet photoelectron spectroscopy, and in-situ irradiation X-ray photoelectron spectroscopy were conducted to confirm the 2D layered CdS/WO3 step-scheme (S-scheme) heterojunctions and CdS/MX ohmic junctions. Impressively, it was found that the strong interfacial electric fields in the S-scheme heterojunction photocatalysts could effectively promote spatially directional charge separation and transport between CdS and WO3 nullosheets. In addition, 2D Ti3C2 MXene nullosheets with a smaller work function and excellent metal conductivity when used as a co-catalyst could build ohmic junctions with CdS nullosheets, thus providing a greater number of electron transfer pathways and hydrogen evolution sites. Results showed that the highest visible-light hydrogen evolution rate of the optimized MX-CdS/WO3 layered multi-heterostructures could reach as high as 27.5 mmol/g/h, which was 11.0 times higher than that of pure CdS nullosheets. Notably, the apparent quantum efficiency reached 12.0% at 450 nm. It is hoped that this study offers a reliable approach for developing multifunctional photocatalysts by integrating S-scheme and ohmic-junction built-in electric fields and rationally designing a 2D/2D interface for efficient light-to-hydrogen fuel production. (C) 2022, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.", + "Times Cited, WoS Core": 324, + "Times Cited, All Databases": 339, + "Publication Year": 2022, + "Research Areas": "Chemistry; Engineering", + "UT (Unique WOS ID)": "WOS:000746696100016", + "Markdown": "# Article \n\n# Integration of 2D layered CdS/WO3 S‐scheme heterojunctions and metallic Ti3C2 MXene‐based Ohmic junctions for effective photocatalytic $\\mathbf{H}_{2}$ generation \n\nJunxian Bai a,†, Rongchen Shen a,†, Zhimin Jiang a, Peng Zhang b, Youji Li c, Xin Li a,\\* \n\na Institute of Biomass Engineering, Key Laboratory of Energy Plants Resource and Utilization, Ministry of Agriculture and Rural Affairs, South China \nAgricultural University, Guangzhou 510642, Guangdong, China \nb State Centre for International Cooperation on Designer Low‐Carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, \nZhengzhou University, Zhengzhou 450001, Henan, China \nc College of Chemistry and Chemical Engineering, Jishou University, Jishou 416000, Hunan, China \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nArticle history: Received 8 May 2021 Accepted 26 June 2021 Available online 3 January 2022 \n\nKeywords: \nPhotocatalytic hydrogen evolution \n2D layered S‐scheme heterojunction \nCdS nanosheets \n$\\mathsf{W O}_{3}$ nanosheets \n$\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene‐based ohmic junctions \nCascade 2D coupling interfaces \n\nThe rapid recombination of photo‐generated electron‐hole pairs, insufficient active sites, and strong photocorrosion have considerably restricted the practical application of CdS in photocatalytic fields. Herein, we designed and constructed a 2D/2D/2D layered heterojunction photocatalyst with cas‐ caded 2D coupling interfaces. Experiments using electron spin resonance spectroscopy, ultraviolet photoelectron spectroscopy, and $i n$ ‐situ irradiation X‐ray photoelectron spectroscopy were con‐ ducted to confirm the 2D layered $\\mathrm{CdS}/\\mathrm{WO_{3}}$ step‐scheme (S‐scheme) heterojunctions and CdS/MX ohmic junctions. Impressively, it was found that the strong interfacial electric fields in the S‐scheme heterojunction photocatalysts could effectively promote spatially directional charge separation and transport between CdS and $\\mathsf{W O}_{3}$ nanosheets. In addition, 2D $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene nanosheets with a smaller work function and excellent metal conductivity when used as a co‐catalyst could build ohmic junc‐ tions with CdS nanosheets, thus providing a greater number of electron transfer pathways and hydrogen evolution sites. Results showed that the highest visible‐light hydrogen evolution rate of the optimized MX‐CdS/ ${\\sf W O}_{3}$ layered multi‐heterostructures could reach as high as $27.5\\ \\mathrm{mmol/g/h},$ which was 11.0 times higher than that of pure CdS nanosheets. Notably, the apparent quantum efficiency reached $12.0\\%$ at $450\\mathrm{nm}$ . It is hoped that this study offers a reliable approach for devel‐ oping multifunctional photocatalysts by integrating S‐scheme and ohmic‐junction built‐in electric fields and rationally designing a 2D/2D interface for efficient light‐to‐hydrogen fuel production. \n\n$\\mathbb{C}2022$ , Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved. \n\n# 1. Introduction \n\nThe use of solar energy for splitting water to produce hy drogen is regarded as a promising strategy to solve global en‐ ergy and environmental problems [1–3]. In particular, photo‐ catalytic water splitting using semiconductor photocatalysts has demonstrated great potential as a low‐cost, sustainable, and clean approach for solar hydrogen evolution [1,4]. Among all hydrogen‐evolution semiconductors, CdS is one of the most promising semiconductor photocatalysts for hydrogen genera‐ tion because of its tunable low‐dimensional nanostructures, considerable visible light response, and suitable band structure [3]. However, pure CdS photocatalysts have several disad‐ vantages, including insufficient active sites, strong photocorro‐ sion, and inevitable recombination of photoexcited photogen‐ erated carriers, which limit their practical applications [5–7]. The intrinsic ultrathin 2D features of 2D CdS nanosheets pro‐ vide a considerable advantage over other sizes of materials, as these features not only enable fast charge transport and sepa‐ ration but may also lead to a larger contact area, more charge transfer and separation pathways, and stronger interfacial in‐ teractions [8–10]. \n\nTo solve the problem of carrier recombination and maintain strong reducing electrons in CdS, a variety of semiconductors with staggered band structures relative to CdS have been used for coupling with CdS to construct CdS‐based heterojunction photocatalysts, including CdS/Fe2O3 [11], CdS/PI [12], $\\mathrm{CdS/g–C_{3}N_{4}}$ [13], $\\mathrm{CdS}/\\mathrm{W}0_{3}$ [14], and ZnO/CdS [15]. In particu‐ lar, ${\\sf W O3}$ nanosheets have good chemical stability, simple fabri‐ cation, and suitable band structures [16]. Thus, many studies have focused on enhancing hydrogen evolution by fabricating CdS/WO3 heterojunctions [17], thereby suppressing the unex‐ pected recombination of photoexcited holes and electrons driven by a strong Coulombic interaction. For example, Dai et al. [14] studied a direct Z‐scheme to enhance hydrogen evolu‐ tion by synthesizing ${\\sf W O}_{3}$ /CdS‐DETA with a nanoparti‐ cle/nanobelt structure. Zhang et al. [17] studied the influence of near‐infrared driving on hydrogen evolution by synthesizing CdS/WO3 with a 0D/2D structure. However, to the best of our knowledge, no studies on photocatalytic $\\mathrm{H}_{2}$ generation over 2D layered ${\\sf W O3/C d S}$ heterojunctions have been conducted. In this study, for the first time, we construct a 2D layered step‐scheme (S‐scheme) heterojunction by combining $\\mathsf{W O}_{3}$ and CdS nanosheets. \n\nThe S‐scheme photocatalytic system can effectively over‐ come the defects of a single catalyst and typical II heterojunc‐ tions, enhance the photo‐absorption range and redox ability, and boost its charge‐separation ability [18,19]. The composi‐ tion of the S‐scheme requires two necessary conditions: (1) two semiconductors with high oxidizing and reducing active sites and a staggered energy band structure, and (2) contact surfaces with strong interaction [20,21]. Obviously, 2D CdS with a high reduction potential acts as a reduction semicon‐ ductor, whereas $\\ensuremath{2\\mathrm{D}}\\ensuremath{\\mathsf{W}}\\ensuremath{0_{3}}$ with a narrow band gap (2.70 eV) and positive valence band (VB) $\\left(3.44~\\mathrm{eV}\\right)$ is a promising oxidation semiconductor. Thus, a 2D layered S‐scheme between CdS and $\\boldsymbol{\\mathsf{W O3}}$ nanosheets can be readily constructed. The driving force of photogenerated carrier transfer is mainly dependent on the S‐scheme internal electric field between $\\mathsf{W O3}$ and CdS [22,23]. Importantly, both the strong photocorrosion and fast charge recombination of CdS are suppressed by the formation of the CdS/WO3 S‐scheme heterojunction. \n\nHowever, the photocatalytic activities of $\\mathrm{CdS}/\\mathrm{WO}_{3}$ hybrids are still inhibited by sluggish $\\mathrm{H}_{2}$ ‐evolution kinetics and suffi‐ cient $\\mathrm{H}_{2}$ ‐evolution active sites [24]. To increase the number of surface active sites and reaction kinetics, loading a proper co‐catalyst over a CdS semiconductor is necessary [2]. In gen‐ eral, a co‐catalyst with a suitable work function is required to create a favorable built‐in electric field and capture the elec‐ trons on the surface of a given semiconductor in time to drive the target photocatalytic reduction reactions [25–27]. Ti3C2 MXene, which is a class of widely studied 2D layered materials with a low activation energy for hydrogen evolution, high con‐ ductivity, and a suitable work function, is catalytically and elec‐ tronically considered a suitable hydrogen evolution co‐catalyst [25]. Compared with traditional noble metal co‐catalysts, they are distinguished by their hydrophilicity, low price, metallic conductivity, tailored surface chemistry, and charge mobility anisotropy [28,29]. Abundant exposed metal sites contribute to the acceleration and activation of hydrogen evolution. Conse‐ quently, the improved hydrogen evolution performance of MXene/n‐type semiconductor heterojunction photocatalysts has been demonstrated. \n\nConsidering the merits of CdS nanosheets, 2D WO3 nanosheets, and metallic 2D $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene, we successfully fab‐ ricated 2D layered MX‐CdS/WO3 multi‐heterojunction photo‐ catalysts. Ultrathin CdS nanosheets were grown on MX and $\\mathsf{W O}_{3}$ nanosheets using a hydrothermal method (Scheme 1). The 2D structure provides more carrier transport, separation pathways, and strong interactions. The construction of S‐scheme heterojunctions reduces the recombination of charge carriers and maintains electrons with strong reducibility [30–32]. The loading of MX allows strong reducing electrons to be utilized quickly. Through the coupling of these favorable aspects, a high‐speed \"highway\" is constructed for electronic separation and transport in multi‐heterostructures. Therefore, the synergistic cooperation of the 2D S‐scheme heterojunction and ohmic junctions greatly enhances photocatalytic hydro‐ gen‐evolution activities, yielding a $\\mathrm{H}_{2}$ evolution rate of 27.5 $\\mathrm{{mmol/g/h,}}$ , which is 11 times higher than that of pure CdS. Based on our findings, this study suggests that by optimizing the MX loading on the CdS/WO3 S‐scheme heterojunction and the $\\mathrm{CdS}/\\mathrm{WO_{3}}$ ratios in nanocomposites, photocatalytic $\\mathrm{H}_{2}$ evo‐ lution activity can be further boosted manyfold. It is expected that this study will pave the way for the rational design of dy‐ namically controlled photocatalysts using different 2D semi‐ conductors and electrocatalytic materials. \n\n![](images/055527c37f0a4f155393fb14261556ef4f01953da8964237d0aae5fdbad713bc.jpg) \nScheme 1. Schematic of the fabrication of MX‐CdS/ $\\mathsf{W O}_{3}$ composites. \n\n# 2. Experimental \n\n# 2.1. Preparation of photocatalysts \n\n# 2.1.1. Synthesis of Ti3C2 MXene NSs \n\nIn the experiments, all reagents were analytically pure and required no further treatment. The method of synthesizing Ti3C2 MXene NSs was based on a previous report in which $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ was etched using hydrofluoric acid (HF) [33]. Typically, $_{1\\mathrm{~g~}}$ of $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ is immersed in $20~\\mathrm{mL}$ of $40\\%$ HF solution and stirred continuously for $72\\ \\mathrm{h}.$ . The prepared samples were washed with deionized water until the pH was close to 7. Next, the as‐prepared samples were dispersed in $20~\\mathrm{mL}$ of dimethyl sulfoxide. After being stirred for $12{\\mathrm{h}}.$ , the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ Mxene was col‐ lected by centrifugation and washed with deionized water and ethanol. The obtained $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene was re‐dispersed in $50~\\mathrm{mL}$ of deionized water and sonicated for $^{1\\mathrm{~h~}}$ under a nitrogen at‐ mosphere to achieve further dispersion. Finally, few‐layered $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene nanosheets were obtained by centrifugation and vacuum drying at $60^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{h}}$ . \n\n# 2.1.2. Synthesis of $W O_{3}$ NSs \n\nThe synthesis of ${\\sf W O}_{3}$ NSs was based on a previous report in which simple hydrothermal and calcination methods were employed [17]. Oxalic acid of $_{2\\mathrm{~g~}}$ and tungsten hexachloride of $0.2{\\mathrm{~g~}}$ were dispersed in $40~\\mathrm{mL}$ of absolute ethanol. After being stirred, the solution changed in appearance from yellow (cloudy) to colorless (transparent). The mixture solution was then transferred into a $50\\mathrm{-mL}$ polytetrafluoroethylene auto‐ clave, sealed, and kept at $100~^{\\circ}\\mathrm{C}$ for $24{\\mathrm{~h.}}$ Finally, the $\\boldsymbol{\\mathsf{W O3}}$ nanosheets were obtained by directly calcining the as‐prepared sample at $200^{\\circ}\\mathrm{C}$ for $^{1\\mathrm{h}}$ . \n\n# 2.1.3. Synthesis of CdS NSs \n\nThe method of synthesizing CdS NSs was in a manner simi‐ lar to that described in our previous report [11]. \n\n# 2.1.4. Synthesis of 2D MX‐CdS/ WO3 composites \n\nSpecific amounts of the aforementioned obtained ${\\sf W O}_{3}$ NSs (3, 15, 30, or $45\\mathrm{mg}$ ) and ultrathin $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene NSs (1.5, 3, 4.5, or $6~\\mathrm{mg}\\dot{}$ ) were dissolved into $15~\\mathrm{mL}$ of EDA and ultrasonicated for $^{1\\mathrm{~h~}}$ to form a uniform solution. ${\\mathrm{Cd}}({\\mathrm{AC}})_{2}{\\cdot}2{\\mathrm{H}}_{2}0$ of $0.5330\\mathrm{~g~}$ was added to $30~\\mathrm{mL}$ of EDA and heated at $60~^{\\circ}\\mathrm{C}$ for $30~\\mathrm{min}$ . \n\nThen, a solution of $\\mathrm{Cd}(\\mathrm{AC})_{2}{\\cdot}2\\mathrm{H}_{2}0$ was slowly added to the sus‐ pension of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene nanosheets, and the mixture was stirred at room temperature for $^{1\\mathrm{~h~}}$ . After $15~\\mathrm{mL}$ of the EDA solution of $\\boldsymbol{\\mathsf{W O3}}$ was added dropwise into the mixture and stirred for $^{1\\mathrm{~h~}}$ at room temperature, $\\ensuremath{0.4567\\mathrm{~g~}}$ of $\\mathrm{CH}_{4}\\mathrm{N}_{2}\\mathrm{S}$ was dissolved in the suspension. After being stirred for $0.5\\mathrm{~h~}$ , the suspension was transferred into a $100\\mathrm{-mL}$ polytetrafluoroeth‐ ylene autoclave and heated at $100^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{h}}$ . The solid product was collected by filtration and washed with water and ethanol three times. The synthesis of MX‐CdS and CdS/WO3 was similar to the aforementioned method but without using $\\boldsymbol{\\mathsf{W O3}}$ and MX, respectively. \n\n# 2.2. Characterization \n\nThe compositions and structures of the samples were de‐ termined using an X‐ray diffractometer (XRD, MSAL‐XD2) with Cu $K_{\\alpha}$ radiation at a scan rate of $4~\\mathrm{min^{-1}}$ . A Digital Instrument Nanoscope IIIA was used for atomic force microscopy (AFM) analysis. X‐ray photoelectron spectroscopy (XPS) (Thermo Scientific NEXSA) was used to study the crystalline structures and chemical compositions of the photocatalysts. The binding energy was normalized to an adventitious carbon signal of $284.8{\\ \\mathrm{eV}}.$ The energies of the Ar ion beam and beam voltage were $1.0\\ \\mathrm{keV}$ and $3.0~\\mathrm{eV_{\\perp}}$ respectively. The microscopic mor‐ phologies of the samples were observed by transmission elec‐ tron microscopy (TEM) and high‐resolution TEM (HRTEM) analyses $(\\mathrm{JEM-}2100\\mathrm{HR};$ accelerating voltage $=200\\ \\mathrm{kV}]$ . The light absorption capacities of the samples were measured and analyzed using a UV‐vis spectrometer (Shimadzu UV‐2600 PC) with a scanning wavelength range of $400{-}800~\\mathrm{~nm}$ . The steady‐state photoluminescence (PL) spectra were measured at $384~\\mathrm{nm}$ , and the fluorescence lifetime was measured using FLS980. Surface photovoltage spectroscopy (PL‐SPS/IPCE1000, Perfect Light, Beijing) was used to characterize the samples. The electron spin resonance (ESR) spectra of the prepared samples were analyzed using a Bruker model ESR 5 JES‐FA200 spectrometer. With HeI $(21.22~\\mathrm{eV})$ used as a monochromatic light source and a total instrument energy resolution of 100 meV, the prepared samples were subjected to ultraviolet (UV) photoelectron spectroscopy (UPS) measurements. \n\n# 2.3. Photocatalytic performance for hydrogen evolution \n\nA photocatalytic hydrogen evolution experiment was con‐ ducted in a $100\\mathrm{-mL}$ three‐necked flat‐bottomed flask. At room temperature and pressure, a Xe lamp (300 W PLS‐SXE300, Perfect Light, Beijing, $\\lambda>420~\\mathrm{{nm}}$ ) was used to simulate sun‐ light at an illumination intensity of $160\\mathrm{mV}{\\cdot}\\mathrm{cm}^{-2}.$ , and a $420\\mathrm{-nm}$ filter was used to filter out the UV light. In the hydrogen evolu‐ tion experiment, $5~\\mathrm{mg}$ of the photocatalyst was dissolved in 80 mL of $10~\\mathrm{wt\\%}$ lactic acid solution. The suspension was soni‐ cated for $15~\\mathrm{min}$ to disperse the photocatalyst uniformly, and then ${\\sf N}_{2}$ was injected into the reaction system for $15~\\mathrm{min}$ to remove oxygen in the flask and prevent interference from other gases in the system. The reactor was exposed to a Xe lamp and illuminated continuously for $^{1\\mathrm{~h~}}$ . Gas of $400~\\ensuremath{\\upmu\\mathrm{L}}$ was extracted from a three‐necked flask, and the composition of the extracted gas was analyzed by gas chromatography (GC‐9560). The ap‐ parent quantum efficiency (AQE) was measured under these conditions and calculated using the following formula: \n\n$$\nA Q E s(\\%)=\\frac{2n_{H_{2}}}{n_{p}}\\times100\\\n$$ \n\n# 2.4. Electrochemical tests \n\nPreparation of working electrode: A photocatalyst of $5~\\mathrm{mg}$ was added to a mixture containing ethanol $(2{\\mathrm{~mL}})$ and Nafion solution $(20~\\upmu\\mathrm{L},~0.25\\%)$ . The obtained suspension was uni‐ formly dispersed by ultrasonic treatment, and then $50~\\upmu\\mathrm{L}$ of the suspension was injected into a $2\\times3.5~\\mathrm{cm}^{2}$ fluorine‐doped tin oxide (FTO) glass substrate and dried under an infrared lamp. Finally, the obtained electrode was calcined at $150^{\\circ}\\mathrm{C}$ for $^{1\\mathrm{~h~}}$ under a ${\\sf N}_{2}$ flow. \n\nTransient photocurrent test: Measurements were conducted in the standard three‐electrode system of an electrochemical analyzer $\\left[\\mathrm{CHI}~660\\right]$ . At room temperature and pressure, a Xe lamp (300 W) was used to simulate sunlight at an illumination intensity of $160~\\mathrm{mV/cm^{2}},$ and a $420\\mathrm{-nm}$ filter was used to filter out the UV light. The prepared electrode was used as the working electrode, $\\mathrm{\\DeltaAg/AgCl}$ as the reference electrode, and a Pt plate as the counter. The electrolyte solution was $0.1\\mathrm{~M~Na_{2}S O_{4}}$ aqueous solution. \n\nElectrochemical impedance spectroscopy (EIS) test: The EIS of the working electrode was analyzed using a comput‐ er‐controlled impedance measurement unit with a frequency range of $0.01\\mathrm{-}105\\mathrm{Hz}$ and an AC amplitude of $5\\mathrm{mV}$ in the dark. For electrolytes, 0.1 mol/L ${\\tt N a}_{2}{\\tt S}$ and $0.02\\mathrm{\\mol/L\\Na_{2}S O_{3}}$ aque‐ ous solutions were used. \n\nElectrocatalytic hydrogen evolution: Linear scanning volt‐ ammetry was performed at a scanning rate of $5\\ \\mathrm{mV}/s$ in a standard three‐electrode system. Pt wire was used as the counter, $\\mathrm{\\DeltaAg/AgCl}$ as the reference electrode, and $0.5\\mathrm{~M~H}_{2}\\mathrm{S}0_{4}$ aqueous solution as the electrolyte solution. The working elec‐ trode was prepared as follows: $6~\\mathrm{mg}$ of the prepared photo‐ catalyst powder was added to $2~\\mathrm{mL}$ of deionized water, and the suspension was treated with ultrasound for $^{2\\mathrm{~h~}}$ . The $3{\\cdot}\\mathrm{mL}$ sus‐ pension was evenly spread on a glassy carbon electrode. After drying under infrared light, $3~{\\upmu\\mathrm{L}}$ of $0.5\\%$ Nafion solution was added to the catalyst layer and dried again under infrared light. \n\n# 3. Results and discussion \n\n# 3.1. Structures and compositions of the photocatalysts \n\nTo determine the phase purities and crystalline structures of the photocatalysts, the XRD patterns were measured (Fig. 1). Fig. 1(a) shows the XRD patterns of Ti3AlC2, Ti3C2, and WO3. For Ti3AlC2, the diffraction peak at $19.17^{\\circ}$ corresponds to the (004) crystal plane. After etching, the (004) diffraction peak widened and shifted to a lower angle. In addition, the peak at $39.0^{\\circ}$ at‐ tributable to the (104) crystal plane completely disappeared after HF etching, which indicated that the Al element in $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ was completely removed [34]. The diffraction peaks at $48.54^{\\circ}\\mathrm{~.~}$ $52.33^{\\circ}.$ , and $56.50^{\\circ}$ also disappeared. The diffraction peak at $60.80^{\\circ}$ was attributed to the (110) crystal plane of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ [35]. Simultaneously, most of the diffraction peaks of Ti3AlC2 after etching became increasingly weaker. These results indicate that $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene was successfully synthesized. As Fig. 1(b) shows, the diffraction peaks of ${\\sf W O}_{3}$ were concentrated at $23.96^{\\circ}.$ , $34.04^{\\circ}.$ , $42.11^{\\circ}$ , $49.04^{\\circ}.$ , $55.25^{\\circ}.$ , and $61.07^{\\circ}.$ which were assigned to the (100), (110), (111), (200), (210), and (211) $\\boldsymbol{\\mathsf{W O3}}$ crystal planes (PDF#41‐0905) , respectively. Fig. 1(a) shows the XRD patterns of pure CdS and composite CdS nanosheets with different $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene and $\\mathsf{W O}_{3}$ contents. All the diffraction peaks shown in Fig. 1(a) correspond to hexago‐ nal CdS (PDF#41‐1049). There was no deviation in the XRD peak of CdS, indicating that the addition of $\\mathsf{W O}_{3}$ and MX co‐catalysts had no effect on the crystalline structures of the CdS nanosheets. However, in the composites, the diffraction peaks of ${\\sf W O}_{3}$ and MX were not detected, which was probably due to the fact that the CdS covered WO3 and MX with low con‐ tent and high dispersibility during the hydrothermal process. The existence of ${\\sf W O}_{3}$ and MX should be further analyzed using TEM, HRTEM, and XPS. \n\nThe morphologies and microstructures of the as‐prepared semiconductors were further studied using TEM and HRTEM. Fig. 2(a) shows that pure CdS had a typical 2D nanosheet structure with an ultrathin thickness [36,37]. A TEM image of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene is shown in Fig. 2(c). The prepared MX clearly showed a porous 2D nanosheet structure with a lateral diame‐ ter of approximately $30\\ \\mathrm{nm}$ . Fig. 2(b) shows the microstruc‐ tures of the 2D $\\mathsf{W O}_{3}$ nanosheets. The synthesized $\\mathsf{W O}_{3}$ clearly exhibited a rectangular 2D nanosheet structure. Some disor‐ dered areas with obscure lattice fringes could be found on the surfaces of the $\\ensuremath{2\\mathrm{D}}\\ensuremath{\\mathsf{W}}\\ensuremath{0_{3}}$ nanosheets, which may be attributable to clusters of oxygen vacancy. The thickness of the CdS NSs was calculated to be $1.21\\ \\mathrm{nm}$ by AFM (Fig. S1(a) and (d)). The thicknesses of the $\\mathsf{W O}_{3}$ (Fig. S1(b) and (e)) and Ti3C2 (Fig. S1(c) and (f)) NSs were calculated to be 5.59 and $13.68~\\mathrm{nm}$ by AFM, respectively. This may have been due to the stacking of the multilayer ${\\sf W O}_{3}$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ nanosheets. We then observed the TEM images of the ternary composite material (Figs. 2(d)–(f)). We found that CdS nanosheets were grown on $\\mathsf{W O}_{3}$ nanosheets with MX distributed on CdS nanosheets. Accordingly, a 2D‐2D‐2D composite‐layered heterojunction photocatalyst was formed. Further observation of the lattice fringes by HRTEM showed that the lattice fringes of 0.25, 0.31, and $0.36~\\mathrm{nm}$ cor‐ responded to the (0110) plane in $\\mathrm{Ti}_{3}{\\mathrm{C}}_{2},$ (101) plane in CdS, and (101) plane in $\\mathsf{W O}_{3},$ respectively. Fig. 2(n) shows that the en‐ ergy‐dispersive X‐ray (EDX) peaks of S, Cd, W, O, Ti, and C were found in the MX‐CdS/WO3 sample. Both the HRTEM elemental mapping (Figs. 2(h)–(m)) and EDX results confirmed the co‐existence of S, Cd, W, O, Ti, and C in the MX‐CdS/WO3 sam‐ ple, which strongly proved the successful synthesis of the ter‐ nary composite photocatalyst. \n\n![](images/374277f2501fcbe04a2b378898f9b25ed95a6b7f9c1258bb3c13830f0b584234.jpg) \n\nFig. 1. (a) The XRD patterns of CdS, CdS/ ${\\mathrm{WO}}_{3},$ MX‐CdS, and MX‐CdS/ ${\\mathrm{WO}}_{3};$ (b) XRD patterns of MX and $\\mathsf{W O}_{3}$ \n\n![](images/6a83ce121f133545d8be4331a2a1d4a39de45e909ab5531f3cf3d9d144b8e0d9.jpg) \nFig. 2. TEM images of CdS (a), $\\mathsf{W O}_{3}$ (b), MX (c), MX‐CdS $/\\mathrm{{WO_{3}}}$ (d,f); (e) HRTEM image of $\\mathrm{MX-CdS/WO_{3}};$ Elemental mapping $(\\mathrm{g-m})$ and EDX spectrum (n) of MX‐CdS/ $\\mathrm{{WO_{3}}}$ . \n\nXPS was performed to analyze the elemental composition and surface properties of the MX‐modified CdS/WO3 2D lay‐ ered heterojunction photocatalyst. As Fig. 3(a) shows, the binding energies of 404.3 and $411.1\\ \\mathrm{eV}$ corresponded to the $3d_{5/2}$ and $3d_{3/2}$ orbitals of the Cd $3d$ in the ternary composite photocatalyst, respectively [38]. The binding energies of $\\varsigma2p$ at 160.1 and $161.9\\ \\mathrm{eV}$ corresponded to the $\\textsf{S}2p_{3/2}$ and S $2p_{1/2}$ orbitals, respectively (Fig. 3(b)) [38]. The binding energies of Cd and S in the ternary photocatalyst elements both showed a slight negative shift as compared with the pure CdS. Strong interactions between the ternary complexes are indicated. The \n\nC element was detected in the energy spectrum, which could be attributed to the indeterminate hydrocarbons from the XPS instrument (Fig. S2(a)). The spectra of O1s included the ad‐ sorbed oxygen peak at the oxygen vacancy and lattice oxygen peak (Fig. S2(b)) [39]. However, the W 4f and Ti $2p$ peaks in the XPS spectrum of MX‐CdS/ ${\\sf W O}_{3}$ were not detected (Figs. S3 and 4). Because of the growth of 2D CdS nanosheets on the surfaces of ${\\sf W O}_{3}$ and MX by the hydrothermal method, CdS nanosheets will cover the surfaces of ${\\sf W O}_{3}$ and MX to a certain extent. After etching of $5\\mathrm{nm}$ with argon, the spectra of W 4f and Ti $2p$ were examined. Fig. 3(c) shows that the W $4f$ orbital was composed of W $4f_{7/5}$ and $\\textsf{W}4f_{5/2}$ . The corresponding binding energies in the ${\\sf W O}_{3}$ nanosheets were 35.9 and $38.1~\\mathrm{{\\eV}}.$ , respectively, whereas the corresponding binding energies in the ternary composite system were 34.9 and $37.6~\\mathrm{eV}.$ , respectively, indicat‐ ing a negative shift. This may have been due to the strong in‐ teraction between the ternary complex and the influence of etching [22]. As Fig. 3(d) shows, Ti $2p$ orbitals were composed of $\\mathrm{Ti^{3+}}2p_{3/2},\\mathrm{Ti^{4+}}2p_{3/2},\\mathrm{Ti^{3+}}2p_{1/2},$ and ${\\mathrm{Ti}}^{4+}2p_{1/2},$ and their cor‐ responding binding energies were 455.0, 458.0, 461.6, and 464.8 eV, respectively [28,40]. We observed that the low‐valence Ti peak did not exist because the electrons in $\\mathrm{CdS}/\\mathrm{WO}_{3}$ transferred to the surface of MX, which led to consid‐ erable reduction activity on the surface of MX [40,41]. Com‐ pared with the single materials, the peaks in $\\mathsf{M X-W O3/C d S}$ had varying degrees of shift, indicating the strong interaction after intimate contact of $\\mathsf{W O}_{3},$ MX, and CdS [22]. It was proved that an intimate heterojunction was generated at the MX‐CdS/WO3 interface. \n\n# 3.2. Optical properties, activities, and stabilities of photocatalysts \n\nThe photocatalytic activities of semiconductor photocata‐ lysts depend on the conduction band (CB), VB, and light ab‐ sorption. The edge position of the pure CdS nanosheets was located at approximately $500~\\mathrm{{nm}}$ , which was measured using an ultraviolet spectrophotometer (Fig. 4(a)). Compared with pure CdS nanosheets, the ternary composite MX‐CdS/WO3 photocatalysts displayed enhanced light absorption capacity under irradiation above $500~\\mathrm{{nm}}$ because of the full spectrum absorption capacity of MX [42]. However, the light absorption of MX‐CdS ${\\mathrm{\\DeltaWO}}_{3}$ was weakened under irradiation below 500 nm. \n\n![](images/bdc052a9404be476deb2c4b245e81c795a1030867b07e2863993a7aed51383e7.jpg) \nFig. 3. XPS scan of Cd 3d (a), $s2p$ (b), W4f (c), and Ti $2p$ (d). \n\n![](images/02050e1d6facbb45d5400f7d27d36480c82fc812e20314417a93de23fa4bd998.jpg) \nFig. 4. UV‐vis absorption spectra (a) and hydrogen evolution (b) of CdS, MX‐CdS, CdS $'\\mathrm{WO_{3}},$ and MX‐CdS/ $\\mathsf{W O}_{3};$ (c) Recycled photocatalytic $\\mathrm{H}_{2}$ evolu tion experiments of MX‐CdS/ $\\mathsf{W O}_{3}$ and CdS; (d) Apparent quantum efficiency of MX‐CdS/ $\\mathsf{W O}_{3}$ . \n\nThe hydrogen evolution performances of the photocatalysts are shown in Fig. 4(b). Under the same conditions, no hydrogen was detected when pure ${\\sf W O}_{3}$ and $\\mathsf{M X}–\\mathsf{W O}_{3}$ acted as photocata‐ lysts. When $10\\mathrm{\\:wt\\%}$ lactic acid was used as the sacrificial agent, the hydrogen evolution rate of the CdS nanosheets was 2.5 $\\mathrm{{mmol/h/g}}$ . After optimization, the highest hydrogen evolution rate of the CdS/WO3 2D/2D S‐scheme heterojunction was 8.1 $\\mathrm{{mmol/h/g}}$ (Fig. S5(a)), which was 3.2 times higher than that of the pure CdS nanosheets. This result indicates that the con‐ structed 2D/2D S‐scheme heterojunction could significantly improve the photocatalytic performance of pure CdS. In addi‐ tion, the highest hydrogen evolution rate of optimized 2D/2D MX‐CdS ohmic junction photocatalysts was $8.5\\ \\mathrm{mmol/h/g}$ (Fig. S5(b)), which was 3.4 times higher than that of pure CdS nanosheets. This result reveals that the formation of 2D/2D ohmic junctions significantly improved the photocatalytic per‐ formance of pure CdS nanosheets. When the S‐scheme hetero‐ junction and ohmic junctions were combined, the highest hy‐ drogen evolution rate of optimized MX‐CdS/WO3 was further increased to $27.5\\ \\mathrm{mmol/h/g}$ (Fig. S5(c)), which was 11 times higher than that of the CdS nanosheets. Compared with other systems of MX as a hydrogen evolution co‐catalyst, $\\mathrm{MX-CdS/WO_{3}}$ has been shown to have higher hydrogen evolu‐ tion activity [25,34,43]. \n\nThe different levels of stability of the MX‐CdS/WO3 compo‐ site photocatalysts are shown in Fig. 4(c). After four reaction cycles (3 h per cycle), the MX‐CdS/WO3 composite photocata‐ lysts maintained a high $\\mathrm{H}_{2}$ evolution rate of $23.1\\ \\mathrm{mmol/h/g},$ indicating the composite maintained an improved stability with $84\\%$ of performance retention following the fourth cycle as compared with that in the first cycle. This may have been caused by the photocorrosion of the CdS nanosheets [44], the loss of sacrificial agents [1,45], and the destruction of the inter‐ faces between MX, WO3, and CdS due to long‐term stirring in the solution [46]. Notably, the hydrogen production rate of the pure CdS nanosheets declined by more than $50\\%$ during the second cycle. This proved that the construction of double het‐ erojunction systems can better inhibit the photocorrosion of CdS [44]. Test results revealed the apparent quantum efficiency of the ternary photocatalyst, as shown in Fig. 4(d), where the AQEs of MX‐CdS/WO3 at 420, 435, 450, 475, and $500~\\mathrm{{nm}}$ were $8.01\\%$ $10.12\\%$ , $12.16\\%$ , $9.00\\%$ , and $4.50\\%$ , respectively, indi‐ cating significantly improved photocatalytic $\\mathrm{H}_{2}$ generation due to the formation of 2D layered heterojunctions. \n\n# 3.3. Charge separation properties and proposed mechanism \n\nTo explore further the strong interactions between the 2D structure and the coupling double heterojunction to improve the charge transfer and separation of CdS, we studied the PL spectrum with an excitation wavelength of $384~\\mathrm{nm}$ (Fig. 5(a)). A previous study showed that efficient separation charges can reduce the intensity of the PL peak [47]. Compared with pure CdS, the average fluorescence intensities of the binary and ter‐ nary photocatalysts were significantly reduced. This was at‐ tributed to the efficient charge transfer at the 2D/2D S‐scheme heterojunction and ohmic junction interface [48,49]. Therefore, compared with pure CdS, the MX‐CdS/WO3 composite photo‐ catalyst showed a higher separation efficiency of photogener‐ ated electron‐hole pairs. In addition, the smaller radius in the Nyquist plots (the corresponding equivalent circuit is shown in \n\n![](images/518a3441cd92bfdd5250002006e9ddd9b05e954a1908a1f26a158b01ea9196bc.jpg) \nFig. 5. (a) PL spectra; (b) EIS Nyquist plots, with inset showing the electrical equivalent circuit of the Nyquist plots; (c) Polarization curves; (d) Photocurrent profiles. \n\nFig. 5(b) with a bias voltage of 0) suggests a lower electrical resistance during the charge transfer process [50,51]. This proves that the coupling of the 2D/2D S‐scheme heterojunction and ohmic junctions could achieve the rapid transfer of photo generated electrons to the reaction sites [50,51]. The recombi‐ nation of photogenerated electron‐hole pairs was thus greatly reduced. This was consistent with the results obtained by PL spectroscopy. \n\nThe overpotential of the MX‐CdS/WO3 photocatalyst was lower than that of the other combinations in the polarization curve (Fig. 5(c)). This shows that the 2D S‐scheme heterojunc‐ tion and ohmic junctions had a synergistic effect in promoting the separation and further utilization of electrons to a certain extent due to the boosted $\\mathrm{H}_{2}$ ‐evolution kinetics and decreased $\\mathrm{H}_{2}$ ‐evolution potentials [14]. The transient photocurrent re‐ sponse was used to further confirm the coupling effect of the 2D double heterojunction. As Fig. 5(d) shows, the transient photocurrent density of MX‐CdS/WO3 was significantly higher than that of the other photocatalysts. It was confirmed that the simultaneous loading of 2D MX and ${\\sf W O}_{3}$ on 2D CdS could sig‐ nificantly enhance the photocurrent density of the photocata‐ lyst. This was determined to be a key factor in improving pho‐ tocatalytic activity. In general, the photocurrent density en‐ hancement of the 2D double heterojunction composite photo‐ catalyst improved the efficiency of charge separation and transfer [52]. The separation of the light‐generated carriers was further confirmed by fluorescence lifetime measurements [53,54], as shown in Fig. 6(a). The results showed that the val‐ ues of CdS, MX‐CdS, CdS/WO3, and MX‐CdS/WO3 were 4.11, 3.99, 3.78, and 3.43 ns, respectively. The MX‐CdS/WO3 sample showed the shortest decay time, indicating the best charge separation ability, which was consistent with the best hydrogen evolution activity. This further proved that introducing the coupling effect of 2D double heterojunctions can decrease the average fluorescence lifetime as compared with that of 2D CdS, which is beneficial for inhibiting the recombination of photo‐ generated carriers [55]. Surface photovoltage (SPV) is also a powerful technique used to characterize the transportation behavior of photogenerated carriers between CdS, $\\mathsf{W O}_{3},$ and MX [56]. A positive PV response of CdS can be observed in Fig. 6(b), indicating that the photogenerated holes were transferred to the upper electrode. The SPV signals of $\\mathrm{CdS}/\\mathrm{WO}_{3}$ and $\\mathrm{MX-CdS/W}0_{3}$ were decreased to a significantly lower extent than those of CdS, which may have been due to the capture of photogenerated holes of CdS by $\\boldsymbol{\\mathsf{W O}}_{3}$ instead of the upper elec‐ trode through the S‐scheme interface electric fields. \n\n![](images/7ca57950e862874cf38dcf6f07000bf31a17579c38742366a84ed2d19437c6a2.jpg) \nFig. 6. (a) Fluorescence lifetime spectra of CdS, MX‐CdS, CdS/ ${\\mathrm{WO}}_{3},$ and MX‐CdS/ $\\mathsf{W O}_{3}$ composites; (b) SPV spectra of CdS, CdS/ $\\mathsf{W O}_{3},$ and MX‐ $\\mathrm{CdS}/\\mathrm{W}0_{3}$ \n\nThe S‐scheme heterojunction plays a vital role in the sepa‐ ration of photogenerated carriers [57]. The band gaps of $\\mathsf{W O}_{3}$ and CdS are shown in Fig. 8(a). In this study, although the band gap of $\\mathsf{W O}_{3}$ was significantly smaller than that of the reported value $(2.7~\\mathrm{eV})$ , the XPS, XRD, and TEM results were consistent with the previous report. This result may have been caused by oxygen defects on the $\\mathsf{W O}_{3}$ surface [17]. A Mott‐Schottky test under dark and light conditions showed that the CBs of CdS under dark and light were $-1.40$ and $-1.36\\mathrm{eV_{\\it1}}$ , respectively (Fig. 7(a)), whereas those of WO3 under dark and light were 0.12 and $0.07\\ \\mathrm{\\eV},$ respectively (Fig. 7(b)). Under irradiation, the band structure of CdS shifted downward, whereas the band structure of $\\boldsymbol{\\mathsf{W O3}}$ shifted upward (Fig. 8(c)). This type of band flattening phenomenon is beneficial to the transfer of photo‐ generated electrons in an S‐scheme heterojunction. In addition, a VB‐XPS test (Figs. 7(c) and (d)) revealed the CB and VB of CdS were $-1.39$ and $1.04\\:\\mathrm{eV}$ , respectively, whereas the CB and VB of $\\boldsymbol{\\mathsf{W O3}}$ were 0.09 and 2.61 eV, respectively. \n\nIn addition, the work function $(\\phi)$ and EVBM (VB energy) of $\\mathrm{MX-CdS/W}0_{3}$ could be calculated from the UPS data. Fig. 8(b) shows the UPS spectra of CdS and WO3. The $\\phi{s}$ of ${\\sf W O}_{3}$ and CdS were calculated as 4.55 and $4.03\\mathrm{eV}$ by subtracting the width of the He I UPS spectrum when the excitation energy was 21.22 eV [58]. The VB energies $(E\\mathrm{vB})$ of ${\\sf W O}_{3}$ and CdS were calculated as 7.05 and $5.55\\mathrm{eV}$ (vs. vacuum levels), respectively. According to the reference criteria, $0\\mathrm{~V~}$ of reversible hydrogen electrode (RHE) is equal to $4.44\\mathrm{eV}$ of the vacuum level. The values of ECB and EVB require unit conversions. Thus, the values of EVB for $\\mathsf{W O}_{3}$ and CdS were calculated as 2.61 and $1.11\\ \\mathrm{eV}$ (vs. RHE), respectively, and the values of ECB were calculated as 0.09 and $-1.32\\ \\mathrm{eV}_{\\mathrm{i}}$ respectively. Therefore, an internal built‐in electric field from CdS to $\\mathsf{W O}_{3}$ was constructed on the 2D/2D interface to facilitate the separation of photogenerated charges. Due to the formation of an electric field, under visible light irradiation, the photogenerated electrons on the CB of ${\\sf W O}_{3}$ would transfer to the VB of CdS and combine with the remaining holes. We used UPS to determine the $\\phi{s}$ of CdS and MX, which were then used to confirm the interface charge transfer route between CdS and MX. In addition, the work functions of CdS and MX were determined to be approximately 4.03 and $2.06\\ \\mathrm{eV},$ , re‐ spectively (Fig. 8(b)). These experimental results showed that the contact between CdS and MX formed an ohmic junction [11,59]. Photogenerated electrons on the surface of the CdS nanosheets will transfer to the surfaces of the metallic MX co‐catalysts with high conductivity to drive photocatalytic $\\mathrm{H}_{2}$ evolution under visible light irradiation. In summary, it was proved that the S‐scheme heterojunction between ${\\sf W O}_{3}$ and CdS could be created because of their suitable energy band structures and arrangement, whereas the ohmic junction be‐ tween CdS and MX could be constructed during the smaller work functions of MX (Fig. 8(d)). \n\n![](images/17149ce9500345540867ebfa38e31a6f581853663606559de533ffe547477a4c.jpg) \nFig. 7. (a,b) Mott‐Schottky plots of CdS and $\\boldsymbol{\\mathsf{W O}}_{3}$ under dark and light conditions; (c,d) VB XPS profiles of CdS and ${\\sf W O}_{3}$ . \n\n![](images/a39aafbdbd8bc146aff77a70b16fbeee1d84eec45575a512de0d5a80a34f20e6.jpg) \nFig. 8. (a) $(\\alpha h\\nu)^{1/2}$ vs. hν plots of CdS and $\\boldsymbol{\\mathsf{W O}}_{3}$ from UV‐visible DRS analysis; (b) UPS spectra of CdS, $\\mathsf{W O3},$ and $\\mathrm{Ti}_{3}\\mathrm{C}_{2};$ ; (c) Energy level posi‐ tion schematics of CdS and $\\mathsf{W O}_{3}$ from the Mott‐Schottky plot under dark and light conditions; (d) Band structures of CdS and $\\mathsf{W O}_{3}$ . \n\nTo determine whether the photogenerated electron‐hole pair delivery mechanism between ${\\sf W O}_{3}$ and CdS complied with the S‐scheme route, an ISI XPS characterization is provided in Fig. 9(a). Under $420\\mathrm{-nm}$ light irradiation, there was a slight negative shift (0.11 eV) as compared with the binding energy of Cd 3d, indicating that the electron density of Cd increased un‐ der $420\\mathrm{-nm}$ light irradiation. However, similar to the XPS re‐ sults, the W 4f and Ti $2p$ peaks in the ISI XPS spectrum of MX‐CdS/ ${\\sf W O}_{3}$ were not detected (Fig. S6). These shifts in bind‐ ing energy provided considerable evidence for the transfer of charge to the CdS interface through the path of the S‐scheme under $420\\mathrm{-nm}$ light conditions of the photocatalytic reaction [60]. The successful construction of the S‐scheme heterojunc‐ tion between the CdS and WO3 nanosheets was further veri‐ fied. DMPO was used as the capture agent for $\\bullet0^{2-}$ and $\\bullet0\\mathrm{H}^{-}$ and ESR technology was used to detect changes in the active oxidants $(\\mathrm{DMPO-}\\bullet0^{2-}$ and $\\mathrm{\\DeltaDMPO{\\cdot}{\\bullet}O H^{-}})$ in the water system [61,62]. As Fig. 9(b) shows, $\\mathsf{W O}_{3}$ CdS, and CdS/WO3 possess no ESR signals in the dark, which proves that both $\\bullet0^{2-}$ and $\\bullet0\\mathrm{H}^{-}$ are excited by visible light. As Fig. 9(c) shows, $\\boldsymbol{\\mathsf{W O3}}$ CdS, and $\\mathrm{CdS}/\\mathrm{WO}_{3}$ in the characteristic peak detection map of ${\\tt D M P O-}{\\tt O}2-$ all responded to visible light and generated a four‐wire ESR signal. More importantly, the peak intensity of $\\mathrm{CdS}/\\mathrm{WO_{3}}$ was greater than those of the $\\mathsf{W O}_{3}$ and CdS nanosheets. In the characteristic peak detection spectrum of $\\mathrm{\\DMPO\\-\\bullet0H^{-}}$ (Fig. 9(d)), $\\mathsf{W O3},$ CdS, and CdS/WO3 all responded to visible light and generated ESR signals with a relative inten‐ sity of 1:2:2:1. More significantly, the peak intensity of $\\mathrm{CdS}/\\mathrm{WO}_{3}$ was greater than those of the WO3 and CdS nanosheets. This proves that the electron transfer route follows the S‐scheme process and shows that CdS/ ${\\mathrm{WO}}_{3}$ has a stronger photogenerated carrier transfer ability than those of pure CdS and $\\mathsf{W O}_{3}$ nanosheets. \n\nBased on the experimental data of the aforementioned charge transfer pathway, it could be proved that the photogen‐ erated electron transfer in MX‐CdS $/\\mathrm{{WO}_{3}}$ followed the S‐scheme mechanism (Fig. 10) [23,57]. A band diagram of MX‐CdS/WO3 is given as Fig. 10(a). Clearly, the oxidation photocatalyst ${\\sf W O}_{3}$ had a lower Fermi level and greater work function $(4.55~\\mathrm{eV})$ , whereas the reduction photocatalyst CdS had a higher Fermi level and smaller work function $\\left(4.03~\\mathrm{eV}\\right)$ . After the CdS and $\\mathsf{W O}_{3}$ contacts interface, the electrons of CdS will transfer to $\\mathsf{W O}_{3}$ spontaneously in thermodynamics, and their EF should be equalized (Fig. 10(b)). As a result, the energy band of ${\\sf W O}_{3}$ will bend downward because of electron accumulation, whereas CdS will bend upward because of electron consumption. An internal electric field in the direction from CdS to WO3 will then be built. In the S‐scheme heterojunction, under irradiation, weak reducibility electrons in the CB of WO3 and weak oxidiz‐ ing holes in the VB of CdS are recombined and quenched at the interface. By contrast, strong oxidizing holes in the VB of $\\mathsf{W O}_{3}$ and strong reducibility electrons in the CB of CdS are main‐ tained due to the presence of the built‐in electric field. Finally, photocatalytic reduction and oxidation reactions are triggered by electrons in the CB of CdS and by holes in the VB of ${\\mathrm{WO}}_{3}.$ , respectively. Because of the smaller work function $\\left(2.06~\\mathrm{eV}\\right)$ , excellent metal conductivity, and high exposure terminal metal sites of MX [42,63], the photogenerated carriers in the CdS nanosheets will migrate to the surface of the MX co‐catalyst through the ohmic junctions and initiate a redox reaction. The holes on $\\boldsymbol{\\mathsf{W O3}}$ are consumed by lactic acid in the solution (Fig. 10(c)). Thus, all photogenerated carriers can be quickly trans‐ ferred and utilized in the MX‐CdS/WO3 2D superimposed built‐in electric field system. \n\n![](images/6e10a2395e1ef41b074eaab3c20291d2260b8593c46b451696845264b7076383.jpg) \nFig. 9. (a) High‐resolution XPS for Cd $3d$ of CdS/ ${\\sf W O}_{3}$ under $420\\mathrm{-nm}$ visible‐light irradiation or in the dark; (b) ESR spectra of CdS, $\\mathsf{W O3},$ and $\\mathrm{CdS}/\\mathrm{WO_{3}}$ in the dark; (c,d) ESR spectra of CdS, $\\mathsf{W O}_{3},$ and $\\mathrm{CdS}/\\mathrm{WO_{3}}$ 1 $_{\\mathrm{DMPO-}{\\bullet}02}.$ – and $\\mathrm{DMPO{\\-}{\\cdot}{0}H^{-}}$ ). \n\n![](images/24e910a8a4c18c41cf085b83b0741bfbd6b0fec076974f97ea4920ff0a05fe71.jpg) \nFig. 10. S‐scheme heterojunction of MX‐CdS/ $\\mathrm{wo}_{3}.$ : (a) before contact interaction, (b) after contact interaction, and (c) after contact interaction under irradiation, photogenerated carrier migration and separation, and photocatalytic hydrogen evolution. \n\n# 4. Conclusions \n\nIn this study, a 2D MX‐CdS/WO3 layered S‐scheme hetero‐ junction photocatalyst with cascaded 2D coupling interfaces was successfully prepared by growing CdS nanosheets on MX and $\\mathsf{W O}_{3}$ nanosheets. It was shown that the 2D/2D heterojunc‐ tion structure provided a tight interface, which is beneficial for photogenerated electron transfer and separation. The con‐ struction of the S‐scheme heterojunction reduced the recom‐ bination of photogenerated electron‐hole pairs and maintained electrons with strong reducibility. The loading of MX offered more hydrogen active sites and effectively utilized electrons for photocatalytic reactions though ohmic junctions. The resulting MX‐CdS/WO3 2D photocatalyst exhibited excellent superim‐ posed built‐in electric field synergy, and its highest hydrogen evolution rate reached $27.5\\ \\mathrm{\\mmol/h/g}$ . This work demon‐ strated an effective strategy for coupling multiple built‐in elec‐ \n\n# Graphical Abstract \n\nChin. J. Catal., 2022, 43: 359–369 doi: 10.1016/S1872‐2067(21)63883‐4 \n\n# Integration of 2D layered CdS/ $\\bf{W O_{3}}$ S‐scheme heterojunctions and metallic Ti3C2 MXene‐based Ohmic junctions for effective photocatalytic H2 generation \n\nJunxian Bai, Rongchen Shen, Zhimin Jiang, Peng Zhang, Youji Li, Xin Li \\* South China Agricultural University; Zhengzhou University; Jishou University \n\n![](images/5f5ecc27be1f32ac9fe6714623c60223199ac790753e85828e22c22ae8c27856.jpg) \n\nConstructing an S‐scheme heterojunction reduces the recombination of photogen‐ erated electron‐hole pairs and maintains electrons with strong reducibility. The loading of MX offers more hydrogen active sites and effectively utilizes electrons for photocatalytic reactions though ohmic junctions. \n\ntric fields in a photocatalyst with a 2D advantageous structure to improve hydrogen evolution activity. It is anticipated that the 2D layered S‐scheme heterojunction could be widely de‐ signed and constructed to improve hydrogen evolution activity and other potential energy‐ and environment‐related applica‐ tions. \n\n# Electronic supporting information \n\nSupporting information is available in the online version of this article. \n\n# References \n\n[1] A. Kudo, Y. Miseki, Chem. Soc. Rev., 2009, 38, 253–278. \n[2] R. Shen, J. Xie, Q. Xiang, X. Chen, J. Jiang, X. Li, Chin. J. Catal., 2019, 40, 240–288. \n[3] R. Shen, D. Ren, Y. Ding, Y. Guan, Y. H. Ng, P. Zhang, X. Li, Sci. China Mater., 2020, 63, 2153–2188. \n[4] J. B. Pan, S. Shen, W. Zhou, J. Tang, H. Z. Ding, J. B. Wang, L. Chen, C. T. Au, S. F. Yin, Acta Phys.‐Chim. Sin., 2020, 36, 1905068. \n[5] Z. Mei, G. Wang, S. Yan, J. Wang, Acta Phys.‐Chim. Sin., 2021, 37, 2009097. \n[6] J. Wei, Y. Chen, H. Zhang, Z. Zhuang, Y. Yu, Chin. J. Catal., 2021, 42, 78–86. \n[7] D. L. Huang, M. Wen, C. Y. Zhou, Z. H. Li, M. Cheng, S. Chen, W. J. Xue, L. Lei, Y. Yang, W. P. Xiong, W. J. Wang, Appl. Catal. B, 2020, 267, 118651. \n[8] Z. Liang, R. Shen, Y.H. Ng, P. Zhang, Q. Xiang, X. Li, J. Mater. Sci. Technol., 2020, 56, 89–121. \n[9] H. Hou, X. Zeng, X. Zhang, Sci. China Mater., 2020, 63, 2119–2152. \n[10] S. Ma, X. Xu, J. Xie, X. Li, Chin. J. Catal., 2017, 38, 1970–1980. \n[11] R. Shen, L. Zhang, X. Chen, M. Jaroniec, N. Li, X. Li, Appl. Catal. B, 2020, 266, 118619. \n[12] Y. Hu, X. Hao, Z. Cui, J. Zhou, S. Chu, Y. Wang, Z. Zou, Appl. Catal. B, 2020, 260, 118131. \n[13] D. Ren, W. Zhang, Y. Ding, R. Shen, Z. Jiang, X. Lu, X. Li, Solar RRL, 2019, 4, 1900423. \n[14] T. Hu, P. Li, J. Zhang, C. Liang, K. Dai, Appl. Surf. Sci., 2018, 442, 20–29. \n[15] S. Wang, B. Zhu, M. Liu, L. Zhang, J. Yu, M. Zhou, Appl. Catal. B, 2019, 243, 19–26. \n[16] H. M. Huang, Z. L. Wang, B. Luo, P. Chen, T. E. Lin, M. Xiao, S. C. Wang, B. Y. Dai, W. Wang, J. H. Kou, C. H. Lu, Z. Z. Xu, L. Z. Wang, Nano Energy, 2020, 69, 9. \n[17] Y. Lu, Y. Li, Y. Wang, J. Zhang, Appl. Catal. B, 2020, 272, 118979. \n[18] Z. Wang, Y. Chen, L. Zhang, B. Cheng, J. Yu, J. Fan, J. Mater. Sci. Technol., 2020, 56, 143–150. \n[19] C. Cheng, B. He, J. Fan, B. Cheng, S. Cao, J. Yu, Adv. Mater., 2021, 33, 2100317. \n[20] Q. Xie, W. He, S. Liu, C. Li, J. Zhang, P. K. Wong, Chin. J. Catal., 2020, 41, 140–153. \n[21] F. Mei, Z. Li, K. Dai, J. Zhang, C. Liang, Chin. J. Catal., 2020, 41, 41–49. \n[22] J. Fu, Q. Xu, J. Low, C. Jiang, J. Yu, Appl. Catal. B, 2019, 243, 556–565. \n[23] Q. Xu, L. Zhang, B. Cheng, J. Fan, J. Yu, Chem, 2020, 6, 1543–1559. \n[24] S. Sun, X. Zhang, X. Liu, L. Pan, X. Zhang, J. Zou, Acta Phys.‐Chim. Sin., 2020, 36, 1905007. \n[25] J. Ran, G. Gao, F. T. Li, T. Y. Ma, A. Du, S. Z. Qiao, Nat. Commun., 2017, 8, 13907. \n[26] R. Shen, Y. Ding, S. Li, P. Zhang, Q. Xiang, Y. H. Ng, X. Li, Chin. J. Catal., 2021, 42, 25–36. \n[27] X. Li, J. Yu, M. Jaroniec, X. Chen, Chem. Rev., 2019, 119, 3962–4179. \n[28] K. Li, S. Zhang, Y. Li, J. Fan, K. Lv, Chin. J. Catal., 2021, 42, 3–14. \n[29] P. Y. Kuang, J. X. Low, B. Cheng, J. G. Yu, J. J. Fan, J. Mater. Sci. Tech‐ nol., 2020, 56, 18–44. \n[30] J. Luo, Z. Lin, Y. Zhao, S. Jiang, S. Song, Chin. J. Catal., 2020, 41, 122–130. \n[31] D. Qin, Y. Xia, Q. Li, C. Yang, Y. Qin, K. Lv, J. Mater. Sci. Technol., 2020, 56, 206–215. \n[32] Y. Liu, X. Hao, H. Hu, Z. Jin, Acta Phys.‐Chim. Sin., 2021, 37, 2008030. \n[33] Y. Yang, Z. Zeng, G. Zeng, D. Huang, R. Xiao, C. Zhang, C. Zhou, W. Xiong, W. Wang, M. Cheng, W. Xue, H. Guo, X. Tang, D. He, Appl. Catal. B, 2019, 258,117956. \n[34] R. Xiao, C. Zhao, Z. Zou, Z. Chen, L. Tian, H. Xu, H. Tang, Q. Liu, Z. Lin, X. Yang, Appl. Catal. B, 2020, 268, 118382. \n[35] Z. Jiang, Q. Chen, Q. Zheng, R. Shen, P. Zhang, X. Li, Acta Phys.‐Chim. Sin., 2021, 37, 2010059. \n[36] D. Ren, R. Shen, Z. Jiang, X. Lu, X. Li, Chin. J. Catal., 2020, 41, 31–40. \n[37] D. Ren, Z. Liang, Y. H. Ng, P. Zhang, Q. Xiang, X. Li, Chem. Eng. J., 2020, 390, 124496. \n[38] J. Yu, Y. Yu, P. Zhou, W. Xiao, B. Cheng, Appl. Catal. B, 2014, 156, 184–191. \n[39] G. Zhuang, Y. Chen, Z. Zhuang, Y. Yu, J. Yu, Sci. China Mater., 2020, 63, 2089–2118. \n[40] T. Cai, L. Wang, Y. Liu, S. Zhang, W. Dong, H. Chen, X. Yi, J. Yuan, X. Xia, C. Liu, S. Luo, Appl. Catal. B, 2018, 239, 545–554. \n[41] H. Xu, R. Xiao, J. Huang, Y. Jiang, C. Zhao, X. Yang, Chin. J. Catal., 2021, 42, 107–114. \n[42] L. Gao, W. Bao, A. V. Kuklin, S. Mei, H. Zhang, H. Agren, Adv. Mater., 2021, 33, 2004129. \n[43] M. Ding, R. Xiao, C. Zhao, D. Bukhvalov, Z. Chen, H. Xu, H. Tang, J. Xu, X. Yang, Solar RRL, 2020, 5, 2000414. \n[44] S. Chen, D. Huang, P. Xu, W. Xue, L. Lei, M. Cheng, R. Wang, X. Liu, R. Deng, J. Mater. Chem. A, 2020, 8, 2286–2322. \n[45] M. Z. Rahman, M. G. Kibria, C. B. Mullins, Chem. Soc. Rev., 2020, 49, 1887–1931. \n[46] Q. Wang, K. Domen, Chem. Rev., 2020, 120, 919–985. \n[47] K. He, J. Xie, X. Luo, J. Wen, S. Ma, X. Li, Y. Fang, X. Zhang, Chin. J. Catal., 2017, 38, 240–252. \n[48] M. Q. Yang, Y. J. Xu, W. Lu, K. Zeng, H. Zhu, Q. H. Xu, G. W. Ho, Nat. Commun., 2017, 8, 14224. \n[49] R. Shi, Y. Cao, Y. Bao, Y. Zhao, G. I. N. Waterhouse, Z. Fang, L. Z. Wu, C. H. Tung, Y. Yin, T. Zhang, Adv. Mater., 2017, 29, 1700803. \n[50] J. Wen, J. Xie, H. Zhang, A. Zhang, Y. Liu, X. Chen, X. Li, ACS Appl. Mater. Inter., 2017, 9, 14031–14042. \n[51] K. He, J. Xie, Z.‐Q. Liu, N. Li, X. Chen, J. Hu, X. Li, J. Mater. Chem. A, 2018, 6, 13110–13122. \n[52] H. Zhao, Y. Dong, P. Jiang, H. Miao, G. Wang, J. Zhang, J. Mater. Chem. A, 2015, 3, 7375–7381. \n[53] L. Hao, L. Kang, H. Huang, L. Ye, K. Han, S. Yang, H. Yu, M. Bat‐ munkh, Y. Zhang, T. Ma, Adv. Mater., 2019, 31, 1900546. \n[54] R. Shen, J. Xie, H. Zhang, A. Zhang, X. Chen, X. Li, ACS Sustain. Chem. Eng., 2017, 6, 816–826. \n[55] P. Ye, X. Liu, J. Iocozzia, Y. Yuan, L. Gu, G. Xu, Z. Lin, J. Mater. Chem. A, 2017, 5, 8493–8498. \n[56] Q. Qiu, S. Li, J. Jiang, D. Wang, Y. Lin, T. Xie, J. Phys. Chem. C, 2017, 121, 21560–21570. \n[57] S. Wageh, A.A. Al‐Ghamdi, R. Jafer, X. Li, P. Zhangc, Chin. J. Catal., 2021, 42, 667–669. \n[58] F. Shi, Z. Geng, K. Huang, Q. Liang, Y. Zhang, Y. Sun, J. Cao, S. Feng, Adv. Sci., 2018, 5, 1800575. \n[59] R. Shen, X. Lu, Q. Zheng, Q. Chen, Y. H. Ng, P. Zhang, X. Li, Solar RRL, 2021, 2100177. \n[60] J. Low, B. Dai, T. Tong, C. Jiang, J. Yu, Adv. Mater., 2019, 31, 1802981. \n[61] J. S. H. Li, Z. Yang, W. Shen, Z. Ai, L. Zhang, Environ. Sci. Technol., 2017, 51, 5685–5694. \n[62] H. Li, F. Qin, Z. Yang, X. Cui, J. Wang, L. Zhang, J. Am. Chem. Soc., 2017, 139, 3513–3521. \n[63] M. Ghidiu, M. R. Lukatskaya, M. Q. Zhao, Y. Gogotsi, M. W. Barsoum, Nature, 2014, 516, 78–81. \n\n# 集成二维层状 $\\mathbf{CdS}/\\mathbf{WO}_{3}$ S型异质结及金属化 $\\mathbf{Ti}_{3}\\mathbf{C}_{2}$ MXene基欧姆结高效光催化产氢 \n\n白浚贤a,†, 沈荣晨a,†, 姜志民a, 张 鹏b, 李佑稷c, 李 鑫a,\\* \na华南农业大学生物质工程研究院, 农业部能源植物资源与利用重点实验室, 广东广州510642 \nb郑州大学材料与工程学院, 低碳环保材料智能设计国际联合研究中心, 河南郑州450001c吉首大学化学化工学院, 湖南吉首416000 \n\n摘要: 开发低成本的半导体光催化剂以实现可见光下高效、持久的光催化分解水产氢是一个非常具有挑战性的课题. 近年来, 具有高产氢活性的CdS光催化剂引起了人们的研究兴趣. 但是光生电子-空穴对快速复合、反应活性位点不足以及严重的光腐蚀等问题, 严重地制约了CdS在光催化领域的实际应用. 构建S型异质结和负载助催化剂被认为是促进光生电子空穴分离和加速产氢动力学的有效策略. 本文通过在低成本的 $\\mathrm{WO}_{3}$ 和 $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene (MX)纳米片上生长CdS纳米片, 设计并构建了具有二维耦合界面的2D/2D/2D层状异质结光催化剂, 以实现高效的可见光光催化分解水产氢. 首先通过水热煅烧和刻蚀的方法分别制备了 $\\mathrm{WO}_{3}$ 和MX纳米片, 然后以乙酸镉和硫脲为原料在乙二胺溶剂中通过水热法合成了MX-CdS/WO 层状异质结光催化剂. 在可见光下, 以乳酸为牺牲剂测试了光催化剂的产氢活性且经过4次连续的循环反应, MX-CdS/WO 体系展现出良好的活性及稳定性. 在可见光的照射下, $\\mathrm{MX-CdS/WO_{3}}$ 层状异质结光催化剂最高的可见光光催化分解水产氢速率达到了 $27.5\\mathrm{mmol/g/h}$ , 是纯CdS纳米片的11倍. 与此同时, 在 $450\\ \\mathrm{nm}$ 的光照下, 表观量子效率达到了 $12.0\\%$ . \n\n为了深入探讨其高效产氢机理, 通过X射线衍射、X射线光电子能谱、原子力显微镜、透射电镜、高分辨电子显微镜等对MX-CdS $\\mathrm{wo}_{3}$ 体系的组成和结构进行分析. 结果表明, 实验成功地合成了CdS, $\\mathrm{WO}_{3}$ 和MX三种纳米片及其复合材料.通过紫外-可见漫反射光谱研究了样品材料的光吸收能力. 通过表面光电压、稳态及瞬态荧光光谱等研究了材料的电荷载流子复合和转移行为, 发现MX-CdS $\\mathrm{\\Delta}/\\mathrm{WO}_{3}$ 的光生电子空穴对相比与纯CdS或者二元复合材料具有更高的分离效率. UPS和ESR等表征结果说明, 材料内部电场的方向和在光照条件下光生载流子的迁移方向, 从而证实了S型异质结和欧姆结的成功构建. 综上, 在MX-CdS $\\mathrm{wo}_{3}$ 光催化剂体系中, S型异质结形成较强的界面电场能够有效促进CdS纳米片与 $\\mathrm{WO}_{3}$ 纳米片之间光生电子-空穴对的分离. 同时, 二维 $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene纳米片作为辅助催化剂, 通过与 $\\mathrm{CdS}/\\mathrm{WO}_{3}$ 纳米片构建欧姆结, 进而提供大量的电子转移途径和更多的析氢反应活性位点, 使得CdS光催化剂的光催化活性和稳定性得到了很大的提升. \n\n通过构建S型内建电场、欧姆结和2D/2D界面可以协同提高CdS纳米片的光催化性能, 从而加速光生电子在异质结中的分离和利用. 本文所采用基于S型异质结与欧姆结基助催化剂之间的耦合策略可以作为一种通用策略扩展到其它传统半导体光催化剂的改性中, 从而推进高效光催化产氢材料的有效合成. \n\n关键词: 光催化分解水产氢; 2D层状S型异质结; CdS纳米片; $\\mathrm{WO}_{3}$ 纳米片; $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene基欧姆结; 2D耦合界面 \n\n收稿日期: 2021-05-08. 接受日期: 2021-06-26. 上网时间: 2022-01-03. \n\\*通讯联系人. 电话: (020)85282633; 传真: (020)85285596; 电子信箱: xinli@scau.edu.cn†共同第一作者. \n基金来源: 国家自然科学基金(21975084, 51672089)和华南农业大学丁颖人才计划. \n本文的电子版全文由Elsevier出版社在ScienceDirect上出版(http://www.sciencedirect.com/journal/chinese-journal-of-catalysis). " + }, + { + "id": "10.1016_j.ssc.2021.114573", + "DOI": "10.1016/j.ssc.2021.114573", + "DOI Link": "http://dx.doi.org/10.1016/j.ssc.2021.114573", + "Relative Dir Path": "mds/10.1016_j.ssc.2021.114573", + "Article Title": "Use and misuse of the Kubelka-Munk function to obtain the band gap energy from diffuse reflectance measurements", + "Authors": "Landi, S Jr; Segundo, IR; Freitas, E; Vasilevskiy, M; Carneiro, J; Tavares, CJ", + "Source Title": "SOLID STATE COMMUNICATIONS", + "Abstract": "The determination of the optical band gap energy (E-g) is important for optimization of the generation of electron/hole pairs in semiconductor materials under illumination. For this purpose, the classical theory proposed by Kubelka and Munk (K-M) has been largely employed for the study of amorphous and polycrystalline materials. In this paper, the authors demonstrate, step by step, how to use the K-M function and apply it thoroughly to the determination of the E-g of TiO2 semiconductor powder (pressed at different thicknesses) from diffuse reflectance spectroscopy (DRS) measurements. For the sample thicknesses 1-4 mm, E-g values of 3.12-3.14 eV were obtained. With this work it is envisaged a clarification to the procedure of determination of the E-g from the K-M theory and DRS data, since some drawbacks, and misconceptions have been identified in the recent literature. In particular, the widely used practice of determining the E-g of a material directly from the K-M function is found to be inadequate.", + "Times Cited, WoS Core": 328, + "Times Cited, All Databases": 332, + "Publication Year": 2022, + "Research Areas": "Physics", + "UT (Unique WOS ID)": "WOS:000725057500009", + "Markdown": "# Use and misuse of the Kubelka-Munk function to obtain the band gap energy from diffuse reflectance measurements \n\nSalmon Landi Jr. a,\\*, Iran Rocha Segundo b, Elisabete Freitas b, Mikhail Vasilevskiy c,d, Joaquim Carneiro c, Carlos Jos´e Tavares c \n\na Federal Institute Goiano, Rio Verde, Goi´as, 75901-970, Brazil b Civil Engineering Department, University of Minho, Guimar˜aes, 4800-058, Portugal c Centre of Physics of the Universities of Minho and Porto, Braga, 4710-057, Portugal d International Iberian Nanotechnology Laboratory (INL), Av. Mestre Jos´e Veiga, 4715-330 Braga, Portugal \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nCommunicated by: L. Brey \n\nKeywords: \nDiffuse reflectance \nKubelka-Munk model \nTauc plot \nBand gap energy \n\nThe determination of the optical band gap energy $(E_{g})$ is important for optimization of the generation of elec­ tron/hole pairs in semiconductor materials under illumination. For this purpose, the classical theory proposed by Kubelka and Munk (K-M) has been largely employed for the study of amorphous and polycrystalline materials. In this paper, the authors demonstrate, step by step, how to use the K-M function and apply it thoroughly to the determination of the $E_{g}$ of $\\mathrm{TiO}_{2}$ semiconductor powder (pressed at different thicknesses) from diffuse reflectance spectroscopy (DRS) measurements. For the sample thicknesses $1{-}4\\mathrm{mm}$ , $E_{g}$ values of $3.12\\mathrm{-}3.14\\mathrm{eV}$ were obtained. With this work it is envisaged a clarification to the procedure of determination of the $E_{g}$ from the K-M theory and DRS data, since some drawbacks, and misconceptions have been identified in the recent literature. In particular, the widely used practice of determining the $E_{g}$ of a material directly from the K-M function is found to be inadequate. \n\n# 1. Introduction \n\nSemiconductor materials have received increasing attention in the photocatalysis field because of their ability to degrade various pollutants present in water or air through a sequence of redox reactions [1–5]. The photocatalytic ability of semiconductors is related to the excitation of electrons from the valence band to the conduction band caused by the absorption of a photon with an appropriate wavelength. The photoex­ cited electrons and holes are good reductant and powerful oxidant species, respectively [6–8]. In this scenario, the application of semi­ conductor materials for environmental remediation in large scale will depend, among other factors, on its activation in an effective way by solar radiation. In this sense, the scientific community has investigated different strategies that allow a more efficient absorption of visible light by wide-gap semiconductors, such as $\\mathrm{TiO}_{2}$ [9–12]. \n\nDiffuse Reflectance Spectroscopy (DRS) with a UV–visible spectro­ photometer is a technique frequently employed to study the optical properties of solids. In this context, the classical Kubelka-Munk (K-M) \n\nmodel has been extensively employed to understand the light scattering from the surface of semiconductor powder materials [13,14]. Initially, Paul Kubelka and Franz Munk proposed a theoretical approach to study how the colour of a substrate is changed after the application of a paint layer with certain composition and thickness [15]. At present, the K-M model is commonly used to analyse DRS results and estimate the optical band gap energy (or simply the band gap) of semiconductor materials [16]. \n\nHowever, in a number of papers published recently, including some in prestigious journals in the field of Materials Science, some in­ consistencies have been detected when the subject matter is the K-M model and the so-called Tauc plot [17–19]. Specifically, the most serious problem consists in determining of the band gap energy directly from the plot of the Kubelka-Munk function versus incident photon energy [20–23]. From the authors of this manuscript point of view, these oversimplified or even incorrect interpretations may confuse the readers concerning the applicability and validity of the K-M model, which are discussed in detail in this work. \n\nTherefore, the main objective of this work is to explain all the necessary steps to obtain the band gap from DRS data of a poly­ crystalline powder of the wide-gap semiconductor $\\mathrm{TiO}_{2}$ . Thus, with this work it is expected to help researchers who are starting their studies involving the determination of the band gap from DRS data and to clarify the procedure to those who could be confused due to the various drawbacks previously identified. \n\n# 2. Kubelka-Munk model \n\nKubelka and Munk suggested that the absorption and scattering are first order phenomena [15]. The system in study consists of a substrate coated with a certain material of interest, which is illuminated with diffuse monochromatic radiation. Moreover, this system must have a disk form (cylindrical geometry) with a flat area $A$ and a thickness $L$ , so boundaries’ effect is neglected. The incident light has intensity I and the reflected portion has intensity $J_{;}$ , which allows to define a dimensionless quantity, the reflectance: $R=J/I$ . Naturally, $R$ depends on $L$ and the absorption and scattering properties of the medium (Appendix). \n\nWhen considering a sample with semi-infinite thickness $(L\\to\\infty)$ ), K-M model implies: \n\n$$\n\\frac{K}{S}=\\frac{\\left(1-R\\right)^{2}}{2R},\n$$ \n\nwhere $K$ and $s$ are the K-M absorption and scattering coefficients respectively. Eq. (1) provides the correct definition of the Kubelka-Munk function $(F(R)=K/S)$ [24]. It is important to emphasize that the Eq. (1) describes a particular case of the K-M model $(L{\\rightarrow}\\infty)$ , which correspond physically to a medium that reflects the same amount of light regardless of the substrate reflectance value. Murphy affirms that typically a thickness of $1{-}3\\mathrm{mm}$ is required [25]. In concordance, Escobedo-Morales et al. state that, in practice, thicknesses ${>}2~\\mathrm{mm}$ are sufficient to avoid any contribution from substrate [26]. \n\nDue to the fact that $K$ and S have the units of inverse length, $F(R)$ is a dimensionless quantity. Therefore, $F(R)$ multiplied by the photon energy $(E)$ , which appears frequently in the band gap determination from the DRS data, has, necessarily, the units of energy. Unfortunately, incorrect unit of $F(R)\\times E$ has been identified [27] or the authors do not specify the respective unit [28–30], which is ambiguous. \n\nFinally, the reader could question whether the model where the light travels in only one direction is appropriate to represent the diffuse reflection phenomenon. In this sense, a detailed study that accounts for the angular dependence of diffused scattering light intensity by a me­ dium was published by Myrick et al. [31]. These authors showed that Eq. (1) applies also in three dimensions when $L{\\rightarrow}{\\infty}$ , the scattering is isotropic and the medium is homogeneous. \n\n# 3. Absorption and scattering coefficients \n\nThis section presents the dependence of the absorption $(\\alpha)$ and scattering (s) coefficients of a semiconductor (or insulator) material as a function of the incident photon energy $(E)$ . In fact, $\\alpha$ and $s$ are intrinsic optical properties of the materials and represent the probabilities of light being absorbed and scattered, respectively, per unit path length [32]. The standard assumption is that the absorption occurs essentially in the material while the scattering is due to material’s inhomogeneity and, to the first approximation, may be considered as independent of the ab­ sorption. The theory of scattering by fluctuations of the dielectric con­ stant in a non-absorbing material has been developed by several authors and, while these theoretical considerations may differ in details, the main result is the following [33]. If the characteristic scale of the in­ homogeneities, d, is much smaller than the wavelength, $d\\ll\\lambda$ , the scattering coefficient is proportional to the fourth power of the photon energy: \n\n$$\ns{\\propto}E^{4},\n$$ \n\nwhich is the case known as the Rayleigh scattering. In the opposite case, $\\lambda{\\ll}d$ , a weaker dependence takes place: \n\nThe spectral dependence of the absorption coefficients is specific for the type of investigated material. For semiconductors, the principal absorption mechanism is due to interband transitions and the absorption coefficient can be written in the following form [34]: \n\n$$\n\\alpha(E)\\propto\\frac{\\left(E-E_{g}\\right)^{p}}{E},\n$$ \n\nwhere the exponent $p$ depends on the band structure of the semi­ conductor material and $E_{g}$ is an important parameter called the optical band gap energy and defined as the energy difference between the bottom of the conduction band and the top of the valence band. In particular, $p=1/2$ for dipole-allowed transitions occurring at a direct band gap, while $p=2$ for dipole-allowed transitions near an indirect gap where the participation of phonons is required. Besides that, there are also relevant cases of dipole-forbidden transitions (direct gap $\\scriptstyle p=3/2$ and indirect gap $p=3\\AA$ ), where the dipolar transitions are suppressed because the involved orbitals have the same parity. In general, such processes are much less likely (weak light absorption or emission) and are sometimes called weakly allowed transitions. As a very instructive example, we recommend reading the work published by Malerba et al. [35], which discusses the contributions of different transition types to the total absorption coefficient of bulk and thin film $\\mathtt{C u_{2}O}$ . \n\nUsing a statistical analysis of light propagation in media, Yang and Kruse proposed a revision to K-M theory by taking into account the effect of scattering on the path length of light propagation [36]. In this case, the authors demonstrated that the $K$ and S parameters depend on the illumination geometry and, consequently, do not represent physical properties of materials. Anyway, Eqs. 35 and 36 in Ref. [36] allow us to conclude that $\\boldsymbol{K}$ and $s$ depend on the intrinsic absorption $\\alpha$ and scat­ tering $s$ coefficients of the material such that: \n\n$$\n{\\frac{\\alpha}{-s}}\\alpha{\\frac{K}{S}}.\n$$ \n\nIn other words, it is not correct to interpret the K-M function (Eq. (1)) as the absorption coefficient [37]. Besides that, it is important to specify that the definition of $F(R)$ involves the K-M coefficients $(K$ and S) in order to avoid a possible confusion with the $\\alpha$ and $s$ coefficients [38–40]. \n\nOnce the diffuse reflectance is measured, Eq. (1) yields the ratio between the K-M absorption and scattering coefficients. Combining Eqs. (1)–(4) and taking into account the power-law energy dependence of the scattering coefficient as $s{\\propto}E^{q}$ (where $q=2$ or 4, according to Eq. (2)), it is possible to write: \n\n$$\nF(R)\\propto\\frac{\\left(E-E_{g}\\right)^{p}/E}{E^{q}}.\n$$ \n\nIn the vicinity of $E_{g}$ , it is possible to approximate the relatively slowly varying factor $E^{q}$ , in comparison to the $\\alpha$ , by a constant. In other words, the scattering phenomenon has been neglected $\\mathit{\\Pi}_{\\mathcal{S}}$ and S are being considered as constants). This allows us to write \n\n$$\n(F(R)\\times E)^{\\frac{1}{p}}=A\\big(E-E_{g}\\big),\n$$ \n\nwhere A is a proportionality constant independent of the photon energy. \n\nFor amorphous and polycrystalline materials, the density of states is non-zero inside the gap, with disorder-induced band tails, so the band gap width is not well defined. Band tail states are, in fact, electronic states present just above the valence band or right below the conduction band. In general, these states originate from thermal, structural, impu­ rity and/or compositional disorder [41]. So, for these materials, the common procedure is to use the so-called Tauc plot obtained by extrapolating the dependence Eq. (6) to zero (while the real absorption coefficient for those energies is still non-zero because of the band tails) [42]. That is, it is clear from Eq. (6) that the $E_{g}$ must be obtained by extrapolating to zero a linear fit to a plot of $(F(R)\\times E)^{1/p}$ versus $E$ . In general, the authors take the liberty of using the “Tauc plot” designation in other similar plots that also aim to obtain $E_{g}$ by extrapolation. \n\n# 4. Application of K-M function and Tauc plot to determine the band gap energy \n\nThe main goal of this section is to emphasize that the determination of $E_{g}$ from the plot $F(R)$ versus $E$ is an inadequate procedure, although recently practiced by several authors [20–23]. The $E_{g}$ of commercial $\\mathrm{TiO}_{2}$ nanoparticles will be calculated from diffuse reflectance data analysed according to Eqs. (1) and (6). For this purpose, diffuse reflec­ tance spectroscopy (DRS) measurements were carried out using a Shi­ madzu 2501 PC spectrophotometer equipped with an integrating sphere. Barium Sulphate $(\\mathrm{BaSO_{4}})$ was used as reference for the reflec­ tance spectra, which means that the value of $R$ in Eq. (1) is actually taken to be the $R_{s a m p l e}/R_{B a S O_{4}}$ ratio. $\\mathrm{TiO}_{2}$ nanoparticles, consisting of a mixture of anatase $(80\\%)$ and rutile $(20\\%)$ crystalline phases, were inserted into the circular cavity of the sample support and then compressed by a glass rod. To analyse the impact of thickness in obtaining $F(R)$ , different samples were compressed with 0.5, 1.0, 1.7, 2.0, 2.5 and $4.0\\ \\mathrm{mm}$ layer thickness. \n\nParticularly, it is interesting to determine whether the thickness of the material deposited on the support satisfies the condition utilized to obtain $F(R)$ , i.e., $L$ tends to infinity. Physically, this means that an in­ crease in the thickness of the material does not cause a significant change in its reflectance or analogously in the $F(R)$ . Technically, it was verified if there are differences between the results of reflectance for the maximum sample thickness allowed by the support (the height of support cavity is equal to $4.0\\ \\mathrm{mm}$ ) in comparison with thinner thick­ nesses (0.5, 1.0, 1.7, 2.0, $2.5\\ \\mathrm{mm}$ ). Fig. 1a illustrates the reflectance results of the $\\mathrm{TiO}_{2}$ samples as a function of the incident radiation wavelength (in the range $300{\\mathrm{-}}750~\\mathrm{nm}.$ obtained from DRS. \n\nPractically, for $\\lambda>430~\\mathrm{~nm}$ all radiation is reflected by $\\mathrm{TiO}_{2}$ $(R\\approx100\\%)$ , for which reason the powders appears white. On the other hand, for $\\lambda<300\\mathrm{nm}$ the incident photons have the energy sufficient for the electron/hole generation and, therefore, are almost completely absorbed by the material (the reflectance is very low). In fact, the slight differences observed in the spectra are more evident for the whole wavelength range shown in Fig. 1b. It is noted that the curves are very close to each other, except for the one corresponding to the sample of thickness equal to $0.5~\\mathrm{mm}$ , suggesting that the sample support reflec­ tance may have affected the spectrum of this sample. Furthermore, it is possible conclude that the wavelength correspondent to the band gap energy, or absorption edge, is most likely located between ${\\sim}420~\\mathrm{nm}$ or $2.95\\mathrm{eV}$ (beginning of absorption of radiation by sample, which $R$ starts to decrease) and ${\\sim}320~\\mathrm{nm}$ or $3.88\\mathrm{eV}$ (value from which almost all ra­ diation is absorbed, i.e., $R\\approx0.$ ). However, as discussed previously, in the vicinity of the absorption edges (320 and $420\\mathrm{nm}\\mathrm{.}$ , there is an influence of the band tails, which cannot be assessed by DRS measurements. From the data illustrated in Fig. 1, $(F(R)\\times E)^{1/2}$ (Fig. 2a) and $F(R)$ (Fig. 2b) were plotted as a function of the incident photon energy, considering the wavelength range between ${\\sim}320$ and ${\\sim}420~\\mathrm{nm}$ . \n\nIt is noteworthy to point out that the curves shown in Fig. 2a (Fig. 2b) present a more pronounced linearity in the range approximately be­ tween ${\\sim}3.2$ and ${\\sim}3.8$ eV ( $_{\\cdot\\sim3.3}$ and ${\\sim}3.8~\\mathrm{eV}.$ ). The correct procedure consists in plotting the $(F(R)\\times E)^{1/2}$ (and not $F(R)_{}^{}$ )versus $E$ fitting the linear portion of this curve by a straight line, which the intercept divided by the slope (in modulus) provides the numerical value for $E_{g}$ (Table 1). The uncertainties (calculated from the linear fit parameters) in Table 1 were determined through error propagation calculations using the quotient rule. \n\nAs it is well known, anatase-rutile binary systems perform better in photocatalytic processes in terms of efficiency, compared to the case when only one of these isolated components is used [43]. So, there is an extensive range of band gap values presented in the scientific literature for $\\mathrm{TiO}_{2}$ resulting from the combination of rutile and anatase phases. Also, the optical properties, in general, show some variations depending on the experimental conditions used to synthesize the samples, chemical composition and degree of disorder [44]. Howsoever, the band gap values obtained from the linear fits to $(F(R)\\times E)^{1/2}$ versus $E$ are in reasonable agreement with those $(3.18\\mathrm{eV})$ reported by Rodríguez et al. [45], unlike the values presented in the last column of Table 1. Addi­ tionally, it is important to note that the $E_{g}$ obtained for $0.5\\mathrm{mm}$ sample $(3.05\\mathrm{eV})$ is slightly lower than the expected value for non-doped $\\mathrm{TiO}_{2}$ nanoparticles consisting of a mixture of anatase $(80\\%)$ and rutile $(20\\%)$ crystalline phases $(3.19\\mathrm{eV})$ [46]. In fact, this thickness is not adequate to apply the K-M function (Eq. (1)), as explained in Section 2. This suggests that the $E_{g}$ reported by Polat is probably incorrect because the K-M function was applied to analyse DRS measurements for a $\\mathtt{C u_{2}O}$ film with a thickness of approximately $291~\\mathrm{nm}$ [47]. \n\n![](images/64046b3400875f10657b51c889a71e4de41acf32c345bbfb913d33a96ae266e4.jpg) \nFig. 1. DRS spectra of $\\mathrm{TiO}_{2}$ samples pressed at different thicknesses and the sample support, plotted in wavelength range $300{\\mathrm{-}}750~\\mathrm{nm}$ (a) and $320{\\-}420\\ \\mathrm{nm}$ (b). \n\n![](images/cc38e116ba5a81e2a3385cb83f267fe3aad7d94643f3573718553ba32e002428.jpg) \nFig. 2. Curves corresponding to the DRS patterns showed in Fig. 2 using: (a) Eq. (6) considering an indirect gap $(p=2)$ and (b) Eq. (1). \n\nTable 1 Indirect band gap values for $\\mathrm{TiO}_{2}$ powder layers with varying thicknesses calculated from the linear fits to $({F}(R)\\times E)^{1/2}$ versus E(Fig. 2a, interval between 3.2 and $3.8\\mathrm{eV},$ and $F(R)$ versus E(Fig. 2b, interval between 3.3 and $3.8\\mathrm{{eV}}$ . \n\n\n
Thickness (mm)Eg(eV) from Fig.2aEg (eV)from Fig. 2b
0.53.05 ± 0.033.23 ± 0.03
1.03.14 ± 0.023.33 ± 0.05
1.73.14 ± 0.023.33 ± 0.05
2.03.12 ± 0.023.32 ± 0.04
2.53.11 ± 0.013.30 ± 0.03
4.03.12 ± 0.013.31 ± 0.03
\n\n# 5. Conclusion \n\nThis work is aimed to discuss the K-M model and apply it to the analysis of diffuse reflectance data for a medium in form of powder pressed at different thicknesses. Also, the necessary steps to interpret $F(R)$ and its use for the determination of the band gap are presented and discussed in order to avoid any misunderstanding and inconsistencies. It is shown that, for a sample with a semi-infinite thickness, the $F(R)$ is defined as the ratio between the K-M absorption $(K)$ and scattering (S) coefficients. Since these two coefficients have the same dimensions, the K-M function is dimensionless. \n\nTauc plots were performed for pressed $\\mathrm{TiO}_{2}$ nanoparticles with varying layer thickness in order to study the dependence of this property in the experimental determination of the band gap value. It was concluded that a thickness of about $0.5\\mathrm{mm}$ is not sufficient for the use of the $F(R)$ in the investigated samples. Finally, the authors hope that this work can be useful to supress the various inconsistencies verified in recent works about the concepts involved in the application of the K-M model and Tauc plots. \n\n# Declaration of competing interest \n\nThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \n\n# Appendix. Original derivation of the Kubelka-Munk function \n\nKubelka and Munk proposed differential equations for the changes of incident light intensity going downward (i) and going upward (j) at any point $x$ within the film material medium [15]. At this moment, it is pertinent to answer the following question: how to calculate the reflectance for a layer of thickness dx located at a distance $x$ from the substrate, inside the material? For this, it is necessary to quantify the incident and reflected flux within dx (Fig A1). \n\n![](images/4e013d3f0e2a79d4d834a4fa3a73d0f941ba1e0f4f1d62796eef5d53e588685e.jpg) \nFig. A1. Material medium of thickness $L$ over a substrate. The medium represents the semiconductor under study and the substrate refers to the sample support (an accessory utilized in DRS experiments of, consisting, in general, in a black metallic piece with a circular cavity to insert the sample). \n\nThe infinitesimal variation of $i(d i)$ is due to the: (I) material absorption presented within the volume of thickness dx – in this case, i suffers a decrease $(d i<0)$ ; (II) scattering of light going downward – di is also negative; and (III) scattering of light going upward – here, di is positive. After these considerations, the following equation is derived: \n\n$$\nd i=-K i d x-S i d x+S j d x,\n$$ \n\nwhere $K$ and S are the Kubelka-Munk absorption and scattering coefficients respectively; are positive and have units of inverse length. If the second and third members (in the right hand side of Eq. (A1)) are negligible, the Beer-Lambert equation is obtained. Similarly, the following equation for the change in light intensity going upward can be derived: \n\n$$\nd j={\\bf-}K j d x-S j d x+S i d x.\n$$ \n\nIt is important to note that dx has different signs in Eqs. A1 and A2. Therefore, when considering the positive $x$ axis oriented upwards, $d x$ is negative in Eq. (A1) and the $d i$ term on the left side of this equation must be replaced by – di. To solve these differential equations, it is useful to sum the results Eq. (A1) divided by $i$ (considering the correct signal) and Eq. (A2) divided by $j,$ resulting in the Eq. (A3). \n\n$$\n\\frac{d j}{j}-\\frac{d i}{i}=-2(K+S)d x+S\\binom{j}{i}+\\frac{i}{j}\\alpha\n$$ \n\nUsing the logarithm function properties and defining the reflectance of layer $d x$ as $r=j/i$ (analogous to $R=J/I)$ , Eq. (A3) can be written as: \n\n$$\n\\begin{array}{l}{\\displaystyle d(\\ln r)=-2(K+S)d x+S\\bigg(r+\\frac{1}{r}\\bigg)d x,}\\\\ {\\displaystyle\\frac{d r}{r}=-2(K+S)d x+S\\bigg(r+\\frac{1}{r}\\bigg)d x,}\\\\ {\\displaystyle d r=\\bigg[r^{2}-2\\bigg(\\frac{K+S}{S}\\bigg)r+1\\bigg]S d x,}\\\\ {\\displaystyle\\frac{d r}{\\bigg[r^{2}-2\\bigg(\\frac{K+S}{S}\\bigg)r+1\\bigg]}=S d x.}\\end{array}\n$$ \n\nDefining $K/S+\\cal{1}=a$ (constant for an optically homogeneous medium [36]) and integrating over the entire thickness of the sample, Eq. (A4d) can be written as: \n\n$$\n\\int_{R_{s}}^{R}\\frac{d r}{r^{2}-2a r+1}=S L,\n$$ \n\nwhere $R$ and $R_{s}$ are the reflectance on the coating surface (i.e. of the sample itself) and the substrate (sample support), respectively. The integral from Eq. (A5) can be solved by the partial fractions method, yielding the following result: \n\n$$\n\\frac{1}{2\\sqrt{a^{2}-1}}\\ln\\left[\\left(\\frac{R-a-\\sqrt{a^{2}-1}}{R-a+\\sqrt{a^{2}-1}}\\right)\\left(\\frac{R_{s}-a+\\sqrt{a^{2}-1}}{R_{s}-a-\\sqrt{a^{2}-1}}\\right)\\right]=S L.\n$$ \n\nWhen considering a sample with semi-infinite thickness $(L{\\rightarrow}\\infty)$ , practically speaking, a layer that is sufficiently thick to “hinder” the substrate influence, Eq. (A6) implies: \n\n$$\nR-a+{\\sqrt{a^{2}-1}}=0.\n$$ \n\nRearranging Eq. (A7), Eq. (A8) becomes: \n\n$$\n\\frac{K}{S}{=}\\frac{\\left(1-R\\right)^{2}}{2R}\\equiv F{(R)},\n$$ \n\nwhich is the K-M function, $F(R)$ . \n\n# Author contributions \n\nSalmon Landi Jr: Conceptualization, Writing – original draft preparation, Project administration. Iran Rocha Segundo: Methodology, Investigation, Data curation. Elisabete Freitas: Validation, Supervision. Mikhail Vasilevskiy: Writing – original draft preparation. Joaquim Carneiro: Resources. Carlos Jos´e Tavares: Writing - Reviewing & Editing. \n\n# References \n\n[1] H. Derikvandi, A. Nezamzadeh-Ejhieh, A comprehensive study on electrochemical and photocatalytic activity of $\\mathbf{SnO}_{2}$ -ZnO/clinoptilolite nanoparticles, J. Mol. Catal. Chem. 426 (2017) 158–169, https://doi.org/10.1016/j.molcata.2016.11.011. \n[2] A. Rahmani-Aliabadi, A. Nezamzadeh-Ejhieh, A visible light FeS/Fe2S3/zeolite photocatalyst towards photodegradation of ciprofloxacin, J. Photochem. Photobiol., A 357 (2018) 1–10, https://doi.org/10.1016/j. jphotochem.2018.02.006. \n[3] H. Derikvandi, A. Nezamzadeh-Ejhieh, Comprehensive study on enhanced photocatalytic activity of heterojunction ZnS-NiS/zeolite nanoparticles: experimental design based on response surface methodology (RSM), impedance spectroscopy and GC-MASS studies, J. Colloid Interface Sci. 490 (2017) 652–664, https://doi.org/10.1016/j.jcis.2016.11.105. \n[4] L. de Oliveira Pereira, I. Marques Sales, L. Pereira Zampiere, S. Silveira Vieira, I. do Rosa´rio Guimara˜es, F. Magalh˜aes, Preparation of magnetic photocatalysts from $\\mathrm{TiO}_{2}$ activated carbon and iron nitrate for environmental remediation, J. Photochem. Photobiol., A 382 (2019) 111907, https://doi.org/10.1016/j. jphotochem.2019.111907. \n[5] H. Yu, W. Dai, G. Qian, X. Gong, D. Zhou, X. Li, X. Zhou, The $\\mathsf{N O}_{\\mathbf{x}}$ degradation performance of nano- $\\mathrm{TiO}_{2}$ coating for asphalt pavement, Nanomaterials 10 (2020) 897, https://doi.org/10.3390/nano10050897. \n[6] A. Yousefi, A. Nezamzadeh-Ejhieh, M. Mirmohammadi, $\\mathsf{S n O}_{2}\\mathrm{-BiVO}_{4}$ mixed catalyst: characterization and kinetics study of the photodegradation of phenazopyridine, Environ. Technol. & Innovation 22 (2021) 101433, https://doi. org/10.1016/j.eti.2021.101433. \n[7] A. Noruozi, A. Nezamzadeh-Ejhieh, Preparation, characterization, and investigation of the catalytic property of $\\mathrm{\\sf{\\alpha}}\\mathrm{-}\\mathrm{Fe}_{2}\\mathrm{O}_{3}\\mathrm{-}\\mathrm{ZnO}$ nanoparticles in the photodegradation and mineralization of methylene blue, Chem. Phys. Lett. 752 (2020) 137587, https://doi.org/10.1016/j.cplett.2020.137587. \n[8] N. Pourshirband, A. Nezamzadeh-Ejhieh, S.N. Mirsattari, The $\\mathrm{CdS}/\\mathrm{g}{\\mathrm{-C}}_{3}\\mathrm{N}_{4}$ nanophotocatalyst: brief characterization and kinetic study of photodegradation and mineralization of methyl orange, Spectrochim. Acta Mol. Biomol. Spectrosc. 248 (2021) 119110, https://doi.org/10.1016/j.saa.2020.119110. \n[9] M.A. Draz, H.H. El-Maghrabi, F.S. Soliman, H. Selim, A. Abdel Razik, A. El-sayed Amin, Y.M. Moustafa, A. Hamdy, A.A. Nada, Large scale hybrid magnetic $\\mathrm{ZnFe_{2}O_{4}/}$ $\\mathrm{TiO}_{2}$ nanocomposite with highly photocatalytic activity for water splitting, J. Nanoparticle Res. 23 (1) (2021) 10, https://doi.org/10.1007/s11051-020- 05122-z. \n[10] M. Olak-Kucharczyk, G. Szczepan´ska, M.H. Kudzin, M. Pisarek, The photocatalytical properties of $\\mathsf{R G O/T i O}_{2}$ coated fabrics, Coatings 10 (11) (2020) 1–15, https://doi.org/10.3390/coatings10111041. \n[11] C.M. Magdalane, G.M.A. Priyadharsini, K. Kaviyarasu, A.I. Jothi, G. Gnanamani Simiyon, Synthesis and characterization of $\\mathrm{TiO}_{2}$ doped cobalt ferrite nanoparticles via microwave method: investigation of photocatalytic performance of Congo red degradation dye, Surf. Interfaces 25 (2021) 101296, https://doi.org/10.1016/j. surfin.2021.101296. \n[12] H. Zabihi-Mobarakeh, A. Nezamzadeh-Ejhieh, Application of supported $\\mathrm{TiO}_{2}$ onto Iranian clinoptilolite nanoparticles in the photodegradation of mixture of aniline and 2, 4-dinitroaniline aqueous solution, J. Ind. Eng. Chem. 26 (2015) 315–321, https://doi.org/10.1016/j.jiec.2014.12.003Ind.Eng.Chem. \n[13] N. Pourshirband, A. Nezamzadeh-Ejhieh, An efficient Z-scheme CdS/ $\\mathrm{'g-C_{3}N_{4}}$ nano catalyst in methyl orange photodegradation: focus on the scavenging agent and mechanism, J. Mol. Liq. 335 (2021) 116543, https://doi.org/10.1016/j. molliq.2021.116543. \n[14] N. Omrani, A. Nezamzadeh-Ejhieh, Focus on scavengers’ effects and GC-MASS analysis of photodegradation intermediates of sulfasalazine by $\\mathrm{Cu_{2}O/C d S}$ nanocomposite, Separ. Purif. Technol. 235 (2020) 116228, https://doi.org/ 10.1016/j.seppur.2019.116228. \n[15] P. Kubelka, F. Munk, Ein beitrag zur optik der farbanstriche, Z. Techn. Phys. 12 (1931) 593–601. \n[16] F. Soori, A. Nezamzadeh-Ejhieh, Synergistic effects of copper oxide-zeolite nanoparticles composite on photocatalytic degradation of 2,6-dimethylphenol aqueous solution, J. Mol. Liq. 255 (2018) 250–256, https://doi.org/10.1016/j. molliq.2018.01.169. \n[17] S. Landi Jr., Comment on “Photocatalytic degradation of RhB from an aqueous solution using $\\mathrm{Ag_{3}P O_{4}/N\\mathrm{-TiO_{2}}}$ heterostructure” and “Evaluation of the effect of dose change of $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ nanoparticles on electrochemical biosensor compatibility using hydrogels as an experimental living organism model, J. Mol. Liq. 338 (2021) 116635, https://doi.org/10.1016/j.molliq.2021.116635. \n[18] S. Landi Jr., Comment on “kubelka-munk function”, Ceram. Int. 47 (2021) 8218–8227, https://doi.org/10.1016/j.ceramint.2021.06.103, and “Kubelka-Munk equation” – Ceram. Int. 47 (2021) 13980–13993, Ceram. Int. 47 (2021) 28055. \n[19] S. Landi Jr., Comment on “molten salt synthesis of $\\mathbf{Bi}_{2}\\mathbf{WO}_{6}$ powders and its visiblelight photocatalytic activity” in materials research, 2019; 22(5): e20190311, Mater. Res. 24 (5) (2021), e20210193, https://doi.org/10.1590/1980-5373-MR2021-0193. \n[20] K. Kucio, V. Sydorchuk, S. Khalameida, B. Charmas, The effect of mechanochemical, microwave and hydrothermal modification of precipitated $\\mathrm{TiO}_{2}$ on its physical-chemical and photocatalytic properties, J. Alloys Compd. 862 (2021) 158011, https://doi.org/10.1016/j.jallcom.2020.158011. \n[21] A. Meng, W. Tian, H. Yang, X. Wang, X. Wang, Z. Li, Molybdenum sulfide-modified metal-free graphitic carbon nitride/black phosphorus photocatalyst synthesized via high-energy ball-milling for efficient hydrogen evolution and hexavalent chromium reduction, J. Hazard Mater. 413 (2021) 125400, https://doi.org/ 10.1016/j.jhazmat.2021.125400. \n[22] K. Kundu, P. Dutta, P. Acharyya, K. Biswas, Pb-free layered all-inorganic metal halides $\\mathrm{Rb}{\\mathsf{S n}}_{2}\\mathrm{Br}_{5};$ mechanochemical synthesis, band gap tuning, optical and dielectric properties, Mater. Res. Bull. 140 (2021) 111339, https://doi.org/ 10.1016/j.materresbull.2021.111339. \n[23] N.O. Azarapin, V.V. Atuchin, N.G. Maximov, A.S. Aleksandrovsky, M.S. Molokeev, A.S. Oreshonkov, N.P. Shestakov, A.S. Krylov, T.M. Burkhanova, S. Mukherjee, O. V. Andreev, Synthesis, structure, melting and optical properties of three complex orthorhombic sulfides BaDyCuS3, BaHoCuS3 and BaYbCuS3, Matter. Res. Bull. 140 (2021) 111314, https://doi.org/10.1016/j.materresbull.2021.111314. \n[24] M. Milosevic, S.L. Berets, A review of FT-IR of diffuse reflection sampling considerations, Appl. Spectrosc. Rev. 37 (4) (2002) 347–364, https://doi.org/ 10.1081/ASR-120016081. \n[25] A.B. Murphy, Band-gap determination from diffuse reflectance measurements of semiconductor films, and application to photoelectrochemical water-splitting, Sol. Energy Mater. Sol. Cells 91 (14) (2007) 1326–1337, https://doi.org/10.1016/j. solmat.2007.05.005. \n[26] A. Escobedo-Morales, I.I. Ruiz-Lo´pez, M. de L. Ruiz-Peralta, L. Tepech-Carrillo, M. S´anchez-Cantú, J.E. Moreno-Orea, Automated method for the determination of the band gap energy of pure and mixed powder samples using diffuse reflectance spectroscopy, Heliyon 5 (2019), e01505, https://doi.org/10.1016/j.heliyon.2019. e01505. \n[27] A. Shawky, R.M. Mohamed, I.A. Mkhalid, M.A. Youssef, N.S. Awwad, Visible lightresponsive $_{\\mathrm{Ag/LaTiO_{3}}}$ nanowire photocatalysts for efficient elimination of atrazine herbicide in water, J. Mol. Liq. 299 (2020) 112163, https://doi.org/10.1016/j. molliq.2019.112163. \n[28] M. Momeni, H. Saghafian, F. Golestani-Fard, N. Barati, A. Khanahmadi, Effect of $\\mathrm{SiO}_{2}$ addition on photocatalytic activity, water contact angle and mechanical stability of visible light activated $\\mathrm{TiO}_{2}$ thin films applied on stainless steel by a sol gel method, Appl. Surf. Sci. 392 (2017) 80–87, https://doi.org/10.1016/j. apsusc.2016.08.165. \n[29] D. Akcan, Effect of type and concentration of cobalt precursor on structural, optical and defect properties of ZnCoO nanoparticles, Mater. Res. Bull. 139 (2021) 111254, https://doi.org/10.1016/j.materresbull.2021.111254. \n[30] J. Wawrzyniak, J. Karczewski, P. Kupracz, K. Grochowska, K. Załęski, O. Pshyk, et al., Laser-assisted modification of titanium dioxide nanotubes in a tilted mode as surface modification and patterning strategy, Appl. Surf. Sci. 508 (2020) 145143, https://doi.org/10.1016/j.apsusc.2019.145143. \n[31] M.L. Myrick, M.N. Simcock, M. Baranowski, H. Brooke, S.L. Morgan, J. N. McCutcheon, The kubelka-munk diffuse reflectance formula revisited, Appl. Spectrosc. Rev. 46 (2) (2011) 140–165, https://doi.org/10.1080/ 05704928.2010.537004. \n[32] L. Yang, B. Kruse, Revised Kubelka-Munk theory. I. Theory and application, J. Opt. Soc. Am. 21 (2004) 1933–1941, https://doi.org/10.1364/josaa.21.001933. \n[33] H.G. Booker, W.E. Gordon, A theory of radio scattering in the troposphere, Proceedings of the IRE 38 (4) (1950) 401–412, https://doi.org/10.1109/ JRPROC.1950.231435. \n[34] P.K. Basu, Theory of Optical Processes in Semiconductors, Clarendon Press, Oxford, 1997. \n[35] C. Malerba, F. Biccari, C.L.A. Ricardo, M. D’Incau, P. Scardi, A. Mittiga, Absorption coefficient of bulk and thin film $\\mathtt{C u_{2}O}$ , Sol. Energy Mater. Sol. Cells 95 (10) (2011) 2848–2854, https://doi.org/10.1016/j.solmat.2011.05.047. \n[36] L. Yang, B. Kruse, S.J. Miklavcic, Revised Kubelka-Munk theory. II. Unified framework for homogeneous and inhomogeneous optical media, J. Opt. Soc. Am. A 21 (2004) 1942–1952, https://doi.org/10.1364/JOSAA.21.001942. \n[37] K. Talukdar, B. Jun, Y. Yoon, Y. Kim, A. Fayyaz, C.M. Park, Novel Z-scheme $\\mathrm{Ag_{3}P O_{4}/F e_{3}O_{4}}$ -activated biochar photocatalyst with enhanced visible-light catalytic performance toward degradation of bisphenol A, J. Hazard Mater. 398 (2020) 123025, https://doi.org/10.1016/j.jhazmat.2020.123025. \n[38] I. Martínez-Ruvalcaba, J.F. Hern´andez-Paz, J.R. Farías Mancilla, P. Piza Ruiz, C. A. Martínez P´erez, P.E. García-Casillas, C.A. Rodríguez-Gonz´alez, Optical properties of bio-inspired silver sulfide structures, J. Alloys Compd. 586 (2014) S526–S530, https://doi.org/10.1016/j.jallcom.2012.10.053. \n[39] D.M. Tobaldi, R.C. Pullar, A.F. Gualtieri, G. Otero-Irurueta, M.K. Singh, M. P. Seabra, J.A. Labrincha, Nitrogen-modified nano-titania: true phase composition, microstructure and visible-light induced photocatalytic $\\mathsf{N O}_{\\mathbf{x}}$ abatement, J. Solid State Chem. 231 (2015) 87–100, https://doi.org/10.1016/j.jssc.2015.08.008. \n[40] F. El Bachraouia, Y. Tamraouia, S. Louihib, J. Alamia, R. Shahbazian-Yassar, Y. Yuan, K. Amine, B. Manoun, Unusual superparamagnetic behavior in bulk Ba0.198La0.784Ti0.096Fe0.8O3-δ, Mater. Res. Bull. 137 (2021) 111187, https://doi. org/10.1016/j.materresbull.2020.111187. \n[41] J.F. Wager, Real- and reciprocal-space attributes of band tail states, AIP Adv. 7 (2017) 125321, https://doi.org/10.1063/1.5008521. \n[42] J. Tauc, R. Grigorovici, A. Vancu, Optical properties and electronic structure of amorphous germanium, Phys. Status Solidi 15 (1966) 627–637, https://doi.org/ 10.1002/pssb.19660150224. \n[43] Z. Sun, V.F. Pichugin, K.E. Evdokimov, M.E. Konishchev, M.S. Syrtanov, V. N. Kudiiarov, K. Li, S.I. Tverdokhlebov, Effect of nitrogen-doping and post annealing on wettability and band gap energy of $\\mathrm{TiO}_{2}$ thin film, Appl. Surf. Sci. 500 (2020) 144048, https://doi.org/10.1016/j.apsusc.2019.144048. \n[44] P. Kut´alek, L. Tichý, On the thickness dependence of both the optical band gap and reversible photodarkening in amorphous Ge-Se films, Thin Solid Films 619 (2016) 336–341, https://doi.org/10.1016/j.tsf.2016.10.037. \n[45] M.J.H. Rodríguez, E.P. Meli´an, O.G. Díaz, J. Aran˜a, M. Macías, A.G. Orive, J.M. D. Rodríguez, Comparison of supported $\\mathrm{TiO}_{2}$ catalysts in the photocatalytic degradation of $\\mathrm{NO}_{\\mathrm{x}},$ J. Mol. Catal. Chem. 413 (2016) 56–66, https://doi.org/ 10.1016/j.molcata.2015.12.007. \n[46] S. Landi, J. Carneiro, O.S.G.P. Soares, M.F.R. Pereira, A.C. Gomes, A. Ribeiro, et al., Photocatalytic performance of N-doped TiO2nano-SiO2-HY nanocomposites immobilized over cotton fabrics, J. Mater. Res. Technol. 8 (2019) 1933–1943, https://doi.org/10.1016/j.jmrt.2018.06.025. \n[47] K. Polat, Cuprous oxide film sputtered on monolayer graphene for visible light sensitive heterogeneous photocatalysis, Thin Solid Films 709 (2020) 138254, https://doi.org/10.1016/j.tsf.2020.138254. \n[48] M. Noda, K. Iida, M. Yamaguchi, T. Yatsui, K. Nobusada, Direct wave-vector excitation in an indirect-band-gap semiconductor of silicon with an optical nearfield, Phys. Rev. Appl. 11 (2019) 44053, https://doi.org/10.1103/ PhysRevApplied.11.044053. " + }, + { + "id": "10.1126_science.abq7652", + "DOI": "10.1126/science.abq7652", + "DOI Link": "http://dx.doi.org/10.1126/science.abq7652", + "Relative Dir Path": "mds/10.1126_science.abq7652", + "Article Title": "Deterministic fabrication of 3D/2D perovskite bilayer stacks for durable and efficient solar cells", + "Authors": "Sidhik, S; Wang, YF; De Siena, M; Asadpour, R; Torma, AJ; Terlier, T; Ho, K; Li, WB; Puthirath, AB; Shuai, XT; Agrawal, A; Traore, B; Jones, M; Giridharagopal, R; Ajayan, PM; Strzalka, J; Ginger, DS; Katan, C; Alam, MA; Even, J; Kanatzidis, MG; Mohite, AD", + "Source Title": "SCIENCE", + "Abstract": "Realizing solution-processed heterostructures is a long-enduring challenge in halide perovskites because of solvent incompatibilities that disrupt the underlying layer. By leveraging the solvent dielectric constant and Gutmann donor number, we could grow phase-pure two-dimensional (2D) halide perovskite stacks of the desired composition, thickness, and bandgap onto 3D perovskites without dissolving the underlying substrate. Characterization reveals a 3D-2D transition region of 20 nullometers mainly determined by the roughness of the bottom 3D layer. Thickness dependence of the 2D perovskite layer reveals the anticipated trends for n-i-p and p-i-n architectures, which is consistent with band alignment and carrier transport limits for 2D perovskites. We measured a photovoltaic efficiency of 24.5%, with exceptional stability of T-99 (time required to preserve 99% of initial photovoltaic efficiency) of >2000 hours, implying that the 3D/2D bilayer inherits the intrinsic durability of 2D perovskite without compromising efficiency.", + "Times Cited, WoS Core": 319, + "Times Cited, All Databases": 332, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000887934300037", + "Markdown": "# SOLAR CELLS \n\n# Deterministic fabrication of 3D/2D perovskite bilayer stacks for durable and efficient solar cells \n\nSiraj Sidhik1,2, Yafei Wang2,3, Michael De Siena4, Reza Asadpour5, Andrew J. Torma6, Tanguy Terlier7, Kevin ${\\mathsf{H o}}^{8}$ , Wenbin $\\mathbf{L}\\mathbf{\\bar{i}}^{2,6}$ , Anand B. Puthirath1, Xinting Shuai1, Ayush Agrawal2, Boubacar Traore9, Matthew Jones1,10, Rajiv Giridharagopal8, Pulickel M. Ajayan1, Joseph Strzalka11, David S. Ginger8, Claudine Katan9, Muhammad Ashraful Alam5, Jacky Even12\\*, Mercouri G. Kanatzidis4, Aditya D. Mohite1,2\\* \n\nRealizing solution-processed heterostructures is a long-enduring challenge in halide perovskites because of solvent incompatibilities that disrupt the underlying layer. By leveraging the solvent dielectric constant and Gutmann donor number, we could grow phase-pure two-dimensional (2D) halide perovskite stacks of the desired composition, thickness, and bandgap onto 3D perovskites without dissolving the underlying substrate. Characterization reveals a 3D–2D transition region of 20 nanometers mainly determined by the roughness of the bottom 3D layer. Thickness dependence of the 2D perovskite layer reveals the anticipated trends for n-i- $\\cdot\\mathsf{p}$ and p-i-n architectures, which is consistent with band alignment and carrier transport limits for 2D perovskites. We measured a photovoltaic efficiency of $24.5\\%$ , with exceptional stability of $\\scriptstyle{\\overline{{I_{99}}}}$ (time required to preserve $99\\%$ of initial photovoltaic efficiency) of $>2000$ hours, implying that the 3D/2D bilayer inherits the intrinsic durability of 2D perovskite without compromising efficiency. \n\nhe progressive increase in the power conversion efficiency (PCE) of solutionprocessed perovskite solar cells (PSCs) $(\\boldsymbol{I},\\boldsymbol{2})$ has been enabled in part by strategies to passivate the grain boundaries \nand interfaces between the perovskite absorber \nand the charge transport layers (3–9). Two \ndimensional (2D) halide perovskite (HaP) \npassivation layers, which have been the most \neffective in improving the open-circuit volt \nage $(V_{\\mathrm{OC}})$ and fill factor (FF) (10–13), are com \nmonly grown by spin-coating an organic cation \ndispersed in isopropyl alcohol or chloroform on \ntop of 3D HaPs (14, 15). This coating removes \nsome excess lead iodide $\\mathrm{(PbI_{2})}$ ) from the 3D \nperovskite layer to then form heterogeneous \n\n2D phases or ultrathin layers of wide-bandgap \n2D HaP (16–18). \n\nThese advances have enhanced durability, as demonstrated recently by Azmi et al., using damp-heat tests (19); however, the lack of control over the phase purity, film thickness, orientation, and structural phase of the 2D HaP has limited their use as an interfacial passivation layer (20). A solvent-free growth of the 2D $\\mathrm{BA_{2}P b I_{4}}$ perovskite on the 3D film by controlling the pressure, temperature, and time was demonstrated by Jang et al., indicating the importance of a high-quality 3D/2D interface (21). However, such solid-state in-plane growth is difficult to scale to large areas. Thus, the fabrication of solution-processed heterostructures of 3D/2D HaP with the desired energy levels, thickness, and orientation has been lacking. \n\nWe report a solvent design principle for fabricating solution-processed 3D/2D HaP bilayer structures with the desired film thickness and phase purity of any 2D HaP—including Ruddlesden-Popper (RP), Dion-Jacobson (DJ), or alternating cation interlayer (ACI)—described by the general formula of $\\mathrm{L}^{\\prime}\\mathrm{A}_{n-1}\\mathrm{B}_{n}\\mathrm{X}_{3n+1}$ (DJ) where L′ is a long-chain organic cation, A is a small monovalent cation, B is a divalent metal, X is a monovalent anion, and $n$ is the number of $\\mathrm{PbI}_{6}$ bonded octahedra along the stacking axis. Our approach leverages two essential properties of the processing solvents, the dielectric constant $(\\varepsilon_{\\mathrm{r}})$ and the Gutmann donor number $(D_{\\mathrm{N}})$ , which controls the coordination between the precursor ions and the solvent (22). Processing solvents with dielectric constant $\\varepsilon_{\\mathrm{r}}>30$ and Gutmann number, $52000$ hours. Thus, these structures had the durability of the 2D perovskite films without compromising PCE (23). \n\nThe comprehensive selection criteria for solvents that could selectively dissolve either the 2D or 3D HaP without disrupting the underlying 3D or 2D layer, respectively, were based on the dielectric constant and the Gutmann donor number (Fig. 1A). These two distinct attributes are correlated. The dielectric constant determines the power of a solvent to dissolve any ionic compound by screening the Coulomb attraction between the ions, whereas the Gutmann donor number describes the Lewis basicity of the solvent and measures the extent to which coordination compounds may form between solvent and cations (high donor number) or between the precursors themselves (low donor number) in the absence of competitive binding of the solvent (24, 25). For example, in the precursor solution composed of methylammonium iodide (MAI), formamidinium iodide (FAI), and $\\mathrm{PbI_{2}},$ , a solvent with a high Gutmann number would strongly coordinate with divalent metal centers $(\\mathrm{Pb^{2+}})$ and suppress the formation of molecular clusters {for example, iodoplumbates such as $\\mathrm{[PbI_{6-x}}$ $(\\mathrm{solvent})_{x}]^{-(4-x)}$ , where $\\begin{array}{r}{x\\leq6\\}}\\end{array}$ that would otherwise form in a solvent with low Gutmann number. The strength of these interactions determined the differences in the solubility of the 3D and 2D HaP powders in various solvents (Fig. 1A). \n\nTypical vials of RP 2D $\\mathrm{(BA_{2}M A P b_{2}I_{7})}$ and the 3D HaP powders (Fig. 1B) illustrate their solubility in different solvents. Polar aprotic solvents (Fig. 1A, green dots) with a dielectric constant $>$ 30, such as $N,$ N-dimethylformamide (DMF) and dimethyl sulfoxide (DMSO), fully dissolved both 3D and 2D HaP. Solvents such as acetonitrile (MeCN), tetramethyl sulfone (TMS), propylene carbonate (PC), and ethylene carbonate (EC) also have a dielectric constant $>30$ but did not dissolve the 3D HaP powders because their weak Lewis basicity $(D_{\\mathrm{N}}<18\\mathrm{kcal/mol})$ ) made the formation of $\\mathrm{Pb^{2+}}$ solvent coordination complexes unlikely. However, these solvents completely dissolved the 2D perovskite powders. This difference is consistent with 3D perovskite lattices being more stable and difficult to disrupt with solvents of intermediate $D_{\\mathrm{N}}$ than the 2D perovskites and implied the presence of additional favorable interactions of these solvents with the organic spacer cations (readily accessible from the edges of the slabs) that were absent in the 3D perovskites. \n\nWe observed that both nonpolar (Fig. 1A, blue dots) and polar protic solvents (Fig. 1A, red dots) did not completely dissolve the 2D HaP powders (Fig. 1B). As controls, we also tested solvents with a high Gutmann number and low dielectric constant, such as tetrahydrofuran $(D_{\\mathrm{N}}=20\\ensuremath{~\\mathrm{kcal/mol}}$ , $\\varepsilon_{\\mathrm{r}}=7.6\\$ ), and vice versa, such as nitromethane (NME) $(D_{\\mathrm{N}}=$ $\\ensuremath{2.7}\\ensuremath{\\mathrm{kcal/mol}}$ , $\\varepsilon_{\\mathrm{r}}=35.9\\$ ), both of which did not dissolve the 2D perovskite powders (figs. S1 and S2). Taken together, these results implied that solvents with a dielectric constant $>30$ and the Gutmann number $5}100\\mathrm{mg/ml}$ for $n=1$ to 30 to $40\\mathrm{mg/ml}$ for $n=$ 4. The decrease in the solubility as a function of increasing $n$ value was consistent with the increase in inorganic lattice fraction of the 2D HaP as the $n$ value approached 3D composition. \n\nIn addition, the $n=2$ ACI and DJ perovskites exhibited low solubilities of 20 to $40\\mathrm{mg/ml}$ and 10 to $25~\\mathrm{mg/ml}$ , respectively, which was consistent with the structure of ACI and DJ 2D perovskites, which was near that of 3D with short interlayer cations that reflected the role of organic spacer cations in the dissolution process. Of all the target solvents, the high volatility of MeCN [boiling point $(\\mathrm{b.p.})\\approx82^{\\circ}\\mathrm{C}]$ compared with those of the others—such as TMS (b.p. $\\approx285^{\\circ}\\mathrm{C})$ , PC (b.p. $\\approx242^{\\circ}\\mathrm{C})$ , and EC (b.p. $\\approx248^{\\circ}\\mathrm{C}$ —made it attractive for lowtemperature processing without affecting the stability of the entire stack (figs. S3 and S4 and movies S1 and S2). We focused on the solvent MeCN for fabricating the targeted 3D/2D HaP bilayer. \n\nThe protocols for fabricating the 3D/2D HaP bilayer by use of spin coating, drop-casting, blade coating, or slot-die coating (Fig. 1D) followed our recent work on obtaining PP-2D HaP films. We created a stable dispersion of 2D perovskite seed solution by dissolving the parent crystal powders in MeCN (fig. S5 and supplementary text) (26, 27). In general, other than the solvents with Gutmann number $52000$ hours, whereas the control 3D device lost $25\\%$ of its initial PCE. As controls, we also measured the stability of the 3D PSC passivated with a spin-coated organic cation, butylammonium iodide, and compared it with our 3D/PP-2D PSCs using the same conditions. The 2D HaP passivated 3D PSCs show a $10\\%$ loss of efficiency after 1000 hours of continuous operation, which is consistent with other recent reports $(4,79)$ . We also measured a pure 2D HaP control device, which showed a $T_{97}>1500$ hours, implying that the 3D/PP-2D bilayer perovskite has acquired the inherent stability of the 2D perovskite material. \n\n# REFERENCES AND NOTES \n\n![](images/d754a7485e34a7b0043a1689043630af7e7e36fda5c181584e1bfce0e6fc7bc7.jpg) \nFig. 4. Photovoltaic performance and long-term stability of the 3D/PP-2D (BA2MA2Pb3I10) HaP bilayer solar cells. (A) Energy-level alignment for different n values $(n\\leq4)$ of 2D perovskite with the 3D perovskite layer with an error of $\\pm0.05\\mathrm{eV}$ . (B) Current-voltage $(1-V)$ curves of the champion 3D/PP-2D n-i-p PSCs as a function of the 2D layer thickness obtained by spin coating different concentration of the 2D perovskite solution in MeCN. (C) Variation in PCE of the $n-i-p$ and p-i-n planar 3D/PP-2D PSCs as a function of 2D perovskite layer thickness. (D) External quantum efficiency of the device with and without the 2D layer, showing the absorption and current generation ability of the stack. (E) ISOS-L-1 stability measured at maximum power point tracking in ambient condition under continuous 1-sun illumination $(55^{\\circ}\\mathrm{C})$ for an epoxy encapsulated PSC. The initial PCE of the control device is $21\\%$ ; that of the 3D/2D passivated device is $22.93\\%$ ; that of the 3D/PP-2D bilayer PSC is $23.75\\%$ ; and that of the PP-2D perovskite device is $16.3\\%$ . \n\ncorroborate these results, we measured the surface photovoltage (SPV) using scanning Kelvin probe microscopy (SKPM) on the ITO/ $\\mathrm{SnO_{2}/3D/P P-2D}$ (RP $\\mathrm{BA_{2}M A_{2}P b_{3}I_{10}},$ ) stack, which showed an increase in the SPV as a function of the 2D layer thickness (figs. S30 and S31). This result suggested an increase in the quasi-Fermi level separation related to the $V_{\\mathrm{OC}}$ of the device (35–38). The dark $I{-}V$ curve traces of the solar cells further confirm the increase in $V_{\\mathrm{OC}}$ (supplementary text and fig. S32). Additionally, the steady-state PL and time-resolved photoluminescence (TRPL) measurements on the ITO/ SnO2/3D/PP-2D (RP $\\mathrm{BA_{2}M A_{2}P b_{3}I_{10}},$ ) stack showed enhanced PL emission and increased charge carrier lifetime up to a 2D HaP thickness of \n\n1. J. Jeong et al., Nature 592, 381–385 (2021). \n2. H. Min et al., Nature 598, 444–450 (2021). \n3. Q. Jiang et al., Nat. Photonics 13, 460–466(2019). \n4. F. Zhang et al., Science 375, 71–76 (2022). \n5. X. Zheng et al., Nat. Energy 5, 131–140 (2020). \n6. Y. Liu et al., Sci. Adv. 5, eaaw2543 (2019). \n7. N. K. Noel et al., ACS Nano 8, 9815–9821 (2014). \n8. D. W. deQuilettes et al., ACS Energy Lett. 1, 438–444 (2016). \n9. I. L. Braly et al., Nat. Photonics 12, 355–361 (2018). \n10. A. A. Sutanto et al., Chem 7, 1903–1916 (2021). \n11. G. Wu et al., Adv. Mater. 34, e2105635 (2022). \n12. G. Li et al., ACS Energy Lett. 6, 3614–3623 (2021). \n13. M. A. Mahmud et al., Adv. Funct. Mater. 32, 2009164 (2022). \n14. E. Jokar et al., ACS Energy Lett. 6, 485–492 (2021). \n15. J. J. Yoo et al., Energy Environ. Sci. 12, 2192–2199 (2019). \n16. T. Zhang et al., Joule 2, 2706–2721 (2018). \n17. P. Li et al., Adv. Mater. 30, e1805323 (2018). \n18. F. Wang et al., Joule 2, 2732–2743 (2018). \n19. R. Azmi et al., Science 376, 73–77 (2022). \n20. M. Xiong et al., ACS Energy Lett. 7, 550–559 (2022). \n21. Y.-W. Jang et al., Nat. Energy 6, 63–71 (2021). \n22. V. Gutmann, Coord. Chem. Rev. 18, 225–255 (1976). \n23. M. V. Khenkin et al., Nat. Energy 5, 35–49 (2020). \n24. J. C. Hamill Jr., J. Schwartz, Y.-L. Loo, ACS Energy Lett. 3, 92–97 (2017). \n25. J. C. Hamill Jr. et al., J. Phys. Chem. C 124, 14496–14502 (2020). \n26. S. Sidhik et al., Adv. Mater. 33, e2007176 (2021). \n27. S. Sidhik et al., Cell Rep. Phys. Sci. 2, 100601 (2021). \n28. M. Tolan, M. Tolan, X-Ray Scattering From Soft-Matter Thin Films: Materials Science and Basic Research (Springer, 1999), vol. 148. \n29. R. M. Kennard et al., Chem. Mater. 33, 7290–7300 (2021). \n30. I. Spanopoulos et al., J. Am. Chem. Soc. 141, 5518–5534 (2019). \n31. M. Seitz et al., Nat. Commun. 11, 2035 (2020). \n32. E. D. Kinigstein et al., Mater. Lett. 2, 1360–1367 (2020). \n33. M. Degani et al., Sci. Adv. 7, eabj7930 (2021). \n34. X. Wang et al., Nat. Commun. 12, 52 (2021). \n35. S. Kavadiya et al., in 2020 47th IEEE Photovoltaic Specialists Conference (PVSC) (IEEE, 2020), pp. 1439–1440. \n36. I. Levine et al., Joule 5, 2915–2933 (2021). \n\n37. L. Kronik, Y. Shapira, Surf. Sci. Rep. 37, 1–206 (1999). \n38. R. Giridharagopal et al., ACS Nano 13, 2812–2821 (2019). \n39. J. Wang et al., ACS Energy Lett. 4, 222–227 (2018). \n\n# ACKNOWLEDGMENTS \n\nWe thank M. H. K. Samani and A. B. Marciel for useful discussions on the DLS measurements. Funding: The work at Rice University was supported by the DOE-EERE 0008843 program. J.E. acknowledges the financial support from the Institut Universitaire de France and GENCI national computational resources. The work at ISCR and Institut FOTON was performed with funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 861985 (Pero CUBE). At Northwestern, the work was supported by the Office of Naval Research (ONR) under grant N00014-20-1-2725. This research used facilities of the Advanced Photon Source, a US Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under contract DE‐AC02‐06CH11357. ToF-SIMS analysis were carried out with support provided by the National Science Foundation CBET1626418. This work was conducted in part using resources of \n\nthe Shared Equipment Authority at Rice University. The work at the University of Washington by K.H., R.G., and D.S.G. is supported by DOE BES under award DE-SC0013957. This research used facilities and instrumentation supported by the US National Science Foundation through the UW Molecular Engineering Materials Center (MEM-C), a Materials Research Science and Engineering Center (DMR-1719797). Author contributions: A.D.M., S.S., and J.E. conceived the idea, designed the experiments, analyzed the data, and cowrote the manuscript. S.S. and Y.W. studied different solvents. Y.W. performed 2D/3D passivation experiments with S.S.; W.L. and J.S. performed GIWAXS measurements, A.J.T. performed PL maps, X.S. performed SEM and AFM imaging, and A.A. helped with solar cell fabrication and characterization. M.D. performed photoluminescence measurements, M.G.K. and M.J. analyzed the solvation chemistry along with synthesis of $20H a P$ crystals. C.K. and B.T. helped understand the 3D/2D interface with DFT modeling. A.B.P. and P.M.A. performed focused ion beam milling (FIB) and electron microscopy (TEM and STEM). K.H., R.G., and D.S.G. performed SKPM and TRPL measurements, R.A. and M.A.A. performed device modeling and optical simulations. T.T. helped perform TOF-SIMS and analyze data. All authors contributed to the manuscript. Competing interests: Rice University have filed patent for method of fabricating the 3D/PP-2D bilayer stack. Data and materials availability: All data are available in the main text or the supplementary materials. License information: Copyright $\\textcircled{\\odot}2022$ the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.science.org/about/sciencelicenses-journal-article-reuse \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abq7652 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S33 \nTables S1 to S8 \nReferences (40–70) \nMovies S1 and S2 \n\nSubmitted 2 May 2022; accepted 18 August 2022 \n10.1126/science.abq7652 " + }, + { + "id": "10.1038_s41467-022-29428-9", + "DOI": "10.1038/s41467-022-29428-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-29428-9", + "Relative Dir Path": "mds/10.1038_s41467-022-29428-9", + "Article Title": "Electrochemical CO2 reduction to ethylene by ultrathin CuO nulloplate arrays", + "Authors": "Liu, W; Zhai, PB; Li, AW; Wei, B; Si, KP; Wei, Y; Wang, XG; Zhu, GD; Chen, Q; Gu, XK; Zhang, RF; Zhou, W; Gong, YJ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electrochemical reduction of CO2 to multi-carbon fuels and chemical feedstocks is an appealing approach to mitigate excessive CO2 emissions. However, the reported catalysts always show either a low Faradaic efficiency of the C2+ product or poor long-term stability. Herein, we report a facile and scalable anodic corrosion method to synthesize oxygen-rich ultrathin CuO nulloplate arrays, which form Cu/Cu2O heterogeneous interfaces through self-evolution during electrocatalysis. The catalyst exhibits a high C2H4 Faradaic efficiency of 84.5%, stable electrolysis for similar to 55 h in a flow cell using a neutral KCI electrolyte, and a full-cell ethylene energy efficiency of 27.6% at 200 mA cm(-2) in a membrane electrode assembly electrolyzer. Mechanism analyses reveal that the stable nullostructures, stable Cu/Cu2O interfaces, and enhanced adsorption of the *OCCOH intermediate preserve selective and prolonged C2H4 production. The robust and scalable produced catalyst coupled with mild electrolytic conditions facilitates the practical application of electrochemical CO2 reduction.", + "Times Cited, WoS Core": 333, + "Times Cited, All Databases": 349, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000779311200034", + "Markdown": "# Electrochemical ${\\mathsf{C O}}_{2}$ reduction to ethylene by ultrathin CuO nanoplate arrays \n\nWei Liu1, Pengbo Zhai2, Aowen $\\mathsf{L i}^{3,4}$ , Bo Wei1, Kunpeng Si1, Yi Wei5,6, Xingguo Wang1, Guangda Zhu7, Qian Chen1, Xiaokang $\\mathsf{G u}^{1},$ Ruifeng Zhang1, Wu Zhou $\\textcircled{1}$ 3,4,8 & Yongji Gong 1,9✉ \n\nElectrochemical reduction of ${\\mathsf{C O}}_{2}$ to multi-carbon fuels and chemical feedstocks is an appealing approach to mitigate excessive ${\\mathsf{C O}}_{2}$ emissions. However, the reported catalysts always show either a low Faradaic efficiency of the $\\mathsf C_{2+}$ product or poor long-term stability. Herein, we report a facile and scalable anodic corrosion method to synthesize oxygen-rich ultrathin $\\mathtt{C u O}$ nanoplate arrays, which form $\\mathsf{C u/C u_{2}O}$ heterogeneous interfaces through selfevolution during electrocatalysis. The catalyst exhibits a high $C_{2}H_{4}$ Faradaic efficiency of $84.5\\%$ , stable electrolysis for ${\\sim}55\\ h$ in a flow cell using a neutral KCl electrolyte, and a full-cell ethylene energy efficiency of $27.6\\%$ at $200\\mathsf{m A c m}^{-2}$ in a membrane electrode assembly electrolyzer. Mechanism analyses reveal that the stable nanostructures, stable $\\mathsf{C u/C u_{2}O}$ interfaces, and enhanced adsorption of the $^{\\star}\\mathsf{O C C O H}$ intermediate preserve selective and prolonged $C_{2}H_{4}$ production. The robust and scalable produced catalyst coupled with mild electrolytic conditions facilitates the practical application of electrochemical ${\\mathsf{C O}}_{2}$ reduction. \n\nTcahobel tdienpueleretgtiyonemcofp favosesirsztiel fhruebeolisnmdapinordx tnhec continue to emphasize the importance of utilizing renew- tnil-nirzteionfeguwerlaesbniaelinwtdy$\\left(\\mathrm{CO}_{2}\\right)$ chemical feedstocks $^{1-3}$ . Artificial conversion of $\\mathrm{CO}_{2}$ is essential to reduce its emissions and realize the sustainable development of humanity3,4. The electrochemical $\\mathrm{CO}_{2}$ reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ is the most attractive method due to its mild reaction conditions and capacity for renewable electricity storage5. Among the products of the ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ low-value $\\mathrm{C_{1}}$ species such as carbon monoxide (CO) and formate $(\\mathrm{HCOO^{-}})$ are the most common products due to the sluggish kinetics of the $C{\\mathrm{-}}C$ coupling reaction6,7. As shown by previous studies, the $C{\\mathrm{-}}C$ coupling reaction is the vital step for $\\mathrm{C}_{2+}$ species formation $^{8-11}$ . Theoretical calculations reveal that excessively strong or weak binding of $^*\\mathrm{CO}$ intermediates is unfavorable for the generation of $\\mathrm{C}_{2+}$ species9,12–14. Copper-based (Cu-based) materials possessing a moderate adsorption energy of the $^*\\mathrm{CO}$ intermediate have been the most efficient catalysts in converting $\\mathrm{CO}_{2}$ to $\\mathrm{C}_{2+}$ hydrocarbons and oxygenates with considerable activity2,15–18. The $\\mathrm{CO}_{2}\\mathrm{RR}$ to ethylene $\\mathrm{(C_{2}H_{4})}$ with high current density and Faradic efficiency (FE) is intensively studied because of the extremely high industrial value and limited sources of $\\mathrm{C_{2}H_{4}}^{18-21}$ . However, as multi-step electron and proton transfer processes are involved in $\\mathrm{C}_{2}\\mathrm{H}_{4}$ formation, hydrogen $\\left(\\operatorname{H}_{2}\\right)$ and other by-products such as methane $\\mathrm{(CH_{4})}$ will inevitably be produced during electrolysis16,20,22–24. Therefore, the activity and selectivity of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ formation are still limited for Cu-based catalysts. \n\nVarious procedures such as facet and grain boundary regulation25–27, morphology engineering18,28–32, electrode surface additive modification14,33–36, electrolyte design37,38 and oxidederived catalysis16,20,39–42 have been proposed to improve the current density and FE of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ production. Among these catalysts, oxide-derived Cu (OD-Cu) has the highest product ratio of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ to $\\mathrm{CH}_{4}{}^{21,26,40}$ . These catalysts have generally been synthesized by thermal oxidation and subsequently reduced through $\\mathrm{H}_{2}$ annealing or in situ electrolysis. Hemma et al. revealed that the increased local $\\mathrm{\\pH}$ caused by the rough morphology of OD-Cu suppressed $\\mathrm{CH}_{4}$ formation21. The existence of $\\mathrm{Cu^{+}}$ species may promote the adsorption of $\\mathrm{CO}_{2}\\mathrm{RR}$ intermediates, which is crucial to improve the $\\mathrm{C_{2}H_{4}}$ selectivity21. Although the existence and important role of $\\mathrm{Cu^{+}}$ species in the $\\mathrm{CO}_{2}\\mathrm{RR}$ have been proven by many in situ and operando tests (Raman spectroscopy, X-ray absorption spectroscopy, etc.)20,26,43,44, thermal oxidation treatments usually result in a disordered morphology and an inadequate amount of oxidation species40. These issues lead to the disappearance of $\\mathrm{Cu/Cu^{\\delta+}}$ heterointerfaces during long-term electrocatalysis tests due to the selfevolution of surface species and morphologies. Therefore, constructing stable $\\mathrm{Cu/Cu}^{\\hat{\\delta}+}$ heterointerfaces with exquisite nanostructures is highly desirable to improve the stability of $\\mathrm{C_{2}H_{4}}$ production. \n\nHere, we report the preparation of an OD-Cu catalyst with a dense vertical lamellate Cu nanostructure (denoted as DVL-Cu). The DVLCu catalyst was obtained via in situ electrochemical reduction of CuO ultrathin nanoplate arrays (denoted as CuO-NPs) synthesized by galvanostatic anodic oxidation in an alkaline solution. The electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ test of DVL-Cu delivered an $\\mathrm{C_{2}H_{4}}$ FE of $73.6\\%$ and a total $\\mathrm{C}_{2+}$ (mainly ethylene and ethanol) FE of ${>}80\\%$ at $-0.8\\mathrm{V}$ vs. the reversible hydrogen electrode (RHE, all potentials are with respect to this reference in this article) in an H-cell and an even higher $\\mathrm{C_{2}H_{4}}$ FE of $84.5\\%$ in a flow cell, with neutral potassium chloride (KCl) as the catholyte. Moreover, the catalyst achieved an ethylene energy efficiency $\\displaystyle(\\mathrm{EE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}})$ of $28.9\\%$ and ${\\sim}55\\mathrm{h}$ stable long-term electrolysis in a flow cell. The experimental and simulation results reveal that the nanostructured DVL-Cu generated $\\mathrm{{Cu/Cu_{2}O}}$ heterogeneous interfaces and dispersed the electrode current density effectively to avoid agglomeration during the $\\mathrm{CO}_{2}\\mathrm{RR}.$ Meanwhile, the KCl electrolyte impedes the dissolution/redeposition of $\\mathrm{Cu^{+}}$ species due to its high local pH microenvironment and suppresses hydrogen evolution at higher overpotentials, which favors the high selectivity and stability of the DVL-Cu catalyst. Density functional theory (DFT) calculations suggest that the $\\mathrm{Cu}/\\mathrm{Cu}_{2}\\mathrm{O}$ interfaces in DVL-Cu facilitate $\\mathrm{C}_{2}\\mathrm{H}_{4}$ formation due to their reduced C–C dimerization energy in the $\\mathrm{C_{2}H_{4}}$ formation pathway. The facile synthetic method, mild electrolysis conditions (neutral electrolyte), and prolonged electrolysis stability make this material a promising candidate for commercial $\\mathrm{CO}_{2}\\mathrm{RR}$ catalysts in the future. \n\n# Results \n\nPreparation and characterization of the DVL-Cu catalyst. First, CuO-NPs were synthesized by galvanostatic anodic oxidation of Cu foil in a $^{1\\mathrm{M}}$ sodium hydroxide $\\left(\\mathrm{NaOH}\\right)$ electrolyte. Copper hydroxide $\\mathrm{(Cu(OH)}_{2})$ was primarily generated on the Cu surface during anodic oxidation45, while $\\mathrm{Cu(OH)}_{2}$ spontaneously converted to $\\mathtt{C u O}$ at a proper current density. We found that $0.26\\operatorname{mA}{\\mathsf{c m}}^{-2}$ (calculated based on the geometric area) was the most suitable current density for $\\mathrm{CuO-N\\bar{P}s}$ synthesis, resulting in the best catalyst performance. Excessive current with rapid $\\mathrm{Cu(OH)}_{2}$ production led to the complete coverage of blue $\\mathrm{Cu(OH)}_{2}$ on the surface, and an insufficient current generated only a thin oxide layer rather than nanoplate arrays. \n\nA schematic illustration of the CuO-NPs formation process is displayed in Fig. 1a. This process can be divided into three stages: the Cu etching stage, CuO nucleation stage and $\\mathtt{C u O}$ growth stage. The Cu surface was first corroded by a positive bias at the etching stage (Fig. 1b). Once ${\\mathrm{Cu}}^{2+}$ was saturated in the solution, CuO nucleated and grew on the surface as $\\mathrm{Cu(OH)}_{2}$ was generated and dehydrated (Supplementary Fig. 1). The surface oxygen content no longer increased after the nucleation stage, indicating that the surface had been completely covered by the oxide layer (Fig. 1c). Eventually, vertically arranged and densely stacked CuO-NPs were synthesized. The successful synthesis of CuO-NPs on a large piece of $\\mathtt{C u}$ foil $(25\\times25~\\mathrm{cm}^{2}.$ by this method proves the scalability to prepare catalysts for industrial applications (Supplementary Figs. 2–4, the samples used for characterization were obtained from Cu foils with a size of $1.5\\times3\\mathrm{cm}^{2}$ unless otherwise specified). The morphology and atomic structure of an individual CuO nanoplate before and after the $\\mathrm{CO}_{2}\\mathrm{RR}$ can be characterized in detail after sonication. As shown by transmission electron microscopy (TEM) images, the CuO nanoplates are composed of polygonal ultrathin CuO nanosheets (Fig. 1d and Supplementary Fig. 5). The nm-scale thickness of the CuO nanosheets was confirmed by atomic force microscopy (AFM), showing that the thicknesses of the corresponding layers are 3.136 and $0.782{\\mathrm{nm}}$ , respectively (Fig. 1e). The ultrathin thickness of $\\mathtt{C u O}$ nanosheets leads to ultrafine Cu nanostructures with numerous exposed catalytically active sites during electrocatalysis. Specifically, the thickness of the whole CuO-NPs layer on $\\mathtt{C u}$ foil is $2.25\\upmu\\mathrm{m}$ , as measured by the scanning electron microscopy (SEM) cross-sectional image (Supplementary Fig. 6), which also exhibits a uniform and compact stacking pattern. Furthermore, this three-dimensional self-supporting structure is beneficial to mass transfer and the exposure of catalytically active sites. In addition, the CuO-NPs were thermally reduced under $\\mathrm{Ar/H}_{2}$ to obtain reduced-CuO-NPs (denoted as R-CuO-NPs, Supplementary Fig. 7) as a control group to test the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance. \n\nThe DVL-Cu catalyst was produced during the in situ electrochemical $\\mathrm{CO}_{2}\\mathrm{R}\\dot{\\mathrm{R}}$ by self-evolution in a gas-tight H-cell (Fig. 2a). CuO-NPs were used as the working electrode, a $\\mathrm{\\Ag/AgCl}$ electrode was used as the reference electrode (RE), and platinum foil was employed as the counter electrode. In situ galvanostatic reduction was performed at $-0.8\\mathrm{V}$ under a $\\mathrm{CO}_{2}$ atmosphere. The black foil quickly turned rufous after $20s$ of electrolysis (Supplementary Fig. 8), suggesting that the CuO-NPs were reduced to a lower valence. After $20\\mathrm{min}$ of electrolysis, the vertically arranged and densely stacked laminated nanostructure was retained (Fig. 2b, c, and Supplementary Figs. 9, 10). However, every single piece of ultrathin CuO nanoplate was converted to a thicker nanoplate composed of small nanoparticles. These nanoparticles were considered active catalytic sites for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ formation, as suggested by a previous study46. This nanoplate-like morphology suppresses the agglomeration of Cu nanoparticles, which benefits the long-term catalytic stability. The curves depicted in Fig. 2d present the grazing incident X-ray diffraction (GI-XRD) results of the original CuO-NPs and DVL-Cu after different reduction times. The GI-XRD result of CuO-NPs shows the successful synthesis of $\\mathtt{C u O}$ without any other impurities (such as $\\mathrm{Cu(OH)}_{2}$ and $\\mathrm{Cu}_{2}\\mathrm{O}$ ). The peaks ascribed to cuprite-type $\\mathrm{Cu}_{2}\\mathrm{O}$ begin to appear after $20s$ of electrochemical reduction. The CuO peaks completely disappear after 1 min of electrochemical reduction, while the peak of $\\mathrm{Cu}_{2}\\mathrm{O}$ still remains even when the reduction time is extended to $^{2\\mathrm{h}}$ , which is consistent with previous studies on OD-Cu catalysts20,26,45,46. Comparing the line for the $^{2\\mathrm{h}}$ reduction time and that for the $5\\mathrm{min}$ reduction time, the peak intensity of the $\\mathtt{C u}(110)$ facet increases with the duration of electrolysis. As $\\mathrm{Cu}(111)$ is the most thermodynamically stable facet in polycrystalline $\\mathrm{Cu}^{26}$ , the increased ratio of $\\operatorname{Cu}(110)$ might result from the stabilizing effect of $\\mathrm{CO}_{2}\\mathrm{RR}$ intermediates26. \n\n![](images/5361dfb8273a69c8e10998f7fd4844f35355cd9cf23934942b2e5ebde221611f.jpg) \nFig. 1 Preparation and characterization of CuO-NPs. a Schematic illustration of the preparation of ${\\mathsf{C u O-N P s}}$ . b SEM images of Cu foils at different anodic oxidation times. The scale bars are $500\\mathsf{n m}$ . c Oxygen content of the Cu surface at different anodic oxidation times. d TEM image of the CuO-NPs. e AFM image of the CuO-NPs and the corresponding height profile from the dashed line. \n\nSupplementary Figs. 11, 12 and Fig. 2e show $\\mathrm{\\DeltaX}$ -ray photoelectron spectroscopy (XPS) and Auger electron spectroscopy (AES) results of $\\mathrm{CuO-NPs}$ and DVL-Cu (taken after $^\\mathrm{1h}$ of electrolysis) for different $\\mathrm{Ar^{+}}$ beam etching times, noting that the $\\mathrm{Ar^{+}}$ beam could etch the surface of the sample to reveal subsurface information. The typical satellite peak and Cu LMM Auger peak location $(971.3\\mathrm{eV})$ of the CuO-NPs indicate the characteristics of $\\mathrm{Cu}^{2+}$ species20. No satellite peak was found in the DVL-Cu XPS results for different etching times, suggesting that the original $\\mathrm{Cu}^{2+}$ species in the CuO-NPs are completely reduced after electrolysis. Cu Auger LMM spectra demonstrate that ${\\mathrm{Cu}}^{0}$ and $\\mathrm{Cu^{+}}$ species co-exist in DVL-Cu even after $300s$ of $\\mathrm{Ar^{+}}$ beam etching (the etching depth was estimated to be $50\\mathrm{nm}\\mathrm{\\cdot}$ ), which could entirely remove the surface oxide layer formed by air oxidation (usually $<~5\\mathrm{nm},$ ). In situ Raman spectroscopy was further performed to identify the valence of $\\mathrm{Cu}$ during electrolysis (Fig. 2f and Supplementary Fig. 13). At the open-circuit potential (OCP), peaks located at 286, 327 and $618\\mathrm{cm}^{-1}$ were ascribed to CuO. CuO characteristic peaks weakened, and peaks associated with $\\mathrm{Cu}_{2}\\mathrm{O}$ began to appear when DVL-Cu was electrolyzed at $-0.6\\mathrm{V}$ for $60\\:s.$ When the electrolysis was carried out at $-0.6\\mathrm{V}$ for $1800\\ s_{\\mathrm{{z}}}$ the peaks of $\\mathrm{Cu}_{2}\\mathrm{O}$ still existed, but those of CuO completely disappeared. These results were similar for electrolysis at a higher overpotential of $-1.0\\mathrm{V}$ , except that the peak intensity of $\\mathrm{Cu}_{2}\\mathrm{O}$ was lower than that at $-0.6\\mathrm{V}$ . Thus, it was concluded that $\\mathrm{Cu^{+}}$ species were preserved during the electrochemical ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ which might be due to stabilization effects generated by the high local $\\mathrm{\\tt{pH}}$ and $\\mathrm{Cl}^{-16,21}$ . \n\n![](images/e3d9a72ba0edb100c769dad9d8d81291be2d5e2cd501461d9395770126179f34.jpg) \nFig. 2 Preparation and characterization of DVL-Cu. a Schematic illustration of morphology changes during the electrochemical reduction of DVL-Cu and CuO-NPs. b, c High-magnification SEM images of CuO-NPs (b) and DVL-Cu (c). The scale bars are $200\\mathsf{n m}$ . d GI-XRD patterns of ${\\mathsf{C u O-N P s}}$ and DVL-Cu for different reduction times. e Cu LMM Auger spectra of CuO-NPs and DVL-Cu (after 1 h reduction) with respect to different $\\mathsf{A r^{+}}$ etching times. f In situ Raman spectra of DVL-Cu during electrolysis. \n\nAdditionally, aberration-corrected scanning transmission electron microscopy (STEM) combined with electron energy-loss spectrometry (EELS) was performed to reveal the valence states and distribution of Cu species in DVL-Cu (Fig. 3 and Supplementary Fig. 14). The structure of a large particle decorated by several small particles is displayed in the brightfield (BF) image (Fig. 3a). The fast Fourier transform (FFT) patterns of the central large particle $(\\#1)$ and a surrounding small particle (#2) are consistent with the $\\mathrm{Cu}[110]$ and $\\mathrm{Cu}_{2}\\mathrm{O}[11\\bar{0}]$ zone axes, respectively. $\\mathrm{Cu}(1\\bar{1}1)$ and (002) facets were delineated in the enlarged image of area $\\#1$ (Fig. 3b). Energy-loss near-edge fine structure (ELNES) analysis, which is a commonly applied method to determine the valence state of 3d metal elements, was also performed on the DVL-Cu sample to confirm its composition and distribution47. The fine structures of the EELS spectrum extracted from area $\\#1$ are consistent with ${\\mathrm{Cu}}^{0}$ , while the spectrum from area $\\#2$ is related to $\\mathrm{Cu^{+}}$ , matching well with the FFT analysis (Fig. 3c). Cu valance state mapping based on EELS spectrum imaging shows the distribution of $\\mathrm{Cu}$ and $\\mathrm{Cu}_{2}\\mathrm{O}$ in the whole area (Fig. 3d). The dashed lines highlighted in the overlay of the Cu and $\\mathrm{Cu}_{2}\\mathrm{O}$ maps indicate the existence of $\\mathrm{Cu}/\\mathrm{Cu}_{2}\\mathrm{O}$ interfaces on DVL-Cu, which might be beneficial for the $\\mathrm{CO}_{2}\\mathrm{RR}$ . \n\nElectrochemical $\\mathbf{CO}_{2}\\mathbf{RR}$ performance in the H-cell. To measure the electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of DVL-Cu, we performed electrolysis in $\\mathrm{CO}_{2}$ -saturated $0.5{\\mathrm{M}}{}$ KCl by using a gas-tight H-cell. For comparison, the electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of the RCuO-NPs was also evaluated under the same conditions. It is worth noting that KCl was chosen as the electrolyte because it benefits the preservation of $\\mathrm{Cu}_{2}\\mathrm{O}$ during the $\\mathrm{CO}_{2}\\mathrm{RR}$ through a high local $\\mathrm{\\DeltapH}$ , and the specific adsorption of $\\mathrm{Cl^{-}}$ suppresses hydrogen evolution at higher overpotentials48,49. \n\nThe geometric current density of DVL-Cu in the $\\mathrm{CO}_{2}$ - saturated electrolyte is considerably higher than that of R-CuONPs over the whole test potential window (Supplementary Fig. 15), while the two catalysts deliver similar geometric current densities in the Ar-saturated electrolyte, indicating that DVL-Cu possesses higher intrinsic $\\mathrm{CO}_{2}\\mathrm{RR}$ activity. To exclude the electrochemical surface area (ECSA) influence, we calculated the roughness factor (RF) of the two samples by the double-layer capacitance method (Supplementary Fig. 17). DVL-Cu has an RF of 201.7, while R-CuO-NPs have a comparable RF of 165.7. These measurements eliminate the influence of the ECSA and confirm the higher intrinsic $\\mathrm{CO}_{2}\\mathrm{RR}$ activity of DVL-Cu than R-CuO-NPs. Moreover, DVL-Cu exhibits high $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and $\\mathrm{FE}_{\\mathrm{C}_{2+}}$ FE, which shows a higher $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ of $74.9\\pm2.6\\%$ and $\\mathrm{FE}_{\\mathrm{C}_{2+}}$ of $80.5\\pm2.3\\%$ at $-0.9\\mathrm{V}$ (Fig. 4a and Supplementary Table 3) than that of R-CuONPs $(\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}=52.0\\pm{\\bar{3}}.7\\% $ $\\mathrm{FE}_{\\mathrm{C}_{2+}}=61.9\\pm4.0\\%)$ (Fig. 4b). The liquid products of DVL-Cu and R-CuO-NPs are mainly composed of ethanol and formate, with a small percentage of acetate, propanol, etc. (Fig. 4e). Furthermore, the $\\mathrm{FE}_{\\mathrm{H}_{2}}$ is only $13.6\\%$ at $-0.9\\mathrm{V}$ of ${\\mathrm{DVL}}{\\cdot}{\\mathrm{Cu}},$ which might be due to the massive consumption of H atoms in the proton-coupled electron transfer (PCET) step during the ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ . Additionally, the partial current density curves and $\\mathrm{C}_{2}\\mathrm{H}_{4}$ Tafel curves were plotted to reveal the kinetic characteristics. The $\\mathrm{C_{1}}$ partial current densities of these two catalysts are comparable, but the $\\mathrm{C}_{2+}$ partial current density of DVL-Cu is five times higher than that of ${\\mathrm{R-CuO-NPs}}$ at $-1.0\\mathrm{V}$ (Fig. 4c). The $\\mathrm{C}_{2}\\mathrm{H}_{4}$ Tafel slopes of DVL-Cu and ${\\mathrm{R-CuO-NPs}}$ are $179.3\\mathrm{mV}$ decade−1 and $421.1\\mathrm{mV}$ decade−1 (Fig. 4d), respectively, suggesting a much lower $\\mathrm{C}_{2}\\mathrm{H}_{4}$ formation kinetic barrier on DVL-Cu than on R-CuO-NPs. The sluggish kinetics of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and $\\mathrm{C}_{2+}$ formation on R-CuO-NPs was further confirmed by the $\\mathrm{C}_{2+}/$ $\\mathrm{C_{1}}$ (CO, formate) and $\\mathrm{C_{2}H_{4}/C H_{4}}$ ratios in $\\mathrm{CO}_{2}\\mathrm{RR}$ products (Fig. 4f). The $\\mathrm{C}_{2+}/\\mathrm{C}_{1}$ and $\\mathrm{C_{2}H_{4}/C H_{4}}$ product ratios of DVL-Cu at $-0.8\\mathrm{V}$ are 19.4 and 208.6, respectively, indicating that most of the CO intermediates tend to dimerize, generating $\\mathrm{C}_{2+}$ products rather than forming $\\mathrm{C}_{1}$ species. In comparison, the $\\mathrm{C}_{2+}/\\mathrm{C}_{1}$ and $\\mathrm{C_{2}H_{4}/C H_{4}}$ product ratios (3.6 and 7.0 at $-0.8\\mathrm{V})$ on R-CuO-NPs are much lower than that of DVL-Cu, which verifies the sluggish kinetics of the $\\scriptstyle{\\mathrm{C-C}}$ coupling step on ${\\mathrm{R-CuO-NPs}}.$ . \n\n![](images/e11038e1f6818d33d9c32eb8daba9e31dd2986757f94a859d8ef9e3f2745ada8.jpg) \nFig. 3 STEM and EELS characterizations of the DVL-Cu catalyst. a STEM BF image (left) of DVL-Cu and FFT patterns (right) of the corresponding area in the BF image. b Enlarged image of area #1 in (a). c EELS spectra acquired from areas #1 and #2 in (a). Standard $\\mathsf{C u}$ , $\\mathsf{C u^{+}}$ and $\\mathsf{C u}^{2+}$ EELS results are plotted as references. d STEM high-angle annular dark-field (HAADF) image and EELS maps of $\\mathsf{C u}$ and $\\mathsf{C u}_{2}\\mathsf{O}$ and their overlay in DVL-Cu. The dashed lines highlighted in the overlay denote the $\\mathsf{C u/C u_{2}O}$ interfaces. \n\nThe performance observed in stability tests with OD-Cu catalysts was always unsatisfactory according to previous studies. We performed long-term electrolysis under potentiostatic mode with the same conditions mentioned above (Supplementary \n\nFigs. 16 and 18). DVL-Cu shows a steady i-t curve and high $\\mathrm{C}_{2}\\mathrm{H}_{4}$ selectivity $(\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}=62.2\\%)$ for $50\\mathrm{h}$ at $-0.8\\mathrm{V}$ . In contrast, RCuO-NPs only retains a stable $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ for less than $^{7\\mathrm{h}}$ at $-0.8\\mathrm{V}$ . Post-electrolysis SEM images of DVL-Cu show that nanoplates densely stack in order without any agglomeration after $50\\mathrm{{h}}$ of electrolysis, and only a slight increase in plate thickness is observed (Supplementary Figs. 25a and b). The poor stability of R-CuO-NPs might be caused by the agglomeration of Cu nanoparticles during the $\\mathrm{CO}_{2}\\mathrm{RR}$ (Supplementary Fig. 19). \n\nAdditionally, the high-resolution transmission electron microscopy (HRTEM) images confirm that there are no $\\mathrm{Cu}_{2}\\mathrm{O}$ species in R-CuONPs after $^{2\\mathrm{h}}$ of the ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ either at the edge or the center (Supplementary Fig. 20), and the exposed plane is similar to that of DVL-Cu. $\\mathrm{Cu}_{2}\\mathrm{O}$ characteristic peaks are also absent in the GI-XRD profiles of R-CuO-NPs after $^\\mathrm{1h}$ of the $\\mathrm{CO}_{2}\\mathrm{RR}$ (Supplementary Fig. 21). However, the DVL-Cu sample preserves a similar $\\mathrm{{Cu}/\\mathrm{{Cu}_{2}\\mathrm{{O}}}}$ composite structure and subsurface $\\mathrm{Cu^{+}}$ content after a long-term test (Supplementary Figs. 27–29). The presence of $\\mathrm{Cu}_{2}\\mathrm{O}$ in DVL-Cu may be the origin of the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance under the premise that the ECSA, exposed Cu facets, and hydrophilicity (Supplementary Fig. 30) of these two catalysts are comparable. \n\nElectrochemical $\\mathbf{CO_{2}R R}$ performance in the flow cell and MEA electrolyzer. To evaluate the application potential of $\\mathrm{CuO-NPs}$ for the industrial ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ we further measured their catalytic performance in a flow cell. A Cu membrane ( $\\langle500\\mathrm{nm}\\rangle$ was deposited on carbon paper (Sigracet 28BC) with a gas diffusion layer (GDL) by electron beam evaporation (Fig. 5a). Then, galvanostatic anodic oxidation was performed to obtain CuO-NPs on the GDL $(\\mathrm{CuO-NPs@GDL})$ , similar to those on copper foil. The synthesis and characterization details can be seen in the supplementary information (Methods and Supplementary Figs. 32 and 33). The as-fabricated electrode was utilized in a flow cell setup reported previously (Supplementary Figs. 34 and 35), where KCl and KOH served as the catholyte and anolyte, respectively. CuO nanoplates on the GDL were converted to DVL-Cu during the $\\bar{\\mathrm{CO}}_{2}\\mathrm{RR}$ with a maintained plate-like nanostructure $(\\mathrm{DVL-Cu@GDL},$ Supplementary Fig. 36). \n\n![](images/0674ecdb0c188ca4d7482d292bd92e07181898219d86cde819fec9a3077dc872.jpg) \nFig. 4 Electrochemical $C O_{2}R R$ performance of DVL-Cu and R-CuO-NPs. a FEs of DVL-Cu. b FEs of $R–C u O–N P s$ . c $\\mathsf C_{2+}$ and ${\\mathsf C}_{1}$ partial current densities of DVL-Cu and $R-C u O-N P s$ . d $C_{2}H_{4}$ partial current density Tafel plots of DVL-Cu and R-CuO-NPs. e FEs of liquid products of DVL-Cu and $R–C u O–N P s$ f $C_{2}H_{4}/C H_{4}$ ratios and $\\mathsf C_{2+}/\\mathsf C_{1}$ ratios for $C O_{2}R R$ products of DVL-Cu and R-CuO-NPs. Error bars represent the standard deviation of three independent measurements. \n\nThe $\\mathrm{CO}_{2}\\mathrm{RR}$ performance and cathodic $\\mathrm{EE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ are displayed in Fig. 5b. For $\\mathrm{C}_{2+}$ species, the FEs increase from $62.3\\pm1.4\\%$ (at $-0.63\\mathrm{V})$ to $85.4\\pm2.0\\%$ (at $-0.81\\mathrm{V},$ and then drop to $69.3\\pm3.2\\%$ (at $-1.01\\mathrm{V},$ due to the increased hydrogen generation at a large overpotential. Remarkably, the selectivity towards $\\mathrm{C}_{2}\\mathrm{H}_{4}$ is incredibly high $(\\sim99\\%)$ among $\\mathrm{C}_{2+}$ products. There is a small amount of ethanol and negligible acetate in the liquid products and no ethane in the gas products (Supplementary Figs. 37 and 38). The maximum $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ and cathodic $\\mathrm{EE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ are $84.5\\pm1.7\\%$ and $47.6\\pm1.0\\%$ respectively (at $-0.81\\mathrm{V})$ , some of the highest $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ and cathodic $\\mathrm{EE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ values ever reported in the literature (Supplementary Table 2). The active $\\mathrm{C}_{2}\\mathrm{H}_{4}$ production is attributed to the stable nanostructure and the $\\mathrm{{Cu/Cu^{+}}}$ interfaces (Supplementary Figs. 40 and 41). Moreover, the excellent $\\mathrm{C}_{2}\\mathrm{H}_{4}$ selectivity does not compromise the current densities. The $\\mathrm{C_{2}H_{4}}$ partial current densities are $\\mathsf{\\partial}92.5\\mathsf{m A}\\mathsf{c m}^{-2}$ at $-0.81\\mathrm{V}$ and $175.2\\mathrm{\\mA}\\mathrm{cm}^{-2}$ at $-1.01\\mathrm{V}$ , respectively, indicating the high intrinsic $\\mathrm{CO}_{2}\\mathrm{RR}$ activity of the DVL$\\mathrm{Cu@GDL}$ catalyst (Supplementary Fig. 42). By comparison, $\\mathrm{H}_{2}$ production, the dominant by-product, is severely suppressed in the flow cell, with a FE of $12.6\\pm1.3\\%$ $\\mathrm{13.8\\mA\\cm^{-2}}$ ) at $-0.81\\mathrm{V}$ , probably due to the high local $\\mathsf{p H}$ generated by fast proton consumption and the low buffering capability of the KCl electrolyte. \n\nThe $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of the two-electrode flow cell configuration was also tested (Fig. 5c and Supplementary Fig. 31). With increasing current density, the voltage increases linearly between $^{-2}$ and $-5\\mathrm{V}$ . At the optimal current density of $75\\mathrm{mAcm}^{-2}$ , the $77.3\\%$ $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ coupled with a full-cell voltage of $-3.1\\mathrm{V}$ realized an $\\mathrm{EE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ of $28.9\\pm1.3\\%$ , the highest value achieved in the neutral catholyte in the literature. Surprisingly, the DVL- $\\mathbf{\\cdot}\\mathbf{Cu@GDL}$ catalyst presented an average $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ of $74.0\\%$ at a constant current density of $150\\mathrm{mA}\\mathrm{cm}^{-2}$ for ${\\sim}55\\mathrm{h}$ of stable electrolysis without any surface hydrophobic treatment (Fig. 5e and Supplementary Fig. 39). The compact evaporated $\\mathtt{C u}$ film and stable nanostructure might have the ability to prevent the GDL from flooding during electrolysis, which accounts for the excellent long-term stability in the flow cell. Furthermore, to improve the $\\bar{\\mathrm{EE}}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ at a high current density ${>}200\\ \\mathrm{mA}\\ \\mathrm{cm}^{-2}$ , we tested our catalyst in a membrane electrode assembly (MEA) electrolyzer (Fig. 5d and f, Supplementary Fig. 43). The full-cell $\\mathrm{EE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ increased markedly to $27.6\\pm0.8\\%$ at $200\\mathrm{mA}\\mathrm{cm}^{-2}$ and $23.7\\pm1.1\\%$ at $250\\mathrm{mAcm}^{-2}$ using $0.5\\mathrm{M}\\mathrm{KHCO}_{3}$ as the anolyte, with competitive $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ values of $80.0\\pm2.2\\%$ and $71.2\\pm3.3\\%$ respectively. In conclusion, the DVL-Cu catalyst realized costeffective and stable ethylene conversion at a competitive current density. \n\nMechanism analysis. To unravel the intrinsic origin of the high structural stability of DVL-Cu, the electrode current density and electrolyte current density of DVL-Cu and $\\mathrm{Cu}_{2}\\mathrm{O}$ nanocubes 1 $\\mathrm{1}2\\mathrm{nm}$ in length) during the $\\mathrm{CO}_{2}\\mathrm{RR}$ were acquired by COMSOL multiphysics simulations (Fig. 6). $\\mathrm{Cu}_{2}\\mathrm{O}$ nanocubes were chosen as a comparison to show the agglomeration effect, and DVL-Cu carefully preserved its nanostructures after the $\\mathrm{CO}_{2}\\mathrm{RR}$ process (Supplementary Fig. 22). Under an identical total circuit current $(10\\bar{0}\\mathrm{\\mA}\\mathrm{cm}^{-2},$ ), $\\bar{\\mathrm{Cu}_{2}\\mathrm{O}}$ nanocubes deliver a nearly 5-fold higher electrode current density than DVL-Cu (Fig. 6c, d). Uniformly distributed nanoplates with a large surface area of DVL-Cu effectively disperse the current density, which guarantees structural stability during the ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ Moreover, the electrolyte current density (correlated to local electrostatic intensity) in the $\\mathrm{Cu}_{2}\\mathrm{O}$ nanocube system is more nonuniform than that in the DVL-Cu system and is especially higher at the corners of the nanocubes (Fig. 6a, b). A faster dissolution/redeposition process occurs in those regions with a higher electrolyte current density, and increased local electrostatic intensity leads to easier electromigration of nanostructures, which results in eventual agglomeration of $\\mathrm{Cu}_{2}\\mathrm{O}$ nanocubes. Simultaneously, the higher electrode current density of $\\mathrm{Cu}_{2}\\mathrm{O}$ nanocubes accelerates this agglomeration process. These simulation results indicate that a moderate electrode current density coupled with the uniformly distributed electrolyte current density of DVL-Cu guarantees its prolonged structural stability during the $\\mathrm{CO}_{2}\\mathrm{RR}$ . \n\n![](images/8a586a62eb40f07ba1dca78e9655d3d41e17c9899fbb7659f7cd0e54e0fed1a8.jpg) \nFig. 5 Preparation and $C O_{2}R R$ performance of DVL- $\\mathbf{\\tilde{c}u@G D L}$ in the flow cell and MEA electrolyzer. a Schematic illustration of the fabrication of $\\mathsf{C u O-}$ $N P s@\\mathsf{G D L}$ . (MPL: microporous layer; CF: carbon fiber) b FEs and cathodic $\\mathsf{E E}_{\\mathsf{C}_{2}\\mathsf{H}_{4}}$ of the DVL-Cu@GDL catalyst in the flow cell. c Full-cell potential and cathodic $\\mathsf{E E}_{\\mathsf{C}_{2}\\mathsf{H}_{4}}$ of the $D\\mathsf{V}\\mathsf{L-C u}@\\mathsf{G D L}$ catalyst in the flow cell. d Gas product FEs of the DVL-Cu@GDL catalyst in an MEA electrolyzer. e Stability test of the DVL-Cu catalyst at a constant current density of $150\\mathsf{m A c m}^{-2}$ in the flow cell. f Cell potential and $\\mathsf{E E}_{\\mathsf{C}_{2}\\mathsf{H}_{4}}$ of the DVL-Cu@GDL catalyst in an MEA electrolyzer. Error bars represent the standard deviation of three independent measurements. \n\nThe role of local $\\mathrm{\\pH}$ and $\\mathrm{Cl^{-}}$ in the catalytic performance was investigated by electrolyte analysis. KCl (non-buffering electrolyte), ${\\mathrm{KHCO}}_{3}$ (buffering electrolyte) and $\\mathrm{K}_{2}\\mathrm{SO}_{4}$ (non-buffering electrolyte without $\\mathrm{Cl^{-}}$ ) were chosen for comparison. A higher local $\\mathrm{\\pH}$ was generated when non-buffering electrolytes were used as catholytes due to their poor $\\mathrm{\\pH}$ stabilization capability. By observing the overall product distribution, it is found that the ethylene production in the presence of ${\\mathrm{KHCO}}_{3}$ is not satisfactory, with significantly higher methane production (Supplementary Fig. 23, detailed analyses are shown in Note 1). It is suggested that the lower local $\\mathsf{p H}$ in ${\\mathrm{KHCO}}_{3}$ electrolyte than that in KCl electrolyte results in inferior ethylene production because lower $\\mathrm{\\pH}$ regions favor hydrogen evolution and methane production, both needing $\\mathrm{H}^{+50}$ . After comparing the catalytic performance in KCl and $\\mathrm{K}_{2}\\mathrm{SO}_{4}$ , we conclude that the existence of $\\mathrm{\\bar{Cl}^{-}}$ suppresses hydrogen evolution, especially at high overpotentials, which is considered the result of the $\\mathrm{Cl^{-}}$ -specific adsorption. The strongly adsorbed $\\mathrm{Cl^{-}}$ facilitates electron transfer from the electrode to $\\mathrm{CO}_{2}$ and suppresses the adsorption of protons, leading to a higher hydrogen evolution overpotential51. \n\nThe long-term stability test results in different electrolytes are also quite informative. Interestingly, DVL-Cu delivered an ${\\sim}50\\mathrm{h}$ stable current density and ethylene FE in $\\mathrm{K}_{2}\\mathrm{SO}_{4}$ under $-0.8\\mathrm{V}$ . In comparison, it only preserved stable performance for less than $10\\mathrm{{h}}$ in ${\\mathrm{KHCO}}_{3}$ under the same conditions. SEM and TEM images of the post- ${\\mathrm{.CO}}_{2}{\\mathrm{RR}}$ sample in $\\mathrm{K}_{2}\\mathrm{SO}_{4}$ (Supplementary Fig. 24) display morphology and $\\mathrm{{Cu}(0)/\\mathrm{{Cu}(I)}}$ interfaces equivalent to those obtained from the KCl sample, indicating that a high local pH plays a critical role in the prolonged stability, rather than morphology. Detailed post-electrolysis characterizations were performed to determine the stability origin for the samples obtained from ${\\mathrm{KHCO}}_{3}$ and KCl. EELS mapping of the ${\\mathrm{KHCO}}_{3}$ sample (Supplementary Fig. 26) reveals that $\\mathtt{C u(I)}$ species agglomerate on the top of nanoplates, while these species distribute uniformly in the KCl sample (Supplementary Figs. 27 and 28). AES depth profile analyses (Supplementary Fig. 29) further verify the $\\mathtt{C u(I)}$ species distribution differences, where the $\\mathtt{C u(I)}$ content in the KCl sample is higher with depth than that in the ${\\mathrm{KHCO}}_{3}$ sample. Apparently, non-buffering electrolytes stabilize the DVL-Cu catalyst by protecting its $\\mathrm{{Cu(0)/Cu(I)}}$ interfaces during electrolysis. Since the ${\\mathrm{K}}_{\\mathrm{sp}}$ of $\\mathrm{\\CuOH}$ is relatively low $(1.0^{*}10^{-14})$ , a high local pH significantly slows the dissolution of $\\mathtt{C u(I)}$ species. Hence, a high local $\\mathrm{pH}$ suppresses the dissolution/redeposition of $\\mathrm{{Cu(I)}}$ species in non-buffering electrolytes, which preserves the $\\mathrm{{Cu}(0)/\\mathrm{{Cu}(I)}}$ interfaces during the $\\mathrm{CO}_{2}\\mathrm{RR}$ \n\n![](images/bd397011bd00a0f4e35d9c1e9f27517f7b49ba02d7c39f2a04c9490b1d61883f.jpg) \nFig. 6 COMSOL multiphysics simulations. a, c Electrode current density and electrolyte current density distribution of DVL-Cu at $100\\mathsf{m A c m}^{-2}$ . b, d Electrode current density and electrolyte current density distribution of $\\mathsf{C u}_{2}\\mathsf{O}$ nanocubes at $100\\mathsf{m A c m}^{-2}$ . The electrode current density and electrolyte current density (in a and b) correspond to the left and right legends, respectively. The electrode current densities in (c) and (d) correspond to the left and right legends, respectively. The conical arrows represent the electrolyte current density vector. \n\nTo gain mechanistic insights into the $\\mathrm{CO}_{2}\\mathrm{RR}$ catalytically active sites and reaction pathway of ${\\mathrm{DVL}}{\\cdot}{\\mathrm{Cu}},$ we further performed DFT calculations to investigate the energy barrier for the production of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and other products at different Cucontaining sites. Here, $\\operatorname{Cu}(110)$ and $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ slabs were first constructed as the model of ${\\mathrm{Cu}}^{0}$ and $\\mathrm{Cu^{+}}$ catalytic sites based on the STEM and GI-XRD results, and $\\operatorname{Cu}(110)$ was considered the corresponding active plane to produce $\\mathrm{C}_{2+}$ products in reference25. The $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(110)$ interface was modeled by distributing the $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ slab on the surface of the $\\mathtt{C u}(110)$ slab (Supplementary Figs. 44–46, the size effect of $\\mathrm{Cu}_{2}\\mathrm{O}$ slab is discussed in Supplementary Fig. 47, Supplementary Table 1 and Supplementary Note 3). Then, the energy barrier of each step in the reaction pathway on the $\\mathtt{C u}(110)$ slab, $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ slab and $\\mathrm{Cu(110)/Cu_{2}\\bar{O}(110)}$ interface was calculated to evaluate the catalytic performance of different catalytic sites in DVL-Cu. \n\nFirst, the $\\mathrm{C}_{2}\\mathrm{H}_{4}$ formation pathway through the $^*\\mathrm{CO-^{*}C O H}$ dimerization pathway was investigated to reveal catalytic sites on DVL-Cu (Supplementary Tables 4 and 5). The $^*\\mathrm{CO-^{*}C O H}$ dimerization pathway was confirmed to be most favorable over other pathways considering the reaction energy and kinetic adsorption structure (Fig. 7a and Supplementary Figs. 48–50). The reduction of $^*\\mathrm{CO}_{2}$ to $^{*}{\\mathrm{COOH}}$ occurs with $\\Delta G=0.50\\mathrm{eV}$ on $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(110)$ , which is lower than that on $\\mathtt{C u}(110)$ 1 $\\Delta G=0.76\\mathrm{eV})$ ) and $\\mathrm{Cu}_{2}\\mathrm{O}$ $\\ ^{\\prime}\\Delta G=1.05\\mathrm{eV},$ since the interfaces promote the stabilization of the $^{*}{\\mathrm{COOH}}$ intermediate. Therefore, $\\mathrm{\\bar{Cu}(110)/C u_{2}O(110)}$ secures a higher surface $^{*}\\mathrm{CO}$ coverage, which is consistent with the higher $\\mathrm{FE}_{\\mathrm{CO}}$ of DVL-Cu at a low overpotential. More importantly, the energy barriers for the ratedetermining step (RDS) are $0.60\\mathrm{eV}$ $({}^{*}\\mathrm{\\bar{C}O}+{}^{*}\\mathrm{CO}\\rightarrow{}^{*}\\mathrm{CO}+{}^{*}$ COH), $1.19\\mathrm{eV}$ $({}^{*}\\mathrm{CO}+{}^{*}\\mathrm{CO}\\rightarrow{}^{*}\\mathrm{CO}+{}^{*}\\mathrm{COH})$ and $1.05\\mathrm{eV}$ $(^{*}\\mathrm{OH}_{2}\\mathrm{CCH}\\longrightarrow{^*}\\mathrm{O}+\\mathrm{C}_{2}\\mathrm{H}_{4})$ on $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(110)$ , $\\mathtt{C u}(110)$ and $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ , respectively (Fig. 7b, c). Hence, $\\mathrm{C_{2}H_{4}}$ production happens more easily on the $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(110)$ interface, indicating that these interfaces are the catalytically active sites in DVL-Cu. Furthermore, DFT calculations reveal that the adsorption energy of the $^{*}{\\mathrm{OCCOH}}$ intermediate is $-0.77\\mathrm{eV}$ on $\\mathrm{Cu}(1\\bar{1}0)/\\mathrm{Cu}_{2}\\mathrm{O}(\\bar{1}\\bar{1}0)$ , which is more negative than that on $\\operatorname{Cu}(110)$ $(-0.18\\mathrm{eV})$ and $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ $(-0.2\\bar{8}\\mathrm{eV})$ (Fig. 7c). These results verify that the presence of heterointerfaces are beneficial to the adsorption of the post-dimerization intermediate $({}^{*}\\mathrm{OCCOH})$ , thus reducing the energy barrier of $C{\\mathrm{-}}C$ dimerization. The carbonyl C binding to the interface while the hydroxyl C binding to Cu atoms is the optimized adsorbed structure of the $^{*}{\\mathrm{OCCOH}}$ intermediate on the $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(110)$ interface (Fig. 7d). Moreover, $\\mathrm{C}_{2}\\mathrm{H}_{4}$ desorption is important for the regeneration of active sites, which is crucial for the production rate of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ Interestingly, this step is exergonic only on $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(110)$ $(-0.52\\mathrm{eV})$ , indicating that DVL-Cu possesses a fast $\\mathrm{C}_{2}\\mathrm{H}_{4}$ production capacity. \n\n![](images/695b6e1a818cd564533c0b960c25f7a069c7830e053261c9c838f87a46159308.jpg) \nFig. 7 DFT calculation results. a A reaction energy diagram for the ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ to $^{\\star}C O H$ (the intermediate of $C H_{4}$ formation) and to $^{\\star}\\mathsf{O C C}$ through different dimerization pathways on the Cu(110) slab, $\\mathsf{C u/C u_{2}O}$ interface and ${\\mathsf{C u}}_{2}{\\mathsf{O}}(110),$ slab. b A reaction energy diagram for the ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ to $C_{2}H_{4}$ on the $\\mathsf{C u}(110)$ slab, $\\mathsf{C u/C u_{2}O}$ interface and $\\mathsf{C u}_{2}\\mathsf{O}(110)$ slab. c The free energy of the rate-determined step for the ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ to $C_{2}H_{4}$ pathway and the adsorption energy of the $^{\\star}\\mathsf{O C C O H}$ intermediate on the Cu(110) slab, $\\mathsf{C u/C u_{2}O}$ interface and $\\mathsf{C u}_{2}\\mathsf{O}(110)$ slab. d Optimized structures for the reaction intermediates of the $C_{2}H_{4}$ formation pathway on the $\\mathsf{C u/C u_{2}O}$ interface. \n\nThe high selectivity towards $\\mathrm{C}_{2}\\mathrm{H}_{4}$ was then studied by comparing the free energy barriers of different catalytic products. The formation of $\\mathrm{CH}_{4}$ via different pathways was primarily considered. As shown in Supplementary Fig. 51, $\\mathrm{CH}_{4}$ production related to the $^{*}\\mathrm{HCOO}$ intermediate is energetically less favorable than other pathways (leading to $\\mathrm{CH}_{4}$ or other products) related to the $\\mathrm{COOH^{*}}$ intermediate in the first hydrogenation step on $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(110$ ). Based on the $^{*}{\\mathrm{COOH}}$ intermediate, the free energy barriers of the second hydrogenation step are $1.57\\mathrm{eV}$ $({}^{*}\\mathrm{HCOOH})$ and $-0.32\\:\\mathrm{eV}(^{*}\\mathrm{CO})$ on the $\\mathrm{Cu}/\\mathrm{Cu}_{2}\\mathrm{O}$ interface, respectively, which indicates that $^*\\mathrm{CO}$ tends to form more than the $^{*}\\mathrm{HCOOH}$ intermediate. Afterwards, insurmountable energy barriers are required for the hydrogenation of $^*\\mathrm{CO}$ to form $^{*}{\\mathrm{COH}}$ on three catalytic sites, while the free energy required for another $^*\\mathrm{CO}$ adsorption step is lower than that for $^*\\mathrm{CO}$ hydrogenation on all three sites, making the reaction pathway to $\\mathrm{C}_{2+}$ products possible. These factors account for the high $\\mathrm{C_{2}H_{4}/C H_{4}}$ product ratios of the DVL-Cu catalyst. Otherwise, the energy barriers required for $\\mathrm{H}_{2},$ formate and $\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH}$ are dramatically larger than that for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ (Supplementary Figs. 51–53). Hence, the formation of $\\mathrm{C}_{2}\\mathrm{H}_{4}$ is energetically more favorable than other products, as demonstrated by DFT calculations, which is identical to the $\\mathrm{CO}_{2}\\mathrm{RR}$ product analysis results. \n\nIn brief, the adsorption of two $^*\\mathrm{CO}$ species, followed by hydrogenation of one of the $^{*}\\mathrm{CO}$ species and the consecutive dimerization of $^*\\mathrm{CO}$ and $^{*}{\\mathrm{COH}}$ to form $^{*}{\\mathrm{OCCOH}}$ , is considered the most favorable pathway for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ production on the $\\mathrm{Cu}(110)/$ $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ interface in DVL-Cu. The insurmountable energy barrier for the hydrogenation of a single adsorbed $^*\\mathrm{CO}$ and the facile $\\mathrm{C}_{2}\\mathrm{H}_{4}$ formation pathway on the $\\mathrm{Cu}(110)/\\mathrm{Cu}_{2}\\mathrm{O}(11$ 0) interface result in the high $\\mathrm{C_{2}H_{4}/C H_{4}}$ ratio in $\\mathrm{CO}_{2}\\mathrm{RR}$ products. These DFT results suggest that the existence of $\\mathrm{Cu}/\\mathrm{Cu}_{2}\\mathrm{O}$ interfaces reduces the energy barrier of $C{\\mathrm{-}}C$ dimerization and accelerates the desorption of ${\\mathrm{C}}_{2}{\\mathrm{H}}_{4},$ leading to highly active and selective $\\mathrm{C}_{2}\\mathrm{H}_{4}$ production on DVL-Cu. \n\n# Discussion \n\nIn summary, we have proposed an anodic oxidation method for the large-scale preparation of oxide-derived $\\mathtt{C u}$ catalysts with stable $\\bar{\\mathrm{Cu}}/\\mathrm{Cu}_{2}\\mathrm{O}$ interfaces for highly active $\\mathrm{CO}_{2}\\mathrm{RR}$ to $\\mathrm{C}_{2}\\mathrm{H}_{4}$ with high FE and prolonged stability. The high oxidation degree of $\\mathrm{Cu}$ foil with vertically arranged Cu nanoplates prevents the agglomeration of nanostructures and preserves stable $\\mathrm{Cu}/\\mathrm{Cu}_{2}\\mathrm{O}$ interfaces during the $\\mathrm{CO}_{2}\\mathrm{RR}.$ Utilizing these advantages, the DVL-Cu catalyst achieves a high $\\mathrm{FE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ of $84.5\\pm1.{\\bar{7}}\\%$ and $\\mathrm{EE}_{\\mathrm{C}_{2}\\mathrm{H}_{4}}$ of $28.9\\pm1.3\\%$ in the flow cell and $27.6\\pm0.8\\%$ EEC H at $200\\mathrm{\\mA}\\mathrm{cm}^{-2}$ in the MEA electrolyzer. Moreover, the DVL-Cu catalyst maintains consistent electrolysis performance for $\\sim55\\mathrm{h}$ in the flow-cell. Mechanism analysis indicates that a moderate electrode current density and uniform electrolyte current density coupled with high local $\\mathrm{\\pH}$ guarantee structural and interfacial stability, while $\\mathrm{Cl^{-}}$ -specific adsorption suppresses hydrogen evolution at higher overpotentials. DFT calculations reveal that the energy barrier for $C{\\mathrm{-}}C$ coupling is significantly reduced because $\\dot{\\mathrm{Cu^{+}}}$ species enhance the adsorption capacity of the $^{*}{\\mathrm{OCCOH}}$ intermediate. The good selectivity, prolonged stability and facile production of the DVL-Cu catalyst highlight its application potential in realizing the industrial conversion of $\\mathrm{CO}_{2}$ to $\\mathrm{C}_{2}\\mathrm{H}_{4}$ . \n\n# Methods \n\nDFT calculations. All DFT calculations were performed using Vienna ab initio simulation package $(\\mathrm{VASP})^{52}$ , within the projector-augmented wave (PAW) potentials53 together with the generalized gradient approximation (GGA) exchange-correlation54 proposed by Perdew–Burke–Ernzerhof $(\\mathrm{PBE})^{55}$ to calculate the correlation energies. The bulk-unit cells for pure Cu and $\\mathrm{Cu}_{2}\\mathrm{O}$ were constructed and the $\\mathbf{k}$ -mesh were $19\\times19\\times19$ and $7\\times7\\times10$ , respectively. The $\\mathrm{Cu}(110)$ surface, a main exposed facet in the experimental result, was composed of four layers with $3\\times3$ supercells, and the $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ supported on $\\mathtt{C u}(110)$ surface was modeled by adding $\\mathrm{Cu}_{2}\\mathrm{O}(110)$ clusters of 8 $\\mathrm{Cu}_{2}\\mathrm{O}$ to the $\\mathtt{C u}(110)$ surface. The bottom two layers of $\\mathrm{Cu}(110)$ were fixed and the vacuum space was set as $20\\textup{\\AA}$ to avoid interactions with their periodic images. The $3\\times5\\times1$ Monkhorst–Pack k-point meshes and plane-wave cutoff energy of $520\\mathrm{eV}$ were used in all calculations. The convergence tolerances for residual force and energy were set to $0.01\\mathrm{eV}\\mathring{\\mathrm{A}}^{-1}$ and $\\bar{1}0^{-5}\\mathrm{eV}$ , respectively. \n\nPreparation of the catalysts. For the DVL-Cu catalyst used in the H-cell, Cu foils (Alfa Aesar, $0.025\\mathrm{mm}$ , $99.8\\%$ ) were cut into $1.5\\times3\\mathrm{{cm}}^{2}$ and annealed at $1050^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ under $\\mathrm{Ar/H}_{2}$ atmosphere to remove the copper oxide layer on it. Then the Cu foil was fixed onto a platinum electrode clip to form a working electrode. The counter electrode was a Cu rod made from curled $\\mathrm{Cu}$ foil. The electrolyte used for anodic oxidation was $1.0\\mathrm{M}\\mathrm{NaOH}$ (Alfa Aesar, $98\\%$ ). Galvanostatic oxidation on the Cu foil at a constant current density of $0.26\\operatorname{mA}{\\mathrm{cm}^{-2}}$ was performed by a CHI 760E potentiostat until the surface of Cu foil entirely turned into black. The CuONPs were washed five times by deionized water before being used as the $\\mathrm{CO}_{2}\\mathrm{RR}$ catalyst. For the R-CuO-NPs catalyst, the CuO-NPs were annealed at $450^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{h}}$ under $\\mathrm{Ar/H}_{2}$ atmosphere. \n\nFor the DVL- $\\mathbf{\\mathcal{C}}\\mathbf{u}@\\mathbf{GDL}$ catalyst used in the flow cell, a $500\\mathrm{nm}$ thick Cu layer was primarily deposited on the carbon paper (Sigracet $28~\\mathrm{BC},$ by an electron beam evaporation system (DZS500, SKY). During the evaporation process, $100\\mathrm{g}$ Cu particles were placed in a graphite crucible inside the evaporation chamber. The chamber pressure was vacuumized to $10^{-6}$ Torr by the molecular pump. A thin $\\mathrm{Cu}$ layer was deposited on carbon paper at an evaporation rate of $1\\mathrm{\\AA}\\dot{\\mathbf{s}}^{-1}$ controlled by the film thickness measurement system. GDL was kept rotating at a slow speed of $50\\mathrm{rpm}$ during evaporation. Evaporated carbon paper was fixed onto a platinum electrode clip to form a working electrode. The electrochemical oxidation process was the same as the Cu foil except that the current density was $0.13\\mathrm{mAcin}^{-2}$ for the carbon paper. \n\nMaterials characterization. SEM images were taken by a ZEISS SUPRA55 microscope. A JEOL F200 microscope was used to take the TEM images. AFM images were obtained by Bruker Dimension FastScan microscope. Aberration corrected STEM imaging and EELS mapping were acquired from a Nion HERMES-100 under $100\\mathrm{kV}$ with a 30 mrad convergence angle. The enlarged STEM-BF image is denoised by low-psss filtering. Cu valence state analysis was performend by multiple linear least squares (MLLS) fitting in the $920{\\-}960\\ \\mathrm{eV}$ energy-loss range. The processed EELS data has been calibrated along the energyloss axis to much the standard data56, as the as-acquired spectra deviate slightly due to the small non-linearity of the energy dispersion at the two ends of the spectrometer prism. XPS spectra (ESCALAB 250Xi, Thermo Fisher Scientific Inc., USA) was used to investigate chemical compositions and elemental oxidation states of the catalysts. Raman spectra were obtained from the Raman spectrometer (Horiba, Olympus microscope) with a $532\\mathrm{nm}$ laser. GI-XRD patterns were obtained by a Panalytical Empyrean X-ray diffractometer. Gas products were analyzed by a Shimadzu GC 2030 gas chromatograph. Liquid products were analyzed by a NMR spectroscopy (AVANCE III $600\\mathrm{M}$ , Bruker). \n\nElectrochemical $\\pmb{\\mathrm{co}}_{2}$ reduction measurements. A gas-tight electrolysis H-cell (Gaoss Union, $50~\\mathrm{mL}$ ) separated by a Nafion 117 membrane (Sigma Aldrich) was used to measure the $\\mathrm{CO}_{2}\\mathrm{RR}$ performance of the catalysts. $30\\mathrm{mL}0.5\\mathrm{M}$ KCl (Sigma Aldrich) was employed as catholyte and anolyte. Before $\\mathrm{CO}_{2}\\mathrm{RR}$ test, 500 standard cubic centimeters per minute (sccm) $\\mathrm{CO}_{2}$ $(99.999\\%$ , Praxair) was constantly bubbled into the electrolytes for $30\\mathrm{min}$ to saturated it with $\\mathrm{CO}_{2}$ . A $\\mathrm{Pt}$ foil (Pine Instruments, $1\\times1~\\mathrm{cm}^{2}$ ) and a $\\mathrm{\\Ag/AgCl}$ electrode (Gaoss Union) filled with saturated KCl solution were used as counter electrode and reference electrode, respectively. We kept the $\\mathrm{CO}_{2}$ flow rate at $20\\ s c c\\mathrm{m}$ and $1000\\mathrm{rpm}$ stirring of the catholyte during the ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ For the long-term $\\mathrm{CO}_{2}\\mathrm{RR}$ stability test, the $\\mathrm{CO}_{2}$ - saturated KCl electrolytes were replaced each $12\\mathrm{h}$ . The electrolysis was performed by a CHI 760E potentiostat using chronoamperometry method at each applied potential for $^{\\textrm{1h}}$ to measure the FE of each product. All applied potentials were converted to the RHE by the equation: $E$ (vs. $\\mathrm{RHE})=E$ (vs. $\\mathrm{\\Ag/AgCl)}$ $^+$ $0.204\\mathrm{V}+0.0591\\mathrm{V}\\times\\mathrm{pH}-i R,$ , with $i R$ compensation. The gas products combined with $\\mathrm{CO}_{2}$ gas were injected into a six-way valve, which is linked with an online GCBID. The gas chromatography was calibrated by five standard gases $\\left(\\operatorname{H}_{2},\\right.$ CO, $\\mathrm{CH}_{4}.$ $\\mathrm{C}_{2}\\mathrm{H}_{2}$ , $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and ${\\mathrm{C}}_{2}{\\mathrm{H}}_{6}$ in $\\mathrm{CO}_{2}\\mathrm{,}$ ) with gradient concentrations at $20\\mathrm{sccm}$ flow rate before using. The gas samples were analyzed at least after $30\\mathrm{min}$ electrolysis to insure the $\\mathrm{CO}_{2}\\mathrm{RR}$ reaching a stable state. Liquid samples were collected after $^{\\textrm{\\scriptsize1h}}$ electrolysis and measured by $^1\\mathrm{H}$ NMR with dimethyl sulfoxide (DMSO) as an internal standard. The Faradaic efficiencies (FEs) were calculated on the basic of the following equation: \n\n$$\n{\\mathrm{Faradaic~effciencies}}={\\frac{Q_{x}}{Q_{\\mathrm{total}}}}={\\frac{n_{x}N_{x}F}{Q_{\\mathrm{total}}}}\n$$ \n\nwhere $Q_{x}$ and $Q_{t o t a l}$ was the charge passed into product $x$ and totally passed charge (C) during $\\mathrm{CO}_{2}\\mathrm{RR},$ , $n_{x}$ represents the electron transfer number of product $x$ , $N_{x}$ was the product amount $\\mathrm{(mol)}$ of $x$ measured by GC or NMR and $F$ was the Faraday constant $(96485{\\mathrm{C}}{\\mathrm{mol}}^{-1}$ ). \n\nThe (cathodic) energy efficiencies were calculated on the basic of the following equation: \n\n$$\n\\mathrm{energyeffciencies}={\\frac{E^{\\ominus}}{E_{\\mathrm{applied}}}}\\times\\mathrm{FE}_{C_{2}H_{4}}\n$$ \n\n$$\n{\\mathrm{cathodic~energy}}{\\mathrm{vffciencies}}={\\frac{E^{\\ominus}}{1.23\\mathrm{V}-E_{\\mathrm{applied}}}}\\times\\mathrm{FE}_{C_{2}H_{4}}\n$$ \n\nwhere $E^{6}$ is the thermodynamic potential for the ethylene formation (1.15 V), $E_{\\mathrm{applied}}$ represents the potential applied during the $\\mathrm{CO}_{2}\\mathrm{RR}.$ \n\nFor the electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ test in a flow cell, a commercial flow cell electrolyzer (Gaoss Union, $\\textstyle1\\cos^{2}$ active area) was used. The CuO-NPs@GDL was placed between the gas chamber and catholyte chamber, and the catholyte and anolyte chambers were separated by an anion-exchange membrane (FAA-3-PK130, Fumapem). A $\\mathrm{Ag/AgCl}$ (filled with saturated KCl solution) electrode and a Ni foam with NiFe hydroxides deposited on it using an electrodeposition method reported previouly57 were employed as reference electrode and counter electrode, respectively. KCl and KOH solution were served as the catholyte and anolyte, respectively. The gas flow rate was $50\\mathrm{sccm}$ during $\\mathrm{CO}_{2}\\mathrm{RR}$ and the gas products were injected into a six-way valve. The catholyte and anolyte were circulated by a peristaltic pump at $10\\mathrm{{sccm}}$ and $200\\mathrm{sccm}$ , respectively. The electrolysis of the flow cell was performed on a potentiostat (CS-150CN, CorrTest) equipped with a $2\\mathrm{A}$ current booster. \n\nFor the electrochemical $\\mathrm{CO}_{2}\\mathrm{RR}$ test in an MEA electrolyzer, a commercial MEA electrolyzer (Shanghaikeqi, $5\\mathrm{cm}^{2}$ active area) was used. The $\\mathrm{CuO-NPs@GDL}.$ an anion-exchange membrane (Sustainion® X37-50) and $\\mathrm{Ti-IrO}_{2}$ mesh were compressed to form MEA. The MEA was placed between the anode chamber and cathode chamber, then assembled together using associated bolts. $0.5{\\bf M}$ ${\\mathrm{KHCO}}_{3}$ solution was served as the catholyte. The gas flow rate was $50\\mathrm{sccm}$ during $\\mathrm{CO}_{2}\\mathrm{RR}$ and the gas products were injected into a six-way valve. The catholyt was circulated by a peristaltic pump at $200\\mathrm{sccm}$ . The electrolysis of the MEA electrolyzer was performed on a potentiostat (HSP-3010, Henghui). \n\nECSA measurements. The electrochemical double-layer capacitance method was used for ECSA measurements. In a typical procedure, the catalysts were reduced at $-0.6\\mathrm{V}$ vs. RHE for 2 min and cyclic voltammograms at different scan rates (20, 40, 60, 80 and $100\\mathrm{mVs^{-1}}$ ) have been obtained in Ar-saturated $^{1\\mathrm{M}}$ KOH solution in the non-Faradaic region $(-0.07$ to $0.13\\mathrm{V}$ vs. RHE) when the curves of different cycles overlapping. The difference between anodic current and cathodic current at $0.03\\mathrm{V}$ of different scan rates was recorded and plot against the scan rates. The $1/$ 2 slope values of these curves were calculated as the double-layer capacitance for corresponding catalysts. The ratios of the double-layer capacitance of the catalysts versus the electropolished copper foil were calculated as the $\\mathrm{RF}^{58}$ . \n\nCOMSOL multiphysics simulations. A two-dimensional finite element model was developed to describe the difference of current density distribution between plate electrode and square electrode. A two-dimensional cross-section of $1000\\times800\\mathrm{nm}$ near the electrode was taken for the computational domain. The slice electrodes are represented by thin irregular columns, while the cube electrodes are assumed to be stacked squares. The average height of the sheet electrode is about $300\\mathrm{nm}$ , and the square electrode is about $50\\mathrm{nm}$ . \n\nThe tertiary current distribution module from the COMSOL multiphysics software was employed for the finite element simulation. The transport of the $\\mathrm{K^{+}}$ and the anion was solved by the Nernst-Plank equation: \n\n$$\n\\nabla\\cdot\\left(D\\nabla c_{i}+\\frac{D_{z_{i}e}}{k_{\\mathrm{B}}T}c_{i}\\nabla V\\right)=0\n$$ \n\nWhere $c_{\\mathrm{i}}$ is the concentrations of the potassium or anion ion, $\\mathbf{z}_{\\mathrm{i}}$ are the valences of ions, $e$ is the elementary charge, $k_{\\mathrm{B}}$ is Boltzmann constant, the absolute temperature $T$ is set as $297.3\\dot{\\mathrm{K}}$ . The reaction current density was obtained by the Butler–Volmer equation: \n\n$$\ni=i_{0}\\bigg[\\exp\\bigg(\\frac{\\alpha_{a}n F\\eta}{R T}\\bigg)-\\exp\\bigg(-\\frac{\\alpha_{c}n F\\eta}{R T}\\bigg)\\bigg]\n$$ \n\nWhere the $\\mathfrak{a}_{\\mathrm{a}}$ and ${\\mathfrak{a}}_{\\mathrm{c}}$ are the dimensionless anodic and cathodic charge transfer coefficients, respectively. $n$ is the number of electrons involved in the electrode reaction, $R$ is the universal gas constant, $F$ is the Faraday constant. The exchange current density $i_{0}$ was obtained by the Arrhenius law: \n\n$$\ni_{0}\\propto\\exp\\left(-{\\frac{E_{a}}{k_{\\mathrm{B}}T}}\\right)\n$$ \n\nWhere the $E_{\\mathrm{a}}$ is the activation energy of the reaction, which was experimentally obtained to be $0.21\\mathrm{eV}$ with $\\mathrm{K^{+}}$ involved. \n\nBoundary conditions: The upper boundary was set as the electrolyte boundary with a current density at $100\\mathrm{m}\\mathrm{\\bar{A}}/\\mathrm{cm}^{2}$ , and an ion and anion concentration with $0.5\\mathrm{mol/L}$ The electrolyte conductivity was assumed to be $10\\mathrm{{S/m}}$ . The diffusion coefficient of $\\mathrm{Li^{+}}$ and the anion were set as $5.273\\times10^{-9}\\mathrm{m}^{2}/s$ and $2.032\\times10^{-9}\\mathrm{m}^{2}/\\mathrm{s},$ respectively. \n\n# Data availability \n\nThe data supporting this study are available within the paper and the Supplementary Information. All other relevant source data are available from the corresponding author upon reasonable request. \n\nReceived: 27 August 2021; Accepted: 15 March 2022; Published online: 06 April 2022 \n\n# References \n\n1. Chu, S., Cui, Y. & Liu, N. The path towards sustainable energy. Nat. Mater. 16, 16–22 (2017). \n2. Nitopi, S. et al. Progress and perspectives of electrochemical $\\mathrm{CO}_{2}$ reduction on copper in aqueous electrolyte. Chem. Rev. 119, 7610–7672 (2019). \n3. Xu, S. & Carter, E. A. Theoretical insights into heterogeneous (photo) electrochemical $\\mathrm{CO}_{2}$ reduction. Chem. Rev. 119, 6631–6669 (2019). \n4. Aresta, M., Dibenedetto, A. & Angelini, A. Catalysis for the balorization of exhaust carbon: from $\\mathrm{CO}_{2}$ to chemicals, materials, and fuels. Technological use of $\\mathrm{CO}_{2}$ . Chem. Rev. 114, 1709–1742 (2014). \n5. Verma, S., Lu, S. & Kenis, P. J. A. Co-electrolysis of $\\mathrm{CO}_{2}$ and glycerol as a pathway to carbon chemicals with improved technoeconomics due to low electricity consumption. Nat. Energy 4, 466–474 (2019). \n6. Hori, Y., Wakebe, H., Tsukamoto, T. & Koga, O. Electrocatalytic process of CO selectivity in electrochemical reduction of $\\mathrm{CO}_{2}$ at metal electrodes in aqueous media. Electrochim. Acta 39, 1833–1839 (1994). \n7. Schouten, K. J. P., Kwon, Y., van der Ham, C. J. M., Qin, Z. & Koper, M. T. M. A new mechanism for the selectivity to $\\mathbf{C}_{1}$ and $\\mathbf{C}_{2}$ species in the electrochemical reduction of carbon dioxide on copper electrodes. Chem. Sci. 2, 1902–1909 (2011). \n8. Calle-Vallejo, F. & Koper, M. T. M. Theoretical considerations on the electroreduction of CO to $\\mathbf{C}_{2}$ species on $\\mathrm{Cu}(100)$ electrodes. Angew. Chem. Int. Ed. 52, 7282–7285 (2013). \n9. Jiang, K. et al. Metal ion cycling of Cu foil for selective C–C coupling in electrochemical $\\mathrm{CO}_{2}$ reduction. Nat. Catal. 1, 111–119 (2018). \n10. Ma, W. et al. Electrocatalytic reduction of $\\mathrm{CO}_{2}$ to ethylene and ethanol through hydrogen-assisted C–C coupling over fluorine-modified copper. Nat. Catal. 3, 478–487 (2020). \n11. Todorova, T. K., Schreiber, M. W. & Fontecave, M. Mechanistic Understanding of $\\mathrm{CO}_{2}$ reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ toward multicarbon products by heterogeneous copper-based catalysts. ACS Catal. 10, 1754–1768 (2020). \n12. Tran, K. & Ulissi, Z. W. Active learning across intermetallics to guide discovery of electrocatalysts for $\\mathrm{CO}_{2}$ reduction and $\\mathrm{H}_{2}$ evolution. Nat. Catal. 1, 696–703 (2018). \n13. Liu, X. et al. Understanding trends in electrochemical carbon dioxide reduction rates. Nat. Commun. 8, 15438 (2017). \n14. Zhou, Y. et al. Dopant-induced electron localization drives $\\mathrm{CO}_{2}$ reduction to $\\mathrm{C}_{2}$ hydrocarbons. Nat. Chem. 10, 974–980 (2018). \n15. Hori, Y., Kikuchi, K. & Suzuki, S. Production of CO and $\\mathrm{CH}_{4}$ in electrochemical reduction of $\\mathrm{CO}_{2}$ at metal electrodes in aqueous hydrogencarbonate solution. Chem. Lett. 14, 1695–1698 (1985). \n16. De Luna, P. et al. Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction. Nat. Catal. 1, 103–110 (2018). \n17. Weng, Z. et al. Active sites of copper-complex catalytic materials for electrochemical carbon dioxide reduction. Nat. Commun. 9, 415 (2018). \n18. Choi, C. et al. Highly active and stable stepped Cu surface for enhanced electrochemical $\\mathrm{CO}_{2}$ reduction to $\\mathrm{C_{2}H_{4}}$ . Nat. Catal. 3, 804–812 (2020). \n19. Lv, J.-J. et al. A highly porous copper electrocatalyst for carbon dioxide reduction. Adv. Mater. 30, 1803111 (2018). \n20. Zhang, W. et al. Atypical oxygen-bearing copper boosts ethylene selectivity toward electrocatalytic $\\mathrm{CO}_{2}$ reduction. J. Am. Chem. Soc. 142, 11417–11427 (2020). \n21. Mistry, H. et al. Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene. Nat. Commun. 7, 12123 (2016). \n22. Cheng, T., Xiao, H. & Goddard, W. A. Full atomistic reaction mechanism with kinetics for CO reduction on $\\mathrm{Cu}(100)$ from ab initio molecular dynamics freeenergy calculations at $298{\\mathrm{~K~}}$ . Proc. Natl Acad. Sci. USA 114, 1795 (2017). \n23. Gao, D. et al. Plasma-activated copper nanocube catalysts for efficient carbon dioxide electroreduction to hydrocarbons and alcohols. ACS Nano 11, 4825–4831 (2017). \n24. Weng, Z. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction to hydrocarbons on a heterogeneous molecular Cu catalyst in aqueous solution. J. Am. Chem. Soc. 138, 8076–8079 (2016). \n25. Zhu, C. et al. Product-specific active site motifs of Cu for electrochemical $\\mathrm{CO}_{2}$ reduction. Chem 7, 406–420 (2020). and promotes renewable fuels electrosynthesis. Nat. Catal. 3, 98–106 (2020). \n27. Feng, X., Jiang, K., Fan, S. & Kanan, M. W. Grain-boundary-dependent $\\mathrm{CO}_{2}$ electroreduction activity. J. Am. Chem. Soc. 137, 4606–4609 (2015). \n28. Loiudice, A. et al. Tailoring copper nanocrystals towards $\\mathbf{C}_{2}$ products in electrochemical $\\mathrm{CO}_{2}$ reduction. Angew. Chem. Int. Ed. 55, 5789–5792 (2016). \n29. Grosse, P. et al. Dynamic changes in the structure, chemical state and catalytic selectivity of Cu nanocubes during $\\mathrm{CO}_{2}$ electroreduction: size and support effects. Angew. Chem. Int. Ed. 57, 6192–6197 (2018). \n30. Hall, A. S., Yoon, Y., Wuttig, A. & Surendranath, Y. Mesostructure-induced selectivity in $\\mathrm{CO}_{2}$ reduction catalysis. J. Am. Chem. Soc. 137, 14834–14837 (2015). \n31. Yang, K. D. et al. Morphology-directed selective production of ethylene or ethane from $\\mathrm{CO}_{2}$ on a Cu mesopore electrode. Angew. Chem. Int. Ed. 56, 796–800 (2017). \n32. Kas, R. et al. Three-dimensional porous hollow fibre copper electrodes for efficient and high-rate electrochemical carbon dioxide reduction. Nat. Commun. 7, 10748 (2016). \n33. Zhu, Q. et al. Carbon dioxide electroreduction to $\\mathrm{C}_{2}$ products over coppercuprous oxide derived from electrosynthesized copper complex. Nat. Commun. 10, 3851 (2019). \n34. Hoang, T. T. H., Ma, S., Gold, J. I., Kenis, P. J. A. & Gewirth, A. A. Nanoporous copper films by additive-controlled electrodeposition: $\\mathrm{CO}_{2}$ reduction catalysis. ACS Catal. 7, 3313–3321 (2017). \n35. Jin, M. et al. Shape-controlled synthesis of copper nanocrystals in an aqueous solution with glucose as a reducing agent and hexadecylamine as a capping agent. Angew. Chem. Int. Ed. 50, 10560–10564 (2011). \n36. Hoang, T. T. H. et al. Nanoporous copper–silver alloys by additive-controlled electrodeposition for the selective electroreduction of $\\mathrm{CO}_{2}$ to ethylene and ethanol. J. Am. Chem. Soc. 140, 5791–5797 (2018). \n37. Gao, D., Scholten, F. & Roldan Cuenya, B. Improved $\\mathrm{CO}_{2}$ electroreduction performance on plasma-activated Cu catalysts via electrolyte design: halide effect. ACS Catal. 7, 5112–5120 (2017). \n38. Chen, C. S., Wan, J. H. & Yeo, B. S. Electrochemical reduction of carbon dioxide to ethane using nanostructured $\\mathrm{Cu}_{2}\\mathrm{O}.$ -derived copper catalyst and palladium(II) chloride. J. Phys. Chem. C. 119, 26875–26882 (2015). \n39. Zhong, D. et al. Coupling of $\\mathrm{Cu}(100)$ and (110) facets promotes carbon dioxide conversion to hydrocarbons and alcohols. Angew. Chem. Int. Ed. 60, 4879–4885 (2020). \n40. Li, C. W. & Kanan, M. W. $\\mathrm{CO}_{2}$ reduction at low overpotential on Cu electrodes resulting from the reduction of thick $\\mathrm{Cu}_{2}\\mathrm{O}$ films. J. Am. Chem. Soc. 134, 7231–7234 (2012). \n41. Yan, Z. et al. The in situ growth of $\\mathrm{Cu}_{2}\\mathrm{O}$ with a honeycomb structure on a roughed graphite paper for the efficient electroreduction of $\\mathrm{CO}_{2}$ to $\\mathrm{C}_{2}\\mathrm{H}_{4}$ . Catal. Sci. Technol. 11, 6742–6749 (2021). \n42. Altaf, N. et al. Electro-derived $\\mathrm{Cu-Cu}_{2}\\mathrm{O}$ nanocluster from LDH for stable and selective $\\mathrm{C}_{2}$ hydrocarbons production from $\\mathrm{CO}_{2}$ electrochemical reduction. $J.$ Energy Chem. 48, 169–180 (2020). \n43. Arán-Ais, R. M., Scholten, F., Kunze, S., Rizo, R. & Roldan Cuenya, B. The role of in situ generated morphological motifs and $\\mathrm{{Cu}(i)}$ species in $\\mathrm{C}_{2+}$ product selectivity during $\\mathrm{CO}_{2}$ pulsed electroreduction. Nat. Energy 5, 317–325 (2020). \n44. Chen, X. et al. Electrochemical $\\mathrm{CO}_{2}$ -to-ethylene conversion on polyamineincorporated Cu electrodes. Nat. Catal. 4, 20–27 (2021). \n45. Pyun, C. H. & Park, S. M. In situ spectroelectrochemical studies on anodic oxidation of copper in alkaline solution. J. Electrochem. Soc. 133, 2024–2030 (1986). \n46. Roberts, F. S., Kuhl, K. P. & Nilsson, A. High selectivity for ethylene from carbon dioxide reduction over copper nanocube electrocatalysts. Angew. Chem. Int. Ed. 54, 5179–5182 (2015). \n47. Leapman, R. D., Grunes, L. A. & Fejes, P. L. Study of the $\\mathrm{L}_{23}$ edges in the 3d transition metals and their oxides by electron-energy-loss spectroscopy with comparisons to theory. Phys. Rev. B 26, 614–635 (1982). \n48. Lee, S., Kim, D. & Lee, J. Electrocatalytic Production of C3-C4 compounds by conversion of $\\mathrm{CO}_{2}$ on a chloride-induced Bi-Phasic $\\mathrm{Cu}_{2}\\mathrm{O}.$ -Cu catalyst. Angew. Chem. Int. Ed. 54, 14701–14705 (2015). \n49. Ozden, A. et al. High-rate and efficient ethylene electrosynthesis using a catalyst/promoter/transport layer. ACS Energy Lett. 5, 2811–2818 (2020). \n50. Hori, Y., Murata, A. & Takahashi, R. Formation of hydrocarbons in the electrochemical reduction of carbon dioxide at a copper electrode in aqueous solution. J. Chem. Soc., Faraday Trans. 1 85, 2309–2326 (1989). \n51. Ogura, K. et al. $\\mathrm{CO}_{2}$ attraction by specifically adsorbed anions and subsequent accelerated electrochemical reduction. Electrochim. Acta 56, 381–386 (2010). \n52. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n53. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994). \n54. Perdew, J. P. & Wang, Y. Accurate and simple analytic representation of the electron-gas correlation energy. Phys. Rev. B 45, 13244–13249 (1992). \n55. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n56. Ahn, C. C., Krivanek, O. L., Burgner, R. P., Disko, M. M., & Swann, P. R. EELS atlas: a reference collection of electron energy loss spectra covering all stable elements. Gatan, Inc. (Warrendale, U.S.A., 1983). \n57. Lu, X. & Zhao, C. Electrodeposition of hierarchically structured threedimensional nickel–iron electrodes for efficient oxygen evolution at high current densities. Nat. Commun. 6, 6616 (2015). \n58. Verdaguer-Casadevall, A. et al. Probing the active surface sites for CO reduction on oxide-derived electrocatalysts. J. Am. Chem. Soc. 137, 9808–9811 (2015). \n\n# Acknowledgements \n\nThis work was supported by the National Key R&D Program of China (Grant No. 2018YFA0306900), the National Natural Science Foundation of China (No. 51872012), the Fundamental Research Funds for the Central Universities and the 111 Project (B17002). \n\n# Author contributions \n\nThese authors contributed equally: W.L., P.Z., A.L., and B.W. Y.G. and W.Z. conceived the project and supervised the research work. W.L. and P.Z. designed and conducted most of the experiments of this project. A.L. and W.Z. performed the STEM measurements and analyzed the results. B.W. and R.Z. designed the computational studies and analyzed the computational data. G.Z. conducted the GI-XRD measurements. K.S., X.G., and Q.C. performed the electronic beam evaporation. W.L., Y.W. and X.W. co-wrote the manuscript. Y.G., W.Z., and R.Z. discussed the results and reviewed the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-29428-9. \n\nCorrespondence and requests for materials should be addressed to Yongji Gong. \n\nPeer review information Nature Communications thanks Gengfeng Zheng, Ali Seifitokaldani and the other anonymous reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1126_science.abj2637", + "DOI": "10.1126/science.abj2637", + "DOI Link": "http://dx.doi.org/10.1126/science.abj2637", + "Relative Dir Path": "mds/10.1126_science.abj2637", + "Article Title": "Metastable Dion-Jacobson 2D structure enables efficient and stable perovskite solar cells", + "Authors": "Zhang, F; Park, SY; Yao, CL; Lu, HP; Dunfield, SP; Xiao, CX; Ulicná, S; Zhao, XM; Du Hill, L; Chen, XH; Wang, XM; Mundt, LE; Stone, KH; Schelhas, LT; Teeter, G; Parkin, S; Ratcliff, EL; Loo, YL; Berry, JJ; Beard, MC; Yan, YF; Larson, BW; Zhu, K", + "Source Title": "SCIENCE", + "Abstract": "The performance of three-dimensional (3D) organic-inorganic halide perovskite solar cells (PSCs) can be enhanced through surface treatment with 2D layered perovskites that have efficient charge transport. We maximized hole transport across the layers of a metastable Dion-Jacobson (DJ) 2D perovskite that tuned the orientational arrangements of asymmetric bulky organic molecules. The reduced energy barrier for hole transport increased out-of-plane transport rates by a factor of 4 to 5, and the power conversion efficiency (PCE) for the 2D PSC was 4.9%. With the metastable DJ 2D surface layer, the PCE of three common 3D PSCs was enhanced by approximately 12 to 16% and could reach approximately 24.7%. For a triple-cation-mixed-halide PSC, 90% of the initial PCE was retained after 1000 hours of 1-sun operation at similar to 40 degrees C in nitrogen.", + "Times Cited, WoS Core": 319, + "Times Cited, All Databases": 330, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000740261400042", + "Markdown": "# SOLAR CELLS \n\n# Metastable Dion-Jacobson 2D structure enables efficient and stable perovskite solar cells \n\nFei Zhang1\\*†, So Yeon Park1†, Canglang $\\yen123,4$ , Haipeng ${\\mathbf{L}}{\\mathbf{u}}^{1}$ , Sean P. Dunfield4,5,6, Chuanxiao Xiao4, Sonˇa Uliˇcná7, Xiaoming Zhao8, Linze Du Hill9, Xihan Chen1, Xiaoming Wang2,3, Laura E. Mundt7, Kevin H. Stone7, Laura T. Schelhas1,7, Glenn Teeter4, Sean Parkin10, Erin L. Ratcliff9,11,12, Yueh-Lin Loo8, Joseph J. Berry4,5,13, Matthew C. Beard1, Yanfa $\\yen123,4$ , Bryon W. Larson1\\*, Kai Zhu1\\* \n\nThe performance of three-dimensional (3D) organic-inorganic halide perovskite solar cells (PSCs) can be enhanced through surface treatment with 2D layered perovskites that have efficient charge transport. We maximized hole transport across the layers of a metastable Dion-Jacobson (DJ) 2D perovskite that tuned the orientational arrangements of asymmetric bulky organic molecules. The reduced energy barrier for hole transport increased out-of-plane transport rates by a factor of 4 to 5, and the power conversion efficiency (PCE) for the 2D PSC was $4.9\\%$ . With the metastable DJ 2D surface layer, the PCE of three common 3D PSCs was enhanced by approximately 12 to $16\\%$ and could reach approximately $24.7\\%$ . For a triple-cation–mixed-halide PSC, $90\\%$ of the initial PCE was retained after 1000 hours of 1-sun operation at $\\tt{\\sim}40^{\\circ}\\tt{C}$ in nitrogen. \n\nP icinegrstip(fPhieCotdEo vol techn stwaheiicrg(chPoaVns) nohlaeovfgfeyi ,cbiaenendpo versio cies (PCEs) as high as $25.5\\%$ $(I)$ . Despite this high performance, device stability hinders their commercialization. Efforts to improve device stability include defect passivation, contact layer modification, and encapsulation (2–5). The use of two-dimensional (2D) perovskite as the interfacial modification layer has great potential for addressing surface defects, in particular to improve the stability and efficiency of PSCs (6–8). The Ruddlesden-Popper (RP) 2D layered perovskites that are based on bulky cations, such as phenethylammonium (PEA+) or butylammonium $\\mathrm{(BA^{+})}$ , have been widely applied to the surface of 3D perovskite thin films to decrease defect densities and enhance device stability (8–11). Such bulky organic cations often self-assemble into a barrier layer that protects against surface water adsorption or ingress. However, bulky-cation–based 2D structures often exhibit anisotropic and poor charge transport across the organic layer and are susceptible to charge-extraction barrier formation that inhibits efficient device operation (12–14). \n\nWe show a rational design strategy to maximize the out-of-plane hole transport based on a metastable Dion-Jacobson (DJ) 2D perovskite surface layer with a reduced transport energy barrier by using asymmetric bulky organic molecules, leading to highly efficient and stable perovskite solar cells. Our general design strategy to maximize the out-of-plane charge transport in 2D perovskites is illustrated in Fig. 1. Because the free electrons and holes are localized in the conduction band minimum (CBM) and valence band maximum (VBM) of the $\\mathrm{[PbI_{6}]}$ planes, respectively, and because of the long distance between two adjacent $\\mathrm{[PbI_{6}]}$ planes, the out-of-plane charge transport must traverse the bulky cationic organic layers. Thus, it is mainly limited by two factors: (i) the low carrier mobility within the organic layer and (ii) the energy barrier between the $\\mathrm{[PbI_{6}]}$ planes and the bulky organic cations. To mitigate the first limit, DJ 2D structures based on a short and single layer of divalent organoammonium cations (15–18) are generally more preferable than the RP 2D structures based on double layers of monovalent organoammonium cations (19). To mitigate the second limiting factor, the band offsets between the $\\mathrm{[PbI_{6}]}$ planes and the bulky cationic organic layers need to be optimized. \n\nThe coupling (interaction) between $\\mathrm{[PbI_{6}]}$ planes and the organic cations is through hydrogen bonding, and the change in the bonding strength can affect the band offsets (20). For a weaker hydrogen bonding configuration, the bonding states of the bulky organic layers are normally at a higher energy position, which brings them nearer the VBM of the $\\mathrm{[PbI_{6}]}$ planes (Fig. 1A). This effect leads to a smaller band offset or barrier for hole transport between the $\\mathrm{[PbI_{6}]}$ inorganic planes and organic cations. Because of the spinorbital coupling of $\\mathrm{Pb~6p}$ orbitals, the antibonding states of the organic layers are much higher than the CBM of the $\\mathrm{[PbI_{6}]}$ planes. Thus, a DJ structure with weaker hydrogen bonding should improve hole transport. Yet, a weaker hydrogen bonding (or H-bonding) configuration generally means a less stable structure. Thus, a metastable DJ 2D structure with short cationic organic layers could in principle facilitate out-of-plane hole transport. \n\nA rational strategy to induce the desired metastable H-bonding motifs in DJ 2D structures is to use asymmetric diammonium cations in lieu of symmetric straight chain divalent cations. For example, both $N{\\mathcal{N}}$ -dimethyl-1,3- propane diammonium $\\mathrm{(DMePDA^{2+}}$ ) and 1,4- butane diammonium $\\mathrm{(BDA^{2+})}$ form DJ 2D structures with short interlayer distances $(l9)$ . Whereas $\\mathrm{BDA}^{2+}$ is symmetric and features two terminal primary ammonium ions on the butyl (C4) chain, $\\mathrm{{DMePDA}^{2+}}$ is asymmetric, with a primary ammonium on one end and a dimethyl-substituted tertiary ammonium on the other end of the propyl (C3) chain. The “head or tail” H-bonding options for the DMePDA2+ molecules are asymmetric, giving rise to different possible relative orientations of the adjacent molecules, and the different H-bonding interactions possible within the $\\mathrm{[PbI_{6}]}$ planes could lead to both stable and metastable energy polymorphs of the 2D structure (Fig. 1B). The alternating relative head-to-tail alignment of adjacent DMePDA2+ cations (most stable orientation configuration) provides a larger compensation for overall structural relaxation than those of other orientation arrangements. By contrast, the symmetric $\\mathrm{BDA}^{2+}$ molecule has only one possible orientation configuration (Fig. 1B) and cannot form metastable polymorphs. \n\nTable 1. PV parameters of PSCs based on control and $\\mathsf{D M e P D A l}_{2}$ -modified perovskite thin films by using different perovskite compositions. $V_{\\infty,}$ , open-circuit voltage; FF, fill factor. \n\n\n
DeviceScanJsc (mA/cm2)Voc (V)FFPCE (%)SPO (%)
FAo.85MAo.1CSo.05Pbl2.gBro.1Forward24.351.1110.77320.920.4
Reverse24.321.0990.76420.4
FA0.85MAo.1CSo.05Pbl2.9Bro.1 /DMePDAl2Forward24.971.1670.82224.023.7
Reverse24.931.1670.81423.7
FA0.97MAo.03Pbl2.91Bro.09Forward25.211.1030.79122.021.7
Reverse25.151.1080.78121.8
FA0.97MAo.03Pbl2.91Bro.09 /DMePDAl2Forward25.251.1580.84324.724.3
Reverse25.261.1580.83924.5
MAPbl3Forward23.09 23.091.0900.74218.718.2
Reverse1.0800.72918.2
MAPbl3/DMePDAl2Forward23.191.1310.79720.920.8
Reverse23.191.1320.79420.8
\n\nWe further examined single-crystal 2D DJ structures from $\\mathrm{BDAI_{2}}$ and $\\mathrm{{DMePDAI_{2}}}$ and conducted first-principle calculations to verify our design strategy. We found that 1,3-propane diammonium diiodine $\\mathrm{(PDAI_{2})}$ )—which is often assumed the shortest diamine (15, 21) to form DJ 2D perovskites—templated Pb-I to a non-perovskite structure (empirical formula: $\\mathrm{[PDAPbI_{4}]_{15}}$ • $\\begin{array}{r}{[\\mathrm{PDAI_{2}}].}\\end{array}$ ) (fig. S1 and table S1). Thus, $\\mathrm{BDA}^{2+}$ represents the shortest linearalkyl-chain diamine that forms an iodide-based 2D DJ structure $\\mathrm{(BDAPbI_{4})}$ (fig. S2A and table S2). C3-based $\\mathrm{{DMePDAI_{2}}}$ with two methyl groups attached to one side of PDA can form 2D DJ structures with two polymorphs, which we refer to as DMePDAPbI4-1 (fig. S2B and table S3) and DMePDAPbI4-2, respectively (fig. S2C) (22). \n\nWe grew the DMePDAP $\\mathrm{\\bI_{4}}$ -1 single crystal, which was based on the most stable DMePDA2+ orientation alignment, from a concentrated hydroiodic acid solution using a slow-crystallization process, as adapted from our previous report (23) and consistent with a previous theoretical predication (24). By contrast, the $\\mathrm{DMePDAPbI_{4}\\mathrm{-2}}$ single crystal, which was based on a metastable orientational alignment, was formed from either a fast cooling (22) or antisolvent quenching during singlecrystal growth (25), both of which represent a fast-crystallization process. In comparison with $\\mathrm{DMePDAPbI_{4}\\mathrm{-}\\mathrm{1}}_{\\mathrm{:}}$ , $\\mathrm{{DMePDAPbI_{4}}\\mathrm{{-}}}$ 2 had an emission wavelength that was red-shifted $\\sim25\\ \\mathrm{nm}$ , which is consistent with the corresponding absorption data (fig. S3). The average interlayer distances were comparable among these 2D structures (\\~10.10 to ${\\bf10.39\\AA}$ ), with that of $\\mathrm{BDAPbI_{4}}$ being the shortest. The corresponding hydrogen-bonding configurations for these three single-crystal structures (figs. S4, S5, and S6) were consistent with the analysis in Fig. 1B. \n\nWe confirmed our design strategy by means of density functional theory (DFT) calculation. \n\n![](images/6072ec17a63380cdb3dbe352662d41d3d550fc4cf9857c863e1c3cf33a37b2d9.jpg) \nFig. 1. Design concept. (A) Illustration of band offsets between $[\\mathsf{P b l}_{6}]$ planes ${\\mathsf{D M e P D A}}^{2+}$ cations and the sole arrangement of symmetric ${\\mathsf{B D A}}^{2+}$ cations. and bulky organic cations with a weaker and stronger degree of H-bonding. (C) $\\mathsf{H S E}+$ vdW calculated total DOSs of the organic cations in $\\mathsf{B D A P b l}_{4}$ , For clarity, the inorganic framework orbital diagram is omitted in the $\\mathsf{D M e P D A P b l}_{4}\\mathrm{-}1$ [with orientation-1 in (B)], and $\\mathsf{D M e P D A P b l}_{4}.2$ [with orientamiddle of the panel. (B) Two possible arrangements of asymmetric tion-2 in (B)]. The VBMs were set to $0.0~\\mathrm{eV}$ . \n\nWe calculated the effect of organic molecules using the screened hybrid functional and van der Waals (vdW) interaction (HSE+vdW) (26, 27). The DMePDAPbI4-2 structure was indeed less stable than the $\\mathrm{{DMePDAPbI_{4}}.}$ - 1 structure. The energy level differences of the organic cations in $\\mathrm{BDAPbI_{4}},$ $\\mathrm{DMePDAPbI_{4}\\mathrm{-}\\mathrm{1},}$ and DMePDAPbI4-2 could be seen in the total density of states (DOSs) of the organic cations (the sum of states of C, N, and H atoms) (Fig. 1C). The total DOS of $\\mathrm{BDA}^{2+}$ cations in $\\mathrm{BDAPbI_{4}}$ was lower in energy (farther from VBM) than that of DMePDA2+ cations in $\\mathrm{DMePDAPbI_{4}\\mathrm{-}\\mathrm{1}};$ 。 which in turn was lower in energy compared with the total DOS of $\\mathrm{{DMePDA}^{2+}}$ cations in DMePDAPbI4-2. Thus, we expected the outof-plane hole transport to improve from $\\mathrm{BDAPbI_{4}}$ to $\\mathrm{DMePDAPbI_{4}{-}2}$ . \n\nRapid perovskite film growth conditions from standard solution deposition also led to the formation of the metastable DMeP$\\mathrm{DAPbI_{4}}\\mathrm{-}2$ structure. The XRD patterns of the DMePDAPbI4 thin film prepared by means of spin coating are shown in Fig. 2A. The powder XRD pattern measured from DMePDAPbI4- 1 and DMePDAPbI4-2 single-crystal samples, along with the calculated powder XRD patterns shown in Fig. 2A for comparison, revealed the differences of XRD patterns between these two single crystals. The XRD pattern of the thin-film sample matched that of the DMePDAPbI4-2 structure. A metastable polymorph does not mean it is unstable under synthetic or ambient conditions. The phase transformation between polymorphs requires $180^{\\circ}$ rotation of the alkyl chain, which is highly energetically unfavorable (Fig. 2B) (figs. S7 and S8). A wide range of thin-film growth conditions from solution all formed DMePDAPbI4-2 thin films (fig. S9). \n\nTo test our hypothesis that the reduced energy barrier from the asymmetric bulky organic cation layer could facilitate charge transport between inorganic $\\mathrm{[PbI_{6}]}$ sheets, we conducted time-resolved microwave conductivity (TRMC) measurements along the out-of-plane direction (28). In Fig. 2C, we compare the normalized TRMC results between several $n=1$ 2D perovskite thin films calibrated by their corresponding internal quantum yield of charges measured in devices. The out-of-plane transport for $\\mathrm{{DMePDAPbI_{4}}}$ (or more specifically, DMePDAP $\\mathrm{\\bI_{4}-^{\\cdot}}$ 2) is about a factor of 4 to 5 faster than that of $\\mathrm{\\BDAPbI_{4}},$ despite the slightly longer interlayer distance. Space-charge–limited current (SCLC) measurements further verified that the DMeP$\\mathrm{DAPbI_{4}}\\mathrm{-}$ 2 structure had faster out-of-plane hole transport than that of the $\\mathrm{DMePDAPbI_{4}{-}1}$ structure (fig. S10). These results confirmed the role of reducing the energy barrier for improving out-of-plane charge transport. The out-of-plane transport for the two 2D DJ structures $\\mathrm{(DMePDAPbI_{4}}$ and $\\mathrm{BDAPbI_{4}},$ ) was faster than those of the two 2D RP structures $\\mathrm{(BA_{2}P b I_{4}}$ and $\\mathrm{PEA_{2}P b I_{4}},$ ). These TRMC results were consistent with the current density-voltage $\\left(J-V\\right)$ results of PSCs on the basis of the corresponding $n=1$ 2D structures (Fig. 2D and table S4). The DMePDAPbI4-based PSC reached a PCE of $4.90\\%$ (forward scan) and $4.33\\%$ (reverse scan), which is among the highest obtained thus far for any $n=1$ 2D lead iodide–based PSCs $\\textcircled{6}$ ; the corresponding external quantum efficiency (EQE) spectrum is shown in fig. S11. \n\nThe use of 2D systems to passivate defects and enhance performance has recently been used in many polycrystalline PV technologies (29). We validated the impact of this metastable design motif with the use of $\\mathrm{{DMePDAPbI_{4}}}$ as a surface layer to improve the quality of 3D perovskite absorbers. We spin-coated the corresponding bulky organic halide salt in isopropanol (IPA) solution on top of a 3D perovskite absorber layer $\\left(6\\right)$ . Specifically, the $\\mathrm{DMePDAI_{2}/I P}/$ A solution was coated atop $\\mathrm{(FAPbI_{3})_{0.85}(M A P b I_{2}B r)_{0.1}(C s P b I_{3})_{0.05}}$ (or $\\mathrm{FA_{0.85}M A_{0.1}C s_{0.05}P b I_{2.9}B r_{0.1}})$ followed by annealing, where FA is formamidinium and MA is methylammonium. The thin-film XRD \n\nFig. 2. 2D thin-film structure, transport, and device characteristics. (A) XRD patterns of a solution-grown $\\mathsf{D M e P D A P b l_{4}}$ thin film and the powder XRD patterns (measured and calculated) from $\\mathsf{D M e P D A P b l}_{4}\\mathrm{-}1$ and $\\mathsf{D M e P D A P b l}_{4}.2$ single-crystal structures. X-ray source, Cu Ka radiation. The peak labeled with an asterisk is from the fluorine tin oxide (FTO) substrates. (B) Energy profile along the transition path between $\\mathsf{D M e P D A P b l}_{4}\\mathrm{-}1$ and DMePDAPbI4-2. (C) TRMC comparison of out-ofplane charge transport across the layers of $n=1$ 2D perovskites. (D) $J{-}V$ characteristics of PSCs based on $n=120$ perovskite thin films using a device stack of glass/FTO/compact- $\\mathrm{TiO}_{2}/$ 2D-perovskite/2,2',7,7'- Tetrakis[N,N-di(4- methoxyphenyl)amino]-9,9'- spirobifluorene (spiroOMeTAD)/Au. \n\n![](images/cf468f869fbe3d046a663141eecf70fcfc775647cb14e1fe7668c6a8749e3e59.jpg) \n\n![](images/4c43217ecaf47db5f9cb3b9f4961bb638572c763e1720f1af6d5d0e60526f3d4.jpg) \nFig. 3. Surface layer treatment. (A) Comparison of grazing incident XRD labeled with an asterisk is from the FTO substrate. X-ray source, (GIXRD) patterns of thin films of $\\mathsf{D M e P D A P b l}_{4}$ and perovskites without Cu Ka radiation. (B to E) Comparison of the XPS spectra of N1s and (control PVK) and with ${\\mathsf{D M e P D A l}}_{2}$ surface treatment $(\\mathsf{P V K}/\\mathsf{D M e P D A l}_{2})$ ). C1s for [(B) and (C)] the control and [(D) and (E)] the DMeP $\\mathsf{D A l}_{2}$ -modified (Inset) Zoom-in view of the GIXRD pattern from $7^{\\circ}$ to $10^{\\circ}$ . The peak perovskite thin film. \n\nresults suggested that the $\\mathrm{{DMePDAPbI_{4}-}^{+}}$ 2 structure formed, as evidenced by the characteristic low-angle diffraction peak, at ${\\sim}8.5^{\\circ}$ for $\\mathrm{{DMePDAPbI_{4}-}}$ 2, rather than ${\\sim}8.7^{\\circ}$ for $\\mathrm{DMePDAPbI_{4}{\\mathrm{-}}}1$ (Fig. 3A). \n\nWe also checked the 2D structures on top of three other common perovskite compositions of $\\mathrm{Cs}_{0.05}\\mathrm{FA}_{0.95}\\mathrm{PbI}_{3}.$ , $\\begin{array}{r}{(\\mathrm{FAPbI_{3}})_{0.95}(\\mathrm{MAPbBr_{3}})_{0.05},}\\end{array}$ and $\\mathrm{FAPbI_{3}}$ (fig. S12). For these compositions, the characteristics peaks at (002), (004), and (006) matched well to $\\mathrm{DMePDAPbI_{4}{-}2}$ , which were absent in the $\\mathrm{DMePDAPbI_{4}{-}1}$ spectrum. Last, the low-angle diffraction peak associated with the 2D structure from the thin-film XRD results were further confirmed with grazingincidence wide-angle x-ray scattering (GIWAXS) measurements (fig. S13). In terms of 2D surfacelayer topology and coverage, the scanning electron microscopy (SEM) measurements indicated that the treatment induced formation of a thin surface layer with small apparent grain sizes (figs. S14 and S15). The conductive-atomic force microscopy (C-AFM) measurements show that the current of the treated film is much more uniform and lower than that of the control film, which is consistent with the formation of a capping layer over the 3D perovskite layer (fig. S16). \n\nTo gain more insight into how the DMeP$\\mathrm{DAI_{2}}$ modification affects the optoelectronic properties in perovskite films, we conducted steady-state photoluminescence (PL), timeresolved photoluminescence (TRPL), and TRMC studies on these samples. The $\\mathrm{DMePDAI_{2}}$ treatment led to enhanced PL intensity (fig. \n\nS17), longer TRPL lifetime (fig. S18 and table S5), and improved TRMC mobility and lifetime (fig. S19) that were consistent with the improved surface properties (8, 30). In addition, the ultraviolet photoelectron spectroscopy (UPS) measurements showed that the 2D surface treatment improved the energetics for hole transport from the 3D perovskite to the 2D surface layer (fig. S20). \n\nThe impact of the $\\mathrm{DMePDAI_{2}}$ treatment on the perovskite surface chemistry was investigated with x-ray photoelectron spectroscopy (XPS). Normalized core levels from key elements identified on the sample surface are included in figs. S21 and S22. The spectral shapes of most core levels showed minimal change between the two samples, indicating similar bonding environments, but surface treatment caused change in the C 1s and N 1s core levels. We fit the core levels (Fig. 3, B to E) using constrained fitting procedures (summarized in tables S6 and S7). The control sample had a N 1s region whose relative peak areas were dominated by a $\\mathrm{{C=NH_{2}}^{+}}$ (FA) peak (\\~401 eV) with a small shoulder to higher binding energy $\\left(\\sim403\\mathrm{eV}\\right)$ that corresponded to $\\mathrm{C-NH_{3}}$ (MA). The $\\mathrm{{DMePDAI_{2}}}$ treatment increased the area of the $\\mathrm{C-NH_{3}}$ peak and also led to two additional peaks at a lower binding energy consistent with that of C– $\\cdot\\mathrm{NH_{2}}$ $\\ensuremath{\\mathrm{\\T}}400~\\mathrm{eV})$ and the tertiary amine in $\\mathrm{{DMePDAI_{2}}}$ $(\\sim398~\\mathrm{eV})$ . Concomitant with these changes, redistribution occurred in the features in the C 1s spectra comprising four main peaks that are consistent with primarily C–C or C–H (\\~285 eV), $\\mathrm{{N\\mathrm{{-CH}_{3}}}}$ $(\\mathrm{\\sim287{eV})}$ , $\\mathrm{{HC(NH_{2})_{2}}}$ $(\\sim289\\ \\mathrm{eV})$ , and C–O or $\\scriptstyle\\mathbf{C}=\\mathbf{O}$ bonds $(\\sim290~\\mathrm{eV})$ . The surface treatment decreased the concentration of $\\mathrm{{HC(NH_{2})_{2}}}$ bonds from FA on the surface while simultaneously increasing the amount of $\\mathrm{N}-$ $\\mathrm{CH}_{3}$ and C–C or C–H bonds. In addition, XPS revealed that surface treatment increased the amount of halide on the surface, from about 2.6 halide-to-lead ratio for the control to 3.1 for the $\\mathrm{{DMePDAI_{2}}}$ -treated film. Collectively, these results suggest that both organic and halide components of the additive incorporated into the top surface of the treated films. Undercoordinated lead can cause donor defects on the surface, resulting in downward band bending and increased recombination centers (31), so the increase in the halideto-lead ratio associated with the formation of 2D interfacial component upon surface treatment was consistent with a less defective surface. \n\nWe investigated the impact of $\\mathrm{{DMePDAI_{2}}}$ surface treatment on the PV performance by fabricating PSCs using the standard n-i-p device architecture, glass/FTO/electron transport layer (ETL)/perovskite/hole transport layer (HTL)/ Au, where ETL is $\\mathrm{TiO_{2}}$ or $\\mathrm{{SnO}_{2}}$ and HTL is spiro-OMeTAD, with more details in the supplementary materials (23). Typical cross-section SEM images of devices are shown in fig. S23. In Fig. 4A, we compare the $J{-}V$ curves of the PSCs on the basis of triple-cation–mixedhalide $\\mathrm{FA_{0.85}M A_{0.1}C s_{0.05}P b I_{2.9}B r_{0.1}}$ without and with $\\mathrm{DMePDAI_{2}}$ treatment under simulated $\\scriptstyle100-{\\mathrm{mW}}/{\\mathrm{cm}}^{2}$ air mass coefficient (AM) $1.5\\mathrm{G}$ illumination (Table 1). With the surface treatment, the device PCE increased from about 20.9 to $24.0\\%$ from forward scan and from 20.4 to $23.7\\%$ from reverse scan. The PCE improvement is also consistent with a better perovskite-HTL junction on the basis of the cross-sectional Kelvin probe force microscopy (KPFM) measurements (fig. S24) (32). The optimum concentration for DMeP $\\mathrm{DAI_{2}}$ -surface treatment was found at $0.5\\mathrm{mg/mL}$ (fig. S25). \n\n![](images/30390fbbae932dbe188c7f80e0e8a44016f6c4c0bcbdcc32f8211167572c71c6.jpg) \nFig. 4. Device characteristics. (A to C) $J{-}V$ characteristics of PSCs based on different perovskite compositions. (A) FA0.85MA0.1Cs0.05PbI2.9Br0.1. (B) $\\mathsf{F A}_{0.97}\\mathsf{M A}_{0.03}\\mathsf{P b}\\mathsf{l}_{2.91}\\mathsf{B r}_{0.09}$ . (C) $\\mathsf{M A P b l}_{3}$ . (Insets) SPOs of the corresponding devices. (D) Operation ISOS-L-1 stability (maximum \npower point tracking, in ${\\sf N}_{2}$ , continuous one-sun illumination at ${\\sim}40^{\\circ}\\mathrm{C}$ ) of unencapsulated PSC based on $\\mathsf{F A}_{0.85}\\mathsf{M A}_{0.1}\\mathsf{C s}_{0.05}\\mathsf{P b}\\mathsf{l}_{2.9}\\mathsf{B r}_{0.1}$ . The initial PCE was $20.5\\%$ for the control and $23.1\\%$ for the ${\\mathsf{D M e P D A l}}_{2}$ -treated device. \n\nIn addition to the $\\mathrm{FA_{0.85}M A_{0.1}C s_{0.05}P b I_{2.9}B r_{0.1}}$ perovskite composition, we also examined the impact of $\\mathrm{{DMePDAI_{2}}}$ surface treatment on PSCs on the basis of double-cation–mixedhalide $(\\mathrm{FA}_{0.97}\\mathrm{MA}_{0.03}\\mathrm{PbI}_{2.91}\\mathrm{Br}_{0.09})$ and singlecation–single-halide $\\mathrm{(MAPbI_{3},}$ ) using ETL of $\\mathrm{{SnO}_{2}}$ and $\\mathrm{TiO_{2}}$ , respectively, and found PCE improvements for both compositions (Fig. 4, B and C). Noteworthy for PSCs based on $\\mathrm{FA_{0.97}M A_{0.03}P b I_{2.91}B r_{0.09}}$ , the PCE was improved from 22.0 to $24.7\\%$ from forward scan and from 21.8 to $24.5\\%$ from reverse scan, with shortcircuit current density $\\mathrm{(\\itJ_{\\mathrm{sc}})>25\\mathrm{mA/cm^{2}}}$ , which is in agreement with the EQE spectrum (fig. S26). For all three perovskite compositions, the stabilized power outputs (SPOs) for PSCs based on the control and DMePDAI2-modified perovskite thin films matched well with the J–V measurements (Fig. 4, A to C, insets, and Table 1). The PCE improvement for all three perovskite compositions was reproducible on the basis of the statistical comparison (fig. S27). The devices with this treatment also exhibited higher PCE than that of devices based on other surface treatments with similar length of bulky organic salts for either RP or DJ 2D perovskites (fig. S28). \n\nLast, we checked the operation stability of unencapsulated $\\mathrm{FA_{0.85}M A_{0.1}C s_{0.05}P b I_{2.9}B r_{0.1}}$ –based PSCs using maximum power point (MPP) tracking at ${\\sim}40^{\\circ}\\mathrm{C}$ in $\\mathrm{{N_{2}}}$ , following the ISOS-L-1 stability protocol (33). The $\\mathrm{{DMePDAI_{2}}}$ -modified PSC (Fig. 4D) showed only $10\\%$ relative efficiency drop after 1000 hours of continuous operation, whereas the PCE of the control device decreased by ${\\sim}43\\%$ . The stability improvement with $\\mathrm{{DMePDAI_{2}}}$ surface treatment was also observed when the devices were tested at high-moisture $585\\%$ relative humidity) or high-temperature $(85^{\\circ}\\mathrm{C})$ conditions (figs. S29 and S30). These results suggest that the $\\mathrm{{DMePDAI_{2}}}$ -modification to form a 2D DJ phase surface layer is a general way to improve PSC performance. Our use of the metastable 2D DJ structure through hydrogen bonding tuning based on asymmetric bulky organic molecules represents a promising chemical design element for perovskite interfacial engineering to enhance PSC efficiency and stability. \n\n# REFERENCES AND NOTES \n\n1. National Renewable Energy Laboratory, Best research-cell efficiency chart (August, 2020); www.nrel.gov/pv/cellefficiency.html. \n2. D. Bi et al., Nat. Energy 1, 16142 (2016). \n3. X. Zheng et al., Nat. Energy 2, 17102 (2017). \n4. F. Zhang et al., Adv. Mater. 29, 1606806 (2017). \n5. X. Li et al., Nat. Chem. 7, 703–711 (2015). \n6. F. Zhang et al., Energy Environ. Sci. 13, 1154–1186 (2020). \n7. E. H. Jung et al., Nature 567, 511–515 (2019). \n8. H. Min et al., Science 366, 749–753 (2019). \n9. L. Liang, H. Luo, J. Hu, H. Li, P. Gao, Adv. Energy Mater. 10, 2000197 (2020). \n10. Y.-W. Jang et al., Nat. Energy 6, 63–71 (2021). \n11. J. Xue et al., Science 371, 636–640 (2021). \n12. D. Thrithamarassery Gangadharan, D. Ma, Energy Environ. Sci. 12, 2860–2889 (2019). \n13. E. Shi et al., Nature 580, 614–620 (2020). \n14. Y. Gao et al., Nat. Chem. 11, 1151–1157 (2019). \n15. S. Ahmad et al., Joule 3, 794–806 (2019). \n16. L. Mao et al., J. Am. Chem. Soc. 140, 3775–3783 (2018). \n17. Y. Lv et al., J. Mater. Chem. A Mater. Energy Sustain. 8, 10283–10290 (2020). \n18. X. Jiang et al., Nano Energy 75, 104892 (2020). \n19. X. Li, J. M. Hoffman, M. G. Kanatzidis, Chem. Rev. 121, 2230–2291 (2021). \n20. G. Miessler, P. Fischer, D. Tarr, Inorganic Chemistry (Prentice Hall, ed. 5, 2014). \n21. C. Ma, D. Shen, T.-W. Ng, M.-F. Lo, C.-S. Lee, Adv. Mater. 30, 1800710 (2018). \n22. T. Yu, L. Zhang, J. Shen, Y. Fu, Y. Fu, Dalton Trans. 43, 13115–13121 (2014). \n23. F. Zhang et al., Chem 7, 774–785 (2021). \n24. S. Silver, S. Xun, H. Li, J.-L. Brédas, A. Kahn, Adv. Energy Mater. 10, 1903900 (2020). \n25. W. Zhao et al., J. Mater. Chem. A Mater. Energy Sustain. 8, 9919–9926 (2020). \n26. A. V. Krukau, O. A. Vydrov, A. F. Izmaylov, G. E. Scuseria, J. Chem. Phys. 125, 224106 (2006). \n27. S. Grimme, J. Antony, S. Ehrlich, H. Krieg, J. Chem. Phys. 132, 154104 (2010). \n28. F. Zhang et al., J. Am. Chem. Soc. 141, 5972–5979 (2019). \n29. D. L. McGott et al., Joule 5, 1057–1073 (2021). \n30. H. Zhu et al., J. Am. Chem. Soc. 143, 3231–3237 (2021). \n31. S. P. Dunfield et al., Adv. Energy Mater. 10, 1904054 (2020). \n32. Y. Hou et al., Science 367, 1135–1140 (2020). \n33. M. V. Khenkin et al., Nat. Energy 5, 35–49 (2020). \n\n# ACKNOWLEDGMENTS \n\nFunding: The work was partially supported by the US Department of Energy under contract DE-AC36-08GO28308 with Alliance for Sustainable Energy, the manager and operator of the National Renewable Energy Laboratory. The authors acknowledge the support on 2D structure design, first-principle calculations, synthesis of $\\mathsf{P D A l}_{2}$ and $\\mathsf{D M e P D A l}_{2}$ single-crystal synthesis and analysis, and optoelectronic characterizations (such as TRPL and TRMC) from the Center for Hybrid Organic-Inorganic Semiconductors for Energy (CHOISE), an Energy Frontier Research Center funded by the Office of Basic Energy Sciences, Office of Science within the US Department of Energy. The authors also acknowledge the support on device fabrication and characterization and general thin-film perovskite characterizations from the De-Risking Halide Perovskite Solar Cells program of the \n\nNational Center for Photovoltaics, and the support on $\\mathsf{S n O}_{2}$ ETL synthesis along with the corresponding device fabrication and characterization from DE-FOA-0002064 and award DEEE0008790, funded by the US Department of Energy, Office of Energy Efficiency and Renewable Energy, Solar Energy Technologies Office. Portions of this research were carried out at the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under contract DE-AC02-76SF00515. L.D.H. and E.L.R. acknowledge funding support on UPS characterization and analysis from the Office of Naval Research under award N00014-20-1-2440. X.Z. and Y.-L.L. acknowledge support on SCLC characterization and analysis from the National Science Foundation, under grant CMMI-1824674, and funding from the Princeton Center for Complex Materials, a National Science Foundation (NSF)–MRSEC program (DMR1420541). The DFT calculations were performed by using computational resources sponsored by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory and resources of the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under contract DE-AC02-05CH11231. The views expressed in the article do not necessarily represent the views of the US Department of Energy or the US government. Author contributions: K.Z. and F.Z. designed the experiment. F.Z. and S.Y.P. carried out the experimental study on device fabrication and characterizations. C.Y. conducted DFT calculations, with help from X.W., under the supervision of Y.Y.; H.L. synthesized ${\\mathsf{P D A l}}_{2}$ , $\\mathsf{D M e P D A l}_{2}$ , and the corresponding single crystals. S.P. tested and analyzed the structures of single crystals. B.W.L. performed the TRMC and analyzed the TRMC data and some corresponding single crystals data. C.X. performed the AFM, CAFM, and KPFM tests. S.P.D. conducted the XPS and analyzed the data, with the guidance from G.T. and J.J.B.; S.U., L.T.S., and K.H.S. performed the GIWAX and analyzed the data, with help from L.E.M.; X.Z. performed the SCLC measurement and analysis, under the supervision of Y.-L.L.; L.D.H. conducted UPS and analyzed the data, with the guidance from E.L.R.; X.C. performed the TRPL and analyzed the data, under the supervision of M.C.B.; F.Z. performed SEM and XRD measurements. J.J.B performed supplemental XRD measurements. F.Z., Y.Y., B.W.L, and K.Z. wrote the first draft of the paper. All authors discussed the results and contributed to the revisions of the manuscript. K.Z. supervised the project. Competing interests: F.Z. and K.Z. are inventors on a provisional patent (US patent application number 63/197,652) related to the subject matter of this manuscript. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. The accession numbers for the crystal structure cif. files reported in this paper are CCDC 2048509 $[P D A P b\\vert_{4}]_{15}$ •[PDAI2]), CCDC 2048508 (BDAPbI4), and CCDC 2048510 (DMePDAPb $\\mathsf{I}_{4}{-}1$ ), which are archived at the Cambridge Crystallographic Data Centre. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abj2637 \nMaterials and Methods \nFigs. S1 to S30 \nTables S1 to S7 \nReferences (34–44) \n\n30 April 2021; resubmitted 20 August 2021 \nAccepted 12 November 2021 \nPublished online 25 November 2021 \n10.1126/science.abj2637 " + }, + { + "id": "10.1038_s41566-022-01083-y", + "DOI": "10.1038/s41566-022-01083-y", + "DOI Link": "http://dx.doi.org/10.1038/s41566-022-01083-y", + "Relative Dir Path": "mds/10.1038_s41566-022-01083-y", + "Article Title": "Efficient selenium-integrated TADF OLEDs with reduced roll-off", + "Authors": "Hu, YX; Miao, JS; Hua, T; Huang, ZY; Qi, YY; Zou, Y; Qiu, YT; Xia, H; Liu, H; Cao, XS; Yang, CL", + "Source Title": "NATURE PHOTONICS", + "Abstract": "Organic light emitters based on multiresonullce-induced thermally activated delayed fluorescent materials have great potential for realizing efficient, narrowband organic light-emitting diodes (OLEDs). However, at high brightness operation, efficiency roll-off attributed to the slow reverse intersystem crossing (RISC) process hinders the use of multiresonullce-induced thermally activated delayed fluorescent materials in practical applications. Here we report a heavy-atom incorporating emitter, BNSeSe, which is based on a selenium-integrated boron-nitrogen skeleton and exhibits 100% photoluminescence quantum yield and a high RISC rate (k(RISC)) of 2.0 x 10(6) s(-1). The corresponding green OLEDs exhibit excellent external quantum efficiencies of up to 36.8% and ultra-low roll-off character at high brightnesses (with very small roll-off values of 2.8% and 14.9% at 1,000 cd m(-2) and 10,000 cd m(-2), respectively). Furthermore, the outstanding capability to harvest triplet excitons also enables BNSeSe to be a superior sensitizer for a hyperfluorescence OLED, which shows state-of-the-art performance with a high excellent external quantum efficiency of 40.5%, power efficiency beyond 200 lm W-1, and luminullce close to 20,0000 cd m(-2). Green OLEDs based on BNSeSe offer high operational efficiency and reduced efficiency roll-off.", + "Times Cited, WoS Core": 319, + "Times Cited, All Databases": 329, + "Publication Year": 2022, + "Research Areas": "Optics; Physics", + "UT (Unique WOS ID)": "WOS:000867521100001", + "Markdown": "# nature photonics \n\n# Efficient selenium-integrated TADF OLEDs with reduced roll-off \n\nReceived: 6 December 2021 \n\nAccepted: 31 August 2022 \n\nPublished online: 13 October 2022 \n\n# Check for updates \n\nYu Xuan Hu1,2,3, Jingsheng Miao1,3, Tao Hua1, Zhongyan Huang    1, Yanyu Qi1, Yang Zou1, Yuntao Qiu1, Han Xia1, He Liu1, Xiaosong Cao1 and Chuluo Yang    1 \n\nOrganic light emitters based on multiresonance-induced thermally activated delayed fluorescent materials have great potential for realizing efficient, narrowband organic light-emitting diodes (OLEDs). However, at high brightness operation, efficiency roll-off attributed to the slow reverse intersystem crossing (RISC) process hinders the use of multiresonance-induced thermally activated delayed fluorescent materials in practical applications. Here we report a heavy-atom incorporating emitter, BNSeSe, which is based on a selenium-integrated boron–nitrogen skeleton and exhibits $100\\%$ photoluminescence quantum yield and a high RISC rate $(k_{\\mathrm{RISC}})$ of $2.0\\times10^{6}{\\sf s}^{-1}$ . The corresponding green OLEDs exhibit excellent external quantum efficiencies of up to $36.8\\%$ and ultra-low roll-off character at high brightnesses (with very small roll-off values of $2.8\\%$ and $14.9\\%$ at 1,000 cd $\\mathfrak{m}^{-2}$ and 1 $\\mathsf{I}0,000\\mathsf{c d}\\mathsf{m}^{-2}$ , respectively). Furthermore, the outstanding capability to harvest triplet excitons also enables BNSeSe to be a superior sensitizer for a hyperfluorescence OLED, which shows state-of-the-art performance with a high excellent external quantum efficiency of $40.5\\%$ , power efficiency beyond $200\\mathsf{I m}\\mathsf{W}^{-1}$ , and luminance close to 20,0000 cd $\\mathfrak{m}^{-2}$ . \n\nOrganic light-emitting diodes (OLEDs) with simultaneously high efficiency and narrowband emission become increasingly important to the demand for energy-saving and high-quality displays. Thanks to the pioneering work by Hatakeyama and colleagues1,2, multiresonance thermally activated delayed fluorescent (TADF) emitters have emerged with a narrowband emission that could fulfill such requirements. A high external quantum efficiency (EQE) of up to $34\\%$ and an electroluminescence with a full-width at half-maximum (FWHM) of $18\\mathsf{n m}$ demonstrated their great potential towards practical applications3. However, multiresonance-induced thermally activated delayed fluorescene (MR-TADF) emitters usually possess long delay lifetimes of several tens of microseconds, which usually lead to large efficiency roll-off at high brightnesses, impeding their commercialization4–10. \n\nTo reduce efficiency roll-off, both singlet and triplet excitons should be converted expeditiously. The intrinsic large Frank–Condon overlap integral ensures MR-TADF emitters with a fast radiative rate of singlet excitons. Although the recycle of triplet excitons depends on the reverse intersystem crossing (RISC) channel, and thus the rate of reversed intersystem crossing $(k_{\\mathrm{RISC}})$ becomes the key factor to realize low efficiency roll-off11–14. According to Fermi’s golden rule, $k_{\\mathrm{RISC}}$ between two states is described as15–18 \n\n$$\nk_{\\mathrm{RISC}}\\propto\\left|\\left\\langle\\mathsf{S}|\\widehat{H}_{\\mathrm{SOC}}|\\mathsf{T}\\right\\rangle\\right|^{2}\\exp\\left(\\frac{-\\Delta E_{\\mathrm{SI}}}{k_{\\mathrm{B}}\\mathsf{T}}\\right)\n$$ \n\nwhere ${}$ is the spin–orbit coupling (SOC) matrix element, $\\Delta E_{\\mathrm{{sT}}}$ is the energy difference between the corresponding states, $k_{\\mathrm{{B}}}$ is the Boltzmann constant and T is the temperature. To enhance $k_{\\mathrm{{RISC}}}$ , one of the practicable strategies is narrowing $\\Delta E_{\\mathrm{{sT}}}$ to provide a smaller energy gap, which benefits the up-conversion process from the low-energy ${\\sf T}_{1}$ state to the high-energy $\\mathsf{S}_{1}$ state15,19. Generally, $\\Delta E_{\\mathrm{{sT}}}$ can be reduced by minimizing the overlap between the highest-occupied molecular orbital (HOMO) and lowest-unoccupied molecular orbital (LUMO), which are already atomically separated in MR-TADF emitters. Such a characteristic leaves little room to reduce $\\Delta E_{\\mathrm{sr}};$ thus, enhancing SOC could be a more practical strategy to facilitate RISC. The heavy-atom effect has been verified to be an effective method to enhance SOC in phosphorescent emitters20–23. In our previous work, sulfur was introduced into the MR-TADF system, which shortens the lifetime of delayed fluorescence $(\\tau_{\\mathrm{d}})$ and smooths the efficiency roll-off compared with its oxygen-substituted analogue, but the device performance is still much less than satisfactory24. Aside from optimizing from the molecular level, an alternative TADF-sensitizing strategy—also known as hyperfluorescence—has proven effective to realize OLEDs with excellent performance, where a TADF emitter is used as a sensitizer to recycle the triplet excitons and then transfer the singlet excitons to the terminal emitter25–27. The long-range Förster resonance energy transfer (FRET) interaction benefits fast consumption of triplet excitons to suppress exciton annihilations such as triplet–triplet annihilation, triplet–polaron annihilation and singlet–triplet annihilation28–33. The core of this mechanism lies on the fast harvesting of triplet excitons via the TADF sensitizer, which also demands a fast RISC process27,34,35. In this context we are driven to develop MR-TADF emitters with fast RISC, which not only facilitates their emissive properties as emitters but also ensures that they are excellent sensitizers for highly efficient hyperfluorescence OLEDs. \n\n# Results \n\n# Molecular design and theoretical calculations \n\nThe molecules designed in this contribution are presented in Fig. 1a. A conventional boron–nitrogen skeleton was chosen for evaluation due to their high photoluminescence quantum yield $(\\phi_{\\mathrm{PL}})$ and narrowband emission. Selenium $(Z_{\\mathsf{N}}=34)$ is inserted to enhance SOC in BNSSe and BNSeSe. The asymmetric BNSSe was developed to establish a comparison and comprehend the structure–property relationship. Their oxygen and sulfur counterparts (2PXZBN, 2PTZBN, respectively) were also prepared to fully validate our molecular design. \n\nWe first used density functional theory (DFT) under the representative B3LYP/6-31G(d,p) set to optimize the ground-state geometries of the four molecules. All four show well-separated HOMO and LUMO distributions. The more twisted structures (see Supplementary Fig. 11) of BNSSe and BNSeSe (compared with 2PXZBN and 2PTZBN) may induce less dense packing to avoid inter-chromophore interactions. According to the time-dependent DFT analysis, high oscillator strengths beyond 0.2 and relatively small $\\Delta E_{\\mathrm{sr}}$ values are acquired in these four emitters, implying a fast radiative decay and potential TADF activity. To more accurately model the excited-state energies by considering electron correlation in the form of double excitations, suitably higher-level SCS-CC2 and ADC(2) calculations were conducted, which provided $\\Delta E_{\\mathrm{sr}}$ values of only ${\\mathsf{\\Pi}}^{-0.12\\mathsf{e V}}$ for BNSSe and BNSeSe (Supplementary Table 2). To evaluate the internal heavy atom effect, their SOC matrix elements $\\mathbf{S}_{1}{-}\\mathbf{T}_{1},\\mathbf{S}_{1}{-}\\mathbf{T}_{2}$ and ${\\sf S}_{1}{-}{\\sf T}_{3}$ were further evaluated using $\\mathsf{P y S O C}^{36}$ . As depicted in Fig. 1a, both 2PXZBN and 2PTZBN show small SOC values; they exhibit very tiny SOCs between $\\mathsf{S}_{1}$ and ${\\sf T}_{1}$ $({<}\\mathsf{S}_{1}|\\hat{H}_{\\mathrm{Soc}}|\\mathsf{T}_{1}{>}=0.079$ and $0.082\\mathrm{cm}^{-1}$ , respectively). By sharp contrast, substantial enhancements are realized in selenium-containing BNSSe and BNSeSe $(<\\mathsf{S}_{1}|\\hat{H}_{\\mathrm{S0C}}|\\mathsf{T}_{1}>=1.580$ and $1.431\\mathrm{cm}^{-1}$ , respectively—nearly 20-times higher than that of 2PXZBN). Spin–orbit couplings between $S_{1}$ and ${\\sf T}_{n}$ ( $\\scriptstyle{\\overset{\\cdot}{n}=2}$ or 3) for BNSSe and BNSeSe are also much larger than those for 2PXZBN and 2PTZBN (for example, $<\\mathsf{S}_{1}|\\hat{H}_{\\mathrm{Soc}}|\\mathsf{T}_{2}>\\mathrm{of}2.060\\mathrm{cm}^{-1}$ and ${}$ of $0.905\\mathrm{cm}^{-1}$ are obtained for BNSSe). Better yet, the values of ${}$ and ${}$ for BNSeSe increase to 2.840 and $2.110\\mathsf{c m}^{-1}$ , respectively, which are higher than those of its sulfur analogue (2PTZBN, $<\\mathsf{S}_{1}|\\hat{H}_{\\mathrm{soc}}|\\mathsf{T}_{2}>=1.510\\mathsf{c m}^{-1}z$ and $<\\mathsf{S}_{1}|\\hat{H}_{\\mathrm{soc}}|\\mathsf{T}_{3}>=1.112\\mathrm{cm}^{-1})$ . These results theoretically support our molecular design, suggesting that the introduction of selenium may immensely promote SOC and in turn accelerate the RISC processes. \n\nCrystallographic and photophysical properties As shown in the crystal structures of BNSSe and BNSeSe, molecules exhibit rigid configurations, which are beneficial for suppressing non-radiative transitions (Supplementary Fig. 12 and 13). Due to the folded configurations of phenothiazine and phenoselenazine units, molecules in BNSSe and BNSeSe crystals are twisted and stacked loosely. The photophysical properties of BNSSe and BNSeSe—including absorption, fluorescence at 298 K and phosphorescence spectra at 77 K—were measured in toluene, as collected in Fig. 2a and Supplementary Table 6. BNSSe and BNSeSe show intense absorption bands at $469\\mathsf{n m}$ and $467\\mathsf{n m}$ , respectively, which refer to intramolecular charge transfer processes. Both compounds exhibit green emission, with fluorescence spectra peaks at $505\\mathsf{n m}$ and $502\\mathsf{n m}$ for BNSSe and BNSeSe, respectively. To evaluate the $\\Delta E_{\\mathrm{{sT}}}$ values of these materials, the lowest singlet and triplet excited-state energies were estimated from the onset of fluorescence and phosphorescence bands at 77 K. BNSSe and BNSeSe exhibit identical $\\Delta E_{\\mathrm{{sr}}}$ values at 0.17 eV, in good agreement with the calculated values by SCS-CC2 and ADC(2) (see above). These small energy gaps are beneficial for RISC from triplet excited states to the singlet excited state. The prompt fluorescence $(\\tau_{\\mathrm{PF}})$ and delayed fluorescence $(\\tau_{\\mathrm{DF}})$ lifetimes of BNSSe are 1.6 ns and $2.1\\upmu\\up s$ , respectively, in oxygen-free toluene, which are distinctly smaller than those of 2PXZBN and 2PTZBN. Moreover, BNSeSe possesses a further decreased $\\tau_{\\mathrm{PF}}$ of 0.76 ns and $\\tau_{\\mathrm{DF}}\\mathbf{of}1.0\\upmu\\mathrm{s}$ , which are the shortest of all reported MR-TADF emitters. Such short delayed fluorescence lifetimes are beneficial for utilizing excitons and suppressing efficiency roll-off. To gain a deeper insight into the emission in the solid state, the photophysical properties of $1-\\mathsf{w t\\%}$ -doped films of 2PXZBN, 2PTZBN, BNSSe and BNSeSe were recorded (see Table 1) in 1,3-dihydro-1,1-dimethyl-3-(3-(4,6-d iphenyl-1,3,5-triazin-2-yl)phenyl)indeno-[2,1-b]carbazole (DMIC-TRZ), a universal bipolar host with a hole mobility of $1.03\\times10^{-4}\\mathsf{c m}^{2}\\mathsf{V}^{-1}\\mathsf{s}^{-1}$ and an electron mobility of $7.35\\times10^{-4}\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}$ at an electric field of $1.2\\times10^{6}\\mathsf{V}\\mathsf{c m}^{-1}$ (ref. 37). As depicted in Fig. 2c, all four doped films exhibit green emission with slight bathochromic shifts with respect to their toluene solution. Photoluminescence decay curves of those films are shown in Fig. 2d. Both $\\tau_{\\mathrm{{PF}}}$ and $\\tau_{\\mathrm{DF}}$ drop in the sequence: 2PXZ $\\mathsf{B N}>2\\mathsf{P T Z B N}>\\mathsf{B N S S e}>\\mathsf{B N S e S}$ e. Furthermore, $\\phi_{\\mathrm{{PL}}}$ values of 2PXZBN, 2PTZBN, BNSSe and BNSeSe were measured to be $71\\%$ , $91\\%$ , $99\\%$ and $100\\%$ , respectively, with an obvious escalating trend as $\\tau_{\\mathrm{DF}}$ shortened. The improved $\\phi_{\\mathrm{{PL}}}$ values of the 1-wt%-DMIC-TRZ-doped BNSSe and BNSeSe films are also associated with their large torsional angles to enlarge intermolecular distance and suppress aggregation-caused quenching. The radiative decay rate constants of fluorescence $(k_{\\mathrm{r},\\mathrm{S}})$ , intersystem crossing $(k_{\\mathrm{ISC}})$ and $k_{\\mathrm{RISC}}$ are further analysed—using a method provided in the literature—on the basis of these lifetimes and quantum yields. With the increasing number of selenium atoms, $k_{\\mathrm{RISC}}$ is greatly enhanced from $6.0\\times10^{5}{\\bf s}^{-1}$ for BNSSe to $2.0\\times10^{6}\\mathsf{s}^{-1}$ for BNSeSe, noting that the latter is, to the best of our knowledge, the largest value among all MR-TADF emitters (typically in the order of $10^{3}–10^{5}s^{-1}$ ; see Supplementary Table 10). Such a tremendous enhancement to $k_{\\mathrm{RISC}}$ is in line with the enhanced SOCs. \n\n# OLED devices \n\nGiven the prominent photoluminescent properties of 2PXZBN, 2PTZBN, BNSSe and BNSeSe, we fabricated and evaluated OLED devices A–D, employing them as emitters, respectively, with the following device configuration: indium tin oxide (ITO)/1,4,5,8,9,11-hexaazatriphenylene hexacarbonitrile (HAT-CN, $5\\mathsf{n m}$ )/1,1-bis[(di-4-tolylamino)phenyl] cyclohexane (TAPC, $30\\mathrm{nm}$ )/tris(4-carbazolyl-9-ylphenyl)amine (TCTA, $15\\mathsf{n m}$ )/3,3-di( $9H\\cdot$ carbazol-9-yl)biphenyl (mCBP, $10\\:\\mathrm{nm};$ )/ EML $(1\\mathsf{w t\\%}$ emitter in DMIC-TRZ, $50\\mathrm{nm};$ )/(1,3,5-triazine-2,4,6-triyl) tris(benzene-3,1-diyl)tris(diphenylphosphine oxide) (POT2T, \n\n![](images/6aa4dc7d6a133abce9b9fa030cb7739563f3f47ae12b023065b06be2e6a80cb0.jpg) \nFig. 1 | Molecular design. a, Molecular structures and the SOC constants of 2PXZBN, 2PTZBN, BNSSe and BNSeSe. b,The DFT-calculated HOMO and LUMO distributions, energy levels, energy band gaps and oscillator strengths (f) of 2PXZBN, 2PTZBN, BNSSe and BNSeSe. \n\n$20\\mathsf{n m}\\cdot$ )/1-(4-(10-([1,1′-biphenyl]−4-yl)anthracen-9-yl)phenyl)-2-ethyl1H-benzo[d]imidazole (ANT-BIZ, $30\\mathrm{nm},$ /8-hydroxyquinolinato lithium (Liq, 2 nm)/alumina (Al, ${\\bf100n m},$ ). All device data are summarized in Table 2 and Supplementary Table 8, and selectively presented in Fig. 3. Devices A–D all exhibit green electroluminescence peaks at 517, 520, 515 and 512 nm, respectively. Narrowband emission with FWMHs of $50\\mathrm{nm}$ and 48 nm were recorded for devices C and D, respectively. Attributed to the host with dipole charge transport ability, all devices exhibit low turn-on voltages below $2.5\\mathsf{V}$ and extremely high luminances of over 100,000 cd $\\mathfrak{m}^{-2}$ . All devices exhibit excellent performance, including high maximum EQEs $(\\mathtt{E Q E}_{\\operatorname*{max}})$ , power efficiencies $(\\mathrm{PE}_{\\operatorname*{max}})$ and current efficiencies $\\langle\\mathrm{CE}_{\\mathrm{max}}\\rangle$ . As shown in Fig. 3c–f, $\\mathsf{E Q E}_{\\operatorname*{max}}$ values of $30.7\\%$ , $34.6\\%$ , $35.7\\%$ and $36.8\\%$ were observed for devices A−D, respectively. The outstanding $\\mathtt{E Q E}_{\\operatorname*{max}}$ of device D is attributed to a concomitant high $\\phi_{\\mathrm{{PL}}}({\\sim}100\\%)$ of EML and horizontal orientation factor $(\\theta_{\\parallel}=89\\%$ ; Supplementary Fig. 21a), and matches well with the theoretically predicted efficiency by using optical simulation (Supplementary Fig. 24a and Supplementary Table 9). Devices A–D exhibit $\\mathsf{P E}_{\\operatorname*{max}}$ values of 123.4, 157.7, 156.2 and $146.3\\mathrm{lm}\\mathrm{W}^{\\mathrm{-1}}.$ , respectively, and their $\\mathbf{CE}_{\\operatorname*{max}}$ values are as high as 108.8, 124.9, 124.2 and 121.0 cd $\\mathbf{A}^{-1}$ , respectively. To the best of our knowledge, the PEs and CEs of devices based on 2PTZBN, BNSSe and BNSeSe are higher than almost all reported TADF OLEDs. Moreover, devices C and especially D exhibit distinctly reduced efficiency roll-off compared with devices A and B, which suggests that the stronger SOCs between $\\mathsf{S}_{1}$ and ${\\sf T}_{n}\\left(n=1,2,3\\right)$ in BNSSe and BNSeSe suppress exciton annihilation more efficiently under high current densities. It is worth mentioning that the efficiency roll-off of device D is much smaller than those observed in the latest narrowband TADF OLEDs7,9,38–41; the EQEs of device D remain $34\\%$ at 1,000 cd $\\mathfrak{m}^{-2}$ , $26.9\\%$ at 5,000 cd $\\mathfrak{m}^{-2}$ and $21.9\\%$ at 10,000 cd $\\mathfrak{m}^{-2}$ . We assume that the very strong SOC and subsequent high $k_{\\mathrm{{RISC}}}$ value suppress the triplet-involved annihilation processes in the device (see Supplementary Table 10). The operational lifetimes of devices A−D were preliminarily measured at an initial luminance of $1,000{\\mathsf{c d}}{\\mathsf{m}}^{-2}$ . Device A shows an $\\mathsf{L T}_{50}$ (the time to reach $50\\%$ of the initial luminance) of $158\\mathsf{h}$ , whereas devices B, C and D exhibit shorter $\\ensuremath{\\mathrm{LT}}_{50}$ values of 5.6, 4.8 and $4.1\\mathsf{h}$ , respectively (Supplementary Fig. 25). \n\n![](images/8c9f977f46fc4aa43d6470ada9083a4e5443ac9548f3f4f934ddbade633987ff.jpg) \nFig. 2 | Photophysical properties. a, Ultraviolet–visbible absorption (Abs), fluorescence (FL) (298 K) and phosphorescence (Ph) spectra (77 K) of BNSSe and BNSeSe in toluene solution. b, Transient photoluminescence decay curves of BNSSe and BNSeSe in toluene solution before and after argon gas bubbling for \n30 min. c, Photoluminescence spectra of 2PXZBN, 2PTZBN, BNSSe and BNSeSe in 1-wt%-DMIC-TRZ-doped film. d, Transient photoluminescence decay curves of 2PXZBN, 2PTZBN, BNSSe and BNSeSe in 1-wt%-DMIC-TRZ-doped film. \n\nTable 1 | Physical data and kinetic parameters of 2PXZBN, 2PTZBN, BNSSe and BNSeSe in 1 wt% DMIC-TRZ doped film \n\n\n
入pL (nm)s, (eV)T, (ev)AEst (eV)ΦPL (%)ΦTADF (%)TpF(ns)TDF (us)k,s (10's-1)knr,s (10's-1)kisc (108s-1)KRisc (106s-1)
2PXZBN5232.542.390.1571285.238.18.23.40.750.043
2PTZBN5252.552.420.1391685.120.74.50.451.50.19
BNSSe5202.562.440.1299863.012.74.30.0432.90.60
BNSeSe5142.582.440.14100951.99.92.60.00264.92.0
\n\nDue to the short delayed fluorescence lifetime, high $\\phi_{\\mathrm{{PL}}}$ and outstanding electroluminescence performance, we anticipate BNSeSe should be a promising TADF sensitizer candidate for a low-energy emitter. To prove it, one yellow emission MR-TADF emitter ${\\mathsf{B N}}3^{42}$ was chosen as the terminal emitter, and the device (E) was fabricated with the following device configuration: ITO/HAT-CN (5 nm)/TAPC $(30\\mathrm{nm})/$ TCTA $(15\\mathrm{nm})/\\mathrm{mCBP}$ $(10\\mathsf{n m})$ /EML $(1\\mathrm{wt\\%}$ BN3 and $25\\mathrm{wt\\%}$ BNSeSe in DMIC-TRZ, $50\\mathrm{nm},$ )/POT2T ( $20\\mathsf{n m},$ )/ANT-BIZ $30\\mathrm{nm}$ )/Liq $(2\\:\\mathrm{nm})/\\mathsf{A l}$ $(100\\mathsf{n m})$ . For comparison, sensitizer-free device F was also fabricated with $1w t\\%$ BN3 doped in DMIC-TRZ as EML. Compared with device F, the \n\nTable 2 | Summary performances for devices A−H \n\n\n
Devices (emitter)CE (cd A-1)PE (lm W-1)EQE (%)
Max (average)1,000, cd m-210,000 cd m-2Max (average)1,000, cd m-210,000 cd m-²Max (average)1,000, cd m-²5,000 cd m-210,000 cd m-2
A (2PXZBN)108.8 (107.1±1.0)75.140.9123.4 (120.3±1.3)55.820.730.7 (29.95±0.30)24.015.811.6
B (2PTZBN)124.9 (121.6±1.7)94.455.1157.7 (154.8 ± 4.1)79.131.934.6 (33.83±0.83)29.520.115.4
C (BNSSe)124.2 (121.2±1.8)110.864.5156.2 (152.0 ±3.1)90.240.435.7 (35.02±0.44)32.024.018.9
D (BNSeSe)121.0 (119.7±0.8)111.070.8146.3 (147.6±2.5)90.145.436.8 (36.40±0.22)34.026.921.9
E (HF BN3)164.5 (162.4±2.0)131.394.7205.8 (197.7±8.7)112.256.940.5 (40.03±0.40)32.426.123.3
F (BN3)152.2 (147.6±3.5)82.238.1170.7 (165.6±3.9)63.518.238.7 (36.94±1.03)20.411.99.4
G (HF DtCzB-DPTRZ)161.6 (154.4±4.6)139.998.4181.3 (174.2±6.6)114.854.139.6 (37.85±0.99)34.527.824.3
H (DtCzB-DPTRZ)119.3 (108.0±8.3)31.524.5156.2 (141.4±10.8)24.612.1 30.7 (23.65±3.39)8.06.86.3
\n\nThe average device parameters in parentheses are based on the measurement of over fifteen independent devices. HF, hyperfluorescence. \n\n![](images/81036fde91ad0f0e7843a64d8acbdbd13da4c15b3961512679c76ac581aa743f.jpg) \nFig. 3 | OLED (devices A−D). a, Device structure with the energy-level diagrams. b, The chemical structures used for the respective layers. c, Normalized electroluminescence spectra at 1,000 cd $\\mathfrak{m}^{-2}$ 2PXZBN, 2PTZBN, BNSSe and \nBNSeSe. The inset shows a photograph of device D. d, Current density and luminance versus driving voltage characteristics. e, EQE versus luminance characteristics. f, Current and power efficiency versus luminance characteristics. \n\n![](images/8570ba51e35f132515e15a965f016bacdd81f887ec5abd23db76a182df03f91c.jpg) \nFig. 4 | Hyperfluorescence OLED. a, Emission spectrum of BNSeSe and ultraviolet–visible absorption of BN3 in solution with a concentration of $10^{-5}\\mathsf{m o l l}^{-1}$ . Filled area reveals the overlap of them. b, Electroluminescence colour coordinates of devices A−H in the CIE 1931 chromaticity diagram. Values were \ntaken at 1,000 cd $\\mathfrak{m}^{-2}$ . c, Normalized electroluminescence spectra at 1,000 cd $\\mathfrak{m}^{-2}$ of BN3 in devices E and F. Inset: photograph of device E. d, Current density and luminance versus driving voltage characteristics. e, EQE versus luminance characteristics. f, Current and power efficiency versus luminance characteristics. \n\nBNSeSe-sensitized device E exhibits lower turn-on voltage below $2.4{\\sf V},$ , which should be attributed to the better energy alignment between BNSeSe and DMIC-TRZ. As summarized in Table 2 and depicted in Fig. 4, excellent electroluminescence performance was observed for device F, with an $\\mathtt{E Q E}_{\\operatorname*{max}}$ of $38.7\\%$ , $\\mathsf{C E}_{\\mathrm{max}}$ of $152.2\\mathsf{c d}\\mathsf{A}^{-1}$ , $\\mathsf{P E}_{\\mathrm{max}}$ of $170.7\\mathrm{lm}\\mathrm{W}^{\\mathrm{-1}}.$ , and maximum luminance $(L_{\\mathrm{max}})$ of $154,424{\\mathrm{cd}}{\\mathrm{m}}^{-2}$ . However, device F shows obvious efficiency roll-off at high luminance—the EQE suddenly drops to $20.4\\%$ at 1,000 cd $\\mathfrak{m}^{-2}$ and $11.9\\%$ at $5,000{\\mathsf{c d}}{\\mathsf{m}}^{-2}$ . By sharp contrast, after introducing BNSeSe as a TADF sensitizer in EML, device E exhibits higher EQEs as well as much smaller efficiency roll-off than device F. An enhanced $\\mathbf{CE}_{\\operatorname*{max}}$ of 164.5 cd $\\mathbf{A}^{-1}$ , $\\mathsf{P E}_{\\mathrm{max}}$ of $205.8\\mathsf{I m}\\mathsf{W}^{-1}$ and $L_{\\mathrm{max}}$ of 191,023 cd $\\mathfrak{m}^{-2}$ were observed for device E. Such high values are never reported in TADF OLEDs. Furthermore, the $\\mathsf{E Q E}_{\\mathrm{max}}$ of device E is boosted to $40.5\\%$ , and the EQEs remain $32.4\\%$ at 1,000 cd $\\mathfrak{m}^{-2}$ and $26.1\\%$ at 5,000 cd $\\mathfrak{m}^{-2}$ . Even at the very high brightness of $10,000{\\mathsf{c d}}{\\mathsf{m}}^{-2}$ , device E maintains a high EQE of $23.3\\%$ . We attributed the improved roll-off to the higher $k_{\\mathrm{FRET}}$ between BNSeSe and BN3 compared with the $k_{\\mathrm{nr}}+k_{\\mathrm{lSC}}$ and $k_{\\mathrm{r}}$ of BNSeSe in the hyperfluorescence system (Supplementary Fig. 20), which leads to the singlet excitons upconverted from the triplet excitons in BNSeSe being quickly consumed by BN3 through FRET. The efficient energy transfer from BNSeSe to BN3 hinders the ISC process in BNSeSe, avoiding the triplet excitons stack at high luminance. Furthermore, the emission luminance of device E decreased from 1,000 cd $\\mathfrak{m}^{-2}$ to 500 cd $\\mathfrak{m}^{-2}$ for 51 h without emission colour change (Supplementary Fig. 25), and the FWHM remains 40 nm at 1,000 cd $\\mathfrak{m}^{-2}$ with marginal enlargement compared with device F. To pursue narrower FWHM in hyperfluorescence device, the terminal emitter BN3 was replaced by a green-emissive dopant DtCzB-DPTRZ with narrower FWHM $23\\mathsf{n m}$ in toluene solution with a concentration of $\\mathbf{\\dot{10}}^{-5}\\mathbf{mol}\\left(\\AA^{-1}\\right);$ 7. The corresponding BNSeSe-sensitized device (G) not only displays a \n\nFWHM of only 31 nm, but also manifests very high EQEs of up to $39.6\\%$ , which remains at $34.5\\%$ at 1,000 cd $\\mathfrak{m}^{-2}$ and $24.3\\%$ at $10,000{\\mathrm{cd}}{\\mathrm{m}}^{-2}$ , greatly outperforming those of the sensitizer-free control device (H) (Supplementary Fig. 23). The $\\mathsf{E Q E}_{\\operatorname*{max}}$ values are well supported by optical simulations (Supplementary Fig. 24b,c and Supplementary Table 9). The state-of-the-art performance of BNSeSe-sensitized devices validates our selenium-incorporated MR-TADF material to be ideal sensitizer for MR-TADF emitters with long delayed lifetime. Notably, this is the first example to employ MR-TADF sensitizer for OLEDs, which will greatly contribute to practical applications. \n\n# Conclusion \n\nIn conclusion we have synthesized two novel MR-TADF emitters (BNSSe and BNSeSe) containing heavy-atom selenium. Due to ultra-strong SOC caused by selenium, RISC for BNSeSe was promoted to reach a high level (with $k_{\\scriptscriptstyle{\\mathrm{RISC}}}=2.0\\times10^{6}\\mathrm{s}^{-1})$ in comparison with all reported MR-TADF materials. Devices based on BNSeSe display excellent electroluminescence performances, including high $\\mathsf{E Q E}_{\\mathrm{max}},$ $\\mathsf{C E}_{\\mathrm{max}}$ and $\\mathsf{P E}_{\\mathrm{max}}$ of $36.8\\%$ , 121 cd $\\mathbf{A}^{-1}$ and $146.3\\ln\\mathsf{W}^{-1}$ , respectively, and an ultra-low efficiency roll-off with an EQE of $21.9\\%$ , even at a high brightness of 10,000 cd $\\mathfrak{m}^{-2}$ . Furthermore, MR-TADF material (BNSeSe) was first used as an assist dopant to sensitize the low-energy MR-TADF emitters (BN3 and DtCzB-DPTRZ), the hyperfluorescence OLEDs exhibit striking $\\mathsf{E Q E}_{\\mathrm{max}}$ beyond $40\\%$ and ultra-low efficiency roll-off. Our results clearly suggest the strong heavy-atom effect could effectively promote the RISC process in MR-TADF compounds while maintaining high $\\phi_{\\mathrm{{PL}}}$ values and narrow-band emission. This work sheds new light on MR-TADF emitters and sensitizers towards highly efficient OLEDs. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/ s41566-022-01083-y. \n\n# References \n\n1. Hatakeyama, T. et al. Ultrapure blue thermally activated delayed fluorescence molecules: efficient HOMO–LUMO separation by the multiple resonance effect. Adv. Mater. 28, 2777–2781 (2016). \n2. Suresh, S. M., Hall, D., Beljonne, D., Olivier, Y. & Zysman-Colman, E. Multiresonant thermally activated delayed fluorescence emitters based on heteroatom-doped nanographenes: recent advances and prospects for organic light-emitting diodes. Adv. Funct. Mater. 30, 1908677–1908701 (2020). \n3. Kondo, Y. et al. Narrowband deep-blue organic light-emitting diode featuring an organoboron-based emitter. Nat. Photon. 13, 678–682 (2019). \n4. Liang, X. et al. Peripheral amplification of multi-resonance induced thermally activated delayed fluorescence for highly efficient OLEDs. Angew. Chem. Int. Ed. 57, 11316–11320 (2018). \n5. Zhang, Y. et al. Multi-resonance induced thermally activated delayed fluorophores for narrowband green OLEDs. Angew. Chem. Int. Ed. 58, 16912–16917 (2019). \n6. Yang, M., Park, I. S. & Yasuda, T. Full-color, narrowband, and high-efficiency electroluminescence from boron and carbazole embedded polycyclic heteroaromatics. J. Am. Chem. Soc. 142, 19468–19472 (2020). \n7. Xu, Y. et al. Highly efficient electroluminescent materials with high color purity based on strong acceptor attachment onto B-N-containing multiple resonance frameworks. CCS Chem. 3, 2077–2091 (2021). thermally activated delayed fluorescent emitters for narrowband orange–red OLEDs boosted by a cyano-functionaliztion strategy. Chem. Sci. 12, 9408–9412 (2021). \n9.\t Zhang, Y. et al. Multi-resonance deep-red emitters with shallow potential-energy surfaces to surpass energy-gap law. Angew. Chem. Int. Ed. 60, 20498–20503 (2021). \n10.\t Qi, Y. et al. Perpheral decoration of multi-resonance molecules as a versatile approach for simultaneous long-wavelength and narrowband emission. Adv. Funct. Mater. 31, 2102017–2102023 (2021). \n11.\t Uoyama, H., Goushi, K., Shizu, K., Nomura, H. & Adachi, C. Highly efficient organic light-emitting diodes from delayed fluorescence. Nature 492, 234–238 (2012). \n12.\t Hirata, S. et al. Highly efcient blue electroluminescence based on thermally activated delayed fluorescence. Nat. Mater. 14, 330–336 (2015). \n13.\t Liu, Y. et al. All-organic thermally activated delayed fluorescence materials for organic light-emitting diodes. Nat. Rev. Mater. 3, 18020 (2018). \n14.\t Wong, M. Y. & Zysman-colman, E. Purely organic thermally activated delayed fluorescence materials for organic light-emitting diodes. Adv. Mater. 29, 1605444–1605497 (2017). \n15.\t Brédas, J.-L., Beljonne, D., Coropceanu, V. & Cornil, J. Charge-transfer and energy-transfer processes in π-conjugated oligomers and polymers: a molecular picture. Chem. Rev. 104, 4971–5004 (2004). \n16.\t Schmidt, K. et al. J. Phys. Chem. A 111, 10490–10499 (2017). \n17. Samanta, P. K., Kim, D., Coropceanu, V. & Brédas, J.-L. Up-conversion intersystem crossing rates in organic emitters for thermally activated delayed fluorescence: impact of the nature of singlet vs triplet excited states. J. Am. Chem. Soc. 139, 4042–4051 (2017). \n18.\t Etherington, M. K., Gibson, J., Higginbotham, H. F., Penfold, T. J. & Monkman, A. P. Revealing the spin–vibronic coupling mechanism of thermally activated delayed fluorescence. Nat. Commun. 7, 13680 (2016). \n19.\t Kim, G. H. et al. Controlling the exciton lifetime of blue thermally activated delayed fluorescence emitters using a heteroatom-containing pyridoindole donor moiety. Mater. Horiz. 4, 619–624 (2017). \n20.\t Turro, N. J., Kavarnos, G. J., Cole, T., Scribe, P. & Dalton, J. C. Molecular photochemistry. XXXIX. External heavy-atom-induced spin–obital coupling. Spectroscopic study of naphthonorbornanes. J. Am. Chem. Soc. 93, 1032–1034 (1971). \n21.\t Zhao, W., He, Z. & Tang, B. Z. Room-temperature phosphorescence from organic aggregates. Nat. Rev. Mater. 5, 869–885 (2020). \n22.\t Yang, Z. et al. Intermolecular electronic coupling of organic units for efficient persistent room-temperature phosphorescence. Angew. Chem. Int. Ed. 55, 2181–2185 (2016). \n23.\t Yan, Z.-A., Lin, X., Sun, S., Ma, X. & Tian, H. Activating room-temperature phosphorescence of organic luminophores via external heavy-atom effect and rigidity of ionic polymer matrix. Angew. Chem. Int. Ed. 60, 19735–19739 (2021). \n24.\t Hua, T. et al. Heavy-atom effect promotes multi-resonance thermally activated delayed fluorescence. Chem. Eng. J. 426, 131169–131177 (2021). \n25.\t Zhang, D. et al. High-effciency fluorescent organic light-emitting devices using sensitizing hosts with a small singlet–triplet exchange energy. Adv. Mater. 26, 5050–5055 (2014). \n26.\t Jeon, S. O. et al. High-efficiency, long-lifetime deep-blue organic light-emitting diodes. Nat. Photon. 15, 208–215 (2021). \n27.\t Chan, C. Y. et al. Stable pure-blue hyperfluorescence organic light-emitting diodes with high-efficiency and narrow emission. Nat. Photon. 15, 203–207 (2021). \n28.\t Baldo, M. A., Adachi, C. & Forrest, S. R. Transient analysis of organic electrophosphorescence. II. Transient analysis of triplet-triplet annihilation. Phys. Rev. B 62, 10967–10977 (2000). \n29.\t Hertel, D. & Meerholz, K. Triplet-polaron quenching in conjugated polymers. J. Phys. Chem. B 111, 12075–12080 (2007). \n30.\t Giebink, N. C. & Forrest, S. R. Temporal response of optically pumped organic semiconductor lasers and its implication for reaching threshold under electrical excitation. Phys. Rev. B 79, 073302–073305 (2009). \n31.\t Murawski, C., Leo, K. & Gather, M. C. Efficiency roll-off in organic light-emitting diodes. Adv. Mater. 25, 6801–6827 (2013). \n32.\t Einzinger, M. et al. Shorter exciton lifetimes via an external heavy-atom effect: alleviating the effects of bimolecular processes in organic light-emitting diodes. Adv. Mater. 29, 1701987–1701996 (2017). \n33.\t Wang, D., Cheng, C., Tsuboi, T. & Zhang, Q. Degradation mechanisms in blue organic light-emitting diodes. CCS Chem. 2, 1278–1296 (2020). \n34.\t Zhang, D. et al. Efficient and stable deep-blue fluorescent organic light-emitting diodes employing a sensitizer with fast triplet upconversion. Adv. Mater. 32, 1908355–1908343 (2020). \n35.\t Zhan, L. et al. Copper(I) complex as sensitizer enables high-performance organic light-emitting diodes with very low efficience roll-off. Adv. Funct. Mater. 31, 2106345 (2021). \n36.\t Gao, X. et al. Evaluation of spin-orbit couplings with linear-response time dependent density functional methods. J. Chem. Theory Comput. 13, 515–524 (2017). \n37.\t Zhang, D. et al. Highly efficient full-color thermally activated delayed fluorescent organic light-emitting diodes: extremely low efficiency roll-off ultilizing a host with small singlet-triplet splliting. ACS Appl. Mater. Interfaces 9, 4769–4777 (2017). \n38.\t Zhang, Y. et al. Achieving pure green electroluminescence with CIEy of 0.69 and EQE of $28.2\\%$ from an aza-fused multi-resonance emitter. Angew. Chem. Int. Ed. 59, 17499–17503 (2020). \n39.\t Xu, Y. et al. Constructing charge-transfer excited states based on frontier molecular orbital engineering: narrowband green electroluminescence with high color purity and efficiency. Angew. Chem. Int. Ed. 59, 17442–17446 (2020). \n40.\t Braveenth, R. et al. Achieving narrow FWHM and high EQE over $38\\%$ in blue OLEDs using rigid heteroatom-based deep blue TADF sensitized host. Adv. Funct. Mater. 31, 2105805 (2021). \n41.\t Jiang, P. et al. Quenching-resistant multi-resonance TADF emitter realizes $40\\%$ extaernal quantum efficiency in narrowband electroluminescence at high doping level. Adv. Mater. 34, \n2106954–2106960 (2022). \n42.\t Qi, Y. et al. Peripheral decoration of multi-resonance molecules as a versatile approach for simultaneous long-wavelength and narrowband emission. Adv. Funct. Mater. 31, 2102017–2102023 (2021). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nSpringer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 \n\n# Methods \n\n# Theoretical calculations \n\nQuantum chemical calculations were performed by the Gaussian 09 program package43. Density functional theory was performed at the B3LYP/6-31G(d,p) level to attain the optimized molecular geometries. The HOMO and the LUMO were obtained logically on the basis of the optimized geometric configurations. Time-dependent DFT calculations were performed at the B3LYP/6-31G(d,p) level to obtain the vertical transitions, as well as the natural transition orbitals of the singlet and triplet states on the basis of the corresponding $\\mathsf{S}_{0}$ geometries. The SDD pseudopotential was used for selenium atoms; SCS-CC2 and ADC(2) calculations were performed using the MRCC program with the cc-pVDZ basis set44,45. The SOC calculations were further evaluated using PySOC. The optical simulation of OLED devices was performed using the SETFOS 5.1 (Fluxim) program. The input parameters include refractive index value, extinction coefficient, thickness of each layer values (all measured by ellipsometry), as well as photoluminescence spectrum of the emitting layer. \n\n# Photophysical measurements \n\nUltraviolet–visible absorption and photoluminescence spectra were measured using a Shimadzu UV-2700 spectrophotometer (Shimadzu) and Hitachi F-7100 fluorescence spectrophotometer (Hitachi), respectively. Phosphorescence spectra were recorded on the Hitachi F-7100 fluorescence spectrophotometer at 77 K. The transient photoluminescence decay curves were obtained by FluoTime 300 (PicoQuant GmbH) with a Picosecond Pulsed UV-LASER (LASER375) as the excitation source. The values of $\\phi_{\\mathrm{{PL}}}$ were measured with a Hamamatsu UV-NIR absolute photoluminescence quantum yield spectrometer (C13534, Hamamatsu Photonics) equipped with a calibrated integrating sphere, the integrating sphere was purged with dry argon to maintain an inert atmosphere. \n\n# Device fabrication and performance measurements \n\nThe ITO-coated glass substrates with a sheet resistance of 15 Ω square–1 were consecutively ultrasonicated with acetone/ethanol and dried with nitrogen gas flow, follwed by 20 min ultraviolet light–ozone treatment in an ultraviolet–ozone surface processor (PL16 series, Sen Lights Corporation). The sample was then transferred to the deposition system. Both 8-hydroxyquinolinolato-lithium (Liq) and alumina as electron injection and cathode layers, respectively, were deposited by thermal evaporation at $5\\times10^{-5}$ Pa. Furthermore, the organic layers were deposited at rates of $0.2\\substack{-3\\mathring{\\mathbf{A}}\\mathbf{S}^{-1}}$ . After the organic film deposition, the Liq and alumina layers were deposited at rates of 0.1 and $\\bar{3}\\mathring{\\mathbf{A}}{\\mathbf{s}}^{-1}.$ , respectively. The emitting area of the device is about $0.09\\mathsf{c m}^{2}$ . The current density– voltage–luminance (J–V–L), $\\iota$ –EQE curves and electroluminescence spectra were measured using a Keithley 2400 source meter and an absolute EQE measurement system (C9920-12, Hamamatsu Photonics). \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding author on reasonable request. Source Data are provided with this paper. \n\n# References \n\n43.\t Gaussian 09 (Revision C.01), Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; \n\nHonda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, Jr. J. A.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Keith, T.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J. M.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J., Dapprich, S.; Daniels, A. D.; Farkas, O.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian, Inc., Wallingford CT, 2010. \n4.\t Kállay, M. et al. The MRCC program system: accurate quantum chemistry from water to proteins. J. Chem. Phys. 152, 074107– 074124 (2020). \n5.\t Kállay, M. et al. MRCC: A Quantum Chemical program Suite (MRCC, 2022); www.mrcc.hu \n\n# Acknowledgements \n\nThis work was funded by the National Natural Science Foundation of China (grant no. 52130308 to C.Y.), the Shenzhen Science and Technology Program (grant nos. KQTD20170330110107046 and ZDSYS20210623091813040 to C.Y.) and the China Postdoctoral Science Foundation (grant no. 2021M692183 to Y.X.H.). We thank C. Zhong (Department of Chemistry, Wuhan University) for the assistance with theoretical calculations, as well as Y. Gu and X. Zhou (TCL China Star Optoelectronics Technology) for their assistance with the optical simulation of the devices. We also thank the Instrumental Analysis Center of Shenzhen University for analytical support. \n\n# Author contributions \n\nC.Y. supervised the projects. C.Y., Y.X.H., Z.H. and Y.Z. designed the TADF emitters. Y.X.H., T.H. and Y.Qi synthesized emitters. Y.X.H. characterized the emitters and measured the photophysical and electrochemical properties. J.M. and H.X. fabricated the OLED devices, measured the electroluminescence and prepared thin films. Y.X.H. and H.L. performed theoretical calculations. Y.Qiu conducted the transient photoluminescnece measurements. Y.X.H., X.C. and C.Y. contributed to the manuscript writing. Y.X.H., H.L., J.M. and C.Y. contributed to discussions. All authors discussed the progress of the research and reviewed the manuscript. \n\n# Competing interests \n\nSZU has filed patent applications on materials and devices. C.Y., Y.X.H. and J.M. are the authors of the invention. CN patent application no. 2021113469101 (pending). The other authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41566-022-01083-y. \n\n# Correspondence and requests for materials should be addressed to Chuluo Yang. \n\nPeer review information Nature Nanotechnology thanks Fernando Dias and Hironori Kaji for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. " + }, + { + "id": "10.1016_j.joule.2022.03.005", + "DOI": "10.1016/j.joule.2022.03.005", + "DOI Link": "http://dx.doi.org/10.1016/j.joule.2022.03.005", + "Relative Dir Path": "mds/10.1016_j.joule.2022.03.005", + "Article Title": "Origins and influences of metallic lead in perovskite solar cells", + "Authors": "Liang, JW; Hu, XZ; Wang, C; Liang, C; Chen, C; Xiao, M; Li, JS; Tao, C; Xing, GC; Yu, R; Ke, WJ; Fang, GJ", + "Source Title": "JOULE", + "Abstract": "Metallic lead (Pb-0) impurities in metal-halide perovskites have attracted tremendous research concerns owing to their detrimental effects on perovskite solar cells (PSCs). However, the origins and influences of the Pb-0 behind this issue have yet to bewell understood. Herein, we show that Pb-0 is hardly formed in the growth of halide perovskites but is easily postformed in the perovskite films with excess PbI2. It is found that Pb-0 impurities are decomposition byproducts of residual PbI2 in perovskites under light or X-ray irradiation. Therefore, PSCs obtained using photodegraded PbI2 films show large efficiency and stability losses. By contrast, the perovskite devices without detectable Pb-0 impurities have a much better efficiency and stability. This work reveals the origins and influences of Pb-0 in halide perovskites and provides a strategy for avoiding the formation of detrimental Pb-0 byproducts, which would drive further enhancements in device performance of halide perovskite solar cells, detectors, etc.", + "Times Cited, WoS Core": 325, + "Times Cited, All Databases": 330, + "Publication Year": 2022, + "Research Areas": "Chemistry; Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000798575600013", + "Markdown": "# Article Origins and influences of metallic lead in perovskite solar cells \n\nJiwei Liang, Xuzhi Hu, Chen Wang, ..., Rui Yu, Weijun Ke, Guojia Fang \n\n![](images/b9a3d0d8431a4eada45704c5e8e8e5b9121eaea459317892ae37d249aaf8542b.jpg) \n\nyurui@whu.edu.cn (R.Y.) weijun.ke@whu.edu.cn (W.K.) gjfang@whu.edu.cn (G.F.) \n\n# Highlights \n\n$\\mathsf{P b l}_{2}$ is very unstable under both light and $\\mathsf{X}$ -ray irradiation \n\n${\\mathsf{P b}}^{0}$ is a photodegradation byproduct of $\\mathsf{P b}|_{2}$ instead of perovskites \n\nInstability of $\\mathsf{P b l}_{2}$ under $\\mathsf{X}.$ -ray irradiation disturbs XPS measurements \n\n${\\mathsf{P b}}^{0}$ deteriorates the efficiency and stability of perovskite solar cells \n\nA systematic study on the origins and influences of ${\\mathsf{P b}}^{0}$ for PSCs was carried out, where we reveal the relationship among ${\\mathsf{P b}}^{0}.$ , ${\\mathsf{P b l}}_{2},$ and perovskites. Our results demonstrate that both light and $\\mathsf{X}.$ -ray irradiation can lead to the decomposition of $\\mathsf{P b}|_{2}$ . By contrast, perovskite themselves are much more stable than lead halides. Furthermore, we propose an effective strategy to restrain the detrimental ${\\mathsf{P b}}^{0}$ by eliminating excess $\\mathsf{P b l}_{2}$ in perovskites and introducing excess A-site cations. \n\n# Article Origins and influences of metallic lead in perovskite solar cells \n\nJiwei Liang,1,2 Xuzhi Hu,1 Chen Wang,1 Chao Liang,3 Cong Chen,1 Meng Xiao,1 Jiashuai Li,1 Chen Tao,1,2 Guichuan Xing,3 Rui Yu,1,\\* Weijun Ke,1,2,\\* and Guojia Fang1,2,4,\\* \n\n# SUMMARY \n\nMetallic lead $(\\mathsf{P b}^{0})$ impurities in metal-halide perovskites have attracted tremendous research concerns owing to their detrimental effects on perovskite solar cells (PSCs). However, the origins and influences of the $\\mathsf{P b}^{\\mathsf{o}}$ behind this issue have yet to be well understood. Herein, we show that $\\mathsf{P b}^{\\mathsf{o}}$ is hardly formed in the growth of halide perovskites but is easily postformed in the perovskite films with excess $\\mathsf{P b l}_{2}$ . It is found that $\\mathsf{P b}^{\\mathsf{o}}$ impurities are decomposition byproducts of residual $\\mathsf{P b l}_{2}$ in perovskites under light or X-ray irradiation. Therefore, PSCs obtained using photodegraded $\\mathsf{P b l}_{2}$ films show large efficiency and stability losses. By contrast, the perovskite devices without detectable $\\bar{\\mathsf{P}}\\bar{\\mathsf{b}}^{\\circ}$ impurities have a much better efficiency and stability. This work reveals the origins and influences of $\\mathsf{P b}^{\\mathsf{o}}$ in halide perovskites and provides a strategy for avoiding the formation of detrimental ${\\mathsf{P b}}^{0}$ byproducts, which would drive further enhancements in device performance of halide perovskite solar cells, detectors, etc. \n\n# Context & scale \n\nLead halide perovskite solar cells (PSCs) have drawn worldwide attention due to their high absorption coefficients, long charge carrier diffusion lengths, and high defect tolerance. The certified power conversion efficiency (PCE) of PSCs has jumped to $25.7\\%$ in the last decade. However, there is a lack of consensus on the origins of metallic lead $(\\mathsf{P b}^{0})$ as to whether it comes from the initial precursor solutions or the resultant perovskite films. Here, we uncover the relationship among ${\\mathsf{P b}}^{0}$ , lead iodide $(\\mathsf{P b}|_{2})$ , and halide perovskites under light or $\\mathsf{X}$ -ray irradiation. It is shown that ${\\mathsf{P b}}^{0}$ impurities are decomposition byproducts of residual $\\mathsf{P b l}_{2}$ in perovskites under light or $\\mathsf{X}$ -ray irradiation. Moreover, the presence of ${\\mathsf{P b}}^{0}$ impurities significantly hampers perovskite crystallization, reduces trap activity energy, and loads deeplevel defect states, which not only increases nonradiative recombination but also accelerates perovskite degradation. By contrast, perovskites themselves are much more stable under light and $x.$ -ray irradiation. \n\n# INTRODUCTION \n\nLead-halide perovskites have been a focus of new-generation photovoltaic technologies owing to their superior optical absorption coefficients, long carrier diffusion lengths, high defect tolerance, etc.1–5 The certified power conversion efficiency (PCE) of perovskite solar cells (PSCs) has jumped to $25.7\\%,$ which is comparable with those of commercialized monosilicon solar cells.7 To achieve high PCEs, mixed cations (e.g., methylammonium $[\\mathsf{M A}^{+}],$ formamidinium $[\\mathsf{F A}^{+}],$ and alkali ions) and anions (I\u0001, $\\mathsf{B r}^{-}$ , and $\\mathsf{C l}^{-}$ ) have been widely employed in many previous works.8–12 Some other common methods, such as additive engineering13,14 and surface passivation,15,16 have also successfully increased the PCE of PSCs, thanks to the decreased nonradiative recombination and trap densities. However, one of the most critical challenges is that halide perovskites are still suffering from poor stability,17–20 which seriously hinder the upcoming commercialization of PSCs. \n\nThe stability limits of PSCs can be attributed into two main categories: extrinsic and intrinsic factors. Extrinsic environmental factors can be well blocked by external encapsulation.21 While intrinsic factors, such as light-induced decomposition,22 ion migration,23 and thermal degradation,24 have to be resolved by improving the quality of perovskites themselves. Metallic lead $(\\mathsf{P b}^{0})^{25}$ is considered one of the most detrimental intrinsic factors for PSCs’ deterioration, resulting in the reduction of both efficiency and stability.26–29 For example, Wang et al. suggested that ${\\mathsf{P b}}^{0}$ stemming from the perovskite precursor solutions is very harmful, but can be reduced by $\\mathsf{E u}^{3+}$ , which enables the oxidation of ${\\mathsf{P b}}^{0}$ to ${\\mathsf{P b}}^{2+}$ for realizing stable PSCs.30 Other reports considered that ${\\mathsf{P b}}^{0}$ resulting from thermal annealing of perovskite films or interface degradation between perovskites and electron-transport layers should be avoided for high-performance PSCs.31–33 Nevertheless, there is a lack of consensus on the origins of ${\\mathsf{P b}}^{0}$ , that is. whether it comes from the initial precursor solutions or the resultant perovskite films. In addition, although ${\\mathsf{P b}}^{0}$ had been commonly regarded as an intrinsic defect in perovskites, the characteristics and influences of ${\\mathsf{P b}}^{0}$ in perovskites, the understanding of and their devices have lagged far behind.34–37 It is therefore essential to thoroughly identify the origins and influences of ${\\mathsf{P b}}^{0}$ in perovskites to further improve solar-cell efficiency and stability. \n\nIn this work, we carried out a series of experiments to understand the origins and influences of ${\\mathsf{P b}}^{0}$ in perovskite solar cells. We found that ${\\mathsf{P b}}^{0}$ impurities are decomposition byproducts of residual lead iodide $(\\mathsf{P b}|_{2})$ in perovskites under light or X-ray irradiation. By contrast, perovskites themselves without excess lead halides hardly induce ${\\mathsf{P b}}^{0}$ impurities and have a much better tolerance for light and X-ray irradiation. The results show that the presence of ${\\mathsf{P b}}^{0}$ in perovskite films hampers the perovskite crystallization, leads to additional deep-defect levels, and loads reduction of trap activity energy, which not only increases nonradiative recombination but also accelerates perovskite degradation. Therefore, the resultant PSCs obtained from the light-aged $\\mathsf{P b l}_{2}$ films with ${\\mathsf{P b}}^{0}$ impurities have much reduced efficiencies and stability. The results give an effective strategy to restrain the formation of ${\\mathsf{P b}}^{0}$ in halide perovskites and further improve the performance of PSCs. \n\n# RESULTS AND DISCUSSION \n\nGiven that excess $\\mathsf{P b l}_{2}$ has been widely applied in highly efficient $\\mathsf{P S C s}^{27,31,38-41}$ and is supposed to be related to ${\\mathsf{P b}}^{0}$ , we firstly investigated perovskite films with excess $\\mathsf{P b l}_{2}$ . We employed a basic perovskite member of $\\mathsf{M A P b l}_{3}$ to study its essential properties. A stoichiometric one-step antisolvent-processed ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ film, a $\\mathsf{M A P b l}_{3}$ film with $5\\mathrm{mol}\\%$ excess ${\\mathsf{P b l}}_{2},$ , and a $\\mathsf{M A P b l}_{3}$ film with $5\\mathrm{mol}\\%$ excess $\\mathsf{P b l}_{2}$ and methylammonium iodide (MAI, $6\\ m\\mathsf{g/m L}$ ) posttreatment were loaded for comparison. Top-view scanning electron microscopy (SEM) images of all samples are shown in Figures 1A–1C, where we can observe that the stoichiometric $\\mathsf{M A P b l}_{3}$ (here defined as the control one) exhibited a small crystal size (Figure 1A). And the crystal size increases with the introduction of excess ${\\mathsf{P b}}|_{2}$ , corresponding to previous reports.38,40,42 Meanwhile, the excess $\\mathsf{P b l}_{2}$ is abundant at the surface of perovskites, which can be observed by the off-white spots (marked with red cycles) in Figure 1B. Besides, when we use $6\\mathrm{mg/mL}$ of MAI/isopropanol (IPA) to modify the surface of perovskites, the abundant $\\mathsf{P b l}_{2}$ gradually disappeared as evidenced in Figure 1C. X-ray diffraction (XRD) measurements further confirmed the appearance and disappearance of $\\mathsf{P b l}_{2}$ in Figure 1D and the zoomed-in XRD patterns are exhibited in Figure S1. What is interesting is that the ${\\mathsf{P b}}^{0}$ peaks in the X-ray photoelectron spectroscopy (XPS) characterization (Figure 1E) are inextricably linked to the $\\mathsf{P b}|_{2}$ . For example, obvious $\\mathsf{P b l}_{2}$ diffractions were detected in the $\\mathsf{M A P b l}_{3}$ film with $5\\%$ excess $\\mathsf{P b l}_{2}$ and also showed strong ${\\mathsf{P b}}^{0}$ peaks in XPS spectra. However, the control and $6{\\bmod{1}}=62$ MAI-treated $\\mathsf{M A P b l}_{3}$ samples did not show any $\\mathsf{P b l}_{2}$ peaks under XRD measurements, which also did not contain ${\\mathsf{P b}}^{0}$ in XPS characterization. It seems that the presence of $\\mathsf{P b}|_{2}$ in the perovskites led to the emergence of ${\\mathsf{P b}}^{0}$ instead of the perovskites themselves. Given that the perovskite film was washed by IPA solvent during the MAI solution-coating process, this might lead to ${\\mathsf{P b}}^{0}$ vanishing. To exclude this concern, we also performed XRD and XPS measurements of the $5\\%$ excess $\\mathsf{P b l}_{2}$ -incorporated $\\mathsf{M A P b l}_{3}$ perovskite film with IPA washing (Figure S2), showing as the unwashed one (Figures 1D and 1E). Therefore, we can conclude that the \n\n![](images/ae9d09d7d7b4c6f9c105564826f801d31285ca4131f75ee0e8c89b20517f9739.jpg) \nFigure 1. X-ray irradiation analysis of MAPbI3 perovskites \n\n(A) Top-view SEM image of a stoichiometric ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ perovskite film (control). \n(B) Top-view SEM image of a ${\\mathsf{M A P b}}{\\mathsf{b}}{\\mathsf{l}}_{3}$ perovskite film with 5 mol $\\%$ excess $\\mathsf{P b l}_{2}$ . \n(C) Top-view SEM image of a ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ perovskite film with 5 mol $\\%$ excess $\\mathsf{P b l}_{2}$ and $6~\\mathrm{mg/mL}$ MAI posttreatment. \n(D) XRD patterns of the corresponding perovskite films. \n(E) Pb 4f high-resolution XPS spectra of the corresponding perovskite films. \n(F) Pb 4f high-resolution $\\mathsf{X P S}$ spectra of $\\mathsf{P b l}_{2}$ films with $\\mathsf{X}$ -ray radiation for $0{-}20~\\mathrm{min}$ . \n(G) J-V curves of a stoichiometric MAPbI3 PSC before and after $\\mathsf{X}$ -ray irradiation. \n(H) J-V curves of a stoichiometric ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ PSC with $5\\mathrm{mol}\\%$ excess $\\mathsf{P b l}_{2}$ before and after X-ray irradiation. \n(I) J-V curves of a stoichiometric MAPbI3 PSC with $5\\mathrm{mol}\\%$ excess $\\mathsf{P b l}_{2}$ and $6~\\mathrm{mg/mL}$ MAI treatment before and after X-ray irradiation. \n\n${\\mathsf{P b}}^{0}$ impurities actually resulted from the decomposition of $\\mathsf{P b l}_{2}$ during the XPS testing but did not exist in the initial perovskite films. In other words, the ${\\mathsf{P b}}^{0}$ impurities in perovskite films were not introduced by precursor solutions but were induced by the postmeasurement process. It is well known that $\\mathsf{P b l}_{2}$ is a light-sensitive material.43 Any photon excitations with energies higher than around $2.51\\ \\mathrm{eV}$ would be able to decompose $\\mathsf{P b l}_{2}$ into ${\\mathsf{P b}}^{0}$ (Equation 1), such as the $\\mathsf{X}.$ -ray source used in the XPS instrument. \n\n$$\n\\mathsf{P b}|_{2}\\xrightarrow{2.51\\mathrm{~eV}}\\mathsf{P b}^{0}+|_{2}\\uparrow\n$$ \n\n(Equation 1) \n\nTo prove this conjecture, we also performed XPS characteristics of the $\\mathsf{P b l}_{2}$ films exposed the X-ray radiation for different times during the measurements. Figure 1F shows that the peak intensity of ${\\mathsf{P b}}^{0}$ gradually increases with prolonging the radiation time. Even though without extra $\\mathsf{X}$ -ray radiation, initial X-ray radiation during the XPS measurements is strong enough to decompose $\\mathsf{P b l}_{2}$ into ${\\mathsf{P b}}^{0}$ . Besides, this decomposition phenomenon existed in not only $\\mathsf{P b l}_{2}$ but also in other lead halides (e.g., Lead bromide $[P b\\mathsf{B r}_{2}]$ and lead chloride $[\\mathsf{P b C l}_{2}])$ , which exhibited similar instability under X-ray radiation in the process of XPS measurements (Figure S3). The dissociation energies of $\\mathsf{P b l}_{2}$ , ${\\mathsf{P b}}{\\mathsf{B}}{\\mathsf{r}}_{2},$ and ${\\mathsf{P b C l}}_{2}$ are estimated to be around 2.51, 3.06, and $3.19\\mathrm{eV}.$ , respectively (Equations 1, 3, and 4).43 All lead halides are X-ray sensitive and $\\mathsf{P b l}_{2}$ should be the most unstable one under X-ray or light irradiation. Therefore, ${\\mathsf{P b}}^{0}$ impurities should be more carefully considered during XPS or any other high-photon-energy measurements, especially for the lead-halide-rich perovskite samples. \n\nDifferent from the film with excess ${\\mathsf{P b l}}_{2},$ the stoichiometric $\\mathsf{M A P b l}_{3}$ sample only shows the peaks of ${\\mathsf{P b}}^{2+}$ at 137.9 and $142.8~\\mathrm{eV}$ , indicating that $\\mathsf{M A P b l}_{3}$ perovskite itself possesses good stability under long-term $\\mathsf{X}$ -ray radiation, as compared with the one with excess $\\mathsf{P b l}_{2}$ (Figure S4). This is because the dissociation energy of $\\mathsf{M A P b l}_{3}$ perovskite reaches up to around $6.17\\mathrm{eV}.$ as described in Equation 2.44 \n\n$$\n\\M A P b|_{3}\\xrightarrow{6.17\\mathrm{~eV}}\\mathsf{P b}|_{2}+M A|\n$$ \n\n(Equation 2) \n\nTherefore, halide perovskites should have much better stability than lead halides $(6.17\\mathrm{eV}$ for $\\mathsf{M A P b l}_{3}$ versus $2.51\\mathrm{eV}$ for $\\mathsf{P b l}_{2})$ . Note that ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ would have lowered dissociation energies under particular conditions of vacuum, heating, and moisture because of the unstable MAI.18,45,46 Perovskite films with excess lead halides under long-term $\\mathsf{X}$ -ray or light irradiation would favor the formation of ${\\mathsf{P b}}^{0}$ , which actually originated from the decomposition of lead halides but not of perovskites. We further checked the X-ray stability of PSCs using the ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ films processed with different conditions, i.e., control, $5\\%$ excess $\\mathsf{P b l}_{2}$ , and $5\\%$ excess $\\mathsf{P b l}_{2}$ plus MAI posttreatment. Figures 1G–1I show that the $\\mathsf{M A P b l}_{3}$ PSC with $5\\%$ excess $\\mathsf{P b l}_{2}$ exhibited poor X-ray stability, which only maintained $90\\%$ of its initial efficiency after $5\\textmd{h}$ of X-ray irradiation. For comparison, ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ PSCs without excess $\\mathsf{P b l}_{2}$ exhibited stronger resistance to X-ray radiation. \n\nIn addition to coating extra MAI, we can also use other different bulky organic cations, i.e., guanidinium iodide (GAI), dimethylammonium iodide (DMAI), and phenethylammonium iodide (PEAI),15,16,47 to react with the residual $\\mathsf{P b}|_{2}$ in ${\\mathsf{M A P b}}{\\mathsf{b}}{\\mathsf{l}}_{3}$ and introduce low-dimensional perovskites with post-annealing. Top-view SEM images of the excess $\\mathsf{P b l}_{2}$ -incorporated $\\mathsf{M A P b l}_{3}$ films with different-cation posttreatments are given in Figure S5, showing an obvious change on the surface of ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ perovskite films. All these cations (GAI, DMAI, and PEAI) can react with the residual $\\mathsf{P b l}_{2}$ to form mixed-dimensional perovskites, as confirmed by the XRD patterns shown in Figure S6. More importantly, the ${\\mathsf{P b}}^{0}$ signal disappeared as the $\\mathsf{P b l}_{2}$ was consumed in these samples (Figure S7). Therefore, low-dimensional perovskites can not only serve as a passivator for reducing surface/interface defects16 but also act as an inhibitor for the formation of ${\\mathsf{P b}}^{0}$ in perovskites. These results strongly suggest that the reduction of excess $\\mathsf{P b l}_{2}$ should be one of the keys to further eliminating detrimental ${\\mathsf{P b}}^{0}$ impurities in perovskite films. \n\nTo further study the effects of ${\\mathsf{P b}}^{0}$ in $\\mathsf{P b l}_{2}$ and perovskites, we then introduced ${\\mathsf{P b}}^{0}$ impurities into $\\mathsf{P b l}_{2}$ films on purpose. The $\\mathsf{P b l}_{2}$ films deposited on glass substrates were directly exposed to a white LED source $(70\\mathrm{mW/cm}^{2})$ ) in a nitrogen-filled glovebox. Figure 2A presents an optical photograph of the $\\mathsf{P b l}_{2}$ films with light irradiation for different times, which gradually turned from yellow to black after light irradiation \n\n![](images/8b3d3b7abfdec8e2d455047d5bb11f0870258e01f89332f09344a3f32eb44bd3.jpg) \nFigure 2. The generation of $\\mathsf{P b}^{\\mathsf{o}}$ in $\\mathsf{P b l}_{2}$ films \n\n(A) Photograph of $\\mathsf{P b l}_{2}$ films with light irradiation for $0{-}8\\ h$ . \n(B) Top-view SEM image of a fresh $\\mathsf{P b l}_{2}$ film. \n(C) Top-view SEM image of a $\\mathsf{P b l}_{2}$ film with light irradiation for $8\\mathfrak{h}$ . \n(D) XRD patterns of $\\mathsf{P b}|_{2}$ films with light irradiation for $0{-}8\\ h$ . \n(E) TEM image of a fresh $\\mathsf{P b l}_{2}$ film. \n(F) TEM image of a $\\mathsf{P b l}_{2}$ film after light irradiation for $8\\mathfrak{h}$ . \n(G) PL spectra of $\\mathsf{P b l}_{2}$ films with light irradiation for $0{-}8\\ h$ . \n(H) TRPL spectra of $\\mathsf{P b l}_{2}$ films with light irradiation for $0{-}8\\ h$ . \n(I) Time-resolved transient absorption spectra of $\\mathsf{P b l}_{2}$ films with light irradiation for $0{-}8\\ h$ . \n\nfor $^{8\\mathrm{~h~}}$ . Ultraviolet-visible (UV-vis) spectra also confirmed the absorption enhancement of the films after light irradiation, as shown in Figure S8. SEM images of the $\\mathsf{P b l}_{2}$ films reveal that pinholes and black spots appeared with the extension of the light-irradiation time (Figures 2B, 2C, and S9). We supposed that the dark spots are mainly cubic ${\\mathsf{P b}}^{0}$ because $\\mathsf{P b l}_{2}$ can easily decompose into ${\\mathsf{P b}}^{0}$ under light irradiation, resulting in pinholes in the $\\mathsf{P b l}_{2}$ films after iodine $(\\mathsf{I}_{2})$ sublimation. The light decomposition process of $\\mathsf{P b l}_{2}$ can be described in Equation 1 as mentioned above. \n\nWe further certified this process by measuring the XRD patterns of these films (Figure 2D). From zoomed-in XRD results in Figure S10, all the films with light irradiation had an extra diffraction peak at $31.3^{\\circ}$ , which can be assigned to a (111) plane of ${\\mathsf{P b}}^{0}$ . \n\nThe intensity of the diffraction peak at $31.3^{\\circ}$ gradually increased after light-irradiation time increased, indicating increased amounts of ${\\mathsf{P b}}^{0}$ in the final films. To further prove the generation of ${\\mathsf{P b}}^{0}.$ , high-resolution transmission electron microscopy (HRTEM) images of a pristine $\\mathsf{P b l}_{2}$ film and a $\\mathsf{P b l}_{2}$ film with $8\\ h$ of light irradiation were carried out, as shown in Figures 2E and 2F. For the pristine $\\mathsf{P b l}_{2}$ film, an interplanar spacing of $1.75\\mathring{\\mathsf{A}}$ is well matched with a (004) reflection of hexagonal lattice (PDF #07-0235), while for the light-aged $\\mathsf{P b l}_{2}$ film, it can be observed an extra lattice spacing of $1.43\\mathring{\\mathsf{A}},$ corresponding to the diffraction of a (222) plane for cubic ${\\mathsf{P b}}^{0}$ (PDF #04-0686). Furthermore, energy dispersive spectrometry (EDS) mapping was also carried out (Figure S11) to analyze element distribution, showing that the amounts of I are reduced after light exposure and confirming that ${\\mathsf{P b}}^{0}$ is a degradation byproduct of $\\mathsf{P b l}_{2}$ with light aging. These results strongly demonstrate that the appearance of ${\\mathsf{P b}}^{0}$ in the light-aged $\\mathsf{P b l}_{2}$ films can only originate from $\\mathsf{P b l}_{2}$ . \n\nTo study the effects of ${\\mathsf{P b}}^{0}$ in charge carrier generation and recombination, photoluminescence (PL) and time-resolved photoluminescence (TRPL) measurements were also performed in the different $\\mathsf{P b l}_{2}$ films (Figures 2G and 2H). In comparison with the fresh $\\mathsf{P b l}_{2}$ film, the PL intensity and lifetime of the light-aged $\\mathsf{P b l}_{2}$ films were significantly decreased, stemming from the increased nonradiative recombination. This is consistent with the notion that the ${\\mathsf{P b}}^{0}$ serving as a recombination center can increase nonradiative recombination and therefore decrease the PL intensity. Also, transient absorption (TA) spectra of the samples were measured, as presented in Figures S12 and 2I. A negative $\\Delta\\mathsf{A}$ signal at $499{\\mathsf{n m}}$ corresponds to photobleaching of $\\mathsf{P b}|_{2}$ (Figure S12). The fitted data of the decay is given in Table S1, where the carrier charge lifetime $\\uptau_{2}\\left(\\uptau_{3}\\right)$ reduces from 13.07 ${\\langle336.60\\ p s\\rangle}$ to 0.41 (11.69 ps) for the film after $8\\ h$ of light aging. This result indicates that the presence of ${\\mathsf{P b}}^{0}$ in $\\mathsf{P b l}_{2}$ significantly aggravates carrier recombination.48 \n\nEncouraged by the above results, we then investigated the influences of ${\\mathsf{P b}}^{0}$ on the efficiency and stability of PSCs. The light-aged $\\mathsf{P b l}_{2}$ films loaded with ${\\mathsf{P b}}^{0}$ impurities on purpose were employed to assemble perovskite films and devices. The perovskite films were fabricated by a two-step deposition method, as illustrated in Figure 3A. The devices used $\\mathsf{S n O}_{2}$ as electron transfer layers and 2,20,7,70-tetrakis [N,N-di(4-methoxyphenyl) amino]-9,90-spiro-bifluorene (spiro-OMeTAD) as holetransfer layers. In the first step, we employed $\\mathsf{P b l}_{2}$ films with light irradiation for different times (e.g., 2, 4, 6, and $8\\ h$ ) and fresh $\\mathsf{P b l}_{2}$ as control sample as precursor layers. The longer light-irradiation times led to more amounts of ${\\mathsf{P b}}^{0}$ in the final films. Top-view SEM images of the fabricated perovskite films obtained using fresh $\\mathsf{P b l}_{2}$ and $^{8\\ h}$ -light-aged $\\mathsf{P b l}_{2}$ are compared in Figures 3B and 3C, where we can observe that some spongy grains appear and gradually increase as the amount of ${\\mathsf{P b}}^{0}$ increases (Figures S13A–S13C). The red dashed lines depict the shape of these spongy materials in the SEM images. Compared with the fresh $\\mathsf{P b l}_{2}$ -fabricated perovskite film, these materials have an irregular and poriferous morphology, as evidenced by the zoomed-in SEM images shown in Figure S14. To identify the spongy materials, we deposited a thin formamidinium iodide (FAI) layer on the surface of an ITO and a perovskite film, as shown in Figures S14C and S14D. We found that the morphology of both films has an extremely similar spongy shape with the perovskite film obtained using light-aged $\\mathsf{P b l}_{2}$ . This demonstrates that ${\\mathsf{P b}}^{0}$ hampered perovskite crystallization and resulted in excess FAI remaining on the surface of perovskites. XRD characteristics further certified the formation of perovskite films was hindered by the light-aged $\\mathsf{P b l}_{2}$ films (Figure 3D). The peak intensities of both perovskite and $\\mathsf{P b l}_{2}$ films (at $12.6^{\\circ}.$ ) present a declining trend, indicating the reduced crystalline quality of the perovskite and the $\\mathsf{P b l}_{2}$ films. Furthermore, confocal PL \n\n![](images/978e287a4b3edc6e7615cdfaf65d4dcb4896cc848f4e4313b201a6416a831d1d.jpg) \nFigure 3. Characterization of PSCs using light-aged $\\mathsf{P b l}_{2}$ as the precursors \n\n(A) Schematic of the fabrication process of sequential deposition using light-aged $\\mathsf{P b}|_{2}$ films as the precursors. \n(B) Top-view SEM image of a perovskite film obtained using fresh ${\\mathsf{P b l}}_{2}$ . \n(C) Top-view SEM image of a perovskite film obtained using ${\\mathsf{P b}}|_{2}$ film with light irradiation for $8\\mathfrak{h}$ . \n(D) XRD patterns of the perovskite films obtained using $\\mathsf{P b l}_{2}$ precursor films with light irradiation for $0{-}8\\ h$ . \n(E) Confocal PL microscopy image of a perovskite film obtained using fresh $\\mathsf{P b l}_{2}$ . \n(F) Confocal PL microscopy image of a perovskite film obtained using $\\mathsf{P b l}_{2}$ film with light irradiation for $8\\ h$ . \n(G) J-V curves of PSCs using different $\\mathsf{P b l}_{2}$ precursor films. \n(H) The corresponding box plots of PCEs. \n(I) Maximum power point tracking of PSCs obtained using different $\\mathsf{P b l}_{2}$ precursor films. \n\nmapping was carried out to analyze the carrier-dynamic properties of perovskite films. Compared with the fresh $\\mathsf{P b l}_{2}$ -fabricated perovskite film, the perovskite film obtained from $8\\mathfrak{h}$ -light-aged $\\mathsf{P b l}_{2}$ exhibited much weaker and dispersive PL distribution arising from the poor crystalline quality, residual FAI, and ${\\mathsf{P b}}^{0}$ impurities (Figures 3E, 3F, and S13D–S13F). \n\nIn the following, we checked the device performance of PSCs obtained from the fresh and light-aged $\\mathsf{P b l}_{2}$ films. Current density-voltage $(J-V)$ characteristics of the corresponding devices are compared in Figures 3G, 3H, and S15 and Table 1. Obviously, the fresh ${\\mathsf{P b}}|_{2}$ -based device presented the optimal performance, giving a $J_{S C}$ of $24.5\\mathsf{m A}/\\mathsf{c m}^{2}$ , a $V_{\\mathrm{OC}}$ of $\\boldsymbol{\\mathscr{1}.13\\vee}$ , an FF of $82\\%$ , and a PCE of $22.7\\%$ . Compared with the fresh ${\\mathsf{P b l}}_{2}$ -based device, the performance of the devices obtained using lightaged $\\mathsf{P b l}_{2}$ exhibited a drastic decline. For example, the solar cell assembled by a $\\mathsf{P b l}_{2}$ precursor layer with $8\\ h$ of light aging had a $J_{S C}$ of $19.1\\ \\mathrm{mA}/\\mathrm{cm}^{2}.$ , a $V_{\\mathrm{OC}}$ of $0.97~\\mathsf{V}.$ , an FF of $53\\%$ , and a PCE of $9.8\\%$ (Table 1). External quantum efficiency (EQE) spectra and integrated current densities of the corresponding devices are exhibited in Figure S16, which are consistent with the trend in $J-V$ results shown in Figure 3G. The photovoltaic parameter distribution of 10 cells for each condition is summarized in Figures 3H and S15B–S15D and Table S2, confirming the good reproducibility of the devices. Furthermore, Figure 3I compares normalized steady-state PCEs of PSCs obtained using different $\\mathsf{P b l}_{2}$ films, where we can observe that the device efficiencies drop significantly for the devices using light-aged $\\mathsf{P b l}_{2}$ films. However, all these perovskite films had similar absorption spectra (Figure S17, calculated as $\\mathsf{E}_{\\mathsf{g}}=1.54\\mathsf{e V}$ , indicating that the performance decline stems from the severe internal recombination induced by ${\\mathsf{P b}}^{0}$ . Therefore, the ${\\mathsf{P b}}^{0}$ impurities in the light-aged $\\mathsf{P b l}_{2}$ films can not only bring down device performance but also accelerate the degradation of PSCs. \n\nTable 1. Photovoltaic parameters of the best-performing PSCs using fresh and light-aged PbI2 precursor films \n\n\n
SampleVoc (M)Jsc (mA/Cm²)FF (%)PCE (%)Integrated Jsc from EQE (mA/cm²)
Fresh1.1324.582.022.723.9
2h1.0122.969.216.022.2
4 h 0.9921.662.213.321.1
6 h0.9920.357.311.520.3
8 h 0.9719.152.99.818.9
\n\nTo explore the origins of performance degradation, we performed PL and TRPL analysis to estimate the carrier recombination in perovskite films. As shown in Figures 4A and 4B, all the samples exhibited a PL peak at about $805\\mathsf{n m}$ , indicating that the main components remained $\\mathsf{F A}_{1-\\times}\\mathsf{M A}_{\\times}\\mathsf{P b l}_{3}$ perovskites even though using light-aged $\\mathsf{P b l}_{2}$ as the precursor layer. Whereas the gradually decreased PL peak of the lightaged $\\mathsf{P b l}_{2}$ -based samples manifests that the ${\\mathsf{P b}}^{0}$ serving as traps to capture carriers would lead to severely photogenerated charge carrier recombination. TRPL results show that the sample obtained from a $\\mathsf{P b l}_{2}$ film with $^{8\\ h}$ of light aging had the shortest carrier lifetime, which agrees with the PL measurements. To study the built-in potential $(V_{\\mathrm{bi}})$ of the devices, Mott-Schottky analyses of PSCs were conducted under a frequency of $1\\mathsf{k H z}$ with bias voltages ranging from 0 to $1.2\\ V.$ as shown in Figure 4C.49,50 It is shown that the $V_{\\mathrm{bi}}$ reduced from $0.85~\\mathsf{V}$ for the reference to $0.73\\mathrm{V}$ for the sample obtained using a $\\mathsf{P b l}_{2}$ film with $8h$ of light aging and the corresponding depletion width (W) decreased from 208 to $82\\mathsf{n m}$ . With a decreased $V_{\\mathrm{bi}},$ the carrier extraction was hindered by a reduced bias, hence leading to serious charge recombination and a reduced $V_{\\mathrm{OC}}$ . \n\nWe then performed temperature-dependent admittance spectroscopy (AS) under low pressure $(\\sim10\\mathsf{P a})$ to identify the location and density of the trap states in the perovskite films. The detailed relationships and analyses can be found in the experimental procedures section. The different capacitance spectra of PSCs are exhibited in Figure S18, and the corresponding derivative capacitance spectra reflecting the carrier freeze-out are shown in Figure S19. By determining the $\\omega=\\omega_{0}$ through applied AC signals with increasing temperature, we fitted the Arrhenius plots of the transition frequencies at each temperature. As presented in Figure 4D, the fitting trap activation energy $(\\mathsf{E}_{\\mathsf{a}})$ reduced from 0.25 to $0.02\\ \\mathrm{eV}$ with ${\\mathsf{P b}}^{0}$ introduction, implying easy trap migration under light irradiation. Besides, the trap migration inevitably led to ion movements which have been considered to be one of the main reasons for PSC instability.51,52 For a $\\mathsf{p}$ -type perovskite semiconductor, the thermal emission depth of trap $\\left(\\mathsf{E}_{\\mathrm{d}}\\right)$ has an energetic formula of $\\mathsf{E}_{\\mathsf{d}}=\\mathsf{E}_{\\mathsf{T}}-\\mathsf{E}_{\\mathsf{V}},$ which is the difference of trap state location and the valence band maximum.53 In Figure 4E, the differentiated capacitance spectra combined with $V_{\\mathrm{bi}}$ can yield the trap density distribution and the trap depth. As exhibited in the trap-energy distribution under room temperature of each device, trap density increased from $5.0\\times10^{16}$ for the reference device to $1.0\\times10^{17}\\mathrm{cm}^{-3}$ for the $^{8\\mathfrak{h}}$ -light-aged ${\\mathsf{P b l}}_{2}$ -based one. Moreover, the distribution of trap-state energy level shifted from 0.25 to $0.4~\\mathrm{eV}$ above the valance band maximum after loading ${\\mathsf{P b}}^{0}$ . The results predicted that the presence of ${\\mathsf{P b}}^{0}$ can significantly influence the trap distribution, mainly in increasing the trap-state density and deepening the trap-state energy. The XPS spectra of \n\n![](images/ad8f8240800333851b5423c056835412cc79cc819a98a7b285801825df443a07.jpg) \nFigure 4. Optical and electrical properties of perovskite films \n(A) PL spectra of the perovskite films using $\\mathsf{P b l}_{2}$ precursor films with light irradiation for $0{-}8\\ h$ . (B) TRPL spectra of the perovskite films using $\\mathsf{P b l}_{2}$ precursor films with light irradiation for $0{-}8\\ h$ . (C) Mott-Schottky plots of the perovskite films using $\\mathsf{P b l}_{2}$ precursor films with light irradiation for $0{-}8\\ h$ . (D) Arrhenius plots of the perovskite films using $\\mathsf{P b l}_{2}$ precursor films with light irradiation for $0{-}8\\ h$ . (E) Trap-state densities of the corresponding PSCs at room temperature. (F) Pb 4f high-resolution $\\mathsf{X P S}$ spectra of the perovskite films using $\\mathsf{P b l}_{2}$ precursor films with light irradiation for $0{-}8\\ h$ . \n\n![](images/6b017dda1ab369feaa79db30904847480a1be78c663c6bce416a324a9327baec.jpg) \nFigure 5. Performance analysis of PSCs \n\n(A) Top-view SEM image of a stoichiometric $\\mathsf{C s}_{0.06}(\\mathsf{F A}_{0.92}\\mathsf{M A}_{0.08})_{0.94}\\mathsf{P b}(\\mathsf{I}_{0.92}\\mathsf{B r}_{0.08})_{3}$ perovskite film. \n(B) Top-view SEM image of a $\\mathsf{C s}_{0.06}(\\mathsf{F A}_{0.92}\\mathsf{M A}_{0.08})_{0.94}\\mathsf{P b}(\\mathsf{I}_{0.92}\\mathsf{B r}_{0.08})_{3}$ perovskite film with $5\\mathrm{mol}\\%$ excess $\\mathsf{P b}|_{2}$ . \n(C) Top-view SEM image of a $\\mathsf{C s}_{0.06}(\\mathsf{F A}_{0.92}\\mathsf{M A}_{0.08})_{0.94}\\mathsf{P b}(\\mathsf{I}_{0.92}\\mathsf{B r}_{0.08})_{3}$ perovskite film with 5 mol $\\%$ excess $\\mathsf{P b l}_{2}$ and BABr posttreatment. \n(D) XRD patterns of the corresponding perovskite films. \n(E) J-V curves of the corresponding PSCs. \n(F) PCEs of the corresponding PSCs. \n(G) MPP tracking curves of the corresponding PSCs. \n\nthe corresponding perovskite films show that the signal of ${\\mathsf{P b}}^{0}$ gradually increases, attributed to the decomposition of $\\mathsf{P b l}_{2}$ with light aging (Figure 4F). \n\nTo further verify the effects of ${\\mathsf{P b}}^{0}$ and excess $\\mathsf{P b l}_{2}$ in general perovskites, we also fabricated mixed-cation and mixed-halide perovskites, which have been widely reported for highly efficient PSCs.3,5 Figures 5A–5C show top-view SEM images of $\\mathsf{C s}_{0.06}(\\mathsf{F A}_{0.92}\\mathsf{M A}_{0.08})_{0.94}\\mathsf{P b}(\\mathsf{I}_{0.92}\\mathsf{B r}_{0.08})_{3}$ (CsFAMA) perovskite films obtained using a stoichiometric precursor, a precursor with excess ${\\mathsf{P b l}}_{2}.$ and a precursor with excess $\\mathsf{P b l}_{2}$ plus $\\mathsf{n}$ -butylammonium bromide (BABr) posttreatment, which we labeled as stoichiometric, $5\\%\\mathsf{P b l}_{2}$ , and $5\\%{\\sf P b l}_{2}+\\mathsf{B A B r}.$ . All these films were prepared by a one-step antisolvent method. The films had similar surface morphonology but, compared with the stoichiometric perovskite film (Figure 5A), there were some bright crystals in the sample with excess $\\mathsf{P b l}_{2}$ (Figure 5B). These bright crystals should be $\\mathsf{P b l}_{2},$ which is consistent with the XRD patterns of the films (Figure 5D) and the previous reports.54 We also deposited a thin film of BABr on the surface of CsFAMA perovskites with post-annealing, which could form a 2D/3D perovskite heterostructure and enhance the device performance.16,55–57 Figure 5C shows that the surface morphology of a CsFAMA perovskite film with $5\\%$ excess $\\mathsf{P b l}_{2}$ and BABr posttreatment is slightly different, as compared with the other two samples. Atomic-force microscopy (AFM) also proved the morphology change, as shown in Figure S20. Combining SEM with XRD results in Figures 5B–5D, it seems that the $\\mathsf{P b l}_{2}$ crystals disappeared after BABr posttreatment. The as-synthesized triple-cation mixed-halide perovskite films exhibited typical XRD patterns, corresponding to the lattice of CsFAMA perovskite (Figure 5D). An additional characteristic peak of $\\mathsf{P b l}_{2}$ at $12.6^{\\circ}$ was only detected in the $5\\%$ excess $\\mathsf{P b l}_{2}$ -incorporated sample. After BABr treatment, the diffraction patterns of $\\mathsf{P b}|_{2}$ completely disappeared and other peaks below $15^{\\circ}$ can be assigned to two-dimensional Ruddlesden-Popper perovskites as reported in the literature.56,57 \n\nTable 2. Photovoltaic parameters of the best-performing CsFAMA PSCs using various perovskite light-absorbers \n\n\n
SampleVoc (V)Jsc (mA/cm²)FF (%)PCE (%)Integrated Jsc from EQE (mA/cm²)
Stoichiometric1.0924.376.020.123.6
5% Pbl21.0924.380.221.223.6
5% Pblz + BABr1.1524.480.122.523.7
\n\nWe then used these films for the fabrication of solar cells and investigated their effects on device performance. The devices employed a planar n-i-p structure using $\\mathsf{S n O}_{2}$ as an electron-transport layer and spiro-OMeTAD as a hole-transfer layer. The detail of the fabrication process is described in the experimental procedures section. $J_{-}V$ characteristics and photovoltaic parameters of the corresponding PSCs are shown in Figures 5E, 5F, and S21 and Tables 2 and S3. The presence of excess $\\mathsf{P b l}_{2}$ in PSCs improved FF from $76.0\\%$ to $80.2\\%$ and PCE from $20.1\\%$ to $21.2\\%$ (Figure 5E). The loading of mixed 2D/3D perovskites by BABr posttreatment further improved $V_{\\mathrm{OC}}$ from 1.09 to $1.15\\mathrm{V}$ and resulted in a significantly enhanced PCE of $22.5\\%$ . Meanwhile, the introduction of excess $\\mathsf{P b l}_{2}$ and BABr posttreatment in perovskite films did not change the bandgap of stoichiometric CsFAMA perovskite $(\\mathsf{E}_{\\mathsf{g}}=1.57\\ \\mathsf{e V}$ calculated from the absorption in Figure S22A) and therefore exhibited no loss in $J_{\\mathsf{S C}}$ . These results agree with the EQE results shown in Figure S22B. The integrated $J_{S C}$ of stoichiometric, excess $\\mathsf{P b l}_{2},$ and excess ${\\mathsf{P b l}}_{2}+$ BABr-based devices are 23.6, 23.6, and $23.7~\\mathsf{m A}/\\mathsf{c m}^{2}$ , respectively. To understand enhancement in $V_{\\mathrm{OC}}.$ , FF, and PCE of solar cells, we also measured PL and TRPL spectra of the corresponding films. It is worth noting that PL intensity is associated with nonradiative recombination, which gradually decreased after the perovskite films introduced excess $\\mathsf{P b l}_{2}$ and were further treated with BABr (Figure S22C). TRPL results show that the carrier lifetime of the perovskite films (Figure S22D) increased after loading excess $\\mathsf{P b}|_{2}$ and BABr treatment, which is beneficial for the FF and $V_{\\mathrm{OC}}$ in devices. \n\nThe long-term stability of the corresponding devices employing stoichiometric, excess $\\mathsf{P b l}_{2},$ and excess ${\\mathsf{P b l}}_{2}+$ BABr-based perovskite absorbers were surveyed, wherein maximum power point (MPP) tracking was recorded by measuring PSCs stored in a nitrogen-filled glovebox. Interestingly, the stability results show a different trend, as compared with the efficiency results. Figure 5G indicate that the stoichiometric and excess ${\\mathsf{P b l}}_{2}+$ BABr-based cells maintained $95\\%$ and $97\\%$ of their initial PCEs after $250~\\mathsf{h},$ , respectively. By contrast, the device with excess $\\mathsf{P b l}_{2}$ exhibited an obvious decline and only maintained $82\\%$ of its initial PCE under the same conditions. In this case, although the excess $\\mathsf{P b l}_{2}$ in PSCs had a positive influence on PCEs, it had a negative influence on light stability, which can be attributed to the light decomposition of excess $\\mathsf{P b l}_{2}$ in perovskites. The results suggest that further strategies for enhancement of the stability of PSCs should control the amount of $\\mathsf{P b l}_{2}$ and provide self-compensating A-site cations. \n\n# Conclusions \n\nIn summary, we carried out a series of experiments to investigate the origins and effects of ${\\mathsf{P b}}^{0}$ in PSCs. Studies on single $\\mathsf{P b l}_{2}$ films showed that light or X-ray irradiation would result in the decomposition of $\\mathsf{P b l}_{2}$ , leading to the formation of detrimental ${\\mathsf{P b}}^{0}$ byproducts. The ${\\mathsf{P b}}^{0}$ impurities can serve as recombination centers that increase nonradiative recombination and suppress charge carrier transfer in $\\mathsf{P b l}_{2}$ and perovskites. We used light-aged $\\mathsf{P b l}_{2}$ films with ${\\mathsf{P b}}^{0}$ impurities as the precursor layers for the fabrication of PSCs. The PCE dramatically reduced from $22.7\\%$ for the reference cell to $9.8\\%$ for the $^{8\\mathfrak{h}}$ -light-aged $\\mathsf{P b l}_{2}$ -based cells, because the ${\\mathsf{P b}}^{0}$ in the light-aged $\\mathsf{P b l}_{2}$ -assembled perovskite films not only deepen the trap-state level from 0.25 to $0.4\\mathsf{e V}$ but also increase the trap density from $5.0\\times10^{16}$ to $1.0\\times10^{17}\\mathsf{c m}^{-3}$ . Besides, the presence of ${\\mathsf{P b}}^{0}$ also hampered the perovskite crystallization and decreased the trap activation energy from 0.25 to $0.02\\ \\mathrm{eV}$ , resulting in a serious device performance deterioration. The results also showed that halide perovskite films are much more stable than their metal-halide precursors of under light or $\\mathsf{X}$ -ray irradiation. This work would suggest that further enhancements on PSC performance need to avoid the formation of excess $\\mathsf{P b l}_{2}$ and light-decomposed ${\\mathsf{P b}}^{0}$ , which should be one of the keys for realizing PSCs’ commercialization in the future. \n\n# EXPERIMENTAL PROCEDURES \n\n# Resource availability \n\nLead contact \n\nFurther information and requests for resources should be directed to and will be full filled by the lead contact, Guojia Fang (gjfang@whu.edu.cn). \n\n# Materials availability \n\nThis study did not generate new unique materials. \n\n# Data and code availability \n\nThis study did not generate any datasets or codes. The data and results supporting the current study are available from the lead contact upon reasonable request. \n\n# Materials and solvents \n\n$\\mathsf{P b l}_{2}$ $(99.9985\\%)$ ) was purchased from Tokyo Chemical Industry (TCI, Japan). $\\mathsf{P b B r}_{2}$ $(99.99\\%)$ , ${\\mathsf{P b C l}}_{2}$ $(99.99\\%)$ , cesium iodide $(\\mathsf{C s l99.99\\%})$ , MAI $(99.9\\%)$ , and methylammonium bromine (MABr $99.9\\%$ ) were purchased from Sigma Aldrich. FAI, poly[bis(4- phenyl) (2,4,6-trimethylphenyl) amine] (PTAA), GAI, DMAI, PEAI, and BABr were purchased from Xi’an Polymer Light Technology (China). Spiro-OMeTAD was purchased from Advanced Election Technology. Besides, N,N-dimethylformamide (DMF, $99.8\\%$ , dimethyl sulfoxide (DMSO, $99.7\\%$ ), IPA $(99.7\\%)$ , and chlorobenzene (CB, $99.8\\%$ ) were purchased from Sigma Aldrich. Ethyl ether $(99.5\\%)$ was purchased from Sinopharm Chemical Reagent (China). \n\n# Precursor and film preparation \n\nBefore film deposition, the etched ITO glass substrates $\\langle\\leq15\\Omega/\\mathsf{s q}\\rangle$ were washed by sonication with detergent, deionized water, acetone, and ethanol for 15 min successively. After drying with dry nitrogen, $15\\mathrm{min}$ of ultraviolet- ${{\\bf{\\cdot}}}{\\bf{O}}_{3}$ treatment was carried out before being transferred to electron transfer layer deposition. Alfa $\\mathsf{S n O}_{2}$ nanoparticle solution $(2.5\\%$ , diluted by ultrapure water, $\\leq18.2\\ \\mathsf{M}\\Omega\\cdot\\mathsf{c m})$ was spincoated on the substrates at 5,000 rpm for $20\\ \\mathsf{s},$ following annealed at $\\mathsf{180^{\\circ}C}$ for $20~\\mathrm{min}$ in the atmosphere. Subsequently, an additional 15 min of ultraviolet- ${{\\bf{\\cdot}}}{\\bf{O}}_{3}$ was treated to enhance the film wettability. The perovskite layers were prepared by antisolvent or sequentially deposition and the whole fabrication process was carried out in an ${\\sf N}_{2}$ -filled glovebox at controlled room temperature $(\\sim23^{\\circ}\\mathsf{C})$ and $H_{2}O$ and oxygen level $:\\leq0.1$ ppm, $\\leq0.1\\ \\mathsf{p p m})$ . After that, a solution of spiro-OMeTAD dissolved in CB $(72.3\\ m g/\\ m L)$ with the addition of $17.5~\\upmu\\up L$ Li-TFSI/acetonitrile $(520~\\mathrm{mg/mL})$ , and $28.8~\\upmu\\up L$ 4-tertbutylpyridine was deposited at 3,000 rpm for $30\\mathrm{~s~}$ by spin coating without further annealing. Finally, $60~\\mathsf{n m}$ of Au was deposited by thermal evaporation under $2.0\\times10^{-4}$ Pa vacuum pressure. \n\n# The perovskite films fabricated by an antisolvent process MAPbI3 \n\nA $1.5{\\mathsf{M}}$ stoichiometric perovskite precursor solution was obtained by dissolving MAI (1.5M) and $\\mathsf{P b l}_{2}$ (1.5 M) in a mixed solvent of DMF:DMSO $=10:1$ (v:v). $2m o l\\%$ or $5\\mathrm{mol}\\%\\mathsf{P b l}_{2}$ was added into a stoichiometric $\\mathsf{M A P b l}_{3}$ perovskite solution to form $\\mathsf{M A P b l}_{3}$ films with excess $\\mathsf{P b l}_{2}$ . The ${\\mathsf{M A P b}}{\\mathsf{b}}_{3}$ films were deposited on the pre-fabricated $\\mathsf{S n O}_{2}/|\\mathsf{T O}$ substrates by a one-step spin-coating process: keeping 4,000 rpm for 30 s and dropping $400~\\upmu\\up L$ of antisolvent (e.g., diethyl ether) at the $23^{\\mathsf{r d}}$ s to form wet perovskite precursor films after spin coating. After that, the as-prepared perovskite films were annealed on a hot plate at $100^{\\circ}\\mathsf C$ for 10 min in an ${\\sf N}_{2}.$ - filled glovebox. To remove excess $\\mathsf{P b l}_{2}$ in perovskites, MAI/IPA solutions (e.g., 3 or $6~\\mathrm{mg/mL})$ were spin-coated on the surface of perovskites at 3,000 rpm for $30\\mathrm{~s~}$ and then annealed at $\\mathsf{100^{\\circ}C}$ for $3\\mathrm{\\min}$ . And for other low-dimensional perovskitemodified samples, organic cation solutions (i.e., GAI, DMAI, and PEAI, $20~\\mathsf{m M}$ dissolved in IPA) were spin-coated on the fabricated perovskite films at 3,000 rpm for 30 s and then annealed at $\\mathsf{100^{\\circ}C}$ for $5\\mathrm{{min}}$ . \n\n# $\\begin{array}{r}{C s_{0.06}(F\\mathsf{A}_{0.92}M\\mathsf{A}_{0.08})_{0.94}P b(I_{0.92}B r_{0.08})_{3}}\\end{array}$ \n\nA $1.4~\\mathsf{M}$ stoichiometric perovskite precursor solution was obtained by dissolving ${\\mathsf{P b l}}_{2},$ , $\\mathsf{P b B r}_{2},$ MABr, FAI, and CsI with $1\\ m o l\\ \\%$ KI additive in a mixed solvent of DMF and DMSO $(4;1/\\upnu;\\upnu)$ . Extra $5\\mathrm{\\mol\\\\%}\\mathsf{P b l}_{2}$ was added into the stoichiometric mixed-cation perovskite solution for the excess $\\mathsf{P b l}_{2}$ . For BABr solution, BABr was dissolved into IPA solvent with a concentration of $2\\ m g/\\mathsf{m L}$ . The perovskite films (with or without excess $\\mathsf{P b}|_{2})$ were deposited on the pre-fabricated $\\mathsf{S n O}_{2}/|\\mathsf{T O}$ substrates by a two-step spin-coating process: first at 1,000 rpm for 5 s with a ramp of $5,000\\ \\mathrm{rpm/s},$ , and then at 5,000 rpm for $45\\mathrm{~s~}$ with a ramp of $10,000\\ \\mathrm{rpm/s}$ . At the $15^{\\mathrm{th}}$ s of the spin coating, $120~\\upmu\\upiota$ of antisolvent (e.g., CB) was dripped to form a wet perovskite precursor film. Then, the as-prepared perovskite films were annealed on a hot plate at $65^{\\circ}\\mathsf{C}$ for 2 min and $120^{\\circ}\\mathsf C$ for $10\\min$ in an ${\\sf N}_{2}$ -filled glovebox. For BABr treatment, $50~\\upmu\\up L$ of BABr/IPA solution was spin-coated on the perovskite surface at 3,000 rpm for 30 s after the film cooling to room temperature and followed by thermal annealing at $100^{\\circ}\\mathsf C$ for $5\\mathrm{{min}}$ . \n\n# The perovskite films fabricated by a sequential deposition process $F A_{1-x}M A_{x}P b I_{3}$ \n\nA $1.3\\mathsf{M P b l}_{2}$ solution dissolved in a mixed solvent of DMF:DMSO $=9:1$ (v:v) was used for spin coating at 1,500 rpm for $30\\mathsf{s},$ and then annealed at $70^{\\circ}\\mathsf{C}$ for 1 min in an ${\\sf N}_{2}$ - filled glovebox. For light-aged samples, the as-fabricated $\\mathsf{P b l}_{2}$ films were put on the platform under simulated one-sun AM 1.5G illumination for different h (e.g., 2, 4,.8 h). After the light-aging process, a mixed solution of FAI:MAI:MACl (90:6.5:9 mg in IPA) was spin-coated on the surface of $\\mathsf{P b l}_{2}$ at 1,500 rpm for $30\\mathsf{s}$ , and then annealed at $150^{\\circ}\\mathsf C$ for $15\\mathrm{min}$ in the atmosphere with controlled humidity $(\\sim30\\%)$ . For FAI posttreated perovskite film, a $50~\\upmu\\up L$ solution of FAI $(60~\\mathrm{mg/mL)}$ was spin-coated on the surface of perovskite at 3,000 rpm for $30\\thinspace s$ and annealed at $\\mathsf{100^{\\circ}C}$ for $5\\mathrm{\\min}$ . Then, the perovskite samples were transferred to an ${\\sf N}_{2}$ -filled glovebox for further processing. \n\n# Characterization and analysis Film characterization \n\nThe morphology of the films was observed by SEM (Zeiss SIGMA) with an accelerating voltage of $15\\mathsf{k V}$ . The crystal lattice and element distribution were investigated using high-resolution TEM (JEM-F200) and EDS mapping (JEM-F200) with an accelerating voltage of $200\\mathsf{k V}.$ . AFM images of perovskites were carried out by using the Bruker dimension icon under peak force mode. Absorption spectra of films were carried out using a spectrophotometer (UV-vis, mini UV-1208 model, Shimadzu). PL spectra of perovskite films were measured using a DeltaFlex fluorescence spectrometer (HORIBA) with a center wavelength of $481~\\mathsf{n m}$ semiconductor laser and TRPL was carried out with time-correlated single-photon counting (TCSPC) module. PL (excitation at $400\\ \\mathsf{n m}$ ) and TRPL of $\\mathsf{P b l}_{2}$ films were measured with an Edinburgh Instrument (FLSP980). The crystallographic films were measured by grazing incidence X-ray diffraction (GIXRD) instrument (D8 Discover, Bruker) with $40\\mathsf{k V},40\\mathsf{m A}$ radiation $(\\mathsf{C u K}\\alpha,\\lambda=0.15406\\mathsf{n m}$ , incident slit $=0.1~\\mathsf{m m}$ , receiving slit $=20\\mathsf{m m}$ , incident angle [center] $=3^{\\circ}$ , scan speed $=5^{\\circ}/\\mathsf{m i n}^{\\dag}$ ). \n\nConfocal microscopy imaging was acquired using a wide-filed, hyperspectral imaging microscope system (TCS SP8, Leica). A wavelength of $552\\mathsf{n m}$ solid-state laser was employed as a PL excitation source, and a charge-coupled-device (CCD) array detector having a detection range from 700 to $800~\\mathsf{n m}$ was used for PL detection. The signal collection area for each film was 100 $(10\\times10)~\\upmu\\mathrm{m}^{2}$ . \n\nX-ray aging measurements were carried out by a miniature X-ray tube system, which includes a Mini- $.{\\big.}\\times2{\\big.}\\times.$ -ray tube module and controller (AMPTEK). The Mini- $.{\\times}2$ generates X-ray radiation with tungsten (W) as the anode material. We used a tube voltage of $35\\mathsf{k V}$ and a tube current of $20\\upmu\\mathsf{A}$ to irradiate the perovskite films (with or without excess $\\mathsf{P b}|_{2})$ for $5\\mathfrak{h}$ . The distance was about $30~\\mathsf{m m}$ between the samples and the X-ray source, where the X-ray dose rate was $3.65~\\mathrm{{mGy/s}}$ during our testing. \n\nFemtosecond optical spectroscopy was obtained from the Ultrafast System HELIOSTM TA spectrometer. The laser source was a Coherent Legend regenerative amplifier (150 fs, $1\\ k H z,800\\mathsf{n m}.$ ) seeded by a Coherent Vitesse oscillator (100 fs, 80 MHz). The broadband probe pulses $(420-800\\ \\mathrm{nm})$ ) were generated by focusing a small portion of the fundamental $800~\\mathsf{n m}$ laser pulses into a $2\\:\\mathrm{mm}$ sapphire plate. $400\\ \\mathsf{n m}$ wavelength laser pulses were obtained through a BBO doubling crystal from an $800\\mathsf{n m}$ femtosecond laser. The dynamics can be described by: \n\n$$\n\\begin{array}{r}{\\mathsf{y}=\\mathsf{A}_{1}\\mathsf{e}^{(-\\mathrm{{t}}/\\tau_{1})}+\\mathsf{A}_{2}\\mathsf{e}^{(-\\mathrm{{t}}/\\tau_{2})}+\\mathsf{A}_{3}\\mathsf{e}^{(-\\mathrm{{t}}/\\tau_{3})}}\\end{array}\n$$ \n\nwhere $\\boldsymbol{\\tau}_{1}$ represents hot carrier process, $\\tau_{2}$ represents carrier charge transfer process, and $\\tau_{3}$ represents free electron-hole recombination process. \n\nXPS measurements were performed by an ESCALAB 250Xi (Thermo Scientific, USA) with a monochromatic magnesium- $\\mathsf{K}\\mathsf{\\alpha}$ X-ray gun (400 W, $\\uplambda=1.254\\mathrm{keV})$ in an ultrahigh vacuum chamber $(\\sim10^{-6}\\mathsf{P a})$ . And the XPS spectra were analyzed using Thermo Scientific Avantage software. All test samples were prepared in an ${\\sf N}_{2}$ -filled glovebox with controlled humidity and oxygen level $\\mathsf{\\Lambda}^{\\prime}\\leq0.1\\mathsf{p p m})$ . The shift of binding energy was referenced to the C 1s peak at $284.8~\\mathrm{eV}$ of the surface adventitious carton. \n\n# Device characterization \n\nEQE measurements were performed with a QE/IPCE system (Enli Technology). J-V curves of the PSCs were measured under air mass 1.5 global (AM 1.5 G) conditions (Enli Technology) in a nitrogen atmosphere. All of the devices were measured by masking the active area $(0.1188~\\mathrm{cm}^{2})$ with a metal mask (the certified area is $0.0578\\ {\\mathsf{c m}}^{2}.$ ). J-V measurements were performed with a scan rate of $20\\mathrm{\\mV}{\\cdot}\\mathsf{s}^{-1}$ ranging from 1.2 to $-0.1\\vee$ and then reversed again from $-0.1$ to $1.2\\lor$ with a dwell time of $25~\\mathsf{m s}$ . \n\n# Stability measurements \n\nAll of the unencapsulated perovskite devices were aged in a multichannel thin-film photovoltaic attenuation test system (PVLT-6001X-16B, Suzhou D&R Instruments). Given that the Li-TFSI doped spiro-OMeTAD would influence the stability of devices, we employed a PTAA HTL prepared using a $20~\\mathrm{mg/mL}$ PTAA solution in our stability measurements. The devices were performed MPP under illumination (white LED source, $70\\mathsf{m}\\mathsf{W}\\mathsf{\\cdot c m}^{-2}$ , wavelength range from 400 to $850\\mathsf{n m}$ ) with one test cycle every 15 s at an average temperature of about $30^{\\circ}\\mathsf{C}$ (glovebox temperature is kept about $25^{\\circ}\\mathsf{C})$ in an ${\\sf N}_{2}$ -filled glovebox. The loaded resistance values ranged from $5\\Omega$ to $10\\ k\\Omega,$ the loaded voltage values ranged from $^{-2}$ to $2\\mathsf{V},$ and one source meter matched with each device, respectively. $J-V$ measurements were carried out with a scan rate of $15\\mathrm{mV}{\\cdot}{\\mathsf{s}}^{-1}$ ranging from 1,200 to $-50~\\mathrm{mV}$ and scan cycle set as every 60 min. \n\n# Admittance characterization \n\nMott-Schottky curves with capacitance-voltage measurements were performed by a CHI760E electrochemical workstation (Shanghai Chenhua Instruments) at $1\\mathsf{k H z}$ with bias voltages ranging from 1.4 to 0 V and an AC voltage of $20\\mathsf{m}\\mathsf{V}$ was used to test the corresponding capacitance at shifty bias voltage. AS measurements were performed with a CHI760E electrochemical workstation (Shanghai Chenhua Instruments) at different temperatures ranging from 250 to $3201\\mathrm{K}$ in the dark at a relatively low vacuum $(\\sim10\\mathsf{P a})$ with a small AC disturbed voltage of $20\\mathsf{m}\\mathsf{V}.$ . The frequency scope from 1 to $100~\\mathsf{k H z}$ and a DC bias voltage of $0\\vee$ was kept during the measurements. The relationship can be derived by the following equation. \n\n$$\n\\mathsf E_{\\varepsilon}=\\mathsf k_{\\mathsf{B}}\\mathsf T\\mathsf{L}\\mathsf{n}\\left(\\frac{\\mathsf{B}\\mathsf{T}^{2}}{\\omega}\\right)\n$$ \n\n$$\n{\\sf N}_{\\sf T}(\\sf E_{\\omega})=-\\frac{\\sf V_{\\mathrm{bi}}}{\\sf q W k_{\\mathrm{B}}T}\\bullet\\frac{\\omega\\mathrm{dC}}{\\mathrm{d}\\omega}\n$$ \n\nwhere $\\omega_{0}$ is the characteristic transition angular frequency, $\\upbeta$ is the temperature parameter, and $\\mathsf{E}_{\\mathsf{a}}$ is the activation energy of the trap. The built-in potential $(\\mathsf{V}_{\\mathrm{bi}})$ and the depletion width $(\\mathsf{W})$ in the perovskite layers can be estimated by the following depletion approximation equation (Mott-Schottky): \n\n$$\n\\frac{\\mathsf{A}^{2}}{\\mathsf{C}^{2}}=\\frac{2(\\mathsf{V}_{\\mathsf{b i}}-\\mathsf{V})}{\\mathsf{q}\\mathsf{\\varepsilon}\\varepsilon_{0}\\mathsf{N}_{\\mathsf{B}}}\n$$ \n\nwhere A, C, N, and $\\vee$ are the active area, capacitance, doping profile, and applied bias voltage, respectively. The linear region of the Mott-Schottky plots describes the property of the depletion layer, where the intersection with the bias voltage \n\ngives $\\mathsf{V}_{\\mathsf{b i}}$ and the slope determines the doping density $\\mathsf{N}$ in perovskites. The depletion width can be obtained according to the following equation: \n\n$$\n\\mathsf{W}=\\sqrt{\\frac{2\\varepsilon\\varepsilon_{0}\\mathsf{V}_{\\mathrm{bi}}}{\\mathsf{q N}_{\\mathrm{B}}}}\n$$ \n\nThe dissociation energies of $\\mathsf{P b B r}_{2}$ and ${\\mathsf{P b C l}}_{2}$ can be estimated by the following equations: \n\n$$\n\\begin{array}{r}{\\mathsf{P b B r_{2}\\xrightarrow{3.06~\\mathsf{e V}}\\mathsf{P b}^{0}+2\\mathsf{B r}~\\uparrow}}\\\\ {\\mathsf{P b C l_{2}\\xrightarrow{3.19~\\mathsf{e V}}\\mathsf{P b}^{0}+2\\mathsf{C l}~\\uparrow}}\\end{array}\n$$ \n\n(Equation 4) \n\n# SUPPLEMENTAL INFORMATION \n\nSupplemental information can be found online at https://doi.org/10.1016/j.joule. \n2022.03.005. \n\n# ACKNOWLEDGMENTS \n\nThis work was supported by the National Natural Science Foundation of China (grant numbers 62074117, 61904126, 12134010, and 12174290), the Shenzhen Fundamental Research Program (grant number JCYJ20190808152609307), the Fundamental Research Funds for the Central Universities (grant number 2042021kf0228), and the Natural Science Foundation of Hubei Province, China (grant numbers 2019AAA020 and 2021CFB039). \n\n# AUTHOR CONTRIBUTIONS \n\nJ.L. and W.K. formulated experimental planning experiments and conducted experiments and data analysis. X.H., C.W., C.C., M.X., J.L., C.T., and R.Y. assisted the experimental process. C.L. and G.X. tested and analyzed transient absorption spectra. This work was supported by funding acquisition from C.T., W.K., and G.F. The original draft was written by J.L. and G.F. The manuscript was reviewed and edited by G.F. \n\n# DECLARATION OF INTERESTS \n\nThe authors declare no competing interests. \n\nReceived: October 18, 2021 \nRevised: January 19, 2022 \nAccepted: March 17, 2022 \nPublished: April 12, 2022 \n\n# REFERENCES \n\n1. Kojima, A., Teshima, K., Shirai, Y., and Miyasaka, T. (2009). Organometal halide perovskites as visible-light sensitizers for photovoltaic cells. J. Am. Chem. Soc. 131, 6050–6051. \n2. Yang, W.S., Noh, J.H., Jeon, N.J., Kim, Y.C. Ryu, S., Seo, J., and Seok, S.I. (2015). SOLAR CELLS. High-performance photovoltaic perovskite layers fabricated through intramolecular exchange. Science 348, 1234–1237. \n3. Yang, X., Luo, D., Xiang, Y., Zhao, L., Anaya, M., Shen, Y., Wu, J., Yang, W., Chiang, Y.H., Tu, Y., et al. (2021). Buried interfaces in halide perovskite photovoltaics. Adv. Mater. 33, e2006435. \n4. Wang, Y., Wu, T., Barbaud, J., Kong, W., Cui, D., Chen, H., Yang, X., and Han, L. (2019). Stabilizing heterostructures of soft perovskite semiconductors. Science 365, \n687–691. \n5. Li, N., Niu, X., Li, L., Wang, H., Huang, Z., Zhang, Y., Chen, Y., Zhang, X., Zhu, C., Zai, H., et al. (2021). Liquid medium annealing for fabricating durable perovskite solar cells with improved reproducibility. Science 373, \n561–567. \n\n6. NREL. Research cell efficiency records, NREL. https://www.nrel.gov/pv/cell-efficiency.html. 7. Richter, A., M ¨uller, R., Benick, J., Feldmann, F., Steinhauser, B., Reichel, C., Fell, A., Bivour, M., Hermle, M., and Glunz, S.W. (2021). Design rules for high-efficiency both-sides-contacted silicon solar cells with balanced charge carrier transport and recombination losses. Nat. Energy 6, 429–438. 8. Cai, B., Xing, Y., Yang, Z., Zhang, W.H., and Qiu, J. (2013). High performance hybrid solar cells sensitized by organolead halide perovskites. Energy Environ. Sci. 6, 1480–1485. \n\n9. Chen, W., Zhou, Y., Wang, L., Wu, Y., Tu, B., Yu, B., Liu, F., Tam, H.-W., Wang, G., Djuris\u0001ic\u0003, A.B., et al. (2018). Molecule-doped nickel oxide: verified charge transfer and planar inverted mixed cation perovskite solar cell. Adv. Mater. 30, e1800515. \n10. Fu, P., Hu, S., Tang, J., and Xiao, Z. (2021). Material exploration via designing spatial arrangement of octahedral units: a case study of lead halide perovskites. Front. Optoelectron. 14, 252–259. \n11. Liang, C., Gu, H., Xia, J., Mei, S., Pang, P., Zhang, N., Guo, J., Guo, R., Shen, Y., Yang, S., et al. (2021). Recent progress in perovskitebased reversible photon-electricity conversion devices. Adv. Funct. Mater. 32, 2108926. \n12. Song, Z., Watthage, S.C., Phillips, A.B., Tompkins, B.L., Ellingson, R.J., and Heben, M.J. (2015). Impact of processing temperature and composition on the formation of methylammonium lead iodide perovskites. Chem. Mater. 27, 4612–4619. \n13. Jeong, J., Kim, M., Seo, J., Lu, H., Ahlawat, P., Mishra, A., Yang, Y., Hope, M.A., Eickemeyer, F.T., Kim, M., et al. (2021). Pseudo-halide anion engineering for a-FAPbI3 perovskite solar cells. Nature 592, 381–385. \n14. Zhang, W., Pathak, S., Sakai, N., Stergiopoulos, T., Nayak, P.K., Noel, N.K., Haghighirad, A.A., Burlakov, V.M., deQuilettes, D.W., Sadhanala, A., et al. (2015). Enhanced optoelectronic quality of perovskite thin films with hypophosphorous acid for planar heterojunction solar cells. Nat. Commun. 6, 10030. \n15. Chavan, R.D., Prochowicz, D., Tavakoli, M.M., Yadav, P., and Hong, C.K. (2020). Surface treatment of perovskite layer with guanidinium iodide leads to enhanced moisture stability and improved efficiency of perovskite solar cells. Adv. Mater. Interfaces 7, 2000105. \n16. Jiang, Q., Zhao, Y., Zhang, X., Yang, X., Chen, Y., Chu, Z., Ye, Q., Li, X., Yin, $Z.,$ and You, J. (2019). Surface passivation of perovskite film for efficient solar cells. Nat. Photon. 13, 460–466. \n17. Ono, L.K., Liu, S.F., and Qi, Y. (2020). Reducing detrimental defects for high-performance metal halide perovskite solar cells. Angew. Chem. Int. Ed. Engl. 59, 6676–6698. \n18. Juarez-Perez, E.J., Ono, L.K., Maeda, M., Jiang, Y., Hawash, Z., and Qi, Y. (2018). Photodecomposition and thermal decomposition in methylammonium halide lead perovskites and inferred design principles to increase photovoltaic device stability. J. Mater. Chem. A 6, 9604–9612. \n19. Meng, L., You, J., and Yang, Y. (2018). Addressing the stability issue of perovskite solar cells for commercial applications. Nat. Commun. 9, 5265. \n20. Song, Z., McElvany, C.L., Phillips, A.B., Celik, I., Krantz, P.W., Watthage, S.C., Liyanage, G.K., Apul, D., and Heben, M.J. (2017). A technoeconomic analysis of perovskite solar module manufacturing with low-cost materials and techniques. Energy Environ. Sci. 10, 1297– 1305. \n21. Weerasinghe, H.C., Dkhissi, Y., Scully, A.D., Caruso, R.A., and Cheng, Y.-B. (2015). Encapsulation for improving the lifetime of flexible perovskite solar cells. Nano Energy 18, 118–125. \n22. Li, Y., Xu, X., Wang, $\\mathsf{C}_{\\cdot,\\prime}$ Ecker, B., Yang, J., Huang, J., and Gao, Y. (2017). Light-induced degradation of CH3NH3PbI3 hybrid perovskite thin film. J. Phys. Chem. C 121, 3904–3910. \n23. Yuan, Y., and Huang, J. (2016). Ion migration in organometal trihalide perovskite and its impact on photovoltaic efficiency and stability. Acc. Chem. Res. 49, 286–293. \n24. Bi, E., Chen, H., Xie, F., Wu, Y., Chen, W., Su, Y., Islam, A., Gra¨ tzel, M., Yang, X., and Han, L. (2017). Diffusion engineering of ions and charge carriers for stable efficient perovskite solar cells. Nat. Commun. 8, 15330. \n25. Dawood, R.I., Forty, A.J., Tubbs, M.R., and Frank, F.C. (1965). The photodecomposition of lead iodide. Proc. R. Soc. A: Math. Phys. Eng. Sci. 284, 272–288. \n26. Wang, R., Xue, J., Wang, K.-L., Wang, Z.-K., Luo, Y., Fenning, D., Xu, G., Nuryyeva, S., Huang, T., Zhao, Y., et al. (2019). Constructive molecular configurations for surface-defect passivation of perovskite photovoltaics. Science 366, 1509–1513. \n27. Wang, H., Wang, Z., Yang, Z., Xu, Y., Ding, Y., Tan, L., Yi, C., Zhang, Z., Meng, K., Chen, G., et al. (2020). Ligand-modulated excess PbI2 nanosheets for highly efficient and stable perovskite solar cells. Adv. Mater. 32, 2000865. \n28. Roose, B., Dey, K., Chiang, Y.-H., Friend, R.H., and Stranks, S.D. (2020). Critical assessment of the use of excess lead iodide in lead halide perovskite solar cells. J. Phys. Chem. Lett. 11, 6505–6512. \n29. Tang, X., Brandl, M., May, B., Levchuk, I., Hou, Y., Richter, M., Chen, H., Chen, S., Kahmann, S., Osvet, A., et al. (2016). Photoinduced degradation of methylammonium lead triiodide perovskite semiconductors. J. Mater. Chem. A 4, 15896–15903. \n30. Wang, L., Zhou, H., Hu, J., Huang, B., Sun, M., Dong, B., Zheng, G., Huang, Y., Chen, Y., Li, L., et al. (2019). A Eu3+-Eu2+ ion redox shuttle imparts operational durability to Pb-I perovskite solar cells. Science 363, 265–270. \n31. Tumen-Ulzii, G., Qin, C., Klotz, D., Leyden, M.R., Wang, P., Auffray, M., Fujihara, T., Matsushima, T., Lee, J.-W., Lee, S.-J., et al. (2020). Detrimental effect of unreacted PbI2 on the long-term stability of perovskite solar cells. Adv. Mater. 32, e1905035. \n32. Jacobsson, T.J., Correa-Baena, J.-P., Halvani Anaraki, E., Philippe, B., Stranks, S.D., Bouduban, M.E.F., Tress, W., Schenk, K., Teuscher, J., Moser, J.-E., et al. (2016). Unreacted PbI2 as a double-edged sword for enhancing the performance of perovskite solar cells. J. Am. Chem. Soc. 138, 10331–10343. \n33. Cappel, U.B., Svanstro¨ m, S., Lanzilotto, $\\mathsf{V}_{\\cdot,\\prime}$ Johansson, F.O.L., Aitola, K., Philippe, B., Giangrisostomi, E., Ovsyannikov, R., Leitner, T., F ¨ohlisch, A., et al. (2017). Partially reversible photoinduced chemical changes in a mixedion perovskite material for solar cells. ACS Appl. Mater. Interfaces 9, 34970–34978. \n34. Chun-Ren Ke, J., Walton, A.S., Lewis, D.J., Tedstone, A., O’Brien, P., Thomas, A.G., and Flavell, W.R. (2017). In situ investigation of degradation at organometal halide perovskite surfaces by X-ray photoelectron spectroscopy at realistic water vapour pressure. Chem. Commun. (Camb) 53, 5231–5234. \n35. Lin, W.-C., Lo, W.-C., Li, J.-X., Wang, Y.-K., Tang, J.-F., and Fong, Z.-Y. (2021). In situ XPS investigation of the X-ray-triggered decomposition of perovskites in ultrahigh vacuum condition. npj Mater. Degrad. 5, 13. \n36. McGettrick, J.D., Hooper, K., Pockett, A. Baker, J., Troughton, J., Carnie, M., and Watson, T. (2019). Sources of Pb(0) artefacts during XPS analysis of lead halide perovskites. Mater. Lett. 251, 98–101. \n37. Yin, W.-J., Shi, T., and Yan, Y. (2014). Unusual defect physics in CH3NH3PbI3 perovskite solar cell absorber. Appl. Phys. Lett. 104, 063903. \n38. Kim, Y.C., Jeon, N.J., Noh, J.H., Yang, W.S., Seo, J., Yun, J.S., Ho-Baillie, A., Huang, S., Green, M.A., Seidel, J., et al. (2016). Beneficial effects of PbI2 incorporated in organo-lead halide perovskite solar cells. Adv. Energy Mater. 6, 1502104. \n39. Shi, B., Yao, X., Hou, F., Guo, S., Li, Y., Wei, C., Ding, Y., Li, Y., Zhao, Y., and Zhang, X. (2018). Unraveling the passivation process of PbI2 to enhance the efficiency of planar perovskite solar cells. J. Phys. Chem. C 122, 21269–21276. \n40. Liu, F., Dong, Q., Wong, M.K., Djuris\u0001i\u0003c, A.B., Ng, A., Ren, Z., Shen, Q., Surya, C., Chan, W.K., Wang, J., et al. (2016). Is excess PbI2 beneficial for perovskite solar cell performance? Adv. Energy Mater. 6, 1502206. \n41. Donakowski, A., Miller, D.W., Anderson, N.C., Ruth, A., Sanehira, E.M., Berry, J.J., Irwin, M.D., Rockett, A., and Steirer, K.X. (2021). Improving photostability of cesium-doped formamidinium lead triiodide perovskite. ACS Energy Lett. 6, 574–580. \n42. Ke, W., Xiao, C., Wang, C., Saparov, B., Duan, H.-S., Zhao, D., Xiao, Z., Schulz, P., Harvey, S.P., Liao, W., et al. (2016). Employing lead thiocyanate additive to reduce the hysteresis and boost the fill factor of planar perovskite solar cells. Adv. Mater. 28, 5214–5221. \n43. Benavides-Garcia, M., and Balasubramanian, K. (1994). Bond energies, ionization potentials, and the singlet-triplet energy separations of SnCl2, SnBr2, SnI2, PbCl2, PbBr2, $P\\mathsf{b}\\mathsf{l}_{2},$ and their positive ions. J. Chem. Phys. 100, 2821–2830. \n44. Emara, J., Schnier, T., Pourdavoud, N., Riedl, T., Meerholz, $\\mathsf{K}_{\\cdot,\\prime}$ and Olthof, S. (2016). Impact of film stoichiometry on the ionization energy and electronic structure of CH3NH3PbI3 perovskites. Adv. Mater. 28, 553–559. \n45. Nickel, N.H., Lang, F., Brus, V.V., Shargaieva, O., and Rappich, J. (2017). Unraveling the lightinduced degradation mechanisms of CH3NH3PbI3 perovskite films. Adv. Electron. Mater. 3, 1700158. \n46. Song, Z., Wang, C., Phillips, A.B., Grice, C.R., Zhao, D., Yu, Y., Chen, C., Li, C., Yin, X., Ellingson, R.J., et al. (2018). Probing the origins of photodegradation in organic-inorganic metal halide perovskites with time-resolved mass spectrometry. Sustainable Energy Fuels 2, 2460–2467. \n47. Ke, W., Spanopoulos, I., Stoumpos, C.C., and Kanatzidis, M.G. (2018). Myths and reality of HPbI3 in halide perovskite solar cells. Nat. Commun. 9, 4785. \n48. Zhang, J., Qin, J., Wang, M., Bai, Y., Zou, H., Keum, J.K., Tao, R., Xu, H., Yu, H., Haacke, S et al. (2019). Uniform permutation of quasi-2d perovskites by vacuum poling for efficient, high-fill-factor solar cells. Joule 3, 3061–3071. \n49. Ye, S., Rao, H., Zhao, Z., Zhang, L., Bao, H., Sun, W., Li, Y., Gu, F., Wang, J., Liu, Z., et al. (2017). A breakthrough efficiency of $19.9\\%$ obtained in inverted perovskite solar cells by using an efficient trap state passivator Cu(thiourea)I. J. Am. Chem. Soc. 139, 7504–7512. \n50. Li, N., Tao, S., Chen, Y., Niu, X., Onwudinanti, C.K., Hu, C., Qiu, Z., Xu, Z., Zheng, G., Wang, L., et al. (2019). Cation and anion immobilization through chemical bonding enhancement with fluorides for stable halide perovskite solar cells. Nat. Energy 4, 408–415. \n51. Slotcavage, D.J., Karunadasa, H.I., and McGehee, M.D. (2016). Light-induced phase segregation in halide-perovskite absorbers. ACS Energy Lett. 1, 1199–1205. \n52. Yang, J., Tang, W., Yuan, R., Chen, Y., Wang, J., Wu, Y., Yin, W.-J., Yuan, N., Ding, J., and Zhang, W.-H. (2020). Defect mitigation using d-penicillamine for efficient methylammoniumfree perovskite solar cells with high operational stability. Chem. Sci. 12, 2050–2059. \n53. Duan, H.-S., Zhou, H., Chen, Q., Sun, P., Luo, S., Song, T.-B., Bob, B., and Yang, Y. (2015). The identification and characterization of defect states in hybrid organic-inorganic perovskite photovoltaics. Phys. Chem. Chem. Phys. 17, 112–116. \n54. Luo, D., Yang, W., Wang, Z., Sadhanala, A., Hu, $\\scriptstyle\\mathbf{\\bigcirc}.,$ Su, R., Shivanna, R., Trindade, G.F., Watts, J.F., Xu, $Z.,$ et al. (2018). Enhanced photovoltage for inverted planar \n\nheterojunction perovskite solar cells. Science 360, 1442–1446. \n\n55. Zhou, Y., Wang, F., Cao, Y., Wang, J.-P., Fang, H.-H., Loi, M.A., Zhao, N., and Wong, C.-P. (2017). Benzylamine-treated wide-bandgap perovskite with high thermal-photostability and photovoltaic performance. Adv. Energy Mater. 7, 1442–1446. \n56. Yang, G., Ren, Z., Liu, K., Qin, M., Deng, W. Zhang, H., Wang, H., Liang, J., Ye, F., Liang, Q. et al. (2021). Stable and low-photovoltage-loss perovskite solar cells by multifunctional passivation. Nat. Photon. 15, 681–689. \n57. Duong, T., Pham, H., Yin, Y., Peng, J., Mahmud, M.A., Wu, Y., Shen, H., Zheng, $\\mathsf{J}_{\\cdot,\\prime}$ Tran-Phu, T., Lu, T., et al. (2021). Efficient and stable wide bandgap perovskite solar cells through surface passivation with long alkyl chain organic cations. J. Mater. Chem. A 9, 18454–18465. " + }, + { + "id": "10.1038_s41467-022-28011-6", + "DOI": "10.1038/s41467-022-28011-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-28011-6", + "Relative Dir Path": "mds/10.1038_s41467-022-28011-6", + "Article Title": "Completely aqueous processable stimulus responsive organic room temperature phosphorescence materials with tunable afterglow color", + "Authors": "Li, D; Yang, YJ; Yang, J; Fang, MM; Tang, BZ; Li, Z", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Stimuli responsive luminescent materials are important in applied research but many of these materials are based on fluorescent stimuli responsive materials. Here, the authors report a stimulus-responsive room temperature phosphorescent materials composed of a phosphorescent chromophore of arylboronic acid and poly(vinylalcohol) with color tunable and water process able properties. Many luminescent stimuli responsive materials are based on fluorescence emission, while stimuli-responsive room temperature phosphorescent materials are less explored. Here, we show a kind of stimulus-responsive room temperature phosphorescence materials by the covalent linkage of phosphorescent chromophore of arylboronic acid and polymer matrix of poly(vinylalcohol). Attributed to the rigid environment offered from hydrogen bond and B-O covalent bond between arylboronic acid and poly(vinylalcohol), the yielded polymer film exhibits ultralong room temperature phosphorescence with lifetime of 2.43 s and phosphorescence quantum yield of 7.51%. Interestingly, the RTP property of this film is sensitive to the water and heat stimuli, because water could destroy the hydrogen bonds between adjacent poly(vinylalcohol) polymers, then changing the rigidity of this system. Furthermore, by introducing another two fluorescent dyes to this system, the color of afterglow with stimulus response effect could be adjusted from blue to green to orange through triplet-to-singlet Forster-resonullce energy-transfer. Finally, due to the water/heat-sensitive, multicolor and completely aqueous processable feature for these three afterglow hybrids, they are successfully applied in multifunctional ink for anti-counterfeit, screen printing and fingerprint record.", + "Times Cited, WoS Core": 322, + "Times Cited, All Databases": 329, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000744540800018", + "Markdown": "# Completely aqueous processable stimulus responsive organic room temperature phosphorescence materials with tunable afterglow color \n\nDan Li1, Yujie Yang1, Jie Yang $\\textcircled{1}$ 1✉, Manman Fang1, Ben Zhong Tang1,2✉ & Zhen Li 1,3,4,5✉ \n\nMany luminescent stimuli responsive materials are based on fluorescence emission, while stimuli-responsive room temperature phosphorescent materials are less explored. Here, we show a kind of stimulus-responsive room temperature phosphorescence materials by the covalent linkage of phosphorescent chromophore of arylboronic acid and polymer matrix of poly(vinylalcohol). Attributed to the rigid environment offered from hydrogen bond and B-O covalent bond between arylboronic acid and poly(vinylalcohol), the yielded polymer film exhibits ultralong room temperature phosphorescence with lifetime of 2.43 s and phosphorescence quantum yield of $7.51\\%$ . Interestingly, the RTP property of this film is sensitive to the water and heat stimuli, because water could destroy the hydrogen bonds between adjacent poly(vinylalcohol) polymers, then changing the rigidity of this system. Furthermore, by introducing another two fluorescent dyes to this system, the color of afterglow with stimulus response effect could be adjusted from blue to green to orange through triplet-tosinglet Förster-resonance energy-transfer. Finally, due to the water/heat-sensitive, multicolor and completely aqueous processable feature for these three afterglow hybrids, they are successfully applied in multifunctional ink for anti-counterfeit, screen printing and fingerprint record. \n\nThnersec ins amagtreoriwailnsgwihnitcehr sct uilnd utinmdeurlguso peshpysoincsailve uchmeimechanical force, heat, light, and $\\mathrm{\\pH}^{1-6}$ , due to the potential application of such materials in the fields of information storage, anti-fake, and optoelectronic devices7–9. To date, despite the everincreasing variety of stimulus-responsive systems have been reported, most of the stimulus-responsive luminescent materials have been based on fluorescence10–12. As the result, the response could only be monitored from the changed emission color or intensity under the external stimulus. Therefore, it is necessary to develop stimulus-responsive materials from another dimension, such as emission lifetime, which could broaden their practical application in much more fields. \n\nOrganic room-temperature phosphorescence (RTP), one recently popularized phenomenon, has received significant attention over the past few years owing to the low toxicity of materials, long emission lifetimes, and large Stokes shifts to enable potential utility in numerous applications13–18. In particular, in comparison with fluorescent materials with short lifetime, RTP ones with a longer lifetime even caught by the naked eye are more conducive to their development as stimulusresponsive materials19–24. Nevertheless, the exploration of stimulus-responsive RTP materials is still at the preliminary stage. The main reasons can be summarized as follows: (i) the RTP emission tended to be realized in crystal, greatly limiting its applications; (ii) it was extremely difficult and complicated to simultaneously control triplet excitons and stimulus-response sites. In light of this, if external stimuli could destroy or rebuild the intermolecular interaction of RTP materials on the macro level, it will provide a simpler method for designing such materials. \n\nHerein, we report a stimulus-responsive ultralong RTP material, namely DPP-BOH-PVA, which is sensitive to water and heat. In our previous work, the arylboronic acid ester, $1,1^{\\prime}{:}3^{\\prime},1^{\\prime\\prime}$ -terphenyl- $5^{\\prime}$ -boronic acid ester (DPP-BO), exhibits remarkable phosphorescent properties at low temperature or under mechanical stimulation25. Inspired by this, arylboronic acid, $1,1^{\\prime}{:}3^{\\prime},1^{\\prime}$ -terphenyl- $5^{\\prime}$ -boronic acid (abbreviated as \n\nDPP-BOH), which tends to occur dehydration condensation reaction for the existence of boronic acid unit26, was chosen as a phosphorescent chromophore to react with poly(vinylalcohol) (PVA) polymer chains, to yield DPP-BOH-PVA (Fig. 1). There are two reasons for choosing PVA as the matrix. On one hand, the hydroxyl groups in PVA could react with the hydroxyl groups of DPP-BOH to form B–O covalent bonds, which could limit the thermal motion of DPP-BOH molecule, then facilitating RTP emission; on the other hand, PVA exhibits excellent hydroscopicity. The rigidity of PVA chains will be broken in a humid environment, which provides a stimulus-responsive site. Therefore, the resultant RTP property could be controlled by the alternating stimulation of heat and water. Furthermore, by introducing another two fluorescent dyes to this system, such as fluorescein and rhodamine B, the afterglow color could be adjusted through triplet-to-singlet Förster-resonance energy transfer (TS-FRET). At this time, the stimulus-response property of these systems could still be retained, as PVA matrix acted as the stimulus-responsive site. More importantly, the fabrication processes of these materials are only based in pure water phase without any organic solvents, which is environmentally friendly and adheres to the purpose of green chemistry. All the products in this work are accessible to be obtained, which may provide a new perspective for designing stimulus-responsive ultralong RTP materials. \n\n# Results \n\nStimulus-responsive room-temperature phosphorescence property of films. As shown in Fig. 1, DPP-BOH-PVA film was prepared through a simple method of dehydration condensation reaction between DPP-BOH and PVA (mass ratio $=1{:}100$ ) under the addition of ammonia water. The photophysical properties of desiccative DPP-BOH-PVA film were systematically investigated. The obtained film exhibited bluish-violet fluorescence at $345\\mathrm{nm}$ under UV-light irradiation $(254\\mathrm{nm})$ (Supplementary Fig. 1). Impressively, the blue phosphorescence with emission peak at $475\\mathrm{nm}$ appeared when turning off the UV lamp and could be captured by the naked eye even lasting for 10 s (Fig. 2a, e and Supplementary Movie 1). The time-resolved emission-decay curve showed that the RTP lifetime of DPP-BOH-PVA reached up to $2.43\\:s,$ while the corresponding RTP quantum yield could achieve $7.51\\%$ (Fig. 2b and Supplementary Tables 1 and 2), surpassing most of the organic RTP materials under ambient condition. \n\n![](images/f1052c22f7f014a6f3146441fbd89e346286acecfcc713378dddbbac09a621d7.jpg) \nFig. 1 Stimulus-responsive room-temperature phosphorescent system. Schematic illustration of the synthetic process of three target products and changes in intermolecular interactions under heating or water stimulus. \n\n![](images/d6f0e86e77a791108e9ed9070435e9ec3e8488fab6d02341709db77073e1762a.jpg) \nFig. 2 Photophysical properties of DPP-BOH-PVA film under the stimuli of water and heat. a Phosphorescence spectra of water-fumed DPP-BOH-PVA film after heating at different temperatures for 15 min. b Time-resolved emission-decay profiles of water-fumed DPP-BOH-PVA film after heating at different temperatures for 15 min. c Phosphorescence spectra of desiccative DPP-BOH-PVA film under water fuming for different times. d Repeated cycles of the heating/water fuming processes and the corresponding photographs of DPP-BOH-PVA film after turning off the UV irradiation. e Photographs of water-fumed DPP-BOH-PVA film after heating at different temperatures $30^{\\circ}\\mathsf{C}\\mathsf{-}80^{\\circ}\\mathsf{C})$ . The temperature gradient was $10^{\\circ}C$ and the corresponding heating time was $15\\min$ , after which the RTP behaviors were studied when the samples were cooled to room temperature. \n\nTo validate that water did have an effect on the RTP emission of DPP-BOH-PVA film, the RTP spectra and corresponding lifetimes of the film were measured after alternating stimulation of heat and water (Fig. 2). First, the film fumed by water vapor for $15\\mathrm{min}$ was measured, which showed nearly no RTP emission at $475\\mathrm{nm}$ (Fig. 2a). After confirming its good thermal stability (Supplementary Figs. 3 and 4 and Supplementary Table 3), the heating-responsive RTP effect was explored. As the heating temperature arose, the RTP intensity of the $475\\mathrm{nm}$ emission band gradually enhanced. When the heating temperature was $60^{\\circ}\\mathrm{C},$ the RTP intensity reached a plateau and hardly enhanced even if elevating the heating temperature unceasingly. By this time, the water in the film should be considered to be removed almost. In addition, the RTP lifetime also exhibited a similar changing tendency. That was, the lifetime of RTP emission gradually prolonged as the heating temperature increased, reaching the maximum of $2.43\\:s$ at $80^{\\circ}\\mathrm{C}$ (Fig. 2b). \n\nSubsequently, we explored the reverse process of removing water by heating the film at $90^{\\circ}\\mathrm{C}$ and then fuming with water vapor for different times. As shown in Fig. 2c, the RTP intensity of the $475\\mathrm{nm}$ emission band gradually decreased with the extension of water fuming time. This further confirms that the water indeed affects the RTP property. Thus, the RTP property of film could be controlled by heating and water fuming, and the cycle could be repeated many times (Fig. 2d and Supplementary Fig. 2). \n\nThe mechanism for ultralong organic phosphorescence of DPP-BOH-PVA film. In order to explore the mechanism for stimulus-responsive RTP effect of DPP-BOH-PVA film, DPPBOH-PVA-C was prepared as a control. The only variable in the preparation process is that there is no addition of alkali to catalyze the reaction between DPP-BOH and PVA. As expected, DPP-BOH-PVA-C film shows unsatisfactory RTP performance with a lifetime of $0.48\\:s$ and a phosphorescent quantum yield of $2.86\\%$ even after heating. Analyzing the UV–vis absorption spectra of these two films (Fig. 3a), it could be found that DPPBOH-PVA film shows an extra absorption peak at about $445\\mathrm{nm}$ compared to DPP-BOH-PVA-C, which may be derived from the formation of $_{\\mathrm{B-O}}$ covalent bond between DPP-BOH and PVA. The reaction yield was proved to be $46.50\\%$ by UV absorption measurement (Supplementary Fig. 5). As for DPP-BOH-PVA-C, lacking this kind of covalent bond, the hydrogen-bonding interactions are not strong enough to build a rigid environment, so the RTP performance is much inferior to that of DPP-BOH-PVA. Even though, the RTP effect of DPP-BOH-PVA-C film is also sensitive to water (Supplementary Figs. 6–8 and Supplementary Table 4). Further on, DPP-BO $(1,\\bar{1^{\\prime}}{:3^{\\prime}},1^{\\prime})$ -terphenyl- ${\\cdot}5^{\\prime}$ -boronic acid ester), the analog of DPP-BOH, was prepared, in which the reaction site to PVA was protected by acid ester. When DPP-BO was mixed with PVA, nearly no RTP emission could be detected for its corresponding film even after heating, although DPP-BO could give strong blue phosphorescence with lifetime up to $4.40s$ at low temperature (at 77 K) (Supplementary Figs. 9–12). These results demonstrate that the ultralong RTP property is largely related to the formation of B–O covalent bond between DPPBOH and PVA, which could control the tightness of the molecules more effectively than hydrogen-bonding interactions. Moreover, the phosphorescence spectrum of DPP-BOH in the solution state at $77\\mathrm{K}$ is consistent with the RTP spectrum of DPP-BOH-PVA film, suggesting that the phosphorescence emission source of DPP-BOH-PVA film is from DPP-BOH (Supplementary Fig. 12). In addition, there was almost no change in phosphorescence intensity of DPP-BOH-PVA film under oxygen atmosphere for $5\\mathrm{min}$ . Even for $15\\mathrm{h}$ , the oxygen did not completely quench the phosphorescence, indicating the close arrangement of molecules caused by hydrogen bond and B–O covalent bond makes it difficult for oxygen to enter (Supplementary Figs. 13 and 14). \n\n![](images/6237f95ccf377fd4b549d76f9c05d628f1796cc44ee6ec8fc50a4a80b320689e.jpg) \nFig. 3 The mechanism for ultralong phosphorescence of DPP-BOH-PVA film. a The absorption spectra of DPP-BOH-PVA film and DPP-BOH-PVA-C film, and the chemical structure of DPP-BOH-PVA. b Three repeated cycles for the Fourier transform infrared (FTIR) spectra of DPP-BOH-PVA film under of the heating/water stimuli. c The Jablonski diagram and theoretical calculations about natural transition orbitals (NTOs) for DPP-BOH $({\\mathsf{H L C T}}=$ hybridized local and charge transfer, $\\mathsf{L E}=$ locally excited, $|{\\mathsf{C}}_{}={}$ internal conversion, $k_{\\mathrm{isc}}=$ rate constant of intersystem crossing, $k_{\\mathsf{p},\\mathsf{r}}=$ radiative rate constant of phosphorescence, $\\phi_{\\mathsf{p}}=$ phosphorescence quantum yield, $\\tau_{\\mathsf{p}}=$ phosphorescence lifetime). \n\nThen, the theoretical calculations were carried out to understand the internal mechanism of remarkable RTP property from DPPBOH-PVA film (Fig. 3c and Supplementary Figs. 15 and 16). The natural transition orbitals (NTOs) of DPP-BOH were evaluated as shown in Fig. 3c. For the $S_{1}$ state, the hole distributes on the terphenyl units, while the particle almost spreads over the whole molecule skeleton. The partial overlap of the hole and the particle demonstrates a significant hybrid local and charge transfer (HLCT) character in the $\\mathsf{S}_{1}$ state, which facilitates the intersystem crossing (ISC) process from $\\mathsf{S}_{1}$ to $\\mathrm{{T}_{m}}$ and results in the larger ISC constant $(k_{\\mathrm{isc}})$ . Thus, it contributes much to the resultant high phosphorescent quantum yield of DPP-BOH. Meanwhile, for the $\\mathrm{T}_{1}$ state, the hole and the particle both distribute on the terphenyl units. The absolutely overlap of the hole and the particle demonstrates a typical locally excited (LE) character, which makes the transition from $\\mathrm{T}_{1}$ to $\\ensuremath{\\mathrm{s}}_{0}$ difficult and leads to a small spin–orbit coupling (SOC) value and phosphorescent radiative transition constant $(k_{\\mathrm{p,r}})$ . Therefore, the phosphorescence lifetime $(\\tau_{\\mathsf{p}})$ would be much prolonged based on the equation of $\\tau_{\\mathrm{p}}=1/(k_{\\mathrm{p,r}}\\mathrm{\\dot{+}}k_{\\mathrm{p,nr}})$ . Besides, the $k_{\\mathrm{isc}}$ and $k_{\\mathrm{p,r}}$ for DPP-BOH-PVA film were calculated based on the experimental results. As shown in Supplementary Table 5, the $k_{\\mathrm{isc}}$ is as large as $6.34\\times10^{7}\\mathrm{s}^{-1}$ , while $k_{\\mathrm{p,r}}$ and $k_{\\mathrm{p,nr}}$ are just 0.04 and $\\:0.37s^{-1}\\:$ , which could well correspond to the theoretical results, and certify the accuracy of internal mechanisms mentioned above. \n\n![](images/62efb38038999b7b117f88d92535c87b044f04a37d5c178f58027ba6e30a1784.jpg) \nFig. 4 Tunable afterglow color through triplet-to-singlet Förster-resonance energy transfer (TS-FRET). a The fluorescence/phosphorescence spectra of DPP-BOH-PVA and the UV–vis absorption spectra of fluorescein and rhodamine B. b The normalized RTP spectra of DPP-BOH-PVA-F and DPP-BOH-PVAR. c Time-resolved emission-decay profiles of DPP-BOH-PVA-F $(\\textcircled{\\alpha}533\\mathsf{n m})$ and DPP-BOH-PVA-R $(\\varpi581\\mathsf{n m})$ . d Simplified Jablonski diagram to explain the phosphorescence energy transfer ${\\mathrm{.}}1{\\mathsf{S C}}=$ intersystem crossing, ${\\mathsf{R T P}}=$ room-temperature phosphorescence). e RTP photographs of DPP-BOH-PVA, DPP-BOH-PVA-F, and DPP-BOH-PVA-R before and after heating at $90^{\\circ}\\mathsf C$ for 15 min. f Commission Internationale de l’Eclairage (CIE) coordinates of afterglow emissions for DPP-BOH-PVA, DPP-BOH-PVA-F, and DPP-BOH-PVA-R. \n\nTo further explore the water-sensitive mechanism of DPP-BOHPVA film, the Fourier transform infrared (FTIR) spectra were measured. As shown in Fig. 3b, the heated DPP-BOH-PVA films exhibit a noticeable peak at $3320\\mathrm{cm}^{-1}$ , which should be ascribed to the associated hydroxyl group between adjacent DPP-BOH-PVA. When the film was fumed with water, the peak shape becomes wider and the peak shifts to short wavenumber of $3285\\mathrm{cm}^{-1}$ indicating that the presence of water in the film could increase the degree of association of hydroxyl groups. Combined with changes in phosphorescence properties, it is considered that the presence of water destroys the hydrogen-bonding interaction between adjacent DPP-BOH-PVA chains, resulting in the destruction of the rigid environment of this system, and thus the RTP emission was quenched. When the film was heated, the water was removed and intermolecular hydrogen bonds were constructed again, then recovering the RTP property. Therefore, the water-sensitive property of DPP-BOH-PVA film should be related to the destruction and reconstruction of intermolecular hydrogen bond interaction between adjacent DPP-BOH-PVA chains. \n\nTunable afterglow color through triplet-to-singlet Försterresonance energy transfer (TS-FRET). In order to expand the stimulus-responsive afterglow materials, the afterglow color was further tuned. The strategy for adjusting the color of afterglow has been reported in 2020 by Subi J. George and co-workers, which utilized a long-lived phosphor as the energy donor and the fluorescent dyes as the energy acceptor to realize the triplet-to-singlet \n\nFörster-resonance energy transfer (TS-FRET)27–30. Inspired by this, the commercially available fluorescent dyes, fluorescein, and rhodamine B were chosen as the energy acceptor in this work. As shown in Fig. 4a, the absorption spectra of fluorescein and rhodamine B show obviously spectral overlap with the phosphorescence spectrum of DPP-BOH-PVA film, which meets the prerequisite for energy transfer from triplet state to the singlet state. DPP-BOHPVA-F and DPP-BOH-PVA-R were prepared by doping fluorescein and rhodamine B into DPP-BOH-PVA, which both exhibited multiple emissions (Supplementary Figs. 17–20). Particularly, two emission peaks could be still observed after turning off the $254\\mathrm{nm}$ UV light (Fig. 4b). As seen from the afterglow spectrum of DPPBOH-PVA-F film, the major emission peak locates at $533\\mathrm{nm}$ from fluorescein and a weak one at about $475\\mathrm{nm}$ from DPP-BOH-PVA, indicating the high energy transfer efficiency from DPP-BOH-PVA to fluorescein (Fig. 4d). As for DPP-BOH-PVA-R film, the intensity of two emission peaks at $581\\mathrm{nm}$ (rhodamine B) and $475\\mathrm{nm}$ (DPPBOH-PVA) is almost equal, which is consistent with the phenomenon of the less spectral overlap between the absorption spectrum of rhodamine B and the phosphorescence spectrum of DPP-BOH-PVA (Fig. 4b). It is worth noting that DPP-BOH-PVA-F film and DPP-BOH-PVA-R film exhibit green and orange afterglows with lifetimes of $1.60s$ $\\left(\\varrho\\right)533\\mathrm{nm}\\right)$ and $1.90s$ $(\\textcircled{\\omega}\\ \\bar{5}81\\ \\mathrm{nm})$ under ambient conditions, respectively (Fig. 4c). Certainly, their ultralong afterglows are also visible to the naked eye for about $10s$ (Supplementary Movies 2 and 3). At this time, the emission lifetimes at $475\\mathrm{nm}$ were measured to be $2.10s$ and $2.20s$ for DPPBOH-PVA-F and DPP-BOH-PVA- $\\cdot\\mathrm{R},$ respectively (Supplementary \n\n![](images/a0d21c1af8bc3f2bcffb868238b7260685a0cdf59f4b3556b38ca0aae7cd6e18.jpg) \nFig. 5 Applications of stimulus-responsive afterglow materials. The schematic illustration of the application process for a flexible film, b anti-counterfeit, c screen printing, and d fingerprint record. \n\nFig. 19). Accordingly, the TS-FRET efficiencies $(\\phi_{\\mathrm{FRET}})$ could be calculated to be $13.58\\%$ and $9.47\\%$ for them based on the equation of $\\Phi_{\\mathrm{FRET}}=1-\\tau/\\tau_{0},$ in which $\\tau$ and $\\tau_{0}$ are the RTP lifetimes of energy donor (DPP-BOH-PVA) after and before energy transfer (Supplementary Table $6)^{31}$ . Besides, the rate constants of FRET from DPP-BOH-PVA to fluorescein and rhodamine B were calculated to be $0.06s^{-1}$ and $0.04s^{-1}$ , respectively (Supplementary Table 6). As these data were larger or similar to the RTP radiative rate $(0.04s^{-1})$ of DPP-BOH-PVA, the FRET occurring from singlet to triplet state could be well certified. Furthermore, the oscillator strength $(f)$ for the donor phosphorescence was calculated to be 0.0078 (Supplementary Table 5), which should be large enough to facilitate the dipole–dipole coupling with an acceptor. \n\nMoreover, the films mixed with PVA and fluorescein or rhodamine B show almost no phosphorescence (Supplementary Fig. 21). Also no delayed emission signal could be detected with the optimal excitation wavelengths of fluorescein and rhodamine B for DPP-BOH-PVA-F and DPP-BOH-PVA-R (Supplementary Fig. 22). These exclude the afterglow originating from phosphorescence of fluorescein or rhodamine B. Excitedly, DPP-BOHPVA-F and DPP-BOH-PVA-R films are sensitive to water, and the cycle by heating and water fuming could be repeated (Fig. 4e and Supplementary Figs. 23–30). In addition, the change of FTIR spectra is also similar to that of DPP-BOH-PVA film, which further confirms the mechanism proposed above (Supplementary Fig. 31). Therefore, a large range of color adjustment can be conveniently achieved for amorphous stimulus-responsive materials with ultralong afterglow, which is conducive to expand their practical applications in many fields (Supplementary Fig. 32). \n\nApplications of stimulus-responsive afterglow materials. Taking advantage of the remarkable ambient multicolor afterglow and the water processability of these materials, four kinds of potential applications were explored as follows. First, making full use of the flexibility of the polymer to prepare multicolor soft films with different letter shapes $(^{\\infty}S^{\\infty},^{\\infty}\\bar{\\cup}^{\\bar{\\infty}}$ , and $^{\\mathfrak{e}}\\mathbf{M}^{\\mathfrak{p}},$ ) is shown in Fig. 5a. When the UV lamp is turning on, these films show different colors of fluorescence, then afterglow appears after turning off the UV irradiation. In the future, it is practicable to choose more shapes of molds to prepare a variety of handicrafts. \n\nFurthermore, the water processability of these materials allows them to be used as ink in many applications. For example, as shown in Fig. 5b, there are two kinds of inks prepared in this application, which both exhibit green fluorescence when the UV irradiation is on $(254\\mathrm{nm})$ . The difference is that one ink (ink 1) is the water solution of DPPBOH-PVA-F, which shows green afterglow after heating when the UV irradiation is off. In the contrast, the other ink (ink 2) is the water solution of mixed fluorescein and PVA, which is nonemissive when the UV lamp is turned off even after heating. Then, these two inks are used to write different letters on the filter paper, respectively. Under $254\\mathrm{nm}$ UV irradiation, a sentence of $^{\\mathrm{{*}}}\\mathrm{{I}}$ believe you $\\left(\\mathsf{S u n}\\right)^{\\flat}$ with green emission could be observed. Due to the afterglow of DPP-BOH-PVA-F could be quenched by the presence of water before heating, nothing could be seen after turning off the UV lamp. After heating the filter paper for about $15\\mathrm{min}$ , the water is removed, then the sentence of $^{\\circ}\\mathrm{{^{*}I}}$ lie you $\\left(\\mathrm{Moon}\\right)^{\\mathfrak{N}}$ appears after turning off the UV lamp, which means completely opposite to that when the UV light on. The stimulus-responsive materials with afterglow realize such a secondary anti-counterfeiting. \n\nIn addition, they also could be chosen as ink for silk-screen printing. Owing to the water solubility of these materials, they can directly use the filter paper as a substrate for printing, rather than limiting the choice of substrate material like most organic solvents. In Fig. 5c, DPP-BOH-PVA was used as the ink to print out the pattern of the gate of Tianjin University. Without heating, nothing was displayed when the UV light was off, but after heating, the blue afterglow could appear. \n\nFinally, based on the water-sensitive property of these materials, a fingerprint recording device was constructed (Fig. 5d). A desiccative DPP-BOH-PVA film could be prepared first. Then, wet your finger and press it on the prepared film for $5s$ . The fingerprints could be clearly displayed when the UV lamp was turned off, because the protruding parts of the fingerprint wet the film, but the recessed position did not touch the film. This application simplifies the process of real-time fingerprint record collection and shows good practical application value. \n\n# Discussion \n\nIn summary, a kind of stimulus-responsive ultralong RTP materials was designed and prepared. The fabricated DPP-BOHPVA film shows the excellent RTP property. When the film is exposed to the water vapor, the RTP property disappears since the water can break the rigid environment in the system. Conversely, heating could remove water and recover the RTP property of the film. Meanwhile, with incorporating fluorescent dyes, the afterglow color was adjusted from blue to green to orange, through triplet-to-singlet Förster-resonance energy transfer. Finally, due to the highly water-processable property of these three afterglow hybrids, they show promising applications in multifunctional ink for anti-counterfeit, screen printing, and the simple fingerprint recording device. The development of the stimulus-responsive multicolor materials with ultralong afterglow will broaden multifunctional stimuli-responsive materials and expand applications in much more fields. \n\n# Methods \n\nReagents and materials. Unless otherwise noted, all reagents used in the experiments were purchased from Jiangtian Chemical Co., LTD (Tianjin, China). The polyvinyl alcohol (PVA) was purchased from Macklin $(\\mathrm{M}_{\\mathrm{W}}\\approx20{,}000$ PDI: 1.16, alcoholysis degree: $87-89\\%$ ). (3,5-diphenylphenyl)boronic acid (purity: $98\\%$ ), fluorescein (purity: $97\\%$ ), and rhodamine B (purity: biological stain, BS) were purchased from Heowns and used as received without further purification. \n\nMeasurements. UV–vis absorption spectra were obtained using a Shimadzu UV2700. Steady-state photoluminescence/phosphorescence spectra and phosphorescence lifetime were measured using Hitachi F-4700. The fluorescence lifetime and photoluminescence quantum efficiency were obtained on FLS-1000. The luminescent photos were taken by iPhone 6 s under the irradiation of a hand-held UV lamp at room temperature. \n\nGeneral procedure for the synthesis of three hybrids. DPP-BOH-PVA film: To a stirred solution of PVA $(500\\mathrm{mg})$ in water $(3\\mathrm{mL})$ , DPP-BOH $\\mathrm{\\langle}5\\mathrm{mg\\rangle}$ in water $\\mathrm{(4~mL)}$ , and ammonium hydroxide $(1\\mathrm{mL})$ was added. The mixture was stirred at $80^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . Subsequently, take $0.7\\mathrm{mL}$ of the obtained aqueous solution and drop it on the cover glass with a syringe. Then, heat the cover glass until the water evaporates. \n\nDPP-BOH-PVA-C film: To a stirred solution of PVA $\\mathrm{\\nabla}500\\mathrm{mg})$ in water $(3\\mathrm{mL})$ , DPP-BOH $(5\\mathrm{mg})$ in water $(5\\mathrm{mL})$ ) was added. The mixture was stirred at $80^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . Subsequently, take $0.7\\mathrm{mL}$ of the obtained aqueous solution and drop it on the cover glass with a syringe. Then, heat the cover glass until the water evaporates. \n\nDPP-BO-PVA film: To a stirred solution of PVA $\\mathrm{\\Omega}^{\\mathrm{\\prime}}500\\mathrm{mg})$ in water $(3\\mathrm{mL})$ , DPP-BO $\\mathrm{\\langle}5\\mathrm{mg\\rangle}$ in water $(5\\mathrm{mL})$ ) was added. The mixture was stirred at $80^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . Subsequently, take $0.7\\mathrm{mL}$ of the obtained aqueous solution and drop it on the cover glass with a syringe. Then, heat the cover glass until the water evaporates. \n\nDPP-BOH-PVA-F film: To a stirred solution of PVA $(500\\mathrm{mg})$ in water $(3\\mathrm{mL}$ ), DPP-BOH $(5\\mathrm{mg})$ in water $(3\\mathrm{mL})$ , ammonium hydroxide (1 mL), and fluorescein $(0.5\\mathrm{mg})$ in water $(1~\\mathrm{mL}$ ) were added. The mixture was stirred at $80^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ . Subsequently, take $0.7\\mathrm{mL}$ of the obtained aqueous solution and drop it on the cover glass with a syringe. Then, heat the cover glass until the water evaporates. \n\nDPP-BOH-PVA-R film: To a stirred solution of PVA $(500\\mathrm{mg})$ in water $(3\\mathrm{mL})$ , DPP-BOH $\\left(5\\:\\mathrm{mg}\\right)$ in water $(3\\mathrm{mL})$ , ammonium hydroxide $(1\\mathrm{mL})$ , and rhodamine B $\\mathrm{(0.5\\:mg)}$ in water $\\mathrm{(1mL)}$ was added. The mixture was stirred at $80^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ Subsequently, take $0.7\\mathrm{mL}$ of the obtained aqueous solution and drop it on the cover glass with a syringe. Then, heat the cover glass until the water evaporates. \n\nTheoretical calculation. All density functional theory (DFT) calculations were performed using Gaussian 09 program. The ground state $\\mathrm{(S_{0})}$ structure and natural transition orbits (NTOs) of $\\mathrm{S_{1}/T_{1}}$ states for DPP-BOH were evaluated by the TD$\\mathrm{m}062{\\times}/6{-}31\\mathrm{g}^{\\ast}$ . \n\n# Data availability \n\nThe authors declare that the data supporting the findings of this study are provided in the Supplementary Information file. All data are available from the authors upon request. \n\nReceived: 17 June 2021; Accepted: 24 December 2021; Published online: 17 January 2022 \n\n# References \n\n1. Yagai, S. et al. Design amphiphilic dipolar p-systems for stimuli-responsive luminescent materials using metastable states. Nat. Commun. 5, 4013 (2014). \n2. Jia, S., Fong, W., Graham, B. & Boyd, B. J. Photoswitchable molecules in longwavelength light-responsive drug delivery: from molecular design to applications. Chem. Mater. 30, 2873–2887 (2018). Zhang, Z. et al. Excited-state conformational/electronic responses of saddleshaped $\\mathrm{N,N^{\\prime}}$ -disubstituted-dihydrodibenzo[a,c]phenazines: wide-tuning emission from red to deep blue and white light combination. J. Am. Chem. Soc. 137, 8509–8520 (2015). \n4. Wang, D. & Imae, T. Fluorescence emission from dendrimers and its pH dependence. J. Am. Chem. Soc. 126, 13204–13205 (2004). \n5. Mei, J., Leung, N. L. C., Kwok, R. T. K., Lam, J. W. Y. & Tang, B. Z. Aggregation-induced emission: together we shine, united we soar. Chem. Rev. 115, 11718–11940 (2015). \n6. Xie, Y. & Li, Z. Triboluminescence: recalling interest and new aspects. Chem. 4, 943–971 (2018). \n7. Kim, S., Yoon, S. & Park, S. Y. Highly fluorescent chameleon nanoparticles and polymer films: multicomponent organic systems that combine FRET and photochromic switching. J. Am. Chem. Soc. 134, 12091–12097 (2012). \n8. Wang, X. et al. Multicolor ultralong organic phosphorescence through alkyl engineering for 4D coding applications. Chem. Mater. 31, 5584–5591 (2019). \n9. Kim, D. et al. High-efficiency electroluminescence and amplified spontaneous emission from a thermally activated delayed fluorescent near-infrared emitter. Nat. Photonics 12, 98–104 (2018). \n10. Gao, Z., Han, Y. & Wang, F. Cooperative supramolecular polymers with anthracene-endoperoxide photo-switching for fluorescent anti-counterfeiting. Nat. Commun. 9, 3977 (2018). \n11. Matsunaga, Y. & Yang, J. Multicolor fluorescence writing based on host-guest interactions and force-induced fluorescence-color memory. Angew. Chem. Int. Ed. 54, 7985–7989 (2015). \n12. Zhou, E. Y., Knox, H. J., Liu, C., Zhao, W. & Chan, J. A conformationally restricted aza-BODIPY platform for stimulus-responsive probes with enhanced photoacoustic properties. J. Am. Chem. Soc. 141, 17601–17609 (2019). \n13. Kenry, Chen, C. & Liu, B. Enhancing the performance of pure organic roomtemperature phosphorescent luminophores. Nat. Commun. 10, 2111 (2019). \n14. Gu, L. et al. Colour-tunable ultra-long organic phosphorescence of a singlecomponent molecular crystal. Nat. Photonics 13, 406–411 (2019). \n15. Hirata, S. & Vacha, M. Circularly polarized persistent room-temperature phosphorescence from metal-free chiral aromatics in air. J. Phys. Chem. Lett. 7, 1539–1545 (2016). \n16. Kabe, R. & Adachi, C. Organic long persistent luminescence. Nature 550, 384–387 (2017). \n17. Su, Y. et al. Ultralong room temperature phosphorescence from amorphous organic materials toward confidential information encryption and decryption. Sci. Adv. 4, eaas9732 (2018). \n18. Kuila, S., Garain, S., Bandi, S. & George, S. J. All-organic, temporally pure white afterglow in amorphous films using complementary blue and greenishyellow ultralong room temperature phosphors. Adv. Funct. Mater. 30, 2003693 (2020). \n19. Afsari, H. S. et al. Time-gated FRET nanoassemblies for rapid and sensitive intra- and extracellular fluorescence imaging. Sci. Adv. 2, e1600265 (2016). \n20. Chen, Z. et al. Using ultrafast responsive phosphorescent nanoprobe to visualize elevated peroxynitrite in vitro and in vivo via ratiometric and timeresolved photoluminescence imaging. Adv. Healthca. Mater. 7, 1800309 (2018). \n21. Wu, Q. et al. Bioorthogonal “labeling after recognition” affording an FRETbased luminescent probe for detecting and imaging caspase-3 via photoluminescence lifetime imaging. J. Am. Chem. Soc. 142, 1057–1064 (2020). \n22. Yang, J., Fang, M. & Li, Z. Stimulus-responsive room temperature phosphorescence in purely organic luminogens. InfoMat. 2, 791–806 (2020). \n23. Huang, L., Qian, C. & Ma, Z. Stimuli-responsive purely organic roomtemperature phosphorescence materials. Chem. Eur. J. 26, 11914–11930 (2020). \n24. Yu, F. et al. Photostimulus-responsive large-area two-dimensional covalent organic framework films. Angew. Chem. Int. Ed. 58, 16101–16104 (2019). \n25. Yang, J. et al. AIEgen with fluorescence-phosphorescence dual mechanoluminescence at room temperature. Angew. Chem. Int. Ed. 56, \n880–884 (2017). \n26. Chai, Z. et al. Abnormal room temperature phosphorescence of purely organic boron-containing compounds: the relationship between the emissive behavior and the molecular packing, and the potential related applications. Chem. Sci. \n8, 8336–8344 (2017). \n27. Kuila, S. & George, S. J. Phosphorescence energy transfer: ambient afterglow fluorescence from water-processable and purely organic dyes via delayed sensitization. Angew. Chem. Int. Ed. 59, 9393–9397 (2020). \n28. Kirch, A., Gmelch, M. & Reineke, S. Simultaneous singlet–singlet and triplet–singlet förster resonance energy transfer from a single donor material. J. Phys. Chem. Lett. 10, 310–315 (2019). \n29. Cravcenco, A. et al. Multiplicity conversion based on intramolecular triplet-tosinglet energy transfer. Sci. Adv. 5, eaaw5978 (2019). \n30. Garain, S., Garain, B. C., Eswaramoorthy, M., Pati, S. K. & George, S. J. Lightharvesting supramolecular phosphors: highly efficient room temperature phosphorescence in solution and hydrogels. Angew. Chem. Int. Ed. 60, \n19720–19724 (2021). \n31. Biju, V., Itoh, T., Baba, Y. & Ishikawa, M. Quenching of photoluminescence in conjugates of quantum dots and single-walled carbon nanotube. J. Phys. Chem. B 110, 26068–26074 (2006). \n\n# Acknowledgements \n\nWe are grateful to the National Natural Science Foundation of China (No. 51903188, J.Y.), the Natural Science Foundation of Tianjin City (No. 19JCQNJC04500, J.Y.), the starting Grants of Tianjin University and Tianjin Government (Z.L.), and the Independent Innovation Fund of Tianjin University (J.Y.) for financial support. We appreciate the Edinburgh Instruments fluorescence spectrophotometer (FLS-1000) for conducting fluorescence lifetime and quantum yield measurements. \n\n# Author contributions \n\nJ.Y. and Z.L. conceived the project. B.T. gave valuable suggestions. D.L. was primarily responsible for the experiments, then measured and analyzed the optical data. Y.Y. and \n\nM.F. took the pictures. J.Y. conducted all the theoretical calculations. D.L., J.Y., and Z.L. \nwrote the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-28011-6. \n\nCorrespondence and requests for materials should be addressed to Jie Yang, Ben Zhong Tang or Zhen Li. \n\nPeer review information Nature Communications thanks anonymous, reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1038_s41586-021-04327-z", + "DOI": "10.1038/s41586-021-04327-z", + "DOI Link": "http://dx.doi.org/10.1038/s41586-021-04327-z", + "Relative Dir Path": "mds/10.1038_s41586-021-04327-z", + "Article Title": "Time-reversal symmetry-breaking charge order in a kagome superconductor", + "Authors": "Mielke, C; Das, D; Yin, JX; Liu, H; Gupta, R; Jiang, YX; Medarde, M; Wu, X; Lei, HC; Chang, J; Dai, PC; Si, Q; Miao, H; Thomale, R; Neupert, T; Shi, Y; Khasanov, R; Hasan, MZ; Luetkens, H; Guguchia, Z", + "Source Title": "NATURE", + "Abstract": "The kagome lattice(1), which is the most prominent structural motif in quantum physics, benefits from inherent non-trivial geometry so that it can host diverse quantum phases, ranging from spin-liquid phases, to topological matter, to intertwined orders(2-8) and, most rarely, to unconventional superconductivity(6,9). Recently, charge sensitive probes have indicated that the kagome superconductors AV(3)Sb(5) (A = K, Rb, Cs)(9-11) exhibit unconventional chiral charge order(12-19), which is analogousto the long-sought-after quantum order in the Haldane model(20) or Varma model(21). However, direct evidence for the time-reversal symmetry breaking of the charge order remains elusive. Here we use muon spin relaxation to probe the kagome charge order and superconductivity in KV3Sb5. We observe a noticeable enhancement of the internal field width sensed by the muon ensemble, which takes place just below the charge orderingtemperature and persists into the superconducting state. Notably, the muon spin relaxation rate below the charge orderingtemperature is substantially enhanced by applying an external magnetic field. We further show the multigap nature of superconductivity in KV3Sb5 and that the T-c/lambda(-2)(ab) ratio (where T-c is the superconducting transition temperature and lambda(ab) is the magnetic penetration depth in the kagome plane) is comparable to those of unconventional high-temperature superconductors. Our results point to time-reversal symmetry-breaking charge order intertwining with unconventional superconductivity in the correlated kagome lattice.", + "Times Cited, WoS Core": 315, + "Times Cited, All Databases": 329, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000753550800017", + "Markdown": "# Article \n\n# Time-reversal symmetry-breaking charge order in a kagome superconductor \n\nhttps://doi.org/10.1038/s41586-021-04327-z \n\nReceived: 25 June 2021 \n\nAccepted: 7 December 2021 \n\nPublished online: 9 February 2022 Check for updates \n\nC. Mielke III1,2,17, D. Das1,17, J.-X. Yin3,17, H. Liu4,5,17, R. Gupta1, Y.-X. Jiang3, M. Medarde6, X. Wu7, H. C. Lei8, J. Chang2, Pengcheng Dai9, Q. Si9, H. Miao10, R. Thomale11,12, T. Neupert2, Y. Shi4,5,13, R. Khasanov1, M. Z. Hasan3,14,15,16 ✉, H. Luetkens1 & Z. Guguchia1 ✉ \n\nThe kagome lattice1, which is the most prominent structural motif in quantum physics, benefits from inherent non-trivial geometry so that it can host diverse quantum phases, ranging from spin-liquid phases, to topological matter, to intertwined orders2–8 and, most rarely, to unconventional superconductivity6,9. Recently, charge sensitive probes have indicated that the kagome superconductors $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}(A=\\mathsf{K},\\mathsf{R}\\mathsf{b},\\mathsf{C}\\mathsf{s})^{9-11}$ exhibit unconventional chiral charge order12–19, which is analogous to the long-sought-after quantum order in the Haldane model20 or Varma model21. However, direct evidence for the time-reversal symmetry breaking of the charge order remains elusive. Here we use muon spin relaxation to probe the kagome charge order and superconductivity in $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ . We observe a noticeable enhancement of the internal field width sensed by the muon ensemble, which takes place just below the charge ordering temperature and persists into the superconducting state. Notably, the muon spin relaxation rate below the charge ordering temperature is substantially enhanced by applying an external magnetic field. We further show the multigap nature of superconductivity in ${\\sf K V}_{3}{\\sf S b}_{5}$ and that the $T_{\\mathrm{c}}/\\lambda_{a b}^{-2}$ ratio (where $T_{\\mathrm{c}}$ is the superconducting transition temperature and $\\lambda_{a b}$ is the magnetic penetration depth in the kagome plane) is comparable to those of unconventional high-temperature superconductors. Our results point to time-reversal symmetry-breaking charge order intertwining with unconventional superconductivity in the correlated kagome lattice. \n\nThe observation of orbital currents is a long-standing quest in both topological and correlated quantum matter. They have been suggested to produce the quantum anomalous Hall effect when interacting with Dirac fermions in a honeycomb lattice20 (Fig. 1a) and to be the hidden phase of high-temperature cuprate superconductors21,22 (Fig. 1b). In both cases, orbital currents run through the lattice and break time-reversal symmetry. Recently, the tantalizing visualization of such exotic order has been reported12–14 in the kagome superconductors $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}\\left(A=\\mathsf{K}_{\\rho}$ Rb, Cs) (Fig. 1c). Scanning tunnelling microscopy observes a chiral $2\\times2$ charge order (Fig. 1d and Extended Data Figs. 1a–d and $2\\mathsf{a-c},$ ) with an unusual magnetic field response. Theoretical analysis12–19 also suggests that this chiral charge order can not only lead to a giant anomalous Hall effect23 but can also be a precursor of unconventional superconductivity18. However, the broken time-reversal symmetry nature of the charge order and its interplay with superconductivity has not been explicitly demonstrated by experiments. \n\nTo explore unconventional aspects of superconductivity and the possible time-reversal symmetry-breaking nature of charge order and superconductivity in $\\mathsf{K V}_{3}\\mathsf{S b}_{5},$ it is critical that the superconducting order parameter and weak internal fields of $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ are measured at the microscopic level. Thus, we concentrate on muon spin relaxation/rotation $(\\upmu\\mathsf{S}\\mathsf{R})$ experiments24 of the normal state depolarization rate and the magnetic penetration depth λ in $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ . Importantly, zero-field $\\upmu\\mathsf{S}\\mathsf{R}$ $(Z\\mathsf{F}{\\cdot}\\upmu\\mathsf{S}\\mathsf{R})$ has the ability to detect internal magnetic fields as small as 0.1 G without applying external magnetic fields, making it a highly valuable tool for probing spontaneous magnetic fields owing to time-reversal symmetry breaking25 in the superconducting and charge ordered states. \n\n# Discussion Magnetic response across charge order Although long-range magnetism has not been reported in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ (ref.  26), ZF- ${\\bf\\ddot{\\mu}}{\\bf S R}$ experiments have been carried out above and below \n\n![](images/a731b4b269aa38b3c596725b67dfd6ce005034993e5f44121d518f193c39af75.jpg) \nFig. 1 | Indication of time-reversal symmetry-breaking of the charge order in $\\mathbf{K}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ . a, Orbital currents (red arrows) proposed in a honeycomb lattice. b, Orbital currents (red arrows) proposed in the $\\mathsf{C u O}_{2}$ lattice of cuprates. c, Schematic of orbital currents (red arrows) in the kagome lattice. d, Scanning tunnelling microscopy of the Sb surface showing $2\\times2$ charge order as illustrated by the black lines. The inset is the Fourier transform of this image, showing lattice Bragg peaks marked by blue circles and $2\\times2$ vector peaks marked by red circles. The three pairs of $2\\times2$ vector peaks feature different intensities, denoting a chirality of the charge order. e, A schematic overview of the experimental setup. Spin polarized muons with spin $S_{\\upmu}$ , forming at an angle of $60^{\\circ}$ with respect to the c axis of the crystal, are implanted in the sample. The sample was surrounded by four detectors: forwards (1), backwards (2), upwards (3) and downwards (4). An electronic clock is started at the time the \nmuon passes the muon detector and is stopped as soon as the decay positron is detected in the positron detectors. f, The ZF- $\\cdot\\upmu\\mathsf{S}\\mathsf{R}$ time spectra for $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ , obtained at different temperatures, all above the superconducting transition temperature $T_{\\mathrm{c}}$ . Longitudinally-applied field (LF) of 50 G clearly decouples the signal. The solid black curves in a represent fits to the recorded time spectra, using equation (1). Error bars are the s.e.m. in about $10^{6}$ events. g, The emperature dependences of the relaxation rates Δ and $T,$ obtained in a wide temperature range. h, The temperature dependence of Γ from two sets of detectors across the charge ordering temperature $T\\simeq80\\mathsf{K}.\\mathsf{i}$ , Temperature dependences of the muon spin relaxation rates Δ and Γ, which can be related to the nuclear and electronic systems, respectively, in the temperature range across $T_{\\mathrm{c}}$ . The error bars represent the s.d. of the fit parameters. \n\nthe superconducting transition temperature $T_{\\mathrm{c}}$ to search for any weak magnetism (static or slowly fluctuating). A schematic overview of the experimental setup with the muon spin forming at an angle of $60^{\\circ}$ with respect to the c axis of the crystal is shown in Fig. 1e. The sample was surrounded by four detectors: forwards (1), backwards (2), upwards (3) and downwards (4). Figure 1f displays the ZF- $\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\left(\\mathsf{\\Pi}_{\\mathsf{\\Pi}}\\mathsf{S}\\mathsf{R}\\right.$ spectra from detectors 3 and 4 collected over a wide temperature range. We see that the muon spin relaxation shows a reasonable temperature dependence. As the zero-field relaxation is decoupled by the application of a small external magnetic field applied in a direction longitudinal to the muon spin polarization, $B_{\\mathrm{\\scriptscriptstyleLF}}=50~\\mathrm{G}$ (Fig. 1f) (LF denotes “Longitudinal Field”), the relaxation is therefore due to spontaneous fields that are static at the microsecond timescale. The ZF- $\\scriptstyle\\mathtt{\\cdot u s R}$ spectra were fitted using the Gaussian Kubo– Toyabe (GKT) depolarization function27, which reflects the field distribution at the muon site created by the nuclear moments of the sample, multiplied by an additional exponential exp $\\left(-T t\\right)$ term (Extended Data Fig. 4a, b): \n\n$$\nP_{\\mathrm{ZF}}^{\\mathrm{GKT}}(t)=\\left(\\frac{1}{3}+\\frac{2}{3}(1-A^{2}t^{2})\\mathrm{exp}\\Bigg[-\\frac{A^{2}t^{2}}{2}\\Bigg]\\right)\\mathrm{exp}(-T t)\n$$ \n\nwhere $\\Delta/\\gamma_{\\upmu}$ is the width of the local field distribution due to the nuclear moments and $\\gamma_{\\upmu}/2\\uppi=135.5\\mathsf{M H z T}^{-1}$ is the muon gyromagnetic ratio. The observed deviation from a pure GKT behaviour in paramagnetic systems is frequently seen in $\\upmu\\mathrm{SR}$ measurements. This can, for example, be due to a mixture of diluted and dense nuclear moments, the presence of electric field gradients or a contribution of electronic origin. A GKT shape is expected due to the presence of the dense system of nuclear moments with large values of nuclear spins $(I=3/2$ for $^{39}\\mathsf{K},I=7/2$ for $^{51}\\mathrm{V}$ and $\\scriptstyle{I=5/2}$ for $^{121}{\\mathsf{S b}}$ ) in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ and a high natural abundance. The relaxation in single crystals might also not be GKT-like due to the fact that the quantization axis for the nuclear moments depends on the electric field gradients28. Naturally, the anisotropy of the electric field gradients is also often responsible for an anisotropy of the nuclear relaxation. As this effect essentially averages out in polycrystalline samples, we note that we also observed the additional exponential term in the polycrystalline sample of $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ (Extended Data Fig. 5a–c), which indicates that this effect is probably not dominant in our single-crystal measurements. Our high-field $\\upmu\\mathsf{S}\\mathsf{R}$ results presented below, however, prove that there is indeed a strong contribution of electronic origin to the muon spin relaxation below the charge ordering temperature. \n\n![](images/b209bf6cc51300d8d3ddd98ce83bbe5fa5a70e392ef0f24ff74c9c98c37a32b3.jpg) \nFig. 2 | Enhanced magnetic response of the charge order with applying external magnetic fields. a, Schematic overview of the high-field $\\upmu\\mathsf{S}\\mathsf{R}$ experimental setup for the muon spin forming an angle of $90^{\\circ}$ with respect to the c axis of the crystal. The sample was surrounded by $2\\times8$ positron detectors, arranged in rings. The specimen was mounted in a He gas-flow cryostat with the largest face perpendicular to the muon beam direction, along which the external field was applied. Behind the sample lies a veto counter (in orange), \nwhich rejects the muons that do not hit the sample. b, c, The temperature dependence of the muon spin relaxation rate (b) and the Knight shift $K_{\\mathrm{exp}}$ (local susceptibility) for $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ (c), measured under the $c$ -axis magnetic fields of $\\mu_{0}H=1$ T, 3 T, 5 T and 8 T. The vertical grey lines mark the charge ordering temperature, determined from magnetization measurements (Methods). $K_{\\mathrm{exp}}$ also shows a shallow minimum at around $30\\mathsf{K}$ , followed by a small peak towards low temperatures. The error bars represent the s.d. of the fit parameters. \n\nTherefore, we conclude that Γ in zero magnetic field also tracks the temperature dependence of the electronic contribution, but we cannot exclude subtle effects owing to changes in the electric field gradients in the charge ordered state. In Fig. 1g, we see the temperature dependence of both the muon spin relaxation $\\varDelta_{12}$ and ${\\cal{T}}_{12,34}$ over a broad temperature range from the base temperature to $300\\mathsf{K}$ . There is a notable increase immediately visible in the relaxation rates ${{I}_{12}}$ and $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{34}$ on lowering the temperature below the charge ordering temperature $T$ , which is more visible in Fig. 1h. This observation indicates the enhanced spread of internal fields sensed by the muon ensemble concurrent with the onset of charge ordering. The enhanced magnetic response that sets in with the charge order persists all the way down to the base temperature, and remains constant across the superconducting transition, as seen in Fig. 1i. Increase of the internal field width visible from the ZF- $\\scriptstyle\\mathtt{\\cdot}\\mathtt{\\backslash}\\mathtt{u}\\mathtt{S}\\mathtt{R}$ relaxation rate corresponds to an anomaly seen also in the nuclear contribution to the relaxation rate $\\varDelta_{12}$ ; namely, a peak coincides with the onset of the charge order, which decreases to a broad minimum before increasing again towards lower temperatures. \n\nThe increase in the exponential relaxation below $\\boldsymbol{\\vec{\\tau}}$ is estimated to be $\\simeq0.025\\upmu\\mathrm{s}^{-1}$ , which can be interpreted as a characteristic field strength of $T_{12}/\\gamma_{\\upmu}\\simeq0.3\\mathrm{G}$ . We note that a similar value of internal magnetic field strength is reported in several time-reversal symmetry-breaking superconductors25. The dip-like temperature dependence of $\\mathbf{{\\varDelta}}_{12}$ is also reminiscent of the behaviour observed in some multigap time-reversal symmetry-breaking superconductors (for example, $\\mathbf{La}_{7}\\mathbf{Ni}_{3}$ (ref. 29)) across $T_{\\mathrm{c}}$ . However, in the present case the ZF- $\\mathsf{\\cdot}\\mathsf{\\Pi}\\mathsf{\\cdot}\\mathsf{\\Pi}\\mathsf{\\cdot}\\mathsf{\\Pi}\\mathsf{\\cdot}\\mathsf{\\Pi}\\mathsf{\\cdot}\\mathsf{\\Pi}\\mathsf{\\cdot}\\mathsf{\\Pi}\\mathsf{\\cdot}\\mathsf{\\Pi}$ results alone do not enable us to draw any conclusions on the time-reversal symmetry-breaking effect in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ below $\\boldsymbol{\\tau}$ . As said above, the onset of charge order might also alter the electric field gradient experienced by the nuclei and correspondingly the magnetic dipolar coupling of the muon to the nuclei28. This can induce a change in the nuclear dipole contribution to the ZF- $\\mathsf{\\Pi}_{\\mathsf{P}}\\mathsf{R}\\mathsf{S}\\mathsf{R}$ signal. To substantiate the above ZF- $\\upmu\\mathsf{S}\\mathsf{R}$ results, systematic high-field $\\upmu\\mathsf{S R}^{30}$ experiments are essential (Fig. 2a). In a high magnetic field, the direction of the applied field defines the quantization axis for the nuclear moments, so that the effect of the charge order on the electric field gradient at the nuclear sites is irrelevant. A non-monotonous behaviour of the relaxation rate is clearly seen in the $\\upmu\\mathsf{S}\\mathsf{R}$ data, measured in a magnetic field of 1 T, applied parallel to the $c$ axis, as shown in Fig. 2b. The data at 1 T look similar to the temperature dependence of the zero-field nuclear rate $\\varDelta_{12}$ , as it seems to be dominated by the nuclear response. However, at higher fields such as 3 T, 5 T and $^{8\\mathsf{T}},$ the rate not only shows a broad bump around $\\boldsymbol{\\tau}$ , but also shows a clear and stronger increase towards low temperatures in the charge ordered state, which is similar to the behaviour observed for the relaxation rates ${{I}_{12}}$ and $\\ensuremath{\\boldsymbol{{\\Gamma}}}_{34}$ in zero field. As the nuclear contribution to the relaxation cannot be enhanced by an external field, this indicates that the low-temperature relaxation rate in magnetic fields higher than 1 T is dominated by the electronic contribution. Notably, we find that an absolute increase of the relaxation rate between the onset of charge order $\\boldsymbol{\\tau}$ and the base temperature in $^{8\\mathsf{T}}$ is $0.15\\upmu\\mathrm{s}^{-1}$ , which is a factor of six higher than that of $0.025{\\upmu\\mathrm{s}}^{-1}$ observed in zero field. This shows a strong field-induced enhancement of the electronic response. Moreover, we find that themagnitudeoftheKnightshift(localmagneticsusceptibility),definedas $K_{\\mathrm{exp}}=(B_{\\mathrm{int}}-B_{\\mathrm{ext}})/B_{\\mathrm{ext}}\\left(L\\right.$ $\\cdot B_{\\mathrm{int}}$ and $B_{\\mathrm{ext}}$ (Extended Data Fig. 6) are the internally measured and externally applied magnetic fields, respectively) and obtained in 3 T, 5 T and 8 T shows a sharp increase just below $\\boldsymbol{\\tau}$ , as shown in Fig. 2c. The change in local magnetic susceptibility across the charge order temperature $\\boldsymbol{T}$ agrees well with the change seen in the macroscopic susceptibility (Extended Data Fig. 3a, b) and indicates the presence of the magnetic response in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ concurrent with the charge order. $K_{\\mathrm{exp}}$ shows a shallow minimum near $30\\mathsf{K}$ at 3 T, 5 T and 8 T, which is also seen in the macroscopic susceptibility. The minimum in $K_{\\mathrm{exp}}$ is followed by a small peak towards low temperatures, which is absent in the macroscopic susceptibility. At present, it is difficult to give a quantitative explanation for the precise origin of such a behaviour. However, in connection with previous experimental results, one possibility is that the dip-like feature and the observed peak are related to the transition from isotropic charge order to a low-temperature electronic nematic state31,32, which breaks rotational symmetry. An electronic nematic transition in the charge ordered state was reported for the related system $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ from transport31 and scanning transmission microscope (STM) experiments32. The appearance of a nematic susceptibility would certainly influence the Knight shift and the muon spin relaxation rate. In addition, changes in the charge section will also modify the hyperfine contact field at the $\\upmu^{+}$ site and therefore also the local susceptibility. If so, the modified local susceptibility will be reflected by a breakdown of the proportionality of the $\\upmu^{+}$ Knight shift to the measured bulk susceptibility, because in this case the local susceptibility is different from the macroscopic susceptibility. This may explain the different temperature dependence of the muon Knight shift and macroscopic susceptibility in a charge ordered state. \n\nThe combination of ZF- $\\scriptstyle\\mathtt{\\cdot}\\mathtt{\\mathtt{u}S R}$ and high-field $\\upmu\\mathsf{S}\\mathsf{R}$ results shows the enhanced internal field width below $\\boldsymbol{\\tau}$ , giving direct evidence for the time-reversal symmetry-breaking fields in the kagome lattice. It is important to note that nearly the entire sample volume experiences an increase in the relaxation rate (Methods), indicating the bulk nature of the transition below $\\vec{\\tau}$ . Such an observation is consistent with charge sensitive probe results that show that the magnetic field switching of the chiral charge order is observed in the impurity-free region12. \n\n![](images/ab6b323a6426a72aff6d5f0099c3b9b4e540bcbb0698d0ca25f959cd08f69c09.jpg) \nFig. 3 | Correlated kagome superconductivity. a, The TF- $\\upmu\\mathsf{S R}$ spectra are obtained above and below $T_{\\mathrm{c}}$ (after field cooling the sample from above $T_{\\mathrm{c}})$ . Error bars are the standard error of the mean in about $10^{6}$ events. The error of each bin count $n$ is given by the s.d. of $n$ . The errors of each bin in $A(t)$ are then calculated by standard error propagation. The solid lines in a represent fits to the data by means of equation (3). The dashed lines are a guide to the eye. b, The temperature dependence of the total muon spin relaxation rate $\\sigma_{\\mathrm{{total}}}$ measured in the magnetic fields of $5\\ensuremath{\\mathrm{mT}}$ and $10\\mathrm{mT}$ applied both parallel to the c axis and parallel to the kagome plane. The dashed lines mark the average value of $\\sigma_{\\mathrm{{total}}}$ estimated from a few data points above $T_{\\mathrm{c}}$ . c, The superconducting muon depolarization rates $\\sigma_{\\scriptscriptstyle\\mathrm{SC},a b},\\sigma_{\\scriptscriptstyle\\mathrm{SC},a c}$ and $\\sigma_{\\mathrm{SC},c}$ as well as the \n\n![](images/e141e3cd35e0bb352ee7646513ef09f6e345130b525ead78cab24dabc84deb8f.jpg) \ninverse squared magnetic penetration depth $\\lambda_{a b}^{-2}$ and $\\ensuremath{\\lambda}_{c}^{-2}$ as a function of temperature, measured in $5\\ensuremath{\\mathrm{mT}}$ , applied parallel and perpendicular to the kagome plane. d, Plot of $T_{\\mathrm{c}}$ versus $\\lambda_{a b}^{-2}(0)$ obtained from our $\\upmu\\mathsf{S R}$ experiments in $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ . The dashed red line represents the relation obtained for the kagome superconductor $\\mathsf{L a R u}_{3}\\mathsf{S i}_{2}$ and for the layered transition metal dichalcogenide superconductors $\\mathsf{T}_{\\mathrm{d}}{\\cdot}\\mathsf{M o T e}_{2}$ and $2{\\mathsf{H}}{\\cdot}{\\mathsf{N b}}{\\mathsf{S e}}_{2}$ (ref. 38). The relation observed for underdoped cuprates is also shown (the solid line for hole doping37 and the dashed black line for electron doping39,40). The points for various conventional BCS superconductors are also shown. The error bars represent the s.d. of the fit parameters. \n\nBoth the $\\upmu\\mathsf{S}\\mathsf{R}$ and charge probe results attest to the intrinsic nature of the time-reversal symmetry breaking in the kagome lattice. One plausible phenomenological scenario is that the charge order has a complex chiral order parameter, which exhibits a phase difference between the three sublattices of the kagome plane. The existence of a phase difference, if not $\\pi$ , breaks time-reversal symmetry. Recent theoretical modelling of the charge ordering in the kagome lattice with van Hove filling and with extended Coulomb interactions (that is, close to the conditions of $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5})$ also suggests that time-reversal symmetry-breaking charge order with orbital currents is energetically favourable16–19. The orbital currents do not break translation symmetry beyond the $2\\times2$ supercell of the charge order. In addition, at least according to the calculations16, the net flux in a $2\\times2$ unit cell of the charge order is vanishingly small. Hence, there is an extremely small net magnetic moment according to the theoretical modelling. The suggested orbital current was reported to be homogeneous on the lattice, however alternating in its flow, which would produce inhomogeneous fields at the muon site. In this framework, muons may couple to the closed current orbits below $\\vec{\\tau}$ , leading to an enhanced internal field width sensed by the muon ensemble concurrent with the charge order. Thus, we conclude that the present results provide key evidence for a time-reversal symmetry-breaking charge order in $\\mathsf{K V}_{3}\\mathsf{S b}_{5}.$ . However, we cannot determine the exact structure of the orbital currents. Our data will inspire future experiments, particularly neutron polarization analysis, to potentially understand the precise order of orbital currents in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ . The current results indicate that the magnetic and charge channels of ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ seem to be strongly intertwined, which can give rise to complex and collective phenomena. The time-reversal symmetry-breaking charge order can open a topological gap in the Dirac nodal lines at the Fermi level, introducing a large anomalous Hall effect. It can also be a strong precursor of unconventional superconductivity as we show below. \n\n# Unconventional superconductivity \n\nThe time-reversal symmetry-breaking charge order can arise from extended Coulomb interactions of the kagome lattice with van Hove singularities, in which the same interactions and instabilities can lead to correlated superconductivity. Thus, we next focus on the low transverse-field $\\upmu\\mathsf{S}\\mathsf{R}$ (TF- $\\upmu\\mathsf{S R},$ ) measurements performed in the superconducting state. With a superconducting transition temperature $T_{\\mathrm{c}}$ of $\\simeq1.1\\mathsf{K}$ , the TF- $\\mathsf{\\Pi}_{\\mathsf{P}}\\mathsf{R}\\mathsf{R}$ spectra above (1.2 K) and below (0.27 K) $T_{\\mathrm{c}}$ are shown in Fig. 3a. To obtain a well-ordered vortex lattice, the measurements were carried out after field cooling of the sample from above $T_{\\mathrm{c}}$ . Above $T_{\\mathrm{c}},$ the oscillations show a damping essentially due to the random local fields from the nuclear magnetic moments. The damping rate is shown to be nearly constant between $10\\mathsf{K}$ and $1.2\\mathsf{K}$ . Below $T_{\\mathrm{c}}$ the damping rate increases with decreasing temperature due to the presence of a non-uniform local magnetic field distribution as a result of the formation of a flux-line lattice in the superconducting state. Figure 3b depicts the temperature evolution of the total Gaussian relaxation rate σtotal = σS2C + σn2m for KV3Sb5 for the 5 mT and 10 mT fields applied both in and out of the kagome plane. To extract the $\\sigma_{\\mathrm{SC}}$ contribution due only to superconductivity, the average value of the normal state depolarization rate $\\sigma_{\\mathrm{nm}}$ , estimated from six temperature points just above the onset of the superconducting transition, has been quadratically subtracted, because above $T_{\\mathrm{c}}$ there is only the normal state contribution to $\\sigma_{\\mathrm{total}}$ . Figure 3c shows the temperature dependences of the superconducting relaxation rates $\\sigma_{\\scriptscriptstyle\\mathrm{SC},a b}$ and $\\sigma_{\\mathrm{sc},a c},$ determined from the data with the field applied along the $c$ axis and in the kagome plane, respectively. The $c$ -axis relaxation rate can be extracted as $\\sigma_{\\mathrm{SC},c}=\\sigma_{\\mathrm{SC},a c}^{2}/\\sigma_{\\mathrm{SC},a b}(\\mathrm{ref}.^{33})$ , which is shown as a function of temperature in Fig. 3c. \n\nWe note that the magnetic penetration depth $\\lambda(T)$ (right axis of Fig. 3c) is related to the relaxation rate $\\sigma_{\\mathrm{sc}}(T)$ in the presence of a triangular (or hexagonal) vortex lattice by the equation24: \n\n$$\n\\frac{\\sigma_{\\scriptscriptstyle\\mathrm{SC}}(T)}{\\gamma_{\\scriptscriptstyle\\upmu}}=0.06091\\frac{\\phi_{0}}{\\lambda^{2}(T)},\n$$ \n\nwhere $\\upgamma_{\\upmu}$ is the gyromagnetic ratio of the muon and $\\boldsymbol{\\phi}_{0}$ is the magnetic-flux quantum. As the applied field is a factor of 20–60 times smaller than the second critical magnetic fields $(\\mu_{\\mathrm{o}}H_{\\mathrm{c}2,\\mathrm{c}}\\simeq0.1$ T for $H||c$ and $\\mu_{0}H_{\\mathrm c2,a b}\\simeq0.3$ T for $H||a b)$ in $\\mathsf{K V}_{3}\\mathsf{S b}_{5},$ , equation (2) is valid to estimate both $\\lambda_{a b}$ and $\\lambda_{c}$ . The value of the in-plane penetration depth $\\lambda_{a b}$ at $0.3{\\sf K}$ , determined from $\\sigma_{\\scriptscriptstyle\\mathrm{SC},a b}$ (with superconducting screening currents flowing parallel to the kagome plane), is found to be $\\lambda_{a b}\\simeq877(+/{-20})\\ensuremath{\\mathrm{nm}}$ . The value of the out-of-plane penetration depth, determined from $\\sigma_{\\mathrm{sc},c}$ (with superconducting screening currents flowing perpendicular to the kagome plane), is found to be $\\lambda_{c}\\simeq730(+/{-20})\\ensuremath{\\mathrm{nm}}$ . The $\\lambda(T)$ in the applied field of $5\\mathsf{m T}$ shows a well-pronounced two step behaviour, which is reminiscent of the behaviour observed in well-known two-band superconductors with single $T_{\\mathrm{c}}$ such as $\\mathrm{FeSe}_{0.94}$ (ref. 33) and $\\mathsf{V}_{3}\\mathsf{S i}$ (ref. 34). These results were explained34 by two nearly decoupled bands with an extremely weak interband coupling (which was still sufficient to give a single $T_{\\mathrm{c}})$ . According to our numerical analysis (Extended Data Figs. 7a–c and 8a–c) our observation of two-step behaviour of λ(T) in $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ is consistent with two-gap superconductivity with very weak interband coupling (0.001–0.005) and strong electron–phonon coupling. Multigap superconductivity was also recently reported for the sister compound $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ by means of $\\upmu\\mathsf{S R}^{35}$ and STM36. The multigap superconductivity in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ is consistent with the presence of multiple Fermi surfaces revealed by electronic structure calculations and tunnelling measurements14. \n\nTo place the system ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ in the context of other superconductors, in Fig. 3d we plot the critical temperature $T_{\\mathrm{c}}$ against the superfluid density $\\lambda_{a b}^{-2}$ . Most unconventional superconductors have $T_{\\mathrm{c}}/\\lambda_{a b}^{\\dot{-}2}$ values of about 0.1–20, whereas all of the conventional Bardeen–Cooper– Schrieffer (BCS) superconductors lie on the far right in the plot, with much smaller ratios37. In other words, unconventional superconductors are characterized by a dilute superfluid (a low density of Cooper pairs) whereas conventional BCS superconductors exhibit a dense superfluid. Moreover, a linear relationship between $T_{\\mathrm{c}}$ and $\\lambda_{a b}^{-2}$ is expected only on the Bose–Einstein–Condensate-like side of the phase diagram and is considered a hallmark of unconventional superconductivity37, in which (on-site or extended) Coulomb interactions play a role. For $\\mathsf{K V}_{3}\\mathsf{S b}_{5},$ the ratio is estimated to be $T_{\\mathrm{c}}/\\lambda_{a b}^{-2}\\simeq0.7,$ which is far away from conventional BCS superconductors and approximately a factor of two greater than that of the charge-density-wave superconductors $2{\\mathsf{H}}{\\cdot}{\\mathsf{N b}}{\\mathsf{S e}}_{2}$ and $4{\\mathsf{H}}{\\cdot}{\\mathsf{N b}}{\\mathsf{S e}}_{2}$ , as well as the Weyl superconductor $\\mathrm{T_{d}}\\mathrm{\\cdot}\\mathrm{MoTe}_{2}$ (ref. 38) and the kagome superconductor $\\mathsf{L a R u}_{3}\\mathsf{S i}_{2},$ as shown in Fig. 3d. The point for ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ is close to the values for electron-doped cuprates, which are well-known correlated superconductors with poorly screened Coulomb interactions. \n\n# Conclusion \n\nOur work points to a time-reversal symmetry-breaking charge order, intertwined with correlated superconductivity, in the kagome superconductor ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ . Although low-temperature time-reversal symmetry-breaking superconductivity has been discussed for many systems, high-temperature time-reversal symmetry-breaking charge order is extremely rare and there is a direct comparison with the fundamental Haldane and Varma models. The complex intertwining of such a charge ordered state with correlated superconductivity highlights the rich nature of the correlated kagome lattice and hints at other previously unknown hybrid phenomena resulting from non-trivial quantum interactions. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-021-04327-z. \n\n1. Syôzi, I. Statistics of kagome lattice. Prog. Theor. Phys. 6, 306-308 (1951). \n2. Barz, H. Ternary transition metal phosphides: high-temperature superconductors. Mater. Res. Bull. 15, 1489-1491 (1980). \n3. Zhou, Y., Kanoda, K. & Ng, T.-K. Quantum spin liquid states. Rev. Mod. Phys. 89, 025003 (2017). \n4. Guguchia, Z. et al. Tunable anomalous Hall conductivity through volume-wise magnetic competition in a topological kagome magnet. Nat. Commun. 11, 559 (2020). \n5. Yin, J.-X., Pan, S. H. & Hasan, M. Z. Probing topological quantum matter with scanning tunneling microscopy. Nat. Rev. Phys. 3, 249–263 (2021). \n6. Mielke, III, C. et al. Nodeless kagome superconductivity in LaR $\\boldsymbol{\\mathbf{\\mathit{1}}}_{3}\\mathsf{S i}_{2}$ Phys. Rev. Materials 5, \n034803 (2021). \n7. J.-X. Yin, et. al., Quantum-limit Chern topological magnetism in ${\\mathsf{T b M n}}_{6}{\\mathsf{S n}}_{6}$ . Nature 583, \n533–536 (2020). \n8. Pershoguba, S. S. & Yakovenko, V. M. Optical control of topological memory based on orbital magnetization. Preprint at http://arxiv.org/abs/2106.01192 (2021). \n9. Ortiz, B. et al. $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}$ : a $Z_{2}$ topological kagome metal with a superconducting ground state. Phys. Rev. Lett. 125, 247002 (2020). \n10.\t Ortiz, B. et al. Superconductivity in the $Z_{2}$ kagome metal $K V_{3}S b_{5}$ . Phys. Rev. Materials 5, \n034801 (2021). \n11. Yin, Q. et al. Superconductivity and normal-state properties of kagome metal ${\\mathsf{R b V}}_{3}{\\mathsf{S b}}_{5}$ single crystals. Chin. Phys. Lett. 38, 037403 (2021). \n12.\t Jiang, Y.-X. et al. Discovery of topological charge order in kagome superconductor $\\mathsf{K V}_{3}\\mathsf{S b}_{5}.$ Nat. Mater. 20, 1353–1357 (2021). \n13. Shumiya, N. et al. Tunable chiral charge order in kagome superconductor $\\mathsf{R b V}_{3}\\mathsf{S b}_{5}$ . Phys. Rev. B 104, 035131 (2021). \n14. Wang, Z. et al. Electronic nature of chiral charge order in the kagome superconductor $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}.$ Phys. Rev. B 104, 075148 (2021). \n15.\t Feng, X., Jiang, K., Wang, Z. & Hu, J. Chiral flux phase in the Kagome superconductor $A V_{3}S b_{5}$ . Sci. Bull. 66, 1384–1388 (2021). \n16. Denner, M., Thomale, R. & Neupert, T. Analysis of charge order in the kagome metal $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}(A=\\mathsf{K},$ Rb, Cs). Phys. Rev. Lett. 127, 217601 (2021). \n17. Lin, Y.-P. & Nandkishore, R. Complex charge density waves at Van Hove singularity on hexagonal lattices: Haldane-model phase diagram and potential realization in kagome metals $A V_{3}S b_{5}$ Phys. Rev. B 104, 045122 (2021). \n18.\t Wu, X. et al. Nature of unconventional pairing in the kagome superconductors $\\mathsf{A V}_{3}\\mathsf{S b}_{5}.$ Phys. Rev. Lett. 127, 177001 (2021). \n19.\t Setty, C., Hu, H., Chen, L. & Si, Q. Electron correlations and T-breaking density wave order in a $Z_{2}$ kagome metal. Preprint at https://arxiv.org/abs/2105.15204 (2021). \n20.\t Haldane, F. D. M. Model for a quantum Hall effect without Landau levels: condensed-matter realization of the parity anomaly. Phys. Rev. Lett. 61, 2015–2018 (1988). \n21. Varma, C. M. Non-Fermi-liquid states and pairing instability of a general model of copper oxide metals. Phys. Rev. B 55, 14554–14580 (1997). \n22.\t Chakravarty, S., Laughlin, R., Morr, D. & Nayak, C. Hidden order in the cuprates. Phys. Rev. B 63, 094503 (2001). \n23.\t Yang, S. et al. Giant, unconventional anomalous Hall effect in the metallic frustrated magnet candidate, $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ . Sci. Adv. 6, eabb6003 (2020). \n24.\t Sonier, J. E., Brewer, J. H. & Kiefl, R. F. $\\mu\\mathsf{S}\\mathsf{R}$ studies of the vortex state in type-II superconductors. Rev. Mod. Phys. 72, 769 (2000). \n25.\t Luke, G. M. et al. Time-reversal symmetry breaking superconductivity in $\\mathsf{S r}_{2}\\mathsf{R u O}_{4}$ . Nature \n394, 558-561 (1998). \n26.\t Kenney, E., Ortiz, B., Wang, C., Wilson, S. & Graf, M. Absence of local moments in the kagome metal $K\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ as determined by muon spin spectroscopy. J. Phys. Condens. Matter 33, 235801 (2021). \n27.\t Kubo, R. & Toyabe, T. Magnetic Resonance and Relaxation (North Holland, 1967). \n28.\t Huang, W. et al. Precision search for magnetic order in the pseudogap regime of $\\mathsf{L a}_{2-x}\\mathsf{S r}_{x}\\mathsf{C u O}_{4}$ by muon spin relaxation. Phys. Rev. B 85, 104527 (2012). \n\n# Article \n\n29.\t Singh, A. D. et al. Time-reversal symmetry breaking and multigap superconductivity in the noncentrosymmetric superconductor $\\mathsf{L a}_{7}\\mathsf{N i}_{3}$ . Phys. Rev. B 103, 174502 (2021). \n30.\t Sedlak, K., Scheuermann, R., Stoykov, A. & Amato, A. GEANT4 simulation and optimisation of the high-field $\\mu\\mathsf{S}\\mathsf{R}$ spectrometer. Physica B 404, 970–973 (2009). \n31.\t Xiang, Y. et al. Twofold symmetry of $c$ -axis resistivity in topological kagome superconductor $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}$ with in-plane rotating magnetic field. Preprint at https://arxiv. org/abs/2104.06909 (2021). \n32.\t Zhao, H. et al. Cascade of correlated electron states in a kagome superconductor $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}$ . Preprint at https://arxiv.org/pdf/2103.03118 (2021). \n33.\t Khasanov, R. et al. Evolution of two-gap behavior of the superconductor $\\mathsf{F e S e}_{1-x}.$ Phys. Rev. Lett. 104, 087004 (2010). \n34.\t Kogan, V. G., Martin, C. & Prozorov, R. Superfluid density and specific heat within a self-consistent scheme for a two-band superconductor. Phys. Rev. B 80, 014507 (2009). \n35.\t Gupta, R. et al. Microscopic evidence for anisotropic multigap superconductivity in the $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}$ kagome superconductor. Preprint at https://arxiv.org/abs/2108.01574 (2021). \n36.\t Han-Shu, X. et al. Multiband superconductivity with sign-preserving order parameter in kagome superconductor $\\mathsf{C s V}_{3}\\mathsf{S b}_{5}$ . Preprint at https://arxiv.org/pdf/2104.08810.pdf (2021). \n37.\t Uemura, Y. J. et al. Universal correlations between $T_{\\mathrm{{c}}}$ and $n_{s}/\\mathsf{m}^{\\ast}$ (carrier density over effective mass) in high- $T_{\\mathrm{{c}}}$ cuprate superconductors. Phys. Rev. Lett. 62, 2317 (1989). \n38.\t von Rohr, F. O. et al. Unconventional scaling of the superfluid density with the critical temperature in transition metal dichalcogenides. Sci. Adv. 5, eaav8465 (2019). \n39.\t Shengelaya, A. et al. Muon-spin-rotation measurements of the penetration depth of the infinite-layer electron-doped $\\mathsf{S r}_{0.9}\\mathsf{L a}_{0.1}\\mathsf{C u O}_{2}$ cuprate superconductor. Phys. Rev. Lett. 94, \n127001 (2005). \n40.\t Luetkens, H. et al. The electronic phase diagram of the $\\mathsf{L a O}_{1-x}\\mathsf{F}$ xFeAs superconductor. Nat. Mater. 8, 305-309 (2009). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 \n\n# Methods \n\n# Sample preparation \n\nSingle crystals of $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ were grown from $\\mathsf{K S b}_{2}$ alloy as a flux. K, V and Sb elements and $\\mathsf{K S b}_{2}$ precursor were sealed in a Ta crucible in a molar ratio of 1:3:14:10, which was finally sealed in a highly evacuated quartz tube. The tube was heated up to 1,273 K, left for 20 h and then slowly cooled down to $773\\mathsf{K}.$ Single crystals were separated from the flux by centrifuging. The crystals obtained from the flux were thin, metallic platelets with high lustre and the largest size was approximately $5\\times5\\mathsf{m m}^{2}$ . The obtained crystals with natural hexagonal facets were easily exfoliated. The X-ray diffraction pattern of a single crystal of ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ was collected using a Bruker D2 Phaser X-ray diffractometer with $\\mathtt{C u K\\upalpha}$ radiation $(\\lambda=0.15418\\mathrm{nm})$ ) at room temperature. The single-crystal diffraction was implemented on a Bruker D8 Venture system equipped with Mo Kα radiation $(\\lambda=0.71073\\mathring{\\mathbf{A}},$ ). The crystal structure was solved and refined using the Bruker SHELXTL software package. Critical magnetic fields for ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ for the field applied along the c axis and in the kagome plane were $100\\mathsf{m}\\mathsf{T}$ and $300\\mathrm{mT}$ , respectively. \n\n# Experimental details \n\nZF- and TF- $\\upmu\\mathsf{S}\\mathsf{R}$ experiments on the single-crystalline samples of ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ were performed on the GPS, Dolly and high-field HAL-9500 instruments at the Swiss Muon Source $(\\mathsf{S}\\upmu\\mathsf{S})$ at the Paul Scherrer Institute, in Villigen, Switzerland. Zero field is dynamically obtained (compensation better than $30\\mathrm{mG}$ ) by a newly installed automatic compensation device41. When performing measurements in zero field the geomagnetic field or any stray fields are tabulated and automatically compensated for by the automatic compensation device. \n\nBecause the ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ samples were thin ( $0.13\\mathrm{-}0.35\\mathrm{mm}$ along the $c$ axis), a mosaic of several crystals stacked on top of each other was used for these measurements. The individual crystals were attached to a $25\\cdot\\upmu\\mathrm{m}$ -thick Cu foil mounted on the Cu sample fork, and the entire ensemble was held together by small droplets of GE varnish. The crystals were aligned with the same in-plane orientation, which was achievable because the thin sheet-like crystals grow with a clearly hexagonal shape (Extended Data Fig. 1c). These multilayer crystal mosaics were then wrapped in a single layer of $60\\upmu\\mathrm{m}$ PE polyester tape. The magnetic field was applied both in-plane (along the ab plane) and out-of-plane (along the crystallographic c axis). A schematic overview of the experimental setup for zero-field and low-transverse-field measurements in GPS is shown in Fig. 1a. The muon spin forms at an angle of $60^{\\circ}$ with respect to the c axis of the crystal. The sample was surrounded by four detectors. A schematic overview of the experimental setup for the high-field $\\upmu\\mathsf{S R}$ instrument is shown in Fig. 2a. The crystals were mounted on $10\\mathrm{mm}$ circular silver sample holder by small droplets of GE varnish. The muon spin forms at an angle of $90^{\\circ}$ with respect to the c axis of the crystal. The sample was surrounded by $2\\times8$ positron detectors, arranged in rings. The specimen was mounted in a He gas-flow cryostat with the largest face perpendicular to the muon beam direction, along which the external field was applied. \n\n# $\\upmu\\mathsf{S R}$ experiment \n\nIn a $\\upmu\\mathsf{S}\\mathsf{R}$ experiment, nearly $100\\%$ spin-polarized muons $\\upmu^{+}$ are implanted into the sample one at a time. The positively charged $\\upmu^{+}$ thermalize at interstitial lattice sites, where they act as magnetic microprobes. In a magnetic material the muon spin precesses in the local field $B_{\\mathrm{int}}$ at the muon site with the Larmor frequency $\\nu_{\\mathrm{int}}{=}\\gamma_{\\mu}/(2\\uppi)B_{\\mathrm{int}}$ (muon gyromagnetic ratio $\\gamma_{\\upmu}/(2\\uppi)=135.5\\mathsf{M H z T}^{-1})$ . Using the $\\upmu\\mathsf{S R}$ technique, important length scales of superconductors can be measured, namely the magnetic penetration depth λ and the coherence length $\\xi$ If a type II superconductor is cooled below $T_{\\mathrm{c}}$ in an applied magnetic field ranging between the lower $(H_{\\mathrm{cl}})$ and the upper $(H_{\\mathrm{c}2})$ critical fields, a vortex lattice is formed that in general is incommensurate with the crystal lattice, with vortex cores separated by much larger distances than those of the crystallographic unit cell. Because the implanted muons stop at the given crystallographic sites, they will randomly probe the field distribution of the vortex lattice. Such measurements need to be performed in a field applied perpendicular to the initial muon spin polarization (the so-called transverse-field configuration). $\\lambda$ is one of the fundamental parameters of a superconductor, as it is related to the superfluid density $n_{s}$ via $_{1}1/\\lambda^{2}{=}\\mu_{0}e^{2}n_{s}/m^{*}$ (where m\\* is the effective mass, $e$ is the elementary charge and $\\mu_{0}$ is the Bohr magneton). \n\n# Analysis of TF- $\\\"\\mathbf{\\upmu}\\mathbf{S}\\mathbf{R}$ data \n\nThe TF- $\\upmu\\mathsf{S R}$ data were analysed by using the following functional form42: \n\n$$\nP_{\\mathrm{TF}}(t)=A_{s}\\exp\\Biggl[-\\frac{(\\sigma_{\\mathrm{SC}}^{2}+\\sigma_{\\mathrm{nm}}^{2})t^{2}}{2}\\Biggr]\\cos\\Bigl(\\gamma_{\\scriptscriptstyle\\parallel}B_{\\mathrm{int},s}t+\\varphi\\Bigr)\n$$ \n\nHere $A_{\\mathrm{s}}$ denotes the initial asymmetry of the sample, $\\varphi$ is the initial phase of the muon-spin ensemble and $B_{\\mathrm{int}}$ represents the internal magnetic field at the muon site. The relaxation rates $\\sigma_{\\mathrm{SC}}$ and $\\sigma_{\\mathrm{nm}}$ characterize the damping due to the formation of the flux-line lattice in the superconducting state and of the nuclear magnetic dipolar contribution, respectively. As indicated by the solid line in Fig. 3a, the $\\upmu\\mathsf{S}\\mathsf{R}$ data are well described by equation (1). \n\n# Crystal structure of $\\mathbf{K}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ \n\nAdditional characterization information is provided here on the kagome superconductor $\\mathsf{K V}_{3}\\mathsf{S b}_{5},$ which crystallizes in the new $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ -type structure (space group P6/mmm, where $\\pmb{A}=\\pmb{\\mathrm{K}}$ , Rb, Cs). The crystallographic structure of prototype compound ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ shown in panel a of Extended Data Fig. 1 illustrates how the V atoms form a kagome lattice (medium beige circles) intertwined with a hexagonal lattice of Sb atoms (small red circles). The K atoms (large purple circles) occupy the interstitial sites between the two parallel kagome planes. In panel b the vanadium kagome net has been emphasized, with the interpenetrating antimony lattice included to highlight the unit cell (see dashed lines). Extended Data Figure 1c, d shows an optical microscope image of a $3\\times2\\times0.2\\mathsf{m m}^{3}$ single crystal of ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ on millimetre paper and an STM image of the V kagome lattice from a cryogenically cleaved sample, respectively. \n\n# Extended laboratory X-ray diffraction experiments of $\\mathbf{\\DeltaKV}_{3}\\mathbf{Sb}_{5}$ \n\nA single-crystalline sample was selected and X-ray diffraction was performed on it. The crystal was oriented such that the incident X-rays scattered off of the ab plane. The resultant diffraction pattern shows clear diffraction peaks, which have been indexed (Extended Data Fig. 2a) and fitted using the SHELX-2018/3 software program. The obtained crystallographic information is summarized in Extended Data Tables 1 and 2. The Laue X-ray diffraction image (Extended Data Fig. 2b) demonstrates the single crystallinity of the samples used for the $\\upmu\\mathsf{S R}$ experiments. \n\n# Extended magnetic susceptibility measurements of $\\mathbf{KV}_{3}\\mathbf{S}\\mathbf{b}_{5}$ \n\nThe magnetic susceptibility measurements show the abrupt drop in susceptibility at $T\\simeq80\\:\\mathsf{K}$ (Extended Data Fig. 2c), which comes from the charge ordering below this temperature. Such an anomaly in susceptibility across the charge order $\\boldsymbol{\\tau}$ is seen up to the highest magnetic field applied along the $c$ axis (Extended Data Fig. 3a). Interestingly, a shallow minimum around $30\\mathsf{K}$ is also seen in the macroscopic susceptibility similar to $\\upmu\\mathrm{SR}$ Knight shift data. Whether this increase is related to the appearance of the electronic nematic susceptibility or not is an open question and requires more exploration. Notably, the anomaly in magnetic susceptibility across the charge order temperature $\\boldsymbol{T}$ is very well pronounced when the field is applied along the c axis, whereas it is hardly seen when the field is applied along the kagome plane (Extended Data Fig. 3b). This indicates that the magnetic response across $\\boldsymbol{\\mathscr{T}}$ is anisotropic. We note that the field dependence of the charge order peak intensities, observed with STM, is also seen only when the magnetic field \n\n# Article \n\nis applied along the c axis, pointing to the anisotropic field response of a charge order. These results are consistent with the scenario of orbital currents: as the orbital currents are coupled to the $c$ -axis moment and do not produce in-plane fields, the pronounced change in susceptibility is seen only when field is applied along the c axis. \n\nWe note that the temperature dependence of the $\\upmu\\mathsf{S}\\mathsf{R}$ Knight shift, $K_{\\mathrm{exp}},$ towards the low temperatures in the charge ordered state does not fully coincide with the temperature dependence of the macroscopic susceptibility; for example, the peak that was seen in $K_{\\mathrm{exp}}$ near $15\\mathsf{K}$ is missing in the macroscopic susceptibility. We note that in a paramagnetic metal $K_{\\mathrm{exp}}$ originates from hyperfine fields produced by the field-induced polarization of conduction electrons and localized electronic moments. The local moments contribute to $K_{\\mathrm{exp}}$ through two coupling mechanisms: (1) the dipolar interaction between the local moments and the $\\upmu^{+}$ , which may be described as a dipolar field at the $\\upmu^{+}$ interstitial site, and (2) a contact term due to electron spin polarization at the interstitial $\\upmu^{+}$ . Both contributions are proportional to the local-moment susceptibility. As there is a possible transition from isotropic charge order to a nematic state in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ below $30\\mathsf{K}$ , changes in the charge section will modify a hyperfine contact field and therefore also the local susceptibility. This may explain the different temperature dependence of the muon Knight shift and the macroscopic susceptibility in the charge ordered state. \n\n# ZF- $\\scriptstyle\\mathbf{\\\"}\\mathbf{\\mathbf{\\&}}\\mathbf{\\mathbf{R}}$ spectrum for $\\mathbf{K}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ \n\nThe ZF- $\\upmu\\mathsf{S R}$ spectrum recorded at 5 K is displayed in Extended Data Fig. 4. The red solid curve represents the fit to the recorded time spectra, using only the GKT function27: \n\n$$\nP_{\\mathrm{ZF}}^{\\mathrm{GKT}}(t)=\\left(\\frac{1}{3}+\\frac{2}{3}(1-\\varDelta^{2}t^{2})\\mathrm{exp}\\Bigg[-\\frac{\\varDelta^{2}t^{2}}{2}\\Bigg]\\right)\n$$ \n\nwhere $\\Delta/\\gamma_{\\upmu}$ is the width of the local field distribution due to the nuclear moments and $\\gamma_{\\upmu}/2\\uppi=135.5\\mathsf{M H z T}^{-1}$ is the muon gyromagnetic ratio. The GKT depolarization function (equation (1)) reflects the field distribution at the muon site created by the nuclear moments of the sample. It is clear that the GKT function alone is not sufficient to fully describe the ZF- $\\mathsf{\\cdot}\\mathsf{\\upmu}\\mathsf{S}\\mathsf{R}$ spectrum. Multiplying the GKT function by the additional exponential exp $\\left(-T t\\right)$ term (equation (1)), which is of electronic in origin, is essential to fully describe the spectrum shown in Extended Data Fig. 4a and in the inset. Thus, ZF- $\\upmu{\\sf S R}$ consists of the muon spin relaxations Δ and Γ due to the nuclear and electronic moments, respectively. This additional exponential rate is higher in the spectra taken from the forwards and backwards detectors as shown in Extended Data Fig. 4b. \n\n# ZF- $\\scriptstyle\\mathbf{\\\"}\\mathbf{\\mathbf{\\&}}\\mathbf{\\mathbf{R}}$ results for the polycrystalline sample of $\\mathbf{K}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ \n\nWe carried out ZF- $\\scriptstyle\\mathtt{\\cdot}\\mathtt{u}S\\mathtt{R}$ experiments on the polycrystalline sample of $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ and the results are shown in Extended Data Fig. 5. The additional exponential term is clearly visible in the spectrum as shown in Extended Data Fig. 5a and in the inset, showing the early time behaviour. There is a clear increase immediately visible in the exponential relaxation rate upon lowering the temperature below the charge ordering temperature $T^{*}$ (Extended Data Fig. 5b), which is more visible in Extended Data Fig. 5c. This observation in the polycrystalline sample of ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ agrees very well with the results on the single crystals. Our results on several $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ samples (both in single crystals and polycrystals) indicate that the exponential term is intrinsically present and is enhanced below $\\boldsymbol{\\tau}$ . \n\n# High-field ${\\mathfrak{u s R}}$ spectrum for a single crystal of $\\mathbf{K}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ \n\nDuring the high-field experiments obtained on the instrument HAL9500, a mosaic of several crystals stacked on top of each other was used. The individual crystals were attached to a $10\\mathrm{mm}$ circular silver sample holder and the entire ensemble was held together by small droplets of GE varnish. Extended Data Figure 6 shows the probability field distribution, measured at 5 K in the $c$ -axis magnetic field of 8 T. In the whole investigated temperature range, two-component signals were observed: a signal with fast relaxation of $0.42\\upmu\\mathrm{s}^{-1}$ (broad signal) and another one with a slow relaxation of $0.08{\\upmu\\mathrm{s}}^{-1}$ (narrow signal). The narrow signal arises mostly from the muons stopping in the silver sample holder and its position is a precise measure of the value of the applied magnetic field. The width and the position of the narrow signal are found to be temperature independent (see the inset of Extended Data Fig. 6) as expected and thus they were kept constant in the analysis. The relative fraction of the muons stopping in the sample was fixed to the value obtained at the base temperature and kept temperature independent. The signal with the fast relaxation, which is shifted towards the lower field from the applied one, arises from the muons stopping in the sample and it takes a major fraction $(60-70\\%)$ of the $\\upmu\\mathsf{S}\\mathsf{R}$ signal. This points to the fact that the sample response arises from the bulk of the sample. Based on this two-component signal, we can determine the Knight shift, which is defined as $K_{\\mathrm{exp}}{=}(B_{\\mathrm{int}}{-}B_{\\mathrm{ext}})/B_{\\mathrm{ext}},$ where $B_{\\mathrm{int}}$ and $B_{\\mathrm{ext}}$ are the internal and externally applied magnetic fields, respectively. \n\n# Superconducting gap symmetry \n\nTheoretically, several scenarios for electronically mediated, unconventional superconductivity have been discussed18. In the band structure of the $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ materials, van Hove singularities are found close to the Fermi energy, which is an electronic structural motif shared with other systems such as the cuprate superconductors or $\\mathsf{S r}_{2}\\mathsf{R u O}_{4}$ . As a particular feature of the kagome lattice, however, there is a sublattice interference mechanism43 by which the Bloch states near each van Hove point are supported on a distinct sublattice. This promotes the relevance of longer-range interactions and unconventional pairing states. \n\nExtended Data Figure 7a shows the temperature dependences of the superconducting relaxation rates $\\sigma_{\\scriptscriptstyle\\mathrm{SC},a b}$ and $\\sigma_{\\scriptscriptstyle\\mathrm{SC},a c},$ determined from the data with the field applied along the $c$ axis and in the kagome plane, respectively. When a magnetic field is applied along the $c$ axis, superconducting screening currents will flow in the ab plane, whereas in the case of a magnetic field applied in-plane, the superconducting screening currents will flow along the c and $a$ axes. Thus, $\\sigma_{\\mathrm{sc},a c}$ consists of both the in-plane and $c$ -axis contributions. A two-step nature of the superconducting state with the onset of $T_{\\mathrm{c}}\\simeq1.1\\mathsf{K}$ is clearly visible in the $5\\mathsf{m T}$ data for both orientations of the magnetic field with respect to the $c$ axis. \n\nIt is worth noticing that the step feature in the temperature dependence of the penetration depth that we observed for $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ is similar to the sudden decrease of the square root of the second moment of the field distribution at the vortex melting temperature in the cuprate high-temperature superconductor $\\mathbf{Bi}_{2.15}\\mathbf{Sr}_{1.85}\\mathbf{CaCu}_{2}\\mathbf{O}_{8+\\varDelta}$ $({\\mathrm{BSCCO}})^{44}$ . This process is thermally activated and caused by increased vortex mobility through a loosening of the inter- or intraplanar flux-line lattice correlations. This raises the question whether the two-step transition is related to the vortex lattice melting in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ . We note several arguments against such a scenario. (1) In BSCCO, the step feature occurs not in low fields $\\mathrm{10}\\mathrm{mT}$ $20\\mathrm{mT},$ ) but only in higher fields at which vortex lattice melting takes place44. In low fields the effects of the thermal fluctuations of the vortex positions on the $\\upmu\\mathsf{S}\\mathsf{R}$ linewidth become negligible, and a smooth temperature dependence of the linewidth is observed all the way up to $T_{\\mathrm{c}}$ (ref. 44). In the case of $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ , the step-like feature is very well pronounced in $5\\mathsf{m T}$ . With the application of $10\\mathrm{mT}$ , the two-step transition becomes smoothed out and less pronounced. This is in contrast to what we expect in the scenario of vortex lattice melting. (2) The effect of the vortex lattice melting on the $\\upmu\\mathsf{S}\\mathsf{R}$ line shape is to change its skewness from positive (ideal static lattice) to a negative value. Thus, vortex lattice melting is clearly reflected in the line shapes. In the case of $\\mathsf{K V}_{3}\\mathsf{S}\\mathsf{b}_{5},$ the superconducting relaxation rate $\\mathsf{\\Pi}_{\\mathsf{\\Pi},\\mathsf{\\Pi}\\upmu\\mathsf{S}\\mathsf{R}}$ linewidth) is small due to the long penetration depth and the $\\upmu\\mathsf{S}\\mathsf{R}$ line is described by a symmetric Gaussian line. Thus, it is difficult to check for the vortex lattice melting based on the shape of the field distribution. However, we carried out such an analysis for the sister compound $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ (ref. 35), which exhibits a higher superconducting critical temperature and a higher width of the $\\upmu\\mathrm{SR}$ line than the ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ sample. This enables us to describe the line shape more precisely. By analysing the asymmetric line shape of the field distribution and the skewness parameter as a function of temperature, we showed that the flux-line lattice in $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ is well arranged in the superconducting state and it is slightly distorted only in the vicinity of $T_{\\mathrm{c}}$ . However, no indication of vortex lattice melting was found in $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ (ref. 35). (3) We also note that the superconductors $A\\mathsf{V}_{3}\\mathsf{S}\\mathsf{b}_{5}$ are characterized by small superconducting anisotropy. The anisotropy of penetration depth for $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ is 2–3, which is two orders of magnitude smaller than that for BSCCO. It is close to the values reported for Fe-based high-temperature superconductors, in which no vortex lattice melting transition is observed. Considering the above arguments, we think that the two-step temperature dependence of the low-field magnetic penetration depth in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ is indeed due to multigap superconductivity with extremely small interband coupling34. The smearing of the step-like feature by increasing the magnetic field may be understood from the tendency of magnetic field to suppress one superconducting gap or by enhancing interband coupling with higher fields. \n\nThe temperature dependence of λ is sensitive to the topology of the superconducting gap: whereas in a fully gapped superconductor $\\Delta\\lambda^{-2}(T)\\equiv\\lambda^{-2}(0)-\\lambda^{-2}(T)$ vanishes exponentially at low T, in a nodal superconductor it vanishes as a power of T. To quantitatively analyse the temperature dependence of the penetration depth λ(T) (refs. 42,45) for ${\\bf K}{\\bf V}_{3}{\\bf S}{\\bf b}_{5}$ , we use the empirical $\\alpha$ -model, which assumes that the gaps occurring in different bands, besides a common $T_{\\mathrm{c}},$ are independent of each other. The $\\lambda(T)$ in the applied field of 5 mT shows a well-pronounced two-step behaviour, as shown in Extended Data Fig. 7a. This suggests that at least two bands are involved in the superconductivity and that the interband coupling is extremely small, which is sufficient to have the same values of $T_{\\mathrm{c}}$ for different bands but still shows the two-step temperature behaviour of the penetration depth34. With the application of $10\\:\\mathrm{mT}$ , the two-step transition becomes smoothed out and less pronounced. The results of the analysis for $\\mu_{\\mathrm{0}}H=10\\mathrm{mT}$ using the $\\alpha$ -model are presented in Extended Data Fig. 7b. We consider two different possibilities for the gap function: either a constant gap, $\\varDelta_{0,i}{=}\\varDelta_{i},$ or an angle-dependent f-wave gap of the form $\\boldsymbol{\\varDelta}_{0,i}$ $\\scriptstyle=\\pmb{\\varDelta}_{i}\\cos3\\varphi$ , which is appropriate for a triangular lattice, where $\\varphi$ is the polar angle around the Fermi surface. We note that the $d$ -wave form $\\varDelta_{0,i}$ $\\mathbf{\\varepsilon}=\\mathbf{\\mathcal{\\Delta}}\\mathbf{\\mathcal{\\Delta}}\\mathbf{\\mathcal{\\Delta}}\\cos2\\varphi$ makes no real sense on a lattice with three-fold rotational symmetry. The analysis certainly rules out a simple one-gap s-wave model as an adequate description of $\\lambda^{-2}(T)$ for ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ . The two-gap (s $+s)$ -wave or two-gap $(s+f)$ -wave models line up with the experimental data very well. Due to the lack of data points below $0.25\\mathsf{K}$ , it is difficult to distinguish between $(s+s)$ -wave and $(s+f)$ -wave models and to give an estimate for the zero-temperature value of λ. We also observe a diamagnetic shift of about 1 G in the superconducting phase, as shown in Extended Data Fig. 7c, which indicates a $T_{\\mathrm{c}}{\\tt o f}{\\simeq}1.1\\mathsf{K}$ , and furthermore supports the bulk nature of superconductivity in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ . \n\nThe value of the in-plane penetration depth $\\lambda_{a b}$ at $0.3{\\sf K}$ is found to $\\mathsf{b e}\\lambda_{a b}\\simeq877(20)\\mathsf{n n}$ m. The value of the out-of-plane penetration depth, determined from $\\sigma_{\\mathrm{SC},c}$ (with superconducting screening currents flowing perpendicular to the kagome plane), is found to be $\\lambda_{c}\\simeq730$ (20) nm. We note that these are the upper limits of $\\dot{\\lambda}_{a b}$ and $\\lambda_{c},$ as they are obtained by assuming a $100\\%$ superconducting volume fraction. However, vortex lattice disorder increases the measured relaxation rate leading to an underestimation of the penetration depth. The unexpected observation of the slightly smaller penetration depth $\\lambda_{c}$ compared to $\\lambda_{a b}$ might therefore originate in a slightly stronger disorder of the vortex lattice when the field is applied in the kagome plane. Another possibility for the similar values of the penetration depths $\\lambda_{a b}$ and $\\lambda_{c}$ in ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ might be as follows. We have recently measured superconducting anisotropy in the related system $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ (ref. 35). The anisotropy of the magnetic penetration depth is found to be around $\\gamma_{\\lambda}\\simeq3$ , which is a factor of three smaller than the anisotropy of the second magnetic critical field $\\gamma_{H\\mathrm{c}2}\\simeq9$ (ref. 35). Such a difference was explained in terms of multiband superconductivity in comparison with well-established multigap superconductors $(\\mathsf{M g B}_{2}$ , Fe-based and so on). For ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ , the anisotropy of the second critical field is only $\\gamma_{H\\mathrm{c}2}\\simeq3$ . Assuming that both systems $\\mathbf{CsV}_{3}\\mathbf{Sb}_{5}$ and ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ have similar superconducting mechanism, we expect the anisotropy of the penetration depth to be much smaller than 3, which makes this system exhibit an almost isotropic penetration depth. \n\n# Analysis of the temperature dependence of λ \n\nThe temperature dependence of the penetration depth λ is particularly sensitive to the topology of the superconducting gap: whereas in a fully gapped superconductor, $\\Delta\\lambda^{-2}(T)\\equiv\\lambda^{-2}(0)-\\lambda^{-2}(T)$ vanishes exponentially at low $T_{\\iota}$ in a nodal superconductor it vanishes as a power of ${\\it T.}\\lambda(T)$ was calculated in the local (London) approximation $(\\lambda\\gg\\xi)$ by using the following expression46: \n\n$$\n\\frac{\\lambda^{-2}\\big(T,\\varDelta_{0,i}\\big)}{\\lambda^{-2}\\big(0,\\varDelta_{0,i}\\big)}{=1+\\frac{1}{\\uppi}\\int_{0}^{2\\uppi}\\int_{\\varDelta(\\tau_{r,\\varphi})}^{\\infty}\\left(\\frac{\\partial f}{\\partial E}\\right)\\frac{E\\mathrm{d}E\\mathrm{d}\\varphi}{\\sqrt{E^{2}-\\varDelta_{i}(T,\\varphi)^{2}}}},\n$$ \n\nwhere $f{=}[1{+}\\exp(E/k_{\\mathrm{B}}T)]^{-1}$ is the Fermi function, $k_{\\mathrm{{B}}}$ is the Boltzmann constant, $\\varphi$ is the angle along the Fermi surface and $\\varDelta_{i}(T,\\varphi)=\\varDelta_{0,i}T$ $(T/T_{\\mathrm{c}})g(\\varphi)\\left(\\varDelta_{0,i}\\right.$ is the maximum gap value at $T=0$ ). The temperature dependence of the gap is approximated by the expression $\\varGamma(T/T_{\\mathrm{c}})=$ tanh{ $[1.82[1.018(T_{\\mathrm{c}}/T-1)]^{0.51}\\};g(\\varphi)$ describes the angular dependence of the gap and it is replaced by 1 for both an s-wave and an $(s+s)$ -wave gap, |cos $(2\\varphi)|$ for a $d$ -wave gap and |cos $(3\\varphi)|$ for an f-wave gap. \n\n# Analysis of λ(T) with a self-consistent approach \n\nThe $\\sigma_{\\mathrm{sc}}(T)$ data collected in the presence of a $50\\mathbf{G}$ and 100 G field were analysed in the framework of the quasiclassical Eilenberger weak-coupling formalism, in which the temperature dependence of the gaps was obtained by solving the self-consistent coupled gap equations rather than using the phenomenological $\\alpha$ -model47–50, in which the latter considers a similar BCS-type temperature dependence for both gaps. The coupled gap equations as introduced by Kogan et al.51 are \n\n$$\n\\begin{array}{r l}&{\\delta_{1}=\\frac{A_{1}}{T_{\\mathrm{c}}}\\frac{1}{2\\pi t}}\\\\ &{\\qquad=n_{1}\\lambda_{1}\\delta_{1}}\\\\ &{\\qquad\\displaystyle\\sum_{n=0}^{\\infty}\\left[S+\\ \\ln\\left(\\frac{1}{t}\\right)-\\left(\\frac{1}{n+0.5}-\\frac{1}{\\sqrt{\\delta_{1}^{2}+(n+0.5)^{2}}}\\right)\\right]}\\\\ &{\\qquad+n_{2}\\lambda_{12}\\delta_{2}\\displaystyle\\sum_{n=0}^{\\infty}\\left[S+\\ \\ln\\left(\\frac{1}{t}\\right)-\\left(\\frac{1}{n+0.5}-\\frac{1}{\\sqrt{\\delta_{2}^{2}+(n+0.5)^{2}}}\\right)\\right],}\\end{array}\n$$ \n\n$$\n\\begin{array}{r l}&{\\delta_{2}=\\frac{\\displaystyle\\frac{1}{T_{\\mathrm{c}}}\\frac{1}{2\\uppi t}}\\\\ &{\\quad=n_{1}\\lambda_{21}}\\\\ &{\\qquad\\displaystyle\\delta_{1}\\sum_{n=0}^{\\infty}\\left[S+\\mathrm{ln}\\{\\frac{1}{t}\\}-\\left(\\frac{1}{n+0.5}-\\frac{1}{\\sqrt{\\delta_{1}^{2}+(n+0.5)^{2}}}\\right)\\right]}\\\\ &{\\qquad\\displaystyle+n_{2}\\lambda_{22}\\delta_{2}\\sum_{n=0}^{\\infty}\\left[S+\\mathrm{ln}\\{\\frac{1}{t}\\}-\\left(\\frac{1}{n+0.5}-\\frac{1}{\\sqrt{\\delta_{2}^{2}+(n+0.5)^{2}}}\\right)\\right],}\\end{array}\n$$ \n\nwhere \n\n# Article \n\n$$\nS=\\frac{n_{1}\\lambda_{11}+n_{2}\\lambda_{22}-\\sqrt{(n_{1}\\lambda_{11}-n_{2}\\lambda_{22})^{2}+4n_{1}n_{2}\\lambda_{12}^{2}}}{2n_{1}n_{2}\\Big(\\lambda_{11}\\lambda_{22}-\\lambda_{12}^{2}\\Big)},\n$$ \n\nand $t{=}T/T_{\\mathrm{c}}$ is the reduced temperature. $n_{1}$ and $n_{2}$ represent the partial density of states for the corresponding bands at the Fermi level. $\\lambda_{11}(\\lambda_{22})$ and $\\lambda_{12}(\\lambda_{21})$ are the strengths of the intraband and the interband coupling, respectively. The two interband coupling strengths are equal, that is, $\\lambda_{12}=\\lambda_{21}$ in the notation of Kogan et al. The temperature variation of $\\varDelta_{1}(T)$ and $\\Delta_{2}(T)$ obtained after solving the above-mentioned coupled gap equations are then used to evaluate the temperature dependence of the normalized inverse-square magnetic penetration depth $\\lambda_{v}^{-2}(T)/\\lambda_{v}^{-2}(0)$ which in turn directly relates to the superfluid densities $(\\rho_{v}(T))$ for the two bands, by using the expression \n\n$$\n\\rho_{\\upsilon}(T)=\\frac{\\lambda_{\\upsilon}(T)^{-2}}{\\lambda_{\\upsilon}(0)^{-2}}=\\delta_{\\upsilon}^{2}\\sum_{n=0}^{\\infty}\\Big[\\delta_{\\upsilon}^{2}+(n+0.5)^{2}\\Big]^{-\\frac{3}{2}},\n$$ \n\nwhere $\\scriptstyle\\upsilon=1,2$ are the band indices. \n\nThe total superfluid density is then extracted by using the known temperature variations of $\\dot{\\rho}_{1}(T)$ and $\\rho_{2}(T)$ through the following expression: \n\n$$\n\\rho(T)=\\gamma\\rho_{{}_{1}}(T)+(1-\\gamma)\\rho_{{}_{2}}(T),\n$$ \n\nwhere $\\gamma$ is the weighting factor for the contribution of superconducting states with the larger gap $\\varDelta_{1}$ . A detailed description of the model can be found in ref. 52. \n\nThe results of these analyses are shown in Extended Data Fig. $_{8\\mathsf{a-c}}$ . Our numerical analysis shows that the two-step transition in $\\sigma_{\\mathrm{sc}}(T)$ at $10\\mathrm{mT}$ requires the interband coupling constant to be small, with a value of 0.005. For $5\\mathsf{m T}$ data, the interband coupling constant was found to be 0.001, which is factor of five smaller than that estimated for $10\\mathrm{mT}.$ This explains why the step-like feature is smoothed out in $10\\mathrm{mT}$ The small values of interband coupling constants imply that the band(s), in which the large and the small superconducting energy gaps are open, become only weakly coupled. One important point is that if we assume the maximum gap-to- $T_{\\mathrm{c}}$ ratio to be 3.75 (BCS value), which is a limitation of the model, then one cannot reproduce the sharp step-like feature in $\\sigma_{\\mathrm{sc}}(T)$ . However, considering this limitation of model, then the data are well explained by a large value of $2\\varDelta/k_{\\mathrm{B}}T_{\\mathrm{c}}=7.$ Our observation of a two-step behaviour of penetration depth in the system ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ with single $T_{\\mathrm{c}}$ is consistent with two-gap superconductivity with very weak interband coupling and a large value of $2\\Delta/k_{\\mathrm{B}}T_{\\mathrm{c}}{=}7$ . \n\n# Data availability \n\nAll relevant data are available from the authors. Alternatively, the data can be accessed through the data base at the following link: http:// musruser.psi.ch/cgi-bin/SearchDB.cgi. \n\n41.\t Amato, A. et al. The new versatile general purpose surface-muon instrument (GPS) based on silicon photomultipliers for $\\mu\\mathsf{S}\\mathsf{R}$ measurements on a continuous-wave beam. Rev. Sci. Instrum. 88, 093301 (2017). \n42.\t Suter, A. and Wojek, B. M. Musrfit: a free platform-independent framework for $\\mu\\mathsf{S}\\mathsf{R}$ data analysis. Phys. Procedia 30, 69 (2012). \n43.\t Kiesel, M. L. & Thomale, R. Sublattice interference in the kagome Hubbard model. Phys. Rev. B 86, 121105 (2012). \n44.\t Lee, S. L. et al. Evidence for two-dimensional thermal fluctuations of the vortex structure in $\\mathsf{B i}_{2.15}\\mathsf{S r}_{1.85}\\mathsf{C a C u}_{2}\\mathsf{O}_{8+\\Delta}$ from muon spin rotation experiments. Phys. Rev. Lett. 75, 922 (1995). \n45.\t Guguchia, Z. et al. Signatures of the topological $s^{\\leftarrow}$ superconducting order parameter in the type-II Weyl semimetal $\\mathsf{T}_{\\mathsf{d}}{\\mathsf{-}}\\mathsf{M}\\mathsf{o}\\mathsf{T}\\mathsf{e}_{2}$ . Nat. Commun. 8, 1082 (2017). \n46.\t Brandt, E. H. Flux distribution and penetration depth measured by muon spin rotation in high- $T_{\\mathrm{c}}$ superconductors. Phys. Rev. B 37, 2349 (1988). \n47.\t Bouquet, F. et al. Phenomenological two-gap model for the specific heat of $\\mathsf{M g B}_{2}$ . Europhys. Lett. 56, 856 (2001). \n48.\t Prozorov, R. & Giannetta, R. W. Magnetic penetration depth in unconventional superconductors. Supercond. Sci. Technol. 19, R41 (2006). \n49.\t Khasanov, R. et al. Experimental evidence for two gaps in the high-temperature $\\mathsf{L a}_{1.83}\\mathsf{S r}_{0.17}\\mathsf{C u O}_{4}$ superconductor. Phys. Rev. Lett. 98, 057007 (2007). \n50.\t Khasanov, R. et al. $\\mathsf{S r P t}_{3}\\mathsf{P};$ a two-band single-gap superconductor. Phys. Rev. B 90, \n140507(R) (2014). \n51.\t Kogan, V. G. London approach to anisotropic type-II superconductors. Phys. Rev. B 24, \n1572 (1981). \n52.\t Gupta, R. et al. Self-consistent two-gap approach in studying multi-band superconductivity in NdFeAsO0.65F0.35. Front. Phys. 8, 2 (2020). \n\nAcknowledgements The $\\upmu\\mathsf{S}\\mathsf{R}$ experiments were carried out at the Swiss Muon Source (SμS) Paul Scherrer Institute, Villigen, Switzerland. The magnetization measurements were carried out on the MPMS device of the Laboratory for Multiscale Materials Experiments, Paul Scherrer Institute, Villigen, Switzerland (SNSF grant no. 206021_139082). Z.G. acknowledges the useful discussions with R. Scheuermann and A. Amato. Z.G., C.M.III and D.D. thank C. Baines for the technical assistance during DOLLY experiments. M.Z.H. acknowledges visiting scientist support from IQIM at the California Institute of Technology. Experimental and theoretical work at Princeton University was supported by the Gordon and Betty Moore Foundation (GBMF4547 and GBMF9461; M.Z.H.) and the material characterization is supported by the US Department of Energy under the Basic Energy Sciences programme (grant no. DOE/BES DE-FG-02-05ER46200). The theory work at Rice has primarily been supported by the US Department of Energy, BES under award no. DE-SC0018197 and has also been supported by the Robert A. Welch Foundation grant no. C-1411 (Q.S.). The work at Rice university is also supported by US Department of Energy, BES under Grant No. DE-SC0012311 (P.D.). This work is also supported by the Beijing Natural Science Foundation (grant no. Z180008, Z200005), the National Key Research and Development Program of China (grant no. 2017YFA0302900, Y2018YFE0202600) and the National Natural Science Foundation of China (grant no. U2032204). The work of R.G. was supported by the Swiss National Science Foundation (SNF grant no. 200021_175935). T.N. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC-StG-Neupert757867-PARATOP). H. M. was sponsored by the US Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. R.T. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through Project-ID 258499086-SFB1170 and by the Wurzburg-Dresden Cluster of Excellence on Complexity and Topology in Quantum Matter-ct.qmat Project-ID 390858490-EXC 2147. \n\nAuthor contributions Z.G., Y.-X.J. and M.Z.H. conceived the study. Z.G. supervised the project. Sample growth and single-crystal X-ray diffraction experiments were carried out by H. Liu and Y.S. Magnetization and Laue X-ray diffraction experiments were performed by C.M.III, Z.G., M.M. and H.C.L. $\\upmu\\mathsf{S}\\mathsf{R}$ experiments and corresponding discussions were carried out by Z.G., C.M.III, D.D., R.G., R.K., H.Luet., J.J.C., J.-X.Y., Y.-X.J., M.Z.H., X.W., P.D., Q.S., H.M., R.T. and T.N. $\\upmu\\mathsf{S}\\mathsf{R}$ data analysis was undertaken by Z.G. and C.M.III, with contributions from R.K., H.L., D.D. and R.G. STM experiments were performed by J.-X.Y., Y.-X.J. and M.Z.H. Figure development and the writing of the paper were carried out by Z.G. and C.M.III, with contributions from J.-X.Y., H.Luet. and M.Z.H.  All authors discussed the results, interpretation and conclusion. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-021-04327-z. \nCorrespondence and requests for materials should be addressed to M. Z. Hasan or Z. Guguchia. \nPeer review information Nature thanks Victor Yakovenko and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/dc6d35c1cdd0005beb9ff57fbb5c26ba32bf630b58a12b326f45859039a6467c.jpg) \nExtended Data Fig. 1 | Crystal structure of K $\\mathbf{N}_{3}\\mathbf{S}\\mathbf{b}_{5}$ . Three dimensional representation (a) and top view (b) of the atomic structure of $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ . In panel (c) is displayed an optical microscope image of a $3\\times2\\times0.2\\mathrm{mm}$ single crystal of \n\n${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ on millimeter paper, with the scale shown. The hexagonal symmetry is immediately apparent. (d) Scanning Transmission Microscope (STM) image of the V kagome lattice from a cryogenically cleaved sample. \n\n# Article \n\n![](images/dcccabd4fe638250a6e8e5fdde63654f231666ac44479851e248c088d9d89d7c.jpg) \nExtended Data Fig. 2 | Single Crystal X-Ray Diffraction for $\\mathbf{K}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ . (a) X-ray diffraction image for ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ recorded at $300\\mathsf{K}$ . The well-defined peaks are labeled with their crystallographic indices. No second phase has been detected. (b) Laue X-ray diffraction image of the single crystal sample ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ , \n\noriented with the $c$ -axis along the beam. (c) The temperature dependence of magnetic susceptibility of ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ above $1.8{\\sf K}$ . It shows an anomaly at $T\\simeq80\\mathsf{K}$ , coinciding with emergence of a charge order. \n\n![](images/82d6cd8a39ee01ddbccf246d841528088f21fdd9236685dc991ed09aaf0c324f.jpg) \nended Data Fig. 3 | Anisotropic magnetic response across charge order magnetic fields applied parallel to the $c$ -axis. (b) The temperature dependence temperature in the single crystalline sample of K $\\mathbf{V}_{3}\\mathbb{S}\\mathbf{b}_{5}$ . (a) The temperature of magnetic susceptibility for ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ measured in the field of 1 T, applied both endence of magnetic susceptibility for ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ measured at various parallel to the kagome plane and parallel to the c-axis. \n\n# Article \n\n![](images/dee710d4100f8f221650a5780f15c72051e67d5038b4baee3d4fc4af935478ac.jpg) \ntended Data Fig. 4 | Zero-field $\\pmb{\\mu}\\pmb{S}\\pmb{R}$ experiment for the single crystalline spectra, using only Gaussian Kubo Toyabe (GKT) function (red) and the one sample of K $\\mathbf{\\Delta}\\mathbf{\\Delta}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ . The ZF $\\mu\\mathsf{S}\\mathsf{R}$ time spectra for ${\\mathsf{K V}}_{3}{\\mathsf{S b}}_{5}$ obtained at $T=5{\\sf K}$ from with an additional exponential exp(−Γt) term (blue). The inset shows the low tectors 3 & 4 and 2 & 1. The solid curves represent fits to the recorded time time part of the spectrum. \n\n![](images/9a6eacb7573839de1efb7fd96950ce1bd295a1a6de3a793fc4ea816ac3a803db.jpg) \nxtended Data Fig. 5 | Zero-field μSR experiment for the polycrystalline spectra, using only Gaussian Kubo Toyabe (GKT) function (red) and the one sample of K $\\mathbf{N}_{3}\\mathbf{S}\\mathbf{b}_{5}$ . The ZF $\\mu\\mathsf{S}\\mathsf{R}$ time spectra for the polycrystalline sample of with an additional exponential exp(−Γt) term (blue). The inset shows the low $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ , obtained at $T=5{\\sf K}$ . The solid curves represent fits to the recorded time time part of the spectrum. \n\n![](images/4d4cf35f978c957844e0e32c5dbc1f0e03decae473a0574e8f4aaf58bf6c31f0.jpg) \n\nExtended Data Fig. 6 | High-field $\\pmb{\\mu}\\pmb{S}\\pmb{R}$ experiment for $\\mathbf{KV}_{3}\\mathbf{S}\\mathbf{b}_{5}$ . Fourier transform for the $\\mu{\\mathsf{S R}}$ asymmetry spectra of $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ at 5 K for the applied field of $\\scriptstyle\\mu_{\\scriptscriptstyle0}H=81$ T. The black solid line represents the fit to the data using the two component signal. Red and blue solid lines show the signals arising from the sample and the silver sample holder (majority), respectively. The inset shows the temperature dependences of the muon spin relaxation rates arising from the sample and the silver sample holder. \n\n![](images/4230fac94e30f46acc13b620beb9b6b7745c04e8032b54cb6fef992c3417ddd5.jpg) \n\nExtended Data Fig. 7 | Superconducting gap symmetry in $\\mathbf{KV}_{3}\\mathbb{S}\\mathbf{b}_{5}$ . (a) The SC muon depolarization rates $\\sigma_{s c,a b},$ and $\\sigma_{s c,a c}$ as well as the inverse squared magnetic penetration depth $\\lambda_{a b}^{-2}$ and $\\lambda_{a c}^{-2}$ as a function of temperature, measured in 5 mT, applied parallel and perpendicular to the kagome plane. (b) The SC muon depolarization rate $\\sigma_{s c,a c},$ measured in $10\\mathrm{mT},$ applied parallel to the kagome plane. The solid line represents the indistinguishable 2-gap $s$ -wave and $s{+}d$ wave model. The error bars represent the s.d. of the fit parameters. (c) Temperature dependence of the difference between the internal field $\\mu_{\\scriptscriptstyle0}H_{\\scriptscriptstyle\\mathrm{SC}}$ measured in the SC state and the one measured in the normal state $\\mu_{\\scriptscriptstyle0}H_{\\scriptscriptstyle\\mathrm{NS}}$ at $T=5{\\sf K}$ for $\\mathsf{K V}_{3}\\mathsf{S b}_{5}$ . \n\n# Article \n\n![](images/a72a533d6f9cae756517f419dfb398e57855ba8a9e49c32418158d7b192eeea3.jpg) \nExtended Data Fig. 8 | A self-consistent approach for a two-band superconductor in $\\mathbf{K}\\mathbf{V}_{3}\\mathbf{S}\\mathbf{b}_{5}$ . The SC muon depolarization rates $\\sigma_{s c,c}$ (a), and $\\sigma_{s c,a b}$ (b) as a function of temperature, measured in $5\\mathsf{m}\\mathsf{T}_{\\cdot}$ , applied perpendicular and parallel to the kagome plane. (c) The SC muon depolarization rate $\\sigma_{s c,a c},$ measured in $10\\mathrm{mT},$ , applied parallel to the kagome plane. The solid black and purple lines are the theoretical curves obtained within the framework of \n\nself-consistent approach for a two-band superconductor described in the text. The red and the blue dashed lines correspond to the contribution of the large and the small superconducting gaps to the total superfluid density, solid black lines. The insets show the temperature dependences of the large $\\Delta_{1}$ and the small $\\Delta_{2}$ . \n\nExtended Data Table 1 | Atomic positions \n\n\n
Atomic Positions
AtomWyckhoff PositionsXyZUeq/A²Occ
Sb011a1100.161
Sb024h2/31/30.253810.0191
V013f1/21/200.0151
K011b101/20.0450.977
\n\n# Article \n\nExtended Data Table 2 | Crystallographic refinement \n\n\n
Crystallographic Data
Chemical Formula Formula WeightK0.98V3Sb5 799.81
Crystal System Space Group a C αhexagonal P6/mmm 5.4831(3) A 8.9544(9) A
Z Cell Volume90° 120° 1A 233.14(3) A3
Density (calculated) Temperature5.697 cm3 273(2) K
WavelengthMo K。 (X = 0.71073 A)
θ Range2.27° to 36.15°
Diffractometer Index RangesData Collection Bruker D8 Venture
\n\n
Refinement
Refinement Method Refinement Program Function Minimized Data Parameters RestraintsFull-matrix least-squares on F2 SHELX-2018/3 (Sheldrick,2018) w(F。²+F2)2 278 reflections (271 final) 13 parameters 0 restraints
Goodness-of-fit on F2 Final R Indices Weighting Scheme1.233 I ≤α(I) R1=0.0162, wR2=0.039 all data; R=0.0171, wR2=0.039
Extinction Coefficient △pMax and △psMin R.M.S. Dev. from MeanW = g2(F2)+(0.0130P)2+0.4869P where P=(F²+2F²)/3 0.0050(10) 1.259 eA-3 and -0.481 eA-3 0.164 eA3
" + }, + { + "id": "10.1038_s41586-022-04443-4", + "DOI": "10.1038/s41586-022-04443-4", + "DOI Link": "http://dx.doi.org/10.1038/s41586-022-04443-4", + "Relative Dir Path": "mds/10.1038_s41586-022-04443-4", + "Article Title": "Reconstructed covalent organic frameworks", + "Authors": "Zhang, WW; Chen, LJ; Dai, S; Zhao, CX; Ma, C; Wei, L; Zhu, MH; Chong, SY; Yang, HF; Liu, LJ; Bai, Y; Yu, MJ; Xu, YJ; Zhu, XW; Zhu, Q; An, SH; Sprick, RS; Little, MA; Wu, XF; Jiang, S; Wu, YZ; Zhang, YB; Tian, H; Zhu, WH; Cooper, A", + "Source Title": "NATURE", + "Abstract": "Covalent organic frameworks (COFs) are distinguished from other organic polymers by their crystallinity(1-3), but it remains challenging to obtain robust, highly crystalline COFs because the framework-forming reactions are poorly reversible(4,5). More reversible chemistry can improve crystallinity(6-9), but this typically yields COFs with poor physicochemical stability and limited application scope(5). Here we report a general and scalable protocol to prepare robust, highly crystalline imine COFs, based on an unexpected framework reconstruction. In contrast to standard approaches in which monomers are initially randomly aligned, our method involves the pre-organization of monomers using a reversible and removable covalent tether, followed by confined polymerization. This reconstruction route produces reconstructed COFs with greatly enhanced crystallinity and much higher porosity by means of a simple vacuum-free synthetic procedure. The increased crystallinity in the reconstructed COFs improves charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to 27.98 mmol h(-1) g(-1). This nulloconfinement-assisted reconstruction strategy is a step towards programming function in organic materials through atomistic structural control.", + "Times Cited, WoS Core": 318, + "Times Cited, All Databases": 327, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000779100400018", + "Markdown": "# Article \n\n# Reconstructed covalent organic frameworks \n\nhttps://doi.org/10.1038/s41586-022-04443-4 \n\nReceived: 29 July 2021 \n\nAccepted: 18 January 2022 \n\nPublished online: 6 April 2022 \n\nOpen access \n\n# Check for updates \n\nWeiwei Zhang1, Linjiang Chen1,2, Sheng Dai1, Chengxi Zhao1,2, Cheng Ma3, Lei Wei4, Minghui Zhu3, Samantha Y. Chong2, Haofan Yang2, Lunjie Liu2, Yang Bai2, Miaojie Yu1, Yongjie Xu2, Xiao-Wei Zhu2, Qiang Zhu2, Shuhao An1, Reiner Sebastian Sprick2, Marc A. Little2, Xiaofeng $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{1,2}$ , Shan Jiang4, Yongzhen Wu1, Yue-Biao Zhang4, He Tian1, Wei-Hong Zhu1 ✉ & Andrew I. Cooper1,2 ✉ \n\nCovalent organic frameworks (COFs) are distinguished from other organic polymers by their crystallinity1–3, but it remains challenging to obtain robust, highly crystalline COFs because the framework-forming reactions are poorly reversible4,5. More reversible chemistry can improve crystallinity6–9, but this typically yields COFs with poor physicochemical stability and limited application scope5. Here we report a general and scalable protocol to prepare robust, highly crystalline imine COFs, based on an unexpected framework reconstruction. In contrast to standard approaches in which monomers are initially randomly aligned, our method involves the pre-organization of monomers using a reversible and removable covalent tether, followed by confined polymerization. This reconstruction route produces reconstructed COFs with greatly enhanced crystallinity and much higher porosity by means of a simple vacuum-free synthetic procedure. The increased crystallinity in the reconstructed COFs improves charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to $27.98\\mathrm{mmol}\\mathrm{h}^{-1}\\mathbf{g}^{-1}.$ This nanoconfinement-assisted reconstruction strategy is a step towards programming function in organic materials through atomistic structural control. \n\nCovalent organic frameworks (COFs) are of growing interest for gas storage, separation, electronics and catalysis applications because of their predictable structures and ordered nanopores10–19. Two-dimensional COFs with π-stacking between the layers allow for charge carrier transport in aligned molecular columns, and these materials show promise for photoenergy conversion and optoelectronics20–31. However, material quality and sometimes demanding synthetic procedures can limit practical applications. In particular, the moderate level of crystallinity in two-dimensional COFs can compromise their performance in optoelectronic applications, and synthetic requirements such as vacuum sealing or strictly anaerobic conditions are practical hurdles to scale-up. \n\nCOFs are typically prepared by simultaneous polymerization and crystallization of monomers following the principle of dynamic covalent chemistry32. Reversible bond formation and structural self-healing have a central role in achieving long-range crystalline order. Strategies have been reported to produce COFs using more reversible chemistry, even to the point of obtaining single crystals6–9, but not all of these strategies lead to porosity. High degrees of crystallinity are much more difficult to obtain when the framework bonding is more robust and less reversible4,5,33. As such, there is a trade-off between stability—which is desirable for practical applications—and high levels of long-range crystalline order. An attractive strategy is to pre-organize monomers before polymerization. This separates the crystallization process from the (irreversible) bond forming step34–39. In this case, monomers are pre-arranged in the solid state to form an ordered self-assembled structure before the polymerization reaction. However, the pre-organization is often based on weak intermolecular interactions, and strain induced by the change in geometry that occurs during polymerization can cause fragmentation of crystallites or structural disorder. Thus, such reactions tend to be limited to mild photo-polymerizations in which the change in geometry is not too large34–36, although more profound structural transformations are possible when flat and rigid building blocks are used37,38. The success of these solid-state transformation strategies relies on appropriate molecular ordering, which is hard to design a priori: for example, pre-organized non-covalent molecular crystals can form different polymorphs in different crystallization solvents, which can thwart reticular framework strategies. \n\nConfinement effects are ubiquitous in the chemistry of life; they prevent the denaturation of proteins and allow the synthesis of complex biomolecules under mild conditions. Likewise in synthetic nanochemistry, confining molecules can profoundly affect reaction pathways by stabilizing reactive species, accelerating reactions or enhancing selectivity40,41. Here we present a reconstruction strategy for COF synthesis that uses a reversible and removable covalent tether to pre-organize monomers before an irreversible polymerization. This route yields highly crystalline and functional COF materials through a facile process (Fig. 1a). By stepwise control over temperature and solvent, we achieved a chemical reconstruction in pre-organized urea-linked COFs. Instead of becoming amorphous, solvothermal treatment initiates a multi-step conversion into ammonia and carbon dioxide gas. b, Transformation of the model compound. A small urea-linked model compound can also be converted into the corresponding $\\upbeta$ -ketoenamine product, but with low isolated yield (around $11\\%$ yield in the solid state in the presence of $\\mathrm{\\ddot{H}}_{2}\\mathrm{O}_{\\cdot}$ ; decomposition occurs when the model compound is dissolved in solution, $\\mathsf{N M P/H}_{2}\\mathsf{O}\\left(9/1\\mathsf{v}/\\mathsf{v}\\right)$ , and the $\\upbeta$ -ketoenamine product is not detected). \n\n![](images/51bdb45c32edbeafc08d6be855f567faa23bde7b9f875d77710472ac250573df.jpg) \nFig. 1 | Chemical reconstruction. a, The synthetic procedure for reconstructed COFs includes two steps: pre-organization of the monomers using reversible urea linkages to form a highly crystalline framework, followed by a solvothermal treatment step that removes the urea tethers, releasing monomers that then undergo in situ polymerization to form the reconstructed $\\upbeta$ -ketoenamine COF. The urea linkage acts as a disposable tether in this one-pot multi-step reaction, organizing the monomers before being removed by \n\nurea hydrolysis reaction followed by imine condensation. Notably, this generates a highly crystalline reconstructed COF (RC-COF) through a framework transformation, even though the mass loss during reconstruction can be as high as $36\\%$ . The position of the monomers that are produced by hydrolysis is directed by nanoconfinement in the framework before in situ polymerization. This results in greatly improved crystallinity and functional properties for the RC-COFs compared to directly polymerized imine frameworks, in which the monomers are aligned randomly before polymerization. \n\n# Structural transformation \n\nUrea chemistry is inexpensive and used in the large-scale manufacture of resins and adhesives. Urea-linked COFs have been synthesized previously42. Urea is quite stable, with a decomposition half-life of 3.6 years in aqueous solution $(38^{\\circ}\\mathsf{C})$ ; in industry, hydrolysis of urea feedstocks into ammonia and carbon dioxide is used for ammonia supply. This hydrolysis reaction is favoured by increased temperatures. We therefore speculated that raising the temperature could promote a structural change in urea-linked COFs. Urea-COF-1 (also known as COF-117; ref. 42) was first synthesized via a Schiff-base condensation reaction of 1,1'-(1,4-phenylene)diurea with 1,3,5-triformylphloroglucinol in a mixture of N-methyl-2-pyrrolidinone (NMP), 1,2-dichlorobenzene ( $\\mathbf{\\chi}_{O}$ -DCB) and aqueous acetic acid $(6\\mathsf{m o l l^{-1}},$ ) at $90^{\\circ}\\mathsf{C}$ for $72\\ensuremath{\\mathrm{h}}$ . Instead of isolating the powdered urea COF, we directly raised the temperature to 110, 120, 130, 150, 160 and $170^{\\circ}\\mathrm{C}$ , respectively, for a further $72\\mathrm{h}$ . A colour change from yellow to dark red was observed after raising the temperature (Fig. 2a), suggesting more extended electronic conjugation. The crystallinity of the solvated samples was assessed by powder X-ray diffraction (PXRD; Fig. 2a). When the reaction temperature was increased from $90^{\\circ}\\mathbf{C}$ to $160^{\\circ}\\mathsf C$ , the first intense diffraction peak was found to shift gradually from $2\\theta=3.5^{\\circ}$ to $4.6^{\\circ}$ . An increase in the reaction temperature to $170^{\\circ}\\mathrm{C}$ did not shift this peak any further (Supplementary Fig. 3). \n\n![](images/3429a940e6595dc4e8745fc5d33161690a4501dd1c93e40e790fda3e2941e3e8.jpg) \nFig. 2 | Thermal and water-triggered reconstruction. a, b, Evolution of the PXRD patterns (a) and FTIR spectra (b) for Urea-COF-1 as-synthesized at $90^{\\circ}\\mathsf{C}$ and treated at the in situ increased reaction temperatures of 110, 120, 130, 150 and $160^{\\circ}\\mathsf{C}$ for a further $72\\mathrm{h}$ , respectively, in an 8/2/1 mixture of NMP, $o$ -DCB and 6 mol l−1 acetic acid. The gradual shift in PXRD peak positions suggests a continuous structural transformation. Insets are photographs of isolated powders. AU, arbitrary units. c, d, Evolution of the PXRD patterns (c) and FTIR spectra (d) for isolated Urea-COF-1 treated by solvents with increased water \ncontent $\\scriptstyle{\\cdot}o$ -DCB, NMP, glacial acetic acid, ${\\mathsf{N M P}}/{\\mathsf{H}}_{2}{\\mathsf{O}}$ (9/1 v/v) and ${\\sf H}_{2}{\\sf O}$ , respectively) at $160^{\\circ}\\mathsf{C}$ for $72\\mathrm{h}$ . Insets are photographs of Urea-COF-1 (yellow) and RC-COF-1 (dark red) powders. A comparison of the FTIR spectrum with that of DP-COF-1, which was synthesized by direct imine polycondensation, is also shown in d. e, $^{13}\\mathrm{C}$ CP-MAS solid-state NMR spectra of Urea-COF-1, RC-COF-1 and DP-COF-1. Spinning sidebands are denoted with asterisks. Carbon atoms responsible for the NMR resonances are labelled A–F (for DP-COF-1 and RC-COF-1) and a–f (for Urea-COF-1). \n\nVarious solvents and solvent mixtures were investigated for this solvothermal treatment, such as $o$ -DCB, NMP, glacial acetic acid and water. We first isolated the Urea-COF-1 powders formed at $90^{\\circ}\\mathsf C$ after $72\\mathrm{h}$ , and then used these solvents or solvent mixtures to treat the urea COF in a sealed Pyrex tube, separately, at a fixed temperature of $160^{\\circ}\\mathrm{C}$ for a further 72 h (Fig. 2c). Urea-COF-1 decomposed in neat $o$ -DCB and NMP, and little solid material was isolated after thermal treatment. In glacial acetic acid, most of the solid was retained and the first diffraction peak shifted to $4.4^{\\circ}$ , suggesting an incomplete phase transformation. When Urea-COF-1 was treated with pure water at $160^{\\circ}\\mathsf C$ (Fig. 2c, Extended Data Fig. 1a), an intense diffraction peak appeared at $2\\theta=4.6^{\\circ}$ and the colour of the powder changed from yellow to dark red (RC-COF-1). A small quantity of water in NMP $\\mathrm{(NMP/H_{2}O;9/1v/v)}$ also promoted \n\n![](images/1a963adcd4e1320c9d6dad540749a4961b1eb7360226b5f8fa63e8fc047d099d.jpg) \nFig. 3 | See next page for caption. \n\n# Article \n\n# Fig. 3 | Reconstructed COFs with enhanced crystallinity and porosity. \n\na, b, Simulated and experimental PXRD patterns for Urea-COF-1 (solvated) (a) and RC-COF-1 (activated) (b). The structural models were built using Materials Studio and refined using experimental PXRD data. c, Comparison of PXRD patterns for RC-COF-1 synthesized by the reconstruction protocol and DP-COF-1 synthesized by direct polymerization. d, Nitrogen adsorption isotherm (filled symbols) and desorption isotherm (open symbols) for RC-COF-1, DP-COF-1 and Urea-COF-1 recorded at $77.318.$ ; RC-COF-1 shows a type I isotherm. e, SEM image of RC-COF-1. Scale bar, $1\\upmu\\mathrm{m}$ . f, HRTEM image of RC-COF-1. Insets show the FFT pattern taken from the regions highlighted by this reconstruction. These experiments demonstrate that the transformation was induced by water, along with the increased temperature. A high concentration of ammonium ion was detected from the aqueous solution (Supplementary Fig. 4). Elemental analysis showed a marked reduction in the nitrogen content for RC-COF-1 relative to Urea-COF-1 (11.89 versus $16.75\\mathrm{wt\\%}$ ), and the experimental weight loss during transformation $(36\\mathrm{wt\\%})$ was close to the proportion of urea in Urea-COF-1 (theoretical mass l $055=29\\mathrm{wt\\%}$ , ignoring any end groups. We therefore hypothesized that the urea-linked COF had transformed into a $\\upbeta$ -ketoenamine COF by solvothermal treatment in water, with ammonia and carbon dioxide being released as by-products (Fig. 1). RC-COF-1 retained high crystallinity after thermal desolvation under dynamic vacuum, in contrast to Urea-COF-1, which has flexible linkages and loses crystallinity after solvent removal42 (Extended Data Fig. 1b). \n\nTo further confirm the structure of RC-COF-1, we synthesized the same $\\upbeta$ -ketoenamine COF by direct polymerization (DP-COF-1; also known as TpPa-14) of 1,3,5-triformylphloroglucinol with $p$ -phenylenediamine according to reported procedures. $^{13}\\mathrm{C}$ cross-polarization magic angle spinning (CP-MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy showed the same resonances for RC-COF-1 and DP-COF-1, although the peaks were narrower and better resolved in RC-COF-1, suggesting increased structural order43 (Fig. 2e). Fourier transform infrared (FTIR) spectroscopy for activated Urea-COF-1 showed strong bands at around 1,713 and $3{,}285\\mathsf{c m}^{-1}$ , corresponding to urea $\\scriptstyle{\\mathbf{C}=0}$ and N–H groups (Fig. 2d). These bands disappeared after increasing the reaction temperature to $110\\mathrm{-}160^{\\circ}\\mathrm{C}$ (Fig. 2b); this change was even more noticeable when we increased the water content in the solvent (Fig. 2d), suggesting hydrolysis of the urea groups. Elemental analysis (Supplementary Table 1) and X-ray photoelectron spectroscopy (Supplementary Fig. 6) also supported the solvothermal transformation of Urea-COF-1 to the $\\upbeta$ -ketoenamine COF, RC-COF-1. \n\n# Improved crystallinity and surface area \n\nThe level of crystallinity in RC-COF-1 was markedly enhanced compared to its directly polymerized analogue, DP-COF-1 (Fig. 3c); RC-COF-1 showed prominent diffraction peaks at 4.6, 8.1, 9.3, 12.3, 14.0, 16.1, 16.6, 18.7, 20.3 and $27.1^{\\circ}$ , which were indexed as 100, 110, 200, 120, 300, 220, 130, 400, 410 and 001 reflections, respectively. By contrast, only four broad peaks could be discerned from the diffraction pattern of DP-COF-1, as measured using the same diffraction set-up and measurement conditions. Eclipsed AA-stacking models yielded PXRD patterns that were consistent with the experimental profiles of Urea-COF-1 and RC-COF-1 (Supplementary Figs. 9, 17). Pawley refinement in the $P6/m$ space group with unit cell parameters of $a=29.39$ , $b=29.39$ , $\\pmb{c}=3.56\\mathring{\\mathbf{A}}$ (Fig. 3a) and $a=22.04$ , $b=22.04$ , $c=3.49\\mathring{\\mathbf{A}}$ (Fig. 3b) reproduced the experimental curve with good agreement factors (weight-profile $R$ -factor $R_{\\mathrm{wp}}=5.52\\%$ and unweighted $R$ -factor $R_{\\mathrm{p}}=4.34\\%$ for Urea-COF-1, and $R_{\\mathrm{wp}}=4.64\\%$ and $R_{\\mathrm{p}}=3.36\\%$ for RC-COF-1), which suggested a pronounced contraction of the unit cell after reconstruction. \n\nThe porosity of these COFs was evaluated by nitrogen adsorption measurements at $77.3\\mathsf{K}$ (Fig. 3d). Urea-COF-1 showed a low Brunauer–Emmett–Teller (BET) surface area of $38{\\mathfrak{m}}^{2}{\\mathfrak{g}}^{-1}$ because of the dashed-line squares and the corresponding filtered inverse FFT image. Scale bars, $50\\mathrm{nm}$ (main image); $10\\mathsf{n m}$ (inset). $\\mathbf{g}$ –i, Simulated and experimental PXRD patterns for RC-COF-2 (g), RC-COF-3 (h) and RC-COF-4 (i), and comparison with PXRD patterns of DP-COF-2, DP-COF-3 and DP-COF-4 synthesized by direct polymerization. j, Nitrogen adsorption isotherm (filled symbols) and desorption isotherm (open symbols) for RC-COF-2, RC-COF-3, RC-COF-4 and directly polymerized analogues. k, l, HRTEM images of RC-COF-2 (k) and RC-COF-3 (l). Insets show FFT patterns and the corresponding filtered inverse FFT images. Scale bars, $50\\mathrm{nm}$ (main images); $10\\mathsf{n m}$ (insets). \n\npore deformation upon activation42. This increased to $\\mathbf{1},7\\mathbf{1}2\\mathbf{m}^{2}\\mathbf{g}^{-1}$ for RC-COF-1, which showed a type I gas adsorption isotherm with rapid gas uptake at low relative pressures $(P/P_{0}{<}0.01)$ , indicating a highly microporous solid (Fig. 3d, Extended Data Fig. 2). The narrow pore size distribution of around $1.6\\:\\mathrm{nm}$ obtained from the adsorption isotherm using nonlocal density functional theory fitting was in precise agreement with the proposed structural model (Extended Data Fig. 3). By contrast, DP-COF-1 adsorbed much less gas (Fig. 3d) and showed a much lower BET surface area of $580\\mathsf{m}^{2}\\mathsf{g}^{-1}$ , close to previous reports for this material4 $(535\\mathsf{m}^{2}\\mathsf{g}^{-1})$ . The broader, less regular pore size distribution for DP-COF-1 (Extended Data Fig. 3) can be ascribed to its semi-crystalline nature. The high crystallinity and regular porosity of RC-COF-1 also translated into high ${\\mathsf{C O}}_{2}$ uptake, as shown by gas adsorption isotherms collected at 273 K (Extended Data Fig. 4a). RC-COF-1 showed a $\\mathbf{CO}_{2}$ uptake of $147\\:\\mathrm{cm}^{3}\\:\\mathbf{g}^{-1}\\left(28.9\\:\\mathrm{wt}\\%\\right)$ at 1 bar. This is to our knowledge the highest ${\\mathsf{C O}}_{2}$ capacity reported in COFs under these measurement conditions44 (Extended Data Fig. 4b). The calculated heat of adsorption was around 35 kJ mol−1 at the adsorption onset (Supplementary Fig. 33), which is comparable to related small-pore COFs with high $\\mathbf{CO}_{2}$ uptakes44. The directly polymerized analogue, DP-COF-1, showed a similar heat of adsorption but a much lower ${\\mathsf{C O}}_{2}$ uptake (Supplementary Fig. 32). RC-COF-1 also showed excellent chemical stability after treatment with concentrated HCl (12 mol $1^{-1}$ ) and NaOH (14 mol l−1) solution for $24\\mathsf{h}$ (Extended Data Fig. 5). \n\nScanning electron microscopy (SEM) showed that RC-COF-1 comprised uniform rod-like crystallites with an average size of around $600\\mathsf{n m}$ (Fig. 3e), whereas DP-COF-1 was composed of less regular aggregates (Supplementary Fig. 35c). The high crystallinity for RC-COF-1 allowed us to confirm its periodic porous structure using high-resolution transmission electron microscopy (HRTEM). Reticular structures with hexagonal pores oriented perpendicular to the crystallographic c axis were observed (Fig. 3f). The calculated distance between the centres of two adjacent pores was $2.2\\mathsf{n m}$ , in good agreement with the refined eclipsed model. Fast Fourier transform (FFT) conducted on a selected area showed a hexagonal symmetry; by contrast, no lattice fringes were discerned for DP-COF-1 prepared by direct polymerization (Supplementary Fig. 37a). \n\nWe next considered the generality of this reconstruction protocol for other COFs. For Urea-COF-2 (also known as COF-118; ref. 42), we used a commercially available isocyanate as the starting material; for Urea-COF-3 and Urea-COF-4, we used more widely accessible arylamine monomers, which could be easily converted into diureas before pre-organization (Fig. 1, Supplementary Fig. 7). Again, these three reconstructed COFs (RC-COF-2, RC-COF-3 and RC-COF-4) all showed superior crystallinity relative to COFs that were prepared by direct polymerization as per previously reported procedures (DP-COF-2 (also known as TpBD- $\\cdot\\mathsf{M}\\mathsf{e}_{2}$ ; ref. 45), DP-COF-3 (or TpBD; ref. 46) and DP-COF-4 (or TP-EDDA; ref. 24)), and all showed sharp and well-resolved diffraction peaks (Fig. 3g–i). Indeed, the difference in crystallinity levels between the pre-organized, reconstructed COF and its direct polycondensation analogue was even more pronounced for the mesoporous COF, RC-COF-4, which has the largest pores in this series of materials. Nitrogen adsorption measurements revealed greatly increased surface areas and pore volumes for the reconstructed COFs (Fig. 3j, Extended Data Fig. 2); BET surface areas increased from $623{\\mathsf{m}}^{2}{\\mathsf{g}}^{-1}$ (DP-COF-2) to $2,792\\mathsf{m}^{2}\\mathsf{g}^{-1}$ (RC-COF-2); from $573\\mathsf{m}^{2}\\mathsf{g}^{-1}$ (DP-COF-3) to $2,461\\mathsf{m}^{2}\\mathsf{g}^{-1}$ (RC-COF-3); and from $877{\\mathrm{m}}^{2}\\mathbf{g}^{-1}$ (DP-COF-4) to $2,301\\mathsf{m}^{2}\\mathsf{g}^{-1}$ (RC-COF-4). As such, the surface areas of the reconstructed COFs were between 2.6 and 4.5 times larger than the directly polymerized analogues. Likewise, the measured pore volumes were two to four times higher for the reconstructed COFs than for directly polymerized analogues. Pore size distribution profiles indicated the mesoporous nature of RC-COF-2, RC-COF-3 and RC-COF-4, with pore sizes of 2.3, 2.4 and $2.8\\mathsf{n m}$ , respectively, in precise agreement with their structural models; whereas directly polymerized COFs show broader pore size distributions (Extended Data Fig. 3). HRTEM images (Fig. 3k, l, Supplementary Fig. 36) showed ordered porous structures extending through the crystal domains with clearly visible honeycomb pores, and the periodicities were consistent with the unit cell derived from the Pawley refined PXRD data. Few such ordered domains could be observed in the directly polymerized analogues (Supplementary Fig. 37). The reconstructed COFs also showed better thermal stability than the directly polymerized analogues, presumably because of their enhanced crystallinity (Supplementary Fig. 34). The increased crystallinity in RC-COF-1 improves photogenerated charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to $27.98\\mathrm{mmolh^{-1}g^{-1}}$ This is one of the highest activities reported for a COF photocatalyst and four times higher than the chemically equivalent but less ordered DP-COF-1 (Extended Data Figs. 6, 7, Supplementary Information). \n\n![](images/111c95f2782f945c4f30a19070e694b0c2518df756a4eebb7197937dfa165df6.jpg) \nFig. 4 | Reconstruction protocol with DFT calculations. a, b, Scheme showing the reaction paths for direct imine polycondensation and reconstruction synthesis (a). Direct polymerization yields only semi-crystalline COFs owing to the poor reversibility of the $\\upbeta$ -ketoenamine linkage, whereas decoration with urea groups decreases the reactivity and increases the reversibility, which leads to highly crystalline Urea-COFs (b); these then undergo framework reconstruction into $\\upbeta$ -ketoenamine RC-COFs with retained crystallinity. c, DFT-optimized geometries of phenylene amine \nmolecules released by hydrolysis, confined on the surface of the reconstructing COF. The results of hydrolysis of a single urea bond (top) and both urea bonds (bottom) are shown. Coloured isosurfaces are the intermolecular interactions quantified by an independent gradient model (isosurface $\\mathbf{\\varepsilon}=0.003$ atomic units). In the bottom example, the interactions between the COF layers are omitted to highlight the interaction between the $p$ -phenylenediamine monomer and the framework. \n\n# Density functional theory calculations \n\nDensity functional theory (DFT) calculations were used to investigate this reconstruction protocol in more detail. Direct polymerization of 1,3,5-triformylphloroglucinol with $p$ -phenylenediamine yields \n\n# Article \n\nrather low crystallinity because of the poorly reversible bond formation and the tautomerization into a stable $\\upbeta$ -ketoenamine form4 (Fig. 4a, Supplementary Fig. 42a), which does not allow for full error correction. As a result, the directly polymerized product, DP-COF-1, does not attain the crystalline thermodynamic minimum structure (Fig. 4b). By contrast, decorating arylamine monomers with urea groups decreases the reactivity and enhances the reversibility for the bond formation (Supplementary Fig. 42b). This yields a highly crystalline but ‘soft’ urea precursor framework. Typically, hydrolysis of crystalline frameworks might lead to amorphization, but here, under appropriate solvothermal conditions (Fig. 2c), confinement in the framework coupled with fast imine condensation leads to the retention of crystallinity, together with a high conversion yield. The nature of the reconstruction process is revealed by the evolution of PXRD patterns recorded at different time intervals (Extended Data Fig. 1a). The diffraction peaks were found to shift continuously47, with no detectable disorder during the reconstruction. We suggest that the reconstruction in each COF crystallite has relatively slow kinetics with respect to the PXRD collection timescale. The gradual shift in peak positions indicates a smooth, continuous shrinkage of the lattice upon hydrolysis and re-polymerization. By contrast, if a rapid and concerted phase transformation was occurring, then we would expect to observe two distinct sets of interconverting PXRD peaks48, and no intermediate phases would be observed. \n\nThe simulation in Fig. 4c suggests well-defined non-covalent interactions in the framework when the urea linkage is hydrolysed. When a single urea bond is cleaved (Fig. 4c), strong hydrogen bonding is found in these simulations at the hydrolysis position between the resulting amine group and fragments of the COF in the same layer, which maintains the position of the molecule in the framework. When both urea bonds are cleaved (Fig. 4c), the $p$ -phenylenediamine molecule that is produced by hydrolysis is still captured by the framework through hydrogen bonds. The π-π stacking between $p$ -phenylenediamine and the adjacent COF layer reinforces these interactions (binding energy of around –16.08 kcal mol−1). We suggest that this nanoconfinement in the framework also stabilizes and protects the amine species by preventing the entry of other reactive species, contributing to the high yield of this multi-step reconstruction reaction. By contrast, such confinement is absent for the small-molecule model compounds (Fig. 1b) and the monomers can become disordered or react with other solution species once the urea linkages are hydrolysed. \n\n# A convenient synthetic route \n\nVacuum sealing procedures are often necessary for COF syntheses to prevent oxidation of the arylamine monomers under solvothermal conditions. Freeze-pump-thaw procedures can be performed in a research laboratory, but they could represent a major hurdle for industrial scale-up. By decorating with urea groups, we decrease the reactivity of the monomers and provide better oxidation resistance, and hence this reconstruction approach can be conducted without any vacuum degassing steps (Extended Data Fig. 8, Supplementary Information), while affording equivalent crystallinity and porosity (BET surface area $S_{\\scriptscriptstyle\\mathrm{BET}}=1,650\\mathrm{m}^{2}\\mathrm{g}^{-1}$ for RC-COF-1) relative to reactions that were performed with vacuum sealing $(S_{\\mathrm{{BET}}}{=}1,712\\mathrm{{m}^{2}\\mathbf{g}^{-1})}$ . Such simple vacuum-free, aqueous processes might prove decisive for the viable commercial scale-up of highly crystalline COFs, for which vacuum degassing and inertization are costly. \n\n# Outlook \n\nCOFs can be highly crystalline or physicochemically robust, but rarely both5. On the basis of an unexpected framework reconstruction in urea COFs, we have established a general and scalable vacuum-free protocol to synthesize highly crystalline imine frameworks by using a reversible and removable urea linkage as a disposable tether to pre-organize monomers before irreversible polymerization. This separates the crystallization process from the formation of robust framework bonds. The removable covalent tether is stronger and more directional compared to the non-covalent interactions in strategies in which monomers are pre-organized in molecular crystals. The superior level of structural order in reconstructed COFs presents new opportunities for applications such as gas adsorption and photocatalysis. We used urea tethers here, but it is likely that other covalent pre-organization chemistries could be devised to access other frameworks. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-022-04443-4. \n\n1. Côté, A. P. et al. Porous, crystalline, covalent organic frameworks. Science 310, 1166–1170 (2005). \n2. Diercks, C. S. & Yaghi, O. M. The atom, the molecule, and the covalent organic framework. Science 355, eaal1585 (2017). \n3. Slater, A. G. & Cooper, A. I. Function-led design of new porous materials. Science 348, aaa8075 (2015). \n4. Kandambeth, S. et al. Construction of crystalline 2D covalent organic frameworks with remarkable chemical (acid/base) stability via a combined reversible and irreversible route. J. Am. Chem. Soc. 134, 19524–19527 (2012). \n5. Haase, F. & Lotsch, B. V. Solving the COF trilemma: towards crystalline, stable and functional covalent organic frameworks. Chem. Soc. Rev. 49, 8469–8500 (2020). \n6. Beaudoin, D., Maris, T. & Wuest, J. D. Constructing monocrystalline covalent organic networks by polymerization. Nat. Chem. 5, 830–834 (2013). \n7. Ma, T. et al. Single-crystal x-ray diffraction structures of covalent organic frameworks. Science 361, 48–52 (2018). \n8. Evans, A. M. et al. Seeded growth of single-crystal two-dimensional covalent organic frameworks. Science 361, 52–57 (2018). \n9. Hu, Y. et al. Single crystals of mechanically entwined helical covalent polymers. Nat. Chem. 13, 660–665 (2021). \n10.\t Ascherl, L. et al. Molecular docking sites designed for the generation of highly crystalline covalent organic frameworks. Nat. Chem. 8, 310–316 (2016). \n11. Guan, X. et al. Chemically stable polyarylether-based covalent organic frameworks. Nat. Chem. 11, 587–594 (2019). \n12. Jin, E. et al. Two-dimensional $\\mathsf{s p}^{2}$ carbon-conjugated covalent organic frameworks. Science 357, 673–676 (2017). \n13. Li, X. et al. Partitioning the interlayer space of covalent organic frameworks by embedding pseudorotaxanes in their backbones. Nat. Chem. 12, 1115–1122 (2020). \n14.\t Zhao, S. et al. Hydrophilicity gradient in covalent organic frameworks for membrane distillation. Nat. Mater. 20, 1551–1558 (2021). \n15. Liang, R. et al. Rational design of crystalline two-dimensional frameworks with highly complicated topological structures. Nat. Commun. 10, 4609 (2019). \n16.\t Zhang, L. et al. Covalent organic framework for efficient two-photon absorption. Matter 2, 1049–1063 (2020). \n17.\t Wang, Z., Zhang, S., Chen, Y., Zhang, Z. & Ma, S. Covalent organic frameworks for separation applications. Chem. Soc. Rev. 49, 708–735 (2020). \n18.\t Dong, J., Han, X., Liu, Y., Li, H. & Cui, Y. Metal–covalent organic frameworks (MCOFS): a bridge between metal–organic frameworks and covalent organic frameworks. Angew. Chem. Int. Edn 59, 13722–13733 (2020). \n19.\t Zhu, H. et al. Efficient electron transmission in covalent organic framework nanosheets for highly active electrocatalytic carbon dioxide reduction. Nat. Commun. 11, 497 (2020). \n20.\t Banerjee, T., Podjaski, F., Kröger, J., Biswal, B. P. & Lotsch, B. V. Polymer photocatalysts for solar-to-chemical energy conversion. Nat. Rev. Mater. 6, 168–190 (2021). \n21. Vyas, V. S. et al. A tunable azine covalent organic framework platform for visible light-induced hydrogen generation. Nat. Commun. 6, 8508 (2015). \n22. Wang, X. et al. Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water. Nat. Chem. 10, 1180–1189 (2018). \n23.\t Wang, Y. et al. Current understanding and challenges of solar-driven hydrogen generation using polymeric photocatalysts. Nat. Energy 4, 746–760 (2019). \n24.\t Pachfule, P. et al. Diacetylene functionalized covalent organic framework (COF) for photocatalytic hydrogen generation. J. Am. Chem. Soc. 140, 1423–1427 (2018). \n25. Jin, E. et al. $2\\mathsf{D}\\mathsf{s p}^{2}$ carbon-conjugated covalent organic frameworks for photocatalytic hydrogen production from water. Chem 5, 1632–1647 (2019). \n26.\t Ghosh, S. et al. Identification of prime factors to maximize the photocatalytic hydrogen evolution of covalent organic frameworks. J. Am. Chem. Soc. 142, 9752–9762 (2020). \n27.\t Bi, S. et al. Two-dimensional semiconducting covalent organic frameworks via condensation at arylmethyl carbon atoms. Nat. Commun. 10, 2467 (2019). \n28.\t Chen, R. et al. Rational design of isostructural 2D porphyrin-based covalent organic frameworks for tunable photocatalytic hydrogen evolution. Nat. Commun. 12, 1354 (2021). \n29.\t Chen, W. et al. Modulating benzothiadiazole-based covalent organic frameworks via halogenation for enhanced photocatalytic water splitting. Angew. Chem. Int. Edn 59, 16902–16909 (2020). \n30.\t Colson, J. W. et al. Oriented 2D covalent organic framework thin films on single-layer graphene. Science 332, 228–231 (2011). \n31.\t Wang, M. et al. Unveiling electronic properties in metal-phthalocyanine-based pyrazine-linked conjugated two-dimensional covalent organic frameworks. J. Am. Chem. Soc. 141, 16810–16816 (2019). \n32.\t Kandambeth, S., Dey, K. & Banerjee, R. Covalent organic frameworks: chemistry beyond the structure. J. Am. Chem. Soc. 141, 1807–1822 (2019). \n33.\t Li, X. et al. Chemically robust covalent organic frameworks: progress and perspective. Matter 3, 1507–1540 (2020). \n34.\t Kissel, P. et al. A two-dimensional polymer prepared by organic synthesis. Nat. Chem. 4, 287–291 (2012). \n35.\t Kory, M. J. et al. Gram-scale synthesis of two-dimensional polymer crystals and their structure analysis by x-ray diffraction. Nat. Chem. 6, 779–784 (2014). \n36.\t Kissel, P., Murray, D. J., Wulftange, W. J., Catalano, V. J. & King, B. T. A nanoporous two-dimensional polymer by single-crystal-to-single-crystal photopolymerization. Nat. Chem. 6, 774–778 (2014). \n37.\t Liu, W. et al. A two-dimensional conjugated aromatic polymer via C–C coupling reaction. Nat. Chem. 9, 563–570 (2017). \n38.\t Liu, W. et al. Two-dimensional polymer synthesized via solid-state polymerization for high-performance supercapacitors. ACS Nano 12, 852–860 (2018). \n39.\t Liu, K. et al. On-water surface synthesis of crystalline, few-layer two-dimensional polymers assisted by surfactant monolayers. Nat. Chem. 11, 994–1000 (2019). \n40.\t Grommet, A. B., Feller, M. & Klajn, R. Chemical reactivity under nanoconfinement. Nat. Nanotechnol. 15, 256–271 (2020). \n41.\t Iwasawa, T., Hooley, R. J. & Rebek, J. Stabilization of labile carbonyl addition intermediate by a synthetic receptor. Science 317, 493–496 (2007). \n42.\t Zhao, C. et al. Urea-linked covalent organic frameworks. J. Am. Chem. Soc. 140, 16438–16441 (2018). \n43.\t Ma, T. et al. Diverse crystal size effects in covalent organic frameworks. Nat. Commun. 11, 6128 (2020). \n44.\t Gao, Q. et al. Covalent organic framework with frustrated bonding network for enhanced carbon dioxide storage. Chem. Mater. 30, 1762–1768 (2018). \n45.\t Chandra, S. et al. Chemically stable multilayered covalent organic nanosheets from covalent organic frameworks via mechanical delamination. J. Am. Chem. Soc. 135, 17853–17861 (2013). \n46.\t Biswal, B. P. et al. Mechanochemical synthesis of chemically stable isoreticular covalent organic frameworks. J. Am. Chem. Soc. 135, 5328–5331 (2013). \n47.\t Carrington, E. J. et al. Solvent-switchable continuous-breathing behaviour in a diamondoid metal–organic framework and its influence on $\\mathsf{C O}_{2}$ versus $\\mathsf{C H}_{4}$ selectivity. Nat. Chem. 9, 882–889 (2017). \n48.\t Reed, D. A. et al. A spin transition mechanism for cooperative adsorption in metal–organic frameworks. Nature 550, 96–100 (2017). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate \n\ncredit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 \n\n# Article Methods \n\n# Chemicals \n\nAll reagents were obtained from Sigma-Aldrich, Fisher Chemical, Adamas, Jilin Chinese Academy of Sciences–Yanshen Technology or Shanghai Tensus Bio-Chem Technology and used as received. Carbon nitride was bought from Carbodeon. Solvents were obtained from commercial sources and used without further purification. A sulfone-decorated imine COF, FS-COF, was synthesized according to previous literature22. \n\n# Liquid NMR spectroscopy \n\n$\\mathsf{\\Omega}^{\\mathrm{1}}\\mathsf{H}$ and $^{13}\\mathsf{C}$ NMR spectra were recorded in solution at $400\\mathsf{M H z}$ and ${\\bf100M H z}$ , respectively, using a Bruker Avance 400 NMR spectrometer. \n\n# High-resolution mass spectrometry \n\nThe high-resolution mass spectrometry data were obtained using a Waters LCT Premier XE spectrometer. \n\n# Powder X-ray diffraction \n\nPXRD patterns were recorded on a Bruker D8 Advance diffractometer with Cu Kα radiation with a voltage of $40\\mathsf{k V}.$ Data were collected in the $2\\theta$ range of $2^{-40^{\\circ}}$ with steps of $0.02^{\\circ}$ . \n\n# Fourier transform infrared spectroscopy \n\nThe FTIR spectra were recorded on neat samples in the range of 4,000– $650\\mathrm{cm}^{-1}$ on a PerkinElmer FTIR spectrometer equipped with a single reflection diamond ATR module. \n\n# $\\pmb{x}$ -ray photoelectron spectroscopy \n\nX-ray photoelectron spectroscopy (XPS) data were measured in powder form using an ESCALAB 250Xi instrument (Thermo Fisher Scientific) with a monochromatized Al Kα line source. \n\n# Elemental microanalyses \n\nElemental microanalyses were measured in the Research Center of Analysis and Test of East China University of Science and Technology using the EURO EA3000 Elemental Analyzer. \n\n# Solid-state NMR spectroscopy \n\nThe solid-state $^{13}{\\mathsf C}$ NMR spectra were recorded on a Bruker Avance 400 NMR spectrometer with CP-MAS at a $^{13}{\\mathsf C}$ frequency of 100 MHz under 12 kHz spinning rate under MAS condition. \n\n# Thermogravimetric analyses \n\nThermogravimetric analyses were performed on an EXSTAR6000 by heating samples at $20^{\\circ}\\mathrm{C}\\mathsf{m i n}^{-1}$ under a nitrogen atmosphere to $800^{\\circ}\\mathsf{C}$ . \n\n# Gas adsorption analysis \n\nApparent surface areas were measured by nitrogen adsorption at $77.31(\\$ using a Micromeritics ASAP 2020 volumetric adsorption analyser. Powder samples were degassed offline at 393 K for 12 h under a dynamic vacuum $(10^{-5}\\mathsf{b a r})$ . Before the adsorption test, the inert gas was removed using a high vacuum provided by the turbo molecular drag pump. The specific surface areas were evaluated using the BET model. Pore size distributions of COFs were obtained from fitting the nonlocal density functional theory to the adsorption data. \n\nLow-pressure gas adsorption measurements of $\\mathbf{CO}_{2}$ (273, 283, 293 and 308 K) were performed on MicrotacBELsorp Max and MaxII gas adsorption analysers. Ultrahigh-purity (higher than $99.999\\%$ ) $\\mathbf{CO}_{2}$ in compressed gas cylinders was used throughout all experiments. Samples were degassed at 393 K for 12 h before measurement. ${\\mathsf{C O}}_{2}$ adsorption isotherms of each COF were then fitted with virial model equations as follows: \n\n$$\n\\ln(p)=\\ln(N)+{\\frac{1}{T}}\\sum_{\\mathrm{i}=0}^{m}a_{\\mathrm{i}}{\\times}N^{\\mathrm{i}}+\\sum_{\\mathrm{j}=0}^{n}b_{\\mathrm{j}}{\\times}N^{\\mathrm{j}},\n$$ \n\nin which $N$ is the amount adsorbed (or uptake) in $\\mathbf{mmol}\\mathbf{g}^{-1};p$ is the pressure in kPa; T is the temperature in K; and $m$ and $n$ are multinomial coefficients that determine the isosteric heat. \n\nThe isosteric heat of each COF was calculated from the virial fitting adsorption isotherms by using the Clausius–Clapeyron equation, in which $Q_{\\mathrm{st}}$ is the isosteric heat in J $\\mathsf{m o l}^{-1}$ , T is the temperature in K, $P$ is the pressure in kPa, and $R$ is the gas constant $(8.314\\mathrm{{J}K^{-1}\\mathsf{m o l^{-1}})}$ : \n\n$$\n-Q_{\\mathrm{st}}^{}{=}R T^{2}\\Bigg(\\frac{\\partial\\ln P}{\\partial T}\\Bigg)_{n}\n$$ \n\n# Scanning electron microscopy \n\nCOF morphologies were imaged using a field-emission scanning electron microscope (Helios G4 UC, Thermo Fisher Scientific). \n\n# Transmission electron microscopy \n\nTransmission electron microscopy (TEM) characterizations were performed on a Themis Z microscope (Thermo Fisher Scientific) equipped with two aberration correctors under $200\\mathsf{k V}.$ To minimize the electron beam damage, a cryo-transfer TEM holder (Model 2550, Fischione Instruments) was used, and the temperature was set below $-175^{\\circ}\\mathsf{C}$ during TEM imaging. \n\n# Ultraviolet-visible absorption spectroscopy \n\nUltraviolet (UV)-visible absorption spectra of the COFs were recorded on a PerkinElmer Lambda 950 UV-vis-NIR spectrometer by measuring the reflectance of powders in the solid state. \n\n# Photoluminescence spectroscopy \n\nPhotoluminescence spectra were recorded on a Varian Cary Eclipse fluorescence spectrophotometer by measuring the powders in the solid state. \n\n# Electron paramagnetic resonance spectroscopy \n\nElectron paramagnetic resonance (EPR) spectra were acquired at room temperature under ambient conditions using a Bruker EMX-8/2.7 spectrometer. COF powders were taken in an EPR tube and excited with a 300-W Xe lamp using a $420\\cdot\\mathrm{nm}$ filter. \n\n# Time-correlated single photon counting measurements \n\nTime-correlated single photon counting measurements were performed on an Edinburgh Instruments LS980-D2S2-STM spectrometer equipped with picosecond-pulsed LED excitation sources and an R928 detector, with a stop count rate below $3\\%$ . An EPL-375 diode $(\\lambda=370.5\\mathsf{n m}$ , instrument response 100 ps, full width at half maximum, FWHM) with a $450\\cdot\\mathrm{nm}$ high-pass filter for emission detection was used. Suspensions were prepared by ultrasonicating the COF in water. The instrument response was measured with colloidal silica (LUDOX HS-40, Sigma-Aldrich) at the excitation wavelength without filter. Decay times were fitted in FAST software using suggested lifetime estimates. \n\n# Photoelectrochemical measurements \n\nIndium tin oxide (ITO) glasses were cleaned by sonication in ethanol and acetone for 30 min respectively, then dried under nitrogen flow. Two milligrams of COF was dispersed in $0.2\\mathsf{m l}$ ethanol with $\\upmu\\mathrm{110}$ ten  Nafion solution $(5\\mathrm{wt\\%}$ in a mixture of lower aliphatic alcohols and water) and ultrasonicated for 20 min to give a homogenous suspension. ITO glass slides were covered with a copper mask giving an area of $0.28\\mathsf{c m}^{2}$ . Ten microlitres of the suspension was drop-casted on the ITO glass and dried overnight at room temperature. Electrochemical impedance spectroscopy and photocurrent response were performed using a Bio-Logic SP-200 electrochemical system. A three-electrode set-up was used with a working electrode (COF on ITO glass), counter electrode (platinum plate) and reference electrode (Ag/AgCl), and the bias voltage was −0.35 V. A 300-W Newport Xe light source (model 6258, ozone-free) with a $420\\cdot\\mathrm{nm}$ filter was used to illuminate the samples. A solution of $0.5\\mathsf{M N a}_{2}\\mathsf{S O}_{4}(\\mathsf{p H}=6.8)$ was used for measurement. \n\n# Photocatalytic hydrogen evolution experiments \n\nA quartz flask was charged with the photocatalyst powder $(2.5\\mathsf{m g})$ , 0.1 mol $\\mathsf{I}^{-1}$ ascorbic acid water solution $(25\\mathsf{m l})$ and a certain amount of platinum (Pt) as a cocatalyst, using hexachloroplatinic acid as a Pt precursor. The resulting suspension was ultrasonicated until the photocatalyst was well-dispersed before degassing by $\\mathsf{N}_{2}$ bubbling for $30\\mathrm{min}$ . The reaction mixture was illuminated with a 300 W Newport Xe light source (model 6258, ozone-free) using appropriate filters for the time specified under atmospheric pressure. The Xe light source was cooled by water circulating through a metal jacket. The samples were first illuminated for 5 h to complete Pt photo-deposition; then the flask was degassed by $\\mathsf{N}_{2}$ bubbling for 30 min followed by the photocatalysis reaction. Gas samples were taken with a gas-tight syringe and run on a Bruker 450-GC gas chromatograph. Hydrogen was detected with a thermal conductivity detector referencing against standard gas with a known concentration of hydrogen. Hydrogen dissolved in the reaction mixture was not measured and the pressure increase generated by the evolved hydrogen was not considered in the calculations. The rates were determined from a linear regression fit. After 5 h of photocatalysis, no carbon monoxide associated with framework or ascorbic acid decomposition could be detected on a gas chromatography system equipped with a pulsed discharge detector. \n\nFor stability measurements, a flask was charged with $2.5\\mathrm{mg}$ of COF photocatalyst, $0.1\\mathrm{moll^{-1}}$ ascorbic acid water solution $(25\\mathsf{m l})$ and a certain amount of Pt $(3\\mathrm{wt\\%})$ as a cocatalyst, using hexachloroplatinic acid as a Pt precursor. The resulting suspension was ultrasonicated to obtain a well-dispersed suspension, then transferred into a quartz reactor connected to a closed gas system (Labsolar-6A, Beijing Perfectlight). The reaction mixture was evacuated several times to ensure complete removal of oxygen, and the pressure was set to 13.33 kPa . The reactor was irradiated in a $90^{\\circ}$ angle with a 300-W Xe light-source. The wavelength of the incident light was controlled using a 420-nm long-pass cut-off filter. The temperature of the reaction solution was maintained at $10^{\\circ}\\mathsf{C}$ by circulation of cool water. The evolved gases were detected on an online gas chromatograph (Shimadzu GC 2014C) with a thermal conductive detector. After the photocatalysis experiment, the photocatalyst was recovered by washing with water then solvent exchange with methanol and tetrahydrofuran, respectively, before drying at $60^{\\circ}\\mathrm{C}$ under a vacuum. \n\n# Measurement of external quantum efficiencies \n\nThe external quantum efficiencies (EQEs) for the photocatalytic ${\\sf H}_{2}$ evolution were measured using monochromatic LED lamps $\\scriptstyle(\\lambda=420$ , 490, 515 and $595\\mathsf{n m}$ , respectively). For the experiments, the photocatalyst $(2.5\\mathsf{m g})$ with Pt loading was suspended in an aqueous solution containing ascorbic acid $\\mathrm{(0.1moll^{-1})}$ . The light intensity was measured with a ThorLabs S120VC photodiode power sensor controlled by a ThorLabs PM100D Power and Energy Meter Console. The EQEs were estimated using the equation: \n\n$$\n\\mathrm{EQE(\\%)=\\frac{2\\times\\mathrm{Number~of~evolved}H_{2}m o l e c u l e s}{N u m b e r~o f~i n c i d e n t~p h o t o n s}\\times100\\%}\n$$ \n\n# Computational methods \n\nPeriodic DFT calculations were performed within the plane-wave pseudopotential formalism, using the Vienna ab initio simulation package (VASP) code49. The projector augmented-wave method was applied to describe the electron–ion interactions50,51. A kinetic-energy cut-off of $500\\mathrm{eV}$ was used to define the plane-wave basis set, and the electronic Brillouin zone was integrated using Γ-centred Monkhorst−Pack grids with the smallest allowed spacing between $k$ -points (KSPACING) being $0.25\\mathring{\\mathbf{A}}^{-1}$ . Geometry optimizations were performed using the \n\nPerdew−Burke−Ernzerhof exchange−correlation functional with the DFT-D3(BJ) dispersion correction52–54. Tolerances of $10^{-6}$ eV and $10^{-2}\\boldsymbol{\\mathrm{eV}}\\mathring{\\mathbf{A}}^{-1}$ were applied during the optimization of the Kohn−Sham wavefunctions and the geometry optimizations, respectively. \n\nFor crystal structures of COFs, both lattice parameters and atomic positions are allowed to change during geometry optimization. The electronic structures of the optimized RC-COF-1 and Urea-COF-1 structures were then computed using a screened hybrid exchange−correlation functional (HSE06), giving key electronic properties, such as band gap and electrostatic potential, for comparison of the COFs. Within periodic boundary conditions, the electronic eigenvalues are given with respect to an internal reference. To achieve valence band alignment, using a common vacuum level, so that band energies can be compared for the different COF structures, we followed an approach devised for determining the vacuum level of porous structures55. \n\nFor the binding model constructed for the hydrolysis products of the COF, the hydrolysis-released $p$ -phenylenediamine monomer was assumed to be trapped in a three-layer COF model, with the first layer being decomposed. The periodic COF layer was parallel to the XY plane and separated from its periodic images along the Z direction by a vacuum of around $14\\mathring{\\mathsf{A}}^{-1}$ . The lattice parameters were fixed, and the atomic positions were fully optimized during this process. \n\nThe binding energy was computed using the following formula: \n\n$$\n\\Delta E_{\\mathrm{bind}}=E_{\\mathrm{system}}-E_{\\mathrm{monomer}}-E_{\\mathrm{framework}},\n$$ \n\nin which $\\boldsymbol{E}_{\\mathrm{{system}}}$ is the energy of COF with the first layer hydrolysed, $E_{\\mathrm{{monomer}}}$ and $E_{\\mathrm{framework}}$ are the energies of $\\dot{p}$ -phenylenediamine and framework, respectively, and the corresponding conformers were kept the same as in that system. \n\nTo visualize the intermolecular interactions between the $p$ -phenylenediamine monomer and the COF fragment, we used the independent gradient model $(\\mathsf{I G M})^{56}$ . The IGM method quantifies the net electron density gradient attenuation that is due to intermolecular interactions, identifying non-covalent interactions and generating data composed solely of intermolecular interactions for drawing the corresponding 3D isosurface representations. Here structures were extracted out from the periodic calculation result with no hydrogen atoms added to the fragment, because we used pro-molecular level electron density here. The Multiwfn program57 was used for IGM analyses and the VMD program58 was used for visualization. \n\nThe geometries of the complexes were fully optimized by means of the hybrid M06-2X functional59. For all atoms, the def2-SVP basis set60,61 was applied. No symmetry or geometry constraint was imposed during optimizations. The optimized geometries were verified as local minima on the potential energy surface by frequency computations at the same theoretical level. These calculations were performed with the Gaussian 16 suite of programs62. Water was used as the solvent in the SMD solvation model63. A temperature of 433 K was used for thermochemistry analysis in all calculations. \n\n# Data availability \n\nThe experimental and theoretical data that support the findings of this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper. \n\n49.\t Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n50.\t Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758 (1999). \n51. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953 (1994). \n52. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865 (1996). \n53.\t Grimme, S., Antony, J., Ehrlich, S. & Krieg, H. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H–Pu. J. Chem. Phys. 132, 154104 (2010). \n\n# Article \n\n54.\t Grimme, S., Ehrlich, S. & Goerigk, L. Effect of the damping function in dispersion corrected density functional theory. J. Comput. Chem. 32, 1456–1465 (2011). \n55.\t Butler, K. T., Hendon, C. H. & Walsh, A. Electronic chemical potentials of porous metal– organic frameworks. J. Am. Chem. Soc. 136, 2703–2706 (2014). \n56.\t Lefebvre, C. et al. Accurately extracting the signature of intermolecular interactions present in the NCI plot of the reduced density gradient versus electron density. Phys. Chem. Chem. Phys. 19, 17928–17936 (2017). \n57.\t Lu, T. & Chen, F. Multiwfn: a multifunctional wavefunction analyzer. J. Comput. Chem. 33, \n580–592 (2012). \n58.\t Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. \n14, 33–38 (1996). \n59.\t Zhao, Y. & Truhlar, D. G. The M06 suite of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four M06-class functionals and 12 other functionals. Theor. Chem. Acc. 120, 215–241 (2008). \n60.\t Weigend, F. & Ahlrichs, R. Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: design and assessment of accuracy. Phys. Chem. Chem. Phys. 7, 3297–3305 (2005). \n61.\t Weigend, F. Accurate Coulomb-fitting basis sets for H to Rn. Phys. Chem. Chem. Phys. 8, \n1057–1065 (2006). \n62.\t Frisch, M. et al. Gaussian 16, Revision A.03 (Gaussian Inc., 2016). \n63.\t Marenich, A. V., Cramer, C. J. & Truhlar, D. G. Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J. Phys. Chem. B 113, 6378–6396 (2009). \n\nAcknowledgements We gratefully acknowledge funding from the National Natural Science Foundation of China (NSFC) Science Center Program (21788102); the NSFC (21905091, 21636002); Shanghai Municipal Science and Technology Major Project (2018SHZDZX03, 21JC1401700); Shanghai Municipal Science and Technology (20120710200); the Engineering and Physical Sciences Research Council (EPSRC) (EP/N004884/1, EP/P034497/1, EP/S017623/1); the Leverhulme Trust through the Leverhulme Research Centre for Functional Materials Design; and China Postdoctoral Science Foundation (no. 2019M651418). S.D. acknowledges support from the Shanghai Rising Star Program (20QA1402400) and the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning. W.Z. thanks the Research Center of Analysis and Testing of East China University of Science and Technology for the characterization of elemental microanalyses. \n\nAuthor contributions W.Z., H.T., W.-H.Z. and A.I.C. conceived the project. W.Z. and M.Y. synthesized and characterized the materials, and performed photocatalysis experiments. L.C. and C.Z. performed the simulations. S.D. performed SEM and HRTEM characterizations. M.Z. and Q.Z. conducted FTIR characterizations. L.C., L.W., Y.-B.Z. and S.Y.C. conducted structural modelling and PXRD refinements. S.J. performed solid-state NMR measurement. C.M., Y.-B.Z. and S.A. conducted the gas adsorption experiments. H.Y., Y.B. and X.-W.Z. carried out optical spectra measurements. L.L. performed photo-electrochemistry characterizations. Y.X. conducted XPS experiments. W.Z., S.D., R.S.S., M.A.L., X.W., Y.W., H.T., W.-H.Z. and A.I.C. analysed the data and wrote the paper. All authors discussed the results and contributed to the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-022-04443-4. \nCorrespondence and requests for materials should be addressed to Wei-Hong Zhu or Andrew I. Cooper. \nPeer review information Nature thanks Jianzhuang Jiang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/e6d9ae3b129465a225dd99156137ed726f90397eec91c13bd2c113773ef56910.jpg) \nExtended Data Fig. 1 | Continuous transformation in water. a, b, The evolution of the PXRD patterns with time for as-synthesized Urea-COF-1 by treatment with water at the reaction temperatures of $160^{\\circ}\\mathsf C$ (samples were \n\n![](images/90deda624962d053ac77701eb41eb3aa751770e9562d13985e220fdd2d98799a.jpg) \nsolvated with water (a) and measured after activation/desolvation (b)). The gradual shift in the peak positions over time suggests a continuous transformation during the COF reconstruction. \n\n![](images/57485f065f19847ae51cd913d19ea2d82ca226612c7a20d1baeff2c14711c793.jpg) \nExtended Data Fig. 2 | Increased porosity. a, b, Comparison of BET surface areas (a) and total pore volumes (b) for RC-COFs (yellow bars) and DP-COFs (green bars). Reconstructed COFs showed greatly improved BET surface area and pore volumes than directly polymerized analogues. \n\n![](images/18b45d53e060b12d56f5280a397fb2c19eba57571dfb4bf37985823c4e33baec.jpg) \nExtended Data Fig. 3 | Pore size distributions. a–h, Pore size distribution profiles for RC-COFs (a, c, e, g) and DP-COFs (b, d, f, h). The reconstructed COFs showed a much narrower pore size distribution, which reflected their enhanced crystallinity. \n\n![](images/a43ae0166e920b6d3a2bbe9d8d8064ca8a668cb5bc21c5502d22915d5fdec04f.jpg) \nExtended Data Fig. 4 $|\\mathbf{CO_{2}}$ uptake. a, b, Adsorption (filled circles) and desorption (open circles) isotherms for ${\\mathsf{C O}}_{2}$ uptake in RC-COF-1 and DP-COF-1 recorded a 273 K (a). Summary of $\\mathbf{CO}_{2}$ uptake capacities for COF materials reported at 273 K and 1 bar (b); see details in Supplementary Table 5. \n\n![](images/e3a0752cb2e185e5cc20a134f89704a1803164ed76d222ed7828e4c5bf7e2c8b.jpg) \n\nExtended Data Fig. 5 | Chemical stability. a, b, PXRD patterns (a) and FTIR spectra (b) for RC-COF-1 after various chemical treatments for 24 h. RC-COF-1 retained its crystalline structure after treatment under all these conditions. \n\n![](images/af3e64c2ea8362ee1ef5c98f879b12700d046c360d6c325933a70f6c578f7952.jpg) \n\nNote that the PXRD peak intensity decreased slightly when treated with concentrated sodium hydroxide solution. \n\n![](images/f56edf2512ad4a9413d73f28e430765ed253f082312c04c59c1cc624b5edfcb6.jpg) \n\nExtended Data Fig. 6 | Optical and electronic properties and photocatalytic hydrogen evolution activity. a, EPR studies showed a single Lorentzian line centred at a g value of 2.006 for RC-COF-1, which intensified dramatically upon light excitation, suggesting an effective light-induced charge carrier generation, whereas DP-COF-1 displayed much lower signal intensity under same test conditions. b, Transient photocurrents with on-off light intermittent irradiation $(\\lambda>420\\mathsf{n m})$ for RC-COF-1, DP-COF-1 and Urea-COF-1, conducted with a bias potential of – 0.35 V vs Ag/AgCl. RC-COF-1 produced an enhanced photocurrent compared to its semi-crystalline counterpart, DP-COF-1, indicating more efficient separation of photogenerated charge carriers. c, Time courses of sacrificial photocatalytic hydrogen production for RC-COF-1, FS-COF, DP-COF-1, Urea-COF-1 and $\\underline{{\\mathbf{y}}}{\\cdot}\\mathbf{C}_{3}\\mathbf{N}_{4}$ (2.5 mg catalyst in water with 3 wt.% Pt loading, $\\lambda>420\\mathrm{nm}$ for RC-COF-1, \n\nFS-COF, DP-COF-1 and Urea-COF-1, and $\\lambda>295\\mathrm{nm}$ for g- ${\\bf\\cdot C}_{3}\\bf N_{4}$ ). d, Time course of photocatalytic hydrogen evolution for RC-COF-1 from three different synthetic batches under visible light irradiation; inset is corresponding hydrogen evolution rate (HER). There is good batch-to-batch reproducibility in terms of photocatalytic performance for materials prepared by this reconstruction route. e, The external quantum efficiencies (EQEs) of RC-COF-1 were estimated to be $6.39\\%$ at $420\\mathrm{nm}$ , $5.92\\%$ at $490\\mathrm{nm}$ , $5.20\\%$ at $515\\mathsf{n m}$ , and $1.62\\%$ at ${595}\\mathrm{nm}$ , respectively. By comparison, DP-COF-1 exhibited a much-lower EQEs of $1.97\\%$ , $1.61\\%,1.37\\%$ , and $0.54\\%$ at the same wavelengths. f, Long-term photocatalytic hydrogen evolution stability test for RC-COF-1 over 60 h under visible light $(\\lambda>420\\mathrm{nm})$ ). The dashed vertical lines denote degassing and addition of a further 1.25 mmol of ascorbic acid. No obvious decrease in activity was observed during this 60-h period. \n\n![](images/9b597db68215c7c7860e2607a93a876756fd6b82ffd60dcde95701c5aad99a82.jpg) \nExtended Data Fig. 7 | RC-COF-1 crystallite with photo-deposited Pt co-catalyst nanoparticles. a–g, SEM (a), TEM (b), high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) (c) images and elemental mapping $(\\mathbf{d}\\mathbf{-}\\mathbf{g})$ for RC-COF-1 crystallite decorated with \nphoto-deposited Pt co-catalyst. The inset in b shows uniform distributions of Pt nanoparticles $(2.5\\pm0.5\\mathsf{n m})$ ) in the selected area (yellow square). The uniform morphology of the reconstructed COF and the good Pt cocatalyst dispersion might also contribute to its enhanced activity. \n\n![](images/b3c41cbb83d20f95296b93f9b98301528333ba654a7f36173b3efcc02dd39c6a.jpg) \nExtended Data Fig. 8 | RC-COF-1 synthesized without vacuum degassing step. a, b, Experimental PXRD patterns (a) and nitrogen adsorption isotherm (b, filled symbols) and desorption isotherm (b, open symbols) for RC-COF-1 synthesized without vacuum degassing steps; inset shows calculated pore size \n\n![](images/fd366e5dff6a2b87185d04088888ddd4fc19e891cbc735dda1ac0bad9dbda7f7.jpg) \ndistribution. Both the crystallinity and the porous properties are close to those obtained with careful degassing, suggesting that this step is unnecessary in the reconstruction synthesis route, at least for these specific monomers. " + }, + { + "id": "10.1038_s41586-022-05183-1", + "DOI": "10.1038/s41586-022-05183-1", + "DOI Link": "http://dx.doi.org/10.1038/s41586-022-05183-1", + "Relative Dir Path": "mds/10.1038_s41586-022-05183-1", + "Article Title": "Spatiotemporal imaging of charge transfer in photocatalyst particles", + "Authors": "Chen, RT; Ren, ZF; Liang, Y; Zhang, GH; Dittrich, T; Liu, RZ; Liu, Y; Zhao, Y; Pang, S; An, HY; Ni, CW; Zhou, PW; Han, KL; Fan, FT; Li, C", + "Source Title": "NATURE", + "Abstract": "The water-splitting reaction using photocatalyst particles is a promising route for solar fuel production(1-4). Photo-induced charge transfer from a photocatalyst to catalytic surface sites is key in ensuring photocatalytic efficiency(5); however, it is challenging to understand this process, which spans a wide spatiotemporal range from nullometres to micrometres and from femtoseconds to seconds(6-8). Although the steady-state charge distribution on single photocatalyst particles has been mapped by microscopic techniques(9-11), and the charge transfer dynamics in photocatalyst aggregations have been revealed by time-resolved spectroscopy(12,13), spatiotemporally evolving charge transfer processes in single photocatalyst particles cannot be tracked, and their exact mechanism is unknown. Here we perform spatiotemporally resolved surface photovoltage measurements on cuprous oxide photocatalyst particles to map holistic charge transfer processes on the femtosecond to second timescale at the single-particle level. We find that photogenerated electrons are transferred to the catalytic surface quasi-ballistically through inter-facet hot electron transfer on a subpicosecond timescale, whereas photogenerated holes are transferred to a spatially separated surface and stabilized through selective trapping on a microsecond timescale. We demonstrate that these ultrafast-hot-electron-transfer and anisotropic-trapping regimes, which challenge the classical perception of a drift-diffusion model, contribute to the efficient charge separation in photocatalysis and improve photocatalytic performance. We anticipate that our findings will be used to illustrate the universality of other photoelectronic devices and facilitate the rational design of photocatalysts.", + "Times Cited, WoS Core": 312, + "Times Cited, All Databases": 328, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000867324800024", + "Markdown": "# Article \n\n# Spatiotemporal imaging of charge transfer in photocatalyst particles \n\nhttps://doi.org/10.1038/s41586-022-05183-1 \n\nReceived: 5 July 2022 \n\nAccepted: 2 August 2022 \n\nPublished online: 12 October 2022 Check for updates \n\nRuotian Chen1,6, Zefeng Ren2,6, Yu Liang2,3, Guanhua Zhang2, Thomas Dittrich4, Runze Liu5, Yang Liu5, Yue Zhao1, Shan Pang1, Hongyu An1, Chenwei $\\mathsf{N i}^{1,3}$ , Panwang Zhou5, Keli Han2,5, Fengtao Fan1 ✉ & Can Li1,3 ✉ \n\nThe water-splitting reaction using photocatalyst particles is a promising route for solar fuel production1–4. Photo-induced charge transfer from a photocatalyst to catalytic surface sites is key in ensuring photocatalytic efficiency5; however, it is challenging to understand this process, which spans a wide spatiotemporal range from nanometres to micrometres and from femtoseconds to seconds6–8. Although the steady-state charge distribution on single photocatalyst particles has been mapped by microscopic techniques9–11, and the charge transfer dynamics in photocatalyst aggregations have been revealed by time-resolved spectroscopy12,13, spatiotemporally evolving charge transfer processes in single photocatalyst particles cannot be tracked, and their exact mechanism is unknown. Here we perform spatiotemporally resolved surface photovoltage measurements on cuprous oxide photocatalyst particles to map holistic charge transfer processes on the femtosecond to second timescale at the single-particle level. We find that photogenerated electrons are transferred to the catalytic surface quasi-ballistically through inter-facet hot electron transfer on a subpicosecond timescale, whereas photogenerated holes are transferred to a spatially separated surface and stabilized through selective trapping on a microsecond timescale. We demonstrate that these ultrafast-hot-electron-transfer and anisotropic-trapping regimes, which challenge the classical perception of a drift–diffusion model, contribute to the efficient charge separation in photocatalysis and improve photocatalytic performance. We anticipate that our findings will be used to illustrate the universality of other photoelectronic devices and facilitate the rational design of photocatalysts. \n\nWe optimized the charge separation behaviour of representative cuprous oxide $\\left(\\mathbf{Cu}_{2}\\mathbf{O}\\right)$ photocatalyst particles14 through facet engineering and defect control (Fig. 1a). Facet engineering offers the potential for anisotropic charge transfer4,15 and enables possible spatial control of defects owing to facet-dependent defect formation16. \n\nAfter tuning the facet ratio of $\\mathbf{Cu}_{2}\\mathbf{O}$ particles, their morphology changed from cubic to octahedral (Extended Data Fig. 1a–c). We mapped the surface charge distribution on these particles using surface photovoltage microscopy (SPVM)10,11 and found that more photogenerated electrons are accumulated on the {001} facet of the $\\mathtt{C u}_{2}0$ cube than on the {111} facet of the octahedron (Fig. 1b). The result is attributed to a more significant p-type character of the {001} facet owing to the higher copper vacancy $(\\mathsf{V}_{\\mathsf{C u}})$ density17. The anisotropic $\\mathtt{V_{C u}}$ density generates inter-facet built-in electric fields15 in $\\mathtt{C u}_{2}0$ particles containing {001} and {111} facets, as demonstrated by the surface potential distributions (Extended Data Fig. 1d,f). Interestingly, the electric fields become prominent with an increasing {111}/{001} ratio. Consistent with this observation, anisotropic charge transfer occurs and becomes optimized in the truncated octahedral configuration (Fig. 1c and Extended Data Fig. 1e–h). The consistency suggests that the inter-facet built-in electric fields contribute to the anisotropic charge transfer. \n\nHowever, only electrons can be observed on the surface after facet engineering. Hence, we introduced a strategy of spatially controllable defect engineering to selectively extract holes onto the {111} surface of ${\\bf C u}_{2}{\\bf O}$ particles and maintain electron transfer to their {001} surfaces. Hydrogen-compensated copper vacancy defects $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ were demonstrated to enable hole extraction to the $\\mathtt{C u}_{2}0$ surface18. Density functional theory (DFT) calculations revealed that $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects were more likely to be formed at {111} facets (Extended Data Fig. 2). \n\nTo implement the selective incorporation of hydrogen, we adjusted the deposition current during the electrochemical growth of ${\\bf C u}_{2}{\\bf O}$ particles because the higher current increased the density of hydrogen that compensated the $\\mathtt{V_{C u}}$ to form $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}})$ defects19. X-ray photoelectron spectroscopy (XPS) and Auger copper (Cu) LMM spectra verified the replacement of $\\mathbf{\\dot{V}}_{\\mathbf{Cu}}$ with $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ , consistent with the observations that the fractions of ${\\mathrm{Cu}}^{0}$ and ${\\mathsf{C u}}^{2+}$ species increased and decreased, respectively (Extended Data Fig. $_{3\\mathsf{a-c})}$ . \n\n![](images/576970ac97c9c688c9f19f50b2fa2d648bde0d5b780491cff949748f61dd54d5.jpg) \nFig. 1 | Relating anisotropic structures to surface charge distribution. a, Illustration of the anisotropic engineering of facets and defects of ${\\bf C u}_{2}0$ photocatalyst particles. b, SPVM images of cubic (top) and octahedral (bottom) ${\\bf C u}_{2}0$ particles. c–e, SPVM images of truncated octahedral ${\\tt C u}_{2}0$ particles without (c), with moderate (d) and with extreme (e) incorporation of $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}})$ defects. Scale bars in b–e, $2\\upmu\\mathrm{m}$ . Dashed arrows in c–e denote the positions for extracting SPV distributions across {111} and {001} facets. f, SPV values extracted across dashed lines in c–e. g, Correlations between the $\\mathtt{V_{C u}}$ \ndensity and SPV. The $\\mathtt{V_{C u}}$ density represents the normalized $\\mathtt{V_{C u}}$ -related Raman peak intensity, which is linear with respect to the $\\mathtt{V_{C u}}$ density determined by XPS. $\\mathsf{v}_{\\mathtt{C u}}$ and $(\\mathsf{H}-\\mathsf{V}_{\\mathsf{C u}})$ are the dominant defects at the intensity above and below 0.7, respectively. See details in Extended Data Fig. 3d,e. The SPV values are statistically averaged by the pixels extracted from corresponding SPVM images using electronic noise as the error bars. h, Confocal Raman microscopy image of an EH- ${\\bf C u}_{2}0$ particle mapped with the $\\ensuremath{\\mathsf{V}}_{\\mathrm{cu}}$ -related Raman peak intensity. The low Raman intensity denotes H- $\\cdot\\mathtt{V}_{\\mathtt{C u}},$ which compensates for $\\mathsf{V}_{\\mathsf{C u}}$ . \n\nAfter defect engineering, SPVM showed that the moderate $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ incorporation resulted in efficient spatial separation of photogenerated electrons and holes on the {001} and {111} facets, respectively (Fig. 1d and Extended Data Fig. 4a). Nonetheless, the extreme $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ incorporation led to the disappearance of surface electrons and the spreading of holes over the entire particle surface (Fig. 1e). We denote the three types of defect-engineered particle in Fig. $\\mathbf{1c-e}$ as $\\bar{\\mathbf{E}}{\\cdot}\\mathbf{C}\\mathbf{u}_{2}\\mathbf{O}$ (only electrons at surface), EH- $\\boldsymbol{\\mathbf{\\ell}}_{\\mathbf{C}\\mathbf{u}_{2}\\mathbf{O}}$ (spatially separated electrons and holes at surface) and H- ${\\bf C u}_{2}0$ (only holes at surface) based on their surface charge distribution. Figure 1f quantitatively compares the SPV distributions across the {111} and {001} facets of the three particles and suggests effective charge separation on the EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ surface through anisotropic defect engineering. \n\nTo identify the non-uniform defect distributions, we probed the $\\mathtt{V_{C u}}$ -related Raman intensity linearly associated with the $\\mathtt{V_{C u}}$ density by confocal Raman microscopy (Extended Data Fig. 3d–f). Figure 1g shows a good intensity correlation between the SPV and $\\mathsf{v}_{\\mathtt{c u}}$ density, and the $\\mathtt{V_{C u}}$ distributions of $\\mathsf{E H-C u}_{2}\\mathbf{O}$ in Fig. 1h yielded a strong spatial correlation with the SPV distributions (Fig. 1d). These correlations indicate that anisotropic defects contribute to the efficient charge separation on the photocatalyst surface. \n\nTo verify the facet-selective defect distributions, we performed spatially resolved X-ray spectroscopy on EH- $\\mathtt{C u}_{2}0$ particles (Extended Data Fig. $3\\mathrm{g-m},$ . A combination of the facet-dependent XPS, Cu LMM Auger electron and $\\mathsf{C u L}_{2,3}$ edge X-ray absorption spectra provided direct evidence for the selective distribution of $\\operatorname{v}_{\\mathtt{c u}}$ at {001} facets and selective distribution of $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}})$ at {111} facets of EH- $\\cdot\\mathrm{cu}_{2}0$ particles. To confirm the facet-dependent charge transfer, we measured the localized charge separation with modulated light on the surface oriented parallel to the substrate (Extended Data Fig. 4b) to eliminate possible effects of the tip–sample geometry and the diffusion process10. The modulated SPV signals were in good agreement with the steady-state SPV data (Extended Data Fig. 4c), confirming efficient charge separation. Furthermore, facet-dependent charge transport measured by photoconductive atomic force microscopy demonstrated that photogenerated holes and electrons could be selectively extracted to the {111} and {001} facets, respectively (Extended Data Fig. 4d). In addition, the two facets exhibited different dependence of their SPV signals on the light intensity (Extended Data Fig. 4e), suggesting different mechanisms for electron and hole transfer. \n\n# Ultrafast inter-facet electron transfer \n\nTo elucidate the origin of anisotropic charge transfer, we used time-resolved photoemission electron microscopy (TR-PEEM)20,21 to access the charge transfer dynamics on the femtosecond–nanosecond timescales. For this purpose, we used 2.4-eV pulses to generate hot electrons in the Γ valley of the conduction band and a time-delayed 4.8-eV probe pulse to emit electrons into the vacuum, where they were detected by PEEM (Extended Data Fig. 5a–c). Figure 2a shows a series of the photoemission electron images of a single EH- $\\boldsymbol{\\mathbf{\\ell}}_{\\mathbf{C}\\mathbf{u}_{2}\\mathbf{O}}$ particle captured at different pump–probe delays. They provide snapshots for creating videos (Supplementary Video 1) and clearly visualize the anisotropic electron transfer dynamics for the particle, where the photoelectron density on the {001} facet is higher than that on the {111} facet. Figure 2b shows the plots of the energy-integrated photoelectron intensity versus time delay for the $\\mathsf{E H-C u}_{2}\\mathsf{O}\\left\\{001\\right\\}$ and {111} facets. Immediately after photoexcitation, the photoelectron intensity increased for the {001} facet but decreased for the {111} facet within about $0.5{\\mathsf p}{\\mathsf s}$ , which indicated the ultrafast electron transfer from the {111} to {001} facets. Subsequently, the photoelectron intensities of both facets slowly increased at tens of picoseconds and then showed a decay at hundreds of picoseconds. The early dynamics was independent of the excitation carrier density, whereas the decay dynamics was accelerated by increasing the excitation density owing to recombination and trapping22 (Extended Data Fig. 5h–k). \n\n![](images/fbf2857c8b8de9a5d18fd12dddc2c512d3779314b9797c5f59c1d5647b268295.jpg) \nFig. 2 | Time-resolved photoemission electron microscopy of E- $\\mathbf{Cu}_{2}\\mathbf{0}$ particles. a, PEEM image and a sequence of TR-PEEM images of an EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ particle captured at different pump–probe delay times, as labelled. Scale bars, $2\\upmu\\mathrm{m}$ . b, Energy-integrated photoelectron intensity plotted as a function of delay time for EH- ${\\tt C u}_{2}0$ {001} and {111} facets. The signals were collected from the surface parallel to the substrate to eliminate the shadowing and electric-field-distortion effects (Extended Data Fig. 5d–g). c, Energy-resolved photoelectron intensity and electron temperature plotted as functions of delay time. The circles and squares indicate the data for the {001} and {111} facets, respectively. LE denotes low-energy electrons in thermal equilibrium, and HE denotes high-energy non-equilibrium electrons (Extended Data Fig. 7a,b). The HE decays were fitted with equations (4) and (5) in Methods, resulting in a decay time constant of 0.05 ps and 0.18 ps for the {111} and {001} \nfacets, respectively. The LE growth for the {001} facets was fitted with equation (6) in Methods and gave a time constant of $\\cdot0.2\\mathsf{p s}$ . Electron temperatures (Temp.) were extracted from hot Fermi–Dirac distributions with error bars representing the standard deviation during the fits (Extended Data Fig. 7c,d). d, SPV signals plotted as functions of delay time for EH- $\\boldsymbol{\\mathbf{\\cdot}}\\mathbf{C}\\mathbf{u}_{2}\\mathbf{O}$ {001} and {111} facets by extracting peak shifts from the corresponding photoelectron spectra (Extended Data Fig. 7j,k). The solid lines are smooth lines. e, Decoupled SPV signals for the {001} facets with contributions from the inter-facet and bulk-to-surface charge transfer processes. The inter-facet SPV data were simulated with the quasi-ballistic model (solid line; see Methods for details). The bulk-to-surface SPV signals were determined from cubic $\\mathtt{C u}_{2}0$ (Extended Data Fig. 8a–d). \n\nThe observed dynamics indicated that the ultrafast inter-facet electron transfer was the reason for the anisotropic electron distribution. The electron transfer was expected owing to the formation of a $1.7\\mathsf{k V}\\mathsf{c m}^{-1}$ built-in electric field from the {001} to {111} facets (Extended Data Fig. ${6}\\mathsf{a-c},$ ). However, simulations indicated that the ultrafast transport behaviour could not be explained by the conventional drift–diffusion model (Extended Data Fig. 6d–f). To further elucidate this process, hot-electron-relaxation behaviour was examined in the energy-resolved mode (Fig. 2c and Extended Data Fig. 7a,b). Upon photoexcitation, the high-energy electron population rapidly decayed within 0.1 ps for the {111} facets, whereas it continued to increase before 0.1 ps and then decayed with a time constant of 0.18 ps for the {001} facets. Meanwhile, the low-energy electron population remained almost unchanged for the {111} facets, indicating that the decay of high-energy electrons on the {111} facets originated from inter-facet electron transfer rather than hot electron relaxation or trapping. In contrast, the low-energy electron population of the {001} facets exhibited a pronounced increase with a time constant of 0.2 ps, consistent with the hot electron relaxation. These data depicted a landscape of the ultrafast inter-facet charge transfer, where the hot electrons were rapidly transferred from the {111} to {001} facets within 0.1 ps, and then underwent energy relaxation to reach quasi-equilibrium on the {001} facets at about 0.2 ps. Coinciding with the hot electron relaxation, the electron temperature decayed from 3,000 K to 1,000 K on the same timescale (Extended Data Fig. 7c–e). The temperature decay proceeded on a timescale of about 2.96 ps (Extended Data Fig. 7f), in line with acoustic phonon–electron interactions23. \n\n![](images/c6e540864e16d2b44cc8edd07158395edbc094db450f28d27045ffa1d5eb5bb3.jpg) \nFig. 3 | Transient SPV spectra of EH- $\\mathbf{Cu}_{2}\\mathbf{0}.$ . a, Pseudocolour image of the spectral and time-dependent distributions of SPV signals for EH- $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}$ particles. The colour scale represents the SPV signals. b, SPV transients of EH- ${\\tt C u}_{2}0$ particles extracted from photon energies of 1.8 eV, 2.0 eV and $2.8\\mathrm{eV}$ . \n\nTo gain insights into the ultrafast relaxation mechanism, we examined the effect of excitation carrier density (Extended Data Fig. 7g,h). The excitation density exerted impact on the growth of the high-energy electron population on the {001} facets occurring within 0.1 ps, suggesting that electron–electron interactions were dominant. The electrons remained highly non-thermal in the energy space after the electron–electron interactions, which suggested the formation of hot electron ensembles24. The excitation density produced little effect on the hot electron relaxation occurring at about 0.2 ps, which excluded the electron–hole scattering25. It is noted that the ultrafast trapping was not observed26, and the intervalley scattering was impossible (Extended Data Fig. 5c). Therefore, the ultrafast energy relaxation originated from optical phonon–electron scattering, which agrees with the established electron–phonon scattering model23. By clarifying the physics of hot electron relaxation (Extended Data Fig. 7i), we concluded that the ultrafast inter-facet electron transfer occurred before the dominant energy relaxation induced by electron–phonon scattering in a hot electron ensemble fashion, which corresponded to a quasi-ballistic regime27. \n\nFigure 2d shows the ultrafast SPV signals extracted from the peak shifts of photoelectron spectroscopy at different delay times (Extended Data Fig. 7j,k). Upon photoexcitation, negative and positive SPV signals were generated on the {001} and {111} facets, respectively, further confirming the ultrafast inter-facet electron transfer. To quantify this process, we deducted the contributions from the bulk-to-surface charge transfer extracted from the SPV signals of cubic ${\\tt C u}_{2}0$ (Extended Data Fig. 8a–d). The decoupled data (Fig. 2e) showed that the inter-facet electron transfer yielded a transient SPV of $80\\mathrm{mV}$ , exceeding the maximum photovoltage limit (about $50\\mathrm{mV}.$ ) in the drift model caused by the inter-facet potential difference. To explain the anomalously large SPV, we used a quasi-ballistic model to simulate the inter-facet electron transfer (Extended Data Fig. 6g,h and the related details in Methods). The simulation results obtained at an initial velocity of about $3\\times10^{5}\\mathsf{m}\\mathsf{s}^{-1}$ were in excellent agreement with the experimental data (solid line in Fig. 2e), validating the quasi-ballistic transport mechanism. The initial velocity agrees well with the calculated group velocity of electrons within the conduction band (Extended Data Fig. 6i), further supporting the quasi-ballistic regime. Similar ultrafast and efficient charge transport attributed to the (quasi-)ballistic regime has also been observed for perovskite28 and silicon $\\mathsf{p}{-}\\mathsf{n}$ junctions29. Notably, the SPV differences between the two facets reduced to $50\\mathrm{mV}$ after 100 ps (Fig. 2d), implying that the drift regime became dominant, consistent with the calculated drifts of equilibrium carriers (Extended Data Fig. 6e). Thereafter, prolonged $-50\\pm15\\mathrm{mV}$ and $-10\\pm20\\mathrm{mVSPV}$ signals were observed for the {001} and {111} facets, respectively, on the nanosecond timescale. \n\nWe related the SPV signals obtained at 1 ns (Fig. 2d) with those obtained by SPVM after excluding the effect of measurement conditions (Extended Data Fig. 8e–k) and found a good agreement for the {001} facet but not for the {111} facet. These results indicate that the steady-state electrons on the {001} facet originated from the ultrafast inter-facet electron transfer. The disagreement observed for the {111} facet implies that the SPV signals changed from $-10\\mathsf{m}\\mathsf{V}$ to $40\\mathrm{mV}$ in the nanosecond–millisecond time window. \n\n# Anisotropic trapping \n\nTo directly observe the charge transfer process on the nanosecond to millisecond timescales, we performed a transient SPV spectroscopy analysis of EH- $\\cdot\\mathrm{cu}_{2}\\mathrm{O}$ (Fig. 3a). At excitation energies above the bandgap $(2.04\\mathrm{eV}$ ; Extended Data Fig. 9e), the SPV signals were negative on the nanosecond timescale. They then became positive as the time progressed to microseconds (for example, about $2\\upmu\\up s$ at 2.8 eV in Fig. 3b). The reversed SPV signals rationalized SPV variations on the {111} facet and were probably associated with $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}})$ -induced trapping localized on the {111} facet. \n\nWe determined the anisotropic-trapping processes from sub-bandgap SPV signals through the facet-dependent absorption (Extended Data Fig. 9a–f). The negative SPV transients at $1.7–1.9\\mathrm{eV}$ and positive SPV transients at about $2.0\\mathrm{eV}$ (Fig. 3a) originated from the selective trapping on the {001} and {111} facets, respectively. The negative SPV signals (red line in Fig. 3b) can be attributed to the hole trapping by $\\mathtt{V_{C u}}$ defects and the drift of electrons to the {001} facets. In contrast, the positive SPV signals on the {111} facets (blue line in Fig. 3b) confirm the trapping of photogenerated electrons by $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects (Extended Data Fig. 9g). These $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects were assumed to be primarily distributed within $60\\mathrm{nm}$ depth beneath the {111} surface (Extended Data Fig. 9d), thereby initiating a localized hole transfer to the {111} facets18. The timescales for the hole trapping by $\\mathtt{V_{C u}}$ and electron trapping by $\\left(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}}\\right)$ were a few nanoseconds and tens of microseconds, respectively, coinciding with the observed inversion of SPV signals at the super-bandgap excitation. Therefore, we concluded that the steady-state holes on the {111} facets originated from the $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{c u}})$ -induced hole transfer. \n\n# Article \n\n![](images/b84616c6fa883774373e20e2f7ced7aba5d6fb7961fc81787295f36948150510.jpg) \nFig. 4 | Selective cocatalyst loading and photocatalytic performance. a,b, AFM image (a) and the corresponding SPVM image (b) of an EH- ${\\tt C u}_{2}0$ particle with selective deposition of Au particles on the {001} facet (denoted as E $\\mathsf{H}{\\cdot}\\mathsf{C u}_{2}\\mathsf{O}/\\mathsf{A u},$ ). Scale bars, $2\\upmu\\mathrm{m}$ . c, Comparison of the statistical SPV signals obtained for the {001} and {111} facets of EH- ${\\bf C u}_{2}0$ and EH- $\\mathbf{Cu}_{2}\\mathbf{O}/\\mathbf{Au}$ particles. d, Driving forces of the anisotropic charge transfer and rates of photocatalytic \n$\\mathsf{H}_{2}$ generation obtained for different $\\mathtt{C u}_{2}0$ photocatalytic systems. The driving forces were extracted from the difference in SPV signals between different facets (Extended Data Fig. 10i). The reaction rates were determined from the time course of $\\mathrm{\\bf{\\ddot{H}}}_{2}$ evolution (Extended Data Fig. 10j). Error bars show standard deviations. Photocatalytic reactions were performed under 300-W Xe lamp illumination using a $0.5\\mathsf{M N a}_{2}\\mathsf{S O}_{3}$ solution as a hole scavenger. \n\nThe aforementioned data allowed us to create a holistic picture of the charge transfer processes in the EH- $\\cdot\\mathrm{cu}_{2}0$ photocatalyst (Extended Data Fig. 9h), including quasi-ballistic inter-facet electron transfer (about 0.2 ps), drift in built-in electric field (about 100 ps), and selective hole (nanosecond) and electron (microsecond) trapping by anisotropic defects. The picture depicted that the efficient charge separation originated from the spatiotemporally anisotropic charge transfer mechanism, that is, ultrafast quasi-ballistic electron transfer to the {001} facets and slow defect-induced hole transfer to the {111} facets. \n\n# Relation to improved performance \n\nThe anisotropic charge transfer enabled selective cocatalyst loading4. Hence, we selectively deposited gold (Au) cocatalyst on the {001} facets of EH- ${\\bf C u}_{2}{\\bf O}$ particles by photoreduction (Fig. 4a and Extended Data Fig. 10a). SPVM (Fig. 4b) shows that both the electron transfer to the {001} facets and hole transfer to the {111} facets were enhanced after the asymmetric Au deposition, and the enhancements were approximately $50\\%$ (Fig. 4c). We attributed this to the amplified built-in electric field by selective Au deposition, based on the observation of increased surface potential at the Au deposition sites (Extended Data Fig. 10b−d). By comparison, the Au deposition on $\\mathsf{E}{\\cdot}\\mathsf{C u}_{2}0$ and ${\\mathsf{H}}{\\cdot}{\\mathsf{C u}}_{2}{\\mathsf{O}}$ particles resulted in lower selectivity and did not promote charge separation (Extended Data Fig. 10e−h). Thus, anisotropic defect engineering can be applied for selective cocatalyst assembly, further enhancing charge separation30. \n\nFinally, we investigated the effect of the anisotropic charge transfer on photocatalytic performance. For this purpose, we quantitatively described the driving force of anisotropic charge transfer with the difference of SPV signals between different facets30 and monitored photocatalytic hydrogen $\\left(\\mathsf{H}_{2}\\right)$ generation (Extended Data Fig. 10i,j). Figure 4d shows that the anisotropic charge transfer is associated with photocatalytic performance. Two major steps that significantly improved the activity were anisotropic facet engineering and defect engineering, which simultaneously ensured efficient inter-facet hot electron transfer and defect-induced hole transfer to the spatially separated surfaces. Moreover, these strategies enabled rational cocatalyst assembly, which further improved the photocatalytic performance. \n\n# Conclusions \n\nThe current study of spatiotemporally tracking the charge transfer process establishes an experimental paradigm for revealing the complex mechanisms in photocatalysis. This ability enables us to demonstrate that the quasi-ballistic inter-facet electron transfer and spatially selective trapping are the dominant processes that facilitate efficient charge separation in photocatalysis. These regimes may be used for describing other photocatalytic systems, such as the facet-engineered and aluminium-doped strontium titanium oxide4. Furthermore, they are associated with anisotropic facets and defect structures, paving the way for the rational design of photocatalysts with improved performance. \n\n# Online content \n\nAny methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-022-05183-1. \n\n6. Corby, S., Rao, R. R., Steier, L. & Durrant, J. R. The kinetics of metal oxide photoanodes from charge generation to catalysis. Nat. Rev. Mater. 6, 1136–1155 (2021). \n7. Esposito, D. V. et al. Methods of photoelectrode characterization with high spatial and temporal resolution. Energy Environ. Sci. 8, 2863–2885 (2015). \n8. Delor, M., Weaver, H. L., Yu, Q. & Ginsberg, N. S. Imaging material functionality through three-dimensional nanoscale tracking of energy flow. Nat. Mater. 19, 56–62 (2020). \n9. Sambur, J. B. et al. Sub-particle reaction and photocurrent mapping to optimize catalyst-modified photoanodes. Nature 530, 77–80 (2016). \n10. Chen, R. et al. Charge separation via asymmetric illumination in photocatalytic $\\mathsf{C u}_{2}\\mathsf{O}$ particles. Nat. Energy 3, 655–663 (2018). \n11. Chen, R., Fan, F., Dittrich, T. & Li, C. Imaging photogenerated charge carriers on surfaces and interfaces of photocatalysts with surface photovoltage microscopy. Chem. Soc. Rev. 47, 8238–8262 (2018). \n12. Yang, Y. et al. Semiconductor interfacial carrier dynamics via photoinduced electric fields. Science 350, 1061–1065 (2015). \n13.\t Selim, S. et al. Impact of oxygen vacancy occupancy on charge carrier dynamics in ${\\mathsf{B i V O}}_{4}$ photoanodes. J. Am. Chem. Soc. 141, 18791–18798 (2019). \n14.\t Wu, Y. A. et al. Facet-dependent active sites of a single $\\mathsf{C u}_{2}\\mathsf{O}$ particle photocatalyst for $\\mathsf{C O}_{2}$ reduction to methanol. Nat. Energy 4, 957–968 (2019). \n15. Mao, X. & Chen, P. Inter-facet junction effects on particulate photoelectrodes. Nat. Mater. 21, 331–337 (2022). \n16. Selcuk, S. & Selloni, A. Facet-dependent trapping and dynamics of excess electrons at anatase $\\mathsf{T i O}_{2}$ surfaces and aqueous interfaces. Nat. Mater. 15, 1107–1112 (2016). \n17. Scanlon, D. O., Morgan, B. J., Watson, G. W. & Walsh, A. Acceptor levels in p-type $\\mathsf{C u}_{2}\\mathsf{O}$ : rationalizing theory and experiment. Phys. Rev. Lett. 103, 096405 (2009). \n18. Chen, R. et al. Giant defect-induced effects on nanoscale charge separation in semiconductor photocatalysts. Nano Lett. 19, 426–432 (2019). \n19. Scanlon, D. O. & Watson, G. W. Uncovering the complex behavior of hydrogen in $\\mathsf{C u}_{2}\\mathsf{O}$ Phys. Rev. Lett. 106, 186403 (2011). \n20.\t Man, M. K. et al. Imaging the motion of electrons across semiconductor heterojunctions. Nat. Nanotechnol. 12, 36–40 (2017). \n21.\t Doherty, T. A. S. et al. Performance-limiting nanoscale trap clusters at grain junctions in halide perovskites. Nature 580, 360–366 (2020). \n22.\t Park, J. S., Kim, S., Xie, Z. & Walsh, A. Point defect engineering in thin-film solar cells. Nat. Rev. Mater. 3, 194–210 (2018). \n23.\t Sadasivam, S., Chan, M. K. Y. & Darancet, P. Theory of thermal relaxation of electrons in semiconductors. Phys. Rev. Lett. 119, 136602 (2017). \n24.\t Tanimura, H., Tanimura, K. & Kanasaki, J. I. Ultrafast relaxation of photoinjected nonthermal electrons in the Γ valley of GaAs studied by time- and angle-resolved photoemission spectroscopy. Phys. Rev. B 104, 245201 (2021). \n25.\t Wittenbecher, L. et al. Unraveling the ultrafast hot electron dynamics in semiconductor nanowires. ACS Nano 15, 1133–1144 (2021). \n26.\t Borgwardt, M. et al. Femtosecond time-resolved two-photon photoemission studies of ultrafast carrier relaxation in $\\mathsf{C u}_{2}\\mathsf{O}$ photoelectrodes. Nat. Commun. 10, 2106 (2019). \n27.\t Sung, J. et al. Long-range ballistic propagation of carriers in methylammonium lead iodide perovskite thin films. Nat. Phys. 16, 171–176 (2019). \n28.\t Guo, Z. et al. Long-range hot-carrier transport in hybrid perovskites visualized by ultrafast microscopy. Science 356, 59–62 (2017). \n29.\t Najafi, E., Scarborough, T. D., Tang, J. & Zewail, A. Four-dimensional imaging of carrier interface dynamics in p–n junctions. Science 347, 164–167 (2015). \n30.\t Zhu, J. et al. Visualizing the nano cocatalyst aligned electric fields on single photocatalyst particles. Nano Lett. 17, 6735–6741 (2017). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nSpringer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2022 \n\n# Article Methods \n\n# Sample preparation \n\nAll $\\mathtt{C u}_{2}0$ single photocatalyst particles were prepared on fluorine tin oxide (FTO) conducting substrates by an electrodeposition method similar to that reported previously31. The $\\mathbf{Cu}_{2}\\mathbf{O}$ particles with morphological evolution from a cube to an octahedron were deposited galvanostatically at a current density of $0.45\\mathsf{m A c m}^{-2}$ , a deposition time of 800 s and a temperature of $60^{\\circ}\\mathsf{C}$ from a precursor solution (the PH value was adjusted to 4.9) containing a mixture of 0.02 M copper(II) nitrate $\\mathrm{(Cu(NO_{3})_{2})}$ and 0 M, 0.01 M, 0.02 M, 0.03 M and 0.05 M sodium sulfate $(\\mathsf{N a}_{2}\\mathsf{S O}_{4})$ , respectively. The scanning electron microscopy (SEM) images in Extended Data Fig. 1 show that all $\\mathtt{C u}_{2}0$ particles are well crystallized and exhibit similar particle sizes of ${5}{-}6\\upmu\\mathrm{m}$ , whereas the morphology of ${\\bf C u}_{2}0$ crystallites changes systematically from a cube to a truncated cube to truncated octahedra with comparable proportions of the {001} and {111} facets and dominant {111} facets, to an octahedron as the ${\\sf N a}_{2}{\\sf S O}_{4}$ concentration increases from 0 to 0.05 M. \n\nDefect engineering was performed on the truncated octahedral $\\mathtt{C u}_{2}0$ particles by varying the deposition current density18. The current densities were equal to $0.45\\mathsf{m A c m}^{-2}$ 1 $\\left(\\mathsf{E}{\\cdot}\\mathsf{C u}_{2}\\mathbf{O}\\right)$ , $0.6\\mathsf{m A}\\mathsf{c m}^{-2}$ $\\left(\\mathsf{E H-C u}_{2}\\mathbf{O}\\right)$ and $0.9\\operatorname*{mA}\\mathrm{cm}^{-2}\\left(\\mathrm{H}{\\cdot}\\mathrm{Cu}_{2}\\mathrm{O}\\right)$ during deposition. The potentials with respect to the silver/silver chloride reference achieved at the ends of the depositions were $28\\mathsf{m V}_{\\cdot}$ , 3 mV and $-23\\boldsymbol{\\mathrm{mV}},$ respectively. During the electrochemical growth of ${\\bf C u}_{2}{\\bf O}$ particles, the ${\\mathsf{C u}}^{2+}$ ions were reduced to $\\mathtt{C u}_{2}0$ through the following chemical reaction: $2{\\bf C}{\\bf u}^{2+}+{\\bf H}_{2}{\\bf O}+2{\\bf e}^{-}\\rightarrow{\\bf C}{\\bf u}_{2}{\\bf O}+2{\\bf H}^{+}$ . At low deposition current and reduction potential (low dose of reductive e−), ${\\mathsf{C u}}^{2+}$ excess was generated, resulting in the formation of $\\mathtt{V_{C u}}$ defects. The higher deposition current and reduction potential increased the hydrogen concentration, which compensated for ${\\tt V}_{\\mathtt{C u}}$ defects and promoted the formation of $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects. To maintain the shape, the precursor solution was adjusted to a mixture of $0.02\\mathsf{M C u}(\\mathsf{N O}_{3})_{2}$ with 0.03 M, 0.02 M and $0.01\\mathrm{M}\\mathrm{Na}_{2}\\mathrm{S}0_{4}$ for $\\begin{array}{r}{\\mathbf{E}{\\cdot}\\mathbf{C}\\mathbf{u}_{2}\\mathbf{O}.}\\end{array}$ , EH- $\\mathtt{C u}_{2}0$ and ${\\mathsf{H}}{\\cdot}{\\mathsf{C u}}_{2}{\\mathsf{O}}$ , respectively, and the integrated charge was $0.36\\mathsf{C c m}^{-2}$ for all samples to maintain similar particle sizes. \n\nFor photodeposition of Au, the utilized precursor solution contained $20\\upmu\\upmu$ chloroauric acid $\\mathrm{(HAuCl_{4})}$ ) and a mixture of methanol and deionized water with a volume ratio of 1:20. $\\mathsf{H A u C l}_{4}$ was used as the precursor, and methanol was utilized as a hole scavenger. The $\\mathtt{C u}_{2}0$ particles grown on an FTO sheet were immersed into the precursor solution and irradiated by a 300-W xenon (Xe) lamp (wavelength ${>}420\\mathsf{n m}$ ) for $60{\\mathsf{s}}.$ \n\n# Scanning probe microscopy \n\nAtomic force microscopy (AFM), Kelvin probe force microscopy (KPFM), SPVM and conductive AFM (C-AFM) measurements were performed under an ambient atmosphere using a commercial AFM system (Bruker Dimension Icon). Platinum/iridium-coated silicon tips with a spring constant of 1– ${\\cdot}5\\mathsf{N}\\mathsf{m}^{-1}$ and a resonance frequency of $60{-}100\\mathrm{kHz}$ (Bruker SCM-PIT) were used in all measurements. \n\nKPFM. During KPFM measurements, the contact potential difference (CPD) signals that denote the surface potential were mapped in the amplitude-modulated (AM-KPFM) mode at an a.c. voltage of $0.5{\\mathrm{V}}.$ During the surface potential measurements, the lift mode was used with minimal lift height to minimize possible cross-talk artefacts from the compensation of the tip and cantilever32. The lift height was set to $30\\mathrm{-}50\\mathrm{nm}$ for high-quality imaging and was set to about $0\\mathsf{n m}$ for the quantitative measurements. KPFM was used to map the inter-facet potential distributions on $\\mathtt{C u}_{2}0$ particles. The surface potential of the {001} facets is higher than that of the {111} facets (Extended Data Fig. 1d), resulting in an inter-facet built-in electric field with direction from the {001} to {111} facets. The strength of the built-in electric field was determined by fitting the inter-facet potential distribution with an abrupt junction model, as shown in Extended Data Fig. 6b. The fitting was conducted by using the following relations between the surface potential (CPD) and position $(x)$ : \n\n$$\n\\mathrm{CPD}(x)=-\\frac{q N_{\\{001\\}}}{2\\varepsilon_{0}\\varepsilon_{r}}{\\left(x+w_{\\{001\\}}\\right)}^{2}+\\mathrm{CPD}_{\\{001\\}},x<0\n$$ \n\n$$\n\\mathrm{CPD}\\left(\\boldsymbol{x}\\right)=\\frac{q N_{\\mathrm{\\{111\\}}}}{2\\varepsilon_{0}\\varepsilon_{r}}\\left(\\boldsymbol{x}-\\boldsymbol{w}_{\\mathrm{\\{111\\}}}\\right)^{2}+\\mathrm{CPD}_{\\mathrm{\\{111\\}}},\\boldsymbol{x}>0\n$$ \n\nwhere $q$ is the elementary charge; $N_{\\{001\\}}$ and $N_{\\{111\\}}$ are the doping density of {001} and {111} facets, respectively; $\\varepsilon_{\\mathrm{r}}$ is the relative dielectric constant and $\\scriptstyle{\\varepsilon_{0}}$ is the vacuum dielectric constant; ${w_{\\mathrm{{\\{001\\}}}}}$ and $\\scriptstyle w_{\\mathrm{:111}}$ are the width of SCR distributed at {001} and {111} facets, respectively; $x=0$ is inter-facet edge; $x<0$ is the region of {001} facet and $x>0$ is the region of {111} facet. The strength of the electric field $(E)$ was calculated based on the equation: \n\n$$\nE\\left(x\\right)=\\Bigg|\\frac{\\mathsf{d C P D}(x)}{\\mathsf{d}x}\\Bigg|.\n$$ \n\nBy using the reasonable values $q=1.6\\times10^{-19}\\mathrm{C},\\varepsilon_{0}=8.85\\times10^{-12}\\mathrm{F}\\mathrm{m}^{-1}$ and $\\varepsilon_{\\mathrm{r}}=7.2$ (ref. 10), the fitting gave $\\ensuremath{N_{\\mathrm{5001}\\rangle}}=6\\times10^{14}\\mathrm{cm}^{-3},\\ensuremath{N_{\\mathrm{5111}}}=1\\times10^{14}\\mathrm{cm}^{-3}.$ , $w_{\\{001\\}}=120\\ \\mathrm{nm},w_{\\{111\\}}=560\\ \\mathrm{nm},\\mathrm{CPD}_{\\{001\\}}=75\\ \\mathrm{mVa}$ and $\\mathrm{CPD}_{\\{111\\}}=23\\:\\mathsf{m V}.$ The strength of the electric field was calculated to be $1.7\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ at $x=0$ . \n\nSPVM. SPV is the difference between the CPD values obtained before and after illumination, which is expressed as $\\mathrm{SPV}=\\mathbf{CPD}_{\\mathrm{light}}-\\mathbf{CPD}_{\\mathrm{dark}}$ (ref. 33). The SPV magnitude is directly proportional to the number of separated charges and charge separation distance11. The SPV sign reflects the types of surface photogenerated charge with positive SPV-denoted photogenerated holes and negative SPV-denoted photogenerated electrons. Steady-state SPV signals can be mapped by SPVM and details about SPVM principles and applications can be found in our review articles11,34. Here, SPVM measurements were conducted by continuously mapping the surface potential images obtained in the dark and under illumination by KPFM. The difference between these images obtained at the same location was extracted as an SPVM image. For typical SPVM images, a $450\\cdot\\mathrm{nm}$ laser with a light intensity of approximately $5\\mathsf{m}\\mathsf{w}\\mathsf{c m}^{-2}$ was used as the excitation source. Modulated SPV signals (Extended Data Fig. 4c) were obtained by feeding the $6{\\cdot}\\mathsf{H z}$ light-modulated CPD signal into an external SR830 DSP lock-in amplifier and synchronizing it with the chopped signal. The SPV signals modulated by the external lock-in amplifier yielded an energy resolution of less than $5\\mathsf{m V}$ , and the related cross-talk artefacts were negligible. To examine the dependence of SPV signals on the light wavelength (Extended Data Fig. 9d), wavelength-tunable monochromatic light was generated by a 300-W Xe arc lamp (PLS-SXE300, Beijing Perfectlight) using a Zolix Omni-λ 500 monochromator. To investigate the dependence of SPV signals on the light power (Extended Data Fig. 4e), $\\mathsf{a}450{\\cdot}\\mathsf{n m}$ laser equipped with a neutral density filter was used to vary the light power from 0 to $100\\mathsf{m w c m}^{-2}$ . \n\nC-AFM. Facet-dependent current–voltage (I–V) curves (Extended Data Fig. 4d) were obtained by C-AFM in the PeakForce TUNA mode. I–V curves were recorded by sweeping the sample bias from negative $(-5\\mathsf{V})$ to positive $(+5\\mathsf{V})$ values. At a positive bias voltage, electrons were injected from the tip into $\\mathtt{C u}_{2}0$ particles and then collected by the FTO back contact. A 450-nm laser with a light intensity of $5\\mathsf{m w}\\mathsf{c m}^{-2}$ was used to measure the photocurrent. \n\n# Electron microscopy \n\nTR-PEEM, X-ray photoemission electron microscopy (XPEEM), and low-energy electron microscopy (LEEM) were performed on a Dreamline (BL09U) XPEEM end-station at the Shanghai Synchrotron Radiation Facility equipped with an aberration-corrected spectroscopic photoemission and low-energy electron microscopy system (SPELEEM III, ELMITEC). These experiments were carried out at room temperature in an ultrahigh vacuum chamber with a base pressure of $2\\times10^{-10}$ torr or better. \n\nTR-PEEM. TR-PEEM is a technique that combines an optical pump– probe method and PEEM to visualize the photogenerated carrier dynamics on the ultrasmall (less than $100\\mathsf{n m}\\cdot$ ) and ultrafast (femtosecond) scales. In TR-PEEM, electrons are excited into vacuum by a two-photon photoemission process, in which a pump pulse induces electronic excitation and a delayed probe pulse excites photoemission electrons from the excited states into vacuum (as schematically shown in Extended Data Fig. 5b), where they are focused by electron optics onto an electron imaging detector. More details of this technique can be found in recent studies20,21,25,35,36. The ultrafast laser used in this work was an oscillator (FLINT, Light Conversion) delivering 6-W pulses with a width of less than 100 fs, a centre wavelength of $\\phantom{-}1,030\\mathsf{n m}$ and a repetition rate of 76 MHz. A true zero-order half-wave plate and a thin-film polarizer were used to distribute the laser power to the pump and probe laser paths. The 1,030-nm fundamental harmonic was focused into a lithium triborate crystal to generate the second-order harmonic 515-nm (2.4-eV) laser pulses that served as the pump pulses. The second second-order harmonic was doubled within a Beta barium borate crystal to generate the fourth-order harmonic $257.5{\\cdot}\\mathsf{n m}\\left(4.8{\\cdot}\\mathsf{e V}\\right)$ laser pulses that served as the probe pulses. The pump and probe lasers were collimated with a customized dichroic mirror and then were focused into the PEEM chamber, where they were incident at a grazing angle of about $16^{\\circ}$ on the sample. The pump laser spot on the sample was about $50\\times100\\upmu\\mathrm{m}^{2}$ , and the probe laser spot was about $100\\times125\\upmu\\mathrm{m}^{2}$ . The cross-correlation of this scheme was approximately 184 fs. Incident pump fluences were tuned using neutral density filters, and a fluence of about $15\\upmu\\mathrm{J}\\mathsf{c m}^{-2}$ was used unless otherwise mentioned. This corresponded to an excitation density of $2.6\\times10^{17}\\mathrm{cm}^{-3}$ obtained at an absorption coefficient of 1 $3,000\\mathsf{c m}^{-1}$ for $\\mathtt{C u}_{2}0$ with 2.4-eV excitation37. The photoelectrons emitted from the surface by the pump–probe were collected in the PEEM mode of SPELEEM after passing through a series of electro-optical elements to produce magnified TR-PEEM images at different pump– probe time delays. To obtain the TR-PEEM images in Fig. 2a, a reference image captured at $^{-2}$ ps is subtracted to eliminate the background. \n\nThe energy-resolved photoelectron signals or time-resolved micro-area photoelectron spectra (PES) were recorded for an area with a diameter of $1.5\\upmu\\mathrm{m}$ by inserting the field-limiting aperture in the dispersive plane imaging mode. The energy-resolved photoelectron yield was computed by integrating the PES signal from over a high-energy or low-energy range (Extended Data Fig. 7a,b). The dynamic traces of energy-resolved photoelectron intensity $(I)$ were fitted with kinetic rate equation to obtain the time constant. For the {111} facets, the decay traces of high-energy photoelectron intensity were fitted with the following equation38: \n\n$$\n\\frac{\\mathrm{d}I\\left(t\\right)}{\\mathrm{d}t}=A_{1}\\times\\mathrm{e}^{\\left\\{-\\frac{(t-t_{0})^{2}}{2w^{2}}\\right\\}}-\\frac{I\\left(t\\right)}{\\tau},\n$$ \n\nwhere $t_{0}$ denotes zero delay; $t$ is the decay time; $\\tau$ is the decay time constant; $w$ is the width of the pump pulse (about 0.07 ps); and A is the proportionality factor. The fitting resulted in a decay time constant of 0.05 ps for the ultrafast inter-facet electron transfer. For the {001} facets, the fitting equation for the decay of high-energy photoelectron intensity is provided below: \n\n$$\n\\frac{\\mathrm{d}I\\left(t\\right)}{\\mathrm{d}t}=A_{1}\\times\\mathrm{e}^{\\left\\{-\\frac{\\left(t-t_{0}\\right)^{2}}{2w^{2}}\\right\\}}-\\frac{I\\left(t\\right)}{\\tau}+A_{2}\\times\\left(1-\\mathrm{e}^{-\\frac{t}{0.05}}\\right),\n$$ \n\nwhere the first term denotes the convoluted time function of probe pulse; the second term denotes the decay of high-energy photoelectrons with a time constant of $\\tau$ ; the third term denotes the increase of photoelectrons owing to inter-facet electron transfer with a time constant of 0.05 ps. The fitting results gave a decay time constant of 0.18 ps for the {001} facets. The growth of low-energy photoelectron intensity for the {001} facets was fitted with the following equation: \n\n$$\nI\\left(E\\right)=A\\times\\left(1-{\\bf e}^{-\\frac{t}{\\tau}}\\right)\\otimes G\\left(\\Delta t\\right),\n$$ \n\nwhere $G(\\Delta t)$ denotes the convoluted time function of probe pulse; the term $\\left(1-\\mathbf{e}^{-\\frac{t}{\\tau}}\\right)$ denotes the growth of low-energy photoelectron intensity; and A is the proportionality factor. The fitting results gave a time constant of 0.2 ps, consistent with decay time constant of high-energy photoelectron intensity. \n\nTo obtain electron temperatures at different time delays, the time-resolved PES were fitted with a hot Fermi–Dirac distribution and density of states in the conduction band. The fitting equation is provided below20: \n\n$$\nI(E)=A\\sqrt{E-E_{\\mathrm{C}}}{\\left({\\bf e}^{{\\textstyle{-E_{\\mathrm{F}}}}}+1\\right)^{-1}}\\otimes G\\left(\\Delta E\\right),\n$$ \n\nwhere $G(\\Delta\\boldsymbol{E})$ is the convoluted Gaussian instrumental resolution function with an energy resolution $(\\Delta E)$ of $150\\mathrm{meV}$ ; the term $\\sqrt{E-E_{\\mathrm{c}}}$ shows that the photoemission intensity is proportional to the density of states in the conduction band with the minimum energy $E_{\\mathrm{c}};k$ is the Boltzmann constant; $T$ is the electron temperature; $\\boldsymbol{E}_{\\mathrm{F}}$ is the Fermi energy; and A is the proportionality factor to account for the photoemission cross-section and other constants. $T$ and $\\boldsymbol{E}_{\\mathrm{F}}$ are fitting variables. The time-resolved and facet-dependent SPV signals were acquired from the shifts in the peak positions of the micro-area PES obtained at different pump–probe delays for each facet. \n\nXPEEM. XPEEM exploited synchrotron radiation X-rays to implement spatially resolved XPS, Auger electron and X-ray absorption spectra. An X-ray photon energy of $1,050\\mathrm{eV}$ was used to directly emit photoelectrons from atomic core levels, which were then imaged by PEEM. By inserting energy slits in the dispersive plane in the imaging mode, energy-filtered XPEEM images were recorded in a stack by scanning the kinetic energy of core-level photoelectrons within a narrow kinetic energy window for the interested ranges, for example, Cu $2p_{3/2},$ O 1s and Cu LMM. Spatially resolved XPS spectra were obtained by extracting the photoelectron intensities from different facets in the stacked XPEEM images. The energy resolution of the XPS spectra, limited by the analyser exit slits, is about $0.2{\\mathrm{eV.}}$ To obtain X-ray absorption imaging, the imaging analyser was set for the detection of secondary electrons with $1.5{\\cdot}\\mathrm{eV}$ photoelectron energy. Spatially resolved X-ray absorption spectra were similarly acquired by varying the incoming photon energy across the absorption edges of interest (Cu L edge) and extracting the photoelectron intensity of every energy point from the stacked X-ray images. \n\nLEEM. LEEM measurements were performed to identify the surface structures of $\\mathtt{C u}_{2}0$ by using the backscattered electrons to image the surface in the LEEM mode of the SPELEEM. The micro-area low-energy electron diffraction (LEED) patterns were obtained by restricting electron beam to a region of $1.5\\upmu\\mathrm{m}$ in diameter in the facet centre of the {001} and {111} facets oriented parallel to the substrate, as shown in Extended Data Fig. 2a. The LEED patterns of {001} and {111} facets recorded with 30-eV electron energy are shown in Extended Data Fig. 2b,c. The LEED pattern of the {001} facet originates from either the $(1\\times1)$ or the $c(2\\times2)$ surface structure, and the LEED pattern of the {111} facet results from either the $(1\\times1)$ or the $(\\sqrt{3}\\times\\sqrt{3})\\mathsf{R}30^{\\circ}$ (a reconstructed surface structure with lattice direction rotating $30^{\\circ}$ \n\n# Article \n\n$$\n\\ v=\\frac{1}{\\hbar}\\frac{\\partial E(k)}{\\partial k},\n$$ \n\ncompared with that of the $(1\\times1)$ structure) surface structure. If the real space lattice constant of $\\mathtt{C u}_{2}0$ is $a$ , the reciprocal lattice constants determined for the $(1\\times1)$ and $c(2\\times2)$ surface structures of the {001} lfatcteicteacreo nesqtuaanlttso $\\frac{1}{a}$ taind ${\\frac{1}{\\surd2}}\\times{\\frac{1}{a}}.$ ,hre taivnedl shuerrfeaciepsrtorucac-l $(1\\times1)$ $(\\sqrt{3}\\times\\sqrt{3})\\mathsf{R}30^{\\circ}$ tures of the {111} facet are equal to $\\frac{\\surd2}{\\surd3}\\times\\frac{1}{a}$ and ${\\frac{\\surd2}{3}}\\times{\\frac{1}{a}},$ respectively. The measured to be approximately $1.22\\approx{\\frac{\\sqrt{3}}{\\sqrt{2}}}$ , corresponding to the $(1\\times1)$ the presence of complex surface oxygen vacancy defects owing to surface reconstruction for $\\mathtt{C u}_{2}0$ (ref. 39), which may affect the ultrafast carrier dynamics38,40. Therefore, we used $(1\\times1)$ surface structures for DFT calculations41. \n\nSEM. Sample morphologies were analysed via SEM using a Quanta 200 FEG scanning electron microscope. The operating voltage was $30{\\mathsf{k V}}.$ \n\n# Transient SPV spectroscopy \n\nTransient SPV spectroscopy measurements were performed in a fixed-capacitor arrangement42. In our set-up, SPV signals were coupled with high-impedance buffers (measurement resistance, 50 GΩ) and SPV transients were excited with pulses from a tunable neodymium-doped yttrium aluminium garnet laser (EKSPLA NT342/1/UVE). The duration and repetition rates of the laser pulses were 4 ns and 1 Hz, respectively. The transients were detected by a sampling oscilloscope (GAGE, CS14200) with a resolution time of 5 ns. A logarithmic read-out based on a logarithmic averaging procedure was applied to register the SPV transients43. \n\n# XPS \n\nEnsemble-averaged XPS measurements were performed on the freshly prepared $\\mathtt{C u}_{2}0$ samples using a Thermo ESCALAB 250Xi spectrometer with a monochromatic Al $\\upkappa\\upalpha$ source (1486.6 eV) at a voltage of $15\\mathsf{k V}$ and current of $10.8\\mathrm{{mA}}$ . \n\n# Raman microscopy \n\nFacet-dependent Raman spectroscopy and Raman imaging were performed using a Renishaw InVia confocal Raman microscope equipped with an Olympus $\\times100$ objective. A laser with an emission wavelength of $532{\\mathsf{n m}}$ was used for excitation. \n\n# Ultraviolet–visible absorption spectroscopy \n\nAbsorbance was measured using a ultraviolet–visible spectrophotometer (JASCO V–650) by recording diffuse reflection spectra. \n\n# DFT calculations \n\nAll DFT calculations in the present study were performed using the Vienna Ab Initio Simulation Package with the projector augmented wave method for the description of ionic cores44. $\\mathtt{C u}_{2}0$ geometry optimization was conducted by the DFT $+U$ method with the Perdew–Burke–Ernzerhof (PBE) exchange correlation functional and an effective Hubbard $\\upsilon$ value of 6 eV. Although the Heyd–Scuseria– Ernzerhof (HSE) hybrid functional can predict structural properties more accurately, it is computationally too expensive for the given sizes of the $\\mathtt{C u}_{2}0$ slabs. A benchmark study of the geometry optimization of the $\\mathtt{C u}_{2}0$ unit cell demonstrated that the unit cell lattice constants calculated by HSE06 and PBE+U were 4.294 Å and $4.288\\mathring{\\mathbf{A}}$ , respectively, indicating that HSE weakly influenced the structural characteristics although it improved the accuracy of electronic structural properties. The band structure (Extended Data Fig. 5c) and group velocity of electrons (Extended Data Fig. 6i) within the conduction band of bulk ${\\bf C u}_{2}{\\bf O}$ were calculated using the hybrid HSE06 functional45 with a cut-off energy of 500 eV and ${\\boldsymbol{8\\times8\\times8}}{\\boldsymbol{\\times}}{\\boldsymbol{\\times}}{\\boldsymbol{\\times}}$ -centred mesh for electronic Brillouin zone integration. The group velocity of electrons was determined via the equation: \n\nwhere $E(k)$ denotes the energy dispersion relation function described by the band structure and ħ is the reduced Planck constant. The electron Fermi velocity was calculated along the $\\Gamma\\to\\mathbb{R}$ direction. \n\nDefect formation energies of $\\mathtt{V_{C u}}$ and $\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}}$ for the $\\{001\\}$ and {111} $\\mathtt{C u}_{2}0$ facets were determined for the $2\\times2$ periodic $\\mathtt{C u}_{2}0$ slab models at the hybrid functional HSE06 level (Extended Data Fig. 2). The formation energy of a certain defect was calculated by the Zhang–Northrup equation46: \n\n$$\nE^{\\mathrm{f}}\\left(X^{q}\\right)=E\\left(X^{q}\\right)-E_{0}-\\sum_{i}n_{i}(E_{i}+\\mu_{i})+q E_{\\mathrm{F}},\n$$ \n\nwhere the X denotes the defective cell and i denotes the defect atoms, and the ${{E}_{0}}$ and $E(X^{q})$ are the total energies of the stoichiometric slab supercell and defective cell, respectively. $E_{i}$ denotes the constituent elements in their standard states, that is, the face-centred cubic Cu and ${\\sf H}_{2}{\\bf g a s.}n_{i}$ is the number of defect atoms added to an external reservoir. The chemical potential $\\mu_{i}$ is determined under a $\\mathtt{C u/H}$ -rich condition. We used $\\mathsf{P B E}{+}U$ to find that $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ in a neutral state had the lowest formation. Ultrafast trapping induced by defects in different charge states40 was not observed in the TR-PEEM data, further supporting this idea. Therefore, only neutral defects were considered and the term $q E_{\\mathrm{{F}}}$ was eliminated. We used $2\\times2$ periodic slab models to make computations affordable for the hybrid HSE06 functional. We calculated surface energies for the two facets using different slabs and found that further increasing the slab size produced little impact on the surface energy (less than $2\\%$ ), indicating that the current model could adequately describe the surface structural relaxation and energy. All slabs were separated by $12\\mathring{\\mathbf{A}}$ in vacuum, and dipole corrections were applied to the model systems. The charge density $(p)$ difference was calculated by the formula: \n\n$$\n\\Delta p=p\\left(\\mathrm{Cu}_{2}\\mathrm{O}/(\\mathsf{H}-\\mathrm{V}_{\\mathrm{Cu}})\\right)-p\\left(\\mathrm{Cu}_{2}\\mathrm{O}\\right)-p\\left(\\mathsf{H}-\\mathrm{V}_{\\mathrm{Cu}}\\right),\n$$ \n\nbased on the optimized defective slabs to show the effect of defect formation on charge distributions at surrounding atoms. \n\nCharge transfer simulations using the drift–diffusion model The simulations were performed based on the Poisson and continuity equations. The continuity equation was first used to describe the charge transfer in the inter-facet built-in electric field as follows47: \n\n$$\n\\begin{array}{c}{\\displaystyle\\frac{\\partial\\Delta p(x,t)}{\\partial t}=D_{\\mathsf{p}}\\times\\displaystyle\\frac{\\partial^{2}\\Delta p(x,t)}{\\partial x^{2}}-\\mu_{\\mathsf{p}}E\\times\\displaystyle\\frac{\\partial\\Delta p(x,t)}{\\partial x}-\\mu_{\\mathsf{p}}\\times\\Delta p(x,t)}\\\\ {\\displaystyle\\frac{\\partial E}{\\partial x}-\\displaystyle\\frac{\\Delta p(x,t)}{\\tau_{\\mathsf{p}}},}\\end{array}\n$$ \n\nwhere $\\Delta p(x,t)$ is the excess hole density, $D_{\\mathfrak{p}}$ is the hole diffusion coefficient, $\\mu_{\\mathfrak{p}}$ is the hole mobility and $E$ is the electric field. $E_{\\mathrm{{\\ell}}}$ corresponding to the x coordinate, is a finite difference; therefore, it can be considered a constant for each differential unit. Hence, the continuity equation was simplified to: \n\n$$\n\\frac{\\partial\\Delta p(x,t)}{\\partial t}=D_{\\mathrm{p}}\\times\\frac{\\partial^{2}\\Delta p(x,t)}{\\partial x^{2}}-\\mu_{\\mathrm{p}}E\\times\\frac{\\partial\\Delta p(x,t)}{\\partial x}-\\frac{\\Delta p(x,t)}{\\tau_{\\mathrm{p}}},\n$$ \n\nA similar description was used for electrons: \n\n$$\n\\frac{\\partial\\Delta n(x,t)}{\\partial t}=D_{\\mathrm{n}}\\times\\frac{\\partial^{2}\\Delta n(x,t)}{\\partial x^{2}}-\\mu_{\\mathrm{n}}E\\times\\frac{\\partial\\Delta n(x,t)}{\\partial x}-\\frac{\\Delta n(x,t)}{\\tau_{\\mathrm{n}}},\n$$ \n\nwhere $\\Delta n(x,t)$ is the excess electron density, $D_{\\mathfrak{n}}$ is the electron diffusion coefficient and $\\mu_{\\mathfrak{n}}$ is the electron mobility. The separation and transfer of photogenerated electrons and holes in the built-in electric field induced a reverse electric field and impeded the further charge transfer, as schematically shown in Extended Data Fig. 6d. $E_{\\mathfrak{p}}$ can be calculated via the Poisson equation as follows: \n\n$$\n\\frac{\\partial E_{\\mathrm{p}}(x,t)}{\\partial x}=-\\frac{e\\left(\\Delta n(x,t)-\\Delta p(x,t)\\right)}{\\varepsilon_{0}\\varepsilon_{r}}.\n$$ \n\nwhere $e$ is elementary charge. By solving the continuity equations (12) and (13), substituting the excess electron and hole densities into the Poisson equation (14), and integrating $E_{\\mathfrak{p}}$ over the propagation distance $(d)$ , we obtain the SPV as follows: \n\n$$\n{\\mathrm{SPV}}(t)=\\int_{0}^{d}E_{\\mathrm{p}}(x,t)\\mathrm{d}x=\\sum_{i=1}^{n}{\\frac{d}{n}}E_{\\mathrm{p}}{\\bigg(}i{\\frac{d}{n}}{\\bigg)}.\n$$ \n\nTo calculate $\\mathsf{S P V}(t)$ , the following parameters were used: propagation distance $d=680\\mathrm{nm}$ , doping density $N{=}10^{14}\\mathsf{c m}^{-3}$ (d and N were determined from the potential distribution fits in Extended Data Fig. 6b), dielectric constant $\\mathcal{E}_{0}=8.85\\times10^{-12}\\mathrm{F}\\mathrm{m}^{-1}$ , $\\varepsilon_{\\mathrm{r}}=7.2$ (ref. 10) and $\\mu_{\\mathrm{p}}=50\\mathrm{cm}^{2}\\mathrm{V}^{-1}\\mathrm{s}^{-1}(\\mathrm{\\Omega}$ ref. 48). The hole diffusion coefficient $D_{\\mathfrak{p}}$ was calculated from the hole mobility based on the Einstein relationship. Two cases were considered during $\\mathsf{S P V}(t)$ calculations. In one case, the carriers were cooled to room temperature (298 K), and the computed $D_{\\mathfrak{p}}$ was $1.25\\mathsf{c m}^{2}\\mathsf{s}^{-1}$ . In the other case, the carriers were in a non-equilibrium state (without carrier scattering) at a temperature of about $_{5,000\\mathsf{K}}$ , calculated as follows49: \n\n$$\nT=\\frac{(E_{\\mathrm{ph}}-E_{\\mathrm{g}})}{k_{0}},\n$$ \n\nwhere $E_{\\mathrm{ph}}=2.4\\:\\mathrm{eV}$ is the energy of the incident photons, $E_{\\mathrm{g}}=2.0$ eV is the optical bandgap of $\\mathtt{C u}_{2}0$ and $k_{0}$ is the Boltzmann constant. The electron mobility is approximately 100 times larger than the hole mobility determined for the electrodeposited $\\mathtt{C u}_{2}0$ single particles in our previous study10. Therefore, the electron mobility used during simulations was $\\scriptstyle5,000\\ c m^{2}\\bigvee^{-1}\\mathbf{S}^{-1}$ , which produced the maximum electron transfer velocity $(\\upsilon)$ in the built-in electric field of $8.5\\times10^{4}\\mathrm{m}\\mathrm{s}^{-1}$ based on $\\scriptstyle{\\boldsymbol{v}}=\\mu E$ . Simulations performed using this model revealed that the drifts of equilibrium and non-equilibrium carriers in the inter-facet built-in electric field occurred on timescales of about 150 ps and about 10 ps, respectively (Extended Data Fig. 6e), which were significantly longer than those observed experimentally (about 0.2 ps). Achieving the experimental timescale would require an inter-facet electron transfer velocity of $5\\times10^{7}\\mathsf{m}\\mathsf{s}^{-1}$ (Extended Data Fig. 6f), which exceeds the experimental value by three orders of magnitude. These simulation results demonstrated that the ultrafast inter-facet electron transfer observed could not be explained by the conventional drift–diffusion model. Although the subpicosecond carrier transport in gallium arsenide surface space charge fields has been simulated using the drift–diffusion model, the simulations used a high drift velocity of $5\\times10^{6}\\mathsf{m}\\mathsf{s}^{-1}$ both for electrons and holes50, which is unreasonable for the ${\\bf C u}_{2}{\\bf O}$ system. \n\nCharge transfer simulations using the quasi-ballistic model In this section, simulations were performed assuming that hot electrons moved in an ensemble with Coulomb screening disregarded51, whereas holes were immobile owing to their much slower mobility compared with that of hot electrons. The electron transfer from the {111} to {001} facets led to charge separation and SPV generation. The oriented electron transfer occurred in the inter-facet SCR and the {001} facet with a velocity determined by the initial kinetic energy, the acceleration by the inter-facet built-in electric field and the deceleration due to scattering (schematically shown in Extended Data Fig. 6g,h). The electron transfer velocity $(\\upsilon)$ is expressed by the formula: \n\n$$\n\\frac{\\mathrm{d}\\nu\\left(x,t\\right)}{\\mathrm{d}t}=\\frac{q^{*}}{m^{*}}E\\left(x\\right)-\\frac{\\nu\\left(x,t\\right)}{\\tau_{\\mathrm{S}}},\n$$ \n\nwhere $\\frac{q^{*}}{m^{*}}$ is the effective specific charge of hot electron ensemble, $E(x)$ is the inter-facet built-in electric field distributions determined by KPFM and $\\tau_{\\mathrm{s}}$ is the time constant of dominant scattering events. We demonstrated that the dominant scattering process was optical phonon–electron scattering with $\\tau_{\\mathrm{S}}\\approx0.2$ ps (Extended Data Fig. 7). The electron density $(Q)$ distribution can be calculated from the electron transfer velocity as follows: \n\n$$\n\\frac{\\mathrm{d}Q(x,t)}{\\mathrm{d}t}{=}Q(x,t)\\times\\upsilon(x,t)-\\frac{Q(x,t)}{\\tau_{\\mathrm{R}}},\n$$ \n\nwhere the first term denotes the electron population increase on the {001} facets due to electron transfer, and the second term represents the decrease in the electron population of conduction band owing to recombination or interactions with defects with a decay time constant of $\\tau_{\\scriptscriptstyle{\\mathrm{R}}}$ . The second term is neglected on the ultrafast timescale as demonstrated by the energy-integrated PEEM data, which show that the electron population decreases after 100 ps. Then, the SPV function can be expressed as: \n\n$$\n\\mathsf{S P V}(t)\\propto\\iint_{\\{111\\}}^{\\{001\\}}t\\times v\\left(x,t\\right)\\times\\mathsf{d}Q\\left(x,t\\right)\\times\\mathsf{d}x\\times\\mathsf{d}t.\n$$ \n\nWe performed numerical simulations to monitor the SPV evolution on the {001} facet (Fig. 2e) by combining equations (17)–(19). $\\tau_{\\mathrm{S}}=0.2$ ps was used, and the effect of $\\tau_{\\mathrm{R}}$ was neglected during simulations. The initially excited electron density involved a Gaussian temporal resolution function. The parameter of initial velocity $\\scriptstyle v_{0}$ and the acceleration $\\textstyle({\\frac{q^{*}}{m^{*}}}E(x))$ in the electric field determine the shape of the simulated SPV curve. To make this curve match the experimental data, the $\\frac{q^{*}}{m^{*}}E(x)\\times\\tau_{\\mathrm{S}}$ term was on the same order of magnitude as $\\boldsymbol{\\upsilon}_{0}$ and the best fit resulted in $\\nu_{0}{\\approx}3\\times10^{5}{\\mathrm{ms}}^{-1}.$ , which was in good agreement with the calculated group velocity of electrons within the conduction band (Extended Data Fig. 6i). It is noted that the electron propagation in both the inter-facet region and {001} facet region without a built-in electric field contributed to the SPV of the {001} facets, yielding a larger SPV value than that generated in the drift regime. \n\n# Photocatalytic measurements \n\nPhotocatalytic reactions were performed in a Pyrex top-irradiation-type reaction vessel connected to a closed gas circulation system. $\\mathtt{C u}_{2}0$ particles grown on $2\\times2\\mathrm{cm}$ FTO sheets were immersed in a $0.5\\mathsf{M N a}_{2}\\mathsf{S O}_{3}$ solution $(150\\mathrm{ml})$ . The mass of these $\\mathtt{C u}_{2}0$ particles calculated from the integrated charge during electrochemical synthesis was approximately 1 mg. According to the results of a previous study52, ${\\bf N a}_{2}{\\bf S O}_{3}$ is the most effective hole scavenger for the photocatalytic ${\\sf H}_{2}$ generation by $\\mathtt{C u}_{2}0$ . The system was evacuated to ensure complete air removal and then irradiated from the top side using a 300-W Xe lamp (Ushio-CERMAX LX300). Cooling water was flowed to maintain the reaction suspension at $288\\mathsf{K}$ . The evolved ${\\sf H}_{2}$ gas was analysed via online gas chromatography (Shimadzu GC-8A, TCD, argon carrier). \n\n# Data availability \n\nThe data that support the findings of this study are available at https:// www.scidb.cn/en/s/FjEzym or from the corresponding authors upon request. \n\n31.\t Siegfried, M. J. & Choi, K. S. Electrochemical crystallization of cuprous oxide with systematic shape evolution. Adv. Mater. 16, 1743–1746 (2004). \n\n# Article \n\n32.\t Barbet, S. et al. Cross-talk artefacts in Kelvin probe force microscopy imaging: a comprehensive study. J. Appl. Phys. 115, 144313 (2014). \n33.\t Kronik, L. & Shapira, Y. Surface photovoltage phenomena: theory, experiment, and applications. Surf. Sci. Rep. 37, 1–206 (1999). \n34.\t Chen, R., Fan, F. & Li, C. Unraveling charge‐separation mechanisms in photocatalyst particles by spatially resolved surface photovoltage techniques. Angew. Chem. Int. Ed. 61, e202117567 (2022). \n35.\t Fukumoto, K. et al. Femtosecond time-resolved photoemission electron microscopy for spatiotemporal imaging of photogenerated carrier dynamics in semiconductors. Rev. Sci. Instrum. 85, 083705 (2014). \n36.\t Da̧browski, M., Dai, Y. & Petek, H. Ultrafast photoemission electron microscopy: imaging plasmons in space and time. Chem. Rev. 120, 6247–6287 (2020). \n37. Malerba, C. et al. Absorption coefficient of bulk and thin film ${\\mathsf{C u}}_{2}{\\mathsf{O}}.$ Sol. Energy Mater. Sol. Cells 95, 2848–2854 (2011). \n38.\t Grad, L., Novotny, Z., Hengsberger, M. & Osterwalder, J. Influence of surface defect density on the ultrafast hot carrier relaxation and transport in $\\mathsf{C u}_{2}\\mathsf{O}$ photoelectrodes. Sci Rep. 10, 10686 (2020). \n39.\t Gloystein, A., Nilius, N., Goniakowski, J. & Noguera, C. Nanopyramidal reconstruction of $\\mathsf{C u}_{2}\\mathsf{O}$ (111): a long-standing surface puzzle solved by STM and DFT. J. Phys. Chem. C 124, 26937–26943 (2020). \n40.\t Ricca, C. et al. Importance of surface oxygen vacancies for ultrafast hot carrier relaxation and transport in ${\\mathsf{C u}}_{2}{\\mathsf{O}}.$ Phys. Rev. Res. 3, 043219 (2021). \n41. Bendavid, L. I. & Carter, E. A. First-principles predictions of the structure, stability, and photocatalytic potential of $\\mathsf{C u}_{2}\\mathsf{O}$ surfaces. J. Phys. Chem. B 117, 15750–15760 (2013). \n42.\t Dittrich, T., Fengler, S. & Franke, M. Transient surface photovoltage measurement over 12 orders of magnitude in time. Rev. Sci. Instrum. 88, 053904 (2017). \n43.\t Dittrich, T., Bonisch, S., Zabel, P. & Dube, S. High precision differential measurement of surface photovoltage transients on ultrathin CdS layers. Rev. Sci. Instrum. 79, 113903 (2008). \n44.\t Kresse, G. & J. Furthmuller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n45.\t Heyd, J., Scuseria, G. E. & Ernzerhof, M. Hydrid functionals based on a screened Coulomb potential. J. Chem. Phys. 118, 8207–8215 (2003). \n46.\t Zhang, S. B. & Northrup, J. E. Chemical potential dependence of defect formation energies in GaAs: application to Ga self-diffusion. Phys. Rev. Lett. 67, 2339–2342 (1991). \n47. de Jongh, P. E. & Vanmaekelbergh, D. Trap-limited electronic transport in assemblies of nanometer-size $\\mathsf{T i O}_{2}$ particles. Phys. Rev. Lett. 77, 3427–3430 (1996). \n48.\t Lee, Y. S. et al. Hall mobility of cuprous oxide thin films deposited by reactive direct-current magnetron sputtering. Appl. Phys. Lett. 98, 192115 (2011). \n49.\t Liao, B. et al. Photo-excited hot carrier dynamics in hydrogenated amorphous silicon imaged by 4D electron microscopy. Nat. Nanotechnol. 12, 871–876 (2017). \n50.\t Dekorsy, T., Pfeifer, T., Kutt, W. & Kurz, H. Subpicosecond carrier transport in GaAs surface-space-charge fields. Phys. Rev. B 47, 3842–3849 (1993). \n51.\t Rossi, F. & Kuhn, T. Theory of ultrafast phenomena in photoexcited semiconductors. Rev. Mod. Phys. 74, 895–950 (2002). \n52.\t Toe, C. Y. et al. Photocorrosion of cuprous oxide in hydrogen production: rationalising self-oxidation or self-reduction. Angew. Chem. Int. Ed. 57, 13613–13617 (2018). \n53.\t Poulston, S., Parlett, P. M., Stone, P. & Bowker, M. Surface oxidation and reduction of CuO and $\\mathsf{C u}_{2}\\mathsf{O}$ studied using XPS and XAES. Surf. Interface Anal. 24, 811–820 (1996). \n54.\t Sander, T. et al. Correlation of intrinsic point defects and the Raman modes of cuprous oxide. Phys. Rev. B 90, 045203 (2014). \n55.\t Petroff, Y., Yu, P. Y. & Shen, Y. R. Study of photoluminescence in $\\mathsf{C u}_{2}\\mathsf{O}.$ Phys. Rev. B 12, 2488–2495 (1975). \n56.\t Önsten, A. et al. Role of defects in surface chemistry on $\\mathsf{C u}_{2}\\mathsf{O}$ (111). J. Phys. Chem. C 117, 19357–19364 (2013). \n57.\t Soldemo, M. et al. The surface structure of $\\mathsf{C u}_{2}\\mathsf{O}(100)$ . J. Phys. Chem. C 120, 4373–4381 (2016). \n58.\t Grioni, M. et al. Unoccupied electronic structure and core-hole effects in the X-ray-absorption spectra of ${\\mathsf{C u}}_{2}{\\mathsf{O}}.$ Phys. Rev. B 45, 3309–3318 (1992). \n59.\t de Jongh, P. E., Vanmaekelbergh, D. & Kelly, J. J. Photoelectrochemistry of electrodeposited ${\\mathsf{C u}}_{2}{\\mathsf{O}}.$ J. Electrochem. Soc. 147, 486–489 (2000). \n60.\t Scanlon, D. O. & Watson, G. W. Undoped n-type $\\mathtt{C u}_{2}\\mathtt{O}$ : fact or fiction? J. Phys. Chem. Lett. 1, 2582–2585 (2010). \n\nAcknowledgements This work was conducted by the Fundamental Research Center of Artificial Photosynthesis (FReCAP) and financially supported by the National Natural Science Foundation of China (22088102, 22102173, 22073097), CAS Projects for Young Scientists in Basic Research (YSBR-004), National Program on Key Basic Research Project (2021YFA1500600, 2018YFA0208700), and Dalian Institute of Chemical Physics Innovation Foundation (DICPSZ201801). \n\nAuthor contributions R.C., F.F. and C.L. conceived the research. R.C. carried out the experiments, analysed the experimental data and wrote the manuscript. Z.R., Y. Liang, and G.Z. collected the TR-PEEM and XPEEM data. T.D. performed transient SPV spectroscopy measurements. R.L., Y. Liu and S.P. performed DFT calculations and simulations. P.Z. and K.H. supervised the DFT calculations. Y.Z. assisted in photocatalytic activity measurements. H.A. assisted in Raman microscopy measurements. C.N. assisted in data analysis. C.L. proposed the project. F.F. and C.L. supervised the project. Z.R., T.D., F.F. and C.L. discussed the data and revised the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-022-05183-1. Correspondence and requests for materials should be addressed to Fengtao Fan or Can Li. Peer review information Nature thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n![](images/a79ff6f4163ca1f76a1635149d20e513a7a7a57aee43050407e5327858b4e91f.jpg) \n\nExtended Data Fig. 1 | See next page for caption. \n\n# Article \n\nExtended Data Fig. 1 | Anisotropic facet engineering of $\\mathbf{Cu}_{2}\\mathbf{0}$ particles. a–e, SEM images obtained at low (a) and high (b) magnifications, AFM images (c), KPFM images (d), and SPVM images (e) of $\\mathbf{Cu}_{2}\\mathbf{O}$ particles with morphologies varying from a cube to an octahedron. Scale bars, (a) $20\\upmu\\mathrm{m}$ and $({\\bf b}-{\\bf e})2\\upmu\\mathrm{m}$ . Proportions (P) are defined as $\\mathsf{P}{=}\\mathsf{S}_{\\{\\mathrm{111}\\}}/(\\mathsf{S}_{\\{001\\}}{+}\\mathsf{S}_{\\{\\mathrm{111}\\}})$ , where $\\mathsf{S}_{\\mathrm{{\\smallillil}}}$ and $\\mathsf{S}_{\\{001\\}}$ represent areas of the {111} and {001} facets, respectively. The KPFM images show that the surface potential signals increase with P, indicating a gradually decreasing p-type doping level from facet {001} to {111}. The higher surface potential of the {001} facet than that of the {111} facet on a truncated octahedral particle suggests a higher p-type doping level near the {001} facet because the two facets have the same Fermi energy. The SPVM images exhibit negative signals due to the electron transfer to the surface and indicate a larger number of electrons are distributed on the {001} facet. f, Surface potential distributions across the {001} and {111} facets indicated as lines in d. g, Histograms of the SPV signals extracted from the {001} and {111} facets of polyhedral $\\mathtt{C u}_{2}0$ particles with various morphologies. Gaussian fits are used to determine the average signals. h, Correlation between the CPD and SPV signals based on the differences between the {001} and {111} facets of polyhedral $\\mathtt{C u}_{2}0$ particles with various morphologies. The data are extracted from f, g. \n\n![](images/ce0301c25eb7221c0f5815ba94c43affb8a6b01d91d4063897f8cfc2804d21dd.jpg) \nExtended Data Fig. 2 | LEEM observations and DFT calculations. a–c, LEEM image of EH- $\\mathtt{C u}_{2}0$ particles recorded at $10\\mathrm{eV}$ (a) and LEED patterns recorded at $30\\mathrm{eV}$ for the {001} (b) and {111} (c) facets of EH- $\\mathtt{C u}_{2}0$ particles circled in a. The LEED patterns and the ratio of the reciprocal lattice a\\* and b\\* $(\\frac{\\surd3}{\\surd2})$ determine the (1×1) surface structures for {001} and {111} facets (see detailed analyses in Methods). d–i, Optimized geometries of the {001} (d–f) and {111} $\\left(\\mathbf{g-i}\\right)$ surfaces of $\\mathtt{C u}_{2}0$ without (d, g) and with ${\\tt V}_{\\mathrm{Cu}}(\\mathbf{e},\\mathbf{h})$ or $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ (f, i) defects. The red, pink, and white spheres represent O, Cu, and H atoms, respectively. j, Calculated formation energies of the $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects on the {001} and {111} facets at the HSE06 level based on the $2{\\times}2$ periodic $\\mathtt{C u}_{2}0$ slab structures depicted in d–i (see details in Methods). These results indicate that the \nformation of $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects is much more favourable at {111} facets compared to {001} facets. k, Charge density difference obtained for the $\\mathtt{C u}_{2}0$ {111} surface structure (i) with a $\\left(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}}\\right)$ defect. The red, blue, and white spheres represent O, Cu, and H atoms, respectively. The yellow and cyan colours denote the increase and decrease in electron density, respectively. The obtained results demonstrate that the formation of $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}})$ defects increases the electron density at Cu atoms. We also performed a Bader charge analysis and found that the averaged charge on Cu atom decreased from 0.514 to 0.495 after the formation of $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects. Therefore, the presence of $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ lowers the valences of the surrounding Cu atoms. \n\n# Article \n\n![](images/3826d04adcd5e6b28bb16c826e95a86c413796207e4ca61d92fea6ae586d2420.jpg) \n\nExtended Data Fig. 3 | See next page for caption. \n\nExtended Data Fig. 3 | Anisotropic defect engineering for truncated octahedral $\\mathbf{Cu}_{2}\\mathbf{0}$ particles. a–c, Ensemble-averaged C $\\mathsf{u}2\\mathsf{p}_{3/2}\\mathsf{X P S}$ (a), Cu LMM Auger (b), and deconvoluted Auger (c) spectra for $\\mathsf{E}\\mathrm{-Cu}_{2}\\mathsf{O}_{\\iota}$ EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ and H- $\\mathtt{C u}_{2}0$ particles. The Cu $2p_{3/2}$ peaks were fitted with the two components centred at approximately 932.4 and $933.6\\mathrm{eV},$ which correspond to $\\mathtt{C u}_{2}0$ and $\\mathtt{V_{C u}}$ species, respectively53. The Cu LMM Auger peaks were fitted with two main peaks located at $570.0\\mathrm{eV}(\\mathrm{Cu}_{2}\\mathrm{O})$ and in the range of $568.2\\substack{-568.8\\mathrm{eV}}$ (an overlap of the ${\\mathsf{C}}{\\mathsf{u}}^{\\mathrm{{0}}}$ and ${\\mathsf{C}}{\\mathsf{u}}^{2+}$ peaks), and three peaks at 573.1, 567.1, and $565.2\\mathrm{eV}$ indicating different transitions states. The component in the the range o $568.2\\mathrm{-}568.8\\mathrm{eV}$ was further fitted with two peaks corresponding to $\\mathrm{Cu}^{0}(568.2\\mathrm{eV})$ and ${\\mathsf{C u}}^{2+}$ $(568.8\\mathrm{eV})$ . The contributions of ${\\bf{C u}}^{0}$ and ${\\mathsf{C u}}^{2+}$ increase and decrease after switching from E- ${\\bf C u}_{2}0$ to ${\\mathsf{H}}{\\cdot}{\\mathsf{C}}{\\mathsf{u}}_{2}{\\mathsf{O}}$ , respectively, indicating increased $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}})$ defects and decreased $\\mathtt{V_{C u}}$ defects from E- ${\\tt C u}_{2}0$ to $\\mathsf{H}{\\cdot}\\mathsf{C u}_{2}\\mathsf{O}$ . d, Confocal Raman spectra of {001} and {111} facets of EH- $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}$ particles with Raman peaks assigned based on previous reports54. Inset, optical image of EH- ${\\mathsf{C u}}_{2}\\mathbf{O}$ particles. The Raman peak intensity was normalized to that of 2Eu phonon mode at Raman shift of $217\\mathrm{cm^{-1}}$ . The 2Eu phonon mode is intrinsic to ${\\tt C u}_{2}0$ crystals owing to the strong coupling to yellow excitation and hence can be used as a ref. 55. The T1u (TO) phonon mode at Raman shift of $124\\mathrm{cm^{\\cdot1}}$ is Raman inactive for the perfect ${\\tt C u}_{2}0$ crystal but can be observed in the presence of $\\mathbf{\\dot{V}}_{\\mathbf{Cu}}$ defects, and therefore the T1u (TO) phonon mode is related to the presence of $\\mathsf{v}_{\\mathtt{c u}}$ defects54. e, Normalized Raman spectra of {001} and {111} facets of E- $\\mathtt{C u}_{2}0$ , EH- $\\mathsf{C u}_{2}\\mathbf{O}_{i}$ and H- $\\mathtt{C u}_{2}0$ particles. The normalized T1u (TO) Raman peak intensity of each facet was extracted to denote the facet-dependent $\\mathtt{V_{C u}}$ density and was correlated to the facet-dependent SPV signals in Fig. 1g. f, Correlations between normalized ${\\sf T}_{\\mathrm{1u}}$ (TO) Raman peak intensity and defect density determined by X-ray spectroscopy. The blue and red data points were obtained from cubic $\\mathtt{C u}_{2}0$ particles with surface defects varying from $\\mathsf{V}_{\\mathsf{C u}}$ to $(\\mathsf{H}-\\mathsf{V}_{\\mathsf{C u}})$ based on data from the Ref. 18. The green data points were collected from the {001} and {111} facets of EH- $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}$ particles with Raman peak intensity shown in d and $\\mathtt{V_{C u}}$ density determined by micro-area XPS. The $\\mathtt{V_{C u}}$ density (square points) was calculated by the ratio of the peak areas of $\\mathtt{V_{C u}}$ and total Cu $2{\\mathsf{p}}_{3/2}$ peak areas of the in XPS spectra. The net defect density (circle points) was \n\ncalculated by the ratio of the difference between the areas of the Auger Cu LMM peaks related to $(\\mathsf{H}-\\mathsf{V}_{\\mathsf{C u}})$ and $\\mathtt{V_{C u}}$ and the area of the total Auger Cu LMM peak. The blue line is the linear fit of the blue points. The good linear relation, which is also consistent for the data of EH- $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}_{\\cdot}$ indicates the reliability of using $\\mathsf{V}_{\\mathtt{C u}}$ - related Raman peak intensity to denote $\\mathtt{V_{C u}}$ density. The red points indicate that the decrease of $\\ensuremath{\\mathsf{V}}_{\\mathrm{cu}}$ density corresponds to the increase of $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ density and their densities are roughly the same at $\\mathtt{V_{C u}}$ -related Raman peak intensity of \\~0.7. g, XPEEM image of a single EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ particle with photoelectron signals collected and integrated in the $\\mathtt{C u2p}_{3/2}$ range. Inset, PEEM image of the same particle. h, i, Facet-dependent Cu ${2}\\mathsf{p}_{3/2}(\\mathbf{h})$ and O 1s (i) XPS profiles recorded from the {001} and {111} facets of the EH- ${\\bf{C u}}_{2}{\\bf{O}}$ particle in g. The fitting procedure for $\\mathrm{Cu}2\\mathsf{p}_{3/2}$ is similar with that in a. The ratios between the peak areas of $\\mathbf{\\dot{V}}_{\\mathbf{Cu}}$ and total peak areas obtained for the {001} and {111} facets are $6.7\\%$ and $1.7\\%$ , respectively, confirming a higher $\\mathtt{V_{C u}}$ density on the {001} facet. The peaks of O 1s were freely fitted with three components that included the main peak at 530.6 eV corresponding to O in $\\mathtt{C u}_{2}0$ , a higher binding energy peak at 531.4 eV corresponding to O–H bond56, and a lower binding energy peak at $529.8\\mathrm{eV}$ corresponding to unsaturated $0^{57}$ . These results confirm selective incorporation of H atoms into the {111} facet to form O–H bonds. j, XPEEM image of EH- $\\mathtt{C u}_{2}0$ particles collected in the Cu LMM Auger spectral range. k, Facet-dependent Cu LMM Auger spectra recorded from the EH- ${\\tt C u}_{2}0$ particles in j. Constrained fitting was performed for the three peaks at 916.5 eV $\\left(\\mathbf{Cu}_{2}\\mathbf{O}\\right)$ , 918.4 eV $(\\mathsf{C u}^{0})$ , and $917.8\\mathrm{eV}(\\mathrm{V}_{\\mathrm{Cu}})$ , and three other peaks at 913.4, 919.4, and 921.3 eV that indicate different transitions. The spectra demonstrate that apparent ${\\mathsf{C u}}^{0}$ species, assigned to $(\\mathsf{H}\\cdot\\mathsf{V}_{\\mathsf{C u}})$ defects, were selectively formed at {111} facets. l, X-ray absorption microscopy image of EH- ${\\bf C u}_{2}0$ particles. The X-ray absorption signals were obtained for the $\\mathsf{C u L}_{2,3}$ edges. m, Facetdependent $\\mathsf{C u L}_{2,3}$ edge X-ray absorption spectra recorded for the {001} and {111} facets of the EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ particles in m. The spectra are normalized to the same intensity at $963.0\\mathrm{eV}.$ The white line intensity $(933.5\\mathrm{eV})$ of the {001} facets is larger than that of the {111} facets, confirming the higher oxidation state of Cu on the {001} facets58. \n\n# Article \n\n![](images/4ca2182847abc51f3a12cc84a9e428e151b015a536d2a1b123343927fe77f4ce.jpg) \nExtended Data Fig. 4 | Anisotropic charge transfer in EH- $\\mathbf{Cu}_{2}\\mathbf{0}$ particles. a, Reproducibility of SPVM images for EH- $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}$ particles. b, AFM images of $\\mathsf{E H-C u}_{2}0$ particles used for modulation measurements. Scale bars, $2\\upmu\\mathrm{m}$ . c, SPV signals obtained for the {111} and {001} facets of EH- $\\mathbf{\\cdot}\\mathbf{Cu}_{2}\\mathbf{O}$ particles in b under 6-Hz chopped light illumination. d, I–V curves obtained by C-AFM for the {111} \nand {001} facets of EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ particles in b in the dark (grey line) and under the $450\\cdot\\mathrm{nm}$ light illumination (blue and red lines). e, SPV values obtained at different light powers for the {111} and {001} facets of EH- ${\\bf C u}_{2}{\\bf O}$ particles in b. The error bars are based on the electronic noise of the modulated SPV signals via an external lock-in amplifier. \n\n![](images/96cfbf500f4dd670cef172d855e32475a4ca8d7a93dd9ecaaaec4f21ca0e531c.jpg) \n\nExtended Data Fig. 5 | TR-PEEM studies of EH- $\\mathbf{Cu}_{2}\\mathbf{0}$ particles. a, b, Schematic illustration of the energy path of electrons with negative (a) and positive (b) pump–probe delay times. VAC, CB, CBM, VCusplit, $\\mathsf{V}_{\\mathsf{C u}},$ VBM, and VB denote the vacuum energy level (VAC), conduction band (CB), conduction band minimum (CBM), energy level of split copper vacancy $(\\mathsf{V}_{\\mathsf{C u}}^{\\mathsf{s p l i t}})$ , energy level of a simple copper vacancy $(\\mathsf{V}_{\\mathsf{C u}})$ , valence band maximum (VBM), and valence band (VB), respectively. The vacuum energy level is set to 0 eV. The CBM energy level is determined from Ref. 59. The energy levels of $\\mathbf{\\ddot{V}}_{\\mathbf{\\Cu}}$ and $\\mathsf{V}_{\\mathsf{C u}}{}^{\\mathsf{s p l i t}}$ located at 0.2– $0.3\\mathrm{eV}$ and $0.4\\substack{-0.5\\mathrm{eV}}$ above VBM, respectively, and no donor levels exist near CBM in $\\mathbf{Cu}_{2}\\mathbf{O}^{60}$ . c, Band structure of $\\mathrm{Cu}_{2}\\mathrm{O}$ calculated by the HSE06 hybrid functional, which indicates that photogenerated carriers can only be excited into the Γ-valley and that the energy of photogenerated carriers in the Γ-valley is lower than other valleys by \\~1 eV; therefore, intervalley scattering cannot occur. The curvity of CBM is approximately six times larger than that of VBM at the Γ point, indicating that the excitation energy of $2.4\\mathrm{eV}$ mostly generates hot electrons while hot holes can be neglected. d, PEEM image of a EH– ${\\tt C u}_{2}0$ particle with different regions marked along the light irradiation direction. Inset, PEEM image of the same particle with a different intensity scale bar featuring a bright ring at the particle–substrate interface (region 1) due to electric field distortion effect and a dark tail on the right side of the particle due to shadowing effect. e, Energy-integrated TR-PEEM signals for different regions marked in d. f, PEEM image of other EH– ${\\bf C u}_{2}0$ particles. \n\ng, Energy-integrated TR-PEEM signals for different regions marked in d and f. The photoelectron intensities in e and g were obtained by subtracting the intensities at negative delay times and were divided by the collected area for quantitative comparison. Comparing TR-PEEM signals collected from different regions of {111} facets, we found that electric field distortion affected TR-PEEM signals at regions in the vicinity of substrate and shadowing effect affected TR-PEEM signals at shadow facets. These effects had a small impact on TR-PEEM signals at lateral facets and had a negligible impact for top facets. Therefore, we conducted TR-PEEM study on {001} and {111} facets parallel to the substrate. No field enhancement effects were observed at the inter-facet edge region (region 4). h, i, Dynamics of the normalized energy-integrated photoelectron signals at 1 ns (h) and within the initial 2 ps (i) with different excitation carrier densities. j, Fitting of decay dynamics at different excitation carrier densities via the single-component exponential decay function. k, Log/log plots of the decay time constant versus the excitation carrier density. At the initial times, the dynamics is independent on the carrier density, excluding the recombination and Auger processes on this timescale. At longer times, the dependence of the decay dynamics on the excitation carrier density is of the order (n) of \\~0.8, indicating the simultaneous occurrence of the radiation recombination $(\\mathsf{n}=\\mathsf{1})$ and trapping $(\\boldsymbol{\\mathsf{n}}=\\boldsymbol{0})$ ) processes. The Auger process $(\\mathsf{n}=2)$ is negligible owing to the relatively low carrier density $(10^{17}\\mathrm{cm}^{-3})$ . \n\n# Article \n\n![](images/5272fcbd4e01787dd7be5f8ccc664dcf8ce5b073907e322e9894a13b6e1a3889.jpg) \n\nExtended Data Fig. 6 | Inter-facet charge transfer mechanism for EH- $\\mathbf{Cu_{2}O}$ particles. a, Potential distribution across the interface between {001} and {111} facets. The KPFM image is mapped at a tip lift height of $10\\mathsf{n m}$ to minimize cross-talk effects. b, Fitting of the potential distribution and strength of the inter-facet built-in electric field. The fitting process (see details in Methods) resulted in doping density $\\mathrm{(N_{d})}$ on the order of $\\mathsf{-10^{14}c m^{-3}}$ , electric field strength of 1.7 kV/cm, and width of $680\\mathrm{nm}$ . c, Band diagram for the interface between the {001} and {111} facets based on the data in b. d, Schematic showing the \n\nphoto-induced inter-facet charge transfer in the drift regime. e,f, Evolution of SPV signals with time studied using the conventional drift–diffusion model at different electron temperatures (e) and at different mobilities (f) (see Methods for details). g, h, Model of the inter-facet electron transfer in the quasi-ballistic regime (see Methods for details). i, Group velocity of electrons (blue points) in the conduction band (Inset) along the $\\scriptstyle\\Gamma\\to\\mathbf{R}$ direction determined by DFT calculations using the HSE functional (see Methods). \n\n![](images/b975a9e70c4f354d9c14c769725e165112e41dd5f964dde9495a0be45908a8a1.jpg) \n\nExtended Data Fig. 7 | See next page for caption. \n\n# Article \n\nExtended Data Fig. 7 | Energy-resolved TR-PEEM measurements of hot electron relaxation. a,b, Pseudocolour images of the energy-resolved and time-resolved photoelectron signals obtained for {001} (a) and {111} (b) facets. The signals in high-energy and low-energy regions were integrated to show the dynamics of hot electrons and electrons near the CBM. c, d, Fitting the energyresolved photoelectron signals with a hot Fermi–Dirac distribution and density of states in the conduction band for the {001} (c) and {111} (d) facets at different decay times as labelled (see Methods for fitting details). The grey points denote the experimental data, and the solid lines are the fitting curves. e, Decays of the electron temperature observed for the {001} and {111} facets. The electron temperatures are extracted from the fitting parameters of the plots in c and d. Error bars represent the standard deviation from the fits in c and d. The decays were fitted with a one-phase exponential association equation with plateau before exponential begins. The fitting results show that the decays begin at 0.05 ps with a time constant of 0.17 ps for the {001} facets and begin at 0.02 ps with a time constant of 0.1 ps for the {111} facets. The faster decay for the {111} facets is owing to hot electron transfer from the {111} to {001} facets, which occurs at delay time of \\~0.05 ps. During the inter-facet electron transfer, the electron temperature displays no decay for the {001} facets, indicating that the transferred electrons are non-thermal in the energy space. f, Electron temperature decay observed at longer times with a bi-exponential fit for the {001} facets. The temperature decay follows the bi-exponential model with time constants of 0.20 and 2.96 ps. g,h, Decays of the high-energy electrons \n\nobtained at different excitation carrier densities for the {001} (g) and {111} (h) facets. The decay traces were fitted with Equations (4) and (5) in Methods for the {111} and {001} facets, respectively. All photoelectron intensities were normalized to the intensity at 0 ps. The initial growth of photoelectron intensity for the {001} facets was affected by the excitation carrier density, which displayed a larger increment at a lower excitation density. This effect can be attributed to the slight energy relaxation induced by electron–electron scattering at high excitation density. The excitation carrier density produced little effect on the decay dynamics for the two facets. The decay time constant varied slightly in the range of 0.15–0.18 ps for the {001} facets and in the range of $0.05\\substack{-0.06}$ ps for the {111} facets. i, Physical picture of electron relaxation process that includes electron–electron interactions leading to the formation of a hot electron ensemble before 0.1 ps, electron–optical phonon scattering at 0.2 ps, and electron–acoustic phonon scattering at 2.96 ps. The electron– phonon scattering follows a two-temperature model and leads to energy relaxation23. j, k, Energy distribution spectra of the photoemitted electrons obtained for the {001} ( j) and {111} facets (k) of EH- $\\mathtt{C u}_{2}0$ particles at different delay times. The delay times span from $^{-47}$ ps to approximately 1700 ps from bottom to top. The characteristic time delays are labelled. The peak positions of the photoelectron spectra at delay times from $^{-47}$ to −1 ps are averaged; subsequently, the averaged peak position is set as the benchmark to evaluate the photo-induced shifts of peak position, which are extracted as SPV signals. \n\n![](images/f82342fde5900b577f7b1778cbfc359896c98995b6ff0ac33d3dde30beb35d19.jpg) \n\nExtended Data Fig. 8 | Effects of the bulk-to-surface charge transfer and measurement conditions. a, PEEM image of cubic $\\mathtt{C u}_{2}0$ particles. b, TR-PEEM signals of the {001} facets of cubic $\\mathtt{C u}_{2}0$ and EH- $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}.$ c, Pseudocolour image of the energy-resolved and time-resolved photoelectron signals obtained for the {001} facets of the cubic $\\mathtt{C u}_{2}0$ particles in a. d, Transient SPV signals of the {001} facets of cubic $\\mathtt{C u}_{2}0$ and EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ particles. The SPV signals of cubic $\\mathtt{C u}_{2}0$ were extracted from the peak shifts of the time-resolved photoelectron spectra in c. The delay time in the x axis was shifted by 1 ps to show the SPV evolution on the logarithmic timescale. The SPV signals of cubic ${\\tt C u}_{2}0$ solely originaate from the bulk-to-surface electron transfer owing to the existence of a p-type surface SCR, while the SPV signals of EH- ${\\tt C u}_{2}0$ result from a combination of the bulk-to-surface electron transfer and inter-facet electron transfer. Therefore, a comparison of SPV signals obtained for cubic $\\mathtt{C u}_{2}0$ and EH- $\\mathtt{C u}_{2}0$ can help decouple bulk-to-surface and inter-facet electron transfer processes. The bulk-to-surface electron transfer yields a maximum SPV at \\~10 ps, and the contribution to SPV signals on the subpicosecond scale is very small. \n\nThe decoupled data are presented in Fig. 2e. e, XPEEM image of EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ particles. f–i, XPS profiles obtained for the {001} (f,g) and {111} (h,i) facets of the EH- $\\mathtt{C u}_{2}0$ (marked in e) under the dark and 2.4-eV excitation conditions. Single peak fits were performed to quantify the photo-induced peak shifts extracted as SPV signals in ultrahigh vacuum (UHV). j, Comparison of the steady-state SPV signals of EH- ${\\tt C u}_{2}0$ particles obtained in UHV $({\\bf-10}^{-8}{\\bf P a})$ and air from the photo-assisted XPS and SPVM data, respectively. It shows that measurement conditions affect the SPV signals very little, which indicates that these SPV signals are induced by the charge transfer within $\\mathtt{C u}_{2}0$ particles and the effects of absorbed molecular on the particle surface can be eliminated. k, SPV spectra of EH- $\\mathtt{C u}_{2}0$ particles recorded in different environments using the fixed-capacitor approach. The atmospheric control is enabled by using a home-made chamber with a vacuum background of $\\mathbf{10^{-3}{-}10^{-4}P}\\mathbf{;}$ a. Above data indicate that different measurement conditions produce little effects on SPV, allowing the combination of different approaches to obtain holistic SPV signals. \n\n# Article \n\n![](images/47287c35476d65945905e5176110580f3686e46c1f5323555de384a70d199743.jpg) \n\nExtended Data Fig. 9 | Facet-dependent absorption and schematic illustration of the charge transfer in EH– $\\mathbf{Cu}_{2}\\mathbf{0}$ particles. a, Diffuse reflectance spectra of cubic ${\\bf C u}_{2}{\\bf O}$ , EH- ${\\tt C u}_{2}0$ , and octahedral $\\mathsf{C u}_{2}\\mathsf{O}.$ . b, c, Tauc plots obtained for cubic and octahedral ${\\bf C u}_{2}{\\bf O}$ particles in the direct transition (b) and indirect transition (c) regimes. They show that the absorption of {001} facets reflects indirect transitions with a bandgap $(\\mathsf{E}_{\\mathrm{g}})$ of 1.91 eV and that the absorption of {111} facets reflects direct transitions with $\\mathsf{E}_{\\mathrm{g}}$ of $2.05\\mathrm{eV}.$ . d, Facet-dependent SPV spectra for EH- $\\mathbf{c}\\mathbf{u}_{2}\\mathbf{O}$ and spectral-dependent absorption length of $\\mathrm{Cu}_{2}\\mathrm{O}$ (reported by Malerba et al.37). As positive SPV signals are related to $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{C u}})$ -induced trapping, they can reflect the depth distribution of $(\\mathsf{H}-\\mathsf{V}_{\\mathsf{C u}})$ ) defects. The SPV signals obtained for the {111} facet reach a maximum at an excitation wavelength below $480\\mathrm{nm}$ corresponding to an absorption length of $60\\mathsf{n m}$ . These results indicate that $(\\mathsf{H}{\\cdot}\\mathsf{V}_{\\mathsf{c u}})$ defects are primarily distributed within $60\\mathrm{nm}$ in the near-surface regions on the {111} facet. e, Tauc plot of direct transitions for EH– $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}$ The onset of the Tauc plots is in good agreement with the SPV spectrum of {111} facet; hence, the absorption edge of the {111} facet of EH- $\\mathbf{Cu}_{2}\\mathbf{O}$ is equal to $2.04\\mathrm{eV.f,}$ Tauc plots of indirect transitions for EH- $\\mathbf{\\cdot}\\mathbf{Cu}_{2}\\mathbf{O}$ . The onset of the Tauc plots agrees well with the SPV spectrum of {001} facet; hence, the absorption edge of the {001} facet of EH- $\\mathbf{\\cdot}\\mathbf{Cu}_{2}\\mathbf{O}$ is equal to 1.91 eV. g, Schematic illustration of the charge separation on the {001} and {111} facets of EH- ${\\tt C u}_{2}0$ with the sub-bandgap excitation. h, Schematic illustration of the holistic charge transfer processes occurring in EH- $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}$ . \n\n![](images/86745b371efd182cdc865df7a0c283177712495875a8df4241e2693d34bd8b9e.jpg) \nTime (h) \n\nExtended Data Fig. 10 | Cocatalyst deposition and photocatalytic performance. a–c, SEM (a), AFM (b), and KPFM (c) images for EH- ${\\bf C u}_{2}{\\bf O}$ particles with photodeposition of Au $(\\mathrm{EH-Cu}_{2}\\mathrm{O}/\\mathrm{Au})$ . Scale bars, $2\\upmu\\mathrm{m}$ . d, CPD distribution along the line in c. The data show the local increase in the surface potential at Au sites, demonstrating an enhancement of the built-in electric field. e, f, SEM images for E $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}$ (e) and H- $\\mathtt{C u}_{2}0$ (f) particles photodeposited with Au. They are denoted as E ${\\bf\\nabla}\\cdot{\\bf C u}_{2}{\\bf O}/{\\bf A u}$ and $\\scriptstyle\\mathsf{H-C u}_{2}\\mathbf{O}/\\mathbf{Au}$ , respectively. g, SPVM image of an ${\\mathsf{H}}{\\cdot}{\\mathsf{C u}}_{2}{\\mathsf{O}}/{\\mathsf{A u}}$ particle. Inset, the corresponding AFM image. h, SPV distributions across the {111} and {001} facets obtained before and after the Au deposition on ${\\bf{H}}{\\cdot}{\\bf{C}}{\\bf{u}}_{2}0$ particles. i, Determination of the driving force of the anisotropic charge transfer in ${\\bf C u}_{2}0$ photocatalytic particles by calculating the differences of SPV signals between different facets. j, Time course of photocatalytic ${\\sf H}_{2}$ evolution for different $\\mathtt{C u}_{2}0$ photocatalyst particles. The lines represent linear fits for determining the rates of $\\mathbf{\\ddot{H}}_{2}$ generation. The association between anisotropic SPV signals and photocatalytic activities can be understood as follows. A photocatalytic process requires photogenerated electrons and holes at surface to drive photooxidation and photoreduction reactions simultaneously. Therefore, effective charge separation refers to creating photogenerated electrons and holes that are localized on the spatially separated surface of the photocatalyst. For cubic $\\mathtt{C u}_{2}0$ , the SPV vectors of different facets are cancelled out due to symmetry considerations and the SPV difference equals to 0, which means no driving force for effective charge separation. In this case, photogenerated electrons are distributed at surface whereas holes are confined in the bulk by the symmetric surface built-in electric field, rendering the photocatalytic reaction inactive. Facet engineering yields an inter-facet built-in electric field for effective electron–hole separation between different facets, resulting in the observed anisotropic SPV signals and a detectable photocatalytic reaction rate ( $\\mathsf{E}\\cdot\\mathsf{C u}_{2}\\mathsf{O})$ . However, the SPV vectors of different facets are partially offset, only resulting in a small driving force. Nevertheless, the conjoint facet engineering and defect engineering enable effective accumulations of electrons and holes at different facets via a synergistic effect of inter-facet built-in electric field and anisotropic trapping. Consequently, the SPV vectors are aligned, leading to significant enhancements of anisotropic SPV signals and photocatalytic activity for EH– $\\cdot\\mathbf{Cu}_{2}\\mathbf{O}.$ . A further selective cocatalyst assembly enhances both the positive SPV signals of {111} facets and negative SPV signals of {001} facets by \\~ $50\\%$ , and therefore facilitates both photogenerated electrons and holes accumulations at surfaces, further improving the photocatalytic activity by $50\\%$ for $\\mathsf{E H-C u}_{2}\\mathsf{O/A u}$ . " + }, + { + "id": "10.1038_s41467-022-30821-7", + "DOI": "10.1038/s41467-022-30821-7", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-30821-7", + "Relative Dir Path": "mds/10.1038_s41467-022-30821-7", + "Article Title": "Giant energy-storage density with ultrahigh efficiency in lead-free relaxors via high-entropy design", + "Authors": "Chen, L; Deng, SQ; Liu, H; Wu, J; Qi, H; Chen, J", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Next-generation advanced high/pulsed power capacitors rely heavily on dielectric ceramics with high energy storage performance. However, thus far, the huge challenge of realizing ultrahigh recoverable energy storage density (W-rec) accompanied by ultrahigh efficiency (eta) still existed and has become a key bottleneck restricting the development of dielectric materials in cutting-edge energy storage applications. Here, we propose a high-entropy strategy to design local polymorphic distortion including rhombohedral-orthorhombic-tetragonal-cubic multiphase nulloclusters and random oxygen octahedral tilt, resulting inultra small polar nulloregions, an enhanced breakdown electric field, and delayed polarization saturation. A giant W-rec similar to 10.06 J cm(-3) is realized in lead-free relaxor ferroelectrics, especially with an ultrahigh eta similar to 90.8%, showing breakthrough progress in the comprehensive energy storage performance for lead-free bulk ceramics. This work opens up an effective avenue to design dielectric materials with ultrahigh comprehensive energy storage performance to meet the demanding requirements of advanced energy storage applications.", + "Times Cited, WoS Core": 318, + "Times Cited, All Databases": 326, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000805202900032", + "Markdown": "# Giant energy-storage density with ultrahigh efficiency in lead-free relaxors via high-entropy design \n\nLiang Chen1,2,4, Shiqing Deng1,3,4, Hui Liu1,3, Jie Wu3, He Qi 1,2✉ & Jun Chen 1 ,2✉ \n\nNext-generation advanced high/pulsed power capacitors rely heavily on dielectric ceramics with high energy storage performance. However, thus far, the huge challenge of realizing ultrahigh recoverable energy storage density ${(W_{\\mathrm{rec}})}$ accompanied by ultrahigh efficiency $(\\eta)$ still existed and has become a key bottleneck restricting the development of dielectric materials in cutting-edge energy storage applications. Here, we propose a high-entropy strategy to design “local polymorphic distortion” including rhombohedral-orthorhombictetragonal-cubic multiphase nanoclusters and random oxygen octahedral tilt, resulting in ultrasmall polar nanoregions, an enhanced breakdown electric field, and delayed polarization saturation. A giant $W_{\\mathrm{rec}}{\\sim}10.06\\mathrm{J}\\mathsf{c m}^{-3}$ is realized in lead-free relaxor ferroelectrics, especially with an ultrahigh $\\eta\\sim90.8\\%$ , showing breakthrough progress in the comprehensive energy storage performance for lead-free bulk ceramics. This work opens up an effective avenue to design dielectric materials with ultrahigh comprehensive energy storage performance to meet the demanding requirements of advanced energy storage applications. \n\nielectric capacitors, as the core component of high/pulsed power electronic devices, are widely used in numerous fields such as hybrid electrical vehicles, microwave communications and distributed power systems1–3. This is because of the high-power density and ultrafast charge/discharge rates in dielectric capacitors, which store energy through the displacement of bound charged elements rather than chemical reactions as in batteries and solid oxide fuel cells4,5. However, the low recoverable energy storage density ( $W_{\\mathrm{rec}}$ generally ${<}4\\thinspace\\mathrm{J}\\thinspace\\mathrm{cm}^{-3};$ ) greatly limits the application fields of ceramic capacitors and their development toward device miniaturization and intelligence. Together with environmental protection, the design of highperformance lead-free energy storage capacitors has enormous potential in the global market. \n\nA breakthrough in $W_{\\mathrm{rec}}$ to $4\\ensuremath{\\mathrm{J}}\\ensuremath{\\mathrm{cm}}^{-3}$ was realized in $\\mathrm{AgNb}{\\mathrm{O}}_{3}$ (AN)-based ceramics by controlling the field-driven antiferroelectricto-ferroelectric phase transition behavior6. Further breakthroughs in energy storage properties were also achieved in other representative lead-free ceramic systems, such as the excellent $W_{\\mathrm{rec}}$ values of 7.4, 8.2, and $12.2\\:\\mathrm{J}\\mathrm{cm}^{-3}$ in $\\left(\\mathrm{K,Na}\\right)\\mathrm{Nb}\\mathrm{O}_{3}$ (KNN), ${\\mathrm{BiFeO}}_{3}$ (BF), and ${\\mathrm{NaNb}}{\\mathrm{O}}_{3}$ (NN)-based systems, respectively7–9. However, their poor energy storage efficiency $(\\eta)$ below $80\\%$ leads to high loss and heat generation after multiple runs, which causes the capacitors to undergo thermal breakdown and fail to work normally. Improving $\\eta$ and reducing heat generation can further increase the service life of the devices and save costs. Especially, in the context of energy saving and emission reduction, achieving high $\\eta$ on the basis of ultrahigh $W_{\\mathrm{rec}}$ is necessary and significant, although there are great challenges10,11. To realize a super high $\\eta,$ numerous strategies, such as nanodomain/ domain engineering3,12, superparaelectric state1,13, defect engineering14,15, enhanced antiferroelectric phase6,16, and enhanced local random field17,18, have been proposed to break the long-range ferroelectric order or decrease the remnant polarization $(P_{\\mathrm{r}})$ . In addition to domain structure adjustment, electric field control, such as narrowing the gap between $E_{\\mathrm{{F}}}$ and $E_{\\mathrm{A}},$ has also become an important strategy to improve efficiency in antiferroelectrics or relaxor antiferroelectrics. Recently, high $W_{\\mathrm{rec}}$ and high $\\eta$ have been reported in some $\\mathrm{Bi}_{0.5}\\mathrm{Na}_{0.5}\\mathrm{TiO}_{3}$ (BNT)-based lead-free ceramics19–21. However, the great challenge of realizing ultrahigh energy storage density $(W_{\\mathrm{rec}}\\ \\breve{\\geq}10\\ \\mathrm{J}\\mathrm{cm}^{-3})$ with simultaneous ultrahigh efficiency $(\\eta\\ge90\\%)$ still exists in lead-free ceramics and has not been overcome. \n\nAccording to the theory of electrostatic energy storage, highperformance capacitors should have a large breakdown electric field $E_{\\mathrm{b}},$ large $\\Delta\\bar{P}\\left(P_{\\operatorname*{max}}-P_{\\mathrm{r}}\\right)$ , delayed polarization saturation and a temperature/frequency-insensitive dielectric response. To realize these electrical factors at the same time, perovskites should be designed to show the following structural features: dense microstructure, fine grains, large polarizability under an electric field, fast response back to the nonpolar state, large barrier such as a local random field delaying the formation of a textured ferroelectric state, highly dynamic structure with a hysteresis-free response at the test frequency and temperature-insensitive structure. Therefore, breaking through the bottleneck of energy storage capacitors is a great challenge. \n\nIn this work, an effective high-entropy strategy is proposed to design “local polymorphic distortion” to enhance the comprehensive energy storage performance to break the status quo, which has usually been used for alloys22,23, oxides24,25, and metal carbides26 to improve mechanical properties. As shown in Fig. 1, numerous ions $\\bar{(}\\mathrm{Li^{+}}$ , $\\mathrm{Ba}^{2+}$ , $\\mathrm{Bi}^{3+}$ , ${\\dot{\\operatorname{Sc}}}^{3+}$ , $\\mathrm{Hf^{4+}}$ , $\\mathrm{Zr^{4+}}$ , $\\mathrm{Ta}^{5+}$ , $\\mathrm{Sb}^{5+}$ ) with different ionic radii and valence states are introduced into $\\mathrm{K}_{0.2}\\mathrm{Na}_{0.8}\\mathrm{Nb}{\\mathrm{O}}_{3}$ lattices to enhance the random field, including the stress and electric field simultaneously. According to the phase boundary regulation of KNN-based ceramics by previous studies27–31, these ions are also considered as additives used to tailor $T_{\\mathrm{R-O}},\\:T_{\\mathrm{O-T}}$ and $T_{\\mathrm{T-C}}$ to form rhombohedral-orthorhombictetragonal-cubic (R-O-T-C) multiphase nanoclusters coexisting at the local scale. Furthermore, different types of oxygen octahedral distortions exist in different nanophases, which would introduce randomly distributed oxygen octahedral tilt, further delaying polarization saturation. The local polymorphic distortion can effectively reduce the size of polar nanoregions (PNRs) and further decrease the loss when working under a strong electric field, providing great potential to improve $\\eta$ and $W_{\\mathrm{rec}}$ at the same time. The mechanical performance could also be optimized by the high-entropy strategy to meet the requirements of practical applications. Encouragingly, a giant $W_{\\mathrm{rec}}\\cdot\\mathrm{\\sim}10.06\\mathrm{J}\\mathrm{cm}^{-3}$ with an ultrahigh $\\eta\\sim90.8\\%$ is realized in lead-free relaxors, which is the optimal comprehensive energy storage performance reported to date for lead-free bulk ceramics. This proves that the highentropy strategy can be used as a guide to develop new available energy storage materials with ultrahigh comprehensive properties. \n\n# Results \n\nR-O-T-C multiphase nanoclusters coexistence. After the highentropy strategy and preparation process optimization, movement of the polymorphic phase transition temperature, introduction of dielectric relaxation behavior and decrease of the dielectric loss can be detected at the same time, as shown in Supplementary Fig. 1. In addition, refined grains and compact microstructures with few pores and dense grain boundary structures can also be found according to the scanning electron microscopy (SEM) and transmission electron microscopy (TEM) results for the KNN-H ceramic in Supplementary Figs. 2 and 3. Owing to the strong dielectric relaxation behavior, PNRs revealed as a weak contrast or Moiré fringe structure32 can be observed by HR-TEM along $[100]_{c},$ $[110]_{c},$ and $[111]_{c}$ due to the insufficient resolution. \n\nTo further explore the local structure, atomic-resolution scanning transmission electron microscopy (STEM) is used to analyze the local structure of the PNRs. The polarization vectors from the center B-site cations to the corner A-site cations are exhibited by the yellow arrows. As shown in Fig. 2a, the $\\mathrm{\\DeltaT}$ phase can be clearly confirmed by the arrows with the $[001]_{c}$ direction, according to the 2D Gaussian peak fitting results. The C phase can also be observed by the arrows with almost no polarization magnitude. However, the arrows with the $[011]_{\\mathrm{c}}$ direction could not distinguish the R and O phases because of their similar projections on the $(100)_{c}$ plane. The detailed transformations of polarization vectors from the T to $\\mathrm{R}/\\mathrm{O}$ to C phases are enlarged in Fig. 2b, showing the clear process of a gradual change of polarization. In addition, the magnified image (Fig. 2c) and schematic projection (Fig. 2d) of the unit cell along $[100]_{\\mathrm{c}}$ show the detailed perovskite structure on the atom scale and the relationship between the direction of the arrows and phases (T and $\\mathrm{R}/\\mathrm{O}\\dot{}$ ). To further distinguish the R and O phases, atomicresolution high-angle annular dark-field (HAADF) STEM polarization vector image is performed along $[110]_{c}$ . As shown in Fig. 2e, the arrows with of the $[1-11]_{\\mathfrak{c}}$ and $[1-10]_{\\mathrm{c}}$ directions represent the R and O phases, respectively, and R-O-T-C multiple phases can be obviously observed. The regions with the same polarization direction form PNRs with sizes of ${\\sim}1{-}3\\ \\mathrm{nm}$ , which confirms the formation of R-O-T multiphase PNRs coexisting in the C matrix. The R-O-T-C multiphase nanoclusters coexistence strongly destroys the long-range ferroelectric order, resulting in a smaller size of PNRs. It is widely accepted that high activity and external electric field response speed can be provided by small PNRs, which are responsible for low loss and high thermal breakdown strength. Furthermore, the polarization vectors also gradually transform from the $\\mathrm{\\DeltaT}$ to $\\mathrm{~R~}$ to $\\mathrm{~O~}$ to C phase (Fig. 2f), which reduces the polarization anisotropy and also leads to an easier polarization response to an external electric field, benefiting the energy efficiency33. The magnified image (Fig. 2g) and schematic projection (Fig. 2h) of the unit cell show the perovskite structure in detail and the relationship between the direction of arrows and phases (T, R and O) along $[110]_{\\mathrm{c}}$ . As shown in Fig. 2i, j and Supplementary Fig. 4, the polarization magnitude and polarization angle mappings show an obvious inhomogeneous random distribution state along $[100]_{c}$ and $[110]_{c}$ , demonstrating the existence of a strongly perturbed random field, which should be related to the enhanced random stress and electric field caused by the introduction of numerous ions with different ionic radii and valence states, respectively. \n\n![](images/38f5841c1146e2ce366d8edcd43106381a2fa60bc7092b681cc488b818324a4c.jpg) \nFig. 1 Schematic diagram of high-entropy design strategy for local polymorphic distortion and giant energy storage performance. \n\nRandom oxygen octahedral tilt. In addition to the cation displacement, oxygen octahedral tilt is another important (anti)ferrodistortion. Oxygen octahedral tilt is usually avoided in piezoceramics because it hinders the formation of a textured domain state under an electric field, leading to a large coercive field and poor piezoelectric effects. However, this would be a beneficial factor for designing energy storage capacitors, which would result in delayed polarization saturation. By considering the KNN binary phase diagram drawn by previous researchers, the $\\begin{array}{r}{\\mathbb{R},}\\end{array}$ O and T phases in the $\\mathrm{K}_{0.2}\\mathrm{Na}_{0.8}\\mathrm{Nb}{\\mathrm{O}}_{3}$ ceramic contain oxygen octahedral tilt (R phase with $a^{-}a^{-}a^{-}$ , O phase with $a^{-}b^{+}c^{0}$ , T phase with $a^{0}b^{+}c^{+}$ and $a^{0}a^{0}c^{+}$ , and C phase with $a^{0}a^{0}c^{+}$ and $a^{0}a^{0}{a}^{\\hat{0}}$ ; the $+,-$ and 0 superscripts are Glazer notations for in-phase, anti-phase and no tilt, respectively34). Through high-entropy design, there may be multiple types of oxygen octahedral tilt in KNN-H ceramics, which can be directly reflected in the superlattice diffractions. According to the conclusions by Glazer et al., in-phase and anti-phase oxygen octahedral tilt can be identified by $\\{\\bar{o}o e\\}/2$ and $\\{o o o\\bar{\\}/2$ ( $\\mathit{\\Pi}_{\\left.\\begin{array}{l}{\\cdot}\\\\ {\\cdot}\\end{array}\\right|}$ is odd and $e$ is even) types of superlattice reflections, respectively34. Both $\\{o o e\\}/2$ and $\\{{\\stackrel{.}{o o o}}\\}/2$ superlattice diffractions can be detected in the KNN-H ceramic, as reflected in the synchrotron X-ray diffraction (XRD) and neutron diffraction patterns in Fig. 3a and selected area electron diffraction (SAED) patterns along $[100]_{\\mathrm{c}}$ $[110]_{\\mathrm{c}},$ and $[111]_{\\mathrm{c}}$ in Fig. 3b. However, the local symmetry of PNRs cannot be distinguished by both synchrotron XRD and neutron diffraction patterns owing to the resolution limitation, instead, a pseudocubic phase is usually identified for relaxor ferroelectrics. Therefore, a chaotic local structure with both disordered oxygen octahedral tilt and polarization can be constructed in the KNN-H ceramic, accompanying the movement of the R, T and C phases to the room temperature O phase and the formation of R-O-T-C multiphase nanoclusters, which can be named “local polymorphic distortion”. This conclusion can be directly confirmed by the atomic-resolution annular bright-field (ABF) STEM image along $[100]_{c}$ in Fig. 3c. The deviation of O–O bonds from the $y$ axis is used to estimate the oxygen octahedral tilt. Irregular alternations of clockwise and anticlockwise rotation as well as randomly distributed tilt angles can be seen. From the local structure point of view, the studied KNN-H sample can be described as a “hopeless mess”35. In addition, as shown in Supplementary Fig. 5, the polarization magnitude and angle mappings for the ABF STEM image of the KNN-H ceramic along $[100]_{\\mathrm{c}}$ again prove the inhomogeneous state of the polarization distribution. \n\nEnergy storage performance of KNN-H relaxor ceramics. Ultrahigh comprehensive energy storage performance is necessary for dielectric materials to achieve cutting-edge applications. As shown in Supplementary Fig. 6a, b, the pure KNN ceramics show obvious ferroelectric behavior with poor $W_{\\mathrm{rec}}\\sim0.55\\:\\mathrm{J}\\mathrm{cm}^{-3}$ and $\\eta$ $\\sim54.2\\%$ . After introducing the high-entropy strategy to design local polymorphic distortion, the slim $P–E$ loops of the KNN-H ceramic show particularly low $P_{\\mathrm{r}}$ and polarization hysteresis even under an ultrahigh electric field up to $740\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ . Both the total energy storage density $(W_{\\mathrm{total}})$ and $W_{\\mathrm{rec}}$ show a nearly parabolic growth trend as the applied electric field increases from 40 to $740\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ (Fig. 4a, b). As a result, a giant $W_{\\mathrm{rec}}{\\sim}10.06\\mathrm{J}\\mathrm{cm}^{-3}$ and an ultrahigh $\\eta$ ${\\sim}90.8\\%$ are simultaneously achieved in the KNN-H ceramic, showing a significant promotional effect of the high-entropy strategy on the energy storage performance ( $236\\%$ for $\\begin{array}{r}{E_{\\mathrm{b}},}\\end{array}$ $1729\\%$ for $W_{\\mathrm{rec}},68\\%$ for $\\eta,$ Supplementary Fig. 6c). The enhanced $W_{\\mathrm{rec}}$ and $\\eta$ benefit from the ultrahigh $E_{\\mathrm{b}},$ large $\\Delta P$ and delayed polarization saturation. Most importantly, Fig. 4c shows that only a few ceramics with energy storage efficiency greater than $90\\%$ have broken through the ${\\dot{5}}\\operatorname{Jcm}^{-{\\bar{3}}}$ level, and the $W_{\\mathrm{rec}}$ of the KNN-H ceramic is approximately more than twice that of most lead-free ceramics, indicating great superiority for low energy consumption. According to Fig. 4d and Supplementary Fig. 7, achieving a giant $W_{\\mathrm{rec}}$ beyond $1\\bar{0}\\:\\mathrm{J}\\mathrm{cm}^{-3}$ , especially accompanied by high $\\eta,$ is challenging for ceramics. The relevant references can be found in Supplementary Table 1. Significantly, the ultrahigh comprehensive performance $\\dot{(}W_{\\mathrm{rec}}\\sim10.0\\dot{6}\\mathrm{J}\\mathrm{cm}^{-3}$ with $\\eta\\sim90.8\\%)$ is realized in lead-free bulk ceramics, showing that the bottleneck of ultrahigh energy storage density $(W_{\\mathrm{rec}}\\ge1\\bar{0}\\ \\mathrm{J}\\mathsf{c m}^{-3})$ with ultrahigh efficiency $(\\eta\\ge90\\%)$ simultaneously in lead-free bulk ceramics has been broken through. \n\n![](images/ee3d796992865bb1ee374bc678312d8aa413c1270f037f65927f6b2e6afab988.jpg) \nFig. 2 R-O-T-C multiphase nanoclusters coexistence. a Atomic-resolution HAADF STEM polarization vector image along $[100]_{\\mathrm{c}}$ . b Enlarged image of the marked area (dark red rectangle) in a showing the transition of polarization vectors from T to ${\\sf R}/{\\sf O}$ to C. c Magnified image and d schematic projection of the unit cell along $[100]_{\\mathrm{c}}$ . e Atomic resolution HAADF STEM polarization vector image along $[110]_{\\mathrm{c}}$ . f Enlarged image of the marked area (dark red rectangle) in e showing the transition of polarization vectors from $\\intercal$ to R to $\\textsf{O}$ to C. g Magnified image and h schematic projection of the unit cell along $[110]_{\\mathrm{c}}$ . i Polarization magnitude mapping, and j polarization angle mapping along $[100]_{\\mathrm{c}}$ . \n\nHardness, stability and charge/discharge performance to meet applications. Mechanical properties such as hardness play an important role in practical applications and directly affect the service life and scope of use of energy storage materials36,37. \n\nFigure 5a and Supplementary Fig. 8 show the typical patterns produced by a Vickers diamond indenter with a symmetric rhombic indentation for KNN and KNN-H ceramics. The nonplastic deformation transforms into plastic deformation when the high-entropy design is introduced to KNN-H ceramics. An ultrahigh Vickers hardness $\\left(H_{\\mathrm{v}}\\right)$ of ${\\sim}7.70\\mathrm{GPa}$ is obtained for the KNN-H ceramic, which is higher than that of KNN $({\\sim}3.24\\mathrm{GPa})$ and some representative perovskite ceramics (Fig. 5b and Supplementary Tables 1–3). Furthermore, the KNN-H ceramic exhibits excellent comprehensive performance in terms of energy storage and hardness (Fig. 5c and Supplementary Table 1), which is helpful for achieving actual applications. \n\nExcellent temperature/frequency/cycling stability of the energy storage performance would give the capacitors an enormous application range37. As displayed in Fig. 5d, e, all the P-E loops of the KNN-H sample are slim with nearly unchanged $P_{\\mathrm{max}}$ under various temperatures from 25 to $140^{\\circ}\\mathrm{C}$ and frequencies from 1 to $300\\mathrm{Hz}$ at 400 and $450\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ , respectively. As a result, temperature $W_{\\mathrm{rec}}$ $\\sim3.38\\pm0.20\\mathrm{J}\\mathrm{cm}^{-3}$ , $\\eta$ $\\sim85.8\\pm6.0\\%)$ and frequency $(W_{\\mathrm{rec}}\\sim4.46\\pm0.25\\mathrm{J}\\mathrm{cm}^{-3},$ $\\eta\\sim87.0\\pm4.3\\%)$ -insensitive energy storage properties can be achieved, as shown in Supplementary Fig. 9. In contrast to other reported highperformance lead-free capacitors, the KNN-H ceramic exhibits not only high $W_{\\mathrm{rec}}$ but also a broader usage temperature/frequency range. Moreover, when the electric field is cycled up to $10^{6}$ times, $W_{\\mathrm{rec}}$ and $\\eta$ remain almost unchanged under $400\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ , implying the superior cycling stability (Supplementary Fig. 10). All of these make KNN-H ceramics a good candidate for cutting-edge capacitors. \n\n![](images/4f16f06b8361b2e2d05a430401c5bc8d870d4acd2d5f21ae781e3325881c735a.jpg) \nFig. 3 Disordered oxygen octahedron tilt in KNN-H ceramic. a Synchrotron XRD and neutron diffraction. “†” represents the positions of the superlattice peaks. b SAED patterns along $[100]_{\\scriptscriptstyle{\\mathrm{c}}},$ $[110]_{\\scriptscriptstyle{\\mathrm{c}}},$ and $[111]_{\\mathrm{c}}$ . c Atomic-resolution ABF STEM image along $[100]_{\\mathrm{c}}$ as well as the calculated oxygen octahedral tilt along y axis, blue and red indicate clockwise and anticlockwise tilt, respectively. \n\n![](images/cb927f001b9b282c7eabc73fc04c71ce5660447891368c1adf7b269c1c43795e.jpg) \nFig. 4 Excellent energy storage performance of KNN-H ceramic. a P-E loops measured till the maximum applied electric fields of KNN-H ceramic. b $W_{\\mathrm{total}},$ $W_{\\mathrm{rec}},$ and $\\eta$ as a function of E for KNN-H ceramic. c Comparisons of $W_{\\mathsf{r e c}}$ $(\\eta\\geq90\\%)$ between KNN-H ceramic and other reported lead-free bulk ceramics with $W_{\\mathrm{rec}}\\geq1\\ \\mathrm{J}\\ \\mathsf{c m}^{-3}$ (ST: $\\mathsf{S r T i O}_{3}$ -based, BT: ${\\mathsf{B a T i O}}_{3}$ -based). d Comparisons of $W_{\\mathrm{rec}}$ versus $\\eta$ between KNN-H ceramic and other reported lead-free ceramics (BKT: $\\mathsf{B i}_{0.5}\\mathsf{K}_{0.5}\\mathsf{T i O}_{3}$ -based). \n\nThe charge/discharge performance is another key parameter for measuring the potential for applications11. Figure 5f, $\\mathbf{g}$ shows the underdamped discharge property of the KNN-H ceramic under various electric fields. The stable discharge performance can be proven by the regular underdamped oscillating waveforms, which show ultrahigh current density $\\mathrm{\\bar{(}C_{D})}\\sim2186.1\\mathrm{\\bar{A}c m}^{-2}$ and power density $(P_{\\mathrm{D}})$ ${\\sim}327.9\\mathrm{MW}\\mathrm{cm}^{-1}$ at $300\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ . The overdamped discharge measurements show an ultrahigh discharge energy density $\\left(W_{\\mathrm{D}}\\right)\\ \\sim3.26\\ \\mathrm{J}\\mathrm{cm}^{-3}$ and an ultrafast discharge rate $(t_{0.9})\\sim34\\mathrm{~I~}$ s at $300\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ (Fig. 5h, i). According to Supplementary Table 4, the charge/discharge performance also shows obvious superiority compared to other reported ceramics. Furthermore, as shown in Supplementary Fig. 11, the high charge/discharge performance also exhibits good temperature stability from 20 to $160^{\\circ}\\mathrm{C}$ at $260\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ , making KNN-H ceramics ideal for advanced high/pulsed power electronic devices. \n\n# Discussion \n\nThe KNN-H ceramic exhibits excellent comprehensive energy storage properties with giant $W_{\\mathrm{rec}},$ ultrahigh $\\eta,$ large $H_{\\mathrm{v}},$ good temperature/frequency/cycling stability, and superior charge/ discharge performance, showing good prospects for advanced high/pulsed power applications. The achievement of these excellent properties should be ascribed to the ultrahigh $E_{\\mathrm{b}},$ large $\\Delta P$ , delayed polarization saturation and temperature/frequencystable dielectric response, all of which should originate from the local polymorphic distortion designed by the high-entropy strategy. \n\n![](images/b1db9d1a8bb3ee094964b402eb28d2ac9b4cea36c7feff5bf8a585679f725bb9.jpg) \nFig. 5 The hardness, stability and charge/discharge performance of KNN-H ceramic. a The surface patterns produced by the Vickers diamond indenter. b A comparison of $H_{\\mathrm{v}}$ between KNN-H ceramic and some representative lead-free ceramics. c A Comparison of $W_{\\mathrm{rec}}$ versus $H_{\\mathrm{v}}$ between KNN-H ceramic and other reported lead-free ceramics. d Temperature-dependent P-E loops at $400\\ensuremath{~\\mathsf{k V}~\\mathsf{c m}^{-1}}$ . e Frequency-dependent P-E loops at $450\\ensuremath{~\\mathsf{k V}~\\mathsf{c m}^{-1}}$ . f Underdamped discharge waveforms, and $\\begin{array}{r}{\\pmb{\\mathsf{g}}\\mathsf{C}_{\\mathsf{D}},}\\end{array}$ and $P_{\\mathsf{D}}$ values under different electric fields. h $W_{\\mathsf{D}}$ as a function of time, and i $W_{\\mathsf{D}},$ and $t_{0.9}$ values under different electric fields $(R=100\\Omega)$ ). \n\nFirst, the KNN-H ceramic shows an ultrahigh $\\boldsymbol{E_{\\mathrm{b}}}$ . Pure KNN ceramics show quite poor sintering properties and thus usually have quite low relative density38–40. An activated lattice as well as a decreased sintering temperature would be realized after highentropy design by introducing multiple elements, especially because of the important contributions of Li and Bi in KNNbased ceramics to optimization of the sintering properties. As a result, refined grains with a uniform distribution of elements, increased relative density and decreased dielectric loss can be found, as shown in Supplementary Figs. 1–3 and 12. Depletion space charge layers can be built up at the grain boundaries in ceramics, which can act as barriers for the charge carriers transporting across the grain boundaries, leading to high resistivity of the grain boundaries41. According to the exponential decay relationship of $E_{b}\\propto1/\\sqrt{G_{a}}^{42}$ , the increased content of high-resistance grain boundaries would be helpful for the enhanced $\\phantom{+}E_{\\mathrm{b}}$ . In addition, high-bandgap species (Hf and Ta) \n\nintroduced by high-entropy strategy hinder the transition of electrons from the top of the valence band to the bottom of the conduction band, thereby enhancing the intrinsic $E_{\\mathrm{b}}^{10,37,43}$ . The impedance performance of the studied samples is measured from 300 to $450^{\\circ}\\mathrm{C}$ and in the frequency range of $50~\\mathrm{Hz}$ to $2~\\mathrm{MHz}$ to analyze impedance contributions. As shown in Supplementary Fig. 13, the resistance value at $400^{\\circ}\\mathrm{C}$ of KNN-H is larger than that of KNN, which is mainly related to the increase in the grain boundaries and is responsible for the enhanced $\\phantom{+}E_{\\mathbf{b}}$ . Furthermore, the formation of coexisting R-O-T-C multiphase nanoclusters can effectively reduce the size of PNRs and loss, greatly decreasing the possibility of thermal breakdown. Therefore, the reduction of grain size to submicron $\\left(G_{\\mathrm{a}}\\sim600\\mathrm{nm}\\right)$ with a uniform and dense structure and R-O-T-C multiphase nanoclusters originating from the high-entropy design should mainly contribute to the large enhancement of $\\boldsymbol{E_{\\mathrm{b}}}$ from 220 to $740\\ensuremath{\\mathrm{kV}}\\ensuremath{\\mathrm{cm}}^{-1}$ . \n\nSecond, the KNN-H ceramic has a large $\\Delta P\\ \\sim32.7\\upmu\\mathrm{C}/\\mathrm{cm}^{2}$ , which should be related to both large $P_{\\mathrm{max}}$ and near-zero $P_{\\mathrm{r}}$ . On the one hand, PNRs with different symmetries coexisting in the nonpolar matrix via high-entropy strategy can make the flexible polarization reorientation process with small stress under electric field, leading to the enhanced polarization texture along the direction of the electric field and providing the basic for large $P_{\\mathrm{max}}.$ Moreover, the introduction of Bi by high-entropy strategy would also enhance polarization due to the orbital hybridization between Bi 6s and O ${\\dot{2p}}^{36,37}$ . On the other hand, the large random field in the ergodic relaxor region with coexisting R-O-T-C multiphase nanoclusters in this high-entropy ceramic would drive the longrange ordering ferroelectric state back to the initial macro nonpolar state during unloading, resulting in a near-zero $P_{\\mathrm{r}}$ . \n\nThird, the delayed polarization saturation also plays an important role in the excellent energy storage properties of the studied KNN-H ceramic. Weak correlation between PNRs owing to the large random electric field, which mainly correlates with the large compositional disorder of the nature of high-entropy materials, would delay a polarization texture along the electric field direction. The medium $\\varepsilon_{\\mathrm{r}}\\sim550$ at room temperature controlled by high-entropy strategy can also effectively delay polarization saturation. At the same time, a unique structure of randomly distributed oxygen octahedral tilt can be found in this KNN-H sample. When an external electric field is applied, the tilt distortion of the oxygen octahedron causes some electric energy to be absorbed during the process of forming long-range ferroelectric ordering, resulting in delayed polarization saturation. In a word, the complex inhomogeneous local distortion structure leads to nearly linear P-E loops with a small slope for the studied high-entropy ceramic. \n\nFourth, the ultrahigh hardness should be contributed by the ultrafine grains with a dense microstructure44, mass disorder and solid solution hardening caused by high-entropy design26, which can withstand the compressive forces generated by the electrostatic attraction of the surface charges and stress generated by the electrostriction effect to reduce the possibility of electromechanical breakdown. \n\nLastly, the enhanced dielectric relaxation behavior through entropy enhancement should benefit both the temperature and frequency stability. The enhanced entropy would broaden the distribution of the $T_{c}$ value of each PNR. In addition, the oxygen octahedral tilt system shows good temperature stability, as confirmed by the stable superlattice and unchanged local structure information in Supplementary Figs. 14 and 15. As a result, a temperature-stable dielectric response meeting the standard of X8R capacitors can be achieved for the KNN-H ceramic, as shown in Supplementary Fig. 1. Taking into consideration the near-linear $P\\mathrm{-}E$ response of the studied sample, temperaturestable energy storage can be ensured. Moreover, the strong entropy weakens the correlation between PNRs, leading to a fast response of each PNR under an electric field and bringing about excellent frequency stability. \n\nIn summary, a high-entropy strategy is proposed to design “local multiple distortion” including R-O-T-C multiphase nanoclusters coexistence and random oxygen octahedral tilt distortion for lead-free relaxors to enhance the comprehensive energy storage performance, leading to ultrasmall PNRs, ultrafine grains with a dense microstructure, and delayed polarization saturation. A giant $W_{\\mathrm{rec}}~\\sim10.06\\textrm{J}{\\mathrm{cm}^{-3}}$ with an ultrahigh $\\eta$ ${\\sim}90.8\\%$ is realized in lead-free relaxor ferroelectrics, which is the optimal comprehensive energy storage performance reported to date for lead-free bulk ceramics, showing a breakthrough progress. The excellent mechanical properties, charge/discharge performance and stability of KNN-H ceramics also show great potential for use in energy storage capacitors. It is encouraging that a new avenue is opened up for designing ultrahigh comprehensive energy storage performance, meeting the urgent demand for advanced high-power or pulsed power capacitors. \n\nMethods Sample preparation. $(\\mathrm{K}_{0.2}\\mathrm{Na}_{0.8})\\mathrm{Nb}\\mathrm{O}_{3}$ (KNN) and $[(\\mathrm{K_{0.2}N a_{0.8}})_{0.8}\\mathrm{Li_{0.08}B a_{0.02}B i_{0.1}}]$ $\\mathrm{(Nb_{0.68}S c_{0.02}H f_{0.08}Z r_{0.1}T a_{0.08}S b_{0.04})O_{3}}$ (KNN-H) ceramics were fabricated by a conventional solid-state reaction method. ${\\mathrm{K}}_{2}{\\mathrm{CO}}_{3}$ (Aladdin, $99.99\\%$ ), $\\mathrm{Na}_{2}\\mathrm{CO}_{3}$ (Aladdin, $99.99\\%$ ), ${\\mathrm{Nb}}_{2}{\\mathrm{O}}_{5}$ (Aladdin, $99.9\\%$ ), $\\mathrm{Li}_{2}\\mathrm{CO}_{3}$ (Aladdin, $99.99\\%$ ), ${\\mathrm{BaCO}}_{3}$ (Aladdin, $99.95\\%$ ), ${\\mathrm{Bi}}_{2}{\\mathrm{O}}_{3}$ $(99.99\\%)$ , $\\mathrm{Sc}_{2}\\mathrm{O}_{3}$ (Macklin, $99.0\\%$ ), $\\mathrm{HfO}_{2}$ (Macklin, $99.99\\%$ ), $\\mathrm{ZrO}_{2}$ (Macklin, $99.99\\%$ ), ${\\mathrm{Ta}}_{2}{\\mathrm{O}}_{5}$ (Aladdin, $99.9\\%$ , and $\\mathrm{Sb}_{2}\\mathrm{O}_{3}$ (Macklin, $99.5\\%$ were used as the starting materials. The stoichiometric powders were planetary ball-milled with alcohol in nylon jars for $24\\mathrm{h}$ using yttrium stabilized zirconia balls as milling media. The mixed powers were dried at $120^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ and then calcined at $800^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ Then, the $0.5\\mathrm{wt\\%}$ PVB binder was mixed with the as-synthesized powders by high-energy ball milling ( $\\ensuremath{\\langle600\\mathrm{\\r/min}}$ for $15\\mathrm{h}$ ) with alcohol. After drying at $120^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ , the mixed powders were pressed into pellets with diameters of $1\\mathrm{cm}$ under $300\\mathrm{Mpa}$ . The pellets were heated to $550^{\\circ}\\mathrm{C}$ at $3^{\\circ}\\mathrm{C}/$ min to burn out the binder and then sintered at $1230^{\\circ}\\mathrm{C}$ in closed crucibles for $^{2\\mathrm{h}}$ . The ceramics were polished into a thickness of $\\sim0.006\\substack{-0.010\\mathrm{cm}}$ for electrical property tests. Two parallel surfaces were coated with silver electrodes with an area of $\\mathsf{\\tilde{\\sim}}0.0\\dot{0}785\\mathrm{cm}^{2}$ ${\\sim}0.1\\mathrm{cm}$ in diameter), which were fired at $550^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . \n\nStructure characterizations. The crystal structure was characterized by powder neutron diffraction using time-of-flight powder diffractometers collected at CSNS (China Spallation Neutron Source, MPI) and high-energy synchrotron XRD $(\\lambda=0.11{\\overset{\\cdot}{7}}3{\\overset{\\cdot}{\\mathrm{A}}})$ with a beam size of $0.05\\mathrm{cm}\\times0.05\\mathrm{cm}$ conducted at the 11-ID-C beamline of the Advanced Photon Source. Temperature-dependent XRD tests were performed using an X-ray diffractometer (X’pert PRO, PANalytical, the Netherlands). Temperature-dependent Raman spectra were tested on well-polished samples under $532\\mathrm{nm}$ excitation using a Raman scattering spectrometer (Horiba Jobin Yvon HR800, France) with a heating stage (Linkam, THM 600, UK). The morphology of grains and element distribution maps of samples were analyzed using a SEM (LEO1530, ZEISS SUPRA 55, Oberkochen, Germany). The samples were carefully polished to $0.004\\mathrm{cm}$ and then prepared by an ion milling system (PIPS, Model 691, Gatan Inc., Pleasanton, CA, USA) with a liquid nitrogen cooled stage for TEM measurement. Domain morphology and SAED were observed on a field-emission TEM (JEM-F200, JEOL, Japan) at an accelerating voltage of $200\\mathrm{kV}$ . HAADF and ABF atomic-scale images were acquired using an atomic-resolution STEM (aberration-corrected Titan Themis G2 microscope). Accurate atomic positions in the STEM images were clarified by 2D Gaussian fitting. The polarization vector, polarization magnitude and polarization angle maps were calculated by customized MATLAB scripts. \n\nElectrical property measurements. The room temperature P-E loops with test frequency of $10\\mathrm{Hz}$ and temperature-, frequency- and cycle-dependent $P-E$ loops were measured using a ferroelectric analyzer (aix ACCT, TF Analyzer 1000, Aachen, Germany). Temperature- and frequency-dependent dielectric performance and impedance spectra were performed using a precision LCR meter (Keysight E4990A, Santa Clara, CA). The charge/discharge properties of samples with a thickness of ${\\sim}0.008\\mathrm{cm}$ were conducted using a commercial charge–discharge platform (CFD-001, Gogo Instruments Technology, Shanghai, China). \n\nMechanical performance measurements. The Vickers hardness of the wellpolished samples with a thickness of ${\\sim}0.1\\mathrm{cm}$ were performed under a load of $4.9033\\mathrm{~N~}$ for 15 s using a Vickers diamond indenter (FALCON 507, INNOVATEST, the Netherlands) and recorded through a metallurgical microscope (DMi 8C, Leica, Germany). \n\n# Data availability \n\nAll data supporting this study and its findings are available within the article and its Supplementary Information. Any data deemed relevant are available from the corresponding author upon request. \n\nReceived: 10 March 2022; Accepted: 20 May 2022; Published online: 02 June 2022 \n\n# References \n\n1. Pan, H. et al. Ultrahigh energy storage in superparaelectric relaxor ferroelectrics. Science 374, 100–104 (2021). \n2. Li, J. et al. Grain-orientation-engineered multilayer ceramic capacitors for energy storage applications. Nat. Mater. 19, 999–1005 (2020). \n3. Pan, H. et al. Ultrahigh–energy density lead-free dielectric films via polymorphic nanodomain design. Science 365, 578–582 (2019). \n4. Yang, L. et al. Perovskite lead-free dielectrics for energy storage applications. Prog. Mater. Sci. 102, 72–108 (2019). \n5. Wang, G. et al. Electroceramics for high-energy density capacitors: current status and future perspectives. Chem. Rev. 121, 6124–6172 (2021). \n\nniobate tantalate with high energy storage performance. Adv. Mater. 29, 1701824 (2017). 7. Zhang, M., Yang, H., Yu, Y. & Lin, Y. Energy storage performance of $\\mathrm{K}_{0.5}\\mathrm{Na}_{0.5}\\mathrm{Nb}\\mathrm{O}_{3}$ -based ceramics modified by $\\mathrm{Bi(Zn_{2/3}(N b_{0.85}T a_{0.15})_{1/3})O_{3}}$ . Chem. Eng. J. 425, 131465 (2021). 8. Lu, Z. et al. Superior energy density through tailored dopant strategies in multilayer ceramic capacitors. Energy Environ. Sci. 13, 2938–2948 (2020). 9. Qi, H. et al. Ultrahigh energy‐storage density in ${\\mathrm{NaNb}}{\\mathrm{O}}_{3}$ ‐based lead‐free relaxor antiferroelectric ceramics with nanoscale domains. Adv. Funct. Mater. 29, 1903877 (2019). 10. Luo, N. et al. Constructing phase boundary in $\\mathrm{AgNb}{\\mathrm{O}}_{3}$ antiferroelectrics: pathway simultaneously achieving high energy density and efficiency. Nat. Commun. 11, 4824 (2020). 11. Yan, F. et al. Significantly enhanced energy storage density and efficiency of BNT-based perovskite ceramics via A-site defect engineering. Energy Storage Mater. 30, 392–400 (2020). 12. Qi, H., Xie, A., Tian, A. & Zuo, R. Superior energy‐storage capacitors with simultaneously giant energy density and efficiency using nanodomain engineered ${\\mathrm{BiFeO}}_{3}$ ‐BaTiO $\\mid_{_{3}}$ ‐NaNbO3 lead‐free bulk ferroelectrics. Adv. Energy Mater. 10, 1903338 (2020). 13. Wang, K. et al. Superparaelectric $(\\mathrm{Ba}_{0.95},\\mathrm{Sr}_{0.05})(\\mathrm{Zr}_{0.2},\\mathrm{Ti}_{0.8})\\mathrm{O}_{3}$ ultracapacitors. Adv. Energy Mater. 10, 2001778 (2020). 14. Yang, H. et al. Novel $\\mathrm{BaTiO}_{3}$ -based, $\\mathrm{Ag/Pd}$ -compatible lead-free relaxors with superior energy storage performance. ACS Appl. Mater. Interfaces 12, 43942–43949 (2020). 15. Zhang, T., Zhao, Y., Li, W. & Fei, W. High energy storage density at low electric field of $\\mathrm{ABO}_{3}$ antiferroelectric films with ionic pair doping. Energy Storage Mater. 18, 238–245 (2019). 16. Lu, Z. et al. Mechanism of enhanced energy storage density in $\\mathrm{AgNb}{\\mathrm{O}}_{3}$ -based lead-free antiferroelectrics. Nano Energy 79, 105423 (2021). 17. Shi, J. et al. Realizing ultrahigh recoverable energy density and superior charge–discharge performance in ${\\mathrm{NaNb}}{\\mathrm{O}}_{3}$ -based lead-free ceramics via a local random field strategy. J. Mater. Chem. C. 8, 3784–3794 (2020). 18. Qi, H., Xie, A. & Zuo, R. Local structure engineered lead-free ferroic dielectrics for superior energy-storage capacitors: a review. Energy Storage Mater. 45, 541–567 (2021). 19. Ji, H. et al. Ultrahigh energy density in short-range tilted NBT-based lead-free multilayer ceramic capacitors by nanodomain percolation. Energy Storage Mater. 38, 113–120 (2021). 20. Yan, F. et al. Sandwich structured lead-free ceramics based on $\\mathrm{Bi}_{0.5}\\mathrm{Na}_{0.5}\\mathrm{TiO}_{3}$ for high energy storage. Chem. Eng. J. 425, 130669 (2021). 21. Wang, M. et al. Ultrahigh energy storage density and efficiency in $\\mathrm{Bi}_{0.5}\\mathrm{Na}_{0.5}\\mathrm{TiO}_{3}$ -based ceramics via the domain and bandgap engineering. ACS Appl. Mater. Interfaces 13, 51218–51229 (2021). 22. Cantor, B., Chang, I., Knight, P. & Vincent, A. Microstructural development in equiatomic multicomponent alloys. Mater. Sci. Eng. A 375, 213–218 (2004). 23. Lim, X. Mixed-up metals make for stronger, tougher, stretchier alloys. Nature 533, 306–307 (2016). 24. Oses, C., Toher, C. & Curtarolo, S. High-entropy ceramics. Nat. Rev. Mater. 5, 295–309 (2020). 25. Sarkar, A. et al. Rare earth and transition metal based entropy stabilised perovskite type oxides. J. Eur. Ceram. Soc. 38, 2318–2327 (2018). 26. Sarker, P. et al. High-entropy high-hardness metal carbides discovered by entropy descriptors. Nat. Commun. 9, 1–10 (2018). 27. Lv, X., Zhu, J., Xiao, D., Zhang, X. X. & Wu, J. Emerging new phase boundary in potassium sodium-niobate based ceramics. Chem. Soc. Rev. 49, 671–707 (2020). 28. Wu, J., Xiao, D. & Zhu, J. Potassium–sodium niobate lead-free piezoelectric materials: past, present, and future of phase boundaries. Chem. Rev. 115, 2559–2595 (2015). 29. Lin, D., Kwok, K. W. & Chan, H. Microstructure, phase transition, and electrical properties of $(\\mathrm{K_{0.5}N a_{0.5}})_{1-x}\\mathrm{Li}_{x}(\\mathrm{Nb_{1-\\ensuremath{y}}T a_{\\ensuremath{y}}})\\mathrm{O}_{3}$ lead-free piezoelectric ceramics. J. Appl. Phys. 102, 034102 (2007). 30. Zuo, R., Fu, J., Lv, D. & Liu, Y. Antimony tuned rhombohedral‐orthorhombic phase transition and enhanced piezoelectric properties in sodium potassium niobate. J. Am. Ceram. Soc. 93, 2783–2787 (2010). 31. Tang, X. et al. Composition dependence of phase structure and electrical properties in $(0.98-x)\\mathrm{K}_{0.35}\\mathrm{Na}_{0.65}\\mathrm{Nb}\\mathrm{O}_{3}-0.02\\mathrm{Ba}\\mathrm{Zr}\\mathrm{O}_{3}-x\\mathrm{Bi}_{0.5}\\mathrm{Na}_{0.5}\\mathrm{ZrO}_{3}$ ternary ceramics. J. Alloy. Compd. 672, 277–281 (2016). 32. Liu, Q. et al. High-performance lead-free piezoelectrics with local structural heterogeneity. Energy Environ. Sci. 11, 3531–3539 (2018). 33. Tao, H. et al. Ultrahigh performance in lead-free piezoceramics utilizing a relaxor slush polar state with multiphase coexistence. J. Am. Chem. Soc. 141, 13987–13994 (2019). 34. Glazer, A. Simple ways of determining perovskite structures. Acta Cryst. A 31, 756–762 (1975). 35. Cohen, R. Relaxors go critical. Nature 441, 941–942 (2006). \n\n36. Yang, Z. et al. Grain size engineered lead-free ceramics with both large energy storage density and ultrahigh mechanical properties. Nano Energy 58, 768–777 (2019). \n37. Chen, L. et al. Outstanding energy storage performance in high‐hardness $(\\mathrm{Bi}_{0.5}\\mathrm{K}_{0.5})\\mathrm{TiO}_{3}$ ‐based lead‐free relaxors via multi‐scale synergistic design. Adv. Funct. Mater. 32, 2110478 (2022). \n38. Saito, Y. et al. Lead-free piezoceramics. Nature 432, 84–87 (2004). \n39. Zheng, T. & Wu, J. Enhanced piezoelectricity over a wide sintering temperature $(400-1050^{\\circ}\\mathrm{C})$ range in potassium sodium niobate-based ceramics by two step sintering. J. Mater. Chem. A 3, 6772–6780 (2015). \n40. Chen, L., Liu, H., Qi, H. & Chen, J. High-electromechanical performance for high-power piezoelectric applications: fundamental, progress, and perspective. Prog. Mater. Sci. 127, 100944 (2022). \n41. Waser, R. TrI4: The role of grain boundaries in conduction and breakdown of perovskite-type titanates. Ferroelectrics 133, 109–114 (1992). \n42. Tunkasiri, T. & Rujijanagul, G. Dielectric strength of fine grained barium titanate ceramics. J. Mater. Sci. Lett. 15, 1767–1769 (1996). \n43. Zhang, L. et al. Effect of $\\mathrm{HfO}_{2}$ addition as intergranular grains on the energy storage behavior of $\\mathrm{Ca}_{0.6}\\mathrm{Sr}_{0.4}\\mathrm{TiO}_{3}$ ceramics. J. Eur. Ceram. Soc. 36, 3157–3163 (2016). \n44. Lu, K., Lu, L. & Suresh, S. Strengthening materials by engineering coherent internal boundaries at the nanoscale. Science 324, 349–352 (2009). \n\n# Acknowledgements \n\nThis work was supported by the National Natural Science Foundation of China (Grant Nos. 21825102 (J.C.), 22161142022 (J.C.), 52172181 (H.Q.), and 22075014 (H.Q.)), the Fundamental Research Funds for the Central Universities, China (Grant No. 06500186 (H.Q.)), the China Postdoctoral Science Foundation (Grant Nos. 2020M680345 (H.Q.) and 2021T140048 (H.Q.)). This research was used resources of the China Spallation Neutron Source and the Advanced Photon Source, a US Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. \n\n# Author contributions \n\nThe work was conceived and designed by L.C., H.Q., and J.C. L.C. fabricated the samples, tested the energy storage, dielectric, structure, stability and other properties, and processed related data, assisted by H.Q. The SEM and TEM images were filmed and processed by L.C. The STEM images were filmed and processed by S.D. and L.C. The synchrotron XRD and neutron diffraction data were processed and analyzed by H.L. and J.W. The oxygen octahedral tilt data were processed by H.Q. The manuscript was drafted by L.C. and revised by H.Q. and J.C. All authors participated in the data analysis and discussions. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-30821-7. \n\nCorrespondence and requests for materials should be addressed to He Qi or Jun Chen. \n\nPeer review information Nature Communications thanks Jiwei Zhai the other anonymous reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1007_s40820-022-00863-z", + "DOI": "10.1007/s40820-022-00863-z", + "DOI Link": "http://dx.doi.org/10.1007/s40820-022-00863-z", + "Relative Dir Path": "mds/10.1007_s40820-022-00863-z", + "Article Title": "Vertically Aligned Silicon Carbide nullowires/ Boron Nitride Cellulose Aerogel Networks Enhanced Thermal Conductivity and Electromagnetic Absorbing of Epoxy Composites", + "Authors": "Pan, D; Yang, G; Abo-Dief, HM; Dong, JW; Su, FM; Liu, CT; Li, YF; Xu, BB; Murugadoss, V; Naik, N; El-Bahy, SM; El-Bahy, ZM; Huang, MA; Guo, ZH", + "Source Title": "nullO-MICRO LETTERS", + "Abstract": "With the innovation of microelectronics technology, the heat dissipation problem inside the device will face a severe test. In this work, cellulose aerogel (CA) with highly enhanced thermal conductivity (TC) in vertical planes was successfully obtained by constructing a vertically aligned silicon carbide nullowires (SiC NWs)/boron nitride (BN) network via the ice template-assisted strategy. The unique network structure of SiC NWs connected to BN ensures that the TC of the composite in the vertical direction reaches 2.21 W m(-1) K-1 at a low hybrid filler loading of 16.69 wt%, which was increased by 890% compared to pure epoxy (EP). In addition, relying on unique porous network structure of CA, EP-based composite also showed higher TC than other comparative samples in the horizontal direction. Meanwhile, the composite exhibits good electrically insulating with a volume electrical resistivity about 2.35 x 1011 Omega cm and displays excellent electromagnetic wave absorption performance with a minimum reflection loss of - 21.5 dB and a wide effective absorption bandwidth (< - 10 dB) from 8.8 to 11.6 GHz. Therefore, this work provides a new strategy for manufacturing polymer-based composites with excellent multifunctional performances in microelectronic packaging applications.", + "Times Cited, WoS Core": 312, + "Times Cited, All Databases": 324, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000789072200001", + "Markdown": "Cite as Nano-Micro Lett. (2022) 14:118 \n\nReceived: 18 February 2022 \nAccepted: 6 April 2022 \nPublished online: 30 April 2022 \n$\\circledcirc$ The Author(s) 2022 \n\n# Vertically Aligned Silicon Carbide Nanowires/ Boron Nitride Cellulose Aerogel Networks Enhanced Thermal Conductivity and Electromagnetic Absorbing of Epoxy Composites \n\nDuo $\\ensuremath{\\mathrm{Pan}}^{1,4}$ , Gui $\\mathrm{Yang^{1}}$ , Hala M. Abo‑Dief2, Jingwen Dong1, Fengmei $\\mathsf{S u}^{1}$ \\*, Chuntai Liu1, Yifan $\\mathrm{Li}^{3}$ , Ben Bin $\\mathrm{Xu}^{3\\boxtimes}$ , Vignesh Murugadoss4,5, Nithesh Naik7, Salah M. El‑Bahy8, Zeinhom M. El‑Bahy9, Minan Huang4,6, Zhanhu Guo4 \\* \n\n# HIGHLIGHTS \n\n•\t Cellulose aerogel with vertically oriented structure was obtained by constructing a vertically aligned SiC nanowires/BN network via the ice template assisted strategy. \n•\t The thermal conductivity of the composite in the vertical direction reaches 2.21 W $\\mathbf{m}^{-1}\\mathbf{K}^{-1}$ at a low hybrid filler loading of 16.69 $w t\\%$ , which was increased $890\\%$ compared to pure epoxy. \n•\t The composite exhibits good electrically insulating with a volume electrical resistivity about $2.35\\times10^{11}\\Omega\\mathrm{{cm}}$ , and displays excellent electromagnetic wave absorption performance. \n\nABSTRACT  With the innovation of microelectronics technology, the heat dissipation problem inside the device will face a severe test. In this work, cellulose aerogel (CA) with highly enhanced thermal conductiv‑ ity (TC) in vertical planes was successfully obtained by constructing a vertically aligned silicon carbide nanowires (SiC NWs)/boron nitride (BN) network via the ice template-assisted strategy. The unique net‑ work structure of SiC NWs connected to BN ensures that the TC of the composite in the vertical direction reaches $2.21\\mathrm{~W~m~}^{-1}\\mathrm{~K~}^{-1}$ at a low hybrid filler loading of $16.69\\ \\mathrm{wt}\\%$ , which was increased by $890\\%$ compared to pure epoxy (EP). In addition, relying on unique porous network structure of CA, EP-based composite also showed higher TC than other comparative samples in the horizontal direction. Meanwhile, the composite exhibits good electrically insulating with a volume electrical resistivity about $2.35\\times10^{11}\\Omega\\mathrm{{cm}}$ and displays excellent electromagnetic wave absorption performance with a minimum reflection loss of $-21.5\\mathrm{dB}$ and a wide effective absorption bandwidth $(<-10\\mathrm{dB})$ from 8.8 to $11.6\\mathrm{GHz}$ . Therefore, this work provides a new strat‑ egy for manufacturing polymer-based composites with excellent multifunctional performances in microelectronic packaging applications. \n\n![](images/b184071e7ab3363d8f03260f065ee5241dc7cae6fdffd7038b573e3ca767818b.jpg) \n\nKEYWORDS  Epoxy; Ice template; Vertical alignment; Thermal conductivity; Multifunctionality \n\n# 1  Introduction \n\nWith the innovation of the third-generation semiconduc‑ tor technology, electronic equipment has shown a develop‑ ment trend of multi-function, miniaturization and integra‑ tion [1–4]. As a result, a large amount of heat generated inside the equipment continue to accumulate, which seri‑ ously affects its reliability and service life [5]. Polymer materials have been widely used in the sealing and interface bonding of various electronic devices due to their excellent mechanical properties, good insulation and unique chemical stability [6–8]. However, the thermal conductivity (TC) of polymer materials is generally low (usually no more than $0.5\\mathrm{~W~m~}^{-1}\\mathrm{K}^{-1},$ ), which limits their wide-ranging applica‑ tions in the microelectronic packaging industry [9–11]. How to improve the TC of polymer materials and make them bet‑ ter apply to the field of thermal management has become an important problem that needs to be solved urgently [12]. \n\nCompared with the difficulty to change the molecular chain structure of the intrinsic polymer to improve TC, it is simple and practical to add a filler with high TC into the polymer [13–15]. Generally, such thermally conductive fill‑ ers mainly include metal oxides (e.g., $\\mathrm{Al}_{2}\\mathrm{O}_{3}$ , $z_{\\mathrm{{nO}}}$ and $\\begin{array}{r}{\\mathbf{MgO}_{\\mathrm{,}}^{\\mathrm{~}}}\\end{array}$ ) [16], metal particles (e.g., Cu, Zn and $\\mathrm{Ag}$ ) [17], aluminum nitride (AlN) [18], boron nitride (BN) [19], silicon carbide (SiC) [20], graphene [21] and carbon nanotubes [22], etc. Among them, BN is considered to be the most promising two-dimensional material because of its low density, excel‑ lent electrical insulation, oxidation resistance and chemical stability properties [23, 24]. Unfortunately, a large amount of BN are often needed in the composite to achieve a satis‑ factory heat dissipation effect due to the existence of inter‑ face thermal resistance between polymer matrix and fillers, which is bound to sacrifice the excellent toughness of the matrix and the mechanical properties of the composite [25, 26]. Therefore, it is of great significance to use less BN fill‑ ers to obtain composites with a better TC in high power density electronic devices. \n\nIn recent years, compared with simple blending, two strategies of driving the horizontally orientation of BN [27] and building a three-dimensional (3D) BN thermally conductive network [28] can effectively construct heat conduction paths to improve the TC at a low BN content. In the former orientation applications, composites mostly appear in the form of films. For example, Yang et al. [29] fabricated polyvinyl alcohol/boron nitride composite film with high in-plane TC ( $(19.99\\mathrm{{W}\\mathrm{{m}^{-1}\\mathrm{{K}^{-1})}}}$ via the combina‑ tion of electrostatic spinning and hot-pressing technique. Wu et al. [30] reported a BN nanosheet/polymer composite film with superior in-plane TC of around $200\\ \\mathrm{W\\m^{-1}\\ K^{-1}}$ and extremely low through-plane TC of $1.0\\ \\mathrm{W\\m^{-1}\\ K^{-1}}$ . Although these film-like composites have considerable inplane TC, the heat dissipation of microelectronic devices is mainly through the rapid transfer of accumulated heat energy from the heat source to the heat sink in a short verti‑ cal direction [31, 32]. The TC of the film-like composites in the vertical direction is quite low, which hinders their large-scale use in actual production. The latter uses fillers to establish a spatially interconnected thermally conductive network structure to improve the overall TC of the compos‑ ite [33]. Chen et al. [34] prepared BN-polyvinylidene dif‑ luoride (PVDF) 3D scaffold by removing the sodium chlo‑ ride salt template method and found that the TC of the final epoxy/BN-PVDF was 1.227 W $\\mathbf{m}^{-1}\\mathbf{K}^{-1}$ . Zhou et al. [35] synthesized a 3D interconnective cross-linking polystyrene (c-PS)/BN composite foam with a TC of $1.28\\ \\mathrm{W\\m^{-1}\\ K^{-1}}$ and found that the composite foams exhibited low density and dielectric constants. Although the 3D heat conduction paths constructed by BN in the matrix improves the overall TC of the bulk composite to a certain extent, the TC in the vertical direction cannot be effectively improved by relying on BN alone [36]. \n\nTherefore, on one hand, one-dimensional materials (e.g., carbon nanotubes, silver nanowire and SiC nanowire) as a thermally conductive bridge to connect BN were introduced [37], and on the other hand, various strategies (e.g., suction filtration method, magnetic field method and electric field method) were adopted to achieve vertical alignment of fill‑ ers [38–40]. One-dimensional SiC nanowire overcomes the defects of traditional SiC materials and has been widely used in aerospace, chemical, electronics and other industrial fields due to its excellent high-temperature strength, good ther‑ mally conductive performance, high wear resistance and cor‑ rosion resistance [41]. Xiao et al. [31] successfully prepared epoxy-based composites with excellent through-plane TC 1 $4.22\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1},$ ) by constructing a free-standing and verti‑ cally aligned SiC nanowires/BN framework through modi‑ fied filtration strategy. Kim et al. [42] fabricated a directional thermally conductive $\\mathrm{{BN}{-}\\mathrm{{Fe}}_{3}\\mathrm{{O}}_{4}/\\mathrm{{SiC}}}$ binary filler epoxy composite by introducing $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ particles on the BN surface via magnetic alignment technology. The obtained composite not only has excellent thermal management performance, but also has a high storage modulus. Unfortunately, these methods have high technical requirements, and many factors such as density mismatch, electric field distribution, interac‑ tion between magnetic ions and uncontrollable grafting sites need to be considered [43]. \n\nIn addition, with the rapid development of the 5G era, microelectronic devices bring us convenience while carrying potentially serious electromagnetic pollution [44–46]. Effi‑ cient microwave absorbing materials have attracted a lot of attention in recent years; however, few studies have combined excellent thermal management and microwave absorption properties simultaneously [47–50]. In this work, based on the previous research work [51, 52] about the cellulose aero‑ gel obtained by the ice template method, the unique structure with a small amount of SiC nanowires (SiC NWs) vertically connected to BN was obtained by modifying the fillers and combining with directional freezing technology. The finally obtained epoxy composite not only exhibits excellent ther‑ mal management capability in the vertical direction, but also displays excellent electromagnetic wave absorption perfor‑ mance, which is attributed to the good synergistic effects of SiC NWs and BN in both function and structure. \n\n# 2  \u0007Experimental \n\n# 2.1  \u0007Materials \n\nHexagonal boron nitride powder $(h{\\mathrm{-BN}},\\sim10\\upmu\\mathrm{m}$ , $99.9\\%$ ) was purchased from Hefei AVIC Nano Technology Development \n\nCo., Ltd., China. SiC nanowires (SiC NWs, diameters: $0.1\\mathrm{-}0.5~\\upmu\\mathrm{m}$ , length: $20{-}50~{\\upmu\\mathrm{m}},$ ) were supplied by Xuzhou Hongwu Nano Material $\\mathrm{Co}$ ., Ltd., China. Sodium hydroxide (NaOH, AR, $96\\%$ ), Urea $(\\mathrm{H}_{2}\\mathrm{NCONH}_{2}$ , AR, $99\\%$ ) and cel‑ lulose with a length of $\\leq25\\mathrm{mm}$ were obtained from Shang‑ hai Aladdin Reagent Co., Ltd., China. Boric acid $\\mathrm{(H}_{3}\\mathrm{BO}_{3}$ , AR, $\\geq99.5\\%$ ) and epichlorohydrin (ECH, $\\mathrm{C}_{3}\\mathrm{H}_{5}\\mathrm{ClO}$ , $1.183\\ \\mathrm{g\\cm}^{-3},$ were supplied by Shanghai McLean Bio‑ chemical Technology Co., Ltd., China. Epoxy (EP, E-44) and amine curing agent 593 were provided by Evergreen Chemicals Technology Co., Ltd., China. All reagents were of analytical grade and used without any further purification. \n\n# 2.2  \u0007Preparation of Cellulose/m‑SiC NWs/m‑BN Aerogel (CA/m‑SiC/m‑BN) \n\nBefore synthesizing aerogels, the surface of $h$ -BN and SiC NWs needs to be modified for better connection and dis‑ persion. Specifically, the original $h$ -BN was exfoliation and modified by putting BN and boric acid (BA) in a planetary ball mill at a mass ratio of $\\mathrm{m}(\\mathrm{BN})/\\mathrm{m}(\\mathrm{BA})=1{:}10$ for $36\\mathrm{~h~}$ at $400\\ \\mathrm{rpm}$ and then subjected to a series of operations of centrifugation, washing and drying to obtain the modified BN, marked as m-BN. For the modification of SiC NWs (m-SiC NWs), commercial SiC NWs were oxidized at a high temperature of $1300~^{\\circ}\\mathrm{C}$ with an air atmosphere in a tube furnace for $5\\mathrm{min}$ . \n\nThe cellulose/m-SiC NWs/m-BN aerogel was obtained by the corresponding hydrogel through directional freezing followed with freeze drying steps. Firstly, the alkaline solu‑ tion was prepared by mixing NaOH/urea/deionized water at a weight ratio of 7:14:79. Then, $\\mathfrak{s}_{\\mathrm{~g~}}$ cellulose was added into $50~\\mathrm{mL}$ above solution and stirred evenly and put it in a refrigerator at − $10^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . After that, different masses of m-BN (0.5, 1.0, 1.5 and $\\begin{array}{r}{1.8\\mathrm{g}}\\end{array}$ ) followed with a small amount of m-SiC NWs were successively added and magnetically stirred for $2\\mathfrak{h}$ to obtain a cellulose/m-SiC NWs/m-BN solu‑ tion. Next, $10~\\mathrm{mL}$ cross-linker ECH is introduced and the obtained mixed paste solution was poured into a mold with an internal diameter of $20\\mathrm{mm}$ and a Cu disk substrate, and cross-linked for regeneration at $60~^{\\circ}\\mathrm{C}$ for $5\\mathrm{~h~}$ in an oven. After that, the formed cellulose/m-SiC NWs/m-BN hydro‑ gels were soaked in deionized water to remove the residual reactants (NaOH, urea and ECH) and followed by direc‑ tional freezing treatment with liquid nitrogen in the mold for $10\\mathrm{min}$ . Finally, the frozen cellulose/m-SiC NWs/m-BN hydrogels were then transferred to a freeze drier at $\\mathrm{~-~}80~^{\\circ}\\mathrm{C}$ for $^{72\\mathrm{~h~}}$ to get cellulose/m-SiC NWs/m-BN aerogels. To simplify writing, cellulose/m-SiC NWs/m-BN aerogel was marked as $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ BN. \n\n# 2.3  \u0007Preparation of CA/m‑SiC/m‑BN/EP Composites \n\nThe CA/m-SiC/m-BN/EP composites were fabricated via a vacuum-assisted impregnation method. In brief, $10\\mathrm{{g}}$ EP and $\\ensuremath{2\\mathrm{~g~}}$ curing agent 593 were magnetically stirred in a water bath $(80~^{\\circ}\\mathrm{C})$ to obtain a homogeneous solution. The $\\mathrm{CA/m{-}S i C/m{-}B}$ N aerogels were immersed into above solu‑ tion in a vacuum system and cured in an oven at $60~^{\\circ}\\mathrm{C}$ for $^{3\\mathrm{~h~}}$ and $80~^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{~h~}}$ . Eventually, the composites denoted as $\\mathrm{CA}/\\mathrm{xm}{-}\\mathrm{SiC}/\\mathrm{ym}{-}\\mathrm{BN}/\\mathrm{EP}$ (x and y correspond to the mass (g) of $\\mathrm{m}{\\cdot}\\mathrm{SiC}$ and m-BN) were obtained. In addition, ${\\mathrm{CA/m}}{\\cdot}{\\mathrm{SiC/EP}}$ and CA/m-BN/EP with the same synthesis method, and $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{SiC}/\\mathrm{m}$ -BN/EP composites by a simple blending $\\mathrm{(CA/m\\mathrm{-}S i C/m\\mathrm{-}B N/E P_{b l e n d})}$ were also prepared for comparison. \n\n# 2.4  \u0007Characterization \n\nThe scanning electron microscopy (SEM, JSM-6380, Japan) was applied to observe the morphologies of m-BN, $\\mathrm{m}{\\cdot}\\mathrm{SiC}$ NWs and the microstructure of the $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ -BN net‑ work. Atomic force microscopy was conducted (AFM, Bruker MultiMode 8) to investigate the lateral size and thickness of m-BN. Fourier transform infrared spectroscopy (FT-IR) was tested in the range of $500{-}4000~\\mathrm{cm}^{-1}$ using Nicolet NEXUS 870 spectrometer. Elemental scanning was achieved by X-ray photoelectron spectroscopy (XPS, ESCALAB 250 Xi). The filler loading of different samples was estimated by a thermal gravimetric analyzer (TGA, 209 F3, Netzsch). Contact angle was obtained from contact angle measurement (CD-100D, innuo-instruments, Shang‑ hai). Volume resistivity was measured by an Electrometer (Tektronix, 6517B, America) at room temperature. The $K$ was measured by a Hot Disk Thermal Constant Analyzer (Hot Disk TPS 2500S, Sweden), and an infrared thermal camera (E60, FLIR) was employed to measure the change of sample surface temperature over different heating and cooling time. A vector network analyzer (VNA, Keysight N5222B, USA) was used to measure the electromagnetic parameters of different samples with the coaxial method in the frequency range of $2{\\mathrm{-}}18\\operatorname{GHz}$ . \n\n# 3  \u0007Results and Discussions \n\n# 3.1  \u0007Characterization of m‑BN, m‑SiC NWs \n\nThe original BN has chemical stability and large thickness, which limits its dispersibility in the organic matrix and the improvement of the overall TC [53]. To illustrate the suc‑ cessful stripping and modification of BN, the microscopic morphology and element bond analysis were tested by using SEM, AFM and FT-IR, respectively. Figure 1a shows the platelet morphology of the original BN, the uneven lateral size (about $5{\\mathrm{-}}10~{\\upmu\\mathrm{m}})$ ) and the thickness of about $500\\ \\mathrm{nm}$ can be clearly observed. After modified by ball milling with boric acid (BA), the obtained $\\mathrm{m-BN}$ presents a thin and transparent morphology (Fig. 1b). Taking 50 pieces of m-BN flakes for further observed with an atomic force microscope, from Fig. 1c–e, it is found that the m-BN with an average lateral size of $2\\mathrm{-}3~\\upmu\\mathrm{m}$ and a thickness of about $20\\mathrm{nm}$ . \n\nThe mechanism of BN modification can be found in FT-IR spectra as shown in Fig. 1f. Except for two char‑ acteristic peaks of B-N stretching vibration $(1375~\\mathrm{{cm}^{-1}},$ and B-N-B bending vibration $(819\\ \\mathrm{cm}^{-1}.$ ) about original BN, m-BN exhibits two other different broad absorptions at 3420 and $3230~\\mathrm{{cm}^{-1}}$ , which correspond to the $-\\mathrm{OH}$ and $\\boldsymbol{\\mathrm{N-H}}$ stretching vibration [54, 55]. The acquisition of hydrophilic groups is due to the high-speed mechanical shearing action that makes the $\\mathbf{N}$ atoms and B atoms in an active state to react with BA [56]. The increase in hydro‑ philicity of $\\mathrm{m-BN}$ is verified by the fact that the contact angle of m-BN is significantly smaller than that of BN in the illustration. \n\nIn order to reduce the interface thermal resistance between SiC NWs and BN, SiC NWs are treated by hightemperature oxidation. According to the SEM image in Fig. 2a, the untreated SiC $\\mathrm{NW_{S}}$ have a rod-like structure with a length of about $25~{\\upmu\\mathrm{m}}$ and have a smooth surface without impurities. After calcination at $1300^{\\circ}\\mathrm{C}$ , the sur‑ face of the $\\mathrm{m{-}S i C\\ N W_{S}}$ becomes rough and has granular aggregates (Fig. 2b). As shown in Fig. 2c, the FT-IR char‑ acteristic peaks at around 810 and $918~\\mathrm{cm}^{-1}$ are attributed to the $\\mathrm{C-}\\mathrm{Si}$ stretching vibration of SiC NWs [57]. The peak at around $3421~\\mathrm{cm}^{-1}$ belongs to the $-\\mathrm{OH}$ group in the water absorbed on the surface of the sample. After modi‑ fication, the new peaks of Si–O–Si and C–O–Si groups at 1095 and $1219~\\mathrm{cm}^{-1}$ appear on m-SiC NWs [58]. Fur‑ thermore, a series of peaks located at around of $1500\\mathrm{cm}^{-1}$ (inside the blue dashed circle) are ascribed to the stretch‑ ing vibration of $\\scriptstyle{\\mathrm{C-O}}$ and $\\scriptstyle{\\mathrm{C=O}}$ [59]. \n\n![](images/4b44c2edac9c9395b77b31a429a4f37957d92382fff4274ca9a8aaf4bb60ebf0.jpg) \nFig. 1   Characterizations of original BN and m-BN. a, b are SEM images of pristine BN and m-BN. c AFM image, d diameter length and e thickness distribution of m-BN. f FT-IR analysis of BN and m-BN. Insets are the corresponding contact angle test results \n\nFigure 2d–f presents the XPS high-resolution spectra of C, Si and O elements to further confirm the linking of functional groups on $\\mathrm{m{-}S i C\\ N W_{S}}$ . From Fig. S1, the C 1s spectrum of commercial SiC $\\mathrm{NW_{S}}$ shows three fit‑ ting peaks at 283.4, 284.9 and $286.4\\ \\mathrm{eV}$ corresponding to ${\\mathrm{C}}{\\mathrm{-}}{\\mathrm{Si}}$ , $scriptstyle\\mathrm{C=C/C-C}$ and C-O, respectively [60]. While the $\\mathrm{~C~}1s$ spectrum of m-SiC $\\mathrm{NW_{S}}$ not only contains the above fitting peaks, but also emerges a $\\scriptstyle{\\mathrm{C=O}}$ bond at $287.1\\ \\mathrm{eV}$ More importantly, after modification, the peak attributed to $scriptstyle{\\mathrm{C=C/C-C}}$ gets stronger. In addition, except for the $\\mathrm{Si-C}$ bond at $102.8\\ \\mathrm{eV}$ in the Si $2p$ spectrum, an obvi‑ ous fitting peak found in m-SiC $\\mathrm{NW_{S}}$ at $100.3{\\mathrm{~eV}}$ cor‑ responds to Si–O bond. [61, 62]. Only one main fitting peak of $_{\\mathrm{~O~l~}s}$ belongs to the $_\\mathrm{O-Si}$ bonding at $532.2\\ \\mathrm{eV}$ From the above FT-IR and XPS results, it can be inferred that multi-oxygen-containing functional group (Si–O–Si, $\\mathrm{C-O-Si}$ and $\\scriptstyle{\\mathrm{C=O}}$ ) were formed on the surface of m-SiC $\\mathrm{NW_{S}}$ after calcination treatment [63]. These valence bond structures not only enhance the dispersion of $\\mathrm{\\m{-}S i C\\ N W_{S}}$ in the matrix (from the illustration in Fig. 2c, compared to the commercial SiC $\\mathrm{NW_{S}}$ , the aqueous dispersion of $\\mathrm{m{-}S i C\\ N W_{S}}$ did not show delamination after standing for $24~\\mathrm{h}\\dot{}$ ), but also provide a theoretical support for m-SiC $\\mathrm{NW_{S}}$ connecting $\\mathrm{m-BN}$ to form thermally conductive paths. \n\n# 3.2  \u0007Fabrication and Characterization of CA/m‑SiC/ m‑BN and CA/m‑SiC/m‑BN/EP \n\nAs shown in Fig. 3, the preparation of CA/m-SiC/m-BN/EP can be summarized in the following four processes: firstly, the preparation of a paste dispersion of cellulose/m-SiC/mBN; then, the mixed dispersion is cross-linked in a mold to form m-SiC/m-BN cellulose hydrogel, which undergoes a directional freezing in a liquid nitrogen environment [64]; Next, the m-SiC/m-BN cellulose hydrogel is freeze-dried to become m-SiC/m-BN cellulose aerogel (CA/m-SiC/m-BN); \n\n![](images/8f47db55f70884b7deae656979f67852eb7e53685cf2663401eb880aa35a65a4.jpg) \nFig. 2   Characterizations of commercial SiC $\\mathrm{NW_{S}}$ and m-SiC $\\mathrm{NW_{S}}$ . a, $\\mathbf{b}$ are SEM images of commercial SiC $\\mathrm{NW_{S}}$ and m-SiC $\\mathrm{NW_{S}}$ . c FT-IR spectra of SiC $\\mathrm{NW_{S}}$ and m-SiC $\\mathrm{NW_{S}}$ . High-resolution XPS analysis of d C 1s, e Si $2p$ and f O $1s$ of m-SiC $\\mathrm{NW_{S}}$ \n\n![](images/43cabed7e7201b4f3e51afe83e60696d76fe8a4744a5d62b6ee8e40d2e21143c.jpg) \nFig. 3   Schematic diagram of the preparation of CA/m-SiC/m-BN/EP \nFigure  4 presents the XPS and FT-IR spectra of cel‑ lulose aerogel (CA), $\\mathrm{{CA/m}{\\cdot}\\mathrm{{SiC}\\ N W_{S}}}$ , $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}$ and $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ to further confirm the covalent connection. Specifically, the binding energy peaks of dif‑ ferent elements contained in CA, SiC $\\mathrm{NW_{S}}$ and BN were observed on the hybrid spectrum of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{Br}$ and \n\nFinally, CA/m-SiC/m-BN/EP is obtained by impregnating the $\\mathrm{CA/m{-}S i C/m{-}B}$ N aerogel in EP with the aid of a vacuum system. In addition, it can be seen from the vignette that $\\mathrm{CA/m{-}S i C/m{-}B N}$ is lightweight, and even the final $\\mathrm{CA/m}\\cdot$ - SiC/m-BN/EP composite can also be placed steadily on the tiny grass branches. \n\n![](images/8950b73d8a80f86106c60eb36a41ef734c78056c8e340122b88aba036e463284.jpg) \nFig. 4   a XPS and b FT-IR spectra of CA, $\\mathrm{CA}/\\mathrm{m}$ -SiC $\\mathrm{NW_{S}}$ , CA/m-SiC $\\mathrm{NW_{S}/m}$ -BN and $\\mathrm{CA}/\\mathrm{m}$ -SiC $\\mathrm{NW_{S}/m}$ -BN/EP \n\n$\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ (Fig. 4a). As shown in Fig. 4b, the observed peak for pure CA centered at 3421, 1375, 1165 and $1053\\mathrm{cm}^{-1}$ correspond to the $-\\mathrm{OH}$ stretching vibration, –OH bending vibration, $-\\mathbf{CO}$ antisymmetric bridge stretch‑ ing vibration and $-\\mathrm{CO-C}$ vibration of pyranoid ring skel‑ eton, respectively [37, 65]. In addition, the bands at 2896 and $1425~\\mathrm{{cm}^{-1}}$ belong to the absorption peak of the –CH stretching vibration on the pyranoid ring and the branched chains, respectively. After the introduction of m-SiC $\\mathrm{NW_{S}}$ and m-BN into cellulose, their characteristic peaks succes‑ sively appeared on the infrared spectra of $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC\\NW_{S}}$ and $\\mathrm{CA/m{-}S i C/m{-}B N}$ , which corresponded to the results in Figs. 1f and 2c. Furthermore, the FT-IR spectrum of the final product $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ not only contains all the above characteristic peaks, but also adds the obvious absorption peaks of the EP matrix. The bands at 2830–3000, 1452 and $940\\mathrm{cm}^{-1}$ correspond to the stretching vibration of $-\\mathrm{CH}/\\mathrm{-CH}_{2}/\\mathrm{-CH}_{3}$ , the stretching vibration peak of benzene ring and the characteristic absorption peak of epoxy group $(-\\mathbf{CH}(\\mathbf{O})\\mathbf{CH}-)$ , respectively. It is worth mentioning that the cellulose with polyhydroxy group (inset in Fig. 4b), the $\\mathrm{\\m{-}S i C\\ N W_{S}}$ with multi-oxygen-containing functional group and $\\mathrm{m-BN}$ with $\\mathsf{N}{\\mathrm{-}}\\mathsf{H}$ group are tightly combined together relying on the hydrogen bond between these groups. Thus, a stable and continuous thermally conductive structure is formed in CA/m-SiC/m-BN/EP [66]. \n\nThe microstructure of the thermally conductive filler has a significant effect on the TC of the composite. In this work, the microstructure of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}$ is affected by the content of $\\mathrm{\\m{-}S i C\\ N W_{S}}$ and m-BN. From Fig. S2, pure cel‑ lulose presents a unique porous network structure with a pore diameter of about $10\\upmu\\mathrm{m}$ [67]. The influence of $\\mathrm{m-SiC}$ $\\mathrm{NW_{S}}$ on the overall microstructure was studied by chang‑ ing its content (0.00, 0.03, 0.06, 0.10 and $0.13{\\mathrm{~g}}{\\dot{}}$ ) when the mass of $\\mathbf{m}$ -BN in the aerogel was controlled at $\\ensuremath{1.8\\mathrm{~g~}}$ . As shown in Fig. 5a, when $\\mathrm{m{\\mathrm{-}}S i C N W_{S}}$ is not introduced, m-BN in $\\mathrm{CA}/1.8\\ \\mathrm{m}{\\bf-B}\\mathrm{N}$ is embedded on the hole wall of the CA. With the addition of $\\mathrm{\\m{-}S i C\\ N W_{S}}$ in different masses and assisted by directional freezing, the $\\mathrm{CA/m{\\cdot}S i C/m{\\cdot}}$ BN skel‑ eton presents a vertically oriented structure in the $x{-}z$ plane (Fig. 5b–d, f). Especially, when the mass of m-SiC $\\mathrm{NW_{S}}$ is $0.10\\mathrm{\\g}$ , $\\mathrm{CA}/0.10\\ \\mathrm{m}{\\cdot}\\mathrm{SiC}/1.8\\ \\mathrm{m}{\\cdot}\\mathrm{BN}$ shows a high orienta‑ tion along the ice growth direction. From the enlarged SEM image of Fig. 5e, it can be clearly seen that the m-SiC $\\mathrm{NW_{S}}$ are arranged in a vertical direction. However, as the mass of SiC NWs continues to increase to $0.13\\mathrm{~g~}$ , SiC NWs are entangled with each other to limit the vertical growth of ice crystals, resulting in a porous network structure with differ‑ ent pore sizes. \n\nThe influence of m-BN on the overall microstructure was studied by changing its content (0.0, 0.5, 1.0, 1.5 and $1.8\\:\\mathrm{g}$ ) when the mass of SiC NWs in the aerogel was controlled at $0.10\\mathrm{~g~}$ . From Fig. $5\\mathrm{g-h}$ , $\\mathrm{CA}/0.10\\ \\mathrm{m}{\\cdot}\\mathrm{SiC}$ shows a network structure of cellulose and $\\mathrm{\\m{-}S i C\\ N W_{S}}$ connected without the participation of m-BN. In order to more intuitively show the influence of different contents of m-BN on the overall mor‑ phology, the structural characterizations of $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ - BN skeleton in the $x{-}y$ plane are shown in Fig. 5i–l. It can be seen that the embedded m-BN in the cellulose increases with increasing its mass. When the mass of m-BN reaches to $1.8\\:\\mathrm{g}$ , the m-BN starts to connect to each other, which is the best content for the construction of thermal conduction path, because excessive BN will aggregate and then increase the interface thermal resistance. More importantly, combined with Fig. 5d, l, it is easy to observe that $\\mathrm{\\m{-}S i C\\ N W_{S}}$ and m-BN form a continuous thermally conductive network structure on the pore wall of CA, which is conducive to the rapid transfer of phonons between the two fillers. \n\n![](images/8436422dd6dc41052bf168d18581721289019d14e34239f82e01fb4cb52d9c6a.jpg) \nFig. 5   SEM images of CA/m-SiC $\\mathrm{NW_{S}/m}$ -BN with different contents of m-SiC $\\mathrm{NW_{S}}$ and GO and $\\mathrm{m}$ -BN. a–d and f are the section mor‑ phologies of $\\mathrm{CA}/1.8\\mathrm{~m~}$ -BN, CA/0.03 m-SiC/1.8 m-BN, CA/0.06 m-SiC/1.8 m-BN, $\\mathrm{CA}/0.10\\ \\mathrm{m}{\\cdot}\\mathrm{SiC}/1.8\\ \\mathrm{m}{\\cdot}\\mathrm{BN}$ and $\\mathrm{CA}/0.13\\ \\mathrm{m}{\\cdot}\\mathrm{SiC}/1.8\\ \\mathrm{m}{\\cdot}\\mathrm{BN}$ skeleton in $x{-}z$ plane. e is local enlarged drawing of d. g, i–l are the section morphologies of $\\mathrm{CA}/0.10\\ \\mathrm{m}{\\cdot}\\mathrm{SiC}$ , $\\mathrm{CA}/0.10\\ m{\\cdot}\\mathrm{SiC}/0.5\\ m{\\cdot}\\mathrm{BN},$ CA/0.10 m-SiC/1.0 m-BN, CA/0.10 m-SiC/1.5 m-BN and $\\mathrm{CA}/0.10\\mathrm{m}{-}\\mathrm{SiC}/1.8\\mathrm{m}{-}\\mathrm{BN}$ skeleton in x–y plane. $\\mathbf{h}$ is local enlarged drawing of g \n\nIn order to explore the influence of the microscopic morphology of the composite on the thermally conduc‑ tive properties, the morphology analysis of the EP-based composites is further carried out. As can be seen from Fig. S3a, the cross-sectional morphology of $\\mathrm{CA}/0.10\\mathrm{m}$ -SiC/EP without m-BN shows a stripe structure with single crack direction and vertical extension, and $\\mathrm{\\m{-}S i C\\ N W_{S}}$ can be evenly distributed in EP, which is attributed to their good interfacial compatibility. Similarly, from Fig. S3b, the crosssectional morphology of CA/1.8 m-BN/EP without m-SiC $\\mathrm{NW_{S}}$ shows that m-BN is uniformly distributed in EP. For the $\\mathbf{CA}/0.10\\ \\mathrm{m{-}S i C/1.8\\ m{-}B N/E P_{\\mathrm{blend}}}$ obtained by simple blending, the cross-sectional appearance has no regular and fixed orientation (Fig. S3c). For the optimal sample $\\mathrm{CA}/0.10\\ \\mathrm{m}\\mathrm{-SiC}/1.8\\ \\mathrm{m}\\mathrm{-BN}/\\mathrm{EP}$ an obvious vertical strati‑ fication can be observed (Fig. S3d). These results further confirm the successful acquisition of EP-based composites with a vertically oriented thermally conductive network. In addition, the EP can penetrate into the 3D network since the modification of the fillers enhances the interfacial interaction. Therefore, this well-arranged vertical structure can provide an efficient heat transfer channel in the direc‑ tion of the through-plane, resulting in excellent anisotropic TC [68]. \n\n# 3.3  \u0007Anisotropic Thermal Properties of CA/m‑SiC/ m‑BN/EP \n\nCombined with the thermal gravimetric analyzer, the den‑ sity and filler loadings of different samples are presented in Tables S1 and S2. Figure 6a, b presents the TC of $\\mathrm{CA}/\\mathrm{m}$ - SiC/m-BN/EP composites in both vertical plane and hori‑ zontal plane directions with different $\\mathrm{m{-}S i C N W_{S}}$ and m-BN contents. It can be seen that the TC of $\\mathrm{CA/m{-}S i C/m{-}B i}$ N/ EP and $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}_{\\mathrm{blend}}$ composites increased with increasing the content of m-SiC $\\mathrm{NW_{S}}$ and m-BN, and the existence of the unique thermally conductive network results in a significant enhancement of TC in both direc‑ tions. For example, whether it is $\\mathrm{CA}/1.8\\ \\mathrm{m}{\\cdot}\\mathrm{BN}/\\mathrm{EP}$ and $\\mathrm{CA}/0.10\\mathrm{m}{\\cdot}\\mathrm{SiC}/\\mathrm{EP}$ with a single filler, or $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{SiC}/\\mathrm{m}{\\cdot}\\mathrm{BN}/$ 1 EP with a composite filler, they all perform higher TC than pure EP $(0.22\\mathrm{~W~m~}^{-1}\\mathrm{K}^{-1})$ in both vertical plane and hori‑ zontal plane. Moreover, at a specific content of $\\mathrm{m{-}S i C N W_{S}}$ and m-BN, the TC in both planes for the composite with unique network structure is better than that of the compos‑ ites with a random dispersion [69]. It is worth noting that in Fig. 6a, the TC of the EP-based composite has basically not changed with the content of m-SiC $\\mathrm{NW_{S}}$ increased from 0.88 to $1.25~\\mathrm{wt}\\%$ (i.e., $0.10{-}0.13\\ \\mathrm{g}\\rangle$ . This is mainly attrib‑ uted to excessive $\\mathrm{m{-}S i C N W_{S}}$ which are entangled with each other (Fig. 5f) and prevent further improvement of TC. In order to visually highlight the superior thermally conductive properties of the composite under the optimal filler content, thermal conductivity enhancement (TCE) was adopted using Eq. (1) [70]: \n\n$$\n\\mathrm{TCE}=\\frac{K_{\\mathrm{c}}-K_{\\mathrm{m}}}{K_{\\mathrm{m}}}\\times100\\%\n$$ \n\nwhere $K_{\\mathrm{c}}$ and $K_{\\mathrm{m}}$ are the TC of EP-based compos‑ ites and pure EP. After calculation, the TCE of the $\\mathrm{CA}/0.10\\mathrm{m}\\mathrm{-}\\mathrm{SiC}/1.8\\mathrm{m}\\mathrm{-}\\mathrm{BN}/\\mathrm{EP}$ $(K_{\\mathrm{c}}{=}2.21\\ \\mathrm{W}\\ \\mathrm{m}^{-1}\\ \\mathrm{K}^{-1})$ com‑ posite reached $890.9\\%$ at the total filler loading of 16.69 $\\mathbf{wt}\\%$ , exhibiting excellent TC enhancement performance. In summary, the appropriate contents of m-SiC $\\mathrm{NW_{S}}$ and $\\mathrm{m-BN}$ in $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{SiC}/\\mathrm{m}$ -BN/EP are $0.88~\\mathrm{wt}\\%$ $(0.10\\ \\mathrm{g})$ and $15.81~\\mathrm{wt}\\%$ $(1.8\\:\\mathrm{g})$ , respectively. \n\nThe TC of the EP-based composites is theoretically described by classic Agari and Hashin–Shtrikman (HS) models, which are often used to test the filler distribution in the specific network. In view of the relatively low con‑ tent of m-SiC NWS (about $0.24\\mathrm{-}0.88~\\mathrm{wt}\\%$ concluded from Tables S1 and S2) in $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC/m}{-}\\mathrm{BN/EP}$ , the filler $\\mathbf{m}$ -BN contributes significantly better to the TC of the composite than $\\mathrm{m}{\\cdot}\\mathrm{SiC}$ as shown in Fig. 6a, b. Therefore, in this work, m-SiC/EP is regarded as a matrix and $\\mathrm{m-BN}$ is used as a thermally conductive filler to simplify the simulation struc‑ ture. The Agari model is shown as Eq. (2) [71]: \n\n$$\n\\log K_{\\mathrm{C}}=\\varphi C_{2}\\log K_{f}+\\left(1-\\varphi\\right)\\log\\left(C_{1}K_{\\mathrm{m}}\\right)\n$$ \n\nwhere $K_{\\mathrm{c}},K_{f}$ and $K_{\\mathrm{m}}$ represent the TC of EP-based compos‑ ites, m-BN and matrix $(\\mathrm{m-SiC/EP})$ , respectively. Here, $K_{f}$ is $350\\ \\mathrm{W\\m^{-1}\\ K^{-1}}$ in horizontal and $600\\ \\mathrm{W\\m^{-1}\\ K^{-1}}$ in the vertical direction, and $30\\mathrm{W}\\mathrm{m}^{-1}\\mathrm{K}^{-1}$ in random dispersion. $K_{\\mathrm{m}}$ is $0.35\\mathrm{~W~m~}^{-1}\\mathrm{K}^{-1}$ in horizontal and $0.52\\mathrm{~W~m~}^{-1}\\mathrm{K}^{-1}$ in the vertical direction, and $0.32\\mathrm{~W~m~}^{-1}\\mathrm{~K}^{-1}$ in random dispersion. $\\varphi$ is the weight fraction of m-BN filler. $C_{1}$ is the influence parameter of filler on the secondary structure of polymer matrix. $C_{2}$ measures how easily the filler can form a thermally conductive network [72]. From Fig. 6c, compared with $\\mathrm{CA/m\\mathrm{-}S i C/m\\mathrm{-}B N/E P_{b l e n d}}$ through a simple blending (random dispersion) method, $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/$ EP obtained by the ice template method has larger $C_{1}$ and $C_{2}$ after simulation calculation on the vertical and horizon‑ tal planes. This indicates that an ideal crystal structure and heat conduction paths are formed inside $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/$ EP [73], especially in the vertical direction. \n\nIn order to further highlight the unique vertical net structure formed inside $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC/m}{-}\\mathrm{BN/EP}$ , the Hashin–Shtrikman (HS) model is introduced as Eqs. (3, 4) [74]: \n\n$$\nK^{\\mathrm{HS+}}=K_{f}\\frac{2K_{f}+K_{\\mathrm{m}}-2\\varphi_{\\mathrm{m}}\\left(K_{f}-K_{\\mathrm{m}}\\right)}{2K_{f}+K_{\\mathrm{m}}+\\varphi_{\\mathrm{m}}\\left(K_{f}-K_{\\mathrm{m}}\\right)}\n$$ \n\n$$\nK^{\\mathrm{HS-}}=K_{m}\\frac{2K_{\\mathrm{m}}+K_{f}-2\\varphi_{\\mathrm{f}}\\big(K_{\\mathrm{m}}-K_{f}\\big)}{2K_{\\mathrm{m}}+K_{f}+\\varphi_{\\mathrm{f}}\\big(K_{\\mathrm{m}}-K_{f}\\big)}\n$$ \n\nwhere the $K^{\\mathrm{HS+}}$ (upper boundary) refers to the matrix that is completely surrounded by filler; $K^{\\mathrm{HS+}}$ (lower boundary) indicates that the fillers are completely separated by matrix. $K_{f}$ and $K_{\\mathrm{m}}$ represent the TC of m-BN and matrix $(\\mathrm{m-SiC}/\\$ EP), In that case, $K_{f}$ takes a value of 600 W $\\mathbf{m}^{-1}\\mathbf{K}^{-1}$ and $K_{\\mathrm{m}}$ takes a value of 0.52 W $\\mathbf{m}^{-1}~\\mathbf{K}^{-1}$ . $\\varphi_{\\mathrm{m}}$ and $\\varphi_{\\mathrm{f}}$ are the weight fraction of matrix and filler. Figure 6d presents the simulation results of anisotropic TC in accordance with HS model. Obviously, the measured TC stays between the upper and lower boundaries, which meets the fitting result of the HS model. The appearance of the approximate logarithmic fitting curve of the $\\mathrm{HS}+$ upper boundary shows that the construction of the heat conduction paths in this experiment can achieve a greater impact on the overall TC with a low m-BN content. \n\n![](images/f1fa1b391e31f68b73d603d3417167d17d44e7dea1341ff9e5cc26757c531bdd.jpg) \nFig. 6   Anisotropic thermal properties analysis of $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ -BN/EP. a Thermal conductivities and thermal conductivity enhancements of ${\\mathrm{CA}}/{\\mathrm{m}}{\\mathrm{-SiC}}/{\\mathrm{m}}{\\mathrm{-}}$ -BN/EP and $\\mathrm{CA/m{-}S i C/m{-}B N/E P_{\\mathrm{blend}}}$ composites with different m-SiC $\\mathrm{NW_{S}}$ contents at the m-BN mass of $1.8\\ \\mathrm{g}$ . b Thermal con‑ ductivities and thermal conductivity enhancements of $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{SiC}/\\mathrm{m}$ -BN/EP and $\\mathrm{CA/m{-}S i C/m{-}B N/E P_{\\mathrm{blend}}}$ composites with different m-BN con‑ tents at the m-SiC $\\mathrm{NW_{S}}$ mass of $0.10\\mathrm{\\g}$ . c Agari model fitting lines, d Hashin–Shtrikman (HS) model fitting lines, e EMT model fitting lines and f Foygel’s theory fitting lines of $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{SiC}/\\mathrm{m}$ -BN/EP and $\\mathrm{CA/m{-}S i C/m{-}B N/E P_{\\mathrm{blend}}}$ composites \n\nIn practical application, the interfacial thermal resistance between the filler/matrix and filler/filler in the thermally con‑ ductive composites is the key factor affecting the heat transfer process [26]. Therefore, the effective medium theory (EMT) and the Foygel theory are used to model and analyze the inter‑ facial thermal resistance in the samples. EMT is used to fit the relationship between the interface thermal resistance from filler/matrix and the TC as shown in Eq. (5) [75]: \n\n$$\nK_{\\mathrm{c}}=K_{\\mathrm{m}}+{\\frac{a\\varphi_{\\mathrm{f}}K_{\\mathrm{m}}}{3{\\Big(}a+{\\frac{R_{\\mathrm{iur}}K_{f}}{L}}{\\Big)}}}\n$$ \n\nwhere $K_{\\mathrm{c}},K_{f}$ and $K_{\\mathrm{m}}$ are the TC of composite, $\\mathrm{m-BN}$ and matrix (m-SiC/EP), respectively. $\\varphi_{\\mathrm{f}}$ is the weight fraction of m-BN, $R_{\\mathrm{itr}}$ is the interfacial thermal resistance at m-BN/ matrix interface, $L$ and $a$ are the average diameter length and diameter-thickness ratio of $\\mathrm{m-BN}$ , respectively. The corresponding fitting results are shown in Fig. 6e and the values of $R_{\\mathrm{itr}}$ for $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ in both vertical and horizontal directions and randomly dispersed $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ 一 $\\mathbf{BN/EP_{blend}}$ composites are $1.48\\times10^{-6}$ , $4.67\\times10^{-6}$ , and $5.55\\times10^{-6}\\mathrm{m}^{2}\\mathrm{KW}^{-1}$ , respectively. This result clearly proves that the successful modification of m-BN enhanced its inter‑ action with the matrix. In addition, $R_{\\mathrm{itr}}$ in vertical direction is lower than horizontal direction, which indicates that m-BN can also be tightly bonded to $\\mathrm{\\m-SiC}$ (as the matrix) in the vertical direction. \n\nThe Foygel model is applied to simulates and calculate the thermal boundary resistance between fillers, as shown by Eqs. (6, 7) [76]: \n\n$$\nK_{\\mathrm{c}}=K_{\\mathrm{m}}+K_{0}\\Bigg[\\frac{\\varphi_{\\mathrm{f}}-\\varphi_{\\mathrm{c}}}{1-\\varphi_{\\mathrm{c}}}\\Bigg]^{\\beta}\n$$ \n\n$$\nR_{\\mathrm{Bd}}=\\frac{1}{K_{\\mathrm{0}}L\\big(\\varphi_{\\mathrm{c}}\\big)^{\\beta}}\n$$ \n\nwhere $K_{\\mathrm{c}}$ and $K_{\\mathrm{m}}$ are the TC of composite and matrix, $K_{0}$ is a pre-exponential factor related to the filler. $\\varphi_{\\mathrm{f}}$ is the weight fraction of m-BN, $\\varphi_{\\mathrm{c}}$ is the critical permeability content of the filler, $L$ is the average diameter length of m-BN, $\\upbeta$ is related to the conductivity index of the filler, and $R_{\\mathrm{Bd}}$ is the thermal boundary resistance at filler/filler interface. It can be seen from Fig. 6f that the $R_{\\mathrm{Bd}}$ of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ in vertical direction is as low as $8.31\\times10^{-7}\\mathrm{m}^{2}{\\cdot}\\mathrm{K}/\\mathrm{W}.$ , which is nearly one order of magnitude lower than the results of hori‑ zontal direction $(2.94\\times10^{-6}\\mathrm{m}^{2}\\mathrm{K}\\mathrm{W}^{-1})$ and random distri‑ bution $(4.65\\times10^{-6}\\mathrm{m}^{2}\\mathrm{K}\\mathrm{W}^{-1})$ . Furthermore, the appearance of an approximate exponential fitting curve in the vertical direction indicates that m-BN is arranged in an orderly man‑ ner and no stacking occurs in this direction. This further confirmed the advantages of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ with high-speed heat conduction channel in the vertical direction. \n\nTo demonstrate the advantage of $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{SiC}/\\mathrm{m}$ -BN/EP obtained in this work in terms of thermally conductive per‑ formance, a comparison with previous similar studies is shown in Table S3. After comprehensive comparison, the $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC/m}{-}\\mathrm{BN/EP}$ exhibits the excellent TC at low con‑ tent among the reported bulk composites. \n\nInfrared thermal imager was used to intuitively estimate the thermal management capability of different EP-based composites. Specifically, as shown in Fig. 7a, different sam‑ ples with a diameter of $2\\mathrm{cm}$ and a thickness of $3\\ \\mathrm{mm}$ are placed simultaneously on a hot plate set at $80~^{\\circ}\\mathrm{C}$ , and then, the infrared thermal imager is used to record the surface temperature changes over time. In order to verify that the TC of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC/m}{-}\\mathrm{BN/EP}$ is anisotropic in two directions, the custom metal bases are used as the point heat source for the sample in the experimental design. It is worth noting that two test points A and B are selected on the sample surface during the experiment, as shown in Fig. 7b; point A is used to test the temperature change of the sample center with the point heat source in the vertical direction, while point B is used to reflect the thermal conduction capability of the sample in the horizontal direction. It is found that the sur‑ face temperature of different samples in the following order: $\\mathrm{CA/m-SiC/m-BN/EP}>\\mathrm{CA/m-SiC/m-BN/EP_{\\blend}>C A/m-}$ ${\\mathrm{BN/EP}}{>}{\\mathrm{CA/m}}{\\mathrm{-}}{\\mathrm{SiC/EP}}{>}{\\mathrm{EP}}.$ , this result is consistent with the order of TC obtained in Fig. 6a, b. Obviously, the surface temperature of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC/m}{-}\\mathrm{BN/EP}$ at point A shows a fast‑ est increasing with time compared to other samples. The specific temperature change with time of point A recorded by a computer is shown in Fig. 7c. After $120\\mathrm{~s~}$ , the center temperature of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{E}$ P is as high as $76.7^{\\circ}\\mathrm{C}$ which is close to the temperature of hot plate. Not only that, as shown in Fig. 7d, the sample $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC/m}{-}\\mathrm{BN/EP}$ also showed excellent heat transfer efficiency at point B close to the edge (the temperature is about $67.2^{\\circ}\\mathrm{C}$ after 120 s), which shows that $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ has high thermal conductivity along both vertical and horizontal directions, thereby forming a heat dissipation area with a larger radius [77]. \n\n# 3.4  \u0007Thermal Conduction Mechanism of Different EP‑Based Composites \n\nAccording to the morphology characterization and TC test results of different samples, the heat flow transmission path can be reasonably simulated. In addition, the packaging material is generally coated on the surface of the micro‑ electronic device, so here we focus on the comparison and analysis of the thermally conductive mechanism of different samples in the vertical direction. As we all know, phonons are the collective modulus of the vibrations of mutually cou‑ pled atomic lattice systems and are the main thermal energy carriers of polymer-based materials. Therefore, constructing efficient phonon transport channel is the key to improve the TC of thermal interface composites. As shown in Fig. 8, for CA/m-SiC/EP and CA/m-BN/EP with a single filler, the phonon transmission channel mainly relies on the vertically oriented m-SiC NWs and m-BN network structures, respec‑ tively. Since the in-plane TC of BN $(600~\\mathrm{W~m^{-1}~K^{-1}})$ )) is higher than the in-line thermal conductivity of m-SiC NWs $(100\\mathrm{~W~m^{-1}~K^{-1}})$ , $\\mathrm{CA}/\\mathrm{m}$ -BN/EP exhibits a faster heat flow transfer rate. At the optimal filler content, the TC of CA/m$\\mathrm{SiC/m{\\cdot}B N/E P_{\\mathrm{blend}}}$ with dual fillers randomly dispersed is higher than that of CA/m-BN/EP and CA/m-SiC/EP, which is mainly due to the fact that more phonon transmission paths can be formed inside the structure of $\\mathbf{CA}/\\mathbf{m}{\\cdot}\\mathbf{SiC}/\\mathbf{m}.$ - $\\mathbf{BN/EP_{blend}}$ [78]. When m-SiC NWs and m-BN form a syn‑ ergistic vertical network structure in $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}.$ -BN/EP, resulting in a faster heat flow transfer compared to other samples. Hence, the vertically aligned networks composed of interconnected m-SiC NWs and m-BN heat conductive paths play a critical role in the phonon transmission, which can significantly improve the TC of the composite in the vertical direction [79]. \n\n![](images/5819c8c085ce821f62c31fc88ce0718f3a8979dcc01b2c10e97b0b3dae3f8efd.jpg) \nFig. 7   a Optical photographs of different EP-based composites and schematic design for thermal imaging test. b Infrared thermal images of dif‑ ferent EP-based composites variation with heating time and $\\mathbf{c-d}$ the temperature changes of A and B on the surface of EP-based composites with heating time \n\n![](images/0d8cfdcb3ea53ad99cbec274cd50db0663ee9a244a60f607b0661161c2a5e569.jpg) \nFig. 8   Schematic diagram of heat flow of different EP-based composites along the vertical direction \n\n# 3.5  \u0007Electrical Insulative Properties of Different EP‑Based Composites \n\nElectrical insulation is the basic feature of electronic pack‑ aging materials [4]. During the experiment, conductive glue was applied on both sides of the tested sample and the experimental results are shown in Fig. 9. It can be seen that compared with pure EP $(8.97\\times10^{14}~\\Omega{\\cdot}\\mathrm{cm})$ , the resistiv‑ ity of ${\\mathrm{CA/m}}{\\mathrm{\\cdot}}{\\mathrm{SiC/EP}}$ $\\left(8.87\\times10^{8}\\Omega{\\cdot}\\mathrm{cm}\\right)$ decreases sharply, while the resistivity of $\\mathrm{CA/m{\\cdot}B N/E P}$ $(9.47\\times10^{15}\\Omega{\\cdot}\\mathrm{cm})$ ) increases slightly, which is mainly attributed to the linear semiconductor characteristics of $\\mathrm{m{-}S i C\\ N W_{S}}$ and the high electrical insulation of BN [80]. For the $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/$ $\\mathrm{EP_{blend}}$ obtained by random dispersion, there is no consist‑ ent linear direction despite the participation of $\\mathrm{\\m{-}S i C\\ N W_{S}}$ , so its resistivity is mainly influenced by EP, which is about $2.42\\times10^{13}\\Omega{\\cdot}\\mathrm{cm}$ . It is worth mentioning that the resistivity of $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ $(2.35\\times10^{11}\\Omega{\\cdot}\\mathrm{cm})$ with a vertical network structure decreases compared with that of pure EP and $\\mathrm{CA/m\\mathrm{-}S i C/m\\mathrm{-}B N/E P_{\\mathrm{blend}}}$ , but it is much higher than the theoretical critical resistivity $(10^{10}\\Omega{\\cdot}\\mathrm{cm})$ [25], com‑ bined with the high resistivity value of $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{BN}/\\mathrm{EP}$ , this is mainly due to the high insulation of $\\mathrm{m-BN}$ playing an important role in this special structure. It is convinced that the thermal management composite CA/m-SiC/m-BN/EP obtained in this work has a great potential for application in the field of microelectronic packaging. \n\n![](images/9cdfc57f1b14a05f517b5e3a1ea696edb3847561620df136fece9c4625cd5856.jpg) \nFig. 9   The volume resistivity of pure EP and different EP-based composites in the vertical direction \n\n# 3.6  \u0007Dielectric and Electromagnetic Wave Absorption Performances of Different Samples \n\nSiC NWs are a very important wide-bandgap semiconduc‑ tor material and have a high dielectric loss capability, so it shows excellent electromagnetic wave absorption potential [81]. In addition, EP with high resistivity $(8.97\\times10^{14}\\Omega{\\cdot}\\mathrm{cm})$ has almost no dielectric response, so the electromagnetic wave absorption capacity of different EP-based compos‑ ites (CA/m-BN/EP, ${\\mathrm{CA/m}}{\\cdot}{\\mathrm{SiC/EP}}$ and $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}$ / EP) mainly depends on the composition and structural framework of the internal filler. Generally speaking, the electromagnetic wave absorption capacity of non-magnetic dielectric materials is directly determined by the real $(\\varepsilon^{\\prime})$ and imaginary $(\\varepsilon^{\\prime\\prime})$ parts of the complex permittivity, $\\varepsilon^{\\prime}$ and $\\varepsilon^{\\prime\\prime}$ represent the ability to store and dissipate electromag‑ netic waves, respectively [82, 83]. The obtained $\\varepsilon^{\\prime}$ , $\\varepsilon^{\\prime\\prime}$ and the corresponding dielectric loss tangents (tan $\\delta_{\\varepsilon}=\\varepsilon^{\\prime\\prime}/\\varepsilon^{\\prime}$ ) are displayed in Fig. 10a–c. According to dielectric theory, the dielectric loss parameter $\\varepsilon^{\\prime}$ for dielectric materials, while $\\varepsilon^{\\prime\\prime}$ is attributed to the electrical conductivity. And the fast movement of electrons in high-conductivity fillers can also promote polarization. Based on the conductivity of $\\mathrm{m-SiC}$ is much higher than that of insulating m-BN, therefore, the CA/m-BN/EP exhibits low $\\varepsilon^{\\prime},\\varepsilon^{\\prime\\prime}$ , and tanδ values, namely, 2.6–3.3, 0.8–1.3, and 0.3–0.4, respectively. Compared with $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{BN}/\\mathrm{EP}$ , the $\\varepsilon^{\\prime},\\varepsilon^{\\prime\\prime}$ , and tan $\\delta_{\\varepsilon}$ values of $\\mathrm{CA}/\\mathrm{m}{\\cdot}\\mathrm{SiC}/$ EP show significant enhancement to 8.5–9.9, 7.0–7.3, and 0.7–0.8, respectively. In addition, tan $\\delta_{\\varepsilon}$ indicates the abil‑ ity of material to convert electromagnetic waves into other forms of energy (most of which are converted into heat), thereby achieving the dissipation of microwave energy, and a high tan $\\delta_{\\varepsilon}$ value indicates the strong ability to absorb electromagnetic waves [84]. It can be seen from Fig. 10c that $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ BN/EP not only has excellent microwave absorption capacity, but also it can convert the absorbed electromagnetic wave energy into heat for effective evacua‑ tion through the vertical heat conduction paths according to the aforementioned analysis of thermally conductive prop‑ erties [85]. \n\nTo evaluate the microwave absorption properties of differ‑ ent composites, the reflection loss (RL) values were calcu‑ lated according to the transmit line theory by the following Eqs. (8, 9) [86]: \n\n$$\n\\mathrm{RL}=20\\log{\\left|\\frac{Z_{\\mathrm{in}}-1}{Z_{\\mathrm{in}}+1}\\right|}\n$$ \n\n$$\nZ_{\\mathrm{in}}=\\sqrt{\\mu_{r/_{\\varepsilon_{r}}}}\\operatorname{tanh}\\left[j\\left(\\frac{2\\pi f d}{c}\\right)\\left(\\sqrt{\\mu_{r}\\varepsilon_{r}}\\right)\\right]\n$$ \n\n![](images/69d65f2ce05d6a148996da3729b06d68767dcdf03a22e106b0038374fc0234bd.jpg) \nFig. 10   a Real parts and b imaginary parts of the complex permittivities. c dielectric loss tangents and d reflection loss of the CA/m-SiC/EP, CA/m-BN/EP and CA/m-SiC/m-BN/EP \n\nwhere $Z_{\\mathrm{in}}$ is the input impedances of the composite, $\\mu_{r}$ and $\\varepsilon_{r}$ denote the complex permeability and complex permittiv‑ ity, respectively, $f$ represents the frequency of microwaves, $d$ refers to the thickness of the composites and $c$ is the velocity of light in vacuum. \n\nFigure 10d shows the electromagnetic wave reflection loss curve of the three systems with a thickness of $3\\mathrm{mm}$ . For the $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ , the minimum reflection loss is $-21.5{\\mathrm{~dB}}$ at $10.4~\\mathrm{GHz}$ , and the effective absorption bandwidth $(<-10~\\mathrm{dB})$ is from 8.8 to $11.6\\:\\mathrm{GHz}$ . Accord‑ ing to Maxwell–Wagner polarization theory, this is mainly attributed to the vertical network structure formed by CA/m$\\mathrm{SiC/m\\mathrm{-}B N}$ in composite, which not only strengthens the effective interface (between $\\mathrm{\\m-SiC}$ and m-BN) of interfa‑ cial polarization, but also enhances the microwave reflec‑ tion paths [87]. In order to verify the excellent microwave absorption properties of the composites, the impedance matching between the materials and the incident micro‑ waves was further explored. From Fig. S4, compared with CA/m-BN/EP, the microwave impedance of CA/m-SiC/EP and $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ -BN/EP increases greatly because of their lower complex permittivity. In addition, $\\mathrm{CA/m{-}S i C/m{-}B N}$ / EP exhibits better microwave absorption performance than CA/m-SiC/EP due to higher microwave impedance and almost the same dielectric loss. \n\n# 4  \u0007Conclusions \n\nIn summary, vertically aligned m-SiC NWs/m-BN cellulose aerogel $(\\mathbf{CA}/\\mathbf{m}{-}\\mathbf{SiC}/\\mathbf{m-BN})$ networks have been success‑ fully constructed by ice template combined with directional freezing technology. CA/m-SiC/m-BN/EP composites were prepared by infiltrating the vertical networks with EP. In particular, the high-temperature calcination treatment of SiC NWs and the combined boric acid ball milling modification of BN not only improve the compatibility between the filler and matrix, but also reduce the thermal boundary resistance between the filler and filler, thereby effectively improving the thermal conductivity of the composite material. The $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}$ composites exhibit a significantly enhanced TC of $2.21\\mathrm{~W~m~}^{-1}\\mathrm{K}^{-1}$ in vertical plane at a low filler loading of $16.69~\\mathrm{wt}\\%$ , which is increased by $890\\%$ compared to pure EP. In addition, from the analysis results of infrared thermal imaging, it is found that $\\mathrm{CA/m}{\\cdot}\\mathrm{SiC/m}{\\cdot}$ 一 BN/EP in the horizontal direction also exhibits a better thermally conductive performance than pure EP, $\\mathrm{CA}/\\mathrm{m}\\cdot$ - SiC/EP, CA/m-BN/EP and $\\mathrm{CA}/\\mathrm{m}{-}\\mathrm{SiC}/\\mathrm{m}{-}\\mathrm{BN}/\\mathrm{EP}_{\\mathrm{blend}}$ with random dispersion. Furthermore, CA/m-SiC/m-BN/EP also has a superior volume resistivity of $2.35\\times10^{11}\\Omega{\\cdot}\\mathrm{cm}$ and a minimum reflection loss of − 21.5 dB. Therefore, the new EP-based composite synthesized in this work will have good application prospects in the fields of electronic packaging. \n\nAcknowledgements  We acknowledge for the financial support from National Natural Science Foundation of China (21704096, 51703217) and the China Postdoctoral Science Foundation (Grant No. 2019M662526). The authors also gratefully acknowledge financial support from Taif University Researchers Supporting Project Number (TURSP-2020/135), Taif University, Taif, Saudi Arabia. \n\nFunding  Open access funding provided by Shanghai Jiao Tong University. \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Com‑ mons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Com‑ mons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\nSupplementary Information  The online version contains supplementary material available at https://​doi.​org/​10.​1007/ s40820-​022-​00863-z. \n\n# References \n\n1.\t Y. Lin, Q. Kang, H. Wei, H. Bao, P. Jiang et al., Spider webinspired graphene skeleton-based high thermal conductivity phase change nanocomposites for battery thermal manage‑ ment. Nano-Micro Lett. 13, 180 (2021). https://​doi.​org/​10. 1007/​s40820-​021-​00702-7 \n2.\t F. Chen, H. Xiao, Z.Q. Peng, Z.P. Zhang, M.Z. Rong et al., Thermally conductive glass fiber reinforced epoxy composites with intrinsic self-healing capability. Adv. Compos. Hybrid Mater. 4(4), 1048–1058 (2021). https://​doi.​org/​10.​1007/ s42114-​021-​00303-3 \n3.\t D. Pan, Q. Li, W. Zhang, J. Dong, F. Su et al., Highly thermal conductive epoxy nanocomposites filled with 3D BN/C spatial network prepared by salt template assisted method. Compos. Part B 209, 108609 (2021). https://​doi.​org/​10.​1016/j.​compo​ sitesb.​2021.​108609 \n4.\t Y. Zhao, M. Niu, F. Yang, Y. Jia, Y. Cheng, Ultrafast electrothermal responsive heating film fabricated from graphene modified conductive materials. Eng. Sci. 8, 33–38 (2019). https://​doi.​org/​10.​30919/​es8d5​01 \n5.\t M. Aleksandrova, C. Jagtap, V. Kadam, S. Jadkar, G. Kolev et al., An overview of microelectronic infrared pyroelectric detector. Eng. Sci. 16, 82–89 (2021). https://​doi.​org/​10.​30919/ es8d5​35 \n6.\t D. Pan, F. Su, C. Liu, Z. Guo, Research progress for plastic waste management and manufacture of value-added products. Adv. Compos. Hybrid Mater. 3(4), 443–461 (2020). https:// doi.​org/​10.​1007/​s42114-​020-​00190-0 \n7.\t Y. Kong, Y. Li, G. Hu, N. Cao, Y. Ling et al., Effects of poly‑ styrene-b-poly(ethylene/propylene)-b-polystyrene compatibi‑ lizer on the recycled polypropylene and recycled high-impact polystyrene blends. Polym. Adv. Technol. 29(8), 2344–2351 (2018). https://​doi.​org/​10.​1002/​pat.​4346 \n8.\t J.C.M. Neto, N.R. Nascimento, R.H. Bello, L.A. Verçosa, J.E. Neto et al., Kaolinite review: intercalation and production of polymer nanocomposites. Eng. Sci. 17, 28–44 (2022). https://​ doi.​org/​10.​30919/​es8d4​99 \n9.\t J. Tu, H. Li, J. Zhang, D. Hu, Z. Cai et al., Latent heat and thermal conductivity enhancements in polyethylene glycol/ polyethylene glycol-grafted graphene oxide composites. Adv. Compos. Hybrid Mater. 2(3), 471–480 (2019). https://​doi.​org/​ 10.​1007/​s42114-​019-​00083-x \n10.\t D. Pan, F. Su, H. Liu, C. Liu, A. Umar et al., Research progress on catalytic pyrolysis and reuse of waste plastics and petro‑ leum sludge. ES Mater. Manuf. 11, 3–15 (2021). https://​doi. org/​10.​30919/​esmm5​f415 \n11.\t P. Hu, L. Liu, M. Zhao, J. Wang, X. Ma et al., Design, synthe‑ sis, and use of high temperature resistant aerogels exceeding $800~^{\\circ}\\mathrm{C}$ . ES Mater. Manuf. 15, 14–33 (2021). https://​doi.​org/ 10.​30919/​esmm5​f459 \n12.\t J. Gu, K. Ruan, Breaking through bottlenecks for thermally conductive polymer composites: a perspective for intrinsic thermal conductivity, interfacial thermal resistance and theo‑ retics. Nano-Micro Lett. 13, 110 (2021). https://​doi.​org/​10. 1007/​s40820-​021-​00640-4 \n13.\t O.M. Atta, S. Manan, M. Ul-Islam, A.A.Q. Ahmed, M.W. Ullah et al., Silver decorated bacterial cellulose nanocom‑ posites as antimicrobial food packaging materials. ES Food Agrof. 6, 12–26 (2021). https://​doi.​org/​10.​30919/​esfaf​590 \n14.\t G. Yang, X. Zhang, D. Pan, W. Zhang, Y. Shang et al., Highly thermal conductive poly(vinyl alcohol) composites with ori‑ ented hybrid networks: silver nanowire bridged boron nitride nanoplatelets. ACS Appl. Mater. Interfaces 13(27), 32286– 32294 (2021). https://​doi.​org/​10.​1021/​acsami.​1c084​08 \n15.\t H. Cheng, Z. Lu, Q. Gao, Y. Zuo, X. Liu et al., PVDF-Ni/PECNTs composite foams with co-continuous structure for elec‑ tromagnetic interference shielding and photo-electro-thermal properties. Eng. Sci. 16, 331–340 (2021). https://​doi.​org/​10. 30919/​es8d5​18 \n16.\t S.H. Khan, B. Pathak, M.H. Fulekar, A study on the influence of metal (Fe, Bi, and Ag) doping on structural, optical, and antimicrobial activity of $Z\\mathrm{nO}$ nanostructures. Adv. Compos. Hybrid Mater. 3(4), 551–569 (2020). https://​doi.​org/​10.​1007/​ s42114-​020-​00174-0 \n17.\t S. Chen, J. Liu, Liquid metal enabled unconventional heat and flow transfer. ES Energy Environ. 5, 8–21 (2019). https://​doi. org/​10.​30919/​esee8​c318 \n18.\t X. He, D. Ou, S. Wu, Y. Luo, Y. Ma et al., A mini review on factors affecting network in thermally enhanced polymer composites: filler content, shape, size, and tailoring methods. Adv. Compos. Hybrid Mater. 5, 21–38 (2022). https://​doi.​org/​ 10.​1007/​s42114-​021-​00321-1 \n19.\t D. Pan, F. Su, H. Liu, Y. Ma, R. Das et al., The properties and preparation methods of different boron nitride nano‑ structures and applications of related nanocomposites. Chem. Rec. 20(11), 1314–1337 (2020). https://​doi.​org/​10. 1002/​tcr.​20200​0079 \n20.\t L. Deng, X. Wang, X. Hua, S. Lu, J. Wang et al., Purifica‑ tion of $\\upbeta$ -SiC powders by heat treatment in vacuum. Adv. Compos. Hybrid Mater. 3(2), 177–186 (2020). https://​doi.​ org/​10.​1007/​s42114-​021-​00372-4 \n21.\t H. Han, H. Sun, F. Lei, J. Huang, S. Lyu et  al., Flexible ethylene-vinyl acetate copolymer/fluorographene composite films with excellent thermal conductive and electrical insu‑ lation properties for thermal management. ES Mater. Manuf. 15, 53–64 (2022). https://​doi.​org/​10.​30919/​esmm5​f523 \n22.\t Y. Hui, W. Xie, H. Gu, Reduced graphene oxide/nanocel‑ lulose/amino-multiwalled carbon nanotubes nanocomposite aerogel for excellent oil adsorption. ES Food Agrofor. 5, 38–44 (2021). https://​doi.​org/​10.​30919/​esfaf​531 \n23.\t D. Pan, X. Zhang, G. Yang, Y. Shang, F. Su et al., Thermally conductive anticorrosive epoxy nanocomposites with tannic acid-modified boron nitride nanosheets. Ind. Eng. Chem. Res. 59(46), 20371–20381 (2020). https://​doi.​org/​10.​1021/​ acs.​iecr.​0c045​10 \n24.\t H. Yan, X. Dai, K. Ruan, S. Zhang, X. Shi et al., Flexible thermally conductive and electrically insulating silicone rubber composite films with $\\mathbf{BNNS}\\ @\\mathbf{Al}_{2}\\mathbf{O}_{3}$ fillers. Adv. Compos. Hybrid Mater. 4(1), 36–50 (2021). https://​doi.​org/ 10.​1007/​s42114-​021-​00208-1 \n25.\t Y. Zhou, F. Liu, C.Y. Chen, Use of BN-coated cop‑ per nanowires in nanocomposites with enhanced ther‑ mal conductivity and electrical insulation. Adv. Compos. Hybrid Mater. 2(1), 46–50 (2019). https://​doi.​org/​10.​1007/​ s42114-​019-​00077-9 \n26.\t S. Wang, X. Lu, A. Negi, J. He, K. Kim et al., Revisiting the reduction of thermal conductivity in nano- to micro-grained bismuth telluride: the importance of grain-boundary thermal resistance. Eng. Sci. 17, 45–55 (2022). https://​doi.​org/​10. 30919/​es8d5​13 \n27.\t C.P. Feng, L. Bai, R.Y. Bao, Z.Y. Liu, M.B. Yang et  al., Electrically insulating POE/BN elastomeric composites with high through-plane thermal conductivity fabricated by two-roll milling and hot compression. Adv. Compos. Hybrid Mater. 1(1), 160–167 (2018). https://​doi.​org/​10.​1007/​ s42114-​017-​0013-2 \n28.\t D. Pan, J. Dong, G. Yang, F. Su, B. Chang et al., Ice tem‑ plate method assists in obtaining carbonized cellulose/boron nitride aerogel with 3D spatial network structure to enhance the thermal conductivity and flame retardancy of epoxy-based composites. Adv. Compos. Hybrid Mater. 5, 58–70 (2022). https://​doi.​org/​10.​1007/​s42114-​021-​00362-6 \n29.\t G. Yang, X. Zhang, Y. Shang, P. Xu, D. Pan et al., Highly thermally conductive polyvinyl alcohol/boron nitride nano‑ composites with interconnection oriented boron nitride nano‑ platelets. Compos. Sci. Technol. 201, 108521 (2021). https:// doi.​org/​10.​1016/j.​comps​citech.​2020.​108521 \n30.\t Y. Wu, Y. Xue, S. Qin, D. Liu, X. Wang et al., BN nanosheet/ polymer films with highly anisotropic thermal conductivity for thermal management applications. ACS Appl. Mater. Inter‑ faces 9(49), 43163–43170 (2017). https://​doi.​org/​10.​1021/ acsami.​7b152​64 \n31.\t C. Xiao, Y. Guo, Y. Tang, J. Ding, X. Zhang et al., Epoxy composite with significantly improved thermal conductivity by constructing a vertically aligned three-dimensional network of silicon carbide nanowires/ boron nitride nanosheets. Compos. Part B 187, 107855 (2020). https://​doi.​org/​10.​1016/j.​compo​ sitesb.​2020.​107855 \n32.\t Y. Xie, Y. Yang, Y. Liu, S. Wang, X. Guo et  al., Paraffin/ polyethylene/graphite composite phase change materials with enhanced thermal conductivity and leakage-proof. Adv. Com‑ pos. Hybrid Mater. 4(3), 543–551 (2021). https://​doi.​org/​10. 1007/​s42114-​021-​00249-6 \n33.\t J. Sun, X. Zhang, Q. Du, V. Murugadoss, D. Wu et al., The contribution of conductive network conversion in thermal con‑ ductivity enhancement of polymer composite: a theoretical and experimental study. ES Mater. Manuf. 13, 53–65 (2021). https://​doi.​org/​10.​30919/​esmm5​f450 \n34.\t X. Chen, J.S.K. Lim, W. Yan, F. Guo, Y.N. Liang et al., Salt template assisted BN scaffold fabrication toward highly ther‑ mally conductive epoxy composites. ACS Appl. Mater. Inter‑ faces 12(14), 16987–16996 (2020). https://​doi.​org/​10.​1021/ acsami.​0c048​82 \n35.\t W. Zhou, Y. Zhang, J. Wang, H. Li, W. Xu et  al., Light‑ weight porous polystyrene with high thermal conductivity by constructing 3D interconnected network of boron nitride nanosheets. ACS Appl. Mater. Interfaces 12(41), 46767– 46778 (2020). https://​doi.​org/​10.​1021/​acsami.​0c115​43 \n36.\t F. Xu, D. Bao, Y. Cui, Y. Gao, D. Lin et al., Copper nanoparti‑ cle-deposited graphite sheets for highly thermally conductive polymer composites with reduced interfacial thermal resist‑ ance. Adv. Compos. Hybrid Mater. (2021). https://​doi.​org/​10. 1007/​s42114-​021-​00367-1 \n37.\t P. Song, B. Liu, C. Liang, K. Ruan, H. Qiu et  al., Light‑ weight, flexible cellulose-derived carbon aerogel@reduced graphene oxide/pdms composites with outstanding EMI shielding performances and excellent thermal conductivi‑ ties. Nano-Micro Lett. 13, 91 (2021). https://​doi.​org/​10.​1007/​ s40820-​021-​00624-4 \n38.\t H. Gu, C. Gao, X. Zhou, A. Du, N. Naik et al., Nanocellulose nanocomposite aerogel towards efficient oil and organic sol‑ vent adsorption. Adv. Compos. Hybrid Mater. 4(3), 459–468 (2021). https://​doi.​org/​10.​1007/​s42114-​021-​00289-y \n39.\t Y. Zhang, Y. Luo, Naturally derived nanomaterials for multi‑ disciplinary applications and beyond. ES Food Agrof. 4, 1–2 (2021). https://​doi.​org/​10.​30919/​esfaf​484 \n40.\t Z. Zhuang, W. Wang, Y. Wei, T. Li, M. Ma et al., Prepara‑ tion of polyaniline nanorods/manganese dioxide nanoflowers core/shell nanostructure and investigation of electrochemical performances. Adv. Compos. Hybrid Mater. 4(4), 938–945 (2021). https://​doi.​org/​10.​1007/​s42114-​021-​00225-0 \n41.\t Y. Tong, W. Zhao, W. Wu, D. Zhang, G. He et al., Realizing enhanced dielectric and mechanical performance of polyvi‑ nylidene fluoride/SiC nanocomposites through a bio-inspired interface design. Adv. Compos. Hybrid Mater. 5(1), 263–277 (2022). https://​doi.​org/​10.​1007/​s42114-​021-​00333- $\\mathbf{\\nabla}\\cdot\\mathbf{x}$ \n42.\t K. Kim, H. Ju, J. Kim, Vertical particle alignment of boron nitride and silicon carbide binary filler system for thermal conductivity enhancement. Compos. Sci. Technol. 123, 99–105 (2016). https://​doi.​org/​10.​1016/j.​comps​citech.​2015.​ 12.​004 \n43.\t X. Zhang, Applications of kinetic methods in thermal analysis: a review. Eng. Sci. 14, 1–13 (2021). https://​doi.​org/​10.​30919/​ es8d1​132 \n44.\t C. Liang, Y. Du, Y. Wang, A. Ma, S. Huang et al., Intumescent fire-retardant coatings for ancient wooden architectures with ideal electromagnetic interference shielding. Adv. Compos. Hybrid Mater. 4(4), 979–988 (2021). https://​doi.​org/​10.​1007/ s42114-​021-​00274-5 \n45.\t Y. Zhou, J. Zhang, C. Qu, L. Li, J. Kong et al., Synchronously improved wave-transparent performance and mechanical properties of cyanate ester resins via introducing fluorinecontaining linear random copolymer. Adv. Compos. Hybrid Mater. 4(4), 1166–1175 (2021). https://​doi.​org/​10.​1007/ s42114-​021-​00349-3 \n46.\t W. Wang, X. Deng, D. Liu, F. Luo, H. Cheng et al., Broadband radar-absorbing performance of square-hole structure. Adv. Compos. Hybrid Mater. 5, 525–535 (2022). https://​doi.​org/ 10.​1007/​s42114-​021-​00376-0 \n47.\t F. Luo, D. Liu, T. Cao, H. Cheng, J. Kuang et al., Study on broadband microwave absorbing performance of gradient porous structure. Adv. Compos. Hybrid Mater. 4(3), 591–601 (2021). https://​doi.​org/​10.​1007/​s42114-​021-​00275-4 \n48.\t W. Shao, D. Liu, T. Cao, H. Cheng, J. Kuang et al., Study on favorable comprehensive properties of superhydrophobic coat‑ ing fabricated by polytetrafluoroethylene doped with graphene. Adv. Compos. Hybrid Mater. 4(3), 521–533 (2021). https:// doi.​org/​10.​1007/​s42114-​021-​00243-y \n49.\t S. Budumuru, M.S. Anuradha, Electromagnetic shielding and mechanical properties of al6061 metal matrix compos‑ ite at $\\mathbf{x}$ -band for oblique incidence. Adv. Compos. Hybrid Mater. 4(4), 1113–1121 (2021). https://​doi.​org/​10.​1007/​ s42114-​021-​00338-6 \n50.\t P. Zhang, X. Zhang, B. Li, L. Xu, F. Dang et al., Enhanced microwave absorption performance in an ultralight porous single-atom Co–N–C absorber. Adv. Compos. Hybrid Mater. 4(4), 1292–1301 (2021). https://​doi.​org/​10.​1007/​ s42114-​021-​00308-y \n51.\t J. Zhang, W. Lei, J. Chen, D. Liu, B. Tang et al., Enhancing the thermal and mechanical properties of polyvinyl alcohol (PVA) with boron nitride nanosheets and cellulose nanocrys‑ tals. Polymer 148, 101–108 (2018). https://​doi.​org/​10.​1016/j. polym​er.​2018.​06.​029 \n52.\t T. Bai, Y. Guo, H. Liu, G. Song, D. Zhang et al., Achieving enhanced electromagnetic shielding and absorption capacity of cellulose-derived carbon aerogels via tuning the carboniza‑ tion temperature. J. Mater. Chem. C 8(15), 5191–5201 (2020). https://​doi.​org/​10.​1039/​d0tc0​0448k \n53.\t C. Liu, Q. Fang, D. Wang, C. Yan, F. Liu et al., Carbon and boron nitride nanotubes: structure, property and fabrication. ES Mater. Manuf. 3, 2–15 (2019). https://​doi.​org/​10.​30919/​ esmm5​f199 \n54.\t Z. Ma, X. Xiang, L. Shao, Y. Zhang, J. Gu, Multifunctional wearable silver nanowire decorated leather nanocomposites for joule heating, electromagnetic interference shielding and pie‑ zoresistive sensing. Angew. Chem. Int. Ed. 61(15), 202200705 (2022). https://​doi.​org/​10.​1002/​anie.​20220​0705 \n55.\t M.A. Kashfipour, N. Mehra, J. Zhu, A review on the role of interface in mechanical, thermal, and electrical properties of polymer composites. Adv. Compos. Hybrid Mater. 1(3), 415–439 (2018). https://​doi.​org/​10.​1007/​s42114-​018-​0022-9 \n56.\t C. Yu, Q. Zhang, J. Zhang, R. Geng, W. Tian et al., One-step in situ ball milling synthesis of polymer-functionalized fewlayered boron nitride and its application in high thermally con‑ ductive cellulose composites. ACS Appl. Nano Mater. 1(9), 4875–4883 (2018). https://​doi.​org/​10.​1021/​acsanm.​8b010​47 \n57.\t H. Yan, Q. Li, Z. Wang, H. Wu, Y. Wu et al., Effect of different sintering additives on the microstructure, phase compositions and mechanical properties of $\\mathrm{Si}_{3}\\mathrm{N}_{4}/\\mathrm{SiC}$ ceramics. ES Mater. Manuf. 15, 65–71 (2022). https://​doi.​org/​10.​30919/​esmm5​ f487 \n58.\t T. Ishikawa, S. Kajii, K. Matsunaga, T. Hogami, Y. Kohtoku et al., A tough, thermally conductive silicon carbide com‑ posite with high strength up to 1600 degreesc in air. Science 282(5392), 1295–1297 (1998). https://​doi.​org/​10.​1126/​scien​ ce.​282.​5392.​1295 \n59.\t X. Zhang, J. Dong, D. Pan, G. Yang, F. Su et  al., Con‑ structing dual thermal conductive networks in electrospun polyimide membranes with highly thermally conductivity but electrical insulation properties. Adv. Compos. Hybrid Mater. 4(4), 1102–1112 (2021). https://​doi.​org/​10.​1007/​ s42114-​021-​00335-9 \n60.\t Y. Xie, B. Zhou, A. Du, Slow-sound propagation in aerogelinspired hybrid structure with backbone and dangling branch. Adv. Comp. Hybrid Mater. 4(2), 248–256 (2021). https://​doi. org/​10.​1007/​s42114-​021-​00234-z \n61.\t X. Li, W. Li, Q. Liu, S. Chen, L. Wang et al., Robust high-tem‑ perature supercapacitors based on sic nanowires. Adv. Funct. Mater. 31(8), 2008901 (2021). https://​doi.​org/​10.​1002/​adfm. 20200​8901 \n62.\t B. Du, D. Zhang, J. Qian, M. Cai, C. He et al., Multifunctional carbon nanofiber-SiC nanowire aerogel films with superior microwave absorbing performance. Adv. Compos. Hybrid Mater. 4(4), 1281–1291 (2021). https://​doi.​org/​10.​1007/​ s42114-​021-​00286-1 \n63.\t J. Xu, J. Cao, M. Guo, S. Yang, H. Yao et al., Metamaterial mechanical antenna for very low frequency wireless commu‑ nication. Adv. Compos. Hybrid Mater. 4(3), 761–767 (2021). https://​doi.​org/​10.​1007/​s42114-​021-​00278-1 \n64.\t Z. Guo, A. Li, Z. Sun, Z. Yan, H. Liu et al., Negative permit‑ tivity behavior in microwave frequency from cellulose-derived carbon nanofibers. Adv. Compos. Hybrid Mater. 5, 50–57 (2022). https://​doi.​org/​10.​1007/​s42114-​021-​00314-0 \n65.\t D.M. Guo, Q.D. An, Z. Xiao, S.R. Zhai, Z. Shi, Polyethyl‑ enimine-functionalized cellulose aerogel beads for efficient dynamic removal of chromium(vi) from aqueous solution. RSC Adv. 7(85), 54039–54052 (2017). https://​doi.​org/​10. 1039/​c7ra0​9940a \n66.\t Z. He, M. Yang, L. Wang, E. Bao, H. Zhang, Concentrated photovoltaic thermoelectric hybrid system: an experimen‑ tal and machine learning study. Eng. Sci. 15, 47–56 (2021). https://​doi.​org/​10.​30919/​es8d4​40 \n67.\t Y. Li, J. Guo, M. Li, Y. Tang, V. Murugadoss et al., Recent application of cellulose gel in flexible sensing-a review. ES Food Agrofor. 4, 9–27 (2021). https://​doi.​org/​10.​30919/​esfaf​ 466 \n68.\t M.A. Kashfipour, N. Mehra, R.S. Dent, J. Zhu, Regulating intermolecular chain interaction of biopolymer with natural polyol for flexible, optically transparent and thermally con‑ ductive hybrids. Eng. Sci. 8, 11–18 (2019). https://​doi.​org/​10.​ 30919/​es8d5​08 \n69.\t P. Liu, X. Li, P. Min, X. Chang, C. Shu et al., 3D lamellarstructured graphene aerogels for thermal interface composites with high through-plane thermal conductivity and fracture toughness. Nano-Micro Lett. 13, 22 (2020). https://​doi.​org/ 10.​1007/​s40820-​020-​00548-5 \n70.\t N. Chen, T. Li, Y. Wang, L. Pan, W. Bao et al., Generalized “slope method” of the 3ω analysis to measure the thermal con‑ ductivity and heat capacity of solids: frequency- vs. currentsweep. ES Energy Environ. 10, 13–21 (2020). https://​doi.​org/​ 10.​30919/​esee8​c725 \n71.\t X. Yang, C. Liang, T. Ma, Y. Guo, J. Kong et al., A review on thermally conductive polymeric composites: classification, measurement, model and equations, mechanism and fabrica‑ tion methods. Adv. Compos. Hybrid Mater. 1(2), 207–230 (2018). https://​doi.​org/​10.​1007/​s42114-​018-​0031-8 \n72.\t X. Hu, H. Wu, S. Liu, S. Gong, Y. Du et al., Fabrication of organic shape-stabilized phase change material and its energy storage applications. Eng. Sci. 17, 1–27 (2022). https://​doi.​org/​ 10.​30919/​es8d4​74 \n73.\t J.P. Huang, Thermal metamaterials make it possible to control the flow of heat at will. ES Energy Environ. 6, 1–3 (2019). https://​doi.​org/​10.​30919/​esee8​c368 \n74.\t H. Fu, Y. Xiao, P. Li, W. Qian, D. Li et al., Ultrasonic-assisted soldering for graphite films as heat sinks with durably superior heat dissipating efficiency. Adv. Compos. Hybrid Mater. (2021). https://​doi.​org/​10.​1007/​s42114-​021-​00255-8 \n75.\t Y. Xue, S. Lofland, X. Hu, Protein-based flexible thermal conductive materials with continuous network structure: Fab‑ rication, properties, and theoretical modeling. Compos. Part B 201, 108377 (2020). https://​doi.​org/​10.​1016/j.​compo​sitesb. 2020.​108377 \n76.\t C. Fu, C. Yan, L. Ren, X. Zeng, G. Du et al., Improving ther‑ mal conductivity through welding boron nitride nanosheets onto silver nanowires via silver nanoparticles. Compos. Sci. Technol. 177, 118–126 (2019). https://​doi.​org/​10.​1016/j. comps​citech.​2019.​04.​026 \n77.\t Q.Y. Li, Q. Hao, T. Zhu, M. Zebarjadi, M. Zebarjadi, Nano‑ structured and heterostructured 2D materials for thermoelec‑ trics. Eng. Sci. 13, 24–50 (2021). https://​doi.​org/​10.​30919/ es8d1​136 \n78.\t C. Liu, C. Wu, P. Lu, Y. Zhao, Non-monotonic thickness dependent hydrodynamic phonon transport in layered titanium trisulphide: first-principles calculation and improved callaway model fitting. ES Energy Environ. 14, 34–42 (2021). https:// doi.​org/​10.​30919/​esee8​c521 \n79.\t Q. Hao, J. Garg, A review on phonon transport within poly‑ crystalline materials. ES Mater. Manuf. 14, 36–50 (2021). https://​doi.​org/​10.​30919/​esmm5​f480 \n80.\t R.K. Bhushan, Effect of SiC particle size and weight $\\%$ on mechanical properties of AA7075 sic composite. Adv. Com‑ pos. Hybrid Mater. 4(1), 74–85 (2021). https://​doi.​org/​10. 1007/​s42114-​020-​00175-z \n81.\t D. Micheli, A. Vricella, R. Pastore, M. Marchetti, Synthesis and electromagnetic characterization of frequency selective radar absorbing materials using carbon nanopowders. Carbon 77, 756–774 (2014). https://​doi.​org/​10.​1016/j.​carbon.​2014.​05. 080 \n82.\t R. Asmatulu, P.K. Bollavaram, V.R. Patlolla, I.M. Alarifi, W.S. Khan, Investigating the effects of metallic submicron and nanofilms on fiber-reinforced composites for light‑ ning strike protection and emi shielding. Adv. Compos. Hybrid Mater. 3(1), 66–83 (2020). https://​doi.​org/​10.​1007/ s42114-​020-​00135-7 \n83.\t P. Xie, Y. Liu, M. Feng, M. Niu, C. Liu et al., Hierarchically porous $\\mathrm{Co/C}$ nanocomposites for ultralight high-performance microwave absorption. Adv. Compos. Hybrid Mater. 4(1), 173–185 (2021). https://​doi.​org/​10.​1007/​s42114-​020-​00202-z \n84.\t Q. Gao, Y. Pan, G. Zheng, C. Liu, C. Shen et al., Flexible multilayered MXene/thermoplastic polyurethane films with excellent electromagnetic interference shielding, thermal conductivity, and management performances. Adv. Compos. Hybrid Mater. 4(2), 274–285 (2021). https://​doi.​org/​10.​1007/ s42114-​021-​00221-4 \n85.\t Y. Han, K. Ruan, J. Gu, Janus (BNNS/ANF)-(AgNWs/ ANF) thermal conductivity composite films with superior electromagnetic interference shielding and joule heating performances. Nano Res. (2022). https://​doi.​org/​10.​1007/ s12274-​022-​4159-z \n86.\t R. Dilli, R. Chandra, D. Jordhana, Ultra-massive MIMO tech‑ nologies for 6G wireless networks. Eng. Sci. 16, 308–318 (2021). https://​doi.​org/​10.​30919/​es8d5​71 \n87.\t P. Song, Z. Ma, H. Qiu, Y. Ru, J. Gu, High-efficiency electro‑ magnetic interference shielding of $\\operatorname{rGO}(\\omega$ FeNi/epoxy com‑ posites with regular honeycomb structures. Nano-Micro Lett. 14, 51 (2022). https://​doi.​org/​10.​1007/​s40820-​022-​00798-5 " + }, + { + "id": "10.1002_adma.202110103", + "DOI": "10.1002/adma.202110103", + "DOI Link": "http://dx.doi.org/10.1002/adma.202110103", + "Relative Dir Path": "mds/10.1002_adma.202110103", + "Article Title": "Electronic Structure Engineering of Single-Atom Ru Sites via Co-N4 Sites for Bifunctional pH-Universal Water Splitting", + "Authors": "Rong, CL; Shen, XJ; Wang, Y; Thomsen, L; Zhao, TW; Li, YB; Lu, XY; Amal, R; Zhao, C", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "The development of bifunctional water-splitting electrocatalysts that are efficient and stable over a wide range of pH is of great significance but challenging. Here, an atomically dispersed Ru/Co dual-sites catalyst is reported anchored on N-doped carbon (Ru/Co-N-C) for outstanding oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) in both acidic and alkaline electrolytes. The Ru/Co-N-C catalyst requires the overpotential of only 13 and 23 mV for HER, 232 and 247 mV for OER to deliver a current density of 10 mA cm(geo)(-2) in 0.5 m H2SO4 and 1 m KOH, respectively, outperforming benchmark catalysts Pt/C and RuO2. Theoretical calculations reveal that the introduction of Co-N4 sites into Ru/Co-N-C efficiently modify the electronic structure of Ru by enlarging Ru-O covalency and increasing Ru electron density, which in turn optimize the bonding strength between oxygen/hydrogen intermediate species with Ru sites, thereby enhancing OER and HER performance. Furthermore, the incorporation of Co-N4 sites induces electron redistribution around Ru-N4, thus enhancing corrosion-resistance of Ru/Co-N-C during acid and alkaline electrolysis. The Ru/Co-N-C has been applied in a proton exchange membrane water electrolyzer and steady operation is demonstrated at a high current density of 450 mA cm(geo)(-2) for 330 h.", + "Times Cited, WoS Core": 307, + "Times Cited, All Databases": 312, + "Publication Year": 2022, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000786440900001", + "Markdown": "# Electronic Structure Engineering of Single-Atom Ru Sites via Co–N4 Sites for Bifunctional pH-Universal Water Splitting \n\nChengli Rong, Xiangjian Shen, Yuan Wang, Lars Thomsen, Tingwen Zhao, Yibing Li, Xunyu Lu, Rose Amal, and Chuan Zhao\\* \n\nThe development of bifunctional water-splitting electrocatalysts that are efficient and stable over a wide range of pH is of great significance but challenging. Here, an atomically dispersed $\\mathsf{R u}/\\mathsf{C o}$ dual-sites catalyst is reported anchored on N-doped carbon $(\\mathsf{R u}/\\mathsf{C o}-\\mathsf{N}-\\mathsf{C})$ for outstanding oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) in both acidic and alkaline electrolytes. The $R\\mathbf{u}/\\mathsf{C o-N-C}$ catalyst requires the overpotential of only 13 and $23~\\mathsf{m}\\mathsf{v}$ for HER, 232 and $247\\ m\\vee$ for OER to deliver a current density of $10\\mathrm{mAcm}_{\\mathrm{geo}}{}^{-2}$ in $\\mathbf{0.5\\m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and ${\\mathsf{1}}{\\mathsf{M}}{\\mathsf{K O H}}$ , respectively, outperforming benchmark catalysts $\\mathsf{P t/C}$ and $\\mathsf{R u O}_{2}$ . Theoretical calculations reveal that the introduction of Co–N4 sites into $R\\mathbf{u}/\\mathsf{c o-N-C}$ efficiently modify the electronic structure of $\\mathsf{R}\\mathsf{u}$ by enlarging $R u\\mathrm{-}0$ covalency and increasing Ru electron density, which in turn optimize the bonding strength between oxygen/hydrogen intermediate species with Ru sites, thereby enhancing OER and HER performance. Furthermore, the incorporation of Co–N4 sites induces electron redistribution around Ru–N4, thus enhancing corrosion–resistance of $R\\mathbf{u}/\\mathsf{C o-N-C}$ during acid and alkaline electrolysis. The $R\\mathbf{u}/C_{0-}N-C$ has been applied in a proton exchange membrane water electrolyzer and steady operation is demonstrated at a high current density o $\\mathsf{f}450\\mathsf{m A c m}_{\\mathsf{g e o}}{}^{-2}$ for $330h$ . \n\nThe ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adma.202110103. \n\n$\\circledcirc$ 2022 The Authors. Advanced Materials published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. \n\nDOI: 10.1002/adma.202110103 \n\n# 1. Introduction \n\nHydrogen evolution reaction (HER) and oxygen evolution reaction (OER) are the two half-reactions of electrochemical water splitting, which is widely recognized as a promising method to produce green hydrogen via renewable energy sources.[1] Compared to OER in alkaline and HER in acids, OER in acidic and HER in alkaline are more challenging due to the additional step caused by water molecule dissociation.[2] Although tremendous efforts have been devoted to developing efficient electrocatalysts to overcome the energy barriers and accelerate the reaction kinetics of OER and/or HER, most of the reported electrocatalysts are only applicable for OER or HER under specific conditions (e.g., acid or alkaline).[3] Besides, the severe activity decay (for both OER and HER) significantly restricts their largescale application. From a practical point of view, it is highly desirable to develop highperformance bifunctional electrocatalysts over a wide pH range for hydrogen production using proton exchange membrane (PEM) electrolyzers and alkaline water electrolyzers. \n\nPlatinum group metals (PGMs) are the benchmark catalysts for OER (e.g., Ru, Ir) and HER (e.g., Pt).[4] Ru-based catalyst exhibits better OER activity than Ir-based catalysts and is also a promising alternative to Pt for HER with significantly lower cost.[5] However, two issues need to be addressed in developing a Ru-based bifunctional electrocatalyst. First, the over-oxidation of $\\mathrm{RuO}_{2}$ into soluble $\\mathrm{RuO}_{4}^{-}$ moieties and the participation of lattice oxygen often results in poor OER stability.[6] Second, Ruthenium (Ru) is a promising substitute for the state-of-theart Pt catalyst for alkaline HER due to its lower price and lower kinetic barrier for water adsorption/dissociation than Pt.[7] However, theoretical studies revealed that the Ru nanoparticles exhibit a much higher hydrogen binding energy than atomically dispersed $\\mathrm{RuN}_{x}\\mathrm{C}_{\\gamma}$ moiety, thus severely slowing down the efficiency of hydrogen adsorption/desorption on Ru sites and resulting in a low HER performance.[8] Strategies are urgently needed to address these issues and simultaneously reduce the usage of Ru metal which are costly. \n\nSingle-atom catalysts (SACs) dispersed on nitrogen-doped carbon support have attracted significant attention owing to the distinct merits of atomically dispersed active sites and maximum atom utilization efficiency.[9] However, SACs is intrinsically limited by the simplicity of their active sites. For complex reactions involving multiple intermediates like OER and HER, their single-site typically follow linear scaling relationships and exhibit either too strong or too weak bonding to one or more intermediates. The atomically dispersed catalysts with dual-sites have shown promise to improve catalytic performance through introducing more accessible active sites and optimizing electronic structures.[10] For example, N-coordinated isolated diatomic Ni–Fe sites with unique electronic structure and geometry configuration exhibited high-performance for $\\mathrm{CO}_{2}$ reduction in a wide potential than individual Ni–N–C and Fe–N–C.[11] Atomically dispersed Mn–N moieties into Fe–N–C catalysts also show an enhanced activity of oxygen reduction reaction via improving the oxygen adsorption states and stretching the $_{\\mathrm{O-O}}$ bond length.[12] \n\nHerein, we show an atomically dispersed Ru–Co dual-sites catalyst to regulate the intermediate species affinity on the Ru surface, thereby enabling a highly active bifunctional catalyst for water splitting in both acidic and alkaline conditions. By pyrolyzing $\\mathrm{{Ru}}/\\mathrm{{Co}}$ codoped $\\mathrm{UiO}{\\cdot}66{\\cdot}\\mathrm{NH}_{2}$ and acid etching, $\\mathrm{RuN}_{4}$ and $\\mathrm{CoN}_{4}$ sites are isolated and well distributed on the nitrogen–carbon support $(\\mathrm{Ru}/\\mathrm{Co-N-C-800}^{\\mathrm{~\\circ~}}\\mathrm{C})$ . Benefiting from the unique atom-isolated structure and atomic-distance synergistic effect between $\\scriptstyle{\\mathrm{Ru-N}}4$ and Co–N4 moieties, the $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ shows exceptional catalytic performance for OER, HER, and overall water splitting, across a wide pH range. \n\n# 2. Results and Discussion \n\n# 2.1. Synthesis and Structural Characterization \n\nThe synthetic process of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ is illustrated in Figure 1a. Briefly, the $\\ensuremath{\\mathrm{Zr}_{6}}$ -based $\\mathrm{UiO}{-}66{\\cdot}\\mathrm{NH}_{2}$ was first synthesized using $\\mathrm{RuCl}_{3}$ and $\\mathrm{CoCl}_{2}$ as metal precursors and 2-aminoterephthalic acid $(\\mathrm{H}_{2}\\mathrm{BDC}\\cdot\\mathrm{NH}_{2})$ as the $\\mathrm{\\DeltaN}$ and C sources, which was acting as a host to encapsulate $\\mathrm{Ru}^{3+}$ and ${\\mathsf{C o}}^{2+}$ ions via a self-assembly process (denoted as $\\mathrm{RuCl_{3}/C o C l_{2}\\mathrm{\\cdotUiO\\mathrm{-}66\\mathrm{-}N H_{2})}}$ . The negatively charged $\\mathrm{-NH}_{2}$ groups in the ligand can function as Lewis acidic sites to immobilize metal atoms, Ru and Co ions can coordinate with the nitrogen atoms, forming metal–N bonds. The color observed after adding $\\mathrm{RuCl_{3}/C o C l_{2}}$ change from yellow to light grey, indicating the strong electrostatic adsorption between $\\mathrm{Ru}^{3+}/\\mathrm{Co}^{2+}$ ions and the electron-rich $\\mathrm{-NH}_{2}$ groups (Figure S1, Supporting Information).[13] During the pyrolysis of $\\mathrm{RuCl_{3}/C o C l_{2}}$ -UiO-66-NH2 in $\\mathrm{Ar}$ at $800~^{\\circ}\\mathrm{C},$ Ru and Co sites were anchored on nitrogen-doped carbon (N–C) derived from $\\mathrm{H}_{2}\\mathrm{BDC}\\cdot\\mathrm{NH}_{2}$ . Finally, the inert $\\mathrm{ZrO}_{2}$ was removed by acid etching to yield the nitrogen co-coordinated $\\mathrm{{Ru/Co}}$ dual-sites catalyst $(\\mathrm{Ru}/\\mathrm{Co-N-C-800\\^{\\circ}C})$ . \n\n![](images/7b36571eeb1fe600d27bc56dafc365d8f5df86e1dff61fff5285bcce0d69ea97.jpg) \nFigure 1.  a) The illustration of the synthesis procedure of $R\\mathsf{u}/{\\mathsf{C o}}-\\mathsf{N}-{\\mathsf{C}}{\\mathsf{-}}800\\ {\\mathsf{\\Omega}}^{\\circ}{\\mathsf{C}}.$ . b) XRD patterns, c) Raman spectra, and d) ${\\sf N}_{2}$ adsorption–desorption isotherm (inset is the pore size distribution) of $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-}\\mathsf{N}\\mathrm{-}\\mathsf{C}\\mathsf{-}800\\ ^{\\circ}\\mathsf{C}$ and $R\\mathsf{u-N-C-}800\\ ^{\\circ}\\mathsf{C}.$ e) TEM, f) HR-TEM, and g) HAADF-STEM images of ${\\sf R u}/{\\sf C o-N-C-800}^{\\circ}{\\sf C}$ . \n\nAfter pyrolysis and acid etching, the X-ray diffraction (XRD) patterns show broad peaks of amorphous features in the absence of characteristic peaks for Ru or Co nanoparticles, implying that the skeleton of $\\mathrm{UiO}{-}66{\\cdot}\\mathrm{NH}_{2}$ was converted in situ into porous N-doped carbon (Figure 1b). Raman spectra exhibit the $\\mathsf{D}_{1}$ $(1360~\\mathrm{cm^{-1}})$ and G $(1595~\\mathrm{cm}^{-1})$ bands at $\\mathrm{Ru/Co-N-C{\\cdot}800\\ ^{\\circ}C}$ and $\\mathrm{Ru-N-C-800\\^{\\circ}C}$ , corresponding to the edge plane defects of graphite and defect-free $\\mathsf{s p}^{2}$ -hybridized carbon network respectively (Figure  1c).[14] The significantly increased $\\mathrm{{I_{D1}/I_{G}}}$ ratio for $\\mathrm{Ru}/\\mathrm{Co-N-C-800~^{\\circ}C}$ (1.12), as compared to that of $\\mathrm{Ru-N-C-800~^{\\circ}C}$ (1.05), suggests that more defects are produced due to the cocoordination between Ru and Co and the N doped carbon support, which is beneficial to improve the electron-transfer rate between the catalyst and reactants.[15] The specific surface area of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ is $449~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ as determined by $\\mathrm{N}_{2}$ adsorption/desorption, suggesting it is rich in micropores and mesopores (Figure 1d). The hierarchical microporous/mesoporous structure can increase the density of active sites and mass transport during the electrochemical reaction.[12] \n\nTransmission electron microscopy (TEM) and scanning electron microscopy (SEM) (Figure 1e; Figure S2, Supporting Information) reveal that $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ maintain the initial octahedral shape after carbonization and acid washing. The absence of discernible Ru and Co particles in the high-angle annular dark-field scanning transmission electron microscopy (HAAD-STEM) images indicates that the Ru and Co are well dispersed on the N-doped carbon framework, which is in line with the XRD results. A series of characterizations including XRD, TEM, and X-ray photoelectron spectroscopy (XPS) was applied to confirm the successful removal of $\\mathrm{ZrO}_{2}$ (Figure S3, Supporting Information). Numerous nanopores (highlight in yellow) are observed on the catalyst surface (Figure  1f).[16] The isolated brighter dots (selectively highlighted in red) in the HAADF-STEM image verify the existence of the atomically dispersed metal sites on the N-doped carbon framework (Figure 1g). The elemental mapping shows that the Ru, Co, C, and N are homogeneously distributed on the carbon support (Figure S4, Supporting Information). The single-atom $\\mathrm{\\Ru-N-}$ $\\mathrm{C}{\\cdot}800^{\\circ}\\mathrm{C}$ and $\\mathrm{{Ru/Co}}$ nanoparticles (denoted as $\\mathrm{Ru}/\\mathrm{Co}\\ \\mathrm{NPs}/\\mathrm{N}-$ $\\mathrm{C}{\\cdot}800^{\\circ}\\mathrm{C})$ ) catalysts were also synthesized by employing a similar method. The Ru atoms in $\\mathrm{Ru-N-C-800\\^{\\circ}C}$ are also distributed homogeneously on the N-doped carbon support without aggregation (Figure S5a,b, Supporting Information). By contrast, $\\mathrm{{Ru/Co}}$ nanoparticles were obtained due to the aggregation of metal atoms at high temperatures in the absence of $\\mathrm{-NH}_{2}$ groups (Figure S5c,d, Supporting Information). The content of Ru and Co are quantified by inductively coupled plasma mass spectroscopic (ICP-MS) to be 0.36 and $0.15~\\mathrm{wt\\%}$ , respectively (Table S1, Supporting Information). Compared with the feed ratio of Ru/Co $(1/1)$ , the relatively larger density of Ru atoms than Co atoms in $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ is attributed to the removal of some unstable Co species during acid washing. \n\n# 2.2. Analysis of Composition and Atomic Structure \n\nThe surface compositions and electronic structure are further investigated by XPS. The signals of $\\mathrm{Ru}~3\\mathrm{p}$ and Co 2p are not detected due to their low concentrations and sensitivity limit of XPS (Figure S6a,b, Supporting Information). The N 1s spectra show that the feature of pyridinic (398.7  eV), metal– nitrogen $(\\mathrm{M}{-}\\mathrm{N}_{x})$ $(399.5\\ \\mathrm{eV})$ , pyrrolic $(401.0\\ \\mathrm{eV})$ , and graphitic– N $\\parallel(402.5\\mathrm{eV})$ ) species (Figure S6c,d, Supporting Information).[17] The dominant N species (pyridinic and pyrrolic N) located in a $\\pi$ conjugated system play an essential role in stabilizing metal atoms, in which p-electrons are effectively coordinated with $\\mathrm{Ru}/$ Co atoms and modulate the electronic properties.[18] Besides, pyridinic nitrogen exhibits better water wettability and a strong affinity to water molecules, thus facilitating electron transfer in OER/HER process.[19] \n\nThe synchrotron-based X-ray absorption spectroscopy (XAS) characterization was carried out to provide a detailed understanding of the chemical state and coordination configurations of Ru and Co atoms. X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) measurements provide a more detailed understanding of the valence states and coordination states of the metal atom centers. As shown in the XANES spectra of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ , the near-edge absorption energy of the Ru K-edge was positioned between those of the Ru foil and $\\mathrm{RuO}_{2}$ references, and close to that of ${\\mathrm{RuCl}}_{3}$ , indicating the dominant valence state of $\\mathrm{Ru}\\ \\mathrm{Ru}/\\mathrm{Co-N-C-800}\\ ^{\\circ}\\mathrm{C}$ is around $+3$ (Figure 2a). Compared with commercial $\\mathrm{RuO}_{2}$ with highly symmetrical octahedral structures, a pre-edge peak of $\\mathrm{Ru}/$ $\\mathrm{Co-N-C-800~^{\\circ}C}$ near $22114\\ \\mathrm{eV}$ is related to the transition of Ru 1s to the unoccupied Ru 4d level.[20] The unoccupied $\\mathrm{Ru}4\\mathrm{d}$ level is ascribed to the electrons transfers from $\\mathrm{Ru}~4\\mathrm{d}$ state to $\\textnormal{N}2\\textnormal{p}$ state via strong $\\mathrm{\\Ru-N}$ hybridization in the $\\scriptstyle{\\mathrm{Ru-N}}4$ sites.[21] Moreover, the Ru K-edge absorption spectra of $\\mathrm{Ru/Co-N-C\\cdot}$ $800~^{\\circ}\\mathrm{C}$ show a significant shift to lower energy compared to $\\mathrm{Ru-N-C-800~^{\\circ}C}$ , implying a decrease in the Ru valence state after introducing Co sites. Moreover, the adsorption threshold energies $(E_{0})$ of Ru obtained from the first derivative in Ru foil, ${\\mathrm{RuCl}}_{3}$ , $\\mathrm{RuO}_{2}$ , $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ , and $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ are 22 117.4, 22 125.4, 22 128.4, 22 126.8, and $22~125.6~\\mathrm{eV},$ respectively (Figure $S7a$ , Supporting Information). The smaller $E_{0}$ of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ than that of the $\\mathrm{Ru-N-C-800~^{\\circ}C}$ indicates a decreased oxidation state of $\\mathtt{R u}$ in $\\mathrm{Ru/Co-N-C{\\cdot}800\\ ^{\\circ}C}$ The average valence state of Ru in $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ is $+3.1$ , lower than that of Ru $(+3.4)$ in $\\mathrm{Ru-N-C-800\\^{\\circ}C}$ , near to $\\mathrm{RuCl}_{3}$ $(+3)$ (Figure $\\mathbf{S}7\\mathbf{b}$ , Supporting Information). The modified electronic properties of Ru atoms is expected to facilitate water dissociation and modulate the binding strength of the adsorbed oxygen/hydrogen intermediate, thus endowing $\\mathrm{Ru/Co-N-C-}$ $800~^{\\circ}\\mathrm{C}$ with remarkable performance than $\\mathrm{Ru-N-C-}800\\ ^{\\circ}\\mathrm{C}$ .[22] As shown in the Fourier-transformed (FT) $k^{3}$ -weighted EXAFS spectra of Ru K-edge (Figure 2c), the dominant peak at ${\\approx}1.48$ Å (without phase correction) for $\\mathrm{Ru/Co-N-C{\\cdot}800\\mathrm{~\\Omega^{\\circ}C}}$ can be assigned to shell coordination of the nearest $\\mathrm{Ru-N/C}$ bond, without the Ru–Ru peaks at ${\\approx}2.3\\mathrm{~\\AA~}$ , as shown in Ru foil.[21] Importantly, a significant increase in the length of $\\mathrm{\\Ru-N}$ bond is detected after the introduction of foreign Co atoms, indicating a strong dipole hybridization of $\\mathrm{\\Ru-N}$ coordination environment.[21] The formation of $\\mathrm{Ru/Co-N}$ coordination can be confirmed by the soft XAS at N K-edge and C K-edge (Figure S8a,b, Supporting Information). Compared to the almost identical C K-edge spectra of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ and $N{\\mathrm{-C-}}800\\ ^{\\circ}\\mathrm{C}$ , the significant variations in the peaks’ intensity of N K-edge spectra represents the strong interaction between N atoms and $\\mathrm{{Ru/Co}}$ atoms through orbital hybridization.[21] The N 1s XPS measurement for $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ also demonstrates the formation of $\\mathrm{M}{-}\\mathrm{N}_{x}$ bonds (Figure S8c,d, Supporting Information). Also, the formation of Ru–O bonds in $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ catalyst can be excluded by the O K-edge spectrum and O 1s XPS measurements (as discussed in Figure S9 in the Supporting Information). \n\n![](images/373e96b6a56c04d48adc6efbb7509627d2d59ceb7bdd0cfd2b50d3f8a8e38dbe.jpg) \nFigure 2.  a) Ru K-edge and b) Co K-edge XANES spectra, and c,d) the corresponding Fourier transforms of EXAFS spectra of $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-}\\mathsf{N}\\mathrm{-}\\mathsf{C}\\mathsf{-}800\\ ^{\\circ}\\mathsf{C}$ and reference samples. Wavelet transform (WT) of e) Ru and f) Co in $R\\mathsf{u}/{\\mathsf{C o}}-\\mathsf{N}-{\\mathsf{C}}{\\mathsf{-}}800{\\mathsf{\\Omega}}^{\\circ}{\\mathsf{C}}.$ g,h) Ru K-edge and Co K-edge FT-EXAFS and the corresponding EXAFS fitting curves at R space for $R\\mathsf{u}/{\\mathsf{C o}}-\\mathsf{N}-{\\mathsf{C}}-800\\ {}^{\\circ}{\\mathsf{C}}.$ i) Proposed structural model of $R\\mathsf{u}/\\mathsf{C o-N-C-800}^{\\circ}\\mathsf{C}$ \n\nFor Co K-edge spectra, the normalized Co adsorption spectrum in $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ is situated between Co foil and CoO, indicating the oxidation state of Co atoms in $\\mathrm{Ru}/$ $\\mathrm{Co-N-C-800\\^{\\circ}C}$ . $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ shares similar characteristic features to cobalt (II) phthalocyanine (CoPc), indicating that $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ possesses comparable $D_{4h}$ symmetry as CoPc (Figure 2b).[23] A pre-edge peak (A) at ${\\approx}7709.6\\mathrm{eV}$ can be assigned to the dipole-forbidden but quadrupole-allowed transition $(1\\mathrm{s}\\to3\\mathrm{d})$ , referring to the 3d and 4p orbital hybridization of the Co central atoms.[24] Compared with CoPc, the reduced peak (B) intensity of $1\\mathrm{s}\\to4\\mathrm{p}$ transition in $\\mathrm{Ru/Co-N-}$ $\\mathrm{C}{\\cdot}800~^{\\circ}\\mathrm{C}$ acts as a fingerprint of square-planar ${\\mathrm{Co-N}}4$ moieties, also confirming the distorted $D_{4h}$ symmetry of Co atom in $\\mathrm{Ru/Co-N-C-800~^{\\circ}C.^{[24]}}$ The adsorption threshold energies $\\left(E_{0}\\right)$ of Co obtained from the first derivative in Co foil, CoO, $\\mathrm{Co}_{3}\\mathrm{O}_{4}.$ and $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ are 7708.3, 7721.0, 7728.1, and $7719.9\\ \\mathrm{eV},$ respectively (Figure S7c, Supporting Information). The calculated average valence state of Co in $\\mathrm{Ru/Co-N-C-}$ $800^{\\circ}\\mathrm{C}$ is $+1.8$ , near to the CoO (Figure S7d, Supporting Information), confirming that the valence of Co in $\\mathrm{Ru/Co-N-C-}$ $800~^{\\circ}\\mathrm{C}$ is indeed between 0 and $+2$ . The prominent peak at ${\\ \\approx}1.39\\mathring\\mathrm{A}$ in FT-EXAFS spectra of Co K-edge is attributed to the scattering interaction between the Co atoms and the nearest shell coordination of the $\\mathrm{Co-N}$ bond (Figure  2d). The negligible peaks at ${\\approx}2.2$ Å in the FT-EXAFS spectra of Ru and Co in $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ exclude the presence of M–M (M: Ru, Co) bonds, implying the isolated distribution of Ru and Co atoms. \n\nThe wavelet transforms (WT) of the $\\mathrm{k}^{3}$ -weighted EXAFS spectra further confirm the above conclusion. The WT contour plot shows two intensity maxima at 5.7 and $10.2\\mathring\\mathrm{A}^{-1}$ in Ru foil and $\\mathrm{RuO}_{2}$ correspond to the $\\mathrm{\\Ru-O}$ and Ru–Ru metallic bonds, respectively (Figure S10, Supporting Information).[25] The only dominant intensity at $4.3\\mathring\\mathrm{A}^{-1}$ in $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ is ascribed to the coordinated configuration of the $\\mathrm{\\Ru-N}$ structure, where no $\\mathrm{{Ru-Ru}}$ signal near $10.2\\mathring\\mathrm{A}^{-1}$ is detected (Figure 2e). Similarly, the WT contour maximum at $4.2\\mathring\\mathrm{A}^{-1}$ confirms the presence of Co–N bonds with the absence of Co–Co or $\\scriptstyle\\mathrm{Co-C}$ bonds, compared with the WT contour plots of Co foil, CoPc, and CoO (Figure  2f; Figure S11, Supporting Information). The EXAFS fitting curves were carried out (Figure  2g,h;  Figures S10a and S12, Supporting Information) and corresponding parameters were summarized (Table S2, Supporting Information). The fitting results reveal that the coordination is in the form of Ru–N4 and ${\\mathrm{Co-N}}4$ moieties with an average bond length of ${\\approx}2\\mathrm{~\\AA~}$ . Together, the above results confirm the successful synthesis of atomically isolated Ru and Co single atoms on the N–C support, via coordinating with the adjacent four pyridinicN atoms, in which the electronic properties of $\\mathtt{R u}$ atoms are modified by Co atoms (Figure 2i). \n\n# 3. Electrochemical Performance of OER \n\nWe first evaluated the OER performance of the as-prepared catalysts in $\\mathrm{N}_{2}$ -saturated electrolytes using a three-electrode system. The OER performances in $0.5\\textbf{M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ and $1\\mathrm{~m~}$ KOH show the same trend: ${\\mathrm{Ru}}/{\\mathrm{Co-N-C-800}}^{\\circ}{\\mathrm{C}}>{\\mathrm{Ru-N-C-800}}^{\\circ}{\\mathrm{C}}>$ commercial $\\mathrm{RuO}_{2}$ (Figure 3a). Specifically, $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ with dual-sites significantly improves OER activity with a lower onset potential of $1.40\\mathrm{V}$ versus reversible hydrogen electrode (RHE) compared to $\\mathrm{Ru-N-C-800~^{\\circ}C}$ (1.44  V vs RHE) in $0.5\\mathrm{~M~H}_{2}\\mathrm{SO}_{4},$ suggesting that the OER activity is significantly improved by introducing CoN4 site in N-doped carbon support. The overpotential of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ for delivering a current density of 10  mA $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ are 232 and $276~\\mathrm{mV}$ in $0.5\\textbf{\\textmu}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and $1\\mathrm{~M~}\\mathrm{KOH}$ , respectively, much lower than those of $\\mathrm{Ru-N-C-800~^{\\circ}C}$ (297 and $347~\\mathrm{mV})$ ) and commercial $\\mathrm{RuO}_{2}$ (329 and $379\\mathrm{mV},$ Figure 3b), ranking $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ one of the most active noble metal-based catalysts in both acidic and alkaline media (Tables S3 and S4, Supporting Information). The $\\mathrm{Ru}/\\mathrm{Co\\NPs}\\mathrm{-N}\\mathrm{-C}{\\cdot}800\\ ^{\\circ}\\mathrm{C}$ catalyst shows a low current density of 3.4 mA $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ at $1.5\\mathrm{~V~}$ versus RHE in $0.5\\textbf{M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4},$ eightfold lower than $\\mathrm{\\DeltaRu/Co-N-C{\\cdot}800\\ ^{\\circ}C}$ (27.6  mA $\\mathrm{cm}_{\\mathrm{geo}}\\mathrm{}^{-2})$ (Figure S13, Supporting Information). Besides, the inferior OER performance of $\\mathrm{Co-N-C-800\\^{\\circ}C}$ suggests that the active center in $\\mathrm{Ru}/$ $\\mathrm{Co-N-C-800~^{\\circ}C}$ is $\\mathrm{RuN}4$ sites, and its electronic structure is efficiently regulated by introducing $\\mathrm{CoN}_{4}$ sites, thereby exhibiting an enhanced OER activity relative to $\\mathrm{Ru-N-C-800}^{\\circ}\\mathrm{C}.$ The carbonization temperature and ratios of $\\mathtt{R u}$ and Co are also found to affect OER performance (Figure S14, Supporting \n\n![](images/6290d386c9dd54e7a39462c95b8c37b626e653ec44c4e896ddbd2d41cbbe722c.jpg) \nFigure 3.  Electrocatalytic OER performance of $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-}\\mathsf{N}\\mathrm{-}\\mathsf{C}\\mathsf{-}800\\ ^{\\circ}\\mathsf{C}$ compared with $R\\mathsf{u-N-C-}800\\ ^{\\circ}\\mathsf{C}$ , $C o{\\mathrm{-}}N{\\mathrm{-}}C{\\cdot}800\\ ^{\\circ}C.$ and commercial ${\\sf R u O}_{2}$ . a) OER polarization curves were obtained at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in ${\\sf N}_{2}$ -saturated $0.5~\\mathsf{m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and ${\\mathsf{1}}{\\mathsf{M}}$ KOH. b) Comparison of overpotential to achieve a current density of 10 mA ${\\mathsf{c m}}_{\\mathsf{g e o}}{}^{-2}$ and TOF value at $\\ensuremath{\\mathsf{1.53V}}$ versus RHE in $0.5~\\mathsf{m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and 1 m KOH. c) The chronopotentiometry of $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-}\\mathsf{N}\\mathrm{-}\\mathsf{C}\\mathsf{-}800\\ ^{\\circ}\\mathsf{C}$ and commercial ${\\mathsf{R u O}}_{2}$ in $0.5~\\mathsf{m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and 1 m KOH. \n\nInformation), possibly by influencing the dispersion of active sites and N-coordination number.[8a,26] \n\nThe turnover frequency (TOF) was calculated to understand the intrinsic activity of the catalysts based on the reported protocols.[27] $\\mathrm{Ru/Co-N-C{\\cdot}800\\ ^{\\circ}C}$ yields an ultrahigh TOF value of $9.20\\ \\mathrm{s}^{-1}$ at $1.53\\mathrm{~V~}$ versus RHE in $0.5~\\mathrm{~m~}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}.$ , which is 4.5 and 1840 times higher than $\\mathrm{Ru{-N{-C{-}800}~^{\\circ}C~(2.05~s^{-1})}}$ and $\\mathrm{RuO}_{2}$ $(0.005~\\mathrm{s^{-1}})$ , respectively (Figure  3b). Besides, the small Tafel slopes and small semicircle in electrochemical impedance spectroscopy (EIS) for $\\mathrm{Ru/Co-N-C{\\cdot}800\\ ^{\\circ}C}$ confirm its more favorable reaction kinetics and charge transfer efficiency (Figure S15, Supporting Information).[28] The Faradaic efficiency (FE) of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ was determined to be $96\\%$ , indicating most of the charge transfer process was dominated by OER electrocatalysis (Figure S16, Supporting Information). \n\nApart from high catalytic activity, $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ also exhibits excellent durability over $20\\mathrm{h}$ at 10 mA $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ without noticeable activity degradation in $0.5\\textbf{\\textmu}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and $1\\mathrm{~M~}\\mathrm{KOH}$ (Figure  3c). By contrast, a sharp increase of overpotential for commercial $\\mathrm{RuO}_{2}$ is observed within $^{4\\mathrm{~h~}}$ , possibly due to the severe dissolution of ${\\mathrm{RuO}}_{2}$ in the electrolytes.[20] The well-overlapped LSV curves before and after CV tests and well-maintained current densities at a set potential in $0.5\\textrm{\\textmu}\\mathrm{H}_{2}\\mathrm{S}\\mathrm{O}_{4}$ and $1\\mathrm{~\\bf~{~M~}~}$ KOH electrolytes reconfirm the remarkable electrocatalytic durability of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ catalyst during the OER process (Figure S17, Supporting Information). After the OER stability test, the unchanged Raman spectrum and homogeneously distribution of $\\mathrm{{Ru}}/\\mathrm{{Co}}$ atoms confirm the robustness of $\\mathrm{Ru}/\\mathrm{Co-N-C-800~^{\\circ}C}$ (Figure S18, Supporting Information). We also evaluated the OER performance of the as-prepared catalysts in neutral conditions. The required overpotential is $400~\\mathrm{mV}$ for $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ to realize a current density of 10 mA $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ , much lower than $\\mathrm{Ru-N-C-800\\^{\\circ}C}$ $(424\\mathrm{mV})$ and commercial $\\mathrm{RuO}_{2}$ $(461~\\mathrm{mV})$ (Figure S19a, Supporting Information). Importantly, the mass activity of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ at $1.7~\\mathrm{V}$ versus RHE is 413-times higher than commercial $\\mathrm{RuO}_{2}$ (Figure S19b, Supporting Information). Additionally, the applied potential to achieve 10  mA $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ for $\\mathrm{Ru/Co-N-C-}$ $800^{\\circ}\\mathrm{C}$ shows little increase during $20\\mathrm{h}$ , implying its stable performance (Figure S19c, Supporting Information). The almost overlapped LSV curves before and after the stability test further approve the robust properties of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ for OER in $^{\\mathrm{~1~u~}}$ PBS (Figure S19d, Supporting Information). Together, the low overpotential, ultrahigh TOF values, and robust stability highlight $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ as an outstanding catalyst for OER over a wide pH range. \n\n# 4. Electrochemical Performance of HER \n\nRu-based materials have been widely regarded as an attractive alternative to Pt-based catalysts for HER since they have similar metal–H bond strength.[29] We, therefore, investigated the HER performance of the as-prepared catalysts in $0.5\\textbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and $1\\mathrm{~M~}\\mathrm{KOH}$ , with commercial $20\\%$ $\\mathrm{Pt/C}$ as a reference. As shown in Figure 4a and Figure S20a,c (Supporting Information), $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ initiates HER at nearly zero overpotential. The required overpotential to deliver a current density of $10~\\mathrm{mA}$ $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ is merely 17 and $19~\\mathrm{mV}$ in $0.5\\textbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and 1 m KOH, which are superior to the $\\mathrm{Ru-N-C-800~^{\\circ}C}$ (44 and \n\n![](images/d2c450ec7394ca245f9af890d582976b3336798d0e8aaa9a24d0b51fb4d284ac.jpg) \nFigure 4.  Electrocatalytic HER performance of $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-}\\mathsf{N}\\mathrm{-}\\mathsf{C}\\mathrm{-}800\\ ^{\\circ}\\mathsf{C}$ compared with $R\\mathsf{u}-\\mathsf{N}-\\mathsf{C}\\cdot800^{\\circ}\\mathsf{C}$ , $C o{\\mathrm{-}}N{\\mathrm{-}}C{\\cdot}800^{\\circ}C$ , and commercial $20\\%$ Pt/C. a) HER polarization curves obtained at a scan rate of $5\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in ${\\mathsf N}_{2}$ -saturated $0.5~\\mathsf{m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and 1 m KOH. b) The corresponding Tafel plots in $0.5~\\mathsf{m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and 1 m KOH. c) Comparison of overpotential at 10 mA ${\\mathsf{c m}}_{\\mathsf{g e o}}{}^{-2}$ and Tafel slope with previously reported HER catalysts in acid and alkaline conditions. Other values were plotted from references in Tables S5 and S6, respectively. d) The chronopotentiometry curves of ${\\mathsf{R u}}/{\\mathsf{C o}}-{\\mathsf{N}}-{\\mathsf{C}}{\\mathsf{-}}800{\\mathsf{\\circ C}}$ and commercial $\\mathsf{P t}/\\mathsf{C}$ in $0.5~\\mathsf{m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and 1 m KOH. \n\n$32~\\mathrm{mV}_{\\mathrm{{i}}}$ respectively) and $\\mathrm{Co-N-C-800\\^{\\circ}C}$ , and even outperform commercial $\\mathrm{Pt/C}$ (33 and $23\\ \\mathrm{\\mV},$ respectively) under same conditions. The $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ also has the smallest Tafel slopes of 23.3 and $27.8~\\mathrm{mV~dec^{-1}}$ in $0.5\\textbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and $1\\textbf{M}$ KOH, respectively (Figure  4b), corresponding to the Volmer–Heyrovsky mechanism.[30] The TOF of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ is more than ten times higher than the previously reported Ru-based catalysts (Figure S20b,d, Supporting Information). To the best of our knowledge, the HER performance of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ surpasses most of the previously reported Ru-based HER catalysts in acid or alkaline conditions (Figure 4c; Tables S5 and S6, Supporting Information). Moreover, the chronoamperometric test at $-100~\\mathrm{{mA}}$ $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ highlights the exceptional stability of $\\mathrm{Ru/Co{-}N{-}C{-}800}$ in $0.5\\textrm{\\textmu}\\mathrm{H}_{2}\\mathrm{S}\\mathrm{O}_{4}$ and $1\\ \\mathrm{M}\\ \\mathrm{KOH}$ after $20\\mathrm{~h~}$ of electrolysis (Figure  4d). In contrast, the severe activity decay for commercial $\\mathrm{Pt/C}$ is observed, attributed to the dissolution of $\\mathrm{Pt}$ surface atoms and agglomeration of Pt particles.[31] The $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ catalyst shows good HER performance in $1\\textbf{M}$ PBS, with an overpotential of $87~\\mathrm{mV}$ at a current density of $10\\ \\mathrm{mA}$ $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ , which approaches that of the commercial $\\mathrm{Pt/C}$ $\\mathrm{58~mV}$ ), and is much better than that of $\\mathrm{Ru-N-C-}800\\ ^{\\circ}\\mathrm{C}$ $(102~\\mathrm{mV})$ ). The recorded chronopotentiometry curves at a constant current density of $-50\\ \\mathrm{\\mA}$ $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ manifest that the \n\nHER activity of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ is well-maintained for $20\\mathrm{h}$ (Figure S21, Supporting Information). \n\n# 5. Discussion \n\nTo gain insight into the origin of the excellent OER performance of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C,}$ we probed the adsorption energy of the first produced oxygenated intermediate $\\mathrm{OH^{*}}$ based on the onset potential of methanol oxidation reaction (MOR) since $\\mathrm{OH^{*}}$ is electrophiles and prone to react with nucleophiles such as alcohol molecules (Figures S22 and S23, Supporting Information).[32] The lower MOR onset potential of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ (1.17  V vs RHE) than $\\mathrm{Ru-N-C-800~^{\\circ}C}$ reflects that the former possesses a higher surface coverage of ${\\mathrm{OH}}^{*}$ intermediates, which may be associated with energetically more favorable water molecule dissociation on $\\mathrm{{Ru}}/\\mathrm{{Co}}$ dual sites. The high concentration of $\\mathrm{OH^{*}}$ intermediates is supposed to accelerate the formation of electrophilic $\\mathrm{O}^{(\\mathrm{II}-\\delta)-}$ species, which are more susceptible to nucleophilic attack by the water molecule, thereby improving OER performance.[33] The coverage of $\\mathrm{OH^{*}}$ shares a similar trend with the OER performance (Figure 5a). Compared with $\\mathrm{Ru-N-C-800~^{\\circ}C}$ and commercial $\\mathrm{RuO}_{2}$ , $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ demonstrates a much smaller Tafel slope at a high potential region after adding $\\mathrm{CH}_{3}\\mathrm{OH}$ , signifying much easier desorption of oxygenated intermediates.[34] Interestingly, the OER performance and bonding strength of ${\\mathrm{OH}}^{*}$ also share the same trend in $0.5\\textbf{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and $1\\ \\mathrm{M}\\ \\mathrm{KOH}$ : $\\mathrm{Ru}/\\mathrm{Co}{-\\mathrm{N}{-}}\\mathrm{C}{-}800\\ ^{\\circ}\\mathrm{C}>\\mathrm{Ru}{-}\\mathrm{N}{-}\\mathrm{C}{-}$ $800\\ ^{\\circ}\\mathrm{C}>\\mathrm{RuO}_{2}$ (Figure S24, Supporting Information). \n\n![](images/cd9849fc440f065602a2ed0cd4f5f859567221160b06bbf95952f4d8b461c38c.jpg) \nFigure 5.  a) The relationship between OER performance and the concentration of OH intermediates for $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-}\\mathsf{N-}\\mathsf{C}\\mathsf{-}800\\mathsf{\\textdegree C}$ , $R\\mathsf{u}-\\mathsf{N}-\\mathsf{C}-800^{\\circ}\\mathsf{C}.$ , and commercial ${\\sf R u O}_{2}$ . b) OER free energy diagram for $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-N-C}\\mathsf{-}800\\ ^{\\circ}\\mathsf{C}$ and $R\\mathsf{u}-\\mathsf{N}-\\mathsf{C}\\cdot800^{\\circ}\\mathsf{C}$ . Partial electronic density of states (PDOS) of c) Ru–N–C- $800^{\\circ}\\mathsf{C}$ and d) $R\\mathsf{u}/\\mathsf{C o-N-C-800}^{\\circ}\\mathsf{C}$ , (inset is the corresponding model). Differential charge density at the atomical Ru centers between Ru and neighboring $\\mathsf{C}/\\mathsf{N}$ atoms in e) $R\\mathsf{u}-\\mathsf{N}-\\mathsf{C}-800\\ ^{\\circ}\\mathsf{C}$ and f) ${\\sf R u}/{\\sf C o-N-C-800}^{\\circ}{\\sf C}.$ Yellow and blue contours represent electron accumulation and depletion, respectively. \n\nTo understand the synergistic effect between isolated RuN4 and CoN4 dual sites on the electrochemical reactions, we took the OER and HER in acid as an example to conduct density functional theory (DFT) calculations and model the configurations of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ catalyst (Figure S25a–d, Supporting Information). The strong water absorption ability is beneficial to the decomposition of water on the catalyst, which is the prerequisite step for OER in acids. The $\\mathrm{H}_{2}\\mathrm{O}$ adsorption energy of $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ and $\\mathrm{Ru-N-C-800~^{\\circ}C}$ are calculated based on the Ru site (Figure S25e, Supporting Information). The $\\mathrm{Ru/Co-N-C{\\cdot}800\\ ^{\\circ}C}$ shows a negligible energy barrier for water absorption, which is more favorable than $\\mathrm{Ru-N-C-800\\^{\\circ}C}$ . This result indicates that the surface states of Ru–N4 site can be regulated by introducing CoN4 sites, thus efficiently facilitating the water absorption and dissociation, which is in line with the higher OER activity. \n\nThe OER process usually involves four proton-electron transfer steps and three successive intermediates $(\\mathrm{OH^{*}}$ , $|\\boldsymbol{0}^{*}$ , and ${\\mathrm{OOH}}^{*}$ , where the asterisk denotes the adsorption site). As shown in Figure  5b and Figure S26, Supporting Information, the $\\mathrm{Ru}/\\mathrm{Co-N-C-800~^{\\circ}C}$ has the lower energy barrier for the rate-determining step (RDS) of the $\\mathrm{{_{OOH}}*}$ intermediate formation (reducing from 2.06 to $2.01\\mathrm{eV})$ ). Moreover, the partial density of states (PDOS) results for $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ with CoN4 sites reveal that the d-band center shifts to a low-energy level relative to $\\mathrm{Ru-N-C-800~^{\\circ}C}$ (Figure  5c,d). The negative shift of d-band center would increase the filling of as-hybridized antibonding orbitals $((\\mathrm{d}{-}\\sigma)^{*})$ and destabilize the interaction between the catalyst surface and the adsorbates, thus thermodynamically improving the binding ability of $\\mathrm{RuN}4$ sites with oxygen intermediates for better OER.[35] Besides, the integrated PDOS results show that the Ru 4d and O 2p centers get closer in $\\mathrm{Ru}/$ $\\mathrm{Co-N-C{\\cdot}800\\ ^{\\circ}C}$ , compared with $\\mathrm{Ru-N-C-800~^{\\circ}C}$ , indicating that the $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ with CoN4 sites exhibits a larger $\\mathrm{{Ru-O}}$ covalency than $\\mathrm{Ru-N-C-800~^{\\circ}C}$ (Table S7, Supporting Information). The enlarged Ru–O covalency can promote the electron transfer between the Ru sites and oxygenated adsorbates and decrease the binding strength of intermediates species on the surface of $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}.$ , thereby boosting the OER rate.[36] The additional calculations about electronic properties such as PDOSs of Ru atom in different models and the OER intermediates species are also investigated. As shown in Figure S27 (Supporting Information), all the d orbital of the Ru atom in $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ , involved with the initial reactants $\\mathrm{\\mathrm{^{*}O H}}$ towards the final product $\\mathbf{O}_{2}$ , shift towards the Fermi energy level with the modification of ${\\mathrm{Co-N}}4$ sites. This guarantees the efficient electron transfer and intermediate transformation during the OER process, indicating the enhanced catalytical activity of the Ru–N4 sites.[37] \n\nThe Bader charges of the Ru atom were performed to give a quantitative comparison of the electron transfer with and without the CoN4 sites. In comparison to $\\mathrm{Ru-N-C-800~^{\\circ}C}$ , the Ru sites in $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ with CoN4 sites gains an increased amount of electron $0.054~\\mathrm{e}^{-}$ per cell) from the adjacent $\\mathrm{C}/\\mathrm{N}$ atoms, suggesting that more electron transfer occurs between neighboring $\\mathrm{C}/\\mathrm{N}$ atoms and the isolated RuN4 sites, which is consistent with XAS results. Moreover, the differential charge density of $\\scriptstyle{\\mathrm{Ru-N}}4$ sites with CoN4 sites suggests that the $\\mathrm{C}/\\mathrm{N}$ atoms act as an electron reservoir to donate electrons to Ru sites, thus efficiently enhancing the resistance to over-oxidation and corrosion of Ru–N4 (Figure 5e,f).[6b] \n\nSimilarly, the Gibbs free energy of hydrogen adsorption $\\langle\\Delta G_{\\mathrm{H}^{*}}$ , \\* denotes an adsorption site) is a vital descriptor for appraising HER activity.[38] An optimum HER electrocatalyst is suggested with a small $\\left|\\Delta G_{\\mathrm{H}^{*}}\\right|$ value. $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ catalyst presents a smaller $\\Delta G_{\\mathrm{H^{*}}}$ $(-0.445\\ \\mathrm{eV})$ than that of $\\mathrm{Ru-N-}$ $\\mathrm{{C-800}^{\\circ}C}$ $(-0.585~\\mathrm{eV})$ in $0.5~\\mathrm{~M~}~\\mathrm{H}_{2}\\mathrm{SO}_{4},$ indicating that $\\mathrm{Ru}/$ $\\mathrm{Co-N-C-800~^{\\circ}C}$ possesses a better HER activity (Figure S25d, Supporting Information). Therefore, the correlations between HER activities and the calculated $\\Delta G_{\\mathrm{H^{*}}}$ values unveil that the incorporation of atomically CoN4 sites efficiently weakens the physiochemical interaction between Ru and H intermediate, thus promoting H adsorption/ $\\mathrm{\\ddot{H}}_{2}$ desorption and achieving a remarkable HER activity. \n\n# 6. Application for Overall Water-Splitting and PEM Water Electrolyzer \n\nEncouraged by the outstanding OER and HER activity of the $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ in a broad $\\mathrm{\\pH}$ range, we further employ $\\mathrm{Ru/Co-N-C-800~^{\\circ}C}$ as both the cathode and anode for overall water splitting. As shown in the polarization curve (Figure 6a), the cell voltage required for $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ is only 1.49 and $1.50~\\mathrm{V}$ to achieve a current density of 10  mA $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ in $0.5\\textbf{\\textmu}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ and $1\\mathrm{~M~KOH}$ , respectively, which is far lower than $\\mathrm{Pt}/\\$ $\\mathrm{C}\\|\\mathrm{RuO}_{2}$ and outperform most reported electrocatalysts to date (Figure  6c; Tables S8 and S9, Supporting Information). $\\mathrm{Ru}/$ $\\mathrm{Co-N-C-800\\^{\\circ}C}$ demonstrates remarkable stability in both acidic and alkaline, ranking it one of the best performing bifunctional electrocatalysts for overall water splitting over the broad $\\mathrm{\\pH}$ range in terms of both activity and stability (Figure  6b). In contrast, due to the rapid dissolution of $\\mathrm{RuO}_{2}$ , the applied potential of $\\mathrm{Pt/C\\|RuO}_{2}$ sharply increases to $1.75\\mathrm{V}$ after only $^{2\\mathrm{h}}$ . Finally, we apply the $\\mathrm{Ru/Co-N-C-800\\^{\\circ}C}$ in a homemade proton exchange membrane (PEM) water electrolyzer device and achieve steady operation at a current density of 450 mA $\\mathrm{cm}_{\\mathrm{geo}}{}^{-2}$ for $330\\mathrm{~h~}$ (Figure S28, Supporting Information), demonstrating the great potential of the catalyst for industrial applications. \n\n# 7. Conclusions \n\nAn atomically dispersed $\\mathrm{{Ru/Co}}$ dual-sites $(\\mathrm{Ru}/\\mathrm{Co-N-C-}$ $800~^{\\circ}\\mathrm{C})$ catalyst is designed for bifunctional and pH-universal electrocatalyst towards OER, HER, and overall water-splitting in a wide $\\mathrm{\\pH}$ range, which outperforms most of the electrocatalysts reported to date. Experimental results and theoretical calculations reveal that the main activity center of $\\mathrm{Ru/Co-N-}$ ${\\mathrm{C}}{\\cdot}800\\ {^{\\circ}}{\\mathrm{C}}$ is RuN4 sites, while CoN4 sites play a critical role in adjusting the electronic structure and bonding strength between oxygen/hydrogen intermediate species with RuN4 sites. Theoretical calculations further reveal that the introduction of ${\\mathrm{Co-N}}4$ sites can increase the electron density of $\\scriptstyle{\\mathrm{Ru-N}}4$ sites, thereby improving the resistance of $\\scriptstyle{\\mathrm{Ru-N}}4$ to over-oxidation and corrosion. These findings provide a new perspective for the design and synthesis of bifunctional single-atom electrocatalysts with bi- or multimetallic active sites for energyrelated conversions technologies such as water splitting, $\\mathrm{CO}_{2}$ reduction and nitrogen reductions and beyond. \n\n![](images/aace38e51c5060c0156bcac0cb2cdf0588bca743787eef45c8e94c6a2c2b110a.jpg) \nFigure 6.  Electrocatalytic overall water-splitting performance of $R\\mathsf{u}/\\mathsf{C o}\\mathrm{-}\\mathsf{N}\\mathrm{-}\\mathsf{C}\\mathsf{-}800\\ ^{\\circ}\\mathsf{C}$ in $0.5~\\mathsf{m}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and 1 m KOH. b) The chronopotentiometry curves of $R\\mathsf{u}/\\mathsf{C o-N-C-800\\ ^{\\circ}C}$ and commercial ${\\mathsf{R u O}}_{2}\\parallel{\\mathsf{P t}}/{\\mathsf{C}}$ in $0.5\\mathrm{~m~}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ and ${\\mathsf{1}}{\\mathsf{M}}$ KOH. c) Comparison of the required voltage of $R\\mathsf{u}/\\mathsf{C o-N-C-800}^{\\circ}\\mathsf{C}$ at 10 mA $\\mathsf{c m}_{\\mathsf{g e o}}{}^{-2}$ with reported electrocatalysts in acid and alkaline conditions. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# Data Availability Statement \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Supporting Information \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\n# Keywords \n\nelectrochemical energy conversion, hydrogen, ruthenium cobalt, singleatom catalysts, water splitting \n\n# Acknowledgements \n\nC.R. and X.S. contributed equally to this work. The study was supported by Australian Research Council (FT170100224, DP210103892, IC200100023). The authors thank the support from UNSW Mark Wainwright Analytical Centre and the Australian Synchrotron for the award of the soft XAS beamtime. X.J.S. thanks the National Natural Science Foundation of China (Grant No. 21873086) and the computational time supported by the National Supercomputer Center in Zhengzhou and Henan Supercomputer Center in Zhengzhou University. The authors acknowledge Dr. Chen Jia and Dr. David R G Mitchell for assistance in TEM tests and Dr. Kamran Dastafkan for the manuscript polishment. \n\nOpen access publishing facilitated by University of New South Wales, as part of the Wiley - University of New South Wales agreement via the Council of Australian University Librarians. \n\nReceived: December 12, 2021 \nRevised: March 25, 2022 \nPublished online: April 24, 2022 \n\n2535; e) F. Luo, H. Hu, X. Zhao, Z. Yang, Q. Zhang, J. Xu, T. Kaneko, Y. Yoshida, C. Zhu, W. Cai, Nano Lett. 2020, 20, 2120. \n[4]\t C. C.  McCrory, S.  Jung, I. M.  Ferrer, S. M.  Chatman, J. C.  Peters, T. F. Jaramillo, J. Am. Chem. Soc. 2015, 137, 4347. \n[5]\t W.  Li, Y.  Zhao, Y.  Liu, M.  Sun, G. I.  Waterhouse, B.  Huang, K. Zhang, T. Zhang, S. Lu, Angew. Chem., Int. Ed. 2021, 60, 3290. \n[6]\t a) A.  Grimaud, O.  Diaz-Morales, B.  Han, W. T.  Hong, Y.-L.  Lee, L.  Giordano, K. A.  Stoerzinger, M. T.  Koper, Y.  Shao-Horn, Nat. Chem. 2017, 9, 457; b) Y.  Yao, S.  Hu, W.  Chen, Z.-Q.  Huang, W.  Wei, T.  Yao, R.  Liu, K.  Zang, X.  Wang, G.  Wu, W.  Yuan, T.  Yuan, B.  Zhu, W.  Liu, Z.  Li, D.  He, Z.  Xue, Y.  Wang, X.  Zheng, J.  Dong, C.-R.  Chang, Y.  Chen, X.  Hong, J.  Luo, S.  Wei, W.-X.  Li, P.  Strasser, Y. Wu, Y. Li, Nat. Catal. 2019, 2, 304. \n[7]\t a) J. Wang, Z. Wei, S. Mao, H. Li, Y. Wang, Energy Environ. Sci. 2018, 11, 800; b) M. Lao, G. Zhao, P. Li, T. Ma, Y. Jiang, H. Pan, S. X. Dou, W. Sun, Adv. Funct. Mater. 2021, 31, 2100698. \n[8]\t a) L.  Bai, Z.  Duan, X.  Wen, R.  Si, Q.  Zhang, J.  Guan, ACS Catal. 2019, 9, 9897; b) B. Lu, L. Guo, F. Wu, Y. Peng, J. E. Lu, T. J. Smart, N. Wang, Y. Z. Finfrock, D. Morris, P. Zhang, Nat. Commun. 2019, 10, 631. \n[9]\t a) X.  Wan, X.  Liu, Y.  Li, R.  Yu, L.  Zheng, W.  Yan, H.  Wang, M.  Xu, J.  Shui, Nat. Catal. 2019, 2, 259; b) Y.  Xue, B.  Huang, Y.  Yi, Y.  Guo, Z.  Zuo, Y.  Li, Z.  Jia, H.  Liu, Y.  Li, Nat. Commun. 2018, 9, 1460. \n[10]\t a) Z.  Lu, B.  Wang, Y.  Hu, W.  Liu, Y.  Zhao, R.  Yang, Z.  Li, J.  Luo, B.  Chi, Z.  Jiang, Angew. Chem., Int. Ed. 2019, 131, 2648; b) X.  Zhu, D.  Zhang, C.-J.  Chen, Q.  Zhang, R.-S.  Liu, Z.  Xia, L.  Dai, R.  Amal, X. Lu, Nano Energy 2020, 71, 104597. \n[11]\t W. Ren, X. Tan, W. Yang, C. Jia, S. Xu, K. Wang, S. C. Smith, C. Zhao, Angew. Chem., Int. Ed. 2019, 58, 6972. \n[12]\t G.  Yang, J.  Zhu, P.  Yuan, Y.  Hu, G.  Qu, B.-A.  Lu, X.  Xue, H.  Yin, W. Cheng, J. Cheng, Nat. Commun. 2021, 12, 1734. \n[13]\t A.  Wong, Q.  Liu, S.  Griffin, A.  Nicholls, J.  Regalbuto, Science 2017, 358, 1427. \n[14]\t Y. Xu, W. Tu, B. Zhang, S. Yin, Y. Huang, M. Kraft, R. Xu, Adv. Mater. 2017, 29, 1605957. \n[15]\t Y.  Tang, W.  Li, L.  Jiao, F.  Li, Y.  Yang, X.  Wang, W.  Gao, R.  Li, New J. Chem. 2017, 41, 12956. \n[16]\t Y.-Y.  Chen, Y.  Zhang, W.-J.  Jiang, X.  Zhang, Z.  Dai, L.-J.  Wan, J.-S. Hu, ACS Nano 2016, 10, 8851. \n[17]\t B.  Bayatsarmadi, Y.  Zheng, Y.  Tang, M.  Jaroniec, S. Z.  Qiao, Small 2016, 12, 3703. \n[18]\t J.  Casanovas, J. M.  Ricart, J.  Rubio, F.  Illas, J. M.  Jiménez-Mateos, J. Am. Chem. Soc. 1996, 118, 8071. \n[19]\t H.  Zhang, Q.  Jiang, J. H. L.  Hadden, F.  Xie, D. J.  Riley, Adv. Funct. Mater. 2021, 31, 2008989. \n[20]\t K.  Sardar, E.  Petrucco, C. I.  Hiley, J. D.  Sharman, P. P.  Wells, A. E.  Russell, R. J.  Kashtiban, J.  Sloan, R. I.  Walton, Angew. Chem., Int. Ed. 2014, 53, 10960. \n[21]\t L.  Cao, Q.  Luo, J.  Chen, L.  Wang, Y.  Lin, H.  Wang, X.  Liu, X.  Shen, W.  Zhang, W.  Liu, Z.  Qi, Z.  Jiang, J.  Yang, T.  Yao, Nat. Commun. 2019, 10, 4849. \n[22]\t M. Luo, S. Guo, Nat. Rev. Mater. 2017, 2, 17059. \n[23]\t T. Yamamoto, X-Ray Spectrom. 2008, 37, 572. \n[24]\t H. B.  Yang, S.-F.  Hung, S.  Liu, K.  Yuan, S.  Miao, L.  Zhang, X. Huang, H.-Y. Wang, W. Cai, R. Chen, Nat. Energy 2018, 3, 140. \n[25]\t H.  Zhang, S.  Zuo, M.  Qiu, S.  Wang, Y.  Zhang, J.  Zhang, X. W. D. Lou, Sci. Adv. 2020, 6, eabb9823. \n[26]\t P. Yin, T. Yao, Y. Wu, L. Zheng, Y. Lin, W. Liu, H. Ju, J. Zhu, X. Hong, Z. Deng, Angew. Chem., Int. Ed. 2016, 128, 10958. \n[27]\t Y. Liu, S. Liu, Y. Wang, Q. Zhang, L. Gu, S. Zhao, D. Xu, Y. Li, J. Bao, Z. Dai, J. Am. Chem. Soc. 2018, 140, 2731. \n[28]\t K.-L. Yan, J.-F. Qin, J.-H. Lin, B. Dong, J.-Q. Chi, Z.-Z. Liu, F.-N. Dai, Y.-M. Chai, C.-G. Liu, J. Mater. Chem. A 2018, 6, 5678. \n[29]\t Y.  Zheng, Y.  Jiao, Y.  Zhu, L. H.  Li, Y.  Han, Y.  Chen, M.  Jaroniec, S.-Z. Qiao, J. Am. Chem. Soc. 2016, 138, 16174. \n[30]\t J.  Xiong, J.  Li, J.  Shi, X.  Zhang, N.-T.  Suen, Z.  Liu, Y.  Huang, G.  Xu, W. Cai, X. Lei, ACS Energy Lett. 2018, 3, 341. \n[31]\t Y. Zhu, H. A. Tahini, Z. Hu, J. Dai, Y. Chen, H. Sun, W. Zhou, M. Liu, S. C. Smith, H. Wang, Nat. Commun. 2019, 10, 149. \n[32]\t H. B.  Tao, Y.  Xu, X.  Huang, J.  Chen, L.  Pei, J.  Zhang, J. G.  Chen, B. Liu, Joule 2019, 3, 1498. \n[33]\t a) T. Reier, Z. Pawolek, S. Cherevko, M. Bruns, T. Jones, D. Teschner, S. r. Selve, A. Bergmann, H. N. Nong, R. Schlögl, J. Am. Chem. Soc. 2015, 137, 13031; b) V.  Pfeifer, T. E.  Jones, S.  Wrabetz, C.  Massué, J. J. V.  Vélez, R.  Arrigo, M.  Scherzer, S.  Piccinin, M.  Hävecker, A. Knop-Gericke, Chem. Sci. 2016, 7, 6791. \n[34]\t W. Gou, M. Zhang, Y. Zou, X. Zhou, Y. Qu, ChemCatChem 2019, 11, 6008. \n[35]\t J. He, X. Zhou, P. Xu, J. Sun, Adv. Energy Mater. 2021, 2102883. \n[36]\t Y. Zhou, S. Sun, J. Song, S. Xi, B. Chen, Y. Du, A. C. Fisher, F. Cheng, X. Wang, H. Zhang, Adv. Mater. 2018, 30, 1802912. \n[37]\t a) T.  Dai, X.  Zhang, M.  Sun, B.  Huang, N.  Zhang, P.  Da, R.  Yang, Z.  He, W.  Wang, P.  Xi, Adv. Mater. 2021, 33, 2102593; b) Y.  Wang, S. Tao, H. Lin, G. Wang, K. Zhao, R. Cai, K. Tao, C. Zhang, M. Sun, J. Hu, Nano Energy 2021, 81, 105606. \n[38]\t Y.  Li, X.  Tan, S.  Chen, X.  Bo, H.  Ren, S. C.  Smith, C.  Zhao, Angew. Chem., Int. Ed. 2019, 58, 461. " + }, + { + "id": "10.1007_s40820-022-00906-5", + "DOI": "10.1007/s40820-022-00906-5", + "DOI Link": "http://dx.doi.org/10.1007/s40820-022-00906-5", + "Relative Dir Path": "mds/10.1007_s40820-022-00906-5", + "Article Title": "Ultrabroad Microwave Absorption Ability and Infrared Stealth Property of nullo-Micro CuS@rGO Lightweight Aerogels", + "Authors": "Wu, Y; Zhao, Y; Zhou, M; Tan, SJ; Peymanfar, R; Aslibeiki, B; Ji, GB", + "Source Title": "nullO-MICRO LETTERS", + "Abstract": "Developing ultrabroad radar-infrared compatible stealth materials has turned into a research hotspot, which is still a problem to be solved. Herein, the copper sulfide wrapped by reduced graphene oxide to obtain three-dimensional (3D) porous network composite aerogels (CuS@rGO) were synthesized via thermal reduction ways (hydrothermal, ascorbic acid reduction) and freeze-drying strategy. It was discovered that the phase components (rGO and CuS phases) and micro/nullo structure (microporous and nullosheet) were well-modified by modulating the additive amounts of CuS and changing the reduction ways, which resulted in the variation of the pore structure, defects, complex permittivity, microwave absorption, radar cross section (RCS) reduction value and infrared (IR) emissivity. Notably, the obtained CuS@rGO aerogels with a single dielectric loss type can achieve an ultrabroad bandwidth of 8.44 GHz at 2.8 mm with the low filler content of 6 wt% by a hydrothermal method. Besides, the composite aerogel via the ascorbic acid reduction realizes the minimum reflection loss (RLmin) of - 60.3 dB with the lower filler content of 2 wt%. The RCS reduction value can reach 53.3 dB m(2), which effectively reduces the probability of the target being detected by the radar detector. Furthermore, the laminated porous architecture and multicomponent endowed composite aerogels with thermal insulation and IR stealth versatility. Thus, this work offers a facile method to design and develop porous rGO-based composite aerogel absorbers with radar-IR compatible stealth.", + "Times Cited, WoS Core": 310, + "Times Cited, All Databases": 324, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000842159200002", + "Markdown": "# Ultrabroad Microwave Absorption Ability and Infrared Stealth Property of Nano‑Micro CuS@ rGO Lightweight Aerogels \n\nReceived: 11 June 2022 \nAccepted: 2 July 2022 \nPublished online: 20 August 2022 \n$\\circledcirc$ The Author(s) 2022 \n\nYue ${\\mathbf{W}}{\\mathbf{u}}^{1}$ , Yue Zhao1, Ming Zhou1, Shujuan Tan1 \\*, Reza Peymanfar2, Bagher Aslibeiki3, Guangbin Ji1 \\* \n\n# HIGHLIGHTS \n\n•\t The $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogel can achieve the broad effective absorption bandwidth (EAB) of $8.44\\:\\mathrm{GHz}$ with the filler content of $6\\mathrm{wt}\\%$ . \n\n•\t The ${\\mathrm{RL}}_{\\operatorname*{min}}$ of $\\mathrm{CuS@rGO}$ composite aerogel is -55.1 dB and EAB is $7.2\\mathrm{GHz}$ with the filler content of $2\\mathrm{wt}\\%$ by ascorbic acid thermal reduction. The radar cross-section reduction value of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogel can reach $53.3\\mathrm{dB}\\mathrm{m}^{2}$ . \n\n•\t The $\\mathrm{CuS@rGO}$ composite aerogels possess lightweight, compression and recovery, radar-infrared compatible stealth properties. \n\nABSTRACT  Developing ultrabroad radar-infrared compatible stealth materials has turned into a research hotspot, which is still a problem to be solved. Herein, the copper sulfide wrapped by reduced graphene oxide to obtain threedimensional (3D) porous network composite aerogels $(\\mathbf{CuS}@\\mathbf{rGO})$ were synthesized via thermal reduction ways (hydrothermal, ascorbic acid reduction) and freeze-drying strategy. It was discovered that the phase components (rGO and $\\mathrm{CuS}$ phases) and micro/nano structure (microporous and nanosheet) were well-modified by modulating the additive amounts of $\\mathtt{C u S}$ and changing the reduction ways, which resulted in the variation of the pore structure, defects, complex permittivity, microwave absorption, radar cross section (RCS) reduction value and infrared (IR) emissivity. Notably, the obtained $\\mathrm{CuS@rGO}$ aerogels with a single dielectric loss type can achieve an ultrabroad bandwidth of $8.44\\:\\mathrm{GHz}$ at $2.8~\\mathrm{mm}$ with the low filler content of $6\\mathrm{wt}\\%$ by a hydrothermal method. Besides, the composite aerogel via the ascorbic acid reduction realizes the minimum reflection loss $(\\mathrm{RL}_{\\operatorname*{min}})$ of $-60.3\\mathrm{dB}$ with the lower filler content of $2\\mathrm{wt}\\%$ . The RCS reduction value can reach $53.3\\mathrm{dB}\\mathrm{m}^{2}$ , which effectively reduces the probability of the target being detected by the radar detector. Furthermore, the laminated porous architecture and multicomponent endowed composite aerogels with thermal insulation and IR stealth versatility. Thus, this work offers a facile method to design and develop porous rGO-based composite aerogel absorbers with radar-IR compatible stealth. \n\n![](images/c85f078032d3b816260d02c99a4cf46c584e964247936d3e8641a0483eaf3fa2.jpg) \n\nKEYWORDS  Microwave absorption; Ultrabroad bandwidth; Composite aerogel; Radar cross section; Radar-infrared compatible stealth \n\n# 1  Introduction \n\nWith the fast development of detection technology, stealth materials have attracted extensive attention [1–3]. However, single-waveband stealth materials are hard to satisfy the requirement of harsh environments, and multispectral compatible stealth is becoming the future direction of stealth materials [4–6]. Particularly, with the occurrence of advanced precision-guided weapons and infrared (IR) detectors, designing and exploring the radar-IR compatible stealth materials is of great significance with low IR emissivity and excellent microwave absorbing (MA) ability. Usually, microwave absorbers need low reflectivity and high absorptivity [7–9], while IR stealth materials require high reflectivity and low IR absorptivity [10]. Furthermore, outstanding thermal insulation ability is also required for IR stealth materials according to the StefanBoltzmann theory [11]. Thus, it seems to be challenging to integrate IR and radar stealth owing to the thoroughly opposite principles. \n\nTo achieve radar-IR compatible stealth, it is of significance to overcome the issue of conflict between IR and radar camouflage material requirements. $\\mathrm{CuS}$ , a kind of semiconductor transition metal sulfide, has caused broad concern in the IR stealth field owing to the absorbance behavior of local surface plasmon resonance in the near-IR region [12]. At the same time, CuS has also been applied as microwave absorbers due to its exceptional electrical property and unique geometrical micromorphology. For instance, Cui et al. prepared a sandwich-like $\\mathrm{CuS/Ti_{3}C_{2}T_{\\it x}}$ MXene composites and got the ${\\mathrm{RL}}_{\\operatorname*{min}}$ value of $-45.3\\mathrm{dB}$ and the effective absorption bandwidth (EAB) of $5.2\\:\\mathrm{GHz}$ with the filler content of $35\\ \\mathrm{wt}\\%$ [13]. Quaternary composite of $\\mathrm{CuS/RGO/PANI/Fe_{3}O_{4}}$ was fabricated and the influence of special microstructure on MA capacity was further studied by Wang’s group [14]. The ${\\mathrm{RL}}_{\\operatorname*{min}}$ of the products was $-60.2\\ \\mathrm{dB}$ and absorption bandwidth below $-10\\mathrm{dB}$ was up to $7.4\\:\\mathrm{GHz}$ . Liu and his team designed $\\mathrm{CuS}$ nanoflakes aligned on magnetically decorated graphene via a solvothermal method [15], and found that the different morphologies of nanocomposites showed excellent MA capacity, that was the EAB of $4.5\\:\\mathrm{GHz}$ and ${\\mathrm{RL}}_{\\operatorname*{min}}$ value of -54.5 dB. Guan et al. synthesized a series of $\\mathrm{{CuS/}}$ $Z\\mathrm{nS}$ nanocomposites with a 3D hierarchical structure by a hydrothermal method [16]. The obtained nanocomposite possessed the ${\\mathrm{RL}}_{\\operatorname*{min}}$ value of − 22.6 dB at $9.7\\mathrm{GHz}$ with the thickness of $3\\mathrm{mm}$ and the EAB of 2.2 GHz (9.2–11.4 GHz). Therefore, CuS-based composites show the application prospects in the field of microwave absorption. \n\nIntegrating $\\mathrm{CuS}$ into thermal-insulating materials is provided a new perspective to design the IR-radar compatible stealth materials. Carbon materials such as carbon nanotubes and graphene have been applied as building blocks to create lightweight and multifunctional microwave absorbers due to their lightweight, conspicuous chemical and mechanical properties, high stability, etc. [17, 18]. Numerous researchers have combined graphene with metallic compounds $\\mathrm{\\Delta}Z\\mathrm{nO}$ , $\\mathrm{CeO}_{2}$ , $\\mathbf{MoS}_{2}$ , etc.) and magnetic nanoparticles (Ni, Fe, Co, or its alloys) or magnetic compounds (typical ferrites) to fabricate composite powder absorbers that can achieve the integration of dielectric/magnetic loss, and optimize the impedance mismatch owing to the poor impedance matching form single graphene [19, 20]. Although they have achieved excellent MA ability, these composites are hard to meet the other functions for unique applicated environments. Besides, common powder materials also have high filler contents and density. In recent years, aerogels with high porosity $(>95\\%)$ and extremely low density $(<0.1\\ \\mathrm{g}\\ \\mathrm{cm}^{-3})$ ) have been attractive to researchers [21]. Among them, graphene-based aerogels consisting of interconnected 3D networks of graphene sheets are gained wide attention for their low cost and density, facile synthesis, unique porous structure, and large specific surface area. Moreover, the porous graphene-based aerogels possess the superior thermal-insulating effect for the existence of high porous, air phase, and 3D network structure. The studies on graphene/Ni aerogel [22], $\\mathrm{CoFe}_{2}\\mathrm{O}_{4}/\\mathrm{N}$ -doped reduced graphene oxide aerogel [23], polyaniline/graphene aerogel [24], and SiC whiskers/reduced graphene oxide aerogel [25] have further confirmed that the composition regulation of graphene-based composite aerogels is conducive to achieving effective absorption bandwidth (EAB) and reducing the filler contents. \n\nCurrently, foams and aerogels with porous network structure, high porosity, high specific surface area, such as melamine hybrid foam [26], chitosan-derived carbon aerogels [27], porous carbon $@\\mathrm{CuS}$ [11], antimony tin oxide/rGO aerogels [28], cobalt ferrite/carbon nanotubes/waterborne polyurethane hybrid aerogels [29], $\\mathrm{Fe}/\\mathrm{Fe}_{2}\\mathrm{O}_{3}@$ porous carbon composites [30], cellulose-chitosan framework/polyaniline hybrid aerogel [31], rGO/MWCNT-melamine composite [32], organic-inorganic hybrid aerogel [33], and $\\mathrm{rGO}/\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ [34], are commonly applied as radar-IR stealth materials. Although the reported carbon-based radar-IR compatible stealth materials can achieve MA performance and thermal/ IR stealth, it is difficult to gain a wide EAB $(>8\\mathrm{{GHz}})$ ) and low IR emissivity $(<6.5)$ with a low filler content $(<5\\mathrm{\\wt}\\%)$ ). \n\nIn this work, two kinds of 3D porous $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels were synthesized by hydrothermal and ascorbic acid thermal reduction methods and subsequent freeze-drying technique. Thanks to the bicomponent synergistic effect and their unique porous architecture, the obtained composite aerogels achieved MA performance and IR stealth ability. By modulating the additive amounts of $\\mathrm{CuS}$ powders and thermal reduction ways, the porous $\\operatorname{CuS}@\\operatorname{rGO}$ aerogels manifested adjustable MA capacity and IR emissivity. Notably, an excellent MA performance of $\\operatorname{CuS}@\\operatorname{rGO}$ $\\mathrm{30mg)}$ aerogel with the widest EAB of $8.44\\:\\mathrm{GHz}$ and ${\\mathrm{RL}}_{\\operatorname*{min}}$ of $-40.2$ dB at an extremely low filler content of merely $6\\mathrm{wt}\\%$ could be achieved. Besides, the low IR emissivity of 0.6442 was also obtained by adjusting the additive amounts of $\\mathtt{C u S}$ . Furthermore, the MA and IR stealth mechanisms of $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogels were investigated in detail. This work exploits a novel path in the design and development of radarIR compatible stealth materials that can work in the today’s complex environment. \n\n# 2  \u0007Experimental Section \n\n# 2.1  \u0007Materials \n\nCopper chloride dihydrate $\\mathrm{(CuCl}_{2}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O})_{2}^{\\cdot}$ ), ethylene glycol (EG), thiourea $\\mathrm{(CH_{4}N_{2}S)}$ , ascorbic acid and anhydrous ethanol $(\\mathrm{C}_{2}\\mathrm{H}_{5}\\mathrm{OH})$ were all bought from the Nanjing Chemical Reagent Co., Ltd. Graphite oxide was provided by Suzhou TANFENG Graphene Tech Co., Ltd. (Suzhou, China). All of the chemical reagents were analytically pure and employed without further purification. \n\n# 2.2  \u0007Preparation of CuS Microspheres \n\nThe CuS microspheres were prepared via an ordinary solvothermal strategy. $\\mathrm{CuCl}_{2}{\\cdot}2\\mathrm{H}_{2}\\mathrm{O}$ (6 mmol) was dissolved in $30~\\mathrm{mL}$ of EG, which was named solution A that was quickly turned from blue to dark green. $\\mathrm{CH}_{4}\\mathrm{N}_{2}\\mathrm{S}$ $24\\mathrm{mmol},$ was dispersed in another $30~\\mathrm{mL}$ of EG that was marked as solution \n\n$B$ at the same time. Then, solution $B$ was poured into solution $A$ , and continuously stirred for $0.5\\mathrm{h}$ until the solution became transparent. Next, the final solution was transformed into a Teflon-lined autoclave ( $\\mathrm{100~mL}$ ) and maintained at $170^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ . The products were collected by centrifugation with distilled water and anhydrous ethanol several times. Finally, the products were dried at $60~^{\\circ}\\mathrm{C}$ in a vacuum oven. \n\n# 2.3  \u0007Preparation via the Hydrothermal Method \n\nThe 3D porous $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogels were synthesized via a hydrothermal method. First, a certain amount of $\\mathrm{CuS}$ powders (0, 15, 30, 60, and $120\\mathrm{mg}$ ) and $120\\mathrm{mg}$ of multilayer graphite oxide were dispersed into distilled water $\\mathrm{30~mL}$ ) under ultrasonication for $^\\textrm{\\scriptsize1h}$ and subsequently stirred for $0.5\\mathrm{~h~}$ . Then, the dispersions were placed into a Teflon-lined autoclave $\\mathrm{50~mL}$ and lasted at $120^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . Finally, the obtained $\\mathrm{CuS@rGO}$ composite hydrogels were dialyzed in anhydrous ethanol/distilled water solution with a volume ratio of 1:9 for $^{48\\mathrm{~h~}}$ and then freeze-drying at $-50{}^{\\circ}\\mathrm{C}$ for $48\\mathrm{~h~}$ to obtain $\\mathrm{CuS@rGO}$ composite aerogels. The composite aerogels were marked as rC-1, rC-2, rC-3, $\\scriptstyle{\\mathrm{rC}}-4$ , and $\\operatorname{rC}-5$ . \n\n# 2.4  \u0007Preparation via the Ascorbic Acid Reduction Method \n\nThe 3D porous $\\mathrm{CuS@rGO}$ composite aerogels were synthesized via the ascorbic acid reduction method. First, a certain amount of $\\mathrm{CuS}$ powders (0, 10, 20, 30, and $40~\\mathrm{mg}$ ), $80~\\mathrm{{mg}}$ of multilayer graphite oxide and $\\boldsymbol{1.2\\mathrm{\\g}}$ ascorbic acid were dispersed into distilled water $(20\\mathrm{mL}$ ) under the ultrasonication treatment for $^{\\textrm{1h}}$ and stirred for $0.5\\mathrm{h}$ . Then, the dispersions were poured into a custom silicone mold ( $25~\\mathrm{mL}$ ) at $95~^{\\circ}\\mathrm{C}$ for $12\\mathrm{h}$ . Finally, the obtained $\\operatorname{CuS}@\\operatorname{rGO}$ composite hydrogels were dialyzed in anhydrous ethanol/distilled water solution with a volume ratio of 1:9 for $48\\mathrm{h}$ and then freezedrying at $-50{}^{\\circ}\\mathrm{C}$ for $48\\mathrm{~h~}$ to obtain $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogels. The composite aerogels were labeled as RC-1, RC-2, RC-3, RC-4, and RC-5. \n\n# 2.5  \u0007Characterization \n\nThe composition and crystal structure of $\\mathrm{CuS@rGO}$ aerogels were investigated by X-ray diffraction (XRD, Bruker D8 \n\nADVANCE, equipped with $\\mathrm{Cu-K}\\alpha$ radiation). X-ray photoelectron spectroscopy (XPS) was carried out on a Kratos AXIS Ultra spectrometer with the Al ${\\mathrm K}\\alpha$ X-rays as the excitation source. The micromorphology was characterized by a Hitachi S4800 field emission scanning electron microscope (SEM) and a Talos F200X transmission electron microscopy (TEM) equipped with energy dispersive spectrum (EDS). \n\n# 2.6  \u0007Microwave Absorption Measurements \n\nThe EM parameters of complex permeability $(\\mu_{r}=\\mu^{\\prime}{-}j\\mu^{\\prime\\prime})$ and complex permittivity $(\\varepsilon_{r}=\\varepsilon^{\\prime}-j\\varepsilon^{\\prime\\prime})$ were measured by the vector network analyzer (VNA, Agilent PNA N5244A) adopting the coaxial line method. The rC aerogels $(6~\\mathrm{wt}\\%)$ were mixed with $94\\mathrm{\\wt\\%}$ paraffin, and RC aerogels (1 and $2\\ \\mathrm{wt}\\%\\$ ) respectively mixed with 99 and $98\\ \\mathrm{wt}\\%$ paraffin, and then pressed into a toroidal ring of the inner diameter of $3.04\\mathrm{mm}$ and out diameter of $7.00\\mathrm{mm}$ . \n\n# 2.7  \u0007Computer Simulation Technology \n\nComputer simulation technology (CST) studio Suite 2018 was applied to simulate the RCS values of as-prepared $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels under open boundary conditions. The simulation model consisted of the perfect electric conductor (PEC) layer with a thickness of $1.0~\\mathrm{mm}$ at the bottom and an absorbing layer with a thickness of $2.0\\ \\mathrm{mm}$ on the top. The dimension of length was equal to the width of $200\\mathrm{mm}$ . Then, the created model was placed on the $x{\\bf O y}$ plane, and the linear polarized plane EMW was added with the incidence direction on $Z$ -axis positive to negative, and the electric polarization was along the $X$ -axis. In addition, the far-field monitor frequency was set as $15.7\\:\\mathrm{GHz}$ . The RCS values could be computed as follows [35]: \n\n$$\n\\sigma=10\\mathrm{log}\\bigg({\\frac{4\\pi S}{\\lambda^{2}}}\\bigg|{\\frac{E_{\\mathrm{S}}}{E_{\\mathrm{i}}}}\\bigg|\\bigg)^{2}\n$$ \n\nwhere $\\lambda$ and $S$ ar|e the| wavelength of incident wave and area of the simulation model, $E_{\\mathrm{i}}$ and $E_{\\mathrm{s}}$ are the intensity of electric field of the incident and scatted EMWs, respectively. \n\n# 2.8  \u0007IR Stealth Measurement \n\nThe IR-2 dual-band IR emissivity meter was used to test the IR emissivity in the waveband of $3\\sim5$ and $8\\sim14~{\\upmu\\mathrm{m}}$ . \n\nThermal IR imaging digital images were recorded by TVS$2000\\mathbf{MK}$ with a heating platform, and the temperature was set as $120^{\\circ}\\mathrm{C}$ . \n\n# 3  \u0007Results and Discussion \n\n# 3.1  \u0007Preparation and Reduction Mechanism \n\nThe synthetic processes of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels are depicted in Fig.  1. The first step is to fabricate $\\mathtt{C u S}$ flower-like microspheres via a solvothermal method in Fig. 1a. Then, the 3D porous $\\mathrm{CuS@rGO}$ composite aerogels were fabricated through complexing $\\mathrm{CuS}$ in graphene/deionized water dispersion and combining with freeze-drying technique. Hydrothermal (Fig. 1b) and ascorbic acid reduction (Fig. 1c) methods were employed for the preparation of $\\operatorname{CuS}@\\operatorname{rGO}$ composite hydrogels, and the freeze-drying technique was applied to obtain the corresponding aerogels with 3D porous architecture. The reduction processes of hydrothermal method can be illustrated in Fig. S1a–b [36]. The carboxyl functional groups can be reduced through a hydrothermal method. As depicted in Fig. S1a, the decarboxylation reaction is accompanied by the production of carbon dioxide. The deoxidation processes of epoxide groups to form a carbon-carbon double bond can be divided into two steps (Fig. S1b). The first step is that the ring of epoxide groups is opened in the existence of formic acid by the acidcatalyzed reaction to produce alcohol in the decarboxylation reaction. The nucleophilic reagent or strong bases can attack the ternary ring of epoxide groups and then relieve the strain energy. Under the circumstances, the hydride ions of formic acid work as nucleophiles at the hydrothermal reaction temperature. First, the epoxide groups are protonated, which activates them to attack the nucleophile. Then, the carbocation is formed that is attacked by hydride ions from formic acid, and the ring is opened to generate alcohol. The second step refers to the dehydration reaction of alcohol to carbon-carbon double bonds with the help of an acidic medium. The -OH (weak leaving groups) needs the protonation reaction to transform it to $\\mathrm{H}_{2}\\mathrm{O}$ which is easy to leave. A carbocation is formed by water loss, and the water then absorbs the protons to generate carbon-carbon double bonds in rGO. The reduction mechanisms for rGO under the action of ascorbic acid are depicted in Fig. S1c [37]. The carboxyl, epoxy, carbonyl and hydroxyl groups are existed on the surfaces or at the edge of the graphene oxide (GO) sheet. The ascorbic acid can liberate two protons to obtain dehydroascorbic acid, while the protons usually possess a strong affinity with the oxygen-containing groups that can react to form water molecules during the reduction of GO to rGO. At the same time, a number of the neighboring carbon atoms will be taken away as the oxygen-containing functional groups are removed, which can cause vacancy defects in the rGO. Due to the difference in reduction strategies, it can be inferred that the structure of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels is also different. Thus, we have further measured the physical parameters of $\\mathrm{\\Delta}_{\\mathrm{rC}}$ composite aerogels. It can be found that the as-prepared aerogels have a few differences in size, including the length, radius and even the mass weight (Table S1). The density of rC composite aerogels is approximate $0.01\\ \\mathrm{g}\\ \\mathrm{cm}^{-3}$ , and is increased with the additive amounts of $\\mathrm{CuS}$ . The results are that the pure rGO aerogel possesses the lowest density of $0.0110\\ \\mathrm{g}\\mathrm{cm}^{-3}$ , while the rC-5 has the largest density of $0.0160\\ {\\mathrm{g}}\\ {\\mathrm{cm}}^{-3}$ . \n\n![](images/d0f00000cb307bc156cc34564ddcda9ac712af8aba83c61a38853d2675ad9796.jpg) \nFig. 1   Schematic diagram of preparation processes of a flower-like CuS microspheres, and b, c $\\mathrm{CuS}@$ rGO composite aerogels through a hydrothermal method (b), and via the ascorbic acid thermal reduction (c) \n\nTo confirm the characteristic of lightweight, it is observed that the $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogel can stand on the petals without damaging them at all, demonstrating excellent lightweight feature (Fig. 2a). Besides, the aerogel is observed to express good thermal insulation when placed over the flame of the alcohol lamp. When the aerogel is further compressed with tweezers, it can be well compressed. While the tweezers are released, it can return to its original shape in Fig. 2b, indicating its good compression and recovery characteristic. \n\nThe crystalline structure of the prepared $\\mathrm{CuS@rGO}$ composite aerogels is characterized through XRD analysis. In Fig. 2c, the diffraction peaks at $54.8^{\\circ}$ , $46.4^{\\circ}$ , $32.3^{\\circ}$ , $29.4^{\\circ}$ , and $27.8^{\\circ}$ are ascribed to the (108), (110), (103), (102), and (101) crystal planes of $\\mathrm{CuS}$ (JCPDS No.06–0464) [13]. The rC-1 and RC-1 samples show a broad peak corresponding to the (002) plane of rGO. Besides, the peak intensity becomes weaker with the addition of $\\mathrm{CuS}$ , and the peak intensity of rGO is too strong, resulting in the relatively weak intensity of $\\mathrm{CuS}$ . The chemical valence state and surface composition of $\\operatorname{rC}-3$ aerogel were measured through XPS. The full spectrum depicted in Fig. 2d confirms the occurrence of S, O, C, and Cu elements that is consistence with the composition of aerogel. From Fig. S2a, the C 1s spectrum shows three peaks at 288.9, 285.5, and $284.6\\mathrm{eV}$ , which are assigned to the $0-{\\cal C}=0$ , $\\mathrm{C-OH}$ , and $\\mathrm{C-C/C=C}$ bonds, severally [38]. Figure S2b is the $\\mathrm{Cu}2p$ high-resolution spectrum with two typical peaks at 932.0 and $952.3{\\mathrm{~eV}}_{:}$ corresponding to the Cu $2p_{3/2}$ and $\\mathrm{{Cu}}2p_{1/2}$ orbitals of $\\mathsf{S-C u}$ bonds [13]. From Fig. S2c, the $S2p$ spectrum can be divided into three peaks, i.e., S–C ( $168.3\\mathrm{eV})$ , S $2p_{1/2}$ $163.6\\mathrm{eV})$ , and S $2p_{3/2}$ $162.0\\mathrm{eV})$ [38]. For the O 1s spectrum illustrated in Fig. S2d, the obvious peaks at 532.8 and $531.9\\mathrm{eV}$ are indexed to the –OH and lattice oxygen, respectively [38]. The above XPS results further verify the high purity of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogel. \n\n![](images/ae1f40af2850f0fe2d8f2a52110d7ee6dc2c82054bc83aee5baa6ae8e3f8af61.jpg) \nFig. 2 $\\mathrm{CuS@rGO}$ aerogel characteristics of a light weight, b compression and recovery. c XRD patterns of CuS, rGO, rC-4, RGO and RC-4. d XPS full spectrum of rC-4. e–f TEM images, and $\\mathbf{g-k}$ EDS mapping images \n\nThe morphology and microstructure of $\\mathrm{CuS}$ and $\\mathrm{CuS}@$ rGO are observed by SEM. Figure S2e shows a hierarchical flower-like structure of $\\mathrm{CuS}$ with an around diameter of ${5\\upmu\\mathrm{m}}$ . From Fig. S2f–j, the $\\mathrm{\\Delta_{rC}}$ composite aerogels present a typical 3D porous structure composed of overlapping neighboring rCO sheets. Furthermore, the surface of the rGO sheet occurs some holes marked as white boxes. The $\\mathrm{CuS}$ was wrapped by the rGO sheet when the additive amounts of $\\mathrm{CuS}$ powders reached $15\\mathrm{mg}$ . In addition, the surface of rGO becomes rougher compared with rC-1 (pure rGO aerogel), which may be the formation of interfaces between $\\mathrm{CuS}$ and rGO that is conducive to attenuating the incident EMWs. From Fig. S2p, it is more evident that the $\\mathrm{CuS}$ microspheres are wrapped by rGO sheet from RC-5 (marked by a red dotted box). Interestingly, the rC-3 possesses a larger porous structure than that of other aerogels. The geometrical structure of $\\mathrm{CuS}$ and rGO of $\\operatorname{rC}-4$ was further investigated by the TEM. As depicted in Fig. 2e–f, the rGO and $\\mathrm{CuS}$ can be easily distinguished from TEM images. The flower-like $\\mathrm{CuS}$ structure was assembled by 2D nanoflakes, and there are many voids between the interwoven $\\mathrm{CuS}$ nanosheets. Besides, the rGO exhibits sparse lamellar structure duo to the almost transparent nature of rGO in the $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogel. From Fig. 2g–k, the EDS mapping images of $\\scriptstyle{\\mathrm{rC}}-4$ demonstrate that the Cu and S elements are chiefly distributed on the $\\mathrm{CuS}$ microsphere. In addition, C and O elements are distributed throughout the region, indicating the structure of $\\mathrm{CuS}$ wrapped by rGO sheets. All of these results can well distinguish and see rGO from $\\mathrm{CuS}$ . \n\n# 3.2  \u0007Microwave Absorption Performance \n\nEM parameters of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels synthesized by two different reduction strategies are investigated to deduce the effects of the defects and porous structure on MA performance. The EM parameters and reflection loss of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels by hydrothermal reduction and ascorbic acid reduction two methods are calculated as follows [39, 40]: \n\n$$\n\\mathrm{RL}=201\\mathrm{g}\\Bigg|\\frac{Z_{\\mathrm{in}}-Z_{0}}{Z_{\\mathrm{in}}+Z_{0}}\\Bigg|\n$$ \n\n$$\nZ_{\\mathrm{in}}=Z_{0}{\\sqrt{\\frac{\\mu_{\\mathrm{r}}}{\\varepsilon_{\\mathrm{r}}}}}\\mathrm{tanh}{\\left(j{\\frac{2\\pi f d{\\sqrt{\\mu_{\\mathrm{r}}\\varepsilon_{\\mathrm{r}}}}}{c}}\\right)}\n$$ \n\nHerein the physical parameters of $Z_{\\mathrm{in}},Z_{0},c,f,d,\\mu_{\\mathrm{r}}$ and $\\varepsilon_{\\mathrm{r}}$ represent the input impedance, free space impedance, speed of light, frequency, matching thickness, relative complex permeability and relative complex permittivity, respectively. As depicted in Fig. $\\mathbf{S3b_{1}{-}b_{5}}$ , the $R L_{\\mathrm{min}}$ values of $\\mathrm{_{rC}}$ aerogels show a trend of increasing first and then declining, that is the ${\\mathrm{RL}}_{\\operatorname*{min}}$ values of − 12.3 $(2.0~\\mathrm{mm})$ , − 16.1 $(2.0~\\mathrm{mm})$ , − 40.2 $(2.3~\\mathrm{mm})$ ), − 50.4 $(2.0~\\mathrm{mm})$ , and − 38.4 $\\left(3.0\\mathrm{mm}\\right)$ dB, respectively. It is worth noting that the complexing with $\\mathrm{CuS}$ microspheres is beneficial to improving MA capacity. As depicted in Fig. 3a1–a2, the rC-3 can achieve the ${\\mathrm{RL}}_{\\operatorname*{min}}$ of − 40.2 dB and a narrow EAB of $4.7\\:\\mathrm{GHz}$ at $2.0\\mathrm{mm}$ . Furthermore, the broadest EAB is up to $8.44\\:\\mathrm{GHz}$ at $2.8\\mathrm{mm}$ . When the additive content of $\\mathrm{CuS}$ is $60\\mathrm{mg}$ , the $\\operatorname{rC}-4$ obtains the EAB of $7.16\\mathrm{GHz}$ at $2.3\\mathrm{mm}$ and the ${\\mathrm{RL}}_{\\operatorname*{min}}$ of $-50.4\\:\\mathrm{dB}$ at $2.0\\mathrm{mm}$ in Fig. 3b1–b2. Interestingly, the ${\\mathrm{RL}}_{\\operatorname*{min}}$ values show a shift to low frequency as the thicknesses increase. \n\nThe EM parameters include the $\\varepsilon^{\\prime},\\varepsilon^{\\prime\\prime}$ , $\\mu^{\\prime}$ and $\\mu^{\\prime\\prime}$ . The $\\mu^{\\prime}$ and $\\varepsilon^{\\prime}$ denote the storage ability of magnetic and electric energy, while $\\mu^{\\prime\\prime}$ and $\\varepsilon^{\\prime\\prime}$ denote the dissipation capacity of magnetic and electric energy, respectively [41]. Owning to the rGO and $\\mathrm{CuS@rGO}$ without magnetic components $\\mathbf{\\mathcal{\\prime}}\\mathbf{\\mathcal{\\prime}}=0$ and $\\mu^{\\prime}=1\\dot{}$ ), we merely pay attention on the $\\varepsilon_{\\mathrm{r}}$ and dielectric loss tangent $(\\mathrm{tan}\\delta_{\\mathrm{e}})$ . From Fig. S4, the dielectric constants ( $\\varepsilon^{\\prime}$ and $\\varepsilon^{\\prime\\prime}$ ) descend as the frequency goes up, indicating an obvious frequency dispersion effect that is conducive to attenuating incident EMWs. In addition, with the increase in additive amounts of $\\mathtt{C u S}$ , the $\\varepsilon^{\\prime}$ and $\\varepsilon^{\\prime\\prime}$ generally present a decreasing trend. The $\\tan\\delta_{\\mathrm{e}}$ of $\\mathrm{_{rC}}$ aerogels with the order of $\\mathrm{rC-1}>\\mathrm{rC-2}>\\mathrm{rC-3}>\\mathrm{rC-4}>\\mathrm{rC}$ -5 is depicted in Fig. S4c. \n\nBesides, the effects of additive contents of $\\mathbf{CuS}$ on EM parameters and MA performance of RC composite aerogels via the ascorbic acid reduction strategy with the lower filler content of $2\\mathrm{wt}\\%$ are also investigated in Fig. S5–S6, Tables S2 and S3. The ${\\mathrm{RL}}_{\\operatorname*{min}}$ values are $-32.0$ ( $\\langle4.0\\mathrm{mm}\\rangle$ , − 16.8 $(2.5~\\mathrm{mm})$ , − 21.5 $(2.5~\\mathrm{mm})$ , − 60.3 $(3.5~\\mathrm{mm})$ ), and − 16.2 $(2.5~\\mathrm{mm})$ dB, respectively. In general, the RC-4 possesses the optimal MA behavior considering the low thickness, strong absorption, and broad bandwidth, i.e., the $R L_{\\mathrm{min}}$ of -55.1 dB and the EAB of $7.2\\:\\mathrm{GHz}$ can be achieved under $2.45\\mathrm{mm}$ . Furthermore, a lower ${\\mathrm{RL}}_{\\operatorname*{min}}$ value is $-60.3$ dB at $3.5\\mathrm{{mma}}$ s shown in Fig. 3c1–c2. \n\nFrom Fig. S6a, the RC-1 has the largest $\\varepsilon^{\\prime}$ values than that of other RC aerogels, and the range of $\\varepsilon^{\\prime}$ values for other aerogels is small. The $\\varepsilon^{\\prime\\prime}$ curves of RC aerogels show a familiar downward trend with multiple polarization peaks in $6{\\mathrm{-}}18\\mathrm{GHz}$ (Fig. S6b), manifesting the existence of conduction loss and polarization loss. Figure S6c displays the frequencydependent curves of $\\tan\\delta_{\\mathrm{e}}$ , which implies that the RC-4 has relatively stronger dielectric loss capacity and the RC aerogels occur polarization peak in high frequency of $11{-}15\\mathrm{GHz}$ . \n\nFurthermore, the RC composite aerogels with the lower filler content of $1\\mathrm{wt}\\%$ are studied in Fig. S7. It is seen that the RC composite aerogels show an enhanced MA capacity than pure rGO aerogel (RC-1). Figure S7f more intuitively observed that the absolute values of $\\mathrm{RL}_{\\operatorname*{min}}\\left(|\\mathrm{RL}_{\\operatorname*{min}}|\\right)$ enhance first and then decline, and RC-4 has the biggest $\\lvert\\mathrm{RL}_{\\mathrm{min}}\\rvert$ of $63.5\\mathrm{dB}$ . It is interesting that by changing filler content, the final result of RC-4 has the optimal reflection loss. \n\nThe Cole-Cole curves of $\\operatorname{CuS}@\\operatorname{rGO}$ aerogel were investigated to further elucidate the polarization relaxation processes. Based on the Debye theory, the $\\varepsilon^{\\prime}$ and $\\varepsilon^{\\prime\\prime}$ are described as follows: \n\n$$\n\\varepsilon^{\\prime}=\\varepsilon_{\\infty}+\\frac{\\varepsilon_{s}-\\varepsilon_{\\infty}}{1+(2\\pi f)^{2}\\tau^{2}}\n$$ \n\n$$\n\\varepsilon^{\\prime\\prime}=\\frac{2\\pi f\\tau\\left(\\varepsilon_{s}-\\varepsilon_{\\infty}\\right)}{1+\\left(2\\pi f\\right)^{2}\\tau^{2}}\n$$ \n\nBased on the above equations, the correlation between $\\varepsilon^{\\prime}$ and $\\varepsilon^{\\prime\\prime}$ could be calculated [42, 43]: \n\n![](images/375d86ec6fcb2cf8f3d6c5ef63b02e7b9e87c091fb4d08b519b9e741874e6272.jpg) \nFig. 3   RL curves: $\\mathbf{a_{1}}\\mathbf{rC}{-3}$ , ${\\bf b_{1}}$ rC-4, $\\mathbf{c_{1}}$ RC-4 $(2\\ \\mathrm{wt}\\%)$ and ${\\bf d}_{1}\\mathrm{RC}{-4}$ $(1~\\mathrm{wt}\\%)$ ). 2D RL contour maps of $\\mathbf{a}_{2}\\mathbf{r}\\mathbf{C}{-3}$ , $\\ensuremath{\\mathbf{b}}_{2}\\ensuremath{\\mathbf{r}}\\ensuremath{\\mathbf{C}}^{-4}$ , $\\mathbf{c}_{2}$ RC-4 $(2\\ \\mathrm{wt}\\%)$ and ${\\bf d}_{2}$ RC-4 $1\\ \\mathrm{wt}\\%)$ ). e ${\\bf R L}_{\\mathrm{min}}$ and f EAB at different thickness of $\\operatorname{rC}-4$ and RC-4. $\\mathbf{g}$ Selected RL-f curves at various frequency wavebands. h Comparison of MA performance considering the EAB and filler contents with reported rGO-based composite aerogels \n\n$$\n\\left(\\varepsilon^{\\prime}-\\frac{\\varepsilon_{s}-\\varepsilon_{\\infty}}{2}\\right)+\\left(\\varepsilon^{\\prime\\prime}\\right)^{2}=\\left(\\frac{\\varepsilon_{s}+\\varepsilon_{\\infty}}{2}\\right)^{2}\n$$ \n\nHerein $\\varepsilon_{\\infty},\\varepsilon_{\\mathrm{s}}$ , and $\\tau$ are relative complex permittivity at infinite frequency limit, static permittivity, and relaxation time, respectively. Therefore, the curve of $\\varepsilon^{\\prime\\prime}\\nu s\\varepsilon^{\\prime}$ should be a semicircle, called the Cole-Cole semicircle. Generally, each semicircle is on behalf of one Debye relaxation process. From Fig. S4d–h, the curves of all $\\mathrm{_{rC}}$ aerogels are made up of distorted semicircles and straight tails. The distorted semicircle may be ascribed to polarization relaxation like dipole polarization and interfacial polarization, while the straight line in tail is relevant to conduction loss. It can be discovered that all rC aerogels have at least two semicircles. From Fig. S6d–h, all RC aerogels also have at least two semicircles, indicating the polarization relaxation loss. \n\nCompared with rC aerogels, the conduction loss of RC aerogels is much lower from the tail straight. The polarization loss of $\\mathrm{CuS@rGO}$ aerogels primarily comes from the following aspects. On the one hand, complexing $\\mathrm{CuS}$ with rGO can be considered as a “capacitor-like” structure that leads to the inhomogeneous distribution and accumulation of free electrons at the heterogeneous interface, enhancing the interfacial polarization to attenuate incident EMWs. On the other hand, $\\mathrm{CuS}$ , a p-type semiconductor, has ample Cu vacancies, which can result in the unbalance of charges located at the defect sites and then induces dipole polarization. In addition, the –COOH, –OH, etc. on the surface or edge of rGO can also cause dipole polarization. \n\nTo compare the effect of reduction way on MA performance, the $R L$ and EAB of RC-4 ( $1\\mathrm{\\wt}\\%$ , RC-4 $(2\\ \\mathrm{wt}\\%)$ ), rC-4 and rC-3 are drawn in Fig. 3e–g. Figure 3e depicts the ${\\mathrm{RL}}_{\\operatorname*{min}}$ values of $\\operatorname{rC}-4$ , RC-4 $(2\\ \\mathrm{wt}\\%)$ at $1.0{-}4.0~\\mathrm{mm}$ . The RC-4 $(2\\ \\mathrm{wt}\\%)$ possesses overall lower ${\\mathrm{RL}}_{\\operatorname*{min}}$ values than $\\scriptstyle{\\mathrm{rC}}-4$ . In addition to ${\\mathrm{RL}}_{\\operatorname*{min}}$ , EAB also should be taken into consideration. From Fig. 3f, RC-4 $(1\\mathrm{wt}\\%)$ ) has the smallest EAB at $2.4\\mathrm{-}3.0\\ \\mathrm{mm}$ , and $\\operatorname{rC}-3$ reaches the highest EAB at $2.6{-}3.0\\ \\mathrm{mm}$ . As presented in Fig. $3\\mathrm{g}$ , the RL curves of the selected thickness for rC-4 and RC-4 $2\\mathrm{wt}\\%)$ ) can occur in different frequency wavebands (C band, X band, and $\\mathtt{K u}$ band). The performance comparison about EAB and filler content of this work to other reported rGO-based aerogels has been given in Fig. 3h [23, 44–50]. Most of reported works had higher filler contents or smaller EAB. However, this work can realize the wider EAB and the lower filler content simultaneously. \n\nAccording to the structure of rC composite aerogels (rC-3 and rC-4) and RC-4, the EM parameters and dielectric loss have been further explored in detail. As depicted in Fig. 4a, d, g, the rC-4 has the largest average dielectric constant $\\cdot\\varepsilon^{\\prime}$ and $\\varepsilon^{\\prime\\prime}$ ), implying the stronger dielectric loss behavior. Due to the difference in additive amounts of $\\mathrm{CuS}$ and reduction methods, the $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels display the various structures in Fig. 4b, e, h. Compared with rC-3, rC-4 has a higher content of $\\mathrm{CuS}$ , which is beneficial to forming the more interfacial polarization. As for rC-4 and RC-4, rGO in rC-4 is reduced at $120^{\\circ}\\mathrm{C}$ , while the RC-4 at $95^{\\circ}\\mathrm{C}$ . Therefore, it is deduced that more defects could be formed in $\\scriptstyle{\\mathrm{rC}}-4$ than RC-4. Besides, the pore diameter of $\\scriptstyle{\\mathrm{rC}}-4$ is much larger than RC-4 according to the SEM results, which is more help to attenuate the EMWs. From Cole-Cole curves in Fig. 4c, f, i, the upward tails of $\\mathrm{_{rC}}$ composite aerogels become longer, suggesting the enhanced conduction loss. So, the structure difference of $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogels with two various reduction methods is presented in Fig. 4j–k. The hydrothermal strategy with the higher temperature can generate more defects and form larger pores than that of the ascorbic acid reduction method. \n\nUsually, attenuation constant $(\\alpha)$ and impedance matching have a decisive impact on MA capability. The $\\alpha$ denotes the dissipation capacity of EMWs, which is described as follows [51–53]. \n\n$$\n\\begin{array}{l}{\\alpha={(\\sqrt{2}\\pi f/c}}\\\\ {\\qquad\\times\\sqrt{\\left(\\varepsilon^{\\prime\\prime}\\mu^{\\prime\\prime}-\\varepsilon^{\\prime}\\mu^{\\prime}\\right)+\\sqrt{\\left(\\varepsilon^{\\prime\\prime}\\mu^{\\prime\\prime}-\\varepsilon^{\\prime}\\mu^{\\prime}\\right)^{2}+\\left(\\varepsilon^{\\prime\\prime}\\mu^{\\prime}+\\varepsilon^{\\prime}\\mu^{\\prime\\prime}\\right)^{2}}}}\\end{array}\n$$ \n\nThe larger $\\varepsilon^{\\prime\\prime}$ values can lead to the improved $\\alpha$ values from Eq. (7) for the $\\mu^{\\prime}=1$ and $\\mu^{\\prime\\prime}=0$ . The $\\alpha$ curves of $\\mathrm{_{rC}}$ aerogels are shown in Fig. S4i, which keep an escalating tendency at $2{\\mathrm{-}}18\\ \\mathrm{GHz}$ . The $\\alpha$ values with the order of $\\operatorname{rC-}$ $5<\\mathrm{r}\\mathrm{C}-3<\\mathrm{r}\\mathrm{C}-4<\\mathrm{r}\\mathrm{C}-2<\\mathrm{r}\\mathrm{C}-1$ reveal that the introduction of low dielectric component $\\mathrm{CuS}$ would reduce the $\\alpha$ values. From Fig. S6j, RC aerogels demonstrate the same variation as the frequency increases, while the order of $\\alpha$ values is RC$2<\\mathrm{RC}-5<\\mathrm{RC}-3<\\mathrm{RC}-4<\\mathrm{RC}-1.$ Since the RC-4 possesses relatively attenuation capacity among composite aerogels, leading to superior MA behavior. \n\nIn addition to attenuation loss, another factor, impedance matching $(Z)$ also can affect MA performance. Impedance matching is on behalf of the EMWs entering into the absorbents, which can be accessed as follows [54]. \n\n$$\nZ=Z_{\\mathrm{in}}/Z_{0}={\\sqrt{\\frac{\\mu_{\\mathrm{r}}}{\\varepsilon_{\\mathrm{r}}}}}\\mathrm{tanh}\\left(j{\\frac{2\\pi f d}{c}}{\\sqrt{\\varepsilon_{\\mathrm{r}}\\mu_{\\mathrm{r}}}}\\right)\n$$ \n\nGenerally, the optimal impedance matching needs that the $Z$ is equal to or close to 1, that is, the input impedance equal to free space impedance $(Z_{\\mathrm{in}}=Z_{0})$ . As illustrated in Fig. $S4j-n$ , it can be discovered that the $\\vert Z_{\\mathrm{in}}/Z_{0}\\vert$ of $\\mathrm{rC}{-}1$ and rC-2 are much lower than 1, indicating poor impedance matching, and other $\\mathrm{_{rC}}$ samples are much closer to 1, which is accordance with the reflection loss results that they possess better MA performance than the other two samples. Figure S4o further draws the impedance matching curves of $\\mathrm{\\Delta}_{\\mathrm{rC}}$ aerogels at the thickness of $2.0\\mathrm{mm}$ , which shows the $\\scriptstyle{\\mathrm{rC}}-4$ is closest to 1 compared with other samples. For RC aerogels, the RC-1 and RC-4 are pretty close to 1 in Fig. S6k–o, manifesting their good absorbing performance (Figs. $\\mathbf{S5b}_{1}–\\mathbf{d}_{1}$ and $\\mathrm{S5b}_{4}\\mathrm{-d}_{4}$ ). The superior performance may be owing to the more defects and functional groups (Fig. S6p). \n\nAccording to the above results, the $R L_{\\mathrm{min}}$ absorption peaks shift to the low frequency with increasing thicknesses, which can use the explanation of $\\lambda/4$ cancellation theory [55, 56]. \n\n$$\nt_{m}=\\frac{n c}{4f_{m}\\sqrt{\\varepsilon_{r}\\mu_{r}}}(n=1,3,5,\\ldots)\n$$ \n\nFrom Fig.  5c-d, compared with rC-3, RC-4 shows the perfect matching point as the ${\\mathrm{RL}}_{\\operatorname*{min}}$ is achieved at $8.56\\mathrm{GHz}$ at $3.5\\mathrm{mm}$ that the impedance match is just at 1. Therefore, the RC-4 can satisfy the $\\lambda/4$ wavelength model and perfect impedance matching at the same time, which is conducive to the formation of ${\\mathrm{RL}}_{\\operatorname*{min}}$ . Besides, the RL, $t_{\\mathrm{m}}$ and $\\vert Z_{\\mathrm{in}}/Z_{0}\\vert$ curves of $\\operatorname{rC}-4$ and RC-4 composite aerogels are given in Fig. S8. It is clear that all $t_{\\mathrm{m}}^{\\mathrm{~\\tiny~exp~}}$ (experimental $t_{\\mathrm{m}})$ values fall perfectly on the $\\lambda/4$ curve, which suggests that the $\\lambda/4$ cancellation model plays a leading role in the relationship between $t_{\\mathrm{m}}$ and $f_{\\mathrm{m}}$ . \n\n![](images/0d92e9a57193563016340417187586fab9c5f1920619d3e1e5e0e9539651e7d6.jpg) \nFig. 4 $\\varepsilon^{\\prime},\\varepsilon^{\\prime\\prime}$ , $\\tan\\delta_{\\mathrm{e}}$ \\~ f curves: a rC-3, d rC-4, and $\\mathbf{g}\\operatorname{RC-4}$ . Structure diagram: b rC-3, e rC-4, and h RC-4. Cole–Cole curves: c rC-3, f rC-4, and i RC-4. Structure difference of $\\mathrm{_{rC}}$ and RC composite aerogels in j pore size and k number of defects \n\nBased on the discussion of composition, structure and performance, the EMW absorbing mechanism of $\\operatorname{CuS}@\\operatorname{rGO}$ is demonstrated in Fig. 5e–g. Firstly, the complex of low dielectric $\\mathrm{CuS}$ can optimize the impedance matching of pure rGO aerogel. rGO with microporous structure can availably reduce the permittivity for the incorporation of the highvolume fraction of air $(\\varepsilon_{r}=1)$ , which is helpful to improve impedance matching. The effective permittivity $(\\varepsilon_{\\mathrm{eff}})$ can be described based on the Maxwell-Garnett model [57, 58]. \n\n$$\n\\varepsilon_{\\mathrm{eff}}^{\\mathrm{MG}}=\\left[\\frac{\\left(\\varepsilon_{2}+2\\varepsilon_{1}\\right)+2p\\left(\\varepsilon_{2}-\\varepsilon_{1}\\right)}{\\left(\\varepsilon_{2}+2\\varepsilon_{1}\\right)-p\\left(\\varepsilon_{2}-\\varepsilon_{1}\\right)}\\right]\\varepsilon_{1}\n$$ \n\nHerein $\\varepsilon_{2},\\varepsilon_{1}$ and $p$ are the permittivity of the air phase and solid phase, and the volume fraction of air phase in the porous structure. Typically, the incident EMWs are uninterested in the hole lower than the wavelength, so the micropore and nanopore can act as the effective medium to reduce the $\\varepsilon_{e f f}$ value for the existence of air. Secondly, the surface or edge of $\\operatorname{rGO}$ has defects and functional groups, which can induce the formation of dipole polarization [59]. Thirdly, the combination of $\\mathrm{CuS}$ micro-flower with rGO aerogel can promote the generation of multiple heterogeneous interfaces like $\\mathrm{CuS/rGO}$ , rGO/paraffin, and CuS/ paraffin, causing the stronger interfacial polarization than pure $\\mathrm{CuS}$ or rGO aerogel [60]. Finally, the interconnected conductive network constructed by rGO sheet can form microcurrents by means of electron migration and hopping, endowing $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogel with excellent conduction loss [61, 62]. As a result, it can be concluded that the $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels can achieve excellent MA performance due to the unique merits of lightweight, low filler content, compression and recovery, wide absorption bandwidth and strong absorption, which integrates the “thin, light, wide and strong” properties of absorbers. \n\n![](images/dd0db15e76235a3bc86a3b02ede3a7ad277c6072c8736d5cc8621c4dd7129753.jpg) \nFig. 5   a RL \\~ $f$ curve of rC-3 with the broadest EAB at $2.8~\\mathrm{mm}$ . b RL \\~ $\\cdot f$ curve of RC-4 with the ${\\mathrm{RL}}_{\\operatorname*{min}}$ at $3.5~\\mathrm{mm}$ . RL, $t_{\\mathrm{m}}$ and $\\lvert Z_{\\mathrm{in}}/Z_{0}\\rvert$ curves: c rC-3 and d RC-4. Possible MA mechanism of $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogels: e dipole polarization, f interfacial polarization and $\\mathbf{g}$ conduction loss \n\n# 3.3  \u0007Microwave Dissipation Capacity Evaluated by RCS through CST Simulation \n\nMicrowave dissipation capacity of rC composite aerogels in the far-field condition is assessed by the RCS values of $\\mathrm{_{rC}}$ aerogels covered with the PEC model that are calculated by CST simulation. Figure 6a–f depicts the 3D radar wave scattering signals of PEC and $\\mathrm{_{rC}}$ aerogels. It is distinct that the rC-4 covered with PEC displays the weakest scattering intensity than other rC aerogels and PEC model, suggesting that the $\\operatorname{rC}-4$ possesses the lowest RCS. The detailed RCS value in the $-60^{\\circ}<\\theta<60^{\\circ}$ angle range are presented in Fig. 6g. The PEC has the biggest RCS values, manifesting that rC aerogels can reduce the radar scattering intensities of the pure PEC plate. Besides, RCS value of PEC larger than 0 at $0^{\\circ}$ is owing to the interference between the reflected EMW and the incident EMW that is perpendicular to the absorber (Fig. 6h). RCS reduction values are further calculated in Fig. 6i. All five samples realize the reduced RCS values compared with the simulated PEC modes, and $\\scriptstyle{\\mathrm{rC}}-4$ exhibits the highest RCS reduction values at each primary angle. It is up to the maximum value of $53.3\\mathrm{dB}\\mathrm{m}^{2}$ , which is in accord with the minimum reflection loss of rC-4. These results confirmed that with the synergistic effect of dipole polarization, interfacial polarization, conduction loss, and unique porous structure, the EM energy can be effectively dissipated, and the radar scattering intensities are reduced at the same time. \n\n# 3.4  \u0007IR Stealth Performance \n\nTo satisfy the demand for radar-IR compatible stealth, the as-prepared $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogels with excellent thermal insulation performance due to the unique porous structure are also necessary in addition to the superior MA ability. The IR radiation will be emitted from the target when the temperature is above absolute zero, which can be detected by the IR detector. Besides, once the target has a high contrast with the background IR radiation, it will be exposed. Reducing the IR radiation energy is the main strategy to achieve IR stealth, originating from the StefanBoltzmann equation [63]. \n\n![](images/7965872da3e2f9e410a90723d855decb63583d61055a181fa41bcc77853bfb52.jpg) \nFig. 6   3D radar wave scattering signals of a PEC, b rC-1, c rC-2, d rC-3, e rC-4 and f rC-5. g RCS simulated curves of PEC and RC composite aerogels. h Schematic diagram of CST simulation. i RCS reduction values of RC composite aerogels at the scanning angles of $0^{\\circ}$ , $20^{\\circ}$ , $40^{\\circ}$ and ${60}^{\\circ}$ \n\n$$\nE(T)=\\int_{0}^{\\infty}\\varepsilon(\\lambda,T)c_{1}\\lambda^{-5}\\left[\\exp\\Big(\\frac{c_{2}}{\\lambda T}\\Big)-1\\right]^{-1}d\\lambda=\\varepsilon(T)\\sigma T^{4}\n$$ \n\nHerein $E,\\varepsilon,T$ and $\\sigma$ mean IR radiation energy, IR emissivity, surface temperature and Stefan-Boltzmann constant, $c_{1}$ and $c_{2}$ represent the first and second radiation constant, respectively. Superior thermal stealth can protect targets from detection in the military field. Thus, the IR stealth performance of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels was studied by a thermal IR camera. Besides, the IR emissivity is also characterized at 3–5 and $8{-}14\\mathrm{m}$ via IR-2 Emissometer. The thermal IR images of $\\scriptstyle{\\mathrm{rC}}-4$ at $10\\mathrm{-min}$ intervals are depicted in Fig. 7a. The rC-4 aerogel is placed in the center of a circular heating platform (Fig. 7d), and the heating temperature is set to $120^{\\circ}\\mathrm{C}$ The surface temperature of $\\scriptstyle{\\mathrm{rC}}-4$ is $26.6^{\\circ}\\mathrm{C}$ at the beginning. From Fig. 7b, it is interesting that the surface temperature will go up at a tiny temperature difference (surface temperature and maximum temperature, $\\Delta T{<}0.8{\\ }^{\\circ}\\mathrm{C}$ ), and then it can maintain almost its original temperature after $30\\mathrm{min}$ heating, indicating its stable thermal stealth capability. The other $\\mathrm{CuS@rGO}$ aerogels are tested with the same condition and their results are depicted in Figs. S9–S12 and Table S4. It can be more intuitively seen from Figs. S13 and 7c that the $\\Delta T$ is decreasing, and rC-5, in particular, has almost no temperature difference, suggesting that the surface temperature of rC composite aerogels is much closer to the beginning temperature after $30\\mathrm{min}$ heating with the increase in $\\mathrm{CuS}$ content. These results further confirm that complexing low-emissivity $\\mathrm{CuS}$ with 3D porous rGO aerogel is conducive to thermal stealth ability. The abundant air with lower thermal conductivity can take the place of solid phase with higher thermal conductivity. Besides, 3D aerogels endow with a low density and porous structure, and a large number of pores inside hinder the heat transfer. The existence of $\\mathrm{CuS}$ microspheres also obstruct the heat transfer between rGO sheets. Therefore, the $\\mathrm{CuS}@\\mathrm{rGO}$ composite aerogels have excellent thermal insulation performance. \n\n![](images/9b6f9d9d360e9fb0681f2adba6d1f7039dd2c51ee1ebae550aeaae06e36f67e5.jpg) \nFig. 7   a Thermal IR images of rC-4 at different heating times. b Surface temperature curve of rC-4. c Difference between heating temperature and surface temperature of rC aerogels. d Schematic diagram of IR thermal imaging test. e IR emissivity of rC composite aerogels at 3 \\~ 5 and $8\\sim14~\\mathrm{m}$ . f Thermal transfer processes of porous $\\mathrm{CuS@rGO}$ composite aerogels. g Schematic diagram of radar-IR compatible stealth \n\nFurthermore, low IR emissivity is another way to realize IR stealth. The IR radiation energy can be reduced by modulating the emissivity with unchanged surface temperature. There are currently two atmospheric window regions of $3\\sim5$ and $8\\sim14\\mathrm{m}$ adopted by IR detectors. As presented in Fig. 7e and Table S2, the IR emissivity of rC composite aerogels shows a downward trend on the IR waveband of both $3{\\sim}5$ and $8\\sim14\\mathrm{m}$ , which is consistence with the results of thermal IR images. Besides, the emissivity at $3{\\sim}5\\mathrm{m}$ is much lower than $8\\sim14\\mathrm{m}$ . The possible IR stealth mechanism is summarized in Fig. 7f. The forms of thermal transfer consist of thermal radiation, thermal conduction and thermal convection, which all occur in $\\mathrm{CuS@rGO}$ aerogels. Owing to the low density of porous aerogels, the gas-phase components can reduce the thermal conduction for their low thermal conductivity. Moreover, the 3D network structure is conducive to prolonging the thermal transfer path and reducing the thermal conduction in the solid phase, leading to a perfect insulation performance. Figure $\\mathrm{7g}$ shows the ideal double-layer radar-IR stealth coating. The EMWs can pass through the IR stealth layer, and enter the MA layer, then be dissipated. Impedance matching is one of the most significant factors in minimizing the radar reflectivity of IR stealth coating. \n\n# 4  \u0007Conclusions \n\nIn this work, we developed an effective composite-structure-performance strategy to enhance MA performance and reduce IR emissivity. Two types of $\\operatorname{CuS}@\\operatorname{rGO}$ composite aerogels were successfully fabricated via hydrothermal reduction and ascorbic acid thermal reduction. The reduction mechanisms involved the decarboxylation process, dehydroxylation process, and deoxidation process of epoxy groups, which could lead to the defects. In addition, adjacent graphene sheets wrapped by numerous tiny $\\mathrm{CuS}$ are stacked with each other to form a 3D porous structure during the thermal reduction process. The porous structure and defects could be modulated by the thermal reduction and additive amounts of $\\mathrm{CuS}$ . Because of the balanced attenuation capability and impedance matching, the as-prepared $\\operatorname{CuS}@\\operatorname{rGO}$ aerogels depicted impressive microwave absorbing performance. The $\\operatorname{CuS}@\\operatorname{rGO}$ aerogels achieved the broadest EAB of $8.44\\:\\mathrm{GHz}$ $(2.8~\\mathrm{mm})$ ) with the additive amount of $30~\\mathrm{mg}$ . The samples realized the ${\\mathrm{RL}}_{\\operatorname*{min}}$ of − 50.4 dB $(2.0\\mathrm{mm})$ with the additive amount of $60~\\mathrm{mg}$ through the hydrothermal reduction method under the filler content of $6\\mathrm{wt}\\%$ . Besides, the $\\operatorname{CuS}@\\operatorname{rGO}$ aerogel (RC-4) could achieve the EAB of $7.2\\mathrm{GHz}$ and ${\\mathrm{RL}}_{\\operatorname*{min}}$ of − 55.1 dB at $2.45~\\mathrm{mm}$ with the filler content of $2\\mathrm{wt}\\%$ , in addition, the ${\\mathrm{RL}}_{\\operatorname*{min}}$ of − 48.1 dB and EAB of $5.96\\:\\mathrm{GHz}$ could be obtained at $2.2~\\mathrm{mm}$ with the lowest filler content of $1\\mathrm{\\mt}\\%$ . The CST simulated results also demonstrated that the $\\mathrm{CuS@rGO}$ composite aerogels could effectively reduce the radar scattering intensity. Furthermore, thermal IR images and IR emissivity could confirm that the $\\mathrm{GuS}@\\mathrm{rGO}$ composite aerogels had the ability to reduce the surface temperature and IR emissivity. Thus, these results will lead to the development of radar-IR compatible stealth materials composed of carbon-based aerogels, which can make them a considerable application prospect in a harsh military environment. \n\nAcknowledgements  We are thankful for financial support from the National Nature Science Foundation of China (No. 51971111). \n\nFunding  Open access funding provided by Shanghai Jiao Tong University. \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\nSupplementary Information  The online version contains supplementary material available at https://​doi.​org/​10.​1007/ s40820-​022-​00906-5. \n\n# References \n\n1.\t Z. Wu, H. Cheng, C. Jin, B. Yang, C. Xu et al., Dimensional design and core–shell engineering of nanomaterials for electromagnetic wave absorption. Adv. Mater. 34(11), 2107538 (2022). https://​doi.​org/​10.​1002/​adma.​20210​7538 \n2.\t J. Lyu, Z. Liu, X. Wu, G. Li, D. Fang et al., Nanofibrous Kevlar aerogel films and their phase-change composites for highly efficient infrared stealth. ACS Nano 13(2), 2236–2245 (2019). https://​doi.​org/​10.​1021/​acsna​no.​8b089​13 \n3.\t J. Xu, X. Zhang, Z. Zhao, H. Hu, B. Li et al., Lightweight, fire-retardant, and anti-compressed honeycombed-like carbon aerogels for thermal management and high-efficiency electromagnetic absorbing properties. Small 17(33), 2102032 (2021). https://​doi.​org/​10.​1002/​smll.​20210​2032 \n4.\t Z. Zeng, N. Wu, J. Wei, Y. Yang, T. Wu et al., Ultralight magnetic and dielectric aerogels achieved by metal–organic framework initiated gelation of graphene oxide for enhanced microwave absorption. Nano-Micro Lett. 14, 59 (2022). https://​doi. org/​10.​1007/​s40820-​022-​00800-0 \n5.\t H. Cheng, Y. Pan, X. Wang, C. Liu, C. Shen et al., Ni flower/ MXene-melamine foam derived 3D magnetic/conductive networks for ultra-efficient microwave absorption and infrared stealth. Nano-Micro Lett. 14, 116 (2022). https://​doi.​org/​10. 1007/​s40820-​022-​00820-w \n6.\t Y. Zhao, G. Ji, Multi-spectrum bands compatibility: new trend in stealth materials research. Sci. China Mater. (2022). https://​ doi.​org/​10.​1007/​s40843-​022-​2074-5 \n7.\t X. Zhang, X. Zhang, H. Yuan, K. Li, Q. Ouyang et al., CoNi nanoparticles encapsulated by nitrogen-doped carbon nanotube arrays on reduced graphene oxide sheets for electromagnetic wave absorption. Chem. Eng. J. 383, 123208 (2020). https://​doi.​org/​10.​1016/j.​cej.​2019.​123208 \n8.\t X. Zhang, J. Qiao, Y. Jiang, F. Wang, X. Tian et al., Carbonbased MOF derivatives: emerging efficient electromagnetic wave absorption agents. Nano-Micro Lett. 13, 135 (2021). https://​doi.​org/​10.​1007/​s40820-​021-​00658-8 \n9.\t J. Luo, M. Feng, Z. Dai, C. Jiang, W. Yao et  al., $\\mathbf{MoS}_{2}$ wrapped MOF-derived N-doped carbon nanocomposite with wideband electromagnetic wave absorption. Nano Res. (2022). https://​doi.​org/​10.​1007/​s12274-​022-​4411-6 \n10.\t W. Gu, J. Sheng, Q. Huang, G. Wang, J. Chen et al., Environmentally friendly and multifunctional shaddock peelbased carbon aerogel for thermal-insulation and microwave absorption. Nano-Micro Lett. 13, 102 (2021). https://​doi.​ org/​10.​1007/​s40820-​021-​00635-1 \n11.\t X. Zhang, L. Cai, Z. Xiang, W. Lu, Hollow CuS microflowers anchored porous carbon composites as lightweight and broadband microwave absorber with flame-retardant and thermal stealth functions. Carbon 184, 514–525 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2021.​08.​026 \n12.\t Q. Huang, Y. Zhao, Y. Wu, M. Zhou, S. Tan et al., A dualband transceiver with excellent heat insulation property for microwave absorption and low infrared emissivity compatibility. Chem. Eng. J. 446, 137279 (2022). https://​doi.​org/​ 10.​1016/j.​cej.​2022.​137279 \n13.\t G. Cui, L. Wang, L. Li, W. Xie, G. Gu, Synthesis of $\\mathrm{CuS}$ nanoparticles decorated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene with enhanced microwave absorption performance. Prog. Nat. Sci. Mater. 30(3), 343–351 (2020). https://​doi.​org/​10.​1016/j.​pnsc.​2020.​06.​001 \n14.\t Y. Wang, X. Gao, W. Zhang, C. Luo, L. Zhang et al., Synthesis of hierarchical $\\mathrm{CuS/RGO/PANI/Fe_{3}O_{4}}$ quaternary composite and enhanced microwave absorption performance. J. Alloys Compd. 757, 372–381 (2018). https://​doi.​org/​10.​1016/j.​jallc​ om.​2018.​05.​080 \n15.\t P. Liu, Y. Huang, J. Yan, Y. Yang, Y. Zhao, Construction of CuS nanoflakes vertically aligned on magnetically decorated graphene and their enhanced microwave absorption properties. ACS Appl. Mater. Interfaces 8(8), 5536–5546 (2016). https://​ doi.​org/​10.​1021/​acsami.​5b105​11 \n16.\t X. Guan, P. Xu, X. Guan, G. Wang, Hydrothermal synthesis of hierarchical CuS/ZnS nanocomposites and their photocatalytic and microwave absorption properties. RCS Adv. 4, 15579 (2014). https://​doi.​org/​10.​1039/​c4ra0​0659c \n17.\t B. Li, J. Xu, H. Xu, F. Yan, X. Zhang et  al., Grafting thin N-doped carbon nanotubes on hollow N-doped carbon nanoplates encapsulated with ultrasmall cobalt particles for microwave absorption. Chem. Eng. J. 435(1), 134846 (2022). https://​doi.​org/​10.​1016/j.​cej.​2022.​134846 \n18.\t J. He, S. Gao, Y. Zhang, X. Zhang, H. Li, N-doped residual carbon from coal gasification fine slag decorated with $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ nanoparticles for electromagnetic wave absorption. J. Mater. Sci. Technol. 104, 98–108 (2022). https://​doi.​org/​10.​1016/j. jmst.​2021.​06.​052 \n19.\t J. Xu, M. Liu, X. Zhang, B. Li, X. Zhang et al., Atomically dispersed cobalt anchored on N-doped graphene aerogels for efficient electromagnetic wave absorption with an ultralow filler ratio. Appl. Phys. Rev. 9(1), 011402 (2022). https://​doi.​ org/​10.​1063/5.​00677​91 \n20.\t C. Wen, X. Li, R. Zhang, C. Xu, W. You et al., High-density anisotropy magnetism enhanced microwave absorption performance in $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene@Ni microspheres. ACS Nano 16(1), 1150–1159 (2022). https://​doi.​org/​10.​1021/​acsna​no. 1c089​57 \n21.\t J. Xu, X. Zhang, H. Yuan, S. Zhang, C. Zhu et al., N-doped reduced graphene oxide aerogels containing pod-like N-doped carbon nanotubes and FeNi nanoparticles for electromagnetic wave absorption. Carbon 159, 357–365 (2020). https://​doi.​org/​10.​1016/j.​carbon.​2019.​12.​020 \n22.\t D. Xu, S. Yang, P. Chen, Q. Yu, X. Xiong et al., Synthesis of magnetic graphene aerogels for microwave absorption by in-situ pyrolysis. Carbon 146, 301–312 (2019). https://​doi. org/​10.​1016/j.​carbon.​2019.​02.​005 \n23.\t X. Wang, Y. Lu, T. Zhu, S. Chang, W. Wang, $\\mathrm{CoFe}_{2}\\mathrm{O}_{4}/\\mathrm{N}$ -doped reduced graphene oxide aerogels for high-performance microwave absorption. Chem. Eng. J. 388, 124317 (2020). https://​doi.​org/​10.​1016/j.​cej.​2020.​124317 \n24.\t Y. Wang, X. Gao, Y. Fu, X. Wu, Q. Wang et al., Enhanced microwave absorption performances of polyaniline/graphene aerogel by covalent bonding. Compos. Part B Eng. 169, 221–228 (2019). https://​doi.​org/​10.​1016/j.​compo​sitesb.​ 2019.​04.​008 \n25.\t J. Chen, H. Jia, Z. Liu, Q. Kong, Z. Hou et al., Construction of C-Si heterojunction interface in SiC whisker/reduced graphene oxide aerogels for improving microwave absorption. Carbon 164, 59–68 (2020). https://​doi.​org/​10.​1016/j.​carbon. 2020.​03.​049 \n26.\t W. Gu, J. Tan, J. Chen, Z. Zhang, Y. Zhao et  al., Multifunctional bulk hybrid foam for infrared stealth, thermal insulation, and microwave absorption. ACS Appl. Mater. Interfaces 12(25), 28727–28737 (2020). https://​doi.​org/​10. 1021/​acsami.​0c092​02 \n27.\t X. Chen, M. Zhou, Y. Zhao, W.H. Gu, Y. Wu et al., Morphology control of eco-friendly chitosan-derived carbon aerogels for efficient microwave absorption at thin thickness and thermal stealth. Green Chem. 24(13), 5280–5290 (2022). https://​doi.​org/​10.​1039/​D2GC0​1604D \n28.\t J. Li, Z. Xu, T. Li, D. Zhi, Y. Chen et al., Multifunctional antimony tin oxide/reduced graphene oxide aerogels with wideband microwave absorption and low infrared emissivity. Compos. Part B Eng. 231, 109565 (2021). https://​doi.​org/ 10.​1016/j.​compo​sitesb.​2021.​109565 \n29.\t J. Luo, Y. Wang, Z. Qu, W. Wang, D. Yu, Lightweight and robust cobalt ferrite/carbon nanotubes/waterborne polyurethane hybrid aerogels for efficient microwave absorption and thermal insulation. J. Mater. Chem. C 9(36), 12201–12212 (2021). https://​doi.​org/​10.​1039/​d1tc0​2427b \n30.\t X. Zhu, Y. Dong, Z. Xiang, L. Cai, F. Pan et al., Morphology-controllable synthesis of polyurethane-derived highly cross-linked 3D networks for multifunctional and efficient electromagnetic wave absorption. Carbon 182, 254–264 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2021.​06.​0284 \n31.\t Z. Zhang, J. Tan, W. Gu, H. Zhao, J. Zheng et al., Cellulosechitosan framework/polyailine hybrid aerogel toward thermal insulation and microwave absorbing application. Chem. Eng. J. 395, 125190 (2020). https://​doi.​org/​10.​1016/j.​cej. 2020.​125190 \n32.\t W. Ma, X. Liu, Z. Qiu, Z. Cai, J. Diao et al., Hydrophobic and flame-retardant multifunctional foam for enhanced thermal insulation and broadband microwave absorption via a triplecontinuous network of RGO/MWCNT-melamine composite. Carbon 196, 913–922 (2022). https://​doi.​org/​10.​1016/j.​carbon. 2022.​05.​060 \n33.\t Y. Li, X. Liu, X. Nie, W. Yang, Y. Wang et al., Multifunctional organic-inorganic hybrid aerogel for self-cleaning, heatinsulating, and highly efficient microwave absorbing material. Adv. Funct. Mater. 29(10), 1807624 (2019). https://​doi.​org/​10. 1002/​adfm.​20180​7624 \n34.\t K. Wu, W. Huang, J. Wang, W. Huang, Infrared stealth and microwave absorption properties of reduced graphene oxide functionalized with $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ . Mater. Sci. Eng. B 276, 115575 (2022). https://​doi.​org/​10.​1016/j.​mseb.​2021.​115575 \n35.\t J. Wang, M. Zhou, Z. Xie, X. Hao, S. Tang et al., Enhanced interfacial polarization of biomass-derived porous carbon with a low radar cross-section. J. Colloid Interf. Sci. 612, 146–155 (2022). https://​doi.​org/​10.​1016/j.​jcis.​2021.​12.​162 \n36.\t M. Hanifah, J. Jaafar, M. Othman, A. Ismail, M. Rahman et al., Advanced ternary RGO/bimetallic Pt-Pd alloy $\\boldsymbol{\\mathscr{I}}\\mathrm{CeO}_{2}$ nanocomposite electrocatalyst by one-step hydrothermal-assisted formic acid reduction reaction for methanol electrooxidation. J. Environ. Chem. Eng. 9(1), 104991 (2021). https://​doi.​org/ 10.​1016/j.​jece.​2020.​104991 \n37.\t B. Kuang, W. Song, M. Ning, J. Li, Z. Zhao et al., Chemical reduction dependent dielectric properties and dielectric loss mechanism of reduced graphene oxide. Carbon 127, 209–217 (2018). https://​doi.​org/​10.​1016/j.​carbon.​2017.​10.​092 \n38.\t Y. Wang, X. Gao, X. Wu, W. Zhang, Q. Wang et al., Hierarchical $\\mathrm{ZnFe}_{2}\\mathrm{O}_{4}@\\mathrm{RGO}@\\mathrm{CuS}$ composite: strong absorption and widefrequency absorption properties. Cream. Int. 44(8), 9816–9822 (2018). https://​doi.​org/​10.​1016/j.​ceram​int.​2018.​02.​220 \n39.\t X. Liang, Z. Man, B. Quan, J. Zheng, W. Gu et al., Environment-stable $\\mathrm{{Co}_{\\mathrm{{x}}}\\mathrm{{Ni}_{\\mathrm{{y}}}}}$ encapsulation in stacked porous carbon nanosheets for enhanced microwave absorption. Nano-Micro Lett. 12, 102 (2020). https://​doi.​org/​10.​1007/ s40820-​020-​00432-2 \n40.\t Y. Cheng, J. Seow, H. Zhao, Z. Xu, G. Ji, A flexible and lightweight biomass-reinforced microwave absorber. Nano-Micro Lett. 12, 125 (2020). https://​doi.​org/​10.​1007/ s40820-​020-​00461-x \n41.\t Q. Liu, Q. Cao, H. Bi, C. Liang, K. Yuan et al., $\\mathrm{CoNi}@\\mathrm{SiO}_{2}@$ $\\mathrm{TiO}_{2}$ and $\\mathrm{CoNi@Air@TiO_{2}}$ microspheres with strong wideband microwave absorption. Adv. Mater. 28(3), 486–490 (2016). https://​doi.​org/​10.​1002/​adma.​20150​3149 \n42.\t X. Zhang, Y. Shi, J. Xu, Q. Ouyang, X. Zhang et al., Identification of the intrinsic dielectric properties of metal single atoms for electromagnetic wave absorption. Nano-Micro Lett. 14, 27 (2022). https://​doi.​org/​10.​1007/​s40820-​021-​00773-6 \n43.\t B. Zhao, X. Guo, W. Zhao, J. Deng, G. Shao et al., Yolk-shell $\\mathrm{Ni}@\\mathrm{SnO}_{2}$ composites with a designable interspace to improve the electromagnetic wave absorption properties. ACS Appl. Mater. Interfaces 8(42), 28917–28925 (2016). https://​doi.​org/ 10.​1021/​acsami.​6b108​86 \n44.\t L. Wu, R. Shu, J. Zhang, X. Chen, Synthesis of three-dimensional porous netlike nitrogen-doped reduced graphene oxide/ cerium oxide composite aerogels towards high-efficiency microwave absorption. J. Colloid Interf. Sci. 608, 1212–1221 (2022). https://​doi.​org/​10.​1016/j.​jcis.​2021.​10.​112 \n45.\t J. Tang, N. Liang, L. Wang, J. Li, G. Tian et al., Three-dimensional nitrogen-doped reduced graphene oxide aerogel decorated with Ni nanoparticles with tunable and unique microwave absorption. Carbon 152, 575–586 (2019). https://​doi.​org/​ 10.​1016/j.​carbon.​2019.​06.​049 \n46.\t J. Cheng, Y. Wang, A. Zhang, H. Zhao, Y. Wang, Growing $\\mathbf{MoO}_{3}$ -doped ${\\bf W O}_{3}$ nanoflakes on rGO aerogel sheets towards superior microwave absorption. Carbon 183, 205–215 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2021.​07.​019 \n47.\t X. Huang, G. Yu, Y. Zhang, M. Zhang, G. Shao, Design of cellular structure of graphene aerogels for electromagnetic wave absorption. Chem. Eng. J. 426, 131894 (2021). https://​doi.​org/ 10.​1016/j.​cej.​2021.​131894 \n48.\t J. Qiu, J. Liao, G. Wang, R. Du, N. Tsidaeva et al., Implanting N-doped CQDs into rGO aerogels with diversified applications in microwave absorption and wastewater treatment. Chem. Eng. J. 443, 136475 (2022). https://​doi.​org/​10.​1016/j.​ cej.​2022.​136475 \n49.\t J. Qiu, H. Cao, J. Liao, R. Du, K. Dou et al., 3D porous corallike Co1. 29Ni1. 71O4 microspheres embedded into reduced graphene oxide aerogels with lightweight and broadband microwave absorption. J. Colloid Interface Sci. 609, 12–22 (2022). https://​doi.​org/​10.​1016/j.​jcis.​2021.​11.​176 \n50.\t H. Zhao, J. Chen, J. Zhu, Y. Wang, Ultralight CoNi/rGO aerogels toward excellent microwave absorption at ultrathin thickness. J. Mater. Chem. C 7(2), 441–448 (2019). https://​doi.​org/ 10.​1039/​c8tc0​5239e \n51.\t X. Liang, G. Wang, W. Gu, G. Ji, Prussian blue analogue derived carbon-based composites toward lightweight microwave absorption. Carbon 177, 97–106 (2021). https://​doi.​org/ 10.​1016/j.​carbon.​2021.​02.​063 \n52.\t J. Qiao, X. Zhang, C. Liu, L. Lyu, Y. Yang et al., Non-magnetic bimetallic MOF-derived porous carbon-wrapped $\\mathrm{TiO}_{2}/$ $\\mathrm{ZrTiO_{4}}$ composites for efficient electromagnetic wave absorption. Nano-Micro Lett. 13, 75 (2021). https://​doi.​org/​10.​1007/​ s40820-​021-​00606-6 \n53.\t B. Li, F. Wang, K. Wang, J. Qiao, D. Xu et al., Metal sulfides based composites as promising efficient microwave absorption materials: a review. J. Mater. Sci. Technol. 104, 244–268 (2022). https://​doi.​org/​10.​1016/j.​jmst.​2021.​06.​065 \n54.\t W. Gu, J. Zheng, X. Liang, X. Cui, J. Chen et al., Excellent lightweight carbon-based microwave absorbers derived from metal–organic frameworks with tunable electromagnetic properties. Inorg. Chem. Front. 7(8), 1667–1675 (2020). https:// doi.​org/​10.​1039/​d0qi0​0099j \n55.\t Y. Cheng, H. Zhao, Y. Zhao, J. Cao, J. Zheng et al., Structureswitchable mesoporous carbon hollow sphere framework toward sensitive microwave response. Carbon 161, 870–879 (2020). https://​doi.​org/​10.​1016/j.​carbon.​2020.​02.​011 \n56.\t J. Luo, Z. Dai, M. Feng, X. Chen, C. Sun et al., Hierarchically porous carbon derived from natural Porphyra for excellent electromagnetic wave absorption. J. Mater. Sci. Technol. 129, 206–214 (2022). https://​doi.​org/​10.​1016/j.​jmst.​2022.​04.​047 \n57.\t C. Liang, Z. Wang, Eggplant-derived SiC aerogels with highperformance electromagnetic wave absorption and thermal insulation properties. Chem. Eng. J. 373, 598–605 (2019). https://​doi.​org/​10.​1016/j.​cej.​2019.​05.​076 \n58.\t B. Zhao, X. Guo, W. Zhao, J. Deng, B. Fan et al., Facile synthesis of yolk–shell $\\mathrm{Ni}@\\mathrm{void}@\\mathrm{SnO}_{2}$ $(\\mathrm{Ni}_{3}\\mathrm{Sn}_{2})$ ternary composites via galvanic replacement/Kirkendall effect and their enhanced microwave absorption properties. Nano Res. 10(1), 331–343 (2018). https://​doi.​org/​10.​1007/​s12274-​016-​1295-3 \n59.\t P. Liu, Y. Wang, G. Zhang, Y. Huang, R. Zhang et al., Hierarchical engineering of double-shelled nanotubes toward hetero-interfaces induced polarization and microscale magnetic interaction. Adv. Funct. Mater. 2202588 (2022).https:// doi.​org/​10.​1002/​adfm.​20220​2588 \n60.\t C. Xu, P. Liu, Z. Wu, H. Zhang, R. Zhang et al., Customizing heterointerfaces in multilevel hollow architecture constructed by magnetic spindle arrays using the polymerizing-etching strategy for boosting microwave absorption. Adv. Sci. 9(17), 220804 (2022). https://​doi.​org/​10.​1002/​advs.​20220​0804 \n61.\t Z. Zeng, N. Wu, J. Wei, Y. Yang, T. Wu et al., Porous and ultra-flexible crosslinked MXene/polyimide composites for multifunctional electromagnetic interference shielding. Nano-Micro Lett. 14, 59 (2022). https://​doi.​org/​10.​1007/ s40820-​022-​00800-0 \n62.\t B. Zhao, Y. Li, R. Che, Galvanic replacement reaction involving core-shell magnetic chains and orientation-tunable microwave absorption properties. Small 16(40), 2003502 (2020). https://​doi.​org/​10.​1002/​smll.​20200​3502 \n63.\t R. Zheng, Y. Cheng, X. Jiang, T. Lin, W. Chen et al., Fiber templated eitaxially grown composite membranes: from thermal insulation to infrared stealth. ACS Appl. Mater. Interfaces 14(23), 27214–27221 (2022). https://​doi.​org/​10.​1021/​acsami. 2c059​06 " + }, + { + "id": "10.1021_jacs.2c02666", + "DOI": "10.1021/jacs.2c02666", + "DOI Link": "http://dx.doi.org/10.1021/jacs.2c02666", + "Relative Dir Path": "mds/10.1021_jacs.2c02666", + "Article Title": "Accelerated Synthesis and Discovery of Covalent Organic Framework Photocatalysts for Hydrogen Peroxide Production", + "Authors": "Zhao, W; Yan, PY; Li, BY; Bahri, M; Liu, LJ; Zhou, X; Clowes, R; Browning, ND; Wu, Y; Ward, JW; Cooper, A", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "A high-throughput sonochemical synthesis and testing strategy was developed to discover covalent organic frameworks (COFs) for photocatalysis. In total, 76 conjugated polymers were synthesized, including 60 crystalline COFs of which 18 were previously unreported. These COFs were then screened for photocatalytic hydrogen peroxide (H2O2) production using water and oxygen. One of these COFs, sonoCOF-F2, was found to be an excellent photocatalyst for photocatalytic H2O2 production even in the absence of sacrificial donors. However, after long-term photocatalytic tests (96 h), the imine sonoCOF-F2 transformed into an amide-linked COF with reduced crystallinity and loss of electronic conjugation, decreasing the photocatalytic activity. When benzyl alcohol was introduced to form a two-phase catalytic system, the photostability of sonoCOF-F2 was greatly enhanced, leading to stable H2O2 production for at least 1 week.", + "Times Cited, WoS Core": 296, + "Times Cited, All Databases": 305, + "Publication Year": 2022, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000810004300001", + "Markdown": "# Accelerated Synthesis and Discovery of Covalent Organic Framework Photocatalysts for Hydrogen Peroxide Production \n\nWei Zhao, Peiyao Yan, Boyu Li, Mounib Bahri, Lunjie Liu, Xiang Zhou, Rob Clowes, Nigel D. Browning, Yue Wu, John W. Ward,\\* and Andrew I. Cooper\\* \n\nCite This: J. Am. Chem. Soc. 2022, 144, 9902−9909 \n\n# Read Online \n\n![](images/490b6d82f64873317c1cf1ecd787e151f65456f42527dfee862227be04c73aee.jpg) \n\n# ACCESS \n\n山 Metrics & More \n\nABSTRACT: A high-throughput sonochemical synthesis and testing strategy was developed to discover covalent organic frameworks (COFs) for photocatalysis. In total, 76 conjugated polymers were synthesized, including 60 crystalline COFs of which 18 were previously unreported. These COFs were then screened for photocatalytic hydrogen peroxide $\\left(\\mathrm{H}_{2}\\mathrm{O}_{2}\\right)$ production using water and oxygen. One of these COFs, sonoCOF-F2, was found to be an excellent photocatalyst for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production even in the absence of sacrificial donors. However, after long-term \n\n面 Article Recommendations \n\nSupporting Information \n\n![](images/df1b6f087e0c235c9e9b8894d2f45e333238898efc89c8fdd8d47ed5c2804f80.jpg) \nHigh-throughput COF synthesis High-throughput $H_{2}O_{2}$ screening Discovery of COF photocatalysts \n\nphotocatalytic tests $(96~\\mathrm{h})$ , the imine sonoCOF-F2 transformed into an amide-linked COF with reduced crystallinity and loss of electronic conjugation, decreasing the photocatalytic activity. When benzyl alcohol was introduced to form a two-phase catalytic system, the photostability of sonoCOF-F2 was greatly enhanced, leading to stable $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production for at least 1 week. \n\n# 1. INTRODUCTION \n\nHydrogen peroxide $\\left(\\mathrm{H}_{2}\\mathrm{O}_{2}\\right)$ is an important oxidant that is used in the chemical industries, healthcare, and water treatment and as a clean fuel,1,2 with an annual demand of 2.2 million tons.3 This figure may reach 5.7 million tons per annum by 2027.4 Anthraquinone oxidation is the most common industrial $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production method, but this consumes a lot of energy and creates harmful waste.5 The artificial photosynthetic production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ from water and oxygen using semiconductor photocatalysts has received attention due to its potential for low energy consumption, reduced pollution, and improved safety.5 To date, however, no photocatalyst exists that can realize the industrial production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ on a large scale. \n\nOrganic polymers, including graphic carbon nitride $({\\bf g}-$ $\\mathrm{C}_{3}\\mathrm{N}_{4}\\big),^{6}$ covalent triazine frameworks (CTFs),7 and polymer resins,8 have emerged as potential semiconductor photocatalysts for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production due to their tunable chemical structures, broad light absorption range, and metal-free composition. However, few organic catalysts have shown good performance for this reaction, particularly in the absence of sacrificial agents. We recently reported a linear conjugated polymer, poly(3−4-ethynylphenyl)ethynyl)pyridine (DE7), with promising photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production, but this catalyst decomposed after a reaction period of $50\\mathrm{~h~}$ or so, suggesting a need to focus on the photostability of organic photocatalysts. \n\nCovalent organic frameworks $\\left(\\mathrm{COFs}\\right)^{10}$ are a relatively new class of porous and crystalline conjugated organic materials that have emerged as potential catalysts owing to their photocatalytic activity and (in some cases) promising stability for photocatalytic water splitting,11 $\\mathrm{CO}_{2}$ reduction,12 and organic transformations.13 To date, only one study has focused on COF photocatalysts for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ synthesis.14 Recently, we reported a fast and simple sonochemical method for imine COF synthesis in aqueous acetic acid.15 We suggested that this might be an enabling methodology for the rapid discovery of functional COF materials due to its speed, simplicity, and the lack of a requirement for anaerobic conditions, all of which lend this approach to high-throughput screening. \n\nHere, we used this rapid and convenient sonochemical synthesis strategy to search for COF photocatalysts for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production from water and oxygen. We prepared 76 imine-conjugated polymers using 11 amine monomers and 11 aldehyde monomers: 60 of these materials were found to be crystalline, including 18 new, unreported COF structures with either 1D or 2D structures. Highthroughput screening experiments found that a triazinecontaining COF (sonoCOF-F2) showed good photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production and improved photostability in pure water compared to our recently reported linear conjugated polymer, DE7.9 However, at longer reaction times $\\left(>96~\\mathrm{h}\\right)$ , this imine sonoCOF-F2 transformed into an amide-linked COF with reduced crystallinity and loss of electronic conjugation, decreasing the photocatalytic activity. When we added a sacrificial hole scavenger (benzyl alcohol, BA),16 the photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate is increased, and this also protects the catalysis against transformation into the inactive amide COF. This two-phase liquid−liquid BA/water system also allows for the spontaneous separation of the reaction products. \n\n![](images/a4ea75f94b49a952bd5b3af73e73dcf174e95cebc56682bd7a0c879df153fa20.jpg) \nFigure 1. Monomer library used to synthesize the sonoCOFs and product outcomes of the 86 sonochemical reactions. Solid pink circles: reported crystalline COFs (footnotes are from Table S4); solid purple cirlces: new, unreported crystalline COFs; solid yellow diamonds: amorphous polymers; \\*: no polymer formed; dashes: linear polymers. The linear polymer combinations were not attempted here, giving a total of 86 sonochemical reactions. \n\n# 2. RESULTS AND DISCUSSION \n\n2.1. High-Throughput sonoCOF Synthesis. As shown in Figure 1, 11 amine monomers and 11 aldehyde monomers were selected to synthesize a library of sonoCOFs. The monomers used in this study were selected to explore a wide range of combinations to investigate structure−function relationships for photocatalytic hydrogen peroxide production. Specifically, we chose both electron-poor monomers (e.g., aldehydes D and G and amines 2 and 10) and electron-rich monomers (e.g., aldehyde H and amines 3, 7, and 11) to generate acceptor−donor systems. The synthesis procedures for each COF were similar to our previous work.15 All COFs were characterized by elemental analysis (EA), powder X-ray diffraction (PXRD), Fourier-transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), nitrogen adsorption−desorption measurements, UV−visible absorption spectroscopy, and thermogravimetric analysis (TGA). The detailed synthesis conditions and characterization results of each COF can be found in the Supplementary Information. \n\n![](images/24e4b7eca23e487c1c7723d31371e882686f898f93f3325e07b699b7fac7ea8b.jpg) \nFigure 2. Pawley refinements against the powder X-ray diffraction patterns of (a) sonoCOF-J1, (b) K1, (c) A3, (d) F3, (e) J3, (f) K3, $(\\mathbf{g})$ A4, (h) J4, (i) K4, (j) A7, $(\\mathbf{k})$ B11, and (l) K11. Pink lines: $y_{\\mathrm{obs}}$ (experimental PXRD data). Black dots: $y_{\\mathrm{calc}}$ (Pawley refinement profile). Blue lines: $y_{\\mathrm{obs}}$ − $y_{\\mathrm{calc}}$ (residual); yellow marks, $h k l$ positions calculated for that phase. Insets: modeled crystal structures. $\\mathbf{C},$ gray; H, white; N, blue; $\\mathrm{~\\boldmath~\\Gamma~}_{\\mathrm{{O}}}$ red. \n\nIn total, 76 conjugated polymers were synthesized successfully (10 combinations failed to give polymers, Figure 1), of which 60 materials showed good crystallinity. This included 18 unreported crystalline COF structures with 1D or 2D topologies (Figure 2). To obtain crystalline materials, the concentration of acetic acid $(\\mathrm{AcOH})$ and the activation conditions must be considered because of the different reactivities of the various monomers and the different stabilities of the resulting frameworks. As such, there is no global optimum synthesis or work-up method. For example, sonoCOF-A1 is very chemically stable and its monomers, \n\nDMTA and TAPB, show good reactivities; hence, we could prepare and isolate crystalline sonoCOF-A1 using various concentrations of AcOH (1, 3, 6, 9, and $12\\mathrm{~M~}\\dot{}$ ) by direct filtration using vacuum drying, albeit with different yields. \n\nOther COFs are more fragile, such as sonoCOF-B1 and sonoCOF-C1, and these materials are more sensitive to the synthesis and activation conditions. In particular, excessive amounts of water seem to inhibit the COF formation. Moreover, the high surface tension of water may result in the formation of amorphous frameworks due to pore collapse during activation if the materials are dried directly. Several studies have shown that the activation process, including the use of low-surface-tension solvents17 and supercritical $\\mathrm{CO}_{2}$ activation,18,19 can be important for such frameworks. As such, it is conceivable that some of the materials that were isolated here as amorphous polymers might be accessed as crystalline frameworks with alternative work-up procedures. \n\n![](images/2481e5821eb344f739f157c093d9f4216a4d8110e5d3c4f28e71dcbdeab5ed9a.jpg) \nFigure 3. High-throughput discovery of sonoCOFs for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in the absence of any added sacrificial reagents. Reaction conditions: $3\\mathrm{mg}$ of polymer, $\\boldsymbol{5}\\mathrm{mL}$ of water, air, simulated solar light for $1.5\\mathrm{h}$ (Oriel Solar Simulator, $1.0\\mathrm{{sun}}$ ). Left axis: amount of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ produced (bars); right axis: BET surface areas for the crystalline sonoCOFs (circle points). \n\nThere were four top-level conclusions for these aqueous sonoCOF syntheses: \n\n(i) In general, a higher concentration $(12\\mathbf{M})$ of $\\mathbf{AcOH}$ was more favorable for the formation of most COFs. In most cases, this both increases the solubility of the monomers and also catalyzes COF formation. \n(ii) Specific activations, such as the use of low-surfacetension solvents (hexane) or supercritical $\\mathrm{CO}_{2}$ activations, are crucial for the isolation of fragile COFs but unnecessary for other more robust frameworks (e.g., sonoCOF-A1). The most generalizable conditions for COF formation were $12\\mathrm{~\\AA~}$ AcOH with low-surfacetension solvent (hexane) activation or supercritical $\\mathrm{CO}_{2}$ activation. \n(iii) For some monomers with low reactivity, such as TFPA, it was difficult to form a solid polymer product under sonochemical conditions. \n(iv) In general, keto-enamine COFs showed lower crystallinity due to the reduced reversibility in the condensation reaction.20 \n\nThe experimental powder X-ray diffraction (PXRD) patterns for 12 of the 18 unreported COFs are shown in Figure 2. All of these COFs have either 1D or 2D structures. The PXRD measurements showed diffraction peaks that are consistent with the simulated structures (Figures S6−S9). The experimental PXRD patterns for sonoCOF-J1 and K1 matched well with a simulated ABC-stacking arrangement. SonoCOF-A3, A7, and B11, in particular, showed good crystallinity with intense and sharp low-angle reflections, which matched well with a simulated AA-stacking arrangement. The diffraction pattern of sonoCOF-F3 was very similar to that of the isostructural PT- $\\boldsymbol{\\mathrm{\\cdotCOF}^{21}}$ with a bex topology. The experimental PXRD patterns of sonoCOF-J3, K3, A4, J4, K4, and K11 matched well with 1D simulated structures. We believe that these 1D COFs have lower crystallinity because they cannot form noncovalent $\\pi{-}\\pi\\cdot$ -stacked 2D layers, which are known to enhance crystallinity in COFs. The unit cell parameters of the sonoCOFs were refined using the Pawley method. \n\n2.2. High-Throughput Screening for Photocatalytic ${\\mathsf{H}}_{2}{\\mathsf{O}}_{2}$ Production. High-throughput screening measurements have been used previously to identify photocatalysts for water splitting.22 Here, we used an analogous approach for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. The 76 functionally diverse conjugated polymers, including 60 crystalline sonoCOFs, were screened for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in pure water (no added sacrificial donors) in air using a high-throughput screening platform (see the Supplementary Information). \n\nHigh crystallinity23 and (arguably) porosity24 are thought to be favorable for photocatalytic performance. The benefits of crystallinity were strongly apparent here: none of the amorphous materials in the library showed $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production levels of greater than $1\\ \\mu\\mathrm{mol}$ (Figure 3), and all the materials that showed high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production $\\left(>2\\mu\\mathrm{mol}\\right)$ were crystalline COFs. This shows that crystalline structures are more suitable for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Most of the best photocatalysts in the library contained triazine (points labeled as G and/or 2 in Figure 3, for example sonoCOF-G2, G4, F2, and D2); this may be because these materials promote twoelectron oxygen reduction.6,25 Keto-enamine-based COFs (e.g., sonoCOF-I2, I5, and -I8) also tended to show good catalytic performance. The relationship between porosity and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production is shown in Figure 3. In general, there is little evidence for a correlation here: the four COFs with the highest $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production $\\left(>\\ 3.3\\ \\mu\\mathrm{mol}\\right)$ also have high Brunauer− Emmett−Teller (BET) surface areas $\\left({>}940\\ \\mathrm{m}^{2}\\ \\mathrm{g}^{-1}\\right)$ , but then again, most of the materials in this library are porous, and many porous COFs have low catalytic activity (e.g., sonoCOFA1, E3, and G8). In general, we found that acceptor−donor systems are beneficial for high activity. For example, sonoCOFF2 produces twice as much hydrogen peroxide as sonoCOF-F1 under visible light irradiation. The only difference between the two structures is that the benzene at the core of sonoCOF-F1 is replaced with a triazine, thus generating electron-rich and electron-poor sites for enhanced charge separation and photocatalytic activity. All of the sonoCOFs studied absorb visible light with an experimental optical band gap of less than $2.90~\\mathrm{eV}$ (Figures S45−S51). The positions of the conduction band (CB) and the valence band (VB) of the COFs govern the reduction of $\\mathrm{O}_{2}$ and the oxidation of ${\\mathrm{H}}_{2}{\\mathrm{O}}_{\\cdot}$ , respectively. As such, both the optical band gap and the band positions play an important role in photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. A comparison between these properties and the catalytic activity is provided in Figures S57−S59. As found for photocatalytic $\\mathrm{H}_{2}$ production using linear conjugated polymers,22 no single factor governs the catalytic activity, but some broad trends can be observed. In general, larger band gaps $\\left({>}2.4~\\mathrm{eV}\\right)$ lead to the highest catalytic activities (Figure S57). Most of the measured sonoCOFs have VB positions that should promote $\\mathrm{H}_{2}\\mathrm{O}$ oxidation (sonoCOF-I6 and sonoCOF-I8 are exceptions and have relatively low activity). All of the measured sonoCOFs have CB positions that should allow $\\mathrm{O}_{2}$ reduction (Figure S59), with $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production broadly increasing as CB values are more negative. Again, these plots illustrate the power of high-throughput methods here since neither the band gap nor CB/VB energy levels are solely deterministic for catalytic activity. We note that sonoCOF-A11 has the same chemical structure as the COF TAPD- $\\left(\\mathrm{OMe}\\right)_{2}$ that was reported previously to catalyze $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in the presence of sacrificial donors.14 For comparison, we also prepared this COF solvothermally (named here as solvoCOF-A11). However, neither sonoCOF-A11 nor solvoCOF-A11 showed measurable photocatalytic activity in pure water. \n\nSonoCOF-B1 showed the highest $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in this library over a short irradiation period of $1.5\\mathrm{~h~}$ using simulated solar light (Figure 3). However, we found that the crystallinity of sonoCOF-B1 was lost rapidly during the reaction (Figure S61a). Also, long-term tests showed that the photocatalytic performance decreased substantially after $24\\mathrm{~h~}$ (Figure S73). By contrast, sonoCOF-F2 showed good performance for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production and promising photostability over short reaction times according to powder X-ray diffraction (PXRD) analysis. Considering that both performance and photostability are important, we chose sonoCOF-F2 for more detailed study. \n\n2.3. Investigation of the Photocatalytic ${\\sf H}_{2}{\\sf O}_{2}$ Production Mechanism. To gain insight into the reaction mechanism, a series of experiments were conducted using a high-throughput screening platform (Supplementary Information). As shown in Figure S74, visible light irradiation is critical for the production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ : in the absence of light, no $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was produced over $^{48\\mathrm{~h~}}$ . An oxygen-rich atmosphere also favors $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production; very little $\\mathrm{H}_{2}\\mathrm{O}_{2}$ $(0.2\\bar{\\mu}\\mathrm{mol})$ ) was produced under a nitrogen atmosphere, whereas $8.5\\ \\mu\\mathrm{mol}$ was produced under pure $\\mathrm{O}_{2}$ $(99\\%)$ , which is 1.5 times greater than the amount produced in air (Figure 4a). This was further confirmed by isotopic labeling experiments using $^{18}{\\mathrm{O}}_{2}$ (Figure S75): the percentage of $^{18}{\\mathrm{O}}_{2}$ detected by mass spectrometry in the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ produced increased from 0 to $63.2\\%$ after $22\\mathrm{~h~}$ . \n\nActive species-trapping experiments were performed in air by using $\\mathrm{AgNO}_{3},$ tert-butyl alcohol (TBA), and benzoquinone (BQ) as electron $\\left(\\mathrm{e}^{-}\\right)$ , hydroxyl radical (·OH), and superoxide radical $\\left(\\cdot\\mathrm{O}_{2}^{-}\\right)$ scavengers. Due to the interference of BQ with the potassium iodide titrimetric assay, the relative peroxide levels were estimated using peroxide test sticks. As shown in Figure S63, the production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ decreases sharply when $\\mathrm{AgNO}_{3}$ is added, indicating that photogenerated electrons play a vital role in the photocatalytic oxygen reduction reaction (ORR). Almost no $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was detected when BQ was added, suggesting that $\\cdot\\mathrm{O}_{2}^{-}$ is involved. By contrast, the addition of TBA has almost no influence on the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production, suggesting that ·OH did not participate in the photocatalytic process. Based on these combined results, we suggest that the photoinduced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production of sonoCOF-F2 involves the stepwise reduction of $\\mathrm{O}_{2}$ $\\left(\\mathrm{O}_{2}\\rightarrow\\cdot\\mathrm{O}_{2}^{-}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}_{2}\\right)$ ). \n\n![](images/fc2615b2f5857d4a724830df3da50bd03206cfe7c575c9c0baab698bba489dcd.jpg) \nFigure 4. (a) Reactions using sonoCOF-F2 under different gas atmospheres: $3\\mathrm{mg}$ of COF in $\\boldsymbol{5}\\mathrm{mL}$ of water, $1.5\\mathrm{h}$ illumination (Oriel Solar Simulator, $1.0\\ s\\mathrm{un}\\$ ). (b) Photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production for sonoCOF-F2 in neat water, with ethanol, isopropanol (IPA), methanol, and benzyl alcohol ( $\\beta\\ \\mathrm{mg}$ of polymer, $4.5~\\mathrm{mL}$ of water, and $0.5\\mathrm{\\mL}$ of solvents), all with $1.5\\mathrm{~h~}$ illumination (Oriel Solar Simulator, $1.0\\quad\\mathrm{sun},$ . (c) Wavelength-dependent AQE values (measured in the first $\\mathrm{~1~h~}$ ) and solid-state UV−visible spectrum of sonoCOF-F2. (d) Longer-term photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production of sonoCOF-F2: $60~\\mathrm{mL}$ of water and $50~\\mathrm{mg}$ of sonoCOF-F2; 300 W Xe lamp; $\\lambda>420~\\mathrm{{nm}}$ . \n\nThe apparent quantum yield (AQY) was measured at different wavelengths to evaluate the photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production performance. The AQY was determined to be $4.8\\%$ at $420\\ \\mathrm{nm}$ , which followed the absorption spectrum, supporting a photoinduced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generation process (Figure 4c). \n\nHole scavengers, including ethanol, isopropanol (IPA), methanol, and benzyl alcohol (BA), were added to gain further insight into the mechanism (Figure 4b). A decrease was observed in the photocatalytic efficiency in the presence of ethanol, IPA, and methanol (all single-phase systems), but a marked increase in activity was observed in the presence of BA (a two-phase, liquid−liquid system). In the two-phase system (water/BA), the sonoCOF-F2 was selectively dispersed in the BA phase and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was produced in the aqueous phase, which may perhaps avoid the photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ decomposition (i.e., the back reaction), thus increasing the overall peroxide production rate. \n\n2.4. Long-Term Photocatalytic ${\\sf H}_{2}{\\sf O}_{2}$ Production. To be practically useful, the long-term photostability of catalysts is essential. We therefore tested the photostability of sonoCOFF2 using a continuous experiment $(96\\mathrm{h})$ in pure water (Figure 4d). As shown in Table S3, the photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate of sonoCOF-F2 is higher than most organic materials reported under similar conditions but lower than a linear conjugated polymer, DE7.9 After about $72\\mathrm{{h}},$ , the rate of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generation for sonoCOF-F2 decreased. Similar photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production profiles were observed in previous studies that involved composite photocatalysts (procyanidin− methoxybenzaldehyde (PM) dipolymers with carbon dots)26 and linear polymer photocatalyst (DE7).9 \n\nTo understand why the catalytic efficiency of sonoCOF-F2 decreased over longer periods of photolysis, we used FT-IR, PXRD, CP-MAS 13C NMR, X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM) to characterize the structure of sonoCOF-F2 before and after photocatalysis. FT-IR measurements showed that the imine bond $(\\mathrm{C}\\mathrm{=}\\mathrm{N})$ ) at $1630~\\mathrm{{cm}^{-1}}$ disappeared and a new peak from amide bond $({\\mathrm{C}}{=}{\\mathrm{O}})$ at $1676~\\mathrm{\\bar{cm}^{-1}}$ emerged after photocatalysis (Figure 5a), indicating that the imine linkage was oxidized to an amide linkage by photogenerated holes or radicals such as $\\cdot\\mathrm{O_{2}}^{-}$ . CP-MAS $^{\\mathrm{i}3}\\dot{\\mathrm{C}}$ NMR and XPS spectra further confirmed this transformation. After photocatalysis, the resonance at $155.1\\ \\mathrm{pm}$ associated with the imine functionality disappeared in the CP-MAS $^{13}\\mathrm{C}$ NMR spectrum, and a new signal appeared $\\left(163.7\\mathrm{ppm}\\right)$ , which was assigned to the amide bond carbon (Figure 5c). The characteristic $\\mathbf{N}$ 1s signal of the $\\mathsf{s p}^{2}$ -bonded nitrogen in the imine bonds and triazine rings was observed at $398.8\\ \\mathrm{~eV}$ for sonoCOF-F2. However, the $\\mathbf{N}$ 1s spectrum showed two separate resolved peaks after photocatalysis. The main peak at $398.7\\ \\mathrm{~eV}$ corresponds to the nitrogen in the triazine rings, and the other signal at $403.9\\ \\mathrm{eV}$ is ascribed to the nitrogen in the amide group (Figure 5d). This transformation from the imine linkage into an amide bond is one reason for the decrease in catalytic efficiency because of the loss of extended conjugation. To confirm that this transformation was not caused by light itself or by $\\mathrm{H}_{2}\\mathrm{O}_{2},$ sonoCOF-F2 was illuminated in water and stirred in $20~\\mathrm{mM}$ $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution under a nitrogen atmosphere for $24\\mathrm{~h~}$ . There was no change in FT-IR and PXRD patterns in either case (Figure S64), indicating that this transformation was caused by photogenerated holes or radicals rather than light or hydrogen peroxide. The conduction band (CB) and valence band (VB) (Figure S60) for sonoCOF-F2 are estimated to be $-2.0\\mathrm{V}$ (vs NHE) and $0.86\\mathrm{V}$ (vs NHE), respectively, which suggests that reduction of oxygen is thermodynamically possible but water oxidation to $\\mathrm{O}_{2}$ ( $\\dot{1}.23\\mathrm{~V~}$ vs $\\mathrm{N}\\mathrm{\\dot{H}E})^{27}$ and two-electron water oxidation (1.76 V vs NHE)28 directly to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ are not. We propose that photogenerated holes that do not participate in water oxidation could react with the COF itself and contribute to the degradation of catalytic performance. In addition, both PXRD (Figure $5\\mathrm{b}$ ) and HR-TEM images (Figure 5e,f) showed that sonoCOF-F2 had reduced crystallinity levels after photocatalysis compared to the pristine COF, which could be a secondary reason for the decrease in catalytic efficiency. \n\n![](images/9041b295d75b75da8856e98defefa66f49416258eb29124552aff058d55a8a9a.jpg) \nFigure 5. (a) FT-IR, (b) PXRD, (c) CP-MAS $\\mathrm{NMR},$ and (d) N 1s XPS spectra and (insets in (e) and (f): Fourier transform (FFT) images) HRTEM images of sonoCOF-F2 before and after a long-term photocatalytic testing $(96~\\mathrm{~h~})$ . Reaction conditions: $50~\\mathrm{~mg}$ of sonoCOF-F2, $60~\\mathrm{mL}$ of water, $\\mathrm{~O}_{2},$ 300 W Xe lamp $\\mathit{\\Omega}\\left(\\lambda>420\\ \\mathrm{nm}\\right)$ for $96\\mathrm{~h~}$ . \n\nWhile sonoCOF-F2 seems to have improved photostability compared to $\\mathrm{DE7}^{9}$ and procyanidin−methoxybenzaldehyde (PM) dipolymers,26 the stability is still far too low for practical applications. We therefore sought to improve the photostability and photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production performance of sonoCOF-F2 by system design. Benzyl alcohol (BA) is a hole scavenger for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production, and it was found to be effective in this sonoCOF-F2 system. Importantly, sonoCOF-F2 was found to be selectively dispersed in the BA phase in this two-phase system of water/BA mixture (Figure 6d), which realizes spontaneous separation of the benzaldehyde that is formed (in the BA phase) and of the photoproduced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (in the aqueous phase). Photocatalytic reduction of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ to $\\mathrm{OH^{-}}$ and ·OH can be avoided in this two-phase system, which will increase the overall activity. \n\n![](images/7ec1f90e43f9a7805f96752dd053231673aa084efa5ecef8100429b30d7a8487.jpg) \nFigure 6. (a) Comparison of long-term photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production using sonoCOF-F2 with and without benzyl alcohol. (b) FT-IR and (c) PXRD spectra of sonoCOF-F2 before and after long-term photocatalytic testing using benzyl alcohol $\\left(166\\ \\mathrm{~h~}\\right)$ . Reaction conditions: $50\\ \\mathrm{\\mg}$ of sonoCOF-F2, $60~\\mathrm{mL}$ of water or water/benzyl alcohol (9/1), $\\mathrm{O}_{2},$ Xe lamp $\\lambda>420~\\mathrm{nm},$ for $166\\mathrm{~h~}$ . (d) Image of sonoCOF-F2 dispersed in a mixture of water/benzyl alcohol (9/1). \n\nA continuous photocatalytic experiment $\\left(166\\ \\mathrm{~h~}\\right)$ was performed in a water/BA $(9/1$ , volume) mixture. This longterm photocatalytic test showed that there was no decrease in rate even after $166\\mathrm{~h~}$ (Figure 6a), with approximately linear kinetics throughout. There was no change in FT-IR spectra or PXRD patterns for sonoCOF-F2 before and after $166\\mathrm{~h~}$ of photocatalysis, suggesting excellent photostability under these conditions (Figure $^{\\mathrm{6b,c}}$ ). To compare the photocatalytic activity with TAPD- $\\left(\\mathrm{OMe}\\right)_{2}$ $\\boldsymbol{\\mathrm{COF}^{14}}$ when using hole scavengers, we performed a long-term photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production test using exactly the same photocatalysis set-up (Supplementary Information, Figure S70). The only difference with the reported procedure was that ethanol was used in place of BA. Over a reaction period of $^{96\\ \\mathrm{h},}$ sonoCOF-F2/BA produced $275.2\\ \\mu\\mathrm{mol}$ of $\\mathrm{H}_{2}\\mathrm{O}_{2},$ which is almost two times the amount produced by TAPD- $\\left(\\mathrm{OMe}\\right)_{2}$ COF/ethanol (142.3 $\\mu\\mathrm{mol})$ ). Also, longer-term photocatalytic tests showed that sono-COF-F2 could produce $\\mathrm{H}_{2}\\mathrm{O}_{2}$ continuously over 1 week using a two-phase mixture of water/BA $(1/9)$ (Figure S72) and $3482.8~\\mu\\mathrm{mol}$ of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was obtained over $168\\mathrm{~h~}$ (final concentration of $\\mathrm{H}_{2}\\mathrm{O}_{2}=116~\\mathrm{mM}$ and an average sustained $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate of $414.6\\ \\mathrm{mmol}\\ \\mathrm{h}^{-1}\\ \\mathrm{g}^{-1}$ based on the mass of the catalyst). \n\n# 3. CONCLUSIONS \n\nA high-throughput sonochemical synthesis strategy of imine COFs was developed and applied for the discovery of functional COFs as photocatalysts for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Imine-based sonoCOF-F2 was found to be an active photocatalyst for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in the absence of any sacrificial agents, but it is unstable over prolonged reaction times, transforming into an amide COF. Benzyl alcohol was introduced to form a two-phase catalytic system, which both improves the photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production performance and also protects the COF structure to enhance its photostability. Moreover, the two-phase system separates the reaction products. While the transformation of benzyl alcohol to benzaldehyde may not provide a practical solution for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generation, the basic concept could be extended to other “sacrificial” agents. For example, it might be possible to selectively oxidize waste materials, such as biomass, to produce value-added chemicals in parallel with $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. \n\n# ASSOCIATED CONTENT \n\n# $\\bullet$ Supporting Information \n\nThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jacs.2c02666. \n\nExperimental details; elemental analysis data; UV/Vis and FT-IR spectra; PXRD patterns; TGA curves; gas sorption data; CV data; SEM and TEM images; hydrogen peroxide production data (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\nJohn W. Ward − Materials Innovation Factory and Department of Chemistry and Leverhulme Research Centre for Functional Materials Design, Materials Innovation \n\nFactory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom; orcid.org/0000-0001-7186-6416; Email: john.ward@ liverpool.ac.uk Andrew I. Cooper − Materials Innovation Factory and Department of Chemistry and Leverhulme Research Centre for Functional Materials Design, Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom; orcid.org/0000-0003-0201-1021; Email: aicooper@ liverpool.ac.uk \n\n# Authors \n\nWei Zhao − Materials Innovation Factory and Department of Chemistry and Leverhulme Research Centre for Functional Materials Design, Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom; $\\circledcirc$ orcid.org/0000-0003-0265- 2590 \nPeiyao Yan − Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom \nBoyu Li − Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom \nMounib Bahri − Albert Crewe Centre for Electron Microscopy, University of Liverpool, Liverpool L69 3GL, United Kingdom \nLunjie Liu − Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom \nXiang Zhou − Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom \nRob Clowes − Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom \nNigel D. Browning − Albert Crewe Centre for Electron Microscopy, University of Liverpool, Liverpool L69 3GL, United Kingdom; $\\circledcirc$ orcid.org/0000-0003-0491-251X \nYue Wu − Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L69 7ZD, United Kingdom; $\\circledcirc$ orcid.org/0000-0003-2874-8267 \n\nComplete contact information is available at: https://pubs.acs.org/10.1021/jacs.2c02666 \n\n# Funding \n\nThis work was financially supported by the Leverhulme Trust via the Leverhulme Research Centre for Functional Materials Design. \n\n# Notes \n\nThe authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThe authors acknowledge funding from the Leverhulme Trust via the Leverhulme Research Centre for Functional Materials Design. P.Y., B.L., and L.L. thank the China Scholarship Council for PhD studentship. The authors thank Haofan Yang for useful discussions. The authors also thank the Materials Innovation Factory (MIF) team for help with instrument training. The TEM analysis was performed in the Albert Crewe Centre for Electron Microscopy, a University of Liverpool Shared Research Facility. The X-ray photoelectron (XPS) data collection was performed at the EPSRC National Facility for XPS (“HarwellXPS”), operated by Cardiff University and UCL under contract no. PR16195. \n\nREFERENCES \n(1) Campos-Martin, J. M.; Blanco-Brieva, G.; Fierro, J. L. G. Hydrogen Peroxide Synthesis: An Outlook beyond the Anthraquinone Process. Angew. Chem., Int. Ed. 2006, 45, 6962−6984. \n(2) Mase, K.; Yoneda, M.; Yamada, Y.; Fukuzumi, S. Seawater Usable for Production and Consumption of Hydrogen Peroxide as a Solar Fuel. Nat. Commun. 2016, 7, 11470. \n(3) Wei, Z.; Liu, M.; Zhang, Z.; Yao, W.; Tan, H.; Zhu, Y. Efficient Visible-Light-Driven Selective Oxygen Reduction to Hydrogen Peroxide by Oxygen-Enriched Graphitic Carbon Nitride Polymers. Energy Environ. Sci. 2018, 11, 2581−2589. \n(4) Zeng, X.; Liu, Y.; Hu, X.; Zhang, X. Photoredox Catalysis over Semiconductors for Light-Driven Hydrogen Peroxide Production. Green Chem. 2021, 23, 1466−1494. \n(5) Hou, H.; Zeng, X.; Zhang, X. Production of Hydrogen Peroxide by Photocatalytic Processes. Angew. Chem., Int. Ed. 2020, 59, 17356− 17376. \n(6) Kofuji, Y.; Isobe, Y.; Shiraishi, Y.; Sakamoto, H.; Tanaka, S.; Ichikawa, S.; Hirai, T. Carbon Nitride-Aromatic Diimide-Graphene Nanohybrids: Metal-Free Photocatalysts for Solar-to-Hydrogen Peroxide Energy Conversion with $0.2\\%$ Efficiency. J. Am. Chem. Soc. 2016, 138, 10019−10025. \n(7) Chen, L.; Wang, L.; Wan, Y.; Zhang, Y.; Qi, Z.; Wu, X.; Xu, H. Acetylene and Diacetylene Functionalized Covalent Triazine Frameworks as Metal-Free Photocatalysts for Hydrogen Peroxide Production: A New Two-Electron Water Oxidation Pathway. Adv. Mater. 2020, 32, 1904433. \n(8) Shiraishi, Y.; Takii, T.; Hagi, T.; Mori, S.; Kofuji, Y.; Kitagawa, Y.; Tanaka, S.; Ichikawa, S.; Hirai, T. Resorcinol-Formaldehyde Resins as Metal-Free Semiconductor Photocatalysts for Solar-toHydrogen Peroxide Energy Conversion. Nat. Mater. 2019, 18, 985− 993. \n(9) Liu, L.; Gao, M.-Y.; Yang, H.; Wang, X.; Li, X.; Cooper, A. I. Linear Conjugated Polymers for Solar-Driven Hydrogen Peroxide Production: The Importance of Catalyst Stability. J. Am. Chem. Soc. 2021, 143, 19287−19293. \n(10) Côté, A. P.; Benin, A. I.; Ockwig, N. W.; O’Keeffe, M.; Matzger, A. J.; Yaghi, O. M. Porous, Crystalline, Covalent Organic Frameworks. Science 2005, 310, 1166−1170. \n(11) Wang, X.; Chen, L.; Chong, S. Y.; Little, M. A.; Wu, Y.; Zhu, W.; Clowes, R.; Yan, Y.; Zwijnenburg, M. A.; Sprick, R. S.; Cooper, A. I. Sulfone-Containing Covalent Organic Frameworks for Photocatalytic Hydrogen Evolution from Water. Nat. Chem. 2018, 10, 1180−1189. \n(12) Fu, Z.; Wang, X.; Gardner, A. M.; Wang, X.; Chong, S. Y.; Neri, G.; Cowan, A. J.; Liu, L.; Li, X.; Vogel, A. A Stable Covalent Organic Framework for Photocatalytic Carbon Dioxide Reduction. Chem. Sci. 2020, 11, 543−550. \n(13) Zhi, Y.; Li, Z.; Feng, X.; Xia, H.; Zhang, Y.; Shi, Z.; Mu, Y.; Liu, X. Covalent Organic Frameworks as Metal-Free Heterogeneous Photocatalysts for Organic Transformations. J. Mater. Chem. A 2017, 5, 22933−22938. \n(14) Krishnaraj, C.; Sekhar Jena, H.; Bourda, L.; Laemont, A.; Pachfule, P.; Roeser, J.; Chandran, C. V.; Borgmans, S.; Rogge, S. M. J.; Leus, K.; Stevens, C. V.; Martens, J. A.; van Speybroeck, V.; Breynaert, E.; Thomas, A.; van der Voort, P. Strongly Reducing (Diarylamino)benzene-Based Covalent Organic Frame-work for Metal-Free Visible Light Photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ Generation. J. Am. Chem. Soc. 2020, 142, 20107−20116. \n(15) Zhao, W.; Yan, P.; Yang, H.; Bahri, M.; James, A. M.; Chen, H.; Liu, L.; Li, B.; Pang, Z.; Clowes, R. Using Sound to Synthesize Covalent Organic Frameworks in Water. Nat. Synth. 2022, 1, 87−95. (16) Isaka, Y.; Kawase, Y.; Kuwahara, Y.; Mori, K.; Yamashita, H. Two-Phase System Utilizing Hydrophobic Metal-Organic Frameworks (MOFs) for Photocatalytic Synthesis of Hydrogen Peroxide. Angew. Chem., Int. Ed. 2019, 58, 5402−5406. \n(17) Zhu, D.; Verduzco, R. Ultralow Surface Tension Solvents Enable Facile COF Activation with Reduced Pore Collapse. ACS Appl. Mater. Interfaces 2020, 12, 33121−33127. \n(18) Feriante, C. H.; Jhulki, S.; Evans, A. M.; Dasari, R. R.; Slicker, K.; Dichtel, W. R.; Marder, S. R. Rapid Synthesis of High Surface Area Imine-Linked 2D Covalent Organic Frameworks by Avoiding Pore Collapse During Isolation. Adv. Mater. 2020, 32, 1905776. \n(19) Sick, T.; Rotter, J. M.; Reuter, S.; Kandambeth, S.; Bach, N. N.; Döblinger, M.; Merz, J.; Clark, T.; Marder, T. B.; Bein, T. Switching on and off Interlayer Correlations and Porosity in 2D Covalent Organic Frameworks. J. Am. Chem. Soc. 2019, 141, 12570−12581. (20) Biswal, B. P.; Chandra, S.; Kandambeth, S.; Lukose, B.; Heine, T.; Banerjee, R. Mechanochemical Synthesis of Chemically Stable Isoreticular Covalent Organic Frameworks. J. Am. Chem. Soc. 2013, 135, 5328−5331. \n(21) Banerjee, T.; Haase, F.; Trenker, S.; Biswal, B. P.; Savasci, G.; Duppel, V.; Moudrakovski, I.; Ochsenfeld, C.; Lotsch, B. V. Substoichiometric 2D Covalent Organic Frameworks from Tri- and Tetratopic Linkers. Nat. Commun. 2019, 10, 2689. \n(22) Bai, Y.; Wilbraham, L.; Slater, B. J.; Zwijnenburg, M. A.; Sprick, R. S.; Cooper, A. I. Accelerated Discovery of Organic Polymer Photocatalysts for Hydrogen Evolution from Water through the Integration of Experiment and Theory. J. Am. Chem. Soc. 2019, 141, 9063−9071. \n(23) Aitchison, C. M.; Kane, C. M.; McMahon, D. P.; Spackman, P. R.; Pulido, A.; Wang, X.; Wilbraham, L.; Chen, L.; Clowes, R.; Zwijnenburg, M. A. Photocatalytic Proton Reduction by a Computationally Identified, Molecular Hydrogen-Bonded Framework. J. Mater. Chem. A 2020, 8, 7158−7170. \n(24) Kawase, Y.; Isaka, Y.; Kuwahara, Y.; Mori, K.; Yamashita, H. Ti Cluster-Alkylated Hydrophobic MOFs for Photocatalytic Production of Hydrogen Peroxide in Two-Phase Systems. Chem. Commun. 2019, 55, 6743−6746. \n(25) Shiraishi, Y.; Kanazawa, S.; Kofuji, Y.; Sakamoto, H.; Ichikawa, S.; Tanaka, S.; Hirai, T. Sunlight-Driven Hydrogen Peroxide Production from Water and Molecular Oxygen by Metal-Free Photocatalysts. Angew. Chem., Int. Ed. 2014, 53, 13454−13459. (26) Wu, $\\mathrm{Q.;}$ Cao, J.; Wang, X.; Liu, Y.; Zhao, Y.; Wang, H.; Liu, Y.; Huang, H.; Liao, F.; Shao, M. A Metal-Free Photocatalyst for Highly Efficient Hydrogen Peroxide Photoproduction in Real Seawater. Nat. Commun. 2021, 12, 483. \n(27) Fang, Y.; Hou, Y.; Fu, X.; Wang, X. Semiconducting Polymers for Oxygen Evolution Reaction under Light Illumination. Chem. Rev. 2022, 122, 4204−4256. \n(28) Yang, L.; Chen, H.; Xu, Y.; Qian, R.; Chen, $\\mathrm{\\underline{{{Q.}}}}{\\mathrm{;}}$ Fang, Y. Synergetic Effects by ${\\mathrm{Co}}^{2+}$ and $\\mathrm{PO_{4}}^{3-}$ on Mo-doped ${\\tt B i V O}_{4}$ for an Improved Photoanodic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ Evolution. Chem. Eng. Sci. 2022, 251, 117435. " + }, + { + "id": "10.1038_s41467-022-31468-0", + "DOI": "10.1038/s41467-022-31468-0", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-31468-0", + "Relative Dir Path": "mds/10.1038_s41467-022-31468-0", + "Article Title": "RuO2 electronic structure and lattice strain dual engineering for enhanced acidic oxygen evolution reaction performance", + "Authors": "Qin, Y; Yu, TT; Deng, SH; Zhou, XY; Lin, DM; Zhang, Q; Jin, ZY; Zhang, DF; He, YB; Qiu, HJ; He, LH; Kang, FY; Li, KK; Zhang, TY", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "While water splitting in acid offers higher operational performances than in alkaline conditions, there are few high-activity, acid-stable oxygen evolution electrocatalysts. Here, authors examine electrochemical Li intercalation to improve the activity and stability of RuO2 for acidic water oxidation. Developing highly active and durable electrocatalysts for acidic oxygen evolution reaction remains a great challenge due to the sluggish kinetics of the four-electron transfer reaction and severe catalyst dissolution. Here we report an electrochemical lithium intercalation method to improve both the activity and stability of RuO2 for acidic oxygen evolution reaction. The lithium intercalates into the lattice interstices of RuO2, donates electrons and distorts the local structure. Therefore, the Ru valence state is lowered with formation of stable Li-O-Ru local structure, and the Ru-O covalency is weakened, which suppresses the dissolution of Ru, resulting in greatly enhanced durability. Meanwhile, the inherent lattice strain results in the surface structural distortion of LixRuO2 and activates the dangling O atom near the Ru active site as a proton acceptor, which stabilizes the OOH* and dramatically enhances the activity. This work provides an effective strategy to develop highly efficient catalyst towards water splitting.", + "Times Cited, WoS Core": 317, + "Times Cited, All Databases": 323, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000819790100020", + "Markdown": "# RuO2 electronic structure and lattice strain dual engineering for enhanced acidic oxygen evolution reaction performance \n\nYin $\\mathsf{Q i n}^{1,10}$ , Tingting $\\mathsf{Y u}^{1,10}$ , Sihao Deng2, Xiao-Ye Zhou $\\textcircled{1}$ 3✉, Dongmei Lin4, Qian Zhang5, Zeyu Jin1, Danfeng Zhang 6, Yan-Bing ${\\mathsf{H e}}^{6},$ Hua-Jun Qiu $\\textcircled{1}$ 1✉, Lunhua ${\\mathsf{H e}}^{2,7,8}$ , Feiyu Kang6, Kaikai Li 1✉ & Tong-Yi Zhang 9✉ \n\nDeveloping highly active and durable electrocatalysts for acidic oxygen evolution reaction remains a great challenge due to the sluggish kinetics of the four-electron transfer reaction and severe catalyst dissolution. Here we report an electrochemical lithium intercalation method to improve both the activity and stability of ${\\sf R u O}_{2}$ for acidic oxygen evolution reaction. The lithium intercalates into the lattice interstices of ${\\mathsf{R u O}}_{2},$ donates electrons and distorts the local structure. Therefore, the Ru valence state is lowered with formation of stable Li-O-Ru local structure, and the Ru–O covalency is weakened, which suppresses the dissolution of Ru, resulting in greatly enhanced durability. Meanwhile, the inherent lattice strain results in the surface structural distortion of $\\mathsf{L i}_{x}\\mathsf{R u O}_{2}$ and activates the dangling O atom near the Ru active site as a proton acceptor, which stabilizes the ${\\mathsf{O O H}}^{\\star}$ and dramatically enhances the activity. This work provides an effective strategy to develop highly efficient catalyst towards water splitting. \n\nTtrhea otpixroyongceinsn elovefocltOrutoEicoRhnenmrveiocalacvlteowsna e(frOosuEprRl-ie)tl ieincs a1on4c tIurncatinrailsfnesarinceoanldcliyec, which demands higher energy than the cathodic reaction, i.e., hydrogen evolution reaction (HER) which needs only two electrons5,6. Therefore, the OER process governs the overall efficiency of electricity-driven water splitting. Water splitting can be operated in either acidic or alkaline conditions. OER under acidic conditions are more preferable benefiting from the higher ionic conductivity of acidic electrolyte and capability of operating at higher current density as well as more compact system design7–9, but their practical application is significantly hindered by the sluggish OER kinetics and limited stability of existing electrocatalysts10–12. Thus, it is imperative to develop acidic OER electrocatalysts with enhanced activity and stability in order to improve the efficiency of electrochemical water splitting. \n\nRutile ${\\mathrm{RuO}}_{2}$ is considered as a benchmark catalyst for the acidic OER13. Nevertheless, the low activity of virgin ${\\mathrm{RuO}}_{2}$ and the poor stability as a result of the dissolution of Ru and participation of lattice oxygen (lattice oxygen-mediated mechanism, LOM) in acidic media remain serious problems for ${\\mathrm{RuO}}_{2}$ catalysts14–16. In order to improve the performance of $\\mathrm{RuO}_{2}$ electrocatalysts, tuning the electronic structure of Ru sites by lattice doping has been demonstrated to be an effective strategy11,17–20. In particular, first-row transition metals are usually considered as doping elements owing to their unique features of $3d$ electrons and low cost4,16,18,21,22. Other transition metals such as $\\mathrm{Y}^{19}$ , $\\mathrm{Pt^{11}}$ , W, and $\\mathrm{Er}^{23}$ were also reported as effective doping elements. The charge density and spin density of ${\\mathrm{RuO}}_{2}$ can be redistributed by doping with these alien atoms of different valence state and electronegativity, thus regulating the adsorption energy of the oxo-intermediates at active sites12,17,18,24. The doped ${\\mathrm{RuO}}_{2}$ , e.g., Co-doped $\\mathrm{RuO}_{2}{}^{25}$ , may follow a LOM mechanism because of the increase of the covalency of the metal–oxygen bonds26, rather than the conventional adsorbate evolution mechanism (AEM), resulting in enhanced activity but probably poor stability due to the oxidation of lattice oxygen. Although W, Er- co-doping strategy was reported to be able to enhance the energy barrier of the lattice oxygen oxidation of $\\mathrm{RuO}_{2}$ and prohibit the formation of oxygen vacancies due to the enlarged gap between the Fermi level and the O $2p$ -band center23, there is still much room to enhance the stability and activity of ${\\mathrm{RuO}}_{2}$ for practical applications. \n\nIn addition to doping, electrochemical ion insertion involving coupled ion–electron transfer is also an effective method to introduce alien elements into a host material for electronic or crystal structure modulation, and has been considered as a synthetic strategy to improve the catalytic performance of layerstructured materials27–29, such as $\\mathrm{LiCoO}_{2}$ for $\\mathrm{OER}^{30}$ and $\\ensuremath{\\mathrm{MoS}}_{2}$ for $\\mathrm{HER}^{28}$ , where the Li concentration is an adjustable variable over a wide range31,32. Recently, Zheng’s group utilized a lithiation strategy to improve the $\\mathrm{CO}_{2}$ reduction performance of catalysts, including $\\mathrm{C}\\mathrm{\\dot{u}}_{3}\\mathrm{N}_{x}{}^{33}$ and $\\mathrm{Sn}^{34}$ . Various studies have shown that ${\\mathrm{RuO}}_{2}$ can be inserted with Li ions for battery applications, and a solid solution phase forms before a $\\mathrm{Li:Ru}=1{:}1$ ratio is reached35–38. On the other hand, the insertion of a large amount of lithium atoms into ${\\mathrm{RuO}}_{2}$ may induce a relatively large lattice strain. Nevertheless, engineering lattice strain by electrochemical lithium insertion has not been fully explored for improving OER performance of ${\\mathrm{RuO}}_{2}$ . \n\nIn this work, we adopt an electrochemical method to intercalate lithium into $\\mathrm{RuO}_{2}$ lattice interstices with tunable lithium concentration to improve the OER activity and durability of ${\\mathrm{RuO}}_{2}$ in acidic media. We find that the OER activity of the formed ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ solid solution phase increases with the nominal lithium concentration $(x)$ and reaches a record low overpotential of $156\\mathrm{mV}$ at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ in 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ when $x$ reaches 0.52. Meanwhile, the $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ exhibits excellent durability during $70\\mathrm{{h}}$ chronopotentiometry test with neglectable overpotential increase. XAS analysis and DFT calculations reveal that lithium, as an electron donor, influences the electronic structure and lattice strain of ${\\mathrm{RuO}}_{2}$ . The $\\mathrm{Ru-O}4d-2p$ hybridization is weakened with a decreased Ru–O covalency. Meanwhile, the valence state of Ru is decreased with the formation of stable Li–O-Ru local structure. Thus, the participation of lattice oxygen and dissolution of Ru are suppressed during OER, enhancing the stability of $\\mathrm{RuO}_{2}$ . DFT calculations find that the surface structural distortion induced by inherent lattice strain activates the dangling O atom near the Ru active site as a proton acceptor to stabilize the $\\scriptstyle{\\mathrm{OOH}^{*}}$ and thus dramatically enhances the activity of $\\mathrm{RuO}_{2}$ . This work proposes a creative strategy to design highly efficient and stable OER catalysts. \n\nResults and discussion Crystal structure and composition. Lithium intercalated ${\\mathrm{RuO}}_{2}$ $(\\mathrm{Li}_{x}\\mathrm{RuO}_{2})$ with tunable lithium concentration was prepared by electrochemical lithiation process which involves coupled ion–electron transfer, as shown in Fig. 1a. The lithium concentration $x$ in ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ is linearly correlated to the time when the current density is constant during electrochemical lithiation, and thus can be easily adjusted. Rutile ${\\mathrm{RuO}}_{2}$ crystallizes in a tetragonal system with a space group of $P4_{2}/m n m$ , consisting of a ruthenium atom octahedrally coordinated to six oxygen atoms (Fig. 1b)39. Operando XRD, ex situ XRD, and TEM were conducted to reveal the crystal structure of the ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ after lithium intercalation. The operando XRD (Fig. 1d and Supplementary Fig. 1) results under a constant current density of $\\mathrm{\\dot{10}\\ m A\\ g^{-\\dot{1}}}$ indicate that a solid solution phase ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ with the same rutile structure to pristine $\\mathrm{RuO}_{2}$ formed in the initial stage of lithium intercalation, evidenced by the slight shifting of the original peaks towards the lower angles. Further lithiation induces a first-order phase transition from the solid solution phase to ${\\mathrm{LiRuO}}_{2}$ phase32, as a new set of diffraction peaks appears. However, the ${\\mathrm{LiRuO}}_{2}$ phase is unstable when the electrochemical lithiation process is terminated. The intensity of the XRD peaks of the $\\mathrm{LiRuO}_{2}$ phase gradually weakens while the peaks of ${\\bar{\\mathrm{Li}}}_{x}{\\mathrm{RuO}}_{2}$ phase strengthen during relaxation, indicating the reversed transition from $\\mathrm{LiRuO}_{2}$ to ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ phase. Thus, the final structure of the ${\\mathrm{RuO}}_{2}$ after lithium intercalation is ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ , a solid solution phase, which is further confirmed by the ex situ TEM and XRD results (Fig. 1e, f). Figure 1e presents the ex situ XRD patterns of the pristine ${\\mathrm{RuO}}_{2}$ and the ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ after electrochemical lithium intercalation under a current density of $10\\mathrm{mAg^{-1}}$ for 2 h, 9 h, $12\\mathrm{h}$ , and $16\\mathrm{h}$ , corresponding to the nominal lithium concentrations of $x=0.07$ , 0.29, 0.39, and 0.52 (Details for the estimation of the nominal lithium concentration can be found in Supplementary Fig. 2). Obviously, the ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ inherits the XRD characteristics of the pristine ${\\mathrm{RuO}}_{2}$ with the shift of XRD peaks towards low angles (Supplementary Fig. 3), which means the lattice of the ${\\mathrm{RuO}}_{2}$ was expanded due to lithium intercalation. Neutron powder diffraction (NPD) analyses (Supplementary Fig. 4) and DFT calculations (Supplementary Figs. 5 and 6 and Fig. 1c) indicate that the lithium ions intercalate into the octahedral interstice formed by six adjacent O atoms rather than replacing the Ru cations, and thereby the ${\\mathrm{RuO}}_{2}$ lattice is expanded, which is in line with the XRD results. To extract the lattice parameters of the $\\mathrm{RuO}_{2}$ before and after lithium intercalation, an Expectation–Maximization (EM) Algorithm-based machine-learning method was adopted to fit the XRD patterns. The fitting results are illustrated in Supplementary Fig. 7, and the lattice parameters of all the samples are listed in Supplementary Table 1. A dilatation strain along the $a$ -axis is observed and increases from 0.14 to $0.25\\%$ with the increase of the degree of lithiation. The HAADF-STEM images show the lattice fringes corresponding to the (002), (210) planes (Fig. 1f, left), and (101), (111) planes (Fig. 1f, right) of rutilestructured $\\mathrm{RuO}_{2}$ , further demonstrating that the ${\\mathrm{RuO}}_{2}$ after lithium intercalation preserves its original crystal structure. In addition, the lithium intercalation shows no influence on the morphology of the ${\\mathrm{RuO}}_{2}$ particles (Supplementary Fig. 8). In contrast to pristine ${\\mathrm{RuO}}_{2}$ , the presence of a Li $\\textbf{1}s$ peak in the X-ray photoelectron spectroscopy (XPS) profile of $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ (Fig. $_{1\\mathrm{g}}$ and Supplementary Fig. 9a) indicates that lithium is inserted. Furthermore, the Li K-edge (edge onset at $55\\mathrm{eV}_{\\cdot}$ ) STEM-EELS map (Supplementary Fig. 9b, c) and EDS elemental map (Supplementary Fig. 10) of the $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ confirm the existence of lithium. \n\n![](images/e5c4338f9041b5560205da38cbf0847af39ac6c07f42ef20a9b99d8daf1544b2.jpg) \nFig. 1 Structural and compositional characterizations. a Schematic illustration of the preparation of lithium intercalated ${\\sf R u O}_{2}$ . b $\\mathsf{R u O}_{6}$ octahedron before lithium intercalation. c ${\\sf R u O}_{6}$ octahedron after lithium intercalation. d Operando $x_{R}\\mathsf{D}$ of ${\\sf R u O}_{2}$ during electrochemical lithiation under a constant current density of $10\\mathsf{m A}\\mathsf{g}^{-1}$ , followed by $14\\mathsf{h}$ relaxation. e Ex situ XRD patterns of the pristine ${\\sf R u O}_{2}$ and the ${\\mathsf{L i}}_{x}{\\mathsf{R u O}}_{2}$ . f The HAADF-STEM images of the pristine ${\\sf R u O}_{2}$ (left) and the $\\mathsf{L i}_{0.52}\\mathsf{R u O}_{2}$ (right). $\\pmb{\\mathsf{g}}$ The high-resolution Li 1 s XPS of $\\mathsf{L i}_{0.52}\\mathsf{R u O}_{2}$ . \n\nCatalytic performance. The OER performance of the pristine $\\mathrm{RuO}_{2}$ and ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ was evaluated using a three-electrode system in 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution. Fig. 2a shows the polarization curves measured by linear sweep voltammetry (LSV) with the current normalized by the disk area of the glassy carbon electrode. Supplementary Fig. 11 shows that the $\\mathrm{O}_{2}$ generation starts at around $1.3\\mathrm{V}$ , and the polarization curve shows almost no change in the initial seven cycles. Here, the overpotential for reaching a current density of $10\\mathrm{\\dot{m}A}\\mathrm{cm}^{-2}$ $(\\boldsymbol{\\eta}_{10})$ of the 3rd cycle is used for activity comparison. The pristine ${\\mathrm{RuO}}_{2}$ exhibits the lowest activity with an overpotential of $320\\mathrm{mV}$ . As the lithium concentration $x$ increases, the overpotential gradually decreases and reaches a significantly low value of $156\\mathrm{mV}$ for $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ (Fig. 2b), which overcomes the limitation from the inherent linear scaling relation44. However, further increasing the lithium concentration does not make further improvement of the activity, and the $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ exhibits the best activity. It is worth noting that the $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ requires a small overpotential of $335\\mathrm{mV}$ to deliver a large OER current density of $200\\mathrm{\\dot{m}A c m}^{-2}$ . We further estimated the electrochemically active surface area (ECSA) of ${\\mathrm{RuO}}_{2}$ and $\\mathrm{Li}_{x}\\mathrm{RuO}_{2}.$ and plotted the LSVs with respect to the ECSA (Supplementary Figs. 12 and 13), which indicates that the higher OER activity of ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ is not attributed to the varied ECSA, and the Li insertion plays an important role in enhancing the intrinsic activity. Tafel plots derived from the polarization curves within the overpotential range of 0.17 to $0.27\\mathrm{V}$ , i.e., $1.4\\mathrm{-}1.5\\mathrm{V}$ vs RHE, are shown in Fig. 2c. The Tafel slopes of the pristine $\\mathrm{RuO}_{2}$ and ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ (where $x=0$ , 0.07, 0.29, 0.39, 0.52) are 105.8, 103.6, 87.7, 86.0, and $83.3\\mathrm{mV}\\mathrm{dec}^{-1}$ , respectively. The decrease of Tafel slope with an increase in lithium concentration indicates that the electrocatalytic kinetics of ${\\mathrm{RuO}}_{2}$ are enhanced by lithium intercalation2,14,45. In addition, all the Tafel slopes are higher than $80\\mathrm{mV}\\mathrm{dec}^{-1}$ , indicating that all the catalysts operate via the same OER mechanism18,42,46. \n\nIn addition to activity, durability is another crucial parameter for evaluating the OER performance of electrocatalysts in acidic electrolyte due to the corrosive conditions. Chronopotentiometry tests were conducted at a current density of $10\\mathrm{\\dot{m}A}\\mathrm{cm}^{-2}$ . As shown in Fig. 2d, the catalytic stability of $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ is far better than that of the pristine $\\mathrm{RuO}_{2}$ . The $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ can continuously work for $70\\mathrm{{h}}$ without an evident increase in the overpotential. In comparison, the OER activity of pristine ${\\mathrm{RuO}}_{2}$ decreases dramatically in less than $20\\mathrm{h}$ . The dissolution of Ru in the acidic electrolyte during electrolysis is further monitored using inductively coupled plasma optical emission spectrometry (ICPOES). The percentage of Ru dissolved from pristine $\\mathrm{RuO}_{2}$ and $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ during the chronopotentiometry tests at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ was measured and shown in Fig. 2e. For pristine ${\\mathrm{RuO}}_{2}$ the dissolution percentage of $\\mathtt{R u}$ is very low because of its low activity and poor stability. For $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ , in the 1st hour of the OER test, the dissolution percentage of Ru is around $0.9\\%$ . After $24\\mathrm{h}$ , the dissolution percentage of $\\mathtt{R u}$ is increased slightly to $1.8\\%$ , and then plateaued. Even after $48\\mathrm{h}$ , the dissolution percentage of $\\mathtt{R u}$ remained very low at $1.9\\%$ which is much lower than those reported for amorphous/crystalline hetero-phase $\\mathrm{RuO}_{2}$ (in $0.1\\mathrm{M}$ $\\mathrm{HClO_{4}})^{47}$ and SrRuIr oxide (in $0.5{\\bf M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4})^{48}$ during chronopotentiometry test at $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , indicating good corrosion resistance of $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ in acidic condition. In sum, the $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ shows excellent activity and stability, outperforming many state-of-the-art $\\mathrm{RuO}_{2}$ -based acidic OER electrocatalysts (Fig. 2f)14,17,23,25,42,48. \n\n![](images/fa40144156e638ac03e1295747c313bc64292fd47f153360836d55ceec9d870d.jpg) \nFig. 2 OER performance in 0.5 M ${\\bf H}_{2}\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\thinspace\\large=\\thinspace\\qquad\\large=\\thinspace\\large=\\thinspace\\frac{1}{2}$ solution. a Polarization curves. RHE reversible hydrogen electrode. b Overpotentials $(\\mathfrak{n}_{110})$ of ${\\mathsf{R u O}}_{2}$ and $\\mathsf{L i}_{x}\\mathsf{R u O}_{2}$ at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ . The error bars represent the deviation from the overpotentials in (a). c Tafel plots. d Chronopotentiometry curve of $\\mathsf{L i}_{0.52}\\mathsf{R u O}_{2}$ and ${\\sf R u O}_{2}$ at a current density of $10\\mathsf{m A}\\mathsf{c m}^{-2}$ . e Percentage of $\\mathsf{R}\\mathsf{u}$ dissolved from ${\\sf R u O}_{2}$ and $\\mathsf{L i}_{0.52}\\mathsf{R u O}_{2}$ after electrocatalysis for different reaction times. f Comparison of the overpotential required to achieve a 10 mA $\\mathsf{c m}^{-2}$ cathodic current density and chronopotentiometry durability at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ in acidic media for various RuO2-based electrocatalysts14,17,23,25,40–43. \n\nOrigin of the enhanced activity. The scaling relation among the OER intermediates in AEM imposes a theoretical overpotential ceiling on the OER activity3, which is apparently overcome by $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ . To uncover the origin of the enhanced activity, density functional theory (DFT) calculations and $\\mathrm{\\DeltaX}$ -ray absorption spectroscopy (XAS) analyses were performed to get insights into the electronic and crystal structures of the ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ . DFT calculations were performed on the superlattice of $\\mathrm{Li}_{n}\\mathrm{Ru}_{32}\\mathrm O_{64}$ $(\\mathrm{Li}_{x}\\mathrm{RuO}_{2}$ with $x=n/32{\\mathrm{.}}$ ) to reveal the influence of lithium intercalation on the electronic structure of $\\mathrm{RuO}_{2}$ . The calculation results show that the $d$ -band structure of Ru and $2p$ -band structure of $\\mathrm{~O~}$ are modulated (Fig. 3a) by lithium intercalation. The partial density of states (PDOS) analyses demonstrate that the $e_{g}$ occupancy is much closer to unity for $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ $(|e_{g}-1|=$ 0.05) than $\\mathrm{RuO}_{2}$ $\\lceil e_{g}-1\\rceil=0.16)$ , and meanwhile the O $2p$ -band center moves closer to the Fermi level slightly. The $e_{g}$ occupancy is highly related to the binding strength of active Ru sites with oxo-intermediates, and the optimal OER activity is generally achieved when the $e_{g}$ occupancy is close to unity3. Thus, the activity enhancement by lithium intercalation is partially attributed to the modulation of the electronic structure of Ru. \n\nHowever, only modulating the $e_{g}$ occupancy of Ru can hardly break the scaling relation for achieving better activity49. Activating the lattice O (LOM) by increasing the $\\mathrm{{Ru-O}}$ covalency can avoid the limitation caused by the scaling relation, which is however demonstrated to be impossible for this case, as discussed in the next section. Figure 3b shows the Fourier-transformed Ru K-edge extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) spectra of pristine ${\\mathrm{RuO}}_{2}$ and ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ . All the spectra exhibit the same spectral components, but a slight loss in intensity and difference in peak position are observed with the increase in lithium concentration. The peaks represent the neighboring atomic shells in the vicinity of Ru, i.e., O in the first shell and Ru in the second shell. Fitting the Fourier-transformed EXAFS spectra determines the bond lengths and average coordination numbers. It is revealed that, as the lithium concentration is increased, the coordination number of $\\mathrm{{Ru-O}}$ decreases slightly, which implies an intrinsically lattice distortion/strain induced by lithium intercalation and is in line with the broadening of the full width at half maximum (FWHM) of the XRD peaks (Supplementary Fig. 14) and the enhancement of the background intensity of NPD patterns (Supplementary Fig. 5). The lattice distortion/strain is also evidenced by HAADF-STEM. Figure 3c and Supplementary Fig. 15 show the lattice strain distributions of $\\mathrm{RuO}_{2}$ and ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ calculated from geometric phase analysis (GPA) of atomicresolution HAADF-STEM images and HRTEM images. Compared with the pristine $\\mathrm{RuO}_{2}$ , the intercalation of lithium generates more intense tensile-compressing dislocation dipoles in these GPA strain maps due to the distortion of ${\\mathrm{RuO}}_{2}$ lattice. The stronger strain field of ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ will give rise to a more distorted surface atomic structure in ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ , which is expected to modify the reactivity of the catalyst surface44,50. \n\nThe free energies of the four elementary steps in OER $(^{*}+2\\mathrm{H}_{2}\\mathrm{O}\\to\\mathrm{OH}^{*}\\to\\mathrm{O}^{*}\\to\\mathrm{OOH}^{*}\\to\\mathrm{O}_{2})$ for ${\\mathrm{RuO}}_{2}$ and $\\operatorname{Li}_{x}$ - ${\\mathrm{RuO}}_{2}$ were calculated through DFT calculations, to uncover the role of the surface structure distortion. As (110) surface is the most stable surface of rutile $\\mathrm{RuO}_{2}$ , two slab models of (110) surfaces were built for ${\\mathrm{RuO}}_{2}$ and $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ (Supplementary Fig. 16). The Ru atom with a coordination number of 5 was considered as the active site47. The results (Fig. 3d) show that the rate-determining step in the four-electron process for both ${\\mathrm{RuO}}_{2}$ and $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ is the formation of ${\\mathrm{OOH}}^{*}$ , thence the absolute value $Z$ $(\\Delta\\mathrm{G}(\\mathrm{OOH^{*}}){\\cdot}\\Delta\\mathrm{G}(\\mathrm{O^{*}}))$ can be used to evaluate the OER catalytic activity. The $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ model shows a $Z$ value of ${\\sim}1.74\\mathrm{eV}.$ , which is lower than that of $\\mathrm{RuO}_{2}$ $({\\sim}2\\mathrm{eV})$ . Subsequently, the energy consumption for the conversion from ${{\\mathrm{O}}^{*}}$ to ${\\bar{\\mathrm{OOH}}}^{*}$ is reduced at the surface of $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ . The decrease of $Z$ in $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ can be attributed to the decreased adsorption energy of ${{\\mathrm{O}}^{*}}$ and increased adsorption energy of ${\\mathrm{OOH^{*}}}$ (stabilization of $\\mathrm{{OOH^{*}}},$ ) at the $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ surface. Figure 3e, f compares the charge density distribution of the ${{\\cal O}}^{*}$ and ${\\mathrm{\\bar{O}O H^{*}}}$ absorbed on the (110) surface of ${\\mathrm{RuO}}_{2}$ and $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ . Interestingly, the obvious overlap of the electron cloud of the H atom of ${\\mathrm{OOH}}^{*}$ and the dangling O atom of $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ is observed (Fig. 3f). The charge density in the center of the “bond” formed by the H atom of ${\\mathrm{\\Gamma}}_{\\mathrm{OOH}^{*}}$ and the dangling O atom is calculated to be 0.091 and $0.132~\\mathrm{e}^{-1}~\\mathrm{Bohr}^{3}$ for $\\mathrm{RuO}_{2}$ and $\\mathrm{Li}_{0.5}\\mathrm{RuO}_{2}$ , respectively. Therefore, the dangling O atoms on the distorted surface are activated as a proton acceptor by lithium intercalation3. The $\\mathrm{~H~}$ atom in ${\\mathrm{OOH}}^{*}$ can be more firmly bonded to the dangling $\\mathrm{~O~}$ atom to stabilize the ${\\mathrm{OOH^{*}}}$ , resulting in a considerable improvement in the catalytic activity3. In sum, the enhanced activity of the ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ is partially attributed to the modulated $d$ -band structure of Ru, and more importantly is attributed to the lattice strain-induced activation of the dangling $\\mathrm{~O~}$ atom as the proton acceptor. Therefore, the ${\\mathrm{OOH^{*}}}$ vs. $\\mathrm{OH^{*}}$ scaling relation is broken and better activity is achieved. It is also worth noting that future efforts directed toward the ideal OER activity may focus on optimizing the free energy of every OER step to approach the equilibrium potential of $1.23\\mathrm{~eV}^{51}$ . \n\n![](images/9b71074c234df04f1b44592dec18c9e27077bd24ba3acb60b8cb71041c12407a.jpg) \nFig. 3 OER mechanism analysis. a PDOS of the ${\\sf R u O}_{2}$ and $\\mathsf{L i}_{0.5}\\mathsf{R u O}_{2}$ . b Fourier-transformed Ru K-edge extended X-ray absorption fine structure (EXAFS) spectra. c Lattice strain $(\\varepsilon_{\\times\\times})$ measured from geometric phase analysis (GPA) of atomic-resolution HAADF − STEM images (Fig. 1f) for ${\\sf R u O}_{2}$ (up) and for $\\mathsf{L i}_{0.56}\\mathsf{R u O}_{2}$ (down). d Calculated OER free-energy diagrams for ${\\mathsf{R u O}}_{2}$ and $\\mathsf{L i}_{0.5}\\mathsf{R u O}_{2}$ . e The charge density distribution of the $0^{\\star}$ absorbed on the (110) surface of ${\\sf R u O}_{2}$ (Up) and $\\mathsf{L i}_{0.5}\\mathsf{R u O}_{2}$ (down). The outermost black curve corresponds to the charge density of $0.0164~\\mathrm{e}^{-}/\\mathsf{B o h r}^{3}$ . f The charge density distribution of the ${\\mathsf{O O H}}^{\\star}$ absorbed on the (110) surface of ${\\sf R u O}_{2}$ (up) and $\\mathsf{L i}_{0.5}\\mathsf{R u O}_{2}$ (down). The outermost black curve corresponds to the charge density of $0.1~\\mathrm{e}^{-}/\\mathsf{B o h r}^{3}$ . \n\nOrigin of the enhanced stability. The prominent drawback of ${\\mathrm{RuO}}_{2}$ in acidic media is its poor stability, which is mainly due to the dissolution of high-valence Ru and oxidation of the lattice oxygen as a result of $\\mathrm{{Ru-O}}$ covalency during the OER process52. Thus, it is necessary to decrease the valence state of Ru and suppress the participation of lattice oxygen. It is found that intercalation of lithium yields a Ru valence state of less than $+4$ and a decreased $\\mathrm{{Ru-O}}$ covalency, as corroborated by the negative shift of the absorption edge position in the normalized Ru K-edge X-ray absorption near-edge structure (XANES) spectra for $\\operatorname{Li}_{x}$ - $\\mathrm{RuO}_{2}$ relative to that of ${\\mathrm{RuO}}_{2}$ (Fig. 4a)17,19,53. Figure 3b reveals that the bond length of $\\mathrm{Ru-O}$ was slightly increased with the increase in lithium concentration. The evolution of the interatomic distances is consistent with the DFT calculations and indicates the languishing interaction of $\\mathrm{Ru}{-}\\mathrm{O}^{53}$ , which may suppress the oxidation of lattice oxygen in OER17,19,44,49,17,19,48,54. From the O K-edge soft XAS (sXAS) as shown in Fig. 4b, the two peaks $\\mathbf{A}_{1}$ and $\\mathbf{A}_{2}$ represent the excitations of the $\\mathrm{~O~l~}s$ core electrons into hybridized states of O $2p-\\mathrm{Ru}4d t_{2g}$ and O $2p-\\ensuremath{\\mathrm{Ru}}4d e_{g}$ states55. The $\\mathbf{A}_{1}$ and $\\mathbf{A}_{2}$ peaks were clearly observed moving towards higher energy regions due to lithium intercalation, indicating the lowered covalency of $\\mathrm{{Ru-O}}$ bond56 as well as the reduced $\\mathrm{{Ru^{4}}}$ , which is in good agreement with $\\mathrm{Ru}\\mathrm{K}$ near-edge absorption results and the PDOS analyses (Fig. 3a)55. \n\n![](images/57abbcfcc69858b64cd51a7fff11374d914db7da1cd7f7fa8ac4c7291ca16860.jpg) \nFig. 4 Electronic structure. a Normalized Ru K-edge $\\mathsf{X}$ -ray absorption near-edge structure (XANES) spectra. Inset: the first derivatives of the Ru K-edge XANES spectra of ${\\sf R u O}_{2}$ and $\\mathsf{L i}_{x}\\mathsf{R u O}_{2}$ . b O K-edge soft XAS of $\\mathsf{L i}_{x}\\mathsf{R u O}_{2}$ and ${\\sf R u O}_{2}$ . c Charge density distribution at the (110) crystal plane of ${\\mathsf{L i}}_{x}{\\mathsf{R u O}}_{2},$ with $n=0$ (left) and 16 (right). d Ru and Li Bader charge. \n\nFigure $\\mathtt{4c}$ shows the charge density distribution at the (110) crystal plane of ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ with $x=0$ and 0.5, respectively. The Bader charges of $\\mathtt{R u}$ and Li are positive, indicating that the lithium atoms are electron donors (Fig. 4d). The donated electrons of a lithium atom increase slightly when increasing lithium concentration, while the donated electrons of Ru decrease gradually, indicating the decrease of the valence state of Ru cations. The donation of electron from Li to $\\mathrm{~o~}$ indicates the formation of Li–O bond, and the bond strength is expected to be strengthened with the increase of lithium concentration. Therefore, the strong interaction in these Ru–O–Li local structure (Supplementary Fig. 17) may further suppress the lattice oxygen involvement during OER, thus improving the stability of the $\\mathrm{Li}_{x}\\mathrm{RuO}_{2}{^{48}}$ . Overall, on one hand, the lithium intercalation decreases the valence state of $\\begin{array}{r}{\\mathrm{{Ru},}}\\end{array}$ which enhances the resistance of $\\mathtt{R u}$ to dissolution in acidic solution. On the other hand, the lithium intercalation decreases the covalency of $\\mathrm{{Ru-O}}$ bond and forms Ru–O–Li local structure, which suppresses the participation of lattice oxygen during OER. \n\nIn summary, the OER performance of $\\mathrm{RuO}_{2}$ was significantly improved by lithium intercalation, and reaches the best when the nominal lithium concentration $x$ is 0.52 in ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ solid solution phase. In particular, the $\\mathrm{Li}_{0.52}\\mathrm{RuO}_{2}$ possesses an ultralow overpotential of $156\\mathrm{mV}$ for delivering a current density of $10\\operatorname{mA}{\\mathrm{cm}^{-2}}$ in 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ , with greatly enhanced durability. The excellent OER performance of ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ is attributed to the dual function of lithium intercalation, i.e., modification of the electronic structure and tuning of the inherent lattice strain of $\\mathrm{RuO}_{2}$ . The lithium donates electrons so that the valence state of Ru decreases, and interaction of Li–O increases. Meanwhile, the Ru−O $4d-2p$ hybridization is weakened and the $\\mathrm{{Ru-O}}$ covalency is decreased. Therefore, the participation of lattice oxygen and dissolution of $\\mathtt{R u}$ is suppressed during OER, enhancing the stability. On the other hand, the lithium intercalation modulates the $e_{g}$ occupancy of Ru $d$ -band electrons to be closer to unity. Further, the inherent lattice strain results in the surface structural distortion, which activates the dangling O atom near the $\\mathtt{R u}$ active site as the proton acceptor, achieving stabilized ${\\mathrm{OOH}}^{*}$ and dramatically improved OER activity. This work proposes a creative strategy to simultaneously tune the electronic structure and lattice strain to design highly active and stable acidic OER catalysts for potential practical applications. \n\n# Methods \n\nSample preparation. ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ was prepared by electrochemical lithium intercalation. First, a working electrode was prepared by mixing $\\mathrm{RuO}_{2}$ carbon nanotubes (CNT), and PVDF (polyvinylidene fluoride) homogenously in n-methylpyrrolidone (NMP) with a weight ratio of 8:1:1, followed by coating the slurry on Cu foil and drying in an oven at $110^{\\circ}\\mathrm{C}$ for $^{12\\mathrm{h}}$ . The working electrode was used to assemble CR2032 coin cells with lithium foil as the counter-electrode and $1\\mathrm{M}$ solution of $\\mathrm{LiPF}_{6}$ in a mixture of ethylene carbonate (EC) and diethyl carbonate (DEC) $(1{:}1=\\mathrm{v}/\\mathrm{v})$ as the electrolyte, in an argon-filled glovebox. The lithium intercalation into $\\mathrm{RuO}_{2}$ was achieved by discharging the cell at a constant current density of $0.05\\mathrm{C}$ $(1~{\\mathrm{C}}=201.03~\\mathrm{mA}~\\mathrm{g}^{-1})$ ), while the content of lithium intercalated was controlled by the discharge time. After discharge, the cell was disassembled and the $\\mathrm{RuO}_{2}$ working electrode was washed using NMP several times to remove the PVDF and electrolyte, followed by drying at $60^{\\circ}\\mathrm{{C}}$ to obtain ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ powders. \n\nCharacterization. TEM images were collected on a JEOL JEM-1230 transmission electron microscope working at an operating voltage of $100\\mathrm{kV}$ . HAADF-STEM photographs were collected on FEI Titan Themis Cube G2 high-resolution transmission electron microscope with $300\\mathrm{kV}$ accelerating voltage. SEM images were recorded by Hitachi SU8230 microscope with $2\\mathrm{kV}$ operating voltage. Ex situ XRD patterns of the powder samples of ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ were measured on a Rigaku D/Max $2500~\\mathrm{VB}2+/\\mathrm{PC}$ X-ray powder diffractometer by using $\\mathrm{Cu}~\\mathrm{K}_{\\mathrm{a}}$ radiation $(\\lambda=0.154\\mathrm{nm})$ ). Operando XRD measurements were performed on the same diffractometer using a self-designed in situ cell whose discharge-charge cycle was controlled by an electrochemical workstation. XPS measurements were executed at Thermo Scientific ESCALAB 250X with Al light source, and all binding energies were calibrated to the peak of C 1 s lied in $284.8\\:\\mathrm{eV}.$ XAS spectra at the K-edge of Ru were collected in transmission mode at beamline BL14W1 of 18KeV synchrotron radiation source at the SSRF, China. Soft XAS spectra of O K-edge were executed at beamline station BL12B in National Synchrotron Radiation Laboratory (NSRL), China, operated at $800\\mathrm{MeV}$ with a maximum current of $300\\mathrm{mA}$ . Neutron powder diffraction measurements were performed on the general-purpose powder diffractometer (GPPD) at the China Spallation Neutron Source (CSNS) in China. \n\nElectrochemical measurements. Electrochemical measurements of $\\mathrm{RuO}_{2}$ and $\\operatorname{Li}_{x}.$ $\\mathrm{RuO}_{2}$ were performed in $0.5\\mathrm{M}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte with a standard three-electrode configuration controlled by an electrochemical workstation at room temperature. Oxygen gas was injected in the 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ electrolyte for $10\\mathrm{min}$ to ensure that the electrolyte is saturated with oxygen before electrochemical measurements. A catalystcoated glassy carbon (GC) electrode (Diameter: $5\\mathrm{mm}$ ), $\\mathrm{\\Ag/AgCl}$ electrode, and carbon rod were used as the working, reference and counter electrodes, respectively. In a typical scenario, $4\\mathrm{mg}$ of ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ powder was added to a mixed solution containing $200\\upmu\\mathrm{L}$ ethanol and $200\\upmu\\mathrm{L}$ Nafion aqueous solution $5\\ \\mathrm{vol.\\%}$ , ethanol as solvent), and dispersed by ultrasonication for $15\\mathrm{min}$ to form a homogeneous black ink. The electrodes of ${\\mathrm{Li}}_{x}{\\mathrm{RuO}}_{2}$ were prepared by scribbling the ink on the GC electrode. The mass loading of Ru on each electrode is the same $\\sim0.637\\mathrm{mg}\\mathrm{cm}^{-2}$ for all the samples. Linear sweep voltammetry (LSV) curves were conducted with a typical voltage range of $1.0{-}1.6\\mathrm{V}$ vs. RHE and a scan rate of $10\\mathrm{mV/s}$ . iR-compensation was not performed. Chronopotentiometric measurements were performed on a constant current of $10\\mathrm{mA}\\mathrm{cm}{\\bar{-}}2$ . Cyclic voltammetry (CV) measurements were conducted in the non-Faradaic region with different scan rates (5, 10, 20, 30, 40, and $50\\mathrm{mVs^{-1}}$ ). The electrochemically active surface areas (ECSA) were estimated from the electrochemical double-layer capacitance $(C_{\\mathrm{DL}})$ of the catalytic surface. The $C_{\\mathrm{DL}}$ was determined by plotting the ΔJ/2 $(\\varDelta J=J_{a}-J_{c},$ where $J_{a}$ is the anodic current and $J_{c}$ is the cathodic current at the middle voltage) against the scan rate, where the slope is equal to $C_{\\mathrm{DL}}$ . The specific capacitance $C_{s}\\dot{=}0.0\\dot{3}5\\mathrm{mF}\\mathrm{cm}^{-2}$ is used, and the ECSA is calculated according to $\\mathrm{ECSA}=C_{\\mathrm{DL}}/C_{\\mathrm{s}}$ \n\nDFT calculations. The DFT calculations were performed using the Vienna ab initio Simulation Package (VASP)57,58. Perdew, Burke, and Ernzerhof (PBE) functional of generalized gradient approximation $(\\mathrm{GGA})^{59}$ with projector augmented wave $\\mathsf{\\bar{(P A W)}}^{60}$ was applied to describe the electronic structures of materials. The plane-wave-basis kinetic energy cutoff was set to $450\\mathrm{eV}$ . For the calculation of Li insertion, The Brillouin zones are sampled using Gamma-centered $k$ -mesh of $5\\times5\\times5$ . For the calculations of the OER process, Van der Waals interaction is considered using the zero damping D3 method. The vacuum layers are set to ${\\sim}15\\mathrm{\\AA}$ to decouple the interaction between periodic images. The Brillouin zones are sampled using Gamma-centered $k$ -mesh of $3\\times3\\times1$ . The slab models are built with $2\\times4\\times2$ supercell and two bottom layers are fixed in the geometry optimization. The rest atomic layers and adsorbates are free to relax until the net force per atom is less than $0.02\\dot{\\mathrm{eV}}/\\mathring{\\mathrm{A}}$ . The gas-phase $\\mathrm{H}_{2}$ and $\\mathrm{H}_{2}\\mathrm{O}$ molecules are optimized in a box of dimensions $15\\times15\\times\\mathbf{\\bar{15}}\\mathbf{\\bar{A}}$ with Gamma point sampling of the Brillouin zone. The adsorption energy $(E_{\\mathrm{ad}})$ is calculated by \n\n$$\nE_{\\mathrm{ad}}=E_{\\mathrm{total}}-E_{\\mathrm{slab}}-E_{\\mathrm{adsorbate}},\n$$ \n\nwhere $E_{\\mathrm{total}}$ refers to the total energy of the optimized structure with the adsorbates absorbed on the slab surface, $E_{\\mathrm{slab}}$ refers to the energy of the clean slab, and $E_{\\mathrm{adsorbate}}$ refers to the energy of the adsorbate $\\mathrm{\\langleO^{*}}$ , $\\mathrm{OH^{*}}$ , and $\\scriptstyle{\\mathrm{OOH}}^{*}$ ) in vacuum. \n\n# Data availability \n\nThe data that support the findings of this study are available within the article and its Supplementary Information files. All other relevant data supporting the findings of this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper. \n\nReceived: 20 November 2021; Accepted: 17 June 2022; Published online: 01 July 2022 \n\nReferences \n1. Seh, Z. W. et al. Combining theory and experiment in electrocatalysis: insights into materials design. Science 355, 146 (2017). \n2. Zheng, Y. et al. High electrocatalytic hydrogen evolution activity of an anomalous ruthenium catalyst. J. Am. Chem. Soc. 138, 16174–16181 (2016). \n3. Jiao, Y., Zheng, Y., Jaroniec, M. & Qiao, S. Z. Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions. Chem. Soc. Rev. 44, 2060–2086 (2015). \n4. Wang, J. et al. Redirecting dynamic surface restructuring of a layered transition metal oxide catalyst for superior water oxidation. Nat. Catal. 4, 212–222 (2021). \n5. Frydendal, R. et al. Benchmarking the stability of oxygen evolution reaction catalysts: the importance of monitoring mass losses. ChemElectroChem 1, 2075–2081 (2014). \n6. Reier, T., Nong, H. N., Teschner, D., Schlögl, R. & Strasser, P. Electrocatalytic oxygen evolution reaction in acidic environments—reaction mechanisms and catalysts. Adv. Energy Mater. 7, 1601275 (2017). \n7. Sardar, K. et al. Water-splitting electrocatalysis in acid conditions using ruthenate-iridate pyrochlores. Angew. Chem. Int. Ed. 53, 10960–10964 (2014). \n8. Feng, Q. et al. A review of proton exchange membrane water electrolysis on degradation mechanisms and mitigation strategies. J. Power Sources 366, 33–55 (2017). \n9. Spöri, C., Kwan, J. T. H., Bonakdarpour, A., Wilkinson, D. P. & Strasser, P. The stability challenges of oxygen evolving catalysts: towards a common fundamental understanding and mitigation of catalyst degradation. Angew. Chem. Int. Ed. 56, 5994–6021 (2017). \n10. Wang, Q. et al. Ultrahigh-loading of Ir single atoms on NiO matrix to dramatically enhance oxygen evolution reaction. J. Am. Chem. Soc. 142, 7425–7433 (2020). \n11. Oh, A. et al. Topotactic transformations in an icosahedral nanocrystal to form efficient water-splitting catalysts. Adv. Mater. 31, 1805546 (2019). \n12. Kim, J. S., Kim, B., Kim, H. & Kang, K. Recent progress on multimetal oxide catalysts for the oxygen evolution reaction. Adv. Energy Mater. 8, 1702774 (2018). \n13. Over, H. Surface chemistry of ruthenium dioxide in heterogeneous catalysis and electrocatalysis: from fundamental to applied research. Chem. Rev. 112, 3356–3426 (2012). \n14. Su, J. et al. Assembling ultrasmall copper-doped ruthenium oxide nanocrystals into hollow porous polyhedra: highly robust electrocatalysts for oxygen evolution in acidic media. Adv. Mater. 30, 1801351 (2018). \n15. Geiger, S. et al. The stability number as a metric for electrocatalyst stability benchmarking. Nat. Catal. 1, 508–515 (2018). \n16. Lin, Y. et al. Chromium-ruthenium oxide solid solution electrocatalyst for highly efficient oxygen evolution reaction in acidic media. Nat. Commun. 10, 162 (2019). \n17. Chen, S. et al. Mn-doped ${\\mathrm{RuO}}_{2}$ nanocrystals as highly active electrocatalysts for enhanced oxygen evolution in acidic media. ACS Catal. 10, 1152–1160 (2020). \n18. Burnett, D. L. et al. $(\\mathrm{M},\\mathrm{Ru})\\mathrm{O}_{2}$ $\\mathbf{\\dot{M}}=\\mathbf{M}\\mathbf{g} $ $Z\\mathrm{n}$ , Cu, Ni, Co) rutiles and their use as oxygen evolution electrocatalysts in membrane electrode assemblies under acidic conditions. Chem. Mater. 32, 6150–6160 (2020). \n19. Kim, J. et al. A porous pyrochlore $\\mathrm{Y}_{2}[\\mathrm{Ru}_{1.6}\\mathrm{Y}_{0.4}]\\mathrm{O}_{7-\\delta}$ electrocatalyst for enhanced performance towards the oxygen evolution reaction in acidic media. Angew. Chem. Int. Ed. 57, 13877–13881 (2018). \n20. Bayatsarmadi, B., Zheng, Y., Tang, Y., Jaroniec, M. & Qiao, S.-Z. Significant enhancement of water splitting activity of N-carbon electrocatalyst by trace level Co doping. Small 12, 3703–3711 (2016). \n21. Onuchukwu, A. I. & Trasatti, S. Effect of substitution of $\\mathrm{SnO}_{2}$ for $\\mathrm{TiO}_{2}$ on the surface and electrocatalytic properties of $\\mathrm{RuO}_{2}{+}\\mathrm{TiO}_{2}$ electrodes. J. Appl. Electrochem. 21, 858–862 (1991). \n22. Wu, X., Tayal, J., Basu, S. & Scott, K. Nano-crystalline $\\mathrm{Ru_{x}S n_{1-x}O_{2}}$ powder catalysts for oxygen evolution reaction in proton exchange membrane water electrolysers. Int. J. Hydrog. Energy 36, 14796–14804 (2011). \n23. Hao, S. et al. Dopants fixation of Ruthenium for boosting acidic oxygen evolution stability and activity. Nat. Commun. 11, 5368 (2020). \n24. Feng, J. et al. Iridium-based multimetallic porous hollow nanocrystals for efficient overall-water-splitting catalysis. Adv. Mater. 29, 1703798 (2017). \n25. Tian, Y. et al. A Co-doped nanorod-like $\\mathrm{RuO}_{2}$ electrocatalyst with abundant oxygen vacancies for acidic water oxidation. iScience 23, 100756 (2020). \n26. Jang, H. et al. Exploring the artificially induced nonstoichiometric effect of ${\\mathrm{Li}}_{2}{\\mathrm{RuO}}_{3}$ as a reactive promoter on electrocatalytic behavior. Energy Environ. Sci. 13, 2167–2177 (2020). \n27. Wang, H. et al. Electrochemical tuning of $\\ensuremath{\\mathrm{MoS}}_{2}$ nanoparticles on threedimensional substrate for efficient hydrogen evolution. ACS Nano 8, 4940–4947 (2014). \n28. Wang, H. et al. Electrochemical tuning of vertically aligned $\\ensuremath{\\mathbf{MoS}}_{2}$ nanofilms and its application in improving hydrogen evolution reaction. Proc. Natl Acad. Sci. USA 110, 19701 (2013). \n29. Lukowski, M. A. et al. Enhanced hydrogen evolution catalysis from chemically exfoliated metallic $\\ensuremath{\\mathbf{MoS}}_{2}$ nanosheets. J. Am. Chem. Soc. 135, 10274–10277 (2013). \n30. Lee, S. W. et al. The nature of lithium battery materials under oxygen evolution reaction conditions. J. Am. Chem. Soc. 134, 16959–16962 (2012). \n31. Sood, A. et al. Electrochemical ion insertion from the atomic to the device scale. Nat. Rev. Mate 6, 847–867 (2021). \n32. Kim, Y. et al. Enhancement of the interfacial reaction on mesoporous $\\mathrm{RuO}_{2}$ for next generation Li batteries. J. Power Sources 396, 749–753 (2018). \n33. Peng, C. et al. Lithiation-enabled high-density nitrogen vacancies electrocatalyze $\\mathrm{CO}_{2}$ to $\\mathbf{C}_{2}$ products. Adv. Mater. 33, 2103150 (2021). \n34. Yan, S. et al. Electron localization and lattice strain induced by surface lithium doping enable ampere-level electrosynthesis of formate from $\\mathrm{CO}_{2}$ . Angew. Chem. Int. Ed. 60, 25741–25745 (2021). \n35. Balaya, P., Li, H., Kienle, L. & Maier, J. Fully reversible homogeneous and heterogeneous Li storage in $\\mathrm{RuO}_{2}$ with high capacity. Adv. Funct. Mater. 13, 621–625 (2003). \n36. Xu, L. & Thompson, C. V. Mechanisms of the cyclic (de)lithiation of ${\\mathrm{RuO}}_{2}$ . J. Mater. Chem. A 8, 21872–21881 (2020). \n37. Jirkovsky, J., Makarova, M. & Krtil, P. The effect of coherent domain size on the insertion activity of nanocrystalline $\\mathrm{RuO}_{2}$ . J. Electrochem. Soc. 152, A1613–A1619 (2005). \n38. Hassan, A. S., Navulla, A., Meda, L., Ramachandran, B. R. & Wick, C. D. Molecular mechanisms for the lithiation of ruthenium oxide nanoplates as lithium-ion battery anode materials: an experimentally motivated computational study. J. Phys. Chem. C. 119, 9705–9713 (2015). \n39. Ze-Jin, Y. et al. Electronic structure and optical properties of rutile $\\mathrm{RuO}_{2}$ from first principles. Chin. Phys. B 19, 077102 (2010). \n40. Miao, X. B. et al. Quadruple perovskite ruthenate as a highly efficient catalyst for acidic water oxidation. Nat. Commun. 10, 3809 (2019). \n41. Wang, J. et al. Transition metal-doped ultrathin $\\mathrm{RuO}_{2}$ networked nanowires for efficient overall water splitting across a broad $\\mathrm{\\pH}$ range. J. Mater. Chem. A 7, 6411–6416 (2019). \n42. Wang, Z. et al. In-situ surface decoration of $\\mathrm{RuO}_{2}$ nanoparticles by laser ablation for improved oxygen evolution reaction activity in both acid and alkali solutions. J. Energy Chem. 54, 510–518 (2021). \n43. Yao, Q. et al. A chemical etching strategy to improve and stabilize $\\mathrm{RuO}_{2}$ -based nanoassemblies for acidic oxygen evolution. Nano Energy 84, 105909 (2021). \n44. Song, J. et al. A review on fundamentals for designing oxygen evolution electrocatalysts. Chem. Soc. Rev. 49, 2196–2214 (2020). \n45. Yan, L. et al. Nickel metal–organic framework implanted on graphene and incubated to be ultrasmall nickel phosphide nanocrystals acts as a highly efficient water splitting electrocatalyst. J. Mater. Chem. A 6, 1682–1691 (2018). \n46. Doyle, R. L., Godwin, I. J., Brandon, M. P. & Lyons, M. E. G. Redox and electrochemical water splitting catalytic properties of hydrated metal oxide modified electrodes. Phys. Chem. Chem. Phys. 15, 13737–13783 (2013). \n47. Zhang, L. et al. Sodium-decorated amorphous/crystalline ${\\mathrm{RuO}}_{2}$ with rich oxygen vacancies: a robust pH-universal oxygen evolution electrocatalyst. Angew. Chem. Int. Ed. 60, 18821–18829 (2021). \n48. Wen, Y. et al. Stabilizing highly active Ru sites by suppressing lattice oxygen participation in acidic water oxidation. J. Am. Chem. Soc. 143, 6482–6490 (2021). \n49. Hwang, J. et al. Perovskites in catalysis and electrocatalysis. Science 358, 751–756 (2017). \n50. Hong, W. T. et al. Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis. Energy Environ. Sci. 8, 1404–1427 (2015). \n51. Govindarajan, N., Garcia-Lastra, J. M., Meijer, E. J. & Calle-Vallejo, F. Does the breaking of adsorption-energy scaling relations guarantee enhanced electrocatalysis? Curr. Opin. Electroche 8, 110–117 (2018). \n52. Sun, H. & Jung, W. Recent advances in doped ruthenium oxides as highefficiency electrocatalysts for the oxygen evolution reaction. J. Mater. Chem. A 9, 15506–15521 (2021). \n53. Chen, I. L. et al. Local structure distortion induced by Ti dopants boosting the pseudocapacitance of ${\\mathrm{RuO}}_{2}$ -based supercapacitors. Nanoscale 7, 15450–15461 (2015). \n54. Kim, J. et al. High-performance pyrochlore-type yttrium ruthenate electrocatalyst for oxygen evolution reaction in acidic media. J. Am. Chem. Soc. 139, 12076–12083 (2017). \n55. Tsai, H. M. et al. Comparison of electronic structures of $\\mathrm{RuO}_{2}$ and $\\mathrm{IrO}_{2}$ nanorods investigated by X-ray absorption and scanning photoelectron microscopy. Appl. Phys. Lett. 90, 042108 (2007). \n56. Huang, Z.-F. et al. Tuning of lattice oxygen reactivity and scaling relation to construct better oxygen evolution electrocatalyst. Nat. Commun. 12, 3992 (2021). \n57. Kresse, G. & Furthmuller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comp. Mater. Sci. 6, 15–50 (1996). \n58. Kresse, G. & Furthmuller, J. Efficient iterative schemes for ab initio totalenergy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996). \n59. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). \n60. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999). \n\n# Acknowledgements \n\nThis work was supported by research grants from the Guangdong Basic and Applied Basic Research Foundation (No. 2020A1515110798, No. 2022A1515012349), and Shenzhen Science and Technology Program (Grant No. RCBS20200714114920129). K.K.L. acknowledges the support by the Harbin Institute of Technology, Shenzhen. The authors thank the support from the general-purpose powder diffractometer (GPPD) at the China Spallation Neutron Source. \n\n# Author contributions \n\nT.-Y.Z. and K.L. managed the project and conceived the storyline of the paper. T.-Y.Z., K.L., X.-Y.Z., and H.-J.Q. guided the research. T.Y. performed the catalytic performance measurements, S.D. and L.H. conducted the NPD measurements and analyses, and Y.Q. conducted all the other experiments. D.L. participated in the in situ XRD measurements. Q.Z. performed the fitting of the XRD patterns using machine learning. Z.J. and D.Z. participated in the experiments. Y.-B.H., L.H., and F.K. contributed to the discussions of the project. X.-Y.Z. carried out the first-principles calculations and data analysis. H.-J.Q. managed the catalytic performance tests and analysis. K.L., T.-Y.Z., Y.Q., X.-Y.Z., and H.-J.Q. wrote the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-31468-0. \n\nCorrespondence and requests for materials should be addressed to Xiao-Ye Zhou, HuaJun Qiu, Kaikai Li or Tong-Yi Zhang. \n\nPeer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1126_science.abo4940", + "DOI": "10.1126/science.abo4940", + "DOI Link": "http://dx.doi.org/10.1126/science.abo4940", + "Relative Dir Path": "mds/10.1126_science.abo4940", + "Article Title": "Machine learning-enabled high-entropy alloy discovery", + "Authors": "Rao, ZY; Tung, PY; Xie, RW; Wei, Y; Zhang, HB; Ferrari, A; Klaver, TPC; Körmann, F; Sukumar, PT; da Silva, AK; Chen, Y; Li, ZM; Ponge, D; Neugebauer, J; Gutfleisch, O; Bauer, S; Raabe, D", + "Source Title": "SCIENCE", + "Abstract": "High-entropy alloys are solid solutions of multiple principal elements that are capable of reaching composition and property regimes inaccessible for dilute materials. Discovering those with valuable properties, however, too often relies on serendipity, because thermodynamic alloy design rules alone often fail in high-dimensional composition spaces. We propose an active learning strategy to accelerate the design of high-entropy Invar alloys in a practically infinite compositional space based on very sparse data. Our approach works as a closed-loop, integrating machine learning with density-functional theory, thermodynamic calculations, and experiments. After processing and characterizing 17 new alloys out of millions of possible compositions, we identified two high-entropy Invar alloys with extremely low thermal expansion coefficients around 2 x 10-6 per degree kelvin at 300 kelvin. We believe this to be a suitable pathway for the fast and automated discovery of high-entropy alloys with optimal thermal, magnetic, and electrical properties.", + "Times Cited, WoS Core": 308, + "Times Cited, All Databases": 322, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000909870100058", + "Markdown": "# METALLURGY \n\n# Machine learning–enabled high-entropy alloy discovery \n\nZiyuan Rao1, Po-Yen Tung1,2, Ruiwen $\\tt X i e^{3}$ , Ye Wei1\\*, Hongbin Zhang3, Alberto Ferrari4, T.P.C. Klaver4, Fritz Körmann1,4, Prithiv Thoudden Sukumar1, Alisson Kwiatkowski da Silva1, Yao Chen1,5, Zhiming $L i^{2,6}$ , Dirk Ponge1, Jörg Neugebauer1, Oliver Gutfleisch1,3, Stefan Bauer7, Dierk Raabe1\\* \n\nHigh-entropy alloys are solid solutions of multiple principal elements that are capable of reaching composition and property regimes inaccessible for dilute materials. Discovering those with valuable properties, however, too often relies on serendipity, because thermodynamic alloy design rules alone often fail in high-dimensional composition spaces. We propose an active learning strategy to accelerate the design of high-entropy Invar alloys in a practically infinite compositional space based on very sparse data. Our approach works as a closed-loop, integrating machine learning with density-functional theory, thermodynamic calculations, and experiments. After processing and characterizing 17 new alloys out of millions of possible compositions, we identified two high-entropy Invar alloys with extremely low thermal expansion coefficients around $2\\times10^{-6}$ per degree kelvin at 300 kelvin. We believe this to be a suitable pathway for the fast and automated discovery of high-entropy alloys with optimal thermal, magnetic, and electrical properties. \n\nlloy design refers to a knowledge-guided approach to the development of highperformance materials. The strategy was established in the Bronze Age and has n undergone further developments since that time. Alloy design is the basis for the development of different materials that enable technological progress. Several thousand metallic alloys have been developed so far that serve in engineering applications. The first essential alloy groups developed, such as bronze and steel, are all based on one main element that forms the matrix of the material. Over time, alloys with a higher number of alloying elements in larger fractions, such as austenitic stainless steels, have been developed. Today, with the development of highentropy alloys (HEAs), we have reached a stage where multiple elements are used in similar fractions $(\\boldsymbol{I},\\boldsymbol{2})$ . Considering only the most used elements of the periodic table, this spans a composition space of at least ${\\mathrm{10}}^{50}$ alloy variants, a space so large that it cannot be managed by conventional alloy design methods (3). These conventional methods for designing alloys, which have been applied to small subspaces of the HEA composition realm, include calculation of phase diagrams (CALPHAD) and density-functional theory (DFT) (4–6). However, CALPHAD provides equilibrium-phase diag \n\nrams only, and DFT is computationally costly and cannot be readily applied to higher temperatures and disordered alloys (5, 7). Likewise, combinatorial experiments (8) are very labor intensive and only cover the limited composition space of HEAs. \n\nBecause of these methodological limitations to finding materials with promising functional and mechanical features, we present a different approach to accelerating the discovery of HEAs. We based our approach on the use of machine learning (ML) techniques, with a focus on probabilistic models and artificial neural networks. Limited by the amount of available composition-property data, conventional ML approaches in alloy design have to predominantly rely on simulation data, often with only limited experimental validation (9, 10). As the experimental microstructure database continues to expand, ML obtains higher accuracy in predicting the phase or microstructure of materials $(I I)$ . However, the direct composition-property prediction is still elusive because of the comparably small databases and the human bias in feature selection. Recently, active learning has emerged as an alternative choice for functional materials discovery $(I2)$ . Active learning is a subfield of ML in which surrogate models iteratively select unseen data points that are most informative to improve the predictive power of the models (13). In this approach, the next set of experiments is guided by the previous model trained based upon the results seen so far, yielding data points that will again be used iteratively for updating the model. Active learning has the potential to reduce the computational costs of alloy design and to both incorporate and guide experimental data and routines. However, active learning approaches to guiding the experimental discovery of materials have relied on simple surrogate models and Bayesian optimization methods, which are limited to low-dimensional data, thus showing property improvements only after many iterations (14, 15). \n\nTo overcome these obstacles, we propose an active learning framework for the composition discovery of HEAs that is efficient for very sparse experimental datasets. The approach comprises ML-based techniques, DFT, meanfield thermodynamic calculations, and experiments. We focused on the design of high-entropy Invar alloys with a low thermal expansion coefficient (TEC) for several reasons: (i) a high demand exists for different types of Invar alloys to serve emerging markets for the transport of liquid hydrogen, ammonia, and natural gas; (ii) the mechanical properties of the original $\\mathrm{Fe}_{63.5}\\mathrm{Ni}_{36.5}$ (wt $\\%$ ) alloy for which Charles Edouard Guillaume received the 1920 physics Nobel Prize leave room for improvement; (iii) alternative Invar alloys (e.g., intermetallic, amorphous, or antiferromagnetic Invar compounds) come at forbiddingly high alloy costs and/or poor ductility $(I6,I7)$ ; (iv) although a few HEAs have the potential to fill this gap (18–20), the lowest TEC $(\\sim10\\times10^{-6}~\\mathrm{K}^{-1})$ of HEAs reported in the literature exceeds the value of the original $\\mathrm{Fe}_{63.5}\\mathrm{Ni}_{36.5}$ (wt $\\%$ ) alloy $({\\sim}1.6\\times10^{-6}\\mathrm{K^{-1}})$ $(I9)$ ; and (v) our active learning framework mainly considers compositional information instead of the alloy manufacturing process, which makes the Invar effect an ideal target because these alloys are mostly determined by composition and less by processing (6, 19) (see fig. S1 and table S1 for more background). \n\n# Results and discussion Generative alloy design \n\nThe active learning framework includes three main steps: targeted composition generation, physics-informed screening, and experimental feedback (Fig. 1). Considering the large number of possible composition combinations of HEAs and the small experimental datasets (699 compositions; fig. S2), the challenge is to directly sample new compositions with the desired properties. Therefore, we developed an HEA generative alloy design (HEA-GAD) approach that is based on a generative model (GM) (21). First, the HEA-GAD uses GM, mathematical modeling, and sampling to perform a large-scale search of potential Invar alloys. GM learns an efficient and effective representation of the high-dimension data, which not only provides direct data visual representation, but also converts the search in highdimensional design spaces to those of lower dimensionality (22). Different GMs are compared and analyzed on the basis of the evaluation metrics. The results show that the Wasserstein autoencoder (WAE) architecture performs better than other models with similar architectures (21) (figs. S3 and S4). The encoder takes the selected candidates from the HEA-GAD are further processed by the TERM framework, which includes two ensemble models composed of multilayer perceptrons and gradient-boosting decision trees. In the last step, the most promising compositions are selected by a ranking-based policy. The top three candidates are experimentally measured and fed back to the database. The iteration is repeated until the discovery of Invar alloys. \n\n![](images/07ddaf79710d3c3c04206f435c662496d7b4b461edce6fd09105066979370812.jpg) \nFig. 1. Approach overview. We developed an active learning framework for the targeted composition design and discovery of HEAs, which combines ML models, DFT calculations, thermodynamic simulations, and experimental feedback. First, the promising candidates are generated under the HEA-GAD framework consisting of two primary steps: (i) an autoencoder for composition generation and (ii) stochastic sampling for composition selection. Second, \n\ncompositions of alloys as the input and learns to compress them down to low-dimensional representations, and the decoder can then act as a generator for producing alloy compositions given the learned continuous latent $z$ representation. Although WAE is trained with only compositional information of alloys, it may implicitly include information on compositionrelated properties, which makes the latent space physically meaningful and informative. In our case, Invar alloys show extremely low TEC (hereafter used to refer to the TEC around room temperature unless otherwise specified) values, and the composition-TEC relation obeys specific physical laws. Subsequently, HEA-GAD uses the Gaussian mixture model (GMM) and Markov chain Monte Carlo (MCMC) sampling (23, 24) to perform a large-scale search for the Invar compositions generated from WAE latent representation. \n\n# Two-stage ensemble regression \n\nNext, we use the two-stage ensemble regression model (TERM) to further investigate the TEC of the HEA-GAD–generated alloy compositions. The first stage concerns compositionbased regression models aiming at fast and large-scale composition inference. Then, the top ${\\sim}1000$ results with potentially low TEC from the HEA-GAD model are screened and enter the second-stage model, where DFT and thermodynamic calculations are included as part of the input, making it a physics-informed model (table S4). In the following section, we demonstrate that incorporating the physical inputs does increase the model accuracy. To increase the robustness of TERM without sacrificing the prediction accuracy, TERM taps into the advantages of the multilayer perceptron (25–27) and gradient-boosting decision tree approaches (28–30) by combining both into a single ensemble (31). Based on prediction and uncertainty, the exploration and exploitation strategy is used to adaptively guide the discovery of desirable compositions (31). Exploration prefers the composition with higher uncertainty (curiosity), whereas exploitation favors the composition with lower predicted TEC (perceived usefulness). Such a baseline strategy is premised on the model’s ability to generalize beyond the known data, which is, however, often hampered by the highly nonlinear nature of the composition-property relation and sparsity of the available dataset. To overcome this issue, we designed a rankorder strategy that allows predictions to be rearranged and ranked in a specific order (32, 33). This strategy is particularly advantageous when the underlying distribution of the data is largely unknown. The rank-based strategy ensures that the candidate selection is less affected by model inaccuracy and provides a systematic way to combine model prediction and uncertainty (31). Finally, the TEC values of the top three selected candidate materials are experimentally determined by the physical properties measurement system. These experimental results then augment the training database for the next active learning iteration. \n\n# Compositional latent space distribution \n\nWe produced a large benchmark dataset with 699 data points of Invar alloys mainly from former publications (fig. S2 and table S3) (34–39). Then, on the basis of the HEA-GAD-TERM framework proposed above, we performed six iterations and cast 18 alloys including 17 new alloys and one $\\mathrm{Fe}_{63.5}\\mathrm{Ni}_{36.5}$ (wt $\\%$ ) classic Invar alloy as a reference alloy. Because of the data imbalance (figs. S5 and S6), the discovery of FeNiCoCrCu HEAs is much more difficult than the discovery of FeNiCoCr HEAs. For this reason, we focused on the design of FeNiCoCr HEAs for the first three iterations and on FeNiCoCrCu HEAs for the last three iterations. We show the WAE latent space and GMMmodeled two-dimensional probability density of the first iteration in Fig. 2, A and B. The latent space yields certain islands that indicate the compositional differences. For example, the HEAs tend to stay in the middle, whereas the binary and ternary alloys tend to stay in the edges of the latent space. Also, a smooth transition among the Fe–Ni, Ni–Co binary alloys and the Fe–Ni–Co ternary alloys can be observed. FeNiCoCrCu forms a single island, indicating that features of compositions with nonzero Cu content are indeed captured by HEA-GAD. The new FeCoNiCr HEAs candidates are cross-marked, whereas the best-ranked HEAs are illustrated with white dots in Fig. 2, A and B. We also show the last iteration result of FeCoNiCrCu HEAs discovered by HEA-GADTERM in Fig. 2, C and D (in red). The entire latent space is slightly rotated because of the addition of new data into the training dataset from previous iterations. The augmented dataset also leads to a modified GMM-modeled probability density shown in Fig. 2D, in which the left Gaussian ellipse extends more to the left region compared with Fig. 2B. Such phenomena suggest that the HEA-GAD-TERM framework is interpretable and sensitive to the dataset. \n\n# Physics-descriptor–informed model \n\nSo far, the Masumoto empirical rule (34, 35) has played an important role in the discovery of several Invar alloys. As exemplified in Fig. 3D for the $\\mathrm{Fe}_{60}\\mathrm{Ni}_{35}\\mathrm{Co}_{5}\\left(\\mathrm{wt}\\%\\right)$ Super Invar alloy, according to this rule, the TEC is related to the ratio $\\omega_{\\mathrm{s}}/T_{\\mathrm{c}}$ (magnetostriction/Curie temperature): Because of the Invar effect, Invar alloys have lower TEC in the ferromagnetic state (below Curie temperature $\\scriptstyle Q,$ ) than in the paramagnetic state (above $\\scriptstyle Q$ ). The TEC in the ferromagnetic state can thus be estimated as \n\n$$\n\\mathrm{TEC}={\\frac{Q S}{R S}}={\\frac{Q A-S A}{T_{\\mathrm{{c}}}}}={\\frac{Q A}{T_{\\mathrm{{c}}}}}-{\\frac{S A}{T_{\\mathrm{{c}}}}}\\approx\\tan8-{\\frac{\\mathrm{{\\omega_{\\mathrm{{s}}}}}}{T_{\\mathrm{{c}}}}}\n$$ \n\nWe demonstrated the correlation between $\\mathrm{{\\omega_{\\mathrm{s}}}/}$ $T_{\\mathrm{c}}$ and the experimental TEC with DFT and \n\nCALPHAD for FeCoNi alloys. The alloys from our experimental dataset were slowly cooled from high-temperature homogenization, so an equilibrium temperature to calculate the phase fractions in our samples cannot be determined unambiguously. We nevertheless calculated ${\\omega_{\\mathrm{s}}}/{T_{\\mathrm{c}}}$ for the annealing temperatures $T_{\\mathrm{ann}}{=}1273\\mathrm{K},107\\mathfrak{s}$ K, and 873 K (Fig. 3, A to C) and observed a good correlation with the experimentally observed TEC values, especially for the values taken at $T_{\\mathrm{ann}}=873\\mathrm{K}$ . $\\mathfrak{\\omega}_{\\mathrm{s}}$ and $T_{\\mathrm{c}}$ are thus useful descriptors that can be exploited to increase the accuracy of TERM. We show the comparison of the model training history with and without the use of the descriptor $T_{\\mathrm{c}}$ (Fig. 3E). This history reflects the performance evolution with time (epoch) as more data were fed to the model. The final testing error was notably reduced from 0.19 to 0.14 upon inclusion of DFT and CALPHAD data, a piece of strong evidence that the physics-descriptor– informed model can achieve better accuracy than that based only on compositions. \n\n# Learning curve and thermal expansion behavior \n\nWe show the measured and predicted TEC values of the 17 alloys experimentally measured (A and B) WAE latent space and GMM-modeled density of the first iteration. (C and D) WAE latent space and GMM-modeled density of the last iteration. The WAE latent space distribution of the different compositions is marked with different symbols. The colors of the data points in the latent space denote their corresponding TEC. The GMM shows the probabilistic density in the latent space. The new candidates proposed by the first stage of the TERM are marked by crosses, and the new compositions proposed by the second stage of the TERM are marked by circles. The learned latent spaces are informative of the TEC of the HEAs. \n\n![](images/fa271dedcb746cf25ede8fd88e98f66ea11dea8605d1aca51f25189ca09ed40b.jpg) \nFig. 2. First and last (sixth) iterations of the HEA-GAD generation. \n\n![](images/231b4fcd937d39b2d558847d534f41d6f70c8a8257a578f507e52fedf7fcf26e.jpg) \nFig. 3. Importance of the physics-informed descriptors. (A to C) Correlation between the proposed descriptor ${\\omega}_{\\mathrm{s}}/T_{\\mathrm{c}}$ and the experimental TEC. (D) Schematic model of the Masumoto empirical rule for discovering Invar alloys. (E) Comparison of training and testing history with and without use of the descriptor ${\\omega_{\\mathrm{s}}}/{T_{\\mathrm{c}}}$ . Both the final training and testing errors decrease after considering the physics-informed descriptors; for example, the testing error decreases from 19 to $14\\%$ . \n\nTable 1. Compositions and TEC of the HEAs designed in this work.\\* \n\n\n
AlloysIterationFe (wt %)Ni (wt %)Co (wt %)Cr (wt %)Cu (wt %)Predicted TEC (×10-6/K)Predicted uncertainty (×10-6/K)Experimental TEC (×10-6/K)
A11st 55.223.916.74.203.411.297.54
A21st 49.217.227.16.503.130.7510.52
A31st41.89.440.9804.390.791.41
A42nd 52.52220.84.7\"03.910.537.97
A52nd4413.834.67.604.200.963.24
A73rd42.412.637.77.304.581.404.09
A83rd44.215.833.26.805.882.174.83
A93rd54.122.817.25.905.161.432.02
B14th406.939.57.95.77.571.455.84
B24th48.817.822.26.255.481.014.38
B44th457616.414.6522654.41.38.54
B55th57.722.98.35.25.94.501.005.31
B65th 6th51.66.827.57.8 7.96.3 5.19.32 5.493.499.68
B76th48.3 5017.8 18.320.9 18.385.45.650.92 1.165.60
B8 B950.719.915.87.95.75.565.13
6th1.056.29
\n\n\\*The original $\\mathsf{F e}_{63.5}\\mathsf{N i}_{36.5}$ Invar (A6) is a reference alloy and is not listed here. \n\nin the six iterations in Table 1. A3 and A9 HEAs with four principal elements show extremely low TECs that are comparable to the classical $\\mathrm{Fe}_{63.5}\\mathrm{Ni}_{36.5}$ (wt $\\%$ ) binary Invar alloy. B2 and B4 HEAs with five principal elements show \n\nTECs that are comparable to the commercially used $\\mathrm{Fe}_{54}\\mathrm{Co}_{17}\\mathrm{Ni}_{29}$ (wt $\\%$ ternary Kovar alloys. In addition, a tabular comparison between HEA-GAD-TERM and trial and error can be found in table S2, where our method shows a fivefold higher discovery rate than that achieved by the trial and error approach alone. \n\nWe illustrate the alloy discovery process in two scenarios (Fig. 4, A and B). In the ideal case, the composition-TEC curve is simple and convex, which means that this specific relation is readily learned and “never forgotten.” Even with a small dataset present, the global maxima can be easily found regardless of their initial starting points: Both path 1 and path 2 can lead to the Invar point. However, in the reality, the lowest TEC curve is highly nonlinear because of the complex underlying composition-property relations, and the composition landscape remains largely unknown. Both experts with appropriate domain knowledge and algorithms will have to explore the unknown territory and accumulate knowledge about the system by making mistakes. Furthermore, the composition axis is multidimensional and therefore the design space is huge. Therefore, the chosen paths, available data, and starting points will notably influence the final results. Path 1 may lead to local minima, whereas path 2 is rather difficult initially, and multiple high TEC nonInvar HEAs can be discovered before the eventual Invar discovery. \n\n![](images/de77aecb5260f12ae9413a1e1b9c01b298aea1b5563920250a9fbdb07b20c3a7.jpg) \nFig. 4. Analysis of the results after six iterations in the active learning loop. (A and B) Representation of the alloy discovery process in the ideal scenario and the real world. (C and D) Cr and Cu distribution histogram. The Cr histogram has various concentrations (from 0 to $20\\%$ ). By contrast, the vast majority $(>95\\%)$ of the compositions have zero Cu concentration. The lowest known TEC as a change of composition is plotted as a solid line, and the unknowns are shown as a dashed line. Gray arrows illustrate the discovery paths of HEA-GAD-TERM. (E) Experimental and predicted TEC of the FeNiCoCr and FeNiCoCrCu HEAs. (F) MAPE of active learning. The dots represent the MAPE \nbetween experiment and predictions. Rapid decrease of the MAPE is akin to a natural learning process. (G and I) Electron backscatter diffraction (EBSD) phase and boundary maps of the A2 alloy. (H and J) EBSD phase and boundary maps of the A3 alloy. (K and L) Change of lattice constants with temperature in the A2 $[(\\mathsf{F e}_{1-\\upeta}^{\\uparrow}\\mathsf{F e}_{\\upeta}^{\\downarrow})_{50.1}(\\mathsf{N i}_{1-\\upeta}^{\\uparrow}\\mathsf{N i}_{\\upeta}^{\\downarrow})_{16.7}(\\mathsf{C o}_{1-\\upeta}^{\\uparrow}\\mathsf{C o}_{\\upeta}^{\\downarrow})_{26.1}(\\mathsf{C r}_{1-\\upeta}^{\\downarrow}\\mathsf{C r}_{\\upeta}^{\\uparrow})_{7.1}]$ and A3 $[(\\mathsf{F e}_{1-\\upeta}^{\\uparrow}\\mathsf{F e}_{\\upeta}^{\\downarrow})_{42.7}(\\mathsf{N i}_{1-\\upeta}^{\\uparrow}\\mathsf{N i}_{\\upeta}^{\\downarrow})_{9.1}(\\mathsf{C o}_{1-\\upeta}^{\\uparrow}\\mathsf{C o}_{\\upeta}^{\\downarrow})_{39.5}(\\mathsf{C r}_{1-\\upeta}^{\\downarrow}\\mathsf{C r}_{\\upeta}^{\\uparrow})_{8.7}]$ alloys for different values of $\\mathfrak{n}$ , where $\\boldsymbol{\\mathfrak{\\upeta}}$ denotes the pseudo-alloy concentration $(0\\leq\\mathfrak{n}\\leq0.50),$ . \n\nWe provide the concentration histogram of Cr and Cu in the current dataset in Fig. 4, C and D. We also plotted the observed lowest TEC curve to illustrate the discovery path in two HEAs. The GAD-TERM framework shows its high efficiency by quickly identifying the Invar points in the first iteration (A3 and B2). However, the algorithm is designed for exploration. The algorithm inevitably discovers some non-Invar alloys along the path (e.g., A4 and A8, denoted by gray arrows in Fig. 4, C and D). As mentioned before, the discovery of FeNiCoCr HEAs and FeNiCoCrCu HEAs are different tasks because of the different data distribution. The distribution of Cu in the alloys is extremely imbalanced (Fig. 4D); that is, by far most of the alloys in the dataset do not contain Cu at all and only a few alloys have $5\\%$ Cu. Such distributional difference likely accounts for the substantially different learning behavior observed (Fig. 4, E and F). \n\nWe show the measured and predicted TEC values for FeNiCoCr and FeNiCoCrCu HEAs in Fig. 4E and the mean absolute percentage error (MAPE) between experiments and predictions versus experimental iteration in Fig. 4F, with each exploitation and exploration step marked by arrows. For FeNiCoCr HEAs, the average experimental TEC value gradually decreases: $6.49\\times10^{-6}$ per degree kelvin (/K) in the first, $5.61\\times10^{-6}/\\mathrm{K}$ in the second, and $3.65\\times10^{-6}/\\mathrm{K}$ in the third iteration (Table 1). Exploration and exploitation take place alternately, akin to a natural learning process, and such a plot represents the “learning curve” of the HEA-GAD-TERM model. The learning curve indicates a progressive trend as the MAPE error decreases notably (from 1.5 to 0.2). Because of the exploration step, the model predictions deviate considerably from their experimental counterparts in the first iteration. Alloy A3 (Table 1) has the highest predicted TEC value $(4.39\\pm0.79\\times10^{-6}/\\mathrm{K})$ , but the experimental TEC value shows exactly the opposite, namely, the lowest measured TEC value $(1.41\\times10^{-6}/\\mathrm{K})$ . In the second and third iterations, the standard deviation of the experimental TEC values declines substantially $(3.34\\times10^{-6}/\\mathrm{K}$ and $1.46\\times10^{-6}/\\mathrm{K},$ respectively). This demonstrates excellent exploration progress in which HEA-GAD-TERM converges quickly and can predict TEC with high accuracy after only three iterations. Conversely, FeNiCoCrCu shows a different learning behavior. The discovery path shows no significant improvements, from experimentally measured $6.26\\times10^{-6}/\\mathrm{K}$ in the first iteration, to $6.64\\times10^{-6}/\\mathrm{K}$ in the second, and $5.67\\times{10}^{-6}/\\mathrm{K}$ in the third (for more numerical details, see Table 1). We can attribute this trend to the lack of Cu-containing FeNiCoCrCu data (only three data points are available at the beginning; Fig. 4D). Despite this shortcoming, the experimental mean deviation narrows down, from $33.9\\%$ for the first iteration to $10.2\\%$ in the last iteration, indicating a gradually improved model accuracy. \n\nTo reveal the physical origin behind the properties, we show experimental and DFT analyses of the A2 and A3 alloys $(\\mathrm{TEC}=10.52\\times$ $10^{-6}/\\mathrm{K}$ and $1.41\\times10^{-6}/\\mathrm{K},$ respectively, in Fig. 4, G to L). It can be seen in Fig. 4, G to J, that A2 and A3 alloys have a single-phase bcc and fcc structure, respectively. The partial disordered local moment (PDLM) model within the coherent potential approximation simulations (40) reveals that the Invar effect is qualitatively related to such volume reduction at finitetemperature PDLM phase compared with the $0\\mathrm{~K~}$ ferromagnetic ground state (41). In contrast to the fcc A3 alloy, the bcc A2 alloy, with a higher $T_{\\mathrm{c}}$ around $950~\\mathrm{K},$ exhibits a slight upward trend of the lattice parameter $a$ . Using DFT simulations, we also validate that if the A2 alloy can be stabilized in its fcc phase state, then an Invar effect can be realized as well [Fig. 4, K and L, red dash-dot line; for simulation details, see (31)]. The TEC value is also affected by the occurrence of phase transformations in some HEAs (18, 20). Our measurements show that the low TEC values of our A3 alloys are not caused by any phase transformation. \n\n![](images/736aeb4215af6e7306d6056196fdf2d4f8f6fdad169df2afd1fb459ce34f8798.jpg) \nFig. 5. Summary of the properties of the ML-designed HEAs. (A) TEC of the $5\\times10^{-6}/\\mathsf{K}$ at $300~\\mathsf{K},$ , which qualifies them as Kovar alloys. (B) Configurational ML-designed HEAs as a function of the change in temperature. As a comparison, entropy plotted against the TEC values for various known alloys and alloys we plotted the thermal expansion curve of the HEAs and MEAs. A3 and A9 discovered in this work. ML enables this approach to efficiently discover new FeNiCoCr HEAs show extremely low TECs around $2\\times10^{-6}/\\upkappa$ at $300\\mathsf{K}$ , which can alloys with excellent properties (high resistance to thermal cycles) in an infinite be used as Invar alloys. B2 and B4 FeNiCoCrCu HEAs show low TECs around phase spectrum (compositionally complex alloys). \n\nWe show the TEC as a function of temperature for the two Invar alloys $(\\mathrm{TEC}\\approx2\\times10^{-6}/\\mathrm{K})$ and two Kovar alloys (TEC $\\approx5\\times10^{-6}/\\mathrm{K})$ that we developed in Fig. 5A, compared with HEAs and medium-entropy alloys (MEAs) (19, 42). The new alloys show abnormally low TEC values compared with the HEAs, MEAs, and conventional alloys previously reported (Fig. 5B) (43–45). Most Invar alloys show a low TEC but also low configurational entropy. The Invar alloys developed in this work offer a good combination of low TEC and high configurational entropy. This indicates the high potential of the HEA concept for the design of Invar alloys, which, beyond their beneficial thermal expansion response, also offer high strength, ductility, and corrosion resistance. \n\n# Conclusions \n\nUnderstanding the underlying physics behind composition-property relations is the key mission in alloy design, a task particularly challenging in the case of compositionally complex materials. In principle, HEAs with interesting features can hide in practically infinite and vastly unexplored composition space, a scenario that puts targeted alloy design to its hardest test. We have therefore developed a widely applicable active learning framework that combines a generative model, regression ensemble, physics-driven learning, and experiments for the compositional design of HEAs. Our method demonstrates its proficiency in designing high-entropy Invar alloys using very sparse experimental data. The entire workflow required only a few months, in contrast to the conventional alloy design approach, which requires years and many more experiments. We expect that more than one property can be optimized simultaneously using the GAD-TERM framework in the compositional spectrum of HEAs. \n\n# REFERENCES AND NOTES \n\n1. J. W. Yeh et al., Adv. Eng. Mater. 6, 299–303 (2004). \n2. B. Cantor, I. Chang, P. Knight, A. Vincent, Mater. Sci. Eng. A 375–377, 213–218 (2004). \n3. E. P. George, D. Raabe, R. O. Ritchie, Nat. Rev. Mater. 4, 515–534 (2019). \n4. H. Mao, H.-L. Chen, Q. Chen, J. Phase Equilibria Diffus. 38, 353–368 (2017). \n5. F. Körmann et al., Appl. Phys. Lett. 107, 142404 (2015). \n6. Z. Rao et al., Intermetallics 111, 106520 (2019). \n7. S. Huang, E. Holmström, O. Eriksson, L. Vitos, Intermetallics 95, 80–84 (2018). \n8. Z. Rao, H. Springer, D. Ponge, Z. Li, Materialia (Oxf.) 21, 101326 (2022). \n9. B. O. Mukhamedov, K. V. Karavaev, I. A. Abrikosov, Phys. Rev. Mater. 5, 104407 (2021). \n10. J. Schmidt, L. Pettersson, C. Verdozzi, S. Botti, M. A. L. Marques, Sci. Adv. 7, eabi7948 (2021). \n11. Z. Pei et al., Adv. Sci. (Weinh.) 8, e2101207 (2021). \n12. P. V. Balachandran, B. Kowalski, A. Sehirlioglu, T. Lookman, Nat. Commun. 9, 1668 (2018). \n13. J. Gubernatis, T. Lookman, Phys. Rev. Mater. 2, 120301 (2018). \n14. D. Xue et al., Nat. Commun. 7, 11241 (2016). \n15. R. Yuan et al., Adv. Mater. 30, 1702884 (2018). \n16. E. Wassermann, M. Acet, in Magnetism and Structure in Functional Materials, A. Planes, L. Mañosa, A. Saxena, Eds. (Springer, 2005), pp. 177–197. \n17. M. Shiga, Curr. Opin. Solid State Mater. Sci. 1, 340–348 (1996). \n18. C. L. Lin et al., Appl. Phys. Lett. 119, 171902 (2021). \n19. Z. Rao et al., Phys. Rev. Mater. 5, 044406 (2021). \n20. C.-L. Lin et al., Mater. Chem. Phys. 271, 124907 (2021). \n21. I. Tolstikhin, O. Bousquet, S. Gelly, B. Schoelkopf, Wasserstein auto-encoders. arXiv:1711.01558 [stat.ML] (2017). \n22. R. Gómez-Bombarelli et al., ACS Cent. Sci. 4, 268–276 (2018). \n23. A. Christophe, N. de Freitas, A. Doucet, M. I. Jordan, Mach. Learn. 50, 5–43 (2003). \n24. W. K. Hastings, Biometrika 57, 97–109 (1970). \n25. K. Hornik, M. Stinchcombe, H. White, Neural Netw. 2, 359–366 (1989). \n26. R. Kohavi, D. H. Wolpert, ICML 96, 275–283 (1996). \n27. U. Von Luxburg, B. Schölkopf, in Handbook of the History of Logic, D. M. Gabbay, S. Hartmann, J. Woods, Eds. (Elsevier, 2011), vol. 10, pp. 651–706. \n28. G. Ke et al., in Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, CA, December 2017, U. von Luxburg, I. Guyon, S. Bengio, H. Wallach, R. Fergus, Eds. (NIPS, 2017), p. 3149–3157. \n29. J. H. Friedman, Comput. Stat. Data Anal. 38, 367–378 (2002). \n30. A. H. Li, J. Bradic, J. Am. Stat. Assoc. 113, 660–674 (2018). \n31. Materials and methods are available as supplementary materials. \n32. F. Wilcoxon, in Breakthroughs in Statistics, S. Kotz, N. L. Johnson, Eds. (Springer, 1992), pp. 196–202. \n33. R. Lowry, “Concepts and applications of inferential statistics” (DOER, 2014); http://doer.col.org/handle//123456789/4853. \n34. H. Masumoto, Science Reports of the Tohoku Imperial University 20, 101–123 (1931). \n35. H. Masumoto, Science Reports of the Tohoku Imperial University 23, 265–275 (1934). \n36. M. Hakaru, S. Hideo, K. Tatsuo, Science Reports of the Research Institutes, Tohoku University. Series A, Physics, Chemistry and Metallurgy 6, 529–538 (1954). \n37. M. Hakaru, S. Hideo, S. Yutaka, Science Reports of the Research Institutes, Tohoku University. Series A, Physics, Chemistry and Metallurgy 7, 533–540 (1955). \n38. M. Hakaru, S. Hideo, G. Kimiyosi, Science Reports of the Research Institutes, Tohoku University. Series A, Physics, Chemistry and Metallurgy 9, 159–169 (1957). \n39. M. Hakaru, S. Hideo, S. Yutaka, Science Reports of the Research Institutes, Tohoku University. Series A, Physics, Chemistry and Metallurgy 9, 170–175 (1957). \n40. I. A. Abrikosov et al., Phys. Rev. B Condens. Matter Mater. Phys. 76, 014434 (2007). \n41. A. V. Ruban, Phys. Rev. B 95, 174432 (2017). \n42. G. Laplanche et al., J. Alloys Compd. 746, 244–255 (2018). \n43. T. Schneider, M. Acet, B. Rellinghaus, E. F. Wassermann, W. Pepperhoff, Phys. Rev. B Condens. Matter 51, 8917–8921 (1995). \n44. C. Chanmuang, M. Naksata, T. Chairuangsri, H. Jain, C. E. Lyman, Mater. Sci. Eng. A 474, 218–224 (2008). \n45. K. Fukamichi, M. Kikuchi, S. Arakawa, T. Masumoto, Solid State Commun. 23, 955–958 (1977). \n46. Code for: Z. Rao et al., Machine learning-enabled high-entropy alloy discovery, GitHub (2022); https://github.com/ziyuanrao11/ Machine-learning-enabled-high-entropy-alloy-discovery. \n47. Data for: Z. Rao et al., Machine learning-enabled high-entropy alloy discovery, Zenodo (2022); https://doi.org/10.5281/ zenodo.7019194. \n\n# ACKNOWLEDGMENTS \n\nWe thank M. Acet from University of Duisburg-Essen and M. Nellessen, M. Adamek, and F. Schlüter from Max-Planck-Institut für Eisenforschung GmbH. The staff of TU Darmstadt is gratefully acknowledged for providing computational resources with the Lichtenberg high-performance computer for the exact muffin-tin orbital (EMTO) calculations in the present work. Funding: Z.R., R.X., O.G., and H.Z. were supported by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation project ID 405553726-TRR 270). Y.W. was supported by BiGmax, the Max Planck Society’s Research Network on Big-Data-Driven Materials Science, and the ERC-CoG-SHINE-771602. P.T. was supported by the Electron and X-Ray Microscopy Community for Structural and Chemical Imaging Techniques for Earth materials (EXCITE grant no. G106564) and the International Max Planck Research School for Interface Controlled Materials for Energy Conservation (IMPRS-SurMat). Author contributions: Z.R., Y.W., and D.R. conceived the study. Y.W. and Z.R. designed the active learning framework. Z.R., Y.W., P.T., and S.B. developed the algorithm and analyzed the results. Z.R. performed the experiments. R.X., H.Z., A.F., P.K., and F.K. performed the DFT calculations. P.T.S., A.K.S., and Z.R. performed the thermodynamic calculations. Z.R., Y.W., and P.T. wrote the main parts of the manuscript. P.T. produced the final figures. All authors discussed the results and commented on the manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: The training dataset is curated from the previous publications (34–39) and can be found in (46). The necessary data produced by our model in this work can be found in the supplementary materials. The original code used to perform this work is available on GitHub (46). We also provide a simplified version of the code integrated into a single Jupyter Notebook on GitHub (46), which is easier to perform and understand. In addition, data are provided in the Zenodo repository (47). License information: Copyright $\\circledcirc$ 2022 the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.science.org/about/science-licenses-journalarticle-reuse \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abo4940 \nMaterials and Methods \nFigs. S1 to S13 \nTables S1 to S16 \nReferences (48–63) \n\nSubmitted 13 February 2022; resubmitted 30 June 2022 \nAccepted 30 August 2022 \n10.1126/science.abo4940 " + }, + { + "id": "10.1038_s41598-022-06657-y", + "DOI": "10.1038/s41598-022-06657-y", + "DOI Link": "http://dx.doi.org/10.1038/s41598-022-06657-y", + "Relative Dir Path": "mds/10.1038_s41598-022-06657-y", + "Article Title": "Antibacterial action and target mechanisms of zinc oxide nulloparticles against bacterial pathogens", + "Authors": "Mendes, CR; Dilarri, G; Forsan, CF; Sapata, VDR; Lopes, PRM; de Moraes, PB; Montagnolli, RN; Ferreira, H; Bidoia, ED", + "Source Title": "SCIENTIFIC REPORTS", + "Abstract": "Zinc oxide nulloparticles (ZnO NPs) are one of the most widely used nulloparticulate materials due to their antimicrobial properties, but their main mechanism of action (MOA) has not been fully elucidated. This study characterized ZnO NPs by using X-ray diffraction, FT-IR spectroscopy and scanning electron microscopy. Antimicrobial activity of ZnO NPs against the clinically relevant bacteria Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and the Gram-positive model Bacillus subtilis was evaluated by performing resazurin microtiter assay (REMA) after exposure to the ZnO NPs at concentrations ranging from 0.2 to 1.4 mM. Sensitivity was observed at 0.6 mM for the Gram-negative and 1.0 mM for the Gram-positive cells. Fluorescence microscopy was used to examine the interference of ZnO NPs on the membrane and the cell division apparatus of B. subtilis (amy::pspac-ftsZ-gfpmut1) expressing FtsZ-GFP. The results showed that ZnO NPs did not interfere with the assembly of the divisional Z-ring. However, 70% of the cells exhibited damage in the cytoplasmic membrane after 15 min of exposure to the ZnO NPs. Electrostatic forces, production of Zn2+ ions and the generation of reactive oxygen species were described as possible pathways of the bactericidal action of ZnO. Therefore, understanding the bactericidal MOA of ZnO NPs can potentially help in the construction of predictive models to fight bacterial resistance.", + "Times Cited, WoS Core": 307, + "Times Cited, All Databases": 312, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000757107700007", + "Markdown": "# Antibacterial action and target mechanisms of zinc oxide nanoparticles against bacterial pathogens \n\nCarolina Rosai Mendes1,5\\*, Guilherme Dilarri1,5, Carolina Froes Forsan1, Vinícius de Moraes Ruy Sapata1, Paulo Renato Matos Lopes2, Peterson Bueno de Moraes3, Renato Nallin Montagnolli1,4, Henrique Ferreira1 & Ederio Dino Bidoia1 \n\nZinc oxide nanoparticles (ZnO NPs) are one of the most widely used nanoparticulate materials due to their antimicrobial properties, but their main mechanism of action (MOA) has not been fully elucidated. This study characterized ZnO NPs by using X-ray diffraction, FT-IR spectroscopy and scanning electron microscopy. Antimicrobial activity of ZnO NPs against the clinically relevant bacteria Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and the Gram-positive model Bacillus subtilis was evaluated by performing resazurin microtiter assay (REMA) after exposure to the ZnO NPs at concentrations ranging from 0.2 to $\\pmb{1.4}\\mathsf{m}\\mathsf{M}$ . Sensitivity was observed at $\\pmb{0.6}\\mathsf{m}\\mathsf{M}$ for the Gram-negative and $\\pmb{1.0}\\mathsf{m}\\mathsf{M}$ for the Gram-positive cells. Fluorescence microscopy was used to examine the interference of ZnO NPs on the membrane and the cell division apparatus of B. subtilis (amy::pspac-ftsZ-gfpmut1) expressing FtsZ-GFP. The results showed that ZnO NPs did not interfere with the assembly of the divisional Z-ring. However, $70\\%$ of the cells exhibited damage in the cytoplasmic membrane after 15 min of exposure to the ZnO NPs. Electrostatic forces, production of $Z n^{2+}$ ions and the generation of reactive oxygen species were described as possible pathways of the bactericidal action of ZnO. Therefore, understanding the bactericidal MOA of ZnO NPs can potentially help in the construction of predictive models to fight bacterial resistance. \n\nNanoparticles (NPs) of metal oxide stand out in the field of antimicrobial compounds by their catalytic inhibition ­activity1,2. However, their bactericidal mechanism of action (MOA) depends on several parameters, such as their morphology, composition and ­concentration3,4. Zinc oxide $(\\mathrm{ZnO})$ , magnesium oxide (MgO) and titanium dioxide $\\mathrm{(TiO}_{2})$ are substances recognized as safe when used as food additives or drug deliverers according to the Food and Drug Administration (FDA 2011) US Code of Federal Regulations (Title 21-CFR 182.8991)5. Zinc oxide nanoparticles $(\\mathrm{ZnO}\\mathrm{NPs})$ are the most promising inorganic materials that have bactericidal action and can be found in the composition of pharmaceutical drugs, sanitizers, cosmetics and food packaging ­processes6. However, the targets of ZnO NPs in bacteria of clinical importance are not fully understood. Zanet et al.7 carried out experiments using $\\mathrm{{}}Z\\mathrm{{nO}}$ NPs against the model cell Saccharomyces cerevisiae in order to elucidate the main MOA, and concluded that the effects of $\\mathrm{{}}Z\\mathrm{{nO}}$ NPs depend on their composition and dose. \n\nThe synthesis of $\\mathrm{znO}$ NPs can be achieved by chemical ­precipitation8, salt ­reduction9, sol–gel way based on an acetate ­precursor10, and sonochemical ­synthesis11. However, different synthetic pathways yield $\\scriptstyle{\\mathrm{ZnO}}$ particles with variable morphologies and ­sizes9,12,13. Thus, their MOA, as well as their interaction with diverse cell structures, may vary significantly. \n\n$\\mathrm{{}}Z\\mathrm{{nO}}$ is a transition metal oxide and semiconductor with high binding energy which allows for a highly oxidative ­character14. This reaction leads to the formation of reactive oxygen species as the pathway of bactericidal action. In addition, another bactericidal MOA occurs through the release of zinc ions $(Z\\boldsymbol{\\mathrm{n}}^{2+})$ that damage the cell membrane and may interrupt some metabolic ­pathways15. Thus, additional studies about the antibacterial MOA of ZnO NPs can relevantly contribute to the prediction of possible mechanisms of bacterial resistance and for the optimizing of the contact time and effective inhibition action. \n\nCell division is a critical process for microbial survival. Among the proteins involved in this process, FtsZ has a pivotal function in which it serves as a scaffold for the assembly of a multiprotein complex structure, the divisome, responsible for coordinating all the steps of cell division and cell wall ­remodeling16. The protein acts during cell division as an organizer of the cytoplasmic ring in bacteria and can be considered the main target of several bactericidal ­compounds17. Bactericidal agents act in diverse ways, such as inhibition of FtsZ in the cell division pathway, and can be identified by cytological profile of cells expressing FtsZ-GFP and observed by fluorescence ­microscopy18. \n\nIn this study, the model Gram-positive bacteria Bacillus subtilis (ATCC 19659) and a set of clinically relevant bacteria Escherichia coli (ATCC 8739), Staphylococcus aureus (ATCC 6538), and Pseudomonas aeruginosa (ATCC 27853) were used to determine the inhibitory concentration of $\\mathrm{znO}$ NPs and to evaluate their effect on the bacteria cytological profile. The focus of the present study was to evaluate the action of $\\mathrm{znO}$ NPs on cell morphology, chromosome organization, and protein production. Therefore, the cytoplasmatic membrane and other proteins, such as FtsZ, which forms the scaffold for the divisome, were not included in the spectra of analysis. Bacillus subtilis FtsZ was used to evaluate any interference in the formation of the FtsZ ring. \n\n# Materials and methods \n\nSynthesis of ZnO NPs.  All reagents were purchased from Sigma-Aldrich (Taufkirchen, Germany). ZnO NPs were synthesized by sonochemical-coprecipitation of $2\\mathrm{mM}$ solution of zinc chloride followed by dripping it with ammonium ­hydroxide19. Next, the mixture was heated to $60^{\\circ}\\mathrm{C}$ under continuous stirring until complete precipitation. The precipitate underwent ultrasonic bath sonicator (USC 1400) for $30~\\mathrm{min}$ to obtain NPs, followed by vacuum filtration using a $0.22\\upmu\\mathrm{m}$ cellulose membrane, washing with deionised water and finally drying at $100^{\\circ}\\mathrm{C}$ overnight. \n\nCharacterization of the synthesized nanomaterial.  ZnO NPs were characterized using Fourier transform infrared spectrophotometer FT-IR (Shimadzu Model 8300), adjusted for scanning at $4000{-}\\mathrm{\\bar{4}00}\\mathrm{cm}^{-1}$ . For the analysis, a KBr pellet was made with the nanomaterial ­sample20. Micrographs of $\\mathrm{znO}$ NPs were taken by Scanning Electron Microscope (SEM)—JEOL JSM-IT100 operated at $30\\mathrm{kV}$ coupled to a Bruker Quantax Energy Dispersive Detector (EDS), in order to study the morphological characteristics. The samples were coated with a gold layer by a metalization process before SEM readings. Finally, the crystalline structure of the $\\mathrm{znONPs}$ was characterized by X-ray diffraction powder (XRD, PHILIPS, $\\mathbf{\\Delta}\\mathbf{X}^{\\prime}$ pert-MPD system) using Cu Kα radiation $(\\lambda=1.5418\\mathrm{~\\AA~},$ . The X-ray wavelength was $0.15418~\\mathrm{nm}$ and the diffraction patterns were measured in the range of $2\\theta$ from $20^{\\circ}$ to $65^{\\circ}$ . \n\nBacterial strain and growth conditions.  Escherichia coli (ATCC 8739), Staphylococcus aureus (ATCC 6538), Bacillus subtilis (ATCC 19659), Pseudomonas aeruginosa (ATCC 27853) and the mutant Bacillus subtilis (amy::pspac‐ftsZ‐gfpmut1; a gift of Dr. F. Gueiros-Filho, $\\scriptstyle{\\mathrm{IQ}},$ USP, São Paulo, Brazil) expressing FtsZ‐GFP were cultivated in nutrient broth medium ( $\\mathbf{\\dot{\\tau}}_{5}\\mathbf{g}\\mathbf{L}^{-1}$ of peptone; $3\\mathrm{~g~L^{-1}}$ of beef extract; for solid medium was added $15\\mathrm{gL}^{-1}$ of bacterial agar) at $28^{\\circ}\\mathrm{C}$ for $24\\mathrm{h}$ in shaker at $200\\mathrm{rpm}$ . All reagents for cellular growth were purchased from Himedia Laboratories Ltd. (Mumbai, India). \n\nAntibacterial activity assay.  The antibacterial activities expressed as Inhibitory Concentrations (ICs) of the $\\mathrm{{ZnO}}$ NPs were determined by using the Resazurin Microtiter Assay (REMA)21. $\\mathrm{{}}Z\\mathrm{{nO}}$ NPs at concentrations between 0.2 and $1.4~\\mathrm{mM}$ were placed in 96-well microplates. The strains were inoculated to independent trials at a final concentration of $10^{5}$ cells per $100\\upmu\\mathrm{L}$ in each well and incubated for $^{12\\mathrm{h}}$ at $30\\pm1{}^{\\circ}\\mathrm{C}.$ . Nisin at $5\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ and Kanamycin at $20~{\\upmu\\mathrm{g}}~\\mathrm{mL}^{-1}$ from Sigma-Aldrich (Taufkirchen, Germany) were used as reference antibiotic (positive controls) against Gram-positive and Gram-negative bacteria, respectively. Nutrient broth medium was used as negative control. After the incubation period, the inhibition of cell growth was measured by the addition of $0.1\\mathrm{mg}\\mathrm{\\bar{mL}^{-1}}$ resazurin (Sigma-Aldrich; Taufkirchen, Germany) in each well. In live cells, resazurin is reduced to resorufin (a fluorescent compound) in the presence of NADH, which indicates cell ­activity18. The fluorescence intensity of resorufin was detected in a plate reader (Synergy H1N1—BioTek, Winooski, VT, USA) set to the excitation and emission wavelengths of 530 and $590\\mathrm{nm}$ , respectively. The results of this assay were used to plot the correlation between $\\mathrm{znO}$ NPs concentration and the inhibition of cell growth. Non-linear regression models were used to derive the $\\mathrm{IC}_{100}$ values for each bacterial strain ( $100\\%$ inhibitory concentration). \n\nEffect of ZnO NPs on the membrane integrity.  E. coli, P. aeruginosa, B. subtilis and S. aureus at $10^{5}$ cells were exposed to $\\mathrm{znO}$ NPs at concentrations equivalent to their $\\mathrm{IC}_{100}$ in $100\\upmu\\mathrm{L}$ of media for $15\\mathrm{min}$ . Next, ${900\\upmu\\mathrm{L}}$ of phosphate buffer were added to stop the reactions. Next, cells were stained using $0.01\\ \\mathrm{mg\\mL^{-1}}$ propidium iodide (PI) and $0.02\\mathrm{mg}\\mathrm{mL}^{-1}$ DAPI ( $^{\\cdot}4^{\\prime}{,}6$ -diamidino-2-phenylin-dole). DAPI stains the nucleoid of every cell, whereas propidium iodide (PI) is a nucleic acid dye that penetrates only cells with damaged cytoplasmatic membranes. Untreated cells were used as negative control, while positive control for damaged membranes was generated by heat-shock stress (Gram-negative) and Nisin treatment (Gram-positive). B. subtilis (amy::pspac‐ ftsZ‐gfpmut1) expressing FtsZ-GFP was used to investigate the potential of the compound to interfere with the divisional septa. The bacterial cells were cultivated in the presence of $0.02~\\mathrm{mM}$ Isopropyl $\\upbeta$ ‐d‐thiogalactopyranoside (IPTG) to induce the expression of FtsZ‐GFP from the pspac promoter. Next, $100\\upmu\\mathrm{L}$ of the cultures (adjusted to contain $\\sim10^{5}$ cells) were exposed for $15\\mathrm{min}$ to $\\mathrm{znO}$ NPs at its respective $\\mathrm{IC}_{100}$ . Cells were washed with water and resuspended in $100~\\upmu\\mathrm{L}$ of $0.85\\%$ NaCl solution prior to microscope ­observation18. Cells were immobilized onto agarose-covered slides and visualized using an Olympus BX-61 (Tokyo, Japan), equipped with a monochromatic camera OrcaFlash 2.8 (Hamamatsu, Japan). Images were processed by the software CellSens version 11 (Olympus). One hundred cells were considered $[\\boldsymbol{\\mathrm{n}}=100\\$ ) per treatment for quantifications. \n\n![](images/8d2cec824f7da8e71869ef1f4da0b7d8be415ee629dc9ed50e8b7d10123393fb.jpg) \nFigure 1.   XRD power of $\\mathrm{znO}$ NPs. \n\nTable 1.   Structural parameters of $\\mathrm{znO}$ crystallite. \n\n\n
Lattice parameters a (A)Lattice parameters c (A)c/a ratioVolume of unit cell (A3)Average crystallite size (nm)Microstrain ε(×103)
3.245.211.60847.4882.380.47
\n\n# Results and discussion \n\nCharacterization of ZnO NPs.  The XRD peaks were consistent with $\\mathrm{znO}$ crystallite. The analysis showed no extra peaks, which is due to the purity of the material applied during the synthesis of ZnO NPs. The positions of the diffraction peaks showed the same pattern found in the Joint Committee on Powder Diffraction Standards: 36–1451 database (JCPDS). \n\nFigure 1 shows the diffraction peaks of $\\mathrm{znO}$ NPs at (100), (002), (101), (102), (110), (103) which correspond respectively to the values in degrees (2θ) at $31.34^{\\circ}$ , $34.50^{\\circ}$ , $36.32^{\\circ}$ , $47.60^{\\circ}$ , $56.68^{\\circ}$ , $62.94^{\\circ}$ . High diffraction peaks indicated the crystalline nature of the ­material22. \n\nTable 1 shows the values of the structural parameters used to calculate the size of the $\\mathrm{{}}Z\\mathrm{{nO}}$ crystallite by Eq. $(1)^{23}$ . The high intensity peak at (101) was used to determine the lattice parameters. \n\n$$\nD=\\left[\\frac{0.9\\lambda}{\\beta\\cos\\theta}\\right]\\times100\\\n$$ \n\nwhere $D$ is the size of the $\\mathrm{znO}$ crystallite; $\\lambda$ is the wavelength of Cu Kα radiation at $1.5418\\mathring\\mathrm{A}$ ; $\\theta$ is the Bragg diffraction angle, and $\\beta$ is the full width at half maximum intensity of the diffraction peak of the sample. \n\nThe crystallite size can be measured more accurately by high resolution $\\mathrm{\\DeltaX}$ -ray diffraction (HRXRD) using the Bond method, which increases peak resolution to find the values of the Lattice ­parameters23,24. In this study, we determined by XRD powder that most synthesized $\\mathrm{znO}$ crystallites are around $80\\mathrm{nm}$ in size. Similar results obtained through the synthesis of $\\mathrm{znO}$ NPs by sonochemical–coprecipitation were shown by Khataee et al.25. \n\nThe surface appearance and morphology of synthesized $\\mathrm{{}}Z\\mathrm{{nO}}$ NPs were analyzed by SEM at $29.0\\mathrm{kx}$ . Based on the images in Fig. 2, the $\\mathrm{{ZnO}}$ NP showed complex bead and rod morphology. In addition, the ZnO NPs have an irregular size with formation of aggregated nanocrystallite. \n\nFT-IR spectra are like molecular fingerprints that provide a valuable insight into chemical structures and their changes due to interactions with other ­molecules20. FT-IR analyses detected the characteristic functional groups associated with the $\\mathrm{znO}$ NPs (Fig. 3). The peak at $575~\\mathrm{cm}^{-1}$ corresponds to the stretching/vibration of the metal–oxygen bond in $Z\\mathrm{n-O}$ . The peak at $371\\bar{3}\\mathrm{cm}^{-1}$ corresponds to carbon residues identified during the sample measurement; and $1210\\mathrm{cm}^{-1}$ belongs to the elongation of C–O. Hydrogen bonds are displayed at 1690 and $2346~\\mathrm{cm^{-1}}$ , and they are ascribed to the stretching vibration of hydroxyl compounds. The hydroxyl group influences photocatalytic reactions in $\\mathrm{znO}$ by generating superoxide radicals, which act as an ­antimicrobial26. \n\n![](images/346ceb0a79c35d6244a878f427568a2a8eb4c3bd0982690d07e2ae738915f774.jpg) \nFigure 2.   Surface morphology of $\\scriptstyle z_{\\mathrm{nO}}$ NPs by SEM. $2\\upmu\\mathrm{m}$ scale bar; $29.0\\mathrm{kx}$ magnification. \n\n![](images/0b344676005f03d4f68cbfabf4ca3fed2608ba997e1ebcc9cf35057cfe05b111.jpg) \nFigure 3.   FT-IR spectrum of $\\mathrm{znO}$ NPs. \n\nAntimicrobial activity.  The bactericidal activities of $\\mathrm{znO}$ NPs against E. coli, P. aeruginosa, S. aureus and B. subtilis were evaluated by monitoring cell respiration. Polynomial regression applied to the dose–response data was used to extrapolate the $\\mathrm{IC}_{100}$ values, which were expressed as $\\mathrm{mM}$ . The decrease in cell numbers observed after treatment is shown in by the plot containing the concentration of $\\mathrm{{}}Z\\mathrm{{nO}}$ NPs versus the inhibition of cell growth (Fig. 4). \n\n$\\mathrm{{}}Z\\mathrm{{nO}}$ NPs inhibited growth of E. coli and P. aeruginosa with $\\mathrm{IC}_{100}$ values of $0.6\\mathrm{mM}$ for both strains. The $\\mathrm{IC}_{100}$ values for B. subtilis and S. aureus were estimated at 0.8 and $1.0\\mathrm{mM}$ , respectively. Gram-negative bacteria have a thin layer of peptidoglycan between two membranes, which is known to provide antimicrobial ­resistance27. In addition, dissociated carboxyl groups present in the membranes generate negative charges on the cell surface. ZnO NPs, on the other hand, have a positive charge, with a zeta potential of $\\bar{\\mathrm{f}}+24{\\mathrm{~mV}}^{28}$ . As a result of electrostatic forces, damage to the cell membrane occurs due to electrostatic gradient differences across the negative membrane and the positive charges of the $Z\\mathrm{n}^{2+}$ ions. Therefore, $E$ . coli and $P.$ aeruginosa died with the lowest concentration of ZnO NPs. Although the present study did not observe a large difference in the IC values for Gram-negative and Gram-positive, it is noteworthy that Gram-positive exhibited $\\mathrm{IC}_{100}$ values higher than Gramnegative. Similar inhibition in Gram-negative bacteria was previously reported by Yusof et al.29, Saqib et al.30 and Zubair and ­Akhtar31; however, with slight variations in the $\\mathrm{IC}_{100}$ values due to differences in the synthesis of the nanomaterial, which yields unique characteristics to each one of them. Overall, the results were close; however, our study not only investigated the percentage of inhibitory growth, but also the MOA target of $\\scriptstyle z_{\\mathrm{nO}}$ NPs in clinical strains. \n\n![](images/93ed29501deeb7d1f7f556d672cf2d8e68a174ba8ef8fbf68e42528359889e48.jpg) \nFigure 4.   Antimicrobial activity of $\\mathrm{znO}$ NPs determined by REMA. \n\nEffect of ZnO NPs on the bacteria cell.  Bacterial cell division is a complex and dynamic process, which starts with the polymerization of the FtsZ protein in order to assemble the divisome, which will guide all the processes related to cell division and cell wall synthesis and ­remodelling32. FtsZ is the ancestral tubulin conserved in bacteria, which exerts its function dependent on the nucleotide guanosine triphosphate $(\\mathrm{GTP})^{33,34}$ . Some bactericidal compounds act by preventing the GTPase activity of FtsZ, which will inhibit cell division and lead to cell ­death17. In addition, blockage of the cell division process generally leads to cell filamentation, which can be easily accessed by fluorescence microscopy. Alternatively, by using mutant cells expressing labelled division proteins, e.g. FtsZ-GFP, one can follow the dynamics of division and study the effects compounds might have on the process. \n\nB. subtilis expressing FtsZ‐GFP was exposed to $\\mathrm{znO}$ NPs at its $\\mathrm{IC}_{100}$ for $15\\mathrm{min}$ , and afterwards observed under the microscope (Fig. 5). Note that even after $\\mathrm{znO}$ NPs exposure, the cells still have intact bars perpendicular to the long axis of the rods, which is the normal profile for the Z-ring. This cytological profile was comparable to the control and did not show any disruption of the divisional ring. \n\nThe integrity of the membranes of $E$ . coli, P. aeruginosa, S. aureus, and B. subtilis cells was investigated upon compound exposure using fluorescence microscopy. The results showed the disruption of cytoplasmic membranes in all strains after $\\mathrm{{15\\min}}$ of exposure at $\\mathrm{IC}_{100}$ (Fig. 6). The filters Tx Red and DAPI Blue were applied together and used to visualize PI and DAPI. Cells with intact membranes are artificially stained in blue, while cells with damaged membranes are stained ­red35. Thus, an increase in red-stained cells by PI is related to the increase in cell permeability due to damaged membranes. \n\nIn this study, all the bacterial species had their cytoplasmic membrane affected within the first $15\\mathrm{min}$ of exposure to $\\mathrm{{znO}}$ NPs. Treatment with the compound led to membrane damage in more than $70\\%$ of the cells. These results were expected since the bactericidal activity of $\\mathrm{znO}$ NPs was already known, and its predominant MOA is associated with the cell ­membrane14. \n\n$\\mathrm{{}}Z\\mathrm{{nO}}$ is a transition metal oxide and semiconductor (which belongs to class II–VI) with wide band gap $(3.3~\\mathrm{eV})$ , there is a general pattern expected. When the radiation has energy larger than the band gap of the $Z_{\\mathrm{{nO},}}$ electron–hole pairs are formed. Electrons are promoted to the conduction band (CB). The hole generated in the valence band (VB) gets a strongly oxidizing character and oxidizing sites are created, which are capable of oxidizing water molecules or hydroxide anions and generate strong oxidizing ­species13. This reaction leads to the redox chain reaction with the generation of reactive oxygen species (ROS) formed by hydroxyl radical (·OH), hydroperoxyde radical $\\left(\\mathrm{\\cdotHO}_{2}^{-}\\right)$ and superoxide radical anion $(\\mathrm{O}_{2}^{.-})$ as the pathways of bactericidal ­action36. \n\n![](images/af8dd08bde66184e831aeed26542fa1ed70a3f30ee445b79646e85a08a7272cb.jpg) \nFigure 5.   B. subtilis expressing FtsZ-GFP. (A) Control of cells grown in nutrient medium and diluted to $10^{6}$ cells per $\\mathrm{mL^{-1}}$ . (B) Cells after $15\\mathrm{min}$ of exposure to $\\mathrm{znO}$ NPs in the $\\mathrm{IC}_{100}$ . GFP/PhC is the phase contrast images superimposed on the GFP fluorescence images. Scale bar $5\\upmu\\mathrm{m};\\times100$ magnification. \n\nOxidative stress in the bacterial cell can be induced by ROS generation produced from ZnO NPs, which leads to the inhibition of protein synthesis and DNA ­replication14. In this situation, the $\\mathrm{{ZnO}}$ conductivity increases, close to the “band gap” of the UV-spectrum characterized by high emission energy. The electronic excitation can destabilize the charges present in the cytoplasmic membrane resulting in their rupture. $\\mathrm{znO}$ can also damage the cytoplasmic membrane by releasing $Z\\mathrm{n}^{2+}$ ions from the dissolution of $\\mathrm{{ZnO}}$ in aqueous solution. The $Z\\mathrm{n}^{\\overline{{2}}+}$ ion acts as an inhibitor of the glycolytic enzyme through the thiol group oxidation due to specific affinity for the sulphur ­group3. \n\nThe MOA reported in this study are represented in schematic drawing shown in Fig. 7. \n\nZnO NPs can be attached to the surfaces of Gram-positive and Gram-negative bacteria through different pathways. The teichoic acid in the peptidoglycan layer and the lipoteichoic acid in the membrane are the source of negative charges in the cell surface. Positive charges from $\\mathrm{znO}$ NPs are attracted to the cell surface by electrostatic interactions, and the difference in electrostatic gradient leads to damage in the cell ­surface37,38. Teicoic and lipoteichoic acids act as a chelating agent on $Z\\mathrm{n}^{2+}$ ions, which are then carried by passive diffusion across membrane proteins (Fig. 8). Moreover, the bactericidal action can occur by different mechanisms, such as adsorption in the bacterial surface, formation of different intermediates and electrostatic interactions. \n\nThe electrochemical gradient is generated by the movement of hydrogen ions across the cell membrane, which facilitates the diffusion of metallic ­ions36. This mechanism is associated with the size of the material, whose small particles would have better electrostatic interactions. Thus, the $\\mathrm{{}}Z\\mathrm{{nO}}$ target for inhibitory action is dependent on different factors such as concentration, size and time of interaction. \n\nZanet et al.7 showed that $\\mathrm{{ZnO}}$ NPs affect the cell morphology and DNA. However, this can be a side effect, since the main target of $\\mathrm{znO}$ NPs ends up being the first structure they have contact with and consequently act, such as the cytoplasmic membrane. Siddiqi et al.13 through SEM and TEM analysis concluded that ZnO NPs damage the cell membrane, and right after go to the cytoplasm, where they interact with other cell structures. Our results also showed damage to the cell. Therefore, it can be concluded that $\\mathrm{znO}$ NPs are multi-target compounds and affect several structures of bacteria cells, but their main mechanism of action is in the cytoplasmic membrane, being other structure effects a consequence/secondary effect after the membrane rupture. \n\n![](images/027e3be5175b6bab209df8727c1d896bcc3951db1c3d6f3d1f418e2bb5418cde.jpg) \nFigure 6.   Fluorescence microscopy in cells stained with DAPI and PI after $15\\mathrm{min}$ of exposure to ZnO NPs. Cells with intact membranes are artificially stained in blue, while cells with damaged membranes are stained in red. (A) E. coli (ATCC 8739) cells in nutrient broth medium (negative control); (B) E. coli (ATCC 8739) cells treated with heat-shock stress (positive control); (C) E. coli (ATCC 8739) cells treated with $\\mathrm{{}}Z\\mathrm{{nO}}$ NPs at $\\mathrm{IC}_{\\mathrm{100}};$ (D) $P.$ aeruginosa (ATCC 27853) cells in nutrient broth medium (negative control); (E) P. aeruginosa (ATCC 27853) cells treated with heat-shock stress (positive control); (F) $P.$ aeruginosa (ATCC 27853) cells treated with $\\mathrm{znO}$ at $\\mathrm{IC}_{100};$ $(\\mathbf{G})$ S. aureus (ATCC 6538) cells in nutrient broth medium (negative control); (H) S. aureus (ATCC 6538) cells treated with nisin at $5\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ (positive control) (I) S. aureus (ATCC 6538) cells treated with $\\mathrm{{}}Z\\mathrm{{nO}}$ at $\\mathrm{IC}_{100}\\mathrm{;}$ (J) B. subtilis (ATCC 19659) cells in nutrient broth medium (negative control); (K) B. subtilis (ATCC 19659) cells treated with nisin at $5\\upmu\\mathrm{g}\\mathrm{mL}^{-1}$ (positive control); (L) B. subtilis (ATCC 19659) cells treated with $\\mathrm{{znO}}$ at $\\mathrm{IC}_{100}$ . Scale bar $2\\upmu\\mathrm{m};\\times100$ magnification. \n\n![](images/3dff10fc9b9590c5e4cab7eba07a9b1cf41a7a2f39dd066b44012eb7f8e0cef3.jpg) \nFigure 7.   Model of the main bactericidal MOA of $\\mathrm{{}}Z\\mathrm{{nO}}$ NPs which target the cytoplasmatic membrane and cell wall. \n\n![](images/106f0cd14edbbad3ab0ec84bf44305aca90c939952cab0c55a4f87bb3afd719a.jpg) \nFigure 8.   Cell model for the main mechanism of bactericidal action of $\\mathrm{znO}$ NPs. \n\nReceived: 5 November 2021; Accepted: 24 January 2022 \nPublished online: 16 February 2022 \n\n# References \n\n1.\t Pachaiappan, R., Rajendran, S., Show, P. L., Manavalan, K. & Naushad, M. Metal oxide nanocomposites for bactericidal effect: A review. Chemosphere 272, 128607. https://​doi.​org/​10.​1016/j.​chemo​sphere.​2020.​128607 (2020). \n2.\t Padilla-Cruz, A. L. et al. Synthesis and design of Ag–Fe bimetallic nanoparticles as antimicrobial synergistic combination therapies against clinically relevant pathogens. Sci. Rep. 11, 5351. https://​doi.​org/​10.​1038/​s41598-​021-​84768-8 (2021). \n3.\t Qi, K., Cheng, B., Yu, J. & Ho, W. Review on the improvement of the photocatalytic and antibacterial activities of $Z\\mathrm{nO}$ J. Alloy. Compds. 727, 792–820. https://​doi.​org/​10.​1016/j.​jallc​om.​2017.​08.​142 (2017). \n4.\t Liao, C., Jin, Y., Li, Y. & Tjong, S. C. Interactions of zinc oxide nanostructures with mammalian cells: Cytotoxicity and photocatalytic toxicity. Int. J. Mol. Sci. 21(17), 6305. https://​doi.​org/​10.​3390/​ijms2​11763​05 (2020). \n5.\t FDA. Part 182—Substances Generally Recognized as Safe (Food and Drug Administration, 2011). \n7.\t Zanet, V. et al. Activity evaluation of pure and doped zinc oxide nanoparticles against Saccharomyces cerevisiae. J. Appl. Microbiol. 127, 1391–1402. https://​doi.​org/​10.​1111/​jam.​14407 (2019). \n8.\t Hoseinzadeh, E., Alikhani, M., Samarghandi, M. & Shirzad-Siboni, M. Antimicrobial potential of synthesized zinc oxide nanoparticles against gram positive and gram negative bacteria. Desalinat. Water Treat. 52, 4969–4976. https://​doi.​org/​10.​1080/​19443​ 994.​2013.​810356 (2014). \n9.\t Jiang, J., Pi, J. & Cai, J. The advancing of zinc oxide nanoparticles for biomedical applications. Bioinorg. Chem. Appl. 2018, 18. https://​doi.​org/​10.​1155/​2018/​10625​62 (2018). \n10.\t Tiwari, V. et al. Mechanism of anti-bacterial activity of zinc oxide nanoparticle against carbapenem-resistant Acinetobacter baumannii. Front. Microbiol. 9, 1218. https://​doi.​org/​10.​3389/​fmicb.​2018.​01218 (2018). \n11.\t Alothman, A. A. & Albaqami, M. D. Nano sized Cu (II) and Zn (II) complexes and their use as a precursor for synthesis of CuO and ZnO nanoparticles: A study on their sonochemical synthesis, characterization, and DNA/binding/cleavage, anticancer, and antimicrobial activities. Appl. Organometal. Chem. 34, 5827. https://​doi.​org/​10.​1002/​aoc.​5827 (2020). \n12.\t Karekar, S. E. et al. Synthesis of zinc molybdate and zinc phosphomolybdate nanopigments by an ultrasound assisted route: Advantage over conventional method. Chem. Eng. 87, 51–59. https://​doi.​org/​10.​1016/j.​cep.​2014.​11.​010 (2015). \n13.\t Siddiqi, K. S., Rahman, A. & Husen, A. Properties of zinc oxide nanoparticles and their activity against microbes. Nanoscale Res. Lett. 13, 141. https://​doi.​org/​10.​1186/​s11671-​018-​2532-3 (2018). \n14.\t Agarwal, H., Menon, S., Kumar, S. V. & Rajeshkumar, S. Mechanistic study of the antibacterial action of zinc oxide nanoparticles synthesized using green route. Chemico-Biol. Inter. 286, 60–70. https://​doi.​org/​10.​1016/j.​cbi.​2018.​03.​008 (2018). \n15.\t Burman, U., Saini, M. & Kumar, P. Effect of zinc oxide nanoparticles on growth and antioxidant system of chickpea seedlings. Toxicol. Environ. Chem. 95, 605–612. https://​doi.​org/​10.​1080/​02772​248.​2013.​803796 (2013). \n16.\t Han, H. et al. Recent progress of bacterial FtsZ inhibitors with a focus on peptides. FEBS J. 288, 1091–1106. https://​doi.​org/​10. 1111/​febs.​15489 (2021). \n17.\t Tripathy, S. & Sahu, S. K. FtsZ inhibitors as a new genera of antibacterial agents. Bioorg. Chem. 91, 103–169. https://​doi.​org/​10. 1016/j.​bioorg.​2019.​103169 (2019). \n18.\t Król, E. et al. Antibacterial activity of alkyl gallates is a combination of direct targeting of FtsZ and permeabilization of bacterial membranes. Front. Microbiol. 6, 390. https://​doi.​org/​10.​3389/​fmicb.​2015.​00390 (2015). \n19.\t Molnár, Á. et al. ZnO nanoparticles induce cell wall remodeling and modify ROS/RNS signalling in roots of Brassica seedlings. Ecotoxicol. Environ. Saf. 206, 111–158. https://​doi.​org/​10.​1016/j.​ecoenv.​2020.​111158 (2020). \n20.\t Mendes, C. R. et al. Zeta potential mechanisms applied to cellular immobilization: A study with Saccharomyces cerevisiae on dye adsorption. J. Polym. Environ. 29, 2214–2226. https://​doi.​org/​10.​1007/​s10924-​020-​02030-0 (2021). \n21.\t Balouiri, M., Sadiki, M. & Ibnsouda, S. K. Methods for in vitro evaluating antimicrobial activity: A review. J. Pharm. Anal. 6, 71–79. https://​doi.​org/​10.​1016/j.​jpha.​2015.​11.​005 (2016). \n22.\t Vijayakumara, S., Mahadevana, P., Arulmozhia, S. & Sriramb, P. K. Green synthesis of zinc oxide nanoparticles using Atalantia monophylla leaf extracts: Characterization and antimicrobial analysis. Mater. Sci. Semicond. Process. 82, 39–45. https://​doi.​org/​10. 1016/j.​mssp.​2018.​03.​017 (2018). \n23.\t Subbiah, R., Muthukumaran, S. & Raja, V. Biosynthesis, structural, photoluminescence and photocatalytic performance of $\\mathbf{M}\\mathbf{n}/$ Mg dual doped ZnO nanostructures using Ocimum tenuiforum leaf extract. Optik 208, 156–166. https://​doi.​org/​10.​1016/j.​ijleo. 2020.​164556 (2020). \n24.\t Sheik, M. S., Raj, K. R., Kottaisamy, M. & Vasantha, V. S. Biosynthesis of ZnO nanoparticles through extract from Prosopis julifora plant leaf: Antibacterial activities and a new approach by rust-induced photocatalysis. J. Saudi Chem. Soc. 24, 393–406. https://​ doi.​org/​10.​1016/j.​jscs.​2020.​03.​003 (2020). \n25.\t Khataee, A., Karimi, A., Zarei, M. & Joo, S. W. Eu-doped ZnO nanoparticles: Sonochemical synthesis, characterization, and sonocatalytic application. Ultrason. Sonochem. 24, 393–406. https://​doi.​org/​10.​1016/j.​ultso​nch.​2015.​03.​016 (2015). \n26.\t Sirelkhatim, A. et al. Review on zinc oxide nanoparticles: Antibacterial activity and toxicity mechanism. Nano-Micro Lett. 7, 219–242. https://​doi.​org/​10.​1007/​s40820-​015-​0040-x (2015). \n27.\t Lundstedt, E., Kahne, D. & Ruiz, N. Assembly and maintenance of lipids at the bacterial outer membrane. Chem. Rev. 121, 5098–5123. https://​doi.​org/​10.​1021/​acs.​chemr​ev.​0c005​87 (2020). \n28.\t Anitha, R. et al. Cytotoxicity, antibacterial and antifungal activities of ZnO nanoparticles prepared by the Artocarpus gomezianus fruit mediated facile green combustion method. J. Sci. Adv. Mater. Devices 3, 440–451. https://​doi.​org/​10.​1016/j.​jsamd.​2018.​11.​ 001 (2018). \n29.\t Yusof, N. A. A., Zain, N. M. & Pauzi, N. Synthesis of ZnO nanoparticles with chitosan as stabilizing agent and their antibacterial properties against Gram-positive and Gram-negative bacteria. Int. J. Biol. Macromol. 124, 1132–1136. https://​doi.​org/​10.​1016/j.​ ijbio​mac.​2018.​11.​228 (2019). \n30.\t Saqib, S. et al. Synthesis, characterization and use of iron oxide nano particles for antibacterial activity. Microsc. Res. Technol. 84, 415–420. https://​doi.​org/​10.​1002/​jemt.​23182 (2019). \n31.\t Zubair, N. & Akhtar, K. Morphology controlled synthesis of $\\mathrm{{znO}}$ nanoparticles for in-vitro evaluation of antibacterial activity. Trans. Nonferrous Metals Soc. China 30, 1605–1614. https://​doi.​org/​10.​1016/​S1003-​6326(20)​65323-7 (2020). \n32.\t Du, S., Pichoff, S. & Lutkenhaus, J. FtsEX acts on FtsA to regulate divisome assembly and activity. Proc. Natl. Acad. Sci. 113, 52–61. https://​doi.​org/​10.​1073/​pnas.​16066​56113 (2016). \n33.\t Hurley, K. A. et al. Targeting the bacterial division protein ftsz. J. Med. Chem. 59, 6975–6998. https://​doi.​org/​10.​1021/​acs.​jmedc​ hem.​5b010​98 (2016). \n34.\t Xiao, J. & Goley, E. D. Redefining the roles of the ftsz-ring in bacterial cytokinesis. Curr. Opin. Microbiol. 34, 90–96. https://​doi. org/​10.​1016/j.​mib.​2016.​08.​008 (2016). \n35.\t Dilarri, G., Caccalano, M. N., Zamuner, C. F. C., Domingues, D. S. & Ferreira, H. Hexanoic acid: A new potential substitute for copper-based agrochemicals against citrus canker. J. Appl. Microbiol. 131, 2488–2499. https://​doi.​org/​10.​1111/​jam.​15125 (2021). \n36.\t Abebe, B., Zereffa, E. A., Tadesse, A. & Murthy, H. C. A. A review on enhancing the antibacteril activity of ZnO: Mechanisms and microscopic investigation. Nanoscale Res. Lett. 15, 190. https://​doi.​org/​10.​1186/​s11671-​020-​03418-6 (2020). \n37.\t Naqvi, Q. U. A. et al. Size-dependent inhibition of bacterial growth by chemically engineered spherical ZnO nanoparticles. J. Biol. Phys. 45, 147–159. https://​doi.​org/​10.​1016/j.​ijbio​mac.​2018.​11.​228 (2019). \n38.\t Raj, N. B. et al. Harnessing ZnO nanoparticles for antimicrobial and photocatalytic activities. J. Photochem. Photobiol. 6, 100021. https://​doi.​org/​10.​1016/j.​jpap.​2021.​100021 (2021). \n\n# Acknowledgements \n\nThis study received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)—Brazil. Guilherme Dilarri received a PhD scholarship from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Process—2017/07306-9). Henrique Ferreira received Grant from FAPESP (Process—2015/50162-2). \n\n# Author contributions \n\nC.R.M. and G.D.: conceptualization, methodology, fluorescence microscopy analyses, FT-IR assays, validation, formal analysis, writing original draft; C.F.F., V.M.R.S. and P.R.M.L.: methodology, formal analysis; E.D.B. and H.F.: conceptualization, methodology, funding acquisition, supervision, writing original draft; P.B.d.M.: SEM and X-ray assays, writing original draft; R.N.M.: conceptualization, visualization, writing/review and editing, supervision, funding acquisition, project administration. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nCorrespondence and requests for materials should be addressed to C.R.M. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1002_adma.202202544", + "DOI": "10.1002/adma.202202544", + "DOI Link": "http://dx.doi.org/10.1002/adma.202202544", + "Relative Dir Path": "mds/10.1002_adma.202202544", + "Article Title": "Mesopore-Rich Fe-N-C Catalyst with FeN4-O-NC Single-Atom Sites Delivers Remarkable Oxygen Reduction Reaction Performance in Alkaline Media", + "Authors": "Peng, LS; Yang, J; Yang, YQ; Qian, FR; Wang, Q; Sun-Waterhouse, D; Shang, L; Zhang, TR; Waterhouse, GIN", + "Source Title": "ADVANCED MATERIALS", + "Abstract": "Fe-N-C catalysts offer excellent performance for the oxygen reduction reaction (ORR) in alkaline media. With a view toward boosting the intrinsic ORR activity of Fe single-atom sites in Fe-N-C catalysts, fine-tuning the local coordination of the Fe sites to optimize the binding energies of ORR intermediates is imperative. Herein, a porous FeN4-O-NCR electrocatalyst rich in catalytically accessible FeN4-O sites (wherein the Fe single atoms are coordinated to four in-plane nitrogen atoms and one subsurface axial oxygen atom) supported on N-doped carbon nullorods (NCR) is reported. Fe K-edge X-ray absorption spectroscopy (XAS) verifies the presence of FeN4-O active sites in FeN4-O-NCR, while density functional theory calculations reveal that the FeN4-O coordination offers a lower energy and more selective 4-electron/4-proton ORR pathway compared to traditional FeN4 sites. Electrochemical tests validate the outstanding intrinsic activity of FeN4-O-NCR for alkaline ORR, outperforming Pt/C and almost all other M-N-C catalysts reported to date. A primary zinc-air battery constructed using FeN4-O-NCR delivers a peak power density of 214.2 mW cm(-2) at a current density of 334.1 mA cm(-2), highlighting the benefits of optimizing the local coordination of iron single atoms.", + "Times Cited, WoS Core": 311, + "Times Cited, All Databases": 318, + "Publication Year": 2022, + "Research Areas": "Chemistry; Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000809631500001", + "Markdown": "# Mesopore-Rich Fe–N–C Catalyst with FeN4–O–NC SingleAtom Sites Delivers Remarkable Oxygen Reduction Reaction Performance in Alkaline Media \n\nLishan Peng, Jiao Yang, Yuqi Yang, Fangren Qian, Qing Wang, Dongxiao Sun-Waterhouse, Lu Shang, Tierui Zhang,\\* and Geoffrey I.N. Waterhouse\\* \n\nFe–N–C catalysts offer excellent performance for the oxygen reduction reaction (ORR) in alkaline media. With a view toward boosting the intrinsic ORR activity of Fe single-atom sites in Fe–N–C catalysts, fine-tuning the local coordination of the Fe sites to optimize the binding energies of ORR intermediates is imperative. Herein, a porous $\\mathsf{F e N}_{4}.$ –O–NCR electrocatalyst rich in catalytically accessible $F e N_{4}\\mathrm{-}0$ sites (wherein the Fe single atoms are coordinated to four in-plane nitrogen atoms and one subsurface axial oxygen atom) supported on N-doped carbon nanorods (NCR) is reported. Fe K-edge X-ray absorption spectroscopy (XAS) verifies the presence of $F e N_{4}\\mathrm{-}0$ active sites in $\\mathsf{F e N}_{4}.$ –O–NCR, while density functional theory calculations reveal that the $F e N_{4}\\mathrm{-}0$ coordination offers a lower energy and more selective 4-electron/4-proton ORR pathway compared to traditional $\\mathsf{F e N}_{4}$ sites. Electrochemical tests validate the outstanding intrinsic activity of $\\mathsf{F e N}_{4}$ –O–NCR for alkaline ORR, outperforming $\\mathsf{P t}/\\mathsf{C}$ and almost all other M–N–C catalysts reported to date. A primary zinc–air battery constructed using $\\mathsf{F e N}_{4}$ –O–NCR delivers a peak power density of $274.2\\ m\\times\\min^{-2}$ at a current density of $334.1\\mathsf{m A c m}^{-2}$ , highlighting the benefits of optimizing the local coordination of iron single atoms. \n\nthese applications relies heavily on the efficiency of ORR electrocatalysts.[1] Ptbased catalysts currently offer the best all-round performance attributes for the ORR, though the high cost and modest durability of Pt-based catalysts are obstacles to their sustainable utilization across the energy sector.[2] In recent years, heterogeneous single-atom catalysts (SACs) with $\\mathrm{\\DeltaM{-}N_{x}}$ sites $(\\mathrm{M}=\\mathrm{Fe}$ , Co, Ni, etc.) on carbon supports have emerged as promising ORR catalysts.[3] SACs have the key advantages of a high metal atom utilization efficiency (theoretically $\\approx100\\%$ ), high intrinsic activity, and low cost.[4] Among $\\mathrm{M-N_{x}/C}$ catalysts with different metal centers, Fe– $\\cdot\\mathrm{N}_{4}/\\mathrm{C}$ catalysts deliver the best ORR activity.[5] However, the activity of $\\mathrm{Fe-N_{4}}$ sites is still not optimal, owing to the adsorption energies of oxygen intermediates formed during ORR being slightly too strong.[6] Therefore, optimizing the bonding between the ORR intermediates and the $\\mathrm{Fe-N_{4}}$ sites \n\n# 1. Introduction \n\nThe oxygen reduction reaction (ORR) plays an essential role in many energy conversion and storage devices including fuel cells and metal–air batteries. Device performance in is a rational approach for boosting ORR electrocatalysis over $\\mathrm{Fe-N_{4}/C}$ materials. \n\nModulating the occupancy of d-orbitals in $\\mathrm{Fe-N_{4}}$ sites affects the adsorption energies of the ORR intermediates. The energy levels of $\\mathrm{~d~}$ -orbital in the $\\mathrm{Fe-N_{4}}$ sites are sensitive to the \n\nFe valence state and the local coordination geometry of Fe.[7] Recently, strategies such as coordination number regulation,[8] heteroatom doping,[9] and carbon support defect engineering[10] have been used to tune the d-orbitals (and d-band center position) of Fe cations in $\\mathrm{Fe-N_{4}/C}$ catalysts, thus allowing marked improvements in ORR activity. These approaches seek to break the square planar symmetry of $\\mathrm{Fe-N_{4}}$ sites (by elongating Fe–N bond lengths or moving the Fe center slightly out the $\\mathrm{N}_{4}$ plane), thus reducing the adsorption energy of ORR intermediates. Axial charge redistribution of the Fe centers is particularly effective for regulating the binding strengths between $\\mathrm{Fe-N_{4}/C}$ catalysts and ORR intermediate species, since Fe–O bonding between ORR intermediates and $\\mathrm{Fe-N_{4}}$ sites involves orbital overlap in the axial direction with respect to the $\\mathrm{Fe-N_{4}}$ plane.[11] Some recent experimental and computational studies have suggested that $\\mathrm{Fe-N_{4}}$ sites with an axial ligand $(\\mathrm{X}_{\\mathrm{A}},$ such as OH, Cl, F, Br) show enhanced ORR activity.[5d,12] However, owing to the ionic nature of the bonding of these axial ligands with $\\mathrm{Fe-N_{4}}$ sites, loss of the axial ligands will occur readily during the ORR.[13] To this end, achieving a stable axial charge redistribution at Fe– ${\\bf\\cdot N_{4}}$ sites is of tremendous fundamental and practical significance. If this could be achieved, step-change improvements in the ORR activity of Fe– $\\cdot\\mathrm{N}_{4}/\\mathrm{C}$ catalysts should be possible. \n\nHerein, we developed a novel interface engineering strategy to construct Fe–N–C catalysts in which $\\mathrm{Fe-N_{4}}$ sites were modulated by axial (subsurface) Fe–O bonds. We first prepared O,N-codoped carbon-rods (denoted as O–NCR), which were then functionalized with surface $\\mathrm{Fe-N_{4}}$ sites using a microwaveassisted pyrolysis method. The synthesis method formed stable $\\mathrm{FeN_{4}{-}O{-}N C R}$ heterostructures. The obtained catalyst, denoted herein as $\\mathrm{FeN_{4}{-}O{-}N C R}$ , featured a hierarchically porous architecture, high specific surface area $(1159~\\mathrm{m}^{2}~\\mathrm{g}^{-1})$ and an abundance of $\\mathrm{FeN_{4}{-}O}$ active sites for optimized oxygen adsorption and activation. The obtained $\\mathrm{FeN_{4}{-}O{-}N C R}$ catalyst exhibited remarkable ORR activity and stability in alkaline media $\\begin{array}{r}{(E_{\\mathrm{onset}},}\\end{array}$ $1.050~\\mathrm{V};$ $\\mathrm{E}_{1/2}$ , 0.942  V; $J_{\\mathrm{k}}$ $39.56~\\mathrm{mA}~\\mathrm{cm}^{-2}$ at $0.9\\mathrm{~V~}$ ), state-of-the art performance for a SAC. A primary Zn–air battery constructed using $\\mathrm{FeN_{4}{-}O{-}N C R}$ as the cathode catalyst delivered a very high-power density $(214.2~\\mathrm{mW~cm^{-2}},$ ), greatly surpassing the performance of a battery constructed using a commercial $\\mathrm{Pt/C}$ catalyst $(104.2\\mathrm{mW}\\mathrm{cm}^{-2})$ ) or other recently reported singleatom catalysts. The merits of $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ were probed by theoretical density functional theory (DFT) calculations, wherein the precise tailoring of the d-orbital electronic structure of Fe cations was found to reduce the thermodynamic barrier for ORR. Results confirm that axial ligand regulation is an effective strategy for fine-tuning metal single-atom sites for optimal electrocatalytic activity. \n\n# 2. Results and Discussion \n\nThe synthesis route adopted in the current work for the preparation of the heterostructured $\\mathrm{FeN_{4}{-}O{-}N C R}$ catalyst involved the preparation of O,N-doped carbon nanorods (O–NCR) from a MOF-74 precursor, followed by electrostatic adsorption of an Fe-phenanthroline (Fe-Phen) complex then a rapid microwaveassisted carbonization step (Figure  1a).[14] First, rod-shaped \n\nMOF-74 (MOF-74-Rod) crystals were synthesized by reaction of zinc acetate and 2,5-dihydroxyterephthalic acid in the presence of salicylic acid as a shape modulator.[15] Transmission electron microscopy (TEM, Figure  S1, Supporting Information) showed the rod-shaped MOF-74 crystals to have a high aspect ratio $(\\approx40$ nm wide and 200–400 in length). Carbonization of MOF-74-Rod at $1\\ 000\\ {}^{\\circ}{\\mathrm{C}}$ in an argon flow yielded 1D carbon nanorods (CR). The carbon nanorods inherited the high aspect ratio of the MOF-74-Rod precursor, though with obvious reductions in all dimensions $(\\approx20\\ \\mathrm{nm}$ in width and $200{-}30\\ \\mathrm{nm}$ in length) (Figure  S2, Supporting Information). In addition, the high-temperature carbonization process introduced mesopores in the surface of the carbon rods. Heteroatom doping of CR utilized a molten salt (KOH)-assisted pyrolysis strategy in an $\\mathrm{NH}_{3}$ atmosphere, yielding O,N–doped carbon nanorods (O–NCR) with a porous surface and unsaturated/edge-hosted N–C sites (Figure  S3, Supporting Information). In the final stage of $\\mathrm{FeN_{4}{-}O{-}N C R}$ synthesis, a Fe-Phen complex was electrostatically adsorbed onto the O–NCR support, after which a rapid high-temperature microwave-assisted pyrolysis treatment was performed for $10\\mathrm{~s~}$ in Ar gas. A control catalyst using CR as a support for $\\mathrm{Fe-N_{4}}$ sites was also obtained by the same general procedure (denoted herein as $\\mathrm{FeN_{4}/C R}$ , Figure S4, Supporting Information). The adsorption of the Fe–Phen complex on O–NCR was monitored by Zeta potential measurements. Zeta potentials measured at $\\mathrm{pH}7$ for the Fe–Phen complex $(+35.66~\\mathrm{mV})$ and O–NCR (Zeta potential of $-7.56\\ \\mathrm{mV}$ ) implied that the positively charged complex would adsorb on the negative charged O–NCR. The obtained composite (O–NCR $@$ Fe–Phen) possessed a Zeta potential $+0.58\\ensuremath{\\mathrm{~mV}}$ (Figure  S5, Supporting Information), confirming the successful adsorption of the Fe–Phen complex on the O–NCR surface. In comparison, the adsorption capacity of CR to Fe–Phen is weak as the zeta potential of CR $@$ Fe–Phen was similar to that of Fe–Phen. The size and morphology of $\\mathrm{FeN_{4}{-}O{-}N C R}$ product obtained after the microwave-assisted pyrolysis of O–NCR $@$ Fe–Phen were comparable to those of the O–NCR support (Figure S6, Supporting Information). \n\nThe morphology and pore structure of $\\mathrm{FeN_{4}{-}O{-}N C R}$ were characterized by various techniques. Scanning electron microscopy (SEM) imaging showed $\\mathrm{FeN_{4}{-}O{-}N C R}$ to be composed of nanorods (Figure 1b). TEM imaging revealed that the nanorods were interconnected and possessed a high aspect ratio (Figure  1c). High-resolution TEM (HR-TEM) showed that the individual nanorods contained abundant mesopores $({\\approx}4~\\mathrm{nm}$ in size) that were expected to ensure good mass transport during ORR and offer abundant edge sites for hosting $\\mathrm{Fe-N_{4}}$ (Figure  1d). Nitrogen adsorption and desorption isotherms were collected to determine the BET surface area and pore sizes in $\\mathrm{FeN_{4}{-}O{-}N C R}$ and other reference samples. $\\mathrm{FeN_{4}{-}O{-}N C R}$ exhibited a type-IV isotherm with a well-defined adsorption–desorption hysteresis loop at higher relative pressures (Figure  S7a,b, Supporting Information), confirming a hierarchical microporous/mesoporous structure similar to the O–NCR support.[16] The hysteresis loops for $\\mathrm{FeN_{4}/C R}$ and CR were smaller, indicating the KOH-assisted thermal ammonolysis N-doping step used to create O–NCR from CR introduced micropores (Figure  S7c,d, Supporting Information).[17] FeN4–O–NCR possessed a BET specific surface area of \n\n![](images/cd28c067f817f3575b809cbbf158c64ae42770f0c50f3092a13b544226648b77.jpg) \nFigure 1.  a) Schematic illustration of the synthesis of the $_{\\mathsf{F e N_{4}-O-N C R}}$ catalyst. b) SEM image and c,d) TEM images at low magnification (c) and high magnification (d) for $F e N_{4}{\\mathrm{-}}{\\mathsf{O}}{\\mathrm{-}}{\\mathsf{N C R}}.$ e) BET surface areas, micropore surface areas (calculated from pores of diameter ${<}2{\\mathsf{n m}}$ ) and external surface areas (calculated by subtracting the micropore surface areas from the BET surface areas), and f) pore size distribution curves for ${\\sf F e N}_{4}{\\sf-O-N C R}$ , $F e N_{4}/C R$ , O–NCR, and CR. g) Raman spectra for $F e N_{4}{\\mathrm{-}}{\\mathsf{O}}{\\mathrm{-}}{\\mathsf{N C R}}$ , $F e N_{4}/C R$ , O–NCR, and CR. \n\n$1159~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ , comprising an external surface area of $677{\\mathrm{~m}}^{2}{\\mathrm{~g}}^{-1}$ and a micropore area of $483~\\mathrm{m}^{2}~\\mathrm{g}^{-1}$ (Figure  1e). The specific surface area of $\\mathrm{FeN_{4}/C R}$ $(1007~\\mathrm{m}^{2}~\\mathrm{g}^{-1})$ was significantly lower than that of $\\mathrm{FeN_{4}{-}O{-}N C R}$ mainly due to the smaller external surface area (Table S1, Supporting Information). The pore size distribution curves in Figure  1f confirmed that micropores and mesopores with pore diameters of ${\\approx}0.6\\mathrm{-}1.8~\\mathrm{nm}$ and ${\\approx}2.6-$ $4.4\\ \\mathrm{nm}$ , respectively, coexisted in $\\mathrm{FeN_{4}{-}O{-}N C R}$ , $\\mathrm{FeN_{4}/C R_{:}}$ , O– NCR, and CR. $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C R}$ was richer in micropores and mesopores than $\\mathrm{FeN_{4}/C R}$ , which was expected to create more active sites, facilitate mass transport and promote the utilization of active sites during ORR.[18] The micropore surface areas for $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ were both ${\\approx}25\\%$ lower than those of the corresponding O–NCR and CR supports, respectively (Table S1, Supporting Information). This implies that the Fe single atoms were likely located in the micropores, leading to a reduction in micropore volumes, micropore surface areas, and specific surface areas after $\\mathrm{FeN}_{4}$ hosting. After functionalization with Fe single atoms, the external surfaces areas for both $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ were increased slightly compared to values for the corresponding bare supports, which is again consistent with Fe occupancy of micropores. Further, carbonization of the adsorbed Fe-Phen complex (i.e., $\\mathrm{Fe}(\\mathsf{o}{\\cdot}\\mathsf{p h e n})_{3}{}^{3+})$ to create the $\\mathrm{FeN}_{4}–\\mathrm{O}$ and $\\mathrm{FeN}_{4}$ sites on in $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN}_{4}/\\mathrm{C}$ , respectively, is expected to generate additional N-doped carbon debris, which may also have contributed to the slight increase in external surface area after the introduction of the Fe single atoms. Raman spectra (Figure 1g) for the same samples showed the characteristic disordered D-band $(1335~\\mathrm{cm}^{-1})$ and graphitic carbon-related G-band $(1580~\\mathrm{cm^{-1}})$ signals.[19] The $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratio for O–NCR (0.97) was slightly higher than that of CR (0.95), suggesting that the KOH-assisted thermal ammonolysis treatment created defects (likely in-plane holes and C–N edge sites). The $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ samples had the same $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratio (0.99), suggesting a similar carbon network structure after hosting $\\mathrm{FeN}_{4}$ moieties. \n\nThe X-ray diffraction (XRD) patterns for the $\\mathrm{FeN_{4}{-}O{-}N C R}$ , $\\mathrm{FeN_{4}/C R}$ , O–NCR, and CR samples contained two broad peaks centered around $25^{\\circ}$ and $44^{\\circ}$ (Figure  S8, Supporting Information), readily attributable to the (002) and (101) reflections of graphitized carbon. No Fe nanoparticles, Fe oxide phases, or Fe carbide phases were detected for the $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ samples. Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM, Figure 2a) showed that Fe in $\\mathrm{FeN_{4}{-}O{-}N C R}$ was atomically dispersed over the O–NCR support. Energy-dispersive X-ray (EDX) mapping images confirmed that C, N, O, and Fe were distributed uniformly in $\\mathrm{FeN_{4}{-}O{-}N C R}$ (Figure  2b). Inductively coupled plasma mass spectrometry (ICP-MS) determined that the Fe loading in $_{\\mathrm{FeN_{4}-O-N C R}}$ and $\\mathrm{FeN_{4}/C R}$ were similar (0.89 and $0.92\\ \\mathrm{wt.\\%}$ , respectively, Table  S2, Supporting Information). X-ray photoelectron spectroscopy (XPS) was performed to investigate the near-surface region chemical composition and element speciation in the samples. $\\mathrm{FeN_{4}{-}O{-}N C R}$ possessed a higher N content $(1.39\\ a t.\\%)$ than $\\mathrm{FeN_{4}/C R}$ $(0.73\\ \\mathrm{at.\\%})$ , which was expected due to the prenitridation of the carbon support in $\\mathrm{FeN_{4}{-}O{-}N C R}$ . High-resolution $\\mathrm{~N~}$ 1s XPS spectra for the samples showed the presence of four peaks, which were readily assigned to pyridinic N (398.3–398.6  eV), pyrrolic N $(400.1\\ \\mathrm{eV})$ , graphitic N (401.5  eV), and N-oxide (403.1  eV) species (Figure  2c).[20] The N 1s XPS spectra for CR showed no obvious signals, as was expected since CR sample did not contain nitrogen (Figure  S9, Supporting Information). The pyridinic N peaks for $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ were at slightly higher binding energy compared with the pyridinic-N peak for O–NCR, suggesting that Fe coordination involved the formation of Fe-pyridinic N bonds.[21] The smaller shift in the pyridinic N peak position for $\\mathrm{FeN_{4}{-}O{-}N C R}$ compared with $\\mathrm{FeN}_{4}/$ CR suggested a slightly different coordination environment of Fe atoms. In the O 1s XPS spectrum of $\\mathrm{FeN_{4}{-}O{-}N C R}$ , an additional peak was seen ${\\approx}530~\\mathrm{eV}$ due to Fe–O bond formation (Figure S10a,b, Supporting Information), which was conspicuously absent in the O 1s spectrum of $\\mathrm{FeN_{4}/C R}$ . The data for $\\mathrm{FeN_{4}{-}O{-}N C R}$ thus implied that Fe sites in the sample contained both Fe–N and Fe–O bonding.[22] The Fe 2p XPS spectra for $_{\\mathrm{FeN_{4}-O-N C R}}$ and $\\mathrm{FeN_{4}/C R}$ showed no obvious Fe signals (Figure  S10c,d, Supporting Information). This is attributed to the Fe loadings in the samples being very low ( $_{<1}$ wt. $\\%$ , i.e., at the detection limits of the technique) and XPS only probing the near surface region (top few nanometers) in the samples. \n\n![](images/efa35f871e7c96eb775bd6eadfe1b4b9c257c376218ad4400fc06ed0b63a4956.jpg) \nFigure 2.  a) AC HAADF-STEM images for $\\mathsf{F e N}_{4}$ –O–NCR. The Fe atoms are marked by the red circles, and the pore edges of graphene are marked by the orange dashed lines. b) HAADF-TEM image and corresponding element mapping images for FeN4–O–NCR. c) High-resolution N 1s XPS spectra for $F e N_{4}\\mathrm{-}O\\mathrm{-}N C R$ , $\\mathsf{F e N}_{4}/\\mathsf{C R}$ , and O–NCR. d) Fe K-edge X-ray absorption near-edge structure spectra, e) FT $\\mathsf{k}^{2}$ -weighted EXAFS spectra, and f) wavelet transforms for the $\\mathsf{k}^{2}$ -weighted Fe K-edge EXAFS signals for $F e N_{4}-O-N C R$ , $F e N_{4}/C R$ and the reference samples of bulk Fe, $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ , and FePc. g) FT-EXAFS fitting for the FeN $_4$ –O–NCR catalyst in R space (inset: proposed schematic model for $\\mathsf{F e N}_{4}{\\mathsf{-O-N C R}})$ . \n\nThe detailed atomic structure and electronic states of $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ were probed by Fe K-edge X-ray absorption spectroscopy (XAS). The oxidation state of Fe atoms in each sample was first analyzed using Fe K-edge X-ray absorption near edge spectroscopy (XANES) (Figure  2d). The Fe K-edge XANES spectra for $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ were located between those of the Fe foil and ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}$ reference samples and were close to that of iron phthalocyanine (FePc), suggesting the presence of cationic Fe states in the samples.[22] The valence state of Fe in $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ were estimated from their corresponding XANES derivative spectra, with the fitting results indicating the average Fe oxidation state in $\\mathrm{FeN_{4}{-}O{-}N C R}$ $(+2.7)$ was higher than the average Fe oxidation state in $\\mathrm{FeN}_{4}/\\mathrm{C}$ $(+2.4)$ (Figure  S11, Supporting Information). A higher average Fe valence state in $\\mathrm{FeN_{4}{-}O{-}N C R}$ is consistent with an additional axial oxygen ligand bound to Fe. For $\\mathrm{FeN}_{4}.$ -centered macrocycles, there are two characteristic Fe K-edge features (labeled as A and B) at photon energies ${\\approx}7132\\ \\mathrm{eV}$ and $\\approx7140\\ \\mathrm{eV}.$ . The relative intensity of the two peaks $(I_{\\mathrm{A}}/I_{\\mathrm{B}})$ is sensitive to the distortion degree of the $\\mathrm{FeN}_{4}$ square-planarity and also the coordination environment of N in the $\\mathrm{FeN}_{4}$ structures. The difference seen in the $I_{\\mathrm{A}}/I_{\\mathrm{B}}$ ratio between the Fe–N–C catalysts and FePc is mainly due to the different $\\mathrm{~N~}$ type, i.e., pyridinic-type $\\mathrm{~N~}$ in the Fe–N–C catalysts and pyrrolic-type N in FePc. As for the Fe–O–NCR and $\\mathrm{FeN}_{4}/$ CR catalysts, both of which were derived from Fe–Phen, the $\\mathrm{Fe-N_{4}}$ sites in both these Fe–N–C materials contained pyridinic N, with their XANES spectra in the photon energy range $7130{\\-}7140{\\ }\\mathrm{eV}$ being very similar. The $\\mathrm{Fe-N_{4}}$ structures of both Fe–O–NCR and $\\mathrm{FeN_{4}/C R}$ catalysts were not absolutely planar, with the distortion degree for Fe–O–NCR $\\left(I_{\\mathrm{A}}/I_{\\mathrm{B}}=1.05\\right)$ ) and $\\mathrm{FeN_{4}/C R}$ $(I_{\\mathrm{A}}/I_{\\mathrm{B}}=1.04)$ being very similar.[23] Results suggest that the presence of the axial oxygen atom bound to Fe in Fe–O–NCR did not really affect the $\\mathrm{FeN}_{4}$ planarity (though as seen in Figure S11, Supporting Information, significantly increased the Fe valency). Fourier transformed (FT) $\\mathrm{k}^{3}$ -weighted $\\chi(\\mathrm{k})$ -function Fe K-edge extended X-ray absorption fine structure (EXAFS) analyses provided detailed information about the local coordination of Fe sites in $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ (Figure  2e). The Fe K-edge EXAFS spectra for $\\mathrm{FeN}_{4}$ –O–NCR and $\\mathrm{FeN_{4}/C R}$ both showed a prominent peak at ${\\approx}1.5\\mathrm{~\\AA~}$ , consistent with the first Fe–N shell in the FePc reference or the first Fe–O shell in $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ . No features were seen at ${\\approx}2.2\\mathrm{~\\AA~}$ (typically for Fe–Fe in Fe foil) or ${\\approx}2.5$ Å (typical for the first Fe–Fe shell in $\\mathrm{Fe}_{2}\\mathrm{O}_{3},$ ), indicating that Fe atoms in $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ were stabilized in the form of $\\mathrm{Fe-N_{x}}$ or $\\mathrm{FeN_{x}{-}O}$ . Wavelet transformed (WT) EXAFS is a useful tool for identifying the $k$ and $R$ dependence of absorption signals simultaneously, thus is capable of distinguishing heavier and lighter backscattering atoms.[24] The $k^{3}$ -weighted WT EXAFS spectra for $\\mathrm{FeN_{4}/C R}$ showed a contour profile in $k$ -space similar to that of FePc with the contour intensity maximum at $3.2\\ \\mathring{\\mathrm{A}}^{-1}$ (Figure  2f ), implying $\\mathrm{FeN_{4}/C R}$ possessed a comparable Fe coordination to FePc (i.e., $\\mathrm{FeN}_{4})$ . The contour intensity maximum for $\\mathrm{FeN_{4}{-}O{-}N C R}$ also resembled $\\mathrm{FeN_{4}/C R}$ , but was shifted slightly toward that of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ suggesting the existence of a Fe–O bond in the $\\mathrm{FeN_{4}{-}O{-}N C R}$ sample.[25] Quantitative structural configuration information for these samples were extracted by least-squares EXAFS curvefitting analyses (Figures $2\\mathrm{g};$ Figures S12–S16 and Table S3, Supporting Information). The first coordination shell of $\\mathrm{FeN_{4}/C R}$ could be fitted by a Fe–N scattering path with a Fe coordination number of 4.02, implying that the central Fe sites possessed a well-defined $\\mathrm{FeN}_{4}$ configuration. In contrast, the data for $\\mathrm{FeN_{4}{-}O{-}N C R}$ was best-fitted by a mixture of Fe–N and Fe–O coordination paths, with Fe coordination numbers of 3.87 (N) and 0.89 (O), respectively. This implies that the central Fe sites in the $\\mathrm{FeN_{4}{-}O{-}N C R}$ possessed a $\\mathrm{FeN}_{4}\\mathrm{O}$ configuration, i.e., near square planar $\\mathrm{FeN}_{4}$ moieties with one axial oxygen atom. The average Fe-N distances in R-space were 1.97 and $1.99\\mathring{\\mathrm{A}}$ for $\\mathrm{FeN_{4}{-}O{-}N C R}$ and $\\mathrm{FeN_{4}/C R}$ , respectively, again suggesting that the axial O bound to Fe in in $\\mathrm{FeN_{4}{-}O{-}N C R}$ did not change the $\\mathrm{FeN}_{4}$ planarity very much. As the same synthesis method was used to introduce $\\mathrm{FeN}_{4}$ moieties on the surface of CR and O–NCR, the additional Fe–O coordination of Fe sites in $\\mathrm{FeN_{4}{-}O{-}N C R}$ must have originated from oxygen atoms originally present on the surface of the O–NCR support (i.e., the axial oxygen atom in $\\mathrm{FeN_{4}{-}O{-}N C R}$ must have been due to subsurface oxygen bridging graphene layers in the O–NCR support rather than post-synthetic adsorption of axial O-containing groups such as water or hydroxyl). To better understand this, DFT calculations were conducted to establish the preferred adsorption site of Fe–Phen on the surface of O–NCR during the pyrolysis treatment. The absolute values of the adsorption energy of Fe–Phen on O sites of O–NCR were all much larger than for adsorption of Fe–Phen on the C or N sites (Figure S17, Supporting Information), confirming that Fe–Phen would preferentially adsorb on the O sites of O–NCR creating axial (subsurface) Fe–O bonds. This would lead to the creation of $\\mathrm{FeN}_{4}–\\mathrm{O}$ active sites during the subsequent microwave-assisted pyrolysis step used to transform Fe–Phen/O–NCR to $\\mathrm{FeN_{4}{-}O{-}N C R}$ . \n\nRing disk electrode (RDE) tests were first performed to assess the catalytic performance of the as-synthesized catalysts using a typical three-electrode system in $0.1\\textbf{M}$ KOH. All the potentials obtained by the RDE tests were calibrated with respect to the RHE and corrected with $90\\%$ iR-compensation unless otherwise specified. From the cyclic voltammetry (CV) curves, $\\mathrm{FeN_{4}{-}O{-}N C R}$ exhibited an obvious $\\mathrm{O}_{2}$ reduction peak in the $\\mathrm{O}_{2}$ -saturated electrolyte and the highest cathodic peak current density among the control catalysts (including $\\mathrm{FeN}_{4}/$ CR) (Figure  S18, Supporting Information). This suggested $\\mathrm{FeN_{4}{-}O{-}N C R}$ possessed both a high intrinsic ORR activity and excellent mass transport properties. $\\mathrm{FeN}_{4}.$ –O–NCR delivered an extremely impressive ORR onset potential $\\left(E_{\\mathrm{onset}}\\right)$ of $1.050\\mathrm{~V~}$ and a half-wave potential $(E_{1/2})$ of $0.942\\mathrm{~V~}$ in linear sweep voltammetry (LSV) measurements (Figure  3a), outperforming $\\mathrm{FeN_{4}/C R}$ (0.999 and $0.890~\\mathrm{V},$ respectively), O–NCR (0.935 and 0.837 V, respectively), CR (0.924 and $0.803\\mathrm{~V},$ respectively), $\\mathrm{Pt/C}$ (0.995 and $0.867\\mathrm{V},$ respectively), and almost all $\\mathrm{M-N_{x}/C}$ SACs reported to date (Table S4, Supporting Information). Moreover, $\\mathrm{FeN_{4}{-}O{-}N C R}$ exhibited a remarkable kinetic current density of $39.56\\mathrm{mAcm}^{-2}$ at 0.9 V $(J_{\\mathrm{k}},$ Figure 3b), which was 10.4 times higher than $\\mathrm{FeN_{4}/C R}$ $(3.80\\mathrm{mA}\\mathrm{cm}^{-2})$ ) and 19.8 times higher than $\\mathrm{Pt/C}$ $(2.00\\mathrm{mA}\\mathrm{cm}^{-2})$ ). The outstanding ORR activity of $\\mathrm{FeN_{4}{-}O{-}N C R}$ was exemplified by its low Tafel slope of $54.3~\\mathrm{\\mV}$ dec−1 (Figure 3c), lower than the Tafel slopes for $\\mathrm{Pt/C}$ $\\mathrm{/71.1mV~dec^{-1}})$ 1 and $\\mathrm{FeN_{4}/C R}$ $(62.5\\ \\mathrm{mV\\dec^{-1})}$ . Further, the electrochemically active surface area (ECSA) of $\\mathrm{FeN_{4}{-}O{-}N C R}$ $(31.6~\\mathrm{mF~cm^{-2}})$ was approximately twice that of $\\mathrm{FeN_{4}/C R}$ $(15.1~\\mathrm{mF}~\\mathrm{cm}^{-2})$ ), which is explained by the highly porous structure of $\\mathrm{FeN_{4}{-}O{-}N C R}$ that was beneficial for good mass transport during ORR. (Figure  S19, Supporting Information).[16c] The RDE tests thus verified that $\\mathrm{FeN_{4}{-}O{-}N C R}$ is an outstanding ORR catalyst under alkaline conditions. \n\n![](images/df085e72df4a4c66de6264ed98d98926f9ac2fb0ddde70d5fe0d7e9373c87a12.jpg) \nFigure 3.  a) LSV curves, b) comparison of $E_{1/2}$ and $j_{\\boldsymbol{\\mathrm{k}}}$ at $0.9\\mathrm{~V~}$ versus RHE, c) Tafel slope, and d) ${\\sf H}_{2}{\\sf O}_{2}$ yield and electron transfer number (n) for $_{\\mathsf{F e N_{4}-O-N C R}}$ , $F e N_{4}/C R$ , O–NCR, CR, and $\\mathsf{P t}/\\dot{\\mathsf{C}}$ in 0.1 m KOH. e) Normalized $_{i-t}$ curves of $\\mathsf{F e N}_{4}{\\mathsf{-O-N C R}}$ , $F e N_{4}/C R_{:}$ , and $\\mathsf{P t}/\\mathsf{C}$ at $0.7\\:\\vee$ (vs RHE) under a rotating rate of 1600 rpm. f) Normalized $_{i-t}$ curves of $F e N_{4}-O-N C R$ , $F e N_{4}/C R$ , and $\\mathsf{P t/C}$ at $0.7\\mathrm{V}$ (vs RHE) and 1600 rpm with $25\\%$ (volume percentage) methanol addition around $300\\mathrm{~s~}$ . \n\nThe selectivity of the electrocatalysts during ORR was next investigated. Hydrogen peroxide $\\mathrm{(H}_{2}\\mathrm{O}_{2})$ yields during ORR were investigated by rotating ring-disk electrode (RRDE) tests, thus allowing examination of the ORR pathway. $\\mathrm{FeN_{4}{-}O{-}N C R}$ showed a $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield below $4\\%$ over a wide range of potentials, whereas $\\mathrm{FeN_{4}/C R}$ produced a much higher $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield at all potentials studied (Figure  3d). The average electron transfer number for $\\mathrm{FeN_{4}{-}O{-}N C R}$ was calculated to be ${\\approx}3.96{\\$ in the potential range from 0.2 to $\\phantom{0.8}0.8\\mathrm{~V},$ indicating an unusually high selectively for oxygen reduction to $\\mathrm{\\OH^{-}}$ through a 4 $\\mathrm{e^{-}}$ pathway. This result is consistent with the calculation results from the Koutecký–Levich (KL) plots (Figure  S20, Supporting Information), where the average electron transfer number for $\\mathrm{FeN_{4}{-}O{-}N C R}$ was close to 4.0 at all potentials studied. In comparison, the control samples $\\mathrm{FeN_{4}/C R}$ , O–NCR and CR showed inferior selectivity toward the 4-electron ORR pathway. The ORR stability of $\\mathrm{FeN_{4}{-}O{-}N C R}$ was next investigated by chronoamperometry tests at a potential of $0.5{\\mathrm{~V~}}$ (vs RHE) and CV cycling at potentials between $0.6{-}1.0\\mathrm{~V~}$ (vs RHE) with a scan rate of $50\\mathrm{mVs^{-1}}$ . $\\mathrm{FeN_{4}{-}O{-}N C R}$ exhibited a current retention of $96\\%$ after 20 000 s chronoamperometry (Figure 3e), with only a $5~\\mathrm{mV}$ degradation in $E_{1/2}$ after $5000~\\mathrm{CV}$ cycles (Figure  S21, Supporting Information), indicating that the catalyst possessed excellent stability. As shown in Figure  S22 (Supporting Information), the Fe K-edge XANES spectra of $\\mathrm{FeN_{4}{-}O{-}N C R}$ before and after the ORR stability test were identical. Further, the FTEXAFS fitting results revealed that $\\mathrm{FeN_{4}{-}O{-}N C R}$ after the ORR stability test ( $\\mathrm{FeN}_{4}$ –O–NCR–ADT) retained its original structure:, i.e., approximately square planar $\\mathrm{FeN}_{4}$ sites with one axial oxygen atom bound to Fe (Table S3, Supporting Information). Furthermore, $\\mathrm{FeN_{4}{-}O{-}N C R}$ showed outstanding methanol resistance with negligible current decay observed after injecting methanol into the electrolyte (Figure 3f). \n\nMotivated by its superior ORR activity, $\\mathrm{FeN_{4}{-}O{-}N C R}$ was applied as the air-electrode catalyst in an aqueous primary zinc–air battery (ZAB) to assess its practical utility in energy devices (Figure  4a). The open–circuit voltage of the Zn–air battery assembled using the $\\mathrm{FeN_{4}{-}O{-}N C R}$ catalyst was 1.51  V (Figure  S23, Supporting Information), higher than that of \n\nZABs constructed using the $\\mathrm{FeN_{4}/C R}$ (1.47  V) or $\\mathrm{Pt/C}$ (1.42  V) catalysts. The ZAB constructed using $\\mathrm{FeN_{4}{-}O{-}N C R}$ exhibited a truly impressive peak power density of $214.2\\ensuremath{\\mathrm{\\mw}}\\ensuremath{\\mathrm{\\cm}}^{-2}$ at $334.1\\mathrm{\\mA\\cm^{-2}}$ (Figure  4b), appreciably higher than the peak power densities of ZABs based on $\\mathrm{FeN_{4}/C R}$ $(174.6~\\mathrm{mW}~\\mathrm{cm}^{-2}$ at $289.5~\\mathrm{mA}~\\mathrm{cm}^{-2}$ ), $\\mathrm{Pt/C}$ $104.2\\mathrm{~mw}\\mathrm{cm}^{-2}$ at $228.5\\mathrm{\\mA\\cm^{-2}}.$ ), and other recently reported SAC-based electrocatalysts (Table  S5, Supporting Information). From the discharge curves at various current densities (Figure 4c), the ZAB containing $\\mathrm{FeN_{4}{-}O{-}N C R}$ delivered higher voltages at all current densities compared to ZABs based on $\\mathrm{FeN_{4}/C R}$ , O–NCR, and $\\mathrm{Pt/C}$ . The performance difference between $\\mathrm{FeN_{4}{-}O{-}N C R}$ and the other catalysts was more pronounced at higher current densities (i.e., practically useful current densities), further highlighting the superiority of $\\mathrm{FeN_{4}{-}O{-}N C R}$ as an ORR electrocatalyst. The ZAB based on $\\mathrm{FeN_{4}{-}O{-}N C R}$ delivered a specific energy density of 1016  Wh $\\mathrm{kg_{Zn}}^{-1}$ at $20\\mathrm{\\mA\\cm^{-2}}$ (Figure  4d), exceeding ZABs using $\\mathrm{FeN_{4}/C R}$ (944 Wh $\\mathrm{kg_{Zn}}^{-1})$ or $\\mathrm{Pt/C}~(863~\\mathrm{Wh}~\\mathrm{kg_{Zn}}^{-1})$ catalysts and approaching the maximum theoretical energy density of a ZAB $(1086~\\mathrm{{Wh}~{k g_{Z n}}^{-1})}$ . \n\nThe key role of axial (subsurface) Fe–O in enhancing the ORR activity of the $\\mathrm{FeN_{4}{-}O{-}N C R}$ catalyst was further examined by DFT calculations. Possible structures for $\\mathrm{FeN_{4}{-}O{-}N C R}$ were first modeled by DFT calculations, with the various proposed structures listed in Figure  S22 (Supporting Information). The observed Fe–O bond length of ${\\approx}2.10\\mathrm{~\\AA~}$ by EXAFS experiments ruled out all structures with adsorbed hydroxyl $\\scriptstyle\\mathrm{(FeN_{4}-O H/N C}$ , $\\mathrm{Fe-O}\\approx1.80\\mathrm{~\\AA~}$ ) or adsorbed oxygen atoms $\\mathrm{FeN_{4}\\mathrm{-}O/N C}$ , Fe–O ${\\approx}1.65\\mathrm{~\\AA})$ at Fe sites, since these structures possessed very small Fe–O bond distances (Figure  S25, Supporting Information). Therefore, the only realistic structure was the N-doped graphene bilayer (O-bridged) $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ structures (Figure  S22c,d, Supporting Information), in which the Fe–O bond lengths of $\\mathrm{FeN_{4}{-}O{-}N_{p d}C}$ $(\\approx2.08{\\mathring\\mathrm{\\A}})$ and $\\mathrm{FeN_{4}{-}O{-}N_{p r}C}$ $({\\approx}1.97\\mathrm{\\AA})$ were similar to experimental observations (subscripts pd and pr refer to pyridinic N and pyrrolic N, respectively). The O-bridged $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ structure was more thermodynamically stable than the $\\mathrm{FeN_{4}/N C}$ structure (Figure  S26, Supporting Information), indicating the formation of $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ structure was completely feasible. To validate the intrinsic activity of the proposed $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ structures, we calculated Gibbs free energy profiles for the ORR elementary steps on the $\\mathrm{FeN}_{4}/\\mathrm{C}$ , $\\mathrm{FeN_{4}/N C}$ , and $\\mathrm{FeN_{4}\\mathrm{-O-NC}}$ models at $1.23~\\mathrm{V}.$ The optimized structure of the ORR intermediates $\\mathrm{\\mathrm{^{*}O}}_{2},\\mathrm{\\mathrm{^{*}O O H}},\\mathrm{\\mathrm{^{*}O}},\\mathrm{\\mathrm{^{*}O H}})$ on $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ are depicted in Figure  5a. As shown in Figure  5b, the potential limiting step (PLS) for most of models was the final $^{*}\\mathrm{OH}$ desorption step, with the exception being the $\\mathrm{FeN_{4}\\mathrm{-}O/C}$ model. The optimal free energy changes of the potential limiting step $(\\Delta G_{\\mathrm{PLS}}$ were $0.34~\\mathrm{\\eV}$ on $\\mathrm{FeN_{4}{-}O{-}N_{p d}C}$ and $0.44~\\mathrm{{\\eV}}$ on $\\mathrm{FeN_{4}{-}O{-}N_{p r}C)}$ were lower than the corresponding values for the $\\mathrm{FeN}_{4}/\\mathrm{C}$ and three $\\mathrm{FeN_{4}/N C}$ structures. Although the $\\Delta G_{\\mathrm{PLS}}$ over the $\\mathrm{FeN_{4}\\mathrm{-}O/C}$ and $\\mathrm{FeN_{4}{-}O/N_{g r}C}$ structure were close to that of $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ , the $\\mathrm{FeN_{4}\\mathrm{-O/C}}$ and $\\mathrm{FeN_{4}\\mathrm{-O/N_{gr}C}}$ structures will not exist in alkaline environments since the O ligands will be protonated and converted into OH ligands (subscripts gr refer to graphitic N).[12c,26] The resulting $\\mathrm{FeN_{4}\\mathrm{-OH/C}}$ and $\\mathrm{FeN}_{4}-$ $\\mathrm{{OH/N_{gr}C}}$ structures delivered the highest $\\Delta G_{\\mathrm{PLS}}$ values of 0.84 and $1.00\\ \\mathrm{eV},$ respectively, indicating poor ORR performance. The DFT results conclusively demonstrate that $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ offered the highest intrinsic activity for ORR, in excellent agreement with the experimental findings. \n\n![](images/682db35e59ed186dcebe974527dc42e120c28bfd2f8aa19e9e3dc3a166aa6941.jpg) \nFigure 4.  a) Schematic illustration of a primary aqueous Zn–air battery. b) Discharge polarization and power density curves of ZABs constructed using $F e N_{4}-O-N C R$ , ${\\sf F e N}_{4}/{\\sf C}{\\sf R},$ or $\\mathsf{P t/C}$ as the air electrode, respectively. c) Galvanostatic discharge curves of the aqueous ZABs at various current densities. d) Galvanostatic discharge curves of the aqueous ZABs at a current density of $20\\mathsf{m A}\\mathsf{c m}^{-2}$ . The specific energy was calculated based on the mass of consumed $Z n$ . \n\nFurther DFT calculations were performed to investigate the origin of the enhanced ORR activity of the $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ catalyst. Adsorption free energies for $\\mathrm{\\\"{ooH}}$ , $^{*}\\mathrm{O}$ , and $^{*}\\mathrm{OH}$ $[\\Delta G_{\\mathrm{*OOH}}$ $\\Delta G_{\\mathrm{*_{O}}}$ , and $\\Delta G_{\\mathrm{*OH}})$ ) on the different $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ structural models are summarized in Table S6 (Supporting Information). Excellent linear correlations were found between $\\Delta G_{\\mathrm{*OOH}}$ and $\\Delta G_{\\mathrm{*OH}}$ , and also $\\Delta G_{\\mathrm{*_{O}}}$ and $\\Delta G_{\\mathrm{*OH}}$ (Figure  5c).[27] The linearity of these plots suggested that $\\Delta G_{*\\mathrm{OH}}$ is an effective descriptor of the ORR overpotential, leading to the volcano plot in Figure 5d. The Fe centers in $\\mathrm{Fe-N_{4}/C}$ and $\\mathrm{Fe-N_{4}/N C}$ bind $^{*}\\mathrm{OH}$ too strongly (left side of the maximum in the volcano plot), while $\\mathrm{\\mathrm{^{*}O H}}$ binding is weakened in the presence of a simple axial O ligand (right side of the maximum in the volcano plot). The optimum $\\Delta G_{\\mathrm{*_{OH}}}$ is found for the Fe centers in $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ with O atoms bridging between N-doped graphene sheets (i.e., subsurface O), thus delivering a very high ORR activity. In order to gain deep insights into the role of the bridging O atoms in tailoring the Fe energy levels and boosting the OOR catalytic activity, we further investigated the charge density and projected density of states (PDOS) of the different catalysts. Interestingly, the interaction between $\\mathrm{FeN}_{4}$ and subsurface O bridging between N-doped graphene sheets gave Fe cations in $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ a unique electronic structure as the active site for ORR. Coordination to a bridging O atom (Figures  S27–S29, Supporting Information) shifted the d-band center of the Fe-3d orbitals to more negative energy relative to traditional $\\mathrm{FeN}_{4}$ sites (Figure  5e; Figure  S30, Supporting Information). As a result, the antibonding states of $\\mathrm{FeN_{4}\\mathrm{-}O\\mathrm{-}N C}$ and adsorbed species were less occupied, thus weakening the adsorption of ORR intermediates (moving toward to apex in the volcano plot in Figure 5d) and enhancing overall ORR kinetics. \n\n![](images/730ac90a6e8ad3e9512f5b25bb7e8471826411f7c9c5062c7bd9f3727043b2ae.jpg) \nFigure 5.  a) Proposed ORR mechanism on the $F e N_{4}{\\mathrm{-}}{\\mathsf{O}}{\\mathrm{-}}{\\mathsf{N C}}$ catalyst. b) Free energy diagram for oxygen reduction reaction (ORR) on various $F e N_{4}-$ based models. c) Scaling relationships between the adsorption free energies of ${}^{*}{\\mathsf{O H}}$ $(\\Delta G_{\\mathrm{*OH}})$ and $^{*}\\mathrm{O}$ $(\\Delta G_{\\ast_{\\mathrm{O}}})$ (cyan line) or $\\mathrel{\\mathrm{\\cdots}}\\boldsymbol{\\mathrm{OOH}}$ $(\\Delta G_{\\mathrm{*OOH}})$ (orange line). d) Volcano plot between $\\Delta G_{\\mathrm{*OH}}$ and the ORR overpotential $(\\eta_{\\tt O R R})$ , e) Scaling relationships between the $\\eta_{\\tt O R R}$ and d-band center of Fe-3d orbits for the $\\mathsf{F e N}_{4}$ –based structures. Subscripts pd, pr, and gr refer to pyridinic N, pyrrolic N, and graphitic N. \n\n# Acknowledgements \n\nL.P. and J.Y. contributed equally to this work. GINW was supported by a James Cook Research Fellowship, administered by the Royal Society Te Apārangi. This work received additional financial support from the MacDiarmid Institute for Advanced Materials and Nanotechnology, the Energy Education Trust of New Zealand, a generous philanthropic donation from Greg and Kathryn Trounson, the National Key Projects for Fundamental Research and Development of China (2018YFB1502002), the National Natural Science Foundation of China (51825205, 51772305, 21871279, and 21902168), the Beijing Natural Science Foundation (2191002), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB17000000), the Royal Society-Newton Advanced Fellowship (NA170422), the International Partnership Program of Chinese Academy of Sciences (GJHZ201974), the K. C. Wong Education Foundation, and the Youth Innovation Promotion Association of the CAS. \n\nOpen access publishing facilitated by The University of Auckland, as part of the Wiley - The University of Auckland agreement via the Council of Australian University Librarians. \n\n# Conflict of Interest \n\nThe authors declare no conflict of interest. \n\n# 3. Conclusion \n\nA novel $\\mathrm{FeN_{4}{-}O{-}N C R}$ catalyst was synthesized, which contained Fe single-atom sites immobilized on porous N-doped carbon-rods, wherein the Fe atoms were coordinated by four in-plane $\\mathrm{~N~}$ atoms and one axial oxygen atom (subsurface O bridging between N-doped graphene sheets). The addition of the axial bridging oxygen atom increased the average Fe valence and lowered the d-band center position compared to conventional square-planar $\\mathrm{FeN}_{4}$ sites present in most Fe–N–C SACs, favorably tuning the adsorption energies of ORR intermediates for optimal ORR activity. Owing to the high intrinsic ORR activity of the $\\mathrm{FeN}_{4}–\\mathrm{O}$ sites, the $\\mathrm{FeN_{4}{-}O{-}N C R}$ catalyst delivered state-of-the-art activity as an ORR catalyst in alkaline media. When applied as the cathode catalyst in an aqueous zinc–air battery, an extraordinary peak power density of $214.2\\ensuremath{\\mathrm{\\mw}}\\ensuremath{\\mathrm{\\cm}}^{-2}$ at $334.1\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ was achieved, with the specific energy density of 1016  Wh $\\mathrm{kg_{Zn}}^{-1}$ at $20\\mathrm{\\mA\\cm^{-2}}$ approaching the theoretical maximum. DFT calculations verified the role of bridging O atoms as an effective electronic modulator of Fe centers. Results guide the development of microenvironment optimized metal single-atom catalysts for ORR and other applications. \n\nSupporting Information is available from the Wiley Online Library or from the author. \n\nThe data that support the findings of this study are available from the corresponding author upon reasonable request. \n\n# Supporting Information \n\n# Data Availability Statement \n\n# Keywords \n\naxial charge redistribution, d-band center, electrocatalysis, Fe singleatom catalysts, oxygen reduction reaction \n\nReceived: March 19, 2022 \nRevised: May 5, 2022 \nPublished online: June 12, 2022 \n\n[1]\t a) M.  Shao, Q.  Chang, J.-P.  Dodelet, R.  Chenitz, Chem. Rev. 2016, 116, 3594; b) D.  Zhao, Z.  Zhuang, X.  Cao, C.  Zhang, Q.  Peng, C.  Chen, Y.  Li, Chem. Soc. Rev. 2020, 49, 2215; c) L.  Peng, Z.  Wei, Engineering 2020, 6, 653. \n[2]\t a) X. F.  Lu, B. Y.  Xia, S. Q.  Zang, X. W.  Lou, Angew. Chem. 2020, 132, 4662; b) J. Liu, M. Jiao, B. Mei, Y. Tong, Y. Li, M. Ruan, P. Song, G. Sun, L. Jiang, Y. Wang, Angew. Chem. 2019, 131, 1175; c) X. Wang, Z. Li, Y. Qu, T. Yuan, W. Wang, Y. Wu, Y. Li, Chem 2019, 5, 1486. \n[3]\t a) Y.  He, S.  Liu, C.  Priest, Q.  Shi, G.  Wu, Chem. Soc. Rev. 2020, 49, 3484; b) L.  Peng, L.  Shang, T.  Zhang, G. I. N.  Waterhouse, Adv. Energy Mater. 2020, 10, 2003018. \n[4]\t a) B.  Qiao, A.  Wang, X.  Yang, L. F.  Allard, Z.  Jiang, Y.  Cui, J.  Liu, J.  Li, T.  Zhang, Nat. Chem. 2011, 3, 634; b) Y.  Chen, S.  Ji, C.  Chen, Q. Peng, D. Wang, Y. Li, Joule 2018, 2, 1242. \n[5]\t a) C. W.  Bezerra, L.  Zhang, K.  Lee, H.  Liu, A. L.  Marques, E. P. Marques, H. Wang, J. Zhang, Electrochim. Acta 2008, 53, 4937; b) M. Lefèvre, E. Proietti, F. Jaouen, J.-P. Dodelet, Science 2009, 324, 71; c) G.  Wu, K. L.  More, C. M.  Johnston, P.  Zelenay, Science 2011, 332, 443; d) H. T.  Chung, D. A.  Cullen, D.  Higgins, B. T.  Sneed, E. F. Holby, K. L. More, P. Zelenay, Science 2017, 357, 479. \n[6]\t a) J. K.  Nørskov, J.  Rossmeisl, A.  Logadottir, L.  Lindqvist, J. R.  Kitchin, T.  Bligaard, H.  Jonsson, J. Phys. Chem. B 2004, 108, 17886; b) J. H. Zagal, M. T. Koper, Angew. Chem., Int. Ed. 2016, 55, 14510; c) A. J.  Medford, A.  Vojvodic, J. S.  Hummelshøj, J.  Voss, F.  Abild-Pedersen, F.  Studt, T.  Bligaard, A.  Nilsson, J. K.  Nørskov, J. Catal. 2015, 328, 36. \n[7]\t a) Y. Zhu, J. Sokolowski, X. Song, Y. He, Y. Mei, G. Wu, Adv. Energy Mater. 2020, 10, 1902844; b) X. Li, H. Rong, J. Zhang, D. Wang, Y. Li, Nano Res. 2020, 13, 1842. \n[8]\t B. Lu, Q. Liu, S. Chen, ACS Catal. 2020, 10, 7584. \n[9]\t a) J.  Zhang, Y.  Zhao, C.  Chen, Y.-C.  Huang, C.-L.  Dong, C.-J.  Chen, R.-S. Liu, C. Wang, K. Yan, Y. Li, J. Am. Chem. Soc. 2019, 141, 20118; b) Y.  Mun, S.  Lee, K.  Kim, S.  Kim, S.  Lee, J. W.  Han, J.  Lee, J. Am. Chem. Soc. 2019, 141, 6254. \n[10]\t K. Jiang, H. Wang, Chem 2018, 4, 194. \n[11]\t K. M.  Zhao, S.  Liu, Y. Y.  Li, X.  Wei, G.  Ye, W.  Zhu, Y.  Su, J.  Wang, H. Liu, Z. He, Adv. Energy Mater. 2022, 12, 2103588. \n[12]\t a) Y.  Han, Y.  Wang, R.  Xu, W.  Chen, L.  Zheng, A.  Han, Y.  Zhu, J.  Zhang, H.  Zhang, J.  Luo, Energy Environ. Sci. 2018, 11, 2348; b) J.  Li, S.  Ghoshal, W.  Liang, M.-T.  Sougrati, F.  Jaouen, B.  Halevi, S. McKinney, G. McCool, C. Ma, X. Yuan, Energy Environ. Sci. 2016, 9, 2418; c) X.  Yang, D.  Xia, Y.  Kang, H.  Du, F.  Kang, L.  Gan, J.  Li, Adv. Sci. 2020, 7, 2000176. \n[13]\t a) A.  Zitolo, V.  Goellner, V.  Armel, M.-T.  Sougrati, T.  Mineva, L.  Stievano, E.  Fonda, F.  Jaouen, Nat. Mater. 2015, 14, 937; b) M. Xiao, J. Zhu, L. Ma, Z. Jin, J. Ge, X. Deng, Y. Hou, Q. He, J. Li, Q.  Jia, ACS Catal. 2018, 8, 2824; c) Y.  Wang, Y.-J.  Tang, K.  Zhou, J. Am. Chem. Soc. 2019, 141, 14115. \n[14]\t H.  Fei, J.  Dong, C.  Wan, Z.  Zhao, X.  Xu, Z.  Lin, Y.  Wang, H.  Liu, K. Zang, J. Luo, Adv. Mater. 2018, 30, 1802146. \n[15]\t a) J. Ma, A. G. Wong-Foy, A. J. Matzger, Inorg. Chem. 2015, 54, 4591; b) C. V.  McGuire, R. S.  Forgan, Chem. Commun. 2015, 51, 5199; c) P.  Li, R. C.  Klet, S.-Y.  Moon, T. C.  Wang, P.  Deria, A. W.  Peters, B. M.  Klahr, H.-J.  Park, S. S.  Al-Juaid, J. T.  Hupp, Chem. Commun. 2015, 51, 10925. \n[16]\t a) X.  Xie, C.  Zhang, M.-B.  Wu, Y.  Tao, W.  Lv, Q.-H.  Yang, Chem. Commun. 2013, 49, 11092; b) H.  Yu, L.  Shang, T.  Bian, R.  Shi, G. I.  Waterhouse, Y.  Zhao, C.  Zhou, L. Z.  Wu, C. H.  Tung, T.  Zhang, Adv. Mater. 2016, 28, 5080; c) X.  Xie, L.  Peng, H.  Yang, G. I.  Waterhouse, L.  Shang, T.  Zhang, Adv. Mater. 2021, 33, 2101038. \n[17]\t a) X. Zhao, P. Pachfule, S. Li, T. Langenhahn, M. Ye, C. Schlesiger, S.  Praetz, J.  Schmidt, A.  Thomas, J. Am. Chem. Soc. 2019, 141, 6623; b) Y. He, S. Hwang, D. A. Cullen, M. A. Uddin, L. Langhorst, B. Li, S. Karakalos, A. J. Kropf, E. C. Wegener, J. Sokolowski, Energy Environ. Sci. 2019, 12, 250; c) W.  Xia, J.  Tang, J.  Li, S.  Zhang, K. C. W.  Wu, J.  He, Y.  Yamauchi, Angew. Chem. 2019, 58, 13354; d) J.  Liang, Y.  Jiao, M.  Jaroniec, S. Z.  Qiao, Angew. Chem., Int. Ed. 2012, 51, 11496. \n[18]\t X.  Wan, X.  Liu, Y.  Li, R.  Yu, L.  Zheng, W.  Yan, H.  Wang, M.  Xu, J. Shui, Nat. Catal. 2019, 2, 259. \n[19]\t Y. Jia, L. Zhang, L. Zhuang, H. Liu, X. Yan, X. Wang, J. Liu, J. Wang, Y. Zheng, Z. Xiao, Nat. Catal. 2019, 2, 688. \n[20]\t J.  Li, S.  Chen, N.  Yang, M.  Deng, S.  Ibraheem, J.  Deng, J.  Li, L.  Li, Z. Wei, Angew. Chem., Int. Ed. 2019, 58, 7035. \n[21]\t N.  Zhang, T.  Zhou, M.  Chen, H.  Feng, R.  Yuan, W.  Yan, Y.  Tian, X. Wu, W. Chu, C. Wu, Energy Environ. Sci. 2020, 13, 111. \n[22]\t J.  Li, L.  Jiao, E.  Wegener, L. L.  Richard, E.  Liu, A.  Zitolo, M. T. Sougrati, S. Mukerjee, Z. Zhao, Y. Huang, J. Am. Chem. Soc. 2019, 142, 1417. \n[23]\t a) Q.  Jia, N.  Ramaswamy, H.  Hafiz, U.  Tylus, K.  Strickland, G.  Wu, B.  Barbiellini, A.  Bansil, E. F.  Holby, P.  Zelenay, ACS Nano 2015, 9, 12496; b) T.  Marshall-Roth, N. J.  Libretto, A. T.  Wrobel, K. J.  Anderton, M. L.  Pegis, N. D.  Ricke, T. V.  Voorhis, J. T.  Miller, Y. Surendranath, Nat. Commun. 2020, 11, 5283. \n[24]\t a) H. Funke, A. Scheinost, M. J. P. R. B. Chukalina, Phys. Rev. B 2005, 71, 094110; b) A.  Aballe, M.  Bethencourt, F.  Botana, M.  Marcos, Electrochim. Acta. 1999, 44, 4805. \n[25]\t Z.  Chen, A.  Huang, K.  Yu, T.  Cui, Z.  Zhuang, S.  Liu, J.  Li, R.  Tu, K. Sun, X. Tan, Energy Environ. Sci. 2021, 14, 3430. \n[26]\t a) M. Xiao, L. Gao, Y. Wang, X. Wang, J. Zhu, Z. Jin, C. Liu, H. Chen, G.  Li, J.  Ge, J. Am. Chem. Soc. 2019, 141, 19800; b) J.  Wang, Z.  Huang, W.  Liu, C.  Chang, H.  Tang, Z.  Li, W.  Chen, C.  Jia, T.  Yao, S.  Wei, J. Am. Chem. Soc. 2017, 139, 17281; c) M.  Xiao, Y.  Chen, J. Zhu, H. Zhang, X. Zhao, L. Gao, X. Wang, J. Zhao, J. Ge, Z. Jiang, J. Am. Chem. Soc. 2019, 141, 17763. \n[27]\t a) H.  Xu, D.  Cheng, D.  Cao, X. C.  Zeng, Nat. Catal. 2018, 1, 339; b) F.  Calle-Vallejo, J.  Martínez, J.  García-Lastra, E.  Abad, M.  Koper, Surf. Sci. 2013, 607, 47; c) F. Calle-Vallejo, J. I. Martínez, J. Rossmeisl, Phys. Chem. Chem. Phys. 2011, 13, 15639. " + }, + { + "id": "10.1021_jacs.2c01194", + "DOI": "10.1021/jacs.2c01194", + "DOI Link": "http://dx.doi.org/10.1021/jacs.2c01194", + "Relative Dir Path": "mds/10.1021_jacs.2c01194", + "Article Title": "Identification of the Highly Active Co-N4 Coordination Motif for Selective Oxygen Reduction to Hydrogen Peroxide", + "Authors": "Chen, SY; Luo, T; Li, XQ; Chen, KJ; Fu, JW; Liu, K; Cai, C; Wang, QY; Li, HM; Chen, Y; Ma, C; Zhu, L; Lu, YR; Chan, TS; Zhu, MS; Cortes, E; Liu, M", + "Source Title": "JOURNAL OF THE AMERICAN CHEMICAL SOCIETY", + "Abstract": "Electrosynthesis of hydrogen peroxide (H2O2) through oxygen reduction reaction (ORR) is an environment-friendly and sustainable route for obtaining a fundamental product in the chemical industry. Co-N4 single-atom catalysts (SAC) have sparkled attention for being highly active in both 2e- ORR, leading to H2O2 and 4e- ORR, in which H2O is the main product. However, there is still a lack of fundamental insights into the structure-function relationship between CoN4 and the ORR mechanism over this family of catalysts. Here, by combining theoretical simulation and experiments, we unveil that pyrrole-type CoN4 (Co-N SACDp) is mainly responsible for the 2e- ORR, while pyridine-type CoN4 catalyzes the 4e- ORR. Indeed, Co-N SACDp exhibits a remarkable H2O2 selectivity of 94% and a superb H2O2 yield of 2032 mg for 90 h in a flow cell, outperforming most reported catalysts in acid media. Theoretical analysis and experimental investigations confirm that Co-N SACDp-with weakening O-2/HOO* interaction-boosts the H2O2 production.", + "Times Cited, WoS Core": 297, + "Times Cited, All Databases": 307, + "Publication Year": 2022, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000860150500001", + "Markdown": "# Identification of the Highly Active $C o-N_{4}$ Coordination Motif for Selective Oxygen Reduction to Hydrogen Peroxide \n\nShanyong Chen,# Tao Luo,# Xiaoqing Li, Kejun Chen, Junwei Fu, Kang Liu, Chao Cai, Qiyou Wang, Hongmei Li, Yu Chen, Chao Ma, Li Zhu, Ying-Rui Lu, Ting-Shan Chan, Mingshan Zhu,\\* Emiliano Cortés,\\* and Min Liu\\* \n\nCite This: J. Am. Chem. Soc. 2022, 144, 14505−14516 \n\n![](images/46fa9ffaf79c13a931c63be08b210ec0c56b7435cfa442a68abb2bdd748c5f7f.jpg) \n\n# Read Online \n\n# ACCESS \n\nMetrics & More \n\nArticle Recommendations \n\nSupporting Information \n\nABSTRACT: Electrosynthesis of hydrogen peroxide $\\left(\\mathrm{H}_{2}\\mathrm{O}_{2}\\right)$ through oxygen reduction reaction (ORR) is an environmentfriendly and sustainable route for obtaining a fundamental product in the chemical industry. ${\\mathrm{Co-N}}_{4}$ single-atom catalysts (SAC) have sparkled attention for being highly active in both $2\\mathrm{e}^{-}$ ORR, leading to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and $4\\mathrm{e}^{-}\\mathrm{ORR},$ in which $\\mathrm{H}_{2}\\mathrm{O}$ is the main product. However, there is still a lack of fundamental insights into the structure−function relationship between $\\mathrm{CoN}_{4}$ and the ORR mechanism over this family of catalysts. Here, by combining theoretical simulation and experiments, we unveil that pyrrole-type $\\mathrm{CoN}_{4}$ $(\\mathrm{Co-N\\SAC_{Dp}})$ is mainly responsible for the $\\mathrm{ie}^{-}$ ORR, while pyridine-type $\\dot{\\mathrm{CoN_{4}}}$ catalyzes the $4\\mathrm{e}^{-}$ ORR. Indeed, $\\scriptstyle\\mathbf{Co-N}$ \n\n![](images/acf0fb53f7234ca27e281eacceb9976e66c54d9be7861f75536283e6932ce6b5.jpg) \n\n$S\\mathrm{AC_{Dp}}$ exhibits a remarkable $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of $94\\%$ and a superb $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield of $2032\\mathrm{mg}$ for $90\\mathrm{{h}}$ in a flow cell, outperforming most reported catalysts in acid media. Theoretical analysis and experimental investigations confirm that $\\scriptstyle\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ \u0001with weakening $\\mathrm{O_{2}/H O O^{*}}$ interaction\u0001boosts the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. \n\n# INTRODUCTION \n\nHydrogen peroxide $\\left(\\mathrm{H}_{2}\\mathrm{O}_{2}\\right)$ is one of the most important chemicals, playing an essential role in chemical production, environmental treatment, paper and textile industry, and medical disinfection.1−4 The demand for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is growing year by year, especially resulting from global public health safety troubles. The traditional industrial anthraquinone process for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production suffers from more and more serious challenges such as intensive energy consumption, large amounts of organic waste generation, and safety issues from the instability of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in transport and storage.5−7 Recently, electroreduction of $\\mathrm{O}_{2}$ to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ through a two-electron $(2\\mathrm{e}^{-})$ oxygen reduction reaction (ORR) has emerged as a promising alternative to the traditional anthraquinone process because of the environment-friendly merits and on-site production ability.8−13 The key to realizing the electrosynthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ from $2\\mathrm{e}^{-}$ ORR is to develop low-cost and high-performance catalysts. Currently, the development of high-performance $2\\mathrm{e}^{-}$ ORR catalysts in alkaline systems has advanced satisfactorily.14−20 However, the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in acidic media possesses prominent advantages relative to the alkaline condition such as higher $\\mathrm{H}_{2}\\mathrm{O}_{2}$ stability $\\left(\\mathrm{H}_{2}\\mathrm{O}_{2}\\right)$ in alkaline conditions is prone to self-decomposition). Most recently, the solid-state electrolytes were used to produce pure water ${\\mathrm{-H}}_{2}\\mathrm{O}_{2}$ solutions, which has gained special attention.1,21,22 Nevertheless, the acidic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production is suitable for most actual application scenarios,23,24 but state-of-the-art electrocatalysts for $2\\mathrm{e}^{-}$ ORR in acid are presently lacking. \n\nIn recent years, there has been an incremental interest in searching for highly efficient and stable $2\\mathrm{e}^{-}$ ORR catalysts in acid environments, including noble-based materials,23,25−28 transitional metal compounds,29−33 single-atom catalysts (SACs),24,34−38 and carbon materials.39−41 Among these, the carbon-based transition metal SAC has received special attention due to its high atom unitization, high electrical conductivity, and adjustable coordination environment.37 For instance, both Liu et $a l.^{42}$ and Strasser et al.43 have screened different carbon-based transition metal SACs (such as Fe, $\\scriptstyle\\mathbf{Co},$ $\\mathrm{{Ni,\\Cu,}}$ and $\\mathbf{M}\\mathbf{n}_{\\cdot}$ ). They found that the Co SAC had the most $2\\mathrm{e}^{-}$ ORR activity and the $\\mathrm{CoN}_{4}$ coordination structure was identified as the most active site. Recently, the Co SAC has emerged as the starred catalyst for $2\\mathrm{e}^{-}$ ORR. $^{4,6,11,24,34}$ On the other hand, it is worth noting that the $\\mathrm{CoN_{4}}$ coordination structure has been demonstrated as the highly active site for $4\\mathrm{e}^{-}$ ORR in quite a few previous studies.44−49 For instance, Li et $a l.^{45}$ have prepared the single-atom $\\mathrm{CoN_{4}}$ in carbon matrix and demonstrated it as the outstanding $4\\mathrm{e}^{-}$ ORR catalyst with the high half potential of $0.773\\mathrm{~V~}$ versus reversible hydrogen electrode (RHE) and low $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of $0.76\\%$ at $0.8\\mathrm{~V~}$ versus RHE in 0.5 M $\\mathrm{H}_{2}S\\mathrm{O}_{4}$ . Summarizing present studies, the structure−function relationship between $\\mathrm{CoN}_{4}$ coordination structure and ORR pathway $2\\mathrm{e}^{-}$ or $4\\mathrm{e}^{-}$ ORR) is highly controversial. The limited understanding is unfavorable for the development of high-performance catalysts for $2\\mathrm{e}^{-}$ ORR in the oxygen reduction community. Therefore, identification of the most active $\\mathrm{CoN_{4}}$ coordination structure for $2\\mathrm{e}^{-}$ ORR is greatly desirable, especially for the development of highly active and selective catalysts in acidic media. \n\n![](images/66ddb92339bf8fa100749d7b8132201e586eef1aa15257c9282ec9d43150e6d0.jpg) \n\n![](images/186ac216b900c70a634ae093eee60fc581a2c76ecd671cd07f2d1620498aecb1.jpg) \nFigure 1. (a) Simulated different $\\mathrm{CoN_{4}}$ coordination structures. (b) Volcano plot depicting the Gibbs free energy of reaction intermediates $\\langle\\Delta_{\\mathrm{HO^{*}}}$ and $\\Delta_{\\mathrm{HOO^{*}}}.$ ) on different $\\scriptstyle\\mathrm{Co-N}$ coordination structures. The $\\mathrm{Pt}$ and $\\mathrm{PtHg}_{4}$ were obtained from ref 25. (c) Free energy diagram of ORR on the pyridine-type and pyrrole-type $\\mathrm{CoN_{4}}$ . (d) Differential charge distribution on pyridine-type $\\mathrm{CoN}_{4}$ with adsorption of $\\mathrm{HOO^{*}}$ . (e) Differential charge distribution on pyrrole-type $\\mathrm{CoN_{4}}$ with adsorption of $\\mathrm{HOO^{*}}$ . (f) 3d electron configuration of pyridine-type and pyrrole-type $\\mathrm{CoN_{4}}$ with adsorption of $\\mathrm{HOO^{*}}$ . \n\nHerein, we focus on the identification of the highly active $\\mathrm{CoN_{4}}$ coordination structure for $2\\mathrm{e}^{-}$ ORR among a series of prepared $\\scriptstyle\\mathrm{Co-N}$ SAC to develop the high-performance catalyst for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in acidic media. Theoretically, screened from a series of $\\mathrm{Co-N}$ motifs, the pyrrole-type $\\mathrm{CoN_{4}}$ is found to show the optimal $\\mathrm{HOO^{*}}$ adsorption strength and highest $2\\mathrm{e}^{-}$ ORR activity. Experimentally, the three types of $\\mathrm{Co-N}$ SACs $\\scriptstyle\\left(\\mathbf{Co-N}\\mathbf{\\SAC}_{\\mathrm{Dp}},\\right.$ Co−N $S A C_{\\mathrm{Pc}},$ and $\\mathrm{Co-N\\SAC_{Mm}},$ ) are prepared using the pyrolysis strategy. Here, the $\\mathrm{Co-N\\SAC_{Dp}}$ and $\\scriptstyle\\mathbf{Co-N}$ $S A C_{\\mathrm{Mm}}$ are obtained by using the nitrogen precursor of 4-dimethylaminopyridine and 2-methylimidazole, respectively, and the Co−N $S\\mathrm{AC_{Pc}}$ involves in the pyrolysis of cobalt phthalocyanine $(\\mathrm{CoPc})$ during the synthesis process. The results of catalyst characterization and performance evaluation confirm that $\\mathrm{Co-N\\SAC_{Dp}}$ (pyrrole-type $\\mathrm{CoN}_{4,\\dag}^{\\dag}$ ) formation occurs in the dominant $2e^{-}$ ORR pathway, while the $\\mathrm{Co-N\\SAC_{Mm}}$ formation with pyridine-type $\\mathrm{CoN_{4}}$ occurs in the ${4e^{-}}$ ORR. Impressively, the $\\scriptstyle\\mathbf{Co-N}$ $S\\mathrm{AC_{Dp}}$ shows a remarkable mass activity of $14.4\\mathrm{~A~g_{\\mathrm{cat}}}^{-1}$ ( $\\operatorname{\\mathrm{~\\sc~0.5~V~}}$ vs RHE) and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of $94\\%$ in $0.1\\mathrm{~M~HClO}_{4}$ . Furthermore, the $\\scriptstyle\\mathbf{Co-N}$ $S\\mathrm{AC_{Dp}}$ has been demonstrated to have a prominent $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate of $26.7~\\mathrm{{mg}~c m^{-2}\\:h^{-1}}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield of up to $2032{\\mathrm{~mg}}$ for $90\\mathrm{{h}}$ in the flow cell, leading to, for example, a practical electro-Fenton degradation of carbamazepine (CBZ). This work affords essential insights into the ORR mechanism based on SAC catalysts and the development of efficient catalysts for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. \n\n# RESULTS AND DISCUSSION \n\nTheoretical Calculation and ORR Mechanism. Among the most reported $\\mathrm{CoN_{4}}$ active sites, $\\begin{array}{r}{3,42-45}\\end{array}$ the unsaturated pyridinic-N and pyrrolic-N are considered to be coordinated with the Co atom. Herein, we focus on varying the type of coordination nitrogen species in $\\mathrm{CoN_{4}}$ sites, which has less been investigated previously. A series of $\\mathrm{Co-N}$ coordination structures with different amounts of pyridinic-N or pyrrolic-N are constructed (Figure 1a). Also, most models show a thermodynamically favorable formation energy (Table S1). The pyridinic-N and pyrrolic-N are abbreviated as $\\mathbf{N}_{\\mathrm{(Pd)}}$ and $\\mathrm{\\bfN_{(Po)},}$ respectively. The $\\mathrm{HOO^{*}}$ and $\\mathrm{HO^{*}}$ are the crucial intermediates to determine if the reaction occurs through the $2\\mathrm{e}^{-}$ or $4\\mathrm{e}^{-}$ ORR pathway, and the Gibbs free energy of them ( $\\Delta_{\\mathrm{HO^{*}}}$ and ${\\Delta}_{\\mathrm{HOO^{*}}}$ ) for different $\\mathrm{Co-N}$ coordination structures are computed. As shown in Figure 1b, ${\\Delta}_{\\mathrm{HO^{*}}}$ is related to $4\\mathrm{e}^{-}$ ORR, while ${\\Delta}_{\\mathrm{HOO^{*}}}$ governs $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production through $2e^{-}$ ORR. According to the previous reports,25,50 there is an approximately linear relationship between the ${\\Delta}_{\\mathrm{HO^{*}}}$ and ${\\Delta}_{\\mathrm{HOO^{*}}}$ with a constant value of $3.2\\pm0.2\\ \\mathrm{eV}.$ Besides, the strong adsorption of $\\mathrm{HOO^{*}}$ or $\\mathrm{HO^{*}}$ is located in the left region, and the weak adsorption corresponds to the right downhill in the volcano plot. The pyridine-type $\\mathrm{CoN}_{4},$ $\\mathrm{CoN}_{\\mathrm{(Pd)1(Po)3}},$ and $\\mathrm{CoN}_{\\mathrm{(Pd)}2\\mathrm{(Po)}2}$ with strong adsorption of $\\mathrm{HOO^{*}}$ prefer to break $_{\\mathrm{O-O}}$ bond, proceeding the $4\\mathrm{e}^{-}$ ORR pathway. More interestingly, the pyridine-type $\\mathrm{CoN}_{4}$ approaches the $\\mathrm{Pt}$ implying the excellent $4\\mathrm{e}^{-}$ ORR activity. In sharp contrast, the pyrrole-type $\\mathrm{CoN_{4}}$ shows ${\\Delta}_{\\mathrm{HOO^{*}}}$ of $4.28\\:\\mathrm{eV}$ , which is close to the optimal $\\mathrm{HOO^{*}}$ adsorption energy of 4.22 $\\mathbf{eV}$ (corresponding to limiting the potential of $0.7\\mathrm{V}$ ), meaning the main $2\\mathrm{e}^{-}$ ORR process. Impressively, the pyrrole-type $\\mathrm{CoN_{4}}$ exhibits better $2\\mathrm{e}^{-}$ ORR performances than other $\\scriptstyle\\mathbf{Co-}$ N coordination structures, considering the small overpotential, which is comparable to the prominent $\\mathrm{PtHg}_{4}$ catalyst25 (Figures 1b and S1). These results indicate that the coordination nitrogen type may govern the ORR pathway for $\\mathrm{CoN}_{4},$ and pyrrole-type $\\mathrm{CoN}_{4}$ is identified as the most active motif for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. These results also can address the contradictory phenomenon that the $\\mathrm{CoN}_{4}$ sites are highly active for both $2\\mathrm{e}^{-}$ ORR and $4\\mathrm{e}^{-}$ ORR reported in previous reports.42−49 \n\n![](images/250674f4ffb145e45c99a9640fa2165d2125d074d759954f1097044fe9955e52.jpg) \nFigure 2. (a) Schematic diagram of the synthesis route for the three SAC catalysts. $^{(\\mathrm{b,c})}$ TEM images, and (d) element mapping images of the Co−N $\\mathrm{SAC_{D_{p}}}$ . AC-HAADF-STEM image of (e) Co−N $\\mathrm{SAC_{Dp},}$ (f) $\\mathrm{Co-N\\SAC_{Pc}},$ and $\\left(\\mathrm{g}\\right)\\mathrm{Co-N}\\ S\\mathrm{AC_{\\mathrm{Mm}}}$ . \n\nNext, we focus on the investigation of distinctly different ORR processes on the pyrrole-type $\\mathrm{CoN}_{4}$ and pyridine-type $\\mathrm{CoN_{4}}$ . The general $2\\mathrm{e}^{-}$ and $4\\mathrm{e}^{-}$ ORR pathway can be depicted as follow $^*$ indicates the catalytically-active site): \n\n$$\n\\begin{array}{r}{\\begin{array}{c}{2\\mathrm{e}^{-}\\mathrm{ORR\\pathway}\\colon\\mathrm{O}_{2}+2\\bigl(\\mathrm{H}^{+}+\\mathrm{e}^{-}\\bigr)\\to\\mathrm{H}_{2}\\mathrm{O}_{2}}\\\\ {U^{0}=0.70\\mathrm{V}}\\end{array}}\\end{array}\n$$ \n\n![](images/1e0b6846b4c71d2a13d708fde9f27374b1a10f99927e627ac2f4b32bb225611b.jpg) \nFigure 3. (a) N 1s XPS spectra, (b) proportion of different $_\\mathrm{N}$ species, and (c) Raman spectra of the three samples. (d) Co K-edge XANES spectra and (e) FT $k_{2}$ -weighted and fitting extended XAFS (EXAFS) spectra of the $\\mathrm{Co-N\\SAC_{Dp},C o-N\\ S A C_{M m},}$ and reference samples, inset: actual or fitting model. (f) Wavelet transform (WT) $k^{2}$ -weighted EXAFS contour plots of the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp},}$ $\\scriptstyle\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}},$ and the reference samples. \n\n$$\n\\begin{array}{r}{\\mathrm{~\\boldmath~\\Psi~}^{*}+\\mathrm{O}_{2}+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\mathrm{\\Lambda}^{*}\\mathrm{OOH}\\phantom{\\frac{1}{2}}}\\\\ {\\mathrm{~\\boldmath~\\Psi~}^{*}\\mathrm{OOH}+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}_{2}+\\mathrm{\\Lambda}^{*}\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}_{2}+\\mathrm{\\Lambda}^{*}}\\end{array}\n$$ \n\n${4e}^{-}$ ORR pathway: $\\mathrm{O}_{2}+4\\big(\\mathrm{H}^{+}+\\mathrm{e}^{-}\\big)\\rightarrow2\\mathrm{H}_{2}\\mathrm{O}$ \n\n$$\n\\begin{array}{c}{{U^{0}=1.23\\mathrm{V}}}\\\\ {{\\ *_{\\begin{array}{c}{{+\\mathrm{O}_{2}+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow{}^{*}\\mathrm{OOH}}}\\\\ {{}}\\\\ {{{}^{*}\\mathrm{OOH}+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}+\\mathrm{O}^{*}}}\\\\ {{}}\\\\ {{\\mathrm{O}^{*}+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\mathrm{OH}^{*}}}\\\\ {{\\ }}\\\\ {{\\mathrm{OH}^{*}+\\mathrm{H}^{+}+\\mathrm{e}^{-}\\rightarrow\\mathrm{H}_{2}\\mathrm{O}+{}^{*}}}\\end{array}}}\\end{array}\n$$ \n\nFor $\\mathrm{O}_{2}$ reduction to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ through $2\\mathrm{e}^{-}\\mathrm{ORR},$ the pyrroletype $\\mathrm{CoN_{4}}$ shows a lower thermodynamic overpotential $(\\eta)$ of $0.06~\\mathrm{eV}$ (Figure 1c) relative to the pyridine-type $\\mathrm{CoN}_{4}\\left(\\eta_{\\mathrm{H}_{2}\\mathrm{O}_{2}}\\right.$ $\\mathbf{\\Sigma}=0.32~\\mathrm{eV})$ . For $4\\mathrm{e}^{-}$ ORR to produce $\\mathrm{H}_{2}\\mathrm{O}$ , the pyridine-type $\\mathrm{CoN}_{4}$ $\\left(\\eta_{\\mathrm{H_{2}O}}\\ =\\ 0.21\\ \\mathrm{eV}\\right)$ exhibits a smaller thermodynamic overpotential than that of pyrrole-type $\\mathrm{CoN}_{4}$ $\\left(\\eta_{\\mathrm{H_{2}O}}=0.59\\ \\mathrm{eV}\\right)$ . These results reveal that pyrrole-type $\\mathrm{CoN_{4}}$ prefers the $2\\mathrm{e}^{-}$ ORR (Figure S2), while the pyridine-type $\\mathrm{CoN}_{4}$ tends to proceed via $4\\mathrm{e}^{-}$ ORR (Figure S3), in accordance with the results from the volcano plot (Figure 1b). Importantly, the kinetic analyses also confirm the kinetic favorable $\\mathrm{HOO^{*}}$ protonation process rather than $\\mathrm{HOO^{*}}$ dissociation on pyrrole-type $\\mathrm{CoN}_{4}$ (Figure S4-5). Furthermore, we investigate the interplay between the $\\mathrm{CoN_{4}}$ sites and the important $\\mathrm{HOO^{*}}$ intermediate, which largely determines the ORR pathway. As shown in Figure 1d,e, the pyridine-type $\\mathrm{CoN_{4}}$ shows a more prominent electron transfer $\\left(0.39\\mathrm{~e~}\\right)$ from the $\\mathrm{CoN}_{4}$ site to $\\mathrm{HOO^{*}}$ intermediate as compared to the pyrroletype $\\mathrm{CoN_{4}}$ (0.29 e) determined by Bader charge analysis. This result indicates the strong electron interaction between the pyridine-type $\\mathrm{CoN_{4}}$ and $\\mathrm{\\bar{HOO^{*}}}$ . Moreover, the density of states (DOS) of $C_{0}$ in pyrrole-type and pyridine-type $\\mathrm{CoN_{4}}$ with adsorption of $\\mathrm{HOO^{*}}$ were calculated (Figure S6), and the Co orbital occupation of electrons are shown in Figure 1f. After adsorption of $\\mathrm{HOO^{*}}$ , there are two single electrons in the $\\mathbf{d}_{y z}\\mathbf{d}_{x z}$ and $\\mathbf{d}_{z}{}^{2}$ orbits for Co of pyrrole-type $\\mathrm{CoN}_{4},$ while the electrons are paired in Co of pyridine-type $\\mathrm{CoN_{4}}$ . It is reported that the high spin state is associated to the weaker adsorption of the $\\mathrm{HOO^{*}}$ intermediate relative to the low spin state.51,52 Therefore, after adsorption of $\\mathrm{HOO^{*}}$ , the pyrrole-type $\\mathrm{CoN}_{4}$ showing a high spin state facilitate the $\\mathrm{HOO^{*}}$ desorption to generate $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . However, the pyridine-type $\\mathrm{CoN}_{4}$ with the low spin state tends to dissociate the $_{\\mathrm{O-O}}$ bond in $\\mathrm{HOO^{*}}$ and, lastly, form $\\mathrm{H}_{2}\\mathrm{O}$ . These results elucidate that the different ORR pathways for pyrrole-type and pyridine-type $\\mathrm{CoN}_{4}$ may come from the electron interaction with the important reaction intermediate (such as $\\mathrm{HOO^{*}}^{\\cdot}$ ) and the accompanying spin state difference. \n\nSynthesis and Characterization of Co−N SAC. Inspired by the density functional theory (DFT) results, we prepared three different $\\scriptstyle\\mathrm{Co-N}$ SACs through a pyrolysis strategy (synthesis details see the Experimental Section in Supporting Information). To exclude the effect of the carbon support, the Ketjen Black (ECP600JD) is used as the support for the three $\\mathrm{Co-N}$ SACs (Figure 2a). Thereinto, the $\\scriptstyle\\mathbf{Co-N}$ $S\\mathrm{AC_{D_{p}}}$ represents the sample derived from the 4-dimethylaminopyridine and cobaltous nitrate hexahydrate. The $\\mathrm{Co-N\\SAC_{\\mathrm{Pc}}}$ comes from pyrolysis of CoPc and dicyandiamide. For $\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}},$ the 2-methylimidazole and cobaltous nitrate hexahydrate are employed as the nitrogen and Co sources, respectively. Herein, considering the different transformation processes of the nitrogen precursor and coordination strength with the $\\mathbf{Co}^{53,54}$ (Figure S7), altering the nitrogen precursor may result in a different coordination structure for $\\mathrm{Co-N}$ SAC samples. \n\nThe structure and morphology of the catalysts are characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), and aberration-corrected high-angle annular dark-field scanning TEM (AC-HAADFSTEM). As shown in Figure S8, the three $\\mathrm{Co-N}$ SAC samples show a similar nanoparticle morphology for the initial carbon black. As shown in TEM images (Figures 2b,c, S9a,b, and S10a,b), there are only wrinkled carbon nanoparticles without obvious metal particles. The X-ray diffraction (XRD) patterns (Figure S11) show the only (002) peak for graphite carbon at about $26^{\\circ}$ and the absence of metal nanoparticles. The HAADF-TEM and element mapping images (Figures 2d, $\\mathrm{{\\calS9}c-}$ f, and $\\operatorname{S10c-f})$ reveal that the Co and nitrogen are homogeneously dispersed in the carbon matrix, indicating the atomical dispersion of Co for the three $\\scriptstyle\\mathbf{Co-N}$ SAC samples. The AC-HAADF-STEM measurements are carried out to investigate the Co single-atom in the three samples. As displayed in Figure $_{2\\mathrm{e-g},}$ the bright and isolated metal atoms can be observed, confirming the successful preparation of the three $\\mathrm{Co-N}$ SAC samples. \n\nTo ascertain the chemical state and coordination structure, the X-ray photoelectron spectroscopy (XPS) and $\\mathrm{x}$ -ray absorption fine structure (XAFS) were performed. Deconvolution of N 1s XPS spectra (Figure 3a) confirms that all the three $\\mathrm{Co-N}$ SAC samples contain the pyridinic-N $\\left(398.0~\\mathrm{eV}\\right)$ , pyrrolic-N (399.6 eV), and graphitic-N $\\left(400.9~\\mathrm{{\\eV})}$ species.55−57 However, the proportion of the three N species has a great difference (Figure 3b and Table S2), suggesting the different coordination environments. Previous studies demonstrated that the transition metals tended to coordinate with the N species to form the $\\mathrm{MN}_{4}$ structure, in which the pyridinic-N and pyrrolic-N species were generally considered.3,43−45 In our prepared three $\\mathrm{Co-N}$ SAC samples, the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ shows the highest content of pyrrolic-N species $(50.9\\%)$ while the $\\mathrm{Co-N}$ $\\ensuremath{\\mathrm{SAC}}_{\\ensuremath{\\mathrm{Mm}}}$ exhibits the highest content of pyridinic-N species $(50.0\\%$ , Figure 3b, and Table S2). That is to say, the $\\mathrm{Co-NSAC_{Dp}}$ may dominate the pyrrole-type $\\mathrm{CoN}_{4}$ sites while the Co−N $\\bar{S_{\\bar{\\mathrm{AC_{Mm}}}}}$ mainly contains the pyridine-type $\\mathrm{CoN_{4}}$ sites. The Fourier transform infrared (FT-IR) spectra (Figure S12) show that all the three $\\mathrm{Co-N}$ SAC samples exhibit a peak at $803~\\mathrm{{cm}^{-1}}$ which is related to the $\\mathrm{Co-N}$ bonds.57 Especially, the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ emerges the characteristic stretch peak of pyrrole-type metal $-\\mathbf{N}$ at $853~\\mathrm{cm}^{-1}$ , which has been identified in Fe phthalocyanine and pyrrole-type $\\mathrm{FeN}_{4}$ in the previous reports.57,58 According to the N K-edge X-ray absorption near edge structure (XANES) spectra (Figure S13), the more distinct pyrrolic-N species can be identified for the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ relative to the Co−N $S\\mathrm{AC_{Mm}}$ . Moreover, the splitting pyrrolic-N peak (pyrrolic- ${\\bf{\\cdot N^{\\prime}}}$ ) for the Co−N ${\\mathrm{SAC}}_{\\mathrm{Dp}}$ may be related to the metal−pyrrolic $\\mathbf{N}$ site.57 Although no oxygencontaining chemicals have been used in the preparation process, the oxygen signals have been detected in XPS for the three $\\scriptstyle\\mathbf{Co-N}$ SACs and a similar phenomenon also has occurred in previously reported SAC materials.42,43,46,48 All the three $\\mathrm{Co-N}$ SAC samples show similar oxygen functional groups and contents (Figure S14 and Table S3), which is expected to have less impact on ORR performances. \n\nIt is shown in Co K-edge XANES spectra (Figure 3d) that the $\\mathrm{Co-N\\SAC_{\\mathrm{Dp}}}$ and $\\mathrm{Co-N\\SAC_{Mm}}$ exhibit higher pre-edge absorption energy than the Co foil but is comparable to the $\\mathrm{CoPc,}$ indicating the positive valency of Co. The Fouriertransformed EXAFS spectra (Figure 3e) prove the absence of $\\scriptstyle\\mathbf{Co-Co}$ bonds (2.17 Å) in the Co−N $S\\mathrm{AC_{Dp}}$ and $\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ further verifying the single-atom dispersion of $\\scriptstyle{\\mathrm{Co}},$ which agrees well with the AC-HAADF-STEM results. Moreover, the main peaks in $1.35\\mathrm{~\\AA~}$ for the $\\scriptstyle\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ and 1.44 Å for the $\\mathrm{Co-N\\SAC_{Dp}}$ are ascribed to the $\\scriptstyle\\mathbf{Co-N}$ coordination structure referring to the CoPc and the reported SACs.35,42,45,48 Noting that the slightly shifted $\\scriptstyle\\mathrm{Co-N}$ peak between the Co−N $S A C_{\\mathrm{Mm}}$ and $\\mathrm{Co-NSAC_{Dp}}$ may come from the different $\\scriptstyle\\mathbf{Co-N}$ coordination structures. Interestingly, the position of the $\\mathrm{Co-N}$ peak in the $\\mathrm{Co-N\\SAC_{Dp}}$ is equivalent to that in $\\mathbf{CoPc}$ , suggesting the Co−pyrrolic-N $(\\bar{\\mathrm{Co}}{-}\\mathrm{N_{Po}})$ coordination structure in the Co−N $S\\mathrm{AC_{Dp}}$ . \n\nFurthermore, the quantitative least-squares fitting of EXAFS spectra confirms (Figures 3e and S15, S16) that the Co atom is coordinated with four pyrrolic-N in the $\\mathrm{Co-N\\SAC_{Dp}}$ while the four coordinated nitrogen species are pyridinic-N for the $\\mathrm{Co-N}$ $\\ensuremath{\\mathrm{SAC}}_{\\ensuremath{\\mathrm{Mm}}}$ screened from different theoretical models (Figures S17, S18, Tables S4, and S5). Besides, the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Pc}}$ matches well with the $\\mathbf{CoN_{(Pd)3(Po)1}}$ model where the Co atom is coordinated with three pyridinic- $.\\mathrm{\\DeltaN}$ and one pyrrolic-N (Figure S19). The coordination number for the $\\mathrm{Co-N\\SAC_{Dp}}$ and $\\mathrm{Co-NSAC_{Mm}}$ is 3.86 and 3.88 (Table S6), respectively. The bond length of ${\\mathrm{Co-N_{Po}}}$ $(2.02\\mathrm{~\\AA~})$ in the Co−N $S\\mathrm{AC_{Dp}}$ is longer than that of $\\mathrm{Co-N_{Pd}}$ $\\left(1.90\\mathrm{\\AA}\\right)$ in the $\\mathrm{Co-N\\SAC_{Mm}},$ which is also corroborated by the proposed DFT model (Figure S20). As shown in the WT-EXAFS contour plots (Figure 3f), the three samples $(\\mathrm{Co-N\\SAC_{Dp}},$ Co−N $\\ensuremath{\\mathrm{SAC}}_{\\ensuremath{\\mathrm{Mm}}},$ and CoPc) with the $\\mathrm{Co-N}$ coordination structure exhibit an intensity maximum of about $4\\mathring\\mathrm{A}^{-1}.$ , which is different from the $6.8\\ \\dot{\\mathrm{~\\AA~}}^{-1}$ of $\\scriptstyle{\\mathrm{Co-Co}}$ bond in Co foil. Summarizing the abovementioned results, we have experimentally confirmed the pyridine-type $\\mathrm{CoN}_{4}$ $(\\mathrm{Co-N\\SAC_{Dp}})$ and pyrrole-type $\\mathrm{CoN}_{4}$ $\\left(\\mathrm{Co-N\\SAC_{Mm}}\\right)$ as illustrated in DFT simulation. \n\nThe physicochemical property has been further studied by Brunauer−Emmett−Teller (BET) specific surface area and Raman spectroscopy. The three $\\mathrm{Co-N}$ SAC samples show the typical mesopore structure (Figure S21) and a comparable BET-specific surface area (Table S7). The characteristic D band and G band can be observed (Figure 3c) for carbonbased materials. Also, the intensity ratio of $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ for the $\\mathrm{Co-N}$ \n\n![](images/b29fe7418cdc7f807fd917d7ef121411d511f59313a811db6c14eea4e936fc80.jpg) \nFigure 4. (a) ORR polarization curves of RRDE at $1600~\\mathrm{rpm}$ in $0.1\\mathrm{~M~HClO}_{4}.$ (b) Calculated Tafel plots. (c) $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity. (d) Mass activity of the $\\scriptstyle\\mathrm{Co-N}$ $S\\mathrm{AC_{D_{p}}}$ and recently reported catalysts (the detailed information about these reference catalysts can see in Table S11). (e) Chronoamperometry measurement of the ${\\mathrm{Co-N}}{\\mathrm{~SAC_{Dp}~}}$ for $20,000\\mathrm{~s~}$ at $0.25\\mathrm{V}$ (vs RHE). (f) Correlation between $I_{\\mathrm{H}_{2}\\mathrm{O}}$ and ${\\cal I}_{\\mathrm{H}_{2}\\mathrm{O}_{2}}$ current at $0.2\\mathrm{V}$ (vs RHE) and the proportion of nitrogen species for the three $\\mathrm{Co-N}$ SACs. \n\n$S\\mathrm{AC_{Dp},}$ $\\mathrm{Co-N}\\ S\\mathrm{AC_{Pc}},$ and $\\mathrm{Co-N}\\mathrm{SAC}_{\\mathrm{Mm}}$ is comparable, indicating a similar defect degree after N-doping. Thus, the three $\\scriptstyle\\mathrm{Co-N}$ SAC samples can be used to study the structure− function relationship between the $\\mathrm{Co-N}$ coordination structure and the ORR pathway, due to the similar physicochemical parameters and similar element contents (Table S8) but different local coordination structures. \n\nORR Performances and Experimental Investigation. Now, we turn to the investigation of ORR performances. The ORR measurement is performed on the three-electrode system with the rotating ring-disk electrode (RRDE) used as the working electrode. Prior to the ORR performance evaluation, the collection efficiency $(N)$ of the RRDE has been determined (Figure S22). Also, the ORR polarization curves are collected on RRDE at $1600~\\mathrm{rpm}$ in $\\mathrm{O}_{2}$ -saturated 0.1 M $\\mathrm{{HClO}_{4}}$ . As shown in Figure 4a, the ORR activity follows the order: $\\mathrm{Co-N}$ $\\mathrm{SAC_{Mm}>C o-N\\ S A C_{P c}>C o-N\\ S A C_{D p}}$ in terms of the $E_{-0.2}$ (The potential corresponds to the current density of $-0.2\\ \\mathrm{mA}$ $\\mathsf{c m}^{-2^{\\cdot}}$ ) and limiting current density $\\left(J_{\\mathrm{L}}\\right)$ . Thereinto, the $\\scriptstyle\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ exhibits a high $E_{-0.2}$ of 0.767 V versus RHE (Table S9) and large $J_{\\mathrm{L}}$ of $5.47\\mathrm{\\mA}\\mathrm{\\cm}^{-2}$ , in correspondence with the reported typical $4\\mathrm{e}^{-}$ ORR polarization curves.45,46,48 Besides, the calculated electrochemical surface area (ECSA) based on the CV curves at different sweep rates accords well with the order of ORR activity (Figure S23 and Table S10). Using Koutecky−Levich $\\scriptstyle(\\mathrm{K-L})$ diffusion equation, the Tafel slopes of the $\\mathrm{Co-N\\SAC_{Mm},\\ C o-N\\ S A C_{P c},}$ and $\\mathrm{Co-N\\SAC_{Dp}}$ are calculated to be 87, 120, and $124~\\mathrm{mV}$ dec−1 (Figure 4b), respectively, implying the different reaction kinetics and ratedetermining step (RDS).59,60 Thereinto, the RDS of $\\scriptstyle\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ may relate to the $\\mathrm{HOO^{*}}$ dissociation,20 while the first electron transfer process $\\left(^{*}+\\mathrm{O}_{2}+\\mathrm{e}^{-}\\rightarrow{^*}\\mathrm{O}_{2}^{-}\\right)$ is ascribed to the RDS for the $\\mathrm{Co-N\\SAC_{\\mathrm{Pc}}}$ and $\\mathrm{Co-N\\SAC_{Dp}.}^{\\mathrm{3}}$ 7,42 The $\\mathrm{Co-N\\SAC_{Mm}}$ and $\\mathrm{Co-N\\SAC_{Dp}}$ show the transfer electron number $(n)$ of $3.6{-}3.5\\$ and $2.3\\mathrm{-}2.2$ in the potential range of $0.6{-}0.2\\mathrm{~V~}$ versus RHE, respectively, indicating the dominant $4\\mathrm{e}^{-}$ ORR and $2\\mathrm{e}^{-}$ ORR, respectively (Figure S24). Furthermore, according to the ORR polarization curves at different rotate rates and $\\scriptstyle\\mathrm{K-L}$ diffusion equation, the $n$ of the Co−N $S\\mathrm{AC_{Mm}}$ and $\\mathrm{Co-N\\SAC_{Dp}}$ is determined to be 3.7 and 2.2 (Figures S25 and S26), respectively. This result is consistent with the RRDE results. To investigate the relationship between the coordination structure and ORR pathway, the correlation between the content of nitrogen species and $I_{\\mathrm{H}_{2}\\mathrm{O}}$ and $I_{\\mathrm{H}_{2}\\mathrm{O}_{2}}$ ( $\\mathrm{~\\i~}0.2\\mathrm{~V~}$ vs RHE) is concluded in Figure 4f. The $I_{\\mathrm{H}_{2}\\mathrm{O}_{2}}$ increases with the incremental content of pyrrolic-N $\\left(\\mathrm{N}_{\\mathrm{Po}}\\right)$ , while the $I_{\\mathrm{H}_{2}\\mathrm{O}}$ decreases with the reduced content of pyridinic-N $\\left(\\mathrm{N}_{\\mathrm{Pd}}\\right)$ . Also, this result implies that pyrrole-type $\\mathrm{CoN}_{4}$ $\\big(\\mathrm{Co-N\\SAC_{Dp}},$ ) contributes to $2\\mathrm{e}^{-}$ ORR for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ generation, while the pyridine-type $\\mathrm{CoN}_{4}$ $(\\mathrm{Co-N}$ $\\begin{array}{r}{{S A C}_{\\mathrm{{Mm},}}}\\end{array}$ ) accounts for the $4\\mathrm{e}^{-}$ ORR to form $\\mathrm{H}_{2}\\mathrm{O}$ through an associative mechanism.37 These analyses from catalytic performances agree well with the DFT calculation results. \n\nConsidering the dominant $2\\mathrm{e}^{-}$ ORR pathway on the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp},}$ we focus on its performance for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Screened from the pyrolysis temperature of 700 to $900~^{\\circ}\\mathrm{C}$ (Figure S27), the $\\mathrm{Co-N\\SAC_{Dp}}$ pyrolyzed at $800~^{\\circ}\\mathrm{C}$ is found to show the highest $2\\mathrm{e}^{-}$ ORR performance. The optimal $\\scriptstyle\\mathbf{Co-}$ $\\mathrm{\\DeltaN\\SAC_{Dp}}$ exhibits a remarkable $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of $94\\%$ at 0.3 $\\mathrm{v}$ versus RHE (Figure $\\mathsf{4c}$ ), outperforming that of the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Pc}}$ $(62\\%)$ and $\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ $(23\\%)$ . Impressively, the $\\mathrm{Co-N\\SAC_{Dp}}$ reveals a superior mass activity of 14.4 A $\\mathrm{{\\dot{g}_{c a t.}}^{-1}}$ $\\left(0.5\\mathrm{~V~}\\nu s\\mathrm{~RHE}\\right)$ ), prominent Co mass activity (Figure S28), and a wide potential range (0.65−0.1 V vs RHE) of ${>}90\\%$ selectivity for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. The $2\\mathrm{e}^{-}$ ORR of the $\\mathrm{Co-N}$ \n\n![](images/b022f42b41933ae69ff95f140a4866831f2f5d26fb614840b497b417d879e9c6.jpg) \nFigure 5. (a) ORR polarization curves in 0.1 M $\\mathrm{HClO}_{4}$ before and after the addition of $1\\mathrm{mM}\\mathrm{SCN^{-}}$ . (b) ORR polarization curves in 0.1 M ${\\mathrm{HClO}}_{4}$ and $\\mathrm{H}_{2}\\mathrm{O}_{2}\\mathrm{RR}$ polarization curves in $0.1\\mathrm{~M~HClO}_{4}$ containing $10\\ \\mathrm{mM}\\ \\mathrm{H}_{2}\\mathrm{O}_{2}$ . (c) $\\mathrm{~O}_{2}$ -TPD curves for the $\\mathrm{Co-N}$ $\\mathrm{SAC_{D_{P}}}$ and $\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ . (d) In situ ATR−SEIRAS spectra for the $\\mathrm{Co-N}$ $S\\mathrm{AC_{D_{p}}}$ at potential range of $0.9\\mathrm{-}0.1\\mathrm{~V~}$ . \n\n$S\\mathrm{AC_{Dp}}$ excels most reported non-noble metal catalysts and is even comparable to advanced noble metal catalysts in acidic media (Figure 4d). These outstanding $2\\mathrm{e}^{-}$ ORR performances make the $\\mathrm{Co-N\\SAC_{Dp}}$ rank as one of the top catalysts for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in acidic media (Table S11). It is shown in Figure 4e that the chronoamperometry measurement is performed to assess the catalytic stability of the $\\scriptstyle\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ on RRDE. The $\\mathrm{Co-N\\SAC_{Dp}}$ shows almost unchanged current signals and maintained $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of $>90\\%$ for ${20,000\\mathrm{s},}$ , verifying its robust catalytic durability for $2\\mathrm{e}^{-}$ ORR in acidic media. The ORR performances of the three $\\scriptstyle\\mathrm{Co-N}$ SACs also have been evaluated in the different electrolytes. As displayed in Figures S29 and S30, the ORR activity shows a similar trend to that in acidic media, that is, Co−N $\\mathrm{SAC}_{\\mathrm{Mm}}>$ $\\scriptstyle\\mathrm{Co-N}$ $\\mathrm{~N~}\\mathrm{SAC_{Pc}~}>\\mathrm{Co-N~}\\mathrm{SAC_{Dp}~}$ . Also, the $\\mathrm{Co-N}~\\mathrm{SAC_{Dp}}$ exhibits a higher $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity than that of the $\\mathrm{Co-N}$ $S\\mathrm{AC_{Pc}}$ and $\\mathrm{Co-N\\SAC_{Mm}}$ both in $0.1\\mathrm{~M~KOH}$ and $0.1\\textbf{M}$ phosphate-buffered saline (PBS). Especially, the Co−N $S\\mathrm{AC_{Dp}}$ possesses the maximal $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of $86.1\\%$ in $0.1~\\mathrm{~M~}$ KOH $\\left(\\mathrm{pH}\\ =\\ 13\\right),$ and $88.5\\%$ in 0.1 M PBS $\\mathrm{(pH~=~}7.2\\mathrm{)}$ , respectively, demonstrating its greatly promising potential for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production in different environments. \n\nNext, we perform further experimental investigations on the typical $4\\mathrm{e}^{-}$ ORR catalyst of the Co−N $\\mathsf{S A C}_{\\mathrm{Mm}}$ and $2\\mathrm{e}^{-}$ ORR catalyst of the $\\mathrm{Co-N\\SAC_{Dp}}$ to probe the origin of different ORR pathways. The $S C\\mathrm{N}^{-}$ poisoning experiments (Figure 5a) verify that the Co metal center is the actual active site in the two $\\mathrm{Co-N}$ SAC. Furthermore, the prepared nitrogen-doped carbon (CN) catalyst without adding Co exhibits much inferior $2\\mathrm{e}^{-}$ ORR activity to the $\\mathrm{Co-N\\SAC_{\\mathrm{Dp}}}$ (Figure S31), further confirming the substantial ORR contribution of the Co center. In the ${\\bf N}_{2}$ -saturated 0.1 M $\\mathrm{\\HClO_{4}}$ containing $10\\ \\mathrm{mM}$ $\\mathrm{H}_{2}\\mathrm{O}_{2},\\mathrm{Co}{-}\\mathrm{N}\\mathrm{SAC}_{\\mathrm{Dp}}$ shows negligible $\\mathrm{H}_{2}\\mathrm{O}_{2}$ reduction reaction $\\left(\\mathrm{H}_{2}\\mathrm{O}_{2}\\mathrm{RR}\\right)$ activity while the Co−N $S A C_{\\mathrm{Mm}}$ exhibits apparent $\\mathrm{H}_{2}\\mathrm{O}_{2}\\mathrm{RR}$ current (Figure 5b). That is to say, when the $2\\mathrm{e}^{-}$ ORR proceeds, the generated $\\mathrm{H}_{2}\\mathrm{O}_{2}$ will be maintained on $\\mathrm{Co-N\\SAC_{Dp}}$ resulting in high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity. However, the generated $\\mathrm{H}_{2}\\mathrm{\\barO}_{2}$ on $\\mathrm{Co-N\\SAC_{Mm}}$ will be reduced to $\\mathrm{H}_{2}\\mathrm{O}$ leading to the dominated $4\\mathrm{e}^{-}$ ORR. The $\\mathrm{O}_{2}$ temperatureprogramed desorption $\\left(\\mathrm{O}_{2}\\mathrm{-TPD}\\right).$ ) curves show that the $\\mathrm{Co-N}$ $\\mathsf{S A C}_{\\mathrm{Mm}}$ exhibits stronger $\\mathrm{O}_{2}$ adsorption than that of $\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ (Figure 5c), which is in line with the facile $\\mathrm{~O}_{2}$ adsorption and activation for pyridine-type $\\mathrm{CoN}_{4}$ $(\\mathrm{Co-N}$ $\\begin{array}{r}{{\\cal S}\\mathrm{AC}_{\\mathrm{Mm}},}\\end{array}$ ) in DFT calculation. However, the strong $\\mathrm{~O}_{2}$ adsorption for the $\\mathrm{Co-N\\SAC_{Mm}}$ will hamper the desorption of $\\mathrm{HOO^{*}}$ intermediates resulting in $4\\mathrm{e}^{-}$ ORR and lowered $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity. However, the weak $\\mathrm{O}_{2}$ adsorption may favor the facile $\\mathrm{HOO^{*}}$ desorption and ensure the high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity for the $\\mathrm{Co-N}~\\mathrm{SAC_{Dp}}$ . Furthermore, the in situ attenuated total reflectance surface−enhanced infrared absorption spectroscopy (ATR−SEIRAS) measurements are performed to detect the reaction intermediate (Figure S32). As shown in Figure 5d, there emerge two absorbance peaks at 1482 and $1231~\\mathrm{{cm}^{-1}}$ which can be attributed to the adsorption of $\\mathrm{O}_{2}$ $(\\mathrm{O}_{2,\\mathrm{ad}})$ and $\\mathrm{HOO^{*}}$ $\\mathrm{(ooH_{ad})}$ , respectively, according to previous reports.34,61 A similar $\\mathrm{\\Gamma_{OOH_{ad}}}$ peak with increasing strength can be observed for Co−N $S A C_{\\mathrm{Mm}}$ (Figure S33) relative to $\\mathrm{Co-NSAC_{Dp}}$ . The relatively strong $\\mathrm{\\Gamma_{OOH_{ad}}}$ peak on the $\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ may be related to the higher coverage of $\\mathrm{HOO^{*}}$ considering the similar measurement procedure of in situ ATR−SEIRAS.62−64 Summarizing the abovementioned results, we use the experimental evidence to verify the DFT calculation results that the $\\mathrm{Co-N\\SAC_{Dp}}$ with pyrrole-type $\\mathrm{CoN_{4}}$ favors the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production as compared to the $\\scriptstyle\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ (pyridine-type $\\mathrm{CoN}_{4},$ ). \n\n![](images/1e1efa1a30d7bd43621d24ccc25c0f851a69a60172f302d500126192e405bb57.jpg) \nFigure 6. (a) Schematic diagram of the flow cell for $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. (b) $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate for different catalysts (the catalysts in this work are highlighted in red color and the other catalysts referred to the previou reports in Table S11). (c) Accumulatively produced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ for $\\mathrm{Co-N}$ $S\\mathrm{AC_{D_{P}}}$ and previously reported catalysts (detailed information in Table S11). (d) Chronopotentiometry curve at the fixed current of $-50\\ \\mathrm{mA}$ and the corresponding $\\mathrm{FE}_{\\mathrm{H}_{2}\\mathrm{O}_{2}}$ in the flow cell for $\\mathrm{Co-N\\SAC_{Dp}}$ . (e) Residual CBZ concentration at a different time in the electro-Fenton process. \n\nFurthermore, based on the control experiment and DFT calculation results (Figures S34−S36), we deduce that the oxygen functional groups cannot account for the totally different ORR selectivity for the three $\\mathrm{Co-N}$ SAC samples and have negligible influence on the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity in the present pyrrole-type $\\mathrm{CoN_{4}}$ system. Noting that the previously reported $\\mathrm{\\dot{C}o\\ S A C^{\\dot{4},24,34}}$ usually used pyridine-type $\\mathrm{CoN_{4}}$ as the theoretical model and the introduction of the $_{\\mathrm{C-O-C}}$ group in pyridine-type $\\mathrm{CoN}_{4}$ could enhance the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity. However, according to the theoretical results (Figure S34), the pyrrole-type $\\mathrm{CoN}_{4}$ initially shows high $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity, and introducing $_{\\mathrm{C-O-C}}$ results in lower $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity. \n\n${\\sf H}_{2}{\\sf O}_{2}$ Production Ability and Electro-Fenton Application. Inspired by the outstanding $2\\mathrm{e}^{-}$ ORR performances, the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production ability in the amplifying device of the flow cell has been assessed in $0.1\\mathrm{~M~HClO}_{4}$ . As shown in Figures 6a and S37, the $\\mathrm{Co-N}$ SAC catalysts have been assembled into the cathode for ORR. Moreover, the $\\mathrm{IrO}_{2}$ coating on the titanium sheet is used as the anode for oxygen evolution reaction, which is separated by the Nafion membrane. The $\\mathrm{Co-NSAC_{Dp}}$ in the flow cell can reach a large ORR current of $-75\\mathrm{\\mA}$ (Figure S38). As shown in Figure 6b, the $\\scriptstyle\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ shows a superior $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate $\\left(26.7~\\mathrm{mg~cm}^{-2}\\right.$ $\\mathbf{h}^{-1}.$ ) to the $\\mathrm{Co-N}~\\mathrm{SAC_{Pc}}$ $(\\bar{8.1}\\mathrm{mg}\\mathrm{cm}^{-2}\\mathrm{h}^{-1})$ and $\\scriptstyle\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ $\\mathsf{\\Omega}^{\\prime}5.0\\mathrm{mg~cm^{-2}~h^{-1}})$ , consistent with the $2\\mathrm{e}^{-}$ ORR activity order on RRDE. Impressively, the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production rate of $\\mathrm{Co{-}N\\ S A C_{\\mathrm{Dp}}}$ surpasses most previously reported catalysts (Figure 6b and Table S11). Furthermore, the longstanding and stable $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production has been performed at a fixed current of $-50\\ \\mathrm{\\mA}$ , and the generated $\\mathrm{H}_{2}\\mathrm{O}_{2}$ is determined by the ${\\mathrm{Ce}}^{4+}$ titration method (Figure S39). It is shown in Figure 6d that the $\\mathrm{Co-NSAC_{Dp}}$ shows a high $\\mathrm{FE}_{\\mathrm{H}_{2}\\mathrm{O}_{2}}$ of $84\\%$ in the initial $^\\textrm{\\scriptsize1h}$ and maintains the $\\mathrm{FE}_{\\mathrm{H}_{2}\\mathrm{O}_{2}}$ of $>70\\%$ in the continuous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production operation up to $90\\mathrm{~h~}$ (the electrolyte is periodically refreshed every $30\\mathrm{~h~}$ ). Importantly, the produced $\\mathrm{H}_{2}\\mathrm{O}_{2}$ amount linearly increases with the operating time and the cumulative $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield reaches up to $2032~\\mathrm{mg}$ for $^{90\\mathrm{~h~}}$ (Figure 6c), which is one of the highest $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production yields in acidic media, to the best of our knowledge (Table S11). Moreover, the $\\mathrm{Co-N\\SAC_{Dp}}$ after the stability test shows no aggregated Co nanoparticles and maintains the atomical dispersion of Co species according to the XRD analysis (Figure S40), TEM, and AC-HAADF-STEM results (Figure S41), confirming its robust stability. \n\nIn a preliminary application, the collected electrolyte after 30 h is used to decompose $200~\\mathrm{ppm}$ of methylene blue (MB, pH $=1$ , containing $10\\ \\mathrm{\\bar{mmol}\\ F e^{2\\bar{+}}}$ ). After adding the electrolyte to the MB solution, the MB can be totally removed (Figure S42), indicative of the promising potential for pollutant degradation. Furthermore, we also have compared the electro-Fenton activity of the $\\mathrm{Co-N}\\ S\\mathrm{AC_{Dp}}$ and $\\mathrm{Co-N}\\ \\mathrm{SAC_{Mm}},$ and the recalcitrant CBZ is selected as the targeted organic pollutant65 (Figures S43 and S44). As shown in Figure 6e, the $\\mathrm{Co-N}$ $S\\mathrm{{AC}_{D p}}$ shows a superior degradation ability to the $\\mathrm{Co-N}$ $S A C_{\\mathrm{Mm}}$ in which the $10\\ \\mathrm{ppm\\CBZ}$ can be completely removed within $12~\\mathrm{min}$ (Figure S45). Therefore, the remarkable $\\mathrm{H}_{2}\\mathrm{O}_{2}$ productivity and outstanding degradation ability make the Co−N ${\\mathrm{SAC}}_{\\mathrm{Dp}}$ a promising and ready catalyst for the actual application. \n\n# CONCLUSIONS \n\nIn summary, by combining DFT calculations and experiments, we addressed key issues about the structure−function relationship for a series of $\\mathrm{Co-N_{4}}$ catalysts with different coordination structures and the ORR pathway over this family of SACs. We disclose that the pyrrole-type $\\mathrm{CoN}_{4}$ mainly accounts for the $2\\mathrm{e}^{-}$ ORR for producing $\\mathrm{H}_{2}\\mathrm{O}_{2},$ while the pyridine-motif promotes the $4\\mathrm{e}^{-}$ ORR. This striking difference may originate from the electron interaction with the important $\\mathrm{HOO^{*}}$ intermediate and the accompanying spin state difference between the different coordinations of the active center. Experimentally, a series of $\\scriptstyle\\mathrm{Co-N}$ SAC catalysts with different coordination structures were prepared. The $\\mathrm{Co-N}$ $S\\mathrm{AC_{Dp}}$ with pyrrole-type of $\\mathrm{CoN}_{4}$ and the $\\mathrm{Co-NSAC_{Mm}}$ with pyridine-type of $\\mathrm{CoN}_{4}$ showed selectivity toward $2\\mathrm{e}^{-}$ ORR and $4\\mathrm{e}^{-}$ ORR, respectively. Impressively, the $\\mathrm{Co-N}$ $S\\mathrm{AC}_{\\mathrm{Dp}}$ exhibits superior $2\\mathrm{e}^{-}$ ORR performances than most previously reported catalysts in acidic media, with a mass activity of 14.4 A $\\mathrm{{\\bar{g}_{c a t.}}^{-1}}$ at $0.5\\mathrm{V}$ versus RHE and $\\mathrm{H}_{2}\\mathrm{O}_{2}$ selectivity of $94\\%$ at 0.3 V versus RHE. Our experimental results indicate that the $\\mathrm{Co-}$ N $S\\mathrm{AC_{D_{p}}}$ (pyrrole-type $\\mathrm{CoN}_{4}\\mathrm{\\cdot}$ ) with weaker intermediate interaction favors the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production compared to the $\\mathrm{Co-}$ N $S\\mathrm{AC_{Mm}}$ (pyridine-type $\\mathrm{CoN}_{4}\\mathrm{\\cdot}$ ). This is also in agreement with our DFT calculation results over these intermediates. Importantly, the $\\mathrm{Co-N\\SAC_{Dp}}$ has been tested in a flow cell, accumulating a $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yield of $\\Bar{2}032\\mathrm{mg}$ for $90\\mathrm{~h~}$ . As such, this work identifies the pyrrole-type $\\mathrm{CoN_{4}}$ as the highly active $\\mathrm{Co-}$ N coordination motif for electrosynthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2},$ and provides fundamental insights into the ORR mechanism on SAC catalysts and beyond. \n\n# ASSOCIATED CONTENT \n\n# $\\bullet$ Supporting Information \n\nThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jacs.2c01194. \n\nCatalyst synthesis, characterization, ORR measurement, kinetic barrier, DOS analysis, SEM images, TEM images, XRD patterns, FT-IR spectra, XANES spectra, O 1s XPS spectra, additional X-ray absorption spectroscopy (XAS) fitting data, $\\mathbf{N}_{2}$ adsorption/desorption isotherms and BET data, ECSA data, additional ORR performance data, in situ ATR−SEIRAS setup and spectra, catalyst characterization after stability test, CBZ degradation data, and performance comparison with the reported catalysts (PDF) \n\n# AUTHOR INFORMATION \n\n# Corresponding Authors \n\nMingshan Zhu − Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, 511443 Guangzhou, China; Email: zhumingshan@jnu.edu.cn \nEmiliano Cortés − Nanoinstitut München, Fakultät für Physik, Ludwig-Maximilians-Universität München, 80539 München, Germany; $\\circledcirc$ orcid.org/0000-0001-8248-4165; Email: emiliano.cortes@lmu.de \nMin Liu − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China; $\\circledcirc$ orcid.org/0000-0002-9007-4817; Email: minliu@ csu.edu.cn \n\n# Authors \n\nShanyong Chen − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China; Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, 511443 Guangzhou, China; $\\textcircled{1}$ orcid.org/0000- \n0002-3944-1810 Tao Luo − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China Xiaoqing Li − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China Kejun Chen − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China Junwei Fu − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China; $\\circledcirc$ orcid.org/0000-0003-0190-1663 Kang Liu − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China; orcid.org/0000-0002-8781-7747 Chao Cai − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China; $\\circledcirc$ orcid.org/0000-0002-3695-3247 Qiyou Wang − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China Hongmei Li − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China Yu Chen − Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, State Key Laboratory of Powder Metallurgy, School of Physical and Electronics, Central South University, 410083 Changsha, China Chao Ma − School of Materials Science and Engineering, Hunan University, Changsha 410082, China; $\\circledcirc$ orcid.org/ \n0000-0001-8599-9340 Li Zhu − Nanoinstitut München, Fakultät für Physik, LudwigMaximilians-Universität München, 80539 München, Germany Ying-Rui Lu − National Synchrotron Radiation Research Center, Hsinchu 30076, Taiwan; $\\circledcirc$ orcid.org/0000-0002- \n6002-5627 Ting-Shan Chan − National Synchrotron Radiation Research Center, Hsinchu 30076, Taiwan \n\n# Author Contributions \n\n$^{\\#}{\\cal S}.C.$ . and T.L. contributed equally. Notes The authors declare no competing financial interest. \n\n# ACKNOWLEDGMENTS \n\nThis study was financially supported by the Natural Science Foundation of China (grant nos. 21872174, 22002189, and U1932148), International Science and Technology Cooperation Program (grant no. 2017YFE0127800), China Postdoctoral Science Foundation (2021M701415 and 2022T150265), Hunan Provincial key research and development program (2020WK2002), the Hunan Provincial Natural Science Foundation of China (2020JJ2041 and 2020JJ5691), Hunan Provincial Science and Technology Program (2017XK2026), Guangdong Basic and Applied Basic Research Foundation (nos. 2020B1515020038 and 2021A1515110907), Shenzhen Science and Technology Innovation Project (grant no. JCYJ20180307151313532), Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy\u0001EXC 2089/1-390776260, the Bavarian program Solar Energies Go Hybrid (SolTech), the Center for NanoScience (CeNS), and the European Commission through the ERC Starting Grant CATALIGHT (802989). M.Z. acknowledges the support of the Pearl River Talent Recruitment Program of Guangdong Province (2019QN01L148). The authors gratefully thank the National Synchrotron Radiation Research Center (NSRRC, the TLS 01C1 and TLS 16A1 beamlines, Taiwan) for XAFS measurement and BL10B in NSRL for soft XAS characterizations by Synchrotron Radiation. We are grateful for resources from the High Performance Computing Center of Central South University. \n\n# REFERENCES \n\n(1) Xia, C.; Xia, Y.; Zhu, P.; Fan, L.; Wang, H. Direct electrosynthesis of pure aqueous $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solutions up to $20\\%$ by weight using a solid electrolyte. Science 2019, 366, 226−231. \n(2) Bu, Y.; Wang, Y.; Han, G.-F.; Zhao, Y.; Ge, X.; Li, F.; Zhang, Z.; Zhong, Q.; Baek, J.-B. Carbon-Based Electrocatalysts for Efficient Hydrogen Peroxide Production. Adv. Mater. 2021, 33, 2103266. (3) Jiang, K.; Back, S.; Akey, A. J.; Xia, C.; Hu, Y.; Liang, W.; Schaak, D.; Stavitski, E.; Nørskov, J. K.; Siahrostami, S.; Wang, H. Highly selective oxygen reduction to hydrogen peroxide on transition metal single atom coordination. Nat. Commun. 2019, 10, 3997. \n(4) Jung, E.; Shin, H.; Lee, B.-H.; Efremov, V.; Lee, S.; Lee, H. S.; Kim, J.; Hooch Antink, W.; Park, S.; Lee, K.-S.; Cho, S.-P.; Yoo, J. S.; Sung, Y.-E.; Hyeon, T. Atomic-level tuning of ${\\mathrm{Co}}{-}{\\mathrm{N}}{-}{\\mathrm{C}}$ catalyst for high-performance electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Nat. Mater. 2020, 19, 436−442. \n(5) Gao, R.; Pan, L.; Li, Z.; Shi, C.; Yao, Y.; Zhang, X.; Zou, J.-J. Engineering Facets and Oxygen Vacancies over Hematite Single Crystal for Intensified Electrocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ Production. Adv. Funct. Mater. 2020, 30, 1910539. \n(6) Li, B.- $\\mathrm{.Q.,}$ Zhao, C.-X.; Liu, J.-N.; Zhang, $\\mathsf{Q}.$ Electrosynthesis of Hydrogen Peroxide Synergistically Catalyzed by Atomic ${\\mathrm{Co-N_{x}-C}}$ Sites and Oxygen Functional Groups in Noble-Metal-Free Electrocatalysts. Adv. Mater. 2019, 31, 1808173. \n(7) Jia, Y.; Xue, Z.; Yang, J.; Liu, Q.; Xian, J.; Zhong, Y.; Sun, Y.; Zhang, X.; Liu, Q.; Yao, D.; Li, G. Tailoring the Electronic Structure of an Atomically Dispersed Zinc Electrocatalyst: Coordination Environment Regulation for High Selectivity Oxygen Reduction. Angew. Chem., Int. Ed. 2022, 61, No. e202110838. \n(8) Choi, C. H.; Kim, M.; Kwon, H. C.; Cho, S. J.; Yun, S.; Kim, H.- T.; Mayrhofer, K. J. J.; Kim, H.; Choi, M. Tuning selectivity of electrochemical reactions by atomically dispersed platinum catalyst. Nat. Commun. 2016, 7, 10922. \n(9) Xia, F.; Li, B.; Liu, Y.; Liu, Y.; Gao, S.; Lu, ${\\mathrm{K}}.{\\mathrm{}}$ Kaelin, J.; Wang, $\\mathrm{R.},$ Marks, T. J.; Cheng, Y. Carbon Free and Noble Metal Free $\\mathrm{Ni}_{2}\\mathrm{Mo}_{6}\\mathrm{S}_{8}$ Electrocatalyst for Selective Electrosynthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Adv. Funct. Mater. 2021, 31, 2104716. \n(10) Wang, Y.; Shi, R.; Shang, L.; Waterhouse, G. I. N.; Zhao, J.; Zhang, $\\mathrm{Q.;}$ Gu, L.; Zhang, T. High-Efficiency Oxygen Reduction to Hydrogen Peroxide Catalyzed by Nickel Single-Atom Catalysts with Tetradentate $\\mathbf{N}_{2}\\mathbf{O}_{2}$ Coordination in a Three-Phase Flow Cell. Angew. Chem., Int. Ed. 2020, 59, 13057−13062. \n(11) Liu, W.; Feng, J.; Yin, R.; Ni, Y.; Zheng, D.; Que, W.; Niu, X.; Dai, X.; Shi, W.; Wu, F.; Yang, J.; Cao, X. Tailoring oxygenated groups of monolithic cobalt-nitrogen-carbon frameworks for highly efficient hydrogen peroxide production in acidic media. Chem. Eng. J. 2022, 430, 132990. \n(12) Tang, C.; Jiao, Y.; Shi, B.; Liu, J.-N.; Xie, Z.; Chen, X.; Zhang, $\\mathrm{Q.;}$ Qiao, S.-Z. Coordination Tunes Selectivity: Two-Electron Oxygen Reduction on High-Loading Molybdenum Single-Atom Catalysts. Angew. Chem., Int. Ed. 2020, 59, 9171−9176. \n(13) Li, L.; Tang, C.; Zheng, Y.; Xia, B.; Zhou, X.; Xu, H.; Qiao, S.- Z. Tailoring Selectivity of Electrochemical Hydrogen Peroxide Generation by Tunable Pyrrolic-Nitrogen-Carbon. Adv. Energy Mater. 2020, 10, 2000789. \n(14) Dong, K.; Lei, Y.; Zhao, H.; Liang, J.; Ding, P.; Liu, $\\mathrm{Q.j}$ Xu, Z.; Lu, S.; Li, Q.; Sun, X. Noble-metal-free electrocatalysts toward $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. J. Mater. Chem. A 2020, 8, 23123−23141. \n(15) Wang, Y.; Waterhouse, G. I. N.; Shang, L.; Zhang, T. Electrocatalytic Oxygen Reduction to Hydrogen Peroxide: From Homogeneous to Heterogeneous Electrocatalysis. Adv. Energy Mater. 2021, 11, 2003323. \n(16) Wang, M.; Zhang, N.; Feng, Y.; Hu, Z.; Shao, $\\mathrm{Q.;}$ Huang, X. Partially Pyrolyzed Binary Metal-Organic Framework Nanosheets for Efficient Electrochemical Hydrogen Peroxide Synthesis. Angew. Chem., Int. Ed. 2020, 59, 14373−14377. \n(17) Chen, S.; Luo, T.; Chen, K.; Lin, Y.; Fu, J.; Liu, K.; Cai, C.; Wang, $\\mathrm{Q.;}$ Li, H.; Li, X.; Hu, J.; Li, H.; Zhu, M.; Liu, M. Chemical Identification of Catalytically Active Sites on Oxygen-doped Carbon Nanosheet to Decipher the High Activity for Electro-synthesis Hydrogen Peroxide. Angew. Chem., Int. Ed. 2021, 60, 16607−16614. (18) Yang, Q.; Xu, W.; Gong, S.; Zheng, G.; Tian, Z.; Wen, Y.; Peng, L.; Zhang, L.; Lu, Z.; Chen, L. Atomically dispersed Lewis acid sites boost 2-electron oxygen reduction activity of carbon-based catalysts. Nat. Commun. 2020, 11, 5478. \n(19) Xu, Z.; Liang, J.; Wang, Y.; Dong, K.; Shi, X.; Liu, $\\mathrm{Q.;}$ Luo, Y.; Li, T.; Jia, Y.; Asiri, A. M.; Feng, Z.; Wang, Y.; Ma, D.; Sun, X. Enhanced Electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ Production via Two-Electron Oxygen Reduction Enabled by Surface-Derived Amorphous Oxygen-Deficient $\\mathrm{TiO}_{2-\\mathrm{x}}.$ ACS Appl. Mater. Interfaces 2021, 13, 33182− 33187. \n(20) Zhang, F.; Zhu, Y.; Tang, C.; Chen, Y.; Qian, B.; Hu, Z.; Chang, Y.-C.; Pao, C.-W.; Lin, $\\mathrm{Q.;}$ Kazemi, S. A.; Wang, Y.; Zhang, L.; Zhang, X.; Wang, H. High-Efficiency Electrosynthesis of Hydrogen Peroxide from Oxygen Reduction Enabled by a Tungsten Single Atom Catalyst with Unique Terdentate $\\mathbf{N}_{1}\\mathbf{O}_{2}$ Coordination. Adv. Funct. Mater. 2021, 32, 2110224. \n(21) Xia, Y.; Zhao, X.; Xia, C.; Wu, Z.-Y.; Zhu, P.; Kim, J. Y.; Bai, X.; Gao, G.; Hu, Y.; Zhong, J.; Liu, Y.; Wang, H. Highly active and selective oxygen reduction to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ on boron-doped carbon for high production rates. Nat. Commun. 2021, 12, 4225. \n(22) Zhang, X.; Xia, Y.; Xia, C.; Wang, H. Insights into PracticalScale Electrochemical $\\mathrm{H}_{2}\\mathrm{O}_{2}$ Synthesis. Trends Chem. 2020, 2, 942− 953. \n(23) Chang, $\\mathrm{Q.;}$ Zhang, P.; Mostaghimi, A. H. B.; Zhao, X.; Denny, S. R.; Lee, J. H.; Gao, H.; Zhang, Y.; Xin, H. L.; Siahrostami, S.; Chen, J. G.; Chen, Z. Promoting $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production via 2-electron oxygen reduction by coordinating partially oxidized Pd with defect carbon. Nat. Commun. 2020, 11, 2178. (24) Zhang, $\\mathrm{Q.;}$ Tan, X.; Bedford, N. M.; Han, Z.; Thomsen, L.; Smith, S.; Amal, R.; Lu, X. Direct insights into the role of epoxy groups on cobalt sites for acidic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Nat. Commun. 2020, 11, 4181. \n(25) Siahrostami, S.; Verdaguer-Casadevall, A.; Karamad, M.; Deiana, D.; Malacrida, P.; Wickman, B.; Escudero-Escribano, M.; Paoli, E. A.; Frydendal, R.; Hansen, T. W.; Chorkendorff, I.; Stephens, I. E. L.; Rossmeisl, J. Enabling direct $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production through rational electrocatalyst design. Nat. Mater. 2013, 12, 1137−1143. (26) Verdaguer-Casadevall, A.; Deiana, D.; Karamad, M.; Siahrostami, S.; Malacrida, P.; Hansen, T. W.; Rossmeisl, J.; Chorkendorff, I.; Stephens, I. E. L. Trends in the Electrochemical Synthesis of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ : Enhancing Activity and Selectivity by Electrocatalytic Site Engineering. Nano Lett. 2014, 14, 1603−1608. \n(27) Fortunato, G. V.; Pizzutilo, E.; Mingers, A. M.; Kasian, O.; Cherevko, S.; Cardoso, E. S. F.; Mayrhofer, K. J. J.; Maia, G.; Ledendecker, M. Impact of Palladium Loading and Interparticle Distance on the Selectivity for the Oxygen Reduction Reaction toward Hydrogen Peroxide. J. Phys. Chem. C 2018, 122, 15878− 15885. \n(28) Jirkovský, J. S.; Halasa, M.; Schiffrin, D. J. Kinetics of electrocatalytic reduction of oxygen and hydrogen peroxide on dispersed gold nanoparticles. Phys. Chem. Chem. Phys. 2010, 12, 8042−8053. \n(29) Sheng, H.; Janes, A. N.; Ross, R. D.; Kaiman, D.; Huang, J.; Song, B.; Schmidt, J. R.; Jin, S. Stable and selective electrosynthesis of hydrogen peroxide and the electro-Fenton process on $\\mathbf{CoSe}_{2}$ polymorph catalysts. Energy Environ. Sci. 2020, 13, 4189−4203. (30) Sheng, H.; Hermes, E. D.; Yang, X.; Ying, D.; Janes, A. N.; Li, W.; Schmidt, J. R.; Jin, S. Electrocatalytic Production of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ by Selective Oxygen Reduction Using Earth-Abundant Cobalt Pyrite $(\\mathrm{CoS}_{2})$ . ACS Catal. 2019, 9, 8433−8442. \n(31) Zhang, X.-L.; Su, X.; Zheng, Y.-R.; Hu, S.-J.; Shi, L.; Gao, F.-Y.; Yang, P.-P.; Niu, Z.-Z.; Wu, Z.-Z.; Qin, S.; Wu, R.; Duan, Y.; Gu, C.; Zheng, X.-S.; Zhu, J.-F.; Gao, M.-R. Strongly Coupled Cobalt Diselenide Monolayers for Selective Electrocatalytic Oxygen Reduction to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ under Acidic Conditions. Angew. Chem., Int. Ed. 2021, 60, 26922−26931. \n(32) Liang, J.; Wang, Y.; Liu, $\\mathrm{Q.}$ Luo, Y.; Li, T.; Zhao, H.; Lu, S.; Zhang, F.; Asiri, A. M.; Liu, F.; Ma, D.; Sun, X. Electrocatalytic hydrogen peroxide production in acidic media enabled by $\\mathrm{Ni}S_{2}$ nanosheets. J. Mater. Chem. A 2021, 9, 6117−6122. \n(33) Ross, R. D.; Sheng, H.; Parihar, A.; Huang, J.; Jin, S. Compositionally Tuned Trimetallic Thiospinel Catalysts for Enhanced Electrosynthesis of Hydrogen Peroxide and Built-In Hydroxyl Radical Generation. ACS Catal. 2021, 11, 12643−12650. \n(34) Tang, C.; Chen, L.; Li, H.; Li, L.; Jiao, Y.; Zheng, Y.; Xu, H.; Davey, ${\\mathrm{K}}.{\\mathrm{}}$ Qiao, S.-Z. Tailoring Acidic Oxygen Reduction Selectivity on Single-Atom Catalysts via Modification of First and Second Coordination Spheres. J. Am. Chem. Soc. 2021, 143, 7819−7827. (35) Zhao, $\\mathrm{Q.;}$ Wang, Y.; Lai, W.-H.; Xiao, F.; Lyu, Y.; Liao, C.; Shao, M. Approaching a high-rate and sustainable production of hydrogen peroxide: oxygen reduction on Co-N-C single-atom electrocatalysts in simulated seawater. Energy Environ. Sci. 2021, 14, 5444−5456. \n(36) Shen, ${\\mathrm{R}};$ Chen, W.; Peng, $\\mathrm{Q.j}$ Lu, S.; Zheng, L.; Cao, X.; Wang, Y.; Zhu, W.; Zhang, J.; Zhuang, Z.; Chen, C.; Wang, D.; Li, Y. HighConcentration Single Atomic Pt Sites on Hollow CuSx for Selective $\\mathrm{O}_{2}$ Reduction to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in Acid Solution. Chem 2019, 5, 2099−2110. (37) Gao, J.; Liu, B. Progress of Electrochemical Hydrogen Peroxide Synthesis over Single Atom Catalysts. ACS Mater. Lett. 2020, 2, 1008−1024. \n(38) Zhu, Y.; Li, J.; Chen, Y.; Zou, J.; Cheng, $\\mathrm{Q.;}$ Chen, C.; Hu, W.; Zou, L.; Zou, Z.; Yang, B.; Yang, H. Switching the Oxygen Reduction Reaction Pathway via Tailoring the Electronic Structure of $\\mathrm{FeN_{4}/C}$ Catalysts. ACS Catal. 2021, 11, 13020−13027. \n(39) Park, J.; Nabae, Y.; Hayakawa, T.; Kakimoto, M.-a. Highly Selective Two-Electron Oxygen Reduction Catalyzed by Mesoporous Nitrogen-Doped Carbon. ACS Catal. 2014, 4, 3749−3754. (40) Pang, Y.; Wang, K.; Xie, H.; Sun, Y.; Titirici, M.-M.; Chai, G.-L. Mesoporous Carbon Hollow Spheres as Efficient Electrocatalysts for Oxygen Reduction to Hydrogen Peroxide in Neutral Electrolytes. ACS Catal. 2020, 10, 7434−7442. \n(41) Iglesias, D.; Giuliani, A.; Melchionna, M.; Marchesan, S.; Criado, A.; Nasi, L.; Bevilacqua, M.; Tavagnacco, C.; Vizza, F.; Prato, M.; Fornasiero, P. N-Doped Graphitized Carbon Nanohorns as a Forefront Electrocatalyst in Highly Selective $\\mathrm{~O}_{2}$ Reduction to $\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Chem 2018, 4, 106−123. \n(42) Gao, J.; Yang, H. b.; Huang, X.; Hung, S.-F.; Cai, W.; Jia, C.; Miao, S.; Chen, H. M.; Yang, X.; Huang, Y.; Zhang, T.; Liu, B. Enabling Direct $\\mathrm{H}_{2}\\mathrm{O}_{2}$ Production in Acidic Media through Rational Design of Transition Metal Single Atom Catalyst. Chem 2020, 6, 658−674. \n(43) Sun, Y.; Silvioli, L.; Sahraie, N. R.; Ju, W.; Li, J.; Zitolo, A.; Li, S.; Bagger, A.; Arnarson, L.; Wang, X.; Moeller, T.; Bernsmeier, D.; Rossmeisl, J.; Jaouen, F.; Strasser, P. Activity-Selectivity Trends in the Electrochemical Production of Hydrogen Peroxide over Single-Site Metal-Nitrogen-Carbon Catalysts. J. Am. Chem. Soc. 2019, 141, 12372−12381. \n(44) Wu, F.; Pan, C.; He, C.-T.; Han, Y.; Ma, W.; Wei, H.; Ji, W.; Chen, W.; Mao, J.; Yu, P.; Wang, D.; Mao, L.; Li, Y. Single-Atom Co− ${\\bf N}_{4}$ Electrocatalyst Enabling Four-Electron Oxygen Reduction with Enhanced Hydrogen Peroxide Tolerance for Selective Sensing. J. Am. Chem. Soc. 2020, 142, 16861−16867. \n(45) Han, Y.; Wang, Y.-G.; Chen, W.; Xu, R.; Zheng, L.; Zhang, J.; Luo, J.; Shen, R.-A.; Zhu, Y.; Cheong, W.-C.; Chen, C.; Peng, Q.; Wang, D.; Li, Y. Hollow N-Doped Carbon Spheres with Isolated Cobalt Single Atomic Sites: Superior Electrocatalysts for Oxygen Reduction. J. Am. Chem. Soc. 2017, 139, 17269−17272. \n(46) He, Y.; Shi, $\\mathrm{\\Q.;}$ Shan, W.; Li, X.; Kropf, A. J.; Wegener, E. C.; Wright, J.; Karakalos, S.; Su, D.; Cullen, D. A.; Wang, G.; Myers, D. J.; Wu, G. Dynamically Unveiling Metal−Nitrogen Coordination during Thermal Activation to Design High-Efficient Atomically Dispersed $\\mathrm{CoN_{4}}$ Active Sites. Angew. Chem., Int. Ed. 2021, 60, 9516−9526. (47) Wang, X. X.; Cullen, D. A.; Pan, Y.-T.; Hwang, S.; Wang, M.; Feng, Z.; Wang, J.; Engelhard, M. H.; Zhang, H.; He, Y.; Shao, Y.; Su, D.; More, K. L.; Spendelow, J. S.; Wu, G. Nitrogen-Coordinated Single Cobalt Atom Catalysts for Oxygen Reduction in Proton Exchange Membrane Fuel Cells. Adv. Mater. 2018, 30, 1706758. (48) He, Y.; Guo, H.; Hwang, S.; Yang, X.; He, Z.; Braaten, J.; Karakalos, S.; Shan, W.; Wang, M.; Zhou, H.; Feng, Z.; More, K. L.; Wang, G.; Su, D.; Cullen, D. A.; Fei, L.; Litster, S.; Wu, G. Single Cobalt Sites Dispersed in Hierarchically Porous Nanofiber Networks for Durable and High-Power PGM-Free Cathodes in Fuel Cells. Adv. Mater. 2020, 32, 2003577. \n(49) Wu, D.; Hu, J.; Zhu, C.; Zhang, J.; Jing, H.; Hao, C.; Shi, Y. Salt melt synthesis of Chlorella-derived nitrogen-doped porous carbon with atomically dispersed $\\mathrm{CoN_{4}}$ sites for efficient oxygen reduction reaction. J. Colloid Interface Sci. 2021, 586, 498−504. \n(50) Kulkarni, A.; Siahrostami, S.; Patel, A.; Nørskov, J. K. Understanding Catalytic Activity Trends in the Oxygen Reduction Reaction. Chem. Rev. 2018, 118, 2302−2312. \n(51) Duan, Z.; Henkelman, G. Surface Charge and Electrostatic Spin Crossover Effects in $\\mathrm{CoN_{4}}$ Electrocatalysts. ACS Catal. 2020, 10, 12148−12155. \n(52) Chen, Z.; Niu, H.; Ding, J.; Liu, H.; Chen, P.-H.; Lu, Y.-H.; Lu, Y.-R.; Zuo, W.; Han, L.; Guo, Y.; Hung, S.-F.; Zhai, Y. Unraveling the Origin of Sulfur-Doped Fe-N-C Single-Atom Catalyst for Enhanced Oxygen Reduction Activity: Effect of Iron Spin-State Tuning. Angew. Chem., Int. Ed. 2021, 60, 25404−25410. \n(53) Menga, D.; Low, J. L.; Li, Y.-S.; Arčon, I.; Koyutürk, B.; Wagner, F.; Ruiz-Zepeda, F.; Gaberšček, M.; Paulus, B.; Fellinger, T.- P. Resolving the Dilemma of Fe-N-C Catalysts by the Selective Synthesis of Tetrapyrrolic Active Sites via an Imprinting Strategy. J. Am. Chem. Soc. 2021, 143, 18010−18019. \n(54) Wang, H.; Shao, Y.; Mei, S.; Lu, Y.; Zhang, M.; Sun, J.-k.; Matyjaszewski, K.; Antonietti, M.; Yuan, J. Polymer-Derived Heteroatom-Doped Porous Carbon Materials. Chem. Rev. 2020, 120, 9363−9419. \n(55) Chen, S.; Bi, F.; Xiang, K.; Zhang, Y.; Hao, P.; Li, M.; Zhao, B.; Guo, X. Reactive Template-Derived CoFe/N-Doped Carbon Nanosheets as Highly Efficient Electrocatalysts toward Oxygen Reduction, Oxygen Evolution, and Hydrogen Evolution. ACS Sustainable Chem. Eng. 2019, 7, 15278−15288. \n(56) Chen, S.; Yan, Y.; Hao, P.; Li, M.; Liang, J.; Guo, J.; Zhang, Y.; Chen, S.; Ding, W.; Guo, X. Iron Nanoparticles Encapsulated in S,NCodoped Carbon: Sulfur Doping Enriches Surface Electron Density and Enhances Electrocatalytic Activity toward Oxygen Reduction. ACS Appl. Mater. Interfaces 2020, 12, 12686−12695. \n(57) Zhang, N.; Zhou, T.; Chen, M.; Feng, H.; Yuan, R.; Zhong, C. a.; Yan, W.; Tian, Y.; Wu, X.; Chu, W.; Wu, C.; Xie, Y. High-purity pyrrole-type $\\mathrm{FeN}_{4}$ sites as a superior oxygen reduction electrocatalyst. Energy Environ. Sci. 2020, 13, 111−118. \n(58) Zhang, Z.; Dou, M.; Ji, J.; Wang, F. Phthalocyanine tethered iron phthalocyanine on graphitized carbon black as superior electrocatalyst for oxygen reduction reaction. Nano Energy 2017, 34, 338−343. \n(59) Lin, Y.; Liu, K.; Chen, K.; Xu, Y.; Li, H.; Hu, J.; Lu, Y.-R.; Chan, T.-S.; Qiu, X.; Fu, J.; Liu, M. Tuning Charge Distribution of $\\mathrm{FeN}_{4}$ via External N for Enhanced Oxygen Reduction Reaction. ACS Catal. 2021, 11, 6304−6315. \n(60) Chen, K.; Liu, K.; An, P.; Li, H.; Lin, Y.; Hu, J.; Jia, C.; Fu, J.; Li, H.; Liu, H.; Lin, Z.; Li, W.; Li, J.; Lu, Y.-R.; Chan, T.-S.; Zhang, N.; Liu, M. Iron phthalocyanine with coordination induced electronic localization to boost oxygen reduction reaction. Nat. Commun. 2020, 11, 4173. \n(61) Nayak, S.; McPherson, I. J.; Vincent, K. A. Adsorbed Intermediates in Oxygen Reduction on Platinum Nanoparticles Observed by In Situ IR Spectroscopy. Angew. Chem., Int. Ed. 2018, 57, 12855−12858. \n(62) Wang, T.; Zhang, Y.; Huang, B.; Cai, B.; Rao, R. R.; Giordano, L.; Sun, S.-G.; Shao-Horn, Y. Enhancing oxygen reduction electrocatalysis by tuning interfacial hydrogen bonds. Nat. Catal. 2021, 4, 753−762. \n(63) Ohta, N.; Nomura, K.; Yagi, I. Adsorption and Electroreduction of Oxygen on Gold in Acidic Media: In Situ Spectroscopic Identification of Adsorbed Molecular Oxygen and Hydrogen Superoxide. J. Phys. Chem. C 2012, 116, 14390−14400. \n(64) Zhou, P.; Li, L.; Mosali, V. S. S.; Chen, Y.; Luan, P.; Gu, $\\mathrm{Q.;}$ Turner, D. R.; Huang, L.; Zhang, J. Electrochemical Hydrogenation of Furfural in Aqueous Acetic Acid Media with Enhanced 2-Methylfuran Selectivity Using CuPd Bimetallic Catalysts. Angew. Chem., Int. Ed. 2022, 61, No. e202117809. \n(65) Zhang, L.; Zhao, X.; Niu, C.; Tang, N.; Guo, H.; Wen, X.; Liang, C.; Zeng, G. Enhanced activation of peroxymonosulfate by magnetic ${\\mathrm{Co}}_{3}{\\mathrm{MnFeO}}_{6}$ nanoparticles for removal of carbamazepine: Efficiency, synergetic mechanism and stability. Chem. Eng. J. 2019, 362, 851−864. \n\n# Recommended by ACS \n\n# Atomically Dispersed Co-N/C Catalyst for Divergent Synthesis of Nitrogen-Containing Compounds from Alkenes \n\nWenxuan Xue, Conghui Tang, et al. 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JANUARY 10, 2023 \nACS CATALYSIS \n\nREAD \n\n# Get More Suggestions > " + }, + { + "id": "10.1038_s41467-022-31427-9", + "DOI": "10.1038/s41467-022-31427-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-31427-9", + "Relative Dir Path": "mds/10.1038_s41467-022-31427-9", + "Article Title": "Boosting electrocatalytic CO2-to-ethanol production via asymmetric C-C coupling", + "Authors": "Wang, PT; Yang, H; Tang, C; Wu, Y; Zheng, Y; Cheng, T; Davey, K; Huang, XQ; Qiao, SZ", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "It is of high interest to convert CO2 into valuable ethanol product. Here the authors demonstrate the asymmetric C-C coupling triggered on Ag-modified oxide-derived Cu sites can accelerate and steer the reaction pathway for ethanol production with high faradaic efficiency and current density. Electroreduction of carbon dioxide (CO2) into multicarbon products provides possibility of large-scale chemicals production and is therefore of significant research and commercial interest. However, the production efficiency for ethanol (EtOH), a significant chemical feedstock, is impractically low because of limited selectivity, especially under high current operation. Here we report a new silver-modified copper-oxide catalyst (dCu(2)O/Ag-2.3%) that exhibits a significant Faradaic efficiency of 40.8% and energy efficiency of 22.3% for boosted EtOH production. Importantly, it achieves CO2-to-ethanol conversion under high current operation with partial current density of 326.4 mA cm(-2) at -0.87 V vs reversible hydrogen electrode to rank highly significantly amongst reported Cu-based catalysts. Based on in situ spectra studies we show that significantly boosted production results from tailored introduction of Ag to optimize the coordinated number and oxide state of surface Cu sites, in which the *CO adsorption is steered as both atop and bridge configuration to trigger asymmetric C-C coupling for stablization of EtOH intermediates.", + "Times Cited, WoS Core": 302, + "Times Cited, All Databases": 310, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000830675000015", + "Markdown": "# Boosting electrocatalytic CO2–to–ethanol production via asymmetric C–C coupling \n\nPengtang Wang1,2,4, Hao Yang 3,4, Cheng Tang1, Yu Wu3, Yao Zheng 1, Tao Cheng 3, Kenneth Davey 1, Xiaoqing Huang 2✉ & Shi-Zhang Qiao 1✉ \n\nElectroreduction of carbon dioxide $(\\mathsf{C O}_{2})$ into multicarbon products provides possibility of large-scale chemicals production and is therefore of significant research and commercial interest. However, the production efficiency for ethanol (EtOH), a significant chemical feedstock, is impractically low because of limited selectivity, especially under high current operation. Here we report a new silver–modified copper–oxide catalyst $\\mathrm{\\langledCu}_{2}\\mathrm{O}/\\mathsf{A g}_{2.3\\%})$ that exhibits a significant Faradaic efficiency of $40.8\\%$ and energy efficiency of $22.3\\%$ for boosted EtOH production. Importantly, it achieves ${\\mathsf{C O}}_{2}$ –to–ethanol conversion under high current operation with partial current density of $326.4\\mathsf{m A c m}^{-2}$ at $-0.87\\vee$ vs reversible hydrogen electrode to rank highly significantly amongst reported $\\mathsf{C u}$ –based catalysts. Based on in situ spectra studies we show that significantly boosted production results from tailored introduction of $\\mathsf{A g}$ to optimize the coordinated number and oxide state of surface Cu sites, in which the $^{\\star}{\\cal C}{\\sf O}$ adsorption is steered as both atop and bridge configuration to trigger asymmetric C–C coupling for stablization of EtOH intermediates. \n\nElcehcetrmoirceadlsucatinodn oefl cisa sbeoen do obxeidpe chemicals and fuels is seen to be practically promising for $\\left(\\mathrm{CO}_{2}\\right)$ tpo hmiigshi-nvgalfuoer the utilization of renewable electricity and mitigation of $\\mathrm{CO}_{2}$ emissions, which has emerged as a frontier in energy conversion and carbon neutrality1–3. During the $\\mathrm{CO}_{2}$ reduction reaction $(\\mathrm{CO}_{2}\\mathrm{RR})$ , the applied electrical energy is converted to stored chemical energy via reorganizing the molecular bonds in $\\mathrm{CO}_{2}$ and water to generate products with one $\\left(\\mathrm{C}_{1}\\right)$ , or two or more $(\\mathsf C_{2+})$ carbon atoms, under the effect of catalysts4–6. Most metal catalysts such as gold (Au), silver $(\\operatorname{Ag})$ , tin $(\\mathsf{S}\\boldsymbol{\\mathrm{n}})$ , and lead $\\left(\\mathrm{Pb}\\right)$ generate a mix of $\\mathrm{C_{1}}$ products7,8, whilst only Cu-based catalysts transform $\\mathrm{CO}_{2}$ toward $\\mathrm{C}_{2+}$ products via coupling the adsorbed $^*\\mathrm{CO}$ intermediates9–11. Amongst the various $\\mathrm{C}_{2+}$ products formed on Cu catalysts, EtOH is important as the liquid fuel because of its wide application and high-energy-density and because it provides the possibility of long-term, large-scale and seasonal energy storage, and convenient transport3,12. The production of EtOH with high current density and Faradaic efficiency (FE) via Cu-based catalysts is significant to advancing $\\mathrm{CO}_{2}\\mathrm{RR}$ as a renewable chemical feedstock2,3,13. During ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ EtOH and ethylene $\\mathrm{(C_{2}H_{4})}$ are both 12-electron reduced products, and share the initial intermediates $^{*}_{\\mathrm{HCCOH}}$ . Given the more saturated structure of EtOH compared with that for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ , the next-intermediates for EtOH are more difficult to stabilize on a pure Cu surface compared with $\\mathrm{C}_{2}\\mathrm{H}_{4}$ . The production of EtOH via $C{\\mathrm{-}}\\mathrm{O}$ bond-reserving of $^{*}{\\mathrm{HCCOH}}$ will therefore have chemical difficulty in competing with $\\mathrm{C}_{2}\\mathrm{H}_{4}$ generation. This typically results in the EtOH production in the range of 2–3 times less than that for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ on Cu-based catalyst3,11–14. \n\nTo boost EtOH production, research interest has concentrated on optimal re-design of Cu-based catalysts5,6,15–22. Strategies including, control of morphology and facet16,17, vacancy steering18, dopant and modification engineering19,20, and defects control21,22 have been reported. Among these, the modification of Cu with other $\\mathrm{CO}_{2}.$ -–active metals to form Cubased bimetallic is reported as practically attractive15,23–28. For example, Jaramillo et al. reported Cu–Au bimetallic catalysts with boosted selectivity for $\\bar{\\mathrm{CO}}_{2}\\mathrm{RR}$ to EtOH, and a synergistic catalytic pathway with CO–tandem mechanism was proposed that CO was first generated on Au, desorbed and migrated to near Cu active sites where C–C coupling to EtOH was conducted24. Zheng et al. reported a boosted EtOH selectivity in a $\\mathrm{Cu}_{3}\\mathrm{Ag}_{1}$ bimetallic catalyst with electron-deficient Cu sites via promoting adsorption of key intermediates25. Clark et al. hypothesized that the boosted EtOH selectivity results from Aginduced strain effects of Cu surfaces that modulate EtOH production and suppresses the hydrogen evolution reaction (HER)26. Despite significant progress, the advances of reported bimetallic catalysts for FE of EtOH $(\\mathrm{FE}_{\\mathrm{EtOH}})$ remain limited, especially the production and output efficiency for EtOH is far from the current target for practical application29–38 (i.e., partial current density $>30\\bar{0}\\mathrm{mA}\\mathrm{cm}^{-2}$ and half-cell cathodic energy efficiencies $\\mathrm{(EE_{HC})}>20\\%$ ). In addition, the key impact of modified components on intrinsic kinetics of reported Cu-based bimetallic catalysts for $\\mathrm{CO}_{2}\\mathrm{RR}$ at high conversion rates is unclear, which significantly hinders understanding of the mechanism and catalyst design3,14. Taken together, there is a need therefore for more efficient catalysts and an improved understanding of the mechanism for $\\mathrm{CO}_{2}\\mathrm{RR}$ to practically boost EtOH under commercial current densities. \n\nHere, through modifying $\\mathrm{Ag}$ onto cubic $\\mathrm{Cu}_{2}\\mathrm{O}$ and activating under ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ we investigated derived $\\mathtt{C u A g}$ bimetallics $\\mathrm{(dCu_{2}O/}$ $\\mathrm{Ag)}$ ) with controlled morphology, phase, and composition for $\\mathrm{CO}_{2}\\mathrm{RR}$ at high current operation. In contrast to the $\\mathrm{Cu}_{2}\\mathrm{O}$ and Au-modified $\\mathrm{Cu}_{2}\\mathrm{O}$ derivatives which favor the conversion of $\\mathrm{CO}_{2}$ to $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and CO, respectively, the optimal $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ exhibited an asymmetric C–C coupling to stabilize reaction intermediates for boosted EtOH production under high current density. The as-obtained $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ exhibits FE and $\\mathrm{EE}_{\\mathrm{HC}}$ for EtOH of, $40.8\\%$ and $22.4\\%$ , respectively. We show in a direct comparison with reported catalysts that it has the greatest reported partial EtOH current density with $326.4\\mathrm{mA}\\mathrm{c}\\mathrm{\\bar{m}}^{-2}$ . In situ studies confirm that the redispersion of $\\mathbf{Ag}$ into $\\mathtt{C u}$ significantly optimizes the coordinated number and oxide state of Cu. In this way, the $^*\\mathrm{CO}$ binding strength is altered to form a blended adsorption configuration, that triggers asymmetric $C{\\mathrm{-}}C$ coupling for stabilization of EtOH intermediates, and results in boosted EtOH production. This work constructs an efficient catalyst for $\\mathrm{CO}_{2}\\mathrm{\\bar{R}R}$ with high EtOH selectivity at commercially relevant current densities, and provides guidance for designing catalysts with tailored selectivity in multi-electron reactions. \n\n# Results \n\nCatalyst preparation and characterization. Pristine Ag-modified $\\mathrm{Cu}_{2}\\mathrm{O}$ nanocubes $\\left(\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}\\ \\mathrm{NCs}\\right)$ were prepared by a one-pot seed-medium method in which $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs were achieved via reduction of $\\mathrm{Cu(OH)}_{2}$ at room temperature (RT, $25^{\\circ}\\mathrm{C})$ with ascorbic acid (AA) as a reducing agent, followed by the addition of ${\\mathrm{AgNO}}_{3}$ . Because of the appropriate lattice spacing match, the added ${\\mathrm{AgNO}}_{3}$ rapidly nucleates and grows due to the effect of AA to deposit ‘small’ $\\mathrm{Ag}$ nanoparticles $(\\mathrm{Ag\\NPs})$ on $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs surface (Fig. 1a). Transmission electron microscopy (TEM) images reveal that the $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}\\mathrm{NCs}$ exhibit heterostructure that Ag NPs sporadically adorn the $\\mathrm{Cu}_{2}\\mathrm{O}$ surface (Fig. 1b and Supplementary Fig. 1a), in comparison to $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs with cubic morphology and a side length of ${\\sim}45\\mathrm{nm}$ (Supplementary Fig. 2). X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy energy-dispersive X-ray spectroscopy (SEM-EDS) confirm that the ${\\bf A g N P s}$ in $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}\\mathrm{NCs}$ are metallic, with the content controlled to $2.3\\%$ (Fig. 1c and Supplementary Fig. 1b). High-resolution TEM (HRTEM) image highlights the interplanar spacing of the lattice fringes for $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs and $\\mathrm{AgNPs}$ regions to be $0.214\\mathrm{nm}$ and $0.236\\mathrm{nm}$ in $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ NCs. This finding is consistent with the $\\mathrm{Cu}_{2}\\mathrm{O}$ (200) plane and $\\mathrm{Ag}$ (111) plane, respectively (Fig. 1d). Powder $\\mathrm{\\DeltaX}$ -ray diffraction (XRD) was carried out to confirm the phase of $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}\\mathrm{NCs}$ . It was found that $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}$ NCs exhibit the same peak as for $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs which is attributed to the low Ag NPs content (Fig. 1e). In addition, the EDX mapping images for $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ NCs also display an apparent element separation between Ag NPs and $\\mathrm{Cu}_{2}\\mathrm{\\bar{O}}$ NCs, (Fig. 1f). XPS assesses the surface properties of catalysts. The peaks at 951.8 and $931.8\\mathrm{eV}$ for $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs are ascribed to, Cu $2p_{1/2}$ and ${\\cal{2}}p_{3/2},$ respectively, confirming the presence of $\\mathtt{C u(I)}$ in $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs (Fig. $1\\bar{\\bf g})^{39}$ . Following $\\mathrm{Ag}$ modification, two shoulder peaks for $\\mathrm{{Cu(II)}}$ were apparent in the XPS spectra, demonstrating that electrons transfer from $\\mathrm{Cu}_{2}\\mathrm{O}$ to $\\mathrm{Ag}$ . This finding is validated via the Auger electron spectroscopy (AES) for Cu LMM in which the peaks for $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ NCs downshifts to a lower kinetic energy compared with those for $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs (Supplementary Fig. 3). These findings indicate that an $\\mathrm{Ag/Cu}_{2}\\mathrm{O}$ heterostructure with altered electron structure for $\\mathrm{Cu}_{2}\\mathrm{O}$ was reached with $\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ NCs. \n\nCatalyst evolution under $\\mathbf{CO}_{2}\\mathbf{RR}$ Given the reported evolution of Cu-based catalysts under high current $\\mathrm{CO}_{2}\\mathrm{\\bar{R}R}^{36}$ , activation and in situ characterization was therefore conducted for $\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ NCs to determine the actual state of the catalyst during ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ A flow cell with gas diffusion electrode (GDE) was especially designed as a reactor for a high current test (Supplementary Fig. 4). As a basis for a detailed comparison, $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs and Au-modified $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs $(\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ NCs) with similar morphology, composition, and structure to $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ NCs were synthesized and assessed (Supplementary Fig. 5). The catalysts were deposited onto the GDE via spray-coating of the configured ink (details in Supplementary Methods). Activation was controlled by electroreduction of the parent material under $\\mathrm{CO}_{2}\\mathrm{RR}$ at a current density of $200\\mathrm{mAc}\\dot{\\mathrm{m}}^{-2}$ in 1 M KOH for $30\\mathrm{min}$ . The derived Cu-based catalysts obtained following activation supported on the GDE, denoted as $\\mathrm{dCu}_{2}\\mathrm{O}$ , ${\\mathrm{d}}\\mathrm{Cu}_{2}\\mathrm{O}/{\\mathrm{Ag}}.$ , and $\\mathsf{d C u}_{2}\\mathrm{O}/\\mathrm{A}\\mathrm{{u}}$ , were subjected to additional characterization. \n\n![](images/d54007c7e07734aeeab8d6823f246a1c8a087adafafb0d7d6145761a108b821e.jpg) \nFig. 1 Structural characterization of $\\mathsf{c u}_{2}\\mathsf{o}/\\mathsf{A g}$ NCs. a Schematic for preparation of $\\mathsf{C u}_{2}\\mathsf{O}/\\mathsf{A g N C s}$ . b TEM image, $\\bullet$ Ag $3d$ XPS curve, d HRTEM images and f EDS elemental mapping images of $\\mathsf{C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ NCs. e XRD patterns and $\\pmb{\\mathsf{g}}\\mathsf{C u}2p$ XPS curves for $C\\mathsf{u}_{2}\\mathsf{O}$ and $\\mathsf{C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ NCs. Scale bars, $10\\mathsf{n m}$ in $({\\pmb6})$ , $1\\mathsf{n m}$ in $(\\pmb{\\mathsf{d}})_{i}$ , and $100\\mathsf{n m}$ in $(\\pmb{\\uparrow})$ . White-color, orange and azure spheres in the model represent $\\circ,$ Cu, and $\\mathsf{A g}$ atoms, respectively. \n\nHigh-angle annular dark-field scanning TEM (HAADF STEM) and SEM images confirm that following activation the original cubic morphology and surface deposited NPs are visually less pronounced, and that instead, ragged surface and hollow structures formed in $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ and $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ (Fig. 2a and Supplementary Figs. 6 and 7a). Concomitantly, the original surface phase separation between deposited metal and $\\mathrm{Cu}$ is lost following activation as is confirmed in EDS mapping images (Fig. 2a, Supplementary Fig. 7b). The lattice space for $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ was altered to $0.210\\mathrm{nm}$ following activation, a value near to the Cu (111) facet (Fig. 2b). Ex situ XRD patterns reveal that the diffraction peaks for $\\mathrm{Cu}_{2}\\mathrm{O}$ for all catalysts are decreased significantly whilst the diffraction peaks for $\\mathtt{C u}$ became dominant. This finding demonstrates that all catalysts are transformed to mainly metallic Cu following activation (Supplementary Fig. 8). Compared with $\\mathsf{d C u}_{2}\\mathrm{O}_{:}$ , the XRD peaks of $\\mathrm{Cu}$ (111) for $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ exhibit a meaningful, slight shift to a higher degree to underscore that the original $\\mathrm{{Cu}}_{2}\\mathrm{{O}}/$ metal heterostructures are evolved into the bimetallic alloy following activation (Fig. 2c). \n\nTo gain insight into the changed valence states and coordination environment of $\\mathtt{C u}$ following activation, operando X-ray absorption spectra (XAS) of Cu K-edge was recorded under activation conditions. The X-ray absorption near-edge structure (XANES) spectra show that the edge features for $\\mathsf{d C u}_{2}\\mathrm{O}_{:}$ $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ , and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ are closed to those for the reference commercial Cufoil. This finding confirms that the valence state for $\\mathtt{C u}$ for these catalysts decrease following activation to lie between 0 and $+1$ , in following ordered sequence, $\\mathrm{dCu_{2}O}<\\mathrm{dCu_{2}O}/\\mathrm{Ag_{2.3\\%}}<\\mathrm{dCu_{2}O}/$ $\\mathrm{Au}_{2.3\\%}$ (Fig. 2d). The wavelet transform analysis confirms that the Cu–Cu region in all activated catalysts are located at ${\\sim}6.7\\mathring\\mathrm{A}^{-1}$ , suggesting that the alloyed $\\mathtt{C u A g}$ and CuAu do not result in significant change in $\\mathrm{{Cu-Cu}}$ bond length compared with the oxide-derived $\\mathrm{cu}$ (Fig. 2e). The corresponding Fourier transform curves (from extended $\\mathrm{\\DeltaX}$ -ray absorption fine structure (EXAFS) spectra) and fitted results of the first coordination shell for these activated catalysts show that the $\\mathrm{{Cu-Cu}}$ coordination located at ${\\sim}2.23\\mathrm{\\AA}$ is the dominant structure in each sample, whilst there remains another $\\mathrm{Cu-O}$ coordination peak at $1.{\\overset{\\cdot}{3}}5\\mathrm{\\AA}$ for $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ . This finding confirms that a significantly small fraction of $\\mathtt{C u(I)}$ remained for $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ and $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ following activation (Fig. $2\\mathrm{f-g}$ and Supplementary Table 1). The coordination number for $\\mathrm{{Cu-Cu}}$ in these catalysts was determined to equal, respectively, 11.4, 10.5, and 10.2 for ${\\mathrm{d}}\\mathrm{Cu}_{2}\\mathrm{O}.$ , $\\mathrm{dCu_{2}O/A g_{2.3\\%}},$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ (Supplementary Fig. 9). Except for variation in $\\mathrm{Cu},$ , the XPS for $\\mathrm{Ag}\\ 3d$ for $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ shows that the binding energy for $\\mathrm{Ag}\\ 3d_{5/2}$ shifts to a high level following activation. This evidences that the activation of alloying \n\n![](images/a4d8e8523e37c9b5f399d2d4b216600d8085607721075f55a557fe1435f1a6c8.jpg) \nFig. 2 Phase and coordination environment for $d C u_{2}O/A g$ catalysts. a HAADF–STEM image with EDS elemental mappings and b high resolution STEM image of $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ . c Enlarged XRD patterns for ${\\mathsf{d C u}}_{2}{\\mathsf{O}}$ , $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ and $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%}$ . d In situ XANES spectra and e Wavelet transform images of EXAFS data with optimized Morlet parameter (i.e., $\\kappa=5$ , $\\sigma=1)$ at Cu $\\mathsf{K}$ -edge for commercial $\\mathsf{C u}$ -foil, ${\\mathsf{d C u}}_{2}{\\mathsf{O}}_{\\iota}$ , $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ and $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%}$ . Fourier transform curves of in situ EXAFS data and corresponding fitted results (first coordination shell) for $\\mathbf{f}{\\mathsf{d C u}}_{2}{\\mathsf{O}}_{i}$ g $:\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ and h $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%}$ . Scale bars, $10\\mathsf{n m}$ in $\\mathbf{\\eta}(\\mathbf{a})$ and $1\\mathsf{n m}$ in $(\\bullet)$ . \n\nAg with $\\mathrm{Cu}$ induces electron transfer (Supplementary Fig. 10). Based on the foregoing, it is concluded that under electroreduction with highly significant structural rearrangement, the pristine metalmodified $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs evolves to Cu-based bimetallics in a regulated valence and coordination environment. \n\n$\\mathbf{CO}_{2}\\mathbf{RR}$ performance. $\\mathrm{CO}_{2}\\mathrm{RR}$ performance for the activated catalysts was directly evaluated via electrolyzing at specified currents (Supplementary Fig. 11). Figure 3a shows the linear sweep voltammetry curves for ${\\tt d C u}_{2}\\mathrm{O}$ , $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ and $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Au}_{2.3\\%}$ . It is seen in the figure that the current density for $\\mathrm{CO}_{2}\\mathrm{RR}$ of $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ are significantly increased, directly evidencing that modification boosted activity for $\\mathrm{CO}_{2}\\mathrm{RR}.$ The FEs were computed for liquid and gaseous product in the applied current range $200{-}800\\mathrm{mA}$ in $1\\mathbf{M}$ KOH by nuclear magnetic resonance (NMR, Supplementary Fig. 12) and gas chromatography (GC) (Supplementary Fig. 13) respectively. Figure 3b presents the FEs of $\\mathrm{C}_{2+}$ products $(\\mathrm{FEs}_{\\mathrm{C}2+})$ ) for these catalysts under different current. $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and EtOH are the major $\\mathrm{C}_{2+}$ products, plus minor acetate and $\\mathfrak{n}$ –propanol. With the applied current increased, all catalysts exhibited increased $\\mathrm{FEs}_{\\mathrm{C}2+}$ and a decreased FEs of CO $(\\mathrm{FEs}_{\\mathrm{co}})$ . Compared with the one–up $\\mathrm{FE}_{\\mathrm{C}2+}$ for ${\\tt d C u}_{2}\\mathrm{O}$ from 200 to $400\\mathrm{mA}$ , $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ exhibits greater $\\mathrm{FE}_{\\mathrm{C}2+}$ at significant current $>$ $600\\mathrm{mA}$ . Importantly, the total $\\mathrm{FE}_{\\mathrm{C}2+}$ for $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ is up to $82.1\\%$ at a current density $800\\mathrm{mAcm}^{-2}$ , to exhibit the greatest partial $\\mathrm{C}_{2+}$ current density of $656.8\\mathrm{mAcm}^{-2}$ and formation rate of $2042.2\\upmu\\mathrm{mol}\\mathrm{h}^{-1}\\mathrm{cm}^{-2}$ at $-2.11\\mathrm{V}$ with reference to the reversible hydrogen electrode 1 $\\mathrm{\\DeltaV_{RHE},}$ no $i R$ correction, Fig. 3c and Supplementary Fig. 14a). In contrast, the $\\mathrm{FE}_{\\mathrm{C}2+}$ for $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ is significantly less than that for $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ at all currents, confirming that the Au modification resulted in directly boosting only targeted CO generation, but not $C{\\mathrm{-}}C$ coupling. \n\n![](images/08a8e39a04feb98b5d786b93a0bf2102273d84439b190a5803486662a302fb4c.jpg) \nFig. 3 $C O_{2}R R$ performance for ${\\mathsf{d}}{\\mathsf{C u}}_{2}{\\mathsf{O}},$ $\\mathsf{d}\\mathsf{C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%}$ and $\\mathsf{d}\\mathsf{C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ . a Linear sweep voltammetry curves toward $C O_{2}R R$ for ${\\mathsf{d C u}}_{2}{\\mathsf{O}}_{\\iota}$ $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%}$ and $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ . b FE value of $\\mathsf C_{2+}$ products for ${\\mathsf{d C u}}_{2}{\\mathsf{O}}_{\\iota}$ , $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%}$ and $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ under selected current density. c Partial $\\mathsf C_{2+}$ current density and e $\\mathsf C_{2+}$ formation vs potential referred to reversible hydrogen electrode (RHE) on ${\\mathsf{d C u}}_{2}{\\mathsf{O}},$ $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%},$ and $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ . d Ratio of $\\mathsf{F E}_{\\mathsf{E t O H}}$ to $\\mathsf{F E}_{\\mathsf{C}2\\mathsf{H}4}$ on ${\\mathsf{d C u}}_{2}{\\mathsf{O}},$ $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%},$ and $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ under selected current density. f EtOH partial current density vs $\\mathsf{F E}_{\\mathsf{E t O H}}$ for reported $\\mathsf{C u}$ -based catalysts. Error bars correspond to the standard deviation of three independent measurements. \n\nWe analyzed the ratio of $\\mathrm{FE_{EtOH}/F E_{C2H4}}$ in $\\mathrm{C}_{2+}$ products at high current density on these catalysts. It is interesting that $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ reaches the $\\mathrm{FE_{EtOH}/F E_{C2H4}}$ ratio 1.17 at an applied current $800\\mathrm{mA}$ , which is significantly greater than that for ${\\tt d C u}_{2}\\mathrm{O}$ (0.51) and $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ of 0.71. This finding confirms that the $\\mathbf{Ag}$ modification significantly inhibits C–O bondbreaking and stabilizes intermediates for EtOH vs $\\mathrm{C}_{2}\\mathrm{H}_{4}$ (Fig. 3d). Relying on the boosted $\\mathrm{FE}_{\\mathrm{EtOH}}$ of $40.8~\\%$ at a high current density $(80\\mathrm{{0}\\ m A\\ c m^{-2}})$ , the $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ exhibits the greatest partial EtOH current density of $326.4\\mathrm{mAcm}^{-2}$ at $-2.1\\bar{1}\\ \\mathrm{V}_{\\mathrm{RHE}}$ (no iR correction, $-0.89\\mathrm{~V}_{\\mathrm{RHE}}$ with $85\\%$ iR correction, Supplementary Figs. 15 and 16). Importantly, this is 1.78 and 1.89 times greater than that for ${\\mathrm{\\dCu}}_{2}{\\mathrm{\\bar{O}}}$ and $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ , respectively (Fig. 3e). The EtOH formation for $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ could reach $1014.9\\upmu\\mathrm{mol}$ $\\mathrm{h}^{-1}\\mathrm{cm}^{-2}$ with current densities of $\\mathrm{800\\mA}\\mathrm{cm}^{-2}$ at $-2.11\\mathrm{V}_{\\mathrm{RHE}}$ (without $i R$ correction) (Supplementary Fig. 14b). Such highly significant performances for EtOH production on $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ were compared directly with reported catalysts (Fig. 3f, Supplementary Table 2). It is apparent that the $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ exhibits the greatest reported partial EtOH current density amongst these, and represents the ‘best’ production for electroreduction of $\\mathrm{CO}_{2}$ to EtOH. In addition, the $\\mathrm{EE}_{\\mathrm{HC}}$ for EtOH on $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ reaches $22.4\\%$ following $i R$ correction under similar conditions, a value greater than that for most catalysts (Supplementary Fig. 16d). In addition, the electrochemically active surface area (ECSA) for $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ was computed via different methods and compared, together with mass normalized current density for EtOH $\\bar{(\\mathrm{J_{ECSA}(E t O H)}}$ and $\\mathrm{J}_{\\mathrm{mass}}(\\mathrm{EtOH}))$ with independently reported studies (Supplementary Figs. 17 and 18 and Supplementary Table 3). The $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ exhibited superior JECSA(EtOH) and $\\mathrm{J}_{\\mathrm{mass}}(\\mathrm{EtOH})$ compared with reported catalysts, confirming that the improved EtOH current density for $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ is because of the intrinsic $\\mathrm{Ag}$ -modified oxide-derived Cu sites and not the changed ECSA and mass loading of the catalyst itself. \n\nBased on these findings therefore of highly significant $\\mathrm{FE}_{\\mathrm{EtOH}}$ with high current density from $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ on ${\\mathrm{CO}}_{2}{\\mathrm{RR}},$ a series of $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}$ NCs with different amounts of modified Ag were assessed for $\\mathrm{CO}_{2}\\mathrm{RR}$ performance (Supplementary Figs. 19 and 20). Characterizations underscore that all pristine $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}$ NCs with different compositions exhibit similar structures, whereas the density of deposited NPs and oxidation state on the surface of $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs increased with the degree of modification (Supplementary Fig. 21). From the comparison of the potential for $\\bar{\\mathrm{CO}}_{2}\\mathrm{RR}$ of different catalysts at a high current density of $800\\mathrm{mAcm}^{-2}$ (Fig. 4a), it can be seen that the demand potential decreases with increased Ag. This finding confirms the positive impact of $\\mathrm{Ag}$ modification on $\\mathrm{CO}_{2}\\mathrm{RR}.$ The degree of introduced Ag-dependent FEs of products from these catalysts was assessed under the same current density. As is shown in Fig. 4b, c, increasing $\\mathrm{Ag}$ in $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ Ag leads to a volcano-shape for $\\mathrm{FE}_{\\mathrm{EtOH}}$ that corresponds with a reverse-volcano on $\\mathrm{FE_{CO}},$ and contrasts with the monotonously decreased FE for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ . This correlation between the amount of modified Ag and FEs for CO and EtOH was observed also with other applied currents (Supplementary Fig. 22). Common to Cubased catalysts, the coverage of CO on Cu surface is conducive to C–C coupling to impact EtOH and $\\mathrm{C}_{2}\\mathrm{H}_{4}$ generation concurrently24. However, here for the $\\mathsf{d C u}_{2}\\mathrm{O}/\\mathrm{Ag},$ only the FE for EtOH exhibits the dependent correlation with CO. These results indicate that the boosted EtOH is not only dependent on variable CO coverage on $\\mathsf{d C u}_{2}\\mathrm{O}/\\mathrm{Ag},$ but also related to other unknown factors. \n\nThe stability of $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ was evaluated via long-term chronopotentiometry testing. It was found that there is no apparent decay of activity with $^{6\\mathrm{h}}$ continuous operation, in which the selectivity of EtOH decreased ${\\sim}6\\%$ following $\\mathrm{CO}_{2}\\mathrm{RR}$ (Supplementary Fig. 23). TEM image and XRD pattern of spent $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ showed that morphology and structure are maintained following the stability test (Supplementary Fig. 24). Given the superior EtOH production on $\\mathrm{dCu_{2}O/A g_{2.3\\%}},$ it was consequently assessed in a commercially relevant membrane electrode assembly (MEA) (Supplementary Fig. 25). It was found that there is a good, linear relationship between applied current and voltage in the MEA (Fig. 4e). The FEs for all products tested in flow cell electrolyzer were well-reproduced in MEA (Supplementary Fig. 26 and Fig. 4d), identifying that high current and high EtOH selectivity can be maintained under commercially relevant conditions (Fig. 4e). Importantly, the durability of $\\mathrm{CO}_{2}\\mathrm{RR}$ in the catholyte–free MEA significantly outperformed the flow cell electrolyzer, which exhibited a decrease of $\\mathrm{\\bar{F}E_{E t O H}}\\left(\\sim3\\%\\right)$ in $12\\mathrm{{h}}$ operation under a full–cell voltage of $-4.72\\mathrm{V}$ with a total current density $800\\mathrm{mA}\\mathrm{cm}^{-2}$ , evidencing the good stability of $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ for $\\mathrm{CO}_{2}\\mathrm{RR}$ (Fig. 4f). \n\nMechanistic studies. The CO reduction reaction (CORR) on $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}$ was assessed to identify whether boosted C–C coupling and EtOH generation followed a classic CO–tandem mechanism (Supplementary Fig. 27). To permit a direct comparison, the CORR behavior of ${\\mathrm{d}}\\mathrm{Cu}_{2}\\mathrm{O}$ and $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ were evaluated and the catalysts were activated by a similar process with $\\mathrm{CO}_{2}\\mathrm{RR}$ . It was expected that if the CO–tandem mechanism dominated, the CORR performance for the catalysts would be similar28. However, as is shown in Supplementary Fig. 28, the $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ exhibits significant suppression of $\\mathrm{H}_{2}$ and promoted $C{\\mathrm{-}}C$ coupling for $\\mathrm{C}_{2+}$ products under CORR. This is in significant contrast to $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ and ${\\tt d C u}_{2}\\mathrm{O}$ results. The partial current density of $\\mathrm{C}_{2+}$ products for $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ reaches $\\mathsf{\\bar{696.0\\ m A}c m}^{-2}$ at $-1.56\\mathrm{~V_{RHE}}$ for $\\mathrm{CORR},$ and is significantly greater than those for $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ $(\\sim154.0\\mathrm{mA}\\mathrm{cm}^{-2})\\$ ) and $\\bar{\\mathsf{d}}\\mathsf{C u}_{2}\\mathsf{O}$ $(\\sim188.0\\mathrm{mA}\\mathrm{cm}^{-2}.$ ). Similarly, the ratio $\\mathrm{FE_{EtOH}/F E_{C2H4}}$ for $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ is also greater than that for $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ and $\\mathsf{d C u}_{2}\\mathrm{O}$ under CORR. Significantly, these findings from $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ contrast with those for reported $\\operatorname{Cu-Ag}$ catalyst with CO–tandem mechanism. This is interpreted that Ag modification results in intrinsic property changes in Cu active sites to: (1) suppress HER, (2) improve C–C coupling activity, and; (3) boost EtOH selectivity. In addition, the modification induced compressive strain, and morphology effects (crystal facets) for boosted EtOH production can be also excluded in our circumstances, because the exposed facets, surface structure and $\\mathrm{{Cu-Cu}}$ bond length of both $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ and $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ catalysts are similar. Therefore, other potential mechanisms on $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ need to be assessed for boosted $\\mathrm{CO}_{2}\\mathrm{RR}$ performance. \n\nReaction pathways for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and EtOH production are similar on Cu surfaces, as they initiate with two adsorbed–CO dimerization followed by several steps of protonation and dehydration to generate a shared intermediate, $^{*}\\mathrm{HCCOH}^{3,14}$ . The selectivity between $\\mathrm{C}_{2}\\mathrm{H}_{4}$ and EtOH, is significantly dependent on the relative stabilities of the next-intermediates for EtOH and $\\mathrm{C}_{2}\\mathrm{H}_{4}$ pathways branched from $^{*}_{\\mathrm{HCCOH}}$ on Cu sites3,14,40. Cu with a relatively low coordinated surface and optimal oxide state is favorable for EtOH generation over $\\mathrm{C}_{2}\\mathrm{H}_{4}$ because the reaction intermediates for EtOH are more saturated compared with those for $\\mathrm{C}_{2}\\mathrm{H}_{4}{}^{41}$ , and the existing oxidation is feasible to binding of key oxygen-bound intermediates for EtOH generation33,42. Combined with this and previous experiment results, it is hypothesized that Ag-induced the moderate coordinated surface and optimal oxidation of $\\mathtt{C u}$ in $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ are responsible for boosted EtOH selectivity. Therefore, the $\\mathrm{CO}_{2}\\mathrm{RR}$ intermediates chemisorbed on ${\\tt d C u}_{2}\\mathrm{O}$ , $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%},$ and $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Au}_{2.3\\%}$ at different potentials were assessed via in situ attenuated total reflectance infrared absorption spectroscopy (ATR–IRAS) to determine the mechanism for boosted EtOH. \n\nAs is shown in Fig. 5a, b and Supplementary Fig. 29, with the cathode potential at $-0.3\\mathrm{V}_{\\mathrm{RHE}}$ , the ATR–IRAS spectra for these catalysts exhibit several new peaks. These are assigned to corresponding intermediates based on independently reported studies (Supplementary Table 4). In particular, there appear two peaks at 2044 and $\\mathrm{i}923\\mathrm{cm}^{-1}$ for $\\mathrm{dCu_{2}O/A g_{2.3\\%}},$ which are associated with the atop–adsorbed $^*\\mathrm{CO}$ $^{*}(\\mathrm{CO_{atop}})$ and bridge–adsorbed $^*\\mathrm{CO}$ $(^{*}\\mathrm{CO_{bridge}})$ on Cu surface, respectively43–45. In comparison, $\\mathrm{dCu}_{2}\\mathrm{O}$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ mainly show the $^{*}\\mathrm{CO}_{\\mathrm{atop}}$ peak with little evidence of $^{*}\\mathrm{CO}_{\\mathrm{bridge}}$ binding in the same potential region. The different $^*\\mathrm{CO}$ binding configurations on these catalysts can also be observed from CO temperatureprogrammed desorption (CO–TPD) (Supplementary Fig. 30b). Mathematical integration and statistical analyses confirm the ratio $^{*}\\mathrm{CO}_{\\mathrm{bridge}}/^{*}\\mathrm{CO}_{\\mathrm{atop}}$ for $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ is significantly greater than that for ${\\tt d C u}_{2}{\\tt O}$ or $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ over the potential range (Supplementary Fig. 31 and Fig. 5c). These findings evidence that compared with $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ , the moderate coordination numbers and optimal oxidation for Cu surface in $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ result in tailored $^*\\mathrm{CO}$ configuration. Given the different electron back-donating and proton-combining ability of adsorbed $^*\\mathrm{CO}$ on atop and bridge Cu sites, the energy barrier for following $^*\\mathrm{CO}$ protonation is altered. Previous studies demonstrate that $^{*}\\mathrm{C}\\bar{\\mathrm{O}}_{\\mathrm{bridge}}$ protonation is more energetically favorable than that of $^{*}\\mathrm{C}\\breve{\\mathrm{O}}_{\\mathrm{atop}}$ on Cu surface46. Therefore, the $\\scriptstyle\\mathbf{C-C}$ coupling on $\\mathrm{{dCu_{2}O/\\bar{A g}_{2.3\\%}}}$ could be triggered under asymmetry between $^*\\mathrm{CO}$ and $^{*}\\mathrm{CHO}$ (or $^*{\\mathrm{COH}},$ following the $^{*}\\mathrm{CO}_{\\mathrm{bridge}}$ protonation step. Notably, adsorbed $^*\\mathrm{CHO}$ intermediate was observed on $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ from ATR-FTIR spectra, and increased with the applied potential (Fig. 5b), strongly evidencing this process. This asymmetric $\\scriptstyle{\\mathrm{C-C}}$ coupling has a lower energy barrier than that for $^*\\mathrm{CO}$ dimerization as evidenced by the reported theory studies19, which contributes to increased $\\mathrm{C}_{2+}$ production. \n\n![](images/ad30d407b3ea2de3d45bd00b11a5922601135eb84ddc41912e7d3b56fc9bfa5f.jpg) \nFig. 4 $C O_{2}R R$ performance for $d C u_{2}O/A g$ with modified Ag. Comparison of a applied potentials, b FEs for $C_{1}$ and ${\\sf H}_{2}$ product, c FEs for $C_{2}H_{4}$ and EtOH and total $\\mathsf C_{2+}$ product on ${\\mathsf{d C u}}_{2}{\\mathsf{O}}/{\\mathsf{A g}}$ with modified $\\mathsf{A g}$ at current density $800\\mathsf{m A c m}^{-2}$ . d Total current density and e FEs for $\\mathsf C_{2+}$ product for $C O_{2}R R$ on $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ at selected cell voltage under MEA measurement. f Stability test for $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ at the current density $800\\mathsf{m A c m}^{-2}$ in MEA. Error bars correspond to the standard deviation of three independent measurements. \n\nAdditional peaks from ATR–IRAS spectra at $\\mathord{\\sim}1567$ and ${\\sim}1182\\ c m^{-1}$ and ${\\sim}1336$ and ${\\sim}1117\\thinspace\\mathrm{cm^{-1}}$ were analyzed. These peaks, indexed to the absorbed $^{*}{\\mathrm{OCCOH}}$ and $^{*}\\mathrm{OC}_{2}\\dot{\\mathrm{H}}_{5}$ on these catalysts, exhibit a ratio value for $^{*}\\mathrm{OC}_{2}\\mathrm{H}_{5}/^{*}\\mathrm{OCCOH}$ on $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Ag}_{2.3\\%}$ that is significantly greater compared with that for ${\\tt d C u}_{2}\\mathrm{O}$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ . This finding evidences that the key $^{*}\\mathrm{OC}_{2}\\mathrm{H}_{5}$ intermediates for EtOH production are more stable on $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ (Fig. 5d)42,43. This is attributed to the asymmetric $\\scriptstyle{\\mathrm{C-C}}$ coupling induced unbalanced coordination environment, which disrupts the coordination sites for $\\mathrm{C}_{2}\\mathrm{H}_{4}$ intermediates, and thereby, stabilizes the EtOH intermediates. This is in agreement with report that diversity of $^*\\mathrm{CO}$ binding site enhances $\\mathrm{C}_{2+}$ liquid product formation27. Therefore we hypothesize that triggered asymmetric $\\scriptstyle{\\mathrm{C-C}}$ coupling on $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ boosts $\\mathrm{C}_{2+}$ production and favors EtOH pathway via stabilizing pivotal intermediates. \n\n![](images/0a3f431a3b1820b050ff465a8d05aed94ab28a381f2c4c1775cc45a1d3150d50.jpg) \nFig. 5 In situ ATR–IRAS measurement and mechanism for $\\mathsf{d}\\mathsf{C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ . In situ ATR–IRAS obtained during chronopotentiometry in a potential window 0.2 to $-1.2V_{\\sf R H E}$ for a ${\\mathsf{d C u}}_{2}{\\mathsf{O}},$ and b $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ under ${\\mathsf{C O}}_{2}{\\mathsf{R R}}.$ (A reference spectrum obtained at $0.3V_{\\mathsf{R H E}}$ in $1M\\mathsf{K O H}$ is subtracted). Potential dependence of ratio of c $\\mathrm{\\dot{^{\\circ}C O_{b r i d g e}}/^{\\star}C O_{a t o p}}$ and $\\mathsf{\\Omega}_{\\mathsf{I}}^{\\star}{\\mathsf{O}}\\mathsf{C}_{2}\\mathsf{H}_{5}/^{\\star}{\\mathsf{O}}\\mathsf{C}\\mathsf{C}{\\mathsf{O}}\\mathsf{H}$ obtained for ${\\mathsf{d C u}}_{2}{\\mathsf{O}}$ , $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ and $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A u}_{2.3\\%}$ . e Schematic for boosted EtOH generation over $\\mathsf{d C u}_{2}\\mathsf{O}/\\mathsf{A g}_{2.3\\%}$ . Yellow-color, gray, white, orange, red, and azure spheres in the model represent H, C, O, ${\\mathsf{C u}}^{1+}$ , ${\\mathsf{C u}}^{0}.$ , and $\\mathsf{A g}$ atoms, respectively. \n\nIn addition, the peak for the absorbed bicarbonate at $1547\\mathrm{cm}^{-1}$ on $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ is missing compared with $\\mathrm{dCu}_{2}\\mathrm{O}$ and $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{O}/$ $\\mathrm{Au}_{2.3\\%}$ , confirming that the value of the local $\\mathrm{pH}$ on the electrode of $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ is greater than that for ${\\tt d}\\tt C{u}_{2}\\bar{\\mathrm{O}}$ and $\\mathrm{dCu_{2}O/A u_{2.3\\%}}$ during $\\mathrm{CO}_{2}\\mathrm{\\bar{R}R^{47}}$ . The high $\\mathrm{\\pH}$ at the surface of electrode is thought to favor C–C coupling by lowering the energy barrier of $\\mathrm{CO}_{2}$ activation and suppressing $\\mathrm{H}_{2}$ evolution, and contributes to the boosted activity for ${\\mathrm{CO}}_{2}{\\mathrm{RR}}.$ Moreover, the CO–TPD and $\\mathrm{CO}_{2}$ –TPD for $\\mathrm{dCu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ also exhibit a higher temperature for $\\mathrm{CO}_{2}$ and CO desorption than those for $\\mathrm{d}\\mathrm{Cu}_{2}\\mathrm{\\bar{O}}$ and $\\mathrm{{dCu}}_{2}\\mathrm{{O}}/\\mathrm{{Au}}_{2.3}.$ indicating $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ has stronger bonding strength of $\\mathrm{CO}_{2}$ and $\\mathrm{CO}$ for efficient $\\mathrm{CO}_{2}\\mathrm{RR}$ at large current (Supplementary Fig. 30). \n\nAccordingly, based on the ATR–IRAS spectra analysis, the mechanism for boosted EtOH on $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ can be soundly proposed (Fig. 5e). At first, the coordinated pure-Cu surface is replaced with neighboring $\\mathrm{Ag}$ atoms with modification by $\\mathrm{Ag}$ in $\\mathrm{Cu}_{2}\\mathrm{O}$ and reduces these to $\\mathrm{CuAg}$ alloy under $\\mathrm{CO}_{2}\\mathrm{RR}.$ Then, the Ag-induced moderate coordination numbers and optimal oxidation of Cu surface regulate binding strength of $^*\\mathrm{CO}$ , to configure mixed $^{*}\\mathrm{CO}_{\\mathrm{bridge}}$ and $^{*}\\mathrm{CO}_{\\mathrm{atop}}$ adsorption that triggers asymmetric C–C coupling after $^{*}\\mathrm{CO}_{\\mathrm{bridge}}$ protonation. Because of the relatively low oxygen affinity and unsaturated nature of the $\\mathrm{C}_{2}\\mathrm{H}_{4}$ intermediates compared with EtOH, the asymmetric $\\scriptstyle{\\mathrm{C-C}}$ coupling provides an unbalanced coordination environment that is beneficial for EtOH intermediate formation and stabilization in lower energy than that for $\\mathrm{C_{2}H_{4}},$ and thereby promotes the pathway for EtOH. \n\n# Discussion \n\nIn summary, an assessment of a newly synthesized, silvermodified copper-oxide catalyst has confirmed that the $\\mathrm{CO}_{2}\\mathrm{RR}$ to EtOH pathway is accelerated via triggering the asymmetric $C{\\mathrm{-}}C$ coupling. An optimized $\\mathrm{dCu_{2}O/A g_{2.3\\%}}$ exhibits a FE of $40.8\\%$ and $\\mathrm{EE}_{\\mathrm{HF}}$ of $22.3\\%$ for EtOH production in flow cell, together with boosted EtOH partial current density of $326.4\\mathrm{mAcm}^{=}2$ at $-0.89$ $\\mathrm{V}_{\\mathrm{RHE}}$ (with an $85\\ \\%$ iR correction). In situ ATR–IRAS spectroscopy confirmed that boosted EtOH selectivity results from moderate coordinated surface and optimal oxidation state of the \n\nCu sites that gives mixed ${}^{*}\\mathrm{CO}_{\\mathrm{bridge}}$ and $^*\\mathrm{CO}_{\\mathrm{atop}}$ configurations for asymmetric $C{\\mathrm{-}}C$ coupling to stabilize the EtOH intermediates. This demonstrated understanding of the mechanism for electroreduction of $\\mathrm{CO}_{2}$ –to– EtOH contrasts with reported, classic CO–tandem catalysis. It can be practically used to significantly boost EtOH production. \n\n# Methods \n\nPreparation of $\\cos_{\\mathbf{\\theta}_{2}\\mathbf{0}}$ , $\\mathsf{c u}_{2}\\mathsf{o}/\\mathsf{A g},$ and $\\mathbb{C}\\mathrm{u}_{2}\\mathbb{O}/\\mathbb{A}\\mathrm{u}$ NCs. In a typical preparation for $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ NCs, $0.5\\mathrm{mL}$ NaOH solution (1 M) and $0.5\\mathrm{mL}$ $\\mathrm{Cu}(\\mathrm{NO}_{3})_{2}$ solution (0.1 M) were added to a $30~\\mathrm{mL}$ vial with $9\\mathrm{mL}$ water under vigorous stirring for $5\\mathrm{{min}}$ at RT to give a blue-color $\\mathrm{Cu(OH)}_{2}$ suspension. $27\\mathrm{mg}$ AA was added to the vial under vigorous stirring. The suspension changed from blue color to yellow, confirming the formation of $\\mathrm{Cu}_{2}\\mathrm{O}$ NCs. Following stirring for $30\\mathrm{min}$ , $0.1\\mathrm{mL}$ $\\mathrm{AgNO}_{3}$ solution $(0.01\\mathrm{M})$ was added to the vial, and stirring continued for $30\\mathrm{min}$ . $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ NCs were obtained and resulting products were collected by centrifugation and washed with EtOH. Preparation of $\\mathrm{Cu}_{2}\\mathrm{O}$ and $\\mathrm{{Cu}}_{2}\\mathrm{{O}}/\\mathrm{{Au}}$ NCs was similarly conducted, but without the addition of $\\mathrm{AgNO}_{3}$ and with the replacement of $\\mathrm{AgNO}_{3}$ with $\\mathrm{HAuCl}_{4}{\\bullet}4\\mathrm{H}_{2}\\mathrm{O}$ $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}$ and $\\mathrm{{Cu}}_{2}\\mathrm{{O}}/\\mathrm{{Au}}$ NCs with different compositions were prepared by adding selected volumes of $\\mathrm{AgNO}_{3}$ and $\\mathrm{HAuCl}_{4}{\\bullet}4\\mathrm{H}_{2}\\mathrm{O}$ solution (Supplementary Table 5). \n\nCharacterizations. TEM and HAADF–STEM were conducted on a FEI Tecnai F20 transmission electron microscope with an acceleration voltage $200\\mathrm{kV}$ . Samples were prepared by dropping EtOH dispersions of the samples onto carbon-coated, Cu TEM grids using a pipette, and dried under ambient RT conditions. SEM images were taken with a HITACHI S–3700 cold–field emission scanning electron microscope operated at $15\\mathrm{kV}$ . XRD patterns were collected on X’Pert–Pro MPD diffractometer (Netherlands PANalytical) with a Cu Kα X-ray source $\\left(\\lambda=1.540598\\mathrm{\\AA}\\right.$ ). XPS was determined with an SSI S–Probe XPS Spectrometer. The carbon peak at $284.6\\mathrm{eV}$ was used as a reference to correct for charging effects. XAS data were collected at the TPS–44 A beamline of the National Synchrotron Radiation Research Center (NSRRC, Hsinchu, Taiwan) using a Si (111) quickscanning monochromator, and processed according to standard procedures using the Demeter program package (Version 0.9.24). \n\n$C O_{2}R R$ test in flow cell. Electroreduction of $\\mathrm{CO}_{2}$ was tested in a microfluidics flow cell that consisted of two electrolyte chambers $20\\times5\\times3$ , mm) and one gas chamber $(20\\times5\\times5,\\mathrm{mm})^{48}$ . An anion exchange membrane (Fumasep FAB–PK–130) was placed between two electrolyte chambers for products separation and ionic conduction. Catalyst-deposited GDE, micro $\\mathrm{\\Ag/AgCl}$ electrode ${\\bf\\dot{4.0M}}$ KCl), and Nifoam $\\mathrm{\\Delta}0.5\\mathrm{mm}$ thickness), respectively, served as working electrode, reference electrode, and anode. To fabricate the working electrode, a certain amount of catalysts $(3\\mathrm{mg})$ were dispersed in $1\\mathrm{mL}$ EtOH with $20\\upmu\\mathrm{L}$ 5 wt% Nafion solution and then sprayed onto a gas diffusion layer (CeTech, NIS1007) via airbrush. The loading amount of catalysts on GDE was controlled to $\\sim0.44\\mathrm{mg}\\mathrm{cm}^{-2}$ . The working electrode was placed between gas and catholyte chambers to ensure gaseous $\\mathrm{CO}_{2}$ diffusion and reaction at the catholyte/catalysts interface. The reference electrodes were inserted in catholyte chamber and maintained at a specified distance with the working electrode. An electrochemical workstation (CHI660, Chenhua, Shanghai) with a current amplifier was used to perform the $\\mathrm{CO}_{2}\\mathrm{RR}$ test. 1 M KOH ( $20\\mathrm{mL})$ was circulated through the electrolyte chambers under constant flow $(15\\mathrm{mL}\\mathrm{min}^{-1},$ ) via peristaltic pump. $\\mathrm{CO}_{2}$ was supplied into gas chambers by a mass-flow controller at a constant flow rate of $30\\mathrm{mL}\\mathrm{min}^{-1}$ . Reactions were tested via chronopotentiometry at differing currents for $^{\\textrm{1h}}$ without $i R$ correction. Gas and liquid products were analyzed, respectively, via GC (Agilent 8890) and $^1\\mathrm{H}$ NMR (Agilent ${600}\\mathrm{MHz}$ DirectDrive2 spectrometers). \n\nPotentials were referenced to RHE and iR correction performed based on the following, namely: \n\n$$\n\\mathrm{E}_{\\mathrm{RHE}}=\\mathrm{E}_{\\mathrm{vs}\\ A\\mathrm{g}/\\mathrm{AgCl}}+0.059\\times\\mathrm{pH}+0.210+0.85\\times i R\n$$ \n\nwhere $i$ is the current at each applied potential and $R$ the equivalent series resistance measured via electrochemical impedance spectroscopy in the frequency. FE for the formation of $\\mathrm{CO}_{2}\\mathrm{RR}$ product was computed from: \n\n$$\n\\mathrm{FE}=\\mathrm{eF}\\times\\mathrm{n}/\\mathrm{Q}=\\mathrm{eF}\\times\\mathrm{n}/(\\mathrm{I}\\times\\mathrm{t})\n$$ \n\nin which $\\mathbf{\\Delta}_{\\mathbf{e}}$ is the number of transferred electrons for each product, F the Faraday constant, $\\mathrm{\\DeltaQ}$ charge, I applied current, t reaction time, and $\\mathbf{n}$ total product (in mole). \n\n$\\mathrm{EE}_{\\mathrm{HC}}$ was computed on the basis of the cathodic $\\mathrm{CO}_{2}\\mathrm{RR}$ coupled with the anodic oxygen evolution reaction $(\\mathrm{O}_{2}+4\\mathrm{H}^{+}+4\\mathrm{e}^{-}\\leftrightarrow2\\mathrm{H}_{2}\\mathrm{O};$ $1.23\\mathrm{V}$ vs RHE) from: \n\n$$\n\\mathrm{EE}_{\\mathrm{HC}}=\\frac{E_{\\mathrm{oe}}^{\\circ}-E_{\\mathrm{red}}^{\\circ}}{E_{\\mathrm{oe}}-E_{\\mathrm{red}}}\\times\\mathrm{FE}_{\\mathrm{EtOH}}\n$$ \n\nwhere $E_{\\mathrm{oe}}^{\\mathrm{~\\tiny~o~}}$ and $E_{\\mathrm{red}}{}^{\\mathrm{o}}$ are, respectively, the thermodynamic potential for oxygen evolution and $\\mathrm{CO}_{2}\\mathrm{RR}$ to EtOH $0.08\\mathrm{V}$ vs RHE), $E_{\\mathrm{oe}}$ and $E_{\\mathrm{red}}$ applied potentials at, respectively, anode and cathode. For the computation of the half-cell EE, the anodic reaction was assumed to occur with an overpotential of $0\\mathrm{V}$ , that is, $E_{\\mathrm{oe}}=1.23\\:\\mathrm{V}$ . \n\n$C O_{2}R R$ test in MEA. Electroreduction of $\\mathrm{CO}_{2}$ in MEA consisted of two titanium backplates (TA2 grade) with a $4.0\\mathrm{cm}^{2}$ serpentine flow field, and MEA. Catalystdeposited GDE $(\\sim0.44\\mathrm{mg}\\mathrm{cm}^{-2}$ for $\\mathrm{Cu}_{2}\\mathrm{O}/\\mathrm{Ag}_{2.3\\%}$ NCs) and Ni-foam ( $0.5\\mathrm{mm}$ thickness) were used, respectively, as cathode and anode. The cathode and anode were pressed onto sides of the anion exchange membrane (Sustainion 37–50, Dioxide Materials). The gap between the electrodes was minimized to reduce ohmic loss. Gaseous $\\mathrm{CO}_{2}$ $\\bar{30}\\mathrm{mL}\\mathrm{min}^{-1}$ ) was passed behind the GDL to contact the catalyst, and $0.1\\mathrm{M}$ solution was used as the anolyte which was circulated via pump at $20\\mathrm{mL}\\mathrm{min}^{-1}$ . $\\mathrm{CO}_{2}\\mathrm{RR}$ performance for MEA was evaluated by applying different currents with a current amplifier in the two-electrode system at the CHI660 (Chenhua, Shanghai) electrochemical workstation. Cathodic gas products were vented through a simplified cold–trap to collect permeable liquid prior to gas chromatograph testing. FE values for the liquid products were computed based on the total mass of product collected on anode and cathode. \n\nECSA measurement. ECSA was measured by double-layer capacitance (DLC) and Pb underpotential deposition (Pb UPD) methods. All experiments are conducted in the flow cell and the used catalysts are obtained following activation under $\\mathrm{CO}_{2}\\mathrm{RR}.$ For DLC method, Cyclic Voltammetry (CV) scans were conducted at the potential range from 0.15 to $0.20{\\mathrm{V}}$ vs RHE with increasing scan rates of 10, 20, 40, 60, 80, and $100\\mathrm{mVs^{-1}}$ . The capacitance currents at $0.17\\mathrm{V}$ vs RHE were plotted against the scan rates, and the double-layer capacitance $(\\mathrm{C_{dl}},\\mathrm{mF}\\ \\mathrm{cm}^{-2}$ ) was derived from the slope according to the following: \n\n$$\n\\mathrm{\\DeltaC_{dl}=I/v}\n$$ \n\nwhere I is the capacitance current (half of the difference between the anodic current density and cathodic current density, $(\\mathrm{J_{a}}\\mathrm{-}\\mathrm{J_{c}})/2^{\\cdot},$ , and $\\mathbf{v}$ is the scan rate. \n\nFor $\\mathrm{\\Pb}$ UPD method, the CV scans were conducted in Ar-saturated $0.01\\mathrm{M}$ $\\mathrm{{HClO}_{4}}$ and $\\boldsymbol{1}\\mathrm{mM}\\ \\mathrm{PbCl_{2}}$ at the potential range from 0.15 to $0.20\\mathrm{V}$ vs RHE with scan rates of $10\\mathrm{mVs^{-1}}$ . The ECSA of catalysts was determined according to the following: \n\n$$\n\\mathrm{ECSA_{Pb\\UPD}}=\\mathrm{A_{Pb\\UPD}}/(320\\upmu\\mathrm{Ccm}^{-2}\\mathrm{v})\n$$ \n\nwhere $\\mathrm{A_{Pb\\UPD}}$ is the peak area of monolayer $\\mathrm{\\Pb}$ stripping, v the scan rate and the constant $320\\upmu\\mathrm{C}\\mathrm{cm}^{-2}$ is the charge density factor for the UPD of $\\mathrm{{Pb}}$ on copper33. \n\nIn situ ATR–IRAS measurement. In situ ATR–IRAS was performed on a Nicolet iS20 spectrometer equipped with an HgCdTe (MCT) detector and a VeeMax III (PIKE Technologies) accessory. The measurement was conducted in a homemade electrochemical single-cell furnished with Pt–wire and $\\mathrm{\\Ag/AgCl}$ as counter and reference electrodes. A fixed-angle Ge prism $(60^{\\circ})$ coated with catalysts embed into the bottom of the cell served as the working electrode. Before testing, the detector was cooled with liquid nitrogen for at least $30\\mathrm{min}$ to maintain a stable signal. Chronoamperometry was used for $\\mathrm{CO}_{2}\\mathrm{RR}$ test and was accompanied by the spectrum collection (32 scans, $4\\mathrm{cm}^{-1}$ resolution). All spectra were subtracted with the background. \n\n# Data availability \n\nData that support findings from this study are available from the corresponding author on reasonable request. \n\nReceived: 20 December 2021; Accepted: 16 June 2022; Published online: 29 June 2022 \n\n# References \n\n1. Arakawa, H. et al. Catalysis research of relevance to carbon management: progress, challenges, and opportunities. Chem. Rev. 101, 953–996 (2001). \n2. Jouny, M., Luc, W. & Jiao, F. General techno–economic analysis of $\\mathrm{CO}_{2}$ electrolysis systems. Ind. Eng. Chem. Res. 57, 2165–2177 (2018). \n3. Birdja, Y. Y. et al. Advances and challenges in understanding the electrocatalytic conversion of carbon dioxide to fuels. Nat. Energy 4, 732–745 (2019). \n4. Qiao, J., Liu, Y., Hong, F. & Zhang, J. A review of catalysts for the electroreduction of carbon dioxide to produce low–carbon fuels. Chem. Soc. Rev. 43, 631–675 (2014). \n5. Ross, M. B. et al. Designing materials for electrochemical carbon dioxide recycling. Nat. Catal. 2, 648–658 (2019). and electrolyte design for $\\mathrm{CO}_{2}$ electroreduction towards multicarbon products. Nat. Catal. 2, 198–210 (2019). \n7. Kuhl, K. P. et al. Electrocatalytic conversion of carbon dioxide to methane and methanol on transition metal surfaces. J. Am. Chem. Soc. 136, 14107–14113 (2014). \n8. Verma, S. et al. Insights into the low overpotential electroreduction of $\\mathrm{CO}_{2}$ to CO on a supported gold catalyst in an alkaline flow electrolyzer. ACS Energy Lett. 3, 193–198 (2018). \n9. Nitopi, S. et al. Progress and perspectives of electrochemical $\\mathrm{CO}_{2}$ reduction on copper in aqueous electrolyte. Chem. Rev. 119, 7610–7672 (2019). \n10. Kuhl, K. P., Cave, E. R., Abram, D. N. & Jaramillo, T. F. New insights into the electrochemical reduction of carbon dioxide on metallic copper surfaces. Energy Environ. Sci. 5, 7050–7059 (2012). \n11. Dinh, C.–T. et al. $\\mathrm{CO}_{2}$ electroreduction to ethylene via hydroxide–mediated copper catalysis at an abrupt interface. Science 360, 783–787 (2018). \n12. Nguyen, T. N. et al. Electrochemical $\\mathrm{CO}_{2}$ reduction to ethanol: from mechanistic understanding to catalyst design. J. Mater. Chem. A 9, 12474–12494 (2021). \n13. Bushuyev, O. S. et al. What should we make with $\\mathrm{CO}_{2}$ and How can we make it? Joule 2, 825–832 (2018). \n14. Zheng, Y. et al. Understanding the roadmap for electrochemical reduction of $\\mathrm{CO}_{2}$ to multi–carbon oxygenates and hydrocarbons on copper–based catalysts. J. Am. Chem. Soc. 141, 7646–7659 (2019). \n15. Vasileff, A., Xu, C., Jiao, Y., Zheng, Y. & Qiao, S. –Z. Surface and interface engineering in copper–based bimetallic materials for selective $\\mathrm{CO}_{2}$ electroreduction. Chem 4, 1809–1831 (2018). \n16. Wang, P. et al. Phase and structure engineering of copper tin heterostructures for efficient electrochemical carbon dioxide reduction. Nat. Commun. 9, 4933 (2018). \n17. Huang, J., Mensi, M., Oveisi, E., Mantella, V. & Buonsanti, R. Structural sensitivities in bimetallic catalysts for electrochemical $\\mathrm{CO}_{2}$ reduction revealed by Ag–Cu nanodimers. J. Am. Chem. Soc. 141, 2490–2499 (2019). \n18. Zhuang, T.–T. et al. Steering post–C–C coupling selectivity enables high efficiency electroreduction of carbon dioxide to multi–carbon alcohols. Nat. Catal. 1, 421–428 (2018). \n19. Ma, W. et al. Electrocatalytic reduction of $\\mathrm{CO}_{2}$ to ethylene and ethanol through hydrogen–assisted C–C coupling over fluorine–modified copper. Nat. Catal. 3, 478–487 (2020). \n20. Zhou, Y. et al. Dopant–induced electron localization drives $\\mathrm{CO}_{2}$ reduction to $\\mathrm{C}_{2}$ hydrocarbons. Nat. Chem. 10, 974–980 (2018). \n21. Hoang, T. T. H., Ma, S., Gold, J. I., Kenis, P. J. A. & Gewirth, A. A. Nanoporous copper films by additive–controlled electrodeposition: $\\mathrm{CO}_{2}$ reduction catalysis. ACS Catal. 7, 3313–3321 (2017). \n22. Lee, S., Park, G. & Lee, J. Importance of $\\mathrm{\\Ag-Cu}$ biphasic boundaries for selective electrochemical reduction of $\\mathrm{CO}_{2}$ to ethanol. ACS Catal. 7, 8594–8604 (2017). \n23. She, X. et al. Tandem electrodes for carbon dioxide reduction into $\\mathrm{C}_{2+}$ products at simultaneously high production efficiency and rate. Cell Rep. Phys. Sci. 1, 100051 (2020). \n24. Morales–Guio, C. G. et al. Improved $\\mathrm{CO}_{2}$ reduction activity towards $\\mathrm{C}_{2+}$ alcohols on a tandem gold on copper electrocatalyst. Nat. Catal. 1, 764–771 (2018). \n25. Lv, X. et al. Electron–deficient Cu sites on $\\mathrm{Cu}_{3}\\mathrm{Ag}_{1}$ catalyst promoting $\\mathrm{CO}_{2}$ electroreduction to alcohols. Adv. Energy Mater. 10, 2001987 (2020). \n26. Clark, E. L., Hahn, C., Jaramillo, T. F. & Bell, A. T. Electrochemical $\\mathrm{CO}_{2}$ reduction over compressively strained CuAg surface alloys with enhanced multi–carbon oxygenate selectivity. J. Am. Chem. Soc. 139, 15848–15857 (2017). \n27. Li, Y. C. et al. Binding site diversity promotes $\\mathrm{CO}_{2}$ electroreduction to ethanol. J. Am. Chem. Soc. 141, 8584–8591 (2019). \n28. Chen, C. et al. $\\operatorname{Cu-Ag}$ tandem catalysts for high–rate $\\mathrm{CO}_{2}$ electrolysis toward multicarbons. Joule 4, 1688–1699 (2020). \n29. Li, F. et al. Cooperative $\\mathrm{CO}_{2}$ –to–ethanol conversion via enriched intermediates at molecule–metal catalyst interfaces. Nat. Catal. 3, 75–82 (2020). \n30. Ren, D., Ang, B. S. H. & Yeo, B. S. Tuning the selectivity of carbon dioxide electroreduction toward ethanol on oxide–derived $\\mathrm{Cu_{x}Z n}$ catalysts. ACS Catal. 6, 8239–8247 (2016). \n31. Lv, J.–J. et al. A highly porous copper electrocatalyst for carbon dioxide reduction. Adv. Mater. 30, 1803111 (2018). \n32. Ma, S. et al. One–step electrosynthesis of ethylene and ethanol from $\\mathrm{CO}_{2}$ in an alkaline electrolyzer. J. Power Sources 301, 219–228 (2016). \n33. Wang, X. et al. Efficient electrically powered $\\mathrm{CO}_{2}$ –to–ethanol via suppression of deoxygenation. Nat. Energy 5, 478–486 (2020). \n34. Luo, M. et al. Hydroxide promotes carbon dioxide electroreduction to ethanol on copper via tuning of adsorbed hydrogen. Nat. Commun. 10, 5814 (2019). \n35. Hoang, T. T. H. et al. Nanoporous copper–silver alloys by additive–controlled electrodeposition for the selective electroreduction of $\\mathrm{CO}_{2}$ to ethylene and ethanol. J. Am. Chem. Soc. 140, 5791–5797 (2018). \n36. Su, X. et al. Hierarchically porous $\\mathrm{{Cu/Zn}}$ bimetallic catalysts for highly selective $\\mathrm{CO}_{2}$ electroreduction to liquid $\\mathrm{C}_{2}$ products. Appl. Catal. B 269, 118800 (2020). \n37. Kim, C. et al. $\\mathrm{Cu}/\\mathrm{Cu}_{2}\\mathrm{O}$ interconnected porous aerogel catalyst for highly productive electrosynthesis of ethanol from $\\mathrm{CO}_{2}$ . Adv. Funct. Mater. 31, 2102142 (2021). \n38. Kim, J. Y. et al. Synergistic effect of $\\mathrm{Cu}_{2}\\mathrm{O}$ mesh pattern on high‐facet Cu surface for selective $\\mathrm{CO}_{2}$ electroreduction to ethanol. Adv. Mater. 34, 2106028 (2021). \n39. Jung, H. et al. Electrochemical fragmentation of $\\mathrm{Cu}_{2}\\mathrm{O}$ nanoparticles enhancing selective C–C coupling from $\\mathrm{CO}_{2}$ reduction reaction. J. Am. Chem. Soc. 141, 4624–4633 (2019). \n40. Lum, Y., Cheng, T., Goddard, W. A. & Ager, J. W. Electrochemical CO reduction builds solvent water into oxygenate products. J. Am. Chem. Soc. 140, 9337–9340 (2018). \n41. Wang, L. et al. Electrochemical carbon monoxide reduction on polycrystalline copper: effects of potential, pressure, and $\\mathrm{\\tt{pH}}$ on selectivity toward multicarbon and oxygenated products. ACS Catal. 8, 7445–7454 (2018). \n42. Zhang, W. et al. Atypical oxygen–bearing copper boosts ethylene selectivity toward electrocatalytic $\\mathrm{CO}_{2}$ reduction. J. Am. Chem. Soc. 142, 11417–11427 (2020). \n43. Zhu, S., Li, T., Cai, W.–B. & Shao, M. $\\mathrm{CO}_{2}$ Electrochemical reduction as probed through infrared spectroscopy. ACS Energy Lett. 4, 682–689 (2019). \n44. Katayama, Y. et al. An in situ surface–enhanced infrared absorption spectroscopy study of electrochemical $\\mathrm{CO}_{2}$ reduction: selectivity dependence on surface C–bound and O/bound reaction intermediates. J. Phys. Chem. C 123, 5951–5963 (2019). \n45. Chou, T.–C. et al. Controlling the oxidation state of the Cu electrode and reaction intermediates for electrochemical $\\mathrm{CO}_{2}$ reduction to ethylene. J. Am. Chem. Soc. 142, 2857–2867 (2020). \n46. Shen, H. et al. Asymmetrical C–C coupling for electroreduction of CO on bimetallic Cu–Pd catalysts. ACS Catal. 12, 5275–5283 (2022). \n47. Chen, X. et al. Electrochemical $\\mathrm{CO}_{2}$ –to–ethylene conversion on polyamine–incorporated Cu electrodes. Nat. Catal. 4, 20–27 (2021). \n48. Wang, P. et al. Synergized $\\mathrm{Cu/Pb}$ core/shell electrocatalyst for high-efficiency $\\mathrm{CO}_{2}$ reduction to $\\mathrm{C}_{2+}$ liquids. ACS Nano 15, 1039–1047 (2021). \n\n# Acknowledgements \n\nThis work was financially supported by the Australian Research Council (ARC) through Discovery Project [FL170100154, DP220102596 (S.Z.Q.)], the National Key R&D Program of China [2020YFB1505802 (X.H.)], Ministry of Science and Technology [2017YFA0208200, 2016YFA0204100 (X.H.)], National Natural Science Foundation of China [21903058, 22173066, 22103054 (T.C.) and 22025108, 2212100020 (X.H)], Natural Science Foundation of Jiangsu Higher Education Institutions [BK20190810 (T.C.)] and Start-up support from Xiamen University (X.H.). T.C. gratefully acknowledges support from the Collaborative Innovation Center of Suzhou Nano Science & Technology, the 111 Project, Joint International Research Laboratory of Carbon-Based Functional Materials and Devices. \n\n# Author contributions \n\nS.Z.Q. and X.H. conceived and supervised the research. X.H. and P.W. designed and conducted the experiments. P.W., H.Y., X.H., and S.Z.Q. performed data analyses. C.T., Y.W., T.C., and Y.Z. participated in experiments and characterizations. P.W., K.D., X.H., and S.Z.Q. wrote and corrected the paper. All authors discussed results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-31427-9. \n\nCorrespondence and requests for materials should be addressed to Xiaoqing Huang or Shi-Zhang Qiao. \n\nPeer review information Nature Communications thanks Hee-Tae Jung and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1093_nsr_nwab188", + "DOI": "10.1093/nsr/nwab188", + "DOI Link": "http://dx.doi.org/10.1093/nsr/nwab188", + "Relative Dir Path": "mds/10.1093_nsr_nwab188", + "Article Title": "Characteristics of the lunar samples returned by the Chang'E-5 mission", + "Authors": "Li, CL; Hu, H; Yang, MF; Pei, ZY; Zhou, Q; Ren, X; Liu, B; Liu, DW; Zeng, XG; Zhang, GL; Zhang, HB; Liu, JJ; Wang, Q; Deng, XJ; Xiao, CJ; Yao, YG; Xue, DS; Zuo, W; Su, Y; Wen, WB; Ouyang, ZY", + "Source Title": "NATIONAL SCIENCE REVIEW", + "Abstract": "The CE-5 sample is consistent with weathered mare basalts in mineralogy and petrochemistry, and is classified as low-Ti/low-Al/low-K type with lower REE (rare earth element) contents than KREEP (potassium, rare earth element, and phosphorus). This new sample characterized by high FeO and low Mg index could represent a new lunar basalt. Forty-five years after the Apollo and Luna missions returned lunar samples, China's Chang'E-5 (CE-5) mission collected new samples from the mid-latitude region in the northeastern Oceanus Procellarum of the Moon. Our study shows that 95% of CE-5 lunar soil sizes are found to be within the range of 1.40-9.35 mu m, while 95% of the soils by mass are within the size range of 4.84-432.27 mu m. The bulk density, true density and specific surface area of CE-5 soils are 1.2387 g/cm(3), 3.1952 g/cm(3) and 0.56 m(2)/g, respectively. Fragments from the CE-5 regolith are classified into igneous clasts (mostly basalt), agglutinate and glass. A few breccias were also found. The minerals and compositions of CE-5 soils are consistent with mare basalts and can be classified as low-Ti/low-Al/low-K type with lower rare-earth-element contents than materials rich in potassium, rare earth element and phosphorus. CE-5 soils have high FeO and low Mg index, which could represent a new class of basalt.", + "Times Cited, WoS Core": 278, + "Times Cited, All Databases": 308, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000753113800002", + "Markdown": "# Characteristics of the lunar samples returned by the Chang’E-5 mission \n\n1Key Laboratory of \nLunar and Deep Space Exploration, National Astronomical \nObservatories, \nChinese Academy of Sciences, Beijing \n100101, China; 2Lunar Exploration and Space Engineering Center, \nBeijing 100190, China; 3Beijing Institute of \nSpacecraft System \nEngineering, Beijing \n100094, China; \n4Department of \nNuclear Physics, \nChina Institute of \nAtomic Energy, Beijing 102413, China; 5State Key Laboratory of \nLithospheric \nEvolution, Institute of Geology and \nGeophysics, Chinese Academy of Sciences, Beijing 100029, China and 6Institute of \nGeochemistry, \nChinese Academy of Sciences, Guiyang \n550081, China \n\n∗Corresponding authors. E-mails: licl@nao.cas.cn; huhaoclep@163.com; yangmf@bice.org.cn \n\nReceived 25 August 2021; Revised 13 October 2021; Accepted 13 October 2021 \n\nChunlai Li $\\textcircled{10}1,*$ , Hao Hu2,∗, Meng-Fei Yang3,∗, Zhao-Yu Pei2, Qin Zhou1, Xin Ren1, Bin Liu1, Dawei Liu1, Xingguo Zeng1, Guangliang Zhang1, Hongbo Zhang1, Jianjun Liu1, Qiong Wang2, Xiangjin Deng3, Caijin Xiao4, Yonggang Yao4, Dingshuai $\\mathsf{X u e}^{5}$ , Wei $Z\\mathsf{U}0^{1}$ , Yan $\\mathsf{S u}^{1}$ , Weibin Wen1 and Ziyuan Ouyang1,6 \n\n# ABSTRACT \n\nForty-five years after the Apollo and Luna missions returned lunar samples, China’s Chang’E-5 (CE-5) mission collected new samples from the mid-latitude region in the northeastern Oceanus Procellarum of the Moon. Our study shows that $95\\%$ of CE-5 lunar soil sizes are found to be within the range of 1.40– $9.35\\mu\\mathrm{m},$ , while $95\\%$ of the soils by mass are within the size range of $4.84\\mathrm{-}432.27\\mu\\mathrm{m}$ The bulk density, true density and specific surface area of CE-5 soils are $1.2387\\mathrm{g}/\\mathrm{cm}^{3}$ , $3.1952{\\mathrm{g}}/{\\mathrm{cm}}^{3}$ and $0.56\\mathrm{m}^{2}/\\mathrm{g},$ respectively. Fragments from the CE-5 regolith are classified into igneous clasts (mostly basalt), agglutinate and glass. A few breccias were also found. The minerals and compositions of CE-5 soils are consistent with mare basalts and can be classified as low-Ti/low-Al/low-K type with lower rare-earth-element contents than materials rich in potassium, rare earth element and phosphorus. CE-5 soils have high FeO and low $\\mathbf{M}\\mathbf{g}$ index, which could represent a new class of basalt. \n\nKeywords: Chang’E-5, lunar soils, physical properties, petrography, mineralogy, chemistry \n\n# INTRODUCTION \n\nThe Moon is the only natural satellite of the Earth and has always been an object of interest for scientists [1]. The first comprehensive lunar photographic atlas was completed by dozens of orbiter probes as early as the 1960s [2]. Based on these early images, the Moon is divided into two basic physiographic regions, namely, smooth maria and cratered highlands, both studded with craters of varying sizes. Studies of the lunar surface’s morphology have indicated that the large craters originated from impact events and that the flat lunar maria might be filled with basalt [3,4]. Using the classical geological principle of superposition, the succession of events on the Moon was unraveled, a relative time scale was constructed and geological maps were prepared [5]. \n\nSamples are the key to promoting our scientific research, from remote observations to laboratory measurements. The returned lunar samples ( $\\sim382~\\mathrm{kg}$ [6,7]) from six Apollo and three Luna missions in the last century have significantly enhanced our understanding of the distribution, age and evolution of mare volcanism [8–12], the lunar mantle’s composition and structure [13,14], the effect of physical properties on lunar exploration [15] and the Moon’s surface processes (e.g. space weathering) [16]. The Apollo lunar samples were ‘the crown jewels of the scientific return of the Apollo missions’ [17]. However, Apollo lunar sampling had focused on areas non-representative of the most widespread lunar surface features [18]. These limited sample sites have restricted new cognition of the Moon. \n\nChang’E-5 (CE-5) is a sample return mission in China’s lunar exploration strategy of ‘Orbit-LandSample return’. The sampling site is in the northeastern Oceanus Procellarum, with longitude and latitude of $51.916^{\\circ}\\mathrm{W}$ and $43.058^{\\circ}\\mathrm{N}$ . It is a new region with the highest sampling latitude to date, a latitude not reached by the previous Apollo and Luna sampling missions (Fig. 1). The returned CE-5 samples might carry information about the youngest volcanic activity on the Moon [19,20]. \n\n![](images/14024385a27b9161fa5cb3ba72f3ae0ef78692b3f21cd468b8abbbd536fcc2d8.jpg) \nFigure 1. The distribution of lunar sampling sites and images of the CE-5 sampling site. (a) Lunar sampling sites and dates. Apollo and Luna sampling sites are within $30^{\\circ}$ of low latitude. The CE-5 sampling site is in a new area at mid-latitude. The image data are from the CE-1 global digital orthophoto map (DOM). Detailed information about these sites can be found in Supplementary Table 1. (b) The panoramic image of the CE-5 landing site. The 120 images taken by the panoramic camera onboard the CE-5 lander were mosaiced using fisheye projection, with a horizontal field of view ${\\sim}220^{\\circ}$ . (c) A partial image of CE-5 scooped sampling. The arrows show the trace of scooped sampling. All images are from the China Lunar Exploration Data Release Website (https://moon.bao.ac.cn). \n\nThis study focuses on the preliminary examination of the lunar samples returned from the CE-5 mission, to obtain the physical properties, petrography, mineralogy and chemical characteristics of lunar soils and clasts, providing basic information for subsequent scientific research. \n\n# RESULTS \n\n# Geological context of the CE-5 lunar samples \n\nOceanus Procellarum, with the largest distribution of lunar mare basalts, is a prominent geochemically anomalous region on the lunar nearside. This region is enriched with thorium, uranium and potassium [21], with a relatively thin lunar crust [22], which might result in a potentially long history of volcanism [23] and a more complex thermal evolutionary history [24]. \n\nThe CE-5 landing area $(41^{\\circ}-45^{\\circ}\\mathrm{N},69^{\\circ}-49^{\\circ}\\mathrm{W})$ is in the relatively flat terrain of the mare plain in the northeastern Oceanus Procellarum (red box in Fig. 2a) [25]. The images of the sampling area show a relatively homogeneous texture and dark color (Figs 1b and 2b). Although the topography of the selected landing area is gentle, geometrically large terrains are distributed in the Oceanus Procellarum region (Fig. 2a and b), such as wrinkle ridges, Mons R¨umker, craters of varied sizes and depths, and narrow lunar rilles. Most craters larger than $2\\mathrm{km}$ in diameter are distributed in the western mare of the selected landing area, where the crater density is greater than in the eastern mare. Studies of crater size-frequency distribution indicate that the eastern mare of the selected landing area is the youngest geologic unit on the Moon [19,20]. Northeast of the sampling area is Rima Sharp, with an overall north–south orientation, a length of $\\sim566\\mathrm{km}$ and a width of $_{0.8-3\\mathrm{km}}$ (Fig. 2a) [26,27]. \n\n![](images/a0334cfc2bb8c7b269cfb9b0072158df758db8a07b8c2a87ea9a4953d14628b4.jpg) \nFigure 2. Geographical and geological backgrounds of the CE-5 lunar sample. The $'+'$ in all images are CE landing sites. (a) Topographic map with the red box showing the selected landing area. The topographic data are from the CE-2 global digital elevation model data. (b) Image and geological background of the landing site with the ejecta distribution. The white box is the area of c and d. Image data are from CE-2 global DOM. (c) Spectral concentration map of FeO (wt%) in the sampling area. It shows that the sampling site is uncontaminated by ejecta materials. FeO content is derived from https://astrogeology.usgs.gov/search/map/Moon/Kaguya/MI/MineralMaps/Lunar˙Kaguya˙MIMap˙MineralDeconv˙ FeOWeightPercent˙50N50S. (d) The enlarged map of the relative ejecta concentration index of the sampling area. The sampling site is free of ejecta contamination. All CE images are from the China Lunar Exploration Data Release Website (https://moon.bao.ac.cn). \n\nCE-5 finally landed in the eastern part of the selected landing area on the mare surface to the northeast of Mons Heng and southeast of Crater Xu \n\nGuangqi (Fig. 2a, c and d). The sampling site’s surface is loose regolith scattered with different sized boulders (Fig. 1c). \n\nThe CE-5 selected landing area (Fig. 2a) is mostly distributed with ejecta rays that might originate from the Crater Pythagoras. Especially in the northwest of the selected landing area, the mare is covered with obvious north–northwest-oriented ejecta materials. However, these ejecta are cut off along the connecting line between Mons Hua and Mons R¨umker (Fig. 2b) because the volcanic activity in the CE5 sampling area might be younger than this impact event, resulting in lava flow covering and obliterating these former ejecta. Two sets of almost orthogonal ejecta (northwest and northeast), rather than Pythagoras ejecta, are distributed in the sampling area. The plume shape and faint concentration indicate the slight influence of these ejecta (Fig. 2c and d). Using FeO content as the tracing parameter, no obvious signs of ejecta can be observed within the sampling site (Fig. 2c). The ejecta index analysis shows that the sampling site is slightly contaminated compared to the darkest region of the selected landing area (Fig. 2d), consistent with Qian et al. [20], who proposed that the influence of the impact ejecta in the sampling area is less than $10\\%$ . Therefore, CE5 lunar samples can be regarded as the product of weathered local rock with only minimal mixing of exotic ejecta materials. \n\n# Physical properties of the CE-5 lunar samples \n\nThe lunar regolith was mostly gray-black near the CE-5 sampling site (Fig. 3a). Although the lunar regolith appears gray-black (Fig. 3b), the minerals are colorful under the stereomicroscope (Fig. 3c). Refer to Supplementary Note 1 for details about sample preparation. \n\nParticle size distribution of CE-5 lunar soils We randomly selected $155\\mathrm{~\\mg~}$ soils (No. CE5C0800YJFM001) from CE-5 scooped samples to systematically analyze its particle size distribution. The images of fully dispersed soil particles were taken using an optical microscope, followed by geometric measurements and statistical analysis. In total, 316 800 images of $2560~\\times~1920$ pixels were acquired, and 299 869 867 particles of $1-$ $500\\mu\\mathrm{m}$ (image resolution $0.4\\mu\\mathrm{m}$ ) were identified. From the major axis, minor axis and projected area measurements, the shape parameters and modal mass of the lunar soil particles were calculated (Supplementary Table 2). \n\nOur results show that $95\\%$ (in number) of CE-5 soil particle sizes (equivalent diameter) are distributed in the range of 1.40–9.35 $\\mu\\mathrm{m}$ (mean $3.96~\\mu\\mathrm{m},$ Fig. 3d), belonging to clay $\\left(<3.91~\\mu\\mathrm{m}\\right)$ to fine silt level $\\left(3.91-15.63\\ \\mu\\mathrm{m}\\right)$ [28]. Similarly, the grain mass of CE-5 samples is also concentrated. Of the lunar soil particles, $95\\%$ have a modal mass between $0.0036~\\mathrm{ng}$ and 0.8304 ng, with a mean of 0.5567 ng, a mode of 0.0095 ng and a median of $0.0205~\\mathrm{ng}$ (Fig. 3e). However, according to the particle size-mass distribution (Fig. 3f), $95\\%$ (in mass) of the CE-5 lunar soils is in the range of $4.84~\\mu\\mathrm{m}$ $(\\Phi7.69)$ to $432.27~\\mu\\mathrm{m}$ $\\left(\\Phi1.21\\right)$ . The mean $((\\phi_{16}\\:+\\:\\phi_{50}\\:+\\:\\phi_{84})/3)$ , mode and median $\\left(\\phi_{50}\\right)$ particle sizes are 49.80 $\\mu\\mathrm{m}$ $\\left(\\Phi4.33\\right)$ , $88.38~\\mu\\mathrm{m}$ $\\left(\\Phi3.50\\right)$ and $52.54~\\mu\\mathrm{m}$ $\\left(\\Phi4.25\\right)$ , respectively [29] (Fig. 3f). Therefore, the particle size of most lunar soils (in mass) is concentrated around $50\\mu\\mathrm{m}$ . \n\n# Density of CE-5 lunar soils \n\nA Quantachrome ULTRAPYC 1200e analyzer was used to determine the true density of three lunar soil samples by helium displacement (one sample from CE5C0800YJFM005 and two samples from CE5C0100YJFM002). Each sample was measured nine times, and the average was taken as the true density of that soil sample. Results showed that the average natural bulk density of the three lunar soil samples was $1.2387\\mathrm{g}/\\mathrm{cm}^{3}$ , and the average true density was $3.1952\\mathrm{g}/\\mathrm{cm}^{3}$ , which is within the density range of terrestrial basalt. \n\nSpecific surface area of CE-5 lunar soils We conducted 15 specific surface area (SSA) measurements on a $7.967\\textrm{~g}$ soil sample (CE5C0100YJFM002) using a Quantachrome inert gas-adsorption SSA analyzer. Results showed that the SSA of the CE-5 whole soils is in the range of $0.55~\\mathrm{m}^{2}/\\mathrm{g}$ to $0.57\\mathrm{~m}^{2}/\\mathrm{g},$ with an average of $0.56\\mathrm{m}^{2}/\\mathrm{g}$ . \n\nA spherical particle’s SSA is inversely proportional to its diameter and proportional to its total surface area. With a known SSA (measured value), the particle aggregate’s mean size can be calculated if the particles are regular spheres (Supplementary Note 2). By comparing the calculated mean particle size with the measured value, the extent to which the particles within this particle aggregate deviate from the sphere can be inferred. Based on the measured SSA and true density of the CE-5 soil sample, the equivalent diameter of the CE-5 soil particle was calculated to be ${\\sim}3.35\\mu\\mathrm{m}$ . It is slightly lower than the average equivalent diameter $(3.96\\mu\\mathrm{m})$ of CE-5 soil particles measured in this study. Therefore, the particle shape of CE-5 lunar soils is less regular than that of the sphere and can reach $84.6\\%$ of the sphere macroscopically. This particle size is more consistent with that of Earth clay. The SSA of Earth clay $\\left(10{-}800~\\mathrm{m}^{2}/\\mathrm{g}\\right)$ [30] is much larger than that of the CE-5 lunar soil sample, indicating that CE-5 lunar soil particles are more regular or have a higher roundness than common Earth clay. However, we cannot rule out that the large porosity of Earth clay might contribute to its large surface area. \n\n![](images/bb99a31962a55fadcca1518d6a6d63c4de0a6f9a6f992cad9737b50774b2634d.jpg) \nFigure 3. Image characteristics and particle size distribution of CE-5 lunar soils. (a) The surveillance camera image shows the characteristics of the lunar regolith at the sample site. The lunar regolith was mostly gray-black. The dark traces are the imprints after sampling. (b) A laboratory camera photo of scooped lunar regolith. (c) An image of lunar soil particles when magnified equivalent to the lunar soil grain size using a stereomicroscope (e.g. yellow-green olivine, white feldspar, brown-black pyroxene and brown glass). (d) The number (percent) distribution of particle size (equivalent diameter). Particle sizes range from $1.11\\ \\mu\\mathsf{m}$ to $499.8\\ \\mu\\mathrm{m}$ , with a mean of $3.96\\mu\\mathrm{m}$ , a median of $2.90\\mu\\mathrm{m}$ and a mode of $3.39\\mu\\mathrm{m}$ . Of the particles, $95\\%$ (the gray part) are distributed between $1.40\\mu\\mathrm{m}$ and $9.35\\mu\\mathrm{m}$ . (e) The modal mass (percent) distribution of particle size. The modal mass ranges from 0.0012 ng to 109177.8937 ng, with a mean of 0.5567 ng, a median of 0.0205 ng and a mode of 0.0095 ng. Of the particle mass, $95\\%$ (the gray part) is distributed between 0.0036 ng and 0.8304 ng. (f) The modal mass-grain size distribution of CE-5 lunar soils. Of the particle mass, $95\\%$ (the gray part) is distributed between $4.84\\mu\\mathrm{m}\\left(\\Phi7.69\\right)$ and $432.27\\mu\\mathrm{m}(\\Phi1.21).$ with a mean of $49.80\\mu\\mathrm{m}\\left(\\Phi4.33\\right)$ , a mode of $88.38\\mu\\mathrm{m}\\left(\\Phi3.50\\right)$ and a median $|\\phi_{50}|$ of $52.54\\mu\\mathrm{m}\\left(\\Phi4.25\\right)$ . (g) The grain size-sorting comparison between CE-5 and Apollo 17 lunar soils. CE-5 lunar soils tend to be mature. Apollo 17 lunar soil data are from Ref. [33]. (h) The comparison of modal mass-grain size distribution between CE-5 and Apollo lunar soils of varying maturity. The red solid line is CE-5 lunar soils, the dashed line is Apollo 17 (71061,1) immature lunar soils, the dot-dashed line is Apollo 17 (75081,36) submature lunar soils and the dotted line is Apollo 17 (74121,12) mature lunar soils. Apollo 17 lunar soil data are from Ref. [33]. \n\n# Petrographic characteristics of CE-5 lunar samples \n\nThe particle sizes of CE-5 lunar samples are mostly distributed in the micron scale, and few rock fragments are larger than $1\\ \\mathrm{cm}$ . More than 95 $\\mathbf{wt\\%}$ (in mass) of the CE-5 particles (equivalently $\\geq5\\ \\mu\\mathrm{m}$ in size) in three polished sections were counted and analyzed by backscattered electron (BSE) images. The statistical results show that the average percentages for a single mineral, dual minerals and three or more minerals are $27.0\\%$ , $21.5\\%$ and $51.5\\%$ , and the average model masses are $57.4\\%$ , $32.1\\%$ and $10.5\\%$ (Supplementary Fig. 1), respectively. The rock clasts percentage $(\\sim50\\%)$ in CE5 lunar soils is high; however, the mass percentage is extremely low $(\\sim10\\%)$ , indicating that the volume/area of rock clasts is much smaller than that of single mineral clasts. This might be related to the coarse-grained structure of the original bedrock breaking and separating easily into single minerals during weathering. \n\nDuring the sample separation process, many small fragments from $1\\ \\mathrm{mm}$ to $1\\ \\mathrm{cm}$ were collected. Through preliminary observations using a stereomicroscope and a scanning electron microscope at the National Astronomical Observatories, Chinese Academy of Sciences (NAOC), these fragments could be classified into basaltic clasts, agglutinates, breccias and glass. \n\n# Basaltic clasts \n\nBasalt is the dominant and most significant lithic clast in the CE-5 lunar sample (many complex mineral grains smaller than $1\\ \\mathrm{mm}$ are of this type). It mostly comprises pyroxene, feldspar, olivine and ilmenite, with minor amounts of troilite, K-feldspar, quartz, tranquillityite, apatite, merrillite, baddeleyite and zirconolite. From detailed petrographic observations, five distinct textural types of basaltic clasts have been recognized. \n\nAphanitic texture: The mineral grains are extremely tiny (typically ${<}0.01\\ \\mathrm{mm}$ ), with fibrous intergrowth of plagioclase and ilmenite microcrystals oriented in the glass matrix (Fig. 4a). \n\nPorphyritic texture: The mineral grain size is typically $<0.05\\mathrm{mm}$ . Plagioclase and ilmenite are stripelike oriented. Olivine occurs as phenocrysts with grain sizes up to $0.5\\mathrm{mm}$ (Fig. 4b). \n\nOphitic/subophitic texture: The grain size is fine, typically $<0.1\\ \\mathrm{mm}$ . Euhedral plagioclase laths are filled with pyroxene and olivine grains (Fig. 4c). \n\nPoikilitic texture: The mineral grains are coarse $(0.1-0.5\\ \\mathrm{mm})$ ). These coexisting silicate minerals, including pyroxene, olivine and plagioclase, show complex petrographic relationships (Fig. 4d). \n\nEquigranular texture: The grain size ranges from $0.1\\mathrm{mm}$ to $0.5\\mathrm{mm}$ . The primary minerals of pyroxene and feldspar are approximately equal in size and have simple coexisting relationships (Fig. 4e). \n\nThe primary minerals in 29 basaltic clasts from seven polished sections were analyzed for their chemical composition (Supplementary Note 3 and Supplementary Table 3). The results showed that An $(100\\times\\mathrm{Ca}/(\\mathrm{Ca}+\\mathrm{Na}+\\mathrm{K})$ molar ratio) of feldspar in these basaltic clasts is in the range of 75.0 to 95.5 ( ${\\bf\\dot{\\rho}}_{n}=172,$ ), with most being bytownite (average composition $\\mathrm{An}_{83.9}\\mathrm{Ab}_{15.2}\\mathrm{Or}_{0.9}.$ , $n=166\\mathrm{\\cdot}$ ) (Supplementary Fig. 2a). Pyroxene is predominantly augite with an average composition of $\\mathrm{Wo}_{32.9}\\mathrm{En}_{28.2}\\mathrm{Fs}_{38.9}$ ( ${\\bf\\dot{\\theta}}_{n}={\\bf\\Phi}_{}$ 90). Pigeonite is rare, with an average composition of $\\mathrm{Wo_{17.8}E n_{14.4}F s_{67.8}}$ ${\\bf\\dot{\\rho}}_{n}=2$ ) (Supplementary Fig. 2b). The Fe/Mn values for pyroxene in basaltic clasts range from 48.4 to 79.4, with an average of 61.6 ${\\bf\\dot{\\boldsymbol{n}}}=92{\\bf\\dot{\\boldsymbol{\\mathbf{\\rho}}}},$ ). The Fo $\\mathrm{\\langle100\\timesMg/(Mg+Fe)}$ molar ratio) of olivine varies from 1.0 to 58.3, with an average of 37.2 ( ${\\bf\\dot{\\rho}}_{n}=73$ ). Most olivines have Fo ${<}50$ ( ${\\bf\\dot{\\theta}}_{n}={\\bf\\Phi}_{}$ 54) (Supplementary Fig. 2c). The mineral compositions of these basaltic clasts correlate well with that of CE-5 whole soils, indicating that the lunar soils from the CE-5 landing site mostly comprises basalt weathered from the local basaltic bedrock. \n\n# Agglutinates \n\nAgglutinates comprise lithic and mineral fragments welded together by the glass produced by melting due to small meteoroid impacts. Most agglutinates are irregular in shape, loose and easily broken, with relatively well-developed pores (Fig. 4f). \n\n# Breccias \n\nThe composition of breccias is complex, including mineral fragments and lithic clasts. The mineral fragments mostly comprise plagioclase, pyroxene, olivine and ilmenite, whereas the lithic clasts are almost exclusively basalt. The matrix mostly comprises plagioclase, pyroxene, olivine and glass, reflecting that this breccia is a bonding product of impacted basalt. The surface is occasionally covered with glass with highly variable content. \n\n# Glasses \n\nAccording to morphological differences, glassy material in lunar soils can be divided into two principal categories. One is round glass beads (Fig. $^{4}\\mathrm{g})$ , highly variable in color, mostly black and brown, with occasional green glass beads. The other is irregularly shaped glass fragments with obvious shell-like fractures (Fig. 4h). Brown pits are sometimes visible on the glass surface. \n\n# Mineralogy of CE-5 lunar samples \n\n# Mineral species and abundance \n\nThe phase types and their contents of CE-5 lunar soils ( ${\\sim}100$ mg, CE5C0800YJFM001-1, CE5C0100YJFM002-1 and CE5C0100YJFM002- \n\n![](images/1d0bcc802aac924057a95756aa86584fdbc4aaf82116a201db00c662269ee55b.jpg) \nFigure 4. BSE images and stereomicrographs of typical basaltic clasts, agglutinate and glasses from the CE-5 lunar sample. (a)–(f) BSE images for basaltic clasts and agglutinate with different textures. The upper right corner of the BSE image is the stereomicrograph corresponding to each clast. (g), (h) Stereomicrographs of glass. Abbreviations: Pyx, pyroxene; Pl, plagioclase; Ol, olivine; Ilm, ilmenite; Glass, Gls. \n\n2) were analyzed using a Bruker D8 Advance X-ray diffraction (XRD) analyzer and the Rietveld whole-pattern fitting method (Supplementary Note 4). The phase types identified by XRD and involved in Rietveld’s whole-pattern fitting include augite, pigeonite, plagioclase, forsterite, fayalite, ilmenite, quartz, apatite and glass (Supplementary Table 4 and Supplementary Fig. 3). Results show that the content of plagioclase and augite in CE-5 lunar soils can reach $\\sim30\\%$ (Supplementary Table 5). The contents of pigeonite and glass are $10\\%-20\\%$ , and the other minerals are ${<}10\\%$ . Olivine (mostly fayalite) is only $5\\%-6\\%$ , and ilmenite is $4\\%-5\\%$ . A small amount of apatite is present (up to $1.4\\%$ ). \n\nHowever, no orthopyroxene was found in CE-5 soils. These features are consistent with the results of basaltic clast mineralogy, indicating that CE-5 lunar soils is equivalent to iron and calcium-rich basalt (Fig. 5a and Supplementary Table 5). \n\n# Mineral composition \n\nThree major silicate minerals (monomineral fragments and minerals in lithic clasts) in 18 lunar soil polished sections were analyzed using an electron probe microanalyzer (EPMA). Two sections were taken from scooped sample bottles 01 to 07, three sections from scooped sample bottle 08, and one from scooped sample bottle 09 (Supplementary Note 3 and Supplementary Table 3). \n\nThe feldspar composition of CE-5 lunar soils is heterogeneous, with An varying from 76.1 to 97.6 ${\\bf\\dot{\\mathbf{\\rho}}}_{n}=277,$ ). More than $90\\%$ of the feldspar are bytownite (Fig. 5b), with an average composition of $\\mathrm{An}_{84.5}\\mathrm{Ab}_{14.6}\\mathrm{Or}_{0.9}$ ${\\bf\\zeta}_{n}=252{\\bf\\zeta}_{,}$ ). The content of anorthite is ${<}10\\%$ , with an average composition of $\\mathrm{An}_{92.5}\\mathrm{Ab}_{7.3}\\mathrm{Or}_{0.2}$ ${\\bf\\ddot{\\Psi}}_{n}=25$ ). This feldspar composition is comparable to the Apollo basalt (An varies from 80.5 to 95.7) [31]. However, minor feldspar with An larger than 95.7 ( ${\\bf\\chi}_{n}=5\\bf{\\chi},$ exists. \n\nThe pyroxene composition of CE-5 lunar soils is variable, mostly comprising augite followed by pigeonite and without orthopyroxene (Fig. 5c), correlating well with previous XRD analyses. The 425 analyzed data points of pyroxene indicate that augite accounts for $90\\%$ of pyroxene, with an average composition of $\\mathrm{Wo}_{31.4}\\mathrm{En}_{26.3}\\mathrm{Fs}_{42.3}$ ${\\mathit{\\check{n}}}=387{\\mathit{\\check{\\mathbf{\\ell}}}}.$ ), and pigeonite accounts for the remaining $10\\%$ , with an average composition of $\\mathrm{Wo_{16.6}E n_{19.0}F s_{64.2}}$ ${\\mathit{\\check{n}}}=38{\\mathit{\\check{\\mathbf{\\ell}}}}$ . The composition of pyroxene is also consistent with that of the Apollo basalts (Wo: 4.0–47.4; En: 0.4– 67.8; Fs: 14.5–85.8) [31]. \n\nThe olivine composition is variable among different grains, with Fo distributed in the range of 0.1 to 65.1 ${\\bf\\dot{\\rho}}_{n}=232\\dot{\\bf\\rho}_{.}$ ) (Fig. 5d). Most olivine grains have Fo concentrated between 40 and 60, and $70\\%$ grains ${\\mathit{\\check{n}}}=162{\\mathit{\\check{\\mathbf{\\ell}}}}$ are Fe-rich (Fo values ${<}50$ ). In some cases, the olivine composition varies slightly from the core to the rim. \n\nMafic minerals (pyroxene and olivine) from different parent bodies (e.g. Earth, Moon and Mars) have different Fe/Mn atomic molar ratios due to the relative volatilities of Fe and Mn and the oxidation conditions of parent bodies. The pyroxene $\\mathrm{Fe/Mn}$ ratio in CE-5 lunar soils ranges from 45 to 86.6, with an average of 62.6 $n=425$ ). The olivine MnO content is $0.28\\mathrm{-}0.94\\mathrm{wt}\\%$ , and the Fe/Mn ratio is 72.1– 121.5, with an average of 95.3 ( $\\scriptstyle n=232$ ). The $\\mathrm{Fe/Mn}$ ratios for pyroxene and olivine are within the lunar trend line (Fig. 5e and f) and possess a genetic linkage with lunar environments, unlike Earth, Mars, asteroids and chondrites [32]. \n\n![](images/5a0fbda6953de023ecba6032df166b20106e36d5b27875b02fd66732c04a57f8.jpg) \nFigure 5. Mineral composition of CE-5 lunar soils compared with Apollo and Luna samples. (a) The triangular plot of major mineral abundances. CE-5 lunar soils are significantly enriched in pyroxene and low in olivine. The data of Apollo and Luna soils are from Refs [40,41]. (b)–(d) The mineral composition of plagioclase, pyroxene and olivine in CE-5 lunar soils. Plagioclase is mostly within the composition of bytownite. Pyroxene lies within the range of high-calcium pyroxene and is dominated by augite with a small amount of pigeonite. Olivine is mostly fayalite. (e), (f) Mn versus Fe atoms per formula unit in pyroxene and olivine in CE-5 lunar soils. Planetary trend lines are from Ref. [32] and references therein. Abbreviations: afu, atoms per formula unit. \n\n# Chemistry of CE-5 lunar samples \n\nThe bulk chemical composition of CE-5 lunar soils was analyzed using instrumental neutron activation analysis (INAA) and X-ray fluorescence spectrometer (XRF) (Supplementary Notes 4 and 5). CE5C0800YJFM002 and CE5C0800YJFM003 were analyzed using INAA (Supplementary Table 6), and CE5C0800YJFM002 was further analyzed using XRF (Table 1 and Supplementary Table 7). Most analyzed major elements (Na, Mg, Al, K, Ca, Ti, Fe and Mn) correlate well. The overall abundance of rare-earth element (REE) for CE-5 lunar soils correlates with that of Apollo 12 and is higher than most other lunar soils, except for Apollo 14 soils. REE patterns show higher light REE (LREE) concentrations, a negative Eu anomaly and lower heavy REE (HREE) concentrations. \n\nTable 1. Bulk chemical composition for CE-5 lunar soils. \n\n\n
XRF
Element wt%SiO2 42.2TiOAlO3FeOMnOMgO 6.48CaO 11.0NaO 0.26KO 0.19PO5 0.23TotalMg#
Uncertainty(k = 2)0.345.00 0.0610.8 0.1822.5 0.330.28 0.030.350.100.2100.150.0598.9433.9
INAA
Fe
Element ppmNa 3420Mg 38600Al 57300K 1510Ca 74500ScTiVCrMnCoNi 136ZnRb 7.47
Uncertainty(k = 2)20524702600151480066 2.631100 160095.8 81410 56.42150 86174000 700040 1.61116.2 3.21.49
U
ElementZrLaCsCePrSmEuGdTbDyHoLuTaTh1.41
ppm45836.10.16992.812.516.12.5618.93.5120.94.501.411.774.72
Uncertainty(k = 2)341.40.0383.72.220.60.10.770.281.41.40.080.180.280.28
\n\n# DISCUSSION \n\n# Comparison of physical properties between CE-5 and Apollo samples \n\nParticle size distribution is a fundamental physical parameter of lunar soils, affecting strength, compressibility, optical properties and thermal properties. During the lunar surface’s weathering process, the soils will develop from immature, submature to mature as the surface exposure time increases. This process gradually decreases coarse particles and increases fine particles and agglutinates. Particle size analysis shows that about half of the immature Apollo lunar soils have a bimodal feature in their particle size distribution [33]. In contrast, most submature and mature Apollo lunar soils showed a single peak. The peak width narrows, exhibiting better sorting characteristics. The number and modal mass distributions of CE-5 lunar soil particles (Fig. 3d and e) have obvious single peaks, indicating their higher maturity. This implies that the CE-5 lunar soils are characterized by a relatively homogeneous origin, possibly from the continuous basaltic bedrock weathering. About $60\\%$ of the Apollo and Luna samples (47 of 80) have a larger mean size, and $88\\%$ (70 of 80) have a larger sorting $((\\phi_{84}-\\phi_{16})/4+$ $\\displaystyle\\big(\\phi_{95}-\\phi_{5}\\big)/6.6\\big)$ [34,35] than CE-5 soils (Supplementary Table 8). Therefore, CE-5 lunar soil samples are finer, better sorted (smaller sorting value) and relatively more mature than most Apollo and Luna soils $(\\mathrm{Fig}.3\\mathrm{g})$ . CE-5 lunar soil samples are different from the immature sample 71061,1 but similar to samples 75018,36 and 74121,12 (Fig. 3h), and can be classified as mature lunar soils. \n\nThe lunar soil density helps us understand its material composition, elasticity, thermal diffusivity, porosity and compressibility [36]. The specific gravity of CE-5 lunar soil samples is within the range of Apollo samples (2.9–3.24), but this value is significantly higher than that of Apollo 12 (12029, 12057) and Apollo 14 (14163, 14259) lunar soils $(\\sim2.9)$ . It is close to Apollo 11 (10004, 10005) and Apollo 15 lunar soils (15061: $3.24~\\mathrm{g/cm}^{3}.$ ), but slightly lower than lunar basalt (10020: $3.25\\mathrm{g}/\\mathrm{cm}^{3}$ ; 70017: $3.57\\ \\mathrm{g}/\\mathrm{cm}^{3}$ ; 70215: $3.44~\\mathrm{g}/\\mathrm{cm}^{3}$ ) [15]. CE-5 whole soils could comprise a mafic component, which is close to basalt. \n\nThe SSA describes the total surface area per unit mass of a collection of solid particles, reflecting the particle size in the collection and the irregularity degree of the particle shape. It is related to the adsorption properties and surface activity of the particle. On the lunar surface, micrometeorite impact, solar wind ion bombardment, and thermal expansion and contraction can fine, destroy, smooth, aggregate, or alter the size and texture of the grains composing lunar soils [35]. By measuring the SSA of lunar soil samples, one can understand the comprehensive effects of these lunar surface processes on lunar soil grains and their capacity to adsorb reactive molecules (e.g. water). The measured SSA of the Apollo samples ranges from $0.02~\\mathrm{m}^{2}/\\mathrm{g}$ to $0.78\\mathrm{\\m}^{2}/\\mathrm{g},$ with an average of $0.5~\\mathrm{m}^{2}/\\mathrm{g}$ [15]. The SSA of the CE-5 sample is close to the average of the Apollo samples, especially close to 10084 (the mass-weighted average particle size of both samples is similar) [37]. The concentrated and small SSA values from Apollo to CE-5 lunar soils indicate relatively consistent particle size and surface properties of lunar soils globally. This demonstrates that gardening processes, such as micrometeorite bombardment, solar wind radiation, and thermal expansion and contraction are constant on the lunar surface [38]. Moreover, it is challenging for water to be stored either in Apollo or CE-5 lunar soil samples because of their small SSAs [39]. \n\n# CE-5 soils originated from weathered basalts \n\nThe total pyroxene content of the CE-5 lunar soils is ${\\sim}42\\%$ , significantly higher than that of Apollo lunar soils $\\left(0.9\\%-33.8\\%\\right)$ . Plagioclase content is ${\\sim}30.1\\%$ , slightly higher than that of Apollo mare samples $\\left(13.4\\%-20.0\\%\\right)$ , but significantly lower than that of Apollo 16 highland samples $\\left(28.1\\%-64.3\\%\\right)$ . The olivine content is ${\\sim}5.7\\%$ , close to that of Apollo lunar soils $\\left(0.3\\%-4.8\\%\\right)$ . The glass content is only $11.6\\%-20.0\\%$ , with an average of $\\sim16.6\\%$ , significantly lower than that of Apollo soils $\\left(25.4\\%-72.3\\%\\right)$ [40,41]. CE-5 samples are mature soils according to the particle size results, and should have a high glass content. However, based on previous studies of Apollo samples, lunar soil maturity is not clearly related to high-intensity large meteorite impacts (producing impact glass) but to the injection of low-intensity micrometeorites, e.g. mm-size or smaller (producing agglutinitic glass). Thus, the low glass content of CE-5 samples indicates that they were less likely to be impacted by large meteorites, consistent with the lower crater density of the CE-5 landing area. \n\nIn the triangular plot of major mineral abundance, CE-5 samples are in the middle left of the map, similar to the Apollo 11, 12, 15 and 17 lunar mare samples (Fig. 5a). The highland lunar soils of Apollo 16 are mostly in the upper vertex in Fig. 5a, whereas Apollo 14 lunar highland soils exhibit a similar mineral distribution to mare soils due to the presence of ${\\sim}58\\%$ of Imbrium ejecta materials [42]. Compared with Apollo, CE-5 samples have higher pyroxene and lower plagioclase, and a typical mineral abundance of mare basalts rather than anorthosite and troctolite. Therefore, CE-5 lunar soils are mostly formed by accumulating weathered local basalt. \n\nSince soils with few clasts larger than 1 cm dominate CE-5 lunar samples, it is challenging to perform a bulk chemical analysis of lunar rock. Compared with the Apollo and Luna missions, the CE-5 lunar soils are lower $\\mathrm{{Al}}_{2}\\mathrm{{O}}_{3}$ $\\left(10.8\\%\\right)$ and CaO $(11\\%)$ and higher FeO $\\left(22.5\\%\\right)$ , significantly different from feldspathic and KREEP (an acronym from the letters K (potassium), REE, and P (phosphorus)) endmembers and similar to the mare basaltic endmember (Fig. 6a–c). Therefore, the CE-5 lunar soils are clean and comprises in situ mare basalts. Combined with the results of the ejecta image analysis of the sampling area (Fig. 2), the CE-5 lunar soils are essentially free of contamination by exotic ejected materials. Therefore, we use the bulk chemical composition of lunar soils to represent the local basalt. \n\nThe $\\mathrm{SiO}_{2}$ content of CE-5 lunar soils is as low as $42.2\\%$ but still within the range of mare basalts from Apollo missions $(38\\%-48\\%)$ . Compared with Earth’s basalts, the $\\mathrm{SiO}_{2}$ content of CE-5 lunar soils is significantly lower than that of subalkaline tholeiitic basalts and belongs to the ultramafic rock $\\mathrm{\\bar{\\itSiO}}_{2}$ $<45\\%$ ), whereas the $\\mathbf{MgO}$ content of $6.5\\%$ is much lower than that of komatiites $\\mathrm{(MgO\\mathrm{~>~}18\\%}$ ). According to the total alkali versus silica classification of the Earth’s volcanic rocks, the basalt in the CE-5 landing site is in the region of picro-basalt based on $\\mathrm{SiO}_{2}$ and alkali element $\\mathrm{(Na_{2}O+K_{2}O}$ $\\qquad<0.5\\%$ ) compositions. However, their olivine content ( $5\\%$ in the XRD results presented previously) is much lower than that of Earth’s picro-basalt $(25\\%-$ $40\\%$ . Therefore, the chemical composition of the protoliths forming CE-5 lunar soils is different from Earth basalts, and it is challenging to study CE-5 lunar soils using the classification criteria of Earth’s basalt. \n\nMare basalts collected from Apollo and Luna missions are commonly defined as diverse types using $\\mathrm{TiO}_{2}$ , ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ and K contents [4]. According to this classification scheme, CE-5 lunar soils belong to low-Ti/low-Al/low-K species (Fig. 6d and e), with significantly higher FeO content $(22.5\\%$ , Fig. 6a and c) and a lower $\\mathbf{M}\\mathbf{g}$ index $(\\mathrm{Mg/(Mg+Fe)}$ molar ratio $=33.9$ ). Most mare basalts from Apollo and Luna collections have FeO contents below $22\\%$ and $\\mathbf{M}\\mathbf{g}^{\\#}$ significantly higher than 35. Only the mare basalt from Luna 24 has a FeO content $(22.4\\%)$ similar to the CE-5 lunar soils, but it still has a high $\\mathbf{M}\\mathbf{g}^{\\#}$ [43]. \n\nThe INAA results showed that the U, Th and $\\mathrm{K}_{2}\\mathrm{O}$ contents of CE-5 lunar soils are $1.41\\mathrm{ppm},4.72\\mathrm{ppm}$ and $0.19\\%$ , respectively, significantly lower than the U ( $\\mathrm{(4\\ppm)}$ , Th $\\left(15.4~\\mathrm{ppm}\\right)$ and $\\mathrm{K}_{2}\\mathrm{O}$ $(0.5\\%)$ contents of typical KREEP basalts [44,45]. Studies of Apollo samples have shown that the REE content of lunar KREEP composition is several hundreds to thousands of times higher than the chondrite CInormalized ratio [46]. However, the REE content of CE-5 lunar soils is significantly lower than that of typical KREEP, indicating that the mare basalt in the CE-5 landing site is not a KREEP basalt (Fig. 6f). Although the REE content of CE-5 is significantly lower than KREEP, it is high among the mare basalts (La is ${\\sim}115$ times higher than that of carbonaceous chondrites) [47] and close to the maximum REE content of mare basalts. In the REE pattern, CE-5 lunar soils are slightly enriched in LREE, with little fractionation between LREE and HREE. The overall REE pattern shape is similar to that of Apollo 12 lunar soils. There is a clear negative anomaly in Eu, a characteristic of mare basalt. This is also consistent with the expectation that the feldspathic lunar crust formed early in the lunar magma ocean model. \n\n![](images/93335be173cec65b6ee7d5c94e4857243ef6e5ae319a3e37d496607aeccb991b.jpg) \nFigure 6. The chemical composition of CE-5 lunar soils compared with Apollo and Luna collections. (a)–(c) Elemental variations of $A l_{2}0_{3}$ , CaO and FeO (database and triangles from Ref. [16]). (d), (e) $\\mathrm{TiO}_{2}$ , $A l_{2}O_{3}$ and K classification scheme of mare basalts. The protoliths of CE-5 lunar soils belong to the low-Ti/low-Al/low-K species (database from Ref. [4]). (f) Chondritenormalized concentrations of REE in lunar soils as a function of an REE atom. The REE pattern of CE-5 lunar soils shows negative Eu anomalies. The database of Apollo samples is from Ref. [16] and the KREEP composition data are from Ref. [46]. Normalization values: 1.36C, where C represents the ‘Mean C1 Chondr.’ values of Table 1 in Ref. [48]. \n\n# Nature of mare basalts returned by the CE-5 mission \n\nThe particle size distribution and the similarity between the true density of CE-5 soils and Apollo basalt indicate a possible basaltic origin of the CE5 sample. The most abundant minerals composing CE-5 soils are pyroxene, followed by plagioclase, with fewer amounts of ilmenite and olivine, indicating that basaltic composition dominates CE-5 soils. Specifically, pyroxene in CE-5 basalt is mostly augite with no orthopyroxene, and fayalite dominates olivine. The CE-5 lunar samples are lowTi/low-Al/low-K basalt, exhibiting low $\\mathrm{SiO}_{2}$ and alkaline $\\left(\\mathrm{Na}_{2}\\mathrm{O}+\\mathrm{K}_{2}\\mathrm{O}\\right)$ content, moderate $\\mathrm{TiO}_{2}$ and ${\\mathrm{Al}}_{2}{\\mathrm{O}}_{3}$ , and very high FeO content. K, U, Th and REE contents of CE-5 soils are lower than KREEP materials but with a significant fractionation between different REE. Therefore, the CE-5 lunar sample could represent a new type of differentiated lunar basaltic rock. \n\n# SUMMARY \n\nThe CE-5 mission returned the latest lunar samples after 45 years of sampling missions by the United States and the Soviet Union. The sampling site is far from the low latitudes of the Apollo Belt, with little disturbance from impact ejecta, and the samples possess properties of native basaltic bedrock. \n\nThe CE-5 lunar sample will open an epochmaking and unique window for studying lunar science in the following aspects: (i) the Moon’s evolution; (ii) the timing, duration, volume, origin and emplacement mechanism of lunar volcanism in the northeastern Oceanus Procellarum; (iii) the bombardment history of the inner solar system; (iv) the galactic record in lunar regolith; (v) the lunar magnetic field and anomalies; and (vi) the relationship between lunar soil maturity and the contents of different glasses (impact and agglutinitic glass) [47]. \n\n# SUPPLEMENTARY DATA \n\nSupplementary data are available at NSR online. \n\n# ACKNOWLEDGEMENTS \n\nThanks to all the staff of China’s Chang’E-5 project for their hard work on in situ investigation and returning lunar samples. The samples studied in this work were provided by the China National Space Administration. We thank Shifeng Jin and Chunhua Xu from the Institute of Physics, Chinese Academy of Sciences, for XRD data analysis and interpretation. \n\n# FUNDING \n\nThis work was supported by the Key Research Program of the Chinese Academy of Sciences (ZDBS-SSW-JSC007). \n\n# AUTHOR CONTRIBUTIONS \n\nC.L., H.H., M.Y., P.Z.Y. and Z.O. designed the research and supervised this project. X.R., D.L., G.Z. and J.L. performed physical properties experiments. Q.Z., B.L., C.X., Y.Y. and D.X. conducted petrographic, mineralogical and geochemical research. G.Z., W.Z., Y.S. and H.Z. prepared sample mounting and measurements. C.L., Q.Z., X.R., B.L., D.L., X.Z., G.Z. and J.L. processed analytical data and wrote the manuscript. Q.W., W.W. and D.X. contributed spacecraft and instrumental operations and in situ lunar sample collection. O.Z., X.Z. and C.L. contributed scientific background and geological context. \n\nConflict of interest statement. None declared. \n\n# REFERENCES \n\n1. Taylor SR. Lunar Science: A Post-Apollo View: Scientific Results and Insights from the Lunar Samples. Amsterdam: Elsevier Science, 2016. \n2. Kuiper GP. Photographic Lunar Atlas. Chicago: University of Chicago Press, 1960. \n3. Smith JV, Anderson AT and Newton RC et al. Petrologic history of the Moon inferred from petrography, mineralogy, and petrogenesis of Apollo 11 rocks. In: Proceedings of the Apollo 11 Lunar Science Conference, Houston, 1970. New York: Pergamon Press, 897. \n4. Neal CR and Taylor LA. Petrogenesis of mare basalts: a record of lunar volcanism. Geochim Cosmochim Acta 1992; 56: 2177– 211. \n5. Shoemaker EM and Hackman RJ. Stratigraphic basis for a lunar time scale. In: Kopal Z and Mikhailov ZK (eds.). The Moon. London: Academic Press, 1962, 289–300. \n6. Neal CR. The Moon 35 years after Apollo: what’s left to learn? Geochemistry 2009; 69: 3–43. \n7. McCubbin FM, Herd CDK and Yada T et al. Advanced curation of astromaterials for planetary science. Space Sci Rev 2019; 215: 48. \n8. BVSP (Basaltic Volcanism Study Project). Basaltic Volcanism on the Terrestrial Planets. New York: Pergamon Press, 1981. \n9. Snape JF, Nemchin AA and Whitehouse MJ et al. The timing of basaltic volcanism at the Apollo landing sites. Geochim Cosmochim Acta 2019; 266: 29–53. \n10. Sto¨ffler D and Ryder G. Stratigraphy and isotope ages of lunar geologic units: chronological standard for the inner solar system. Space Sci Rev 2001; 96: 9–54. \n11. Hiesinger H and Head JW III. New views of lunar geoscience: an introduction and overview. Rev Mineral Geochem 2006; 60: 1–81. \n12. Borg LE, Connelly JN and Boyet M et al. Chronological evidence that the Moon is either young or did not have a global magma ocean. Nature 2011; 477: 70–2. \n13. Wieczorek MA, Jolliff BL and Khan A et al. The constitution and structure of the lunar interior. Rev Mineral Geochem 2006; 60: 221–364. \n14. Longhi J. Experimental petrology and petrogenesis of mare volcanics. Geochim Cosmochim Acta 1992; 56: 2235–51. \n15. Carrier WD III, Olhoeft GR and Mendell W. Physical properties of the lunar surface. In: Heiken GH, Vaniman DT and French BM surface and space-Moon interactions. Rev Mineral Geochem 2006; 60: 83–219. \n17. Wasserburg GJ. Isotopic adventures—geological, planetological, and cosmic. Annu Rev Earth Planet Sci 2003; 31: 1–74. \n18. Wasserburg GJ. The Moon and sixpence of science. Aeronaut Astronaut 1972; 10: 16–21. \n19. Hiesinger H, Head JW III and Wolf U et al. Ages and stratigraphy of mare basalts in Oceanus Procellarum, mare nubium, mare cognitum, and mare insularum. J Geophys Res 2003; 108: 5065–91. \n20. Qian YQ, Xiao L and Head JW et al. Young lunar mare basalts in the Chang’E-5 sample return region, northern Oceanus Procellarum. Earth Planet Sci Lett 2021; 555: 116702. \n21. Shearer CK, Hess PC and Wieczorek MA et al. Thermal and magmatic evolution of the Moon. Rev Mineral Geochem 2006; 60: 365–518. \n22. Wieczorek MA, Neumann GA and Nimmo F et al. The crust of the Moon as seen by GRAIL. Science 2013; 339: 671–5. \n23. Morota T, Haruyama J and Ohtake M et al. Timing and characteristics of the latest mare eruption on the Moon. Earth Planet Sci Lett 2011; 302: 255–66. \n24. Wieczorek MA and Phillips RJ. The Procellarum KREEP terrane: implications for mare volcanism and lunar evolution. J Geophys Res 2000; 105: 20417–30. \n25. Liu J, Zeng X and Li C et al. Landing site selection and overview of China’s lunar landing missions. Space Sci Rev 2021; 217: 6. \n26. Qian YQ, Xiao L and Zhao SY et al. Geology and scientific significance of the Ru¨mker region in northern Oceanus Procellarum: China’s Chang’E-5 landing region. J Geophys Res Planets 2018; 123: 1407–30. \n27. Qian Y, Xiao L and Head JW et al. The long sinuous rille system in northern Oceanus Procellarum and its relation to the Chang’e-5 returned samples. Geophys Res Lett 2021; 48: e2021GL092663. \n28. Wentworth CK. A scale of grade and class terms for clastic sediments. J Geol 1922; 30: 377–92. \n29. Folk RL and Ward WC. A study in the significance of grain size parameters. J Sediment Res 1957; 27: 3–26. \n30. Mitchell JK. Fundamentals of Soil Behavior. New York: Wiley, 1976. \n31. Papike J, Taylor L and Simon S. Lunar minerals. In: Heiken GH, Vaniman DT and French BM (eds.). Lunar Source Book—A User’s Guide to the Moon. Cambridge: Cambridge University Press, 1991. \n32. Joy KH, Crawford IA and Huss GR et al. An unusual clast in lunar meteorite MacAlpine Hills 88105: a unique lunar sample or projectile debris? Meteorit Planet Sci 2014; 49: 677–95. \n33. McKay DS, Fruland RM and Heiken GH. Grain size and the evolution of lunar soils. In: Proceedings of the Fifth Lunar Conference, Houston, 1974. New York: Pergamon Press, 887–903. \n34. National Aeronautics and Space Administration. Lunar Soils Grain Size Catalog. Houston, TX: Johnson Space Center, 1993. (NASA reference publication no. 1265). \n35. Gammage RB and Holmes HF. Specific surface area as a maturity index of lunar fines. Earth Planet Sci Lett 1975; 27: 424–6. \n36. Cadenhead DA and Stetter JR. Specific gravities of lunar materials using helium pycnometry. In: Lunar and Planetary Science Conference Proceedings, Houston, 1975. New York: Pergamon Press, 3199–206. \n37. Cadenhead DA, Brown MG and Rice DK et al. Some surface area and porosity characterizations of lunar soils. In: Proceedings of the Lunar Science Conference 8th, Houston, 1977. New York: Pergamon Press, 1291– 303. \n38. Holmes HF, Fuller EL Jr and Gammage RB. Interaction of gases with lunar materials: Apollo 12, 14, and 16 samples. In: Proceedings of the Lunar Science Conference, Houston, 1973. New York: Pergamon Press, 2413. \n39. Robens E, Bischoff A and Schreiber A et al. Investigation of surface properties of lunar regolith part II. J Therm Anal Calorim 2008; 94: 627–31. \n40. Taylor LA, Pieters CM and Keller LP et al. Lunar mare soils: space weathering and the major effects of surface-correlated nanophase Fe. J Geophys Res 2001; 106:27985–99. \n41. Taylor LA, Pieters CM and Patchen A et al. Mineralogical and chemical characterization of lunar highland soils: insights into the space weathering of soils on airless bodies. J Geophys Res 2010; 115: E02002. \n42. Haskin LA, Korotev RL and Gillis JJ et al. Stratigraphies of Apollo and Luna highland landing sites and provenances of materials from the perspective of basin impact ejecta modeling. In: Lunar and Planetary Science XXXIII, Houston, 2002. New York: Pergamon Press, 1364. \n43. Taylor GJ, Warren P and Ryder G et al. Lunar rocks. In: Heiken GH, Vaniman DT and French BM (eds.). Lunar Source Book—A User’s Guide to the Moon. Cambridge: Cambridge University Press, 1991. \n44. Warren PH and Wasson JT. Compositional petrographic investigation of pristine nonmare rocks. In: Proceedings of the Lunar and Planetary Science Conference 9th, Houston, 1978. New York: Pergamon Press, 185–217. \n45. Neal CR and Kramer GY. The composition of KREEP: a detailed study of KREEP basalt 15386. In: Lunar and Planetary Science XXXIV, Houston, 2003. New York: Pergamon Press, 2023. \n46. Warren PH, Jerde EA and Kallemeyn GW. Lunar meteorites: siderophile element contents, and implications for the composition and origin of the Moon. Earth Planet Sci Lett 1989; 91: 245–60. \n47. Tarte\\`se R, Anand M and Gattacceca J et al. Constraining the evolutionary history of the Moon and the inner solar system: a case for new returned lunar samples. Space Sci Rev 2019; 215: 54. \n48. Anders E and Grevesse N. Abundances of the elements: meteoritic and solar. Geochim Cosmochim Acta 1989; 53: 197–214. " + }, + { + "id": "10.1038_s41467-022-30702-z", + "DOI": "10.1038/s41467-022-30702-z", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-30702-z", + "Relative Dir Path": "mds/10.1038_s41467-022-30702-z", + "Article Title": "Iron atom-cluster interactions increase activity and improve durability in Fe-N-C fuel cells", + "Authors": "Wan, X; Liu, QT; Liu, JY; Liu, SY; Liu, XF; Zheng, LR; Shang, JX; Yu, RH; Shui, JL", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Simultaneously increasing the activity and stability of the single-atom active sites of M-N-C catalysts is critical but remains a great challenge. Here, we report an Fe-N-C catalyst with nitrogen-coordinated iron clusters and closely surrounding Fe-N-4 active sites for oxygen reduction reaction in acidic fuel cells. A strong electronic interaction is built between iron clusters and satellite Fe-N-4 due to unblocked electron transfer pathways and very short interacting distances. The iron clusters optimize the adsorption strength of oxygen reduction intermediates on Fe-N-4 and also shorten the bond amplitude of Fe-N-4 with incoherent vibrations. As a result, both the activity and stability of Fe-N-4 sites are increased by about 60% in terms of turnover frequency and demetalation resistance. This work shows the great potential of strong electronic interactions between multiphase metal species for improvements of single-atom catalysts. It is challenging to break the activity-stability trade-off in Fe-N-C fuel cell catalysts. Here, the authors show that interactions between iron atoms and clusters accelerate reaction kinetics and suppress demetalation to improve fuel cell stability.", + "Times Cited, WoS Core": 305, + "Times Cited, All Databases": 312, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000800650200024", + "Markdown": "# Iron atom–cluster interactions increase activity and improve durability in Fe–N–C fuel cells \n\nXin Wan 1, Qingtao Liu 1, Jieyuan Liu 1, Shiyuan Liu 1, Xiaofang Liu1, Lirong Zheng2, Jiaxiang Shang1, Ronghai $\\mathsf{Y u}^{1}\\&$ Jianglan Shui 1✉ \n\nSimultaneously increasing the activity and stability of the single-atom active sites of M–N–C catalysts is critical but remains a great challenge. Here, we report an Fe–N–C catalyst with nitrogen-coordinated iron clusters and closely surrounding $F e\\mathrm{-}N_{4}$ active sites for oxygen reduction reaction in acidic fuel cells. A strong electronic interaction is built between iron clusters and satellite Fe– ${\\bf\\cdot N_{4}}$ due to unblocked electron transfer pathways and very short interacting distances. The iron clusters optimize the adsorption strength of oxygen reduction intermediates on $F e\\mathrm{-}N_{4}$ and also shorten the bond amplitude of $F e\\mathrm{-}N_{4}$ with incoherent vibrations. As a result, both the activity and stability of $F e-N_{4}$ sites are increased by about $60\\%$ in terms of turnover frequency and demetalation resistance. This work shows the great potential of strong electronic interactions between multiphase metal species for improvements of single-atom catalysts. \n\nPyohrixgoylhgylezynee cmdieuentcat f-onri rmoegaencntyi-ocnahr (moOincR )rM icnNt pCnr)so iocnac leydxsictnhsg tahgre membrane fuel cells (PEMFC), and therefore regarded as promising low-cost alternatives to $\\mathrm{Pt/C}$ catalyst1–6. The overall activity of $\\mathrm{\\Delta\\M-N-C}$ catalysts can be promoted either by maximizing the active site density $(\\mathrm{SD})^{\\mathord{\\left.\\kern-\\nulldelimiterspace}-11\\right.}$ , or by enhancing the turnover frequency (TOF) of a single site. The latter could be realized by the atomic level regulation of the geometric and electronic structures of the active sites, so as to optimize the adsorption/desorption of ORR intermediates12–17. However, so far, the ORR activity of $\\mathrm{\\Delta\\M-N-C}$ in acidic media is still significantly lower than that of $\\mathrm{Pt}$ -based catalysts due to insufficient accessible active sites and less competitive $\\mathrm{TOF^{8,11,18}}$ . More importantly, the stability of $\\mathrm{\\Delta\\M-N-C}$ is far from satisfactory in real PEMFC19–24. The major causes of instability include the oxidation of carbon supports and the demetalation of $\\mathrm{M}{-}\\mathrm{N}_{x}$ active sites25–28. Anchoring active sites on highly graphitic carbons such as carbon nanotubes and graphene can improve the catalyst stability by enhancing corrosion resistance of the support29,30. However, such strategy often works at the cost of SD or $\\mathrm{\\ddot{T}O F}^{31,32}$ . As for the anti-demetalation strategy, this is still rare. To develop methods that can break the activity–stability trade-off for $\\mathrm{M-N}_{x}$ species is essential for both theoretical investigation and practical applications of $\\scriptstyle\\mathbf{M-N-C}$ catalysts. \n\n$\\mathrm{Fe-N-C}$ is the most active component among all M–N–C catalysts for ORR in acid. Fe–N–C catalysts may contain multiscale metal phases from single atoms (SAs), atomic clusters (ACs) to nanoparticles (NPs) depending on the metal contents and the synthesis methods33–35. Recent studies have shown that the electronic interactions between SA active sites and metal $\\mathrm{NPs}/$ ACs can enhance the activity of single-atom catalysts $(\\mathrm{SACs})^{36-42}$ . Most of these synergies are demonstrated in alkaline media because these metal $\\mathrm{NPs}/\\mathrm{ACs}$ are readily soluble in acids. It suggests that these metal $\\mathrm{NPs/ACs}$ are weakly anchored (or bonded) on the carbon support, which may result in a very limited regulation effect on the electronic configuration of the SA sites. Fe NPs can be present in acids when they are encapsulated by a few layers of graphitic carbon $(L>3)^{43,\\dot{4}4}$ . However, theoretical calculations reveal that the electron penetration becomes very faint if the layer number is more than three, due to the quick drop of electron potential with the distance $(U_{e}=-k e^{2}/r)^{\\bar{4}5}$ . It has been shown that if the ACs are chemically bound to the carbon support, they are acid resistant46. We therefore expect that acid-stable and closely adjacent Fe ACs and SAs should have much stronger electronic interactions than previously reported composite systems. It is also more worthy of expecting this strong interaction on the stability of Fe–N–C in acidic media and real PEMFC devices, which has not been explored either. Furthermore, it is still very challenging to predict the stability of $\\mathrm{Fe-N}_{x}$ active sites under PEMFC operating conditions by theoretical computational methods. Although attempts have been made by density functional theory (DFT) thermodynamic calculations, from the perspective of formation energy20,47 or demetalation energy19, these methods are oversimplified and cannot consider factors such as PEMFC temperature and voltage, which are known to have a large impact on catalyst stability48. Therefore, theoretical prediction methods for active site stability still need to be upgraded to incorporate practical operating conditions. \n\nHerein, we synthesized N-anchored Fe ACs and satellite $\\mathrm{Fe-N_{4}}$ sites on two-dimensional porous carbon $(\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-2\\mathrm{DNPC}})$ as an efficient and stable ORR catalyst in acidic media. The introduction of Fe clusters is based on the utilization of protonated N-doped carbon substrate that has a moderate coordination strength to metal during the heat treatment, thus achieving balanced dispersion of Fe SAs and clusters on substrate. It is experimentally and theoretically demonstrated that Fe cluster can boost the activity of satellite $\\dot{\\mathrm{Fe-N_{4}}}$ site by introducing an OH ligand that reduces the ORR energy barrier. Molecular dynamics (MD) simulations are used for the stability prediction of Fe– $\\mathbf{\\nabla}\\cdot\\mathrm{N}_{x}$ at varying operating temperatures. A pinning effect of iron clusters is revealed, which shortens the amplitude of $\\mathrm{Fe-N}$ bonds of satellite $\\mathrm{Fe-N_{4}}$ by incoherent vibrations of iron cluster and SAs. In this way, the demetalation of $\\mathrm{Fe-N_{4}}$ is reduced by $60\\%$ . In PEMFC, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ exhibited an ultrahigh mass activity and promising long-term stability and durability, superior to the traditional Fe–N–C single-atom catalyst. These results demonstrate that the strong coupling of single atom and cluster is an effective strategy to improve the intrinsic activity and stability of single-atom active sites. \n\n# Results \n\nCatalyst synthesis and morphology characterization. FeSA/ $\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ was synthesized via pyrolyzing a mixture of N-doped carbon quantum dots (CQD) and TPI (a ${\\mathrm{Fe}}(\\mathrm{II})$ -phenanthroline complex) using ice/silica dual templates. In brief, CQD was synthesized by acid-leaching half-carbonized zeolite imidazole frameworks (ZIF-8), which produced a protonated surface on CQD (Supplementary Figs. 1 and 2). Silica spheres with a diameter of ${\\sim}100\\mathrm{nm}$ were prepared by the Stöber method (Supplementary Fig. 3). The well-dispersed colloidal solution of CQD, $\\mathrm{SiO}_{2}$ spheres and TPI was freeze-dried to form a CQD/ $\\mathrm{TPI}@\\mathrm{SiO}_{2}$ composite foam. Zeta potentials of these precursors are different as shown in Supplementary Fig. 4. During the freezing, negatively charged $\\mathrm{SiO}_{2}$ spheres were squeezed into a twodimensional array at the interface of ice crystals, while positively charged CQD/TPI filled the voids of $\\mathrm{SiO}_{2}$ stacks, thereby forming a 2D inverse-opal porous structure. The freeze-dried foam was pyrolyzed to $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ after removing the silica. The pyrolysis temperature was optimized to $1000^{\\circ}\\mathrm{C}$ to achieve the best activity and stability (Supplementary Figs. 5–7). The high temperature is crucial for the formation of optimal active sites and highly graphitic carbon support49. The catalyst was refluxed in a hot acid to remove soluble metal phases. As such, the remaining iron species should be robust to withstand the acidic environment. \n\nThe scanning electron microscopy (SEM) images (Fig. 1a, b) of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ exhibit a micron-sized 2D nanosheet structure, constructed by 1–2 layers of open hollow spheres with an average diameter of $\\sim80\\mathrm{nm}$ . The transmission electron microscopy (TEM) image shows the interconnected ultrathin sphere walls without visible iron agglomerates (Fig. 1c). Atomicresolution high-angle annular dark-field scanning TEM (HAADF-STEM) was performed to investigate the distribution of iron species at the atomic scale. As shown in Fig. 1d and Supplementary Fig. 8, the coexistence of Fe SAs and single-layer clusters is observed on carbon support. The magnified image in Fig. 1e more clearly shows that several iron atoms (red circles) closely surround a cluster (cyan circle) with a distance ${<}0.5\\mathrm{nm}$ , indicating the successful construction of Fe ACs and satellite SAs. The short inter-site distance allows rapid transfer of electrons from the ACs to the SAs. Graphene fringes are not observed around the cluster, indicating that the acid resistance of Fe ACs is not due to the protection of the graphene encapsulation. The elemental mapping further demonstrates the uniform distribution of the hybrid sites on nitrogen-doped carbon support (Fig. 1f). From HAADF-STEM images, we estimate that the average diameter of Fe ACs is $0.7\\mathrm{nm}$ and the ratio of SA to AC is about 10:1 (Supplementary Fig. 9). We note that there is a fraction of SAs far away from the ACs, which should behave like regular single-atom active sites. \n\n![](images/2b55cddd0c3d993d7b50810c00adccb7ca5ff1668f531904718a0b794db662a5.jpg) \nFig. 1 Morphology characterization of $\\ F e_{S A}/F e_{A C}$ −2DNPC. a, b SEM images; c TEM image; d, e HAADF-STEM image with zoom-in image showing an iron cluster (cyan circle) and its satellite iron atoms (red circles); f HAADF-STEM image and corresponding element mappings. \n\nActive site structure analysis of $\\mathbf{Fe}_{\\mathbf{SA}}/\\mathbf{Fe}_{\\mathbf{AC}}-2\\mathbf{DNPC}$ . The X-ray photoelectron spectroscopy (XPS) N 1 s spectrum reveals the existence of pyridinic N $(\\sim398.4\\mathrm{eV})$ , Fe–N bonding $(\\sim399.3\\mathrm{eV})$ , graphitic N $({\\sim}401.0\\mathrm{eV})$ and oxidized $\\mathrm{~N~}$ $(\\sim403.1\\mathrm{eV})$ , demonstrating the presence of Fe–N moieties in $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ (Fig. 2a, b and Supplementary Fig. 10)50. Notably, the Fe $2p$ spectrum of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ shows the positively charged iron species without obvious zero-valent iron $({\\sim}706.7\\mathrm{eV})$ , indicating that Fe atoms in the clusters are possibly coordinated by the substrate $\\mathrm{{N/C}}$ atoms. The fine structure of the iron species was analyzed by X-ray absorption spectroscopy (XAS). Figure 2c shows the Fe K-edge X-ray absorption near-edge structure spectra of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ and reference samples. The absorption threshold position of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ is close to that of phthalocyanine (FePc) and far away from those of Fe foil and ${\\mathrm{Fe}}_{2}{\\mathrm{O}}_{3}{\\mathrm{;}}$ , implying that the chemical valence of iron is around $+2$ in $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}-2\\mathrm{DNPC}.$ , consistent with the XPS results. The Fourier-transformed extended X-ray absorption fine structure (EXAFS) spectrum of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ (Fig. 2d) shows a predominant peak at $1.5\\mathring\\mathrm{A}$ in $R$ space, close to the Fe–N peak of FePc. A small peak corresponding to Fe–Fe path at around $2.3\\mathring\\mathrm{A}$ is also observed. The FT-EXAFS spectrum was well fitted using backscattering paths of $\\mathrm{Fe-N/O}$ and Fe–Fe (Fig. 2d, Supplementary Table 1). The coordination numbers of Fe–N/O and Fe–Fe were about 5.17 and 0.72, respectively. EXAFS wavelet transforms (WT) plot, a powerful method to distinguish the backscattering atoms, exhibits an intensity maximum at ${\\sim}5\\mathring{\\mathrm{A}}^{-1}$ in $k$ space that was assigned to $\\mathrm{Fe-N/O}$ , and a second intensity maximum at ${\\sim}6.5\\mathring\\mathrm{A}^{-1}$ that could be ascribed to the Fe–Fe scattering (Fig. 2e). The negative shift of the $k$ value referring to the Fe–Fe bond of Fe foil $(\\sim8\\mathring{\\mathrm{A}}^{-1})$ may associate with the different coordination numbers between bulk Fe and Fe $\\mathrm{ACs}^{51,52}$ . Overall, the above characterizations prove that the Fe atoms exist as both mononuclear and multinuclear centers, and all are coordinated and stabilized by the support. \n\nBy varying the ratio of TPI in the precursor $5\\%$ $15\\%$ and $30\\%$ of the CQD mass), the existing form of iron could be gradually tuned from SAs, to SAs/ACs, and then to SAs/NPs. The iron species on $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ and $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC}$ are characterized by X-ray diffraction, HAADF-STEM and XAS in Supplementary Figs. 11–16. $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ shows atomic iron only, while $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC}$ has atomic iron and iron NPs encapsulated by graphitic layers. According to inductively coupled plasma optical emission spectrometry analysis, the overall iron contents are 0.59, 1.16, and $1.56\\mathrm{wt\\%}$ for $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ , $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC},$ and $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC},$ respectively. XPS analysis shows that iron was enriched on the catalyst surface (Supplementary Table 2). $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ has a high specific surface area of $99{\\dot{5}}\\mathrm{m}^{2}\\mathrm{g}^{-1}$ , and is micropore-dominant as evidenced by the Type-I $\\mathrm{N}_{2}$ sorption isotherms with a sharp uptake at the low relative pressure $(P/P_{0}<0.015)$ (Supplementary Fig. 17). Pore size distribution shows that micropores are mainly distributed at ${\\sim}0.75$ and ${\\sim}1.30\\mathrm{nm}$ , while mesopores are less pronounced. The high gas uptake at the high relative pressure $(P/P_{0}>0.9)$ is indicative of the presence of a large number of macropores. Therefore, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ possesses a pore structure composed of micropores and macropores, which serve as active site hosts and fast mass-transport channels, respectively. The other two catalysts have similar porosity and surface areas (Supplementary Fig. 17 and Supplementary Table 3). Therefore, the differences in the electrochemical performances, as discussed later, could be ascribed to the different forms of iron species on three Fe–N–C catalysts. \n\nHalf-cell tests and quantitative analysis of active sites. The ORR activity of synthesized catalysts was first evaluated by rotating ring disk electrode (RRDE) in $\\mathrm{O}_{2}$ -saturated $0.5\\mathrm{M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution. Among three Fe-based catalysts, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-2\\mathrm{DNPC}}$ shows the highest ORR activity in terms of half-wave potential $(E_{1/2})$ of $0.81\\mathrm{V}$ vs. reversible hydrogen electrode (RHE) and Tafel slope of $54.5\\mathrm{mV}$ dec−1 (Fig. 3a and Supplementary Fig. 18). In the potential window of $0.2\\mathrm{-}0.8\\:\\mathrm{V}$ , the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ yields are below $4\\%$ while the electron transfer numbers are above 3.9 for all catalysts (Fig. 3b), indicating four-electron ORR processes. To further understand the effect of the strong atom-cluster interaction on the intrinsic activity of $\\mathrm{Fe-N_{4}}$ site, the apparent activity of the catalyst was deconvoluted to SD and TOF by the in situ electrochemical method of nitrite adsorption and stripping, which is only sensitive to the ORR active site of $\\mathrm{Fe-N_{4}}$ rather than Fe AC and NP (Supplementary Figs. 19–21 and Supplementary Table 4)53. The results are summarized in Fig. 3c. Although with the highest activity, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ does not possess the highest SD among the three catalysts. Instead, a decrease in SD is observed with the emergence of Fe ACs and NPs, which consume considerable iron sources while contribute negligible activity33. The lower SD but higher apparent activity of $\\mathrm{Fe}_{\\mathrm{SA}}\\mathrm{\\bar{/}F e}_{\\mathrm{AC}}{-2\\mathrm{DNPC}}$ compared with $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ points to a nearly $60\\%$ TOF enhancement (2.82 vs. $1.79\\:s^{-1}.$ ) of the $\\mathrm{Fe-N_{4}}$ site due to the incorporation of Fe cluster. The presence of Fe NPs also promotes the TOF of $\\mathrm{Fe-N_{4}}$ but to a small extent, suggesting that Fe ACs serve as a more powerful promoter to the activity of $\\mathrm{Fe-N_{4}}$ compared with the encapsulated NPs. \n\n![](images/d6938bdff31ccc3478d8a784caa87625255a6bc4796e7d3363f97cd8bdbd8e9c.jpg) \nFig. 2 Active site structure analysis of $F e_{S A}/F e_{A C}$ −2DNPC. a, b High-resolution N 1 s (a) and Fe $2p$ (b) XPS spectra of $\\mathsf{F e}_{\\mathsf{S A}}-2\\mathsf{D}\\mathsf{N P C}$ , $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{A C}}-2\\mathsf{D N P C},$ $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{N P}}-2\\mathsf{D N P C}$ . c Normalized Fe K-edge XANES spectra of $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{A C}}-2\\mathsf{D N P C}$ and references of Fe foil, FePc and $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ . d, e $k^{3}$ -weighted Fourier transforms (d) and wavelet transforms (e) of the experimental EXAFS spectra of $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{A C}}-2\\mathsf{D N P C}$ and references of Fe foil, FePc and $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ . FT-EXAFS fitting curve of $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{A C}}-2\\mathsf{D N P C}$ is present in $({\\pmb d})$ . Source data are provided as a Source Data file. \n\nThe stability of the developed catalysts was also evaluated in the half-cell as shown in Fig. 3d–f. After 10,000 potential cycles between 0.6 and $1.0\\mathrm{V}$ in an $\\mathrm{O}_{2}$ -purged 0.5 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ at ambient temperature, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ exhibits the best stability with an $E_{1/2}$ loss of only $15\\mathrm{mV}$ , much smaller than those of $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ $(53\\mathrm{mV})$ and $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC}$ $(40\\mathrm{mV})$ . Stability tests were also performed by chronoamperometry at $0.75\\mathrm{V}$ for $20\\mathrm{h}$ (Supplementary Fig. 22). We observed a $79\\%$ current density retention for $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}.$ , outperforming $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ $(58\\%)$ and $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC}$ $(60\\ \\%)$ again. To evaluate the stability of the catalysts at a more practical temperature, we raised the temperature to $80^{\\circ}\\mathrm{C}$ . Notably, after 5000 potential cycles, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-2\\mathrm{DNPC}}$ still demonstrates extraordinarily high stability relative to the references, with a minimal $E_{1/2}$ loss of only $20\\mathrm{mV}$ (Supplementary Fig. 23). Chronoamperometry tests at \n\n$80^{\\circ}\\mathrm{C}$ and $0.75\\mathrm{V}$ for $20\\mathrm{h}$ also show that $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ has the best current density retention (Supplementary Fig. 24). All the above results demonstrate that the satellite $\\mathrm{Fe-N_{4}}$ sites around the Fe cluster have higher stability compared to the isolated $\\mathrm{Fe-N_{4}}$ sites. \n\nCarbon corrosion and $\\mathrm{Fe-N_{4}}$ demetalation have been identified as the two most likely degradation mechanisms of $\\mathrm{Fe-N-C}$ catalysts. Carbon corrosion is associated with the graphitization degree of carbon support. Figure $3\\mathrm{g}$ shows the Raman spectra of the catalysts, displaying two prominent peaks at ${\\sim}1320$ and $1588~\\mathrm{cm}^{-1}$ assigned to the D band (crystal defects) and G band (in-plane stretching of $\\mathsf{s p}^{2}\\mathrm{C})$ of carbon species, respectively. The approximately equal $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ ratios indicate a similar degree of graphitization of the three catalysts, which is controlled by the pyrolysis temperature regardless of the iron content (Supplementary Fig. 7a). Therefore, the difference in the stability of the three catalysts is independent of the graphitic degree of the carbon supports. In addition, the ORR selectivity of the catalysts after potential cycles remains almost unchanged (see inset in Fig. 3d–f), implying the insignificant oxidation of the carbon support25. It is thus speculated that the enhanced stability of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ is due to the strong electronic interaction between $\\mathrm{Fe-N_{4}}$ and Fe cluster, which lowers the tendency of the demetalation of $\\mathrm{Fe-N_{4}}$ sites. To prove this hypothesis, we quantified the demetalation of the catalysts after 5000 potential cycles. For $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}.$ , the amount of leached Fe was as high as $35.6\\%$ , whereas the Fe loss in $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ was greatly reduced to $15.5\\%$ (Fig. 3h and Supplementary Table 5). However, due to the complex composition of the catalysts with ACs or NPs, it is hard to identify the types of leached Fe species and whether they are responsible for the performance decline. Again, we monitored the changes in $\\mathrm{Fe-N_{4}}$ SD and TOF (Fig. 3i, Supplementary Figs. 25–27 and Supplementary Table 5). After the stability test, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ showed the highest retentions of the kinetic current density $(72.3\\%)$ and SD $(81.3\\%)$ , while the other two catalysts lost nearly half of their active sites. It can be deduced that the presence of Fe clusters reduced the demetalation of $\\mathrm{Fe-N_{4}}$ by about $60\\%$ compared to isolated $\\mathrm{Fe-N_{4}}$ . We note that TOF of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ decreased slightly from 2.60 to $2.39\\ s^{-1}$ , which can be explained by either the preferential loss of the more active sites at the carbon edge31 or the mild surface oxidation25,54. The HAADFSTEM image of the used $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ after 5000 potential cycles (Supplementary Fig. 28) shows the well-retained SA/AC hybrid sites, confirming its structural stability during the ORR process. Therefore, it can be said that the presence of Fe clusters hinders the demetalation of satellite $\\mathrm{Fe-N_{4}}$ . \n\n![](images/e4c821f12ae221f104650939c55f2776e8aec3fc518fc224575bc15b15571719.jpg) \nFig. 3 Half-cell tests and quantitative analysis of active sites. a ORR polarization curves and (b) ${\\sf H}_{2}{\\sf O}_{2}$ yields and electron transfer numbers of $\\mathsf{F e}_{\\mathsf{S A}}-2\\mathsf{D}\\mathsf{N P C}$ , $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{A C}}-2\\mathsf{D N P C}.$ , $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{N P}}-2\\mathsf{D N P C}$ and $\\mathsf{P t/C}$ in $\\mathsf{O}_{2}$ -saturated $0.5{\\ensuremath{\\mathsf{M}}}$ ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ (0.1 M ${\\mathsf{H C l O}}_{4}$ for $\\mathsf{P t/C})$ . c SD and TOF of Fe– ${\\cdot}\\mathsf{N}_{4}$ sites of the indicated Fe–N–C catalysts. Error bars correspond to the standard deviation of three-time measurements. d–f ORR polarization curves and $H_{2}O_{2}$ yields (inset) before and after 10,000 potential cycles (0.6–1.0 V vs. RHE) in $\\mathsf{O}_{2}$ -purged 0.5 M ${\\sf H}_{2}{\\sf S}{\\sf O}_{4}$ . $\\pmb{\\mathsf{g}}$ Raman spectra of the catalysts. h Results of metal leaching experiments. $\\Delta F e\\%$ , relative amount of demetalation; $v(\\Delta\\mathsf{F e})$ , demetalation rate. i The changes of kinetic current density $(j_{\\boldsymbol{\\mathsf{k}}})$ and SD after the CV cycling. Source data are provided as a Source Data file. \n\nPEMFC tests. From a practical point of view, it is important to evaluate the performance of Fe–N–C catalysts in $\\mathrm{H}_{2}.$ –air PEMFC. \n\nFigure $_{4a-c}$ show the initial polarization and power density plots and the corresponding performance after $100/1\\bar{5}0\\mathrm{h}$ of stability test. In good agreement with the half-cell results, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ exhibits the highest peak power density $(P_{\\mathrm{max}})$ of $0.34\\mathrm{W}\\mathrm{cm}^{-2}$ in 1.0 bar $\\mathrm{H}_{2}$ –air PEMFC, compared to $0.28\\mathrm{W}\\mathrm{cm}^{-2}$ of $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ and $0.26\\mathrm{W}\\mathrm{cm}^{-2}$ of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC}$ . In the $150\\mathrm{h}$ stability test at $0.5\\mathrm{V}$ , $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ showed a slight drop in performance during the first $32\\mathrm{h}.$ , which was associated with the unstable active sites located at the edge of the carbon support or isolated from iron clusters; then followed by a relatively stable performance of about $0.37\\mathrm{Acm}^{-2}$ until the end of the test. Its performance at the 150th hour is almost identical to that at the $100\\mathrm{{th}}$ hour. Such a degradation pattern means that the catalyst has long-term stability, as confirmed by the stabiltiy test of another fuel cell (Supplementary Fig. 29). This stability performance is very promising compared with reported $\\scriptstyle\\mathrm{M-N-C}$ catalysts (Supplementary Table 7). In contrast, $\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ and $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC}$ show fast and constant declines throughout the tests. Catalyst stability was also evaluated by square wave voltage cycling, where continuous surface oxidation and reduction cycles accelerate catalyst degradation and can simulate vehicle operation (Fig. 4d, protocol according to US DOE). $\\mathrm{Fe}_{\\mathrm{SA}}/$ \n\n![](images/af909731c0a724d0692cf3547bc53faa44f1628afc5c0828c3a8dfb93e2599c8.jpg) \nFig. 4 PEMFC tests. a–c Polarization and power density curves of the indicated catalysts (b, c) before and after the stability test at a constant voltage of $0.5\\mathsf{V}$ under 1 bar ${\\sf H}_{2}$ –air (a). d Polarization curves of $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{A C}}-2\\mathsf{D N P C}$ (under 1 bar ${\\mathsf{H}}_{2}{-}\\mathsf{O}_{2})$ through 30,000 square-wave cycles between 0.6 and $0.95\\vee$ under $H_{2}-N_{2}$ . e Polarization and power density curves of $\\mathsf{F e}_{\\mathsf{S A}}/\\mathsf{F e}_{\\mathsf{A C}}-2\\mathsf{D N P C}$ under 1 and 2 bar $H_{2}\\mathrm{-}\\mathsf{O}_{2}$ . Test conditions: cathode loading $1.5\\mathsf{m g}_{\\mathsf{F e-N-C}}\\mathsf{c m}^{-2}$ and, anode loading $0.2\\mathsf{m g}_{\\mathsf{P t}}\\mathsf{c m}^{-2},$ , Nafion 211 membrane, $5\\mathsf{c m}^{2}$ electrode, $80^{\\circ}\\mathsf C,$ $100\\%$ relative humidity (RH), flow rates of $300/600\\mathsf{m l}\\mathsf{m i n}^{-1}$ for ${\\sf H}_{2}$ –air polarization, $100/100\\mathsf{m l}\\mathsf{m i n}^{-1}$ for ${\\sf H}_{2}$ –air stability test, and $300/400\\mathsf{m l}\\mathsf{m i n}^{-1}$ for ${\\sf H}_{2}\\mathrm{-}{\\sf O}_{2}$ polarization. f Comparison of mass activity of the highperforming $\\mathsf{P t}$ -group-metal free catalysts in PEMFC under 1 bar $H_{2}\\mathrm{-}\\mathsf{O}_{2}$ . The references to the data points are supplied in Supplementary Table 8. Source data are provided as a Source Data file. \n\nFeAC−2DNPC showed $7.4\\%$ current loss at $0.6\\mathrm{V}$ after 10,000 cycles and $17.2\\%$ after 30,000 cycles, outperforming previous reports of non-precious metal catalysts55. \n\nTo gain better insight into the intrinsic activity of $\\mathrm{Fe}_{\\mathrm{SA}}/$ FeAC−2DNPC, we performed fuel cell tests under 1.0 and 2.0 bar $\\mathrm{H}_{2}\\mathrm{-}\\mathrm{O}_{2}$ (Fig. 4e). $P_{\\mathrm{max}}$ reached 0.80 and $0.94\\mathrm{W}\\mathrm{cm}^{-2}$ , respectively. The current density at $0.9\\mathrm{~V}_{i R-\\mathrm{free}}$ (where $i R$ -free indicates that the internal resistance is compensated for) is $15\\mathrm{mAcm}^{-2}$ under 1.0 bar $\\mathrm{H}_{2}\\mathrm{-}\\mathrm{O}_{2}$ (see Tafel plot in Supplementary Fig. 30). This value translates to a mass activity of $\\mathrm{\\bar{10}m A~m g_{\\mathrm{cat.}}}^{-1}$ at 0.9 $\\mathrm{V}_{i R-\\mathrm{free}},$ outperforming most of the reported platinum-groupmetal free catalysts (Fig. 4f and Supplementary Table 8). We note that the performance difference between 1 bar and 2 bar pressure is small even in the high current region. This phenomenon shows a small concentration effect due to the rapid mass transport in the interconnected porous structure of the catalyst32,56. We prepared a control structure of 2D flat-film (Supplementary Fig. $_{3\\mathrm{la-c}})$ , using the same process as $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ but without the $\\mathrm{SiO}_{2}$ spheres. In RRDE test, the catalyst shows a considerable $E_{1/2}$ of $0.78\\mathrm{V}$ but a small limiting current density of $4\\mathrm{mA}\\mathrm{cm}^{-2}$ (Supplementary Fig. 31d), indicating the difficult mass transport in the stacked 2D films. In fuel cell tests, this flat catalyst could hardly deliver a considerable current density (Supplementary Fig. 31e). This comparison clearly demonstrates the efficient mass transport capability of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ . \n\nTheoretical analysis of the activity and stability of the hybrid active site. To understand the role of Fe cluster in promoting the activity of satellite $\\mathrm{Fe-N_{4}}.$ , DFT calculations were performed. As shown in Fig. 5a, a model of $\\mathrm{Fe}_{4}\\mathrm{-N}_{6}$ with a closely adjacent $\\mathrm{Fe-N_{4}}$ site is built on graphene to mimic the hybrid active site of $\\mathrm{Fe}_{\\mathrm{SA}}/$ FeAC−2DNPC. The distance of $4.97\\mathring{\\mathrm{A}}$ between Fe SA and AC is consistent with the observation of HAADF-STEM. An isolated $\\mathrm{Fe-N_{4}}$ is also constructed for comparison (Supplementary Fig. 32). We assumed a $4e^{-}$ associative ORR pathway that proceeds through ${{\\mathrm{O}}_{2}}^{*}$ , $\\mathrm{\\Gamma_{OOH}*}$ , ${{\\cal O}^{*}}$ , and $\\mathrm{\\Gamma{OH^{*}}}$ (\\* denotes the adsorption site, Fig. 5b). The calculated energy diagrams at $1.23\\mathrm{V}$ are presented in Fig. 5c. Consistent with our previous DFT calculations47, the rate limiting step of ORR on $\\mathrm{Fe-N_{4}}$ is the formation of ${\\mathrm{OH}}^{*}$ $(\\mathrm{O^{*}+H^{+}}+e^{-}=\\mathrm{OH^{*}})$ with an energy barrier of $0.53\\mathrm{eV}$ . When the iron cluster is introduced, Fe– ${\\bf\\cdot N_{4}}/$ $\\mathrm{Fe}_{4}\\mathrm{-N}_{6}$ shows strong adsorption to $\\mathrm{OH}$ to the extent that a permanent OH ligand is grafted on $\\mathrm{Fe}{-}\\mathrm{N}_{4}{}^{32}$ . This OH ligand optimizes the binding strength of the other side of the $\\mathrm{Fe-N_{4}}$ site to the ORR intermediates, greatly reducing the limiting energy barrier to $0.35\\mathrm{eV}$ . The $\\mathrm{Fe}_{4}$ in $\\mathrm{Fe{-N_{4}{-O H}/F e_{4}{-N_{6}}}}$ is predicted with inferior activity (Supplementary Figs. 33 and 34), indicating the cluster mainly acts as an activity booster. Two variants of the cluster are further investigated using models of $\\mathrm{Fe}_{13}\\mathrm{-N}_{6}$ and $\\mathrm{Fe}_{4}–\\mathrm{C}_{6}$ . The calculations show that the N-coordinated iron cluster has a more significant boosting effect on the adjacent $\\mathrm{Fe-N_{4}}$ sites than the C-coordinated iron cluster, while the number of Fe atoms in the cluster plays a less significant role (Supplementary Figs. 35 and 36). \n\nNext, the stability of active sites was investigated by MD simulations from the perspective of the bond-length fluctuation, because the demetalation starts from the elongation and break of the Fe–N bond57. The radial distribution function (RDF) of $\\mathrm{Fe-N}$ bond, $g_{\\mathrm{Fe-N}}(r)$ , offers a direct measure of the frequency of appearance of $_\\mathrm{N}$ atom at a distance $r$ from the central Fe atom, thus can represent the distribution of Fe–N bond-length (Fig. 5d). If an Fe–N bond is long and widely distributed, it means that it is prone to fracture. At room temperature, $g_{\\mathrm{Fe-N}}(r)$ of $\\mathrm{Fe-N_{4}}$ shows three peaks in the range of $\\mathrm{\\bar{1}}.82\\mathrm{-}2.38\\mathrm{\\bar{A}}$ due to the thermal vibration of Fe–N bond. After the addition of the Fe cluster, the length distribution of $\\mathrm{Fe-N}$ bonds narrows to $1.82{-}2.22\\mathring\\mathrm{A}$ , indicating that the Fe–N bonds are more stable. In other words, the Fe– ${\\bf\\cdot N_{4}}$ site in $\\mathrm{Fe{-N_{4}/F e_{4}{-N_{6}}}}$ is more stable than an isolated $\\mathrm{Fe-N_{4}}$ site. At the PEMFC operating temperature of $80^{\\circ}\\mathrm{C},$ the Fe–N bond-length distribution increases to $1.71{-}2.50\\mathrm{\\AA}$ in the isolated $\\mathrm{Fe-N_{4}}.$ , while it still maintains a narrow distribution of $1.86{-}2.06\\mathring\\mathrm{A}$ in the $\\mathrm{Fe-N_{4}}$ of $\\mathrm{Fe{-}N_{4}/F e_{4}{-}N_{6}}$ . This explains why the degradation of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ was not substantially accelerated at the elevated temperature. The thermal vibrations of Fe–N bond of the $\\mathrm{Fe-N_{4}}$ and the $\\mathrm{Fe{-}N_{4}/F e_{4}{-}N_{6}}$ can be visualized in Supplementary Movies 1–4. Snapshots obtained from MD simulations at $80^{\\circ}\\mathrm{C}$ are shown in Fig. 5e for a quick comparison. Previous research has predicted that the vibration frequency of metal clusters increases with decreasing size down to diatomic molecules58. It is reasonable to assume that the incoherent vibration of Fe clusters and Fe SAs are responsible for the reduced amplitude of Fe–N bonds. Therefore, the iron clusters produce a pinning effect that suppresses the thermal vibrations of the satellite $\\mathrm{Fe-N_{4}}$ sites, thus reducing their tendency for demetalation. \n\n![](images/b0eb276f5b4ea99b28f2433e214a3ffe5120a360bc8156bb3afc2fb79a557f89.jpg) \nFig. 5 Theoretical analysis of the activity and stability of the hybrid active site. a Model structure of F $\\underline{{\\mathsf{\\Pi}}}-\\mathsf{N}_{4}/\\mathsf{F e}_{4}-\\mathsf{N}_{6}$ used for theoretical calculation with a spontaneously formed OH ligand. b Schematic ORR process on the Fe– ${\\cdot}\\mathsf{N}_{4}$ site of $\\mathsf{F e}{-}\\mathsf{N}_{4}{-}\\mathsf{O H}/\\mathsf{F e}_{4}{-}\\mathsf{N}_{6}$ . c Free energy diagrams at $\\boldsymbol{\\mathrm{1.23V}}$ for ORR over three types of active sites of Fe– ${\\cdot}\\mathsf{N}_{4},$ Fe $-N_{4}/F e_{4}-N_{6}$ and $F e-N_{4}{\\cdot}O H/F e_{4}{-}N_{6}$ . d Fe–N radical distribution function profiles of the Fe– ${\\cdot}\\mathsf{N}_{4}$ moiety in the models of bare $F e\\mathrm{-}N_{4}$ and $\\mathsf{F e{-N_{4}/F e_{4}{-}N_{6}}}$ at 25 and $80^{\\circ}\\mathsf{C}$ . Wavy arrows are used to indicate the amplitude of Fe–N bond-length fluctuation. e Snapshots of Fe– ${\\cdot}\\mathsf{N}_{4}$ and $\\mathsf{F e{-N_{4}/F e_{4}{-}N_{6}}}$ obtained from MD simulations at $80^{\\circ}\\mathsf{C}$ . The initial configuration (left) and an intermediate state (right) are provided to show the elongation of the Fe–N bond as marked by the yellow box. Source data are provided as a Source Data file. \n\n# Discussion \n\nIn summary, a type of Fe–N–C catalyst has been synthesized with Fe cluster and satellite $\\mathrm{Fe-N_{4}}$ coupling active sites on carbon support. Despite complete exposure, the N-anchored Fe clusters are acid-stable. The iron cluster introduces an OH ligand on the satellite ${\\mathrm{Fe-N}}_{4},$ thus lowering the ORR energy barrier and increasing the intrinsic activity of the $\\mathrm{Fe-N_{4}}$ site by $60\\%$ . Moreover, the method of MD simulation was introduced to observe the vibration and amplitude of the chemical bonds of $\\mathrm{Fe-N_{4}}$ active site at varying working temperatures of PEMFC, and revealed the stability-enhancing mechanism of the $\\mathrm{Fe_{SA}/F e_{A C}}$ active site, namely the pinning effect. The incoherent vibrations of Fe clusters and Fe SAs suppress the amplitude of $\\mathrm{Fe-N}$ bonds, resulting in a $60\\%$ reduction in the demetalation of $\\mathrm{Fe-N_{4}}$ sites as well. In the PEMFC device, $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ achieves an ultrahigh mass activity of $10\\mathrm{mA}\\mathrm{mg_{cat.}}^{-1}$ at $0.9\\mathrm{V}_{i R-\\mathrm{free}}$ under 1 bar $\\mathrm{H}_{2}{-}\\bar{\\mathrm{O}}_{2}$ and significantly enhanced stability compared with the singleatom catalyst $({\\mathrm{Fe}}_{\\mathrm{SA}}{-}2\\mathrm{DNPC})$ and nanoparticle/single-atom catalyst $(\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-2\\mathrm{DNPC}})$ . The synthetic method, active site structure, and performance-enhancing mechanisms can be extended to other single-atom catalyst systems. \n\n# Methods \n\nChemicals. Zinc nitrate hexahydrate $(\\mathrm{Zn}(\\mathrm{NO}_{3})_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ , $99.99\\%$ ), 2-methylimidazole $(98\\%)$ and nitric acid $\\mathrm{(HNO_{3}}$ $65\\mathrm{-}68\\%$ ) were purchased from Aladdin. Perchloric acid $\\mathrm{(HClO_{4})}$ $70\\mathrm{-}72\\%$ ), sulfuric acid $\\mathrm{(H}_{2}\\mathrm{SO}_{4},$ A.R.), hydrochloric acid (HCl, $36{-}38\\%$ ), acetic acid ( $\\mathrm{CH_{3}C O O H}$ , $99.5\\%$ , methanol $\\mathrm{\\backslashCH_{3}O H}$ , A.R.), ethanol $\\mathrm{(C_{2}H_{5}O H}$ A.R.), sodium nitrite $(\\mathrm{NaNO}_{2},$ A.R.) and sodium acetate anhydrous $\\mathrm{'CH_{3}C O O N a}$ , A.R.) were purchased from Beijing Chemical Works. Tetraethyl orthosilicate (TEOS, $\\mathrm{C_{8}H_{20}O_{4}S i},$ $99\\%$ ) was obtained from Innochem. Ferrous acetate $\\mathrm{(Fe(C_{2}H_{3}O_{2})_{2}}$ , $95\\%$ ) was purchased from J&K Chemicals. \n\n1,10-phenanthroline and sodium hydroxide (NaOH, $95\\%$ ) were obtained from Macklin. Commercial $\\mathrm{Pt}/\\mathrm{C}\\left(40\\mathrm{wt\\%}\\right)$ was obtained from BASF. Nafion alcohol (5 wt $\\%$ , D520) was obtained from Aldrich. Nafion 211 membrane was obtained from DuPont. All chemicals were used without further purification. All aqueous solutions were prepared using deionized (DI) water with a resistivity of $18.2\\mathrm{M}\\Omega$ . \n\nSynthesis of CQD. First, ZIF-8 NPs were prepared by quickly pouring a $200\\mathrm{ml}$ methanol solution containing $5.88\\mathrm{g}\\mathrm{Zn(NO_{3})_{2}{\\cdot}6H_{2}O}$ into another $200\\mathrm{ml}$ methanol solution of 2-methylimidazole $(6.48\\:\\mathrm{g})$ while stirring. The mixture was stirred for $^{5\\mathrm{h}}$ . The white precipitates were centrifuged, washed with methanol three times and dried in a vacuum at $60^{\\circ}\\mathrm{C}$ . The obtained ZIF-8 powder was grinded and then underwent a heat treatment at $535^{\\circ}\\mathrm{C}$ for $^{8\\mathrm{h}}$ under argon atmosphere in a tube furnace. The obtained brown powder was dispersed in $20~\\mathrm{ml}$ DI water and then etched to CQD by adding $5\\mathrm{ml}$ concentrated hydrochloric acid $(36-38\\%)$ ) under ultrasonic vibration. Then the suspension was purified by membrane dialysis (molecular weight cut off $8000{-}14,000\\mathrm{Da}$ ) against ultrapure water for 2 days to obtain the CQD colloidal solution59. The concentration of the CQD colloidal solution was determined by a dry weighing method. A $100\\mathrm{-}\\upmu\\mathrm{l}$ aliquot of CQD colloidal solution was pipetted onto microscope slides and dried on a hot plate, and then the remaining solid was weighed. The yield of CQD was about $25\\mathrm{wt\\%}$ from the raw ZIF-8 precursor. \n\nSynthesis of $\\mathsf{s i o}_{2}$ spheres. Silica spheres were prepared by the Stöber method60. Typically, $100\\mathrm{ml}$ ethanol, 6 ml DI water, $6\\mathrm{ml}$ ammonium hydroxide and $3\\mathrm{ml}$ TEOS were mixed and stirred for $^{5\\mathrm{h}}$ . Then the resulting suspension was centrifuged, washed with ethanol and water, and dried in a vacuum at $60^{\\circ}\\mathrm{C}$ to obtain $\\mathrm{SiO}_{2}$ spheres with a diameter of about $100\\mathrm{nm}$ . \n\nSynthesis of the catalysts. In a typical procedure, a colloidal solution of CQD $(3\\mathrm{mg}\\mathrm{ml^{-1}},$ , $\\mathrm{SiO}_{2}$ sphere $(9\\mathrm{mg}\\mathrm{ml}^{-1}.$ ) and TPI $(0.45\\mathrm{mg}\\mathrm{ml}^{-1}$ , prepared by dissolving ferrous acetate and 1,10-phenanthroline with the molar ratio of 1:3 in water) was prepared and freeze-dried to form a $\\mathrm{CQD/TPI@SiO_{2}}$ foam. The foam was firstly pyrolyzed at $800^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ under argon atmosphere in a tube furnace. The carbonized foam was ground for $20\\mathrm{min}$ to fine powders in a mortar and then dispersed in $\\mathrm{\\DeltaNaOH}$ solution $(3\\mathrm{moll^{-1}})$ at $50^{\\circ}\\mathrm{C}$ for $10\\mathrm{{h}}$ to etch the silica spheres. The dispersion was separated by filtration and washed thoroughly and dried in a vacuum at $60^{\\circ}\\mathrm{C}$ . The obtained black powder was subjected to a second pyrolysis in the tube furnace at $1000^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ under argon atmosphere. The product was subsequently refluxed in $0.5\\mathrm{M}$ ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ solution at $80~^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ to remove any possible unstable metal species. The final catalyst $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ was collected by filtration and washed thoroughly and dried in vacuum at $60^{\\circ}\\mathrm{C}$ . The yield of the catalyst was about $20\\mathrm{wt\\%}$ based on CQD. \n\n$\\mathrm{Fe}_{\\mathrm{SA}}{-}2\\mathrm{DNPC}$ and $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{NP}}{-}2\\mathrm{DNPC}$ were prepared by the same procedure but changing the concentration of TPI to 0.15 and $\\mathrm{\\bar{0.9}m g\\dot{m l^{-1}}}$ , respectively. As another control sample, 2D-Fe-N-C was prepared without the use of the silica sphere template and the silica etching process, while other synthesis steps were identical to the synthesis of $\\mathrm{Fe}_{\\mathrm{SA}}/\\mathrm{Fe}_{\\mathrm{AC}}{-}2\\mathrm{DNPC}$ . \n\nCharacterizations. The SEM was performed with JEOL JSM-7500. The TEM was performed with JEOL JEM-2100F with an electron acceleration energy of $200\\mathrm{kV}$ . The images of single iron atoms and elemental mapping were obtained by a HAADF-STEM (JEOL JEM-ARM200F) operated at $200\\mathrm{kV}$ . XRD patterns were recorded on Rigaku $\\mathrm{D/max}2500$ with Cu Kα irradiation. XPS measurements were performed on Thermo ESCALAB 250Xi using Al Kα irradiation. XPS data analysis comprised a Shirley background subtraction and a least-square fitting procedure of the spectra using XPSPEAK software. Raman spectra were recorded on Renishaw inVia Raman microscope $(\\lambda=514\\mathrm{{nm}}$ ). $\\Nu_{2}$ sorption isotherms were measured by the SSA-7000 system (Beijing Builder) at $77.3\\mathrm{K}$ and the porosity parameters were analyzed using the software QuadraWin (version 6.0). The specific surface area was obtained using the Brunauer–Emmett–Teller (BET) method. The pore size distribution was determined using quenched solid DFT model for slit shaped and cylindrical pores61. The external surface area is defined as non-micropore area, which was obtained by subtracting the micropore surface area (calculated through t-plot method) from the BET surface area. The iron concentration measurements were conducted on the Optima-7000DV ICP-OES. A certain amount of catalyst was placed in an alundum boat and burned to iron oxide in a muffle furnace at $800^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ . The obtained iron oxide was dissolved by aqua regia heated in an oil bath at $80~^{\\circ}\\mathrm{C}$ until it was clear, and then diluted to the ppm range for the ICP-OES measurements. The zeta potentials of the samples were determined using a Zetasizer Nano ZS90. The samples were dispersed by sonication in water with a concentration of $10\\mathrm{mgl}^{-1}$ and the dispersion was used for measurements without the $\\mathrm{\\tt{pH}}$ adjustment. XAS was performed at room temperature on the 1W1B beamline at BSRF (Beijing Synchrotron Radiation Facility). The catalysts $\\left(\\sim15\\:\\mathrm{mg}\\right)$ were pelletized as disks of $8\\mathrm{mm}$ diameter using paraffin as a binder, while the iron phthalocyanine was mixed with BN powder with a ratio of 1:6. Fluorescence-mode Fe K-edge X-ray absorption spectra were collected for all samples over a range of $6915-7891{\\mathrm{~eV}}$ , where a $100\\%$ Ar filled Lytle ion-chamber detector with Mn X-ray filters and soller slits were used. The monochromator energy was calibrated using a Fe foil. The XAFS data were analyzed using IFEFFIT62. The XAFS raw data were background subtracted, normalized and Fourier transformed by standard procedures within the ATHENA program63. Least-squares curve fitting analysis of the EXAFS $\\chi(\\boldsymbol{k})$ data was carried out using the ARTEMIS program63. All fits were performed in the $R$ space with $k$ -weight of 3. The amplitude reduction factor $(S_{0}{}^{2})$ was determined from the Fe foil and held constant for the analysis of the samples. The EXAFS $R$ -factor, which indicates the percentage misfit of the theory to the data, was used to evaluate the goodness of the fitting. \n\nRRDE tests. The ORR activity was measured in acid medium on a glassy carbon RRDE $\\cdot5.61\\mathrm{mm}$ of disk outer diameter, Pine Research Instrumentation, USA) with an electrochemical workstation (CHI 760E, CH Instruments). The reference electrode was a calibrated saturated calomel electrode and the counter electrode was a graphite rod. All the potentials reported in this work were calibrated to the RHE and not $i R$ -compensated. Catalyst inks were prepared by dispersing $1\\mathrm{mg}$ of catalyst in $200\\upmu\\mathrm{l}$ Nafion solution $(1\\mathrm{mg}\\mathrm{ml}^{-1},\\$ ), which was prepared by mixing $215{\\upmu\\mathrm{l}}$ Nafion alcohol $5\\mathrm{wt\\%}$ , Aldrich), $4.3\\mathrm{ml}$ DI water and $5.485\\mathrm{ml}$ isopropanol, with $30\\mathrm{min}$ sonication to get a uniform suspension. Before the test, the glassy carbon electrode was polished and rinsed with DI water. Two aliquots of $10\\upmu\\mathrm{l}$ of the catalyst ink were successively pipetted onto the glassy carbon and dried in air, resulting in a catalyst loading of around $400\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ . A $\\mathrm{Pt/C}$ ( $40\\mathrm{wt\\%}$ of Pt, BASF) catalyst with a loading of $80\\upmu\\mathrm{g}_{\\mathrm{Pt}}\\mathrm{cm}^{-2}$ was used as a reference (only one aliquot of $10\\upmu\\mathrm{l}$ of the catalyst ink was deposited on the glassy carbon). \n\nORR activity was recorded at room temperature $({\\sim}25^{\\circ}\\mathrm{C})$ at a rotation rate of $1600\\mathrm{rpm}$ . The electrolyte was $0.5\\mathrm{M}\\mathrm{H}_{2}\\mathrm{SO}_{4}$ for Fe–N–C catalysts, and $0.1\\mathrm{M}$ $\\mathrm{{HClO}_{4}}$ for $\\mathrm{Pt/C}$ . The electrolyte was purged by any specific gas for at least $30\\mathrm{min}$ before the tests and the gas flow was maintained during the experiments. The electrolyte was purged with $\\mathrm{O}_{2}$ first, followed by linear sweep voltammetry (LSV) at a scan rate of $\\bar{10}\\mathrm{mVs^{-1}}$ for ORR activity tests. Afterward, the LSV curve at the same scan rate was collected to obtain capacitive background in the Ar-saturated electrolyte. The oxygen reduction currents were obtained by subtracting the background currents from the original LSV measured in the $\\mathrm{O}_{2}$ -saturated electrolyte. The peroxide yields $(\\mathrm{H}_{2}\\mathrm{O}_{2}\\%)$ were calculated from the ring current $\\left(I_{\\mathrm{r}}\\right)$ and the disk current $(I_{\\mathrm{d}})$ using the equation [Eqs. 1 and 2]: \n\n$$\n\\mathrm{H}_{2}O_{2}\\%=200\\times I_{\\mathrm{r}}/\\left(I_{\\mathrm{r}}+N I_{\\mathrm{d}}\\right)\n$$ \n\nThe electron transfer number $(n)$ in acid was calculated by the equation: \n\n$$\nn=4I_{\\mathrm{d}}/\\left(I_{\\mathrm{d}}+I_{\\mathrm{r}}/N\\right)\n$$ \n\nwhere $N=0.37$ is the current collection efficiency of the Pt ring (ring potential $=1.27\\:\\mathrm{V}$ vs. RHE). \n\nThe accelerated stability tests (AST) were performed by potential cycling from 0.6 to $1.0\\mathrm{V}$ vs. RHE in $\\mathrm{O}_{2}$ -purged 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at a scan rate of $50\\mathrm{mVs^{-1}}$ and a rotation rate of $300\\mathrm{rpm}$ . Chronoamperometry tests at $0.75\\mathrm{V}$ vs. RHE at a rotation rate of $300\\mathrm{rpm}$ were also performed to study the catalyst stability. \n\nQuantification of the active sites. The active SD and TOF were obtained according to the method presented by Kucernak et $\\mathrm{al}^{53}$ . Briefly, the catalyst inks were prepared by dispersing $1\\mathrm{mg}$ of catalyst in $200\\upmu\\mathrm{l}$ Nafion solution $(1\\mathrm{mig}\\mathrm{ml^{-1}})$ . An aliquot of $6\\upmu\\upmu$ of the catalyst ink was deposited on the glassy carbon (rotating disk electrode, diameter of $5\\mathrm{mm}$ ), resulting in a catalyst loading of around $150\\upmu\\mathrm{gcm}^{-2}$ . Then extensive cycling in $\\mathrm{pH}~5.2$ acetate buffer alternatively in $\\mathrm{O}_{2}$ and $\\Nu_{2}$ was performed to obtain non-changing CV curves in $\\Nu_{2}$ . Then the catalyst was poisoned by $\\mathrm{NaNO}_{2}$ . ORR performance was recorded before, during and after the nitrite absorption. Nitrite stripping was conducted in the region of 0.35 to $-0.35\\mathrm{V}$ vs. RHE. The excess in cathodic charge $(Q_{\\mathrm{strip}})$ was proportional to the active SD, and the TOF was calculated by dividing the difference of kinetic current before and after nitrite absorption by SD [Eqs. 3 and 4]: \n\n$$\n\\operatorname{SD}\\bigl(\\mathrm{mol}\\ \\mathbf{g}^{-1}\\bigr)=\\frac{Q_{\\mathrm{strip}}\\bigl(\\mathbf{C}\\ \\mathbf{g}^{-1}\\bigr)}{n_{\\mathrm{strip}}F\\bigl(\\mathbf{C}\\ \\mathrm{mol}^{-1}\\bigr)}\n$$ \n\n$$\n\\mathrm{TOF}\\bigl(s^{-1}\\bigr)=\\frac{n_{\\mathrm{strip}}\\triangle j_{\\mathrm{k}}\\bigl(\\mathrm{mA~cm}^{-2}\\bigr)}{Q_{\\mathrm{strip}}\\bigl(\\mathrm{C~g}^{-1}\\bigr)L_{\\mathrm{C}}\\bigl(\\mathrm{mg~cm}^{-2}\\bigr)}\n$$ \n\nwhere $n_{\\mathrm{strip}}\\left(=5\\right)$ is the number of electrons associated with the reduction of one nitrite per site, $\\begin{array}{r}{j_{\\mathrm{k}}=\\frac{j_{\\mathrm{lim}}\\times j}{j_{\\mathrm{lim}}-j}}\\end{array}$ is the kinetic current density, $L_{\\mathrm{C}}$ is the catalyst loading $(0.15\\mathrm{mg}\\mathrm{cm}^{-2}.$ . \n\nFor the comparison of SD and TOF before and after stability test, the AST was performed in $0.5{\\mathrm{M}}{}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ while SD was determined in $\\mathrm{pH}5.2$ acetate buffer. We note that nitrite ions may be reduced by the trace amount of metallic iron (if any) in the catalysts64. However, the major products are ammonium and nitrogen gas, which should not interfere with adsorption and subsequent stripping of nitrite on the active $\\mathrm{Fe-N}_{x}$ sites. \n\nDemetalation experiments. $2\\mathrm{mg}$ of catalyst was mixed with $12\\upmu\\mathrm{l}$ Nafion alcohol solution $(5\\mathrm{wt\\%}$ , Aldrich), ${38\\upmu1\\mathrm{H}_{2}O}$ and $50\\upmu\\mathrm{l}$ isopropanol and sonicated for $30\\mathrm{min}$ . 5 aliquots of $10\\upmu\\mathrm{l}$ of the catalyst ink were successively deposited on the glassy carbon of rotating disk electrode (diameter of $5\\mathrm{mm}$ ), achieving a total catalyst loading of $1\\mathrm{mg}$ . The electrode was subjected to 5000 potential cycling from \n\n0.6 to $1.0\\mathrm{V}$ vs. RHE in $\\mathrm{O}_{2}$ -purged 0.5 M $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ at a scan rate of $50\\mathrm{mVs^{-1}}$ and a rotation rate of $300\\mathrm{rpm}$ at $25^{\\circ}\\mathrm{C}$ . The post-testing catalyst was carefully transferred to an alundum boat with no remaining with the assistance of isopropanol. The alundum boat with the collected post-testing catalyst was heated in a muffle furnace at $800^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ to convert the catalyst to iron oxide. The obtained iron oxide was dissolved in aqua regia at $80^{\\circ}\\mathrm{C}$ and diluted to the ppm range for the ICP-OES measurements. \n\nPEMFC tests. The Fe–N–C catalyst $({\\sim}9\\mathrm{mg})$ was mixed with Nafion alcohol solution $5\\mathrm{wt\\%}$ , Aldrich), DI water $(200\\mathrm{mg})$ and isopropanol $\\left(400\\mathrm{mg}\\right)$ to prepare the catalyst ink. The Nafion-to-catalyst ratio (NCR) was 1.5. The ink was subjected to sonication for $10\\mathrm{min}$ and stirring for $10\\mathrm{{h}}$ to make a uniform suspension. The well-dispersed ink was brushed on a piece of carbon paper ( $5\\mathrm{cm}^{2}$ , GDS2240, Ballard), followed by drying in vacuum at $80^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . As for anode, $\\mathrm{Pt/C}$ ( $40\\mathrm{wt\\%}$ of Pt, BASF) was used with a loading of ${\\sim}0.2\\ \\mathrm{mg}_{\\mathrm{Pt}}c\\mathrm{m}^{-2}$ . The prepared cathode and anode were pressed onto the two sides of a Nafion 211 membrane (DuPont) at $130^{\\circ}\\mathrm{C}$ for $90\\mathrm{{s}}$ under a pressure of $1.5\\mathrm{MPa}$ to obtain the MEA. The performance of MEA was measured by a fuel cell test station (Scribner 850e) with UHP-grade $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ or air at $80^{\\circ}\\mathrm{C}.$ , $100\\%\\mathrm{RH}$ . The flow rates were $0.31\\mathrm{min}^{-1}$ for $\\mathrm{H}_{2}$ $0.41\\mathrm{min}^{-1}$ for $\\mathrm{O}_{2}$ and $0.51\\mathrm{min}^{-1}$ for air. The pressure conditions for each fuel cell data were specified in the figure captions. For example, 1 bar $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ means that the absolute pressure for $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ is both 1 bar, which is achieved by applying 0.5 bar backpressure. Polarization curves were recorded by scanning the current density with an increment of $20\\mathrm{mA}\\mathrm{cm}^{-2}$ and the system is allowed to equilibrate by $3s$ at each current step before a data point is recorded. The $i R$ -compensated cell voltage was used for the Tafel pot in Supplementary Fig. 30. The cell internal resistance was provided by the test station. When performing stability test at the constant voltage mode, the flow rate was switched to $\\mathrm{0.11\\mathrm{min}^{-1}}$ for any gas. Fuel cell durability was assessed followed the US Department of Energy (DOE) protocols simulating automotive drive cycles using a voltage square wave (steps between $0.6\\mathrm{V}$ $(3\\thinspace\\mathrm{s})$ and $0.95\\mathrm{V}$ (3 s) with rise time of ${\\sim}0.5\\:s,\\$ , in which successive cycles of surface oxidation and reduction will accelerate the catalyst degradation. During the voltage cycles, the cathode and anode were purged with $100\\%\\mathrm{RH}$ $\\mathrm{H}_{2}$ and $\\Nu_{2}$ at $80^{\\circ}\\mathrm{C},$ respectively. The flow rates were $0.2\\dot{1}\\mathrm{min}^{-1}$ for $\\mathrm{H}_{2}$ and $0.0751\\mathrm{min}^{-1}$ for $\\Nu_{2}$ . Polarization curves were recorded under 1 bar $\\mathrm{H}_{2}{-}\\mathrm{O}_{2}$ before the durability test and after 0, 1k, 5k, 10k, and 30k cycles. Each test was repeated several times to obtain a relatively stable polarization curve for performance comparison. \n\nComputational methods. DFT calculations were performed using Vienna Ab Initio Simulation Package. The interactions between valence electrons and ion cores were modeled by projector augmented wave based potentials. The generalized gradient approximation, as parameterized by Perdew-Burke-Ernzerhof was used to describe the electron exchange and correlation energy. A plane-wave kinetic energy cut off of $500\\mathrm{eV}$ was adopted after a series of tests for all the calculated models. The Brillouin zone was sampled with a Monkhorst-Pack $3\\times3\\times1$ k-point grid. Geometries were optimized until the force was converged to $0.01\\mathrm{eV}\\mathrm{\\bar{/A}}$ . A large vacuum slab of $25\\mathrm{\\bar{A}}$ was inserted in the $\\textbf{z}$ direction for surface isolation to avoid the interaction between two neighboring surfaces for all the calculations. \n\nThe ORR in an acid electrolyte takes place through the following elementary steps [Eqs. $5-9]^{65}$ : \n\n$$\n\\mathrm{O}_{2}(\\mathrm{g})+\\mathrm{H}^{+}+e^{-}+^{\\ast}\\rightarrow\\mathrm{OOH}^{\\ast}\n$$ \n\n$$\n\\mathrm{OOH^{*}}+\\mathrm{H^{+}}+e^{-}\\rightarrow\\mathrm{O^{*}}+\\mathrm{H_{2}O(l)}\n$$ \n\n$$\n\\mathrm{O^{*}+H^{+}+}e^{-}\\rightarrow\\mathrm{OH^{*}}\n$$ \n\n$$\n\\mathrm{OH^{*}+H^{+}}+e^{-}\\rightarrow\\mathrm{H}_{2}\\mathrm{O(l)}{+}^{*}\n$$ \n\nwhere \\* stands for the active site on the catalyst, $\\mathrm{{OOH^{*}}}$ , ${}^{\\mathrm{O^{*}}}$ , and $\\mathrm{OH^{*}}$ refer to adsorbed intermediates, (l) and (g) refer to liquid and gas phases, respectively. \n\nThe change of Gibbs free energy for each elementary step was calculated as follows: \n\n$$\n\\Delta G=\\Delta E+\\Delta\\mathrm{ZPE}-T\\Delta S+\\Delta G_{\\mathrm{U}}+\\triangle G_{\\mathrm{pH}}\n$$ \n\nwhere $\\Delta E$ refers to the reaction energy obtained from DFT calculations, ΔZPE and ΔS are the change in zero-point energy and entropy, respectively. The effect of a bias on all the states involving an electron in the electrode is taken into account by shifting the electron energy of the corresponding state by $\\Delta G_{\\mathrm{U}}=-e U_{\\mathrm{:}}$ , when an electron is transferred. $\\Delta G_{\\mathrm{pH}}$ is the free energy correction of the $\\mathrm{H^{+}}$ , and is calculated by the equation: $\\Delta G=k_{\\mathrm{B}}T\\times\\mathrm{ln}10\\times\\mathrm{pH}$ , where $k_{\\mathrm{B}}$ is the Boltzmann constant and $T$ is the temperature. $\\mathrm{\\pH}=0$ was taken for ORR in an acidic electrolyte. For $_\\mathrm{H}_{2}\\mathrm{O}$ in the liquid phase, the gas phase of $_\\mathrm{H_{2}O}$ at 0.035 bar, which is the equilibrium pressure of $_\\mathrm{H_{2}O}$ at $298.15\\mathrm{K},$ was used as the reference system. The free energy of $\\mathrm{O}_{2}$ was obtained from the reaction $\\mathrm{O}_{2}+2\\mathrm{H}_{2}{\\rightarrow}2\\mathrm{H}_{2}\\mathrm{O}$ due to the inaccuracy of DFT in estimating the cohesive energy of $\\mathrm{O}_{2}$ . The overpotential of a catalyst for ORR is determined by [Eq. 10]: \n\n$$\n\\eta=\\Delta G_{\\mathrm{max}}/e+1.23\\:\\mathrm{V}\n$$ \n\nwhere $\\Delta G_{\\mathrm{max}}$ is the maximum Gibbs free energy difference between each two successive reaction steps at $U{=}0\\mathrm{V}$ . \n\nMD simulations were carried out in the Large-scale Atomic/Molecular Massively Parallel Simulator $\\mathrm{code}^{66}$ . The energy of the $\\mathrm{Fe-N_{4}}$ and $\\mathrm{Fe{-}N_{4}/F e_{4}{-}N_{6}}$ system was minimized using the conjugate gradient algorithm prior to MD simulations. Periodic boundary condition was applied in all directions. The mixed interaction is defined via the hybrid command combining Tersoff 67, $\\mathrm{MEAM^{68}}$ , and Lennard-Jones $(\\mathrm{LJ})^{69}$ potential. Tersoff and MEAM potential were used for C–N, and Fe–N, Fe–Fe bonding interactions, respectively. While the interaction between Fe and C is modeled using the LJ potential. The time step was set up as 0.001 ps in the constant-pressure, constant-temperature ensemble (NPT). The Nosé−Hoover chain thermostat was applied for temperature control. Visual Molecular Dynamics (VMD) software70 is used for 2D visualization of the atomic configurations. \n\n# Data availability \n\nThe data supporting this study are available within the paper and the Supplementary Information. Source data are provided with this paper. \n\nReceived: 30 January 2022; Accepted: 13 May 2022; Published online: 26 May 2022 \n\n# References \n\nChong, L. et al. Ultralow-loading platinum-cobalt fuel cell catalysts derived from imidazolate frameworks. Science 362, 1276–1281 (2018). \n2. Ott, S. et al. Ionomer distribution control in porous carbon-supported catalyst layers for high-power and low Pt-loaded proton exchange membrane fuel cells. Nat. Mater. 19, 77–85 (2020). \n3. Liu, Q., Liu, X., Zheng, L. & Shui, J. The solid-phase synthesis of an Fe-N-C electrocatalyst for high-power proton-exchange membrane fuel cells. Angew. Chem. Int. Ed. 57, 1204–1208 (2018). \n4. He, Y., Liu, S., Priest, C., Shi, Q. & Wu, G. Atomically dispersed metalnitrogen-carbon catalysts for fuel cells: advances in catalyst design, electrode performance, and durability improvement. Chem. Soc. Rev. 49, 3484–3524 (2020). \n5. Asset, T. & Atanassov, P. Iron-nitrogen-carbon catalysts for proton exchange membrane fuel cells. Joule 4, 33–44 (2020). \n6. Zhao, C.-X. et al. Recent advances of noble-metal-free bifunctional oxygen reduction and evolution electrocatalysts. Chem. Soc. Rev. 50, 7745–7778 (2021). \n7. Al-Zoubi, T. et al. Preparation of nonprecious metal electrocatalysts for the reduction of oxygen using a low-temperature sacrificial metal. J. Am. Chem. Soc. 142, 5477–5481 (2020). \n8. Wan, X. et al. Fe–N–C electrocatalyst with dense active sites and efficient mass transport for high-performance proton exchange membrane fuel cells. Nat. Catal. 2, 259–268 (2019). \n9. Menga, D. et al. Resolving the dilemma of Fe–N–C catalysts by the selective synthesis of tetrapyrrolic active sites via an imprinting strategy. J. Am. Chem. Soc. 143, 18010–18019 (2021). \n10. Wang, Q. et al. Molten NaCl-assisted synthesis of porous Fe-N-C electrocatalysts with a high density of catalytically accessible $\\mathrm{FeN_{4}}$ active sites and outstanding oxygen reduction reaction performance. Adv. Energy Mater. 11, 2100219 (2021). \n11. Jiao, L. et al. Chemical vapour deposition of Fe–N–C oxygen reduction catalysts with full utilization of dense Fe– ${\\bf\\cdot N_{4}}$ sites. Nat. Mater. 20, 1385–1391 (2021). \n12. Jiang, R. et al. Edge-site engineering of atomically dispersed $\\mathrm{Fe-N_{4}}$ by selective $\\mathrm{C-N}$ bond cleavage for enhanced oxygen reduction reaction activities. J. Am. Chem. Soc. 140, 11594–11598 (2018). \n13. Fu, X. et al. Tailoring $\\mathrm{FeN_{4}}$ sites with edge enrichment for boosted oxygen reduction performance in proton exchange membrane fuel cell. Adv. Energy Mater. 9, 1803737 (2019). \n14. Mun, Y. et al. Versatile strategy for tuning ORR activity of a single Fe- ${\\bf\\cdot N_{4}}$ site by controlling electron-withdrawing/donating properties of a carbon plane. $J.$ Am. Chem. Soc. 141, 6254–6262 (2019). \n15. Yuan, K. et al. Boosting oxygen reduction of single iron active sites via geometric and electronic engineering: nitrogen and phosphorus dual coordination. J. Am. Chem. Soc. 142, 2404–2412 (2020). \n16. Zhang, N. et al. High-purity pyrrole-type $\\mathrm{FeN_{4}}$ sites as a superior oxygen reduction electrocatalyst. Energy Environ. Sci. 13, 111–118 (2020). \n17. Han, A. et al. An adjacent atomic platinum site enables single-atom iron with high oxygen reduction reaction performance. Angew. Chem. Int. Ed. 60, 19262–19271 (2021). \n18. Gasteiger, H. A., Kocha, S. S., Sompalli, B. & Wagner, F. T. Activity benchmarks and requirements for $\\mathrm{Pt,}$ Pt-alloy, and non-Pt oxygen reduction catalysts for PEMFCs. Appl. Catal. B Environ. 56, 9–35 (2005). \n19. Xie, X. et al. Performance enhancement and degradation mechanism identification of a single-atom $\\scriptstyle\\mathrm{Co-N-C}$ catalyst for proton exchange membrane fuel cells. Nat. Catal. 3, 1044–1054 (2020). \n20. Miao, Z. et al. Improving the stability of non-noble-metal M–N–C catalysts for proton-exchange-membrane fuel cells through M–N bond length and coordination regulation. Adv. Mater. 33, 2006613 (2021). \n21. Xia, D. et al. Degradation and regeneration of $\\mathrm{Fe-N}_{x}$ active sites for the oxygen reduction reaction: the role of surface oxidation, Fe demetallation and local carbon microporosity. Chem. Sci. 12, 11576–11584 (2021). \n22. Liu, Q. et al. Sequential synthesis and active-site coordination principle of precious metal single-atom catalysts for oxygen reduction reaction and PEM fuel cells. Adv. Energy Mater. 10, 2000689 (2020). \n23. Luo, E. et al. Single-atom $\\mathrm{Cr-N_{4}}$ sites designed for durable oxygen reduction catalysis in acid media. Angew. Chem. Int. Ed. 58, 12469–12475 (2019). \n24. Ye, C.-W. & Xu, L. Recent advances in the design of a high performance metal–nitrogen–carbon catalyst for the oxygen reduction reaction. J. Mater. Chem. A 9, 22218–22247 (2021). \n25. Choi, C. H. et al. The Achilles’ heel of iron-based catalysts during oxygen reduction in an acidic medium. Energy Environ. Sci. 11, 3176–3182 (2018). \n26. Chenitz, R. et al. A specific demetalation of $\\mathrm{Fe-N_{4}}$ catalytic sites in the micropores of $\\mathrm{NC\\_Ar}+\\mathrm{NH}_{3}$ is at the origin of the initial activity loss of the highly active Fe/N/C catalyst used for the reduction of oxygen in PEM fuel cells. Energy Environ. Sci. 11, 365–382 (2018). \n27. Wan, X., Liu, X. & Shui, J. Stability of PGM-free fuel cell catalysts: degradation mechanisms and mitigation strategies. Prog. Nat. Sci. Mater. Int. 30, 721–731 (2020). \n28. Kumar, K. et al. On the influence of oxygen on the degradation of Fe-N-C. Catalysts. Angew. Chem. Int. Ed. 59, 3235–3243 (2020). \n29. Xia, D. et al. Direct growth of carbon nanotubes doped with single atomic Fe– ${\\bf\\cdot N_{4}}$ active sites and neighboring graphitic nitrogen for efficient and stable oxygen reduction electrocatalysis. Adv. Funct. Mater. 29, 1906174 (2019). \n30. He, Y. et al. Single cobalt sites dispersed in hierarchically porous nanofiber networks for durable and high-power PGM-free cathodes in fuel cells. Adv. Mater. 32, 2003577 (2020). \n31. Li, J. et al. Identification of durable and non-durable $\\mathrm{FeN}_{x}$ sites in Fe–N–C materials for proton exchange membrane fuel cells. Nat. Catal. 4, 10–19 (2020). \n32. Chung, H. T. et al. Direct atomic-level insight into the active sites of a highperformance PGM-free ORR catalyst. Science 357, 479–484 (2017). \n33. Han, X. et al. Generation of nanoparticle, atomic-cluster, and single-atom cobalt catalysts from zeolitic imidazole frameworks by spatial isolation and their use in zinc-air batteries. Angew. Chem. Int. Ed. 58, 5359–5364 (2019). \n34. Wan, X. et al. Synthesis and active site identification of Fe−N−C single-atom catalysts for the oxygen reduction reaction. ChemElectroChem 6, 304–315 (2019). \n35. Chen, M.-X. et al. Identification of catalytic sites for oxygen reduction in metal/nitrogen-doped carbons with encapsulated metal nanoparticles. Angew. Chem. Int. Ed. 59, 1627–1633 (2020). \n36. Jiang, W.-J. et al. Understanding the high activity of $\\mathrm{Fe-N-C}$ electrocatalysts in oxygen reduction: $\\mathrm{Fe}/\\mathrm{Fe}_{3}\\mathrm{C}$ nanoparticles boost the activity of Fe‒ $\\cdot\\mathrm{N}_{x}$ . J. Am. Chem. Soc. 138, 3570–3578 (2016). \n37. Ao, X. et al. Markedly enhanced oxygen reduction activity of single-atom Fe catalysts via integration with Fe nanoclusters. ACS Nano 13, 11853–11862 (2019). \n38. Qi, D. et al. Engineering atomic sites via adjacent dual-metal sub-nanoclusters for efficient oxygen reduction reaction and Zn-air battery. Small 16, 2004855 (2020). \n39. Liu, M. et al. Synergies of Fe single atoms and clusters on N-Doped carbon electrocatalyst for $\\mathrm{\\pH}$ -universal oxygen reduction. Small Methods 5, 2001165 (2021). \n40. Jin, Z. et al. Understanding the inter-site distance effect in single-atom catalysts for oxygen electroreduction. Nat. Catal. 4, 615–622 (2021). \n41. Zhao, S.-N., Li, J. K., Wang, R., Cai, J. & Zang, S.-Q. Electronically and geometrically modified single-atom Fe sites by adjacent Fe nanoparticles for enhanced oxygen reduction. Adv. Mater. 34, 2107291 (2021). \n42. Huang, H. et al. Clusters induced electron redistribution to tune oxygen reduction activity of transition metal single-atom for metal-air batteries. Angew. Chem. Int. Ed. 61, e202116068 (2021). \n43. Yin, S.-H. et al. Construction of highly active metal-containing nanoparticles and FeCo- ${\\bf\\cdot N_{4}}$ composite sites for the acidic oxygen reduction reaction. Angew. Chem. Int. Ed. 59, 21976–21979 (2020). \n44. Cheng, X. et al. Nano-geometric deformation and synergistic Co nanoparticles $\\mathrm{-Co-N_{4}}$ composite sites for proton exchange membrane fuel cells. Energy Environ. Sci. 14, 5958–5967 (2021). \n45. Deng, J., Ren, P., Deng, D. & Bao, X. Enhanced electron penetration through an ultrathin graphene layer for highly efficient catalysis of the hydrogen evolution reaction. Angew. Chem. Int. Ed. 54, 2100–2104 (2015). \n46. Ye, W. et al. Precisely tuning the number of Fe atoms in clusters on N-doped carbon toward acidic oxygen reduction reaction. Chem. 5, 2865–2878 (2019). and comparison of their activities for the oxygen reduction reaction and performances in proton exchange membrane fuel cells. J. Mater. Chem. A 7, 26147–26153 (2019). \n48. Choi, C. H. et al. Stability of Fe-N-C catalysts in acidic medium studied by operando spectroscopy. Angew. Chem. Int. Ed. 54, 12753–12757 (2015). \n49. Li, J. et al. Thermally driven structure and performance evolution of atomically dispersed $\\mathrm{FeN_{4}}$ sites for oxygen reduction. Angew. Chem. Int. Ed. 58, 18971–18980 (2019). \n50. Zhu, Z. et al. Coexisting single-atomic Fe and Ni sites on hierarchically ordered porous carbon as a highly efficient ORR electrocatalyst. Adv. Mater. 32, 2004670 (2020). \n51. Ji, S. et al. Confined pyrolysis within metal-organic frameworks to form uniform ${\\mathrm{Ru}}_{3}$ clusters for efficient oxidation of alcohols. J. Am. Chem. Soc. 139, 9795–9798 (2017). \n52. Gu, J. et al. Synergizing metal-support interactions and spatial confinement boosts dynamics of atomic nickel for hydrogenations. Nat. Nanotechnol. 16, 1141–1149 (2021). \n53. Malko, D., Kucernak, A. & Lopes, T. In situ electrochemical quantification of active sites in Fe–N/C non-precious metal catalysts. Nat. Commun. 7, 13285 (2016). \n54. Liu, J. et al. Hydrogen passivation of M–N–C (M = Fe, Co) catalysts for storage stability and ORR activity improvements. Adv. Mater. 33, 2103600 (2021). \n55. Strickland, K. et al. Highly active oxygen reduction non-platinum group metal electrocatalyst without direct metal-nitrogen coordination. Nat. Commun. 6, 7343 (2015). \n56. Qiao, M. et al. Hierarchically ordered porous carbon with atomically dispersed $\\mathrm{FeN_{4}}$ for ultra-efficient oxygen reduction reaction in proton-exchange membrane fuel cells. Angew. Chem. Int. Ed. 59, 2688–2694 (2020). \n57. Zhang, H. et al. High-performance fuel cell cathodes exclusively containing atomically dispersed iron active sites. Energy Environ. Sci. 12, 2548–2558 (2019). \n58. Maioli, P. et al. Mechanical vibrations of atomically defined metal clusters: from nano- to molecular-size oscillators. Nano Lett. 18, 6842–6849 (2018). \n59. Amali, A. J., Hoshino, H., Wu, C., Ando, M. & Xu, Q. From metal-organic framework to intrinsically fluorescent carbon nanodots. Chem. Eur. J. 20, 8279–8282 (2014). \n60. Sato-Berrú, R., Saniger, J. M., Flores-Flores, J. & Sanchez-Espíndola, M. Simple method for the controlled growth of $\\mathrm{SiO}_{2}$ spheres. J. Mater. Sci. Eng. A 3, 237–242 (2013). \n61. Gor, G. Y., Thommes, M., Cychosz, K. A. & Neimark, A. V. Quenched solid density functional theory method for characterization of mesoporous carbons by nitrogen adsorption. Carbon 50, 1583–1590 (2012). \n62. Newville, M. IFEFFIT: interactive XAFS analysis and FEFF fitting. J. Synchrotron Radiat. 8, 322–324 (2001). \n63. Ravel, B. & Newville, M. ATHENA, ARTEMIS, HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT. J. Synchrotron Radiat. 12, 537–541 (2005). \n64. Hu, H.-Y., Goto, N. & Fujie, K. Effect of pH on the reduction of nitrite in water by metallic iron. Water Res. 35, 2789–2793 (2001). \n65. Reda, M., Hansen, H. A. & Vegge, T. DFT study of the oxygen reduction reaction on carbon-coated iron and iron Carbide. ACS Catal. 8, 10521–10529 (2018). \n66. Plimpton, S. Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117, 1–19 (1995). \n67. Kınacı, A., Haskins, J. B., Sevik, C. & Çağın, T. Thermal conductivity of BN-C nanostructures. Phys. Rev. B 86, 115410 (2012). \n68. Lee, B.-J., Lee, T.-H. & Kim, S.-J. A modified embedded-atom method interatomic potential for the Fe–N system: a comparative study with the Fe–C system. Acta Mater. 54, 4597–4607 (2006). \n69. Liang, T., Zhou, M., Zhang, P., Yuan, P. & Yang, D. Multilayer in-plane graphene/hexagonal boron nitride heterostructures: Insights into the interfacial thermal transport properties. Int. J. Heat Mass Transf. 151, 119395 (2020). \n70. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996). \n\n# Acknowledgements \n\nThis work was supported by Natural Science Foundation of Beijing Municipality (Z200012), National Natural Science Foundation of China (21975010, U21A20328) and the Academic Excellence Foundation of BUAA for PhD Students. \n\n# Author contributions \n\nJ.Shu. and X.W. conceived and designed the research. X.W. conducted the synthesis, electrochemical measurements, and characterizations. Q.L., J.L., S.L., and J.Sha. \n\nperformed the theoretical calculations. L.Z. conducted XAS measurements. X.W., X.L., and J.Shu. co-wrote the paper. The project was supervised by R.Y. and J.Shu. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-30702-z. \n\nCorrespondence and requests for materials should be addressed to Jianglan Shui. \n\nPeer review information Nature Communications thanks Lawrence Yoon Suk Lee, Jinwoo Lee and the other, anonymous, reviewer for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1038_s41467-022-28906-4", + "DOI": "10.1038/s41467-022-28906-4", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-28906-4", + "Relative Dir Path": "mds/10.1038_s41467-022-28906-4", + "Article Title": "Hygroscopic holey graphene aerogel fibers enable highly efficient moisture capture, heat allocation and microwave absorption", + "Authors": "Hou, YL; Sheng, ZZ; Fu, C; Kong, J; Zhang, XT", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Aerogel fibers have been recognized as the rising star in the fields of thermal insulation and wearable textiles. Yet, the lack of functionalization in aerogel fibers limits their applications. Herein, we report hygroscopic holey graphene aerogel fibers (LiCl@HGAFs) with integrated functionalities of highly efficient moisture capture, heat allocation, and microwave absorption. LiCl@HGAFs realize the water sorption capacity over 4.15 g g(-1), due to the high surface area and high water uptake kinetics. Moreover, the sorbent can be regenerated through both photo-thermal and electro-thermal approaches. Along with the water sorption and desorption, LiCl@HGAFs experience an efficient heat transfer process, with a heat storage capacity of 6.93 kJ g(-1). The coefficient of performance in the heating and cooling mode can reach 1.72 and 0.70, respectively. Notably, with the entrapped water, LiCl@HGAFs exhibit broad microwave absorption with a bandwidth of 9.69 GHz, good impedance matching, and a high attenuation constant of 585. In light of these findings, the multifunctional LiCl@HGAFs open an avenue for applications in water harvest, heat allocation, and microwave absorption. This strategy also suggests the possibility to functionalize aerogel fibers towards even broader applications. Functionalization of aerogel fibers, characterized by high porosity and low thermal conductivity, to obtain multifunctional materials is highly desirable. Here the authors report hygroscopic holey graphene aerogel fibers hosting LiCl salt, enabling moisture capture, heat allocation, and microwave absorption performance.", + "Times Cited, WoS Core": 293, + "Times Cited, All Databases": 302, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000766759300018", + "Markdown": "# Hygroscopic holey graphene aerogel fibers enable highly efficient moisture capture, heat allocation and microwave absorption \n\nYinglai ${\\mathsf{H o u}}^{1,2,4},$ Zhizhi Sheng2,4, Chen $\\mathsf{F u}^{2}$ , Jie Kong 1✉ & Xuetong Zhang 2,3✉ \n\nAerogel fibers have been recognized as the rising star in the fields of thermal insulation and wearable textiles. Yet, the lack of functionalization in aerogel fibers limits their applications. Herein, we report hygroscopic holey graphene aerogel fibers $\\langle\\mathsf{L i C l}(\\varpi\\mathsf{H G A F s})$ with integrated functionalities of highly efficient moisture capture, heat allocation, and microwave absorption. LiCl $@$ HGAFs realize the water sorption capacity over $4.15{\\mathrm{g}}{\\mathrm{g}}^{-1}, $ due to the high surface area and high water uptake kinetics. Moreover, the sorbent can be regenerated through both photo-thermal and electro-thermal approaches. Along with the water sorption and desorption, $\\mathsf{L i C l}@\\mathsf{H G A F s}$ experience an efficient heat transfer process, with a heat storage capacity of $6.93\\mathsf{k J}\\mathsf{g}^{-1}$ . The coefficient of performance in the heating and cooling mode can reach 1.72 and 0.70, respectively. Notably, with the entrapped water, LiC $@$ HGAFs exhibit broad microwave absorption with a bandwidth of $9.69\\mathsf{G H z}$ good impedance matching, and a high attenuation constant of 585. In light of these findings, the multifunctional LiCl@HGAFs open an avenue for applications in water harvest, heat allocation, and microwave absorption. This strategy also suggests the possibility to functionalize aerogel fibers towards even broader applications. \n\nerogel fibers have been the focal points in a broad spectrum of applications, ranging from thermal insulation1–4, wearable textiles3,5, to stimuli-responsive electronics6, due to their high specific area, high porosity, low density, and low thermal conductivity. A variety of materials can be fabricated into aerogel fibers, such as polymers (e.g., Kevlar, polyimide)3,7, ceramics (e.g., silica, boron nitride) $1,4,8,9$ , carbon-based materials (e.g., CNT, graphene, MXene)6,10–12, and hybrid materials (e.g., cellulose/cobalt ferrite, silk fibroin/graphene oxide, graphene/ $\\mathrm{Ni})^{5,13,14}$ . Different strategies are exploited for the construction of aerogel fibers starting from variant nanoscale building blocks, for instance, reaction spinning4, coaxial spinning5, wet spinning6,10, and sol-gel confined transition method7. With further freezedrying or supercritical $\\mathrm{CO}_{2}$ drying, aerogel fibers with superior thermal insulation3,4, superhydrophobicity3,4, high transparency4, high mechanical strength, and desirable flame-resistance7 can be realized, depending on the selection of nanoscale building blocks. The resulting aerogel fibers can be easily knotted, bent, and even woven into fabrics for wearable applications at room temperature or under extreme environments3. The low thermal conductivity of aerogel materials, combined with the shape flexibility of onedimensional fibers, has facilitated the development of thermal insulation textiles. \n\nHowever, to extend the applications beyond thermal insulation, the functionalization of aerogel fibers is quite necessary. Specifically, the porous architecture in aerogel fibers provides sufficient confinements and high surface area to host other guest components for their further functionalization15. That is, aerogel fibers possess a high surface area that can bear rich functionalities to interact with ions or molecules7,11,16, and even external stimuli6. Prior efforts have been focused on the infiltration of an intelligent guest into aerogel fibers. For example, graphene aerogel fibers have been adopted as the porous host to incorporate the phase change materials, exhibiting self-clean superhydrophobic surface and excellent multiple responsiveness to external stimuli (electric field/light/thermal field) as well as reversible energy storage and conversion capability6. Introducing the phase change material into aerogel fibers would also improve the thermal comfort of humans by adjusting the microenvironment through thermal storage and release of phase change materials3. However, current aerogel fibers are still limited on a single function, multiple functionalities are greatly needed when encountering variant or complex environments. Therefore, it is highly desirable to develop multifunctional aerogel fibers for broader promising applications. \n\nHerein, we report the hygroscopic holey graphene aerogel fibers (LiCl@HGAFs), where the holey graphene aerogel fibers host efficient hygroscopic salt LiCl, enabling superior moisture capture, heat allocation, and microwave absorption performance. The holey graphene aerogel porous matrix provides not only sufficient binding sites and surface area for water uptake but also abundant water transport pathways through the etched nanopores. These LiCl $@$ HGAFs exhibit $4.15\\:\\mathrm{g}\\mathrm{g}^{-1}$ moisture sorption capacity at $90\\%$ relative humidity and multiple pathways to perform sorption/desorption processes, and thermodynamics and kinetics of the water sorption with the $\\mathrm{LiCl@HGAFs}$ are determined. In addition, during the process of water sorption and desorption, not only mass transfer but also heat transfer occurs. Benefitting from moisture sorption performance, LiCl@HGAFs are also demonstrated as adsorption-based heat transfer (AHT) devices such as adsorption-driven cooling/chiller and adsorptiondriven heat pump. Bearing water as the ideal working fluid (the latent heat of evaporation up to $44\\mathrm{kJ}\\mathrm{mol}^{-1}$ at room temperature and recyclability), AHT devices have the potential to be environmental-friendly, non-flammable, and low-cost, targeting a drastic reduction of energy consumption for cooling and heating owing to the potential use of natural solar energy or waste heat from industrial plants. Furthermore, the ${\\mathrm{LiCl@HGAFs}}$ contain above $2{\\bf\\delta g^{\\underline{{}}}g^{\\underline{{}}}}1$ saline water in the porous host after absorbing the moisture, showing microwave absorption performance. The microwave absorption of the LiCl@HGAFs is greatly improved after the sorption of water. The effect adsorption bandwidth has been improved from 0 to $9.69\\mathrm{GHz}$ $(8.31\\mathrm{-}18\\mathrm{GHz})$ . Hence, the LiCl $@$ HGAFs hold great promise for water harvest from the air, sorption-based heat allocation, as well as microwave absorption, paving the way towards multifunctional fiber-based devices and emerging applications. \n\n# Results \n\nFabrication strategy and functional design. The design strategy for LiCl $@$ HGAFs is illustrated in Fig. 1. LiCl is selected as the active salt decorated within the fiber because of its low density, low dehydration temperature, and super high water sorption capacity17. First, the holey graphene oxide (HGO) was prepared by etching graphene oxide (GO) in $\\mathrm{H}_{2}\\mathrm{O}_{2}$ at $100^{\\circ}\\mathrm{C}$ followed by washing and centrifuging. Then, the LiCl $@$ HGAFs were fabricated by wet spun, reduction, supercritical drying (Sc-drying), and filling with LiCl in sequence (Fig. 1a). LiCl $@$ HGAFs are further demonstrated with outstanding water harvest, heat allocation, and microwave adsorption behavior (Fig. 1b). Water molecules can be captured by LiCl@HGAFs and easily released based on the electro-thermal or photo-thermal effect of graphene. Efficient heat allocation was realized since heat is reversibly generated and released along with the adsorption and desorption of water. With water saturated in the interconnected porous structure, LiCl@HGAFs also show outstanding microwave adsorption performance, due to dipole polarization of water molecules, dipole polarization at the nanopore defects within the graphene plane, and multiple reflections between twodimensional (2D) graphene sheets. \n\nDuring the etching process, the carbon atoms in the actively defective zones of GO can be oxidized by $\\mathrm{H}_{2}\\mathrm{O}_{2}.$ thereby generating nanopores gradually (Fig. 2a)18. The transmission electron microscopy (TEM) study shows that abundant in-plane nanopores are produced on the GO sheets by etching with $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (Fig. 2b(ii)). And as the etching time lengthens, the number of pores in the sheets increases (Supplementary Fig. 1b–d). As a contrast, no obvious in-plane nanopores are observed in the sample without $\\mathrm{H}_{2}\\mathrm{O}_{2}$ etching (Fig. 2b(i) and Supplementary Fig. 1a). The resulting HGO has fewer oxygen functionalities and defects than GO, which can be concluded from the decreased intensity ratio of the $\\mathrm{~D~}$ band to G band in Raman spectra (Supplementary Fig. 2). There are two typical peaks in the spectra, where one peak at $1350\\mathrm{cm}^{-1}$ is attributed to the D band with disordered and defected structure and the other peak at $1583\\mathrm{cm}$ $^{-1}$ corresponding to the G band with graphitic structure19. After etching, the $\\mathrm{I_{D}/I_{G}}$ decreases from 0.9937 to 0.9197, indicating that GO is deoxygenated during the etching process, which is consistent with previous reports20,21. It is proposed that oxidative-etching initiates and propagates in the oxygenic defect sites within the basal plane of GO, resulting in the removal of oxygenated carbon atoms and the formation of carbon vacancies that eventually extend into nanopores21,22. Further studying the oxygen functional groups on HGO sheets by XPS proves that the C-O group $(\\sim286\\mathrm{eV})$ is decreased after $\\mathrm{H}_{2}\\mathrm{O}_{2}$ etching (Supplementary Fig. 3). After centrifugation, the HGO aqueous lyotropic crystal phase suspension is analogous to that of GO suspension with a high concentration, which can be observed under a polarizing microscope (Fig. 2c). \n\nBy injecting HGO suspension with a spinning nozzle of $500\\upmu\\mathrm{m}$ into $\\mathrm{CaCl}_{2}$ aqueous solution, the HGO hydrogel fibers were obtained (Supplementary Fig. 4). Compared with GO hydrogel fibers, HGO hydrogel fibers have a darker color, indicating a lower degree of oxidation. The liquid crystals of HGO could be self-assembled by the shear force applied through the syringe piston and $\\mathrm{Ca}^{2+}$ offered interlayer and intralayer cross-linking bridges between the oxygen-containing groups to improve the stability of HGO hydrogel fibers. Hydriodic acid (HI) was employed to reduce the HGO hydrogel fiber. The XPS result shows that -C-O and ${\\mathrm{C}}={\\mathrm{O}}$ groups are decreased after reduction (Supplementary Fig. 3 and Supplementary Fig. 5b). However, compared with GAF, holey graphene aerogel fiber (HGAF) has more oxygen and less reduction (Supplementary Fig. 5a), which is attributed to more defects. Raman spectra show that obtained HGAFs have more defects than GAFs, the $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ of HGAFs is 1.13–1.23, higher than the value for GAFs $(I_{\\mathrm{D}}/I_{\\mathrm{G}}=1.06)$ ) (Supplementary Fig. 6). This may be due to the fact that more defects are produced in the etching process, and the oxygencontaining groups at the defects are more difficult to reduce. However, the existence of these defects will affect the final properties of the fiber. The electrical conductivity of the fiber decreases significantly with the increase of defects (Supplementary Fig. 7). In the Sc-drying process, the solvent has a low surface tension, and the transformation from wet gel to aerogel is completed with a contraction ratio of 0.42 by preserving the porous skeleton. The hierarchical structure of obtained HGAFs with the density of $0.23\\mathrm{g}\\mathrm{cm}^{-3}$ was revealed by the field emission electron microscopy (FESEM). The images indicate that holey graphene sheets are assembled in uniform long-range order as same as GAF (Fig. 2g, h and Supplementary Fig. 8), which are induced by the shearing force through the injection. Due to hydrogen peroxide etching, the pore size distribution and pore volume of the fiber are significantly increased (Supplementary Fig. 9). The specific surface area of HGAFs $(356.{\\dot{3}}\\mathrm{m}^{2}\\mathrm{g}^{-1})$ is higher than GAF $(218.8\\mathrm{m}^{2}\\mathrm{g}^{-1})$ , which can be attributed to the existence of nanopores on the graphene sheets. Furthermore, The HGAF possesses flexibility (bending stiffness $R_{\\mathrm{f}}=3.08\\times10^{-9}\\mathrm{N}$ $\\mathbf{m}^{2}.$ ) and can be knotted or woven into a textile (Fig. 2d–f). Additionally, in view of the aging effect on the preparation of aerogel materials, the specific surface area, electrical conductivity, tensile strength, and average diameter of HGAFs with different aging times $(1,2,$ , and 3 days) were investigated in Supplementary Figs. 10–13. The specific surface area decreases with increasing aging time (Supplementary Fig. 10). It can be attributed to the fact that the diffusion of ions during aging increases the ionic crosslinks between holey graphene sheets, making them more tightly packed and causing more shrinkage (Supplementary Fig. 13, the average diameter of the fibers decreases from $329.41\\upmu\\mathrm{m}$ to $273.44\\upmu\\mathrm{m}$ with aging time). Nevertheless, at the same time, the electrical conductivity (from $146.77\\mathrm{S}\\mathrm{m}^{-1}$ to $211.69\\mathrm{S}\\mathrm{m}^{-1}$ , Supplementary Fig. 11) and tensile strength (from $0.77\\mathrm{MPa}$ to $1.03\\mathrm{MPa}$ , Supplementary Fig. 12) of fibers increase with the aging time. Moreover, we employ a liquid impregnation strategy for the construction of the LiCl@HGAFs. Obviously, the hygroscopic LiCl is uniformly distributed across the graphene sheets (Fig. 2i, j and Supplementary Fig. 14). The distribution of Cl element derived from LiCl further reveals that LiCl crystals are homogeneously anchored on the holey graphene sheets (Supplementary Fig. 15). With the increase of LiCl mass loading $(3\\mathrm{~wt.\\%}$ , $5\\ \\mathrm{wt.\\%}.$ , and $7\\ \\mathrm{wt.\\%}$ , denoted as LiCl@HGAF-3, LiCl $@$ HGAF-5, and $\\mathrm{LiCl}@\\mathrm{HGAF-7}$ , respectively), it can be observed that the filling amount in the porous architecture increased significantly. \n\n![](images/691cafb9f32c2cfcf4952b99f3d9e038de908e6371733c815200ffb364dc0a64.jpg) \nFig. 1 Fabrication strategy and application of LiCl@HGAFs. a Schematic illustration of the fabrication of hygroscopic holey graphene aerogel fibers (LiCl@HGAFs). HGAFs were obtained by wet spinning, HI reduction, and supercritical drying. LiCl was introduced by simple impregnation. b Schematic illustrations on moisture capture, heat allocation, and microwave absorption, respectively. LiCl in the fiber can effectively capture moisture and liquefy it, which can be regenerated by heating and harvested water. The adsorption heat is generated in the adsorption process $(Q_{\\mathsf{a d s}})$ and the heat is absorbed in the regeneration process $(Q_{\\mathrm{des}})$ . This heat transfer property makes the LiCl $@$ HGAFs applicable in heat storage and heat distribution allocation. In the process of moisture capture, the liquid water produced in the fibers has a significant loss effect on microwave adsorption, which can significantly improve the microwave absorption performance of the fibers. \n\n![](images/02477b928f5dea84c46da06b43a2ab9479156132087f8cbaec943684666ee4bd.jpg) \nFig. 2 Characterization of LiCl@HGAFs. a Schematic of the nanopores on graphene oxide formation by $H_{2}O_{2}$ etching. b TEM images of GO (i) and HGO (ii) sheets. c The optical images of GO liquid crystal (i) and HGO liquid crystal (ii) made from etching GO by ${\\sf H}_{2}{\\sf O}_{2}$ . d A digital photo of HGAF (i) and knotted HGAF (ii). e SEM images of the knotted holey graphene aerogel fiber (i) and a partial enlargement of the knot (ii). f Photographs of ${\\mathsf{H G A F}}$ based textile (i) and folding test (ii–iii). g, h SEM images of the holey graphene aerogel fiber. i, j SEM images of LiCl@HGAF-3 ( $3\\mathrm{\\:wt.\\%}$ LiCl). $\\textbf{\\^k}$ XRD patterns of HGAFs and $\\mathsf{L i C l}@\\mathsf{H G A F s}$ . Source data are provided as a Source Data file. l I-E curves of HGAF and LiC $\\varrho\\_$ HGAF. Source data are provided as a Source Data file. $m$ The water contact angle measurements for HGAF and Li $C l@{\\mathsf{H G A F}}$ . \n\nWhen the loading amount is high enough, LiCl is prone to decorate around the whole graphene sheets in the fiber. X-ray Diffraction (XRD) patterns of HGAFs, LiCl@HGAF show the structure of HGAF is preserved after the impregnation of LiCl (Fig. 2k). The newly appeared diffraction peak in $\\mathrm{LiCl@HGAF}$ is assigned to lithium chloride hydrate, indicating that water molecules can rapidly interact with the LiCl to form LiCl∙ $_\\mathrm{H}_{2}\\mathrm{O}$ , which is known as hydration reaction17,23. The electrical conductivity of LiCl@HGAF is illustrated by the I-E curve (Fig. 2l), where the conductivity of $\\mathrm{LiCl}@\\mathrm{HAGF}$ $(149\\mathrm{S}\\mathrm{m}^{-1}.$ ) drops only slightly in comparison with that of HGAF (163 S $\\mathrm{m^{-1}}$ ). This reveals that the impregnation and subsequent freezedrying do not damage the three-dimensional network structure in the fiber, and the slight decrease in conductivity is attributed to the existence of non-conductive hygroscopic salt crystals on the graphene sheets. Besides, HGAF is inherently hydrophobic with the contact angle of $132.6\\pm0.5^{\\circ}$ while $\\mathrm{LiCl}\\bar{\\ @}\\mathrm{HGAF}$ is hydrophilic with the contact angle of $67.3\\pm0.5^{\\circ}$ , supporting that the presence of salt causes the fiber to change from hydrophobic to hydrophilic (Fig. 2m and Supplementary Fig. 16). The hydrophilicity of the composite fiber also guarantees the ease of water sorption. \n\n![](images/1b12363fe7c9c38c7dc8f196ad3d67e0e2e98877709d21ffa589e5031aa1426c.jpg) \nFig. 3 High efficient moisture capture by LiCl@HGAFs. a Schematic illustration of the moisture sorption process. In this process, LiCl reacts with water first to form ${\\mathsf{L i C l}}{\\mathsf{.H}}_{2}{\\mathsf{O}},$ , and then deliquesce to form LiCl solution, and the captured moisture exists in the form of liquid water (blue-shaded region). b Water uptake of LiC $\\varrho\\_$ GAFs and LiCl $@$ HGAFs at $25^{\\circ}\\mathsf{C}$ and $90\\%$ RH in $30\\mathrm{min}$ . Source data are provided as a Source Data file. c Water uptake of LiC ${\\mathsf{I}}@{\\mathsf{H G A F s}}$ with different salt contents at $25^{\\circ}\\mathsf{C}$ and $90\\%$ RH. Source data are provided as a Source Data file. d Water uptake of LiC $@$ HGAFs under the relative humidity of $30\\%$ , $60\\%$ , and $90\\%$ . Source data are provided as a Source Data file. e Comparison of water sorption capacity with reported hygroscopic materials: P $\\mathsf{V I P A A m/A l g^{54}}$ , Hydrogel28, MIL-101(Cr)@GO37, $\\mathsf{C a C l}_{2}@\\mathsf{U i O-}66^{55}$ , Y-shp-MOF- ${.542}$ , and PAN/MIL@LiCl NFM56. The materials marked in the blue-shaded region are Li ${\\tt I}(\\tt a\\sf H G A F s$ . Source data are provided as a Source Data file. f Temperature response of HGAFs and LiC $\\varrho\\_$ HGAFs under one-sun irradiation. Source data are provided as a Source Data file. g Temperature response of LiCl@HGAFs under various voltages. Source data are provided as a Source Data file. h Cycling stability of the sorption-desorption process of LiC $\\varrho\\_$ HGAFs under photo-thermal or electro-thermal conditions. Source data are provided as a Source Data file. \n\nMoisture sorption and desorption behaviors of LiCl@HGAFs. Figure 3 displays the moisture sorption mechanism and moisture capture characterization of $\\mathrm{LiCl@HGAFs}$ . The whole water uptake process includes three-step sorption processes: (i) the chemisorption from LiCl $@$ HGAFs to $\\mathrm{LiCl}@\\mathrm{HGAFs}.\\mathrm{H}_{2}\\mathrm{O},$ (ii) the deliquescence of LiCl $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ to LiCl concentrated solution, and (iii) solution absorption from the concentrated solution to dilute solution (Fig. 3a). The saturated solution formed continues to capture water molecules from the air to form a diluted solution, demonstrating the absorption behavior of the liquid absorbent in this condition. The moisture sorption performance of $\\operatorname{LiCl@H}.$ GAFs was gravimetrically evaluated at $25^{\\circ}\\mathrm{C}$ . Compared with \n\nLiCl@GAFs, LiCl $@$ HGAFs exhibits faster adsorption kinetics during the same period (Fig. 3b, LiCl@HGAFs: $1.81\\mathrm{g}\\mathrm{g}^{-1}$ , $30\\mathrm{min}$ ; LiCl@GAFs: $1.37\\:\\mathrm{g}\\:\\mathrm{g}^{-\\bar{1}}$ , $30\\mathrm{min}\\dot{}$ ), due to the presence of etched nanopores on the sheet that increase the diffusion pathways for water molecules. However, with increasing the sorption time up to $350\\mathrm{min}$ , two curves would gradually approach to each other (Supplementary Fig. 17), originating from the deliquescence of $\\mathrm{LiCl}{\\cdot}\\mathrm{H}_{2}\\mathrm{\\bar{O}}$ inside the fiber and that LiCl aqueous solution gradually fills the entire fiber. \n\nCombining the various pore structure and high porosity of the aerogel matrix with the strong moisture sorption of LiCl, LiCl@HGAFs show excellent moisture sorption capacity. Meanwhile, the LiCl content in LiCl $@$ HGAF plays a crucial role in the moisture sorption capacity. As shown in Fig. 3c, at the temperature of $25^{\\circ}\\mathrm{C}$ and the humidity of $90\\%$ RH, the moisture sorption capacity increases dramatically with increasing the loading fraction of LiCl. $\\mathrm{LiCl}@\\mathrm{HGAF}-7\\%$ and $\\mathrm{LiCl}@\\mathrm{HGAF}-5\\%$ exhibit much higher sorption capacity than $\\mathrm{LiCl}@\\mathrm{HGAF}-3\\%$ , corresponding to $4.14\\:\\mathrm{g}\\:\\mathrm{g}^{-1}$ , $3.56\\mathrm{g}\\mathrm{g}^{-1}$ , and $1.11\\ \\mathrm{g}\\mathrm{g}^{-1}$ , respectively. Interestingly, the difference between the sorption kinetics (i.e., the slope of the curve at the initial stage) of $\\mathrm{LiCl}@\\mathrm{HGAF}-7\\%$ and $\\mathrm{LiCl}@\\mathrm{HGAF}-5\\%$ is not obvious (Supplementary Fig. 18a), mainly due to the LiCl solution entrapped in the pores of the fiber. In addition, $\\mathrm{LiCl@HGAFs}$ exhibit high moisture sorption capacity and kinetics under a wide range of humidities (Fig. 3d and Supplementary Fig. 18b). Although the decrease in relative humidity has a huge impact on the moisture absorption of the fiber, the moisture absorption can reach $1.4\\mathrm{g}\\mathrm{g}^{-1}$ at moderate humidity $60\\%$ RH), with $\\mathsf{\\bar{0}}.66\\mathsf{g}\\mathsf{g}^{-1}$ at lower humidity $30\\%$ RH). Compared with previously reported moisture sorption materials, LiCl@HGAFs in this work exhibit superior sorption capacity at $25^{\\circ}\\mathrm{C}$ over a broad range of humidities, achieving more than $30\\%$ above the best material from some literature at $90\\%$ RH (Fig. 3e). Furthermore, dehumidification tests of a series of moisture sorption materials were conducted in a closed chamber with the same initial relative humidity (Supplementary Fig. 19). For the dehumidification performance of the sorbents with the same mass (Supplementary Fig. 19a), LiC $@$ HGAFs outperforms most of the compared sorbents and is slightly weaker than LiCl. For the sorbents with the same volume (Supplementary Fig. 19b), LiCl $@$ HGAFs shows moderate hygroscopic performance compared with other sorption materials. As a result, LiCl@HGAF can fully meet the needs of practical applications and can be easily operated at ambient temperature, surpassing the performance of other granular or membraniform moisture sorbents. \n\nLiCl@HGAFs possess both high solar-thermal conversion and high electro-thermal capability. Therefore, both solar energy and electrical energy can be used as the driving force to desorb the captured water from the sorbent. These regeneration processes for the moisture sorbents are environmental-friendly and meanwhile, low energy input is required. Both HGAFs and LiCl@HGAFs show a rapid photothermal response under onesun radiation $(1\\mathrm{kW}/\\mathrm{m}^{2})$ , with the temperature rising from $22^{\\circ}\\mathrm{C}$ to $46^{\\circ}\\mathrm{C}$ and $44^{\\circ}\\mathrm{C}$ within $44s,$ , respectively (Fig. 3f and Supplementary Fig. 21). The highest temperature reaches around $50^{\\circ}\\mathrm{C}$ for HGAFs and $47^{\\circ}\\mathrm{C}$ for ${\\mathrm{LiCl@HGAFs}}$ , respectively. The desorption of LiCl $@$ HGAFs was carried out under a typical water vapor pressure of $1.2\\mathrm{kPa}$ . Considering that the desorption temperature of LiCl@HGAFs depends on the dehydration of $\\mathrm{LiCl}{\\cdot}\\mathrm{H}_{2}\\mathrm{O};$ , the theoretical desorption temperature to the product of LiCl is $69^{\\circ}\\mathrm{C}$ according to Clausius–Clapeyron equilibrium equation24. Therefore, under the photo-thermal condition $(47^{\\circ}\\mathrm{C})$ , $\\operatorname{LiCl}(\\omega$ HGAFs undergo the desorption from LiCl solution to $\\mathrm{LiCl}{\\cdot}\\mathrm{H}_{2}\\mathrm{O}$ , where the regeneration degree can reach $83.4\\%$ (Supplementary Fig. 20). Unlike granular sorbents, LiCl@HGAFs are featured with interconnecting conductive networks, so they can also be desorbed and regenerated by electric heating. The fibers show excellent electro-thermal performance with the temperature rising to $131^{\\circ}\\mathrm{C}$ under $12\\mathrm{V}$ (Fig. $3\\mathrm{g}$ and Supplementary Fig. 23), sufficient to enable the complete desorption of the sorbent. Moreover, the fiber was subjected to 10 times sorption-desorption cycles using photo-thermal desorption and electro-thermal desorption, respectively. After five cycles, the fiber sorption rate coefficient drops from $1.575\\times\\dot{1}0^{-4}s^{-1}$ to $1.3\\dot{9}3\\times10^{-4}{s^{-1}}$ (Supplementary Fig. 18c and Supplementary Table 1), caused by the slight agglomeration of hygroscopic salt. The overall cycle stability of GAFs and HAGFs is maintained at a relatively stable level up to 10 cycles, both demonstrating rapid cycling capability of water capture and water release (Fig. 3h and Supplementary Fig. 22). The obtained transmission electron microscopy (TEM) images of LiCl@GAFs and ${\\mathrm{LiCl@HGAFs}}$ before and after the cyclic test show that there is no obvious change in fiber structure before and after the cyclic test (Supplementary Fig. 24). The corresponding elemental maps of \n\nLiCl $@$ HGAFs after cyclic test show that Cl element derived from LiCl was uniformly distributed along the holey graphene sheets along with C element, further revealing the satisfactory stability of LiCl@HGAFs (Supplementary Fig. 25). \n\nThe sorption kinetic performance can be expressed by the sorption rate coefficient, which can be determined by the following equation:25 \n\n$$\n\\frac{x}{x_{e q}}=1-e^{-k t}\n$$ \n\nwhere, $\\boldsymbol{x}_{\\mathrm{eq}}$ stands for the equilibrium water sorption quantity $\\mathrm{(g\\thinspaceg\\right.}$ $-1\\gamma$ , $x$ stands for the dynamic water sorption quantity $(\\mathbf{g\\mu}\\mathbf{g}^{-1})$ , k stands for the sorption rate coefficient $(s^{-1})$ , and t stands for sorption time (s). As the salt content increases, the sorption rate coefficient of the fiber decreases from $2.388\\times10^{-4}{{s}}^{{-}{1}}$ for LiCl@HGAFs- $3\\%$ to $1.653\\times10^{-4}{s^{-1}}$ for $\\mathrm{LiCl}@\\mathrm{HGAFs}.7\\%$ (Supplementary Fig. 18a and Supplementary Table 1). This is caused by the increased diffusion resistance due to the hygroscopic salt incorporated into the matrix pores26. In addition, with the increase of humidity, although the specific sorption capacity increases from $0.66\\mathrm{g}\\mathrm{g}^{-1}$ ( $30\\%$ RH) to $4.14{\\mathrm{gg}}$ $^{-1}$ ( $90\\%$ RH), the sorption rate coefficient shows a downward trend (from $2.998\\times10^{-4}{s^{-1}}$ at $30\\%$ RH to $1.653\\times10^{-4}{{s}}^{{-}{1}}$ at $90\\%$ RH). This is because the hygroscopic salt will form a solution during the sorption process, which changes the sorption mechanism from solid adsorption to liquid absorption. As the relative humidity increases, the liquid absorption mechanism will be dominated, leading to a lower sorption rate coefficient or slower mass transfer rate. Still, the sorption rate coefficient of LiCl@HGAFs $\\phantom{+}(1.653\\times10^{-4}\\phantom{+}s^{-1}$ to $2.998\\dot{\\times}10^{-4}s^{-1})$ in this work is higher than that of silica gel impregnated with LiCl, LiBr, and ${\\mathrm{CaCl}}_{2}$ , where the sorption rate coefficient ranges from $9.03\\times10^{-5}{{s}}^{{-1}}$ to $1.49\\times\\dot{1}0^{-4}s^{-1}^{~27}$ . \n\nAdsorption-based heat transfer application based on moisture sorption property. As a multifunctional hygroscopic material, in addition to obtaining water from the air, it can also be used as a thermal energy storage material along with an excellent water sorption property. Adsorption-based heat transfer (AHT) devices, such as adsorption-driven cooling/chiller, adsorption-driven heat pumps, and thermal batteries, have been recently proposed as cutting edge renewable energy alternative solutions to meet the huge global energy demands for heating and cooling28. We further utilize the LiC $@$ HGAFs for heat allocation in AHT devices. A schematic working principle of AHT devices is illustrated in Fig. 4a. AHT system typically operates under a full cycle of water adsorption/desorption. Incorporating the efficient “adsorbentwater“ working pair, AHT devices can operate through the endothermic process of water evaporation or exothermic process of water adsorption29. Adsorption-driven heating can thus operate with the released heat of adsorption $(Q_{\\mathrm{ads}})$ and condensation $(Q_{\\mathrm{cond}})$ . To evaluate our LiCl $@$ HGAFs as sorbents for thermal batteries, we selected LiCl@HGAF-7 because it has a higher working capacity due to the high salt content. The watersorption behavior of LiCl $@$ HGAF-7 was explored at four different temperatures (Fig. 4b). The isotherm curves obtained at four different temperatures $(293\\mathrm{K},\\ 303\\mathrm{K},\\ 313\\mathrm{K},$ and $323\\mathrm{K}$ ) are nearly linear at moderate pressures from 0.15 to 0.7 and can therefore be described by the Freundlich model and S-B-K model (Supplementary Fig. 26, Supplementary Tables 2 and 3)30,31. \n\nThe variable-temperature water vapor isotherms for $\\mathrm{LiCl@H}$ - GAFs are also used to validate a characteristic curve. Two characteristic curves under $303\\mathrm{K}$ and $313\\mathrm{K}$ are close, indicating that the characteristic curve is temperature invariant, justifying its use to calculate isotherms at other temperatures (Supplementary \n\n![](images/767a0c7952a537160470286db63440ba54685f90583bbb37372a89059cb4e3c2.jpg) \nFig. 4 Heat allocation of LiCl@HGAFs. a Working principle of LiCl@HGAF in an ATH device. During the adsorption process, the working fluid water absorbs heat $(Q_{\\mathrm{eva}})$ and evaporates, which is then captured by LiCl@HGAFs to release heat $(Q_{\\mathsf{a d s}})$ . And in the desorption process, the fibers absorb heat $(Q_{\\mathrm{des}})$ to release water vapor, which then condenses in the condenser and releases heat $(Q_{\\mathsf{c o n}})$ . b Water sorption isotherms of LiCl@HGAFs-7 at $293\\mathsf{K},$ $303\\mathsf{K},$ $3131<,$ and $3231$ . Source data are provided as a Source Data file. c Isosteric enthalpy of adsorption for water at LiCl@HGAFs-7 (black) and the corresponding heat storage capacity (red). Source data are provided as a Source Data file. d Comparison of energy density among our $\\mathsf{L i C l}@\\mathsf{H G A F}$ sorbent, the reported MOFs, salt@MOF sorbents, and commercial hygroscopic fibers35, 57–62. Source data are provided as a Source Data file. e Plots of working capacity as a function of driving temperature for cooling conditions $\\cdot T_{\\mathrm{eva}}=283\\mathsf{K},$ $T_{\\mathsf{a d s}}=303\\mathsf{K}$ and $T_{\\mathsf{c o n}}=303\\mathsf{K})$ and heating conditions $(T_{\\mathrm{eva}}=288\\mathsf{K},$ ${\\cal T}_{\\sf a d s}=3131\\sf R,$ and $T_{\\mathsf{c o n}}=313\\mathsf{K})$ . Source data are provided as a Source Data file. f Calculation of the COP values for cooling and heating at different driving temperatures. Source data are provided as a Source Data file. \n\nFig. 27). Therefore, the working capacity of LiCl@HGAF at different temperatures can be obtained. At high temperatures, chemisorption plays a key role in water uptake, while the solution absorption improves water uptake at low temperatures. And the change of water vapor pressure does not significantly affect the capacity of chemical adsorption, but will increase the absorption capacity of the solution. Therefore, the $\\mathrm{LiCl}@\\mathrm{HGAF}$ sorbent shows the flexibility of water uptake at different temperatures and water vapor pressures and becomes more adaptable than most reported adsorbents32–34. \n\nLiCl@HGAF exhibits high working capacity $(w=0.2\\mathrm{g}\\mathrm{g}^{-1})$ ) at $P/P_{0}=0.1$ . It is worth noting that in the thermal application, it is more appropriate for working at low vapor pressure $(P/P_{0}<0.1)$ , which can reduce the use of compressors or increase the evaporation temperature35. The heat storage capacity $(C_{\\mathrm{HS}})$ can be determined by:36 \n\n$$\nC_{\\mathrm{HS}}={\\frac{\\Delta H_{\\mathrm{ads}}\\triangle w}{M_{\\mathrm{w}}}}\n$$ \n\nwhere, $M_{\\mathrm{w}}$ is the water molar weight and $\\Delta H_{\\mathrm{ads}}$ is the isosteric enthalpy of sorption for water, which can be calculated using the Clausius-Clapeyron equation from two adsorption isotherm curves at different temperatures (details in Supplementary Section 1)37. \n\nIt is found that as the water uptake increases, $|\\dot{\\Delta}H_{\\mathrm{ads}}|$ decreases rapidly (from ${\\sim}67\\mathrm{kJmol^{-1}}$ to ${\\tilde{\\sim}}47\\mathrm{kJ}\\mathrm{mol}^{-1}$ ) (Fig. 4c), and that | $\\Delta\\bar{H}_{\\mathrm{ads}}\\dot{\\big|}$ is $63\\mathrm{kJ}\\mathrm{mol}^{-1}$ for a working capacity of $0.6\\mathrm{g}\\mathrm{g}^{-1}$ . The initial high enthalpy of sorption corresponds to the formation of hydrates, where the water molecules are strongly bounded. The \n\n![](images/4e173b896b9a99d90e95e26f40f810d70964c28e39f9ee5f3bb784ca3c6d0784.jpg) \nFig. 5 Heat transfer between the sorbent and the working fluid water for heating and cooling. In the heating mode, the sorbents LiCl@HGAFs capture water molecules and release adsorption heat $(Q_{\\mathsf{a d s}})$ to the house for indoor heating. As the adsorbent will become saturated with water, regeneration is required. Energy is taken up at a relatively high temperature $(Q_{\\mathrm{regen}})$ to desorb the water, which is subsequently condensed, releasing heat at an intermediate temperature $(Q_{\\mathsf{c o n}})$ to the house. Both of the released $Q_{\\mathsf{a d s}}$ and $Q_{\\mathsf{c o n}}$ contribute to indoor heating. In the cooling mode, heat is taken up from the house by the evaporation of the working fluid $(Q_{\\mathrm{eva}}),$ driven by the water sorption of the sorbents $\\mathsf{L i C l}@\\mathsf{H G A F s}$ . \n\nTherefore, one can operate such a switchable sorption cycle as a heat pump to produce heating using $Q_{\\mathsf{c o n}}$ and $Q_{a d s},$ or to produce cooling by using $Q_{\\mathrm{eva}}$ . \n\nsorption enthalpy of this process is the reaction enthalpy of the hydration, which value is usually higher than $60\\mathrm{kJ}\\mathrm{mol}^{-1}$ 32,35. After the water sorption, the enthalpy performs a decrease to $47\\mathrm{kJ}\\mathrm{mol}^{-1}$ , as close as the enthalpy of water evaporation $(44\\mathrm{kJ}\\mathrm{mol}^{-1};$ ), due to the formation of an aqueous LiCl solution. The heat storage capacity $(C_{\\mathrm{HS}})$ for LiCl $@$ HGAF-7 is calculated to be $6.93\\mathrm{kJ}\\mathrm{g}^{-1}$ $(=0.19\\mathrm{kWh\\kg^{-1})}$ , which is 1.68 times higher than that required by the U.S. Department of Energy (DOE) with the value of $0.071\\dot{\\mathrm{kW}}\\mathrm{h}\\ \\mathrm{kg}^{-13}$ 6. Furthermore, in comparison with other reported sorbents, our LiC $@$ HGAFs exhibit greater water uptake within a wide RH range (Fig. 3e) and it has the distinct advantages of high energy density for thermal storage applications (Fig. 4d). \n\nThe coefficient of performance (COP) is defined as useful energy output divided by the required energy as input, which is a commonly adopted indicator of the thermodynamic efficiency of the cycling process and depends strongly on the operating conditions (Fig. 5). The heating model $(\\mathrm{\\dot{C}O P_{H})}$ and cooling model $(\\mathrm{COP_{C})}$ are given by Eqs. 3 and 4, respectively38. \n\n$$\n\\mathrm{COP}_{\\mathrm{H}}=\\frac{-(Q_{\\mathrm{con}}+Q_{\\mathrm{ads}})}{Q_{\\mathrm{regen}}}\n$$ \n\n$$\n\\mathrm{COP}_{\\mathrm{C}}={\\frac{Q_{\\mathrm{eva}}}{Q_{\\mathrm{regen}}}}\n$$ \n\nThe $\\mathrm{COP_{H}}$ values can range from 1 to 2. A high $\\mathrm{COP_{H}}$ value indicates the high energy efficiency in the heating mode. In this work, the $\\mathrm{COP_{H}}^{\\mathrm{-}}$ value obtained at different desorption temperatures is shown in Fig. 4f. The $\\mathrm{COP_{H}}$ is low at low temperature owning to the small working capacity, but it will increase abruptly as the desorption temperature rises (Fig. 4e). When the desorption temperature is $343\\mathrm{K},$ the COP value can reach close to 1.5. As for a heat pump, an evaporator temperature of $288\\mathrm{K},$ a heating or sorption temperature of $313\\mathrm{K},$ and a desorption temperature of $373\\mathrm{K}$ were used. In these conditions, the $\\bar{\\mathrm{COP_{H}}}$ can reach 1.73 for LiCl@HGAF-7. In comparison, the highest $\\mathrm{COP_{H}}$ value (1.65) for salt@silica gel selective water sorbent has been reported in the literature, and the desorption temperature was higher in the range of $398\\mathrm{-}423\\mathrm{K}.$ , requiring more energy input39. For the sorbent-sorbate pairs such as MIL-101-methanol, SG/LiBr-methanol, CAU-3-ethanol, Maxsorb III-ethanol, and Ax-21-ammonia, the $\\mathrm{COP_{H}}$ only ranges from 1.0 to $1.2^{40}$ . \n\nTo evaluate the fiber as sorbents for adsorption chillers, we selected sorption temperature $T_{\\mathrm{ad}}=303\\mathrm{K}$ and evaporation temperature $T_{\\mathrm{evap}}=28\\bar{3}\\mathrm{K}$ in the sorption-based cooling cycle, which is a typical value for practical applications41. The working capacity can be determined as $1.1\\mathrm{g}\\mathrm{\\bar{g}}^{-1}$ due to the complete desorption at $T_{\\mathrm{des}}$ (Fig. 4e). The $\\mathrm{COP_{C}}$ for LiCl $@$ HGAFs-7 can reach 0.7 at the desorption temperature of $373\\mathrm{K}.$ Aside from the $\\mathrm{COP_{C}}$ value, the specific cooling power (SCP) is another factor to demonstrate the efficiency of adsorption chillers. The average SCP is defined as the ratio of cooling power per mass of sorbent per cycle time, which describes the effectiveness of the system during the cooling process25. Finally, an SCP value of 297 W $\\mathrm{Kg^{-1}}$ was calculated (details in Supplementary Note 2), outperforming conventional adsorbents (e.g., silica gel: $63.4\\mathrm{W}\\mathrm{Kg^{-1}}$ ; activated carbon: 65 W $\\mathrm{Kg^{-1}}$ ; zeolite 13-X: $25.7\\mathrm{W}\\mathrm{Kg}^{-1})^{42,43}$ . Our adsorbents demonstrated here encompass the optimal watersorption properties with the high working capacities and specific energy capacities ever attained under adsorption-driven cooling and adsorption-driven heat pump working conditions \n\nEnhancement of microwave absorption performance based on moisture sorption. Water has a frequency-dispersive permittivity in microwave frequencies and high transmittance characteristics, which can be seen as a promising candidate for designing broadband absorbers. Therefore, the fiber may obtain better microwave absorption performance after absorbing moisture. To achieve good absorption, the absorbing material must meet two criteria: (1) The incident electromagnetic wave can fully enter the interior of the material without reflection on the surface. That is, the matching characteristics of the material; (2) The electromagnetic wave entering the material can be quickly attenuated. To explore the microwave absorption performance, the relative complex permittivity (real part $\\varepsilon^{\\prime}$ and imaginary part $\\varepsilon^{\\prime\\prime}$ ) were measured in the frequency range of $1{-}18\\operatorname{GHz}$ via the coaxial line method44,45. $\\varepsilon^{\\prime}$ represents the dielectric and polarization property of material, and $\\varepsilon^{\\bar{\\prime\\prime}}$ stands for the dielectric loss of materials. The $\\varepsilon^{\\prime}$ values of LiCl@HGAFs and ${\\mathrm{LiCl}}@{\\mathrm{HGAFs–H}}_{2}{\\mathrm{O}}$ tend to decrease with the increases in frequency, and the $\\varepsilon^{\\prime\\prime}$ values for $\\operatorname{LiCl@H}.$ - GAFs- $\\mathrm{\\cdotH}_{2}\\mathrm{O}$ reach their extremums at $6{-}8\\operatorname{GHz}$ (Supplementary Fig. 29). The change of complex permittivity of all samples is closely related to the Debye relaxation process in the frequency range. With the effect of the applied electric field, the dipoles in the composites are deflected with the direction of the applied electric field, resulting in polarization loss. When the rearrangement of dipoles cannot keep its rhythm up with the rapidly changing external electromagnetic field, dielectric relaxation loss will occur46. The mechanism of microwave absorption is shown in Fig. 6. The conductivity of holey graphene oxide (HGO) benefits conductivity loss and layered sheet-like HGO could result in multiple microwave reflections and thus further enhance the electromagnetic damping capacity (Fig. 6a). The interface polarization is generated by charge aggregation on the interface between the graphene and LiCl (Fig. 6b), where the oxygencontaining groups and defects on the HGO introduce more polar centers (Fig. 6a–c), and the addition of water further increases the dielectric loss (Fig. 6c). To understand the microwave absorption mechanism of the fiber, Cole-Cole curves were plotted to examine the polarization relaxation behaviors according to Debye relaxation theory (details in Supplementary Note 5)47. $\\operatorname{LiCl@H}.$ GAFs- $\\mathrm{.H}_{2}\\mathrm{O}$ display an undulant curve containing many semicircles and a linear tail representing the multiple polarization relaxations, such as dipolar polarization, interfacial polarization, and electron conduction loss when electromagnetic waves pass through the LiCl $@$ HGAFs- $_{\\mathrm{H}_{2}\\mathrm{O}}$ (Fig. 7g). Moreover, water can interact with wide microwave frequencies and thus exhibit wide microwave absorption. (Fig. 6c)48. \n\n![](images/822524a0bc27e9493052f945899c35c87dfd8b4c51549715e34abcaa623824dd.jpg) \nFig. 6 Schematic diagram of the absorption mechanism. a HGAFs, b LiCl@HGAFs, and c LiCl $@$ HGAFs- $\\cdot{\\sf H}_{2}{\\sf O}$ . The blue-shaded region in panel c refers to the liquid water in the fibers. The absorption mechanism mainly includes conductive loss, interface polarization, and dipole polarization. The incident wave will have multiple reflections in the material, and the above loss process will occur continuously. The dipole polarization process is greatly enhanced when water is present in the material. \n\n![](images/c0e593092ecf12ea3c6339c494743ee49845bf3d37d317f5372c10c3255bcce3.jpg) \nFig. 7 Microwave absorption characterization. Reflection loss (RL) value of a HGAFs, b LiC ${\\mathsf{I}}({\\overline{{a}}}{\\mathsf{H G A F s}},$ and c LiCl@HGAFs- $\\cdot\\mathsf{H}_{2}\\mathsf{O}$ . Source data are provided as a Source Data file. Calculated $\\lvert Z_{\\mathrm{in}}/Z_{0}\\rvert$ values of d HGAFs, e LiC ${\\mathsf{I}}@{\\mathsf{H G A F s}},$ , and f $L i C l@{\\mathsf{H G A F s-H}_{2}}0$ at different thicknesses. Source data are provided as a Source Data file. $\\pmb{\\mathsf{g}}$ Cole-cole plot of LiCl@HGAFs- $H_{2}O$ . Source data are provided as a Source Data file. h The $\\vert{Z_{\\mathrm{in}}}/{Z_{0}}\\vert$ value of HGAFs, LiCl@HGAFs, and $L i C l(\\underline{{\\omega}}H G A F s\\ –H_{2}O$ with a thickness of $2.5\\mathsf{m m}$ . Source data are provided as a Source Data file. i The integrated effective absorption bandwidth (EAB) at the scope of 1–18 GHz. The $\\mathsf{S},\\mathsf{C},\\mathsf{X},$ and $\\mathsf{K u}$ in panel (i) refer to different microwave bands, 2–4 GHz, 4–8 GHz, 8–12 GHz, and 12–18 GHz, respectively. Source data are provided as a Source Data file. \n\ntheory, the electromagnetic wave absorption properties (reflection loss, RL) of different HGAF profiles were calculated (Fig. $\\mathtt{7a-c}$ and Supplementary Fig. 30). Generally, $\\mathrm{RL}\\leq-10$ dB means more than $90\\%$ absorption of electromagnetic waves49. Compared with the HGAF, the microwave absorption performance of $\\bar{\\mathrm{LiCl}}@\\mathrm{HGAF}$ is significantly improved by the enhanced polarization in the HGO network (Figs. 6b and 7b). After filling of $_\\mathrm{H}_{2}\\mathrm{O}$ , $\\mathrm{LiCl}@\\mathrm{HGAF-H_{2}O}$ exhibits a wide-band microwave absorption ranging from $8.31\\mathrm{GHz}$ to $18\\mathrm{GHz}$ at the sample thickness of $2.5\\mathrm{mm}$ and the minimum reflection loss can reach $-27.9\\mathrm{dB}$ at $17.3\\mathrm{GHz}$ (Fig. 7c). Effective absorption bandwidth (EAB) is an important property to evaluate the wideband characteristic of microwave absorbing materials. The acceptable RL value for EAB is $-10.0\\mathrm{dB}$ , which means that the incidence wave is attenuated by $90\\%$ . The integrated EABs of LiCl@HGAF- $_\\mathrm{H}_{2}\\mathrm{O}$ along with some conventional homologous 2D graphene-based microwave absorption materials are displayed in Fig. 7h. In comparison, $\\operatorname{LiCl@HGAF}.$ - $_\\mathrm{H}_{2}\\mathrm{O}$ presents an excellent wideband EM absorption ability with almost integrated EAB covering all of Ku band, X band, C band, and even part of S band. Compared with $\\mathrm{LiCl@HGAF}$ , $\\mathrm{LiCl}@\\mathrm{HGAF}–\\mathrm{H}_{2}\\mathrm{O}$ has unique advantages in broadband microwave absorption. However, as the water content increases, the reflection loss of the samples $(2.5\\mathrm{mm})$ increases first and then decreases (Supplementary Fig. 30g). This is due to the excessive water content makes the impedance matching worse (Supplementary Fig. 31b–e). Impedance matching is a crucial factor for microwave absorption performance, which describes the ability of electromagnetic wave attenuation by generating more input impedance rather than reflection to the air. The impedance matching $\\begin{array}{r}{(Z=\\left|Z_{\\mathrm{in}}/Z_{0}\\right|}\\end{array}$ , Fig. 7d–f) between materials and space is calculated by Supplementary Note 4. When the value of $\\lvert Z_{\\mathrm{in}}/Z_{0}\\rvert$ is close to 1 (the impedance of free space), the sample would exhibit good impedance match performance, which is a prerequisite for excellent microwave absorption. As shown in Fig. 7h and Supplementary Fig. 25, both HGAF, LiCl@HGAF show relatively poor impedance matching areas in the range of 0.8–1.2. However, the impedance matching area of $_{\\mathrm{LiCl}@\\mathrm{HGAF-H}_{2}O}$ in this range increases markedly, revealing that the impedance matching has been obtained successfully with the confinement of water (Fig. 6c). To obtain high microwave absorption performance, the material needs to not only meet impedance match, but also a large attenuation constant (α) is required to satisfy the large energy $\\log{50}$ . The attenuation constant α (details in Supplementary Section 2) determines the attenuation capability of the input electromagnetic waves51. Here, the $\\alpha$ values decrease with improving the water content in the $\\mathrm{LiCl}@\\mathrm{HGAF}-7$ (Supplementary Fig. 32). Although the sample with a water content of $2{\\bf g}{\\bf g}^{-1}$ exhibits a moderate $\\mathfrak{a}.$ , the impedance matching allows EM waves to enter the absorbing materials as much as possible, which is the prerequisite to obtain a better EM wave absorbing property52. Since the microwave absorption stability of hygroscopic holey graphene aerogel fibers containing water is crucial in real applications, we characterized the long-time stability of $\\mathrm{LiCl@H}$ - GAF- $_\\mathrm{\\cdotH_{2}O}$ fibers in an electromagnetic environment with the power of $+10$ dBm. The samples with variant thicknesses exhibit stable microwave sorption behavior up to $^{12\\mathrm{h}}$ (Supplementary Fig. 33a–f). The maximum absorptivity of the fibers was above $99\\%$ invariably (Supplementary Fig. 33g). \n\n# Discussion \n\nIn summary, we report a strategy to develop LiCl@HGAFs with superior moisture capture, heat allocation, and microwave absorption functionalities. The hygroscopic nature of LiCl, combined with the high surface area and interconnected porous network of graphene host fiber, ensure that LiCl@HGAF obtains ultra-high water sorption capacity and uptake kinetics. Besides, due to the outstanding photo-thermal and electro-thermal effects, the $\\operatorname{LiCl}(\\omega$ HGAFs can realize the regeneration in multiple pathways and with low energy input. On the other hand, the LiCl@HGAFs are demonstrated in the adsorption-based heat transfer devices with high heat storage capacity and desirable coefficient of performance both in the heating mode and cooling mode. The incorporation of efficient “adsorbent-water” in our AHT devices is an attractive alternative solution to develop a green and sustainable technology to meet the surge in global energy demands for heating and cooling. Furthermore, when containing saline water in the porous confinements, the LiCl@HGAFs can effectively absorb the electromagnetic wave in a wide range of bandwidth, with outstanding impedance matching and a large attenuation coefficient. In short, the holey graphene aerogel fibers combining with hygroscopic LiCl salt introduced here may offer important alternatives for developing multifunctional materials for water harvest, thermal energy utilization, and microwave adsorption, as well as open unexplored opportunities for aerogel fiber-related technology in various applications. It is envisioned that our results will also spur future efforts for the development of advanced adsorbents, dehumidifiers, sorption-based heat transfer systems, adsorption-driven refrigeration, and beyond. \n\n# Methods \n\nGeneral. The experimental materials and detailed calculations for heat allocation and microwave absorption applications are given in the Supplementary Methods. \n\nSynthesis of GO. GO aqueous dispersion was prepared from natural graphite powder according to a modified Hummers method53. Briefly, $12{\\mathrm{g}}$ graphite powder, $100\\mathrm{ml}$ $\\mathrm{H}_{2}\\mathrm{SO}_{4};$ , $10\\mathrm{g}\\mathrm{K}_{2}\\mathrm{S}_{2}\\mathrm{O}_{8},$ and $10\\mathrm{~g~P}_{2}\\mathrm{O}_{5}$ were added to a $250\\mathrm{ml}$ flask and the mixture was kept at $80^{\\circ}\\mathrm{C}$ for $4.5\\mathrm{h}$ . After cooling to room temperature, the mixture was diluted with 1 L water and vacuum-filtered and washed with water using a $0.22\\mathrm{-}\\upmu\\mathrm{m}$ pore polycarbonate membrane. After drying, the $^{4}{\\bf g}$ solid was added into $160\\mathrm{ml}$ concentrated $\\mathrm{H}_{2}\\mathrm{SO}_{4}$ $(0^{\\circ}\\mathrm{C})$ , and then $20\\mathrm{g}\\mathrm{KMnO_{4}}$ was added slowly under continuous stirring. After the introduction of $\\mathrm{KMnO_{4}},$ the mixture was heated to $35^{\\circ}\\mathrm{C}$ and stirred for $^{2\\mathrm{h}}$ . The mixture was then diluted with $1.2\\mathrm{L}$ water, followed by dropwise addition of $10\\ \\mathrm{ml}\\ 30\\%\\ \\mathrm{H}_{2}\\mathrm{O}_{2}$ . Using the centrifugation washing method, the precipitate was repeatedly washed with water, 1 M HCl solution, and water successively. Finally, we obtained GO aqueous dispersions after ultrasonication for $^{2\\mathrm{h}}$ . \n\nSynthesis of holey graphene oxide-LC. The holey graphene oxide was synthesized according to our previous work20. Briefly, $50\\mathrm{ml}$ $\\mathrm{H}_{2}\\mathrm{O}_{2}$ $30\\%$ aqueous solution) was added into $500\\mathrm{ml}\\mathrm{GO}$ aqueous dispersion $(2\\mathrm{mg/ml})$ and stirred for $10\\mathrm{min}$ to obtain a uniform mixture. And the mixture was then heated at $100^{\\circ}\\mathrm{C}$ under stirring for different periods. The reaction time of the mixture was 0.5, 1, 1.5, $^{2\\mathrm{h},}$ respectively, denoted as HGO-1, HGO-2, HGO-3, and HGO-4. Then the mixture was centrifuged and washed with water 3 times to remove the impurities. Finally, the obtained HGO aqueous dispersion was concentrated by centrifuging at a high speed for $^{4\\mathrm{h}}$ to obtain HGO-LC. \n\nPreparation of holey graphene aerogel fiber. The holey graphene oxide liquid crystal $(25\\mathrm{mg/ml})$ was spinning into $0.5\\mathrm{wt\\%}\\mathrm{CaCl_{2}}$ aqueous solution and the obtained holey graphene oxide hydrogel fiber was immersed into $10\\%$ hydroiodic acid aqueous solution at $60^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ . Followed by washing at least four times with absolute ethyl alcohol to replace the water and supercritical drying with $\\mathrm{CO}_{2}$ $(40^{\\circ}\\mathrm{C},10\\mathrm{MPa})$ for $12\\mathrm{h}$ the HGAF was obtained. \n\nAging effect of HGAF. The as-prepared holey graphene oxide hydrogel fibers were aged for 1, 2, and 3 days at room temperature. Then the fibers were immersed into $10\\%$ hydroiodic acid aqueous solution at $60^{\\circ}\\mathrm{C}$ for $^{5\\mathrm{h}}$ . After that, they were washed at least four times with absolute ethyl alcohol to replace the water followed by supercritical drying with $\\mathrm{CO}_{2}$ $(40^{\\circ}\\mathrm{C},10\\mathrm{MPa}),$ for $12\\mathrm{h}$ . Then, the specific surface area, electrical conductivity, tensile strength, and average diameter of the aged fibers were characterized. \n\nPreparation of LiCl@holey graphene aerogel fiber. The impregnation method was applied to coat LiCl into holy graphene aero fibers. The periods of LiCl solutions (concentration of $3\\%$ , $5\\%$ , $7\\%$ , respectively) were prepared by adding LiCl particles to water and stirring for $30\\mathrm{min}$ . The samples were LiCl@HGAF-3, LiCl@HGAF-5, and LiCl@HGAF-7. Subsequently, the holey graphene aerogel fiber was impregnated to the solution for $24\\mathrm{h}$ . Due to the hydrophobicity of holey graphene aerogel fiber, the fiber was difficult to submerge in LiCl solution. Therefore, we infiltrated the fiber with ethanol before the impregnating process. Finally, the freeze-drying process was carried out. \n\nCharacterizations. The morphologies and structures of holey graphene aerogel fibers and LiCl@holey graphene aerogel fibers were characterized by a scanning electron microscope (S-4800) operated at $15\\mathrm{kV}$ and a transmission electron microscope (Tecnai G2 F20 S-Twin). $\\Nu_{2}$ gas adsorption isotherms were measured with a physisorption apparatus (ASAP 2020, Micromeritics Instrument) at $77\\mathrm{K}$ . Raman spectra were recorded on a LabRam HR Raman spectrometer with 50 W He-Ne laser operating at $632\\mathrm{nm}$ with a CCD deter. X-ray diffraction (XRD) patterns were recorded on a D8 Advanced spectrometer with an angular range of $10{-}90^{\\circ}$ (2 thetas). Thermal gravimetric analysis and DTG were carried out using a TG 209F1 Libra (NETZSCH) analyzer with a heating rate of $10^{\\circ}\\mathrm{C}\\operatorname*{min}^{-1}$ in a nitrogen atmosphere. DSC analysis was performed on a DSC 200F3 NETZSCH with a heating and cooling rate of $10^{\\circ}\\mathrm{C}\\mathrm{min}^{-1}$ . The electric resistances of the aerogel and its composites were measured by using a CHIChief 600D electrochemical workstation, and the electric conductivity can be calculated by the equation: $\\kappa=I L/U S.$ , where $\\kappa$ is the electric conductivity, $I$ is the current that crosses the sample, $U$ is the voltage applied in the sample, $L$ is the length of sample current goes through, and S is the cross area of current. The stress-strain curves were measured by an Instron 3365 tensile testing machine and the bending stiffness can be calculated by the equation: $R_{\\mathrm{f}}=\\pi E D^{4}/6\\bar{4}$ , where $E$ is the elastic modulus, $D$ is the average diameter of the fiber. The contact angle was measured by OCA 15EC DataPhysics Instruments GmbH. Infrared photos were taken with a MinIR (M1100150) camera. The XPS spectra were measured by Escalab 250Xi, Thermo Scientific. The temperature-time curves were measured and recorded by the thermal couple and Keysight 34970 Data Acquisition. Water vapor adsorption isotherms were measured by a volumetric method using a volume method vapor sorption analyzer (BSD-PMV2) at the temperature of ${2\\bar{9}3\\mathrm{K},303\\mathrm{K},313\\mathrm{K},}$ and $323\\mathrm{K}.$ . Before the measurement, the sample was pre-activated at $100^{\\circ}\\mathrm{C}$ for $^{6\\mathrm{h}}$ to remove all residual water. The sorption kinetics curves and cyclic capacity were measured in a glove box with a balance measuring the weight of the fibers under a constant temperature and humidity. The cycle test was performed at $25^{\\circ}\\mathrm{C},$ · $90\\mathrm{RH\\%}$ for $^{6\\mathrm{h}}$ for adsorption, and at $10\\mathrm{RH\\%}$ , $60^{\\circ}\\mathrm{C}$ for $60\\mathrm{min}$ for desorption. \n\n# Dehumidification experiment of different moisture sorption materials. \n\nLiCl@HGAFs, as well as other moisture sorption materials including colorchanging silica gel (methyl violet@silical gel), commercial hygroscopic fibers (EKS fibers from TOYOBO CO., LTD), LiCl, UiO-66 (zirconium 1,4-dicarboxybenzene MOF), LiCl@UiO-66, active carbon fiber loaded with lithium chloride $({\\mathrm{LiCl}}(\\omega{\\mathrm{ACF}})$ , were conducted with the dehumidification experiment. A series of moisture sorption materials in two sets of experiments were prepared for the dehumidification test. One group of them were in the same mass $(2\\mathrm{g})$ , and the other group of them were in the same packing volume $(5~\\mathrm{cm}^{3})$ . At room temperature, the sorption materials were placed in a sealed chamber with a size of $\\overline{{60^{*}50^{*}50}}\\mathrm{cm}$ and an initial relative humidity of $90\\%$ , and the relative humidity in the chamber was detected after $^{6\\mathrm{h}}$ . \n\nMicrowave sorption stability of LiCl@HGAF- $\\mathbf{\\boldsymbol{H}}_{2}\\mathbf{\\boldsymbol{O}}$ . We placed the LiCl@HGAF$\\mathrm{H}_{2}\\mathrm{O}$ in the testing chamber and set the test power to $+10$ dBm $(\\mathrm{{10}m W})$ to keep the materials in the electromagnetic environment all the time. After that, this test was conducted every $^{2\\mathrm{h}}$ to obtain the changes in the microwave absorption properties of the materials. \n\n# Data availability \n\nAll data generated in this study are provided in the Supplementary Information/Source Data file or from the corresponding author upon request. Source data are provided with this paper. \n\nReceived: 6 September 2021; Accepted: 17 February 2022; Published online: 09 March 2022 \n\n# References \n\n1. Xu, X. et al. Double-negative-index ceramic aerogels for thermal superinsulation. Science 363, 723 (2019). \n2. Zhao, S. et al. Additive manufacturing of silica aerogels. Nature 584, 387 (2020). \n3. Liu, Z. et al. Nanofibrous kevlar aerogel threads for thermal insulation in harsh environments. ACS Nano 13, 5703 (2019). \n4. Du, Y. et al. Reaction-spun transparent silica aerogel fibers. ACS Nano 14, 11919 (2020). \n5. Wang, Z. et al. Robust silk fibroin/graphene oxide aerogel fiber for radiative heating textiles. ACS Appl. Mater. Interfaces 12, 15726 (2020). \n6. Li, G. et al. Multiresponsive graphene-aerogel-directed phase-change smart fibers. Adv. Mater. 30, 1801754 (2018). \n7. Li, X. et al. Polyimide aerogel fibers with superior flame resistance, strength, hydrophobicity, and flexibility made via a universal sol-gel confined transition strategy. ACS Nano 15, 4759–4768 (2021). \n8. Meng, S. et al. Construction of continuous hollow silica aerogel fibers with hierarchical pores and excellent adsorption performance. Micropor. Mesopor. Mater. 273, 294–296 (2019). \n9. Wordsworth, R. et al. Enabling martian habitability with silica aerogel via the solid-state greenhouse effect. Nat. Astron. 3, 898–903 (2019). \n10. Xu, Z. et al. Strong, conductive, lightweight, neat graphene aerogel fibers with aligned pores. ACS Nano 6, 7103–7113 (2012). \n11. Bi, H. et al. Carbon fiber aerogel made from raw cotton: a novel, efficient and recyclable sorbent for oils and organic solvents. Adv. Mater. 25, 5916–5921 (2013). \n12. Li, Y. et al. Electrically conductive, optically responsive, and highly orientated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene aerogel fibers. Adv. Funct. Mater. 31, 2107767 (2021). \n13. Olsson, R. T. et al. Making flexible magnetic aerogels and stiff magnetic nanopaper using cellulose nanofibrils as templates. Nat. Nanotechnol. 5, 584–588 (2010). \n14. Wu, X. et al. Electroless plating of graphene aerogel fibers for electrothermal and electromagnetic applications. Langmuir 35, 3814–3821 (2019). \n15. Sheng, Z. et al. Solid-liquid host-guest composites: the marriage of porous solids and functional liquids. Adv. Mater. 33, 2104851 (2021). \n16. Li, J. et al. Symbiotic aerogel fibers made via in-situ gelation of aramid nanofibers with polyamidoxime for uranium extraction. Molecules 24, 1821 (2019). \n17. Donkers, P. A. J. et al. A review of salt hydrates for seasonal heat storage in domestic applications. Appl. Energy 199, 45–68 (2017). \n18. Qiu, H. et al. Magnetothermal microfluidic-assisted hierarchical microfibers for ultrahigh-energy-density supercapacitors. Angew. Chem. Int. Ed. 59, 7934–7943 (2020). \n19. Li, X. et al. Supercapacitor electrode materials with hierarchically structured pores from carbonization of MWCNTs and ZIF-8 composites. Nanoscale 9, 2178–2187 (2017). \n20. Li, G. et al. High-efficiency cryo-thermocells assembled with anisotropic holey graphene aerogel electrodes and a eutectic redox electrolyte. Adv. Mater. 31, e1901403 (2019). \n21. Xu, Y. et al. Solution processable holey graphene oxide and Its derived macrostructures for high-performance supercapacitors. Nano Lett. 15, 4605 (2015). \n22. Sun, H. et al. Three-dimensional holey-graphene/niobia composite architectures for ultrahigh-rate energy storage. Science 356, 599–604 (2017). \n23. Li, R. et al. Harvesting water from air: using anhydrous salt with sunlight. Environ. Sci. Technol. 52, 5398–5406 (2018). \n24. Xu, J. et al. Ultrahigh solar-driven atmospheric water production enabled by scalable rapid-cycling water harvester with vertically aligned nanocomposite sorbent. Energy Environ. Sci. 14, 5979–5994 (2021). \n25. Gordeeva, L. G. et al. $\\mathrm{NH}_{2}$ -MIL-125 as a promising material for adsorptive heat transformation and storage. Energy 100, 18–24 (2016). \n26. Dawoud, B. et al. Experimental study on the kinetics of water vapor sorption on selective water sorbents, silica gel and alumina under typical operating conditions of sorption heat pumps. Int. J. Heat. Mass Transf. 46, 273–281 (2003). \n27. Zheng, X. et al. Performance study of composite silica gels with different pore sizes and different impregnating hygroscopic salts. Chem. Eng. Sci. 120, 1–9 (2014). \n28. Nandakumar, D. K. et al. A super hygroscopic hydrogel for harnessing ambient humidity for energy conservation and harvesting. Energy Environ. Sci. 11, 2179–2187 (2018). \n29. Cho, K. H. et al. Defective Zr-fumarate MOFs enable high-efficiency adsorption heat allocations. ACS Appl. Mater. Interfaces 13, 1723–1734 (2021). \n30. Mohammed, R. H. et al. Revisiting the adsorption equilibrium equations of silica-gel/water for adsorption cooling applications. Int. J. Refrig. 86, 46–47 (2018). \n31. Saha, B. B. et al. Computer simulation of a silica gel water adsorption refrigeration cycle - the influence of operating conditions on cooling output and COP. ASHRAE Trans. 101, 348–357 (1995). \n32. Kim, H. Y. et al. Water harvesting from air with metal-organic frameworks powered by natural sunlight. Science 356, 430–434 (2017). \n33. AbdulHalim, R. G. et al. A fine-tuned metal-organic framework for autonomous indoor moisture control. J. Am. Chem. Soc. 139, 10715–10722 (2017). \n34. Ma, D. et al. A hydrolytically stable vanadium(IV) metal-organic framework with photocatalytic bacteriostatic activity for autonomous indoor humidity control. Angew. Chem. Int. Ed. 59, 3905–3909 (2020). \n35. Furukawa, H. et al. Water adsorption in porous metal-organic frameworks and related materials. J. Am. Chem. Soc. 136, 4369 (2014). \n36. Advanced Research Projects Agency-DOE, HEATS Program Overview. https://arpae.energy.gov/sites/default/files/documents/files/ HEATS_ProgramOverview.pdf,accessed. (2016). \n37. Yan, J. et al. Adsorption isotherms and kinetics of water vapor on novel adsorbents MIL- $101(\\mathrm{Cr})@\\mathrm{GO}$ with super-high capacity. Appl. Therm. Eng. 84, 118–125 (2015). \n38. Cho, K. H. et al. Rational design of a robust aluminum metal-organic framework for multi-purpose water-sorption-driven heat allocations. Nat. Commun. 11, 5112 (2020). \n39. Aristov, Y. R. et al. A family of new working materials for solid sorption air conditioning systems. Appl. Therm. Eng. 22, 191-204 (2002). \n40. Boman, D. B. et al. Screening of working pairs for adsorption heat pumps based on thermodynamic and transport characteristics. Appl. Therm. Eng. 123, 422–434 (2017). \n41. Canivet, J. et al. Water adsorption in MOFs: fundamentals and applications. Chem. Soc. Rev. 43, 5594 (2014). \n42. Tso, C. Y. et al. Activated carbon, silica-gel and calcium chloride composite adsorbents for energy efficient solar adsorption cooling and dehumidification systems. Int. J. Refrig. 35, 1626–1638 (2012). \n43. Wang, D. C. et al. Study of a novel silica gel–water adsorption chiller. Part I. Design and performance prediction. Int. J. Refrig. 28, 1073–1083 (2005). \n44. Che, R. C. et al. Microwave absorption enhancement and complex permittivity and permeability of Fe encapsulated within carbon nanotubes. Adv. Mater. 16, 401–405 (2004). \n45. Sun, H. et al. Cross-stacking aligned carbon-nanotube films to tune microwave absorption frequencies and increase absorption intensities. Adv. Mater. 26, 8120 (2014). \n46. Wang, Y. et al. Synthesis of polyaniline nanorods and $\\mathrm{Fe}_{3}\\mathrm{O}_{4}$ microspheres on graphene nanosheets and enhanced microwave absorption performances. Mater. Chem. Phys. 209, 23–30 (2018). \n47. Xiang, Z. et al. Rational construction of hierarchical accordion-like Ni@porous carbon nanocomposites derived from metal-organic frameworks with enhanced microwave absorption. Carbon 167, 364–377 (2020). \n48. Xiong, H. et al. Ultra-broadband and tunable saline water-based absorber in microwave regime. Opt. Express 28, 5306–5316 (2020). \n49. Gopakumar, D. A. et al. Cellulose nanofiber-based polyaniline flexible papers as sustainable microwave absorbers in the X-band. ACS Appl. Mater. Interfaces 10, 20032–20043 (2018). \n50. Huang, X. et al. Water-injected all-dielectric ultra-wideband and prominent oblique incidence metamaterial absorber in microwave regime. J. Phys. D Appl. Phys. 50, 385304 (2017). \n51. Zhang, Y. et al. Sorption thermal energy storage: concept, process, applications and perspectives. Energy Stor. Mater. 27, 352–369 (2020). \n52. Wu, Q. et al. Facile synthesis of Co-embedded porous spherical carbon composites derived from $\\mathrm{Co_{3}O_{4}}/\\mathrm{ZIF}{-8}$ compounds for broadband microwave absorption. Compos. Sci. Technol. 195, 108206 (2020). \n53. Li, G. et al. From anisotropic graphene aerogels to electron- and photo-driven phase change composites. J. Mater. Chem. A 4, 17042–17049 (2016). \n54. Matsumoto, K. et al. Thermo-responsive gels that absorb moisture and ooze water. Nat. Commun. 9, 2315 (2018). \n55. Garzón-Tovar, L. et al. Composite salt in porous metal-organic frameworks for adsorption heat transformation. Adv. Funct. Mater. 27, 1606424 (2017). \n56. Zhang, Y. et al. Super hygroscopic nanofibrous membrane-based moisture pump for solar-driven indoor dehumidification. Nat. Commun. 11, 3302 (2020). \n57. Xie, P. et al. Tunneling-induced negative permittivity in Ni/MnO nanocomposites by a bio-gel derived strategy. J. Mater. Chem. C 8, 3029–3039 (2020). \n58. de Lange, M. F. Adsorption-driven heat pumps: the potential of metal-organic frameworks. Chem. Rev. 115, 12205 (2015). \n59. Wang, S. et al. A robust large-pore zirconium carboxylate metal–organic framework for energy-efficient water-sorption-driven refrigeration. Nat. Energy 3, 985–993 (2018). \n60. Permyakova, A. et al. Design of salt–metal organic framework composites for seasonal heat storage applications. J. Mater. Chem. A 5, 12889–12898 (2017). \n61. Kallenberger, P. A. et al. Alginate-derived salt/polymer composites for thermochemical heat storage. Adv. Sustain. Syst. 2, 1700160 (2018). \n62. Grekova, A. et al. Composite sorbents “Li/Ca halogenides inside Multi-wall Carbon Nano-tubes” for Thermal Energy Storage. Sol. Energy Mater. Sol. Cells \n155, 176–183 (2016). \n\n# Acknowledgements \n\nThis work was supported by the National Key Research and Development Program of China (no. 2020YFB1505703) to Z.S., the Royal Society Newton Advanced Fellowship (no. NA170184) to X.Z., the National Science Fund for Distinguished Young Scholars (no. 52025034) to J.K., the National Natural Science Foundation of China (no. 52173052) to X.Z., the National Science Foundation of Jiangsu Province (no. BK20211099) to Z.S., and the Youth Innovation Promotion Association of Chinese Academy of Sciences (no. 2022325) to Z.S. We appreciate the beneficial discussion of theoretical data fitting with Dr. Mengchuang Zhang and Zhizhuo Zhang from Northwestern Polytechnical University. \n\n# Author contributions \n\nX.Z. supervised the project. Y.H., Z.S., and J.K. conceived and designed the experiments. Y.H. performed experiments and acquired data. Y.H., Z.S., J.K., and X.Z. analyzed the data and drafted the manuscript. All authors supported revising the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-28906-4. \n\nCorrespondence and requests for materials should be addressed to Jie Kong or Xuetong Zhang. \n\nPeer review information Nature Communications thanks Bidyut Baran Saha, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\n# Reprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41467-021-27914-0", + "DOI": "10.1038/s41467-021-27914-0", + "DOI Link": "http://dx.doi.org/10.1038/s41467-021-27914-0", + "Relative Dir Path": "mds/10.1038_s41467-021-27914-0", + "Article Title": "Guest-host doped strategy for constructing ultralong-lifetime near-infrared organic phosphorescence materials for bioimaging", + "Authors": "Xiao, FM; Gao, HQ; Lei, YX; Dai, WB; Liu, MC; Zheng, XY; Cai, ZX; Huang, XB; Wu, HY; Ding, D", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Organic near-infrared room temperature phosphorescence materials have unparalleled advantages in bioimaging due to their excellent penetrability. However, limited by the energy gap law, the near-infrared phosphorescence materials (>650 nm) are very rare, moreover, the phosphorescence lifetimes of these materials are very short. In this work, we have obtained organic room temperature phosphorescence materials with long wavelengths (600/657-681/732 nm) and long lifetimes (102-324 ms) for the first time through the guest-host doped strategy. The guest molecule has sufficient conjugation to reduce the lowest triplet energy level and the host assists the guest in exciton transfer and inhibits the non-radiative transition of guest excitons. These materials exhibit good tissue penetration in bioimaging. Thanks to the characteristic of long lifetime and long wavelength emissive phosphorescence materials, the tumor imaging in living mice with a signal to background ratio value as high as 43 is successfully realized. This work provides a practical solution for the construction of organic phosphorescence materials with both long wavelengths and long lifetimes.", + "Times Cited, WoS Core": 288, + "Times Cited, All Databases": 296, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000849942600001", + "Markdown": "# Guest-host doped strategy for constructing ultralong-lifetime near-infrared organic phosphorescence materials for bioimaging \n\nFuming Xiao1,4, Heqi Gao2,4, Yunxiang Lei1✉, Wenbo Dai3, Miaochang Liu1, Xiaoyan Zheng 3, Zhengxu Cai 3, Xiaobo Huang1✉, Huayue Wu1 & Dan Ding 2✉ \n\nOrganic near-infrared room temperature phosphorescence materials have unparalleled advantages in bioimaging due to their excellent penetrability. However, limited by the energy gap law, the near-infrared phosphorescence materials $>650\\mathsf{n m},$ ) are very rare, moreover, the phosphorescence lifetimes of these materials are very short. In this work, we have obtained organic room temperature phosphorescence materials with long wavelengths (600/657–681/732 nm) and long lifetimes ( $102-324\\mathrm{ms},$ for the first time through the guest-host doped strategy. The guest molecule has sufficient conjugation to reduce the lowest triplet energy level and the host assists the guest in exciton transfer and inhibits the non-radiative transition of guest excitons. These materials exhibit good tissue penetration in bioimaging. Thanks to the characteristic of long lifetime and long wavelength emissive phosphorescence materials, the tumor imaging in living mice with a signal to background ratio value as high as 43 is successfully realized. This work provides a practical solution for the construction of organic phosphorescence materials with both long wavelengths and long lifetimes. \n\nRfrorioaolmsm tweitemhnpvpeireaortsniusmrtenpthaelosmpishesolifro-elnsuscmecniancne c(meRitnTicgPea.)teoftMhoeorigenaotnveiercfermeatnthceeorganic matter often has advantages of low toxicity and good biocompatibility1–10. Therefore, constructing organic RTP materials would benefit tissue imaging, tumor diagnosis, and drug tracking10–15. To date, most phosphorescent materials have poor biological tissue permeability because the wavelengths of their emission spectra are short (less than $580\\mathrm{nm})^{9,16-\\widetilde{2}6}$ . This only means phosphors provide good imaging in shallow regions of an organism. Constructing near-infrared phosphorescent materials has gained some urgency. Although some red RTP materials such as boron fluoride, carbazole, and naphthalene diimides have been developed, those with wavelengths exceeding $650\\mathrm{nm}$ are rare27–32. Moreover, presumably limited by the energy gap law, phosphorescence lifetimes of these red RTP materials are very short and not conducive for bioimaging (Fig. 1a and Supplementary Fig. 1). \n\nEstablishing ultralong-lifetime RTP materials with longwavelength emission inevitably means lowering the lowest triplet $\\left(\\mathrm{T}_{1}\\right)$ level of the material. However, lower $\\mathrm{T}_{1}$ levels bring two major obstacles to phosphorescence. One of the obstacles is that lower $\\mathrm{T}_{1}$ increases the band gap between $\\mathsf{S}_{1}$ and $\\mathrm{T}_{1}\\left(\\Delta E_{\\mathrm{ST}}\\right)$ , which is not conducive to intersystem crossing (ISC) of excitons. The other obstacle is that a lower $\\mathrm{T}_{1}$ level easily causes excitons to be consumed non-radiatively, resulting in a significant reduction in lifetime and intensity of phosphorescence (Fig. 1b). Therefore, assuming materials already have low $\\mathrm{T}_{1}$ , improving the ISC capability of excitons and suppressing the non-radiative transitions of excitons are key in achieving ultralong-lifetime nearinfrared/NIR phosphorescence. Recently, guest–host materials have gradually attracted more attention33–40, because the host molecules can inhibit the non-radiative transition of the guest energy in the guest–host system41–46. Additionally, several research results have shown that there is a synergy of energy between host and guest molecules, which can assist the guest molecules to transfer the excited state energy effectively38–42. Therefore, the guest–host system provides a new strategy for the construction of organic RTP materials with long-wavelength emissions and long lifetimes. \n\nWith that in mind, we tried to construct ultralong-lifetime near-infrared RTP materials employing a guest–host doped strategy. The pyrene derivatives with high conjugation are regarded as guests. Their high conjugation can reduce the $\\mathrm{T}_{1}$ levels of the molecules, thereby ensuring that the resultant materials undergo long-wavelength phosphorescence. The benzophenone (BPO) compound is chosen as the host matrix, which can act as two roles. One role is associated with assisting transfers of guest excitons; the other role is associated with restricting the motion of the guest molecules, thereby suppressing the nonradiative transition of guest excitons (Fig. 1c). The results show that the designed guest–host materials have strong red afterglow visible to the naked eye. By increasing the degree of conjugation of the guest molecules, phosphorescence wavelengths of the guest–host materials are red-shifted from $600/657\\mathrm{nm}$ to $681/$ $732{\\mathrm{nm}}$ . More importantly, our newly developed guest–host materials have long phosphorescence lifetimes of $102{-}324\\mathrm{ms}$ . To the best of our knowledge, this is the first RTP material with both long-wavelength $(>700\\mathrm{nm})$ and long lifetime $(>100\\mathrm{ms})$ simultaneously. Comparative experiments of the molten state and the crystalline state prove that the host matrix restricts the motion of guest molecules is a necessary condition for the doped system to have phosphorescence emission. Molecular dynamics (MD) simulations further show that between host and guest there is a strong interaction that suppresses non-radiative transitions of guest excitons. Moreover, experimental results also confirm that host molecules exhibit synergies with guest molecules in excited states. As a proof-of-concept, the materials were used for precise mapping of lymph nodes and labeling of armpit tumors with high signal-to-background ratios (SBR) of 55 and 43, respectively. The long wavelengths help to reduce scattering from tissue and long lifetimes further mitigate the interference from autofluorescence in bioimaging. Thus, phosphorescent materials with both kinds of properties can provide more unambiguous imaging of tumors. \n\n# Results \n\nSynthesis and photophysical properties. The guest molecules are based on the pyrene unit, to which adding anisole or $N,N.$ \n\n![](images/ffe7fbf5e3ff6472122598f8040ddbbd1f1756a95622d2c09aec57edbd2a9412.jpg) \nFig. 1 Design concept of the guest/host system. a Problems in constructing ultralong near-infrared RTP materials b Phosphorescence performance distribution of RTP materials. c Strategy used in this work for constructing ultralong near-infrared RTP materials. \n\n![](images/c0e6c2fe1ab4c5f891e8a953d6dff479a1193ffdb57083ff40be17584ac60e0a.jpg) \nFig. 2 Photoluminescence properties of the guest–host system. a Molecular structures of the guest and host molecules. b Fluorescence (top) and phosphorescence (down) images of the guest–host materials. c Phosphorescence spectra of host–guest materials. Excitation wavelength: $380\\mathsf{n m}$ ; Delayed time: 1 ms. d Phosphorescence decay curves of guest–host materials. Excitation wavelength: $380\\mathsf{n m}$ . \n\ndimethylaniline groups on one or both sides through the Suzuki reaction increases the molecular conjugation (Fig. 2a and Supplementary Fig. 2). The five guests show good solubility in chloroform, tetrahydrofuran, and dimethyl sulfoxide. The molecular structures and purities of the target compounds were confirmed by NMR spectroscopy, single-crystal X-ray diffraction, and high-performance liquid chromatography (Supplementary Figs. 3, 4). As guest conjugation increases, the maximum absorption peaks are red-shifted from 343 to $378\\mathrm{nm}$ (Supplementary Fig. 5a), and the corresponding fluorescence peaks are also red-shifted from 381 to $467\\mathrm{nm}$ (Supplementary Fig. 5b). The host BPO was purchased directly from a commercial supplier and used without further processing. BPO has a low melting point $(48^{\\circ}\\mathrm{C})$ and stable subcooling states and thus the guest molecules can be dispersed in the host using the melt-casting method (The detailed process is in the supplementary information). Because the concentration of the guest molecules is very important in determining the RTP properties of the guest–host materials, we first prepared a series of Py/BPO guest–host materials with different guest–host molar ratios (1:50–1:50000) to optimize the luminescence performance. The phosphorescence quantum yields of 1:50, 1:100, 1:500, 1:1000, 1:5000, 1:10000, and 1:50000 are 3.3, 5.5, 7.8, 9.2, 6.8, 5.1, and $3.6\\%$ , respectively. The delayed emission spectra further shows that doped material with the guest–host molar ratio of 1:1000 has the strongest phosphorescence intensity (Supplementary Fig. 7), which is in accordance with our previous work39–42. Four other guest–host materials (MOPy/BPO, MAPy/ BPO, DMOPy/BPO, and DMAPy/BPO, Fig. 2a) with a guest–host molar ratio of 1:1000 were prepared, and the luminescence characteristics of the guest–host systems were systematically investigated. \n\nFive guest–host materials show blue to cyan fluorescence under the excitation source (Fig. 2b) and the maximum emission peaks of the guest–host materials are red-shifted from 416 to $483\\mathrm{nm}$ as guest conjugation increases (Table 1 and Supplementary Fig. 8). Importantly, after finishing the irradiation, with the exception of \n\nDMAPy/BPO, the other four guest–host materials have visible to the naked eye a deep red afterglow for ${\\sim}3~\\mathsf{s}$ that reveal the RTP properties (Fig. 2b). Delayed spectra further show that the guest–host materials have two phosphorescence peaks, which are fine structures that arise from energy level vibrations. Similarly, with increasing guest conjugation, the phosphorescence peaks of the guest–host materials are red-shifted from 657 to $732{\\mathrm{nm}}$ or 600 to $681\\mathrm{nm}$ (Table 1 and Fig. 2c). That is, the guest–host materials produce deep-red or even near-infrared phosphorescence emissions and belong to a group that produces phosphorescence with the longest wavelengths to date. The Commission Internationale de l’Eclairage coordinates further indicate that the guest–host materials have a very deep phosphorescent color (0.63, 0.35; 0.64, 0.34; 0.65, 0.33; 0.69, 0.30; 0.70, and 0.29) (Supplementary Fig. 9). Unlike most red RTP materials which have short phosphorescence lifetimes, the phosphorescence lifetimes of this guest–host system are $102{-}324\\mathrm{ms}$ (Table 1 and Fig. 2d). Moreover, the guest–host materials have satisfactory luminous intensities, the phosphorescence quantum efficiency being in the range $4.2\\substack{-9.2\\%}$ (Table 1). The above results fully prove that, with the guest–host doped strategy, we have developed a group of ultralong-lifetime near-infrared RTP materials. As we know that the stability of materials will greatly affect practical applications. To verify the stability of the doped materials, Py/ BPO and MAPy/BPO were chosen to soak in water for $24\\mathrm{h}$ and two materials still have a strong red afterglow (Supplementary Fig. 12). And the Py/BPO and MAPy/BPO can still maintain obvious red afterglow after being continuously irradiated for $24\\mathrm{h}$ 1 $365\\mathrm{nm}$ , $40\\upmu\\mathrm{W}/\\upmathrm{c m}^{2}.$ (Supplementary Fig. 12). In addition, even if the doped materials are left in the ambient environment for one month, the phosphorescence activities are basically unchanged. Therefore, the RTP properties of these materials are very stable to water, light, and air. \n\nGenerally, the triplet excitons are unstable and easily assimilated by the motion of molecules, leading to the quenching of phosphorescence. However, for the guest–host system, the host matrix can provide a rigid environment to restrict the motion of guest molecules, thereby ensuring the guests emit phosphorescence42,43. We first register the phosphorescence of the solution and solid guests at low temperature (77 K) to verify that the phosphorescence from the guest–host system is emitted by the guest molecules. The spectra show that the guests in the solution state have two fine peaks at $77\\mathrm{K},$ and the emission peaks are also red-shifted from $596/665\\mathrm{nm}$ to $652/725\\mathrm{nm}$ (Supplementary Fig. 13). The spectral data were almost completely consistent with the phosphorescence wavelengths of the corresponding doped materials. The results confirm that the phosphorescence in the guest–host system is emitted by the guest molecules. Taking advantage of the low melting point of the host, the influence of the host morphology on the phosphorescence performance of the guest–host system was analyzed. The Py/BPO molten state at room temperature (subcooling state) show only fluorescence but no phosphorescence (Fig. 3a, b). However, when the guest–host material begins to crystallize, the material produces a bright red phosphorescence. This clearly proves that the host matrix restricts the guest molecular motion and is a necessary factor in determining the RTP properties of the guest–host system. \n\n
Table 1 Photophysical data of the guest-host materials.
Sample Fluo.
aem (nm)F (%)T (ns)Phos. Aem (nm)p (%)T (ms)
Py/BPO41514.21.43600a,657b9.2327a,324b
MOPy/BPO42413.42.03623a,680b8.0215a,210b
MAPy/BPO44015.21.98643a,697b6.3201a,198b
DMOPy/BPO47112.32.19657a,713b5.4180a,175b
DMAPy/BPO48316.12.32681a,732b4.2106a,102b
\n\nEx. of Fluo.: 360 nm; Ex. of Phos.: $380\\mathsf{n m};$ Delayed time: 1 ms. aThe short phosphorescence peak. bThe long phosphorescence peak. \n\nMolecular dynamics simulations. The local microenvironment of the molecules such as the molecular configuration, intermolecular distance, and intermolecular interaction plays an important role in determining the photophysical phenomena of materials. However, obtaining the co-crystal of host–guest is difficult because of the trace amounts of guest molecules $(<0.1\\%)$ in the entire materials. Moreover, the traditional characterization methods such as $\\mathrm{\\DeltaX}$ -ray diffractometry, scanning electron microscopy, and transmission electron microscopy are difficult to apply in investigating the molecular conformation of the guests in the host matrix in detail. Therefore, we simulated the molecular conformations of Py molecules in the BPO matrix using molecular dynamics/MD simulations40. The initial Py/BPO model was based on the BPO crystal. A BPO molecule is removed from the BPO crystal (Fig. 3c) and a Py molecule is inserted into the vacancy. This Py/BPO model has a 1:191 molar ratio of Py to BPO. Starting from the initial Py/BPO configuration, we performed production MD simulations for 10-ns to relax the whole guest–host system using the GROMACS software package (version 5.1.5, details in Supplementary Information). Compared with the conformations of BPO molecules in a single crystal, the corresponding conformations of the BPO molecules adjacent to the guest Py molecule in the Py/BPO guest–host system are slightly different because twisting increases the angles slightly after doping (Supplementary Fig. 14). This is because the spatial volume of the Py molecule is larger than that of the BPO molecule. However, because the number of guest/Py in the guest–host system is very small, the impact on the overall arrangement of the host matrix is minimal. Therefore, the stacking of BPO molecules in the simulated guest–host system is almost the same as for a single crystal (Supplementary Fig. 15, Supplementary Fig. 16). The XRD results also confirm little change in the arrangement of the BPO host before and after doping with guest molecules (Supplementary Fig. 17). Therefore, we have a microenvironment model of the guest–host system that is reasonable and reliable for our MD simulations. \n\nWith this Py/BPO model, we first analyzed the relative spatial positions of the Py molecule in the BPO matrix (Fig. 3d). The distances between the guest and host molecules in the six directions (up, down, front, back, left, and right) range from 2.3 to $3.1\\mathring\\mathrm{A}$ . That is, the guest molecules are in a relatively dense matrix environment, which can effectively inhibit their motion. More importantly, although these distances are relatively similar, the host has a twisted molecular conformation. Therefore, there is no $\\pi\\mathrm{-}\\mathrm{-}\\pi$ interaction between host and guest, and hence it is not conducive for luminescence. In contrast, between the host and Py molecules, multiple $\\mathrm{C-H}\\mathrm{--}\\pi$ interactions are evident over short distances $(2.3\\mathrm{-}3.{\\dot{2}}{\\dot{\\mathrm{A}}}$ , red line) (Fig. 3e), and the average distance between a Py molecule and surrounding host molecules is only $2.77\\mathring\\mathrm{A}$ . In addition, the C-H---O interactions between Py and host molecules are also evident over short distances (2.5 and $2.6\\mathring{\\mathrm{A}};$ , blue line) (Fig. 3e). The above analysis shows that the Pydoped host matrix provides a relatively close and strongly interactive environment for guest molecules that effectively restricts the non-radiative decay channels. \n\nRTP mechanism study. The rigid environment provided by the matrix is necessary for the guest–host system to display RTP characteristics. However, is this the only role the host molecules play? We chose separately as host sulfonyldibenzene (SOB), sulfinyldibenzene (SIB), and diphenylphosphine oxide (PPO), which also have good crystallinity and a similar structure to BPO (Fig. 4a), and MAPy as guest. The three guest–host materials (MAPy/SOB, MAPy/SIB, and MAPy/PPO) were prepared with a guest–host molar ratio of 1:1000. Unfortunately, although these materials have strong cyan fluorescence under a UV lamp, no red afterglow appears once the UV source is removed (Fig. 4b). The fluorescence spectra of the three guest–host materials show wavelengths centered around $430\\mathrm{nm}$ (Supplementary Fig. 18a), with quantum yields as high as 63, 71, and $76\\%$ in the order given above. Such high luminous intensities indicate that the host indeed inhibits the motion of the guest molecules. However, the delayed spectra suggest that the guest–host materials have almost no phosphorescence emission (Supplementary Fig. 18b). Note that, although the phosphorescence from MAPy/SOB and MAPy/SIB are very weak, there is an emission peak near $670\\mathrm{nm}$ that once again demonstrates that the phosphorescence in the guest–host material is emitted by the guest molecules. The above comparative experiments show that the rigid restrictive environment provided by the host is a necessary but not a sufficient factor, for the guest–host materials to display RTP properties. \n\n![](images/af8f86e377ffd3dede587f160b748179fa52881e9981f9a1b7f11be7331e26cb.jpg) \nFig. 3 Non-radiative suppression of guest excitons by host matrix. a Photographs of Py/BPO in different states. b Phosphorescence spectra of Py/BPO. Excitation wavelength: $380{\\mathsf{n m}}.$ Delayed time: 1 ms. c Model setup of $P y/B P O$ guest–host system. d Spatial distances between the Py molecule and the surrounding BPO molecules. e Interaction distances of $C-H\\mathrm{-}\\mathrm{-}\\pi$ or C-H---O interactions between Py molecule and surrounding BPO molecules. The distances between each phenyl ring center of $\\pmb{\\mathsf{P}}\\pmb{\\mathsf{y}}$ molecule and the hydrogen atom of the BPO molecules are marked by a red line. The corresponding distances between the oxygen atom of BPO and the hydrogen atoms of $\\pmb{\\mathsf{P}}\\pmb{\\mathsf{y}}$ are marked by a blue line. \n\n![](images/4b007f0c2d7a50941c1287ab7e62fdc91a6792c5339a82f1539a847ec1ca108a.jpg) \nFig. 4 Luminescence properties of guest molecules in other hosts. a Molecular structure of the reference hosts. b Luminescent images of the reference guest–host materials. \n\nEnergy transfers between host and guest molecules have gradually been revealed to play a vital role in phosphorescence activity. Among them, Förster resonance energy transfer (FRET) is considered a viable explanation why some guest–host materials have RTP properties23,38. To verify whether there is a FRET between host and guest, the absorption and excitation spectra of host BPO and guest MAPy were investigated. The absorption and excitation wavelengths of host BPO (Fig. 5a) only reach $418\\mathrm{nm}$ , whereas the absorption and excitation wavelengths of the guest MAPy reach $465\\mathrm{nm}$ . Therefore, we investigated the phosphorescence emission of MAPy/BPO material at different excitation wavelengths. The results show that even if the excitation wavelength is extended to $440\\mathrm{nm}$ , the MAPy/BPO powder maintains a strong phosphorescence emission (Fig. 5b) and has a red afterglow visible to the naked eye after removing the $420\\mathrm{-nm}$ UV source (Fig. 5c). These results clearly demonstrate that the phosphorescence of MAPy/BPO does not come from the energy absorbed by the host matrix, but from the energy absorbed by the guest molecules. Therefore, a FRET between host and guest is ruled out. \n\nIn our previous work, we found that the host could assist the excitons of the guests in energy transfer40–42. We, therefore, recorded the excitation spectra (fluorescence emission $/420\\mathrm{nm},$ ) of guest MAPy in common solvents (toluene, THF, and $N,N-$ dimethylformamide/DMF) and host BPO (molten state and crystal state). The results (Fig. 5d) show that the maximum excitation wavelength in MAPy emissions in these solvents is $346\\mathrm{nm}$ , whereas the maximum excitation wavelengths in host emissions in the molten and crystalline states are red-shifted to 392 and $387\\mathrm{nm}$ , respectively. The excitation spectra of the phosphorescence emission $\\left(660\\mathrm{nm}\\right)$ also show that the maximum excitation wavelengths in emissions from MAPy in these solvents are significantly longer than that of the crystalline host (Fig. 5e). Hence, we conclude that the host not only acts as the rigid matrix, but also changes the energy transfer process for the guest in the excited state. Furthermore, the phosphorescence lifetimes of guest molecules at $77\\mathrm{K}$ are only between $12{-}23\\mathrm{ms}$ (Fig. 5f), which are much shorter than that of the host matrix. This also shows that the host matrix prolongs the ISC process of the guest excitons. \n\nFrom the above experimental results and our previous work40–42, we conjecture that the $\\mathrm{T}_{1}$ of the host is the bridge between $\\mathsf{S}_{1}$ and $\\mathrm{T}_{1}$ of the guest (Fig. 5g), and hence the excited energy from the guest is transferred from $\\mathsf{S}_{1}$ to $\\mathrm{T}_{1}$ of the guest via the $\\mathrm{\\bar{T}}_{1}$ path of the host. To verify this mechanism, density functional theory calculations were performed to obtain the singlet and triplet energy levels of the guests and host (Calculated the energy level of the host in the crystalline state). The energy range for the $\\mathsf{S}_{1}$ and $\\mathrm{T}_{1}$ states of the five guest molecules are $3.01{-}3.49\\mathrm{eV}$ and $1.84\\mathrm{-}2.15\\mathrm{eV}$ , respectively (Fig. 5h). The $\\Delta\\mathrm{E}_{\\mathrm{ST}}$ of the guest molecules are in the range of $1.17\\mathrm{-}1.34\\mathrm{eV}$ ; such large energy gaps make excitonic ISC difficult. However, the band gaps between the $\\mathsf{S}_{1}$ state of the guests and the $\\mathrm{T}_{1}$ state of the host are only $0.11{-}0.59\\mathrm{eV}$ (Fig. 5h), which is advantageous for excitonic ISC. Therefore, the synergy action for the guest–host system is also an important factor in the phosphorescence activity of guest–host materials. \n\n![](images/ccd5332aaf990ba759d5c389bba2b6f76d6de8dec1af76b14158c16c3db1523a.jpg) \nFig. 5 Energy transfer between guest and host. a Excitation spectra of host BPO powder and guest MAPy powder. b Phosphorescence spectra of guest–host material MAPy/BPO at different excitation wavelengths. Excitation wavelength: $380\\mathsf{n m}$ ; Delayed time: 1 ms. c Luminescence photos of the MAPy/BPO powder. Excitation spectra of fluorescence (d)/phosphorescence (e) of MAPy in different solvent and molten state host (Concentration: $1\\times10^{-4}\\mathsf{m o l/L})$ . f Phosphorescence decay curves of the guests in $77\\mathsf{K}\\left(\\mathsf{E x}\\colon380\\mathsf{n m};\\right.$ Concentration: $1\\times10^{-4}\\mathsf{m o l/L}$ ; Solvent: 2-methyltetrahydrofuran). g Proposed transfer path between guest and host. h The energy levels of BPO and five guests. \n\nApplication studies in time-resolved bioimaging. Longwavelength emissions are well-known to be beneficial in reducing tissue scattering and enhancing tissue penetration, and thus improve bioimaging quality. Encouraged by the excellent properties of these near-infrared RTP materials, an application to bioimaging was investigated. Because DMAPy/BPO among the materials studied exhibits the longest wavelength with a quite long lifetime, DMAPy/BPO and the biocompatible amphiphilic copolymer PEG-b-PPG-b-PEG (F127) were selected as nanoparticle (NP) cores and the encapsulation matrix, respectively. To ensure our DMAPy/BPO NPs were accessible in vivo with good RTP performance, a top-down method was employed to produce the $\\mathrm{NPs}^{12,47}$ . The phosphorescence wavelength of nanoparticles is almost the same as that in the solid-state (Supplementary Fig. 19a), but the phosphorescence lifetime is reduced to $70\\mathrm{m}s$ (Supplementary Fig. 19b), and the phosphorescence quantum yield has also been reduced to $3.1\\%$ . This may be due to the small size of the nanoparticles causing the host matrix to not be able to coat the guest molecules well12,47. In addition, to study the morphology of the nanoparticles, the XRD curve of the nanoparticles obtained by suction filtration were tested, and the result showed that the nanoparticles have good crystallinity (Supplementary Fig. 20). To further verify the advantages of longwavelength RTP materials, a short-wavelength $(\\lambda_{\\mathrm{Phos}}.=520\\mathrm{nm})$ ) but strong intensity $(\\phi_{\\mathrm{Phos}}.=64\\%$ ) RTP material DOB/BPO reported in our previous work was selected as a control and DOB/BPO NPs were prepared by the same method48. Dynamic light scattering and transmission electron microscopy data indicated both DMAPy/BPO and DOB/BPO NPs formed a nearspherical morphology with a mean hydrodynamic diameter of $\\approx$ $100\\mathrm{nm}$ (Fig. 6a and Supplementary Fig. 21). Both kinds of NPs revealed strong resistance to photobleaching, indicative of little change in their intensities after eight cycles of stimulation or eighty minutes of $365\\mathrm{-nm}$ UV light irradiation (Fig. 6b and Supplementary Figs. 22, 23). We further verified the quantitative conversion of the phosphorescence intensity with NP concentrations. The phosphorescence intensities of DMAPy/BPO NPs and DOB/BPO NPs were captured at $t=10s$ post-excitation, and possess good linearity with the NP concentration (Fig. 6c and Supplementary Fig. 24). DMAPy/BPO NPs and DOB/BPO NPs display the main phosphorescence signals (Fig. 6d) under Dsred $(575-650\\mathrm{nm})$ ) and GFP $(515-575\\mathrm{nm})$ ) filters, respectively. This result is consistent with their phosphorescence spectra. \n\nAs tissue penetration is a considerable challenge for in vivo bioimaging, tissue penetration depths of the NPs were compared between DMAPy/BPO NPs and DOB/BPO NPs. The phosphorescence signals of both DMAPy/BPO NPs and DOB/BPO NPs (Fig. 6e, f) decreased with the increasing thickness of chicken breast tissue. With the advantages of RTP materials, ultra-high SBR signals were observed without covering the chicken breast tissue. However, the inherent limit with short wavelengths leads to a relatively low tissue penetration ( $\\mathrm{\\Delta}\\mathrm{SBR}=5.4$ at thickness $7.5\\mathrm{mm}$ ). In contrast, the NIR phosphorescence signal of the DMAPy/BPO NPs can still be detected $(\\mathrm{SBR}=15\\$ ) under a 12.5- mm thick coverage of chicken breast tissue. This result revealed excellent deep tissue imaging from NIR emissions of NPs and moreover without excitation. \n\n![](images/0c782578500e0088443e2866fc16e84fe25bf69316a0e271bd53816e2a60d5b2.jpg) \nFig. 6 Phosphorescence properties of DMAPy/BPO and DOB/BPO nanoparticles. a Diameter distribution of DMAPy/BPO nanoparticles. Inset: transmission electron microscopy image, scale bar $=100\\mathsf{n m}$ . b The normalized phosphorescence intensities of DMAPy/BPO ${\\mathsf{N P s}}$ as a function of cycle number of UV light irradiation $\\left(n=3\\right)$ . c The phosphorescence intensities as a function of the concentration of DMAPy/BPO NPs $(n=3)$ . d Phosphorescence images of DMAPy/BPO and DOB/BPO ${\\mathsf{N P s}}$ $(4\\log\\mathsf{m L^{-1}})$ were captured through different filters. e Phosphorescence images of DMAPy/ BPO and DOB/BPO NPs $(10\\mathrm{mg}\\mathrm{mL}^{-1}),$ covered with different thicknesses of chicken tissue. f SBR ratios from coverings with different tissue thicknesses given in (e). g Cytotoxicities of DMAPy/BPO and DOB/BPO NPs against 4T1 cells. The 4T1 cells were incubated with DMAPy/BPO and DOB/BPO NPs at different concentrations for $^{8\\mathfrak{h}}$ ${\\mathrm{\\Omega}}_{n}=4,$ ). h Fold change plot of phosphorescence intensities of DMAPy/BPO NPs in various metal ions. Error bars: mean $\\pm$ standard deviation $\\displaystyle(n=3)$ ). Triple asterisks represent $p<0.01$ compared with ${\\mathsf{N a}}^{+}$ . i Fold change plot of phosphorescence intensities for DMAPy/ BPO NPs in different tissue homogenates. Error bars: mean $\\pm$ standard deviation $\\left(n=3\\right)$ . Triple asterisks represent $p<0.01$ compared with PBS. \n\nAfter we verified that both kinds of NPs had good cytocompatibility (Fig. 6g), we investigated the phosphorescent performance of DMAPy/BPO NPs in various metal ions (widespread in vivo) and tissue homogenates to confirm bioimaging feasibility in vivo. After 1 min-long irradiation using a $365\\mathrm{-nm}$ handheld UV lamp, the phosphorescence signals of DMAPy/BPO NPs incubated with different metal ions were recorded immediately under the same conditions using an IVIS bioimaging instrument. However, ferric ions (including $\\mathrm{\\bar{F}e}^{2+}$ and $\\mathrm{Fe}^{3+}$ ) were found to quench the phosphorescence signals significantly compared with the signals in $\\mathrm{\\bar{N}a^{+}}$ (Fig. 6h). This result might be attributed to the interaction between ferric ions with outer vacant orbitals and $\\mathrm{O}/\\mathrm{N}$ heteroatoms with lone pair electrons in DMAPy/BPO $\\mathrm{NPs^{49}}$ Furthermore, the DMAPy/BPO NPs were found to exhibit different phosphorescence quench behaviors in different tissue homogenates and blood (Fig. 6i). Compared with the phosphorescence signal in PBS, the signals of DMAPy/BPO NPs were significantly quenched in blood and blood-rich tissues (such as heart and liver) through the quenching of $\\mathrm{Fe}^{2+}$ and $\\mathrm{Fe}^{3+}$ ions, which would be beneficial when imaging tumors. \n\nApplications in intravital phosphorescence imaging were investigated. The solutions of DMAPy/BPO NPs and DOB/ BPO NPs were subcutaneously injected into Balb/c nude mice, followed by imaging with an IVIS instrument in bioluminescent mode after 1-min irradiation from the $365\\mathrm{nm}$ handheld UV lamp. The images were captured $10s$ after the removal of the light source. To ensure the biosafety of the UV irradiation procedure, the phosphorescence signals were activated by the handheld UV lamp at $10\\mathrm{mW}\\mathrm{cm}^{-2}$ power density, which is below the maximum power exposure allowed for skin irradiation ( $\\mathrm{\\Delta}\\mathrm{18\\mW}$ $c\\mathrm{m}^{-2})^{47}$ . For comparison, fluorescence signals derived from DMAPy/BPO NPs and DOB/BPO NPs were also evaluated, simultaneously. The subcutaneous phosphorescence imaging result (Fig. 7a) in living mice reveals that both phosphorescent signals from DMAPy/BPO and DOB/BPO NPs can be observed at $10s$ after excitation. The SBR of DMAPy/BPO NPs and DOB/ BPO NPs subcutaneous phosphorescence imaging at $10s$ are 160 and 75 (Fig. 7b), respectively. In contrast, the fluorescence signals of DMAPy/BPO NPs and DOB/BPO NPs were hardly distinguished from the tissue autofluorescence. We note that, although the skin thickness of mice is just ${\\sim}0.5\\mathrm{mm}$ , shortwavelength-emitting DOB/BPO NPs exhibit a lower SBR than DMAPy/BPO NPs in subcutaneous phosphorescence imaging because of scattering from skin tissue. These results are in accordance with Fig. 5e, f and also demonstrate that longwavelength emissions from DMAPy/BPO can effectively decrease tissue scattering and provide high-quality phosphorescence bioimaging. The phosphorescence imaging of lymph nodes was further investigated because lymph-node labeling is clinically important in guiding tumor surgery. The phosphorescence signal (Fig. 7c, d) of the axillary lymph node is clearly evident $\\mathrm{\\Delta}\\mathrm{\\left.\\langle{\\cal{S}}B R\\right.=55}$ ) whereas the fluorescence signal is not distinguishable. Thus, the lymph-node imaging confirms the effectiveness of DMAPy/BPO NPs for phosphorescence tissue imaging. \n\n![](images/19f9b84c23f978ad400c51b8bec955433705f8d38729f9fd5562d194bf0bcdad.jpg) \nFig. 7 Applications in intravital phosphorescence imaging. a Phosphorescence and fluorescence imaging of a mouse with the subcutaneous inclusions of DMAPy/BPO NPs and DOB/BPO ${\\mathsf{N P s}}$ $(4\\log\\mathsf{m L}^{-1})$ . Circles indicate the locations of nanoparticle injection. b Signal to background ratio for phosphorescence and fluorescence imaging of subcutaneous injection in live mice. c Phosphorescence and fluorescence imaging of lymph nodes in mice $0.5\\mathsf{h}$ after intradermal injection of DMAPy/BPO NPs $(4\\mathrm{mg}\\mathrm{mL}^{-1})$ into the forepaw of live mice. d Signal to background ratio for phosphorescence and fluorescence imaging of lymph nodes in live mice. e Phosphorescence and fluorescence imaging of live tumor-bearing mice 6 h after the injection of DMAPy/BPO NPs into the vein $(4\\log\\mathsf{m L}^{-1})$ . f Signal to background ratio for phosphorescence and fluorescence imaging of tumor in live mice. All error bars were based on standard deviation $\\displaystyle(n=3)$ ). \n\nPrecise identification of complicated diseases such as cancer cells for high-performance imaging. Encouraged by the good performance of lymph-node imaging, we evaluated the phosphorescence imaging capability in cancer diagnosis in vivo. To probe the feasibility of using long-wavelength RTP materials in such circumstances, the armpit tumor-bearing mice were prepared with 4T1 breast cancer cells. A solution of DMAPy/ BPO NPs was injected through the tail vein into live mice. At $6\\mathrm{{h}}$ post-injection, the signals of DMAPy/BPO NPs were activated by UV light for 1 min. Next, after removal of the UV lamp excitation, phosphorescence images were captured at $10s$ using the IVIS instrument in the bioluminescence mode. Similarly, fluorescence imaging was recorded at the same time for comparison. The phosphorescence signal (Fig. 7e) clearly originates from the armpit tumor. Because the NIR phosphorescence emission involves no autofluorescence interference, the SBR for the phosphorescence guided armpit tumor imaging is as high as 43 (Fig. 7f). \n\nThe mice bearing armpit tumors were sacrificed, and the main tissues were excised for ex vivo phosphorescence imaging. Reticuloendothelial system organs are known to have enriched nanomaterials. Interestingly, only the liver displayed a low phosphorescence signal; in other main organs, almost no phosphorescence signal was observed (Supplementary Fig. 25). This result might be attributed to the phosphorescence signal being quenched by the liver because of its abundant blood supply, which is in accordance with an earlier result (Fig. 6i). Furthermore, tissues with phosphorescence signals were collected and stained with H&E (Supplementary Fig. 26), verifying the presence of an armpit tumor. The main organs were stained with H&E as well. Compared with the main organs of PBS pretreatment live mice, the DMAPy/BPO NPs did not cause obvious damage to these organs (Supplementary Fig. 27). This work confirmed that by avoiding autofluorescence interference and reducing the tissue scattering, RTP materials (DMAPy/BPO NPs) with both long-wavelength and long-lifetime properties can serve as potent probes for image-guided diagnosis. \n\n# Discussion \n\nIn conclusion, we provide a practical idea for the construction of organic RTP materials with NIR wavelength and ultralong lifetime: i.e., the guests should have sufficient conjugation to reduce the $\\mathrm{T}_{1}$ level, and the host matrix assists the guest molecules in exciton transfer and inhibits the non-radiative transition. To the best of our knowledge, this is the first report on pure organic RTP materials with both long-wavelength $(>700\\mathrm{nm})$ and ultralong lifetime $(>100\\mathrm{ms})$ simultaneously. What’s more, we demonstrate for the first time that pure organic NIR phosphorescence is successfully used for in vivo bioimaging. This work also represents one of the very few examples among currently available pure organic RTP materials able to be competent for in-depth in vivo bioimaging via intravenous injection in an animal model. \n\n# Methods \n\nSynthesis of guest compounds. The mixture of 1-bromopyrene or 1,6-dibromopyrene $\\left(10.0\\mathrm{mmol}\\right)$ , boronic acid (12.0 or $24.0\\mathrm{mmol})$ , $\\mathrm{Pd}(\\mathrm{PPh}_{3})_{4}$ $5.0\\mathrm{mol\\%}^{\\prime}$ ), and ${\\mathrm{K}}_{2}{\\mathrm{CO}}_{3}$ $5.0\\mathrm{mol\\%}^{\\cdot}$ were dissolved in THF $(10.0\\mathrm{mL})$ and water $(1.0\\mathrm{mL})$ . The mixture was stirred for $^{12\\mathrm{h}}$ at $80^{\\circ}\\mathrm{C}$ under a nitrogen atmosphere. The solvent was removed under reduced pressure and the residue were purified by column chromatography (petroleum ether: ethyl acetate $=1{:}100$ , v:v) to afford the pure MOPy/MAPy/DMOPy/DMAPy compounds. \n\nPreparation of doped materials. Put the corresponding amount of host and guest together, and heat the mixture to $60^{\\circ}\\mathrm{C}$ in an air atmosphere. After the guests are completely dissolved in the molten hosts, the mixed systems are cooled to room temperature, and the mixed systems are crystallized to obtain the doped materials. The doped materials with high guest–host molar ratios (1:10, 1:100, 1:100) are using a direct weighing method, while for guest–host molar ratio (1:10000) doped materials, we use the indirect dilution method. \n\nBioimaging measurement. The amphiphilic copolymer PEG-b-PPG-b-PEG (F127) was purchased from Aladdin Ltd. Fetal bovine serum (FBS) was provided by Thermo Fisher Scientific Inc. (Waltham, MA, USA). Transmission electron microscopy (TEM) images were acquired from a JEM-2010F transmission electron microscope with an accelerating voltage of $200\\mathrm{kV}$ . Dynamic light scattering (DLS) was measured on a 90 plus particle size analyzer. In vitro and in vivo phosphorescence imaging was performed by the IVIS® Lumina II imaging system. \n\n# References \n\nPreparation of nanoparticles. To 1 mL of the aqueous solution of F127 $(10\\mathrm{mg})$ , the DMAPy/BPO crystals $\\left(1\\:\\mathrm{mg}\\right)$ were added. The mixture was then sonicated by a microtip-equipped probe sonicator (Branson, S-250D) for $10\\mathrm{min}$ . The resultant suspension was filtered through a $0.45\\upmu\\mathrm{m}$ syringe-driven filter to afford a solution of nanoparticles. And then the resultant solution was concentrated. \n\n# Data availability \n\nThe authors state that the data supporting the results of this study are available in this paper and its supplementary materials. Extra data are available from the corresponding authors upon reasonable request. The data generated in this study have been deposited in the Figshare database: https://doi.org/10.6084/m9.figshare.16863643. The X-ray crystallographic coordinates for structures reported in this study have been deposited at the Cambridge Crystallographic Data Centre (CCDC), under deposition numbers 2091331, 2091334, 2091335, and 2091336. These data can be obtained free of charge from The Cambridge Crystallographic Data Centre via www.ccdc.cam.ac.uk/ data_request/cif. Source data are provided with this paper. \n\n# Code availability \n\nNo custom computer code is used in the manuscript. \n\nReceived: 23 June 2021; Accepted: 17 December 2021; Published online: 10 January 2022 \n\nIn vitro phosphorescent imaging of nanoparticles solutions. The phosphorescent intensities of DMAPy/BPO and DOB/BPO nanoparticles were recorded using ${\\mathrm{IVIS}}^{\\infty}$ Lumina II imaging system at $t=10:$ after each kind of nano solutions were irradiated by $365\\mathrm{nm}$ handheld UV lamp (12 W) for 1 min. The IVIS system was set in bioluminescence mode with an open/GFP/Dsred filter setting (exposure time: 17 s). \n\n1. Zhao, W., He, Z. & Tang, B. Z. Room-temperature phosphorescence from organic aggregates. Nat. Rev. Mater. 5, 869–885 (2020). \n2. Peng, Q., Ma, H. & Shuai, Z. G. Theory of long-lived room-temperature phosphorescence in organic aggregates. Acc. Chem. Res. 54, 940–949 (2021). \n3. Kabe, R. & Adachi, C. Organic long persistent luminescence. Nature 550, 384–387 (2017). \n4. Gu, L. et al. Colour-tunable ultra-long organic phosphorescence of a singlecomponent molecular crystal. Nat. Photonics 13, 406–411 (2019). \n5. An, Z. et al. Stabilizing triplet excited states for ultralong organic phosphorescence. Nat. Mater. 14, 685–690 (2015). \n6. Wang, X. et al. Organic phosphors with bright triplet excitons for efficient Xray-excited luminescence. Nat. Photonics 15, 187–192 (2021). \n7. Bolton, O. et al. Activating efficient phosphorescence from purely organic materials by crystal design. Nat. Chem. 3, 205–210 (2011). \n8. Wang, J. et al. A facile strategy for realizing room temperature phosphorescence and single molecule white light emission. Nat. Commun. 9, 2963 (2018). \n9. Zhang, Y. et al. Ultraviolet irradiation-responsive dynamic ultralong organic phosphorescence in polymeric systems. Nat. Commun. 12, 2297 (2021). \n10. Bian, L. et al. Simultaneously enhancing efficiency and lifetime of ultralong organic phosphorescence materials by molecular self-assembly. J. Am. Chem. Soc. 140, 10734–10739 (2018). \n11. Ali Fateminia, S. M. et al. Organic nanocrystals with bright red persistent room-temperature phosphorescence for biological applications. Angew. Chem. Int. Ed. 129, 12328–12332 (2017). \n12. Dang, Q. et al. Room-temperature phosphorescence resonance energy transfer for construction of near-infrared afterglow imaging agents. Adv. Mater. 32, 2006752 (2020). \n13. Wang, Y. et al. High performance of simple organic phosphorescence hostguest materials and their application in time-resolved bioimaging. Adv. Mater. 33, 2007811 (2021). \n14. Gao, H. et al. Boosting room temperature phosphorescence performance by alkyl modification for intravital orthotopic lung tumor imaging. Small 17, 2005449 (2021). \n15. He, Z. et al. Achieving persistent, efficient, and robust room-temperature phosphorescence from pure organics for versatile applications. Adv. Mater. 31, 1807222 (2019). \n16. Zhang, T. et al. Molecular engineering for metal-free amorphous materials with room-temperature phosphorescence. Angew. Chem. Int. Ed. 59, 11206–11216 (2020). \n17. Li, J. et al. Transientand persistent room-temperature mechanoluminescence from a white-light-emitting AIEgen with tricolor emission switching triggered by light. Angew. Chem. Int. Ed. 130, 6559–6563 (2018). \n18. Wang, T. et al. Thermochromic aggregation-induced dual phosphorescence via temperature-dependent $s p^{3}$ -linked donor-acceptor electronic coupling. Nat. Commun. 12, 1364 (2021). \n19. Yang, Z. et al. Boosting the quantum efficiency of ultralong organic phosphorescence up to $52\\%$ via intramolecular halogen bonding. Angew. Chem. Int. Ed. 59, 17451–17455 (2020). \n20. Dou, X. et al. Color-tunable, excitation-dependent, and time-dependent afterglows from pure organic amorphous polymers. Adv. Mater. 32, 2004768 (2020). \n21. Ren, J. et al. Force-induced turn-on persistent room-temperature phosphorescence in purely organic luminogen. Angew. Chem. Int. Ed. 60, 1–7 (2021). \n22. Li, D. et al. Amorphous metal-free room-temperature phosphorescent small molecules with multicolor photoluminescence via a host-guest and dualemission strategy. J. Am. Chem. Soc. 140, 1916–1923 (2018). \n23. Zhou, B. & Yan, D. P. Hydrogen-bonded two-component ionic crystals showing enhanced long-lived room-temperature phosphorescence via TADFassisted förster resonance energy transfer. Adv. Funct. Mater. 29, 1807599 (2019). \n24. Nidhankar, A. et al. Self-assembled helical arrays for the stabilization of the triplet state. Angew. Chem. Int. Ed. 59, 13079–13085 (2020). \n25. Cai, S. et al. Enabling long-lived organic room temperature phosphorescence in polymers by subunit interlocking. Nat. Commun. 10, 4247 (2019). \n26. Xiao, F. et al. Achieving crystal-induced room temperature phosphorescence and reversible photochromic properties by strong intermolecular interactions. J. Mater. Chem. C. 8, 17410–17416 (2020). \n27. Xiao, L. et al. Room-temperature phosphorescence in pure organic materials: halogen bonding switching effects. Chem. Eur. J. 24, 1801–1805 (2018). \n28. Wu, X. et al. Exploiting racemism enhanced organic room-temperature phosphorescence to demonstrate Wallach’s rule in the lighting chiral chromophores. Nat. Commun. 11, 2145 (2020). \n29. Wang, X. et al. Pure organic room temperature phosphorescence from unique micelle-assisted assembly of nanocrystals in water. Adv. Funct. Mater. 30, 1907282 (2020). \n30. Wang, X. et al. Pure Organic room temperature phosphorescence from excited dimers in self-assembled nanoparticles under visible and near-infrared irradiation in water. J. Am. Chem. Soc. 141, 5045–5050 (2019). \n31. Ono, T. et al. Room-temperature phosphorescence emitters exhibiting red to near-infrared emission derived from intermolecular charge-transfer triplet states of naphthalenediimide-halobenzoate triad molecules. Chem. Eur. J. 27, 9535–9541 (2021). \n32. Katsurada, Y. et al. Photoreversible on-off recording of persistent roomtemperature phosphorescence. Adv. Optical Mater. 3, 1726–1737 (2015). \n33. Zhang, X. et al. Ultralong UV/mechano-excited room temperature phosphorescence from purely organic cluster excitons. Nat. Commun. 10, 5161 (2019). \n34. Chen, C. et al. Carbazole isomers induce ultralong organic phosphorescence. Nat. Mater. 20, 175–180 (2021). \n35. Alam, P. et al. Two are better than one: a design principle for ultralongpersistent luminescence of pure organics. Adv. Mater. 32, 2001026 (2020). \n36. Chen, Y. et al. Tunable phosphorescence/fluorescence dual emissions of organic isoquinoline-benzophenone doped systems by akoxy engineering. Chem. Eur. J. 26, 17376–17380 (2020). \n37. Chen, B. et al. An unexpected chromophore–solvent reaction leads to bicomponent aggregation-induced phosphorescence. Angew. Chem. Int. Ed. 59, 10023–10026 (2020). \n38. Wang, Y. et al. Forster resonance energy transfer: An efficient way to develop stimulus-responsive room-temperature phosphorescence materials and their applications. Matter 3, 449–463 (2020). \n39. Lei, Y. et al. Revealing insight into long-lived room-temperature phosphorescence of host-guest systems. J. Phys. Chem. Lett. 10, 6019–6025 (2019). \n40. Lei, Y. et al. Efficient and organic host-guest room-temperature phosphorescence: tunable triplet-singlet crossing and theoretical calculations for molecular packing. Chem. Sci. 12, 6518–6525 (2021). \n41. Wang, D. et al. Excitation-dependent triplet-singlet intensity from organic host-guest materials: tunable color, white-light emission, and roomtemperature phosphorescence. J. Phys. Chem. Lett. 12, 1814–1821 (2021). \n42. Lei, Y. et al. Wide-range color-tunable organic phosphorescence materials for printable and writable security inks. Angew. Chem. Int. Ed. 59, 16054–16060 (2020). \n43. Wei, J. et al. Induction of strong long-lived room-temperature phosphorescence of $N$ -phenyl-2-naphthylamine molecules by confinement in a crystalline dibromobiphenyl matrix. Angew. Chem. Int. Ed. 128, 15818–15822 (2016). \n44. Xie, Z. et al. Wide-range lifetime-tunable and responsive ultralong organic phosphorescent multi-host/guest system. Nat. Commun. 12, 3522 (2021). \n45. Wang, X. et al. TADF-type organic afterglow. Angew. Chem. Int. Ed. 60, 17138–17147 (2021). \n46. Chen, B. et al. Organic guest-host system produces room-temperature phosphorescence at part-per-billion level. Angew. Chem. Int. Ed. 60, \n16970–16973 (2021). \n47. Zhen, X. et al. Ultralong phosphorescence of water-soluble organic nanoparticles for in vivo afterglow imaging. Adv. Mater. 29 1606665 (2017). \n48. Liu, X. et al. Pure room temperature phosphorescence emission of an organic host–guest doped system with a quantum efficiency of $64\\%$ . J. Mater. Chem. C. \n9, 3391–3395 (2021). \n49. Wang, Y. et al. High performance of simple organic phosphorescence host–guest materials and their application in time-resolved bioimaging. Adv. Mater. 33, 2007811 (2021). \n\n# Acknowledgements \n\nAll animal studies were performed according to the guidelines set by the Tianjin Committee of Use and Care of Laboratory Animals, and the overall project protocols were approved by the Animal Ethics Committee of Nankai University. The accreditation number of the laboratory is SYXK(Jin) 2019-0003 promulgated by the Tianjin Science and Technology Commission. This work was supported by financial support from the National Natural Science Foundation of China (No 22071184, X.B.H; 51961160730, 51873092, and 81921004, D.D.) and the Zhejiang Provincial Natural Science Foundation of China (No LY20B020014, D.D), the National Key R&D Program of China (Intergovernmental Cooperation Project, No 2017YFE0132200, X.B.H.), and the Tianjin Science Fund for Distinguished Young Scholars (No 19JCJQJC61200, D.D.). \n\n# Author contributions \n\nYL, XH, and DD designed the research work and revised the manuscript. FX synthesized the materials. FX and YL carried out photophysical property measurements. HG carried out biological tissue measurements. XZ carried out density functional theory calculations. YL, XH, and DD wrote the manuscript. WD, ML, ZC, and HW edited the manuscript. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-021-27914-0. \n\nCorrespondence and requests for materials should be addressed to Yunxiang Lei, Xiaobo Huang or Dan Ding. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. " + }, + { + "id": "10.1038_s41467-022-28146-6", + "DOI": "10.1038/s41467-022-28146-6", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-28146-6", + "Relative Dir Path": "mds/10.1038_s41467-022-28146-6", + "Article Title": "Unraveling of cocatalysts photodeposited selectively on facets of BiVO4 to boost solar water splitting", + "Authors": "Qi, Y; Zhang, JW; Kong, Y; Zhao, Y; Chen, SS; Li, D; Liu, W; Chen, YF; Xie, TF; Cui, JY; Li, C; Domen, K; Zhang, FX", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Artificial photosynthesis offers an integrated means to convert light to fuel, but efficiencies are often low. Here, authors report a Z-scheme system utilizing Ir and FeCoOx co-catalysts to enhance charge separation on BiVO4 facets that achieves high quantum efficiencies for overall water splitting. Bismuth vanadate (BiVO4) has been widely investigated as a photocatalyst or photoanode for solar water splitting, but its activity is hindered by inefficient cocatalysts and limited understanding of the underlying mechanism. Here we demonstrate significantly enhanced water oxidation on the particulate BiVO4 photocatalyst via in situ facet-selective photodeposition of dual-cocatalysts that exist separately as metallic Ir nulloparticles and nullocomposite of FeOOH and CoOOH (denoted as FeCoOx), as revealed by advanced techniques. The mechanism of water oxidation promoted by the dual-cocatalysts is experimentally and theoretically unraveled, and mainly ascribed to the synergistic effect of the spatially separated dual-cocatalysts (Ir, FeCoOx) on both interface charge separation and surface catalysis. Combined with the H-2-evolving photocatalysts, we finally construct a Z-scheme overall water splitting system using [Fe(CN)(6)](3-/4-) as the redox mediator, whose apparent quantum efficiency at 420 nm and solar-to-hydrogen conversion efficiency are optimized to be 12.3% and 0.6%, respectively.", + "Times Cited, WoS Core": 286, + "Times Cited, All Databases": 295, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000747410400003", + "Markdown": "# Unraveling of cocatalysts photodeposited selectively on facets of BiVO4 to boost solar water splitting \n\n$\\mathsf{Y u}\\mathsf{Q i}^{1,7}$ , Jiangwei Zhang 1,7, Yuan Kong2,7, Yue Zhao1, Shanshan Chen $\\textcircled{1}$ 3, Deng Li1, Wei Liu1, Yifan Chen4, Tengfeng Xie4, Junyan ${\\mathsf{C u i}}^{5},$ Can Li 1✉, Kazunari Domen $\\textcircled{1}$ 3,6 & Fuxiang Zhang 1✉ \n\nBismuth vanadate $(\\mathsf{B i V O}_{4})$ ) has been widely investigated as a photocatalyst or photoanode for solar water splitting, but its activity is hindered by inefficient cocatalysts and limited understanding of the underlying mechanism. Here we demonstrate significantly enhanced water oxidation on the particulate $B i V O_{4}$ photocatalyst via in situ facet-selective photodeposition of dual-cocatalysts that exist separately as metallic Ir nanoparticles and nanocomposite of FeOOH and CoOOH (denoted as $\\mathsf{F e C o O}_{\\times})$ , as revealed by advanced techniques. The mechanism of water oxidation promoted by the dual-cocatalysts is experimentally and theoretically unraveled, and mainly ascribed to the synergistic effect of the spatially separated dual-cocatalysts $(1\\mathsf{r},\\mathsf{F e C o O}_{\\mathsf{x}})$ on both interface charge separation and surface catalysis. Combined with the ${\\sf H}_{2}$ -evolving photocatalysts, we finally construct a Z-scheme overall water splitting system using $[\\mathsf{F e}(\\mathsf{C N})_{6}]^{3-/4-}$ as the redox mediator, whose apparent quantum efficiency at $420\\mathsf{n m}$ and solar-to-hydrogen conversion efficiency are optimized to be $12.3\\%$ and $0.6\\%,$ , respectively. \n\nPagbroatsoiecdupaothne npsohtraogbtaiolncitiayctalshyeatsim b oenvndudacletlomrownamsttaertra eisadpl attswniotgh r eoOlfaWttihvSe) most promising ways of realizing scalable and economically viable solar hydrogen production to address energy- and environmentrelated issues1–12. To achieve high solar-to-hydrogen (STH) energy conversion efficiency, it is necessary to increase the quantum efficiency of photocatalytic OWS over a wide range of wavelengths, particularly the use of visible light11,12. However, extended visible light utilization is generally accompanied by a decreased driving force of the photogenerated carriers to make charge separation extremely difficult. Furthermore, the construction of OWS systems faces serious challenges originating from the sluggish kinetics of water oxidation involving uphill energy barrier and multiple electron transfer13. Consequently, visible-light-driven photocatalytic OWS systems are not only limited in number, but also show lower efficiency than those driven by ultraviolet $\\mathrm{light^{14-19}}$ . Accordingly, it is highly desirable to precisely design and modify photocatalysts with efficient visible light utilization for promotion of water oxidation. \n\nN-type monoclinic bismuth vanadate $\\mathrm{(BiVO_{4})}$ ) has emerged as one of the most promising visible-light-responsive photocatalysts and photoanodes for water oxidation since Kudo’s report in $1998^{\\Bar{2}0-28}$ . Owing to its advantages, such as efficient light absorption in the visible light region, good carrier mobility, controllable exposed facets, and non-toxic properties, ${\\mathrm{BiVO}}_{4}$ semiconductor has been widely and successfully employed as the water oxidation photocatalyst for the assembly of Z-scheme OWS systems using solid conductor (i.e., Au, reduced graphene oxide) or redox couple (i.e., $\\mathrm{Fe}^{3+/2+}$ , $\\mathrm{[Fe(CN)_{6}]^{3-/4-}})$ as electron mediator15,16,29–31. Specifically, our previous work revealed that the spatial separation of photogenerated electrons and holes can be achieved on the anisotropic facets of $\\mathrm{BiVO}_{4}{}^{32}$ , based on which reduction and oxidation cocatalysts are selectively deposited on different facets to remarkably promote its water oxidation and the efficiency of OWS under visible light16. Although the ${\\mathrm{BiVO}}_{4}$ photocatalyst has been widely investigated for the assembly of artificial Z-scheme OWS systems, the apparent quantum efficiency (AQE) and STH conversion efficiency achieved so far are still considerably below what is expected. This is mainly due to the shortage of effective cocatalyst regulation and the lack of in-depth understanding of the microscopic mechanisms behind it33,34. Notably, for the assembly of the redox couple-mediated Z-scheme OWS system shown in Fig. 1, the loading of effective cocatalysts is extremely important not only for the acceleration of interfacial electron transfer between the $\\mathrm{H}_{2}$ -evolving photocatalyst (HEP) and the $\\mathrm{O}_{2}$ -evolving photocatalyst (OEP), but also for the promotion of surface reaction kinetics of water splitting35–38. Therefore, it is a long-term task to develop innovative cocatalysts and unravel their structures as well as influence mechanism on water splitting. \n\nIn this study, we address the sluggish water oxidation of ${\\mathrm{BiVO}}_{4}$ via in situ photodeposition of dual innovative cocatalysts, with emphasis on elucidating the local structures of the cocatalysts and the mechanism of promotion of water oxidation. We demonstrate that the nanocomposite of FeOOH and CoOOH (denoted as $\\mathrm{FeCoO_{x})}$ in situ formed on the $\\{110\\}$ facet of ${\\mathrm{BiVO}}_{4}$ not only lowers Gibbs free energy barrier of water oxidation, but also makes a better promotion on the electron transfer as well as charge separation compared with the commonly used $\\mathrm{CoO_{x}}$ cocatalyst. Furthermore, the Ir cocatalyst in situ deposited on the $\\{010\\}$ facet of ${\\mathrm{BiVO}}_{4}$ was found to exhibit superior reduction ability of $\\mathrm{[Fe(CN)_{6}]^{3-}}$ ions to our previously reported Au. Based on the facet-selective loading of the innovative dual-cocatalysts, the evolution rate of $\\mathrm{O}_{2}$ on the ${\\mathrm{BiVO}}_{4}$ was significantly enhanced, and a particulate Z-scheme OWS system with an AQE of $12.3\\%$ at $420\\mathrm{nm}$ and a STH of $0.6\\%$ , was finally fabricated using $\\mathrm{[Fe(CN)_{6}]^{3-/4-}}$ as a redox mediator and $\\mathrm{ZrO_{2}/T a O N}$ or $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ as the HEP. Our results demonstrate the importance and effectiveness of developing suitable cocatalysts for enhancing interfacial charge separation and surface water oxidation kinetics in promoting solar energy conversion. \n\n# Results \n\nStructural characterizations of cocatalysts photodeposited. The anisotropic ${\\mathrm{BiVO}}_{4}$ with exposed $\\{010\\}$ and $\\{110\\}$ facets was prepared according to our previous study39. The Ir nanoparticles and $\\mathrm{FeCoO_{x}}$ nanocomposite were in situ photodeposited on the surface of ${\\mathrm{BiVO}}_{4}$ from an aqueous solution containing the precursors $\\mathrm{K}_{2}\\mathrm{Ir}{\\mathrm{Cl}_{6}},$ $\\mathrm{CoSO_{4}}$ , and redox $\\mathrm{[Fe(CN)_{6}]^{3-}}$ ions. The asobtained sample is hereafter denoted as $\\mathrm{Ir{-FeCoO_{x}}/B i V O_{4}}$ . As expected from our previous findings on the spatial separation of photogenerated electrons and holes on the anisotropic $\\mathrm{BiVO}_{4}{}^{32}$ , the Ir nanoparticles, and $\\mathrm{FeCoO_{x}}$ nanocomposite were clearly observed to be selectively deposited on the $\\{010\\}$ and $\\{110\\}$ facets of ${\\mathrm{BiVO}}_{4}$ , respectively (Fig. 2a, b). For comparison, the in situ photodeposition of single Ir or $\\mathrm{CoO_{x}}$ particles on ${\\mathrm{BiVO}}_{4}$ was similarly obtained (denoted as $\\mathrm{Ir/BiVO_{4}}$ and $\\mathrm{CoO_{x}/B i V O_{4}})$ , and the sample was characterized by field-emission scanning electron microscopy (FESEM) to further confirm the facet-selective deposition (Supplementary Fig. 1). It should be noted that the morphology of the cocatalysts located on the {110} facet of Ir$\\mathrm{FeCoO_{x}/B i V O_{4}}$ (Fig. 2b) is clearly different from that of the $\\mathrm{CoO_{x}/B i V O_{4}}$ sample (Supplementary Fig. 1b), demonstrating the possible interaction between Fe and Co-based compounds. And the change in the long wavelength range of UV-Vis diffuse reflectance spectra (DRS) can confirm the successful deposition of the dual-cocatalysts (Supplementary Fig. 2). The deposited Ir species were verified to exist as metallic Ir nanoparticles by means of $\\mathrm{\\DeltaX}$ -ray absorption near edge structure (XANES) spectroscopy (Supplementary Fig. 3) and high-resolution transmission electron microscopy image (Supplementary Fig. 4). \n\n![](images/f40cbc4a7447e5ead85e6c9bdcae63437b592a6f06a37d6725cbc6f90dfd05f3.jpg) \nFig. 1 The energy diagram for a two-step photoexcitation (also called Z-scheme) system with an aqueous redox mediator for overall water splitting. Red. cat.: reduction cocatalyst; $\\mathsf{O}_{\\mathsf{x}}$ . cat.: oxidation cocatalyst; RHE: reversible hydrogen electrode; HEP: ${\\sf H}_{2}$ -evolving photocatalyst; OEP: $\\mathsf{O}_{2}$ -evolving photocatalyst. \n\n![](images/102a8698176c19aa813eeef66c6fc22a4e0ba184a9e21e34514c69634a37db13.jpg) \nFig. 2 Morphology and structural characterizations of typical samples. a, b FESEM images of the $\\mathsf{I r{-F e C o O_{\\times}/B i V O_{4}}}$ with different magnification times. c–i Structural characterizations of the $\\mathsf{F e C o O_{\\times}/B i V O_{4}}$ sample together with references: c Normalized Fe K-edge XANES $\\upmu(\\mathsf{E})$ spectra. d Normalized Co K-edge XANES $\\upmu(\\mathsf{E})$ spectra. e Fe K-edge and Co K-edge radial distance $\\chi({\\sf R})$ space spectra. f Fourier-transformed (FT)-Extended $\\mathsf{X}$ -ray absorption fine structure (EXAFS) fitting curves at R space of Fe K-edge. g FT-EXAFS fitting curves at R space of Co K-edge. h Fe K-edge 3D contour wavelet transform. i Co K-edge 3D contour wavelet transform. \n\nTo unravel the formation of the $\\mathrm{FeCoO_{x}}$ nanocomposite on the $\\{110\\}$ facets of ${\\mathrm{BiVO}}_{4}$ , the existing state and dispersion of both Fe and Co elements on $\\mathrm{FeCoO_{x}/B i V O_{4}}$ (free of Ir nanoparticles to rule out its possible interference during characterization) were first analyzed. According to the elemental mapping results shown in Supplementary Fig. 5, both Fe and Co species are similarly located and dispersed, accompanied by the existence of O, which further demonstrates that $\\scriptstyle{\\mathrm{Co}}$ and Fe combine together in the form of oxidation state during the photo-oxidation process. The deposition of Fe should result from redox ions in the reaction solution. The coexistence of both Fe and Co can be further revealed by electron energy loss spectroscopy analysis (Supplementary Fig. 6). And their oxidation states can be confirmed to be $\\bar{\\mathrm{Fe}^{3+}}$ and ${\\mathrm{Co}}^{3+}$ by the Fe and Co K-edge XANES measurements through comparing with the reference materials (Fig. 2c, d, respectively). \n\nSecond, the radial distance space spectra $\\chi(\\mathbb{R})$ of Fe and Co in $\\mathrm{FeCoO_{x}/B i V O_{4}}$ and their corresponding references were analyzed, which provides more convincing support for the formation of nanocomposite. As shown in Fig. 2e and Supplementary Fig. 7, the peaks located at approximately $2.72\\mathring{\\mathrm{A}}$ assigned to the Fe–O–Co bond are consistently observed in both the Fe and Co K-edge of the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ sample, but no scattering path signals attributing to the $C o{-}C0$ bond $(2.41\\textup{\\AA})$ from $C\\mathrm{{o}}$ foil, Fe–Fe bond $(2.47\\mathrm{\\AA})$ from Fe foil, $_{\\mathrm{Co-O-Co}}$ bond $(2.69\\mathring\\mathrm{A})$ from CoOOH, or Fe–O–Fe bond $(2.86\\mathring{\\mathrm{A}})$ from FeOOH can be observed. This clearly reveals that the formation of nanocomposite is a homogeneous phase of bimetallic hydroxide, instead of single-phase Fe or Co hydroxides. It should be pointed out that the possible nanocomposite of $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ and $\\mathrm{Co}_{2}\\mathrm{O}_{3}$ can be ruled out by comparing the fingerprint feature pattern of normalized XANES $\\bar{\\upmu}(\\mathrm{E})$ spectra (Fig. 2c, d and Supplementary Fig. 8a, b) and the first derivative of the normalized XANES $\\upmu(\\mathrm{E})$ spectra (Supplementary Fig. 8c, d). In particular, as shown in Supplementary Fig. 8c, d, the peak positions of $\\mathrm{FeCoO_{x}/B i V O_{4}}$ are closer to the FeOOH and CoOOH references. Based on these results, the phase species of the $\\mathrm{FeCoO_{x}}$ on the surface of ${\\mathrm{BiVO}}_{4}$ sample can be deduced to be more similar to $\\mathrm{FeOOH/CoOOH}$ with respect to $\\mathrm{Fe}_{2}\\mathrm{O}_{3}/\\mathrm{Co}_{2}\\mathrm{O}_{3}$ . In addition, compared with the corresponding single-phase hydroxides FeOOH and CoOOH, $\\mathrm{Fe/BiVO_{4}^{-}}$ sample exhibits much shorter Fe–O bond and longer ${\\mathrm{Co-O}}$ bond, and the length of Co–O–Fe bond is between $_{\\mathrm{Co-O-Co}}$ and Fe–O–Fe (Fig. 2e). This demonstrates the existence of electron transfer and a strong interaction between Fe and Co in the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ sample, providing further proof about the formation of the nanocomposite. \n\n![](images/0e5617473722cf61957d68e2ace2c3eba32354290ca8ec3c32b0ec451b06c5ce.jpg) \nFig. 3 Electrochemical measurements and characterizations of typical samples. a Linear sweep voltammetry curves of typical samples in the $100~\\mathsf{m}\\mathsf{M}$ sodium phosphate buffer solution $\\mathsf{\\langle p H6.0\\rangle}$ containing $5{\\mathsf{m}}M$ $\\mathsf{K}_{3}[\\mathsf{F e}(\\mathsf{C N})_{6}]$ . b EIS spectra of typical samples in a $100~\\mathsf{m}\\mathsf{M}$ sodium phosphate buffer solution $\\mathsf{\\Gamma}(\\mathsf{p H}6.0)$ containing 5 mM $k_{3}[\\mathsf{F e}(\\mathsf{C N})_{6}]$ . SCE, saturated calomel electrode. c Photocurrent density-potential curves of ${\\mathsf{B i V O}}_{4},$ $\\mathsf{C o O}_{\\mathsf{x}}/\\mathsf{B i V}\\mathsf{O}_{4},$ and $\\mathsf{F e C o O}_{\\times}/$ $B i V O_{4}$ . d EIS spectra of ${\\mathsf{B i V O}}_{4},$ $\\mathsf{C o O}_{\\mathsf{x}}/\\mathsf{B i V}\\mathsf{O}_{4},$ and $\\mathsf{F e C o O_{\\times}/B i V O_{4}}$ in a $100~\\mathsf{m}{\\mathsf{M}}$ sodium phosphate buffer solution $(\\mathsf{p H}6.0)$ . e Comparison of difference of OCPs on the $B i V O_{4},$ , $\\mathsf{C o O}_{\\mathsf{x}}/\\mathsf{B i V}\\mathsf{O}_{4},$ and $\\mathsf{F e C o O_{\\times}/B i V O_{4}}$ under dark and illumination conditions. Measurements were taken at least three times for separate samples and average values are presented with the standard deviation as the error bar. f Comparison of promotion effect of cocatalysts on the SPV values of the $B i V O_{4}$ photocatalyst under chopped visible light irradiation. \n\nThird, the formation of the nanocomposite can be further verified by the results of quantitative $\\chi(\\mathbb{R})$ space spectra fitting and wavelet transform of $\\chi(\\mathbf{k})$ . As seen in Supplementary Table 1, Fe–O–Co bond with similar coordination numbers $(\\mathrm{Fe-O-Co};2$ at ca. $2.745\\mathring{\\mathrm{A}}$ in Fe K-edge; Co–O–Fe: 2 at ca. $2.761\\mathring{\\mathrm{A}}$ in Co Kedge) can be confirmed. The good fitting results of $\\chi(\\mathbb{R})$ and $\\chi(\\mathbf{k})$ space spectra (Fig. 2f, $\\mathbf{g}$ and Supplementary Fig. 9) with reasonable R-factors and the obtained fitting parameters (Supplementary Table 1) provide a quantitative illustration of the existence of $\\mathrm{Fe-O-Co}$ bond originating from the nanocomposite structure. As similarly revealed in Fig. 2h, i, the Fe–O–Co bond located at $[\\chi(\\mathrm{k}),\\chi(\\mathrm{R})]$ of [4.2, 2.74] or Co–O–Fe bond ([6.4, 2.76]) as well as the $_\\mathrm{Fe-O}$ bond ([4.8, 1.64]) or ${\\mathrm{Co-O}}$ bond ([4.2, 1.88]) with two scattering path signal can be observed for both Fe and Co K-edge wavelet transform of $\\chi(\\mathrm{k})$ spectra of $\\mathrm{FeCoO_{x}/}$ ${\\mathrm{BiVO}}_{4}$ , but the characteristic scattering path signal of Fe–Fe bond ([8.4, 2.52]), Co–Co bond ([7.8, 2.42]), Fe–O–Fe bond ([5.6 2.82]) or Co–O–Co bond ([6.8, 2.78]) is not observed as similarly as the reference sample (Supplementary Fig. 10). \n\nEffect of reduction and oxidation cocatalysts. As shown in Fig. 1, the water oxidation process of OEP is strongly dependent on both the reduction and oxidation cocatalysts. Therefore, understanding the effect of deposited Ir and $\\mathrm{FeCoO_{x}}$ cocatalysts is highly desirable. As depicted in Fig. 3a, the ability of the deposited metallic Ir to reduce $\\mathrm{[\\dot{F}e(C N)_{6}]^{3-}}$ ions was evaluated and found to exhibit a much higher cathode current than that of our previously reported Au nanoparticles on $\\mathrm{BiVO}_{4}{}^{16}$ , indicating its superior performance in activating and reducing the $\\mathrm{[Fe(CN)_{6}]^{3-}}$ ions. In addition, the deposition of Ir or Au cocatalyst on the surface of ${\\mathrm{BiVO}}_{4}$ can significantly decrease the charge-transfer resistance $\\mathrm{(R_{ct})}$ across the semiconductor/electrolyte interface (Fig. 3b), further revealing the effectiveness of the deposited cocatalysts in accelerating the electron transfer from ${\\mathrm{BiVO}}_{4}^{-}$ to the $\\mathrm{[Fe(CN)_{6}]^{3-}}$ ions (values of $\\mathrm{R}_{s}$ and $\\mathrm{R_{ct}}$ listed in Supplementary Table 2). Meanwhile, the promotion effect of Ir is better than that of Au. \n\nTo determine the effect of the $\\mathrm{FeCoO_{x}}$ nanocomposite, the efficiencies of charge separation and injection (denoted as $\\boldsymbol\\upeta_{\\mathrm{sep}}$ and $\\upeta_{\\mathrm{inj}}$ respectively) on the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ photoanode $(\\dot{\\mathrm{CoO_{x}}}/\\$ $\\mathrm{Bi\\check{V}O_{4}}$ and ${\\mathrm{BiVO}}_{4}$ as references) were evaluated by referring to a previous photoelectrochemical analysis22. Figure 3c and Supplementary Fig. 11a show that the current of the ${\\mathrm{BiVO}}_{4}$ photoanode can be remarkably promoted after the deposition of $\\mathrm{FeCoO_{x}}$ and $\\mathrm{CoO_{x}}$ in both cases, with and without the use of a hole scavenger, among which $\\mathrm{FeCoO_{x}}$ exhibits a much better promotion effect than $\\mathrm{CoO_{x}}$ . On this basis, both $\\boldsymbol\\upeta_{\\mathrm{sep}}$ and $\\mathfrak{n}_{\\mathrm{inj}}$ on the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ photoanode were calculated to be higher than that of the $\\mathrm{CoO_{x}/B i V O_{4}}$ photoanode (Supplementary Fig. 11c, d), demonstrating the better promotion effect of the $\\mathrm{FeCoO_{x}}$ nanocomposite on both the separation of photogenerated carriers and the injection of holes into the reaction solution (i.e., surface reaction) with respect to $\\mathrm{CoO_{x}}$ . The excellent promotion of $\\mathrm{FeCoO_{x}}$ on the surface reaction can be further supported by the electrochemical impedance spectroscopy (EIS) results given in Fig. 3d and Supplementary Table 3, based on which the $\\mathrm{R}_{\\mathrm{ct}}$ resistance on the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ electrode is the smallest among the three electrodes investigated. On the other hand, the superior promotion effect of $\\mathrm{FeCoO_{x}}$ on the charge separation can also be evidenced by its larger open-circuit potential (OCP) on the $\\mathrm{FeCoO_{x}/B i V\\dot{O}_{4}}$ compared with $\\mathrm{CoO_{x}/B i V O_{4}}$ (Fig. 3e). Based on the previous result that a larger difference of OCPs under dark and illumination conditions corresponds to more intense band bending40, therefore the $\\mathrm{FeCoO_{x}^{-}/B i V O_{4}}$ sample can be deduced to own a more intense band bending than the $\\mathrm{CoO_{x}/B i V O_{4}}$ sample, leading to a significantly improved $\\boldsymbol\\upeta_{\\mathrm{sep}}$ and the more intense band bending should result from the p-n heterojunction between $\\mathrm{FeCoO_{x}}$ and $\\mathrm{BiVO_{4}}^{41}$ . \n\nEncouraged by the understanding of the functionalities of both reduction and oxidation cocatalysts (i.e., Ir and $\\mathrm{FeCoO_{x})}$ , the synergistic effect of dual-cocatalysts on the charge separation was examined using the surface photovoltage (SPV) spectrum. As shown in Fig. 3f, the sample with both Ir and $\\mathrm{FeCoO_{x}}$ deposited exhibits a greater SPV amplitude with respect to the sample with single Ir or $\\mathrm{FeCoO_{x}}$ loaded. It should be mentioned that a much better promotion effect is also observed for the sample with facetselective deposition of Ir and $\\mathrm{FeCoO_{x}}$ compared to that with facet-selective deposition of Au and $\\mathrm{CoO_{x}}$ . These results reveal the importance of both facet-selective deposition of dualcocatalysts and the development of innovative cocatalysts for maximizing the promotion effect. \n\nDensity functional theory calculations on the $\\mathbf{O}_{2}$ -evolving reaction. Density functional theory (DFT) calculations were performed to further elucidate the microscopic mechanism of the promotion effect of the $\\mathrm{FeCoO_{x}}$ cocatalyst on the $\\mathrm{O}_{2}$ -evolving reaction (OER) from the viewpoint of both surface catalysis and interfacial charge transfer. As shown in Fig. $\\mathtt{4a\\mathrm{-c}}_{\\mathtt{i}}$ , the $\\mathrm{CoO_{x}\\mathrm{-FeO_{x}\\mathrm{-Co\\bar{O}_{x}\\mathrm{-FeO_{x}}}}}$ and $\\mathrm{CoO_{x}{-}C o O_{x}{-}C o O_{x}{-}C o O_{x}{-}C o O_{x}}$ clusters were simply extracted and placed on the $\\{110\\}$ facets of ${\\mathrm{BiVO}}_{4}$ to simulate the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ and $\\mathrm{CoO_{x}/B i V O_{4}}$ interfaces, respectively, which origin from the structure of EXAFS measurement. And the schematic of the whole OER mechanism on the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ and $\\mathrm{CoO_{x}/B i V O_{4}}$ is given in Supplementary Fig. 12 and illustrated in detail in supporting information. Fig. 4d and e presents the Gibbs free energy change diagram of the four elementary steps of OER on the surface of $\\mathrm{Fe\\bar{Co}O_{x}/B i V O_{4}}$ and $\\mathrm{CoO_{x}/B i V O_{4}}.$ during which the Co and Fe sites on $\\mathrm{FeCoO_{x}/}$ ${\\mathrm{BiVO}}_{4}$ were mainly considered as the active sites, respectively. It was demonstrated that the rate-determining step of $\\mathrm{FeCoO_{x}/}$ ${\\mathrm{BiVO}}_{4}$ $\\scriptstyle\\mathrm{Co}$ or Fe site) and $\\mathrm{CoO_{x}/B i V O_{4}}$ is the adsorption of one $\\mathrm{OH^{-}}$ to form ${\\mathrm{OOH^{*}}}$ from ${{\\cal O}^{*}}$ . The largest decrease of the Gibbs free energy barrier was observed for $\\mathrm{\\bar{Fe}C o O_{x}/B i V O_{4}}$ (Co site), whereas the OER performance of $\\mathrm{FeCoO_{x}/B i V O_{4}}$ (Fe site) is much weaker than that of the corresponding Co site, suggesting that the $\\scriptstyle{\\mathrm{Co}}$ site acts as the main OER site. \n\nNext, we plotted the calculated densities of states (DOS) of the ${\\mathrm{BiVO}}_{4}$ {110} surface, $\\mathrm{CoO_{x}/B i V O_{4}}$ $\\left\\{110\\right\\}$ interface, and $\\mathrm{FeCoO_{x}}/$ ${\\mathrm{BiVO}}_{4}$ {110} interface (Fig. 4f, g, h and Supplementary Fig. 13). Both $\\mathrm{CoO_{x}}$ and $\\mathrm{FeCoO_{x}}$ are set to be located at the {110} facets of ${\\mathrm{BiVO}}_{4}$ . For the bare ${\\mathrm{BiVO}}_{4}$ $\\{110\\}$ surface, there is a direct bandgap about $2.1\\mathrm{eV}$ between the valence band and conduction band (Fig. 4f). However, when the $\\mathrm{CoO_{x}\\mathrm{-FeO_{x}\\mathrm{-CoO_{x}\\mathrm{-FeO_{x}}}}}$ cluster is settled on the $\\{110\\}$ surface of ${\\mathrm{BiVO}}_{4}$ , a mixed band mainly composed of Co 3d, Fe 3d, and O 2p states emerges between the valence band and conduction band (Fig. 4g). It has been demonstrated that the localization of photoexcited holes, as well as subsequent charge separation can be promoted through the formation of mixed bands42. In addition, the DOS of the $\\mathrm{CoO_{x}/B i V O_{4}\\left\\{\\right.}\\Omega}$ {110} interface (Fig. 4h) has no similar result as that of the $\\mathrm{FeCoO_{x}/B i V O_{4}\\{110\\}}$ interface (Fig. $^{4}\\mathrm{g},$ bandgap $=2.0\\mathrm{eV},$ , implying that the loading of $\\mathrm{FeCoO_{x}}$ on ${\\mathrm{BiVO}}_{4}$ should have better charge separation. In order to microscopically understand the better electron transfer on the $\\mathrm{FeCoO_{x}}$ with respect to the $\\mathrm{CoO_{x},}$ their bader charges were calculated and compared. As given in Supplementary Table 4, the changing trend of bader charge on the Co active site after introduction of Fe (increase from $1.2\\mathsf{a.u}$ . in $\\mathrm{CoO_{x}/B i V O_{4}}$ to 1.3 a.u. in $\\mathrm{FeCoO_{x}/B i V O_{4})}$ is in line with the changing one of experimental valence state (Supplementary Fig. 14). Compared to the $\\mathrm{CoO_{x}/B i V O_{4}}$ , the higher bader charge on the Co active site in $\\mathrm{FeCoO_{x}/B i V O_{4}}$ indicates its stronger oxidation capacity as well as more beneficial electron transfer43. In addition, as shown in Supplementary Fig. 15, the d-band center (Ed) value of $\\scriptstyle{\\mathrm{Co}}$ active sites in $\\mathrm{FeCoO_{x}/B i V O_{4}}$ was calculated as $-1.63\\mathrm{eV}$ , which is sharply increased with respect to the $\\mathrm{CoO_{x}/B i V O_{4}}$ $(-2.56\\mathrm{eV})$ . This demonstrates that the electronic structure of Co active sites can be well modulated and optimized in the $\\mathrm{FeCoO_{x}/B i V O_{4}}$ due to the introduction of Fe atoms to get much stronger adsorption properties to the OER intermediates according to the d-band center theory44,45. According to previous experimental and theoretical demonstration, the Fe site is relatively inactive during the OER process46,47. So we deduce that the role of Fe is to assist in modifying the geometric and electronic structure of Co in the OER together with our results that very limited contributions of Fe 3d states are observed for the mixed band (Fig. $\\ensuremath{\\mathbf{4g}})$ . These conclusions from DFT calculation well match with the aforementioned experimental results. \n\nPhotocatalytic performances of Z-scheme OWS. The modified ${\\mathrm{BiVO}}_{4}$ was employed as an OEP for the assembly of efficient Z-scheme OWS systems together with $\\mathrm{ZrO_{2}/T a O N}$ or $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ as a HEP under visible light irradiation. The HEPs were prepared and modified with cocatalysts according to previously reported procedures16,48,49, and the diffraction structure and morphology features were coarsely revealed by their powder X-ray diffraction patterns and FESEM images (Supplementary Figs. 16, 17). The contents of deposited Ir and Co on ${\\mathrm{BiVO}}_{4}$ were optimized to be 0.8 and $0.2\\mathrm{wt\\%}$ , respectively, via the photocatalytic $\\mathrm{O}_{2}$ evolution reaction (Supplementary Figs. 18, 19). As seen in Fig. 5a, stable evolution curves of $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ with the stoichiometric molar ratio of 2:1 can be observed at the experimental region using the optimized photocatalysts, indicating the successful achievement of the OWS process. Moreover, regardless of using $\\mathrm{ZrO_{2}/T a O N}$ or $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ as the HEP, similar OWS activities with the initial rates of $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ evolution (ca. 160 and $80\\upmu\\mathrm{mol/h}$ , respectively) were separately observed, implying that the $\\mathrm{O}_{2}$ evolution on ${\\mathrm{BiVO}}_{4}$ is the ratedetermining step, as similarly observed in our previous study16. It should be pointed out that when the I $\\mathrm{r{-}C o O_{x}(I m p.)/B i V O_{4}}$ with Ir and Co randomly impregnated is employed as the OEP, the OWS will not be achieved owing to the significantly decreased $\\mathrm{O}_{2}$ -evolving activity (Supplementary Fig. 20). This indicates the importance of facet-selective deposition of dual-cocatalysts in promoting the $\\mathrm{O}_{2}$ -evolving activity and fabricating a successful OWS system. The multiple cycles of time-course curves shown in Supplementary Figs. 21 and 22 demonstrate the good photostability of the system constructed in this study. The AQE value of OWS as a function of absorption wavelength was found to be in good accordance with the UV-Vis DRS of the OEP and HEP, indicating that the Z-scheme OWS system is driven by visible light excitation (Fig. 5b and Supplementary Fig. 23). The optimal AQE value of OWS at $420\\pm10\\mathrm{nm}$ is $12.3\\%$ , and the AQE value at the $500\\pm10\\mathrm{nm}$ is about $3\\%$ , demonstrating the wide visible light utilization. According to the activity measurements under the irradiation of AM $1.5\\dot{\\mathrm{G}}$ (Fig. 5c), the STH energy conversion efficiency was calculated to be $0.6\\%$ . To the best of our knowledge, both the AQE and STH values should be the highest among the suspending particulate photocatalytic OWS systems using inorganic semiconductor materials with visible light utilization, regardless of one-step or two-step (i.e., Z-scheme) systems. \n\n![](images/545ee70e0c27fbf6853bcef874c1df250298be70aae7911ef21da42a16bc9262.jpg) \nFig. 4 Theoretical understanding of the promotion effect of the $\\pmb{\\operatorname{FeCoO}}_{\\mathbf{x}}$ cocatalyst. Visual representation of structures of $B i V O_{4}$ {110} surface (a) $\\mathsf{F e C o O_{x}/B i V O_{4}}$ {110} interface $(\\pmb{\\ b})$ and $\\mathsf{C o O}_{\\times}/\\mathsf{B i V O}_{4}$ {110} interface (c) for the DFT calculations. d Free energy diagram for OER process on $\\mathsf{F e C o O_{x}/B i V O_{4}}$ and $\\mathsf{C o O}_{\\times}/\\mathsf{B i V O}_{4}$ {110} interfaces. The surface structures with various reaction intermediates are shown alongside the free energy diagram. $\\mathsf{U}_{\\mathsf{p d s}},$ equilibrium potential for the potential determining step. e Theoretical overpotential plot with $0^{*}$ and ${\\mathsf{O H}}^{*}$ binding energies as descriptors. Calculated densities of state for the $B i V O_{4}$ {110} surface $(\\bullet),$ , $\\mathsf{F e C o O}_{\\times}/\\mathsf{B i V O}_{4}$ {110} interface $\\mathbf{\\sigma}(\\pmb{\\mathsf{g}})$ , and $\\mathsf{C o O}_{\\times}/\\mathsf{B i V O}_{4}$ {110} interface ${\\bf\\Pi}({\\bf h})$ . \n\n# Discussion \n\nHere, we show a highly efficient Z-scheme OWS system with benchmarked AQE and STH value over particulate inorganic semiconductor photocatalysts with visible light utilization. The success is mainly ascribed to the in situ facet-selective photodeposition of innovative dual-cocatalysts (Ir nanoparticles and $\\mathrm{FeCoO_{x}}$ nanocomposite), based on which the sluggish water oxidation on ${\\mathrm{BiVO}}_{4}$ can be largely overcome. Besides the finding and structural unraveling of efficient cocatalysts, the microscopic work mechanism of both reduction and oxidation cocatalysts on the interfacial charge transfer and surface catalysis has been well elucidated respectively. These results should be encouraging and enlightening to the design and assembly of OWS systems for more efficient solar-to-chemical energy conversion. \n\n# Methods \n\nSynthesis of modified-TaON and $B i v o_{4}$ . $\\mathrm{ZrO}_{2}$ -modified TaON $(Z\\mathrm{r/Ta}=0.1\\$ ) sample and $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ $(\\mathrm{Mg/Ta}=0.15\\$ composite were used as the HEPs. The $\\mathrm{ZrO}_{2}$ -modified sample was synthesized by nitridation of the $\\mathrm{ZrO}_{2}/\\$ $\\mathrm{Ta}_{2}\\mathrm{O}_{5}$ composite and the $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ was prepared by nitridation of the $\\mathrm{MgTa_{2}O_{6}/T a_{2}O_{5}}$ composite under an ammonia flow $(2\\bar{0}\\mathrm{mL}\\mathrm{min}^{-1}.$ ) at $1123\\mathrm{K}$ for $15\\mathrm{h}$ by referring to the previous works48,49. ${\\mathrm{BiVO}}_{4}$ was chosen as the OEP, which was similarly synthesized according to our previous hydrothermal process39. Typically, 10 mmol $\\mathrm{NH_{4}V O_{3}}$ and 10 mmol ${\\mathrm{Bi}}(\\mathrm{NO}_{3})_{3}{\\cdot}5{\\mathrm{H}}_{2}{\\mathrm{O}}$ were dissolved in $2.0\\mathrm{M}$ nitric acid solution, whose pH value was then adjusted to be about 0.5 with \n\n![](images/fdaa78ad00f2c84145b88aa01ec252d0b3d81b51ccdb62913efa9a663d86e40c.jpg) \nFig. 5 Photocatalytic activity of Z-scheme OWS. a Time course of Z-scheme OWS on the optimized conditions under visible light irradiation. b Dependence curve of AQE value as a function of irradiation wavelength, and UV-Vis DRS of the HEP and OEP. c Time curve of Z-scheme OWS under illumination of the standard solar simulator (AM 1.5 G, $100\\mathsf{m w c m}^{-2})$ . Reaction conditions: a $50\\mathrm{mg}$ OEP, $50\\mathrm{mg}$ HEP $(Z r O_{2}/\\mathsf{T a O N}$ $1.0\\mathrm{wt\\%}$ Rh, $1.5\\mathrm{wt\\%}$ Cr) or $50\\mathrm{mg}$ OEP, $100~\\mathrm{{mg}}$ HEP $(M g\\mathrm{Ta}_{2}\\mathrm{O}_{6-\\times}\\mathrm{N}_{\\mathrm{y}}/\\mathrm{TaON},$ $2.5\\mathsf{w t\\%}$ Rh, $3.75\\mathrm{wt\\%}$ Cr), $100m L25m M$ sodium phosphate buffer solution $\\left(\\mathsf{p H}6.0\\right)$ containing $k_{4}[F e(C N)_{6}]$ $10\\mathsf{m}\\mathsf{M},$ ), 300 W xenon lamp $(\\lambda\\ge420\\mathsf{n m})$ , temperature: $288\\mathsf{K},$ Pyrex top-irradiation type. b $75\\mathrm{mg}$ OEP, $75\\mathsf{m g H E P}$ $(Z r O_{2}/\\mathsf{T a O N}$ , $1.0\\mathrm{wt\\%}$ Rh, $1.5\\mathsf{w t\\%}(\\mathsf{r})$ , $150\\mathrm{mL}25\\mathrm{mM}$ sodium phosphate buffer solution $\\mathsf{\\langle p H6.O\\rangle}$ containing $k_{4}[F e(C N)_{6}]$ ( $\\mathsf{10}\\mathsf{m}\\mathsf{M},$ , 300 W xenon lamp, temperature: $298\\mathsf{K},$ Pyrex top-irradiation type. (c) 50 mg OEP, $50\\mathrm{mg}$ HEP $(Z r O_{2}/\\mathsf{T a O N}_{\\cdot}$ , $1.0\\mathrm{wt\\%}$ Rh, $1.5\\:\\mathrm{wt\\%}\\:\\mathrm{Cr}$ ), $100m L25m M$ sodium phosphate buffer solution $\\left(\\mathsf{p H}6.0\\right)$ containing $k_{4}[\\mathsf{F e}(\\mathsf{C N})_{6}]$ $(10\\mathsf{m}M)$ , temperature: $288\\mathsf{K},$ Pyrex top-irradiation type. \n\nammonia solution $(25-28\\mathrm{wt\\%}$ ). The mixed solution was strongly stirred until the observation of a light yellow precipitate that was further aged for about $^{2\\mathrm{h}}$ and then transferred to a Teflon-lined stainless steel autoclave for $^{10\\mathrm{h}}$ hydrothermal treatment at $473\\mathrm{K}$ . \n\nPreparation of $\\pmb{\\mathrm{Ir}}/\\pmb{\\mathrm{BiV}}\\pmb{0_{4}}$ and $\\mathsf{C o o}_{\\mathsf{x}}/\\mathsf{B i v}\\mathsf{o}_{4}$ . The deposition of Ir or $\\mathrm{CoO_{x}}$ on the surface of ${\\mathrm{BiVO}}_{4}$ was carried out by the photodeposition method. Typically, $0.2{\\mathrm{g}}$ ${\\mathrm{BiVO}}_{4}$ powder was dispersed in deionized water containing a calculated amount of $\\mathrm{K}_{2}\\mathrm{Ir}{\\mathrm{Cl}_{6}}$ $(2.0\\mathrm{wt\\%})$ or $\\mathrm{CoSO_{4}}$ $(2.0\\mathrm{wt\\%})$ ), and hole $\\mathrm{(CH_{3}O H)}$ or electron $\\left(\\mathrm{NaIO}_{3}\\right)$ scavenger, separately. The well-mixed solution was then irradiated by $300\\mathrm{W}$ xenon lamp free of any cut-off filter for $^{2\\mathrm{h}}$ . The as-obtained powders after filtration and washing are correspondingly denoted as $\\mathrm{Ir/BiVO_{4}}$ and $\\mathrm{CoO_{x}/B i V O_{4}}$ , which were used for further characterizations and tests. \n\nPreparation of $\\mathsf{F e C o O}_{\\mathsf{x}}/\\mathsf{B i V O}_{4}$ and $\\mathsf{i r}{\\mathsf{-F e C o O}}_{\\mathsf{x}}/\\mathsf{B i V O}_{4}$ . Both of the samples were similarly prepared by the in situ photodeposition. Meanwhile, $25\\mathrm{mM}$ phosphate buffer solution (PBS, $\\mathrm{\\pH}=6$ , $50~\\mathrm{mL}$ ) containing a calculated amount of $\\mathrm{CoSO_{4}}$ and $\\mathrm{[Fe(CN)_{6}]^{3-}}$ ions was prepared for the synthesis of $\\mathrm{FeCoO_{x}/B i V O_{4}};$ while $25\\mathrm{mM}$ phosphate buffer solution (PBS, $\\mathfrak{p H}=6$ , $50~\\mathrm{mL}$ ) containing a calculated amount of $\\mathrm{K}_{2}\\mathrm{Ir}{\\mathrm{Cl}_{6}}$ , $\\mathrm{CoSO_{4}}$ and $\\mathrm{[Fe(CN)_{6}]^{3-}}$ ions was prepared for synthesis of Ir- $\\mathrm{\\cdotFeCoO_{x}/}$ ${\\mathrm{BiVO}}_{4}$ . \n\nPreparation of HEP. The deposition of nanoparticulate rhodium-chromium mixed oxides (denoted as $\\mathrm{Rh}_{\\mathrm{y}}\\mathrm{Cr}_{2-\\mathrm{y}}\\mathrm{O}_{3})$ as a cocatalyst was carried out by the photodeposition method. $0.2\\mathrm{~g~}\\mathrm{Zr}\\mathrm{O}_{2}$ -modified TaON or $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ was dispersed in $20\\mathrm{v\\%}150\\mathrm{mL}$ methanol solution. A certain amount of ${\\mathrm{Na}}_{3}{\\mathrm{RhCl}}_{6}$ and ${\\mathrm{K}}_{2}{\\mathrm{CrO}}_{4}$ $1.0\\mathrm{wt\\%}$ Rh and $1.5\\mathrm{wt\\%}$ Cr vs. photocatalyst for $\\mathrm{ZrO_{2}/T a O N}$ and $2.0\\mathrm{wt\\%}$ Rh and $3.75\\mathrm{wt\\%}$ Cr vs. photocatalyst for $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N)}$ were added as the precursors. The deposition was carried out under the full-spectral irradiation of $300\\mathrm{W}$ xenon lamp for $^{6\\mathrm{h}}$ . Whereafter, the irradiated solution was centrifuged and washed with distilled water, and then dried at $353\\mathrm{K}$ for overnight to get powder for use. \n\nPreparation of $B i v o_{4}$ electrodes. The ${\\mathrm{BiVO}}_{4}$ photoanode was prepared according to the previous work50. First of all, ${\\mathrm{Bi}}(\\mathrm{NO}_{3})_{3}{\\cdot}5\\mathrm{H}_{2}\\mathrm{O}$ , $\\mathrm{NH_{4}V O_{3}}$ , and polyvinyl alcohol were dissolved in $60\\%$ ${\\mathrm{HNO}}_{3}$ to prepare the precursor solution. Then the precursor solution was spin-coated on the FTO followed by heat treatment at $623\\mathrm{K}$ for $^{2\\mathrm{h}}$ in air to form the ${\\mathrm{BiVO}}_{4}$ seed layer. Second, the treated FTO was immersed in $2.0\\mathrm{M}\\mathrm{HNO}_{3}$ aqueous solution containing ${\\mathrm{Bi}}({\\mathrm{NO}}_{3})_{3}{\\cdot}5{\\mathrm{H}}_{2}{\\mathrm{O}}$ and ${\\mathrm{NH}}_{4}{\\mathrm{VO}}_{3}$ , whose $\\mathrm{\\tt{pH}}$ was adjusted to be 0.9 by adding ${\\mathrm{NH}}_{3}{\\cdot}{\\mathrm{H}}_{2}{\\mathrm{O}}$ drop by drop. The formed ${\\mathrm{BiVO}}_{4}$ precursor film solution was transferred to a Teflon-lined autoclave with the as-prepared substrate for hydrothermal treatment at $473\\mathrm{K}$ for $12\\mathrm{{h}}$ . The ${\\mathrm{BiVO}}_{4}$ photoanode film was finally calcined at $773\\mathrm{K}$ for $^{4\\mathrm{h}}$ . \n\nAs for the selective deposition of $\\mathrm{Ir}$ and $\\mathrm{FeCoO_{x}}$ cocatalysts on the ${\\mathrm{BiVO}}_{4}$ photoanode, similar in situ photodeposition method as the powder was adopted. Specifically, the photoanode was immersed in $25\\mathrm{mM}$ phosphate buffer solution (PBS, $\\mathrm{\\pH}=6$ , $50~\\mathrm{mL}$ ) containing the $\\mathrm{K}_{2}\\mathrm{Ir}{\\mathrm{Cl}_{6}}$ or/and $\\mathrm{CoSO_{4}}$ $\\mathrm{(K_{2}I r C l_{6}}$ : $40\\upmu\\mathrm{L};$ $\\mathrm{CoSO_{4}}$ : $10\\upmu\\mathrm{L}$ , the concentration of solution: $\\mathrm{1\\mg/mL}$ ) and $\\mathrm{K}_{3}[\\mathrm{Fe(CN)}_{6}]$ $(0.5\\mathrm{mM})$ and irradiated for $^{3\\mathrm{h}}$ Similarly, $\\mathrm{CoO_{x}}$ was photodeposited on the surface of ${\\mathrm{BiVO}}_{4}$ to prepare the $\\mathrm{CoO_{x}/B i V O_{4}}$ photoanode. \n\nMeasurements of AQE and STH conversion efficiency. The AQE was measured using a Pyrex top-irradiation-type reaction vessel and a $300\\mathrm{W}$ xenon lamp fitted with band-pass filters (ZBPA420, Asahi Spectra Co., FWHM: $10\\mathrm{nm}$ ). The number of photons reaching the solution was measured using a calibrated Si photodiode (LS-100, EKO Instruments Co., LTD.), and the AQE $(\\phi)$ was calculated using the following Eq. (1): \n\n$$\n\\phi(\\%)=(A R/I)\\times100\\\n$$ \n\nwhere $A,R,$ and $I$ are coefficients, A represents a coefficient (4 for $\\mathrm{H}_{2}$ evolution; 8 for $\\mathrm{O}_{2}$ evolution) and $R$ represents the evolution rate of $\\mathrm{H}_{2}$ or $\\mathrm{O}_{2}$ . As measured and calculated, the total number of incident photons at the wavelength of 420, 460, 480, 500, and $560\\mathrm{nm}$ are $8.4\\times10^{20}$ , $6.5\\ \\times\\dot{10}^{20}$ , $7.1\\times10^{20}$ , $4.8\\times10^{\\overline{{20}}}$ , and $6.9\\times10^{20}$ photons $\\ensuremath{\\mathrm{h}}^{-1}$ , respectively. The evolution rates of $\\mathrm{H}_{2}$ on the system containing $\\mathrm{Rh_{y}C r_{2-y}O_{3}{-}Z r O_{2}/T a O N}$ and $\\mathrm{Ir{-FeCoO_{x}}/B i V O_{4}}$ photocatalysts under the wavelength of 420, 460, 480, 500, and $560\\mathrm{nm}$ were tested to be 41.6, 23.0, 17.5, 7.4, and $0\\upmu\\mathrm{mol}\\mathrm{h}^{-1}$ , respectively. The evolution rates of $\\mathrm{H}_{2}$ on the system containing $\\mathrm{Rh}_{\\mathrm{y}}\\mathrm{Cr}_{2-\\mathrm{y}}\\mathrm{O}_{3}\\mathrm{-MgTa}_{2}\\mathrm{O}_{6-\\mathrm{x}}\\mathrm{N}_{\\mathrm{y}}/\\mathrm{TaON}$ and $\\mathrm{Ir{-FeCoO_{x}}/B i V O_{4}}$ photocatalysts under the wavelength of 420, 460, 480, and $560\\mathrm{nm}$ were tested to be 42.4, 19.0, 9.0, and $0\\upmu\\mathrm{mol}\\mathrm{h}^{-1}$ , respectively. \n\nThe STH energy conversion efficiency $(\\eta)$ was calculated according to the following Eq. (2): \n\n$$\n\\eta(\\%)=(R_{\\mathrm{H}}\\times\\varDelta G^{\\mathrm{O}})/(P\\times S)\\times100\n$$ \n\nwhere $R_{\\mathrm{H}},\\Delta G^{\\circ}$ , $P,$ and $s$ denote the rate of $\\mathrm{H}_{2}$ evolution $(\\mathrm{mol}\\ s^{-1})$ in photocatalytic water splitting, standard Gibbs energy of water $(237.13\\times10^{3}\\mathrm{J}\\mathrm{mol}^{-1}\\$ ), intensity of simulated sunlight $(0.1\\mathrm{W}\\mathrm{cm}^{-2}$ ), and irradiation area $(4.0\\thinspace{\\mathrm{cm}}^{2})$ , respectively. The light source was an $\\mathrm{AM}1.5\\mathrm{G}$ solar simulator (XES-40S2-CE, San-Ei Electric), and a top-irradiation reaction vessel was used. The initial rates of $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ evolution are about 36 and $18\\upmu\\mathrm{mol/h}$ , separately. \n\nPhotoelectrochemical tests. As for the tests of linear sweep voltammetry (LSV) and EIS, a platinum plate was used as a counter electrode and the saturated calomel electrode (SCE) as the reference electrode. The phosphate buffer solution $({\\mathrm{pH}}=6 $ $0.1\\mathrm{M})$ with 5 mM $\\mathrm{K}_{3}[\\mathrm{Fe(CN)}_{6}]$ aqueous solution and phosphate buffer solution $\\mathrm{(pH=6,0.1M)}$ were used as the electrolyte. The potential of the working electrode was controlled by a potentiostat (CHI 660E) for the LSV test and potentiostat (Solartron analytic AMETEK) for the EIS test. Before the measurement, the solution was purged with argon gas. The Nyquist plots calculated from EIS were performed from 100,000 to $0.1\\mathrm{Hz}$ . Data were fitted using Zview software. \n\nCurrent–voltage $\\left(J-V\\right)$ curves under irradiation and darkness were recorded on an electrochemical workstation (CHI 660E). The OCP of photoanode were recorded under illumination and darkness using electrochemical workstation (Solartron analytic AMETEK). A $300\\mathrm{W}$ xenon lamp was used as the light source and the irradiation intensity was high enough to produce a flat band condition of the photoanodes. The electrolyte for $J{-}V$ curves and OCP was 1 M KBi $(\\mathrm{pH}=9\\$ ). 0.2 M ${\\mathrm{Na}}_{2}{\\mathrm{SO}}_{3}$ was added to the electrolyte as a hole scavenger if necessary. \n\n# Data availability \n\nThe data that support the findings of this study are available from the source data. Source data are provided with this paper. \n\nReceived: 26 April 2021; Accepted: 6 January 2022; Published online: 25 January 2022 \n\n# References \n\n1. Fujishima, A. & Honda, K. Electrochemical photolysis of water at a semiconductor electrode. Nature 238, 37–38 (1972). \n2. Lewis, N. S. Toward cost-effective solar energy use. Science 315, 798–801 (2007). \n3. Kudo, A. & Miseki, Y. Heterogeneous photocatalyst materials for water splitting. Chem. Soc. Rev. 38, 253–278 (2009). \n4. Chen, X. et al. Semiconductor-based photocatalytic hydrogen generation. Chem. Rev. 110, 6503–6570 (2010). \n5. Linic, S., Christopher, P. & Ingram, D. B. Plasmonic-metal nanostructures for efficient conversion of solar to chemical energy. Nat. Mater. 10, 911–921 (2011). \n6. Pinaud, B. A. et al. Technical and economic feasibility of centralized facilities for solar hydrogen production via photocatalysis and photoelectrochemistry. Energy Environ. Sci. 6, 1983–2002 (2013). \n7. Li, X., Tung, C. & Wu, L. Semiconducting quantum dots for artificial photosynthesis. Nat. Rev. Chem. 2, 160–173 (2018). \n8. Hisatomi, T. & Domen, K. Reaction systems for solar hydrogen production via water splitting with particulate semiconductor photocatalysts. Nat. Catal. 2, 387–399 (2019). \n9. Cestellos-Blanco, S. et al. Photosynthetic semiconductor biohybrids for solardriven biocatalysis. Nat. Catal. 3, 245–255 (2020). \n10. Kornienko, N. et al. Interfacing nature’s catalytic machinery with synthetic materials for semi-artificial photosynthesis. Nature Nanotech 13, 890–899 (2018). \n11. Wang, Q. & Domen, K. Particulate photocatalysts for light-driven water splitting: mechanisms, challenges, and design strategies. Chem. Rev. 120, 919–985 (2020). \n12. Kong, D. et al. Recent advances in visible light-driven water oxidation and reduction in suspension systems. Mater. Today 21, 897–924 (2018). \n13. Bard, A. J. & Fox, M. A. Artificial photosynthesis: solar splitting of water to hydrogen and oxygen. Acc. Chem. Res. 28, 141–145 (1995). \n14. Fabian, D. M. et al. Particle suspension reactors and materials for solar-driven water splitting. Energy Environ. Sci. 8, 2825–2850 (2015). \n15. Wang, Q. et al. Scalable water splitting on particulate photocatalyst sheets with a solar-to-hydrogen energy conversion efficiency exceeding $1\\%$ . Nat. Mater. 15, 611–615 (2016). \n16. Qi, Y. et al. Redox-based visible-light-driven Z-scheme overall water splitting with apparent quantum efficiency exceeding $10\\%$ . Joule 2, 2393–2402 (2018). \n17. Maeda, K. et al. Photocatalyst releasing hydrogen from water. Nature 440, 295 (2006). \n18. Chen, S., Takata, T. & Domen, K. Particulate photocatalysts for overall water splitting. Nat. Rev. Mater 2, 17050 (2017). \n19. Takata, T. et al. Photocatalytic water splitting with a quantum efficiency of almost unity. Nature 581, 411–414 (2020). \n20. Kudo, A. et al. Photocatalytic $\\mathrm{O}_{2}$ evolution under visible light irradiation on ${\\mathrm{BiVO}}_{4}$ in aqueous $\\mathrm{AgNO}_{3}$ solution. Catal. Lett 53, 229–230 (1998). \n21. Kudo, A., Omori, K. & Kato, H. A first aqueous process for preparation of crystal form-controlled and highly crystalline ${\\mathrm{BiVO}}_{4}$ powder from layered vanadates at room temperature and its photocatalytic and photophysical properties. J. Am. Chem. Soc. 121, 11459–11467 (1999). \n22. Kim, T. W. & Choi, K. S. Nanoporous ${\\mathrm{BiVO}}_{4}$ photoanodes with dual-layer oxygen evolution catalysts for solar water splitting. Science 343, 990–994 (2014). \n23. Kim, J. H. & Lee, J. S. Elaborately modified ${\\mathrm{BiVO}}_{4}$ photoanodes for solar water splitting. Adv. Mater 31, 1806938 (2019). \n24. Luo, W. et al. Solar hydrogen generation from seawater with a modified ${\\mathrm{BiVO}}_{4}$ photoanode. Energy Environ. Sci. 4, 4046–4051 (2011). \n25. Abdi, F. F. et al. Efficient solar water splitting by enhanced charge separation in a bismuth vanadate-silicon tandem photoelectrode. Nat. Commun. 4, 2195 (2013). \n26. Chen, Y. S., Manser, J. S. & Kamat, P. V. All solution-processed lead halide perovskite- ${\\mathrm{BiVO}}_{4}$ tandem assembly for photolytic solar fuels production. J. Am. Chem. Soc. 137, 974–981 (2015). \n27. Resasco, J. et al. $\\mathrm{TiO}_{2}/\\mathrm{BiVO}_{4}$ nanowire heterostructure photoanodes based on Type II band alignment. ACS Cent. Sci. 2, 80–88 (2016). \n28. Wang, Q. et al. Molecularly engineered photocatalyst sheet for scalable solar formate production from carbon dioxide and water. Nat. Energy 5, 703–710 (2020). \n29. Kato, H. et al. Construction of Z-scheme type heterogeneous photocatalysis systems for water splitting into $\\mathrm{H}_{2}$ and $\\mathrm{O}_{2}$ under visible light irradiation. Chem. Lett. 33, 1348–1349 (2004). \n30. Iwase, A. et al. Reduced graphene oxide as a solid-state electron mediator in Z-scheme photocatalytic water splitting under visible light. J. Am. Chem. Soc. \n133, 11054–11057 (2011). \n31. Pan, L. et al. Boosting the performance of $\\mathrm{Cu}_{2}\\mathrm{O}$ photocathodes for unassisted solar water splitting devices. Nat. Catal. 1, 412–420 (2018). \n32. Li, R. et al. Spatial separation of photogenerated electrons and holes among $\\{010\\}$ and {110} crystal facets of ${\\mathrm{BiVO}}_{4}$ . Nat. Commun. 4, 1432 (2013). \n33. Yang, J. et al. Roles of cocatalysts in photocatalysis and photoelectrocatalysis. Acc. Chem. Res. 46, 1900–1909 (2013). \n34. Wang, Y. et al. Mimicking natural photosynthesis: solar to renewable $\\mathrm{H}_{2}$ fuel synthesis by Z-scheme water splitting systems. Chem. Rev. 118, 5201–5241 (2018). \n35. Sasaki, Y. et al. The effect of co-catalyst for Z-scheme photocatalysis systems with an $\\mathrm{Fe}^{3+}/\\mathrm{Fe}^{2+}$ electron mediator on overall water splitting under visible light irradiation. J. Catal. 259, 133–137 (2008). \n36. Maeda, K., Abe, R. & Domen, K. Role and function of ruthenium species as promoters with TaON-based photocatalysts for oxygen evolution in two-step water splitting under visible light. J. Phys. Chem. C 115, 3057–3064 (2011). \n37. Tabata, M. et al. Modified $\\mathrm{Ta}_{3}\\mathrm{N}_{5}$ powder as a photocatalyst for $\\mathrm{O}_{2}$ evolution in a two-step water splitting system with an iodate/iodide shuttle redox mediator under visible light. Langmuir 26, 9161–9165 (2010). \n38. Ma, S. S. K. et al. Visible-light-driven nonsacrificial water oxidation over tungsten trioxide powder modified with two different cocatalysts. Energy Environ. Sci. 5, 8390–8397 (2012). \n39. Zhao, Y. et al. A hydrogen farm strategy for scalable solar hydrogen production with particulate photocatalysts. Angew. Chem. Int. Ed. 59, \n9653–9658 (2020). \n40. Li, D. et al. Crystallographic-orientation-dependent charge separation of ${\\mathrm{BiVO}}_{4}$ for solar water oxidation. ACS Energy Lett. 4, 825–831 (2019). \n41. Wang, S. et al. New iron-cobalt oxide catalysts promoting ${\\mathrm{BiVO}}_{4}$ films for photoelectrochemical water splitting. Adv. Funct. Mater. 28, 1802685 (2018). \n42. Chu, C. et al. Spatially separating redox centers on 2D carbon nitride with cobalt single atom for photocatalytic $\\mathrm{H}_{2}\\mathrm{O}_{2}$ production. Proc. Natl Acad. Sci. USA 117, 6376–6382 (2020). \n43. Zhang, B. et al. High-valence metals improve oxygen evolution reaction performance by modulating 3d metal oxidation cycle energetics. Nat. Catal. 3, \n985–992 (2020). \n44. Norsköv, J. K. Chemisorption on metal-surfaces. Rep. Prog. Phys. 53, \n1253–1295 (1990). \n45. Norsköv, J. K. Electronic factors in catalysis. Prog. Surf. Sci 38, 103–144 (1991). \n46. Zhang, B. et al. Homogeneously dispersed multimetal oxygen-evolving catalysts. Science 352, 333–337 (2016). \n47. Cheng, W. et al. Lattice-strained metal-organic-framework arrays for bifunctional oxygen electrocatalysis. Nat. Energy 4, 115–122 (2019). \n48. Chen, S. et al. Efficient visible-light-driven Z-scheme overall water splitting using a $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ heterostructure photocatalyst for $\\mathrm{H}_{2}$ evolution. Angew. Chem. Int. Ed. 54, 8498–8501 (2015). \n49. Maeda, K. et al. Efficient nonsacrificial water splitting through two-step photoexcitation by visible light using a modified oxynitride as a hydrogen evolution photocatalyst. J. Am. Chem. Soc. 132, 5858–5868 (2010). \n50. Kim, C. et al. (040)-Crystal facet engineering of ${\\mathrm{BiVO}}_{4}$ plate photoanodes for solar fuel production. Adv. Energy Mater. 6, 1501754 (2016). \n\n# Acknowledgements \n\nThis work was financially supported by the National Natural Science Foundation of China (21902156, 21925206, 21633009), the National Key R&D Program of China (2020YFA0406102, 2017YFA0204904), the DICP Foundation of Innovative Research (DICP I201927), and the Dalian Science and Technology Innovation Fund (2020JJ26GX032). We gratefully acknowledge the BL14W1 beamline of the Shanghai Synchrotron Radiation Facility (SSRF), Shanghai, China, and the 1W1B beamline of the Beijing Synchrotron Radiation Facility (BSRF), Beijing, China for providing the beam time. The numerical calculations in this paper have been done on the supercomputing system in the Supercomputing Center of University of Science and Technology of China. \n\n# Author contributions \n\nF.Z. conceived and designed the experiments. Y.Q. carried out most of the preparations, activity test, catalyst characterizations, and wrote the first draft. J.Z. carried out the XAFS measurements and analysis. Y.K. conducted DFT calculation. Y.Z. assisted the synthesis of ${\\mathrm{BiVO}}_{4}$ photocatalyst. S.C. assisted the synthesis of $\\mathrm{MgTa_{2}O_{6-x}N_{y}/T a O N}$ heterostructure photocatalyst. D.L. assisted the synthesis of ${\\mathrm{BiVO}}_{4}$ photoanode. W.L. conducted the HRTEM and EELS measurements. Y.C. and T.X. conducted the SPV characterizations. F.Z. and C.L. directed the work and revised the manuscript. J.C. gave corrections about DFT calculation part. K.D. instructed synthesis of $\\mathrm{H}_{2}$ -evolving photocatalysts and provided useful suggestions and discussion on the EXAFS results. All authors discussed the results and contributed to the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-28146-6. \n\nCorrespondence and requests for materials should be addressed to Can Li or Fuxiang Zhang. \n\nPeer review information Nature Communications thanks Krishnan Rajeshwar and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1038_s41929-022-00796-1", + "DOI": "10.1038/s41929-022-00796-1", + "DOI Link": "http://dx.doi.org/10.1038/s41929-022-00796-1", + "Relative Dir Path": "mds/10.1038_s41929-022-00796-1", + "Article Title": "Atomically dispersed Pt and Fe sites and Pt-Fe nulloparticles for durable proton exchange membrane fuel cells", + "Authors": "Xiao, F; Wang, Q; Xu, GL; Qin, XP; Hwang, IH; Sun, CJ; Liu, M; Hua, W; Wu, HW; Zhu, SQ; Li, JC; Wang, JG; Zhu, YM; Wu, DJ; Wei, ZD; Gu, M; Amine, K; Shao, MH", + "Source Title": "NATURE CATALYSIS", + "Abstract": "Proton exchange membrane fuel cells convert hydrogen and oxygen into electricity without emissions. The high cost and low durability of Pt-based electrocatalysts for the oxygen reduction reaction hinder their wide application, and the development of non-precious metal electrocatalysts is limited by their low performance. Here we design a hybrid electrocatalyst that consists of atomically dispersed Pt and Fe single atoms and Pt-Fe alloy nulloparticles. Its Pt mass activity is 3.7 times higher than that of commercial Pt/C in a fuel cell. More importantly, the fuel cell with a low Pt loading in the cathode (0.015 mg(P)(t) cm(-2)) shows an excellent durability, with a 97% activity retention after 100,000 cycles and no noticeable current drop at 0.6V for over 200 hours. These results highlight the importance of the synergistic effects among active sites in hybrid electrocatalysts and provide an alternative way to design more active and durable low-Pt electrocatalysts for electrochemical devices.", + "Times Cited, WoS Core": 279, + "Times Cited, All Databases": 284, + "Publication Year": 2022, + "Research Areas": "Chemistry", + "UT (Unique WOS ID)": "WOS:000805042200002", + "Markdown": "# OPEN Atomically dispersed Pt and Fe sites and Pt– Fe nanoparticles for durable proton exchange membrane fuel cells \n\nFei Xiao1,13, Qi Wang2,13, Gui-Liang Xu   3,13, Xueping Qin1,13, Inhui Hwang4, Cheng-Jun Sun4, Min Liu5, Wei Hua6, Hsi-wen $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{\\intercal}$ , Shangqian Zhu $\\oplus1$ , Jin-Cheng Li1,7, Jian-Gan Wang $\\oplus6$ , Yuanmin Zhu2, Duojie $\\boldsymbol{\\mathsf{W}}\\boldsymbol{\\mathsf{u}}^{2}$ , Zidong Wei $\\textcircled{\\dag}8$ , Meng Gu   2 ✉, Khalil Amine   3,9,10 ✉ and Minhua Shao   1,7,11,12 ✉ \n\nProton exchange membrane fuel cells convert hydrogen and oxygen into electricity without emissions. The high cost and low durability of Pt-based electrocatalysts for the oxygen reduction reaction hinder their wide application, and the development of non-precious metal electrocatalysts is limited by their low performance. Here we design a hybrid electrocatalyst that consists of atomically dispersed Pt and Fe single atoms and Pt–Fe alloy nanoparticles. Its Pt mass activity is 3.7 times higher than that of commercial Pt/C in a fuel cell. More importantly, the fuel cell with a low Pt loading in the cathode $(0.015\\mathrm{mg}_{\\mathrm{pt}}\\mathrm{cm}^{-2})$ shows an excellent durability, with a $97\\%$ activity retention after 100,000 cycles and no noticeable current drop at 0.6 V for over 200 hours. These results highlight the importance of the synergistic effects among active sites in hybrid electrocatalysts and provide an alternative way to design more active and durable low-Pt electrocatalysts for electrochemical devices. \n\nProton exchange membrane fuel cells (PEMFCs) as a promising clean energy conversion technology have gained considerable attention. However, the high cost and low durability of Pt-based nanocatalysts for the cathodic oxygen reduction reaction (ORR) hinder the wide adoption of this technology1,2. According to the ultimate cost target of $\\mathrm{US}\\$30\\text k W^{-1}$ for the fuel cell stack3, the $\\mathrm{Pt}$ loading in the catalyst layers must be below $0.125\\mathrm{mgcm}^{-2}$ (ref. 4). However, as the $\\mathrm{Pt}$ loading decreases, the oxygen transfer resistance increases because of the limited accessible active sites, which results in a lower durability4. Thus, the ambition to develop low- $\\cdot\\mathrm{Pt}$ -loading cathodes poses great challenges in the areas of Pt utilization and the intrinsic durability of Pt-based electrocatalysts. \n\nDespite great efforts in the development of advanced $\\mathrm{\\Pt}$ -based catalysts to improve the $\\mathrm{\\Pt}$ utilization and mass activity (MA) towards ORR5,6, high activities and/or durability measured in liquid cells have rarely been realized in fuel cells. However, carbon-based $\\mathrm{Pt}$ -group-metal-free ORR electrocatalysts that consist of highly dispersed transition metal single atoms in nitrogen-coordinated carbon surfaces (Me–N–C) are promising candidates to replace Pt (ref. 7). Unfortunately, the poor durability of $\\scriptstyle\\mathrm{Me-N-C}$ has limited their practical applications8. Some early studies9,10 applied Me–N–C as a support for $\\mathrm{Pt}$ -based electrocatalyst with the aim to improve the stability of the latter. Recently, Liu and co-workers reported a hybrid catalyst with an ultralow $\\mathrm{Pt}$ loading $(2-3\\mathrm{wt\\%})$ that consisted of $\\mathrm{Pt-Co}$ alloy nanoparticles supported on $_{\\mathrm{Co-N-C}}$ with an excellent ORR activity $(1.77\\mathrm{Amg_{pt}}^{-1}$ at $0.9\\mathrm{V}_{i R\\mathrm{\\cdotfree}},$ without pressure correction)11. This result indicates that even small amounts of Pt introduction could contribute to a high activity enhancement of the hybrid electrocatalyst. Despite the excellent Pt MA of this hybrid ORR catalyst, it still suffered notable activity losses during potential cycling ( $83\\%$ after 30,000 cycles between 0.6 and $0.95\\mathrm{V}$ and potential hold ( $45\\%$ after 22 hours at $0.75\\mathrm{V}$ ) (ref. 11). Jaouen and co-workers12 found that the stability of Fe–N–C could be improved by adding a small amount of $\\mathrm{Pt}\\left(1{-}2\\mathrm{wt\\%}\\right)$ , although the activity did not change. \n\nHere we report a hybrid electrocatalyst (denoted as Pt-Fe-N-C) that consists of Pt–Fe alloy nanoparticles on highly dispersed Pt and Fe single atoms in a nitrogen-doped carbon support. The multiple types of active sites result not only in a 3.7 times higher Pt MA, but also in an excellent durability. The performance loss is negligible even after 100,000 potential cycles, and no current drop is observed at $0.6\\mathrm{V}$ in a fuel cell test with an ultralow Pt loading $(0.015\\mathrm{{mg}_{P t}\\mathbf{cm}^{-2}})$ in the cathode. \n\n# Results \n\nStructure and composition of Pt-Fe-N-C. Figure 1a shows a typical transmission electron microscopy (TEM) image of the as-synthesized $\\mathrm{Pt}$ -Fe-N-C catalyst, which clearly reveals nanoparticles with a main size distribution of $2-3{\\mathrm{nm}}$ (Supplementary Fig. 1) dispersed on a carbon substrate with a Brunauer–Emmett–Teller surface area of $750\\mathrm{m}^{2}\\mathrm{g}^{-1}$ and mesopores (Supplementary Fig. 2). High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) images of Pt-Fe-N-C at a relatively low magnification (Fig. 1b and Supplementary Fig. 3) clearly indicate a high density of isolated atoms anchored on the carbon substrate in addition to the nanoparticles. The set of peaks from intermetallic PtFe was well-assigned in the $\\mathrm{\\DeltaX}$ -ray diffraction pattern of Pt-Fe-N-C (Supplementary Fig. 4). An additional peak at $42.5^{\\circ}$ could be attributed to disordered $\\mathrm{PtFe}_{x}$ $\\left(120\\%)$ ). This resilient compressibility is further highlighted by a durable cyclic performance at $60\\%$ strain with a high strain rate of $80\\mathrm{mm}\\mathrm{min}^{-1}$ (Fig. 4d). The $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA possesses a ceramic nature and nanofiber microstructures, which are expected to achieve stable superelasticity at various extreme service temperatures. First, the hyperelasticity of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA at high temperature is confirmed by compression testing after heat treatment with an alcohol torch. As expected, the stress–strain curves after high-temperature treatment show a deformation trend similar to that found for original $\\mathrm{SiC@SiO_{2}N F A(\\sim700\\mathit{^{\\circ}C}.}$ Fig. 4e). The heat-treated aerogel also endures 1000 fatigue cycles at $60\\%$ strain with a strain rate of $80\\ \\mathrm{mm/min}$ (Fig. 4f). This high speed in the loading–unloading cycles demonstrates the superb elastic recovery ability of the $\\operatorname{SiC}\\@$ $\\mathrm{SiO}_{2}$ NFA. After 1000 cycles, the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA almost retains its original macroscopic shape completely with only a slight permanent deformation. Then, the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ was placed on an iron plate above a jar filled with liquid nitrogen to measure its superelasticity at low temperature $\\left(\\sim-40^{\\circ}\\mathbf{C}\\right)$ . The stress–strain curves obtained for the $\\operatorname{SiC}\\@$ $\\mathrm{SiO}_{2}$ NFA (Fig. 4g) at $10\\%$ , $20\\%$ , $40\\%$ , and $60\\%$ strain are similar to those at room temperature, indicating that the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA still has excellent mechanical properties after low-temperature treatment. The aerogel also exhibits good cyclic fatigue resistance (strain rate: $80\\ \\mathrm{mm/min},$ ), as displayed in Fig. 4h. Finally, the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA also shows excellent robust hyperelasticity at ultralow temperatures $(\\sim-196^{\\circ}\\mathbf{C})$ under direct immersion in liquid nitrogen. The stress–strain curves obtained at different strains (Fig. 4i) and 1000 compression cycles test (Fig. 4j) for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA show that there is not much difference compared to the test results obtained at $\\sim-40^{\\circ}\\mathrm{C}$ . \n\n![](images/4161914a2e4dd25d7a3f58258fff860994d3cdfb944182490d43f6fa147f9a41.jpg) \nFig. 4   Temperature-invariance hyperelasticity of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA. a The $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA placed inside the flame of an alcohol blowtorch $(\\sim700~^{\\circ}\\mathrm{C})$ and immersed in liquid nitrogen $(\\sim-196~^{\\circ}\\mathrm{C})$ . b Compression test for the S $\\mathrm{iC}@\\mathrm{SiO}_{2}$ NFA, which can quickly recover to its original shape. Compression stress–strain curves for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA at $\\mathbf{c}\\sim25\\ {^{\\circ}}\\mathrm{C}$ , $\\mathbf{e}\\sim700\\ {^{\\circ}}\\mathbf{C}$ $\\mathbf{g}{\\sim}-40\\mathbf{\\Omega}^{\\circ}\\mathbf{C}$ and $\\mathbf{i}{\\sim}-196\\ ^{\\circ}\\mathbf{C}$ . Cyclic compression stress–strain curves for the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA at $\\mathbf{d}\\sim25{\\ }^{\\circ}\\mathbf{C}$ , $\\mathbf{f}\\sim700\\ ^{\\circ}\\mathbf{C}$ , $\\mathbf{h}\\sim-40{\\mathrm{~}}^{\\circ}\\mathbf{C}$ and $\\mathbf{j}\\sim-196{}^{\\circ}\\mathbf{C}$ . k The maximum stress and Young’s modulus as a function of the compression test cycles. l Comparison of the specific modulus of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA with that of other aerogels with random structures \n\nThe maximum stress and Young’s modulus during cyclic compression for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ treated at various temperatures are shown in Fig. 4k and Table S2. For the first cycle, the maximum stress and Young’s modulus at $\\sim25^{\\circ}\\mathrm{C}$ are 29.33 and $41.17\\mathrm{kPa}$ , respectively. After 1000 cycles, the maximum stress and Young’s modulus are 28.12 and $37.08~\\mathrm{kPa}$ , respectively. It can be observed that both the maximum compressive strength and Young’s modulus show only a slight decrease, indicating that the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA has a nearly constant compressive strength at ${\\sim}25^{\\circ}\\mathrm{C}.$ Likewise, the values for the maximum compressive strength and the Young’s modulus also show only a small drop after 1000 cycles at ${\\sim}700,\\sim-40$ , and \\~ $\\cdot-196^{\\circ}\\mathrm{C}$ , respectively. These results are similar to those obtained for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ at $\\sim25^{\\circ}\\mathrm{C}$ . In addition, the Young’s modulus $(E)$ of the aerogel at $\\sim25~^{\\circ}\\mathrm{C}$ is approximately $41.17\\mathrm{kPa}$ . The calculated specific modulus $(\\mathrm{E}/\\uprho)$ is $\\sim3.74\\mathrm{~kN~m~kg^{-1}}$ , which is significantly higher than that of other work (Fig. 4l) [47–50]. These highlight that the present ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA has excellent mechanical properties. \n\n# 3.3  \u0007Piezoresistivity and Pressure Sensing Properties of the $\\mathbf{SiC}@\\mathbf{SiO}_{2}$ NFA for Detecting Human Motions \n\nThe SiC cores of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers are semiconducting, and their resistance value will change accordingly with compression deformation; hence, a $\\operatorname{SiC}@\\operatorname{SiO}_{2}$ NFAbased piezoresistive pressure sensor is fabricated. Figure 5a displays the change in resistance $(\\Delta R/R_{0}=(R_{0}-R)/R_{0}$ (7) [51], where $R_{0}$ and $R$ represent the incipient resistance and momentary resistance, respectively) of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA for a gradual increase in strain from 5 to $40\\%$ at a compression rate of $6\\mathrm{{mm}\\mathrm{{min}^{-1}}}$ . The $\\Delta R/R_{0}$ increases proportionally with the strain, suggesting that the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA possesses remarkable strain-dependent piezoresistive sensing behavior. As shown in Fig. 5b, $\\Delta R/R_{0}$ varies under different cyclic strains. The resistance can completely return to its initial value owing to the excellent compressive recoverability and fatigue resistance, which exhibits outstanding strain-sensing reversibility for every stage. Furthermore, the change in the relative resistance and the increase in compression strain show a clear linear relationship, yielding a gauge factor $(\\mathrm{GF}=(\\Delta R/R_{0})/\\varepsilon$ (8)) of 1.23 (inset Fig. 5b). This result demonstrates the huge potential of using the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA in sensors with excellent repeatability to detect various strains. Meanwhile, the dependence on the speed of the external compression was also examined. Figure 5c exhibits the $\\Delta R/R_{0}$ for the piezoresistive pressure sensor at varying compression rates of 6, 12, 24, 36, and $48~\\mathrm{mm}~\\mathrm{min}^{-1}$ . The various compression rates have little effect on the maximum $\\Delta\\mathrm{R}/\\mathrm{R}_{0}$ value under the same strain of $30\\%$ , which is crucial for the stability of the sensor in practical applications. It is noteworthy that the resistance variation ratio of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ sensor for $30\\%$ strain with a compression rate of $6\\mathrm{{mm}\\mathrm{{min}^{-1}}}$ shows no noticeable change after 1000 compression cycles (Fig. 5d), and the inset displays no obvious attenuation, which originates from the excellent superelasticity and microstructural reversibility of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA. In addition, the sensor can be exposed to the moisture in the air in practical applications; in particular, it will inevitably come cross human sweat in the process of detecting human motion. Therefore, it is particularly important to simulate the effect of human sweat on the sensor resistance. As shown in Fig. 5e, $\\Delta R/R_{0}$ decreases stably as an aqueous solution of $\\mathrm{\\DeltaNaCl}$ is gradually dripped onto the sensor. The possible reason for this is that the penetration of NaCl solution into the interior of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA increases its electrical conductivity, thereby reducing the resistance. Therefore, the amount of human motion can be effectively detected according to the real-time change in the resistance to ensure the health of the human body. Figure 5f shows a schematic of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA sensor used to detect human motion and the mechanism of the piezoresistive sensing performance. In practical applications, pressure sensors can be used to detect human activity and tiny pressures and then transmit this information to mobile phones. The principle of realizing this function is that $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA is compressed and bent upon loading, which leads to the nanofibers touching and interlinking with neighboring nanofibers. A large number of temporary junction contacts shorten the transport path for electrons through the aerogel, thereby reducing the electrical resistance [52]. These contacts disappear after unloading, and the resistance fully returns to its original value. It is believed that the superb structural integrity and compressive recoverability of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA dictate the piezoresistivity of the sensing behavior. \n\n![](images/6b39f7d8058a5122277c580c0aa8475021eeaf9cbf811c66cd380d78d2222c0e.jpg) \nFig. 5   Strain- and pressure-sensing behaviors of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA. a $\\Delta R/R_{0}$ for the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}{\\mathrm{NFA}}$ with the strain from 5 to $40\\%$ at a compression rate of $6~\\mathrm{{mm}~\\mathrm{{min}^{-1}}}$ . b Real-time $\\Delta R/R_{0}$ cycling test at different compression strains under a compression speed of $6\\mathrm{{mm/min}}$ ; $\\Delta R/R_{0}$ varies linearly with strain (inset b, ${\\mathrm{GF}}=1.23{\\mathrm{\\Omega}}$ ). c $\\Delta R/R_{0}$ for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA under various compression rates with a compression strain of $30\\%$ . d Stability testing of the piezoresistive behavior of $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA with a $30\\%$ compressive strain, $6~\\mathrm{{mm}~\\mathrm{{min^{-1}}}}$ compression rate, and 1000 cycles (inset shows the magnified curves). e Real-time $\\Delta\\mathrm{R}/\\mathrm{R}_{0}$ response in the presence of drops of $\\mathrm{{NaCl}}$ aqueous solution (inset depicts the corresponding schematic diagram for the $\\mathrm{\\DeltaNaCl}$ aqueous solution drop tests). f Applications of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ pressure sensor to detect body activities and tiny pressures \n\n# 3.4  \u0007Application as a Super Thermal Insulator at Extreme Temperatures \n\nThe as-prepared $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA exhibits excellent chemical and thermal stability at high temperature, which is crucial for high-temperature EMW-absorbing applications. As shown in Fig. 6a, the macroscopic shape of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA does not change when the aerogel is placed in the alcohol flame for $10~\\mathrm{{min}}$ , indicating that it has superb ablation resistance and thermal stability. The temperature-dependent thermal conductivities of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA in an argon atmosphere are presented in Fig. 6b and Table S3. Notably, the thermal conductivity of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA at room temperature is only $0.027~\\mathrm{W~m}^{-1}~\\mathrm{K}^{-1}$ , suggesting that the obtained aerogel is an excellent thermal insulator. The thermal conductivity increases with increasing temperature from 20 to $600^{\\circ}\\mathrm{C}$ , which is mainly related to thermal radiation at high temperature [53]. As shown in Fig. 6c, a flower is carbonized within 10 s when it is placed onto a heated asbestos mesh. However, the fresh flower can survive after $10~\\mathrm{{min}}$ heating when being placed on a piece of aerogel (thickness, $10~\\mathrm{mm}$ , Fig. 6d). This result further proves that the $\\operatorname{SiC}\\ @$ $\\mathrm{SiO}_{2}$ NFA has excellent thermal insulation properties. Figure 6e shows the real-time temperature measured from the side of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA on a heating platform. After $10~\\mathrm{{min}}$ , the temperatures at the top (Sp1), middle (Sp2), and bottom (Sp3) are 82.5, 186.3, and $366.2\\ ^{\\circ}\\mathrm{C}$ , respectively. The temperature at the top is much lower than that at the bottom and middle and reaches a relatively stable value of $\\sim82~^{\\circ}\\mathrm{C}$ after $7~\\mathrm{min}$ under the same heating conditions. The corresponding real-time temperatures are shown in \n\n![](images/0e0617cae5e489356a2731ba4e733de75f2490ab4095b811810fcaa7dcb3f58c.jpg) \nFig. 6   Fire and high/low-temperature resistance and thermal insulation performance of the S $\\mathrm{i}\\mathrm{C}@\\mathrm{SiO}_{2}$ NFA. a Digital photographs of the $\\operatorname{SiC}\\@$ $\\mathrm{SiO}_{2}$ NFA exposed to the flame of an alcohol lamp. b Thermal conductivities of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA at various temperatures in an argon atmosphere. c A flower placed onto the asbestos network and d a flower placed onto the S $\\mathrm{i}\\mathrm{C}@\\mathrm{SiO}_{2}$ NFA in a burner flame. Thermal images of the SiC NFAS recorded during e heating on a heated platform and g freezing on a refrigeration platform with the corresponding (f and $\\mathbf{h}$ ) temperature vs. time curves. i Schematic of the thermal insulation mechanism for the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA \n\nFig. 6f. Additionally, Fig. 6g shows the real-time temperatures measured for the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA on a refrigeration platform. The corresponding temperatures at the top (Sp1), middle (Sp2), and bottom (Sp3) are 15.9, 2.1, and $-28{}^{\\circ}\\mathrm{C}$ after $10\\mathrm{min}$ , respectively. It can be observed that the temperature at the top is much higher than that at the bottom and middle, as evident from the corresponding real-time temperature vs. time graph (Fig. 6h). This result indicates that ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA also has excellent thermal insulation properties at low temperature. The $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA can also be cut into various shapes owing to its superior flexibility. The letters ${}^{\\cdot}\\mathrm{SiC}@\\mathrm{SiO}_{2}^{,,,}$ cut from the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA are clearly visible in the thermal image against a heated platform $(\\sim306^{\\circ}\\mathrm{C})$ , as shown in Fig. 6i, suggesting that $\\operatorname{SiC}\\@$ $\\mathrm{SiO}_{2}$ NFA has great potential for blocking infrared signal transmissions. The thermal insulation mechanism mainly involves two aspects: (1) when heat flux is transferred in the 3D network structure of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA, the limited contact surface among the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ nanofibers can effectively reduce the solid-phase heat conduction; (2) the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA possesses a large number of mesoporous structures, which can shackle air molecules to decrease the gas-phase thermal convection. These results also confirm that $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ possesses outstanding thermal insulation properties, therefore, it can be used as a potential highperformance thermal insulation material in the aerospace field. \n\n# 3.5  \u0007High Absorption Capacities and Self‑cleaning Properties of the Oil‑modified SiC $:\\textcircled{a}\\mathbf{SiO}_{2}$ NFA \n\nThe pristine $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA is superhydrophilic with a water contact angle (WCA) of $\\sim0^{\\circ}$ , as displayed in Fig. S8. Hydrophilic $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA can be converted to a hydrophobic material by oil impregnation of the surface of the aerogel [54]. In Fig. 7a, a blue acidic water droplet at $\\mathrm{\\pH}=1$ displays a WCA value of $\\sim148.58^{\\circ}$ on the surface of a piece of the oil-modified $\\operatorname{SiC}@\\operatorname{SiO}_{2}$ NFA. At $\\mathrm{pH}=7$ , the orange color water droplet is recorded with a WCA value of $\\sim149.2^{\\circ}$ (Fig. 7b). Similarly, the rose-red alkaline water droplet still has a spherical morphology on the surface of the oil-modified $\\operatorname{SiC}@\\operatorname{SiO}_{2}$ NFA, which exhibits a slightly lower WCA value $(\\sim144.94^{\\circ})$ than the other two water droplets, as shown in Fig. 7c. These results demonstrate the excellent hydrophobicity of the oil-modified $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ in various solutions, which lays the foundation for investigating the self-cleaning property of the prepared aerogel. To confirm the selfcleaning performance of the obtained aerogel, silicon nanopowders were dispersed across the surface of the oilmodified $\\operatorname{SiC}@\\operatorname{SiO}_{2}$ NFA. Then, a $2.5~\\mathrm{mL}$ syringe was used to flush a piece of dusty sample surface with water droplets to confirm the self-cleaning performance of the obtained aerogel. As shown in Fig. $7\\mathrm{d-g}$ , the powderladen surface is well cleaned by the water droplet. To further expand the practicality of the oil-modified $\\operatorname{SiC}\\ @$ $\\mathrm{SiO}_{2}$ NFA aerogels in terms of hydrophobicity, their adsorption of organic solvents and oils was investigated. As demonstrated in Fig. $\\mathrm{7h-j}$ , a kerosene/Sudan I solution was quickly absorbed, which can also be consumed by combustion (Fig. 7k). \n\nCycling experiments with absorbing and burning organic solvents were carried out to further evaluate the cycling stability of the oil-modified ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA. As displayed in Fig. 7I, black colour cycles of the combustion test were performed in an air atmosphere, and no obvious adsorption capacity change is found during this process. In addition, the aerogel experienced no change throughout the burning test, which exhibits good flame retardancy and a robust structure. The practicability of the oil-modified $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA is further explored, as revealed in Fig. $7\\mathrm{m}$ . Specifically, the broad applicability of the oil-modified ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA for adsorbing organic solvents was verified by adsorbing n-hexane, gasoline, kerosene, diesel, ethanol, and soybean oil. The results show that the absorption weight of these organic solvents is equivalent to 121 to 175 times the weight of the oil-modified ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA, which depends on the surface tension and density of the adsorbed organic liquid. Additionally, these absorbed organic liquids were all subjected to 10-cycle combustion tests, as shown in Fig. 7n. The oil-modified ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA retains its original structure and appearance during these combustion cycle tests, further demonstrating the excellent three-dimensional structural stability and ablation resistance of the aerogel. These results indicate that oil-modified ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA can be used as a highly efficient selective adsorption material. In addition, the excellent hydrophobicity of oil-modified ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA is the key to its use as a high-performance EMW-absorbing material. \n\n![](images/554924d5165e35e96ad48abaaf39b4d296d5f603fbf667e7bc91fa7b6a9669e1.jpg) \nFig. 7   High absorption capacities for organic liquids and the self-cleaning property of the oil-modified $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA. a − c Digital photograph of a water droplet with $\\mathrm{\\pH}$ value $\\sim1,\\sim7$ , and $\\sim14$ on an oil-modified $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA and the corresponding WCA images, respectively. $\\mathbf{d-g}$ Self-cleaning process of the oil-modified ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA. h–k Process of absorption of methyl orange aqueous solution by the oil-modified $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA and a subsequent combustion test. l Recyclability of the oil-modified $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ in the absorption of kerosene by the combustion method. m Absorption capacities of the oil-modified $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA for various organic liquids and the corresponding $\\mathbf{n}$ recyclability of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA \n\n# 3.6  \u0007EMW Absorption Performance of the Si $\\mathbf{\\dot{C}}@\\mathbf{SiO}_{2}$ NFA \n\nReflection loss (RL) is an important factor to evaluate the EMW absorption property of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA, which can be calculated by as follows [55, 56]: \n\n$$\n\\mathrm{RL}=20\\log\\left|{\\frac{Z_{\\mathrm{in}}-Z_{o}}{Z_{\\mathrm{in}}+Z_{o}}}\\right|\n$$ \n\n$$\nZ_{i n}=Z_{o}{\\sqrt{\\frac{\\mu_{r}}{\\varepsilon_{r}}}}\\operatorname{tanh}\\left[j{\\frac{2\\pi f d{\\sqrt{\\mu_{r}\\varepsilon_{r}}}}{c}}\\right]\n$$ \n\nwhere $Z_{i n}$ is the input impedance of the aerogel, $f$ is the frequency, $c$ is the speed of light, d is the thickness of the aerogel, and $Z_{o}$ is the impedance in free space. \n\nWe know that a $R L$ value of − 10 dB means $90\\%$ absorbed of the incident EMW radiation, and the corresponding bandwidth indicates an effective absorption bandwidth (EAB) [57, 58]. As shown in Fig. 8a and Table S1, the $E A B_{\\operatorname*{max}}$ for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ is $8.6\\mathrm{GHz}$ corresponding to a frequency range of $5.82{-}14.42~\\mathrm{GHz}$ , while the ${\\mathrm{RL}}_{\\operatorname*{min}}$ value for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA is − 50.36 dB at $7.44\\:\\mathrm{GHz}$ (thickness, $1.6\\mathrm{mm},$ ). According to the quarter-wave attenuation law [59], the $R L_{\\mathrm{min}}$ value shifts to low frequencies with the increasing thickness (Fig. 8b): \n\n$$\nt_{m}=n\\lambda/4=\\frac{n c}{4f_{m}\\sqrt{\\left|\\mu_{r}\\right|\\left|\\varepsilon_{r}\\right|}}(n=1,3,5...)\n$$ \n\nOptimization of the impedance matching $(|Z_{i n}/Z_{o}|)$ results in excellent EMW absorption performance. The value $\\mathsf{I}Z_{i n}$ $/Z_{o}|$ of 1 indicates the absorber has a great impedance match and let EMW easily enter inside. Figure 8c shows that the value of $\\lvert Z_{i n}/Z_{o}\\rvert$ is close to 1 for the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA in the thickness range of $1.6{-}2~\\mathrm{mm}$ , indicating that the incident EMW can effectively enter the interior of the aerogel, which can be converted into heat to be consumed to avoid reflection into the air at the interface. In Fig. 8d, it further proves that a good impedance matching can be beneficial to the improving EMW absorption property of the materials. The other influence factor of attenuation constant $(\\alpha)$ can be calculated from Eq. (4) [60, 61]: \n\n$$\n\\alpha=\\frac{\\sqrt{2}\\pi f}{c}\\times\\sqrt{(\\mu^{\\prime\\prime}\\varepsilon^{\\prime\\prime}-\\mu^{\\prime}\\varepsilon^{\\prime})+\\sqrt{(\\mu^{\\prime}\\varepsilon^{\\prime\\prime}+\\mu^{\\prime\\prime}\\varepsilon^{\\prime})^{2}+(\\mu^{\\prime\\prime}\\varepsilon^{\\prime\\prime}-\\mu^{\\prime}\\varepsilon^{\\prime})^{2}}}\n$$ \n\nIt is generally believed that the larger $\\upalpha$ value is, the greater ability of the absorber attenuates the EMWs, as displayed in Fig. 8e. Moreover, 3D plots and 2D RL diagrams for the $\\operatorname{SiC}@\\operatorname{SiO}2$ NFA with various thicknesses at $2{\\mathrm{-}}18\\operatorname{GHz}$ are shown in Fig. $8\\mathrm{f-g}$ . The 3D and 2D diagrams for the $Z$ of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ corresponding to the thickness and frequency are further shown in Fig. 8h–i. The Z values for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA with a thickness of $1\\sim2\\mathrm{mm}$ almost always range between 0.8 and 1.2 at frequencies from 4 to 9 GHz. The results demonstrate the superb impedance matching of the aerogel can be an important factor for the excellent EMW-absorbing properties. \n\n![](images/55c8ee9866891e0cfa9e87d8805545f009d66602972a02db1337c9b56a70df3b.jpg) \nFig. 8   EMW absorption performance of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA. a Frequency- and thickness-dependent RL values, b the relationship between the simulation thickness and peak RL at typical frequencies, c the frequency- and thickness-dependent impedance matching (Z), d the relationship between $R L_{\\mathrm{min}}$ and $Z$ at a thickness of $1.6\\mathrm{mm}$ , e the attenuation constant $\\upalpha$ , f 3D and $\\mathbf{g}\\mathbf{\\Lambda}^{}2\\mathrm{D}$ representations, and h 3D and i 2D plots of $Z$ for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ \n\nOff-axis electron holographic analysis can clearly reveal the dielectric polarization, especially the potential orientation and charge density distribution at specific interface regions, which can be characterized intuitively and quantitatively [62]. Figure 9a–d shows the TEM image and corresponding charge density images under various amplified signals obtained for the longitudinal section of a ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ nanofiber. It can be clearly observed that the charges are concentrated at the ${\\mathrm{SiC}}/{\\mathrm{SiO}}_{2}$ and $\\mathrm{SiO}_{2}/$ air interfaces with the continuous amplification of the signal, resulting in a strong interface polarization. Furthermore, the two ends of each ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ nanofiber easily form induced polarized charges during the propagation of EMWs inside the aerogel owing to the large aspect ratio of the nanofibers. Therefore, each nanofiber can be regarded as a one-dimensional vibrating electric dipole and generate periodic motions to dissipate the EMW energy under alternating EM fields [63]. In addition to the dipolar polarization, the heterostructure of the $\\operatorname{SiC}\\ @$ $\\mathrm{SiO}_{2}$ nanofibers also contributes significantly to the permittivity enhancement. As shown in Fig. 9e, three fibers are cross-linked together to form a junction node (TEM image of the transverse section). The free charges can be trapped at these nodes originating from the difference in Fermi levels, which is essentially due to the various dielectric constant properties of SiC and $\\mathrm{SiO}_{2}$ [64]. Figure 9f–h displays the state of the charge density distribution at the interface between SiC and $\\mathrm{SiO}_{2}$ to form an obvious local polarization field with increasing signal intensity, which will greatly consume the incident EMWs and enhance the microwave absorption property. In addition, it can be clearly observed from Fig. 9i that SiC and $\\mathrm{SiO}_{2}$ grow closely together and make it possible for the leakage and tunneling of electrons. The charges accumulated at the interface (Fig. 9j–l) could break the potential barrier under a local strong electric field, which expands the electron transition path and further dissipates the energy of the EMW. The charge density distribution in the SiC core of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ nanofibers further confirms that the 3D cross-linked aerogels can be used as an electron transport network, thus contributing to a conductive loss. \n\n![](images/a443c001f52e810ae7aaa342b54eb38326e53edd1048ce9c458fbc33b68b05ec.jpg) \nFig. 9   Off-axis electron holography images of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ NFA. a TEM image and b–d charge density images of the longitudinal section of a $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofiber. e TEM image and $\\mathbf{f-h}$ charge density images of the transverse section of a junction node. i TEM image and j–l charge density images of the transverse section of a $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofiber \n\nActually, SiC is an excellent dielectric loss electromagnetic wave absorption material [57, 65], and $\\mathrm{SiO}_{2}$ is an electromagnetic wave transparent material [66, 67]. When the electromagnetic wave is incident on the surface of $\\operatorname{SiC}\\@$ $\\mathrm{SiO}_{2}$ nanofiber, the $\\mathrm{SiO}_{2}$ nanolayer can lock the electromagnetic wave to avoid being reflected, and the SiC core can effectively convert electromagnetic energy into heat or electricity energy. These results suggest that the synergistic effect of the SiC cores and $\\mathrm{SiO}_{2}$ nanolayer of the $\\operatorname{SiC}\\ @$ $\\mathrm{SiO}_{2}$ nanofiber enables aerogel to exhibit excellent electromagnetic wave absorption properties. Herein, we comprehensively studied the EMW-absorbing mechanisms for the $\\mathrm{SiC}@\\mathrm{SiO}_{2}\\mathrm{NFA}$ from a perspective of dielectric loss, including multiple reflection, conduction loss, defect-induced polarization, interfacial polarization, and dipolar polarization, and the results are shown in Fig. 10. \n\nThe ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA was constructed by a large number of cross-linked $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers, which have a 3D porous structure. The incident EMW was attenuated by multiple reflections among the pores, resulting in the conversion of EM energy into heat for dissipation [68]. The conduction loss was caused by the converted energy of the EMW into an electric current when it propagated in the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers. When the generated current was transported along the nanofibers, Joule heat was generated due to the resistance of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers, which consumed the EMW energy [69]. \n\nIn general, electron migration and electron hopping are two common types of conductive loss models. The 3D network structure constructed from $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers shows enhanced electrical conductivity; under an external EM field, and the electrons will flow along the radial direction of nanofibers and rapidly propagate out to the entire 3D network [70]. In other words, electron migration simply refers to the free movement of electrons in the process of propagation. Moreover, electron hopping mainly refers to the transfer of electrons among the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers [71]. However, the $\\mathrm{SiO}_{2}$ shell on the nanofiber surface is nonconductive, and the high energy barrier will greatly limit the electron hopping process. \n\n![](images/4eff61453f78cf761033172c2275e90bd265b819389eae212e49aee5aef5c5f7.jpg) \nFig. 10   Schematic of the EMW absorption mechanisms for the S $\\mathrm{i}\\mathrm{C}@\\mathrm{SiO}_{2}$ NFA \n\nIt is worth noting that defects can also lead to electron hopping, which also involves another dielectric loss mechanism—defect polarization. It can be determined that oxygen vacancies are introduced during the oxidation process to form defect sites in the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ nanofibers. The charge carriers can be trapped at these defect sites, leading to an imbalanced charge distribution. The resulted polarization and EM energy loss then occur [72]. Furthermore, 2H-SiC fragments are embedded in the 3C-SiC grains during the formation of 3C-SiC nanofibers, and the resulting 3C/2H-SiC heterostructures form stacking faults [73]. Charge separation easily occurs at the interface of stacking faults, which induces the generation of dipoles and increases the polarization loss of dipoles. \n\nThe interface polarization effect is also known as the Maxwell–Wagner-Sillars effect [74]. The enhancement of the interface polarization effect can improve the dielectric loss capacity, thereby promoting electromagnetic wave loss. The unique core–shell structure of ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ nanofibers contributes to the interface polarization. As discussed before, in situ growth of a layer of wave-transparent $\\mathrm{SiO}_{2}$ on the surface of SiC nanofibers cannot only achieve a good impedance matching but also form a heterogeneous interface at the connection between SiC and $\\mathrm{SiO}_{2}$ in the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA. The accumulated charges and collective interface polarization can lead to the conversion of EM energy into heat [75]. Therefore, the interfacial polarization and dipole relaxation induced by the $\\mathrm{SiO}_{2}$ nanolayers can improve the dielectric loss. In addition, a local strong electric field is generated due to the difference in electrical conductivity between the SiC and $\\mathrm{SiO}_{2}$ [76]. When the electric field strength is sufficient to breakdown the $\\mathrm{SiO}_{2}$ nanolayer, electrons will pass freely among the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers, thereby forming homogeneous interfaces. Predictably, the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ nanofibers are well interconnected by junction nodes (Fig. 2b), and the SiC cores at the junction also form homogeneous interfaces. \n\nIt is well known that dipole polarization involves the movement of polar or nonpolar molecules under a changing electromagnetic field. As a polar molecule, the inherent dipole rearrangement of SiC will occur under the action of an external EM field, so it is called directional polarization [77]. The SiC cores of the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers undergo dipole polarization and relaxation processes under a change in the EM field, consuming the EM energy. In addition, transverse electric fields are formed inside the $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanofibers under the action of the dipoles, and the electrons are affected by the transverse electric field during the movement process, which increases the transmission path and further consumes the EM energy. Thus, the synergistic effect of multiple reflection, conduction loss, defect-induced polarization, interfacial polarization, and dipolar polarization together enables the excellent EMW-absorbing property of the ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFA. \n\n# 4  \u0007Conclusions \n\nWe have successfully fabricated 3D porous cross-linked ${\\mathrm{SiC}}@{\\mathrm{SiO}}_{2}$ NFAs by combining a simple CVD technique with a subsequent heat treatment process. The obtained aerogel displays outstanding properties, including an ultralow density $(\\sim11\\mathrm{mg}\\ c m^{-3}),$ , thermal superinsulation $(0.027~\\mathrm{W~m}^{-1}~\\mathrm{K}^{-1},$ ), great recoverable compressibility (repeated full recovery from $60\\%$ strain), good thermal and chemical stabilities, and significant strain-dependent piezoresistive sensing behavior. Furthermore, the oil-modified $\\operatorname{SiC}@\\operatorname{SiO}_{2}$ NFA exhibits superb hydrophobicity and self-cleaning feature, which can adsorb a great quantity of organic liquids (121–175 times its own weight). The $\\operatorname{SiC}\\ @$ $\\mathrm{SiO}_{2}$ NFA also shows excellent EMW-absorption performance, with a remarkable $R L_{\\mathrm{min}}$ of − 50.36 dB at $7.44\\:\\mathrm{GHz}$ and thickness of $1.6\\mathrm{mm}$ , and a superwide $E A B$ of $8.6\\mathrm{GHz}$ over the frequency range of $5.82{-}14.42~\\mathrm{GHz}$ . Given the excellent multifunctional properties of this material, we believe it has great potentials for various practical applications in areas such as elastic components, high-efficiency oil/water adsorption materials, piezoresistive pressure sensors, and high-performance EMW absorbers in extreme environments. \n\nAcknowledgements  This work was financially supported by the National Natural Science Foundation of China (No. U2004177 and U21A2064), Outstanding Youth Fund of Henan Province (No. 212300410081), Scientific and Technological Innovation Talents in Colleges and Universities in Henan Province (22HASTIT001) \n\nand Bingbing Fan would like to say thanks to The Research and Entrepreneurship Start-up Projects for Overseas Returned Talents. \n\nFunding  Open access funding provided by Shanghai Jiao Tong University. \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\nSupplementary Information  The online version contains supplementary material available at https://​doi.​org/​10.​1007/ s40820-​022-​00905-6. \n\n# References \n\n1.\t G. Li, D. Dong, G. Hong, L. Yan, X. Zhang et al., High efficiency cryo-thermocells assembled with anisotropic holey graphene aerogel electrodes and a eutectic redox electrolyte. Adv. Mater. 31(25), 1901403 (2019). https://​doi.​org/​10.​1002/ adma.​20190​1403 \n2.\t X. Xu, Q. Zhang, M. Hao, Y. Hu, Z. Lin et al., Double-negative-index ceramic aerogels for thermal superinsulation. Science 363(6428), 723–727 (2019). https://​doi.​org/​10.​1126/ scien​ce.​aav73​04 \n3.\t M. Chhowalla, D. Jariwala, Hyperbolic 3D architectures with 2D ceramics. Science 363(3428), 694–695 (2019). https://​doi. org/​10.​1126/​scien​ce.​aaw56​70 \n4.\t Z. Yu, B. Qin, Z. Ma, J. Huang, S. Li et al., Superelastic hard carbon nanofiber aerogels. Adv. Mater. 31(23), 1900651 (2019). https://​doi.​org/​10.​1002/​adma.​20190​0651 \n5.\t A.C. Pierre, G.M. Pajonk, Chemistry of aerogels and their applications. Chem. Rev. 102(11), 4243–4266 (2002). https:// doi.​org/​10.​1021/​cr010​1306 \n6.\t L.S. Zhang, Z.C. Tang, R. Tusiime, S.F. Wang, N.N. Feng et al., Synthesis and electromagnetic wave absorbing properties of a polymer-derived SiBNC ceramic aerogel. Ceram. Int. 47(13), 18984–18990 (2021). https://​doi.​org/​10.​1016/j.​ceram int.​2021.​03.​242 \n7.\t W.Y. Zhao, G. Shao, M.J. Jiang, B. Zhao, H.L. Wang et al., Ultralight polymer-derived ceramic aerogels with wide bandwidth and effective electromagnetic absorption properties. J. Eur. Ceram. Soc. 37, 3973–3980 (2017). https://​doi.​org/​10. 1016/j.​jeurc​erams​oc.​2017.​04.​068 8.\t R. Kumar, S. Sahoo, E. Joanni, R.K. Singh, W.K. Tan et al., Recent progress on carbon-based composite materials for microwave electromagnetic interference shielding. Carbon 177, 304–331 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2021. 02.​091 \n9.\t R. Kumar, W.C. Macedo, R.K. Singh, V.S. Tiwari, C.J.L. Constantino et al., Nitrogen-sulfur Co-doped reduced graphene oxide-nickel oxide nanoparticle composites for electromagnetic interference shielding. ACS Appl. Nano Mater. 2, 4626–4636 (2019). https://​doi.​org/​10.​1021/​acsanm.​9b010​ 02 \n10.\t R. Kumar, A.V. Alaferdov, R.K. Singh, A.K. Singh, J. Shah et  al., Self-assembled nanostructures of 3D hierarchical faceted-iron oxide containing vertical carbon nanotubes on reduced graphene oxide hybrids for enhanced electromagnetic interface shielding. Compos. Part B Eng. 168, 66–76 (2019). https://​doi.​org/​10.​1016/j.​compo​sitesb.​2018.​12.​047 \n11.\t N. Leventis, A. Sadekar, N. Chandrasekaran, C. SotiriouLeventis, Click synthesis of monolithic silicon carbide aerogels from polyacrylonitrile-coated 3D silica networks. Chem. Mater. 22(9), 2790–2803 (2010). https://​doi.​org/​10. 1021/​cm903​662a \n12.\t Z. Lin, Z. Zeng, X. Gui, Z. Tang, M. Zou et  al., Carbon nanotube sponges, aerogels, and hierarchical composites: synthesis, properties, and energy applications. Adv. Energy Mater. 6(17), 1600554 (2016). https://​doi.​org/​10.​1002/​aenm. 20160​0554 \n13.\t S. Jiang, S. Agarwal, A. Greiner, Low-density open cellular sponges as functional materials. Angew. Chem. Int. Ed. 56(49), 15520–15538 (2017). https://​doi.​org/​10.​1002/​anie. 20170​0684 \n14.\t Y. Si, X. Wang, C. Yan, L. Yang, J. Yu et al., Ultralight biomass-derived carbonaceous nanofibrous aerogels with superelasticity and high pressure-sensitivity. Adv. Mater. 28(43), 9512–9518 (2016). https://​doi.​org/​10.​1002/​adma.​20160​3143 \n15.\t C. Ziegler, A. Wolf, W. Liu, A.K. Herrmann, N. Gaponik et al., Modern inorganic aerogels. Angew. Chem. Int. Ed. 56(43), 13200–13221 (2017). https://​doi.​org/​10.​1002/​anie. 20161​1552 \n16.\t J. Cai, S. Liu, J. Feng, S. Kimura, M. Wada et al., Cellulosesilica nanocomposite aerogels by in situ formation of silica in cellulose gel. Angew. Chem. Int. Ed. 51(9), 2076–2079 (2012). https://​doi.​org/​10.​1002/​anie.​20110​5730 \n17.\t L. Verdolotti, M. Lavorgna, R. Lamanna, E.D. Maio, S. Iannace, Polyurethane-silica hybrid foam by sol-gel approach: chemical and functional properties. Polymer 56, 20–28 (2015). https://​doi.​org/​10.​1016/j.​polym​er.​2014.​10.​017 \n18.\t L. Qiu, J.Z. Liu, S.L.Y. Chang, Y. Wu, D. Li, Biomimetic superelastic graphene-based cellular monoliths. Nat. Commun. 3, 1241 (2012). https://​doi.​org/​10.​1038/​ncomm​s2251 \n19.\t Y. Si, J. Yu, X. Tang, J. Ge, B. Ding, Ultralight nanofibreassembled cellular aerogels with superelasticity and multifunctionality. Nat. Commun. 5, 5802 (2014). https://​doi.​org/ 10.​1038/​ncomm​s6802 \n20.\t X.S. Fang, Y. Bando, U.K. Gautam, C.H. Ye, D. Golberg, Inorganic semiconductor nanostructures and their field-emission applications. J. Mater. Chem. 18(5), 509–522 (2008). https://​ doi.​org/​10.​1039/​b7128​74f \n21.\t P. Hu, S. Dong, X.H. Zhang, K.H. Gui, G.Q. Chen et al., Synthesis and characterization of ultralong SiC nanowires with unique optical properties, excellent thermal stability and flexible nanomechanical properties. Sci. Rep. 3011, 1–10 (2017). https://​doi.​org/​10.​1038/​s41598-​017-​03588-x \n22.\t D. Nakamura, I. Gunjishima, S. Yamaguchi, T. Ito, A. Okamoto et al., Ultrahigh-quality silicon carbide single crystals. Nature 430, 1009–1012 (2004). https://​doi.​org/​10.​1038/​natur​ e02810 \n23.\t X.Y. Chen, X.H. Liu, X.J. Geng, Q.L. Jia, Photoluminescence properties of ${\\mathrm{SiC}}/{\\mathrm{SiO}}_{2}$ heterojunctions obtained by $\\mathrm{TiO}_{2}$ -assisted chemical vapor deposition. Ceram. Int. 44(10), 11204–11210 (2018). https://​doi.​org/​10.​1016/j.​ceram​int.​2018. 03.​152 \n24.\t B. Khalid, X. Bai, H. Wei, Y. Huang, H. Wu et  al., Direct blow-spinning of nanofibers on a window screen for highly efficient PM2.5 removal. Nano Lett. 17(2), 1140–1148 (2017). https://​doi.​org/​10.​1021/​acs.​nanol​ett.​6b047​71 \n25.\t Y. Si, Z. Zhang, W. Wu, Q. Fu, K. Huang et al., Daylightdriven rechargeable antibacterial and antiviral nanofibrous membranes for bioprotective applications. Sci. Adv. 4(3), eaar5931 (2018). https://​doi.​org/​10.​1126/​sciadv.​aar59​31 \n26.\t X. Wang, J. Yu, G. Sun, B. Ding, Electrospun nanofibrous materials: a versatile medium for effective oil/water separation. Mater. Today 19(7), 403–414 (2016). https://​doi.​org/​10. 1016/j.​mattod.​2015.​11.​010 \n27.\t D. Lu, L. Su, H.J. Wang, M. Niu, L. Xu et al., Scalable fabrication of resilient SiC nanowires aerogels with exceptional hightemperature stability. ACS Appl. Mater. Interfaces 11(48), 45338–45344 (2019). https://​doi.​org/​10.​1021/​acsami.​9b168​11 \n28.\t Y.Y. Dong, X.J. Zhu, F. Pan, L. Cai, H.J. Jiang et al., Implanting $\\mathrm{NiCo}_{2}\\mathrm{O}_{4}$ equalizer with designable nanostructures in agaric aerogel-derived composites for efficient multiband electromagnetic wave absorption. Carbon 190, 68–79 (2022). https://​ doi.​org/​10.​1016/j.​carbon.​2022.​01.​008 \n29.\t W.H. Huang, Q. Qiu, X.F. Yang, S.W. Zuo, J.A. Bai et al., Ultrahigh density of atomic CoFe-electron synergy in noncontinuous carbon matrix for highly efficient magnetic wave adsorption. Nano Micro Lett. 14, 96 (2022). https://​doi.​org/​ 10.​1007/​s40820-​022-​00830-8 \n30.\t Y.P. Zhao, X.Q. Zuo, Y. Guo, H. Huang, H. Zhang et al., Structural engineering of hierarchical aerogels comprised of multi-dimensional gradient carbon nanoarchitectures for highly efficient microwave absorption. Nano Micro Lett. 13, 144 (2021). https://​doi.​org/​10.​1007/​s40820-​021-​00667-7 \n31.\t S.S. Wu, H. Fu, X.S. Hu, C.Y. Ding, X. Yan et  al., High aspect-ratio sycamore biomass microtube constructed permittivity adjustable ultralight microwave absorbent. J. Colloid Interface Sci. 622, 719–727 (2022). https://​doi.​org/​10.​1016/j. jcis.​2022.​04.​128 \n32.\t H.K. Jang, J. Kim, J.S. Park, J.B. Moon, J. Oh et al., Synthesis and characterization of a conductive polymer blend based on PEDOT:PSS and its electromagnetic applications. Polymers 14, 393 (2022). https://​doi.​org/​10.​3390/​polym​14030​393 \n33.\t C.P.R. Malere, B. Donati, N. Eras, V.A. Silva, L.F. Lona, Electromagnetic evaluation of radar absorbing materials based on conducting polypyrrole and organic-inorganic nanocomposite of polypyrrole/kaolinite. J. Appl. Polym. Sci. 139(17), e52023 (2021). https://​doi.​org/​10.​1002/​app.​52023 \n34.\t Y.B. Gong, Z.G. Yang, X.G. Wei, S.L. Song, S.Q. Ma, Synthesis and electromagnetic wave absorbing properties of highentropy metal diboride-silicon carbide composite powders. J. Mater. Sci. 57, 9218–9230 (2022). https://​doi.​org/​10.​1007/​ s10853-​022-​07238-0 \n35.\t Y.T. Fan, D. Yang, H. Mei, S.S. Xiao, Y.T. Yao et al., Tuning SiC nanowires interphase to improve the mechanical and electromagnetic wave absorption properties of SiCf/SiCnw $/\\mathrm{Si}_{3}\\mathrm{N}_{4}$ composites. J. Alloy. Compd. 896, 163017 (2022). https://​doi. org/​10.​1016/j.​jallc​om.​2021.​163017 \n36.\t R.B. Wu, K. Zhou, Z.H. Yang, X.K. Qian, J. Wei et  al., Molten-salt-mediated synthesis of SiC nanowires for microwave absorption applications. CrystEngComm 15, 570–576 (2013). https://​doi.​org/​10.​1039/​c2ce2​6510a \n37.\t Y.H. Cheng, M.Y. Tan, Hu. Pi, X.H. Zhang, B.Q. Sun et al., Strong and thermostable SiC nanowires/graphene aerogel with enhanced hydrophobicity and electromagnetic wave absorption property. Appl. Surf. Sci. 448, 138–144 (2018). https://​ doi.​org/​10.​1016/j.​apsusc.​2018.​04.​132 \n38.\t M. Han, X. Yin, W. Duan, S. Ren, L. Zhang et al., Hierarchical graphene/SiC nanowire networks in polymer-derived ceramics with enhanced electromagnetic wave absorbing capability. J. Eur. Ceram. Soc. 36(11), 2695–2703 (2016). https://​doi.​org/​ 10.​1016/j.​jeurc​erams​oc.​2016.​04.​003 \n39.\t J. Chen, Q. Shi, W. Tang, Field emission performance of SiC nanowires directly grown on graphite substrate. Mater. Chem. Phys. 126(3), 655–659 (2011). https://​doi.​org/​10.​1016/j.​match emphys.​2010.​12.​066 \n40.\t Z.M. An, C.S. Ye, R.B. Zhang, P. Zhou, Flexible and recoverable SiC nanofiber aerogels for electromagnetic wave absorption. Ceram. Int. 45, 22793–22801 (2019). https://​doi.​org/​10.​ 1016/j.​ceram​int.​2019.​07.​321 \n41.\t L. Su, H.J. Wang, M. Niu, S. Dai, Z.X. Cai et al., Anisotropic and hierarchical $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanowire aerogel with exceptional stiffness and stability for thermal superinsulation. Sci. Adv. 6(26), eaay6689 (2020). https://​doi.​org/​10.​1126/​sciadv.​aay66​ 89 \n42.\t M. Bechelany, A. Brioude, D. Cornu, G. Ferro, P. Miele, A Raman spectroscopy study of individual SiC nanowires. Adv. Funct. Mater. 17(6), 939–943 (2007). https://​doi.​org/​10.​1002/​ adfm.​20060​0816 \n43.\t C.L. Wang, Z.W. Fang, A.L. Yi, B.C. Yang, Z. Wang et al., High-Q microresonators on 4H-silicon-carbide-on-insulator platform for nonlinear photonics. Light Sci. Appl. 10, 139 (2021). https://​doi.​org/​10.​1038/​s41377-​021-​00584-9 \n44.\t G. Zu, T. Shimizu, K. Kanamori, Y. Zhu, A. Maeno et al., Transparent, superflexible doubly cross-linked polyvinylpolymethylsiloxane aerogel superinsulators via ambient pressure drying. ACS Nano 12(1), 521–532 (2018). https://​doi.​org/​10. 1021/​acsna​no.​7b071​17 \n45.\t K. Peng, J.X. Zhou, H.F. Gao, J.W. Wang, H.J. Wang et al., Emerging one-/two-dimensional heteronanostructure integrating SiC nanowires with $\\mathbf{MoS}_{2}$ nanosheets for efficient electrocatalytic hydrogen evolution. ACS Appl. Mater. Interfaces 12(17), 19519–19529 (2020). https://​doi.​org/​10.​1021/​acsami. 0c020​46 \n46.\t H.W. Liang, Q.F. Guan, L.F. Chen, Z. Zhu, W.J. Zhang et al., Macroscopic-scale template synthesis of robust carbonaceous nanofiber hydrogels and aerogels and their applications. Angew. Chem. Int. Ed. 51(21), 5101–5105 (2012). https:// doi.​org/​10.​1002/​anie.​20120​0710 \n47.\t H.L. Wang, X. Zhang, N. Wang, Y. Li, X. Feng et al., Ultralight, scalable, and high-temperature–resilient ceramic nanofiber sponges. Sci. Adv. 3(6), e1603170 (2017). https://​ doi.​org/​10.​1126/​sciadv.​16031​70 \n48.\t L. Su, M.Z. Li, H.J. Wang, M. Niu, D. Lu et  al., Resilient $\\mathrm{Si}_{3}\\mathrm{N}_{4}$ nanobelt aerogel as fire-resistant and electromagnetic wave-transparent thermal insulator. ACS Appl. Mater. Interfaces 11(17), 15795–15803 (2019). https://​doi.​org/​10.​1021/​ acsami.​9b028​69 \n49.\t B. Ren, J.J. Liu, Y.D. Rong, L. Wang, Y.J. Lu et al., Nanofibrous aerogel bulk assembled by cross-linked $\\mathrm{{SiC/SiO_{x}}}$ core− shell nanofibers with multifunctionality and temperatureinvariant hyperelasticity. ACS Nano 13(10), 11603–11612 (2019). https://​doi.​org/​10.​1021/​acsna​no.​9b054​06 \n50.\t S. Chabi, V.G. Rocha, E. Garcia-Tunon, C. Ferraro, E. Saiz et al., Ultralight, strong, three-dimensional SiC structures. ACS Nano 10(2), 1871–1876 (2016). https://​doi.​org/​10.​1021/ acsna​no.​5b055​33 \n51.\t L. Wang, M.Y. Zhang, B. Yang, J.J. Tan, X.Y. Ding, Highly compressible, thermally stable, light-weight, and robust aramid nanofibers $/\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MXene composite aerogel for sensitive pressure sensor. ACS Nano 14(8), 10633–10647 (2020). https://​doi.​org/​10.​1021/​acsna​no.​0c048​88 \n52.\t Y. Chen, O. Ola, H.M. Chen, N.N. Wang, Y.D. Xia et al., SiC nanowire sponges as electropressure sensors. ACS Appl. Nano Mater. 2(12), 7540–7548 (2019). https://​doi.​org/​10.​1021/​ acsanm.​9b015​90 \n53.\t C.Y. Liang, Z.F. Wang, L. Wu, X.C. Zhang, H. Wang et al., Light and strong hierarchical porous SiC foam for efficient electromagnetic interference shielding and thermal insulation at elevated temperatures. ACS Appl. Mater. Interfaces 9(35), 29950–29957 (2017). https://​doi.​org/​10.​1021/​acsami.​7b077​35 \n54.\t L. Su, H.J. Wang, M. Niu, X.Y. Fan, M.B. Ma et al., Ultralight, recoverable, and high-temperature-resistant SiC nanowire aerogel. ACS Nano 12(4), 3103–3111 (2018). https://​doi.​org/​ 10.​1021/​acsna​no.​7b085​77 \n55.\t Y. Wang, X. Gao, Y. Fu, X. Wu, Q. Wang et al., Enhanced microwave absorption performances of polyaniline/graphene aerogel by covalent bonding. Compos. Part B Eng. 169, 221– 228 (2019). https://​doi.​org/​10.​1016/j.​compo​sitesb.​2019.​04.​ 008 \n56.\t H. Du, Q.P. Zhang, B. Zhao, F. Marken, Q.C. Gao et al., Novel hierarchical structure of $\\mathbf{MoS}_{2}/\\mathrm{TiO}_{2}/\\mathrm{Ti}_{3}\\mathbf{C}_{2}\\mathbf{T}x$ composites for dramatically enhanced electromagnetic absorbing properties. J. Adv. Cream. 10, 1042–1051 (2021). https://​doi.​org/​10.​1007/​ s40145-​021-​0487-9 \n57.\t B. Huang, Z.Q. Wang, H.L. Hu, X.Z. Tang, X.Z. Huang et al., Enhancement of the microwave absorption properties of PyC-SiCf/SiC composites by electrophoretic deposition of SiC nanowires on SiC fibers. Ceram. Int. 46(7), 9303–9310 (2020). https://​doi.​org/​10.​1016/j.​ceram​int.​2019.​12.​185 \n58.\t K.L. Zhang, J.Y. Zhang, Z.L. Hou, S. Bi, Q.L. Zhao, Multifunctional broadband microwave absorption of flexible graphene composites. Carbon 141, 608–617 (2019). https://​ doi.​org/​10.​1016/j.​carbon.​2018.​10.​024 \n59.\t H.R. Cheng, Y.M. Pan, X. Wang, C.T. Liu, C.Y. Shen et al., Ni flower/MXene-melamine foam derived 3D magnetic/conductive networks for ultra-efficient microwave absorption and infrared stealth. Nano Micro Lett. 14, 63 (2022). https:// doi.​org/​10.​1007/​s40820-​022-​00820-w \n60.\t D. Ding, Y. Wang, X.D. Li, R. Qiang, P. Xu et al., Rational design of core-shell $\\operatorname{Co}\\ @\\operatorname{C}$ microspheres for high-performance microwave absorption. Carbon 111, 722–732 (2017). https://​doi.​org/​10.​1016/j.​carbon.​2016.​10.​059 \n61.\t W. Xue, G. Yang, S. Bi, J.Y. Zhang, Z.L. Hou, Construction of caterpillar-like hierarchically structured Co/MnO/CNTs derived from $\\mathrm{MnO}_{2}/\\mathrm{ZIF}{-}8@\\mathrm{ZIF}{-}67$ for electromagnetic wave absorption. Carbon 173, 521–527 (2021). https://​doi.​ org/​10.​1016/j.​carbon.​2020.​11.​016 \n62.\t W. You, R. Che, Excellent NiO-Ni nanoplate microwave absorber via pinning effect of antiferromagnetic-ferromagnetic interface. ACS Appl. Mater. Interfaces 10(17), 15104– 15111 (2018). https://​doi.​org/​10.​1021/​acsami.​8b036​10 \n63.\t X. Shi, J. Yuan, W. Zhou, J. Rong, M. Cao, Preparation and dielectric properties of nanostructured ZnO whiskers. Chin. Phys. Lett. 24, 2994–2997 (2007). https://​doi.​org/​10.​1088/​ 0256-​307X/​24/​10/​078 \n64.\t X. Li, L. Wang, W.B. You, L.S. Xing, L.T. Yang et  al., Enhanced polarization from flexible hierarchical $\\mathbf{M}\\mathbf{n}\\mathbf{O}_{2}$ arrays on cotton cloth with excellent microwave absorption. Nanoscale 11(28), 13269–13281 (2019). https://​doi.​org/​10.​ 1039/​c9nr0​2667c \n65.\t C.S. Wang, S.Q. Wu, Z.Q. Li, S. Chen, A.N. Chen et al., 3D printed porous biomass-derived SiCnw/SiC composite for structure-function integrated electromagnetic aoborption. Virtual Phys. Prototy. 17, 718–733 (2022). https://​doi.​org/​ 10.​1080/​17452​759.​2022.​20569​50 \n66.\t X.Y. Yuan, L.F. Cheng, L.T. Zhang, Electromagnetic wave absorbing properties of ${\\mathrm{SiC}}/{\\mathrm{SiO}}_{2}$ composites with ordered inter-filled structure. J. Alloy. Compd. 680, 604–611 (2016). https://​doi.​org/​10.​1016/j.​jallc​om.​2016.​03.​309 \n67.\t Z.J. Li, X.H. Wang, H.L. Ling, H. Lin, T. Wang et al., Electromagnetic wave absorption properties of $\\mathrm{SiC}@\\mathrm{SiO}_{2}$ nanoparticles fabricated by a catalyst-free precursor pyrolysis method. J. Alloy. Compd. 830, 154643 (2020). https://​doi.​ org/​10.​1016/j.​jallc​om.​2020.​154643 \n68.\t C.H. Wang, Y.J. Ding, Y. Yuan, X.D. He, S.T. Wu et al., Graphene aerogel composites derived from recycled cigarette filters for electromagnetic wave absorption. J. Mater. Chem. C 3(45), 11893–11901 (2015). https://​doi.​org/​10. 1039/​c5tc0​3127c \n69.\t C. Liang, H. Qiu, Y. Han, H. Gu, P. Song et al., Superior electromagnetic interference shielding 3D graphene nanoplatelets/reduced graphene oxide foam/epoxy nanocomposites with high thermal conductivity. J. Mater. Chem. C 7(9), 2725–2733 (2019). https://​doi.​org/​10.​1039/​c8tc0​5955a \n70.\t B. Wen, M. Cao, Z. Hou, W. Song, L. Zhang et al., Temperature dependent microwave attenuation behavior for carbonnanotube/silica composites. Carbon 65, 124–139 (2013). https://​doi.​org/​10.​1016/j.​carbon.​2013.​07.​110 \n71.\t L.Y. Zhu, X.J. Zeng, M. Chen, R.H. Yu, Controllable permittivity in 3D $\\mathrm{Fe_{3}O_{4}/C N T s}$ network for remarkable microwave absorption performances. RSC Adv. 7, 26801–26808 (2017). https://​doi.​org/​10.​1039/​c7ra0​4456a \n72.\t P.B. Liu, S. Gao, G.Z. Zhang, Y. Huang, W.B. You et  al., Hollow engineering to $\\operatorname{Co}\\ @\\operatorname{N}.$ -doped carbon nanocages via synergistic protecting-etching strategy for ultrahigh microwave absorption. Adv. Funct. Mater. 31(27), 2102812 (2021). https://​doi.​org/​10.​1002/​adfm.​20210​2812 \n73.\t H. Zhang, Y. Xu, J. Zhou, J. Jiao, Y. Chen et  al., Stacking fault and unoccupied densities of state dependence of electromagnetic wave absorption in SiC nanowires. J. Mater. Chem. C 3(17), 4416–4423 (2015). https://​doi.​org/​10.​1039/ c5tc0​0405e \n74.\t M. Qin, L.M. Zhang, H.J. Wu, Dual-template hydrothermal synthesis of multi-channel porous $\\mathrm{NiCo}_{2}\\mathrm{O}_{4}$ hollow spheres as high-performance electromagnetic wave absorber. Appl. Surf. Sci. 515, 146132 (2020). https://​doi.​org/​10.​1016/j.​apsusc. 2020.​146132 \n75.\t T. Xia, C. Zhang, N.A. Oyler, X. Chen, Hydrogenated $\\mathrm{TiO}_{2}$ nanocrystals: a novel microwave absorbing material. Adv. Mater. 25(47), 6905–6910 (2013). https://​doi.​org/​10.​1002/ adma.​20130​3088 \n76.\t M. Kuriakose, S. Longuemart, M. Depriester, S. Delenclos, A.H. Sahraoui, Maxwell-Wagner-Sillars effects on the thermal-transport properties of polymer-dispersed liquid crystals. Phys. Rev. E 89, 022511 (2014). https://​doi.​org/​10.​1103/ PhysR​evE.​89.​022511 \n77.\t M. Li, X. Yin, G. Zheng, M. Chen, M. Tao et al., High-temperature dielectric and microwave absorption properties of $\\mathrm{Si}_{3}\\mathrm{N}_{4}\\mathrm{-}\\mathrm{SiC/SiO}_{2}$ composite ceramics. J. Mater. Sci. 50, 1478– 1487 (2014). https://​doi.​org/​10.​1007/​s10853-​014-​8709-y " + }, + { + "id": "10.1038_s41467-022-29093-y", + "DOI": "10.1038/s41467-022-29093-y", + "DOI Link": "http://dx.doi.org/10.1038/s41467-022-29093-y", + "Relative Dir Path": "mds/10.1038_s41467-022-29093-y", + "Article Title": "Highly stable flexible pressure sensors with a quasi-homogeneous composition and interlinked interfaces", + "Authors": "Zhang, Y; Yang, JL; Hou, XY; Li, G; Wang, L; Bai, NN; Cai, MK; Zhao, LY; Wang, Y; Zhang, JM; Chen, K; Wu, X; Yang, CH; Dai, Y; Zhang, ZY; Guo, CF", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "E-skins often have poor interfaces that lead to unstable performances. Here, authors report e-skins with a quasi-homogeneous composition and bonded micro-structured interfaces, through which both the sensitivity and stability of the devices are improved. Electronic skins (e-skins) are devices that can respond to mechanical stimuli and enable robots to perceive their surroundings. A great challenge for existing e-skins is that they may easily fail under extreme mechanical conditions due to their multilayered architecture with mechanical mismatch and weak adhesion between the interlayers. Here we report a flexible pressure sensor with tough interfaces enabled by two strategies: quasi-homogeneous composition that ensures mechanical match of interlayers, and interlinked microconed interface that results in a high interfacial toughness of 390 J center dot m(-2). The tough interface endows the sensor with exceptional signal stability determined by performing 100,000 cycles of rubbing, and fixing the sensor on a car tread and driving 2.6 km on an asphalt road. The topological interlinks can be further extended to soft robot-sensor integration, enabling a seamless interface between the sensor and robot for highly stable sensing performance during manipulation tasks under complicated mechanical conditions.", + "Times Cited, WoS Core": 274, + "Times Cited, All Databases": 282, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000767467900015", + "Markdown": "# Highly stable flexible pressure sensors with a quasi-homogeneous composition and interlinked interfaces \n\nYuan Zhang1,6, Junlong Yang 2,6, Xingyu Hou1, Gang Li1, Liu Wang1, Ningning Bai1, Minkun Cai1, Lingyu Zhao1, Yan Wang1, Jianming Zhang1, Ke Chen3, Xiang Wu4, Canhui Yang $\\textcircled{1}$ 5, Yuan Dai3, Zhengyou Zhang 3 & Chuan Fei Guo 1,5✉ \n\nElectronic skins (e-skins) are devices that can respond to mechanical stimuli and enable robots to perceive their surroundings. A great challenge for existing e-skins is that they may easily fail under extreme mechanical conditions due to their multilayered architecture with mechanical mismatch and weak adhesion between the interlayers. Here we report a flexible pressure sensor with tough interfaces enabled by two strategies: quasi-homogeneous composition that ensures mechanical match of interlayers, and interlinked microconed interface that results in a high interfacial toughness of $390\\mathrm{J}{\\cdot}\\mathsf{m}^{-2}$ . The tough interface endows the sensor with exceptional signal stability determined by performing 100,000 cycles of rubbing, and fixing the sensor on a car tread and driving $2.6\\ k\\mathsf{m}$ on an asphalt road. The topological interlinks can be further extended to soft robot-sensor integration, enabling a seamless interface between the sensor and robot for highly stable sensing performance during manipulation tasks under complicated mechanical conditions. \n\nRtofliboonts wprhoesnt etqiucis,ppaend owtith1he– elmeactcrhoiniecs gsakin (nes-sokriynfs)u ocrmechanoreceptors in human skin. Performances of such devices have been significantly improved by introducing new designs such as interfacial microstructures, or doping conductive fillers into the dielectric layer7–15. For example, the introduction of microstructures in flexible pressure sensors can improve both the sensitivity by enhancing the compressibility of the dielectric and the response speed of the device by rapidly restoring and releasing energy13–17; and adding conductive fillers in dielectric can produce a higher and pressure-dependent dielectric constant and thereby improve signal magnitude13. A long-standing challenge for e-skins is their poor stability under harsh and complicated mechanical conditions because of the poor interfaces in the devices. Both the human skin and most e-skins possess multilayer structures; however, they exhibit significantly different levels of mechanical stability. The human skin consists of epidermis, dermis, and subcutaneous fat layers that grow together to have tough interfaces (Supplementary Fig. 1a)18,19. Such firm interlocking between the layers allows the skin to survive during manipulation tasks that involve complex mechanical modes such as stretching, torsion, shear, and compression (Supplementary Fig. 1b). By contrast, existing layered e-skins often consist of stacked functional layers (e.g., two electrodes sandwiching a soft dielectric layer) with non-bonded interfaces16,20,21. The mechanical stability of such an interface is further undermined when microstructures and air gaps are introduced to improve the sensitivity of the device22–25. Another important concern for the weak interfaces in e-skins is the mechanical mismatch between different layers. For example, Young’s moduli of different layers can vary up to five orders of magnitude16,21,22,26–28. As a result, delamination or separation of layers readily ensues under complex mechanical deformations, impairing to a large extent the performance of the e-skins and thus the sensory functions of the machine employing the e-skins. Although the integration of interlayers with homogenous composition or fully elastic components that exhibit close rigidity has been used to achieve minimized mechanical mismatch and improved stretchability29–31, microstructures and robust interface are not introduced, and thus desired sensing performance and interfacial stability cannot be achieved. Furthermore, integrating e-skins into soft robots or other machines inevitably introduces additional interfaces32,33. Such integration likewise suffers from poor interfacial adhesion and mechanical mismatch. It thus remains an urgent necessity to form robust interfaces between different layers for e-skins and for sensor-robot integration. \n\nHere we address the challenges by using a quasi-homogeneous composition for all interlayers and introducing interlinked and microstructured interfaces in a multilayered sensor. The quasihomogeneous composition made by polydimethylsiloxane-carbon nanotubes (PDMS-CNTs) can avoid the mechanical mismatch between the layers, and the strong topological interlinks between different functional layers can lead to tough and strong interfaces. The sensors consist of a microconed electrode $7\\mathrm{wt\\%}$ CNTs), a dielectric layer ( $2\\mathrm{wt\\%}$ CNTs), and a flat electrode layer $(7\\mathrm{wt\\%}$ CNTs). The microstructured interface with topological interlinks has a high interfacial toughness of $390\\mathrm{J}{\\cdot}\\mathrm{m}^{-2}$ enabled by two mechanisms: elastic dissipation and discrete rupture of the microstructures. The microcones can be significantly stretched to dissipate energy upon peeling, and the discrete rupture mode stabilizes the interface to prevent catastrophic crack propagation. The CNT doping in the dielectric layer together with the microstructures also boosts the signal intensity of the sensor by a factor of 33. The enhancement of the signal magnitude lies in a composition-structure synergistic effect: the conductive filler enlarges the dielectric constant of the composite upon loading, and the microstructure deformation changes the dielectricelectrode contact area. The tough and strong interface ensures high fidelity of the sensing signal under harsh mechanical conditions: the sensors exhibit adequate signal stability when subjected to repeated rubbing and shear test for at least 10,000 cycles, or when fixated to the tire tread of a running car driven $2.6\\mathrm{km}$ on an asphalt road. \n\nThe interlinks can also be applied to the soft robot-sensor interface, and we demonstrate the seamless integration of a soft robot and sensors, both made of PDMS-CNTs composites, for pressure and strain sensing during demanding gripping tasks without any interfacial failure or fatigue. The sensor can identify various stages during the gripping process via the decoupled bimodal signals of capacitance for pressure information. We expect this strategy to be extended to other material systems and other types of sensors for attaining robust interfaces and highly stable signals. \n\n# Results \n\nDesign of the integrated all PDMS-CNTs pressure sensor. In conventional multilayered e-skins, the functional layers are stacked on top of each other without introducing interlayer bonding (Fig. 1a)16,21–25, and thus the layers in such devices will easily separate or delaminate when exposed to in-plane compressive stresses or shear stresses (Fig. 1b). In addition, the layers are often made of different materials, which induce remarkable mechanical mismatch22,26,27,34. For example, in a capacitive type sensor, the electrodes are mostly metal or indium tin oxide (Young’s modulus $E\\sim100$ GPa) deposited on plastic substrates $(E\\sim\\mathrm{1\\bar{GPa})}$ , while the dielectric layer is made of a soft material such as PDMS $(E\\sim1\\mathrm{MPa})^{22,34}$ . The significant mechanical mismatch between the electrode and the dielectric may cause interfacial failure under large deformations35,36. \n\nThe devices studied in this work are made of an all-PDMSCNTs material system to avoid mechanical mismatch, and their functional layers are interlinked (generating a new network that penetrates with the adherend networks) to form tough and strong interfaces (Fig. 1c, d). From top to bottom, the device consists of a flat electrode $7\\mathrm{wt\\%}$ CNTs, $50\\upmu\\mathrm{m}$ thick), a flat dielectric layer $(2\\mathrm{wt\\%}$ CNTs, $120\\upmu\\mathrm{m}$ thick), and an electrode that features dense surface microcones $7\\mathrm{wt\\%}$ CNTs, ${\\sim}100\\upmu\\mathrm{m}$ thick) with an average cone height of ${\\sim}30\\upmu\\mathrm{m}$ and an inter-cone distance of $34\\upmu\\mathrm{m}^{37}$ . Our selection of the material system of the sensor is based on the characteristics of the composite: the electrodes (with $7\\mathrm{wt\\%}$ CNTs) are electrically conductive, while the dielectric (with $2\\mathrm{wt\\%}$ CNTs) has a significant change in dielectric constant upon loading (Supplementary Fig. 2), which will be discussed in details hereinafter. The interlinks between the layers are formed using a procedure developed here. First, the electrodes and the dielectric layer are swollen in a trichloromethane solvent with a PDMS base $(5.5\\mathrm{wt\\%})$ and a curing agent $(0.55\\mathrm{wt\\%})$ solute (Fig. 1e). Next, the swollen components are stacked in the order described above, exposed to a pressure of $20\\mathrm{kPa}$ , and cured (Fig. 1f). A new PDMS network is formed, in topological entanglement with preformed PDMS networks, to interlink the layers together (Fig. 1g). With interlinking, all layers are seamlessly integrated at the interfaces, as shown in the scanning electron microscopy (SEM) images in Fig. 1h. Specifically, at the interface between the dielectric layer and the bottom microstructured electrode, the cone tips are found to merge into the dielectric layer (low panel, Fig. 1h). \n\nThe interlinking method is specially suitable to bond microstrucrued interface. In the process, monomers and crosslinkers are infiltrated into the preformed polymer networks of the microstructured electrode and the flat dielectric. The microstructures maintain during the swelling process, and a third polymer network forms to interlink the microstructured and the flat surfaces together upon curing. In addition, no adhesives are introduced in the interlinking process, and homogenous composition can thus be achieved. \n\n![](images/a8d125ed6ac38ba8352147d31e14b4faceeec4c73cbcf138a6f48bb0c3183a0b.jpg) \nFig. 1 Design of the all PDMS-CNTs-based flexible pressure sensor. a Conventional sensors or e-skins have non-bonded interfaces and exhibit significant mechanical mismatch between layers. b Delamination readily occurs in conventional sensors upon loading. c The all-PDMS-CNTs-based sensor has bonded interfaces and exhibits mechanical match between layers. d Interfaces in the all-PDMS-CNTs sensor remains stable under loading. e Infiltration by monomers and crosslinkers of PDMS, dissolved in an organic solvent, into the polymer networks of the electrodes and the dielectric layer. f The swollen electrodes and dielectric layer are integrated together before curing the infiltrated monomers and crosslinkers. g After curing, an interlink PDMS network forms at each interface between an electrode and the dielectric layer, in topological entanglement with the two adherend PDMS networks, resulting in robust electrode-dielectric layer interfaces. h Cross-section SEM images of the sensor, showing seamlessly interlinked interfaces between different layers. \n\nInterfacial toughness and strength. Our design with a quasihomogeneous composition of the whole sensor and interlinked interfaces enables mechanical match between the functional layers as well as strong and tough interfaces. In our devices, all the layers exhibit similar mechanical properties because the whole system is based on a PDMS matrix doped with small amounts of CNTs. Figure 2a shows that the Young’s moduli of pure PDMS, PDMS-CNTs composites doped with $2\\mathrm{wt\\%}$ and $7\\mathrm{wt\\%}$ CNTs are 1.2, 1.4, and $3.4\\mathrm{MPa}$ , respectively. Although the CNTs doping leads to increased Young’s modulus of the composite, the small difference can hardly cause mechanical mismatch. Such a mechanical match cannot be achieved in other sensor designs that include a soft dielectric layer and metal- or plastic-based electrodes. \n\nWe also measured the toughness and shear strength of all interfaces in the device. The flat interface between the top electrode (which is flat) and the dielectric layer has an interfacial toughness of $420\\mathrm{J}{\\cdot}\\mathrm{m}^{-2}$ and a shear strength of $90\\mathrm{\\kPa}$ , while the microstructured interface, although containing abundant voids and pores, exhibits an interfacial toughness of $390\\mathrm{J}{\\cdot}\\mathrm{m}^{-2}$ and a shear strength of $88~\\mathrm{\\kPa}$ , as shown in Fig. 2b, c and Supplementary Fig. 3. Although the interlinked microconed interface has a slightly lower interfacial toughness than the interlinked flat interface that makes the sensor fail at the cones, the microstructured interface will contribute to improved sensing properties while being much tougher than the non-interlinked one. The device’s topological interlinks are crucial to the high interfacial toughness and shear strength. For example, when applying a thin (few microns) liquid layer of a PDMS base and a curing agent (10:1 in weight ratio) as an adhesive between the non-swollen microconed electrode and dielectric layer, because the PDMS precursor is viscous and barely infiltrates into the preformed PDMS networks, the cured interface exhibits a much lower interfacial toughness of ${\\sim}96\\ \\mathrm{J}{\\cdot}\\mathrm{m}^{-2}$ , only $1/4$ that of the interlinked interface. Likewise, the shear strength of the noninterlinked interface is only $39\\mathrm{kPa}$ , also much lower than that of the interface with topological interlinks. \n\n![](images/38a25b1a895be8601434574c27a793f910a53ad3dcc063e5ff498a0f4ebd3c13.jpg) \nFig. 2 Mechanical properties of the microstructured interface and mechanisms for the tough interface. a Young’s moduli of pure PDMS, PDMS-CNTs $2w t\\%$ CNTs) dielectric layer, and PDMS-CNTs $(7\\mathrm{wt\\%}$ CNTs) electrode. Comparisons of b, interfacial toughness and c, shear strength between a microstructured non-bonded interface, a microstructured bonded interface without interlinks, a flat bonded interface with crosslinks, and a microstructured bonded interface with interlinks. d SEM image of the microstructured interface under peeling, showing cohesive ruptures of the microcones marked by dashed ellipses. A schematic illustration of the peeling test is shown at left. e Sequential optical images of the microconed interface during in-situ stretching, showing a rupture strain of ${>}200\\%$ that enables significant energy dissipation. f Schematic illustrations of brittle rupture of bulk PDMS and discrete rupture of a microstructured interface. $\\pmb{\\mathrm{\\pmb{g}}}\\mathsf{S E M}$ images of the sensor under (from left) twisting, bending, and stretching, showing stable bonding between the microcones and the dielectric layer. \n\nElastic dissipation mode and discrete rupture mode. Such a high interfacial toughness is attributed to its significant elastic dissipation and the discrete rupture mode of the cones. First, the strong adhesion of the cone-dielectric interface and the large stretchability of the cones enable high elastic dissipation. On one hand, the cones can be significantly elongated to a large strain $(\\sim200\\%$ , Fig. 2d, e) to dissipate energy. We ascribe such a large stretchability to the fact that small-scale structures have far fewer flaws than bulk materials38,39. On the other hand, the strong adhesion enabled by the topological interlinks allows the cones to survive under large strains until cohesive ruptures of the cones occurs, as shown by SEM observation of a microstructured interface upon peeling (Fig. 2d and Supplementary Fig. 4). \n\nWe conducted a calculation of the interfacial toughness based on the elastic dissipation of individual cones and the result matches well with the experimental value. The interfacial toughness is the energy needed to advance the crack by unit area during peeling, or the energy required to break the cones per unit area. Therefore, interfacial toughness can be expressed as \n\n$$\n\\begin{array}{r}{{\\cal{I}}=E_{c o n e}\\times N}\\end{array}\n$$ \n\nwhere $E_{c o n e}$ is the energy required to break an individual cone, and $N$ is the areal density of bonded cones. We estimated that about $6.8\\times10^{-7}$ J energy $(E_{c o n e})$ is dissipated when an individual cone is elongated until it fractures, by taking into account the stress-strain curve of the CNT-doped PDMS and the size of the cones. Considering that the areal density $N$ is about $7.9\\times10^{8}\\mathrm{m}^{-2}$ (Supplementary Fig. 5) and about $20\\%$ cones are not bonded due to their small height (which decreases the interfacial toughness), the interfacial toughness based on our elastic dissipater mode is calculated to be $420{\\mathrm{J}}{\\cdot}{\\mathrm{m}}^{-2}$ , which is satisfactorily close to the experimental value of 390 J·m−2. \n\nSecond, the microcones undergo discrete rupture that can locally stabilize the interface to avoid continuous, catastrophic, brittle failure. Although bulk PDMS is soft and stretchable, it becomes brittle and fractures catastrophically once a crack forms and propagates (Fig. 2f). By contrast, at the microstructured interface, the cones are elongated collectively and fracture one-byone. When the cones at crack tip fracture, they dissipate the stored strain energy and relax the local strain on their neighbors while the rest of the cones ahead of the crack tip deform more and maintain the overall integrity. We call this failure mode “discrete rupture” (Fig. 2f), and it is similar to the delocalized rupture of a two-dimensional nanomesh electrode on an elastomeric substrate40 and splitting the contact mechanism in the detachment of gecko’s foot-hair41,42. Because of its elastic dissipation and discrete rupture mode features, the microstructured interface exhibits a high interfacial toughness close to $400\\mathrm{J}{\\cdot}\\mathrm{m}^{-2}$ , which is comparable to the fracture toughness of pure PDMS (Supplementary Fig. 6). Note that the rupture of the interface is contributed by the failure of individual microcones, which are three-dimentional structures. The toughening mechanism introduced by a three-dimensional interface offers an opportunity to significantly improve the stability of the interfaces in sensors and other devices. \n\nThe toughness and stability of the microstructure interface were further confirmed by in situ inspection in various mechanical modes, including bending, stretching, and twisting (Fig. 2g). No delamination of layers or interfacial failure is observed for our interlinked sample under any of these conditions. If the interfaces are not bonded, however, delamination will occur during bending (Supplementary Fig. 7). Twisting will generate particularly large shear strain at the interfaces, and our SEM analysis shows that the cones remain firmly bonded to the dielectric layer under a large shear strain of ${\\sim}0.8$ or $45^{\\circ}$ (Fig. $2\\mathrm{g}$ and Supplementary Fig. 8), corresponding to a local shear stress of ${\\sim}400\\mathrm{kPa}$ at the cone tip. The structural stability under large shear strain is important for practical applications since interfacial failures are mostly caused by shear. \n\nSensing properties of the sensor. The capacitance response of the sensor $\\mathrm{10\\mm\\times10\\mm}$ in area) under pressure is shown in Fig. 3a. As a key parameter for pressure sensing, the sensitivity of a capacitive-type sensor is defined as $S=(\\Delta C/\\bar{C}_{0})/\\Delta P;$ where $C_{0}$ is the initial capacitance before loading and $\\Delta C$ is the change in capacitance with the change in pressure, $\\Delta P^{43,44}$ . From Fig. 3a, the sensitivity is $0.15\\mathrm{kPa}^{-1}$ when the pressure is below $4\\bar{7}\\mathrm{kPa}$ and it drops to $0.08\\mathrm{kPa}^{-1}$ in the range between 47 and $214\\mathrm{kPa}$ and then to $0.04\\mathrm{kPa}^{-1}$ above $214\\mathrm{kPa}$ up to $450\\mathrm{kPa}$ , as indicated by the dashed lines for $S_{I},S_{2},$ and $S_{3},$ respectively. The normalized change in capacitance $(\\Delta C/C_{O})$ at $450\\ \\mathrm{kPa}$ is ${\\sim}30$ , which is 33 times that of a sensor with a dielectric layer of pure PDMS 1 $\\langle\\Delta C/C_{O}{\\sim}0.90$ ; black circles in Fig. 3a) or with a micro or nanostructured dielectric layer $(\\Delta C/C_{O}\\sim1.4)^{44}$ . The limit of detection (LOD) reflects the minimum pressure that a sensor can resolve at a base pressure of $0\\mathrm{Pa}$ . The LOD of this sensor is determined to be ${\\sim}0.35\\mathrm{Pa}$ (Supplementary Fig. 9), which is superior to that of human skin $(\\sim\\mathrm{i00Pa})^{45}$ . The low LOD suggests that the sensor can detect tiny pressure signals or weight down to a few milligrams. Additionally, we studied the sensing performance of four sensors prepared from different batches, and the data indicate a high repeatability (Supplementary Fig. 10). \n\nResponse and relaxation speeds are other important sensing parameters that are affected by the viscoelasticity and surface structures of materials28. Soft elastomers such as PDMS often exhibit quite low response and relaxation speeds because of their high viscosity and sticky surfaces. We tested the response and relaxation time of our sensor $\\mathrm{7}\\mathrm{mm}\\times7\\mathrm{mm}$ in area) by applying, holding, and removing a pressure of $1.1\\mathrm{kPa}$ . Both the response time and the relaxation time were measured to be $6\\mathrm{ms}$ (Fig. 3b), which is actually the temporal resolution of our LCR meter. This hints that the true response and relaxation speeds should be even faster. \n\nWe further measured the capacitance-pressure hysteresis loops of the device by loading from 0 to $100\\mathrm{kPa}$ and releasing back to $0\\mathrm{kPa}$ at a loading rate of $0.8\\mathrm{kPa}\\ s^{-1}$ , and the results are displayed in Supplementary Fig. 11. The curves of loading and unloading almost overlap completely, indicating that the sensor can precisely detect the pressure in both the loading and the unloading processes. \n\nThe PDMS-CNTs electrode $7\\mathrm{wt\\%}$ CNTs) can also be used as a strain sensor. In the strain range of $0{-}60\\%$ , the flat electrode exhibits a constant gauge factor (GF) of 2.5 (dashed-dotted line for $\\mathrm{GF}_{1}$ in Fig. 3c). GF is defined as the $\\Delta R/(R_{o}{\\cdot}e)$ , where $\\Delta R$ is the change in resistance with loading, $R_{O}$ is the initial resistance before loading, and $e$ is the engineering strain. Such a response has high repeatability over 10,000 cycles (Supplementary Figs. 12 and 13). Therefore, our device can be used as a bimodal sensor— providing a capacitance signal for pressure sensing and a resistance signal for strain sensing. The two signals decouple from each other since they are measured from different channels (Supplementary Fig. 14). Furthermore, the sensor can be stretched to ${\\sim}160\\%$ (Supplementary Fig. 15), which is sufficient for most applications in conventional robotic systems and on soft robots. It should be noted that strain leads to a limited contribution on the capacitance signal judged from the experimental results on the capacitance to strain response (Supplementary Fig. 16), which is negligible to the overall capacitance change ( $\\Delta C/C_{0}\\sim30$ under a pressure of $450\\mathrm{kPa}$ ). \n\nSensing mechanism: a synergistic effect of compositionstructure design. The doping by CNTs not only determines the function of different layers (electrode or dielectric), but also significantly boosts the signal magnitude of the sensor by over 30 times through a synergetic effect of composition and microstructure design. Figure 3d shows that the doping of CNT $(2\\mathrm{wt\\%})$ can significantly increase the relative permittivity of the dielectric layer, and the relative permittivity becomes highly pressuredependent: it increases from 19.8 to 114 as the pressure increases from 0 to $460\\ \\mathrm{kPa}$ . The increased relative permittivity can be explained by the power-law equation based on the percolation theory: $\\varepsilon\\propto\\dot{(}\\ensuremath{f_{c}}-\\dot{f_{}}_{C N T s})^{-s}$ , where $\\varepsilon$ is the relative permittivity, $f_{\\mathrm{c}}$ is the percolation threshold, and $f_{\\mathrm{CNTs}}$ is the CNTs concentration. A shortened distance of neighboring CNTs upon loading leads to the decrease of $f_{c}$ and thereby increased $\\stackrel{\\cdot}{\\varepsilon}^{46,47}$ . Without CNT doping, the relative permittivity of a pure PDMS is small and its change upon loading is limited—the maximum relative permittivity is only 3.98 at $\\mathsf{450k P a}$ (Supplementary Fig. 17). \n\nWhen pressure is applied on the sensor, the compressive stresses, as well as the relative permittivity of the underlying dielectric layer will be dramatically amplified by the cone-tips (Supplementary Fig. 18 and Supplementary Movie 1). It should be noted that the air gap also serves as a dielectric. As such, our sensor consists of many microconed capacitors and a mesh-like air-gapped capacitor connected in parallel (Supplementary Fig. 19). \n\n![](images/73d4328bd9decceca6162746f3dca3be9370c5f96f54c45062cb11d7575c5b58.jpg) \nFig. 3 Sensing properties, sensing mechanism, and signal stability of the sensor. a Normalized change in capacitance as a function of pressure for a sensor with a dielectric layer of PDMS-CNTs $(2\\mathrm{wt\\%})$ ) or pure PDMS. b Response and relaxation time. c Normalized change in resistance as a function of strain for the flat PDMS-CNTs electrode $(7\\mathrm{wt\\%}\\mathsf{C N T s})$ , showing a constant gauge factor of 2.5 in the strain range of $0{-}60\\%$ . d Relative permittivity of the PDMS-CNTs $(2\\mathrm{wt\\%})$ ) dielectric layer as a function of pressure. e Model used to calculate the normalized capacitance by considering both the localized microstructure deformation and pressure-dependent permittivity. f Calculated normalized capacitance as a function of applied stress using the model shown in panel e. $\\pmb{\\mathsf{g}}$ Cyclic rubbing test response results. Inset: schematic illustration of the rubbing test. h Comparison of the signals at the 1st, $50,000^{\\mathrm{th}},$ and $100,000^{\\mathrm{th}}$ rubbing cycles. i Comparison of signal stability over 10,000 shear-release cycles between sensors with bonded (upper panel) and nonbonded (lower panel) interfaces. \n\nTo elucidate the pressure sensing mechanism, we extract the deformed configurations of the microstructured interface and calculate the capacitance of individual unit by using the simplified electric circuit model as depicted in Fig. 3e. The total capacitance $C$ is roughly divided into three parts of dielectric layer denoted as \n\n$C_{I},C_{2},$ and $C_{3},$ respectively, and one part of air denoted as $C_{a i r}$ . The total capacitance can be expressed as: C \u0003 C1 þ C2 þ Cai3rCaiCr3, $\\begin{array}{r}{C_{1}\\approx\\frac{\\epsilon_{1}(P)R_{1}^{2}\\pi}{H_{1}},C_{2}\\approx\\int_{R_{1}}^{R_{2}}\\frac{\\epsilon_{2}(P)\\left(x-R_{1}\\right)^{2}\\pi}{\\frac{H_{2}-H_{1}}{R_{2}-R_{1}}(x-R_{1})+H_{1}}d x,C_{3}\\approx\\frac{\\epsilon_{3}(P)\\left(R_{3}^{2}-R_{2}^{2}\\right)\\pi}{H_{3}},}\\end{array}$ $\\begin{array}{r}{C_{a i r}\\approx\\int_{R_{2}}^{R_{3}}\\frac{\\epsilon_{0}\\left(x-R_{2}\\right)^{2}\\pi}{R_{3}-R_{2}}d x}\\end{array}$ . Here $\\epsilon_{0}$ represents the vacuum permittivity, and $\\epsilon_{1}(P),\\epsilon_{2}(P),\\epsilon_{3}(P)$ are the pressure-dependent permittivity of the dielectric parts (Fig. 3d); $R_{I},R_{2},$ and $R_{3}$ are the radii of circular capacitors $C_{I},C_{2},$ and $C_{3},$ respectively; $H_{I},H_{2}$ and $H_{3}$ are the dielectric thickness of circular capacitors $C_{I},C_{2},$ . and $\\displaystyle{C_{3},}$ respectively, and $x$ is the distance to the cone axis. Note that pressure distribution inside each part of the dielectric layer is approximated to be uniform because higher stress is only observed in the tip contact zones and parameters $R_{I}–R_{3}$ , $H_{I}–H_{3}$ vary with the pressure (Supplementary Fig. 18). At different compressive pressures, the contact zone configuration changes, leading to different $R_{1},R_{2},R_{3},H_{1},H_{2}$ ; and $H_{3}$ . By extracting them from the FEA model, we can calculate the total capacitance C. Next, normalized $\\Delta C/C_{0}$ is computed and shown in Fig. 3f, which agrees well with experimental measurement. \n\nOur model indicates that the capacitance change is a synergistic effect of the cone structures (for local stress amplification and change in electrode-dielectric contact) and CNT doping (which enables pressure-dependent relative permittivity). By comparing Fig. 3d, f, we can conclude that the response at the high-pressure region (pressure $>200$ kPa) is mainly contributed from the localized microstructure deformation, while the response at low pressures is mainly contributed from the permittivity change enabled by the CNT doping. Without a microstructured electrode, the sensor with CNT-doped dielectric and all flat electrodes exhibits a maximum $\\Delta C/C_{0}$ of only 5 (Supplementary Fig. 20), and the pressure response range of the sensor becomes much narrow. \n\nHigh stability of signal during cycling. Our sensor exhibits high stability under cyclic loading-unloading. We tested the signal stability of the sensor $\\mathrm{10mm}\\times20\\mathrm{mm}$ in area) under rubbing and shear conditions, each for at least 10,000 cycles. Figure 3g, h show that when the sensor is rubbed with abrasive paper for 100,000 cycles under a normal pressure of $10\\mathrm{kPa}$ and a reciprocating displacement of $2\\mathrm{mm}$ , no obvious change in signal waveform or amplitude is observed. By contrast, the sensing signal of a commercial flexible pressure sensor is apparently unstable (Supplementary Fig. 21). We also tested the signal stability by applying repeated shear stress of $5\\mathrm{kPa}$ (Fig. 3i and Supplementary Fig. 22) for 10,000 cycles, and likewise no significant change in signal amplitude or mechanical failure was observed. By contrast, control samples with a non-bonded microstructured interface show clear signal drift (low panels, Fig. 3i). \n\n# Applications of the sensor under harsh mechanical conditions. \n\nOur design of the material system and the interface enables performances that otherwise cannot be achieved without the advancements made in this work. We tested the stability of our sensor under extreme mechanical conditions, and a running car that generates a high pressure and a large shear stress at its tire tread was used for this purpose. We affixed a sensor $\\mathrm{{10}m m}\\times$ $40\\mathrm{mm}$ in area) to the tire tread to test its signal stability during driving, and meanwhile a commercial pressure sensor serving as the control sample was also tested. The capacitance signal was collected using a data acquisition module, and the measured data were transmitted to a computer through Bluetooth (Fig. 4a, and Supplementary Note 1). When the test car is running, the tire tread is loaded with a normal pressure of ${\\sim}300\\mathrm{kPa}$ and a shear stress of about $6\\ensuremath{\\mathrm{kPa}}$ (Fig. 4b, c), and thus it is a great challenge for a flexible pressure sensor to survive under such complicated mechanical conditions. The calculation of the pressure and the shear stress can be seen in Supplementary Note 2. \n\nWe tested the capacitance signal of our sensor and resistance signal of the commercial sensor when the car was in motion over a long distance on an asphalt road. Both sensors performed normally at the beginning of the test (Supplementary Fig. 23). \n\nFigure 4d shows that, as the car was driving with an average speed of $22\\mathrm{km}\\cdot\\mathrm{h}^{-1}$ , the capacitance signal remained stable over at least $2.6\\mathrm{km}$ (or 1102 rotations). However, the commercial sensor failed after driving over a shorter distance of $0.5\\mathrm{km}$ . We also tested other samples of our sensor under different road conditions and all of them exhibited high stability (Supplementary Movie 2). Note that the non-uniform signal amplitudes of our sensor is caused by the rough surface of the asphalt road containing millimeter and centimeter scale features. The high stability of the signal is in line with the microstructure of the sensor displayed in Fig. 4e, which shows that the cones remain well bonded at the interface without rupture after testing. We ascribe the high stability of our sensor under such harsh mechanical conditions to the quasi-homogeneous material system as well as the interlinked interfaces between different functional layers. \n\nSoft robot-sensor integration. A requirement for nextgeneration soft robots is to merge with e-skins to gain sensory functions, such that they can interact with human beings and the environment. Existing sensors and robots, however, are often made of different materials, and thus their integration suffers from the poor sensor-robot interface due to the large difference in mechanical properties. Such integration thus requires complicated designs like embedding the sensor inside the robotic matrix48. \n\nHere both our sensor and the soft robot are made of PDMSCNTs composites with interlinked interfaces. Figure 5a shows a photograph of a soft gripper with eight sensors integrated on its surface. The SEM image of a section of the gripper displayed in Fig. 5b shows that the gripper matrix has merged with the bottom electrode of the sensor. Because of the tough interfaces in the robot-sensor system, the soft robots can be used both to grasp objects and to detect the pressure distribution on the gripper surface. Figure $5\\mathrm{c-g}$ show grippers being used to grasp a netted melon (weight: $\\boldsymbol{1250}\\mathrm{g})$ and a stuffed doll (weight: $\\mathrm{180~g}$ ), as well as the corresponding pressure mapping of a gripper surface. Grasping heavy items can generate pressure and shear stress of tens of kilopascals on the gripper surface. When grasping the melon, which is relatively heavy and hard, the gripper surface does not fully conform to the curvature of the melon (Fig. 5d) and the pressure is mainly focused on the bottom of the gripper (Fig. 5d) since the melon tends to slip down and makes more intimate contact with the bottom sensor. By contrast, when grasping a stuffed doll that is softer and lighter (Fig. 5e), the contact elevates to a higher position and a more gradually varied pressure distribution is observed due to its lighter weight, as indicated by the corresponding pressure mapping. Furthermore, when setting a weight on the doll to equalize the weight as the netted melon $(1250\\mathrm{g})$ , a gradually varied pressure distribution focused at the bottom of the gripper is observed (Fig. 5f), which combines the features of the previous two cases. \n\nDuring cyclic manipulation of the melon by the soft robot, the capacitance signal can precisely identify the specific manipulation stage, and it shows high stability over at least 1000 cycles. A force gauge is setup to record the force that lifts the griper during the different manipulation stages (lifting, holding, and landing). Before the melon is lifted, the force is zero. Figure $5\\mathrm{g}$ shows the manipulation cycle, including grasping the melon placed on a table, lifting it up to ${\\sim}10\\mathrm{cm}$ , holding it at this height for ${\\sim}1\\ s,$ returning it to the table, and releasing it. The capacitance signal reflects the different manipulation stages (Fig. 5g and Supplementary Fig. 24). After repeating the process for a total of 1000 cycles, neither a significant change in signal amplitude nor delamination of the sensor was observed (Fig. 5h). The high stability is due to the interlinking of all interfaces in this system. Without this strong topological adhesion, sensors cannot survive under such harsh mechanical conditions. This is shown by repeating the manipulation-cycling experiment with a control sample, in which a thin PDMS layer was used to adhere the microcones and the dielectric layer (without introducing interlinks). In this case, the device delaminates and fails at the $137^{\\mathrm{th}}$ cycle (Fig. 5i). \n\n![](images/e910d3278572c75df5790a4ff7f15b4cde5869e447255af637f01f72945b9ad7.jpg) \nFig. 4 Test of the all PDMS-CNTs sensor and a commercial sensor on a tire tread. a Schematic illustration of the testing setup, which consists of a sensor attached to a tire tread, a data acquisition module, and a Bluetooth transmitter for sending test data to a computer. b Stress conditions on the sensor. c Photograph of the testing system. The sensor is affixed to the tire tread and the data acquisition module and the Bluetooth transmitter are affixed to the wheel hub. d Signal stability of the all PDMS-CNTs sensor and the commercial sensor during operation of the car over ${\\sim}2.6k\\mathrm{m}$ on an asphalt road with an average speed of $22\\mathsf{k m}\\mathsf{h}^{-1}$ . e SEM image of the microstructured interface of the all PDMS-CNTs sensor after testing. \n\nIn addition, our devices can serve as bimodal sensors by responding sensitively to both pressure and strain, which are measured from capacitance and resistance signals, respectively. Here, we integrated the sensor on a soft-robot gripper and demonstrated the capacitance and resistance response under a dynamic process of grasping, lifting, holding, and releasing a doll. In the initial state, the gripper is fully open in order to grasp the large item, and a tensile strain is imposed on the sensor. Upon touching and grasping the doll, the capacitance increases sharply, and the resistance decreases due to the reduced strain on the gripper surface. The doll is then lifted and held for ${\\sim}2\\ s,$ and it falls down upon release (Fig. 5j). Accordingly, the capacitance signal remains unchanged during holding, and suddenly decreases to the initial value after release; the resistance signal also shows a relatively stable value when the doll is held and recovers to the original values after release (Fig. 5k). \n\nMoreover, the sensor does not require encapsulation. Encapsulating tactile sensors or e-skins is often conventionally achieved by piling up the device’s functional layers and sealing them with a layer of tape29,49. Such sensors work stably under normal compression, but fail under other mechanical modes that generate in-plane shear stresses. Supplementary Fig. 25 shows that in a sensor sealed and affixed to a soft-robot gripper with a thin layer of polyimide tape, the top functional layer buckles upon concave bending due to the much higher rigidity of the tape and the non-bonded interface. As a result, the capacitance signal becomes negative during cycles of bending and release since a thick air gap is generated between the electrode and the CNTsdoped dielectric layer. In comparison, our sensor with tough interfaces does not show any structure damage or signal degradation over bending-release cycling (Supplementary Fig. 23). All these results confirm that our design, which incorporates an all-PDMS-CNTs composition together with interlinked interfaces, is a good selection for sensor-integrated soft robots. \n\n# Discussion \n\nTraditional $\\mathbf{e}$ -skins designs have mainly focused on the improvement of sensing performance, while few efforts have taken robust interfaces into considerations. Challenges among interfaces stem either from the interlayer debonding/delamination in the sensors, or from the poor fixation of the sensors on robots. Additive manufacturing is expected to be promising for integrated e-skins and for sensor-soft robot integration achieved by multimaterial printing50; but this technology is still in its infancy and is currently limited to strain sensors with simple device structures. \n\n![](images/dd02ab331591fbd5bea6545e2654329959297240b173c23a1e9d87995316adee.jpg) \n\nHere we still used the traditional multilayered design for sensors and for sensor-soft robot integration, but simply applied a single-material system with tunable functions, together with the interlinking of the layers. Our design minimizes the mechanical mismatch and achieves strong adhesion between different layers in sensors, and between the sensors and a soft robot, while significantly boosting sensing performances. As expected, the tough and strong interfaces remarkably improve the signal fidelity of the sensor under extreme mechanical conditions. Although our strategy of using a single material-system and introducing interlinks between the layers can provide highly stable signal, the maximum sensitivity is relatively low, which might be due to the low conductivity of the electrodes17,51,52. This problem can possibly be addressed by using other highly conducting fillers such as Ag nanowires, or by using an ionic material to replace the dielectric layer that help form a supercapacitor at the interface. \n\nFig. 5 Soft robot-sensor integration. a Photograph of a soft robot integrated with a sensor array consisting of eight sensors. b Left: SEM image showing the robot-sensor interface and the interfaces in the sensor. Right: schematic illustration of the integrated robot-sensor configuration. c Photograph of soft-robot grippers grasping a netted melon. d Magnified image showing the contact between the melon and one gripper. The sensors are numbered from 1–8 from bottom to top, and corresponding pressure mapping on the surface of the gripper surface. e Photograph of the grippers grasping a stuffed doll and corresponding pressure mapping. f Photograph of the grippers grasping a stuffed doll with a weight to have a total mass of ${1250}\\mathrm{g},$ and corresponding pressure mapping. g Capacitance change evolution of sensor 1 [as marked in panel d] as the soft-robot grippers grasp the melon on a table, lift it up to $10\\mathsf{c m}$ , hold it at this height for 1 s, return it to the table, and release it. The photographs illustrate each stage of the manipulation process. The evolutions of the height of the melon and the change in force throughout the process are also plotted. h Capacitance change measurement over 1000 cycles of the manipulation stages indicated in panel g. i Capacitance change measurement of a control sample with a bonded but non-interlinked interface. The sensor fails at the $137^{\\mathrm{th}}$ cycle. Inset: schematic illustration of delamination in the control sample and optical image of the delaminated electrode in the control sample. j Photographs of soft-robot grippers grasping, lifting, holding, and releasing of a doll. k Corresponding capacitance signal for pressure sensing (upper panel) and resistance signal for strain sensing (lower panel) during three cycles of the manipulation shown in j. All measured from sensor 1 [as marked in panel d]. Upper and lower insets: schematic illustrations of the measuring circuits for the capacitance and resistance signals, respectively. \n\nIn summary, we have developed all-PDMS-CNTs-based sensors with topologically interlinked interfaces, integrated the sensors on soft robots, and demonstrated stable sensing performance under harsh mechanical conditions. By controlling the concentration of CNTs in PDMS, the function of the composite can be tuned to be a dielectric layer or an electrode, while both exhibit similar mechanical properties. The interlinked interface as well as the doping of CNTs in dielectric remarkably boosts the signal amplitude and sensitivity by tens of times. The interlinked interfaces have a high toughness of ${\\tt>}390{\\mathrm{J}}{\\cdot}{\\mathrm{m}}^{-2}$ , and a shear strength of ${>}88\\mathrm{kPa}$ . As such, the sensor exhibits negligible fatigue when subjected to repeated rubbing and shear test for at least 10,000 cycles, or when attached on a tire tread and run over $2.6\\mathrm{km}$ . The high toughness and strength of the microstructured interfaces stem from the topological interlinks, the elastic dissipation caused by the microcones, and the discrete rupture mode of the cones. The interlinked interface and the all-PDMS-CNTs composition can also be extended to the integration of e-skins on soft robots, and we have shown that e-skins bonded on soft robot grippers exhibit high stability during manipulation tasks under harsh mechanical conditions. Our strategy opens a path for the fabrication of highly robust e-skins with improved sensitivity and response/relaxation speeds, as well as for the integration of sensors and soft robotics. \n\n# Methods \n\nPreparation of all PDMS-CNTs functional layers. CNTs $\\mathrm{\\langle0.77~g.}$ purity: $95\\%$ , diameter: $10{-}20~\\mathrm{nm}$ , length: $10{-}30\\upmu\\mathrm{m}$ , Nanjing Xianfeng Nano-technology Co., Ltd.), a PDMS base $(10\\:\\mathrm{g})$ , and a curing agent ${\\bf\\Pi}(1\\mathrm{\\bfg})$ (with a weight ratio of 10:1, Sylgard 184, Dow Corning Co., Ltd) were dispersed in trichloromethane $(265{\\mathrm{g}},$ Aladdin, $99\\%$ ) for $^{2\\mathrm{h}}$ with ultrasonic assistance. For each layer, the solution was then poured into a mold, the trichloromethane was allowed to evaporate at room temperature, and the degassed liquid was cured at $80^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ . The flat electrode was controlled to be $\\sim50\\upmu\\mathrm{m}$ thick with a CNTs-to-PDMS weight ratio of $7\\mathrm{wt\\%}$ . Similarly, by controlling the casted weight and area of the mold, the dielectric layer was controlled to be $120~{\\upmu\\mathrm{m}}$ thick with a CNTs-to-PDMS weight ratio of $2\\mathrm{wt\\%}$ . \n\nCalathea zebrine leaves were used as the template for the fabrication of the microconed electrode. The Calathea zebrine leaves were washed clean and cut into rectangular pieces (area: $50\\mathrm{mm}\\times80\\mathrm{mm},$ ), which were then fixed onto glass substrates using pieces of Scotch tapes (3 M). A PDMS base and a curing agent (weight ratio of 5:1) were casted on the surface of the Calathea zebrine templates. After being cured at $70^{\\circ}\\mathrm{C}$ for $^{\\textrm{1h}}$ , the PDMS pieces with structures featuring microholes were peeled off and served as the secondary templates. Each PDMS template was then subjected to air plasma treatment (TS-PL05, Dongxingaoke Co., Ltd) at $50\\mathrm{W}$ for $3\\mathrm{min}$ . Finally, uncured PDMS-CNTs liquid was casted on the secondary template. After being cured at $80^{\\circ}\\mathrm{C}$ for $\\displaystyle{2\\mathrm{h}.}$ , the microstructured PDMS films featuring microcones were carefully peeled off and were ${\\sim}100\\ \\upmu\\mathrm{m}$ thick with a CNT-to-PDMS weight ratio of $7\\mathrm{wt\\%}$ . \n\nInterlinking of functional layers. After exploring the effect of different weight ratio of PDMS base and curing agent on the sensing performance (Supplementary Fig. 26), a weight ratio of 10:1 was chosen for the interlinking PDMS network. To introduce interlinks between the adherend networks, a PDMS base $(5.5\\mathrm{wt\\%})$ and a curing agent $(0.55\\mathrm{wt\\%})$ were added to trichloromethane and sonicated for $30\\mathrm{min}$ to obtain a homogenized dispersion. The electrodes and the dielectric layer were then swollen in the trichloromethane solution for $^{6\\mathrm{h}}$ at room temperature. The swollen components were removed from the solution to allow the trichloromethane to evaporate. Finally, the flat electrode, the dielectric layer, and the microstructured electrode were stacked in order from top to bottom, exposed to a pressure of $20\\mathrm{kPa}$ , and stored at $80~^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{h}}$ for the monomers to be cured and interlinked. \n\nSensing performance of the sensors. Most of sensors used for testing sensing properties have a surface area of $10\\mathrm{mm}\\times10\\mathrm{mm}$ unless otherwise specified. To test of the sensitivity and the limit of detection, a sensor was placed on the flat stage of a mechanical test system (XLD-500E, Jingkong Mechanical Testing Co., Ltd). A flat indenter (larger than the sensor size) was used to slowly approach the sensor, make contact with the sensor, and load the programmed-set force. Capacitance signal was recorded in real-time during the loading process via an LCR meter $({\\mathrm{E4980AL}},$ KEYSIGHT) at a testing frequency of 0.1 MHz. For the test of the response/release time, we used a general operation in the field18,53. First, a weight $(5\\:\\mathrm{g})$ was placed close to the top surface of the sensor $\\mathrm{7mm\\times7mm})$ and released carefully, producing a pressure of $1.1\\ \\mathrm{kPa}$ . Next, the weight was removed after placing for 5 s. The capacitance signal was recorded using an LCR meter (E4981A, KEYSIGHT) at a frequency of 1 MHz to obtain the response and recovery time. \n\nStability testing. Sensors $\\mathrm{10\\mm}\\times20\\mathrm{mm}$ in area) were adhered to specifically designed holders using a layer of cyanoacrylate glue (Krazy Glue, 3 M CA40H) to ensure that it could be fixed stably during test. The holders were controlled using a force gauge with a computer-controlled stage (XLD-500E, Jingkong Mechanical Testing Co., Ltd). For the rubbing tests, the pressure applied to each sensor was 10 kPa and the test speed was $2\\mathrm{mm}\\cdot\\mathrm{min}^{-1}$ to realize a reciprocating displacement of $2\\mathrm{mm}$ for 100,000 cycles. For the shear tests, the shear stress was $5\\mathrm{kPa}$ for 10,000 cycles. \n\nMechanical characterization. To measure interfacial toughness and shear strength, adhered samples, each with a surface area $10\\mathrm{mm}$ in width and $30\\mathrm{mm}$ in length, were prepared and subjected to a standard $180^{\\circ}$ peel test using a force gauge with a computer-controlled stage (XLD-500E, Jingkong Mechanical Testing Co., Ltd). The peeling speed was controlled at $50\\mathrm{mm}{\\cdot}\\mathrm{min}^{-1}$ . The sensors were adhered to a polyimide sheet by using a layer of cyanoacrylate glue (Krazy Glue) as a stiff backing. \n\nTesting of the sensor on a tire tread. The tire-tread sensing system consisted of a sensor ( $10\\mathrm{mm}\\times40\\mathrm{mm}$ in surface area), a data acquisition module, and a data receiver. A commercialized flexible pressure sensor (MD30-60-50Kgf, diameter: $25\\mathrm{mm}$ ) was purchased from Suzhou Leanstar Electronic Technology Co., Ltd (website: http://www.lssensor.com) as a control sample to compare with our sensor in terms of sensing stability. The sensors were adhered to the tread of a rear tire on a car using VHB tape (3 M) and was connected to the data acquisition module attached to the wheel hub. Data was transmitted from the data acquisition module to the data receiver via Bluetooth. The driving conditions (including speed and distance) were recorded simultaneously through an GPS app on a phone. To avoid the complicated road condition, we chose to drive on a new asphalt loop-road ( $_{\\sim300\\mathrm{m}}$ long) containing straight and turns. \n\nSensor-soft robot integration and sensing performance during grasp manipulation. A pneumatic soft robot with three gripper fingers was used for sensorrobot integration. The grippers had a PDMS-CNTs $(0.2\\mathrm{wt\\%})$ matrix and eight sensors $10\\mathrm{mm}\\times14\\mathrm{mm}$ in area) were adhered on the gripper surface with interlinked interface by using the aforementioned methods. A netted melon (weight: $1250{\\mathrm{g}})$ and a doll (weight: $\\mathbf{180}\\ \\mathbf{g})$ were chosen as specific subjects for the grasp manipulation. The driving pressure for griping the netted melon and the doll were $140\\ \\mathrm{kPa}$ and $80\\ensuremath{\\mathrm{\\kPa}}$ , respectively. For the bimodal sensing test, the resistance signals were collected from the flat electrode. \n\nCharacterization. A field-emission scanning electron microscope (FESEM, TESCAN) was used to characterize the morphology of the sensor structures and the interfaces between the robot and the sensor. External pressure was applied and measured using a force gauge with a computer-controlled stage (XLD-500E, Jingkong Mechanical Testing Co., Ltd). The capacitance response and the permittivity were measured via an LCR meter (E4980AL, KEYSIGHT) at a testing frequency of $0.1\\mathrm{MHz}$ unless otherwise specified. The response time and relaxation time were measured via an LCR meter (E4981A, KEYSIGHT) at a testing frequency of 1 MHz. The resistance was recorded using a digital multimeter (Keithley 2100). For the stable electrical connection of the sensor to the LCR meter, two thin silver wires (dimeter ${\\sim}0.1\\ \\mathrm{mm}$ ) were adhered on a protruding part of the electrodes by using soft elargol, and a thin PDMS layer was further casted and cured to protect the joint. \n\nReporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article. \n\n# Data availability \n\nAll relevant data sets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. \n\nReceived: 18 November 2021; Accepted: 22 February 2022; Published online: 10 March 2022 \n\n# References \n\n1. Li, G., Liu, S., Wang, L. & Zhu, R. Skin-inspired quadruple tactile sensors integrated on a robot hand enable object recognition. Sci. Robot. 5, eabc8134 (2020). \n2. Pang, K. et al. Hydroplastic foaming of graphene aerogels and artificially intelligent tactile sensors. Sci. Adv. 6, eabd4045 (2020). \n3. Araromi, O. A. et al. Ultra-sensitive and resilient compliant strain gauges for soft machines. Nature 587, 219–224 (2020). \n4. Zhang, C. et al. A stretchable dual-mode sensor array for multifunctional robotic electronic skin. Nano Energy 62, 164–170 (2019). \n5. Wang, H. S. et al. Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics. Sci. Adv. 7, eabe5683 (2021). \n6. Chen, L. et al. 3D printed super-anti-freezing self-adhesive human-machine interface. Mater. Today Phys. 19, 100404 (2021). \n7. Park, J. et al. Tactile-direction-sensitive and stretchable electronic skins based on human-skin-iInspired interlocked iicrostructures. ACS Nano 8, 12020–12029 (2014). \n8. Park, J. et al. Fingertip skin-inspired microstructured ferroelectric skins discriminate static/dynamic pressure and temperature stimuli. Sci. Adv. 1, e1500661 (2015). \n9. Boutry, C. et al. A hierarchically patterned, bioinspired e-skin able to detect the direction of applied pressure for robotics. Sci. Robot. 3, eaau6914 (2018). \n10. Lee, Y. et al. Flexible ferroelectric sensors with ultrahigh pressure sensitivity and linear response over exceptionally broad pressure range. ACS Nano 12, 4045–4054 (2018). \n11. Wang, K. et al. Bioinspired interlocked structure-induced high deformability for two-dimensional titanium carbide (MXene)/natural microcapsule-based flexible pressure sensors. ACS Nano 13, 9139–9147 (2019). \n12. Lee, Y. et al. Bioinspired gradient conductivity and stiffness for ultrasensitive electronic skins. ACS Nano 15, 1795–1804 (2021). \n13. Guo, Z. H. et al. Printed and flexible capacitive pressure sensor with carbon nanotubes based composite dielectric layer. Micromachines 10, 715 (2019). \n14. Zhang, Z. et al. Highly sensitive capacitive pressure sensor based on a micropyramid array for health and motion monitoring. Adv. Electron. Mater. 7, 2100174 (2021). \n15. Zhang, P., Zhang, J., Li, Y. X. & Huang, L. S. Flexible and high sensitive capacitive pressure sensor with microstructured electrode inspired by ginkgo leaf. J. Phys. D: Appl. Phys. 54, 465401 (2021). \n16. Mannsfeld, S. C. et al. Highly sensitive flexible pressure sensors with microstructured rubber dielectric layers. Nat. Mater. 9, 859–864 (2010). \n17. Bai, N. et al. Graded intrafillable architecture-based iontronic pressure sensor with ultra-broad-range high sensitivity. Nat. Commun. 11, 209 (2020). \n18. Chortos, A., Liu, J. & Bao, Z. Pursuing prosthetic electronic skin. Nat. Mater. 15, 937–950 (2016). \n19. Gogurla, N., Roy, B., Min, K., Park, J. Y. & Kim, S. A skin-inspired, interactive, and flexible optoelectronic device with hydrated melanin nanoparticles in a protein hydrogel-elastomer hybrid. Adv. Mater. Technol. 5, 1900936 (2020). \n20. Ren, Y. et al. Electric-field-induced gradient ionogels for highly sensitive, broad-range-response, and freeze/heat-resistant ionic fingers. Adv. Mater. 33, 2008486 (2021). \n21. Niu, H. et al. Highly morphology-controllable and highly sensitive capacitive tactile sensor based on epidermis-dermis-inspired interlocked asymmetricnanocone arrays for detection of tiny pressure. Small 16, 1904774 (2020). \n22. Chhetry, A., Sharma, S., Yoon, H., Ko, S. & Park, J. Y. Enhanced sensitivity of capacitive pressure and strain sensor based on $\\mathrm{CaCu}_{3}\\mathrm{Ti}_{4}\\mathrm{O}_{12}$ wrapped hybrid sponge for wearable applications. Adv. Funct. Mater. 30, 1910020 (2020). \n23. Guo, H. et al. Artificially innervated self-healing foams as synthetic piezoimpedance sensor skins. Nat. Commun. 11, 1–10 (2020). \n24. Schwartz, G. et al. Flexible polymer transistors with high pressure sensitivity for application in electronic skin and health monitoring. Nat. Commun. 4, 1–8 (2013). \n25. Zhang, Z. et al. Feetbeat: A flexible iontronic sensing wearable detects pedal pulses and muscular activities. IEEE Trans. Biomed. Eng. 66, 3072–3079 (2019). \n26. Ruth, S. R. A. et al. Rational design of capacitive pressure sensors based on pyramidal microstructures for specialized monitoring of biosignals. Adv. Funct. Mater. 30, 1903100 (2020). \n27. Yang, J. C. et al. Electronic skin: recent progress and future prospects for skinattachable devices for health monitoring, robotics, and prosthetics. Adv. Mater. 31, 1904765 (2019). \n28. Byun, J. et al. Electronic skins for soft, compact, reversible assembly of wirelessly activated fully soft robots. Sci. Robot. 3, eaas9020 (2018). \n29. Cicek, M. O. et al. Seamless monolithic design for foam based, flexible, parallel plate capacitive sensors. Adv. Mater. Technol. 6, 2001168 (2021). \n30. Woo, S.-J., Kong, J.-H., Kimb, D.-G. & Kim, J.-M. A thin all-elastomeric capacitive pressure sensor array based on micro-contact printed elastic conductors. J. Mater. Chem. C. 2, 4415 (2014). \n31. Devaraj, H. et al. Highly elastic and flexible multi-layered carbon black/ elastomer composite based capacitive sensor arrays for soft robotics. Meas.: Sens. 2-4, 100004 (2020). \n32. Tee, B. C.-K. et al. A skin-inspired organic digital mechanoreceptor. Science 350, 313–316 (2015). \n33. Noblesse, E. et al. Lysyl oxidase-like and lysyl oxidase are present in the dermis and epidermis of a skin equivalent and in human skin and are associated to elastic fibers. J. Invest. Dermatol. 122, 621–630 (2004). \n34. Zhu, Z., Li, R. & Pan, T. Imperceptible epidermal–iontronic interface for wearable sensing. Adv. Mater. 30, 1705122 (2018). \n35. Jeong, J. W. et al. Materials and optimized designs for human-machine interfaces via epidermal electronics. Adv. Mater. 25, 6839–6846 (2013). \n36. Someya, T. Ensuring smooth strain gradient across interconnects in Stretchable Electronics, 91–94 (Wiley-VCH, Weinheim, 2012). \n37. Qiu, Z. et al. Ionic skin with biomimetic dielectric layer templated from calathea zebrine leaf. Adv. Funct. Mater. 28, 1802343 (2018). \n38. Gao, H., Ji, B., Jäger, I. L., Arzt, E. & Fratzl, P. Materials become insensitive to flaws at nanoscale: lessons from nature. Proc. Natl Acad. Sci. 100, 5597–5600 (2003). \n39. Gu, X. W., Wu, Z., Zhang, Y.-W., Srolovitz, D. J. & Greer, J. R. Microstructure versus flaw: mechanisms of failure and strength in nanostructures. Nano Lett. 13, 5703–5709 (2013). \n40. Guo, C. F., Sun, T., Liu, Q., Suo, Z. & Ren, Z. Highly stretchable and transparent nanomesh electrodes made by grain boundary lithography. Nat. Commun. 5, 1–8 (2014). \n41. Kamperman, M. et al. Functional adhesive surfaces with “gecko” effect: The concept of contact splitting. Adv. Eng. Mater. 12, 335–348 (2010). \n42. Chan, E. P., Greiner, C., Arzt, E. & Crosby, A. J. Designing model systems for enhanced adhesion. MRS Bull. 32, 496–503 (2007). \n43. Ruth, S. R. A. & Bao, Z. Designing tunable capacitive pressure sensors based on material properties and microstructure geometry. ACS Appl. Mater. Interfaces 12, 58301–58316 (2020). \n44. Lee, S. et al. Nanomesh pressure sensor for monitoring finger manipulation without sensory interference. Science 370, 966–970 (2020). \n45. Xu, T. et al. High resolution skin-like sensor capable of sensing and visualizing various sensations and three dimensional shape. Sci. Rep. 5, 12997 (2015). \n46. Lin, C., Wang, H. T. & Yang, W. Variable percolation threshold of composites with fiber fillers under compression. J. Appl. Phys. 108, 013509 (2010). \n47. Wang, J. et al. A highly sensitive and flexible pressure sensor with electrodes and elastomeric interlayer containing silver nanowires. Nanoscale 7, 2926 (2015). \n48. Thuruthel, T. G., Shih, B., Laschi, C. & Tolley, M. T. Soft robot perception using embedded soft sensors and recurrent neural networks. Sci. Robot. 4, eaav1488 (2019). \n49. Nie, B., Li, R., Cao, J., Brandt, J. D. & Pan, T. Flexible transparent iontronic film for interfacial capacitive pressure sensing. Adv. Mater. 27, 6055–6062 (2015). \n50. Ge, Q. et al. 3D printing of highly stretchable hydrogel with diverse UV curable polymers. Sci. Adv. 7, eaba4261 (2021). \n51. Amoli, V. et al. A bioinspired hydrogen bond-triggered ultrasensitive ionic mechanoreceptor skin. Nat. Commun. 10, 4019 (2019). \n52. Sharma, S. et al. Hydrogen-bond-triggered hybrid nanofibrous membranebased wearable pressure sensor with ultrahigh sensitivity over a broad pressure range. ACS Nano 15, 4380–4393 (2021). \n53. Feng, J. G. et al. Single-crystalline layered metal-halide perovskite nanowires for ultrasensitive photodetectors. Nat. Electron. 1, 404–410 (2018). \n\n# Acknowledgements \n\nThe work was funded by the National Natural Science Foundation of China (No. 52073138 [C.F.G.], 51903118 [J.Y.]), the “Guangdong Innovative and Entrepreneurial Research Team Program” under Contract No. 2016ZT06G587 [C.F.G.], the “Science Technology and Innovation Committee of Shenzhen Municipality” (Grant No. JCYJ20210324120202007 [C.F.G.]), the Shenzhen Sci-Tech Fund (No. KYTDPT20181011104007 [C.F.G.]), and the “Tencent Robotics X Lab Rhino-Bird Focused Research Program” (No. JR201984 [C.F.G.]). \n\n# Author contributions \n\nC.F.G. conceived the idea and directed the study. Y.Z. conducted the majority of experiments. C.F.G., Y.Z. and J.Y. conducted data analysis; J.Y., X.H., G.L., L.W., M.C., L.Z., J.Z., N.B. and Y.W. also participated in experiments. K.C., Y.D., and Z.Z. contributed the testing system for pressure mapping. C.F.G. and C.Y. studied the physical mechanism of tough interfaces. C.F.G. drafted the manuscript, X.W. helped revise the manuscript, and the manuscript was written through contributions of all authors. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-022-29093-y. \n\nCorrespondence and requests for materials should be addressed to Chuan Fei Guo. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permission information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2022 " + }, + { + "id": "10.1073_pnas.2119492119", + "DOI": "10.1073/pnas.2119492119", + "DOI Link": "http://dx.doi.org/10.1073/pnas.2119492119", + "Relative Dir Path": "mds/10.1073_pnas.2119492119", + "Article Title": "Identification of Fenton-like active Cu sites by heteroatom modulation of electronic density", + "Authors": "Zhou, X; Ke, MK; Huang, GX; Chen, C; Chen, WX; Liang, K; Qu, YT; Yang, J; Wang, Y; Li, FT; Yu, HQ; Wu, YE", + "Source Title": "PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA", + "Abstract": "Developing heterogeneous catalysts with atomically dispersed active sites is vital to boost peroxymonosulfate (PMS) activation for Fenton-like activity, but how to controllably adjust the electronic configuration of metal centers to further improve the activation kinetics still remains a great challenge. Herein, we report a systematic investigation into heteroatom-doped engineering for tuning the electronic structure of Cu-N-4 sites by integrating electron-deficient boron (B) or electron-rich phosphorus (P) heteroatoms into carbon substrate for PMS activation. The electron-depleted Cu-N-4/C-B is found to exhibit the most active oxidation capacity among the prepared Cu-N-4 single-atom catalysts, which is at the top rankings of the Cu-based catalysts and is superior to most of the state-of-the-art heterogeneous Fenton-like catalysts. Conversely, the electron-enriched Cu-N-4/C-P induces a decrease in PMS activation. Both experimental results and theoretical simulations unravel that the long-range interaction with B atoms decreases the electronic density of Cu active sites and down-shifts the d-band center, and thereby optimizes the adsorption energy for PMS activation. This study provides an approach to finely control the electronic structure of Cu-N-4 sites at the atomic level and is expected to guide the design of smart Fenton-like catalysts.", + "Times Cited, WoS Core": 282, + "Times Cited, All Databases": 284, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000766924200016", + "Markdown": "# Identification of Fenton-like active Cu sites by heteroatom modulation of electronic density \n\nXiao Zhoua,b,1, Ming-Kun Ke (柯明坤)c,1 $\\circledcirc$ , Gui-Xiang Huangc, Cai Chenb, Wenxing Chend, Kuang Liangb, Yunteng $\\mathsf{\\Omega}\\mathsf{Q}\\mathsf{u}^{\\mathsf{b}}$ Jia Yangb, Ying Wanga,2 , Fengting Lia, Han-Qing $\\gamma_{\\mathbf{u}}c,2_{\\mathbf{\\overline{{\\mathbf{v}}}}}$ , and Yuen $\\mathsf{w u}^{\\mathsf{b},\\mathsf{e},2}(\\mathbb{D}$ \n\naCollege of Environmental Science and Engineering, Tongji University, State Key Laboratory of Pollution Control and Resources Reuse, Shanghai 200092, China; bHefei National Laboratory for Physical Sciences at the Microscale, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China; cChinese Academy of Sciences Key Laboratory of Urban Pollutant Conversion, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China; dBeijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications, School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China; and eDalian National Laboratory for Clean Energy, Dalian 116023, China \n\nEdited by Alexis Bell, Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA; received October 25, 2021; accepted December 15, 2021 \n\nDeveloping heterogeneous catalysts with atomically dispersed active sites is vital to boost peroxymonosulfate (PMS) activation for Fenton-like activity, but how to controllably adjust the electronic configuration of metal centers to further improve the activation kinetics still remains a great challenge. Herein, we report a systematic investigation into heteroatom-doped engineering for tuning the electronic structure of $\\mathsf{C u-N}_{4}$ sites by integrating electron-deficient boron (B) or electron-rich phosphorus (P) heteroatoms into carbon substrate for PMS activation. The electrondepleted $C u-N_{4}/C-B$ is found to exhibit the most active oxidation capacity among the prepared $\\mathsf{C u-N}_{4}$ single-atom catalysts, which is at the top rankings of the Cu-based catalysts and is superior to most of the state-of-the-art heterogeneous Fenton-like catalysts. Conversely, the electron-enriched $C u-N_{4}/C-P$ induces a decrease in PMS activation. Both experimental results and theoretical simulations unravel that the long-range interaction with B atoms decreases the electronic density of Cu active sites and down-shifts the d-band center, and thereby optimizes the adsorption energy for PMS activation. This study provides an approach to finely control the electronic structure of $\\mathsf{C u-N}_{4}$ sites at the atomic level and is expected to guide the design of smart Fenton-like catalysts. \n\nsingle-atom catalysts electronic structure heteroatom-doped engineering reaction kinetics Fenton-like process \n\nThwea eFr nttroena-tlimkentprtoecehsnsolporgeisesnttsootnaeckolfe phe simstoestntporwgearnfiucl pollutants resulting from rapid economic development and unsustainable industrial and agricultural expansion (1–4). The peroxymonosulfate (PMS)-based advanced oxidation process has attracted extensive attention due to its high efficiency at a wide $\\mathrm{\\pH}$ range and ease of transport and storage (5–7). However, the sluggish kinetics of PMS activation during oxidation processes results in prohibitive costs and substantial chemical inputs (8, 9). Therefore, developing efficient catalysts to accelerate the reaction kinetics of PMS is crucial toward efficient catalytic oxidation of recalcitrant organics. Although homogeneous first-row transition metals $(\\mathrm{Co}^{2+},\\mathrm{Fe}^{2+},\\mathrm{Cu}^{2+}$ , and $\\mathrm{Mn}^{\\Sigma+}$ ) generally exhibit remarkable capabilities for PMS activation, they also suffer problems such as poor recyclability and accumulation of sludge (10–12). Comparatively, heterogeneous catalysts [e.g., transition metal oxides (13, 14), supported nanoparticles (NPs) (15, 16), and carbon-based materials (17, 18)] can be readily recovered and regenerated and are recognized as promising candidates for PMS activation. Nevertheless, the heterogeneity of NPs results in lower utilization efficiency of surface atoms (with $81.6\\%$ atoms buried and unavailable for 6-nm nickel NPs) and generally slower reaction kinetics than their homogeneous counterparts (19). \n\nSingle-atom catalysts (SACs) featuring utmost atomutilization efficiency and tunable electronic structure can break the limitations of heterogeneous catalysts in terms of the kinetics and catalytic activity (20, 21). Thus, SACs show a great potential to address the slow reaction kinetics of PMS for the Fenton-like process via maximizing the number of catalytic sites (22). For instance, a single-site Fe catalyst exhibited much faster reaction kinetics toward the degradation of phenol than the Fe NP catalyst, owing to the maximized atomic utilization (23). In addition, the synergetic effect between the atomic center and pyrrolic $\\mathbf{N}$ site of supports endowed Co SACs with dual reaction sites and high activity for PMS-based oxidation (24). To further accelerate the reaction kinetics of PMS, various strategies have been developed to improve the intrinsic activity of single atomic sites. By controlling the configurations of single atomic sites, PMS was more favorable for adsorption and activation on the $\\mathrm{CoN}_{2+2}$ site than the $\\mathrm{CoN_{4}}$ site (25). Previous work shows that manipulating the electronic structure of single sites plays an essential role in mediating the intrinsic activity (26, 27). It is highly desirable to gain insights into tuning the electronic structure of single-atom sites to achieve superior PMS activation kinetics. \n\n# Significance \n\nThe Fenton-like process based on peroxymonosulfate (PMS) has been widely investigated and recognized as a promising alternative in recent years for the degradation of persistent organic pollutants. However, the sluggish kinetics of PMS activation results in prohibitive costs and substantial chemical inputs, impeding its practical applications in water purification. This work demonstrates that tuning the electronic structure of single-atom sites at the atomic level is a powerful approach to achieve superior PMS activation kinetics. The Cu-based catalyst with the optimized electronic structure exhibits superior performance over most of the state-of-theart heterogeneous Fenton-like catalysts, while homogeneous Cu(II) shows very poor activity. This work provides insights into the electronic structure regulation of metal centers and structure–activity relationship at the atomic level. \n\nAuthor contributions: Y. Wang, H.-Q.Y., and Y. Wu designed research; X.Z. and M.-K.K. performed research; G.-X.H., C.C., K.L., and J.Y. contributed new reagents/ analytic tools; X.Z., M.-K.K., W.C., Y.Q., and F.L. analyzed data; and X.Z., Y. Wang, H.-Q.Y., and Y. Wu wrote the paper. \n\nThe authors declare no competing interest. \nThis article is a PNAS Direct Submission. \nThis article is distributed under Creative Commons Attribution-NonCommercialNoDerivatives License 4.0 (CC BY-NC-ND). \n$^1{\\times}.2$ . and M-K.K. contributed equally to this work. \n2To whom correspondence may be addressed. Email: yingwang@tongji.edu.cn, hqyu@ ustc.edu.cn, or yuenwu@ustc.edu.cn. \nThis article contains supporting information online at http://www.pnas.org/lookup/ suppl/doi:10.1073/pnas.2119492119/-/DCSupplemental. \nPublished February 14, 2022. \n\nRecent studies demonstrate that the electronic structure of isolated metal sites can be directly modulated by altering the coordinated atom species of the metal centers, favorable for expediting catalytic activity (28, 29). Notably, controlling the long-range interactions with suitable functionalities on the substrate of SACs can be a promising approach for tuning the electronic structure of metal centers (30). Indeed, the kinetic activity of single atomic sites was successfully tuned by the introduction of electron-withdrawing oxidized S groups or electron-donating thiophene-like S species into carbon supports of SACs (31). To this end, nonmetallic heteroatoms offer a substantial potential to serve as electron-withdrawing/donating functionalities on the carbon plane by chemical substitution (32, 33). Specifically, boron (B) with a vacant $2p_{z}$ orbital conjugating with the carbon $\\mathfrak{\\pi}$ system extracts the electrons, while phosphorus (P) with a readily available lone electron pair and low electronegativity is expected to donate electron in graphene (34, 35). With this strategy, incorporating particular heteroatoms $\\left(\\mathbf{B}/\\mathbf{P}\\right)$ into the substrate is a possible route to deplete/ enrich the electronic density of metal centers, tuning the electronic structure of single sites to promote PMS activation kinetics. \n\nIn this work, we designed a versatile strategy to systematically tune the electronic structure of $\\mathrm{Cu-N_{4}}$ sites by integrating specific heteroatoms $\\left(\\mathbf{B}/\\mathbf{P}\\right)$ into N-doped carbon substrates of Cu SACs. Subsequently, the effect of the controlled electronic features of Cu centers on facilitating PMS reaction kinetics was explored. Here, the heteroatom modified $\\mathrm{Cu-N_{4}}$ catalysts were first prepared by using a hydrogen-bonding-assisted pyrolysis approach. Synchrotron $\\mathbf{X}$ -ray adsorption spectroscopy and the projected density of states (PDOS) analysis verified the successful regulation of the electronic configuration of the $\\mathrm{Cu-N_{4}}$ SACs by different heteroatom functionalities. Furthermore, electron paramagnetic resonance and Raman spectra were employed to elucidate the PMS activation mechanism in the $\\mathrm{Cu{-}i N_{4}/C{-}B/P M S}$ system. This study opens an avenue to regulating the electronic structures of single active site of SACs to accelerate PMS activation kinetics for pollutant degradation. \n\n# Results and Discussion \n\nHeteroatom-Doped Engineering of Cu SACs. Single-atom $\\mathtt{C u}$ catalysts decorated with specific nonmetallic heteroatom $\\mathrm{(Cu-N_{4}/C-B}$ and $\\mathrm{Cu-N_{4}/C{-}P};$ ) were prepared through an H-bonding-assisted pyrolysis strategy to study the electronic structure effect of single $\\mathrm{Cu}$ sites for PMS activation, as illustrated in Fig. 1A. Typically, boric/phosphoric acid and carbamide were adopted as building units for self-assembled architecture by H-bonding interaction. The Cu-contained precursor was homogeneously mixed with the supramolecular assembly. SACs consisting of $\\mathrm{Cu-N_{4}}$ active sites anchored on heteroatom substituted carbon supports were obtained after pyrolyzing the mixed powder under an Ar atmosphere. The control sample (denoted as $\\mathrm{Cu-N_{4}/C)}$ without heteroatom was also prepared through a similar procedure but with some modifications (see Materials and Methods). \n\nThe transmission electron microscopy (TEM) images illustrate that $\\mathrm{Cu-N_{4}/C{-}B}$ displays a thin graphene-like layered structure, without obvious agglomerates of $\\mathtt{C u}$ nanoparticles (SI Appendix, Fig. S1 $A$ and $B$ ). As revealed by $S I$ Appendix, Fig. $S1D$ , the ring-like selected-area electron diffraction (SAED) pattern of $\\mathrm{Cu-N_{4}/C-B}$ excludes the existence of crystalline Cu. The energy-dispersive spectroscopy (EDS) mapping images from Fig. $1B$ show that Cu, B, N, and C are distributed uniformly across the entire architecture. To investigate the dispersion properties of Cu species at the atomic level, the aberration-corrected highangle dark-field scanning TEM (AC HAADF-STEM) measurement was carried out. As shown in Fig. $_{1\\ C}$ and $D$ and $S I$ Appendix, Fig. S2, the single bright dots corresponding to isolated $\\mathtt{C u}$ atoms can be clearly distinguished from the heteroatom-doped carbon matrix. The atomic dispersion of $\\mathrm{cu}$ in $\\mathrm{Cu-N_{4}/C{-}B}$ is further confirmed by the atom-overlapping Gaussian-function fitting mapping and analysis of intensity profile (Fig. $1E$ ). The morphologies of $\\mathrm{Cu-N_{4}/C}$ and $\\mathrm{Cu-N_{4}/C-P}$ were also checked, revealing a similar thin graphene-like layered structure (SI Appendix, Figs. S3A and S4A). Additionally, the EDS mappings of $\\mathrm{Cu-N_{4}/C-P}$ reveal the presence of Cu, C, N, and P elements (SI Appendix, Fig. $S4~C{-}F_{.}$ ). \n\nThe powder X-ray diffraction pattern of $\\mathrm{Cu-N_{4}/C-B}$ exhibits only one broad peak at approximately $25^{\\circ}$ indexed to the (002) plane of the graphitic carbon (36), which is similar to these of $\\mathrm{\\bar{C}u-N_{4}/C}$ and $\\mathrm{\\bar{C}u{-}N_{4}/C{-}P}$ (SI Appendix, Fig. S5). No typical peaks ascribed to crystalline Cu species are observed, which is consistent with the observation from the SAED pattern. Moreover, the Raman spectra of the $\\mathrm{Cu-N_{4}}$ catalysts reveal the characteristic D and G bands of conductive carbon materials with similar calculated $I_{\\mathrm{D}}/I_{\\mathrm{G}}$ values (SI Appendix, Fig. S6). Heteroatom modified SACs exhibit slightly larger values than the primary sample, indicating the formation of more defects and disordered structures in $\\mathrm{Cu-N_{4}/C-B}$ and $\\mathrm{Cu-N_{4}/C{-}P}.$ ${\\bf N}_{2}$ physisorption analysis confirms that all the catalysts have comparable BET surface areas and pore sizes (SI Appendix, Fig. S7). Furthermore, the $\\mathrm{Cu}$ loadings, measured by inductively coupled plasma atomic emission spectroscopy, are close to each other in the $\\mathrm{Cu-N_{4}}$ catalysts (SI Appendix, Table S1). Considering all the above findings, there are no obvious differences in carbon crystallinity, surface area, or total $\\mathrm{Cu}$ content for $\\mathrm{Cu-N_{4}/C}$ , $\\mathrm{Cu-N_{4}/C-B}$ , and ${\\mathrm{Cu-N}}_{4}/{\\mathrm{C}}{\\mathrm{-P}},$ which ensures that the effect of heteroatom decoration on the electronic structure of the $\\mathrm{Cu-N_{4}}$ catalysts could be investigated independently. \n\nAtomic Structure and Chemical State Analysis of Cu SACs. Synchrotron $\\mathbf{X}$ -ray absorption spectra were used to clarify the fine structures of $\\mathrm{Cu-N_{4}}$ catalysts. As shown in Fig. 2A, the Fourier transform extended X-ray absorption fine structure (FTEXAFS) spectra of the $\\mathrm{Cu-N_{4}}$ catalysts all exhibit one major peak at about $1.5\\mathrm{\\AA}$ , which can be attributed to $\\mathrm{{Cu-N}}$ coordination (37). In contrast to $\\mathrm{Cu}$ foil and $\\mathtt{C u O}$ , the absence of a metallic Cu-Cu scattering path $(2.2\\mathring\\mathrm{\\textrm{A}})$ in the spectra of $\\mathrm{Cu-N_{4}}$ catalysts further verifies the atomic dispersion of $\\mathrm{Cu}$ . To better investigate the atomic configuration of $\\mathrm{Cu-N_{4}}$ catalysts, wavelet transform (WT) analysis was performed, which can provide powerful resolution in both $\\ensuremath{\\mathbf{R}}$ and $\\mathbf{k}$ spaces and discriminate the backscattering atoms. In line with the FT-EXAFS analysis, the WT contour plots of $\\mathrm{Cu-N_{4}}$ catalysts exhibit only one intensity maximum at $4.8\\mathrm{~\\AA~}^{-1}$ , which is assigned to the $\\mathrm{Cu-N}$ bond (Fig. $2\\ G\\mathrm{-}I$ ). For comparison, both $\\mathrm{Cu}$ foil and $\\mathrm{CuO}$ counterparts show higher intensity maxima at 7.6 and $6.8\\mathring\\mathrm{~A~}^{-1}$ , corresponding to $\\mathrm{{Cu-Cu}}$ and $\\mathrm{\\bar{C}u-O-C u}$ coordination, respectively (Fig. 2 $E$ and $F$ ). We performed EXAFS fitting to analyze the structural parameters of $\\mathrm{Cu}$ atoms ( $S I$ Appendix, Fig. $S\\dot{8}A{-}F_{\\cdot}$ ), and the corresponding parameters are listed in SI Appendix, Table S2. It is observed that the best-fit EXAFS results match quite well with the experiment spectra. Based on the results, $\\bar{\\mathrm{Cu}}$ species in three single-atom samples exist as the form of isolated $\\mathrm{Cu-N_{4}}$ sites, as illustrated by the local atomic structure model (insets in $S I$ Appendix, Fig. $S8\\ B$ , $D$ , and $F$ ). The above results strongly suggest that $\\mathtt{C u}$ atoms are atomically dispersed in $\\mathrm{Cu-N_{4}/C}$ , $\\mathrm{\\bar{C}u-N_{4}\\bar{/}C-B}$ , and $\\mathrm{Cu-N_{4}/C-P_{5}}$ without the existence of metal-derived crystalline structures. \n\nThe electronic structure of the prepared catalysts was first probed by soft $\\mathbf{X}$ -ray absorption near-edge structure (XANES) analysis. As revealed in Fig. $2B$ , the N K-edge spectra of $\\mathrm{Cu-N_{4}}$ catalysts are dominated by three well-resolved resonance peaks attributed to the pyridinic $\\pi^{*}$ (N1), graphitic $\\pi^{*}$ (N2), and $\\mathrm{C-N}$ $\\upsigma^{*}$ (N3) transitions, respectively (38). Notably, the typical peaks of $\\mathrm{Cu-N_{4}}$ catalyst shift to lower energy with $\\mathrm{~\\bf~P~}$ incorporation. \n\n![](images/6b5ed53907d78e43aeca95ef257307805b59d4b3293c85214fe6849280985fdc.jpg) \nFig. 1. Synthetic illustration and morphology characterizations. (A) Schematic of the preparation strategy for $C u-N_{4}/C-B$ and $\\mathsf{C u-N_{4}/C-P}$ . The color bar indicates the electronic density of $C u-N_{4}$ site, electro-rich (blue) and electro-poor (red). (B) HAADF-STEM image and the corresponding EDS mapping images of $C u-N_{4}/C-B$ . (C) AC HAADF-STEM image and (D) enlarged intensity image of $C u-N_{4}/C-B$ . (E) Atom-overlapping Gaussian-function-fitting mapping of the square from $D$ , intensity profile along X–Y in $D$ . \n\nA similar shift, but in the opposite direction (i.e., to higher energy), was observed in the case of B-decorated $\\mathrm{Cu-N_{4}}$ catalyst. The observed changes in the soft XANES spectra indicate a variation in the chemical environment around nitrogen atoms upon heteroatom doping (39, 40), strongly implying a possible change of electronic structure of Cu metal centers. Meanwhile, the B and P K-edge spectra confirm that heteroatoms $\\left(\\mathbf{B}/\\mathbf{P}\\right)$ have been successfully doped into carbon substrate (SI Appendix, Fig. S9). \n\nThe Cu K-edge XANES spectra of $\\mathrm{Cu-N_{4}}$ catalysts were employed to survey the chemical state of Cu. The energy absorption thresholds of the three $\\mathrm{Cu-N_{4}}$ catalysts are situated between that of $\\mathrm{Cu}$ foil and $\\mathtt{C u O}$ , indicating the atomically dispersed $\\mathrm{Cu}$ atoms carry partially positive charges (Fig. 2C). Of particular note is that the valence state of single $\\mathtt{C u}$ sites was found to rank in the order $2>\\mathrm{Cu{-}N_{4}/C{-}B>\\tilde{C u{-}}N_{4}/C>C u{-}N_{4}/}$ $\\mathrm{C}{\\cdot}P>0$ , which means the electronic properties of the $\\mathrm{Cu-N_{4}}$ sites can be tailored by controlling the heteroatom species in carbon substrate. This observation also shows a good agreement with the $\\mathrm{Cu}2p$ high-resolution $\\mathbf{\\boldsymbol{X}}$ -ray photon spectroscopy (XPS) spectra. As shown in Fig. $2D$ , the fitted ratios of $\\mathrm{cu}$ (0) to Cu $(2+)$ valence state in three $\\mathrm{Cu-N_{4}}$ catalysts show the same trend as the $\\mathtt{C u}$ K-edge XANES results, indicating that $\\mathrm{Cu-N_{4}/C-B}$ possesses a higher chemical valence compared with $\\mathrm{Cu-N_{4}/C}$ and ${\\mathrm{Cu-N_{4}/C{\\cdot}P}}.$ Moreover, N 1s XPS spectra of $\\mathrm{Cu-N_{4}}$ catalysts exhibit three characteristic peaks derived from pyridinic $\\mathbf{N}$ , pyrrolic N, and graphitic $\\mathbf{N}$ , respectively (SI Appendix, Fig. S11) (41, 42). These $\\mathbf{N}$ species exhibit different composition distributions and consequently are associated with the heteroatom incorporation. The successful modification of $\\mathrm{Cu-N_{4}}$ catalysts by heteroatoms was further confirmed by B 1s and $\\boldsymbol{\\textbf{P}}2p$ XPS spectra of $\\mathrm{Cu-N_{4}/C{-}B}$ and $\\mathrm{Cu-N_{4}/C-P_{5}}$ , respectively. \n\nRegulation of Cu Electronic Structure for PMS Activation. To assess the effect of heteroatom-induced electronic structure regulation of $\\mathtt{C u}$ centers on tuning PMS activation activity, the Fentonlike catalytic performance was evaluated for bisphenol A (BPA) removal. As shown in Fig. $3A$ , the pristine $\\bar{\\mathrm{Cu-N_{4}/C}}$ catalyst achieved less than $60\\%$ degradation of BPA in $5\\mathrm{{min}}$ . Remarkably, the electron-depleted $\\mathrm{Cu-N_{4}}$ sites drastically boosted the activation of PMS, with BPA almost completely decomposed using $\\mathrm{Cu-N_{4}/C{-}B}$ as the catalyst. However, only about $11\\%$ BPA was degraded by PMS when $\\mathrm{Cu-N_{4}/C{-}P}$ with electronenriched Cu centers was employed. In order to provide a better comparison of the catalytic performance, the BPA removal kinetics were then fitted by the pseudo-first-order reactions. It is worth mentioning that the apparent rate constant $(k)$ of Cu$\\mathrm{N_{4}/C-B}$ was ${\\sim}70\\$ and 5.5 times that of $\\mathrm{Cu-N_{4}/C-P}$ and $\\mathrm{Cu-N_{4}/C,}$ respectively (Fig. 3B), being one of the most active Cu-based catalysts for PMS activation (SI Appendix, Fig. S18 and Table S3). Homogeneous $\\mathtt{C u}$ catalyst $\\mathrm{{[Cu(II)]}}$ showed very poor activity for the activation of PMS $S I$ Appendix, Fig. S20). Furthermore, the Fenton-like performance of $\\mathrm{Cu-N_{4}/C-B}$ is superior to most of the state-of-the-art heterogeneous catalysts (SI Appendix, Fig. S19 and Table S4). In addition, the comparison with the BPA degradation kinetic curve of BCN without $\\mathtt{C u}$ active centers reveals that the Fenton-like activity was mainly ascribed to $\\mathrm{Cu-N_{4}}$ sites (Fig. 3C). \n\nThe dynamic enhancement in the oxidation performance of $\\mathrm{Cu-N_{4}/C{\\cdot}B}$ indicates the critical role of electronic structure of Cu sites for catalytic PMS activation. Specifically, the reaction rate constant for the synthesized $\\mathrm{Cu-N_{4}}$ catalysts was found to correlate well with the $\\mathtt{C u}$ valence state calculated from XPS results (Fig. $3D$ ). The B modified $\\mathtt{C u}$ SACs with a relatively high valence state led to a higher value of $k$ in BPA removal. $\\mathrm{Cu-N_{4}/C-B}$ catalyst with optimal B content showed the best activity for pollutant oxidation. However, the incorporation of P heteroatom into the substrates of $\\mathrm{Cu}$ SACs enriched the electronic density of $\\mathtt{C u}$ centers (relatively low valence state), resulting in loss of degradation activity. In this regard, electronic structure regulation of metal centers can be an approach to enhance PMS activation kinetics. Moreover, $\\mathrm{Cu-N_{4}/C-B}$ exhibited satisfying catalytic performance over a broad $\\mathrm{\\pH}$ range (Fig. $3E$ ), which is beneficial for practical treatment of wastewater. \n\n![](images/ab2164744e45a5340046a8af57d73279b546d50e2ff3d51f10b6963f955bbc8c.jpg) \nFig. 2. Atomic local structure and chemical state of $C u\\mathrm{-}N_{4}$ catalysts. (A) Cu K-edge FT-EXAFS spectra of $C u-N_{4}/C-B$ , $C u-N_{4}/C-P.$ ${C u-N_{4}}/{C_{1}}$ and reference samples. (B) N K-edge XANES spectra of the $\\mathsf{C u-N}_{4}$ catalysts. (C) The normalized Cu K-edge XANES spectra of the $C u\\mathrm{-}N_{4}$ catalysts and the references (Cu foil and CuO). $(D)$ Cu $2p$ XPS spectra of $C u-N_{4}/C-B$ , $C u-N_{4}/C-P,$ and $C u-N_{4}/C$ . (E–I) WT-EXAFS plots of Cu foil, CuO, $C u-N_{4}/C-B$ , $C u-N_{4}/C_{1}$ and $C u{\\cdot}N_{4}/C{\\cdot}P,$ respectively. \n\nTo identify the reactive oxygen species (ROS) generated during PMS activation, electron paramagnetic resonance (EPR) experiments were conducted. As shown in Fig. $3F.$ , the signals for the hydroxyl radical $(\\mathrm{HO^{\\bullet}})$ and sulfate radical $(\\mathrm{SO}_{4}^{\\bullet-})$ were barely detectable in the $\\mathrm{Cu-N_{4}/C-B/P M S}$ system. Specifically, the characteristic triplet signals of $\\mathrm{TMP\\mathrm{\\mathrm{^1O_{2}}}}$ adducts for the three $\\mathrm{Cu-N_{4}}$ catalysts exhibited enhanced intensity compared to PMS (SI Appendix, Fig. S24), implying the existence of singlet oxygen $(^{1}\\dot{\\mathrm{O}_{2}})$ during PMS activation (43). The EPR analysis suggested that the nonradical ROS was the dominant oxidant in the $\\mathrm{Cu-N_{4}/C-B/P M S}$ system. Radical quenching experiments were carried out to further identify the active species during PMS activation. As shown in Fig. $3G$ , excessive ethanol (EtOH) served as radical scavengers for $\\mathrm{{so_{4}}^{\\bullet-}/{^\\bullet}\\mathrm{{o}H}}$ (18, 44), with slight inhibition on BPA removal, indicating that both $\\mathrm{SO_{4}}^{\\bullet-}$ and $\\mathrm{\\bar{\\cdot}_{O H}}$ contributed little to BPA degradation. Both benzoquinone (BQ) and sodium azide $\\left({\\bf N a N}_{3}\\right)$ demonstrated noticeable inhibition effect on BPA degradation, suggesting the potential role of ${}^{1}{\\bf O}_{2}$ (45, 46). However, the solvent exchange 0 $\\mathrm{~\\cal~H}_{2}\\mathrm{O}$ to ${\\bf D}_{2}\\mathrm{O}_{\\it4}^{\\prime}$ ) did not result in an acceleration of BPA decomposition $S I$ Appendix, Fig. S26A). This contradicts the previous findings that $\\mathbf{D}_{2}\\mathbf{O}$ is a promoter for singlet oxygenation because the lifetime of ${}^{1}{\\bf O}_{2}$ in ${\\bf D}_{2}\\mathrm{O}$ is extended up to 10 times (47, 48). Thus, ${}^{1}{\\bf O}_{2}$ was not primarily responsible for BPA degradation under such conditions, indicating the existence of a secondary nonradical PMS activation pathway (49, 50). \n\nIn fact, BQ and ${\\bf N a N}_{3}$ can also be oxidized by the activated PMS complex via a nonradical pathway (17). Therefore, potassium dichromate $(\\mathbf{K}_{2}\\mathbf{Cr}_{2}\\mathbf{O}_{7})$ was alternatively employed as an electron scavenger to investigate the electron transfer process. BPA decomposition was barely inhibited in the $\\mathrm{Cu-N_{4}/C\\mathrm{\\bar{-}B/P M S}}$ upon $\\ensuremath{\\mathrm{K}}_{2}\\ensuremath{\\mathrm{Cr}}_{2}\\ensuremath{\\mathrm{O}}_{7}$ addition (SI Appendix, Fig. S26B), suggesting that the system was likely based on direct electron transfer on the catalyst surface other than in solution phase (51). Moreover, chronoamperometry measurements were performed (Fig. $3H$ ) to verify PMS activation with $\\mathrm{Cu-N_{4}}$ catalysts. The injection of PMS caused distinct current jumps for the three Cu SACs, which verifies electron transfer in the Cu SACs/PMS systems and most likely from $\\mathtt{C u}$ SACs to PMS. Impressively, $\\mathrm{Cu-N_{4}/C-B}$ exhibited the maximum intensity of current jump, demonstrating efficient electron transfer between $\\mathrm{Cu-N_{4}/C-B}$ and PMS. It is well documented that high-valent intermediates are formed through heterolytically cleaving the peroxide $_{0-0}$ bond for transition metal catalyzed systems (52, 53). In this case, after electron transfer from $\\mathrm{Cu-N_{4}/C-B}$ to PMS, high-valent copper-oxo species $\\mathrm{[Cu(III)\\mathrm{-OH]}}$ were generated by heterolytic cleavage of the $_{0-0}$ bond and served as key intermediates in PMS activation. Furthermore, the subsequent injection of BPA led to the opposite direction of current change, implying electron transfer from BPA to Cu SACs, which resulted in BPA degradation. \n\n![](images/b75e0480e37f586c6be62dd0809cc9f21a3a4a5927c49af6034f83bf841764f9.jpg) \nFig. 3. Fenton-like performance for $C u\\mathrm{-}N_{4}$ catalysts. (A) Kinetics of BPA degradation by PMS catalyzed by $C u-N_{4}/C-B$ , ${C u-N_{4}}/{C_{1}},$ and $C u-N_{4}/C-P$ within 5 min. (B) Comparison of the rate constant of BPA removal by the three $\\mathsf{C u-N}_{4}$ catalysts. (C) Kinetics of BPA degradation by PMS catalyzed by $C u-N_{4}/C-B$ and BCN. $(D)$ The relationship between the rate constant and the $\\mathsf{c u}$ valence state in the prepared $C u\\mathrm{-}N_{4}$ catalysts. $(E)$ Influence of pH on BPA degradation in the $\\mathsf{C u-N_{4}/C-B/P M S}$ system. (F) EPR spectra in the activation of PMS in the presence of $C u-N_{4}/C-B$ catalyst. (G) Comparison of degradation kinetics under different quenching conditions. $(H)$ Current responses after the sequential injection of PMS and BPA at the $C u-N_{4}/C-B$ , ${C u-N_{4}/C_{,}}$ , and $C u-N_{4}/C-P$ working electrodes. $(I)$ Raman spectra of the Cu- ${\\bf\\cdot N_{4}}/{\\sf C}$ -B/PMS and ${C u-N_{4}}/{C}/{P M S}$ systems (ABS: pH buffer). Reaction condition: $[\\mathsf{B P A}]=20\\mathsf{m}\\mathsf{g}\\cdot\\mathsf{L}^{-1}$ , $[\\mathsf{P M S}]=0.2\\ \\mathsf{g}.\\mathsf{L}^{-1}$ , catalyst $=0.1\\ \\mathfrak{g}{\\cdot}\\mathsf{L}^{-1}$ , ${\\sf T}=298{\\sf K},$ initial solution $\\mathsf{p H}=6.0$ . \n\nTo further verify the formation of high-valent copper during the PMS activation, Raman spectra were collected. As shown in \n\nFig. 3I, the new peak around $614~\\mathrm{cm}^{-1}$ in the $\\mathrm{Cu-N_{4}/C-B/P M S}$ system was likely due to high-valent copper-oxo species, because this is a characteristic $\\mathrm{Cu-\\bar{O}}$ stretching vibration band of a metastable $\\mathrm{{Cu}(I I I)}$ (7, 54). Moreover, this featured peak for $\\mathrm{{Cu}(I I I)}$ - OH was also observed in the $\\mathrm{Cu-N_{4}/C/P M S}$ system, further confirming the presence of high-valent copper intermediate during PMS activation. The peak at $654~\\mathrm{cm}^{-1}$ was associated with the ABS buffer’s contribution. Moreover, the PMS decomposition rate was basically the same in the presence and absence of BPA, confirming that PMS was decomposed after being activated by $\\mathrm{Cu-N_{4}/C-B}$ . Therefore, the degradation of BPA in $\\mathrm{\\bar{Cu}{-}N_{4}/C{-}B/}$ PMS system displayed a nonradical pathway based on highvalent copper formation (SI Appendix, Fig. S31). First, PMS was adsorbed and activated on Cu sites, forming $\\mathrm{Cu(III)\\mathrm{-OH}}$ intermediate. Subsequently, the pollutant BPA was adsorbed and attacked by the reactive complex. Afterward, $\\mathrm{Cu-N_{4}}$ sites were reactivated after the desorption of the oxidized BPA. \n\nTheoretical Study of Electronic Structure of Cu SACs. To gain a fundamental understanding of the heteroatom-doped engineering effect on $\\mathrm{Cu-N_{4}}$ SACs, density functional theory (DFT) \n\n![](images/835a962a96d511985dee5a87a795706c8d29be1c1b100db5d8fc8fbaa2141436.jpg) \nFig. 4. PDOS and charge density differences analyses. (A) PDOS of Cu atom, heteroatoms in the substrate, and oxygen of PMS adsorbed on the Cu center (EF is marked in each graph with the black dashed line). (B) The calculated electron density difference diagrams of $C u-N_{4}/C-B$ with PMS adsorbed on the $\\mathsf{C u-N}_{4}$ site. (C) The adsorption energy values of PMS on $C u\\mathrm{-}N_{4}/C\\cdot B$ , $C u-N_{4}/C$ and $C u-N_{4}/C-P$ catalysts. $(D)$ Relationship between the d-band center and adsorption energy and reaction rate constant for three Cu- ${\\bf\\cdot N_{4}}$ samples. (E–G) The optimized structure and the corresponding electron density plots of $C u\\mathrm{-}N_{4}/C\\mathrm{-}B$ , ${C u-N_{4}/C_{,}}$ and $C u\\mathrm{-N}_{4}/C\\cdot P$ catalysts. \n\ncalculations were performed to shed light on regulating the electronic structure of $\\mathtt{C u}$ active sites for PMS activation. As shown in Fig. 4A, the PDOS for the Cu centers, heteroatoms in the substrate and oxygen of PMS adsorbed on the $\\mathrm{Cu}$ sites were calculated. In apparent contrast to primary $\\mathrm{Cu-N_{4}/C}$ , the PDOS of $\\mathtt{C u}$ sites in $\\mathrm{\\bar{C}u-N_{4}/C-B}$ displays a negative shift, indicating a decrease in d-band center. Comparatively, the PDOS of Cu atoms in $\\mathrm{Cu-N_{4}/C{-}P}$ moves toward the opposite direction, with an increased d-band center (SI Appendix, Fig. S33). Additionally, the PDOS for PMS adsorbed on Cu centers of the three SACs shows that $\\mathrm{Cu-N_{4}/C{-}B}$ has a relatively weak interaction with PMS compared to $\\mathrm{Cu-N_{4}/C}$ (SI Appendix, Fig. S35). On the contrary, the interaction between $\\mathrm{Cu-N_{4}/C-P}$ and PMS is pretty strong. As evidenced from the charge density analysis (Fig. $^{4B}$ and $S I$ Appendix, Fig. S36), electron transfer between PMS and $\\mathrm{Cu-N_{4}}$ is observed, suggesting the chemisorption of PMS on all the Cu SACs. \n\nThe corresponding adsorption energies $\\left(\\mathrm{{E}_{\\mathrm{{ads}}}}\\right)$ were further calculated, as shown in Fig. 4C. Consistent with the PDOS analysis, $\\mathrm{Cu-N_{4}/C-B}$ possesses a small adsorption energy, while $\\mathrm{Cu-N_{4}/C}$ and $\\mathrm{Cu-N_{4}/C{-}P}$ display strong binding for PMS. It is inferred that $\\mathrm{Cu-N_{4}/C-B}$ catalyst corresponds to a moderate adsorption energy for PMS activation, which results in its superior Fenton-like activity (Fig. 4D). On the other hand, both Cu$\\mathrm{N}_{4}/\\mathrm{C}$ and $\\mathrm{Cu-N_{4}/C-P}$ might cause poison of the active sites. Moreover, Bader charge analysis (Fig. 4 $E{-}G{\\mathrm{\\backslash}}$ shows that the incorporation of heteroatoms has appreciable influence on electron distribution, especially for the $\\mathtt{C u}$ centers. As revealed in $S I$ Appendix, Fig. S37, the calculated $\\mathrm{Cu}$ valence state in $\\mathrm{Cu}.$ $\\mathrm{N}_{4}/\\mathrm{C}{\\cdot}\\mathrm{B}$ increases markedly in contrast to that of $\\mathrm{Cu-N_{4}/C}_{\\mathrm{i}}$ , while $\\mathrm{Cu-N_{4}/C{-}P}$ displays the opposite behavior. The trend of Cu valence state is qualitatively consistent with the XANES and XPS results. Therefore, heteroatom functionalization can serve as an effective strategy to optimize the electronic structure of $\\mathrm{Cu-N_{4}}$ sites, boosting the activation of PMS. \n\n# Conclusions \n\nIn summary, we systematically investigated the modulation of the electronic structure of $\\mathrm{Cu-N_{4}}$ catalytic sites by heteroatomdoped engineering for Fenton-like oxidation at the atomic level. A series of atomically dispersed $\\mathrm{Cu-N_{4}}$ catalysts were successfully prepared by a hydrogen-bonding-assisted pyrolysis strategy. Both DFT calculations and experimental investigations indicate that the electronic density of the active $\\mathtt{C u}$ centers is well controlled via the long-range interaction with heteroatoms. The modified catalyst can readily achieve high improvement of PMS activation kinetics. Importantly, the electron-depleted Cu$\\mathrm{N_{4}/C{-}B}$ catalyst induces optimized adsorption energy for PMS with an increase of oxidation activity, whereas electron-rich Cu$\\bf N_{4}/C$ and $\\mathrm{Cu-N_{4}/C-P}$ display strong binding of PMS, causing the poison of active sites. This work would provide a deep insight into the electronic structure regulation of metal centers and structure–activity relationship at the atomic level, which could be helpful to develop advanced Fenton-like catalysts. \n\n# Materials and Methods \n\nMaterials. Copper (II) acetate $\\begin{array}{r}{[\\mathsf{C u}(\\mathsf{O A c})_{2}],~2,2^{\\prime}:6^{\\prime},2^{\\prime\\prime}.}\\end{array}$ -terpyridine, boric acid, phosphoric acid, glucose, and urea were purchased from Sinopharm Chemical Reagent Beijing Co., Ltd. BPA and polyether F127 were obtained from SigmaAldrich Chemical Co., Ltd. $\\mathsf{K H S O}_{5}.0.5\\mathsf{K H S O}_{4}.0.5\\mathsf{K}_{2}\\mathsf{S O}_{4}$ (PMS), 5,5-dimethyl-1- pyrroline- ${\\bf\\nabla}\\cdot N\\cdot$ -oxide (DMPO), and 2,2,6,6-tetramethyl-4-piperidinol (TMP) were bought from Alfa Aesar Co. Inc. All the chemical reagents were used as received without any other purification. \n\nSynthesis of $\\mathbf{Cu-N_{4}/C-B}$ Catalysts. In a typical synthesis of $C u-N_{4}/C-B$ catalyst, first the Cu precursor was prepared by mixing ${\\mathsf{C u}}(\\mathsf{O A c})_{2}$ (1 mmol) and $2,2^{\\prime}{:}6^{\\prime},2^{\\prime\\prime}$ -terpyridine $(1~\\mathrm{mmol})$ ) in $10~\\mathrm{mL}$ of tetrahydrofuran under stirring for $24~\\mathsf{h}$ . The resultant precipitate was centrifuged, washed, and vacuum-dried. Subsequently, 50 mmol of carbamide and 1.6 mmol of boric acid were dispersed in $10~\\mathrm{mL}$ deionized (DI) water under ultrasonication for 15 min. Then, $0.034\\:\\mathrm{mmol}$ of Cu-contained precursor and 2 mmol of F127 in ethanol $(10~\\mathrm{mL})$ were injected into the above solution and the resulting mixture was stirred for 4 h. Then, the H-bonded assemblies were obtained by rotary evaporation of the solvent. Afterward, the sample were pyrolyzed in the Ar atmosphere, maintaining $800^{\\circ}\\mathsf C$ for $2h$ at a heating rate of $5^{\\circ}{\\mathsf{C}}/{\\mathsf{m i n}}$ . After being naturally cooled to room temperature, a black powder sample can be obtained. The Cu SACs with B content gradient were prepared by a similar procedure except for changing the amount of boric acid to 0.8 and $2.4\\:\\mathrm{mmol}$ . They are denoted as $\\mathsf{C u-N}_{4}/\\mathsf{C}-\\mathsf{B}\\cdot0.8$ and Cu-N4/C-B-2.4, respectively. \n\nSynthesis of BCN. For the BCN catalyst preparation, 50 mmol of carbamide and 1.6 mmol of boric acid were dispersed in $10~\\mathrm{mL}$ DI water under ultrasonication for 15 min, then 2 mmol of F127 in ethanol $(10~\\mathrm{mL})$ were injected into the above solution and the resulting mixture was stirred for $4\\ h$ . Then, the H-bonded assemblies were obtained by rotary evaporation of the solvent. Afterward, the sample was pyrolyzed in the Ar atmosphere, maintaining $800^{\\circ}\\mathsf C$ for $2h$ at a heating rate of $5^{\\circ}{\\mathsf{C}}/{\\mathsf{m i n}}$ . After being naturally cooled to room temperature, a black powder sample can be obtained. \n\nSynthesis of $C u\\mathrm{-}N_{4}/\\ C$ Catalysts. Typically, for the synthesis of $C u-N_{4}/C$ catalyst, $50\\ \\mathrm{mmol}$ of carbamide and 0.56 mmol glucose were dispersed in $10~\\mathrm{mL}$ DI water under ultrasonication for 15 min. Then, 0.034 mmol of Cu-contained precursor and $2\\:\\mathrm{mmol}$ of F127 in ethanol $(10~\\mathrm{mL})$ were injected into the above solution and the resulting mixture was stirred for $4\\ h$ . Then, the H-bonded assemblies were obtained by rotary evaporation of the solvent. Afterward, the sample were pyrolyzed in the Ar atmosphere, maintaining $800^{\\circ}\\mathsf C$ for $2h$ at a heating rate of $5^{\\circ}{\\mathsf{C}}/{\\mathsf{m i n}}$ . After being naturally cooled to room temperature, a black powder sample can be obtained. \n\nSynthesis of $C u-N_{4}/C-P$ Catalysts. In brief, for the synthesis of $C u-N_{4}/C-P$ catalyst, 50 mmol of carbamide and $100~\\upmu\\upiota$ $\\cdot1.6\\ \\mathrm{mmol})$ phosphoric acid were dispersed in $10~\\mathrm{{mL}}$ DI water under ultrasonication for 15 min. Then, 0.034 \n\n1. D. Jassby, T. Y. Cath, H. Buisson, The role of nanotechnology in industrial water treatment. Nat. Nanotechnol. 13, 670–672 (2018). 2. P. Westerhoff, T. Boyer, K. Linden, Emerging water technologies: Global pressures force innovation toward drinking water availability and quality. Acc. Chem. Res. 52, 1146–1147 (2019). 3. J. Wang, S. Li, Q. Qin, C. Peng, Sustainable and feasible reagent-free electro-Fenton via sequential dual-cathode electrocatalysis. Proc. Natl. Acad. Sci. U.S.A. 118, e2108573118 (2021). \n4. Z. Yang, J. Qian, A. Yu, B. Pan, Singlet oxygen mediated iron-based Fenton-like catalysis under nanoconfinement. Proc. Natl. Acad. Sci. U.S.A. 116, 6659–6664 (2019). \n5. Z.-Y. Guo et al., Mn O covalency governs the intrinsic activity of Co-Mn spinel oxides for boosted peroxymonosulfate activation. Angew. Chem. Int. Ed. Engl. 60, 274–280 (2021). 6. A. Jawad et al., Tuning of persulfate activation from a free radical to a nonradical pathway through the incorporation of non-redox magnesium oxide. Environ. Sci. Technol. 54, 2476–2488 (2020). \n7. L. Wang et al., Trace cupric species triggered decomposition of peroxymonosulfate and degradation of organic pollutants: Cu(III) being the primary and selective intermediate oxidant. Environ. Sci. Technol. 54, 4686–4694 (2020). 8. G. P. Anipsitakis, D. D. Dionysiou, Radical generation by the interaction of transition metals with common oxidants. Environ. Sci. Technol. 38, 3705–3712 (2004). 9. J. Wang, S. Wang, Activation of persulfate (PS) and peroxymonosulfate (PMS) and application for the degradation of emerging contaminants. Chem. Eng. J. 334, 1502–1517 (2018). \n10. P. Hu, M. Long, Cobalt-catalyzed sulfate radical-based advanced oxidation: A review on heterogeneous catalysts and applications. Appl. Catal. B 181, 103–117 (2016). \n11. L. W. Matzek, K. E. Carter, Activated persulfate for organic chemical degradation: A review. Chemosphere 151, 178–188 (2016). \n12. S. Wacławek et al., Chemistry of persulfates in water and wastewater treatment: A review. Chem. Eng. J. 330, 44–62 (2017). \n13. G. P. Anipsitakis, E. Stathatos, D. D. Dionysiou, Heterogeneous activation of oxone using $\\mathsf{C o}_{3}\\mathsf{O}_{4}.$ . J. Phys. Chem. B 109, 13052–13055 (2005). \n14. T. Zhang, H. Zhu, J.-P. Croue\u0001, Production of sulfate radical from peroxymonosulfate induced by a magnetically separable $\\mathsf{C u F e}_{2}\\mathsf{O}_{4}$ spinel in water: Efficiency, stability, and mechanism. Environ. Sci. Technol. 47, 2784–2791 (2013). \n15. X. Li, A. I. Rykov, B. Zhang, Y. Zhang, J. Wang, Graphene encapsulated $\\mathsf{F e}_{\\mathsf{x}}\\mathsf{C o}_{\\mathsf{y}}$ nanocages derived from metal–organic frameworks as efficient activators for peroxymonosulfate. Catal. Sci. Technol. 6, 7486–7494 (2016). \n16. S. Yang et al., MOF-templated synthesis of $\\mathsf{C o F e}_{2}\\mathsf{O}_{4}$ nanocrystals and its coupling with peroxymonosulfate for degradation of bisphenol A. Chem. Eng. J. 353, 329–339 (2018). \n\nmmol of Cu-contained precursor and 2 mmol of F127 in ethanol $(10~\\mathsf{m L})$ were injected into the above solution and the resulting mixture was stirred for $4\\ h$ . Then, the H-bonded assemblies were obtained by rotary evaporation of the solvent. Afterward, the sample were pyrolyzed in the Ar atmosphere, maintaining $800^{\\circ}\\mathsf C$ for $^\\textrm{\\scriptsize2h}$ at a heating rate of $5^{\\circ}{\\mathsf{C}}/{\\mathsf{m i n}}$ . After being naturally cooled to room temperature, a black powder sample can be obtained. The Cu SACs with P content gradient were prepared by a similar procedure except for changing the amount of phosphoric acid to 0.8 and $2.4~\\mathrm{\\mmol}$ . They are denoted as $\\mathsf{C u-N_{4}/C-P{-}}0.8$ and ${\\mathsf{C u-N}}_{4}/{\\mathsf{C}}{\\cdot}{\\mathsf{P}}{\\cdot}2.4,$ respectively. \n\nSynthesis of PCN. For the PCN catalyst preparation, 50 mmol of carbamide and $100~\\upmu\\upiota$ phosphoric acid were dispersed in $10~\\mathsf{m L}$ DI water under ultrasonication for 15 min, then 2 mmol of F127 in ethanol $(10\\ m L)$ were injected into the above solution and the resulting mixture was stirred for $4h$ . Then, the H-bonded assemblies were obtained by rotary evaporation of the solvent. Afterward, the sample were pyrolyzed in the Ar atmosphere, maintaining $800^{\\circ}\\mathsf C$ for $^\\textrm{\\scriptsize2h}$ at a heating rate of $5^{\\circ}{\\mathsf{C}}/{\\mathsf{m i n}}$ . After being naturally cooled to room temperature, a black powder sample can be obtained. \n\n# Data Availability. All study data are included in the article and/or SI Appendi \n\nACKNOWLEDGMENTS. This work was supported by China Ministry of Science and Technology (2021YFA1600800), the National Natural Science Foundation of China (202074104, 51821006, and 52100195), the National Program for Support of Top-Notch Young Professionals, the DNL Cooperation Fund, Chinese Academy of Sciences (CAS) (DNL201918), the Fundamental Research Funds for the Central Universities (WK2060120004, WK2060000021, WK2060000025, and KY2060000180), the CAS Fujian Institute of Innovation, and the DNL201918 Cooperation Fund. This work was partially carried out at the USTC Center for Micro and Nanoscale Research and Fabrication. We acknowledge the Experimental Center of Engineering and Material Science in the University of Science and Technology of China. We thank the photoemission end stations BL1W1B in the Beijing Synchrotron Radiation Facility, BL14W1 in the Shanghai Synchrotron Radiation Facility, and BL10B and BL11U in the National Synchrotron Radiation Laboratory for help with characterizations. \n\n17. E.-T. Yun, J. H. Lee, J. Kim, H.-D. Park, J. Lee, Identifying the nonradical mechanism in the peroxymonosulfate activation process: Singlet oxygenation versus mediated electron transfer. Environ. Sci. Technol. 52, 7032–7042 (2018). \n18. X. Duan, H. Sun, Y. Wang, J. Kang, S. Wang, N-doping-induced nonradical reaction on single-walled carbon nanotubes for catalytic phenol oxidation. ACS Catal. 5, 553–559 (2015). \n19. G. C. Bond, The origins of particle size effects in heterogeneous catalysis. Surf. Sci. 156, 966–981 (1985). \n20. L. Liu, A. Corma, Metal catalysts for heterogeneous catalysis: From single atoms to nanoclusters and nanoparticles. Chem. Rev. 118, 4981–5079 (2018). \n21. X. Zheng et al., Origin of enhanced water oxidation activity in an iridium single atom anchored on NiFe oxyhydroxide catalyst. Proc. Natl. Acad. Sci. U.S.A. 118, e2101817118 (2021). \n22. Y. Shang, X. Xu, B. Gao, S. Wang, X. Duan, Single-atom catalysis in advanced oxidation processes for environmental remediation. Chem. Soc. Rev. 50, 5281–5322 (2021). \n23. Z. Li et al., Activation of peroxymonosulfate by iron-biochar composites: Comparison of nanoscale Fe with single-atom Fe. J. Colloid Interface Sci. 582 (Pt B), 598–609 (2021). \n24. X. Li et al., Single cobalt atoms anchored on porous N-doped graphene with dual reaction sites for efficient fenton-like catalysis. J. Am. Chem. Soc. 140, 12469–12475 (2018). \n25. X. Mi et al., Almost $100\\%$ peroxymonosulfate conversion to singlet oxygen on single-atom $\\mathsf{C o N}_{2+2}$ sites. Angew. Chem. Int. Ed. Engl. 60, 4588–4593 (2021). \n26. J. A. Zamora Zeled\u0001on et al., Tuning the electronic structure of Ag-Pd alloys to enhance performance for alkaline oxygen reduction. Nat. Commun. 12, 620 (2021). \n27. J. Wang et al., Heteroatom-doping of non-noble metal-based catalysts for electrocatalytic hydrogen evolution: An electronic structure tuning strategy. Small Methods 5, e2000988 (2021). \n28. J. Wan et al., In situ phosphatizing of triphenylphosphine encapsulated within metal–organic frameworks to design atomic $\\mathsf{C o}_{1}\\mathsf{-P}_{1}\\mathsf{N}_{3}$ interfacial structure for promoting catalytic performance. J. Am. Chem. Soc. 142, 8431–8439 (2020). \n29. Y. Wang et al., High-efficiency oxygen reduction to hydrogen peroxide catalyzed by nickel single-atom catalysts with tetradentate ${\\mathsf N}_{2}{\\mathsf O}_{2}$ coordination in a three-phase flow cell. Angew. Chem. Int. Ed. Engl. 59, 13057–13062 (2020). \n30. H. Shen et al., Synergistic effects between atomically dispersed Fe\u0002N\u0002C and C\u0002S\u0002C for the oxygen reduction reaction in acidic media. Angew. Chem. Int. Ed. Engl. 56, 13800–13804 (2017). \n31. Y. Mun et al., Versatile strategy for tuning ORR activity of a single Fe- ${\\cdot}\\mathsf{N}_{4}$ site by controlling electron-withdrawing/donating properties of a carbon plane. J. Am. Chem. Soc. 141, 6254–6262 (2019). \n32. H. Wu et al., Regulating the allocation of N and P in codoped graphene via supramolecular control to remarkably boost hydrogen evolution. Energy Environ. Sci. 12, 2697–2705 (2019). \n33. Y. Zheng et al., Toward design of synergistically active carbon-based catalysts for electrocatalytic hydrogen evolution. ACS Nano 8, 5290–5296 (2014). \n34. Y. Zhao et al., Can boron and nitrogen co-doping improve oxygen reduction reaction activity of carbon nanotubes? J. Am. Chem. Soc. 135, 1201–1204 (2013). \n35. H. L. Poh, M. Pumera, $p$ -Element-doped graphene: Heteroatoms for electrochemical enhancement. ChemElectroChem 2, 190–199 (2015). \n36. H. B. Yang et al., Atomically dispersed ${\\mathsf{N i}}({\\mathsf{I}})$ as the active site for electrochemical ${\\mathsf{C O}}_{2}$ reduction. Nat. Energy 3, 140–147 (2018). \n37. F. Li et al., Boosting oxygen reduction catalysis with abundant copper single atom active sites. Energy Environ. Sci. 11, 2263–2269 (2018). \n38. C. Zhao et al., Solid-diffusion synthesis of single-atom catalysts directly from bulk metal for efficient $\\mathsf{C O}_{2}$ reduction. Joule 3, 584–594 (2019). \n39. R. Golnak et al., Intermolecular bonding of hemin in solution and in solid state probed by N K-edge X-ray spectroscopies. Phys. Chem. Chem. Phys. 17, 29000–29006 (2015). \n40. H. C. Choi et al., X-ray absorption near edge structure study of BN nanotubes and nanothorns. J. Phys. Chem. B 109, 7007–7011 (2005). \n41. W. Liu et al., Discriminating catalytically active $\\mathsf{F e N}_{\\times}$ species of atomically dispersed Fe–N–C catalyst for selective oxidation of the C–H bond. J. Am. Chem. Soc. 139, 10790–10798 (2017). \n42. H. Shang et al., Engineering unsymmetrically coordinated $C u-S_{1}N_{3}$ single atom sites with enhanced oxygen reduction activity. Nat. Commun. 11, 3049 (2020). \n43. Y. Zhou et al., Activation of peroxymonosulfate by benzoquinone: A novel nonradical oxidation process. Environ. Sci. Technol. 49, 12941–12950 (2015). \n44. T. Zhang et al., Efficient peroxydisulfate activation process not relying on sulfate radical generation for water pollutant degradation. Environ. Sci. Technol. 48, 5868–5875 (2014). \n45. G. Yu, Y. Wang, H. Cao, H. Zhao, Y. Xie, Reactive oxygen species and catalytic active sites in heterogeneous catalytic ozonation for water purification. Environ. Sci. Technol. 54, 5931–5946 (2020). \n46. L. Ge, J. Chen, X. Qiao, J. Lin, X. Cai, Light-source-dependent effects of main water constituents on photodegradation of phenicol antibiotics: Mechanism and kinetics. Environ. Sci. Technol. 43, 3101–3107 (2009). \n47. A. A. Gorman, M. A. J. Rodgers, Singlet molecular oxygen. Chem. Soc. Rev. 10, 205–231 (1981). \n48. Y. Gao, Z. Chen, Y. Zhu, T. Li, C. Hu, New insights into the generation of singlet oxygen in the metal-free peroxymonosulfate activation process: Important role of electron-deficient carbon atoms. Environ. Sci. Technol. 54, 1232–1241 (2020). \n49. J. Lee, U. von Gunten, J.-H. Kim, Persulfate-based advanced oxidation: Critical assessment of opportunities and roadblocks. Environ. Sci. Technol. 54, 3064–3081 (2020). \n50. X. Duan, H. Sun, Z. Shao, S. Wang, Nonradical reactions in environmental remediation processes: Uncertainty and challenges. Appl. Catal. B 224, 973–982 (2018). \n51. K. Z. Huang, H. Zhang, Direct electron-transfer-based peroxymonosulfate activation by iron-doped manganese oxide $(\\delta\\ –\\mathsf{M n O}_{2})$ and the development of galvanic oxidation processes (GOPs). Environ. Sci. Technol. 53, 12610–12620 (2019). \n52. Y. Wang et al., Insights into the generation of high-valent copper-oxo species in ligand-modulated catalytic system for oxidizing organic pollutants. Chem. Eng. J. 304, 1000–1008 (2016). \n53. J. G. McAlpin et al., Electronic structure description of a $[\\mathsf{C o}(\\mathsf{I I I})_{3}\\mathsf{C o}(\\mathsf{I V})\\mathsf{O}_{4}]$ cluster: A model for the paramagnetic intermediate in cobalt-catalyzed water oxidation. J. Am. Chem. Soc. 133, 15444–15452 (2011). \n54. Y. Deng, A. D. Handoko, Y. Du, S. Xi, B. S. Yeo, In situ Raman spectroscopy of copper and copper oxide surfaces during electrochemical oxygen evolution reaction: Identification of $\\mathsf{C u}^{\\mathsf{I I I}}$ oxides as catalytically active species. ACS Catal. 6, 2473–2481 (2016). " + }, + { + "id": "10.1093_nsr_nwab197", + "DOI": "10.1093/nsr/nwab197", + "DOI Link": "http://dx.doi.org/10.1093/nsr/nwab197", + "Relative Dir Path": "mds/10.1093_nsr_nwab197", + "Article Title": "Dual-ligand and hard-soft-acid-base strategies to optimize metal-organic framework nullocrystals for stable electrochemical cycling performance", + "Authors": "Zheng, SS; Sun, Y; Xue, HG; Braunstein, P; Huang, W; Pang, H", + "Source Title": "NATIONAL SCIENCE REVIEW", + "Abstract": "Most metal-organic frameworks (MOFs) hardly maintain their physical and chemical properties after exposure to acidic, neutral, or alkaline aqueous solutions, resulting in insufficient stability, therefore limiting their applications. Thus, the design and synthesis of stable size/morphology-controlled MOF nullocrystals is critical but challenging. In this study, dual-ligand and hard-soft-acid-base strategies were used to fabricate a variety of 3D pillared-layer [Ni(thiophene-2,5-dicarboxylate)(4,4'-bipyridine)](n) MOF nullocrystals (1D nullofibers, 2D nullosheets and 3D aggregates) with controllable morphology by varying the concentration of 4,4'-bipyridine and thus controlling the crystal growth direction. Owing to the shorter ion diffusion length, enhanced electron/ion transfer and strong interactions between thiophene-2,5-dicarboxylate and 4,4'-bipyridine, the 2D nullosheets showed much larger specific capacitance than 1D nullofibers and 3D aggregates. A single device with an output voltage as high as 3.0 V and exceptional cycling performance (95% of retention after 5000 cycles at 3 mA cm(-2)) was realized by configuring two aqueous asymmetric supercapacitive devices in series. The excellent cycling property and charge-discharge mechanism are consistent with the hard-soft-acid-base theory.", + "Times Cited, WoS Core": 284, + "Times Cited, All Databases": 295, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000837772000003", + "Markdown": "CHEMISTRY \n\n# Dual-ligand and hard-soft-acid-base strategies to optimize metal-organic framework nanocrystals for stable electrochemical cycling performance \n\nShasha Zheng $\\textcircled{10}1$ , Yan Sun1, Huaiguo Xue1, Pierre Braunstein4, Wei Huang $\\textcircled{10}2,3,*$ and Huan Pang1,∗ \n\n1School of Chemistry \nand Chemical \nEngineering, Yangzhou \nUniversity, Yangzhou \n225009, China; 2State \nKey Laboratory of \nOrganic Electronics \nand Information \nDisplays, and Institute \nof Advanced \nMaterials (IAM), \nNanjing University of \nPosts and \nTelecommunications, \nNanjing 210023, \nChina; 3Frontiers \nScience Center for \nFlexible Electronics \n(FSCFE), MIIT Key \nLaboratory of Flexible \nElectronics (KLoFE), \nNorthwestern \nPolytechnical \nUniversity, Xi’an \n710072, China and \n4Institut de Chimie \nUMR 7177, \nUniversite´ de \nStrasbourg, CNRS, \nStrasbourg 67081, \nFrance \n\n# ABSTRACT \n\nMost metal-organic frameworks (MOFs) hardly maintain their physical and chemical properties after exposure to acidic, neutral, or alkaline aqueous solutions, resulting in insufficient stability, therefore limiting their applications. Thus, the design and synthesis of stable size/morphology-controlled MOF nanocrystals is critical but challenging. In this study, dual-ligand and hard-soft-acid-base strategies were used to fabricate a variety of 3D pillared-layer [Ni(thiophene-2,5-dicarboxylate) $^{\\prime}4,4^{\\prime}$ -bipyridine)]n MOF nanocrystals (1D nanofibers, 2D nanosheets and 3D aggregates) with controllable morphology by varying the concentration of $^{4,4^{\\prime}}$ -bipyridine and thus controlling the crystal growth direction. Owing to the shorter ion diffusion length, enhanced electron/ion transfer and strong interactions between thiophene-2,5-dicarboxylate and $^{4,4^{\\prime}}$ -bipyridine, the 2D nanosheets showed much larger specific capacitance than 1D nanofibers and 3D aggregates. A single device with an output voltage as high as $3.0\\mathrm{V}$ and exceptional cycling performance ( $95\\%$ of retention after 5000 cycles at $3\\mathrm{mAcm}^{-2}$ ) was realized by configuring two aqueous asymmetric supercapacitive devices in series. The excellent cycling property and charge–discharge mechanism are consistent with the hard-soft-acid-base theory. \n\nKeywords: metal-organic framework, dual ligand, hard-soft-acid-base, electrochemical energy storage, supercapacitor \n\n∗Corresponding authors. E-mails: panghuan@yzu.edu.cn; iamwhuang@njupt.edu.cn \n\nReceived 16 March 2021; Revised 25 September 2021; Accepted 26 September 2021 \n\n# INTRODUCTION \n\nSupercapacitors (SCs) have emerged as promising devices for electrochemical energy storage, on account of their long life cycle, high power density and fast charging ability [1]. Recently, 2D pseudocapacitive nanomaterials (e.g. black phosphorus [2] and transition-metal carbide/nitrides [3]) have been proven to be efficient electrode materials for high-energy and high-power-oriented applications of SCs [4]. Therefore, the synthesis and development of 2D pseudocapacitive nanomaterials is crucial for the future development of SCs. \n\nMetal-organic frameworks (MOFs) are crystalline materials whose diverse structures, large surface areas and tunable pore sizes attract considerable attention [5,6]. Because of their remarkable properties, MOFs have been used in diverse fields, including gas storage and separation [7], batteries [8], SCs [9,10], catalysis [11,12], water treatment [13,14] and desalination [15,16]. Earlier research in this field has mainly focused on the preparation, characterization and application of bulk MOFs, and has shown considerable influence of their chemical composition, size and morphology on their functionality and utility [17,18]. In recent years, it was found that MOF nanomaterials are more promising for electrochemical energy storage devices than bulk MOF materials because of the shorter diffusion pathways and size-dependent physical–chemical properties [19,20]. However, most of these MOF nanomaterials still suffer from insufficient stability, which severely limits their application [21,22]. Consequently, the synthesis of size/morphologycontrolled MOF nanocrystals with improved stability has become central to their wider application. \n\n![](images/cb006aa8fc3486ebb2ae9dadeb9d441447d7d6e21a25a94dd9d3f10f29f15359.jpg) \nScheme 1. Schematic of the dual-ligand and HSAB strategies for fabricating 3D pillared-layer [Ni(Tdc)(Bpy)]n MOF nanocrystals. \n\nAlthough there is a growing number of methods used to regulate the size/morphology of MOFs, using different reagents and templates, most of them are only applicable to specific materials [23–25]. Therefore, it is highly desirable to develop a general and efficient method for adjusting the crystal size and morphology of different MOFs, endowed with excellent electrochemical energy storage performances. In the process of developing new methods for the crystal engineering of coordination networks, the double-ligand strategy has been shown to be effective for controlling the size, morphology and chemical properties of MOFs [26,27]. In particular, the dual-ligand strategy can provide unique pillaredlayer networks to assemble specific MOFs with diverse properties [27]. Such pillared-layer networks are based on coordination bonds, which confer better structural stability and are more attractive than hydrogen bonds [28,29]. One of the reasons for the instability of many MOF crystals may be the combination of soft metal cations $\\mathrm{(Co^{2+},Z n^{2+},N i^{2+}}$ , ${\\mathrm{Cu}}^{2+}$ , etc.) with hard carboxylic acid ligands, which do not conform to the hard-soft-acid-base (HSAB) principle [30]. Coordination bonds involving soft metal cations with softer N-containing organic ligands are stronger than those formed with hard carboxylic acid ligands [31,32]. \n\nWe decided to utilize $^{4,4^{\\prime}}$ -bipyridine (Bpy) as a coordination modulator to achieve a more controllable morphology and good stability of MOFs based on dual-ligand and HSAB strategies. We report a general, rapid, room-temperature solution reaction method to fabricate a variety of 3D pillared-layer $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF materials (Tdc $\\c=$ thiophene-2,5-dicarboxylate). The ${\\bf N i}^{\\mathrm{II}}$ center can be connected to the softer base Bpy to form stable 1D Ni-Bpy linear chains, which can in turn be used as pillars to support 2D Ni-Tdc network structures resulting from coordination of the $\\mathrm{\\mathbf{Ni}^{\\mathrm{{II}}}}$ center with the carboxylate ligand Tdc (Scheme 1). We have successfully synthesized $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF nanocrystals with different controllable morphologies (1D nanofibers, 2D nanosheets and 3D aggregates) by adjusting the concentration of Bpy to control the direction of crystal growth. The resulting $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF nanocrystals were used as electrodes for SCs, and the 2D nanosheets displayed the highest specific capacity of $612\\mathrm{F}\\ \\mathbf{g}^{-1}$ at $0.5\\mathrm{Ag}^{-1}$ . Furthermore, two aqueous asymmetric SC (ASC) devices placed in series were successfully fabricated using 2D nanosheets and activated carbon (AC), which delivers superior cycling properties. \n\n# RESULTS AND DISCUSSION \n\n$\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOFs were readily prepared by a room-temperature alkaline solution reaction of the organic linkers Tdc and Bpy with $\\mathrm{NiCl}_{2}{\\cdot}6\\mathrm{H}_{2}\\mathrm{O}$ The different morphologies obtained for $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ according to the Tdc and Bpy molar ratios of 1:0.03, 1:0.06, 1:0.12, 1:0.25, 1:0.5, 1:1, 1:1.5 and 1:2, are denoted as M1 to M8, respectively. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images of the $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOFs (Fig. 1) indicate that the samples M1, M5 and M8 are 1D nanofibers, 2D nanosheets and 3D aggregates with uniform morphology, respectively. The change in morphology of the MOF nanomaterials from 1D nanofibers to 3D aggregates was also observed in Figs S1 and S2. Obviously, an increasing amount of Bpy (on going from M1 to M8) results in gradual stacking and agglomeration of the 1D nanofibers to form 2D nanosheets (from M1 to M5), and then the 2D nanosheets gradually assemble to form 3D aggregates (from M6 to M8). Moreover, the high-resolution TEM images of M5 in Fig. S3 exhibit no lattice fringe, which may be due to the damage caused by the light beam at high voltage. The high-angle annular dark-field scanning TEM combined with elemental mapping show that the elements C, N, O, S and Ni are distributed throughout the M5 nanosheets (Fig. S3b). The MOF stability in water and alcohol was investigated by soaking M5 in a water or ethanol solution for 7 days. Figure S4 indicates that the structure of M5 nanosheets is destroyed in ethanol solution, but remains stable without any change in water, which is beneficial to application in aqueous SC devices. The Fourier transform infrared (FTIR) spectra of M1–M8, Tdc and Bpy are displayed in Fig. S5. For Tdc, the peaks at ${\\sim}1411$ , 1662 and $1522\\mathrm{cm}^{-1}$ arise from the symmetric and asymmetric stretching modes of the –COOH group, respectively [33]. The peaks of the Bpy appearing at ${\\sim}1406$ , 1482 and $1587\\mathrm{cm}^{-1}$ arise from $\\scriptstyle{\\mathrm{C}}={\\mathrm{C}}$ stretching. The absorptions at $800{-}1215\\mathrm{cm}^{-1}$ are related to aromatic $\\mathrm{\\bfC}\\mathrm{-}\\mathrm{\\bfH}$ stretching vibrations. The FTIR spectra of MOFs (M1–M8) exhibit peaks at 1566 and $1350\\mathrm{cm}^{-1}$ , which can be associated with the asymmetric and symmetric stretching modes of coordinated $-\\mathrm{COO^{-}}$ groups, respectively. The difference between the peaks of the –COOH and $-\\mathbf{C}\\mathbf{O}\\mathbf{O}^{-}$ groups confirms the coordination of $-\\mathbf{C}\\mathbf{O}\\mathbf{O}^{-}$ to $\\mathrm{Ni}^{2+}$ . In addition, compared with the free ligands, a new peak at $629\\mathrm{cm}^{-1}$ corresponds to Ni-O from $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ . \n\n![](images/10d2698854ffa2b5577f875f6a7ed5fdf0fcc71be703b56f212d77cba9ee84c2.jpg) \nFigure 1. (a–c) The morphological transformation process of MOF nanomaterials from 1D nanofibers to 3D aggregates. (d–f) SEM (scale bar, 200 nm) images. $(\\mathfrak{g-}\\mathrm{i})$ TEM (scale bar, 200 nm) images of the samples: (a, d, g) M1, (b, e, h) M5 and (c, f, i) M8. \n\nFurthermore, X-ray diffraction (XRD) patterns confirmed that the various samples of $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ were successfully prepared and their characteristic peaks were indexed using the standard simulated pattern of MOFs (CCDC No. 298903) [34,35]. Figure 2a shows the XRD patterns of M1, M5 and M8, demonstrating that the 1D nanofibers (M1) preferentially grow (202) crystal planes, while 2D nanosheets and 3D aggregates have exposed crystal planes (010), (020), (024) and (124). Interestingly, upon stacking of 1D nanofibers and agglomeration to 2D nanosheets (from M1 to M5), the (024) crystal plane is gradually exposed and the diffraction peak intensity increases (Fig. S6). To further explain this phenomenon, the molecular structure of a $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF, which belongs to the orthorhombic space group $\\left(P c c n\\right)$ , was analyzed [34]. Figure S7a shows that each ${\\bf N i}^{\\mathrm{II}}$ center is coordinated by four oxygen atoms and two nitrogen atoms, and the $\\mathrm{\\mathbf{Ni}^{\\mathrm{\\mathrm{II}}}}$ center is in a six-coordinated environment, forming an octahedral structure [36]. In the 3D stacking structure of a $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF, the $\\mathrm{\\mathbf{Ni}^{\\mathrm{\\bar{II}}}}$ ions connect to the N atoms of Bpy to construct 1D Ni-Bpy linear chains, and these 1D chains serve as ‘pillars’ to support the 2D Ni-Tdc network structures formed by coordination of the carboxyl oxygen atoms of Tdc to the ${\\bf N i}^{\\mathrm{II}}$ center $\\left(\\mathrm{Fig.}\\mathrm{S7b-e}\\right)$ [37]. A view along the (202) direction (Fig. 2b) shows that adjacent 1D Ni-Bpy linear chains are bridged by Tdc to further extend into a 3D porous structure through Ni-O bonds. Therefore, when a small amount of Bpy is introduced, the 1D NiBpy linear chains form and control the growth of $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF crystals along the (202) crystal plane as a priority, making M1 appear as 1D nanofibers. With an increasing amount of Bpy, the 1D nanofibers gradually stack and agglomerate to form 2D nanosheets, the crystal planes (010), (020), (024) and (124) are exposed, and the perspective views along the direction of these crystal planes (Figs 2c and S8) indicate that the adjacent 2D Ni-Tdc network structures are bridged by Bpy to further extend into a 3D porous structure by Ni-N bonds, resulting in the formation of 2D nanosheets. \n\nX-ray photoelectron spectroscopy (XPS) measurements confirm that M5 contains five elements: Ni, N, C, S and O (Fig. 2d). The $\\mathrm{Ni}\\ 2\\mathrm{p}$ spectrum demonstrates the presence of two types of Ni species: $\\mathrm{Ni}^{2+}$ at 855.2 and $872.8~\\mathrm{eV}$ and $\\mathrm{Ni}^{3+}$ at 856.5 and $874.2\\ \\mathrm{eV}$ (Fig. 2e) [38,39]. The deconvoluted N 1s XPS spectrum (Fig. 2f) indicates peaks at 399.5 and $398.8\\ \\mathrm{~eV}$ arising from Ni-N and pyridinic $\\mathbf{N}$ [40]. In the C 1s XPS spectrum (Fig. 2g), the peaks appearing at ${\\sim}288.2\\$ , 287.6, 285.3 and $284.5\\mathrm{eV}$ arise from $\\scriptstyle\\mathrm{O=C-O,C-S/C=O,}$ $\\mathrm{C-N/C-O}$ and $\\scriptstyle{\\mathrm{C=C-C,}}$ , respectively [41]. Moreover, the existence of $scriptstyle{\\mathrm{O=C-O}}$ $\\left(531.3~\\mathrm{eV}\\right)$ and $\\scriptstyle{\\mathrm{C=O}}$ $(530.7~\\mathrm{eV})$ units is further verified by the O 1s spectrum (Fig. 2i) [41]. The $\\mathtt{\\Delta}S\\mathtt{\\ a p}$ spectrum (Fig. 2h) reveals the presence of C–S–C, further confirming the formation of $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ [42]. Furthermore, the XPS spectra of other samples also indicated that the constructed MOF materials are $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ (Figs S9–S15). To study the porous structure of the MOF materials, the Brunauer-Emmett-Teller (BET) surface areas were determined. A sample of M5 exhibited a high specific surface area that was remarkably larger than those of other MOF materials (Fig. S16 and Table S2). Furthermore, the pore size distribution also indicates the coexistence of micropores and mesopores in the MOF materials, with M5 possessing a larger pore volume (Fig. S17). Therefore, the high specific surface area of M5 is favorable for promoting electrolyte permeation to access more redox active sites. \n\nThe electrochemical capacitive properties of the samples M1–M8 were first studied in a threeelectrode system. The SEM images of the prepared \n\n![](images/b2bf20dec7c985ae307bd05a80c2c813ab9661ad840e248e598938f5f9bb138c.jpg) \nFigure 2. (a) XRD patterns of M1, M5 and M8. (b) The accumulation viewed along the (202) direction. (c) The accumulation viewed along the (024) direction. XPS spectra of the M5: (d) survey and high resolution, (e) Ni 2p, (f) N 1s, (g) C 1s, (h) $\\mathtt{S2p}$ and (i) O 1s XPS spectra. \n\nMOF electrodes show that the morphology of 1D nanofibers, 2D nanosheets and 3D aggregates is well maintained during the fabrication process of the electrodes (Fig. S18). The cyclic voltammetry (CV) curves in Fig. 3a reveal that the redox current density of M5 is much higher than that of the other electrodes. The electrochemical reaction kinetics of the as-fabricated electrodes were further studied via CV at multiple scan rates (Figs 3b, S19a, S21a, S23a, S25a, S28a, S30a and S32a). As the scan rates increase, the reduction peak (peak 1) moves to a more negative voltage and the oxidation peak (peak 2) shifts to a more positive voltage, which may be caused by an increase in the internal diffusion resistance at high scan rates. Even at high scan rates, the redox peaks of M3–M5 are well maintained, indicating their excellent capacitive behavior and rate capability. Furthermore, the relationship between current (i) and scanning rate $\\mathbf{\\tau}(\\mathbf{v})$ is $i=a\\nu^{b}$ (details in the Supplementary Data) [43]. The $b$ values are between 0.5 and 0.7, indicating that both diffusion-controlled and surface capacitive-controlled processes exist in the entire electrochemical reaction (Figs 3c, S19b, S21b, S23b, S25b, S28b, S30b and S32b). Subsequently, the ratios of the two capacitive mechanism contributions at various scan rates can be calculated (details in the Supplementary Data). As the scan rate increases, the capacitive contribution shows an increasing trend, indicating high-efficiency charge storage (Figs 3d, S19c, S20, S21c, S22, S23c, S24, S25c, S26, S27, S28c, S29, S30c, S31, S32c and S33). As shown in Fig. S34, compared with other electrodes, M5 has a higher diffusion-controlled contribution, which means that the corresponding redox reactions in the M5 electrode are mainly diffusioncontrolled processes. Figure S35a shows CV curves for the M5 electrode at various potentials. As the potential window increases, the area delimited by the corresponding CV curve increases accordingly. To further explore the electrochemical behavior of M1–M8, galvanostatic charge–discharge (GCD) tests were performed. In Fig. S35b and c, the GCD and specific capacitance change versus potential curves of the M5 electrode at different potentials suggest that this electrode possesses the longest charge–discharge time and highest specific capacitance at a charge–discharge potential of $0.5\\mathrm{V}.$ . From the GCD curves in Fig. 3e at $1\\mathrm{Ag^{-1}}$ , M5 displays the longest discharge time compared with M1 and M8. The GCD curves of the other electrodes at various current densities are displayed in Figs S36 and S37. As shown in Fig. S38, although M3 has a longer discharge time than M5, the coulombic efficiency and rate performance of M3 are relatively poor. Overall, M5 exhibits the highest specific capacity $(592\\mathrm{F}\\mathrm{g}^{-1}$ at $1\\mathrm{Ag}^{-1}.$ ), and its coulombic efficiency is also good (Fig. 3f). To highlight the outstanding electrochemical capacitive performance of M5, a comparison with recently reported MOF nanomaterials [44–46] is presented in Table S3. For comparison, the electrochemical capacitive properties of the organic ligands (Bpy, Tdc, Bpy/Tdc) were also tested (Fig. S39). The organic ligand electrodes exhibit almost no electrochemical energy storage characteristics, which indicates that the $[\\mathrm{Ni}(\\mathrm{Tdc})(\\mathrm{Bpy})]_{\\mathrm{n}}$ MOFs formed by the organic ligands and $\\mathrm{Ni}^{2+}$ have unique energy storage characteristics. Their superior electrochemical activity was further confirmed via electrochemical impedance spectroscopy (EIS) measurements (Fig. S40). The intersection point of the Nyquist plot with the $Z\\prime$ axis represents $\\mathbb{R}_{s}$ (series resistance). M5 exhibits a low value of $\\mathbb{R}_{s}$ at $1.06~\\Omega$ , similar to M1 $\\left(2.28~\\Omega\\right)$ , M2 $\\left(2.20~\\Omega\\right)$ , M3 $\\left(0.70~\\Omega\\right)$ , M4 (0.92 $\\Omega$ ), M6 $\\left(1.48~\\Omega\\right)$ , M7 $\\left(1.02\\Omega\\right)$ and M8 $\\left(0.93~\\Omega\\right)$ . The results indicate that the as-obtained electrodes have high electronic conductivity and rapid reaction kinetics. \n\n![](images/2db6725fb9c50b858f41eb9a05f8e2def2e5e44277e998ffed1336db49ba4df9.jpg) \nFigure 3. (a) CV curves of the M1, M5 and M8 at $30\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in a three-electrode cell. (b) $\\complement\\lor$ curves for M5 at various scan rates. (c) Log(i) versus $\\mathsf{l o g}(v)$ plots for M5. (d) Bar chart showing the $\\%$ of capacitive contribution of M5 at various scan rates. (e) Galvanostatic discharge curves of M1, M5 and M8 at ${\\mathsf{1}}{\\mathsf{A}}{\\mathsf{g}}^{-1}$ . (f) Specific capacitance of M1, M5 and M8 at multiple current densities. \n\nASC devices were fabricated from $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOFs (positive) and AC (negative) materials using our previously reported method (at a mass ratio of 1:1.8, details are in the Supplementary Data, Fig. S41). As displayed in Fig. 4a, the shape of the CV curves of the M5//AC ASC device can be maintained at various scan rates, suggesting typical pseudocapacitive performance with rapid and reversible charge storage capacity. To better understand the enhanced properties of the M5//AC ASC device, the interfacial capacitive behavior of all ASC devices was further confirmed via CV tests at multiple scan rates. By plotting log(i) versus $\\log(\\mathbf{v})$ , $b$ values of M1–M8//AC ASC devices were found to be between 0.8 and 1 (Figs 4b, S42–S57). This result indicates that the overall charge storage by M1–M8//AC ASC devices can be divided into diffusion-controlled and surface capacitance-controlled processes but are mainly due to a surface capacitance-controlled process. Figure S58 shows that the surface capacitancecontrolled contribution in the M5//AC ASC device is more significant. With an increasing scan rate, the surface capacitance-controlled contribution rate of M5//AC gradually increases from $52.8\\%$ to $94.8\\%$ , indicating that M5//AC has good charge-transfer kinetics, which is also the reason why M5//AC has high rate capability. A shaded area related to the surface capacitancecontrolled contribution in M5//AC accounts for a large fraction of $74.2\\%$ at $30\\ \\mathrm{mV\\{s}^{-1}}$ (Fig. 4c). As displayed in Fig. S59, the specific capacitance of the as-constructed M5//AC ASC devices is the highest at $1.5{\\mathrm{~V}}.$ Additionally, the GCD curves of the assembled M1–M8//AC ASC devices were tested at different current densities (Figs S60 and S61). In Fig. S62, the M5//AC ASC device reveals a specific capacitance of $207\\mathrm{mFcm}^{-2}$ , which is high compared to other devices (the values for M1, M2, M3, M4, M6, M7 and M8 are 98.5, 155, 90, 106, 119, 74 and $61\\mathrm{mFcm}^{-2}$ , respectively), mainly because 2D MOF nanosheets have a shorter ion transport pathway (Fig. S63). At $8\\ \\mathrm{mAcm}^{-2}$ , the M5//AC ASC device provides an excellent rate capability by maintaining a capacitance of \n\n![](images/78425947e77215b6909f775c80948292294a21a3a10a1c7b44906a4745793271.jpg) \nFigure 4. (a) CV curves of ${\\mathsf{M}}5//{\\mathsf{A C}}$ at multiple scan rates. (b) Log(i) versus log(v) plots for M5//AC. (c) CV curve with the capacitive fraction displayed by the shaded area of M5//AC at $30\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ . (d) GCD curves of two M5//AC devices linked in series at multiple current densities. (e) Specific capacitance changes versus current density of two $\\mathsf{M}5//\\mathsf{A C}$ devices linked in series. (Inset) Optical image of two M5//AC devices linked in series. (f) Schematic illustration of two M5//AC devices linked in series to light up a yellow LED and power a rotating motor. $({\\mathfrak{g}})$ Cycling performance and coulombic efficiency at $3\\mathsf{m A c m}^{-2}$ for 5000 cycles. (Inset) The first 20 and last 20 GCD curves of two M5//AC devices linked in series. \n\n$144\\mathrm{mF}\\mathrm{cm}^{-2}$ . To further explore the impedance performance, EIS analysis was performed, and the Nyquist plots of the M1–M8//AC ASC devices are displayed in Fig. S64. The charge-transfer resistance $\\left(\\mathrm{R}_{\\mathrm{ct}}\\right)$ of this device was calculated using ZView software. The M5//AC ASC device revealed a low $\\mathbb{R}_{s}$ of $1.2~\\Omega$ and an $\\mathrm{R}_{\\mathrm{ct}}$ of $79\\ \\Omega$ . The low resistance value for the M5//AC ASC device indicates easy ion diffusion. In addition, the GCD curves of the device at different mass loadings were investigated. The specific capacitance was found to gradually increase with the mass loading, but with the higher mass loading $\\left(8\\mathrm{\\mg}\\mathrm{cm}^{-2}\\right)$ , the specific capacitance decreases, probably because the active material on the electrode is not fully utilized under the high mass loading conditions (Fig. S65). \n\nTo explore the practical applications of the ASC device, two M5//AC ASC devices were linked in series. Figure 4d shows GCD curves for two M5//AC \n\nASC devices linked in series. This device could be extended to a large voltage window of $3.0\\mathrm{V}.$ As displayed in Fig. 4e, the specific capacitance of the series device at 1.5, 3, 6 and $8\\mathrm{mAcm}^{-2}$ was calculated to be 102, 83, 72 and $67\\mathrm{mFcm}^{-2}$ , respectively, showing good rate capability. According to the GCD curves in Fig. 4d, we calculated the coulombic efficiency of the device at different current densities (Fig. S66). With the increase of current density, the coulombic efficiency gradually increases, and is close to $100\\%$ at $8.0\\ \\mathrm{mA}\\mathrm{cm}^{-2}$ . More importantly, in Fig. 4f, this series device was used to power a yellow LED and a rotating motor for ${\\sim}5\\ \\mathrm{min}$ and $_{3\\mathrm{~s,~}}$ respectively, after charging for $1\\mathrm{min}$ (Videos S1 and S2). Moreover, this device demonstrates an excellent cycling property with a capacitance retention of $95\\%$ and an excellent coulombic efficiency of $96\\%$ at $3\\mathrm{mAcm}^{-2}$ after 5000 cycles, which should be of benefit for fast-charging energy storage devices (Fig. 4g). \n\n![](images/2d61ac5469e1e9b2c329abcd7db0b7d9acd9a1e493897a889713540e9c7b0a84.jpg) \nFigure 5. (a) Schematic for the selective removal of Tdc carboxylate links from $[\\mathsf{N i}(\\mathsf{T d c})(\\mathsf{B p y})]_{\\mathsf{n}}$ nanosheets by $0\\mathsf{H}^{-}$ in the electrolyte during charging and discharging. (b) Mechanism of charge/discharge of a $\\mathrm{[Ni(Tdc)(Bpy)]_{n}}$ MOF-based electrode. \n\nTo further investigate the charge–discharge mechanism of the electrode materials, SEM images of M5 after cycling were obtained (Fig. S67). The SEM images show that the nanosheet morphology of M5 is well maintained without visible damage. The corresponding elemental mapping images of M5 after cycling indicate that C, N, O, S, Ni and K are distributed throughout the whole nanosheet (Fig. S68). The XRD patterns show that the (202) crystal plane of M5 is retained and the other crystal planes disappear after cycling (Fig. S69). This phenomenon can be explained by the selective removal of Tdc carboxylate links from $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ nanosheets by $\\mathrm{OH^{-}}$ in the electrolyte during charging and discharging, whereas the Ni-Bpy layers are well protected (Fig. 5a). Therefore, the (202) crystal plane corresponding to the Ni-Bpy layers is well preserved. In addition, Fig. S70 shows that the XPS spectral peaks of N 1s and C 1s decrease after cycling, and the XPS spectral peak of $\\mathtt{\\Delta}\\mathtt{S}\\mathtt{\\ }2\\mathtt{p}$ almost disappears, which also confirms the above hypothesis. As can be seen from the cycling performance (Fig. $^{4}\\mathrm{g})$ , the specific capacitance slowly increases before 1000 cycles, which may be due to the capacity contribution of $\\mathrm{\\DeltaNi(OH)_{2}}$ generated during the removal of Tdc carboxylate linkers. Therefore, the possible charge–discharge mechanism is shown in Fig. 5b. \n\npillared-layer $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF nanocrystals, based on the synergetic dual-ligand and HSAB strategies. The nanocrystals are revealed as efficient electrode materials for SCs with excellent life cycles. Bpy was found to act as a coordination modulator to adjust the morphology transformation of $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF nanocrystals from 1D nanofibers to 2D nanosheets and then to 3D aggregates. This appears related to the amount of Bpy introduced, which causes MOF crystals to grow along 1D Ni-Bpy linear chains or in a 2D Ni-Tdc network direction. Compared with the 1D nanofibers and 3D aggregates, the 2D nanosheets demonstrate higher electrochemical performance. This is closely related to the ion diffusion and charge-transfer processes. The excellent electrochemical properties of 2D nanosheets are due to their short ion transport distance. Furthermore, by way of HSAB strategies, in the 3D pillared-layer $\\mathrm{\\big[Ni\\big(Tdc\\big)\\big(Bpy\\big)\\big]_{n}}$ MOF structure the $\\mathrm{\\mathbf{Ni}^{\\mathrm{\\mathrm{II}}}}$ center can be used as a soft metal site to connect with the soft base Bpy to construct a stable 1D Ni-Bpy linear chain. During the charging and discharging process, the Ni-Tdc network in the MOF was removed by $\\mathrm{OH^{-}}$ in the electrolyte, while the Ni-Bpy layer was well protected, thus providing good cycling stability. We believe that this work can provide a general approach to designing size/morphology-controllable and functional adjustable MOFs. \n\n# CONCLUSIONS \n\nIn conclusion, we have proposed a facile method for the preparation of morphology-controllable 3D \n\n# SUPPLEMENTARY DATA \n\nSupplementary data are available at NSR online. \n\n# FUNDING \n\nThis work was supported by the National Natural Science Foundation of China (U1904215), the Top-Notch Academic Programs Project of Jiangsu Higher Education Institutions, the Natural Science Foundation of Jiangsu Province (BK20200044), the Excellent Doctoral Dissertation of Yangzhou University, the Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX19 2099) and the Priority Academic Program Development of Jiangsu Higher Education Institutions. \n\n# AUTHOR CONTRIBUTIONS \n\nH.P. conceived the idea and supervised the work. S.S.Z. carried out most experiments and wrote the manuscript. Y.S., H.G.X., P.B., W.H. and H.P. discussed the manuscript and commented on it. P.B. polished the manuscript. H.P. and H.G.X. carried out funding acquisition. All authors discussed the results and participated in analyzing the experimental results. \n\nConflict of interest statement. None declared. \n\n# REFERENCES \n\n1. Zhang P, Wang M and Liu Y et al. Dual-redox-sites enable twodimensional conjugated metal-organic frameworks with large pseudocapacitance and wide potential window. J Am Chem Soc 2021; 143: 10168–76. \n2. Nakhanivej P, Yu X and Park SK et al. Revealing molecular-level surface redox sites of controllably oxidized black phosphorus nanosheets. Nat Mater 2019; 18: 156–62. \n3. VahidMohammadi A, Mojtabavi M and Caffrey NM et al. Assembling 2D MXenes into highly stable pseudocapacitive electrodes with high power and energy densities. Adv Mater 2019; 31: 1806931. \n4. Nakhanivej P, Dou Q and Xiong P et al. Two-dimensional pseudocapacitive nanomaterials for high-energy- and high-poweroriented applications of supercapacitors. Acc Mater Res 2021; 2: 86–96. \n5. Lv X, Feng L and Wang K et al. A series of mesoporous rare-earth metal-organic frameworks constructed from organic secondary building units. Angew Chem Int Ed 2021; 60: 2053–7. \n6. Jiao L and Jiang HL. Metal-organic-framework-based singleatom catalysts for energy applications. Chem 2019; 5: 786–804. \n7. Jiang $Z,\\mathsf{X}\\mathsf{u}\\times$ and Ma Y et al. Filling metal-organic framework mesopores with $\\mathtt{T i O}_{2}$ for $\\mathsf{C O}_{2}$ photoreduction. Nature 2020; 586: 549–54. \n8. Jiang H, Liu XC and Wu Y et al. Metal-organic frameworks for high charge-discharge rates in lithium-sulfur batteries. Angew Chem Int Ed 2018; 57: 3916–21. \n9. Zheng S, Xue H and Pang H. Supercapacitors based on metal coordination materials. Coord Chem Rev 2018; 373: 2–21. \n10. Pei C, Choi MS and Yu X et al. Recent progress in emerging metal and covalent organic frameworks for electrochemical and functional capacitors. J Mater Chem A 2021; 9: 8832–69. \n11. Hou CC, Wang HF and Li C et al. From metal-organic frameworks to single/dual-atom and cluster metal catalysts for energy applications. Energy Environ Sci 2020; 13: 1658–93. \n12. Liao PQ, Shen JQ and Zhang JP. Metal-organic frameworks for electrocatalysis. Coord Chem Rev 2018; 373: 22–48. \n13. Sarkar A, Adhikary A and Mandal A et al. Zn-BTC MOF as an adsorbent for iodine uptake and organic dye degradation. Cryst Growth Des 2020; 20: 7833–9. \n14. Zhang X, Wang LJ and Han Z et al. Degradation of azo dyes under visible light with stable MOF based on tetrastyrene imidazole ligand. Dalton Trans 2020; 49: 4352–7. \n15. Xu X, Tang J and Kaneti YV et al. Unprecedented capacitive deionization performance of interconnected iron–nitrogendoped carbon tubes in oxygenated saline water. Mater Horiz 2020; 7: 1404–12. \n16. Elsayed E, Al-Dadah R and Mahmoud S et al. Experimental testing of aluminium fumarate MOF for adsorption desalination. Desalination 2020; 475: 114170. \n17. Guo H, Zhu Y and Wang S et al. Combining coordination modulation with acid-base adjustment for the control over size of metal-organic frameworks. Chem Mater 2012; 24: 444–50. \n18. Xiao X, Zou L and Pang H et al. Synthesis of micro/nanoscaled metal-organic frameworks and their direct electrochemical applications. Chem Soc Rev 2020; 49: 301–31. \n19. Zhao M, Huang Y and Peng Y et al. Two-dimensional metalorganic framework nanosheets: synthesis and applications. Chem Soc Rev 2018; 47: 6267–95. \n20. Zheng S, Zheng Y and Xue H et al. Ultrathin nickel terephthalate nanosheet three-dimensional aggregates with disordered layers for highly efficient overall urea electrolysis. Chem Eng J 2020; 395: 125166. \n21. Lu XF, Liao PQ and Wang JW et al. An alkaline-stable, metal hydroxide mimicking metal-organic framework for efficient electrocatalytic oxygen evolution. J Am Chem Soc 2016; 138: 8336–9. \n22. Zheng S, Li Q and Xue H et al. A highly alkaline-stable metal oxide@metal-organic framework composite for highperformance electrochemical energy storage. Natl Sci Rev 2020; 7: 305–14. \n23. Hou Q, Wu Y and Zhou S et al. Ultra-tuning of the aperture size in stiffened ZIF-8 Cm frameworks with mixed-linker strategy for enhanced $\\mathsf{C O}_{2}/\\mathsf{C H}_{4}$ separation. Angew Chem Int Ed 2019; 58: 327–31. \n24. Gumilar G, Kaneti YV and Henzie J et al. General synthesis of hierarchical sheet/plate-like M-BDC $M=\\complement\\ u$ , Mn, Ni, and Zr) metal-organic frameworks for electrochemical non-enzymatic glucose sensing. Chem Sci 2020; 11: 3644–55. \n25. Sun J, Yu X and Zhao S et al. Solvent-controlled morphology of amino-functionalized bimetal metal-organic frameworks for asymmetric supercapacitors. Inorg Chem 2020; 59: 11385–95. \n26. He H, Zhu QQ and Li CP et al. Design of a highly-stable pillarlayer zinc(II) porous framework for rapid, reversible, and multiresponsive luminescent sensor in water. Cryst Growth Des 2019; 19: 694–703. \n27. Wu AQ, Wang WQ and Zhan HB et al. Layer-by-layer assembled dual-ligand conductive MOF nano-films with modulated chemiresistive sensitivity and selectivity. Nano Res 2020; 12: 3–8. \n28. Yao MS, Zheng JJ and Wu AQ et al. A dual-ligand porous coordination polymer chemiresistor with modulated conductivity and porosity. Angew Chem Int Ed 2020; 59: 172–6. \n29. Li L, Yi JD and Fang ZB et al. Creating giant secondary building layers via alkalietching exfoliation for precise synthesis of metal-organic frameworks. Chem Mater 2019; 31: 7584–9. \n30. Li XJ, Ma W and Li HM et al. Sulfur-functionalized metal-organic frameworks: synthesis and applications as advanced adsorbents. Coord Chem Rev 2020; 408: 213191. \n31. Yuan S, Feng L and Wang K et al. Stable metal-organic frameworks: design, synthesis, and applications. Adv Mater 2018; 30: 1704303. \n32. Xue H, Huang XS and Yin Q et al. Bimetallic cationic metal-organic frameworks for selective dye adsorption and effective $\\mathsf{C r}_{2}0_{7}{}^{2-}$ removal. Cryst Growth Des 2020; 20: 4861–6. \n33. Jahan M, Bao Q and Yang JX et al. Structure-directing role of graphene in the synthesis of metal-organic framework nanowire. J Am Chem Soc 2010; 132: 14487–95. \n34. Jia HP, Li W and Ju ZF et al. Synthesis, structure and magnetism of metalorganic framework materials with doubly pillared layers. Eur J Inorg Chem 2006; 2006: 4264–70. \n35. Tong M, Liu S and Zhang X et al. Two-dimensional CoNi nanoparticles@S,Ndoped carbon composites derived from S,N-containing Co/Ni MOFs for high performance supercapacitors. J Mater Chem A 2017; 5: 9873–81. \n36. Sun XZ, Huang ZL and Wang HZ et al. Syntheses and crystal structures of cadmium complexes with thiophene-dicarboxylate and bipyridine-like ligands. Z Anorg Allg Chem 2005; 631: 919–23. \n37. Kettner F, Worch C and Moellmer J et al. Synthesis, crystal structure and catalytic behavior of homo- and heteronuclear coordination polymers [M(tdc)(bpy)] $\\mathsf{(M^{2+}=F e^{2+}}$ , $\\mathsf{C o}^{2+}$ , $Z n^{2+}$ , $\\mathsf{C d}^{2+}$ ; $\\mathrm{tdc}^{2-}=2{,}5$ -thiophenedicarboxylate). Inorg Chem 2013; 52: 8738–42. \n38. Xu X, Li L and Huang J et al. Engineering ${\\mathsf{N i}}^{3+}$ cations in NiO lattice at the atomic level by ${\\mathsf{L i}}^{+}$ doping: the roles of ${\\mathsf{N i}}^{3+}$ and oxygen species for CO oxidation. ACS Catal 2018; 8: 8033–45. \n39. Zhang F, Ji R and Liu Y et al. A novel nickel-based honeycomb electrode with microtapered holes and abundant multivacancies for highly efficient overall water splitting. Appl Catal B Environ 2020; 276: 119141. \n40. Zhang X, Liu S and Zang Y et al. $\\mathsf{C o/C o g S_{8}@S,N}$ -doped porous graphene sheets derived from S, N dual organic ligands assembled Co-MOFs as superior electrocatalysts for full water splitting in alkaline media. Nano Energy 2016; 30: 93–102. \n41. Liu S, Zhang X and Wang G et al. High-efficiency ${\\sf C o}/{\\sf C o}_{\\sf X}{\\sf S}_{\\sf y}@{\\sf S}$ ,N-Codoped porous carbon electrocatalysts fabricated from controllably grown sulfurand nitrogen-including cobalt-based MOFs for rechargeable zinc-air batteries. ACS Appl Mater Interfaces 2017; 9: 34269–78. \n42. Chao S, Wu H and Xia Q et al. Ultrathin two-dimensional metal-organicframework-derived CoO/nitrogen and sulfur Co-doped ultrathin porous carbon nanoplates for highly efficient water electrolysis. ChemElectroChem 2019; 6: 3940–8. \n43. Augustyn V, Come J and Lowe MA et al. High-rate electrochemical energy storage through ${\\mathsf{L i}}^{+}$ intercalation pseudocapacitance. Nat Mater 2013; 12: 518–22. \n44. Sheberla D, Bachman JC and Elias JS et al. Conductive MOF electrodes for stable supercapacitors with high areal capacitance. Nat Mater 2017; 16: 220–4. \n45. Qu C, Jiao Y and Zhao B et al. Nickel-based pillared MOFs for high-performance supercapacitors: design, synthesis and stability study. Nano Energy 2016; 26: 66–73. \n46. Wang R, Yan X and Lang J et al. A hybrid supercapacitor based on flowerlike $C o(O H)_{2}$ and urchin-like VN electrode materials. J Mater Chem A 2014; 2: 12724–32. " + }, + { + "id": "10.1038_s41467-023-37526-5", + "DOI": "10.1038/s41467-023-37526-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-023-37526-5", + "Relative Dir Path": "mds/10.1038_s41467-023-37526-5", + "Article Title": "19.31% binary organic solar cell and low non-radiative recombination enabled by non-monotonic intermediate state transition", + "Authors": "Fu, JH; Fong, PWK; Liu, H; Huang, CS; Lu, XH; Lu, SR; Abdelsamie, M; Kodalle, T; Sutter-Fella, CM; Yang, Y; Li, G", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Non-radiative recombination loss suppression is critical for boosting performance of organic solar cells. Here, the authors regulate self-organization of bulk-heterojunction in a non-monotonic manner, and achieve device efficiency over 19% with low non-radiative recombination loss down to 0.168 eV. Non-fullerene acceptors based organic solar cells represent the frontier of the field, owing to both the materials and morphology manipulation innovations. Non-radiative recombination loss suppression and performance boosting are in the center of organic solar cell research. Here, we developed a non-monotonic intermediate state manipulation strategy for state-of-the-art organic solar cells by employing 1,3,5-trichlorobenzene as crystallization regulator, which optimizes the film crystallization process, regulates the self-organization of bulk-heterojunction in a non-monotonic manner, i.e., first enhancing and then relaxing the molecular aggregation. As a result, the excessive aggregation of non-fullerene acceptors is avoided and we have achieved efficient organic solar cells with reduced non-radiative recombination loss. In PM6:BTP-eC9 organic solar cell, our strategy successfully offers a record binary organic solar cell efficiency of 19.31% (18.93% certified) with very low non-radiative recombination loss of 0.190 eV. And lower non-radiative recombination loss of 0.168 eV is further achieved in PM1:BTP-eC9 organic solar cell (19.10% efficiency), giving great promise to future organic solar cell research.", + "Times Cited, WoS Core": 399, + "Times Cited, All Databases": 407, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000961133600031", + "Markdown": "# 19.31% binary organic solar cell and low nonradiative recombination enabled by nonmonotonic intermediate state transition \n\nReceived: 18 December 2022 \n\nAccepted: 21 March 2023 \n\nPublished online: 30 March 2023 \n\nCheck for updates \n\nJiehao Fu 1,2, Patrick W. K. Fong 1,2, Heng Liu3, Chieh-Szu Huang 4, Xinhui Lu 3, Shirong $\\mathbf{Lu^{5}}$ , Maged Abdelsamie6,7, Tim Kodalle 8, Carolin M. Sutter-Fella $\\textcircled{\\bullet}^{8}$ , Yang Yang 4 & Gang Li 1,2 \n\nNon-fullerene acceptors based organic solar cells represent the frontier of the field, owing to both the materials and morphology manipulation innovations. Non-radiative recombination loss suppression and performance boosting are in the center of organic solar cell research. Here, we developed a nonmonotonic intermediate state manipulation strategy for state-of-the-art organic solar cells by employing 1,3,5-trichlorobenzene as crystallization regulator, which optimizes the film crystallization process, regulates the selforganization of bulk-heterojunction in a non-monotonic manner, i.e., first enhancing and then relaxing the molecular aggregation. As a result, the excessive aggregation of non-fullerene acceptors is avoided and we have achieved efficient organic solar cells with reduced non-radiative recombination loss. In PM6:BTP-eC9 organic solar cell, our strategy successfully offers a record binary organic solar cell efficiency of $19.31\\%$ $(18.93\\%$ certified) with very low non-radiative recombination loss of $0.190\\mathrm{eV}.$ And lower non-radiative recombination loss of $0.168\\mathrm{eV}$ is further achieved in PM1:BTP-eC9 organic solar cell $(19.10\\%$ efficiency), giving great promise to future organic solar cell research. \n\nTremendous efforts in non-fullerene acceptor (NFA) materials have brought organic solar cells (OSCs) to a new era1–3. Now, the reported power conversion efficiency (PCE) of OSCs has exceeded $18\\%^{4-11}$ , with $18.2\\%$ certified record on NREL efficiency chart (https://www.nrel.gov/ pv/cell-efficiency.html). However, compared to perovskite counterparts at $25.7\\%$ PCE, there is still clear PCE gap mainly due to the high non-radiative recombination loss in $\\boldsymbol{0}\\mathsf{S C}\\mathsf{s}^{12}$ . Therefore, a key question is how to form high-quality organic active layer that can reduce nonradiative recombination loss without deteriorating charge separation and transport. In the field of OSC, the quality of active layer is related to the distribution and molecular stacking of donor and acceptor (D:A) bulk-heterojunction (BHJ) blend13–15, which is more complicated than that in perovskite. In our previous fullerene-based work, we demonstrated that slowing down evaporation rate of high boiling point solvent is a strategy to induce highly ordered and crystalline polymer in the blend $\\hbar|\\boldsymbol{\\mathsf{m}}^{15,16}$ . Some of the landmark fullerene acceptor OSC works like solvent annealing, additive strategies are also tightly linked to BHJ active layer drying and crystallization kinetics17,18, but due to the limitation of characterization tools, little insightful detail about the drying and crystallization kinetics of active layer has been presented so far. Entering NFA OSC era, the morphology-modifying techniques are commonly restricted to molecule optimization and ternary strategy, assisted by solvent additives originally designed for fullerene-based OSC systems, which does not fully realize the potential of $\\mathsf{N F A}^{4,5,19-24}$ . Taking the benchmark additive DIO as an example, DIO can increase the crystallinity of NFA while it has less impact on polymer donor25–27. The low volatility of DIO leads to the excessive aggregation of NFA associated with increased non-radiative recombination loss of OSC, which is one reason why DIO treated devices commonly suffer more serious voltage loss than as-cast devices8,28. While the recent explorations on volatile solid additives have led to better device stability comparing to the traditional solvent additives26,27,29, little obviously enhanced PCE over solvent additives approach has been validated. Therefore, it is imperative to develop new morphology-regulating techniques that can optimize the self-organization of D:A and reduce non-radiative recombination simultaneously. Here, by employing 1,3,5- trichlorobenzene (TCB) as crystallization regulator30–32, we report a non-monotonic intermediate state manipulation (ISM) strategy to maneuver the self-organization process of D:A blend. TCB can interact with both polymer donor and NFA, thereby improving their crystallinity and contributing to more efficient and balanced charge transport process. At the same time, the volatility of TCB is excellent, and it can be removed during spin-coating process. Finally, the OSC morphology of D:A molecules experienced a two-step manipulation process—the first enhancement and then relaxation of molecular aggregation. Assisted by the delicate intermediate states transition, active layer with more suitable molecular aggregation is achieved, facilitating higher $\\mathsf{E Q E}_{\\mathtt{E L}}$ , eventually leading to a record PCE of $19.31\\%$ 1 $18.93\\%$ certified) in binary OSC with reduced $E_{l o s s,n r}$ of $0.190\\mathrm{eV}$ . And lower $E_{l o s s,n r}$ of $0.168\\mathrm{eV}$ is further achieved in high efficiency PM1:BTP-eC9 OSC (with \n\n$19.10\\%$ PCE). With the combined high device efficiency, reduced nonradiative recombination, excellent generality, and superior stability, the ISM strategy provides a new promising route towards OSC technology future. \n\n# Results \n\n# Interaction between TCB and active materials \n\nThe chemical structures of PM6, TCB, and Y6 are presented in Fig. 1a–c. We first conducted differential scanning calorimetry (DSC) test, formerly used to identify eutectic phase in $\\cos C^{33}$ . As illustrated in Fig. 1d–f, on the one hand, for PM6, Y6, and PM6:Y6 samples, no peak is observed in the cooling direction in a temperature range of $90{\\cdot}10^{\\circ}\\mathrm{C}$ , illustrating no endothermic or exothermic behavior in these samples. On the other hand, neat TCB shows an obvious exothermic peak at $53^{\\circ}\\mathrm{C}$ , which is related to the solidification temperature of TCB during the cooling process. The most interesting thermal behavior occurs in samples of TCB:PM6, TCB:Y6, and TCB:PM6:Y6. Take TCB:PM6 as an example, except the exothermic peak (at around ${53^{\\circ}}\\mathrm{C}$ ) that attributed to the solidification process of TCB, we can observe another exothermic peak at lower temperature. As the neat PM6 sample does not show any peak during the cooling process, we ascribe this unexpected peak to the formation of a new phase in TCB:PM6 complex—to be specific, TCB can interact with PM6 and form a new phase. The similar phenomenon is again observed in TCB:Y6 and TCB:PM6:Y6 complexes, revealing that TCB can simultaneously interact with both donor and acceptor materials. To further elucidate the underlying mechanism at molecular level, we performed density functional theory (DFT) simulation (Supplementary Fig. 1). According to the computational result, in TCB molecule, the hydrogen (H) atoms show the maximum positive electrostatic potential (ESP) value. While oxygen (O) atoms in carbonyl groups (-CO) and nitrogen (N) atoms in cyano groups (-CN) show the minimum negative ESP value in PM6 molecule and Y6 molecule, respectively. This indicates the interaction between TCB and light absorbing materials originates from hydrogen bonds, i.e. -CO…H- and -CN…H-. In our recent work, we found eutectic phase behavior between the additive and acceptor (happened at the heating process) can be used as the driving force for nanomorphology optimization of absorbing layer33. In this work, no extra peak can be observed, except the melting peak of TCB in heating process (Supplementary Fig. 2). However very interestingly, in the cooling process, all three (PM6, Y6, D:A blend) mixtures with TCB exhibited new phases, which has never been reported in OSCs before. In principle, the crystallization-related physical processes are potentially effective in influencing OSC active layer film formation/crystallization kinetics, thereby influencing device performance. Therefore, we examined whether the interaction between TCB and active materials could have a positive impact on device performance. \n\n![](images/7505ea9b12a1a1678e0f77d69591b1603865f8afb96736c5a016565d340eb405.jpg) \nFig. 1 | Chemical structures and thermal behaviors between TCB and active process) of Y6, Y6:TCB, and TCB. f DSC thermograms (cooling process) of PM6:Y6, materials. Chemical structures of PM6 (a), TCB (b), and Y6 (c). d DSC thermograms PM6:Y6:TCB, and TCB. Here exo. is the abbreviation of exothermic. (cooling process) of PM6, PM6:TCB, and TCB. e DSC thermograms (cooling \n\n![](images/f891d29eb8adac27e3661f443685b52926bd5a5ca68bd5cf315c7464027e2ce0.jpg) \nFig. 2 | Device performance of OSCs with DIO and TCB processing. a Device structure used in this work. $\\mathbf{b}J$ –V curves for PM6: Y6-based OSCs with benchmark solvent additive DIO and with TCB. c EQE spectra for PM6:Y6-based OSCs with DIO and with TCB. d PCE histograms of PM6:Y6-based OSCs with DIO and with TCB. e $\\mathsf{E Q E}_{\\mathtt{E L}}$ of PM6:Y6 devices with different treatments at various injected current densities. f Detailed energy loss in the DIO processed and TCB processed PM6:Y6 devices. Source data are provided as a Source Data file. \n\n
Table1| Detailed photovoltaic performances of PM6:Y6-based devices processed with diferent treatments
AdditiveVoc (V)Jsc (mA cm-2)Jsccal (mA cm-2)FF (%) PCEa (%)
DIO0.82926.6026.06 76.3616.83 (16.61± 0.10)
TCB0.852 27.0226.3178.4318.06 (17.86 ± 0.09)
\n\naThe average PCEs with standard deviation were calculated from 33 devices in each case. calIntegrated $J_{S C}$ values from EQE measurements. \n\n# The impact of TCB on device performance \n\nWe fabricated OSCs with sandwich structure of indium tin oxide (ITO) / poly (3,4-ethylenedioxythiophene):poly (styrenesulfonate) (PEDOT:PSS)/PM6:Y6/poly[(9,9-bis( $3^{\\prime}$ -((N,N-dimethyl)-N-ethyl ammonium)-propyl)−2,7-fluorene)-alt-2,7-(9,9-dioctylfluorene)] dibromide (PFN-Br) / Ag (Fig. 2a). The current density–voltage $\\left(J-V\\right)$ curves of optimal OSCs treated with TCB and the current OSC field benchmark solvent additive 1,8-diiodooctane (DIO) are plotted in Fig. 2b, and the corresponding photovoltaic parameters are summarized in Table 1. Compared to the device without additive treatment with $16.16\\%$ PCE (Supplementary \n\nTable 1), the DIO treated devices show a champion PCE of $16.83\\%$ , with a $\\nu_{o c}$ of $0.829\\mathrm{V}.$ , a $J_{S C}$ of $26.60\\:\\mathrm{mA}/\\mathrm{cm}^{2}$ and a FF of $76.39\\%$ . Excitingly, for the TCB-treated devices, the $\\nu_{o c}$ of champion device increases to $_{0.852\\mathrm{v}}$ , and the other two parameters also get improvements— $-J_{S C}$ and FF increase to $27.02\\mathrm{mA}/\\mathrm{cm}^{2}$ and $78.43\\%$ , respectively, thereby leading to a PCE of $18.06\\%$ . It is worth mentioning that $18.06\\%$ is among the highest efficiency for PM6:Y6-based binary system so far. To verify the $J_{S C}$ from J–V test, we conducted external quantum efficiency (EQE) measurements (Fig. 2c). The integrated $J_{S C}$ values are 26.06 and $26.31\\mathrm{mA}/\\mathrm{cm}^{2}$ for the DIO and TCB-treated devices, respectively, which are in good agreement with the results form $J{-}V$ test. \n\n# Physical properties of devices with different treatments \n\nTo understand the much higher efficiency improvement in the TCBtreated device from a physical point of view, we then analyzed the charge transport and recombination processes. The charge carrier transport properties were investigated by space charge limited current (SCLC) method. As shown in Supplementary Fig. 3 and Supplementary Table 3, TCB treatment contributes to similar electron $(3.5\\times10^{-4}~\\mathrm{cm}^{2}/\\mathrm{Vs}$ in DIO device versus $3.6\\times10^{-4}\\ \\mathrm{cm}^{2}/\\mathrm{Vs}$ in the TCB processed device) and slightly faster hole $(2.5\\times10^{-4}\\mathrm{cm}^{2}/\\mathrm{Vs}$ in DIO device versus $3.0\\times10^{-4}\\mathrm{cm}^{2}/\\mathrm{Vs}$ in the TCB processed device) mobility, which should ascribe to the more ordered molecular stacking in the TCB processed film (will be discussed later). Transient photovoltage (TPV) measurement was performed to explore the charge recombination dynamics. As shown in Supplementary Fig. 4, device with TCB treatment exhibits a longer decay time ${\\bf\\chi}^{\\prime}\\tau=1.82{\\upmu\\mathrm{s}},$ ) than that of the DIO one $(\\tau=1.39\\upmu s)$ , which indicates that TCB treatment is a more effective way to suppress charge carrier recombination. The free charge carrier recombination mechanism was further studied by the dependence of $V_{O C}$ on light intensity (Supplementary Fig. 5). \n\nTable 2 | Detailed $\\pmb{E}_{l o s s}$ parameters of PM6:Y6 systems made with different treatments \n\n\n
Active layerVoca (V)Eloss (eV)Eg (ev)AE (eV)AE2 (eV)EQEEL (%)AE3 (eV)AE3cal (eV)
PM6:Y6-DIO0.8330.5581.3910.2610.0641.7×10-²0.2240.233
PM6:Y6-TCB0.8580.5381.3960.2620.0623.4×10-20.2060.214
\n\naDevice area is \\~11 mm2, no mask applied. \n\n![](images/d2d84f0208b511137b9d98b6138552d1480b9442c7b8872c72d353d3049058f0.jpg) \nig. 3 | Morphology—Surface topography and molecular stacking. AFM height PM6:Y6 blend films with DIO and TCB treatment. h The areas of π-π and lamellar mages of Y6 films (a, e) and PM6:Y6 films (b, f) with DIO and TCB treatment. 2D diffraction peak for PM6:Y6 blend films with DIO and TCB treatment. Source data GIWAXS diffraction patterns $(\\mathbf{c},\\mathbf{g})$ and 1D GIWAXS diffraction patterns (d) of are provided as a Source Data file. \n\nThe power $n$ of the TCB-treated device is 1.02, lower than that of the DIO device ${\\mathrm{\\Delta}n}=1.09{\\mathrm{\\Delta}}$ ), underlining the DIO device suffers from more serious trap-assisted recombination and this should ascribe to the residual DIO in active layer34–36. Because the vapor pressure of TCB (77 Pa at $25^{\\circ}\\mathrm{C})$ is much higher than that of DIO $_{(0.03\\mathsf{P a}}$ at $25^{\\circ}\\mathrm{C})^{37-39}$ , TCB shows much more excellent volatility than DIO (Supplementary Fig. 6). And TCB can be removed during spin-coating process (Supplementary Fig. 7 and 8), therefore TCB-treated device suffers from less trap-assistant recombination. The combination of higher charge mobility, more balanced charge transport, and less recombination restricts charge carrier accumulation, thereby contributing to the enhanced $J_{S C}$ and FF in the TCB-treated device40. \n\nAs DIO is the most widely used benchmark additive in pursing modern high-efficiency OSCs so far, the obviously higher $\\nu_{o c}$ via TCB processing is of upmost interest for OSC society. To obtain more insights, we quantitatively analyzed the $\\nu_{o c}$ loss (also known as energy loss $(E_{l o s s}))$ in devices processed with different treatments. The $E_{l o s s}$ in solar cells can normally be divided into three parts, named $\\varDelta E_{1},\\varDelta E_{2}$ and $\\phantom{}\\Delta E_{3}.\\Delta E_{I}$ and $\\varDelta E_{2}$ are related to radiative recombination above and below the bandgap, respectively41,42. $\\varDelta E_{3}$ is non-radiative recombination loss, also known as $E_{l o s s,n r}.$ The calculation procedure is presented in Methods section (‘The calculation procedure of $E_{l o s s}'$ part and Supplementary Fig. 9), and detailed $E_{l o s s}$ parameters are summarized in Table 2 and Figs. 2e, f. The bandgaps of the DIO processed and TCB processed OSCs are 1.391 eV and 1.396 eV, respectively, corresponding to $\\varDelta E_{I}$ values of \n\n0.261 eV and $0.262\\mathrm{eV}$ , respectively. As for $\\varDelta E_{2},$ the DIO processed and TCB processed OSCs show similar values, around $0.06\\mathrm{eV}$ , illustrating the nearly same charge transfer states in these two OSCs. The first method used to calculate $\\varDelta E_{3}$ is from $J{-}V$ characteristics $(\\varDelta E_{3}^{c a l}=E_{g}-q V_{O C}-\\varDelta E_{1}-\\varDelta E_{2})$ . Here, the $\\varDelta E_{3}$ values of the DIO processed and TCB processed OSCs are $0.233\\mathrm{eV}$ and $0.214\\mathrm{eV}$ , respectively, meaning the more serious $E_{l o s s}$ in the DIO processed OSC is from nonradiative recombination loss. \n\nIn principle, $\\varDelta E_{3}$ can also be equivalently calculated from electroluminescence quantum efficiency $(\\mathsf{E Q E}_{\\mathsf{E L}},$ $\\Delta E_{3}=$ $\\begin{array}{r}{E_{l o s s,n o n-r a d}=\\mathrm{~-}\\frac{k T}{q}{\\ln E Q E_{E L}})}\\end{array}$ according to reciprocal principle—the stronger $\\mathtt{E Q E}_{\\mathtt{E L}}$ , the lower $\\Delta E_{3}^{43}$ . As presented in Table 2 and Fig. 2e, the TCB based device shows $\\mathsf{E Q E}_{\\mathtt{E L}}$ of $3.4\\times10^{-4}$ (corresponds to $\\varDelta E_{3}$ of $0.206\\mathrm{eV})$ , while the DIO processed device shows weaker $\\mathsf{E Q E}_{\\mathtt{E L}}$ of $1.7\\times10^{-4}$ (corresponds to $\\varDelta E_{3}$ of $0.224\\mathrm{eV},$ ), again verifying the DIO processed OSC suffers more serious non-radiative recombination loss. \n\n# The nanostructure and crystalline ordering of D:A blends \n\nAs device performance is directly linked to the nanostructure and crystalline ordering of D:A blend. We investigated the DIO and TCBtreated blends by tapping mode atomic force microscopy (AFM) and grazing incidence wide-angle $\\mathsf{x}$ -ray scattering (GIWAXS). As seen in Fig. 3a, e, DIO processed Y6 films show obvious molecular aggregation, with higher root-mean-square roughness (Rq) and more hole-like “craters”. In comparison, as the volatility of TCB is much more excellent, TCB is removed during spin-coating process, so the excessive molecular aggregation did not occur in TCB processed Y6 film. Although both DIO (Fig. 3b) and TCB (Fig. 3f) processed blend films show similar Rq of around 1 nm, the DIO processed film shows excessive molecular aggregation with more hole-like “craters”, which is consistent with the fact that the DIO device suffers more serious nonradiative recombination loss. Two-dimensional (2D) GIWAXS diffraction patterns are presented in Fig. 3c, g, and the relevant onedimensional (1D) line cuts in out-of-plane (OOP) and in-plane (IP) directions are depicted in Fig. 3d. No matter with DIO or TCB processing, the blend film shows two prominent diffraction peaks, one is at around $1.8\\mathring{\\mathsf{A}}^{-1}$ due to π-π stacking in OOP direction. Since PM6 shows much weaker diffraction at $q{=}1.8\\mathring\\mathbf{A}^{-1}$ in OOP direction than Y6 (Supplementary Fig. 10), the face-on π-π diffractions observed in blend films is more likely to stem from the π-π stacking of Y6. Another peak is at around $0.3\\mathring{\\mathbf{A}}^{-1}$ due to lamellar stacking in IP direction, reflecting preferred face-on orientations in both blends3,29. Detailed peak information is summarized in Fig. 3h and Supplementary Table 4. As we can see, the TCB processed film shows larger lamellar and π-π peak areas, reflecting TCB processing contributes to higher crystallinity in active blend, which is beneficial to charge transport process7,44. Besides, TCB can simultaneously improve the crystallinity of both polymer donor and NFA (Supplementary Fig. 10 and Supplementary Table 5), while DIO has more impact on NFA than polymer, explaining why TCB based device shows higher hole mobility. \n\n# Non-monotonic intermediate state transition induced by TCB during film formation \n\nTo understand the working mechanisms behind these devices, we investigated the drying and crystallization dynamics of active blends by in situ GIWAXS and in situ time-resolved UV-vis reflectance spectroscopy measurements to monitor the spin-coating process in real time. The in situ GIWAXS measurement conducted at beamline 12.3.2, the Advanced Light Source, Lawrence Berkeley National Laboratory (LBNL), supports the fastest exposure of 1 frame/s, which however did not give a diffraction signal (Supplementary Fig. 11a). Although we further set an exposure time of 3 s (Supplementary Fig. 11b–f), the organic film still cannot show obvious diffraction due to the lower crystallinity of organic molecules, unlike high crystalline inorganic material or perovskite. Extending the exposure time to dozens of seconds may help to get clear diffraction images, but as seen from the in situ UV-vis result (as we discussed later), the transition state only lasts for about $10{\\mathsf{s}}.$ Therefore, the in situ GIWAXS setup we have access to cannot help to understand the phenomenon. Fortunately, the in situ UV-vis characterizations with resolution about $0.4\\:\\mathsf{s}$ gave us much useful information. The color mappings of normalized UV-vis reflection spectra as a function of spin-coating time for samples with DIO and TCB are presented in Fig. 4a, b, respectively. Time-resolved reflectance intensity at $600\\mathsf{n m}$ (corresponds to PM6) and $750\\ensuremath{\\mathrm{nm}}$ (corresponds to Y6) during spin-coating process are extracted and plotted in Fig. 4c, f, respectively. As we can see, the reflectance of the DIO sample gets saturated very quickly (within 0.73 s), corresponding to the removal of host solvent, chloroform. However, the TCB sample takes more time (over 10 s) to make the reflectance of sample steady, which illustrates the self-organization process of D:A is more complicated and lasts much longer. For a more direct comparison, the evolution of normalized absorption spectra at representative time points for DIO and TCB samples are extracted in Fig. 4d, e, respectively. Unlike the DIO sample, the TCB sample shows an interesting nonmonotonic intermediate state transition. Starting from liquid film at 0 s, the 0.73 s curves show the largest redshift in both the DIO and TCBtreated samples, corresponding to the enhanced molecular stacking caused by the transition from solution state to solid state and the interactions between additives and active materials. However, while the DIO film’s spectra keep the same after $\\mathbf{0.73s},$ the TCB-treated sample shows a continuous edge blueshift until becomes saturated at around 10 s after the starting of spin-coating. This observation of first redshift then blueshift during the spin-coating film formation can also be visualized in pseudo-colored Fig. 4b, implying the molecular aggregation in TCB sample experienced a two-step process of first enhancing and then relaxing26,45–47. \n\n![](images/7576d435d1d4be6ba8b25392212affe3a67fb005e0fcabbc9f84792530a77b4f.jpg) \nFig. 4 | In situ UV-vis characterization. The color mapping of in situ UV-vis DIO and with TCB. Normalized absorption spectra (here we defined the absorption reflectance spectra as a function of spin-coating time for PM6:Y6 blends with DIO of sample as the difference between the reflectance of background and the (a) and with TCB (b). Normalized in situ absorption intensity at the wavelength of reflectance of sample) at representative time points for PM6:Y6 blends with DIO (d) $600\\mathsf{n m}$ (c) and $750\\ensuremath{\\mathrm{nm}}$ (f) as a function of spin-coating time for PM6:Y6 blends with and with TCB (e). Source data are provided as a Source Data file. \n\n![](images/ac8fed6afe0d3176bd6bb0528d545f7511173299caaabf5119f8b84a3be2845f.jpg) \nFig. 5 | A schematic diagram illustrating working mechanisms induced by different treatments. a DIO treatment. b TCB treatment. \n\nBased on the results from DFT simulation, TGA, in situ microscopy, FTIR, DSC GIWAXS, in situ UV-vis spectroscopy measurements and $E_{l o s s}$ analysis, the Fig. 5 schematic diagram illustrates the working mechanism induced by TCB. Starting from precursor solution dropping at $0\\mathsf{s}$ , the solvent CF is already removed at ${\\bf-0.75;}$ at the same time, the wet film is converted into dry film and the interaction between additive and active materials occurs. For DIO, it can interact with NFA molecule and increase the crystallinity of NFA, thereby improving device performance25,48. But the low volatility of DIO tends to induce the excessive aggregation of NFA molecules, leading to increased non-radiative recombination28. Besides, the residual DIO is harmful to charge transport process and device stability, especially under illumination36,48. \n\nFor TCB, it can simultaneously interact with both polymer and small molecule by hydrogen bond, thereby facilitating not only the donor polymer and small molecule NFA self-organization, but also the interpenetrating network structure. Because the volatility of TCB is excellent, it is removed during spin-coating (after the CF removal), and the interaction between TCB and active materials is released at the same time. The non-monotonic intermediate state transition then occurs, with the relaxation of molecular aggregation. This scenario explains the unique first redshift and then blueshift stages (in situ UVvis characterization) observed in TCB case. Eventually, the TCB processing achieves film with more ordered molecular stacking, facilitating faster and more balanced charge transport. Besides, after the delicate non-monotonic intermediate state transition, the TCB-treated film exhibits more suitable molecular aggregation than the DIOtreated film, which agrees with the fact that the TCB-treated device has less non-radiative recombination than the DIO case. \n\n# Versatility of TCB-ISM strategy \n\nAs shown in Fig. 6, Table 3 and Supplementary Fig. 12, TCB-ISM strategy’s versatility was demonstrated in five more OSC systems, including all-small-molecule system (BTR-Cl:Y6)49, and polymer:NFA systems (PBDB-T:ITIC, PBDB-T-2Cl:IT-4F, PM1:BTP-eC9 and PM6: BTP$\\mathbf{e}(9)^{22,50-52}$ . The same tendency as in PM6:Y6-based systems was observed: TCB processed devices show clearly improved photovoltaic performance than the benchmark DIO processed devices. Here we take the two over $19\\%$ systems as examples. The film formation processes of these two more efficient blends with DIO and TCB were investigated by in situ UV-vis characterizations, Supplementary Fig. 13 and 14 summarize the in situ UV-vis results of PM1:BTP-eC9 and PM6:BTP-eC9 blends, respectively. Like what we observed in the PM6:Y6 case, the TCB based blends show a two-step film formation process—the first enhancement and then relaxation of molecular aggregation while the DIO based blends do not, verifying TCB can also induce the non-monotonic intermediate state transition in PM6:BTP-eC9 and PM1:BTP-eC9 blends. As a result, in PM1:BTP-eC9 systems, device efficiency increased from $17.86\\%$ by DIO processing to $19.10\\%$ by TCB processing. In PM6:BTP-eC9 systems, while the DIO device also shows an already high PCE of $17.98\\%$ , more excitingly, the TCB-ISM device offers a clearly higher PCE of $19.31\\%$ . The TCB-ISM cell was sent to an ISO/IEC 17025:2017 accredited Calibration Lab—Enli Tech Optoelectronic Calibration Lab for certification, which exhibited an efficiency of $18.93\\%$ (Supplementary Fig. 15). To the best of our knowledge, $19.31\\%$ $(18.93\\%$ certified) is the highest efficiency for binary OSCs so far. \n\nWe quantitatively analyzed the $E_{l o s s}$ in these two more efficient OSC systems (Fig. $6\\mathsf{c}\\mathsf{-}\\mathsf{e}$ and Supplementary Fig. 16) and detailed $E_{l o s s}$ parameters were summarized in Table 4. In the PM1:BTP-eC9 system, the bandgaps of the DIO based and TCB based OSCs are 1.384 eV and 1.394 eV, respectively, corresponding to $\\varDelta E_{1}$ values of $0.259\\mathrm{eV}$ and $0.262\\mathrm{eV}$ , respectively. As for $\\varDelta E_{2},$ OSCs based on DIO and TCB show similar values, around $0.07\\mathrm{eV}$ . As mentioned before, there are two methods to calculate $\\varDelta E_{3}$ . One is from $J{-}V$ characteristics $(\\varDelta E_{3}^{c a l}=E_{g}-q V_{O C}-\\varDelta E_{1}-\\varDelta E_{2})$ . Here, the $\\varDelta E_{3}$ of the TCB based device is $0.168\\mathrm{eV}$ , the lowest reported so far in efficient (PCEå $16\\%$ OSCs, to the best of our knowledge. Another one is from $\\mathsf{E Q E}_{\\mathtt{E L}}$ $\\begin{array}{r}{(\\Delta E_{3}=E_{l o s s,n o n-r a d}=\\_\\underline{{k}}T_{}\\mathsf{l n}E Q E_{E L})}\\end{array}$ . The DIO based OSC shows excellent high $\\mathsf{E Q E}_{\\mathtt{E L}}$ of $7.2\\times10^{-4}$ , corresponding to a $\\varDelta E_{3}$ of $\\mathbf{0.187eV}$ The TCB-ISM strategy gives even more superior result, with $\\mathsf{E Q E}_{\\mathtt{E L}}$ of $1.1\\times10^{-3}$ —the record in efficient OSCs (PCEå $16\\%$ reported so far, corresponding to a $\\varDelta E_{3}$ of 0.175 eV. To the best of our knowledge, both $0.168\\mathrm{eV}$ (by $J{-}V)$ and $0.175\\mathrm{eV}$ (by $\\mathsf{E Q E}_{\\mathtt{E L}},$ ) are the lowest nonrecombination energy loss in high efficiency OSCs (Fig. 6f and Supplementary Table 6, with reported $\\mathrm{PCE}>16\\%$ ). \n\nIn the more efficient PM6:BTP-eC9 system, we observed a similar $E_{l o s s}$ tendency, which again verifying the effectiveness of ISM processing in suppressing non-radiative recombination loss. OSC based on PM6:BTP-eC9 with TCB-ISM processing shows a slightly higher $\\varDelta E_{3}$ of $0.19\\mathrm{eV}$ , next only to that of PM1-based OSC here (Fig. 6f and Supplementary Table 6) so far. In addition to suppressing non-radiative recombination loss, ISM strategy also improves the device stability. Figure $6\\mathrm{g}$ shows the operational stability of PM6:BTP-eC9-based OSCs by maximum power point (MPP) tracking method. The DIO-treated device shows a stronger initial drop in PCE, suffering $17\\%$ efficiency decay within the first $75\\mathsf{h}$ , while the efficiency of the TCB-treated device is only reduced by $7\\%$ within the same $75\\mathsf{h}$ . After 1000-hour simulated 1-sun illumination stress test at MPP, the TCB-treated device shows very encouraging result, maintaining $78\\%$ of initial efficiency, versus $69\\%$ in the DIO case. It is worth noting the $\\mathtt{T}_{80}$ lifetime (the time in which device efficiency drop to $80\\%$ of initial value) of the TCBtreated device is $660\\mathsf{h}$ , much higher than that of the DIO-treated one (169 h). It is also encouraging that it took 340 more hours stress test (from 660 to $\\mathsf{1000h},$ ) for the TCB device PCE to drop from $80\\%$ to $78\\%$ of its initial value. We believe the enhanced light stability is related to (a) TCB-induced uniform molecular aggregation for inhibiting the formation of isolated NFA aggregates as morphological traps53,54, (b) the higher crystallinity in the TCB-treated blend for delaying the morphology evolution under light illumination53–55, and (c) the excellent volatility of TCB for no residue left in the blend film. \n\n![](images/65271759164f7daa2fbbee23043073dcb0cb64b083ff7ce8684baef1fcc69399.jpg) \nFig. 6 | The generality of TCB and the analysis of $\\mathbf{v_{oc}}$ loss as well as light stability. a J–V curves for the DIO processed and TCB processed OSCs based on PM1:BTP-eC9. b J–V curves for the DIO processed and TCB processed OSCs based on PM6:BTP-eC9. c $\\mathsf{E Q E}_{\\mathtt{E L}}$ of OSCs at various injected current densities. d Detailed energy loss in the DIO-processed and TCB-processed OSCs based on PM1:BTP-eC9. \ne Detailed $\\mathsf{v}_{\\mathrm{oc}}$ loss in the DIO processed and TCB processed OSCs based on PM6:BTP-eC9. f Comparison of PCE versus $\\varDelta E_{3}$ in reported OSCs with over $18\\%$ efficiency. g Light stability tests for PM6:BTP-eC9 based OSCs with different treatments, all OSCs were encapsulated and stored under continuous illumination equivalent to 1 sun in air. Source data are provided as a Source Data file. \n\n# Discussion \n\nIn summary, we developed a non-monotonic intermediated state transition strategy to manipulate the BHJ OSC morphology—simultaneously optimize crystallization dynamics and energy loss of nonfullerene OSCs. Unlike the excessive molecular aggregation in films based on traditional solvent additive, the ISM strategy assists the formation of more ordered molecular stacking and suitable molecular aggregation. As a result, we achieved obvious efficiency enhancement with reduced non-radiative recombination loss. In high-performance PM6:BTP-eC9 and PM1:BTP-eC9 binary OSC systems, the ISM strategy contributes to a record efficiency of $19.31\\%$ and very low $E_{l o s s,n r}$ of $\\ensuremath{0.168\\mathrm{eV}}$ , respectively. The success of the ISM strategy paves a new avenue to further unleash the potential of emerging non-fullerene materials. \n\n# Methods \n\n# Materials \n\nAll materials are provided by commercial suppliers: PEDOT:PSS (Clevios P VP AI. 4083 (Heraeus)), PM6 (Solarmer Energy Inc.), PBDB-T (Solarmer Energy Inc.), PBDB-T-2Cl (Solarmer Energy Inc.), BTR-Cl (Solarmer Energy Inc.), PM1 (Solarmer Energy Inc.), Y6 (Solarmer Energy Inc.), ITIC (Solarmer Energy Inc.), IT-4F (Solarmer Energy Inc.), BTP-eC9 (Solarmer Energy Inc.), DIO (Tokyo Chemical Industry Co., Ltd.), TCB (Tokyo Chemical Industry Co., Ltd.), PFN-Br (Solarmer Energy Inc.), Chloroform (Sigma-Aldrich, Ltd.), methanol (Sigma-Aldrich, Ltd.) and \n\nTable 3 | Summary of photovoltaic operating parameters for 5 OSC systems made with different additives \n\n\n
ConditionVoc (v)Jsc (mA cm-2) FF (%)PCEa (%)
BTR-Cl:Y6, DIO0.822 23.7571.9914.05 (13.82 ± 0.16)
BTR-Cl:Y6, TCB0.838 23.9874.7115.01 (14.81 ± 0.14)
PBDB-T:ITIC, DIO0.866 17.4371.8111.06 (10.81 ± 0.13)
PBDB-T:ITIC, TCB0.887 17.6574.3711.84 (11.62 ± 0.12)
PBDB-T-2Cl:IT-4F, DIO0.860 21.7576.0614.23 (13.95 ± 0.16)
PBDB-T-2Cl:IT-4F, TCB0.88021.95 77.2814.93 (14.72 ± 0.13)
PM1:BTP-eC9, DIO0.86626.82 76.9117.86 (17.51 ± 0.21)
PM1:BTP-eC9, TCB0.887 27.2978.9019.10 (18.85 ± 0.18)
PM6:BTP-eC9, DIO0.83627.48 78.2617.98 (17.65 ± 0.21)
PM6:BTP-eC9, TCB0.86127.88 80.3919.31 (19.03 ± 0.19)
PM6:BTP-eC9, TCB0.85927.86 79.1618.93b
\n\naThe average PCEs with standard deviation calculated from 20 devices. All devices were tested with a metal mask applied. bThe certified photovoltaic parameters from Enli Tech Optoelectronic Calibration Lab, Accreditation Criteria: ISO/IEC 17025:2017. \n\n
Table 4| Detailed Eloss parameters of two efficient OSC systems made with different additives
Active layer Voc℃ (V)Etoss (ev)Eg (ev)AE, (eV)AE (eV)EQEEL (%)AE3 (eV)AEcal (eV)
PM1:BTP-eC9a 0.8720.5121.3840.2590.0747.2×10-²0.1870.179
PM1:BTP-eC9b 0.8980.4961.3940.2620.0661.1×10-10.1750.168
PM6:BTP-ec9a 0.8450.5491.3940.2620.0753.8×10-20.2040.212
PM6:BTP-eCgb0.873 0.5211.3940.2620.0695.7×10-20.1920.190
\n\naDevices made with DIO. bDevices made with TCB. cDevice area were tested without metal mask applied. \n\nIPA (Sigma-Aldrich, Ltd.). And all reagents and solvents are used directly without further purification. \n\n# Device fabrication and testing \n\nAt first, the ITO-coated glass substrates were cleaned sequentially with detergent, de-ionized water, acetone, and isopropyl alcohol (IPA) for 15 min under sonication. Then they were dried in nitrogen flow and treated with UV ozone for $30\\mathrm{min}$ . The PM6:Y6, BTR-Cl:Y6, PM1:BTPeC9, PM6:BTP-eC9 OSCs were fabricated with a conventional structure of ITO/PEDOT:PSS/active layer/PFN-Br or Phen-NaDPO/Ag. In these systems, ${\\sim}50\\upmu\\mathrm{L}$ PEDOT:PSS was firstly dripped on ITO substrates and spin-coated at $6000{\\mathrm{rpm}}$ for 20 s, followed by thermal annealing on a hot plate at $120^{\\circ}\\mathrm{C}$ for $20\\mathrm{min}$ to remove the water in PEDOT:PSS film. Then, the substrates were transferred into a glovebox filled with nitrogen $(0_{2}<10$ ppm; $\\mathsf{H}_{2}\\mathbf{O}<10\\mathsf{p p m})$ . The total concentrations of polymer:NFA (PN) and all-small-molecule (ASM) systems are $17\\mathrm{mg/mL}$ $\\left(\\mathbf{D}{\\cdot}\\mathbf{A}=\\mathbf{1}{\\cdot}\\mathbf{1}.2\\right)$ , and $16\\mathrm{{mg/mL}}$ $(\\mathrm{D}{:}\\mathrm{A}=1.7{:}1),$ ), respectively, with chloroform as solvent. The concentrations of DIO are $0.75\\ \\%\\ (\\mathrm{v/v})$ in PM1:BTPeC9 system and $0.5\\%\\%\\%$ in other systems. The concentration of TCB is $10\\mathrm{mg/mL}$ in all OSC systems. The thickness of the active layer was controlled at around $110\\mathsf{n m}$ , then the PN and ASM active layers experienced a process of thermal annealing at $100^{\\circ}\\mathrm{C}$ for 5 min and at $110^{\\circ}\\mathsf{C}$ for $10\\mathrm{{min}}$ , respectively. The next stage is to coat electron transport material, ${\\sim}5\\mathsf{n m}$ PFN-Br, and $5\\mathsf{n m}$ Phen-NaDPO were coated on the top of PN active layers and ASM active layers, respectively. Finally, these semi-finished cells were transferred into a thermal evaporation chamber with a base pressure of ${\\sim}2\\times10^{-4}\\mathrm{Pa}$ , where $\\scriptstyle100\\cdot\\mathsf{n m}$ Ag were deposited through a shadow mask with an active area of $\\scriptstyle11\\mathsf{m m}^{2}$ . The PBDBT:ITIC and PBDB-T-2Cl:IT-4F OSCs were fabricated with an inverted structure of ITO/ZnO/active layer $/\\mathsf{M o O}_{3}/\\mathsf{A g}$ . In these systems, \\~L ZnO precursor solution was firstly dripped on ITO substrates and spin-coated at $3000{\\mathrm{rpm}}$ for $30{\\mathsf{s}}_{\\mathrm{.}}$ , followed by thermal annealing on a hot plate at $200^{\\circ}\\mathrm{C}$ for $30\\mathrm{min}$ . Then, the substrates were transferred into a glovebox filled with nitrogen $(0_{2}<10$ ppm; ${\\mathsf{H}}_{2}\\mathbf{O}<10$ ppm). The total concentrations of these two systems are $22\\mathrm{mg/mL}$ $(\\mathrm{D}{\\cdot}\\mathbf{A}=\\mathbf{1}{\\cdot}\\mathbf{1}.2),$ , with chlorobenzene as solvent. \n\nThe concentration of DIO is $1\\%(\\mathsf{v}/\\mathsf{v})$ and the concentration of TCB is $15\\mathrm{mg/mL}$ . The thickness of the active layer was controlled at around $110\\mathsf{n m}$ , then the active layers experienced a process of thermal annealing at $100^{\\circ}\\mathrm{C}$ for $5\\mathrm{{min}}$ . Finally, these semi-finished cells were transferred into a thermal evaporation chamber with a base pressure of ${\\sim}2\\times10^{-4}\\mathsf{P a}$ , where $8\\mathsf{n m}\\mathsf{M o O}_{3}$ and $100{\\mathsf{n m}}\\mathsf{A g}$ were deposited. All devices were tested with a metal mask whose area is $\\scriptstyle\\mathtt{\\sim}6.1\\mathsf{m m}^{2}$ . The current density–voltage $\\left(J-V\\right)$ curves of OSCs were tested by a Keithley 2400 source meter and an AAA grade solar simulator (SS-F7-3A, Enli Tech. Co., Ltd., Taiwan) along with AM 1.5 G spectra whose intensity was corrected by a standard silicon solar cell at $1000\\mathsf{W}/\\mathsf{m}^{2}$ . The $J{-}V$ curves are measured in the forward direction from $-0.2$ to $1.2\\mathrm{V}$ The external quantum efficiency (EQE) was measured by a certified incident photon to electron conversion (IPCE) equipment (QE-R) from Enli Technology Co., Ltd. \n\n# DSC and TGA \n\nThe thermogravimetric analysis (TGA) was carried out on a Mettler Toledo TGA/DSC 1 thermogravimetric analyzer with a thermal balance under the protection of nitrogen. Differential scanning calorimetry (DSC) test was carried out on Thermal Analysis System DSC 3 (Mettler Toledo), and the data we used is from the second scan because the first-scan data may be influenced by other factors like residual solvents and the thermal history of the polymer. \n\n# SCLC mobility measurements \n\nElectron-only devices with the structure of ITO/ZnO/PFN-Br/active layer/PFN-Br/Ag and hole-only devices with the structure of ITO/ $\\mathsf{M o o}_{3}$ /active layer/ $\\mathsf{M o O}_{3}/\\mathsf{A g}$ are used to conduct SCLC measurements. The mobilities were determined by fitting the dark-field current density-voltage curves using the Mott-Gurney relationship, which is described in the following equation, \n\n$$\n\\mathsf{J}(\\mathsf{V})=\\frac{9}{8}\\varepsilon_{0}\\varepsilon_{r}\\mu_{0}\\frac{V^{2}}{L^{3}}\n$$ \n\nwhere J is the current density, $\\ensuremath{\\varepsilon}_{0}$ is the permittivity of free space, $\\ensuremath{\\varepsilon}_{r}$ is the relative permittivity of the material, $\\mu_{0}$ is the zero-field mobility, V is the effective voltage and L is the thickness of the active layer. From the plot of $J^{\\prime2}$ versus $\\boldsymbol{V},$ the hole and electron mobilities can be deduced. \n\n# AFM and GIWAXS \n\nThe atomic force microscopic (AFM) images were acquired using a Bruker Dimension EDGE in tapping mode. GIWAXS measurements were carried out with a Xeuss 2.0 SAXS/WAXS laboratory beamline using a Cu X-ray source $(8.05\\mathrm{keV},1.54\\mathring{\\mathrm{A}})$ and Pilatus3R 300 K detector. The incidence angle is $0.2^{\\circ}$ . \n\n# TPV measurements \n\nTPV is tested under the open-circuit and 1 sun intensity background light condition to explore the photovoltage decay. The subsequent voltage decay is then recorded by the digital storage oscilloscope to directly monitor charge carrier recombination. The intensity of light is $230\\upmu\\mathrm{W}/\\mathrm{cm}^{2}$ and the wavelength of light is ${520}\\ensuremath{\\mathrm{nm}}$ . The light pulse is 10 ns. The normalized curves are easier to compare the decay time and the slower decline one is the one with a longer lifetime. The photovoltage decay kinetics of all devices follow a mono-exponential decay: $\\delta{\\sf V}={\\sf A e x p}(\\cdot t/\\tau)$ where $t$ is the time, and $\\tau$ is the decay time. The fitted decay time would not be affected by the A value, thus the TPV curves are normalized. \n\n# Highly sensitive EQE and $\\mathbf{EQE_{EL}}$ measurements \n\nHighly sensitive EQE was measured using an integrated system (PECT600, Enlitech), where the photocurrent was amplified and modulated by a lock-in instrument. $\\mathsf{E Q E}_{\\mathtt{E L}}$ measurements were performed by applying external voltage/current sources through the devices (ELCT3010, Enlitech). \n\n# The calculation processes of $\\pmb{{\\cal E}}_{t o s s}$ \n\nThe equations used for $E_{l o s s}$ calculation are described as follow: 1. Radiative recombination above the bandgap $(\\varDelta E_{I})$ \n\n$$\n\\Delta E_{1}=E_{g}-q V_{O C}^{S Q}\n$$ \n\n$$\nV_{O C}^{S Q}=\\frac{k T}{q}\\mathrm{ln}\\left(\\frac{J_{S C}}{J_{0}^{S Q}}+1\\right)=\\frac{k T}{q}\\mathrm{ln}\\left(\\frac{q\\int_{0}^{\\infty}{E Q E_{P V}(E)\\mathcal{Q}_{A M1.S}(E)d E}}{q\\int_{E_{g}}^{\\infty}{\\mathcal{Q}_{B B}(E)d E}}+1\\right)\n$$ \n\n$$\n\\displaystyle\\mathcal{O}_{B B}(E)=\\frac{2\\pi}{h^{3}c^{2}}E^{2}\\mathbf{e}^{-\\frac{E}{K T}}\n$$ \n\n2. Radiative recombination below the bandgap $(\\varDelta E_{2})$ \n\n$$\n\\Delta E_{2}=E_{l o s s,r a d}=q V_{O C}^{S Q}-q V_{O C}^{r a d}\n$$ \n\n$$\nV_{O C}^{r a d}=\\frac{k T}{q}\\ln\\left(\\frac{J_{S C}}{J_{0}^{r a d}}+1\\right)=\\frac{k T}{q}\\ln\\left(\\frac{q\\int_{0}^{\\infty}E Q E_{P V}(E)\\mathcal{Q}_{A M1.S}(E)d E}{q\\int_{E_{0}}^{\\infty}\\mathcal{Q}_{B B}(E)d E}+1\\right)\n$$ \n\n3. Non-radiative recombination loss $(\\varDelta E_{3})$ \n\n$$\n\\Delta E_{3}=E_{l o s s,n o n-r a d}=\\ -\\frac{k T}{q}\\mathsf{l n}E Q E_{E L}\n$$ \n\n$$\n\\Delta E_{3}^{c a l}=E_{g}-q V_{O C}-\\Delta E_{1}-\\Delta E_{2}\n$$ \n\nwhere $\\mathsf{E}_{\\mathrm{g}},\\mathsf{V}_{\\mathrm{OC}}^{\\mathrm{SQ}},k,T,\\mathsf{q},\\bigotimes_{\\mathsf{B B}}$ , and $\\ensuremath{\\mathsf{V}}_{\\mathrm{OC}}^{\\mathrm{rad}}$ are energy bandgap, ShockleyQueisser (SQ) open-circuit voltage limit, the Boltzmann constant, the \n\ntemperature, the elementary charge, the black body spectrum and radiative recombination open-circuit voltage limit. \n\n# Reporting summary \n\nFurther information on research design is available in the Nature Portfolio Reporting Summary linked to this article. \n\n# Data availability \n\nThe data that support the findings of this study are presented in Supplementary Information. And the source data underlying Figs. 2b, 3h, 4c, f, 6a, b, g, and Supplementary Figs. 3, 5, 12, as well as Tables 1, 3 and Supplementary Tables 1 and 2 are provided in Source Date file with this paper or available from the corresponding author on request. Source data are provided with this paper. \n\n# References \n\n1. Lin, Y. et al. An electron acceptor challenging fullerenes for efficient polymer solar cells. Adv. Mater. 27, 1170–1174 (2015). \n2. Yuan, J. et al. Enabling low voltage losses and high photocurrent in fullerene-free organic photovoltaics. Nat. Commun. 10, 570 (2019). \n3. Yuan, J. et al. Single-junction organic solar cell with over $15\\%$ efficiency using fused-ring acceptor with electron-deficient core. Joule 3, 1140–1151 (2019). \n4. Li, C. et al. Non-fullerene acceptors with branched side chains and improved molecular packing to exceed $18\\%$ efficiency in organic solar cells. Nat. Energy 6, 605–613 (2021). \n5. Liu, Q. et al. $18\\%$ efficiency organic solar cells. Sci. Bull. 65, 272–275 (2020). \n6. An, Q. et al. Two compatible polymer donors contribute synergistically for ternary organic solar cells with $17.53\\%$ efficiency. Energy Environ. Sci. 13, 5039–5047 (2020). \n7. Zhang, M. et al. Single-layered organic photovoltaics with double cascading charge transport pathways: $18\\%$ efficiencies. Nat. Commun. 12, 309 (2021). \n8. Song, J. et al. High-efficiency organic solar cells with low voltage loss induced by solvent additive strategy. Matter 4, 2542–2552 (2021). \n9. Zhang, T. et al. A thiadiazole-based conjugated polymer with ultradeep HOMO level and strong electroluminescence enables $18.6\\%$ efficiency in organic solar cell. Adv. Energy Mater. 11, 2101705 (2021). \n10. Cai, Y. et al. A well-mixed phase formed by two compatible nonfullerene acceptors enables ternary organic solar cells with efficiency over $18.6\\%$ . Adv. Mater. 33, 2101733 (2021). \n11. Bi, P. et al. Reduced non-radiative charge recombination enables organic photovoltaic cell approaching $19\\%$ efficiency. Joule 5, 2408–2419 (2021). \n12. Gillett, A. J. et al. The role of charge recombination to triplet excitons in organic solar cells. Nature 597, 666–671 (2021). \n13. Liang, Y. et al. For the bright future—bulk heterojunction polymer solar cells with power conversion efficiency of $7.4\\%$ . Adv. Mater. 22, E135–E138 (2010). \n14. Zhang, Y. et al. Graded bulk-heterojunction enables $17\\%$ binary organic solar cells via nonhalogenated open air coating. Nat. Commun. 12, 4815 (2021). \n15. Li, G. et al. High-efficiency solution processable polymer photovoltaic cells by self-organization of polymer blends. Nat. Mater. 4, 864–868 (2005). \n16. Chu, C.-W. et al. Control of the nanoscale crystallinity and phase separation in polymer solar cells. Appl. Phys. Lett. 92, 103306 (2008). \n17. Lee, J. K. et al. Processing additives for improved efficiency from bulk heterojunction solar cells. J. Am. Chem. Soc. 130, 3619–3623 (2008). on poly (3‐hexylthiophene) and methanofullerenes. Adv. Funct. Mater. 17, 1636–1644 (2007). \n19. Yan, C. et al. Reducing $\\mathsf{V}_{\\mathrm{OC}}$ loss via structure compatible and high lowest unoccupied molecular orbital nonfullerene acceptors for over $17\\%$ -efficiency ternary organic photovoltaics. EcoMat 2, e12061 (2020). \n20. Zhang, Y. et al. A novel wide-bandgap polymer with deep ionization potential enables exceeding $16\\%$ efficiency in ternary nonfullerene polymer solar cells. Adv. Funct. Mater. 30, 1910466 (2020). \n21. Lv, J. et al. Additive-induced miscibility regulation and hierarchical morphology enable $17.5\\%$ binary organic solar cells. Energy Environ. Sci. 14, 3044–3052 (2021). \n22. Cui, Y. et al. Single-junction organic photovoltaic cells with approaching $18\\%$ efficiency. Adv. Mater. 32, 1908205 (2020). \n23. Huang, J., Tang, H., Yan, C. & Li, G. 1, 1-dicyanomethylene-3- indanone end-cap engineering for fused-ring electron acceptorbased high-performance organic photovoltaics. Cell Rep. Phys. Sci. 2, 100292 (2021). \n24. Tang, H. et al. Benzodithiophene-based small-molecule donors for next-generation all-small-molecule organic photovoltaics. Matter 3, 1403–1432 (2020). \n25. He, Q. et al. Revealing morphology evolution in highly efficient bulk heterojunction and pseudo‐planar heterojunction solar cells by additives treatment. Adv. Energy Mater. 11, 2003390 (2021). \n26. Yu, R. et al. Design and application of volatilizable solid additives in non-fullerene organic solar cells. Nat. Commun. 9, 4645 (2018). \n27. Yu, R. et al. Enhanced π–π interactions of nonfullerene acceptors by volatilizable solid additives in efficient polymer solar cells. Adv. Mater. 31, 1900477 (2019). \n28. Huang, Y. et al. Reducing aggregation caused quenching effect through co-assembly of PAH chromophores and molecular barriers. Nat. Commun. 10, 169 (2019). \n29. Fu, J. et al. A “σ-Hole”-containing volatile solid additive enabling $16.5\\%$ efficiency organic solar cells. iScience 23, 100965 (2020). \n30. Brinkmann, M. & Wittmann, J. C. Orientation of regioregular poly (3‐ hexylthiophene) by directional solidification: a simple method to reveal the semicrystalline structure of a conjugated polymer. Adv. Mater. 18, 860–863 (2006). \n31. Brinkmann, M. & Rannou, P. Effect of molecular weight on the structure and morphology of oriented thin films of regioregular poly (3‐hexylthiophene) grown by directional epitaxial solidification. Adv. Funct. Mater. 17, 101–108 (2007). \n32. Kruefu, V., Khantha, C., Pookmanee, P. & Phanichphant, S. Improvement of the solar efficiency of polymer solar cells by using 1, 3, 5-trichlorobenzene as co-solvent. Mol. Cryst. Liq. Cryst. 566, 170–174 (2012). \n33. Fu, J. et al. Eutectic phase behavior induced by a simple additive contributes to efficient organic solar cells. Nano Energy 84, 105862 (2021). \n34. Kyaw, A. K. K. et al. Intensity dependence of current–voltage characteristics and recombination in high-efficiency solution-processed small-molecule solar cells. ACS Nano 7, 4569–4577 (2013). \n35. Zhang, K. et al. Efficient large area organic solar cells processed by blade-coating with single-component green solvent. Sol. RRL 2, 1700169 (2018). \n36. Lin, J. D., Mikhnenko, O. V., van der Poll, T. S., Bazan, G. C. & Nguyen, T. Q. Temperature dependence of exciton diffusion in a small‐ molecule organic semiconductor processed with and without additive. Adv. Mater. 27, 2528–2532 (2015). \n37. Yaws, C. L. The Yaws handbook of vapor pressure: Antoine coefficients. (Gulf Professional Publishing, 2015). \n38. Mackay, D., Bobra, A., Chan, D. W. & Shiu, W. Y. Vapor-pressure correlations for low-volatility environmental chemicals. Environ. Sci. Technol. 16, 645–649 (1982). \n39. Sprau, C. et al. Highly efficient polymer solar cells cast from nonhalogenated xylene/anisaldehyde solution. Energy Environ. Sci. 8, \n2744–2752 (2015). \n40. Melzer, C., Koop, E. J., Mihailetchi, V. D. & Blom, P. W. Hole transport in poly (phenylene vinylene)/methanofullerene bulk-heterojunction solar cells. Adv. Funct. Mater. 14, 865–870 (2004). \n41. Rau, U., Blank, B., Müller, T. C. & Kirchartz, T. Efficiency potential of photovoltaic materials and devices unveiled by detailed-balance analysis. Phys. Rev. Appl. 7, 044016 (2017). \n42. Shockley, W. & Queisser, H. J. Detailed balance limit of efficiency of p-n junction solar cells. J. Appl. Phys. 32, 510–519 (1961). \n43. Nikolis, V. C. et al. Reducing voltage losses in cascade organic solar cells while maintaining high external quantum efficiencies. Adv. Energy Mater. 7, 1700855 (2017). \n44. Zhang, M. et al. High-efficiency organic photovoltaics using eutectic acceptor fibrils to achieve current amplification. Adv. Mater. 33, 2007177 (2021). \n45. Shi, M.-M. et al. π−π interaction among violanthrone molecules: observation, enhancement, and resulting charge transport properties. J. Phys. Chem. B 115, 618–623 (2011). \n46. Hao, Q. et al. Enhanced photochemical oxidation ability of carbon nitride by π–π stacking interactions with graphene. Chin. J. Catal. \n38, 278–286 (2017). \n47. Luo, Z. et al. Altering the positions of chlorine and bromine substitution on the end group enables high-performance acceptor and efficient organic solar cells. Adv. Energy Mater. 10, 2002649 (2020). \n48. Mcdowell, C., Abdelsamie, M., Toney, M. F. & Bazan, G. C. Solvent additives: key morphology-directing agents for solution-processed organic solar cells. Adv. Mater. 30, 1707114 (2018). \n49. Chen, H. et al. All-small-molecule organic solar cells with an ordered liquid crystalline donor. Joule 3, 3034–3047 (2019). \n50. Wu, J. et al. Random terpolymer based on thiophenethiazolothiazole unit enabling efficient non-fullerene organic solar cells. Nat. Commun. 11, 4612 (2020). \n51. Zhao, W. et al. Fullerene-free polymer solar cells with over $11\\%$ efficiency and excellent thermal stability. Adv. Mater. 28, \n4734–4739 (2016). \n52. Zhang, S., Qin, Y., Zhu, J. & Hou, J. Over $14\\%$ efficiency in polymer solar cells enabled by a chlorinated polymer donor. Adv. Mater. 30, \n1800868 (2018). \n53. Du, X. et al. Unraveling the microstructure-related device stability for polymer solar cells based on nonfullerene small-molecular acceptors. Adv. Mater. 32, 1908305 (2020). \n54. Sun, R. et al. Single-junction organic solar cells with $19.17\\%$ efficiency enabled by introducing one asymmetric guest acceptor. Adv. Mater. 34, 2110147 (2022). \n55. Zhan, L. et al. Desired open-circuit voltage increase enables efficiencies approaching $19\\%$ in symmetric-asymmetric molecule ternary organic photovoltaics. Joule 6, 662–675 (2022). \n\n# Acknowledgements \n\nG.L. thanks the Research Grants Council of Hong Kong (GRF grant 15211320, CRF C5037-18G, SRFS RGC Senior Research Fellowship Scheme (SRFS2122-5S04)), National Science Foundation of China (NSFC 51961165102), Hong Kong Polytechnic University (the Sir Szeyuen Chung Endowed Professorship Fund (8-8480), RISE (Q-CDA5), GSAC5), and Guangdong-Hong Kong-Macao Joint Laboratory for Photonic-Thermal-Electrical Energy Materials and Devices (GDSTC No. 2019B121205001). T.K. thanks the German Research Foundation (DFG) for funding (Fellowship No. KO6414). M.A. acknowledges support by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Contract No. DE-AC02-05-CH 11231 (D2S2 program KCD2S2). Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under \n\nContract No. DE-AC02-05-CH 11231. This research used resources from the Advanced Light Source, which is a DOE Office of Science User Facility under contract no. DE-AC02-05CH11231 (beamline 12.3.2). \n\n# Author contributions \n\nG.L. and J.F. conceived the study. J.F. fabricated the devices and performed most of the characterizations and analysis. P.F. conducted in situ UV-vis characterization. H.L. and X.L. performed ex-situ GISAXS measurements. S.L. assisted AFM measurements. C.H., M.A., T.K., and C.M.S.-F. facilitated and helped with in situ GIWAXS measurements at the Advanced Light Source for the revision of the paper. G.L. and Y.Y. guided the study and supervised the execution. The manuscript is prepared, revised, and finalized by J.F., Y.Y., and G.L. All authors discussed the results and commented on the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\nAdditional information \nSupplementary information The online version contains supplementary material available at \nhttps://doi.org/10.1038/s41467-023-37526-5. \n\nCorrespondence and requests for materials should be addressed to Yang Yang or Gang Li. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 " + }, + { + "id": "10.1038_s41560-023-01255-2", + "DOI": "10.1038/s41560-023-01255-2", + "DOI Link": "http://dx.doi.org/10.1038/s41560-023-01255-2", + "Relative Dir Path": "mds/10.1038_s41560-023-01255-2", + "Article Title": "Silicon heterojunction solar cells with up to 26.81% efficiency achieved by electrically optimized nullocrystalline-silicon hole contact layers", + "Authors": "Lin, H; Yang, M; Ru, XN; Wang, GS; Yin, S; Peng, FG; Hong, CJ; Qu, MH; Lu, JX; Fang, L; Han, C; Procel, P; Isabella, O; Gao, PQ; Li, ZG; Xu, XX", + "Source Title": "NATURE ENERGY", + "Abstract": "Improvements in the power conversion efficiency of silicon heterojunction solar cells would consolidate their potential for commercialization. Now, Lin et al. demonstrate 26.81% efficiency devices using a p-doped nullocrystalline silicon and low-sheet-resistance transparent conductive oxide contact layer. Silicon heterojunction (SHJ) solar cells have reached high power conversion efficiency owing to their effective passivating contact structures. Improvements in the optoelectronic properties of these contacts can enable higher device efficiency, thus further consolidating the commercial potential of SHJ technology. Here we increase the efficiency of back junction SHJ solar cells with improved back contacts consisting of p-type doped nullocrystalline silicon and a transparent conductive oxide with a low sheet resistance. The electrical properties of the hole-selective contact are analysed and compared with a p-type doped amorphous silicon contact. We demonstrate improvement in the charge carrier transport and a low contact resistivity (<5 m ohm cm(2)). Eventually, we report a series of certified power conversion efficiencies of up to 26.81% and fill factors up to 86.59% on industry-grade silicon wafers (274 cm(2), M6 size).", + "Times Cited, WoS Core": 347, + "Times Cited, All Databases": 357, + "Publication Year": 2023, + "Research Areas": "Energy & Fuels; Materials Science", + "UT (Unique WOS ID)": "WOS:000984178200002", + "Markdown": "# Silicon heterojunction solar cells with up to 26.81% efficiency achieved by electrically optimized nanocrystalline-silicon hole contact layers \n\nHao Lin    1,2,4, Miao Yang1,4, Xiaoning $\\mathsf{R u}^{1,4}$ , Genshun Wang1,2, Shi Yin    1  , Fuguo Peng1, Chengjian Hong1, Minghao Qu1, Junxiong Lu1, Liang Fang1, Can Han2,3, Paul Procel    3, Olindo Isabella    3, Pingqi Gao    2  , Zhenguo Li1 & Xixiang Xu    1 \n\nSilicon heterojunction (SHJ) solar cells have reached high power conversion efficiency owing to their effective passivating contact structures. Improvements in the optoelectronic properties of these contacts can enable higher device efficiency, thus further consolidating the commercial potential of SHJ technology. Here we increase the efficiency of back junction SHJ solar cells with improved back contacts consisting of p-type doped nanocrystalline silicon and a transparent conductive oxide with a low sheet resistance. The electrical properties of the hole-selective contact are analysed and compared with a p-type doped amorphous silicon contact. We demonstrate improvement in the charge carrier transport and a low contact resistivity $(<5\\mathsf{m}\\Omega\\mathsf{c m}^{2})$ . Eventually, we report a series of certified power conversion efficiencies of up to $26.81\\%$ and fill factors up to $86.59\\%$ on industry-grade silicon wafers $(274\\thinspace\\mathrm{cm}^{2}$ , M6 size). \n\nPhotovoltaic (PV) solar cells are one of the main renewable energy sources with zero operating carbon emissions; driven by ambitious carbon neutral policies worldwide, they are quickly becoming a mainstream energy supply. To a large extent, power conversion efficiency (PCE) determines whether a PV technology is competitive. Wafer-based crystalline silicon (c-Si) solar cells are the dominant technology in the global PV market. Aiming at a higher PCE, technology iteration is occurring from the passivated emitter and rear cell (PERC) to tunnel oxide passivated contact (TOPCon) and silicon heterojunction (SHJ) solar cells1–7. \n\nSHJ technology employs an n-type (p-type) doped hydrogenated amorphous silicon (a-Si:H) layer, called n-a-Si:H (p-a-Si:H), as the electron-selective contact layer (ESC)–hole-selective contact layer (HSC). This overlays the intrinsic hydrogenated amorphous silicon (i-a-Si:H) layer, providing high-quality chemical passivation and minimizing the deficit in open circuit voltage $(V_{\\mathrm{oc}})^{8-13}$ . The electrical performance of the solar cells depends strongly on the net doping of both the ESC and HSC layers. This is particularly relevant to the HSC layer, which is the emitter in SHJ solar cells based on n-type wafers. A sufficiently high doping concentration produces favourable band bending, allowing holes (minority carriers) to tunnel (selective collection of holes); efficient field-effect passivation, repelling electrons from the interface and mitigating the resulting interface recombination; and a reduced energy barrier when directly in contact with the n-type transparent conducting oxide (TCO)14–16. However, doped a-Si:H layers are always limited by unsatisfying electrical conductivity $(\\sigma{<}10^{-4}\\mathsf{S}\\mathsf{c m}^{-1})$ and relatively high activation energy $(E_{\\mathrm{a}}>250\\mathrm{meV})$ , which cause high contact resistivity in SHJ solar cells17–20. \n\nIn contrast to defect-rich amorphous silicon, hydrogenated nanocrystalline silicon (nc-Si:H) dramatically improves film crystallinity, which straightforwardly favours the improvement of carrier mobility and effective doping concentration. However, depositing a sufficiently thin layer of highly crystalline nc-Si:H on amorphous surfaces at low temperature is challenging. Depositing p-type doped nc-Si:H (p-nc-Si:H) is even more difficult, as boron doping restricts grain growth. Sophisticated techniques from deposition engineering, including pretreatment methods, adjusting deposition parameters (pressure, temperature, power, frequency and silane dilution) and posttreatment, help to address these issues21–25. For example, researchers discovered that ${\\mathsf{C O}}_{2}$ treatment facilitates fast nucleation for the growth of nanocrystalline silicon film26. High crystalline volume fraction $(X_{\\mathrm{c}})$ —up to $50\\%$ —has been reported by several groups through finetuning gas flow rates21,25. Umishio et al.27 found a clear relation between the nanostructure evolution of the p-nc-Si:H layers and their electrical properties and resulting performance. They concluded that surface coalescence of the $\\boldsymbol{\\mathsf{p}}$ -nc-Si:H nanocrystals, rather than doping concentration, dominantly determines the $E_{\\mathrm{a}}$ of the $\\mathbf{film}^{27}$ . In other words, hole selectivity and hole transport through the TCO– $\\mathfrak{p}$ -nc-Si:H contact and hence, the solar cell’s $V_{\\mathrm{oc}}$ and fill factor (FF) are crucially influenced by the electrical contact properties between TCO and the crystalline phase at the surface of the p-nc-Si:H layer19. Based on this understanding, the contact resistivity of p-nc-Si:H-based HSCs has been reduced to about $100\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ , yielding a series resistance $(R_{\\mathrm{S}})$ of $0.65\\textbar{\\textperthousand}$ $1.3\\Omega\\mathrm{cm}^{2}$ and a $23\\mathrm{-}25\\%$ PCE (Supplementary Table 1)27–31. Nevertheless, realizing the advantageous electrical properties of SHJ solar cells over their TOPCon counterparts still poses a challenge, and the opportunity to unlock the full potential of SHJ technology remains open. \n\nIn this contribution, we report the successful introduction of nanocrystallization processes for fabricating cutting-edge HSCs, which—when paired with correspondingly tailored TCO—result in improved PCEs and FFs on wafer-scale single-junction SHJ solar cells. We demonstrate a $26.30\\%$ SHJ solar cell with an FF of $86.59\\%$ ; to the best of our knowledge, this FF outperforms any other silicon solar cell. By reducing the shading ratio from 2.8 to $2.0\\%$ and modifying the window layers at the front to minimize the parasitic absorption, we further boost the PCE to $26.74\\%$ by increasing the short-circuit current density $(\\boldsymbol{J_{\\mathrm{SC}}})$ to $41.16\\mathsf{m A c m}^{-2}$ . Finally, by introducing an additional reflective $\\mathsf{M g F}_{2}/\\mathsf{A g}$ stack at the rear side and regulating the transmittance of TCO, we achieve a PCE of $26.81\\%$ with $\\mathsf{a}J_{\\mathrm{sc}}$ of $41.45\\mathsf{m A c m^{-2}}$ . Investigation of the power and series resistance losses reveals outstanding performance of these HSCs, with reduced contact resistivity $(\\rho_{\\mathrm{c}}<5\\mathsf{m}\\Omega\\mathsf{c m}^{2})$ and improved passivation (recombination current density $\\prime J_{0}{=}0.5\\mathsf{f A c m}^{-2})$ ). Structural and electrical characterizations of the p-nc-Si:H indicate high $\\chi_{\\mathrm{c}}(63\\%)$ , ultralow $E_{\\mathrm{a}}(<115\\mathrm{meV})$ and excellent $\\sigma(>3\\mathsf{S c m}^{-1})$ , which is four orders of magnitude higher than that of the traditional p-a-Si:H $\\mathbf{film}^{32,33}$ . HSCs endowed with these electrical improvements easily trigger band-to-band tunnelling (BTBT) transport behaviour and induce a sharp band bending, enhancing hole extraction efficiency. \n\n# Efficiency increase analysis of SHJ solar cells \n\nIn mass production, the competition between SHJ and TOPCon techno­ logies is fierce. As can be seen from Fig. 1a, SHJ solar cells feature greater electrical performance measured by $V_{\\mathrm{oc}}\\times\\mathsf{F F},$ while TOPCon and PERC hold relatively superior $J_{\\mathrm{SC}}$ . The inferior $J_{\\mathrm{sc}}$ of SHJ solar cells can be attri­ buted to the strong parasitic absorption inherent in the functional layers at the front side; PERC and TOPCon usually yield higher $J_{\\mathrm{sc}}$ $(>41\\mathsf{m A}\\mathsf{c m}^{-2})$ ) due to the use of conventionally diffused front junctions and optically transparent antireflective coatings34. Benefiting from the unique design of rear-sided passivating contact with an $\\mathsf{S i O}_{x}{\\mathrm{\\Omega}}$ poly-Si(n+) stack, TOPCon wins out over PERC with intrinsically improved $V_{\\mathrm{oc}}$ (ref. 35). SHJ produces the highest $V_{\\mathrm{oc}}$ among the c-Si solar cell technologies because of the excellent surface passivation provided by the i-a-Si:H layers. Figure 1b illustrates the FF versus $V_{\\mathrm{{oc}}}$ of different solar cell technologies, in which one can clearly see the superior FF of SHJ solar cells as compared with that of PERC and TOPCon devices. \n\nIn Fig. 1b, the lines corresponding to the Green limits36 for different ideal factors $(n)$ are indicated as well. The value of the ideality factor of a c-Si cell is based on the recombination mechanism: $n=2/3$ for Auger recombination and $n=1$ for Shockley–Read–Hall (SRH) and band-to-band recombination at low injection level. Combining high-quality c-Si wafers with the superior surface passivation we obtained, the intrinsic recombination of SHJ solar cells becomes dominant. In the case of Auger recombination at high injection level, the ideality factor value of our SHJ cells is found to be lower than one. The reduction in ideality factor causes a more square shape in the –V curve, leading to a remarkable improvement in FF. \n\nAs indicated in Fig. 1, the performance of SHJ solar cells has increased almost linearly both electrically and optically. The first SHJ solar cell from our group (LONGi) delivered a PCE of $25.26\\%$ (ref. 37), and we have now further boosted all the PV parameters. In this work, we show a PCE of $26.81\\%$ , with $V_{\\mathrm{{oc}}}$ of $751.4\\mathrm{{mV}}$ (an improvement of $2.9\\mathrm{mV})$ , FF of $86.07\\%$ 1 $0.57\\%$ improvement) and $J_{\\mathrm{SC}}$ of $41.45\\mathsf{m A c m^{-2}}$ (an improvement of $\\mathbf{\\widetilde{1.97}m A c m^{-2}},$ , an overall efficiency gain of $1.55\\%$ . Note that we achieved the highest FF of $86.59\\%$ on a different device: that is, the cell delivering an efficiency of $26.30\\%$ . Theoretical predictions yield a similar trend, as shown by the blue to red gradient solid line in Fig. 1b. Radiative, Auger and surface recombinations were taken into consideration in the calculation, while additional $R_{\\mathrm{{s}}}$ and shunt resistance $(R_{\\mathrm{sh}})$ were not included. The improvement of LONGi’s SHJ solar cells follows the overall tendency apart from small deviations in practical and calculated FF, which are mainly attributed to the advance in reduction of $R_{\\mathrm{s}}$ . Note that the measurement approach (Methods) excludes some $R_{\\mathrm{{s}}}$ components, such as the resistance of the grid at the rear side and of the bus bars at the front side. We found that ultrahigh FF only occurs at extremely low $R_{\\mathrm{{s}}}$ and furthermore, requires high-quality passivation: that is, high $V_{\\mathrm{oc}}$ . This is why LONGi SHJ solar cells possess a prominent advantage in electrical performance $(V_{\\mathrm{oc}}\\times\\mathsf{F F})$ (Fig. 1a) over PERC and TOPCon cells. Limited by insufficient passivation, the positive effect of reduced $R_{\\mathrm{s}}$ on FF cannot be fully unlocked for PERC and TOPCon cells. \n\nTo reveal the main contributions to the efficiency increase, two related designs with p-a-Si:H (cell 1, $25.26\\%$ PCE) and p-nc-Si:H (cell 2, $26.30\\%$ serving as the rear emitter are investigated with the Quokka2 software38,39. For the sake of simplicity, hereafter we name cell 1 and cell 2 as p-a-Si:H cell and p-nc-Si:H cell, respectively. Numerical simula­ tions and fits to experimental data of ${\\bf\\ddot{\\it R}}_{\\mathrm{s}}$ and power loss analysis (PLA) are shown in Fig. 2. Figure 2a shows the structure of the LONGi SHJ solar cells; the parameter variations between the p-a-Si:H cell and p-nc-Si:H cell are listed in Supplementary Table 3. The two devices are in a front and back contact architecture on an n-type c-Si (n-Si) wafer with front-sided n-type nanocrystalline silicon oxide $(\\boldsymbol{\\mathrm{n}}{\\cdot}\\boldsymbol{\\mathrm{n}}\\mathbf{c}{\\cdot}\\mathbf{S}\\mathbf{i}0_{x}{:}\\mathbf{H})$ and a back junction (BJ). Using BJ structure alleviates the electrical requirements on the front-side TCO and metal electrodes since a large portion of the majority carriers (electrons) can be laterally collected via the n-Si wafer absorber40. The main difference between the two solar cells comes from the BJ stacks; the p-nc-Si:H cell features p-nc-Si:H and a tailored TCO with a sheet resistance of $40\\Omega$ per sqaure, while the p-a-Si:H cell features p-a-Si:H and a TCO with a sheet resistance of $80\\Omega$ per square. Due to the excellent $\\sigma$ and $E_{\\mathrm{a}}$ of p-nc-Si:H, the rear contact resistivity is reduced, which will be discussed in the next section. \n\nFigure 2b,c shows the experimental and fitted J–V curves of their related cells. The experimental curves include the real-light J–V curve (blue triangles) and the pseudo-light J–V curve tested by a Suns– $V_{\\mathrm{oc}}$ measurement (blue circles). The fitted J–V curves were simulated by Quokka2 (refs. 38,39). Input parameters were determined \n\n![](images/ce0d4a75fc080e8677245c6cf0b332d20b1c05b03dd123b1f35bc76cd57469ff.jpg) \nFig. 1 | Comparison of PV parameters of high-efficiency silicon solar cells. a, Measured PCEs of different high-performance c-Si solar cell technologies, including n-type wafer SHJ solar cells (n-SHJ) reported by LONGi and Hanergy, TOPCon solar cells reported by LONGi, Jinko and Fraunhofer ISE (FhG-ISE) and PERC solar cells based on p-type wafer (p-PERC) reported by LONGi and University of New South Wales (UNSW), overlaid on efficiency curves as a function of electrical $(V_{\\mathrm{oc}}\\times\\mathsf{F F})$ and optical $(\\boldsymbol{J}_{\\mathrm{sc}})$ performances and normalized by the Shockley–Queisser (SQ) limit of a c-Si cell under standard test conditions. The raw data are provided in Supplementary Table 2. The upper limits of the electrical contribution and Richter limit as a function of $\\mathrm{\\Delta}\\mathcal{J}_{\\mathrm{SC}}$ are shown for wafer thicknesses of $130\\upmu\\mathrm{m}$ (the wafer thickness of SHJ solar cells in this paper) and \n\n$110\\upmu\\mathrm{m}$ (the ideal wafer thickness for approaching the theoretical limiting efficiency of $29.43\\%)^{65,71}$ . b, Detailed distributions of measured PCEs of different high-performance c-Si solar cell technologies as a function of $\\boldsymbol{V_{\\mathrm{oc}}}$ and FF. The Green limit36 with ideality factor $n=2/3$ $_{n=1)}$ , assuming a one-diode model and without considering the effects of ${\\bf\\ddot{\\it R}}_{\\mathrm{s}}$ and $R_{\\mathrm{sh}}.$ is drawn with a blue (red) dotted line. The blue to red gradient solid line is derived by theoretical calculation (same as the calculation in Supplementary Fig. 1) contributed from only intrinsic and surface recombination for devices with n-Si wafers of $130\\upmu\\mathrm{m}$ thick and 1.5 Ω cm resistivity. The red arrows indicate the trend towards improved efficiency in SHJ solar cells over time. LONGi cells with typical SHJ design and p-a-Si:H (p-nc-Si:H) as the rear emitter are indicated by 1 (2). \n\nby the measured sheet resistance of the TCO, the line resistance of the finger, the contact resistivity and recombination of the heterojunction. A full description of these parameters is in Supplementary Table 4. For comparison, the corresponding intrinsic light J–V curves computed from the theoretical limit in electrical performance are also shown (grey lines). Observe that the deviation between the Suns– $V_{\\mathrm{oc}}$ curve and the light J–V curve (arrows enclosed by black circles) differs between the p-a-Si:H cell and the p-nc-Si:H cell. To explain this, note that we can define a pseudo-fill factor (pFF) from a Suns– $V_{\\mathrm{{oc}}}$ curve ignoring all resistance. Both the p-a-Si:H cell and p-nc-Si:H cell have similar pFF values, which means that the difference in FF at the maximum power point (MPP) originates from a difference in the series resistance $R_{\\mathrm{s}}$ . Therefore, a smaller gap between the light and pseudolight J–V curves in the p-nc-Si:H cell indicates a smaller $R_{\\mathrm{s}}$ . \n\nTo explore how the record FF of $86.59\\%$ was achieved, we fit the $J{\\cdot}$ –V curves in Fig. 2b,c to determine power loss and series resistance, seen in Fig. 2d. The losses are divided into three regions: front ESC, bulk silicon (bulk) and rear HSC. Figure 2d also shows the series resistance determined from the power loss at MPP. From the p-a-Si:H cell to p-nc-Si:H cell, the total electrical power loss is reduced from 0.41 to $0.13\\mathsf{m w c m}^{-2}$ at the rear HSC alone; this is nearly equal to the full power loss reduction, $0.3\\mathsf{m w c m}^{-2}$ (from 1.01 to $0.71\\mathrm{mW}\\mathrm{cm}^{-2},$ . This indicates that the improvement in electrical performance comes primarily from the rear HSC (as expected). In particular, the reduction of power loss at the rear HSC is attributed to the use of $\\boldsymbol{\\mathsf{p}}$ -nc-Si:H and the updated TCO, which facilitates excellent passivation and contact performance. The series resistance analysis shows the same trend as the PLA. The total $R_{\\mathrm{s}}$ is reduced from $381\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ for the p-a-Si:H cell to $206\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ for the p-nc-Si:H cell (Supplementary Fig. 2a); this difference mostly appears at the rear HSC, at which $R_{\\mathrm{{s}}}$ is reduced from more than $130\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ to less than $20\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ (Fig. 2d). The slightly increased power loss in the bulk seen in the p-nc-Si:H cell could be caused by a small fluctuation in wafer quality. A slightly reduced $R_{\\mathrm{s}}$ of the front \n\nESC (from 47 to $41\\mathsf{m}\\Omega\\mathsf{c m}^{2}.$ ) lies in the reduction of the sheet resistance of front TCO from \\~150 to $\\mathord{\\sim}50\\Omega$ per square. Note that to ensure the credibility of the $R_{\\mathrm{s}}$ data, we measured the total $R_{\\mathrm{s}}$ at MPP with four different methods41, obtaining $R_{\\scriptscriptstyle5}=353-381{\\mathrm{m}}\\Omega{\\mathrm{cm}}^{\\scriptscriptstyle2}$ (p-a-Si:H cell) and $175{-}206\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ (p-nc-Si:H cell), as shown in Supplementary Fig. 2b. \n\n# Characterization of p-nc-Si:H \n\nAs discussed above, the implementation of p-nc-Si:H together with matched TCO leads to a dramatic reduction in the contact resistivity at the rear side, resulting in an efficiency increase to $26.30\\%$ . As this contact, the overall resistance depends mainly on the bulk resistance of p-nc-Si:H itself and on the contact resistivity at the p-nc-Si:H–TCO interface. Therefore, gaining the optimal p-nc-Si:H layer is of critical importance to achieve high-efficiency SHJ solar cells. We investigated p-nc-Si:H layers grown from different recipes; corresponding deposition conditions and characterization results are elaborated in Fig. 3 and Supplementary Table 5. We studied the structural properties of the p-a-Si:H and p-nc-Si:H layers by both Raman spectroscopy and transmission electron microscopy (TEM). The Raman measurement was carried out with a $325\\cdot\\mathsf{n m}$ laser and performed on the p-a-Si:H or p-nc-Si:H layer deposited on a planar i-a-Si:H–glass substrate. The deposition process was identical to that of the fabrication procedure for solar cells. The Raman spectra were fitted with multiple (or single) Gaussian functions, as shown in Fig. 3a. For $\\boldsymbol{\\mathsf{p}}$ -nc-Si:H, three Gaussian peaks are identified with the centres at 482, 507 and $518\\mathsf{c m}^{-1}$ , representing separately the transverse optical phonon mode of amorphous silicon and two optical vibrational modes of nanocrystalline silicon42,43. In contrast, only one peak at $478\\mathsf{c m}^{-1}$ is observed for p-a-Si:H, indicating a fully amorphous structure. $X_{\\mathrm{c}}$ is determined from the integrated intensities $(I)$ of the Gaussian peaks via equation (1) as follows44,45: \n\n$$\n\\chi_{\\mathrm{{C}}}={\\frac{I_{510\\mathrm{cm}^{-1}}+I_{520\\mathrm{cm}^{-1}}}{\\beta I_{480\\mathrm{cm}^{-1}}+I_{510\\mathrm{cm}^{-1}}+I_{520\\mathrm{cm}^{-1}}}},\n$$ \n\n![](images/f12311766b443ce126c103a68efe3eace43404094179e1ea3a53ce9c7740f65a.jpg) \nFig. 2 | Electrical performance of LONGi SHJ solar cells with different designs. a, Diagram of LONGi SHJ solar cells. b,c, Experimental (Exp.) and fitted (Fit.) $J{\\cdot}$ –V curves for the p-a-Si:H cell (b, cell 1 in Fig. 1) and the $\\mathfrak{p}$ -nc-Si:H cell (c, cell 2 in Fig. 1). The fitted curves are derived from the Quokka2 simulations (Methods). Intrinsic J–V curves are obtained according to the Richter et al. model of intrinsic recombination with photon recycling (photon recycling coefficient of $0.6)^{65,71}$ . \nThe black arrows between the Suns– $V_{\\mathrm{{oc}}}$ and light J–V curves indicate the series resistance of solar cells. Insets: the PV parameters certified by ISFH. d, PLA and corresponding $R_{\\mathrm{s}}$ at the MPP derived by fitting J–V curves in b and c; rec, recombination. The loss of intrinsic recombination is not shown, and only the $R_{\\mathrm{s}}$ at the rear is analysed. For a full analysis of ${\\bf\\ddot{\\it R}}_{\\mathrm{s}}$ , see Supplementary Fig. 2a. \n\nwhere $\\beta=0.8$ represents the ratio of the back-scattering cross-sections46. \nFor the p-nc-Si:H sample, an $X_{\\mathrm{c}}$ of $63\\%$ is obtained. \n\nThe cross-sectional TEM images of the HSCs based on p-a-Si:H and p-nc-Si:H are shown in Fig. 3b,c. The samples, namely TCO–p-nc-Si: H–i-a-Si:H–n-Si and TCO–p-a-Si:H–i-a-Si:H–n-Si, were taken by focused ion beam from as-prepared SHJ solar cells. In the TEM images, each layer in the stack is identified by its thickness, which was indivi­dually measured and confirmed by ellipsometry. In both samples, the thickness of the i-a-Si:H layer is almost same (about $6\\mathsf{n m}\\cdot$ ), while the p-nc-Si:H layer (about 21 nm) is much thicker than that of p-a-Si:H (about 5 nm). A thicker p-nc-Si:H layer is required for incubation and for the subsequent phase transition from amorphous to crystalline. The higher $X_{\\mathrm{c}}$ of the p-nc-Si:H layer is evidenced by the observation that nanocrystalline domains embedded in an amorphous phase coalesce laterally to one another. No crystalline feature is observed in the i-a-Si:H and p-a-Si:H layers. To identify nanocrystalline domains, fast Fourier transforms (FFTs) were performed on the TEM images (insets in Fig. 3b,c). In both samples, the reciprocal spots derived from the c-Si substrate are highlighted by red circles; these include high-order spots. In the p-nc-Si:H sample, additional reciprocal spots derived from nanocrystalline domains can be seen. We performed inverse FFT calculations on the FFT images, masking selected reciprocal spots, to identify the corresponding nanocrystalline domains in the TEM images. The nanocrystalline domains with different crystalline orientation in the amorphous context are labelled with different background colours, and the corresponding reciprocal spots in the FFT image are circled in the same colours. A large fraction of nanocrystalline domains is observed in the p-nc-Si:H layer, while the amorphous structure of the i-a-Si:H layer is completely intact, ensuring a well-passivated and contacted silicon surface. In practice, the growth of the p-nc-Si:H layer on i-a-Si:H film is a great technical challenge, especially for high-efficiency devices, where the crystalline phase should be localized within a thin layer to balance out detrimental parasitic absorption and resistive transport. Here, the strategy for highly crystalline p-nc-Si:H involves fast nucleation at the initial stage, which was facilitated by $\\mathbf{CO}_{2}$ plasma treatment on its underlying i-a-Si:H layer47,48, and selective removal of the amorphous fraction by the plasma with high hydrogen dilution. This led to the accumulation of dense crystallites into the a-Si:H matrix28. \n\n![](images/e72f64f445b3506573ac08a01d5b4afc5f2d699f2d96e12448a81e376bae62a3.jpg) \nFig. 3 | Electrical and microstructure characterizations as well as band alignment analysis of HSCs based on p-a-Si:H and p-nc-Si:H. a, Raman spectra collected from p-a-Si:H–i-a-Si:H–glass and p-nc-Si:H–i-a-Si:H–glass samples. Gaussian fitting (colour shaded areas) was implemented on the characteristic peaks at $478\\mathsf{c m}^{-1}$ (a-Si:H) and at 507 and $518\\mathrm{cm}^{-1}(\\mathsf{n c}{\\cdot}\\mathsf{S i}{\\cdot}\\mathsf{H})^{42,43}$ . The $X_{\\mathrm{c}}$ was calculated by equation (1). b,c, TEM images of TCO– $\\mathbf{\\sigma}\\cdot\\mathbf{p}$ -a-Si:H–i-a-Si:H–n-Si (b) and TCO– $\\mathbf{\\sigma}\\cdot\\mathbf{p}$ -nc-Si:H–i-a-Si:H–n-Si (c) structures. The TEM images were captured on the Si (110) cross-section, and the corresponding FFT images (insets) were mathematically obtained. Crystallites in p-nc-Si:H with different orientation are distinguished by colour, and the corresponding reciprocal spots in FFT images are highlighted with coloured circles. The red arrows depict the growth direction of the \nsilicon thin films on the Si (111) plane. d, Extraction of $\\cdot_{E_{\\mathrm{a}}}$ for p-nc-Si:H and p-a-Si:H films without light soaking following equation (2) (dotted lines)49. e,f, Equilibrium band diagrams of HSCs based on p-a-Si:H (e) and p-nc-Si:H (f) related to the cross-sectional structures in b and c. $E_{\\mathrm{c}},E_{\\mathrm{v}}$ and $E_{\\mathrm{{F}}}$ denote conduction band energy, valence band energy and Fermi level, respectively. Insets: enlarged view of the black wire frames; there, $\\Delta E$ equals the difference between $E_{\\mathrm{{F}}}$ and $\\ensuremath{E_{\\mathrm{v}}}$ at the i-a-Si:H–n-Si interface. The collection path of holes across the heterojunction is depicted as a more complicated curve (red arrows) for p-a-Si:H to illustrate a more challenging transport mechanism at the relative interfaces, with respect to the p-nc-Si:H counterpart. Current is generated once the holes meet and recombine with the electrons (along blue arrows) at the interface of the TCO–hole transport layer. \n\nApart from the $X_{\\mathrm{c}}$ , electrical characteristics such as $\\sigma$ and $E_{\\mathrm{a}}$ can reflect the quality of doped films. As shown in Fig. 3d, the p-nc-Si:H layer on glass exhibits a high $\\sigma{>}3\\mathsf{S c m}^{-1}$ and a low $E_{\\mathrm{a}}<16$ meV. By contrast, the p-a-Si:H layer on glass shows values of $\\sigma{\\approx}10^{-4}\\mathsf{S c m^{-1}}$ and $E_{\\mathrm{a}}\\approx350$ meV, respectively. The higher $\\sigma$ and lower $E_{\\mathrm{a}}$ values are thus obtained from the p-nc-Si:H layer. We computed $E_{\\mathrm{a}}$ from the equation \n\n$$\n\\sigma=\\sigma_{0}\\exp\\left(-E_{\\mathrm{a}}/k_{\\mathrm{B}}T\\right),\n$$ \n\nwhere $k_{\\mathrm{{B}}}$ is the Boltzmann constant and $T$ is the temperature in kelvin49. The values of $E_{\\mathrm{a}}$ for $\\boldsymbol{\\mathsf{p}}$ -type semiconductors describe the energy difference between the Fermi level and the valence band maximum. A lower $E_{\\mathrm{a}}$ in the $\\boldsymbol{\\mathsf{p}}$ -nc-Si:H layer, therefore, indicates higher effective doping and work function. Note that the test films are deposited on two types of substrates ( $\\mathrm{SiO}_{2}$ -coated textured silicon wafer and planar glass) using the same deposition processes. Correspondingly, the depo sited p-nc-Si:H layer on glass is about 1.7 times thicker than the layer grown on the pyramidal textured surface of c-Si wafer. Considering the thickness sensitivity of $\\cdot\\chi_{\\mathrm{c}}$ and $E_{\\mathbf{a}}^{31}$ , the much smaller $E_{\\mathrm{a}}$ value of the p-nc-Si:H layer on glass than that on the c-Si wafer is caused by variations in the thickness-dependent crystallization fraction. It should also be noted that the above tests are on samples without light soaking; the $E_{\\mathrm{a}}$ plots of the samples under light soaking are shown in Supplementary Fig. 4. With light soaking, the $E_{\\mathrm{a}}$ and $\\sigma$ values of both films are slightly improved, except for the $\\sigma$ of p-a-Si:H; this increases by a factor of two to three. Although light soaking is used in final devices, it occurs at the front side of the solar cell. Thus, we assume that the properties of HSCs at the rear side are negligibly influenced, and the p-a-Si:H- and p-nc-Si:H-layer properties without light soaking should approximate conditions seen by real devices. \n\n![](images/cf0c1d08c0bb29f6a693e3941b6cf3c86c779d5d7fe822dea47634591bc079b3.jpg) \nFig. 4 | Evaluation of the carrier selectivity of HSCs based on a p-nc-Si:H layer. a, Plot of ideal PCE as a function of contact resistivity $\\rho_{\\mathrm{c}}$ and recombination current density $J_{0}$ for different HSCs, assuming a 110- $\\upmu\\mathrm{m}$ -thick undoped c-Si bulk and $J_{\\mathrm{sc}}$ of $43.31\\mathsf{m A c m}^{-2}$ per Richter’s limiting efficiency model. Blue lines (with blue numbers) represent the selectivity $S_{10}$ according to ref. 53, while dashed– dotted lines (with black numbers) are the contour lines for ideal PCE. Several typical HSCs, including p-a-Si:H (this work; red circle), p-nc-Si:H (this work; red star), $\\mathsf{p}{\\cdot}\\mathsf{S i C}_{x}{\\cdot}\\mathsf{H}$ (ref. 7; yellow circle) and p-poly-Si:H (refs. 55,56; purple circle) are \n\nTo evaluate the real device performance more accurately, we chose $E_{\\mathrm{a}}$ values of 110.7 meV $(346.8\\mathrm{meV})$ for p-nc-Si:H (p-a-Si:H) tested on textured silicon wafers as input parameters for simulated band diagrams. Here, to fit the tested I–V curves in Supplementary Fig. 5, the simulated I–V curves in Supplementary Fig. 6 were carefully regulated by adjusting the simulation parameters so that the accuracy of the technology computer-aided design (TCAD) simulated band diagrams shown in Fig. 3e,f is ensured. The p-layer change leads to adjustments from three aspects: (1) conductivity of the p layer itself, (2) band bending at the c-Si surface and (3) carrier transport at the TCO–p-layer interface. All the three aspects have favourable influences on minimizing resistive losses in the HSC and consequently, yielding maximal FF in the devices. The relevant interpretation is elaborated as follows. \n\nFirst, the p-nc-Si:H layer presents a much higher dark conductivity than the p-a-Si:H layer, which is beneficial for reducing resistive loss in the p layer itself. Second, compared with the p-a-Si:H case, the p-nc-Si:H layer has favourable band bending at the c-Si surface region. This is reflected by the smaller gap between the valence band maximum and the Fermi level $(\\Delta E)$ (insets in Fig. 3e,f). The reason for this is the lower $E_{\\mathrm{a}},$ , hence higher work function, of the p-nc-Si:H sample. The accumulation of holes at the surface of n-Si for the p-nc-Si:H sample is also much higher than that of the p-a-Si:H case, leading to a larger difference between hole and electron concentrations and thus, an improvement in electrical passivation. Moreover, this enhanced band bending at the p layer–i layer–n-Si stack provides a lower and sharper energy barrier, which favours a collection of holes through tunnelling at the HSC. \n\nmarked for comparison. b,c, Experimental measurements of $\\cdot\\rho_{\\mathrm{c}}$ by $\\mathsf{E C S M}^{58,59}$ (b) and $J_{0}$ by Sinton WCT-120 (c) for HSC based on p-nc-Si:H (ref. 6). Inset (b): the total series resistances $(R_{\\mathrm{t}})$ from different disks plotted against inverse area $(15^{-1})$ . The $\\rho_{\\mathrm{c}}$ of $3.6\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ is extracted by linear fitting (dashed line). Inset (c): the passivated sample with a symmetrical structure used for the $J_{0}$ test; $\\tau_{\\mathrm{{SRH}}}{\\mathrm{and}}J_{0}$ are estimated as 15 ms and $1.0\\mathsf{f A}\\mathsf{c m}^{-2}$ , respectively, according to the methods from ref. 5 (here, the grey line indicating intrinsic lifetime, $\\tau_{\\mathrm{{intr}}},$ is taken from ref. 61). \n\nAccordingly, lower $J_{0}$ and $\\rho_{\\mathrm{c}}$ in the p layer–i layer–n-Si stack is obtained. Third, holes in the p-layer valence band recombine with electrons in the TCO conduction band. As elaborated by Procel et al.50,51, the $\\rho_{\\mathrm{c}}$ variations at the interface are linked to the dominating carrier transport mechanisms and can be influenced by the energy alignment of the p layer–TCO contact. The p-nc-Si:H–TCO interface features a lower hole transport barrier than the p-a-Si:H–TCO case, as indicated in Fig. 3e,f. According to Fig. 3f, the energy alignment at the p-nc-Si: H–TCO interface could facilitate carrier transport through dominating BTBT, which is widely considered to be the most efficient carrier transport mechanism. By contrast, at the p-a-Si:H–TCO interface, trap-assisted tunnelling, which is usually a less efficient tunnelling mechanism than BTBT, is likely to dominate; this is confirmed by our simulated results in Fig. 3e. Therefore, a higher $\\rho_{\\mathrm{c}}$ at the p-a-Si:H–TCO interface is to be expected. It should be mentioned that the band gap of p-nc-Si:H (\\~1.7–2 eV) is simplified to be consistent with that of i-a-Si:H because it has little effect on the simulation result $(J-V)$ if the $E_{\\mathrm{a}}$ of the doped layer is small enough $^{50-52}$ . \n\n# Evaluation of holes selectivity \n\nThe replacement of the p-a-Si:H layer with a p-nc-Si:H layer improves the passivation quality and reduces $\\rho_{\\mathrm{c}}$ values at both the p layer–i-a-Si:H–n-Si contact and the TCO–p layer interface. These positive effects contribute to delivering a larger hole selectivity of the HSCs. Figure 4a shows the distributions of simulated solar cell efficiency and hole selectivity as functions of $\\dot{\\rho}_{\\mathrm{c}}$ and $J_{0}$ . We extract $\\rho_{\\mathrm{c}}$ and $J_{0}$ of HSCs based on p-nc-Si:H directly from the measurements shown in Fig. 4b,c, while those of p-a-Si:H are evaluated according to the fitting parameters in Fig. 2 and Supplementary Fig. 1. The selectivity values are indicated by the blue lines, with $S_{10}{=}\\log_{10}[V_{\\mathrm{th}}/(J_{0}{\\times}\\rho_{\\mathrm{c}})]$ (refs. 53,54). For comparison, the $S_{10}$ values of several typical HSCs with p layers of p-a-Si:H, p-SiCx:H and p-poly-Si:H are also included. As shown in Fig. 4a, from the top right corner to the bottom left corner of the plot, solar cell efficiency increases with the increase of $S_{10}$ from 13 to 17. The solar cell with a p-nc-Si:H layer features $S_{10}>16$ which is higher than solar cells using the p-a-Si:H (this work), $\\mathbf{p}{\\cdot}\\mathsf{S i C}_{x}{\\mathbf{:}}\\mathsf{H}$ (ref. 7) and p-poly-Si:H layers55,56. Provided that an ideal ESC and our p-nc-Si:H HSC are considered, the theoretical PCE of the resultant SHJ solar cells could reach up to $29.2\\%$ . \n\n![](images/ae14915db42f1cb48ddf41fa42ceb48f7adf8afaa62195166e0982030b745572.jpg) \nFig. 5 | Certified SHJ solar cell with a PCE of $26.74\\%$ . a, Light I–V and power– voltage (P–V) curves of the record front–back contact silicon solar cell. b, External quantum efficiency (EQE) spectrum and analysis of the optical \nloss, including reflection (R) and absorption (A). The maximal EQE (Green $4n^{2}$ limit72) for $130{\\cdot}|{\\upmu}||$ -thick n-Si excluding electrode shading is also reported for comparison. \n\nThree methods—the Cox and Strack method $(\\mathsf{C S M})^{57}$ , the expanded Cox and Strack method $(\\mathsf{E C S M})^{58,59}$ and the transfer length method $({\\mathsf{T L M}})^{60}$ —were utilized to extract the $\\rho_{\\mathrm{c}}$ of HSCs based on p-nc-Si:H. Emphasis was placed on the ECSM, which can directly extract the $\\rho_{\\mathrm{c}}$ values of the TCO– $\\mathfrak{p}$ -nc-Si:H–i-a-Si:H–n-Si stack, as shown in Fig. 4b. The other two methods, which evaluate the $\\rho_{\\mathrm{c}}$ through measuring symmetric samples on a p-type silicon wafer (p-Si), are shown in Supplementary Fig. 7. The coloured lines in Fig. 4b are the dark current–voltage (dark I–V) curves of the ECSM disks with different diameters (the same as the CSM disks shown in Supplementary Fig. 7a but with the n-Si wafer as the substrate). The inset in Fig. 4b shows total series resistance $(R_{\\mathrm{t}})$ from different disks plotted against inverse area $(1S^{-1})$ . From the linear fit (red dashed line), we can extract a $\\rho_{\\mathrm{c}}$ of $3.6\\:\\mathrm{m}\\Omega\\mathrm{cm}^{2}$ . For comparison, the results extracted from CSM and TLM are 4.2 and $6.5\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ , respectively. \n\nA symmetric structure, shown in the inset of Fig. 4c, was used to characterize $J_{0}$ for the HSC based on p-nc-Si:H. The transient mode of a Sinton measurement was used for testing minority carrier lifetime, and the results are indicated by red circles. The intrinsic recombination mode presented by Black and Macdonald61 was used to fit the data, tuning the parameters of SRH recombination $\\dot{\\tau}_{\\mathrm{SRH;}}$ reflecting the quality of silicon wafer) and $J_{0}$ (representing the quality of surface passivation). The fitted tota $\\mid J_{0}$ is 1.0 fA $\\mathsf{c m}^{-2}$ . Considering the symmetry of the structure, it should be 0.5 fA $\\mathsf{c m}^{-2}$ for the $J_{0}$ of the p-nc-Si:H–i-a-Si:H–n-Si HSC. \n\nThe achievements in electrical performance of the p-nc-Si:H cell $(26.30\\%$ PCE) define a state-of-the-art SHJ process on which advanced optical designs can be adopted to further promote PCE. As shown in Fig. 5a, with the same BJ processing as the p-nc-Si:H cell, reducing the shading ratio from 2.8 to $2.0\\%$ after using the laser transfer process and modifying the window layers of n-nc- $\\mathrm{\\quad}\\operatorname{siO}_{x}{\\mathrm{:}}\\mathrm{H}.$ , i-a-Si:H and TCO at the front (such as reducing the thickness of n-nc- $\\mathsf{S i O}_{x}{:}\\mathsf{H}$ and i-a-Si:H, increasing the oxygen content of n-nc- $\\mathrm{\\bullet}\\mathrm{sio}_{x}\\mathrm{:}\\mathrm{H}$ and decreasing the carrier density of TCO) to minimize the parasitic absorption, we achieved a higher PCE of $26.74\\%$ with the increase of $\\boldsymbol{J}_{\\mathrm{sc}}$ t $\\mathsf{o}41.16\\mathsf{m A c m}^{-2}$ . The slight reduction of FF is mainly due to the change of front metal fingers. In addition, $V_{\\mathrm{oc}}$ increases by $0.9\\mathrm{mV}$ , possibly enhanced by the higher $J_{\\mathrm{SC}}$ . The external quantum efficiency spectrum and main optical loss of each layer are shown in Fig. 5b. The absorption by $\\mathbf{n}{\\cdot}\\mathbf{S}\\mathbf{i}$ fits well with the Institute for Solar Energy Research in Hamelin (ISFH)-certified one, and the slight deviation at short wavelength may arise from the refractive indices used in the simulation. The front grid electrode causes a decrease of $0.97\\mathsf{m A c m}^{-2}$ in $J_{\\mathrm{SC}}$ , accounting for a shading fraction of $2.0\\%$ . In the ultraviolet range, the front TCO, n-nc- ${\\mathrm{siO}}_{x}{\\mathrm{:}}{\\mathrm{H}}$ and i-a-Si:H dominate the loss due to parasitic absorption. In the near-infrared range, the major source of loss is the escape of light from the front, which is attributed to reflection by the test chunk due to the limited wafer thickness. With introducing an additional reflective ${\\sf M g F}_{2}/{\\sf A g}$ stack at the rear side and regulating the transmittance of TCO, the $J_{\\mathrm{sc}}$ was further improved to $41.45\\mathsf{m A c m}^{-2}$ due to the optical gain, while FF decreased to $86.07\\%$ due to the decrease of TCO conductivity. Finally, the PCE was improved to $26.81\\%$ . The certified J–V curve of the device is reported in Supplementary Fig. 8. \n\n# Conclusion \n\nThrough introducing nanocrystallization technology in the doped layer at carrier-selective contacts for both polarities, we achieve a record efficiency of $26.81\\%$ and on a different cell, an extremely high FF $(86.59\\%)$ on M6-sized BJ SHJ solar cells. Two types of SHJ solar cells equipped with p-type transporting layers of amorphous silicon and nanocrystalline silicon are comprehensively investigated; we study their power loss, contact resistivity, transport mechanism and so on. Structural and electrical characterizations of the boron-doped nanocrystalline silicon films indicate that a higher $X_{\\mathrm{C}}(>63\\%)$ , an increase in conductivity of four orders of magnitude (in comparison with p-type amorphous silicon) and an ultralow $E_{\\mathrm{a}}(<115\\mathrm{meV})$ are the main causes of its excellent electrical performance. Because of the low $E_{\\mathrm{a}}$ of p-nc-Si:H, it is easy to enable BTBT at the n-type TCO– $\\cdot\\mathbf{p}$ -nc-Si:H interface and achieve sharp band bending at the i-a-Si:H–n-Si interface, facilitating efficient transport and collection of holes across the whole junction. Our study shows that the implementation of p-nc-Si:H together with a modified TCO greatly reduces the contact resistivity of HSC, from $>100$ to $<5\\mathsf{m}\\Omega\\mathsf{c m}^{2}$ . The total series resistance of the solar cell is reduced from the original 0.37 to $0.2\\Omega\\mathrm{cm}^{2}$ , yielding a record FF for single-junction silicon solar cell. \n\n# Methods \n\n# Solar cell fabrication \n\nIn this work, solar cells were fabricated by the commercial SHJ research and development line on LONGi M2 (the $25.26\\%$ efficiency SHJ solar cell) or on an M6 Czochralski n-Si wafer with a resistivity of $1.2\\substack{-1.5\\Omega}$ cm and a thickness of $130\\upmu\\mathrm{m}$ in (100) orientation. The n-Si wafer was first cleaned and textured by a wet chemical process. Before subsequent deposition, the thickness of the n-Si wafer was confirmed by weight measurement. Radiofrequency plasma-enhanced chemical vapour deposition was used to prepare i-a-Si:H, and then, very high-frequency plasma-enhanced chemical vapour deposition $(40.68\\mathsf{M H z})$ systems were used to deposit n-nc- $\\operatorname{siO}_{x:\\mathsf{H}}$ , p-a-Si:H and p-nc-Si:H layers during the device fabrication. For the i-a-Si:H– $\\cdot\\mathsf{n}$ -Si interface of the $25.26\\%$ cell, an ultrathin 0.5- to $1.0{\\cdot}\\mathsf{n m}$ buffer layer, rich in H content, was introduced to improve the passivation.12 While for that of 26.30, 26.74 and $26.81\\%$ cells, an O-terminated Si surface, grown by a self-limiting wet chemical oxidation process (using ${\\sf H F}/{\\sf H}_{2}\\sf O_{2}$ solution), was introduced to suppress Si epitaxy62–64. Before deposition of p-nc-Si:H, ${\\mathsf{C O}}_{2}$ plasma treatment was carried out on i-a-Si:H, which forms a thin barrier layer for impeding the damage. Supplementary Table 6 shows the detail parameters of the growth process for doped layers. The TCO layers used in $25.26\\%$ cells were prepared by direct current sputtering with rotationally target, while the updated TCO layers used in 26.30, 26.74 and $26.81\\%$ cells were grown by the reactive plasma deposition technique. The material of the updated TCO is 1 $\\mathbf{wt}\\%\\mathbf{CeO}_{2}$ doped $\\begin{array}{r}{\\operatorname*{In}_{2}0_{3}.}\\end{array}$ , while that of original TCO is SCOT (name of commodity; manufactured by Advanced Nano Products) for the front side and conventional $10\\mathrm{{wt\\%}}$ $\\mathsf{S n O}_{2}$ doped $\\quad\\quad\\quad\\operatorname{In}_{2}\\boldsymbol{0}_{3}$ for the rear side of the device. Silver grid electrodes were printed followed by annealing at $190^{\\circ}\\mathbf{C}$ for $30\\mathrm{min}$ . With the improvement of the metallization process, the metal fraction of the front electrode for different SHJ solar cells decreased from 3.2 to $2.0\\%$ , while the rear electrode patterning with fingers and bus bars remained basically unchanged. For the above situation of $2.0\\%$ metal fraction, laser transfer process was introduced to make the front finger. To further increase $J_{\\mathrm{SC.}}$ , a 150-nm-thick $\\mathsf{M g F}_{2}$ film was evaporated on the front TCO layer as a second antireflective coating. For $26.81\\%$ cell, an additional 120-nm-thick MgF2/150-nm-thick Ag stack was evaporated on the rear TCO layer, which means this cell is a monofacial solar cell. Finally, light soaking under 60 suns was carried out for 90 s at $190^{\\circ}\\mathsf{C}$ . \n\n# PLA \n\nTwo methods were utilized for the PLA of the solar cells with PCEs of $25.26\\%$ (p-a-Si:H cell) and $26.30\\%$ (p-nc-Si:H cell). One is based on Quokka2 software (as shown in Fig. 2), and the other is referring to a simple recombination model (as shown in Supplementary Fig. 1). For the Quokka2 simulation, the unit cell was modelled in two dimensions to calculate the power loss in the transversal transport of carriers between two fingers. The input parameters were primarily obtained from measurements 'Characterizations'. The line resistance of the finger and the contact resistivity of the heterojunction were considered as series resistance in an external circuit. The optical path-length factor $(Z)$ was set as $4n^{2}$ , and the transmittance was adjusted to match the simulated $J_{\\mathrm{SC}}$ to that of actual cells. The $\\tau_{\\scriptsize{\\mathrm{SRH}}}$ of the silicon wafers was set by adjusting the values of $\\cdot_{\\sigma_{\\mathfrak{n}},\\sigma_{\\mathfrak{p}}}$ and the defect density of the SRH defect $(N_{\\mathrm{t}}).\\tau_{\\mathrm{SRH}}\\/J_{\\mathrm{01}}$ (surface recombination) and $R_{s}$ were further tuned to obtain agreement between the light J–V and the Suns– $V_{\\mathrm{oc}}$ curves. Richter’s Auger mode was chosen, and the value of radiation recombination was changed to $0.4\\times B_{\\mathrm{rad}}$ with a photon recycling probability of 0.6 (ref. 65). Other parameters in the simulation are listed in Supplementary Table 4. It should be noted that since band gap narrowing is not considered in this model, the corresponding $V_{\\mathrm{oc}}$ may deviate somewhat from the experimental value. For the simulation by the simple recombination model method, we first assume a uniform quasi-Fermi level and then fit the Suns– $V_{\\mathrm{oc}}$ and light J–V curves by adding the formulas of intrinsic recombination, SRH recombination, surface recombination, series resistance and so on. The specific fitting parameters, consequent results and corresponding descriptions are shown in Supplementary Discussion 1 and Supplementary Fig. 1. \n\n# Electrical simulation \n\nThe band diagrams in Fig. 3e,f and the dark I–V curves in Supplementary Fig. 6 were calculated by using Sentaurus TCAD based on drift-diffusion models. The simulation structure of the testing device is illustrated in Supplementary Fig. 7a but with n-Si as the substrate: that is, a stacked film of Ag–TCO–p-nc-Si:H (or p-a-Si:H)–i-a-Si:H on bulk n-Si with a disk shape on the front surface and a full-area ohmic contact on the rear surface of the n-Si substrate. Physical models, including surface recombination, Auger recombination in substrate and thermionic emission at proper interfaces, are taken into consideration. Moreover, p-a-Si:H and p-nc-Si:H layers feature spatially uniformly distributed traps in the exponential and Gaussian energy distributions50. Trap-assisted tunnelling and BTBT models are also considered at the TCO– $\\mathfrak{p}$ -nc-Si:H (or p-a-Si:H) interface. The specific film parameters are shown in Supplementary Table 7. The simulated results are consistent with the experiments (Supplementary Figs. 5 and 6 and Supplementary Discussion 2). \n\n# Optical simulation \n\nThe optical simulation in Fig. 5b was performed using the SunSolve software provided by PV Lighthouse. In the simulation, we use refractive indices from the literature $\\scriptstyle\\lfloor66-70$ except for the TCO film, which we measured by ellipsometry. In SunSolve, ray tracing and thin-film optics were adopted with a Monte Carlo algorithm for sampling and averaging the absorption in each layer. Here, 1 million rays with zero zenith angle and air mass 1.5G were randomly generated for better confidence of the statistics; the $95\\%$ confidence interval of cell absorption is less than $0.01\\mathsf{m A}\\mathsf{c m}^{-2}$ . \n\n# Characterizations \n\nThe light J–V curves of the solar cells were tested and certified by ISFH (Supplementary Fig. 8); gold‐coated brass chuck was used to mount the solar cells, and the resistance of the grid at the rear side and of bus bars at the front side was neglected. The pseudo light J–V curves were extracted from a Suns– $\\boldsymbol{V_{\\mathrm{oc}}}$ measurement. The Suns– $V_{\\mathrm{{oc}}}$ module of a Sinton WCT-120 instrument was used to collect the changes in voltage of the device by reducing the light intensity of the flashlight; these were computationally transformed them into Suns– $\\cdot\\V_{\\mathrm{oc}}$ curves. Raman spectra were obtained with a Horiba LabRAM Odyssey Raman spectrometer with a $325\\cdot\\mathrm{nm}$ excitation laser. Test films were deposited on cleaned glass substrates using the same deposition processes as the solar cells. The morphology of heterojunctions, consisting of TCO-coated doped amorphous and nanocrystalline silicon films on c-Si bulk, was observed by TEM, and the test samples were prepared by the focused ion beam method. Activation energies were calculated from measurements of electrical conductivity as a function of test temperature. Electrical conductivities were calculated from I–V curves measured by a semiconductor analyser (Keithley 4200A-SCS). It should be noted that the ${50}{\\cdot}\\mathrm{nm}$ isolation layer of $\\mathsf{S i O}_{x}$ film was deposited by plasma-enhanced chemical vapour deposition before the deposition of p-nc-Si:H or p-a-Si:H on the pyramid-textured silicon wafers. Contact resistivity tests were carried out using the CSM, ECSM and TLM; the details are shown in Fig. 4b and Supplementary Fig. 7. Sinton’s minority carrier lifetime test was used to characterize the passivation quality on a symmetric structure of p-nc-Si:H–i-a-Si:H–n-Si–i-a-Si:H– $\\mathbf{\\sigma}\\cdot\\mathbf{p}$ -nc-Si:H (Fig. 4c). The transient mode of a Sinton measurement was used for testing the minority carrier lifetime. Pyramid-textured n-Si wafers with a thickness of about $130{\\upmu\\mathrm{m}}$ and resistivity of about $1.59\\Omega$ cm were used as the substrates. \n\n# Reporting summary \n\nFurther information on research design is available in the Nature Portfolio Reporting Summary linked to this article. \n\n# Data availability \n\nAll data generated or analysed during this study are included in the published article and its Supplementary Information. Source data are provided with this paper. \n\n# References \n\n1. Min, B., Müller, M., Wagner, H., Fischer, G. & Brendel, R. A roadmap toward $24\\%$ efficient PERC solar cells in industrial mass production. IEEE J. Photovolt. 7, 1541–1550 (2017). \n\n# Article \n\n3.\t Richter, A. et al. Design rules for high-efficiency both-sidescontacted silicon solar cells with balanced charge carrier transport and recombination losses. Nat. Energy 6, 429–438 (2021). \n4.\t Haase, F. et al. Laser contact openings for local poly-Si-metal contacts enabling $26.1\\%$ -efficient POLO-IBC solar cells. Sol. Energy Mater. Sol. Cells 186, 184–193 (2018). \n5. Yoshikawa, K. et al. Silicon heterojunction solar cell with interdigitated back contacts for a photoconversion efficiency over $26\\%$ . Nat. Energy 2, 17032 (2017). \n6. Yoshikawa, K. et al. Exceeding conversion efficiency of $26\\%$ by heterojunction interdigitated back contact solar cell with thin-film Si technology. Sol. Energy Mater. Sol. Cells 173, 37–42 (2017). \n7.\t Khler, M. et al. A silicon carbide-based highly transparent passivating contact for crystalline silicon solar cells approaching efficiencies of $24\\%$ . Nat. Energy 6, 529–537 (2021). \n8. Wolf, S. D., Descoeudres, A., Holman, Z. C. & Ballif, C. Highefficiency silicon heterojunction solar cells: a review. Green 2, 7–24 (2012). \n9. Herasimenka, S. Y., Dauksher, W. & Bowden, S. G. >750 mV open-circuit voltage measured on $50\\ –\\upmu\\mathrm{m}$ -thick silicon heterojunction solar cell. Appl. Phys. Lett. 103, 053511 (2013). \n10.\t Taguchi, M., Yano, A., Tohoda, S., Matsuyama, K. & Maruyama, E. $24.7\\%$ record efficiency HIT solar cell on thin silicon wafer. IEEE J. Photovolt. 4, 96–99 (2014). \n11.\t Li, H. et al. The amorphous/crystalline silicon interface research of HIT solar cells by simulation. Adv. Mat. Res. 773, 124–131 (2013). \n12.\t Ru, X., Qu, M., Wang, J., Ruan, T. & Xu, X. 25.11% efficiency silicon heterojunction solar cell with low deposition rate intrinsic amorphous silicon buffer layers. Sol. Energy Mater. Sol. Cells 215, 110643 (2020). \n13.\t Qu, X. et al. Identification of embedded nanotwins at c-Si/a-Si:H interface limiting the performance of high-efficiency silicon heterojunction solar cells. Nat. Energy 6, 194–202 (2021). \n14.\t Street, R. A., Biegelsen, D. K. & Knights, J. C. Defect states in doped and compensated a-Si:H. Phys. Rev. B 24, 969–984 (1981). \n15.\t Bivour, M., Reichel, C., Hermle, M. & Glunz, S. W. Improving the a-Si:H(p) rear emitter contact of n-type silicon solar cells. Sol. Energy Mater. Sol. Cells 106, 11–16 (2012). \n16.\t Messmer, C., Bivour, M., Luderer, C., Tutsch, L. & Hermle, M. Influence of interfacial oxides at TCO/doped Si thin film contacts on the charge carrier transport of passivating contacts. IEEE J. Photovolt. 10, 343–350 (2019). \n17.\t Gogolin, R. et al. Analysis of series resistance losses in a-Si:H/c-Si heterojunction solar cells. IEEE J. Photovolt. 4, 1169–1176 (2014). \n18.\t Liu, W. et al. Light-induced activation of boron doping in hydrogenated amorphous silicon for over $25\\%$ efficiency silicon solar cells. Nat. Energy 7, 427–437 (2022). \n19.\t Luderer, C., Messmer, C., Hermle, M. & Bivour, M. Transport losses at the TCO/a-Si:H/c-Si heterojunction: influence of different layers and annealing. IEEE J. Photovolt. 10, 952–958 (2020). \n20.\t Ghahfarokhi, O. M., Maydell, K. V. & Agert, C. Enhanced passivation at amorphous/crystalline silicon interface and suppressed Schottky barrier by deposition of microcrystalline silicon emitter layer in silicon heterojunction solar cells. Appl. Phys. Lett. 104, 113901 (2014). \n21.\t Seif, J. P. et al. Strategies for doped nanocrystalline silicon integration in silicon heterojunction solar cells. IEEE J. Photovolt. 6, 1132–1140 (2016). \n22.\t Sharma, M., Panigrahi, J. & Komarala, V. K. Nanocrystalline silicon thin-film growth and application for silicon heterojunction solar cells: a short review. Nanoscale Adv. 3, 3373–3383 (2021). \n23.\t Strahm, B., Howling, A. A., Sansonnens, L. & Hollenstein, C. Plasma silane concentration as a determining factor for the transition from amorphous to microcrystalline silicon in $\\mathsf{S i H}_{4}/\\mathsf{H}_{2}$ discharges. Plasma Sources Sci. Technol. 16, 80–89 (2007). \n24.\t Finger, F. et al. Improvement of grain size and deposition rate of microcrystalline silicon by use of very high frequency glow discharge. Appl. Phys. Lett. 65, 2588–2590 (1994). \n25.\t Zhao, Y. et al. Doped hydrogenated nanocrystalline silicon oxide layers for high-efficiency c-Si heterojunction solar cells. Prog. Photovolt. 28, 425–435 (2020). \n26.\t Mazzarella, L. et al. Nanocrystalline silicon emitter optimization for Si-HJ solar cells: substrate selectivity and ${\\mathsf{C O}}_{2}$ plasma treatment effect. Phys. Status Solidi A 214, 1532958 (2017). \n27.\t Umishio, H., Sai, H., Koida, T. & Matsui, T. Nanocrystalline-silicon hole contact layers enabling efficiency improvement of silicon heterojunction solar cells: impact of nanostructure evolution on solar cell performance. Prog. Photovolt. Res. Appl. 29, 344–356 (2021). \n28.\t Fioretti, A. N., Boccard, M., Monnard, R. & Ballif, C. Lowtemperature p-type microcrystalline silicon as carrier selective contact for silicon heterojunction solar cells. IEEE J. Photovolt. 9, 1158–1165 (2019). \n29.\t Boccard, M. et al. Hole-selective front contact stack enabling $24.1\\%$ -efficient silicon heterojunction solar cells. IEEE J. Photovolt. 11, 9–15 (2020). \n30.\t Sai, H., Umishio, H. & Matsui, T. Very thin $(56\\upmu\\mathrm{m})$ silicon heterojunction solar cells with an efficiency of $23.3\\%$ and an open-circuit voltage of 754 mV. Sol. RRL 5, 2100634 (2021). \n31.\t Zhao, Y. et al. Design and optimization of hole collectors based on nc-SiOx:H for high-efficiency silicon heterojunction solar cells. Sol. Energy Mater. Sol. Cells 219, 110779 (2021). \n32.\t Mazzarella, L., Morales-Vilches, A. B., Hendrichs, M., Kirner, S. & Stannowski, B. Nanocrystalline n-type silicon oxide front contacts for silicon heterojunction solar cells: photocurrent enhancement on planar and textured substrates. IEEE J. Photovolt. 8, 70–78 (2017). \n33.\t Mazzarella, L. et al. p-type microcrystalline silicon oxide emitter for silicon heterojunction solar cells allowing current densities above $40\\mathsf{m A}/\\mathsf{c m}^{2}$ . Appl. Phys. Lett. 106, 023902 (2015). \n34.\t Thomas, G., Allen, J. B., Yang, X., Javey, A. & De Wolf, S. Passivating contacts for crystalline silicon solar cells. Nat. Energy 4, 914–928 (2019). \n35.\t Chen, Y. et al. Mass production of industrial tunnel oxide passivated contacts (TOPCon) silicon solar cells with average efficiency over $23\\%$ and modules over 345 W. Prog. Photovolt. Res. Appl. 27, 827–834 (2019). \n36.\t Green, M. A. Solar cell fill factors: general graph and empirical expressions. Solid-State Electron. 24, 788–789 (1981). \n37.\t LONGi breaks three more world records for solar cell efficiency. LONGi https://www.longi.com/en/news/7474/ (2021). \n38.\t Quokka 2 (PV Lighthouse, 2016). \n39.\t Fell, A. A free and fast three-dimensional/two-dimensional solar cell simulator featuring conductive boundary and quasineutrality approximations. IEEE Trans. Electron Devices 60, 733–738 (2013). \n40.\t Han, C. et al. Towards bifacial silicon heterojunction solar cells with reduced TCO use. Prog. Photovolt. 30, 750–762 (2022). \n41.\t Pysch, D., Mette, A. & Glunz, S. W. A review and comparison of different methods to determine the series resistance of solar cells. Sol. Energy Mater. Sol. Cells 91, 1698–1706 (2007). \n42.\t Xia, H. et al. Phonon mode study of Si nanocrystals using micro-Raman spectroscopy. J. Appl. Phys. 78, 6705–6708 (1995). \n43.\t Zhang, S. et al. The diphasic nc-Si/a-Si:H thin film with improved medium-range order. J. Non Cryst. Solids 338, 188–191 (2004). \n45.\t Fathi, E. V., Vieira, Y. & Sazonov, M. Boron-doped nanocrystalline silicon thin films for solar cells. Appl. Surf. Sci. 257, 8901–8905 (2011). \n46.\t Voutsas, A. T., Hatalis, M. K., Boyce, J. & Chiang, A. Raman spectroscopy of amorphous and microcrystalline silicon films deposited by low‐pressure chemical vapor deposition. J. Appl. Phys. 78, 6999–7006 (1995). \n47.\t Boccard, M., Monnard, R., Antognini, L. & Ballif, C. Silicon oxide treatment to promote crystallinity of p-type microcrystalline layers for silicon heterojunction solar cells. In The 8th Internationa Conference on Crystalline Silicon Photovoltaics https://doi.org/ 10.1063/1.5049266 (AIP, 2018). \n48.\t Yang, Y. et al. n-type nc-SiOx:H film enables efficient and stable silicon heterojunction solar cells in sodium environment. Mater. Lett. 309, 131360 (2022). \n49.\t Nie, G. Z. N., Zhong, C. L., Luo, L. E. & Xu, Y. A modification of usual C–V measurement to more precisely characterize the band offsets in a-Si:H/c-Si heterojunctions. Results Phys. 5, 286–289 (2015). \n50.\t Procel, P. et al. The role of heterointerfaces and subgap energy states on transport mechanisms in silicon heterojunction solar cells. Prog. Photovolt. Res. Appl. 28, 935–945 (2020). \n51.\t Procel, P., Yang, G., Isabella, O. & Zeman, M. Theoretical evaluation of contact stack for high efficiency IBC-SHJ solar cells. Sol. Energy Mater. Sol. Cells 186, 66–77 (2018). \n52.\t Biron, R. et al. Window layer with p doped silicon oxide for high $V_{\\infty}$ thin-film silicon n–i–p solar cells. J. Appl. Phys. 110, 1081–1842 (2011). \n53.\t Brendel, R. & Peibst, R. Contact selectivity and efficiency in crystalline silicon photovoltaics. IEEE J. Photovolt. 6, 1413–1420 (2016). \n54.\t Brendel, R., Riencker, M. & Peibst, R. A quantitative measure for the carrier selectivity of contacts to solar cells. In 32nd European Photovoltaic Solar Energy Conference & Exhibition 447–451 (WIP, 2016). \n55.\t Yan, D., Cuevas, A., Wan, Y. & Bullock, J. Passivating contacts for silicon solar cells based on boron-diffused recrystallized amorphous silicon and thin dielectric interlayers. Sol. Energy Mater. Sol. Cells 152, 73–79 (2016). \n56.\t Jan, S., Robby, P. & Rolf, B. Surface passivation of crystalline silicon solar cells: present and future. Sol. Energy Mater. Sol. Cells 187, 39–54 (2018). \n57.\t Cox, R. H. & Strack, H. A. Ohmic contacts for GaAs devices. Solid State Electron. 10, 1213–1218 (1966). \n58.\t Wang, W. et al. An expanded Cox and Strack method for precise extraction of specific contact resistance of transition metal oxide/n-silicon heterojunction. IEEE J. Photovolt. 9, 1113–1120 (2019). \n59.\t Chen, L. et al. Realization of a general method for extracting specific contact resistance of silicon-based dopant-free heterojunctions. Sol. RRL 6, 2100394 (2021). \n60.\t Reeves, G. K. & Harrison, H. B. Obtaining the specific contact resistance from transmission line model measurements. IEEE Electron Device Lett. 3, 111–113 (2005). \n61.\t Black, L. E. & Macdonald, D. H. On the quantification of Auger recombination in crystalline silicon. Sol. Energy Mater. Sol. Cells 234, 111428 (2022). \n62.\t Eom, D. H., Kim, K. S. & Park, J. G. Passivation and etching of wafer surfaces in HF– ${\\bf\\cdot H}_{2}{\\bf O}_{2}$ –IPA solutions. Jpn J. Appl. Phys. 41, 5881– 5886 (2002). \n63.\t Jayachandran, S. et al. Growth mechanisms for Si epitaxy on O atomic layers: impact of O content and surface structure. Appl. Surf. Sci. 384, 152–160 (2016). \n64.\t Koehler, M. et al. Wet-chemical preparation of silicon tunnel oxides for transparent passivated contacts in crystalline silicon solar cells. ACS Appl. Mater. Interfaces 10, 14259–14263 (2018). \n65.\t Richter, A., Hermle, M. & Glunz, S. W. Reassessment of the limiting efficiency for crystalline silicon solar cells. IEEE J. Photovolt. 3, 1184–1191 (2013). \n66.\t Abolmasov, S., Cabarrocas, P. R. I. & Chatterjee, P. Towards $12\\%$ stabilised efficiency in single junction polymorphous silicon solar cells: experimental developments and model predictions. EPJ Photovolt. 7, 70302 (2016). \n67.\t Dodge, M. J. Refractive properties of magnesium fluoride. Appl. Opt. 23, 1980–1985 (1984). \n68.\t Green, M. A. Self-consistent optical parameters of intrinsic silicon at 300 K including temperature coefficients. Sol. Energy Mater. Sol. Cells 92, 1305–1310 (2015). \n69.\t Nguyen, H. T., Rougieux, F. E., Mitchell, B. & Macdonald, D. Temperature dependence of the band-band absorption coefficient in crystalline silicon from photoluminescence. J. Appl. Phys. 115, 1245 (2014). \n70.\t Holman, Z. C. et al. Current losses at the front of silicon heterojunction solar cells. IEEE J. Photovolt. 2, 7–15 (2012). \n71.\t Richter, A., Werner, F., Cuevas, A., Schmidt, J. & Glunz, S. W. Improved quantitative description of Auger recombination in crystalline silicon. Phys. Rev. B 86, 165202 (2012). \n72.\t Yablonovitch, E. Statistical ray optics. J. Opt. Soc. Am. 72, 1917–1983 (1982). \n\n# Acknowledgements \n\nWe thank Y. Wang, H. Deng, T. Xie, P. Li, Y. Liu, H. Chen, Y. Long, C. Li, Z. Zhang, L. Feng, J. Qian, B. Yang, B. Liu and K. Zhang for wafer optimization, sample preparation, cell fabrication and characterizations. We also thank Z. Liu and H. Tang of Sun Yat-sen University for transmission electron microscopy characterization and simulation. This work was financially supported by the National Key R&D Program of China (grants 2022YFB4200203 and 2022YFB4200200) and the National Natural Science Foundation of China (grants 62034009 and 62104268). \n\n# Author contributions \n\nH.L., S.Y. and P.G. designed the characterization experiments, performed quokka simulation and analysed the data. M.Y. and X.R. contributed to the optimization of the transport layer. G.W. and S.Y. performed the characterization. M.Y., X.R., S.Y., F.P., C.H., M.Q., J.L., L.F. and X.X. contributed to the development of the silicon heterojunction solar cells. X.X. designed the solar cells. X.X., Z.L. and P.G. supervised the study. C.H., P.P.M. and O.I. performed TCAD simulation and theoretical support. H.L., S.Y. and P.G. designed the idea of the study. H.L. and S.Y. co-wrote the paper. All authors discussed and reviewed the manuscript. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\nAdditional information Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41560-023-01255-2. \n\nCorrespondence and requests for materials should be addressed to Shi Yin, Pingqi Gao or Xixiang Xu. \n\nPeer review information Nature Energy thanks Martin Green, Bertrand Paviet-Salomon, Rutger Schlatmann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at www.nature.com/reprints. \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons. org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 \n\n# natureresearch \n\n# Solar Cells Reporting Summary \n\nNatureResachihesmeepbilifhekateublihifoitedfublcaiallcda reportingtechactezatifhttaicevicesadprescturtecraspieptigomlisigh not apply to an individual manuscript, but allfields must be completed for clarity. \n\nFor further information on Nature Research policies,including our data availability policy,see Authors & Referees. \n\n# Experimental design \n\n# Please check: are the following details reported in the manuscript? \n\n1. Dimensions \n\nArea of the tested solar cells \n\n244.53 square centimeter, 274.3 square centimeter, 274.4 square centimeter and \n274.4 square centimeter; Stated in Methods, Fig.S8 and Calibration certificate. \n\n![](images/4acaef7034a9f36fbbd1ec0761e8fe5c360d3ac08c93e00784c5092de4dd274e.jpg) \n\nMethod used to determine the device area \n\nThe area of the calibration object is measured using an optical scanning system working in transmission mode and is traceable to a primary calibrated area standard (Calibration mark 5O716-PTB-19 (FNoo1)), stated in Calibration certificate. \n\n2. Current-voltage characterization \n\nCurrent density-voltage (J-V) plots in both forward and backward direction \n\n![](images/3611f4054dea2a90d7ab91deba698f45178eb002a4808e390ab96258fc082a45.jpg) \n\nVoltage scan conditions For instance: scan direction, speed, dwell times One current-voltage characteristics consists of 165 voltage steps and each step takes a time of 3oo ms, stated in Calibration certificate. \n\n![](images/fc955bca9a9b9f1e3d99c728c5cf7a18136581338d82fbe5866a35e71872e6f7.jpg) \n\nTest environment For instance: characterization temperature, in air or in glove box \n\nStandard testing conditions (AM1.5G, 100 mW/cm², $25^{\\circ}\\mathrm{C}$ ),stated in Calibration certificate. \n\nProtocol for preconditioning of the device before its characterization \n\n![](images/8837a821d85c4fe10f57d9f6dc45238a161d4fe47df3482a8302b9e2712f6959.jpg) \n\nStability of the J-V characteristic Verified with time evolution of the maximum power point or with the photocurrent at maximum power point; see ref. 7 for details. \n\nThe layers and materials used for the solar cell are stable under standard testing conditions. \n\n3. Hysteresis or any other unusual behaviour \n\nDescription of the unusual behaviour observed during the characterization \n\nA hysteresis between forward and reverse measurements was not observed, stated in Calibration certificate. \n\n![](images/9587e30dc29d839dba4e34907e5cdfd75b87898233f2a6a7f691b065a6df4542.jpg) \n\nRelated experimental data \n\nA hysteresis between forward and reverse measurements was not observed, stated in Calibration certificate. \n\n4.Efficiency \n\nExternal quantum efficiency (EQE) or incident photons to current efficiency (IPCE) \n\n![](images/2ab93b990d327948fae8e69b30aebf0b2ceafdf6b1e990e13ac50b5c4111e5df.jpg) \n\n![](images/b29ad892869e8921624ef04c02ac77c32a668ae09aa9db3efb26c00e606fb273.jpg) \n\nA comparison between the integrated response under the standard reference spectrum and the response measure under the simulator \n\n![](images/4a56e8b67479a2c3c39e2cc73921f180a637de5b32931d01f4d3b42f173c98e3.jpg) \n\nThis is done by a WPVS reference cell measured at ISFH, stated in Calibration certificate. \n\nFor tandem solar cells, the bias illumination and bias voltage used for each subcell \n\n![](images/3012c02b31e4973d26bb51474763732bfedf9798eca552f1a3340709af1e2b55.jpg) \n\nThey are not tandem solar cells. \n\n5. Calibration \n\nLight source and reference cell or sensor used for the characterization \n\n![](images/a5abcc96380273dd6dd2cee32d8e0662a2621aab5a8ab76f2640e839501fad0f.jpg) \n\nThe sun simulator is adjusted using a WPVS reference cell, stated in Calibration certificate. \n\nConfirmation that the reference cell was calibrated and certified \n\nThe short circuit current of this reference cell was calibrated (primary standard “IV\", Calibration mark 47086-PTB-21 (RD001)) under standard test conditions (1000 W/ m²,AM1.5G reference spectrum and $25^{\\circ}\\mathrm{C})$ , stated in Calibration certificate. \n\nCalculation of spectral mismatch between the reference cell and the devices under test \n\n![](images/9714373a667e966f5b75950dbf3e492729341f7ec8791d7662735cd591c76aa0.jpg) \n\nReference cell and the as measured cells are the same kind of devices, no spectral mismatch. \n\n6. Mask/aperture \n\nSize of the mask/aperture used during testing \n\nAll solar cells are conducted as total-area testing, stated in Calibration certificate. \n\nVariation of the measured short-circuit current density with the mask/aperture area \n\n![](images/01e4865977be51b52de8145e84aa4473634351b432cdd813608b82dba46e614e.jpg) \n\nAll solar cells are conducted as total-area testing, stated in Calibration certificate. \n\n7. Performance certification \n\nIdentity of the independent certification laboratory that confirmed the photovoltaic performance \n\nThee cells used in our manuscript have been independently confirmed by ISFH; \n\nA copy of any certificate(s) Provide in Supplementary Information \n\n![](images/099bc9af55c275eb03c608dd274d9eff2fb79d9398d7ec974d3d39732a708670.jpg) \n\nFigure S8 and Calibration certificate. \n\n8. Statistics \n\nNumber of solar cells tested \n\nIt only shows three typical champion solar cells certified by ISFH. \n\nStatistical analysis of the device performance \n\n![](images/fc465192170692559e5429ddab39ff5c299c9f573572a824da1bf6243f43498f.jpg) \n\nIt only shows three typical champion solar cells certified by ISFH. \n\n9. Long-term stability analysis \n\nType of analysis, bias conditions and environmental conditions For instance: illumination type, temperature, atmosphere humidity, encapsulation method, preconditioning temperature long-term stability analysis has not yet been performed \n\n![](images/9d6045ab0a5509861bdcb04a91e6fe4e74723c3ef59dd1ce122055ce1f3724ae.jpg) " + }, + { + "id": "10.1038_s41586-023-06784-0", + "DOI": "10.1038/s41586-023-06784-0", + "DOI Link": "http://dx.doi.org/10.1038/s41586-023-06784-0", + "Relative Dir Path": "mds/10.1038_s41586-023-06784-0", + "Article Title": "Homogenizing out-of-plane cation composition in perovskite solar cells", + "Authors": "Liang, Z; Zhang, Y; Xu, HF; Chen, WJ; Liu, BY; Zhang, JY; Zhang, H; Wang, ZH; Kang, DH; Zeng, JR; Gao, XY; Wang, QS; Hu, HJ; Zhou, HM; Cai, XB; Tian, XY; Reiss, P; Xu, BM; Kirchartz, T; Xiao, ZG; Dai, SY; Park, NG; Ye, JJ; Pan, X", + "Source Title": "NATURE", + "Abstract": "Perovskite solar cells with the formula FA(1-x)CsxPbI(3), where FA is formamidinium, provide an attractive option for integrating high efficiency, durable stability and compatibility with scaled-up fabrication. Despite the incorporation of Cs cations, which could potentially enable a perfect perovskite lattice(1,2), the compositional inhomogeneity caused by A-site cation segregation is likely to be detrimental to the photovoltaic performance of the solar cells(3,4). Here we visualized the out-of-plane compositional inhomogeneity along the vertical direction across perovskite films and identified the underlying reasons for the inhomogeneity and its potential impact for devices. We devised a strategy using 1-(phenylsulfonyl)pyrrole to homogenize the distribution of cation composition in perovskite films. The resultant p-i-n devices yielded a certified steady-state photon-to-electron conversion efficiency of 25.2% and durable stability.", + "Times Cited, WoS Core": 415, + "Times Cited, All Databases": 427, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:001169177500001", + "Markdown": "# Article \n\n# Homogenizing out-of-plane cation composition in perovskite solar cells \n\nhttps://doi.org/10.1038/s41586-023-06784-0 \n\nReceived: 1 January 2023 \n\nAccepted: 25 October 2023 \n\nPublished online: 1 November 2023 \n\nOpen access \n\n# Check for updates \n\nZheng Liang1,2,15, Yong Zhang3,4,15, Huifen $\\mathbf{X}\\mathbf{u}^{1,2,15}$ , Wenjing Chen2,5, Boyuan Liu1,2, Jiyao Zhang3,4, Hui Zhang1,2, Zihan Wang1,2, Dong-Ho Kang6,7, Jianrong Zeng8, Xingyu Gao8, Qisheng Wang8, Huijie ${\\mathsf{H}}{\\mathsf{u}}^{1,2}$ , Hongmin Zhou2,9, Xiangbin Cai10, Xingyou Tian1, Peter Reiss11, Baomin $\\mathsf{X}\\mathsf{u}^{3,4}$ , Thomas Kirchartz12,13, Zhengguo Xiao2,5, Songyuan Dai14 ✉, Nam-Gyu Park6,7 ✉, Jiajiu $\\forall e^{1,12\\boxtimes}\\&$ Xu Pan1 ✉ \n\nPerovskite solar cells with the formula $\\mathbf{FA}_{1-x}\\mathbf{Cs}_{x}\\mathbf{Pbl}_{3}$ , where FA is formamidinium, provide an attractive option for integrating high efficiency, durable stability and compatibility with scaled-up fabrication. Despite the incorporation of Cs cations, which could potentially enable a perfect perovskite lattice1,2, the compositional inhomogeneity caused by A-site cation segregation is likely to be detrimental to the photovoltaic performance of the solar cells3,4. Here we visualized the out-of-plane compositional inhomogeneity along the vertical direction across perovskite films and identified the underlying reasons for the inhomogeneity and its potential impact for devices. We devised a strategy using 1-(phenylsulfonyl)pyrrole to homogenize the distribution of cation composition in perovskite films. The resultant p–i–n devices yielded a certified steady-state photon-to-electron conversion efficiency of $25.2\\%$ and durable stability. \n\nThere have been significant improvements in the efficiency of lead-halide perovskite solar cells (PSCs)5, largely due to the development of new passivation strategies6,7 and the optimization of the perovskite composition8. Notably, the modulation of the A-site composition, specifically with FA-Cs alloyed perovskite, where FA is formamidinium, is emerging as a promising method for boosting efficiency9. However, there are growing concerns about the stability of Cs-containing perovskites due to the segregation of the cations, which could potentially accelerate the long-term degradation3,4,10,11. The distribution of these inhomogeneous phases within perovskites and their direct impact on efficiency are not yet fully understood. \n\nHerein, we visualize the spatially inhomogeneous phase distribution along the vertical direction across perovskite films and propose that device performance is limited by out-of-plane compositional inhomogeneity. Furthermore, we identified that unbalanced crystallization and phase transition between A-site components have a significant effect on the segregation of the FA and Cs phases. To address this issue, we devised a strategy using 1-(phenylsulfonyl) pyrrole (PSP) as an additive to retard the segregation of cations in FA-Cs perovskites. The PSP-treated devices have a $\\mathsf{p}{\\mathsf{-i-n}}$ structure and yielded a champion photon-to-electron conversion efficiency (PCE) of $26.1\\%$ (certified reverse PCE of $25.8\\%$ and certified steady-state PCE of $25.2\\%$ ). \n\n# Out-of-plane cation inhomogeneity \n\nThe distribution of A-site cations within perovskite films critically affects the performance of the device12. Although Cs has been widely used as a cation dopant in perovskite formulations, there are still concerns about the inhomogeneous distribution of cations. Figure 1a is a schematic illustration of the out-of-plane cation inhomogeneity. It shows that Cs prefers to aggregate at the bottom of the perovskite film because crystallization has a significant impact on the compositional evolution within perovskite films. An organic molecule of PSP with a sulfone group13,14 was designed as an additive to the precursor to address the cation inhomogeneity within perovskites, particularly for FA-Cs-containing perovskites (Fig. 1b, Supplementary Fig. 2 and Supplementary Note 1). \n\nWe conducted time-of-flight secondary-ion mass spectroscopy (ToF-SIMS) to investigate the cation distribution (Supplementary Fig. 4). Figure 1c illustrates that in the reference film, for the Cs there is an increasing intensity gradient from the perovskite surface towards the bottom. The FA cations have the opposite trend. This observation confirms the out-of-plane cation inhomogeneity within the perovskite film. Notably, the addition of PSP resulted in a homogeneous cation distribution. Furthermore, as inferred from the characteristic fraction of $\\cdot{\\sf S}{\\sf O}_{2}^{-}$ , PSP molecules accumulate at the bottom of the perovskite film. To further survey the elemental variation within the perovskite film, we conducted depth-dependent X-ray photoelectron spectroscopy (XPS). The extracted atomic percentage depth profiles have a similar out-of-plane compositional gradient (Fig. 1d). \n\n![](images/5bff8af0cb7a86faabe264954a27bdd8627f10a71693fd108da1300b70243be3.jpg) \nFig. 1 | Spatial vertical segregation of the FA and Cs phases. a, Illustration of inhomogeneous phase distribution caused by out-of-plane FA and Cs segregation. b, Electrostatic potential image and molecular structure of PSP. c, Distribution of cations obtained from ToF-SIMS spectra for the reference (Ref.; blue) and PSP (red) devices. d, Atomic percentage profile of the reference (solid lines) and the PSP (dashed lines) extracted from depth-dependent XPS measurements. e,f, High-angle annular dark-field TEM images for the reference sample (e) and the PSP-treated sample (f). Scale bars, $200\\mathsf{n m}$ . The crosssectional samples were prepared with a stack configuration of ITO/PTAA/ \nperovskite/PTAA/Cu. The second row underneath each image shows highresolution TEM images collected from the corresponding boxes. Scale, $7.3\\times7.3$ nm. The third row shows the variation of calculated intensity over $3\\mathsf{n m}$ . The calculated interplanar spacing for each lattice is given in the corresponding images. g,h, Enlarged GIXRD spectra collected from the bottom of the reference perovskite film (g) and the PSP-treated perovskite film (h). Structural information with a spatially vertical resolution could be obtained by varying the incident angle of the X-ray beam. In g, the red and blue shading represents the Cs-rich phase and FA-rich phase, respectively. a.u., arbitrary units. \n\nThe out-of-plane cation inhomogeneity could potentially influence the perovskite lattice, thereby altering the crystal structure. Hence, it is crucial to systematically investigate the structural variations induced by cation inhomogeneities. We visualized the out-of-plane A-site compositional inhomogeneity by studying the lattice heterogeneity of various perovskite phases. We collected cross-sectional transmission electron microscopy (TEM) images. Three regions across the perovskite films (denoted as surface, bulk and bottom) were selected to survey the interplanar spacing of the lattice $(d)$ , which is a direct indication of phase heterogeneity. Vertical gradients for the cation distributions were directly observed by comparing the values of $d_{\\{200\\}}$ . For the reference film, the three $d$ values were measured to be $\\overset{\\cdot}{d}_{\\mathrm{surface}}=3.20\\overset{\\circ}{\\mathrm{A}}$ , $d_{\\mathrm{bulk}}=3.15\\mathring\\mathrm{A}$ and $d_{\\mathrm{{bottom}}}=3.11{\\mathring{\\mathsf{A}}}$ (Fig. 1e). The decreasing trend of the $d$ values correlates with the increasing internal lattice stress within the perovskite film. The decrease in $d_{\\mathrm{{bottom}}}$ suggests that there is a significant lattice mismatch at the bottom of the film15. This could be ascribed to the relatively smaller Cs atoms accumulating at the bottom, thereby generating a Cs-rich perovskite phase. Importantly, the detected lattice contraction implies that cation inhomogeneity is a contributory factor to the lattice strain16,17. In contrast, as shown in Fig. 1f, negligible variation of the d values was found in the PSP-treated film, which has $d_{\\mathrm{surface}}=3.13{\\mathring{\\mathsf{A}}}$ , $d_{\\mathrm{bulk}}=3.13\\mathring\\mathrm{A}$ and $d_{\\mathrm{{bottom}}}=3.13\\mathring{\\mathsf{A}}$ . This finding indicates that PSP treatment provides a better out-of-plane lattice alignment and releases the lattice stress by inhibiting phase segregation. \n\nWe employed the grazing incident X-ray diffraction (GIXRD) technique to detect the crystal structure from the exposed lower interface (Fig. 1g and Extended Data Fig. 1). For the reference film, the peaks are at around $28.1^{\\circ}$ , which are indexed for the (200) plane of perovskite. The split is significantly wider. Shoulder peaks emerge at around $28.4^{\\circ}$ when the incident angle was lower than $2^{\\circ}$ . These emergent shoulder peaks gradually weaken with an increase of the incident angle and ultimately vanish. The spectrum changes to stronger integrated peaks when the incident angle is larger than 3°. In contrast, the shoulder peaks are negligible after introducing the PSP (Fig. 1h). Moreover, a vertical misalignment of the peaks, which is an indication of the internal strain caused by lattice mismatch, is observed for the reference and PSP-1.2 films (Supplementary Figs. 5 and  6), which agrees well with the findings of the microscale TEM measurements. These results suggest that there is an out-of-plane inhomogeneous crystal structure within the reference perovskite film. The shoulder peaks may be associated with an undesired Cs-rich phase2 in the buried region of the perovskite film. \n\nWe presume, according to the coherence between 2θ and the lattice space, that the shoulder peaks can be attributed to a Cs-rich phase caused by Cs incorporation15,18,19. Considering the conventional X-ray diffraction (XRD) results (Supplementary Figs. 7 and  8), we may conclude that the spatially out-of-plane compositional inhomogeneity is generated by segregation of the FA and Cs phases in the perovskite films, even for ${\\bf C}s/({\\bf C}s+{\\bf F}{\\bf A})$ ratios as low as $5\\%$ . The Cs-rich phase prefers to accumulate in the bottom region within perovskite films, thus leading to a gradient in the phase distribution from Cs-poor to Cs-rich from the surface to the bottom. \n\nConsequently, the results obtained allow us to conclude that in FA-Cs perovskite films, the different sizes of the cations of FA and Cs result in a spatially out-of-plane lattice mismatch. As shown in Fig. 1a, from top to bottom, there is a FA-rich phase, a phase in which the cations have nominal stoichiometry and a Cs-rich phase. \n\n# Origin of the cation inhomogeneity \n\nWe performed in situ synchrotron radiation grazing incidence wide-angle X-ray scattering (GIWAXS) to investigate the two critical kinetics processes of crystallization and phase transition during perovskite formation. As demonstrated in Fig. 2a, signals for a q vector of around 0.8, 0.82 and $1.0\\mathring{\\mathsf{A}}^{-1}$ can be assigned to the δ-phase perovskite of 2H (100), 6H (101), and $\\upalpha$ -phase perovskite, respectively20. We defined two periods when analysing the kinetic processes. Period I was from after chlorobenzene dripping until the emergence of $\\upalpha$ -phase perovskite. The duration of this period is indicative of the crystallization rate. Period II was the duration it took for the $\\upalpha$ phase to become stable, which reflects the δ- to $\\upalpha$ -phase transition rate. From the in situ GIWAXS results, we found that the introduction of PSP accelerates both the crystallization and phase transition. Combined with the results from ‘Out-of-plane cation inhomogeneity’, this shows that PSP has effectively inhibited the segregation of the FA and Cs phases. A possible kinetical culprit for the phase segregation is the slow speeds of crystallization and phase transition. \n\nWe further conducted density functional theory computations to thermodynamically investigate the barrier energy $(E_{\\mathtt{B}})$ for perovskite crystallization and phase transition and subdivided the energy into the processes for the FA and Cs components. The difference between the barrier energies was defined as $\\overset{\\cdot}{\\Delta E_{\\mathrm{B}}}=E_{\\mathrm{B}}^{\\mathrm{FA}}-E_{\\mathrm{B}}^{\\mathrm{Cs}}$ . To evaluate more accurately the imbalance between the FA and Cs components, we calculated the mismatch factor $\\mu=\\frac{E_{\\mathrm{{B}}}^{\\mathrm{{FA}}}-E_{\\mathrm{{B}}}^{\\mathrm{{Cs}}}}{E_{\\mathrm{{s}}}^{\\mathrm{{FA}}}}$ EB −FAEB . As shown in Fig. 2b,c, during period I, for the reference system, ref = 101.6 meV. After the PSP was introduced, $\\Delta E_{\\mathrm{B,l}}^{\\mathrm{\\Delta\\PSP}}=35.3\\mathrm{me}$ V. The corresponding $\\mu$ values were calculated to be $\\mu_{\\mathrm{l,ref}}{=}20.48\\%$ and $\\mu_{\\scriptscriptstyle{1,\\mathrm{PSP}}}=5.34\\%$ . During period II, for the reference system, $\\Delta E_{\\mathrm{B,II}}^{\\mathrm{~\\tiny~{ref}}}=82$ meV with $\\mu_{\\mathrm{ref}}=12.49\\%$ , whereas $\\Delta E_{\\mathrm{B,II}}^{\\mathrm{~\\tiny~{~PSP}}}=-6$ meV with $\\mu_{\\tt P S P}=-1.79\\%$ for the PSP system (Supplementary Table 2). The lower $\\mu_{\\mathrm{{l}}}$ and $\\mu_{\\mathfrak{u}}$ for the PSP system indicate that the differences in the crystallization and phase transition rates of the FA and Cs components were reduced. Such differences in the rates for cations were probably responsible for the tardiness observed by in situ GIWAXS. A possible reason for the cation inhomogeneity could be the soft base property of the Cs cations compared to the FA cations, which may lead to a much more intensive interaction with $\\mathsf{P b l}_{3}^{-}$ , leading to Cs preferentially aggregating at the bottom. Additionally, the difference in the solubilities of Cs and FA components might partially also contribute to the cation inhomogeneity21. \n\nWe collected adsorption spectra of the Pb $\\mathsf{L}_{\\mathsf{I I I}}$ edge using extended X-ray absorption fine spectroscopy (EXAFS) to evaluate the interactions between PSP and perovskite. We selected five grazing incident angles to capture information at various depths within the perovskite film (Supplementary Fig. 12). As shown in Fig. 2d,e, peaks at radial distances of approximately 2.2 and $2.9\\mathring{\\mathbf{A}}$ can be attributed to Pb–O and Pb–I coordination, respectively22. In the reference film, we observed a gradual downwards shift of around $0.03{\\mathring{\\mathbf{A}}}$ for the Pb–I coordination with an increase in detection depth (Fig. 2d). This indicates that the lattice was compressed at the bottom of the perovskite23. In contrast, the peaks associated with Pb–I coordination remained relatively stable upon the incorporation of PSP, further reinforcing the existence of out-of-plane cation inhomogeneity. Notably, in the PSP film, peaks corresponding to Pb–O coordination migrated by a higher radial distance as the depth increased (Fig. 2e). This suggests the creation of a longer Pb–O coordination at the bottom of the film. By calculating of the $\\mathsf{P b}{-}\\mathsf{O}$ coordination ratio as (Pb–O)/ $((\\mathbf{Pb-O})+(\\mathbf{Pb-I}))$ (Fig. 2f), we concluded that Pb atoms at the bottom of the perovskite film tend to coordinate with additional oxygen atoms from PSP. Consequently, we hypothesize that PSP possibly interacts with the Pb atoms in perovskite through electrons donated by its two oxygen atoms. \n\nTo precisely evaluate the interaction between PSP and $\\mathbf{Pbl}_{2}.$ , we synthesized $(\\mathsf{P b l}_{2})_{x}(\\mathsf{P S P})_{y}$ complex crystals (Extended Data Fig. 2 and Supplementary Fig. 13), and performed Fourier transform infrared spectroscopy (FTIR) measurements. Peaks at around 1,328, 1,133 and $964\\thinspace\\mathrm{cm^{-1}}$ correspond to asymmetric stretching vibration $(\\nu_{\\mathrm{as}})$ and symmetric stretching vibration $(\\nu_{s})$ of the sulfone ( $scriptstyle\\mathbf{\\overbar{O}}=\\mathbf{S}=\\mathbf{0}$ ) and vibration $(\\nu)$ of the sulfoxide $(\\mathsf{S}\\mathrm{=}0)$ group, respectively. Significant shifts in all three characteristic peaks indicate the coordination of PSP with $\\mathsf{P b l}_{2}$ through the sulfone $scriptstyle\\mathbf{\\bar{O}}=\\mathbf{S}=\\mathbf{O}$ ) group (Fig. 2g). The upward shifts of the $\\nu_{\\mathrm{as}}$ and $\\nu_{\\mathrm{s}}$ peaks imply that both oxygen atoms from PSP may serve as active sites. Additionally, nuclear magnetic resonance (NMR) spectra corroborated the coordination of the $scriptstyle0=\\mathbf{S}=0$ group with $\\mathsf{P b l}_{2}$ . This was discerned through shifts in the carbon atoms adjacent to the $scriptstyle0=\\mathbf{S}=0$ group (nos. 1, 2, 6, 11 and 14) to a higher field (Extended Data Fig. 3). These findings align with the decreased $\\mathsf{P b l}_{2}$ signal observed by in situ GIWAXS tests and the peak shifts detected in XPS measurements (Supplementary Fig. 14). \n\n# Optoelectronic properties \n\nBesides retarding the phase segregation, PSP has a practical passivation effect. The steady-state and time-resolved photoluminescence were examined to optically evaluate changes in recombination caused by \n\n# Article \n\n![](images/da91682cfd2b5aa883ae83249f1e3c49a7b5fa6dc7a6a83150f65b7ae7b39202.jpg) \nFig. 2 | Revealing the origin of the segregation of the FA and Cs phases. and red solid lines indicate the free energy evolution of $\\mathsf{F A P b l}_{3}$ and $\\mathsf{C s P b l}_{3}$ , a, In situ GIWAXS pattern revealing processes of crystallization and phase respectively. d,e, Plots of Fourier-transformed R space results of EXAFS transition. The  colour bars range from 0 to 1. b,c, Schematics of computation measurements of the reference films (d) and PSP films (e). The dashed lines at results for free energy evolution in the reference system (b) and PSP system (c) 2.9 Å and 2.2 Å correspond to the Pb–I and Pb–O coordination, respectively. during crystallization and the phase transition. The blue and red rectangles f, Pb–O coordination ratios calculated from the EXAFS measurements. g, FTIR represent the relevant $\\mathsf{F A P b l}_{3}$ phases and $\\mathsf{C s P b l}_{3}$ phases, respectively. The blue spectra of PSP and the PSP(PbI2) complex. CB, chlorobenzene. \n\nthe out-of-plane lattice mismatch. In Fig. 3a, a significantly stronger photoluminescence peak was observed for the PSP film relative to that of the reference film. Moreover, the carrier lifetime of the PSP-treated film was extended to 1,876.6 ns compared with 491.7 ns for the reference (Fig. 3b and Supplementary Table 3). We used thermal admittance spectroscopy to characterize the trap density of the perovskite films. Supplementary Fig. 17 depicts that the trap density of states decreased after PSP introduction at shallow and deep energetic levels. Shallow traps could be attributed to a homogeneous phase distribution, which may inhibit the formation of vacancies. Further, a released spatial lattice mismatch is beneficial for stabilizing octahedral frameworks, which in turn positively reduces the metal-related deep defects24,25. We further modelled the lattice and calculated the defect formation energy using $\\mathbf{FA}_{0.95}\\mathbf{Cs}_{0.05}\\mathbf{Pbl}_{3}$ perovskite (Fig. 3c and Supplementary Fig. 19). Figure 3d shows that the defect formation energy of a series of defects was increased after PSP introduction, especially for the Pb and I vacancies, which should result in lower defect densities and longer carrier lifetimes in experiments. \n\nEfficient carrier diffusion and extraction are affected by the vertical band alignment of different phases within a perovskite film, which correlates with the out-of-plane compositional inhomogeneity. Depth-profile ultraviolet-photoelectron spectroscopy was carried out to evaluate the internal band alignment (Extended Data Fig. 4). Figure 3e shows that the out-of-plane compositional inhomogeneity may lead to quasi-type I band alignment at the contact region of the Cs-rich phase with a thickness of a few hundreds of nanometres. The conduction-band minimum and valence-band maximum are downwards and upwards twisted, respectively. This band alignment adversely affects carrier transport for solar cells through electrical doping26 whether in a p–i–n or n–i–p configuration (Extended Data Fig. 5). In this case, the inherent disequilibrium of electron–hole extraction would be seriously aggravated27,28. Ultimately, it would worsen the device efficiency, especially the fill factor29–31. After PSP introduction, the band diagram had a favourable flattened alignment, mitigating energy losses of charge carriers within perovskite films (Fig. 3f). The findings from transient adsorption measurements align with the conclusion obtained from energy band alignment (Extended Data Fig. 6). Moreover, we tested the built-in electrical field $(V_{\\mathbf{bi}})$ in a $\\mathsf{p}{\\mathsf{-i-n}}$ device. The improved $V_{\\mathbf{bi}}$ was beneficial for carrier diffusion as well (Supplementary Fig. 20). \n\n# Device performance \n\nWe fabricated devices with a p–i–n stack of indium tin oxide (ITO)/ poly(triaryl)amine (PTAA) $\\mathrm{\\primeFA_{0.95}C s_{0.05}P b l_{3}/C_{60}/}$ bathocuproine (BCP)/ \n\n![](images/98e999442b2b632c22e1ae79102a1a1a75f0b7aac8a350778796d590dc8dcbd8.jpg) \nFig. 3 | Optoelectronic properties. a, Steady-state photoluminescence (PL) spectra of perovskite films with and without PSP treatment deposited onto quartz glass substrates. b, Time-resolved PL spectra of perovskite films deposited onto quartz glass substrates. The solid lines are fitted using the dual exponential fitting method. c, Constructed lattice model of $\\mathbf{\\ddot{F}A_{0.95}C s_{0.05}P b l_{3}}$ perovskite. The (100) plane of the lattice was exposed so that it could adsorb a PSP molecule for the density functional theory computation. d, Statistics for \nthe defect formation energy for various types of defect in the reference and PSP systems. e,f, Schematics for the band alignment within the reference perovskite film (e) and the PSP perovskite film (f). The values of the conductionband minimum, valence-band maximum and Fermi level $(E_{\\mathrm{{F}}})$ were extracted from the depth-profile ultraviolet-photoelectron spectrum. The schematics were finally obtained by combining data from three depth regions with a manually aligned $E_{\\mathrm{{F}}}$ HTL, hole-transport layer; ETL, electron-transport layer. \n\nAg. The bandgap of this perovskite recipe was determined to be 1.51 eV by the Tauc plot method (Supplementary Figs. 21) and by using the derivative of the external quantum efficiency (EQE) of the solar cell (Extended Data Fig. 7). The champion device yielded a notable PCE of up to $26.09\\%/25.16\\%$ (reverse/forward scan direction) whereas the reference cell had PCEs of $24.62\\%/23.48\\%$ (Fig. 4a). The corresponding steady-state power output efficiencies were $25.15\\%$ and $23.72\\%$ , respectively. An unencapsulated device achieved certified PCEs of $25.8\\%$ and $25.2\\%$ for the reverse scan and for the steady-state output, as certified by an independent organization (Supplementary Fig. 22). The fill factor of the champion device exceeded $85\\%$ , which is nearly $95\\%$ of the theoretical limit $(89.5\\%)$ . We attributed the remarkable fill factor improvement to the improved charge carrier extraction, which is supported by the efficiency improvement in the n–i–p configuration as well (Supplementary Fig. 23). The open-circuit voltage $(V_{\\mathrm{oc}})$ improved from 1.145 to 1.164 V, which is consistent with the reduced trap density. The short-circuit current density $(\\boldsymbol{J}_{\\mathrm{sc}})$ over $26\\mathsf{m A c m}^{-2}$ was consistent with the integrated $J_{\\mathrm{SC}}$ extracted from the incident photon-to-electron conversion efficiency (IPCE) (Fig. 4b). The reproducibility was evaluated using a batch of devices comprising 16 individuals for each set-up (Supplementary Fig. 25). We further tested the solar cells in a light-emitting diode (LED) mode. The LED $\\mathsf{E Q E}_{\\mathtt{E L}}$ improved from $7.1\\%$ to $9.7\\%$ (Fig. 4c), so that the emission peaks were around ${820}\\mathrm{nm}$ (Supplementary Fig. 26). We fabricated devices with an upscaled area of 1 $\\mathsf{c m}^{2}$ , and the efficiency improved from $21.78\\%$ to $23.64\\%$ (Fig. 4d). This improvement was mainly associated with the enhanced fill factor. Further devices with typical efficient perovskite formulas were fabricated to assess the universality of the PSP strategy (Supplementary Figs. 27–29), although some perovskite formulas still require further evaluation. \n\nDevice reliability was evaluated following the procedure specified in the ISOS protocols32. An unencapsulated PSP-treated device retained $92\\%$ of its initial PCE after 2,500 h of continuous tracking at the maximum power point in a nitrogen atmosphere. By contrast, the PCE of the reference device dropped to around $80\\%$ of its initial value under the same conditions (Fig. 4e). Damp-heat experiments were conducted using encapsulated devices in an ageing box with $85^{\\circ}\\mathrm{C}$ and $85\\%$ relative humidity. The PSP-treated device exhibited almost $90\\%$ efficiency after over 300 h on average, compared with around $80\\%$ for the initial PCE of the reference (Fig. 4f). Regarding the temperature cycling reliability, the encapsulated PSP-treated device retained $93\\%$ of its initial PCE after 300 cycles, compared to $67\\%$ for the reference (Extended Data Fig. 8). Overall, these findings provide an in-depth understanding of phase segregation and suggest a promising strategy for accelerating commercialization of perovskite photovoltaics. \n\n![](images/3c85644a839463c3a4860c351d18af209b4e515e6f6e5500f2149782b265f607.jpg) \nFig. 4 | Device performance and stability. a, J–V curves of champion p–i–n PSCs at laboratory scale. The active area was around $0.073\\mathsf{c m}^{2}$ . The inset shows the detailed photovoltaic parameters from the reverse scan and the steady-state power output. b, IPCE plots for the PSP solar cells. The solid red line is the integrated $J_{\\mathrm{SC}}$ . c, EQE curves measured for the reference and PSP solar cells in LED mode. The inset is a photograph showing the PSCs working in LED mode. ${\\bf d},J-$ –V curves of scaled-up PSCs with and without PSP. The inset is a photograph showing the scaled-up PSCs with 1 cm2 active area. e, Normalized evolution of the PCE for unencapsulated reference and PSP devices under continuous \ntracking at the maximum power point following the ISOS L-1I protocol. The initial PCEs of the reference and PSP devices were $25.40\\%$ and $23.54\\%$ , respectively. RT, room temperature. f, Results of damp-heat reliability tests of the encapsulated devices tested at $85^{\\circ}\\mathrm{C}$ and $85\\%$ relative humidity (RH) following the ISOS D-3 protocol. A device stack based on ITO/PTAA/perovskite $\\mathrm{\\langleC_{60}/A u}$ was used in the damp-heat tests. The solid lines represent the average PCE for six individual devices. The initial average PCEs of the reference and PSP devices were $19.2\\%$ and $21.8\\%$ . The error bars denote the standard deviation. champ., champion; FF, fill factor. \n\n# Online content \n\nAny methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-023-06784-0. \n\n1. Li, Z. et al. Stabilizing perovskite structures by tuning tolerance factor: formation of formamidinium and cesium lead iodide solid-state alloys. Chem. Mater. 28, 284–292 (2015). \n2. Yi, C. et al. Entropic stabilization of mixed A-cation ABX3 metal halide perovskites for high performance perovskite solar cells. Energy Environ. Sci. 9, 656–662 (2016). \n3. Li, N. et al. Microscopic degradation in formamidinium-cesium lead iodide perovskite solar cells under operational stressors. Joule 4, 1743–1758 (2020). \n4. Bai, Y. et al. Initializing film homogeneity to retard phase segregation for stable perovskite solar cells. Science 378, eabn3148 (2022). \n5. Yoo, J. J. et al. Efficient perovskite solar cells via improved carrier management. Nature 590, 587–593 (2021). \n6. Jiang, Q. et al. Surface reaction for efficient and stable inverted perovskite solar cells. Nature 611, 278–283 (2022). \n7. Zhao, Y. et al. Inactive $(\\mathsf{P b l}_{2})_{2}\\mathsf{R b c l}$ stabilizes perovskite films for efficient solar cells. Science 377, 531–534 (2022). \n8. Kim, G. et al. Impact of strain relaxation on performance of α-formamidinium lead iodide perovskite solar cells. Science 370, 108–112 (2020). \n9. Bu, T. et al. Lead halide-templated crystallization of methylamine-free perovskite for efficient photovoltaic modules. Science 372, eabh1035 (2021). \n10.\t Liu, L. et al. A-site phase segregation in mixed cation perovskite. Mater. Rep., Energy 1, 100064 (2021). \n11. Correa-Baena, J.-P. et al. Homogenized halides and alkali cation segregation in alloyed organic–inorganic perovskites. Science 363, eaah5065 (2019). \n12. Lee, J. W. et al. Rethinking the A cation in halide perovskites. Science 375, eabj1186 (2022). \n13.\t Jeon, N. J. et al. Solvent engineering for high-performance inorganic–organic hybrid perovskite solar cells. Nat. Mater. 13, 897–903 (2014). \n14. Ren, Y. et al. A bi-functional additive for linking $\\mathsf{P l}_{2}$ and decreasing defects in organo-halide perovskites. J. Alloys Compd. 758, 171–176 (2018). \n15. Kim, H.-S. & Park, N.-G. Importance of tailoring lattice strain in halide perovskite crystals. NPG Asia Mater. 12, 78 (2020). \n16.\t Turren-Cruz, S.-H. et al. Methylammonium-free high-performance, and stable perovskite solar cells on a planar architecture. Science 362, eaat3583 (2018). \n17.\t Zhu, C. et al. Strain engineering in perovskite solar cells and its impacts on carrier dynamics. Nat. Commun. 10, 815 (2019). \n18.\t Kubicki, D. J. et al. Phase segregation in Cs-, Rb- and K-doped mixed-cation (MA)x(FA)1−xPbI3 hybrid perovskites from solid-state NMR. J. Am. Chem. Soc. 139, 14173–14180 (2017). \n19. Chen, L. et al. Toward long-term stability: single-crystal alloys of cesium-containing mixed cation and mixed halide perovskite. J. Am. Chem. Soc. 141, 1665–1671 (2019). \n20.\t Proppe, A. H. et al. Multication perovskite 2D/3D interfaces form via progressive dimensional reduction. Nat. Commun. 12, 3472 (2021). \n21. Zheng, Y. et al. Downward homogenized crystallization for inverted wide‐bandgap mixed‐ halide perovskite solar cells with $21\\%$ efficiency and suppressed photo‐induced halide segregation. Adv. Funct. Mater. 32, 2200431 (2022). \n22.\t Kang, D.-H. et al. Extended X-ray absorption fine structure (EXAFS) of $\\mathsf{F A P b l}_{3}$ for understanding local structure–stability relation in perovskite solar cells. J. Energy Chem. 67, 549–554 (2022). \n23.\t Park, J. et al. Controlled growth of perovskite layers with volatile alkylammonium chlorides. Nature 616, 724–730 (2023). \n24.\t Zhou, Y., Poli, I., Meggiolaro, D., De Angelis, F. & Petrozza, A. Defect activity in metal halide perovskites with wide and narrow bandgap. Nat. Rev. Mater. 6, 986–1002 (2021). \n25. Shao, Y. et al. Origin and elimination of photocurrent hysteresis by fullerene passivation in $\\mathsf{C H}_{3}\\mathsf{N H}_{3}\\mathsf{P b l}_{3}$ planar heterojunction solar cells. Nat. Commun. 5, 5784 (2014). \n26. Euvrard, J. et al. Electrical doping in halide perovskites. Nat. Rev. Mater. 6, 531–549 (2021). \n27. Eperon, G. E. et al. Formamidinium lead trihalide: a broadly tunable perovskite for efficient planar heterojunction solar cells. Energy Environ. Sci 7, 982–988 (2014). \n28.\t Herz, L. M. Charge-carrier mobilities in metal halide perovskites: fundamental mechanisms and limits. ACS Energy Lett. 2, 1539–1548 (2017). \n29. Peng, J. et al. Centimetre-scale perovskite solar cells with fill factors of more than 86 per cent. Nature 601, 573–578 (2022). \n30.\t Ding, Y. et al. Single-crystalline $\\mathsf{T i O}_{2}$ nanoparticles for stable and efficient perovskite modules. Nat. Nanotechnol. 17, 598–605 (2022). \n31.\t Cao, Q. et al. Efficient and stable inverted perovskite solar cells with very high fill factors via incorporation of star-shaped polymer. Sci. Adv. 7, eabg0633 (2021). \n32.\t Khenkin, M. V. et al. Consensus statement for stability assessment and reporting for perovskite photovoltaics based on ISOS procedures. Nat. Energy 5, 35–49 (2020). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 \n\n# Article Methods \n\n# Materials \n\nLead iodide $\\left(\\mathsf{P}\\mathsf{b}\\mathsf{I}_{2}\\right.$ , $99.999\\%$ ), lead bromide $(\\mathsf{P b B r}_{2},$ , $99.999\\%\\rangle$ ), caesium iodide (CsI, $99.999\\%$ ), bis(trifluoromethane)sulfonimide lithium salt (Li-TFSI, $99.95\\%$ ) and 4-tert-butylpyridine were purchased from Sigma Aldrich. Formamidinium iodide, methylammonium (MA) bromide and methylammonium chloride (MACl) were synthesized in house by reacting equal molar amounts of formamidine (FA) acetate and methylamine alcohol solution with the corresponding halogen acid33. PSP was synthesized in a laboratory according to the method mentioned in the Supplementary Information. PTAA, $2{,}2{^{\\prime}}{,}7{,}7{^{\\prime}}$ -tetrakis[N,N-di (4-methoxyphenyl)amino]- ${\\mathfrak{g}},{\\mathfrak{g}}^{\\prime}$ -spirobifluorene (spiro-OMeTAD) and BCP were purchased from Lumtec. Tin (IV) oxide $(\\mathsf{S n O}_{2},15\\%$ in ${\\sf H}_{2}{\\sf O}$ colloidal dispersion) was purchased from Alfa Aesar. Fullerene $\\left(\\mathbf{C}_{60}\\right)$ was purchased from Nano-C. All solvents used in the experiments, includ$\\operatorname{ing}N,N.$ -dimethylformamide $(99.8\\%)$ , dimethyl sulfoxide (anhydrous, $99.9\\%$ ), chlorobenzene (anhydrous, $99.8\\%$ ), acetonitrile $(99.9\\%)$ and isopropyl alcohol (anhydrous, $99.8\\%$ ), were purchased from Sigma Aldrich. All chemicals were used as received without any further purification. \n\n# Perovskite precursor solution \n\nThe perovskite precursor solution was prepared by dissolving $\\mathsf{F A P b l}_{3}$ (1.71 M) powder and $\\mathsf{C s P b l}_{3}$ powder (0.09 M) in a mixture of the solvents dimethylformamide and dimethyl sulfoxide $(8{:}1\\upnu/\\upnu)$ . $0.5\\%\\mathsf{M A P b B r}_{3}$ powder, $7.2\\%\\mathsf{P b l}_{2}$ and $30\\%$ MACl with molar ratio were added to increase the crystallinity34. For a solution with PSP agents, PSP powder was directly added into the perovskite precursor solution with different concentrations. PSP at 1.2, 2.4 and $4.8\\mathrm{{mg}\\mathrm{{ml}^{-1}}}$ was added to perovskite precursors for comparison (denoted as PSP-1.2, PSP-2.4 and PSP-4.8, respectively). The obtained precursor was vigorously shaken at room temperature for over 3 h. Finally, the perovskite precursor solutions were filtered through $0.22\\upmu\\mathrm{m}$ polytetrafluoroethylene filters before use. \n\n# Device fabrication \n\nThe devices with the p–i–n configuration were fabricated as follows. Prepatterned ITO-coated glass substrates (7 Ω per square) were cleaned by sequential ultrasonication in detergent, deionized water, acetone and isopropanol each for 15 min, respectively. The cleaned substrates were dried under a flow of clean ${\\sf N}_{2}$ and further dried in a $60^{\\circ}\\mathsf{C}$ oven overnight. Before depositing the hole transport layer, the substrates were exposed to oxygen plasma cleaner for 5 min and then transferred into an ${\\sf N}_{2}$ glovebox immediately for rest deposition progress. PTAA solution $(2.5\\mathsf{m g}\\mathsf{m l}^{-1}$ dissolved in chlorobenzene) was spin-coated onto the substrate at 6,000 rpm for 30 s, then annealed at $100^{\\circ}\\mathsf C$ for $15\\mathrm{{min}}$ . The perovskite layer was deposited by one-step spin-coating of the filtered precursor solution at 1,000 rpm for 10 s and 4,000 rpm for $40{\\mathsf{s}}.$ Then $200{\\upmu\\mathrm{l}}$ of chlorobenzene was quickly dropped onto the centre of the spinning substrate at 15 s before the end. The film was immediately annealed at $100^{\\circ}\\mathsf{C}$ for 30 min. After cooling down to room temperature, $100\\upmu\\mathrm{l}$ of phenethylammonium iodide or $n$ -octylammonium iodide solution $(5\\mathrm{{mg}\\mathrm{{ml^{-1}})}}$ was dynamically coated onto the perovskite films at 3,000 rpm for 30 s, followed by annealing at $100^{\\circ}\\mathsf{C}$ for 5 min. The device fabrication was accomplished after sequential thermal evaporation of $\\mathbf{C}_{60}$ $(30\\mathsf{n m},0.1\\mathring{\\mathrm{A}}\\mathsf{s}^{-1})$ , BCP $(7\\mathsf{n m},0.1\\mathrm{\\AA}\\mathsf{s}^{-1})$ and Ag $\\mathtt{i00}\\mathtt{n m}$ , $0.2\\mathring{\\mathrm{A}}\\mathsf{s}^{-1}\\big)$ in a high-vacuum chamber $(7\\times10^{-5}\\mathsf{P a})$ . Note that all procedures for device fabrication were conducted in a nitrogen glovebox 1 $\\mathrm{\\langle{O}}_{2}$ and ${\\mathsf{H}}_{2}{\\mathsf{O}}$ less than 0.1 ppm). \n\nThe devices with the n–i–p configuration were fabricated as follows. After the same pretreatment of the ITO substrates, $\\mathsf{S n O}_{2}$ in a colloidal dispersion (diluted by $\\pmb{1}{:}4\\mathbf{v}/\\mathbf{v}$ with deionized ${\\displaystyle{\\sf H}_{2}{\\sf O}}_{\\displaystyle{\\cal I}}^{\\prime}$ ) was spin-coated onto the substrates at 3,000 rpm for $30{\\mathsf s}_{\\r{\\r{\\r{\\r{\\r{\\theta}}}}}}$ , and sequentially annealed at $180^{\\circ}\\mathrm{C}$ for 50 min in air $35\\%$ relative humidity). The procedures for perovskite film deposition were the same as those for the p–i–n devices. A solution of hole transport material was prepared 30 min before use by mixing spiro-OMeTAD $(91\\mathrm{mg})$ ) and 4-tert-butylpyridine $(36\\upmu\\mathrm{l})$ in chlorobenzene $\\left(1\\mathsf{m}\\mathsf{l}\\right)$ . Li-TFSI $(23\\upmu\\mathrm{l}$ , $520\\mathrm{mg}\\mathrm{ml}^{-1}$ in acetonitrile) was doped to improve its conductivity. $50\\upmu\\upmu\\upmu\\upmu$ of the solution of hole transport material was dynamically spin-coated onto the perovskite films at 3,000 rpm for 30 s in a nitrogen-filled glovebox. Finally, gold electrodes $(100\\mathsf{n m},0.2\\mathrm{\\AA}\\mathsf{s}^{-1})$ were deposited through thermal evaporation. \n\n# Photovoltaic performance characterization \n\nThe J–V measurements were carried out with a xenon lamp-based solar simulator (Enlitech SS-F5-3A, Class AAA) and a source meter (Keithley 2400). The simulated AM 1.5G irradiation $(100\\mathsf{m}\\mathsf{W}\\mathsf{c m}^{-2},$ was calibrated by a standard silicon cell (traced to NREL, SRC-2020). The solar cells were measured with a metal mask with an area of $7.485\\mathrm{mm}^{2}$ to accurately define the active area. The voltage was applied from $-0.2$ to 1.3 V with a scanning rate of $0.2\\mathrm{V}\\mathsf{s}^{-1}$ , and the voltage step was $20\\mathrm{mV}.$ All devices were measured immediately after fabrication in an ${\\sf N}_{2}$ glovebox. The IPCE was measured in a.c. mode on the xenon lamp-based system (Newport TLS260-300X). The scan range was from 300 to $1,000{\\mathsf{n m}}$ . The solar cells were measured in LED mode in ${\\bf N}_{2}$ using a home-made motorized goniometer set-up consisting of a source meter unit (Keithley 2400), a calibrated Si photodiode (FDS-100-CAL, Thorlabs), a pico-ammeter (4140B, Agilent) and a calibrated fibre optic spectrophotometer (UVN-SR, StellarNet Inc.). The distance between the LED device and the photodetector was $59.5\\mathsf{m m}$ . \n\n# Stability characterization \n\nA home-made calibrated LED-based solar simulator with an intensity of $100\\mathrm{mW}\\mathrm{cm}^{-2}$ was used as an illumination source in the stability tests. The tracking of the maximum power point was performed in $\\mathsf{N}_{2}$ A blower was used to ensure the device was at a constant temperature. A home-made system was used to acquire the continuous power evolution. Devices for the damp-heat test were encapsulated with epoxy. The Ag electrodes were replaced by Au, and BCP was removed from the device. The damp-heat tests and thermal cycling tests were conducted in a customized ageing box. The accuracies of the temperature and humidity were under $\\pm1^{\\circ}\\mathsf{C}$ and $\\pm5\\%$ , respectively. The damp-heat tests were periodically performed during the J–V scan after cooling down in ${\\sf N}_{2}$ for around $30\\mathrm{min}$ . The thermal cycling tests were carried out by repeatedly performing the J–V characterization after the stages for stabilizing the temperature. \n\n# Cross-sectional microstructure characterization \n\nNote that all measurements, unless otherwise specified, were conducted with a perovskite formulation of $\\mathbf{FA}_{0.95}\\mathbf{Cs}_{0.05}\\mathbf{Pbl}_{3}$ . The samples were prepared with ITO/PTAA/perovskite/PTAA/Cu stacks, in which a higher concentration of PTAA solution $(30\\mathrm{mg}\\mathrm{ml}^{-1}$ in chlorobenzene) and thermally evaporated copper $(200\\mathsf{n m},0.2\\mathrm{\\AA}\\mathsf{s}^{-1})$ were used. Thick layers of PTAA and copper on the perovskite films can protect the samples from milling damage35. The other procedures were the same as in device fabrication apart from the absence of surface passivation. Pt and carbon layers were deposited before thinning using focused ion beam (FIB) equipment (ThermoFisher Helios 5 CX). A thick plate was extracted from the bulk sample at $30\\up k\\upnu$ and 3,000–30,000 pA, which was welded onto a Cu grid (omniprobe grid) by a probing system. The thick plate was first thinned at $30\\upkappa\\upnu$ and 50–1,000 pA and then at a lower current of 10–30 pA. Finally, the specimen was completed by thinning at a lower voltage of 1 kV and 30–50 pA after beam showering at $3\\upkappa\\upnu$ and $10{-}30\\mathbf{pA}$ . The samples were immediately transferred to a TEM system (ThermoFisher Talos F200S). High-angle annular dark-field images across the full cross section of the samples and high-resolution TEM images were collected at an acceleration voltage of $200\\mathsf{k V}.$ \n\n# Structure characterization \n\nXRD and GIXRD data were acquired from a diffractometer (SmartLab, Rigaku) using Cu Kα $\\left(\\lambda{=}1.5406\\mathrm{\\AA}\\right.$ ) radiation. The tests were performed by scanning 2θ of $5^{\\circ}-45^{\\circ}$ with a scan rate of $3^{\\circ}\\mathsf{m i n}^{-1}$ and $0.02^{\\circ}$ per step. The GIXRD tests detected signals from the bottom side of the perovskite films at grazing incident angles of $0.1^{\\circ},0.4^{\\circ},0.8^{\\circ},1^{\\circ},2^{\\circ},3^{\\circ},4^{\\circ}$ and $5^{\\circ}$ . The corresponding penetration depths for the perovskite material were calculated36 as described in the Supplementary Information. \n\n# Depth profiling characterization \n\nThe depth profiles of perovskite deposited onto ITO substrates were recorded using a ToF-SIMS system (TOF-SIMS 5, ION-TOF) with a $\\mathbf{B}\\mathbf{i}^{3+}$ primary beam (25 keV, 1 pA) and an oxygen sputter beam $(1\\mathsf{k e V},45\\mathsf{n A})$ . Note that an oxygen sputter gun can help in expelling pollution from the perovskite surface37. Samples were prepared with the full solar cell configuration for the depth-dependent photoelectron spectroscopy with an integrated etching system (ThermoFisher, ESCALAB Xi+). \n\n# Synchrotron radiation characterization \n\n$\\mathsf{P b}\\mathsf{L}_{\\mathsf{I I I}}$ -edge EXAFS data were collected on the BL13SSW beamline at the Shanghai Synchrotron Radiation Facility (SSRF) using the top-up mode operation with a ring current of $200\\mathrm{{mA}}$ at $3.5{\\mathrm{GeV.}}$ From the high-intensity X-ray photons of the multipole wiggler source, monochromatic X-ray beams could be obtained using a liquid-nitrogen-cooled double-crystal monochromator with a Si(111) crystal pair. For each grazing incident angle, X-ray absorption spectra were recorded in fluorescence mode using an ${\\sf N}_{2}/{\\sf A}{\\sf r}$ mixed-gas-filled ionization chamber and passivated implanted planar silicon (Canberra Co.) for the incident and fluorescent X-ray photons, respectively. Higher-order harmonic contamination was eliminated by detuning to reduce the incident X-ray intensity by about $30\\%$ . The energy calibration was performed with a Pb foil reference using the Athena package38. Fourier-transformed radial distribution functions of k3-weighted $\\mathsf{P b}\\mathsf{L}_{\\mathsf{I I I}}$ -edge EXAFS spectra $k^{3}\\chi(k)$ were obtained in the k range between 3.0 and $9.0\\mathring{\\mathsf{A}}^{-1}$ through a standard XAFS data-analysis process. In situ GIWAXS tests were performed at the beamlines BL14B1 and BL17B1 of SSRF. A two-dimensional detector (Rayonix MX300) was used to capture 360-frame spectra with 2 s intervals during spin-coating. Chlorobenzene dripping was automatically controlled in this experiment. \n\n# Other characterizations \n\nThe ultraviolet to visible absorption spectra were acquired with a spectrophotometer (Lambda 365, PerkinElmer). The photoluminescence and time-resolved photoluminescence were measured with a spectrofluorometer (Horiba Fluorolog-3 system). The excitation wavelength for the photoluminescence was $480\\mathsf{n m}$ . The time-resolved photoluminescence was measured using a $532\\mathsf{n m}$ laser nano-LED as an excitation source. All samples were deposited onto quartz glass. The morphology images were collected by a scanning electron microscope (Gemini SEM 500, Zeiss). The Mott–Schottky plots were measured with an applied bias range from $-0.1$ to 1.2 V. The built-in potential was determined using the equation $\\left({\\frac{A}{C}}\\right)_{\\cdot}^{2}={\\frac{2}{q\\varepsilon_{\\mathrm{{r}}}\\varepsilon_{0}N_{\\mathrm{{D}}}}}(V_{\\mathbf{{bi}}}-V)$ where A is the device area, $c$ the capacitance, $q$ the elementary charge, $V_{\\mathrm{bi}}$ the built-in potential, V the applied voltage, $\\varepsilon_{\\mathrm{r}}$ the dielectric constant, $\\scriptstyle{\\varepsilon_{0}}$ the permittivity of free space and $N_{\\mathrm{D}}$ the carrier density. The depletion width was calculated using $W{=}\\left(\\frac{2\\varepsilon_{\\mathrm{r}}\\varepsilon_{0}}{N_{\\mathrm{D}}}V_{\\mathrm{bi}}\\right)^{1}$ . The capacitance–frequency curves were measured over a frequency range from $10^{1}$ to $10^{6}\\mathsf{H z}$ using an electrochemical workstation (Zahner IM6ex). An a.c. amplitude voltage of $5\\mathsf{m V}$ was used, and the d.c. bias was kept at $_{0\\vee}$ to avoid the influence of the ferroelectric effect. The final trap density of states was calculated $\\mathrm{tDOS}(E_{\\omega})=-\\frac{\\mathrm{d}C}{\\mathrm{d}\\omega}\\frac{V_{\\mathrm{bi}}}{q W}\\frac{\\omega}{k_{\\mathrm{R}}T}$ $\\omega$ \ndepletion width, $k_{\\mathrm{B}}$ the Boltzmann constant and $T$ temperature. Here, $\\scriptstyle{E_{\\omega}=k_{\\mathrm{B}}T\\ln\\left({\\frac{\\omega_{0}}{\\omega}}\\right)}$ where $\\varOmega_{0}$ is the attempt-to-escape frequency at temperature $T$ . \n\n# Computational details \n\nAll the spin theoretical simulations in our work were carried out with the Vienna ab initio Simulation Package (VASP) v.5.4.4. The generalized gradient approximation with the Perdew–Burke–Emzerhof functional form was employed to evaluate the electron–electron exchange and correlation interactions. Projector augmented-wave methods were implanted to represent the core-electron (valence electron) interactions. The plane-wave basis function was set with a kinetic cutoff energy of $550\\mathrm{eV}$ . The ground-state atomic geometries were optimized by relaxing the force below $0.02\\mathrm{eV}/\\mathring{\\mathbf{A}}$ and the convergence criteria for energy was set with a value of $1.0\\times10^{-5}\\mathrm{eV}$ per cell. The Brillouin zone was sampled using Monkhorst–Pack meshes of size $5\\times5\\times1$ for the slab models. All slab models were modelled with a 20 Å vacuum layer. Gaussian smearing was employed for the stress/force relaxations. To better describe the interactions between molecules, van der Waal interactions were included with the zero damping DFT-D3 method of Grimme. The transition states during the reaction pathway were evaluated with the climbing-image nudged elastic band method. The convergence criteria for force were below 0.05 eV/Å. Only the gamma point was considered in this calculation. \n\n# Data availability \n\nThe data that support the findings of this study are available from the corresponding author (X.P.) upon request. \n\n33.\t Jeong, J. et al. Pseudo-halide anion engineering for $\\mathsf{\\alpha}_{\\mathsf{G}-\\mathsf{F A P b l}_{3}}$ perovskite solar cells. Nature https://doi.org/10.1038/s41586-021-03406-5 (2021). \n34.\t Min, H. et al. Perovskite solar cells with atomically coherent interlayers on $\\mathsf{S n O}_{2}$ electrodes. Nature 598, 444–450 (2021). \n35.\t Zhang, Y. et al. Achieving reproducible and high-efficiency $(>21\\%)$ perovskite solar cells with a presynthesized $\\mathsf{F A P b l}_{3}$ powder. ACS Energy Lett. 5, 360–366 (2019). \n36.\t Chateigner, D. Book review of Thin Film Analysis by X-ray Scattering by M. Birkholz with contributions by P. F. Fewster and C. Genzel. J. Appl. Crystallogr. 39, 925–926 (2006). \n37.\t Harvey, S. P. et al. Probing perovskite inhomogeneity beyond the surface: TOF-SIMS analysis of halide perovskite photovoltaic devices. ACS Appl. Mater. Interfaces 10, 28541–28552 (2018). \n38.\t Rehr, J. J. et al. Theoretical X-ray absorption fine structure standards. J. Am. Chem. Soc. https://doi.org/10.1021/ja00014a001 (1991). \n\nAcknowledgements This work was financially supported by the National Key R&D Program of China (grant no. 2021YFB3800102), the National Natural Science Foundation of China (grant nos. 52272252, U22A20142, 52302324 and 62204108), the Director’s Fund of the Hefei Institutes of Physical Science (grant no. YZJJ-GGZX-2022-01) and the Science Funds of Distinguished Young Scholars of Anhui Province (grant no. 2108085J34). We acknowledge use of the beamlines BL13SSW, BL14B1, BL17B1 and BL10U2 at SSRF, China, for the synchrotron radiation experiments. We thank S. He, Z. Su and L. Cheng from SSRF for support with the synchrotron radiation experiments. N.-G.P. acknowledges financial support through grants from the National Research Foundation of Korea, which is funded by the Korean Ministry of Science and ICT under contract NRF-2021R1A3B1076723 (Research Leader Program). S.D. acknowledges support from the 111 project (B16016) and the Beijing Key Laboratory of Novel Thin-Film Solar Cells. \n\nAuthor contributions Z.L., J.Y. and X.P. conceived the idea. J.Y. and X.P. supervised the project and process. Z.L. and H.X. fabricated the perovskite devices, conducted the photovoltaic performance characterizations and analysed the experimental data described in this manuscript. Z.L., Y.Z. and H.X. wrote the manuscript. Y.Z. performed the structural characterizations, including those using GIXRD and TEM, with the assistance of J.Z. under the supervision of B.X. and N.-G.P. W.C. assessed performance in LED mode with photoluminescence, time-resolved photoluminescence and IPCE measurements under the supervision of Z.X. T.K. and P.R. analysed the results of the optoelectronic characterizations. B.L. conducted the in situ GIWAXS measurements with help from S.D. J.Z., X.G. and Q.W. assisted in the EXAFS and WAXS measurements. D.-H.K. assisted in the EXAFS measurements and analysis under the supervision of N.-G.P. H.Z. and Z.W. assisted in the synthesis of perovskite materials and PSP molecules. H.H. conducted the density functional theory computations. X.C. helped in the FIB-TEM measurements and analysis of the results. H.Z. conducted the SEM measurements. T.K., B.X., Z.X., S.D., N.-G.P., J.Y. and X.P. revised the manuscript. All authors discussed the results and commented on the manuscript. \n\nCompeting interests A patent application related to the subject matter of this manuscript has been submitted (Application Nos. PCT/CN2022/143637 and 2022114089354) by the Hefei Institutes of Physical Science, Chinese Academy of Sciences. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-023-06784-0. \nCorrespondence and requests for materials should be addressed to Songyuan Dai, Nam-Gyu Park, Jiajiu Ye or Xu Pan. \nPeer review information Nature thanks Zhaoning Song and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n# Article \n\n![](images/a2aa73cb31a67c3858f2ab061a6aaa2094de5872dea1b093d8b3a73368989ade.jpg) \n\nExtended Data Fig. 1 | Illustration of peel-off method to expose the bottom of perovskite films. We prepared sample comprising ITO/PTAA/Perovskite/ Cu stacks for GIXRD measurements. PTAA $(30\\mathrm{mg}\\mathrm{ml}^{-1}$ in CB) was deposited as sacrifice layer to further expose bottom interface, and Cu layer was evaporated to ensure the completeness of perovskite films. After fabrication, the samples were immersed in a tank filled with CB for 20 min in a nitrogen glovebox. Along with dissolving of PTAA layer, an entire perovskite film together with Cu would float in CB. A clean quartz substrate was used for flipping and carrying the obtained films. The samples should be immersed in CB again for another 5 min to clear potential PTAA residues. Finally, the samples were dried naturally in nitrogen and for further characterizations of bottom interface. It should be noted that, immersion in CB within 1 h would not affect perovskite structure. To ensure the reliability for these results, the controlled trial was conducted with perovskite films deposited on quartz glass. We tested conventional XRD measurements for the perovskite surface, which demonstrated identical results of 1 h immersed perovskite films. \n\n![](images/7961fa6e46777bc064c45bfc535984706ac91dfa28e563f467e9f04030d9a128.jpg) \n\nxtended Data Fig. 2 | Analysis of synthesised (PbI2)x(PSP)y complex. a-b, The potential crystal structure of $(\\mathsf{P b l}_{2})_{\\mathsf{x}}(\\mathsf{P S P})_{\\mathsf{y}};,$ c, The experimental XRD patterns of SP, $\\mathsf{P b l}_{2}$ and $(\\mathsf{P b I}_{2})_{\\mathsf{x}}(\\mathsf{P S P}),$ y and the complex simulations. \n\n# Article \n\n![](images/df173e9fd1fd21faca473742021ed5290e2136b9196b5f98410267afce1396e5.jpg) \n\nExtended Data Fig. 3 | NMR results. $^{13}{\\mathsf C}$ Chemical shift information of PSP and PSP(PbI2) complex obtained from NMR measurements. \n\n![](images/1b8ee4ee703f321d32efded39e1f76da9dd7719d31467e213624f1f5ee009522.jpg) \n\nExtended Data Fig. 4 | Band alignment analysis from ultraviolet photoelectron spectroscopy (UPS) depth profile. a, Schematic diagram of method for depth profile UPS. b-c, UPS depth profiles of perovskite films (b) \n\nwithout and (c) with PSP introduction. The colour from the light to dark indicated spectra recorded after etching $0\\mathsf{n m}$ , $400\\mathsf{n m}$ and $700\\mathrm{nm}$ , respectively. \n\n# Article \n\n![](images/4ea063957394a0595e0ccb43df449f560edeb5fd2f45e0c0be130e12ce1867f3.jpg) \nExtended Data Fig. 5 | Schematic diagram of band alignment extracted from UPS results. The band structures of different depths have been combined through manually aligning the Fermi energy level, due to there were not actual contact junction of different detection region. a-b, Schematics of quasi-type I band alignment caused by FA-Cs phase segregation. In a solar cell with (a) p-i-n stacks, holes undergo extra energy loss at bottom region when it diffuses within \n\nthe perovskite film, leading to charge carriers (holes) accumulate at this region. Ultimately break the carrier extraction equilibrium. The same situation would arise for the electrons in solar cells with (b) n-i-p configuration. c-d, Resultant flatten band alignment by PSP introduction in a device with (c) p-i-n configuration and (d) n-i-p configuration. \n\n![](images/e657206f871f815b999673c72ba477a660b5a4f97582a33ac082ea6e3c1f7604.jpg) \nExtended Data Fig. 6 | Transient absorption (TA) spectra. a-b, TA spectra of perovskite films of (a) the reference and (b) PSP film deposited on quartz glass. c, Time-resolved fitting curve at $780\\mathrm{nm}$ . We utilized TA measurements to examine carrier dynamics. In the PSP film, an enhancement in absorption variation (ΔA) was observed, corroborating the reduction in Shockley-ReadHall (SRH) recombination due to the passivation of trap states. Time-resolved \nabsorption at the ground-state bleach (GSB) of $780\\mathsf{n m}$ revealed a decrease in the fast decay lifetime $(\\uptau_{1})$ and an increase in the slow decay lifetime $(\\uptau_{2})$ . The five-fold reduction in $\\boldsymbol{\\uptau}_{1}$ suggests effective passivation, while the nearly threefold increase in $\\boldsymbol{\\uptau}_{2}$ implies a seamless carrier diffusion within the perovskite (Supplementary Table 4). This finding aligns with the conclusion obtained from energy band alignment. \n\n![](images/af9986be2d4dab20fb1faec5067cf76bbaf9884ed6f7669def0820ddb960f176.jpg) \nExtended Data Fig. 7 | The plots of the first order derivative of EQE curve. The bandgap was extracted from the first order derivative of EQE curve, which located at around $818\\mathsf{n m}$ . \n\n![](images/f016ec0602fe3ef26dd27a0b5313292bb4412ef21434f12ef7a17de4e100d827.jpg) \nExtended Data Fig. 8 | Additional stability assessments. a, PCE evolution curves of PSCs under thermal cycling stress. The temperature cycling reliability were tested between the $-40^{\\circ}\\mathsf{C}\\cdot60^{\\circ}\\mathsf{C}$ with duration time of 2 h. The initial PCE of the reference and the PSP device is $25.27\\%$ and $24.09\\%$ , respectively. b, Stability test followed ISOS L-2I protocol that performing MPP tracking under continuous \n\n1 sun illumination at $65^{\\circ}\\mathrm{C}$ in $\\mathsf{N}_{2}$ atmosphere. The solid lines represent for the average efficiency evolution among the eight individual device, and the shadow region represent for the efficiency evolution range during the tests. The average initial PCE of the reference and PSP device is $25.47\\%$ and $24.26\\%$ , respectively. " + }, + { + "id": "10.1126_science.ade1499", + "DOI": "10.1126/science.ade1499", + "DOI Link": "http://dx.doi.org/10.1126/science.ade1499", + "Relative Dir Path": "mds/10.1126_science.ade1499", + "Article Title": "La- and Mn-doped cobalt spinel oxygen evolution catalyst for proton exchange membrane electrolysis", + "Authors": "Chong, LA; Gao, GP; Wen, JG; Li, HX; Xu, HP; Green, Z; Sugar, JD; Kropf, AJ; Xu, WQ; Lin, XM; Xu, H; Wang, LW; Liu, DJ", + "Source Title": "SCIENCE", + "Abstract": "Discovery of earth-abundant electrocatalysts to replace iridium for the oxygen evolution reaction (OER) in a proton exchange membrane water electrolyzer (PEMWE) represents a critical step in reducing the cost for green hydrogen production. We report a nullofibrous cobalt spinel catalyst codoped with lanthanum (La) and manganese (Mn) prepared from a zeolitic imidazolate framework embedded in electrospun polymer fiber. The catalyst demonstrated a low overpotential of 353 millivolts at 10 milliamperes per square centimeter and a low degradation for OER over 360 hours in acidic electrolyte. A PEMWE containing this catalyst at the anode demonstrated a current density of 2000 milliamperes per square centimeter at 2.47 volts (Nafion 115 membrane) or 4000 milliamperes per square centimeter at 3.00 volts (Nafion 212 membrane) and low degradation in an accelerated stress test.", + "Times Cited, WoS Core": 332, + "Times Cited, All Databases": 338, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000999020900004", + "Markdown": "# ELECTROCHEMISTRY \n\n# La- and Mn-doped cobalt spinel oxygen evolution catalyst for proton exchange membrane electrolysis \n\nLina Chong1, Guoping $\\mathsf{G a o}^{2}$ , Jianguo Wen3, Haixia Li2, Haiping ${\\tt X}{\\bf u}^{1}$ , Zach Green4, Joshua D. Sugar5, A. Jeremy Kropf1, Wenqian $\\mathsf{X}\\mathsf{u}^{6}$ , Xiao-Min $\\mathsf{L i n}^{3}$ , Hui $\\mathsf{X}\\mathsf{u}^{4}$ , Lin-Wang Wang2, Di-Jia Liu1,7\\* \n\nDiscovery of earth-abundant electrocatalysts to replace iridium for the oxygen evolution reaction (OER) in a proton exchange membrane water electrolyzer (PEMWE) represents a critical step in reducing the cost for green hydrogen production. We report a nanofibrous cobalt spinel catalyst codoped with lanthanum (La) and manganese (Mn) prepared from a zeolitic imidazolate framework embedded in electrospun polymer fiber. The catalyst demonstrated a low overpotential of 353 millivolts at 10 milliamperes per square centimeter and a low degradation for OER over 360 hours in acidic electrolyte. A PEMWE containing this catalyst at the anode demonstrated a current density of 2000 milliamperes per square centimeter at 2.47 volts (Nafion 115 membrane) or 4000 milliamperes per square centimeter at 3.00 volts (Nafion 212 membrane) and low degradation in an accelerated stress test. \n\now-temperature water electrolysis can rapidly produce environmentally sustainable, or green, hydrogen and is a prospective means of storing energy from renewable but intermittent power sources, such as wind and solar, in future clean energy infrastructure $(l{-}4)$ . Commercial systems use either liquid alkaline electrolyte or proton exchange membrane electrolyte $(I)$ . Compared with the alkaline counterpart, a proton exchange membrane water electrolyzer (PEMWE) offers the advantages of higher current density, higher $\\mathrm{H_{2}}$ purity, lower resistance losses, and more compact design, rendering it a preferred technology where high efficiency and small footprint are essential (1, 2). Working under the acidic and oxidative environment, however, adds substantial challenges to the catalyst activity and stability profile. This is particularly the case for the anode catalyst because of the high overpotential for oxygen evolution reaction (OER) (3). At present, OER catalysts for PEMWE are primarily restricted to the platinum group metal (PGM) materials, such as $\\mathrm{IrO}_{x}\\left(I\\right)$ . Their high cost and limited reserve, however, pose substantial barriers to the widespread implementation of PEMWE. Low-cost transition metals and their oxides are known to be active toward OER in alkaline electrolyte (4–6), but their demonstration in acidic electrolyte is very limited $(I,7,8)$ . \n\nCobalt molecular and oxide compounds have emerged as promising OER catalysts for water splitting in recent years (9). Kanan and Nocera systematically investigated water oxidation using a catalyst deposited from ${\\mathrm{Co}}^{2+}$ solution in $\\mathrm{pH}7$ phosphate buffer (10). Gerken et al. performed a comprehensive mechanistic study of cobalt-catalyzed water oxidation from homogeneous to heterogeneous phases in electrolyte over a broad pH range of 0 to 14 (11). Those studies have provided profound understanding of electrocatalytic oxygen evolution by cobalt. More recently, thin film spinel-type $\\mathrm{Co_{3}O_{4}}$ was found to be active toward OER and stable at low overpotential in acid (12). The activity and stability of Co oxide were improved substantially when modified with iron, manganese, antimonite, and $\\mathrm{Pb}0_{x}$ (13–15). In addition to activity and stability, the inherent conductivity represents an essential requirement for efficient OER electrocatalysis to overcome the insulating properties of most transition metal oxides in their crystalline form. Conventional carbon supports, used to facilitate the electron conductivity, are not stable against oxidation to $\\mathrm{CO_{2}}$ at the PEMWE anode under OER operating potential. For example, a Copolyoxometalate composited with carbon paste achieved a lower OER onset potential than $\\mathrm{IrO_{2}}$ in $\\mathbf{\\Omega}_{1\\mathbf{M}}$ sulfuric acid but decayed quickly, presumably as a result of oxidative corrosion of the carbon (16). Self-conductive oxide catalysts can also enhance the active -site volumetric density without being diluted by a secondary nonactive support. A recently developed self-healing OER catalyst has demonstrated excellent activity and durability in acidic electrolyte (14). The approach, however, requires the presence of metal precursors in the aqueous electrolyte, hindering integration into a PEMWE. Most of the aforementioned studies were carried out either in half-cells or aqueous electrolyzers, where the demands for OER catalyst stability and conductivity are different from those in a PEMWE. For example, the dissolved transition metal concentration must be minimized to avoid poisoning the proton exchange membrane in the PEMWE. Effective OER for PEMWE requires optimal interfacial properties, microporosity, and surface catalytic activity $(I)$ , all of which need to be validated in the operating electrolyzer. \n\nIn this work, we present a cobalt spinel– based OER catalyst derived from a zeolitic methyl-imidazolate framework (Co-ZIF) and processed by electrospinning. The catalyst demonstrated excellent OER activity benefiting from its high specific surface area, porous interconnected nanonetwork structure, and high conductivity. \n\n# Design of an acid-stable cobalt OER catalyst \n\nOur design concept of an efficient cobalt spinel–based OER catalyst for PEMWE anodes is based on the following rationale: To enhance OER activity in acid, an oversized and more stable second element can be selectively introduced to the cobalt oxide surface to generate strain, oxygen vacancy $(V_{0})$ , and acid tolerance $(I7)$ ; to improve the oxide electronic conductivity, a third element with similar charge and dimension to cobalt may be incorporated inside the lattice to bridge the Fermi bandgap through $d$ orbital partial occupation of the third element induced by its d-electron delocalization. Advancing further from the rotating disk electrode (RDE) or halfcell study to a membrane electrode assembly (MEA) demonstration, the catalyst should have a high porosity and surface area easily accessible to the reactant $\\mathrm{(H_{2}O)}$ . Meanwhile, the electrode layer should be effective in transporting $\\mathrm{H_{2}O}$ and releasing $\\mathrm{O_{2}}$ without blocking the water-catalyst interface. Furthermore, the oxide catalyst should be self-conductive without the need for another conductive support, such as carbon, that is unstable under high OER operating potential and current density. Finally, the metal oxide should be stable against oxidative and acidic $\\mathrm{(pH~2~}$ to 4) corrosion in the PEMWE environment. \n\nWe selected Co-ZIF as the precursor for the catalyst preparation because of its high intrinsic porosity and reticular structure. It has recently been used to prepare a nanoplate oxide with excellent OER activity tested in strong alkaline electrolyte (1 M KOH) using the RDE method (18). Our catalyst preparation through low-temperature oxidation partially retained the porosity and morphology of Co-ZIFs after their conversion into interconnected hollow metal oxide particles, providing an excellent platform for enhanced charge and mass transfer. Among different elements that we screened, we selected lanthanum $\\mathrm{(La^{3+})}$ as the second element because of its much larger radius compared with that of ${\\mathrm{Co}}^{2+}$ (1.06 Å versus $0.72\\mathrm{\\AA})$ along with its strong affinity to bind −OH groups at the surface of cobalt oxide. We also added manganese ions $(\\mathrm{Mn^{2+}})$ of similar radius to ${\\mathrm{Co}}^{2+}$ (0.8 Å versus $0.72\\mathrm{{\\AA}}$ during the Co-ZIF synthesis, which would be oxidized to $\\mathrm{Mn}^{3+}(0.72\\AA)$ during the oxidative conversion and uniformly distributed inside the cobalt spinel lattice to promote conductivity (via bandgap) and OER activity (via affinity OH or H group). The catalyst synthesis scheme is shown in Fig. 1A. Briefly, La- and Mn-doped Co-ZIF, LaMn@Co-ZIF, was prepared in solution. Powder x-ray diffraction (XRD) combined with scanning electron microscopy (SEM)– energy dispersive x-ray spectroscopy (EDX) elemental mapping confirmed the successful incorporation of atomic La and Mn into the structure and cavity of the Co-ZIF (fig. S1). \n\n![](images/c69780c8b981ddc435d15bcefa6525496d3cfc9f5963c5836f99c00e09c0e106.jpg) \nFig. 1. Synthesis, morphology, and structure of LMCF. (A) Schematics of LMCF synthesis including formation of Co-ZIF embedded PAN polymer fiber by electrospinning and thermal oxidative activation to produce interconnected porous cobalt oxide particles after removing all the organics. The background SEM images show a cross-linked, ZIF-containing fiber nanonetwork produced by electrospinning and the interconnected porous oxide after the activation. (B) SEM image (scale bar, $1\\upmu\\mathrm{m}\\uplambda,$ ). (C) HAADF-STEM image (scale bar, $500~\\mathsf{n m}$ ). (D) TEM image (scale bar, $200~\\mathsf{n m}^{\\cdot}$ ). (E) HRTEM image (scale bar, $5\\mathsf{n m}$ ). \n(F to H) STEM image and the corresponding La and Mn distributions (scale bar, 2 nm). The color bars show the element counts. The maximal counts are 321 for La and 142 for Mn. (I) HRTEM image (scale bar, $0.5\\mathsf{n m}$ ). The green dots represent atomic columns of tetrahedral (T) and octahedral (O) oxygens, and the red dots represent the cobalt atomic columns simulated based on bulk phase inside lattice. The dotted yellow ellipses (on surface) show a different orientation compared with the solid yellow ellipses from the simulation (in bulk), suggesting a shift of oxygen position as a result of lattice relaxation. \n\nThe LaMn@Co-ZIF was then suspended in a polyacrylonitrile (PAN) polymer slurry (LaMn $@$ Co-ZIF/PAN) (19), which was subsequently electrospun into a fibrous mat. The nanofiber embedded with individual LaMn $@\\mathrm{Co}$ -ZIF was activated in flowing air at $360^{\\circ}\\mathrm{C}$ for 6 hours to remove the organic components, forming Laand Mn-codoped porous cobalt spinel fibers (denoted LMCF). Thermogravimetric analysis (TGA) confirmed the removal of carbon and nitrogen in LMCF after oxidative activation (fig. S2). The SEM image of LMCF shows an interconnected nanofibrous network morphology with ample macropores in between the entwined nanofibers (Fig. 1B). High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) revealed that individual LMCF particles retained the original $\\mathrm{Co}$ -ZIF’s rhombic dodecahedral shape, aligned and fused together in strings after oxidation (Fig. 1C). The ZIF-shaped LMCF particle is highly porous with a hollow structure composed of nanopores, as shown by transmission electron microscopy (TEM) (Fig. 1D). Each particle is composed of aggregates of $\\mathrm{Co_{3}O_{4}}$ nanocrystallites, with an average size of ${\\sim}3.5~\\mathrm{nm}$ , determined by aberration-corrected high-resolution transmission electron microscopy (HRTEM) (Fig. 1E and fig. S3). Nitrogen adsorption measurement of LMCF at 77 K provided a Brunauer–Emmett–Teller (BET) specific surface area (SSA) of 197 $\\mathrm{m^{2}g^{-1}}$ and a pore volume of $0.463\\mathrm{cm}^{3}\\mathrm{g}^{-1}$ (fig. S4). The high porosity of individual LMCF particle combined with nanofibrous morphology improves accessibility of reactants to the catalytic sites and facilitates water-oxygen mass transport in and out of the catalyst structure—an essential attribute for high-OER current density. XRD and Raman spectroscopy confirmed that the catalyst exhibited a spinel $\\mathrm{Co_{3}O_{4}}$ structure of slightly expanded lattice and higher $\\mathrm{Co^{2+}/C o^{3+}}$ ratio (fig. S5C and table S1). STEM images showed that the individual crystal surface is dominated by (111) facets, and electron energyloss spectroscopy (EELS) elemental mapping revealed La localization on the surface, with Mn distributed mainly in the bulk (Fig. 1, F to H, and fig. S6). Low-magnification EDX elemental mapping disclosed a uniform distribution of Co, Mn, La, and O in LMCF, and inductively coupled plasma optical emission spectrometry (ICP-OES) determined an atomic ratio of Co:Mn:La of 80:12:8 (fig. S7 and table S3). HRTEM imaging revealed that the LMCF lattice surface was terminated by oxygen atoms in a relaxed state, with positions shifted from those inside the crystallite (20) due to $V_{\\mathrm{o}}$ (Fig. 1I and fig. S8), an important attribute in lowering the OER activation energy and stabilizing the intermediate during the reaction (17, 21). We also measured LMCF conductivity using the four-probe van der Pauw method for comparison with $\\mathrm{IrO}_{x}$ and commercial $\\mathrm{Co_{3}O_{4}}.$ . The LMCF conductivity was found to be 8.6 times as high as that of commercial $\\mathrm{Co_{3}O_{4}}$ and about two-thirds that of $\\mathrm{IrO}_{x}$ (fig. S9). \n\n![](images/0548dfd2976014df1ac1a58e3df9cd5f8fcddb7d553ba69057b7b147bb831159.jpg) \nFig. 2. XAS study of LMCF. (A to C) Fluorescence XANES spectra collected at (D and E) R-space EXAFS spectra at Co K-edge (D) and Mn K-edge (E) of the Co K-edge (A) (inset: enlarged pre-edge $\\mathtt{1s}\\to3\\mathtt{d}$ transition), Mn K-edge (B), same samples. (F) Co-O bond distances (blue line) and DWF (red line) surround and La $\\mathsf{L}_{||\\mathsf{I}}.$ -edge (C) under ex situ (LMCF) and operando conditions at different Co derived from EXAFS data taken at different cell potentials. Error bars represent potentials. $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ , CoO, $M n_{2}O_{3}$ , $\\mathsf{M n O}_{2}$ , and $\\mathsf{L}a_{2}\\mathsf{O}_{3}$ are used as the references. the uncertainty of Fourier transformation of the experimental EXAFS data. \n\nThe electronic configuration and the coordination structure of Co, La, and Mn in LMCF were investigated using x-ray photoelectron spectroscopy (XPS) (fig. S10A and table S4) and synchrotron x-ray absorption spectroscopy (XAS). The high-resolution O 1s XPS spectrum confirmed the presence of high $V_{\\mathrm{o}}$ concentration in LMCF (fig. S11A). The Co 2p XPS spectrum revealed a higher ratio of $\\mathrm{Co^{2+}{:}C o^{3+}}$ in LMCF compared with that in $\\mathrm{Co_{3}O_{4}}$ (fig. S11B). The $\\mathbf{\\boldsymbol{x}}$ -ray absorption near-edge structure (XANES) spectrum at the Co K-edge (LMCF) shows a very similar spectral pattern to that of $\\mathrm{Co_{3}O_{4}}$ with a slightly red-shifted absorption energy and a decreased white line (WL) intensity (Fig. 2A), indicating a lower average oxidation state and a smaller O coordination number (CN) to cobalt in LMCF, which agrees well with the Raman and XPS results. We also observed an enhanced 1s $\\rightarrow3\\mathrm{d}$ transition peak intensity, which reveals that the cobalt in LMCF is in a less centrosymmetric coordination environment than that in $\\mathrm{Co_{3}O_{4}}$ suggesting a distorted Co oxide lattice by $V_{\\mathrm{o}}$ . Compared with $\\mathrm{Co_{3}O_{4}}$ , the LMCF extended x-ray absorption fine structure (EXAFS) shows lower peak intensities and CNs corresponding to Co-O and Co-Co shells (Fig. 2D, fig. S12, and table S5), which further supports a less developed lattice with a high concentration of $V_{\\mathrm{o}}$ from smaller particle size and higher ${\\mathrm{Co}}^{2+}$ (tetrahedral O-coordinated) fraction in LMCF. XANES at the Mn K-edge indicates that the average manganese oxidation state is between $+3$ and $^{+4}$ (Fig. 2B). Both K-space and R-space spectra extracted from EXAFS exhibit significant differences from that in Mn oxide references $\\mathrm{(Mn_{3}O_{4},}$ , $\\mathrm{{Mn}_{2}\\mathrm{{O}_{3},}}$ and $\\mathrm{{MnO}_{2}}^{\\cdot}$ ) (fig. S13, B and C). R-space fitting determined the CNs of Mn to O and Mn to Co to be $5.5\\pm0.4$ and $7.2\\pm\\:0.3$ , respectively (table S5). Most noticeably, the first and second shell radii and CNs are close to those of $\\mathrm{Co-O}$ and ${\\mathrm{Co-Co}}_{\\mathrm{(oh)}}$ in $\\mathrm{Co_{3}O_{4}}$ (Fig. 2E and tables S5 and S6) instead of Mn-O and Mn-Mn paths in Mn references, including $\\mathrm{{Mn}_{3}\\mathrm{{O}_{4}}}$ , $\\mathrm{{Mn}_{2}\\mathrm{{O}_{3}}}$ , and $\\mathrm{{MnO}_{2}}$ (fig. S13B). These observations provide convincing evidence that the Mn substitutes for the ${\\mathrm{Co}}^{3+}$ at the edge-sharing octahedral site and is embedded inside the cobalt oxide matrix in LMCF, in agreement with the HAADFSTEM result. The $\\ensuremath{\\mathrm{Mn}}^{3+}$ in the lattice is known to enhance OER activity of the oxide in acid (22). The XANES spectrum of La in LMCF shows significantly higher WL intensity than that of the $\\mathrm{La}_{2}\\mathrm{O}_{3}$ reference (Fig. 2C). Given that the WL intensity for oxides is generally proportional to the number of coordinated oxygens, R-space fitting determined the CN of La to oxygen in LMCF to be 8.3, which is in between that of lanthanum oxide $\\mathrm{CN}=6)$ and hydroxide $\\mathrm{CN}=9,$ (fig. S14). \n\n# Electrocatalytic activity in solution \n\nWe first evaluated the OER catalytic activity of LMCF using the RDE method in 0.1 M $\\mathrm{HClO}_{4}$ electrolyte $\\mathrm{(pH=1)}$ . To better understand the effects of the second and third elemental doping, we also prepared $\\mathrm{Co_{3}O_{4}}$ fiber (CF) \n\nand La-doped $\\mathrm{Co_{3}O_{4}}$ fiber (LCF) using a similar Co-ZIF–electrospinning method. Commercial $\\mathrm{Co_{3}O_{4}}$ and Ir black were also studied as benchmarks. Figure 3A shows a progressive improvement of OER activity measured by cyclic voltammogram (CV) through the addition of Mn and La in CF. The performance of LMCF also significantly exceeds that of commercial $\\mathrm{Co_{3}O_{4}}$ and approaches that of Ir black. Figure 3B presents the mass activity (MA) Tafel plot for LMCF together with the benchmark samples. LMCF again exhibits a high intrinsic catalytic activity. For example, LMCF catalyst shows a bulk MA of $126\\pm20\\mathrm{Ag^{-1}}$ at an overpotential of $370\\mathrm{mV}$ , which is higher than that of commercial Ir black (table S7). This is possibly because of a higher gravimetric catalytic site density of LMCF due to its lower molecular weight compared with $\\mathrm{IrO}_{x}$ . LMCF evaluated by linear sweep voltammetry (LSV) (Fig. 3C, with $95\\%$ iR correction) shows an onset potential of $1.28{\\mathrm{~V~}}$ measured at $0.46\\mathrm{\\mA\\cm^{-2}}$ and an overpotential of $353\\pm30\\mathrm{mV}$ at $\\mathrm{10\\mA\\cm^{-2}}$ . The LMCF catalyst activity was also measured in $0.5{\\bf M}$ $\\mathrm{\\cdot\\mathrm{M}\\mathrm{H}_{2}S O_{4}\\left(p H=0\\right)}$ , and the overpotential was reduced to $\\mathrm{335\\pm30~mV}$ at $\\mathrm{10\\mA\\cm^{-2}}$ (fig. S15). These results placed LMCF among the most active PGM-free catalysts reported in aqueous acid (23) (table S2). We estimated the electrochemical surface areas (ECSA) of the catalysts by measuring the double-layer capacitance from the CV curves in the nonFaradaic region (fig. S16) and produced Tafel plots of the ECSA-based specific current densities (fig. S17). The intrinsic activities of LMCF were further assessed based on turnover frequencies (TOFs) at different overpotentials $\\mathrm{320~mV}$ , $370~\\mathrm{mV}$ , and $650~\\mathrm{mV},$ ), which are among the highest when compared with representative PGM-free and PGM OER catalysts tested in various acidic media (table S8). For example, the TOF of LMCF is calculated to be $0.079\\pm0.011{\\mathrm{s}}^{-1}$ at an overpotential of $370\\mathrm{mV}$ based on the total loading mass, which increases to $0.87\\pm0.09\\mathrm{s}^{-1}$ when calculated based on ECSA (table S7). We also analyzed $\\mathrm{O_{2}}$ produced during OER over LMCF in a H cell using in situ gas chromatography (GC) and calculated the Faradaic efficiencies (FEs) for the oxygen produced at the current densities of $\\mathrm{10\\mA\\cm^{-2}}$ , $20\\mathrm{\\mA\\cm^{-2}}$ , $30\\mathrm{\\mA\\cm^{-2}}$ , and $50\\mathrm{\\mA\\cm^{-2}}$ (fig. S18, A to C). An average FE of $99.3\\pm5\\%$ was obtained, indicating that the oxygen formation through the four-electron transfer during water splitting is the only electrochemical reaction over LMCF. Ir was measured as reference, for which the FE was $97.0\\pm5\\%$ (fig. S18C). \n\n![](images/593ad8fce54a1c2b3450f366804a68ad7612aecbb251121f7ea3c6299ec05568.jpg) \nFig. 3. Electrocatalytic performance of LMCF. (A) CVs of LMCF, LCF, CF, Ir black, and commercial $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ in $0_{2}$ -saturated ${0.1\\mathrm{~M~HC}|0_{4}}$ (PGM-free catalyst loadings $=-260\\pm30{\\upmu\\mathrm{g}}{\\mathrm{cm}}^{-2}$ , Ir black loading $=-230\\pm30{\\upmu\\mathrm{g}}{\\uptau}{\\mathrm{m}}^{-2})$ . (B) Tafel plots of LMCF, LCF, CF, Ir black, and commercial $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ , with error bars of one standard deviation over four experimental replicates. (C) LSVs of LMCF measured by RDE before and after 14,000 voltage cycles in $0_{2}$ -saturated 0.1 M ${\\mathsf{H C l O}}_{4}$ (with $95\\%\\ i R$ correction). (D) Chronopotentiometric response at $10\\mathsf{m A}\\mathsf{c m}^{-2}$ with LMCF catalyst loading of $0.9~\\mathsf{m g}~\\mathsf{c m}^{-2}$ over 353-hour test. (E) S number calculated for LMCF after different hours onstream compared with selected benchmark Ir-based catalysts. (F) Current-voltage polarizations $i R$ corrected and uncorrected) of the PEMWE cell with LMCF anodic catalyst compared with that of Ir black catalysts with different loadings at $80^{\\circ}\\mathrm{C}$ . The \npolarization plot for LMCF represents an average of three MEA measurements with one standard deviation. (G) Current-voltage polarizations of the PEMWE after selected cycle numbers during a multiple-voltage cycling AST. The inset shows the stepwise voltage swing between $1.4\\ V$ and $1.7\\:\\forall$ with 10-s dwell time at each potential. (H) PEMWE cell voltage measured at different current densities after selected voltage cycles during the AST. (I) Potentiostatic measurement of PEMWE at the cell potential of $1.65\\mathrm{V}$ for LMCF anodic catalyst over 100 hours. Test conditions: anode LMCF catalyst loading, 1 to $2~{\\bmod{\\mathrm{cm}}}^{-2}$ ; cathode Pt loading, $0.4~\\mathsf{m g}_{\\mathsf{P}^{\\dagger}}~\\mathsf{c m}^{-2}$ ; $60^{\\circ}$ or $80^{\\circ}\\mathrm{C}$ cell temperature, unless otherwise specified; $5\\cdot{\\mathsf{c m}}^{2}$ active electrode area; Nafion 115 membrane for (F), (G), and (H), and Nafion 212 membrane for (I); DI water at flow rate of $10\\mathrm{m}|\\mathrm{min}^{-1}$ . \n\nLMCF was subjected to an accelerated aging test through voltage cycling between $1.4\\mathrm{V}$ and $2.0\\mathrm{V}$ versus reversible hydrogen electrode (RHE) by RDE in 0.1 M $\\mathrm{HClO_{4}}$ electrolyte. A mere ${\\sim}20\\mathrm{-}\\mathrm{mV}$ potential loss at $10\\mathrm{\\mA\\cm^{-2}}$ was observed after 14,000 CV cycles (Fig. 3C). Such stability was found to be better than that of commercial $\\mathrm{Co_{3}O_{4}}$ or Ir black at comparable catalyst weight loadings (fig. S19). The morphology, composition, and electronic states of the LMCF after the voltage cycling were found to be nearly unchanged from the pristine state (fig. S20, A to E). Similarly, no appreciable changes in the XANES spectra of Co, Mn, and La were observed after the voltage cycling (fig. S20, F to H). We further tested LMCF galvanostatic stability by holding the electrode current density at $\\mathrm{10\\mA\\cm^{-2}}$ for an extended operation period, following a test protocol (23, 24) (Fig. 3D). The change of electrode potential in acidic electrolyte was monitored over 353 hours, and a slow degradation at an average rate of $0.28\\mathrm{mV}$ hour 1 was observed. Transient potential dips in Fig. 3D were the result of pauses of the measurement while the electrolyte was refreshed. We also checked the metal contents in the electrolyte from acid leaching by performing ICP-OES under OER electrocatalysis. A mild loss of Co, Mn, and La ions by ${\\sim}1.9$ wt $\\%$ , ${\\sim}2.8\\mathrm{wt}\\%$ , and ${\\sim}1.1$ wt $\\%$ over their stoichiometric loadings in the LMCF catalyst, respectively, in a period of 80 hours was observed during the chronopotentiometry at $\\mathrm{10\\mA\\cm^{-2}}$ (fig. S21A). After an initial jump at the first hour, the metal dissolution rate decreased markedly afterward. Meanwhile, the catalytic activity remained nearly the same, which suggests that the dissolved metals could be attributed mainly to some loosely bound oxides at the surface. We also calculated the stability number (S number) for LMCF based on the amount of Co dissolved in the electrolyte at different testing times using the framework proposed by Geiger et al. (25) as well as the activitystability factor (ASF) by Kim et al. (26). These values are compared with some of the Irbased benchmarks in the literature, and the LMCF stability was found to be comparable to some less-stable Ir materials (Fig. 3E and fig. S21B). \n\n# Electrocatalytic activity in a PEMWE \n\nThe ultimate test of an OER catalyst is its performance in the operating PEMWE. Key properties, such as porosity, stability, and conductivity, become more important for the catalyst performance under the electrolyzer working conditions in comparison with the less-strenuous RDE measurements. The LMCF was assembled into the anode of a PEMWE single cell and tested using deionized (DI) water as the feed. Figure 3F shows composite current-voltage polarization curves derived from three measurements in the PEMWE. The electrolyzer reached a current density of $2000~\\mathrm{{mA}}$ $\\mathrm{cm}^{-2}$ at a voltage of 2.47 V $2.20{\\mathrm{V}}$ after cell iR correction), which could be further reduced to $2.30\\mathrm{V}$ by switching the membrane from Nafion 115 to Nafion 212, and reached a current density of $4000\\pm200\\mathrm{{mAcm^{-2}}}$ at $3.0\\mathrm{V}$ (fig. S22). In comparison, PEMWEs with Ir loading at $0.4\\mathrm{{mg}_{I r}\\mathrm{{cm}^{-2}}}$ and $2.0\\mathrm{{mg}_{I r}\\mathrm{{cm}^{-2}}}$ at the anode displayed cell voltages of $\\boldsymbol{\\mathrm{1.93\\:V}}$ and $1.78{\\mathrm{V}}$ at $2000\\mathrm{\\mA\\cm^{-2}}$ before $i R$ correction, respectively. Comparisons with other reported anodic catalysts are given in table S2 (14–16). \n\nThe MEA with LCMF was also subjected to accelerated stress tests (ASTs) using voltage cycling, galvanostatic, and potentiostatic methods. In the voltage cycling test, the PEMWE cell voltage was swept between $\\boldsymbol{\\mathrm{1.4V}}$ and $1.7\\mathrm{V}$ with a 10-s dwell time at each voltage (square-wave) up to 10,000 cycles. Current-voltage polarization was recorded periodically after designated voltage cycles. Figure 3G shows the polarization curves recorded after the selected voltage cycles. Figure 3H demonstrates the iR-corrected PEMWE cell voltages at four different current densities $(\\mathrm{{100mAcm^{-2}}}$ , $200\\mathrm{{mAcm}^{-2}}$ , $300\\mathrm{{mAcm}^{-2}}$ , and $400\\mathrm{\\mA\\cm^{-2}}.$ ) after each designated cycle number taken from the tests in Fig. 3G. Only small fluctuations in the cell voltage were observed between the first and the 10,000th cycles, suggesting excellent catalyst stability under such cycling conditions. After the voltage cycling, we conducted a galvanostatic test on the same MEA at incrementally increased current densities of $50\\mathrm{\\mA\\cm^{-2}}$ , $100\\mathrm{mAcm^{-2}}$ , $200\\mathrm{{mAcm^{-2}}}$ , and $300\\mathrm{\\mAcm^{-2}}$ over a 90-hour time span (fig. S23). The cell voltages remained nearly constant after each incremental increase of the cell current until the last 10 hours, when an increasing cell voltage was observed after the current density was raised to $300\\mathrm{\\mA\\cm^{-2}}$ . We also conducted a separate potentiostatic test over another PEMWE with LMCF anodic catalyst at a cell potential of $\\boldsymbol{1.65\\mathrm{~V~}}$ for 100 hours (Fig. 3I). A constant cell current density of $\\mathrm{\\sim210\\mAcm^{-2}}$ was observed, and the anodic effluent from the PEMWE was analyzed by ICP-MS. The cobalt dissolution gradually leveled off during the first 10 hours and became negligible thereafter (fig. S24). The S number calculated based on the dissolution rate was found to be two orders of magnitude higher than that obtained from RDE (fig. S25A). The difference may be ascribed to the higher acidity of the electrolyte used in the RDE $\\mathrm{(pH=1)}$ relative to that at the MEA anode layer $\\mathrm{(pH=2}$ to 4). A similar phenomenon was found in the study of $\\mathrm{RuO_{2}}$ catalyzed water oxidation (25). The lifetime determined by the $s$ number suggests excellent durability of LMCF operated at the PEMWE (fig. S25B). The morphology and the surface structure of the catalyst were preserved after AST by RDE as well as by combined voltage cycling and galvanostatic tests in the PEMWE (fig. S26). \n\n# Active -site analysis \n\nTo understand the nature of the active site and the impact of the second and third metal doping, we performed in situ XAS of LMCF in an $\\mathrm{O_{2}}$ -saturated electrolysis cell (0.1 M $\\mathrm{HClO}_{4}\\rangle$ 0 at the Co, Mn K-edge, and $\\mathrm{La}\\mathrm{-}\\mathrm{L}_{\\mathrm{III}}$ edge. Figure 2A shows the XANES spectra at the Co K-edge under different OER operating potentials. At the onset potential of $\\mathrm{1.23V}$ when OER has yet to commence, XANES already shows a decrease in WL intensity and an increase in pre-edge 1s $\\rightarrow3\\mathrm{d}$ peak intensity compared with the spectrum of as-prepared LMCF, accompanied by a decrease of CN of the first Co-O shell (Fig. 2D, fig. S12, and table S5). This signals oxygen loss and structural change as a result of interaction with the acidic electrolyte under the electric field, altering cobalt’s centrosymmetric coordination (symmetry breakdown) and electronic structure $(27)$ . The CN is significantly lower than that in $\\mathrm{Co_{3}O_{4},}$ indicating a higher fraction of tetrahedral coordinated ${\\mathrm{Co}}^{2+}$ combined with higher concentration of $V_{\\mathrm{o}},$ which serves as the nucleophilic site in promoting O–O bond formation (28). As the cell potential increases to initiate OER, the $\\mathrm{1s}\\to\\mathrm{3d}$ transition becomes more intense (Fig. 2A, inset). The average valence state of cobalt in LMCF was maintained at a lower value than that of $\\mathrm{Co_{3}O_{4}}$ $(+2.67)$ under all the test potentials from $+2.51$ at $\\mathrm{1.02V}$ to $+2.32$ at $1.70{\\mathrm{V}}$ (29) (fig. S27). Simultaneously, Fourier transformation of EXAFS spectra shows the reduction of Co-O and Co-Co shell intensities (Fig. 2D). At a potential of $1.7\\mathrm{~V~}$ when the OER reaction proceeds much more rapidly, XAS analysis shows shortening of the Co-O bond length (Fig. 2F and table S5), indicating a high degree of covalency contraction, which positively affects the catalytic activity of the nanoparticles (28). A similar phenomenon was observed in an $\\mathbf{MnO_{2}}$ film, where the Mn-O bond was shortened concomitant with accumulation of $\\ensuremath{\\mathrm{Mn^{3+}}}$ and $V_{\\mathrm{o}}$ under applied potential in acid (22). Shortened Co-O bonds during OER were also found in the amorphous cobalt oxide OER catalyst (CoCat) (30), except that Co was in the $^{+4}$ state, distinct from our catalyst. Accompanying the rapid acceleration of OER at $1.7~\\mathrm{V}$ , a clear increase of the Debye–Waller factor (DWF) $\\upsigma^{2}$ was also observed. DWF pertains to the motion of the coordinated atoms. In this case, it indicates increased Co-O vibration as the adsorbed $\\mathrm{H_{2}O}$ is converted to $\\mathrm{O}_{2}$ , possibly involving the shuffling lattice oxygen in LMCF, as was recently observed in a perovskite OER catalyst (31). The participation of surface and lattice oxygen creates anisotropic displacement of the ligation to cobalt, causing an increase of $\\mathrm{1s}\\rightarrow\\mathrm{3d}$ transition intensity. The Co XANES and EXAFS spectra were nearly fully restored to their original intensities at the onset voltage $\\left(1.23{\\mathrm{V}}\\right)$ when the cell potential was returned to $\\mathrm{1.02V}$ , suggesting the reversibility of the active -site restructuring in LMCF. By contrast, XANES spectra at the Mn K-edge and La $\\mathrm{L}_{\\mathrm{III}}$ -edges show little changes under different cell potentials (Fig. 2, B and C). Compared with Co, the EXAFS spectrum of Mn only showed a minor reduction of shell peak intensity at $\\mathrm{1.23V}$ after the catalyst was immersed in the electrolyte. No apparent changes in shell structure and DWF were observed for Mn during OER (Fig. 2E and fig. S13). XANES and EXAFS analyses indicate that Mn and La do not participate in the electrocatalysis directly. Rather, their presence modifies the structure and activity of the cobalt site. To this end, we also investigated the in situ XAS at different potentials over the fibrous cobalt oxide catalyst prepared by the same method but in the absence of Mn and La $(\\mathrm{CF})$ . The changes in XANES and EXAFS are significantly less dominant than those found in LMCF (fig. S28). \n\n# Comparison with theory \n\nThe experimentally observed atomic and electronic configurations in LMCF correspond well with density functional theory (DFT) \n\n![](images/036b20d573c72c81620897bf8263a08b71a4f5664102e8bc074cdc08d3710b07.jpg) \nFig. 4. Computational Pourbaix diagram and Fermi band structure of LMCF. (A) Surface Pourbaix diagram for the La-doped $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ (111) facet obtained from the $\\mathsf{D F T}+\\mathsf{U}$ calculations. (B) Possible intermediate state configurations. Blue, gray, red, and white balls denote the octahedral ${\\mathsf{C o}}^{3+}$ , tetrahedral ${\\mathsf{C}}0^{2+}$ , oxygen, and hydrogen ions. An asterisk denotes the pure surface; $\\mathsf{H}^{*}$ and $\\_{\\mathsf{H}^{\\ast}}$ denote the configurations in which the surface oxygen atoms are covered by H; ${\\mathsf{C}}{\\mathsf{0}}^{\\mathrm{{0}}}$ denotes the octahedral coordinated cobalt, and ${\\mathsf{C}}{\\mathsf{0}}^{\\mathsf{T}}$ denotes the tetrahedral coordinated cobalt; the nO/nOH/nOOH refer to the numbers of O/OH/OOH groups covering over each Co atom; configurations denoted \n\n“disCo/La” are generated after the Co/La dissolution; and the prefix “bri-” means that the covered groups act as a bridge connecting ${\\mathsf{L}}{\\mathsf{a}}^{\\mathsf{O}}$ and ${\\mathsf{C}}{\\mathsf{0}}^{\\mathsf{T}}$ . The potential is relative to the standard hydrogen electrode (SHE). (C) Calculated Fermi band structure of LMCF by replacing ${\\mathsf{C o}}^{3+}$ with $\\mathsf{M n}^{3+}$ in the $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ lattice. (D) Charge density distribution at the Fermi level upon Mn substitution in LMCF. Yellow refers to the charge density contour. Blue, gray, and red balls indicate octahedral ${\\mathsf{C o}}^{3+}$ , tetrahedral ${\\mathsf{C}}0^{2+}$ , and oxygen, respectively. Mn ions are behind yellow contour and circled by violet dotted line. \n\ncalculations. For example, our calculation reveals that in the bulk, in terms of total energy, both Mn and La preferentially replace Co in octahedral rather than tetrahedral sites, with stability differences of $0.25\\mathrm{eV}$ and $1.28\\:\\mathrm{eV}_{:}$ , respectively. This is in agreement with the above XAS observation of the increased ${\\mathrm{Co}}^{2+}$ percentage due to the Mn and La doping. The stronger preference for La is because of its most stable $+3$ oxidation state, whereas Mn could be present in either a $^{+2}$ or $^{+3}$ state. Our calculation also shows that Mn preferentially remains in the bulk of the $\\mathrm{Co_{3}O_{4}}$ , whereas La is extruded to the surface because of its large size. We compared the relaxed atomic structures of Mn and La at the surface layers and in the bulk of $\\mathrm{Co_{3}O_{4}}$ (fig. S29). For Mn, the surface layer structure is merely $0.1\\mathrm{eV}$ higher than that in the bulk, suggesting that it can displace Co anywhere in the system. For La, the energy is $3.09\\mathrm{eV}$ lower at the surface than in the bulk. This agrees well with the STEM measurement of Mn and La distributions, as shown in Fig. 1, G and H, affirming their roles as dopants in enhancing oxide conductivity and surface defect or oxygen vacancies for better OER activity according to our design concept (32). \n\nFor cobalt spinel–based OER catalysts operable in a PEMWE, the most imposing challenge is stability in the acidic media. To better understand the enhanced acid tolerance of LMCF under electrolytic condition, we calculated the surface Pourbaix diagram of the Ladecorated $\\mathrm{Co_{3}O_{4}}$ (111) facet (Fig. 4A) because it represents the dominant facet in the LMCF observed by STEM (Fig. 1, F, G, and I, and fig. S6, D and E). The Pourbaix diagram consists of five regions—I: disLa $\\mathrm{^{o}\\_H^{*}+2L a^{3+}}$ , II: $\\mathrm{{\\dis{La}^{o}\\_C o^{T}O O H^{*}\\ +\\ 2L a^{3+}}}$ , III: b $\\mathrm{\\ri3OH{\\mathrm{\\_H}}^{\\ast}}$ , IV: bri3OH\\*, and V: $\\mathrm{La^{o}3O\\_C o^{T}O^{*}}$ —with their intermediate state configuration shown in Fig. 4B. Among these five phases, phases I and II contain ionic $\\mathrm{La}^{3+}$ and therefore are unstable and soluble, whereas phases III, IV, and V contain the surfaces of ${\\mathrm{Co}}^{2+}$ , $\\mathrm{Co^{3+}}$ , and $\\mathrm{La^{3+}}$ bridged by $\\mathrm{OH^{*}}$ , $\\mathrm{OH\\_H^{*}}$ , and $0^{*}$ and exhibit relative stability against Co dissolution. Under low pH and low or negative potential, the surface La in the La-doped $\\mathrm{Co_{3}O_{4}}$ (111) facet dissolves to form $\\mathrm{La^{3+}}$ (phase I). At potentials between $0.86\\mathrm{~V~}$ and $\\mathrm{1.1~V}$ (RHE), the cation on the surface is oxidized and stabilized by $\\mathrm{OH^{*}}$ , and the oxygen on the surface is covered by $\\mathrm{H^{\\ast}}$ to form the stable $\\mathrm{\\bri3OH{\\_}H^{\\ast}}$ structure (phase III). As the potential further increases to $\\geq1.23\\mathrm{~V~}$ (RHE), the surface is protected by $\\mathrm{OH^{*}}$ to form a bri3OH\\* stable structure (phase IV). Under high pH and high potential, the surface of the Ladoped $\\mathrm{Co_{3}O_{4}}$ (111) facet tends to be oxidized by water, and the surface cations La and Co are protected by $0^{*}$ by forming a stable structure $\\mathrm{La^{o}3O\\_C o^{T}O^{*}}$ (phase V). \n\nThe calculated Pourbaix diagram demonstrates that the stability of the LMCF catalyst is defined by the combination of cell potential and pH. It also agrees well with our experimental observations. For example, under no electric field (potential $\\mathbf{\\varepsilon}=0$ ) at $\\mathrm{pH}<7$ , the catalyst is in phase I and is thermodynamically unstable in the acidic solution. During our RDE study in 0.1 M $\\mathrm{HClO_{4}}\\left(\\mathrm{pH}=1\\right)$ at cell potentials between $1.5\\mathrm{V}$ and $2\\mathrm{v}$ , only a very small fraction of tests at low cell potential will overlap with phase II, which could explain why the dissolution rate was higher in the RDE test. In our PEMWE test, the actual cell voltage runs from $1.5\\mathrm{V}$ to $3.0\\mathrm{V}$ (between the two red dashed lines) within the anodic pH between 2 and 4 (defined by the two vertical green dashed lines) in Fig. 4A. Therefore, the actual PEMWE anode operates in a window within these two boundaries, as marked by the area covered by the green diagonal stripes. This operating window falls within phase V, $\\mathrm{La^{o}3O\\_C o^{T}O^{*}}$ , which is stable, thus offering a preliminary explanation of the stability of the LMCF catalyst in the PEMWE. \n\nFor comparison, we also calculated the Pourbaix diagram of the pure $\\mathrm{Co_{3}O_{4}}$ (111) facet and confirmed its weaker stability compared with the La-doped surface (fig. S30). We furthermore calculated Pourbaix diagrams of the LMCF (110) facet (fig. S31) and (100) facet (fig. S32). Both facets offer good stability under PEMWE operating conditions according to the calculation. Our study revealed the critical role of surface La in stabilizing multiple $\\mathrm{Co_{3}O_{4}}$ facets against corrosion under working PEMWE condition. \n\nAnother critical issue in electrocatalysis is the inherent electron conductivity of the oxide itself. Our calculation of LMCF shows that substituting a low concentration of ${\\mathrm{Co}}^{3+}$ ions with uniformly distributed $\\ensuremath{\\mathrm{Mn}}^{3+}$ ions in the $\\mathrm{Co_{3}O_{4}}$ lattice induces two partially occupied defect states in the midbandgap (Fig. 4, C and D). The Mn-induced electron wave function overlaps significantly with neighboring Co ions, causing obvious dispersion and hence good electron mobility. This provides a direct enhancement of bulk-based electron conductivity, which, combined with the connectivity of the nanofibrous oxide network, offers an overall high conductivity value for LMCF. The improved electronic conductivity was further confirmed experimentally by the four-probe van der Pauw method (fig. S9). \n\n# Outlook \n\nThis study offers prospective directions and design insight for the future development of PGM-free OER catalysts for hydrogen production using PEMWE technology. For example, the catalytic activity enhancement can be further explored by increasing the surface functional group density through elemental doping, primary size control, and morphology innovation. The PEMWE durability can be improved by removing the electrochemically unattached oxide, therefore limiting metal ion dissolution because of the lack of electro-potential stabilization. Fundamental understanding of the OER mechanism with respect to mononuclear versus binuclear reaction intermediates and catalytic pathways will help to guide the precursor and catalyst designs for lower overpotential and better acid tolerance (33, 34). These improvements offer paths to the next-generation, PGM-free OER catalysts as viable replacements for precious metals, such as iridium. \n\n1. K. Ayers et al., Annu. Rev. Chem. Biomol. Eng. 10, 219–239 (2019). \n2. M. Carmo, D. L. Fritz, J. Mergel, D. Stolten, Int. J. Hydrogen Energy 38, 4901–4934 (2013). \n3. M. T. M. Koper, J. Electroanal. Chem. 660, 254–260 (2011). \n4. R. D. L. Smith et al., Science 340, 60–63 (2013). \n5. B. Zhang et al., Science 352, 333–337 (2016). \n6. Z.-F. Huang et al., Nat. Energy 4, 329–338 (2019). \n7. T. Reier, H. N. Nong, D. Teschner, R. Schlögl, P. Strasser, Adv. Energy Mater. 7, 1601275 (2017). \n8. Z. W. Seh et al., Science 355, eaad4998 (2017). \n9. V. Artero, M. Chavarot-Kerlidou, M. Fontecave, Angew. Chem. Int. Ed. 50, 7238–7266 (2011). \n10. M. W. Kanan, D. G. Nocera, Science 321, 1072–1075 (2008). \n11. J. B. Gerken et al., J. Am. Chem. Soc. 133, 14431–14442 (2011). \n12. J. S. Mondschein et al., Chem. Mater. 29, 950–957 (2017). \n13. B. Rodríguez-García et al., Sustain. Energy Fuels 2, 589–597 (2018). \n14. M. Chatti et al., Nat. Catal. 2, 457–465 (2019). \n15. I. A. Moreno-Hernandez et al., Energy Environ. Sci. 10, 2103–2108 (2017). \n16. M. Blasco-Ahicart, J. Soriano-López, J. J. Carbó, J. M. Poblet, J. R. Galan-Mascaros, Nat. Chem. 10, 24–30 (2018). \n17. J. Bao et al., Angew. Chem. Int. Ed. 54, 7399–7404 (2015). \n18. S. L. Zhang et al., Adv. Mater. 32, 2002235 (2020). \n19. J. Shui, C. Chen, L. Grabstanowicz, D. Zhao, D. J. Liu, Proc. Natl. Acad. Sci. U.S.A. 112, 10629–10634 (2015). \n20. W. Wang, A. Janotti, C. G. Van de Walle, J. Mater. Chem. C 4, 6641–6648 (2016). \n21. Y. Wang et al., Adv. Energy Mater. 4, 1400696 (2014). \n22. Z. Morgan Chan et al., Proc. Natl. Acad. Sci. U.S.A. 115, E5261–E5268 (2018). \n23. L. C. Seitz et al., Science 353, 1011–1014 (2016). \n24. C. C. McCrory et al., J. Am. Chem. Soc. 137, 4347–4357 (2015). \n25. S. Geiger et al., Nat. Catal. 1, 508–515 (2018). \n26. Y. T. Kim et al., Nat. Commun. 8, 1449 (2017). \n27. C. H. van Oversteeg, H. Q. Doan, F. M. de Groot, T. Cuk, Chem. Soc. Rev. 46, 102–125 (2017). \n28. H. N. Nong et al., Nat. Catal. 1, 841–851 (2018). \n29. H. Dau, P. Liebisch, M. Haumann, Anal. Bioanal. Chem. 376, 562–583 (2003). \n30. M. Risch et al., Energy Environ. Sci. 8, 661–674 (2015). \n31. A. Grimaud et al., Nat. Chem. 9, 457–465 (2017). \n32. O. Diaz-Morales et al., Nat. Commun. 7, 12363 (2016). \n33. I. C. Man et al., ChemCatChem 3, 1159–1165 (2011). \n34. M. Busch, Curr. Opin. Electrochem. 9, 278–284 (2018). \n35. W. Xu et al., La and Mn-doped cobalt spinel oxygen evolution catalyst for proton exchange membrane electrolysis, dataset, Dryad (2023); https://doi.org/10.5061/dryad.76hdr7t1v. \n\n# REFERENCES AND NOTES \n\n# ACKNOWLEDGMENTS \n\nWe thank J. Bareno, C. Yang, B. Fisher, M. S. Ferrandon, D. J. Myers, D. Abraham, and J. Wang of Argonne National Laboratory and S. Kabir of Giner Inc. for experimental assistance and comments on the manuscript. Funding: This work is supported by the US Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office (D. Peterson, project manager), and by Laboratory Directed Research and Development (LDRD) funding of Argonne National Laboratory, provided by the Director, Office of Science, of the US DOE under contract no. DEAC02-06CH11357 through a Maria Goeppert Mayer Fellowship to L.C. Work performed at the Center for Nanoscale Materials and Advanced Photon Source, both US \n\nDOE Office of Science User Facilities, was supported by the US DOE, Office of Basic Energy Sciences, under contract no. DE-AC02- 06CH11357. The work at Lawrence Berkeley National Laboratory was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy of the US DOE under the Hydrogen Generation program. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the US DOE’s National Nuclear Security Administration under contract no. DE-NA0003525. This paper describes objective technical results and analysis. The views and opinions of the authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof; neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, \n\ncompleteness, nor usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Author contributions: D.-J.L. designed and supervised the experiment. L.C. designed and synthesized the catalyst and conducted electrochemical measurement and data analysis. L.C., Ha.X., D.-J.L., Z.G., and Hu.X. conducted MEA preparation and PEMWE measurements. J.W. and J.D.S. performed electron microscopy imaging and analysis. L.C., Ha.X., A.J.K., W.X., X.-M.L., and D.-J.L. conducted spectroscopic and catalyst structural investigation and data analysis. G.G., H.L., and L.-W.W. performed DFT calculation. L.C., L.-W.W., and D.-J.L. wrote the manuscript. Competing interests: A US patent (USP 11,033,888) on the nanofibrous catalyst for OER with D.-J.L. and L.C. as the coinventors was granted to UCHICAGO ARGONNE, LLC. The authors declare no other competing interests. Data and materials availability: Data used for Pourbaix diagram calculations on La-doped cobalt spinel are available from Dryad (35). Other data are available in the main text and the supplementary materials. License information: Copyright $\\circledcirc$ 2023 the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.science.org/ about/science-licenses-journal-article-reuse \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.ade1499 \nMaterials and Methods \nFigs. S1 to S32 \nTables S1 to S8 \nReferences (36–70) \nSubmitted 31 July 2022; resubmitted 13 February 2023 \nAccepted 12 April 2023 \n10.1126/science.ade1499 " + }, + { + "id": "10.1126_science.abi8703", + "DOI": "10.1126/science.abi8703", + "DOI Link": "http://dx.doi.org/10.1126/science.abi8703", + "Relative Dir Path": "mds/10.1126_science.abi8703", + "Article Title": "Capturing the swelling of solid-electrolyte interphase in lithium metal batteries", + "Authors": "Zhang, ZW; Li, YZ; Xu, R; Zhou, WJ; Li, YB; Oyakhire, ST; Wu, YC; Xu, JW; Wang, HS; Yu, ZA; Boyle, DT; Huang, W; Ye, YS; Chen, H; Wan, JY; Bao, ZN; Chiu, W; Cui, Y", + "Source Title": "SCIENCE", + "Abstract": "Although liquid-solid interfaces are foundational in broad areas of science, characterizing this delicate interface remains inherently difficult because of shortcomings in existing tools to access liquid and solid phases simultaneously at the nulloscale. This leads to substantial gaps in our understanding of the structure and chemistry of key interfaces in battery systems. We adopt and modify a thin film vitrification method to preserve the sensitive yet critical interfaces in batteries at native liquid electrolyte environments to enable cryo-electron microscopy and spectroscopy. We report substantial swelling of the solid-electrolyte interphase (SEI) on lithium metal anode in various electrolytes. The swelling behavior is dependent on electrolyte chemistry and is highly correlated to battery performance. Higher degrees of SEI swelling tend to exhibit poor electrochemical cycling.", + "Times Cited, WoS Core": 267, + "Times Cited, All Databases": 289, + "Publication Year": 2022, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000740261400041", + "Markdown": "# BATTERIES \n\n# Capturing the swelling of solid-electrolyte interphase in lithium metal batteries \n\nZewen Zhang1, Yuzhang ${\\mathsf{L}}{\\mathsf{i}}^{2}$ , Rong Xu1, Weijiang Zhou3, Yanbin Li1, Solomon T. Oyakhire4, Yecun Wu5, Jinwei $\\mathsf{x u}^{1},$ , Hansen Wang1, Zhiao $\\yen4,6$ , David T. Boyle6, William Huang1, Yusheng $\\mathsf{v e}^{1}$ , Hao Chen1, Jiayu Wan1, Zhenan $\\scriptstyle{\\mathsf{B a o}}^{4}$ , Wah Chiu $^{3,7,8\\ast}$ , $\\mathsf{\\tt r i c u i^{\\tt t i,9*}}$ \n\nAlthough liquid-solid interfaces are foundational in broad areas of science, characterizing this delicate interface remains inherently difficult because of shortcomings in existing tools to access liquid and solid phases simultaneously at the nanoscale. This leads to substantial gaps in our understanding of the structure and chemistry of key interfaces in battery systems. We adopt and modify a thin film vitrification method to preserve the sensitive yet critical interfaces in batteries at native liquid electrolyte environments to enable cryo–electron microscopy and spectroscopy. We report substantial swelling of the solid-electrolyte interphase (SEI) on lithium metal anode in various electrolytes. The swelling behavior is dependent on electrolyte chemistry and is highly correlated to battery performance. Higher degrees of SEI swelling tend to exhibit poor electrochemical cycling. \n\nL lteacnttrotodet-eclehcntrolloygtie isnrtaernfgaicnegs faroe im epleocrE trical energy generation and storage to L the synthesis of chemicals and materials $(\\boldsymbol{I},2)$ . These electrochemical interfaces are complex and experimentally difficult to study, in part as the result of a lack of effective tools to characterize with high resolution. This gap in understanding has contributed to insufficient experimental control over interfacial structure and reactivity. For example, the solidelectrolyte interphase (SEI)—an interfacial layer formed at the electrode-electrolyte interface because of the electrochemical and chemical decomposition of electrolytes—is a key component responsible for the reversible operation of Li-ion and Li metal batteries (3–5). Thus, efforts have been made to engineer the SEI to enable battery chemistries with higher energy densities and longer cycles (6–9). However, fundamental understanding of the interfacial phenomena in these battery chemistries is still limited. Elucidating the nanoscale structures and chemistries at the electrodeelectrolyte interface is therefore critical for developing high–energy density batteries (10–13). \n\nConventional characterization techniques with high spatial resolution, such as highresolution transmission electron microscopy (HRTEM), are incompatible with volatile liquid electrolytes and sensitive solid electrodes, like Li metal anode. Moreover, both electrodes and electrolytes are highly reactive and easily subject to contamination or damage during sample preparation and transfer. Cryogenic temperatures can help stabilize sensitive battery materials and interfaces during sample preparation and enable high-resolution characterization in TEM (14–18). Nonetheless, the nanoscale structure of SEI in the layer that is closely interfaced with the electrode revealed with cryo–electron microscopy (cryo-EM) in many state-of-the-art electrolytes is often amorphous $(6,7)$ . Thus, it is hard to correlate the difference in battery performance with the SEI nanostructure and chemistry. \n\nThe experiments referenced in the previous paragraph were performed in the absence of liquid electrolyte; however, ideally one would want to preserve the solid-liquid interface in the “wet” state with liquid electrolyte. A cryo– scanning transmission electron microscopy (cryo-STEM) method, combined with cryo– focused ion beam (cryo-FIB), was reported to access the buried interface in batteries with solid and liquid phases together (19). However, high-resolution imaging of SEI in the electrolyte is difficult because of the technical challenge in preparing thin enough lamellae suitable for HRTEM. Additionally, the effect of ion milling on SEI nanostructure and chemistry is also a concern. \n\nWe adapt the original thin film vitrification method (20) to preserve the electrodeelectrolyte interface of batteries in its native organic liquid electrolyte environment. Such samples can be characterized with cryo-(S)TEM to investigate the intact structure and chemistry of the interphase in Li metal batteries. The key is to directly obtain thin film specimens of organic liquid electrolyte interfaced with the solid battery material while avoiding any mechanical or chemical artifacts from extra sample preparation steps. \n\nFigure 1, A and B, shows a schematic of the thin film vitrification method developed for batteries and the cross-sectional view of the vitrified specimen. Such a process yields uniform thin films inside the holes throughout the grid (fig. S1) and generates the electrontransparency of the specimen (fig. S2, A to C). There are two crucial factors to ensure that the vitrification of organic electrolytes is a practical method. (i) Organic solvent molecules often require substantially slower cooling rates for vitrification than aqueous solutions of biological samples (21), so the original method of freezing biological specimens directly in liquid nitrogen was used. (ii) Although lower in surface tension, organic electrolytes can still form a self-supporting thin film of submicron thickness by themselves and can remain for seconds before breaking as aqueous solutions. The amorphous diffraction pattern of pure frozen electrolyte without any salt or solvent crystallization confirms the successful vitrification process (fig. S2, D and E). Cryo– scanning electron microscopy (cryo-SEM) revealed rod-shape morphologies covered by a thin film in the TEM grid hole, corresponding to Li metal dendrites covered with a thin layer of vitrified electrolyte (Fig. 1, D and E, and fig. S2, F and G). \n\nLi metal plated in commercial carbonate electrolyte—1 M $\\mathrm{LiPF}_{6}$ in ethylene carbonate/ diethyl carbonate (EC/DEC)—was used as an example to reveal the SEI in the electrolyte. In Fig. 2A, Li metal dendrites show a lighter contrast compared with that of the organic electrolyte as a result of a lower average atomic number. A thick layer of $\\sim20\\mathrm{nm}$ with slightly darker contrast in the vitrified electrolyte was identified as the SEI layer (Fig. 2C). However, the SEI characterized in the absence of liquid electrolyte is $\\mathrm{\\sim}10~\\mathrm{nm}$ thick (Fig. 2D). There is a visible thickness difference between these two samples (Fig. 2E) that can be observed across multiple experiments (Fig. 2F). A video recorded after electrolyte removal but without drying shows that the SEI shrinks under electron beam exposure as a result of the evaporation of volatile solvent species (movie S2). Thus, this change in thickness should be ascribed to the loss of electrolyte species during washing and drying in preparing dry-state samples, which indicates a swollen SEI in the electrolyte environment. In the following discussion, the SEI in the electrolyte is denoted as w-SEI to indicate that the SEI is in a vitrified (also referred to as a wet or w-) state, and the SEI in the absence of electrolyte is denoted as d-SEI to indicate that the SEI is in a dry state. \n\nWe used cryo-STEM and electron energy-loss spectroscopy (EELS) to explore the chemistry of Li metal and its SEI in vitrified electrolyte. Spectroscopic mapping of EELS shows that the SEI layer is tens of nanometers thick (fig. S4). We observe distinct carbon-bonding environments in the d-SEI, the w-SEI, and the electrolyte in the carbon K-edge fine structures (fig. S5). The peaks at 288 and $290\\mathrm{eV}$ correspond to C–H and carbonate $\\scriptstyle\\mathbf{C=O}$ bonds present in all three regions, consistent with evidence that SEI is mainly composed of alkyl carbonates in carbonate-based electrolyte (22). The increase in the relative intensity of $\\mathrm{C-H}$ bonds from the w-SEI compared with the d-SEI correlates well with the observed swelling behavior. More carbonate-based organic molecules are present in the SEI layer in the wet state. \n\n![](images/5992801e09b9fde098e09bf39d7d2b37bcba595cf4d05793d869f8d25af23954.jpg) \nFig. 1. Sample preparation of dendrite in vitrified organic electrolyte. (A) blotting (movie S1) in an Ar-filled glove box and vitrified by liquid nitrogen Schematic process of sample preparation for vitrified specimens. Cu-evaporated without air exposure. (B) Schematic cross section of vitrified specimens. (C) commercial holey carbon TEM grids were used as the working electrode for Li Cryo-SEM image of Cu-evaporated TEM grid. (D) Cryo-SEM image of frozen Li metal plating in the coin cell setup. Upon coin cell disassembly after Li metal metal dendrite along with electrolyte. (E) Cryo-TEM image of Li dendrite in frozen deposition, excess electrolyte on the TEM grid is removed with double-sided electrolyte. The light-contrast rodlike region represents the Li metal dendrite. \n\nThus, the average carbon and oxygen bonding environment in the w-SEI more closely resembles that in the electrolyte as compared with the d-SEI. \n\nLocal mechanical properties of SEI were measured by nanoindentation with atomic force microscopy (AFM). The measurements were carried out in an inert environment to prevent undesired side reactions, and for w-SEI particularly, a closed liquid cell for AFM was used to further keep the electrode in the liquid electrolyte environment (fig. S6A). Typical force-displacement curves for nanoindentation experiments on both d-SEI and w-SEI are shown in Fig. 3. w-SEI showed an elastic-plastic deformation, where the forcedisplacement curves during loading and unloading are not fully reversible. However, under similar force loading, d-SEI only exhibited elastic deformation with small displacement $(<5\\mathrm{{nm})}$ (fig. S6, C and D). The elastic modulus of w-SEI is $0.31\\pm0.14$ GPa, whereas that of d-SEI is $2.01\\pm0.63$ GPa. This difference can be explained by the swelling behavior of SEI in liquid electrolyte because swelling can cause polymers to soften (23). Additionally, swelling has been shown to increase the spatial heterogeneity of polymer materials $\\left(24\\right)$ , which corresponds to a more diverse distribution of elastic modulus from w-SEI. \n\nOur result suggests that SEI is in a swollen state in liquid electrolyte. This is important in part because it suggests that SEI may not be a dense layer and that there is a nontrivial amount of electrolyte in this region. This is different from previous understanding, where SEI was thought to be a mixing layer of solid inorganic species (such as $\\mathrm{Li}_{2}\\mathrm{O}$ , $\\mathrm{Li_{2}C O_{3}}$ , etc.) and polymers and thus was electrolyte blocking and surface passivating to make the electrodeelectrolyte interface metastable. Our results indicate that the electrolyte is in close contact with the electrode at the solid-liquid interface in batteries. Several fundamental yet critical aspects about this interface, for example the Li-ion desolvation process and Li-ion transport mechanism through SEI, need to be reconsidered to better understand the key processes during battery cycling. Notably, after calendar aging or cycling, SEI can become much thicker, where the swelling might become more substantial and eventually lead to the drying out of the electrolyte (25, 26). \n\n![](images/ea268d0019d0aba30850d734acac7df6eaf309f0113682c6db812084664fba25.jpg) \nFig. 2. SEI on Li dendrite in dry state and vitrified organic electrolyte imaged with cryo-TEM. (A and B) Li metal dendrites in vitrified electrolyte (A) and in dry state (B). (C and D) HRTEM of SEI on Li metal dendrite in vitrified electrolyte (C) and in dry state (D). (E) Representative line profiles of intensity across the interfaces on Li metal dendrite deposited in 1 M LiPF6 in EC/DEC electrolyte. a.u., arbitrary units. (F) The histogram of SEI thickness in vitrified electrolyte and in dr state across multiple Li metal dendrites with 20 measurements for both in vitrified electrolyte and in dry state. \n\n![](images/3606b9dc60d4f799ad3ccbfec6cc42040f74d6e3eda11089bd9886b6245dc8f0.jpg) \nFig. 3. AFM nanoindentation analysis of SEI in liquid electrolyte. (A and D) AFM height images of deposited Li metal in liquid electrolyte (A) and in dry state (D). The white box indicates the region for nanoindentation mapping. (B and E) Representative force-displacement curves for nanoindentation experiments for both w-SEI (B) and d-SEI (E). (C and F) Histograms of the elastic modulus of w-SEI (C) and of d-SEI (F). The insets are corresponding two-dimensional maps of elastic moduli in the regions of interest. Indentation displacement curves were offset for clarity. The scales of the $\\chi$ axes are different in (C) and (F). \n\nFurthermore, the swelling of SEI sheds light on the mechanism of SEI growth after the formation of the initial SEI layer. Previously, the decrease in the rate of SEI formation was projected to be caused by the need for the reactants to diffuse through the already-existing layer (27). However, whether it is solvent diffusion through SEI inward to electrode surface or electron conduction through SEI outward toward electrolyte is still subject to debate. On the basis of our observation, it is highly likely that solvent diffusion plays a more significant role in the continuous growth of the SEI, particularly because the presence of solvents within the SEI reduces the distance required for electron tunneling during the decomposition of electrolytes. The reaction hotspot is now at or near the electrode-SEI interface. \n\nThis observation provides a practical method to quantitatively measure the electrolyte uptake of SEI in the liquid environment. Alternatively, this can also be viewed as SEI porosity at (sub)-nanoscale, as projected in earlier SEI models (27–30). By measuring the swelling ratio, defined as the thickness ratio of w-SEI and d-SEI, we can estimate the amount of electrolyte in the SEI region. For example, in 1 M $\\mathrm{LiPF}_{6}$ in EC/DEC, the w-SEI has an average thickness of $20~\\mathrm{{nm}}$ , whereas the d-SEI is ${\\sim}10~\\mathrm{nm}$ . This indicates that $\\sim50\\%$ of the SEI volume is composed of the electrolyte. Further questions, like nanoscale pore or electrolyte distribution in the SEI, need to be addressed for better understanding of the transport mechanism of Li across the interface. \n\nSEI is the key determinant for Li metal anode performance, and its properties vary with electrolyte systems, where solvent chemistry and salt composition largely determine SEI composition and structure (31). Even changing salt concentration would alter the solvation chemistry and the derived SEI (9). Generally, a mechanically robust, spatially uniform, and chemically passivating SEI is desirable (32). The swelling of SEI directly contradicts these design principles. We hypothesize that a better SEI should swell less with the electrolyte. \n\nAs a test of the above hypothesis, we performed electrochemical experiments and extended this cryo-TEM analysis to four other electrolytes with a variety of salts, solvents, and additives from the literature: 1 M $\\mathrm{LiPF}_{6}$ in EC/DEC with $10\\%$ fluoroethylene carbonate (EC/DEC, $10\\%$ FEC), 1 M lithium bis(fluorosulfonyl)imide (LiFSI) in 1,2- dimethoxyethane (DME), 4 M LiFSI in DME, and 1 M LiFSI in fluorinated $^{1,4}$ -dimethoxylbutane (FDMB) (7). These electrolytes have different Coulombic efficiencies (CEs) measured with the Aurbach method, ranging from 97.2 to $99.4\\%$ . Despite their differences in surface tension and viscosity, we could obtain highquality thin film vitrified specimens for all these electrolytes (fig. S7). No salt precipitation was observed even for the highly concentrated electrolyte (fig. S8). \n\n![](images/69874e77551c2ab3bc7bf1a9fbbe8af6a2b9d132f4cda92f9245074a5ea4097b.jpg) \nFig. 4. The correlation of Li metal anode performance and swelling ratio of SEI in different electrolytes. (A) Representative comparison of SEI thickness in d-SEI and w-SEI with high-resolution cryo-TEM for various electrolyte systems. (B) d-SEI is thinner compared with w-SEI in vitrified electrolyte for all five systems. (C) SEI swelling ratio (w-SEI thickness versus d-SEI thickness) as a function of CE. \n\nWe find the swelling of SEI in the electrolyte to be a universal phenomenon across all these electrolyte systems, regardless of solvent chemistry (Fig. 4 and table S1). This swelling behavior is dependent on electrolyte chemistry and highly correlated to battery performance, where higher degrees of SEI swelling tend to exhibit poor electrochemical cycling. The average d-SEI thicknesses in these five electrolytes are 8.8, 10.2, 9.9, 9.8, and $8.8\\mathrm{nm}$ , whereas the average thicknesses of corresponding w-SEI are 20.1, 19.8, 17.6, 15.7, and $10.9\\ \\mathrm{nm}$ , respectively (fig. S9 and table S1). We correlate the cycling performance of Li metal anode represented by CE with SEI swelling behaviors. Among the five electrolytes examined here, 1 M $\\mathrm{LiPF}_{6}$ in EC/DEC—the electrolyte with the lowest CE or worst cycling performance—has the largest swelling ratio, ${\\sim}2.3$ . For one of the best performing electrolytes, 1 M LiFSI in FDMB, this ratio is the smallest, \\~1.2. Overall, an increased swelling ratio correlates to a decreased CE (i.e., cycle life) (table S1). \n\nWe also find that the increase of elements associated with salt decomposition in d-SEI is accompanied by a decrease in swelling ratio. These elements most likely form inorganic domains in the SEI, and inorganic species in SEI have less affinity toward organic solvents compared with organic species. This results in a less–electrolyte-philic SEI with a smaller swelling ratio. In the 0.1 M $\\mathrm{LiPF}_{6}$ in EC/DEC electrolyte, where the salt concentration is much lower than that in commercial carbonate electrolytes, we observed a swelling ratio of ${\\sim}2.6$ , which is higher than that of 1 M $\\mathrm{LiPF}_{6}$ in EC/DEC (fig. S10 and table S2). The elastic moduli of both d-SEI and w-SEI are lower than those of 1 M $\\mathrm{LiPF}_{6}$ in EC/DEC, respectively (fig. S11), corresponding to a more polymeric composition, as expected. Such analysis is also valid in ether-based electrolytes (table S3). The highly concentrated electrolyte, $^{4\\mathrm{~M~}}$ LiFSI in DME, exhibited a smaller swelling ratio as well as a higher elastic modulus for both d-SEI and w-SEI compared with 1 M LiFSI in DME (fig. S12), in accord with the account that SEI from 4 M LiFSI in DME is highly anion derived (9). Such observation of smaller swelling ratios in more–inorganic-rich SEI provides a possible explanation for the pursuit of more– anion-derived SEI in the community. The better anion-derived SEI has a higher ratio of elements from the decomposition products of the salt instead of solvents, which means that the SEI swells less with the electrolyte to remain mechanically robust and chemically passivating. This relationship between SEI swelling and battery performance can be a potential design principle in conjunction with other electrochemical and mechanical properties, such as ionic conductivity, elasticity, and uniformity. Because current density plays a critical role in controlling the structure of SEI (33), this analysis could be further extended to understand current density effect on SEI composition and nanostructure (fig. S13 and table S4). Beyond that, given the similarities in chemical composition of SEI, we also expect this swelling behavior in SEI on other negative electrodes. Furthermore, such insights also highlight the importance of preserving both the liquid and solid phases for studying complex interfacial phenomena with high resolution using cryo-EM methods. \n\n# REFERENCES AND NOTES \n\n1. A. J. Bard et al., J. Phys. Chem. 97, 7147–7173 (1993). \n2. V. R. Stamenkovic, D. Strmcnik, P. P. Lopes, N. M. Markovic, Nat. Mater. 16, 57–69 (2017). \n3. K. Xu, Chem. Rev. 114, 11503–11618 (2014). \n4. E. Peled, S. Menkin, J. Electrochem. Soc. 164, A1703–A1719 (2017). \n5. M. B. Pinson, M. Z. Bazant, J. Electrochem. Soc. 160, A243–A250 (2013). \n6. X. Cao et al., Nat. Energy 4, 796–805 (2019). \n7. Z. Yu et al., Nat. Energy 5, 526–533 (2020). \n8. R. Weber et al., Nat. Energy 4, 683–689 (2019). \n9. J. Qian et al., Nat. Commun. 6, 6362 (2015). \n10. M. Gauthier et al., J. Phys. Chem. Lett. 6, 4653–4672 (2015). \n11. X. Yu, A. Manthiram, Energy Environ. Sci. 11, 527–543 (2018). \n12. X.-B. Cheng, R. Zhang, C.-Z. Zhao, Q. Zhang, Chem. Rev. 117, 10403–10473 (2017). \n13. J. W. Choi, D. Aurbach, Nat. Rev. Mater. 1, 16013 (2016). \n14. Y. Li et al., Science 358, 506–510 (2017). \n15. X. Wang et al., Nano Lett. 17, 7606–7612 (2017). \n16. W. Huang et al., Nano Lett. 19, 5140–5148 (2019). \n17. W. Huang et al., Matter 1, 1232–1245 (2019). \n18. Z. Zhang et al., Matter 4, 302–312 (2021). \n19. M. J. Zachman, Z. Tu, S. Choudhury, L. A. Archer, L. F. Kourkoutis, Nature 560, 345–349 (2018). \n20. K. A. Taylor, R. M. Glaeser, Science 186, 1036–1037 (1974). \n21. D. Danino, R. Gupta, J. Satyavolu, Y. Talmon, J. Colloid Interface Sci. 249, 180–186 (2002). \n22. L. Wang et al., Nat. Chem. 11, 789–796 (2019). \n23. M. Rubinstein, R. H. Colby, Polymer Physics (Oxford Univ. Press, 2003). \n24. R. Subramani et al., Front. Mater. 7, 212 (2020). \n25. S. Kranz, T. Kranz, A. G. Jaegermann, B. Roling, J. Power Sources 418, 138–146 (2019). \n26. M. Nojabaee, K. Küster, U. Starke, J. Popovic, J. Maier, Small 16, e2000756 (2020). \n27. F. Single, B. Horstmann, A. Latz, Phys. Chem. Chem. Phys. 18, 17810–17814 (2016). \n28. M. Garreau, J. Power Sources 20, 9–17 (1987). \n29. P. Guan, L. Liu, X. Lin, J. Electrochem. Soc. 162, A1798–A1808 (2015). \n30. J. Popovic, Energy Technol. 9, 2001056 (2021). \n31. X. Ren et al., Proc. Natl. Acad. Sci. U.S.A. 117, 28603–28613 (2020). \n32. X.-B. Cheng et al., Adv. Sci. 3, 1500213 (2016). \n33. Y. Xu et al., ACS Nano 14, 8766–8775 (2020). \n\n# ACKNOWLEDGMENTS \n\nWe acknowledge the use and support of the Stanford-SLAC Cryo-EM Facilities. Part of this work was performed at the Stanford Nano Shared Facilities (SNSF) and the Stanford Nanofabrication Facility (SNF). K3 IS camera and support are courtesy of Gatan, Inc. Funding: This study received funding from the Office of Basic Energy Sciences, Division of Materials Science and Engineering, Department of Energy, DE-AC02-76SF00515 (to Y.C. and W.C.); the Stanford Interdisciplinary Graduate Fellowship (to Z.Z. and W.Z.); the Stanford University Knight Hennessy scholarship (to S.T.O.); and National Science Foundation award ECCS-2026822. Author contributions: Z.Z., Yu.L., W.C., and Y.C. conceived the project and designed the experiments. Z.Z. performed electrochemical measurements. Z.Z. carried out cryo-(S)TEM experiments. Yu.L. helped with cryo-TEM experiments. R.X. and Z.Z. designed and carried out AFM measurements. W.Z. performed cryo-SEM characterization. Ya.L. and Y.W. helped with TEM grid modification. Z.Y. and Z.B. synthesized and provided the FDMB electrolyte. S.T.O., J.X., H.W., W.H., D.T.B., Ya.L., Y.Y., J.W., and H.C. interpreted the TEM and electrochemical data. Z.Z., W.C., and Y.C. cowrote the manuscript. All authors discussed the results and commented on the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in this paper are present in the paper or the supplementary materials. \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.abi8703 \nMaterials and Methods \nFigs. S1 to S13 \nTables S1 to S4 \nReferences (34–38) \nMovies S1 and S2 \n6 April 2021; accepted 10 November 2021 \n10.1126/science.abi8703 " + }, + { + "id": "10.1126_science.add9204", + "DOI": "10.1126/science.add9204", + "DOI Link": "http://dx.doi.org/10.1126/science.add9204", + "Relative Dir Path": "mds/10.1126_science.add9204", + "Article Title": "Direct synthesis and chemical vapor deposition of 2D carbide and nitride MXenes", + "Authors": "Wang, D; Zhou, CK; Filatov, AS; Cho, WJ; Lagunas, F; Wang, MZ; Vaikuntanathan, S; Liu, C; Klie, RF; Talapin, DV", + "Source Title": "SCIENCE", + "Abstract": "Two-dimensional transition-metal carbides and nitrides (MXenes) are a large family of materials actively studied for various applications, especially in the field of energy storage. MXenes are commonly synthesized by etching the layered ternary compounds, called MAX phases. We demonstrate a direct synthetic route for scalable and atom-economic synthesis of MXenes, including compounds that have not been synthesized from MAX phases, by the reactions of metals and metal halides with graphite, methane, or nitrogen. The direct synthesis enables chemical vapor deposition growth of MXene carpets and complex spherulite-like morphologies that form through buckling and release of MXene carpet to expose fresh surface for further reaction. The directly synthesized MXenes showed excellent energy storage capacity for lithium-ion intercalation.", + "Times Cited, WoS Core": 343, + "Times Cited, All Databases": 360, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000994409800005", + "Markdown": "# NANOMATERIALS \n\n# Direct synthesis and chemical vapor deposition of 2D carbide and nitride MXenes \n\nDi Wang1, Chenkun Zhou1, Alexander S. Filatov1, Wooje Cho1, Francisco Lagunas2, Mingzhan Wang3, Suriyanarayanan Vaikuntanathan1, Chong Liu3, Robert F. Klie2, Dmitri V. Talapin1,3,4\\* \n\nTwo-dimensional transition-metal carbides and nitrides (MXenes) are a large family of materials actively studied for various applications, especially in the field of energy storage. MXenes are commonly synthesized by etching the layered ternary compounds, called MAX phases. We demonstrate a direct synthetic route for scalable and atom-economic synthesis of MXenes, including compounds that have not been synthesized from MAX phases, by the reactions of metals and metal halides with graphite, methane, or nitrogen. The direct synthesis enables chemical vapor deposition growth of MXene carpets and complex spherulite-like morphologies that form through buckling and release of MXene carpet to expose fresh surface for further reaction. The directly synthesized MXenes showed excellent energy storage capacity for lithium-ion intercalation. \n\nXenes, where M stands for early transition metal (such as Ti, V, Nb, or Mo) and X is C or N, are a large family of two-dimensional (2D) transition-metal carbides and nitrides. Since the discovery of $\\mathrm{Ti_{3}C_{2}T_{\\it{x}}}$ $\\mathrm{T}=\\mathrm{O}$ , OH, and F) in 2011 $(I)$ , MXenes have been commonly synthesized from crystalline MAX phases (where A is typically Al, Si, or Ga) through selective etching of A atoms with hydrofluoric acid (HF)–containing solutions (1–3) or Lewis acidic molten salts $(4,5)$ , followed by the delamination of the MXene sheets (6). Interest in MXenes continues to grow because of their potential applications in energy storage (7, 8), electromagnetic interference (EMI) shielding (9, 10), transparent conductive layers $(I I)$ , superconductivity (5), and catalysis (12). Moreover, the aforementioned T components in MXenes can be replaced with covalently bonded surface groups, including organic molecules, either during etching of the MAX phases (4, 13), or through postsynthetic modifications of surface groups (5). As such, opportunities are available to combine the benefits of 2D MXenes, such as a low diffusion barrier for cation intercalation $(I4)$ , excellent electrical and thermal conductivity (3), and nearly endless tailorability of molecular surface groups. \n\nPreparations of MXenes through hightemperature synthesis and chemical etching of MAX (15) or non-MAX (16, 17) phases require high energy consumption, show poor atom economy, and use large amounts of hazardous HF or Lewis acidic molten salts. The development of direct synthetic methods would facilitate practical applications of the rapidly developing family of functional MXenes. An ideal approach would involve a reaction of inexpensive precursors into MXenes bypassing intermediate MAX phases. In 2019, Druffel et al. reported the synthesis of $\\mathrm{Y_{2}C F_{2}}$ with a MXenelike structure from the solid-state reaction between $\\mathrm{YF}_{3}$ , Y metal, and graphite (18), based on the previously reported synthesis of Sc, Y, and $\\mathrm{zr}$ metal carbide halides by Hwu et al. in 1986 (19). \n\nAmong about 100 known MXene structures, Ti MXenes show some of the best combinations of physical and chemical properties (20) relevant to a variety of applications (21). We show that $\\mathrm{Ti_{2}C C l_{2}}$ and $\\mathrm{Ti_{2}N C l_{2}}$ MXenes can be directly synthesized from Ti metal, titanium chlorides $\\mathrm{\\TiCl_{3}}$ or $\\mathrm{TiCl_{4,}}$ ), and various carbon or nitrogen sources, including graphite, $\\mathrm{CH}_{4},$ or $\\mathrm{{N_{2}}}$ . The directly synthesized MXenes (denoted as DS-MXenes) can be delaminated, and their surface groups can be replaced with other molecules through nucleophilic substitution or completely removed by means of reductive elimination (5). Besides convenience and scalability, the direct synthesis routes offer synthetic modalities not compatible with traditional MAX etching methods. For example, we demonstrated chemical vapor deposition (CVD) synthesis of extended carpets of $\\mathrm{Ti_{2}C C l_{2}}$ , $\\mathrm{Ti_{2}N C l_{2}},$ , $\\mathrm{Zr_{2}C C l_{2}},$ and $\\mathrm{Zr_{2}C B r_{2}}$ MXene sheets oriented perpendicular to the substrate. Such orientations make MXene surfaces easily accessible for ion intercalation (7, 22) and chemical or electrochemical transformations (23, 24) by exposing edge sites with high catalytic activity (25, 26). \n\n# Direct synthesis of $\\bar{\\mathsf{I i}}_{2}\\mathsf{C C l}_{2}$ MXene \n\nThe synthesis of DS- $\\mathrm{{Ti}_{2}\\mathrm{{CCl}_{2}}}$ was accomplished through the high-temperature reaction between Ti, graphite, and $\\mathrm{TiCl_{4}}$ (Fig. 1A). Titanium and graphite were ground into a fine powder in a 3:1.8 molar ratio and combined with 1.1 molar equivalent $\\mathrm{TiCl_{4}}$ . The mixture was sealed in a quartz ampoule and heated to $950^{\\circ}\\mathrm{C}$ in $20\\mathrm{min}$ , and the temperature was maintained until the reaction was finished; typically, 2 hours is sufficient for maximum yield of MXene. The reaction could be performed on a multigram scale (fig. S1) and should be easily amenable to further scaling. \n\nPowder x-ray diffraction (XRD) and structural analysis by means of Rietveld refinement of the as-synthesized reaction products (Fig. 1B) revealed the presence of a $\\mathrm{Ti_{2}C C l_{2}}$ MXene phase with the lattice parameters $a=$ 3.2284(2) Å and $c=8.6969(\\mathrm{1})\\mathrm{~\\AA~}$ (numbers in parentheses are standard uncertainties), which are near the values reported for $\\mathrm{{Ti}_{2}\\mathrm{{CCl}_{2}}}$ MXene synthesized by etching of $\\mathrm{Ti_{2}A l C}$ MAX phase with Lewis acidic molten salt (referred to as MS-MXenes) (5). Cubic $\\mathrm{TiC}_{x}$ $(x=0.5$ to 1) was often present as a by-product but could be efficiently removed through its precipitation from nonaqueous dispersions of the raw product prepared, for example, by means of ultrasonic dispersion in propylene carbonate (PC) or delamination of DS- $\\mathrm{\\cdotTi_{2}C C l_{2}}$ with $n$ -butyllithium 1 $_n$ -BuLi) (Fig. 1C). \n\nThe formation of $\\mathrm{Ti_{2}C C l_{2}}$ MXene was observed initially at ${\\sim}850^{\\circ}\\mathrm{C},$ , and the yield of MXene was maximal at $950^{\\circ}\\mathrm{C}$ (fig. S2A). $\\mathrm{TiC}_{x}$ became the dominant reaction product at temperatures ${\\mathrm{>}}1000^{\\circ}\\mathrm{C}.$ At $950^{\\circ}\\mathrm{C},$ the formation of $\\mathrm{Ti_{2}C C l_{2}}$ phase was observed after 2 hours, and the ratio between $\\mathrm{Ti_{2}C C l_{2}}$ and $\\mathrm{TiC}_{x}$ in products did not change substantially after increasing reaction time from 2 hours to 10 days at this temperature (fig. S2B). This finding naturally raises a question whether MXene was the kinetic or thermodynamic product of the reaction. We noticed that MXene phase did not form when we attempted to react $\\mathrm{TiC}_{x}$ with $\\mathrm{Ti}$ and $\\mathrm{TiCl}_{3}$ or $\\mathrm{TiCl_{4}}$ (fig. S2C). However, prolonged heating of purified $\\mathrm{MS–Ti_{2}C C l_{2}}$ at $950^{\\circ}\\mathrm{C}$ resulted in a partial conversion into $\\mathrm{TiC}_{x}$ (fig. S3). We concluded from these observations that $\\mathrm{Ti_{2}C C l_{2}}$ was a kinetically favored phase forming in competition with $\\mathrm{TiC}_{x}$ . \n\nThe XRD patterns of $\\mathrm{DS-Ti_{2}C C l_{2}}$ synthesized from $\\mathrm{TiCl}_{3}$ or $\\mathrm{TiCl_{4}}$ were similar (fig. S4B), as were scanning electron microscopy (SEM) images of the products’ morphology, represented by large MXene stacks (Fig. 1D and figs. S5 and S6). A high-resolution high-angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) image of $\\mathrm{{DS-Ti_{2}C C l_{2}}}$ oriented along the 21\u00011\u00010 zone axis and its corresponding electron energy loss spectroscopy (EELS) elemental maps are shown in Fig. 1, F and G, respectively. The center-to-center distance between MXene sheets calculated from the HAADF image is $0.87\\pm0.06~\\mathrm{nm}$ (fig. S7), which is in agreement with the value of $0.87\\pm$ $0.02{\\mathrm{nm}}$ measured with XRD on multiple samples. DS- $\\mathrm{\\cdot\\mathrm{{I}\\mathrm{{i}_{2}\\mathrm{{CC}_{2}}}}}$ MXene sheets contained Ti and \n\n![](images/e2e049b93806224b9aa4e76debbe694aa212d9a01b2cf57e11022d39f2ae1a28.jpg) \nFig. 1. Direct synthesis and characterization of DS- $\\bar{\\mathbf{Ii}}_{2}\\hat{\\mathbf{ccl}}_{2}$ MXene. (A) Schematic diagram of the synthesis. (B) XRD pattern and Rietveld refinement of $\\mathsf{D S}\\cdot\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ prepared by reacting Ti, graphite, and $\\mathsf{T i C l}_{4}$ at $950^{\\circ}\\mathrm{C}$ . (C) XRD patterns of dispersible delaminated and sonicated DS- $\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ \nMXenes. (Inset) Colloidal solution of the delaminated $\\mathsf{D S}\\cdot\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ . (D) SEM image and (E) EDX elemental mapping of a $\\mathsf{D S}\\cdot\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ stack. (F) Highresolution HAADF image and (G) EELS atomic column mapping representing the layered structure of $\\mathsf{D S}\\cdot\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ . \n\nCl with an atomic ratio of 49.9:50.1 (fig. S8), which is near the ideal 1:1 stoichiometry. This ratio suggested that the full coverage of MXene surfaces with Cl was achieved. In comparison, the MXenes synthesized by using the traditional MAX-exfoliation route are often deficient in surface coverage, with a typical stoichiometry of $\\mathrm{Ti_{2}C C l_{1.5-1.7}}(5)$ . The formation of Cl-terminated titanium carbide sheets was further confirmed by characteristic binding energies (fig. S9) in the x-ray photoelectron spectroscopy (XPS) (27). All these features, together with the assessment of crystal quality from linewidths in Raman spectra (fig. S10), confirmed the high degree of structural perfection of our DS- $\\mathrm{{Ti}_{2}\\mathrm{{CCl}_{2}}}$ product. \n\nAs-synthesized $\\mathrm{{DS-Ti_{2}C C l_{2}}}$ MXene stacks could be delaminated and solution-processed as individual 2D monolayers (Fig. 1C and fig. S11). For delamination, multilayer MXene was first intercalated with $\\mathrm{Li^{+}}$ by treatment with $2.5\\mathrm{M}$ $n$ -BuLi hexane solution (fig. S12A) (5, 28) then shaken with polar solvents such as $N\\mathrm{\\Omega}$ 一 methylformamide (NMF) or 2,6-difluoropyridine (DFP) to form a suspension of delaminated 2D sheets (fig. S13). Insoluble by-products were selectively precipitated by a mild centrifugation at $240\\ \\mathrm{g}$ for $15~\\mathrm{min}$ (fig. S12B). In delaminated $\\mathrm{{DS}\\mathrm{{-Ti}_{2}\\mathrm{{CCl}_{2}},}}$ , the (0001) diffraction peak shifted to a lower 2q angle of $7.02^{\\circ},$ corresponding to the enlarged $d$ -spacing of $\\mathrm{12.54\\AA}$ , from the original $8.70\\mathrm{\\AA}.$ A similar $d$ -spacing expansion was found in delaminated $\\mathrm{Ti_{3}C_{2}C l_{2}}$ MXenes (from 11.08 to $14.96\\mathrm{\\AA})$ (5). Delamination of $\\mathrm{{DS-Ti_{2}C C l_{2}}}$ MXenes can be performed on a multigram scale, producing ${\\sim}25~\\mathrm{g}.\\mathrm{liter}^{-1}$ colloidal dispersions that can be stable for months under $\\mathbf{N}_{2}$ atmosphere (fig. S14). \n\n# CVD of MXenes \n\nCVD is a versatile technique for synthesizing films, heterostructures, and complete devices by reacting gaseous precursors on a substrate. Although transition-metal carbides and nitrides such as $\\mathrm{{\\bf{Mo}}_{2}\\mathrm{{C}},}$ $\\mathrm{Mo_{2}N}$ , and $\\mathrm{TiC}_{x}$ can be grown with CVD (29–31), such a synthetic option has not been previously available for MXenes. We introduce the direct synthesis of MXenes through CVD and show a route to new morphologies of MXenes with more easily accessible surfaces and exposed catalytically active edges. \n\nWe grew MXenes by CVD at $950^{\\circ}\\mathrm{C}$ on a Ti surface with a $\\mathrm{CH}_{4}$ and $\\mathrm{TiCl_{4}}$ gas mixture diluted in Ar (Fig. 2A). After the exposure for $15\\mathrm{min}$ , the as-synthesized product (denoted as $\\mathrm{{CVD-Ti_{2}C C l_{2}},}$ was characterized by means of XRD (Fig. 2B). According to the Rietveld refinement, the lattice parameters $a=3.2225(2)\\AA$ and $c=8.7658(8)$ Å matched well with the reported values for $\\mathrm{Ti_{2}C C l_{2}}$ MXene $\\textcircled{5}$ . Raman spectra (Fig. 2C) also confirmed the purity of $\\mathrm{Ti_{2}C C l_{2}}$ MXene. High-resolution STEM-EELS (fig. S15) and EDX analysis (fig. S16) confirmed the crystallinity and stoichiometry of CVD$\\mathrm{Ti_{2}C C l_{2}}$ . The center-to-center interlayer distance of $0.88\\pm0.05\\mathrm{nm}$ calculated from STEM images (fig. S17) was typical for $\\mathrm{{Ti}_{2}\\mathrm{{CCl}_{2}}}$ MXenes. SEM images showed a substrate fully covered with a wrinkled layer of $\\mathrm{Ti_{2}C C l_{2}}$ (Fig. 2D). Such a carpet of $\\mathrm{Ti_{2}C C l_{2}}$ MXene sheets grown perpendicular to the substrate would be difficult for traditionally synthesized MXenes to achieve. This morphology, previously observed for other CVD-grown 2D materials such as $\\mathbf{MoS}_{2}$ (32), appeared particularly promising for efficient ion intercalation, such as in supercapacitors (7, 22). \n\nWe used direct CVD synthesis to produce MXenes that have not been previously prepared by the etching of MAX phases. For example, $\\mathrm{Zr_{2}C C l_{2}}$ and $\\mathrm{Zr_{2}C B r_{2}}$ MXenes were synthesized by exposing a $z\\mathrm{r}$ foil to $\\mathrm{CH}_{4}$ and $\\mathrm{zrCl_{4}}$ or $\\mathrm{zrBr_{4}}$ vapor at $975^{\\circ}\\mathrm{C}$ . These two zirconium MXenes appeared in the same general morphology as that of the titanium MXenes, adopting vertically aligned carpet-like structure on the surface of the Zr foil (fig. S18). Arguably the most intriguing product of the direct synthesis was phase-pure nitride $\\mathrm{Ti_{2}N C l_{2}}$ MXene formed through the reaction of $\\mathrm{\\DeltaTi}$ foil with $\\mathrm{TiCl_{4}}$ and $\\mathrm{{N_{2}}}$ above $640^{\\circ}\\mathrm{C}$ (Fig. 2, A to C and E, and figs. S19 and S20). Nitride MXenes have been predicted to have a variety of attractive properties, including ferromagnetism and higher conductivity as compared with that of carbide MXenes (33). However, the challenge of making nitride MXenes by traditional methods of etching nitride MAX phases lies in higher energies needed to extract “A” atoms from corresponding MAX phase—for example, Al from $\\mathrm{Ti}_{n+1}\\mathrm{AlN}_{n}$ (34). The nitride MXene sheets can dissolve in HF solution because of their lower stability (35). To date, only a few nitride MXenes have been synthesized, and experimental realization of chloride-terminated nitride MXenes has not been achieved. Our \n\n![](images/02b609a3ecb3fa06eaff7fedcf5fb9ac461dd476d511a270f7bae2c2e9a731c7.jpg) \nFig. 2. CVD growth of MXenes. (A) Schematic diagram of the CVD reactions. traditional MS- $\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ MXene, which was synthesized by etching Ti2AlC MAX phase (B) XRD patterns and Rietveld refinement for CVD- $\\cdot\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ and CVD- ${\\mathrm{Ti}}_{2}{\\mathsf{N C l}}_{2}$ . (C) Raman with $\\mathsf{C d C l}_{2}$ molten salt. (D) Frontal and cross-sectional SEM images of $_{C V D-T i_{2}C C l_{2}}$ . spectra of $\\mathsf{C V D-T i}_{2}\\mathsf{C C l}_{2}$ and $\\mathsf{C V D-T i}_{2}\\mathsf{N C l}_{2}$ MXenes in comparison with that of a (E) High-resolution HAADF images and EELS elemental mapping of $\\mathsf{C V D-T i}_{2}\\mathsf{N C l}_{2}$ . \n\nCVD method, using $\\mathrm{{N_{2}}}$ as the nitrogen source, further demonstrates the versatility of bottomup MXene syntheses. These reactions can be useful beyond MXenes synthesis. Given that $\\mathrm{TiCl_{4}}$ plays the key role in Ti metallurgy (Kroll process) and in synthesis of $\\mathrm{TiO_{2}}$ from titanium ores (chloride process), both being on the millions of tons annually, the above reactions may create interesting opportunities, such as nitrogen fixation as a side process in conventional $\\mathrm{TiO_{2}}$ synthesis. \n\n# CVD growth of hierarchically structured MXenes \n\nDuring the CVD synthesis of $\\mathrm{Ti_{2}C C l_{2}}$ MXene, gaseous reagents react with the titanium surface (36). As the thickness of growing MXene carpet increases, the diffusion of gaseous reagents toward the reaction zone (Fig. 3A) would slow down, and the growth of the MXene carpet would be expected to be self-limiting. \n\nHowever, we observed a new growth regime that allowed MXenes to bypass this kinetic bottleneck through the sequence of growth stages captured by ex situ SEM studies (fig. S21) and shown schematically in Fig. 3B. The uniform growth of the MXene carpet (Fig. 2D) was followed by the formation of “bulges” (Fig. 3C) that further evolved into spherical MXene “vesicles” (Fig. 3D). Next, these vesicles detached from the substrate (Fig. 3, F and G). The process could repeat itself, the exposed fresh surfaces enabling continuous synthesis of MXenes. After a prolonged CVD reaction, metal titanium was completely consumed (fig. S22). The internal structure of CVD-MXene vesicles was composed of $\\mathrm{Ti_{2}C C l_{2}}$ sheets radiating from the center and oriented normal to the surface (Fig. 3H and fig. S23). Imaging of a fragmented vesicle (Fig. 3E) and individual vesicles dissected with a focused ion beam (FIB) revealed a small void at the vesicle centers (fig. S24). Small $\\mathrm{TiC}_{x}$ crystallites have been often found around the central void of MXene vesicles (figs. S25 and S26), suggesting that buckling of MXene carpet can be initiated by $\\mathrm{TiC}_{x}$ nucleated under the growing MXene carpet. \n\nThe complexity of hierarchical organization of CVD- $\\mathrm{\\cdot\\mathrm{{Ti_{2}C C l_{2}}}}$ vesicles is unusual for MXenes. The formation of “flower-like” morphologies— observed, for example, for graphene (37)— typically resulted from anisotropic growth initiated by a spherical seed acting as center. However, in the case of CVD-grown MXenes, spherical vesicles emerged from the planar MXene carpet. Their possible growth mechanism can be derived from a recent theoretical work, inspired by the nonequilibrium evolution of cell and organelle membranes, that illustrated how membrane growth could lead to a variety of nontrivial geometries similar to our experimentally observed MXene vesicles (38). \n\n![](images/9268f4b19c90bdc9ec149e40b0810bbf193e219afaefc18f6d952498f858d4b6.jpg) \nFig. 3. Morphologies of $\\mathsf{c v o-T i}_{2}\\mathsf{c c l}_{2}$ . (A and B) Schematic diagrams conditions. (C) Microspheres growing on carpets. (D) Individual microspheres. illustrating the (A) reaction zone and (B) proposed buckling mechanism of (E) A fragmented microsphere showing a hollow center. (F to H) STEM $\\mathsf{C V D-T i}_{2}\\mathsf{C C l}_{2}$ through which microspheres are formed. (C to E) SEM images analysis further shows that vertically aligned MXene sheets constitute the show that morphology of $\\mathsf{C V D-T i}_{2}\\mathsf{C C l}_{2}$ can be varied by tuning reaction microspheres, while a void is left at the center. \n\nThe MXene carpet formed at an early stage of CVD growth (Fig. 2C) and loosely attached to the substrate can be approximated as an elastic 2D membrane. The energetics of such an elastic membrane can be defined through the surface area and local curvature by using a Helfrich Hamiltonian with a surface tension and bending rigidity terms, proportional to the surface tension $\\boldsymbol{\\upgamma}$ and the bending rigidity $\\kappa$ , respectively (39). When $\\gamma$ , $\\upkappa>0$ , the membrane naturally prefers a flat geometry under equilibrium conditions (40). However, when new material is constantly added to the sheet, the standard equilibrium description fails to predict its shape and stability (41). During a CVD process, new MXene sheets keep nucleating and growing on the surface of Ti foil. The addition of new materials to a substrate with a fixed area creates substantial in-plane stress within MXene carpet, which can be relaxed by out-of-plane wrinkling or buckling where flexible MXene carpet detaches from rigid Ti surface (42, 43). Viewed in the context of the above-described elastic sheet model, the growth of MXenes induced a negative surface tension in an effective free-energy landscape (supplementary text 2). \n\nVan der Waals–bonded 2D MXene sheets can efficiently slide against each other, which creates only a small elastic penalty for the formation of buckled and curved geometries. Ultimately, these deformations can collapse into spherical vesicles that detach and refresh the substrate for further growth, as schematically shown in Fig. 3B. We found that gas reagent flow rate has a strong effect on the morphology of the CVD product. Flat carpets and bulges were favored at different flow rates (fig. S27), further suggesting that hierarchical morphology of CVD-grown MXenes results from the interplay of complex reaction kinetics rather than from templated growth. We emphasize that detailed mechanistic understanding of MXene vesicles growth will require additional computational and experimental studies. We simply propose a plausible mechanism to help explain the observed phenomenology. \n\n# Electrochemical energy storage \n\nMXenes are known for their excellent pseudocapacitive energy storage properties that stem from the combination of large surface-tovolume ratio and high electrical conductivity. $\\mathrm{Ti}_{2}\\mathrm{CT}_{\\alpha}$ MXenes show some of the highest predicted and experimentally observed capacities among all studied MXene materials (20, 44). We investigated the Li-ion storage properties of electrodes prepared from DS$\\mathrm{Ti_{2}C C l_{2}}$ and $\\mathrm{{CVD-Ti_{2}C C l_{2}}}$ . We performed electrochemical characterizations on $\\mathrm{{DS-Ti_{2}C C l_{2}}}$ using a two-electrode (Li coin cell) configuration. A conducting additive, 10 wt $\\%$ Super $\\mathrm{\\bf~P}$ carbon black, was added following the standard approach. The first several cyclic voltammetry (CV) cycles of a delaminated $\\mathrm{DS-Ti_{2}C C l_{2}}$ electrode recorded at a scan rate of $0.5~\\mathrm{mV}{\\cdot}\\mathrm{s}^{-1}$ within the electrochemical potentials from 0.2 to $3.0\\mathrm{~V~}$ versus $\\mathrm{Li^{+}/L i}$ (fig. S28A) showed redox peaks that can be assigned to the formation of a solid electrolyte interphase (SEI) layer (4, 45). After the third CV cycle, the specific capacitance of DS-MXene electrode stabilized at 341 $\\mathrm{F}{\\cdot}\\mathrm{g}^{-1}$ (which corresponds to a capacity of 265 mA·hour $\\mathbf{g}^{-1})$ (fig. S28B), which is in a good agreement with previously reported data for $\\mathbf{MS-Ti_{2}C C l}_{x}$ MXene $(44)$ . The rectangular CV profile without redox peaks suggests a pseudocapacitive energy storage mechanism for delaminated MXenes (46), which is further supported by the consistency of the rectangular CV profiles recorded with different negative cut-off potentials (Fig. 4A). \n\n![](images/bbcf143a9603a3c57f871ccbaab912e6d9d04d3090811efcaec36cecec9b9ec8.jpg) \nFig. 4. Electrochemical energy storage properties of $\\bar{\\boldsymbol{\\mathsf{I i}}}_{2}\\boldsymbol{\\mathsf{C C l}}_{2}$ MXenes. (A) Cyclic voltammetry (CV) profiles of delaminated $\\mathsf{D S}\\mathsf{-T i}_{2}\\mathsf{C C l}_{2}$ with various negative cut-off potentials at a scan rate of $0.5\\mathsf{m}\\mathsf{V}{\\cdot}\\mathsf{s}^{-1}$ . (B) CV profiles of delaminated DS$\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ at different scan rates from 0.5 to $100\\mathrm{mV}{\\cdot}\\mathsf{s}^{-1}$ . Differential capacity Q was derived from differential capacitance $\\complement$ . (C) Change of DS-MXene electrode capacity and capacitance versus the discharge time during CV scan recorded at \nvarious potential scan rates. (Inset) $b$ -value determination. (D) Galvanostatic charge-discharge (GCD) profiles of DS- $\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ from current densities of 0.1 to $10{\\mathsf{A}}{\\cdot}{\\mathsf{g}}^{-1}.$ (E) GCD profiles of CVD- $\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ from current densities of 3.4 to $650\\upmu\\mathrm{A}$ (F) Normalized galvanostatic discharge capacity of $\\mathsf{C V D-T i}_{2}\\mathsf{C C l}_{2}$ and $\\mathsf{D S}\\cdot\\mathsf{T i}_{2}\\mathsf{C C l}_{2}$ electrodes from 0.4 to \\~160 C. Absolute capacity of $\\mathsf{D S}\\mathsf{-T i}_{2}\\mathsf{C C l}_{2}$ is shown in the secondary y axis as a reference. \n\nThe charge storage kinetics were investigated by measuring the dependence of electrochemical current $i$ on the potential scan rate $v$ (supplementary text 3). In theory, the current scales with scan rate as $\\boldsymbol{i}\\sim\\boldsymbol{v}^{b}$ , where a $b$ -value of 1 corresponds to a capacitive process, and a $b$ -value of 0.5 is typical for battery-type energy storage (47). CV profiles of delaminated $\\mathrm{{DS-Ti_{2}C C l_{2}}}$ MXene at scan rates from 0.5 to $100\\ \\mathrm{mV}{\\cdot}\\mathrm{s}^{-1}$ are shown in Fig. 4B. The specific lithiation capacities and capacitances, versus charge-discharge times and scan rates calculated from the CV profiles, are plotted in Fig. 4C. The Fig. 4C inset shows the $\\mathbf{\\chi}_{i}$ versus $v$ plotted in logarithmic scale from 0.5 to $100\\mathrm{mV}{\\cdot}\\mathrm{s}^{-1}$ . We observed a linear relationship with a slope of $b\\approx0.89$ for scan rates that ranged from 0.5 to $20\\mathrm{mV}{\\cdot}\\mathrm{s}^{-1}$ , indicating a capacitive-like charge storage for the delaminated $\\mathrm{DS-Ti_{2}C C l_{2}}$ electrodes. Galvanostatic charge-discharge (GCD) profiles of a $\\mathrm{DS-Ti_{2}C C l_{2}}$ electrode are shown Fig. 4D. About $48\\%$ capacity was maintained from a current density of 0.1 to $2\\mathrm{A}{\\cdot}\\mathrm{g}^{-1}$ , which is comparable with previously reported values for Cl-terminated MXenes (44, 48). A maximum capacity of $286~\\mathrm{mA}$ ·hour $\\mathbf{g}^{-1}$ was recorded at a specific current of $0.1\\mathrm{A}{\\cdot}\\mathrm{g}^{-1}$ within 0.1 to $3.0\\mathrm{V}$ (fig. S29), which is slightly higher than previously reported value for the optimized performance of MS- $\\mathrm{\\cdotTi_{2}C C l}_{x}$ MXene $(44)$ . These electrochemical studies further confirm excellent electrochemical characteristics of $\\mathrm{{DS-Ti_{2}C C l_{2}}}$ MXene. \n\nThe high-rate performance of MXenes is sensitive to electrode microstructure such as flake size, flake orientation, and pore size distribution (49). For example, restacking of exfoliated MXene sheets can reduce the surface area that is easily accessible for intercalating ions, which is a well-known problem of 2D materials (50). New morphologies, such as CVD-grown MXene carpets and vesicles with individual sheets oriented normal to the substrate (Fig. 3), can facilitate the development of MXenes for fast electrochemical energy storage. To preserve the as-synthesized morphology, $\\mathrm{{CVD-Ti_{2}C C l_{2}}}$ grown on Ti foil (fig. S30) was directly used as an electrode for an electrochemical cell. Galvanostatic plots at various current densities highlight the high-power performance of CVD- $\\mathrm{\\cdotTi_{2}C C l_{2}}$ electrode with vertically oriented MXene sheets in $\\mathrm{Li^{+}}$ intercalation processes (Fig. 4E). The CVD electrode further shows a slightly better high-rate performance than that of delaminated MXene from $0.4\\mathrm{C}$ to ${\\sim}160\\mathrm{~C~}$ (Fig. 4F). The $b$ -value of CVD- $\\mathrm{{Ti}_{2}\\mathrm{{CCl}_{2}}}$ was calculated as 0.93 (fig. S31D), which indicates an energy storage mechanism closer to that of a freely diffusing capacitor. A better understanding of ion transport in complex morphologies of CVD-grown MXenes, as well as charge transport between individual MXene vesicles, should help to further optimize the electrochemical performance of DS- and CVD-grown MXenes. \n\n# REFERENCES AND NOTES \n\n1. M. Naguib et al., Adv. Mater. 23, 4248–4253 (2011). \n2. J. Halim et al., Chem. Mater. 26, 2374–2381 (2014). \n3. M. Ghidiu, M. R. Lukatskaya, M. Q. Zhao, Y. Gogotsi, M. W. Barsoum, Nature 516, 78–81 (2014). \n4. Y. Li et al., Nat. Mater. 19, 894–899 (2020). \n5. V. Kamysbayev et al., Science 369, 979–983 (2020). \n6. O. Mashtalir et al., Nat. Commun. 4, 1716 (2013). \n7. Y. Xia et al., Nature 557, 409–412 (2018). \n8. M. Naguib et al., J. Am. Chem. Soc. 135, 15966–15969 (2013). \n9. A. Iqbal et al., Science 369, 446–450 (2020). \n10. F. Shahzad et al., Science 353, 1137–1140 (2016). \n11. K. Hantanasirisakul et al., Adv. Electron. Mater. 2, 1600050 (2016). \n12. H. Zhou et al., Nat. Commun. 12, 5510 (2021). \n13. M. A. Hope et al., Phys. Chem. Chem. Phys. 18, 5099–5102 (2016). \n14. G. R. Bhimanapati et al., ACS Nano 9, 11509–11539 (2015). \n15. M. Naguib et al., ACS Nano 6, 1322–1331 (2012). \n16. J. Zhou et al., Angew. Chem. Int. Ed. 55, 5008–5013 (2016). \n17. J. Halim et al., Adv. Funct. Mater. 26, 3118–3127 (2016). \n18. D. L. Druffel et al., Chem. Mater. 31, 9788–9796 (2019). \n19. S. J. Hwu, R. P. Ziebarth, S. Vonwinbush, J. E. Ford, J. D. Corbett, Inorg. Chem. 25, 283–287 (1986). \n20. B. Anasori, M. R. Lukatskaya, Y. Gogotsi, Nat. Rev. Mater. 2, 16098 (2017). \n21. A. VahidMohammadi, J. Rosen, Y. Gogotsi, Science 372, 1165–1178 (2021). \n22. X. L. Li et al., Adv. Energy Mater. 10, 2001394 (2020). \n23. H. Wang et al., Adv. Mater. 30, e1704561 (2018). \n24. C. J. Zhang et al., Chem. Mater. 29, 4848–4856 (2017). \n25. Y. R. Luo et al., Joule 3, 279–289 (2019). \n26. X. Yang, N. Gao, S. Zhou, J. Zhao, Phys. Chem. Chem. Phys. 2 19390–19397 (2018). \n27. V. Natu et al., Matter 4, 1224–1251 (2021). \n28. D. Voiry et al., Nat. Chem. 7, 45–49 (2015). \n29. C. Xu et al., Nat. Mater. 14, 1135–1141 (2015). \n30. Y. L. Hong et al., Science 369, 670–674 (2020). \n31. O. Ledain et al., Phys. Procedia 46, 79–87 (2013). \n32. C. Stern et al., Sci. Rep. 8, 16480 (2018). \n33. H. Kumar et al., ACS Nano 11, 7648–7655 (2017). \n34. I. R. Shein, A. L. Ivanovskii, Comput. Mater. Sci. 65, 104–114 (2012). \n35. M. Naguib, V. N. Mochalin, M. W. Barsoum, Y. Gogotsi, Adv. Mater. 26, 992–1005 (2014). \n36. J. Gavillet et al., Phys. Rev. Lett. 87, 275504 (2001). \n37. S. Y. Wang et al., Carbon 120, 103–110 (2017). \n38. J. Binysh, T. R. Wilks, A. Souslov, Sci. Adv. 8, eabk3079 (2022). \n39. G. Salbreux, F. Jülicher, Phys. Rev. E 96, 032404 (2017). \n40. A. D. Pezzutti, H. Hernández, J. Phys. Conf. Ser. 1603, 012003 (2020). \n41. Z. Hua et al., Nat. Commun. 10, 5406 (2019). \n42. B. Li, Y. P. Cao, X. Q. Feng, H. J. Gao, Soft Matter 8, 5728–5745 (2012). \n43. D. J. Schmidt et al., ACS Nano 3, 2207–2216 (2009). \n44. G. Ma et al., Nat. Commun. 12, 5085 (2021). \n45. R. M. Gnanamuthu, C. W. Lee, Mater. Chem. Phys. 130, 831–834 (2011). \n46. S. Fleischmann et al., Nat. Energy 7, 222–228 (2022). \n47. N. Elgrishi et al., J. Chem. Educ. 95, 197–206 (2018). \n48. L. Liu et al., ACS Nano 16, 111–118 (2022). \n49. M. R. Lukatskaya et al., Nat. Energy 2, 17105 (2017). \n50. J. Wang, V. Malgras, Y. Sugahara, Y. Yamauchi, Nat. Commun. 12, 3563 (2021). \n\n# ACKNOWLEDGMENTS \n\nThe authors express their appreciation to I. Golovina for helping with atomic force microscopy measurements. We thank Y. Han and G. Yan for helpful discussions about electrochemical measurements and G. Olack for helping with SEM data analysis. We are also grateful to A. Nelson for a critical reading and editing of the manuscript and M. Talapin for help with artwork. Funding: The work on direct MXene synthesis was supported by the National Science Foundation under award DMR-2004880, and CVD synthesis was supported by the US Department of Defense Air Force Office of Scientific Research under grants FA9550-22-1-0283 and FA9550-20-1-0104. Electrochemical studies were supported by the Advanced Materials for Energy-Water Systems (AMEWS) Center, an Energy Frontier Research Center funded by the US Department of Energy (DOE), Office of Science, Basic Energy Sciences. W.C. and S.V. were supported by the University of Chicago Materials Research Science and Engineering Center, which is funded by the National Science Foundation under award DMR-2011854. S.V. acknowledges support from the National Science Foundation under grant DMR-1848306. F.L. and R.F.K. at UIC were supported by a grant from the National Science Foundation (NSF-DMR 1831406). Acquisition of UIC JEOL ARM200CF was supported by an MRI-R2 grant from the National Science Foundation (DMR-0959470). The Gatan Continuum GIF acquisition at UIC was supported by an MRI grant from the National Science Foundation (DMR-1626065). FIB-SEM was performed at the Canadian Centre for Electron Microscopy, a Canada Foundation for Innovation Major Science Initiatives funded facility. The work also used resources of the Center for Nanoscale Materials, a DOE Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under contract DE-AC02-06CH11357. Author contributions: D.W. performed and designed the experiments, analyzed data, and cowrote the paper. C.Z. carried out Raman measurements and data analysis. A.S.F. contributed to x-ray measurements and data analysis. W.C. contributed to TEM analysis of delaminated MXene and building the CVD system. F.L. and R.F.K. performed high-resolution STEM studies and image analysis. M.W. and C.L. contributed to the electrochemistry measurements and data analysis. S.V. performed simulations and interpretation of the morphology of CVD-MXenes. D.V.T. conceived and designed experiments and simulations, analyzed data, cowrote the paper, and supervised the project. All authors discussed the results and commented on the manuscript. Competing interests: D.W. and D.V.T. are inventors on patent application US 63/399,931 submitted by the University of Chicago, which covers direct synthesis and CVD of MXenes. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. The samples can be provided by the authors upon reasonable request under a materials transfer agreement with the university. Correspondence and requests for materials should be addressed to D.V.T. (dvtalapin@uchicago.edu). License information: Copyright $\\circledcirc$ 2023 the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.science.org/about/ science-licenses-journal-article-reuse \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.add9204 \nMaterials and Methods \nSupplementary Notes \nFigs. S1 to S34 \nTables S1 to S5 \nReferences (51–59) \n\nSubmitted 13 July 2022; accepted 31 January 2023 \n10.1126/science.add9204 " + }, + { + "id": "10.1126_science.ade3970", + "DOI": "10.1126/science.ade3970", + "DOI Link": "http://dx.doi.org/10.1126/science.ade3970", + "Relative Dir Path": "mds/10.1126_science.ade3970", + "Article Title": "Rational design of Lewis base molecules for stable and efficient inverted perovskite solar cells", + "Authors": "Li, CW; Wang, XM; Bi, EB; Jiang, FY; Park, SM; Li, Y; Chen, L; Wang, ZW; Zeng, LW; Chen, H; Liu, YJ; Grice, CR; Abudulimu, A; Chung, JH; Xian, YM; Zhu, T; Lai, HG; Chen, B; Ellingson, RJ; Fu, F; Ginger, DS; Song, ZN; Sargent, EH; Yan, YF", + "Source Title": "SCIENCE", + "Abstract": "Lewis base molecules that bind undercoordinated lead atoms at interfaces and grain boundaries (GBs) are known to enhance the durability of metal halide perovskite solar cells (PSCs). Using density functional theory calculations, we found that phosphine-containing molecules have the strongest binding energy among members of a library of Lewis base molecules studied herein. Experimentally, we found that the best inverted PSC treated with 1,3-bis(diphenylphosphino)propane (DPPP), a diphosphine Lewis base that passivates, binds, and bridges interfaces and GBs, retained a power conversion efficiency (PCE) slightly higher than its initial PCE of similar to 23% after continuous operation under simulated AM1.5 illumination at the maximum power point and at similar to 40 degrees C for >3500 hours. DPPP-treated devices showed a similar increase in PCE after being kept under open-circuit conditions at 85 degrees C for >1500 hours.", + "Times Cited, WoS Core": 347, + "Times Cited, All Databases": 357, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:001016371000012", + "Markdown": "# SOLAR CELLS \n\n# Rational design of Lewis base molecules for stable and efficient inverted perovskite solar cells \n\nChongwen Li1, Xiaoming Wang1, Enbing Bi1, Fangyuan Jiang2, So Min Park3, You Li1, Lei Chen1, Zaiwei Wang3, Lewei Zeng3, Hao Chen3, Yanjiang Liu3, Corey R. Grice1,4, Abasi Abudulimu1, Jaehoon Chung1, Yeming Xian1, Tao Zhu1, Huagui Lai5, Bin Chen3,6, Randy J. Ellingson1, Fan $\\mathsf{F u}^{5}$ , David S. Ginger2, Zhaoning Song1, Edward H. Sargent3,6,7, Yanfa Yan1\\* \n\nLewis base molecules that bind undercoordinated lead atoms at interfaces and grain boundaries (GBs) are known to enhance the durability of metal halide perovskite solar cells (PSCs). Using density functional theory calculations, we found that phosphine-containing molecules have the strongest binding energy among members of a library of Lewis base molecules studied herein. Experimentally, we found that the best inverted PSC treated with 1,3-bis(diphenylphosphino)propane (DPPP), a diphosphine Lewis base that passivates, binds, and bridges interfaces and GBs, retained a power conversion efficiency (PCE) slightly higher than its initial PCE of ${\\sim}23\\%$ after continuous operation under simulated AM1.5 illumination at the maximum power point and at $\\sim40^{\\circ}\\mathsf{C}$ for $>3500$ hours. DPPP-treated devices showed a similar increase in PCE after being kept under open-circuit conditions at $85^{\\circ}\\mathsf{C}$ for $>1500$ hours. \n\nG iven their high power conversion efficiencies (PCEs), metal halide perovskite solar cells (PSCs) offer a route to lowering the cost of solar electricity (1–4). However, durability remains a major hurdle along the path to technological relevance $(5-7)$ and must be assessed through accelerated degradation tests (8). Damp heat testing at $85^{\\circ}\\mathrm{C}$ in the dark at $85\\%$ relative humidity (RH), a test standard for crystalline silicon (Si) and thin-film photovoltaic (PV) modules, has been adopted for accelerating the durability test of PSCs (9–11). These tests are typically used to evaluate packaging rather than PV material durability. PSCs can also show degradation under photoexcited conditions (12), and especially under open-circuit (OC) conditions (13), that are more acute than one sees in standardized silicon tests. Mechanistically, such findings are often attributed to ion migration (14, 15) and charge accumulation at interfaces (9, 16, 17). \n\nWe studied the operating stability at $85^{\\circ}\\mathrm{C}$ under simulated 1-sun illumination (where 1 sun is defined as the standard illumination at AM1.5, or $\\mathrm{1kWm^{-2}},$ ) and OC conditions— important test conditions under which PSCs have been studied to date only to a limited degree (18–20). Light- and heat-induced degradation in PSCs is related to point defects formed at interfaces and grain boundaries (GBs) (14, 21). Moisture-induced degradation is curtailed using encapsulation (22), whereas the passivation of defects at interfaces and GBs within the perovskite film is required to improve the PCE and intrinsic durability of PSCs (11, 23–26). The use of phosphorus (P)–, nitrogen (N)–, sulfur (S)– and oxygen (O)– containing Lewis base molecules to form coordinate covalent bonds (dative bonds) that donate electrons to undercoordinated Pb atoms at interfaces and GBs has shown particular promise for increasing PSC durability (27–29). \n\nUsing density functional theory (DFT), we saw evidence that P-containing Lewis base molecules showed the strongest binding with uncoordinated Pb atoms. We thus pursued diphosphine-containing molecules, reasoning that these would provide additional binding and bridging at interfaces and GBs. For our experimental studies, we selected 1,3- bis(diphenylphosphino)propane (DPPP), a diphosphine Lewis base. We found that treating perovskites with a small amount of DPPP improves PCE and durability: Inverted (p-i-n) PSCs after DPPP treatment showed a champion PCE of $24.5\\%$ . A DPPP-treated PSC with an initial PCE of ${\\sim}23\\%$ stabilized at ${\\sim}23.5\\%$ after maximum power point tracking (MPPT) under continuous simulated AM1.5 illumination at ${\\sim}40^{\\circ}\\mathrm{C}$ for $>3500$ hours. DPPP-stabilized PSCs showed no PCE degradation after being kept at OC and $85^{\\circ}\\mathrm{C}$ conditions for $>1500$ hours. \n\n# Bonding interactions of Lewis bases \n\nThe P, N, S, and O atoms in Lewis base molecules donate electrons to the Lewis acid sites in perovskites, such as the undercoordinated $\\mathrm{Pb^{2+}}$ at perovskite surfaces, in order to form coordinate covalent bonds. In general, the \n\nLewis basicity, which is inversely proportional to electronegativity, is expected to determine the binding energy and the stabilization of interfaces and GBs. We compared binding energies of the prototypical Lewis bases trimethylphosphine (TMP), trimethylamine (TMA), dimethyl sulfide (DMS), and dimethyl ether (DME), with $\\mathrm{sp}^{3}$ hybridization to the surface of formamidinium lead iodide $\\mathrm{(FAPbI_{3})}$ 0 through DFT calculations (Fig. 1A). The calculated binding strength followed the order $\\mathrm{{\\DeltaP>}}$ $\\mathbf{N}>\\mathbf{S}>0$ , indicating that the electronegativity rule did not strictly apply—a finding we attribute to the remaining lone-pair electrons in the case of S and O after binding with perovskites. We also compared frequently reported Lewis base molecules with the $\\mathrm{sp}^{2}$ oxygen in the carbonyl groups and took acetone and methyl acetate (MeOAc) as examples in Fig. 1A (26, 30). The binding energies were similar to that of DME. \n\nLewis base molecules have mostly been used to passivate uncoordinated Pb atoms (24, 31–33). A Lewis base molecule with two electron-donating atoms can potentially bind and bridge interfaces and GBs, offering the potential to enhance the adhesion and strengthen the mechanical toughness of PSCs and provide additional benefits related to the durability of PSCs. For this reason, we selected DPPP, a diphosphine Lewis base molecule, in seeking to stabilize and passivate PSCs. As shown in Fig. 1B and fig. S1, a DPPP molecule has two P atoms with $\\mathrm{sp}^{3}$ hybridization in tetrahedral coordination. The lone-pair electrons occupy the missing vertex of the tetrahedron, and if donated to Lewis acids (metal cations) to form a covalent bond, the fully tetrahedral coordination would realize and gain more stabilization. \n\nWe calculated the binding of DPPP on the surfaces of $\\mathrm{FAPbI_{3}}$ both with lead(II) iodide $\\mathrm{(PbI_{2})}$ and formamidinium iodide (FAI) terminations. Although DFT calculations predicted that the FAI-terminated surface would be more stable $(34)$ , experimental evidence showed that the $\\mathrm{PbI_{2}}$ -terminated surface is readily formed during the solvent treatment from depositing subsequent layers (35). DFT calculations also showed that DPPP was chemically bonded to the $\\mathrm{PbI_{2}}$ -terminated surface through P–Pb bond formation with a binding energy of $2.24~\\mathrm{eV}$ but was weakly bonded to the FAIterminated surface by van der Waals interaction with a binding energy of $1.09\\mathrm{eV}$ (Fig. 1, C and D). Moreover, the calculated binding energy of DPPP with perovskites in two adjacent slabs $(3.08\\ \\mathrm{eV})$ was larger than that in the same slab $(2.24~\\mathrm{eV})$ (Fig. 1, D and E). Similarly, the binding energy of DPPP with both the perovskite and $\\mathrm{NiO}_{\\alpha}$ slabs (4.31 eV) was larger than that in the same $\\mathrm{NiO}_{x}$ slab $(3.28~\\mathrm{eV})$ (Fig. 1F and fig. S2). Thus, DPPP was predicted to bind, bridge, and stabilize perovskite GBs and the perovskite $\\mathrm{NiO}_{x}$ interface. DPPP molecules also provided hole transport channels through the P-terminated alkane chain of DPPP (fig. S3). \n\n# Synthesis and structure \n\nThe interaction between DPPP molecules and $\\mathrm{Pb^{2+}}$ is observed through the formation of a new adduct when a thin layer of DPPP is deposited on a $\\mathrm{PbI_{2}}$ layer (fig. S4). When fabricating devices, we deposited the FA-based perovskite layer on a DPPP-coated $\\mathrm{NiO}_{x}$ hole transport layer. During the growth of perovskite films, some DPPP molecules redissolved and segregated at both the perovskite $\\mathrm{\\DeltaNiO}_{x}$ interface and the perovskite surface regions, as verified by the time-of-flight secondary ion mass spectrometry (TOF-SIMS) depth profiles shown in Fig. 2A. X-ray photoelectron spectroscopy (XPS) revealed that after DPPP treatment, the core levels of the elements in both perovskite and $\\mathrm{NiO}_{x}$ shifted (Pb and Ni XPS spectra in Fig. 2, B and C, and the O, C, N, and I spectra in fig. S5). The universal shift of core levels caused by electrostatic interaction indicates the existence of DPPP at both interfaces. The DPPP treatment also slightly improved the crystallinity of perovskite films, as can be seen from the enhancement of grain domain size (fig. S6) and x-ray diffraction (XRD) peak intensity (fig. S7). DPPP treatment did not change the bandgap of the perovskite films (fig. S8). Photoluminescence (PL) and time-resolved PL spectroscopy (TRPL) spectra (Fig. 2, D and E) showed enhanced PL intensity and an $\\sim50\\%$ improvement in lifetime, from 0.98 to $1.49\\upmu\\mathrm{s},$ for the DPPP-treated perovskite films, consistent with the expected reduction in nonradiative recombination and defect density upon Lewis base treatment (29, 36). We further verified that DPPP treatment enhanced the mechanical toughness of the perovskite $\\mathrm{NiO}_{x}$ interface. Perovskite films were deposited on a half-cell structure with and without DPPP treatment, protected by a thin polymethyl methacrylate (PMMA) layer, and adhered to a glass plate with epoxy (see details in the supplementary materials and fig. S9). A (A) TOF-SIMS depth profile of a DPPP-treated sample showing that DPPP molecules segregate at both interfaces. XPS spectra comparing (B) binding energy of Pb-4f core levels of control and DPPP-treated samples and (C) binding energy of Ni- $2{\\mathsf{p}}$ core levels of ${\\mathsf{N i O}}_{x}$ before and after DPPP treatment. PL (D) and TRPL (E) spectra of control and DPPP-treated perovskite films measured from the film side. The samples were excited with a continuous-wave $633\\cdot\\mathsf{n m}$ laser at a fluence of $1.5\\times10^{17}$ photons $\\mathsf{c m}^{-2}\\mathsf{s}^{-1}$ . (F) Histogram and standard control perovskite film (Fig. 3, B and D, and fig. S12). Scanning electron microscopy (SEM) images measured from the bottom surface show needle-shaped $\\mathrm{PbI_{2}}$ crystals on the asprepared control film, which is likely caused by the excess $\\mathrm{PbI_{2}}$ added to the precursor solution (fig. S14A). The as-prepared DPPPtreated film showed distinct layered structures (fig. S14B), which we speculated could possibly be the Lewis acid-base adduct of $\\mathrm{PbI_{2}}$ and DPPP. After aging, the $\\mathrm{PbI_{2}}$ crystals in the control film decomposed and produced pinholes on the grains (Fig. 3E). In contrast, the DPPP-treated films exhibited much-suppressed degradation (Fig. 3F). Time-resolved mass spectroscopy was also conducted on control and DPPP-treated films under illumination to investigate the degradation process. The control sample showed the release of hydrogen iodide (HI) and iodide (I) species (fig. S15), which are by-products of the photoinduced decomposition and trigger irreversible chemical chain reactions that accelerate the decomposition of perovskites (37, 38). In addition to the iodide species, another perovskite decomposition by-product, metallic lead $\\left(\\mathrm{Pb}_{0}\\right)$ , was also observed on the control film after light soaking. The XPS spectrum of the control film after light soaking showed two $\\mathrm{Pb}_{0}$ peaks at ${\\sim}136$ and \\~141 eV (Fig. 3G), whereas no $\\mathrm{Pb}_{0}$ peaks were observed in DPPP-treated film. These results reveal that DPPP treatment could effectively suppress the photodecomposition at the $\\mathrm{NiO}_{\\alpha}/$ perovskite interface, likely by reducing the density of reactive undercoordinated lead sites (halide vacancies) at the surface and interfaces. \n\n![](images/293f7cf6012be8a933fd5d2e0083c464b52ba4ac4c4fc1612e968737f8494809.jpg) \nFig. 1. DFT-calculated DPPP binding with perovskites. (A) Chemical structures of prototypical Lewis base molecules. The values shown are the DFT-calculated binding energies (in electron volts) of the Lewis base molecule bonded to the $\\mathsf{F A P b l}_{3}$ surface with $\\mathsf{P b l}_{2}$ termination. (B) Molecular structure of DPPP. The P atom of DPPP donates a lone-pair electron to the metal cation forming a coordinate covalent bond. Covalent bonding and van der Waals bonding for DPPP bound on $\\mathsf{F A P b l}_{3}$ surfaces with (C) FAI and (D) $\\mathsf{P b l}_{2}$ terminations, respectively. DPPP binds (E) two perovskite slabs and (F) perovskite and $\\mathsf{N i O}_{x}$ substrate through chemical-bond formation between P and $\\mathsf{P b}$ or Ni atoms in a Lewis acid-base reaction. \n\n![](images/16db0ad380a535246c92de1b8f9cf134c432938631a25e5d1a3b380eecc23611.jpg) \nFig. 2. Effects of DPPP on perovskite film quality and device performance. \ndeviation values of loads at break of 10 sets of control and DPPP-treated samples. a.u., arbitrary units. \n\n![](images/0e1ab195e264a7cbffc45c45b4fb63a18abe40d87ca57e3d56cb4e3e11c2b80e.jpg) \nFig. 3. Characterization of perovskite film stability before and after DPPP treatment. (A to D) Hyperspectral PL images and histograms of control and DPPP-treated perovskite films before and after light aging. The PL images were taken from the buried interface side, and the PL count at each pixel refers to the integrated PL counts over the whole spectrum. (E and F) SEM top-view images taken from the buried interface of control and DPPP-treated perovskite films after light soaking. (G) XPS measured from the buried interface of control and DPPP-treated perovskite films after light soaking. \n\n# Solar cell fabrication and performance \n\ntensile load was applied to delaminate the films using the testing machine shown in fig. S10. After delamination, both the $\\mathrm{NiO}_{x}$ and perovskite surfaces of the $\\mathrm{NiO}_{\\alpha}/$ perovskite interface showed $\\mathrm{~\\bf~P~}$ signals, indicating that DPPP remained on both surfaces (fig. S11). The tensile force recorded during the delamination process (Fig. 2F) suggests that DPPP treatment enhanced the mechanical strength of the perovskite $\\mathrm{NiO}_{x}$ interface through the binding of DPPP at the interface. \n\nHyperspectral PL mapping measured from the buried interfaces and PL intensity histograms (Fig. 3, A to D) revealed an overall higher PL intensity of the DPPP-treated perovskite film that was consistent with the longer PL lifetimes and indicated reduced defect density as compared with the control perovskite films. The PL emission heterogeneity increased, and more dark spots were observed over time in the control film after light aging (fig. S12). These dark spots showed lower PL emission intensity, and we attributed them to the initial sites of photodegradation at localized defects and local heterogeneities, which were more prevalent in the control sample without DPPP. PL decay takes place mostly in regions with low initial PL counts, whereas PL enhancement takes place in regions with high initial PL counts (fig. S13). This observation proves that local PL enhancement or decay in the control sample is associated with local defect heterogeneities. In comparison, the DPPPtreated films exhibited higher uniformity and better light stability, with most of the pixels showing photo-brightening with increased PL counts, rather than photo-decay with decreased PL counts, as was observed for the \n\nWe fabricated PSCs with the p-i-n configuration of glass/FTO $\\mathrm{NiO}_{\\mathit{x}}/$ Me-4PACz/(with or without) DPPP $\\mathrm{\\langleFA_{0.95}C s_{0.05}P b I_{3}/P E A I/C_{60}/}$ $\\mathrm{SnO_{2}/A g}$ to show the effect of DPPP treatment on improving device performance and stability {FTO, fluorine-doped tin oxide; Me-4PACz, [4- (3,6-dimethyl-9H-carbazol-9-yl)butyl]phosphonic acid; PEAI, phenethylammonium iodide}. Note that $\\mathrm{NiO}_{x}$ was treated by a very thin layer of Me-4PACz to improve the reproducibility (fig. S16). The statistics of our device performance results are shown in fig. S17. A small amount of DPPP (1 or $2\\mathrm{mg/ml}.$ ) consistently improved the open-circuit voltage $(V_{\\mathrm{OC}})$ and fill factor (FF) across the comparison of 40 devices. Both the improvement in $V_{\\mathrm{OC}}$ and FF are expected to accompany a reduction in surface recombination velocity through a reduction in surface defects (39), and they are also in qualitative agreement with the increase in film PL and PL lifetime upon treatment. Higher concentrations of DPPP $\\mathrm{\\langle4mg/ml\\rangle}$ ) decreased short-circuit current density $(J_{\\mathrm{SC}})$ and FF, which may have resulted from the overreaction between DPPP and perovskites. Figure 4A shows current \n\nFor durability tests, we replaced the Ag electrodes with $\\mathtt{C r-C u}$ alloy to avoid instability caused by Ag corrosion and diffusion but slightly lowered the device efficiency (by ${\\sim}4\\%$ ) (fig. S20). We used $0.1\\mathrm{{cm}^{2}}$ aperture masks for solar cells when conducting all the stability tests. We first tested the effect of DPPP on device stability by MPPT under continuous 1-sun illumination in an $\\mathrm{{N}_{2}}$ environment at a temperature of ${\\sim}40^{\\circ}\\mathrm{C}$ . As shown in Fig. 4C, the DPPP-treated device exhibited an initial PCE of ${\\sim}23\\%$ , which increased to ${\\sim}23.5\\%$ after \\~450 hours and remained unchanged after 3500 hours. The increased PCE resulted from the increased voltage at maximum power point (fig. S21). The increased voltage is likely due to the light-induced annihilation of halide defects (10, 40–43). However, the PCE of the control device decreased to $<80\\%$ of its initial PCE after 1000 hours. The film area of the control PSC turned dark yellow, indicating the decomposition of perovskite to $\\mathrm{PbI_{2}}$ after 3500 hours (fig. S22). In contrast, the film area of the DPPP-treated device remained dark, indicating a more-stabilized perovskite after DPPP treatment. \n\n![](images/bd5120b608fa2be1ae9ac7099e77520bf9f4b0fc451591c8d364223ecbc7d97a.jpg) \nFig. 4. Performance and stability of control and DPPP-treated devices. (A) $J\\cdot V$ curves of champion control and DPPP-treated devices. REV, reverse scan; FWD, forward scan. (B) EQE spectra of the corresponding control and DPPP-treated devices. (C) MPPT of control and DPPP-treated devices measured under continuous 1-sun illumination in an ${\\sf N}_{2}$ environment at a temperature of ${\\sim}40^{\\circ}\\mathrm{C}$ . (D) Thermal stress test of control and DPPP-treated devices aged at $85^{\\circ}\\mathrm{C}$ following the ISOS-D-2 protocol. (E) Tracking of control and DPPP-treated devices measured at $85^{\\circ}\\mathrm{C}$ and under continuous ${\\sim}0.9$ -sun illumination and OC condition. \n\ndensity–voltage (J-V) scans of the champion control and DPPP-treated $\\mathrm{{\\langle2\\mg/ml}\\rangle}$ devices with $0.1\\mathrm{{cm}^{2}}$ aperture masks under forward and reverse scans. The PCE of the DPPP-treated device improved from 22.6 to $24.5\\%$ , with $V_{\\mathrm{OC}}$ increasing from ${\\sim}1.11$ to ${\\sim}1.16~\\mathrm{V}$ and FF increasing from ${\\sim}79\\$ to ${\\sim}82\\%$ (see detailed device parameters in table S1). External quantum efficiency (EQE) spectra (Fig. 4B) verified the $J_{\\mathrm{SC}}$ values obtained from the $J{-}V$ measurement. The enhanced EQE at short wavelengths also indicates improved carrier extraction at the front interface, which may be associated \n\nWe then conducted accelerated durability tests at elevated temperatures. We kept the PSCs in a dark oven at $85^{\\circ}\\mathrm{C}$ and in the ambient atmosphere and measured the PCEs periodically for the thermal stress test (ISOS-D-2 protocol). We tested 18 PSCs and summarize their statistics in fig. S23. The average PCEs and their corresponding standard deviations (Fig. 4D) reveal that the DPPP-treated devices retain, on average, ${\\sim}90\\%$ of their initial PCE after 1500 hours, whereas, in contrast, the average PCE of the control devices dropped to $<90\\%$ after 168 hours. \n\nwith the passivated interface achieved through the use of DPPP. We also fabricated PSCs with a larger active area $(1.05\\mathrm{cm}^{2})$ to validate the benefits of DPPP treatment. The target devices with DPPP treatment also showed overall improvement in device parameters (fig. S18), with the champion target device showing PCEs of 23.9 and $23.6\\%$ under reverse and forward scans, respectively (fig. S19 and table S2). The improvement on FF and $V_{\\mathrm{OC}}$ confirmed the reduction in defect density at the $\\mathrm{NiO}_{x}$ /perovskite front interface after DPPP treatment. \n\nWe conducted a more rigorous accelerated durability test under the OC condition and continuous ${\\sim}0.9$ -sun illumination. The devices were kept in an oven at a temperature of $85^{\\circ}\\mathrm{C}$ and humidity of ${\\sim}65\\%$ and measured every $208~\\mathrm{s}$ . The devices measured at $85^{\\circ}\\mathrm{C}$ showed slightly lower PCEs, possibly owing to the negative temperature coefficient (fig. S24). The PCE was stable for the first $\\sim300$ hours and then slightly increased to ${\\sim}108\\%$ of its initial value and showed no degradation after 1500 hours (Fig. 4E). However, the control device degraded rapidly after 400 hours, dropping to ${\\sim}80\\%$ of its initial PCE. Two more DPPP-treated PSCs were measured to validate the improved stability by DPPP treatment (fig. S25). The photos of devices after 1500 hours of illumination are shown in fig. S26. The glass-side view of the control film turned gray, which was likely the result of delamination of the perovskite film at the $\\mathrm{NiO}_{\\alpha}/$ perovskite front interface and the degradation of the perovskite layer. In contrast, the DPPP-treated device showed partial delamination on the edge but remained dark over most of the film area. \n\n# Discussion \n\nTaking experimental findings together with DFT studies, we offer that DPPP molecules strengthen the $\\mathrm{NiO}_{\\alpha}/$ perovskite interface and stabilize the perovskite phase. The robust binding between the $\\mathrm{NiO}_{x}$ and perovskite enabled by DPPP modification appears to be an enabler of the stable operation of PSCs under outdoor conditions. The measured stability under accelerated testing conditions indicates a benefit from DPPP in the form of improved device stability and provides ways of realizing commercialization of PSCs. \n\n# REFERENCE AND NOTES \n\n1. A. K. Jena, A. Kulkarni, T. Miyasaka, Chem. Rev. 119, 3036–3103 (2019). \n2. Z. Li et al., Nat. Rev. Mater. 3, 18017 (2018). \n3. H. Min et al., Nature 598, 444–450 (2021). \n4. Y. Zhao et al., Science 377, 531–534 (2022). \n5. Y. Rong et al., Science 361, eaat8235 (2018). \n6. L. Meng, J. You, Y. Yang, Nat. Commun. 9, 5265 (2018). \n7. P. Holzhey, M. Saliba, J. Mater. Chem. A 6, 21794–21808 (2018). \n8. K. Domanski, E. A. Alharbi, A. Hagfeldt, M. Grätzel, W. Tress, Nat. Energy 3, 61–67 (2018). \n9. M. V. Khenkin et al., Nat. Energy 5, 35–49 (2020). \n10. R. Azmi et al., Science 376, 73–77 (2022). \n11. C. C. Boyd, R. Cheacharoen, T. Leijtens, M. D. McGehee, Chem. Rev. 119, 3418–3451 (2019). \n12. M. Kim et al., ACS Energy Lett. 6, 3530–3537 (2021). \n13. E. Bi, Z. Song, C. Li, Z. Wu, Y. Yan, Trends Chem. 3, 575–588 (2021). \n14. K. Domanski et al., Energy Environ. Sci. 10, 604–613 (2017). \n15. T. Duong et al., ACS Appl. Mater. Interfaces 9, 26859–26866 (2017). \n16. B. Chen et al., Adv. Mater. 31, e1902413 (2019). \n17. Y. Yuan, J. Huang, Acc. Chem. Res. 49, 286–293 (2016). \n18. L. Shi et al., ACS Appl. Mater. Interfaces 9, 25073–25081 (2017). \n19. S. Yang et al., Science 365, 473–478 (2019). \n20. Y.-H. Lin et al., Science 369, 96–102 (2020). \n21. S. Bai et al., Nature 571, 245–250 (2019). \n22. Z. Li et al., Science 376, 416–420 (2022). \n23. T.-H. Han et al., Nat. Commun. 10, 520 (2019). \n24. M. Zhu et al., Mater. Horiz. 7, 2208–2236 (2020). \n25. D. W. deQuilettes et al., ACS Energy Lett. 1, 438–444 (2016). \n26. C. Shi et al., Adv. Funct. Mater. 32, 2201193 (2022). \n27. Z. Yang et al., Adv. Funct. Mater. 30, 1910710 (2020). \n28. N. K. Noel et al., ACS Nano 8, 9815–9821 (2014). \n29. N. Ahn et al., J. Am. Chem. Soc. 137, 8696–8699 (2015). \n30. A. Seidu, M. Dvorak, J. Järvi, P. Rinke, J. Li, APL Mater. 9, 111102 (2021). \n31. S. Tan et al., J. Am. Chem. Soc. 143, 6781–6786 (2021). \n32. D. W. deQuilettes et al., Science 348, 683–686 (2015). \n33. Z. Song et al., Sustain. Energy Fuels 2, 2460–2467 (2018). \n34. F. Fu et al., Energy Environ. Sci. 12, 3074–3088 (2019). \n35. J. Wang et al., ACS Energy Lett. 4, 222–227 (2019). \n36. J. A. Christians et al., Nat. Energy 3, 68–74 (2018). \n37. W. Nie et al., Nat. Commun. 7, 11574 (2016). \n38. G. Kresse, J. Furthmüller, Phys. Rev. B 54, 11169–11186 (1996). \n39. G. Kresse, J. Furthmüller, Comput. Mater. Sci. 6, 15–50 (1996). \n40. P. E. Blöchl, Phys. Rev. B 50, 17953–17979 (1994). \n41. J. P. Perdew, K. Burke, M. Ernzerhof, Phys. Rev. Lett. 77, 3865–3868 (1996). \n42. S. Grimme, J. Antony, S. Ehrlich, H. Krieg, J. Chem. Phys. 132, 154104 (2010). \n43. A. R. M. Alghamdi, M. Yanagida, Y. Shirai, G. G. Andersson, K. Miyano, ACS Omega 7, 12147–12157 (2022). \n\n# ACKNOWLEDGMENTS \n\nC.L. acknowledges D. Luo for important discussions about the XPS analysis. Funding: This material is based on work supported by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technologies Office awards DE-EE0008970 and DE-EE0008753 and by the US Air Force Research Laboratory under agreement FA9453-21- C-0056. The contributions of F.J. and D.S.G., focusing on hyperspectral imaging for cell metrology, are based primarily on work supported by EERE under the Solar Energy Technologies Office (award DE-EE0009528) as well as institutional support from the B. Seymour Rabinovitch Endowment and the state of Washington. DFT calculations were supported by the Center for Hybrid Organic-Inorganic Semiconductors for Energy (CHOISE), an Energy Frontier Research Center funded by the Office of Basic Energy Sciences, Office of Science, within the US Department of Energy and the National Science Foundation under contract DMR-1807818. The DFT calculations were performed using computational resources sponsored by the Department of Energy’s Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory and the DOS calculations used resources of the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under contract DE-AC02-05CH11231 using NERSC award BES-ERCAP0017591. The US Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation thereon. The views expressed are those of the authors and do not reflect the official guidance or position of the United States government, the Department of Defense, or of the United States Air Force. The appearance of external hyperlinks does not constitute endorsement by the United States Department of Defense (DoD) of the linked websites, or the information, products, or services contained therein. The DoD does not exercise any editorial, security, or other control over the information you may find at these locations. Approved for public release; distribution is unlimited. Public Affairs release approval #AFRL-2022-3776. E.H.S. acknowledges support from the US Department of the Navy, Office of Naval Research (grant NO0014-20-1-2572). Author contributions: C.L. and Y.Y. conceived of the idea. Y.Y. supervised the projects and process. C.L., S.M.P., and E.B. fabricated perovskite films and devices for characterization and performance measurement. X.W. and Y.X. carried out DFT calculations. C.L., L.C., T.Z., and L.Z. carried out SEM, ultravioletvisible, and XRD measurements and data analysis. Z.S. carried out time-resolved mass spectroscopy measurements and data analysis. F.J. and D.S.G. carried out hyperspectral microscope measurements and associated data analysis. C.L. and J.C. prepared $\\mathsf{N i O}_{x}$ substrates. Y.Li carried out stability tests and data analysis. Z.W., Y.Liu, and H.C. carried out XPS measurements and data analysis. H.L. and F.F. carried out the TOF-SIMS measurements and data analysis. C.R.G. carried out tensile force measurements and data analysis. A.A. and R.J.E. carried out the PL and TRPL measurements and data analysis. C.L., X.W., Z.S., and Y.Y. wrote the first draft of the manuscript. E.H.S., Y.Y., C.L., Z.S., and B.C. reviewed and edited the manuscript. All authors discussed the results and contributed to the manuscript revisions. Competing interests: C.L. and Y.Y are inventors on a patent application (no. 17038731) related to this work filed by the University of Toledo. The other authors declare no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. License information: Copyright $\\textcircled{\\mathtt{c}}2023$ the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www. science.org/about/science-licenses-journal-article-reuse \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.ade3970 \nMaterials and Methods \nFigs. S1 to S26 \nTables S1 and S2 \nReferences \n\nSubmitted 16 August 2022; resubmitted 18 September 2022 \nAccepted 13 January 2023 \n10.1126/science.ade3970 \n\n# Erratum \n\n# Erratum for the Research Article “Rational design of Lewis base molecules for stable and efficient inverted perovskite solar cells” by C. Li et al. \n\nIn the Research Article “Rational design of Lewis base molecules for stable and efficient inverted perovskite solar cells” (17 February 2023, p. 690), the upper bounds of the scale bars in Fig. 3, A and C, were incorrectly labeled as 120,000 during manuscript revision before publication; the upper bound for both should be 140,000. The error has been corrected. This adjustment does not affect the interpreta­ tion of the data or any discussions in the manuscript. " + }, + { + "id": "10.1038_s41586-022-05540-0", + "DOI": "10.1038/s41586-022-05540-0", + "DOI Link": "http://dx.doi.org/10.1038/s41586-022-05540-0", + "Relative Dir Path": "mds/10.1038_s41586-022-05540-0", + "Article Title": "Operando studies reveal active Cu nullograins for CO2 electroreduction", + "Authors": "Yang, Y; Louisia, S; Yu, S; Jin, JB; Roh, I; Chen, CB; Guzman, MVF; Feijóo, J; Chen, PC; Wang, HS; Pollock, CJ; Huang, X; Shao, YT; Wang, C; Muller, DA; Abruña, HD; Yang, PD", + "Source Title": "NATURE", + "Abstract": "Carbon dioxide electroreduction facilitates the sustainable synthesis of fuels and chemicals(1). Although Cu enables CO2-to-multicarbon product (C2+) conversion, the nature of the active sites under operating conditions remains elusive(2). Importantly, identifying active sites of high-performance Cu nullocatalysts necessitates nulloscale, time-resolved operando techniques(3-5). Here, we present a comprehensive investigation of the structural dynamics during the life cycle of Cu nullocatalysts. A 7 nm Cu nulloparticle ensemble evolves into metallic Cu nullograins during electrolysis before complete oxidation to single-crystal Cu2O nullocubes following post-electrolysis air exposure. Operando analytical and four-dimensional electrochemical liquid-cell scanning transmission electron microscopy shows the presence of metallic Cu nullograins under CO2 reduction conditions. Correlated high-energy-resolution time-resolved X-ray spectroscopy suggests that metallic Cu, rich in nullograin boundaries, supports undercoordinated active sites for C-C coupling. Quantitative structure-activity correlation shows that a higher fraction of metallic Cu nullograins leads to higher C2+ selectivity. A 7 nm Cu nulloparticle ensemble, with a unity fraction of active Cu nullograins, exhibits sixfold higher C2+ selectivity than the 18 nm counterpart with one-third of active Cu nullograins. The correlation of multimodal operando techniques serves as a powerful platform to advance our fundamental understanding of the complex structural evolution of nullocatalysts under electrochemical conditions.", + "Times Cited, WoS Core": 400, + "Times Cited, All Databases": 410, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000938818200001", + "Markdown": "# Article \n\n# Operando studies reveal active Cu nanograins for CO electroreduction \n\nhttps://doi.org/10.1038/s41586-022-05540-0 \n\nReceived: 17 March 2022 \n\nAccepted: 8 November 2022 \n\nPublished online: 8 February 2023 Check for updates \n\nYao Yang1,2,3,11, Sheena Louisia1,3,11, Sunmoon $\\yen123,4,11$ , Jianbo Jin1, Inwhan Roh1,3, Chubai Chen1,3, Maria V. Fonseca Guzman1,3, Julian Feijóo1,3, Peng-Cheng Chen1,5, Hongsen Wang6, Christopher J. Pollock7, Xin Huang7, Yu-Tsun Shao8, Cheng Wang9, David A. Muller8,10, Héctor D. Abruña6,10 & Peidong Yang1,3,4,5 ✉ \n\nCarbon dioxide electroreduction facilitates the sustainable synthesis of fuels and chemicals1. Although Cu enables ${\\mathsf{C O}}_{2}$ -to-multicarbon product $(\\mathbf{C}_{2+})$ conversion, the nature of the active sites under operating conditions remains elusive2. Importantly, identifying active sites of high-performance Cu nanocatalysts necessitates nanoscale, time-resolved operando techniques3–5. Here, we present a comprehensive investigation of the structural dynamics during the life cycle of Cu nanocatalysts. A 7 nm Cu nanoparticle ensemble evolves into metallic Cu nanograins during electrolysis before complete oxidation to single-crystal $\\mathtt{C u}_{2}0$ nanocubes following post-electrolysis air exposure. Operando analytical and four-dimensional electrochemical liquid-cell scanning transmission electron microscopy shows the presence of metallic Cu nanograins under ${\\mathsf{C O}}_{2}$ reduction conditions. Correlated high-energy-resolution time-resolved X-ray spectroscopy suggests that metallic Cu, rich in nanograin boundaries, supports undercoordinated active sites for C–C coupling. Quantitative structure–activity correlation shows that a higher fraction of metallic Cu nanograins leads to higher $\\mathbf{C}_{2+}$ selectivity. A 7 nm Cu nanoparticle ensemble, with a unity fraction of active Cu nanograins, exhibits sixfold higher $\\mathbf{C}_{2+}$ selectivity than the $18\\mathsf{n m}$ counterpart with one-third of active Cu nanograins. The correlation of multimodal operando techniques serves as a powerful platform to advance our fundamental understanding of the complex structural evolution of nanocatalysts under electrochemical conditions. \n\nCopper remains the only heterogeneous electrocatalyst to selectively catalyse the ${\\mathsf{C O}}_{2}$ reduction reaction $(\\mathsf{C O}_{2}\\mathsf{R R})$ to multicarbon $\\displaystyle(\\mathbf{C}_{2+})$ products, including ethylene, ethanol and propanol, at appreciable rates1,2. Recent developments in operando/in situ methods, including advanced electron microscopy and synchrotron-based X-ray, provide powerful nondestructive tools to probe active sites and structural changes of electrocatalysts under reaction conditions3–5. However, there remains a lingering debate over the active state of Cu catalysts regarding valence state or coordination environments under ${\\bf C O}_{2}{\\bf R R}$ . For instance, some reports have proposed ${{\\mathsf{C}}{\\mathbf{u}}}^{+}$ species and subsurface oxide as potential active sites of oxide-derived Cu electrocatalysts6–9 whereas others have suggested that the active state of bulk Cu catalysts is metallic10–12, because subsurface oxides are not stable under negative potentials13–15. Another potential structural descriptor of locally enhanced ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ activity reported is micrometre-sized grain boundaries on bulk metal electrodes13–18. Those studies probed local activity at grain boundaries at micrometre-level spatial resolution, suitable only for bulk electrodes. Because $\\mathbf{C}_{2+}$ product formation involves a C–C coupling step over multiple atomic Cu sites in close proximity2, resolving catalytically active sites at or close to subnanometre resolution is necessary to uncover the structural origin of ${\\bf C O}_{2}{\\bf R R}$ -active surfaces. In particular, operando methods with high spatiotemporal resolution are instrumental in elucidating active sites of Cu nanoparticle (NP) electrocatalysts (under $\\mathsf{100}\\mathsf{n m},$ among many other nanocatalysts19. \n\nBuilding on our previous studies, this study presents a comprehensive structural picture of the life cycle for a family of high-performance Cu NP ensemble electrocatalysts and provides a baseline understanding of their structures20–22. An ensemble of monodisperse Cu NPs underwent a structural transformation process (that is, ‘electrochemical scrambling’) where the surface oxide is reduced, followed by ligand desorption and formation of aggregated/disordered Cu structures that correlate with the formation of catalytically active sites for ${\\bf C O}_{2}{\\bf R R}$ (Fig. 1a). The active Cu structures rapidly evolve into single-crystal $\\mathtt{C u}_{2}0$ nanocubes on exposure to air. Herein, we propose that active Cu nanograins play a critical role in the reduction/oxidation life cycle of these Cu nanocatalysts: (1) active sites for selective reduction of ${\\mathsf{C O}}_{2}$ to $\\mathbf{C}_{2+}$ products and (2) highly reactive sites for breaking $\\scriptstyle0=0$ bonds and insertion of O atoms in the tetrahedral sites of Cu lattice. \n\n![](images/5216373c7b05867d51bda10216bd8d47095646d0f87fdc59373233b632b70be3.jpg) \nFig. 1 | Scheme of the life cycle of Cu nanocatalysts and operando EC-STEM studies of dynamic morphological changes of 7 nm NPs. a, While conventional ex situ methods are limited to the study of nanocatalysts before/after ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ , the operando/in situ methods used in this study uncover the dynamic changes in morphology, composition and structure under real-time catalytically relevant conditions. An ensemble of monodisperse Cu NPs undergo structural transformation during which the surface oxide is reduced, ligands are desorbed and a progressive coalescence/aggregation leads to the formation of active metallic Cu nanograins. We propose that these highly polycrystalline Cu nanograins are made of disordered grain boundaries that support undercoordinated Cu active sites for $\\mathbf{C}_{2+}$ formation. On exposure to air, Cu nanograins also demonstrate high reactivity for $\\mathbf{O}_{2}$ bond breakage and insertion in the Cu \nlattice to form $\\mathsf{C u}_{2}\\mathsf{O}.$ . b, Schematic of operando EC-STEM and 4D-STEM with the capability of enabling quantitative electrochemical measurements and simultaneous tracking of morphological and structural changes under ${\\bf C O}_{2}{\\bf R R}$ - relevant conditions. c–e. Overview of the life cycle of 7 nm Cu nanocatalysts shown by EC-STEM images of initial growth after a single negative-direction LSV scan, from 0.4 to 0 V (c), further growth under CA at 0 V (d) and the postelectrolysis formation of $\\mathbf{Cu}_{2}\\mathbf{O}$ cubes (marked by the arrow) when exposed to air at the same location (e). f–i, Morphological evolution of 7 nm NPs at 0 V versus RHE at 0 (f), 8 (g), 16 (h) and 24 s (i). False-colour images in the inset of (i) highlight newly formed regions (green) after 24 s growth. j–m, Further particle aggregation of 7 nm NPs at −0.8 V for 0 (j), 8 (k), 16 (l) and 32 s (m), with significant changes highlighted in dashed boxes. \n\n# Article \n\nA family of Cu NP (7, 10 and $18\\:\\mathrm{nm}$ ) ensembles was studied to investigate size dependence on their structural evolution dynamics. High-angle annular dark-field scanning transmission electron microscopy (HAADF–STEM) images show synthesized Cu NPs with narrow size distribution (Supplementary Fig. 1). Atomic-scale STEM images and corresponding electron energy loss spectroscopy (EELS) mapping of as-synthesized fresh 7 nm NPs show a $\\mathtt{C u@C u_{2}O}$ core-shell structure with a metallic Cu core surrounded by an oxide shell of approximately $2\\mathsf{n m}$ (Extended Data Fig. 1a,b and Supplementary Fig. 2). The $7\\mathsf{n m C u}$ NPs oxidized to ${\\tt C u}_{2}0$ NPs after air exposure for over 5 h post synthesis (Supplementary Figs. 3 and 4). We note that, whether 7 nm NPs are partially or fully oxidized, this does not impact catalytic performance because they probably reach a comparable active state during electrolysis (Supplementary Fig. 4). By contrast, both 10 and 18 nm NPs maintain a stable $\\mathtt{C u@C u_{2}O}$ core-shell structure over extended air exposure, suggesting that a minimum particle size of around $10\\:\\mathrm{nm}$ is required to form a self-passivated surface oxide layer (Extended Data Fig. 1c–f and Supplementary Figs. 6–10). This ex situ analysis of pristine Cu nanocatalysts provides the necessary guidance for further operando electrochemical STEM (EC-STEM) studies. \n\nTo track the dynamic morphological and structural evolution of Cu nanocatalysts and elucidate the nature of Cu active sites, we used operando EC-STEM and four-dimensional STEM (4D-STEM) diffraction imaging. The operando EC-STEM cell encapsulates a liquid pocket with a three-electrode configuration, including Cu NPs deposited on the carbon working electrode, Pt counter and Pt pseudoreference electrode (WE, CE and RE, respectively)23–25 (Fig. 1b). The redox potential and current density measured in the operando EC-STEM cell indicate that Cu NPs electrochemically behave consistently with standard H-cell measurements (Supplementary Figs. 11–13). A potential of −0.8 V versus reversible hydrogen electrode (RHE; all potentials are referenced to the RHE scale unless noted otherwise) was applied on the 7 nm NPs ensemble in the EC-STEM cell to simulate the optimal ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ potential for $\\mathbf{C}_{2+}$ product formation (Supplementary Fig. 14). The as-prepared EC-STEM cell has a liquid thickness of 500 nm or greater26, which is often too thick to resolve NPs below $10\\mathsf{n m}$ (Supplementary Fig. 15). Thus we adopted a ‘thin liquid’ strategy27,28, performing a single linear sweep voltammetry (LSV) scan from 0.4 to 0 V to trigger the hydrogen evolution reaction (typically co-existent during ${\\bf C O}_{2}{\\bf R R}_{}^{*}$ ). Electrogenerated ${\\sf H}_{2}$ bubbles enable a thinner liquid film of about $100\\mathsf{n m}$ , as quantified by liquid-cell EELS (Supplementary Fig. 16), leading to a significantly enhanced spatial resolution for tracking of individual NPs in liquids (Supplementary Fig. 17 and Supplementary Video 1). We observed that parts of the NP ensemble (lower part below the dashed line) already experienced noticeable particle aggregation immediately after the LSV scan (Fig. 1c). This points to the high reactivity/mobility of small Cu NPs even at potentials more positive than the onset of the ${\\bf C O}_{2}{\\bf R R}$ $(-0.4\\mathsf{V})$ . Operando EC-STEM images captured at $_{0\\vee}$ at an identical location show marked aggregation of the remaining 7 nm NPs into Cu nanograins with sizes of $_{50-100\\mathsf{n m}}$ (Fig. 1d,e). On exposure to air, small Cu nanograins (under $50\\mathrm{nm}.$ ) evolved into ${\\bf C u}_{2}{\\bf O}$ nanocubes whereas some large Cu nanoclusters (over $100\\mathsf{n m}$ ) maintained an irregular morphology, possibly because of the loss of reactivity of bulk Cu with ${\\ O_{2}}^{22}$ . Figure 1c–e provides an overview of the electroreduction/oxidation life cycle of the ${7}{\\mathrm{nm}}{\\mathsf{C u N P}}$ ensemble. \n\nTo resolve the initial stage of Cu nanograin formation, a mild potential of 0 V was applied on the $7\\mathsf{n m}$ NP ensemble (Fig. 1f–i). Operando EC-STEM videos in this study were first recorded without applied potentials as control experiments to ensure that no beam-induced damage had occurred (Supplementary Video 2). After the initial LSV scan, Cu nanograins were observed and the remaining 7 nm Cu NPs underwent rapid structural transformation, leading to the formation of new Cu nanograins and additional particle growth (Fig. 1f–h). A false-colour STEM image taken at 0 and $24\\thinspace s$ (red versus green) illustrates the difference, with the image in the inset highlighting the particle growth process on existing Cu nanograins (Fig. 1i and Supplementary Fig. 18). At the $\\mathbf{C}_{2+}$ optimal potential (−0.8 V), more marked particle movement occurred in the first 8 s followed by progressive particle aggregation/coalescence (8–32 s) (Fig. 1j–m and Supplementary Video 3). Cu nanograins of 50–100 nm formed at $-0.8\\mathsf{V}$ approached a steady-state structure after extended electroreduction for 90 s (Supplementary Fig. 19). Following airflow, Cu nanograins rapidly evolved into well-defined $\\mathtt{C u}_{2}0$ nanocubes of around $100\\mathsf{n m}$ , similar to those formed after H-cell measurement (Supplementary Figs. 20 and 21). In summary, operando EC-STEM of the 7 nm Cu NP ensemble identified two types of morphology: loosely connected small Cu nanograins and closely packed large Cu nanograins, which may serve as active sites for ${\\bf C O}_{2}{\\bf R R}$ . \n\nOperando 4D-STEM diffraction imaging in liquid provides unique structural information beyond the traditional STEM imaging of morphological changes27. 4D-STEM uses a newly developed electron microscope pixel array detector (EMPAD) that can rapidly record a two-dimensional (2D) electron diffraction pattern over a 2D grid of probe positions29–32. 4D-STEM, with its high sensitivity and dynamic range, can significantly lower electron dose while retrieving nanometre-scale crystallographic information, which is indispensable for beam-sensitive materials in liquid. We focus on the structural transformation of the most active $7\\mathsf{n m N P s}$ from the initial stage to the steady state of Cu nanograins, followed by post-electrolysis ${\\bf C u}_{2}{\\bf O}$ nanocubes formed following air exposure (Fig. 2, left). The HAADF–STEM image in Fig. 2a shows 7 nm, NP-derived, loosely connected Cu nanograins formed at 0 V. A virtual bright-field (BF) STEM image, retrieved from 4D-STEM datasets, better shows the fine granular features of Cu nanograins (Fig. 2b). One particular domain (Fig. 2c) was selected to show the diffraction pattern of a metallic Cu domain with Cu{111} (2.1 Å) and $\\mathtt{C u}\\{200\\}$ (1.8 Å) close to the Cu[110] zone axis. 4D-STEM dark-field imaging, based on diffraction spots 1 (red), 2 (green) and 3 (blue), yielded a false-colour map showing crystal domains with the same/similar crystal orientations resembling those three diffraction spots. The 4D-STEM composite maps in Fig. 2d clearly show the highly polycrystalline nature of active Cu with fine nanograins. Two particular regions highlight those nanograin boundaries that are either loosely connected (Fig. 2e) or closely overlapped (Fig. 2f). The Cu grains shown in Fig. 2e,f are around $5\\mathrm{-}10\\mathsf{n m}$ , comparable to the size of pristine 7 nm Cu NPs. This indicates that pristine 7 nm Cu NPs serve as building blocks in the formation of nanograin boundaries, which are probably rich in defects and dislocations after the initial stage of electroreduction at 0 V. Similar metallic Cu nanograins were widely observed in other 4D-STEM maps (Supplementary Fig. 22). To the best of our knowledge, this observation represents the first report of sub- $10\\mathsf{n m}$ nanograin boundaries supporting possible Cu active sites, at an unprecedented spatial resolution enabled by a probe size of approximately 1 nm. \n\nFollowing electroreduction at $-0.8\\mathsf{V}$ , metallic Cu nanograins (50– $\\mathsf{100}\\mathsf{n m},$ ) achieved a steady-state, closely packed structure (Fig. 2g). A majority of diffraction patterns from Cu domains indicate polycrystalline metallic Cu (Fig. 2h), with few domains showing a single-crystal-like metallic Cu feature close to the Cu[110] zone axis (Fig. 2i). This indicates that some Cu nanograins have sufficient driving force for reconstruction into highly crystalline Cu domains during electroreduction at $-0.8\\mathsf{V}.$ False-colour dark-field 4D-STEM maps, based on the three diffraction spots shown in Fig. 2i, show that the majority of Cu nanograins are composed of individual grains separated by grain boundaries and/or stacking faults (Fig. 2j, white arrows). Interestingly, the Cu nanograins magnified in the dashed box in Fig. 2j show the predominant crystal orientation in green resembling diffraction spot 2 in Fig. 2i, and some metallic Cu nanograins on the surface with other crystal orientations in red resembling diffraction spot 1. This in-depth structural analysis indicates that the dominant active Cu sites, formed at $-0.8\\mathsf{V}_{\\F}$ , are closely packed and highly polycrystalline metallic Cu nanograins relative to the loosely connected Cu nanograins formed at $\\mathbf{\\Delta}_{0}\\mathbf{\\upnu}$ . \n\n![](images/78a516c8bccadced66e8e425b7eb1692bd31094106a44435a5d97536f6870105.jpg) \nFig. 2 | Operando 4D-STEM diffraction imaging of metallic Cu nanograins. a–n, Left, scheme serving as a visual guide to the structural evolution, from the initial stage of loosely connected Cu nanograins at 0 V (a–e) to steady-state closely packed Cu nanograins at $-0.8\\mathsf{V}(\\mathbf{g}-\\mathbf{i})$ , followed by the formation of $\\mathrm{Cu}_{2}\\mathrm{O}$ cubes when exposed to air $\\mathbf{\\Gamma}(\\mathbf{k}{-}\\mathbf{n})$ . a, HAADF–STEM images of co-existing 7 nm NPs and loosely connected active Cu nanograins following initial growth at 0 V. b, Virtual BF STEM image of Cu nanograins reconstructed from 4D-STEM datasets from the dashed box in a. c, Representative electron diffraction pattern of one Cu domain in a showing the metallic Cu with $\\mathrm{Cu}\\{200\\}$ (1.8 Å) and Cu{111} $(2.1\\mathring{\\mathbf{A}})$ close to the [110] zone axis. d, False-colour dark-field 4D-STEM maps showing Cu nanograins with diffraction spots resembling those in b marked as \n1 (red), 2 (green) and 3 (blue), respectively. e,f, Two particular regions, extracted from the dashed box in d, showing loosely connected Cu nanograins (e) and overlapping nanograin boundaries (f). g, HAADF–STEM image of closely packed Cu nanograins formed at $-0.8\\mathsf{V}.$ h,i, Representative diffraction patterns of highly polycrystalline Cu (poly-Cu) (h) and single-crystal-like Cu nanograins (i). j, False-colour dark-field 4D-STEM maps showing highly crystalline Cu nanograins with diffraction spots resembling those three marked as 1, 2 and 3 in i. k, HAADF– STEM image of $\\mathrm{\\hat{C}}\\mathbf{u}_{2}\\mathbf{O}$ nanocubes formed on air exposure. l–n, Selective diffraction patterns of single-crystal $\\mathtt{C u}_{2}0$ cubes with d-spacings of {200} (2.1 Å), {111} $(2.5\\mathring\\mathrm{A})$ or {110} $(3.0{\\mathring\\mathrm{A}})$ . \n\nUnder airflow to repel electrolytes, metallic Cu nanograins at the same location in the EC-STEM cell rapidly evolved into well-defined $\\mathtt{C u}_{2}0$ nanocubes (Fig. 2k). The 4D-STEM diffraction patterns in Fig. $21-{\\mathsf{n}}$ show that the $\\mathtt{C u}_{2}0$ nanocubes are single crystals with edge length of around 60–120 nm. We hypothesize that metallic Cu nanograins formed under bias are highly defective/disordered, rendering them especially reactive to $\\mathbf{O}_{2}$ molecules. $\\scriptstyle0=0$ bonds can dissociate and allow the spontaneous insertion of O atoms in the Cu lattice. In addition, operando EC-STEM of post-synthesis $\\mathtt{C u}_{2}0$ nanocubes under bias shows the fragmentation of large cubes (about $100\\mathsf{n m}$ ) and redeposition of small nanoclusters (under $20\\mathsf{n m}$ ), which is markedly different from the structure of metallic Cu nanograins $(50-100\\mathrm{nm})$ formed at $-0.8\\ensuremath{\\mathsf{V}}$ (Supplementary Fig. 23 and Supplementary Video 4). This suggests that metallic Cu nanograins can be derived only from the ${7}\\mathrm{{nm}\\mathrm{{Cu}\\mathrm{{NP}}}}$ ensemble and cannot be reversibly obtained from post-electrolysis $\\mathtt{C u}_{2}0$ nanocubes. As demonstrated by the loss of $\\mathrm{{\\bf{C}}}_{2+}$ selectivity/activity on utilization of these post-electrolysis nanocubes (Supplementary Fig. 24), only metallic Cu nanograins obtained through the assembly and reconstruction of self-assembled Cu NPs can serve as the supporting structure for ${\\bf C O}_{2}{\\bf R R}$ -active undercoordinated Cu sites. In summary, operando EC-STEM suggests that the ${7}\\boldsymbol{\\mathrm{nm}}\\mathbf{Cu}\\mathbf{NP}$ ensemble evolves into polycrystalline/disordered Cu nanograins and transforms into single-crystal ${\\bf C u}_{2}0$ nanocubes post electrolysis. \n\nSimilar to 7 nm NPs, $10\\mathsf{n m}$ NPs underwent substantial particle movement/aggregation during the first 8 s at $-0.8\\ensuremath{\\mathsf{V}}$ and continued to grow into larger Cu nanograins $(50\\mathrm{-}100\\mathrm{nm})$ (Fig. 3a–d, Supplementary Figs. 25 and 26 and Supplementary Video 5). Meanwhile, the $18\\mathsf{n m}$ Cu NP ensemble showed a distinctly different structural evolution. After an initial LSV to 0 V, $18\\mathsf{n m}$ Cu NPs on the carbon WE partially aggregated and formed intriguing ‘melting’ features at the initial stage (Fig. 3e,f). Subsequent air exposure led to the transformation of metallic nanograins into well-defined ${\\bf C u}_{2}{\\bf O}$ nanocubes whereas nearby unreacted 18 nm Cu NPs remained unchanged (Fig. 3g and Supplementary Fig. 27). At −0.8 V, 18 nm Cu NPs underwent progressive particle reconstruction and migration (Fig. 3i–k) and agglomerated into large Cu nanograins after around 4 min (Supplementary Fig. 28 and Supplementary Video 6). The limited and slower structural reconstruction of the larger NPs probably originates from their intrinsically lower surface energy; additionally, larger NPs are packed less closely due to restricted interdigitation of their surface ligands in comparison with the smaller NP ensemble33,34. As a result, the initial aggregation of 10 and 18 nm Cu NPs is less dramatic than that of 7 nm Cu NPs, leading to a lower density of nanograin boundaries and less active undercoordinated Cu sites. This hypothesis is corroborated by Pb underpotential deposition (UPD) that indicates a higher density of undercoordinated sites on the 7 nm Cu NP ensemble (Supplementary Fig. 29). \n\n# Article \n\n![](images/e58ba24dae01950c2aebef2171b41e66cfa506ce6c572899c015e2a55763becb.jpg) \nFig. 3 | Operando EC-STEM studies of dynamic morphological changes in 10 and 18 nm NPs. a–d, Selected operando EC-STEM video frames of the evolution of 10 nm NPs at $-0.8\\ensuremath{\\mathrm{V}}$ at 0 (a), 8 (b), 16 (c) and 32 s (d). e,f, EC-STEM images showing $18\\mathsf{n m N P s}$ partially melted into Cu nanograins after initial growth following one LSV scan from 0.4 to 0 V. Limit of NP aggregation (e) and Cu nanograins (f). g, STEM image of ${\\bf C u}_{2}{\\bf O}$ nanocubes formed from Cu nanograins following exposure to air, with nearby unreacted 18 nm NPs \nmaintaining their pristine morphology. h,l, Structural models showing the transformation from 18 nm Cu NP ensembles to metallic Cu nanograins with surface Cu sites $(\\mathsf{C u}@\\mathsf{C u}^{s})$ (h) and average grain size smaller than pristine NPs by around $3\\mathring{\\mathbf{A}}$ (l), which was supported by operando RSoXS studies using the same liquid-cell TEM holder. i–k, Operando EC-STEM images of the slower dynamic evolution of $18\\ \\mathrm{nm}$ NPs relative to 7  nm NPs at −0.8  V for 0 (i), 8 ( j) and 164 s (k) relative to 7  nm NPs. AU, arbitrary units. \n\nThe particle aggregation dynamics of 18 nm Cu NPs are illustrated in the structural model in Fig. 3h. We posit that the surface oxide of 18 nm Cu NPs is reduced and that NPs form metallic Cu nanograins with surface-active sites $(\\mathsf{C u}@\\mathsf{C u}^{s})$ in a more closely packed structure. This hypothesis is supported by operando resonant soft X-ray scattering (RSoXS)34 using the same liquid-cell set-up as operando EC-STEM (Fig. 3l). At 0 V, the X-ray scattering intensity of Cu increased dramatically relative to the pristine 18 nm Cu NP ensembles measured at open circuit potential (OCP). This indicates a higher level of aggregation of Cu NPs per unit area leading to stronger X-ray scattering, which is consistent with the formation of the denser melting feature in EC-STEM (Fig. 3f). At $-0.8\\ensuremath{\\mathsf{V}}$ the X-ray intensity remained at a similar level but exhibited a noticeable shift of the first minimum to a higher $Q$ -value, which corresponds to an average grain size smaller than that of pristine $18\\mathsf{n m}$ Cu NPs, by $2.9\\pm0.2\\mathring{\\mathbf{A}}$ (one monolayer) (Supplementary Fig. 30). This suggests that, although $18\\mathsf{n m}\\mathsf{C u N P s}$ , as building blocks, aggregated to form active Cu nanograins, only the surface $2\\mathsf{n m}$ oxide layer participated in formation of a lower density of nanograin boundaries, thus resulting in a smaller contribution of active undercoordinated Cu sites. Operando RSoXS provides a statistically robust analysis of the aggregation dynamics of Cu NPs, complementing the operando EC-STEM studies. \n\nOperando high-energy-resolution fluorescence detected X-ray absorption spectroscopy (HERFD-XAS) was then used to elucidate the valence state and coordination environment of the Cu NP ensemble under ${\\bf C O}_{2}{\\bf R R}$ conditions and following exposure to air (Fig. 4). The electrochemical behaviour of Cu nanocatalysts was comparable in both the customized $\\mathsf{x}$ -ray cell and H-cell, with no observation of beam damage on the Cu NPs in electrolyte (Supplementary Figs. 31–33). HERFD-XAS enables a significantly higher energy resolution (approximately 1 eV) than conventional solid-state fluorescence detection $(50-200\\mathrm{eV})^{10-12,35,36}.$ , enabling the detection of fine features in X-ray absorption near-edge spectroscopy (XANES) pre-edge regions (Supplementary Figs. 34–36). HERFD-XANES of the ${7}\\mathrm{{nm}\\mathrm{{Cu}\\mathrm{{NP}}}}$ ensemble showed the same pre-edge energy as bulk $\\mathtt{C u}_{2}0$ (Fig. 4a), supporting the view that NPs are fully oxidized after storage in air as previously shown by EELS (Supplementary Fig. 3). The chemical state of Cu NPs was then investigated under ${\\bf C O}_{2}{\\bf R R}$ . At $-0.8\\mathsf{V}.$ , the NP ensemble showed edge features similar to those of Cu foil. The observed transition to metallic Cu is consistent with the formation of the Cu nanograins observed with 4D-STEM (Fig. 2). On post-electrolysis air exposure, the NPs completely re-oxidized to $\\mathtt{C u}_{2}0$ . The resolution of HERFD-XANES enabled us to carry out accurate quantitative analysis of the valence states achieved throughout the NP life cycle (Supplementary Figs. 37–39). The oxide volume fractions of NP ensembles, as determined by XAS, are consistent with oxide shell thickness in EELS analysis (Supplementary Fig. 40). Quantitative valence analysis over the course of electrolysis showed nanograins to mixed phases of $\\mathrm{{Cu}/\\mathrm{{Cu}_{2}O}}$ following exposure to air. The electroreduction/reoxidation cycle was confined to the surface oxide layer. e, Operando HERFD-EXAFS of 7 nm NPs under ${\\bf C O}_{2}{\\bf R R}$ conditions and following exposure to air, with EXAFS after 1 h of electroreduction, suggesting the presence of undercoordinated Cu sites as highlighted by the red asterisk. |Χ(R)| is the EXAFS amplitude. f, Structure–activity correlation of relative fraction of active Cu nanograins and $\\mathbf{C}_{2+}$ faradaic efficiency of Cu NP ensembles with three different NP sizes. g, Faradaic efficiency for all ${\\bf C O}_{2}{\\bf R R}$ products grouped as $\\mathbf{C}_{2+}$ , $\\mathbf{C}_{1}$ products and ${\\sf H}_{2}$ obtained from ensembles of three different Cu NP sizes (7, 10 and $18\\mathsf{n m}$ ) at $-0.8\\mathrm{V}$ in an H-cell. \n\n![](images/6dac0ed344a50782fc49bcbd2f5948ada3756448b1dfbe40dbfe21cdc271a2ea.jpg) \nFig. 4 | Operando HERFD-XAS study of the valence state and coordination environment of Cu nanocatalysts during their electroreduction/ reoxidation life cycle. a, Operando HERFD-XANES spectra of pristine 7 nm NPs, metallic Cu formed at $-0.8\\ensuremath{\\mathrm{V}}$ under ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ conditions and $\\mathtt{C u}_{2}0$ cubes formed following post-electrolysis exposure to air, along with the standard references (ref.) of bulk Cu and $\\mathtt{C u}_{2}0$ (dashed lines). b, Quantitative analysis of relative fraction of metallic Cu, showing conversion from ${\\bf C u}_{2}0$ NPs to fully metallic Cu nanograins and reoxidation of Cu nanograins to ${\\bf C u}_{2}0$ nanocubes following exposure to air. c,d, Operando HERFD-XANES (c) and corresponding quantitative analysis (d) of 18 nm NPs at $-0.8\\ensuremath{\\mathrm{V}}$ showing transformation from $\\mathtt{C u@C u_{2}O}$ NPs to fully metallic Cu nanograins and reoxidation of those Cu \n\nthe metallic Cu fraction increasing from 0 to $100\\%$ over 1 h (Fig. 4b and Supplementary Fig. 41), which was corroborated by second-level tracking of electroreduction/oxidation kinetics at constant photon energy (Supplementary Figs. 42 and 43). These measurements testify that electroreduction of the 7 nm Cu NPs was completed within around $30\\mathrm{min}$ at $-0.8{\\mathsf{V}}.$ \n\nHERFD-XANES of 18 nm Cu NPs indicated an average composition of around $70\\%$ metallic Cu in the core and around $30\\%\\mathrm{Cu}_{2}0$ in the shell. These larger NPs underwent a similar transition to metallic Cu under electroreduction, although less marked relative to the smaller NPs (Fig. 4c and Supplementary Fig. 44). In addition, the pre-edge peak after post-electrolysis exposure to air suggested that 18 nm Cu NPs evolved into a mixed Cu and ${\\bf C u}_{2}{\\bf O}$ phase, matching the partial formation of nanocubes from EC-STEM studies (Fig. $_{3\\mathbf{g})}$ . Quantitative valence analysis suggested that the electroreduction of 18 nm Cu NPs was confined to the surface $\\mathtt{C u}_{2}0$ layer and required a shorter time (approximately $10\\mathrm{min}\\mathrm{,}$ ) than their $7\\mathsf{n m N P}$ counterparts (around $30\\mathrm{min}\\mathrm{,}$ , whereas the partial reoxidation of metallic Cu occurred progressively over 1 h (Fig. 4d and Supplementary Fig. 45). \n\nGiven that all three types of Cu NP ensembly (7, 10 and $18\\mathsf{n m}$ ) show complete conversion from partially/fully oxidized pristine NPs to fully metallic Cu nanograins (Supplementary Figs. 37, 45 and 46), the fraction of active Cu nanograins is defined as the relative fraction of the pristine Cu NP ensemble that can be converted to metallic Cu active sites under electrochemical potentials (Fig. 4f). This quantitative value was then correlated to the ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ performance of the different Cu NP ensembles (Fig. 4f,g and Supplementary Tables 1 and 2). The resulting structure–activity correlation suggests that a higher fraction of \n\n# Article \n\nactive Cu nanograins leads to higher $\\mathbf{C}_{2+}$ selectivity. In particular, the $7\\mathrm{{nmCuNP}}$ ensemble with $100\\%$ Cu nanograins shows a $\\mathbf{C}_{2+}$ selectivity sixfold higher than that of the $18\\mathsf{n m}\\mathsf{C u N P}$ ensemble, with only $32\\%\\mathrm{Cu}$ nanograins at $-0.8{\\mathsf{V}}.$ The activity and stability of these nanograins was also tested in a gas diffusion electrode (GDE) in which the ${7}{\\mathsf{n m C u N P}}$ ensemble showed a higher $\\mathbf{C}_{2+}$ faradaic efficiency of $(-57\\%)$ at a much higher current density of $300{\\mathrm{mA}}\\mathrm{cm}^{-2}$ relative to the H-cell $(\\sim44\\%)$ at $15\\mathsf{m A c m}^{-2}$ (Supplementary Table 3). This demonstrates that $7\\mathsf{n m}\\mathsf{C u}$ NP-derived nanograins can also perform under industrially relevant conditions. \n\nFurther EXAFS analysis of the Cu NP ensembles provides additional details on their active structure (Fig. 4e and Supplementary Figs. 47–50). The scattering amplitude of the $\\mathbf{\\mathop{Cu-Cu}}$ peak for $7\\mathsf{n m}$ Cu NPs after 1 h of electroreduction was markedly lower than that of the standard Cu foil (Fig. 4e). Specifically, EXAFS fitting of the nanocatalyst after 1 h of ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ yielded an average nearest Cu–Cu coordination number (CN) of approximately 8, suggesting the presence of undercoordinated Cu sites (Supplementary Fig. 50). Eventually, after 4 h of electroreduction the $\\mathtt{C u-C u C N}$ approached a steady-state value of 12, comparable to that of Cu foil. Such an increase probably resulted from the continuous aggregation/coalescence of smaller Cu nanograins into fully grown Cu nanograins $(50-100\\mathrm{nm})$ ), with a negligible contribution from undercoordinated surface Cu sites37 (Supplementary Fig. 47). We hypothesize that whereas surface and bulk Cu become spectroscopically indistinguishable, because EXAFS is more sensitive to bulk than surface, undercoordinated sites are still present within the steady-state structure of the Cu nanocatalysts. This is corroborated by Pb UPD measurements indicating the presence of stronger binding sites formed on the 7 nm Cu NP ensemble (Supplementary Fig. 29). \n\nAlthough our EXAFS results suggest that the slow structural change in the NP ensemble would lead to variation in nanocatalyst catalytic activity, we note that only the signal obtained after 4 h is associated with the catalyst steady-state structure. Such slow kinetics result from the operando X-ray cell configuration and are otherwise much faster in the H-cell, as demonstrated by ${\\bf C O}_{2}{\\bf R R}$ activity becoming stabilized within 20 min and maintained for 4 h and beyond (Supplementary Fig. 51). We further narrow down the time frame when the Cu NP ensemble structural transformation leads to the formation of C–C coupling active sites with operando differential electrochemical mass spectrometry (DEMS) measurements at high temporal resolution, enabled by a dual thin-layer flow cell38. Specifically, $\\mathbf{C}_{2}\\mathbf{H}_{4}$ production reaches a steady state within the first 2.5 s in a DEMS flow-cell configuration, which is sufficiently fast compared with the time of around 20 min necessary to reach the steady-state structure and $\\mathbf{C}_{2}\\mathbf{H}_{4}$ production in an H-cell (Supplementary Fig. 52). The early-stage $\\mathbf{C}_{2+}$ production demonstrated by DEMS ties in with the formation of Cu nanograins observed within the first few seconds under applied potentials in the EC-STEM cell. Meanwhile, the steady-state structure identified by operando XAS can be correlated to steady-state activity measured in the H-cell (Supplementary Fig. 51). Overall, we can chronologically establish a structure–activity correlation that confirms the catalytic significance of undercoordinated sites supported on Cu nanograins relevant to $\\mathbf{C}_{2+}$ production. \n\nIn summary, this correlated operando structural studies with electron of the electroreduction/reoxidation life cycle of Cu nanocatalysts. Metallic Cu nanograins, rich in grain boundaries, support a high density of active undercoordinated sites that enhances the $\\mathbf{C}_{2+}$ selectivity of the ${7}{\\mathsf{n m C u N P}}$ ensemble. This study represents a milestone towards spatially resolving the complex nature of active Cu sites for ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ . Further statistical analysis of grain boundary density13,39, grain–grain distance40 and relative grain orientations24 will provide additional insights on which structural factors of Cu nanograins are beneficial to $\\mathbf{C}_{2+}$ formation. Inspired by the active formation of Cu nanograins via rapid NP evolution, various approaches can be devised to utilize such structural transformation to generate nanocatalysts with higher $\\mathbf{C}_{2+}$ intrinsic activity. For instance, smaller nanoparticles, clusters or molecular complexes can be used as smaller building blocks to generate a higher density of nanograin boundaries supporting undercoordinated active Cu sites. As proof of concept, a smaller-sized Cu NP ensemble (about $5\\mathsf{n m}^{\\prime}$ ) was synthesized and demonstrated markedly higher $\\mathbf{C}_{2+}$ selectivity $(55\\%)$ at lower Cu mass loading relative to the 7 nm counterpart $(44\\%)$ (Supplementary Note, Supplementary Figs. 53–57, Supplementary Video 7 and Supplementary Table 4). We anticipate that correlation of operando structural studies with electron and X-ray probes and additional molecular-level spectroscopical methods will be necessary to unravel which intermediates bind and undergo $\\mathsf{C}^{\\mathrm{-}\\mathrm{{C}}}$ coupling on the active sites supported on those nanograin boundaries. This study emphasizes the importance and prospects of using correlative operando methods in contributing to the rational design of future nanoscale electrocatalysts. \n\n# Online content \n\nAny methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-022-05540-0. \n\n1. Ross, M. B. et al. Designing materials for electrochemical carbon dioxide recycling. Nat. Catal. 2, 648–658 (2019). \n2. Birdja, Y. Y. et al. Advances and challenges in understanding the electrocatalytic conversion of carbon dioxide to fuels. Nat. Energy 4, 732–745 (2017). \n3. Yang, Y. et al. Operando methods in electrocatalysis. ACS Catal. 11, 1136–1178 (2021). \n4. Mefford, J. T. et al. Correlative operando microscopy of oxygen evolution electrocatalysts. Nature 593, 67–73 (2021). \n5. Vavra, J., Shen, T. H., Stoian, D., Tileli, V. & Buonsanti, R. Real-time monitoring reveals dissolution/redeposition mechanism in copper nanocatalysts during the initial stages of the $\\mathsf{C O}_{2}$ reduction reaction. Angew. Chem. Int. Ed. Engl. 60, 1347–1354 (2021). \n6. Hahn, C. et al. Engineering Cu surfaces for the electrocatalytic conversion of ${\\mathsf{C O}}_{2};$ : controlling selectivity toward oxygenates and hydrocarbons. Proc. Natl Acad. Sci. USA 114, 5918–5923 (2017). \n7. Li, C. W., Ciston, J. & Kanan, M. W. Electroreduction of carbon monoxide to liquid fuel on oxide-derived nanocrystalline copper. Nature 508, 504–507 (2014). \n8. Arán-Ais, R. M., Scholten, F., Kunze, S., Rizo, R. & Roldan Cuenya, B. The role of in situ generated morphological motifs and $\\mathsf{C u(i)}$ species in $\\mathsf{C}_{2+}$ product selectivity during $\\mathsf{C O}_{2}$ pulsed electroreduction. Nat. Energy 5, 317–325 (2020). \n9. Eilert, A. et al. Subsurface oxygen in oxide-derived copper electrocatalysts for carbon dioxide reduction. J. Phys. Chem. Lett. 8, 285–290 (2017). \n10. Chang, C.-J. et al. Dynamic reoxidation/reduction-driven atomic interdiffusion for highly selective $\\mathsf{C O}_{2}$ reduction toward methane. J. Am. Chem. Soc. 142, 12119–12132 (2020). \n11. Kimura, K. W. et al. Selective electrochemical $\\mathsf{C O}_{2}$ reduction during pulsed potential stems from dynamic interface. ACS Catal. 10, 8632–8639 (2020). \n12. Li, J. et al. Copper adparticle enabled selective electrosynthesis of n-propanol. Nat. Commun. 9, 4614 (2018). \n13. Lum, Y. & Ager, J. W. Stability of residual oxides in oxide‐derived copper catalysts for electrochemical $\\mathsf{C O}_{2}$ reduction investigated with $^{18}\\mathrm{O}$ labeling. Angew. Chem. Int. Ed. Engl. 57, 551–554 (2018). \n14.\t Fields, M., Hong, X., Nørskov, J. K. & Chan, K. Role of subsurface oxygen on Cu surfaces for $\\mathsf{C O}_{2}$ electrochemical reduction. J. Phys. Chem. C 122, 16209–16215 (2018). \n15. Garza, A. J., Bell, A. T. & Head-Gordon, M. Is subsurface oxygen necessary for the electrochemical reduction of $\\mathsf{C O}_{2}$ on copper? J. Phys. Chem. Lett. 9, 601–606 (2018). \n16. Feng, X., Jiang, K., Fan, S. & Kanan, M. W. A direct grain-boundary-activity correlation for CO electroreduction on Cu nanoparticles. ACS Cent. Sci. 2, 169–174 (2016). \n17. Mariano, R. G., McKelvey, K., White, H. S. & Kanan, M. W. Selective increase in $\\mathsf{C O}_{2}$ electroreduction activity at grain-boundary surface terminations. Science 358, 1187–1192 (2017). \n18. Mariano, R. G. et al. Microstructural origin of locally enhanced $\\mathsf{C O}_{2}$ electroreduction activity on gold. Nat. Mater. 20, 1000–1006 (2021). \n19. Yang, Y. et al. Electrocatalysis in alkaline media and alkaline membrane-based energy technologies. Chem. Rev. 122, 6117–6321 (2022). \n20.\t Hung, L., Tsung, C.-K., Huang, W. & Yang, P. Room-temperature formation of hollow $\\mathsf{C u}_{2}\\mathsf{O}$ nanoparticles. Adv. Mater. 22, 1910–1914 (2010). \n21.\t Kim, D., Kley, C. S., Li, Y. & Yang, P. Copper nanoparticle ensembles for selective electroreduction of $\\mathsf{C O}_{2}$ to $\\mathsf C_{2}\\mathsf{-C}_{3}$ products. Proc. Natl Acad. Sci. USA 114, 10560–10565 (2017). \n22.\t Li, Y. et al. Electrochemically scrambled nanocrystals are catalytically active for $\\mathsf{C O}_{2}\\cdot$ tomulticarbons. Proc. Natl Acad. Sci. USA 117, 9194–9201 (2020). \n23.\t Holtz, M. E. et al. Nanoscale imaging of lithium ion distribution during in situ operation of battery electrode and electrolyte. Nano Lett. 14, 1453–1459 (2014). \n24.\t Yang, Y., Shao, Y.-T., Lu, X., Abruña, H. D. & Muller, D. A. Metal monolayers on command: underpotential deposition at nanocrystal surfaces: a quantitative operando electrochemical transmission electron microscopy study. ACS Energy Lett. 7, 1292–1297 (2022). \n25.\t Williamson, M., Tromp, R., Vereecken, P., Hull, R. & Ross, F. Dynamic microscopy of nanoscale cluster growth at the solid–liquid interface. Nat. Mater. 2, 532–536 (2003). \n26.\t Holtz, M. E., Yu, Y., Gao, J., Abruña, H. D. & Muller, D. A. In situ electron energy-loss spectroscopy in liquids. Microsc. Microanal. 19, 1027–1035 (2013). \n27.\t Yang, Y., Shao, Y.-T., Lu, X., Abruña, H. D. & Muller, D. A. Elucidating cathodic corrosion mechanisms with operando electrochemical transmission electron microscopy. J. Am. Chem. Soc. 144, 15698–15708 (2022). \n28.\t Serra-Maia, R. et al. Nanoscale chemical and structural analysis during in situ scanning/transmission electron microscopy in liquids. ACS Nano 15, 10228–10240 (2021). \n29.\t Chen, Z. et al. Electron ptychorgraphy achieves atomic-resolution limits set by lattice vibrations. Science 372, 826–831 (2021). \n30.\t Tate, M. W. et al. High dynamic range pixel array detector for scanning transmission electron microscopy. Microsc. Microanal. 22, 237–249 (2016). \n31.\t Ophus, C. Four-dimensional scanning transmission electron microscopy (4D-STEM): from scanning nanodiffraction to ptychography and beyond. Micro. Microanal. 25, 563–582 (2020). \n32.\t Zuo, J. M. & Tao, J. in Scanning Transmission Electron Microscopy (eds Pennycook, S. & Nellist, P.) Ch. 9 (Springer, 2011). \n33.\t Yu, S. et al. Nanoparticle assembly induced ligand interactions for enhanced electrocatalytic $\\mathsf{C O}_{2}$ conversion. J. Am. Chem. Soc. 143, 19919–19927 (2021). \n34.\t Yang, Y. et al. Operando resonant soft X-ray scattering studies of chemical environment and interparticle dynamics of Cu nanocatalysts for $\\mathsf{C O}_{2}$ electroreduction. J. Am. Chem. Soc. 144, 8927–8931 (2022). \n35.\t Glatzel, P. & Bergmann, U. High resolution 1s core hole X-ray spectroscopy in 3D transition metal complexes-electronic and structural information. Coord. Chem. Rev. 249, 65–95 (2005). \n36.\t Yang, Y. et al. In situ X-ray absorption spectroscopy of a synergistic Co-Mn oxide catalyst for the oxygen reduction reaction. J. Am. Chem. Soc. 141, 1463–1466 (2019). \n37.\t Reske, R., Mistry, H., Behafarid, F., Roldan Cuenya, B. & Strasser, P. Particle size effects in the catalytic electroreduction of $\\mathsf{C O}_{2}$ on Cu nanoparticles. J. Am. Chem. Soc. 136, 6978–6986 (2018). \n38.\t Zeng, R. et al. Methanol oxidation using ternary ordered intermetallic electrocatalysts: a DEMS study. ACS Catal. 10, 770–776 (2020). \n39.\t Cao, L. et al. Mechanistic insights for low-overpotential electroreduction of $\\mathsf{C O}_{2}$ to CO on copper nanowires. ACS Catal. 7, 8578–8587 (2017). \n40.\t Jeong, H. M. et al. Atomic-scale spacing between copper facets for the electrochemical reduction of carbon dioxide. Adv. Energy Mater. 10, 1903423 (2020). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nSpringer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2023 \n\n# Article Methods \n\n# Synthesis \n\nCopper NPs $(7\\mathsf{n m})$ were synthesized as previously reported by our group21. For larger nanoparticles, size was controlled by tuning the mole ratio of tetradecylphosphonic acid to copper(I) acetate (CuAc) precursors, in which higher ratios resulted in larger particles. Specifically, to synthesize 7, 10 and $18\\mathsf{n m N P s}$ , ratios of 0.5, 0.7 and 1.2, respectively, were used while maintaining the absolute concentration of CuAc (1 mmol). Synthesis of 5 nm Cu NPs was adapted from a previously reported hot-injection method41. Additional synthesis details can be found in Supplementary Information. \n\n# Electrochemical measurements in H-cells \n\nOne monolayer of densely packed 7 nm NPs was achieved with a mass loading of $68.9\\upmu\\mathrm{g}$ deposited on 1 cm2 carbon paper (Sigracet 29AA, Fuel Cell Store). The design of the H-cell used in this study was described in detail previously21,42. Electrochemical measurements were performed $\\mathsf{i n}0.1\\mathsf{M K H C O}_{3}$ at a ${\\mathsf{C O}}_{2}$ flow rate of $20\\mathsf{m l}\\mathsf{m i n}^{-1}$ using a Biologic potentiostat, with Cu NPs supported on carbon paper as the WE, $\\mathbf{Ag/AgCl}$ (3 M KCl) as the RE and Pt wire as the CE, the last of these separated from the WE by an anion exchange membrane (Selemion AMV). All faradaic efficiencies reported herein are normalized whereas those before normalization are in the range $90\\mathrm{-}100\\%$ . Pb UPD measurement was conducted in a solution of $\\boldsymbol{0.1\\mathsf{M N a C l O}_{4},10\\mathsf{m M H C l O}_{4}}$ and $3\\mathsf{m M}$ $\\mathsf{P b}(\\mathsf{I I})(\\mathsf{C l O}_{4})_{2}(\\mathsf{r e f.}^{43})$ . Additional details about GDE measurements can be found in Supplementary Information. \n\n# Operando EC-STEM and 4D-STEM measurements \n\nOperando EC-STEM imaging was performed in $\\mathbf{CO}_{2}$ -saturated 0.1 M ${\\mathsf{K H C O}}_{3}$ of regular liquid thickness $500\\mathsf{n m}$ or greater) in a Tecnai F-20 STEM. A Protochips Poseidon liquid-cell holder and Gamry potentiostat were used for electrochemical measurements in EC-STEM. Operando EC-STEM images were acquired at a speed of 4 s per frame $(1,024\\times1,024$ pixels with a dwell time of $3\\upmu\\mathrm{s}$ per pixel) at a beam dose of around $50\\mathrm{e}^{-}\\mathsf{n m}^{-2}$ per frame (dose rate of about $12.5\\mathrm{e}^{-}\\mathsf{n m}^{-2}\\mathsf{s}^{-1})$ . This low dose is critical to ensure the absence of beam-induced damage to reliably track electrochemical reactions. A beam dose control experiment was routinely performed before each dynamic video capture to ensure no evidence of beam damage. 4D-STEM experiments were performed using an EMPAD by recording a 2D diffraction pattern at each probe position, resulting in 4D datasets. 4D-STEM diffraction imaging was performed with a probe size of about 1.3 nm in full-width at half-maximum and $256\\times256$ pixels at a dose of approximately $2,000\\mathrm{e}^{-}\\mathsf{n m}^{-2}$ (dose rate of about $6\\mathsf{e}^{-}\\mathsf{n m}^{-2}\\mathsf{s}^{-1})$ . Additional details can be found in Supplementary Information. \n\n# Ex situ STEM and EELS measurement \n\nEx situ atomic-scale HAADF–STEM imaging and EELS were performed in a fifth-order, aberration-corrected STEM (Nion UltraSTEM) operated at $100\\mathrm{keV}$ with a semiconvergence angle of 30 mrad. EELS spectrum images were acquired with $0.25\\mathrm{eV}$ per channel energy dispersion in a Gatan spectrometer at a size of around 100–200 pixels and an acquisition time of 10–20 ms per pixel. Cu and O elemental maps were extracted using $\\mathsf{C u L}_{3,2}$ and O K edges from EELS spectrum images, and processed using principal component analysis and the linear combination of power law to subtract the background in ImageJ software. \n\n# Operando HERFD-XAS measurements \n\nCu K-edge XANES and EXAFS were acquired in HERFD mode at the PIPOXS beamline of the Cornell High Energy Synchrotron Source (CHESS) under ring conditions of $100\\mathrm{{mA}}$ at 6 GeV. Incident energy was selected using a cryogenically cooled Si(311) monochromator and focused using a pair of Rh-coated mirrors. HERFD-XAS selects one particular fluorescence decay channel, the Cu ${\\mathsf{K}}{\\mathsf{\\alpha}}_{1}$ emission line at 8,048 eV (refs. 36,37), by Si{444} single crystals in Rowland geometry. \n\nThe sample was placed at an angle of $45^{\\circ}$ relative to the incident beam and fluorescence was detected using a Pilatus 100K detector, enabling the isolation of decay transition from a single orbital with a much longer core hole lifetime. Given the energy–time uncertainty principle, this enables significantly enhanced energy resolution in the order of 1 eV relative to the typical 50–200 eV of a conventional solid-state fluorescence detector. The design of the customized X-ray cell can be found in our previous report37. Cu NP catalysts were deposited on carbon paper as the WE with the same Cu loading as H-cell measurements. The RE $(\\mathsf{A g/A g C l}$ (saturated KCl)) was placed (via a salt bridge) at the bottom of the cell to minimize iR drop during electrochemical testing. Additional details can be found in Supplementary Information. \n\n# Operando RSoXS measurements \n\nSoft X-ray measurements were performed in the same type of liquid-cell set-up (Protochips, Inc.) as the operando EC-STEM holder, with a liquid thickness of about $1\\upmu\\mathrm{m}$ . Soft X-ray data were collected at the Advanced Light Source beamline 11.0.1.2 with a back-illuminated Princeton PI-MTE CCD cooled to $-45^{\\circ}\\mathsf C.$ . Scattering patterns of 18 nm NPs were collected for 0.6 s to minimize soft X-ray beam damage. RSoXS data fitting was conducted using the software package Scatter44. \n\n# Operando DEMS measurements \n\nElectrochemical measurements were performed with an EG&G Model 173 potentiostat/galvanostat, an EG&G Model 175 universal programmer and a DEMS set-up. A monolayer of 7 nm NPs on a glassy carbon electrode (diameter, $1.0\\mathsf{c m}$ ) served as the working electrode, with a mass loading of $8.14\\upmu\\mathrm{g}\\mathrm{cm}^{-2}$ . Two Pt wires were used as dual counter electrodes to minimize iR drop. A Ag/AgCl (saturated KCl) was used as the reference electrode. DEMS measurements were performed in a dual thin-layer flow cell at a flow rate of $\\mathsf{I}0\\upmu\\mathsf{I}\\mathsf{s}^{-1}$ . A detailed description of the DEMS set-up can be found in our previous work38. \n\n# Data availability \n\nAll relevant data are available from the corresponding author on request. \n\n41.\t Mantella, V. et al. Polymer lamellae as reaction intermediates in the formation of copper nanospheres as evidenced by in situ X-ray studies. Angew. Int. Chem. Ed. Engl. 59, 11627–11633 (2020). \n42.\t Kim, D. et al. Selective $\\mathsf{C O}_{2}$ electrocatalysis at the pseudocapacitive nanoparticle/ ordered-ligand interlayer. Nat. Energy 5, 1032–1042 (2020). \n43.\t Sebastián-Pascual, P. & Escudero-Escribano, M. Surface characterization of copper electrocatalysts by lead underpotential deposition. J. Electroanal. Chem. 896, 115446 (2021). \n44.\t Förster, S., Apostol, L. & Bras, W. Scatter: software for the analysis of nano- and mesoscale small-angle scattering. J. Appl. Crystallogr. 43, 639–646 (2010). \n\nAcknowledgements This work was supported by the Director, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, & Biosciences Division of the US Department of Energy under contract nos. DE-AC02-05CH11231 and FWP CH030201 (Catalysis Research Program). Work at Cornell University (in particular, operando EC-STEM) was supported by the Center for Alkaline-Based Energy Solutions, an Energy Frontier Research Center programme supported by the US Department of Energy, under grant no. DE-SC0019445. This work made use of TEM facilities at the CCMR, which are supported through the National Science Foundation Materials Research Science and Engineering Center (NSF MRSEC) programme (no. DMR-1719875). This work also used TEM facilities at the Molecular Foundry, supported by the Office of Science, Office of Basic Energy Sciences of the US Department of Energy under contract no. DE-AC02-05CH11231. This research used resources of the Advanced Light Source, which is a DOE Office of Science User Facility under contract no. DE-AC02- 05CH11231. This work is based on research conducted at the Center for High-Energy X-ray Sciences (CHEXS), which is supported by the National Science Foundation under award DMR-1829070. We thank J. Grazul and M. Thomas at Cornell for TEM technical support, and R. Dhall and K. Bustillo at NCEM. We thank H. Celik and UC Berkeley’s NMR facility at the College of Chemistry (CoC-NMR) for spectroscopic assistance. Instruments in the CoC-NMR are supported in part by NIH S10OD024998. We thank Y. Li for the initial discussion on in situ TEM. We thank R. Page and S. McFall for X-ray cell fabrication at the machine shop of Cornell LASSP. Y.Y. acknowledges support from the Miller Research Fellowship. S.Y. acknowledges support from the Samsung Scholarship. J.J. and C.C. acknowledge support from the Suzhou Industrial Park Scholarship. \n\nAuthor contributions Y.Y., S.L. and S.Y. designed the project under the guidance of P.Y. and H.D.A. Y.Y. performed atomic-scale STEM–EELS and operando EC-STEM measurements. \n\nY.Y. performed operando 4D-STEM, with the help of Y.-T.S. and under the guidance of D.A.M. S.L. and I.R. synthesized Cu nanocatalysts and performed ${\\mathsf{C O}}_{2}{\\mathsf{R R}}$ performance measurements, with the help of M.V.F.G. and J.F. S.Y. performed X-ray diffraction analysis and H-cell measurements. I.R. performed GDE measurements. Y.Y. performed operando HERFD-XAS studies, with help from S.L., S.Y. and X.H. C.J.P. provided generous support for the operando HERFD set-up. Y.Y. performed operando RSoXS studies under the guidance of C.W., with help from J.J. and C.C. H.W. and Y.Y. performed operando DEMS measurements. J.J. and C.C. prepared the scheme. Y.Y., S.L. and S.Y. wrote the manuscript under the supervision of P.Y. All authors revised and approved the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-022-05540-0. \nCorrespondence and requests for materials should be addressed to Peidong Yang. Peer review information Nature thanks Dunfeng Gao and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. \n\n# Article \n\n![](images/b71a29984f2b8bf5bb1732c12fe0f3b8e10440051e3411dc6f44ac464ae19810.jpg) \nExtended Data Fig. 1 | Atomic-scale microstructures and chemical compositions of a family of Cu NP ensembles (7, 10, 18 nm). (a–b) HAADF-STEM image and EELS composite map of fresh 7 nm NPs with metallic Cu core (red) and \\~2 nm oxide shell (green), which were oxidized to ${\\tt C u}_{2}0$ NPs after brief air exposure (Supplementary Fig. 3). (c) STEM image of 1 $0\\mathrm{nm}\\mathsf{C u}@\\mathsf{C u}_{2}0$ NPs with \nmulti-domain Cu core close to the [110] zone axis surrounded by the $\\mathtt{C u}_{2}0$ shell with characteristic d-spacings of $\\mathrm{\\hat{C}u}_{2}($ O{111} (2.5 Å). (d) STEM-EELS composite map of $10\\mathsf{n m}\\mathsf{C u@C u_{2}O}$ NPs with \\~2 nm oxide shell. (e–f) STEM image of 18 nm $\\mathtt{C u@C u_{2}O}$ NPs and EELS composite map showing the \\~2 nm oxide shell. " + }, + { + "id": "10.1038_s41586-023-06735-9", + "DOI": "10.1038/s41586-023-06735-9", + "DOI Link": "http://dx.doi.org/10.1038/s41586-023-06735-9", + "Relative Dir Path": "mds/10.1038_s41586-023-06735-9", + "Article Title": "Scaling deep learning for materials discovery", + "Authors": "Merchant, A; Batzner, S; Schoenholz, SS; Aykol, M; Cheon, G; Cubuk, ED", + "Source Title": "NATURE", + "Abstract": "Novel functional materials enable fundamental breakthroughs across technological applications from clean energy to information processing1-11. From microchips to batteries and photovoltaics, discovery of inorganic crystals has been bottlenecked by expensive trial-and-error approaches. Concurrently, deep- learning models for language, vision and biology have showcased emergent predictive capabilities with increasing data and computation12-14. Here we show that graph networks trained at scale can reach unprecedented levels of generalization, improving the efficiency of materials discovery by an order of magnitude. Building on 48,000 stable crystals identified in continuing studies15-17, improved efficiency enables the discovery of 2.2 million structures below the current convex hull, many of which escaped previous human chemical intuition. Our work represents an order-of-magnitude expansion in stable materials known to humanity. Stable discoveries that are on the final convex hull will be made available to screen for technological applications, as we demonstrate for layered materials and solid-electrolyte candidates. Of the stable structures, 736 have already been independently experimentally realized. The scale and diversity of hundreds of millions of first-principles calculations also unlock modelling capabilities for downstream applications, leading in particular to highly accurate and robust learned interatomic potentials that can be used in condensed-phase molecular-dynamics simulations and high-fidelity zero-shot prediction of ionic conductivity.", + "Times Cited, WoS Core": 372, + "Times Cited, All Databases": 397, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:001169148800004", + "Markdown": "# Scaling deep learning for materials discovery \n\nhttps://doi.org/10.1038/s41586-023-06735-9 \n\nReceived: 8 May 2023 \n\nAccepted: 10 October 2023 \n\nPublished online: 29 November 2023 \n\nOpen access \n\n# Check for updates \n\nAmil Merchant1,3 ✉, Simon Batzner1,3, Samuel S. Schoenholz1,3, Muratahan Aykol1, Gowoon Cheon2 & Ekin Dogus Cubuk1,3 ✉ \n\nNovel functional materials enable fundamental breakthroughs across technological applications from clean energy to information processing1–11. From microchips to batteries and photovoltaics, discovery of inorganic crystals has been bottlenecked by expensive trial-and-error approaches. Concurrently, deep-learning models for language, vision and biology have showcased emergent predictive capabilities with increasing data and computation12–14. Here we show that graph networks trained at scale can reach unprecedented levels of generalization, improving the efficiency of materials discovery by an order of magnitude. Building on 48,000 stable crystals identified in continuing studies15–17, improved efficiency enables the discovery of 2.2 million structures below the current convex hull, many of which escaped previous human chemical intuition. Our work represents an order-of-magnitude expansion in stable materials known to humanity. Stable discoveries that are on the final convex hull will be made available to screen for technological applications, as we demonstrate for layered materials and solid-electrolyte candidates. Of the stable structures, 736 have already been independently experimentally realized. The scale and diversity of hundreds of millions of first-principles calculations also unlock modelling capabilities for downstream applications, leading in particular to highly accurate and robust learned interatomic potentials that can be used in condensed-phase moleculardynamics simulations and high-fidelity zero-shot prediction of ionic conductivity. \n\nThe discovery of energetically favourable inorganic crystals is of fundamental scientific and technological interest in solid-state chemistry. Experimental approaches over the decades have catalogued 20,000 computationally stable structures (out of a total of 200,000 entries) in the Inorganic Crystal Structure Database (ICSD)15,18. However, this strategy is impractical to scale owing to costs, throughput and synthesis complications19. Instead, computational approaches championed by the Materials Project (MP)16, the Open Quantum Materials Database (OQMD)17, AFLOWLIB20 and NOMAD21 have used first-principles calculations based on density functional theory (DFT) as approximations of physical energies. Combining ab initio calculations with simple substitutions has allowed researchers to improve to 48,000 computationally stable materials according to our own recalculations22–24 (see Methods). Although data-driven methods that aid in further materials discovery have been pursued, thus far, machine-learning techniques have been ineffective in estimating stability (decomposition energy) with respect to the convex hull of energies from competing phases25. \n\nIn this paper, we scale up machine learning for materials exploration through large-scale active learning, yielding the first models that accurately predict stability and, therefore, can guide materials discovery. Our approach relies on two pillars: first, we establish methods for generating diverse candidate structures, including new symmetry-aware partial substitutions (SAPS) and random structure search26. Second, we use state-of-the art graph neural networks (GNNs) that improve modelling of material properties given structure or composition. In a series of rounds, these graph networks for materials exploration (GNoME) are trained on available data and used to filter candidate structures. \n\nThe energy of the filtered candidates is computed using DFT, both verifying model predictions and serving as a data flywheel to train more robust models on larger datasets in the next round of active learning. \n\nThrough this iterative procedure, GNoME models have discovered more than 2.2 million structures stable with respect to previous work, in particular agglomerated datasets encompassing computational and experimental structures15–17,27. Given that discovered materials compete for stability, the updated convex hull consists of 381,000 new entries for a total of 421,000 stable crystals, representing an-order-of-magnitude expansion from all previous discoveries. Consistent with observations in other domains of machine learning28, we observe that our neural networks predictions improve as a power law with the amount of data. Final GNoME models accurately predict energies to 11 meV atom−1 and improve the precision of stable predictions (hit rate) to above $80\\%$ with structure and $33\\%$ per 100 trials with composition only, compared with $1\\%$ in previous work17. Moreover, these networks develop emergent out-of-distribution generalization. For example, GNoME enables accurate predictions of structures with $5+$ unique elements (despite omission from training), providing one of the first strategies to efficiently explore this chemical space. We validate findings by comparing predictions with experiments and higher-fidelity $\\mathsf{r}^{2}\\mathsf{S C A N}$ (ref. 29) computations. \n\nFinally, we demonstrate that the dataset produced in GNoME discovery unlocks new modelling capabilities for downstream applications. The structures and relaxation trajectories present a large and diverse dataset to enable training of learned, equivariant interatomic potentials30,31 with unprecedented accuracy and zero-shot generalization. \n\n![](images/bd17827d931df147160eacdd20f0c5a8dd4c8742fb899ac0995a4f6940e83f0a.jpg) \nFig. 1 | GNoME enables efficient discovery. a, A summary of the GNoME-based discovery shows how model-based filtration and DFT serve as a data flywheel to improve predictions. b, Exploration enabled by GNoME has led to 381,000 new stable materials, almost an order of magnitude larger than previous work. c, 736 structures have been independently experimentally verified, with six examples shown50–55. d, Improvements from graph network predictions enable \nefficient discovery in combinatorial regions of materials, for example, with six unique elements, even though the training set stopped at four unique elements. e, GNoME showcases emergent generalization when tested on out-of-domain inputs from random structure search, indicating progress towards a universal energy model. \n\nWe demonstrate the promise of these potentials for materials property prediction through the estimation of ionic conductivity from molecular-dynamics simulations. \n\n# Overview of generation and filtration \n\nThe space of possible materials is far too large to sample in an unbiased manner. Without a reliable model to cheaply approximate the energy of candidates, researchers guided searches by restricting generation with chemical intuition, accomplished by substituting similar ions or enumerating prototypes22. Although improving search efficiency17,27, this strategy fundamentally limited how diverse candidates could be. By guiding searches with neural networks, we are able to use diversified methods for generating candidates and perform a broader exploration of crystal space without sacrificing efficiency. \n\nTo generate and filter candidates, we use two frameworks, which are visualized in Fig. 1a. First, structural candidates are generated by modifications of available crystals. However, we strongly augment the set of substitutions by adjusting ionic substitution probabilities to give priority to discovery and use newly proposed symmetry aware partial substitutions (SAPS) to efficiently enable incomplete replacements32. This expansion results in more than $10^{9}$ candidates over the course of active learning; the resulting structures are filtered by means of GNoME using volume-based test-time augmentation and uncertainty quantification through deep ensembles33. Finally, structures are clustered and polymorphs are ranked for evaluation with DFT (see Methods). In the second framework, compositional models predict stability without structural information. Inputs are reduced chemical formulas. Generation by means of oxidation-state balancing is often too strict (for example, neglecting $\\mathsf{L i}_{15}\\mathsf{S i}_{4},$ . Using relaxed constraints (see Methods), we filter compositions using GNoME and initialize 100 random structures for evaluation through ab initio random structure searching (AIRSS)26. In both frameworks, models provide a prediction of energy and a threshold is chosen on the basis of the relative stability (decomposition energy) with respect to competing phases. Evaluation is performed through DFT computations in the Vienna Ab initio Simulation Package (VASP)34 and we measure both the number of stable materials discovered as well as the precision of predicted stable materials (hit rate) in comparison with the Materials Project16. \n\n# GNoME \n\nAll GNoME models are GNNs that predict the total energy of a crystal. Inputs are converted to a graph through a one-hot embedding of the elements. We follow the message-passing formulation35,36, in which aggregate projections are shallow multilayer perceptrons (MLPs) with swish nonlinearities. For structural models, we find it important to normalize messages from edges to nodes by the average adjacency of atoms across the entire dataset. Initial models are trained on a snapshot of the Materials Project from 2018 of approximately 69,000 materials. Previous work benchmarked this task at a mean absolute error (MAE) of 28 meV atom−1 (ref. 37); however, we find that the improved networks achieve a MAE of 21 meV atom−1. We fix this promising architecture (see Methods) and focus on scaling in the rest of this paper. \n\n![](images/04aa0fde75c2d6afc24bdba5833f03dfc3ee22add666809f5079a8b3036f6238.jpg) \n\nFig. 2 | Summaries of discovered stable crystals. a, GNoME enables efficient than previous catalogues. c, Discovered stable crystals correspond to 45,500 discovery in the combinatorial spaces of $^{\\cdot}4^{+}$ unique elements that can be difficult novel prototypes as measured by XtalFinder (ref. 39). d, Validation by $\\mathsf{r}^{2}\\mathsf{S C A N}$ for human experts. b, Phase-separation energies (energy to the convex hull) for shows that $84\\%$ of discovered binary and ternary crystals retain negative phase discovered quaternaries showcase similar patterns but larger absolute numbers separations with more accurate functionals. \n\n# Active learning \n\nA core step in our framework for accelerating materials discovery is active learning. In both structural and compositional frameworks, candidate structures filtered using GNoME are evaluated using DFT calculations with standardized settings from the Materials Project. Resulting energies of relaxed structures not only verify the stability of crystal structures but are also incorporated into the iterative active-learning workflow as further training data and structures for candidate generation. Whereas the hit rate for both structural and compositional frameworks start at less than $6\\%$ and $3\\%$ , respectively, performance improves steadily through six rounds of active learning. Final ensembles of GNoME models improve to a prediction error of 11 meV atom−1 on relaxed structures and hit rates of greater than $80\\%$ and $33\\%$ , respectively, clearly showing the benefits of scale. An analysis of final GNoME hit rates is provided in Fig. 1d. \n\n# Scaling laws and generalization \n\nThe test loss performance of GNoME models exhibit improvement as a power law with further data. These results are in line with neural scaling laws in deep learning28,38 and suggest that further discovery efforts could continue to improve generalization. Emphatically, unlike the case of language or vision, in materials science, we can continue to generate data and discover stable crystals, which can be reused to continue scaling up the model. We also demonstrate emergent generalization to out-of-distribution tasks by testing structural models trained on data originating from substitutions on crystals arising from random search26 in Fig. 1e. These examples are often high-energy local minima and out of distribution compared with data generated by our structural pipeline (which, by virtue of substitutions, contains structures near their minima). Nonetheless, we observe clear improvement with scale. These results indicate that final GNoME models are a substantial step towards providing the community with a universal energy predictor, capable of handling diverse materials structures through deep learning. \n\n# Discovered stable crystals \n\nUsing the described process of scaling deep learning for materials exploration, we increase the number of known stable crystals by almost an order of magnitude. In particular, GNoME models found 2.2 million crystal structures stable with respect to the Materials Project. Of these, 381,000 entries live on the updated convex hull as newly discovered materials. \n\nConsistent with other literature on structure prediction, the GNoME materials could be bumped off the convex hull by future discoveries, similar to how GNoME displaces at least 5,000 ‘stable’ materials from the Materials Project and the OQMD. See Supplementary Note 1 for discussion on improving structures of already-discovered compositions. Nevertheless, Figs. 1 and 2 provide a summary of the stable materials, with Fig. 1b focusing on the growth over time. We see substantial gains in the number of structures with more than four unique elements in Fig. 2a. This is particularly promising because these materials have proved difficult for previous discovery efforts27. Our scaled GNoME models overcome this obstacle and enable efficient discovery in combinatorially large regions. \n\nClustering by means of prototype analysis39 supports the diversity of discovered crystals with GNoME, leading to more than 45,500 novel prototypes in Fig. 2c (a 5.6 times increase from 8,000 of the Materials Project), which could not have arisen from full substitutions or prototype enumeration. Finally, in Fig. 2b, we compare the phase-separation energy (also referred to as the decomposition enthalpy) of discovered quaternaries with those from the Materials Project to measure the relative distance to the convex hull of all other competing phases. The similarities in distribution suggest that the found materials are meaningfully stable with respect to competing phases and not just ‘filling in the convex hull.’ Further analyses of materials near to (but not on) the updated convex hull is given in Supplementary Note 3. \n\n# Validation through experimental matching and r2SCAN \n\nAll candidates for GNoME are derived from snapshots of databases made in March 2021, including the Materials Project and the OQMD. Concurrent to our discovery efforts, researchers have continued to experimentally create new crystals, providing a way to validate GNoME findings. Of the experimental structures aggregated in the ICSD, 736 match structures that were independently obtained through GNoME. Six of the experimentally matched structures are presented in Fig. 1c and further details of the experimental matches are provided in Supplementary Note 1. Similarly, of the 3,182 compositions added to the Materials Project since the snapshot, 2,202 are available in the GNoME database and $91\\%$ match on structure. A manual check of ‘newly’ discovered crystals supported the findings, with details in Supplementary Note 4. \n\nWe also validate predictions to ensure that model-based exploration did not overfit simulation parameters. We focus on the choice of functional. Standard projector augmented wave (PAW)-Perdew– Burke–Ernzerhof (PBE) potentials provided a speed–accuracy trade-off suited for large-scale discovery40,41, but the r2SCAN functional provides a more accurate meta-generalized gradient approximation29,42,43. $84\\%$ of the discovered binaries and ternary materials also present negative phase-separation energies (as visualized in Fig. 2d, comparable with a $90\\%$ ratio in the Materials Project but operating at a larger scale). $86.8\\%$ of tested quaternaries also remain stable on the $\\mathsf{r}^{2}\\mathsf{S C A N}$ convex hull. The discrepancies between PBE and $\\mathsf{r}^{2}\\mathsf{S C A N}$ energies are further analysed in Supplementary Note 2. \n\n# Composition families of interest \n\nWe highlight the benefits of a catalogue of stable materials an order of magnitude larger than previous work. When searching for a material with certain desirable properties, researchers often filter such catalogues, as computational stability is often linked with experimental realizability. We perform similar analyses for three applications. First, layered materials are promising systems for electronics and energy storage44. Methods from previous studies45 suggest that approximately 1,000 layered materials are stable compared with the Materials Project, whereas this number increases to about 52,000 with GNoME-based discoveries. Similarly, following a holistic screening approach with filters such as exclusion of transition metals or by lithium fraction, we find 528 promising Li-ion conductors among GNoME discoveries, a 25 times increase compared with the original study46. Finally, Li/Mn transition-metal oxides are a promising family to replace $\\mathsf{L i C o O}_{2}$ in rechargeable batteries25 and GNoME has discovered an extra 15 candidates stable relative to the Materials Project compared with the original nine. \n\n# Scaling up learned interatomic potentials \n\nThe process of discovery of stable crystals also provides a data source beyond stable materials. In particular, the ionic relaxations involve computation of first-principles energies and forces for a diverse set of materials structures. This generates a dataset of unprecedented diversity and scale, which we explore to pretrain a general-purpose machine-learning interatomic potential (MLIP) for bulk solids. MLIPs have become a promising tool to accelerate the simulation of materials by learning the energies and forces of reference structures computed at first-principles accuracy30,47–49. Existing efforts typically train models per material, with data often sampled from ab initio molecular dynamics (AIMD). This markedly limits their general applicability and adoption, requiring expensive data collection and training a new potential from scratch for each system. By making use of the GNoME dataset of first-principles calculations from diverse structural relaxations, we demonstrate that large-scale pretraining of MLIPs enables models that show unprecedented zero-shot accuracy and can be used to discover superionic conductors, without training on any material-specific data. \n\n# Zero-shot scaling and generalization \n\nWe scale pretraining of a NequIP potential30 on data sampled from ionic relaxations. Increasing the pretraining dataset, we observe consistent power-law improvements in accuracy (see Fig. 3a,b). Despite only being trained on ionic relaxations and not on molecular-dynamics data, the pretrained GNoME potential shows remarkable accuracy when evaluated on downstream data sampled from the new distribution of AIMD in a zero-shot manner, that is, in which no training data originate from AIMD simulations (see Fig. 3). Notably, this includes unseen compositions, melted structures and structures including vacancies, all of which are not included in our training set (see Supplementary Note 6.4). In particular, we find that the scale of the GNoME dataset allows it to outperform existing general-purpose potentials (see Fig. 3d) and makes the pretrained potential competitive with models trained explicitly on hundreds of samples from the target data distributions (see Supplementary Note 6.4). We observe particularly pronounced improvements in the transferability of MLIPs, one of the most pressing shortcomings of MLIPs. To assess the transferability of the potentials, we test their performance under distribution shift: we train two types of NequIP potential on structures sampled from AIMD at $T{=}400\\mathsf{K}$ , one in which the network is trained from randomly initialized weights and the other in which we fine-tune from a pretrained GNoME checkpoint. We then measure the performance of both potentials on data sampled from AIMD at $T{=}1{,}000\\kappa$ (see Fig. 3c), out of distribution with respective to the 400-K data. The potential pretrained on GNoME data shows systematic and strong improvements in transferability over the potential trained from scratch, even when training is performed on more than 1,000 structures. The zero-shot GNoME potential, not fine-tuned on any data from this composition, outperforms even a state-of-the-art NequIP model trained on hundreds of structures. \n\n# Screening solid-state ionic conductors \n\nSolid electrolytes are a core component of solid-state batteries, promising higher energy density and safety than liquid electrolytes, but suffer from lower ionic conductivities at present. In the search for novel electrolyte materials, AIMD allows for the prediction of ionic conductivities from first principles. However, owing to the poor scaling of DFT with the number of electrons, routine simulations are limited to hundreds of picoseconds, hundreds of atoms and, most importantly, small compositional search spaces. Here we show that the GNOME potentials show high robustness in this out-of-distribution, zero-shot setting and generalizes to high temperatures, which allows them to serve as a tool for high-throughput discovery of novel solid-state electrolytes. We use GNoME potentials pretrained on datasets of increasing size in molecular-dynamics simulations on 623 never-before-seen compositions. Figure 3a shows the ability of the pretrained GNoME potentials to classify unseen compositions as superionic conductors in comparison with AIMD. \n\nWhen scaled to the GNoME dataset—much larger than existing approaches—we find that deep learning unlocks previously impossible capabilities for building transferable interatomic potentials for \n\n# Article \n\n![](images/c77ad6619ed73e141772ed72e85459bbf800c11c5eb896bfa901ee6507741ff1.jpg) \nFig. 3 | Scaling learned interatomic potentials. a, Classification of whether a material is a superionic conductor as predicted by GNoME-driven simulations in comparison with AIMD, tested on 623 unseen compositions. The classification error improves as a power law with training set size. b, Zero-shot force error as a function of training set size for the unseen material $\\mathsf{K}_{24}\\mathsf{L i}_{16}\\mathsf{P}_{24}\\mathsf{S}\\mathsf{n}_{8}$ . c, Robustness under distribution shift, showing the MAE in forces on the example material $\\mathbf{Ba}_{8}\\mathbf{Li}_{16}\\mathbf{Se}_{32}\\mathbf{Si}_{8}$ . A GNoME-pretrained and a randomly initialized potential are \ntrained on data of various sizes sampled at $T{=}400\\kappa$ and evaluated on data sampled at $T{=}1{,}000\\kappa$ . The zero-shot GNoME potential outperforms state-ofthe-art models trained from scratch on hundreds of structures. d, Comparison of zero-shot force errors of three different pretrained, general-purpose potentials for bulk systems on the test set of ref. 56. Note that the composition Ni is not present in the GNoME pretraining data. RMSE, root-mean-square error. \n\ninorganic bulk crystals and allows for high-accuracy, zero-shot prediction of materials properties at scale. \n\n# Conclusion \n\nWe show that GNNs trained on a large and diverse set of first-principles calculations can enable the efficient discovery of inorganic materials, increasing the number of stable crystals by more than an order of magnitude. Associated datasets empower machine-learned interatomic potentials, giving accurate and robust molecular-dynamics simulations out of the box on unseen bulk materials. Our findings raise interesting questions about the capabilities of deep-learning systems in the natural sciences: the application of machine-learning methods for scientific discovery has traditionally suffered from the fundamental challenge that learning algorithms work under the assumption of identically distributed data at train and test times, but discovery is inherently an out-of-distribution effort. Our results on large-scale learning provide a potential step to move past this dilemma, by demonstrating that GNoME models exhibit emergent out-of-distribution capabilities at scale. This includes discovery in unseen chemical spaces (for example, with more than four different elements), as well as on new downstream tasks (for example, predicting kinetic properties). \n\nGNoME models have already found 2.2 million stable crystals with respect to previous work and enabled previously impossible modelling capabilities for materials scientists. Some open problems remain for the transition of findings in applications, including a greater understanding of phase transitions through competing polymorphs, dynamic stability arising from vibrational profiles and configurational entropies and, ultimately, synthesizability. Nevertheless, we see pretrained, general-purpose GNoME models being used as powerful tools across a diverse range of applications to fundamentally accelerate materials discovery. \n\n# Online content \n\nAny methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-023-06735-9. \n\n15.\t Hellenbrandt, M. The Inorganic Crystal Structure Database (ICSD)—present and future. Crystallogr. Rev. 10, 17–22 (2004). \n16. Jain, A. et al. Commentary: The Materials Project: a materials genome approach to accelerating materials innovation. APL Mater. 1, 011002 (2013). \n17. Saal, J. E., Kirklin, S., Aykol, M., Meredig, B. & Wolverton, C. Materials design and discovery with high-throughput density functional theory: the Open Quantum Materials Database (OQMD). JOM 65, 1501–1509 (2013). \n18. Belsky, A., Hellenbrandt, M., Karen, V. L. & Luksch, P. New developments in the Inorganic Crystal Structure Database (ICSD): accessibility in support of materials research and design. Acta Crystallogr. B Struct. Sci. 58, 364–369 (2002). \n19.\t Aykol, M., Montoya, J. H. & Hummelshøj, J. Rational solid-state synthesis routes for inorganic materials. J. Am. Chem. Soc. 143, 9244–9259 (2021). \n20.\t Curtarolo, S. et al. AFLOWLIB.ORG: a distributed materials properties repository from high-throughput ab initio calculations. Comput. Mater. Sci. 58, 227–235 (2012). \n21.\t Draxl, C. & Scheffler, M. The NOMAD laboratory: from data sharing to artificial intelligence. J. Phys. Mater. 2, 036001 (2019). \n22. Hautier, G., Fischer, C., Ehrlacher, V., Jain, A. & Ceder, G. Data mined ionic substitutions for the discovery of new compounds. Inorg. Chem. 50, 656–663 (2011). \n23.\t Ong, S. P. et al. Python Materials Genomics (pymatgen): a robust, open-source Python library for materials analysis. Comput. Mater. Sci. 68, 314–319 (2013). \n24.\t Aykol, M. et al. Network analysis of synthesizable materials discovery. Nat. Commun. 10, 2018 (2019). \n25. Bartel, C. J. et al. A critical examination of compound stability predictions from machinelearned formation energies. npj Comput. Mater. 6, 97 (2020). \n26.\t Pickard, C. J. & Needs, R. Ab initio random structure searching. J. Phys. Condens. Matter 23, 053201 (2011). \n27.\t Wang, H.-C., Botti, S. & Marques, M. A. Predicting stable crystalline compounds using chemical similarity. npj Comput. Mater. 7, 12 (2021). \n28.\t Hestness, J. et al. Deep learning scaling is predictable, empirically. Preprint at https:// arxiv.org/abs/1712.00409 (2017). \n29.\t Furness, J. W., Kaplan, A. D., Ning, J., Perdew, J. P. & Sun, J. Accurate and numerically efficient r2SCAN meta-generalized gradient approximation. J. Phys. Chem. Lett. 11, 8208–8215 (2020). \n30.\t Batzner, S. et al. E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials. Nat. Commun. 13, 2453 (2022). \n31. Thomas, N. et al. Tensor field networks: rotation- and translation-equivariant neural networks for 3D point clouds. Preprint at https://arxiv.org/abs/1802.08219 (2018). \n32. Togo, A. & Tanaka, I. Spglib: a software library for crystal symmetry search. Preprint at https://arxiv.org/abs/1808.01590 (2018). \n33. Behler, J. Constructing high-dimensional neural network potentials: a tutorial review. Int. J. Quantum Chem. 115, 1032–1050 (2015). \n34. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a pla sis set. Phys. Rev. B 54, 11169 (1996). \n35. Battaglia, . W. et al. Relational inductive biases, deep learning, and graph networks. Preprint at s://arxiv.org/abs/1806.01261 (2018). \n36. Gilmer, J., , S. S., Riley, P. F., Vinyals, O. & Dahl, G. E. Neural message passing for quantum y. Proc. Mach. Learn. Res. 70, 1263–1272 (2017). \n37. Chen, C., Ye, W., Zuo, Y., Zheng, C. & Ong, S. P. Graph networks as a universal machine learning framework for molecules and crystals. Chem. Mater. 31, 3564–3572 (2019). \n38.\t Kaplan, J. et al. Scaling laws for neural language models. Preprint at https://arxiv.org/ abs/2001.08361 (2020). \n39.\t Hicks, D. et al. AFLOW-XtalFinder: a reliable choice to identify crystalline prototypes. npj Comput. Mater. 7, 30 (2021). \n40.\t Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953 (1994). \n41.\t Perdew, J. P., Ernzerhof, M. & Burke, K. Rationale for mixing exact exchange with density functional approximations. J. Chem. Phys. 105, 9982–9985 (1996). \n42.\t Kitchaev, D. A. et al. Energetics of $\\mathsf{M n O}_{2}$ polymorphs in density functional theory. Phys. Rev. B 93, 045132 (2016). \n43.\t Kingsbury, R. et al. Performance comparison of $\\mathsf{r}^{2}\\mathsf{S C A N}$ and SCAN metaGGA density functionals for solid materials via an automated, high-throughput computational workflow. Phys. Rev. Mater. 6, 013801 (2022). \n44.\t Bassman Oftelie, L. et al. Active learning for accelerated design of layered materials. npj Comput. Mater. 4, 74 (2018). \n45.\t Cheon, G. et al. Data mining for new two- and one-dimensional weakly bonded solids and lattice-commensurate heterostructures. Nano Lett. 17, 1915–1923 (2017). \n46.\t Sendek, A. D. et al. Holistic computational structure screening of more than 12000 candidates for solid lithium-ion conductor materials. Energy Environ. Sci. 10, 306–320 (2017). \n47.\t Behler, J. & Parrinello, M. Generalized neural-network representation of high-dimensional potential-energy surfaces. Phys. Rev. Lett. 98, 146401 (2007). \n48.\t Bartók, A. P., Payne, M. C., Kondor, R. & Csányi, G. Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons. Phys. Rev. Lett. 104, 136403 (2010). \n49.\t Lot, R., Pellegrini, F., Shaidu, Y. & Küçükbenli, E. PANNA: properties from artificial neural network architectures. Comput. Phys. Commun. 256, 107402 (2020). \n50.\t Zhou, Y., Qiu, Y., Mishra, V. & Mar, A. Lost horses on the frontier: ${\\mathsf{K}}_{2}{\\mathsf{B i C l}}_{5}$ and ${\\sf K}_{3}\\mathsf{B i}_{2}\\mathsf{B r}_{9}$ J. Solid State Chem. 304, 122621 (2021). \n51.\t Abudurusuli, A. et al. $\\mathsf{L i}_{4}\\mathsf{M g G e}_{2}\\mathsf{S}_{7};$ : the first alkali and alkaline-earth diamond-like infrared nonlinear optical material with exceptional large band gap. Angew. Chem. Int. Ed. 60, 24131–24136 (2021). \n52.\t Ruan, B.-B., Yang, Q.-S., Zhou, M.-H., Chen, G.-F. & Ren, Z.-A. Superconductivity in a new $T_{2}$ -phase ${\\mathsf{M o}}_{5}{\\mathsf{G e B}}_{2}$ J. Alloys Compd. 868, 159230 (2021). \n53.\t Guo, Z. et al. Local distortions and metal–semiconductor–metal transition in quasi-onedimensional nanowire compounds ${\\sf A V}_{3}{\\sf Q}_{3}{\\sf O}_{\\delta}$ ( $\\mathsf{A}=\\mathsf{K},$ Rb, Cs and $\\mathsf{Q}=\\mathsf{S}\\mathsf{e}$ , Te). Chem. Mater. 33, 2611–2623 (2021). \n54.\t Deng, A. et al. Novel narrow-band blue light-emitting phosphor of Eu2+-activated silicate used for WLEDs. Dalton Trans. 50, 16377–16385 (2021). \n55.\t Zhak, O., Köhler, J., Karychort, O. & Babizhetskyy, V. New ternary phosphides $R E_{5}\\mathsf{P d}_{9}\\mathsf{P}_{7}$ (RE=Tm, Lu): synthesis, crystal and electronic structure. Z. Anorg. Allg. Chem. 648, e202200024 (2022). \n56.\t Zuo, Y. et al. Performance and cost assessment of machine learning interatomic potentials. J. Phys. Chem. A 124, 731–745 (2020). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate \n\ncredit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 \n\n# Article Methods \n\n# Datasets and candidate generation \n\nSnapshots of available datasets. GNoME discoveries aim to extend the catalogues of known stable crystals. In particular, we build off previous work by the Materials Project16, the OQMD17, Wang, Botti and Marques (WBM)27 and the ${\\mathsf{I C S D}}^{15}$ . For reproducibility, GNoME-based discoveries use snapshots of the two datasets saved at a fixed point in time. We use the data from the Materials Project as of March 2021 and the OQMD as of June 2021. These structures are used as the basis for all discovery including via SAPS, yielding the catalogue of stable crystals as a result of GNoME. Further updates and incorporation of discoveries by these two groups could yield an even greater number of crystal discoveries. \n\nFor a revised comparison, another snapshot of the Materials Project, the OQMD and WBM was taken in July 2023. Approximately 216,000 DFT calculations were performed at consistent settings and used to compare the rate of GNoME discoveries versus the rate of discoveries by concurrent research efforts. From 2021 to 2023, the number of stable crystals external to GNoME expanded from 35,000 to 48,000, relatively small in comparison with the 381,000 new stable crystal structures available on the convex hull presented in this paper. \n\nSubstitution patterns. Structural substitution patterns are based on data-mined probabilities from ref. 22. That work introduced a probabilistic model for assessing the likelihood for ionic species substitution within a single crystal structure. In particular, the probability of substitution is calculated as a binary feature model such that $p(X,X^{\\prime})\\approx{\\frac{\\exp\\sum_{i}\\lambda_{i}f_{i}^{(n)}(X,X^{\\prime})}{Z}},$ , in which X and $\\chi^{\\prime}$ are $n$ -component vectors of $n$ different ions. The model is simplified so that $f_{i}$ is 0 or 1 if a specific substitution pair occurs and $\\lambda_{i}$ provides a weighting for the likelihood of a given substitution. The resulting probabilities have been helpful, for example, in discovering new quaternary ionic compounds with limited computation budgets. \n\nIn our work, we adjust the probabilistic model so as to increase the number of candidates and give priority to discovery. In particular, the conditional probability computation in the original substitution patterns prefers examples that are more likely to be found in the original dataset. For example, any uncommon element is assigned a smaller probability in the original model. To give priority to novel discovery and move further away from the known sets of stable crystals, we modify the implementation so that probabilities are only computed when two compositions differ. This minor modification has substantial benefits across our pipeline, especially when scaling up to six unique elements. \n\nWe also introduce changes to the model parameters to promote novel discovery. In the original probabilistic model, positive lambda refers to more likely substitutions, although ‘unseen’ or uncommon substitution resulted in negative lambda values. We increase the number of generations by setting the minimum value of any substitution pair to be 0. We then threshold high-probability substitutions to a value of 0.001, enabling efficient exploration in composition space through branch-and-bound algorithms available from pymatgen. Overall, these settings allow for many one-ion or two-ion substitutions to be considered by the graph networks that otherwise would not have been considered. We find this to be a good intermediate between the original model and using all possible ionic substitutions, in which we encounter combinatorial blow-ups in the number of candidates. \n\nFor the main part of this paper, substitutions are only allowed into compositions that do not match any available compositions in the Materials Project or in the OQMD, rather than comparing structures using heuristic structure matchers. This ensures that we introduce novel compositions in the dataset instead of similar structures that may be missed by structure matchers. \n\nSAPS. To further increase the diversity of structures generations, we introduce a framework that we refer to as symmetry aware partial substitutions (SAPS), which generalizes common substitution frameworks. For a motivating example, consider the cases of (double) perovskites. Ionic substitutions on crystals of composition ${\\bf A}_{2}{\\bf B}_{2}X_{6}$ does not lead to discovering double perovskites ${\\bf A}_{2}{\\bf B}{\\bf B}^{\\prime}{\\bf O}_{6}$ , although the two only differ by a partial replacement on the B site. \n\nSAPS enable efficient discovery of such structures. Starting with an original composition, we obtain candidate ion replacements using the probabilities as defined in the ‘Substitution patterns’ section. We then obtain Wyckoff positions of the input structures by means of symmetry analysers available through pymatgen. We enable partial replacements from 1 to all atoms of the candidate ion, for which at each level we only consider unique symmetry groupings to control the combinatorial growth. Early experiments limited the partial substitutions to materials that would charge-balance after partial substitutions when considering common oxidation states; however, greater expansion of candidates was achieved by removing such charge-balancing from the later experiments. This partial-substitution framework enables greater use of common crystal structures while allowing for the discovery of new prototypical structures, as discussed in the main part of this paper. Candidates from SAPS are from a different distribution to the candidates from full substitutions, which increases the diversity of our discoveries and our dataset. \n\nTo validate the impact of the SAPS, we traced reference structures from substitutions of all 381,000 novel stable structures back to a structure in the Materials Project or the OQMD by means of a topological sort (necessary as discovered materials were recycled for candidate generation). A total of 232,477 out of the 381,000 stable structures can be attributed to a SAPS substitution, suggesting notable benefit from this diverse candidate-generation procedure. \n\nOxidation-state relaxations. For the compositional pipeline, inputs for evaluation by machine-learning models must be unique stoichiometric ratios between elements. Enumerating the combinatorial number of reduced formulas was found to be too inefficient, but common strategies to reduce such as oxidation-state balancing was also too restrictive, for example, not allowing for the discovery of $\\mathsf{L i}_{15}\\mathsf{S i}_{4}$ . In this paper, we introduce a relaxed constraint on oxidation-state balancing. We start with the common oxidation states from the Semiconducting Materials by Analogy and Chemical Theory (SMACT)57, with the inclusion of 0 for metallic forms. We allow for up to two elements to exist between two ordered oxidation states. Although this is a heuristic approach, it substantially improves the flexibility of composition generation around oxidation-state-balanced ratios. \n\nAIRSS structure generation. Random structures are generated through AIRSS when needed for composition models26. Random structures are initialized as ‘sensible’ structures (obeying certain symmetry requirements) to a target volume and then relaxed through soft-sphere potentials. A substantial number of initializations and relaxations are needed to discover new materials, as different initial structures lead to different minima on the structure–energy landscape. For this paper, we always generate 100 AIRSS structures for every composition that is otherwise predicted to be within 50 meV of stable through composition-only model prediction. \n\nAs we describe in Supplementary Note 5, not all DFT relaxations converge for the 100 initializations per composition. In fact, for certain compositions, only a few initializations converge. One of the main difficulties arises from not knowing a good initial volume guess for the composition. We try a range of initial volumes ranging from 0.4 to 1.2 times a volume estimated by considering relevant atomic radii, finding that the DFT relaxation fails or does not converge for the whole range for each composition. Prospective analysis was not able to uncover why most AIRSS initializations fail for certain compositions, and future work is needed in this direction. \n\n# Model training and evaluation \n\nGraph networks. For structural models, edges are drawn in the graph when two atoms are closer than an interatomic distance cutoff $(4.0\\mathrm{\\AA}$ for structural models, $5.0\\mathrm{\\AA}$ for interatomic potentials). Compositional models default to forming edges between all pairs of nodes in the graph. The models update latent node features through stages of message passing, in which neighbour information is collected through normalized sums over edges and representations are updated through shallow $\\mathsf{M L P S}^{36}$ . After several steps of message passing, a linear readout layer is applied to the global state to compute a prediction of the energy. \n\nTraining structural and composition models. Following Roost (representation learning from stoichiometry)58, we find GNNs to be effective at predicting the formation energy of a composition and structure. \n\nFor the structural models, the input is a crystal definition, which encodes the lattice, structure and atom definitions. Each atom is represented as a single node in the graph. Edges are defined when the interatomic distance is less than a user-defined threshold. Nodes are embedded by atom type, edges are embedded on the basis of the interatomic distance. We also include a global feature that is connected in the graph representation to all nodes. At every step of the GNN, neighbouring nodes and edge features are aggregated and used to update the corresponding representations of nodes, edges or globals individually. After 3–6 layers of message passing, an output layer projects the global vector to get an estimate of the energy. All data for training are shifted and scaled to approximately standardize the datasets. This structural model trained on the Materials Project data obtains state-of-the-art results of a mean absolute error of 21 meV atom−1. Training during the active-learning procedure leads to a model with a final mean absolute error of 11 meV atom−1. Training for structural models is performed with 1,000 epochs, with a learning rate of $5.55\\times10^{-4}$ and a linear decay learning rate schedule. By default, we train with a batch size of 256 and use swish nonlinearities in the MLP. To embed the edges, we use a Gaussian featurizer. The embedding dimension for all nodes and edges is 256 and, unless otherwise stated, the number of message-passing iterations is 3. \n\nFor the compositional models, the input composition to the GNN is encoded as a set of nodes, for which each element type in the composition is represented by a node. The ratio of the specific element is multiplied with the one-hot vector. For example, $\\mathsf{S i O}_{2}$ would be represented with two nodes, in which one node feature is a vector of zeros and a 1/3 on the 14th row to represent silicon and the other node is a vector of zeros with a 2/3 on the 8th row to represent oxygen. Although this simplified GNN architecture is able to achieve state-of-the-art generalization on the Materials Project (MAE of 60 meV atom−1 (ref. 25)), it does not offer useful predictions for materials discovery, which was also observed by Bartel et al.25. One of the issues with compositional models is that they assume that the training label refers to the ground-state phase of a composition, which is not guaranteed for any dataset. Thus, the formation-energy labels in the training and test sets are inherently noisy, and reducing the test error does not necessarily imply that one is learning a better formation-energy predictor. To explore this, we created our own training set of compositional energies, by running AIRSS simulations on novel compositions. As described in Supplementary Note 5, we find that compositions for which there are only a few completed AIRSS runs tend to have large formation energies, often larger than predicted by the compositional GNN. We find that, if we limit ourselves to compositions for which at least ten AIRSS runs are completed, then the compositional GNN error is reduced to 40 meV atom−1. We then use the GNN trained on such a dataset (for which labels come from the minimum formation energy phase for compositions with at least ten completed AIRSS runs and ignoring the Materials Project data) and are able to increase the precision of stable prediction to $33\\%$ . \n\nModel-based evaluation. Discovering new datasets aided by neural networks requires a careful balance between ensuring that the neural networks trained on the dataset are stable and promoting new discoveries. New structures and prototypes will be inherently out of distribution for models; however, we hope that the models are still capable of extrapolating and yielding reasonable predictions. This is out-of-distribution detection problem is further exacerbated by the implicit domain shift, in which models are trained on relaxed structures but evaluated on substitutions before relaxation. To counteract these effects, we make several adjustments to stabilize test-time predictions. \n\nTest-time augmentations. Augmentations at test time are a common strategy for correcting instabilities in machine-learning predictions. Specific to structural models, we especially consider isotropic scaling of the lattice vectors, which both shrinks and stretches bonds. At 20 values ranging from $80\\%$ to $120\\%$ of the reference lattice scaling volume, we aggregate by means of minimum reduction. This has the added benefit of potentially correcting for predicting on nonrelaxed structures, as isotropic scaling may yield a more appropriate final structure. \n\nDeep ensembles and uncertainty quantification. Although neural network models offer flexibility that allows them to achieve state-of-the-art performance on a wide range of problems, they may not generalize to data outside the training distribution. Using an ensemble of models is a simple, popular choice for providing predictive uncertainty and improving generalization of machine-learning predictions33. This technique simply requires training $n$ models rather than one. The prediction corresponds to the mean over the outputs of all n models; the uncertainty can be measured by the spread of the n outputs. In our application of training machine-learning models for stability prediction, we use $n=10$ graph networks. Moreover, owing to the instability of graph-network predictions, we find the median to be a more reliable predictor of performance and use the interquartile range to bound uncertainty. \n\nModel-based filtration. We use test-time augmentation and deep-ensemble approaches discussed above to filter candidate materials based on energy. Materials are then compared with the available GNoME database to estimate the decomposition energy. Note that the structures provided for model-based filtration are unlikely to be completely related, so a threshold of 50 meV atom−1 was used for active learning to improve the recall of stable crystal discovery. \n\nClustered-based reduction. For active-learning setups, only the structure predicted to have the minimum energy within a composition is used for DFT verification. However, for an in-depth evaluation of a specific composition family of interest, we design clustering-based reduction strategies. In particular, we take the top 100 structures for any given composition and perform pairwise comparisons with pymatgen’s built-in structure matcher. We cluster the connected components on the graph of pairwise similarities and take the minimum energy structure as the cluster representation. This provides a scalable strategy to discovering polymorphs when applicable. \n\nActive learning. Active learning was performed in stages of generation and later evaluation of filtered materials through DFT. In the first stage, materials from the snapshots of the Materials Project and the OQMD are used to generate candidates with an initial model trained on the Materials Project data, with a mean absolute error of 21 meV atom−1 in formation energy. Filtration and subsequent evaluation with DFT led to discovery rates between $3\\%$ and $10\\%$ , depending on the threshold used for discovery. After each round of active learning, new structural GNNs are trained to improve the predictive performance. Furthermore, stable crystal structures are added to the set of materials that can be substituted into, yielding a greater number of candidates to be filtered \n\n# Article \n\nby the improved models. This procedure of retraining and evaluation was completed six times, yielding the total of 381,000 stable crystal discoveries. Continued exploration with active learning may continue to drive the number of stable crystals higher. \n\nComposition-based hashing. Previous efforts to learn machinelearning models of energies often use a random split over different crystal structures to create the test set on which energy predictions are evaluated. However, as the GNoME dataset contains several crystal structures with the same composition, this metric is less trustworthy over GNoME. Having several structures within the same composition in both the training and the test sets markedly reduces test error, although the test error does not provide a measure of how well the model generalizes to new compositions. In this paper, we use a deterministic hash for the reduced formula of each composition and assign examples to the training $(85\\%)$ and test $(15\\%)$ sets. This ensures that there are no overlapping compositions in the training and test sets. We take a standard MD5 hash of the reduced formula, convert the hexadecimal output to an integer and take modulo 100 and threshold at 85. \n\n# DFT evaluation \n\nVASP calculations. We use the VASP (refs. 34,59) with the $\\mathsf{P B E}^{41}$ functional and PAW40,60 potentials in all DFT calculations. Our DFT settings are consistent with the Materials Project workflows as encoded in pymatgen23 and atomate61. We use consistent settings with the Materials Project workflow, including the Hubbard $U$ parameter applied to a subset of transition metals in DFT $+\\mathsf{U}$ , 520 eV plane-wave-basis cutoff, magnetization settings and the choice of PBE pseudopotentials, except for Li, Na, Mg, Ge and Ga. For Li, Na, Mg, Ge and Ga, we use more recent versions of the respective potentials with the same number of valence electrons. For all structures, we use the standard protocol of two-stage relaxation of all geometric degrees of freedom, followed by a final static calculation, along with the custodian package23 to handle any VASP-related errors that arise and adjust appropriate simulations. For the choice of KPOINTS, we also force gamma-centred kpoint generation for hexagonal cells rather than the more traditional Monkhorst–Pack. We assume ferromagnetic spin initialization with finite magnetic moments, as preliminary attempts to incorporate different spin orderings showed computational costs that were prohibitive to sustain at the scale presented. In AIMD simulations, we turn off spin polarization and use the NVT ensemble with a 2-fs time step. \n\nBandgap calculations. For validation purposes (such as the filtration of Li-ion conductors), bandgaps are calculated for most of the stable materials discovered. We automate bandgap jobs in our computation pipelines by first copying all outputs from static calculations and using the pymatgen-based MPNonSCFSet in line mode to compute the bandgap and density of states of all materials. A full analysis of patterns in bandgaps of the novel discoveries is a promising avenue for future work. \n\nr2SCAN. r2SCAN is an accurate and numerically efficient functional that has seen increasing adoption from the community for increasing the fidelity of computational DFT calculations. This functional is provided in the upgraded version of VASP6 and, for all corresponding calculations, we use the settings as detailed by MPScanRelaxSet and MPScanStaticSet in pymatgen. Notably, $\\mathsf{r}^{2}\\mathsf{S C A N}$ functionals require the use of PBE52 or PBE54 potentials, which can differ slightly from the PBE equivalents used elsewhere in this paper. To speed up computation, we perform three jobs for every SCAN-based computation. First, we precondition by means of the updated PBE54 potentials by running a standard relaxation job under MPRelaxSet settings. This preconditioning step greatly speeds up SCAN computations, which—on average—are five times slower and can otherwise crash on our infrastructure owing to elongated trajectories. Then, we relax with the r2SCAN functional, followed by a static computation. \n\n# Metrics and analysis methodology \n\nDecomposition energies. To compute decomposition energies and count the total number of stable crystals relative to previous work16,17 in a consistent fashion, we recalculated energies of all stable materials in the Materials Project and the OQMD with identical, updated DFT settings as enabled by pymatgen. Furthermore, to ensure fair comparison and that our discoveries are not affected by optimization failures in these high-throughput recalculations, we use the minimum energy of the Materials Project calculation and our recalculation when both are available. \n\nPrototype analysis. We validate the novel discoveries using XtalFinder (ref. 39), using the compare_structures function available from the command line. This process was parallelized over 96 cores for improved performance. We also note that the symmetry calculations in the built-in library fail on less than ten of the stable materials discovered. We disable these filters but note that the low number of failures suggests minimal impact on the number of stable prototypes. \n\nFamilies of interest. Layered materials. To count the number of layered materials, we use the methodology developed in ref. 45, which is made available through the pymatgen.analysis.dimensionality package with a default tolerance of $0.45\\mathring{\\mathbf{A}}$ . \n\nLi-ion conductors. The estimated number of viable Li-ion conductors reported in the main part of this paper is derived using the methodology in ref. 46 in a high-throughput fashion. This methodology involves applying filters based on bandgaps and stabilities against the cathode Li-metal anode to identify the most viable Li-ion conductors. \n\nLi/Mn transition-metal oxide family. The Li/Mn transition-metal oxide family is discussed in ref. 25 to analyse the capabilities of machinelearning models for use in discovery. In the main text, we compare against the findings in the cited work suggesting limited discovery within this family through previous machine-learning methods. \n\nDefinition of experimental match. In the main part of this paper, we refer to experimentally validated crystal structures with the ICSD. More specifically, we queried the ICSD in January 2023 after many of crystal discoveries had been completed. We then extracted relevant journal (year) and chemical (structure) information from the provided files. By rounding to nearest integer formulas, we found 4,235 composition matches with materials discovered by GNoME. Of these, 4,180 are successfully parsed for structure. Then, we turn to the structural information provided by the ICSD. We used the CIF parser module of pymatgen to load the experimental ICSD structures into pymatgen and then compared those to the GNoME dataset using its structure matcher module. For both modules, we tried using the default settings as well as more tolerant settings that improve structure parsing and matching (higher occupancy tolerance in CIF parsing to fix cases with ${\\tt>}1.0\\$ total occupancy and allowing supercell and subset comparison in matching). The latter resulted in a slight increase (about 100) in the number of matched structures with respect to the default settings. Given that we are enforcing a strict compositional match, our matching process is still relatively conservative and is likely to yield a lower bound. Overall, we found 736 matches, providing experimental confirmation for the GNoME structures. 184 of these structures correspond to novel discoveries since the start of the project. \n\n# Methods for creating figures of GNoME model scaling \n\nFigures 1e and 3a,b show how the generalization abilities of GNoME models scale with training set size. In Fig. 1e, the training sets are sampled uniformly from the materials from the Materials Project and from our structural pipeline, which only includes elemental and partial substitutions into stable materials in the Materials Project and the OQMD. The training labels are the final formation energy at the end of relaxation. The test set is constructed by running AIRSS on 10,000 random compositions filtered by the SMACT. Test labels are the final formation energy at the end of the AIRSS relaxation, for crystals that AIRSS and DFT (both electronically and ionically) converged. Because we apply the same composition-based hash filtering (see ‘Composition-based hashing’ section) on all of our datasets, there is no risk of label leakage between the training set from the structural pipeline and the test set from AIRSS. \n\nIn Fig. 3a, we present the classification error for predicting the outcome of DFT-based molecular dynamics using GNN molecular dynamics. ‘GNoME: unique structures’ refers to the first step in the relaxation of crystals in the structural pipeline. We train on the forces on each atom on the first DFT step of relaxation. The different training subsets are created by randomly sampling compositions in the structural pipeline uniformly. ‘GNoME: intermediate structures’ includes all the same compositions as ‘GNoME: unique structures’, but has all steps of DFT relaxation instead of just the first step. The red diamond refers to the same GNN interatomic potential trained on the data from M3GNet, which includes three relaxation steps per composition (first, middle and last), as described in the M3GNet paper62. \n\n# Coding frameworks \n\nFor efforts in machine learning, GNoME models make use of JAX and the capabilities to just-in-time compile programs onto devices such as graphics processing units (GPUs) and tensor processing units (TPUs). Graph networks implementations are based on the framework developed in Jraph, which makes use of a fundamental GraphsTuple object (encoding nodes and edges, along with sender and receiver information for message-passing steps). We also make great of use functionality written in JAX MD for processing crystal structures63, as well as TensorFlow for parallelized data input64. \n\nLarge-scale generation, evaluation and summarization pipelines make use of Apache Beam to distribute processing across a large number of workers and scale to the sizes as described in the main part of this paper (see ‘Overview of generation and filtration’ section). For example, billions of proposal structures, even efficiently encoded, requires terabytes of storage that would otherwise fail on single nodes. \n\nAlso, crystal visualizations are created using tooling from VESTA (ref. 65). \n\n# MLIPs \n\nPretrained GNoME potential. We train a NequIP potential30, implemented in JAX using the e3nn-jax library66, with five layers, hidden features of $128\\ell=0$ scalars, $64\\ell=1$ vectors and $32\\ell=2$ tensors (all even irreducible representations only, $128x0e+64x1x+32x2e)$ , as well as an edge-irreducible representation of $0e+1e+2e$ . We use a radial cutoff of $5\\mathring{\\mathbf{A}}$ and embed interatomic distances $r_{i j}$ in a basis of eight Bessel functions, which is multiplied by the XPLOR cutoff function, as defined in HOOMD-blue (ref. 67), using an inner cutoff of $\\mathbf{\\dot{4.5\\mathring{A}}}$ . We use a radial MLP $R(r)$ with two hidden layers with 64 neurons and a SiLU nonlinearity. We also use SiLU for the gated, equivariant nonlinearities68. We embed the chemical species using a 94-element one-hot encoding and use a self-connection, as proposed in ref. 30. For internal normalization, we divide by 26 after each convolution. Models are trained with the Adam optimizer using a learning rate of $2\\times10^{-3}$ and a batch size of 32. Given that high-energy structures in the beginning of the trajectory are expected to be more diverse than later, low-energy structures, which are similar to one another and often come with small forces, each batch is made up of 16 structures sampled from the full set of all frames across all relaxations and 16 structures sampled from only the first step of the relaxation only. We found this oversampling of first-step structures to substantially improve performance on downstream tasks. The learning rate was decreased to a new value of $2\\times10^{-4}$ after approximately 23 million steps, to $5\\times10^{-5}$ after a further approximately 11 million steps and then trained for a final 2.43 million steps. Training was performed on four TPU v3 chips. \n\nWe train on formation energies instead of total energies. Formation energies and forces are not normalized for training but instead we predict the energy as a sum over scaled and shifted atomic energies, such that E = ∑i∈Natoms $\\begin{array}{r}{\\hat{E}=\\sum_{i\\in N_{\\mathrm{atoms}}}\\left(\\hat{\\epsilon}_{i}\\sigma+\\mu\\right)}\\end{array}$ , in which $\\hat{\\epsilon}_{i}$ is the final, scalar node feature on atom i and $\\sigma$ and $\\mu$ are the standard deviation and mean of the per-atom energy computed over a single pass of the full dataset. The network was trained on a joint loss function consisting of a weighted sum of a Huber loss on energies and forces: \n\n$$\n\\begin{array}{r l}&{\\mathcal{L}=\\lambda_{E}\\displaystyle\\frac{1}{N_{\\mathrm{b}}}\\sum_{b=1}^{b=N_{\\mathrm{b}}}\\mathcal{L}_{\\mathrm{Huber}}\\Biggl(\\delta_{E},\\frac{\\hat{E}_{\\mathrm{b}}}{N_{\\mathrm{a}}},\\frac{E_{\\mathrm{b}}}{N_{\\mathrm{a}}}\\Biggr)}\\\\ &{\\quad\\quad\\quad+\\lambda_{F}\\displaystyle\\frac{1}{N_{\\mathrm{b}}}\\sum_{b=1}^{b=N_{\\mathrm{b}}}\\sum_{a=1}^{b=N_{\\mathrm{a}}}\\mathcal{L}_{\\mathrm{Huber}}\\Biggl(\\delta_{F},-\\frac{\\partial\\hat{E}_{\\mathrm{b}}}{\\partial r_{\\mathrm{b},\\mathrm{a},\\alpha}},F_{b,a,\\alpha}\\Biggr)}\\end{array}\n$$ \n\nin which $N_{\\mathrm{a}}$ and $N_{\\mathbf{b}}$ denote the number of atoms in a structure and the number of samples in a batch, respectively, $\\hat{E}_{\\mathrm{{b}}}$ and $\\boldsymbol{E}_{\\mathrm{b}}$ are the predicted and true energy for a given sample in a batch, respectively, and $F_{a,\\alpha}$ is the true force component on atom $a$ , for which $\\alpha\\in\\{x,y,z\\}$ is the spatial component. $\\mathcal{L}_{\\mathrm{Huber}}(\\delta,\\hat{a},a)$ denotes a Huber loss on quantity a, for which we use $\\delta_{E}=\\delta_{F}=0.01$ . The pretrained potential has 16.24 million parameters. Inference on an A100 GPU on a 50-atom system takes approximately $14\\mathrm{ms}$ , enabling a throughput of approximately 12 ns day−1 at a 2-fs time step, making inference times highly competitive with other implementations of GNN interatomic potentials. Exploring new approaches with even further improved computational efficiency is the focus of future work. \n\nTraining on M3GNet data. To allow a fair comparison with the smaller M3GNet dataset used in ref. 62, a NequIP model was trained on the M3GNet dataset. We chose the hyperparameters in a way that balances accuracy and computational efficiency, resulting in a potential with efficient inference. We train in two setups, one splitting the training and testing sets based on unique materials and the other over all structures. In both cases, we found the NequIP potential to perform better than the M3GNet models trained with energies and forces (M3GNet-EF) reported in ref. 62. Given this improved performance, to enable a fair comparison of datasets and dataset sizes, we use the NequIP model trained on the structure-split M3GNet data in the scaling tests (the pretrained M3GNet model is used for zero-shot comparisons). We expect our scaling and zero-shot results to be applicable to a wide variety of modern deep-learning interatomic potentials. \n\nThe structural model used for downstream evaluation was trained using the Adam optimizer with a learning rate of $2\\times10^{-3}$ and a batch size of 16 for a total of 801 epochs. The learning rate was decreased to $2\\times10^{-4}$ after 601 epochs, after which we trained for another 200 epochs. We use the same joint loss function as in the GNoME pretraining, again with $\\lambda_{E}=1.0,\\lambda_{F}=0.05$ and $\\delta_{E}=\\delta_{F}=0.01$ . The network hyperparameters are identical to the NequIP model used in GNoME pretraining. To enable a comparison with ref. 62, we also subtract a linear compositional fit based on the training energies from the reference energies before training. Training was performed on a set of four V100 GPUs. \n\nAIMD conductivity experiments. Following ref. 69, we classify a material as having superionic behaviour if the conductivity $\\sigma$ at the temperature of 1,000 K, as measured by AIMD, satisfies $\\sigma_{1,000\\kappa}{>}101.18\\mathrm{mScm}^{-1}$ . Refer to the original paper for applicable calculations. See Supplementary Information for further details. \n\nRobustness experiments. For the materials selected for testing the robustness of our models, $\\mathrm{As_{24}C a_{24}L i_{24},B a_{8}L i_{16}S e_{32}S i_{8},K_{24}L i_{16}P_{24}S n_{8}}$ and $\\mathsf{L i}_{32}\\mathsf{S}_{24}\\mathsf{S i}_{4},$ a series of models is trained on increasing training set sizes sampled from the $T{=}400\\kappa$ AIMD trajectory. We then evaluate these models on AIMD data sampled at both $T{=}400\\kappa$ (to measure the effect of fine-tuning on data from the target distribution) and \n\n# Article \n\n$T{=}1{,}000\\kappa$ (to measure the robustness of the learned potentials). We trained two types of model: (1) a NequIP model from scratch and (2) a fine-tuned model that was pretrained on the GNoME dataset, starting from the checkpoint before the learning rate was reduced the first time. The network architecture is identical to that used in pretraining. Because the AIMD data contain fewer high-force/high-energy configurations, we use a L2 loss in the joint loss function instead of a Huber loss, again with $\\lambda_{E}=1.0$ and $\\lambda_{\\scriptscriptstyle F}=0.05.$ For all training set sizes and all materials, we scan learning rates $1\\times10^{-2}$ and $2\\times10^{-3}$ and batch sizes 1 and 16. Models are trained for a maximum of 1,000 epochs. The learning rate is reduced by a factor of 0.8 if the test error on a hold-out set did not improve for 50 epochs. We choose the best of these hyperparameters based on the performance of the final checkpoint on the 400-K test set. The $400{\\cdot}\\mathsf{K}$ test set is created using the final part of the AIMD trajectory. The training sets are created by sampling varying training set sizes from the initial part of the AIMD trajectory. The out-of-distribution robustness test is generated from the AIMD trajectory at 1,000 K. Training is performed on a single V100 GPU. \n\nMolecular dynamics simulations. The materials for AIMD simulation are chosen on the basis of the following criteria: we select all materials in the GNoME database that are stable, contain one of the conducting species under consideration (Li, Mg, Ca, K, Na) and have a computationally predicted band gap >1 eV. The last criterion is chosen to not include materials with notable electronic conductivity, a desirable criterion in the search for electrolytes. Materials are run in their pristine structure, that is, without vacancies or stuffing. The AIMD simulations were performed using the VASP. The temperature is initialized at $T{=}300\\mathsf{K}$ , ramped up over a time span of 5 ps to the target temperature, using velocity rescaling. This is followed by a 45-ps simulation equilibration using a Nosé–Hoover thermostat in the NVT ensemble. Simulations are performed at a 2-fs time step. \n\nMachine-learning-driven molecular dynamics simulations using JAX $\\mathsf{M D}^{63}$ are run on a subset of materials for which AIMD data were available and for which the composition was in the test set of the pretraining data (that is, previously unseen compositions), containing Li, Na, K, Mg and Ca as potentially conducting species. This results in 623 materials for which GNoME-driven molecular dynamics simulations are run. Simulations are performed at $T{=}1,000\\kappa$ using a Nosé–-Hoover thermostat, a temperature equilibration constant of 40 time steps, a 2-fs time step and a total simulation length of 50 ps. Molecular dynamics simulations are performed on a single P100 GPU. \n\nFor analysis of both the AIMD and the machine learning molecular dynamics simulation, the first 10 ps of the simulation are discarded for equilibration. From the final 40 ps, we compute the diffusivity using the DiffusionAnalyzer class of pymatgen with the default smoothed=max setting23,70,71. \n\n# Data availability \n\nCrystal structures corresponding to stable discoveries discussed throughout the paper will be made available at https://github.com/ google-deepmind/materials_discovery. In particular, we provide results for all stable structures, as well as any material that has been recomputed from previous datasets to ensure consistent settings. Associated data from the $\\mathsf{r}^{2}\\mathsf{S C A N}$ functional will be provided, expectantly serving as a foundation for analysing discrepancies between functional choices. Data will also be available via the Materials Project at https://materialsproject.org/gnome with permanent link: https:// doi.org/10.17188/2009989. \n\n# Code availability \n\nSoftware to analyse stable crystals and associated phase diagrams, as well as the software implementation of the static GNN and the interatomic potentials, will be made available at https://github.com/ google-deepmind/materials_discovery. \n\n57.\t Davies, D. W. et al. SMACT: semiconducting materials by analogy and chemical theory. J. Open Source Softw. 4, 1361 (2019). \n58.\t Goodall, R. E. & Lee, A. A. Predicting materials properties without crystal structure: deep representation learning from stoichiometry. Nat. Commun. 11, 6280 (2020). \n59.\t Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). \n60.\t Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758 (1999). \n61. Mathew, K. et al. atomate: a high-level interface to generate, execute, and analyze computational materials science workflows. Comput. Mater. Sci. 139, 140–152 (2017). \n62. Chen, C. & Ong, S. P. A universal graph deep learning interatomic potential for the periodic table. Nat. Comput. Sci. 2, 718–728 (2022). \n63.\t Schoenholz, S. & Cubuk, E. D. JAX MD: a framework for differentiable physics. Adv. Neural Inf. Process. Syst. 33, 11428–11441 (2020). \n64.\t Abadi, M. et al. TensorFlow: large-scale machine learning on heterogeneous systems. https://www.tensorflow.org/ (2015). \n65.\t Momma, K. & Izumi, F. VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J. Applied Crystallogr. 44, 1272–1276 (2011). \n66.\t Geiger, M. & Smidt, T. e3nn: Euclidean neural networks. Preprint at https://arxiv.org/abs/ 2207.09453 (2022). \n67.\t Anderson, J. A., Glaser, J. & Glotzer, S. C. HOOMD-blue: a Python package for highperformance molecular dynamics and hard particle Monte Carlo simulations. Comput. Mater. Sci. 173, 109363 (2020). \n68.\t Hendrycks, D. & Gimpel, K. Gaussian Error Linear Units (GELUs). Preprint at https://arxiv. org/abs/1606.08415 (2016). \n69.\t Jun, K. et al. Lithium superionic conductors with corner-sharing frameworks. Nat. Mater. 21, 924–931 (2022). \n70.\t Ong, S. P. et al. Phase stability, electrochemical stability and ionic conductivity of the $\\mathsf{L i}_{10\\pm1}\\mathsf{M P}_{2}\\mathsf{X}_{1}2$ ( $\\mathsf{M}=$ Ge, Si, Sn, Al or P, and $\\mathsf{X}=\\mathsf{O},$ S or Se) family of superionic conductors. Energy Environ. Sci. 6, 148–156 (2013). \n71.\t Mo, Y., Ong, S. P. & Ceder, G. First principles study of the $\\mathsf{i}_{1}0\\mathsf{G e P}_{2}\\mathsf{S}_{1}2$ lithium super ionic conductor material. Chem. Mater. 24, 15–17 (2012). \n\nAcknowledgements We would like to acknowledge D. Eck, J. Sohl-Dickstein, J. Dean, J. Barral, J. Shlens, P. Kohli and Z. Ghahramani for sponsoring the project; L. Dorfman for product management support; A. Pierson for programme management support; O. Loum for help with computing resources; L. Metz for help with infrastructure; E. Ocampo for help with early work on the AIRSS pipeline; A. Sendek, B. Yildiz, C. Chen, C. Bartel, G. Ceder, J. Sun, J. P. Holt, K. Persson, L. Yang, M. Horton and M. Brenner for insightful discussions; and the Google DeepMind team for continuing support. \n\nAuthor contributions A.M. led the code development, experiments and analysis in most parts of the project, including the proposal of the data flywheel through active learning, candidate generation (for example, invention of SAPS), large-scale training and evaluation workflows, DFT calculations, convex-hull analysis and materials screening. S.B. led the code development, training and experiments of the force fields and the zero-shot evaluations, fine-tuning, robustness and the GNN molecular dynamics experiments, and contributed to overall code development, as well as training infrastructure. S.S.S. led the scaling of GNN training and JAX MD infrastructure and contributed to force-field experiments. M.A. contributed to data analyses, validation and benchmarking efforts, ran experiments and provided guidance. G.C. contributed to analysis, zero-shot evaluations and provided guidance. E.D.C. conceived and led the direction of the project, wrote software for data generation, model implementations and training, and led the scaling experiments. All authors contributed to discussion and writing. \n\nCompeting interests Google LLC owns intellectual property rights related to this work, including, potentially, patent rights. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-023-06735-9. \nCorrespondence and requests for materials should be addressed to Amil Merchant or Ekin Dogus Cubuk. \nPeer review information Nature thanks the anonymous reviewers for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. " + }, + { + "id": "10.1038_s41467-023-39366-9", + "DOI": "10.1038/s41467-023-39366-9", + "DOI Link": "http://dx.doi.org/10.1038/s41467-023-39366-9", + "Relative Dir Path": "mds/10.1038_s41467-023-39366-9", + "Article Title": "Fe/Cu diatomic catalysts for electrochemical nitrate reduction to ammonia", + "Authors": "Zhang, S; Wu, JH; Zheng, MT; Jin, X; Shen, ZH; Li, ZH; Wang, YJ; Wang, Q; Wang, XB; Wei, H; Zhang, JW; Wang, P; Zhang, SQ; Yu, LY; Dong, LF; Zhu, QS; Zhang, HG; Lu, J", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Electrochemical conversion of nitrate to ammonia offers an efficient approach to reducing nitrate pollutants and a potential technology for low-temperature and low-pressure ammonia synthesis. However, the process is limited by multiple competing reactions and NO3- adsorption on cathode surfaces. Here, we report a Fe/Cu diatomic catalyst on holey nitrogen-doped graphene which exhibits high catalytic activities and selectivity for ammonia production. The catalyst enables a maximum ammonia Faradaic efficiency of 92.51% (-0.3 V(RHE)) and a high NH3 yield rate of 1.08 mmol h(-1) mg(-1) (at - 0.5 V(RHE)). Computational and theoretical analysis reveals that a relatively strong interaction between NO3- and Fe/Cu promotes the adsorption and discharge of NO3- anions. Nitrogen-oxygen bonds are also shown to be weakened due to the existence of hetero-atomic dual sites which lowers the overall reaction barriers. The dual-site and hetero-atom strategy in this work provides a flexible design for further catalyst development and expands the electrocatalytic techniques for nitrate reduction and ammonia synthesis. Nitrate electroreduction to ammonia can decrease pollutants and produce high-value ammonia. Here, the authors design a Fe/Cu diatomic catalyst on nitrogen-doped graphene, which exhibits high catalytic activities of and selectivity for ammonia.", + "Times Cited, WoS Core": 280, + "Times Cited, All Databases": 283, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:001015306500018", + "Markdown": "# Fe/Cu diatomic catalysts for electrochemical nitrate reduction to ammonia \n\nReceived: 3 July 2022 \n\nAccepted: 9 June 2023 \n\nPublished online: 19 June 2023 \n\nCheck for updates \n\nShuo Zhang1,2,3, Jianghua $\\boldsymbol{\\mathsf{w}}\\boldsymbol{\\mathsf{u}}^{2}$ , Mengting Zheng4, Xin Jin2, Zihan Shen 1, Zhonghua Li2, Yanjun Wang2, Quan Wang2, Xuebin Wang $\\textcircled{\\bullet}^{2}$ , Hui Wei 2, Jiangwei Zhang5, Peng Wang 2,6, Shanqing Zhang4, Liyan $\\gamma_{\\mathbf{{u}}}\\mathbf{\\Lambda}^{3}$ , Lifeng Dong3, Qingshan Zhu1,7 , Huigang Zhang 1,2,7 & Jun Lu 8 \n\nElectrochemical conversion of nitrate to ammonia offers an efficient approach to reducing nitrate pollutants and a potential technology for low-temperature and low-pressure ammonia synthesis. However, the process is limited by multiple competing reactions and ${\\mathsf{N O}}_{3}{}^{-}$ adsorption on cathode surfaces. Here, we report a $\\mathsf{F e/C u}$ diatomic catalyst on holey nitrogen-doped graphene which exhibits high catalytic activities and selectivity for ammonia production. The catalyst enables a maximum ammonia Faradaic efficiency of $92.51\\%$ (−0.3 V(RHE)) and a high ${\\mathsf{N H}}_{3}$ yield rate of 1.08 mmol $\\mathsf{h}^{-1}\\mathsf{m}\\mathsf{g}^{-1}$ (at − 0.5 V(RHE)). Computational and theoretical analysis reveals that a relatively strong interaction between ${\\mathsf{N O}}_{3}^{-}$ and $\\mathsf{F e/C u}$ promotes the adsorption and discharge of ${\\mathsf{N O}}_{3}^{-}$ anions. Nitrogen-oxygen bonds are also shown to be weakened due to the existence of hetero-atomic dual sites which lowers the overall reaction barriers. The dual-site and hetero-atom strategy in this work provides a flexible design for further catalyst development and expands the electrocatalytic techniques for nitrate reduction and ammonia synthesis. \n\nAmmonia is a common and important chemical in agriculture, plastic, pharmaceutical industries, etc1,2. Since the invention of the Haber–Bosch process, large-scale synthesis and application of ammonia dramatically increase the crop yield and sustain the growing human population3,4. However, the Harber-Bosch process consumes extravagant resources and energy $(1-2\\%$ of the annual global energy supply) and produces $1\\%$ of $\\mathbf{CO}_{2}$ emission (1.8 tons $\\mathbf{CO}_{2}$ for 1 ton $\\mathsf{N H}_{3})^{5}$ , causing severe environmental impact. Therefore, clean and energyefficient technologies for ammonia synthesis receive increasing attention. At the same time, human activities have ceaselessly released reactive nitrogen into the environment, leading to an imbalance in the global nitrogen cycle6–8. The increasing concentration of nitrate $(\\mathsf{N O}_{3}{}^{-})$ in surface water and underground aquifer pollutes the water resources and poses severe threats to human health9–11. As ${\\mathsf{N O}}_{3}^{-}$ is soluble and thermodynamically stable, removing ${\\mathsf{N O}}_{3}{}^{-}$ from water is considered a challenging and long-standing task12,13. The direct conversion of nitrate to ammonia could reduce environmental pollution and concurrently save energy for sustainable ammonia production. \n\nHydrogenation of nitrate to ammonia is intrinsically a spontaneous energy-releasing process $(\\Delta\\mathsf{G}<0)$ because nitrates are usually strong oxidative agents14. To pursue carbon neutrality, a thermocatalytic nitrate reduction requires hydrogen gas $\\left(\\mathsf{H}_{2}\\right)$ to be produced in a green and clean way without $\\mathbf{CO}_{2}$ emission (most industrial ${\\sf H}_{2}$ is generated from fossil fuels by steam reforming of hydrocarbons or coal gasification). By contrast, the electroreduction of nitrate to ammonia (as follows) is a promising green strategy because electrons are clean reducing agents without producing secondary wastes15,16. \n\n$$\n{\\tt N O}_{3}^{-}+6{\\sf H}_{2}{\\sf O}+8e^{-}\\rightarrow{\\tt N H}_{3}+9{\\tt O H}^{-},E^{0}=0.69V v s{\\tt R H E}({\\tt p H}=14)\\\n$$ \n\nThe electrochemical nitrate reduction reaction $(\\mathsf{N O}_{3}\\mathsf{^{-}R R})$ involves an eight-electron transfer, which has slow kinetics17,18. In addition, the competitive hydrogen evolution reaction (HER) and a variety of byproducts complicate the reaction routes and render the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ less selective and efficient19,20. To date, achieving efficient catalysts for the $N O_{3}^{-}\\mathsf{R R}$ remains a major challenge mainly because the catalytic mechanism and the structure–activity relationship of catalysts are poorly understood21. \n\nSingle-atom catalysts (SACs) have recently emerged as a new frontier in catalysis science owing to their convenient atomic design, easy structure–activity correlation, and maximum atom utilization efficiency22–24. Tunable local coordination and well-defined active sites25–27 make SACs an ideal platform to study the structure–activity relationship of catalytic $\\mathsf{N O}_{3}\\mathsf{^{-}R R}$ . By engineering the coordination environments of active single atoms, the energy barriers of different proton-electron transfer steps could be selectively shifted, offering opportunities of increasing the selectivity of the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ . Sargent et al. reported that the appropriately optimized d-band center position could enhance the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ performance of $\\mathtt{C u}_{50}\\mathtt{N i}_{50}$ alloy as compared to pure ${\\mathsf{C u}}^{28}$ . Guo et al. loaded a single transition metal atom on graphitic carbon nitrides and demonstrated efficient nitrate degradation and ammonia synthesis14. Fe SACs were reported to have high activity and selectivity toward the production of ${\\mathsf{N H}}_{3}$ via the $\\mathsf{N O}_{3}\\mathsf{^{-}R R}^{29}$ . Yu et al. fabricated isolated Fe sites in $\\mathsf{F e N}_{4}$ coordination and displayed twelve times higher turnover frequency than Fe nanoparticles30. These important studies imply that SACs including $\\mathsf{F e/C u}$ may offer higher catalytic behavior. However, for multi-electron transfer reactions, one specific site makes SACs difficult to break the linear scaling relations of adsorption strength between catalysts and multiple similar intermediates31,32. Optimizing the interaction of a key intermediate in the rate-determining step (r.d.s) may turn another step to the r.d.s33. Dual-site catalysts could extend the catalysts with substantially different coordination environment34,35. However, the precise design and fabrication of dual-site catalysts remain a challenge and the catalytic mechanism of heteroatomic sites is elusive, especially for ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}.$ \n\nIn this work, we propose a dual atoms catalyst for high-efficiency $N O_{3}^{-}\\mathsf{R R}$ . Active metal atoms $(\\mathrm{Fe/Cu})$ are anchored to the holey edge sites of nitrogen-doped graphene (HNG), forming a “Y-type” $\\mathsf{M L}_{3}$ coordination with two nitrogen atoms and one metal atom. Fe and Cu atoms bind together to form a dimer structure inside the holes (Fig. 1a). The resultant catalyst, $\\mathsf{F e/C u-H N G}$ , demonstrates high activity $(\\sim38.5\\mathsf{m A c m}^{-2}$ at $-0.3\\ensuremath{\\mathsf{V}}$ vs reversible hydrogen electrode (RHE)) and selectivity (maximum Faradaic efficiency (FE) of $92.51\\%\\$ for the reduction of ${\\mathsf{N O}}_{3}^{-}$ towards ${\\mathsf{N H}}_{3}$ under alkaline conditions. The maximum ${\\mathsf{N H}}_{3}$ yield rate is as high as 1.08 mmol $\\mathsf{h}^{-1}\\mathsf{m g}^{-1}$ at $-0.5\\mathsf{V}$ vs RHE. By combining operando differential electrochemical mass spectrometry (DEMS) and density functional theory (DFT) calculations, we reveal the reaction pathways and conversion mechanisms from ${\\mathsf{N O}}_{3}^{-}$ to $N\\mathsf{H}_{3}$ . An in-depth analysis of electronic structure indicates that the strong coupling between ${\\mathsf{N O}}_{3}$ and ${\\bf d}$ -orbitals of dual metal atoms lowers the energy barrier of the first anionic adsorption step, which is the r.d.s at high current densities. The dual atoms heterostructure could further weaken N-O bonds, enabling low energy barriers for ${\\mathsf{N H}}_{3}$ production. The synergistic effects of dual atoms offer an alternative approach to designing the ${\\mathsf{N O}}_{3}{\\mathrm{\\cdot}}$ –RR catalysts. \n\n# Results Structural characterization of Fe/Cu-HNG \n\nTo anchor dual atoms and form metal–metal dimers (as shown in Fig. 1a), we first engineered holes in graphene to create a great number of edge sites, which were further nitrified to bind $\\mathsf{F e/C u}$ atoms. Holey graphene was fabricated by sonicating graphene oxide (GO) in nitric acid $(68\\%)$ . The strong oxidation capability of nitric acid would cut the C-C bonds of GO layers to yield epoxy chains (carboxyl and/or hydroxyl) and other defects36–38. During the following hydrothermal and annealing treatments, the above-mentioned functional groups and defects were substituted by nitrogen, forming HNG. Supplementary Fig. 1 shows the scanning electron microscope (SEM) images of HNG and reduced GO (rGO). An rGO layer exhibits a large and flat area whereas HNG becomes porous. The transmission electron microscope (TEM) images in Supplementary Fig. 2 further reveal the successful synthesis of micropores on HNG. When $\\mathsf{F e/C u}$ precursors were added during the hydrothermal and annealing steps, Fe/Cu dual atoms could be loaded onto the N-edge of micropores. The Fe/Cu loadings in Fe/CuHNG are determined to be 3.3 and $2.8~\\mathsf{w t\\%}$ , respectively, by using an inductively coupled plasma method (Supplementary Table 1). \n\n![](images/3cb38aaf816ba2bc5a807e6a1b592f5eba644f296b35b953d0fd27a746a9806c.jpg) \nFig. 1 | Schematic illustration of the synthesis of Fe/Cu-HNG and electrochemical nitrate reduction. a Schematic illustration of catalyst construction. b Electrochemical nitrate reduction. c Catalytic conversion steps from ${\\mathsf{N O}}_{3}^{-}$ to $\\mathsf{N H}_{3}$ . \n\n![](images/eba9bf0b137c3d3d302c1094934049f42ec73d9a8fd2455ddd8aef9d3aa4a0f9.jpg) \nFig. 2 | Materials characterization of Fe/Cu dual atoms catalyst. a HAADF-STEM e EDX elemental mapping images of C, N, Fe, and Cu in $\\mathsf{F e/C u}$ -HNG. f Statistical image of Fe/Cu-HNG. b Zoomed-in HAADF-STEM image indicates the formation of distribution of $\\mathsf{F e/C u}$ distance of the observed diatomic pairs. $\\mathbf{g}$ EELS spectrum of dual atoms sites where two distinct adjacent bright dots were marked with blue $\\mathsf{F e/C u}$ atomic sites. h $\\mathsf{N}_{2}$ adsorption–desorption isotherms of Fe/Cu-HNG (inset: dashed circles. c Corresponding intensity profiles of dual atoms pair. d STEM and corresponding pore-size distribution). i XRD pattern of $\\mathrm{Fe/Cu\\mathrm{\\cdot}H N G}$ \n\nFigure 2a, b show the aberration-corrected high-angle annular dark-filed scanning TEM (HAADF-STEM) images of $\\mathrm{Fe/Cu\\mathrm{\\cdot}H N G}$ . A great number of atom-sized bright dots are distributed on HNG. By zooming into the image, diatomic pairs (like dimers) could be mostly observed. Energy-dispersive $\\mathsf{x}$ -ray spectroscopic (EDX) line scan through two bright dots indicates a distance of ${\\sim}2.3\\mathring\\mathrm{A}$ (Fig. 2c), which is in agreement with the bond length of Fe-Cu in the simulated model (Fig. 1a). The EDX elemental mapping images in Fig. 2d, e clearly indicate the uniform distribution of C, N, Fe, and Cu. Figure 2f presents a statistical distribution of the metal–metal pair length. The average bond length is $2.3\\pm0.2\\mathring{\\mathsf{A}}$ . The electron energy loss spectrum (EELS) in Fig. 2g reveals the coexistence of Fe and Cu elements in $\\mathrm{Fe/Cu\\mathrm{\\cdot}H N G}$ . More complementary characterizations and statistical analyses were shown in Supplementary Figs. 3, 4 to identify diatomic sites. \n\nThe $\\mathsf{N}_{2}$ adsorption–desorption isotherms of Fe/Cu-HNG (Fig. 2h) confirm the presence of highly mesoporous structures. The corresponding pore-size distribution has a major peak of $2\\div3{\\mathsf{n m}}$ . The Brunauer–Emmett–Teller (BET) method is used to estimate the surface area to be $858{\\mathrm{m}}^{2}{\\mathrm{g}}^{-1}.$ , which is five times higher than rGO $(132\\mathsf{m}^{2}\\mathsf{g}^{-1}$ , Supplementary Fig. 5). A high surface area and porous structure could facilitate mass transport and improve the apparent activity of catalysts39–41. The X-ray diffraction (XRD) pattern (Fig. 2i) shows only two broad peaks, which are ascribed to stacking graphene layers (Supplementary Fig. $6)^{42,43}$ . No other impurity peaks are observed. In conjunction with a wide-range SEM (Supplementary Fig. 7) and TEM (Supplementary Fig. 8) analysis, we may conclude that $\\mathsf{F e/C u}$ diatomic structures were successfully constructed on HNG and no aggregation or nanoparticles of metals were observed. For comparison, homogenous diatomic materials (Fe/Fe-HNG and $\\mathrm{Cu/Cu\\mathrm{\\cdot}H N G)}$ were also synthesized by adding Fe or Cu precursors, respectively. Detailed morphologic and structural characterizations of Fe/Fe-HNG and $\\mathtt{C u/}$ Cu-HNG were shown in Supplementary Figs. 9, 10, respectively. \n\nFigure 3a presents the X-ray photoelectron spectroscopic (XPS) analyses of the N 1s signal. The broad peak of the N 1s signal could be de-convoluted to pyridinic N $(-398.3\\mathsf{e V})$ , pyrrolic N $(-400.6\\mathrm{eV})$ , graphitic $\\mathsf{V}\\left(\\mathsf{-401.4e V}\\right)$ , and $\\mathrm{Fe-N/Cu-N}(-399.0\\mathrm{eV})^{44,45}$ . The Fe $2p_{3/2}$ signals exhibit two peaks that could be assigned to the $\\mathsf{F e}^{2+}\\left(709.9\\mathsf{e V}\\right)$ and $\\mathsf{F e}^{3+}\\ (711.5\\mathrm{eV})^{46,47}$ . By decreasing the number of metal precursors, we synthesized single-atom-loaded HNG (labeled as Fe-HNG or $\\mathbf{Cu-HNG},$ . As compared to single-atom Fe-HNG, the Fe $2p$ peaks of $\\mathrm{Fe/Cu\\mathrm{-}H N G}$ shift toward high binding energy (Supplementary Fig. 11b). The Cu $2p_{3/2}$ spectrum in Supplementary Fig. 11c shows two peaks at 932.5 and $933.7\\mathrm{eV}$ , which are assigned to ${{\\mathsf{C}}{\\mathbf{u}}}^{+}$ and ${\\mathsf{C u}}^{2+}$ , respectively48,49. By contrast, the $\\mathtt{C u}2p$ peaks of $\\mathsf{F e/C u-H N G}$ have lower binding energy than those in single-atom Cu-HNG. The XPS peak shift of Fe/Cu dual atoms may imply electron transfer from Fe to Cu. The Raman spectra in Fig. 3b show two typical D and G bands of graphene at 1362 and $1576\\mathrm{cm}^{-1}$ , respectively. The intensity ratio of D to G is higher for $\\mathsf{F e/C u\\mathrm{-}}$ HNG than that for rGO and HNG, indicating that the defective carbon nanosheets are formed owing to Fe/Cu dopants50,51. \n\n![](images/e336b8495f0d54dccfd096d50359cbd103a51ef1cf2482c6c8e95be1284745bc.jpg) \nFig. 3 | Atomic structural and chemical states analyses of Fe/Cu dual atom K-edge EXAFS. f $k^{3}$ -weighted FT of $\\mathsf{X}^{(\\mathsf{k})}$ -function from the Cu K-edge EXAFS. WT catalyst. a High-resolution N 1s XPS spectrum of $\\mathrm{Fe/Cu\\mathrm{\\cdot}H N G}$ . b Raman spectra of images of the Cu K-edge from g Cu-HNG h Fe/ $\\mathtt{C u}$ -HNG, and the Fe K-edge from i FerGO, HNG, and Fe/Cu-HNG. c Cu K-edge XANES spectra of Fe/Cu-HNG, $\\mathtt{C u/C u}$ -HNG, HNG, and j Fe/Cu-HNG. k Proposed schematic model of Fe/Cu-HNG: Fe (aqua), Cu $\\mathtt{c u}$ -HNG, Cu foil, CuO, and $\\mathsf{C u}_{2}\\mathsf{O}.$ . d Fe K-edge XANES spectra of Fe/Cu-HNG, Fe/Fe- (orange), N (blue), and C (brown). l Fitting results of the EXAFS spectra of Fe/CuHNG, Fe-HNG, Fe foil, FeO, and $\\mathrm{Fe}_{2}\\mathrm{O}_{3}$ . e $k^{3}$ -weighted FT of χ(k)-function from the Cu HNG at k-space and R space of Fe K-edge. \n\nFigure 3c–f show the X-ray absorption near-edge spectra (XANES) and extended X-ray absorption fine structure (EXAFS). The Cu K-edge XANES of Fe/Cu-HNG (Fig. 3c) confirms that Cu has an oxidation state between $\\mathtt{C u}_{2}0$ $(1+)$ and CuO $(2+)^{52}$ . Similarly, the Fe K-edge XANES of $\\mathsf{F e/C u-H N G}$ (Fig. 3d) resides between Fe (0) foil and $\\mathsf{F e}_{2}\\mathsf{O}_{3}$ $(3+)$ , indicative of the oxidized Fe in $\\mathsf{F e/C u-H N G^{43,53}}$ . As compared to Fe-HNG, a minor shift of Fe K-edge in Fe/Cu-HNG toward high energy implies that $\\mathsf{F e/C u}$ dimers in HNG slightly increase the oxidation state of Fe owing to Cu ligands. Fe atoms in $\\mathsf{F e/C u-H N G}$ transfer electrons to Cu and slightly reduce Cu as compared to Cu-HNG. Such a trend obtained by the absorption spectra is in agreement with the XPS analyses. The $k^{3}$ - weighted Fourier transform (FT) from Cu K-edge EXAFS spectra (Fig. 3e) show that the major peaks of Fe/Cu-HNG, Cu-HNG, and $\\mathrm{{Cu/Cu\\mathrm{{-}}}}$ HNG are located at ${\\bf-1.45\\mathring\\mathrm{A}}$ , which corresponds to the first shell scattering of the $\\mathsf{C u-N}$ coordination54. Notably, the second peaks at 2.15 and $2.27\\mathring{\\mathrm{A}}$ for $\\mathsf{F e/C u-H N G}$ and $\\mathrm{{Cu/Cu/HNG}}$ , respectively, are comparable to the first shell distance of Cu foil $(2.24\\mathring{\\mathrm{A}})$ , suggesting the presence of metal–metal diatomic configuration. Similarly, the major peaks at ${\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}{\\boldmath{\\widetilde{\\mathbf{\\Gamma}}}}$ for Fe/Cu-HNG, Fe-HNG, and Fe/Fe-HNG in Fig. 3f are ascribed to Fe–N coordination55,56. The second peaks at 2.15 and $2.03\\mathring{\\mathbf{A}}$ for $\\mathsf{F e/C u-H N G}$ and Fe/Fe-HNG, respectively, further confirm the presence of metal–metal diatomic configuration. The $k^{3}$ -weighted FT spectra indicate that the metal–metal distance in $\\mathrm{Fe/Cu\\mathrm{-}H N G}$ is shorter than Cu–Cu coordination in $\\mathrm{{Cu/Cu/HNG}}$ and longer than Fe–Fe coordination in Fe/Fe-HNG, verifying the existence of heterogeneous Fe-Cu sites in $\\mathsf{F e/C u-H N G}$ . Figure $3{\\bf g}-{\\bf j}$ present the wavelet transform (WT) of the EXAFS spectra. Both Cu-HNG and Fe/Cu-HNG exhibit the intensity maxima at ${\\bf-}4.8\\mathring{\\bf A}^{-1}$ due to the $\\mathsf{C u-N}$ path in the Cu K-edge spectra, differing from the $\\mathsf{C u-O}$ path $(-4.2\\mathring{\\mathbf{A}}^{-1})$ . In addition, Fe-HNG and Fe/CuHNG display the intensity maxima at $4.6\\mathring{\\mathsf{A}}^{-1}$ due to the Fe–N path in the Fe K-edge spectra. For $\\mathrm{Fe/Cu/\\mathrm{\\Sigma/HNG}}$ , the WT of either Fe or Cu K-edge signals display a maximum at $2.15\\mathring{\\mathrm{A}}$ , which is between the metal–metal bond length of Cu and Fe foils and different with Fe/Fe-HNG and $\\mathrm{cu/}$ Cu-HNG (see Supplementary Figs. 9–13), suggesting the formation of Fe–Cu bond (Fig. 3h, j). Therefore, the WT and FT-EXAFS analyses confirm the existence of metal– $\\mathbf{\\nabla\\cdotN}$ coordination and metal–metal bonds in $\\boldsymbol{\\mathrm{Fe/Cu-HNG^{57-59}}}$ . \n\nTo further verify the coordination structure of $\\mathsf{F e/C u-H N G}$ , we used the model in Fig. $3\\mathbf{k}$ to fit the FT-EXAFS curves in Fig. 3l (see other fittings in Supplementary Figs. 9–14). The fitted main peak around $1.97\\bar{\\mathsf{A}}$ and $2.0\\dot{5}\\mathring{\\mathrm{A}}$ originate from the first Fe–N and $\\mathsf{C u{-}N}$ coordination shell. The coordination numbers of Fe–N and $\\mathsf{C u-N}$ are around 2.16 and 2.23 (Supplementary Table 2), respectively. The second peak in Fig. 3l is fitted to be ${\\bf\\tilde{\\Gamma}}\\tilde{\\bf\\Delta}{\\bf\\tilde{\\Gamma}}^{2.25\\hat{\\bf A}}$ , which corresponds to the Fe–Cu path. The good agreement between the experimental and fitting results confirms the proposed structure that $\\mathsf{F e/C u}$ dual atoms are anchored on $\\mathsf{M N}_{2}$ sites and the neighboring $\\mathsf{F e/C u}$ atoms bond together to form a metal–metal dimer structure60,61. \n\n# Electrocatalytic performance for the ${\\bf N O}_{3}{\\bf\\Phi}^{-}{\\bf R R}$ \n\nFigure 4a presents the linear sweep voltammetry (LSV) curves of electrochemical nitrate reduction in an electrolyte of 1 M KOH and 0.1 M ${\\mathsf{K N O}}_{3}$ . HNG delivers ultralow current density until the negative polarization reaches $-0.4\\upnu$ vs RHE. SACs (Fe-HNG and Cu-HNG) \n\n![](images/bdeae3ecae1c37a60b59d9cb38a640a3f6768323f528d708b1c32c9bb7bf3cb6.jpg) \nFig. 4 | Electrochemical properties and mechanism of $\\mathbf{NO_{3}}^{-}\\mathbf{RR}$ ammonia synthesis. a LSV curves of Fe/Cu-HNG, Fe-HNG, Cu-HNG, and HNG in an electrolyte of 1 M KOH and 0.1 M ${\\mathsf{K N O}}_{3}$ . b ${\\mathsf{N H}}_{3}$ FEs of Fe/Cu-HNG at varied potentials. c ${\\mathsf{N H}}_{3}$ yield rates of Fe/Cu-HNG, Fe-HNG, and Cu-HNG. d $\\mathsf{\\Pi}^{\\mathrm{1}}\\mathsf{H}$ NMR spectra of the electrolytes after electrocatalysis at $-0.3\\ensuremath{\\mathrm{V}}$ (vs RHE) using 0.1 M $^{15}\\mathrm{N}\\mathrm{H}_{4}^{+}$ or $0.01\\mathrm{M}^{14}\\mathrm{N}\\mathrm{H}_{4}^{+}$ in 1 M KOH as nitrogen source (1H NMR of the fresh electrolytes marked as $^{15}{\\mathrm{NO}}_{3}{}^{-}$ and \n$^{14}{\\mathsf{N O}}_{3}{}^{-}$ were provided as the controls). e Chronoamperometric curve of Fe/Cu-HNG at $-0.3\\ensuremath{\\mathrm{V}}$ vs RHE for $24\\mathsf{h}.$ f Cycling tests of Fe/Cu-HNG for the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}.$ g Comparison of the cathodic $\\mathsf{N H}_{3}$ EEs obtained using the Fe/Cu-HNG, Fe-HNG, and Cu-HNG catalysts. h Time-dependent concentration changes of ${\\mathsf{N O}}_{3}^{-}$ and ammonia during the $N O_{3}^{-}\\mathrm{RR}$ using $\\mathrm{Fe/Cu}$ -HNG. i DEMS analyses of nitrogen species during the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ (each cycle is one LSV scan from 0.1 to $-0.6\\:\\mathsf{V}$ vs RHE). \n\nslightly push the on-set potential to positive voltages and modestly increase the current density. Furthermore, by increasing metal loading, we synthesized homogenous diatomic catalysts (Fe/Fe-HNG and $\\mathrm{Cu/Cu\\mathrm{\\cdot}H N G)}$ . Supplementary Fig. 15 shows that dual sites further improve the catalytic activity. Notably, hetero-atomic dual-site catalyst $(\\mathrm{Fe/Cu\\mathrm{-}H N G})$ dramatically boosts the current density as compared to single-atom, homogenous diatomic catalysts, and a mechanic mixture of Fe/Fe-HNG and $\\mathrm{Cu/Cu-HNG}$ . In particular, the LSV curve of Fe/Cu-HNG exhibits a downward hump around $-0.3$ to $-0.5\\mathsf{V}$ vs RHE, which may result from the mass-transport-limited reduction of nitrates. To separate the contribution of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ from HER, we first measured the LSV in 1 M KOH without 0.1 M ${\\mathsf{K N O}}_{3}$ (Supplementary Fig. 16). Supplementary Fig. 17a shows that $\\mathsf{F e/C u\\mathrm{-}}$ HNG does not catalyze the HER well and delivers a nearly zero current density (at voltages higher than $-0.35\\mathsf{V})$ in a pure KOH solution, implying a low contribution of the HER to the total current density in the nitrate solution. Given that the HER and ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ are competitive reactions, we tentatively simulated the total reactions by simultaneously considering the HER with the Butler-Volmer equation and the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ with a mass-transport-limited LSV relation. Supplementary Fig. 17b shows that the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ accounts for $85.7\\%$ of total transferred electrons in the LSV measurement. \n\nTo confirm the LSV analytic results, we quantified the Faraday efficiency (FE) and yield rate of major products at varied voltages (Eqs1, 2 in Supplementary Methods) using standard curves of $\\mathsf{N H}_{3}$ , ${\\mathsf{N O}}_{3}{}^{-}$ , and ${\\mathsf{N O}}_{2}^{-}$ in Supplementary Figs. 18–20. In addition, a typical electrolysis curve and UV-vis testing curves confirm the increase in $\\mathsf{N H}_{3}$ (Supplementary Fig. 21). Figure 4b demonstrates that the FE of $\\mathsf{N H}_{3}$ initially increases with voltages and then decreases at high voltages. Specifically, $\\mathsf{F e/C u-H N G}$ enables the higher FE maximum of $\\mathsf{N H}_{3}$ $(92.51\\%)$ at a more positive voltage $(-0.3\\mathsf{V})$ than SACs Fe-HNG and CuHNG (Supplementary Figs. 22, 23), suggesting that diatomic catalysts have higher catalytic activity than SACs. The yield rates of ${\\mathsf{N H}}_{3}$ displayed in Fig. 4c further exemplify the much-enhanced activity and selectivity of $\\mathrm{Fe/Cu\\mathrm{-}H N G}$ as compared to Fe-HNG and Cu-HNG. Supplementary Table 3 summarizes the performance of previouslyreported catalysts. $\\mathsf{F e/C u-H N G}$ delivers high yield rates $\\left(1.08\\mathrm{mmol}\\mathrm{h}^{-1}\\mathrm{mg}^{-1}\\right.$ at $-0.5\\mathsf{V}$ vs RHE) and the ultralow energy consumption (8.76 Wh ${\\bf g}_{\\mathrm{NH3}}^{-1}{\\bf m}{\\bf g}^{-1})$ , demonstrating the high catalytic activity of diatomic sites. To determine the N source of the detected ammonia and assess the yield rate of $\\mathsf{N H}_{3}$ independently, a $\\mathsf{\\Pi}^{\\mathrm{1}}\\mathsf{H}$ nuclear magnetic resonance (NMR) test was employed to identify the $\\mathsf{N H}_{3}$ generation of $\\mathrm{Fe/Cu\\mathrm{-}H N G}$ in 1 M KOH with $0.1\\mathsf{M}\\ ^{15}\\mathsf{N O}_{3}^{-}$ or $^{14}{\\mathsf{N O}}_{3}^{-}$ (Fig. 4d and Supplementary Fig. 24). The typical $\\mathsf{\\Pi}^{1}\\mathsf{H}$ NMR spectra show two peaks due to $^{15}\\mathsf{N H}_{4}^{+}$ after electrolyzing $^{15}{\\mathsf{N O}}_{3}^{-}$ and three peaks related to $^{14}\\mathsf{N H}_{4}^{+}$ after electrolyzing $^{14}\\mathrm{NO}_{3}{}^{-}$ , confirming that the product ${\\mathsf{N H}}_{3}$ actually originates from the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ rather than contaminations62. The $^{15}\\mathsf{N H}_{3}$ and $^{14}\\mathsf{N H}_{3}$ yields were quantified by the averaged NMR peak areas. The calibration curves of $\\mathsf{\\Pi}^{\\mathrm{1}}\\mathsf{H}$ NMR spectra are in good agreement with UV-vis spectrophotometry measurements by colorimetric methods, demonstrating the reliability of the ammonia production efficiency test (Supplementary Fig. 24c). The FEs of byproducts about ${\\mathsf{N O}}_{2}^{-}$ and $\\mathsf{H}_{2}$ were shown in Supplementary Fig. 25. \n\nFigure 4e presents the chronoamperometric curve. Only a slight decrease in the current density is observed at a constant voltage. Continuous electrolysis for $24\\mathsf{h}$ (Fig. 4f) shows that the FEs and yield rates of $\\mathsf{N H}_{3}$ could be maintained at $90\\%$ and $-2400\\upmu\\mathrm{g}\\mathsf{h}^{-1}\\mathsf{c m}^{-1}$ , respectively, indicative of the electrochemical stability of $\\mathsf{F e/C u-H N G}$ catalysts. The HAADF-STEM analyses indicate that the diatomic sites in $\\mathsf{F e/C u-H N G}$ remain after $24\\mathsf{h}$ (Supplementary Fig. 26). The distribution of diatomic sites is similar to that prior to the test. Furthermore, the $k^{3.}$ weighted FT of $\\upchi(\\upkappa)$ -function in Supplementary Fig. 27 indicates the metal–N coordination and metal–metal remain similar as well. Supplementary Fig. 28 presents the LSV curves after $24\\mathsf{h}$ cycles. The voltage curve nearly overlaps with that prior to the test, suggesting the stability of the $\\mathrm{Fe/Cu\\mathrm{-}H N G}$ catalyst. Figure $_{4\\mathrm{g}}$ displays the energy efficiency (EE) of ${\\mathsf{N H}}_{3}$ production at varied concentrations (Eq-3 in Supplementary Methods). Owing to the lower overpotentials, Fe/CuHNG demonstrates much higher EEs than Fe-HNG and Cu-HNG. Supplementary Fig. 29 provides the influence of nitrate concentration on the ${\\mathsf{N H}}_{3}$ yield rates and FEs. The maximal FEs of ${\\mathsf{N O}}_{3}{}^{-}$ to ${\\mathsf{N H}}_{3}$ in the tested concentration range were $83-93\\%$ at $-0.3\\ensuremath{\\mathsf{V}}$ (vs RHE). Fe/CuHNG basically exhibits appreciable ammonia yield rates and high selectivity under varied nitrate concentrations. Figure 4h presents the concentration changes of ${\\mathsf{N O}}_{3}{}^{-}$ -N and ${\\mathsf{N H}}_{3}$ -N in H-cell batch electrolysis $(50\\mathrm{mL})$ . Fe/Cu-HNG $(1\\times1\\mathrm{cm}^{2})$ could almost completely reduce $200\\mathrm{mgL^{-1}\\ N O_{3}{\\bar{\\cdot}}N}$ and generate $189.2\\mathrm{mg}\\mathrm{L}^{-1}\\mathrm{\\sfNH}_{3}{\\cdot}\\mathrm{\\sfN}$ in 180 min. The sum of $N O_{3}^{-}\\cdot N$ and $\\mathsf{N H}_{3}$ -N is less than the initial ${\\mathsf{N O}}_{3}{}^{-}$ . The imbalance of N implies the existence of byproducts beyond $\\mathsf{N H}_{3}$ . \n\nTo decipher the intermediate byproducts and reaction pathway, we conducted a DEMS analysis for multiple cycles63,64 (see the schematic setup in Supplementary Fig. 30). During each cycle, the applied voltage was scanned from 0.1 to $-0.6\\:\\mathsf{V}$ (vs RHE). Figure 4i presents the mass-to-charge $\\mathbf{\\Pi}(\\mathbf{m}/z)$ ratio signals of 46, 30, 33, and 17, which correspond to ${\\mathsf{N O}}_{2}$ , NO, $\\mathsf{N H}_{2}\\mathsf{O H}$ , and $\\mathsf{N H}_{3},$ respectively. In addition to the major product $\\left(\\mathsf{N H}_{3}\\right)$ , NO has two orders of magnitude higher fraction than $\\mathsf{N H}_{2}\\mathsf{O H}$ and $\\mathsf{N O}_{2}$ . \n\nTheoretical analysis of $M O_{3}^{-}R R$ mechanism. There exist four possible pathways65,66 from ${\\mathsf{N O}}_{3}^{-}$ to ${\\mathsf{N H}}_{3}$ as shown in Supplementary Fig. 31. The DEMS measurements reveal the appearance of $\\mathsf{N O}_{2}$ , NO, and ${\\mathsf{N H}}_{2}{\\mathsf{O H}}$ , implying the most possible reaction pathway as illustrated in Fig. 5a. ${\\mathsf{N O}}_{3}^{-}$ is first adsorbed and discharged to form ${}^{*}\\mathsf{N O}_{3}$ which plays an important role because the poor affinity of ${\\mathsf{N O}}_{3}^{-}$ make the discharge difficult (Fig. 1b). Once absorbed, ${^{*}{\\mathsf{N O}}_{3}}$ is then hydrogenated to form ${}^{*}\\mathsf{N O}_{3}\\mathsf{H}$ , which is further attacked by protons to release ${\\sf H}_{2}{\\sf O}$ and yield ${^*{\\mathsf{N O}}}_{2}$ . The hydrogenation/dehydration cycle reduces ${^*{\\mathsf{N O}}}_{2}$ following the sequence: ${}^{*}\\mathrm{NO}_{2}\\mathrm{H}\\to{}^{*}\\mathrm{NO}\\to{}^{*}\\mathrm{NOH}\\to$ $\\mathrm{^{*}N H O H}\\rightarrow\\mathrm{^{*}N H_{2}O H}\\rightarrow\\mathrm{^{*}N H_{2}}\\rightarrow\\mathrm{^{*}N H_{3}}$ . The last step is the desorption of $\\mathsf{N H}_{3}$ off catalysts. \n\nTo understand the catalytic mechanism of the $\\mathsf{N O}_{3}\\mathsf{^{-}R R}$ , we first analyzed the structure and bonding of Fe/Cu-HNG and the influence of diatomic sites on the reaction routes. The geometric model of Fe/CuHNG is constructed from the EXAFS fitting result (Fig. 3k). Based on the molecular orbital (MO) theory understanding of “Y-type” $\\mathtt{M L}_{3}$ coordination (see discussion below Supplementary Fig. 32), we plotted the energy level splitting of $3d$ orbitals and their interactions with ${\\mathsf{N O}}_{3}$ in Fig. 5b. Figure 5c shows the calculated partial density of states (PDOS) of $d$ orbitals of $\\mathsf{F e/C u-H N G}$ . By integrating these $3d$ orbitals, we obtained the relative energy level of each d-orbital. Their relative positions are in agreement with the MO theory analysis in Fig. 5b. \n\nFurthermore, ${\\mathsf{N O}}_{3}$ on $\\mathsf{F e/C u-H N G}$ was modeled and analyzed. After geometric optimization, two oxygen atoms of ${\\mathsf{N O}}_{3}$ are attracted to $\\mathsf{F e/C u}$ dual sites. Figure 5d presents the interacting Wannier orbitals of ${\\mathsf{N O}}_{3}$ on $\\mathsf{F e/C u-H N G}$ , where the $3d_{x z}$ orbitals of $\\mathsf{F e/C u}$ form bonds with $2p_{x}$ orbitals of two oxygen of $\\mathsf{N O}_{3},$ which basically agree with the MO theory analysis. The binding energy of ${\\mathsf{N O}}_{3}$ on $\\mathsf{F e/C u-H N G}$ is $-1.19\\mathrm{eV}$ , which is stronger than that of single-atom sites $(-0.89\\mathrm{eV}$ for Fe-HNG and $-0.56\\mathrm{eV}$ for Cu-HNG, Supplementary Fig. 33). Strong adsorption of ${\\mathsf{N O}}_{3}$ could lower the energy barrier of the first discharge step $(^{*}+\\mathsf{N O}_{3}^{-}\\to\\mathsf{N O}_{3}^{*}+e^{-}.$ ). $N O_{3}^{-}\\mathrm{RR}$ differs from other electroreduction reactions (like the HER) because the planar symmetrical $(\\mathsf{D}_{3\\mathsf{h}})$ resonant structure of ${\\mathsf{N O}}_{3}^{-}$ and a strong hydrogen bond with water weaken the interaction between ${\\mathsf{N O}}_{3}^{-}$ and electrodes and thus limits electron transfer67,68. Once absorbed, negative polarization will accelerate the following hydrogenation and/or dehydration steps. Diatomic sites facilitate the first discharge step owing to the strong adsorption to ${\\mathsf{N O}}_{3}$ and however, may increase the energy barriers of the following steps because other intermediates may also strongly bind to the diatomic sites. \n\nAn efficient catalyst has to make a balance between the need for strongly adsorbing ${\\mathsf{N O}}_{3}$ and modestly adsorbing other intermediates. Furthermore, we analyzed the adsorption configuration and energy change of intermediates on diatomic sites. Supplementary Fig. 34 presents the optimized geometric models of ${^*{\\mathsf{N O}}_{3}}$ on these diatomic sites. The binding energy of ${^*{\\mathsf{N O}}_{3}}$ on Fe/Fe is $-1.89\\mathrm{eV}$ , which is stronger than that on $\\mathsf{C u}/\\mathsf{C u}\\left(-0.21\\mathrm{eV}\\right)$ because the Fe $3d_{z^{2}}$ and $3d_{x z}$ states have a higher level than those of Cu. In addition, it is noted that the Fe-O bond length of ${^*{\\mathsf{N O}}_{3}}$ on Fe/Fe is $1.823\\mathring{\\mathbf{A}}$ and the $\\mathtt{C u-O}$ bond length of ${^*{\\mathsf{N O}}_{3}}$ on $\\mathtt{C u/C u}$ is $1.945\\mathring{\\mathbf{A}},$ , implying that Fe interacts more strongly with intermediates than Cu. Supplementary Fig. 35 shows that most intermediates (except ${\\bf\\Pi}^{*}{\\bf N}{\\bf O}_{2}$ and $*_{\\mathsf{N H}_{2}}$ ) on Fe/Cu-HNG have medium binding energies as compared to them on Fe/Fe-HNG or $\\mathrm{cu/}$ Cu-HNG. It is understandable from the viewpoint of the d-band center that higher 3d orbitals of Fe than Cu may lead to stronger adsorption of most intermediates. The exceptions may mainly result from heteroatomic dimer configuration, which is also demonstrated by the electron density difference diagram in Fig. 5e. Fe transfers electrons to Cu, forming a polarized metal–metal dimer. Such a $\\mathsf{F e/C u}$ hetero-atomic dimer tunes the adsorption energy slightly off the general trend. \n\nSupplementary Fig. 36 presents the energy diagram at the equilibrium potential $\\mathrm{(U}=0.69\\:\\mathrm{V}.$ ). The second step $(^{*}\\mathsf{N O}_{3}\\to^{*}\\mathsf{N O}_{3}\\mathsf{H})$ has the highest energy barrier at equilibrium. When the voltage is polarized to $-0.3{\\ensuremath{\\mathsf{V}}}$ vs RHE (Fig. 5f), all the steps are downhill and the ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ occurs spontaneously. Therefore, the diatomic sites of Fe/ Cu-HNG appropriately reconcile the conflicting requirements on reducing energy barriers of both the initial discharge and following hydrogenation/dehydration steps, thereby dramatically enhancing the catalytic activity of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ from ${\\mathsf{N O}}_{3}{}^{-}$ to ${\\mathsf{N H}}_{3}$ . \n\nTo further elucidate the subsequent deoxygenation/hydrogenation, we calculated the crystal orbital Hamilton population (COHP) of NO molecules adsorbed on $\\mathsf{F e/C u}$ , Fe/Fe, and $\\mathtt{C u/C u}$ diatomic sites. The integrated COHP (ICOHP) in Fig. 6a can be used as a quantitative indicator of the N-O activation. Compared to a free NO molecule, NO molecules on Fe/Fe and $\\mathrm{{cu/Cu}}$ sites were activated to varying degrees. A relatively more positive ICOHP (−14.04 eV) of NO molecules on Fe/ Cu sites indicates a substantially weakened N-O bond because of the hetero-atomic structure. The activated N-O bond will facilitate the subsequent hydrogenation69. Operando DEMS measurements were conducted to verify the calculation results. Figure 6b shows that the NO yield ratio of $\\mathsf{F e/C u}$ to $\\mathtt{C u/C u}$ (or Fe/Fe) is around 2. Owing to the significant activation of Fe/Cu sites, the $\\mathsf{N H}_{2}\\mathsf{O H}/\\mathsf{N H}_{4}$ yield of $\\mathsf{F e/C u-}$ HNG is dramatically increased to 8–10 times higher than those of $\\mathrm{cu/}$ Cu or Fe/Fe catalysts. It should also be noted that the intensity scale of the ${\\mathsf{N H}}_{3}$ signal is two orders of magnitude higher than intermediates. These experimental and theoretical results confirm that $\\mathsf{F e/C u-H N G}$ could lower the energy barrier of ${\\mathsf{N O}}_{3}{\\mathsf{^{-}R R}}$ and activate NO molecules, leading to a high ${\\mathsf{N H}}_{3}$ yield and selectivity. \n\n![](images/b5cbd39d0b9c4c98e08719214af11a2ff6a6c761e9465e143d187402582a3be2.jpg) \nFig. 5 | Theoretical analyses of the catalytic mechanism. a Reaction pathway of the $N O_{3}^{-}\\mathsf{R R}$ and adsorption models of intermediates. b MO theory analysis of the splitting of metal $3d$ orbitals in a “Y-type” triple coordination and the interaction diagram between ${\\sf F e/C u3d}$ orbitals and $0p$ orbitals of ${\\mathsf{N O}}_{3}$ . c PDOS of ${\\sf F e/C u3d$ \n\norbitals. d Interacting Wannier orbitals of ${\\mathsf{N O}}_{3}$ on $\\mathsf{F e/C u}$ -HNG. e Electron density difference diagram in the sliced plane through the $\\mathsf{F e/C u}$ dimer. f Free energy diagram of each intermediate state on the metal atom sites in $\\mathsf{F e/C u}$ at $\\mathsf{U}=-0.3\\mathsf{V}$ vs RHE. \n\n![](images/1ced30ef4759a3e840dbe4e156506a7ebff5431d569c7b59bb31dffd8a5b87ae.jpg) \nReaction pathway \nFig. 6 | Theoretical and experimental analyses of N-O bond activation. a Crystal orbital Hamilton population $(\\mathrm{-COHP})$ and its integrated value (ICOHP) of NO\\* adsorption on different metal sites. b DEMS analyses of hydrogenation intermediates after the ${\\mathsf{N O}}^{*}$ adsorption step during the $N O_{3}^{-}\\mathsf{R R}$ . \n\n# Discussion \n\nElectrochemical reduction of nitrate to ammonia could reduce nitrate pollution and concurrently realize low-temperature and low-pressure ammonia synthesis. The slow kinetics of the nitrateto-ammonia reaction requires efficient catalysts. We synthesized a $\\mathsf{F e/C u}$ diatomic catalyst on holey nitrogen-doped graphene for nitrate reduction. $\\mathsf{F e/C u}$ is coordinated with two nitrogen atoms and one metal, which is similar to a “Y-type” $\\mathtt{M L}_{3}$ structure. Dual metal sites are bonded to form a metal–metal dimer with a local configuration of ${\\sf N}_{2}{\\sf F e}{\\cdot}{\\sf C u N}_{2}$ . Owing to the relatively strong adsorption to ${\\mathsf{N O}}_{3}$ , the resultant $\\mathsf{F e/C u}$ diatomic catalyst enhances the first rate-determining step, which is used to limit the approach of ${\\mathsf{N O}}_{3}{}^{-}$ to the cathode because of its poor affinity with electrodes. Operando DEMS and DFT calculations reveal the reaction pathway and conversion mechanisms from ${\\mathsf{N O}}_{3}^{-}$ to ${\\mathsf{N H}}_{3}$ . Compared to Fe/Fe and $\\mathrm{\\cu/Cu}$ configurations, Fe/Cu diatomic sites provide medium interactions toward most other intermediates and lower the overall energy barriers for the conversion from ${\\mathsf{N O}}_{3}^{-}$ to ${\\mathsf{N H}}_{3}$ . In brief, $\\mathsf{F e/C u}$ dual sites reconcile the opposite requirements of molecule-catalyst interaction and realize a low energy consumption and high activity synthesis of ammonia. Specifically, the resultant catalyst demonstrates the high activity of ${\\sim}38.5\\mathsf{m A c m}^{-2}$ (at $-0.3{\\ensuremath{\\mathsf{V}}}$ vs RHE) and selectivity of $92.51\\%$ FE for the reduction of ${\\mathsf{N O}}_{3}^{-}$ to ${\\mathsf{N H}}_{3}$ . The high ${\\mathsf{N H}}_{3}$ yield rate of $\\mathbf{1.08\\mmol\\h^{-1}m g^{-1}}$ is achieved at $-0.5\\ensuremath{\\mathsf{V}}$ . Overall, this work provides an alternative opportunity for both nitrate abatement and ammonia synthesis and expands the rational design of atomically dispersed catalysts and their applications. \n\n# Methods \n\n# Synthesis of catalyst \n\nGO were prepared via a modified Hummers method70. Typically, $3.0{\\mathrm{g}}$ graphite (Aladdin, $99.9\\%$ metals basis) and $_{18.0\\mathrm{g}}$ potassium permanganate $(\\mathsf{K M n O}_{4}$ , Sinopharm Chemical Reagents Co., Ltd., AR, $299.5\\%)$ 1 were slowly added into the solution of sulfuric acid $\\mathrm{(H}_{2}S O_{4}$ , Sinopharm Chemical Reagents Co., Ltd., GR, $95.0\\substack{-98\\%}$ , $360\\mathrm{mL}$ ) and phosphoric acid $\\mathrm{(H}_{3}\\mathrm{{PO}_{4}}$ , Sinopharm Chemical Reagents Co., Ltd., GR, $285.0\\%$ , $40\\mathrm{mL}$ ) under stirring. The mixture was heated to $50^{\\circ}\\mathrm{C}$ for $12\\mathsf{h}$ . After cooling down to room temperature by pouring onto ice $(\\sim400\\mathrm{mL},$ , a $3.0\\mathrm{mL}$ hydrogen peroxide solution $(\\mathsf{H}_{2}\\mathsf{O}_{2},$ Aladdin, AR, $30\\%$ in ${\\bf H}_{2}{\\bf O}_{\\mathrm{,}}^{\\mathrm{{\\rangle}}}$ ) was added dropwise. The resultant solid was washed sequentially by de-ionized water, hydrochloric acid (HCl, Sinopharm Chemical Reagents Co., Ltd., AR, $36.0\\substack{-38.0\\%}$ , and ethanol (Sinopharm Chemical Reagents Co., Ltd., AR, $299.5\\%$ ). Finally, the GO product was collected by vacuum freeze drying for $24\\mathsf{h}$ . Approximately $100\\mathrm{mg}$ GO was dispersed in an aqueous solution of $200\\mathrm{mL}$ nitric acid $({\\mathsf{H N O}}_{3},$ Sinopharm Chemical Reagents Co., Ltd., GR, $65.0\\substack{-68.0\\%}$ . After ultrasonicated for $3\\mathsf{h}$ , the dispersion was centrifuged and the solid phase was cleaned with de-ionized water. Iron chloride hexahydrate $(\\mathrm{FeCl}_{3}{\\cdot}6\\mathsf{H}_{2}0$ , Aladdin, $99\\%$ , $\\mathbf{9.0\\mg})$ , cupric chloride dihydrate $\\mathrm{(CuCl}_{2}{\\cdot}2\\mathrm{H}_{2}0,$ , Aladdin, AR, $6.0\\mathrm{mg},$ , and urea (Aladdin, $299.5\\%$ , 100 mg) were added in the re-dispersed GO suspension $(100\\mathrm{{mL}}$ , ${\\sim}2.0\\mathrm{mgL^{-1}}.$ ) and then ultrasonicated for $2\\mathfrak{h}$ . The mixed suspension was stirred for $12\\mathsf{h}$ and then transferred into a Teflon-lined autoclave. After hydrothermally treated at $180^{\\circ}\\mathrm{C}$ for $12\\mathsf{h}$ , a porous hydrogel was formed. The hydrogel was washed and freeze-dried. The resultant powder was annealed at $800^{\\circ}\\mathrm{C}$ for $2\\mathfrak{h}$ at a flowing gas of argon (Ar, Nanjing Special Gas Factory Co., Ltd., $99.999\\%$ , 100 sccm) and ammonia $(\\mathsf{N H}_{3}$ , Nanjing Special Gas Factory Co., Ltd., $99.999\\%$ , 50 sccm) to yield $\\mathsf{F e/C u-H N G}$ powder. \n\n# Materials characterization \n\nMorphologic and EDS mapping images were collected using a Zeiss Ultra 55 field emission scanning electron microscope. TEM analyses were conducted with an FEI Tecnai G2 20 microscope at $200\\mathsf{k V}.$ Atomic-resolution STEM-HAADF images and EELS spectra were obtained on an FEI Titan G2 60-300 STEM/TEM at $300\\mathsf{k V}$ with a field emission gun or on a JEOL Grand ARM with double spherical aberration correctors. XRD patterns were collected using Rigaku D/MAX 2500 V with Cu Kα radiation (1.5418 Å). XPS analysis was performed on an ESCALab MKII spectrometer with Mg Kα X-ray as the excitation source. Raman spectroscopic characterizations (Renishaw inVia Raman spectroscope) experiments were performed using a $514\\ensuremath{\\mathrm{nm}}$ laser. ${\\sf N}_{2}$ adsorption–desorption isotherms were recorded on an ASAP 2020 accelerated surface area and porosimetry instrument (Micromeritics), equipped with automated surface area. Barrett–Emmett–Teller methods were used to calculate the surface area. The XAS spectra of Fe and Cu K-edge were measured in a fluorescence mode at the beamline BL14W1 of the Shanghai Synchrotron Radiation Facility in China. The concentrations of ions were analyzed by a Shimadzu UV-3600 plus spectrophotometer. The detailed measuring processes are described in detail in the Supplementary Information. \n\n# Data availability \n\nAll data are available from the authors upon request. Source data are provided with this paper. \n\n# References \n\n1. Van Langevelde, P. H., Katsounaros, I. & Koper, M. T. M. Electrocatalytic nitrate reduction for sustainable ammonia production. Joule 5, 290–294 (2021). \n2. Suryanto, B. H. R. et al. Challenges and prospects in the catalysis of electroreduction of nitrogen to ammonia. Nat. Catal. 2, 290–296 (2019). \n3. Chen, J. G. et al. Beyond fossil fuel-driven nitrogen transformations. Science 360, 6611 (2018). \n4. Chen, G.-F. et al. Electrochemical reduction of nitrate to ammonia via direct eight-electron transfer using a copper–molecular solid catalyst. Nat. Energy 5, 605–613 (2020). \n5. Wang, J. et al. Electrocatalytic reduction of nitrate to ammonia on low-cost ultrathin $\\mathsf{C o O_{x}}$ nanosheets. ACS Catal. 11, 15135–15140 (2021). \n6. Wang, J. et al. Electrocatalytic nitrate/nitrite reduction to ammonia synthesis using metal nanocatalysts and bio-inspired metalloenzymes. Nano Energy 86, 106088 (2021). \n7. Yu, Y. et al. Promoting selective electroreduction of nitrates to ammonia over electron-deficient Co modulated by rectifying Schottky contacts. Sci. China Chem. 63, 1469–1476 (2020). \n8. Li, Y. et al. Molybdenum sulfide: A bioinspired electrocatalyst for dissimilatory ammonia synthesis with geoelectrical current. J. Phys. Chem. C. 121, 2154–2164 (2016). \n9. Wei, L. et al. Mild and selective hydrogenation of nitrate to ammonia in the absence of noble metals. ACS Catal. 10, 3618–3628 (2020). \n10. Wang, Z., Young, S. D., Goldsmith, B. R. & Singh, N. Increasing electrocatalytic nitrate reduction activity by controlling adsorption through PtRu alloying. J. Catal. 395, 143–154 (2021). \n11. Li, J. et al. Efficient ammonia electrosynthesis from nitrate on strained ruthenium nanoclusters. J. Am. Chem. Soc. 142, 7036–7046 (2020). \n12. McEnaney, J. M. et al. Electrolyte engineering for efficient electrochemical nitrate reduction to ammonia on a titanium electrode. ACS Sustain. Chem. Eng. 8, 2672–2681 (2020). \n13. Duca, M. & Koper, M. T. M. Powering denitrification: the perspectives of electrocatalytic nitrate reduction. Energy Environ. Sci. 5, 9726–9742 (2012). \n14. Niu, H. et al. Theoretical insights into the mechanism of selective nitrate-to-ammonia electroreduction on single-atom catalysts. Adv. Funct. Mater. 31, 2008533 (2021). \n15. Ye, S. et al. Elucidating the activity, mechanism and application of selective electrosynthesis of ammonia from nitrate on cobalt phosphide. Energy Environ. Sci. 15, 760–770 (2022). Energy Environ. Sci. 14, 6349–6359 (2021). \n17. Daiyan, R. et al. Nitrate reduction to ammonium: from CuO defect engineering to waste $\\mathsf{N O}_{\\mathsf{x}}$ -to- $\\cdot N H_{3}$ economic feasibility. Energy Environ. Sci. 14, 3588–3598 (2021). \n18. Jia, R. et al. Boosting selective nitrate electroreduction to ammonium by constructing oxygen vacancies in $\\mathsf{T i O}_{2}$ . ACS Catal. 10, 3533–3540 (2020). \n19. Garcia-Segura, S., Lanzarini-Lopes, M., Hristovski, K. & Westerhoff, P. Electrocatalytic reduction of nitrate: fundamentals to full-scale water treatment applications. Appl. Catal. B 236, 546–568 (2018). \n20. Fang, Z. et al. Porous two-dimensional iron-cyano nanosheets for high-rate electrochemical nitrate reduction. ACS Nano 16, 1072–1081 (2022). \n21. Choi, J. et al. Electroreduction of nitrates, nitrites, and gaseous nitrogen oxides: a potential source of ammonia in dinitrogen reduction studies. ACS Energy Lett. 5, 2095–2097 (2020). \n22. Gu, J. et al. Atomically dispersed $\\mathsf{F e}^{3+}$ sites catalyze efficient ${\\mathsf{C O}}_{2}$ electroreduction to CO. Science 364, 1091–1094 (2019). \n23. Jung, E. et al. Atomic-level tuning of Co-N-C catalyst for highperformance electrochemical ${\\sf H}_{2}{\\sf O}_{2}$ production. Nat. Mater. 19, 436–442 (2020). \n24. Luo, F. et al. P-block single-metal-site tin/nitrogen-doped carbon fuel cell cathode catalyst for oxygen reduction reaction. Nat. Mater. 19, 1215–1223 (2020). \n25. Zhou, M. et al. Single-atom $N i\\mathrm{-}N_{4}$ provides a robust cellular NO sensor. Nat. Commun. 11, 3188 (2020). \n26. DeRita, L. et al. Structural evolution of atomically dispersed Pt catalysts dictates reactivity. Nat. Mater. 18, 746–751 (2019). \n27. Liu, J. C. et al. Heterogeneous $\\mathsf{F e}_{3}$ single-cluster catalyst for ammonia synthesis via an associative mechanism. Nat. Commun. 9, 1610 (2018). \n28. Wang, Y. et al. Enhanced nitrate-to-ammonia activity on coppernickel alloys via tuning of intermediate adsorption. J. Am. Chem. Soc. 142, 5702–5708 (2020). \n29. Wu, Z.-Y. et al. Electrochemical ammonia synthesis via nitrate reduction on Fe single atom catalyst. Nat. Commun. 12, 2870 (2021). \n30. Li, P., Jin, Z., Fang, Z. & Yu, G. A single-site iron catalyst with preoccupied active centers that achieves selective ammonia electrosynthesis from nitrate. Energy Environ. Sci. 14, 3522–3531 (2021). \n31. Zhang, W. et al. Emerging dual-atomic-site catalysts for efficient energy catalysis. Adv. Mater. 33, 2102576 (2021). \n32. Khorshidi, A., Violet, J., Hashemi, J. & Peterson, A. A. How strain can break the scaling relations of catalysis. Nat. Catal. 1, 263–268 (2018). \n33. Nwaokorie, C. F. & Montemore, M. M. Alloy catalyst design beyond the volcano plot by breaking scaling relations. J. Phys. Chem. C. 126, 3993–3999 (2022). \n34. Darby, M. T., Stamatakis, M., Michaelides, A. & Sykes, E. C. H. Lonely atoms with special gifts: breaking linear scaling relationships in heterogeneous catalysis with single-atom alloys. J. Phys. Chem. Lett. 9, 5636–5646 (2018). \n35. Hannagan, R. T. et al. First-principles design of a single-atom-alloy propane dehydrogenation catalyst. Science 372, 1444–1447 (2021). \n36. Zhang, S. et al. High-performance supercapacitor of graphene quantum dots with uniform sizes. ACS Appl. Mater. Interfaces 10, 12983–12991 (2018). \n37. Zhao, X., Hayner, C. M., Kung, M. C. & Kung, H. H. Flexible holey graphene paper electrodes with enhanced rate capability for energy storage applications. ACS Nano 5, 8739–8749 (2011). \n38. Sun, H. et al. Three-dimensional holey-graphene/niobia composite architectures for ultrahigh-rate energy storage. Science 356, 599–604 (2017). universal electro atalytic hydroge evolution. i. Adv. 6, 6586 (2020). \n40. Yang, H. B. et al. Atomically dispersed Ni(i) as the active site for electrochemical ${\\mathsf{C O}}_{2}$ reduction. Nat. Energy 3, 140–147 (2018). \n41. Fei, H. et al. General synthesis and definitive structural identification of $\\mathsf{M N}_{4}\\mathsf{C}_{4}$ single-atom catalysts with tunable electrocatalytic activities. Nat. Catal. 1, 63–72 (2018). \n42. Ren, W. et al. Isolated diatomic Ni-Fe metal-nitrogen sites for synergistic electroreduction of CO2. Angew. Chem. Int. Ed. 58, 6972–6976 (2019). \n43. Chen, Y. et al. Atomic Fe dispersed on N-doped carbon hollow nanospheres for high-efficiency electrocatalytic oxygen reduction. Adv. Mater. 31, 1806312 (2019). \n44. Pan, Y. et al. A bimetallic Zn/Fe polyphthalocyanine-derived singleatom Fe- ${\\cdot}\\mathsf{N}_{4}$ catalytic site:A superior trifunctional catalyst for overall water splitting and Zn-air batteries. Angew. Chem. Int. Ed. 57, 8614–8618 (2018). \n45. Zeng, Z. et al. Orbital coupling of hetero-diatomic nickel-iron site for bifunctional electrocatalysis of $\\mathsf{C O}_{2}$ reduction and oxygen evolution. Nat. Commun. 12, 4088 (2021). \n46. Gan, G. et al. Ultrathin Fe-N-C single-atom catalysts with bifunctional active site for simultaneous production of ethylene and aromatic chlorides. Nano Energy 80, 105532 (2021). \n47. Wan, X. et al. Iron atom-cluster interactions increase activity and improve durability in Fe-N-C fuel cells. Nat. Commun. 13, 2963 (2022). \n48. Xu, J. et al. Organic wastewater treatment by a single-atom catalyst and electrolytically produced ${\\sf H}_{2}{\\sf O}_{2}$ . Nat. Sustain. 4, 233–241 (2021). \n49. Shang, H. et al. Engineering unsymmetrically coordinated $C u-S_{1}N_{3}$ single atom sites with enhanced oxygen reduction activity. Nat. Commun. 11, 3049 (2020). \n50. Xia, C. et al. General synthesis of single-atom catalysts with high metal loading using graphene quantum dots. Nat. Chem. 13, 887–894 (2021). \n51. Kawai, S. et al. Three-dimensional graphene nanoribbons as a framework for molecular assembly and local probe chemistry. Sci. Adv. 6, 8913 (2020). \n52. Cheng, H. et al. Atomically dispersed Ni/Cu dual sites for boosting the $\\mathsf{C O}_{2}$ Reduction Reaction. ACS Catal. 11, 12673–12681 (2021). \n53. Han, J. et al. Single-atom Fe- ${\\bf\\cdot N_{x}}$ -C as an efficient electrocatalyst for zinc-air batteries. Adv. Funct. Mater. 29, 1808872 (2019). \n54. Li, Y. et al. Synergistic effect of atomically dispersed Ni-Zn pair sites for enhanced ${\\mathsf{C O}}_{2}$ electroreduction. Adv. Mater. 33, 2102212 (2021). \n55. Ying, Y., Luo, X., Qiao, J. & Huang, H. “More is different:” synergistic effect and structural engineering in double‐atom catalysts. Adv. Funct. Mater. 31, 2007423 (2020). \n56. Han, X. et al. Atomically dispersed binary Co-Ni sites in nitrogendoped hollow carbon nanocubes for reversible oxygen reduction and evolution. Adv. Mater. 31, 1905622 (2019). \n57. Pan, Y. et al. Regulating the coordination structure of single-atom $F e\\mathrm{-}N_{\\mathrm{x}}C_{\\mathrm{y}}$ catalytic sites for benzene oxidation. Nat. Commun. 10, 4290 (2019). \n58. Wang, J. et al. Synergistic effect of well-defined dual sites boosting the oxygen reduction reaction. Energy Environ. Sci. 11, 3375–3379 (2018). \n59. Chen, J. et al. Dual single-atomic Ni- ${\\cdot}{\\mathsf{N}}_{4}$ and $\\mathsf{F e}\\cdot\\mathsf{N}_{4}$ sites constructing janus hollow graphene for selective oxygen electrocatalysis. Adv. Mater. 32, 2003134 (2020). \n60. Gu, J. et al. Synergizing metal-support interactions and spatial confinement boosts dynamics of atomic nickel for hydrogenations. Nat. Nanotechnol. 16, 1141–1149 (2021). \n61. Lu, X. et al. Bioinspired copper single-atom catalysts for tumor parallel catalytic therapy. Adv. Mater. 32, 2002246 (2020). \n62. Chen, F. Y. et al. Efficient conversion of low-concentration nitrate sources into ammonia on a Ru-dispersed Cu nanowire electrocatalyst. Nat. Nanotechnol. 17, 759–767 (2022). \n63. Yao, D. et al. In situ fragmented bismuth nanoparticles for electrocatalytic nitrogen reduction. Adv. Energy Mater. 10, 2001289 (2020). \n64. Wang, Y. et al. Unveiling the activity origin of a copper-based electrocatalyst for selective nitrate reduction to ammonia. Angew. Chem. Int. Ed. 59, 5350–5354 (2020). \n65. Hu, T. et al. Theoretical insights into superior nitrate reduction to ammonia performance of copper catalysts. ACS Catal. 11, 14417–14427 (2021). \n66. Liu, J.-X., Richards, D., Singh, N. & Goldsmith, B. R. Activity and selectivity trends in electrocatalytic nitrate reduction on transition metals. ACS Catal. 9, 7052–7064 (2019). \n67. Courtney, L. F., Yun, J. P., Ellen, M. M., Zachary, G. & Alison, R. F. A bioinspired iron catalyst for nitrate and perchlorate reduction. Science 354, 741–743 (2016). \n68. He, W. et al. Splicing the active phases of copper/cobalt-based catalysts achieves high-rate tandem electroreduction of nitrate to ammonia. Nat. Commun. 13, 1129 (2022). \n69. Niu, H. et al. A feasible strategy for identifying single-atom catalysts toward electrochemical NO-to-NH3 conversion. Small 17, 2102396 (2021). \n70. Daniela, C. et al. Improved synthesis of graphene oxide. ACS Nano 4, 4806–4814 (2010). \n\n# Acknowledgements \n\nThe authors acknowledge the financial support of the National Key R&D Program of China (No. 2020YFA0406104), the National Natural Science Foundation of China (Nos. 22075131), and the State Key Laboratory of Multiphase Complex Systems (No. MPCS-2021-A). The numerical calculations were carried out at the computing facilities in the HighPerformance Computing Center (HPCC) of Nanjing University. S.Z thanks Program B for Outstanding PhD candidate at Nanjing University. \n\n# Author contributions \n\nShu.Z. and H.Z. conceived and designed this work. Shu.Z., J.W., X.J., Z.L., and Z.S. synthesized materials and conducted characterizations. J.W. and P.W. carried out microscopic analyses. Y.W., Q.W. X.W., and H.W. conducted surface analyses and N quantification. Shu.Z. performed the DFT simulation. X.J., M.Z., Sha.Z., L.Y., L.D., and J.Z characterized and analyzed the X-ray adsorption data. J.L., H.Z., and Shu.Z. wrote the paper. H.Z. and Q.Z. supervises the work. All authors have discussed the results and commented on the manuscript. Shu.Z. and J.W. contributed equally to the work. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-023-39366-9. \n\nCorrespondence and requests for materials should be addressed to Qingshan Zhu, Huigang Zhang or Jun Lu. \n\nPeer review information Nature Communications thanks Huiyuan Zhu, Wenhui He and the other, anonymous, reviewer for their contribution to the peer review of this work. \n\nReprints and permissions information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 " + }, + { + "id": "10.1126_science.ade9637", + "DOI": "10.1126/science.ade9637", + "DOI Link": "http://dx.doi.org/10.1126/science.ade9637", + "Relative Dir Path": "mds/10.1126_science.ade9637", + "Article Title": "Stabilized hole-selective layer for high-performance inverted p-i-n perovskite solar cells", + "Authors": "Li, Z; Sun, XL; Zheng, XP; Li, B; Gao, DP; Zhang, SF; Wu, X; Li, S; Gong, JQ; Luther, JM; Li, ZA; Zhu, ZL", + "Source Title": "SCIENCE", + "Abstract": "P-i-n geometry perovskite solar cells (PSCs) offer simplified fabrication, greater amenability to charge extraction layers, and low-temperature processing over n-i-p counterparts. Self-assembled monolayers (SAMs) can enhance the performance of p-i-n PSCs but ultrathin SAMs can be thermally unstable. We report a thermally robust hole-selective layer comprised of nickel oxide (NiOx) nulloparticle film with a surface-anchored (4-(3,11-dimethoxy-7H-dibenzo[c,g]carbazol-7-yl)butyl)phosphonic acid (MeO-4PADBC) SAM that can improve and stabilize the NiOx/perovskite interface. The energetic alignment and favorable contact and binding between NiOx/MeO-4PADBC and perovskite reduced the voltage deficit of PSCs with various perovskite compositions and led to strong interface toughening effects under thermal stress. The resulting 1.53-electron-volt devices achieved 25.6% certified power conversion efficiency and maintained >90% of their initial efficiency after continuously operating at 65 degrees Celsius for 1200 hours under 1-sun illumination.", + "Times Cited, WoS Core": 300, + "Times Cited, All Databases": 311, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:001138559400027", + "Markdown": "# SOLAR CELLS Stabilized hole-selective layer for high-performance inverted p-i-n perovskite solar cells \n\nZhen $\\pmb{\\mathrm{Li}}_{\\dagger}$ , Xianglang Sun1, $^2\\dag$ , Xiaopeng Zheng3, $^4\\dag$ , Bo $\\pmb{\\mathrm{Li}}_{\\dagger}$ , Danpeng Gao1, Shoufeng Zhang1, Xin Wu1, Shuai Li1, Jianqiu Gong1, Joseph M. Luther3, Zhong’an $L i^{2\\times}$ , Zonglong Zhu1\\* \n\nP-i-n geometry perovskite solar cells (PSCs) offer simplified fabrication, greater amenability to charge extraction layers, and low-temperature processing over n-i- $\\cdot\\mathsf{p}$ counterparts. Self-assembled monolayers (SAMs) can enhance the performance of $p-i-n P S C S$ but ultrathin SAMs can be thermally unstable. We report a thermally robust hole-selective layer comprised of nickel oxide $(\\mathsf{N i O}_{\\mathsf{x}})$ nanoparticle film with a surface-anchored (4-(3,11-dimethoxy-7H-dibenzo[c,g]carbazol-7-yl)butyl)phosphonic acid (MeO-4PADBC) SAM that can improve and stabilize the $\\mathsf{N i O}_{\\mathsf{x}},$ /perovskite interface. The energetic alignment and favorable contact and binding between NiOx/MeO-4PADBC and perovskite reduced the voltage deficit of PSCs with various perovskite compositions and led to strong interface toughening effects under thermal stress. The resulting 1.53–electronvolt devices achieved $25.6\\%$ certified power conversion efficiency and maintained $>90\\%$ of their initial efficiency after continuously operating at 65 degrees Celsius for 1200 hours under 1-sun illumination. \n\nP hosphonic acid self-assembled monolayers (SAMs) with a carbazole core have enabled performance advances in perovskite solar cells (PSCs), for both singlejunction (1–4) and perovskite-based tandem solar cells (5–9), because of their high hole selectivity, fast hole transfer rate, and low interfacial trap state density (10–13). However, compared with conventional polymeric and metal oxide hole transporting materials, SAMbased PSCs have exhibited poorer thermal stability (14–18). The investigation of the device’s operational stability, with electrical bias under maximum power point (MPP) operation or at open-circuit voltage $(V_{\\mathrm{OC}})$ , under elevated temperatures $65^{\\circ}$ to $85^{\\circ}\\mathrm{C}$ is critical to improve the confidence in their stability and to meet the qualification of international stability standards (i.e., International Summit on Organic Photovoltic Stability (ISOS) and International Electrotechnical Commission 61215 standards) (19). Whereas most studies on the SAM-based PSCs have reported the operational stability at room temperature or enhanced the device’s durability under thermal stress by stabilizing perovskite surface and bulk (20, 21), the degradation effect of SAM-forming molecules under elevated temperature $(>65^{\\circ}\\mathrm{C})$ have rarely been discussed (fig. S1 and table S1). The thermal stability of SAM-forming molecules depends largely on their bonding to the selected substrates, as the bond between the anchoring group and the spacer of the molecule can be broken through temperature-induced desorption (22–25). \n\nWe report a new SAM, (4-(3,11-dimethoxy7H-dibenzo[c,g]carbazol-7-yl)butyl)phosphonic acid (MeO-4PADBC), which we anchored to the $\\mathrm{NiO_{x}}$ film to fabricate inverted p-i-n PSCs (fig. S2). The $\\mathrm{NiO_{x}/}$ MeO-4PADBC exhibited an optimal dipole moment and amenable surface for favorable contact with perovskite that resulted in an ideal energetic alignment, fast hole extraction, and low defect density. Such an interface configuration also immobilized the SAM molecules at the $\\mathrm{NiO_{x}/}$ perovskite interface and produced a robust hole-selective layer (HSL) for thermally stable PSCs that had thermal-degradation activation energy ${\\sim}3$ times greater than that for ITO/MeO-4PADBC. These synergetic effects enabled 1.53-electron volt (eV) p-i-n PSCs $V_{\\mathrm{OC}}$ of 1.19 V $95\\%$ of calculated potential) and a verified power conversion efficiency (PCE) of $25.6\\%$ . 1.68- and 1.80-eV– wide bandgap perovskite composition devices also showed encouraging PCEs of 22.7 and $20.1\\%$ , respectively. Moreover, 1.53-eV PSCs using $\\mathrm{NiO_{x}}$ /MeO-4PADBC HSL maintained ${>}90\\%$ of initial efficiency in long-term operational stability tests under $65^{\\circ}\\mathrm{C}$ for 1200 hours, and extrapolation of the Arrhenius energy indicates that the solar cells should maintain $80\\%$ of initial efficiency for more than 10 months at $25^{\\circ}\\mathrm{C}$ . \n\n# SAM design and synthesis \n\nModulating the terminal functional group is an effective way to tune the interfacial interactions between SAMs and perovskite. For example, the introduction of two methoxy groups (OMe) into [2-(9H-carbazol-9-yl)ethyl]phosphonic acid (2PACz) enabled a new SAM, [2-(3,6- dimethoxy-9H-carbazol-9-yl)ethyl]phosphonic acid (MeO-2PACz), which improved the interfacial contact and enabled a higher efficiency of p-i-n PSC compared with 2PACz (10). Nonetheless, the OMe substitution on the carbazole core also caused a decrease in dipole moment from ${\\sim}2.0\\mathrm{D}$ of 2PACz to ${\\sim}0.2\\mathrm{D}$ of MeO-2PACz, which in turn led to the offset between the highest occupied molecular orbital (HOMO) of the SAM molecule and the valence band maximum (VBM) of the perovskite (10, 26). This phenomenon can be ascribed to high planarity and symmetry of the carbazole structure; the incorporation of two OMe groups with opposite directions of dipole moment resulted in a net molecular dipole moment of MeO-2PACz close to zero (Fig. 1A). We addressed this issue by using a non-coplanar screw-shaped dibenzo[c,g]carbazole (DBC) unit as the core to reduce the negative effect on the dipole moment when introducing OMe groups, affording a new SAM of MeO-4PADBC (Fig. 1B). Density functional theory (DFT) calculations verified that MeO-4PADBC only has a slightly decreased dipole moment (2.4 D) compared with that of (4-(7H-dibenzo[c,g]carbazol7-yl)butyl)phosphonic acid (4PADBC) (2.9 D), which is quite different from those obtained for carbazole-based SAMs (figs. S3 and S4). \n\nThe synthetic route of MeO-4PADBC is shown in fig. S5, along with structural characterizations presented in figs. S6 to S9. The calculated HOMO and lowest unoccupied molecular orbital distributions are shown in fig. S10, with values of −4.91 and −1.15 eV, respectively. To gain a deeper insight of the SAM molecule structure, we grew a single crystal of 3,11-dimethoxy-7H-dibenzo[c,g] carbazole (MeO-DBC, CCDC number: 2279245), which lacks the anchoring group that would disrupt intermolecular interactions. As shown in fig. S11, A and B, two naphthalene rings are located on different sides of the pyrrole ring and exhibit a dihedral angle of $12.44^{\\circ}{}_{;}$ , which greatly reduces the planarity and symmetry of the skeleton structure to enable a negligible effect on the dipole moment when introducing OMe groups. Moreover, the MeO-DBC core had a slipped $\\pi$ -stacked packing motif with strong $\\mathrm{C-H}\\cdots\\pi$ (2.72 Å) and $\\pi-\\pi$ (3.79 Å) interactions (fig. S11C), which could induce a highly ordered one-dimensional assembly that favors a dense, tilted, highly ordered monolayer on the substrate (fig. S11D) (9, 27, 28). \n\nWe then calculated the interfacial binding energies between SAMs and perovskite, showing that MeO-4PADBC has a stronger binding with perovskite with a total binding energy $(E_{b})$ of −7.19 eV, compared with that of $-5.27\\mathrm{eV}$ for MeO-2PACz (fig. S12). The main electrostatic interaction of the calculated SAMs is the O atoms from OMe groups with the Pb from (right) UPS spectra in the valence band (VB) region. (F) Schematic representation of the band edge positions of the studied HSLs based on values from UPS measurements, referenced to the vacuum level. EF and EVAC represent Fermi and vacuum levels, respectively. EVBM and ECBM represent the energy of valence band maximum and conduction band minimum, respectively. \n\n![](images/4a9fa2c8ffa5ee612c2eeb2d4e01e674f7d5360c031b141e3562931413405cd6.jpg) \nFig. 1. Molecular structure and electrical properties of HSLs. Molecular structure and side view of (A) ${\\mathsf{M e O}}{\\cdot}2\\mathsf{P A C}z$ and (B) MeO-4PADBC. (C) Schematic illustration of MeO-4PADBC anchoring on $\\mathsf{N i O}_{\\mathsf{x}}$ nanoparticle as the HSL in PSC. (D) FTIR spectra of MeO-4PADBC and NiOx/MeO-4PADBC. (E) UPS spectra of ITO substrates covered by $\\mathsf{N i O}_{\\mathsf{x}}$ , MeO-4PADBC, and NiOx/MeO-4PADBC. (Left) UPS spectra around the secondary electron cutoff (WF, work function); \n\nperovskite, however MeO-4PADBC has a more energetically favorable contact with perovskite compared with MeO-2PACz, which can be ascribed to the more concentrated electron distribution of the coordinated OMe group on MeO-4PADBC than that on MeO-2PACz (fig. S13). Moreover, Bader charge analysis also suggests a stronger Pb-O interaction between MeO-4PADBC and perovskite with a shorter calculated interaction length of $4.7\\mathrm{\\AA}$ than that of MeO-2PACz of $4.9\\mathrm{~\\AA~}$ (fig. S14), which can be further confirmed by the results of $^{1}\\mathrm{H}$ NMR spectra of the SAMs in DMSO- $\\cdot d_{\\delta}$ with or without mixing with $\\mathrm{PbI_{2}}$ (fig. S15). \n\n# Hole-selective layer applications \n\nWe compared MeO-4PADBC SAM and $\\mathrm{NiO_{x}/}$ MeO-4PADBC as the HSLs for p-i-n PSCs (Fig. 1C). Fourier-transform infrared (FTIR) spectra were then collected by scraping the MeO-4PADBC and $\\mathrm{NiO_{x}/}$ MeO-4PADBC films off the substrates to amplify the signal, in which the $\\mathrm{P{=}O(1169\\ c m^{-1})}$ and P-OH (1035 and $950\\mathrm{cm}^{-1}.$ ) absorption peaks show a clear shift (Fig. 1D), indicating the formation of a chemical bond (29). This can be further confirmed by the changes of the $\\mathrm{Ni}2p$ core level of $\\mathrm{NiO_{x}}$ and $\\mathrm{NiO_{x}}/$ MeO-4PADBC films deposited on the indium tin oxide (ITO) substrates obtained by x-ray photoelectron spectroscopy (XPS) spectra (fig. S16). The crystal structure and absorbance of representative perovskite film with a composition of $\\mathrm{Cs_{0.05}F A_{0.85}M A_{0.1}P b I_{3}}$ on both substrates remained unchanged (figs. S17 and S18). However, the perovskite deposited on ITO $\\mathrm{NiO_{x}}/$ MeO-4PADBC substrate had larger crystal domains than those on control substrates (fig. S19). This is because of the denser anchoring of SAM molecules onto the $\\mathrm{{IIO/NiO_{x}}}$ substrate through more robust tridentate binding absorption, which can not only reduce the surface roughness of ITO/ $\\mathrm{NiO_{x}}$ substrate (30–32) (figs. S20 and S21), but also lead to a more hydrophobic surface (fig. S22) and stronger interaction between perovskite and SAM molecules (33–35). These synergetic effects contribute to facilitating the perovskite crystal nucleation and growth, thus enhancing the perovskite crystallization. \n\nWe further used ultraviolet photoelectron spectroscopy (UPS) to assess the energetic alignment of different substrates relative to perovskite absorbers with different bandgaps (1.53, 1.68, and $1.8~\\mathrm{eV}$ , see Fig. 1E and fig. S23), and the results are summarized in Fig. 1F. The HOMO energy levels are $-5.34\\mathrm{eV}$ for ITO/MeO-4PADBC and −5.45 eV ITO $\\mathrm{\\DeltaNiO_{x}/}$ MeO-4PADBC, respectively, and the work function $(\\Phi)$ of the latter substrate is deeper than that of the former one $\\cdot^{-4.95}$ versus $-4.90\\ \\mathrm{eV},$ , indicative of better energetic alignment with different perovskite absorbers. However, upon application of the carbazole-based SAM molecules onto the ITO/ $\\mathrm{NiO_{x}}$ surface, the ITO/NiOx/MeO-2PACz system exhibited an upward shift of the $\\Phi$ , in contrast to the ITO/NiOx/2PACz substrate (26, 36) (fig. S24). This phenomenon can be attributed to the incorporation of OMe groups on 2PACz, which considerably reduced the dipole moment. This reduction can be explained by the highly planar carbazole motif, as discussed earlier. Timeresolved photoluminescence (TRPL) decay data showed a decreased carrier lifetime from 925.5 ns for the perovskite on ITO to 42.9 and 32.3 ns for the perovskite on ITO/MeO-4PADBC and ITO/NiOx/MeO-4PADBC, respectively, indicating a more facilitated hole extraction resulted \n\nby the ITO/NiOx/MeO-4PADBC substrate (fig. \nS25 and table S2). \n\nSolar cell performance and characterization We further evaluated the photovoltaic performance of PSCs with a p-i-n device configuration: glass/ITO/HSL/perovskite/two-dimensional (2D) passivation layer $/\\mathrm{C}_{60}/$ /bathocuproine (BCP)/ Ag (Fig. 2A). The 2D passivation layer was a mixture of 4-trifluorophenylethylammonium iodide ( $\\mathrm{\\tilde{CF_{3}}}$ -PEAI) and methylammonium iodide (MAI) with an optimal volume ratio of 3:1 (4). The cross-section scanning electron microscopy (SEM) images of the PSC (1.53 eV) showed a thickness of $\\sim715\\ \\mathrm{nm}$ for the perovskite films (fig. S26). The device with $\\mathrm{NiO_{x}/M e O-}$ 4PADBC as the HSL (1.53 eV) showed negligible hysteresis and had a high verified PCE of $25.6\\%$ for a mask area of $0.0414\\mathrm{cm}^{2}$ (figs. S27 and S28), with a $V_{\\mathrm{OC}}$ of $1.19\\mathrm{V}$ , a short-circuit current density $(J_{\\mathrm{SC}})$ of $25.4\\mathrm{mAcm^{-2}}$ , and a fill factor (FF) of $84.6\\%$ , which outperformed the MeO-4PADBC–based device $\\mathrm{\\DeltaPCE}=24.2\\%$ with $V_{\\mathrm{OC}}=1.16\\:\\mathrm{V}$ , $J_{\\mathrm{SC}}=25.4~\\mathrm{mA~cm^{-2}}$ , and $\\mathrm{FF=}$ $82.1\\%$ ). The $\\mathrm{NiO_{x}}$ control device without a SAM only showed a PCE of $21.6\\%$ , attributed to a mismatch of energetic alignment and high surface defect density on $\\mathrm{NiO_{x}}$ film (37, 38) (Fig. 2B). Moreover, we have also conducted HSL engineering by applying carbazole-based SAM anchoring on $\\mathrm{NiO_{x}}$ . The $V_{\\mathrm{OC}}$ of the $\\mathrm{NiO_{x}/M e O-}$ 2PACz–based device (1.15 V) is lower than that of the device with $\\mathrm{NiO_{x}/2P A C z}$ (1.17 V) (figs. S29, A and B). This issue was addressed by replacing the carbazole motif with a nonplanar DBC core in SAM molecules (fig. S29, C and D). To better understand the mechanism of the improved $V_{\\mathrm{OC}}$ and FF with the use of $\\mathrm{NiO_{x}/}$ MeO-4PADBC as HSL, we further conducted the FF loss (supplementary text and fig. S30) and $V_{\\mathrm{OC}}$ loss calculations (supplementary text, fig. S31, and table S3). We observed that the improved $V_{\\mathrm{OC}}$ and FF of $\\mathrm{NiO_{x}}/$ /MeO-4PADBC were mainly attributed to the suppressed nonradiative recombination loss, indicating reduced trap state density at the HSL/perovskite interface. \n\nOur $\\mathrm{NiO_{x}}$ /MeO-4PADBC strategy also worked effectively for 1.68- and 1.80-eV PSCs, resulting in PCEs of 22.7 and $20.1\\%$ , respectively (Fig. 2C, fig. S32, and table S4). Steady-state power output (SPO) confirmed the reliability of three bandgap devices, with stabilized PCEs of 25.5, 22.3, and $19.5\\%$ for 1.53-, 1.68- and 1.80-eV, respectively (Fig. 2D). Additionally, the calculated $J_{\\mathrm{SC}}$ values from external quantum efficiency (EQE) of the champion devices were consistent with those extracted from the current density-voltage (J-V) measurements (fig. S33), and the derivatives of EQE spectra can further confirm the perovskite bandgaps applied here (fig. S34). We further presented the EQE with internal quantum efficiency (IQE) results of representative 1.53-eV device with HSLs of $\\mathrm{NiO_{x},}$ MeO-4PADBC, and $\\mathrm{NiO_{x}}/$ /MeO \n\n4PADBC in fig. S35. The IQE between $550\\mathrm{nm}$ to $700~\\mathrm{nm}$ is spectrally flat and approaches nearly $100\\%$ for both of MeO-4PADBC and $\\mathrm{NiO_{\\mathrm{{x}}}/M e O}$ -4PADBC–based devices, indicating efficient charge collection and transfer at the perovskite interface achieved by the incorporation of SAM (12, 39). \n\nThe defect density profiles were then studied to identify enhanced photovoltaic performance through the space charge limit current (SCLC) method (fig. S36). The hole-only devices with $\\mathrm{NiO_{x}/}$ MeO-4PADBC showed the lowest defect density of $1.96{\\times}10^{15}\\mathrm{cm}^{-3}$ , compared with those with MeO-4PADBC $(2.91{\\times}10^{15}\\ \\mathrm{cm^{-3}})$ and $\\mathrm{NiO_{x}}$ $(3.81\\times10^{15}~\\mathrm{cm}^{-3},$ ). In addition, the decreased slope of the light intensity dependence $V_{\\mathrm{OC}}$ plot for $\\mathrm{NiO_{x}/}$ MeO-4PADBC-based devices supported a reduced interfacial trap density at the HSL/perovskite interface (40) (fig. S37). We note that PSCs based on $\\mathrm{NiO_{x}/}$ MeO-4PADBC further demonstrated a lower leakage current than those on other HSLs (fig. S38), which we attributed to the compact $\\mathrm{NiO_{x}}$ layer preventing the perovskite from contacting ITO through the pinholes in the ultrathin SAM layer. These results demonstrated that the $\\mathrm{NiO_{x}/}$ MeO-4PADBC HSL effectively increased the $V_{\\mathrm{OC}}$ of the PSCs. \n\nTo quantify the interface losses, quasi-Fermi level splitting (QFLS) analysis for partial cell stacks was conducted. A laser wavelength of ${375}\\mathrm{nm}$ was used to illuminate a PSC with 1-sun equivalent intensity by accommodating the generated current near $J_{\\mathrm{SC}}$ under a standard solar simulator (41, 42) (supplementary text, fig. S39). As shown in Fig. 2E, the QFLS of $\\mathrm{ITO}/\\mathrm{NiO}_{\\mathrm{x}}$ /MeO-4PADBC/perovskite stack was comparable to the glass/perovskite stack, with implied $V_{\\mathrm{OC}}$ of 1.17 V versus 1.18 V for 1.53-eV perovskite film, 1.26 V versus 1.27 V for 1.68-eV perovskite film, and $1.35\\mathrm{V}$ versus $\\mathrm{1.36~V}$ for 1.80-eV perovskite film, respectively. These results indicated a low voltage loss on the interface between $\\mathrm{NiO_{x}}$ MeO-4PADBC and perovskites. \n\nWe further performed the QFLS measurements on the ITO/HSL/perovskite/passivation layer/electron-transporting layer (ETL) stacks (Fig. 2F), with the $V_{\\mathrm{OC}}\\mathrm{s}$ of the PSCs listed as a comparison. The differences between the QFLS of PSCs on ITO/ $\\mathrm{NiO_{x}/}$ MeO-4PADBC and the $V_{\\mathrm{OC}}$ extracted from related $J_{-}V$ measurements were comparable, demonstrating spatially flat Fermi levels throughout the device and low energy offset on the HSL for carrier extraction (27, 28). It is noteworthy that the $V_{\\mathrm{OC}}$ of our 1.53-eV devices (1.19 V) reached $95\\%$ of their calculated potential and the $V_{\\mathrm{OC}}$ of our 1.68-eV $(1.25{\\mathrm{~V}})$ and 1.80-eV (1.34 V) devices also approached $90\\%$ of the calculated potential (Fig. 2G). \n\n# PSC stability studies \n\nPrevious reports have demonstrated that SAMs desorb under thermal stress from the anchored substrate (29, 30), but few effective solutions to this problem have been explored. To estimate the thermal stability of the $\\mathrm{ITO/NiO_{x}/M e O\\mathrm{-}}$ 一 4PADBC substrate, we applied Kelvin probe force microscopy (KPFM) to record the surface potential evolution of the SAM under heat treatment by taking pristine ITO/MeO-4PADBC as a reference. Before thermal aging, the ITO/ MeO-4PADBCand ITO/NiOx/MeO-4PADBC substrates both exhibited relatively uniform surface potential with a narrow contact potential distribution (CPD) of $\\mathrm{\\sim}40~\\mathrm{mV}$ , indicating that the SAM molecules were densely packed onto both of ITO and $\\mathrm{NiO_{x}}$ surfaces (Fig. 3, A and B). After aging on a hotplate at $65^{\\circ}\\mathrm{C}$ for 1200 hours, the $\\mathrm{NiO_{x}}$ MeO-4PADBC substrate displayed negligible CPD changes, whereas the ITO/MeO4PADBC CPD value increased to $\\mathrm{\\sim}70\\mathrm{mV}$ (Fig. 3, C and D). We propose that the fluctuations of CPD for the ITO/MeO-4PADBC substrate could be attributed to desorption, morphological changes under thermal stress, or both. \n\n![](images/6de09cb9301f697d9d5cd958157c86b284d9731742bfc45941209a9bbb4678bf.jpg) \nFig. 2. Photovoltaic performance of PSCs with different HSLs. (A) Schematic absorbers. (E) QFLS in the case of three bandgaps of perovskite with different illustration of p-i-n PSC. (B) $J-V$ curves of the best-performing 1.53 eV devices with HSLs. (F) Comparison of the $V_{\\mathrm{OC}}$ of actual PSCs with the corresponding QFLS $\\mathsf{N i O}_{\\times},$ , MeO-4PADBC, and NiOx/MeO-4PADBC as HSL. (C) J-V curves of the best- of representative layer stacks. (G) Comparison of the $V_{\\mathrm{OC}}$ with different performing NiOx/MeO-4PADBC-based devices with bandgaps of 1.53, 1.68, and bandgaps of devices from the literature to our work. The line represents the 1.80 eV (Rev., reverse scan; For., forward scan). (D) SPO at the MPP for the best- $V_{\\mathrm{OC}}$ extracted from calculated potential. The wide-bandgap region refers to 1.6 to performing NiOx/MeO-4PADBC-based PSCs with three bandgaps of perovskite $1.9\\ \\mathrm{eV}$ in the figure. \n\nTo further explore the binding ability of SAM to the substrate under heating, DFT simulations were conducted to investigate the binding energies between MeO-4PADBC and ITO or $\\mathrm{NiO_{x}}$ substrate at $300\\mathrm{~K~}$ $({\\sim}27^{\\circ}\\mathrm{C})$ and $340\\mathrm{~K~}$ $({\\sim}67^{\\circ}\\mathrm{C})$ (Fig. 3, E and F). MeO-4PADBC had a higher binding energy with $\\mathrm{NiO_{x}}$ $(-22.4~\\mathrm{eV})$ than with ITO $\\mathrm{-}16.7\\mathrm{eV})$ at $300\\mathrm{K}$ , suggesting a stronger bonding strength on the $\\mathrm{NiO_{x}}$ film. This difference was attributed to the higher density of hydroxyl groups on the $\\mathrm{NiO_{x}}$ surface than on the ITO, which is critical to the chemisorption of SAM on the metal oxide (43, 44). The tridentate binding between SAM and $\\mathrm{NiO_{x}}$ was stronger than the bidentate binding between SAM and ITO (29, 45). At $340~\\mathrm{K},$ , the binding energy between SAM and ITO decreased from −16.7 to $-11.6\\ \\mathrm{eV}.$ , but that between MeO-4PADBC and $\\mathrm{NiO_{x}}$ film showed minor changes $(-20.3\\ \\mathrm{eV},$ . These results indicated that MeO-4PADBC on the $\\mathrm{NiO_{x}}$ film is more robust against thermal stress compared with MeO-4PADBC on bare ITO. \n\n![](images/15d35fa1fc053f156914989a858f480a7e51954044ef0ad6315c827f4b239064.jpg) \nFig. 3. Analysis of the degradation mechanism of PSCs. (A to D) Surface potential images obtained by scanning Kelvin probe microscopy (scale bar $500~\\mathsf{n m}$ ) of the HSLs before and after aging at $65^{\\circ}\\mathrm{C}$ for 1200 hours. At the bottom of the figure are the statistical potential distributions of film surfaces. (E) DFT calculation of the binding energy of MeO-4PADBC with ITO and $\\mathsf{N i O}_{\\mathsf{x}}$ . (F) Binding energies $(\\boldsymbol{E_{b}})$ of MeO-4PADBC with ITO and with $\\mathsf{N i O}_{\\times}$ at the temperatures of 300 and $340~\\mathsf{K}.$ \n\nThermal accelerated aging measurements were conducted to evaluate the reliability of SAM-based PSCs. To avoid the influence of the 2D capping layer, the encapsulated devices without top passivation were prepared for stability testing. The initial $J{-}V$ curves and photographs of the encapsulated devices are shown in fig. S40 and S41, respectively. The PSCs were operated under constant 1-sun illumination at fixed resistance loads near the MPP with the temperature ranging from \n\n$25^{\\circ}$ to $100^{\\circ}\\mathrm{C}_{\\mathrm{i}}$ , following the ISOS-L-2I procedure (19). The MeO-4PADBC-based devices degraded to 85 and $65\\%$ of starting PCEs after 1200 hours at $25^{\\circ}\\mathrm{C}$ and $65^{\\circ}\\mathrm{C}_{\\mathrm{i}}$ , respectively (Fig. 4A). When the aging temperature increased to $85^{\\circ}\\mathrm{C},$ only $47\\%$ of its initial PCE was retained after 800 hours. The $\\mathrm{NiO_{x}}$ devices retained 85 and $65\\%$ of initial PCEs at $65^{\\circ}$ and $85^{\\circ}\\mathrm{C},$ respectively, after 1200 hours (Fig. 4B). However, the $\\mathrm{NiO_{x}/}$ MeO-4PADBC-based devices retained 90 and $74\\%$ of initial PCEs after 1200 hours at $65^{\\circ}$ and $85^{\\circ}\\mathrm{C}$ , respectively (Fig. 4C), which was consistent with the degradation analysis in Fig. 3. Both devices based on $\\mathrm{NiO_{x},}$ MeO-4PADBC, or $\\mathrm{NiO_{x}/}$ MeO-4PADBC as HSL showed a more obvious downward trend when the aging temperature was raised to $100^{\\circ}\\mathrm{C}.$ . For a more comprehensive evaluation of the thermal stability of our $\\mathrm{NiO_{x}/}$ MeO4PADBC strategy, we further applied the PSCs with top passivation to conduct the operational stability at $65^{\\circ}\\mathrm{C}$ for 500 hours (fig. S42). The devices presented a slightly improved stability compared with the device without passivation at the same time stage, which maintained $96\\%$ of its initial PCE. This may be due to the higher hydrophobic surface brought by the $\\mathrm{CF_{3}}$ -PEAI passivation (46). \n\nWe then determined the activation energy $\\left(E_{\\mathrm{a}}\\right)$ of the temperature-dependent degradation of our PSCs with different HSLs according to a previously reported method (supplementary text) (47). The $E_{a}$ value of $\\mathrm{NiO_{x}}$ MeO-4PADBC– based devices $(0.389\\pm0.022~\\mathrm{eV})$ was almost three times higher than that of MeO-4PADBC– based devices $\\mathrm{0.150\\pm0.017\\mathrm{eV}},$ ). The lifetime acceleration factor (AF) of each temperature can be obtained from $E_{a}$ (Fig. 4D), from which it can be estimated that PSCs with $\\mathrm{NiO_{x}}$ /MeO-4PADBC HSL could retained $80\\%$ of its initial PCE at room temperature after 7567 hours operation, without top passivation treatment. \n\n# Conclusions \n\nWe have demonstrated an efficient and stabilized HSL with greatly improved thermal stability for high efficiency SAM-containing inverted p-i-n PSCs. Rational molecular structure design of MeO-4PADBC and in-depth analysis revealed that optimal dipole moment and favorable contact with perovskite are the keys to ideal energy alignment and fast hole extraction to improve the device efficiency and stability. Moreover, the anchoring of MeO4PADBC SAM molecules on the $\\mathrm{NiO_{x}}$ film can form a stronger tridentate bond with $\\mathrm{NiO_{x},}$ which effectively reduces the voltage loss and further maintains a strong fixation effect under thermal stress. Our study provides theoretical guidance for the design of efficient and stable HSL and paves the path for facile access to commercially available inverted p-i-n PSCs. \n\n![](images/61b823f512a52ab83f0112d39ed4d5e04b311651503436a59a00a4432b4758fb.jpg) \nFig. 4. Long-term stability assessment of PSCs under different temperatures. (A to C) Operational stability of PSCs with HSL of (A) MeO-4PADBC, (B) $\\mathsf{N i O}_{\\times}$ and (C) $\\mathsf{N i O}_{\\mathrm{x}}/\\mathsf{M e O-}\\mathsf{4P A D B C}$ at temperatures of $25^{\\circ}$ $65^{\\circ}$ , 85°, and $100^{\\circ}\\mathsf{C}$ , respectively. (D) Natural logarithm of slow degradation rate $(k_{s l o w})$ versus $1/k_{B}\\top$ \nobtained from biexponential fits, where $k_{B}$ is Boltzmann’s constant and T is aging temperature. The dashed line comes from the linear fits to extract the $E_{a}$ from each exponential (left); and natural logarithm of AF versus $1/k_{B}\\mathsf{T}$ . Standard operating condition for AF value calculation refers to 1-sun illumination at $25^{\\circ}\\mathrm{C}$ (right). \n\n# REFERENCES AND NOTES \n\n1. Q. Jiang et al., Nature 611, 278–283 (2022). \n2. Q. Tan et al., Nature 620, 545–551 (2023). \n3. S. Zhang et al., Science 380, 404–409 (2023). \n4. X. Zheng et al., Nat. Energy 8, 462–472 (2023). \n5. H. Chen et al., Nature 613, 676–681 (2023). \n6. X. Y. Chin et al., Science 381, 59–63 (2023). \n7. S. Mariotti et al., Science 381, 63–69 (2023). \n8. K. O. Brinkmann et al., Nature 604, 280–286 (2022). \n9. R. He et al., Nature 618, 80–86 (2023). \n10. A. Al-Ashouri et al., Energy Environ. Sci. 12, 3356–3369 \n(2019). \n11. A. Al-Ashouri et al., Science 370, 1300–1309 (2020). \n12. I. Levine et al., Joule 5, 2915–2933 (2021). \n13. F. H. Isikgor et al., Nat. Rev. Mater. 8, 89–108 (2022). \n14. C. M. Crudden et al., Nat. Chem. 6, 409–414 (2014). \n15. L. Srisombat, A. C. Jamison, T. R. Lee, Colloids Surf. A \nPhysicochem. Eng. Asp. 390, 1–19 (2011). \n16. H. Chen et al., Nat. Photonics 16, 352–358 (2022). \n17. X. Li et al., Science 375, 434–437 (2022). \n18. Z. Li et al., Science 376, 416–420 (2022). \n19. M. V. Khenkin et al., Nat. Energy 5, 35–49 (2020). \n20. S. M. Park et al., Science 381, 209–215 (2023). \n21. G. Li et al., Science 379, 399–403 (2023). \n22. G. Mani et al., Langmuir 24, 6774–6784 (2008). \n23. P. Thissen, M. Valtiner, G. Grundmeier, Langmuir 26, 156–164 (2010). \n24. E. Delamarche, B. Michel, H. Kang, C. Gerber, Langmuir 10, \n4103–4108 (1994). \n25. X. Wan et al., J. Phys. Chem. C 124, 2531–2542 (2020). \n26. L. Li et al., Nat. Energy 7, 708–717 (2022). \n27. W. Jiang et al., Angew. Chem. Int. Ed. 61, e202213560 \n(2022). \n28. H. J. Yoon et al., Angew. Chem. Int. Ed. 51, 4658–4661 (2012). \n29. J. Sun et al., Sol. RRL 5, 2100663 (2021). \n30. E. Yalcin et al., Energy Environ. Sci. 12, 230–237 (2019). \n31. R. Guo et al., Adv. Funct. Mater. 33, 2211955 (2023). \n32. W. Wang et al., Adv. Energy Mater. 13, 2300694 (2023). \n33. M. Li et al., Nat. Commun. 14, 573 (2023). \n34. H. Zhang, C. Zhao, J. Yao, W. C. H. Choy, Angew. Chem. Int. Ed. \n62, e202219307 (2023). \n35. S. Y. Kim, S. J. Cho, S. E. Byeon, X. He, H. J. Yoon, Adv. Energy \nMater. 10, 2002606 (2020). \n36. I. Lange et al., Adv. Funct. Mater. 24, 7014–7024 (2014). \n37. D. Di Girolamo et al., Chem. Sci. 11, 7746–7759 (2020). \n38. F. Ma et al., J. Energy Chem. 52, 393–411 (2021). \n39. Q. Lin, A. Armin, R. C. R. Nagiri, P. L. Burn, P. Meredith, Nat. \nPhotonics 9, 106–112 (2015). \n40. J. Wang et al., Nat. Commun. 11, 177 (2020). \n41. M. Stolterfoht et al., Adv. Mater. 32, e2000080 (2020). \n42. M. Stolterfoht et al., Nat. Energy 3, 847–854 (2018). \n43. N. Phung et al., ACS Appl. Mater. Interfaces 14, 2166–2176 (2022). \n44. D. Koushik et al., J. Mater. Chem. C. 7, 12532–12543 (2019). \n45. C. J. Flynn et al., ACS Appl. Mater. Interfaces 8, 4754–4761 (2016). \n46. R. Chen et al., Nat. Energy 8, 839–849 (2023). \n47. X. Zhao et al., Science 377, 307–310 (2022). \n\n# ACKNOWLEDGMENTS \n\nFunding: This work was supported by the Innovation and Technology Fund (GHP/100/20SZ, GHP/102/20GD, MRP/040/ 21X), the ECS grant (21301319) and GRF grant (11306521) from the Research Grants Council of Hong Kong, Green Tech Fund (GTF202020164), the Science Technology and Innovation \n\nCommittee of Shenzhen Municipality (SGDX20210823104002015, JCYJ20220818101018038). Zho.L. also acknowledges financial support from the National Natural Science Foundation of China (21975085) and Excellent Youth Foundation of Hubei Scientific Committee (2021CFA065). This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract DE-AC36-08GO28308. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. Author contributions: Zhe.L., X.S., X.Z., and B.L. contributed equally to this work. Z.Z. conceived the ideas and designed the project with Zho.L., J.M.L, and X.Z. Z.Z directed and supervised the research. Zhe.L. fabricated the devices, conducted the characterization, and analyzed the data. Zho.L. directed X.S. to design and synthesize the hole-selective molecule. B.L. and D.G. also contributed to the device fabrication, characterization, and data analyses. S.Z. conducted the DFT calculations. S.L. and J.G. also helped to fabricate the devices. Zhe.L., X.Z., B.L., Zho.L., J.M.L. and Z.Z. drafted, revised, and finalized the manuscript. All the authors revised the manuscript. Competing interests: Authors declare that they have no competing interests. The patent application been submitted. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the supplementary materials. License information: Copyright $\\circledcirc$ 2023 the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.sciencemag.org/ about/science-licenses-journal-article-reuse \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.ade9637 \nMaterials and Methods \nSupplementary Text \nFigs. S1 to S42 \nTables S1 to S5 \nReferences (48–67) \nSubmitted 3 May 2023; accepted 6 September 2023 \n10.1126/science.ade9637 " + }, + { + "id": "10.1038_s41586-022-05498-z", + "DOI": "10.1038/s41586-022-05498-z", + "DOI Link": "http://dx.doi.org/10.1038/s41586-022-05498-z", + "Relative Dir Path": "mds/10.1038_s41586-022-05498-z", + "Article Title": "A wearable cardiac ultrasound imager", + "Authors": "Hu, HJ; Huang, H; Li, MH; Gao, XX; Yin, L; Qi, RX; Wu, RS; Chen, XJ; Ma, YX; Shi, KR; Li, CH; Maus, TM; Huang, B; Lu, C; Lin, MY; Zhou, S; Lou, ZY; Gu, Y; Chen, YM; Lei, YS; Wang, XY; Wang, RT; Yue, WT; Yang, XY; Bian, YZ; Mu, J; Park, G; Xiang, S; Cai, SQ; Corey, PW; Wang, JS; Xu, S", + "Source Title": "NATURE", + "Abstract": "Continuous imaging of cardiac functions is highly desirable for the assessment of long-term cardiovascular health, detection of acute cardiac dysfunction and clinical management of critically ill or surgical patients(1-4). However, conventional non-invasive approaches to image the cardiac function cannot provide continuous measurements owing to device bulkiness(5-11), and existing wearable cardiac devices can only capture signals on the skin(12-16). Here we report a wearable ultrasonic device for continuous, real-time and direct cardiac function assessment. We introduce innovations in device design and material fabrication that improve the mechanical coupling between the device and human skin, allowing the left ventricle to be examined from different views during motion. We also develop a deep learning model that automatically extracts the left ventricular volume from the continuous image recording, yielding waveforms of key cardiac performance indices such as stroke volume, cardiac output and ejection fraction. This technology enables dynamic wearable monitoring of cardiac performance with substantially improved accuracy in various environments.", + "Times Cited, WoS Core": 285, + "Times Cited, All Databases": 303, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000930959700001", + "Markdown": "# Article \n\n# A wearable cardiac ultrasound imager \n\n# Check for updates \n\nHongjie Hu1,15, Hao Huang1,15, Mohan Li2,15, Xiaoxiang Gao1,15, Lu Yin1, Ruixiang Qi3, Ray S. Wu1, Xiangjun Chen4, Yuxiang Ma1,5, Keren $\\mathsf{\\leq h i^{4,6}}$ , Chenghai Li7, Timothy M. Maus8, Brady Huang9, Chengchangfeng Lu2, Muyang Lin1, Sai Zhou4, Zhiyuan Lou1, Yue Gu4,10, Yimu Chen1, Yusheng Lei1,11, Xinyu Wang1, Ruotao Wang1, Wentong Yue1, Xinyi Yang4, Yizhou Bian1, Jing Mu4, Geonho Park1, Shu Xiang12, Shengqiang Cai4,7, Paul W. Corey13, Joseph Wang1,4 & Sheng Xu1,2,4,9,14 ✉ \n\nContinuous imaging of cardiac functions is highly desirable for the assessment of long-term cardiovascular health, detection of acute cardiac dysfunction and clinical management of critically ill or surgical patients1–4. However, conventional non-invasive approaches to image the cardiac function cannot provide continuous measurements owing to device bulkiness5–11, and existing wearable cardiac devices can only capture signals on the skin12–16. Here we report a wearable ultrasonic device for continuous, real-time and direct cardiac function assessment. We introduce innovations in device design and material fabrication that improve the mechanical coupling between the device and human skin, allowing the left ventricle to be examined from different views during motion. We also develop a deep learning model that automatically extracts the left ventricular volume from the continuous image recording, yielding waveforms of key cardiac performance indices such as stroke volume, cardiac output and ejection fraction. This technology enables dynamic wearable monitoring of cardiac performance with substantially improved accuracy in various environments. \n\nThe device features piezoelectric transducer arrays, liquid metal composite electrodes and triblock copolymer encapsulation, as shown by the exploded schematics (Fig. 1a, left, Extended Data Fig. 1 and Supplementary Discussion 3). The device is built on styrene–ethylene– butylene–styrene (SEBS). To provide a comprehensive view of the heart, standard clinical practice is to image it in two orthogonal orientations by rotating the ultrasound probe17. To eliminate the need for manual rotation, we designed the device with an orthogonal configuration (Fig. 1a, right and Supplementary Videos 1 and 2). Each transducer element consisted of an anisotropic 1-3 piezoelectric composite and a silver-epoxy-based backing layer18,19. To balance the penetration depth and spatial resolution, we chose a centre resonant frequency of 3 MHz for deep tissue imaging19 (Supplementary Fig. 1). The array pitch was $0.4\\mathrm{mm}$ (that is, 0.78 ultrasonic wavelengths), which enhances lateral resolutions and reduces grating lobes20. \n\nTo individually address each element in such a compact array, we made high-density multilayered stretchable electrodes based on a composite of eutectic gallium–indium liquid metal and SEBS21. The composite is highly conductive and easy to pattern (Fig. 1b,c, Supplementary Figs. 2–4 and Methods). Lap shear measurements show that the interfacial bonding strength is about 250 kPa between the transducer element and the SEBS substrate, and about 236 kPa between the transducer element and the composite electrode (Fig. 1d and \n\nSupplementary Fig. 5), which are both stronger than typical commercial adhesives22 (Supplementary Table 2). The resulting electrode has a thickness of only about ${8\\upmu\\mathrm{m}}$ (Supplementary Figs. 6 and 7). Electromagnetic shielding, also made of the composite, can mitigate the interference of ambient electromagnetic waves, which reduces the noise in the ultrasound radiofrequency signals and enhances the image quality23 (Supplementary Fig. 8 and Supplementary Discussion 4). The device has excellent electromechanical properties, as determined by its high electromechanical coupling coefficient, low dielectric loss, wide bandwidth and negligible crosstalk (Supplementary Fig. 1 and Methods). The entire device has a low Young’s modulus of 921 kPa, comparable with the human skin modulus24 (Supplementary Fig. 9). The device exhibits a high stretchability of up to approximately $110\\%$ (Fig. 1e and Supplementary Fig. 10) and can withstand various deformations (Fig. 1f). Considering that the typical strain on the human skin is within $20\\%$ (ref. 19), these mechanical properties allow the wearable imager to maintain intimate contact with the skin over a large area, which is challenging for rigid ultrasound devices25. \n\n# Imaging strategies and characterizations \n\nWe evaluated the quality of the generated images based on the five most crucial metrics for anatomical imaging: spatial resolutions (axial, \n\n# Article \n\n![](images/dcb3e48134582f4b030a015fe845b2bab887c738189df452d83498eaf6dd2a7e.jpg) \nFig. 1 | Design and characterization of the wearable cardiac imager. a, Schematics showing the exploded view of the wearable imager, with key components labelled (left) and its working principle (right). b, Resistance of the liquid metal composite electrode as a function of uniaxial tensile strain. The electrode can be stretched up to about $750\\%$ without failure. The y axis is the relative resistance defined as $R/R_{0}$ , in which $R_{0}$ and $R$ are the measured resistances at $0\\%$ strain and a given strain, respectively. The inset is a scanning electron micrograph of the liquid metal composite electrodes with a width as small as about $30\\upmu\\mathrm{m}$ . Scale bar, ${50\\upmu\\mathrm{m}}$ . c, Cycling performance of the electrode \nbetween $0\\%$ and $100\\%$ uniaxial tensile strain, showing the robustness of the electrode. The inset shows the zoomed-in features of the graph during cyclic stretching and relaxing of the electrode. d, Lap shear strength of the bonding between transducer elements and SEBS or liquid metal composite electrode. Data are mean and s.d. from $\\scriptstyle n=3$ tests. The inset is a schematic setup of the lap shear test. e, Finite element analysis of the entire device under $110\\%$ biaxial stretching. f, Optical images showing the mechanical compliance of the wearable imager when bent on a developable surface, wrapped around a non-developable surface, poked and twisted. Scale bars, $5\\mathsf{m m}$ . \n\nlateral and elevational), signal-to-noise ratio, location accuracies (axial and lateral), dynamic range and contrast-to-noise-ratio26. \n\nThe transmit beamforming strategy is critical for image quality. Therefore, we compared three distinct strategies: plane-wave, monofocus and wide-beam compounding. Phantoms containing monofilament wires were used for this comparison (Supplementary Fig. 11, position 1). Among the three strategies, the wide-beam compounding implements a sequence of divergent acoustic waves with a series of transmission angles, and the generated images of each transmission are coherently combined to create a compounding image, which has the best quality with an expanded sonographic window27 (Fig. 2a,b and Supplementary Figs. 12–14). We also used a receive beamforming strategy to further improve the image quality (Supplementary Fig. 15 and Methods). The wide-beam compounding achieves a synthetic focusing effect and, therefore, a high acoustic intensity across the entire insonation area (Fig. 2c and Supplementary Fig. 13), which leads to the best signal-to-noise ratio and spatial resolutions (Fig. 2a, third column, Fig. 2b and Supplementary Fig. 12). \n\n![](images/332afe2f6968e121afe142dc614428b8c17a51b33173d6452d66ecdbaafa4fd4.jpg) \nFig. 2 | B-mode imaging strategies and characterizations. a, Imaging results on wire $(100\\upmu\\mathrm{m}$ in diameter) phantoms using different transmit beamforming strategies. The first three columns show the images through plane-wave, monofocus and wide-beam compounding at different depths, respectively. The fourth column shows the imaging resolution of wide-beam compounding in the elevational direction. The bottom row shows images of laterally distributed wires by the wide-beam compounding, from which the lateral accuracy and spatial resolutions at different lateral distances from the central axis can be obtained. b, Signal-to-noise ratios as a function of the imaging depth under \ndifferent transmission strategies. c, Simulated acoustic fields of the wide-beam compounding, with enhanced acoustic field across the entire insonation area. d, Elevational, lateral and axial resolutions of the device using wide-beam compounding at different depths. e, Lateral and axial resolutions of the device using wide-beam compounding with different lateral distances from the central axis. Data in d and e are mean and s.d. from five tests $(n=5)$ . f, Imaging inclusions with different contrasts to the matrix. On the basis of these B-mode images, the dynamic range (g) and contrast-to-noise ratio ${\\bf\\Pi}({\\bf h})$ of the device can be quantified. \n\nTo quantify the device spatial resolutions using the wide-beam compounding strategy, we measured full widths at half maximum from the point spread function curves28 extracted from the images (Fig. 2a, third and fourth columns and the bottom row and Supplementary Fig. 11, positions 1 and 2). As the depth increases, the elevational resolution deteriorates (Fig. 2d) because the beam becomes more divergent in the elevational direction. Therefore, we integrated six small elements into a long element (Extended Data Fig. 1) to offer better acoustic beam convergence and elevational resolution. The lateral resolution deteriorates only slightly with depth (Fig. 2d) owing to the process of receive beamforming (Methods). The axial resolution remains almost constant with depth (Fig. 2d) because it depends only on the frequency and bandwidth of the transducer array. Similarly, at the same depth, the axial resolution remains consistent with different lateral distances from the central axis of the device, whereas the lateral resolution is the best at the centre, where there is a high overlap of acoustic beams after compounding (Fig. 2e and Methods). \n\nAnother critical metric for imaging is the location accuracies. The agreements between the imaging results and the ground truths (the red dots in Fig. 2a) in the axial and lateral directions are $96.01\\%$ and $95.90\\%$ , respectively, indicating excellent location accuracies (Methods). \n\nFinally, we evaluated the dynamic range and contrast-to-noise ratio of the device using the wide-beam compounding strategy. Phantoms containing cylindrical inclusions with different acoustic impedances \n\n# Article \n\nwere used for the evaluation (Supplementary Fig. 11, position 3). A high acoustic impedance mismatch results in images with high contrast (Fig. 2f). We extracted the average grey values of the inclusion images and performed a linear regression29, and determined the dynamic range to be 63.2 dB (Fig. 2g, Supplementary Fig. 16 and Methods), which is well above the 60-dB threshold typically used in medical diagnosis30. \n\nWe selected two regions of interest, one inside and the other outside each inclusion area, to derive the contrast-to-noise ratios31, which range from 0.63 to 2.07 (Fig. 2h and Methods). A higher inclusion contrast leads to a higher contrast-to-noise ratio of the image. The inclusions with the lowest contrast ( $+3$ dB or $-3\\mathrm{d}\\mathbf{B}$ ) can be clearly visualized, demonstrating the outstanding sensitivity of this device20. The performance of the wearable imager is comparable with that of the commercial device (Supplementary Figs. 17 and 18, Extended Data Table 1 and Supplementary Discussion 5). \n\n# Echocardiography from several views \n\nEchocardiography is commonly used to examine the structural integrity and blood-delivery capabilities of the heart. Uniquely for soft devices, the contours of the human chest cause a non-planar distribution of the transducer elements, which leads to phase distortion and therefore image artefacts32. We used a three-dimensional scanner to collect the chest curvature to compensate for element position shifts within the wearable imager and thus correct phase distortion during transmit and receive beamforming (Supplementary Fig. 19, Extended Data Fig. 2 and Supplementary Discussion 6). \n\nWe compared the performance of the wearable device with a commercial device in four primary views of echocardiography, in which critical cardiac features can be identified (Extended Data Fig. 3). Figure 3a shows the schematics and corresponding B-mode images of these four views, including apical four-chamber view, apical two-chamber view, parasternal long-axis view and parasternal short-axis view. The difference between the results from the wearable and commercial devices is negligible. The parasternal short-axis view is particularly useful for evaluating the contractile function of the myocardium based on its motion in the radial direction and its relative thickening, as both are easily seen from this view. During contraction and relaxation, healthy myocardium undergoes strain and the wall thickness changes accordingly: thickening during contraction and thinning during relaxation. The strength of the left ventricle’s contractile function can be directly reflected on the ultrasound image through the magnitude of the myocardial strain. Abnormalities in the contractile function, such as akinesia, can be indicative of ischaemic heart disease and myocardial infarction33. \n\nTo better localize the specific segment of the left ventricular wall that is potentially pathological, the 17-segment model can be adopted as in standard clinical practice33 (Fig. 3b). We took the basal, mid-cavity and apical slices of the parasternal short-axis view from the left ventricular wall, and divided them into segments according to the model. Each segment is linked to a certain coronary artery, allowing ischaemia in the coronary arteries to be localized on the basis of akinesia in the corresponding myocardial segment33. We then recorded the displacement waveforms of the myocardium boundaries (Fig. 3c and Supplementary Discussion 6). The two peaks in each cardiac cycle in the displacement curves correspond to the two inflows into the left ventricle during diastole. The wall displacements, as measured in the basal, mid-cavity and apical views, become sequentially smaller owing to the decreasing radius of the myocardium along the conical shape of the left ventricle. \n\nMotion-mode (M-mode) images track activities over time in a one-dimensional target region34,35. We extracted M-mode images from parasternal long-axis view B-mode images (Fig. 3d). Primary targets include the left ventricular chamber, the septum and the mitral/aortic valves. In M-mode, structural information, such as the myocardial thickness and the left ventricular diameter, can be tracked according to the distances between the boundaries of features. Valvular functions, for example, their opening and closing velocities, can be evaluated on the basis of the distance between the leaflet and septal wall (Supplementary Discussion 1). Moreover, we can correlate the mechanical activities in the M-mode images with the electrical activities in the electrocardiogram measured simultaneously during different phases in a cardiac cycle (Fig. 3d and Supplementary Discussions 1 and 6). \n\n# Monitoring during motion \n\nStress echocardiography assesses cardiac responses to stress induced by exercise or pharmacologic agents, which may include new or worsened ischaemia presenting as wall-motion abnormalities, and is crucial in the diagnosis of coronary artery diseases36. Furthermore, subjects with heart failure may sometimes seem asymptomatic at rest, as the heart sacrifices its efficiency to maintain the same cardiac output37,38. Thus, by pushing the heart towards its limits during exercise, the lack of efficiency becomes apparent. However, in current procedures, ultrasound images are obtained only before and after exercise. With the cumbersome apparatus, it is impossible to acquire data during exercise, which may contain invaluable real-time insights when new abnormal­ ities initiate39 (Supplementary Discussion 7). Also, because images are traditionally obtained after exercise, a quick recovery can mask any transient pathologic response during stress and lead to false-negative examinations40. In addition, the end point for terminating the exercise is subjective, which may result in suboptimal testing. \n\nThe wearable ultrasonic patch is ideal for overcoming these challenges. The device can be attached to the chest with minimal constraint to the movement of the subject, providing a continuous recording of cardiac activities before, during and after exercise with negligible motion artefacts (Extended Data Fig. 4). This not only captures the real-time responses during the test but also offers objective data to standardize the end point and enhances patient safety throughout the test (Supplementary Discussion 7). We used liquidus silicone as the couplant to achieve images of stable quality instead of water-based ultrasound gels that evaporate over time (Supplementary Figs. 20 and 21 and Supplementary Discussion 8). We observed no skin irritation or allergy after $24\\mathsf{h}$ of continuous wear (Supplementary Fig. 22). The heart rate of the subject remained stable with a constant device temperature of about $32^{\\circ}\\mathbf{C}$ after the device continuously worked for 1 h (Supplementary Fig. 23). In addition, one device was tested on different subjects (Supplementary Fig. 24). The reproducible results indicate the stable and reliable performance of the wearable imager. \n\nWe performed stress echocardiography to demonstrate the performance of the device during exercise (Supplementary Discussion 7). The device was attached to the subject for continuous recording along the parasternal long axis during the entire process, which consisted of three main stages (Fig. 4a). In the rest stage, the subject laid in the supine position. In the exercise stage, the subject exercised on a stationary bike with several intervals until a possible maximal heart rate was reached. In the recovery stage, the subject was placed in the supine position again. The device demonstrated uninterrupted tracking of the left ventricular activities, including the corresponding M-mode echocardiography and synchronized heart-rate waveform (Fig. 4b,c, Extended Data Fig. 5 and Supplementary Video 3). We examined a representative section of each testing stage and extracted the left ventricular internal diameter end systole (LVIDs) and left ventricular internal diameter end diastole (LVIDd) (Fig. 4d). The LVIDs and LVIDd of the subject remained stable during the rest stage (Fig. 4e). In the exercise stage, the interventricular septum and left ventricular posterior wall of the subject moved closer to the skin surface, with the latter moving more than the former, resulting in a decrease in LVIDs and LVIDd. In the recovery stage, the LVIDs and LVIDd slowly returned to normal. The variation in fractional shortening, a measure of the cardiac muscular contractility, reflects the changing demand for blood supply in different stages of stress echocardiography (Fig. 4e). Particularly, section 4 in Fig. 4b includes periods of exercise d, M-mode images (upper left) extracted from parasternal long-axis view and corresponding electrocardiogram signals (lower left). A zoomed-in plot shows the different phases of a representative cardiac cycle (right). Primary events include diastole and opening of the mitral valve during the P-wave of the electrocardiogram, opening of the aortic valve and systole during the QRS complex and closure of the aortic valve during the T-wave. AC, atrial contraction; AMVL, anterior mitral valve leaflet; C.I., commercial imager; ERF, early rapid filling; Ej., ejection; IVCT, isovolumetric contraction time; IVRT, isovolumetric relaxation time; IVS, interventricular septum; LA, left atrium; LV, left ventricle; LVIDd, left ventricular internal diameter end diastole; LVIDs, left ventricular internal diameter end systole; LVOT, left ventricular outflow tract; LVPW, left ventricular posterior wall; MV, mitral valve; RA, right atrium; RV, right ventricle; TV, tricuspid valve; W.I., wearable imager. \n\n![](images/be88ae5b10c6ad9f9f8ccb18cbcdaf6fd0210dc68aaae7d38902fc54fd796e38.jpg) \nFig. 3 | Echocardiography in several standard views. a, Schematics and B-mode images of cardiac anatomies from the wearable and commercial imagers. The wearable imager was placed in the parasternal position for imaging in the parasternal long-axis and short-axis views and relocated at the apical position for imaging in the apical four-chamber and two-chamber views. b, 17-segment model representation of the left ventricular wall. Each of the concentrically nested rings that make up the circular plot represents the parasternal short-axis view of the myocardial wall from a different level of the left ventricle. c, B-mode images of the left ventricle in basal, mid-cavity and apical views (top row) and corresponding typical displacement for segments 3, 10 and 14, respectively (bottom row). The physical regions of the left ventricular wall represented by each segment of the 17-segment model have been labelled on the corresponding short-axis views. The peaks are marked with red dots. \n\n![](images/ac8cb255dd657bc34dbeb39b61d2108202d8322066cb27ea6e47d6e7bea681ab.jpg) \nFig. 4 | Monitoring during motion. a, Three stages of stress echocardiography. In the rest stage, the subject laid supine for around 4 min. In the exercise stage, the subject rode a stationary bike for about 15 min, with intervals for rest. In the recovery stage, the subject laid supine again for about 10 min. The wearable imager was attached to the chest of the subject throughout the entire test, even during the transitions between the stages. b, Continuous M-mode echocardiography extracted from the parasternal long-axis-view B-mode images of the entire process. Key features of the interventricular septum and left ventricular posterior wall are identified. The stages of rest, exercise (with intervals of rest) and recovery are labelled. c, Variations in the heart rate \nextracted from the M-mode echocardiography. d, Zoomed-in images of sections 1 (rest), 2 (exercise) and 3 (recovery) (dashed boxes) in b. e, Left ventricular internal diameter end diastole (LVIDd) and left ventricular internal diameter end systole (LVIDs) waveforms of the three different sections of the recording and corresponding average fractional shortenings. f, Zoomed-in images of section 4 (dashed box) during exercise with intervals of rest in b. In the first interval, the subject took a rhythmic deep breath six times, whereas during exercise, there seems to be no obvious signs of a deep breath, probably because the subject switched from diaphragmatic (rest) to thoracic (exercise) breathing, which is shallower and usually takes less time. \n\nand intervals for rest, when patterns of a deep breath can also be seen from the left ventricular posterior wall motions (Fig. 4f). \n\n# Automatic image processing \n\nCardiovascular diseases are often associated with changes in the pumping capabilities of the heart, which could be measured by stroke volume, cardiac output and ejection fraction. Non-invasive, continuous monitoring of these indices are valuable for the early detection and surveillance of cardiovascular conditions (Supplementary Discussion 9). Critical information embodied in these waveforms may help precisely determine potential risk factors and track the health state41 (Supplementary Discussion 10). On the other hand, processing of the unprecedented image data streams, if done manually, can be overwhelming for clinicians, which potentially introduces interobserver variability or even errors42. \n\nAutomatic image processing can overcome the challenges. We applied a deep learning neural network to extract key information (for example, the left ventricular volume in apical four-chamber view) from the continuous stream of images (Fig. 5a, Supplementary Fig. 25 and Supplementary Discussion 11). We evaluated different types of deep learning models43 through the output images and waveforms of the left ventricular volume (Extended Data Figs. 6 and 7, Supplementary Table 3 and Supplementary Video 4). The FCN-32 model outperforms others based on qualitative and quantitative analyses (Supplementary Fig. 26, Supplementary Tables 4 and 5 and Supplementary Discussion 11). We also applied data augmentation to expand the dataset and improve the performance (Supplementary Fig. 27 and Supplementary Discussion 11). \n\n![](images/097e698a7319e665cd880e971488a5ced9c48bfcb662b3d1974b08a2d476227a.jpg) \nFig. 5 | Automatic image processing by deep learning. a, Schematic workflow. Pre-processed images are used to train the FCN-32 model. The trained model accepts the unprocessed images and predicts the left ventricular (LV) volume, based on which stroke volume, cardiac output and ejection fraction are derived. b, Left ventricular volume waveform generated by the FCN-32 model from both the wearable imager (W.I.) and the commercial imager (C.I.) (left). Critical features are labelled in one detailed cardiac cycle (right). c, Bland–Altman analysis of the average of (x axis) and the difference between (y axis) the modelgenerated and manually labelled left ventricular volumes for the wearable (black) and commercial (red) imagers. Dashed lines indicate the $95\\%$ confidence interval and about $95\\%$ of the data points are within the interval for both imagers. Solid lines indicate mean differences. d, Comparing the stroke volume, cardiac output and ejection fraction extracted from results by the \nwearable and commercial imagers. Data are mean and s.d. from twelve cardiac cycles $(n=12)$ . e, The model-generated left ventricular volume waveform in the recovery stage. f, Three representative sections of the recording from the initial, middle and end stages of e. End-systolic volume (ESV), end-diastolic volume (EDV), stroke volume and ejection fraction (g) and cardiac output and heart rate waveforms ${\\bf\\Pi}({\\bf h})$ derived from the left ventricular volume waveform. The end-systolic volume and end-diastolic volume gradually recover to the normal range in the end section. The stroke volume increases from about $60\\mathrm{{ml}}$ to about $70\\mathrm{ml}$ The ejection fraction decreases from about $80\\%$ to about $60\\%$ . The cardiac output decreases from about 11 l $|\\mathsf{m i n}^{-1}$ to about $9\\mathsf{l m i n^{-1}}$ , indicating that the decreasing heart rate from about 175 bpm to about 130 bpm overshadowed the increasing stroke volume. AS, atrial systole; IC, isovolumetric contraction; IR, isovolumetric relaxation; RI, rapid inflow. \n\n# Article \n\nThe output left ventricular volumes for the wearable and commercial imagers show similar waveform morphologies (Fig. 5b, left). From the waveforms, corresponding phases of a cardiac cycle can be identified (Fig. 5b, right and Extended Data Fig. 8). Bland–Altman analysis gives a quantitative comparison between the model-generated and manually labelled left ventricular volumes, indicating a stable and reliable performance of the FCN-32 model44 (Fig. 5c and Supplementary Discussion 11). The mean differences in the left ventricular volume are both approximately $-1.5\\mathsf{m l}$ , which is acceptable for standard medical diagnosis45. We then derived stroke volume, cardiac output and ejection fraction from the left ventricular volume waveforms. No marked difference is observed in the averages or standard deviations between the two devices (Fig. 5d). The results verified the comparable performance of the wearable imager to the commercial imager. \n\nThe left ventricular volume is constantly changing and generally follows a steady-state pattern at rest in healthy subjects. Therefore, stroke volume, cardiac output and ejection fraction also tend to remain constant. However, cardiac pathologies or ordinary daily activities such as exercise may dynamically change those indices. To validate the performance of the wearable imager under dynamic situations, we extracted the left ventricular volume from recordings in the recovery stage of stress echocardiography (Fig. 5e). The dimensions of the left ventricle cannot be accurately determined when the images are collected in the standing position, owing to anatomical limitations of the human body (Supplementary Fig. 28 and Supplementary Discussion 9). Owing to the deep breathing after exercise, the heart was sometimes blocked by the lungs in the image. We used an image-imputation algorithm to complement the blocked part (Supplementary Fig. 29 and Supplementary Discussion 11). The acquired waveform shows an increasing trend in the left ventricular volume. Figure 5f illustrates three representative sections of the recording taken from the beginning, middle and end of the recovery stage. In the initial section, the diastasis stage is barely noticeable because of the high heart rate. In the middle section, the diastasis stage becomes visible. In the end section, the heart rate decreases notably. The end-diastolic and end-systolic volumes are increasing, because the slowing heartbeat during recovery allows more time for blood to fill the left ventricle46 (Fig. 5g). The stroke volume gradually increases, indicating that the end-diastolic volume increases slightly faster than the end-systolic volume (Fig. 5g). The ejection fraction decreases as heart contraction decreases during the recovery (Fig. 5g). The cardiac output reduces, indicating a larger influence brought about by the decreasing heart rate than the increasing stroke volume (Supplementary Discussion 9). \n\n# Discussion \n\nEchocardiography is crucial in the diagnosis of cardiac diseases, but the current implementation in clinics is cumbersome and limits its application in continuous monitoring. Emerging technologies based on wearable rigid modules25 or flexible patches47 lack one or more of the ideal properties of wearable ultrasound technologies (Extended Data Table 2). In this work, we provided uninterrupted frame-by-frame acquisitions of cardiac images even when the subject was undertaking intensive exercise. In addition, the wearable imager with deep learning gave actionable information by automatically and continuously outputting curves of critical cardiac metrics, such as myocardial displacement, stroke volume, ejection fraction and cardiac output, which are highly desirable in critical care, cardiovascular disease management and sports science48. This capability is unprecedented in conventional clinical practice9 and the non-invasiveness can extend potential benefits to the outpatient and athletic populations. \n\nThe implications of this technology go far beyond imaging the heart, as it can be generalized to image other deep tissues, such as the inferior vena cava, abdominal aorta, spine and liver (Supplementary Fig. 30). \n\nFor example, as demonstrated in an ultrasound-guided biopsy procedure on a cyst phantom (Supplementary Fig. 31), the two orthogonal imaging sections present the entire biopsy process simultaneously, freeing up one hand of the operator (Supplementary Video 5). The uniquely enabling capability of this technology forgoes the need for an operator to constantly hold the device. \n\nOther future efforts could ensue by further improving spatial resolutions (Supplementary Fig. 32). A three-dimensional scanner can only provide the curvature of a static human chest. To accommodate the dynamic chest curvature, advanced imaging algorithms need to be developed to compensate for the phase distortion and thus improve spatial resolutions. In addition, the wearable imager is connected to the back-end system for data processing by means of a flexible cable (Supplementary Fig. 33) and future work needs to focus on system miniaturization and integration. Besides, the FCN-32 neural network can only be applied to subjects in the training dataset at present. Its generalizability could potentially be improved by expanding the training dataset or optimizing the network with few-shot-learning49 or reinforcement-learning50 strategies, which will allow the model to adapt to a larger population. \n\n# Online content \n\nAny methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-022-05498-z. \n\n1. Levick, J. R. An Introduction to Cardiovascular Physiology (Butterworth-Heinemann, 1991). \n2. Yazdanyar, A. & Newman, A. B. The burden of cardiovascular disease in the elderly: morbidity, mortality, and costs. Clin. Geriatr. Med. 25, 563–577 (2009). \n3. Ouyang, D. et al. Video-based AI for beat-to-beat assessment of cardiac function. Nature 580, 252–256 (2020). \n4. Jozwiak, M., Monnet, X. & Teboul, J. L. Monitoring: from cardiac output monitoring to echocardiography. Curr. Opin. Crit. Care 21, 395–401 (2015). \n5. Frahm, J., Voit, D. & Uecker, M. Real-time magnetic resonance imaging: radial gradient-echo sequences with nonlinear inverse reconstruction. Invest. Radiol. 54, 757–766 (2019). \n6. Commandeur, F., Goeller, M. & Dey, D. Cardiac CT: technological advances in hardware, software, and machine learning applications. Curr. Cardiovasc. Imaging Rep 11, 19 (2018). \n7. Angelidis, G. et al. SPECT and PET in ischemic heart failure. Heart Fail. Rev. 22, 243–261 (2017). \n8. Efimov, I. R., Nikolski, V. P. & Salama, G. Optical imaging of the heart. Circ. Res. 95, 21–33 (2004). \n9. Gargesha, M., Jenkins, M. W., Wilson, D. L. & Rollins, A. M. High temporal resolution OCT using image-based retrospective gating. Opt. Express 17, 10786–10799 (2009). \n10. Wang, R. Y. et al. High-resolution image reconstruction for portable ultrasound imaging devices. EURASIP J. Adv. Signal Process. 2019, 56 (2019). \n11. Baribeau, Y. et al. Handheld point-of-care ultrasound probes: the new generation of POCUS. J. Cardiothorac. Vasc. Anesth. 34, 3139–3145 (2020). \n12. Zimetbaum, P. J. & Josephson, M. E. Use of the electrocardiogram in acute myocardial infarction. N. Engl. J. Med. 348, 933–940 (2003). \n13. Alihanka, J., Vaahtoranta, K. & Saarikivi, I. A new method for long-term monitoring of the ballistocardiogram, heart rate, and respiration. Am. J. Physiol. 240, R384–R392 (1981). \n14. García-González, M. A., Argelagós-Palau, A., Fernández-Chimeno, M. & Ramos-Castro, J. in Computing in Cardiology 2013 461–464 (IEEE, 2014). \n15. Elgendi, M. On the analysis of fingertip photoplethysmogram signals. Curr. Cardiol. Rev. 8, 14–25 (2012). \n16. Isaacson, D., Mueller, J. L., Newell, J. C. & Siltanen, S. Imaging cardiac activity by the D-bar method for electrical impedance tomography. Physiol. Meas. 27, S43–S50 (2006). \n17. Schiller, N. B. et al. Recommendations for quantitation of the left ventricle by two-dimensional echocardiography. J. Am. Soc. Echocardiogr. 2, 358–367 (1989). \n18. Hu, H. et al. Stretchable ultrasonic transducer arrays for three-dimensional imaging on complex surfaces. Sci. Adv. 4, eaar3979 (2018). \n19. Wang, C. et al. Monitoring of the central blood pressure waveform via a conformal ultrasonic device. Nat. Biomed. Eng. 2, 687–695 (2018). \n20.\t Shung, K. K. Diagnostic Ultrasound: Imaging and Blood Flow Measurements (CRC, 2005). \n21. Huang, Z. L. et al. Three-dimensional integrated stretchable electronics. Nat. Electron. 1, 473–480 (2018). \n22.\t Wu, S. J., Yuk, H., Wu, J., Nabzdyk, C. S. & Zhao, X. A multifunctional origami patch for minimally invasive tissue sealing. Adv. Mater. 33, e2007667 (2021). \n23.\t Wu, H., Shen, G. & Chen, Y. A radiation emission shielding method for high intensity focus ultrasound probes. Biomed. Mater. Eng. 26, S959–S966 (2015). \n24.\t Chen, Q. P. et al. Ultrasonic inspection of curved structures with a hemisphericalomnidirectional ultrasonic probe via linear scan SAFT imaging. NDT E Int. 129, 102650 (2022). \n25.\t Wang, C. et al. Bioadhesive ultrasound for long-term continuous imaging of diverse organs. Science 377, 517–523 (2022). \n26.\t Wang, C. et al. Continuous monitoring of deep-tissue haemodynamics with stretchable ultrasonic phased arrays. Nat. Biomed. Eng. 5, 749–758 (2021). \n27.\t Montaldo, G., Tanter, M., Bercoff, J., Benech, N. & Fink, M. Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 56, 489–506 (2009). \n28.\t Ghavami, M., Ilkhechi, A. K. & Zemp, R. Flexible transparent CMUT arrays for photoacoustic tomography. Opt. Express 30, 15877–15894 (2022). \n29.\t Xiao, Y., Boily, M., Hashemi, H. S. & Rivaz, H. High-dynamic-range ultrasound: application for imaging tendon pathology. Ultrasound Med. Biol. 44, 1525–1532 (2018). \n30.\t Zander, D. et al. Ultrasound image optimization (“knobology”): B-mode. Ultrasound Int. Open 6, E14–E24 (2020). \n31. Kempski, K. M., Graham, M. T., Gubbi, M. R., Palmer, T. & Lediju Bell, M. A. Application of the generalized contrast-to-noise ratio to assess photoacoustic image quality. Biomed. Opt. Express 11, 3684–3698 (2020). \n32.\t Huang, X., Lediju Bell, M. A. & Ding, K. Deep learning for ultrasound beamforming in flexible array transducer. IEEE Trans. Med. Imaging 40, 3178–3189 (2021). \n33.\t Cerqueira, M. D. et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. Circulation 105, 539–542 (2002). \n34.\t Feigenbaum, H. Role of M-mode technique in today’s echocardiography. J. Am. Soc. Echocardiogr. 23, 240–257, 335-247 (2010). \n35.\t Devereux, R. B. et al. Standardization of M-mode echocardiographic left ventricular anatomic measurements. J. Am. Coll. Cardiol. 4, 1222–1230 (1984). \n36.\t Armstrong, W. F., Pellikka, P. A., Ryan, T., Crouse, L. & Zoghbi, W. A. Stress echocardiography recommendations for performance and interpretation of stress echocardiography. J. Am. Soc. Echocardiogr. 11, 97–104 (1998). \n37.\t Rerych, S. K., Scholz, P. M., Newman, G. E., Sabiston, D. C. Jr & Jones, R. H. Cardiac function at rest and during exercise in normals and in patients with coronary heart disease: evaluation by radionuclide angiocardiography. Ann. Surg. 187, 449–464 (1978). \n38.\t Little, W. C. & Applegate, R. J. Congestive heart failure: systolic and diastolic function. J. Cardiothorac. Vasc. Anesth. 7, 2–5 (1993). \n39.\t Hill, J. & Timmis, A. Exercise tolerance testing. Br. Med. J. 324, 1084–1087 (2002). \n40.\t Marwick, T. H. in Echocardiography (eds Nihoyannopoulos, P. & Kisslo, J.) 491–519 (Springer, 2018). \n41.\t Hammermeister, K. E., Brooks, R. C. & Warbasse, J. R. The rate of change of left ventricular volume in man: I. Validation and peak systolic ejection rate in health and disease. Circulation 49, 729–738 (1974). \n42.\t Pellikka, P. A. et al. Variability in ejection fraction measured by echocardiography, gated single-photon emission computed tomography, and cardiac magnetic resonance in patients with coronary artery disease and left ventricular dysfunction. JAMA Netw. Open 1, e181456 (2018). \n43.\t Ghorbanzadeh, O. et al. Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection. Remote Sens. 11, 196 (2019). \n44.\t Bland, J. M. & Altman, D. G. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327, 307–310 (1986). \n45.\t Matheijssen, N. A. et al. Assessment of left ventricular volume and mass by cine magnetic resonance imaging in patients with anterior myocardial infarction intra-observer and inter-observer variability on contour detection. Int. J. Cardiovasc. Imaging 12, 11–19 (1996). \n46.\t Fritzsche, R. G., Switzer, T. W., Hodgkinson, B. J. & Coyle, E. F. Stroke volume decline during prolonged exercise is influenced by the increase in heart rate. J. Appl. Physiol. 86, 799–805 (1999). \n47.\t Pashaei, V. et al. Flexible body-conformal ultrasound patches for image-guided neuromodulation. IEEE Trans. Biomed. Circuits Syst. 14, 305–318 (2020). \n48.\t Kenny, J. S. et al. A novel, hands-free ultrasound patch for continuous monitoring of quantitative Doppler in the carotid artery. Sci. Rep. 11, 7780 (2021). \n49.\t Sung, F. et al. in Proc. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition 1199–1208 (IEEE, 2018). \n50.\t Kaelbling, L. P., Littman, M. L. & Moore, A. W. Reinforcement learning: a survey. J. Artif. Intell. Res. 4, 237–285 (1996). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 \n\n# Article Methods \n\n# Materials \n\nGallium–indium eutectic liquid metal, toluene, ethyl alcohol, acetone and isopropyl alcohol were purchased from Sigma-Aldrich. SEBS (G1645) was obtained from Kraton. Silicone (Ecoflex 00-30) was bought from Smooth-On as the encapsulation material of the device. Silicone (Silbione) was obtained from Elkem Silicones as the ultrasound couplant. Aquasonic ultrasound transmission gel was bought from Parker Laboratories. 1-3 composite (PZT-5H) was purchased from Del Piezo Specialties. Silver epoxy (Von Roll 3022 E-Solder) was obtained from EIS. Anisotropic conductive film cable was purchased from Elform. \n\n# Design and fabrication of the wearable imager \n\nWe designed the transducer array in an orthogonal geometry, similar to a Mills cross array (Supplementary Fig. 34), to achieve biplane standard views simultaneously. For the transducers, we chose the 1-3 composite for transmitting and receiving ultrasound waves because it possesses superior electromechanical coupling18. In addition, the acoustic impedance of 1-3 composites is close to that of the skin, maximizing the acoustic energy propagating into human tissues19. The backing layer dampens the ringing effect, broadens the bandwidth and thus improves the spatial resolution18,51. \n\nWe used an automatic alignment strategy to fabricate the orthogonal array. The existing method of bonding the backing layer to the 1-3 composite was to first dice many small pieces of backing layer and 1-3 composite, and then bond each pair together one by one. A template was needed to align the small pieces. This method was of very low efficiency. In this study, we bond a large piece of backing layer with a large piece of 1-3 composite and then dice them together into small pieces with designed configurations. The diced array is then automatically aligned on adhesive tape with high uniformity and perfect alignment. \n\nElectrodes based on eutectic gallium–indium liquid metal are fabricated to achieve better stretchability and higher fabrication resolution than existing electrodes based on serpentine-shaped copper thin film. Eutectic gallium–indium alloys are typically patterned through approaches such as stencil lithography52, masked deposition53, inkjet printing54, microcontact printing55 or microfluidic channelling56. Although these approaches are reliable, they are either limited in patterning resolution or require sophisticated photolithography or printing hardware. The sophisticated hardware makes fabrication complicated and time-consuming, which presents a challenge in the development of compact, skin-conformal wearable electronics. \n\nIn this study, we exploited a new technology for patterning. We first screen-printed a thin layer of liquid metal on a substrate. A key consideration before screen printing was how to get the liquid metal to wet the substrate. To solve this problem, we dispersed big liquid metal particles into small microparticles using a tip sonicator (Supplementary Fig. 2). When microparticles contacted air, their outermost layer generated an oxide coating, which lowered the surface tension and prevented those microparticles from aggregating. In addition, we used 1.5 wt.% SEBS as a polymer matrix to disperse the liquid metal particles because SEBS could wet well on the liquid metal surface. We also used SEBS as the substrate. Therefore, the SEBS in the matrix and the substrate could merge and cure together after screen printing, allowing the liquid metal layer to adhere to the substrate efficiently and uniformly. Then we used laser ablation to selectively remove the liquid metal from the substrate to form patterned electrodes. \n\nThe large number of piezoelectric transducer elements in the array requires many such electrodes to address each element individually. We designed a four-layered top electrode and a common ground electrode. There are SEBS layers between different layers of liquid metal electrodes as insulation. To expose all electrode layers to connect to transducer elements, we used laser ablation to drill vertical interconnect accesses21. Furthermore, we created a stretchable shielding layer using liquid metal and grounded it through a vertical interconnect access, which effectively protected the device from external electromagnetic noises (Supplementary Fig. 8). \n\nBefore we attached the electrodes to the transducer array, we spin-coated toluene–ethanol solution (volume ratio 8:2) on the top of the multilayered electrode to soften the liquid-metal-based elastomer, also known as ‘solvent-welding’. The softened SEBS provided a sufficient contact surface, which could help form a relatively strong van der Waals force between the electrodes and the metal on the transducer surface. After bonding the electrodes to the transducer array, we left the device at room temperature to let the solvent evaporate. The final bonding strength of more than 200 kPa is stronger than many commercial adhesives22. \n\nTo encapsulate the device, we irrigated the device in a petri dish with uncured silicone elastomer (Ecoflex 00-30, Smooth-On) to fill the gap between the top and bottom electrodes and the kerf among the transducer elements. We then cured the silicone elastomer in an oven for 10 min at $80^{\\circ}\\mathsf C.$ . As the filling material, it suppresses spurious shear waves from adjacent elements, effectively isolating crosstalk between the elements18,19. With that being said, we think the main reason for the suppressed spurious shear waves is because of the epoxy in the 1-3 composite, which limits the lateral vibration of the piezoelectric materials. The Ecoflex as the filling material may have contributed but not played a chief role because the kerf is not too wide, only 100 to $200\\upmu\\mathrm{m}$ . We lifted off the glass slide on the top electrode and directly covered the top electrode with a shielding layer. Then we lifted off the glass slide on the bottom electrode to release the entire device. Finally, screen-printing an approximately ${50}{\\cdot}{\\upmu\\mathrm{{m}}}$ layer of silicone adhesive on the device surface completed the entire fabrication. \n\n# Characterization of the liquid metal electrode \n\nExisting wearable ultrasound arrays can achieve excellent stretchability by serpentine-shaped metal thin films as electrodes19,26. The serpentine geometry, however, severely limits the filling ratio of functional components, precluding the development of systems that require a high integration density or a small pitch. In this study, we chose to use liquid metal as the electrode owing to its large intrinsic stretchability, which makes the high-density electrode possible. The patterned liquid metal electrode had a minimum width of about $30\\upmu\\mathrm{m}$ with a groove of about $24\\upmu\\mathrm{m}$ (Supplementary Fig. 3), an order of magnitude finer than other stretchable electrodes18,26,57. The liquid metal electrode is ideal for connecting arrays with a small pitch58. \n\nThis liquid metal electrode exhibited high conductivity, exceptional stretchability and negligible resistance change under tensile strain (Fig. 1b and Supplementary Fig. 4). The initial resistance at $0\\%$ strain was $\\phantom{-}1.74\\Omega$ (corresponding to a conductivity of around 11, $800\\mathsf{S}\\mathsf{m}^{-1},$ ), comparable with reported studies59,60. The resistance gradually increased with strain until the electrode reached the approximately $750\\%$ failure strain (Fig. 1b and Supplementary Fig. 4). The relative resistance is a parameter widely used to characterize the change in the resistance of a conductor (that is, the liquid metal electrode in this case) under different strains relative to the initial resistance58–60. The relative resistance is unitless. When the strain was $0\\%$ , the initial resistance $R_{0}$ was 1.74 Ω. When the electrode was under $750\\%$ strain, the electrode was broken and the resistance $R$ at the breaking point was measured to be $44.87\\Omega$ . Therefore, the relative resistance $(R/R_{0})$ at the breaking point was 25.79. \n\nTo investigate the electrode fatigue, we subjected them to $100\\%$ cyclic tensile strain (Fig. 1c). The initial 500 cycles observed a gradual increase in the electrode resistance because the liquid metal, when stretched, could expose more surfaces. These new surfaces were oxidized after contacting with air, leading to the resistance increase (Supplementary Fig. 4). After the initial 500 cycles, the liquid metal electrode exhibited stable resistance because, after a period of cycling, there were not many new surfaces exposed. \n\nThis study is the first to use liquid metal-based electrodes to connect ultrasound transducer elements. The bonding strength between them directly decides the robustness and endurance of the device. This is especially critical for the wearable patch, which will be subjected to repeated deformations during use. Therefore, we characterized the bonding strength of the electrode to the transducer element using a lap shear test. The liquid metal electrode was first bonded with the transducer element. The other sides of the electrode and the element were both fixed with stiff supporting layers. The supporting layer serves to be clamped by the tensile grips of the testing machine. Samples will be damaged if they are clamped by the grips directly. Then a uniaxial stretching was applied to the sample at a strain rate of $0.5{\\sf s}^{-1}$ . The test was stopped when the electrode was delaminated from the transducer element. A SEBS film was bonded with a transducer element and we performed the lap shear test using the same method. The peak values of the curve were used to represent the lap shear strength (Fig. 1d). The bonding strength between the pure SEBS film and the transducer element was roughly $250\\mathsf{k P a}$ , and that between the electrode and the transducer element was about $236\\mathsf{k P a}$ , which were both stronger than many commercial adhesives (Supplementary Table 2). The results indicate the robust bonding between the electrode and the element, preventing the electrodes from delamination under various deformations. This robust bonding does not have any limitations on the ultrasound pressures that can be transduced. \n\n# Characterization of the transducer elements \n\nThe electromechanical coupling coefficient of the transducer elements was calculated to be 0.67, on par with that of commercial probes $(0.58\\ –0.69)^{61}$ . This superior performance was largely owing to the technique for bonding transducer elements and electrodes at room temperature in this study, which protected the piezoelectric material from heat-induced damage and depolarization. The phase angle was ${>}60^{\\circ}$ , substantially larger than most earlier studies18,62, indicating that most of the dipoles in the element aligned well after bonding63. The large phase angle also demonstrated the exceptional electromechanical coupling performance of the device. Dielectric loss is critical for evaluating the bonding process because it represents the amount of energy consumed by the transducer element at the bonding interface20. The average dielectric loss of the array was 0.026, on par with that of the reported rigid ultrasound probes $(0.02\\mathrm{-}0.04)^{64-66}$ , indicating negligible energy consumed by this bonding approach (Supplementary Fig. 1b). The response echo was characterized in time and frequency domains (Supplementary Fig. 1c), from which the approximately 35 dB signal-to-noise ratio and roughly $55\\%$ bandwidth were derived. The crosstalk values between a pair of adjacent elements and a pair of second nearest neighbours have been characterized (Supplementary Fig. 1d). The average crosstalk was below the standard $-30$ dB in the field, indicating low mutual interference between elements. \n\n# Characterization of the wearable imager \n\nWe characterized the wearable imager using a commercial multipurpose phantom with many reflectors of different forms, layouts and acoustic impedances at various locations (CIRS ATS 539, CIRS Inc.) (Supplementary Fig. 11). The collected data are presented in Extended Data Table 1. For most of the tests, the device was first attached to the phantom surface and rotated to ensure the best imaging plane. Raw image data were saved to guarantee minimum information loss caused by the double-to-int8 conversion. Then the raw image data were processed using the ‘scanConversion’ function provided in the k-Wave toolbox to restore the sector-shaped imaging window (restored data). We applied five times upsampling in both vertical and lateral directions. The upsampled data were finally converted to the dB unit using: \n\n$$\nI_{\\mathrm{new}}{=}20\\times\\mathsf{l o g}_{\\mathrm{10}}(I_{\\mathrm{old}})\n$$ \n\nThe penetration depth was tested with a group of lines of higher acoustic impedance than the surrounding background distributed at different depths in the phantom. The penetration depth is defined as the depth of the deepest line that is differentiable from the background (6 dB higher in pixel value). Because the deepest line available in this study was at a depth of 16 cm and was still recognizable from the background, the penetration depth was determined as $>16\\mathrm{cm}$ . \n\nThe accuracy is defined as the precision of the measured distance. The accuracy was tested with the vertical and lateral groups of line phantoms. The physical distance between the two nearest pixels in the vertical and lateral directions was calculated as: \n\n$$\n\\Delta y=\\frac{\\mathrm{imagingdepth}}{N_{\\mathrm{pixel,vertical}}-1}\n$$ \n\n$$\n\\Delta x=\\frac{\\mathrm{imagingwidth}}{N_{\\mathrm{pixel,lateral}}-1}\n$$ \n\nWe acquired the measured distance between two lines (shown as two bright spots in the image) by counting the number of pixels between the two spots and multiplying them by Δy or $\\Delta x$ , depending on the measurement direction. The measured distances at different depths were compared with the ground truth described in the data sheet. Then the accuracy can be calculated by: \n\n$$\n\\mathrm{Accuracy}=1-\\left|{\\frac{\\mathrm{computed}\\mathrm{distance}}{\\mathrm{groundtruth}}}-1\\right|\n$$ \n\nThe lateral accuracy was presented as the mean accuracy of the four neighbouring pairs of lateral lines at a depth of $50\\mathrm{mm}$ in the phantom. \n\nThe spatial resolutions were tested using the lateral and vertical groups of wires. For the resolutions at different depths, the full width at half maximum of the point spread function in the vertical or lateral directions for each wire was calculated. The vertical and lateral resolutions could then be derived by multiplying the number of pixels within the full width at half maximum by Δy or $\\Delta x_{\\cdot}$ depending on the measurement direction. The elevational resolutions were tested by rotating the imager to form a $45^{\\circ}$ angle between the imager aperture and the lines. Then the bright spot in the B-mode images would reveal scatters out of the imaging plane. The same process as calculating the lateral resolutions was applied to obtain the elevational resolutions. The spatial resolutions at different imaging areas were also characterized with the lateral group of wires. Nine wires were located at $\\pm4\\mathsf{c m}$ , $^{\\pm3\\mathrm{cm}}$ , $\\pm2\\mathsf{c m}$ , ±1 cm and $0\\mathrm{cm}$ from the centre. The lateral and axial resolutions of the B-mode images from those wires were calculated with the same method. \n\nNote that the lateral resolution worsens with the depth, mainly because of the receive beamforming (Supplementary Fig. 15). There are two beamformed signals, A and B. The lateral resolution of the A point $(x_{1})$ is obviously better than that of the B point $(x_{2})$ . The fact that lateral resolution becomes worse with depth is inevitable in all ultrasound imaging, as long as receive beamforming is used. \n\nAs for different transmit beamforming methods, the wide-beam compounding is the best because it can achieve a synthetic focusing effect in the entire insonation area. The better the focusing effect, the higher the lateral resolution, which is why the lateral resolution of the wide-beam compounding is better than the other two transmit methods at the same depth. Furthermore, the multiple-angle scan used in the wide-beam compounding can enhance the resolution at high-angle areas. The multiple-angle scan combines transmissions at different angles to achieve a global high signal-to-noise ratio, resulting in improved resolutions. \n\nThe elevational resolution can only be characterized when the imaging target is directly beneath the transducer. For those targets that are far away from the centre, they are difficult to be imaged, which makes \n\n# Article \n\ntheir elevational resolutions challenging to calculate. When characterizing the elevational resolution, the device should rotate $45^{\\circ}$ . In this case, most of the reflected ultrasound waves from those wires cannot return to the device owing to the large incidence angles. Therefore, those wires cannot be captured in the B-mode images. One potential solution is to decrease the rotating angle of the device, which may help capture more wires distributed laterally in the B-mode image. However, a small rotating angle will cause the elevational image to merge with the lateral image, which increases the error of calculating the elevational resolution. Considering those reasons, we only characterized the elevational resolution of the imaging targets directly beneath the transducer array. \n\nThe contrast resolution, the minimum contrast that can be differentiated by the imaging system, was tested with greyscale objects. The collected B-mode images are shown in Fig. 2. Because the targets with $^{+3}$ and −3 dB, the lowest contrast available in this study, could still be recognized in the images, the contrast resolution of the wearable imager is determined as $^{<3}$ dB. \n\nThe dynamic range in an ultrasound system refers to the contrast range that can be displayed on the monitor. The contrast between an object and the background is indicated by the average grey value of all pixels in the object in the display. The grey value is linearly proportional to the contrast. The larger the contrast, the larger the grey value. Because the display window was using the data type ‘uint8’ to differentiate the greyscale, the dynamic range was defined as the contrast range with a grey value ranging from 0 to 255. \n\nThe object with −15 dB contrast has the lowest average grey value, whereas the object with $+15$ dB contrast has the highest (Supplementary Fig. 16). In our case, there are six objects with different contrasts to the background in the phantom. The highest grey value obtained from the object of $+15$ dB contrast was 159.8, whereas the lowest grey value from the object of −15 dB contrast was 38.7. We used a linear fit to extrapolate the contrasts when the corresponding average grey values were equal to 255 and 0, which corresponded to contrasts of 39.2 dB and $-24.0$ dB, respectively. Then the dynamic range was determined as: \n\n$$\n{\\mathrm{Dynamic~range}}=39.2-(-24.0)=63.2{\\mathrm{~dB}}\n$$ \n\nThe dead zone is defined as the depth of the first line phantom that is not overwhelmed by the initial pulses. The dead zone was tested by imaging a specific set of wire phantoms with different depths right beneath the device (Supplementary Fig. 11, position 4) directly and measuring the line phantoms that were visible in the B-mode image. \n\nThe bandwidth of the imager is defined as the ratio between the full width at half maximum in the frequency spectrum and the centre frequency. It was measured by a pulse-echo test. A piece of glass was placed 4 cm away from the device and the reflection waveform was collected with a single transducer. The collected reflection waveform was converted to the frequency spectrum by a fast Fourier transform. The full width at half maximum was read from the frequency spectrum. We obtained the bandwidth using: \n\nContrast sensitivity represents the capability of the device to differentiate objects with different brightness contrasts20. The contrast sensitivity was tested with the greyscale objects. The contrast sensitivity is defined as the contrast-to-noise ratio (CNR) of the objects having certain contrasts to the background in the B-mode image: \n\n$$\n\\mathbf{CNR}=\\frac{|\\boldsymbol{\\mu}_{\\mathrm{in}}-\\boldsymbol{\\mu}_{\\mathrm{out}}|}{\\sqrt{\\sigma_{\\mathrm{in}}^{2}+\\sigma_{\\mathrm{out}}^{2}}}\n$$ \n\nin which $\\mu_{\\mathrm{in}}$ and $\\sigma_{\\mathrm{in}}$ are the mean and the standard deviation of pixel intensity within the object, and $\\mu_{\\mathrm{out}}$ and $\\sigma_{\\mathrm{out}}$ are the mean and the standard deviation of pixel intensity of the background. \n\nThe insertion loss is defined as the energy loss during the transmission and receiving. It was tested in water with a quartz crystal, a function generator with an output impedance of $50\\Omega$ and an oscilloscope (Rigol DS1104). First, the transducer received an excitation in the form of a tone burst of a 3-MHz sine wave from the function generator. Then the same transducer received the echo from the quartz crystal. Given the 1.9-dB energy loss of the transmission into the quartz crystal and the $2.2\\times10^{-4}\\mathrm{dB}(\\mathrm{mmMHz})^{-1}$ attenuation of water, the insertion loss could be calculated as: \n\n$$\n\\mathrm{lnsertion\\loss=\\left|~20\\timeslog_{10}}{\\left(\\frac{V_{\\mathrm{r}}}{V_{\\mathrm{t}}}\\right)}+1.9+2.2\\times10^{-4}\\times2d\\times f_{\\mathrm{r}}^{2}\\ \\right|\\ }\n$$ \n\n# Simulation of the acoustic field \n\nThe simulation computes the root mean square of the acoustic pressure at each point in the defined simulation field. The root mean square is defined in the equation below and gives an average acoustic pressure over a certain time duration, which is pre-defined in a packaged function of the software. In the equation, $x_{i}$ is the simulated acoustic pressure at the ith time step. \n\n$$\nx_{\\mathrm{RMS}}={\\sqrt{{\\frac{1}{n}}(x_{1}^{2}+x_{2}^{2}+\\cdots+x_{n}^{2})}}\n$$ \n\nFigure 2c is the simulated root mean square of the transmitted acoustic pressure field by the orthogonal transducers. The simulation was done using the MATLAB UltraSound Toolbox67. Each one-dimensional phased array in the orthogonal transducers gives a sector-shaped acoustic pressure field. The simulation merges two such sector-shaped acoustic pressure fields. The imaging procedure was done with the same parameters as the simulations. \n\nIn the simulation, we defined the transducer parameters first: the centre frequency of the transducers as $3\\mathsf{M H z}$ , the width of the transducers as $0.3\\mathsf{m m}$ , the length of the transducers as $2.3\\mathsf{m m}$ , the pitch of the array as $0.4\\mathrm{mm}$ , the number of elements as 32 and the bandwidth of the transducers as $55\\%$ . Then we defined wide-beam compounding (Supplementary Fig. 13) as the transmission method: 97 transmission angles, from $-37.5^{\\circ}$ to $+37.5^{\\circ}$ , with a step size of $0.78^{\\circ}$ . Then the acoustic pressure field was the overall effect of the 97 transmissions. Finally, we defined the computation area: $-8\\mathsf{m m}$ to $+8\\mathsf{m m}$ in the lateral direction, $-6\\mathsf{m m}$ to $+6\\mathsf{m m}$ in the elevational direction and 0 mm to $140\\mathsf{m m}$ in the axial direction. \n\n# Data availability \n\nAll data are available in the manuscript or Supplementary Information. \n\n# Code availability \n\n# The code that produced the findings of this study is available at https:// github.com/UCSD-XuGroup/Wearable-Cardiac-Ultrasound-Imager. \n\n51.\t Lin, M. Y., Hu, H. J., Zhou, S. & Xu, S. Soft wearable devices for deep-tissue sensing. Nat. Rev. Mater. 7, 850–869 (2022). \n52.\t Jeong, S. H. et al. Liquid alloy printing of microfluidic stretchable electronics. Lab Chip \n12, 4657–4664 (2012). \n53.\t Kramer, R. K., Majidi, C. & Wood, R. J. Masked deposition of gallium-indium alloys for liquid-embedded elastomer conductors. Adv. Funct. Mater. 23, 5292–5296 (2013). \n54.\t Ladd, C., So, J. H., Muth, J. & Dickey, M. D. 3D printing of free standing liquid metal microstructures. Adv. Mater. 25, 5081–5085 (2013). \n55.\t Tabatabai, A., Fassler, A., Usiak, C. & Majidi, C. Liquid-phase gallium–indium alloy electronics with microcontact printing. Langmuir 29, 6194–6200 (2013). \n56.\t Cheng, S. & Wu, Z. Microfluidic electronics. Lab Chip 12, 2782–2791 (2012). \n57.\t Sempionatto, J. R. et al. An epidermal patch for the simultaneous monitoring of haemo­ dynamic and metabolic biomarkers. Nat. Biomed. Eng. 5, 737–748 (2021). \n58.\t Liu, S., Shah, D. S. & Kramer-Bottiglio, R. Highly stretchable multilayer electronic circuits using biphasic gallium-indium. Nat. Mater. 20, 851–858 (2021). \n59.\t Ma, Z. et al. Permeable superelastic liquid-metal fibre mat enables biocompatible and monolithic stretchable electronics. Nat. Mater. 20, 859–868 (2021). \n60.\t Lopes, P. A., Santos, B. C., de Almeida, A. T. & Tavakoli, M. Reversible polymer-gel transition for ultra-stretchable chip-integrated circuits through self-soldering and self-coating and self-healing. Nat. Commun. 12, 4666 (2021). \n61.\t Mi, X. H., Qin, L., Liao, Q. W. & Wang, L. K. Electromechanical coupling coefficient and acoustic impedance of 1-1-3 piezoelectric composites. Ceram. Int. 43, 7374–7377 (2017). \n62.\t Wang, Z. et al. A flexible ultrasound transducer array with micro-machined bulk PZT. Sensors 15, 2538–2547 (2015). \n63.\t Hong, C.-H. et al. Lead-free piezoceramics – where to move on? J. Materiomics 2, 1–24 (2016). \n64.\t Zhu, B. P. et al. Sol–gel derived PMN–PT thick films for high frequency ultrasound linear array applications. Ceram. Int. 39, 8709–8714 (2013). \n65.\t Li, X. et al. 80-MHz intravascular ultrasound transducer using PMN-PT free-standing film. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 58, 2281–2288 (2011). \n66.\t Zhu, B. et al. Lift-off PMN–PT thick film for high-frequency ultrasonic biomicroscopy. J. Am. Ceram. Soc. 93, 2929–2931 (2010). \n67.\t Shahriari, S. & Garcia, D. Meshfree simulations of ultrasound vector flow imaging using smoothed particle hydrodynamics. Phys. Med. Biol. 63, 205011 (2018). \n\nAcknowledgements We thank Z. Wu, R. Chen and W. Zhao for guidance and discussions on experiments. We thank E. Echegaray, M. Kraushaar, X. Guo and Y. Hewei for testing and \n\nconsultation of echocardiography. This work was supported by the National Institutes of Health (NIH) (1R21EB025521-01, 1R21EB027303-01A1, 3R21EB027303-02S1 and 1R01EB033464-01). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. All bio-experiments were conducted in accordance with the ethical guidelines of the NIH and with the approval of the Institutional Review Board of the University of California, San Diego. \n\nAuthor contributions H. Hu, H. Huang, M. Li, X.G. and S. Xu designed the research. H. Hu, H. Huang, M. Li and L.Y. performed the experiments. X.G., R.Q. and M. Li designed and trained the neural network. H. Hu, H. Huang, M. Li and Y.M. performed the data processing and simulations. H. Hu, H. Huang and S.Xu analysed the data. H. Hu, H. Huang, M. Li, R.S.W., R.Q., S. Xiang, J.W. and S. Xu wrote the paper. All authors provided constructive and valuable feedback on the manuscript. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-022-05498-z. Correspondence and requests for materials should be addressed to Sheng Xu. Peer review information Nature thanks David Ouyang, Roger Zemp and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Reprints and permissions information is available at http://www.nature.com/reprints. \n\n# Article \n\n![](images/cdef79794dbc4b68c94051cddc13db0ce3a7b96db8dbd76958550d615ebcbfc8.jpg) \nExtended Data Fig. 1 | Schematics and optical images of the orthogonal imager. a, The orthogonal imager consists of four arms, in which six small elements in one column are combined as one long element, and a central part that is shared by the four arms. The blue and red boxes label a long element integrated by six small pieces in each direction. The number of elements in one direction is 32. The pitch between the elements is $0.4\\mathrm{mm}$ . Optical images in \n\ntop view (b) and isometric view (c) showing the morphology of the orthogonal array. We used an automatic alignment strategy to fabricate the orthogonal array by bonding a large piece of backing layer with a large piece of 1-3 composite and then dicing them together into small elements with designed configurations. Inset in c shows the details of the elements. The 1-3 composite and backing layer have been labelled. \n\n![](images/887e1ff944d6954f7af026a4df7adb880a352c50db1d81fc3fc636aaf171ddf7.jpg) \n\nExtended Data Fig. 2 | Characterization of the effects of phase correction on imaging quality. B-mode images of a line phantom obtained from different situations (a). Left, from a planar surface. Middle, from a curvilinear surface without phase correction. Right, from a curvilinear surface with phase correction. b, The axial and lateral resolutions at different depths under these three situations. No obvious difference in axial resolution was found because it is mainly dependent on the transducer frequency and bandwidth. The lateral resolution of the wearable imager was improved after phase correction. Images collected in (c), the parasternallong-axis (PLAX) view of the heart and (d), the apical four-chamber view when measured by a planar probe (left panel), a curved probe without phase correction (middle panel) and a curved probe with phase correction (right panel). The left ventricular boundaries are labelled by white dashed lines in the images. e, Comparison of measured cardiac indices showing the impact of phase correction. Each measurement is based on the mean of five consecutive cardiac cycles $(\\mathsf{n}=5)$ . The standard deviations are indicated by the error bars. \n\n# Article \n\n![](images/2117f601ea760403df8fbc08daff9473d19e079919129d4cdd2f2586ebc07461.jpg) \nExtended Data Fig. 3 | Optical images showing positions and orientations for ultrasound heart imaging. a, Parasternal long-axis view. b, Parasternal short-axis view. c, Apical four-chamber view. d, Apical two-chamber view. The orthogonal wearable cardiac imager combines parasternal long-axis and \n\nshort-axis views (e) and apical four-chamber and apical two-chamber views without rotation (f). The wearable imager can capture two parasternal views from a single position or two apical views from another single position. The sternum and ribs are labelled to indicate intercostal spaces. \n\n![](images/21d159fdc5d9d9b4dafd7b109ad6e94791c9cffc703b53301b7d1cae36e1d6ac.jpg) \nExtended Data Fig. 4 | B-mode images collected from a subject with different postures. The four views collected when the subject is sitting (a), standing (b), bending over (c), lying flat (d) and lying on their side (e). The PLAX and PSAX views can keep their quality at different postures, whereas the quality \nof A4C and A2C views can only be achieved when lying on the side. A2C, apical two-chamber view; A4C, apical four-chamber view; PLAX, parasternal long-axis view; PSAX, parasternal short-axis view. \n\n# Article \n\n![](images/3cca1b3db7208e4387a52d751147b02d51773cd1c12374e39aa57a22a863e7de.jpg) \nExtended Data Fig. 5 | Continuous cardiac imaging during rest, exercise and recovery. Representative B-mode and M-mode images during rest (a), exercise (b) and recovery (c). The red line highlights the M-mode section corresponding to the current B-mode frame. More details can be seen in Supplementary Video 3. \n\n![](images/362098f770ac017d18cf5d7f0ddf08a15753d97c892461785736e322d07c4153.jpg) \nExtended Data Fig. 6 | Segmentation results of the left ventricle with different deep learning models. By qualitatively evaluating the result, we found no ‘jitteriness’ in Supplementary Video 4. The segmented left ventricle contracts and relaxes as naturally as the B-mode video. The \n\nsegmentation boundaries are smooth with the highest fidelity. Compared with the original B-mode image, the FCN-32 model has the best agreement among all models used in this study. \n\n![](images/4077ee7dd0726720243fcb63910565429a9cd1d8d013b4e1de5ad259db9896e4.jpg) \nExtended Data Fig. 7 | Waveforms of the left ventricular volume obtained with different deep learning models. Those waveforms are from segmenting the same B-mode video. Qualitatively, the waveform generated by the FCN-32 model gains the best stability and the least noise, and the waveform morphology \n\nis more constant from cycle to cycle. Quantitatively, the comparison results of those models is in Supplementary Fig. 26, which shows that the FCN-32 model has the highest mean intersection over union, showing the best performance in this study. \n\n![](images/b8b7062c10a59bd0657af273c3446fdc965e607fd41c5a2ceebc3c55a25f7977.jpg) \nExtended Data Fig. 8 | Different phases in a cardiac cycle obtained from B-mode imaging. The rows are B-mode images of A4C, A2C, PLAX and PSAX views in the same phase. The columns are B-mode images of the same view during ventricular filling, atrial contraction, isovolumetric contraction, end of ejection and isovolumetric relaxation. The dashed lines highlight the main features of the current phase. Bluish lines mean shrinking in the volume of the \nlabelled chamber. Reddish lines mean expansion in the volume of the labelled chamber. Yellowish lines mean retention in the volume of the labelled chamber. A2C, apical two-chamber view; A4C, apical four-chamber view; LA, left atrium; LV, left ventricle; LVOT, left ventricular outflow tract; RA, right atrium; RV, right ventricle; PLAX, parasternal long-axis view; PSAX: parasternal short-axis view. \n\n# Article \n\nExtended Data Table 1 | Full comparison of the imaging metrics between the wearable imager and a commercial ultrasound imager (Model P4-2v) \n\n\n
Wearable imagerCommercial acima er m3nts)Commercial imager (64 active
Depth of penetration (cm)>16>16>16
Axial accuracy (%)98.7 (40 mm)95.9 (40 mm)99. (0 mm)
96.0 (110 mm)98.9 (110 mm)99.0 (110 mm)
Lateral accuracy (%)95.996.597.0
Axial0.59 (40 mm)0.58 (40 mm)0.54 (40 mm)
resolution (mm)0.65 (70 mm)0.63 (70 mm)0.55 (70 mm)
0.62 (110 mm)0.61 (110 mm)0.60 (110 mm)
1.55 (40 mm)1.26 (40 mm)1.26 (40 mm)
Lateral resolution2.27 (70 mm)1.73 (70 mm)1.57 (70 mm)
(mm)3.49 (110 mm)2.52 (110 mm)2.28 (110 mm)
Elevational resolution3.65 (40 mm)4.36 (40 mm)3.87 (40 mm)
4.61 (70 mm)2.64 (70 mm)2.30 (70 mm)
6.41 (110 mm)3.45 (110 mm)3.14 (110 mm)
Contrast resolution (dB)<3<3<3
Dyamis )(-24.0-39.2)(-30.6-26.3)50.3 (-28.7~21.6)
Dead zone (mm)6<1<1
Bandwidth (%)557474
Contrast-to- noise ratio1.51 (-15 dB)2.01 (-15 dB)2.24 (-15 dB)
0.76 (-6 dB)0.69 (-6 dB)0.90 (-6 dB)
0.63 (-3 dB)0.26 (-3 dB)0.33 (-3 dB)
1.12 (+3 dB)0.73 (+3 dB)0.59 (+3 dB)
1.53 (+6 dB)1.23 (+6 dB)1.10 (+6 dB)
2.08 (+15 dB)1.49 (+15 dB)1.82 (+15 dB)
Insertion loss (dB)24.9816.6816.68
\n\nThe overall performance of the wearable imager is comparable with that of the commercial one. Because the wearable orthogonal array has 32 elements in each direction, we also provided measurements of the commercial imager with only 32 elements activated. \n\nExtended Data Table 2 | Summary of wearable ultrasonic devices for continuous monitoring of deep tissues \n\n\n
Device form factorImagingSensing modeIn vivoReal-timeContinuous sampling in-motionAutomatic image analysisNumber of quantified functionsCitation
Rigid moduleYes2DYesYesNoNo225
Rigid moduleNo1DYesYesNoNo148
Rigid moduleNo1DYesYesYesNo168
FlexiblepatchYes2DNoYesNoYes032
FlexiblepatchYes2DNoNoNoNo028
FlexiblepatchNo1DYesYesYesNo169
Flexible patchNo1DNoNoNoNo070
Flexible patchYes2DYesYesNoYes047
Flexible patchYes2DNoYesNoNo071
FlexiblepatchYes2DYesYesNoNo072
FlexiblepatchYes2DNoYesNoNo073
Flexible patchYes3DNoNoNoNo074
FlexiblepatchNo1DYesYesNoNo175
StretchablepatchYes2DYesYesNoNo126
Stretchable patchNo No1D 1DYesYesNoNo176 19
StretchablepatchYes2DYesYes YesYes NoNo No1 077
Stretchable patchYesNoNoNo018
Stretchablepatch StretchablepatchYes3D Bi-planesof 2DNo YesNo YesYesYes7Thiswork
\n\n‘Number of quantified functions’ means the amount of physiological signals collected from images. For example, the number of quantified functions in this work is seven because we can extract myocardium displacement, left ventricular internal diameter, fractional shortening, stroke volume, ejection fraction, cardiac output and heart rate from those B-mode images. " + }, + { + "id": "10.1038_s41586-022-05467-6", + "DOI": "10.1038/s41586-022-05467-6", + "DOI Link": "http://dx.doi.org/10.1038/s41586-022-05467-6", + "Relative Dir Path": "mds/10.1038_s41586-022-05467-6", + "Article Title": "Observation of intrinsic chiral bound states in the continuum", + "Authors": "Chen, Y; Deng, HC; Sha, XB; Chen, WJ; Wang, RZ; Chen, YH; Wu, D; Chu, JR; Kivshar, YS; Xiao, SM; Qiu, CW", + "Source Title": "NATURE", + "Abstract": "Photons with spin angular momentum possess intrinsic chirality, which underpins many phenomena including nonlinear optics(1), quantum optics(2), topological photonics(3) and chiroptics(4). Intrinsic chirality is weak in natural materials, and recent theoretical proposals(5-7) aimed to enlarge circular dichroism by resonullt metasurfaces supporting bound states in the continuum that enhance substantially chiral light-matter interactions. Those insightful works resort to three-dimensional sophisticated geometries, which are too challenging to be realized for optical frequencies(8). Therefore, most of the experimental attempts(9-11) showing strong circular dichroism rely on false/extrinsic chirality by using either oblique incidence(9,10) or structural anisotropy(11). Here we report on the experimental realization of true/intrinsic chiral response with resonullt metasurfaces in which the engineered slant geometry breaks both in-plane and out-of-plane symmetries. Our result marks, to our knowledge, the first observation of intrinsic chiral bound states in the continuum with near-unity circular dichroism of 0.93 and a high quality factor exceeding 2,663 for visible frequencies. Our chiral metasurfaces may lead to a plethora of applications in chiral light sources and detectors, chiral sensing, valleytronics and asymmetric photocatalysis.", + "Times Cited, WoS Core": 286, + "Times Cited, All Databases": 303, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000955590300008", + "Markdown": "# Article \n\n# Observation of intrinsic chiral bound states in the continuum \n\nhttps://doi.org/10.1038/s41586-022-05467-6 \n\nReceived: 6 May 2022 \n\nAccepted: 20 October 2022 \n\nPublished online: 18 January 2023 Check for updates \n\nYang Chen1,2,6, Huachun Deng3,6, Xinbo Sha3,6, Weijin Chen2,6, Ruize Wang1, Yu-Hang Chen1, Dong Wu1, Jiaru Chu1, Yuri S. Kivshar4, Shumin Xiao3,5 ✉ & Cheng-Wei Qiu2 ✉ \n\nPhotons with spin angular momentum possess intrinsic chirality, which underpins many phenomena including nonlinear optics1, quantum optics2, topological photonics3 and chiroptics4. Intrinsic chirality is weak in natural materials, and recent theoretical proposals5–7 aimed to enlarge circular dichroism by resonant metasurfaces supporting bound states in the continuum that enhance substantially chiral light–matter interactions. Those insightful works resort to three-dimensional sophisticated geometries, which are too challenging to be realized for optical frequencies8. Therefore, most of the experimental attempts9–11 showing strong circular dichroism rely on false/extrinsic chirality by using either oblique incidence9,10 or structural anisotropy11. Here we report on the experimental realization of true/ intrinsic chiral response with resonant metasurfaces in which the engineered slant geometry breaks both in-plane and out-of-plane symmetries. Our result marks, to our knowledge, the first observation of intrinsic chiral bound states in the continuum with near-unity circular dichroism of 0.93 and a high quality factor exceeding 2,663 for visible frequencies. Our chiral metasurfaces may lead to a plethora of applications in chiral light sources and detectors, chiral sensing, valleytronics and asymmetric photocatalysis. \n\nChirality, a fundamental trait of nature, refers to the geometric attribute of objects that lack mirror-reflection symmetry. To evaluate how chiral an object is, electromagnetic chirality, with the manifestation of circular dichroism (CD), is conventionally adopted based on the differential interactions between the object and electromagnetic fields of different handedness12,13. However, it is found that planar structures with out-of-plane mirror symmetry, which are not supposed to be chiral, can still demonstrate strong CD signals through the introduction of structural anisotropy14 or oblique incidence15,16. In these cases, the amplitude of CD cannot measure the ‘true chirality’ or ‘intrinsic chirality’ of an object, but it is originated from anisotropy-induced polarization conversion or chiral configurations of the experimental setup, which are usually called ‘false chirality’ or ‘extrinsic chirality’15–18. Although false chirality may yield similar CD signals as its counterpart of true chirality, its applications in a range of important fields such as chiral emission and polarized photodetection are notably limited. \n\nApart from intrinsic chirality, another key parameter for enhancing the strength of chiral light–matter interactions is the quality $(Q)$ factor of the associated resonance. Owing to the potential applications in chiral emission, chiral sensing and enantiomer separation, high-Q resonances with large intrinsic chirality have long been pursued but remain unexplored. Chiral metamaterials and metasurfaces can produce strong chiroptical responses19–21, but their achieved $Q$ -factors are still low, typically less than 200, owing to large radiative and non-radiative losses. \n\nRecently, the physics of bound states in the continuum (BICs) has been used in photonics to achieve and engineer high-Q resonances22–25. When a BIC acquires intrinsic chirality, the resulting chiral BIC can simultaneously generate high $Q$ -factors and strong CDs without involving extrinsic chirality. As pointed out by previous theoretical works, the key to enabling the chiral BIC is to break all the mirror symmetries of the structure5–7, which has hindered its experimental realization. We have witnessed numerous approaches that break either the in-plane24,26 or the out-of-plane27 mirror symmetry, but the remaining symmetry planes still prevent the generation of intrinsic chiral BICs. The measured high-Q CD resonances are inevitably attributed to the false chirality of oblique incidence9,10 or polarization conversion11. \n\nHere we report the optical realization of intrinsic chiral BICs based on a new paradigm of slant-perturbation metasurfaces. The metasurface is composed of a square array of slanted trapezoid nanoholes in a $\\mathrm{TiO}_{2}$ film, which is placed on a glass substrate and covered with PMMA (Fig. 1a). This structure is evolved from vertical square nanoholes by introducing two types of perturbations, an in-plane deformation angle $\\alpha$ and an out-of-plane slant angle $\\varphi$ , so that all the mirror symmetries are broken. A series of Bloch modes are supported by the metasurface (Fig. 1b), the mode profiles of which are shown in Supplementary Fig. 1. Without loss of generality, we first consider the fundamental transverse magnetic $(\\mathsf{T M}_{1})$ mode. When no perturbations are involved $(\\alpha=0$ , $\\varphi=0.$ ), it supports a symmetry-protected BIC at the Γ point of the \n\n![](images/494370f1343d6e71089aeef98d6ad7b75d3f316b6f67a04b6c0fcda61faa5a37.jpg) \nFig. 1 | Origin of intrinsic chirality induced by slant perturbation. a, Schematic of the slant-perturbation metasurface to realize intrinsic chiral BICs. The geometric parameters are: $\\ensuremath{p=340\\mathrm{nm}}$ , $\\scriptstyle w=210{\\mathsf{n m}}$ , $h=220\\mathsf{n m}$ . b, Calculated bandstructure of the metasurface with only non-degenerate modes plotted. c, Cross-sectional OCD distributions for the case of $\\alpha\\neq0$ , $\\scriptstyle\\varphi=0$ (left) and $\\alpha\\neq0,\\varphi\\neq0$ (right). OCD distributions in the slant-perturbed areas are \nhighlighted in the middle panel with their permittivity change $(\\Delta\\varepsilon)$ indicated. d, In-plane components of electric $(E_{\\mathrm{in\\cdotplane}})$ and magnetic $(H_{\\mathrm{in\\cdotplane}})$ field distributions at the central $x$ –y plane of the metasurface without (left) and with (right) slant perturbation, along with the configurations of the corresponding electric dipole p and magnetic dipole m. \n\nBrillouin Zone because of the $C_{2}^{z}$ symmetry of the structure. Owing to time-reversal symmetry, the electromagnetic near fields are always linearly polarized for BICs and their distributions cancel each other to stop far-field radiation (Supplementary Information Section 2). \n\nOnce an in-plane geometric perturbation is introduced to break the $C_{2}^{z}$ symmetry, for example, the square nanohole is cut into a trapezoid $(\\alpha\\neq0,\\varphi=0)$ , the BIC evolves to a quasi-BIC possessing circular polarizations in the near field, the chirality of which can be evaluated by the optical chirality density28,29: $\\begin{array}{r}{0\\mathbf{C}\\mathbf{D}=(-\\frac{1}{2})\\omega\\mathbf{Re}[\\mathbf{D}\\cdot\\mathbf{B}^{*}]}\\end{array}$ , where $\\omega$ is the angular frequency of light, D is the electric displacement field, and $\\mathbf{B}^{*}$ is the complex conjugation of magnetic flux density. Because the optical chirality density (OCD) is a parity-odd scalar30, the exis­ tence of a mirror symmetry forces it to have opposite values on the two sides of the mirror as shown in Fig. 1c. In the far field, the Stokes parameter $S_{3}$ of the radiation is related to the optical chirality flux $\\mathcal{F}$ tbhyetlhige hetqvuealtoicoint $S_{3}=\\frac{c}{\\omega S}\\int_{V}\\mathrm{Re}(\\nabla\\bullet\\mathcal{F})\\mathrm{d}\\nu.$ ,i nwchluerdei $s$ itshteh eslpabowanerdftlhuex ,s cuirsrounding background zone, dv is the volume element and $\\mathcal{F}$ is defined as $\\mathcal{F}{=}\\frac{1}{4}\\overset{\\leftarrow}{\\left[\\boldsymbol{\\mathsf{E}}\\times(\\boldsymbol{\\mathsf{\\nabla}}\\times\\boldsymbol{\\mathsf{H}}^{*})-\\boldsymbol{\\mathsf{H}}^{*}\\times(\\boldsymbol{\\nabla}\\times\\boldsymbol{\\mathsf{E}})\\right]}$ . In analogy to Poynting’s theorem, optical chirality is also bounded by the conservation law. Thus, the optical chirality flux $\\mathcal{F}$ is directly related to the near-field OCD of the associated resonance by the equation \n\n$$\n-2\\omega\\int_{V}\\mathrm{OCD}\\mathrm{d}\\nu+\\int_{V}\\mathrm{Re}\\left(\\nabla\\bullet\\mathcal{F}\\right)\\mathrm{d}\\nu=0\n$$ \n\nHere the antisymmetric OCD distributions cancel each other in the near field of the metasurface and, hence, generate no chiral flux in the far field. The absence of far-field chiral flux is protected by out-of-plane mirror symmetry and is immune from in-plane geometries. \n\nOne of the most convenient methods to break the out-of-plane mirror symmetry is to slant the nanohole in the x direction. Then the variation of OCD is written as $\\Delta\\mathrm{OCD}=\\left(\\Delta\\varepsilon/\\varepsilon\\right)\\times\\mathrm{OCD}$ , where $(\\Delta\\varepsilon/\\varepsilon)$ denotes the change of permittivity divided by its original value. As highlighted in Fig. 1c (middle panel), $\\Delta\\varepsilon$ and OCD have opposite signs in all perturbed areas and hence the volume-integrated ΔOCD is negative. The unbalanced OCD distributions in the near field of the slant-perturbation metasurface will induce non-zero optical chirality flux in the far field, corresponding to circularly polarized radiation (Fig. 1c). \n\nThe origin of slant-induced chirality can also be analysed by examining the near-field electromagnetic distributions at the central $x{-}y$ plane. As shown in Fig. 1d, when no slant perturbation is introduced, the magnetic fields of quasi-BICs are predominantly $x$ polarized whereas the electric fields are out-of-plane. According to the generalized theory of chiroptics12,15, the optical chirality of an object in the dipole approximation is controlled by the dot product $\\pmb{\\mathrm{p}}_{\\perp}\\pmb{\\cdot}\\pmb{\\mathrm{m}}_{\\perp}$ where ${\\pmb{\\mathsf{p}}}_{\\bot}$ and $\\mathbf{m}_{\\perp}$ are the projections of the associated electric dipole p and magnetic dipole m on the plane perpendicular to the k vector of incident light. Here p is parallel to k, resulting in no optical chirality. To break such a parallel configuration, the nanohole can be slanted towards the negative $x$ direction so that the associated electric field vectors are tilted towards the same direction, while the magnetic fields approximately remain $x$ polarized (Fig. 1d), leading to non-zero $\\pmb{\\mathrm{p}}_{\\perp}\\pmb{\\cdot}\\pmb{\\mathrm{m}}_{\\perp}$ and optical chirality. \n\nIn Fig. 2a, we calculate the unbalanced OCD that is equal to $\\int_{V}$ OCD dv as a function of the slant angle for different quasi-BICs. It can now be seen that an optimal slant angle exists for attaining the maximal unbalanced OCD in which the largest degree of circular polarization of far-field radiation is anticipated. We can also see that the amplitude of unbalanced OCD cannot reach unity through the slant operation alone for the second-order transverse magnetic $\\left(\\mathsf{T M}_{2}\\right)$ and transverse electric $(\\mathsf{T E}_{2})$ modes. For the fundamental transverse electric (TE1) mode, the slant angle needs to be larger to obtain large unbalanced OCD, and inevitably leads to a much smaller $Q$ -factor. Thus, the $\\mathsf{T M}_{1}$ mode is found to be the best candidate for achieving intrinsic chiral BICs with large $Q$ -factor. \n\n![](images/c220be4d267631cc71b00a276a63927e5179d866244ecf098dd594624c00051f.jpg) \nFig. 2 | Design, fabrication and characterization of slant-perturbation metasurfaces. a, Unbalanced OCD integrated over the metasurface as a function of the slant angle for different quasi-BICs. b, Evolution of C points over $k$ -space for the metasurfaces of different $\\alpha$ and $\\varphi$ . The elliptical polarizations are represented by ellipses of red or blue colours corresponding to right- or left-handed states, whereas the black lines represent linear polarizations. \nc, Side-view (left) and cross-sectional (right) scanning electron microscope images of a fabricated metasurface. Scale bar, $300\\mathsf{n m}$ . d, Angle-resolved transmission spectra of the metasurface under LCP (left) and RCP (right) incidence obtained from simulations (top) and experiments (bottom). d, Incident angles at which $C+$ and $c-$ points are observed for different slant angles $\\varphi$ , retrieved from simulations and experiments. \n\nThe evolution of the momentum-space eigenpolarization map of $\\mathsf{T M}_{1}$ along with geometric perturbations is presented in Fig. 2b. For the unperturbed case, BIC is manifested by an at-Γ V point in the map to represent a polarization singularity. Once a non-zero $\\alpha$ is induced, the integer-charged V point is decomposed into a pair of half-charged C points distributed symmetrically on the two sides of the Γ point, where the $C^{+}$ and $C^{-}$ points possess right-handed circular polarization (RCP) and left-handed circular polarization (LCP), respectively. Further, if a non-zero $\\varphi$ is introduced as well, the polarization map as a whole is moved in the same direction of structural inclination. For a proper combination of $\\alpha$ and $\\varphi$ , for example, $\\alpha=0.12$ and $\\varphi=0.1$ , the $C^{-}$ point is shifted further to the left, while the $C+$ point can be located right at the Γ point, leading to the achievement of an intrinsic chiral BIC (Fig. 2b). Similarly, we can also create chiral BIC in the $\\mathsf{T E}_{1}$ mode (Supplementary Fig. 3). The role played by the index-matched PMMA layer is discussed in Supplementary Information Section 4. \n\nThe proposed metasurface is fabricated by a modified slanted-etching system (see details in the Methods and Supplementary Fig. 5). For the accurate control of small slant angles, the sample is placed on a wedged substrate and an ${\\bf A l}_{2}{\\bf O}_{3}$ screen with an aperture is laid above the sample acting as an ion collimator. The scanning electron microscope images of fabricated samples are shown in Fig. 2c and Supplementary Fig. 6. Because of the usage of an ion collimator, the left and right sidewalls exhibit an almost identical slant angle. The angle-resolved transmission spectra of a slant-perturbation metasurface ( $\\scriptstyle\\alpha=0.12$ , $\\varphi=0.1\\mathrm{;}$ under RCP and LCP incidence are simulated in Fig. 2d. It is observed that the $C+$ point represented by the diminishing point in the $\\mathsf{T M}_{1}$ band of LCP incidence appears at a normal direction, that is, the Γ point. However, for the RCP incidence case, the $\\mathsf{T M}_{1}$ mode can be excited at normal incidence, and the $C^{-}$ point is observed at the incidence angle of $-0.04$ rad. The experimental results agree well with simulations, in which the measured $C^{+}$ and $C^{-}$ points are present at the incidence angles of 0 and $-0.044$ rad, respectively (Fig. 2d). The details of the optical experimental setup are provided in the Methods and Supplementary Fig. 7. \n\nTo study the evolution of C points with the slant angle, we have fabricated a series of metasurfaces with a fixed α but variable $\\varphi$ . As retrieved from transmission spectra, the incident angles at which $C+$ and $c-$ points occur approximately follow linear relationships with $\\varphi$ , which is consistent with the simulation results (Fig. 3a). Apparently, the key point for achieving chiral BICs is to cooperatively modulate $\\alpha$ and $\\varphi$ , so that one C point is generated and then moved back to the Γ point. To reveal such an inherent linkage between $\\alpha$ and $\\varphi$ , the generalized model based on electric and magnetic dipoles shown in Fig. 1d is revisited. When the associated perturbations $\\alpha$ and $\\varphi$ are small, the $Q$ -factor of quasi-BICs roughly scales with the inversely quadratic square of all the perturbations24: $Q\\sim1/(\\alpha^{2}+A\\varphi^{2})$ , where A expresses the different sensitivities of $Q$ to $\\alpha$ and $\\varphi$ . Meanwhile, the amplitudes of the electric dipole p and magnetic dipole m are proportional to the square root of the $Q$ -factor: $|\\pmb{\\mathrm{p}}|\\sim Q^{1/2}$ and $|\\mathbf{m}|\\sim Q^{1/2}$ . Then, the intrinsic chirality of quasi-BICs, manifested by CD, can be estimated by: \n\n![](images/cfb361d2f87bdbbc2478f30092a9bb35506ef67950f7ece7d3f53748631fca45.jpg) \nig. 3 | Inherent linkage between geometric perturbations for achieving (sim.) and experimental (exp.) results are included for comparison. c, Relation hiral BICs. a, Incident angles for which $C+$ and $C^{-}$ points are observed for between $\\varphi$ and $\\alpha$ for maximizing CD. The experimental data points are fitted by ifferent slant angles $\\varphi$ , retrieved from simulations and experiments. b, CD a linear relation (Exp._fit). mplitude as a function of $\\varphi$ while $\\alpha$ is fixed at 0.12. Theoretical, simulation \n\n$$\n\\mathbf{CD}\\cdot\\mathbf{p}_{\\perp}\\cdot\\mathbf{m}_{\\perp}=|\\mathbf{p}||\\mathbf{m}|\\ \\sin(\\varphi)\\cdot{\\frac{\\sin(\\varphi)}{\\alpha^{2}+A\\varphi^{2}}}\\approx{\\frac{\\varphi}{\\alpha^{2}+A\\varphi^{2}}}\n$$ \n\nAs predicted by equation (2), if $\\varphi$ is raised from zero while $\\alpha$ is fixed, CD will first rapidly increase to the maximum and then gradually decrease. This is well reproduced by the results of simulations (Fig. 3b). The experimental results also follow a similar dependence, except that the measured CDs are smaller than the simulated ones (see detailed spectral data in Supplementary Fig. 8). Such a deviation is mainly attributed to the fabrication tolerance and the undesired scattering from surface roughness. Further, by calculating the derivative of CD versus $\\varphi$ , the condition for maximizing CD is deduced to be $\\alpha=\\sqrt{A}\\times\\varphi$ . This offers a straightforward recipe to select a suitable set of $\\varphi$ and $\\alpha$ for achieving chiral BICs. The slope $\\sqrt{A}$ is related to the mode profile and could take different values for different chiral BICs. For the $\\mathsf{T M}_{1}$ mode, the slope is theoretically predicted to be 1.066 (Supplementary Information Section 8), which agrees well with the simulation results (Fig. 3c). The experimental data also follow a linear relationship and the fitted slope of 1.197 slightly deviates from the predicted one. Accordingly, as long as $\\varphi$ and $\\alpha$ are cooperatively decreased, the $Q$ -factor of chiral BICs can be continuously boosted while maintaining a CD of unity (Supplementary Information Section 9). In our experiments, $\\varphi$ and $\\alpha$ are set as 0.1 and 0.12, respectively, owing to the fabrication capacity. We notice that the slant direction of the nanohole can also be rotated with an azimuthal angle θ, the impact of which is discussed in Supplementary Information Section 10. \n\nAnother way to raise the $Q$ -factor of chiral BICs is to enlarge the metasurface size, so that both in-plane and out-of-plane leakage are suppressed31. We have fabricated a group of metasurface samples with different sizes. The highest $Q$ -factor of 2,663 is obtained for the largest sample of $200\\upmu\\mathrm{m}$ and the maximum CD is also reached, with a value of 0.93 (Fig. 4a). Here CD is defined as $\\mathbf{CD}=(R_{\\mathrm{R}}-R_{\\mathrm{L}})/(R_{\\mathrm{R}}+R_{\\mathrm{L}})$ , where $R_{\\mathrm{R(L)}}$ is the normalized reflection spectra under RCP (LCP) illumination. The near-field distributions under RCP and LCP illuminations are presented in Supplementary Fig. 12. To exclude the possible impact of structural anisotropy, we have measured the normalized reflection matrix $R=[R_{\\mathrm{RR}},R_{\\mathrm{RL}};R_{\\mathrm{LR}},R_{\\mathrm{LL}}]$ on a circular basis, where the notation $R_{\\mathrm{{RL}}}$ refers to the reflection of RCP light under LCP incidence. As shown in Fig. 4b, the cross-polarized components, $R_{\\mathrm{{RL}}}$ and $R_{\\mathrm{{LR}}},$ possess negligible intensities, suggesting the absence of polarization conversion. It is thus concluded that the observed CD signal is attributed to the intrinsic chirality of quasi-BICs. The measured transmission spectra are included in Supplementary Fig. 13. The fundamental difference between our demonstrated intrinsic chiral BICs and other BIC works relying on extrinsic chirality to generate large CDs is explicitly discussed in Supplementary Information Section 13. \n\nIn Fig. 4c, we have summarized the experimental $Q$ -factors and CDs from some typical works about chiral metamaterials and/or metasurfaces11,14,32–40. These works are divided into two categories according to the origin of the CD signals: one purely relies on the intrinsic chirality of \n\n![](images/3e30071eb5886096828aa3bcb41d114ef790641bc57f0ec26b92b37e4d1861a8.jpg) \nFig. 4 | Giant CD and Q-factor enabled by intrinsic chiral BICs. a, Measured circular basis for the $200\\upmu\\mathrm{m}$ sample. c, CDs and $Q$ -factors obtained from some reflection spectra of the two metasurface samples of $68\\upmu\\mathrm{m}$ (L1 and R1) and typical experimental works as compared to our work. They are classified into $200\\upmu\\mathrm{m}$ sizes (L2 and R2) under LCP and RCP incidence, respectively. Their two categories: intrinsic chirality and extrinsic chirality involved, according to retrieved CDs and $Q$ -factors are marked. b, Measured reflection matrix R in the the origin of the CD signals. \n\n# Article \n\nassociated resonance and the other also has extrinsic chirality involved. Clearly, most approaches achieving high CDs rely on extrinsic chirality effects11,35,37,38 and their $Q$ -factors are still much smaller than ours. It is noted that the previous works exhibiting relatively large $Q$ -factors are inevitably conducted in the infrared spectra11,38,39, highlighting the great difficulty and significance of achieving intrinsic chiral BICs in the visible spectrum. \n\nIn conclusion, we have presented, to our knowledge, the first experimental observation of optical chiral BICs enabling simultaneously high values of the $Q$ -factor ( $Q=2663)$ ) and a near-unity CD of 0.93. We have developed a microscopic model based on the variation of local spin density to explain the origin of optical chirality. Although our chiral BIC metasurface is demonstrated in the visible spectrum, the concept is general, being applicable to the infrared and longer spectra and promising future applications for chiral light sources and detectors, chiral sensing, quantum optics and asymmetric photocatalysis. \n\n# Online content \n\nAny methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41586-022-05467-6. \n\n1. Collins, J. T. et al. First observation of optical activity in hyper-Rayleigh scattering. Phys. Rev. X 9, 011024 (2019). \n2. Lodahl, P. et al. Chiral quantum optics. Nature 541, 473–480 (2017). \n3. Parappurath, N., Alpeggiani, F., Kuipers, L. & Verhagen, E. Direct observation of topological edge states in silicon photonic crystals: spin, dispersion, and chiral routing. Sci. Adv. 6, eaaw4137 (2020). \n4. Chen, Y. et al. Multidimensional nanoscopic chiroptics. Nat. Rev. Phys. 4, 113–124 (2021). \n5. Gorkunov, M. V., Antonov, A. A. & Kivshar, Y. S. Metasurfaces with maximum chirality empowered by bound states in the continuum. Phys. Rev. Lett. 125, 093903 (2020). \n6. Overvig, A., Yu, N. & Alu, A. Chiral quasi-ound states in the continuum. Phys. Rev. Lett. 126, 073001 (2021). \n7. Dixon, J., Lawrence, M., Barton, D. R. & Dionne, J. Self-isolated raman lasing with a chiral dielectric metasurface. Phys. Rev. Lett. 126, 123201 (2021). \n8. Gorkunov, M. V., Antonov, A. A., Tuz, V. R., Kupriianov, A. S. & Kivshar, Y. S. Bound states in the continuum underpin near‐lossless maximum chirality in dielectric metasurfaces. Adv. Opt. Mater. 9, 2100797 (2021). \n9. Liu, W. et al. Circularly polarized states spawning from bound states in the continuum. Phys. Rev. Lett. 123, 116104 (2019). \n10.\t Wu, J. et al. Observation of giant extrinsic chirality empowered by quasi-bound states in the continuum. Phys. Rev. Appl. 16, 064018 (2021). \n11. Shi, T. et al. Planar chiral metasurfaces with maximal and tunable chiroptical response driven by bound states in the continuum. Nat. Commun. 13, 4111 (2022). \n12. Barron, L. D. Molecular Light Scattering and Optical Activity (Cambridge Univ. Press, 2004). \n13. Fernandez-Corbaton, I., Fruhnert, M. & Rockstuhl, C. Objects of maximum electromagnetic chirality. Phys. Rev. X 6, 031013 (2016). \n14.\t Wu, C. et al. Spectrally selective chiral silicon metasurfaces based on infrared Fano resonances. Nat. Commun. 5, 3892 (2014). \n15.\t Plum, E., Fedotov, V. A. & Zheludev, N. I. Optical activity in extrinsically chiral metamaterial. Appl. Phys. Lett. 93, 191911 (2008). \n16.\t Plum, E. et al. Metamaterials: optical activity without chirality. Phys. Rev. Lett. 102, 113902 (2009). \n17. Barron, L. D. True and false chirality and absolute asymmetric synthesis. J. Am. Chem. Soc. 108, 5539–5542 (1986). \n18.\t Barron, L. D. True and false chirality and absolute enantioselection. Rend. Lincei 24, \n179–189 (2013). \n19.\t Valev, V. K., Baumberg, J. J., Sibilia, C. & Verbiest, T. Chirality and chiroptical effects in plasmonic nanostructures: fundamentals, recent progress, and outlook. Adv. Mater. 25, \n2517–2534 (2013). \n20.\t Hentschel, M., Schaferling, M., Duan, X., Giessen, H. & Liu, N. Chiral plasmonics. Sci. Adv. \n3, e1602735 (2017). \n21. Mun, J. et al. Electromagnetic chirality: from fundamentals to nontraditional chiroptical phenomena. Light Sci. Appl. 9, 139 (2020). \n22. Hsu, C. W. et al. Observation of trapped light within the radiation continuum. Nature 499, \n188–191 (2013). \n23.\t Hsu, C. W., Zhen, B., Stone, A. D., Joannopoulos, J. D. & Soljačić, M. Bound states in the continuum. Nat. Rev. Mater. 1, 16048 (2016). \n24.\t Koshelev, K., Lepeshov, S., Liu, M., Bogdanov, A. & Kivshar, Y. Asymmetric metasurfaces with high-Q resonances governed by bound states in the continuum. Phys. Rev. Lett. 121, \n193903 (2018). \n25.\t Azzam, S. I., Shalaev, V. M., Boltasseva, A. & Kildishev, A. V. Formation of bound states in the continuum in hybrid plasmonic-photonic systems. Phys. Rev. Lett. 121, 253901 (2018). \n26.\t Liu, Z. et al. High-Q quasibound states in the continuum for nonlinear metasurfaces. Phys. Rev. Lett. 123, 253901 (2019). \n27.\t Yin, X., Jin, J., Soljacic, M., Peng, C. & Zhen, B. Observation of topologically enabled unidirectional guided resonances. Nature 580, 467–471 (2020). \n28.\t Poulikakos, L. V. et al. Optical chirality flux as a useful far-field probe of chiral near fields. ACS Photonics 3, 1619–1625 (2016). \n29. Cameron, R. P., Barnett, S. M. & Yao, A. M. Optical helicity, optical spin and related quantities in electromagnetic theory. New J. Phys. 14, 053050 (2012). \n30.\t Tang, Y. & Cohen, A. E. Enhanced enantioselectivity in excitation of chiral molecules by superchiral light. Science 332, 333–336 (2011). \n31.\t Taghizadeh, A. & Chung, I. S. Quasi bound states in the continuum with few unit cells of photonic crystal slab. Appl. Phys. Lett. 111, 031114 (2017). \n32. Hentschel, M. et al. Optical Properties of chiral three-dimensional plasmonic oligomers at the onset of charge-transfer plasmons. ACS Nano 6, 10355–10365 (2012). \n33.\t Zhang, S. et al. Photoinduced handedness switching in terahertz chiral metamolecules. Nat. Commun. 3, 942 (2012). \n34.\t Cui, Y., Kang, L., Lan, S., Rodrigues, S. & Cai, W. Giant chiral optical response from a twistedarc metamaterial. Nano Lett. 14, 1021–1025 (2014). \n35.\t Chen, Y., Gao, J. & Yang, X. Chiral metamaterials of plasmonic slanted nanoapertures with symmetry breaking. Nano Lett. 18, 520–527 (2018). \n36.\t Wu, Z., Chen, X., Wang, M., Dong, J. & Zheng, Y. High-performance ultrathin active chiral metamaterials. ACS Nano 12, 5030–5041 (2018). \n37. Yang, S. et al. Spin-selective transmission in chiral folded metasurfaces. Nano Lett. 19, \n3432–3439 (2019). \n38.\t Semnani, B., Flannery, J., Al Maruf, R. & Bajcsy, M. Spin-preserving chiral photonic crystal mirror. Light Sci. Appl. 9, 23 (2020). \n39.\t Zhu, A. Y. et al. Giant intrinsic chiro-optical activity in planar dielectric nanostructures. Light Sci. Appl. 7, 17158 (2018). \n40.\t Ji, C.-Y. et al. Artificial propeller chirality and counterintuitive reversal of circular dichroism in twisted meta-molecules. Nano Lett. 21, 6828–6834 (2021). \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nSpringer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. \n\n$\\circledcirc$ The Author(s), under exclusive licence to Springer Nature Limited 2023 \n\n# Methods \n\n# Simulations \n\nAll the simulations in this work are conducted by a finite-elementmethod solver in COMSOL Multiphysics. Bloch boundary conditions are applied in the $x$ and y directions, whereas perfectly matched layers are used in the $z$ direction. The refractive index of the substrate and PMMA layer is set as 1.46, whereas the refractive index of $\\mathrm{TiO}_{2}$ is set as $2.13+0.001\\mathrm{i}$ . \n\n# Sample fabrication \n\n$\\mathbf{A}220\\mathsf{n m T i O}_{2}$ is first deposited on the $\\mathsf{S i O}_{2}$ substrate by an electron beam evaporator $(0.65\\mathring{\\mathbf{A}}\\mathbf{s}^{-1}.$ , Syskey Tech.) and then covered by a $20\\mathsf{n m}$ Cr film $(0.{\\overset{\\cdot}{3}}{\\overset{\\circ}{\\mathbf{A}}}\\mathbf{s}^{-1}$ , Syskey Tech.) as a hard mask (Supplementary Fig. 5). Next, an $80\\mathrm{nm}$ PMMA film is spin-coated and patterned by electron beam lithography. After the development of the resist, the pattern is transferred to the Cr film by an inductively coupled plasma (Oxford ICP180, gases: $\\mathbf{Cl}_{2}$ and $\\mathbf{O}_{2}$ ). Then, the whole sample is placed inside our home-made slant-etching system, and the gases of reactive ion etching we used are $\\mathbf{O}_{2}$ ${\\mathsf{S}}{\\mathsf{F}}_{6}$ , Ar and $\\mathsf{C H F}_{3}$ . Finally, the remaining Cr film is removed by a chromium etchant and a $400\\mathsf{n m}$ PMMA film is spin-coated on the sample for index matching. \n\n# Optical characterization \n\nA supercontinuum laser is used as the light source, and it is passed through a linear polarizer and a quarter-wave plate to generate circularly polarized light, which is then focused on the metasurface sample through an objective lens (Supplementary Fig. 7). The metasurface sample is positioned on a rotary stage so that the incident angle of the circularly polarized light can be controlled. The reflected and transmitted light are collected by the front and rear objective lenses, respectively. \n\nAfter passing through the quarter-wave plate and polarizer, their corresponding left-handed and right-handed circular components can be analysed. \n\n# Data availability \n\nThe data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request. The raw data can be accessed in the repository by the link: https://figshare.com/articles/dataset/Raw_Data_for_Nature_ manuscript_2022-05-07139B/21257547. \n\nAcknowledgements S.X. acknowledges support from the National Key Research and Development Project (grant no. 2021YFA1400802). Y.C. acknowledges support from the National Natural Science Foundation of China (No. 62275241) and the CAS Talents Programme. D.W. acknowledges support from the National Natural Science Foundation of China (grant no. 61927814). C.-W.Q. acknowledges financial support from the National Research Foundation, Prime Minister’s Office, Singapore under the Competitive Research Programme Award NRFCRP22-2019-0006. C.-W.Q. is also supported by a grant (no. R-261-518-004-720| A-0005947-16- 00) from the Advanced Research and Technology Innovation Centre from the National University of Singapore. \n\nAuthor contributions Y.C., S.X. and C.-W.Q. conceived the idea and designed the experiments. S.X. and C.-W.Q. supervised the project. Y.C. and W.C. conducted the simulations and theoretical analysis. H.D. and X.S. performed the experiments. Y.C., R.W., Y.-H.C., D.W., J.C., Y.S.K., S.X. and C.-W.Q analysed the data. Y.C. drafted the paper with inputs from all authors. \n\nCompeting interests The authors declare no competing interests. \n\n# Additional information \n\nSupplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-022-05467-6. \nCorrespondence and requests for materials should be addressed to Shumin Xiao \nor Cheng-Wei Qiu. \nPeer review information Nature thanks the anonymous reviewers for their contribution to the peer review of this work. \nReprints and permissions information is available at http://www.nature.com/reprints. " + }, + { + "id": "10.1126_science.add7331", + "DOI": "10.1126/science.add7331", + "DOI Link": "http://dx.doi.org/10.1126/science.add7331", + "Relative Dir Path": "mds/10.1126_science.add7331", + "Article Title": "Highly efficient p-i-n perovskite solar cells that endure temperature variations", + "Authors": "Li, GX; Su, ZH; Canil, L; Hughes, D; Aldamasy, MH; Dagar, J; Trofimov, S; Wang, LY; Zuo, WW; Jeronimo-Rendon, JJ; Byranvand, MM; Wang, CY; Zhu, R; Zhang, ZH; Yang, F; Nasti, G; Naydenov, B; Tsoi, WC; Li, Z; Gao, XY; Wang, ZK; Jia, Y; Unger, E; Saliba, M; Li, M; Abate, A", + "Source Title": "SCIENCE", + "Abstract": "Daily temperature variations induce phase transitions and lattice strains in halide perovskites, challenging their stability in solar cells. We stabilized the perovskite black phase and improved solar cell performance using the ordered dipolar structure of beta-poly(1,1-difluoroethylene) to control perovskite film crystallization and energy alignment. We demonstrated p-i-n perovskite solar cells with a record power conversion efficiency of 24.6% over 18 square millimeters and 23.1% over 1 square centimeter, which retained 96 and 88% of the efficiency after 1000 hours of 1-sunmaximum power point tracking at 25 degrees and 75 degrees C, respectively. Devices under rapid thermal cycling between -60 degrees and +80 degrees C showed no sign of fatigue, demonstrating the impact of the ordered dipolar structure on the operational stability of perovskite solar cells.", + "Times Cited, WoS Core": 318, + "Times Cited, All Databases": 326, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:001058669200001", + "Markdown": "# SOLAR CELLS \n\n# Highly efficient p-i-n perovskite solar cells that endure temperature variations \n\nGuixiang $\\mathbf{Li}_{\\dagger}$ , Zhenhuang $\\mathsf{s u}^{2}\\dag$ , Laura Canil1, Declan Hughes3, Mahmoud H. Aldamasy1, Janardan Dagar1, Sergei Trofimov1, Luyao Wang1\\*, Weiwei $\\scriptstyle{\\pmb{Z}}\\mathbf{u}\\mathbf{o}^{4}$ , José J. Jerónimo-Rendon4, Mahdi Malekshahi Byranvand4,5, Chenyue Wang2, Rui $z\\hslash\\mathbf{u}^{6}$ , Zuhong Zhang6, Feng Yang6, Giuseppe Nasti7, Boris Naydenov1, Wing C. Tsoi3, Zhe $L i^{8}$ , Xingyu $\\mathtt{G a o}^{2}$ , Zhaokui Wang9, Yu Jia6, Eva Unger1, Michael Saliba4,5, Meng ${\\mathsf{L i}}^{1,6,8\\ast}$ , Antonio Abate1,7\\* \n\nDaily temperature variations induce phase transitions and lattice strains in halide perovskites, challenging their stability in solar cells. We stabilized the perovskite black phase and improved solar cell performance using the ordered dipolar structure of $\\mathbf{\\beta}_{\\mathbf{\\beta}}$ -poly(1,1-difluoroethylene) to control perovskite film crystallization and energy alignment. We demonstrated p-i-n perovskite solar cells with a record power conversion efficiency of $24.6\\%$ over 18 square millimeters and $23.1\\%$ over 1 square centimeter, which retained 96 and $88\\%$ of the efficiency after 1000 hours of 1-sun maximum power point tracking at $25^{\\circ}$ and $75^{\\circ}0$ , respectively. Devices under rapid thermal cycling between $-60^{\\circ}$ and $+80^{\\circ}{\\mathsf{C}}$ showed no sign of fatigue, demonstrating the impact of the ordered dipolar structure on the operational stability of perovskite solar cells. \n\nhe highest power conversion efficiencies (PCEs) of $>25\\%$ reported for singlejunction perovskite solar cells (PSCs) rely on regular n-i-p architectures $(I)$ . However, inverted p-i-n PSCs have several advantages, including low-temperature processability and long-term operational stability derived from non-doped hole-transporting materials (2, 3). Nonetheless, they have lower PCEs, with only a few certified values exceeding $23\\%$ and a bottleneck value of $24\\%$ over 10 square millimeter cells (4–6). This lower performance is mainly correlated with nonradiative recombination losses and reduced charge extraction that stem from the high density of defects in the perovskite bulk and interfacial contacts (7, 8). \n\nFor practical applications, ambient temperature variations can limit PSC performance (9) because the perovskite can undergo severe ion migration, phase transition, and temperatureinduced strain, leading to lower PCE (10–12). Cycling over variable temperatures demands that the perovskite tolerate alternating tension and compression in the device structure (13). Thus, developing high-efficiency PSCs with thermal cycle stability is critical to advancing PSC application. \n\nWe use polymer dipoles to optimize triple cation halide perovskite $\\mathrm{Cs}_{0.05}(\\mathrm{FA}_{0.98}\\mathrm{MA}_{0.02})_{0.95}$ $\\mathrm{Pb}(\\mathrm{I_{0.98}B r_{0.02}})_{3}$ films from bulk to the surface. The polymer dipole promoted the growth of a low-defect crystalline film by reducing the formation energy of the black photoactive phase. The formation of dipoles at the perovskite surface suppressed ion migration and facilitated interfacial charge extraction while enhancing hydrophobicity. We achieved a certified PCE of $24.2\\%$ over an active area of $9.6~\\mathrm{mm^{2}}$ , and lab recorded PCEs of $24.6\\%$ over $\\mathrm{18~mm^{2}}$ and $23.1\\%$ over $\\mathrm{1~cm^{2}}$ . The high PCE was stable under severe thermal cycling (120 cycles, from $-60^{\\circ}$ to $+80^{\\circ}\\mathrm{C})$ ), demonstrating the resiliency of the crystal structure to the temperatureinduced strains. \n\n# Film formation and characterization \n\nThe alternate symmetric hydro and fluorocarbon units along the polymeric backbone of $\\upbeta$ -poly(1,1-difluoroethylene) $\\mathrm{.\\dot{\\beta}}$ -pV2F) result in an ordered molecular dipole distribution. After screening a few molecular weights, $0.5\\mathrm{mg/mL\\upbeta}$ -pV2F of 180,000 molecular weight was used (figs. S1 and S2). The influence of $\\upbeta$ -pV2F on the film morphology and work function is shown in Fig. 1. From the top view and cross sectional scanning electron microscope (SEM) images (Fig. 1, A to C), we can observe evident voids at the grain boundaries of the control perovskite film, with an average grain size of ${\\sim}400\\mathrm{nm}$ (fig. S3A). These defects can create shunting paths and nonradiative recombination centers (14). $\\upbeta$ -pV2F enabled a more compact perovskite film with an enlarged grain size of ${\\sim}480\\mathrm{nm}$ (Fig. 1, D to F, and fig. S3B). A smaller full width at half maximum in the (001) peak of the x-ray diffraction support an enhanced crystallinity in the $\\upbeta$ -pV2F–treated perovskite film (fig. S4) (15). Furthermore, atomic force microscopy images showed that $\\upbeta$ -pV2F reduced the surface roughness from 54.4 to $41.1\\mathrm{nm}$ (fig. S5), which is expected to ameliorate coverage with charge-transporting layers (16). \n\nBecause of the electron-withdrawing effect of the fluorine atoms, the neighboring hydrogen atoms have a partial positive charge density. Then, the all-trans planar zigzag conformation of $\\upbeta$ -pV2F makes it resemble a Lewis acid, which can interact with the surface of the perovskite (17, 18). Fourier transform infrared spectroscopy revealed that the $\\mathrm{-CH_{2}}$ stretching vibration peak shifted from $3025\\mathrm{cm}^{-1}$ of b-pV2F to $3019\\mathrm{cm}^{-1}$ in contact with the target perovskite (fig. S6), suggesting a solid C-H···X dipole interaction between $\\mathrm{-CH_{2}}$ moieties and halide ions of the $\\mathrm{[PbX_{6}]}^{4-}$ frame. Such polar interaction with the precursors of the perovskite influences the crystallization during film formation and leads to an upward shift of the surface work function (WF) after film formation (Fig. 1G) (17, 18); Fig. 1H displays the increase in WF up to $300\\mathrm{\\meV}$ for the target perovskite film, which facilitates the interfacial charge extraction and enhances the device’s stability (19). \n\nThe WF shift was near that of standard perovskite film treated with $\\upbeta$ -pV2F only at the surface, which indicated that as the crystal growth proceeded, $\\upbeta$ -pV2F was partially expelled from the bulk and assembled on the perovskite surface (2, 20). The fluorine-exposed surface arrangement induced hydrophobicity (figs. S7 and S8). We measured reduced nonradiative recombination and improved interfacial charge transfer in target perovskites (figs. S9 to S13) (21–24). This scenario is expected to enhance the solar cells’ efficiency and stability (25, 26). \n\nTo acquire an in-depth perspective on the promoted perovskite crystallization kinetics, we performed synchrotron-based in situ grazing incidence wide-angle x-ray scattering (GIWAXS) measurements to monitor the entire film formation process (several different stages are shown in Fig. 2, A and B). The initial $\\mathrm{t_{1}}$ stage (during the first 25 s) revealed the scattering halo at scattering vector $q$ values from 8 to $8.5\\mathrm{nm}^{-1}$ from the solvated colloidal sol precursor. The signal transition at $\\mathrm{t_{2}}$ (25 s) originated from dripping antisolvent, where the rapid solvent extraction caused the disappearance of the diffraction signal. Subsequently, the spin coating process was performed at stage $\\mathbf{t}_{3},$ where supersaturated solvate intermediate emerges. The $\\mathrm{t_{4}}$ near 60 s represented annealing staging. Stage $\\mathbf{t}_{5}$ revealed the intermediate phase signal with annealing. Stage $\\mathbf{t}_{6}$ was the perovskite evolution process. Stage $\\mathrm{t}_{7}$ described the cessation of further crystal growth. \n\n![](images/fcb9700dcf150dd0888a98e333207bb24a649b0a86b117b10ea27296b5b65dd7.jpg) \nFig. 1. Working mechanism and morphology characterization of perovskite films. Schematic of processing (A) control and (D) target perovskites. (B) Top view and (C) cross sectional SEM images of control perovskites. (E) Top view and (F) cross sectional SEM images of target perovskites. (G and H) WF shift related to perovskite functionalized with $\\mathsf{\\beta-p V}2\\mathsf{F}$ . \n\nComparing GIWAXS patterns (Fig. 2, A and B), the weakened diffraction signal in the initial 60 s suggested that the initial solvated phase of DMSO-DMF- $\\mathrm{\\cdotPbX_{2}}$ —in which DMSO is dimethylsulfoxide, DMF is dimethylformamide, and X is a halide $(\\mathrm{I}^{-},\\mathrm{Br}^{-})$ —was suppressed. This effect could be ascribed to the initial solvated phase isolated by the long-chain $\\upbeta$ -pV2F molecules (27). The intermediate phase concentration was lower in the target than in the control (fig. S14). The scattering feature centered at $q=\\sim10\\ \\mathrm{nm^{-1}}$ along the (001) crystal plane observed in the cast film indicated that the colloid had solidified and converted into a black phase. Notably, we found that the perovskite phase of the target emerged earlier than that of the control $(\\Delta\\mathfrak{t}_{\\mathrm{t}}>\\Delta\\mathfrak{t}_{\\mathrm{c}})$ , which implied that $\\upbeta$ -pV2F promoted the conversion of the intermediate phase to the perovskite black phase. The fast phase inversions were associated with the lower formation energy (28, 29) and could be attributed to $\\mathrm{\\beta_{\\mathrm{-pV2F}}}$ rapidly aggregating dispersed $\\mathrm{PbX_{2}}$ and organic salts during the elimination of DMSO and DMF (30). \n\n![](images/1906643eafb826c6bc942c52e27e05105304152ffc5eac115892055bb3a4f011.jpg) \nFig. 2. Crystallization kinetics of perovskite films. In situ GIWAXS spectra during forming (A) control and (B) target perovskite films. (C) Time-resolved integrated peak area intensity for black phases of control and target perovskites. \n\nMoreover, the target ceased crystal growth sooner at 250 s than the control at 350 s. When the crystallization is completed (stage $\\mathrm{t}_{7}\\mathrm{,}$ , the signal is more intense in the target than in the control (Fig. 2C). This result indicates that the target perovskite film is more ordered. The time-dependent in situ GIWAXS intensity profiles with other scattering vectors, such as $q=$ $\\sim20\\ \\mathrm{nm^{-1}}$ corresponding to the (002) crystal plane (fig. S15), showed the same phase transition trend. Thus, $\\upbeta$ -pV2F controls the perovskite crystallization kinetics by lowering the perovskite formation energy, promoting phase conversion, and enabling a more ordered crystal structure (fig. S16). \n\n# Photovoltaic performance \n\nThe photovoltaic performance of inverted p-i-n PSCs with control and polymer-modified perovskite films is shown in Fig. 3. The device architecture is glass/indium tin oxide (ITO)/ self-assembled [2-(3,6-dimethoxy-9H-carbazol9-yl)ethyl]phosphonic acid (MeO-2PACz)/ perovskite/ [6,6]-phenyl-C61-butyric acid methyl ester $\\mathrm{(PC_{61}B M)_{/}}$ /bathocuproine (BCP)/silver (Ag) (fig. S17). Typical current-voltage $\\left(J{-}V\\right)$ curves for the PSCs (Fig. 3A) were measured with a device area of $\\mathrm{18\\mm^{2}}$ . The control PSCs had a PCE of $22.3\\%$ , with short-circuit current density $(J_{\\mathrm{sc}})$ of $24.7\\mathrm{mA}/\\mathrm{cm}^{2}$ , $V_{\\mathrm{{oc}}}$ of $\\boldsymbol{1.13\\mathrm{V}}_{:}$ , and fill factor (FF) of $80.2\\%$ . With $\\mathrm{\\beta-pV2F}$ , the device performance improved with a $V_{\\mathrm{{oc}}}$ of $1.18\\mathrm{V}$ , a $J_{\\mathrm{sc}}$ of $24.8~\\mathrm{mA/cm^{2}}$ , and a FF of $84.3\\%$ for a PCE of $24.6\\%$ . The target $\\mathrm{PSCs}^{\\mathrm{q}}$ reverse- and forward-sweep $J.$ -V curves (fig. S18) had negligible hysteresis. A PCE of $24.2\\%$ for an aperture area of $9.6\\mathrm{{mm}^{2}}$ was obtained from the independent accredited certification institute of Test and Calibration Center of New Energy Device and Module, Shanghai Institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences (fig. S19). We also recorded a PCE of $23.1\\%$ for devices with a working area of $\\mathrm{1cm^{2}}$ (Fig. 3B). \n\nFrom the external quantum efficiency (EQE) spectra (Fig. 3C), we calculated an integrated $J_{\\mathrm{sc}}$ of 24.3 and $24.4\\mathrm{mA}/\\mathrm{cm}^{2}$ for control and target devices, respectively, comparable to the values extracted from the J-V curves. The optical bandgaps of both perovskite absorbers determined by the $x$ axis intercept of the EQE linear are shown in fig. S20 (31, 32). The statistical distribution of the device parameters collected from 38 devices shows an improved PV performance and increased reproducibility with $\\upbeta$ -pV2F (fig. S21) (33), which we explain with better charge extraction and reduced nonradiative recombination (27). \n\nThe stabilized power outputs at the maximum power point (MPP) are plotted in Fig. 3D. The control device showed a persistent attenuation in efficiency under continuous 1 equivalent sun illumination for 400 s. By contrast, the tracked target device yielded highly stable power output and even progressively improved performance, which we attributed to the lightsoaking effect (34). The stability of unencapsulated devices under working conditions shows that target PSCs retain $96\\%$ of the initial PCE after continuous MPP tracking for 1000 hours. By contrast, control PSCs decay to $84\\%$ of their original PCE (Fig. 3E). Device stability statistics $(n=12)$ are presented in fig. S22. After heating the device to $75^{\\circ}\\mathrm{C}$ , $88\\%$ PCE was retained in the target device in contrast to only $56\\%$ in the control (fig. S23). \n\nWe further evaluated device stability against temperature variations. The J-V curves in fig. S24 show that the control device’s PV parameters $(J_{\\mathrm{sc}},$ FF, and $V_{\\mathrm{oc}})$ exhibited large fluctuations when tested at temperatures ranging from $-60^{\\circ}$ to $+80^{\\circ}\\mathrm{C}$ (table S1). However, this variation was suppressed in the target device (fig. S25 and table S2). Furthermore, compared with the control, the target device had reduced hysteresis and its hysteresis factor was relatively stable under temperature variations (fig. S26). The statistical PCE distribution in Fig. 4, A and B, indicates that the $\\upbeta$ -pV2F stabilization effect is highly reproducible. All performance parameter evolution is reported in figs. S27 and S28. Subsequently, the unencapsulated devices were aged under rapid thermal cycling (TC) between $-60^{\\circ}$ and $+80^{\\circ}\\mathrm{C},$ swept at a rate of $20^{\\circ}\\mathrm{C}$ per minute. As shown in Fig. 4, C and D, the control device suffered a severe decline of $75.6\\%$ at $+80^{\\circ}\\mathrm{C}$ and $63.0\\%$ at $-60^{\\circ}\\mathrm{C},$ whereas the target device retained $93.9\\%$ at $80^{\\circ}\\mathrm{C}$ and $88.7\\%$ at $-60^{\\circ}\\mathrm{C}$ of its initial value after 120 thermal cycles. \n\n![](images/bc129b242a38f831c993e73d9253df064e99e4a08e5ae3d637f90d291b57a1ea.jpg) \nFig. 3. PV performance of perovskite solar cells. (A) $J\\cdot V$ curves of control and target PSCs under a device area of $0.18~\\mathsf{c m}^{2}$ . (B) $J-V$ curves with the reverse and forward sweeps for large-area target PSCs $(1\\mathsf{c m}^{2})$ . (C) EQE spectra and integrated $J_{\\mathsf{s c}}$ for control and target PSCs. (D) Stabilized power outputs with \nevolving current density at the maximum power points as a function of time for the best-performing PSCs. (E) Long-term stability at maximum power point tracking under room-temperature continuous illumination in ${\\sf N}_{2}$ atmosphere for unencapsulated PSCs (ISOS-L-1 procedure). \n\n![](images/8cf21cf2efce68f8ae9f8aaf6ab9bc1482bade71c5eadac6ca368de1c714989d.jpg) \nFig. 4. Thermal cycling stability of perovskite solar cells. Statistical temperature dependence PCE profiles of (A) control PSCs and (B) target PSCs. PCE evolution recorded at (C) $+80^{\\circ}\\mathsf{C}$ and (D) $-60^{\\circ}\\mathsf{C}$ of control and target PSCs against thermal cycles between $-60^{\\circ}$ and $+80^{\\circ}\\mathsf{C}$ . The rapid thermal cycling was implemented with a ramp rate of $20^{\\circ}\\mathrm{C}$ per minute. There is an extra 2-minute waiting window for the device to reach thermal equilibrium when cycling to $-60^{\\circ}$ and $+80^{\\circ}\\mathsf{C}$ . The temperature starts at room temperature and is heated to $+80^{\\circ}\\mathsf{C}$ , then cooled to $-60^{\\circ}\\mathsf{C}$ . The progress ends at room temperature. The time per complete cycle is 18 minutes. \n\n# Device film morphologies and structures during thermal cycling \n\nThe difference in device performance stems from use of $\\upbeta$ -pV2F in the perovskite film. We characterized the morphology and crystal structure of perovskite films undergoing aging with thermal cycling to identify the impact of $\\upbeta\\mathrm{.}$ -pV2F. The film aging followed the same device protocol: 120 rapid thermal cycles between $-60^{\\circ}$ and $+80^{\\circ}\\mathrm{C}$ at a rate of $20^{\\circ}\\mathrm{C}$ per minute. As observed from the SEM images in fig. S29, control films exhibited severe morphological degradation with enlarged grain boundaries and voids. Such degradation features were not detected in the aged target films (fig. S30), which appeared nearly identical to the pristine film shown in Fig. 1E. This result indicates that the temperature-induced degradation of perovskite films is suppressed in target perovskites (fig. S31) (35). \n\nWe observed additional GIWAXS peaks forming in the control perovskite after three thermal cycles (Fig. 5A). Specifically, in the second cycle, the peak for $\\mathrm{PbI_{2}}$ , a degradation product, emerged at $q=9.2\\ \\mathrm{nm}^{-1}$ . During the third thermal cycle, additional peaks ${\\sim}8.2$ and $8.6\\mathrm{nm}^{-1}$ formed, corresponding to the hexagonal photoinactive polytypes 4H and 6H from $\\mathrm{Cs_{0.05}(F A_{0.98}M A_{0.02})_{0.95}P b(I_{0.98}B r_{0.02})_{3}}$ perovskite (fig. S32A) (36, 37). This result indicates that the control perovskite undergoes irreversible phase changes. The generation of these phases may originate from the lattice deformation at the grain boundaries caused by the mutual extrusion of unit cells from neighbored crystals of different orientations (36). Such phenomena were not observed in the target perovskite (Fig. 5B), indicating high structural stability (fig. S32B). \n\nFor $q$ values from 16 to $19\\mathrm{nm}^{-1}$ , we observed additional peaks in both control and target (figs. S33 and S34), corresponding to the tetragonal phase (b phase) (10, 38). The tetragonal phase was only retained in the cold temperature region. This suggests that the degradation products of perovskite under thermal cycling include irreversible $\\mathrm{PbI_{2}}$ , 4H, and 6H, and reversible tetragonal phase transition, jointly contributing to device performance degradation. Temperature-resolved azimuthally integrated intensity patterns (figs. S35 and S36) indicate that $\\upbeta$ -pV2F suppresses the phase transitions. We found that suppressing the phase transition also suppressed ion migration in the complete device under working conditions, i.e., lower hysteresis (fig. S37). \n\nBecause of differences in thermal expansion coefficients between the perovskite film and the substrate, temperature variation induces strain in the perovskite (39, 40). The control perovskite underwent substantial lattice strain evolution $_{-0.13}$ to $0.57\\%$ ) during thermal cycling (Fig. 5C). We observed that the perovskite strain drifted with temperature cycling, showing a constant lattice parameter change in perovskite. By contrast, the target perovskite exhibits stable strain cycling in a narrower range $(-0.06$ to $0.38\\%$ ), corresponding to a recoverable crystal structure and releasable lattice strain (tables S3 to S5). We propose that a strain-buffering and lattice-stabilizing effect exists in target perovskite because $\\upbeta$ -pV2F creates a self-assembly polymeric layer that coats the crystals within the perovskite film reducing friction during thermal cycling (figs. S38 and S39) (41–44). \n\n# Conclusions \n\nThermal stress experienced in normal working conditions induces phase transitions and lattice strains that hamper the stability of perovskite solar cells (PSCs). Coating the crystals comprising the perovskite film with polymer dipoles results in a strain-buffering and latticestabilizing effect that mitigates the impact of thermal stress. We selected the specific polymer dipole $\\upbeta$ -poly(1,1-difluoroethylene) $\\mathrm{.\\bf{\\vec{\\upbeta}}}$ -pV2F). The $\\upbeta$ -pV2F highly ordered dipolar structure interacts with specific perovskite components enabling control of perovskite film crystallization during the processing and energy alignment with the charge-selective contacts within the device. We reported $\\upbeta$ -pV2F devices with improved power conversion efficiency up to $24.6\\%$ on an active area of $\\mathrm{18~mm^{2}}$ and $23.1\\%$ over a larger area of $\\mathrm{1cm^{2}}$ (certified PCE of $24.24\\%$ with an active area of $9.6\\mathrm{{mm^{2}}}$ from SIMIT). The $\\upbeta$ -pV2F strain-buffering effects enabled stable power output at temperatures as high as $75^{\\circ}\\mathrm{C}$ and rapid temperature variation between $-60^{\\circ}$ and $+80^{\\circ}\\mathrm{C}$ . Our work identifies a new strategy for making stable perovskite solar cells. \n\n![](images/5fb0fb666bf8764f827b5da2749f6c4b84ee568c2f393f2f84fde567c06c3963.jpg) \nFig. 5. Perovskite structural evolution during temperature cycling. The temperature-resolved GIWAXS profiles for (A) control and (B) target perovskites. (C) The temperature-resolved lattice strain for control and target perovskites. (The temperature starts from room temperature, heating to $+80^{\\circ}\\mathsf{C}$ and then cooling to $-60^{\\circ}\\mathsf{C}$ . The progress ends at room temperature. The time per complete cycle is 90 minutes.) \n\n# REFERENCES AND NOTES \n\n1. The National Renewable Energy Laboratory, US Departmen of Energy, Office of Energy Efficiency and Renewable Energy, Alliance for Sustainable Energy LLC., Best Research Cell Efficiency Chart, https://www.nrel.gov/pv/cellefficiency.html. \n2. X. Zheng et al., Nat. Energy 5, 131–140 (2020). \n3. Y.-N. Lu et al., Energy Environ. Sci. 14, 4048–4058 (2021). \n4. Z. Li et al., Science 376, 416–420 (2022). \n5. H. Chen et al., Nat. Photonics 16, 352–358 (2022). \n6. X. Li et al., Science 375, 434–437 (2022). \n7. M. Degani et al., Sci. Adv. 7, eabj7930 (2021). \n8. D. Luo et al., Science 360, 1442–1446 (2018). \n9. W. Tress et al., Nat. Energy 4, 568–574 (2019). \n10. S. Kahmann et al., ACS Appl. Mater. Interfaces 14, 34253–34261 (2022). \n11. X. Zhang, S.-H. Wei, Phys. Rev. Lett. 128, 136401 (2022). \n12. D.-J. Xue et al., Nat. Commun. 11, 1514 (2020). \n13. R. Cheacharoen et al., Energy Environ. Sci. 11, 144–150 (2018). \n14. C. Sun et al., Nat. Commun. 12, 2207 (2021). \n15. Z. Wang et al., Nat. Energy 2, 17135 (2017). \n16. L. Xu et al., Adv. Mater. 34, 2107111 (2022). \n17. L. Canil et al., Energy Environ. Sci. 14, 1429–1438 (2021). \n18. A. J. de Jesus Silva, M. M. Contreras, C. R. Nascimento, M. F. da Costa, Heliyon 6, e04573 (2020). \n19. P. Metrangolo, L. Canil, A. Abate, G. Terraneo, G. Cavallo, Angew. Chem. Int. Ed. 61, e202114793 (2022). \n20. Y. Moriya, R. Ishikawa, S. Akiyama, K. Ueno, H. Shirai, Chem. Lett. 49, 87–90 (2019). \n21. J. Jeong et al., Nature 592, 381–385 (2021). \n22. G. Li et al., Adv. Energy Mater. 11, 2101539 (2021). \n23. D. Koo et al., Adv. Energy Mater. 10, 2001920 (2020). \n24. S. Chen et al., Science 373, 902–907 (2021). \n25. M. Stolterfoht et al., Adv. Mater. 32, e2000080 (2020). \n26. L. Canil et al., Adv. Energy Mater. 11, 2101553 (2021). \n27. Y. Li et al., Joule 6, 676–689 (2022). \n28. Y. Cho et al., Adv. Energy Mater. 8, 1703392 (2018). \n29. H. Hu et al., J. Mater. Chem. A Mater. Energy Sustain. 8, 1578–1603 (2020). \n30. M. Qin et al., Adv. Mater. 32, e2004630 (2020). \n31. A. Y. Alsalloum et al., Energy Environ. Sci. 14, 2263–2268 (2021). \n32. P. S. C. Schulze et al., Sol. RRL 4, 2000152 (2020). \n33. R. Azmi et al., Science 376, 73–77 (2022). \n34. S. Wu et al., Joule 4, 1248–1262 (2020). \n35. Z. Dai et al., Science 372, 618–622 (2021) \n36. M. Qin et al., Adv. Mater. 31, e1901284 (2019). \n37. P. Gratia et al., ACS Energy Lett. 2, 2686–2693 (2017). \n38. W. Peng et al., Angew. Chem. Int. Ed. 55, 10686–10690 (2016). \n39. C. Zhu et al., Nat. Commun. 10, 815 (2019). \n40. J. Zhao et al., Sci. Adv. 3, eaao5616 (2017). \n41. L. Wang, Q. Gong, S. Zhan, L. Jiang, Y. Zheng, Adv. Mater. 28 7729–7735 (2016). \n\n42. L. T. Hieu, S. So, I. T. Kim, J. Hur, Chem. Eng. J. 411, 128584 (2021). 43. W. Chen et al., Adv. Funct. Mater. 29, 1808855 (2019). 44. L. Zuo et al., Sci. Adv. 3, e1700106 (2017). \n\n# ACKNOWLEDGMENTS \n\nThe authors acknowledge the support of all the technicians at Helmholtz-Zentrum Berlin (HZB). The authors thank beamline BL14B1 at the Shanghai Synchrotron Radiation Facility (SSRF) for providing the beam time. G.L., L.C., and M.H.A. thank the support from HyPerCells graduate school at HZB. R.Z. was supported by the National Natural Science Foundation of China (22103022). G.L. thanks the Chinese Scholarship Council (CSC) for its financial support (201906150131). M.S. and W.Z. thank the German Research Foundation (DFG) for funding (SPP2196, 431314977/ GRK 2642). M.S. acknowledges funding by ProperPhotoMile. Project ProperPhotoMile is supported under the umbrella of SOLAR-ERA.NET Cofund 2 by the Spanish Ministry of Science and Education and the AEI under the project PCI2020-112185 and CDTI project number IDI-20210171; the Federal Ministry for Economic Affairs and Energy based on a decision by the German Bundestag project number FKZ 03EE1070B and FKZ 03EE1070A and the Israel Ministry of Energy with project number 220-11-031. The European Commission supports SOLAR-ERA.NET within the EU Framework Programme for Research and Innovation HORIZON 2020 (Cofund ERA-NET Action, 786483). This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement 804519). Author contributions: G.L., L.W., M.L., and A.A. conceived the idea. G.L. and M.L. designed the experiments. G.L., Z.S., L.W., S.T., M.H.M., Z.Z., F.Y., and M.L. fabricated and characterized perovskite films and devices. Z.S. and C.W. conducted the GIWAXS measurements. G.L., D.H., L.W., W.Z., R.Z., F.Y., Y.J., and M.L. performed the device performance measurements. G.L., Z.S., L.C., L.W., M.L., and A.A. participated in the data analysis and result discussions. G.L. composed the manuscript. D.H., M.H.M., J.D., S.T., W.Z., J.J.J.-R., M.M.B., G.N., B.N., M.L., and A.A. contributed to suggestions for the manuscript. L.W., W.C.T., Z.L., X.G., Z.W., E.U., M.S., M.L., and A.A. provided expertise and supervised the work. All authors reviewed the manuscript. Competing interests: Authors declare that they have no competing interests. Data and materials availability: All data are available in the manuscript or the supplementary materials. License information: Copyright $\\circledcirc$ 2023 the authors, some rights reserved; exclusive licensee American \n\nAssociation for the Advancement of Science. No claim to original US government works. https://www.sciencemag.org/about/ science-licenses-journal-article-reuse \n\n# SUPPLEMENTARY MATERIALS \n\nscience.org/doi/10.1126/science.add7331 Materials and Methods \n\nSupplementary Text Figs. S1 to S39 Tables S1 to S5 References (45–52) \n\nSubmitted 30 June 2022; accepted 27 December 2022 \n10.1126/science.add7331 " + }, + { + "id": "10.1007_s40820-023-01073-x", + "DOI": "10.1007/s40820-023-01073-x", + "DOI Link": "http://dx.doi.org/10.1007/s40820-023-01073-x", + "Relative Dir Path": "mds/10.1007_s40820-023-01073-x", + "Article Title": "nullocellulose-Assisted Construction of Multifunctional MXene-Based Aerogels with Engineering Biomimetic Texture for Pressure Sensor and Compressible Electrode", + "Authors": "Xu, T; Song, Q; Liu, K; Liu, HY; Pan, JJ; Liu, W; Dai, L; Zhang, M; Wang, YX; Si, CL; Du, HS; Zhang, K", + "Source Title": "nullO-MICRO LETTERS", + "Abstract": "Multifunctional architecture with intriguing structural design is highly desired for realizing the promising performances in wearable sensors and flexible energy storage devices. Cellulose nullofiber (CNF) is employed for assisting in building conductive, hyperelastic, and ultralight Ti3C2Tx MXene hybrid aerogels with oriented tracheid-like texture. The biomimetic hybrid aerogels are constructed by a facile bidirectional freezing strategy with CNF, carbon nullotube (CNT), and MXene based on synergistic electrostatic interaction and hydrogen bonding. Entangled CNF and CNT mortars bonded with MXene bricks of the tracheid structure produce good interfacial binding, and superior mechanical strength (up to 80% compressibility and extraordinary fatigue resistance of 1000 cycles at 50% strain). Benefiting from the biomimetic texture, CNF/CNT/MXene aerogel shows ultralow density of 7.48 mg cm(-3) and excellent electrical conductivity (similar to 2400 S m(-1)). Used as pressure sensors, such aerogels exhibit appealing sensitivity performance with the linear sensitivity up to 817.3 kPa(-1), which affords their application in monitoring body surface information and detecting human motion. Furthermore, the aerogels can also act as electrode materials of compressive solid-state supercapacitors that reveal satisfactory electrochemical performance (849.2 mF cm(-2) at 0.8 mA cm(-2)) and superior long cycle compression performance (88% after 10,000 cycles at a compressive strain of 30%).", + "Times Cited, WoS Core": 274, + "Times Cited, All Databases": 279, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics; Materials Science; Physics", + "UT (Unique WOS ID)": "WOS:000968816500005", + "Markdown": "Cite as Nano-Micro Lett. (2023) 15:98 \n\n# Nanocellulose‑Assisted Construction of Multifunctional MXene‑Based Aerogels with Engineering Biomimetic Texture for Pressure Sensor and Compressible Electrode \n\nReceived: 6 January 2023 \nAccepted: 10 March 2023 \nPublished online: 10 April 2023 \n$\\circledcirc$ The Author(s) 2023 \n\nTing $\\mathrm{{Xu}^{1}}$ , Qun Song2, Kun Liu1, Huayu Liu1, Junjie $\\mathrm{Pan}^{2}$ , Wei Liu1,2, Lin Dai1, Meng Zhang1, Yaxuan Wang1, Chuanling $\\mathrm{Si}^{1,4}$ \\*, Haishun ${\\mathrm{Du}}^{3}$ \\*, Kai Zhang2 \\* \n\n# HIGHLIGHTS \n\n•\t Hyperelastic and superlight multifunctional MXene/nanocellulose composite aerogels with high conductivity are designed by constructing biomimetic texture. \n•\t The MXene/nanocellulose aerogels as flexible pressure sensors exhibit appealing linear sensitivity performance $(817.3\\mathrm{{kPa}^{-1}},$ ). \n•\t The as-prepared compressible supercapacitor with MXene/nanocellulose electrodes reveals superior electrochemical performance $(849.2\\mathrm{mF}\\mathrm{cm}^{-2}$ at $0.8\\mathrm{mA}\\mathrm{cm}^{-2}$ ). \n\nABSTRACT  Multifunctional architecture with intriguing structural design is highly desired for realizing the promising performances in wearable sensors and flexible energy storage devices. Cellulose nanofiber (CNF) is employed for assisting in building conductive, hyperelastic, and ultralight $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene hybrid aerogels with oriented tracheid-like texture. The biomimetic hybrid aerogels are constructed by a facile bidirectional freezing strategy with CNF, carbon nanotube (CNT), and MXene based on synergistic electrostatic interaction and hydrogen bonding. Entangled CNF and CNT “mortars” bonded \n\nwith MXene “bricks” of the tracheid structure produce good interfacial binding, and superior mechanical strength (up to $80\\%$ compressibility and extraordinary fatigue resistance of 1000 cycles at $50\\%$ strain). Benefiting from the biomimetic texture, CNF/CNT/MXene aerogel shows ultralow density of $7.48~\\mathrm{mg~cm}^{-3}$ and excellent electrical conductivity $(\\sim2400\\mathrm{~S~m~}^{-1},$ . Used as pressure sensors, such aerogels exhibit appealing sensitivity performance with the linear sensitivity up to $817.3\\mathrm{kPa}^{-1}$ , which affords their application in monitoring body surface information and detecting human motion. Furthermore, the aerogels can also act as electrode materials of compressive solid-state supercapacitors that reveal satisfactory electrochemical performance ( $849.2\\mathrm{mF}\\mathrm{cm}^{-2}$ at $0.8\\mathrm{mA}\\mathrm{cm}^{-2}$ ) and superior long cycle compression performance $88\\%$ after 10,000 cycles at a compressive strain of $30\\%$ ). \n\n![](images/a7ac57690392542decaa6c56b85bd50de5aa024772d5369bd2b59345a70ab1af.jpg) \n\nKEYWORDS  Nanocellulose; Aerogels; MXene; Supercapacitors; Pressure sensors \n\n# 1  Introduction \n\nWith the booming development of human–computer interaction, the Internet of Things, and wearable electronics, multifunctional materials with superb electrical conductivity and good mechanical properties are emergently desired for flexible sensors and energy storage devices [1–5]. Lightweight and elastic aerogels have been one of the most important candidates for developing high-performance multifunctional platforms due to their tunable structure, low density, and high porosity [6, 7]. The conductive carbon aerogels synthesized from nanocarbons [such as graphene oxide, carbon nanotube (CNT)] or carbonized polymer materials have been demonstrated good performances in the application of constructing flexible sensors and energy storage devices [8–11]. Although carbon aerogels show good conductivity, their components need to be further reduced or carbonized, which is prone to severe volume shrinkage, resulting in poor mechanical properties. \n\nTransition-metal carbon/nitride (MXene)-based aerogels are appealing for flexible electronics because of their highly porous structure and large internal surface areas [12–15]. MXene aerogels can be derived by direct freeze-drying or supercritical drying of MXene hydrogels. However, the relatively weak interactions between MXenes sheets derived from the surface terminations (–O, –OH, and $-\\mathrm{F}$ groups) cannot effectively balance the electrostatic repulsive interactions and the strong interplanar van der Waals interactions between MXene nanosheets, which make delaminated MXene nanosheets inevitably begin to aggregate and restack during the aerogel fabrication processes [16, 17]. The compact self-stacking structure hinders electrons transport and restricts stress transfer in 3D frameworks, bringing about poor conductivity and mechanical properties. Therefore, the introduction of hydrogen bonding, covalent bonding, or van der Waals forces by low dimensional nanomaterials [18–21] or polymers [22, 23] is useful for the construction of highperformance MXene aerogels. \n\nAt present, the development of multifunctional platforms by MXene-based aerogels is still in its infancy. Effective structure design has been verified to be of great significance in constructing functional carbon aerogels [10, 24]. Specifically, the cellulose nanofiber (CNF)/lignin-based carbon aerogel with ordered tracheid-like texture was fabricated and revealed high performance in the application of pressure sensors and flexible electrodes due to the effective stress transfer [24]. The tailored internal structure in the 3D scaffold was demonstrated to be very suitable to construct functional materials with excellent mechanical compressibility and fatigue resistance. To this end, designing MXene-based aerogels with engineering tailored architecture and components to facilitate electrons transport and stress transfer should be an effective route to obtain ideal multifunctional framework. \n\nCNF with sustainability, high aspect ratio, and abundant hydroxyl groups as a component of functional materials has been attracted increasing attention [25–28]. Herein, inspired by the hierarchical tracheid structure in nature wood, multifunctional CNF/CNT/MXene aerogels with engineering biomimetic texture are fabricated by facile bidirectional freezing strategy, demonstrating good mechanical strength and superior electrical conductivity. To this aim, three key considerations are proposed: (1) the electrostatic repulsion between CNF and MXene can avoid restacking of MXene nanosheets, (2) the entangled CNF and CNT “mortars” bonded with MXene “bricks” of the tracheid structure produce good interfacial interactions, and (3) the ordered engineering structure could effectively enable electrons transport and stress transfer. The constructed CNF/CNT/MXene aerogels as pressure sensors exhibit appealing sensing performance, which have broad applications in capturing human bio signals. The aerogels can also act as electrode materials for compressive solid-state supercapacitors with satisfactory electrochemical performance and superior long cycle compression performance. \n\n# 2  \u0007Experimental Section \n\n# 2.1  \u0007Materials \n\nTEMPO-oxidized CNF suspension was purchased from Woodelfbio Co., Ltd. (China), whose length ranged from 1 to $5\\upmu\\mathrm{m}$ and the diameter from 10 to $20\\mathrm{nm}$ . Multi-walled carbon nanotubes were purchased from Beijing HWRK Chemical Co., Ltd. (China). $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ powder was provided by Jilin 11 technology Co., Ltd. (China). PVA and Lithium fluoride (LiF) were purchased from Aladdin (China). Sulfuric acid $\\mathrm{(H}_{2}\\mathrm{SO}_{4}\\mathrm{)}$ and hydrochloric acid (HCl) were bought from Beijing Chemical Reagents Co., Ltd. (China). \n\n# 2.2  \u0007Preparation of ­Ti3C2Tx \n\n$\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ was synthesized by selectively etching the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MAX phase with LiF/HCl solution [29]. Typically, LiF powder $(1.6\\ \\mathrm{g})$ was dissolved in 9 M HCl $20~\\mathrm{mL}$ ) in a Teflon vessel and stirred for $10\\mathrm{min}$ to ensure the dissolution of LiF. Then, $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ powder $(1\\ \\mathrm{g})$ was gradually added into the above LiF/HCl etching solution, and the mixture was continuously stirred for $48\\mathrm{h}$ at $35^{\\circ}\\mathrm{C}$ to obtain a stable suspension. The etched $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ suspension was repeatedly washed with deionized water by centrifugation at $3500~\\mathrm{rpm}$ for $5\\mathrm{min}$ until the $\\mathrm{\\pH}$ of the obtained suspension was adjusted to 6. The suspension was conducted by ultrasonic treatment for $30~\\mathrm{min}$ to obtain exfoliated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ . Finally, the $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ dispersion was further centrifuged at $3500~\\mathrm{rpm}$ for $^\\textrm{\\scriptsize1h}$ to obtain the delaminated $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ sheets. \n\n# 2.3  \u0007Preparation of CNF/CNT/MXene Aerogel \n\nCNF dispersion $(4\\ \\mathrm{\\mg\\mL^{-1}},$ ) and CNT suspension $(4\\ \\mathrm{mg\\mL^{-1}},\\$ were mixed at the CNF/CNT mass ratios of 1:1, 2:1 and 3:1. The mixtures of CNF and CNT were stirred and sonicated for $^\\textrm{\\scriptsize1h}$ to form a homogeneous suspension. Then, the above mixtures of three different ratios were respectively added into MXene dispersion $(8~\\mathrm{mg~mL^{-1}},$ ) at the CNF/CNT/MXene mass ratios of 1:1:8, 2:1:7 and 3:1:6, followed by stirring and ultrasonicating for $^{\\textrm{1h}}$ . The uniform suspension was poured into a silicone mold placed on a copper bridge, one end of which was inserted into liquid nitrogen, and the other end was immersed into water at room temperature to form a temperature gradient on the copper surface. Subsequently, the sample was freeze dried at $\\mathrm{-50^{\\circ}C}$ under a pressure of 0.2 mbar for $72\\mathrm{{h}}$ in a freeze dryer to obtain CNF/CNT/MXene aerogel. \n\n# 2.4  \u0007Characterization \n\nThe morphology of MXene was characterized by transmission electron microscopy (TEM, Talos G2 200X) and Bruker multimode atomic force microscope (AFM). The microstructure of CNF/CNT/MXene aerogel was observed under a scanning electron microscopy (SEM, JEOL JSMIT300LV, Japan). X-ray diffraction (XRD) analysis was carried out using a DMAX2500 Riguku diffractometer with $\\mathrm{Cu}\\ \\mathrm{K}_{\\upalpha}$ radiation in the 2θ range of $5^{\\circ}-50^{\\circ}$ at a scan rate of $5^{\\circ}\\operatorname*{min}^{-1}$ . The surface elemental and chemical bonding in CNF/CNT/MXene aerogel were evaluated by X-ray photoelectron spectroscopy (XPS, Thermo Fisher K-Alpha, USA). The chemical structure was recorded by Fourier Transform Infrared Spectrometer (FTIR, FTIR-650, China). The electrical conductivity is determined with a 4-probeTech RST-8 resistivity meter (China). Compression and cycling tests were carried out using a universal tester (Lishi LD23.53). \n\nAssembly and sensing performance testing of strain sensor: The highly sensitive strain sensor was fabricated by placing the CNF/CNT/MXene aerogel between two pieces of copper foil adhered to a bandage. The electrical current and sensing measurements of aerogel were recorded on the electrochemical workstation. \n\nThe sensitivity $(\\mathbf{S},\\mathbf{kPa}^{-1})$ is calculated according to the following Eq. (1): \n\n$$\n\\mathrm{S}=\\delta\\big(\\Delta\\mathrm{I}/\\mathrm{I}_{0}\\big)/\\delta\\mathrm{P}\n$$ \n\nwhere $\\mathrm{I}_{0}$ is the initial current (A), $\\Delta{\\mathrm I}$ is the relative change in current (A), $\\mathrm{\\bfP}$ is the applied pressure $(\\mathrm{{kPa})}$ . \n\nElectrochemical measurements: All electrochemical tests were performed on a Chenhua $\\mathrm{CHI~}660\\mathrm{E}$ electrochemical workstation. Three-electrode electrochemical measurement was tested in $1.0\\mathrm{~M~H}_{2}\\mathrm{SO}_{4}$ aqueous solution, by using $\\mathrm{Ag/}$ $\\mathrm{\\sfAgCl}$ electrode and platinum sheet as reference electrode and counter electrode, respectively. The CNF/CNT/MXene aerogel was directly used as working electrode without additional conductive additive. Cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) were measured at room temperature. The specific capacitance of the electrode was calculated on the basis of GCD curves according to the following Eq. (2) [30]: \n\n$$\n\\mathrm{C}=\\mathrm{I}\\Delta\\mathrm{t}/\\mathrm{m}\\Delta\\mathrm{V}\n$$ \n\nwhere I is the discharge current (A), $\\Delta{\\mathfrak{t}}$ is the discharge time (s), m is the mass of electroactive material $\\mathbf{\\tau}(\\mathbf{g})$ , and $\\Delta\\mathsf{V}$ is the voltage range of discharge (V). \n\nThe solid-state supercapacitor was fabricated using two pieces of CNF/CNT/MXene aerogel as electrodes, a cellulose paper as separator, $\\mathrm{PVA}/\\mathrm{H}_{2}\\mathrm{SO}_{4}$ gel as solid electrolyte, and two pieces of copper foil as current collector. To prepare $\\mathrm{PVA}/\\mathrm{H}_{2}\\mathrm{SO}_{4}$ gel, $10\\mathrm{{g}}$ PVA was mixed with $100~\\mathrm{{mL}}$ deionized water and stirring for $6\\mathrm{{h}}$ at $95^{\\circ}\\mathrm{C}$ . After cooling, $_{\\textrm{1g}}$ of concentrated ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ was added into the above mixture. Subsequently, the CNF/CNT/MXene aerogels were placed onto copper foils and coated with $\\mathrm{PVA}/\\mathrm{H}_{2}\\mathrm{SO}_{4}$ gel. These two electrodes were separated by a cellulose paper and assembled into a sandwich architecture supercapacitor. \n\nThe areal specific capacitance of electrode $(\\mathrm{C_{\\mathrm{S}}})$ was calculated on the basis of GCD curves according to the following Eq. (3): \n\n$$\n\\mathrm{C_{\\mathrm{s}}}=2\\mathrm{I}\\Delta\\mathrm{t}/\\mathrm{S}\\Delta\\mathrm{V}\n$$ \n\nThe capacitance of the supercapacitor $\\mathrm{(C_{device})}$ was calculated according to the following Eq. (4): \n\n$$\n\\mathrm{C}_{\\mathrm{device}}=\\mathrm{C}_{\\mathrm{s}}/2=\\mathrm{I}\\Delta\\mathrm{t}/\\mathrm{S}\\Delta\\mathrm{V}\n$$ \n\nThe energy density and power density were respectively calculated according to the following equations: \n\n$$\n\\begin{array}{l}{{\\mathrm{E}=0.5\\mathrm{C}_{\\mathrm{device}}(\\Delta\\mathrm{V})^{2}/3600}}\\\\ {{\\ }}\\\\ {{\\mathrm{P}=\\mathrm{E}\\times3600/\\Delta\\mathrm{t}}}\\end{array}\n$$ \n\nwhere I is the discharge current (A), $\\Delta{\\mathfrak{t}}$ is the discharge time (s), S is the area accessible to the electrolyte, and $\\Delta\\mathsf{V}$ is the voltage range of discharge (V). \n\n# 3  \u0007Results and Discussion \n\n# 3.1  \u0007Preparation of CNF/CNT/MXene Aerogels and Structural Characterizations \n\nTo form ordered porous and robust CNF/CNT/MXene architectures, CNF is employed for tailoring the interaction between surface chemical groups and suppressing restacking of MXene sheets. Moreover, the presence of multi-walled CNT can improve the conductivity of CNF/ CNT/MXene aerogels [31]. Figure  1a illustrates the fabrication process of CNF/CNT/MXene aerogels. The high aspect ratio CNF with a diameter of $(10-15~\\mathrm{nm})$ (Fig. S1a) was prepared by 2,2,6,6-tetramethylpiperidine1-oxyl-oxide (TEMPO) oxidation and subsequent highpressure homogenization. The MXene sheets (Fig. S1b, c) were obtained by etching and exfoliating their $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX phase precursor with LiF/HCl solution to selectively remove the Al layers. Moreover, the AFM image of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ nanosheets reveals their average thickness of $1.4\\:\\mathrm{nm}$ and length of $3{\\-}4\\upmu\\mathrm{m}$ . The typical XRD patterns of raw material ­( $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX), etched $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ , and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ are shown in Fig. S2. By comparing the position of the peaks between the $\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MAX precursor and $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene, it could be found that the (002) peak shifted from $9.7^{\\circ}$ of MAX to $7.3^{\\circ}$ of MXene, indicating that the interlayer distance increased, which was attributed to the fact that the Al layer was removed and surface terminations were introduced [14]. The CNT was added into the CNF dispersion to ensure the uniform dispersion of CNT. In the dispersion of CNF/CNT, the electrostatic repulsion formed between the carboxyl groups on the CNF chain prevented the agglomeration of CNT [32]. Then, MXene suspension and the CNF/CNT dispersion were mixed to obtain the CNF/CNT/MXene (CCM) dispersion. In this process, MXene nanosheets with abundant surface oxygen-containing functional groups strongly interacted with CNF through hydrogen bonding [33]. The CNF inserted the interlayer of MXene and prevented the aggregation of MXene nanosheets. Finally, the resultant CCM dispersion suffered from the bidirectional freezing and freezedried process to obtain the CNF/CNT/MXene aerogel. As shown in Fig. 1a, by applying the bidirectional temperature gradient to CCM dispersion, water molecules nucleated at the frozen surface and grew along the direction of the temperature gradient. The intertwined CNF, CNT, and MXene were repelled by ice crystals and squeezed onto the interface, then ordered porous aerogel was obtained after freeze-drying. To investigate the effects of CNF component on porous structure, the CNF/CNT/MXene aerogels with different mass ratios and CNT/MXene aerogel were prepared, as shown in Table S1. The as-prepared CNF/ CNT/MXene aerogel demonstrates robust architecture and ultralow density, which can rest on the tips of a dandelion (Fig. 1b). The interactions among the components of CNF/ CNT/MXene aerogels were investigated in detail. In the FTIR spectrum (Fig. 1c), the typical bands of 550, 1625, and $3440\\mathrm{cm}^{-1}$ in MXene and CNF/CNT/MXene aerogels correspond to Ti–O, $\\scriptstyle{\\mathrm{C=O}}$ , and $-\\mathrm{OH}$ groups, respectively [34]. For MXene, the peaks at 1040 and $1330~\\mathrm{cm}^{-1}$ are attributed to the stretching vibration of $\\mathrm{{C-O}}$ and $-\\mathrm{OH}$ groups, confirming oxygen-containing groups on the surface of MXene. And the band relating to the stretching vibration of $-\\mathbf{CO}-$ shifts to a lower wavenumber (from 1050 to $1030~\\mathrm{{cm}^{-1}}$ ), which indicate the strong hydrogen bonding interaction between CNF and MXene nanosheets [35]. The structural evolutions from MXene to the CNF/ CNT/MXene aerogels were monitored with XRD patterns (Figs. 1d and S3). In the XRD profile of MXene, a prominent peak is found at $7.3^{\\circ}$ , corresponding to the (002) peak of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene, and the peak of $16.0^{\\circ}$ is referred to the (004) plane of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene [36]. The characteristic peak (002) in the patterns of CNF/CNT/MXene aerogels shows a left shift, indicating that the interlayer $d$ -spacing of MXene nanosheets is enlarged and CNF/CNT successfully insert the interlayers of MXene nanosheets. The XPS spectrum of CNF/CNT/MXene aerogels was also performed to study the chemical bonding states and elemental compositions of the aerogels. As demonstrated in Fig. S4a, the XPS patterns show that the CNF/CNT/ MXene aerogels contain the element of Ti, C, O, and F. The $\\mathrm{~C~}1s$ spectrum of CNF/CNT/MXene (2:1:7) aerogel is shown in Fig. S4b. A typical peak at $281.8\\ \\mathrm{eV}$ (Ti–C) is observed, the $287.5\\mathrm{eV}$ of $\\scriptstyle{\\mathrm{C=O}}$ , $286.2\\:\\mathrm{eV}$ of $\\scriptstyle\\mathbf{C-O}$ , and $284.6\\mathrm{eV}$ of (C–C) are well-maintained in the CNF/CNT/ MXene aerogels. \n\n![](images/9faa07cd68ba268d7f4f79a888c2ab10c727b5d1f747d423bbc7feeaf3d20d5d.jpg) \nFig. 1   a Schematic illustration for the fabrication process of CNF/CNT/MXene aerogels. b Photo image of the lightweight CNF/CNT/MXene aerogel on the top of a dandelion. c FTIR and d XRD patterns of MXene and different CNF/CNT/MXene aerogels \n\n![](images/0a186507b1e6b87d1e900b96fb13ca893d8a14e4ee63fec36659a4b33bfa72d4.jpg) \nFig. 2   a, b The top-view and c side-view SEM images of CNT/MXene (1:7) aerogel. d, e The top-view and f side-view SEM images of CNF/ CNT/MXene (2:1:7) aerogel, the inset is schematic diagram of the pore structure. g Schematic illustration of compression and release process for CNF/CNT/MXene aerogel (2:1:7). h Comparison of the conductivity with other MXene-based aerogels \n\nFigure 2a–f show the SEM images of CNT/MXene (1:7) and CNF/CNT/MXene (2:1:7) aerogels. The CNT/MXene (1:7) aerogel without CNF component exhibits a loosely disordered porous structure (Fig. 2a, b), and the connections between MXene sheets are not continuous (Fig. 2c), which makes the fragile and brittle architecture collapse easily by large strain compression. Conversely, the CNF/ CNT/MXene (2:1:7) aerogel demonstrates the ordered tracheid network (Fig. 2d, e) and smooth cell walls structure (Fig. 2f), exhibiting anisotropic porous structure. These structural differences can be attributed to the intrinsic interactions among the components in aerogels. For CNT/MXene aerogel, the existing relatively weak $\\pi{-}\\pi$ interaction between \n\nCNT and MXene, and the relatively weak intrinsic interaction of MXene sheets make the poor structural continuity [37]. For CNF/CNT/MXene aerogel, numerous hydrogen bonds can be formed between the groups of –COOH/–OH on CNF and –OH on the surface of MXene. The CNF acts as a coupling agent to enhance the assembled MXene sheets. Therefore, the CNF entangled with CNT interconnects adjacent MXene nanosheets to form the continuous and ordered network. Furthermore, the CNF/CNT/MXene (1:1:8) and CNF/CNT/MXene (3:1:6) aerogels also display similar pore structures, as shown in Fig. S5. However, the continuity of the biomimetic structure is broken when the CNF content is too high (Fig. S5c, d), which mainly because of the excessive \n\nCNF would join the main body of the MXene “bricks”. The designed elaborately pore structure endows CNF/CNT/ MXene (2:1:7) aerogel with superior mechanical compressibility and resilience, as shown in Fig. S6. And Fig. 2g exhibits the schematic illustration of stress transfer in internal pore structure during the compression-recovery process. Benefiting from the ordered tracheid network, the CNF/CNT/ MXene (2:1:7) aerogel with the low density of $7.5\\mathrm{mg}\\mathrm{cm}^{-3}$ also exhibits superhigh conductivity of $2400{\\mathrm{S}}{\\mathrm{m}}^{-1}$ , which is superior to that of $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene/reduced graphene oxide hybrid aerogel [38], $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}/\\mathrm{CNT}$ hybrid aerogel [18], CNF/ ammonium polyphosphate $/\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ composite aerogels [39], and etc. [29, 40], as shown in Fig. 2h. The conductivities of the aerogel along vertical and longitudinal directions were also measured to be 2080 and $2300\\mathrm{{S}\\thinspace m^{-1}}$ , respectively. The similar conductivities of three directions could be ascribed to the exceptional continuity and interconnection of the tracheid network. \n\n# 3.2  \u0007Mechanical Properties of CNF/CNT/MXene Aerogels \n\nThe compressibility and fatigue resistance are investigated to explore the effects of CNF component and the designed biomimetic porous structure on the mechanical strength of CNF/CNT/MXene aerogel. The compressibility and fatigue resistance of CNT/MXene (Fig. S7) and CNF/ CNT/MXene aerogels (Figs. 3 and S8) are demonstrated. As shown in Fig. 3a and b, The CNT/MXene (1:7) aerogel exhibit severe plastic deformation (irreversible deformation of up to $28.5\\%$ ) at $80\\%$ compression strain. In contrast, the CNF/CNT/MXene aerogels can undergo broad compression strain and show much smaller unrecoverable plastic deformation of merely $0.6\\%$ (Fig. 3b) owing to the addition of CNF and ordered tracheid structure. Figure 3c demonstrates the stress–strain curves at $40\\mathrm{-}80\\%$ compression strain of CNF/CNT/MXene (2:1:7) aerogels in X-direction. With increasing compression strains the profiles become gradually steepened. Particularly, the recovery curves almost overlap under the low strain $(\\varepsilon<60\\%)$ . This is because the distance between the aerogel sheets decreases with increasing strains in the initial elastic region but the microstructure of CNF/CNT/MXene (2:1:7) aerogel remains stable. Moreover, the fatigue resistance of \n\nCNF/CNT/MXene (2:1:7) aerogel is evaluated by cyclic compressions at a strain of $50\\%$ and $80\\%$ . Remarkably, the CNF/CNT/MXene (2:1:7) aerogel can withstand long-term compression for 1000 cycles, showing high stress retention of $90.3\\%$ at the strain of $50\\%$ (Fig. 3d). Even at $80\\%$ compression strain, the aerogel can keep a stress retention of $92.6\\%$ after 100 cycles of compression (Fig. 3e), which further proves the excellent compressibility and elasticity of CNF/CNT/MXene aerogel. Therefore, the tracheid structure including the entangled CNF and CNT “mortars” bonded with MXene “bricks” endows the aerogels with high compressibility and elasticity. As shown in Fig. 3f, the mechanical performance of CNF/CNT/MXene aerogel is superior to MXene/aramid nanofibers composite aerogel [20], many carbon-based compressible aerogels [41–45]. \n\nTo illustrate the superior structural stability of CNF/ CNT/MXene aerogels, the elastic and compressible mechanism is proposed in Fig. 3g. In the structural model, the regular mortars-bricks structure of CNF/CNT/MXene aerogel makes it possible to avoid slipping and splitting along the perpendicular direction of compression, which is more conducive to the storage of elastic energy [24]. Moreover, the entangled CNF and CNT a role in reinforcing the MXene-based architecture by interconnecting the MXene nanosheets. During the compression process, the anisotropic pore structure is deformable, facilitating the stress transformation and compression to large strains. The continuous and dense CNF/CNT/MXene hybrid architecture like a bow makes the aerogels elastic. The stress–strain curves of CNF/CNT/MXene (2:1:7) aerogel from $\\mathrm{Y}-$ and Z-directions were examined, as shown in Fig. S9. As can be seen, the structure of the aerogels was destroyed at $25\\%$ ( $\\mathbf{Z}$ -direction) and $32\\%$ (Y-direction), respectively. It could be attributed to the directional porous structure of anisotropic aerogels [40]. \n\n# 3.3  \u0007Pressure and Strain Sensing Performances of CNF/ CNT/MXene Aerogels \n\nExcellent conductivity, mechanical robustness, large compressive strain, and superior fatigue resistance make the CNF/CNT/MXene (2:1:7) aerogel a promising candidate for the flexible pressure sensor. During the process of compression, the bulb gradually turned bright in the closed circuit (Fig. S10). It is turn out that the distance between the aerogels gradually decreased, resulting in enhanced electric current and lower electrical resistance. To explore its piezoelectric properties, a sensor is fabricated with a sandwich structure by CNF/CNT/MXene (2:1:7) aerogel between two pieces of polyethylene terephthalate substrates [10], and the corresponding sensor is shown in Fig. S11. Figure S12 demonstrates the real-time current response to different pressures $(0{-}10,000\\mathrm{Pa})$ . The current intensity continuously rises with increasing pressure, demonstrating its potential application in detecting pressure. The sensing sensitivity (S) is a significant performance parameter of flexible pressure sensor, which characterizes the sensitivity of the sensor to external stress. As ${\\bf S}=(\\Delta{\\mathrm{I}}/{\\mathrm{I}_{0}})/\\Delta{\\mathrm{P}}$ [46, 47], where $\\mathrm{I}_{0}$ is the current without the external pressure, $\\Delta{\\mathrm I}$ is the relative change of the current, and $\\Delta\\mathrm{P}$ is the change external pressure. As demonstrated in Fig. 4a, like most reported sensors, the current change versus pressure curve of the CNF/CNT/MXene (2:1:7) aerogel piezosensor can be divided into two linear regions [48]. In the region of $0{-}200\\mathrm{Pa}$ , the sensitivity of $\\mathbf{S}_{1}$ is $817.3\\mathrm{{kPa}^{-1}}$ . And in the region of $200{-}1{,}500\\mathrm{Pa}$ , $\\mathbf{S}_{2}$ is up to $234.9\\mathrm{{kPa}^{-1}}$ . The sensitivities are superior to CNF/CNT/ reduced graphene oxide (RGO) carbon aerogels $(5.61\\mathrm{{kPa}^{-1}},$ [10], melamine sponge-MWCNTs $@$ CB $(48.26\\mathrm{kPa}^{-1}$ ) [49], wood-derived CNFs/lignin carbon aerogels $(5.16~\\mathrm{kPa}^{-1},$ ) [24], etc. The higher sensitivity of the CNF/CNT/MXene (2:1:7) aerogel-based pressure sensor can be attributed to the following reasons: (1) The entangled nano-CNFs and CNTs on the surface of the CNF/CNT/MXene aerogel enhance the roughness, and the larger contact area increases the number of conductive paths under the action of external force. (2) The unique tracheid structure of the aerogel makes the inner pore size and the distance between the pores uniformly decrease under the action of external force, then the closely contacted nanowalls in CNF/CNT/MXene aerogel can form lots of conductive paths. Figure 4b shows the real-time current responses of the CNF/CNT/MXene (2:1:7) aerogel for 5 cycles at compression strains from $20\\%$ to $80\\%$ . As expected, the current increased significantly during compression and decreased rapidly during release, indicating a fast current responsive capability with compressive strain for the CNF/CNT/MXene aerogel. Moreover, the 2000 cycles test experiments at $30\\%$ strain on the CNF/CNT/MXene aerogel-based sensor were performed, as shown in Fig. 4c. It was found that the CNF/CNT/MXene aerogel-based sensor exhibited good stability, and the initial current intensity was basically maintained. Furthermore, the sensor reveals rapid response ( $74\\mathrm{ms})$ and recovery $\\mathrm{\\nabla{50}m s})$ ) abilities, as shown in Fig. S13. Generally, the sensing performance of CNF/CNT/ \n\n![](images/b5265d499e8e6ec4258309b9747eb039eafd556d22f9d3bef04b1d231e222714.jpg) \nFig. 3   a Experimental photographs for the first compression cycle of CNT/MXene (1:7) and CNF/CNT/MXene (2:1:7) aerogels. b Histograms of irreversible deformation percentages after the first cycle. The inset shows the height contrast photos of samples after the first cycle (the scale bar is $1~\\mathrm{cm}$ ). c Stress–strain curves of CNF/CNT/MXene (2:1:7) aerogel at $40\\%-80\\%$ compression strains in X-direction (the inset shows the direction of compression). Stress–strain curves d at $50\\%$ strain for 1000 cycles and e at $80\\%$ strain for 100 cycles. f Comparison of the stress retention of CNF/CNT/MXene (2:1:7) aerogel with those of MXene- and carbon-based aerogels. $\\mathbf{g}$ Mechanism illustration of the compressive deformation of the CNF/CNT/MXene (2:1:7) aerogel \n\n![](images/0081daefeb72a401bb791a4a45a1776ec88a679f6fe5d587207525b6bd55c55e.jpg) \nFig. 4   a The relationship between the change of the relative current and the linear sensitivity of the pressure sensor. b Current response at various pressures of $0.1{-}6.4\\mathrm{\\kPa}$ . c Current stability at $20\\%$ strain for 2000 cycles. d Illustration diagram of application in human behavior monitoring. Current signals from e elbow swing, f wrist bending, g normal working, and $\\mathbf{h}$ finger touching \n\nMXene aerogels with those compressible MXene-based aerogels and carbon aerogels was compared (Table S3), exhibiting superior sensitivity, response/recovery time, and long-term stability. \n\nBased on the superior mechanical sensing properties of CNF/CNT/MXene aerogel, it was applied to monitor body movement and physiological state (Fig. 4d). First, the sensor was attached to the elbow, wrist, and knee to monitor joint flexion movement. As exhibited in Fig. 4e, the current gradually enhances as the angle of the elbow swing increases. At a fixed swing amplitude, the current remains relatively constant. And when the swing is repeated at the same swing angle, the current curve shows good repeatability. Similarly, for the bending of the wrist, normal working, and finger touching (Fig. 4f–h), the current response values also show the same trend and demonstrate good cycling stability. In addition, when attaching the sensor to the human throat, it can detect the current change when speaking a word such as “MXene” or “Chemical” (Fig. S14). \n\n# 3.4  \u0007Electrochemical Performance of CNF/CNT/MXene Aerogels \n\nThe ordered porous structure, superior fatigue resistance, and good electrical conductivity of the CNF/CNT/MXene aerogels make them potential as electrodes for compressible supercapacitors [50]. Firstly, the electrochemical performance of CNF/CNT/MXene aerogels was evaluated in a three-electrode system in 1 M ${\\mathrm{H}}_{2}{\\mathrm{SO}}_{4}$ electrolyte (Figs. S15–S17). As shown in Fig. S15, CNF/CNT/MXene (2:1:7) aerogel electrode showed the largest specific capacitance of $215.8\\mathrm{~F~g}^{-1}$ at $0.3\\mathrm{~A~g^{-1}}$ . This is attributed to the excellent conductivity, continuous pore wall structure, and good hydrophilic of CNF/CNT/MXene (2:1:7) aerogel that facilitate the electrons and ions transport. When a sufficiently small amount of MXene nanosheets is added to the CNF and CNT systems, MXene nanosheets are evenly dispersed in the 3D network structure resulting in a large rectangular curve [51]. In comparison, excessive MXene at higher contents will destroy the 3D pore structure of aerogels, resulting in the decrease of carbon aerogel capacitance. Figure S15a, b exhibits cyclic voltammetry (CV) curves of the CNF/CNT/ MXene (2:1:7) aerogel electrode at various scan rates from 2 to $500\\mathrm{mVs^{-1}}$ . Clearly, all the CV curves present a rectangular-like shape, indicating good electrochemical reversibility [52]. Otherwise, obvious redox peaks were observed at $2{-}50\\mathrm{mV\\s^{-1}}$ , which corresponds to the pseudo capacitance behavior of MXene. Figure S15c demonstrates the galvanostatic charge/discharge (GCD) curves of CNF/CNT/MXene (2:1:7) aerogel electrode at current density of $0.3{-}1.0\\mathrm{Ag^{-1}}$ . Even at $1.0\\mathrm{Ag}^{-1}$ , the specific capacitance of the electrode remains $146.9\\mathrm{F}\\:\\mathrm{g}^{-1}$ . The good electrochemical reversibility and rate performance make the CNF/CNT/MXene (2:1:7) aerogel promising for high-performance supercapacitors. \n\nTo show the potential application of CNF/CNT/MXene aerogel as the compressible electrode, the sandwich-like compressible supercapacitors (Fig. 5a) were assembled with the same two CNF/CNT/MXene (2:1:7) aerogel electrodes and polyvinyl alcohol $\\mathrm{{\\cal{H}}}_{2}\\mathrm{{SO}}_{4}$ $\\mathrm{(PVA/H}_{2}\\mathrm{SO}_{4}\\mathrm{)}$ gel electrolyte. By tuning the thickness of the compressible supercapacitors, the strains of CNF/CNT/MXene aerogel can be facilely controlled. Figure 5b shows the CV profiles of the compressible supercapacitors under different strains. The CV curves of obtained solid supercapacitors showed similar shapes at different scan rates $(2{-}50\\ \\mathrm{mV\\s^{-1}})$ , indicating good rate-adaptive performance and electrochemical reversibility. The solid-state supercapacitors at different current densities showed good capacitive behaviors based on their almost symmetrical triangle shapes within GCD curves (Fig. 5c). Based on these GCD curves, the electrodes delivered an areal specific capacitance of $849.2~\\mathrm{mF~cm}^{-2}$ at a current density of $0.8~\\mathrm{mA}~\\mathrm{cm}^{-2}$ , which is higher than that of CNF/CNT/RGO carbon aerogel $(109.4~\\mathrm{mF~cm}^{-2}$ at $0.4\\mathrm{\\mA\\cm^{-2}}$ ) [10], MXene-RGO composite aerogel $34.6~\\mathrm{mF~cm}^{-2}$ at $1\\mathrm{mV}\\mathrm{s}^{-1}$ ) [20], and comparable to the 3D printed carbon aerogel $\\cdot870.3\\mathrm{~mF~cm^{-2}})$ [53], and other aerogels [54, 55]. As shown in Fig. S18, the specific capacitance retention of the solid-state supercapacitors is as high as $88\\%$ even after 10,000 charging and discharging cycles at a current density of $10\\mathrm{mA}\\mathrm{cm}^{-2}$ , highlighting its excellent cycle stability. Furthermore, the assembled solidstate supercapacitors delivered an energy density of about $21.2~\\upmu\\mathrm{Wh}~\\mathrm{cm}^{-2}$ at a power density of $240.0~\\upmu\\mathrm{W}~\\mathrm{cm}^{-2}$ . The excellent electrochemical performance should be attributed to the highly porous structure of the CNF/CNT/MXene aerogel, which enable the enhanced interface and high contact surface area between the microcells inside the electrode and the electrolyte, thereby reducing the interface transfer resistance and improving the capacitance [56]. Owing to the high mechanical compressibility of CNF/CNT/MXene aerogel, assembled solid-state supercapacitors are expected to be highly compressible. To evaluate the compressibility, solid supercapacitors were tested under different compressive strains. It is obvious that the devices can withstand up to $80\\%$ strain without structural damage. The GCD curves expanded as the strain increased from 0 to $80\\%$ , and the capacitive performance of the device was significantly enhanced (Fig. 5d). Similarly, the area of CV curves became larger with increasing compression strains (Fig. S19). The capacitance retention under different strains is shown in Fig. S20. To understand the mechanism of the performance difference, the EIS of solid-state supercapacitor under various strains were performed and the Nyquist plots are presented in Fig. 5e. It is seen that all the Nyquist plots display similar shape consisting of an arc in the higher frequency region followed by a spike at low frequency. The charge transfer resistance $(\\mathbf{R}_{\\mathrm{ct}})$ is found to decrease with the increase of the strains, showing gradually enhanced charge transfer capability at the electrode/electrolyte interfaces due to the improved conductivity at higher strains [57, 58]. Therefore, increasing compression should improve the interface contact between electrolyte and electrode, thereby increasing the accessible electrochemical position and accelerating ion transfer (Fig. 5g). Apart from the outstanding energy density and power density, the solid-state symmetric supercapacitor also exhibited excellent cycling stability under compressive strain. At a strain of $30\\%$ , almost of its initial capacitance was retained after 10,000 consecutive cycles, suggesting the excellent cycling stability of assembled devices under high compression (Fig. 5f). The strategy of using compressive CNF/CNT/MXene aerogel as composite electrodes provides a novel and feasible method for the preparation of compressible supercapacitors with high electrochemical and mechanical properties. \n\n![](images/d07677d0eb1177532ad044cb54fba19ea9f6771cf8b3c1b88d275f6d63eb3120.jpg) \nFig. 5   a Schematic illustration of the assembled compressible supercapacitor. b CV curves of compressible supercapacitor at scan rates of $2{-}\\bar{5}0\\ \\mathrm{mV\\}\\mathrm{s}^{-1}$ . c GCD curves at different areal current densities. d GCD curves and e Nyquist plots of compressible supercapacitor under various strains from 0 to $80\\%$ . f Cycling stability of solid-state compressible supercapacitors over 10,000 cycles under $30\\%$ strain. g The process illustration of ions and electrons transport in electrodes before and after compression \n\n# 4  \u0007Conclusions \n\nIn summary, multifunctional conductive nanocellulose/ carbon nanotube/MXene aerogels have been designed and fabricated with ultralight and superior mechanical strength by facile bidirectional freezing. Supporting CNF and CNT in the composite aerogels effectively inhibited the stacking of MXene nanosheets, resulting in the formation of regularly arranged tracheid-like architecture. The abundant oriented pore structure not only effectively transferred stress, but also contributed to the transportation of electrons and ions. Being used as electrodes for strain sensors, the composite aerogel exhibited good linear sensitivity of $817.3\\mathrm{kPa}^{-1}$ , demonstrating application prospects in monitoring body movement and physiology. Moreover, the CNF/CNT/MXene aerogel can be used for solid-state compressible supercapacitors, and displayed significant electrochemical performances, including high capacitance $849.2\\mathrm{mF}\\mathrm{cm}^{-2}$ at $0.8\\mathrm{mA}\\mathrm{cm}^{-2}$ ), outstanding cycling stability ( $88\\%$ capacitance retention after 10,000 cycles), and superior mechanical flexibility. It is believed that this research can provide a facile but effective method for constructing high-performance and promising multifunctional platforms. \n\nAcknowledgements  This work is supported by the Project of Jinan City (202228044), National Natural Science Foundation of China (32071720, 32271814) and the China Postdoctoral Science Foundation (2021M702456). Q.S., J.P. and W. L. thank China Scholarship Council for supporting their PhD program. \n\nFunding  Open access funding provided by Shanghai Jiao Tong University. \n\nOpen Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative \n\nCommons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. \n\nSupplementary Information  The online version contains supplementary material available at https://​doi.​org/​10.​1007/ s40820-​023-​01073-x. \n\n# References \n\n1.\t P. Simon, Y. Gogotsi, Perspectives for electrochemical capacitors and related devices. Nat. Mater. 19, 1151–1163 (2020). https://​doi.​org/​10.​1038/​s41563-​020-​0747-z \n2.\t L. Fan, H. He, C. Nan, Tailoring inorganic–polymer composites for the mass production of solid-state batteries. Nat. Rev. Mater. 6, 1003–1019 (2021). https://​doi.​org/​10.​1038/ s41578-​021-​00320-0 \n3.\t T. Xu, K. Liu, N. Sheng, M. Zhang, W. Liu et al., Biopolymer-based hydrogel electrolytes for advanced energy storage/ conversion devices: properties, applications, and perspectives. Energy Storage Mater. 48, 244–262 (2022). https://​doi.​org/​10. 1016/j.​ensm.​2022.​03.​013 \n4.\t X. Wei, H. Li, W. Yue, S. Gao, Z. Chen et al., A high-accuracy, real-time, intelligent material perception system with a machine-learning motivated pressure-sensitive electronic skin. Matter 5, 1481–1501 (2022). https://​doi.​org/​10.​1016/j.​matt. 2022.​02.​016 \n5.\t H. Niu, S. Gao, W. Yue, Y. Li, W. Zhou et al., Highly morphology-controllable and highly sensitive capacitive tactile sensor based on epidermis-dermis-inspired interlocked asymmetricnanocone arrays for detection of tiny pressure. Small 16, 1904774 (2019). https://​doi.​org/​10.​1002/​smll.​20190​4774 \n6.\t Y. Chen, L. Zhang, Y. Yang, B. Pang, W. Xu et al., Recent progress on nanocellulose aerogels: preparation, modification, composite fabrication, applications. Adv. Mater. 33, 2005569 (2021). https://​doi.​org/​10.​1002/​adma.​20200​5569 \n7.\t T. Xu, H. Du, H. Liu, W. Liu, X. Zhang et al., Advanced nanocellulose-based composites for flexible functional energy storage devices. Adv. Mater. 33, 2101368 (2021). https://​doi.​org/ 10.​1002/​adma.​20210​1368 \n8.\t Z. Wang, H. Gao, Q. Zhang, Y. Liu, J. Chen et al., Recent advances in 3D graphene architectures and their composites for energy storage applications. Small 15, 1803858 (2019). https://​doi.​org/​10.​1002/​smll.​20180​3858 \n9.\t G. Zu, X. Wang, K. Kanamori, K. Nakanishi, Superhydrophobic highly flexible doubly cross-linked aerogel/carbon nanotube composites as strain/pressure sensors. J. Mater. Chem. B 8, 4883–4889 (2020). https://​doi.​org/​10.​1039/​C9TB0​2953B \n10.\t H. Liu, T. Xu, C. Cai, K. Liu, W. Liu et  al., Multifunctional superelastic, superhydrophilic, and ultralight nanocellulose-based composite carbon aerogels for compressive supercapacitor and strain sensor. Adv. Funct. Mater. 32, 2113082 (2022). https://​doi.​org/​10.​1002/​adfm.​20211​3082 \n11.\t V. Rahmanian, T. Pirzada, S. Wang, S.A. Khan, Cellulosebased hybrid aerogels: strategies toward design and functionality. Adv. Mater. 33, 2102892 (2021). https://​doi.​org/​10.​1002/ adma.​20210​2892 \n12.\t T. Shang, Z. Lin, C. Qi, X. Liu, P. Li et al., 3D macroscopic architectures from self-assembled MXene hydrogels. Adv. Funct. Mater. 29, 1903960 (2019). https://​doi.​org/​10.​1002/ adfm.​20190​3960 \n13.\t Y. Ma, Y. Yue, H. Zhang, F. Cheng, W. Zhao et al., 3D synergistical MXene/reduced graphene oxide aerogel for a piezoresistive sensor. ACS Nano 12, 3209–3216 (2018). https://​doi.​ org/​10.​1021/​acsna​no.​7b069​09 \n14.\t J. Liu, H.-B. Zhang, R. Sun, Y. Liu, Z. Liu et al., Hydrophobic, flexible, and lightweight MXene foams for high-performance electromagnetic-interference shielding. Adv. Mater. 29, 1702367 (2017). https://​doi.​org/​10.​1002/​adma.​20170​2367 \n15.\t M. Ding, S. Li, L. Guo, L. Jing, S. Gao et  al., Metal ioninduced assembly of MXene aerogels via biomimetic microtextures for electromagnetic interference shielding, capacitive deionization, and microsupercapacitors. Adv. Energy Mater. 11, 2101494 (2021). https://​doi.​org/​10.​1002/​aenm.​20210​1494 \n16.\t C. Zhang, Interfacial assembly of two-dimensional MXenes. J. Energy Chem. 60, 417–434 (2021). https://​doi.​org/​10.​1016/j. jechem.​2020.​12.​036 \n17.\t Z. Wu, T. Shang, Y. Deng, Y. Tao, Q.-H. Yang, The assembly of MXenes from 2D to 3D. Adv. Sci. 7, 1903077 (2020). https://​doi.​org/​10.​1002/​advs.​20190​3077 \n18.\t P. Sambyal, A. Iqbal, J. Hong, H. Kim, M.-K. Kim et  al., Ultralight and mechanically robust $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ hybrid aerogel reinforced by carbon nanotubes for electromagnetic interference shielding. ACS Appl. Mater. Interfaces 11, 38046–38054 (2019). https://​doi.​org/​10.​1021/​acsami.​9b125​50 \n19.\t Z. Zeng, C. Wang, G. Siqueira, D. Han, A. Huch et al., Nanocellulose–MXene biomimetic aerogels with orientation-tunable electromagnetic interference shielding performance. Adv. Sci. 7, 2000979 (2020). https://​doi.​org/​10.​1002/​advs.​20200​ 0979 \n20.\t Y. Yue, N. Liu, Y. Ma, S. Wang, W. Liu et al., Highly selfhealable 3D microsupercapacitor with MXene–graphene composite aerogel. ACS Nano 12, 4224–4232 (2018). https://​doi.​ org/​10.​1021/​acsna​no.​7b075​28 \n21.\t Z. Chen, Y. Hu, H. Zhuo, L. Liu, S. Jing et al., Compressible, elastic, and pressure-sensitive carbon aerogels derived from 2D titanium carbide nanosheets and bacterial cellulose for wearable sensors. Chem. Mater. 31, 3301–3312 (2019). https://​doi.​org/​10.​1021/​acs.​chemm​ater.​9b002​59 \n22.\t L. Wang, M. Zhang, B. Yang, J. Tan, X. Ding, Highly compressible, thermally stable, light-weight, and robust aramid nanofibers $/\\mathrm{Ti}_{3}\\mathrm{AlC}_{2}$ MXene composite aerogel for sensitive pressure sensor. ACS Nano 14, 10633–10647 (2020). https://​ doi.​org/​10.​1021/​acsna​no.​0c048​88 \n23.\t X. Wu, B. Han, H.-B. Zhang, X. Xie, T. Tu et  al., Compressible, durable and conductive polydimethylsiloxanecoated MXene foams for high-performance electromagnetic interference shielding. Chem. Eng. J. 381, 122622 (2020). https://​doi.​org/​10.​1016/j.​cej.​2019.​122622 \n24.\t Z. Chen, H. Zhuo, Y. Hu, H. Lai, L. Liu et al., Wood-derived lightweight and elastic carbon aerogel for pressure sensing and energy storage. Adv. Funct. Mater. 30, 1910292 (2020). https://​doi.​org/​10.​1002/​adfm.​20191​0292 \n25.\t W. Liu, K. Liu, H. Du, T. Zheng, N. Zhang et al., Cellulose nanopaper: fabrication, functionalization, and applications. Nano-Micro Lett. 14, 104 (2022). https://​doi.​org/​10.​1007/​ s40820-​022-​00849-x \n26.\t D. Zhao, B. Pang, Y. Zhu, W. Cheng, K. Cao et al. A stiffnessswitchable, biomimetic smart material enabled by supramolecular reconfiguration. Adv. Mater. 34, 2107857 (2022). https://​ doi.​org/​10.​1002/​adma.​20210​7857 \n27.\t H. Liu, H. Du, T. Zheng, K. Liu, X. Ji et al., Cellulose based composite foams and aerogels for advanced energy storage devices. Chem. Eng. J. 426, 130817 (2021). https://​doi.​org/​ 10.​1016/j.​cej.​2021.​130817 \n28.\t T. Budtova, Cellulose II aerogels: a review. Cellulose 26, 81–121 (2019). https://​doi.​org/​10.​1007/​s10570-​018-​2189-1 \n29.\t C. Ma, Q. Yuan, H. Du, M. Ma, C. Si et  al., Multiresponsive MXene $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}})$ -decorated textiles for wearable thermal management and human motion monitoring. ACS Appl. Mater. Interfaces 12, 34226–34234 (2020). https://​doi.​org/​10.​ 1021/​acsami.​0c107​50 \n30.\t T. Xu, D. Yang, S. Zhang, T. Zhao, M. Zhang et al., Antifreezing and stretchable all-gel-state supercapacitor with enhanced capacitances established by graphene/PEDOT-polyvinyl alcohol hydrogel fibers with dual networks. Carbon 171, 201–210 (2021). https://​doi.​org/​10.​1016/j.​carbon.​2020.​08.​071 \n31.\t Z. Deng, P. Tang, X. Wu, H. Zhang, Z.-Z. Yu, Superelastic, ultralight, and conductive $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene/acidified carbon nanotube anisotropic aerogels for electromagnetic interference shielding. ACS Appl. Mater. Interfaces 13, 20539–20547 (2021). https://​doi.​org/​10.​1021/​acsami.​1c020​59 \n32.\t Q. Zheng, Z. Cai, Z. Ma, S. Gong, Cellulose nanofibril/ reduced graphene oxide/carbon nanotube hybrid aerogels for highly flexible and all-solid-state supercapacitors. ACS Appl. Mater. Interfaces 7, 3263–3271 (2015). https://​doi.​org/​10. 1021/​am507​999s \n33.\t W. Tian, A. VahidMohammadi, M.S. Reid, Z. Wang, L. Ouyang et al., Multifunctional nanocomposites with high strength and capacitance using 2D MXene and 1D nanocellulose. Adv. Mater. 31, 1902977 (2019). https://​doi.​org/​10.​1002/​adma.​ 20190​2977 \n34.\t Y. Wan, P. Xiong, J. Liu, F. Feng, X. Xun et al., Ultrathin, strong, and highly flexible $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene/bacterial cellulose composite films for high-performance electromagnetic interference shielding. ACS Nano 15, 8439–8449 (2021). https://​ doi.​org/​10.​1021/​acsna​no.​0c106​66 \n35.\t Z. Zhan, Q. Song, Z. Zhou, C. Lu, Ultrastrong and conductive MXene/cellulose nanofiber films enhanced by hierarchical nano-architecture and interfacial interaction for flexible electromagnetic interference shielding. J. Mater. Chem. C 7, 9820–9829 (2019). https://​doi.​org/​10.​1039/​C9TC0​3309B \n36.\t A. Lipatov, M. Alhabeb, M.R. Lukatskaya, A. Boson, Y. Gogotsi et al., Effect of synthesis on quality, electronic properties and environmental stability of individual monolayer $\\mathrm{Ti}_{3}\\mathrm{C}_{2}$ MXene flakes. Adv. Electron. Mater. 2, 1600255 (2016). https://​doi.​org/​10.​1002/​aelm.​20160​0255 \n37.\t J. Liu, H.-B. Zhang, X. Xie, R. Yang, Z. Liu et al., Multifunctional, superelastic, and lightweight MXene/polyimide aerogels. Small 14, 1802479 (2018). https://​doi.​org/​10.​1002/ smll.​20180​2479 \n38.\t S. Zhao, H.-B. Zhang, J. Luo, Q. Wang, B. Xu et al., Highly electrically conductive three dimensional $\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}}$ MXene/ reduced graphene oxide hybrid aerogels with excellent electromagnetic interference shielding performances. ACS Nano 12, 11193–11202 (2018). https://​doi.​org/​10.​1021/​acsna​no.​ 8b057​39 \n39.\t Y. Zhang, J. Yu, J. Lu, C. Zhu, D. Qi, Facile construction of 2D MXene $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}})$ based aerogels with effective fireresistance and electromagnetic interference shielding performance. J. Alloys Compd. 870, 159442 (2021). https://​doi.​org/ 10.​1016/j.​jallc​om.​2021.​159442 \n40.\t Y. Dai, X. Wu, Z. Liu, H.-B. Zhang, Z.-Z. Yu, Highly sensitive, robust and anisotropic MXene aerogels for efficient broadband microwave absorption. Compos. Part B 200, 108263 (2020). https://​doi.​org/​10.​1016/j.​compo​sitesb.​2020. 108263 \n41.\t Q. Wang, T. Xia, X. Jia, J. Zhao, Q. Li et al., Honeycombstructured carbon aerogels from nanocellulose and skin secretion of Andrias davidianus for highly compressible binderfree supercapacitors. Carbohydr. Polym. 245, 116554 (2020). https://​doi.​org/​10.​1016/j.​carbp​ol.​2020.​116554 \n42.\t Y. Si, X. Wang, C. Yan, L. Yang, J. Yu et al., Ultralight biomass-derived carbonaceous nanofibrous aerogels with superelasticity and high pressure-sensitivity. Adv. Mater. 28, 9512 (2016). https://​doi.​org/​10.​1002/​adma.​20160​3143 \n43.\t J. Xiao, Y. Tan, Y. Song, Q. Zheng, A flyweight and superelastic graphene aerogel as a high-capacity adsorbent and highly sensitive pressure sensor. J. Mater. Chem. A 6, 9074–9080 (2018). https://​doi.​org/​10.​1039/​C7TA1​1348J \n44.\t L. Li, T. Hu, H. Sun, J. Zhang, A. Wang, Pressure-sensitive and conductive carbon aerogels from poplars catkins for selective oil absorption and oil/water separation. ACS Appl. Mater. Interfaces 9, 18001–18007 (2017). https://​doi.​org/​10.​1021/​ acsami.​7b046​87 \n45.\t J. Zhang, B. Li, L. Li, A. Wang, Ultralight, compressible and multifunctional carbon aerogels based on natural tubular cellulose. J. Mater. Chem. A 4, 2069–2074 (2016). https://​doi. org/​10.​1039/​C5TA1​0001A \n46.\t B. Yin, X. Liu, H. Gao, T. Fu, J. Yao, Bioinspired and bristled microparticles for ultrasensitive pressure and strain sensors. Nat. Commun. 9, 5161 (2018). https://​doi.​org/​10.​1038/ s41467-​018-​07672-2 \n47.\t H. Niu, H. Li, S. Gao, Y. Li, X. Wei et al., Perception-to-cognition tactile sensing based on artificial-intelligence-motivated human full-skin bionic electronic skin. Adv. Mater. 34, 2202622 (2022). https://​doi.​org/​10.​1002/​adma.​20220​2622 \n48.\t C. Liu, Q. Tan, Y. Deng, P. Ye, L. Kong et al., Highly sensitive and stable 3D flexible pressure sensor based on carbon black and multi-walled carbon nanotubes prepared by hydrothermal method. Compos. Commun. 32, 101178 (2022). https://​doi. org/​10.​1016/j.​coco.​2022.​101178 \n49.\t T. Su, N. Liu, Y. Gao, D. Lei, L. Wang et al., MXene/cellulose nanofiber-foam based high performance degradable piezoresistive sensor with greatly expanded interlayer distances. Nano Energy 87, 106151 (2021). https://​doi.​org/​10.​1016/j.​nanoen.​ 2021.​106151 \n50.\t L. Liu, Z. Niu, J. Chen, Unconventional supercapacitors from nanocarbon-based electrode materials to device configurations. Chem. Soc. Rev. 45, 4340–4363 (2016). https://​doi.​org/​ 10.​1039/​C6CS0​0041J \n51.\t W. Chen, D. Zhang, K. Yang, M. Luo, P. Yang et al., MXene $(\\mathrm{Ti}_{3}\\mathrm{C}_{2}\\mathrm{T}_{\\mathrm{x}})$ /cellulose nanofiber/porous carbon film as freestanding electrode for ultrathin and flexible supercapacitors. Chem. Eng. J. 413, 127524 (2021). https://​doi.​org/​10.​1016/j. cej.​2020.​127524 \n52.\t J. Nan, G. Zhang, T. Zhu, Z. Wang, L. Wang et al., A highly elastic and fatigue-resistant natural protein-reinforced hydrogel electrolyte for reversible-compressible quasi-solid-state supercapacitors. Adv. Sci. 7, 2000587 (2020). https://​doi.​org/​ 10.​1002/​advs.​20200​0587 \n53.\t S. Yuan, W. Fan, D. Wang, L. Zhang, Y.-E. Miao et al., 3D printed carbon aerogel microlattices for customizable supercapacitors with high areal capacitance. J. Mater. Chem. A 9, 423–432 (2021). https://​doi.​org/​10.​1039/​d0ta0​8750e \n54.\t Y. Liu, D. Wang, C. Zhang, Y. Zhao, P. Ma et al., Compressible and lightweight MXene/carbon nanofiber aerogel with “layer-strut” bracing microscopic architecture for efficient energy storage. Adv. Fiber Mater. 4, 820–831 (2022). https://​ doi.​org/​10.​1007/​s42765-​022-​00140-z \n55.\t X. Cheng, D. Wang, H. Ke, Y. Li, Y. Cai et al., Hierarchical $\\mathrm{NiCo_{2}S_{4}/P A N I/C N T}$ nanostructures grown on graphene polyamide blend fiber as effective electrode for supercapacitors. Compos. Commun. 30, 101073 (2022). https://​doi.​org/ 10.​1016/j.​coco.​2022.​101073 \n56.\t C. Zhu, T.Y.-J. Han, E.B. Duoss, A.M. Golobic, J.D. Kuntz et al., Highly compressible 3D periodic graphene aerogel microlattices. Nat. Commun. 6, 6962 (2015). https://​doi.​org/​10. 1038/​ncomm​s7962 \n57.\t Z. Yang, L. Jin, G. Lu, Q. Xiao, Y. Zhang et al., Spongetemplated preparation of high surface area graphene with ultrahigh capacitive deionization performance. Adv. Funct. Mater. 24, 3917–3925 (2014). https://​doi.​org/​10.​1002/​adfm. 20130​4091 \n58.\t H. Liu, T. Xu, Q. Liang, Q. Zhao, D. Zhao et al., Compressible cellulose nanofibrils/reduced graphene oxide composite carbon aerogel for solid-state supercapacitor. Adv. Compos. Hybrid Mater. 5, 1168–1179 (2022). https://​doi.​org/​10.​1007/​ s42114-​022-​00427-0 " + }, + { + "id": "10.1038_s41467-023-39637-5", + "DOI": "10.1038/s41467-023-39637-5", + "DOI Link": "http://dx.doi.org/10.1038/s41467-023-39637-5", + "Relative Dir Path": "mds/10.1038_s41467-023-39637-5", + "Article Title": "Revealing the closed pore formation of waste wood-derived hard carbon for advanced sodium-ion battery", + "Authors": "Tang, Z; Zhang, R; Wang, HY; Zhou, SY; Pan, ZY; Huang, YC; Sun, D; Tang, YG; Ji, XB; Amine, K; Shao, MH", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Although the closed pore structure plays a key role in contributing low-voltage plateau capacity of hard carbon anode for sodium-ion batteries, the formation mechanism of closed pores is still under debate. Here, we employ waste wood-derived hard carbon as a template to systematically establish the formation mechanisms of closed pores and their effect on sodium storage performance. We find that the high crystallinity cellulose in nature wood decomposes to long-range carbon layers as the wall of closed pore, and the amorphous component can hinder the graphitization of carbon layer and induce the crispation of long-range carbon layers. The optimized sample demonstrates a high reversible capacity of 430 mAh g-1 at 20 mA g-1 (plateau capacity of 293 mAh g-1 for the second cycle), as well as good rate and stable cycling performances (85.4% after 400 cycles at 500 mA g-1). Deep insights into the closed pore formation will greatly forward the rational design of hard carbon anode with high capacity. It is essential to investigate the formation mechanism of closed pore, which contributes to low-voltage plateau capacity of hard carbon anode in sodium ion batteries. Herein, the authors explore the impact of wood precursor components and carbonization temperature on closed pore formation in hard carbon for enhanced battery performance.", + "Times Cited, WoS Core": 255, + "Times Cited, All Databases": 268, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:001095471200017", + "Markdown": "# Revealing the closed pore formation of waste wood-derived hard carbon for advanced sodium-ion battery \n\nReceived: 15 July 2022 \n\nAccepted: 21 June 2023 \n\nPublished online: 27 September 2023 \n\n# Check for updates \n\nZheng Tang1,5, Rui Zhang1,5, Haiyan Wang 1 , Siyu Zhou1,2, Zhiyi Pan3, Yuancheng Huang1, Dan Sun 1 , Yougen Tang1, Xiaobo Ji1, Khalil Amine 4 & Minhua Shao 2 \n\nAlthough the closed pore structure plays a key role in contributing low-voltage plateau capacity of hard carbon anode for sodium-ion batteries, the formation mechanism of closed pores is still under debate. Here, we employ waste woodderived hard carbon as a template to systematically establish the formation mechanisms of closed pores and their effect on sodium storage performance. We find that the high crystallinity cellulose in nature wood decomposes to long-range carbon layers as the wall of closed pore, and the amorphous component can hinder the graphitization of carbon layer and induce the crispation of long-range carbon layers. The optimized sample demonstrates a high reversible capacity of $430\\mathrm{mAhg^{-1}}$ at $20\\mathrm{mAg^{-1}}$ (plateau capacity of $293\\mathrm{mAhg^{-1}}$ for the second cycle), as well as good rate and stable cycling performances $85.4\\%$ after 400 cycles at $500\\mathrm{mAg^{-1}}$ ). Deep insights into the closed pore formation will greatly forward the rational design of hard carbon anode with high capacity. \n\nSodium-ion batteries (SIBs) are one of the most promising candidates of lithium-ion batteries (LIBs) for large-scale electrical energy storage and low-speed electric vehicles due to the low cost and abundance of sodium resources1. Although plenty of cathode materials have been developed, the lack of high-performance anode materials greatly impedes the further improvement of energy density in SIBs. For instance, graphite, which is a benchmark anode material for LIBs, demonstrates limited sodium storage capacity because of the instability of sodium-graphite intercalation compounds2. In this respect, the innovation of affordable and achievable anode materials with remarkable performance is of great significance. \n\nAmong the various reported anode materials, hard carbon is the most promising one for practical SIBs owing to its balanced performances in terms of moderate specific capacity $(\\small{\\sim}300\\mathrm{mAh}\\mathrm{g}^{-1})$ , low operating potential (\\~0.2 V), low cost, and long cycle life3. Noting that the sodium storage mechanism of hard carbon is still controversial, which severely hinders the further improvement of specific capacity and rate capability2,4. As is well known, hard carbon is composed of randomly oriented, curved, and defective graphene nanosheets, turbostratic structure with large interlayer distance5–7. Recent declaration on the sodium storage mechanism by Hu et al. pointed out that the sloping and plateau capacity relates to the complex turbostratic structure and internal closed pore, respectively8. It should be noted that the exact nature of the sodium stored within the pores is disputed, with some observing metallic sodium, whilst only ionic sodium is present in other systems8–11. The low-voltage plateau capacity is the main contributor to the higher energy density of hard carbon anodes for SIBs3,12,13. Therefore, it is urgent to gain a deep understanding of the sodium storage mechanism and elaborate on how to design the microstructure of hard carbon. \n\nAccording to previous reports, a low-cost method to prepare hard carbon is carbonizing biomass, such as apricot shells14, rice husks15, lotus seedpods and stems16,17, banana peels18, coconut oil19, palm fruit calyx20, and cotton7. As well known, large amounts of waste wood are used to generate electricity by burning, discarded to rubbish, and plant agriculture21. Fabrication of higher-value products from waste wood is an important route to improve its economic competitiveness and utilization efficiency21. Moreover, wood-derived materials show unique advantages in terms of resource abundance, renewability, sustainability, and material cost, which are intriguing for electrochemical energy storage, especially for the low-cost stationary grid and portable electronics22. Hence, these unique advantages and significance inspire researchers to develop high-performance hard carbon materials derived from waste wood. Wang et al. proposed a poreforming-opening strategy to achieve a high-capacity hard carbon anode with the precursor of natural balsa (439 mAh $\\mathbf{g}^{-1}$ at $100\\mathrm{mAg^{-1}})^{23}$ . Our group also successfully regulated the pore structure of rose woodderived hard carbon via chemical pre-treatment and low-temperature pyrolysis24. The as-prepared carbon anode delivered a capacity of $326\\mathrm{mAhg^{-1}}$ at $20\\mathrm{mAg^{-1}}$ . Nevertheless, a more systematic formation mechanism of closed pores has not been established sufficiently in wood-derived carbon materials. \n\nIn this work, we investigate the effect of different components (crystalline cellulose and amorphous hemicellulose/lignin) in natural wood precursor and carbonization temperature on the formation of closed pore structure in the derived hard carbon. With the support of in-situ or ex-situ characterization techniques, we reveal that long graphite-like layers originated from the decomposition of crystalline cellulose serve as the wall of closed pore structure, while the amorphous hemicellulose and lignin are the inhibitors that prevent the overgraphitization of carbon layer during the high-temperature carbonization. Besides, the length of graphite-like carbon layer increases with the increase in carbonization temperature, accelerating the formation of closed pore structure. Meanwhile, the optimum hard carbon derived from waste wood displays good rate capability, high reversible plateau capacity, and stable cycling performance. The proposed closed pore formation mechanism for waste wood-derived carbon can motivate us to develop hard carbon anodes with high plateau-region capacity towards high-energy density SIBs. \n\n# Results \n\n# The role of crystalline cellulose content on forming closed pore in hard carbon \n\nAs is well known, wood is a complex composite composed of cellulose, hemicellulose, lignin, and so on25–28. To better uncover the correlation between the composition of wood precursor and the microstructure in its derived hard carbon, three wood precursors with low, middle and high contents of crystalline cellulose were chosen and noted as Lwood, M-wood and H-wood, respectively. To quantify the cellulose crystallinity in wood precursors, powder X-ray diffraction (XRD) tests were performed. As shown in Fig. 1a, three peaks at $17^{\\circ}$ , $22^{\\circ}$ , and $35^{\\circ}$ are indexed to the crystalline cellulose29. According to the intensity of the characteristic peak at $22^{\\circ}$ and the Segal method30, the crystalline cellulose contents for L-wood, M-wood and H-wood are calculated to be $49.9\\%$ , $53.2\\%$ and $68.4\\%$ , respectively. The crystallinity index values of cellulose in L-wood, M-wood and $\\mathsf{H}$ -wood are 0.97, 0.98 and 1.09, respectively, which are calculated based on Nelson and O’connor method according to the Fourier transforms infrared (FTIR) spectra (Fig. 1b)31. The morphology and microstructure of wood precursors were investigated with SEM and HRTEM. L-wood (Fig. 1c and Supplementary Fig. 1a, b) mainly consists of many uniform tracheid cells, similar to a honeycomb-like structure. As the wood cellulose crystallinity increases, both M-wood (Fig. 1d and Supplementary Fig. 1c, d) and H-wood (Fig. 1e and Supplementary Fig. 1e, f) show more complicated micromorphology with thicker walls and more fibers. HRTEM images demonstrate that L-wood (Fig. 1f) is composed of disordered domains and some regions of short-range order (marked by white cycle). More long-range order structures are observed in M-wood (Fig. 1g) and H-wood (Fig. 1h) precursors, which are ascribed to the higher crystalline cellulose content. \n\n![](images/8f36e0f2603c0314463051f1ef3d7ec909ac5813b20dffbcce715148a1482cba.jpg) \nig. 1 | Physico-chemical characterization of different wood precursors before respectively and (f–h) the corresponding HRTEM images. HRTEM images of (i–k) L and after carbonization. a XRD patterns and (b) FTIR spectra of L-wood, M-wood 1500, M-1500 and H-1500 samples respectively. Scale bars: $10\\upmu\\mathrm{m}$ (c–e); 5 nm (f–h); nd H-wood samples. SEM images of $(\\bullet-\\bullet)$ L-wood, M-wood and H-wood samples 10 nm (i–k). \n\n![](images/f7fec68b6363d1d3f671e9c1be466a2ec73cc577a36e0d0f441404547a233def.jpg) \nFig. 2 | The physicochemical characterization of L-1500, M-1500 and H-1500. a XRD patterns, (b) FTIR spectra, (c) SAXS patterns, and (d) the relationship between the closed pore volume and the true density. \n\nAfter heat treatment, all wood precursors were well carbonized and decreased in size (Supplementary Fig. 2). SEM images show that these as-prepared hard carbon samples still retain natural pores and well-connected structure (Supplementary Fig. 3). To investigate the microstructure of hard carbon samples formed at $1500^{\\circ}\\mathrm{C}$ , HRTEM images are shown in Fig. 1i–k. Figure 1i demonstrates the highly disordered nature of L-1500 sample prepared from carbonized L-wood precursor, and it is difficult to identify obvious closed pore areas and long graphite-like layers. Nevertheless, some closed pores and long graphite-like layers can be clearly observed in M-1500 (Fig. 1j) and H-1500 (Fig. 1k). Remarkably, H-1500 sample possesses abundant graphite-like layers longer than $5\\mathsf{n m}$ and closed pores larger than $2\\mathsf{n m}$ , where they stack into turbostratic closed void domains (marked by the white cycles). The rich closed pores in H-1500 sample might be related to the high crystalline cellulose content of its wood precursor, which can be decomposed to the long graphite-like layers during the carbonization process to surround and shrink the sites. \n\nThe physicochemical properties of L-1500, M-1500 and H-1500 were further characterized. XRD patterns of H-1500 and M-1500 have two peaks at about $23^{\\circ}$ and $43^{\\circ}$ , corresponding to the (002) and (100) crystal planes of disordered graphite domains, respectively, which are typical characteristics of hard carbon (Fig. 2a)3. In contrast, L-1500 exhibits a sharp peak at $25.8^{\\circ}$ , demonstrating that the graphite-like layers are highly stacked and the corresponding interlayer spacing is close to that of the graphite. FTIR spectroscopy analysis was conducted to interpret the degree of cellulose decomposition in different wood-derived carbon. As shown in Fig. 2b, FTIR spectra verify the existence of - $\\mathrm{OH}(3338\\mathrm{cm}^{-1})$ , $-\\mathbf{CH}_{2}-$ $(1465\\mathsf{c m}^{-1})$ and $\\mathsf{C}{\\mathsf{-}}\\mathsf{O}{\\mathsf{-}}\\mathsf{C}$ (1125 and $1250\\mathsf{c m}^{-1})$ in all carbon samples22. Noting that, the absorption peak intensities of $-\\mathsf{O H}$ , $-\\mathbf{CH}_{2}-$ , $-\\mathbf{CH-}$ , and $\\scriptstyle{\\mathsf{C}}-{\\mathsf{O}}-{\\mathsf{C}}$ in H-1500 significantly decrease in comparison to those of H-wood, indicating that the H-wood precursor underwent more sufficient carbonization and had an underlying effect on the internal structure formation. X-ray photoelectron spectra (XPS) demonstrate that no other heteroatom is found except a small number of O atoms $(-5\\ \\mathsf{a t\\%})$ in hard carbon samples (Supplementary Fig. 4a and Supplementary Table 1). The peaks at 284.77, 285.38, 285.9 and 288.9 eV in the C 1s high-resolution spectra are ascribed to $s p^{2},s p^{3}$ , C-O and $\\scriptstyle0=\\mathbf{C}\\cdot0$ , respectively (Supplementary Fig. 4b)6,15,21. The Raman spectra of hard carbons generally exhibit broad peaks around $1345\\mathsf{c m}^{-1}$ (D-band) and $1586~\\mathrm{cm^{-1}}$ (Gband). The integrated intensity ratio of G-band and D-band, $\\mathrm{I_{G}/I_{D}}$ can reflect the defects concentration along with the graphene sheets1,5. As seen in Supplementary Fig. 5, the $\\mathrm{{I_{G}/I_{D}}}$ value of wood-derived carbon is gradually increased (1.15 to L-1500, 1.17 to M-1500, 1.295 to H-1500) indicating that H-1500 processes higher disordered degree due to the formation of more closed pores12. $\\mathsf{N}_{2}$ and $\\mathbf{CO}_{2}$ physisorption tests (Supplementary Fig. 6 and Supplementary Table 2) were performed to reveal the pore structure in hard carbon samples. Compared with L-1500 and M-1500, H-1500 possesses the smallest specific surface area (SSA) and the lowest content of micropores and mesopores. \n\nAs known, ${\\sf N}_{2}$ and $\\mathbf{CO}_{2}$ adsorption/desorption measurement only can probe the open surface porosity and is not sensitive to the internal closed porosity. To better describe the properties of closed pores in hard carbon samples, the small-angle $\\mathsf{x}$ -ray scattering (SAXS) test was conducted. SAXS patterns reveal broad humps at the scattering vector $Q$ of $1{-}2\\mathsf{n m}^{-1}.$ , which can be calculated by the following equation3,8,13,32,33: \n\n$$\nQ=\\frac{4\\pi\\mathrm{sin}\\theta}{\\lambda}\n$$ \n\nwhere $\\lambda{=}1.541\\mathring\\mathbf{A}$ is the X-ray wavelength and θ is half the scattering angle. The humps are attributed to closed pores in the carbon matrix, including micrometer-sized and nanometer-sized voids between $s p^{2}$ graphite layers8,32. According to SAXS patterns of hard carbon, H-1500 possesses an obvious peak around $1\\mathsf{n m}^{-1}.$ , indicating the radius increase of closed pores and high content of closed pores (Fig. $2\\mathbf{c})^{8}$ . The true density analysis is also an effective technique to characterize the closed pore. During the true density test, the volume of open pores and interparticle space can be well excluded. Therefore, the true density analysis can measure the total volume of closed pores and the solid portion. As a reference, the ideal graphite anode, regarded as a perfect crystal layered material without closed pores, possesses a high true density value of $2.26\\mathrm{gcm}^{-3}$ (Fig. $2\\mathsf{d})^{12}$ . Nevertheless, as the content of crystalline cellulose increases in wood precursors, the true density of the corresponding hard carbon decreases, which reveals the increased closed pore volume. For comparison, H-1500 carbonized from H-wood with the most crystalline cellulose owns the highest closed pore volume of $0.48\\mathsf{c m}^{3}\\mathsf{g}^{-1}$ . Obviously, the closed pore content in hard carbon is related to the crystalline cellulose content in its wood precursor8. \n\n# The role of amorphous composition on forming closed pore in hard carbon \n\nTo reveal the relationship between the amorphous components (lignin and hemicellulose) on the closed pore formation, acid and subsequent alkali hydrolysis treatment was employed to remove the amorphous composition in H-wood (see more experimental details in Experimental Section)34,35. The FTIR spectra of wood precursors pretreated with acid (Wood-AH-6h, Wood-AH-12h and Wood-AH-24h) or alkali (Wood-AT) show that the peak intensity of characteristic functional groups related to hemicellulose and lignin12 weakens with the extended processing time, revealing that hemicellulose and lignin could be effectively removed, while the crystalline cellulose was maintained (Supplementary Fig. 7). This conclusion can be further verified by the increased cellulose crystallinity along with the removal of hemicellulose and lignin (Fig. 3a). These pretreated wood precursors were carbonized at $1500^{\\circ}\\mathrm{C}$ for further investigation. The XRD patterns of as-prepared hard carbon samples only show two broad diffraction peaks ((002) and (100) crystal planes) similar to that of H-1500 without pretreatment, which is attributed to their typical disordered carbon structure (Fig. 3b). Compared with HC-AH-6h, HC-AH-12h and \n\n![](images/0a32debaafe18d37466d79cd4dfaacd13380213217a4c5bb5d92e5686fdbe279.jpg) \nFig. 3 | Physico-chemical characterization of the pretreated precursors and the derived hard carbon samples. XRD patterns of (a) wood precursors pretreated with acid or alkali and (b) the corresponding carbonized samples at $1500^{\\circ}\\mathrm{C}$ . c SAXS \npatterns of the carbonized samples at $1500^{\\circ}\\mathrm{C}$ . The material characterization of H-1700 and AT-1700. d XRD patterns, (e) Raman spectra and (f) SAXS patterns (f) of H-1700 and AT-1700; TEM images of $(\\mathbf{g},\\mathbf{h})$ AT-1700 and H-1700. Scale bars: ${\\bf10n m}\\left({\\bf g,h}\\right)$ . \n\nHC-AH-24h, the (002) peak of HC-AT shifts to a higher degree, which means narrower carbon interlayer distance and more obvious graphitization tendency. According to the SAXS patterns of hard carbon after treatment, the peaks around $1{-}2\\mathsf{n m}^{-1}$ decrease with the increased treatment time, meaning that the formed closed pores obviously decrease after removing the amorphous content (Fig. 3c). Obviously, the content of amorphous composition in wood precursor has an important influence on the pore structure and the graphitization degree of the derived hard carbon. \n\nAs is known to all, high pyrolysis temperature can provide a strong driving force to elevate the graphitization degree and closed pore content of hard carbon12. To better highlight the function of amorphous composition on tuning the microstructure of hard carbon, the pristine H-wood and the treated wood-AT were carbonized at $1700^{\\circ}\\mathrm{C}$ to prepare H-1700 and AT-1700, respectively. Even at a pyrolysis temperature up to $1700^{\\circ}\\mathrm{C}$ , the XRD pattern of H-1700 still maintains a typical feature of highly disordered carbon (Fig. 3d). In contrast, AT1700 exhibits a sharp peak at $26^{\\circ}$ , which is characteristic of highly graphitic carbon structure formed at high temperature, further confirming that amorphous region is a barrier for long-range graphitization of carbon layer. Raman spectra also prove the variation of graphitization degree, and the intensity ratio $\\mathrm{(I_{D}/I_{G})}$ of hard carbon samples decreases from 1.384 (H-1700) to 0.646 (AT-1700) after removing the amorphous composition (Fig. 3e). According to the SAXS patterns in Fig. 3f, the H-1700 with amorphous region retaining induces a more obvious peak at $\\mathbf{1}{\\cdot}2\\mathsf{n m}^{\\cdot1}$ , indicating the H-1700 possesses more closed pores. The visualized differences between H-1700 and AT1700 on microstructures are shown in HRTEM images (Fig. 3g, h). AT1700 exhibits a highly ordered and parallel graphitic-like layers structure in Fig. 3g, while some closed pores still can be observed in H-1700 in Fig. 3h, which should be induced by the folding of long-range and curved graphite layers. Hence, the amorphous regions not only effectively prevent the graphitization of wood-derived carbon, but also facilitate the formation of closed pore structures. \n\n# The influence of temperature on forming closed pore of hard carbon \n\nThe influence of carbonization temperature on the microstructure of hard carbon was also investigated. As displayed in Supplementary Fig. 8, all hard carbon samples prepared at different pyrolysis temperatures (H-1100, H-1300 and H-1500) show similar honeycomb-like structure with clear micro/nano channels and pores. As the pyrolysis temperature increases, the content of the residual oxygen atom is slightly reduced according to the XPS result (Supplementary Fig. 9 and Supplementary Table 3). In Fig. 4a, H-1100, H-1300 and H-1500 show similar XRD patterns, except that the (002) diffraction peak for H-1500 shifts to a larger angle owing to the decreased interlayer distance. As an almost universal cognizance, higher carbonization temperature means fewer defects and higher graphitization degree, resulting in a lower intensity ratio of $\\mathsf{I}_{\\mathrm{D}}/\\mathsf{I}_{\\mathrm{G}}$ . Nevertheless, the value of $\\mathrm{\\DeltaI_{D}/I_{G}}$ increases from 1.15 to 1.295 with the elevated pyrolysis temperature (Supplementary Fig. 10), which might be ascribed to abundant closed pores in H-1500 and they influence the degree of disorder value. Moreover, the SSA and the pore volume of H-wood derived hard carbon samples decrease with the increase in heat temperature (Fig. 4b, Supplementary Fig. 11, 12 and Supplementary Table 4). These results of SAXS patterns and true density tests in Fig. 4c, d show that on increasing carbonization temperature, the formation of closed pores between graphene basal planes keeps growing. This is because the high crystallinity cellulose is fused to form a graphite-like layer, which shrunk to form closed pores29. The closed pore structure for H-1500 is further confirmed by TEM. The TEM images show that the orientation of the graphite-like domains becomes clearer and short graphite-like layers grow into long-range layers with increasing pyrolysis temperature (Fig. 4e, f and Supplementary Fig. 13). The high pyrolysis temperature facilitates the shift and fold of the graphite-like layers, generating more closed pore surrounded by several parallel carbon layers for sodium storage. \n\n# The carbonization model of wood \n\nBased on the above-mentioned characterization results, it is clear that the formation of closed pore structure involves two key factors. The first one is enough length of graphene sheets in hard carbon. The second is that the produced graphene sheets can be effectively bent and disordered. The roles of wood components and calcination temperature in the formation of closed pores are first proposed. As illustrated in Fig. 5, the crystalline cellulose content is crucial to achieving closed pore structure during the pyrolysis process. The crystallinity cellulose can decompose and is carbonized to generate long graphene sheets as the walls of the closed pore, which will shrink to form closed pore structure. Meanwhile, the amorphous component is not only an active site to form closed pores but also a barrier to prevent woodderived carbon from graphitization tendency. The wood precursor with low crystallinity cellulose shows few closed pores and abundant open pores (micropores and mesopores) even at a high annealing temperature of $1500^{\\circ}\\mathsf{C}.$ Moreover, graphene sheets are easy to stack and result in the thick wall of close pore owing to the obstruction of these amorphous components. In contrast, more closed pores with thin wall appear after the wood precursor with high crystallinity cellulose is carbonized at the same temperature. The carbonization temperature also plays an important role in the formation of pore structure of wood-derived hard carbon. Some curved carbon layers also tend to fold and form “quasi-close pore” at the relatively low pyrolysis temperature. Although beneficial for the formation of new close pores, the high temperature also facilitates the migration, stacking and growth of graphitic layers, resulting in the shrunken closed pores. \n\n# Electrochemical performance and storage mechanism of hard carbon \n\nThe electrochemical performances of as-prepared hard carbon samples were first tested after assembling Na-ion half cells. The charge/ discharge curves of L-1500, M-1500 and H-1500 can be divided into slope region (above 0.1 V) and plateau region (below 0.1 V), demonstrating typical Na ion storage behavior of hard carbon (Fig. 6a). Interestingly, H-1500 delivers a much higher initial reversible capacity of $390\\mathrm{mAhg^{-1}}$ in comparison to L-1500 $(284\\mathrm{mAhg^{-1}})$ and M-1500 $(286\\mathrm{mAhg^{-1}})$ at $50\\mathrm{mAg^{-1}}$ . Figure 6b shows the plateau discharge capacities of three samples in the second cycle, and the corresponding value is 187, 212 and $293\\mathrm{mAhg^{-1}}$ , respectively. Such a high plateau capacity of H-1500 should be attributed to the abundant closed pores, which have been regarded as excellent $\\mathsf{N}\\mathsf{a}^{+}$ storage sites in many references3,8,13. The similar phenomenon that the discharge capacity or plateau capacity varies with their closed pore content is also observed in other hard carbon electrodes (Supplementary Fig. 14). Such results reveal the correlation between $\\mathsf{N}\\mathsf{a}^{+}$ storage capacity and closed pore structure. Also, H-1500 exhibits better rate capability with a high specific capacity of $280\\mathrm{mAhg^{-1}}$ at $1000\\mathsf{m}\\mathsf{A}\\mathsf{g}^{-1}$ , while M-1500 and L-1500 possess a capacity of 202 and $147\\mathsf{m A h g}^{-1}$ , respectively (Fig. 6c). Nevertheless, when the current density further increases to $2000\\mathsf{m A}\\mathsf{g}^{-1}$ , the discharge capacity of H-1500 electrode is slightly lower than that of M-1500 electrode. Note that the discharge capacity of $\\mathbf{H}\\mathbf{-}\\mathbf{1}500$ electrode at $20\\ \\mathrm{\\mA\\}\\mathrm{\\g}^{-1}$ is as high as $430\\mathsf{m A h g}^{-1}$ . It is speculated that the sluggish kinetics of closed pore as $\\mathsf{N}\\mathsf{a}^{+}$ storage site results in inferior rate performance. All three samples show excellent cycling stability (Fig. 6d). In particular, even at a current density of $500\\mathrm{mAg^{-1}}$ , H-1500 still maintains a capacity of $280\\mathrm{mAhg^{-1}}$ after 400 cycles (Fig. 6e). When further increased the mass loading from $1.8\\mathsf{m g}\\mathsf{c m}^{-2}$ to $3.7\\mathrm{mg}\\mathrm{cm}^{-2}$ , H-1500 electrode delivers an initial capacity of $273\\mathrm{mAhg^{-1}}$ with a capacity retention of $89.9\\%$ at $\\mathbf{1Ag^{-1}}$ for 250 cycles (Supplementary Fig. 15). Compared with previous reports $7,12,16,19,20,22,24,36$ on biomass-derived carbon materials in common ether or ester electrolytes, the as-prepared H-1500 here demonstrates much higher reversible capacity and rate performance (Fig. 6f). \n\n![](images/fddf722e47ad92467e23483fc97a39e18955fbff653e1ad4c81c6a1a0c3a7590.jpg) \nFig. 4 | Physico-chemical characterization of hard carbon samples at different carbonization temperatures. a XRD patterns, (b) $\\mathsf{N}_{2}$ adsorption-desorption isotherms, (c) SAXS patterns and (d) the relationship between the closed pore volume \nand true density of H-1100, H-1300 and H-1500. TEM images of (e) H-1100 and (f) H-1500. Scale bars: 10 nm (e, f). \n\nAccording to previously proposed adsorption/intercalation mechanism, the plateau capacity results from the accommodation of Na ions in curved graphene nanosheets of hard carbon, similar to Li ions insertion into graphite10,33. During this sodiation process, the interlayer spacing is inevitably expanded, which will lead to the obvious shift of diffraction peaks. As a reference, the process of $\\mathsf{N a}^{+}.$ ether insertion/extraction into/from graphite interlayer was firstly investigated via in-situ XRD technique. As seen, the diffraction peaks shift obviously (Fig. 7a). While for hard carbon electrode (H-1500), in addition to the characteristic peak of Be window at ${\\sim}29^{\\circ37}$ , the broad peak in a range of $24^{\\circ}$ and $26^{\\circ}$ , corresponding to the (002) graphitic plane of hard carbon remains the same, indicating that Na ions may not store in the interlayer spacing of hard carbon (Fig. 7b)38. Based on the adsorption-insertion-filling mechanism, it is probable that the quasimetallic forms in closed pores at the plateau region8. To verify the presence of quasi-metallic sodium, Fig. 7c displays the optical photograph of hard carbon electrodes discharged to 0.01 V (vs. $\\bf N a^{+}/\\bf N a)$ , which were soaked in the ethanol solution containing $1\\%$ phenolphthalein for $5\\mathsf{m i n}^{39}$ . It can be observed that the color of the ethanol-phenolphthalein solution deepens gradually with the increased plateau capacity of different derived-wood carbon, wherein H-1500 has more closed pores to store Na ions and the corresponding ethanol solution shows deeper red in contrast with L-1500 and M-1500. Meanwhile, SAXS tests of the pristine and discharged hard carbon electrodes were also employed4,33. As shown in Fig. 7d, when the electrode was discharged to $_{0.01\\mathrm{~V~}}$ , the SAXS intensity around $\\mathsf{Q}=\\mathsf{1n m}^{-1}$ decreases significantly, which implies the decrease of closed pores because of the Na ions filling. \n\nTo verify the practical application potential of H-1500 electrode, the full-cell composed of the homemade $\\mathrm{Na}_{3}\\mathrm{Fe}_{2}(\\mathrm{PO}_{4})\\mathrm{P}_{2}\\mathrm{O}_{7}@\\mathrm{C}$ (NFPP) \n\n![](images/2182d4164fc783ccdea47bc8ea96b17b6101de44610d216f040a45d928fb67f9.jpg) \nFig. 5 | A formation mechanism of closed pores based on the observation in this work. Both the composition of wood precursor (crystallinity cellulose and amorphous hemicellulose/lignin) and the carbonization temperature play important \n\ncathode and H-1500 anode was constructed. Supplementary Fig. 16a is the charge/discharge curves of NFPP cathode at $100\\mathrm{mAg^{-1}}$ , and two plateaus at $-2.9\\ensuremath{\\upnu}$ and ${\\sim}3.2\\mathrm{v}$ can be observed, which are consistent with the previous literature40. NFPP delivers a discharge capacity of $86.6\\mathsf{m A h g^{-1}}$ after 90 cycles at $100\\mathrm{\\mAg^{-1}}$ , corresponding to the capacity retention of ${\\bf-99\\%}$ (Supplementary Fig. 16b). The average Coulombic efficiency of NFPP is $99.5\\%,$ further demonstrating the stable cycling performance of this cathode material. NFPP also exhibits good rate performance with capacities of 87, 86, 84, 79 and 71 mAh $\\mathbf{g}^{-1}$ at 0.2, 0.5, 1, 2 and $3\\mathsf{A}\\mathsf{g}^{-1}.$ , respectively (Supplementary Fig. 16c, d). Supplementary Fig. 17a presents the charge/discharge curves of H1500//NFPP full-cell at different current densities. H-1500//NFPP fullcell shows the initial reversible capacities of 346, 319 and $299\\mathrm{{mAhg^{-1}}}$ (based on the mass of active anode material) at 0.1, 0.5 and $\\mathbf{1Ag^{-1}}$ , respectively. H-1500//NFPP full-cell remains a discharge capacity of $254\\mathsf{m A h g^{-1}}$ (based on the mass of active anode material) with a capacity retention of $79.6\\%$ after 100 cycles at $0.5\\mathsf{A g}^{-1}$ (Supplementary Fig. 17b). Even at 1 A $\\mathbf{g}^{-1}$ , H-1500//NFPP full-cell still delivers a reversible capacity of $250\\mathrm{mAhg^{-1}}$ (based on the mass of active anode material) with the capacity retention of $83.6\\%$ , demonstrating good cycling stability (Supplementary Fig. 17c, d). \n\n# Discussion \n\nIn summary, the formation mechanism of closed pore, which is the main sodium storage structure in hard carbon, was established based on the wood-derived hard carbons. It was found that high crystalline cellulose content in nature wood could transform into long graphitelike layers to surround and shrink active sites to form closed pore structures. The existence of amorphous components (hemicellulose and lignin) not only helped to form nano-sized pores but also prevented the over-graphitization of carbon layer during the hightemperature carbonization. With the increase in carbonization temperature, the length of graphite-like carbon layer increased, which was beneficial to the formation of closed pore structure. Based on this carbonization model, the optimum H-1500 electrode exhibited a high reversible discharge capacity of $430\\mathrm{mAhg^{-1}}$ at $20\\mathrm{mAg^{-1}}$ , good rate capability $(175\\mathsf{m A h g^{-1}}$ at $2000\\mathsf{m A g^{-1}}$ , and stable cycling roles in affecting the microstructure (such as number, size and wall thickness) of closed pores. \n\nperformance $(280\\mathrm{mAh}\\mathrm{g}^{-1}$ after 400 cycles at $500\\mathrm{mAg^{-1}})$ . The assembled H-1500//NFPP full-cell remained a discharge capacity of $250\\mathrm{mAhg^{-1}}$ (based on the mass of active anode material) with a capacity retention of $83.6\\%$ after 100 cycles at $\\mathbf{1Ag^{-1}}$ , demonstrating good cycling stability. With the aid of in-situ XRD and SAXS, it was demonstrated that the plateau area mainly corresponded to the metallic Na cluster filling the closed pore. Therefore, H-1500 with abundant closed pores possessed more Na storage sites, contributing to its superior capacity. This work not only clarifies the closed pore formation mechanism for waste wood-derived carbon, but also offers a strategy to design high plateau-region hard carbon anodes for highperformance and low-cost SIBs in the future. \n\n# Methods \n\n# Synthesis of hard carbon samples \n\nAll precursors of hard carbon samples in this work were waste woods purchased on Taobao. These woods were divided into three categories according to their density and noted as L-wood (cork, $0.13\\mathrm{g}\\mathrm{cm}^{-3},$ , M-wood (yellow sandal, $0.392\\mathrm{gcm}^{-3},$ and H-wood (rosewood, $0.891\\mathrm{g}\\mathrm{cm}^{-3})$ , respectively. The waste wood blocks were firstly cut into small pieces and then the precursors were directly carbonized for $2\\mathfrak{h}$ in a tube furnace under argon flow at $1100^{\\circ}\\mathsf C$ , $1300^{\\circ}\\mathrm{C}$ and $1500^{\\circ}\\mathrm{C}$ , respectively. The heating rate was $2^{\\circ}\\mathrm{C}\\mathsf{m i n}^{-1}$ . Typically, these hard carbon samples derived from L-wood, which were prepared at different temperatures, were noted as L-1100, L-1300 and L-1500. The other samples were noted similarly. To investigate the influence of the disorder area on the formation of the closed pores, H-wood was pretreated via chemical methods in the following: firstly, H-wood blocks were crushed into powder. To remove the lignin in the precursor, a certain amount of H-wood powder was immersed into a yellow-green solution, in which $\\mathbf{1}\\mathbf{gNaClO}_{2}$ (Macklin, $80\\%$ ) and $2\\mathrm{mL}$ $\\mathrm{CH}_{3}\\mathrm{COOH}$ (Macklin, AR) were dissolved in $150\\mathrm{mL}$ deionized water35. The obtained mixture was stirred vigorously at $80^{\\circ}\\mathrm{C}$ for different times (6, 12, $24\\mathsf{h}$ , and then was separated via suction filtration. The treated powder was further washed with deionized water until the filtrate was almost neutral and dried at $80^{\\circ}\\mathrm{C}$ overnight. To further remove the hemicellulose, the above acid-treated powder (24 h) was added in \n\n![](images/b305dafb5e4d1e8dd6d1f0aa774409ba53b0f8ec434ecd62f69e2485719a00ec.jpg) \nFig. 6 | Battery performance. The (a) charge/discharge profiles at $50\\mathrm{mAg^{-1}}$ , (b) $2^{\\mathrm{nd}}$ cycling performance of hard carbon samples prepared at different temperatures. scharge capacity contributed from slope and plateau region, (c) rate and (d) Comparison of rate performance with the typical biomass-derived hard carbon cling performance of hard carbon samples prepared at $1500^{\\circ}\\mathsf C$ . e The long-term reported previously for sodium storage. \n\n$200\\mathrm{mL}$ NaOH (HUSHi, AR) aqueous solution with a gradient concentration of $6w t\\%$ , $8w t\\%$ , and $10\\mathrm{{wt\\%}}$ , and kept at $80^{\\circ}\\mathrm{C}$ for $12\\mathsf{h}^{34}$ . Finally, the alkali-treated powder was washed with deionized water until the pH of the filtrate was ${\\sim}7$ and dried at $80^{\\circ}\\mathrm{C}$ overnight. \n\n# Material characterization \n\nPowder X-ray diffraction (XRD) was performed using a Rigaku diffractometer equipped with a Cu Kα radiation source $(1.542\\mathring{\\mathbf{A}})$ . Raman spectra were tested by the LabRAM HR800. Small-angle X-ray scattering (SAXS) data were collected with the X-ray diffractometer in a transmission and parallel-beam geometry with a Ni-filtered Cu Kα radiation and a scintillation point detector (Anton Paar SAXSess MC2). SAXS patterns of fully sodiated hard carbon samples were collected from the fabricated pouch cells with a metallic sodium reference and counter electrode, which were eventually discharged to 0.01 V (vs. $\\mathsf{N a^{+}}/$ Na) after 3 cycles at a specific current of $50\\mathrm{{mAg}^{-1}}$ . X-ray photoelectron spectroscopy (XPS, ESCALAB250Xi) was conducted to detect the surface valence state of samples. To avoid interference from the gas adsorbed in hard carbon, these powder samples were dried at $100^{\\circ}\\mathrm{C}$ in a vacuum oven for 6h before the XPS test. $\\mathbf{\\nabla}\\tilde{\\mathbf{\\Gamma}}^{-2}\\mathbf{m}\\mathbf{g}$ hard carbon powder was distributed on the double side tape and fixed on the sample stage. Then the sample stage was transferred to the analysis room, which was vacuumed until the value reached to $10^{-9}\\mathsf{P a}$ . A focused monochromatic Al Kα X-ray was used as an excitation source and high energy-resolution spectra collection were conducted with a spherical section analyzer. The hard carbon sample discharged to 0.01 V was collected from the cycled pouch cell, which was scraped from the Cu current collector and washed with dimethyl ether (DME) for drying in a vacuum before SAXS measurements. $\\mathsf{N}_{2}$ and $\\mathbf{CO}_{2}$ adsorption-desorption tests were conducted with BELSORP-mini II (MicrotracBEL Corp.) at 77K and 273K, respectively. Prior to the adsorption-desorption measurement, the samples were heat-treated at $300^{\\circ}\\mathrm{C}$ for $5\\mathsf{h}$ under vacuum to remove moisture trapped in the surface pores. The true densities of hard carbon samples were measured via helium gas pycnometry with the BELPycno density analyser (MicrotracBEL Corp.) and via n-butanol displacement pycnometry with a specific gravity bottle (Shibata Scientific Technology Ltd.) based on Japanese Industrial Standard (JIS) R7212:1995 as reported in the references12. Field-emission scanning electron microscopy (FE-SEM, Nova Nano SEM 230) and transmission electron microscopy (TEM, Titan G2 60-300) were utilized to characterize the morphological structures of samples. \n\n![](images/12309e4cf394309c856634499cd627ed1d6773cc4a8a558449f8b8baa65082b3.jpg) \nFig. 7 | Analysis of sodium storage mechanism. In-situ XRD patterns of the graphite electrode (a) and the H-1500 electrode (b) during the first discharge-charge process at $100\\mathrm{\\mAg^{-1}}$ . c The optical photograph of hard carbon electrodes \ndischarged to $_{0.01\\mathrm{v}}$ (vs. ${\\bf N a}^{+}/{\\bf N a}^{-}$ soaked in the ethanol solution containing $1\\%$ phenolphthalein for $5\\mathrm{{min}}$ (d) SAXS patterns of pristine and 0.01 V discharged H-1500 electrodes. \n\n# Electrochemical tests \n\nCR2016 coin cells were assembled in an argon-filled glove box (Mikarouna) before testing the electrochemical performance of samples. Hard carbon anode was prepared by mixing $80\\mathrm{{wt\\%}}$ hard carbon powder sample, $10\\mathrm{{wt\\%}}$ acetylene black (Shenzhen Kejing) and $10\\mathrm{{wt\\%}}$ polyvinylidene fluoride (PVDF, Shenzhen Kejing, HSV-900). The uniform slurry was prepared by adding the proper amount of N-methylpyrrolidone (Aladdin, AR) as solvent. And the slurry was cast on the copper foil and cut into $12\\mathsf{m m}$ disks with a mass loading of around $1.8\\mathsf{m g}\\mathsf{c m}^{-2}$ after the drying treatment at $100^{\\circ}\\mathsf{C}$ for $12\\mathsf{h}$ in a vacuum oven. The homemade Na circular pieces with a diameter of $12\\mathsf{m m}$ that punched from the pressed Na foil, were used as the counter electrode and reference electrode. The glass fiber (Whatman) was used as the separator and the electrolyte was a solution of $1\\mathsf{M N a P F}_{6}$ in dimethyl ether (Dodo Chem) in all cells. The hard carbon electrode in the pouch cell was prepared with a similar process to the electrode used in the coin cell except that the dried electrode was cut into a rectangle (width: $45\\mathsf{m m}$ , height: $55\\mathsf{m m}\\bar{}$ ). The mass loading of hard carbon electrode in the pouch cell was $\\mathbf{\\nabla}\\tilde{}80\\mathrm{mg}$ . The homemade Na foils with a similar size to hard carbon anode were used and pressed on the Cu foil as the counter electrode and reference electrode. Ni tap needed to be welded on the Cu current collector. Eventually, hard carbon anode, glass fiber and Na foil were stacked in sequence and then encapsulated in aluminum-plastic film after adding a certain amount of electrolyte. For H-1500 electrode in the full-cell, the mass ratio of H-1500 powder, acetylene black and PVDF was 7:2:1, and the mass loading was $-1.5\\mathsf{m g c m}^{-2}$ . For NFPP electrode in the full-cell, the mass ratio of NFPP powder, acetylene black and PVDF was 8:1:1, and the mass loading of cathode disks with a diameter of $12\\mathsf{m m}$ was $7{-}8\\mathrm{mgcm}^{-2}$ . \n\nAccording to the capacity of cathode and anode, the mass ratio between cathode and anode was ${\\sim}4.58$ . Before assembling $\\mathsf{H}{-}1500//$ NFPP full-cell, H-1500 electrode was precycled for 2 cycles at a specific current of $100\\mathrm{mAg^{-1}}$ within the voltage range of $_{0.01-2\\mathrm{V}}$ in the half-cell. Both NFPP half-cell and H-1500//NFPP full-cell were cycled within the voltage range of 3.8-2 V. Galvanostatic charge/discharge tests were all conducted with Neware battery system in a thermotank at $30^{\\circ}\\mathsf{C}$ . \n\n# In-situ XRD measurement \n\nThe hard carbon/graphite (HUSHi, AR) electrode in the pouch cell was prepared with a similar process to the electrode used in the coin cell except that the prepared slurry was directly cast on the Be current collector with excellent X-ray penetration. This special electrode was dried in a vacuum oven at $100^{\\circ}\\mathsf{C}$ for $12\\mathsf{h}$ . The in-situ cell was fabricated in the glove box (Mikarouna). The homemade Na foils were used as the counter electrode and reference electrode. The glass fiber (Whatman) was used as the separator and the electrolyte was a solution of $1\\mathsf{M N a P F}_{6}$ in dimethyl ether (Dodo Chem). The in-situ cell was cycled at a specific current of $100\\mathrm{\\mAg^{-1}}$ between 0.01 and $2\\mathsf{V}$ . \n\n# Data availability \n\nThe data that support the findings of this study are available within the article and its Supplementary Information files. All other relevant data supporting the findings of this study are available from the corresponding authors upon reasonable request. \n\n# References \n\n1. Qi, Y. et al. Slope-dominated carbon anode with high specific capacity and superior rate capability for high safety Na-ion. Batteries. Angew. Chem. Int. Ed. 58, 4361–4365 (2019). \n2. Nobuhara, K., Nakayama, H., Nose, M., Nakanishi, S. & Iba, H. Firstprinciples study of alkali metal-graphite intercalation compounds. J. Power Sources 243, 585–587 (2013). capacity hard carbon for Na‐ion battery. Angew. Chem. Int. Ed. 5, 114–5120 (2021). \n4. Alvin, S. et al. Revealing sodium ion storage mechanism in hard carbon. Carbon 145, 67–81 (2019). \n5. Hou, B. H. et al. Self-supporting, flexible, additive-free, and scalable hard carbon paper self-interwoven by 1D microbelts: superb room/ low-temperature sodium storage and working mechanism. Adv. Mater. 31, 1903125 (2019). \n6. Li, Z. et al. Defective hard carbon anode for Na-ion batteries. Chem. Mater. 30, 4536–4542 (2018). \n7. Li, Y., Hu, Y.-S., Titirici, M.-M., Chen, L. & Huang, X. Hard carbon microtubes made from renewable cotton as high-performance anode material for sodium-ion batteries. Adv. Energy Mater. 6, 1600659 (2016). \n8. Au, H. et al. A revised mechanistic model for sodium insertion in hard carbons. Energy Environ. Sci. 13, 3469–3479 (2020). \n9. Gotoh, K. et al. NMR study for electrochemically inserted Na in hard carbon electrode of sodium ion battery. J. Power Sources 225, 137–140 (2013). \n10. Stratford, J. M., Allan, P. K., Pecher, O., Chater, P. A. & Grey, C. P. Mechanistic insights into sodium storage in hard carbon anodes using local structure probes. Chem. Commun. 52, 12430–12433 (2016). \n11. Morita, R. et al. Combination of solid state NMR and DFT calculation to elucidate the state of sodium in hard carbon electrodes. J. Mater. Chem. A 4, 13183–13193 (2016). \n12. Li, Y. et al. Regulating pore structure of hierarchical porous waste cork‐derived hard carbon anode for enhanced Na storage performance. Adv. Energy Mater. 9, 1902852 (2019). \n13. Meng, Q. et al. Tuning the closed pore structure of hard carbons with the highest Na storage capacity. ACS Energy Lett. 4, 2608–2612 (2019). \n14. Zhu, Y., Chen, M., Li, Q., Yuan, C. & Wang, C. A porous biomassderived anode for high-performance sodium-ion batteries. Carbon 129, 695–701 (2018). \n15. Wang, Q. et al. Rice husk-derived hard carbons as highperformance anode materials for sodium-ion batteries. Carbon 127, 658–666 (2018). \n16. Wu, F. et al. Lotus Seedpod-derived hard carbon with hierarchical porous structure as stable anode for sodium-ion batteries. ACS Appl. Mater. Interfaces 11, 12554–12561 (2019). \n17. Zhang, N. et al. High capacity hard carbon derived from lotus stem as anode for sodium ion batteries. J. Power Sources 378, 331–337 (2018). \n18. Lotfabad, E. M. et al. High-density sodium and lithium ion battery anodes from banana peels. ACS Nano 8, 7115–7129 (2014). \n19. Gaddam, R. R. et al. Biomass derived carbon nanoparticle as anodes for high performance sodium and lithium ion batteries. Nano Energy 26, 346–352 (2016). \n20. Damodar, D., Ghosh, S., Usha Rani, M., Martha, S. K. & Deshpande, A. S. Hard carbon derived from sepals of Palmyra palm fruit calyx as an anode for sodium-ion batteries. J. Power Sources 438, 227008 (2019). \n21. Zhang, S. et al. Sustainable production of value-added carbon nanomaterials from biomass pyrolysis. Nat. Sustain. 3, 753–760 (2020). \n22. Berglund, L. A. & Burgert, I. Bioinspired wood nanotechnology for functional materials. Adv. Mater. 30, 1704285 (2018). \n23. Jing, W. et al. Pore structure engineering of wood-derived hard carbon enables their high-capacity and cycle-stable sodium storage properties. Electrochim. Acta 391, 139000 (2021). \n24. Zhou, S. et al. Regulating closed pore structure enables significantly improved sodium storage for hard carbon pyrolyzing at relatively low temperature. SusMat 2, 357–367 (2022). \n25. Lee, H. V., Hamid, S. B. & Zain, S. K. Conversion of lignocellulosic biomass to nanocellulose: structure and chemical process. Sci. World J. 2014, 631013 (2014). \n26. Wang, S., Dai, G., Yang, H. & Luo, Z. Lignocellulosic biomass pyrolysis mechanism: a state-of-the-art review. Prog. Energy Combust. Sci. 62, 33–86 (2017). \n27. Hu, B. et al. Recent progress in quantum chemistry modeling on the pyrolysis mechanisms of lignocellulosic biomass. Energy Fuels 34, 10384–10440 (2020). \n28. Zhang, X., Xu, M., Sun, R. & Sun, L. Study on biomass pyrolysis kinetics. J. Eng. Gas. Turbine Power 128, 493–496 (2006). \n29. Kim, Y. E. et al. Structure-dependent sodium ion storage mechanism of cellulose nanocrystal-based carbon anodes for highly efficient and stable batteries. J. Power Sources 468, 228371 (2020). \n30. Nam, S., French, A. D., Condon, B. D. & Concha, M. Segal crystallinity index revisited by the simulation of X-ray diffraction patterns of cotton cellulose Ibeta and cellulose II. Carbohydr. Polym. 135, 1–9 (2016). \n31. Chen, C. J., Luo, J. J., Huang, X. P. & Zhao, S. K. Analysis on cellulose crystalline and FTIR spectra of artocarpus heterophyllus lam wood and its main chemical compositions. Adv. Mater. Res. 236-238, 369–375 (2011). \n32. Yang, J. et al. From micropores to ultra-micropores inside hard carbon: toward enhanced capacity in room-/low-temperature sodium-ion storage. Nano-Micro Lett. 13, 98 (2021). \n33. Morikawa, Y., Nishimura, S. I., Hashimoto, R. I., Ohnuma, M. & Yamada, A. Mechanism of sodium storage in hard carbon: an X‐ray scattering analysis. Adv. Energy Mater. 10, 1903176 (2019). \n34. Schwanninger, M., Rodrigues, J. C., Pereira, H. & Hinterstoisser, B. Effects of short-time vibratory ball milling on the shape of FT-IR spectra of wood and cellulose. Vib. Spectrosc. 36, 23–40 (2004). \n35. Akerholm, M. & Salmen, L. The oriented structure of lignin and its viscoelastic properties studied by static and dynamic FT-IR spectroscopy. Holzforschung 57, 459–465 (2003). \n36. Kim, H. et al. Sodium storage behavior in natural graphite using etherbased electrolyte systems. Adv. Funct. Mater. 25, 534–541 (2015). \n37. Li, Y. et al. Advanced sodium-ion batteries using superior low cost pyrolyzed anthracite anode: towards practical applications. Energy Stor. Mater. 5, 191–197 (2016). \n38. Zhang, B., Ghimbeu, C. M., Laberty, C., Vix-Guterl, C. & Tarascon, J.- M. Correlation between microstructure and Na storage behavior in hard carbon. Adv. Energy Mater. 6, 1501588 (2016). \n39. Wang, Z. et al. Probing the energy storage mechanism of auasimetallic Na in hard carbon for sodium-ion batteries. Adv. Energy Mater. 11, 2003854 (2021). \n40. Wang, H. et al. A green and scalable synthesis of $\\mathsf{N a}_{3}\\mathsf{F e}_{2}(\\mathsf{P O}_{4})\\mathsf{P}_{2}\\mathsf{O}_{7}/$ rGO cathode for high-rate and long-life sodium-ion batteries. Small Methods 5, e2100372 (2021). \n\n# Acknowledgements \n\nThis study was financially supported by the National Nature Science Foundation of China (22272205, 21975289 and U19A2019), Hunan Provincial Nature Science Foundation of China (2022JJ30685), Hunan Provincial Science and Technology Plan Project of China (2017TP1001 and 2022RC3050). D.S. acknowledges support from Young Elite Scientists Sponsorship Program by CAST (No. YESS20220432). Z.T. and R.Z. acknowledge support from the Fundamental Research Funds for the Central South University (2020zzts060 and 2021zzts0104). M.S. acknowledges support from Innovation and Technology Fund of the Hong Kong Special Administrative Region (ITS/001/20FP). Research at the Argonne National Laboratory was funded by the US Department of Energy (DOE), Vehicle Technologies Office under contract No. DE-AC02- 06CH11357. Support from Tien Duong of the US DOE’s Office of Vehicle Technologies Program is gratefully acknowledged. K.A. also thanks the support from Clean Vehicles, US-China Clean Energy Research Center (CERC-CVC2). \n\n# Author contributions \n\nH.Y.W., D.S. and Y.G.T. managed the project and guided the research. Z.T. and R.Z. contributed equally to the paper, and synthesized the samples and carried out the characterizations. S.Y.Z., Y.C.H., and Z.Y.P. participated in the experiments. K.A., X.B.J. and M.H.S. were involved in the discussions and manuscript revision. Z.T. and R.Z. wrote the manuscript with the supervision of H.Y.W. and D.S. All authors have read and approved the final paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\nAdditional information \nSupplementary information The online version contains supplementary material available at \nhttps://doi.org/10.1038/s41467-023-39637-5. \n\nCorrespondence and requests for materials should be addressed to Haiyan Wang, Dan Sun, Khalil Amine or Minhua Shao. \n\nPeer review information Nature Communications thanks Annica Isabel Freytag and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 " + }, + { + "id": "10.1038_s41467-023-37091-x", + "DOI": "10.1038/s41467-023-37091-x", + "DOI Link": "http://dx.doi.org/10.1038/s41467-023-37091-x", + "Relative Dir Path": "mds/10.1038_s41467-023-37091-x", + "Article Title": "Regulating electronic states of nitride/hydroxide to accelerate kinetics for oxygen evolution at large current density", + "Authors": "Zhai, PL; Wang, C; Zhao, YY; Zhang, YX; Gao, JF; Sun, LC; Hou, JA", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "Rational design efficient transition metal-based electrocatalysts for oxygen evolution reaction (OER) is critical for water splitting. However, industrial water-alkali electrolysis requires large current densities at low overpotentials, always limited by intrinsic activity. Herein, we report hierarchical bimetal nitride/hydroxide (NiMoN/NiFe LDH) array as model catalyst, regulating the electronic states and tracking the relationship of structure-activity. As-activated NiMoN/NiFe LDH exhibits the industrially required current density of 1000 mA cm(-2) at overpotential of 266 mV with 250 h stability for OER. Especially, in-situ electrochemical spectroscopic reveals that heterointerface facilitates dynamic structure evolution to optimize electronic structure. Operando electrochemical impedance spectroscopy implies accelerated OER kinetics and intermediate evolution due to fast charge transport. The OER mechanism is revealed by the combination of theoretical and experimental studies, indicating as-activated NiMoN/NiFe LDH follows lattice oxygen oxidation mechanism with accelerated kinetics. This work paves an avenue to develop efficient catalysts for industrial water electrolysis via tuning electronic states. Rational design of efficient electrocatalysts for oxygen evolution reaction is critical for water-alkali electrolysis. Here, the authors fabricate a NiMoN/NiFe layered double hydroxide and show the accelerated oxygen evolution kinetics are due to the heterointerface.", + "Times Cited, WoS Core": 266, + "Times Cited, All Databases": 270, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000983843800002", + "Markdown": "# Regulating electronic states of nitride/ hydroxide to accelerate kinetics for oxygen evolution at large current density \n\nReceived: 26 September 2022 \n\nAccepted: 2 March 2023 \n\nPublished online: 04 April 2023 \n\nCheck for updates \n\nPanlong Zhai1,5, Chen Wang1,5, Yuanyuan Zhao2,5, Yanxue Zhang2, Junfeng Gao 2 , Licheng Sun3,4 & Jungang Hou 1 \n\nRational design efficient transition metal-based electrocatalysts for oxygen evolution reaction (OER) is critical for water splitting. However, industrial water-alkali electrolysis requires large current densities at low overpotentials, always limited by intrinsic activity. Herein, we report hierarchical bimetal nitride/hydroxide (NiMoN/NiFe LDH) array as model catalyst, regulating the electronic states and tracking the relationship of structure-activity. Asactivated NiMoN/NiFe LDH exhibits the industrially required current density of $1000\\mathsf{m A c m}^{-2}$ at overpotential of $266\\boldsymbol{\\mathrm{mV}}$ with $250\\mathsf{h}$ stability for OER. Especially, in-situ electrochemical spectroscopic reveals that heterointerface facilitates dynamic structure evolution to optimize electronic structure. Operando electrochemical impedance spectroscopy implies accelerated OER kinetics and intermediate evolution due to fast charge transport. The OER mechanism is revealed by the combination of theoretical and experimental studies, indicating as-activated NiMoN/NiFe LDH follows lattice oxygen oxidation mechanism with accelerated kinetics. This work paves an avenue to develop efficient catalysts for industrial water electrolysis via tuning electronic states. \n\nWith the intensification of the energy crisis and climate concerns, the development of renewable and clean resources has far-reaching significance for fossil fuel consumption and sustainable economic development. As a clean and reliable energy technology, hydrogen is regarded as an appropriate alternative to fossil fuel, while water electrolysis using intermittent electric energy represents a promising commercial technology for industrial hydrogen production1,2. Water splitting reaction consists of hydrogen evolution reaction (HER) at the cathode and oxygen evolution reaction (OER) at the anode. Compared with the HER, the OER has sluggish kinetics and a large reaction barrier, limiting the efficiency of electrocatalytic water splitting3. To address these points, the development of highly active oxygen evolution electrocatalysts has become a research hotspot. Pt and Ir/Ru oxidebased electrocatalysts are benchmark catalysts for water splitting; however, scarcity of reserves, high cost and inferior stability limit their large-scale application. To overcome these challenges, the exploration of transition metal-based electrocatalysts serviced in alkaline media, which simultaneously meets the requirements of intrinsic activity and stability, has attracted wide attention4. \n\nTo date, numerous strategies, such as composition tuning5,6, heteroatom doping7,8 and defect engineering9,10, have been reported for enhancing OER activity. Among various tactics, heterointerface engineering11–16 is one of the most considerable ways to overcome the limitation of catalytic activity and improve the intrinsic activity of electrocatalysts. The construction of heterostructure is conducive to the formation of the active phase and optimization of electronic structure, owing to the multi-component synergistic effect, in which creates catalytic sites and modulates intermediate adsorption11,17,18. For instance, Luo et al.19 designed a $\\mathsf{C o o o H/C o S_{\\alpha}}$ hybrid catalysts, regulating the formation of high-valent metal species and enhancing the adsorption capacity of the intermediate. Du et al.20 synthesized NiO/ NiFe LDH with excellent OER performance. In situ spectroscopies and theoretical calculations revealed the dynamic tridimensional adsorption of the intermediate at the heterointerface, which bypasses the scaling relationship and facilitates the reaction kinetics. Even though numerous efforts have been made, the structure-property relationships between heterostructure and catalytic performance need to be further analyzed, especially, the electronic configuration and reaction kinetics. \n\nAlthough various advances have been obtained in performance and mechanistic understanding for OER, the progress in industrial application is still unsatisfactory21–26. The bottleneck hindering the progress of industrial water-alkali electrolysis is the rational design of catalysts towards practically-relevant current density $\\scriptstyle(>1000\\ m\\mathbf{A}\\ c m^{-2})$ ). It is desirable to synthesize transition metal-based and robust electrocatalysts, especially at large current densities. For instance, threedimensional (3D) core-shell NiMoN@NiFeN catalysts present the current densities of 500 and $1000\\mathsf{m A c m}^{-2}$ at the low voltages of 1.608 and 1.709 V for overall alkaline seawater splitting at $60^{\\circ}\\mathsf C^{21}$ . The EP $\\mathsf{N i}\\|$ EP NiFe LDH/Ni–cotton cell (electroplate noted as EP) show the cell voltages of 1.39, 1.63, and 1.81 V at the current densities of 10, 100, and $1000\\mathsf{m A c m}^{-2}$ in 1 M KOH electrolyte24. Based on the previous literatures for industrial water electrolysis, the obvious conditions such as sufficient active sites, rapid diffusion of bubbles and good mechanically or chemically stability should be noticed27,28. In brief, we need rationally designed electrocatalysts to lay a solid foundation for industrial water electrolysis. Generally, OER process follows adsorbate evolution mechanism (AEM) where a series of sequential concerted proton-electron transfer (CPET) step occurs on metal sites via multiple oxygen intermediates. However, the thermodynamics constraint of the scaling relationship between the Gibbs free energy of $^{*}00\\mathsf{H}$ and $^{*}\\mathrm{OH}$ cause the minimum theoretical overpotential of $0.37\\mathrm{V}$ for the optimal catalysts29. More recently, the OER mechanism based on oxygen redox chemical was mentioned as lattice oxygen oxidation mechanism $(\\mathsf{L O M})^{22,23,25}$ . LOM can bypass the O-O bond formation which was regarded as rate-determining step in AEM and broke up the scaling relationship limitation. Enlightened by the above analysis, the OER mechanism is highly desirable to be implemented, shedding light on the correlation between the mechanism and electrocatalytic performance. \n\nHerein, we report the hierarchical core-shell bimetal nitride/ hydroxide (NiMoN/NiFe LDH) heterostructure array with twodimensional NiFe LDH nanosheets attached to one-dimensional NiMoN nanorods, regulating the electronic states on catalytically active sites and tracking the relationship of structure-activity. Asactivated NiMoN/NiFe LDH delivers industrial current density of $1000\\mathsf{m A c m}^{-2}$ at an overpotential of $266\\mathsf{m V}$ and durability of $250\\mathsf{h}$ for OER. Especially, the NiMoN/NiFe LDH forms optimized electronic structure through dynamic structure evolution, recording by in-situ Raman spectroscopy and ultraviolet-visible spectroscopy. The OER kinetics and intermediate evolution of NiMoN/NiFe LDH is exhibited by operando electrochemical impedance spectroscopy (EIS). Moreover, density functional theory (DFT) calculation and differential electrochemical mass spectrometry (DEMS) prove that as-activated NiMoN/NiFe LDH prefers LOM pathway for OER, breaking the scaling relationship limitation and accelerating reaction kinetics. This work paves an avenue to develop efficient heterojunction electrocatalysts for industrial water-splitting electrolysis. \n\n# Results \n\n# Synthesis and structural characterization \n\nThe synthetic procedure of 3D core-shell NiMoN/NiFe LDH electrocatalyst was illustrated in Fig. 1a, where NiMoN nanorods as the core derived from the $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ and amorphous NiFe LDH is used as shell. Briefly, $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ nanorods array was perpendicularly grown on the nickel foam (NF) via a facile hydrothermal process30. Subsequently, $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ nanorods array was calcined in ammonia atmosphere at different temperatures, resulting in ${\\mathsf{N i}}_{0.2}{\\mathsf{M o}}_{0.8}{\\mathsf{N}}$ nanorods array (abbreviated as NiMoN). Finally, the amorphous NiFe LDH nanosheets were electrodeposited on NiMoN nanorods to form 3D hierarchical NiMoN/NiFe LDH electrocatalyst. As-synthesized NiMoN/NiFe LDH heterostructure electrocatalyst not only provides abundant active sites due to multi-interface but also facilitates the mass transfer of reactant and fast release of gas bubbles. X-ray diffraction (XRD) patterns of NiMoN/NiFe LDH are shown in Fig. 1b. The crystalline structure of as-prepared precursor by the first-step hydrothermal reaction can be assigned to $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ (Supplementary Fig. 1). After the annealed-treatment in ammonia atmosphere, the diffraction peaks at $36.5^{\\circ}$ and $65.7^{\\circ}$ are indexed to (100) and (110) planes of $\\mathsf{N i}_{0.2}\\mathsf{M o}_{0.8}\\mathsf{N}$ (JCPDS No. 29-0931). The remaining three sharp diffraction peaks can be assigned to the substrate of Ni foam. After the electrodeposition process of NiFe LDH nanosheets on NiMoN nanorods (Fig. 1b), no obvious diffraction peak can be detected except for two diffraction peaks from $\\mathsf{N i}_{0.2}\\mathsf{M o}_{0.8}\\mathsf{N}.$ indicating the amorphous and ultrathin feature of NiFe LDH. \n\nTo confirm the geometric morphology of hierarchical core-shell NiMoN/NiFe LDH electrocatalyst, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) are employed. As shown in Supplementary Fig. 2, dense $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}0$ nanorods array with an average diameter of $0.5~{\\upmu\\mathrm{m}}$ and lengths of tens of microns are perpendicularly aligned on NF. After the nitridation treatment of $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ nanorods, there is no significant change upon the morphology of NiMoN nanorods except the surface became rougher. Then, NiFe LDH nanosheets were directly electrodeposited on the conductive NiMoN nanorods. As shown in Fig. 1c, d, the ultrathin NiFe LDH nanosheets were vertically and densely distributed on the surface of NiMoN nanorods, indicating the formation of 3D hierarchical architecture of NiMoN/NiFe LDH. In comparison, NiFe LDH nanosheets were directly electrodeposited on NF (Supplementary Fig. 2). Elemental mappings of various arrays were conducted, indicating that these elements were homogeneously distributed (Supplementary Fig. 3\\~5). The detailed heterostructure of NiMoN/NiFe LDH was further confirmed by TEM images (Fig. 1e, f). It is obvious that NiMoN/NiFe LDH is composed of NiMoN nanorods cores and NiFe LDH nanosheets shells. NiFe LDH is interconnected with each other and tightly grow on NiMoN nanorods, offering abundant active sites and facilitating electrolyte diffusion31. The high-resolution TEM (HR-TEM) image shows the heterointerface existed between NiMoN and amorphous NiFe LDH (Fig. 1g and Supplementary Fig. 6). The lattice fringe with a d-spacing of $0.28\\ensuremath{\\mathrm{nm}}$ is attributed to the (001) plane of NiMoN, whereas the shell is dominated by the amorphous NiFe LDH, which is more OER-active than their crystalline counterparts and consistent with the XRD results (Fig. 1b)32,33. The different contrast in HR-TEM images is interrelated to the difference in the thickness between the nanosheets and the nanorods. The high-angle annular dark-field scanning TEM (HAADFSTEM) and energy dispersive X-ray (EDX) mapping images showed that Ni, Mo, N, Fe and O elements are distributed in the entire region. (Fig. 1h and Supplementary Fig. 7\\~8). In comparison, the TEM images of NiMoN nanorods and NiFe LDH nanosheets are shown in Supplementary Fig. 9\\~10. Therefore, these results demonstrated the 3D hierarchical NiMoN/NiFe LDH electrocatalyst has been synthesized by this typical approach. \n\n![](images/cf3560359d4c848955f439f3fb35d414d89e4245b6a4b5d9ebf4f07a40aefd2d.jpg) \nFig. 1 | Schematic representation, structural and morphological characterizations. a Schematic illustration of the synthesis procedure of NiMoN/NiFe LDH. b The XRD patterns of NiMoN and NiMoN/NiFe LDH. c, d SEM images, e, f TEM and \ng HR-TEM images of NiMoN/NiFe LDH. h EDS element mapping of NiMoN/ NiFe LDH. \n\nX-ray photoelectron spectroscopy (XPS) measurement was employed to analyze the surface element composition and chemical state of various electrocatalysts. Ni, Mo, Fe, N and O was identified in the survey spectrum of NiMoN/NiFe LDH (Supplementary Fig. 11). For the Ni $2p$ spectra in Fig. 2a, the binding energy of 852.8, 855.8, 870.1 and $873.6\\mathrm{eV}$ are ascribed to Ni $2p_{3/2}$ and Ni $2p_{1/2}$ of Ni-N and ${\\mathsf{N i}}^{2+}$ for NiMoN nanorods, respectively33. The two peaks at 855.6 and $873.4\\mathrm{eV}$ are attributed to ${\\mathsf{N i}}^{2+}$ in NiFe LDH (Supplementary Fig. 12b). After deposition of NiFe LDH, the peaks of Ni-N species disappeared and the two peaks at 856.2 and $873.9\\mathrm{eV}$ can be assigned to divalent Ni from NiMoN/NiFe LDH. The positive shift compared with NiMoN revealed the efficient charge transfer between NiFe LDH and NiMoN34. As shown in Fig. 2b, the Mo $3d$ core-level spectra of NiMoN can be well-deconvoluted into three doublets at 229.3, 229.8, 232.3, 232.5, 233.0 and $235.5\\mathrm{eV}.$ , which can be attributed to Mo $3d_{5/2}$ and Mo $3d_{3/2}$ of $\\mathsf{M o}^{3+}$ , $\\mathsf{M o}^{4+}$ and $\\mathsf{M o}^{6+}$ , respectively16,33. After the decoration of NiFe LDH, there remain two valence states of $\\mathsf{M o}^{4+}$ and $\\mathsf{M o}^{6+}$ in Mo $3d$ spectrum from NiMoN/NiFe LDH. The Fe $2p$ XPS spectra of NiMoN/NiFe LDH in Fig. 2c shows four deconvoluted peaks at 710.9, 712.5, 724.5 and $726.3\\mathrm{eV}$ , corresponding to Fe $2p_{3/2}$ and Fe $2p_{1/2}$ of $\\mathsf{F e}^{2+}$ and $\\mathsf{F e}^{3+}$ , respectively, which is negative shift in binding energy compared with NiFe LDH, indicating the strong electronic interactions between NiFe LDH and NiMoN32. The $\\textsf{N}_{1s}$ spectra of NiMoN shows three peaks at 395.6, 398.3 and $399.9\\mathrm{eV}$ , attributing to Mo $3p_{3/2}$ , Ni/Mo-N and N-H moieties (Fig. 2d), in which the latter results from incomplete reaction with ammonia18,35. The binding energy of NiMoN/NiFe LDH is similar with NiMoN, along with the decreased strength due to the deposition of the NiFe LDH. From the high-resolution O 1s spectra of NiMoN/NiFe LDH, the peaks at 529.6, 531.0 and ${532.4\\mathrm{eV}}$ can be attributed to metal-oxygen bond, hydroxyl species and adsorbed water molecules on the surface (Supplementary Fig. 11b)36. The XPS spectra of NiFe LDH and $N i M o O\\cdot H_{2}O$ were conducted (Supplementary Fig. 12\\~13). Based on the above analysis, the strong heterogeneous interactions between NiFe LDH and NiMoN modulate the surface electronic structure, possibly enhancing electrocatalytic activity. \n\n![](images/d36ce855024af2144c586d29ef6e7414e5fb7085d6eace29d3f6a2aaebb36f8c.jpg) \nFig. 2 | XPS spectra. The high-resolution XPS spectra of a Ni $2p$ , b Mo 3d, c Fe $2p$ and d N 1s. \n\n# Electrocatalytic performance for OER \n\nThe electrocatalytic OER performance of various catalysts was evaluated by a standard three-electrode setup in $0_{2}$ -saturated alkaline solution and the potentials were calibrated versus reversible hydrogen electrode (vs. RHE). Figure 3a shows the $i R^{\\prime}$ -corrected linear sweep voltammetry (LSV) polarization curves of various electrocatalysts, exhibiting the highest OER performance of as-activated NiMoN/NiFe LDH. Strikingly, as-activated NiMoN/NiFe LDH requires the overpotentials of only 236 and $266\\mathrm{mV}$ at the current densities of 500 and $1000\\mathsf{m A c m}^{-2}$ , dramatically lower than those of NiFe LDH (351 and $406\\mathsf{m V})$ , NiMoN (492 and $575\\mathrm{mV}$ ), $\\mathsf{N i M o O}_{4}$ (465 and ${548}\\mathrm{mV}.$ ), and Ni foam $(719\\mathrm{mV})$ in Fig. 3b. Moreover, the value surpasses most heterostructure catalysts in the previous reports (Fig. 3d and Supplementary Table $1)^{37-40}$ . As shown in Fig. 3c, as-activated NiMoN/NiFe LDH possess the Tafel slope of $42.2\\boldsymbol{\\mathrm{mV}}\\boldsymbol{\\mathrm{dec}}^{-1}$ , which is lower than $83.2\\mathsf{m V}$ dec-1 for NiFe LDH and $170.9\\mathrm{mV}\\mathrm{dec}^{\\cdot1}$ for NiMoN, indicating the rapid reaction kinetics toward electrocatalytic water oxidation. To gain a general understanding of the intrinsic activity of as-activated NiMoN/NiFe LDH, turnover frequency (TOF) and electrochemical surface area (ECSA) normalized current density have been estimated. The number of active sites was quantified through an electrochemical method according to the literature41. The TOF of as-activated NiMoN/NiFe LDH is $3.39\\mathsf{s}^{-1}$ at $1.53\\ensuremath{\\mathrm{V}}$ vs. RHE, which is $^{\\sim3}$ times and $^{-37}$ times higher than those of NiFe LDH $(\\mathbf{1.03s^{-1}})$ and NiMoN $\\left(0.09{\\sf s}^{-1}\\right)$ , respectively (Fig. 3e and Supplementary Fig. 14). The ECSA value was measured through the electrochemical double-layer capacitances $\\mathrm{(C_{dl})}$ determined by cyclic voltammetry method. As-activated NiMoN/NiFe LDH possesses the highest $\\mathbf{C_{dl}}$ value of ${\\bf11.4}~{\\bf m}{\\bf F}~{\\bf c m}^{-2}.$ , which is higher than those of NiFe LDH $(7.5~\\mathsf{m F}~\\mathsf{c m}^{-2})$ ) and NiMoN $(4.1~\\mathsf{m F}~\\mathsf{c m}^{-2})$ , indicating that more exposed catalytic active sites are attained by the hierarchical architecture (Fig. 3f and Supplementary Fig. 15). In Fig. 3g, ECSA-normalized current density has the same trend as current density evaluated by geometric surface area, indicating the improvement of electrocatalytic activity is ascribed to the enlarged ECSA and the promoted intrinsic activity42. The larger TOF value and higher ECSA-normalized current density of as-activated NiMoN/NiFe LDH as compared to other samples reveal that the heterostructure plays a significant role in facilitating kinetics toward water oxidation. EIS was measured to detect the charge-transfer property. As shown in Fig. 3h, the Nyquist plot is fitted using Randles equivalent circuit model. As-activated NiMoN/NiFe LDH possesses a smaller semicircle, presenting the excellent conductivity and rapid electronic transport of the heterostructure. Long-term stability is a pivotal parameter to estimate the electrocatalytic performance, especially at large current density and large-scale water splitting application. As shown in Fig. 3i, as-activated NiMoN/NiFe LDH was observed by the continuous test over $250\\mathsf{h}$ at a constant potential without obvious decay in current density around $1000\\mathsf{m A c m}^{-2}$ , suggesting the excellent catalytic stability of the catalyst for water oxidation. The Faradaic efficiency (FE) was calculated in comparison to the amount oxygen produced experimentally against theoretical quantity. The FE of as-activated NiMoN/NiFe LDH is about $98.6\\%$ (Supplementary Fig. 16), indicating no side reaction occurred during OER process. \n\nA series of control experiments were conducted for NiMoN/NiFe LDH. Firstly, the effect of nitridation temperature on the preparation of NiMoN-T/NiFe LDH (T represents the nitridation temperature) was investigated. From XRD pattern (Supplementary Fig. 17), the crystallinity of NiMoN improved with the increasing nitridation temperature. The OER performance of NiMoN under different nitridation conditions and the decoration of NiFe LDH nanosheets has been measured. As presented in Supplementary Fig. 18, as-activated NiMoN/NiFe LDH drives the current density of $500\\mathsf{m A c m}^{-2}$ at the overpotential of $236\\mathrm{mV}.$ , which is smaller than that of NiMoN-400/NiFe LDH $(275\\mathrm{mV})$ and NiMoN-600/NiFe LDH $(286\\mathsf{m V})$ , indicating that the best nitridation condition is $500^{\\circ}\\mathrm{C}$ . The effect of different calcination atmosphere on ${\\mathsf{N i M o O}}_{4}{\\cdot}{\\mathsf{H}}_{2}{\\cdot}_{}0$ was also investigated. $\\mathbf{MoNi_{4}}/\\mathbf{MoO}_{2}$ and $\\mathsf{N i M o O}_{4}$ were formed in a reductive and argon atmosphere, respectively (Supplementary Fig. 19). For a better comparison, NiFe LDH nanosheets were also deposited on $\\mathbf{MoNi_{4}}/\\mathbf{MoO}_{2}$ and $\\mathsf{N i M o O}_{4}$ . The $\\mathsf{M o N i_{4}/M o O_{2}/l}$ NiFe LDH and NiMoO4/NiFe LDH requires the overpotentials of 271 and $330\\mathrm{mV}$ at $500\\mathsf{m A c m}^{-2}$ , which is worse than that of NiMoN nanorods (Supplementary Fig. 20). This result indicated that the nitridation treatment is better choice due to the good electrical conductivity for these catalysts. \n\n![](images/19afd7ab225568d39c5a7ada3ab995172f7860b204223b601b2310ed43780876.jpg) \nFig. 3 | OER catalytic performance. a The OER polarization curves of as-activated LDH, NiFe LDH and NiMoN. f Double-layer capacitance $\\mathrm{(C_{dl})}$ . $\\pmb{\\mathrm{\\check{g}}}$ ECSA normalized NiMoN/NiFe LDH, NiFe LDH, NiMoN, $\\mathsf{N i M o O}_{4}$ and Ni foam in 1 M KOH. b The polarization curves. h Electrochemical impedance spectroscopy. i The chronoverpotential of catalysts at different current densities. c Corresponding Tafel oamperometry curve of as-activated NiMoN/NiFe LDH for a continuous $250\\mathsf{h}$ slope. d Comparison of the overpotentials for reported electrocatalysts at operation at a constant potential. $1000\\mathsf{m A c m}^{-2}$ . e The potential-dependent TOF plot of as-activated NiMoN/NiFe \n\nThe electrochemical HER performance of NiMoN/NiFe LDH was assessed in ${\\sf N}_{2}$ -saturated 1 M KOH, corresponding to the LSV polarization curves with $i R$ compensation (Supplementary Fig. 21a). To deliver the current densities of 500 and $1000\\mathsf{m A c m}^{-2}$ , NiMoN/NiFe LDH presents the smallest overpotentials of 150 and $205\\mathsf{m V}$ among the electrocatalysts including NiMoN (210 and $260\\mathrm{mV}.$ ), NiFe LDH (455 and $509\\mathrm{mV})$ , $\\mathsf{N i M o O}_{4}$ (482 and $530\\mathrm{mV})$ , and Ni foam (588 and $711\\mathrm{mV},$ , demonstrating the substantial improvement in catalytic activity after the decoration of NiFe LDH nanosheets (Supplementary Fig. 21b). The Tafel slope of NiMoN/NiFe LDH is $39.1\\mathrm{mV~dec^{-1}}$ , indicating the rapid reaction kinetics and the reaction process follows the Volmer-Heyrovsky mechanism with the Heyrovsky as the ratedetermining step (Supplementary Fig. 21c). The synergistic effect of the heterostructure could enhance the HER activity. NiFe LDH nanosheets as the shell promote the water dissociation and enhance the rate for the formation of adsorbed hydrogen $\\mathrm{(H_{ad})}$ intermediates. Subsequently, $\\mathrm{H}_{\\mathrm{ad}}$ transfers and adsorbs on the NiMoN nanorods to combine with another $\\mathrm{H}_{\\mathrm{ad}}$ or adsorbed water molecule to form ${\\mathsf{H}}_{2}^{\\ 14,43,44}$ . Furthermore, EIS was performed to probe the charge-transfer kinetics. NiMoN/NiFe LDH shows the smallest semicircle diameter (Supplementary Fig. 21d), revealing a rapid catalytic kinetics electrontransfer process. The calculated $\\mathbf{C_{dl}}$ value of NiMoN/NiFe LDH from CV scans with different rates is $17.5\\mathsf{m F c m}^{-2}$ , which is the largest among asobtained electrocatalysts, indicating more exposure area of the active sites attained by hierarchical architecture (Supplementary Fig. 22\\~23). The I-t curves were used to evaluate the long-term stability of the catalysts at a constant potential. NiMoN/NiFe LDH exhibits negligible degradation in $100\\mathsf{h}$ (Supplementary Fig. 24), indicating superior catalytic stability and promising of industrial application. \n\n# Electrocatalytic performance for overall water splitting \n\nConsidering the excellent HER and OER electrochemical activities, asactivated NiMoN/NiFe LDH served as bifunctional catalysts for both anode and cathode to assemble a two-electrode system for overall water splitting (Fig. 4a). As-activated NiMoN/NiFe LDH | | NiMoN/NiFe LDH exhibits the low cell voltages of 1.70 and 1.77 V at the current densities of 500 and $1000\\mathsf{m A c m}^{-2}$ in 1 M KOH at $25^{\\circ}\\mathrm{C}$ (Fig. 4b). We note that performance of NiMoN/NiFe LDH outperforms NiMoN (2.00 and 2.20 V), NiFe LDH (2.11 and 2.33 V), and other electrocatalysts reported in previous literature, highlighting the potential for practical overall water splitting. (Fig. 4e and Supplementary Table $2)^{37,39}$ . Furthermore, the industrial conditions are implemented to seek the potential for the large-scale application. Strikingly, NiMoN/NiFe LDH delivers the current densities of 500 and $1000\\mathsf{m A c m}^{-2}$ as low as 1.54 and $\\boldsymbol{1.62\\mathrm{V}}$ in $30\\%$ KOH at $80^{\\circ}\\mathrm{C}$ (Fig. 4c). Concerning the stability as a significant parameter, the electrocatalyst should operate over a longterm test under large current density. The two-electrode system shows no evident fluctuation at a constant potential for a current density of \n\n![](images/c9255cf5e2029264e1502a353ab72570646bbebba0eeb6da2872b04721649ad6.jpg) \nFig. 4 | Schematic diagram and catalytic performance of overall water splitting. a Schematic diagram of overall water splitting in a two-electrode system. Overall water splitting performance of as-activated NiMoN/NiFe LDH in b 1 M KOH at $25^{\\circ}\\mathrm{C}$ and $c30\\%$ KOH at $80^{\\circ}\\mathrm{C}$ . d Chronoamperometry curve of as-activated NiMoN/NiFe \n\n$1000\\mathsf{m A c m}^{-2}$ for $50\\mathsf{h}$ , suggesting good durability (Fig. 4d). Alkaline anion exchange membrane (AEM) water electrolysis is a competitive way to produce clean hydrogen fuel. Furthermore, as-activated NiMoN/NiFe LDH was integrated into a membrane electrode assembly (MEA) to evaluate the water splitting performance at different temperature (Supplementary Notes 1 and Fig. 25). As-activated NiMoN/ NiFe LDH achieves the industrial current density of $1000\\mathsf{m A c m}^{-2}$ at the cell voltage of $2.29{\\mathrm{V}}$ at $25^{\\circ}\\mathrm{C}$ . With the temperature increase to $60^{\\circ}\\mathrm{C}$ , the electrocatalyst requires the cell voltage of 1.85 and $\\boldsymbol{1.92\\mathrm{V}}$ to drive the current densities 500 and $1000\\mathsf{m A c m}^{-2}$ , which was lower than that at $25^{\\circ}\\mathrm{C}$ , indicating the activities of the electrocatalysts are related to the operating temperature. In brief, the 3D hierarchical coreshell structure of NiMoN/NiFe LDH leads to the electron redistribution at the interface and modulates the electronic structure, facilitating the water dissociation and adjusting the binding strength of adsorbed intermediates. Secondly, the combination of NiMoN nanorods and NiFe LDH nanosheets not only gives a large surface area and more exposed active sites, but also improves the intrinsic activity of catalyst. Moreover, NiMoN/NiFe LDH nanoarray was in situ grown on a current collect without use of polymer binder. The nanoarrays accelerates mass transfer, ensures sufficient contact with the electrolyte, and facilitates the release of bubbles. All these advantages promote the catalytic activity of as-activated NiMoN/NiFe LDH and offer an opportunity to practical application. \n\n# In-situ spectroelectrochemistry analysis \n\nTo identify the active phase and dynamic surface reconstruction of NiMoN/NiFe LDH, in-situ Raman spectroscopy was performed and \n\nLDH toward overall water splitting in $30\\%$ KOH at $80^{\\circ}\\mathrm{C}$ e Comparison of the cell voltage with as-activated NiMoN/NiFe LDH and other electrocatalysts at current density of $500\\mathsf{m A c m}^{-2}$ . \n\nacquired as the function of applied potential with an interval of 0.1 V. At the open circuit potential (OCP), NiMoN/NiFe LDH and NiFe LDH show characteristic peaks at 532 and $702\\mathrm{cm}^{-1}$ , which can be attributed to Ni-O in disordered ${\\mathsf{N i}}({\\mathsf{O H}})_{2}$ and Fe-O in $\\gamma\\mathrm{-FeOOH^{45,46}}$ , respectively (Fig. 5a, b). Specifically, a well-defined peak at $890\\mathsf{c m}^{-1}$ is assigned to Mo-O bond for NiMoN/NiFe LDH. For NiMoN/NiFe LDH, two characteristic peaks appeared at 473 and $551\\mathrm{cm}^{-1}$ beyond $1.35\\mathsf{V}$ corresponding to $E_{\\mathrm{g}}$ bending and $A_{\\mathrm{{1g}}}$ stretching vibration of ${\\mathsf{N i}}^{\\mathsf{I I I}}{\\cdot}{\\mathsf{O}}$ in $\\gamma\\mathrm{.}$ NiOOH, respectively. While Mo-O bond at $890\\mathsf{c m}^{-1}$ has vanished at this potential46. The appearance of these two peaks indicated that $\\gamma{\\cdot}\\mathsf{N i}$ (Fe) OOH is the active species for NiMoN/NiFe LDH in OER process. Moreover, a broad band in the region of $900{\\cdot}1100{\\ c m}^{-1}$ assigned to $\\nu(0\\cdot0)$ of active oxygen species was observed above $\\boldsymbol{1.35\\mathrm{V}}$ , which is generated by the deprotonation of oxyhydroxide47. Similar Raman peaks appeared until the potential up to $1.4\\upnu$ for NiFe LDH. In addition, the higher $I_{473}/I_{551}$ ratio of NiMoN/NiFe LDH than NiFe LDH at 1.5 V should be assigned to $\\gamma{\\mathrm{-}}\\mathsf{N i O O H}$ , revealing the approximate oxidation state of $+3.5^{48}$ . Thus, the generation of active species is easier and more active $\\mathsf{N i}^{3+/4+}$ species accumulate for as-activated NiMoN/NiFe LDH, promoting the acquisition of optimized electronic structure for OER. \n\nIn-situ ultraviolet-visible (UV-Vis) spectroelectrochemistry tests were conducted in home-made cell to get insight into metal redox process during OER. As shown in Fig. 5c, d, a conspicuous spectroscopic feature was observed for NiMoN/NiFe LDH and NiFe LDH at different applied potentials. There is a broad absorption band between 350 and $600\\mathsf{n m}$ with increasing anodic potential, suggesting the oxidation of Ni center, which is assigned to nickel d-d interband transition and the formation of active oxygen species49,50. The accumulation of oxidized species for NiMoN/NiFe LDH starts at $\\boldsymbol{1.35\\mathrm{V}}$ vs. RHE, which is in a lower potential compared with NiFe LDH, indicating the heterostructure is beneficial to generate the active species. The absorbance intensity was recorded through potential cycling to track the variation for the oxidation state of Ni (Supplementary Fig. 26). The absorbance intensity rises along with the Ni redox wave. NiMoN/NiFe LDH shows the increased absorption intensity with an onset potential shift to more negative potentials than NiFe LDH, demonstrating the heterointerface enables to generate higher oxidation state of Ni and improves the reaction kinetics, in accordance with the analysis of in-situ Raman spectra. \n\n![](images/83efe6e71398781643772578c29900b2c79cd4f5b9db6c555c57504f15afaea5.jpg) \nFig. 5 | Mechanism analysis. In-situ Raman spectroscopy of a NiMoN/NiFe LDH and LDH and d NiFe LDH at various potentials. Nyquist plots for e NiMoN/NiFe LDH and b NiFe LDH at various potentials. In-situ UV-Vis absorption spectra of c NiMoN/NiFe f NiFe LDH at different applied potentials. \n\nEIS is a useful electrochemical measurement to probe the properties of electrode/electrolyte interfaces and the adsorption kinetics of reactants on the electrode surface. Operando EIS was performed to get in-depth information on electrochemical reaction kinetics. Figure 5e, f shows the Nyquist plot of NiMoN/NiFe LDH and NiFe LDH in 1 M KOH from 1.10 to $1.50\\mathrm{v}$ . The total resistance of as-activated NiMoN/NiFe LDH and NiFe LDH at different applied potentials are quantified from Nyquist plots (Supplementary Fig. 27a). It is obvious that NiMoN/NiFe LDH presents smaller charge transfer resistance within the range of applied potential, indicating the heterostructure accelerates interfacial charge transfer, which could promote surface activation of electrocatalyst51. Moreover, the evolution of reactants $({}^{*}\\mathrm{OH})$ on the catalysts surface could be described by total resistance. The resistance of NiMoN/NiFe LDH was much lower than that of NiFe LDH within \n\n1.30 V, revealing the faster kinetics for adsorption of $^{*}\\mathrm{OH}$ at low driving potential. The pseudocapacitance arising from $^{*}\\mathrm{OH}$ was defined as $\\mathrm{c}_{\\upphi},$ which was utilized to quantify the adsorption coverage of ${^*}\\mathrm{OH}^{52}$ . The $\\mathbf{C}_{\\Psi}$ of NiMoN/NiFe LDH is higher than that of NiFe LDH in the whole potential, indicating the higher coverage of $^{*}\\mathrm{OH}$ for NiMoN/NiFe LDH (Supplementary Fig. 27b, 28). The fast $^{*}\\mathrm{OH}$ accumulation of NiMoN/ NiFe LDH should be in favor of overall catalytic driving force53,54. Moreover, the evolution of adsorbed $^{*}\\mathrm{OH}$ on electrocatalysts was evaluated based on Laviron equation54. The steady redox currents all exhibit linear correlation with the square root of potential scan rate in CV $(5{\\sim}700\\mathrm{mV}\\mathrm{s}^{-1})$ . The $K_{s}$ value of NiMoN/NiFe LDH is $0.14\\ s^{-1}$ , which is larger than that of NiFe LDH $_{(0.11\\mathsf{s}^{-1})}$ , revealing the strong binding strength of $^{*}\\mathrm{OH}$ (Supplementary Fig. 29\\~31). Moreover, the Bode plot reflects both the dynamic evolution of electrocatalysts and OER process, exhibiting the variation of phase angle with frequency. Generally, the peaks of phase angle at low and high frequency are on account of surface charge conduct and electron transfer in inner layer of catalyst, respectively, corresponding to the OER process and electrocatalyst electrooxidation reaction51. At the potential of $1.35\\mathsf{V}$ the phase angle of NiMoN/NiFe LDH reduces much quicker at the high-frequency region, indicating the violent electrocatalyst electrooxidation reaction with the fast charge transfer of electrocatalyst inner-layer (Supplementary Fig. 32). While NiFe LDH experiences similar phenomenon at more positive potential, consistent with in-situ Raman and UV-Vis spectra. In the low-frequency region, the smaller phase angle reveals that OER process occurs drastically after $\\ensuremath{1.40\\mathrm{V}}$ for NiMoN/NiFe LDH. For the NiFe LDH, OER process starts at 1.45 V. In a word, NiMoN/NiFe LDH has a faster charge transfer in surface and inner layer, revealing a better electrochemical performance compared with NiFe LDH. This is attributed to the ensemble effect and electronic interaction, thus optimizing adsorption energies and accelerating reaction kinetics. \n\n![](images/8b4213ec99fd8df67a4d159120d1d87515df7ee10b1a1587c3e2a650f800ee76.jpg) \nFig. 6 | Mechanism and theoretical analysis. a Linear sweep voltammetry curve of as-activated NiMoN/NiFe LDH in alkaline electrolytes with different pH. b The logarithms of current density at $1.50\\mathrm{V}$ vs. RHE against the pH. The DEMS signals of $^{34}\\mathrm{O}_{2}$ and $^{36}\\mathrm{O}_{2}$ vs. c time and d applied potential for as-activated NiMoN/NiFe LDH. \n\nAs-activated NiMoN/NiFe LDH electrocatalyst after OER test was characterized to check the crystal structure and chemical state. From XRD patterns, the peak intensity weakened after the OER test (Supplementary Fig. 33). The TEM image shows that as-activated NiMoN/ NiFe LDH retains the core-shell structure and NiFe LDH nanosheet attached NiMoN nanorods tightly, consistent with SEM results (Supplementary Fig. 34). For the high-resolution XPS spectra of Ni $2p$ , the binding energy positively shifts and the higher valence states of ${\\mathsf{N i}}^{3+}$ appears, indicating the formation of oxyhydroxides. Besides, the main peak of Fe $2p$ positively shifts towards higher binding energy compared with pristine electrocatalyst, demonstrating the oxidation state of Fe $(+3)$ . Moreover, the signals of Mo $3d$ and N 1s after OER test were weaker than the pristine catalyst (Supplementary Fig. 35). \n\n# Identification of mechanism \n\nTo get deep insight into the reaction mechanism, a series of electrocatalytic measurements were performed. The catalytic performance of as-activated NiMoN/NiFe LDH in alkaline electrolytes with increasing \n\nThe calculated DOS of metal 3d, oxygen 2p and total DOS for e NiMoN/NiFe LDH and f NiFe LDH. $\\mathbf{g}$ Calculated crystal orbital Hamilton population (COHP). Gibbs free energy diagram of OER steps for h LOM pathway and i AEM pathway. \n\npH values from 12.5 to 14 was shown in Fig. 6a, b to detect the protonelectron transfer kinetics. The activity of as-activated NiMoN/NiFe LDH exhibits strong pH dependence, revealing the non-concerted protonelectron transfer process22,23. While NiFe LDH showed significantly lower pH-dependent OER kinetics with dominant CPET steps (Supplementary Fig. 36). Therefore, we proposed as-activated NiMoN/NiFe LDH follows the LOM pathway rather than AEM pathway, in which lattice oxygen directly participates in OER process. To direct clarify the lattice oxygen oxidation process, $^{18}0$ isotope labeling DEMS was conducted by NiMoN/NiFe LDH. Firstly, NiMoN/NiFe LDH was electrochemically activated in 0.1 M KOH electrolyte with $\\mathsf{H}_{2}^{\\mathsf{18}}\\mathsf{O}$ and rinsed by ${\\mathsf{H}}_{2}^{\\ 16}{\\mathsf{O}}$ after labeled process. Afterward, the $^{18}0$ isotope labeled catalysts were tested in 0.1 M KOH with ${\\mathsf{H}}_{2}^{\\ 16}{\\mathsf{O}}$ by CV test, and the generated gaseous product was monitored by mass spectrometry. In Fig. 6c, the peak of $^{18}0^{16}0$ (mass-to-charge, $\\scriptstyle{\\mathrm{m}}/z=34$ ) with pronounced periodical intensity was observed for as-activated NiMoN/NiFe LDH, while no signal for $^{18}0^{18}0$ $(\\mathsf{m}/z=36)$ . The results testified lattice oxygen was involved in OER process and half of oxygen atom in oxygen was derived from lattice oxygen, while another oxygen was from the electrolyte22,25. The mass signal of $^{18}0^{16}0$ was plotted against the anodic potential, and it shows similar variation tendency under CV measurement, revealing the dynamic trace of DEMS (Fig. 6d). Moreover, NiFe LDH exhibits similar periodic signal of $^{18}0^{16}0$ and the much lower intensity reveals that the degree of lattice oxygen involvement is lower (Supplementary Fig. 37\\~38). Above results indicates as-activated NiMoN/NiFe LDH prefers LOM pathway. \n\nTo gain theoretical insights into the transformation of the reaction mechanism, DFT calculations were employed to determine the electronic structure and energy barrier (Supplementary Notes 2). Based on the experiment results, NiFeOOH and Mo-doped NiFeOOH were selected as model for DFT calculation. Firstly, the projected density of state (PDOS) was employed to analyze the orbital distribution of metal d band and oxygen p band for both NiMoN/NiFe LDH and NiFe LDH (Fig. 6e, f). The overlap of metal d band and O 2p bands evidently, reveals the covalent hybridization of metal sites and oxygen ligands enhanced23. Moreover, the electronic configuration and metaloxygen bond strength were evaluated by crystal orbital Hamilton populations (COHP). The higher occupied anti-bonding states of Ni 3d band near Fermi level for NiMoN/NiFe LDH manifests the stronger hybridization between the metal d band and O 2p band. The metaloxygen bond strength was quantified by the integral of COHP up to Fermi level, and the larger absolute value of ICOHP of Ni-O (−1.14) bonding for NiMoN/NiFe LDH reveals the enhanced covalency26. The enhanced covalency of M-O bond promotes the delocalization of electrons in NiMoN/NiFe LDH, providing a premise for the participation of lattice oxygen during OER. Based on the above analysis, OER process through different reaction pathway was simulated by DFT calculation. For OER process based on LOM pathway, the catalyst experiences deprotonation to form exposed lattice oxygen (Supplementary Fig. 39). Then, the OH- adsorbs on lattice oxygen by nucleophilic attacking. After the deprotonation of $^{*}00\\mathsf{H}$ , the oxygen releases and leave oxygen vacancy sites on the surface. In the end, the produced oxygen vacancy site is refilled by OH-. The calculated Gibbs free energy for LOM was implemented (Fig. $6\\mathsf{h})^{54,55}$ . For NiMoN/NiFe LDH, the deprotonation of $^{*}\\mathrm{OH}$ was the rate-determine step (RDS) with the overpotential of $0.72\\mathrm{eV}$ . As for the conventional AEM pathway, it undergoes four CPET steps with the oxygen intermediates $({}^{*}\\mathrm{OH},{}^{*}\\mathrm{O}$ and ${}^{*}00\\mathsf{H}$ ) on metal sites (Supplementary Fig. 40). The RDS was the conversion from $^{*}\\mathrm{OH}$ to $^*0$ intermediates with a high energy barrier of $2.29\\mathrm{eV}$ (Fig. 6i). This consequence is consistent with the results of $^{18}0$ labeling DEMS, indicating the reaction mechanism was switched to LOM. \n\n# Discussion \n\nIn summary, the hierarchical heterostructure electrocatalysts of NiMoN/NiFe LDH have been synthesized by attaching NiFe LDH nanosheets on NiMoN nanorods, regulating the electronic states on catalytically active sites and tracking the relationship of structureactivity. Remarkably, as-activated NiMoN/NiFe LDH exhibits a low overpotential of $266\\mathsf{m V}$ to deliver an industrial current density of $1000\\mathsf{m A c m}^{-2}$ , maintaining decent performance for at least $250\\mathsf{h}$ for OER. The as-activated NiMoN/NiFe LDH promotes the generation of high valence active sites to optimize the electronic structure and accelerate OER kinetics by in-situ spectroelectrochemistry. From both theoretical and experimental results, the metal-oxygen covalency is enhanced and the OER mechanism switched to lattice oxygen mechanism. This work opens an avenue for the rational design of nonprecious based and efficient electrocatalysts for sustainable hydrogen production from industrial water splitting. \n\n# Methods Synthesis of NiMoN nanorods \n\nFirstly, a piece of nickel foam $(2\\times3\\mathrm{cm}^{2})$ was immersed in the solution containing $0.04\\mathsf{M}$ ${\\mathsf{N i}}({\\mathsf{N O}}_{3})_{2}{\\cdot}6{\\mathsf{H}}_{2}{\\mathsf{O}}$ and 0.01 M $(\\mathsf{N H}_{4})_{6}\\mathsf{M o}_{7}\\mathsf{O}_{24}{\\cdot}4\\mathsf{H}_{2}\\mathsf{O}$ with 15 ml ${\\sf H}_{2}{\\sf O}$ and transferred into a $25\\mathrm{mL}$ Teflon vessel. Then, the vessel was sealed in a stainless autoclave and heated to $150^{\\circ}\\mathrm{C}$ and kept for $6\\mathsf{h}$ . After cooling down to room temperature, the $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ washed with DI water and ethanol and dried in an oven at $60^{\\circ}\\mathsf C.$ Finally, the as-prepared $\\mathsf{N i M o O}_{4}{\\cdot}\\mathsf{H}_{2}\\mathsf{O}$ nanorods were heated to $500^{\\circ}\\mathrm{C}$ at a ramp rate of $5^{\\circ}\\mathrm{C}_{I}$ min and maintained for $2\\mathfrak{h}$ in ${\\mathsf{N H}}_{3}$ atmosphere. After the furnace naturally cooled down to room temperature and NiMoN nanorods were obtained. \n\n# Synthesis of NiMoN/NiFe LDH \n\nThe NiFe LDH nanosheets were electrodeposited on the surface of NiMoN nanorods to obtain NiMoN/NiFe LDH. The electrodeposition was conducted in a standard three-electrode setup, using NiMoN as working electrode, a parallel platinum net as counter electrode and Ag/AgCl(saturated) as reference electrode. The electrolyte was containing 0.06 M ${\\mathsf{N i}}({\\mathsf{N O}}_{3})_{2}{\\cdot}6{\\mathsf{H}}_{2}0$ and $0.048\\mathrm{~M~Fe}(\\mathsf{N O}_{3})_{3}{\\cdot}9\\mathsf{H}_{2}\\mathsf{O}.$ The electrodeposition potential was $-1.0\\vee$ vs. $\\mathbf{Ag/AgCl}$ for $200{\\mathsf{s}}.$ Then, the assynthesized electrode was rinsed with deionized water and ethanol and dried at $60^{\\circ}\\mathsf C$ The loading weight of the formed electrocatalysts on the nickel foam was $\\approx15.8\\mathrm{mg}\\mathrm{cm}^{2}$ . \n\n# Synthesis of NiFe LDH \n\nThe NiFe LDH nanosheet was direct electrodeposited on NF as working electrode under the same procedure for NiMoN/NiFe LDH. \n\n# Structural characterization \n\nX-ray diffraction patterns were characterized using X-ray diffractometer (Rigaku Rotaflex, Japan) by Cu $\\mathsf{K}_{\\upalpha}$ radiation $(\\lambda=1.5418\\mathring{\\mathbf{A}})$ . Field emission scanning electron microscope (FE-SEM) tests were recorded on HITACHI SU5000 with an accelerating voltage of $10\\mathsf{k V}$ and energy-dispersive X-ray spectrum (EDS). Transmission electron microscope (TEM) with high-resolution mode and EDS elemental mapping were performed on FEI Tecnai F30 at an accelerating voltage of $200\\mathsf{k V}.$ X-ray photon energy spectroscopy (XPS) was performed using a Thermo Fisher ESCALAB 250Xi. In-situ Raman experiments were measured by a Raman spectrometer (Thermo Fisher, DXR Microscope) and the laser wavelength is $532\\mathsf{n m}$ . The UV-Vis measurements were conducted with UV-Vis-NIR spectrophotometer (Shimadzu UV-3600 Plus). The in-situ UV-Vis experiments were performed with a home-made quartz cuvette. The catalyst-loaded fluorine-doped tin oxide (FTO) glass was used as working electrode and the electrocatalysts loading was $0.1\\mathrm{mg}\\mathrm{cm}^{2}$ . \n\n# Electrochemical measurements \n\nThe electrochemical measurements were conducted with Corrtest CS310M using a standard three-electrode cell. As-synthesized electrode was employed as the working electrode. A Pt wire and ${\\sf H g/H g O}$ electrode were applied as the counter electrode and reference electrode, respectively. All potentials were converted to RHE using the following equation: $E_{\\mathrm{RHE}}=E_{\\mathrm{Hg/HgO}}+0.059\\:\\mathrm{pH}+0.098\\:\\mathrm{V}.$ The working area is $\\mathsf{1}\\times\\mathsf{1}\\ \\mathsf{c m}^{2}$ . The LSV polarization curves were recorded with a sweeping rate of $2\\mathsf{m}\\mathsf{V}\\mathsf{s}^{-1}$ in oxygen-saturated 1 M KOH at $25^{\\circ}\\mathrm{C}$ . The $85\\%i R$ compensation was performed manually for polarization curves after the measurement for ohmic resistance by EIS. The ECSA was measured through a series of cyclic voltammetry at various scan rate in the non-Faradaic region. EIS was performed over the frequency range from $100\\mathsf{k H z}$ to $0.01\\mathsf{H z}$ at the potential 1.48 V vs. RHE by applying an AC voltage of $5\\mathrm{mV}$ amplitude. For the measurement of FE, gas products were measured by gas chromatography (Shimadzu, GC-2014), where produced oxygen was collected by online sampling system. \n\n# First-principle calculation \n\nDFT calculations were carried out using the Vienna Ab-initio Simulation Package $(\\mathsf{V A S P})^{56}$ . The Perdew-Burke-Ernzerhof (PBE) functional within the generalized gradient approximation (GGA) was used to describe the exchange-correlation interactions. The electron-ion interactions were described by projector augmented wave (PAW) potentials57. A kinetics energy cut-off of $450\\mathrm{eV}$ was used. The force and energy convergence criteria were set as $0.02\\mathrm{eV}\\mathring{\\mathbf{A}}^{-1}$ and $10^{-4}$ eV. The Brillouin zone was sampled with a $3\\times3\\times1$ Monkhorst-Pack grid. The \n\nDFT-D3 method was used to evaluate the van der Waals (vdW) correction58. The Hubbard-U terms for Ni and Fe were considered, with the effective U value of 4.0 and $4.3\\mathrm{eV}$ for Ni and Fe, respectively. The water solvation effect was also considered by using VASPsol59. The COHP of considered atomic pairs was calculated by the Lobster code60. \n\n# Data availability \n\nThe data reported in this paper are available from the corresponding author upon reasonable request. \n\n# References \n\n1. Yu, Z. Y. et al. Clean and affordable hydrogen fuel from alkaline water splitting: past, recent progress, and Future Prospects. Adv. Mater. 33, e2007100 (2021). \n2. Abbasi, R. et al. A roadmap to low-cost hydrogen with hydroxide exchange membrane electrolyzers. Adv. Mater. 31, e1805876 (2019). \n3. Li, L., Wang, P., Shao, Q. & Huang, X. Metallic nanostructures with low dimensionality for electrochemical water splitting. Chem. Soc. Rev. 49, 3072–3106 (2020). \n4. King, L. A. et al. A non-precious metal hydrogen catalyst in a commercial polymer electrolyte membrane electrolyser. Nat. Nanotechnol. 14, 1071–1074 (2019). \n5. Zhang, B. et al. Homogeneously dispersed multimetal oxygenevolving catalysts. Science 352, 333–337 (2016). \n6. Zhang, B. et al. High-valence metals improve oxygen evolution reaction performance by modulating 3d metal oxidation cycle energetics. Nat. Catal. 3, 985–992 (2020). \n7. Wang, C. & Qi, L. Heterostructured inter-doped ruthenium-cobalt oxide hollow nanosheet arrays for highly efficient overall water splitting. Angew. Chem. Int. Ed. 59, 17219–17224 (2020). \n8. Dou, Y. et al. Approaching the activity limit of $\\mathsf{C o S e}_{2}$ for oxygen evolution via Fe doping and Co vacancy. Nat. Commun. 11, 1664 (2020). \n9. Sun, J. et al. Synergetic metal defect and surface chemical reconstruction into $\\mathsf{N i C o}_{2}\\mathsf{S}_{4}/\\mathsf{Z n S}$ heterojunction to achieve outstanding oxygen evolution performance. Angew. Chem. Int. Ed. 60, 19435–19441 (2021). \n10. Wu, T. et al. Iron-facilitated dynamic active-site generation on spinel ${\\mathsf{C o A l}}_{2}{\\mathsf{O}}_{4}$ with self-termination of surface reconstruction for water oxidation. Nat. Catal. 2, 763–772 (2019). \n11. Xu, Q. C. et al. Atomic heterointerface engineering breaks activity limitation of electrocatalysts and promises highly-efficient alkaline water splitting. Energy Environ. Sci. 14, 5228–5259 (2021). \n12. Chen, Z. et al. TM LDH meets birnessite: A 2D-2D hybrid catalyst with long-term stability for water oxidation at industrial operating conditions. Angew. Chem. Int. Ed. 60, 9699–9705 (2021). \n13. Zhang, X. et al. $\\mathsf{C o_{3}O_{4}}/\\mathsf{F e_{0.33}C o_{0.66}P}$ interface nanowire for enhancing water oxidation catalysis at high current density. Adv. Mater. 30, e1803551 (2018). \n14. Subbaraman, R. et al. Enhancing hydrogen evolution activity in water splitting by tailoring $L i^{+}{\\mathrm{-}}N i(O H)_{2}$ -Pt interfaces. Science 334, 1256–1260 (2011). \n15. Zhang, N. et al. Surface activation and Ni-S stabilization in $N i O/N i S_{2}$ for efficient oxygen evolution reaction. Angew. Chem. Int. Ed. 61, e202207217 (2022). \n16. Zhao, G. et al. An $\\mathsf{I r}/\\mathsf{N i}(\\mathsf{O H})_{2}$ heterostructured electrocatalyst for the oxygen evolution reaction: breaking the scaling relation, stabilizing iridium(V), and beyond. Adv. Mater. 32, e2000872 (2020). \n17. Du, X. et al. Modulating electronic structures of inorganic nanomaterials for efficient electrocatalytic water splitting. Angew. Chem. Int. Ed. 58, 4484–4502 (2019). \n18. Zhang, X. L. et al. An efficient turing-type $\\mathsf{A g}_{2}\\mathsf{S e}\\mathsf{-C o S e}_{2}$ multiinterfacial oxygen-evolving electrocatalyst. Angew. Chem. Int. Ed. 60, 6553–6560 (2021). efficie e202117178 (2022). \n20. Gao, Z. W. et al. Engineering NiO/NiFe LDH intersection to bypass scaling relationship for oxygen evolution reaction via dynamic tridimensional adsorption of intermediates. Adv. Mater. 31, e1804769 (2019). \n21. Yang, H. et al. Intramolecular hydroxyl nucleophilic attack pathway by a polymeric water oxidation catalyst with single cobalt sites. Nat. Catal. 5, 414–429 (2022). \n22. Grimaud, A. et al. Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution. Nat. Chem. 9, 457–465 (2017). \n23. Huang, Z.-F. et al. Chemical and structural origin of lattice oxygen oxidation in Co-Zn oxyhydroxide oxygen evolution electrocatalysts. Nat. Energy 4, 329–338 (2019). \n24. Ko, Y. et al. Layer-by-layer assembly-based electrocatalytic fibril electrodes enabling extremely low overpotentials and stable operation at 1 A cm−2 in water-splitting reaction. Adv. Funct. Mater. 31, 2102530 (2021). \n25. Wang, C. et al. Engineering lattice oxygen activation of iridium clusters stabilized on amorphous bimetal borides array for oxygen evolution reaction. Angew. Chem. Int. Ed. 60, 27126–27134 (2021). \n26. Wu, Y. et al. Triggering lattice oxygen activation of single-atomic Mo sites anchored on Ni-Fe oxyhydroxides nanoarrays for electrochemical water oxidation. Adv. Mater. 34, e2202523 (2022). \n27. Luo, Y., Zhang, Z., Chhowalla, M. & Liu, B. Recent advances in design of electrocatalysts for high-current-density water splitting. Adv. Mater. 34, e2108133 (2022). \n28. Lagadec, M. F. & Grimaud, A. Water electrolysers with closed and open electrochemical systems. Nat. Mater. 19, 1140–1150 (2020). \n29. Dionigi, F. et al. In-situ structure and catalytic mechanism of NiFe and CoFe layered double hydroxides during oxygen evolution. Nat. Commun. 11, 2522 (2020). \n30. Zhang, J. et al. Efficient hydrogen production on MoNi4 electrocatalysts with fast water dissociation kinetics. Nat. Commun. 8, 15437 (2017). \n31. Zou, X. et al. Ultrafast formation of amorphous bimetallic hydroxide films on 3D conductive sulfide nanoarrays for large-current-density oxygen evolution electrocatalysis. Adv. Mater. 29, 1700404 (2017). \n32. He, K. et al. Utilizing the space-charge region of the FeNi-LDH/CoP p-n junction to promote performance in oxygen evolution electrocatalysis. Angew. Chem. Int. Ed. 58, 11903–11909 (2019). \n33. Jia, J. et al. Nickel molybdenum nitride nanorods grown on ni foam as efficient and stable bifunctional electrocatalysts for overall water splitting. ACS Appl. Mater. Interfaces 10, 30400–30408 (2018). \n34. Wen, Q. et al. Schottky heterojunction nanosheet array achieving high-current-density oxygen evolution for industrial water splitting electrolyzers. Adv. Energy Mater. 11, 2102353 (2021). \n35. Wang, B. et al. Rational design of NiFe $\\mathsf{L D H@N i_{3}N}$ nano/microsheet arrays as a bifunctional electrocatalyst for overall water splitting. J. Mater. Chem. A 8, 17202–17211 (2020). \n36. Sun, H. et al. Rh-engineered ultrathin NiFe-LDH nanosheets enable highly-efficient overall water splitting and urea electrolysis. Appl. Catal. B 284, 119740 (2021). \n37. Shan, X. et al. An Engineered superhydrophilic/superaerophobic electrocatalyst composed of the supported $\\mathsf{C o M o S}_{\\mathrm{x}}$ chalcogel for overall water splitting. Angew. Chem. Int. Ed. 59, 1659–1665 (2020). \n38. Yu, M. et al. A hierarchically porous and hydrophilic 3D nickel–iron/ MXene electrode for accelerating oxygen and hydrogen evolution at high current densities. Nano Energy 63, 103880 (2019). \n39. Sun, H. et al. Boosting activity on $\\mathsf{C o}_{4}\\mathsf{N}$ porous nanosheet by coupling ${\\mathsf{C e O}}_{2}$ for efficient electrochemical overall water splitting at high current densities. Adv. Funct. Mater. 30, 1910596 (2020). \n40. Wu, L. et al. Heterogeneous bimetallic phosphide ${\\sf N i}_{2}{\\sf P-F e}_{2}{\\sf P}$ as an efficient bifunctional catalyst for water/seawater splitting. Adv. Funct. Mater. 31, 2006484 (2020). \n41. Chen, Y. Y. et al. Self-templated fabrication of $\\mathsf{M o N i_{4}/M o O_{3-x}}$ nanorod arrays with dual active components for highly efficient hydrogen evolution. Adv. Mater. 29, 1703311 (2017). \n42. Zhai, P. et al. Engineering single-atomic ruthenium catalytic sites on defective nickel-iron layered double hydroxide for overall water splitting. Nat. Commun. 12, 4587 (2021). \n43. Subbaraman, R. et al. Trends in activity for the water electrolyser reactions on 3d M(Ni,Co,Fe,Mn) hydr(oxy)oxide catalysts. Nat. Mater. 11, 550–557 (2012). \n44. Chang, B. et al. Bimetallic NiMoN nanowires with a preferential reactive facet: an ultraefficient bifunctional electrocatalyst for overall water splitting. ChemSusChem 11, 3198–3207 (2018). \n45. Wu, Y. J. et al. Evolution of cationic vacancy defects: A motif for surface restructuration of OER precatalyst. Angew. Chem. Int. Ed. 60, 26829–26836 (2021). \n46. Louie, M. W. & Bell, A. T. An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen. J. Am. Chem. Soc. 135, 12329–12337 (2013). \n47. Lee, S. et al. Oxygen isotope labeling experiments reveal different reaction sites for the oxygen evolution reaction on nickel and nickel iron oxides. Angew. Chem. Int. Ed. 58, 10295–10299 (2019). \n48. Li, N. et al. Influence of iron doping on tetravalent nickel content in catalytic oxygen evolving films. Proc. Natl Acad. Sci. USA 114, 1486–1491 (2017). \n49. Francas, L. et al. Spectroelectrochemical study of water oxidation on nickel and iron oxyhydroxide electrocatalysts. Nat. Commun. 10, 5208 (2019). \n50. Rao, R. R. et al. Spectroelectrochemical analysis of the water oxidation mechanism on doped nickel oxides. J. Am. Chem. Soc. 144, 7622–7633 (2022). \n51. Chen, X. et al. S-doping triggers redox reactivities of both iron and lattice oxygen in FeOOH for low-cost and high-performance water oxidation. Adv. Funct. Mater. 32, 2112674 (2022). \n52. Ge, R. et al. Selective electrooxidation of biomass-derived alcohols to aldehydes in a neutral medium: promoted water dissociation over a nickel-oxide-supported ruthenium single-atom catalyst. Angew. Chem. Int. Ed. 61, e202200211 (2022). \n53. Wang, H. Y. et al. In operando identification of geometrical-sitedependent water oxidation activity of spinel $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ . J. Am. Chem. Soc. 138, 36–39 (2016). \n54. Xiao, Z. et al. Operando identification of the dynamic behavior of oxygen vacancy-rich $\\mathsf{C o}_{3}\\mathsf{O}_{4}$ for oxygen evolution reaction. J. Am. Chem. Soc. 142, 12087–12095 (2020). \n55. He, Z. et al. Activating lattice oxygen in NiFe-based (oxy)hydroxide for water electrolysis. Nat. Commun. 13, 2191 (2022). \n56. Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 78, 1396–1396 (1997). \n57. Blochl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953 (1994). \n58. Grimme, S., Ehrlich, S. & Goerigk, L. Effect of the damping function in dispersion corrected density functional theory. J. Comput. Chem. 32, 1456–1465 (2011). \n59. Mathew, K., Sundararaman, R., Letchworth-Weaver, K., Arias, T. A. & Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 140, 084106 (2014). \n\n60. Dronskowski, R. & Blochl, P. E. Crystal orbital hamilton populations (COHP): energy-resolved visualization of chemical bonding in solids based on density-functional calculations. J. Phys. Chem. 97, 8617–8624 (1993). \n\n# Acknowledgements \n\nThis work was supported by National Natural Science Foundation of China (Nos. 21972015, 22088102, 12074053), Young top talents project of Liaoning Province (No. XLYC1907147), the Fundamental Research Funds for the Central Universities (Nos. DUT22QN207, DUT22LAB602, DUT2022TB05), the Liaoning Revitalization Talent Program (XLYC2008032) and Special Project for Key Research and Development Program of Xinjiang Autonomous Region (2022B01033). The authors acknowledge the assistance of DUT Instrumental Analysis Center. \n\n# Author contributions \n\nJ.H. supervised the research. J.H. and P.Z. conceived the research. P.Z. and C.W. carried out the experiments, collected and analyzed the experimental data. C.W. performed TEM characterization. Y.Zhang., Y.Zhao. and J.G. conducted theoretical calculations. L.S. gave helpful advice on manuscript preparation. P.Z. and J.H. wrote the paper. \n\n# Competing interests \n\nThe authors declare no competing interests. \n\nAdditional information \nSupplementary information The online version contains supplementary material available at \nhttps://doi.org/10.1038/s41467-023-37091- $\\cdot\\mathsf{x}$ . \n\nCorrespondence and requests for materials should be addressed to Junfeng Gao or Jungang Hou. \n\nPeer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. \n\nReprints and permissions information is available at http://www.nature.com/reprints \n\nPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. \n\nOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. \n\n$\\circledcirc$ The Author(s) 2023 " + }, + { + "id": "10.1016_j.bioactmat.2022.06.018", + "DOI": "10.1016/j.bioactmat.2022.06.018", + "DOI Link": "http://dx.doi.org/10.1016/j.bioactmat.2022.06.018", + "Relative Dir Path": "mds/10.1016_j.bioactmat.2022.06.018", + "Article Title": "Wound microenvironment self-adaptive hydrogel with efficient angiogenesis for promoting diabetic wound healing", + "Authors": "Shao, ZJ; Yin, TY; Jiang, JB; He, Y; Xiang, T; Zhou, SB", + "Source Title": "BIOACTIVE MATERIALS", + "Abstract": "Neovascularization is critical to improve the diabetic microenvironment, deliver abundant nutrients to the wound and promote wound closure. However, the excess of oxidative stress impedes the healing process. Herein, a self-adaptive multifunctional hydrogel with self-healing property and injectability is fabricated through a boronic ester-based reaction between the phenylboronic acid groups of the 3-carboxyl-4-fluorophenylboronic acid -grafted quaternized chitosan and the hydroxyl groups of the polyvinyl alcohol, in which pro-angiogenic drug of desferrioxamine (DFO) is loaded in the form of gelatin microspheres (DFO@G). The boronic ester bonds of the hydrogel can self-adaptively react with hyperglycemic and hydrogen peroxide to alleviate oxidative stress and release DFO@G in the early phase of wound healing. A sustained release of DFO is then realized by responding to overexpressed matrix metalloproteinases. In a full-thickness diabetic wound model, the DFO@G loaded hydrogel accelerates angiogenesis by upregulating expression of hypoxia-inducible factor-1 and angiogenic growth factors, resulting in collagen deposition and rapid wound closure. This multifunctional hydrogel can not only self-adaptively change the microenvironment to a pro-healing state by decreasing oxidative stress, but also respond to matrix metalloproteinases to release DFO. The self-adaptive multifunctional hydrogel has a potential for treating diabetic wounds.", + "Times Cited, WoS Core": 296, + "Times Cited, All Databases": 299, + "Publication Year": 2023, + "Research Areas": "Engineering; Materials Science", + "UT (Unique WOS ID)": "WOS:000826897500002", + "Markdown": "# Wound microenvironment self-adaptive hydrogel with efficient angiogenesis for promoting diabetic wound healing \n\nZijian Shao , Tianyu Yin , Jinbo Jiang , Yang He , Tao Xiang , Shaobing Zhou \n\nKey Laboratory of Advanced Technologies of Materials, Ministry of Education, School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu, 610031, PR China \n\n# A R T I C L E I N F O \n\n# A B S T R A C T \n\nKeywords: \nWound microenvironment \nSelf-adaptive hydrogel \nMMP-9 responsive \nAngiogenesis \nDiabetic wound healing \n\nNeovascularization is critical to improve the diabetic microenvironment, deliver abundant nutrients to the wound and promote wound closure. However, the excess of oxidative stress impedes the healing process. Herein, a self-adaptive multifunctional hydrogel with self-healing property and injectability is fabricated through a boronic ester-based reaction between the phenylboronic acid groups of the 3-carboxyl-4-fluorophenylboronic acid -grafted quaternized chitosan and the hydroxyl groups of the polyvinyl alcohol, in which pro-angiogenic drug of desferrioxamine (DFO) is loaded in the form of gelatin microspheres $\\operatorname{\\rhoDFO}(\\varnothing\\mathbf{G})$ . The boronic ester bonds of the hydrogel can self-adaptively react with hyperglycemic and hydrogen peroxide to alleviate oxidative stress and release $\\operatorname{DFO@G}$ in the early phase of wound healing. A sustained release of DFO is then realized by responding to overexpressed matrix metalloproteinases. In a full-thickness diabetic wound model, the $\\mathsf{D F O@G}$ loaded hydrogel accelerates angiogenesis by upregulating expression of hypoxia-inducible factor-1 and angio­ genic growth factors, resulting in collagen deposition and rapid wound closure. This multifunctional hydrogel can not only self-adaptively change the microenvironment to a pro-healing state by decreasing oxidative stress, but also respond to matrix metalloproteinases to release DFO. The self-adaptive multifunctional hydrogel has a potential for treating diabetic wounds. \n\n# 1. Introduction \n\nDiabetes mellitus shows a high prevalence around the world and about $19-34\\%$ of diabetic patients are predicted to develop complica­ tions such as diabetic wounds, which turn into a critical threat to the health and life of the patients [1]. Unlike four overlapping processes of hemostasis, inflammation, proliferation, and re-epithelialization for acute wound healing [2], diabetic wound reveals complicated charac­ teristics that delay the healing process. Large amounts of reactive oxy­ gen species (ROS) from oxidative stress, increased expression of pro-inflammatory cytokines, and bacterial infection impel the wound to become a continuous inflammatory microenvironment [3–6]. Over­ expression of the matrix metalloproteinase-9 (MMP-9) in the diabetic wound microenvironment impairs wound healing by weakening the formation of granulation tissue and inactivating growth factors [7,8], which acts as the primary gelatinase after wounding and participates in extracellular matrix (ECM) degradation and tissue reorganization [8]. In addition, hyperglycemia-induced inadequate vascularization limits the input of nutrients and oxygen to the wound sites, thus delaying wound healing [9,10]. These features impair the growth factors needed for wound healing, forming a negative microenvironment of diabetic wound healing. Materials like hydrogels with microenvironment-responsive ability could achieve a stimuli-responsive drug release on demand and biodegradation affected by the microen­ vironment. Thus, they are applied in several biomedical applications such as tumor therapy [11], brain injury [12], and bone healing [13]. On the other hand, the wound microenvironment is dynamically changed with the repair process, in which pH value, biological cues such as growth factors and cytokines are included. The functions of hydrogel should change with the dynamical microenvironment. Therefore, it’s urgent to develop a multifunctional hydrogel which cannot only accel­ erate wound healing by taking advantage of the microenvironment, but also possess self-adaption to dynamically regulate and respond to the wound microenvironment. \n\nOne of the most efficient ways to directly deliver therapeutics for wound healing is wound dressing therapy. Wound dressings, such as electrospun nanofibers, polyurethane-based film, porous foams and functional hydrogels have been introduced to accelerate the healing process [14–18]. Hydrogels have drawn much attention since they can absorb wound exudate, maintain moisture at the wound sites and possess a suitable modulus that matches the soft tissues [19–21]. During the past years, hydrogels with multiple functions such as ROS-scavenging, antibacterial property, regulation of the immune cells, and promoting angiogenesis have been designed to modulate the microenvironment of the wound [18,22–25]. However, the integrity of the hydrogels is easy to be destroyed when exposed to normal movement and local pressure [26]. The self-healing capacity of the hydrogels has attracted much attention due to their many similarities to the ECM, which can self-heal after minor injuries [27,28]. Furthermore, the injectability can be realized through the self-healing capacity, allowing the hydrogel can smoothly fill the deep or irregular-shaped wound [29]. Consequently, endowing the hydrogel dressings with self-healing capability and injectability is crucial for designing functional wound dressings. \n\nSelf-healing capacity provides hydrogel with the guarantee of inte­ grating its fragments and maintaining functional integrity. Reversible interactions are regarded as an efficient way to induce hydrogel with not only proper mechanical strength but also outstanding self-healing capability, which is coincident with the demand for wound dressings [30,31]. Serval types of covalent and non-covalent interactions including Schiff base, boronic ester bonds hydrogen bonds, ionic bonds, and coordinate bonds have been applied to design self-healing hydrogel dressings [32–36]. Among them, boronic ester bonds possess the char­ acteristics that they can respond to high concentrations of glucose and hydrogen peroxide $\\left(\\mathrm{H}_{2}\\mathrm{O}_{2}\\right)$ , which matches consistently with the microenvironment of diabetic wounds. However, the formation of the diol-boronic acid complex relies on the pKa of the boronic acid, in which most of the boronic acids have pKa values $>8$ . In consequence, the utility in physiologic conditions of these materials is limited. The sub­ stituent of fluorine on benzene can decrease the pKa [37]. To meet the needs of wound dressings for diabetic wounds, 3-carboxyl-4-fluorophe­ nylboronic acid (FPBA) with pKa of ${\\sim}7.2$ can be introduced, in which the phenylboronic acid groups of the FPBA-grafted quaternized chitosan (QCSF) and the hydroxyl groups of the polyvinyl alcohol (PVA) bonded to form hydrogel networks to maintain stability on diabetic wound sites. In addition, the pH of skin tissue is below 7.0 after the wound healing process. The hydrogel can be disassembled to avoid residue on account of the destruction of the diol-boronic acid complex under a lower pKa value. \n\nIn this work, we developed a wound microenvironment self-adaptive multifunctional hydrogel based on boronic ester bonds between the QCSF and PVA, which was named as QCSFP (Fig. 1a). The boronic ester bonds in the hydrogel which contains desferrioxamine loaded gelatin microspheres $(\\mathrm{DFO}@\\mathbf{G})$ could react with the hyperglycemia and over­ expressed ROS to regulate the microenvironment and release $\\mathsf{D F O@G}$ microspheres. The microspheres could respond to the highly expressed MMP-9 to achieve a controlled release of desferrioxamine (DFO). Additionally, released DFO acted as a $\\mathrm{Fe}^{2+}$ chelator to interfere with the required prolyl-hydroxylases cofactor, which was the critical factor in the process of hypoxia inducible factor-1 (HIF-1α) degradation [38]. Simultaneously, the ROS was further suppressed owing to the chelation. Thus, the modification of $\\mathtt{p}300$ by methylglyoxal was reduced, and $\\ensuremath{\\mathbf{p}}^{300}$ could up-regulate the expression of HIF- $\\cdot1\\upalpha$ and its downstream vascular endothelial growth factor (VEGF), thereby facilitating angiogenesis [39]. Through dynamically responding and decreasing oxidative stress of the diabetic wound by self-adaption of DFO@G-QCSFP hydrogel, $\\mathsf{D F O@G}$ and subsequent DFO were released on demand to promote angiogenesis to accelerate the diabetic wound healing (Fig. 1b). \n\n![](images/892986b4222ceac650df4fa2494a50b5f44acbc7ee61799352e5293ae6def854.jpg) \nFig. 1. The fabrication and application of self-adaptive DFO $@$ G-QCSFP for accelerating diabetic wound healing on the full-thickness diabetic wound of a diabetic SD rat. a) The chemical structure of the hydrogel and the mechanism of the hydrogel for accelerating diabetic wound healing. b) The self-adaption of the hydrogel to wound microenvironment. The hydrogel reduced oxidative stress and released $\\operatorname{DFO@G}$ on demand. Then DFO was released and promoted angiogenesis. \n\n# 2. Experimental \n\n# 2.1. Materials \n\nChitosan (CS, $100{-}200~\\mathrm{\\mPa}~\\mathfrak{s}$ , Mw: $2000\\mathrm{kDa}$ , Macklin), 2,3-epoxy­ propyltrimethylammonium chloride (GTMAC, 80 $\\mathbf{wt\\%}$ in water, Huaxia Reagent), FPBA $(98\\%$ , Aladdin), PVA1788 $98\\%$ , Mw:56000, Adamas), gelatin $98\\%$ , Adamas), DFO (Sigma-Aldrich), genipin (Aladdin), streptozotocin (STZ, Sigma-Aldrich), sorbitan monooleate, (Span-80, Aladdin), acetone (AR, Kelong), ethanol (AR, Kelong), $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution $(30\\mathrm{wt\\%}$ , Kelong), sodium chloride (NaCl, $98\\%$ , Kelong), titanyl sulfate $96\\%$ , Aladdin) and methylene blue (MB, $98\\%$ , Kelong), sodium hydroxide solution (NaOH, $98\\%$ , Kelong), hydrogen chloride solution (HCl, $37\\%$ , Kelong), glycine $99\\%$ , Kelong), acetic acid $(99\\%$ , Kelong), ethanol $96\\%$ , Kelong), ninhydrin (AR, Kelong), N-hydroxysuccinimide (NHS, $98\\%$ , Aladdin), N-(3-dimethylaminopropyl)- ${\\bf{\\cdot N^{\\prime}}}$ -ethyl­ carbodiimide hydrochloride (EDC⋅HCl, $98\\%$ , Aladdin), dimethyl sulf­ oxide (DMSO, AR, Kelong), citric acid monohydrate (AR, $99.5\\%$ , Aladdin), tin chloride dihydrate $\\mathrm{(SnCl\\cdot2H_{2}O}$ , $99\\%$ , Aladdin) and ethylene glycol monomethyl ether (ACS, $99.5\\%$ , Sigma-Aldrich) were received. 2,7-dichlorofuor-escin diacetate (DCFH-DA, Beyotime), Hoechest 33342 $97\\%$ , Sigma-Aldrich), dihydroethidium (DHE, SigmaAldrich) were obtained and used for experiments. All other chemicals were analytical reagents. Deionized (DI) water was used throughout the study. \n\n# 2.2. Synthesis of QCSF \n\nQuaternized chitosan (QCS) was synthesized according to a previous literature [40]. Briefly, $5.00~\\mathrm{g}$ CS powders were suspended in $180~\\mathrm{mL}$ deionized water, then $\\mathbf{0.94}\\ \\mathbf{g}$ glacial acetic acid was added. Subse­ quently, $6.40~\\mathrm{g}$ GTMAC was dropped slowly into the solution, then the reaction was stirred for $21\\mathrm{~h~}$ at $55~^{\\circ}\\mathrm{C}$ . After that, the solution was centrifuged ( $6500~\\mathrm{rpm}$ , 8 min). The supernatant was precipitated with pre-cold acetone. The whole purification process was repeated 3 times, and the collected product was dried in a vacuum oven. The chemical structure was characterized by $^1\\mathrm{H}$ nuclear magnetic resonance ( $\\cdot^{1}\\mathrm{H}$ NMR) and Fourier transform infrared spectroscopy (FTIR). \n\nQCSF was synthesized by an amide reaction between the QCS and FPBA. Briefly, the QCS powders were dissolved in $300~\\mathrm{{mL}}$ phosphate buffered saline (PBS) and the pH was adjusted to 5.5. Meanwhile, $1.27\\:\\mathrm{g}$ FPBA, $2.39\\:\\mathrm{g}\\:\\mathrm{NHS}$ and $3.98\\:\\mathrm{g}$ EDC were dissolved in $180~\\mathrm{mL}$ DMSO and the solution was stirred at room temperature for $^{4\\mathrm{h}}$ . Then two solutions were mixed and the reaction was carried out at room temperature for 36 h. The solution was lyophilized after dialysis and the FPBA-grafted quaternized chitosan (QCSF) was obtained. The $^1\\mathrm{H}$ NMR and FTIR of QCSF were performed as well. The grafting ratios of QCS and QCSF were calculated by the peak integral area ratio using equation (1) and equa­ tion (2) following: \n\n$$\n(\\%)\\ {=}\\frac{A H_{b}}{A H_{1}}\\times100\\%\n$$ \n\n$$\nQ C S F~G r a f t i n g~r a t i o~(\\%)~=\\frac{A H_{e1\\sim e3}}{A H_{1}}\\times100\\%\n$$ \n\n# 2.3. Evaluation of pKa of the QCSF \n\nThe pKa value of the QCSF polymer was measured by titration [41]. In each case, $50\\mathrm{mg}$ of QCSF was dispersed in $50~\\mathrm{mL}$ of deionized water, and the pH was adjusted to 3 by 0.1 M HCl solution. Then $0.01\\mathrm{MNaOH}$ was added to the solution to adjust the $\\mathfrak{p H}$ . The value of pKa was determined as the inflection point of the titration curve. \n\n# 2.4. Preparation and characterization of DFO@G \n\n$\\mathsf{D F O@G}$ were prepared through a post-crosslinking strategy by genipin after an emulsification-solvent extraction [42]. Briefly, $_{0.001\\ g}$ DFO and $_{1.50\\ g}$ gelatin powders were dissolved in $10~\\mathrm{mL}$ DI water at $60\\ {}^{\\circ}{\\bf C}.$ . Then the aqueous phase was dropped into $100~\\mathrm{{mL}}$ corn oil con­ taining $1\\ \\mathrm{wt\\%}$ Span-80 and emulsified for $20~\\mathrm{min}$ . The whole mixture was cooled at $7^{\\circ}\\mathrm{C}$ and stirred for $30\\mathrm{min}$ . Subsequently, $150\\mathrm{mL}$ acetone was added to dehydrate for $30\\ \\mathrm{min}$ . Then, the organic solvent was removed by suction filtration and the gelatin microspheres (GMs) were dried in a vacuum oven at room temperature. To prepare $\\operatorname{DFO@G}$ , 50 mg dried GMs were suspended in $4~\\mathrm{mL}$ PBS, in which $1\\%$ w/v genipin solution was added and the crosslinking process was carried out for $^{12\\mathrm{h}}$ . After being washed by ethanol, the $\\mathrm{DFO@G}$ were obtained. The particle sizes of GMs and $\\mathsf{D F O@G}$ were recorded by optical microscope (Carl Zeiss Observer 7, Germany) and manually analyzed by Nano Measurer 1.2 software. \n\n# 2.5. Fabrication and characterization of the injectable hydrogels \n\nThe injectable hydrogel was fabricated by mixing $5\\%$ w/v QCSF solution, $10\\%$ w/v PVA solution and $1\\ \\mathrm{mg}\\ \\mathrm{DFO@G}$ . The obtained hydrogel was defined as DF $\\mathbf{O}@\\mathbf{G}$ -QCSFP. For the control experiments, DFO directly loaded hydrogel and drug-free hydrogel were prepared using the same method, which were defined as DFO-QCSFP and QCSFP, respectively. The FTIR spectra were characterized on a Nicolet 5700 spectrophotometer to determine the chemical structure of the hydrogel. The distinct 3D porous structures of the hydrogels were observed by a Phenom Pro scanning electron microscope (SEM). \n\n# 2.6. Rheological properties of the hydrogels \n\nRheometer (HAAKE RheoStress 5000, Germany) was applied to evaluate the rheological properties of the hydrogels. The experiment temperature was set to $37^{\\circ}\\mathrm{C}$ and the storage modulus $(\\mathbf{G}^{\\prime})$ and loss modulus $(\\mathbf{G}^{\\prime\\prime})$ were investigated by putting the hydrogel on a parallel plate with a $20~\\mathrm{mm}$ diameter and a $1\\mathrm{mm}$ gap. Strain amplitude sweep tests were applied to detect the critical strain point of QCSFP and DFO@G-QCSFP hydrogel with a frequency of 1 rad $s^{-1}$ . Frequency sweep tests were conducted at a $1\\%$ strain amplitude. \n\n# 2.7. Self-healing and injectable properties of the hydrogels \n\nThe self-healing ability of the hydrogel was evaluated by both macroscopic and quantitative experiments. For macroscopic tests, the hydrogel block was cut into two pieces, which were then put together and placed in a humidor at $25~^{\\circ}\\mathrm{C}$ for $^{2\\mathrm{~h~}}$ to observe. In addition, twocolored hydrogel blocks were blended for $^{2\\mathrm{~h~}}$ and stretched by twee­ zers. All the situations of the hydrogels were photographed. Further­ more, quantitative tests of QCSFP and DFO@G-QCSFP hydrogel were investigated by using the rheometer. The experiment was performed by using a time sweep test at $37^{\\circ}\\mathrm{C}$ with a frequency of 1 rad $\\boldsymbol{\\mathsf{s}}^{-1}$ . Strains were switched from small strain $(\\gamma=1\\%$ , $300s$ for each interval) to large strain $(\\gamma=500\\%$ , $100s$ for each interval), and 3 cycles were carried out. QCSFP hydrogel was prepared and loaded into a syringe then injected into a mold to recover their shapes. The injection processes were vid­ eotaped and photographed. To quantitatively analyze the shearthinning properties of hydrogels, the rheometer was applied to detect the viscosity and shear-thinning behaviors of the hydrogel. \n\n# 2.8. Responsive degradation behavior of the hydrogels \n\nSince the boronic ester-based hydrogel was sensitive to stimuli of pH and glucose, the hydrogel was added to the PBS with different pH values (7.8 and 6.0, representing non-healing wound and healed wound, respectively [43]) and $16.6\\mathrm{\\mM}$ glucose to simulate the responsive degradation behavior under diabetic wound environment at $37^{\\circ}\\mathrm{C}$ . The remaining samples were collected, dried and weighed at different in­ tervals, and the remaining hydrogel was calculated by the following equation: \n\n$$\nR e m a n i n g h y d r o g e l\\left(\\%\\right)=\\frac{W_{t}}{W_{0}}\\mathrm{~\\times~}100\\%\n$$ \n\nwhere $W_{\\mathrm{t}}$ and $W_{0}$ are the dry weight of remaining hydrogels after degradation at different time points and the initial dry weight of the hydrogels, respectively. \n\n# 2.9. MMP-9 responsive drug release analysis \n\nIn vitro drug release experiments were conducted to investigate the drug release property of the drug delivery system based on gelatin mi­ crospheres when responding to MMP-9. Briefly, $5\\mathrm{\\mg\\DFO@G}$ was added to prepare hydrogel with drug-loaded microspheres. Then the prepared hydrogel was added to $4\\mathrm{mL}$ of PBS solution containing $100\\mathrm{ng}$ $\\mathrm{mL}^{-1}$ MMP-9 to simulate the microenvironment of diabetic wounds [44, 45]. At predetermined time intervals, $300~\\ensuremath{\\upmu\\mathrm{L}}$ of the supernatant was collected, followed by addition of $7.5\\upmu\\mathrm{LFeCl}_{3}$ solution, then $300~\\ensuremath{\\upmu\\mathrm{L}}$ of fresh PBS buffer with MMP-9 was added to maintain a constant volume. The concentrations of the DFO released from hydrogel were analyzed by UV–vis spectra using a Shimadzu UV-2550 spectrophotometer at 485 nm. Meanwhile, the drug release behavior of the direct drug-loaded hydrogel DFO-QCSFP and the DFO $@$ G-QCSFP hydrogel without MMP-9 were investigated and analyzed. \n\n# 2.10. ROS-scavenging ability evaluation \n\nTitanyl sulfate (0.03 M) was used for evaluating the ROS-scavenging ability of the hydrogel [46]. The standard curve of different concen­ trations of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was established. Then the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution $(1\\ \\mathrm{mM},3\\ \\mathrm{mL})$ ) was incubated with the $200\\upmu\\mathrm{L}/500\\upmu\\mathrm{L}$ hydrogel for different periods. At different time points, the supernatants $(100\\upmu\\mathrm{L})$ were collected and $30\\upmu\\mathrm{L}$ titanyl sulfate was added. Subsequently, the absorbance spectra of the above mixture solutions were measured to determine $\\mathrm{H}_{2}\\mathrm{O}_{2}$ concentra­ tions. The ⋅OH scavenging capacity of the hydrogel was also investi­ gated. Briefly, methylene blue ${\\bf\\left(0.1\\ m g\\ m L^{-1}\\right)}.$ ) was added into a ⋅OH containing solution, which was produced by a Fenton reaction between $\\mathrm{H}_{2}\\mathrm{O}_{2}$ (1 mM) and $\\mathrm{Fe}^{2+}(0.2\\mathrm{mg}\\mathrm{mL}^{-1})$ . Subsequently, the ⋅OH solution was incubated with or without the hydrogel for different time intervals. The supernatant $(100~\\upmu\\mathrm{L})$ was collected and the absorption of the su­ pernatant at $666~\\mathrm{{nm}}$ was recorded. The effect of concentration of DFO on ⋅OH scavenging was also evaluated. \n\n# 2.11. Cytocompatibility of the hydrogel \n\nAlamar Blue (AB) and Live/Dead assays were conducted to evaluate the effect of $\\mathsf{D F O@G}$ and $\\mathrm{DFO@G}$ -QCSFP hydrogels on cell viability and proliferation. Briefly, human umbilical vein endothelial cells (HUVECs) were seeded in a 48-well plate at a density of $1\\times10^{4}$ cells per well. After the HUVECs adhered to the plate for $24\\mathrm{~h~}$ , $500~\\upmu\\mathrm{L}$ of the sample was added into each well to incubate for different time intervals. Finally, cell viabilities were quantified using AB assay and normalized to the control group. Then, Live/Dead staining was performed by using a 12-well plate with a density of $2\\times10^{4}$ cells per well. After cells adhered to the plate for $24\\mathrm{~h~}$ , $500~\\upmu\\mathrm{L}$ hydrogel was added and incubated for different time intervals. After staining with $500~\\upmu\\mathrm{L}$ of calcein-AM/propidium iodide dye for $15\\mathrm{min}$ , cells were observed under a fluorescent microscope (Carl Zeiss Observer 7, Germany) for the green and red fluorescence. \n\n# 2.12. Effective DFO concentration determination \n\nTo determine the effect of DFO concentration on cytocompatibility, DFO with different concentrations was incubated with HUVECs and AB assay was performed to confirm the cell compatibility to HUVECs. The cells were seeded to a 48-well plate at a density of $2\\times10^{4}$ cells per well, then the cells were cultured in DMEM supplemented with $10\\%$ FBS containing different concentrations of DFO (1, 3, 6 and $9\\upmu\\mathrm{M})$ . On day 0, day 1, day 3, and day 5 of culture, $200~\\upmu\\mathrm{L}$ of $10\\%$ AB solution was added into each well and the cells were further cultured for $^{4\\mathrm{~h~}}$ , after the absorbance of each cell was measured at 570 and $600\\ \\mathrm{nm}$ with a UV spectrophotometer. A tube formation assay was conducted to investigate the effect of different concentrations of DFO on angiogenesis. In detail, $40\\upmu\\mathrm{L}$ of Matrigel was added in a 96-well followed by gel under $37^{\\circ}\\mathrm{C}$ for $30~\\mathrm{min}$ . Then $1\\times{10}^{4}$ cells were added onto Matrigel and media con­ taining different concentrations of DFO $(0,1,3,6\\upmu\\mathrm{M})$ were used. After $^{4\\mathrm{~h~}}$ incubation, optical microscopy (Leica DMR HCS, Germany) was employed to observe the tube formation. Nodes and tubes of each group were counted using Image J software. Combined with the results of cell proliferation and tube formation experiments, an effective concentra­ tion of DFO was determined. \n\n# 2.13. Intracellular ROS-scavenging evaluation \n\nThe ROS-scavenging abilities of the hydrogels at cell levels were evaluated using the DCFH-DA probe. In short, HUVECs were seeded on 48-well plates for $^{24\\mathrm{~h~}}$ with followed by treatment with different hydrogels containing $100\\upmu\\mathrm{MH}_{2}\\mathrm{O}_{2}$ while the control group only treated with $100~\\upmu\\mathrm{M}~\\mathrm{H}_{2}\\mathrm{O}_{2}$ . Cells treated with PBS served as negative group. Following treatment for $24\\mathrm{h}$ , cells were rinsed with PBS and stained for $20\\mathrm{min}$ with DCFH-DA and Hoechst. The ROS-scavenging ability of each group was imaged using fluorescence microscopy, and the mean fluo­ rescence intensity was quantified by ImageJ. \n\n# 2.14. In vivo diabetic wound healing assessment \n\nDiabetic rats were induced by a method of intraperitoneal injection of STZ into healthy rats according to a previous literature [47]. After 16 h of fasting subjects, 25 male SD rats were induced by intraperitoneal injection of STZ $(55~\\mathrm{mg}~\\mathrm{kg}^{-1}\\mathrm{\\Omega}.$ ) dissolved in $\\tt p H4.5$ citrate buffer. Then blood glucose was measured every $_{3\\mathrm{~d~}}$ . The rats with blood glucose concentration greater than $16.6~\\mathrm{mM}$ after 4 weeks were determined as diabetic rats. The dorsal hairs of 20 diabetic rats were firstly shaved. Two full-thickness skin wounds with $10\\mathrm{mm}$ diameter were made on the back of each rat. The diabetic rats were randomly divided into 4 groups and treated with: control, QCSFP, DFO-QCSFP, $\\scriptstyle\\mathrm{{DFO@G-QCSP}}$ . The wound sites were treated and observed every three days and photo­ graphed on day 0, 3, 7, 10, 14, and 20 post-wounding. Wound areas in each group were measured and analyzed using the Image J software. The wound contraction rate was calculated by the following equation: \n\n$$\nW o u n d c o n t r a c t i o n\\left(\\%\\right)=\\frac{\\left(S_{0}-S_{n}\\right)}{S_{0}}\\times100\\%\n$$ \n\nwhere $s_{0}$ and $S_{\\mathrm{n}}$ represent the initial wound area and wound area at different time points, respectively. All animal experiments were carried out according to the guidelines approved by the Institutional Animal Care and Use Committee of Southwest Jiaotong University (No. SWJTU2013-008). \n\n# 2.15. In vivo ROS-scavenging ability evaluation \n\nRats were sacrificed and the regenerated skin samples were excised and collected on day 1 and day 3 to evaluate the in vivo ROS-scavenging ability. The in vivo ROS- scavenging was assessed by dihydroethidium (DHE) assay. In short, after washed in PBS, the frozen tissue sections were stained with DHE for $30~\\mathrm{{min}}$ . The in vivo ROS-scavenging ability was imaged using fluorescence microscopy, and analyzed by ImageJ. \n\n# 2.16. Histology and immunohistochemistry \n\nRats were sacrificed and the regenerated skin samples were excised and collected on day 10 and day 20. The skin samples were fixed in $10\\%$ paraformaldehyde, dehydrated in gradient alcohol, and embedded in paraffin. Briefly, $5~{\\upmu\\mathrm{m}}$ sections were prepared for Hematoxylin-eosin (H&E) and Masson trichrome (MT) staining. Image J software was applied to determine the proportion of collagen deposition by measuring the intensity of the blue areas. For immunohistochemical (IHC) evalu­ ation, the skin wound tissues were also excised on day 10 and day 20 post-surgery. To assess the effect of DFO on angiogenesis, the IHC method was used to detect CD31, $\\upalpha$ -smooth actin ( $\\overset{\\cdot}{\\propto}\\overset{}{\\underset{}{\\propto}}$ -SMA), VEGF and HIF-1α. In addition, the IHC staining of MMP-9 and Ki67 was also applied to detect the change of the wound microenvironment. The quantification of IHC was counted by Image-Pro Plus software. \n\n# 2.17. Statistical analyses \n\nAll the experimental data were statistically analyzed and the results were expressed as a mean $\\pm$ standard deviation. One-way ANOVA was used to measure differences for more than two groups with SPSS, version 24 (IBM). Data were considered as statistically significant difference when $\\aleph_{\\mathbf{p}}<0.05$ , $^{**}\\mathbf{p}<0.01$ , $\\ddot{\\substack{\\ast\\ast\\ast}}_{\\mathfrak{p}}<0.001$ and $^{****}\\mathbf{p}<0.0001$ versus the indicated group. \n\n# 3. Results and discussion \n\n# 3.1. Fabrication of the wound microenvironment-responsive hydroge \n\nWound dressings with multifunctional properties are highly desired owing to the complicated wound healing process [3,48]. To optimize the promotion of wound healing through wound dressing, a kind of wound environment self-adaptive multifunctional hydrogel dressing based on boronic ester was prepared (Fig. 2a). CS is known for its abundant biomedical advantages such as a variety of modifications, antimicrobial ability, and hemostatic activity. However, the limited solubility in water impedes its further applications. Compared to CS, QCS could efficiently improve the water solubility, which broadened the applications. PVA possesses a large number of hydroxyl groups, which favored the for­ mation of boronic ester bonds compared to sodium alginate and dextran with a certain content of phenylboronic acid groups. Additionally, both quaternized chitosan and PVA have good biocompatibility [49,50]. As shown in Figure S1, GTMAC was firstly grafted on the side chain of the chitosan to prepare QCS. QCSF was synthesized by grafting FPBA on the QCS chain. The hydrogel was formed by the chemical crosslinking of boronic ester bonds between boric acid groups of QCSF and hydroxyl groups of PVA. The structures of QCS and QCSF were measured and confirmed by $^1\\mathrm{H}$ NMR (Figure S2 and S3), the grafting ratios of QCS and QCSF were $70\\%$ and $20\\%$ , respectively. The pKa of QCSF was measured and the value was 6.78 (Figure S4). $\\mathsf{D F O@G}$ microspheres were then prepared through a post-crosslinking process. The optical microscope image in Fig. 2b confirmed that the $\\mathrm{DFO@G}$ had a good dispersion. In addition, the average size of microsphere was counted and the value was $32.56\\pm1.09\\upmu\\mathrm{m}$ as shown. Compared to GMs in Figure S5a, the average size of $\\mathrm{DFO@G}$ was reduced, which was attributed to the increase in the degree of crosslinking (Figure S6). The encapsulation efficiency and drug loading capacity of the $\\mathsf{D F O@G}$ were evaluated as shown in Table S1. The SEM image in Fig. 2c shows that the $\\scriptstyle\\mathrm{DFO@G-QCSFP}$ had an irregular and porous network structure, and the $\\mathrm{DFO@G}$ were dispersed in the hydrogel. FTIR spectroscopy was also utilized to confirm the chemical structure of CS, QCS, QCSF, and QCSFP hydrogel. As shown in Fig. 2d, the fresh peak at $1480\\mathrm{cm}^{-1}$ of QCS was contributed to the methyl group of GTMAC, indicating the success of quaternization modification [51]. Compared with QCS, new peaks at 1352 and 804 $\\mathsf{c m}^{-1}$ were contributed to B–O stretching vibration and benzene ring, respectively [52]. These peaks revealed that QCSF was successfully synthesized. Besides, the formation of boronic ester bonds could be proved by the two new peaks at $1431~\\mathrm{cm}^{-1}$ and $1734~\\mathrm{cm}^{-1}$ , which indicated that the boronic ester bonds cross-linked hydrogel was suc­ cessfully prepared [53]. \n\n![](images/63bef95aa5eb65ac8129fad679769ce7c461a5964c1b3329a9a49d85f564afd7.jpg) \nFig. 2. Fabrication, responsibility, degradation and ROS scavenging of the multifunctional hydrogel. a) Optical images of the formation of QCSFP hydrogel based on boronic ester bonds. b) Optical microscope image and particle size statistics of the $\\mathrm{DFO@G}$ c) SEM images of the $\\mathrm{DFO@G}$ -QCSFP hydrogel. d) FTIR spectra of the CS, QCS, QCSF, and QCSFP hydrogel. e) Degradation profile of the $\\mathrm{DFO@G}$ -QCSFP hydrogel in simulated diabetic wound microenvironment $(16.6~\\mathrm{mM}$ glucose and 1 mM $\\mathrm{H}_{2}\\mathrm{O}_{2})$ at $37^{\\circ}\\mathrm{C}.$ f) DFO released from DFO $@6$ -QCSFP with addition of MMP-9. g) UV–vis absorbance spectra of the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution incubated with $\\mathrm{DFO@G}$ QCSSFP hydrogel within different time intervals. h) The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ scavenging experiment in solutions incubated without or with the hydrogel. i) UV–vis absorbance spectra of MB degradation with or without the hydrogel triggered by Fenton reaction induced by $\\mathrm{Fe^{2+}}$ and $\\mathrm{{H}}_{2}\\mathrm{{O}}_{2}$ . \n\n# 3.2. Responsive degradation behavior of hydrogel \n\nIn addition to the high glucose of the wound sites, enormous ROS were generated on the wound sites under physical and chemical effects [54]. Because the boronic ester bonds-based hydrogel could respond to the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and glucose of the wound microenvironment [55–57], the responsive degradation behaviors of the hydrogel were investigated. The results in Fig. 2e showed that after being incubated in a glucose environment for $24\\mathrm{h}$ , the remaining weight of dry hydrogel was $35.3\\%$ , which revealed a higher degradation rate than the blank group. The hydrogel degradation was accelerated in the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ environment and the remaining hydrogel was only $3.9\\%$ after incubation for $^{16\\mathrm{~h~}}$ , demon­ strating the ROS-responsive ability of QCSFP hydrogel. When the hydrogel was incubated in the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ and glucose environment, it showed the fastest degradation rate and the hydrogel could be almost cleared within $^{8\\mathrm{~h~}}$ . Since the boronic ester bonds are sensitive to the change of pH, the pH-dependent degradation behavior of the hydrogel was also evaluated at $\\mathrm{pH}6.0$ and 7.8 to stimulate the healed and non-healing wound [43], respectively (Figure S7a). It was found that lower pH accelerated the degradation of the hydrogel. These results demonstrated that the hydrogel could respond to the ROS, glucose, and pH of the wound microenvironment, suggesting the QCSFP hydrogel had excellent wound microenvironment-responsive ability. \n\n# 3.3. MMP-9 responsive drug release analysis \n\nMMP-9, as a primary gelatinase, plays a critical role in ECM reor­ ganization during the wound healing process. In diabetic wounds, MMP9 is always overexpressed in the microenvironment [7,8,58]. To inves­ tigate the MMP-9 responsive release of DFO from the $\\mathsf{D F O@G}$ micro­ spheres, an in vitro experiment was conducted. As shown in Fig. 2f, without the $\\operatorname{DFO@G}$ system, DFO-QCSFP hydrogel revealed a rapid drug release behavior $91\\%$ drug release) after $96\\mathrm{~h~}$ . When adding the $\\mathsf{D F O@G}$ system based on gelatin microspheres, the released drug of DFO@G-QCSFP reduced to $31\\%$ after $96\\mathrm{~h~}$ , which indicated that the $\\mathsf{D F O@G}$ could efficiently slow down the rate of drug release. Further­ more, the releasing rate of DFO $\\wp6$ -QCSFP was much more accelerated 1 $56\\%$ drug release after $96~\\mathrm{h}$ ) when incubated with overexpression of MMP-9 ${\\bf\\Omega}^{(100\\ n g\\ m L^{-1}}$ to simulate the diabetic wounds), suggesting that the $\\scriptstyle\\mathrm{DFO@G-QCSFP}$ could respond to the high expression of MMP-9 in wound sites and achieve controlled drug release. Therefore, the results demonstrated that through the response of $\\operatorname{DFO@G}$ to the overexpressed MMP-9, the DFO $@$ G-QCSFP hydrogel could achieve controlled drug release, which guaranteed the effective time of drug on the wound sites while reducing the drug toxicity under safety control. \n\n# 3.4. ROS scavenging ability evaluation \n\nExtensive production of ROS in diabetic wounds impedes wound healing. The $\\mathrm{H}_{2}\\mathrm{O}_{2}$ scavenging ability of the hydrogel was evaluated and showed in Fig. 2g and S7b. After incubated with the hydrogel, the ab­ sorption intensity of the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ solution was significantly reduced as the incubation time increased. We found that $200~\\ensuremath{\\upmu\\mathrm{L}}$ of the hydrogel could eliminate $55\\%$ of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ within $^{16\\mathrm{~h~}}$ (Fig. 2h). In addition, with increasing the amount of the hydrogel, the removed $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was also increased to $69\\%$ within $16\\mathrm{h}$ . To further investigate the ROS-scavenging ability of the hydrogel on the diabetic wound sites, $\\mathrm{1mMH_{2}O_{2}}$ and 16.6 mM glucose were used to be incubated with the hydrogel. The results showed that nearly $68\\%$ of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ was eliminated after incubated for 16 h, indicating that the hydrogel could efficiently reduce the amount of the $\\mathrm{H}_{2}\\mathrm{O}_{2}$ in a high glucose environment. Meanwhile, the ROS-scavenging ability of the hydrogel against the hydroxyl radical (⋅OH) was also evaluated by using MB as the ⋅OH) indicator. The color of MB solution turned from blue to dark green when ⋅OH was produced by Fenton re­ action, demonstrating the ⋅OH generation (Figure S7c). The absorption intensity of the ⋅OH solution was significantly reduced compared with the MB solution (Fig. 2i). After incubated with the hydrogel, the ab­ sorption intensity increased, suggesting that the hydrogel had an outstanding ⋅OH-scavenging ability. Additionally, DFO was known to improve the interaction between HIF- $\\cdot1\\upalpha$ and coactivator $\\mathtt{p}300$ by scav­ enging hydroxyl radical-generating free iron $\\mathrm{Fe}^{2+}$ [38], thus the ⋅OH-scavenging experiment of DFO was conducted (Figure S7d). As shown, with the increase of DFO concentration, the ⋅OH-scavenging ability was enhanced. All the above results demonstrated that effective ROS-scavenging activity could probably enable the hydrogel to reduce the ROS level in the wound sites. The responsive degradation, controlled drug release, and ROS-scavenging capacity of the hydrogel suggested a remarkable self-adaption behavior when applied in the diabetic wound microenvironment. \n\n# 3.5. Rheological behavior, self-healing and injectable properties of hydrogel \n\nDynamic bonds crosslinked hydrogels usually showed promising properties that matched the elastic modulus of biological tissues [59]. In rheological analysis, gel point, which represented the critical state be­ tween solid and liquid, was defined as the cross point of storage modulus $(\\mathbf{G}^{\\prime})$ and loss modulus $(\\mathbf{G}^{\\prime\\prime})$ . Dynamic frequency-sweep tests were carried out to prove the hydrogel formation of QCSFP and DFO $@$ G-QCSFFP (Fig. 3a and d). From low frequency to high frequency, $\\ensuremath{\\mathbf{G}}^{\\prime}$ was greater than $\\mathbf{G}^{\\prime\\prime}$ for all samples, indicating a gel-like character. Furthermore, strain-dependent oscillatory measurements were applied to determine the critical strains for disrupting the gel network of QCSFP and DFO@G-QCSFP, found here to be $270.6\\%$ and $435.1\\%$ , respectively (Figure S8a and S8b). Hydrogel with self-healing ability could greatly maintain stability when subjected to external mechanical forces. The self-healing properties of QCSFP and $\\mathsf{D F O@G}$ -QCSFP were quantita­ tively examined by using step-strain measurements (Fig. 3b and e). Based on the critical points, $500\\%$ was chosen as large strain while small strains were fixed at $1\\%$ . For both samples, $\\ensuremath{\\mathbf{G}}^{\\prime}$ was greater than $\\mathbf{G}^{\\prime\\prime}$ when under small strain. As the strain was switched to $500\\%$ , $\\mathbf{G}^{\\prime\\prime}$ was higher than $\\ensuremath{\\mathbf{G}}^{\\prime}$ , indicating the collapse of the hydrogel. When small strain processed again, $\\ensuremath{\\mathbf{G}}^{\\prime}$ and $\\mathbf{G}^{\\prime\\prime}$ recovered, revealing the network of hydrogel restored. In addition, the moduli had no noticeable change during three cycles, demonstrating the repeatable mechanical self-healing property of QCSFP and DFO $@6$ -QCSFP hydrogels. The effect of high shear rate on gel viscosity was measured to evaluate the injectability of the QCSFP and DFO@G-QCSFP (Fig. 3c and f). As expected, for both samples, the viscosity decreased with the increase of shear rate, demonstrating that the shear disrupted the dynamic cross-links in the gel network. Addi­ tionally, the injectable ability was visualized by injecting the hydrogel through a needle (Fig. 3c inset). \n\n![](images/fb43ba9902e8e452aa095c8bffb13dd3abb3a16fd9c970f2461ad302e4315b56.jpg) \nFig. 3. Self-healing and injectable properties of the QCSFP and DFO@G-QCSFP hydrogels. a) Dynamic frequency-sweep measurements of the QCSFP hydrogel. b) Step-strain measurements to confirm self-healing capacity of the QCSFP hydrogel. c) Shear-thinning behavior of the QCSFP hydrogel. d) Dynamic frequency-sweep measurements of the d DFO@G-QCSFP hydrogel. e) Step-strain measurements to confirm self-healing capacity of the DFO@G-QCSFP hydrogel. f) Shear-thinning behavior of the DFO@G-QCSFP hydrogel. g) Optical images of the injection and healing processes. h) Reinjection of DFO $@6$ -QCSFP into different shapes. i) Op­ tical images of the self-healing process of two individual hydrogel blocks, in which the left block was stained with MB. \n\nThe self-healing and injectable capacities of the samples were also macroscopically evaluated. The QCSFP hydrogel was injected into a heart shape by a syringe and a crack was cut in the middle, then the two pieces of hydrogel were patched (Fig. 3g). The cracked hydrogel could recombine into a heart shape in $10~\\mathrm{{min}}$ without any stimuli. Further­ more, the QCSFP and DFO $@$ G-QCSFP hydrogel could be repeatably injected into different shapes (Fig. 3g and h). Moreover, two indepen­ dent hydrogel blocks were contacted and then stretched to visually investigate the self-healing properties (Fig. 3i). After being recombined for $^{2\\mathrm{~h~}}$ , the blocks became an integrated one and could maintain an integrated shape under stretching, indicating excellent self-healing ability of the hydrogels. \n\n# 3.6. Cytocompatibility of the hydrogel \n\nThe cytotoxicity of the $\\scriptstyle{\\mathrm{DFO@G}}$ and DFO $@$ G-QCSFP hydrogel was assessed by AB assay and Live/Dead staining. After incubated with HUVECs for 1, 3 and $^\\textrm{\\scriptsize5d}$ at $37^{\\circ}\\mathrm{C}$ , both two samples revealed no sig­ nificant cytotoxicity and the cell viability was higher than $85\\%$ after 5 d incubation (Fig. 4a). In addition, the cell cytotoxicity was visually observed by the Live/Dead staining, in which the green and red fluo­ rescence represented the live and dead cells, respectively (Fig. 4b). For all the samples, the majority of HUVECs showed normal morphology. It was observed that $\\mathsf{D F O@G}$ and DFO@G-QCSFP groups revealed no difference in cell density from the control group. Hence, it could be concluded that the hydrogel possessed good cytocompatibility and could be used as a dressing for in vivo wound healing. \n\n![](images/fdace989e53906affc655859dc3534d0d2952f7cea7119caa110a0c81abff388.jpg) \nFig. 4. Cell viability of HUVEC cells and tube formation to assess the in vitro angiogenesis capacity. a) Cell viability of HUVEC cells treated with $\\operatorname{DFO@G}$ and $\\mathrm{DFO@G}$ -QCSFP hydrogel for 1, 3, 5 d. b) Live/Dead staining of HUVEC cells after being treated with hydrogels for different time intervals. c) Cell viability after being treated with different concentrations of DFO. d) Optical images of tube formation by HUVEC cells treated with different concentrations of DFO, and quantification through counting the number of (e) nodes ${\\mathrm{(n=4}}{\\dot{\\mathrm{)}}}$ ) and (f) meshes $(\\boldsymbol{\\mathrm{n}}=4)_{\\circ}$ in each group. g) The alleviation of oxidative stress in HUVECs was monitored via a DCFHDA after different treatment. h) The quantitative studies of ROS decreasing intracellularly were analyzed by quantify the fluorescent intensity. \n\n# 3.7. Effect of DFO concentration on tube formation and cytocompatibility \n\nThe concentration of DFO has an impact on cell proliferation. Thus, AB assay was performed on 1, 3, 6, and $9~{\\upmu\\mathrm{M}}$ DFO to investigate the relationship between DFO concentration and cytocompatibility (Fig. 4c). It could be noticed that with the increase of the DFO concen­ tration, the cell viability first raised then decreased. Compared with the groups with lower concentrations, DFO with $6~{\\upmu\\mathrm{M}}$ and above concen­ tration showed obvious cytotoxicity on HUVECs. In particular, DFO with $3~{\\upmu\\mathrm{M}}$ presented the effect of promoting cell proliferation with cell viability of $109\\%$ after incubated for $^{5\\mathrm{d}}$ while ${\\mathfrak{s}}\\upmu\\mathbf{M}$ of DFO revealed a cell viability of $86.1\\%$ . Moreover, DFO is proved to promote angiogen­ esis. To determine an effective concentration of DFO for promoting blood vessel formation, a tube formation assay was conducted. As shown in Fig. 4d, the angiogenesis capacity was significantly enhanced by adding DFO with concentrations of 1, 3, and $6~{\\upmu\\mathrm{M}}$ compared to the control group, as $9~{\\upmu\\mathrm{M}}$ showed a decreased cytotoxicity, it was not chosen for the tube formation assay. In addition, the concentration of 3 $\\upmu\\mathrm{M}$ presented the higher stimulatory effects on tube formation, which showed 40 tubes and 20 nodes. The results demonstrated that DFO with a concentration of $3\\upmu\\mathrm{M}$ possessed significant enhancement on both cell proliferation and tube formation. \n\n# 3.8. Intracellular ROS-scavenging evaluation \n\nTo certificate the ability of DFO $@$ G-QCSFP to decrease ROS level, the ROS-scavenging evaluation was conducted using the DCFH-DA probe. As shown in Fig. $_{4g}$ and h, the intracellular ROS levels in hydrogel incubated groups were significantly decreased contrasted to the control group, in which cells presented prominent green fluorescence. The reason that three hydrogel groups presented similar ROS-scavenging abilities mainly due to the consistent content of phenylboronic acid groups in the hydrogel components, which were contributed to the ROSscavenging. In summary, these results confirmed that the $\\mathrm{DFO@G}.$ QCSFP hydrogel was sufficient to scavenge ROS thus alleviate the oxidative stress. \n\n# 3.9. In vivo diabetic wound healing assessment \n\nAs a non-healing wound, a diabetic wound requires specific medical treatment owing to its complicated microenvironment [60]. The designed DFO@G-QCSFP hydrogel possessed the desired properties as a self-adaptive wound dressing for diabetic wounds. The treatment effi­ ciency of DFO $@$ G-QCSFP hydrogel was evaluated on a full-thickness diabetic wound model, which was established on SD rats through intraperitoneal injection of STZ. The details of the treatment were summarized in Fig. 5a. After the wounds with a diameter of $10\\mathrm{mm}$ were formed, QCSFP, DFO-QCSFP, and DFO@G-QCSFP hydrogels were applied on the wound sites while the untreated wound was used as a control group. At specific time intervals, images of the wounds treated with different groups were shown in Fig. 5b. The treatment efficiency of DFO $@$ G-QCSFP was much higher than other groups after $10\\mathrm{d}$ observa­ tion. In addition, the wound healing traces were drawn based on the representative photos to show the treatment efficiency macroscopically. As shown in Fig. 5c and d, the wound area of each group was evaluated after $10\\mathrm{d}$ of treatment. In the control group, the wound area remained as high as $38.1\\%$ , which was only remained $5.1\\%$ for the DFO@G-QCSFP group. Furthermore, the wound contraction during $20{\\mathrm{~d~}}$ of treatment was monitored. As shown in Fig. 5e and Figure S9, it was observed that on the 14th day the wound contraction was $99.7\\%$ of the DFO@G-QCSFP group, which was superior to the QCSFP, DFO-QCSFP, and control group. These results indicated the DFO $@$ G-QCSFP had faster healing rates than other groups. The mechanism of wound healing was then investigated by histological analysis in the next section. \n\n# 3.10. Histological analysis \n\nH&E and MT staining were conducted on the regenerated skin tissues to evaluate the healing effect from a histological perspective. As shown in Fig. 5f and h, the H&E stained sections revealed an inflammatory response and inflammatory cells were observed on the edge of the wound. After treatment with hydrogel dressings, the thickness of the epidermal layer of the wound sites was thicker than the control group (Fig. 5g). Among them, DFO $@$ G-QCSFP showed the highest thickness at $101~{\\upmu\\mathrm{m}}$ , indicating a significant enhancement of epidermal layer for­ mation of the hydrogel was conducive to wound healing. The deposition of collagen was detected on the regenerated skin tissues which were collected on day 10 by MT staining. It was observed that all the hydrogel groups exhibited higher collagen deposition than the control group (Fig. 5i). In addition, DFO@G-QCSFP presented the densest collagen deposition at $55\\%$ , which was 1.71-fold higher than that of the control group. Compared to the DFO-QCSFP group, it also revealed significant acceleration on epithelization and collagen deposition, which demon­ strated that the DFO $@$ G-QCSFP hydrogel could accelerate the diabetic wound healing through the promotion of collagen deposition. \n\n![](images/fedb4f151eb840d8033612f7e9134e4bfc90865e60cc3e4aef890c4b9a50b53b.jpg) \nFig. 5. In vivo diabetic wound healing assessment of multifunctional hydrogels. a) Treatment schedule of diabetic wounds treated by different hydrogel formulations. b) Representative images of the diabetic wounds at different times. c) Wound traces of the healing process. d) Quantification of relative wound area on day 10 after treatment. e) Quantification of wound contraction during the healing process. f) H&E staining of wound sections in all groups on day 10. g) Epidermis thickness on day 10. h) MT images of wounds on day 10. i) Collagen accumulation on day 10 based on MT staining. $\\mathrm{\\ddot{\\varepsilon}_{p}}<0.05$ , $\\ddot{\\mathbf{\\rho}}\\ddot{}\\ast\\mathbf{\\rho}_{\\mathbf{p}}<0.01$ , $^{***}\\mathbf{p}<0.001$ . \n\nBesides collagen deposition, angiogenesis is also crucial for diabetic wound healing since the growth of the newly-formed granulation tissue was very dependent on the nutrition, which was provided by the blood vessels [61]. To visually examine the angiogenesis effect of hydrogels, IHC staining of HIF- $.1\\upalpha$ and VEGF was performed. As shown in Fig. 6a and c, the staining of HIF-1α and VEGF was the deepest in the DFO $@$ G-QCSFP group, demonstrating this group had the highest ex­ pressions of HIF-1α and VEGF than other groups. IHC evaluation sta­ tistical analysis of HIF-1α and VEGF was also performed to confirm the angiogenesis effect. The results in Fig. 6b and d revealed that the expression of HIF-1α and VEGF was increased after adding DFO in the wound sites. In addition, the controlled release system of DFO@G-QCSFP could significantly enhance the expressions, with the IHC scores of DFO@G-QCSFP 3.81-folder (HIF-1α) and 2.88-folder (VEGF) than the control group on day 10. The intensity of staining was similar across the hydrogel groups without significant difference on day 20. Because the healing process was almost completed while the control group showed increased expression on day 20. The reason was probably due to that the wound treated by $\\mathrm{DFO@G}$ -QCSFP returned to a regular state in day 20 so the expression of $\\upalpha$ -SMA and CD31 was on a normal level. In the meantime, the control group was still in the healing process in day 20, which presented a high expression of $\\upalpha$ -SMA and CD31, which showed a similar tendency with previous literature [47]. \n\nCD31 is a transmembrane protein expressed in early angiogenesis, thus its expression could be evaluated to illustrate the newly formed blood vessels. IHC staining of $\\upalpha$ -SMA and CD31 was conducted as shown in Fig. 6e and h. It was observed that DFO $@$ G-QCSFP had the highest expressions of $\\upalpha$ -SMA (Fig. 6f), consistent with the results of HIF-1α and VEGF staining. Furthermore, as shown in Fig. 6h, the newly formed blood vessels were counted from the CD31 staining and the results showed the DFO@G-QCSFP had the highest number of blood vessels at 71 vessels $\\mathrm{mm}^{-2}$ on day 10, which was 2.65-folder than the control group. The results indicated that the DFO@G-QCSFP exhibited excellent pro-vascularization capability. \n\nThe in vivo ROS-scavenging ability of DFO $@$ G-QCSFP was con­ ducted as well. As shown in Figure S10, it could be observed that all the hydrogel treated groups presented a good ROS-scavenging ability compared to the control group in day 1. No significant difference between the three hydrogel groups was owing to the same amount of boronate ester bonds, which contributed the most to ROS-scavenging. Followed 3 days of treatment, DFO@G-QCSFP revealed a significant elimination of ROS than other groups mainly because of the sustained release of DFO helped to reduce the ROS level by chelation with $\\mathrm{Fe}^{2+}$ . The results demonstrated that the DFO $@$ G-QCSFP could efficiently accelerate wound healing by reducing ROS levels in diabetic wounds. The in vivo degradation of the hydrogel was conducted and the result was shown in Figure S11. After applying in the wound, the hydrogel revealed a fast degradation behavior. The remaining hydrogel after $24\\mathrm{h}$ was $34.78\\%$ and decreased to $9.5\\%$ after $36\\mathrm{~h~}$ . \n\n![](images/54aaa4b421604fb9a6f87f2beb564a5e84b0ea0bf70c0062daeaaaedeba9d080.jpg) \nFig. 6. IHC staining and quantification of a), b) HIF-1α, c), d) VEGF, e), f) α-SMA and g) CD31, h) Quantification of blood vessels from CD31 staining. $\\therefore p<0.05$ , ${}^{\\ast\\ast}\\mathbf{p}$ $<0.01$ , $\\ddot{\\substack{\\ast\\ast\\ast}}_{\\mathfrak{p}}<0.001$ . \n\nMoreover, the self-adaptive hydrogel dressings were supposed to change the microenvironment to a pro-healing state by eliminating ROS and promoting angiogenesis. Therefore, IHC staining of MMP-9 and Ki67 was detected to investigate the microenvironment of the wounds treated by different groups. The results revealed that the control group had the highest expression of MMP-9, which was consistent with the pathological characteristics of diabetic wounds (Figure S12a). After being treated with QCSFP, DFO-QCSFP and DFO@G-QCSFP, the ex­ pressions were decreased. IHC evaluation statistical analysis results demonstrated that after treatment, DFO@G-QCSFP showed the most apparent effect on reducing the expression of MMP-9, which was 1.86- folder less than the control group at day 10 (Figure S12b). IHC stain­ ing and evaluation statistical analysis of Ki67 was also detected to confirm the change of the microenvironment after treatment (Figure S12c and S12d). It could be observed that DFO@G-QCSFP showed the highest expression of Ki67, indicating its ability to pro­ mote cell proliferation. These results demonstrated that after being treated with DFO $@$ G-QCSFP hydrogel, the microenvironment of the wound could be changed to a pro-healing state by regulating the ROS level, promoting collagen deposition and cell proliferation, improving vascularization and decreasing the expression of MMP-9. \n\n# 4. Conclusion \n\nIn summary, a microenvironment self-adaptive hydrogel based on boronic ester bonds was constructed to accelerate diabetic wound healing by dynamically regulating the microenvironment through ROS scavenging and on-demand DFO release to promote angiogenesis. Owing to the dynamic nature of the boronic ester bonds, the hydrogel revealed excellent self-healing capability, injectability as well as the wound microenvironment perception self-adaptive ability. As well, the hydrogel could eliminate $68\\%$ of $\\mathrm{H}_{2}\\mathrm{O}_{2}$ , revealing good ROS-scavenging ability. Meanwhile, the $\\scriptstyle{\\mathrm{DFO@G}}$ released from the hydrogel could respond to the overexpressed MMP-9, achieving an on-demand release of DFO. A full-thickness diabetic wound exhibited a reduced wound area of only $5.1\\%$ after 10 days’ treatment with this hydrogel. Furthermore, the hydrogel reshaped the microenvironment to a pro-healing state to accelerate wound healing. As a wound microenvironment self-adaptive multifunctional wound dressing, this hydrogel possesses a potential for the treatment of diabetic wounds and skin tissue regeneration. \n\n# Ethics approval and consent to participate \n\nThe authors declare that all animal experiments are carried out ac­ cording to the guidelines approved by the Institutional Animal Care and Use Committee of Southwest Jiaotong University (No. SWJTU-2013- 008). All authors comply with all relevant ethical regulations. \n\n# CRediT authorship contribution statement \n\nZijian Shao: Conceptualization, Methodology, Software, Data curation, Investigation, Writing – original draft. Tianyu Yin: Data curation, Investigation, Writing – original draft. Jinbo Jiang: Visuali­ zation, Investigation. Yang He: Visualization, Investigation. Tao Xiang: Data curation, Investigation, Writing – original draft, Funding acquisition, Writing – review & editing. Shaobing Zhou: Funding acquisition, Writing – review & editing. \n\n# Declaration of competing interest \n\nThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. \n\n# Acknowledgements \n\nThis work was supported by the National Natural Science Foundation of China (Nos. 52103186, 51725303 and 52033007), the Fundamental Research Funds for the Central Universities (Nos. 2682020ZT84 and 2682021ZTPY008). The authors also thank the Analytical and Testing Center of Southwest Jiaotong University. \n\n# Appendix A. Supplementary data \n\nSupplementary data to this article can be found online at https://doi. org/10.1016/j.bioactmat.2022.06.018. \n\n# References \n\n[1] H. Wang, Z. Xu, M. Zhao, G. Liu, J. Wu, Advances of hydrogel dressings in diabetic wounds, Biomater. Sci. 9 (5) (2021) 1530–1546, https://doi.org/10.1039/ D0BM01747G. \n[2] G.C. Gurtner, S. Werner, Y. Barrandon, M.T. Longaker, Wound repair and regeneration, Nature 453 (7193) (2008) 314–321, https://doi.org/10.1038/ nature07039. \n[3] V. Falanga, Wound healing and its impairment in the diabetic foot, Lancet 366 (9498) (2005) 1736–1743, https://doi.org/10.1016/S0140-6736(05)67700-8. \n[4] C. Tong, X. Zhong, Y. Yang, X. Liu, G. Zhong, C. Xiao, B. Liu, W. Wang, X. Yang, Pb@pda@ag nanosystem for synergistically eradicating mrsa and accelerating diabetic wound healing assisted with laser irradiation, Biomaterials 243 (2020), 119936, https://doi.org s.2020.119936. \n[5] W.-C. Huang, R. Ying, He, X. Mo, C. Xue, X. Mao, A macroporous hydrog d antibacterial and antiinflammatory cap healing, Adv. Funct. Mater. 30 (21) (2020), 2000644, .202000644. \n[6] L. Wang, X. Zhang, D. Zhang, L.-N. Wang, C.-S. Lee, A novel double-cr r injectable hydrogels with enhanced tissue adhesi ility for wound treatment, Adv. Funct. Mater. 30 (1) (2020) .org/10.1002/adfm.201904156. \n[7] J. Liu, Z. Chen, J. Wang, R. Li, hang, F. Yan, Y. Wang, Encapsulation of curcumin nanoparticles with mmp9-responsive and thermos-sensitive hydrogel improves diabetic wound healing, ACS Appl. Mater. Interfaces 10 (19) (2018) 16315–16326, https://doi.org/10.1021/acsami.8b03868. \n[8] S.A. Castleberry, B.D. Almquist, W. Li, T. Reis, J. Chow, S. Mayner, P.T. Hammond, Self-assembled wound dressings silence mmp-9 and improve diabetic wound healing in vivo, Adv. Mater. 28 (9) (2016) 1809–1817, https://doi.org/10.1002/ adma.201503565. \n[9] Z. Tu, M. Chen, M. Wang, Z. Shao, X. Jiang, K. Wang, Z. Yao, S. Yang, X. Zhang, W. Gao, C. Lin, B. Lei, C. Mao, Engineering bioactive M2 macrophage-polarized anti-inflammatory, antioxidant, and antibacterial scaffolds for rapid angiogenesis and diabetic wound repair, Adv. Funct. Mater. 31 (2021), 2100924, https://doi. org/10.1002/adfm.202100924. \n[10] X. Zheng, S. Narayanan, V.G. Sunkari, S. Eliasson, I.R. Botusan, J. Grunler, A. I. Catrina, F. Radtke, C. Xu, A. Zhao, N.R. Ekberg, U. Lendahl, S.-B. Catrina, Triggering of a dll4-notch1 loop impairs wound healing in diabetes, Proc. Natl. Acad. Sci. USA 116 (14) (2019) 6985–6994, https://doi.org/10.1073/ pnas.1900351116. \n[11] M. Wang, M. Chen, W. Niu, D.D. Winston, W. Cheng, B. Lei, Injectable biodegradation-visual self-healing citrate hydrogel with high tissue penetration for microenvironment-responsive degradation and local tumor therapy, Biomaterials 261 (2020), 120301, https://doi.org/10.1016/j.biomaterials.2020.120301. \n[12] F. Qian, Y. Han, Z. Han, D. Zhang, L. Zhang, G. Zhao, S. Li, G. Jin, R. Yu, H. Liu, In situ implantable, post-trauma microenvironment-responsive, ros depletion hydrogels for the treatment of traumatic brain injury, Biomaterials 270 (2021), 120675, https://doi.org/10.1016/j.biomaterials.2021.120675. \n[13] S. Xue, X. Li, S. Li, N. Chen, Q. Zhan, L. Long, J. Zhao, X. Hou, X. Yuan, Bone fracture microenvironment responsive hydrogel for timing sequential release of cargoes, Colloids Surf., A 629 (2021), 127413, https://doi.org/10.1016/j. colsurfa.2021.127413. \n[14] B. Yu, C. He, W. Wang, Y. Ren, J. Yang, S. Guo, Y. Zheng, X. Shi, Asymmetric wettable composite wound dressing prepared by electrospinning with bioinspired micropatterning enhances diabetic wound healing, ACS Appl. Bio Mater. 3 (8) (2020) 5383–5394, https://doi.org/10.1021/acsabm.0c00695. \n[15] M. Li, J. Chen, M. Shi, H. Zhang, P.X. Ma, B. Guo, Electroactive anti-oxidant polyurethane elastomers with shape memory property as non-adherent wound dressing to enhance wound healing, Chem. Eng. J. 375 (2019), 121999, https:// doi.org/10.1016/j.cej.2019.121999. \n[16] F.V. Ferreira, C.G. Otoni, K.J. De France, H.S. Barud, L.M.F. Lona, E.D. Cranston, O. J. Rojas, Porous nanocellulose gels and foams: breakthrough status in the development of scaffolds for tissue engineering, Mater, Today Off. 37 (2020) 126–141, https://doi.org/10.1016/j.mattod.2020.03.003. \n[17] X. Ding, G. Li, P. Zhang, E. Jin, C. Xiao, X. Chen, Injectable self-healing hydrogel wound dressing with cysteine-specific on-demand dissolution property based on tandem dynamic covalent bonds, Adv. Funct. Mater. 31 (19) (2021), https://doi. rg/10.1002/adfm.202011230, 2011230. \n[18] X. Zhao, Y. Liang, Y. Huang, J. He, Y. Han, B. Guo, Physical double-network hydrogel adhesives with rapid shape adaptability, fast self-healing, antioxidant and NIR/pH stimulus-responsiveness for multidrug-resistant bacterial infection and removable wound dressing, Adv. Funct. Mater. 30 (17) (2020), 1910748, https:// oi.org/10.1002/adfm.201910748. \n[19] M.A.M. Jahromi, P.S. Zangabad, S.M.M. Basri, K.S. Zangabad, A. Ghamarypour, A. R. Aref, M. Karimi, M.R. Hamblin, Nanomedicine and advanced technologies for burns: preventing infection and facilitating wound healing, Adv. Drug Deliv. Rev. 123 (2018) 33–64, https://doi.org/10.1016/j.addr.2017.08.001. \n[20] X. Chen, Making electrodes stretchable, Small Methods 1 (4) (2017), 1600029, https://doi.org/10.1002/smtd.201600029. \n[21] J. Li, F. Yu, G. Chen, J. Liu, X.-L. Li, B. Cheng, X.-M. Mo, C. Chen, J.-F. Pan, Moistretaining, self-recoverable, bioadhesive, and transparent in situ forming hydrogels to accelerate wound healing, ACS Appl. Mater. Interfaces 12 (2) (2020) 2023–2038, https://doi.org/10.1021/acsami.9b17180. \n[22] H. Chen, R. Cheng, X. Zhao, Y. Zhang, A. Tam, Y. Yan, H. Shen, Y.S. Zhang, J. Qi, Y. Feng, L. Liu, G. Pan, W. Cui, L. Deng, An injectable self-healing coordinative hydrogel with antibacterial and angiogenic properties for diabetic skin wound repair, NPG Asia Mater. 11 (2019) 3, https://doi.org/10.1038/s41427-018-0103- \n[23] T. Chen, Y. Chen, H.U. Rehman, Z. Chen, Z. Yang, M. Wang, H. Li, H. Liu, Ultratough, self-healing, and tissue-adhesive hydrogel for wound dressing, ACS Appl. Mater. Interfaces 10 (39) (2018) 33523–33531, https://doi.org/10.1021/ acsami.8b10064. \n[24] H. Zhao, J. Huang, Y. Li, X. Lv, H. Zhou, H. Wang, Y. Xu, C. Wang, J. Wang, Z. Liu, ROS-scavenging hydrogel to promote healing of bacteria infected diabetic wounds, Biomaterials 258 (2020), 120286, https://doi.org/10.1016/j. biomaterials.2020.120286. \n[25] S.-W. Kim, G.-B. Im, G.-J. Jeong, S. Baik, J. Hyun, Y.-J. Kim, C. Pang, Y.C. Jang, S. H. Bhang, Delivery of a spheroids-incorporated human dermal fibroblast sheet increases angiogenesis and M2 polarization for wound healing, Biomaterials 275 (2021) 120954, https://doi.org/10.1016/j.biomaterials.2021.120954. \n[26] L. Li, B. Yan, J. Yang, L. Chen, H. Zeng, Novel mussel-inspired injectable selfhealing hydrogel with anti-biofouling property, Adv. Mater. 27 (7) (2015) 1294–1299, https://doi.org/10.1002/adma.201405166. \n[27] Q. Feng, K. Zhang, R. Li, L. Bian, Injectable hydrogels for regenerative medicine, Acta Polym. Sin. 52 (1) (2021) 1–15, https://doi.org/10.1007/s13770-018-0161- \n[28] Y. Tu, N. Chen, C. Li, H. Liu, R. Zhu, S. Chen, Q. Xiao, J. Liu, S. Ramakrishna, L. He, Advances in injectable self-healing biomedical hydrogels, Acta Biomater. 90 (2019) 1–20, https://doi.org/10.1016/j.actbio.2019.03.057. \n[29] R. Dimatteo, N.J. Darling, T. Segura, In situ forming injectable hydrogels for drug delivery and wound repair, Adv. Drug Deliv. Rev. 127 (2018) 167–184, https:// doi.org/10.1016/j.addr.2018.03.007. \n[30] R. Du, Z. Xu, C. Zhu, Y. Jiang, H. Yan, H.-C. Wu, O. Vardoulis, Y. Cai, X. Zhu, Z. Bao, Q. Zhang, X. Jia, A highly stretchable and self-healing supramolecular elastomer based on sliding crosslinks and hydrogen bonds, Adv. Funct. Mater. 30 (7) (2020), 1907139, https://doi.org/10.1002/adfm.201907139. \n[31] S. Li, L. Wang, W. Zheng, G. Yang, X. Jiang, Rapid fabrication of self-healing, conductive, and injectable gel as dressings for healing wounds in stretchable parts of the body, Adv. Funct. Mater. 30 (31) (2020), 2002370, https://doi.org/ 10.1002/adfm.202002370. \n[32] C. Hou, W. He, Z. Wang, B. Yi, Z. Hu, W. Wang, X. Deng, X. Yao, Particulateaggregated adhesives with exudate-sensitive properties and sustained bacteria disinfection to facilitate wound healing, ACS Appl. Mater. Interfaces 12 (28) (2020) 31090–31098, https://doi.org/10.1021/acsami.0c04920. \n[33] H. Mndlovu, L.C. du Toit, P. Kumar, T. Marimuthu, P.P.D. Kondiah, Y.E. Choonara, V. Pillay, Development of a fluid-absorptive alginate-chitosan bioplatform for potential application as a wound dressing, Carbohydr. Polym. 222 (2019), 114988, https://doi.org/10.1016/j.carbpol.2019.114988. \n[34] S. Li, N. Chen, X. Li, Y. Li, Z. Xie, Z. Ma, J. Zhao, X. Hou, X. Yuan, Bioinspired double-dynamic-bond crosslinked bioadhesive enables post-wound closure care, Adv. Funct. Mater. 30 (17) (2020), 2000130, https://doi.org/10.1002/ adfm.202000130. \n[35] M. Wang, C. Wang, M. Chen, Y. Xi, W. Cheng, C. Mao, T. Xu, X. Zhang, C. Lin, W. Gao, Y. Guo, B. Lei, Efficient angiogenesis-based diabetic wound healing/skin reconstruction through bioactive antibacterial adhesive ultraviolet shielding nanodressing with exosome release, ACS Nano 13 (9) (2019) 10279–10293, https://doi.org/10.1021/acsnano.9b03656. \n[36] X. Zhao, D. Pei, Y. Yang, K. Xu, J. Yu, Y. Zhang, Q. Zhang, G. He, Y. Zhang, A. Li, Y. Cheng, X. Chen, Green tea derivative driven smart hydrogels with desired functions for chronic diabetic wound treatment, Adv. Funct. Mater. 31 (2021), 2009442, https://doi.org/10.1002/adfm.202009442. \n[37] V. Yesilyurt, M.J. Webber, E.A. Appel, C. Godwin, R. Langer, D.G. Anderson, Injectable self-healing glucose-responsive hydrogels with ph-regulated mechanical properties, Adv. Mater. 28 (1) (2016) 86–91, https://doi.org/10.1002/ ma.201502902. \n[38] H. Chen, P. Jia, H. Kang, H. Zhang, Y. Liu, P. Yang, Y. Yan, G. Zuo, L. Guo, M. Jiang, Upregulating HIF-1α by hydrogel nanofibrous scaffolds for rapidly recruiting angiogenesis relative cells in diabetic wound, Adv. Healthc. Mater. 5 (8) (2016) 907–918, https://doi.org/10.1002/adhm.201501018. \n[39] H. Chen, L. Guo, J. Wicks, C. Ling, X. Zhao, Y. Yan, J. Qi, W. Cui, L. Deng, Quickly promoting angiogenesis by using a dfo-loaded photo-crosslinked gelatin hydrogel for diabetic skin regeneration, J. Mater. Chem. B 4 (21) (2016) 3770–3781, https://doi.org/10.1039/C6TB00065G. \n[40] X. Zhao, P. Li, B.L. Guo, P.X. Ma, Antibacterial and conductive injectable hydrogels based on quaternized chitosan-graft-polyaniline/oxidized dextran for tissue engineering, Acta Biomater. 26 (2015) 236–248, https://doi.org/10.1016/j. actbio.2015.08.006. \n[41] F. Xu, X. Li, X. Huang, J. Pan, Y. Wang, S. Zhou, Development of a ph-responsive polymersome inducing endoplasmic reticulum stress and autophagy blockade, Sci. Adv. 6 (31) (2020), https://doi.org/10.1126/sciadv.abb8725 eabb8725. \n[42] L. Yuan, X. Li, L. Ge, X. Jia, J. Lei, C. Mu, D. Li, Emulsion template method for the fabrication of gelatin-based scaffold with a controllable pore structure, ACS Appl. Mater. Interfaces 11 (1) (2019) 269–277, https://doi.org/10.1021/ sami.8b17555. \n[43] S.L. Percival, S. McCarty, J.A. Hunt, E.J. Woods, The effects of ph on wound healing, biofilms, and antimicrobial efficacy, Wound Repair Regen. 22 (2) (2014) 174–186, https://doi.org/10.1111/wrr.12125. \n[44] R. Lobmann, A. Ambrosch, G. Schultz, K. Waldmann, S. Schiweck, H. Lehnert, Expression of matrix-metalloproteinases and their inhibitors in the wounds of diabetic and non-diabetic patients, Diabetologia 45 (7) (2002) 1011–1016, https:// doi.org/10.1007/s00125-002-0868-8. \n[45] Z. Li, S. Guo, F. Yao, Y. Zhang, T. Li, Increased ratio of serum matrix metalloproteinase-9 against TIMP-1 predicts poor wound healing in diabetic foot ulcers, J. Diabet. Complicat. 27 (4) (2013) 380–382, https://doi.org/10.1016/j. jdiacomp.2012.12.007. \n[46] S. Wang, H. Zheng, L. Zhou, F. Cheng, Z. Liu, H. Zhang, L. Wang, Q. Zhang, Nanoenzyme-reinforced injectable hydrogel for healing diabetic wounds infected with multidrug resistant bacteria, Nano Lett. 20 (7) (2020) 5149–5158, https:// doi.org/10.1021/acs.nanolett.0c01371. \n[47] L. Kong, Z. Wu, H. Zhao, H. Cui, J. Shen, J. Chang, H. Li, Y. He, Bioactive injectable hydrogels containing desferrioxamine and bioglass for diabetic wound healing, ACS Appl. Mater. Interfaces 10 (36) (2018) 30103–30114, https://doi.org/ 10.1021/acsami.8b09191. \n[48] M. Kharaziha, A. Baidya, N. Annabi, Rational design of immunomodulatory hydrogels for chronic wound healing, Adv. Mater. 33 (2021), 2100176, https:// doi.org/10.1002/adma.202100176. \n[49] J. Qu, X. Zhao, Y. Liang, T. Zhang, P.X. Ma, B. Guo, Antibacterial adhesive injectable hydrogels with rapid self-healing, extensibility and compressibility as wound dressing for joints skin wound healing, Biomaterials 183 (2018) 185–199, https://doi.org/10.1016/j.biomaterials.2018.08.044. \n[50] L. Liu, M. Zhu, X. Xu, X. Li, Z. Ma, Z. Jiang, A. Pich, H. Wang, P. Song, Dynamic nanoconfinement enabled highly stretchable and supratough polymeric materials with desirable healability and biocompatibility, Adv. Mater. 33 (51) (2021), 2105829, https://doi.org/10.1002/adma.202105829. \n[51] X. Zhao, B. Guo, H. Wu, Y. Liang, P.X. Ma, Injectable antibacterial conductive nanocomposite cryogels with rapid shape recovery for noncompressible hemorrhage and wound healing, Nat. Commun. 9 (2018) 2784, https://doi.org/ 10.1038/s41467-018-04998-9. \n[52] S.H. Hong, S. Kim, J.P. Park, M. Shin, K. Kim, J.H. Ryu, H. Lee, Dynamic bonds between boronic acid and alginate: hydrogels with stretchable, self-healing, stimuli-responsive, remoldable, and adhesive properties, Biomacromolecules 19 (6) (2018) 2053–2061, https://doi.org/10.1021/acs.biomac.8b00144. \n[53] C.C. Deng, W.L.A. Brooks, K.A. Abboud, B.S. Sumerlin, Boronic acid-based hydrogels undergo self-healing at neutral and acidic ph, ACS Macro Lett. 4 (2) (2015) 220–224, https://doi.org/10.1021/acsmacrolett.5b00018. \n[54] T. Wang, Y. Li, E.J. Cornel, C. Li, J. Du, Combined antioxidant-antibiotic treatment for effectively healing infected diabetic wounds based on polymer vesicles, ACS Nano 15 (5) (2021) 9027–9038, https://doi.org/10.1021/acsnano.1c02102. \n[55] B. Marco-Dufort, M.W. Tibbitt, Design of moldable hydrogels for biomedical applications using dynamic covalent boronic esters, Mater. Today Chem. 12 (2019) 16–33, https://doi.org/10.1016/j.mtchem.2018.12.001. \n[56] B. Wang, K. Yoshida, K. Sato, J.-i. Anzai, Phenylboronic acid-functionalized layerby-layer assemblies for biomedical applications, Polymers 9 (6) (2017) 202, https://doi.org/10.3390/polym9060202. \n[57] Y.E. Kim, J. Kim, ROS-scavenging therapeutic hydrogels for modulation of the inflammatory response, ACS Appl. Mater. Interfaces 14 (20) (2022) 23002–23021, https://doi.org/10.1021/acsami.1c18261. \n[58] J. Sonamuthu, Y. Cai, H. Liu, M.S.M. Kasim, V.R. Vasanthakumar, B. Pandi, H. Wang, J. Yao, MMP-9 responsive dipeptide-tempted natural protein hydrogelbased wound dressings for accelerated healing action of infected diabetic wound, Int. J. Biol. Macromol. 153 (2020) 1058–1069, https://doi.org/10.1016/j. ijbiomac.2019.10.236. \n[59] S. Talebian, M. Mehrali, N. Taebnia, C.P. Pennisi, F.B. Kadumudi, J. Foroughi, M. Hasany, M. Nikkhah, M. Akbari, G. Orive, A. Dolatshahi-Pirouz, Self-healing \n\n# Z. Shao et al. \n\nhydrogels: the next paradigm shift in tissue engineering? Adv. Sci. 6 (16) (2019), 1801664 https://doi.org/10.1002/advs.201801664. [60] G. Han, R. Ceilley, Chronic wound healing: a review of current management and treatments, Adv. Ther. 34 (3) (2017) 599–610, https://doi.org/10.1007/s12325- 017-0478-y. \n\n[61] X. Zhang, G. Chen, Y. Liu, L. Sun, L. Sun, Y. Zhao, Black phosphorus-loaded separable microneedles as responsive oxygen delivery carriers for wound healing, ACS Nano 14 (5) (2020) 5901–5908, https://doi.org/10.1021/acsnano.0c01059. " + }, + { + "id": "10.1038_s41467-023-36329-y", + "DOI": "10.1038/s41467-023-36329-y", + "DOI Link": "http://dx.doi.org/10.1038/s41467-023-36329-y", + "Relative Dir Path": "mds/10.1038_s41467-023-36329-y", + "Article Title": "Learning local equivariant representations for large-scale atomistic dynamics", + "Authors": "Musaelian, A; Batzner, S; Johansson, A; Sun, LX; Owen, CJ; Kornbluth, M; Kozinsky, B", + "Source Title": "NATURE COMMUNICATIONS", + "Abstract": "A simultaneously accurate and computationally efficient parametrization of the potential energy surface of molecules and materials is a long-standing goal in the natural sciences. While atom-centered message passing neural networks (MPNNs) have shown remarkable accuracy, their information propagation has limited the accessible length-scales. Local methods, conversely, scale to large simulations but have suffered from inferior accuracy. This work introduces Allegro, a strictly local equivariant deep neural network interatomic potential architecture that simultaneously exhibits excellent accuracy and scalability. Allegro represents a many-body potential using iterated tensor products of learned equivariant representations without atom-centered message passing. Allegro obtains improvements over state-of-the-art methods on QM9 and revMD17. A single tensor product layer outperforms existing deep MPNNs and transformers on QM9. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular simulations using Allegro recover structural and kinetic properties of an amorphous electrolyte in excellent agreement with ab-initio simulations. Finally, we demonstrate parallelization with a simulation of 100 million atoms. The paper presents a method that allows scaling machine learning interatomic potentials to extremely large systems, while at the same time retaining the remarkable accuracy and learning efficiency of deep equivariant models. This is obtained with an E(3)- equivariant neural network architecture that combines the high accuracy of equivariant neural networks with the scalability of local methods.", + "Times Cited, WoS Core": 253, + "Times Cited, All Databases": 265, + "Publication Year": 2023, + "Research Areas": "Science & Technology - Other Topics", + "UT (Unique WOS ID)": "WOS:000955633400011", + "Markdown": "# Learning local equivariant representations for large-scale atomistic dynamics \n\nReceived: 16 June 2022 \n\nAccepted: 23 January 2023 \n\nPublished online: 03 February 2023 \n\n# Check for updates \n\nAlbert Musaelian1,3, Simon Batzner 1,3 , Anders Johansson 1, Lixin Sun1, Cameron J. Owen 1, Mordechai Kornbluth $\\textcircled{\\bullet}^{2}$ & Boris Kozinsky 1,2 \n\nA simultaneously accurate and computationally efficient parametrization of the potential energy surface of molecules and materials is a long-standing goal in the natural sciences. While atom-centered message passing neural networks (MPNNs) have shown remarkable accuracy, their information propagation has limited the accessible length-scales. Local methods, conversely, scale to large simulations but have suffered from inferior accuracy. This work introduces Allegro, a strictly local equivariant deep neural network interatomic potential architecture that simultaneously exhibits excellent accuracy and scalability. Allegro represents a many-body potential using iterated tensor products of learned equivariant representations without atom-centered message passing. Allegro obtains improvements over state-of-the-art methods on QM9 and revMD17. A single tensor product layer outperforms existing deep MPNNs and transformers on QM9. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular simulations using Allegro recover structural and kinetic properties of an amorphous electrolyte in excellent agreement with ab-initio simulations. Finally, we demonstrate parallelization with a simulation of 100 million atoms. \n\nMolecular dynamics (MD) and Monte-Carlo (MC) simulation methods are a core pillar of computational chemistry, materials science, and biology. Common to a diverse set of applications ranging from energy materials1 to protein folding2 is the requirement that predictions of the potential energy and atomic forces must be both accurate and computationally efficient to faithfully describe the evolution of complex systems over long timescales. While first-principles methods such as density functional theory (DFT), which explicitly treat the electrons of the system, provide an accurate and transferable description of the system, they exhibit poor scaling with system size and thus limit practical applications to small systems and short simulation times. Classical force fields based on simple functions of atomic coordinates are able to scale to large systems and long timescales but are inherently limited in their fidelity and can yield unfaithful dynamics. Descriptions of the potential energy surface (PES) using machine learning (ML) have emerged as a promising approach to move past this trade-off3–24. Machine learning interatomic potentials (MLIPs) aim to approximate a set of high-fidelity energy and force labels with improved computational efficiency that scales linearly in the number of atoms. A variety of approaches have been proposed, from shallow neural networks and kernel-based approaches3–6 to more recent methods based on deep learning14,15,20,25,26. In particular, a class of MLIPs based on atom-centered message-passing neural networks (MPNNs) has shown remarkable accuracy9,11,14,15,26,27. In interatomic potentials based on MPNNs, an atomistic graph is induced by connecting each atom (node) to all neighboring atoms inside a finite cutoff sphere surrounding it. Information is then iteratively propagated along this graph, allowing MPNNs to learn many-body correlations and access non-local information outside of the local cutoff. This iterated propagation, however, leads to large receptive fields with many effective neighbors for each atom, which impedes parallel computation and limits the length scales accessible to atom-centered message-passing MLIPs. MLIPs using strictly local descriptors such as Behler-Parrinello neural networks5, $\\mathbf{GAP^{6}}$ , SNAP7, DeepMD20, Moment Tensor Potentials8, or $\\mathsf{A C E}^{12}$ do not suffer from this obstacle due to their strict locality. As a result, they can be easily parallelized across devices and have been successfully scaled to extremely large system sizes28–31. Approaches based on local descriptors, however, have so far fallen behind in accuracy compared to state-of-the-art equivariant, atom-centered message passing interatomic potentials15. \n\n# Message-passing interatomic potentials \n\nMessage-passing neural networks (MPNNs) which learn atomistic representations have recently gained popularity in atomistic machine learning due to advantages in accuracy compared to hand-crafted descriptors. Atom-centered message-passing interatomic potentials operate on an atomistic graph constructed by representing atoms as nodes and defining edges between atoms that are within a fixed cutoff distance of one another. Each node is then represented by a hidden state $\\mathbf{h}_{i}^{t}\\in\\mathbb{R}^{c}$ representing the state of atom $i$ at layer $t,$ and edges are represented by edge features $\\mathbf{e}_{i j},$ for which the interatomic distance $r_{i j}$ is often used. The message-passing formalism can then be concisely described $\\mathbf{a}\\mathbf{s}^{32}$ : \n\n$$\n\\mathbf{m}_{i}^{t+1}{=}\\sum_{j\\in\\mathcal{N}(i)}M_{t}\\Big(\\mathbf{h}_{i}^{t},\\mathbf{h}_{j}^{t},\\mathbf{e}_{i j}\\Big)\n$$ \n\n$$\n\\ensuremath{\\mathbf{\\mathsf{h}}}_{i}^{t+1}{=}{\\cal U}_{t}\\left(\\ensuremath{\\mathbf{\\mathsf{h}}}_{i}^{t},\\ensuremath{\\mathbf{\\mathsf{m}}}_{i}^{t+1}\\right)\n$$ \n\nwhere $M_{t}$ and $U_{t}$ are an arbitrary message function and node update function, respectively. From this propagation mechanism, it is immediately apparent that as messages are communicated over a sequence of $t$ steps, the local receptive field of an atom $i,$ i.e., the effective set of neighbors that contribute to the final state of atom $i$ grows approximately cubically with the effective cutoff radius $r_{c,e}$ . In particular, given a MPNN with $N_{\\mathrm{layer}}$ message-passing steps and local cutoff radius of ${\\dot{\\boldsymbol{r}}}_{c,l},$ the effective cutoff is $r_{c,e}{=}N_{\\mathrm{layer}}r_{c,l}.$ Information from all atoms inside this receptive field feeds into a central atom’s state $\\mathbf{h}_{i}$ at the final layer of the network. Due to the cubic growth of the number of atoms inside the receptive field cutoff $r_{c,e},$ parallel computation can quickly become unmanageable, especially for extended periodic systems. As an illustrative example, we may take a structure of 64 molecules of liquid water at pressure $P{=}1$ bar and temperature $T{=}300\\mathsf{K}$ For a typical setting of $N_{t}{=}6$ message-passing layers with a local cutoff of $r_{c,l}=6\\mathring{\\mathbf{A}}$ this would result in an effective cutoff of $r_{c,e}=36\\mathring{\\mathbf{A}}$ . While each atom only has approximately 96 atoms in its local $6\\mathring{\\mathbf{A}}$ environment (including the central atom), it has 20,834 atoms inside the extended $36\\mathring{\\mathbf{A}}$ environment. Due to the atom-centered message-passing mechanism, information from each of these atoms flows into the current central atom. In a parallel scheme, each worker must have access to the high-dimensional feature vectors $\\mathbf{h}_{i}$ of all 20,834 nodes, while the strictly local scheme only needs to have access to approximately $6^{3}=216$ times fewer atoms’ states. From this simple example, it becomes obvious that massive improvements in scalability can be obtained from strict locality in machine learning interatomic potentials. It should be noted that conventional, atom-centered message passing allows for the possibility, in principle, to capture long-range interactions (up to $r_{c,e})$ and can induce many-body correlations. The relative importance of these effects in describing molecules and materials is an open question, and one of the aims of this work is to explore whether many-body interactions can be efficiently captured without increasing the effective cutoff. \n\n# Equivariant neural networks \n\nThe physics of atomic systems is unchanged under the action of a number of geometric symmetries—rotation, inversion, and translation —which together comprise the Euclidean group $E(3)$ (rotation alone is $S O(3)$ , and rotation and inversion together comprise $O(3){\\mathrm{.}}$ ). Scalar quantities such as the potential energy are invariant to these symmetry group operations, while vector quantities such as the atomic forces are equivariant to them and transform correspondingly when the atomic geometry is transformed. More formally, a function between vector spaces $f{:}X{\\to}Y$ is equivariant to a group $G$ if \n\n$$\nf(D_{X}[g]x)=D_{Y}[g]f(x)\\quad\\forall g\\in G,\\forall x\\in X\n$$ \n\nwhere $D_{\\lambda}[g]\\in G L(\\lambda)$ is the representation of the group element $g$ in the vector space $\\chi.$ The function $f$ is invariant if $D_{\\mathrm{{\\smash~\\left[g\\right]~}}}$ is the identity operator on $r\\mathrm{:}$ in this case, the output is unchanged by the action of symmetry operations on the input $x$ \n\nMost existing MLIPs guarantee the invariance of their predicted energies by acting only on invariant inputs. In invariant, atom-centered message-passing interatomic potentials in particular, each atom’s hidden latent space is a feature vector consisting solely of invariant scalars25. More recently, however, a class of models known as equivariant neural networks33–36 have been developed which can act directly on non-invariant geometric inputs, such as displacement vectors, in a symmetry-respecting way. This is achieved by using only $E(3)$ -equivariant operations, yielding a model whose internal features are equivariant with respect to the 3D Euclidean group. Building on these concepts, equivariant architectures have been explored for developing interatomic potential models. Notably, the NequIP model15, followed by several other equivariant implementations26,27,37–39, demonstrated unprecedentedly low error on a large range of molecular and materials systems, accurately describes structural and kinetic properties of complex materials, and exhibits remarkable sample efficiency. In both the present work and in NequIP, the representation $D_{\\mathrm{{\\scriptscriptstyle{X}}}}[g]$ of an operation $g\\in O(3)$ on an internal feature space $\\chi$ takes the form of a direct sum of irreducible representations (commonly referred to as irreps) of $O(3)$ . This means that the feature vectors themselves are comprised of various geometric tensors corresponding to different irreps that describe how they transform under symmetry operations. The irreps of $O(3)$ , and thus the features, are indexed by a rotation order $\\ell\\geq0$ and a parity $p\\in(-1,1)$ . A tensor that transforms according to the irrep $\\ell,p$ is said to “inhabit” that irrep. We note that in many cases one may also omit the parity index to instead construct features that are only $S E(3)$ -equivariant (translation and rotation), which simplifies the construction of the network and reduces the memory requirements. \n\nA key operation in such equivariant networks is the tensor product of representations, an equivariant operation that combines two tensors $\\pmb{x}$ and y with irreps $\\ell_{1},p_{1}$ and $\\ell_{2},p_{2}$ to give an output inhabiting an irrep $\\ell_{\\mathrm{out}},p_{\\mathrm{out}}$ satisfying $|\\ell_{1}-\\ell_{2}|\\leq\\ell_{\\mathrm{out}}\\leq|\\ell_{1}+\\ell_{2}|$ and $p_{\\mathrm{out}}=p_{1}p_{2}$ : \n\n$$\n(\\mathbf{x}\\otimes\\mathbf{y})_{\\ell_{\\mathrm{out}},m_{\\mathrm{out}}}=\\sum_{m_{1},m_{2}}{\\binom{\\ell_{1}}{m_{1}}}\\ {\\begin{array}{l l l}{\\ell_{2}}&{\\ell_{\\mathrm{out}}}\\\\ {m_{2}}&{m_{\\mathrm{out}}}\\end{array}}\\right)\\mathbf{x}_{\\ell_{1},m_{1}}\\mathbf{y}_{\\ell_{2},m_{2}}\n$$ \n\nwhere $\\left(\\begin{array}{c c c}{\\ell_{1}}&{\\ell_{2}}&{\\ell_{\\mathrm{out}}}\\\\ {m_{1}}&{m_{2}}&{m_{\\mathrm{out}}}\\end{array}\\right)$ is the Wigner $3j$ symbol. Two key properties of the tensor product are that it is bilinear (linear in both $\\pmb{x}$ and $\\textbf{y}$ ) and that it combines tensors inhabiting different irreps in a symmetrically valid way. Many simple operations are encompassed by the tensor product, such as for example: \n\nscalar-scalar multiplication: $(\\ell_{1}=0,p_{1}=1),(\\ell_{2}=0,p_{2}=1)\\to(\\ell_{\\mathrm{out}}=$ $0,p_{\\mathrm{out}}=1)$ \nvector dot product: $(\\ell_{1}=1,p_{1}=-1),(\\ell_{2}=1,p_{2}=-1)\\to(\\ell_{\\mathrm{out}}=0,$ $\\boldsymbol{p_{\\mathrm{out}}}=1)$ \nvector cross product, resulting in a pseudovector: $(\\ell_{1}=1,p_{1}=-1)$ , $(\\ell_{2}=1,p_{2}=-1)\\to(\\ell_{\\mathrm{out}}=1,p_{\\mathrm{out}}=1)$ \n\nThe message function $M_{t}(\\mathbf h_{i}^{t},\\mathbf h_{j}^{t},\\mathbf e_{i j})$ of the NequIP model, for example, uses this tensor product to define a message from atom j to $i$ as a tensor product between equivariant features of the edge $\\ddot{y}$ and the equivariant features of the neighboring node $j$ . \n\n![](images/e86fa96b5b406c713219f2db7f94f96108ea033e33ece625061d0b50ccfc2500.jpg) \nFig. 1 | The Allegro network. a shows the Allegro model architecture and $\\boldsymbol{\\mathbf{b}}$ details a tensor product layer. Blue and red arrows represent scalar and tensor information, respectively, $\\otimes$ denotes the tensor product, and $\\circledast$ is concatenation. \n\n# Atomic cluster expansion \n\nFinally, parallel to atom-centered message-passing interatomic potentials, the Atomic Cluster Expansion (ACE) has been developed as a unifying framework for various descriptor-based MLIPs12. ACE can also be expressed in terms of the same tensor product operation introduced above, with further details provided in “Methods”. \n\nIn this work, we present Allegro, an equivariant deep-learning approach that retains the high accuracy of the recently proposed class of equivariant MPNNs15,26,27,37,39,40 while combining it with strict locality and thus the ability to scale to large systems. We demonstrate that Allegro not only obtains state-of-the-art accuracy on a series of different benchmarks but can also be parallelized across devices to access simulations with hundreds of millions of atoms. We further find that Allegro displays a high level of transferability to out-ofdistribution data, significantly outperforming other local MLIPs, in particular including body-ordered approaches. Finally, we show that Allegro can faithfully recover structural and kinetic properties from molecular dynamics simulations of $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ , a complex phosphate electrolyte. \n\nThe outline of the article is as follows: we first surveyed relevant related work on message-passing interatomic potentials, equivariant neural networks, and the atomic cluster expansion. We then outline the core ideas and design of the Allegro approach, followed by a series of results on standard benchmarks. Finally, we show the results of molecular dynamics simulations on a challenging material, an analysis of the scaling properties of Allegro, and a theoretical analysis of the framework. \n\n# Energy decomposition \n\nWe start by decomposing the potential energy of a system into peratom energies $E_{i},$ in line with previous approaches5,6,25: \n\n$$\nE_{\\mathrm{system}}=\\sum_{i}^{N}\\sigma_{Z_{i}}E_{i}+\\mu_{Z_{i}}\n$$ \n\nwhere $\\sigma_{Z_{i}}$ and $\\mu_{Z_{i}}$ are per-species scale and shift parameters, which may be trainable. Unlike most existing MLIPs, we further decompose the per-atom energy into a sum of pairwise energies, indexed by the central atom and one of its local neighbors \n\n$$\nE_{i}=\\sum_{j\\in\\mathcal{N}(i)}\\sigma_{Z_{i},Z_{j}}E_{i j}\n$$ \n\nwhere $j$ ranges over the neighbors of atom $i,$ and again one may optionally apply a per-species-pair scaling factor $\\sigma_{Z_{i},Z_{j}}$ . It is important to note that while these pairwise energies are indexed by the atom $i$ and its neighbor ${j,}$ they may depend on all neighboring atoms $k$ belonging to the local environment $\\mathcal{N}(i)$ . Because $E_{i j}$ and $E_{j i}$ contribute to different site energies $E_{i}$ and $E_{j},$ respectively, we choose that they depend only on the environments of the corresponding central atoms. As a result and by design, $E_{i j}\\not=E_{j i}$ . Finally, the force acting on atom i, ${\\vec{F}}_{i},$ is computed using autodifferentiation according to its definition as the negative gradient of the total energy with respect to the position of atom i: \n\n$$\n\\vec{F}_{i}=-\\nabla_{i}E_{\\mathrm{system}}\n$$ \n\nwhich gives an energy-conserving force field. \n\n# Results \n\nIn the following, we describe the proposed method for learning highdimensional potential energy surfaces using strictly local many-body equivariant representations. \n\n# The Allegro model \n\nThe Allegro architecture, shown in Fig. 1, is an arbitrarily deep equivariant neural network with $N_{\\mathrm{layer}}{\\geq}1$ layers. The architecture learns representations associated with ordered pairs of neighboring atoms using two latent spaces: an invariant latent space, which consists of scalar $(\\ell=0)$ features, and an equivariant latent space, which processes tensors of arbitrary rank $\\ell\\geq0$ . The two latent spaces interact with each other at every layer. The final pair energy $E_{i j}$ is then computed by a multi-layer perceptron (MLP) acting on the final layer’s scalar features. \n\nWe use the following notations: $\\scriptstyle{\\vec{r}}_{i}$ : position of the ith atom in the system $\\vec{r}_{i j}$ : relative displacement vector $\\Vec{r_{j}}-\\Vec{r}_{i}$ from i to j $r_{i j}$ : corresponding interatomic distance $\\hat{r}_{i i\\dot{\\cdot}i}$ unit vector of $\\vec{r}_{i j}$ $\\overrightarrow{Y}_{\\ell,p}^{\\upsilon}$ : projection of $\\hat{\\boldsymbol r}_{i j}$ onto the $\\ell$ -th real spherical harmonic which has parity $p=(-1)^{\\ell}$ . We omit the $\\boldsymbol{m}=-\\ell,\\ldots,0,\\ldots\\ell$ index within the representation from the notation for compactness $Z_{i}\\colon$ chemical species of atom i $\\mathsf{M L P}(\\ldots)$ : multi-layer perceptron—a fully connected scalar neural network, possibly with nonlinearities $\\mathbf{x}^{i j,L}$ : invariant scalar latent features of the ordered pair of atoms $\\ddot{y}$ at layer $\\iota$ $\\mathbf{v}_{n,\\ell,p}^{i j,L}$ : equivariant latent features of the ordered pair of atoms $\\ddot{y}$ at layer L. These transform according to a direct sum of irreps indexed by the rotation order $\\ell\\in0,1,\\ldots,\\ell_{\\mathrm{max}}$ and parity $p\\in-1,1$ and thus consist of both scalars $(\\ell=0)$ and higher-order tensors $(\\ell>0)$ . The hyperparameter $\\ell_{\\mathrm{{max}}}$ controls the maximum rotation order to which features in the network are truncated. In Allegro, $n$ denotes the channel index which runs over $0,\\ldots,n_{\\mathrm{equivariant}}-1.$ We omit the $m$ index within each irreducible representation from the notation for compactness. \n\nTwo-body latent embedding. Before the first tensor product layer, the scalar properties of the pair $\\ddot{y}$ are embedded through a nonlinear MLP to give the initial scalar latent features $\\mathbf{x}^{i j,L=0}$ : \n\n$$\n\\begin{array}{r}{\\pmb{x}^{i j,L=0}=\\pmb{\\mathrm{MLP}}_{\\mathrm{two-body}}\\left(\\pmb{\\mathrm{1Hot}}(Z_{i})\\parallel\\pmb{\\mathrm{1Hot}}(Z_{j})\\parallel B(r_{i j})\\right)\\cdot\\pmb{u}(r_{i j})}\\end{array}\n$$ \n\nwhere $\\parallel$ denotes concatenation, $\\mathrm{1Hot(\\cdot)}$ is a one-hot encoding of the center and neighbor atom species $Z_{i}$ and $Z_{j},$ and \n\n4. an equivariant linear layer that mixes channels in the equivariant latent space. \n\nTensor product: Our goal is to incorporate interactions between the current equivariant state of the center-neighbor pair and other neighbors in the environment, and the most natural operation with which to interact equivariant features is the tensor product. We thus define the updated equivariant features on the pair $\\ddot{y}$ as a weighted sum of the tensor products of the current features with the geometry of the various other neighbor pairs $i k$ in the local environment of $\\dot{t}.$ \n\n$$\n\\mathbf{V}_{n,(\\ell_{1},p_{1},\\ell_{2},p_{2})\\rightarrow(\\ell_{\\mathrm{out}},p_{\\mathrm{out}})}^{i j,L}=\\sum_{k\\in\\mathcal{N}(i)}w_{n,\\ell_{2},p_{2}}^{i k,L}\\left(\\mathbf{V}_{n,\\ell_{1},p_{1}}^{i j,L-1}\\otimes\\overrightarrow{Y}_{\\ell_{2},p_{2}}^{i k}\\right)\n$$ \n\n$$\n=\\sum_{k\\in\\mathcal{N}(i)}\\mathbf{V}_{n,\\ell_{1},p_{1}}^{i j,L-1}\\otimes\\left(w_{n,\\ell_{2},p_{2}}^{i k,L}\\vec{Y}_{\\ell_{2},p_{2}}^{i k}\\right)\n$$ \n\n$$\n=\\mathbf{V}_{n,\\ell_{1},p_{1}}^{i j,L-1}\\otimes\\left(\\sum_{k\\in\\mathcal{N}(i)}w_{n,\\ell_{2},p_{2}}^{i k,L}\\vec{Y}_{\\ell_{2},p_{2}}^{i k}\\right)\n$$ \n\nIn the second and third lines, we exploit the bilinearity of the tensor product in order to express the update in terms of one tensor product, rather than one for each neighbor $k$ which saves significant computational effort. This is a variation on the “density trick”6,41. \n\nWe note that valid tensor product paths are all those satisfying $|\\ell_{1}-\\ell_{2}|\\leq\\ell_{\\mathrm{out}}\\leq|\\ell_{1}+\\ell_{2}|$ and $p_{\\mathrm{out}}=p_{1}p_{2},$ , so it is possible to have $(\\ell_{1},p_{1})\\neq(\\ell_{2},p_{2})\\neq(\\ell_{\\mathrm{out}},p_{\\mathrm{out}})$ . We additionally enforce $\\ell_{\\mathrm{out}}\\leq\\ell_{\\mathrm{max}}$ . Which tensor product paths to include is a hyperparameter choice. In this work we include all allowable paths but other choices, such as restricting $(\\ell_{\\mathrm{out}},p_{\\mathrm{out}})$ to be among the values of $(\\ell_{1},p_{1})$ , are possible. \n\n$$\nB(r_{i j})=(B_{1}(r_{i j})\\parallel\\ldots\\parallel B_{N_{\\mathrm{basis}}}(r_{i j})))\n$$ \n\nis the projection of the interatomic distance $r_{i j}$ onto a radial basis. We use the Bessel basis functions with a polynomial envelope function as proposed in ref. 14. The basis is normalized as described in Supplementary Note 1 and plotted in Supplementary Fig. 1. Finally, the function $u(r_{i j}):\\mathbb{R}\\rightarrow\\mathbb{R}$ by which the output of MLPtwo-body is multiplied is the same smooth cutoff envelope function as used in the radial basis function. \n\nThe initial equivariant features Vinj,‘L, p= 0 are computed as a linear embedding of the spherical harmonic projection of $\\hat{\\boldsymbol r}_{i j}$ : \n\n$$\n\\mathbf{V}_{n,\\ell,p}^{i j,L=0}=w_{n,\\ell,p}^{i j,L=0}\\vec{Y}_{\\ell,p}^{i j}\n$$ \n\nwhere the channel index is $n{=}0,\\ldots,n_{\\mathrm{equivariant}}{-}1,$ , and where the scalar weights $w_{n,\\ell,p}^{i j,L=0}$ for each center-neighbor pair $\\ddot{y}$ are computed from the initial two-body scalar latent features: \n\nEnvironment embedding: The second argument to the tensor product, $\\begin{array}{r}{\\sum_{k\\in\\mathcal{N}(i)}w_{n,\\ell_{2},p_{2}}^{i k,L}\\vec{Y}_{\\ell_{2},p_{2}}^{i k},}\\end{array}$ Y!‘2,p2 , is a weighted sum of the spherical harmonic projections of the various neighbor atoms in the local environment. This can be viewed as a weighted spherical harmonic basis projection of the atomic density, similar to the projection onto a spherical-radial basis used in $\\mathsf{A C E}^{12}$ and $\\mathsf{S O A P}^{41}$ . For this reason, we refer to Pk2N ðiÞwink,,‘L2,p2 Y!i‘k2,p2 a s the “embedded environment” of atom i. \n\nA central difference from the atomic density projections used in descriptor methods, however, is that the weights of the sum are learned. In descriptor approaches such as ACE, the $n$ index runs over a pre-determined set of radial–chemical basis functions, which means that the size of the basis must increase with both the number of species and the desired radial resolution. In Allegro, we instead leverage the previously learned scalar featurization of each center-neighbor pair to further learn \n\n$$\n\\boldsymbol{w}_{n,\\ell_{2},p_{2}}^{i k,L}=\\mathbf{MLP}_{\\mathrm{embed}}^{L}(\\mathbf{x}^{i k,L-1})_{n,\\ell_{2},p_{2}}\n$$ \n\n$$\n\\begin{array}{r}{\\begin{array}{r}{w_{n,\\ell,p}^{i j,L=0}=\\mathsf{M L P}_{\\mathrm{embed}}^{L=0}(\\mathbf{x}^{i j,L=0})_{n,\\ell,p}.}\\end{array}}\\end{array}\n$$ \n\nLayer architecture. Each Allegro tensor product layer consists of four components: \n\n1. an MLP that generates weights to embed the central atom’s environment \n2. an equivariant tensor product using those weights \n3. an MLP to update the scalar latent space with scalar information resulting from the tensor product \n\nwhich yields an embedded environment with a fixed, chosen number of channels nequivariant. It is important to note that $w_{n,\\ell_{2},p_{2}}^{i k,L}$ is learned as a function of the existing scalar latent representation of the centerneighbor pair $i k$ from previous layers. At later layers, this can contain significantly more information about the environment of i than a twobody radial basis. We typically choose $\\mathsf{M L P_{e m b e d}}$ to be a simple onelayer linear projection of the scalar latent space. \n\nLatent MLP: Following the tensor product defined in Eq. (11), the scalar outputs of the tensor product are reintroduced into the scalar \n\nTable 1 | MAE on the revised MD-17 dataset for energies and force components, in units of [meV] and [meV/Å], respectively \n\n\n
MoleculeFCHL1913, 43UNiTE26GAP6ANI- pretrained48,49ANI- random48.49ACE12GemNet- (T/Q)%NequlP (l=3)15Allegro
AspirinEnergy6.22.417.716.625.46.12.32.3
Forces20.97.644.940.675.017.99.58.27.3
AzobenzeneEnergy2.81.18.515.919.03.60.71.2
Forces10.84.224.535.452.110.9_2.92.6
BenzeneEnergy0.30.070.753.33.40.040.040.3
Forces2.60.736.010.017.50.50.50.30.2
EthanolEnergy0.90.623.52.57.71.2-0.40.4
Forces6.23.718.113.445.67.33.62.82.1
MalonaldehydeEnergy1.51.14.84.69.41.70.80.6
Forces10.26.626.424.552.411.16.65.13.6
NaphthaleneEnergy1.20.463.811.316.00.90.20.5
Forces6.52.616.529.252.25.11.91.30.9
ParacetamolEnergy2.91.98.511.518.24.01.41.5
Forces12.27.128.930.463.312.75.94.9
Salicylic acidEnergy1.80.735.69.213.51.80.70.9
Forces9.53.824.729.752.09.35.34.02.9
TolueneEnergy1.60.454.07.712.61.10.30.4
Forces8.82.517.824.352.96.52.21.61.8
UracilEnergy0.60.583.05.18.31.1-0.40.6
Forces4.23.817.621.444.16.63.83.11.8
\n\nResults for GAP, ANI, and ACE as reported in ref. 24. Best results are marked in bold. ANI-pretrained refers to a version of ANI that was pretrained on 8.9 million structures and fine-tuned on the revMD17 dataset, ANI-random refers to a randomly initialized model trained from scratch. \n\nlatent space as follows: \n\n$$\n\\mathbf{x}^{i j,L}=\\mathsf{M L P}_{\\mathrm{latent}}^{L}\\left(\\mathbf{x}^{i j,L-1}\\parallel\\bigoplus_{(\\ell_{1},p_{1},\\ell_{2},p_{2})}\\mathbf{V}_{n,(\\ell_{1},p_{1},\\ell_{2},p_{2})\\to(\\ell_{\\mathrm{out}}=0,p_{\\mathrm{out}}=1)}^{i j,L}\\right)\\cdot\\boldsymbol{u}(r_{i j})\n$$ \n\nwhere $\\parallel$ denotes concatenation and $\\circledast$ denotes concatenation over all tensor product paths whose outputs are scalars $(\\ell_{\\mathrm{out}}=0,{p_{\\mathrm{out}}}=1)$ , each of which contributes nequivariant scalars. The function $u(r_{i j}):\\mathbb{R}\\rightarrow\\mathbb{R}$ is again the smooth cutoff envelope from Eq. (7). The purpose of the latent MLP is to compress and integrate information from the tensor product, whatever its dimension, into the fixed dimension invariant latent space. This operation completes the coupling of the scalar and equivariant latent spaces since the scalars taken from the tensor product contain information about non-scalars previously only available to the equivariant latent space. \n\nMixing equivariant features: Finally, the outputs of various tensor \nproduct paths with the same irrep $(\\ell_{\\mathrm{out}},p_{\\mathrm{out}})$ are linearly mixed to \ncgheannernaetles ionudtepxuetdebqyu arsiatnhtefienaptutrefse $\\mathbf{v}_{n,\\ell,p}^{i j,L}$ swhiatdh the same number of $n$ \n\n$$\n\\mathbf{V}_{n,\\ell,p}^{i j,L}=\\sum_{n^{\\prime}}\\begin{array}{l l}{\\displaystyle{w_{n,n^{\\prime},(\\ell_{1},p_{1},\\ell_{2},p_{2})\\to(\\ell,p)}^{L}\\mathbf{V}_{n^{\\prime},(\\ell_{1},p_{1},\\ell_{2},p_{2})\\to(\\ell,p)}^{i j,L}}}\\\\ {\\displaystyle{(\\ell_{1},p_{1},\\ell_{2},p_{2})}}\\end{array}}\\\\ {\\end{array}\n$$ \n\nThe weights $w_{n,n^{\\prime},(\\ell_{1},p_{1},\\ell_{2},p_{2})\\to(\\ell,p)}^{L}$ are learned. This operation compresses the equivariant information from various paths with the same output irrep $(\\ell,p)$ into a single output space regardless of the number of paths. \n\nWe finally note that an $S E(3)$ -equivariant version of Allegro, which is sometimes useful for computational efficiency, can be constructed identically to the $E(3)$ -equivariant model described here by simply omitting all parity subscripts $p$ . \n\nResidual update. After each layer, Allegro uses a residual update42 in the scalar latent space that updates the previous scalar features from layer $_{L-1}$ by adding the new features to them (see Supplementary Note 2). The residual update allows the network to easily propagate scalar information from earlier layers forward. \n\nOutput block. To predict the pair energy $E_{i j},$ we apply a fully connected neural network with output dimension 1 to the latent features output by the final layer: \n\n$$\nE_{i j}=\\mathsf{M L P}_{\\mathrm{output}}(\\mathbf{x}^{i j,L=N_{\\mathrm{layer}}})\n$$ \n\nFinally, we note that we found normalization, both of the targets and inside the network, to be of high importance. Details are outlined in “Methods”. \n\n# Dynamics of small molecules \n\nWe benchmark Allegro’s ability to accurately learn energies and forces of small molecules on the revised MD-17 dataset43, a recomputed version of the original MD-17 dataset10,44,45 that contains ten small, organic molecules at DFT accuracy. As shown in Table 1, Allegro obtains state-of-the-art accuracy in the mean absolute error (MAE) in force components, while NequIP performs better for the energies of some molecules. We note that while an older version of the MD-17 dataset which has widely been used to benchmark MLIPs exists10,44,45, it has been observed to contain noisy labels43 and is thus only of limited use for comparing the accuracy of MLIPs. \n\n# Transferability to higher temperatures \n\nFor an interatomic potential to be useful in practice, it is crucial that it be transferable to new configurations that might be visited over the course of a long molecular dynamics simulation. To assess Allegro’s generalization capabilities, we test the transferability to conformations sampled from higher-temperature MD simulations. We use the temperature transferability benchmark introduced in ref. 24: here, a series of data were computed using DFT for the flexible drug-like molecule 3- (benzyloxy)pyridin-2-amine (3BPA) at temperatures 300, 600, and 1200 K. Various state-of-the-art methods were trained on 500 structures from the $T{=}300\\kappa$ dataset and then evaluated on data sampled at all three temperatures. Table 2 shows a comparison of Allegro against existing approaches reported in ref. 24: linear $\\mathsf{A C E}^{12}$ , sGDML10, $\\mathsf{G A P^{6}}$ , a classical force field based on the GAFF functional form46,47 as well as two ANI parametrizations48,49 (ANI-pretrained refers to a version of ANI that was pretrained on 8.9 million structures and fine-tuned on this dataset, while ANI-2x refers to the original parametrization trained on 8.9 million structures, but not fine-tuned on the 3BPA dataset). The equivariant neural networks Allegro and NequIP are observed to generalize significantly better than all other approaches. \n\nTable 2 | Energy and Force RMSE for the 3BPA temperature transferability dataset, reported in units of [meV] and [meV/Å] \n\n\n
ACE12SGDML10GAP6FF46,47ANI-pretrained48.49ANI-2x48, 49NequlP15Allegro
Fit to 300 K
300 K, E7.19.122.860.823.538.63.28 (0.12)3.84 (0.10)
300 K, F27.146.287.3302.842.884.410.77 (0.28)12.98 (0.20)
600 K, E24.0484.861.4136.837.854.511.16 (0.17)12.07 (0.55)
600 K, F64.3439.2151.9407.971.7102.826.37 (0.11)29.11 (0.27)
1200 K, E85.3774.5166.8325.576.888.838.52 (2.00)42.57 (1.79)
1200 K, F187.0711.1305.5670.9129.6139.676.18 (1.36)82.96 (2.17)
\n\nAll models were trained on ${\\cal T}=300$ K. Results for all models except for NequIP and Allegro from ref. 24. Best results are marked in bold. For NequIP and Allegro, we report the mean over three different seeds as well as the sample standard deviation in parentheses. \n\n
Table 3 | Comparison of models onthe QM9 dataset, mea- sured by the MAE in units of [meV]
Model
U。 Schnet25 14U H G
DimeNet++7719 14 14
6.36.3 6.5 7.6
Cormorant23 2221 21 20
LieConv78 1919 24 22
L1Net79 13.513.8 14.4 14.0
SphereNet80 6.37.3 6.4 8.0
EGNN40 1112 12 12
ET38 6.26.3 6.5 7.6
NoisyNodes81 7.37.6 7.4 8.3
PaiNN27 5.95.7 6.0 7.4
Allegro, 1 layer 5.7 (0.3)5.3 5.3 6.6
Allegro, 3 layers 4.7 (0.2)4.4 4.4 5.7
\n\nAllegro outperforms all existing atom-centered message-passing and transformer-based models, in particular even with a single layer. Best methods are shown in bold. \n\n# Quantum-chemical properties of small molecules \n\nNext, we assess Allegro’s ability to accurately model properties of small molecules across chemical space using the popular QM9 dataset50. The QM9 dataset contains molecular properties computed with DFT of approximately 134k minimum-energy structures with chemical elements (C, H, O, N, F) that contain up to 9 heavy atoms (C, O, N, F). We benchmark Allegro on four energy-related targets, in particular: (a) $U_{0},$ - the internal energy of the system at $T\\mathrm{=}0\\mathsf{K}$ , (b) $U,$ , the internal energy at $T=298.15\\mathsf{K},$ (c) $H,$ , the enthalpy at $T=298.15\\mathsf{K},$ and (d) $G,$ the free energy at $\\scriptstyle{T=298.15K}$ . Unlike other experiments in this work, which probed conformational degrees of freedom, we here assess the ability of Allegro to describe properties across compositional degrees of freedom. Table 3 shows a comparison with a series of state-of-the-art methods that also learn the properties described above as a direct mapping from atomic coordinates and species. We find that Allegro outperforms all existing methods. Surprisingly, even an Allegro model with a single tensor product layer obtains higher accuracy than all existing methods based on atom-centered message-passing neural networks and transformers. \n\n# Li-ion diffusion in a phosphate electrolyte \n\nIn order to examine Allegro’s ability to describe kinetic properties with MD simulations, we use it to study amorphous structure formation and Li-ion migration in the $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ solid electrolyte. This class of solid-state electrolytes is characterized by the intricate dependence of conductivity on the degree of crystallinity51–54. \n\nIn particular, the $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ dataset used in this work consists of two parts: a 50 ps ab-initio molecular dynamics (AIMD) simulation in the molten liquid state at $T{=}3000\\upkappa$ , followed by a 50 ps AIMD simulation in the quenched state at $T{=}600\\kappa$ . We train a potential on structures from the liquid and quenched trajectories. The model used here is computationally efficient due to a relatively small number of parameters (9058 weights) and tensor products. In particular, we note that the model used to measure the faithfulness of the kinetics and to measure Allegro’s ability to predict thermodynamic observables is identical to the one used in scaling experiments detailed below. This is crucial for fair assessment of a method that simultaneously scales well and can accurately predict material properties. When evaluated on the test set for the quenched amorphous state, which the simulation is performed on, a MAE in the energies of 1.7 meV/atom was obtained, as well as a MAE in the force components of $73.4\\mathrm{meV}/\\mathring{\\mathbf{A}}$ . We then run a series of ten MD simulations starting from the initial structure of the quenched AIMD simulation, all of length 50 ps at $T{=}600\\kappa$ in the quenched state, in order to examine how well Allegro recovers the structure and kinetics compared to AIMD. To assess the quality of the structure after the phase change, we compare the all-atom radial distribution functions (RDF) and the angular distribution functions (ADF) of the tetrahedral angle $\\mathsf{P}{-}\\mathsf{O}{-}\\mathsf{O}$ (P central atom). We show in Fig. 2 that Allegro can accurately recover both distribution functions. For the aspect of ion transport kinetics, we test how well Allegro can model the Li mean-square-displacement (MSD) in the quenched state. We again find excellent agreement with AIMD, as shown in Fig. 3. The structure of $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ can be seen Fig. 4. \n\n# Scaling \n\nMany interesting phenomena in materials science, chemistry, and biology require large numbers of atoms, long timescales, a diversity of chemical elements, or often all three. Scaling to large numbers of atoms requires parallelization across multiple workers, which is difficult in atom-centered MPNNs because the iterative propagation of atomic state information along the atomistic graph increases the size of the receptive field as a function of the number of layers. This is further complicated by the fact that access to energy-conservative force fields requires computing the negative gradient of the predicted energy, which in standard backpropagation algorithms also requires propagating gradient information along the atom graph. Allegro is designed to avoid this issue by strict locality. A given Allegro model scales as: \n\n![](images/e86524ac37434d0dc159e76a89d1d991ed5e4f6b71cff23429cb7fbeac59606b.jpg) \nFig. 2 | Structural properties of $\\bf{L i_{3}P O_{4}}$ . Left: radial distribution function, right: angular distribution function of tetrahedral bond angle. All defined as probability density functions. Results from Allegro are shown in red, and those from AIMD are shown in black. \n\n![](images/5df8bb71aaaec9664463fbd526b1c1607846a7d34ec322acf3bb8f80aec26b62.jpg) \nFig. 3 | Li dynamics in $\\mathbf{Li_{3}P O_{4}}$ . Comparison of the Li MSD of AIMD vs. Allegro. Results are averaged over 10 runs of Allegro, shading indicates $+/-$ one standard deviation. Results from Allegro are shown in red, and those from AIMD are shown in blue. \n\n![](images/02b4cf53d2eec8077024d2559c37689896e410a8a4838c47dbc82857d746bcab.jpg) \nFig. 4 | Structure of $\\mathbf{Li_{3}P O_{4}}$ . The quenched $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ structure at $T{=}600\\kappa$ \n\n$\\mathcal{O}(N)$ in the number of atoms in the system $N_{\\astrosun}$ , in contrast to the $\\mathcal{O}(N^{2})$ scaling of some global descriptor methods such as $\\mathsf{s G D M L}^{10}$ ; $\\mathcal{O}(M)$ in the number of neighbors per atom M, in contrast to the quadratic $\\mathcal{O}(M^{2})$ scaling of some deep-learning approaches such as DimeNet14 or Equivariant Transformers38,55; \n\n$\\mathcal{O}(1)$ in the number of species $S$ , unlike local descriptors such as SOAP ( S2 ) or ACE ( Sbodyorder\u00041 )12. \n\nWe note, however, that the per-pair featurization of Allegro has larger memory requirements than if one were to choose the same number of features in a per-atom featurization. In practice, we find this to not be a problem and see that Allegro can be scaled to massive systems by parallelizing over modest computational resources. \n\nIn particular, in addition to scaling as $\\mathcal{O}(N)$ in the number of atoms, Allegro is strictly local within the chosen cutoff and thus easy to parallelize in large-scale calculations. Recall that Eqs. (5) and (6) define the total energy of a system in Allegro as a sum over scaled pairwise energies $E_{i j}.$ Thus by linearity, the force on atom $a$ \n\n$$\n\\vec{F}_{a}=-\\nabla_{a}E_{\\mathrm{system}}=-\\sum_{i,j}\\nabla_{a}E_{i j},\n$$ \n\nignoring the per-species and per-species-pair scaling coefficients $\\sigma_{Z_{i}}$ and $\\sigma_{Z_{i},Z_{j}}$ for clarity. Because each $E_{i j}$ depends only the atoms in the neighborhood of atom $\\dot{\\iota},-\\nabla_{a}E_{i j}{\\neq}0$ only when $a$ is in the neighborhood of i. Further, for the same reason, pair energy terms $\\boldsymbol{E}_{i j}$ with different central atom indices $i$ are independent. As a result, these groups of terms may be computed independently for each central atom, which facilitates parallelization: the contributions to the force on atom $a$ due to the neighborhoods of various different atoms can be computed in parallel by whichever worker is currently assigned the relevant center’s neighborhood. The final forces are then simple sum reductions over force terms from various parallel workers. \n\nWe first demonstrate the favorable scaling of Allegro in system size by parallelizing the method across GPUs on a single compute node as well as across multiple GPU nodes. We choose two test systems for the scaling experiments: (a) the quenched state structures of the multicomponent electrolyte $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ and (b) the Ag bulk crystal with a vacancy, simulated at $90\\%$ of the melting temperature. The Ag model used 1000 structures for training and validation, resulting in energy MAE of 0.397 meV/atom and force MAE of $16.8\\mathrm{meV/\\mathring{A}}$ on a test set of 159 structures. Scaling numbers are dependent on a variety of hyperparameter choices, such as network size and radial cutoff, that control the trade-off between evaluation speed and accuracy. For $\\mathsf{L i}_{3}\\mathsf{P O}_{4},$ we explicitly choose these identically to those used in the previous set of experiments in order to demonstrate how well an Allegro potential scales that we demonstrated to give highly accurate prediction of structure and kinetics. Table 4 shows the computational efficiency for varied size and computational resources. We are able to simulate the Ag system with over 100 million atoms on 16 GPU nodes. \n\nThe parallel nature of the method and its implementation also allows multiple GPUs to be used to increase the speed of the potential calculation for a fixed-size system. Figure 5 shows such strong scaling \n\nTable 4 | Simulation times obtainable in [ns/day] and time required per atom per step in [microseconds] for varying number of atoms and computational resources \n\n\n
MaterialNumber of atomsNumber of GPUsSpeed in ns/dayMicroseconds/ (atom ·step)
LiPO4192132.39127.785
LiPO4421,82410.5180.552
LiPO4421,82421.0060.284
LiPO4421,82441.9940.143
LiPO4421,82483.8100.075
LiPO4421,824166.9740.041
LiPO4421,8243211.5300.025
Li3PO4421,8246415.5150.018
LiPO450,331,6481280.2740.013
Ag71190.19067.463
Ag1,022,40011.4610.289
Ag1,022,40022.6480.160
Ag1,022,40045.3190.079
Ag1,022,400810.1800.042
Ag1,022,4001618.8120.022
Ag1,022,4003228.1560.015
Ag1,022,4006443.4380.010
Ag1,022,40012849.3950.009
Ag100,640,5121281.5390.003
\n\nTime steps of 2fs and 5fs were used for $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ and Ag, respectively. \n\n![](images/515cda601bd3e8ff6550af790e20a2e0c65e09864ae2ffc45d979f94f5a16301.jpg) \nFig. 5 | Scaling results. Strong scaling results on a $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ structure of 421,824 atoms, performed in LAMMPS. \n\n$$\n\\begin{array}{r l}{\\mathbf{V}_{n_{1}}^{i j,L=1}=}&{\\displaystyle\\sum_{n_{1}^{\\prime}}}\\end{array}w_{n_{1},n_{1}^{\\prime},\\mathrm{path}}^{L=1}\\displaystyle\\sum_{k_{1}\\in\\mathcal{N}(i)}w_{n_{1}^{\\prime}}^{i k_{1},L=1}\\bigg(w_{n_{1}^{\\prime}}^{i j,L=0}\\overrightarrow{\\gamma}^{i j}\\otimes\\overrightarrow{Y}^{i k_{1}}\\bigg)}\\end{array}\n$$ \n\n$$\nk\\in\\mathcal{N}(i)\\\n$$ \n\n$$\n\\begin{array}{r l}{=}&{{}\\displaystyle\\sum_{n_{1}^{\\prime}}}&{{w}_{n_{1},n_{1}^{\\prime},\\mathrm{path}}^{L=1}\\displaystyle\\sum_{k_{1}\\in\\mathcal{N}(i)}{w}_{n_{1}^{\\prime}}^{i k_{1},L=1}{w}_{n_{1}^{\\prime}}^{i j,L=0}\\left(\\overrightarrow{\\gamma}^{i j}\\otimes\\overrightarrow{\\gamma}^{i k_{1}}\\right)}\\end{array}\n$$ \n\nresults on a 421,824 atom $\\mathsf{L i}_{3}\\mathsf{P O}_{4}$ structure. The system size was kept constant while varying the number of A100 GPUs. \n\n# Theoretical analysis \n\nIn this section, we provide a theoretical analysis of the method by highlighting similarities and differences to the Atomic Cluster Expansion (ACE) framework12. Throughout this section we omit representation indices $\\ell$ and $p$ from the notation for conciseness: every weight or feature that carries $\\ell$ and $p$ indices previously implicitly carries them in this section. Starting from the initial equivariant features for the pair of atoms $\\ddot{y}$ at layer $L=0$ \n\nwhich follows from the bilinearity of the tensor product. The sum over “paths” in this equation indicates the sum over all symmetrically valid combinations of implicit irrep indices on the various tensors present in the equation as written out explicitly in Eq. (16). Repeating this substitution, we can express the equivariant features at layer $L=2$ and reveal a general recursive relationship: \n\n$$\n{\\bf V}_{n_{0}}^{i j,L=0}=w_{n_{0}}^{i j,L=0}\\vec{Y}^{i j}\n$$ \n\nthe first Allegro layer computes a sum over tensor products between $\\mathbf{V}_{n_{0}}^{i j,L=0}$ and the spherical harmonics projection of all neighbors \n\n$$\n\\mathbf{V}_{n_{2},\\ell_{2},p_{2}}^{i j,l=2}=\\sum_{n_{2}^{\\prime}}\\mathbf{\\delta}w_{n_{2},n_{2}^{\\prime},\\mathrm{path}}^{L=2}\\sum_{k_{2}\\in\\mathcal{N}(i)}w_{n_{2}^{\\prime}}^{i k_{2},L=2}\\left(\\mathbf{V}_{n_{2}^{\\prime}}^{i j,L=1}\\otimes\\stackrel{\\longrightarrow}{Y}^{i k_{2}}\\right)\n$$ \n\n$$\n=\\sum_{n_{1}^{\\prime},n_{2}^{\\prime}}w_{n_{2},n_{2},\\mathrm{path}}^{L=2}w_{n_{2}^{\\prime},n_{1}^{\\prime},\\mathrm{path}}^{L=1}\\left[\\sum_{k_{2}\\in\\mathcal{N}(i)}\\sum_{k_{1}\\in\\mathcal{N}(i)}w_{n_{2}^{\\prime}}^{i k_{2},L=2}w_{n_{1}^{\\prime}}^{i k_{1},L=1}w_{n_{1}^{\\prime}}^{i j,L=0}\\left(\\stackrel{\\rightarrow}{Y}^{i j}\\otimes\\stackrel{\\rightarrow}{Y}^{i k_{1}}\\otimes\\stackrel{\\rightarrow}{Y}^{i k_{2}}\\right)\\right]\n$$ \n\n$$\n\\mathbf{V}_{n_{\\alpha},\\ell_{L},p_{L}}^{i j,L}=\\sum_{k_{1},\\dots,k_{L}}\\left[\\left(\\prod_{\\alpha\\in1,\\dots,L}w_{n_{\\alpha+1}^{\\prime\\alpha},n_{\\alpha}^{\\prime},\\mathrm{path}}^{L^{-\\alpha}}\\right)\\left(\\prod_{\\alpha\\in0,\\dots,L}w_{n_{\\alpha}^{\\prime\\alpha}}^{i k_{\\alpha},L=\\alpha}\\right)\\left(\\bigotimes_{\\alpha\\in0,\\dots,L}\\vec{Y}^{i k_{\\alpha}}\\right)\\right]\n$$ \n\nwhere $k_{0}=j,n_{L+1}^{\\prime}=n_{L}$ , and $n_{0}^{\\prime}=n_{1}^{\\prime}$ . \n\nThe ACE descriptor $B_{n_{1}...n_{\\nu}}^{(\\nu)}$ of body order $\\nu+1^{12}$ can also be written as an iterated tensor product, specifically of the projection $A_{n}$ of the local atomic density onto a spherical harmonic and radial–chemical basis. The $n$ index here runs over the $N_{\\mathrm{full-basis}}{=}S\\times N_{\\mathrm{basis}}$ combined radial–chemical basis functions. Starting from this definition we may again use the bilinearity of the tensor product to expand the ACE descriptor: \n\n$$\nB_{n_{1}...n_{\\nu}}^{(\\nu)}=\\bigotimes_{\\alpha=1,...,\\nu}A_{n_{i}}\n$$ \n\n$$\n=\\bigotimes_{\\alpha=1,...,\\nu}\\left(\\sum_{k_{\\alpha}\\in\\mathcal{N}(i)}R_{n_{\\alpha}}(r_{i k_{\\alpha}},z_{k_{\\alpha}})\\overrightarrow{Y}^{i k_{\\alpha}}\\right)\n$$ \n\n$$\n=\\sum_{k_{1},...,k_{\\nu}}\\left[\\left(\\prod_{\\alpha\\in1,...,\\nu}R_{n_{\\alpha}}(r_{i k_{\\alpha}},z_{k_{\\alpha}})\\right)\\left(\\bigotimes_{\\alpha\\in1,...,\\nu}\\vec{Y}^{i k_{\\alpha}}\\right)\\right]\n$$ \n\nComparing Eqs. (23) and (26) it is immediately evident that an Allegro model with $N_{\\mathrm{layer}}$ layers and an ACE expansion of body order $\\nu+1=N_{\\mathrm{layer}}+2$ share the core equivariant iterated tensor products $\\overrightarrow{Y}^{i j}\\otimes\\overrightarrow{Y}^{i k_{1}}\\otimes...\\otimes\\overrightarrow{Y}^{i k_{N_{\\mathrm{layer}}}}$ Y!ikNlayer . The equivariant Allegro features Vinj,L are analogous—but not equivalent—to the full equivariant ACE basis functions BðL + 1Þ n1 :::nL + 1 \n\nThe comparison of these expansions of the two models emphasizes, as discussed earlier in the scaling section, that the ACE basis functions carry a full set of $n_{\\alpha}$ indices (which label radial–chemical twobody basis functions), the number of which increases at each iteration, while the Allegro features do not exhibit this increase as a function of the number of layers. This difference is the root of the contrast between the $\\mathcal{O}(N_{\\mathrm{full-basis}}^{\\nu})$ scaling of ACE in the size of the radial–chemical basis $N_{\\mathrm{full-basis}}$ and the $\\mathcal{O}(1)$ of Allegro. Allegro achieves this more favorable scaling through the learnable channel mixing weights. \n\nA key difference between Allegro and ACE, made clear here, is their differing construction of the scalar pairwise weights. In ACE, the scalar weights carrying $i k_{\\alpha}$ indices are the radial–chemical basis functions $R$ , which are two-body functions of the distance between atoms i and $k_{\\alpha}$ and their chemistry. These correspond in Allegro to the environment embedding weights $w_{i k_{\\alpha},n}^{L},$ , which—critically—are functions of all the lower-order equivarianαt features $\\mathbf{v}_{n}^{i j,L^{\\prime}